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https://r-lib.github.io/zip/ + url_pkgdown: '' + url_cran: https://CRAN.R-project.org/package=zip + version_cran: 2.3.2 + name: zip +zoo: + title: |- + S3 Infrastructure for Regular and Irregular Time Series (Z's + Ordered Observations) + version: 1.8.13 + maintainer: Achim Zeileis + url_git: https://zoo.R-Forge.R-project.org/ + url_other: '' + url_pkgdown: '' + url_cran: https://CRAN.R-project.org/package=zoo + version_cran: 1.8-13 + name: zoo +class: + title: Functions for Classification + version: 7.3.22 + maintainer: Brian Ripley + url_git: '' + url_other: http://www.stats.ox.ac.uk/pub/MASS4/ + url_pkgdown: '' + url_cran: https://CRAN.R-project.org/package=class + version_cran: 7.3-23 + name: class +codetools: + title: Code Analysis Tools for R + version: 0.2.20 + maintainer: Luke Tierney + url_git: https://gitlab.com/luke-tierney/codetools + url_other: '' + url_pkgdown: '' + url_cran: https://CRAN.R-project.org/package=codetools + version_cran: 0.2-20 + name: codetools +lattice: + title: Trellis Graphics for R + version: 0.22.6 + maintainer: Deepayan Sarkar + url_git: https://lattice.r-forge.r-project.org/ + url_other: '' + url_pkgdown: '' + url_cran: https://CRAN.R-project.org/package=lattice + version_cran: 0.22-6 + name: lattice +spatial: + title: Functions for Kriging and Point Pattern Analysis + version: 7.3.17 + maintainer: Brian Ripley + url_git: '' + url_other: http://www.stats.ox.ac.uk/pub/MASS4/ + url_pkgdown: '' + url_cran: https://CRAN.R-project.org/package=spatial + version_cran: 7.3-18 + name: spatial diff --git a/_vendor/github.com/jemus42/hugo-rstats-pkg-meta/data/packages/cran.yml b/_vendor/github.com/jemus42/hugo-rstats-pkg-meta/data/packages/cran.yml new file mode 100644 index 0000000..a72993d --- /dev/null +++ b/_vendor/github.com/jemus42/hugo-rstats-pkg-meta/data/packages/cran.yml @@ -0,0 +1,347782 @@ +A3: + version: 1.0.0 + title: |- + Accurate, Adaptable, and Accessible Error Metrics for Predictive + Models + maintainer: Scott Fortmann-Roe + description: Supplies tools for tabulating and analyzing the results of predictive + models. The methods employed are applicable to virtually any predictive model + and make comparisons between different methodologies straightforward. + date_publication: '2015-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=A3 + url_git: '' +AalenJohansen: + version: '1.0' + title: Conditional Aalen-Johansen Estimation + maintainer: Martin Bladt + description: Provides the conditional Nelson-Aalen and Aalen-Johansen estimators. + The methods are based on Bladt & Furrer (2023), in preparation. + date_publication: '2023-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AalenJohansen + url_git: '' +AATtools: + version: 0.0.3 + title: Reliability and Scoring Routines for the Approach-Avoidance Task + maintainer: Sercan Kahveci + description: |- + Compute approach bias scores using different scoring algorithms, + compute bootstrapped and exact split-half reliability estimates, + and compute confidence intervals for individual participant scores. + date_publication: '2024-08-16' + bug_reports: https://github.com/Spiritspeak/AATtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AATtools + url_git: '' +ABACUS: + version: 1.0.0 + title: |- + Apps Based Activities for Communicating and Understanding + Statistics + maintainer: Mintu Nath + description: A set of Shiny apps for effective communication and understanding in + statistics. The current version includes properties of normal distribution, properties + of sampling distribution, one-sample z and t tests, two samples independent (unpaired) + t test and analysis of variance. + date_publication: '2019-09-20' + bug_reports: '' + url: https://shiny.abdn.ac.uk/Stats/apps/ + url_cran: https://CRAN.R-project.org/package=ABACUS + url_git: '' +abasequence: + version: 0.1.0 + title: Coding 'ABA' Patterns for Sequence Data + maintainer: Andrew Pilny + description: Provides a suite of functions for analyzing sequences of events. Users + can generate and code sequences based on predefined rules, with a special focus + on the identification of sequences coded as 'ABA' (when one element appears, followed + by a different one, and then followed by the first). Additionally, the package + offers the ability to calculate the length of consecutive 'ABA'-coded sequences + sharing common elements. The methods implemented in this package are based on + the work by Ziembowicz, K., Rychwalska, A., & Nowak, A. (2022). . + date_publication: '2023-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abasequence + url_git: '' +abbreviate: + version: '0.1' + title: Readable String Abbreviation + maintainer: Sigbert Klinke + description: |- + Strings are abbreviated to at least "minlength" characters, such that they remain unique + (if they were). The abbreviations should be recognisable. + date_publication: '2021-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abbreviate + url_git: https://github.com/sigbertklinke/abbreviate(developmentversion) +abc: + version: 2.2.2 + title: Tools for Approximate Bayesian Computation (ABC) + maintainer: Blum Michael + description: |- + Implements several ABC algorithms for + performing parameter estimation, model selection, and goodness-of-fit. + Cross-validation tools are also available for measuring the + accuracy of ABC estimates, and to calculate the + misclassification probabilities of different models. + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abc + url_git: '' +abc.data: + version: '1.1' + title: 'Data Only: Tools for Approximate Bayesian Computation (ABC)' + maintainer: Blum Michael + description: Contains data which are used by functions of the 'abc' package. + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abc.data + url_git: '' +ABC.RAP: + version: 0.9.0 + title: Array Based CpG Region Analysis Pipeline + maintainer: Abdulmonem Alsaleh + description: |- + It aims to identify candidate genes that are “differentially + methylated” between cases and controls. It applies Student’s t-test and delta beta analysis to + identify candidate genes containing multiple “CpG sites”. + date_publication: '2016-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ABC.RAP + url_git: '' +ABCanalysis: + version: 1.2.1 + title: Computed ABC Analysis + maintainer: Florian Lerch + description: For a given data set, the package provides a novel method of computing + precise limits to acquire subsets which are easily interpreted. Closely related + to the Lorenz curve, the ABC curve visualizes the data by graphically representing + the cumulative distribution function. Based on an ABC analysis the algorithm calculates, + with the help of the ABC curve, the optimal limits by exploiting the mathematical + properties pertaining to distribution of analyzed items. The data containing positive + values is divided into three disjoint subsets A, B and C, with subset A comprising + very profitable values, i.e. largest data values ("the important few"), subset + B comprising values where the yield equals to the effort required to obtain it, + and the subset C comprising of non-profitable values, i.e., the smallest data + sets ("the trivial many"). Package is based on "Computed ABC Analysis for rational + Selection of most informative Variables in multivariate Data", PLoS One. Ultsch. + A., Lotsch J. (2015) . + date_publication: '2017-03-13' + bug_reports: '' + url: https://www.uni-marburg.de/fb12/datenbionik/software-en + url_cran: https://CRAN.R-project.org/package=ABCanalysis + url_git: '' +abclass: + version: 0.4.0 + title: Angle-Based Large-Margin Classifiers + maintainer: Wenjie Wang + description: |- + Multi-category angle-based large-margin classifiers. + See Zhang and Liu (2014) for details. + date_publication: '2022-09-18' + bug_reports: https://github.com/wenjie2wang/abclass/issues + url: https://wwenjie.org/abclass + url_cran: https://CRAN.R-project.org/package=abclass + url_git: https://github.com/wenjie2wang/abclass +ABCoptim: + version: 0.15.0 + title: Implementation of Artificial Bee Colony (ABC) Optimization + maintainer: George Vega Yon + description: |- + An implementation of Karaboga (2005) Artificial Bee Colony + Optimization algorithm . + This (working) version is a Work-in-progress, which is + why it has been implemented using pure R code. This was developed upon the basic + version programmed in C and distributed at the algorithm's official website. + date_publication: '2017-11-06' + bug_reports: '' + url: http://mf.erciyes.edu.tr/abc/ + url_cran: https://CRAN.R-project.org/package=ABCoptim + url_git: http://github.com/gvegayon/ABCoptim +abcrf: + version: '1.9' + title: Approximate Bayesian Computation via Random Forests + maintainer: Jean-Michel Marin + description: |- + Performs Approximate Bayesian Computation (ABC) model choice and parameter inference via random forests. + Pudlo P., Marin J.-M., Estoup A., Cornuet J.-M., Gautier M. and Robert C. P. (2016) . + Estoup A., Raynal L., Verdu P. and Marin J.-M. . + Raynal L., Marin J.-M., Pudlo P., Ribatet M., Robert C. P. and Estoup A. (2019) . + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abcrf + url_git: '' +abcrlda: + version: 1.0.3 + title: |- + Asymptotically Bias-Corrected Regularized Linear Discriminant + Analysis + maintainer: Dmitriy Fedorov + description: |- + Offers methods to perform asymptotically bias-corrected regularized linear discriminant analysis (ABC_RLDA) for cost-sensitive binary classification. The bias-correction is an estimate of the bias term added to regularized discriminant analysis (RLDA) that minimizes the overall risk. The default magnitude of misclassification costs are equal and set to 0.5; however, the package also offers the options to set them to some predetermined values or, alternatively, take them as hyperparameters to tune. + A. Zollanvari, M. Abdirash, A. Dadlani and B. Abibullaev (2019) . + date_publication: '2020-05-28' + bug_reports: '' + url: https://ieeexplore.ieee.org/document/8720003/ + url_cran: https://CRAN.R-project.org/package=abcrlda + url_git: '' +abctools: + version: 1.1.7 + title: Tools for ABC Analyses + maintainer: Matt Nunes + description: |- + Tools for approximate Bayesian computation including summary statistic selection and assessing coverage. + See Nunes and Prangle (2015) and Rodrigues, Prangle and Sisson (2018) . + date_publication: '2023-09-18' + bug_reports: https://github.com/dennisprangle/abctools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=abctools + url_git: https://github.com/dennisprangle/abctools +abd: + version: 0.2-8 + title: The Analysis of Biological Data + maintainer: Kevin M. Middleton + description: |- + The abd package contains data sets and sample code for The + Analysis of Biological Data by Michael Whitlock and Dolph Schluter (2009; + Roberts & Company Publishers). + date_publication: '2015-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abd + url_git: '' +abdiv: + version: 0.2.0 + title: Alpha and Beta Diversity Measures + maintainer: Kyle Bittinger + description: |- + A collection of measures for measuring ecological diversity. + Ecological diversity comes in two flavors: alpha diversity measures the + diversity within a single site or sample, and beta diversity measures the + diversity across two sites or samples. This package overlaps considerably + with other R packages such as 'vegan', 'gUniFrac', 'betapart', and 'fossil'. + We also include a wide range of functions that are implemented in software + outside the R ecosystem, such as 'scipy', 'Mothur', and 'scikit-bio'. The + implementations here are designed to be basic and clear to the reader. + date_publication: '2020-01-20' + bug_reports: https://github.com/kylebittinger/abdiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=abdiv + url_git: https://github.com/kylebittinger/abdiv +abe: + version: 3.0.1 + title: Augmented Backward Elimination + maintainer: Rok Blagus + description: Performs augmented backward elimination and checks the stability of + the obtained model. Augmented backward elimination combines significance or information + based criteria with the change in estimate to either select the optimal model + for prediction purposes or to serve as a tool to obtain a practically sound, highly + interpretable model. More details can be found in Dunkler et al. (2014) . + date_publication: '2017-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abe + url_git: '' +aberrance: + version: 0.2.0 + title: Detect Aberrant Behavior in Test Data + maintainer: Kylie Gorney + description: |- + Detect several types of aberrant behavior, including answer + copying, answer similarity, nonparametric misfit, parametric misfit, + preknowledge, rapid guessing, and test tampering. + date_publication: '2025-02-07' + bug_reports: https://github.com/kyliegorney/aberrance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aberrance + url_git: https://github.com/kyliegorney/aberrance +abess: + version: 0.4.9 + title: Fast Best Subset Selection + maintainer: Jin Zhu + description: Extremely efficient toolkit for solving the best subset selection problem + . This package is its R interface. + The package implements and generalizes algorithms designed in + that exploits a novel sequencing-and-splicing technique to guarantee exact support + recovery and globally optimal solution in polynomial times for linear model. It + also supports best subset selection for logistic regression, Poisson regression, + Cox proportional hazard model, Gamma regression, multiple-response regression, + multinomial logistic regression, ordinal regression, (sequential) principal component + analysis, and robust principal component analysis. The other valuable features + such as the best subset of group selection and sure + independence screening are also provided. + date_publication: '2024-09-09' + bug_reports: https://github.com/abess-team/abess/issues + url: https://abess-team.github.io/abess/ + url_cran: https://CRAN.R-project.org/package=abess + url_git: https://github.com/abess-team/abess +abglasso: + version: 0.1.1 + title: Adaptive Bayesian Graphical Lasso + maintainer: Jarod Smith + description: Implements a Bayesian adaptive graphical lasso data-augmented block + Gibbs sampler. The sampler simulates the posterior distribution of precision matrices + of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB + routine proposed in Wang (2012) . + date_publication: '2021-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abglasso + url_git: '' +ABHgenotypeR: + version: 1.0.1 + title: Easy Visualization of ABH Genotypes + maintainer: Stefan Reuscher + description: |- + Easy to use functions to visualize marker data + from biparental populations. Useful for both analyzing and + presenting genotypes in the ABH format. + date_publication: '2016-02-04' + bug_reports: http://github.com/StefanReuscher/ABHgenotypeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ABHgenotypeR + url_git: http://github.com/StefanReuscher/ABHgenotypeR +abima: + version: '1.1' + title: |- + Adaptive Bootstrap Inference for Mediation Analysis with + Enhanced Statistical Power + maintainer: Canyi Chen + description: Assess whether and how a specific continuous or categorical exposure + affects the outcome of interest through one- or multi-dimensional mediators using + an adaptive bootstrap (AB) approach. The AB method allows to make inference for + composite null hypotheses of no mediation effect, providing valid type I error + control and thus optimizes statistical power. For more technical details, refer + to He, Song and Xu (2024) . + date_publication: '2024-10-25' + bug_reports: https://github.com/canyi-chen/abima/issues + url: https://websites.umich.edu/~songlab/software.html#ABIMA + url_cran: https://CRAN.R-project.org/package=abima + url_git: https://github.com/canyi-chen/abima +abind: + version: 1.4-8 + title: Combine Multidimensional Arrays + maintainer: Tony Plate + description: |- + Combine multidimensional arrays into a single array. + This is a generalization of 'cbind' and 'rbind'. Works with + vectors, matrices, and higher-dimensional arrays (aka tensors). + Also provides functions 'adrop', 'asub', and 'afill' for + manipulating, extracting and replacing data in arrays. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abind + url_git: '' +abjData: + version: 1.1.2 + title: |- + Databases Used Routinely by the Brazilian Jurimetrics + Association + maintainer: Julio Trecenti + description: |- + The Brazilian Jurimetrics Association (ABJ in + Portuguese, see for more information) is + a non-profit organization which aims to investigate and promote the + use of statistics and probability in the study of Law and its + institutions. This package has a set of datasets commonly used in + our book. + date_publication: '2022-06-15' + bug_reports: '' + url: https://abjur.github.io/abjData/ + url_cran: https://CRAN.R-project.org/package=abjData + url_git: '' +abjutils: + version: 0.3.2 + title: |- + Useful Tools for Jurimetrical Analysis Used by the Brazilian + Jurimetrics Association + maintainer: Caio Lente + description: |- + The Brazilian Jurimetrics Association (ABJ in Portuguese, see + for more information) is a non-profit + organization which aims to investigate and promote the use of + statistics and probability in the study of Law and its institutions. + This package implements general purpose tools used by ABJ, such as + functions for sampling and basic manipulation of Brazilian lawsuits + identification number. It also implements functions for text cleaning, + such as accentuation removal. + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abjutils + url_git: https://github.com/abjur/abjutils +ablasso: + version: '1.1' + title: Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models + maintainer: Junyu Chen + description: Implements the Arellano-Bond estimation method combined with LASSO + for dynamic linear panel models. See Chernozhukov et al. (2024) "Arellano-Bond + LASSO Estimator for Dynamic Linear Panel Models". arXiv preprint . + date_publication: '2025-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ablasso + url_git: '' +ABM: + version: 0.4.3 + title: Agent Based Model Simulation Framework + maintainer: Junling Ma + description: |- + A high-performance, flexible and extensible framework to + develop continuous-time agent based models. Its high performance + allows it to simulate millions of agents efficiently. Agents are + defined by their states (arbitrary R lists). The events are handled in + chronological order. This avoids the multi-event interaction problem + in a time step of discrete-time simulations, and gives precise + outcomes. The states are modified by provided or user-defined events. + The framework provides a flexible and customizable implementation of + state transitions (either spontaneous or caused by agent + interactions), making the framework suitable to apply to epidemiology + and ecology, e.g., to model life history stages, competition and + cooperation, and disease and information spread. The agent + interactions are flexible and extensible. The framework provides + random mixing and network interactions, and supports multi-level + mixing patterns. It can be easily extended to other interactions such + as inter- and intra-households (or workplaces and schools) by + subclassing an R6 class. It can be used to study the effect of + age-specific, group-specific, and contact- specific intervention + strategies, and complex interactions between individual behavior and + population dynamics. This modeling concept can also be used in + business, economical and political models. As a generic event based + framework, it can be applied to many other fields. More information + about the implementation and examples can be found at + . + date_publication: '2025-01-26' + bug_reports: https://github.com/junlingm/ABM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ABM + url_git: https://github.com/junlingm/ABM +abmR: + version: 1.0.10 + title: Agent-Based Models in R + maintainer: Benjamin Gochanour + description: Supplies tools for running agent-based models (ABM) in R, as discussed + in Gochanour et al. (2022) . The package contains + two movement functions, each of which is based on the Ornstein-Uhlenbeck (OU) + model (Ornstein & Uhlenbeck, 1930) . It also contains + several visualization and data summarization functions to facilitate the presentation + of simulation results. + date_publication: '2023-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abmR + url_git: '' +abn: + version: 3.1.1 + title: Modelling Multivariate Data with Additive Bayesian Networks + maintainer: Matteo Delucchi + description: |- + The 'abn' R package facilitates Bayesian network analysis, a + probabilistic graphical model that derives from empirical data a + directed acyclic graph (DAG). This DAG describes the dependency + structure between random variables. The R package 'abn' provides + routines to help determine optimal Bayesian network models for a given + data set. These models are used to identify statistical dependencies + in messy, complex data. Their additive formulation is equivalent to + multivariate generalised linear modelling, including mixed models with + independent and identically distributed (iid) random effects. The core + functionality of the 'abn' package revolves around model selection, + also known as structure discovery. It supports both exact and + heuristic structure learning algorithms and does not restrict the data + distribution of parent-child combinations, providing flexibility in + model creation and analysis. The 'abn' package uses Laplace + approximations for metric estimation and includes wrappers to the + 'INLA' package. It also employs 'JAGS' for data simulation purposes. + For more resources and information, visit the 'abn' website. + date_publication: '2024-05-30' + bug_reports: https://github.com/furrer-lab/abn/issues + url: https://r-bayesian-networks.org/ + url_cran: https://CRAN.R-project.org/package=abn + url_git: https://github.com/furrer-lab/abn +abnormality: + version: 0.1.0 + title: |- + Measure a Subject's Abnormality with Respect to a Reference + Population + maintainer: Michael Marks + description: 'Contains the functions to implement the methodology and considerations + laid out by Marks et al. in the manuscript Measuring Abnormality in High Dimensional + Spaces: Applications in Biomechanical Gait Analysis. As of 2/27/2018 this paper + has been submitted and is under scientific review. Using high-dimensional datasets + to measure a subject’s overall level of abnormality as compared to a reference + population is often needed in outcomes research. Utilizing applications in instrumented + gait analysis, that article demonstrates how using data that is inherently non-independent + to measure overall abnormality may bias results. A methodology is introduced to + address this bias to accurately measure overall abnormality in high dimensional + spaces. While this methodology is in line with previous literature, it differs + in two major ways. Advantageously, it can be applied to datasets in which the + number of observations is less than the number of features/variables, and it can + be abstracted to practically any number of domains or dimensions. After applying + the proposed methodology to the original data, the researcher is left with a set + of uncorrelated variables (i.e. principal components) with which overall abnormality + can be measured without bias. Different considerations are discussed in that article + in deciding the appropriate number of principal components to keep and the aggregate + distance measure to utilize.' + date_publication: '2018-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abnormality + url_git: '' +abodOutlier: + version: '0.1' + title: Angle-Based Outlier Detection + maintainer: Jose Jimenez + description: Performs angle-based outlier detection on a given dataframe. Three + methods are available, a full but slow implementation using all the data that + has cubic complexity, a fully randomized one which is way more efficient and another + using k-nearest neighbours. These algorithms are specially well suited for high + dimensional data outlier detection. + date_publication: '2015-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abodOutlier + url_git: '' +ABPS: + version: '0.3' + title: The Abnormal Blood Profile Score to Detect Blood Doping + maintainer: Frédéric Schütz + description: |- + An implementation of the Abnormal Blood Profile Score (ABPS, + part of the Athlete Biological Passport program of the World Anti-Doping + Agency), which combines several blood parameters into a single score in + order to detect blood doping (Sottas et al. (2006) + ). The package also contains functions to + calculate other scores used in anti-doping programs, such as the + OFF-score (Gore et al. (2003) ), + as well as example data. + date_publication: '2018-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ABPS + url_git: '' +ABRSQOL: + version: 1.0.0 + title: |- + Quality-of-Life Solver for "Measuring Quality of Life under + Spatial Frictions" + maintainer: Max von Mylius + description: |- + This toolkit implements a numerical solution algorithm + to invert a quality of life measure from observed data. Unlike + the traditional Rosen-Roback measure, this measure accounts for + mobility frictions—generated by idiosyncratic tastes and local + ties — and trade frictions — generated by trade costs and + non-tradable services, thereby reducing non-classical + measurement error. The QoL measure is based on Ahlfeldt, Bald, + Roth, Seidel (2024) + + "Measuring Quality of Life under Spatial Frictions". When using + this programme or the toolkit in your work, please cite the paper. + date_publication: '2024-11-06' + bug_reports: https://github.com/Ahlfeldt/ABRSQOL-toolkit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ABRSQOL + url_git: https://github.com/Ahlfeldt/ABRSQOL-toolkit#readme +abseil: + version: 2023.8.2.1 + title: '''C++'' Header Files from ''Abseil''' + maintainer: Xingchi Li + description: |- + Wraps the 'Abseil' 'C++' library for use by R packages. + Original files are from . + Patches are located at + . + date_publication: '2023-10-01' + bug_reports: https://github.com/doccstat/abseil-r/issues + url: https://abseil.xingchi.li + url_cran: https://CRAN.R-project.org/package=abseil + url_git: https://github.com/doccstat/abseil-r +absorber: + version: '1.0' + title: Variable Selection in Nonparametric Models using B-Splines + maintainer: Mary E. Savino + description: A variable selection method using B-Splines in multivariate nOnparametric + Regression models Based on partial dErivatives Regularization (ABSORBER) implements + a novel variable selection method in a nonlinear multivariate model using B-splines. + For further details we refer the reader to the paper Savino, M. E. and Lévy-Leduc, + C. (2024), . + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=absorber + url_git: '' +abstr: + version: 0.4.1 + title: |- + R Interface to the A/B Street Transport System Simulation + Software + maintainer: Nathanael Sheehan + description: |- + Provides functions to convert origin-destination data, + represented as straight 'desire lines' in the 'sf' Simple Features + class system, into JSON files that can be directly imported into + A/B Street , a free and open source tool + for simulating urban transport systems and scenarios of change + . + date_publication: '2021-11-30' + bug_reports: https://github.com/a-b-street/abstr/issues + url: https://a-b-street.github.io/abstr/ + url_cran: https://CRAN.R-project.org/package=abstr + url_git: https://github.com/a-b-street/abstr +abstractr: + version: 0.1.0 + title: An R-Shiny Application for Creating Visual Abstracts + maintainer: Matthew Kumar + description: An R-Shiny application to create visual abstracts for original research. + A variety of user defined options and formatting are included. + date_publication: '2019-01-20' + bug_reports: '' + url: https://matt-kumar.shinyapps.io/portfolio + url_cran: https://CRAN.R-project.org/package=abstractr + url_git: '' +ABSurvTDC: + version: 0.1.0 + title: |- + Survival Analysis using Time Dependent Covariate for Animal + Breeding + maintainer: Dr. Himadri Ghosh + description: Survival analysis is employed to model the time it takes for events + to occur. Survival model examines the relationship between survival and one or + more predictors, usually termed covariates in the survival-analysis literature. + To this end, Cox-proportional (Cox-PH) hazard rate model introduced in a seminal + paper by Cox (1972) , is a broadly applicable + and the most widely used method of survival analysis. This package can be used + to estimate the effect of fixed and time-dependent covariates and also to compute + the survival probabilities of the lactation of dairy animal. This package has + been developed using algorithm of Klein and Moeschberger (2003) . + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ABSurvTDC + url_git: '' +abtest: + version: 1.0.1 + title: Bayesian A/B Testing + maintainer: Quentin F. Gronau + description: |- + Provides functions for Bayesian A/B testing including prior elicitation + options based on Kass and Vaidyanathan (1992) . + Gronau, Raj K. N., & Wagenmakers (2021) . + date_publication: '2021-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abtest + url_git: '' +abundant: + version: '1.2' + title: |- + High-Dimensional Principal Fitted Components and Abundant + Regression + maintainer: Adam J. Rothman + description: |- + Fit and predict with the high-dimensional principal fitted + components model. This model is described by Cook, Forzani, and Rothman (2012) + . + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=abundant + url_git: '' +Ac3net: + version: 1.2.2 + title: Inferring Directional Conservative Causal Core Gene Networks + maintainer: Gokmen Altay + description: Infers directional conservative causal core (gene) networks. It is + an advanced version of the algorithm C3NET by providing directional network. Gokmen + Altay (2018) , bioRxiv. + date_publication: '2018-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ac3net + url_git: '' +ACA: + version: '1.1' + title: Abrupt Change-Point or Aberration Detection in Point Series + maintainer: Daniel Amorese + description: Offers an interactive function for the detection of breakpoints in + series. + date_publication: '2018-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACA + url_git: '' +AcademicThemes: + version: 0.0.2 + title: Colour Plots with Palettes from Academic Institutions + maintainer: Hugh Warden + description: |- + Functionality to allow users to easily colour plots with the colour + palettes of various academic institutions. + date_publication: '2024-02-26' + bug_reports: https://github.com/hwarden162/AcademicThemes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AcademicThemes + url_git: https://github.com/hwarden162/AcademicThemes +academictwitteR: + version: 0.3.1 + title: |- + Access the Twitter Academic Research Product Track V2 API + Endpoint + maintainer: Christopher Barrie + description: |- + Package to query the Twitter Academic Research Product Track, + providing access to full-archive search and other v2 API endpoints. Functions + are written with academic research in mind. They provide flexibility in how + the user wishes to store collected data, and encourage regular storage of data + to mitigate loss when collecting large volumes of tweets. They also provide + workarounds to manage and reshape the format in which data is provided on + the client side. + date_publication: '2022-02-16' + bug_reports: https://github.com/cjbarrie/academictwitteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=academictwitteR + url_git: https://github.com/cjbarrie/academictwitteR +acc: + version: 1.3.3 + title: Exploring Accelerometer Data + maintainer: Jaejoon Song + description: |- + Processes accelerometer data from uni-axial and tri-axial devices, + and generates data summaries. Also includes functions to plot, analyze, and + simulate accelerometer data. + date_publication: '2016-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acc + url_git: '' +acca: + version: '0.2' + title: A Canonical Correlation Analysis with Inferential Guaranties + maintainer: livio finos + description: It performs Canonical Correlation Analysis and provides inferential + guaranties on the correlation components. The p-values are computed following + the resampling method developed in Winkler, A. M., Renaud, O., Smith, S. M., & + Nichols, T. E. (2020). Permutation inference for canonical correlation analysis. + NeuroImage, . Furthermore, it provides plotting + tools to visualize the results. + date_publication: '2022-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acca + url_git: '' +accelerometry: + version: 3.1.2 + title: Functions for Processing Accelerometer Data + maintainer: Dane R. Van Domelen + description: A collection of functions that perform operations on time-series accelerometer + data, such as identify non-wear time, flag minutes that are part of an activity + bout, and find the maximum 10-minute average count value. The functions are generally + very flexible, allowing for a variety of algorithms to be implemented. Most of + the functions are written in C++ for efficiency. + date_publication: '2018-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=accelerometry + url_git: '' +accelmissing: + version: '1.4' + title: Missing Value Imputation for Accelerometer Data + maintainer: Jung Ae Lee + description: Imputation for the missing count values in accelerometer data. The + methodology includes both parametric and semi-parametric multiple imputations + under the zero-inflated Poisson lognormal model. This package also provides multiple + functions to pre-process the accelerometer data previous to the missing data imputation. + These includes detecting wearing and non-wearing time, selecting valid days and + subjects, and creating plots. + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=accelmissing + url_git: '' +AccelStab: + version: 2.1.1 + title: Accelerated Stability Kinetic Modelling + maintainer: Ben Wells + description: |- + Estimate the Šesták–Berggren kinetic model (degradation model) from experimental data. A + A closed-form (analytic) solution to the degradation model is implemented as a non-linear fit, + allowing for the extrapolation of the degradation of a drug product - both in time and + temperature. Parametric bootstrap, with kinetic parameters drawn from the multivariate + t-distribution, and analytical formulae (the delta method) are available options to calculate + the confidence and prediction intervals. + The results (modelling, extrapolations and statistical intervals) can be visualised + with multiple plots. The examples illustrate the accelerated stability modelling in drugs and + vaccines development. + date_publication: '2025-01-20' + bug_reports: https://github.com/AccelStab/AccelStab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AccelStab + url_git: https://github.com/AccelStab/AccelStab +accept: + version: 1.0.0 + title: The Acute COPD Exacerbation Prediction Tool (ACCEPT) + maintainer: Amin Adibi + description: Allows clinicians to predict the rate and severity of future acute + exacerbation in Chronic Obstructive Pulmonary Disease (COPD) patients, based on + the clinical prediction models published in Adibi et al. (2020) + and Safari et al. (2022) . + date_publication: '2023-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=accept + url_git: '' +AcceptanceSampling: + version: 1.0-10 + title: Creation and Evaluation of Acceptance Sampling Plans + maintainer: Andreas Kiermeier + description: |- + Provides functionality for creating and + evaluating acceptance sampling plans. Sampling plans can be single, + double or multiple. + date_publication: '2023-12-06' + bug_reports: https://github.com/andreaskiermeier/AcceptanceSampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AcceptanceSampling + url_git: https://github.com/andreaskiermeier/AcceptanceSampling +AcceptReject: + version: 0.1.2 + title: |- + Acceptance-Rejection Method for Generating Pseudo-Random + Observations + maintainer: Pedro Rafael D. Marinho + description: 'Provides a function that implements the acceptance-rejection method + in an optimized manner to generate pseudo-random observations for discrete or + continuous random variables. Proposed by von Neumann J. (1951), , + the function is optimized to work in parallel on Unix-based operating systems + and performs well on Windows systems. The acceptance-rejection method implemented + optimizes the probability of generating observations from the desired random variable, + by simply providing the probability function or probability density function, + in the discrete and continuous cases, respectively. Implementation is based on + references CASELLA, George at al. (2004) , NEAL, + Radford M. (2003) and Bishop, Christopher + M. (2006, ISBN: 978-0387310732).' + date_publication: '2024-05-07' + bug_reports: https://github.com/prdm0/AcceptReject/issues/ + url: https://prdm0.github.io/AcceptReject/ + url_cran: https://CRAN.R-project.org/package=AcceptReject + url_git: '' +accessibility: + version: 1.4.0 + title: Transport Accessibility Measures + maintainer: Daniel Herszenhut + description: |- + A set of fast and convenient functions to help conducting + accessibility analyses. Given a pre-computed travel cost matrix and a + land use dataset (containing the location of jobs, healthcare and + population, for example), the package allows one to calculate + accessibility levels and accessibility poverty and inequality. The + package covers the majority of the most commonly used accessibility + measures (such as cumulative opportunities, gravity-based and floating + catchment areas methods), as well as the most frequently used + inequality and poverty metrics (such as the Palma ratio, the + concentration and Theil indices and the FGT family of measures). + date_publication: '2024-03-06' + bug_reports: https://github.com/ipeaGIT/accessibility/issues + url: https://ipeagit.github.io/accessibility/ + url_cran: https://CRAN.R-project.org/package=accessibility + url_git: https://github.com/ipeaGIT/accessibility +accessr: + version: 1.1.1 + title: |- + Command Line Tools to Produce Accessible Documents using 'R + Markdown' + maintainer: Paul J. Northrop + description: |- + Provides functions to produce accessible 'HTML' slides, 'HTML', + 'Word' and 'PDF' documents from input 'R markdown' files. Accessible 'PDF' + files are produced only on a 'Windows' Operating System. One aspect of + accessibility is providing a headings structure that is recognised by a + screen reader, providing a navigational tool for a blind or + partially-sighted person. A key aim is to produce documents of different + formats easily from each of a collection of 'R markdown' source files. + Input 'R markdown' files are rendered using the render() function from the + 'rmarkdown' package . A 'zip' + file containing multiple output files can be produced from one function + call. A user-supplied template 'Word' document can be used to determine the + formatting of an output 'Word' document. Accessible 'PDF' files are + produced from 'Word' documents using 'OfficeToPDF' + . A convenience function, + install_otp() is provided to install this software. The option to print + 'HTML' output to (non-accessible) 'PDF' files is also available. + date_publication: '2025-01-15' + bug_reports: https://github.com/paulnorthrop/accessr/issues + url: https://paulnorthrop.github.io/accessr/ + url_cran: https://CRAN.R-project.org/package=accessr + url_git: https://github.com/paulnorthrop/accessr +accessrmd: + version: 1.0.0 + title: Improving the Accessibility of 'rmarkdown' Documents + maintainer: Rich Leyshon + description: |- + Provides a simple method to improve the accessibility of + 'rmarkdown' documents. The package provides functions for creating or + modifying 'rmarkdown' documents, resolving known errors and alerts that + result in accessibility issues for screen reader users. + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=accessrmd + url_git: '' +accrual: + version: '1.4' + title: Bayesian Accrual Prediction + maintainer: Junhao Liu + description: Participant recruitment for medical research is challenging. Slow accrual + leads to delays in research. Accrual monitoring during the process of recruitment + is critical. Researchers need reliable tools to manage the accrual rate. We developed + a Bayesian method that integrates the researcher's experience with previous trials + and data from the current study, providing reliable predictions on accrual rate + for clinical studies. For more details and background on these methodologies, + see the publications of Byron, Stephen and Susan (2008) , + and Yu et al. (2015) . In this R package, Bayesian accrual + prediction functions are presented, which can be easily used by statisticians + and clinical researchers. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=accrual + url_git: '' +accrualPlot: + version: 1.0.7 + title: Accrual Plots and Predictions for Clinical Trials + maintainer: Lukas Bütikofer + description: |- + Tracking accrual in clinical trials is important for trial success. + If accrual is too slow, the trial will take too long and be too expensive. If + accrual is much faster than expected, time sensitive tasks such as the writing + of statistical analysis plans might need to be rushed. 'accrualPlot' provides + functions to aid the tracking of accrual and predict when a trial will reach + it's intended sample size. + date_publication: '2022-08-16' + bug_reports: https://github.com/CTU-Bern/accrualPlot/issues + url: https://ctu-bern.github.io/accrualPlot/ + url_cran: https://CRAN.R-project.org/package=accrualPlot + url_git: https://github.com/CTU-Bern/accrualPlot +accSDA: + version: 1.1.3 + title: Accelerated Sparse Discriminant Analysis + maintainer: Gudmundur Einarsson + description: |- + Implementation of sparse linear discriminant analysis, which is a supervised + classification method for multiple classes. Various novel optimization approaches to + this problem are implemented including alternating direction method of multipliers ('ADMM'), + proximal gradient (PG) and accelerated proximal gradient ('APG') (See Atkins 'et al'. ). + Functions for performing cross validation are also supplied along with basic prediction + and plotting functions. + Sparse zero variance discriminant analysis ('SZVD') is also included in the package + (See Ames and Hong, ). See the 'github' wiki for a more extended description. + date_publication: '2024-03-06' + bug_reports: https://github.com/gumeo/accSDA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=accSDA + url_git: https://github.com/gumeo/accSDA/wiki +accucor: + version: 0.3.1 + title: Natural Abundance Correction of Mass Spectrometer Data + maintainer: Lance Parsons + description: |- + An isotope natural abundance correction algorithm that + is needed especially for high resolution mass spectrometers. Supports + correction for 13C, 2H and 15N. Su X, Lu W and Rabinowitz J (2017) + . + date_publication: '2023-09-14' + bug_reports: https://github.com/XiaoyangSu/AccuCor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=accucor + url_git: https://github.com/XiaoyangSu/AccuCor +accumulate: + version: 0.9.3 + title: Split-Apply-Combine with Dynamic Groups + maintainer: Mark van der Loo + description: |- + Estimate group aggregates, where one can set user-defined conditions + that each group of records must satisfy to be suitable for aggregation. If + a group of records is not suitable, it is expanded using a collapsing scheme + defined by the user. + date_publication: '2023-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=accumulate + url_git: https://github.com/markvanderloo/accumulate +acdcquery: + version: 1.0.1 + title: Query the Attentional Control Data Collection + maintainer: Sven Lesche + description: |- + Interact with the Attentional Control Data Collection (ACDC). + Connect to the database via connect_to_db(), set filter arguments via add_argument() + and query the database via query_db(). + date_publication: '2023-10-20' + bug_reports: https://github.com/SLesche/acdc-query/issues + url: '' + url_cran: https://CRAN.R-project.org/package=acdcquery + url_git: https://github.com/SLesche/acdc-query +acdcR: + version: 1.0.0 + title: Agro-Climatic Data by County + maintainer: Seong D. Yun + description: |- + The functions are designed to calculate the most widely-used county-level variables in + agricultural production or agricultural-climatic and weather analyses. To operate some functions + in this package needs download of the bulk PRISM raster. See the examples, testing versions and + more details from: . + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acdcR + url_git: https://github.com/ysd2004/acdcR +ACDm: + version: 1.0.4.3 + title: Tools for Autoregressive Conditional Duration Models + maintainer: Markus Belfrage + description: Package for Autoregressive Conditional Duration (ACD, Engle and Russell, + 1998) models. Creates trade, price or volume durations from transactions (tic) + data, performs diurnal adjustments, fits various ACD models and tests them. + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACDm + url_git: '' +ACE.CoCo: + version: '0.1' + title: Analysis of Correlated High-Dimensional Expression (ACE) Data + maintainer: Peng Wang + description: |- + A function for estimating factor models. Give factor-adjusted statistics, + factor-adjusted mean estimation (one-sample test) or factor-adjusted mean difference + estimation (two-sample test). + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACE.CoCo + url_git: https://github.com/hongyuan-cao/ACE +ace2fastq: + version: 0.6.0 + title: ACE File to FASTQ Converter + maintainer: Reinhard Simon + description: |- + The ACE file format is used in genomics to store contigs from sequencing machines. + This tools converts it into FASTQ format. Both formats contain the + sequence characters and their + corresponding quality information. Unlike the FASTQ file, the ace file stores the + quality values numerically. + The conversion algorithm uses the standard Sanger formula. The package facilitates insertion + into pipelines, and content inspection. + date_publication: '2019-06-20' + bug_reports: https://github.com/c5sire/ace2fastq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ace2fastq + url_git: https://github.com/c5sire/ace2fastq +acebayes: + version: '1.10' + title: Optimal Bayesian Experimental Design using the ACE Algorithm + maintainer: Antony M. Overstall + description: Optimal Bayesian experimental design using the approximate coordinate + exchange (ACE) algorithm. See . + date_publication: '2020-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acebayes + url_git: '' +aceEditor: + version: 1.0.1 + title: The 'Ace' Editor as a HTML Widget + maintainer: Stéphane Laurent + description: Wraps the 'Ace' editor in a HTML widget. The 'Ace' editor has support + for many languages. It can be opened in the viewer pane of 'RStudio', and this + provides a second source editor. + date_publication: '2021-03-06' + bug_reports: https://github.com/stla/aceEditor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aceEditor + url_git: https://github.com/stla/aceEditor +ACEP: + version: 0.0.22 + title: Analisis Computacional de Eventos de Protesta + maintainer: Agustin Nieto + description: |- + La libreria 'ACEP' contiene funciones especificas para + desarrollar analisis computacional de eventos de protesta. Asimismo, + contiene base de datos con colecciones de notas sobre protestas y + diccionarios de palabras conflictivas. Coleccion de diccionarios que + reune diccionarios de diferentes origenes. The 'ACEP' library + contains specific functions to perform computational analysis of + protest events. It also contains a database with collections of notes + on protests and dictionaries of conflicting words. Collection of + dictionaries that brings together dictionaries from different sources. + date_publication: '2023-10-19' + bug_reports: https://github.com/agusnieto77/ACEP/issues + url: https://agusnieto77.github.io/ACEP/ + url_cran: https://CRAN.R-project.org/package=ACEP + url_git: https://github.com/agusnieto77/ACEP +acepack: + version: 1.6.1 + title: ACE and AVAS for Selecting Multiple Regression Transformations + maintainer: Shawn Garbett + description: |- + Two nonparametric methods for multiple regression transform selection are provided. + The first, Alternating Conditional Expectations (ACE), + is an algorithm to find the fixed point of maximal + correlation, i.e. it finds a set of transformed response variables that maximizes R^2 + using smoothing functions [see Breiman, L., and J.H. Friedman. 1985. "Estimating Optimal Transformations + for Multiple Regression and Correlation". Journal of the American Statistical Association. + 80:580-598. ]. + Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when + correlation is low [see Tibshirani, R. 1986. "Estimating Transformations for Regression via Additivity + and Variance Stabilization". Journal of the American Statistical Association. 83:394-405. + ]. A good introduction to these two methods is in chapter 16 of + Frank Harrell's "Regression Modeling Strategies" in the Springer Series in Statistics. + A permutation independence test is included from [Holzmann, H., Klar, B. 2025. "Lancaster correlation - a new dependence measure + linked to maximum correlation". Scandinavian Journal of Statistics. + 52(1):145-169 ]. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acepack + url_git: '' +ACEsearch: + version: 1.0.0 + title: '''ACE'' Search Engine API' + maintainer: Vladimir Polony + description: |- + 'ACE' (Advanced Cohort Engine) is a powerful tool that allows constructing cohorts of patients + extremely quickly and efficiently. This package is designed to interface directly with an + instance of 'ACE' search engine and facilitates API queries and data dumps. Prerequisite + is a good knowledge of the temporal language to be able to efficiently construct a query. + More information available at . + date_publication: '2020-09-28' + bug_reports: '' + url: https://shahlab.stanford.edu/start + url_cran: https://CRAN.R-project.org/package=ACEsearch + url_git: '' +ACEsimFit: + version: 0.0.0.9 + title: ACE Kin Pair Data Simulations and Model Fitting + maintainer: Xuanyu Lyu + description: A few functions aim to provide a statistic tool for three purposes. + First, simulate kin pairs data based on the assumption that every trait is affected + by genetic effects (A), common environmental effects (C) and unique environmental + effects (E).Second, use kin pairs data to fit an ACE model and get model fit output.Third, + calculate power of A estimate given a specific condition. For the mechanisms of + power calculation, we suggest to check Visscher(2004). + date_publication: '2022-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACEsimFit + url_git: '' +ACEt: + version: 1.9.0 + title: Estimating Dynamic Heritability and Twin Model Comparison + maintainer: Liang He + description: Twin models that are able to estimate the dynamic behaviour of the + variance components in the classical twin models with respect to age using B-splines + and P-splines. + date_publication: '2023-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACEt + url_git: '' +acfMPeriod: + version: 1.0.0 + title: Robust Estimation of the ACF from the M-Periodogram + maintainer: Higor Cotta + description: Non-robust and robust computations of the sample autocovariance (ACOVF) + and sample autocorrelation functions (ACF) of univariate and multivariate processes. + The methodology consists in reversing the diagonalization procedure involving + the periodogram or the cross-periodogram and the Fourier transform vectors, and, + thus, obtaining the ACOVF or the ACF as discussed in Fuller (1995) . + The robust version is obtained by fitting robust M-regressors to obtain the M-periodogram + or M-cross-periodogram as discussed in Reisen et al. (2017) . + date_publication: '2019-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acfMPeriod + url_git: '' +Achilles: + version: 1.7.2 + title: Achilles Data Source Characterization + maintainer: Frank DeFalco + description: |- + Automated Characterization of Health Information at Large-Scale + Longitudinal Evidence Systems. Creates a descriptive statistics summary for + an Observational Medical Outcomes Partnership Common Data Model standardized + data source. This package includes functions for executing summary queries on + the specified data source and exporting reporting content for use across a + variety of Observational Health Data Sciences and Informatics community + applications. + date_publication: '2023-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Achilles + url_git: '' +acid: + version: '1.1' + title: Analysing Conditional Income Distributions + maintainer: Alexander Sohn + description: Functions for the analysis of income distributions for subgroups of + the population as defined by a set of variables like age, gender, region, etc. + This entails a Kolmogorov-Smirnov test for a mixture distribution as well as functions + for moments, inequality measures, entropy measures and polarisation measures of + income distributions. This package thus aides the analysis of income inequality + by offering tools for the exploratory analysis of income distributions at the + disaggregated level. + date_publication: '2016-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acid + url_git: '' +acled.api: + version: 1.1.8 + title: Automated Retrieval of ACLED Conflict Event Data + maintainer: Christoph Dworschak + description: Access and manage the application programming interface (API) of the + Armed Conflict Location & Event Data Project (ACLED) at . + The package makes it easy to retrieve a user-defined sample (or all of the available + data) of ACLED, enabling a seamless integration of regular data updates into the + research work flow. It requires a minimal number of dependencies. See the package's + README file for a note on replicability when drawing on ACLED data. When using + this package, you acknowledge that you have read ACLED's terms and conditions + of use, and that you agree with their attribution requirements. + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acled.api + url_git: +acledR: + version: 0.1.0 + title: Manipulate ACLED Data + maintainer: Trey Billing + description: Tools working with data from ACLED (Armed Conflict Location and Event + Data). Functions include simplified access to ACLED's API (), + methods for keeping local versions of ACLED data up-to-date, and functions for + common ACLED data transformations. + date_publication: '2025-02-24' + bug_reports: https://github.com/dtacled/acledR/issues + url: https://dtacled.github.io/acledR/ + url_cran: https://CRAN.R-project.org/package=acledR + url_git: '' +ACNE: + version: 0.9.1 + title: |- + Affymetrix SNP Probe-Summarization using Non-Negative Matrix + Factorization + maintainer: Henrik Bengtsson + description: A summarization method to estimate allele-specific copy number signals + for Affymetrix SNP microarrays using non-negative matrix factorization (NMF). + date_publication: '2024-02-17' + bug_reports: https://github.com/HenrikBengtsson/ACNE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ACNE + url_git: https://github.com/HenrikBengtsson/ACNE +acnr: + version: 1.0.0 + title: Annotated Copy-Number Regions + maintainer: Morgane Pierre-Jean + description: |- + Provides SNP array data from different types of + copy-number regions. These regions were identified manually by the authors + of the package and may be used to generate realistic data sets with known + truth. + date_publication: '2017-04-18' + bug_reports: https://github.com/mpierrejean/acnr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=acnr + url_git: https://github.com/mpierrejean/acnr +acopula: + version: 0.9.4 + title: |- + Modelling Dependence with Multivariate Archimax (or any + User-Defined Continuous) Copulas + maintainer: Tomas Bacigal + description: Archimax copulas are mixture of Archimedean and EV copulas. The package + provides definitions of several parametric families of generator and dependence + function, computes CDF and PDF, estimates parameters, tests for goodness of fit, + generates random sample and checks copula properties for custom constructs. In + 2-dimensional case explicit formulas for density are used, contrary to higher + dimensions when all derivatives are linearly approximated. Several non-archimax + families (normal, FGM, Plackett) are provided as well. + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acopula + url_git: '' +acoRn: + version: 0.1.0 + title: |- + Exclusion-Based Parentage Assignment Using Multilocus Genotype + Data + maintainer: Nikos Pechlivanis + description: 'Exclusion-based parentage assignment is essential for studies in biodiversity + conservation and breeding programs - Kang Huang, Rui Mi, Derek W Dunn, Tongcheng + Wang, Baoguo Li, (2018), . The tool compares + multilocus genotype data of potential parents and offspring, identifying likely + parentage relationships while accounting for genotyping errors, missing data, + and duplicate genotypes. ''acoRn'' includes two algorithms: one generates synthetic + genotype data based on user-defined parameters, while the other analyzes existing + genotype data to identify parentage patterns. The package is versatile, applicable + to diverse organisms, and offers clear visual outputs, making it a valuable resource + for researchers.' + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acoRn + url_git: '' +AcousticNDLCodeR: + version: 1.0.2 + title: Coding Sound Files for Use with NDL + maintainer: Denis Arnold + description: |- + Make acoustic cues to use with the R packages 'ndl' or 'ndl2'. The package implements functions used + in the PLoS ONE paper: + Denis Arnold, Fabian Tomaschek, Konstantin Sering, Florence Lopez, and R. Harald Baayen (2017). + Words from spontaneous conversational speech can be recognized with human-like accuracy by + an error-driven learning algorithm that discriminates between meanings straight from smart + acoustic features, bypassing the phoneme as recognition unit. PLoS ONE 12(4):e0174623 + + More details can be found in the paper and the supplement. + 'ndl' is available on CRAN. 'ndl2' is available by request from . + date_publication: '2018-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AcousticNDLCodeR + url_git: '' +acp: + version: '2.1' + title: Autoregressive Conditional Poisson + maintainer: Siakoulis Vasilios + description: Analysis of count data exhibiting autoregressive properties, using + the Autoregressive Conditional Poisson model (ACP(p,q)) proposed by Heinen (2003). + date_publication: '2015-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acp + url_git: '' +acro: + version: 0.1.4 + title: |- + A Tool for Semi-Automating the Statistical Disclosure Control of + Research Outputs + maintainer: Jim Smith + description: Assists researchers and output checkers by distinguishing between research + output that is safe to publish, output that requires further analysis, and output + that cannot be published because of substantial disclosure risk. A paper about + the tool was presented at the UNECE Expert Meeting on Statistical Data Confidentiality + 2023; see . + date_publication: '2025-01-29' + bug_reports: https://github.com/AI-SDC/ACRO-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=acro + url_git: https://github.com/AI-SDC/ACRO-R +acroname: + version: 0.1.0 + title: Engine for Acronyms and Initialisms + maintainer: VP Nagraj + description: A tool for generating acronyms and initialisms from arbitrary text + input. + date_publication: '2021-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=acroname + url_git: '' +AcrossTic: + version: 1.0-3 + title: A Cost-Minimal Regular Spanning Subgraph with TreeClust + maintainer: Sam Buttrey + description: |- + Construct minimum-cost regular spanning subgraph as part of a + non-parametric two-sample test for equality of distribution. + date_publication: '2016-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AcrossTic + url_git: '' +acss: + version: 0.2-5 + title: Algorithmic Complexity for Short Strings + maintainer: Henrik Singmann + description: 'Main functionality is to provide the algorithmic complexity forshort + strings, an approximation of the Kolmogorov Complexity of a shortstring + using the coding theorem method (see ?acss). The database containingthe + complexity is provided in the data only package acss.data, this packageprovides + functions accessing the data such as prob_random returning theposterior + probability that a given string was produced by a random process.In addition, + two traditional (but problematic) measures of complexity arealso provided: + entropy and change complexity.' + date_publication: '2014-11-25' + bug_reports: '' + url: http://complexitycalculator.com/methodology.html + url_cran: https://CRAN.R-project.org/package=acss + url_git: '' +acss.data: + version: '1.0' + title: 'Data Only: Algorithmic Complexity of Short Strings (Computed viaCoding + Theorem Method)' + maintainer: Henrik Singmann + description: Data only package providing the algorithmic complexity of short strings, + computed using the coding theorem method. For a given set of symbols in a string, + all possible or a large number of random samples of Turing machines (TM) with + a given number of states (e.g., 5) and number of symbols corresponding to the + number of symbols in the strings were simulated until they reached a halting state + or failed to end. This package contains data on 4.5 million strings from length + 1 to 12 simulated on TMs with 2, 4, 5, 6, and 9 symbols. The complexity of the + string corresponds to the distribution of the halting states of the TMs. + date_publication: '2014-04-05' + bug_reports: '' + url: http://complexitycalculator.com/methodology.html + url_cran: https://CRAN.R-project.org/package=acss.data + url_git: '' +ACSSpack: + version: 0.0.1.4 + title: ACSS, Corresponding ACSS, and GLP Algorithm + maintainer: Ziqian Yang + description: |- + Allow user to run the Adaptive Correlated Spike and Slab (ACSS) algorithm, corresponding INdependent Spike and Slab (INSS) algorithm, and Giannone, Lenza and Primiceri (GLP) algorithm with adaptive burn-in. + All of the three algorithms are used to fit high dimensional data set with either sparse structure, or dense structure with smaller contributions from all predictors. + The state-of-the-art GLP algorithm is in Giannone, D., Lenza, M., & Primiceri, G. E. (2021, ISBN:978-92-899-4542-4) + "Economic predictions with big data: The illusion of sparsity". + The two new algorithms, ACSS algorithm and INSS algorithm, and the discussion on their performance can be seen in + Yang, Z., Khare, K., & Michailidis, G. (2024, preprint) "Bayesian methodology for adaptive sparsity and shrinkage in regression". + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACSSpack + url_git: '' +ACSWR: + version: '1.0' + title: A Companion Package for the Book "A Course in Statistics with R" + maintainer: Prabhanjan Tattar + description: A book designed to meet the requirements of masters students. Tattar, + P.N., Suresh, R., and Manjunath, B.G. "A Course in Statistics with R", J. Wiley, + ISBN 978-1-119-15272-9. + date_publication: '2015-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACSWR + url_git: '' +act: + version: 1.3.1 + title: Aligned Corpus Toolkit + maintainer: Oliver Ehmer + description: The Aligned Corpus Toolkit (act) is designed for linguists that work + with time aligned transcription data. It offers functions to import and export + various annotation file formats ('ELAN' .eaf, 'EXMARaLDA .exb and 'Praat' .TextGrid + files), create print transcripts in the style of conversation analysis, search + transcripts (span searches across multiple annotations, search in normalized annotations, + make concordances etc.), export and re-import search results (.csv and 'Excel' + .xlsx format), create cuts for the search results (print transcripts, audio/video + cuts using 'FFmpeg' and video sub titles in 'Subrib title' .srt format), modify + the data in a corpus (search/replace, delete, filter etc.), interact with 'Praat' + using 'Praat'-scripts, and exchange data with the 'rPraat' package. The package + is itself written in R and may be expanded by other users. + date_publication: '2023-06-07' + bug_reports: '' + url: http://www.oliverehmer.de + url_cran: https://CRAN.R-project.org/package=act + url_git: https://github.com/oliverehmer/act +ACTCD: + version: 1.3-0 + title: Asymptotic Classification Theory for Cognitive Diagnosis + maintainer: Wenchao Ma + description: Cluster analysis for cognitive diagnosis based on the Asymptotic Classification + Theory (Chiu, Douglas & Li, 2009; ). Given the + sample statistic of sum-scores, cluster analysis techniques can be used to classify + examinees into latent classes based on their attribute patterns. In addition to + the algorithms used to classify data, three labeling approaches are proposed to + label clusters so that examinees' attribute profiles can be obtained. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACTCD + url_git: '' +ActCR: + version: 0.3.0 + title: Extract Circadian Rhythms Metrics from Actigraphy Data + maintainer: Junrui Di + description: Circadian rhythms are rhythms that oscillate about every 24 h, which + has been observed in multiple physiological processes including core body temperature, + hormone secretion, heart rate, blood pressure, and many others. Measuring circadian + rhythm with wearables is based on a principle that there is increased movement + during wake periods and reduced movement during sleep periods, and has been shown + to be reliable and valid. This package can be used to extract nonparametric circadian + metrics like intradaily variability (IV), interdaily stability (IS), and relative + amplitude (RA); and parametric cosinor model and extended cosinor model coefficient. + Details can be found in Junrui Di et al (2019) . + date_publication: '2022-05-11' + bug_reports: https://github.com/junruidi/ActCR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ActCR + url_git: https://github.com/junruidi/ActCR +actel: + version: 1.3.0 + title: Acoustic Telemetry Data Analysis + maintainer: Hugo Flávio + description: |- + Designed for studies where animals tagged with acoustic tags are expected + to move through receiver arrays. This package combines the advantages of automatic sorting and checking + of animal movements with the possibility for user intervention on tags that deviate from expected + behaviour. The three analysis functions (explore(), migration() and residency()) + allow the users to analyse their data in a systematic way, making it easy to compare results from + different studies. + CJS calculations are based on Perry et al. (2012) . + date_publication: '2023-10-19' + bug_reports: https://github.com/hugomflavio/actel/issues + url: https://hugomflavio.github.io/actel-website/ + url_cran: https://CRAN.R-project.org/package=actel + url_git: https://github.com/hugomflavio/actel +ActFrag: + version: 0.1.1 + title: |- + Activity Fragmentation Metrics Extracted from Minute Level + Activity Data + maintainer: Junrui Di + description: |- + Recent studies haven shown that, on top of total daily active/sedentary volumes, the time + accumulation strategies provide more sensitive information. This package provides functions to extract + commonly used fragmentation metrics to quantify such time accumulation strategies based on minute level + actigraphy-measured activity counts data. + date_publication: '2020-02-11' + bug_reports: https://github.com/junruidi/ActFrag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ActFrag + url_git: https://github.com/junruidi/ActFrag +actilifecounts: + version: 1.1.1 + title: Generate Activity Counts from Raw Accelerometer Data + maintainer: Jairo Hidalgo Migueles + description: |- + A tool to obtain activity counts, originally a translation of the + 'python' package 'agcounts' . This tool + allows the processing of data from any accelerometer brand, with a more flexible + approach to handle different sampling frequencies. + date_publication: '2023-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=actilifecounts + url_git: https://github.com/jhmigueles/actilifecounts +ActiSleep: + version: 0.2.2 + title: Sleep Duration Estimate Algorithm + maintainer: Nathan Szeto + description: |- + Provides sleep duration estimates using a Pruned Dynamic + Programming (PDP) algorithm that efficiently identifies + change-points. PDP applied to physical activity data can identify + transitions from wakefulness to sleep and vice versa. Baek, Jonggyu, Banker, + Margaret, Jansen, Erica C., She, Xichen, Peterson, Karen E., Pitchford, + E. Andrew, Song, Peter X. K. (2021) An Efficient Segmentation Algorithm to + Estimate Sleep Duration from Actigraphy Data . + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ActiSleep + url_git: '' +activAnalyzer: + version: 2.1.2 + title: |- + A 'Shiny' App to Analyze Accelerometer-Measured Daily Physical + Behavior Data + maintainer: Pierre-Yves de Müllenheim + description: |- + A tool to analyse 'ActiGraph' accelerometer data and to implement + the use of the PROactive Physical Activity in COPD (chronic obstructive pulmonary disease) instruments. Once analysis + is completed, the app allows to export results to .csv files and to generate + a report of the measurement. All the configured inputs relevant for interpreting + the results are recorded in the report. In addition to the existing 'R' packages + that are fully integrated with the app, the app uses some functions from the + 'actigraph.sleepr' package developed by Petkova (2021) . + date_publication: '2024-09-23' + bug_reports: https://github.com/pydemull/activAnalyzer/issues + url: https://pydemull.github.io/activAnalyzer/ + url_cran: https://CRAN.R-project.org/package=activAnalyzer + url_git: https://github.com/pydemull/activAnalyzer +activatr: + version: 0.2.1 + title: Utilities for Parsing and Plotting Activities + maintainer: Daniel Schafer + description: |- + This contains helpful functions for parsing, managing, plotting, and + visualizing activities, most often from GPX (GPS Exchange Format) files + recorded by GPS devices. It allows easy parsing of the source files into + standard R data formats, along with functions to compute derived data for + the activity, and to plot the activity in a variety of ways. + date_publication: '2024-07-27' + bug_reports: https://github.com/dschafer/activatr/issues + url: https://dschafer.github.io/activatr/ + url_cran: https://CRAN.R-project.org/package=activatr + url_git: https://github.com/dschafer/activatr +ActiveDriver: + version: 1.0.0 + title: |- + Finding Cancer Driver Proteins with Enriched Mutations in + Post-Translational Modification Sites + maintainer: Juri Reimand + description: 'A mutation analysis tool that discovers cancer driver genes with frequent + mutations in protein signalling sites such as post-translational modifications + (phosphorylation, ubiquitination, etc). The Poisson generalised linear regression + model identifies genes where cancer mutations in signalling sites are more frequent + than expected from the sequence of the entire gene. Integration of mutations with + signalling information helps find new driver genes and propose candidate mechanisms + to known drivers. Reference: Systematic analysis of somatic mutations in phosphorylation + signaling predicts novel cancer drivers. Juri Reimand and Gary D Bader. Molecular + Systems Biology (2013) 9:637 .' + date_publication: '2017-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ActiveDriver + url_git: '' +activegp: + version: 1.1.1 + title: |- + Gaussian Process Based Design and Analysis for the Active + Subspace Method + maintainer: Nathan Wycoff + description: The active subspace method is a sensitivity analysis technique that + finds important linear combinations of input variables for a simulator. This package + provides functions allowing estimation of the active subspace without gradient + information using Gaussian processes as well as sequential experimental design + tools to minimize the amount of data required to do so. Implements Wycoff et al. + (JCGS, 2021) . + date_publication: '2024-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=activegp + url_git: '' +ActivePathways: + version: 2.0.5 + title: |- + Integrative Pathway Enrichment Analysis of Multivariate Omics + Data + maintainer: Juri Reimand + description: 'Framework for analysing multiple omics datasets in the context of + molecular pathways, biological processes and other types of gene sets. The package + uses p-value merging to combine gene- or protein-level signals, followed by ranked + hypergeometric tests to determine enriched pathways and processes. Genes can be + integrated using directional constraints that reflect how the input datasets are + expected interact with one another. This approach allows researchers to interpret + a series of omics datasets in the context of known biology and gene function, + and discover associations that are only apparent when several datasets are combined. + The recent version of the package is part of the following publication: Directional + integration and pathway enrichment analysis for multi-omics data. Slobodyanyuk + M^, Bahcheli AT^, Klein ZP, Bayati M, Strug LJ, Reimand J. Nature Communications + (2024) .' + date_publication: '2024-07-28' + bug_reports: https://github.com/reimandlab/ActivePathways/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ActivePathways + url_git: '' +activity: + version: 1.3.4 + title: Animal Activity Statistics + maintainer: Marcus Rowcliffe + description: |- + Provides functions to express clock time data relative to + anchor points (typically solar); fit kernel density functions to animal + activity time data; plot activity distributions; quantify overall + levels of activity; statistically compare activity metrics through + bootstrapping; evaluate variation in linear variables with time (or + other circular variables). + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=activity + url_git: '' +ActivityIndex: + version: 0.3.7 + title: Activity Index Calculation using Raw 'Accelerometry' Data + maintainer: Jiawei Bai + description: |- + Reads raw 'accelerometry' from 'GT3X+' data and + plain table data to calculate Activity Index from 'Bai et al.' (2016) + . The Activity Index refers to the + square root of the second-level average variance of the three + 'accelerometry' axes. + date_publication: '2021-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ActivityIndex + url_git: '' +activPAL: + version: 0.1.3 + title: |- + Advanced Processing and Chart Generation from activPAL Events + Files + maintainer: Craig Speirs + description: |- + Contains functions to generate pre-defined summary statistics from activPAL + events files . The package also contains functions to produce informative + graphics that visualise physical activity behaviour and trends. This includes + generating graphs that align physical activity behaviour with additional time based + observations described by other data sets, such as sleep diaries and continuous glucose + monitoring data. + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=activPAL + url_git: '' +actLifer: + version: 1.0.0 + title: Creating Actuarial Life Tables + maintainer: Grace Rade + description: |- + Contains data and functions that can be used to make + actuarial life tables. Each function adds a column to the inputted dataset for + each intermediate calculation between mortality rate and life expectancy. Users can + run any of our functions to complete the life table until that step, or run + lifetable() to output a full life table that can be customized to remove optional columns. + Methods for creating lifetables are as described in Zedstatistics (2021) . + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=actLifer + url_git: https://github.com/g-rade/actLiferhttps://g-rade.github.io/actLifer/ +actogrammr: + version: 0.2.3 + title: Read in Activity Data and Plot Actograms + maintainer: Robert Corty + description: |- + Read in activity measurements from standard file formats + used by circadian rhythm researchers, currently only 'ClockLab' format, + and process and plot the data. The central type of plot is the actogram, + as first described by in "Activity and distribution of certain wild mice + in relation to biotic communities" by MS Johnson (1926) . + date_publication: '2017-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=actogrammr + url_git: '' +actuar: + version: 3.3-5 + title: Actuarial Functions and Heavy Tailed Distributions + maintainer: Vincent Goulet + description: |- + Functions and data sets for actuarial science: + modeling of loss distributions; risk theory and ruin theory; + simulation of compound models, discrete mixtures and compound + hierarchical models; credibility theory. Support for many additional + probability distributions to model insurance loss size and + frequency: 23 continuous heavy tailed distributions; the + Poisson-inverse Gaussian discrete distribution; zero-truncated and + zero-modified extensions of the standard discrete distributions. + Support for phase-type distributions commonly used to compute ruin + probabilities. Main reference: . + Implementation of the Feller-Pareto family of distributions: + . + date_publication: '2025-01-09' + bug_reports: https://gitlab.com/vigou3/actuar/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=actuar + url_git: https://gitlab.com/vigou3/actuar +actuaRE: + version: 0.1.5 + title: |- + Handling Hierarchically Structured Risk Factors using Random + Effects Models + maintainer: Campo Bavo D.C. + description: Using this package, you can fit a random effects model using either + the hierarchical credibility model, a combination of the hierarchical credibility + model with a generalized linear model or a Tweedie generalized linear mixed model. + See Campo, B.D.C. and Antonio, K. (2023) . + date_publication: '2023-03-20' + bug_reports: '' + url: https://bavodc.github.io/websiteactuaRE/ + url_cran: https://CRAN.R-project.org/package=actuaRE + url_git: '' +ActuarialM: + version: 0.1.0 + title: Computation of Actuarial Measures Using Bell G Family + maintainer: Muhammad Imran + description: |- + It computes two frequently applied actuarial measures, the expected shortfall and the value at risk. Seven well-known classical distributions in connection to the Bell generalized family are used as follows: Bell-exponential distribution, Bell-extended exponential distribution, Bell-Weibull distribution, Bell-extended Weibull distribution, Bell-Lomax distribution, Bell-Burr-12 distribution, and Bell-Burr-X distribution. Related works include: + a) Fayomi, A., Tahir, M. H., Algarni, A., Imran, M., & Jamal, F. (2022). "A new useful exponential model with applications to quality control and + actuarial data". Computational Intelligence and Neuroscience, 2022. . + b) Alsadat, N., Imran, M., Tahir, M. H., Jamal, F., Ahmad, H., & Elgarhy, M. (2023). "Compounded Bell-G class of statistical models with applications to COVID-19 and actuarial data". Open Physics, 21(1), 20220242. . + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ActuarialM + url_git: '' +actuaryr: + version: 1.1.1 + title: Develop Actuarial Models + maintainer: Zuzanna Chmielewska + description: |- + Actuarial reports are prepared for the last day of a specific + period, such as a month, a quarter or a year. Actuarial models assume that + certain events happen at the beginning or end of periods. The package + contains functions to easily refer to the first or last (working) day + within a specific period relative to a base date to facilitate actuarial + reporting and to compare results. + date_publication: '2020-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=actuaryr + url_git: '' +actxps: + version: 1.6.0 + title: |- + Create Actuarial Experience Studies: Prepare Data, Summarize + Results, and Create Reports + maintainer: Matt Heaphy + description: |- + Experience studies are used by actuaries to explore historical + experience across blocks of business and to inform assumption setting + activities. This package provides functions for preparing data, creating + studies, visualizing results, and beginning assumption development. + Experience study methods, including exposure calculations, are described in: + Atkinson & McGarry (2016) "Experience Study Calculations" + . + The limited fluctuation credibility method used by the 'exp_stats()' + function is described in: Herzog (1999, ISBN:1-56698-374-6) + "Introduction to Credibility Theory". + date_publication: '2025-01-07' + bug_reports: https://github.com/mattheaphy/actxps/issues + url: https://mattheaphy.github.io/actxps/ + url_cran: https://CRAN.R-project.org/package=actxps + url_git: https://github.com/mattheaphy/actxps/ +AcuityView: + version: '0.1' + title: |- + A Package for Displaying Visual Scenes as They May Appear to an + Animal with Lower Acuity + maintainer: Eleanor Caves + description: This code provides a simple method for representing a visual scene + as it may be seen by an animal with less acute vision. When using (or for more + information), please cite the original publication. + date_publication: '2017-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AcuityView + url_git: '' +acumos: + version: 0.4-4 + title: '''Acumos'' R Interface' + maintainer: Alassane Samba + description: |- + Create, upload and run 'Acumos' R models. + 'Acumos' () is a platform and open source framework intended to make it easy to build, + share, and deploy AI apps. 'Acumos' is part of the 'LF AI Foundation', an umbrella + organization within 'The Linux Foundation'. With this package, user can create a + component, and push it to an 'Acumos' platform. + date_publication: '2021-07-02' + bug_reports: https://jira.acumos.org/projects/ACUMOS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=acumos + url_git: https://www.acumos.org(Acumosprojectwebsite)https://gerrit.acumos.org/r/gitweb?p=acumos-r-client.git(coderepository)https://github.com/acumos/acumos-r-client(mirrorrepository)https://docs.acumos.org/en/latest/submodules/acumos-r-client/docs(docs) +ACV: + version: 1.0.2 + title: |- + Optimal Out-of-Sample Forecast Evaluation and Testing under + Stationarity + maintainer: Filip Stanek + description: Package 'ACV' (short for Affine Cross-Validation) offers an improved + time-series cross-validation loss estimator which utilizes both in-sample and + out-of-sample forecasting performance via a carefully constructed affine weighting + scheme. Under the assumption of stationarity, the estimator is the best linear + unbiased estimator of the out-of-sample loss. Besides that, the package also offers + improved versions of Diebold-Mariano and Ibragimov-Muller tests of equal predictive + ability which deliver more power relative to their conventional counterparts. + For more information, see the accompanying article Stanek (2021) . + date_publication: '2022-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ACV + url_git: '' +ACWR: + version: 0.1.0 + title: Acute Chronic Workload Ratio Calculation + maintainer: Jorge R Fernandez-Santos + description: |- + Functions for calculating the acute chronic workload ratio using three + different methods: exponentially weighted moving average (EWMA), rolling + average coupled (RAC) and rolling averaged uncoupled (RAU). Examples of this + methods can be found in Williams et al. (2017) + for EWMA and Windt & Gabbet (2018) for RAC and RAU . + date_publication: '2022-03-01' + bug_reports: https://github.com/JorgeDelro/ACWR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ACWR + url_git: https://github.com/JorgeDelro/ACWR +ada: + version: 2.0-5 + title: The R Package Ada for Stochastic Boosting + maintainer: Mark Culp + description: |- + Performs discrete, real, and gentle boost under both exponential and + logistic loss on a given data set. The package ada provides a straightforward, + well-documented, and broad boosting routine for classification, ideally suited + for small to moderate-sized data sets. + date_publication: '2016-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ada + url_git: '' +adabag: + version: '5.0' + title: Applies Multiclass AdaBoost.M1, SAMME and Bagging + maintainer: Esteban Alfaro + description: |- + It implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging + algorithm using classification trees as individual classifiers. Once these classifiers have been + trained, they can be used to predict on new data. Also, cross validation estimation of the error can + be done. Since version 2.0 the function margins() is available to calculate the margins for these + classifiers. Also a higher flexibility is achieved giving access to the rpart.control() argument + of 'rpart'. Four important new features were introduced on version 3.0, AdaBoost-SAMME (Zhu + et al., 2009) is implemented and a new function errorevol() shows the error of the ensembles as + a function of the number of iterations. In addition, the ensembles can be pruned using the option + 'newmfinal' in the predict.bagging() and predict.boosting() functions and the posterior probability of + each class for observations can be obtained. Version 3.1 modifies the relative importance measure + to take into account the gain of the Gini index given by a variable in each tree and the weights of + these trees. Version 4.0 includes the margin-based ordered aggregation for Bagging pruning (Guo + and Boukir, 2013) and a function to auto prune the 'rpart' tree. Moreover, three new plots are also + available importanceplot(), plot.errorevol() and plot.margins(). Version 4.1 allows to predict on + unlabeled data. Version 4.2 includes the parallel computation option for some of the functions. + Version 5.0 includes the Boosting and Bagging algorithms for label ranking (Albano, Sciandra + and Plaia, 2023). + date_publication: '2023-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adabag + url_git: '' +adace: + version: 1.0.2 + title: Estimator of the Adherer Average Causal Effect + maintainer: Run Zhuang + description: |- + Estimate the causal treatment effect for subjects that can adhere + to one or both of the treatments. Given longitudinal data with missing + observations, consistent causal effects are calculated. Unobserved potential + outcomes are estimated through direct integration as described in: + Qu et al., (2019) and + Zhang et. al., (2021) . + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adace + url_git: '' +adagio: + version: 0.9.2 + title: Discrete and Global Optimization Routines + maintainer: Hans W. Borchers + description: |2- + + The R package 'adagio' will provide methods and algorithms for + (discrete) optimization, e.g. knapsack and subset sum procedures, + derivative-free Nelder-Mead and Hooke-Jeeves minimization, and + some (evolutionary) global optimization functions. + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adagio + url_git: '' +adaHuber: + version: '1.1' + title: Adaptive Huber Estimation and Regression + maintainer: Xiaoou Pan + description: Huber-type estimation for mean, covariance and (regularized) regression. + For all the methods, the robustification parameter tau is chosen by a tuning-free + principle. + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adaHuber + url_git: https://github.com/XiaoouPan/adaHuber +adamethods: + version: 1.2.1 + title: Archetypoid Algorithms and Anomaly Detection + maintainer: Guillermo Vinue + description: |- + Collection of several algorithms to obtain archetypoids with small and large databases, and with both classical + multivariate data and functional data (univariate and multivariate). Some of these algorithms also allow to detect + anomalies (outliers). Please see Vinue and Epifanio (2020) . + date_publication: '2020-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adamethods + url_git: '' +adana: + version: 1.1.0 + title: |- + Adaptive Nature-Inspired Algorithms for Hybrid Genetic + Optimization + maintainer: Erkut Tekeli + description: 'The Genetic Algorithm (GA) is a type of optimization method of Evolutionary + Algorithms. It uses the biologically inspired operators such as mutation, crossover, + selection and replacement.Because of their global search and robustness abilities, + GAs have been widely utilized in machine learning, expert systems, data science, + engineering, life sciences and many other areas of research and business. However, + the regular GAs need the techniques to improve their efficiency in computing time + and performance in finding global optimum using some adaptation and hybridization + strategies. The adaptive GAs (AGA) increase the convergence speed and success + of regular GAs by setting the parameters crossover and mutation probabilities + dynamically. The hybrid GAs combine the exploration strength of a stochastic GAs + with the exact convergence ability of any type of deterministic local search algorithms + such as simulated-annealing, in addition to other nature-inspired algorithms such + as ant colony optimization, particle swarm optimization etc. The package ''adana'' + includes a rich working environment with its many functions that make possible + to build and work regular GA, adaptive GA, hybrid GA and hybrid adaptive GA for + any kind of optimization problems. Cebeci, Z. (2021, ISBN: 9786254397448).' + date_publication: '2022-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adana + url_git: '' +AdapSamp: + version: 1.1.1 + title: Adaptive Sampling Algorithms + maintainer: Dong Zhang + description: 'For distributions whose probability density functions are log-concave, + the adaptive rejection sampling algorithm can be used to build envelope functions + for sampling. For others, we can use the modified adaptive rejection sampling + algorithm, the concave-convex adaptive rejection sampling algorithm and the adaptive + slice sampling algorithm. So we designed an R package mainly including 4 functions: + rARS(), rMARS(), rCCARS() and rASS(). These functions can realize sampling based + on the algorithms above.' + date_publication: '2018-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdapSamp + url_git: '' +adapt4pv: + version: 0.2-3 + title: Adaptive Approaches for Signal Detection in Pharmacovigilance + maintainer: Emeline Courtois + description: A collection of several pharmacovigilance signal detection methods + based on adaptive lasso. Additional lasso-based and propensity score-based signal + detection approaches are also supplied. See Courtois et al . + date_publication: '2023-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adapt4pv + url_git: '' +adaptalint: + version: 0.2.4 + title: Check Code Style Painlessly + maintainer: Max Conway + description: |- + Infer the code style (which style rules are followed and which ones are + not) from one package and use it to check another. This makes it easier to + find and correct the most important problems first. + date_publication: '2019-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adaptalint + url_git: '' +adaptDiag: + version: 0.1.0 + title: Bayesian Adaptive Designs for Diagnostic Trials + maintainer: Graeme L. Hickey + description: |- + Simulate clinical trials for diagnostic test devices and evaluate + the operating characteristics under an adaptive design with futility + assessment determined via the posterior predictive probabilities. + date_publication: '2021-08-17' + bug_reports: https://github.com/graemeleehickey/adaptDiag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adaptDiag + url_git: https://github.com/graemeleehickey/adaptDiag +AdaptGauss: + version: '1.6' + title: Gaussian Mixture Models (GMM) + maintainer: Michael Thrun + description: Multimodal distributions can be modelled as a mixture of components. + The model is derived using the Pareto Density Estimation (PDE) for an estimation + of the pdf. PDE has been designed in particular to identify groups/classes in + a dataset. Precise limits for the classes can be calculated using the theorem + of Bayes. Verification of the model is possible by QQ plot, Chi-squared test and + Kolmogorov-Smirnov test. The package is based on the publication of Ultsch, A., + Thrun, M.C., Hansen-Goos, O., Lotsch, J. (2015) . + date_publication: '2024-02-02' + bug_reports: https://github.com/Mthrun/AdaptGauss/issues + url: https://www.deepbionics.org + url_cran: https://CRAN.R-project.org/package=AdaptGauss + url_git: '' +adaptiveGPCA: + version: 0.1.3 + title: Adaptive Generalized PCA + maintainer: Julia Fukuyama + description: |- + Implements adaptive gPCA, as described in: Fukuyama, J. (2017) + . The package also includes functionality for applying + the method to 'phyloseq' objects so that the method can be easily applied + to microbiome data and a 'shiny' app for interactive visualization. + date_publication: '2022-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adaptiveGPCA + url_git: '' +adaptivetau: + version: 2.3-2 + title: Tau-Leaping Stochastic Simulation + maintainer: Philip Johnson + description: |- + Implements adaptive tau leaping to approximate the + trajectory of a continuous-time stochastic process as + described by Cao et al. (2007) The Journal of Chemical Physics + (aka. the Gillespie stochastic + simulation algorithm). This package is based upon work + supported by NSF DBI-0906041 and NIH K99-GM104158 to Philip + Johnson and NIH R01-AI049334 to Rustom Antia. + date_publication: '2024-10-24' + bug_reports: https://github.com/plfjohnson/adaptivetau/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adaptivetau + url_git: https://github.com/plfjohnson/adaptivetau +adaptIVPT: + version: 1.1.0 + title: Adaptive Bioequivalence Design for In-Vitro Permeation Tests + maintainer: Daeyoung Lim + description: Contains functions carrying out adaptive procedures using mixed scaling + approach to establish bioequivalence for in-vitro permeation test (IVPT) data. + Currently, the package provides procedures based on parallel replicate design + and balanced data, according to the U.S. Food and Drug Administration's "Draft + Guidance on Acyclovir" . + Potvin et al. (2008) provides the basis for our adaptive + design (see Method B). For a comprehensive overview of the method, refer to Lim + et al. (2023) . This package reflects the views of the authors + and should not be construed to represent the views or policies of the U.S. Food + and Drug Administration. + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adaptIVPT + url_git: '' +adaptMCMC: + version: '1.5' + title: |- + Implementation of a Generic Adaptive Monte Carlo Markov Chain + Sampler + maintainer: Andreas Scheidegger + description: Enables sampling from arbitrary distributions if the log density is + known up to a constant; a common situation in the context of Bayesian inference. + The implemented sampling algorithm was proposed by Vihola (2012) + and achieves often a high efficiency by tuning the proposal distributions to a + user defined acceptance rate. + date_publication: '2024-01-29' + bug_reports: https://github.com/scheidan/adaptMCMC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adaptMCMC + url_git: https://github.com/scheidan/adaptMCMC +adaptMT: + version: 1.0.0 + title: |- + Adaptive P-Value Thresholding for Multiple Hypothesis Testing + with Side Information + maintainer: Lihua Lei + description: |- + Implementation of adaptive p-value thresholding (AdaPT), including both a framework that allows the user to specify any + algorithm to learn local false discovery rate and a pool of convenient functions that implement specific + algorithms. See Lei, Lihua and Fithian, William (2016) . + date_publication: '2018-07-31' + bug_reports: https://github.com/lihualei71/adaptMT/issues + url: https://arxiv.org/abs/1609.06035 + url_cran: https://CRAN.R-project.org/package=adaptMT + url_git: https://github.com/lihualei71/adaptMT +adaptr: + version: 1.4.0 + title: Adaptive Trial Simulator + maintainer: Anders Granholm + description: |- + Package that simulates adaptive (multi-arm, multi-stage) clinical + trials using adaptive stopping, adaptive arm dropping, and/or adaptive + randomisation. Developed as part of the INCEPT (Intensive Care Platform + Trial) project (), primarily supported by a grant + from Sygeforsikringen "danmark" (). + date_publication: '2024-05-03' + bug_reports: https://github.com/INCEPTdk/adaptr/issues/ + url: https://inceptdk.github.io/adaptr/ + url_cran: https://CRAN.R-project.org/package=adaptr + url_git: https://github.com/INCEPTdk/adaptr/ +ADAPTS: + version: 1.0.22 + title: |- + Automated Deconvolution Augmentation of Profiles for Tissue + Specific Cells + maintainer: Samuel A Danziger + description: |- + Tools to construct (or add to) cell-type signature matrices using flow sorted or single cell samples and deconvolve bulk gene expression data. + Useful for assessing the quality of single cell RNAseq experiments, estimating the accuracy of signature matrices, and determining cell-type spillover. + Please cite: Danziger SA et al. (2019) ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells . + date_publication: '2022-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADAPTS + url_git: '' +adaptsmoFMRI: + version: '1.2' + title: Adaptive Smoothing of FMRI Data + maintainer: Maximilian Hughes + description: |- + Adaptive smoothing functions for estimating the blood + oxygenation level dependent (BOLD) effect by using functional Magnetic + Resonance Imaging (fMRI) data, based on adaptive Gauss Markov random + fields, for real as well as simulated data. The implemented models make + use of efficient Markov Chain Monte Carlo methods. Implemented methods + are based on the research developed by A. Brezger, L. Fahrmeir, A. + Hennerfeind (2007) . + date_publication: '2022-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adaptsmoFMRI + url_git: '' +adaptTest: + version: '1.2' + title: Adaptive Two-Stage Tests + maintainer: Marc Vandemeulebroecke + description: |- + The functions defined in this program serve for implementing adaptive + two-stage tests. Currently, four tests are included: Bauer and Koehne (1994), + Lehmacher and Wassmer (1999), Vandemeulebroecke (2006), and the horizontal conditional + error function. User-defined tests can also be implemented. Reference: Vandemeulebroecke, + An investigation of two-stage tests, Statistica Sinica 2006. + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adaptTest + url_git: '' +adaR: + version: 0.3.4 + title: A Fast 'WHATWG' Compliant URL Parser + maintainer: David Schoch + description: A wrapper for 'ada-url', a 'WHATWG' compliant and fast URL parser written + in modern 'C++'. Also contains auxiliary functions such as a public suffix extractor. + date_publication: '2025-01-16' + bug_reports: https://github.com/gesistsa/adaR/issues + url: https://gesistsa.github.io/adaR/ + url_cran: https://CRAN.R-project.org/package=adaR + url_git: https://github.com/gesistsa/adaR +adas.utils: + version: 1.0.0 + title: Design of Experiments and Factorial Plans Utilities + maintainer: Paolo Bosetti + description: A number of functions to create and analyze factorial plans according + to the Design of Experiments (DoE) approach, with the addition of some utility + function to perform some statistical analyses. DoE approach follows the approach + in "Design and Analysis of Experiments" by Douglas C. Montgomery (2019, ISBN:978-1-119-49244-3). + The package also provides utilities used in the course "Analysis of Data and Statistics" + at the University of Trento, Italy. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adas.utils + url_git: '' +AdaSampling: + version: '1.3' + title: |- + Adaptive Sampling for Positive Unlabeled and Label Noise + Learning + maintainer: Pengyi Yang + description: Implements the adaptive sampling procedure, a framework for both positive + unlabeled learning and learning with class label noise. Yang, P., Ormerod, J., + Liu, W., Ma, C., Zomaya, A., Yang, J. (2018) . + date_publication: '2019-05-21' + bug_reports: https://github.com/PengyiYang/AdaSampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AdaSampling + url_git: https://github.com/PengyiYang/AdaSampling/ +adass: + version: 1.0.1 + title: |- + Adaptive Smoothing Spline (AdaSS) Estimator for the + Function-on-Function Linear Regression + maintainer: Fabio Centofanti + description: Implements the adaptive smoothing spline estimator for the function-on-function + linear regression model described in Centofanti et al. (2023) . + date_publication: '2024-07-18' + bug_reports: https://github.com/unina-sfere/adass + url: '' + url_cran: https://CRAN.R-project.org/package=adass + url_git: https://github.com/unina-sfere/adass +adbcdrivermanager: + version: 0.16.0 + title: '''Arrow'' Database Connectivity (''ADBC'') Driver Manager' + maintainer: Dewey Dunnington + description: |- + Provides a developer-facing interface to 'Arrow' Database + Connectivity ('ADBC') for the purposes of driver development, driver + testing, and building high-level database interfaces for users. 'ADBC' + is an API standard for database access + libraries that uses 'Arrow' for result sets and query parameters. + date_publication: '2025-01-22' + bug_reports: https://github.com/apache/arrow-adbc/issues + url: https://arrow.apache.org/adbc/current/r/adbcdrivermanager/ + url_cran: https://CRAN.R-project.org/package=adbcdrivermanager + url_git: https://github.com/apache/arrow-adbc +adbcpostgresql: + version: 0.16.0 + title: '''Arrow'' Database Connectivity (''ADBC'') ''PostgreSQL'' Driver' + maintainer: Dewey Dunnington + description: |- + Provides a developer-facing interface to the 'Arrow' Database + Connectivity ('ADBC') 'PostgreSQL' driver for the purposes of building high-level + database interfaces for users. 'ADBC' is + an API standard for database access libraries that uses 'Arrow' for result + sets and query parameters. + date_publication: '2025-01-22' + bug_reports: https://github.com/apache/arrow-adbc/issues + url: https://arrow.apache.org/adbc/current/r/adbcpostgresql/ + url_cran: https://CRAN.R-project.org/package=adbcpostgresql + url_git: https://github.com/apache/arrow-adbc +adbcsqlite: + version: 0.16.0 + title: '''Arrow'' Database Connectivity (''ADBC'') ''SQLite'' Driver' + maintainer: Dewey Dunnington + description: |- + Provides a developer-facing interface to the 'Arrow' Database + Connectivity ('ADBC') 'SQLite' driver for the purposes of building high-level + database interfaces for users. 'ADBC' is + an API standard for database access libraries that uses 'Arrow' for result + sets and query parameters. + date_publication: '2025-01-22' + bug_reports: https://github.com/apache/arrow-adbc/issues + url: https://arrow.apache.org/adbc/current/r/adbcsqlite/ + url_cran: https://CRAN.R-project.org/package=adbcsqlite + url_git: https://github.com/apache/arrow-adbc +adbi: + version: 0.1.1 + title: '''DBI'' Compliant Database Access Using ''ADBC''' + maintainer: Nicolas Bennett + description: In order to make Arrow Database Connectivity ('ADBC' ) + accessible from R, an interface compliant with the 'DBI' package is provided, + using driver back-ends that are implemented in the 'adbcdrivermanager' framework. + This enables interacting with database systems using the Arrow data format, thereby + offering an efficient alternative to 'ODBC' for analytical applications. + date_publication: '2024-01-25' + bug_reports: https://github.com/r-dbi/adbi/issues + url: https://adbi.r-dbi.org + url_cran: https://CRAN.R-project.org/package=adbi + url_git: https://github.com/r-dbi/adbi +adc: + version: 1.0.0 + title: Calculate Antecedent Discharge Conditions + maintainer: Michael Schramm + description: |- + Calculates some antecedent discharge conditions useful in + water quality modeling. Includes methods for calculating flow + anomalies, base flow, and smooth discounted flows from daily flow + measurements. Antecedent discharge algorithms are described and + reviewed in Zhang and Ball (2017) . + date_publication: '2023-02-17' + bug_reports: https://github.com/TxWRI/adc/issues + url: https://txwri.github.io/adc/ + url_cran: https://CRAN.R-project.org/package=adc + url_git: https://github.com/TxWRI/adc +ADCT: + version: 0.1.0 + title: Adaptive Design in Clinical Trials + maintainer: Yalin Zhu + description: |- + Existing adaptive design methods in clinical trials. The package + includes power, stopping boundaries (sample size) calculation functions for + two-group group sequential designs, adaptive design with coprimary endpoints, + biomarker-informed adaptive design, etc. + date_publication: '2016-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADCT + url_git: '' +add2ggplot: + version: 0.3.0 + title: Add to 'ggplot2' + maintainer: Jiaxiang Li + description: Create 'ggplot2' themes and color palettes. + date_publication: '2020-02-07' + bug_reports: https://github.com/JiaxiangBU/add2ggplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=add2ggplot + url_git: https://github.com/JiaxiangBU/add2ggplot +addhaz: + version: '0.5' + title: Binomial and Multinomial Additive Hazard Models + maintainer: Renata T C Yokota + description: Functions to fit the binomial and multinomial additive hazard models + and to estimate the contribution of diseases/conditions to the disability prevalence, + as proposed by Nusselder and Looman (2004) and extended by Yokota et al (2017). + date_publication: '2018-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=addhaz + url_git: '' +addhazard: + version: 1.1.0 + title: Fit Additive Hazards Models for Survival Analysis + maintainer: Jie (Kate) Hu + description: |- + Contains tools to fit the additive hazards model to data from a cohort, + random sampling, two-phase Bernoulli sampling and two-phase finite population sampling, + as well as calibration tool to incorporate phase I auxiliary information into the + two-phase data model fitting. This package provides regression parameter estimates and + their model-based and robust standard errors. It also offers tools to make prediction of + individual specific hazards. + date_publication: '2017-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=addhazard + url_git: '' +addinsJoaoMelo: + version: 0.1.0 + title: Addins Made of Joao Melo + maintainer: Joao Melo + description: |- + Provide addins for 'RStudio'. + It currently contains 3 addins. The first to add a shortcut for the double pipe. The second is to add a shortcut for the same operator. And the third to simplify the creation of vectors from texts pasted from the computer transfer area. + date_publication: '2020-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=addinsJoaoMelo + url_git: '' +addinslist: + version: 0.5.0 + title: Discover and Install Useful RStudio Addins + maintainer: Dean Attali + description: |- + Browse through a continuously updated list of existing RStudio + addins and install/uninstall their corresponding packages. + date_publication: '2023-05-15' + bug_reports: https://github.com/daattali/addinslist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=addinslist + url_git: https://github.com/daattali/addinslist +addinsOutline: + version: 0.1.6 + title: |- + 'RStudio' Addins for Show Outline of a R Markdown/'LaTeX' + Project + maintainer: Pedro L. Luque-Calvo + description: |- + 'RStudio' allows to show and navigate for the outline of a + R Markdown file, but not for R Markdown projects with multiple + files. For this reason, I have developed several 'RStudio' addins capable + of show project outline. Each addin is specialized in showing projects + of different types: R Markdown project, 'bookdown' package project + and 'LaTeX' project. There is a configuration file that allows you + to customize additional searches. + date_publication: '2019-12-02' + bug_reports: https://github.com/calote/addinsOutline/issues + url: '' + url_cran: https://CRAN.R-project.org/package=addinsOutline + url_git: https://github.com/calote/addinsOutline +additive: + version: 1.0.1 + title: Bindings for Additive TidyModels + maintainer: Hamada S. Badr + description: |- + Fit Generalized Additive Models (GAM) using 'mgcv' with 'parsnip'/'tidymodels' + via 'additive' . 'tidymodels' is a collection of + packages for machine learning; see Kuhn and Wickham (2020) ). + The technical details of 'mgcv' are described in Wood (2017) + . + date_publication: '2024-04-28' + bug_reports: https://github.com/hsbadr/additive/issues + url: https://hsbadr.github.io/additive/ + url_cran: https://CRAN.R-project.org/package=additive + url_git: https://github.com/hsbadr/additive +additivityTests: + version: 1.1-4.2 + title: |- + Additivity Tests in the Two Way Anova with Single Sub-Class + Numbers + maintainer: Petr Simecek + description: |- + Implementation of the Tukey, Mandel, Johnson-Graybill, LBI, Tusell + and modified Tukey non-additivity tests. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=additivityTests + url_git: https://github.com/simecek/additivityTests +addreg: + version: '3.0' + title: Additive Regression for Discrete Data + maintainer: Mark W. Donoghoe + description: |- + Methods for fitting identity-link GLMs and GAMs to discrete data, + using EM-type algorithms with more stable convergence properties than standard methods. + date_publication: '2017-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=addreg + url_git: https://github.com/mdonoghoe/addreg +addScales: + version: 1.0-1 + title: |- + Adds Labeled Center Line and Scale Lines/Regions to Trellis + Plots + maintainer: Bert Gunter + description: |- + Modifies trellis objects by adding horizontal and/or vertical + reference lines or shaded regions that provide visual scaling information. + This is mostly useful in multi-panel plots that use the relation = 'free' + option in their 'scales' argument list. + date_publication: '2020-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=addScales + url_git: '' +ADDT: + version: '2.0' + title: Analysis of Accelerated Destructive Degradation Test Data + maintainer: Yili Hong + description: Accelerated destructive degradation tests (ADDT) are often used to + collect necessary data for assessing the long-term properties of polymeric materials. + Based on the collected data, a thermal index (TI) is estimated. The TI can be + useful for material rating and comparison. This package implements the traditional + method based on the least-squares method, the parametric method based on maximum + likelihood estimation, and the semiparametric method based on spline methods, + and the corresponding methods for estimating TI for polymeric materials. The traditional + approach is a two-step approach that is currently used in industrial standards, + while the parametric method is widely used in the statistical literature. The + semiparametric method is newly developed. Both the parametric and semiparametric + approaches allow one to do statistical inference such as quantifying uncertainties + in estimation, hypothesis testing, and predictions. Publicly available datasets + are provided illustrations. More details can be found in Jin et al. (2017). + date_publication: '2016-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADDT + url_git: '' +ade4: + version: 1.7-23 + title: |- + Analysis of Ecological Data: Exploratory and Euclidean Methods + in Environmental Sciences + maintainer: Aurélie Siberchicot + description: Tools for multivariate data analysis. Several methods are provided + for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, + correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), + three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia + analysis). The philosophy of the package is described in Dray and Dufour (2007) + . + date_publication: '2025-02-14' + bug_reports: https://github.com/adeverse/ade4/issues + url: https://adeverse.github.io/ade4/ + url_cran: https://CRAN.R-project.org/package=ade4 + url_git: '' +ade4TkGUI: + version: 0.3-1 + title: '''ade4'' Tcl/Tk Graphical User Interface' + maintainer: Aurélie Siberchicot + description: A Tcl/Tk GUI for some basic functions in the 'ade4' package. + date_publication: '2020-12-03' + bug_reports: https://github.com/aursiber/ade4TkGUI/issues + url: http://pbil.univ-lyon1.fr/ade4TkGUI/ + url_cran: https://CRAN.R-project.org/package=ade4TkGUI + url_git: '' +adea: + version: 1.5.2 + title: Alternate DEA Package + maintainer: Manuel Munoz-Marquez + description: |- + The meaning of adea is "alternate DEA". This package is devoted to provide the alternative method of DEA described in the paper entitled "Stepwise Selection of Variables in DEA Using Contribution Load", by F. Fernandez-Palacin, M. A. Lopez-Sanchez and M. Munoz-Marquez. Pesquisa Operacional 38 (1), pg. 1-24, 2018. . + A full functional on-line and interactive version is available at + . + date_publication: '2024-11-12' + bug_reports: '' + url: http://knuth.uca.es/dea/ + url_cran: https://CRAN.R-project.org/package=adea + url_git: '' +adegenet: + version: 2.1.11 + title: Exploratory Analysis of Genetic and Genomic Data + maintainer: Zhian N. Kamvar + description: |- + Toolset for the exploration of genetic and genomic + data. Adegenet provides formal (S4) classes for storing and handling + various genetic data, including genetic markers with varying ploidy + and hierarchical population structure ('genind' class), alleles counts + by populations ('genpop'), and genome-wide SNP data ('genlight'). It + also implements original multivariate methods (DAPC, sPCA), graphics, + statistical tests, simulation tools, distance and similarity measures, + and several spatial methods. A range of both empirical and simulated + datasets is also provided to illustrate various methods. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adegenet + url_git: https://github.com/thibautjombart/adegenet +adegraphics: + version: 1.0-21 + title: |- + An S4 Lattice-Based Package for the Representation of + Multivariate Data + maintainer: Aurélie Siberchicot + description: Graphical functionalities for the representation of multivariate data. + It is a complete re-implementation of the functions available in the 'ade4' package. + date_publication: '2023-10-13' + bug_reports: https://github.com/sdray/adegraphics/issues + url: http://pbil.univ-lyon1.fr/ADE-4/ + url_cran: https://CRAN.R-project.org/package=adegraphics + url_git: '' +adehabitatHR: + version: 0.4.22 + title: Home Range Estimation + maintainer: Clement Calenge + description: A collection of tools for the estimation of animals home range. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adehabitatHR + url_git: '' +adehabitatHS: + version: 0.3.18 + title: Analysis of Habitat Selection by Animals + maintainer: Clement Calenge + description: A collection of tools for the analysis of habitat selection. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adehabitatHS + url_git: '' +adehabitatLT: + version: 0.3.28 + title: Analysis of Animal Movements + maintainer: Clement Calenge + description: A collection of tools for the analysis of animal movements. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adehabitatLT + url_git: '' +adehabitatMA: + version: 0.3.17 + title: Tools to Deal with Raster Maps + maintainer: Clement Calenge + description: A collection of tools to deal with raster maps. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adehabitatMA + url_git: '' +adelie: + version: 1.0.7 + title: Group Lasso and Elastic Net Solver for Generalized Linear Models + maintainer: Trevor Hastie + description: |- + Extremely efficient procedures for fitting the entire group lasso and group elastic net regularization path for GLMs, multinomial, the Cox model and multi-task Gaussian models. Similar to the R package 'glmnet' in scope of models, and in computational speed. This package provides R bindings to the C++ code underlying the corresponding Python package 'adelie'. These bindings offer a general purpose group elastic net solver, + a wide range of matrix classes that can exploit special structure + to allow large-scale inputs, and an assortment of + generalized linear model classes for fitting various types of data. + The package is an implementation of Yang, J. and Hastie, T. (2024) . + date_publication: '2025-02-28' + bug_reports: https://github.com/JamesYang007/adelie-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adelie + url_git: https://github.com/JamesYang007/adelie-r +adephylo: + version: 1.1-16 + title: Exploratory Analyses for the Phylogenetic Comparative Method + maintainer: Aurélie Siberchicot + description: Multivariate tools to analyze comparative data, i.e. a phylogeny and + some traits measured for each taxa. The package contains functions to represent + comparative data, compute phylogenetic proximities, perform multivariate analysis + with phylogenetic constraints and test for the presence of phylogenetic autocorrelation. + The package is described in Jombart et al (2010) . + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adephylo + url_git: '' +adepro: + version: 4.1.2 + title: |- + A 'shiny' Application for the (Audio-)Visualization of Adverse + Event Profiles + maintainer: Bodo Kirsch + description: Contains a 'shiny' application called AdEPro (Animation of Adverse + Event Profiles) which (audio-)visualizes adverse events occurring in clinical + trials. As this data is usually considered sensitive, this tool is provided as + a stand-alone application that can be launched from any local machine on which + the data is stored. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adepro + url_git: https://github.com/Bayer-Group/BIC-AdEPro +adept: + version: '1.2' + title: Adaptive Empirical Pattern Transformation + maintainer: Marta Karas + description: |- + Designed for optimal use in performing fast, + accurate walking strides segmentation from high-density + data collected from a wearable accelerometer worn + during continuous walking activity. + date_publication: '2021-02-01' + bug_reports: https://github.com/martakarass/adept/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adept + url_git: https://github.com/martakarass/adept +adeptdata: + version: '1.1' + title: Accelerometry Data Sets + maintainer: Marta Karas + description: Created to host raw accelerometry data sets and their derivatives which + are used in the corresponding 'adept' package. + date_publication: '2021-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adeptdata + url_git: '' +AdequacyModel: + version: 2.0.0 + title: |- + Adequacy of Probabilistic Models and General Purpose + Optimization + maintainer: Pedro Rafael Diniz Marinho + description: The main application concerns to a new robust optimization package + with two major contributions. The first contribution refers to the assessment + of the adequacy of probabilistic models through a combination of several statistics, + which measure the relative quality of statistical models for a given data set. + The second one provides a general purpose optimization method based on meta-heuristics + functions for maximizing or minimizing an arbitrary objective function. + date_publication: '2016-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdequacyModel + url_git: '' +ADER: + version: '1.5' + title: Data Analysis in Ecology + maintainer: Marcelino De la Cruz + description: Data sets used in Cayuela and De la Cruz (2022, ISBN:978-84-8476-833-3). + date_publication: '2024-01-09' + bug_reports: '' + url: https://www.paraninfo.es/catalogo/9788484768333/ + url_cran: https://CRAN.R-project.org/package=ADER + url_git: '' +adespatial: + version: 0.3-24 + title: Multivariate Multiscale Spatial Analysis + maintainer: Aurélie Siberchicot + description: |- + Tools for the multiscale spatial analysis of multivariate data. + Several methods are based on the use of a spatial weighting matrix and its + eigenvector decomposition (Moran's Eigenvectors Maps, MEM). + Several approaches are described in the review Dray et al (2012) + . + date_publication: '2024-09-06' + bug_reports: https://github.com/adeverse/adespatial/issues + url: http://adeverse.github.io/adespatial/ + url_cran: https://CRAN.R-project.org/package=adespatial + url_git: https://github.com/adeverse/adespatial +adestr: + version: 1.0.0 + title: Estimation in Optimal Adaptive Two-Stage Designs + maintainer: Jan Meis + description: |- + Methods to evaluate the performance characteristics of + various point and interval estimators for optimal adaptive two-stage designs as described + in Meis et al. (2024) . + Specifically, this package is written to work with trial designs created by the 'adoptr' package + (Kunzmann et al. (2021) ; Pilz et al. (2021) )). + Apart from the a priori evaluation of performance characteristics, this package also allows for the + evaluation of the implemented estimators on real datasets, and it implements methods + to calculate p-values. + date_publication: '2024-07-12' + bug_reports: '' + url: https://jan-imbi.github.io/adestr/ + url_cran: https://CRAN.R-project.org/package=adestr + url_git: '' +adfExplorer: + version: 2.0.3 + title: Access and Manipulate Amiga Disk Files + maintainer: Pepijn de Vries + description: |- + Amiga Disk Files (ADF) are virtual + representations of 3.5 inch floppy disks for the + Commodore Amiga. Most disk drives from other systems + (including modern drives) are not able to read these + disks. The 'adfExplorer' package enables you to + establish R connections to files on such + virtual DOS-formatted disks, which can be use to + read from and write to those files. + date_publication: '2025-01-10' + bug_reports: https://github.com/pepijn-devries/adfExplorer/issues + url: https://pepijn-devries.github.io/adfExplorer/ + url_cran: https://CRAN.R-project.org/package=adfExplorer + url_git: '' +adformR: + version: 0.1.0 + title: Get Adform Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Adform Ads using + the 'Windsor.ai' API . + date_publication: '2022-11-28' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=adformR + url_git: '' +ADGofTest: + version: '0.3' + title: Anderson-Darling GoF test + maintainer: Carlos J. Gil Bellosta + description: Anderson-Darling GoF test with p-value calculation based on Marsaglia's + 2004 paper "Evaluating the Anderson-Darling Distribution" + date_publication: '2011-12-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADGofTest + url_git: '' +adheRenceRX: + version: 1.0.0 + title: Assess Medication Adherence from Pharmaceutical Claims Data + maintainer: Brennan Beal + description: |- + A (mildly) opinionated set of functions to help assess medication adherence for researchers working with medication claims data. + Medication adherence analyses have several complex steps that are often convoluted and can be time-intensive. The focus is to create a + set of functions using "tidy principles" geared towards transparency, speed, and flexibility while working with adherence metrics. All functions perform exactly one task + with an intuitive name so that a researcher can handle details (often achieved with vectorized solutions) while we handle non-vectorized tasks common to most + adherence calculations such as adjusting fill dates and determining episodes of care. The methodologies in referenced in this package come from + Canfield SL, et al (2019) "Navigating the Wild West of Medication Adherence Reporting in Specialty Pharmacy" . + date_publication: '2020-11-20' + bug_reports: https://github.com/btbeal/adheRenceRX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adheRenceRX + url_git: https://github.com/btbeal/adheRenceRX +AdhereR: + version: 0.8.1 + title: Adherence to Medications + maintainer: Dan Dediu + description: |- + Computation of adherence to medications from Electronic Health care + Data and visualization of individual medication histories and adherence + patterns. The package implements a set of S3 classes and + functions consistent with current adherence guidelines and definitions. + It allows the computation of different measures of + adherence (as defined in the literature, but also several original ones), + their publication-quality plotting, + the estimation of event duration and time to initiation, + the interactive exploration of patient medication history and + the real-time estimation of adherence given various parameter settings. + It scales from very small datasets stored in flat CSV files to very large + databases and from single-thread processing on mid-range consumer + laptops to parallel processing on large heterogeneous computing clusters. + It exposes a standardized interface allowing it to be used from other + programming languages and platforms, such as Python. + date_publication: '2022-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdhereR + url_git: https://github.com/ddediu/AdhereR +AdhereRViz: + version: 0.2.1 + title: Adherence to Medications + maintainer: Dan Dediu + description: |- + Interactive graphical user interface (GUI) for the package + 'AdhereR', allowing the user to access different data sources, to explore + the patterns of medication use therein, and the computation of various + measures of adherence. It is implemented using Shiny and HTML/CSS/JavaScript. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdhereRViz + url_git: https://github.com/ddediu/AdhereR +adimpro: + version: 0.9.7.2 + title: Adaptive Smoothing of Digital Images + maintainer: Karsten Tabelow + description: |- + Implements tools for manipulation of digital + images and the Propagation Separation approach + by Polzehl and Spokoiny (2006) + for smoothing digital images, see Polzehl and Tabelow (2007) + . + date_publication: '2024-09-25' + bug_reports: '' + url: https://www.wias-berlin.de/software/imaging/ + url_cran: https://CRAN.R-project.org/package=adimpro + url_git: '' +AdIsMF: + version: 0.1.0 + title: Adsorption Isotherm Model Fitting + maintainer: Debopam Rakshit + description: The Langmuir and Freundlich adsorption isotherms are pivotal in characterizing + adsorption processes, essential across various scientific disciplines. Proper + interpretation of adsorption isotherms involves robust fitting of data to the + models, accurate estimation of parameters, and efficiency evaluation of the models, + both in linear and non-linear forms. For researchers and practitioners in the + fields of chemistry, environmental science, soil science, and engineering, a comprehensive + package that satisfies all these requirements would be ideal for accurate and + efficient analysis of adsorption data, precise model selection and validation + for rigorous scientific inquiry and real-world applications. Details can be found + in Langmuir (1918) and Giles (1973) . + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdIsMF + url_git: '' +adiv: + version: 2.2.1 + title: Analysis of Diversity + maintainer: Sandrine Pavoine + description: Functions, data sets and examples for the calculation of various indices + of biodiversity including species, functional and phylogenetic diversity. Part + of the indices are expressed in terms of equivalent numbers of species. The package + also provides ways to partition biodiversity across spatial or temporal scales + (alpha, beta, gamma diversities). In addition to the quantification of biodiversity, + ordination approaches are available which rely on diversity indices and allow + the detailed identification of species, functional or phylogenetic differences + between communities. + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adiv + url_git: '' +adjclust: + version: 0.6.10 + title: |- + Adjacency-Constrained Clustering of a Block-Diagonal Similarity + Matrix + maintainer: Pierre Neuvial + description: |- + Implements a constrained version of hierarchical agglomerative + clustering, in which each observation is associated to a position, and only + adjacent clusters can be merged. Typical application fields in + bioinformatics include Genome-Wide Association Studies or Hi-C data + analysis, where the similarity between items is a decreasing function of + their genomic distance. Taking advantage of this feature, the implemented + algorithm is time and memory efficient. This algorithm is described in + Ambroise et al (2019) . + date_publication: '2024-10-08' + bug_reports: https://github.com/pneuvial/adjclust/issues + url: https://pneuvial.github.io/adjclust/ + url_cran: https://CRAN.R-project.org/package=adjclust + url_git: '' +adjROC: + version: '0.3' + title: |- + Computing Sensitivity at a Fix Value of Specificity and Vice + Versa as Well as Bootstrap Metrics for ROC Curves + maintainer: E. F. Haghish + description: |- + For a binary classification the adjusted sensitivity and specificity + are measured for a given fixed threshold. If the threshold for either + sensitivity or specificity is not given, the crossing point between + the sensitivity and specificity curves are returned. For bootstrap + procedures, mean and CI bootstrap values of sensitivity, specificity, + crossing point between specificity and specificity as well as AUC + and AUCPR can be evaluated. + date_publication: '2023-01-25' + bug_reports: https://github.com/haghish/adjROC/issues + url: https://www.sv.uio.no/psi/english/people/aca/haghish/ + url_cran: https://CRAN.R-project.org/package=adjROC + url_git: https://github.com/haghish/adjROC +adjSURVCI: + version: '1.0' + title: |- + Parameter and Adjusted Probability Estimation for Right-Censored + Data + maintainer: Manoj Khanal + description: |- + Functions in this package fit a stratified Cox proportional hazards and a proportional subdistribution hazards model by extending Zhang et al., (2007) + and Zhang et al., (2011) respectively to clustered right-censored data. The functions also provide the estimates of the cumulative baseline hazard along with their standard errors. Furthermore, the adjusted survival and cumulative incidence probabilities are also provided along with their standard errors. Finally, the estimate of cumulative incidence and survival probabilities given a vector of covariates along with their standard errors are also provided. + date_publication: '2021-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adjSURVCI + url_git: '' +adjustedcranlogs: + version: 0.1.0 + title: |- + Remove Automated and Repeated Downloads from 'RStudio' 'CRAN' + Download Logs + maintainer: Tyler Morgan-Wall + description: Adjusts output of 'cranlogs' package to account for 'CRAN'-wide daily + automated downloads and re-downloads caused by package updates. + date_publication: '2017-11-23' + bug_reports: https://github.com/tylermorganwall/adjustedcranlogs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adjustedcranlogs + url_git: https://github.com/tylermorganwall/adjustedcranlogs +adjustedCurves: + version: 0.11.2 + title: |- + Confounder-Adjusted Survival Curves and Cumulative Incidence + Functions + maintainer: Robin Denz + description: |- + Estimate and plot confounder-adjusted survival curves using + either 'Direct Adjustment', 'Direct Adjustment with Pseudo-Values', + various forms of 'Inverse Probability of Treatment Weighting', two + forms of 'Augmented Inverse Probability of Treatment Weighting', + 'Empirical Likelihood Estimation' or 'Targeted Maximum Likelihood Estimation'. + Also includes a significance test for the difference + between two adjusted survival curves and the calculation of adjusted + restricted mean survival times. Additionally enables the user to + estimate and plot cause-specific confounder-adjusted cumulative + incidence functions in the competing risks setting using the same + methods (with some exceptions). + For details, see Denz et. al (2023) . + date_publication: '2024-07-29' + bug_reports: https://github.com/RobinDenz1/adjustedCurves/issues + url: https://robindenz1.github.io/adjustedCurves/ + url_cran: https://CRAN.R-project.org/package=adjustedCurves + url_git: https://github.com/RobinDenz1/adjustedCurves +adklakedata: + version: 0.6.1 + title: Adirondack Long-Term Lake Data + maintainer: Luke Winslow + description: |- + Package for the access and distribution of Long-term lake datasets from lakes in the + Adirondack Park, northern New York state. Includes a wide variety of physical, chemical, and + biological parameters from 28 lakes. Data are from multiple collection organizations and have + been harmonized in both time and space for ease of reuse. + date_publication: '2018-02-16' + bug_reports: https://github.com/lawinslow/adklakedata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adklakedata + url_git: '' +adlift: + version: 1.4-5 + title: An Adaptive Lifting Scheme Algorithm + maintainer: Matt Nunes + description: Adaptive wavelet lifting transforms for signal denoising using optimal + local neighbourhood regression, from Nunes et al. (2006) . + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adlift + url_git: '' +ADLP: + version: 0.1.0 + title: |- + Accident and Development Period Adjusted Linear Pools for + Actuarial Stochastic Reserving + maintainer: Yanfeng Li + description: |- + Loss reserving generally focuses on identifying a single model that can generate superior predictive performance. However, different loss reserving models specialise in capturing different aspects of loss data. + This is recognised in practice in the sense that results from different models are often considered, and sometimes combined. For instance, actuaries may take a weighted average of the prediction outcomes from + various loss reserving models, often based on subjective assessments. + This package allows for the use of a systematic framework to objectively combine (i.e. ensemble) multiple stochastic loss reserving models such that the strengths offered by different models can be utilised effectively. Our + framework is developed in Avanzi et al. (2023). Firstly, our criteria model combination considers the full distributional properties of the ensemble and not just the central + estimate - which is of particular importance in the reserving context. Secondly, our framework is that it is tailored for the features inherent to reserving data. These include, for instance, accident, development, + calendar, and claim maturity effects. Crucially, the relative importance and scarcity of data across accident periods renders the problem distinct from the traditional ensemble techniques in statistical learning. + Our framework is illustrated with a complex synthetic dataset. In the results, the optimised ensemble outperforms both (i) traditional model selection strategies, and (ii) an equally weighted ensemble. In + particular, the improvement occurs not only with central estimates but also relevant quantiles, such as the 75th percentile of reserves (typically of interest to both insurers and regulators). + Reference: Avanzi B, Li Y, Wong B, Xian A (2023) "Ensemble distributional forecasting for insurance loss reserving" . + date_publication: '2024-04-18' + bug_reports: https://github.com/agi-lab/ADLP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ADLP + url_git: https://github.com/agi-lab/ADLP +admiral: + version: 1.2.0 + title: ADaM in R Asset Library + maintainer: Ben Straub + description: |- + A toolbox for programming Clinical Data Interchange Standards + Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. + ADaM datasets are a mandatory part of any New Drug or Biologics + License Application submitted to the United States Food and Drug + Administration (FDA). Analysis derivations are implemented in + accordance with the "Analysis Data Model Implementation Guide" (CDISC + Analysis Data Model Team, 2021, + ). + date_publication: '2025-01-15' + bug_reports: https://github.com/pharmaverse/admiral/issues + url: https://pharmaverse.github.io/admiral/ + url_cran: https://CRAN.R-project.org/package=admiral + url_git: https://github.com/pharmaverse/admiral +admiral.test: + version: 0.7.0 + title: Test Data for the 'admiral' Package + maintainer: Ben Straub + description: |- + A set of Study Data Tabulation Model (SDTM) datasets from the Clinical + Data Interchange Standards Consortium (CDISC) pilot project used for testing + and developing Analysis Data Model (ADaM) derivations inside the 'admiral' + package. + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=admiral.test + url_git: '' +admiraldev: + version: 1.2.0 + title: |- + Utility Functions and Development Tools for the Admiral Package + Family + maintainer: Ben Straub + description: |- + Utility functions to check data, variables and conditions for + functions used in 'admiral' and 'admiral' extension packages. + Additional utility helper functions to assist developers with + maintaining documentation, testing and general upkeep of 'admiral' and + 'admiral' extension packages. + date_publication: '2025-01-15' + bug_reports: https://github.com/pharmaverse/admiraldev/issues + url: https://pharmaverse.github.io/admiraldev/ + url_cran: https://CRAN.R-project.org/package=admiraldev + url_git: https://github.com/pharmaverse/admiraldev/ +admiralmetabolic: + version: 0.1.0 + title: Metabolism Extension Package for ADaM in 'R' Asset Library + maintainer: Anders Askeland + description: |- + A toolbox for programming Clinical Data Standards Interchange + Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. + ADaM datasets are a mandatory part of any New Drug or Biologics + License Application submitted to the United States Food and Drug + Administration (FDA). Analysis derivations are implemented in + accordance with the "Analysis Data Model Implementation Guide" (CDISC + Analysis Data Model Team, 2021, + ). The package is + an extension package of the 'admiral' package focusing on the + metabolism therapeutic area. + date_publication: '2025-01-20' + bug_reports: https://github.com/pharmaverse/admiralmetabolic/issues + url: https://pharmaverse.github.io/admiralmetabolic/ + url_cran: https://CRAN.R-project.org/package=admiralmetabolic + url_git: https://github.com/pharmaverse/admiralmetabolic +admiralonco: + version: 1.2.0 + title: Oncology Extension Package for ADaM in 'R' Asset Library + maintainer: Stefan Bundfuss + description: |- + Programming oncology specific Clinical Data Interchange Standards Consortium + (CDISC) compliant Analysis Data Model (ADaM) datasets in 'R'. ADaM datasets are a + mandatory part of any New Drug or Biologics License Application submitted to the + United States Food and Drug Administration (FDA). Analysis derivations are + implemented in accordance with the "Analysis Data Model Implementation Guide" + (CDISC Analysis Data Model Team (2021), ). + The package is an extension package of the 'admiral' package. + date_publication: '2025-01-27' + bug_reports: https://github.com/pharmaverse/admiralonco/issues + url: https://pharmaverse.github.io/admiralonco/ + url_cran: https://CRAN.R-project.org/package=admiralonco + url_git: https://github.com/pharmaverse/admiralonco +admiralophtha: + version: 1.2.0 + title: ADaM in R Asset Library - Ophthalmology + maintainer: Edoardo Mancini + description: |- + Aids the programming of Clinical Data Standards Interchange + Consortium (CDISC) compliant Ophthalmology Analysis Data Model (ADaM) + datasets in R. ADaM datasets are a mandatory part of any New Drug or + Biologics License Application submitted to the United States Food and + Drug Administration (FDA). Analysis derivations are implemented in + accordance with the "Analysis Data Model Implementation Guide" (CDISC + Analysis Data Model Team, 2021, + ). + date_publication: '2025-01-16' + bug_reports: https://github.com/pharmaverse/admiralophtha/issues/ + url: https://pharmaverse.github.io/admiralophtha/ + url_cran: https://CRAN.R-project.org/package=admiralophtha + url_git: https://github.com/pharmaverse/admiralophtha/ +admiralpeds: + version: 0.2.0 + title: Pediatrics Extension Package for ADaM in 'R' Asset Library + maintainer: Fanny Gautier + description: |- + A toolbox for programming Clinical Data Standards Interchange + Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. + ADaM datasets are a mandatory part of any New Drug or Biologics + License Application submitted to the United States Food and Drug + Administration (FDA). Analysis derivations are implemented in + accordance with the "Analysis Data Model Implementation Guide" (CDISC + Analysis Data Model Team, 2021, + ). The package is + an extension package of the 'admiral' package for pediatric clinical + trials. + date_publication: '2025-01-16' + bug_reports: '' + url: https://pharmaverse.github.io/admiralpeds/ + url_cran: https://CRAN.R-project.org/package=admiralpeds + url_git: https://github.com/pharmaverse/admiralpeds +admiralvaccine: + version: 0.4.0 + title: Vaccine Extension Package for ADaM in 'R' Asset Library + maintainer: Sukalpo Saha + description: |- + Programming vaccine specific Clinical Data Interchange + Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) + datasets in 'R'. Flat model is followed as per + Center for Biologics Evaluation and Research (CBER) guidelines for + creating vaccine specific domains. ADaM datasets are a mandatory part + of any New Drug or Biologics License Application submitted to the + United States Food and Drug Administration (FDA). Analysis derivations + are implemented in accordance with the "Analysis Data Model + Implementation Guide" (CDISC Analysis Data Model Team (2021), + ). + The package is an extension package of the 'admiral' package. + date_publication: '2025-01-31' + bug_reports: https://github.com/pharmaverse/admiralvaccine/issues/ + url: https://pharmaverse.github.io/admiralvaccine/ + url_cran: https://CRAN.R-project.org/package=admiralvaccine + url_git: https://github.com/pharmaverse/admiralvaccine/ +admisc: + version: '0.37' + title: Adrian Dusa's Miscellaneous + maintainer: Adrian Dusa + description: |- + Contains functions used across packages 'DDIwR', 'QCA' and 'venn'. + Interprets and translates, factorizes and negates SOP - Sum of Products + expressions, for both binary and multi-value crisp sets, and extracts + information (set names, set values) from those expressions. Other functions + perform various other checks if possibly numeric (even if all numbers reside + in a character vector) and coerce to numeric, or check if the numbers are + whole. It also offers, among many others, a highly versatile recoding + routine and some more flexible alternatives to the base functions 'with()' + and 'within()'. + SOP simplification functions in this package use related minimization from + package 'QCA', which is recommended to be installed despite not being listed + in the Imports field, due to circular dependency issues. + date_publication: '2024-12-08' + bug_reports: https://github.com/dusadrian/admisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=admisc + url_git: https://github.com/dusadrian/admisc +AdMit: + version: 2.1.9 + title: Adaptive Mixture of Student-t Distributions + maintainer: David Ardia + description: |- + Provides functions to perform the fitting of an adaptive mixture + of Student-t distributions to a target density through its kernel function as described in + Ardia et al. (2009) . The + mixture approximation can then be used as the importance density in importance + sampling or as the candidate density in the Metropolis-Hastings algorithm to + obtain quantities of interest for the target density itself. + date_publication: '2022-02-08' + bug_reports: https://github.com/ArdiaD/AdMit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AdMit + url_git: https://github.com/ArdiaD/AdMit +admix: + version: 2.3.3 + title: Package Admix for Admixture (aka Contamination) Models + maintainer: Xavier Milhaud + description: |- + Implements techniques to estimate the unknown quantities + related to two-component admixture models, where the two components + can belong to any distribution (note that in the case of multinomial + mixtures, the two components must belong to the same family). + Estimation methods depend on the assumptions made on the unknown + component density; see Bordes and Vandekerkhove (2010) + , Patra and Sen (2016) + , and Milhaud, Pommeret, Salhi, Vandekerkhove + (2024) . In practice, one can estimate both + the mixture weight and the unknown component density in a wide variety + of frameworks. On top of that, hypothesis tests can be performed in + one and two-sample contexts to test the unknown component density (see + Milhaud, Pommeret, Salhi and Vandekerkhove (2022) + , and Milhaud, Pommeret, Salhi, + Vandekerkhove (2024) ). Finally, clustering of + unknown mixture components is also feasible in a K-sample setting (see + Milhaud, Pommeret, Salhi, Vandekerkhove (2024) + ). + date_publication: '2024-11-08' + bug_reports: https://github.com/XavierMilhaud/admix-Rpackage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=admix + url_git: https://github.com/XavierMilhaud/admix-Rpackage +admixr: + version: 0.9.1 + title: An Interface for Running 'ADMIXTOOLS' Analyses + maintainer: Martin Petr + description: |- + An interface for performing all stages of 'ADMIXTOOLS' analyses + () entirely from R. Wrapper functions + (D, f4, f3, etc.) completely automate the generation of intermediate + configuration files, run 'ADMIXTOOLS' programs on the command-line, and + parse output files to extract values of interest. This allows users to focus + on the analysis itself instead of worrying about low-level technical details. + A set of complementary functions for processing and filtering of data in + the 'EIGENSTRAT' format is also provided. + date_publication: '2020-07-03' + bug_reports: https://github.com/bodkan/admixr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=admixr + url_git: https://github.com/bodkan/admixr +ADMM: + version: 0.3.3 + title: Algorithms using Alternating Direction Method of Multipliers + maintainer: Kisung You + description: |- + Provides algorithms to solve popular optimization problems in statistics such as regression or denoising based on Alternating Direction Method of Multipliers (ADMM). + See Boyd et al (2010) for complete introduction to the method. + date_publication: '2021-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADMM + url_git: '' +admmDensestSubmatrix: + version: 0.1.0 + title: |- + Alternating Direction Method of Multipliers to Solve Dense + Dubmatrix Problem + maintainer: Polina Bombina + description: Solves the problem of identifying the densest submatrix in a given + or sampled binary matrix, Bombina et al. (2019) . + date_publication: '2019-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=admmDensestSubmatrix + url_git: '' +ADMMsigma: + version: '2.1' + title: Penalized Precision Matrix Estimation via ADMM + maintainer: Matt Galloway + description: |- + Estimates a penalized precision matrix via the alternating direction method of multipliers (ADMM) algorithm. It currently supports a general elastic-net penalty that allows for both ridge and lasso-type penalties as special cases. This package is an alternative to the 'glasso' package. + See Boyd et al (2010) for details regarding the estimation method. + date_publication: '2018-08-02' + bug_reports: https://github.com/MGallow/ADMMsigma/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ADMMsigma + url_git: https://github.com/MGallow/ADMMsigma +admtools: + version: 0.4.0 + title: Estimate and Manipulate Age-Depth Models + maintainer: Niklas Hohmann + description: |- + Estimate age-depth models from stratigraphic and sedimentological data, + and transform data + between the time and stratigraphic domain. + date_publication: '2024-10-03' + bug_reports: https://github.com/MindTheGap-ERC/admtools/issues + url: https://mindthegap-erc.github.io/admtools/ + url_cran: https://CRAN.R-project.org/package=admtools + url_git: https://github.com/MindTheGap-ERC/admtools +ADMUR: + version: 1.0.3 + title: Ancient Demographic Modelling Using Radiocarbon + maintainer: Adrian Timpson + description: Provides tools to directly model underlying population dynamics using + date datasets (radiocarbon and other) with a Continuous Piecewise Linear (CPL) + model framework. Various other model types included. Taphonomic loss included + optionally as a power function. Model comparison framework using BIC. Package + also calibrates 14C samples, generates Summed Probability Distributions (SPD), + and performs SPD simulation analysis to generate a Goodness-of-fit test for the + best selected model. Details about the method can be found in Timpson A., Barberena + R., Thomas M. G., Mendez C., Manning K. (2020) . + date_publication: '2021-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADMUR + url_git: https://github.com/UCL/ADMUR +adnuts: + version: 1.1.2 + title: No-U-Turn MCMC Sampling for 'ADMB' Models + maintainer: Cole Monnahan + description: |- + Bayesian inference using the no-U-turn (NUTS) algorithm by + Hoffman and Gelman (2014) . + Designed for 'AD Model Builder' ('ADMB') models, + or when R functions for log-density and log-density gradient + are available, such as 'Template Model Builder' + models and other special cases. Functionality is similar to 'Stan', + and the 'rstan' and 'shinystan' packages are used for diagnostics and + inference. + date_publication: '2021-03-02' + bug_reports: https://github.com/Cole-Monnahan-NOAA/adnuts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adnuts + url_git: https://github.com/Cole-Monnahan-NOAA/adnuts +adobeanalyticsr: + version: 0.5.0 + title: R Client for 'Adobe Analytics' API 2.0 + maintainer: Ben Woodard + description: |- + Connect to the 'Adobe Analytics' API v2.0 + which powers 'Analysis Workspace'. The package was developed + with the analyst in mind, and it will continue to be + developed with the guiding principles of iterative, + repeatable, timely analysis. + date_publication: '2025-01-16' + bug_reports: https://github.com/benrwoodard/adobeanalyticsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adobeanalyticsr + url_git: https://github.com/benrwoodard/adobeanalyticsr +adoptr: + version: 1.1.1 + title: Adaptive Optimal Two-Stage Designs + maintainer: Maximilian Pilz + description: |- + Optimize one or two-arm, two-stage designs for clinical trials with + respect to several implemented objective criteria or custom objectives. + Optimization under uncertainty and conditional (given stage-one outcome) + constraints are supported. + See Pilz et al. (2019) and + Kunzmann et al. (2021) for details. + date_publication: '2024-10-02' + bug_reports: https://github.com/optad/adoptr/issues + url: https://optad.github.io/adoptr/ + url_cran: https://CRAN.R-project.org/package=adoptr + url_git: https://github.com/optad/adoptr +ADP: + version: 0.1.6 + title: Adoption Probability, Triers and Users Rate of a New Product + maintainer: Mickey Kislev + description: 'Calculate users prevalence of a product based on the prevalence of + triers in the population. The measurement of triers is relatively easy. It is + just a question of whether a person tried a product even once in his life or not. + On the other hand, The measurement of people who also adopt it as part of their + life is more complicated since adopting an innovative product is a subjective + view of the individual. Mickey Kislev and Shira Kislev developed a formula to + calculate the prevalence of a product''s users to overcome this difficulty. The + current package assists in calculating the users prevalence of a product based + on the prevalence of triers in the population. See for: Kislev, M. M., and S. + Kislev (2020) .' + date_publication: '2021-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADP + url_git: '' +ADPclust: + version: '0.7' + title: Fast Clustering Using Adaptive Density Peak Detection + maintainer: Yifan (Ethan) Xu + description: |- + An implementation of ADPclust clustering procedures (Fast + Clustering Using Adaptive Density Peak Detection). The work is built and + improved upon the idea of Rodriguez and Laio (2014). + ADPclust clusters data by finding density peaks in a density-distance plot + generated from local multivariate Gaussian density estimation. It includes + an automatic centroids selection and parameter optimization algorithm, which + finds the number of clusters and cluster centroids by comparing average + silhouettes on a grid of testing clustering results; It also includes a user + interactive algorithm that allows the user to manually selects cluster + centroids from a two dimensional "density-distance plot". Here is the + research article associated with this package: "Wang, Xiao-Feng, and + Yifan Xu (2015) Fast clustering using adaptive + density peak detection." Statistical methods in medical research". url: + http://smm.sagepub.com/content/early/2015/10/15/0962280215609948.abstract. + date_publication: '2016-10-15' + bug_reports: https://github.com/ethanyxu/ADPclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ADPclust + url_git: https://github.com/ethanyxu/ADPclust +ADPF: + version: 0.0.1 + title: |- + Use Least Squares Polynomial Regression and Statistical Testing + to Improve Savitzky-Golay + maintainer: Samuel Kruse + description: |- + This function takes a vector or matrix of data and smooths + the data with an improved Savitzky Golay transform. The Savitzky-Golay + method for data smoothing and differentiation calculates convolution + weights using Gram polynomials that exactly reproduce the results of + least-squares polynomial regression. Use of the Savitzky-Golay + method requires specification of both filter length and + polynomial degree to calculate convolution weights. For maximum + smoothing of statistical noise in data, polynomials with + low degrees are desirable, while a high polynomial degree + is necessary for accurate reproduction of peaks in the data. + Extension of the least-squares regression formalism with + statistical testing of additional terms of polynomial degree + to a heuristically chosen minimum for each data window leads + to an adaptive-degree polynomial filter (ADPF). Based on noise + reduction for data that consist of pure noise and on signal + reproduction for data that is purely signal, ADPF performed + nearly as well as the optimally chosen fixed-degree + Savitzky-Golay filter and outperformed sub-optimally chosen + Savitzky-Golay filters. For synthetic data consisting of noise + and signal, ADPF outperformed both optimally chosen and + sub-optimally chosen fixed-degree Savitzky-Golay filters. See Barak, P. (1995) for more information. + date_publication: '2017-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADPF + url_git: '' +adplots: + version: 0.1.0 + title: |- + Ad-Plot and Ud-Plot for Visualizing Distributional Properties + and Normality + maintainer: Uditha Amarananda Wijesuriya + description: |- + The empirical cumulative average deviation function introduced by the author is utilized to + develop both Ad- and Ud-plots. The Ad-plot can identify symmetry, skewness, and outliers of the + data distribution, including anomalies. The Ud-plot created by slightly modifying Ad-plot is + exceptional in assessing normality, outperforming normal QQ-plot, normal PP-plot, and their + derivations. The d-value that quantifies the degree of proximity between the Ud-plot and the graph + of the estimated normal density function helps guide to make decisions on confirmation of + normality. Full description of this methodology can be found in the article by Wijesuriya (2025) + . + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adplots + url_git: '' +adproclus: + version: 2.0.0 + title: Additive Profile Clustering Algorithms + maintainer: Henry Heppe + description: |- + Obtain overlapping clustering models for object-by-variable data + matrices using the Additive Profile Clustering (ADPROCLUS) method. + Also contains the low dimensional ADPROCLUS method + for simultaneous dimension reduction and overlapping clustering. + For reference see Depril, Van Mechelen, Mirkin (2008) + and Depril, Van Mechelen, Wilderjans + (2012) . + date_publication: '2024-08-17' + bug_reports: https://github.com/henry-heppe/adproclus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adproclus + url_git: https://github.com/henry-heppe/adproclus +adpss: + version: 0.1.2 + title: |- + Design and Analysis of Locally or Globally Efficient Adaptive + Designs + maintainer: Kosuke Kashiwabara + description: |- + Provides the functions for planning and conducting a + clinical trial with adaptive sample size determination. Maximal statistical + efficiency will be exploited even when dramatic or multiple adaptations + are made. Such a trial consists of adaptive determination of sample size + at an interim analysis and implementation of frequentist statistical test at the + interim and final analysis with a prefixed significance level. The required + assumptions for the stage-wise test statistics are independent and stationary + increments and normality. Predetermination of adaptation rule is not required. + date_publication: '2022-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adpss + url_git: https://github.com/ca4wa/R-adpss +ads: + version: 1.5-10 + title: Spatial Point Patterns Analysis + maintainer: Dominique Lamonica + description: |- + Perform first- and second-order multi-scale analyses derived from Ripley K-function (Ripley B. D. (1977) ), for univariate, + multivariate and marked mapped data in rectangular, circular or irregular shaped sampling windows, with tests of + statistical significance based on Monte Carlo simulations. + date_publication: '2023-12-11' + bug_reports: https://forge.ird.fr/amap/ads/-/issues + url: https://forge.ird.fr/amap/ads + url_cran: https://CRAN.R-project.org/package=ads + url_git: '' +adsDataHubR: + version: 0.1.1 + title: Google Ads Data Hub API Client + maintainer: Pankaj Bhatlawande + description: Interact with Google Ads Data Hub API . + The functionality allows to fetch customer details, submit queries to ADH. + date_publication: '2021-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adsDataHubR + url_git: '' +ADSIHT: + version: 0.1.0 + title: Adaptive Double Sparse Iterative Hard Thresholding + maintainer: Yanhang Zhang + description: Solving the high-dimensional double sparse linear regression via iterative + hard thresholding algorithm. For more details, please see Zhang et al. (2024, + ). + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADSIHT + url_git: '' +ADTSA: + version: 1.0.1 + title: Time Series Analysis + maintainer: Leila Marvian Mashhad + description: |- + Analyzes autocorrelation and partial autocorrelation using surrogate methods and + bootstrapping, and computes the acceleration constants for the vectorized moving block + bootstrap provided by this package. It generates percentile, bias-corrected, and accelerated + intervals and estimates partial autocorrelations using Durbin-Levinson. This package + calculates the autocorrelation power spectrum, computes cross-correlations between two + time series, computes bandwidth for any time series, and performs autocorrelation frequency + analysis. It also calculates the periodicity of a time series. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADTSA + url_git: '' +AdvancedBasketballStats: + version: 1.0.1 + title: Advanced Basketball Statistics + maintainer: Francisco Javier Cantero + description: Provides different functionalities and calculations used in the world + of basketball to analyze the statistics of the players, the statistics of the + teams, the statistics of the quintets and the statistics of the plays. For more + details of the calculations included in the package can be found in the book Basketball + on Paper written by Dean Oliver. + date_publication: '2021-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdvancedBasketballStats + url_git: '' +AdvBinomApps: + version: '1.0' + title: |- + Upper Clopper-Pearson Confidence Limits for Burn-in Studies + under Additional Available Information + maintainer: Horst Lewitschnig + description: Functions to compute upper Clopper-Pearson confidence limits of early + life failure probabilities and required sample sizes of burn-in studies under + further available information, e.g. from other products or technologies. + date_publication: '2016-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdvBinomApps + url_git: '' +AdvDif4: + version: 0.7.18 + title: Solving 1D Advection Bi-Flux Diffusion Equation + maintainer: Jader Lugon Junior + description: This software solves an Advection Bi-Flux Diffusive Problem using the + Finite Difference Method FDM. Vasconcellos, J.F.V., Marinho, G.M., Zanni, J.H., + 2016, Numerical analysis of an anomalous diffusion with a bimodal flux distribution. + . Silva, L.G., Knupp, D.C., Bevilacqua, L., Galeao, + A.C.N.R., Silva Neto, A.J., 2014, Formulation and solution of an Inverse Anomalous + Diffusion Problem with Stochastic Techniques. . In + this version, it is possible to include a source as a function depending on space + and time, that is, s(x,t). + date_publication: '2019-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdvDif4 + url_git: '' +adventr: + version: 0.1.8 + title: |- + Interactive R Tutorials to Accompany Field (2016), "An Adventure + in Statistics" + maintainer: Andy Field + description: |- + Interactive 'R' tutorials written using 'learnr' for Field (2016), "An Adventure in Statistics", . + Topics include general workflow in 'R' and 'Rstudio', the 'R' environment and 'tidyverse', summarizing data, model fitting, central tendency, + visualising data using 'ggplot2', inferential statistics and robust estimation, hypothesis testing, the general linear model, comparing means, + repeated measures designs, factorial designs, multilevel models, growth models, and generalized linear models (logistic regression). + date_publication: '2020-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=adventr + url_git: '' +AdverseEvents: + version: 0.0.4 + title: '''shiny'' Application for Adverse Event Analysis of ''OnCore'' Data' + maintainer: Z Thompson + description: |- + An application for analysis of Adverse Events, as described in Chen, et al., (2023) . + The required data for the application includes demographics, follow up, adverse event, drug administration and optional tumor measurement data. + The app can produce swimmers plots of adverse events, Kaplan-Meier plots and Cox Proportional Hazards model results + for the association of adverse event biomarkers and overall survival and progression free survival. + The adverse event biomarkers include occurrence of grade 3, low grade (1-2), and treatment related adverse events. + Plots and tables of results are downloadable. + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AdverseEvents + url_git: https://github.com/dungtsa/AdverseEvents +ADVICE: + version: '1.0' + title: |- + Automatic Direct Variable Selection via Interrupted Coefficient + Estimation + maintainer: L. Tazik + description: Accurate point and interval estimation methods for multiple linear + regression coefficients, under classical normal and independent error assumptions, + taking into account variable selection. + date_publication: '2021-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ADVICE + url_git: '' +adw: + version: 0.4.0 + title: Angular Distance Weighting Interpolation + maintainer: Panfeng Zhang + description: The irregularly-spaced data are interpolated onto regular latitude-longitude + grids by weighting each station according to its distance and angle from the center + of a search radius. In addition to this, we also provide a simple way (Jones and + Hulme, 1996) to grid the irregularly-spaced data points onto regular latitude-longitude + grids by averaging all stations in grid-boxes. + date_publication: '2024-04-15' + bug_reports: https://github.com/PanfengZhang/adw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=adw + url_git: https://github.com/PanfengZhang/adw +adwave: + version: '1.3' + title: Wavelet Analysis of Genomic Data from Admixed Populations + maintainer: Murray Cox + description: Implements wavelet-based approaches for describing population admixture. + Principal Components Analysis (PCA) is used to define the population structure + and produce a localized admixture signal for each individual. Wavelet summaries + of the PCA output describe variation present in the data and can be related to + population-level demographic processes. For more details, see J Sanderson, H Sudoyo, + TM Karafet, MF Hammer and MP Cox. 2015. Reconstructing past admixture processes + from local genomic ancestry using wavelet transformation. Genetics 200:469-481 + . + date_publication: '2018-05-17' + bug_reports: '' + url: https://doi.org/10.1534/genetics.115.176842 + url_cran: https://CRAN.R-project.org/package=adwave + url_git: '' +adwordsR: + version: 0.3.1 + title: Access the 'Google Adwords' API + maintainer: Sean Longthorpe + description: |- + Allows access to selected services that are part of the + 'Google Adwords' API . + 'Google Adwords' is an online advertising service by 'Google', that delivers Ads + to users. This package offers a authentication process using 'OAUTH2'. Currently, + there are two methods of data of accessing the API, depending on the type of + request. One method uses 'SOAP' requests which require building an 'XML' structure + and then sent to the API. These are used for the 'ManagedCustomerService' and + the 'TargetingIdeaService'. The second method is by building 'AWQL' queries for + the reporting side of the 'Google Adwords' API. + date_publication: '2018-06-19' + bug_reports: '' + url: https://www.branded3.com/ + url_cran: https://CRAN.R-project.org/package=adwordsR + url_git: '' +aebdata: + version: 0.1.4 + title: Access Data from the Atlas do Estado Brasileiro + maintainer: Hugo Macedo + description: |- + Facilitates access to the data from the Atlas do Estado Brasileiro + (), maintained by the Instituto de + Pesquisa Econômica Aplicada (Ipea). It allows users to search for specific + series, list series or themes, and download data when available. + date_publication: '2025-02-03' + bug_reports: https://github.com/ipea/aebdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aebdata + url_git: https://github.com/ipea/aebdata +aeddo: + version: 0.1.1 + title: Automated and Early Detection of Disease Outbreaks + maintainer: Lasse Engbo Christiansen + description: |- + A powerful tool for automating the early detection of disease + outbreaks in time series data. 'aeddo' employs advanced statistical + methods, including hierarchical models, in an innovative manner to + effectively characterize outbreak signals. It is particularly useful + for epidemiologists, public health professionals, and researchers + seeking to identify and respond to disease outbreaks in a timely + fashion. For a detailed reference on hierarchical models, consult + Henrik Madsen and Poul Thyregod's book (2011), ISBN: 9781420091557. + date_publication: '2023-11-27' + bug_reports: https://github.com/ssi-dk/aeddo/issues + url: https://ssi-dk.github.io/aeddo/ + url_cran: https://CRAN.R-project.org/package=aeddo + url_git: https://github.com/ssi-dk/aeddo +AEDForecasting: + version: 0.20.0 + title: Change Point Analysis in ARIMA Forecasting + maintainer: Nhat Cuong Pham + description: Package to incorporate change point analysis in ARIMA forecasting. + date_publication: '2016-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AEDForecasting + url_git: '' +aedseo: + version: 0.1.2 + title: Automated and Early Detection of Seasonal Epidemic Onset + maintainer: Lasse Engbo Christiansen + description: |- + A powerful tool for automating the early detection of seasonal epidemic + onsets in time series data. It offers the ability to estimate growth rates + for consecutive time intervals and calculate the sum of cases (SoC) within + those intervals. It is particularly useful for epidemiologists, public + health professionals, and researchers seeking to identify and respond to + seasonal epidemics in a timely fashion. + For reference on growth rate estimation, see Walling and Lipstich (2007) + and Obadia et al. (2012) . + date_publication: '2023-11-27' + bug_reports: https://github.com/ssi-dk/aedseo/issues + url: https://ssi-dk.github.io/aedseo/ + url_cran: https://CRAN.R-project.org/package=aedseo + url_git: https://github.com/ssi-dk/aedseo +AEenrich: + version: 1.1.0 + title: Adverse Event Enrichment Tests + maintainer: Michael Kleinsasser + description: |- + We extend existing gene enrichment tests to perform adverse + event enrichment analysis. Unlike the continuous gene expression data, + adverse event data are counts. Therefore, adverse event data has many zeros + and ties. We propose two enrichment tests. One is a modified Fisher's exact + test based on pre-selected significant adverse events, while the other is + based on a modified Kolmogorov-Smirnov statistic. We add Covariate + adjustment to improve the analysis."Adverse event enrichment tests using + VAERS" Shuoran Li, Lili Zhao (2020) . + date_publication: '2021-11-01' + bug_reports: https://github.com/umich-biostatistics/AEenrich/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AEenrich + url_git: https://github.com/umich-biostatistics/AEenrich +aelab: + version: 1.0.1 + title: Data Processing for Aquatic Ecology + maintainer: Zhao-Jun Yong + description: |- + Facilitate the analysis of data related to aquatic ecology, specifically the establishment of carbon budget. + Currently, the package allows the below analysis. + (i) the calculation of greenhouse gas flux based on data obtained from trace gas analyzer using the method described in Lin et al. (2024). + (ii) the calculation of Dissolved Oxygen (DO) metabolism based on data obtained from dissolved oxygen data logger using the method described in Staehr et al. (2010). + Yong et al. (2024) . + Staehr et al. (2010) . + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aelab + url_git: '' +AEP: + version: 0.1.4 + title: |- + Statistical Modelling for Asymmetric Exponential Power + Distribution + maintainer: Mahdi Teimouri + description: |- + Developed for Computing the probability density function, cumulative + distribution function, random generation, estimating the parameters of asymmetric + exponential power distribution, and robust regression analysis with error + term that follows asymmetric exponential power distribution. The asymmetric + exponential power distribution studied here is a special case of that introduced + by Dongming and Zinde-Walsh (2009) . + date_publication: '2022-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AEP + url_git: '' +AER: + version: 1.2-14 + title: Applied Econometrics with R + maintainer: Achim Zeileis + description: |- + Functions, data sets, examples, demos, and vignettes for the book + Christian Kleiber and Achim Zeileis (2008), + Applied Econometrics with R, Springer-Verlag, New York. + ISBN 978-0-387-77316-2. + (See the vignette "AER" for a package overview.) + date_publication: '2024-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AER + url_git: '' +AeRobiology: + version: 2.0.1 + title: A Computational Tool for Aerobiological Data + maintainer: '"Jose Oteros"' + description: 'Different tools for managing databases of airborne particles, elaborating + the main calculations and visualization of results. In a first step, data are + checked using tools for quality control and all missing gaps are completed. Then, + the main parameters of the pollen season are calculated and represented graphically. + Multiple graphical tools are available: pollen calendars, phenological plots, + time series, tendencies, interactive plots, abundance plots...' + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AeRobiology + url_git: '' +AeroSampleR: + version: 0.2.0 + title: Estimate Aerosol Particle Collection Through Sample Lines + maintainer: Mark Hogue + description: |- + Estimate ideal efficiencies of aerosol sampling through sample + lines. Functions were developed consistent with the approach described in + Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis, (2014), + "Hand Calculations for Transport of Radioactive Aerosols through Sampling + Systems" Health Phys 106, 5, S78-S87, . + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AeroSampleR + url_git: '' +AF: + version: 0.1.5 + title: |- + Model-Based Estimation of Confounder-Adjusted Attributable + Fractions + maintainer: Elisabeth Dahlqwist + description: |- + Estimates the attributable fraction in different sampling designs + adjusted for measured confounders using logistic regression (cross-sectional + and case-control designs), conditional logistic regression (matched case-control + design), Cox proportional hazard regression (cohort design with time-to- + event outcome), gamma-frailty model with a Weibull baseline hazard and instrumental variables analysis. + An exploration of the AF with a genetic exposure can be found in the package 'AFheritability' Dahlqwist E et al. (2019) . + date_publication: '2019-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AF + url_git: '' +afc: + version: 1.4.0 + title: Generalized Discrimination Score + maintainer: Jonas Bhend + description: |- + This is an implementation of the Generalized Discrimination Score + (also known as Two Alternatives Forced Choice Score, 2AFC) for various + representations of forecasts and verifying observations. The Generalized + Discrimination Score is a generic forecast verification framework which + can be applied to any of the following verification contexts: dichotomous, + polychotomous (ordinal and nominal), continuous, probabilistic, and ensemble. + A comprehensive description of the Generalized Discrimination Score, including + all equations used in this package, is provided by Mason and Weigel (2009) + . + date_publication: '2017-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=afc + url_git: '' +afcharts: + version: 0.4.1 + title: |- + Produce Charts Following UK Government Analysis Function + Guidance + maintainer: Olivia Box Power + description: |- + Colour palettes and a 'ggplot2' theme to follow the UK Government + Analysis Function best practice guidance for producing data visualisations, + available at + . + Includes continuous and discrete colour and fill scales, as well as a + 'ggplot2' theme. + date_publication: '2025-01-13' + bug_reports: https://github.com/best-practice-and-impact/afcharts/issues + url: https://best-practice-and-impact.github.io/afcharts/ + url_cran: https://CRAN.R-project.org/package=afcharts + url_git: https://github.com/best-practice-and-impact/afcharts +afcolours: + version: 1.0.0 + title: |- + Government Analysis Function Recommended Accessible Colour + Palette + maintainer: Luke Davies + description: |- + Government Analysis Function recommended colours for use in + charts on gov.uk to help meet accessibility guidance. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=afcolours + url_git: '' +afdx: + version: 1.1.1 + title: Diagnosis Performance Using Attributable Fraction + maintainer: John J. Aponte + description: |- + Estimate diagnosis performance (Sensitivity, Specificity, + Positive predictive value, Negative predicted value) of a diagnostic test + where can not measure the golden standard but can estimate it using the + attributable fraction. + date_publication: '2021-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=afdx + url_git: https://github.com/johnaponte/afdx +afex: + version: 1.4-1 + title: Analysis of Factorial Experiments + maintainer: Henrik Singmann + description: |- + Convenience functions for analyzing factorial experiments using ANOVA or + mixed models. aov_ez(), aov_car(), and aov_4() allow specification of + between, within (i.e., repeated-measures), or mixed (i.e., split-plot) + ANOVAs for data in long format (i.e., one observation per row), + automatically aggregating multiple observations per individual and cell + of the design. mixed() fits mixed models using lme4::lmer() and computes + p-values for all fixed effects using either Kenward-Roger or Satterthwaite + approximation for degrees of freedom (LMM only), parametric bootstrap + (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). + afex_plot() provides a high-level interface for interaction or one-way + plots using ggplot2, combining raw data and model estimates. afex uses + type 3 sums of squares as default (imitating commercial statistical software). + date_publication: '2024-09-01' + bug_reports: https://github.com/singmann/afex/issues + url: https://afex.singmann.science/ + url_cran: https://CRAN.R-project.org/package=afex + url_git: https://github.com/singmann/afex +AFFECT: + version: 0.1.2 + title: |- + Accelerated Functional Failure Time Model with + Error-Contaminated Survival Times + maintainer: Hsiao-Ting Huang + description: We aim to deal with data with measurement error in the response and + misclassification censoring status under an AFT model. This package primarily + contains three functions, which are used to generate artificial data, correction + for error-prone data and estimate the functional covariates for an AFT model. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AFFECT + url_git: '' +affiner: + version: 0.1.3 + title: |- + A Finer Way to Render 3D Illustrated Objects in 'grid' Using + Affine Transformations + maintainer: Trevor L. Davis + description: Dilate, permute, project, reflect, rotate, shear, and translate 2D + and 3D points. Supports parallel projections including oblique projections such + as the cabinet projection as well as axonometric projections such as the isometric + projection. Use 'grid's "affine transformation" feature to render illustrated + flat surfaces. + date_publication: '2024-12-02' + bug_reports: https://github.com/trevorld/affiner/issues + url: https://trevorldavis.com/R/affiner/ + url_cran: https://CRAN.R-project.org/package=affiner + url_git: '' +affinity: + version: 0.2.5 + title: Raster Georeferencing, Grid Affine Transforms, Cell Abstraction + maintainer: Michael D. Sumner + description: |- + Tools for raster georeferencing, grid affine transforms, and general raster logic. + These functions provide converters between raster specifications, world vector, geotransform, + 'RasterIO' window, and 'RasterIO window' in 'sf' package list format. There are functions to offset + a matrix by padding any of four corners (useful for vectorizing neighbourhood operations), and + helper functions to harvesting user clicks on a graphics device to use for simple georeferencing + of images. Methods used are available from and + . + date_publication: '2021-06-02' + bug_reports: https://github.com/hypertidy/affinity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=affinity + url_git: https://github.com/hypertidy/affinity +affinitymatrix: + version: 0.1.0 + title: Estimation of Affinity Matrix + maintainer: Edoardo Ciscato + description: Tools to study sorting patterns in matching markets and to estimate + the affinity matrix of both the bipartite one-to-one matching model without frictions + and with Transferable Utility by 'Dupuy' and 'Galichon' (2014) + and its 'unipartite' variant by 'Ciscato', 'Galichon' and 'Gousse' (2020) . + It also contains all the necessary tools to implement the 'saliency' analysis, + to run rank tests of the affinity matrix and to build tables and plots summarizing + the findings. + date_publication: '2020-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=affinitymatrix + url_git: '' +affluenceIndex: + version: '2.2' + title: Affluence (Richness) Indices + maintainer: Alicja Wolny-Dominiak + description: Enables to compute the statistical indices of affluence (richness) + with bootstrap errors, and inequality and polarization indices. Moreover, gives + the possibility of calculation of affluence line. Some simple errors are fixed + and it works with new version of Spatial Statistics packaged. + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=affluenceIndex + url_git: '' +AFheritability: + version: 0.1.0 + title: |- + The Attributable Fraction (AF) Described as a Function of + Disease Heritability, Prevalence and Intervention Specific + Factors + maintainer: Elisabeth Dahlqwist + description: |- + The AFfunction() is a function which returns an estimate of the Attributable Fraction (AF) and a plot of the AF as a function of heritability, disease prevalence, size of target group and intervention effect. + Since the AF is a function of several factors, a shiny app is used to better illustrate how the relationship between the AF and heritability depends on several other factors. The app is ran by the function runShinyApp(). + For more information see Dahlqwist E et al. (2019) . + date_publication: '2019-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AFheritability + url_git: '' +AFM: + version: '2.0' + title: Atomic Force Microscope Image Analysis + maintainer: Mathieu Beauvais + description: |- + Provides Atomic Force Microscope images analysis such as Gaussian mixes identification, Power + Spectral Density, roughness against lengthscale, experimental variogram and variogram models, + fractal dimension and scale, 2D network analysis. The AFM images can be exported to STL format for 3D + printing. + date_publication: '2020-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AFM + url_git: '' +afmToolkit: + version: 0.0.1 + title: |- + Functions for Atomic Force Microscope Force-Distance Curves + Analysis + maintainer: Rafael Benitez + description: Set of functions for analyzing Atomic Force Microscope (AFM) force-distance + curves. It allows to obtain the contact and unbinding points, perform the baseline + correction, estimate the Young's modulus, fit up to two exponential decay function + to a stress-relaxation / creep experiment, obtain adhesion energies. These operations + can be done either over a single F-d curve or over a set of F-d curves in batch mode. + date_publication: '2017-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=afmToolkit + url_git: '' +afpt: + version: 1.1.0.4 + title: Tools for Modelling of Animal Flight Performance + maintainer: Marco KleinHeerenbrink + description: |- + Allows estimation and modelling of flight costs in animal (vertebrate) flight, + implementing the aerodynamic power model described in Klein Heerenbrink et al. + (2015) . Taking inspiration from the program + 'Flight', developed by Colin Pennycuick (Pennycuick (2008) "Modelling the flying + bird". Amsterdam: Elsevier. ISBN 0-19-857721-4), flight performance is estimated + based on basic morphological measurements such as body mass, wingspan and wing + area. 'afpt' can be used to make predictions on how animals should adjust their + flight behaviour and wingbeat kinematics to varying flight conditions. + date_publication: '2023-11-03' + bug_reports: https://github.com/MarcoKlH/afpt-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=afpt + url_git: https://github.com/MarcoKlH/afpt-r/ +AFR: + version: 0.3.6 + title: |- + Toolkit for Regression Analysis of Kazakhstan Banking Sector + Data + maintainer: Sultan Zhaparov + description: |- + Tool is created for regression, prediction and forecast analysis of macroeconomic and credit data. + The package includes functions from existing R packages adapted for banking sector of Kazakhstan. + The purpose of the package is to optimize statistical functions for easier interpretation for bank analysts and non-statisticians. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AFR + url_git: '' +africamonitor: + version: 0.2.4 + title: Africa Macroeconomic Monitor Database API + maintainer: Sebastian Krantz + description: |- + An R API providing access to a relational database with macroeconomic data for Africa. + The database contains >700 macroeconomic time series from mostly international sources, + grouped into 50 macroeconomic and development-related topics. Series are carefully selected + on the basis of data coverage for Africa, frequency, and relevance to the macro-development context. + The project is part of the 'Kiel Institute Africa Initiative' + , + which, amongst other things, aims to develop a parsimonious database with highly relevant indicators + to monitor macroeconomic developments in Africa, accessible through a fast API and a web-based platform + at . + The database is maintained at the Kiel Institute for the World Economy . + date_publication: '2024-01-25' + bug_reports: https://github.com/kielinstitute/africamonitor/issues + url: https://africamonitor.ifw-kiel.de/ + url_cran: https://CRAN.R-project.org/package=africamonitor + url_git: '' +aftables: + version: 1.0.2 + title: Create Spreadsheet Publications Following Best Practice + maintainer: Olivia Box Power + description: |- + Generate spreadsheet publications that follow best practice + guidance from the UK government's Analysis Function, available at + , + with a focus on accessibility. See also the 'Python' package 'gptables'. + date_publication: '2025-02-19' + bug_reports: https://github.com/best-practice-and-impact/aftables/issues + url: https://best-practice-and-impact.github.io/aftables/ + url_cran: https://CRAN.R-project.org/package=aftables + url_git: https://github.com/best-practice-and-impact/aftables +aftgee: + version: 1.2.1 + title: |- + Accelerated Failure Time Model with Generalized Estimating + Equations + maintainer: Sy Han Chiou + description: A collection of methods for both the rank-based estimates and least-square + estimates to the Accelerated Failure Time (AFT) model. For rank-based estimation, + it provides approaches that include the computationally efficient Gehan's weight + and the general's weight such as the logrank weight. Details of the rank-based + estimation can be found in Chiou et al. (2014) + and Chiou et al. (2015) . For the least-square estimation, + the estimating equation is solved with generalized estimating equations (GEE). + Moreover, in multivariate cases, the dependence working correlation structure + can be specified in GEE's setting. Details on the least-squares estimation can + be found in Chiou et al. (2014) . + date_publication: '2024-10-07' + bug_reports: https://github.com/stc04003/aftgee/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aftgee + url_git: https://github.com/stc04003/aftgee +afthd: + version: 1.1.0 + title: Accelerated Failure Time for High Dimensional Data with MCMC + maintainer: Atanu Bhattacharjee + description: |- + Functions for Posterior estimates of Accelerated Failure Time(AFT) model with MCMC and Maximum likelihood estimates of AFT model without MCMC for univariate and multivariate analysis in high dimensional gene expression data are available in this 'afthd' package. + AFT model with Bayesian framework for multivariate in high dimensional data has been proposed by Prabhash et al.(2016) + . + date_publication: '2021-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=afthd + url_git: '' +aftR2: + version: 0.1.0 + title: R-Squared Measure under Accelerated Failure Time (AFT) Models + maintainer: Yuyao Wang + description: Compute the R-squared measure under the accelerated failure time (AFT) + models proposed in Chan et. al. (2018) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aftR2 + url_git: '' +aftsem: + version: '1.0' + title: Semiparametric Accelerated Failure Time Model + maintainer: Martin Benedikt + description: 'Implements several basic algorithms for estimating regression parameters + for semiparametric accelerated failure time (AFT) model. The main methods are: + Jin rank-based method (Jin (2003) ), Heller’s estimating + method (Heller (2012) ), Polynomial smoothed Gehan + function method (Chung (2013) ), Buckley-James + method (Buckley (1979) ) and Jin`s improved least squares + method (Jin (2006) ). This package can be used for + modeling right-censored data and for comparing different estimation algorithms.' + date_publication: '2024-09-15' + bug_reports: https://github.com/benedma2/aftsem-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aftsem + url_git: https://github.com/benedma2/aftsem-package +afttest: + version: 4.3.2.3 + title: Model Diagnostics for Accelerated Failure Time Models + maintainer: Woojung Bae + description: |- + A collection of model checking methods for semiparametric accelerated + failure time (AFT) models under the rank-based approach. For the (computational) + efficiency, Gehan's weight is used. It provides functions to verify whether the + observed data fit the specific model assumptions such as a functional form of + each covariate, a link function, and an omnibus test. The p-value offered in this + package is based on the Kolmogorov-type supremum test and the variance of the + proposed test statistics is estimated through the re-sampling method. Furthermore, + a graphical technique to compare the shape of the observed residual to a number of + the approximated realizations is provided. + date_publication: '2024-01-16' + bug_reports: https://github.com/WooJungBae/afttest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=afttest + url_git: https://github.com/WooJungBae/afttest +ag5Tools: + version: 0.0.2 + title: Toolbox for Downloading and Extracting Copernicus AgERA5 Data + maintainer: David Brown + description: |- + Tools for downloading and extracting data from the Copernicus "Agrometeorological indicators + from 1979 to present derived from reanalysis" + (AgERA5). + date_publication: '2023-10-12' + bug_reports: '' + url: https://agrdatasci.github.io/ag5Tools/ + url_cran: https://CRAN.R-project.org/package=ag5Tools + url_git: '' +agcounts: + version: 0.6.6 + title: Calculate 'ActiGraph' Counts from Accelerometer Data + maintainer: Brian C. Helsel + description: |- + Calculate 'ActiGraph' counts from the X, Y, and Z axes of a triaxial + accelerometer. This work was inspired by Neishabouri et al. who published the + article "Quantification of Acceleration as Activity Counts in 'ActiGraph' Wearables" + on February 24, 2022. The link to the article () + and 'python' implementation of this code (). + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agcounts + url_git: '' +AGD: + version: 0.45.0 + title: Analysis of Growth Data + maintainer: Stef van Buuren + description: |- + Tools for the analysis of growth data: to extract an + LMS table from a gamlss object, to calculate the standard + deviation scores and its inverse, and to superpose two wormplots + from different models. The package contains a some varieties of + reference tables, especially for The Netherlands. + date_publication: '2024-05-03' + bug_reports: https://github.com/stefvanbuuren/AGD/issues + url: https://stefvanbuuren.name/AGD/ + url_cran: https://CRAN.R-project.org/package=AGD + url_git: '' +ageg: + version: 1.0.0 + title: Age Grouping Functions + maintainer: Austin Anders + description: Pair of simple convenience functions to convert a vector of birth dates + to age and age distributions. These functions may be helpful when related age + and custom age distributions are desired given a vector of birth dates. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ageg + url_git: '' +agena.ai: + version: 1.1.1 + title: R Wrapper for 'agena.ai' API + maintainer: Eugene Dementiev + description: 'An R wrapper for ''agena.ai'' which provides + users capabilities to work with ''agena.ai'' using the R environment. Users can + create Bayesian network models from scratch or import existing models in R and + export to ''agena.ai'' cloud or local API for calculations. Note: running calculations + requires a valid ''agena.ai'' API license (past the initial trial period of the + local API).' + date_publication: '2023-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agena.ai + url_git: '' +AgePopDenom: + version: 0.4.0 + title: |- + Model Fine-Scale Age-Structured Population Data using + Open-Source Data + maintainer: Mohamed A. Yusuf + description: |- + Automate the modelling of age-structured population data + using survey data, grid population estimates and urban-rural extents. + date_publication: '2025-02-25' + bug_reports: '' + url: https://truenomad.github.io/AgePopDenom/ + url_cran: https://CRAN.R-project.org/package=AgePopDenom + url_git: '' +ageutils: + version: 0.0.7 + title: Collection of Functions for Working with Age Intervals + maintainer: Tim Taylor + description: |- + Provides a collection of efficient functions for working with + individual ages and corresponding intervals. These include functions for + conversion from an age to an interval, aggregation of ages with associated + counts in to intervals and the splitting of interval counts based on + specified age distributions. + date_publication: '2024-12-06' + bug_reports: https://github.com/TimTaylor/ageutils/issues + url: https://timtaylor.github.io/ageutils/ + url_cran: https://CRAN.R-project.org/package=ageutils + url_git: '' +agfh: + version: 0.2.1 + title: Agnostic Fay-Herriot Model for Small Area Statistics + maintainer: Marten Thompson + description: |- + Implements the Agnostic Fay-Herriot model, an extension of + the traditional small area model. In place of normal sampling errors, the + sampling error distribution is estimated with a Gaussian process to + accommodate a broader class of distributions. This flexibility is most + useful in the presence of bounded, multi-modal, or heavily skewed sampling + errors. + date_publication: '2023-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agfh + url_git: '' +agghoo: + version: 0.1-0 + title: Aggregated Hold-Out Cross Validation + maintainer: Benjamin Auder + description: |- + The 'agghoo' procedure is an alternative to usual cross-validation. + Instead of choosing the best model trained on V subsamples, it determines + a winner model for each subsample, and then aggregates the V outputs. + For the details, see "Aggregated hold-out" by Guillaume Maillard, + Sylvain Arlot, Matthieu Lerasle (2021) + published in Journal of Machine Learning Research 22(20):1--55. + date_publication: '2023-05-25' + bug_reports: '' + url: https://git.auder.net/?p=agghoo.git + url_cran: https://CRAN.R-project.org/package=agghoo + url_git: '' +AggregateR: + version: 0.1.1 + title: Aggregate Numeric, Date and Categorical Variables + maintainer: Matthias Bogaert + description: |- + Convenience functions for aggregating a data frame or data table. + Currently mean, sum and variance are supported. For Date variables, the recency + and duration are supported. There is also support for dummy variables in + predictive contexts. Code has been completely re-written in data.table for computational speed. + date_publication: '2020-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AggregateR + url_git: '' +aggregation: + version: 1.0.1 + title: p-Value Aggregation Methods + maintainer: Lynn Yi + description: 'Contains functionality for performing the following methods of p-value + aggregation: Fisher''s method [Fisher, RA (1932, ISBN: 9780028447308)], the Lancaster + method (weighted Fisher''s method) [Lancaster, HO (1961, )], + and Sidak correction [Sidak, Z (1967, )]. Please + cite Yi et al., the manuscript corresponding to this package [Yi, L et al., (2017), + ].' + date_publication: '2018-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aggregation + url_git: '' +aggTrees: + version: 2.1.0 + title: Aggregation Trees + maintainer: Riccardo Di Francesco + description: |- + Nonparametric data-driven approach to discovering heterogeneous subgroups in a selection-on-observables framework. + 'aggTrees' allows researchers to assess whether there exists relevant heterogeneity in treatment effects by generating a sequence of optimal groupings, + one for each level of granularity. For each grouping, we obtain point estimation and inference about the group average treatment effects. + Please reference the use as Di Francesco (2022) . + date_publication: '2024-09-09' + bug_reports: https://github.com/riccardo-df/aggTrees/issues + url: https://riccardo-df.github.io/aggTrees/ + url_cran: https://CRAN.R-project.org/package=aggTrees + url_git: '' +aggutils: + version: 1.0.2 + title: Utilities for Aggregating Probabilistic Forecasts + maintainer: Molly Hickman + description: |- + Provides several methods for aggregating probabilistic forecasts. You have a group of + people who have made probabilistic forecasts for the same event. You want to take advantage of + the "wisdom of the crowd" and combine these forecasts in some sensible way. This package + provides implementations of several strategies, including geometric mean of odds, an extremized + aggregate (Neyman, Roughgarden (2021) ), and "high-density trimmed + mean" (Powell et al. (2022) ). + date_publication: '2023-08-22' + bug_reports: https://github.com/forecastingresearch/aggutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aggutils + url_git: https://github.com/forecastingresearch/aggutils +AGHmatrix: + version: 2.1.4 + title: Relationship Matrices for Diploid and Autopolyploid Species + maintainer: Rodrigo Amadeu + description: |- + Computation of A (pedigree), G (genomic-base), and H (A corrected + by G) relationship matrices for diploid and autopolyploid species. Several methods + are implemented considering additive and non-additive models. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AGHmatrix + url_git: https://github.com/rramadeu/AGHmatrix +aghq: + version: 0.4.1 + title: Adaptive Gauss Hermite Quadrature for Bayesian Inference + maintainer: Alex Stringer + description: |- + Adaptive Gauss Hermite Quadrature for Bayesian inference. + The AGHQ method for normalizing posterior distributions + and making Bayesian inferences based on them. Functions are provided for doing + quadrature and marginal Laplace approximations, and summary methods are provided + for making inferences based on the results. + See Stringer (2021). "Implementing Adaptive Quadrature for Bayesian Inference: + the aghq Package" . + date_publication: '2023-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aghq + url_git: '' +aglm: + version: 0.4.0 + title: Accurate Generalized Linear Model + maintainer: Kenji Kondo + description: Provides functions to fit Accurate Generalized Linear Model (AGLM) + models, visualize them, and predict for new data. AGLM is defined as a regularized + GLM which applies a sort of feature transformations using a discretization of + numerical features and specific coding methodologies of dummy variables. For more + information on AGLM, see Suguru Fujita, Toyoto Tanaka, Kenji Kondo and Hirokazu + Iwasawa (2020) . + date_publication: '2021-06-09' + bug_reports: https://github.com/kkondo1981/aglm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aglm + url_git: https://github.com/kkondo1981/aglm +agop: + version: 0.2.4 + title: Aggregation Operators and Preordered Sets + maintainer: Marek Gagolewski + description: |- + Tools supporting multi-criteria and group decision making, + including variable number of criteria, by means of + aggregation operators, spread measures, + fuzzy logic connectives, fusion functions, + and preordered sets. Possible applications include, + but are not limited to, quality management, scientometrics, + software engineering, etc. + date_publication: '2023-11-30' + bug_reports: https://github.com/gagolews/agop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=agop + url_git: https://github.com/gagolews/agop/ +AGPRIS: + version: '2.0' + title: AGricultural PRoductivity in Space + maintainer: Edoardo Baldoni + description: |- + Functionalities to simulate space-time data and to estimate dynamic-spatial panel data models. + Estimators implemented are the BCML (Elhorst (2010), ), the MML (Elhorst (2010) ) and the INLA Bayesian estimator (Lindgren and Rue, (2015) ; Bivand, Gomez-Rubio and Rue, (2015) ) + adapted to panel data. The package contains functions to replicate the analyses of the scientific article entitled "Agricultural Productivity in Space" (Baldoni and Esposti (2021), )). + date_publication: '2023-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AGPRIS + url_git: '' +agRee: + version: 0.5-3 + title: Various Methods for Measuring Agreement + maintainer: Dai Feng + description: |- + Bland-Altman plot and scatter plot with identity line + for visualization and point and + interval estimates for different metrics related to + reproducibility/repeatability/agreement including + the concordance correlation coefficient, + intraclass correlation coefficient, + within-subject coefficient of variation, + smallest detectable difference, + and mean normalized smallest detectable difference. + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agRee + url_git: '' +AgreementInterval: + version: 0.1.1 + title: Agreement Interval of Two Measurement Methods + maintainer: Jialin Xu + description: A tool for calculating agreement interval of two measurement methods + (Jason Liao (2015) ) and present results in plots with + discordance rate and/or clinically meaningful limit to quantify agreement quality. + date_publication: '2018-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AgreementInterval + url_git: '' +agricolae: + version: 1.3-7 + title: Statistical Procedures for Agricultural Research + maintainer: Felipe de Mendiburu + description: Original idea was presented in the thesis "A statistical analysis tool + for agricultural research" to obtain the degree of Master on science, National + Engineering University (UNI), Lima-Peru. Some experimental data for the examples + come from the CIP and others research. Agricolae offers extensive functionality + on experimental design especially for agricultural and plant breeding experiments, + which can also be useful for other purposes. It supports planning of lattice, + Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, + factorial, split and strip plot designs. There are also various analysis facilities + for experimental data, e.g. treatment comparison procedures and several non-parametric + tests comparison, biodiversity indexes and consensus cluster. + date_publication: '2023-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agricolae + url_git: '' +agricolaeplotr: + version: 0.6.1 + title: |- + Visualization of Design of Experiments from the 'agricolae' + Package + maintainer: Jens Harbers + description: |- + Visualization of Design of Experiments from the 'agricolae' package with 'ggplot2' framework + The user provides an experiment design from the 'agricolae' package, calls the corresponding function and will receive a + visualization with 'ggplot2' based functions that are specific for each design. As there are many different designs, each design is tested on its type. + The output can be modified with standard 'ggplot2' commands or with other packages with 'ggplot2' function extensions. + date_publication: '2025-01-30' + bug_reports: https://github.com/jensharbers/agricolaeplotr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=agricolaeplotr + url_git: https://github.com/jensharbers/agricolaeplotr +agridat: + version: '1.24' + title: Agricultural Datasets + maintainer: Kevin Wright + description: |- + Datasets from books, papers, and websites related to + agriculture. Example graphics and analyses are included. Data come + from small-plot trials, multi-environment trials, uniformity trials, + yield monitors, and more. + date_publication: '2024-10-27' + bug_reports: https://github.com/kwstat/agridat/issues + url: https://kwstat.github.io/agridat/ + url_cran: https://CRAN.R-project.org/package=agridat + url_git: '' +agrifeature: + version: 1.0.3 + title: Agriculture Image Feature + maintainer: Chun-Han Lee + description: Functions to calculate Gray Level Co-occurrence Matrix(GLCM), RGB-based + Vegetative Index(RGB VI) and Normalized Difference Vegetation Index(NDVI) family + image features. GLCM calculations are based on Haralick (1973) . + date_publication: '2021-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agrifeature + url_git: '' +agriTutorial: + version: 0.1.5 + title: Tutorial Analysis of Some Agricultural Experiments + maintainer: Rodney Edmondson + description: |- + Example software for the analysis of data from designed + experiments, especially agricultural crop experiments. The basics + of the analysis of designed experiments are discussed + using real examples from agricultural field trials. + A range of statistical methods using a range + of R statistical packages are exemplified . The experimental + data is made available as separate data sets for each example + and the R analysis code is made available as example code. + The example code can be readily extended, as required. + date_publication: '2019-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agriTutorial + url_git: '' +agriutilities: + version: 1.2.1 + title: Utilities for Data Analysis in Agriculture + maintainer: Johan Aparicio + description: |- + Utilities designed to make the analysis of field trials easier and + more accessible for everyone working in plant breeding. It provides a simple + and intuitive interface for conducting single and multi-environmental trial + analysis, with minimal coding required. Whether you're a beginner or an + experienced user, 'agriutilities' will help you quickly and easily carry out + complex analyses with confidence. With built-in functions for fitting Linear + Mixed Models, 'agriutilities' is the ideal choice for anyone who wants to save + time and focus on interpreting their results. + Some of the functions require the R package 'asreml' for the 'ASReml' software, + this can be obtained upon purchase from 'VSN' international . + date_publication: '2025-01-17' + bug_reports: https://github.com/AparicioJohan/agriutilities/issues + url: https://apariciojohan.github.io/agriutilities/ + url_cran: https://CRAN.R-project.org/package=agriutilities + url_git: https://github.com/AparicioJohan/agriutilities +agriwater: + version: 1.0.2 + title: Evapotranspiration and Energy Fluxes Spatial Analysis + maintainer: Cesar de Oliveira Ferreira Silva + description: |- + Spatial modeling of energy balance and actual + evapotranspiration using satellite images and meteorological data. + Options of satellite are: Landsat-8 (with and without thermal bands), + Sentinel-2 and MODIS. Respectively spatial resolutions are 30, 100, + 10 and 250 meters. User can use data from a single meteorological + station or a grid of meteorological stations (using any spatial + interpolation method). Silva, Teixeira, and Manzione (2019) . + date_publication: '2023-06-08' + bug_reports: https://github.com/cesarofs/agriwater/issues + url: '' + url_cran: https://CRAN.R-project.org/package=agriwater + url_git: '' +agrmt: + version: 1.42.12 + title: Calculate Concentration and Dispersion in Ordered Rating Scales + maintainer: Didier Ruedin + description: 'Calculates concentration and dispersion in ordered rating scales. + It implements various measures of concentration and dispersion to describe what + researchers variably call agreement, concentration, consensus, dispersion, or + polarization among respondents in ordered data. It also implements other related + measures to classify distributions. In addition to a generic city-block based + concentration measure and a generic dispersion measure, the package implements + various measures, including van der Eijk''s (2001) + measure of agreement A, measures of concentration by Leik, Tatsle and Wierman, + Blair and Lacy, Kvalseth, Berry and Mielke, Reardon, and Garcia-Montalvo and Reynal-Querol. + Furthermore, the package provides an implementation of Galtungs AJUS-system to + classify distributions, as well as a function to identify the position of multiple + modes.' + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agrmt + url_git: http://agrmt.r-forge.r-project.org +AgroR: + version: 1.3.6 + title: Experimental Statistics and Graphics for Agricultural Sciences + maintainer: Gabriel Danilo Shimizu + description: 'Performs the analysis of completely randomized experimental designs + (CRD), randomized blocks (RBD) and Latin square (LSD), experiments in double and + triple factorial scheme (in CRD and RBD), experiments in subdivided plot scheme + (in CRD and RBD), subdivided and joint analysis of experiments in CRD and RBD, + linear regression analysis, test for two samples. The package performs analysis + of variance, ANOVA assumptions and multiple comparison test of means or regression, + according to Pimentel-Gomes (2009, ISBN: 978-85-7133-055-9), nonparametric test + (Conover, 1999, ISBN: 0471160687), test for two samples, joint analysis of experiments + according to Ferreira (2018, ISBN: 978-85-7269-566-4) and generalized linear model + (glm) for binomial and Poisson family in CRD and RBD (Carvalho, FJ (2019), ). + It can also be used to obtain descriptive measures and graphics, in addition to + correlations and creative graphics used in agricultural sciences (Agronomy, Zootechnics, + Food Science and related areas).' + date_publication: '2024-04-24' + bug_reports: '' + url: https://agronomiar.github.io/AgroR_package/index.html + url_cran: https://CRAN.R-project.org/package=AgroR + url_git: '' +AgroReg: + version: 1.2.10 + title: Regression Analysis Linear and Nonlinear for Agriculture + maintainer: Gabriel Danilo Shimizu + description: Linear and nonlinear regression analysis common in agricultural science + articles (Archontoulis & Miguez (2015). ). The package + includes polynomial, exponential, gaussian, logistic, logarithmic, segmented, + non-parametric models, among others. The functions return the model coefficients + and their respective p values, coefficient of determination, root mean square + error, AIC, BIC, as well as graphs with the equations automatically. + date_publication: '2024-01-16' + bug_reports: '' + url: https://fisher.uel.br/AgroReg_shiny/ + url_cran: https://CRAN.R-project.org/package=AgroReg + url_git: '' +agrostab: + version: 0.1.0 + title: Stability Analysis for Agricultural Research + maintainer: Anna Cheshkova + description: Statistical procedures to perform stability analysis in plant breeding + and to identify stable genotypes under diverse environments. It is possible to + calculate coefficient of homeostaticity by Khangildin et al. (1979), variance + of specific adaptive ability by Kilchevsky&Khotyleva (1989), weighted homeostaticity + index by Martynov (1990), steadiness of stability index by Udachin (1990), superiority + measure by Lin&Binn (1988) , regression on environmental + index by Erberhart&Rassel (1966) , + Tai's (1971) stability parameters , + stability variance by Shukla (1972) , ecovalence by Wricke + (1962), nonparametric stability parameters by Nassar&Huehn (1987) , + Francis&Kannenberg's parameters of stability (1978) . + date_publication: '2019-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agrostab + url_git: '' +AgroTech: + version: 1.0.2 + title: Data Analysis of Pesticide Application Technology + maintainer: Rodrigo Yudi Palhaci Marubayashi + description: In total it has 7 functions, three for calculating machine calibration, + which determine application rate (L/ha), nozzle flow (L/min) and amount of product + (L or kg) to be added. to the tank with each sprayer filling. Two functions for + graphs of the flow distribution of the nozzles (L/min) in the application bar + and, of the temporal variability of the meteorological conditions (air temperature, + relative humidity of the air and wind speed). Two functions to determine the spray + deposit (uL/cm2), through the methodology called spectrophotometry, with the aid + of bright blue (Palladini, L.A., Raetano, C.G., Velini, E.D. (2005), ) + or metallic markers (Chaim, A., Castro, V.L.S.S., Correles, F.M., Galvão, J.A.H., + Cabral, O.M.R., Nicolella, G. (1999), ). + The package supports the analysis and representation of information, using a single + free software that meets the most diverse areas of activity in application technology. + date_publication: '2022-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AgroTech + url_git: '' +ags: + version: 1.0.1 + title: Crosswalk Municipality and District Statistics in Germany + maintainer: Moritz Marbach + description: Construct time series for Germany's municipalities (Gemeinden) and + districts (Kreise) using a annual crosswalk constructed by the Federal Office + for Building and Regional Planning (BBSR). + date_publication: '2023-02-21' + bug_reports: https://github.com/sumtxt/ags/issues + url: https://sumtxt.github.io/ags/ + url_cran: https://CRAN.R-project.org/package=ags + url_git: '' +agtboost: + version: 0.9.3 + title: Adaptive and Automatic Gradient Boosting Computations + maintainer: Berent Ånund Strømnes Lunde + description: |- + Fast and automatic gradient tree boosting designed + to avoid manual tuning and cross-validation by utilizing an information + theoretic approach. This makes the algorithm adaptive to the dataset at + hand; it is completely automatic, and with minimal worries of overfitting. + Consequently, the speed-ups relative to state-of-the-art implementations + can be in the thousands while mathematical and technical knowledge required + on the user are minimized. + date_publication: '2021-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=agtboost + url_git: '' +agua: + version: 0.1.4 + title: '''tidymodels'' Integration with ''h2o''' + maintainer: Qiushi Yan + description: |- + Create and evaluate models using 'tidymodels' and 'h2o' . The + package enables users to specify 'h2o' as an engine for several + modeling methods. + date_publication: '2024-06-04' + bug_reports: https://github.com/tidymodels/agua/issues + url: https://agua.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=agua + url_git: https://github.com/tidymodels/agua +agvgd: + version: 0.1.2 + title: An R Implementation of the 'Align-GVGD' Method + maintainer: Ramiro Magno + description: |- + 'Align-GVGD' ('A-GVGD') is a method to predict the impact of + 'missense' substitutions based on the properties of amino acid side + chains and protein multiple sequence alignments + . 'A-GVGD' is an extension of the original + 'Grantham' distance to multiple sequence alignments. This package + provides an alternative R implementation to the web version found on + . + date_publication: '2022-09-10' + bug_reports: https://github.com/maialab/agvgd/issues + url: https://maialab.org/agvgd/ + url_cran: https://CRAN.R-project.org/package=agvgd + url_git: https://github.com/maialab/agvgd +ahaz: + version: 1.15.1 + title: Regularization for Semiparametric Additive Hazards Regression + maintainer: Anders Gorst-Rasmussen + description: |- + Computationally efficient procedures for regularized + estimation with the semiparametric additive hazards regression + model. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ahaz + url_git: '' +AHM: + version: 1.0.1 + title: |- + Additive Heredity Model: Method for the Mixture-of-Mixtures + Experiments + maintainer: Sumin Shen + description: An implementation of the additive heredity model for the mixture-of-mixtures + experiments of Shen et al. (2019) in Technometrics . + The additive heredity model considers an additive structure to inherently connect + the major components with the minor components. The additive heredity model has + a meaningful interpretation for the estimated model because of the hierarchical + and heredity principles applied and the nonnegative garrote technique used for + variable selection. + date_publication: '2019-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AHM + url_git: '' +AHMbook: + version: 0.2.10 + title: |- + Functions and Data for the Book 'Applied Hierarchical Modeling + in Ecology' Vols 1 and 2 + maintainer: Ken Kellner + description: 'Provides functions to simulate data sets from hierarchical ecological + models, including all the simulations described in the two volume publication + ''Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance + and species richness in R and BUGS'' by Marc Kéry and Andy Royle: volume 1 (2016, + ISBN: 978-0-12-801378-6) and volume 2 (2021, ISBN: 978-0-12-809585-0), . + It also has all the utility functions and data sets needed to replicate the analyses + shown in the books.' + date_publication: '2024-09-11' + bug_reports: https://github.com/hmecology/AHMbook/issues + url: https://www.mbr-pwrc.usgs.gov/pubanalysis/keryroylebook/ + url_cran: https://CRAN.R-project.org/package=AHMbook + url_git: '' +ahMLE: + version: 1.20.1 + title: Methods for the Additive Hazard Model + maintainer: Chengyuan Lu + description: |- + Methods for fitting additive hazards model. + Perform the maximum likelihood method as well as the traditional Aalen's method for estimating the additive hazards model. + For details see Chengyuan Lu(2021) . + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ahMLE + url_git: '' +ahnr: + version: 0.3.1 + title: An Implementation of the Artificial Hydrocarbon Networks + maintainer: Jose Roberto Ayala Solares + description: |- + Implementation of the Artificial Hydrocarbon Networks for data + modeling. + date_publication: '2018-06-18' + bug_reports: https://github.com/jroberayalas/ahnr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ahnr + url_git: https://github.com/jroberayalas/ahnr +AhoCorasickTrie: + version: 0.1.3 + title: Fast Searching for Multiple Keywords in Multiple Texts + maintainer: Matt Chambers + description: |- + Aho-Corasick is an optimal algorithm for finding many + keywords in a text. It can locate all matches in a text in O(N+M) time; i.e., + the time needed scales linearly with the number of keywords (N) and the size of + the text (M). Compare this to the naive approach which takes O(N*M) time to loop + through each pattern and scan for it in the text. This implementation builds the + trie (the generic name of the data structure) and runs the search in a single + function call. If you want to search multiple texts with the same trie, the + function will take a list or vector of texts and return a list of matches to + each text. By default, all 128 ASCII characters are allowed in both the keywords + and the text. A more efficient trie is possible if the alphabet size can be + reduced. For example, DNA sequences use at most 19 distinct characters and + usually only 4; protein sequences use at most 26 distinct characters and usually + only 20. UTF-8 (Unicode) matching is not currently supported. + date_publication: '2025-02-05' + bug_reports: https://github.com/chambm/AhoCorasickTrie/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AhoCorasickTrie + url_git: https://github.com/chambm/AhoCorasickTrie +AHPGaussian: + version: 0.1.1 + title: 'New Multicriteria Method: AHPGaussian' + maintainer: Cid Edson Povoas + description: 'Implements the Analytic Hierarchy Process (AHP) method using Gaussian + normalization (AHPGaussian) to derive the relative weights of the criteria and + alternatives. It also includes functions for visualizing the results and generating + graphical outputs. Method as described in: dos Santos, Marcos (2021) .' + date_publication: '2023-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AHPGaussian + url_git: '' +AHPhybrid: + version: 0.1.0 + title: AHP Hybrid Method + maintainer: Miguel Angelo Lellis Moreira + description: |- + The AHP method (Analytic Hierarchy Process) is a multi-criteria decision-making method addressing + choice and outranking problems. The method enables to perform the analysis of alternatives in each + type of criterion and then provides a global performance of each alternative in the decision context. + The main difference of this package is the possibility of evaluating the alternatives using quantitative + data, by numerical representation, and qualitative data, using the Saaty scale, providing preference + relation between variables by a pairwise evaluation. + date_publication: '2021-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AHPhybrid + url_git: '' +ahpsurvey: + version: 0.4.1 + title: Analytic Hierarchy Process for Survey Data + maintainer: Frankie Cho + description: The Analytic Hierarchy Process is a versatile multi-criteria decision-making + tool introduced by Saaty (1987) that allows + decision-makers to weigh attributes and evaluate alternatives presented to them. This + package provides a consistent methodology for researchers to reformat data and + run analytic hierarchy process in R on data that are formatted using the survey + data entry mode. It is optimized for performing the analytic hierarchy process + with many decision-makers, and provides tools and options for researchers to aggregate + individual preferences and test multiple options. It also allows researchers to + quantify, visualize and correct for inconsistency in the decision-maker's comparisons. + date_publication: '2019-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ahpsurvey + url_git: '' +AHPtools: + version: 0.3.0 + title: Consistency in the Analytic Hierarchy Process + maintainer: Amarnath Bose + description: |- + A Swiss Army knife of utility functions for users of the Analytic + Hierarchy Process (AHP) which will help you to assess the consistency of a + PCM as well as to improve its consistency ratio, to compute the sensitivity + of a PCM, create a logical (as distinct from a random PCM) from preferences + provided for the alternatives, and a function that helps evaluate the actual + consistency of a PCM based on objective, fair bench marking. The various + functions in the toolkit additionally provide the flexibility to users to + specify only the upper triangular comparison ratios of the PCM in order to + performs its assigned task. + date_publication: '2024-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AHPtools + url_git: '' +ahptopsis2n: + version: 0.2.0 + title: Hybrid Method for Multiple Criteria Decision-Making (MCDM) + maintainer: Raquel Coutinho + description: 'Implementation of a hybrid MCDM method build from the AHP (Analytic + Hierarchy Process) and TOPSIS-2N (Technique for Order of Preference by Similarity + to Ideal Solution - with two normalizations). This method is described in Souza + et al. (2018) .' + date_publication: '2021-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ahptopsis2n + url_git: '' +AHPWR: + version: 0.1.0 + title: Compute Analytic Hierarchy Process + maintainer: Luciane Ferreira Alcoforado + description: Compute a tree level hierarchy, judgment matrix, consistency index + and ratio, priority vectors, hierarchic synthesis and rank. Based on the book + entitled "Models, Methods, Concepts and Applications of the Analytic Hierarchy + Process" by Saaty and Vargas (2012, ISBN 978-1-4614-3597-6). + date_publication: '2022-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AHPWR + url_git: '' +AHSurv: + version: 0.1.0 + title: Flexible Parametric Accelerated Hazards Models + maintainer: Abdisalam Hassan Muse + description: Flexible parametric Accelerated Hazards (AH) regression models in overall + and relative survival frameworks with 13 distinct Baseline Distributions. The + AH Model can also be applied to lifetime data with crossed survival curves. Any + user-defined parametric distribution can be fitted, given at least an R function + defining the cumulative hazard and hazard rate functions. See Chen and Wang (2000) + , and Lee (2015) + for more details. + date_publication: '2022-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AHSurv + url_git: '' +ahw: + version: 0.1.0 + title: |- + Calculates Continuous Time Likelihood Ratio Weights Assuming + Multiplicative Intensity Models and Additive Hazard Models + maintainer: Pål Christie Ryalen + description: |- + Estimates continuous time weights for performing causal survival + analysis. For instance, weighted Nelson-Aalen or Kaplan-Meier + estimates can be given a causal interpretation. See Ryalen, Stensrud, + and Røysland (2019) and Ryalen (2019) + + for theory and examples. + date_publication: '2022-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ahw + url_git: '' +ai: + version: 1.0.4.44 + title: Build, Predict and Analyse Artificial Intelligence Models + maintainer: Rafal Urniaz + description: An interface for data processing, building models, predicting values + and analysing outcomes. Fitting Linear Models, Robust Fitting of Linear Models, + k-Nearest Neighbor Classification, 1-Nearest Neighbor Classification, and Conditional + Inference Trees are available. + date_publication: '2024-10-02' + bug_reports: https://github.com/urniaz/ai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ai + url_git: https://github.com/urniaz/ai +aIc: + version: '1.0' + title: Testing for Compositional Pathologies in Datasets + maintainer: Greg Gloor + description: 'A set of tests for compositional pathologies. Tests for coherence + of correlations with aIc.coherent() as suggested by (Erb et al. (2020) ), compositional + dominance of distance with aIc.dominant(), compositional perturbation invariance + with aIc.perturb() as suggested by (Aitchison (1992) ) + and singularity of the covariation matrix with aIc.singular(). Currently tests + five data transformations: prop, clr, TMM, TMMwsp, and RLE from the R packages + ''ALDEx2'', ''edgeR'' and ''DESeq2'' (Fernandes et al (2014) , + Anders et al. (2013)).' + date_publication: '2022-10-04' + bug_reports: https://github.com/ggloor/aIc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aIc + url_git: https://github.com/ggloor/aIc +AICcmodavg: + version: 2.3-3 + title: Model Selection and Multimodel Inference Based on (Q)AIC(c) + maintainer: Marc J. Mazerolle + description: Functions to implement model selection and multimodel inference based + on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well + as their quasi-likelihood counterparts (QAIC, QAICc) from various model object + classes. The package implements classic model averaging for a given parameter + of interest or predicted values, as well as a shrinkage version of model averaging + parameter estimates or effect sizes. The package includes diagnostics and goodness-of-fit + statistics for certain model types including those of 'unmarkedFit' classes estimating + demographic parameters after accounting for imperfect detection probabilities. Some + functions also allow the creation of model selection tables for Bayesian models + of the 'bugs', 'rjags', and 'jagsUI' classes. Functions also implement model + selection using BIC. Objects following model selection and multimodel inference + can be formatted to LaTeX using 'xtable' methods included in the package. + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AICcmodavg + url_git: '' +AICcPermanova: + version: 0.0.2 + title: Model Selection of PERMANOVA Models Using AICc + maintainer: Derek Corcoran + description: |- + Provides tools for model selection and model averaging of PerMANOVA + models using Akaike Information Criterion corrected for small sample sizes + (AICc) and Information Theoretic criteria principles. The package is built + around the PERMANOVA analysis from the 'vegan' package and provides a + streamlined workflow for generating and comparing models, obtaining model + weights, and summarizing results using model averaging approaches. The + methods implemented in this package are based on the practical information- + theoretic approach described by Burnham, K. P. and Anderson, D. R. (2002) + (). + date_publication: '2023-04-11' + bug_reports: https://github.com/Sustainscapes/AICcPerm/issues + url: https://sustainscapes.github.io/AICcPerm/ + url_cran: https://CRAN.R-project.org/package=AICcPermanova + url_git: https://github.com/Sustainscapes/AICcPerm +AID: + version: '3.1' + title: Box-Cox Power Transformation + maintainer: Osman Dag + description: Performs Box-Cox power transformation for different purposes, graphical + approaches, assesses the success of the transformation via tests and plots, computes + mean and confidence interval for back transformed data. + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AID + url_git: '' +aidar: + version: 1.0.5 + title: Tools for Reading AIDA Files + maintainer: Andreas Pfeiffer + description: Read objects from the AIDA () file and make + them available as dataframes in R. + date_publication: '2018-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aidar + url_git: '' +aides: + version: 1.3.3 + title: Additive Information & Details of Evidence Synthesis + maintainer: Enoch Kang + description: A supportive collection of functions for pooled analysis of aggregate + data. The current version supports users to test assumptions before relevant analysis + of bias from study size and sequential analysis such as mentioned by Wetterslev, + J., Jakobsen, J. C., & Gluud, C. (2017) . + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aides + url_git: '' +aifeducation: + version: 1.0.2 + title: Artificial Intelligence for Education + maintainer: Berding Florian + description: |- + In social and educational settings, the use of Artificial + Intelligence (AI) is a challenging task. Relevant data is often only + available in handwritten forms, or the use of data is restricted by + privacy policies. This often leads to small data sets. Furthermore, in + the educational and social sciences, data is often unbalanced in terms + of frequencies. To support educators as well as educational and social + researchers in using the potentials of AI for their work, this package + provides a unified interface for neural nets in 'PyTorch' to deal with + natural language problems. In addition, the package ships with a shiny + app, providing a graphical user interface. This allows the usage of + AI for people without skills in writing python/R scripts. The tools + integrate existing mathematical and statistical methods for dealing + with small data sets via pseudo-labeling (e.g. Cascante-Bonilla et al. + (2020) ) and imbalanced data via the + creation of synthetic cases (e.g. Bunkhumpornpat et al. (2012) + ). Performance evaluation of AI is + connected to measures from content analysis which educational and + social researchers are generally more familiar with (e.g. Berding & + Pargmann (2022) , Gwet (2014) + , Krippendorff (2019) + ). Estimation of energy consumption and CO2 + emissions during model training is done with the 'python' library + 'codecarbon'. Finally, all objects created with this package allow to + share trained AI models with other people. + date_publication: '2025-02-05' + bug_reports: https://github.com/cran/aifeducation/issues + url: https://fberding.github.io/aifeducation/ + url_cran: https://CRAN.R-project.org/package=aifeducation + url_git: '' +AIFFtools: + version: '1.0' + title: Read AIFF Files and Convert to WAVE Format + maintainer: Carl Witthoft + description: Functions are provided to read and convert AIFF audio files to WAVE + (WAV) format. This supports, for example, use of the 'tuneR' package, which does + not currently handle AIFF files. The AIFF file format is defined in + and + . + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AIFFtools + url_git: '' +aihuman: + version: 1.0.0 + title: |- + Experimental Evaluation of Algorithm-Assisted Human + Decision-Making + maintainer: Sooahn Shin + description: |- + Provides statistical methods for analyzing experimental + evaluation of the causal impacts of algorithmic recommendations + on human decisions developed by Imai, Jiang, Greiner, Halen, and + Shin (2023) and Ben-Michael, Greiner, + Huang, Imai, Jiang, and Shin (2024) . + The data used for this paper, and made available here, are interim, + based on only half of the observations in the study and (for those + observations) only half of the study follow-up period. We use them + only to illustrate methods, not to draw substantive conclusions. + date_publication: '2025-01-09' + bug_reports: https://github.com/sooahnshin/aihuman/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aihuman + url_git: https://github.com/sooahnshin/aihuman +aimPlot: + version: 1.0.0 + title: Create Pie Like Plot for Completeness + maintainer: Yusman Kamaleri + description: |- + Create a pie like plot to visualise if the aim or several aims of a + project is achieved or close to be achieved i.e the aim is achieved when the point is at the + center of the pie plot. Imagine it's like a dartboard and the center means 100% + completeness/achievement. Achievement can also be understood as 100% + coverage. The standard distribution of completeness allocated in the pie plot + is 50%, 80% and 100% completeness. + date_publication: '2016-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aimPlot + url_git: '' +aimsir17: + version: 0.0.2 + title: Irish Weather Observing Stations Hourly Records for 2017 + maintainer: Jim Duggan + description: |- + Named after the Irish name for weather, this package contains + tidied data from the Irish Meteorological Service's hourly observations for 2017. + In all, the data sets include observations from 25 weather stations, and also + latitude and longitude coordinates for each weather station. Now includes energy + generation data for Ireland and Northern Ireland (2017), including Wind Generation data. + date_publication: '2020-08-14' + bug_reports: '' + url: https://www.met.ie + url_cran: https://CRAN.R-project.org/package=aimsir17 + url_git: https://github.com/JimDuggan/aimsir17 +aion: + version: 1.4.0 + title: Archaeological Time Series + maintainer: Nicolas Frerebeau + description: |- + A toolkit for archaeological time series and time intervals. + This package provides a system of classes and methods to represent and + work with archaeological time series and time intervals. Dates are + represented as "rata die" and can be converted to (virtually) any + calendar defined by Reingold and Dershowitz (2018) + . This packages offers a simple API that + can be used by other specialized packages. + date_publication: '2025-02-27' + bug_reports: https://codeberg.org/tesselle/aion/issues + url: https://codeberg.org/tesselle/aion + url_cran: https://CRAN.R-project.org/package=aion + url_git: '' +AIPW: + version: 0.6.3.2 + title: Augmented Inverse Probability Weighting + maintainer: Yongqi Zhong + description: 'The ''AIPW'' pacakge implements the augmented inverse probability + weighting, a doubly robust estimator, for average causal effect estimation with + user-defined stacked machine learning algorithms. To cite the ''AIPW'' package, + please use: "Yongqi Zhong, Edward H. Kennedy, Lisa M. Bodnar, Ashley I. Naimi + (2021, In Press). AIPW: An R Package for Augmented Inverse Probability Weighted + Estimation of Average Causal Effects. American Journal of Epidemiology". Visit: + for more information.' + date_publication: '2021-06-11' + bug_reports: https://github.com/yqzhong7/AIPW/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AIPW + url_git: https://github.com/yqzhong7/AIPW +air: + version: 0.2.2 + title: AI Assistant to Write and Understand R Code + maintainer: Soumya Ray + description: |- + An R console utility that lets you ask R related questions to the + 'OpenAI' large language model. It can answer 'how-to()' questions by + providing code, and 'whatis()' questions by explaining what given code does. + You must provision your own key for the 'OpenAI' API + . + date_publication: '2023-11-17' + bug_reports: https://github.com/soumyaray/air/issues + url: '' + url_cran: https://CRAN.R-project.org/package=air + url_git: https://github.com/soumyaray/air +aire.zmvm: + version: 1.0.0 + title: Download Mexico City Pollution, Wind, and Temperature Data + maintainer: Diego Valle-Jones + description: |- + Tools for downloading hourly averages, daily maximums and + minimums from each of the pollution, wind, and temperature measuring + stations or geographic zones in the Mexico City metro area. The + package also includes the locations of each of the stations and zones. + See for more information. + date_publication: '2024-06-26' + bug_reports: https://github.com/diegovalle/aire.zmvm/issues + url: https://hoyodesmog.diegovalle.net/aire.zmvm/ + url_cran: https://CRAN.R-project.org/package=aire.zmvm + url_git: https://github.com/diegovalle/aire.zmvm +AirExposure: + version: '1.0' + title: |- + Exposure Model to Air Pollutants Based on Mobility and Daily + Activities + maintainer: Josefina Urquiza + description: Model that assesses daily exposure to air pollution, which considers + daily population mobility on a geographical scale and the spatial and temporal + variability of pollutant concentrations, in addition to traditional parameters + such as exposure time and pollutant concentration. + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AirExposure + url_git: https://github.com/flortames/Air-Exposure-Model +airGR: + version: 1.7.6 + title: |- + Suite of GR Hydrological Models for Precipitation-Runoff + Modelling + maintainer: Olivier Delaigue + description: Hydrological modelling tools developed at INRAE-Antony (HYCAR Research + Unit, France). The package includes several conceptual rainfall-runoff models + (GR4H, GR5H, GR4J, GR5J, GR6J, GR2M, GR1A) that can be applied either on a lumped + or semi-distributed way. A snow accumulation and melt model (CemaNeige) and the + associated functions for the calibration and evaluation of models are also included. + Use help(airGR) for package description and references. + date_publication: '2023-10-26' + bug_reports: https://gitlab.irstea.fr/HYCAR-Hydro/airgr/-/issues + url: https://hydrogr.github.io/airGR/ + url_cran: https://CRAN.R-project.org/package=airGR + url_git: '' +airGRdatasets: + version: 0.2.1 + title: |- + Hydro-Meteorological Catchments Datasets for the 'airGR' + Packages + maintainer: Olivier Delaigue + description: Sample of hydro-meteorological datasets extracted from the 'CAMELS-FR' + French database . It provides metadata and + catchment-scale aggregated hydro-meteorological time series on a pool of French + catchments for use by the 'airGR' packages. + date_publication: '2023-07-12' + bug_reports: https://gitlab.irstea.fr/HYCAR-Hydro/airgrgalaxy/airgrdatasets/-/issues + url: https://gitlab.irstea.fr/HYCAR-Hydro/airgrgalaxy/airgrdatasets + url_cran: https://CRAN.R-project.org/package=airGRdatasets + url_git: '' +airGRdatassim: + version: 0.1.3 + title: Ensemble-Based Data Assimilation with GR Hydrological Models + maintainer: Olivier Delaigue + description: Add-on to the 'airGR' package which provides the tools to assimilate + observed discharges in daily GR hydrological models. The package consists in two + functions allowing to perform the assimilation of observed discharges via the + Ensemble Kalman filter or the Particle filter as described in Piazzi et al. (2021) + . + date_publication: '2021-02-11' + bug_reports: https://gitlab.irstea.fr/HYCAR-Hydro/airgrdatassim/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=airGRdatassim + url_git: '' +airGRiwrm: + version: 0.7.0 + title: '''airGR'' Integrated Water Resource Management' + maintainer: David Dorchies + description: |- + Semi-distributed Precipitation-Runoff Modeling based on + 'airGR' package models integrating human infrastructures and their + managements. + date_publication: '2024-09-22' + bug_reports: https://github.com/inrae/airGRiwrm/issues + url: https://inrae.github.io/airGRiwrm/ + url_cran: https://CRAN.R-project.org/package=airGRiwrm + url_git: https://github.com/inrae/airGRiwrm#readme +airGRteaching: + version: 0.3.4 + title: |- + Teaching Hydrological Modelling with the GR Rainfall-Runoff + Models ('Shiny' Interface Included) + maintainer: Olivier Delaigue + description: Add-on package to the 'airGR' package that simplifies its use and is + aimed at being used for teaching hydrology. The package provides 1) three functions + that allow to complete very simply a hydrological modelling exercise 2) plotting + functions to help students to explore observed data and to interpret the results + of calibration and simulation of the GR ('Génie rural') models 3) a 'Shiny' graphical + interface that allows for displaying the impact of model parameters on hydrographs + and models internal variables. + date_publication: '2025-02-11' + bug_reports: https://gitlab.irstea.fr/HYCAR-Hydro/airgrteaching/-/issues + url: https://hydrogr.github.io/airGRteaching/ + url_cran: https://CRAN.R-project.org/package=airGRteaching + url_git: '' +aiRly: + version: 0.1.0 + title: R Wrapper for 'Airly' API + maintainer: Piotr Janus + description: Get information about air quality using 'Airly' + API through R. + date_publication: '2020-03-19' + bug_reports: https://github.com/piotrekjanus/aiRly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aiRly + url_git: https://github.com/piotrekjanus/aiRly +AirMonitor: + version: 0.4.2 + title: Air Quality Data Analysis + maintainer: Jonathan Callahan + description: |- + Utilities for working with hourly air quality monitoring data + with a focus on small particulates (PM2.5). A compact data model is + structured as a list with two dataframes. A 'meta' dataframe contains + spatial and measuring device metadata associated with deployments at known + locations. A 'data' dataframe contains a 'datetime' column followed by + columns of measurements associated with each "device-deployment". + Algorithms to calculate NowCast and the associated Air Quality Index (AQI) + are defined at the US Environmental Projection Agency AirNow program: + . + date_publication: '2024-09-27' + bug_reports: https://github.com/MazamaScience/AirMonitor/issues + url: https://mazamascience.github.io/AirMonitor/ + url_cran: https://CRAN.R-project.org/package=AirMonitor + url_git: https://github.com/MazamaScience/AirMonitor +airnow: + version: 0.1.0 + title: Retrieve 'AirNow' Air Quality Observations and Forecasts + maintainer: Brian Connelly + description: |- + Retrieve air quality data via the 'AirNow' + API. + date_publication: '2022-10-31' + bug_reports: https://github.com/briandconnelly/airnow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=airnow + url_git: https://github.com/briandconnelly/airnow +airportr: + version: 0.1.3 + title: Convenience Tools for Working with Airport Data + maintainer: Dmitry Shkolnik + description: Retrieves open source airport data and provides tools to look up information, + translate names into codes and vice-verse, as well as some basic calculation functions + for measuring distances. Data is licensed under the Open Database License. + date_publication: '2019-10-09' + bug_reports: https://github.com/dshkol/airportr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=airportr + url_git: https://github.com/dshkol/airportr +airports: + version: 0.1.0 + title: Data on Airports + maintainer: Mine Çetinkaya-Rundel + description: Geographic, use, and property related data on airports. + date_publication: '2020-06-29' + bug_reports: https://github.com/OpenIntroStat/airports/issues + url: '' + url_cran: https://CRAN.R-project.org/package=airports + url_git: https://github.com/OpenIntroStat/airports +airqualityES: + version: 1.0.0 + title: Air Quality Measurements in Spain from 2011 to 2018 + maintainer: Jose V. Die + description: |- + These dataset contains daily quality air measurements in + Spain over a period of 18 years (from 2001 to 2018). The measurements refer to + several pollutants. These data are openly published by the Government of Spain. + The datasets were originally spread over a number of files and formats. Here, + the same information is contained in simple dataframe for convenience of + researches, journalists or general public. See the Spanish Government website + for more information. + date_publication: '2020-02-29' + bug_reports: https://github.com/jdieramon/airqualityES/issues + url: '' + url_cran: https://CRAN.R-project.org/package=airqualityES + url_git: https://github.com/jdieramon/airqualityES +airr: + version: 1.5.0 + title: AIRR Data Representation Reference Library + maintainer: Jason Vander Heiden + description: |- + Schema definitions and read, write and validation tools for data + formatted in accordance with the AIRR Data Representation schemas defined + by the AIRR Community . + date_publication: '2023-08-29' + bug_reports: https://github.com/airr-community/airr-standards/issues + url: http://docs.airr-community.org + url_cran: https://CRAN.R-project.org/package=airr + url_git: '' +airship: + version: 1.4.3 + title: |- + Visualization of Simulated Datasets with Multiple Simulation + Input Dimensions + maintainer: Elias Laurin Meyer + description: Plots simulation results of clinical trials. Its main feature is allowing + users to simultaneously investigate the impact of several simulation input dimensions + through dynamic filtering of the simulation results. A more detailed description + of the app can be found in Meyer et al. or the + vignettes on 'GitHub'. + date_publication: '2024-12-05' + bug_reports: https://github.com/el-meyer/airship/issues + url: '' + url_cran: https://CRAN.R-project.org/package=airship + url_git: '' +airt: + version: 0.2.2 + title: Evaluation of Algorithm Collections Using Item Response Theory + maintainer: Sevvandi Kandanaarachchi + description: |- + An evaluation framework for algorithm portfolios using Item Response + Theory (IRT). We use continuous and polytomous IRT models to evaluate algorithms and introduce + algorithm characteristics such as stability, effectiveness and anomalousness + (Kandanaarachchi, Smith-Miles 2020) . + date_publication: '2023-08-08' + bug_reports: '' + url: https://sevvandi.github.io/airt/ + url_cran: https://CRAN.R-project.org/package=airt + url_git: '' +aiRthermo: + version: 1.2.1 + title: Atmospheric Thermodynamics and Visualization + maintainer: Santos J. González-Rojí + description: Deals with many computations related to the thermodynamics of atmospheric + processes. It includes many functions designed to consider the density of air + with varying degrees of water vapour in it, saturation pressures and mixing ratios, + conversion of moisture indices, computation of atmospheric states of parcels subject + to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices + that are routinely used for operational weather forecasts or meteorological diagnostics. + date_publication: '2018-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aiRthermo + url_git: '' +AIscreenR: + version: 0.1.1 + title: AI Screening Tools in R for Systematic Reviewing + maintainer: Mikkel H. Vembye + description: Provides functions to conduct title and abstract screening in systematic + reviews using large language models, such as the Generative Pre-trained Transformer + (GPT) models from 'OpenAI' . These functions can + enhance the quality of title and abstract screenings while reducing the total + screening time significantly. In addition, the package includes tools for quality + assessment of title and abstract screenings, as described in Vembye, Christensen, + Mølgaard, and Schytt (2024) . + date_publication: '2024-11-26' + bug_reports: https://github.com/MikkelVembye/AIscreenR/issues + url: https://mikkelvembye.github.io/AIscreenR/ + url_cran: https://CRAN.R-project.org/package=AIscreenR + url_git: https://github.com/MikkelVembye/AIscreenR +aisoph: + version: '0.4' + title: Additive Isotonic Proportional Hazards Model + maintainer: Yunro Chung + description: Nonparametric estimation of additive isotonic covariate effects for + proportional hazards model. + date_publication: '2023-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aisoph + url_git: '' +AIUQ: + version: 0.5.3 + title: Ab Initio Uncertainty Quantification + maintainer: Mengyang Gu + description: 'Uncertainty quantification and inverse estimation by probabilistic + generative models from the beginning of the data analysis. An example is a Fourier + basis method for inverse estimation in scattering analysis of microscopy videos. + It does not require specifying a certain range of Fourier bases and it substantially + reduces computational cost via the generalized Schur algorithm. See the reference: + Mengyang Gu, Yue He, Xubo Liu and Yimin Luo (2023), .' + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AIUQ + url_git: '' +ajv: + version: 1.0.0 + title: Another JSON Schema Validator + maintainer: Jason Thorpe + description: |- + A thin wrapper around the 'ajv' JSON validation package for + JavaScript. See for details. + date_publication: '2017-04-24' + bug_reports: https://github.com/jdthorpe/ajvr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ajv + url_git: https://github.com/jdthorpe/ajvr +aka: + version: 0.1.0 + title: Define Aliases for R Expressions + maintainer: Konrad Rudolph + description: 'Create aliases for other R names or arbitrarily complex R expressions. + Accessing the alias acts as-if the aliased expression were invoked instead, and + continuously reflects the current value of that expression: updates to the original + expression will be reflected in the alias; and updates to the alias will automatically + be reflected in the original expression.' + date_publication: '2024-07-23' + bug_reports: https://github.com/klmr/aka/issues + url: https://klmr.me/aka/ + url_cran: https://CRAN.R-project.org/package=aka + url_git: https://github.com/klmr/aka +akc: + version: 0.9.9.1 + title: Automatic Knowledge Classification + maintainer: Tian-Yuan Huang + description: A tidy framework for automatic knowledge classification and visualization. + Currently, the core functionality of the framework is mainly supported by modularity-based + clustering (community detection) in keyword co-occurrence network, and focuses + on co-word analysis of bibliometric research. However, the designed functions + in 'akc' are general, and could be extended to solve other tasks in text mining + as well. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=akc + url_git: https://github.com/hope-data-science/akc +Ake: + version: 1.0.1 + title: Associated Kernel Estimations + maintainer: W. E. Wansouwé + description: Continuous and discrete (count or categorical) estimation of density, + probability mass function (p.m.f.) and regression functions are performed using associated + kernels. The cross-validation technique and the local Bayesian procedure are + also implemented for bandwidth selection. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ake + url_git: '' +akiFlagger: + version: 0.3.0 + title: Flags Acute Kidney Injury (AKI) + maintainer: Ishan Saran + description: Flagger to detect acute kidney injury (AKI) in a patient dataset. + date_publication: '2021-04-07' + bug_reports: https://github.com/isaranwrap/akiFlagger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=akiFlagger + url_git: https://github.com/isaranwrap/akiFlagger +akima: + version: 0.6-3.4 + title: Interpolation of Irregularly and Regularly Spaced Data + maintainer: Albrecht Gebhardt + description: |- + Several cubic spline interpolation methods of H. Akima for irregular and + regular gridded data are available through this package, both for the bivariate case + (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697). + Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas + triangulation code which is part of Akimas Fortran code. A bilinear interpolator + for regular grids was also added for comparison with the bicubic interpolator on + regular grids. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=akima + url_git: '' +akmbiclust: + version: 0.1.0 + title: Alternating K-Means Biclustering + maintainer: Zichao Li + description: Implements the alternating k-means biclustering algorithm in Fraiman + and Li (2020) . + date_publication: '2020-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=akmbiclust + url_git: '' +alabama: + version: 2023.1.0 + title: Constrained Nonlinear Optimization + maintainer: Ravi Varadhan + description: |- + Augmented Lagrangian Adaptive Barrier Minimization + Algorithm for optimizing smooth nonlinear objective functions + with constraints. Linear or nonlinear equality and inequality + constraints are allowed. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alabama + url_git: '' +alakazam: + version: 1.3.0 + title: Immunoglobulin Clonal Lineage and Diversity Analysis + maintainer: Susanna Marquez + description: |- + Provides methods for high-throughput adaptive immune + receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In + particular, immunoglobulin (Ig) sequence lineage reconstruction, + lineage topology analysis, diversity profiling, amino acid property + analysis and gene usage. + Citations: + Gupta and Vander Heiden, et al (2017) , + Stern, Yaari and Vander Heiden, et al (2014) . + date_publication: '2023-09-30' + bug_reports: https://bitbucket.org/kleinstein/alakazam/issues + url: https://alakazam.readthedocs.io/ + url_cran: https://CRAN.R-project.org/package=alakazam + url_git: '' +alarmdata: + version: 0.2.1 + title: Download, Merge, and Process Redistricting Data + maintainer: Cory McCartan + description: |2- + + Utility functions to download and process data produced by the ALARM Project, + including 2020 redistricting files Kenny and McCartan (2021) + and the 50-State + Redistricting Simulations of McCartan, Kenny, Simko, Garcia, Wang, Wu, + Kuriwaki, and Imai (2022) . The package extends + the data introduced in McCartan, Kenny, Simko, Garcia, Wang, Wu, Kuriwaki, + and Imai (2022) to also include states with + only a single district. + date_publication: '2024-02-28' + bug_reports: https://github.com/alarm-redist/alarmdata/issues/ + url: https://alarm-redist.org/alarmdata/ + url_cran: https://CRAN.R-project.org/package=alarmdata + url_git: https://github.com/alarm-redist/alarmdata/ +ALassoSurvIC: + version: 0.1.1 + title: |- + Adaptive Lasso for the Cox Regression with Interval Censored and + Possibly Left Truncated Data + maintainer: Daewoo Pak + description: |- + Penalized variable selection tools for the Cox + proportional hazards model with interval censored and possibly + left truncated data. It performs variable selection via + penalized nonparametric maximum likelihood estimation with an + adaptive lasso penalty. The optimal thresholding parameter can be + searched by the package based on the profile Bayesian information + criterion (BIC). The asymptotic validity of the methodology is + established in Li et al. (2019 ). + The unpenalized nonparametric maximum likelihood estimation for + interval censored and possibly left truncated data is also + available. + date_publication: '2022-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALassoSurvIC + url_git: '' +albatross: + version: 0.3-8 + title: PARAFAC Analysis of Fluorescence Excitation-Emission Matrices + maintainer: Ivan Krylov + description: |- + Perform parallel factor analysis (PARAFAC: Hitchcock, 1927) + on fluorescence excitation-emission + matrices: handle scattering signal and inner filter effect, scale + the dataset, fit the model; perform split-half validation or + jack-knifing. Modified approaches such as Whittaker interpolation, + randomised split-half, and fluorescence and scattering model + estimation are also available. The package has a low dependency + footprint and has been tested on a wide range of R versions. + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=albatross + url_git: '' +aLBI: + version: 0.1.7 + title: Estimating Length-Based Indicators for Fish Stock + maintainer: Ataher Ali + description: |- + Provides tools for estimating length-based indicators from length frequency data to assess fish stock status and manage fisheries sustainably. Implements methods from Cope and Punt (2009) for data-limited stock assessment and Froese (2004) for detecting overfishing using simple indicators. Key functions include: + FrequencyTable(): Calculate the frequency table from the collected and also the extract the length frequency data from the frequency table with the upper length_range. A numeric value specifying the bin width for class intervals. If not provided, the bin width is automatically calculated using Sturges (1926) formula. + CalPar(): Calculates various lengths used in fish stock assessment as biological length indicators such as asymptotic length (Linf), maximum length (Lmax), length at sexual maturity (Lm), and optimal length (Lopt). + FishPar(): Calculates length-based indicators (LBIs) proposed by Froese (2004) such as the percentage of mature fish (Pmat), percentage of optimal length fish (Popt), percentage of mega spawners (Pmega), and the sum of these as Pobj. This function also estimates confidence intervals for different lengths, visualizes length frequency distributions, and provides data frames containing calculated values. + FishSS(): Makes decisions based on input from Cope and Punt (2009) and parameters calculated by FishPar() (e.g., Pobj, Pmat, Popt, LM_ratio) to determine stock status as target spawning biomass (TSB40) and limit spawning biomass (LSB25). These tools support fisheries management decisions by providing robust, data-driven insights. + date_publication: '2024-11-21' + bug_reports: https://github.com/Ataher76/aLBI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aLBI + url_git: https://github.com/Ataher76/aLBI +albopictus: + version: '0.5' + title: Age-Structured Population Dynamics Model + maintainer: Kamil Erguler + description: Implements discrete time deterministic and stochastic age-structured + population dynamics models described in Erguler and others (2016) + and Erguler and others (2017) . + date_publication: '2018-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=albopictus + url_git: https://github.com/kerguler/albopictusR +alcyon: + version: 0.7.0 + title: Spatial Network Analysis + maintainer: Petros Koutsolampros + description: |- + Interface package for 'sala', the spatial network analysis library + from the 'depthmapX' software application. The R parts of the code are based + on the 'rdepthmap' package. Allows for the analysis of urban and + building-scale networks and provides metrics and methods usually found + within the Space Syntax domain. Methods in this package are described by K. + Al-Sayed, A. Turner, B. Hillier, S. Iida and A. Penn (2014) "Space Syntax + methodology", and also by A. Turner (2004) + "Depthmap 4: a researcher's + handbook". + date_publication: '2025-01-21' + bug_reports: '' + url: https://spatialnous.github.io/alcyon/ + url_cran: https://CRAN.R-project.org/package=alcyon + url_git: https://github.com/spatialnous/alcyon +ald: + version: 1.3.1 + title: The Asymmetric Laplace Distribution + maintainer: Christian E. Galarza + description: |- + It provides the density, distribution function, quantile function, + random number generator, likelihood function, moments and Maximum Likelihood estimators for a given sample, all this for + the three parameter Asymmetric Laplace Distribution defined + in Koenker and Machado (1999). This is a special case of the skewed family of distributions + available in Galarza et.al. (2017) useful for quantile regression. + date_publication: '2021-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ald + url_git: '' +ALDqr: + version: '1.0' + title: Quantile Regression Using Asymmetric Laplace Distribution + maintainer: Luis Benites Sanchez + description: EM algorithm for estimation of parameters and other methods in a quantile + regression. + date_publication: '2017-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALDqr + url_git: '' +aldvmm: + version: 0.8.8 + title: Adjusted Limited Dependent Variable Mixture Models + maintainer: Mark Pletscher + description: |- + The goal of the package 'aldvmm' is to fit adjusted limited + dependent variable mixture models of health state utilities. Adjusted + limited dependent variable mixture models are finite mixtures of normal + distributions with an accumulation of density mass at the limits, and a gap + between 100% quality of life and the next smaller utility value. The + package 'aldvmm' uses the likelihood and expected value functions proposed + by Hernandez Alava and Wailoo (2015) using + normal component distributions and a multinomial logit model of + probabilities of component membership. + date_publication: '2023-10-28' + bug_reports: https://github.com/pletschm/aldvmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aldvmm + url_git: https://github.com/pletschm/aldvmm/ +ale: + version: 0.3.0 + title: |- + Interpretable Machine Learning and Statistical Inference with + Accumulated Local Effects (ALE) + maintainer: Chitu Okoli + description: 'Accumulated Local Effects (ALE) were initially developed as a model-agnostic + approach for global explanations of the results of black-box machine learning + algorithms. ALE has a key advantage over other approaches like partial dependency + plots (PDP) and SHapley Additive exPlanations (SHAP): its values represent a clean + functional decomposition of the model. As such, ALE values are not affected by + the presence or absence of interactions among variables in a mode. Moreover, its + computation is relatively rapid. This package rewrites the original code from + the ''ALEPlot'' package for calculating ALE data and it completely reimplements + the plotting of ALE values. It also extends the original ALE concept to add bootstrap-based + confidence intervals and ALE-based statistics that can be used for statistical + inference. For more details, see Okoli, Chitu. 2023. “Statistical Inference Using + Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” + arXiv. . .' + date_publication: '2024-02-14' + bug_reports: https://github.com/tripartio/ale/issues + url: https://tripartio.github.io/ale/ + url_cran: https://CRAN.R-project.org/package=ale + url_git: https://github.com/tripartio/ale +ALEPlot: + version: '1.1' + title: |- + Accumulated Local Effects (ALE) Plots and Partial Dependence + (PD) Plots + maintainer: Dan Apley + description: Visualizes the main effects of individual predictor variables and their + second-order interaction effects in black-box supervised learning models. The + package creates either Accumulated Local Effects (ALE) plots and/or Partial Dependence + (PD) plots, given a fitted supervised learning model. + date_publication: '2018-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALEPlot + url_git: '' +ALFAM2: + version: '4.2' + title: Dynamic Model of Ammonia Emission from Field-Applied Manure + maintainer: Sasha D. Hafner + description: An implementation of the ALFAM2 dynamic emission model for ammonia + volatilization from field-applied animal slurry (manure with dry matter below + about 15%). The model can be used to predict cumulative emission and emission + rate of ammonia following field application of slurry. Predictions may be useful + for emission inventory calculations, fertilizer management, assessment of mitigation + strategies, or research aimed at understanding ammonia emission. Default parameter + sets include effects of application method, slurry composition, and weather. The + model structure is based on a simplified representation of the physical-chemical + slurry-soil-atmosphere system. See Hafner et al. (2018) + for information on the model and Hafner et al. (2019) + for more on the measurement data used for parameter development. + date_publication: '2024-11-08' + bug_reports: '' + url: https://projects.au.dk/alfam/ + url_cran: https://CRAN.R-project.org/package=ALFAM2 + url_git: https://github.com/AU-BCE-EE/ALFAM2/ +aLFQ: + version: 1.3.6 + title: |- + Estimating Absolute Protein Quantities from Label-Free LC-MS/MS + Proteomics Data + maintainer: George Rosenberger + description: Determination of absolute protein quantities is necessary for multiple + applications, such as mechanistic modeling of biological systems. Quantitative + liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics can measure + relative protein abundance on a system-wide scale. To estimate absolute quantitative + information using these relative abundance measurements requires additional information + such as heavy-labeled references of known concentration. Multiple methods have + been using different references and strategies; some are easily available whereas + others require more effort on the users end. Hence, we believe the field might + benefit from making some of these methods available under an automated framework, + which also facilitates validation of the chosen strategy. We have implemented + the most commonly used absolute label-free protein abundance estimation methods + for LC-MS/MS modes quantifying on either MS1-, MS2-levels or spectral counts together + with validation algorithms to enable automated data analysis and error estimation. + Specifically, we used Monte-carlo cross-validation and bootstrapping for model + selection and imputation of proteome-wide absolute protein quantity estimation. + Our open-source software is written in the statistical programming language R + and validated and demonstrated on a synthetic sample. + date_publication: '2020-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aLFQ + url_git: https://github.com/aLFQ +alfr: + version: 1.2.1 + title: Connectivity to 'Alfresco' Content Management Repositories + maintainer: Roy Wetherall + description: |- + Allows you to connect to an 'Alfresco' content management repository and interact + with its contents using simple and intuitive functions. You will be able to establish a connection session to the 'Alfresco' repository, + read and upload content and manage folder hierarchies. For more details on the 'Alfresco' content management repository + see . + date_publication: '2019-07-19' + bug_reports: https://github.com/rwetherall/alfr/issues + url: https://rwetherall.github.io/alfr/ + url_cran: https://CRAN.R-project.org/package=alfr + url_git: https://github.com/rwetherall/alfr +alfred: + version: 0.2.1 + title: |- + Downloading Time Series from ALFRED Database for Various + Vintages + maintainer: Onno Kleen + description: |- + Provides direct access to the ALFRED () and FRED () databases. + Its functions return tidy data frames for different releases of the specified time series. + Note that this product uses the FRED© API but is not endorsed or certified by the Federal Reserve Bank of St. Louis. + date_publication: '2023-03-21' + bug_reports: https://github.com/onnokleen/alfred/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alfred + url_git: https://github.com/onnokleen/alfred/ +AlgDesign: + version: 1.2.1.1 + title: Algorithmic Experimental Design + maintainer: Jerome Braun + description: |- + Algorithmic experimental designs. Calculates exact and + approximate theory experimental designs for D,A, and I + criteria. Very large designs may be created. Experimental + designs may be blocked or blocked designs created from a + candidate list, using several criteria. The blocking can be + done when whole and within plot factors interact. + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AlgDesign + url_git: https://github.com/jvbraun/AlgDesign +AlgebraicHaploPackage: + version: '1.2' + title: Haplotype Two Snips Out of a Paired Group of Patients + maintainer: Jan Wolfertz + description: Two unordered pairs of data of two different snips positions is haplotyped + by resolving a small number ob closed equations. + date_publication: '2015-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AlgebraicHaploPackage + url_git: '' +algo: + version: 0.1.0 + title: |- + Implement an Address Search Auto Completion Menu on 'Shiny' Text + Inputs Using the 'Algolia Places' 'Javascript' Library + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to implement an address search auto completion menu on 'shiny' text inputs. + This is done using the 'Algolia Places' 'JavaScript' library. See . + date_publication: '2020-06-24' + bug_reports: https://github.com/feddelegrand7/algo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=algo + url_git: https://github.com/feddelegrand7/algo +algorithmia: + version: 0.3.0 + title: Allows you to Easily Interact with the Algorithmia Platform + maintainer: Robert Fulton + description: |- + The company, Algorithmia, houses the largest marketplace of online + algorithms. This package essentially holds a bunch of REST wrappers that + make it very easy to call algorithms in the Algorithmia platform and access + files and directories in the Algorithmia data API. To learn more about the + services they offer and the algorithms in the platform visit + . More information for developers can be found at + . + date_publication: '2020-10-12' + bug_reports: https://github.com/algorithmiaio/algorithmia-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=algorithmia + url_git: '' +aliases2entrez: + version: 0.1.2 + title: Converts Human gene symbols to entrez IDs + maintainer: Raphael Bonnet + description: |- + Queries multiple resources authors HGNC (2019) , authors limma (2015) + to find the correspondence between evolving nomenclature of human gene symbols, aliases, previous symbols or synonyms with + stable, curated gene entrezID from NCBI database. This allows fast, accurate and up-to-date correspondence + between human gene expression datasets from various date and platform (e.g: gene symbol: BRCA1 - ID: 672). + date_publication: '2021-02-15' + bug_reports: https://github.com/peyronlab/aliases2entrez/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aliases2entrez + url_git: '' +alien: + version: 1.0.2 + title: Estimate Invasive and Alien Species (IAS) Introduction Rates + maintainer: Yehezkel Buba + description: |- + Easily estimate the introduction rates of alien species given first records data. + It specializes in addressing the role of sampling on the pattern of discoveries, + thus providing better estimates than using Generalized Linear Models which assume perfect + immediate detection of newly introduced species. + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alien + url_git: '' +align: + version: 0.1.0 + title: A Modified DTW Algorithm for Stratigraphic Time Series Alignment + maintainer: Cedric Hagen + description: |- + A dynamic time warping (DTW) algorithm for stratigraphic alignment, + translated into R from the original published 'MATLAB' code by Hay et al. (2019) + . The DTW algorithm incorporates two geologically relevant + parameters (g and edge) for augmenting the typical DTW cost matrix, allowing + for a range of sedimentologic and chronologic conditions to be explored, as + well as the generation of an alignment library (as opposed to a single alignment + solution). The g parameter relates to the relative sediment accumulation rate + between the two time series records, while the edge parameter relates to the + amount of total shared time between the records. Note that this algorithm is + used for all DTW alignments in the Align Shiny application, detailed in Hagen + et al. (in review). + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=align + url_git: '' +AlignLV: + version: 0.1.0.0 + title: |- + Multiple Group Item Response Theory Alignment Helpers for + 'lavaan' and 'mirt' + maintainer: Maxwell Mansolf + description: Allows for multiple group item response theory alignment a la 'Mplus' + to be applied to lists of single-group models estimated in 'lavaan' or 'mirt'. + Allows item sets that are overlapping but not identical, facilitating alignment + in secondary data analysis where not all items may be shared across assessments. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AlignLV + url_git: '' +alkahest: + version: 1.3.0 + title: Pre-Processing XY Data from Experimental Methods + maintainer: Nicolas Frerebeau + description: |- + A lightweight, dependency-free toolbox for pre-processing XY + data from experimental methods (i.e. any signal that can be measured + along a continuous variable). This package provides methods for + baseline estimation and correction, smoothing, normalization, + integration and peaks detection. Baseline correction methods includes + polynomial fitting as described in Lieber and Mahadevan-Jansen (2003) + , Rolling Ball algorithm after Kneen + and Annegarn (1996) , SNIP algorithm + after Ryan et al. (1988) , 4S Peak + Filling after Liland (2015) and more. + date_publication: '2025-02-25' + bug_reports: https://codeberg.org/tesselle/alkahest/issues + url: https://codeberg.org/tesselle/alkahest + url_cran: https://CRAN.R-project.org/package=alkahest + url_git: '' +allcontributors: + version: 0.2.2 + title: Acknowledge all Contributors to a Project + maintainer: Mark Padgham + description: |- + Acknowledge all contributors to a project via a single + function call. The function appends to a 'README' or other specified + file(s) a table with names of all individuals who contributed via code + or repository issues. The package also includes several additional + functions to extract and quantify contributions to any repository. + date_publication: '2024-10-23' + bug_reports: https://github.com/ropensci/allcontributors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=allcontributors + url_git: https://github.com/ropensci/allcontributors +alleHap: + version: 0.9.9 + title: |- + Allele Imputation and Haplotype Reconstruction from Pedigree + Databases + maintainer: Nathan Medina-Rodriguez + description: |- + Tools to simulate alphanumeric alleles, impute genetic missing data and reconstruct non-recombinant haplotypes from pedigree databases in a deterministic way. Allelic simulations can be implemented taking into account many factors (such as number of families, markers, alleles per marker, + probability and proportion of missing genotypes, recombination rate, etc). + Genotype imputation can be used with simulated datasets or real databases (previously loaded in .ped format). Haplotype reconstruction can be carried + out even with missing data, since the program firstly imputes each family genotype (without a reference panel), to later reconstruct the corresponding + haplotypes for each family member. All this considering that each individual (due to meiosis) should unequivocally have two alleles per marker (one inherited + from each parent) and thus imputation and reconstruction results can be deterministically calculated. + date_publication: '2017-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alleHap + url_git: '' +allelematch: + version: 2.5.4 + title: |- + Identifying Unique Multilocus Genotypes where Genotyping Error + and Missing Data may be Present + maintainer: Todd Cross + description: Tools for the identification of unique of multilocus genotypes when + both genotyping error and missing data may be present; targeted for use with large + datasets and databases containing multiple samples of each individual (a common + situation in conservation genetics, particularly in non-invasive wildlife sampling + applications). Functions explicitly incorporate missing data and can tolerate + allele mismatches created by genotyping error. If you use this package, please + cite the original publication in Molecular Ecology Resources (Galpern et al., + 2012), the details for which can be generated using citation('allelematch'). For + a complete vignette, please access via the Data S1 Supplementary documentation + and tutorials (PDF) located at . + date_publication: '2024-03-28' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=allelematch + url_git: '' +AlleleRetain: + version: 2.0.2 + title: Allele Retention, Inbreeding, and Demography + maintainer: Emily Weiser + description: Simulate the effect of management or demography on allele retention + and inbreeding accumulation in bottlenecked populations of animals with overlapping + generations. + date_publication: '2018-01-11' + bug_reports: '' + url: https://sites.google.com/site/alleleretain/ + url_cran: https://CRAN.R-project.org/package=AlleleRetain + url_git: '' +AlleleShift: + version: 1.1-2 + title: |- + Predict and Visualize Population-Level Changes in Allele + Frequencies in Response to Climate Change + maintainer: Roeland Kindt + description: Methods () are provided of calibrating and + predicting shifts in allele frequencies through redundancy analysis ('vegan::rda()') + and generalized additive models ('mgcv::gam()'). Visualization functions for predicted + changes in allele frequencies include 'shift.dot.ggplot()', 'shift.pie.ggplot()', + 'shift.moon.ggplot()', 'shift.waffle.ggplot()' and 'shift.surf.ggplot()' that + are made with input data sets that are prepared by helper functions for each visualization + method. Examples in the documentation show how to prepare animated climate change + graphics through a time series with the 'gganimate' package. Function 'amova.rda()' + shows how Analysis of Molecular Variance can be directly conducted with the results + from redundancy analysis. + date_publication: '2023-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AlleleShift + url_git: '' +AllelicSeries: + version: 0.1.1.2 + title: Allelic Series Test + maintainer: Zachary McCaw + description: 'Implementation of gene-level rare variant association tests targeting + allelic series: genes where increasingly deleterious mutations have increasingly + large phenotypic effects. The COding-variant Allelic Series Test (COAST) operates + on the benign missense variants (BMVs), deleterious missense variants (DMVs), + and protein truncating variants (PTVs) within a gene. COAST uses a set of adjustable + weights that tailor the test towards rejecting the null hypothesis for genes where + the average magnitude of effect increases monotonically from BMVs to DMVs to PTVs. + See McCaw ZR, O’Dushlaine C, Somineni H, Bereket M, Klein C, Karaletsos T, Casale + FP, Koller D, Soare TW. (2023) "An allelic series rare variant association test + for candidate gene discovery" .' + date_publication: '2024-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AllelicSeries + url_git: https://github.com/insitro/AllelicSeries +allestimates: + version: 0.2.3 + title: Effect Estimates from All Models + maintainer: Zhiqiang Wang + description: |- + Estimates and plots effect estimates from models with all possible + combinations of a list of variables. It can be used for assessing treatment + effects in clinical trials or risk factors in bio-medical and epidemiological + research. Like Stata command 'confall' (Wang Z (2007) ), + 'allestimates' calculates and stores all effect estimates, and plots them against p values or + Akaike information criterion (AIC) values. It currently has functions for linear + regression: all_lm(), logistic and Poisson regression: all_glm(), + and Cox proportional hazards regression: all_cox(). + date_publication: '2023-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=allestimates + url_git: '' +AllMetrics: + version: 0.2.1 + title: Calculating Multiple Performance Metrics of a Prediction Model + maintainer: Dr. Sandip Garai + description: Provides a function to calculate multiple performance metrics for actual + and predicted values. In total eight metrics will be calculated for particular + actual and predicted series. Helps to describe a Statistical model's performance + in predicting a data. Also helps to compare various models' performance. The metrics + are Root Mean Squared Error (RMSE), Relative Root Mean Squared Error (RRMSE), + Mean absolute Error (MAE), Mean absolute percentage error (MAPE), Mean Absolute + Scaled Error (MASE), Nash-Sutcliffe Efficiency (NSE), Willmott’s Index (WI), and + Legates and McCabe Index (LME). Among them, first five are expected to be lesser + whereas, the last three are greater the better. More details can be found from + Garai and Paul (2023) and Garai et al. (2024) + . + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AllMetrics + url_git: '' +allMT: + version: 0.1.0 + title: Acute Lymphoblastic Leukemia Maintenance Therapy Analysis + maintainer: Tushar Mungle + description: Evaluates acute lymphoblastic leukemia maintenance therapy practice + at patient and cohort level. + date_publication: '2023-04-20' + bug_reports: https://github.com/tmungle/allMT/issues + url: https://tmungle.github.io/allMT/ + url_cran: https://CRAN.R-project.org/package=allMT + url_git: https://github.com/tmungle/allMT +allofus: + version: 1.2.0 + title: Interface for 'All of Us' Researcher Workbench + maintainer: Rob Cavanaugh + description: Streamline use of the 'All of Us' Researcher Workbench ()with + tools to extract and manipulate data from the 'All of Us' database. Increase interoperability + with the Observational Health Data Science and Informatics ('OHDSI') tool stack + by decreasing reliance of 'All of Us' tools and allowing for cohort creation via + 'Atlas'. Improve reproducible and transparent research using 'All of Us'. + date_publication: '2024-11-06' + bug_reports: https://github.com/roux-ohdsi/allofus/issues + url: https://roux-ohdsi.github.io/allofus/ + url_cran: https://CRAN.R-project.org/package=allofus + url_git: https://github.com/roux-ohdsi/allofus +allomr: + version: 0.3.0 + title: |- + Removing Allometric Effects of Body Size in Morphological + Analysis + maintainer: Sämi Schär + description: |- + Implementation of the technique of Lleonart et al. + (2000) to scale body measurements + that exhibit an allometric growth. This procedure is a theoretical + generalization of the technique used by Thorpe + (1975) and + Thorpe (1976) . + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=allomr + url_git: '' +Allspice: + version: 1.0.7 + title: RNA-Seq Profile Classifier + maintainer: Ville-Petteri Makinen + description: We developed a lightweight machine learning tool for RNA profiling + of acute lymphoblastic leukemia (ALL), however, it can be used for any problem + where multiple classes need to be identified from multi-dimensional data. The + methodology is described in Makinen V-P, Rehn J, Breen J, Yeung D, White DL (2022) + Multi-cohort transcriptomic subtyping of B-cell acute lymphoblastic leukemia, + International Journal of Molecular Sciences 23:4574, . + The classifier contains optimized mean profiles of the classes (centroids) as + observed in the training data, and new samples are matched to these centroids + using the shortest Euclidean distance. Centroids derived from a dataset of 1,598 + ALL patients are included, but users can train the models with their own data + as well. The output includes both numerical and visual presentations of the classification + results. Samples with mixed features from multiple classes or atypical values + are also identified. + date_publication: '2023-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Allspice + url_git: '' +ALLSPICER: + version: 0.1.9 + title: ALLelic Spectrum of Pleiotropy Informed Correlated Effects + maintainer: Wenhan Lu + description: Provides statistical tools to analyze heterogeneous effects of rare + variants within genes that are associated with multiple traits. The package implements + methods for assessing pleiotropic effects and identifying allelic heterogeneity, + which can be useful in large-scale genetic studies. Methods include likelihood-based + statistical tests to assess these effects. For more details, see Lu et al. (2024) + . + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALLSPICER + url_git: '' +alluvial: + version: 0.1-2 + title: Alluvial Diagrams + maintainer: Michal Bojanowski + description: |- + Creating alluvial diagrams (also known as parallel sets plots) for multivariate + and time series-like data. + date_publication: '2016-09-09' + bug_reports: https://github.com/mbojan/alluvial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alluvial + url_git: https://github.com/mbojan/alluvial +almanac: + version: 1.0.0 + title: Tools for Working with Recurrence Rules + maintainer: Davis Vaughan + description: |- + Provides tools for defining recurrence rules and recurrence + sets. Recurrence rules are a programmatic way to define a recurring + event, like the first Monday of December. Multiple recurrence rules + can be combined into larger recurrence sets. A full holiday and + calendar interface is also provided that can generate holidays within + a particular year, can detect if a date is a holiday, can respect + holiday observance rules, and allows for custom holidays. + date_publication: '2023-04-13' + bug_reports: https://github.com/DavisVaughan/almanac/issues + url: '' + url_cran: https://CRAN.R-project.org/package=almanac + url_git: https://github.com/DavisVaughan/almanac +alone: + version: '0.5' + title: Datasets from the Survival TV Series Alone + maintainer: Daniel Oehm + description: |- + A collection of datasets on the Alone survival TV series in tidy format. + Included in the package are 4 datasets detailing the survivors, their loadouts, + episode details and season information. + date_publication: '2024-09-02' + bug_reports: https://github.com/doehm/alone/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alone + url_git: https://github.com/doehm/alone +alookr: + version: 0.3.9 + title: Model Classifier for Binary Classification + maintainer: Choonghyun Ryu + description: |- + A collection of tools that support data splitting, predictive modeling, and model evaluation. + A typical function is to split a dataset into a training dataset and a test dataset. + Then compare the data distribution of the two datasets. + Another feature is to support the development of predictive models and to compare the performance of several predictive models, + helping to select the best model. + date_publication: '2024-02-11' + bug_reports: https://github.com/choonghyunryu/alookr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alookr + url_git: '' +aloom: + version: 0.1.1 + title: All Leave-One-Out Models + maintainer: Damjan Krstajic + description: Creates all leave-one-out models and produces predictions for test + samples. + date_publication: '2024-01-08' + bug_reports: '' + url: https://www.rcc.org.rs/aloom.html + url_cran: https://CRAN.R-project.org/package=aloom + url_git: '' +alpaca: + version: 0.3.4 + title: Fit GLM's with High-Dimensional k-Way Fixed Effects + maintainer: Amrei Stammann + description: Provides a routine to partial out factors with many levels during the + optimization of the log-likelihood function of the corresponding generalized linear + model (glm). The package is based on the algorithm described in Stammann (2018) + and is restricted to glm's that are based on maximum likelihood + estimation and nonlinear. It also offers an efficient algorithm to recover estimates + of the fixed effects in a post-estimation routine and includes robust and multi-way + clustered standard errors. Further the package provides analytical bias corrections + for binary choice models derived by Fernandez-Val and Weidner (2016) + and Hinz, Stammann, and Wanner (2020) . + date_publication: '2022-08-10' + bug_reports: https://github.com/amrei-stammann/alpaca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alpaca + url_git: https://github.com/amrei-stammann/alpaca +alpha.correction.bh: + version: 0.0.1 + title: Benjamini-Hochberg Alpha Correction + maintainer: Michael Mogessie + description: 'Provides the alpha-adjustment correction from "Benjamini, Y., & Hochberg, + Y. (1995) Controlling the false discovery + rate: a practical and powerful approach to multiple testing. Journal of the Royal + statistical society: series B (Methodological), 57(1), 289-300". For researchers + interested in using the exact mathematical formulas and procedures as used in + the original paper.' + date_publication: '2023-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alpha.correction.bh + url_git: '' +alphabetr: + version: 0.2.2 + title: |- + Algorithms for High-Throughput Sequencing of Antigen-Specific T + Cells + maintainer: Edward Lee + description: |- + Provides algorithms for frequency-based pairing of alpha-beta T + cell receptors. + date_publication: '2017-01-28' + bug_reports: http://github.com/edwardslee/alphabetr + url: '' + url_cran: https://CRAN.R-project.org/package=alphabetr + url_git: http://github.com/edwardslee/alphabetr +alphaci: + version: 1.0.1 + title: |- + Confidence Intervals for Coefficient Alpha and Standardized + Alpha + maintainer: Jonas Moss + description: |- + Calculate confidence intervals for alpha and standardized + alpha using asymptotic theory or the studentized bootstrap, with or + without transformations. Supports the asymptotic distribution-free + method of Maydeu-Olivares, et al. (2007) + , the pseudo-elliptical method of Yuan + & Bentler (2002) , and the normal method of + van Zyl et al. (1999) , for both coefficient + alpha and standardized alpha. + date_publication: '2024-02-05' + bug_reports: '' + url: https://jonasmoss.github.io/alphaci/ + url_cran: https://CRAN.R-project.org/package=alphaci + url_git: '' +alphahull: + version: '2.5' + title: |- + Generalization of the Convex Hull of a Sample of Points in the + Plane + maintainer: Beatriz Pateiro-Lopez + description: |- + Computation of the alpha-shape and alpha-convex + hull of a given sample of points in the plane. The concepts of + alpha-shape and alpha-convex hull generalize the definition of + the convex hull of a finite set of points. The programming is + based on the duality between the Voronoi diagram and Delaunay + triangulation. The package also includes a function that + returns the Delaunay mesh of a given sample of points and its + dual Voronoi diagram in one single object. + date_publication: '2022-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alphahull + url_git: '' +alphaN: + version: 0.1.0 + title: Set Alpha Based on Sample Size Using Bayes Factors + maintainer: Jesper Wulff + description: |- + Sets the alpha level for coefficients in a regression model + as a decreasing function of the sample size through the use of + Jeffreys' Approximate Bayes factor. You tell alphaN() your sample + size, and it tells you to which value you must lower alpha to avoid + Lindley's Paradox. For details, see Wulff and Taylor (2023) + . + date_publication: '2023-01-12' + bug_reports: https://github.com/jespernwulff/alphaN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alphaN + url_git: https://github.com/jespernwulff/alphaN +alphaOutlier: + version: 1.2.0 + title: |- + Obtain Alpha-Outlier Regions for Well-Known Probability + Distributions + maintainer: Andre Rehage + description: 'Given the parameters of a distribution, the package uses the concept + of alpha-outliers by Davies and Gather (1993) to flag outliers in a data set. + See Davies, L.; Gather, U. (1993): The identification of multiple outliers, JASA, + 88 423, 782-792, for details.' + date_publication: '2016-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alphaOutlier + url_git: '' +AlphaPart: + version: 0.9.8 + title: |- + Partition/Decomposition of Breeding Values by Paths of + Information + maintainer: Gregor Gorjanc + description: |- + A software that implements a method for partitioning genetic trends to + quantify the sources of genetic gain in breeding programmes. + The partitioning method is described in Garcia-Cortes et al. + (2008) . The package includes the + main function AlphaPart for partitioning breeding values and auxiliary + functions for manipulating data and summarizing, visualizing, and saving + results. + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AlphaPart + url_git: '' +alphashape3d: + version: 1.3.2 + title: |- + Implementation of the 3D Alpha-Shape for the Reconstruction of + 3D Sets from a Point Cloud + maintainer: Beatriz Pateiro-Lopez + description: Implementation in R of the alpha-shape of a finite set of points in + the three-dimensional space. The alpha-shape generalizes the convex hull and allows + to recover the shape of non-convex and even non-connected sets in 3D, given a + random sample of points taken into it. Besides the computation of the alpha-shape, + this package provides users with functions to compute the volume of the alpha-shape, + identify the connected components and facilitate the three-dimensional graphical + visualization of the estimated set. + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alphashape3d + url_git: '' +AlphaSimR: + version: 1.6.1 + title: Breeding Program Simulations + maintainer: Chris Gaynor + description: |- + The successor to the 'AlphaSim' software for breeding program + simulation [Faux et al. (2016) ]. + Used for stochastic simulations of breeding programs to the level of DNA + sequence for every individual. Contained is a wide range of functions for + modeling common tasks in a breeding program, such as selection and crossing. + These functions allow for constructing simulations of highly complex plant and + animal breeding programs via scripting in the R software environment. Such + simulations can be used to evaluate overall breeding program performance and + conduct research into breeding program design, such as implementation of + genomic selection. Included is the 'Markovian Coalescent Simulator' ('MaCS') + for fast simulation of biallelic sequences according to a population + demographic history [Chen et al. (2009) ]. + date_publication: '2024-11-01' + bug_reports: '' + url: https://gaynorr.github.io/AlphaSimR/ + url_cran: https://CRAN.R-project.org/package=AlphaSimR + url_git: https://github.com/gaynorr/AlphaSimR +alphastable: + version: 0.2.1 + title: Inference for Stable Distribution + maintainer: Mahdi Teimouri + description: |- + Developed to perform the tasks given by the following. 1-computing the probability density function and distribution function of a univariate stable distribution; 2- generating from univariate stable, truncated stable, multivariate elliptically contoured stable, and bivariate strictly stable distributions; 3- estimating the parameters of univariate symmetric stable, skew stable, Cauchy, multivariate elliptically contoured stable, and multivariate strictly stable distributions; 4- estimating + the parameters of the mixture of symmetric stable and mixture of Cauchy distributions. + date_publication: '2019-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alphastable + url_git: '' +alphavantager: + version: 0.1.3 + title: Lightweight Interface to the Alpha Vantage API + maintainer: Matt Dancho + description: |2- + + Alpha Vantage has free historical financial information. + All you need to do is get a free API key at . + Then you can use the R interface to retrieve free equity information. + Refer to the Alpha Vantage website for more information. + date_publication: '2023-03-31' + bug_reports: https://github.com/business-science/alphavantager/issues + url: '' + url_cran: https://CRAN.R-project.org/package=alphavantager + url_git: https://github.com/business-science/alphavantager +alqrfe: + version: '1.1' + title: Adaptive Lasso Quantile Regression with Fixed Effects + maintainer: Ian Meneghel Danilevicz + description: Quantile regression with fixed effects solves longitudinal data, considering + the individual intercepts as fixed effects. The parametric set of this type of + problem used to be huge. Thus penalized methods such as Lasso are currently applied. + Adaptive Lasso presents oracle proprieties, which include Gaussianity and correct + model selection. Bayesian information criteria (BIC) estimates the optimal tuning + parameter lambda. Plot tools are also available. + date_publication: '2022-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=alqrfe + url_git: '' +alr4: + version: 1.0.6 + title: Data to Accompany Applied Linear Regression 4th Edition + maintainer: Sanford Weisberg + description: |- + Datasets to Accompany S. Weisberg (2014, ISBN: 978-1-118-38608-8), + "Applied Linear Regression," 4th edition. Many data files + in this package are included in the `alr3` package as well, so only one of them + should be used. + date_publication: '2018-04-20' + bug_reports: '' + url: http://www.z.umn.edu/alr4ed + url_cran: https://CRAN.R-project.org/package=alr4 + url_git: '' +ALS: + version: 0.0.7 + title: |- + Multivariate Curve Resolution Alternating Least Squares + (MCR-ALS) + maintainer: Katharine Mullen + description: |- + Alternating least squares is often used to resolve + components contributing to data with a bilinear structure; the + basic technique may be extended to alternating constrained + least squares. Commonly applied constraints include + unimodality, non-negativity, and normalization of components. + Several data matrices may be decomposed simultaneously by + assuming that one of the two matrices in the bilinear + decomposition is shared between datasets. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALS + url_git: '' +ALSCPC: + version: '1.0' + title: Accelerated line search algorithm for simultaneous orthogonaltransformation + of several positive definite symmetric matricesto nearly diagonal form. + maintainer: Dariush Najarzadeh + description: Using of the accelerated line search algorithm for simultaneously + diagonalize a set of symmetric positive definite matrices. + date_publication: '2013-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALSCPC + url_git: '' +altadata: + version: 0.1.1 + title: API Wrapper for Altadata.io + maintainer: Emre Durukan + description: Functions for interacting directly with the 'ALTADATA' API. With this + R package, developers can build applications around the 'ALTADATA' API without + having to deal with accessing and managing requests and responses. 'ALTADATA' + is a curated data marketplace for more information go to . + date_publication: '2020-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=altadata + url_git: https://github.com/altabering/altadata-r +altair: + version: 4.2.3 + title: Interface to 'Altair' + maintainer: Ian Lyttle + description: |- + Interface to 'Altair' , which itself + is a 'Python' interface to 'Vega-Lite' . + This package uses the 'Reticulate' framework + to manage the interface between R + and 'Python'. + date_publication: '2023-09-04' + bug_reports: https://github.com/vegawidget/altair/issues + url: '' + url_cran: https://CRAN.R-project.org/package=altair + url_git: https://github.com/vegawidget/altair +altdoc: + version: 0.5.0 + title: |- + Package Documentation Websites with 'Quarto', 'Docsify', + 'Docute', or 'MkDocs' + maintainer: Etienne Bacher + description: |- + This is a simple and powerful package to create, render, preview, + and deploy documentation websites for 'R' packages. It is a lightweight and + flexible alternative to 'pkgdown', with support for many documentation + generators, including 'Quarto', 'Docute', 'Docsify', and 'MkDocs'. + date_publication: '2025-01-23' + bug_reports: https://github.com/etiennebacher/altdoc/issues + url: https://altdoc.etiennebacher.com + url_cran: https://CRAN.R-project.org/package=altdoc + url_git: https://github.com/etiennebacher/altdoc +AlteredPQR: + version: 0.1.0 + title: Detection of Altered Protein Quantitative Relationships + maintainer: Marija Buljan + description: Inference of protein complex states from quantitative proteomics data. + The package takes information on known stable protein interactions (i.e. protein + components of the same complex) and assesses how protein quantitative ratios change + between different conditions. It reports protein pairs for which relative protein + quantities to each other have been significantly altered in the tested condition. + date_publication: '2023-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AlteredPQR + url_git: '' +altfuelr: + version: 0.1.0 + title: Provides an Interface to the NREL Alternate Fuels Locator + maintainer: Christopher Burch + description: |- + Provides a number of functions to access the + National Energy Research Laboratory Alternate Fuel Locator API + . + The Alternate Fuel Locator shows the location of alternate fuel stations in the United States + and Canada. This package also includes the data from the US Department of Energy Alternate Fuel + database as a data set. + date_publication: '2020-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=altfuelr + url_git: '' +altmeta: + version: '4.2' + title: Alternative Meta-Analysis Methods + maintainer: Lifeng Lin + description: |- + Provides alternative statistical methods for meta-analysis, including: + - bivariate generalized linear mixed models for synthesizing odds ratios, relative risks, + and risk differences + (Chu et al., 2012 ) + - heterogeneity tests and measures and penalization methods that are robust to outliers + (Lin et al., 2017 ; + Wang et al., 2022 ); + - measures, tests, and visualization tools for publication bias or small-study effects + (Lin and Chu, 2018 ; + Lin, 2019 ; + Lin, 2020 ; + Shi et al., 2020 ); + - meta-analysis of combining standardized mean differences and odds ratios + (Jing et al., 2023 ); + - meta-analysis of diagnostic tests for synthesizing sensitivities, specificities, etc. + (Reitsma et al., 2005 ; + Chu and Cole, 2006 ); + - meta-analysis methods for synthesizing proportions + (Lin and Chu, 2020 ); + - models for multivariate meta-analysis, measures of inconsistency degrees of freedom + in Bayesian network meta-analysis, and predictive P-score + (Lin and Chu, 2018 ; + Lin, 2020 ; + Rosenberger et al., 2021 ). + date_publication: '2024-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=altmeta + url_git: '' +ALTopt: + version: 0.1.2 + title: Optimal Experimental Designs for Accelerated Life Testing + maintainer: Kangwon Seo + description: |- + Creates the optimal (D, U and I) designs for the accelerated life + testing with right censoring or interval censoring. It uses generalized + linear model (GLM) approach to derive the asymptotic variance-covariance + matrix of regression coefficients. The failure time distribution is assumed + to follow Weibull distribution with a known shape parameter and log-linear + link functions are used to model the relationship between failure time + parameters and stress variables. The acceleration model may have multiple + stress factors, although most ALTs involve only two or less stress factors. + ALTopt package also provides several plotting functions including contour plot, + Fraction of Use Space (FUS) plot and Variance Dispersion graphs of Use Space + (VDUS) plot. For more details, see Seo and Pan (2015) . + date_publication: '2019-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ALTopt + url_git: '' +altR2: + version: 1.1.0 + title: Alternative Estimators to Adjusted R-Squared + maintainer: Julian Karch + description: |- + Provides alternatives to the normal adjusted R-squared estimator for the estimation of the multiple squared correlation in regression models, + as fitted by the lm() function. The alternative estimators are described in Karch (2020) . + date_publication: '2024-09-02' + bug_reports: https://github.com/karchjd/altR2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=altR2 + url_git: https://github.com/karchjd/altR2 +ALUES: + version: 0.2.1 + title: Agricultural Land Use Evaluation System + maintainer: Al-Ahmadgaid B. Asaad + description: |- + Evaluates land suitability for different crops production. + The package is based on the Food and Agriculture Organization (FAO) and the + International Rice Research Institute (IRRI) methodology for land evaluation. + Development of ALUES is inspired by similar tool for land evaluation, Land Use + Suitability Evaluation Tool (LUSET). The package uses fuzzy logic approach to evaluate + land suitability of a particular area based on inputs such as rainfall, temperature, + topography, and soil properties. The membership functions used for fuzzy modeling are + the following: Triangular, Trapezoidal and Gaussian. The methods for computing the + overall suitability of a particular area are also included, and these are the Minimum, + Maximum and Average. Finally, ALUES is a highly optimized library with core algorithms + written in C++. + date_publication: '2022-01-12' + bug_reports: https://github.com/alstat/ALUES/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=ALUES + url_git: https://github.com/alstat/ALUES/ +amadeus: + version: 1.2.3 + title: Accessing and Analyzing Large-Scale Environmental Data + maintainer: Kyle Messier + description: Functions are designed to facilitate access to and utility with large + scale, publicly available environmental data in R. The package contains functions + for downloading raw data files from web URLs (download_data()), processing the + raw data files into clean spatial objects (process_covariates()), and extracting + values from the spatial data objects at point and polygon locations (calculate_covariates()). + These functions call a series of source-specific functions which are tailored + to each data sources/datasets particular URL structure, data format, and spatial/temporal + resolution. The functions are tested, versioned, and open source and open access. + For sum_edc() method details, see Messier, Akita, and Serre (2012) . + date_publication: '2025-01-16' + bug_reports: https://github.com/NIEHS/amadeus/issues + url: https://niehs.github.io/amadeus/ + url_cran: https://CRAN.R-project.org/package=amadeus + url_git: '' +amanida: + version: 0.3.0 + title: Meta-Analysis for Non-Integral Data + maintainer: Maria Llambrich + description: |- + Combination of results for meta-analysis using significance + and effect size only. P-values and fold-change are combined to obtain + a global significance on each metabolite. Produces a volcano plot + summarising the relevant results from meta-analysis. Vote-counting + reports for metabolites. And explore plot to detect discrepancies + between studies at a first glance. Methodology is described in the + Llambrich et al. (2021) . + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amanida + url_git: https://github.com/mariallr/amanida +amanpg: + version: 0.3.4 + title: Alternating Manifold Proximal Gradient Method for Sparse PCA + maintainer: Zhong Zheng + description: |- + Alternating Manifold Proximal Gradient Method for Sparse PCA uses the Alternating Manifold Proximal + Gradient (AManPG) method to find sparse principal components from a data or covariance matrix. Provides + a novel algorithm for solving the sparse principal component analysis problem which provides + advantages over existing methods in terms of efficiency and convergence guarantees. + Chen, S., Ma, S., Xue, L., & Zou, H. (2020) . + Zou, H., Hastie, T., & Tibshirani, R. (2006) . + Zou, H., & Xue, L. (2018) . + date_publication: '2022-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amanpg + url_git: '' +amap: + version: 0.8-20 + title: Another Multidimensional Analysis Package + maintainer: Antoine Lucas + description: |- + Tools for Clustering and Principal Component Analysis + (With robust methods, and parallelized functions). + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amap + url_git: '' +amapGeocode: + version: 0.6.0 + title: An Interface to the 'AutoNavi Maps' API Geocoding Services + maintainer: Han Chen + description: Getting and parsing data of location geocode/reverse-geocode and administrative + regions from 'AutoNavi Maps' API. + date_publication: '2021-04-19' + bug_reports: https://github.com/womeimingzi11/amapGeocode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=amapGeocode + url_git: https://github.com/womeimingzi11/amapGeocode +amapro: + version: 0.1.3 + title: Thin Wrapper for Mapping Library 'AMap' + maintainer: Larry Helgason + description: |- + Build and control interactive 2D and 3D maps with 'R/Shiny'. Lean set of powerful commands wrapping native calls to 'AMap' . + Deliver rich mapping functionality with minimal overhead. + date_publication: '2023-05-12' + bug_reports: https://github.com/helgasoft/amapro/issues/ + url: https://helgasoft.github.io/amapro/ + url_cran: https://CRAN.R-project.org/package=amapro + url_git: https://github.com/helgasoft/amapro/ +AMAPVox: + version: 2.2.1 + title: LiDAR Data Voxelisation + maintainer: Philippe Verley + description: |- + Read, manipulate and write voxel spaces. Voxel spaces are + read from text-based output files of the 'AMAPVox' software. 'AMAPVox' + is a LiDAR point cloud voxelisation software that aims at estimating + leaf area through several theoretical/numerical approaches. See more + in the article Vincent et al. (2017) and the + technical note Vincent et al. (2021) . + date_publication: '2024-03-15' + bug_reports: https://forge.ird.fr/amap/amapvox/AMAPVox/-/issues + url: https://amapvox.org + url_cran: https://CRAN.R-project.org/package=AMAPVox + url_git: '' +amazonadsR: + version: 0.1.0 + title: Get Amazon Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Amazon Ads using + the 'Windsor.ai' API . + date_publication: '2022-10-27' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=amazonadsR + url_git: '' +amazons3R: + version: 0.1.0 + title: Get Amazon S3 Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Amazon S3 using + the 'Windsor.ai' API . + date_publication: '2022-12-13' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=amazons3R + url_git: '' +amazonspR: + version: 0.1.0 + title: Get Amazon Sp Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Amazon Sp using + the 'Windsor.ai' API . + date_publication: '2023-01-25' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=amazonspR + url_git: '' +amberr: + version: 1.1.0 + title: '''Amber'' Electronic Data Capture Client' + maintainer: Yannick Marcon + description: |- + 'Amber' is a server application for capturing electronic data records. + Rich forms are used to collect data. This 'Amber' client allows + to perform data extraction for reporting or data transfer at persistent location + purposes. + date_publication: '2024-07-05' + bug_reports: https://github.com/obiba/amberr/issues/ + url: https://www.obiba.org/pages/products/amber/ + url_cran: https://CRAN.R-project.org/package=amberr + url_git: https://github.com/obiba/amberr/ +ambient: + version: 1.0.2 + title: A Generator of Multidimensional Noise + maintainer: Thomas Lin Pedersen + description: |- + Generation of natural looking noise has many application within + simulation, procedural generation, and art, to name a few. The 'ambient' + package provides an interface to the 'FastNoise' C++ library and allows for + efficient generation of perlin, simplex, worley, cubic, value, and white + noise with optional perturbation in either 2, 3, or 4 (in case of simplex and + white noise) dimensions. + date_publication: '2022-09-08' + bug_reports: https://github.com/thomasp85/ambient/issues + url: https://ambient.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=ambient + url_git: https://github.com/thomasp85/ambient +ambit: + version: 0.1.2 + title: Simulation and Estimation of Ambit Processes + maintainer: Almut E. D. Veraart + description: |- + Simulation and estimation tools for + various types of ambit processes, including trawl processes and weighted + trawl processes. + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ambit + url_git: '' +AMCP: + version: 1.0.2 + title: A Model Comparison Perspective + maintainer: Ken Kelley + description: |- + Accompanies the book "Designing experiments and + analyzing data: A model comparison perspective" (3rd ed.) by + Maxwell, Delaney, & Kelley (2018; Routledge). + Contains all of the data sets in the book's chapters and + end-of-chapter exercises. Information about the book is available at + . + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AMCP + url_git: '' +AMCTestmakeR: + version: 1.0.0 + title: Generate LaTeX Code for Auto-Multiple-Choice (AMC) + maintainer: Nils Myszkowski + description: Generate code for use with the Optical Mark Recognition free software + Auto Multiple Choice (AMC). More specifically, this package provides functions + that use as input the question and answer texts, and output the LaTeX code for + AMC. + date_publication: '2018-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AMCTestmakeR + url_git: '' +Amelia: + version: 1.8.3 + title: A Program for Missing Data + maintainer: Matthew Blackwell + description: |- + A tool that "multiply imputes" missing data in a single cross-section + (such as a survey), from a time series (like variables collected for + each year in a country), or from a time-series-cross-sectional data + set (such as collected by years for each of several countries). + Amelia II implements our bootstrapping-based algorithm that gives + essentially the same answers as the standard IP or EMis approaches, + is usually considerably faster than existing approaches and can + handle many more variables. Unlike Amelia I and other statistically + rigorous imputation software, it virtually never crashes (but please + let us know if you find to the contrary!). The program also + generalizes existing approaches by allowing for trends in time series + across observations within a cross-sectional unit, as well as priors + that allow experts to incorporate beliefs they have about the values + of missing cells in their data. Amelia II also includes useful + diagnostics of the fit of multiple imputation models. The program + works from the R command line or via a graphical user interface that + does not require users to know R. + date_publication: '2024-11-08' + bug_reports: '' + url: https://gking.harvard.edu/amelia + url_cran: https://CRAN.R-project.org/package=Amelia + url_git: '' +amelie: + version: 0.2.1 + title: Anomaly Detection with Normal Probability Functions + maintainer: Dmitriy Bolotov + description: 'Implements anomaly detection as binary classification for cross-sectional + data. Uses maximum likelihood estimates and normal probability functions to classify + observations as anomalous. The method is presented in the following lecture from + the Machine Learning course by Andrew Ng: , + and is also described in: Aleksandar Lazarevic, Levent Ertoz, Vipin Kumar, Aysel + Ozgur, Jaideep Srivastava (2003) .' + date_publication: '2019-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amelie + url_git: '' +amen: + version: 1.4.5 + title: |- + Additive and Multiplicative Effects Models for Networks and + Relational Data + maintainer: Peter Hoff + description: |- + Analysis of dyadic network and relational data using additive and + multiplicative effects (AME) models. The basic model includes + regression terms, the covariance structure of the social relations model + (Warner, Kenny and Stoto (1979) , + Wong (1982) ), and multiplicative factor + models (Hoff(2009) ). + Several different link functions accommodate different + relational data structures, including binary/network data, normal + relational data, zero-inflated positive outcomes using a tobit model, ordinal relational data and data from + fixed-rank nomination schemes. Several of these link functions are + discussed in Hoff, Fosdick, Volfovsky and Stovel (2013) + . Development of this + software was supported in part by NIH grant R01HD067509. + date_publication: '2024-02-20' + bug_reports: https://github.com/pdhoff/amen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=amen + url_git: https://github.com/pdhoff/amen +amerifluxr: + version: 1.0.0 + title: Interface to 'AmeriFlux' Data Services + maintainer: Housen Chu + description: |- + Programmatic interface to the 'AmeriFlux' database + (). Provide query, download, + and data summary tools. + date_publication: '2022-02-08' + bug_reports: https://github.com/chuhousen/amerifluxr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=amerifluxr + url_git: https://github.com/chuhousen/amerifluxr +amerika: + version: 0.1.0 + title: American Politics-Inspired Color Palette Generator + maintainer: Philip Waggoner + description: |- + A color palette generator inspired by American politics, with colors ranging from blue on the + left to gray in the middle and red on the right. A variety of palettes allow for a range of applications + from brief discrete scales (e.g., three colors for Democrats, Independents, and Republicans) to + continuous interpolated arrays including dozens of shades graded from blue (left) to red (right). This + package greatly benefitted from building on the source code (with permission) from Ram and Wickham (2015). + date_publication: '2019-05-03' + bug_reports: https://github.com/pdwaggoner/amerika/issues + url: '' + url_cran: https://CRAN.R-project.org/package=amerika + url_git: '' +AmesHousing: + version: 0.0.4 + title: The Ames Iowa Housing Data + maintainer: Max Kuhn + description: Raw and processed versions of the data from De Cock (2011) + are included in the package. + date_publication: '2020-06-23' + bug_reports: https://github.com/topepo/AmesHousing/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AmesHousing + url_git: https://github.com/topepo/AmesHousing +ami: + version: 0.2.1 + title: Checks for Various Computing Environments + maintainer: Brian Connelly + description: |- + A collection of lightweight functions that can be used to + determine the computing environment in which your code is running. + This includes operating systems, continuous integration (CI) + environments, containers, and more. + date_publication: '2024-11-15' + bug_reports: https://github.com/briandconnelly/ami/issues + url: https://briandconnelly.github.io/ami/ + url_cran: https://CRAN.R-project.org/package=ami + url_git: https://github.com/briandconnelly/ami +AmigaFFH: + version: 0.4.7 + title: Commodore Amiga File Format Handler + maintainer: Pepijn de Vries + description: |- + Modern software often poorly support older file formats. This + package intends to handle many file formats that were native to the + antiquated Commodore Amiga machine. This package focuses on file types from + the older Amiga operating systems (<= 3.0). It will read and write specific + file formats and coerces them into more contemporary data. + date_publication: '2025-01-08' + bug_reports: https://github.com/pepijn-devries/AmigaFFH/issues + url: https://pepijn-devries.github.io/AmigaFFH/ + url_cran: https://CRAN.R-project.org/package=AmigaFFH + url_git: https://github.com/pepijn-devries/AmigaFFH/ +AMIM: + version: 1.0.0 + title: Compute the Adjusted Market Inefficiency Measure + maintainer: Vu Le Tran + description: Fast tool to calculate the Adjusted Market Inefficiency Measure following + Tran & Leirvik (2019) . This tool provides rolling + window estimates of the Adjusted Market Inefficiency Measure for multiple instruments + simultaneously. + date_publication: '2023-07-07' + bug_reports: https://github.com/gelotran/AMIM/issues + url: https://gelotran.github.io/AMIM/ + url_cran: https://CRAN.R-project.org/package=AMIM + url_git: https://github.com/gelotran/AMIM +AMISforInfectiousDiseases: + version: 0.1.0 + title: Implement the AMIS Algorithm for Infectious Disease Models + maintainer: Simon Spencer + description: Implements the Adaptive Multiple Importance Sampling (AMIS) algorithm, + as described by Retkute et al. (2021, ), to estimate + key epidemiological parameters by combining outputs from a geostatistical model + of infectious diseases (such as prevalence, incidence, or relative risk) with + a disease transmission model. Utilising the resulting posterior distributions, + the package enables forward projections at the local level. + date_publication: '2025-01-20' + bug_reports: https://github.com/drsimonspencer/AMISforInfectiousDiseases-dev/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AMISforInfectiousDiseases + url_git: https://github.com/drsimonspencer/AMISforInfectiousDiseases-dev +ammiBayes: + version: 1.0-2 + title: Bayesian Ammi Model for Continuous Data + maintainer: Fabio M. Correa + description: |- + Flexible multi-environment trials analysis via MCMC method for Additive Main Effects and Multiplicative Model (AMMI) for continuous data. + Biplot with the averages and regions of confidence can be generated. The chains run in parallel on Linux systems and run serially on Windows. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ammiBayes + url_git: '' +ammistability: + version: 0.1.4 + title: |- + Additive Main Effects and Multiplicative Interaction Model + Stability Parameters + maintainer: B. C. Ajay + description: |- + Computes various stability parameters from Additive Main Effects + and Multiplicative Interaction (AMMI) analysis results such as Modified + AMMI Stability Value (MASV), Sums of the Absolute Value of the Interaction + Principal Component Scores (SIPC), Sum Across Environments of + Genotype-Environment Interaction Modelled by AMMI (AMGE), Sum Across + Environments of Absolute Value of Genotype-Environment Interaction Modelled + by AMMI (AV_(AMGE)), AMMI Stability Index (ASI), Modified ASI (MASI), AMMI + Based Stability Parameter (ASTAB), Annicchiarico's D Parameter (DA), Zhang's + D Parameter (DZ), Averages of the Squared Eigenvector Values (EV), Stability + Measure Based on Fitted AMMI Model (FA), Absolute Value of the Relative + Contribution of IPCs to the Interaction (Za). Further calculates the + Simultaneous Selection Index for Yield and Stability from the computed + stability parameters. See the vignette for complete list of citations for + the methods implemented. + date_publication: '2023-05-24' + bug_reports: https://github.com/ajaygpb/ammistability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ammistability + url_git: https://github.com/ajaygpb/ammistability/https://CRAN.R-project.org/package=ammistabilityhttps://ajaygpb.github.io/ammistability/https://doi.org/10.5281/zenodo.1344756 +AMModels: + version: 0.1.4 + title: Adaptive Management Model Manager + maintainer: Jon Katz + description: |- + Helps enable adaptive management by codifying knowledge in the + form of models generated from numerous analyses and data sets. Facilitates + this process by storing all models and data sets in a single object that can + be updated and saved, thus tracking changes in knowledge through time. A shiny + application called AM Model Manager (modelMgr()) enables the use of these + functions via a GUI. + date_publication: '2018-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AMModels + url_git: '' +AmmoniaConcentration: + version: '0.1' + title: Un-Ionized Ammonia Concentration + maintainer: Felipe Tumenas Marques + description: Provides a function to calculate the concentration of un-ionized ammonia + in the total ammonia in aqueous solution using the pH and temperature values. + date_publication: '2016-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AmmoniaConcentration + url_git: https://github.com/tumenas/ammonia +aMNLFA: + version: 1.1.2 + title: Automated Moderated Nonlinear Factor Analysis Using 'M-plus' + maintainer: Veronica Cole + description: 'Automated generation, running, and interpretation of moderated nonlinear + factor analysis models for obtaining scores from observed variables, using the + method described by Gottfredson and colleagues (2019) . + This package creates M-plus input files which may be run iteratively to test two + different types of covariate effects on items: (1) latent variable impact (both + mean and variance); and (2) differential item functioning. After sequentially + testing for all effects, it also creates a final model by including all significant + effects after adjusting for multiple comparisons. Finally, the package creates + a scoring model which uses the final values of parameter estimates to generate + latent variable scores. \n\n This package generates TEMPLATES for M-plus inputs, + which can and should be inspected, altered, and run by the user. In addition to + being presented without warranty of any kind, the package is provided under the + assumption that everyone who uses it is reading, interpreting, understanding, + and altering every M-plus input and output file. There is no one right way to + implement moderated nonlinear factor analysis, and this package exists solely + to save users time as they generate M-plus syntax according to their own judgment.' + date_publication: '2022-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aMNLFA + url_git: '' +AmoudSurv: + version: 0.1.0 + title: Tractable Parametric Odds-Based Regression Models + maintainer: Abdisalam Hassan Muse + description: Fits tractable fully parametric odds-based regression models for survival + data, including proportional odds (PO), accelerated failure time (AFT), accelerated + odds (AO), and General Odds (GO) models in overall survival frameworks. Given + at least an R function specifying the survivor, hazard rate and cumulative distribution + functions, any user-defined parametric distribution can be fitted. We applied + and evaluated a minimum of seventeen (17) various baseline distributions that + can handle different failure rate shapes for each of the four different proposed + odds-based regression models. For more information see Bennet et al., (1983) , + and Muse et al., (2022) . + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AmoudSurv + url_git: '' +amp: + version: 1.0.0 + title: Statistical Test for the Multivariate Point Null Hypotheses + maintainer: Adam Elder + description: |- + A testing framework for testing the multivariate point null hypothesis. + A testing framework described in Elder et al. (2022) to test the multivariate point null hypothesis. After the user selects a parameter of interest and defines the assumed data generating mechanism, this information should be encoded in functions for the parameter estimator and its corresponding influence curve. Some parameter and data generating mechanism combinations have codings in this package, and are explained in detail in the article. + date_publication: '2022-04-06' + bug_reports: https://github.com/adam-s-elder/amp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=amp + url_git: '' +ampd: + version: '0.2' + title: |- + An Algorithm for Automatic Peak Detection in Noisy Periodic and + Quasi-Periodic Signals + maintainer: Oliver Sieber + description: |- + A method for automatic detection of peaks in noisy periodic and quasi-periodic signals. This method, called automatic multiscale-based peak detection (AMPD), is based on the calculation and analysis of the local maxima scalogram, a matrix comprising the scale-dependent occurrences of local maxima. + For further information see . + date_publication: '2016-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ampd + url_git: '' +AmpGram: + version: '1.0' + title: Prediction of Antimicrobial Peptides + maintainer: Michal Burdukiewicz + description: |- + Predicts antimicrobial peptides using random forests trained on the + n-gram encoded peptides. The implemented algorithm can be accessed from + both the command line and shiny-based GUI. The AmpGram model is too large + for CRAN and it has to be downloaded separately from the repository: + . + date_publication: '2020-05-31' + bug_reports: https://github.com/michbur/AmpGram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AmpGram + url_git: https://github.com/michbur/AmpGram +ampir: + version: 1.1.0 + title: Predict Antimicrobial Peptides + maintainer: Legana Fingerhut + description: |- + A toolkit to predict antimicrobial peptides from protein sequences on a genome-wide scale. + It incorporates two support vector machine models ("precursor" and "mature") trained on publicly available antimicrobial peptide data using calculated + physico-chemical and compositional sequence properties described in Meher et al. (2017) . + In order to support genome-wide analyses, these models are designed to accept any type of protein as input + and calculation of compositional properties has been optimised for high-throughput use. For best results it is important to select the model that accurately + represents your sequence type: for full length proteins, it is recommended to use the default "precursor" model. The alternative, "mature", model is best suited + for mature peptide sequences that represent the final antimicrobial peptide sequence after post-translational processing. For details see Fingerhut et al. (2020) . + The 'ampir' package is also available via a Shiny based GUI at . + date_publication: '2021-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ampir + url_git: https://github.com/Legana/ampir +AMPLE: + version: 1.0.2 + title: Shiny Apps to Support Capacity Building on Harvest Control Rules + maintainer: Finlay Scott + description: |- + Three Shiny apps are provided that introduce Harvest Control Rules (HCR) for fisheries management. + 'Introduction to HCRs' provides a simple overview to how HCRs work. Users are able to select their own HCR and + step through its performance, year by year. Biological variability and estimation uncertainty are introduced. + 'Measuring performance' builds on the previous app and introduces the idea of using performance indicators + to measure HCR performance. + 'Comparing performance' allows multiple HCRs to be created and tested, and their performance compared so that the + preferred HCR can be selected. + date_publication: '2023-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AMPLE + url_git: https://github.com/PacificCommunity/ofp-sam-ample +AmpliconDuo: + version: 1.1.1 + title: |- + Statistical Analysis of Amplicon Data of the Same Sample to + Identify Artefacts + maintainer: Anja Lange + description: Increasingly powerful techniques for high-throughput sequencing open + the possibility to comprehensively characterize microbial communities, including + rare species. However, a still unresolved issue are the substantial error rates + in the experimental process generating these sequences. To overcome these limitations + we propose an approach, where each sample is split and the same amplification + and sequencing protocol is applied to both halves. This procedure should allow + to detect likely PCR and sequencing artifacts, and true rare species by comparison + of the results of both parts. The AmpliconDuo package, whereas amplicon duo from + here on refers to the two amplicon data sets of a split sample, is intended to + help interpret the obtained read frequency distribution across split samples, + and to filter the false positive reads. + date_publication: '2020-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AmpliconDuo + url_git: '' +AMR: + version: 2.1.1 + title: Antimicrobial Resistance Data Analysis + maintainer: Matthijs S. Berends + description: |- + Functions to simplify and standardise antimicrobial resistance (AMR) + data analysis and to work with microbial and antimicrobial properties by + using evidence-based methods, as described in . + date_publication: '2023-10-21' + bug_reports: https://github.com/msberends/AMR/issues + url: https://msberends.github.io/AMR/ + url_cran: https://CRAN.R-project.org/package=AMR + url_git: https://github.com/msberends/AMR +amregtest: + version: 1.0.3 + title: Runs Allelematch Regression Tests + maintainer: Torvald Staxler + description: |- + Automates regression testing of package 'allelematch'. Over + 2500 tests covers all functions in 'allelematch', reproduces the + examples from the documentation and includes negative tests. The + implementation is based on 'testthat'. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amregtest + url_git: '' +amscorer: + version: 0.1.0 + title: Clinical Scores Calculator for Healthcare + maintainer: Amadou Khalilou Sow + description: |- + Provides functions to compute various clinical scores used in healthcare. + These include the Charlson Comorbidity Index (CCI), predicting 10-year survival in patients with multiple comorbidities; + the EPICES score, an individual indicator of precariousness considering its multidimensional nature; + the MELD score for chronic liver disease severity; the Alternative Fistula Risk Score (a-FRS) for postoperative pancreatic fistula risk; + and the Distal Pancreatectomy Fistula Risk Score (D-FRS) for risk following distal pancreatectomy. + For detailed methodology, refer to Charlson et al. (1987) , + Sass et al. (2006) , + Kamath et al. (2001) , + Kim et al. (2008) + Kim et al. (2021) , + Mungroop et al. (2019) , + and de Pastena et al. (2023) .. + date_publication: '2024-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amscorer + url_git: '' +amt: + version: 0.2.2.0 + title: Animal Movement Tools + maintainer: Johannes Signer + description: |- + Manage and analyze animal movement data. The functionality of + 'amt' includes methods to calculate home ranges, track statistics + (e.g. step lengths, speed, or turning angles), prepare data for + fitting habitat selection analyses, and simulation of space-use from + fitted step-selection functions. + date_publication: '2024-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=amt + url_git: https://github.com/jmsigner/amt +amVennDiagram5: + version: 1.0.0 + title: Interactive Venn Diagrams + maintainer: Stéphane Laurent + description: |- + Creates interactive Venn diagrams using the 'amCharts5' library for + 'JavaScript'. They can be used directly from the R console, from 'RStudio', + in 'shiny' applications, and in 'rmarkdown' documents. + date_publication: '2024-07-31' + bug_reports: https://github.com/stla/amVennDiagram5/issues + url: '' + url_cran: https://CRAN.R-project.org/package=amVennDiagram5 + url_git: https://github.com/stla/amVennDiagram5 +AmyloGram: + version: '1.1' + title: Prediction of Amyloid Proteins + maintainer: Michal Burdukiewicz + description: |- + Predicts amyloid proteins using random forests trained on the + n-gram encoded peptides. The implemented algorithm can be accessed from + both the command line and shiny-based GUI. + date_publication: '2017-10-11' + bug_reports: https://github.com/michbur/AmyloGram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AmyloGram + url_git: https://github.com/michbur/AmyloGram +anabel: + version: 3.0.1 + title: Analysis of Binding Events + l + maintainer: Hoor Al-Hasani + description: |- + A free software for a fast and easy analysis of 1:1 molecular interaction studies. + This package is suitable for a high-throughput data analysis. + Both the online app and the package are completely open source. + You provide a table of sensogram, tell 'anabel' which method to use, + and it takes care of all fitting details. + The first two releases of 'anabel' were created and implemented as in + (, ). + date_publication: '2023-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anabel + url_git: '' +AnaCoDa: + version: 0.1.4.4 + title: |- + Analysis of Codon Data under Stationarity using a Bayesian + Framework + maintainer: Cedric Landerer + description: |- + Is a collection of models to analyze genome scale codon + data using a Bayesian framework. Provides visualization + routines and checkpointing for model fittings. Currently + published models to analyze gene data for selection on codon + usage based on Ribosome Overhead Cost (ROC) are: ROC (Gilchrist + et al. (2015) ), and ROC with phi + (Wallace & Drummond (2013) ). In + addition 'AnaCoDa' contains three currently unpublished models. + The FONSE (First order approximation On NonSense Error) model + analyzes gene data for selection on codon usage against of + nonsense error rates. The PA (PAusing time) and PANSE (PAusing + time + NonSense Error) models use ribosome footprinting data to + analyze estimate ribosome pausing times with and without + nonsense error rate from ribosome footprinting data. + date_publication: '2020-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnaCoDa + url_git: https://github.com/clandere/AnaCoDa +Anaconda: + version: 0.1.5 + title: |- + Targeted Differential and Global Enrichment Analysis of + Taxonomic Rank by Shared Asvs + maintainer: Pierre-Louis Stenger + description: |- + Targeted differential and global enrichment analysis of taxonomic rank by shared ASVs (Amplicon Sequence Variant), for high-throughput eDNA sequencing of fungi, bacteria, and metazoan. + Actually works in two steps: I) Targeted differential analysis from QIIME2 data and II) Global analysis by Taxon Mann-Whitney U test analysis from targeted analysis (I) + (I) Estimate variance-mean dependence in count/abundance ASVs data from high-throughput sequencing assays and test for differential represented ASVs based on a model using the negative binomial distribution. + (II) NCBITaxon_MWU uses continuous measure of significance (such as fold-change or -log(p-value)) to identify NCBITaxon that are significantly enriches with either up- or down-represented ASVs. If the measure is binary (0 or 1) the script will perform a typical 'NCBITaxon enrichment' analysis based Fisher's exact test: it will show NCBITaxon over-represented among the ASVs that have 1 as their measure. On the plot, different fonts are used to indicate significance and color indicates enrichment with either up (red) or down (blue) regulated ASVs. No colors are shown for binary measure analysis. The tree on the plot is hierarchical clustering of NCBITaxon based on shared ASVs. Categories with no branch length between them are subsets of each other. The fraction next to the category name indicates the fraction of 'good' ASVs in it; 'good' ASVs are the ones exceeding the arbitrary absValue cutoff (option in taxon_mwuPlot()). For Fisher's based test, specify absValue=0.5. This value does not affect statistics and is used for plotting only. The original idea was for genes differential expression analysis from Wright et al (2015) ; adapted here for taxonomic analysis. + The 'Anaconda' package makes it possible to carry out these analyses by automatically creating several graphs and tables and storing them in specially created subfolders. You will need your QIIME2 pipeline output for each kingdom (eg; Fungi and/or Bacteria and/or Metazoan): i) taxonomy.tsv, ii) taxonomy_RepSeq.tsv, iii) ASV.tsv and iv) SampleSheet_comparison.txt (the latter being created by you). + date_publication: '2022-10-14' + bug_reports: https://github.com/PLStenger/Anaconda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Anaconda + url_git: https://github.com/PLStenger/Anaconda +anacor: + version: 1.1-4 + title: Simple and Canonical Correspondence Analysis + maintainer: Patrick Mair + description: Performs simple and canonical CA (covariates on rows/columns) on a + two-way frequency table (with missings) by means of SVD. Different scaling methods + (standard, centroid, Benzecri, Goodman) as well as various plots including confidence + ellipsoids are provided. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anacor + url_git: https://r-forge.r-project.org/projects/psychor/ +analogsea: + version: 1.0.7.2 + title: Interface to 'DigitalOcean' + maintainer: Mauricio Vargas + description: |- + Provides a set of functions for interacting with the 'DigitalOcean' + API , including creating images, destroying + them, rebooting, getting details on regions, and available images. + date_publication: '2023-04-19' + bug_reports: https://github.com/pachadotdev/analogsea/issues + url: '' + url_cran: https://CRAN.R-project.org/package=analogsea + url_git: https://github.com/pachadotdev/analogsea(devel)https://pacha.dev/analogsea/(docs) +analogue: + version: 0.17-7 + title: Analogue and Weighted Averaging Methods for Palaeoecology + maintainer: Gavin L. Simpson + description: |- + Fits Modern Analogue Technique and Weighted Averaging transfer + function models for prediction of environmental data from species + data, and related methods used in palaeoecology. + date_publication: '2024-09-21' + bug_reports: https://github.com/gavinsimpson/analogue/issues + url: '' + url_cran: https://CRAN.R-project.org/package=analogue + url_git: https://github.com/gavinsimpson/analogue +AnalysisLin: + version: 0.1.2 + title: Exploratory Data Analysis + maintainer: Zhiwei Lin + description: A quick and effective data exploration toolkit. It provides essential + features, including a descriptive statistics table for a quick overview of your + dataset, interactive distribution plots to visualize variable patterns, Principal + Component Analysis for dimensionality reduction and feature analysis, missing + value imputation methods, and correlation analysis. + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnalysisLin + url_git: '' +analyzer: + version: 1.0.1 + title: Data Analysis and Automated R Notebook Generation + maintainer: Apurv Priyam + description: Easy data analysis and quality checks which are commonly used in data + science. It combines the tabular and graphical visualization for easier usability. + This package also creates an R Notebook with detailed data exploration with one + function call. The notebook can be made interactive. + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=analyzer + url_git: '' +AnanseSeurat: + version: 1.2.0 + title: Construct ANANSE GRN-Analysis Seurat + maintainer: Jos Smits + description: |- + Enables gene regulatory network (GRN) analysis on single cell clusters, + using the GRN analysis software 'ANANSE', Xu et al.(2021) . + Export data from 'Seurat' objects, for GRN analysis by 'ANANSE' + implemented in 'snakemake'. Finally, incorporate results for visualization + and interpretation. + date_publication: '2023-11-11' + bug_reports: https://github.com/JGASmits/AnanseSeurat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AnanseSeurat + url_git: https://github.com/JGASmits/AnanseSeurat/ +AncestryMapper: + version: '2.0' + title: Assigning Ancestry Based on Population References + maintainer: Eoghan T O'Halloran + description: |- + Assigns genetic ancestry to an individual and + studies relationships between local and global populations. + date_publication: '2016-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AncestryMapper + url_git: '' +AnchorRegression: + version: 0.1.3 + title: Perform AnchorRegression + maintainer: Simon Zimmermann + description: |- + Performs AnchorRegression proposed by Rothenhäusler et al. 2020. + The code is adapted from the original paper repository. () + The code was developed independently from the authors of the paper. + date_publication: '2021-01-06' + bug_reports: https://github.com/simzim96/AnchorRegression/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AnchorRegression + url_git: https://github.com/simzim96/AnchorRegression +and: + version: 0.1.6 + title: Construct Natural-Language Lists with Internationalization + maintainer: Alexander Rossell Hayes + description: |- + Construct language-aware lists. Make "and"-separated and + "or"-separated lists that automatically conform to the user's language + settings. + date_publication: '2025-02-25' + bug_reports: https://github.com/rossellhayes/and/issues + url: https://pkg.rossellhayes.com/and/ + url_cran: https://CRAN.R-project.org/package=and + url_git: https://github.com/rossellhayes/and +andrews: + version: 1.1.2 + title: Various Andrews Curves + maintainer: Sigbert Klinke + description: |- + Visualisation of multidimensional data through different Andrews curves: + Andrews, D. F. (1972) Plots of High-Dimensional Data. Biometrics, 28(1), 125-136. . + date_publication: '2023-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=andrews + url_git: https://github.com/sigbertklinke/andrews(developmentversion) +Andromeda: + version: 0.6.7 + title: Asynchronous Disk-Based Representation of Massive Data + maintainer: Martijn Schuemie + description: Storing very large data objects on a local drive, while still making + it possible to manipulate the data in an efficient manner. + date_publication: '2024-08-22' + bug_reports: https://github.com/OHDSI/Andromeda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Andromeda + url_git: https://github.com/OHDSI/Andromeda +andurinha: + version: 0.0.2 + title: Make Spectroscopic Data Processing Easier + maintainer: Noemi Alvarez Fernandez + description: |- + The goal of 'andurinha' is provide a fast and friendly way to + process spectroscopic data. It is intended for processing several spectra of + samples with similar composition (tens to hundreds of spectra). It compiles + spectroscopy data files, produces standardized and second derivative spectra, + finds peaks and allows to select the most significant ones based on the second + derivative/absorbance sum spectrum. It also provides functions for graphic + evaluation of the outputs. + date_publication: '2020-08-13' + bug_reports: https://github.com/noemiallefs/andurinha/issues + url: '' + url_cran: https://CRAN.R-project.org/package=andurinha + url_git: https://github.com/noemiallefs/andurinha +anesrake: + version: '0.80' + title: ANES Raking Implementation + maintainer: Josh Pasek + description: |- + Provides a comprehensive system for selecting + variables and weighting data to match the specifications of the American + National Election Studies. The package includes methods for identifying + discrepant variables, raking data, and assessing the effects of the raking + algorithm. It also allows automated re-raking if target variables fall + outside identified bounds and allows greater user specification than other + available raking algorithms. A variety of simple weighted statistics that + were previously in this package (version .55 and earlier) have been moved to + the package 'weights.' + date_publication: '2018-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anesrake + url_git: '' +AnglerCreelSurveySimulation: + version: 1.0.3 + title: Simulate a Bus Route Creel Survey of Anglers + maintainer: Ranney Steven H. + description: Simulate an angler population, sample the simulated population with + a user-specified survey times, and calculate metrics from a bus route-type creel + survey. + date_publication: '2024-05-14' + bug_reports: https://github.com/stevenranney/AnglerCreelSurveySimulation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AnglerCreelSurveySimulation + url_git: https://github.com/stevenranney/AnglerCreelSurveySimulation +angstromATE: + version: 0.1.3 + title: Imports Log Files from Angstrom Engineering Thermal Evaporator + maintainer: Thomas Gredig + description: |- + Opens and imports log files from Angstrom Engineering Thermal Evaporator + and extracts basic characteristics, such as base pressure, time of the evaporation. + It can visualize the deposition observables for review. + date_publication: '2024-10-20' + bug_reports: https://github.com/thomasgredig/angstromATE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=angstromATE + url_git: '' +angstroms: + version: 0.0.1 + title: Tools for 'ROMS' the Regional Ocean Modeling System + maintainer: Michael D. Sumner + description: |- + Helper functions for working with Regional Ocean Modeling System 'ROMS' output. See + for more information about 'ROMS'. + date_publication: '2017-05-01' + bug_reports: https://github.com/mdsumner/angstroms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=angstroms + url_git: https://github.com/mdsumner/angstroms +aniDom: + version: 0.1.5 + title: Inferring Dominance Hierarchies and Estimating Uncertainty + maintainer: Damien R. Farine + description: 'Provides: (1) Tools to infer dominance hierarchies based on calculating + Elo scores, but with custom functions to improve estimates in animals with relatively + stable dominance ranks. (2) Tools to plot the shape of the dominance hierarchy + and estimate the uncertainty of a given data set.' + date_publication: '2021-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aniDom + url_git: '' +anim.plots: + version: 0.2.2 + title: Simple Animated Plots for R + maintainer: David Hugh-Jones + description: |- + Simple animated versions of basic R plots, using the 'animation' + package. Includes animated versions of plot, barplot, persp, contour, + filled.contour, hist, curve, points, lines, text, symbols, segments, and + arrows. + date_publication: '2021-04-30' + bug_reports: https://github.com/hughjonesd/anim.plots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=anim.plots + url_git: https://github.com/hughjonesd/anim.plots +animalEKF: + version: '1.2' + title: Extended Kalman Filters for Animal Movement + maintainer: Samuel Ackerman + description: Synthetic generation of 1-D and 2-D correlated random walks (CRWs) + for animal movement with behavioral switching, and particle filter estimation + of movement parameters from observed trajectories using Extended Kalman Filter + (EKF) model. See Ackerman (2018) . + date_publication: '2023-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=animalEKF + url_git: '' +AnimalHabitatNetwork: + version: 0.1.0 + title: |- + Networks Characterising the Physical Configurations of Animal + Habitats + maintainer: Peng He + description: Functions for generating and visualising networks for characterising + the physical attributes and spatial organisations of habitat components (i.e. + habitat physical configurations). The network generating algorithm first determines + the X and Y coordinates of N nodes within a rectangle with a side length of L + and an area of A. Then it computes the pair-wise Euclidean distance Dij between + node i and j, and then a complete network with 1/Dij as link weights is constructed. + Then, the algorithm removes links from the complete network with the probability + as shown in the function ahn_prob(). Such link removals can make the network disconnected + whereas a connected network is wanted. In such cases, the algorithm rewires one + network component to its spatially nearest neighbouring component and repeat doing + this until the network is connected again. Finally, it outputs an undirected network + (weighted or unweighted, connected or disconnected). This package came with a + manuscript on modelling the physical configurations of animal habitats using networks + (in preparation). + date_publication: '2019-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnimalHabitatNetwork + url_git: '' +AnimalSequences: + version: 0.2.0 + title: Analyse Animal Sequential Behaviour and Communication + maintainer: Alex Mielke + description: All animal behaviour occurs sequentially. The package has a number + of functions to format sequence data from different sources, to analyse sequential + behaviour and communication in animals. It also has functions to plot the data + and to calculate the entropy of sequences. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnimalSequences + url_git: '' +animate: + version: 0.3.9.4 + title: A Web-Based Graphics Device for Animated Visualisations + maintainer: Chun Fung Kwok + description: |- + Implements a web-based graphics device for animated visualisations. + Modelled on the 'base' syntax, it extends the 'base' graphics functions to + support frame-by-frame animation and keyframes animation. + The target use cases are real-time animated visualisations, including agent-based + models, dynamical systems, and animated diagrams. + The generated visualisations can be deployed as GIF images / MP4 videos, as + 'Shiny' apps (with interactivity) or as HTML documents through embedding into + R Markdown documents. + date_publication: '2023-02-03' + bug_reports: https://github.com/kcf-jackson/animate/issues + url: https://kcf-jackson.github.io/animate/ + url_cran: https://CRAN.R-project.org/package=animate + url_git: '' +animation: + version: '2.7' + title: |- + A Gallery of Animations in Statistics and Utilities to Create + Animations + maintainer: Yihui Xie + description: |- + Provides functions for animations in statistics, covering topics + in probability theory, mathematical statistics, multivariate statistics, + non-parametric statistics, sampling survey, linear models, time series, + computational statistics, data mining and machine learning. These functions + may be helpful in teaching statistics and data analysis. Also provided in this + package are a series of functions to save animations to various formats, e.g. + Flash, 'GIF', HTML pages, 'PDF' and videos. 'PDF' animations can be inserted + into 'Sweave' / 'knitr' easily. + date_publication: '2021-10-07' + bug_reports: https://github.com/yihui/animation/issues + url: https://yihui.org/animation/ + url_cran: https://CRAN.R-project.org/package=animation + url_git: '' +animbook: + version: 1.0.0 + title: |- + Visualizing Changes in Performance Measures and Demographic + Affiliations using Animation + maintainer: Krisanat Anukarnsakulchularp + description: Create an interactive visualization to be used for communication purposes. + Providing the function for preparing, plotting, and animating the data. + date_publication: '2023-12-05' + bug_reports: https://github.com/KrisanatA/animbook/issues + url: '' + url_cran: https://CRAN.R-project.org/package=animbook + url_git: https://github.com/KrisanatA/animbook +animint2: + version: 2025.1.28 + title: Animated Interactive Grammar of Graphics + maintainer: Toby Hocking + description: |- + Functions are provided for defining animated, + interactive data visualizations in R code, and rendering + on a web page. The 2018 Journal of Computational and + Graphical Statistics paper, + + describes the concepts implemented. + date_publication: '2025-01-28' + bug_reports: https://github.com/animint/animint2/issues + url: https://animint.github.io/animint2/ + url_cran: https://CRAN.R-project.org/package=animint2 + url_git: '' +animl: + version: 2.0.0 + title: A Collection of ML Tools for Conservation Research + maintainer: Kyra Swanson + description: Functions required to classify subjects within camera trap field data. + The package can handle both images and videos. The authors recommend a two-step + approach using Microsoft's 'MegaDector' model and then a second model trained + on the classes of interest. + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=animl + url_git: '' +anipaths: + version: 0.10.4 + title: Animation of Multiple Trajectories with Uncertainty + maintainer: Henry Scharf + description: Animation of observed trajectories using spline-based interpolation + (see for example, Buderman, F. E., Hooten, M. B., Ivan, J. S. and Shenk, T. M. + (2016), "A functional model for characterizing long-distance + movement behaviour". Methods Ecol Evol). Intended to be used exploratory data + analysis, and perhaps for preparation of presentations. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anipaths + url_git: '' +aniSNA: + version: 1.1.1 + title: Statistical Network Analysis of Animal Social Networks + maintainer: Prabhleen Kaur + description: |- + Obtain network structures from animal GPS telemetry observations and + statistically analyse them to assess their adequacy for social network analysis. Methods include + pre-network data permutations, bootstrapping techniques to obtain confidence intervals + for global and node-level network metrics, and correlation and regression analysis of the local network metrics. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aniSNA + url_git: '' +aniview: + version: 0.1.0 + title: Animate Shiny and R Markdown Content when it Comes into View + maintainer: Félix Luginbuhl + description: Animate Shiny and R Markdown content when it comes into view using + 'animate-css' effects thanks to 'jQuery AniView'. + date_publication: '2020-03-31' + bug_reports: https://github.com/lgnbhl/aniview/issues + url: https://felixluginbuhl.com/aniview + url_cran: https://CRAN.R-project.org/package=aniview + url_git: https://github.com/lgnbhl/aniview +anMC: + version: 0.2.5 + title: Compute High Dimensional Orthant Probabilities + maintainer: Dario Azzimonti + description: Computationally efficient method to estimate orthant probabilities + of high-dimensional Gaussian vectors. Further implements a function to compute + conservative estimates of excursion sets under Gaussian random field priors. + date_publication: '2023-08-22' + bug_reports: '' + url: https://doi.org/10.1080/10618600.2017.1360781 + url_cran: https://CRAN.R-project.org/package=anMC + url_git: '' +ANN2: + version: 2.3.4 + title: Artificial Neural Networks for Anomaly Detection + maintainer: Bart Lammers + description: |- + Training of neural networks for classification and regression tasks + using mini-batch gradient descent. Special features include a function for + training autoencoders, which can be used to detect anomalies, and some + related plotting functions. Multiple activation functions are supported, + including tanh, relu, step and ramp. For the use of the step and ramp + activation functions in detecting anomalies using autoencoders, see + Hawkins et al. (2002) . Furthermore, + several loss functions are supported, including robust ones such as Huber + and pseudo-Huber loss, as well as L1 and L2 regularization. The possible + options for optimization algorithms are RMSprop, Adam and SGD with momentum. + The package contains a vectorized C++ implementation that facilitates + fast training through mini-batch learning. + date_publication: '2020-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ANN2 + url_git: https://github.com/bflammers/ANN2 +anndata: + version: 0.7.5.6 + title: '''anndata'' for R' + maintainer: Robrecht Cannoodt + description: |- + A 'reticulate' wrapper for the Python package 'anndata'. + Provides a scalable way of keeping track of data and learned + annotations. Used to read from and write to the h5ad file format. + date_publication: '2023-03-17' + bug_reports: https://github.com/dynverse/anndata/issues + url: https://anndata.dynverse.org + url_cran: https://CRAN.R-project.org/package=anndata + url_git: https://github.com/dynverse/anndata +annmatrix: + version: 0.1.2 + title: |- + Annotated Matrix: Matrices with Persistent Row and Column + Annotations + maintainer: Karolis Koncevičius + description: Implements persistent row and column annotations for R matrices. The + annotations associated with rows and columns are preserved after subsetting, transposition, + and various other matrix-specific operations. Intended use case is for storing + and manipulating genomic datasets which typically consist of a matrix of measurements + (like gene expression values) as well as annotations about rows (i.e. genomic + locations) and annotations about columns (i.e. meta-data about collected samples). + But 'annmatrix' objects are also expected to be useful in various other contexts. + date_publication: '2023-05-14' + bug_reports: https://github.com/karoliskoncevicius/annmatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=annmatrix + url_git: https://github.com/karoliskoncevicius/annmatrix +AnnoProbe: + version: 0.1.7 + title: Annotate the Gene Symbols for Probes in Expression Array + maintainer: Yonghe Xia + description: |- + We curated 147 of expression array, from 3 species(human,mouse,rat), + 3 companies('Affymetrix','Illumina','Agilent'), + by aligning the 'Fasta' sequences of all probes of each platform to their corresponding reference genome, + and then annotate them to genes. + date_publication: '2022-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnnoProbe + url_git: https://github.com/jmzeng1314/AnnoProbe +annotater: + version: 0.2.3 + title: Annotate Package Load Calls + maintainer: Luis D. Verde Arregoitia + description: |- + Provides non-invasive annotation of package load calls + such as \code{library()}, \code{p_load()}, and \code{require()} so that we can have an idea of what + the packages we are loading are meant for. + date_publication: '2024-01-26' + bug_reports: https://github.com/luisDVA/annotater/issues + url: https://annotater.liomys.mx + url_cran: https://CRAN.R-project.org/package=annotater + url_git: https://github.com/luisDVA/annotater +AnnotationBustR: + version: 1.3.0 + title: Extract Subsequences from GenBank Annotations + maintainer: Samuel R. Borstein + description: Extraction of subsequences into FASTA files from GenBank annotations + where gene names may vary among accessions. Borstein & O'Meara (2018) . + date_publication: '2020-09-24' + bug_reports: https://github.com/sborstein/AnnotationBustR/issues + url: https://www.ncbi.nlm.nih.gov/nuccore + url_cran: https://CRAN.R-project.org/package=AnnotationBustR + url_git: https://github.com/sborstein/AnnotationBustR +annotator: + version: 0.0.3.1 + title: Image Annotation and Polygon Outlining using Free Drawing + maintainer: Mihai Valcu + description: Provides functions to create image annotations through polygon outlining. + Annotator has the same function as 'graphics::locator()' but achieves its purpose + through drawing, rather than multiple mouse clicks. It is based on the 'htmlwidgets' + package and 'fabric.js' JavaScript library . + date_publication: '2023-10-18' + bug_reports: https://github.com/valcu/annotator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=annotator + url_git: https://github.com/valcu/annotator +AnnuityRIR: + version: 1.0-0 + title: Annuity Random Interest Rates + maintainer: Fabrizio Maturo + description: Annuity Random Interest Rates proposes different techniques for the + approximation of the present and final value of a unitary annuity-due or annuity-immediate + considering interest rate as a random variable. Cruz Rambaud et al. (2017) . + Cruz Rambaud et al. (2015) . + date_publication: '2017-11-03' + bug_reports: https://github.com/fabriziomaturo/AnnuityRIR + url: '' + url_cran: https://CRAN.R-project.org/package=AnnuityRIR + url_git: '' +anocva: + version: 0.1.1 + title: |- + A Non-Parametric Statistical Test to Compare Clustering + Structures + maintainer: Maciel C. Vidal + description: |- + Provides ANOCVA (ANalysis Of Cluster VAriability), a non-parametric statistical test + to compare clustering structures with applications in functional magnetic resonance imaging + data (fMRI). The ANOCVA allows us to compare the clustering structure of multiple groups + simultaneously and also to identify features that contribute to the differential clustering. + date_publication: '2017-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anocva + url_git: '' +ANOFA: + version: 0.1.3 + title: Analyses of Frequency Data + maintainer: Denis Cousineau + description: |2- + + Analyses of frequencies can be performed using an alternative test based + on the G statistic. The test has similar type-I error rates and power as + the chi-square test. However, it is based on a total statistic that can be + decomposed in an additive fashion into interaction effects, main effects, simple + effects, contrast effects, etc., mimicking precisely the logic of ANOVA. We call + this set of tools 'ANOFA' (Analysis of Frequency data) to highlight its + similarities with ANOVA. This framework also renders plots of frequencies + along with confidence intervals. Finally, effect sizes and planning statistical + power are easily done under this framework. The ANOFA is a tool that assesses + the significance of effects instead of the significance of parameters; as such, + it is more intuitive to most researchers than alternative approaches based on + generalized linear models. + See Laurencelle and Cousineau (2023) . + date_publication: '2023-11-18' + bug_reports: https://github.com/dcousin3/ANOFA/issues/ + url: https://dcousin3.github.io/ANOFA/ + url_cran: https://CRAN.R-project.org/package=ANOFA + url_git: '' +anoint: + version: '1.5' + title: Analysis of Interactions + maintainer: Ravi Varadhan + description: 'The tools in this package are intended to help researchers assess + multiple treatment-covariate interactions with data from a parallel-group randomized + controlled clinical trial. The methods implemented in the package were proposed + in Kovalchik, Varadhan and Weiss (2013) .' + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anoint + url_git: '' +ANOM: + version: '0.5' + title: Analysis of Means + maintainer: Philip Pallmann + description: Analysis of means (ANOM) as used in technometrical computing. The package + takes results from multiple comparisons with the grand mean (obtained with 'multcomp', + 'SimComp', 'nparcomp', or 'MCPAN') or corresponding simultaneous confidence intervals + as input and produces ANOM decision charts that illustrate which group means deviate + significantly from the grand mean. + date_publication: '2017-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ANOM + url_git: https://github.com/PhilipPallmann/ANOM +anomalize: + version: 0.3.0 + title: Tidy Anomaly Detection + maintainer: Matt Dancho + description: |2- + + The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. + The main functions are time_decompose(), anomalize(), and time_recompose(). + When combined, it's quite simple to decompose time series, detect anomalies, + and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). + Time series decomposition is used to remove trend and seasonal components via the time_decompose() function + and methods include seasonal decomposition of time series by Loess ("stl") and + seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements + two methods for anomaly detection of residuals including using an inner quartile range ("iqr") + and generalized extreme studentized deviation ("gesd"). These methods are based on + those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. + Refer to the associated functions for specific references for these methods. + date_publication: '2023-10-31' + bug_reports: https://github.com/business-science/anomalize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=anomalize + url_git: https://github.com/business-science/anomalize +anomaly: + version: 4.3.3 + title: Detecting Anomalies in Data + maintainer: Daniel Grose + description: Implements Collective And Point Anomaly (CAPA) Fisch, Eckley, and Fearnhead + (2022) , Multi-Variate Collective And Point Anomaly (MVCAPA) + Fisch, Eckley, and Fearnhead (2021) , Proportion + Adaptive Segment Selection (PASS) Jeng, Cai, and Li (2012) , + and Bayesian Abnormal Region Detector (BARD) Bardwell and Fearnhead (2015) . + These methods are for the detection of anomalies in time series data. Further + information regarding the use of this package along with detailed examples can + be found in Fisch, Grose, Eckley, Fearnhead, and Bardwell (2024) . + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anomaly + url_git: '' +AnomalyScore: + version: '0.1' + title: Anomaly Scoring for Multivariate Time Series + maintainer: Guillermo Granados + description: Compute an anomaly score for multivariate time series based on the + k-nearest neighbors algorithm. Different computations of distances between time + series are provided. + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnomalyScore + url_git: '' +anominate: + version: '0.7' + title: Alpha-NOMINATE Ideal Point Estimator + maintainer: Christopher Hare + description: Provides functions to estimate and interpret the alpha-NOMINATE ideal + point model developed in Carroll et al. (2013, ). alpha-NOMINATE + extends traditional spatial voting frameworks by allowing for a mixture of Gaussian + and quadratic utility functions, providing flexibility in modeling political actors' + preferences. The package uses Markov Chain Monte Carlo (MCMC) methods for parameter + estimation, supporting robust inference about individuals' ideological positions + and the shape of their utility functions. It also contains functions to simulate + data from the model and to calculate the probability of a vote passing given the + ideal points of the legislators/voters and the estimated location of the choice + alternatives. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anominate + url_git: '' +anomo: + version: 1.0.0 + title: |- + Analysis of Moderation, Statistical Power, and Optimal Design + for Studies Detecting Difference and Equivalence + maintainer: Zuchao Shen + description: |- + Analysis of moderation (ANOMO) method conceptualizes + the difference and equivalence tests as a moderation problem to + test the difference and equivalence of + two means (or two effects in two studies). + date_publication: '2025-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anomo + url_git: '' +ANOPA: + version: 0.1.3 + title: Analyses of Proportions using Anscombe Transform + maintainer: Denis Cousineau + description: |2- + + Analyses of Proportions can be performed on the Anscombe (arcsine-related) transformed + data. The 'ANOPA' package can analyze proportions obtained from up to + four factors. The factors can be within-subject or between-subject or a mix + of within- and between-subject. The main, omnibus analysis can be followed by + additive decompositions into interaction effects, main effects, simple + effects, contrast effects, etc., mimicking precisely the logic of ANOVA. For + that reason, we call this set of tools 'ANOPA' (Analysis of Proportion + using Anscombe transform) to highlight its similarities with ANOVA. + The 'ANOPA' framework also allows plots of proportions easy to obtain + along with confidence intervals. Finally, effect sizes and planning statistical + power are easily done under this framework. Only particularity, the 'ANOPA' computes + F statistics which have an infinite degree of freedom on the denominator. + See Laurencelle and Cousineau (2023) . + date_publication: '2024-03-22' + bug_reports: https://github.com/dcousin3/ANOPA/issues/ + url: https://dcousin3.github.io/ANOPA/ + url_cran: https://CRAN.R-project.org/package=ANOPA + url_git: '' +ANOVAIREVA: + version: 0.1.0 + title: Interactive Document for Working with Analysis of Variance + maintainer: Kartikeya Bolar + description: An interactive document on the topic of one-way and two-way analysis + of variance using 'rmarkdown' and 'shiny' packages. Runtime examples are provided + in the package function as well as at . + date_publication: '2019-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ANOVAIREVA + url_git: '' +ANOVAShiny: + version: 0.1.0 + title: Interactive Document for Working with Analysis of Variance + maintainer: Kartikeya Bolar + description: An interactive document on the topic of one-way and two-way analysis + of variance using 'rmarkdown' and 'shiny' packages. Runtime examples are provided + in the package function as well as at . + date_publication: '2019-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ANOVAShiny + url_git: '' +ANOVAShiny2: + version: 0.1.0 + title: Interactive Document for Working with Analysis of Variance + maintainer: Kartikeya Bolar + description: An interactive document on the topic of one-way and two-way analysis + of variance using 'rmarkdown' and 'shiny' packages. Runtime examples are provided + in the package function as well as at . + date_publication: '2020-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ANOVAShiny2 + url_git: '' +anovir: + version: 0.1.0 + title: Analysis of Virulence + maintainer: Philip Agnew + description: |- + Epidemiological population dynamics models traditionally define + a pathogen's virulence as the increase in the per capita rate of mortality + of infected hosts due to infection. This package provides functions + allowing virulence to be estimated by maximum likelihood techniques. The + approach is based on the analysis of relative survival comparing survival + in matching cohorts of infected vs. uninfected hosts (Agnew 2019) + . + date_publication: '2020-10-24' + bug_reports: '' + url: https://www.biorxiv.org/content/10.1101/530709v1 + url_cran: https://CRAN.R-project.org/package=anovir + url_git: '' +anscombiser: + version: 1.1.0 + title: Create Datasets with Identical Summary Statistics + maintainer: Paul J. Northrop + description: |- + Anscombe's quartet are a set of four two-variable datasets that + have several common summary statistics but which have very different joint + distributions. This becomes apparent when the data are plotted, which + illustrates the importance of using graphical displays in Statistics. This + package enables the creation of datasets that have identical marginal sample + means and sample variances, sample correlation, least squares regression + coefficients and coefficient of determination. The user supplies an initial + dataset, which is shifted, scaled and rotated in order to achieve target + summary statistics. The general shape of the initial dataset is retained. + The target statistics can be supplied directly or calculated based on a + user-supplied dataset. The 'datasauRus' package + provides further examples + of datasets that have markedly different scatter plots but share many + sample summary statistics. + date_publication: '2022-10-02' + bug_reports: https://github.com/paulnorthrop/anscombiser/issues + url: https://paulnorthrop.github.io/anscombiser/ + url_cran: https://CRAN.R-project.org/package=anscombiser + url_git: https://github.com/paulnorthrop/anscombiser +ANSM5: + version: 1.1.1 + title: |- + Functions and Data for the Book "Applied Nonparametric + Statistical Methods", 5th Edition + maintainer: Neil Spencer + description: 'Functions and data to accompany the 5th edition of the book "Applied + Nonparametric Statistical Methods" (4th edition: Sprent & Smeeton, 2024, ISBN:158488701X), + the revisions from the 4th edition including a move from describing the output + from a miscellany of statistical software packages to using R. While the output + from many of the functions can also be obtained using a range of other R functions, + this package provides functions in a unified setting and give output using both + p-values and confidence intervals, exemplifying the book''s approach of treating + p-values as a guide to statistical importance and not an end product in their + own right. Please note that in creating the ANSM5 package we do not claim to have + produced software which is necessarily the most computationally efficient nor + the most comprehensive.' + date_publication: '2024-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ANSM5 + url_git: '' +AntAngioCOOL: + version: '1.2' + title: Anti-Angiogenic Peptide Prediction + maintainer: Javad Zahiri + description: 'Machine learning based package to predict anti-angiogenic peptides + using heterogeneous sequence descriptors. ''AntAngioCOOL'' exploits five descriptor + types of a peptide of interest to do prediction including: pseudo amino acid composition, + k-mer composition, k-mer composition (reduced alphabet), physico-chemical profile + and atomic profile. According to the obtained results, ''AntAngioCOOL'' reached + to a satisfactory performance in anti-angiogenic peptide prediction on a benchmark + non-redundant independent test dataset.' + date_publication: '2016-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AntAngioCOOL + url_git: '' +antaresEditObject: + version: 0.9.0 + title: Edit an 'Antares' Simulation + maintainer: Tatiana Vargas + description: |- + Edit an 'Antares' simulation before running it : create new areas, links, thermal + clusters or binding constraints or edit existing ones. Update 'Antares' general & optimization settings. + 'Antares' is an open source power system generator, more information available here : . + date_publication: '2025-02-14' + bug_reports: https://github.com/rte-antares-rpackage/antaresEditObject/issues + url: https://rte-antares-rpackage.github.io/antaresEditObject/ + url_cran: https://CRAN.R-project.org/package=antaresEditObject + url_git: https://github.com/rte-antares-rpackage/antaresEditObject +antaresProcessing: + version: 0.18.3 + title: '''Antares'' Results Processing' + maintainer: Tatiana Vargas + description: |- + Process results generated by 'Antares', a powerful open source software developed by + RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about + 'Antares' here: ). + This package provides functions to create new columns like net load, load factors, upward and + downward margins or to compute aggregated statistics like economic surpluses + of consumers, producers and sectors. + date_publication: '2024-11-27' + bug_reports: https://github.com/rte-antares-rpackage/antaresProcessing/issues + url: '' + url_cran: https://CRAN.R-project.org/package=antaresProcessing + url_git: https://github.com/rte-antares-rpackage/antaresProcessing +antaresRead: + version: 2.9.0 + title: |- + Import, Manipulate and Explore the Results of an 'Antares' + Simulation + maintainer: Tatiana Vargas + description: |- + Import, manipulate and explore results generated by 'Antares', a + powerful open source software developed by RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems + (more information about 'Antares' here : ). + date_publication: '2025-02-11' + bug_reports: https://github.com/rte-antares-rpackage/antaresRead/issues + url: https://rte-antares-rpackage.github.io/antaresRead/ + url_cran: https://CRAN.R-project.org/package=antaresRead + url_git: https://github.com/rte-antares-rpackage/antaresRead +antaresViz: + version: 0.18.3 + title: Antares Visualizations + maintainer: Tatiana Vargas + description: |- + Visualize results generated by Antares, a powerful open source software + developed by RTE to simulate and study electric power systems + (more information about 'Antares' here: ). + This package provides functions that create interactive charts to help + 'Antares' users visually explore the results of their simulations. + date_publication: '2024-12-02' + bug_reports: https://github.com/rte-antares-rpackage/antaresViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=antaresViz + url_git: https://github.com/rte-antares-rpackage/antaresViz +anthro: + version: 1.0.1 + title: Computation of the WHO Child Growth Standards + maintainer: Dirk Schumacher + description: |- + Provides WHO Child Growth Standards (z-scores) with + confidence intervals and standard errors around the + prevalence estimates, taking into account complex sample designs. + More information on the methods is + available online: + . + date_publication: '2023-09-17' + bug_reports: https://github.com/worldhealthorganization/anthro/issues + url: '' + url_cran: https://CRAN.R-project.org/package=anthro + url_git: https://github.com/worldhealthorganization/anthro +anthroplus: + version: 1.0.0 + title: |- + Computation of the WHO 2007 References for School-Age Children + and Adolescents (5 to 19 Years) + maintainer: Dirk Schumacher + description: |- + Provides WHO 2007 References for School-age Children and + Adolescents (5 to 19 years) (z-scores) with + confidence intervals and standard errors around the + prevalence estimates, taking into account complex sample designs. + More information on the methods is + available online: + . + date_publication: '2024-11-11' + bug_reports: https://github.com/WorldHealthOrganization/anthroplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=anthroplus + url_git: https://github.com/WorldHealthOrganization/anthroplus +AnthropMMD: + version: 4.0.3 + title: An R Package for the Mean Measure of Divergence (MMD) + maintainer: Frédéric Santos + description: Offers a graphical user interface for the calculation of the mean measure + of divergence, with facilities for trait selection and graphical representations + . + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AnthropMMD + url_git: https://gitlab.com/f-santos/anthropmmd/ +Anthropometry: + version: '1.19' + title: Statistical Methods for Anthropometric Data + maintainer: Guillermo Vinue + description: "Statistical methodologies especially developed to analyze anthropometric + data. These methods are aimed \t\tat providing effective solutions to some commons + problems related to Ergonomics and Anthropometry. They are based on clustering, + the \t\tstatistical concept of data depth, statistical shape analysis and archetypal + analysis. Please see Vinue (2017) ." + date_publication: '2023-02-22' + bug_reports: '' + url: https://www.uv.es/vivigui/ + url_cran: https://CRAN.R-project.org/package=Anthropometry + url_git: '' +AntibodyForests: + version: 1.0.0 + title: Delineating Inter- And Intra-Antibody Repertoire Evolution + maintainer: Daphne van Ginneken + description: |- + The generated wealth of immune repertoire sequencing data + requires software to investigate and quantify inter- and + intra-antibody repertoire evolution to uncover how B cells evolve + during immune responses. Here, we present 'AntibodyForests', a software + to investigate and quantify inter- and intra-antibody repertoire + evolution. + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AntibodyForests + url_git: '' +AntibodyTiters: + version: 0.1.24 + title: Antibody Titer Analysis of Vaccinated Patients + maintainer: Hiroaki Kato + description: |- + Visualization of antibody titer scores is valuable for examination of vaccination + effects. 'AntibodyTiters' visualizes antibody titers of all or selected patients. This + package also produces empty excel files in a specified format, in which users can fill in + experimental data for visualization. Excel files with toy data can also be produced, so that + users can see how it is visualized before obtaining real data. The data should contain + titer scores at pre-vaccination, after-1st shot, after-2nd shot, and at least one + additional sampling points. Patients with missing values can be included. The first two + sampling points (pre-vaccination and after-1st shot) will be plotted discretely, whereas + those following will be plotted on a continuous time scale that starts from the day of + second shot. Half-life of titer can also be calculated for each pair of sampling points. + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AntibodyTiters + url_git: '' +anticlust: + version: 0.8.9-1 + title: Subset Partitioning via Anticlustering + maintainer: Martin Papenberg + description: |- + The method of anticlustering partitions a pool of elements + into groups (i.e., anticlusters) with the goal of maximizing + between-group similarity or within-group heterogeneity. The + anticlustering approach thereby reverses the logic of cluster analysis + that strives for high within-group homogeneity and clear separation + between groups. Computationally, anticlustering is accomplished by + maximizing instead of minimizing a clustering objective function, such + as the intra-cluster variance (used in k-means clustering) or the sum + of pairwise distances within clusters. The main function + anticlustering() gives access to optimal and heuristic anticlustering + methods described in Papenberg and Klau (2021; + ), Brusco et al. (2020; + ), and Papenberg (2024; + ). The optimal algorithms require that an + integer linear programming solver is installed. This package will install + 'lpSolve' () + as a default solver, but it is also possible to + use the package 'Rglpk' (), + which requires the GNU linear programming + kit (), or the + package 'Rsymphony' (), which + requires the SYMPHONY ILP solver (). + 'Rglpk' and 'Rsymphony' have to be manually installed by the user because they + are only "suggested" dependencies. Full access to the + bicriterion anticlustering method proposed by Brusco et al. (2020) is + given via the function bicriterion_anticlustering(), while + kplus_anticlustering() implements the full functionality of the k-plus + anticlustering approach proposed by Papenberg (2024). Some other + functions are available to solve classical clustering problems. The + function balanced_clustering() applies a cluster analysis under size + constraints, i.e., creates equal-sized clusters. The function + matching() can be used for (unrestricted, bipartite, or K-partite) + matching. The function wce() can be used optimally solve the + (weighted) cluster editing problem, also known as correlation + clustering, clique partitioning problem or transitivity clustering. + date_publication: '2025-01-20' + bug_reports: https://github.com/m-Py/anticlust/issues + url: https://m-py.github.io/anticlust/ + url_cran: https://CRAN.R-project.org/package=anticlust + url_git: https://github.com/m-Py/anticlust +antitrust: + version: 0.99.26 + title: Tools for Antitrust Practitioners + maintainer: Charles Taragin + description: A collection of tools for antitrust practitioners, including the ability + to calibrate different consumer demand systems and simulate the effects of mergers + under different competitive regimes. + date_publication: '2022-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=antitrust + url_git: https://github.com/luciu5/antitrust +antiword: + version: 1.3.4 + title: Extract Text from Microsoft Word Documents + maintainer: Jeroen Ooms + description: |- + Wraps the 'AntiWord' utility to extract text from Microsoft Word + documents. The utility only supports the old 'doc' format, not the new xml + based 'docx' format. Use the 'xml2' package to read the latter. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/antiword/issues + url: https://docs.ropensci.org/antiword/ + url_cran: https://CRAN.R-project.org/package=antiword + url_git: '' +AntMAN: + version: 1.1.0 + title: Anthology of Mixture Analysis Tools + maintainer: Bruno Bodin + description: 'Fits finite Bayesian mixture models with a random number of components. + The MCMC algorithm implemented is based on point processes as proposed by Argiento + and De Iorio (2019) and offers a more computationally efficient + alternative to reversible jump. Different mixture kernels can be specified: univariate + Gaussian, multivariate Gaussian, univariate Poisson, and multivariate Bernoulli + (latent class analysis). For the parameters characterising the mixture kernel, + we specify conjugate priors, with possibly user specified hyper-parameters. We + allow for different choices for the prior on the number of components: shifted + Poisson, negative binomial, and point masses (i.e. mixtures with fixed number + of components).' + date_publication: '2021-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AntMAN + url_git: https://github.com/bbodin/AntMAN +AnxietySleep: + version: 0.0.1 + title: Sleep Quality and Anxiety in Confinement + maintainer: Matías Castillo-Aguilar + description: Data from the anxiety and confinement study from Alvarado-Aravena et + al. (2022) . + date_publication: '2022-12-12' + bug_reports: https://github.com/NIM-ACh/AnxietySleep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AnxietySleep + url_git: https://github.com/NIM-ACh/AnxietySleep +anybadger: + version: 0.1.0 + title: Create Custom Pipeline Badges + maintainer: Lorenzo Meninato + description: |2- + + You can use this package to create custom pipeline badges in a standard 'svg' format. + This is useful for a company to use internally, where it may not be possible + to create badges through external providers. + This project was inspired by the 'anybadge' library in python. + date_publication: '2021-01-29' + bug_reports: https://github.com/lmeninato/anybadger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=anybadger + url_git: https://github.com/lmeninato/anybadger +anyflights: + version: 0.3.5 + title: |- + Query 'nycflights13'-Like Air Travel Data for Given Years and + Airports + maintainer: Simon P. Couch + description: |- + Supplies a set of functions to query air travel data for user- + specified years and airports. Datasets include on-time flights, airlines, + airports, planes, and weather. + date_publication: '2025-01-10' + bug_reports: https://github.com/simonpcouch/anyflights/issues + url: https://simonpcouch.github.io/anyflights/ + url_cran: https://CRAN.R-project.org/package=anyflights + url_git: https://github.com/simonpcouch/anyflights +anyLib: + version: 1.0.5 + title: Install and Load Any Package from CRAN, Bioconductor or Github + maintainer: Aurelien Chateigner + description: |- + Made to make your life simpler with packages, by + installing and loading a list of packages, whether they are on CRAN, + Bioconductor or github. For github, if you do not have the full path, with + the maintainer name in it (e.g. "achateigner/topReviGO"), it will be able to + load it but not to install it. + date_publication: '2018-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=anyLib + url_git: '' +anytime: + version: 0.3.11 + title: Anything to 'POSIXct' or 'Date' Converter + maintainer: Dirk Eddelbuettel + description: |- + Convert input in any one of character, integer, numeric, factor, + or ordered type into 'POSIXct' (or 'Date') objects, using one of a number of + predefined formats, and relying on Boost facilities for date and time parsing. + date_publication: '2024-12-19' + bug_reports: https://github.com/eddelbuettel/anytime/issues + url: https://dirk.eddelbuettel.com/code/anytime.html + url_cran: https://CRAN.R-project.org/package=anytime + url_git: https://github.com/eddelbuettel/anytime +ao: + version: 1.1.0 + title: Alternating Optimization + maintainer: Lennart Oelschläger + description: |- + Alternating optimization is an iterative procedure that optimizes + a function by alternately performing restricted optimization over individual + parameter subsets. Instead of tackling joint optimization directly, it + breaks the problem down into simpler sub-problems. This approach can make + optimization feasible when joint optimization is too difficult. + date_publication: '2024-07-13' + bug_reports: https://github.com/loelschlaeger/ao/issues + url: https://loelschlaeger.de/ao/ + url_cran: https://CRAN.R-project.org/package=ao + url_git: https://github.com/loelschlaeger/ao/ +AOboot: + version: 0.1.1 + title: Bootstrapping in Different One-Way and Two-Way ANOVA + maintainer: Christian Blötner + description: To address the violation of the assumption of normally distributed + variables, researchers frequently employ bootstrapping. Building upon established + packages for R (Sigmann et al. (2024) , Lenth + (2024) ), we provide bootstrapping functions + to approximate a normal distribution of the parameter estimates for between-subject, + within-subject, and mixed one-way and two-way ANOVA. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AOboot + url_git: '' +aod: + version: 1.3.3 + title: Analysis of Overdispersed Data + maintainer: Renaud Lancelot + description: |- + Provides a set of functions to analyse + overdispersed counts or proportions. Most of the methods are + already available elsewhere but are scattered in different + packages. The proposed functions should be considered as + complements to more sophisticated methods such as generalized + estimating equations (GEE) or generalized linear mixed effect + models (GLMM). + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aod + url_git: '' +aods3: + version: '0.5' + title: Analysis of Overdispersed Data using S3 Methods + maintainer: Aurélie Siberchicot + description: Provides functions to analyse overdispersed counts or proportions. + These functions should be considered as complements to more sophisticated methods + such as generalized estimating equations (GEE) or generalized linear mixed effect + models (GLMM). aods3 is an S3 re-implementation of the deprecated S4 package aod. + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aods3 + url_git: '' +aoos: + version: 0.5.0 + title: Another Object Orientation System + maintainer: Sebastian Warnholz + description: |- + Another implementation of object-orientation in R. It provides + syntactic sugar for the S4 class system and two alternative new + implementations. One is an experimental version built around S4 + and the other one makes it more convenient to work with lists as objects. + date_publication: '2017-05-07' + bug_reports: https://github.com/wahani/aoos/issues + url: https://wahani.github.io/aoos + url_cran: https://CRAN.R-project.org/package=aoos + url_git: '' +aopdata: + version: 1.1.1 + title: Data from the 'Access to Opportunities Project (AOP)' + maintainer: Rafael H. M. Pereira + description: |- + Download data from the 'Access to Opportunities Project (AOP)'. The + 'aopdata' package brings annual estimates of access to employment, + health, education and social assistance services by transport mode, + as well as data on the spatial distribution of population, jobs, + health care, schools and social assistance facilities at a fine + spatial resolution for all cities included in the project. More + info on the 'AOP' website . + date_publication: '2025-01-29' + bug_reports: https://github.com/ipeaGIT/aopdata/issues + url: https://ipeagit.github.io/aopdata/ + url_cran: https://CRAN.R-project.org/package=aopdata + url_git: https://github.com/ipeaGIT/aopdata +Aoptbdtvc: + version: 0.0.3 + title: |- + A-Optimal Block Designs for Comparing Test Treatments with + Controls + maintainer: Baidya Nath Mandal + description: A collection of functions to construct A-optimal block designs for + comparing test treatments with one or more control(s). Mainly A-optimal balanced + treatment incomplete block designs, weighted A-optimal balanced treatment incomplete + block designs, A-optimal group divisible treatment designs and A-optimal balanced + bipartite block designs can be constructed using the package. The designs are + constructed using algorithms based on linear integer programming. To the best + of our knowledge, these facilities to construct A-optimal block designs for comparing + test treatments with one or more controls are not available in the existing R + packages. For more details on designs for tests versus control(s) comparisons, + please see Hedayat, A. S. and Majumdar, D. (1984) + A-Optimal Incomplete Block Designs for Control-Test Treatment Comparisons, Technometrics, + 26, 363-370 and Mandal, B. N. , Gupta, V. K., Parsad, Rajender. (2017) + Balanced treatment incomplete block designs through integer programming. Communications + in Statistics - Theory and Methods 46(8), 3728-3737. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Aoptbdtvc + url_git: '' +aoristic: + version: 1.1.1 + title: Generates Aoristic Probability Distributions + maintainer: Jerry Ratcliffe + description: |- + It can sometimes be difficult to ascertain when some events (such as property crime) + occur because the victim is not present when the crime happens. As a result, police databases often + record a 'start' (or 'from') date and time, and an 'end' (or 'to') date and time. The time span between + these date/times can be minutes, hours, or sometimes days, hence the term 'Aoristic'. + Aoristic is one of the past tenses in Greek and represents an uncertain occurrence in time. + For events with a location describes with either a latitude/longitude, or X,Y coordinate pair, + and a start and end date/time, this package generates an aoristic data frame with aoristic weighted + probability values for each hour of the week, for each observation. The coordinates are not + necessary for the program to calculate aoristic weights; however, they are part of this package + because a spatial component has been integral to aoristic analysis from the start. Dummy + coordinates can be introduced if the user only has temporal data. Outputs include an aoristic + data frame, as well as summary graphs and displays. + For more information see: + Ratcliffe, JH (2002) Aoristic signatures and the temporal analysis of high volume crime patterns, + Journal of Quantitative Criminology. 18 (1): 23-43. + Note: This package replaces an original 'aoristic' package (version 0.6) by George Kikuchi that + has been discontinued with his permission. + date_publication: '2022-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aoristic + url_git: '' +aorsf: + version: 0.1.5 + title: Accelerated Oblique Random Forests + maintainer: Byron Jaeger + description: |- + Fit, interpret, and compute predictions with oblique random + forests. Includes support for partial dependence, variable importance, + passing customized functions for variable importance and identification + of linear combinations of features. Methods for the oblique random + survival forest are described in Jaeger et al., (2023) + . + date_publication: '2024-05-30' + bug_reports: https://github.com/ropensci/aorsf/issues/ + url: https://docs.ropensci.org/aorsf/ + url_cran: https://CRAN.R-project.org/package=aorsf + url_git: https://github.com/ropensci/aorsf +aos: + version: 0.1.0 + title: Animate on Scroll Library for 'shiny' + maintainer: Félix Luginbuhl + description: |- + Trigger animation effects on scroll on any HTML element + of 'shiny' and 'rmarkdown', such as any text or plot, thanks to + the 'AOS' Animate On Scroll jQuery library. + date_publication: '2020-04-29' + bug_reports: https://github.com/lgnbhl/aos/issues + url: https://felixluginbuhl.com/aos + url_cran: https://CRAN.R-project.org/package=aos + url_git: https://github.com/lgnbhl/aos +AOV1R: + version: 0.1.0 + title: Inference in the Balanced One-Way ANOVA Model with Random Factor + maintainer: Stéphane Laurent + description: 'Provides functions to perform statistical inference in the balanced + one-way ANOVA model with a random factor: confidence intervals, prediction interval, + and Weerahandi generalized pivotal quantities. References: Burdick & Graybill + (1992, ISBN-13: 978-0824786441); Weerahandi (1995) ; + Lin & Liao (2008) .' + date_publication: '2020-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AOV1R + url_git: '' +AovBay: + version: 0.1.0 + title: |- + Classic, Nonparametric and Bayesian One-Way Analysis of Variance + Panel + maintainer: Mauricio Rojas-Campuzano + description: It covers various approaches to analysis of variance, provides an assumption + testing section in order to provide a decision diagram that allows selecting the + most appropriate technique. It provides the classical analysis of variance, the + nonparametric equivalent of Kruskal Wallis, and the Bayesian approach. These results + are shown in an interactive shiny panel, which allows modifying the arguments + of the tests, contains interactive graphics and presents automatic conclusions + depending on the tests in order to contribute to the interpretation of these analyzes. + 'AovBay' uses 'Stan' and 'FactorBayes' for Bayesian analysis and 'Highcharts' + for interactive charts. + date_publication: '2021-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AovBay + url_git: '' +apa: + version: 0.3.4 + title: Format Outputs of Statistical Tests According to APA Guidelines + maintainer: Daniel Gromer + description: |- + Formatter functions in the 'apa' package take the return value of a + statistical test function, e.g. a call to chisq.test() and return a string + formatted according to the guidelines of the APA (American Psychological + Association). + date_publication: '2023-10-06' + bug_reports: https://github.com/dgromer/apa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=apa + url_git: https://github.com/dgromer/apa +apache.sedona: + version: 1.7.0 + title: R Interface for Apache Sedona + maintainer: Apache Sedona + description: |- + R interface for 'Apache Sedona' based on 'sparklyr' + (). + date_publication: '2024-12-03' + bug_reports: https://github.com/apache/sedona/issues + url: https://sedona.apache.org/ + url_cran: https://CRAN.R-project.org/package=apache.sedona + url_git: https://github.com/apache/sedona/ +ApacheLogProcessor: + version: 0.2.3 + title: Process the Apache Web Server Log Files + maintainer: Diogo Silveira Mendonca + description: Provides capabilities to process Apache HTTPD Log files.The main functionalities + are to extract data from access and error log files to data frames. + date_publication: '2018-07-19' + bug_reports: https://github.com/diogosmendonca/ApacheLogProcessor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ApacheLogProcessor + url_git: https://github.com/diogosmendonca/ApacheLogProcessor +APackOfTheClones: + version: 1.2.4 + title: |- + Visualization of Clonal Expansion for Single Cell Immune + Profiles + maintainer: Qile Yang + description: 'Visualize clonal expansion via circle-packing. ''APackOfTheClones'' + extends ''scRepertoire'' to produce a publication-ready visualization of clonal + expansion at a single cell resolution, by representing expanded clones as differently + sized circles. The method was originally implemented by Murray Christian and Ben + Murrell in the following immunology study: Ma et al. (2021) .' + date_publication: '2024-11-18' + bug_reports: https://github.com/Qile0317/APackOfTheClones/issues + url: https://qile0317.github.io/APackOfTheClones/ + url_cran: https://CRAN.R-project.org/package=APackOfTheClones + url_git: https://github.com/Qile0317/APackOfTheClones +apaTables: + version: 2.0.8 + title: Create American Psychological Association (APA) Style Tables + maintainer: David Stanley + description: |- + A common task faced by researchers is the creation of APA style + (i.e., American Psychological Association style) tables from statistical + output. In R a large number of function calls are often needed to obtain all of + the desired information for a single APA style table. As well, the process of + manually creating APA style tables in a word processor is prone to transcription + errors. This package creates Word files (.doc files) containing APA style tables + for several types of analyses. Using this package minimizes transcription errors + and reduces the number commands needed by the user. + date_publication: '2021-01-04' + bug_reports: https://github.com/dstanley4/apaTables/issues + url: '' + url_cran: https://CRAN.R-project.org/package=apaTables + url_git: https://github.com/dstanley4/apaTables +apaText: + version: 0.1.7 + title: |- + Create R Markdown Text for Results in the Style of the American + Psychological Association (APA) + maintainer: David Stanley + description: Create APA style text from analyses for use within R Markdown documents. + Descriptive statistics, confidence intervals, and cell sizes are reported. + date_publication: '2023-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apaText + url_git: '' +apc: + version: 2.0.0 + title: Age-Period-Cohort Analysis + maintainer: Bent Nielsen + description: Functions for age-period-cohort analysis. Aggregate data can be organised + in matrices indexed by age-cohort, age-period or cohort-period. The data can include + dose and response or just doses. The statistical model is a generalized linear + model (GLM) allowing for 3,2,1 or 0 of the age-period-cohort factors. Individual-level + data should have a row for each individual and columns for each of age, period, + and cohort. The statistical model for repeated cross-section is a generalized + linear model. The statistical model for panel data is ordinary least squares. + The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) + is used. Thus, the analysis does not rely on ad hoc identification. + date_publication: '2020-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apc + url_git: '' +APCalign: + version: 1.1.3 + title: Resolving Plant Taxon Names Using the Australian Plant Census + maintainer: Daniel Falster + description: The process of resolving taxon names is necessary when working with + biodiversity data. 'APCalign' uses the Australian Plant Census (APC) and the Australian + Plant Name Index (APNI) to align and update plant taxon names to current, accepted + standards. 'APCalign' also supplies information about the established status of + plant taxa across different states/territories. + date_publication: '2025-02-11' + bug_reports: https://github.com/traitecoevo/APCalign/issues + url: https://traitecoevo.github.io/APCalign/ + url_cran: https://CRAN.R-project.org/package=APCalign + url_git: https://github.com/traitecoevo/APCalign +APCanalysis: + version: '1.0' + title: |- + Analysis of Unreplicated Orthogonal Experiments using All + Possible Comparisons + maintainer: Arden Miller + description: Analysis of data from unreplicated orthogonal experiments such as + 2-level factorial and fractional factorial designs and Plackett-Burman designs + using the all possible comparisons (APC) methodology developed by Miller (2005) + . + date_publication: '2017-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=APCanalysis + url_git: '' +apcf: + version: 0.3.2 + title: Adapted Pair Correlation Function + maintainer: Robert Nuske + description: |- + The adapted pair correlation function transfers the concept of the + pair correlation function from point patterns to patterns of objects of + finite size and irregular shape (e.g. lakes within a country). The pair + correlation function describes the spatial distribution of objects, e.g. + random, aggregated or regularly spaced. This is a reimplementation of the + method suggested by Nuske et al. (2009) + using the library 'GEOS'. + date_publication: '2025-02-28' + bug_reports: https://github.com/rnuske/apcf/issues + url: https://rnuske.github.io/apcf/ + url_cran: https://CRAN.R-project.org/package=apcf + url_git: https://github.com/rnuske/apcf +APCI: + version: 1.0.8 + title: |- + A New Age-Period-Cohort Model for Describing and Investigating + Inter-Cohort Differences and Life Course Dynamics + maintainer: Jiahui Xu + description: It implemented Age-Period-Interaction Model (APC-I Model) proposed + in the paper of Liying Luo and James S. Hodges in 2019. A new age-period-cohort + model for describing and investigating inter-cohort differences and life course + dynamics. + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=APCI + url_git: '' +apcluster: + version: 1.4.13 + title: Affinity Propagation Clustering + maintainer: Ulrich Bodenhofer + description: |- + Implements Affinity Propagation clustering introduced by Frey and + Dueck (2007) . The algorithms are largely + analogous to the 'Matlab' code published by Frey and Dueck. + The package further provides leveraged affinity propagation and an + algorithm for exemplar-based agglomerative clustering that can also be + used to join clusters obtained from affinity propagation. Various + plotting functions are available for analyzing clustering results. + date_publication: '2024-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apcluster + url_git: https://github.com/UBod/apcluster +aPCoA: + version: '1.3' + title: Covariate Adjusted PCoA Plot + maintainer: Yushu Shi + description: In fields such as ecology, microbiology, and genomics, non-Euclidean + distances are widely applied to describe pairwise dissimilarity between samples. + Given these pairwise distances, principal coordinates analysis (PCoA) is commonly + used to construct a visualization of the data. However, confounding covariates + can make patterns related to the scientific question of interest difficult to + observe. We provide 'aPCoA' as an easy-to-use tool to improve data visualization + in this context, enabling enhanced presentation of the effects of interest. Details + are described in Yushu Shi, Liangliang Zhang, Kim-Anh Do, Christine Peterson and + Robert Jenq (2020) Bioinformatics, Volume 36, Issue 13, 4099-4101. + date_publication: '2021-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aPCoA + url_git: '' +APCtools: + version: 1.0.4 + title: Routines for Descriptive and Model-Based APC Analysis + maintainer: Alexander Bauer + description: |- + Age-Period-Cohort (APC) analyses are used to differentiate relevant drivers for long-term developments. + The 'APCtools' package offers visualization techniques and general routines to simplify the workflow of an APC analysis. + Sophisticated functions are available both for descriptive and regression model-based analyses. + For the former, we use density (or ridgeline) matrices and (hexagonally binned) heatmaps as innovative visualization + techniques building on the concept of Lexis diagrams. + Model-based analyses build on the separation of the temporal dimensions based on generalized additive models, + where a tensor product interaction surface (usually between age and period) is utilized + to represent the third dimension (usually cohort) on its diagonal. + Such tensor product surfaces can also be estimated while accounting for + further covariates in the regression model. + See Weigert et al. (2021) for methodological details. + date_publication: '2023-01-13' + bug_reports: https://github.com/bauer-alex/APCtools/issues + url: https://bauer-alex.github.io/APCtools/ + url_cran: https://CRAN.R-project.org/package=APCtools + url_git: '' +apdesign: + version: 1.0.0 + title: An Implementation of the Additive Polynomial Design Matrix + maintainer: Tyler Matta + description: |- + An implementation of the additive polynomial (AP) design matrix. It + constructs and appends an AP design matrix to a data frame for use with + longitudinal data subject to seasonality. + date_publication: '2016-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apdesign + url_git: '' +ape: + version: 5.8-1 + title: Analyses of Phylogenetics and Evolution + maintainer: Emmanuel Paradis + description: Functions for reading, writing, plotting, and manipulating phylogenetic + trees, analyses of comparative data in a phylogenetic framework, ancestral character + analyses, analyses of diversification and macroevolution, computing distances + from DNA sequences, reading and writing nucleotide sequences as well as importing + from BioConductor, and several tools such as Mantel's test, generalized skyline + plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation + of absolute evolutionary rates and clock-like trees using mean path lengths and + penalized likelihood, dating trees with non-contemporaneous sequences, translating + DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation + can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several + methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding + triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, + Muscle) whose results are returned into R. + date_publication: '2024-12-16' + bug_reports: https://github.com/emmanuelparadis/ape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ape + url_git: https://github.com/emmanuelparadis/ape +apercu: + version: 0.2.5 + title: Quick Look at your Data + maintainer: Aurelien Chateigner + description: |- + The goal is to print an "aperçu", a short view of a vector, a + matrix, a data.frame, a list or an array. By default, it prints the first 5 + elements of each dimension. By default, the number of columns is equal to + the number of lines. If you want to control the selection of the elements, + you can pass a list, with each element being a vector giving the selection + for each dimension. + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apercu + url_git: '' +apex: + version: 1.0.6 + title: Phylogenetic Methods for Multiple Gene Data + maintainer: Klaus Schliep + description: |- + Toolkit for the analysis of multiple gene data (Jombart et al. 2017) . + 'apex' implements the new S4 classes 'multidna', 'multiphyDat' and associated methods to handle aligned DNA sequences from multiple genes. + date_publication: '2024-01-31' + bug_reports: https://github.com/thibautjombart/apex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=apex + url_git: https://github.com/thibautjombart/apex +apexcharter: + version: 0.4.4 + title: |- + Create Interactive Chart with the JavaScript 'ApexCharts' + Library + maintainer: Victor Perrier + description: |- + Provides an 'htmlwidgets' interface to 'apexcharts.js'. + 'Apexcharts' is a modern JavaScript charting library to build interactive charts and visualizations with simple API. + 'Apexcharts' examples and documentation are available here: . + date_publication: '2024-09-06' + bug_reports: https://github.com/dreamRs/apexcharter/issues + url: https://dreamrs.github.io/apexcharter/ + url_cran: https://CRAN.R-project.org/package=apexcharter + url_git: https://github.com/dreamRs/apexcharter +APFr: + version: 1.0.2 + title: |- + Multiple Testing Approach using Average Power Function (APF) and + Bayes FDR Robust Estimation + maintainer: Nicolò Margaritella + description: |- + Implements a multiple testing approach to the + choice of a threshold gamma on the p-values using the + Average Power Function (APF) and Bayes False Discovery + Rate (FDR) robust estimation. Function apf_fdr() + estimates both quantities from either raw data or + p-values. Function apf_plot() produces smooth graphs + and tables of the relevant results. Details of the methods + can be found in Quatto P, Margaritella N, et al. (2019) + . + date_publication: '2019-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=APFr + url_git: '' +aphid: + version: 1.3.5 + title: Analysis with Profile Hidden Markov Models + maintainer: Shaun Wilkinson + description: |- + Designed for the development and application of + hidden Markov models and profile HMMs for biological sequence analysis. + Contains functions for multiple and pairwise sequence alignment, + model construction and parameter optimization, file import/export, + implementation of the forward, backward and Viterbi algorithms for + conditional sequence probabilities, tree-based sequence weighting, + and sequence simulation. + Features a wide variety of potential applications including + database searching, gene-finding and annotation, phylogenetic + analysis and sequence classification. + Based on the models and algorithms described in Durbin et + al (1998, ISBN: 9780521629713). + date_publication: '2022-12-05' + bug_reports: https://github.com/shaunpwilkinson/aphid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aphid + url_git: https://github.com/shaunpwilkinson/aphid +aphylo: + version: 0.3-4 + title: |- + Statistical Inference and Prediction of Annotations in + Phylogenetic Trees + maintainer: George Vega Yon + description: |- + Implements a parsimonious evolutionary model to analyze and + predict gene-functional annotations in phylogenetic trees as described in Vega + Yon et al. (2021) . Focusing on + computational efficiency, 'aphylo' makes it possible to estimate pooled + phylogenetic models, including thousands (hundreds) of annotations (trees) in + the same run. The package also provides the tools for visualization of + annotated phylogenies, calculation of posterior probabilities (prediction) + and goodness-of-fit assessment featured in Vega Yon et al. (2021). + date_publication: '2024-12-03' + bug_reports: https://github.com/USCbiostats/aphylo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aphylo + url_git: https://github.com/USCbiostats/aphylo +api2lm: + version: '0.2' + title: |- + Functions and Data Sets for the Book "A Progressive Introduction + to Linear Models" + maintainer: Joshua P. French + description: Simplifies aspects of linear regression analysis, particularly simultaneous + inference. Additionally, supports "A Progressive Introduction to Linear Models" + by Joshua French (). + date_publication: '2023-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=api2lm + url_git: '' +APIS: + version: 2.0.8 + title: |- + Auto-Adaptive Parentage Inference Software Tolerant to Missing + Parents + maintainer: Julien Roche + description: |- + Parentage assignment package. + Parentage assignment is performed based on observed average Mendelian transmission probability distributions or Exclusion. + The main functions of this package are the function APIS_2n(), APIS_3n() and launch_APIShiny(), which perform parentage assignment. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=APIS + url_git: '' +apisensr: + version: 1.0.0 + title: |- + Interface to 'episensr' for Sensitivity Analysis of + Epidemiological Results + maintainer: Denis Haine + description: API for using 'episensr', Basic sensitivity analysis of the observed + relative risks adjusting for unmeasured confounding and misclassification of the + exposure/outcome, or both. See . + date_publication: '2023-09-06' + bug_reports: https://github.com/dhaine/apisensr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=apisensr + url_git: https://github.com/dhaine/apisensr +aplore3: + version: '0.9' + title: |- + Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic + Regression" (3rd Ed., 2013) + maintainer: Luca Braglia + description: |- + An unofficial companion to "Applied + Logistic Regression" by D.W. Hosmer, S. Lemeshow and + R.X. Sturdivant (3rd ed., 2013) containing the dataset used in the book. + date_publication: '2016-10-20' + bug_reports: https://github.com/lbraglia/aplore3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aplore3 + url_git: https://github.com/lbraglia/aplore3 +aplot: + version: 0.2.5 + title: Decorate a 'ggplot' with Associated Information + maintainer: Guangchuang Yu + description: For many times, we are not just aligning plots as what 'cowplot' and + 'patchwork' did. Users would like to align associated information that requires + axes to be exactly matched in subplots, e.g. hierarchical clustering with a heatmap. + Inspired by the 'Method 2' in 'ggtree' (G Yu (2018) ), + 'aplot' provides utilities to aligns associated subplots to a main plot at different + sides (left, right, top and bottom) with axes exactly matched. + date_publication: '2025-02-27' + bug_reports: '' + url: https://yulab-smu.top/aplot/ + url_cran: https://CRAN.R-project.org/package=aplot + url_git: https://github.com/YuLab-SMU/aplot +aplotExtra: + version: 0.0.3 + title: Creating Composite Plots using 'aplot' + maintainer: Guangchuang Yu + description: Many complex plots are actually composite plots, such as 'oncoplot', + 'funkyheatmap', 'upsetplot', etc. We can produce subplots using 'ggplot2' and + combine them to create composite plots using 'aplot'. In this way, it is easy + to customize these complex plots, by adding, deleting or modifying subplots in + the final plot. This package provides a set of utilities to help users to create + subplots and complex plots. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aplotExtra + url_git: https://github.com/YuLab-SMU/aplotExtra +aplpack: + version: 1.3.5 + title: |- + Another Plot Package: 'Bagplots', 'Iconplots', 'Summaryplots', + Slider Functions and Others + maintainer: Hans Peter Wolf + description: |- + Some functions for drawing some special plots: + The function 'bagplot' plots a bagplot, + 'faces' plots chernoff faces, + 'iconplot' plots a representation of a frequency table or a data matrix, + 'plothulls' plots hulls of a bivariate data set, + 'plotsummary' plots a graphical summary of a data set, + 'puticon' adds icons to a plot, + 'skyline.hist' combines several histograms of a one dimensional data set in one plot, + 'slider' functions supports some interactive graphics, + 'spin3R' helps an inspection of a 3-dim point cloud, + 'stem.leaf' plots a stem and leaf plot, + 'stem.leaf.backback' plots back-to-back versions of stem and leaf plot. + date_publication: '2021-09-30' + bug_reports: '' + url: https://www.uni-bielefeld.de/fakultaeten/wirtschaftswissenschaften/fakultaet/lehrende-ehemalige/pwolf/wolf_aplpack/index.xml + url_cran: https://CRAN.R-project.org/package=aplpack + url_git: '' +apmx: + version: 1.1.1 + title: Automated Population Pharmacokinetic Dataset Assembly + maintainer: Stephen Amori + description: |- + Automated methods to assemble population PK (pharmacokinetic) and + PKPD (pharmacodynamic) datasets for analysis in 'NONMEM' (non-linear mixed effects + modeling) by Bauer (2019) . The package includes functions + to build datasets from SDTM (study data tabulation module) + , ADaM (analysis dataset + module) , or other dataset + formats. The package will combine population datasets, add covariates, and + create documentation to support regulatory submission and internal communication. + date_publication: '2024-01-09' + bug_reports: https://github.com/stephen-amori/apmx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=apmx + url_git: https://github.com/stephen-amori/apmx +apng: + version: '1.1' + title: Convert Png Files into Animated Png + maintainer: Quinten Stokkink + description: |- + Convert several png files into an animated png file. + This package exports only a single function `apng'. Call the + apng function with a vector of file names (which should be + png files) to convert them to a single animated png file. + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apng + url_git: '' +Apoderoides: + version: 3.0.0 + title: |- + Prioritize and Delete Erroneous Taxa in a Large Phylogenetic + Tree + maintainer: Satoshi Aoki + description: Finds, prioritizes and deletes erroneous taxa in a phylogenetic tree. + This package calculates scores for taxa in a tree. Higher score means the taxon + is more erroneous. If the score is zero for a taxon, the taxon is not erroneous. + This package also can remove all erroneous taxa automatically by iterating score + calculation and pruning taxa with the highest score. + date_publication: '2024-07-10' + bug_reports: https://github.com/Sa-to-shi-A-o-ki/Apoderoides/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Apoderoides + url_git: https://github.com/Sa-to-shi-A-o-ki/Apoderoides +apollo: + version: 0.3.4 + title: Tools for Choice Model Estimation and Application + maintainer: Stephane Hess + description: |- + Choice models are a widely used technique across numerous scientific disciplines. The Apollo package is a very flexible tool for the estimation and application + of choice models in R. Users are able to write their own + model functions or use a mix of already available ones. Random heterogeneity, + both continuous and discrete and at the level of individuals and + choices, can be incorporated for all models. There is support for both standalone + models and hybrid model structures. Both classical + and Bayesian estimation is available, and multiple discrete + continuous models are covered in addition to discrete choice. + Multi-threading processing is supported for estimation and a large + number of pre and post-estimation routines, including for computing posterior + (individual-level) distributions are available. + For examples, a manual, and a support forum, visit + . For more information on choice + models see Train, K. (2009) and Hess, + S. & Daly, A.J. (2014) for an overview + of the field. + date_publication: '2024-10-01' + bug_reports: http://www.apolloChoiceModelling.com/forum/ + url: http://www.apolloChoiceModelling.com + url_cran: https://CRAN.R-project.org/package=apollo + url_git: '' +Apollonius: + version: 1.0.1 + title: 2D Apollonius Graphs + maintainer: Stéphane Laurent + description: |- + Computation of the Apollonius diagram of given 2D points and + its dual the Apollonius graph, also known as the additively weighted + Voronoï diagram, and which is a generalization of the classical Voronoï + diagram. For references, see the bibliography in the CGAL documentation + at . + date_publication: '2023-12-13' + bug_reports: https://github.com/stla/Apollonius/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Apollonius + url_git: https://github.com/stla/Apollonius +appeears: + version: '1.1' + title: Interface to 'AppEEARS' NASA Web Services + maintainer: Koen Hufkens + description: |- + Programmatic interface to the NASA Application for Extracting and Exploring Analysis Ready Samples services (AppEEARS; ). + The package provides easy access to analysis ready earth observation data in R. + date_publication: '2023-09-15' + bug_reports: https://github.com/bluegreen-labs/appeears/issues + url: '' + url_cran: https://CRAN.R-project.org/package=appeears + url_git: https://github.com/bluegreen-labs/appeears +APPEstimation: + version: 0.1.1 + title: Adjusted Prediction Model Performance Estimation + maintainer: Eisuke Inoue + description: Calculating predictive model performance measures adjusted for predictor + distributions using density ratio method (Sugiyama et al., (2012, ISBN:9781139035613)). + L1 and L2 error for continuous outcome and C-statistics for binomial outcome are + computed. + date_publication: '2018-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=APPEstimation + url_git: '' +appleadsR: + version: 0.1.0 + title: Get Apple Search Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Apple Search + Ads using the 'Windsor.ai' API . + date_publication: '2022-11-10' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=appleadsR + url_git: '' +applicable: + version: 0.1.1 + title: A Compilation of Applicability Domain Methods + maintainer: Marly Gotti + description: |- + A modeling package compiling applicability domain methods in + R. It combines different methods to measure the amount of + extrapolation new samples can have from the training set. See Gadaleta + et al (2016) for an overview of + applicability domains. + date_publication: '2024-04-25' + bug_reports: https://github.com/tidymodels/applicable/issues + url: https://applicable.tidymodels.org + url_cran: https://CRAN.R-project.org/package=applicable + url_git: https://github.com/tidymodels/applicable +AppliedPredictiveModeling: + version: 1.1-7 + title: Functions and Data Sets for 'Applied Predictive Modeling' + maintainer: Max Kuhn + description: A few functions and several data set for the Springer book 'Applied + Predictive Modeling'. + date_publication: '2018-05-22' + bug_reports: '' + url: http://appliedpredictivemodeling.com/ + url_cran: https://CRAN.R-project.org/package=AppliedPredictiveModeling + url_git: '' +appnn: + version: 1.0-1 + title: Amyloid Propensity Prediction Neural Network + maintainer: Carlos Família + description: Amyloid propensity prediction neural network (APPNN) is an amyloidogenicity + propensity predictor based on a machine learning approach through recursive feature + selection and feed-forward neural networks, taking advantage of newly published + sequences with experimental, in vitro, evidence of amyloid formation. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=appnn + url_git: '' +apportion: + version: 0.0.1 + title: Apportion Seats + maintainer: Christopher T. Kenny + description: |- + Convert populations into integer number of seats for legislative + bodies. Implements apportionment methods used historically and currently in the + United States for reapportionment after the Census, as described in + . + date_publication: '2023-02-16' + bug_reports: https://github.com/christopherkenny/apportion/issues + url: http://christophertkenny.com/apportion/ + url_cran: https://CRAN.R-project.org/package=apportion + url_git: https://github.com/christopherkenny/apportion +appRiori: + version: 0.0.6 + title: Code and Obtain Customized Planned Comparisons with 'appRiori' + maintainer: Umberto Granziol + description: With 'appRiori' , users upload the research + variables and the app guides them to the best set of comparisons fitting the hypotheses, + for both main and interaction effects. Through a graphical explanation and empirical + examples on reproducible data, it is shown that it is possible to understand both + the logic behind the planned comparisons and the way to interpret them when a + model is tested. + date_publication: '2025-02-27' + bug_reports: https://github.com/Ugranziol/appRiori/issues + url: '' + url_cran: https://CRAN.R-project.org/package=appRiori + url_git: https://github.com/Ugranziol/appRiori +approximator: + version: 1.2-8 + title: Bayesian Prediction of Complex Computer Codes + maintainer: Robin K. S. Hankin + description: Performs Bayesian prediction of complex computer codes when fast approximations + are available. It uses a hierarchical version of the Gaussian process, originally + proposed by Kennedy and O'Hagan (2000), Biometrika 87(1):1. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=approximator + url_git: '' +approxmatch: + version: '2.0' + title: Approximately Optimal Fine Balance Matching with Multiple Groups + maintainer: Bikram Karmakar + description: |- + Tools for constructing a matched design with multiple comparison groups. + Further specifications of refined covariate balance restriction and exact match on + covariate can be imposed. Matches are approximately optimal in the sense that the + cost of the solution is at most twice the optimal cost, Crama and Spieksma (1992) + , Karmakar, Small and Rosenbaum (2019) + . + date_publication: '2020-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=approxmatch + url_git: '' +approxOT: + version: '1.2' + title: Approximate and Exact Optimal Transport Methods + maintainer: Eric Dunipace + description: |- + R and C++ functions to perform exact and + approximate optimal transport. All C++ methods can be linked + to other R packages via their header files. + date_publication: '2025-01-09' + bug_reports: https://github.com/ericdunipace/approxOT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=approxOT + url_git: https://github.com/ericdunipace/approxOT +appsflyeR: + version: 0.1.0 + title: Get Data from 'Appsflyer' via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from 'Appsflyer' + using the 'Windsor.ai' API . + date_publication: '2022-12-02' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=appsflyeR + url_git: '' +appsheet: + version: 0.1.0 + title: An Interface to the 'AppSheet' API + maintainer: Samuel Calderon + description: |- + Functionality to add, delete, read and update table + records from your 'AppSheet' apps, using the official API . + date_publication: '2023-09-18' + bug_reports: https://github.com/calderonsamuel/appsheet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=appsheet + url_git: https://github.com/calderonsamuel/appsheet +aprean3: + version: 1.0.1 + title: |- + Datasets from Draper and Smith "Applied Regression Analysis" + (3rd Ed., 1998) + maintainer: Luca Braglia + description: |- + An unofficial companion to the textbook "Applied Regression + Analysis" by N.R. Draper and H. Smith (3rd Ed., 1998) including all the + accompanying datasets. + date_publication: '2015-05-09' + bug_reports: https://github.com/lbraglia/aprean3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aprean3 + url_git: https://github.com/lbraglia/aprean3 +aprof: + version: 0.4.1 + title: Amdahl's Profiler, Directed Optimization Made Easy + maintainer: Marco D. Visser + description: |- + Assists the evaluation of whether and + where to focus code optimization, using Amdahl's law and visual aids + based on line profiling. Amdahl's profiler organizes profiling output + files (including memory profiling) in a visually appealing way. + It is meant to help to balance development + vs. execution time by helping to identify the most promising sections + of code to optimize and projecting potential gains. The package is + an addition to R's standard profiling tools and is not a wrapper for them. + date_publication: '2018-05-22' + bug_reports: http://github.com/MarcoDVisser/aprof/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aprof + url_git: http://github.com/MarcoDVisser/aprof +apsimx: + version: 2.8.0 + title: |- + Inspect, Read, Edit and Run 'APSIM' "Next Generation" and + 'APSIM' Classic + maintainer: Fernando Miguez + description: |- + The functions in this package inspect, read, edit and run files for 'APSIM' "Next Generation" ('JSON') + and 'APSIM' "Classic" ('XML'). The files with an 'apsim' extension correspond to + 'APSIM' Classic (7.x) - Windows only - and the ones with an 'apsimx' extension correspond to 'APSIM' "Next Generation". + For more information about 'APSIM' see () and for 'APSIM' + next generation (). + date_publication: '2024-08-19' + bug_reports: https://github.com/femiguez/apsimx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=apsimx + url_git: '' +apt: + version: '4.0' + title: Asymmetric Price Transmission + maintainer: Changyou Sun + description: The transmission between two time-series prices is assessed. It contains + several functions for linear and nonlinear threshold co-integration, and furthermore, + symmetric and asymmetric error correction models. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=apt + url_git: '' +APtools: + version: 6.8.8 + title: |- + Average Positive Predictive Values (AP) for Binary Outcomes and + Censored Event Times + maintainer: Hengrui Cai + description: |- + We provide tools to estimate two prediction accuracy metrics, + the average positive predictive values (AP) as well as the well-known AUC + (the area under the receiver operator characteristic curve) for risk scores. + The outcome of interest is either binary or censored event time. + Note that for censored event time, our functions' estimates, the AP and the + AUC, are time-dependent for pre-specified time interval(s). A function that + compares the APs of two risk scores/markers is also included. Optional + outputs include positive predictive values and true positive fractions at + the specified marker cut-off values, and a plot of the time-dependent AP + versus time (available for event time data). + date_publication: '2018-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=APtools + url_git: '' +apyramid: + version: 0.1.3 + title: Visualize Population Pyramids Aggregated by Age + maintainer: Zhian N. Kamvar + description: |- + Provides a quick method for visualizing non-aggregated line-list + or aggregated census data stratified by age and one or two categorical + variables (e.g. gender and health status) with any number of values. It + returns a 'ggplot' object, allowing the user to further customize the + output. This package is part of the 'R4Epis' project + . + date_publication: '2023-02-14' + bug_reports: https://github.com/R4EPI/apyramid/issues + url: https://r4epis.netlify.app/ + url_cran: https://CRAN.R-project.org/package=apyramid + url_git: https://github.com/R4EPI/apyramid +AQEval: + version: 0.6.0 + title: Air Quality Evaluation + maintainer: Karl Ropkins + description: |- + Developed for use by those tasked with the routine detection, + characterisation and quantification of discrete changes in air quality + time-series, such as identifying the impacts of air quality policy + interventions. The main functions use signal isolation then + break-point/segment (BP/S) methods based on 'strucchange' and 'segmented' + methods to detect and quantify change events (Ropkins & Tate, 2021, + ). + date_publication: '2025-01-09' + bug_reports: https://github.com/karlropkins/AQEval/issues + url: https://karlropkins.github.io/AQEval/ + url_cran: https://CRAN.R-project.org/package=AQEval + url_git: https://github.com/karlropkins/AQEval +aqfig: + version: '0.9' + title: Display Air Quality Model Output and Monitoring Data + maintainer: Jenise Swall + description: Display air quality model output and monitoring data using scatterplots, + grids, and legends. + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aqfig + url_git: '' +AQLSchemes: + version: 1.7-2 + title: Retrieving Acceptance Sampling Schemes + maintainer: John Lawson + description: |- + Functions are included for recalling AQL (Acceptable Quality Level or Acceptance Quality Level) + Based single, double, and multiple attribute sampling plans from the Military Standard (MIL-STD-105E) - American + National Standards Institute/American Society for Quality (ANSI/ASQ Z1.4) tables and for retrieving variable + sampling plans from Military Standard (MIL-STD-414) - American National Standards Institute/American Society + for Quality (ANSI/ASQ Z1.9) tables. The sources for these tables are listed in the URL: field. Also included + are functions for computing the OC (Operating Characteristic) and ASN (Average Sample Number) coordinates + for the attribute plans it recalls, and functions for computing the estimated proportion nonconforming and + the maximum allowable proportion nonconforming for variable sampling plans. The MIL-STD AQL Sampling schemes + were the most used and copied set of standards in the world. They are intended to be used for sampling a stream + of lots, and were used in contract agreements between supplier and customer companies. When the US military + dropped support of MIL-STD 105E and 414, The American National Standards Institute (ANSI) and the International + Standards Organization (ISO) adopted the standard with few changes or no changes to the central tables. This + package is useful because its computer implementation of these tables duplicates that available in other + commercial software and subscription online calculators. + date_publication: '2023-09-13' + bug_reports: '' + url: https://archive.org/details/MIL-STD-105E_1https://archive.org/details/MIL-STD-414 + url_cran: https://CRAN.R-project.org/package=AQLSchemes + url_git: '' +aqp: + version: '2.2' + title: Algorithms for Quantitative Pedology + maintainer: Dylan Beaudette + description: The Algorithms for Quantitative Pedology (AQP) project was started + in 2009 to organize a loosely-related set of concepts and source code on the topic + of soil profile visualization, aggregation, and classification into this package + (aqp). Over the past 8 years, the project has grown into a suite of related R + packages that enhance and simplify the quantitative analysis of soil profile data. + Central to the AQP project is a new vocabulary of specialized functions and data + structures that can accommodate the inherent complexity of soil profile information; + freeing the scientist to focus on ideas rather than boilerplate data processing + tasks . These functions and data structures have + been extensively tested and documented, applied to projects involving hundreds + of thousands of soil profiles, and deeply integrated into widely used tools such + as SoilWeb . Components + of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important + role in routine data analysis within the USDA-NRCS Soil Science Division. The + AQP suite of R packages offer a convenient platform for bridging the gap between + pedometric theory and practice. + date_publication: '2025-02-15' + bug_reports: https://github.com/ncss-tech/aqp/issues + url: https://ncss-tech.github.io/AQP/ + url_cran: https://CRAN.R-project.org/package=aqp + url_git: https://github.com/ncss-tech/aqp +AquaAnalytix: + version: 0.1.0 + title: Water Quality Analysis + maintainer: Tanuj Misra + description: A varied array of mathematical derivations from various titrimetric + and colorimetric methods for analyzing water quality parameters were condensed + and integrated for the better physicochemical analysis. It is indispensable for + managing any aquatic ecosystem, including aquaculture facilities. By substituting + titrant and spectrophotometric absorbance readings, accurate determination of + the concentrations of critical parameters such as Dissolved Oxygen, Free Carbon + Dioxide, Total Alkalinity, Water Hardness, Hydrogen Sulfide, Total Ammonia Nitrogen, + Nitrite, Nitrate, Chlorinity, Salinity, Inorganic Phosphate, and Transparency + can be facilitated APHA(2017,ISBN:9780875532875). + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AquaAnalytix + url_git: '' +AquaBEHER: + version: 1.4.0 + title: |- + Estimation and Prediction of Wet Season Calendar and Soil Water + Balance for Agriculture + maintainer: Robel Takele + description: |- + Computes and integrates daily potential evapotranspiration (PET) + and a soil water balance model. It allows users to estimate and predict the + wet season calendar, including onset, cessation, and duration, based + on an agroclimatic approach for a specified period. This functionality + helps in managing agricultural water resources more effectively. For + detailed methodologies, users can refer to Allen et al. (1998, + ISBN:92-5-104219-5); Allen (2005, ISBN:9780784408056); Doorenbos and + Pruitt (1975, ISBN:9251002797); Guo et al. (2016) + ; Hargreaves and Samani (1985) + ; Priestley and Taylor (1972) + . + date_publication: '2024-09-24' + bug_reports: https://github.com/RobelTakele/AquaBEHER/issues + url: https://robeltakele.github.io/AquaBEHER/ + url_cran: https://CRAN.R-project.org/package=AquaBEHER + url_git: https://github.com/RobelTakele/AquaBEHER +AQuadtree: + version: 1.0.4 + title: Confidentiality of Spatial Point Data + maintainer: Raymond Lagonigro + description: |- + Provides an automatic aggregation tool to manage point data privacy, + intended to be helpful for the production of official spatial data and for researchers. + The package pursues the data accuracy at the smallest possible areas preventing + individual information disclosure. The methodology, based on hierarchical geographic + data structures performs aggregation and local suppression of point data to ensure privacy + as described in Lagonigro, R., Oller, R., Martori J.C. (2017) . + The data structures are created following the guidelines for grid datasets from the + European Forum for Geography and Statistics. + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AQuadtree + url_git: '' +AquaEnv: + version: 1.0-4 + title: |- + Integrated Development Toolbox for Aquatic Chemical Model + Generation + maintainer: Karline Soetaert + description: |- + Toolbox for the experimental aquatic chemist, focused on + acidification and CO2 air-water exchange. It contains all elements to + model the pH, the related CO2 air-water exchange, and + aquatic acid-base chemistry for an arbitrary marine, + estuarine or freshwater system. It contains a suite of tools for + sensitivity analysis, visualisation, modelling of chemical batches, + and can be used to build dynamic models of aquatic systems. + As from version 1.0-4, it also contains functions to calculate + the buffer factors. + date_publication: '2016-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AquaEnv + url_git: '' +AQuality: + version: '1.1' + title: Water and Measurements Quality + maintainer: Maela Lupo + description: The functions proposed in this package allows to graphically evaluate + the process of measurement of the chemical components of water. TSSS() and ICHS + functions are useful to control the quality of measurements of chemical components + of a sample of water. If one or more measurements include an error, the generated + graph will indicate it with a position of the point that represents the sample + outside the confidence interval. + date_publication: '2024-07-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AQuality + url_git: '' +AquaticLifeHistory: + version: 1.0.5 + title: Life History Analysis Tools + maintainer: Jonathan Smart + description: |- + Estimate aquatic species life history using robust techniques. + This package supports users undertaking two types of analysis: 1) Growth from + length-at-age data, and 2) maturity analyses for length and/or age data. + Maturity analyses are performed using generalised linear model approaches incorporating + either a binomial or quasibinomial distribution. + Growth modelling is performed using the multimodel approach presented by + Smart et al. (2016) "Multimodel approaches in shark and ray growth studies: + strengths, weaknesses and the future" . + date_publication: '2023-11-17' + bug_reports: https://github.com/jonathansmart/AquaticLifeHistory/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AquaticLifeHistory + url_git: https://github.com/jonathansmart/AquaticLifeHistory +aquodom: + version: 0.1.1 + title: Access to Aquo domaintables from R (Dutch) + maintainer: Johan van Tent + description: |- + The Aquo Standard is the Dutch Standard for the exchange of + data in water management. With *aquodom* (short for aquo domaintables) + it is easy to exploit the API () to download domaintables + of the Aquo Standard and use them in R. + date_publication: '2022-02-12' + bug_reports: https://github.com/RedTent/aquodom/issues + url: https://redtent.github.io/aquodom/ + url_cran: https://CRAN.R-project.org/package=aquodom + url_git: '' +AR: + version: '1.1' + title: Another Look at the Acceptance-Rejection Method + maintainer: Abbas Parchami + description: In mathematics, 'rejection sampling' is a basic technique used to generate + observations from a distribution. It is also commonly called 'the Acceptance-Rejection + method' or 'Accept-Reject algorithm' and is a type of Monte Carlo method. 'Acceptance-Rejection + method' is based on the observation that to sample a random variable one can perform + a uniformly random sampling of the 2D cartesian graph, and keep the samples in + the region under the graph of its density function. Package 'AR' is able to generate/simulate + random data from a probability density function by Acceptance-Rejection method. + Moreover, this package is a useful teaching resource for graphical presentation + of Acceptance-Rejection method. From the practical point of view, the user needs + to calculate a constant in Acceptance-Rejection method, which package 'AR' is + able to compute this constant by optimization tools. Several numerical examples + are provided to illustrate the graphical presentation for the Acceptance-Rejection + Method. + date_publication: '2018-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AR + url_git: '' +ar.matrix: + version: 0.1.0 + title: Simulate Auto Regressive Data from Precision Matricies + maintainer: Neal Marquez + description: Using sparse precision matricies and Choleski factorization simulates + data that is auto-regressive. + date_publication: '2018-12-02' + bug_reports: https://github.com/nmmarquez/ar.matrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ar.matrix + url_git: '' +arabic2kansuji: + version: 0.1.3 + title: Convert Arabic Numerals to Kansuji + maintainer: Mao Kobayashi + description: |- + Simple functions to convert given Arabic numerals to Kansuji + numerical figures that represent numbers written in Chinese characters. + date_publication: '2022-10-13' + bug_reports: https://github.com/indenkun/arabic2kansuji/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arabic2kansuji + url_git: https://github.com/indenkun/arabic2kansuji +arabicStemR: + version: '1.3' + title: Arabic Stemmer for Text Analysis + maintainer: Rich Nielsen + description: Allows users to stem Arabic texts for text analysis. + date_publication: '2022-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arabicStemR + url_git: '' +arakno: + version: 1.3.0 + title: ARAchnid KNowledge Online + maintainer: Pedro Cardoso + description: Allows the user to connect with the World Spider Catalogue (WSC; ) + and the World Spider Trait (WST; ) databases. + Also performs several basic functions such as checking names validity, retrieving + coordinate data from the Global Biodiversity Information Facility (GBIF; ), + and mapping. + date_publication: '2022-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arakno + url_git: '' +ArArRedux: + version: '1.0' + title: |- + Rigorous Data Reduction and Error Propagation of Ar40 / Ar39 + Data + maintainer: Pieter Vermeesch + description: Processes noble gas mass spectrometer data to determine the isotopic + composition of argon (comprised of Ar36, Ar37, Ar38, Ar39 and Ar40) released from + neutron-irradiated potassium-bearing minerals. Then uses these compositions to + calculate precise and accurate geochronological ages for multiple samples as well + as the covariances between them. Error propagation is done in matrix form, which + jointly treats all samples and all isotopes simultaneously at every step of the + data reduction process. Includes methods for regression of the time-resolved mass + spectrometer signals to t=0 ('time zero') for both single- and multi-collector + instruments, blank correction, mass fractionation correction, detector intercalibration, + decay corrections, interference corrections, interpolation of the irradiation + parameter between neutron fluence monitors, and (weighted mean) age calculation. + All operations are performed on the logs of the ratios between the different argon + isotopes so as to properly treat them as 'compositional data', sensu Aitchison + [1986, The Statistics of Compositional Data, Chapman and Hall]. + date_publication: '2018-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ArArRedux + url_git: '' +arc: + version: '1.4' + title: Association Rule Classification + maintainer: Tomas Kliegr + description: |- + Implements the Classification-based on + Association Rules (CBA) algorithm for association rule classification. + The package, also described in Hahsler et al. (2019) , + contains several convenience methods that allow to automatically + set CBA parameters (minimum confidence, minimum support) and it also natively + handles numeric attributes by integrating a pre-discretization step. + The rule generation phase is handled by the 'arules' package. + To further decrease the size of the CBA models produced by the 'arc' package, postprocessing by the + 'qCBA' package is suggested. + date_publication: '2023-08-17' + bug_reports: https://github.com/kliegr/arc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arc + url_git: https://github.com/kliegr/arc +ARCensReg: + version: 3.0.1 + title: |- + Fitting Univariate Censored Linear Regression Model with + Autoregressive Errors + maintainer: Fernanda L. Schumacher + description: |- + It fits a univariate left, right, or interval censored linear regression model + with autoregressive errors, considering the normal or the Student-t distribution for the + innovations. It provides estimates and standard errors of the parameters, predicts + future observations, and supports missing values on the dependent variable. + References used for this package: + Schumacher, F. L., Lachos, V. H., & Dey, D. K. (2017). Censored regression models with + autoregressive errors: A likelihood-based perspective. Canadian Journal of Statistics, + 45(4), 375-392 . + Schumacher, F. L., Lachos, V. H., Vilca-Labra, F. E., & Castro, L. M. (2018). Influence + diagnostics for censored regression models with autoregressive errors. Australian & New + Zealand Journal of Statistics, 60(2), 209-229 . + Valeriano, K. A., Schumacher, F. L., Galarza, C. E., & Matos, L. A. (2021). Censored + autoregressive regression models with Student-t innovations. arXiv preprint + . + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARCensReg + url_git: '' +arcgeocoder: + version: 0.2.1 + title: Geocoding with the 'ArcGIS' REST API Service + maintainer: Diego Hernangómez + description: |- + Lite interface for finding locations of addresses or + businesses around the world using the 'ArcGIS' REST API service + . + Address text can be converted to location candidates and a location + can be converted into an address. No API key required. + date_publication: '2024-12-17' + bug_reports: https://github.com/dieghernan/arcgeocoder/issues + url: https://dieghernan.github.io/arcgeocoder/ + url_cran: https://CRAN.R-project.org/package=arcgeocoder + url_git: https://github.com/dieghernan/arcgeocoder +arcgisgeocode: + version: 0.2.2 + title: A Robust Interface to ArcGIS 'Geocoding Services' + maintainer: Josiah Parry + description: |- + A very fast and robust interface to ArcGIS 'Geocoding + Services'. Provides capabilities for reverse geocoding, finding + address candidates, character-by-character search autosuggestion, and + batch geocoding. The public 'ArcGIS World Geocoder' is accessible for + free use via 'arcgisgeocode' for all services except batch geocoding. + 'arcgisgeocode' also integrates with 'arcgisutils' to provide access + to custom locators or private 'ArcGIS World Geocoder' hosted on + 'ArcGIS Enterprise'. Learn more in the 'Geocode service' API reference + . + date_publication: '2024-09-27' + bug_reports: '' + url: https://r.esri.com/arcgisgeocode/ + url_cran: https://CRAN.R-project.org/package=arcgisgeocode + url_git: https://github.com/r-arcgis/arcgisgeocode +arcgislayers: + version: 0.3.1 + title: An Interface to ArcGIS Data Services + maintainer: Josiah Parry + description: |- + Enables users of 'ArcGIS Enterprise', 'ArcGIS Online', or + 'ArcGIS Platform' to read, write, publish, or manage vector and raster + data via ArcGIS location services REST API endpoints + . + date_publication: '2024-09-27' + bug_reports: https://github.com/R-ArcGIS/arcgislayers/issues + url: https://r.esri.com/arcgislayers/ + url_cran: https://CRAN.R-project.org/package=arcgislayers + url_git: https://github.com/R-ArcGIS/arcgislayers +arcgisplaces: + version: 0.1.1 + title: Search for POIs using ArcGIS 'Places Service' + maintainer: Josiah Parry + description: |- + The ArcGIS 'Places service' is a ready-to-use location + service that can search for businesses and geographic locations around + the world. It allows you to find, locate, and discover detailed + information about each place. Query for places near a point, within a + bounding box, filter based on categories, or provide search text. + 'arcgisplaces' integrates with 'sf' for out of the box compatibility + with other spatial libraries. Learn more in the 'Places service' API reference . + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arcgisplaces + url_git: '' +arcgisutils: + version: 0.3.1 + title: ArcGIS Utility Functions + maintainer: Josiah Parry + description: |- + Developer oriented utility functions designed to be used as + the building blocks of R packages that work with ArcGIS Location + Services. It provides functionality for authorization, Esri JSON + construction and parsing, as well as other utilities pertaining to + geometry and Esri type conversions. To support 'ArcGIS Pro' users, + authorization can be done via 'arcgisbinding'. Installation + instructions for 'arcgisbinding' can be found at + . + date_publication: '2024-09-26' + bug_reports: https://github.com/R-ArcGIS/arcgisutils/issues + url: https://r.esri.com/arcgisutils/ + url_cran: https://CRAN.R-project.org/package=arcgisutils + url_git: https://github.com/R-ArcGIS/arcgisutils +ArchaeoPhases: + version: '2.0' + title: |- + Post-Processing of Markov Chain Monte Carlo Simulations for + Chronological Modelling + maintainer: Anne Philippe + description: |- + Statistical analysis of archaeological dates and groups of + dates. This package allows to post-process Markov Chain Monte Carlo + (MCMC) simulations from 'ChronoModel' , + 'Oxcal' or 'BCal' + . It provides functions for the study of + rhythms of the long term from the posterior distribution of a series + of dates (tempo and activity plot). It also allows the estimation and + visualization of time ranges from the posterior distribution of groups + of dates (e.g. duration, transition and hiatus between successive + phases) as described in Philippe and Vibet (2020) + . + date_publication: '2024-06-16' + bug_reports: https://github.com/ArchaeoStat/ArchaeoPhases/issues + url: https://ArchaeoStat.github.io/ArchaeoPhases/ + url_cran: https://CRAN.R-project.org/package=ArchaeoPhases + url_git: https://github.com/ArchaeoStat/ArchaeoPhases +ArchaeoPhases.dataset: + version: 0.2.0 + title: Data Sets for 'ArchaeoPhases' Vignettes + maintainer: Anne Philippe + description: Provides the data sets used to build the 'ArchaeoPhases' vignettes. The + data sets were formerly distributed with 'ArchaeoPhases', however they exceed + current CRAN policy for package size. + date_publication: '2022-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ArchaeoPhases.dataset + url_git: '' +archdata: + version: 1.2-1 + title: Example Datasets from Archaeological Research + maintainer: David L. Carlson + description: The archdata package provides several types of data that are typically + used in archaeological research. It provides all of the data sets used in "Quantitative + Methods in Archaeology Using R" by David L Carlson, one of the Cambridge Manuals + in Archaeology. + date_publication: '2021-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=archdata + url_git: '' +archeofrag: + version: 1.0.0 + title: Spatial Analysis in Archaeology from Refitting Fragments + maintainer: Sebastien Plutniak + description: 'Methods to analyse spatial units in archaeology from the relationships + between refitting fragmented objects scattered in these units (e.g. stratigraphic + layers). Graphs are used to model archaeological observations. The package is + mainly based on the ''igraph'' package for graph analysis. Functions can: 1) create, + manipulate, and simulate fragmentation graphs, 2) measure the cohesion and admixture + of archaeological spatial units, and 3) characterise the topology of a specific + set of refitting relationships. Empirical datasets are provided as examples. Documentation + about ''archeofrag'' is provided by the vignette included in this package, by + the accompanying scientific papers: Plutniak (2021, Journal of Archaeological + Science, ) and Plutniak (2022, Journal of Open + Source Software, ). This package is complemented by a + companion GUI application available at .' + date_publication: '2024-12-17' + bug_reports: https://github.com/sebastien-plutniak/archeofrag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=archeofrag + url_git: https://github.com/sebastien-plutniak/archeofrag +archeofrag.gui: + version: 0.1.0 + title: Spatial Analysis in Archaeology from Refitting Fragments (GUI) + maintainer: Sebastien Plutniak + description: 'A ''Shiny'' application to access the functionalities and datasets + of the ''archeofrag'' package for spatial analysis in archaeology from refitting + data. Quick and seamless exploration of archaeological refitting datasets. Features + include: exclusive focus on connection relationships (i.e. physical refits), built-in + documentation and convenient workflow, plot generation and export, R code generation + to re-execute the simulations in R and ensure reproducibility, support for parallel + computing to speed up computation. A demonstration version of the app is available + at .' + date_publication: '2025-01-08' + bug_reports: https://github.com/sebastien-plutniak/archeofrag.gui/issues + url: '' + url_cran: https://CRAN.R-project.org/package=archeofrag.gui + url_git: https://github.com/sebastien-plutniak/archeofrag.gui +archeoViz: + version: 1.3.5 + title: |- + Visualisation, Exploration, and Web Communication of + Archaeological Spatial Data + maintainer: Sebastien Plutniak + description: An R 'Shiny' application for visual and statistical exploration and + web communication of archaeological spatial data, either remains or sites. It + offers interactive 3D and 2D visualisations (cross sections and maps of remains, + timeline of the work made in a site) which can be exported in SVG and HTML formats. + It performs simple spatial statistics (convex hull, regression surfaces, 2D kernel + density estimation) and allows exporting data to other online applications for + more complex methods. 'archeoViz' can be used offline locally or deployed on a + server, either with interactive input of data or with a static data set. Example + is provided at . + date_publication: '2024-06-17' + bug_reports: https://github.com/sebastien-plutniak/archeoviz/issues + url: https://archeoviz.hypotheses.org + url_cran: https://CRAN.R-project.org/package=archeoViz + url_git: https://github.com/sebastien-plutniak/archeoviz +archetypal: + version: 1.3.1 + title: Finds the Archetypal Analysis of a Data Frame + maintainer: Demetris Christopoulos + description: |- + Performs archetypal analysis by using Principal Convex Hull Analysis + under a full control of all algorithmic parameters. + It contains a set of functions for determining the initial solution, the optimal + algorithmic parameters and the optimal number of archetypes. + Post run tools are also available for the assessment of the derived solution. + Morup, M., Hansen, LK (2012) . + Hochbaum, DS, Shmoys, DB (1985) . + Eddy, WF (1977) . + Barber, CB, Dobkin, DP, Huhdanpaa, HT (1996) . + Christopoulos, DT (2016) . + Falk, A., Becker, A., Dohmen, T., Enke, B., Huffman, D., Sunde, U. (2018), . + Christopoulos, DT (2015) . + Murari, A., Peluso, E., Cianfrani, Gaudio, F., Lungaroni, M., (2019), . + date_publication: '2024-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=archetypal + url_git: '' +archetyper: + version: 0.1.0 + title: An Archetype for Data Mining and Data Science Projects + maintainer: Michael Korvink + description: A project template to support the data science workflow. + date_publication: '2021-03-17' + bug_reports: https://github.com/mkorvink/archetyper/issues + url: https://mkorvink.github.io/archetyper/index.html + url_cran: https://CRAN.R-project.org/package=archetyper + url_git: '' +archetypes: + version: 2.2-0.1 + title: Archetypal Analysis + maintainer: Manuel J. A. Eugster + description: |- + The main function archetypes implements a + framework for archetypal analysis supporting arbitrary + problem solving mechanisms for the different conceptual + parts of the algorithm. + date_publication: '2019-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=archetypes + url_git: '' +archiDART: + version: '3.4' + title: |- + Plant Root System Architecture Analysis Using DART and RSML + Files + maintainer: Benjamin M Delory + description: 'Analysis of complex plant root system architectures (RSA) using the + output files created by Data Analysis of Root Tracings (DART), an open-access + software dedicated to the study of plant root architecture and development across + time series (Le Bot et al (2010) "DART: a software to analyse root system architecture + and development from captured images", Plant and Soil, ), + and RSA data encoded with the Root System Markup Language (RSML) (Lobet et al + (2015) "Root System Markup Language: toward a unified root architecture description + language", Plant Physiology, ). More information can + be found in Delory et al (2016) "archiDART: an R package for the automated computation + of plant root architectural traits", Plant and Soil, .' + date_publication: '2021-02-11' + bug_reports: https://github.com/archiDART/archidart/issues + url: https://archidart.github.io/ + url_cran: https://CRAN.R-project.org/package=archiDART + url_git: '' +archive: + version: 1.1.11 + title: Multi-Format Archive and Compression Support + maintainer: Gábor Csárdi + description: |- + Bindings to 'libarchive' the + Multi-format archive and compression library. Offers R connections and + direct extraction for many archive formats including 'tar', 'ZIP', + '7-zip', 'RAR', 'CAB' and compression formats including 'gzip', + 'bzip2', 'compress', 'lzma' and 'xz'. + date_publication: '2025-02-05' + bug_reports: https://github.com/r-lib/archive/issues + url: https://archive.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=archive + url_git: https://github.com/r-lib/archive +archiveRetriever: + version: 0.4.0 + title: Retrieve Archived Web Pages from the 'Internet Archive' + maintainer: Lukas Isermann + description: |- + Scraping content from archived web pages stored in + the 'Internet Archive' () using a systematic + workflow. Get an overview of the mementos available from the + respective homepage, retrieve the Urls and links of the page and + finally scrape the content. The final output is stored in tibbles, + which can be then easily used for further analysis. + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=archiveRetriever + url_git: https://github.com/liserman/archiveRetriever/ +archivist: + version: 2.3.8 + title: Tools for Storing, Restoring and Searching for R Objects + maintainer: Przemyslaw Biecek + description: |- + Data exploration and modelling is a process in which a lot of data + artifacts are produced. Artifacts like: subsets, data aggregates, plots, + statistical models, different versions of data sets and different versions + of results. The more projects we work with the more artifacts are produced + and the harder it is to manage these artifacts. Archivist helps to store + and manage artifacts created in R. Archivist allows you to store selected + artifacts as a binary files together with their metadata and relations. + Archivist allows to share artifacts with others, either through shared + folder or github. Archivist allows to look for already created artifacts by + using it's class, name, date of the creation or other properties. Makes it + easy to restore such artifacts. Archivist allows to check if new artifact + is the exact copy that was produced some time ago. That might be useful + either for testing or caching. + date_publication: '2024-08-29' + bug_reports: https://github.com/pbiecek/archivist/issues + url: https://pbiecek.github.io/archivist/ + url_cran: https://CRAN.R-project.org/package=archivist + url_git: '' +archivist.github: + version: 0.2.6 + title: Tools for Archiving, Managing and Sharing R Objects via GitHub + maintainer: Marcin Kosinski + description: The extension of the 'archivist' package integrating the archivist + with GitHub via GitHub API, 'git2r' packages and 'httr' package. + date_publication: '2018-08-07' + bug_reports: https://github.com/MarcinKosinski/archivist.github/issues + url: http://marcinkosinski.github.io/archivist.github/ + url_cran: https://CRAN.R-project.org/package=archivist.github + url_git: '' +ArCo: + version: 0.3-1 + title: Artificial Counterfactual Package + maintainer: Gabriel F. R. Vasconcelos + description: Set of functions to analyse and estimate Artificial Counterfactual + models from Carvalho, Masini and Medeiros (2016) . + date_publication: '2017-11-05' + bug_reports: https://github.com/gabrielrvsc/ARCO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ArCo + url_git: '' +ARCokrig: + version: 0.1.2 + title: Autoregressive Cokriging Models for Multifidelity Codes + maintainer: Pulong Ma + description: For emulating multifidelity computer models. The major methods include + univariate autoregressive cokriging and multivariate autoregressive cokriging. + The autoregressive cokriging methods are implemented for both hierarchically nested + design and non-nested design. For hierarchically nested design, the model parameters + are estimated via standard optimization algorithms; For non-nested design, the + model parameters are estimated via Monte Carlo expectation-maximization (MCEM) + algorithms. In both cases, the priors are chosen such that the posterior distributions + are proper. Notice that the uniform priors on range parameters in the correlation + function lead to improper posteriors. This should be avoided when Bayesian analysis + is adopted. The development of objective priors for autoregressive cokriging models + can be found in Pulong Ma (2020) . The development of + the multivariate autoregressive cokriging models with possibly non-nested design + can be found in Pulong Ma, Georgios Karagiannis, Bledar A Konomi, Taylor G Asher, + Gabriel R Toro, and Andrew T Cox (2019) . + date_publication: '2021-12-02' + bug_reports: https://github.com/pulongma/ARCokrig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ARCokrig + url_git: '' +arcpbf: + version: 0.1.6 + title: Process ArcGIS Protocol Buffer FeatureCollections + maintainer: Josiah Parry + description: |- + Fast processing of ArcGIS FeatureCollection protocol buffers in R. + It is designed to work seamlessly with 'httr2' and integrates with 'sf'. + date_publication: '2024-10-01' + bug_reports: https://github.com/R-ArcGIS/arcpbf/issues + url: https://r.esri.com/arcpbf/ + url_cran: https://CRAN.R-project.org/package=arcpbf + url_git: https://github.com/R-ArcGIS/arcpbf +arcpullr: + version: 0.3.0 + title: Pull Data from an 'ArcGIS REST' API + maintainer: Paul Frater + description: |- + Functions to efficiently query 'ArcGIS REST' APIs + . + Both spatial and SQL queries can be used to retrieve data. + Simple Feature (sf) objects are utilized to perform spatial queries. + This package was neither produced nor is maintained by Esri. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arcpullr + url_git: '' +arcpy: + version: 0.4-0 + title: Interface to 'ArcGIS' 'Python' Modules + maintainer: Michael Koohafkan + description: |- + An interface to the 'ArcGIS' 'arcpy' and 'arcgis' 'python' API + . + Provides various tools for installing and configuring a 'Conda' environment + for accessing 'ArcGIS' geoprocessing functions. Helper functions for + manipulating and converting 'ArcGIS' objects from R are also provided. + date_publication: '2024-01-22' + bug_reports: https://github.com/mkoohafkan/arcpy/issues + url: https://hydroecology.net/arcpy/ + url_cran: https://CRAN.R-project.org/package=arcpy + url_git: https://github.com/mkoohafkan/arcpy +arctools: + version: 1.1.6 + title: |- + Processing and Physical Activity Summaries of Minute Level + Activity Data + maintainer: Marta Karas + description: Provides functions to process minute level actigraphy-measured activity + counts data and extract commonly used physical activity volume and fragmentation + metrics. + date_publication: '2022-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arctools + url_git: '' +ArDec: + version: 2.1-1 + title: Time Series Autoregressive-Based Decomposition + maintainer: Susana Barbosa + description: Autoregressive-based decomposition of a time series based on the approach + in West (1997). Particular cases include the extraction of trend and seasonal + components. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ArDec + url_git: '' +ARDECO: + version: 2.1.0 + title: Annual Regional Database of the European Commission (ARDECO) + maintainer: Carmelo Attardo + description: |- + A set of functions to access the 'ARDECO' (Annual Regional Database + of the European Commission) data directly from the official ARDECO public + repository through the exploitation of the 'ARDECO' APIs. + The APIs are completely transparent to the user and the provided functions + provide a direct access to the 'ARDECO' data. + The 'ARDECO' database is a collection of variables related to demography, + employment, labour market, domestic product, capital formation. + Each variable can be exposed in one or more units of measure as well as + refers to total values plus additional dimensions like economic sectors, gender, + age classes. Data can be also aggregated at country level according + to the tercet classes as defined by EUROSTAT. + The description of the 'ARDECO' database can be found at the following URL + . + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARDECO + url_git: '' +ARDL: + version: 0.2.4 + title: ARDL, ECM and Bounds-Test for Cointegration + maintainer: Kleanthis Natsiopoulos + description: |- + Creates complex autoregressive distributed lag (ARDL) models and + constructs the underlying unrestricted and restricted error correction + model (ECM) automatically, just by providing the order. It also performs + the bounds-test for cointegration as described in Pesaran et al. (2001) + and provides the multipliers and the cointegrating + equation. The validity and the accuracy of this package have been verified + by successfully replicating the results of Pesaran et al. (2001) in + Natsiopoulos and Tzeremes (2022) . + date_publication: '2023-08-21' + bug_reports: https://github.com/Natsiopoulos/ARDL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ARDL + url_git: https://github.com/Natsiopoulos/ARDL +ardl.nardl: + version: 1.3.0 + title: |- + Linear and Nonlinear Autoregressive Distributed Lag Models: + General-to-Specific Approach + maintainer: Eric I. Otoakhia + description: Estimate the linear and nonlinear autoregressive distributed lag (ARDL + & NARDL) models and the corresponding error correction models, and test for longrun + and short-run asymmetric. The general-to-specific approach is also available in + estimating the ARDL and NARDL models. The Pesaran, Shin & Smith (2001) () + bounds test for level relationships is also provided. The 'ardl.nardl' package + also performs short-run and longrun symmetric restrictions available at Shin et + al. (2014) and their corresponding tests. + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ardl.nardl + url_git: '' +ards: + version: 0.1.1 + title: Creates Analysis Results Datasets + maintainer: David Bosak + description: |- + Contains functions to help create an Analysis Results Dataset. + The dataset follows industry recommended structure. The dataset can be + created in multiple passes, using different data frames as input. Analysis + Results Datasets are used in the pharmaceutical and biotech industries + to capture analysis in a common tabular data structure. + date_publication: '2023-03-21' + bug_reports: https://github.com/dbosak01/ards/issues + url: https://ards.r-sassy.org + url_cran: https://CRAN.R-project.org/package=ards + url_git: '' +area: + version: 0.2.0 + title: Calculate Area of Triangles and Polygons + maintainer: Michael Sumner + description: |- + Calculate the area of triangles and polygons using the shoelace + formula. Area may be signed, taking into account path orientation, or unsigned, + ignoring path orientation. The shoelace formula is described at + . + date_publication: '2023-12-21' + bug_reports: https://github.com/hypertidy/area/issues + url: '' + url_cran: https://CRAN.R-project.org/package=area + url_git: https://github.com/hypertidy/area +areabiplot: + version: 1.0.0 + title: Area Biplot + maintainer: Alberto Silva + description: |- + Considering an (n x m) data matrix X, this package is based on the method proposed + by Gower, Groener, and Velden (2010) , and + utilize the resulting matrices from the extended version of the NIPALS decomposition + to determine n triangles whose areas are used to visually estimate the elements of + a specific column of X. After a 90-degree rotation of the sample points, the triangles + are drawn regarding the following points: 1.the origin of the axes; 2.the sample points; + 3. the vector endpoint representing some variable. + date_publication: '2021-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=areabiplot + url_git: '' +areal: + version: 0.1.8 + title: Areal Weighted Interpolation + maintainer: Christopher Prener + description: |- + A pipeable, transparent implementation of areal weighted interpolation + with support for interpolating multiple variables in a single function call. + These tools provide a full-featured workflow for validation and estimation + that fits into both modern data management (e.g. tidyverse) and spatial + data (e.g. sf) frameworks. + date_publication: '2022-05-31' + bug_reports: https://github.com/chris-prener/areal/issues + url: https://chris-prener.github.io/areal/ + url_cran: https://CRAN.R-project.org/package=areal + url_git: '' +arealDB: + version: 0.9.4 + title: Harmonise and Integrate Heterogeneous Areal Data + maintainer: Steffen Ehrmann + description: |- + Many relevant applications in the environmental and socioeconomic + sciences use areal data, such as biodiversity checklists, agricultural statistics, + or socioeconomic surveys. For applications that surpass the spatial, temporal or + thematic scope of any single data source, data must be integrated from several + heterogeneous sources. Inconsistent concepts, definitions, or messy data tables + make this a tedious and error-prone process. 'arealDB' tackles those problems and + helps the user to integrate a harmonised databases of areal data. Read the paper + at Ehrmann, Seppelt & Meyer (2020) . + date_publication: '2025-01-20' + bug_reports: https://github.com/luckinet/arealDB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arealDB + url_git: https://github.com/luckinet/arealDB +areaplot: + version: 2.1.3 + title: Plot Stacked Areas and Confidence Bands as Filled Polygons + maintainer: Arni Magnusson + description: |- + Plot stacked areas and confidence bands as filled polygons, or add + polygons to existing plots. A variety of input formats are supported, + including vectors, matrices, data frames, formulas, etc. + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=areaplot + url_git: https://github.com/arni-magnusson/areaplot +arena2r: + version: 1.0.0 + title: Plots, Summary Statistics and Tools for Arena Simulation Users + maintainer: Pedro Nascimento de Lima + description: Reads Arena CSV output files and + generates nice tables and plots. The package contains a Shiny App that can be + used to interactively visualize Arena's results. + date_publication: '2018-10-19' + bug_reports: https://github.com/pedroliman/arena2r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arena2r + url_git: https://github.com/pedroliman/arena2r +arenar: + version: 0.2.0 + title: Arena for the Exploration and Comparison of any ML Models + maintainer: Piotr Piątyszek + description: |- + Generates data for challenging machine learning models in 'Arena' + - an interactive web application. You can start + the server with XAI (Explainable Artificial Intelligence) plots to be + generated on-demand or precalculate and auto-upload data file beside + shareable 'Arena' URL. + date_publication: '2020-10-01' + bug_reports: https://github.com/ModelOriented/ArenaR/issues + url: https://arenar.drwhy.ai + url_cran: https://CRAN.R-project.org/package=arenar + url_git: https://github.com/ModelOriented/ArenaR +arf: + version: 0.2.4 + title: Adversarial Random Forests + maintainer: Marvin N. Wright + description: |- + Adversarial random forests (ARFs) recursively partition data into + fully factorized leaves, where features are jointly independent. The + procedure is iterative, with alternating rounds of generation and + discrimination. Data becomes increasingly realistic at each round, until + original and synthetic samples can no longer be reliably distinguished. + This is useful for several unsupervised learning tasks, such as density + estimation and data synthesis. Methods for both are implemented in this + package. ARFs naturally handle unstructured data with mixed continuous and + categorical covariates. They inherit many of the benefits of random forests, + including speed, flexibility, and solid performance with default parameters. + For details, see Watson et al. (2023) . + date_publication: '2025-02-24' + bug_reports: https://github.com/bips-hb/arf/issues + url: https://bips-hb.github.io/arf/ + url_cran: https://CRAN.R-project.org/package=arf + url_git: https://github.com/bips-hb/arf +arfima: + version: 1.8-1 + title: Fractional ARIMA (and Other Long Memory) Time Series Modeling + maintainer: JQ Veenstra + description: |- + Simulates, fits, and predicts long-memory and anti-persistent + time series, possibly mixed with ARMA, regression, transfer-function + components. + Exact methods (MLE, forecasting, simulation) are used. + Bug reports should be done via GitHub (at + ), where the development version + of this package lives; it can be installed using devtools. + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arfima + url_git: '' +Argentum: + version: 1.0.0 + title: Access and Import WMS and WFS Data from Argentine Organizations + maintainer: Thomas Artopoulos + description: |- + Provides functions to retrieve information from Web Feature Service (WFS) and Web Map Service (WMS) layers + from various Argentine organizations and import them into R for further analysis. + WFS and WMS are standardized protocols for serving georeferenced map data over the internet. + For more information on these services, see and . + date_publication: '2025-02-13' + bug_reports: https://github.com/thomasartopoulos/argentum/issues + url: https://thomasartopoulos.github.io/argentum/ + url_cran: https://CRAN.R-project.org/package=Argentum + url_git: https://github.com/thomasartopoulos/argentum/ +argo: + version: 3.0.2 + title: |- + Accurate Estimation of Influenza Epidemics using Google Search + Data + maintainer: Shihao Yang + description: Augmented Regression with General Online data (ARGO) for accurate estimation + of influenza epidemics in United States on national level, regional level and + state level. It replicates the method introduced in paper Yang, S., Santillana, + M. and Kou, S.C. (2015) ; Ning, S., Yang, S. and + Kou, S.C. (2019) ; Yang, S., Ning, S. and Kou, + S.C. (2021) . + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=argo + url_git: '' +argoFloats: + version: 1.0.7 + title: Analysis of Oceanographic Argo Floats + maintainer: Dan Kelley + description: Supports the analysis of oceanographic data recorded by Argo autonomous + drifting profiling floats. Functions are provided to (a) download and cache data + files, (b) subset data in various ways, (c) handle quality-control flags and (d) + plot the results according to oceanographic conventions. A shiny app is provided + for easy exploration of datasets. The package is designed to work well with the + 'oce' package, providing a wide range of processing capabilities that are particular + to oceanographic analysis. See Kelley, Harbin, and Richards (2021) + for more on the scientific context and applications. + date_publication: '2023-10-17' + bug_reports: https://github.com/ArgoCanada/argoFloats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=argoFloats + url_git: https://github.com/ArgoCanada/argoFloats +argonDash: + version: 0.2.0 + title: Argon Shiny Dashboard Template + maintainer: David Granjon + description: |- + Create awesome 'Bootstrap 4' dashboards powered by 'Argon'. + See more here . + date_publication: '2019-11-27' + bug_reports: https://github.com/RinteRface/argonDash/issues + url: '' + url_cran: https://CRAN.R-project.org/package=argonDash + url_git: https://github.com/RinteRface/argonDash +argonR: + version: 0.2.0 + title: R Interface to Argon HTML Design + maintainer: David Granjon + description: |- + R wrapper around the argon HTML library. + More at . + date_publication: '2019-11-27' + bug_reports: https://github.com/RinteRface/argonR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=argonR + url_git: https://github.com/RinteRface/argonR +ARGOS: + version: 0.1.1 + title: Automatic Regression for Governing Equations (ARGOS) + maintainer: Kevin Egan + description: Comprehensive set of tools for performing system identification of + both linear and nonlinear dynamical systems directly from data. The Automatic + Regression for Governing Equations (ARGOS) simplifies the complex task of constructing + mathematical models of dynamical systems from observed input and output data, + supporting various types of systems, including those described by ordinary differential + equations. It employs optimal numerical derivatives for enhanced accuracy and + employs formal variable selection techniques to help identify the most relevant + variables, thereby enabling the development of predictive models for system behavior + analysis. + date_publication: '2024-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARGOS + url_git: +argosfilter: + version: '0.70' + title: Argos Locations Filter + maintainer: Carla Freitas + description: Filters animal satellite tracking data obtained from the Argos system(), + following the algorithm described in Freitas et al (2008) . + It is especially indicated for telemetry studies of marine animals, where Argos + locations are predominantly of low-quality. + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=argosfilter + url_git: '' +argparse: + version: 2.2.5 + title: Command Line Optional and Positional Argument Parser + maintainer: Trevor L. Davis + description: |- + A command line parser to + be used with 'Rscript' to write "#!" shebang scripts that gracefully + accept positional and optional arguments and automatically generate usage. + date_publication: '2024-12-20' + bug_reports: https://github.com/trevorld/r-argparse/issues + url: https://trevorldavis.com/R/argparse/ + url_cran: https://CRAN.R-project.org/package=argparse + url_git: https://github.com/trevorld/r-argparse +argparser: + version: 0.7.2 + title: Command-Line Argument Parser + maintainer: David J. H. Shih + description: |- + Cross-platform command-line argument parser written purely in R + with no external dependencies. It is useful with the Rscript + front-end and facilitates turning an R script into an executable script. + date_publication: '2024-04-04' + bug_reports: https://bitbucket.org/djhshih/argparser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=argparser + url_git: https://bitbucket.org/djhshih/argparser +argus: + version: 0.1.1 + title: Random Variate Generator for the Argus Distribution + maintainer: Wolfgang Hormann + description: |2- + + Random variate generation, density, CDF and quantile function + for the Argus distribution. Especially, it includes for random variate generation a + flexible inversion method that is also fast in the varying parameter case. + A Ratio-of-Uniforms method is provided as second alternative. + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=argus + url_git: '' +ARHT: + version: 0.1.0 + title: |- + Adaptable Regularized Hotelling's T^2 Test for High-Dimensional + Data + maintainer: Haoran Li + description: |- + Perform the Adaptable Regularized Hotelling's T^2 test (ARHT) proposed by + Li et al., (2016) . Both one-sample and two-sample mean test are available with + various probabilistic alternative prior models. It contains a function to consistently + estimate higher order moments of the population covariance spectral distribution using + the spectral of the sample covariance matrix (Bai et al. (2010) ). + In addition, it contains a function to sample from 3-variate chi-squared random vectors approximately + with a given correlation matrix when the degrees of freedom are large. + date_publication: '2018-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARHT + url_git: '' +ari: + version: 0.3.5 + title: Automated R Instructor + maintainer: Sean Kross + description: |- + Create videos from 'R Markdown' documents, or images and audio + files. These images can come from image files or HTML slides, and the audio + files can be provided by the user or computer voice narration can be created + using 'Amazon Polly'. The purpose of this package is to allow users to create + accessible, translatable, and reproducible lecture videos. See + for more information. + date_publication: '2020-02-08' + bug_reports: http://github.com/seankross/ari/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ari + url_git: http://github.com/seankross/ari +ARIbrain: + version: '0.2' + title: All-Resolution Inference + maintainer: Livio Finos + description: |- + It performs All-Resolutions Inference (ARI) on functional Magnetic Resonance Image (fMRI) data. As a main feature, + it estimates lower bounds for the proportion of active voxels in a set of clusters as, for example, given by a cluster-wise analysis. + The method is described in Rosenblatt, Finos, Weeda, Solari, Goeman (2018) . + date_publication: '2018-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARIbrain + url_git: '' +aricode: + version: 1.0.3 + title: |- + Efficient Computations of Standard Clustering Comparison + Measures + maintainer: Julien Chiquet + description: |- + Implements an efficient O(n) algorithm based on bucket-sorting for + fast computation of standard clustering comparison measures. Available measures + include adjusted Rand index (ARI), normalized information distance (NID), + normalized mutual information (NMI), adjusted mutual information (AMI), + normalized variation information (NVI) and entropy, as described in Vinh et al (2009) + . Include AMI (Adjusted Mutual Information) since version 0.1.2, + a modified version of ARI (MARI), as described in Sundqvist et al. + and simple Chi-square distance since version 1.0.0. + date_publication: '2023-10-20' + bug_reports: https://github.com/jchiquet/aricode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aricode + url_git: https://github.com/jchiquet/aricode +AriGaMyANNSVR: + version: 0.1.0 + title: Hybrid ARIMA-GARCH and Two Specially Designed ML-Based Models + maintainer: Mr. Sandip Garai + description: Describes a series first. After that does time series analysis using + one hybrid model and two specially structured Machine Learning (ML) (Artificial + Neural Network or ANN and Support Vector Regression or SVR) models. More information + can be obtained from Paul and Garai (2022) . + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AriGaMyANNSVR + url_git: '' +arima2: + version: 3.3.0 + title: Likelihood Based Inference for ARIMA Modeling + maintainer: Jesse Wheeler + description: |- + Estimating and analyzing auto regressive integrated moving average + (ARIMA) models. The primary function in this package is arima(), which fits + an ARIMA model to univariate time series data using a random restart + algorithm. This approach frequently leads to models that have model + likelihood greater than or equal to that of the likelihood obtained by + fitting the same model using the arima() function from the 'stats' package. + This package enables proper optimization of model likelihoods, which is a + necessary condition for performing likelihood ratio tests. This package + relies heavily on the source code of the arima() function of the 'stats' + package. For more information, please see Jesse Wheeler and Edward L. + Ionides (2023) . + date_publication: '2024-08-19' + bug_reports: https://github.com/jeswheel/arima2/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=arima2 + url_git: '' +ARIMAANN: + version: 0.1.0 + title: Time Series Forecasting using ARIMA-ANN Hybrid Model + maintainer: Mrinmoy Ray + description: Testing, Implementation, and Forecasting of the ARIMA-ANN hybrid model. + The ARIMA-ANN hybrid model combines the distinct strengths of the Auto-Regressive + Integrated Moving Average (ARIMA) model and the Artificial Neural Network (ANN) + model for time series forecasting.For method details see Zhang, GP (2003) . + date_publication: '2022-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARIMAANN + url_git: '' +arkdb: + version: 0.0.18 + title: Archive and Unarchive Databases Using Flat Files + maintainer: Carl Boettiger + description: |- + Flat text files provide a robust, compressible, and portable + way to store tables from databases. This package provides convenient + functions for exporting tables from relational database connections + into compressed text files and streaming those text files back into + a database without requiring the whole table to fit in working memory. + date_publication: '2024-01-16' + bug_reports: https://github.com/ropensci/arkdb/issues + url: https://docs.ropensci.org/arkdb/ + url_cran: https://CRAN.R-project.org/package=arkdb + url_git: https://github.com/ropensci/arkdb +arkhe: + version: 1.10.0 + title: Tools for Cleaning Rectangular Data + maintainer: Nicolas Frerebeau + description: |- + A dependency-free collection of simple functions for cleaning + rectangular data. This package allows to detect, count and replace + values or discard rows/columns using a predicate function. In + addition, it provides tools to check conditions and return informative + error messages. + date_publication: '2025-02-25' + bug_reports: https://codeberg.org/tesselle/arkhe/issues + url: https://codeberg.org/tesselle/arkhe + url_cran: https://CRAN.R-project.org/package=arkhe + url_git: '' +arlclustering: + version: 1.0.5 + title: |- + Exploring Social Network Structures Through Friendship-Driven + Community Detection with Association Rules Mining + maintainer: Mohamed El-Moussaoui + description: Implements an innovative approach to community detection in social + networks using Association Rules Learning. The package provides tools for processing + graph and rules objects, generating association rules, and detecting communities + based on node interactions. Designed to facilitate advanced research in Social + Network Analysis, this package leverages association rules learning for enhanced + community detection. This approach is described in El-Moussaoui et al. (2021) + . + date_publication: '2024-09-11' + bug_reports: https://github.com/assuom44/arlclustering/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arlclustering + url_git: https://github.com/assuom44/arlclustering +arm: + version: 1.14-4 + title: |- + Data Analysis Using Regression and Multilevel/Hierarchical + Models + maintainer: Yu-Sung Su + description: Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression + and Multilevel/Hierarchical Models, Cambridge University Press, 2007. + date_publication: '2024-04-01' + bug_reports: https://github.com/suyusung/arm/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=arm + url_git: '' +ARMALSTM: + version: 0.1.0 + title: Fitting of Hybrid ARMA-LSTM Models + maintainer: Debopam Rakshit + description: 'The real-life time series data are hardly pure linear or nonlinear. + Merging a linear time series model like the autoregressive moving average (ARMA) + model with a nonlinear neural network model such as the Long Short-Term Memory + (LSTM) model can be used as a hybrid model for more accurate modeling purposes. + Both the autoregressive integrated moving average (ARIMA) and autoregressive fractionally + integrated moving average (ARFIMA) models can be implemented. Details can be found + in Box et al. (2015, ISBN: 978-1-118-67502-1) and Hochreiter and Schmidhuber (1997) + .' + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARMALSTM + url_git: '' +armspp: + version: 0.0.2 + title: Adaptive Rejection Metropolis Sampling (ARMS) via 'Rcpp' + maintainer: Michael Bertolacci + description: An efficient 'Rcpp' implementation of the Adaptive Rejection Metropolis + Sampling (ARMS) algorithm proposed by Gilks, W. R., Best, N. G. and Tan, K. K. + C. (1995) . This allows for sampling from a univariate target + probability distribution specified by its (potentially unnormalised) log density. + date_publication: '2019-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=armspp + url_git: '' +arnie: + version: 0.1.2 + title: '"Arnie" box office records 1982-2014' + maintainer: '''Imanuel Costigan''' + description: Arnold Schwarzenegger movie weekend box office records from1982-2014 + date_publication: '2014-06-16' + bug_reports: https://github.com/imanuelcostigan/arnie/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arnie + url_git: https://github.com/imanuelcostigan/arnie +aroma.affymetrix: + version: 3.2.2 + title: Analysis of Large Affymetrix Microarray Data Sets + maintainer: Henrik Bengtsson + description: A cross-platform R framework that facilitates processing of any number + of Affymetrix microarray samples regardless of computer system. The only parameter + that limits the number of chips that can be processed is the amount of available + disk space. The Aroma Framework has successfully been used in studies to process + tens of thousands of arrays. This package has actively been used since 2006. + date_publication: '2024-02-18' + bug_reports: https://github.com/HenrikBengtsson/aroma.affymetrix/issues + url: https://www.aroma-project.org/ + url_cran: https://CRAN.R-project.org/package=aroma.affymetrix + url_git: https://github.com/HenrikBengtsson/aroma.affymetrix +aroma.apd: + version: 0.7.0 + title: |- + A Probe-Level Data File Format Used by 'aroma.affymetrix' + [deprecated] + maintainer: Henrik Bengtsson + description: DEPRECATED. Do not start building new projects based on this package. + (The (in-house) APD file format was initially developed to store Affymetrix probe-level + data, e.g. normalized CEL intensities. Chip types can be added to APD file and + similar to methods in the affxparser package, this package provides methods to + read APDs organized by units (probesets). In addition, the probe elements can + be arranged optimally such that the elements are guaranteed to be read in order + when, for instance, data is read unit by unit. This speeds up the read substantially. This + package is supporting the Aroma framework and should not be used elsewhere.) + date_publication: '2023-06-23' + bug_reports: https://github.com/HenrikBengtsson/aroma.apd/issues + url: URL:https://www.aroma-project.org/ + url_cran: https://CRAN.R-project.org/package=aroma.apd + url_git: https://github.com/HenrikBengtsson/aroma.apd +aroma.cn: + version: 1.7.1 + title: Copy-Number Analysis of Large Microarray Data Sets + maintainer: Henrik Bengtsson + description: |- + Methods for analyzing DNA copy-number data. Specifically, + this package implements the multi-source copy-number normalization (MSCN) + method for normalizing copy-number data obtained on various platforms and + technologies. It also implements the TumorBoost method for normalizing + paired tumor-normal SNP data. + date_publication: '2024-02-17' + bug_reports: https://github.com/HenrikBengtsson/aroma.cn/issues + url: https://www.aroma-project.org/ + url_cran: https://CRAN.R-project.org/package=aroma.cn + url_git: https://github.com/HenrikBengtsson/aroma.cn +aroma.core: + version: 3.3.1 + title: |- + Core Methods and Classes Used by 'aroma.*' Packages Part of the + Aroma Framework + maintainer: Henrik Bengtsson + description: |- + Core methods and classes used by higher-level 'aroma.*' packages + part of the Aroma Project, e.g. 'aroma.affymetrix' and 'aroma.cn'. + date_publication: '2024-02-19' + bug_reports: https://github.com/HenrikBengtsson/aroma.core/issues + url: https://www.aroma-project.org/ + url_cran: https://CRAN.R-project.org/package=aroma.core + url_git: https://github.com/HenrikBengtsson/aroma.core +Arothron: + version: 2.0.5 + title: Geometric Morphometric Methods and Virtual Anthropology Tools + maintainer: Antonio Profico + description: Tools for geometric morphometric analysis. The package includes tools + of virtual anthropology to align two not articulated parts belonging to the same + specimen, to build virtual cavities as endocast (Profico et al, 2021 ). + date_publication: '2023-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Arothron + url_git: '' +ARPALData: + version: 1.6.1 + title: |- + Retrieving and Analyzing Air Quality and Weather Data from ARPA + Lombardia + maintainer: Paolo Maranzano + description: |- + Contains functions for retrieving, managing and analysing air quality and weather data from Regione Lombardia open database (). + Data are collected by ARPA Lombardia (Lombardia Environmental Protection Agency), Italy, through its ground monitoring network (). + See the webpage for further information on ARPA Lombardia's activities and history. + Data quality (e.g. missing values, exported values, graphical mapping) has been checked involving members of the ARPA Lombardia's office for air quality control. + The package makes available observations since 1989 (for weather) and 1968 (for air quality) and are updated with daily frequency by the regional agency. + Full description of the package can be retrieved in the companion paper Maranzano \& Algieri (2024), "ARPALData: an R package for retrieving and analyzing air quality + and weather data from ARPA Lombardia (Italy)", Environmental and Ecological Statistics, . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARPALData + url_git: '' +ARpLMEC: + version: 2.4.1 + title: |- + Censored Mixed-Effects Models with Different Correlation + Structures + maintainer: Rommy C. Olivari + description: Left, right or interval censored mixed-effects linear model with autoregressive + errors of order p or DEC correlation structure using the type-EM algorithm. The + error distribution can be Normal or t-Student. It provides the parameter estimates, + the standard errors and prediction of future observations (available only for + the normal case). Olivari et all (2021) . + date_publication: '2022-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARpLMEC + url_git: '' +ARPobservation: + version: 1.2.2 + title: |- + Tools for Simulating Direct Behavioral Observation Recording + Procedures Based on Alternating Renewal Processes + maintainer: James E. Pustejovsky + description: |- + Tools for simulating data generated by direct observation + recording. Behavior streams are simulated based on an alternating renewal + process, given specified distributions of event durations and interim + times. Different procedures for recording data can then be applied to the + simulated behavior streams. Functions are provided for the following + recording methods: continuous duration recording, event counting, momentary + time sampling, partial interval recording, whole interval recording, and + augmented interval recording. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARPobservation + url_git: '' +arpr: + version: 0.1.2 + title: Advanced R Pipes + maintainer: Sébastien Rochette + description: |- + Provides convenience functions for programming with + 'magrittr' pipes. Conditional pipes, a string prefixer and a function + to pipe the given object into a specific argument given by character + name are currently supported. It is named after the dadaist Hans Arp, + a friend of Rene Magritte. + date_publication: '2021-08-02' + bug_reports: https://github.com/statnmap/arpr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arpr + url_git: https://github.com/statnmap/arpr +aRpsDCA: + version: 1.1.1 + title: Arps Decline Curve Analysis in R + maintainer: Derrick Turk + description: Functions for Arps decline-curve analysis on oil and gas data. Includes + exponential, hyperbolic, harmonic, and hyperbolic-to-exponential models as well + as the preceding with initial curtailment or a period of linear rate buildup. + Functions included for computing rate, cumulative production, instantaneous decline, + EUR, time to economic limit, and performing least-squares best fits. + date_publication: '2017-07-23' + bug_reports: https://github.com/derrickturk/aRpsDCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aRpsDCA + url_git: https://github.com/derrickturk/aRpsDCA +arrangements: + version: 1.1.9 + title: |- + Fast Generators and Iterators for Permutations, Combinations, + Integer Partitions and Compositions + maintainer: Randy Lai + description: |- + Fast generators and iterators for permutations, combinations, + integer partitions and compositions. The arrangements are in + lexicographical order and generated iteratively in a memory efficient manner. + It has been demonstrated that 'arrangements' outperforms most existing + packages of similar kind. Benchmarks could be found at + . + date_publication: '2020-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arrangements + url_git: https://github.com/randy3k/arrangements +arrApply: + version: 2.2.1 + title: Apply a Function to a Margin of an Array + maintainer: Serguei Sokol + description: |- + High performance variant of apply() for a fixed set of functions. + Considerable speedup of this implementation is a trade-off for universality: user defined + functions cannot be used with this package. However, about 20 most currently employed + functions are available for usage. They can be divided in three types: + reducing functions (like mean(), sum() etc., giving a scalar when applied to a vector), + mapping function (like normalise(), cumsum() etc., giving a vector of the same length + as the input vector) and finally, vector reducing function (like diff() which produces + result vector of a length different from the length of input vector). + Optional or mandatory additional arguments required by some functions + (e.g. norm type for norm()) can be + passed as named arguments in '...'. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arrApply + url_git: '' +arrayhelpers: + version: 1.1-0 + title: Convenience Functions for Arrays + maintainer: C. Beleites + description: Some convenient functions to work with arrays. + date_publication: '2020-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arrayhelpers + url_git: http://arrayhelpers.r-forge.r-project.org/ +arrg: + version: 0.1.0 + title: Flexible Argument Parsing for R Scripts + maintainer: Jon Clayden + description: |- + Argument parsing for R scripts, with support for long and short + Unix-style options including option clustering, positional arguments + including those of variable length, and multiple usage patterns which may + take different subsets of options. + date_publication: '2024-09-25' + bug_reports: https://github.com/jonclayden/arrg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arrg + url_git: https://github.com/jonclayden/arrg +arrow: + version: 19.0.1 + title: Integration to 'Apache' 'Arrow' + maintainer: Jonathan Keane + description: |- + 'Apache' 'Arrow' is a cross-language + development platform for in-memory data. It specifies a standardized + language-independent columnar memory format for flat and hierarchical data, + organized for efficient analytic operations on modern hardware. This + package provides an interface to the 'Arrow C++' library. + date_publication: '2025-02-26' + bug_reports: https://github.com/apache/arrow/issues + url: https://arrow.apache.org/docs/r/ + url_cran: https://CRAN.R-project.org/package=arrow + url_git: https://github.com/apache/arrow/ +arrowheadr: + version: 1.0.1 + title: Make Custom Arrowheads + maintainer: W. Joel Schneider + description: |- + The 'ggarrow' package is a 'ggplot2' extension that plots + a variety of different arrow segments with many options to customize. + The 'arrowheadr' package makes it easy to create custom arrowheads + and fins within the parameters that 'ggarrow' functions expect. It + has preset arrowheads and a collection of functions to create and + transform data for customizing arrows. + date_publication: '2024-06-10' + bug_reports: https://github.com/wjschne/arrowheadr/issues + url: https://wjschne.github.io/arrowheadr/ + url_cran: https://CRAN.R-project.org/package=arrowheadr + url_git: https://github.com/wjschne/arrowheadr +ars: + version: '0.8' + title: Adaptive Rejection Sampling + maintainer: Paulino Perez Rodriguez + description: Adaptive Rejection Sampling, Original version. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ars + url_git: '' +arse: + version: 1.0.0 + title: Area of Resilience to Stress Event + maintainer: Nathaniel Ratcliff + description: |- + A method for quantifying resilience after a stress event. A set of functions + calculate the area of resilience that is created by the departure of baseline + 'y' (i.e., robustness) and the time taken 'x' to return to baseline + (i.e., rapidity) after a stress event using the Cartesian coordinates of the + data. This package has the capability to calculate areas of resilience, + growth, and cases in which resilience is not achieved + (e.g., diminished performance without return to baseline). + date_publication: '2019-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arse + url_git: https://github.com/nr3xe/arse +arsenal: + version: 3.6.3 + title: |- + An Arsenal of 'R' Functions for Large-Scale Statistical + Summaries + maintainer: Ethan Heinzen + description: |- + An Arsenal of 'R' functions for large-scale statistical summaries, + which are streamlined to work within the latest reporting tools in 'R' and + 'RStudio' and which use formulas and versatile summary statistics for summary + tables and models. The primary functions include tableby(), a Table-1-like + summary of multiple variable types 'by' the levels of one or more categorical + variables; paired(), a Table-1-like summary of multiple variable types paired across + two time points; modelsum(), which performs simple model fits on one or more endpoints + for many variables (univariate or adjusted for covariates); + freqlist(), a powerful frequency table across many categorical variables; + comparedf(), a function for comparing data.frames; and + write2(), a function to output tables to a document. + date_publication: '2021-06-04' + bug_reports: https://github.com/mayoverse/arsenal/issues + url: https://mayoverse.github.io/arsenal/ + url_cran: https://CRAN.R-project.org/package=arsenal + url_git: https://github.com/mayoverse/arsenal +ART: + version: '1.0' + title: Aligned Rank Transform for Nonparametric Factorial Analysis + maintainer: Pablo J. Villacorta + description: |- + An implementation of the Aligned Rank Transform technique for + factorial analysis (see references below for details) including models with + missing terms (unsaturated factorial models). The function first + computes a separate aligned ranked response variable for each effect of the + user-specified model, and then runs a classic ANOVA on each of the aligned + ranked responses. For further details, see Higgins, J. J. and Tashtoush, S. + (1994). An aligned rank transform test for interaction. Nonlinear World 1 + (2), pp. 201-211. Wobbrock, J.O., Findlater, L., Gergle, D. and + Higgins,J.J. (2011). The Aligned Rank Transform for nonparametric factorial + analyses using only ANOVA procedures. Proceedings of the ACM Conference on + Human Factors in Computing Systems (CHI '11). New York: ACM Press, pp. + 143-146. . + date_publication: '2015-08-13' + bug_reports: http://decsai.ugr.es/~pjvi + url: http://decsai.ugr.es/~pjvi/r-packages.html + url_cran: https://CRAN.R-project.org/package=ART + url_git: '' +artfima: + version: '1.5' + title: ARTFIMA Model Estimation + maintainer: A.I. McLeod + description: Fit and simulate ARTFIMA. Theoretical autocovariance function and spectral + density function for stationary ARTFIMA. + date_publication: '2016-07-14' + bug_reports: '' + url: http://www.stats.uwo.ca/faculty/aim + url_cran: https://CRAN.R-project.org/package=artfima + url_git: '' +arthistory: + version: 0.1.0 + title: Art History Textbook Data + maintainer: Sara Lemus + description: |- + Data from Gardner and Janson art history textbooks about both the artists featured in these books as well as their works. + See Helen Gardner ("Art through the ages; an introduction to its history and significance," 1926, . + Helen Gardner, revised by Horst de la Croix and Richard G. Tansey ("Gardner’s Art through the ages," 1980, ISBN: 0155037587). + Fred S. Kleiner ("Gardner’s art through the ages: a global history," 2020, ISBN: 9781337630702). + Horst de la Croix and Richard G. Tansey ("Gardner's art through the ages," 1986, ISBN: 0155037633). + Helen Gardner ("Art through the ages; an introduction to its history and significance," 1936, ). + Helen Gardner ("Art through the ages," 1948, ). + Helen Gardner, revised under the editorship of Sumner M. Crosby ("Art through the ages," 1959, ). + Helen Gardner, revised by Horst de la Croix and Richard G. Tansey ("Gardner’s Art through the ages," 1975, ISBN: 0155037560). + Fred S. Kleiner ("Gardner’s Art through the ages: a global history," 2013, ISBN: 9780495915423. + Fred S. Kleiner, Christin J. Mamiya, Richard G. Tansey ("Gardner’s art through the ages," 2001, ISBN: 0155083155). + Fred S. Kleiner ("Gardner’s Art through the ages: a global history," 2016, ISBN: 9781285837840). + Fred S. Kleiner, Christin J. Mamiya ("Gardner’s art through the ages," 2005, ISBN: 0534640958). + Helen Gardner, revised by Horst de la Croix and Richard G. Tansey ("Gardner’s Art through the ages," 1970, ISBN: 0155037528). + Helen Gardner, Richard G. Tansey, Fred S. Kleiner ("Gardner’s Art through the ages," 1996, ISBN: 0155011413). + Helen Gardner, Horst de la Croix, Richard G. Tansey, Diane Kirkpatrick ("Gardner’s Art through the ages," 1991, ISBN: 0155037692). + Helen Gardner, Fred S. Kleiner ("Gardner’s Art through the ages: a global history," 2009, ISBN: 9780495093077). + Davies, Penelope J.E., Walter B. Denny, Frima Fox Hofrichter, Joseph F. Jacobs, Ann S. Roberts, David L. Simon ("Janson’s history of art: the western tradition," 2007, ISBN: 0131934554). + Davies, Penelope J.E., Walter B. Denny, Frima Fox Hofrichter, Joseph F. Jacobs, Ann S. Roberts, David L. Simon ("Janson’s history of art: the western tradition," 2011, ISBN: 9780205685172). + H. W. Janson, Anthony F. Janson ("History of Art," 2001, ISBN: 0810934469). + H. W. Janson, revised and expanded by Anthony F. Janson ("History of art," 1986, ISBN: 013389388). + H. W. Janson, Dora Jane Janson ("History of art: a survey of the major visual arts from the dawn of history to present day," 1977, ISBN: 0810910527). + H. W. Janson, Dora Jane Janson ("History of art: a survey of the major visual arts from the dawn of history to present day," 1969, ). + H. W. Janson, Dora Jane Janson ("History of art: a survey of the major visual arts from the dawn of history to present day," 1963, ). + H. W. Janson, revised and expanded by Anthony F. Janson ("History of art," 1991, ISBN: 0810934019). + H. W. Janson, revised and expanded by Anthony F. Janson ("History of art," 1995, ISBN: 0810934213). + date_publication: '2022-05-03' + bug_reports: https://github.com/saralemus7/arthistory/issues + url: https://saralemus7.github.io/arthistory/ + url_cran: https://CRAN.R-project.org/package=arthistory + url_git: https://github.com/saralemus7/arthistory +ARTofR: + version: 0.4.1 + title: To Insert Title, Divider, and Block of Comments + maintainer: Huanyuan Zhang + description: For instructions, check . This + is a wrapper of 'bannerCommenter', for inserting neat comments, headers and dividers. + date_publication: '2022-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARTofR + url_git: '' +ARTool: + version: 0.11.1 + title: Aligned Rank Transform + maintainer: Matthew Kay + description: |- + The aligned rank transform for nonparametric + factorial ANOVAs as described by Wobbrock, + Findlater, Gergle, and Higgins (2011) . + Also supports aligned rank transform contrasts as described + by Elkin, Kay, Higgins, and Wobbrock (2021) + . + date_publication: '2021-10-13' + bug_reports: https://github.com/mjskay/ARTool/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=ARTool + url_git: https://github.com/mjskay/ARTool/ +artpack: + version: 0.1.0 + title: Creates Generative Art Data + maintainer: Meghan Harris + description: Create data that displays generative art when mapped into a 'ggplot2' + plot. Functionality includes specialized data frame creation for geometric shapes, + tools that define artistic color palettes, tools for geometrically transforming + data, and other miscellaneous tools that are helpful when using 'ggplot2' for + generative art. + date_publication: '2023-08-24' + bug_reports: https://github.com/Meghansaha/artpack/issues + url: https://meghansaha.github.io/artpack/ + url_cran: https://CRAN.R-project.org/package=artpack + url_git: '' +aRtsy: + version: 1.0.0 + title: Generative Art with 'ggplot2' + maintainer: Koen Derks + description: Provides algorithms for creating artworks in the 'ggplot2' language + that incorporate some form of randomness. + date_publication: '2024-11-06' + bug_reports: https://github.com/koenderks/aRtsy/issues + url: https://koenderks.github.io/aRtsy/ + url_cran: https://CRAN.R-project.org/package=aRtsy + url_git: https://github.com/koenderks/aRtsy +ARTtransfer: + version: 1.0.0 + title: Adaptive and Robust Pipeline for Transfer Learning + maintainer: Boxiang Wang + description: Adaptive and Robust Transfer Learning (ART) is a flexible framework + for transfer learning that integrates information from auxiliary data sources + to improve model performance on primary tasks. It is designed to be robust against + negative transfer by including the non-transfer model in the candidate pool, ensuring + stable performance even when auxiliary datasets are less informative. See the + paper, Wang, Wu, and Ye (2023) . + date_publication: '2024-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ARTtransfer + url_git: '' +arules: + version: 1.7-9 + title: Mining Association Rules and Frequent Itemsets + maintainer: Michael Hahsler + description: |- + Provides the infrastructure for representing, manipulating + and analyzing transaction data and patterns (frequent itemsets and + association rules). Also provides C implementations of the + association mining algorithms Apriori and Eclat. Hahsler, Gruen and + Hornik (2005) . + date_publication: '2024-12-14' + bug_reports: https://github.com/mhahsler/arules/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arules + url_git: https://github.com/mhahsler/arules +arulesCBA: + version: 1.2.7 + title: Classification Based on Association Rules + maintainer: Michael Hahsler + description: |- + Provides the infrastructure for association rule-based classification including the algorithms + CBA, CMAR, CPAR, C4.5, FOIL, PART, PRM, RCAR, and RIPPER to build associative classifiers. + Hahsler et al (2019) . + date_publication: '2024-05-15' + bug_reports: https://github.com/mhahsler/arulesCBA + url: '' + url_cran: https://CRAN.R-project.org/package=arulesCBA + url_git: https://github.com/mhahsler/arulesCBA +arulesNBMiner: + version: 0.1-8 + title: Mining NB-Frequent Itemsets and NB-Precise Rules + maintainer: Michael Hahsler + description: NBMiner is an implementation of the model-based mining algorithm for + mining NB-frequent itemsets and NB-precise rules. Michael Hahsler (2006) . + date_publication: '2021-09-07' + bug_reports: https://github.com/mhahsler/arulesNBMiner + url: '' + url_cran: https://CRAN.R-project.org/package=arulesNBMiner + url_git: https://github.com/mhahsler/arulesNBMiner +arulesSequences: + version: 0.2-31 + title: Mining Frequent Sequences + maintainer: Christian Buchta + description: |- + Add-on for arules to handle and mine frequent sequences. + Provides interfaces to the C++ implementation of cSPADE by + Mohammed J. Zaki. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=arulesSequences + url_git: '' +arulesViz: + version: 1.5.3 + title: Visualizing Association Rules and Frequent Itemsets + maintainer: Michael Hahsler + description: Extends package 'arules' with various visualization techniques for + association rules and itemsets. The package also includes several interactive + visualizations for rule exploration. Michael Hahsler (2017) . + date_publication: '2024-04-26' + bug_reports: https://github.com/mhahsler/arulesViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=arulesViz + url_git: https://github.com/mhahsler/arulesViz +ARUtools: + version: 0.7.1 + title: |- + Management and Processing of Autonomous Recording Unit (ARU) + Data + maintainer: David Hope + description: |- + Parse Autonomous Recording Unit (ARU) data and for sub-sampling recordings. + Extract Metadata from your recordings, select a subset of recordings for + interpretation, and prepare files for processing on the + 'WildTrax' platform. Read and process metadata + from recordings collected using the SongMeter and BAR-LT types of ARUs. + date_publication: '2024-10-08' + bug_reports: https://github.com/ARUtools/ARUtools/issues + url: https://arutools.github.io/ARUtools/ + url_cran: https://CRAN.R-project.org/package=ARUtools + url_git: https://github.com/ARUtools/ARUtools +aRxiv: + version: '0.10' + title: Interface to the arXiv API + maintainer: Karl Broman + description: |- + An interface to the API for 'arXiv', + a repository of electronic preprints for + computer science, mathematics, physics, quantitative biology, + quantitative finance, and statistics. + date_publication: '2024-02-29' + bug_reports: https://github.com/ropensci/aRxiv/issues + url: https://docs.ropensci.org/aRxiv/ + url_cran: https://CRAN.R-project.org/package=aRxiv + url_git: https://github.com/ropensci/aRxiv +asaur: + version: '0.50' + title: Data Sets for "Applied Survival Analysis Using R"" + maintainer: Dirk F. Moore + description: |- + Data sets are referred to in the text "Applied Survival Analysis Using R" + by Dirk F. Moore, Springer, 2016, ISBN: 978-3-319-31243-9, . + date_publication: '2016-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asaur + url_git: '' +asbio: + version: '1.11' + title: A Collection of Statistical Tools for Biologists + maintainer: Ken Aho + description: 'Contains functions from: Aho, K. (2014) Foundational and Applied Statistics + for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.' + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asbio + url_git: '' +ascentTraining: + version: 1.0.0 + title: Ascent Training Datasets + maintainer: Harry Alexander + description: |- + Datasets to be used primarily in conjunction with Ascent + training materials but also for the book 'SAMS Teach Yourself R in 24 Hours' (ISBN: 978-0-672-33848-9). + Version 1.0-7 is largely for use with the book; however, version 1.1 has a much greater focus on use with + training materials, whilst retaining compatibility with the book. + date_publication: '2022-04-27' + bug_reports: https://github.com/HarryJAlexander/ascentTraining/issues + url: https://www.ascent.io/ + url_cran: https://CRAN.R-project.org/package=ascentTraining + url_git: '' +ascii: + version: '2.6' + title: Export R Objects to Several Markup Languages + maintainer: Mark Clements + description: |- + Coerce R object to 'asciidoc', 'txt2tags', + 'restructuredText', 'org', 'textile' or 'pandoc' syntax. + Package comes with a set of drivers for 'Sweave'. + date_publication: '2024-01-22' + bug_reports: https://github.com/mclements/ascii/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ascii + url_git: https://github.com/mclements/ascii +asciicast: + version: 2.3.1 + title: Create 'Ascii' Screen Casts from R Scripts + maintainer: Gábor Csárdi + description: |- + Record 'asciicast' screen casts from R scripts. Convert them + to animated SVG images, to be used in 'README' files, or blog posts. + Includes 'asciinema-player' as an 'HTML' widget, and an 'asciicast' + 'knitr' engine, to embed 'ascii' screen casts in 'Rmarkdown' + documents. + date_publication: '2024-01-18' + bug_reports: https://github.com/r-lib/asciicast/issues + url: https://asciicast.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=asciicast + url_git: https://github.com/r-lib/asciicast +asciichartr: + version: 0.1.0 + title: Lightweight ASCII Line Graphs + maintainer: Brian + description: |- + Create ASCII line graphs of a time series directly on + your terminal in an easy way. There are some configurations you + can add to make the plot the way you like. This project was + inspired by the original 'asciichart' package by Igor Kroitor. + date_publication: '2020-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asciichartr + url_git: '' +asciiruler: + version: '0.2' + title: Render an ASCII Ruler + maintainer: Jeremy Leipzig + description: An ASCII ruler is for measuring text and is especially useful for sequence + analysis. Included in this package are methods to create ASCII rulers and associated + GenBank sequence blocks, multi-column text displays that make it easy for viewers + to locate nucleotides by position. + date_publication: '2018-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asciiruler + url_git: '' +asciiSetupReader: + version: 2.5.2 + title: |- + Reads Fixed-Width ASCII Data Files (.txt or .dat) that Have + Accompanying Setup Files (.sps or .sas) + maintainer: Jacob Kaplan + description: |- + Lets you open a fixed-width ASCII file (.txt or + .dat) that has an accompanying setup file (.sps or .sas). These file + combinations are sometimes referred to as .txt+.sps, .txt+.sas, + .dat+.sps, or .dat+.sas. This will only run in a txt-sps or txt-sas + pair in which the setup file contains instructions to open that text + file. It will NOT open other text files, .sav, .sas, or .por data + files. Fixed-width ASCII files with setup files are common in older + (pre-2000) government data. + date_publication: '2024-08-17' + bug_reports: https://github.com/jacobkap/asciiSetupReader/issues + url: '' + url_cran: https://CRAN.R-project.org/package=asciiSetupReader + url_git: https://github.com/jacobkap/asciiSetupReader +ascotraceR: + version: 0.0.1 + title: Simulate the Spread of Ascochyta Blight in Chickpea + maintainer: Paul Melloy + description: |- + A spatiotemporal model that simulates the spread of Ascochyta + blight in chickpea fields based on location-specific weather conditions. + This model is adapted from a model developed by Diggle et al. (2002) + for simulating the spread of anthracnose + in a lupin field. + date_publication: '2021-12-20' + bug_reports: https://github.com/IhsanKhaliq/ascotraceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ascotraceR + url_git: https://github.com/IhsanKhaliq/ascotraceR +asd: + version: '2.2' + title: Simulations for Adaptive Seamless Designs + maintainer: Nick Parsons + description: |- + Package runs simulations for adaptive seamless designs with and without early outcomes + for treatment selection and subpopulation type designs. + date_publication: '2016-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asd + url_git: '' +asdreader: + version: 0.1-3 + title: Reading ASD Binary Files in R + maintainer: Pierre Roudier + description: |- + A simple driver that reads binary data created by the ASD Inc. + portable spectrometer instruments, such as the FieldSpec (for more information, + see ). Spectral data + can be extracted from the ASD files as raw (DN), white reference, radiance, or + reflectance. Additionally, the metadata information contained in the ASD file + header can also be accessed. + date_publication: '2017-09-13' + bug_reports: http://github.com/pierreroudier/asdreader/issues + url: '' + url_cran: https://CRAN.R-project.org/package=asdreader + url_git: http://github.com/pierreroudier/asdreader +ASGS.foyer: + version: 0.3.3 + title: Interface to the Australian Statistical Geography Standard + maintainer: Hugh Parsonage + description: |- + The Australian Statistical Geography Standard ('ASGS') is + a set of shapefiles by the Australian Bureau of Statistics. This package + provides an interface to those shapefiles, as well as methods for converting + coordinates to shapefiles. + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ASGS.foyer + url_git: '' +ash: + version: 1.0-15 + title: David Scott's ASH Routines + maintainer: Albrecht Gebhardt + description: David Scott's ASH routines ported from S-PLUS to R. + date_publication: '2015-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ash + url_git: '' +ashapesampler: + version: 1.0.0 + title: Generating Alpha Shapes + maintainer: Emily Winn-Nunez + description: 'Understanding morphological variation is an important task in many + applications. Recent studies in computational biology have focused on developing + computational tools for the task of sub-image selection which aims at identifying + structural features that best describe the variation between classes of shapes. + A major part in assessing the utility of these approaches is to demonstrate their + performance on both simulated and real datasets. However, when creating a model + for shape statistics, real data can be difficult to access and the sample sizes + for these data are often small due to them being expensive to collect. Meanwhile, + the landscape of current shape simulation methods has been mostly limited to approaches + that use black-box inference---making it difficult to systematically assess the + power and calibration of sub-image models. In this R package, we introduce the + alpha-shape sampler: a probabilistic framework for simulating realistic 2D and + 3D shapes based on probability distributions which can be learned from real data + or explicitly stated by the user. The ''ashapesampler'' package supports two mechanisms + for sampling shapes in two and three dimensions. The first, empirically sampling + based on an existing data set, was highlighted in the original main text of the + paper. The second, probabilistic sampling from a known distribution, is the computational + implementation of the theory derived in that paper. Work based on Winn-Nunez et + al. (2024) .' + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ashapesampler + url_git: '' +ashr: + version: 2.2-63 + title: Methods for Adaptive Shrinkage, using Empirical Bayes + maintainer: Peter Carbonetto + description: |- + The R package 'ashr' implements an Empirical Bayes + approach for large-scale hypothesis testing and false discovery + rate (FDR) estimation based on the methods proposed in + M. Stephens, 2016, "False discovery rates: a new deal", + . These methods can be applied + whenever two sets of summary statistics---estimated effects and + standard errors---are available, just as 'qvalue' can be applied + to previously computed p-values. Two main interfaces are + provided: ash(), which is more user-friendly; and ash.workhorse(), + which has more options and is geared toward advanced users. The + ash() and ash.workhorse() also provides a flexible modeling + interface that can accommodate a variety of likelihoods (e.g., + normal, Poisson) and mixture priors (e.g., uniform, normal). + date_publication: '2023-08-21' + bug_reports: https://github.com/stephens999/ashr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ashr + url_git: https://github.com/stephens999/ashr +asht: + version: 1.0.1 + title: Applied Statistical Hypothesis Tests + maintainer: Michael P. Fay + description: Gives some hypothesis test functions (sign test, median and other quantile + tests, Wilcoxon signed rank test, coefficient of variation test, test of normal + variance, test on weighted sums of Poisson [see Fay and Kim ], + sample size for t-tests with different variances and non-equal n per arm, Behrens-Fisher + test, nonparametric ABC intervals, Wilcoxon-Mann-Whitney test [with effect estimates + and confidence intervals, see Fay and Malinovsky ], two-sample + melding tests [see Fay, Proschan, and Brittain ], one-way + ANOVA allowing var.equal=FALSE [see Brown and Forsythe, 1974, Biometrics]), prevalence + confidence intervals that adjust for sensitivity and specificity [see Lang and + Reiczigel, 2014 ] or Bayer, Fay, and Graubard, + 2023 ). The focus is on hypothesis tests that have + compatible confidence intervals, but some functions only have confidence intervals + (e.g., prevSeSp). + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asht + url_git: '' +AsioHeaders: + version: 1.22.1-2 + title: '''Asio'' C++ Header Files' + maintainer: Dirk Eddelbuettel + description: |- + 'Asio' is a cross-platform C++ library for network and low-level + I/O programming that provides developers with a consistent asynchronous model + using a modern C++ approach. It is also included in Boost but requires linking + when used with Boost. Standalone it can be used header-only (provided a recent + compiler). 'Asio' is written and maintained by Christopher M. Kohlhoff, and + released under the 'Boost Software License', Version 1.0. + date_publication: '2022-12-08' + bug_reports: https://github.com/eddelbuettel/asioheaders/issues + url: https://dirk.eddelbuettel.com/code/asioheaders.html + url_cran: https://CRAN.R-project.org/package=AsioHeaders + url_git: https://github.com/eddelbuettel/asioheaders +askgpt: + version: 0.1.3 + title: Asking GPT About R Stuff + maintainer: Johannes Gruber + description: |- + A chat package connecting to API endpoints by 'OpenAI' + () to answer questions (about R). + date_publication: '2023-09-08' + bug_reports: https://github.com/JBGruber/askgpt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=askgpt + url_git: https://github.com/JBGruber/askgpt +askpass: + version: 1.2.1 + title: Password Entry Utilities for R, Git, and SSH + maintainer: Jeroen Ooms + description: |- + Cross-platform utilities for prompting the user for credentials or a + passphrase, for example to authenticate with a server or read a protected key. + Includes native programs for MacOS and Windows, hence no 'tcltk' is required. + Password entry can be invoked in two different ways: directly from R via the + askpass() function, or indirectly as password-entry back-end for 'ssh-agent' + or 'git-credential' via the SSH_ASKPASS and GIT_ASKPASS environment variables. + Thereby the user can be prompted for credentials or a passphrase if needed + when R calls out to git or ssh. + date_publication: '2024-10-04' + bug_reports: https://github.com/r-lib/askpass/issues + url: https://r-lib.r-universe.dev/askpass + url_cran: https://CRAN.R-project.org/package=askpass + url_git: '' +aslib: + version: 0.1.2 + title: Interface to the Algorithm Selection Benchmark Library + maintainer: Lars Kotthoff + description: |- + Provides an interface to the algorithm selection benchmark library + at and the 'LLAMA' package + () for building + algorithm selection models; see Bischl et al. (2016) + . + date_publication: '2022-08-25' + bug_reports: https://github.com/coseal/aslib-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aslib + url_git: https://github.com/coseal/aslib-r/ +asm: + version: 0.2.1 + title: |- + Optimal Convex M-Estimation for Linear Regression via Antitonic + Score Matching + maintainer: Min Xu + description: 'Performs linear regression with respect to a data-driven convex loss + function that is chosen to minimize the asymptotic covariance of the resulting + M-estimator. The convex loss function is estimated in 5 steps: (1) form an initial + OLS (ordinary least squares) or LAD (least absolute deviation) estimate of the + regression coefficients; (2) use the resulting residuals to obtain a kernel estimator + of the error density; (3) estimate the score function of the errors by differentiating + the logarithm of the kernel density estimate; (4) compute the L2 projection of + the estimated score function onto the set of decreasing functions; (5) take a + negative antiderivative of the projected score function estimate. Newton''s method + (with Hessian modification) is then used to minimize the convex empirical risk + function. Further details of the method are given in Feng et al. (2024) .' + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asm + url_git: '' +ASMap: + version: 1.0-8 + title: Linkage Map Construction using the MSTmap Algorithm + maintainer: Julian Taylor + description: Functions for Accurate and Speedy linkage map construction, manipulation + and diagnosis of Doubled Haploid, Backcross and Recombinant Inbred 'R/qtl' objects. + This includes extremely fast linkage map clustering and optimal marker ordering + using 'MSTmap' (see Wu et al.,2008). + date_publication: '2024-11-01' + bug_reports: https://github.com/DrJ001/ASMap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ASMap + url_git: https://github.com/DrJ001/ASMap +ASMbook: + version: 1.0.2 + title: |- + Functions for the Book "Applied Statistical Modeling for + Ecologists" + maintainer: Ken Kellner + description: 'Provides functions to accompany the book "Applied Statistical Modeling + for Ecologists" by Marc Kéry and Kenneth F. Kellner (2024, ISBN: 9780443137150). + Included are functions for simulating and customizing the datasets used for the + example models in each chapter, summarizing output from model fitting engines, + and running custom Markov Chain Monte Carlo.' + date_publication: '2024-07-31' + bug_reports: https://github.com/kenkellner/ASMbook/issues + url: https://shop.elsevier.com/books/applied-statistical-modelling-for-ecologists/kery/978-0-443-13715-0 + url_cran: https://CRAN.R-project.org/package=ASMbook + url_git: '' +asmbPLS: + version: 1.0.0 + title: |- + Predicting and Classifying Patient Phenotypes with Multi-Omics + Data + maintainer: Runzhi Zhang + description: Adaptive Sparse Multi-block Partial Least Square, a supervised algorithm, + is an extension of the Sparse Multi-block Partial Least Square, which allows different + quantiles to be used in different blocks of different partial least square components + to decide the proportion of features to be retained. The best combinations of + quantiles can be chosen from a set of user-defined quantiles combinations by cross-validation. + By doing this, it enables us to do the feature selection for different blocks, + and the selected features can then be further used to predict the outcome. For + example, in biomedical applications, clinical covariates plus different types + of omics data such as microbiome, metabolome, mRNA data, methylation data, copy + number variation data might be predictive for patients outcome such as survival + time or response to therapy. Different types of data could be put in different + blocks and along with survival time to fit the model. The fitted model can then + be used to predict the survival for the new samples with the corresponding clinical + covariates and omics data. In addition, Adaptive Sparse Multi-block Partial Least + Square Discriminant Analysis is also included, which extends Adaptive Sparse Multi-block + Partial Least Square for classifying the categorical outcome. + date_publication: '2023-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asmbPLS + url_git: '' +ASML: + version: 1.0.0 + title: Algorithm Portfolio Selection with Machine Learning + maintainer: Brais González-Rodríguez + description: A wrapper for machine learning (ML) methods to select among a portfolio + of algorithms based on the value of a key performance indicator (KPI). A number + of features is used to adjust a model to predict the value of the KPI for each + algorithm, then, for a new value of the features the KPI is estimated and the + algorithm with the best one is chosen. To learn it can use the regression methods + in 'caret' package or a custom function defined by the user. Several graphics + available to analyze the results obtained. This library has been used in Ghaddar + et al. (2023) ). + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ASML + url_git: '' +asnipe: + version: 1.1.17 + title: Animal Social Network Inference and Permutations for Ecologists + maintainer: Damien R. Farine + description: 'Implements several tools that are used in animal social network analysis, + as described in Whitehead (2007) Analyzing Animal Societies and Farine & Whitehead (2015) . In particular, + this package provides the tools to infer groups and generate networks from observation + data, perform permutation tests on the data, calculate lagged association rates, + and performed multiple regression analysis on social network data.' + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asnipe + url_git: '' +aspace: + version: 4.1.2 + title: Functions for Estimating Centrographic Statistics + maintainer: Tarmo K. Remmel + description: |- + A collection of functions for computing centrographic + statistics (e.g., standard distance, standard deviation + ellipse, standard deviation box) for observations taken at + point locations. Separate plotting functions have been + developed for each measure. Users interested in writing results + to ESRI shapefiles can do so by using results from 'aspace' + functions as inputs to the convert.to.shapefile() and + write.shapefile() functions in the 'shapefiles' library. We intend to + provide 'terra' integration for geographic data in a future release. + The 'aspace' package was originally conceived to aid in the analysis of + spatial patterns of travel behaviour (see Buliung and Remmel 2008 + ). + date_publication: '2024-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aspace + url_git: '' +aspect: + version: 1.0-6 + title: |- + A General Framework for Multivariate Analysis with Optimal + Scaling + maintainer: Patrick Mair + description: Contains various functions for optimal scaling. One function performs + optimal scaling by maximizing an aspect (i.e. a target function such as the sum + of eigenvalues, sum of squared correlations, squared multiple correlations, etc.) + of the corresponding correlation matrix. Another function performs implements + the LINEALS approach for optimal scaling by minimization of an aspect based on + pairwise correlations and correlation ratios. The resulting correlation matrix + and category scores can be used for further multivariate methods such as structural + equation models. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aspect + url_git: https://r-forge.r-project.org/projects/psychor/ +aspi: + version: 0.2.0 + title: Analysis of Symmetry of Parasitic Infections + maintainer: Matt Wayland + description: Tools for the analysis and visualization of bilateral asymmetry in + parasitic infections. + date_publication: '2016-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aspi + url_git: '' +aspline: + version: 0.2.0 + title: Spline Regression with Adaptive Knot Selection + maintainer: Vivien Goepp + description: |- + Perform one-dimensional spline regression with automatic knot selection. + This package uses a penalized approach to select the most relevant knots. + B-splines of any degree can be fitted. More details in 'Goepp et al. (2018)', + "Spline Regression with Automatic Knot Selection", . + date_publication: '2022-06-09' + bug_reports: https://github.com/goepp/aspline/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aspline + url_git: https://github.com/goepp/aspline +aSPU: + version: '1.50' + title: Adaptive Sum of Powered Score Test + maintainer: Il-Youp Kwak + description: |- + R codes for the (adaptive) Sum of Powered Score ('SPU' and 'aSPU') + tests, inverse variance weighted Sum of Powered score ('SPUw' and 'aSPUw') tests + and gene-based and some pathway based association tests (Pathway based Sum of + Powered Score tests ('SPUpath'), adaptive 'SPUpath' ('aSPUpath') test, 'GEEaSPU' + test for multiple traits - single 'SNP' (single nucleotide polymorphism) + association in generalized estimation equations, 'MTaSPUs' test for multiple + traits - single 'SNP' association with Genome Wide Association Studies ('GWAS') + summary statistics, Gene-based Association Test that uses an extended 'Simes' + procedure ('GATES'), Hybrid Set-based Test ('HYST') and extended version + of 'GATES' test for pathway-based association testing ('GATES-Simes'). ). + The tests can be used with genetic and other data sets with covariates. The + response variable is binary or quantitative. Summary; (1) Single trait-'SNP' set + association with individual-level data ('aSPU', 'aSPUw', 'aSPUr'), (2) Single trait-'SNP' + set association with summary statistics ('aSPUs'), (3) Single trait-pathway + association with individual-level data ('aSPUpath'), (4) Single trait-pathway + association with summary statistics ('aSPUsPath'), (5) Multiple traits-single + 'SNP' association with individual-level data ('GEEaSPU'), (6) Multiple traits- + single 'SNP' association with summary statistics ('MTaSPUs'), (7) Multiple traits-'SNP' set association with summary statistics('MTaSPUsSet'), (8) Multiple traits-pathway association with summary statistics('MTaSPUsSetPath'). + date_publication: '2021-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aSPU + url_git: https://github.com/ikwak2/aSPU +asremlPlus: + version: 4.4.46 + title: |- + Augments 'ASReml-R' in Fitting Mixed Models and Packages + Generally in Exploring Prediction Differences + maintainer: Chris Brien + description: |- + Assists in automating the selection of terms to include in mixed models when + 'asreml' is used to fit the models. Procedures are available for choosing models that + conform to the hierarchy or marginality principle, for fitting and choosing between + two-dimensional spatial models using correlation, natural cubic smoothing spline and + P-spline models. A history of the fitting of a sequence of models is kept in a data frame. + Also used to compute functions and contrasts of, to investigate differences between and + to plot predictions obtained using any model fitting function. The content falls into + the following natural groupings: (i) Data, (ii) Model modification functions, (iii) Model + selection and description functions, (iv) Model diagnostics and simulation functions, + (v) Prediction production and presentation functions, (vi) Response transformation + functions, (vii) Object manipulation functions, and (viii) Miscellaneous functions + (for further details see 'asremlPlus-package' in help). The 'asreml' package provides a + computationally efficient algorithm for fitting a wide range of linear mixed models using + Residual Maximum Likelihood. It is a commercial package and a license for it can be + purchased from 'VSNi' as 'asreml-R', who will supply a zip file + for local installation/updating (see ). It is not needed + for functions that are methods for 'alldiffs' and 'data.frame' objects. The package + 'asremPlus' can also be installed from . + date_publication: '2025-02-17' + bug_reports: https://github.com/briencj/asremlPlus/issues + url: http://chris.brien.name + url_cran: https://CRAN.R-project.org/package=asremlPlus + url_git: '' +ASRgenomics: + version: 1.1.4 + title: Complementary Genomic Functions + maintainer: Salvador Gezan + description: |- + Presents a series of molecular and genetic routines in the R + environment with the aim of assisting in analytical pipelines before + and after the use of 'asreml' or another library to perform analyses such + as Genomic Selection or Genome-Wide Association Analyses. + Methods and examples are described in Gezan, Oliveira, Galli, and Murray (2022) + . + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ASRgenomics + url_git: '' +ASSA: + version: '2.0' + title: Applied Singular Spectrum Analysis (ASSA) + maintainer: Miguel de Carvalho + description: Functions to model and decompose time series into principal components + using singular spectrum analysis (de Carvalho and Rua (2017) ; + de Carvalho et al (2012) ). + date_publication: '2020-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ASSA + url_git: '' +assert: + version: 1.0.1 + title: Validate Function Arguments + maintainer: Olivier Binette + description: |- + Lightweight validation tool for checking function arguments and + validating data analysis scripts. This is an alternative to stopifnot() from + the 'base' package and to assert_that() from the 'assertthat' package. It + provides more informative error messages and facilitates debugging. + date_publication: '2020-11-28' + bug_reports: https://github.com/OlivierBinette/assert/issues + url: '' + url_cran: https://CRAN.R-project.org/package=assert + url_git: https://github.com/OlivierBinette/assert +assertable: + version: 0.2.8 + title: |- + Verbose Assertions for Tabular Data (Data.frames and + Data.tables) + maintainer: Grant Nguyen + description: Simple, flexible, assertions on data.frame or data.table objects with + verbose output for vetting. While other assertion packages apply towards more + general use-cases, assertable is tailored towards tabular data. It includes functions + to check variable names and values, whether the dataset contains all combinations + of a given set of unique identifiers, and whether it is a certain length. In addition, + assertable includes utility functions to check the existence of target files and + to efficiently import multiple tabular data files into one data.table. + date_publication: '2021-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=assertable + url_git: '' +assertions: + version: 0.2.0 + title: Simple Assertions for Beautiful and Customisable Error Messages + maintainer: Sam El-Kamand + description: |- + Provides simple assertions with sensible defaults and customisable error messages. + It offers convenient assertion call wrappers and a general assert function that can handle any condition. + Default error messages are user friendly and easily customized with inline code evaluation and styling powered by the 'cli' package. + date_publication: '2024-11-19' + bug_reports: https://github.com/selkamand/assertions/issues + url: https://selkamand.github.io/assertions/ + url_cran: https://CRAN.R-project.org/package=assertions + url_git: https://github.com/selkamand/assertions +assertr: + version: 3.0.1 + title: Assertive Programming for R Analysis Pipelines + maintainer: Tony Fischetti + description: |- + Provides functionality to assert conditions + that have to be met so that errors in data used in + analysis pipelines can fail quickly. Similar to + 'stopifnot()' but more powerful, friendly, and easier + for use in pipelines. + date_publication: '2023-11-23' + bug_reports: https://github.com/ropensci/assertr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=assertr + url_git: https://docs.ropensci.org/assertr/(website)https://github.com/ropensci/assertr +assertthat: + version: 0.2.1 + title: Easy Pre and Post Assertions + maintainer: Hadley Wickham + description: |- + An extension to stopifnot() that makes it easy to declare + the pre and post conditions that you code should satisfy, while also + producing friendly error messages so that your users know what's gone + wrong. + date_publication: '2019-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=assertthat + url_git: '' +assessor: + version: 1.1.1 + title: |- + Assessment Tools for Regression Models with Discrete and + Semicontinuous Outcomes + maintainer: Jeonghwan Lee + description: Provides assessment tools for regression models with discrete and semicontinuous + outcomes proposed in Yang (2023) . It calculates + the double probability integral transform (DPIT) residuals, constructs QQ plots + of residuals and the ordered curve for assessing mean structures. + date_publication: '2025-02-17' + bug_reports: https://github.com/jhlee1408/assessor/issues + url: https://jhlee1408.github.io/assessor/ + url_cran: https://CRAN.R-project.org/package=assessor + url_git: '' +AssetCorr: + version: 1.0.4 + title: Estimating Asset Correlations from Default Data + maintainer: Maximilian Nagl + description: 'Functions for the estimation of intra- and inter-cohort correlations + in the Vasicek credit portfolio model. For intra-cohort correlations, the package + covers the two method of moments estimators of Gordy (2000) , + the method of moments estimator of Lucas (1995) + and a Binomial approximation extension of this approach. Moreover, the maximum + likelihood estimators of Gordy and Heitfield (2010) + and Duellmann and Gehde-Trapp (2004) are implemented. + For inter-cohort correlations, the method of moments estimator of Bluhm and Overbeck + (2003) /Bams et al. (2016) + is provided and the maximum likelihood estimators comprise the approaches of Gordy + and Heitfield (2010)/Kalkbrener and Onwunta (2010) and + Pfeuffer et al. (2020). Bootstrap and Jackknife procedures for bias correction + are included as well as the method of moments estimator of Frei and Wunsch (2018) + for auto-correlated time series.' + date_publication: '2021-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AssetCorr + url_git: '' +AssetPricing: + version: 1.0-3 + title: Optimal Pricing of Assets with Fixed Expiry Date + maintainer: Rolf Turner + description: |- + Calculates the optimal price of assets (such as + airline flight seats, hotel room bookings) whose value + becomes zero after a fixed ``expiry date''. Assumes + potential customers arrive (possibly in groups) according + to a known inhomogeneous Poisson process. Also assumes a + known time-varying elasticity of demand (price sensitivity) + function. Uses elementary techniques based on ordinary + differential equations. Uses the package deSolve to effect + the solution of these differential equations. + date_publication: '2021-10-07' + bug_reports: '' + url: http://www.stat.auckland.ac.nz/~rolf/ + url_cran: https://CRAN.R-project.org/package=AssetPricing + url_git: '' +assignPOP: + version: 1.3.0 + title: |- + Population Assignment using Genetic, Non-Genetic or Integrated + Data in a Machine Learning Framework + maintainer: Kuan-Yu (Alex) Chen + description: |- + Use Monte-Carlo and K-fold cross-validation coupled with machine- + learning classification algorithms to perform population assignment, with + functionalities of evaluating discriminatory power of independent training + samples, identifying informative loci, reducing data dimensionality for genomic + data, integrating genetic and non-genetic data, and visualizing results. + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=assignPOP + url_git: https://github.com/alexkychen/assignPOP +assignR: + version: 2.4.3 + title: Infer Geographic Origin from Isotopic Data + maintainer: Gabe Bowen + description: Routines for re-scaling isotope maps using known-origin tissue isotope + data, assigning origin of unknown samples, and summarizing and assessing assignment + results. Methods are adapted from Wunder (2010, in ISBN:9789048133536) and Vander + Zanden, H. B. et al. (2014) as described in Ma, + C. et al. (2020) . + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=assignR + url_git: '' +assist: + version: 3.1.9 + title: A Suite of R Functions Implementing Spline Smoothing Techniques + maintainer: Yuedong Wang + description: |- + Fit various smoothing spline models. Includes an ssr() function for smoothing + spline regression, an nnr() function for nonparametric nonlinear regression, an snr() + function for semiparametric nonlinear regression, an slm() function for semiparametric + linear mixed-effects models, and an snm() function for semiparametric nonlinear + mixed-effects models. See Wang (2011) for an overview. + date_publication: '2023-08-22' + bug_reports: '' + url: https://yuedong.faculty.pstat.ucsb.edu/software.html + url_cran: https://CRAN.R-project.org/package=assist + url_git: '' +ASSISTant: + version: 1.4.3 + title: Adaptive Subgroup Selection in Group Sequential Trials + maintainer: Balasubramanian Narasimhan + description: |- + Clinical trial design for subgroup selection in three-stage group + sequential trial as described in Lai, Lavori and Liao (2014, + ). Includes facilities for design, + exploration and analysis of such trials. An implementation of + the initial DEFUSE-3 trial is also provided as a vignette. + date_publication: '2022-12-02' + bug_reports: https://github.com/bnaras/ASSISTant/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ASSISTant + url_git: https://github.com/bnaras/ASSISTant +AssocBin: + version: 1.0-2 + title: Measuring Association with Recursive Binning + maintainer: Chris Salahub + description: An iterative implementation of a recursive binary partitioning algorithm + to measure pairwise dependence with a modular design that allows user specification + of the splitting logic and stop criteria. Helper functions provide suggested versions + of both and support visualization and the computation of summary statistics on + final binnings. For a complete description of the functionality and algorithm, + see Salahub and Oldford (2023) . + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AssocBin + url_git: '' +assocInd: + version: 1.0.1 + title: |- + Implements New and Existing Association Indices for Constructing + Animal Social Networks + maintainer: Damien Farine + description: Implements several new association indices that can control for various + types of errors. Also includes existing association indices and functions for + simulating the effects of different rates of error on estimates of association + strength between individuals using each method. + date_publication: '2017-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=assocInd + url_git: '' +AssocTests: + version: 1.0-1 + title: Genetic Association Studies + maintainer: Lin Wang + description: |- + Some procedures including EIGENSTRAT (a procedure for detecting and correcting + for population stratification through searching for the eigenvectors in genetic association + studies), PCoC (a procedure for correcting for population stratification through calculating + the principal coordinates and the clustering of the subjects), Tracy-Widom test (a procedure + for detecting the significant eigenvalues of a matrix), distance regression (a procedure for + detecting the association between a distance matrix and some independent variants of interest), + single-marker test (a procedure for identifying the association between the genotype at a + biallelic marker and a trait using the Wald test or the Fisher's exact test), MAX3 (a procedure + for testing for the association between a single nucleotide polymorphism and a binary phenotype + using the maximum value of the three test statistics derived for the recessive, additive, and + dominant models), nonparametric trend test (a procedure for testing for the association between + a genetic variant and a non-normal distributed quantitative trait based on the nonparametric + risk), and nonparametric MAX3 (a procedure for testing for the association between a biallelic + single nucleotide polymorphism and a quantitative trait using the maximum value of the three + nonparametric trend tests derived for the recessive, additive, and dominant models), which are + commonly used in genetic association studies. To cite this package in publications use: + Lin Wang, Wei Zhang, and Qizhai Li. AssocTests: An R Package for Genetic Association Studies. + Journal of Statistical Software. 2020; 94(5): 1-26. + date_publication: '2021-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AssocTests + url_git: '' +assortnet: + version: '0.20' + title: |- + Calculate the Assortativity Coefficient of Weighted and Binary + Networks + maintainer: Damien Farine + description: Functions to calculate the assortment of vertices in social networks. This + can be measured on both weighted and binary networks, with discrete or continuous + vertex values. + date_publication: '2023-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=assortnet + url_git: '' +AST: + version: 0.1.0 + title: Age-Spatial-Temporal Model + maintainer: Ali Ghanbari + description: 'Fits a model to adjust and consider additional variations in three + dimensions of age groups, time, and space on residuals excluded from a prediction + model that have residual such as: linear regression, mixed model and so on. Details + are given in Foreman et al. (2015) .' + date_publication: '2018-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AST + url_git: '' +ast2ast: + version: 0.3.2 + title: Translates an R Function to a C++ Function + maintainer: Krämer Konrad + description: Enable translation of a tiny subset of R to C++. The user has to define + a R function which gets translated. For a full list of possible functions check + the documentation. After translation an R function is returned which is a shallow + wrapper around the C++ code. Alternatively an external pointer to the C++ function + is returned to the user. The intention of the package is to generate fast functions + which can be used as ode-system or during optimization. + date_publication: '2023-12-09' + bug_reports: https://github.com/Konrad1991/ast2ast + url: '' + url_cran: https://CRAN.R-project.org/package=ast2ast + url_git: https://github.com/Konrad1991/ast2ast +aster: + version: 1.1-3 + title: Aster Models + maintainer: Charles J. Geyer + description: |- + Aster models (Geyer, Wagenius, and Shaw, 2007, + ; Shaw, Geyer, Wagenius, Hangelbroek, and + Etterson, 2008, ; Geyer, Ridley, Latta, Etterson, + and Shaw, 2013, ) are exponential family + regression models for life + history analysis. They are like generalized linear models except that + elements of the response vector can have different families (e. g., + some Bernoulli, some Poisson, some zero-truncated Poisson, some normal) + and can be dependent, the dependence indicated by a graphical structure. + Discrete time survival analysis, life table analysis, + zero-inflated Poisson regression, and + generalized linear models that are exponential family (e. g., logistic + regression and Poisson regression with log link) are special cases. + Main use is for data in which there is survival over discrete time periods + and there is additional data about what happens conditional on survival + (e. g., number of offspring). Uses the exponential family canonical + parameterization (aster transform of usual parameterization). + There are also random effects versions of these models. + date_publication: '2023-12-14' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/aster/ + url_cran: https://CRAN.R-project.org/package=aster + url_git: '' +aster2: + version: 0.3-2 + title: Aster Models + maintainer: Charles J. Geyer + description: |- + Aster models are exponential family regression models for life + history analysis. They are like generalized linear models except that + elements of the response vector can have different families (e. g., + some Bernoulli, some Poisson, some zero-truncated Poisson, some normal) + and can be dependent, the dependence indicated by a graphical structure. + Discrete time survival analysis, zero-inflated Poisson regression, and + generalized linear models that are exponential family (e. g., logistic + regression and Poisson regression with log link) are special cases. + Main use is for data in which there is survival over discrete time periods + and there is additional data about what happens conditional on survival + (e. g., number of offspring). Uses the exponential family canonical + parameterization (aster transform of usual parameterization). + Unlike the aster package, this package does dependence groups (nodes of + the graph need not be conditionally independent given their predecessor + node), including multinomial and two-parameter normal as families. Thus + this package also generalizes mark-capture-recapture analysis. + date_publication: '2024-09-17' + bug_reports: '' + url: https://www.stat.umn.edu/geyer/aster/ + url_cran: https://CRAN.R-project.org/package=aster2 + url_git: '' +asteRisk: + version: 1.4.3 + title: Computation of Satellite Position + maintainer: Rafael Ayala + description: |- + Provides basic functionalities to calculate the position of + satellites given a known state vector. The package includes implementations + of the SGP4 and SDP4 simplified perturbation models to propagate orbital + state vectors, as well as utilities to read TLE files and convert coordinates + between different frames of reference. Several of the functionalities of the + package (including the high-precision numerical orbit propagator) require + the coefficients and data included in the 'asteRiskData' package, available + in a 'drat' repository. To install this data package, run + 'install.packages("asteRiskData", repos="https://rafael-ayala.github.io/drat/")'. + Felix R. Hoots, Ronald L. Roehrich and T.S. Kelso (1988) . + David Vallado, Paul Crawford, Richard Hujsak and T.S. Kelso (2012) . + Felix R. Hoots, Paul W. Schumacher Jr. and Robert A. Glover (2014) . + date_publication: '2023-01-14' + bug_reports: https://github.com/Rafael-Ayala/asteRisk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=asteRisk + url_git: '' +AsthmaNHANES: + version: 1.1.0 + title: Asthma Data Sets from NHANES + maintainer: Tao Sun + description: Data sets and examples from National Health and Nutritional Examination + Survey (NHANES). + date_publication: '2021-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AsthmaNHANES + url_git: '' +astrochron: + version: '1.4' + title: A Computational Tool for Astrochronology + maintainer: Stephen Meyers + description: Routines for astrochronologic testing, astronomical time scale construction, + and time series analysis . Also included + are a range of statistical analysis and modeling routines that are relevant to + time scale development and paleoclimate analysis. + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=astrochron + url_git: '' +astrodatR: + version: '0.1' + title: Astronomical Data + maintainer: '"Eric D., Feigelson"' + description: 'A collection of 19 datasets from contemporary astronomical research. They + are described the textbook `Modern Statistical Methods for Astronomy with R Applications'' + by Eric D. Feigelson and G. Jogesh Babu (Cambridge University Press, 2012, Appendix + C) or on the website of Penn State''s Center for Astrostatistics (http://astrostatistics.psu.edu/datasets). These + datasets can be used to exercise methodology involving: density estimation; heteroscedastic + measurement errors; contingency tables; two-sample hypothesis tests; spatial point + processes; nonlinear regression; mixture models; censoring and truncation; multivariate + analysis; classification and clustering; inhomogeneous Poisson processes; periodic + and stochastic time series analysis.' + date_publication: '2014-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=astrodatR + url_git: '' +astroFns: + version: 4.2-1 + title: 'Astronomy: Time and Position Functions, Misc. Utilities' + maintainer: Andrew Harris + description: Miscellaneous astronomy functions, utilities, and data. + date_publication: '2022-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=astroFns + url_git: '' +astsa: + version: '2.2' + title: Applied Statistical Time Series Analysis + maintainer: David Stoffer + description: 'Contains data sets and scripts for analyzing time series in both the + frequency and time domains including state space modeling as well as supporting + the texts Time Series Analysis and Its Applications: With R Examples (5th ed), + by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2025, , + and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, .' + date_publication: '2025-01-16' + bug_reports: https://github.com/nickpoison/astsa/issues + url: https://dsstoffer.github.io/ + url_cran: https://CRAN.R-project.org/package=astsa + url_git: '' +asus: + version: 1.5.0 + title: Adaptive SURE Thresholding Using Side Information + maintainer: Trambak Banerjee + description: |- + Provides the ASUS procedure for estimating a high dimensional sparse parameter in the presence of auxiliary data that encode side information on sparsity. It is a robust data combination procedure in the sense that even when pooling non-informative auxiliary data ASUS would be at least as efficient as competing soft thresholding based methods that do not use auxiliary data. + For more information, please see the paper Adaptive Sparse Estimation with Side Information by Banerjee, Mukherjee and Sun (JASA 2020). + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asus + url_git: https://github.com/trambakbanerjee/asus#asus +ASV: + version: 1.1.4 + title: Stochastic Volatility Models with or without Leverage + maintainer: Yasuhiro Omori + description: The efficient Markov chain Monte Carlo estimation of stochastic volatility + models with and without leverage (asymmetric and symmetric stochastic volatility + models). Further, it computes the logarithm of the likelihood given parameters + using particle filters. + date_publication: '2024-02-15' + bug_reports: '' + url: https://sites.google.com/view/omori-stat/english/software/asv-r + url_cran: https://CRAN.R-project.org/package=ASV + url_git: '' +AsyK: + version: 1.5.5 + title: Kernel Density Estimation + maintainer: Javaria Ahmad Khan + description: A collection of functions related to density estimation by using Chen's + (2000) idea. Mean Squared Errors (MSE) are calculated for estimated curves. For + this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull. + For details see Chen (2000), Scaillet (2004) + and Khan and Akbar. + date_publication: '2021-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AsyK + url_git: '' +asylum: + version: 1.1.2 + title: Data on Asylum and Resettlement for the UK + maintainer: Matthew Gwynfryn Thomas + description: |- + Data on Asylum and Resettlement for the UK, + provided by the Home Office . + date_publication: '2023-12-19' + bug_reports: https://github.com/humaniverse/asylum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=asylum + url_git: https://github.com/humaniverse/asylum +asymLD: + version: '0.1' + title: |- + Asymmetric Linkage Disequilibrium (ALD) for Polymorphic Genetic + Data + maintainer: Richard M. Single + description: Computes asymmetric LD measures (ALD) for multi-allelic genetic data. + These measures are identical to the correlation measure (r) for bi-allelic data. + date_publication: '2016-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asymLD + url_git: '' +AsymmetricSORDs: + version: 1.0.0 + title: Asymmetric Second Order Rotatable Designs (AsymmetricSORDs) + maintainer: Ashutosh Dalal + description: 'Response surface designs (RSDs) are widely used for Response Surface + Methodology (RSM) based optimization studies, which aid in exploring the relationship + between a group of explanatory variables and one or more response variable(s) + (G.E.P. Box and K.B. Wilson (1951), "On the experimental attainment of optimum + conditions" ; M. Hemavathi, Shashi Shekhar, Eldho Varghese, Seema Jaggi, Bikas + Sinha & Nripes Kumar Mandal (2022) ."Theoretical + developments in response surface designs: an informative review and further thoughts".). + Second order rotatable designs are the most prominent and popular class of designs + used for process and product optimization trials but it is suitable for situations + when all the number of levels for each factor is the same. In many practical situations, + RSDs with asymmetric levels (J.S. Mehta and M.N. Das (1968). "Asymmetric rotatable + designs and orthogonal transformations" ; M. Hemavathi, Eldho Varghese, Shashi + Shekhar & Seema Jaggi (2020) . "Sequential + asymmetric third order rotatable designs (SATORDs)" .) are more suitable as these + designs explore more regions in the design space.This package contains functions + named Asords() ,CCD_coded(), CCD_original(), SORD_coded() and SORD_original() + for generating asymmetric/symmetric RSDs along with the randomized layout. It + also contains another function named Pred.var() for generating the variance of + predicted response as well as the moment matrix based on a second order model.' + date_publication: '2022-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AsymmetricSORDs + url_git: '' +asymmetry: + version: 2.0.4 + title: Multidimensional Scaling of Asymmetric Proximities + maintainer: Berrie Zielman + description: Multidimensional scaling models and methods for the visualization and + analysis of asymmetric proximity data . + An asymmetric data matrix has the same number of rows and columns, and these rows + and columns refer to the same set of objects. At least some elements in the upper-triangle + are different from the corresponding elements in the lower triangle. An example + of an asymmetric matrix is a student migration table, where the rows correspond + to the countries of origin of the students and the columns to the destination + countries. This package provides algorithms for three multidimensional scaling + models. These are the slide-vector model , a scaling model + with unique dimensions and the asymscal model for asymmetric multidimensional + scaling. Furthermore, a heat map for skew-symmetric data, and the decomposition + of asymmetry are provided for the exploratory analysis of asymmetric tables. + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asymmetry + url_git: '' +asymmetry.measures: + version: '0.2' + title: Asymmetry Measures for Probability Density Functions + maintainer: Dimitrios Bagkavos + description: 'Provides functions and examples for the weak and strong density asymmetry + measures in the articles: "A measure of asymmetry", Patil, Patil and Bagkavos + (2012) and "A measure of asymmetry based on a + new necessary and sufficient condition for symmetry", Patil, Bagkavos and Wood + (2014) . The measures provided here are useful + for quantifying the asymmetry of the shape of a density of a random variable. + The package facilitates implementation of the measures which are applicable in + a variety of fields including e.g. probability theory, statistics and economics.' + date_publication: '2020-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asymmetry.measures + url_git: '' +asympTest: + version: 0.1.4 + title: |- + A Simple R Package for Classical Parametric Statistical Tests + and Confidence Intervals in Large Samples + maintainer: Pierre Lafaye de Micheaux + description: |- + One and two sample mean and variance + tests (differences and ratios) are considered. + The test statistics are all expressed in the same + form as the Student t-test, which facilitates their + presentation in the classroom. This contribution + also fills the gap of a robust (to non-normality) + alternative to the chi-square single variance test + for large samples, since no such procedure is implemented + in standard statistical software. + date_publication: '2018-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=asympTest + url_git: '' +asymptor: + version: 1.1.0 + title: Estimate Asymptomatic Cases via Capture/Recapture Methods + maintainer: Hugo Gruson + description: |- + Estimate the lower and upper bound of asymptomatic cases in an + epidemic using the capture/recapture methods from Böhning et al. (2020) + and Rocchetti et al. (2020) + . Note there is currently some discussion + about the validity of the methods implemented in this package. You should + read carefully the original articles, alongside this answer from Li et al. + (2022) before using this package in your + project. + date_publication: '2022-10-05' + bug_reports: https://github.com/bisaloo/asymptor/issues + url: https://hugogruson.fr/asymptor/ + url_cran: https://CRAN.R-project.org/package=asymptor + url_git: https://github.com/bisaloo/asymptor +AsynchLong: + version: '2.3' + title: Regression Analysis of Sparse Asynchronous Longitudinal Data + maintainer: Shannon T. Holloway + description: |- + Estimation of regression models for sparse asynchronous + longitudinal observations, where time-dependent response and covariates + are mismatched and observed intermittently within subjects. Kernel + weighted estimating equations are used for generalized linear models + with either time-invariant or time-dependent coefficients. Cao, H., + Li, J., and Fine, J. P. (2016) . Cao, H., + Zeng, D., and Fine, J. P. (2015) . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AsynchLong + url_git: '' +ata: + version: 1.1.1 + title: Automated Test Assembly + maintainer: Michael Chajewski + description: |- + Provides a collection of psychometric methods to process item metadata + and use target assessment and measurement blueprint constraints to assemble a test form. Currently two automatic + test assembly (ata) approaches are enabled. For example, the weighted (positive) deviations method, wdm(), proposed + by Swanson and Stocking (1993) was implemented in its full specification allowing + for both item selection as well as test form refinement. The linear constraint programming approach, atalp(), uses the + linear equation solver by Berkelaar et. al (2014) + to enable a variety of approaches to select items. + date_publication: '2020-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ata + url_git: '' +atable: + version: 0.1.15 + title: Create Tables for Reporting Clinical Trials + maintainer: Armin Ströbel + description: |- + Create Tables for Reporting Clinical Trials. + Calculates descriptive statistics and hypothesis tests, + arranges the results in a table ready for reporting with LaTeX, HTML or Word. + date_publication: '2024-08-29' + bug_reports: https://github.com/arminstroebel/atable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=atable + url_git: https://github.com/arminstroebel/atable +ATAforecasting: + version: 0.0.60 + title: |- + Automatic Time Series Analysis and Forecasting using the Ata + Method + maintainer: Ali Sabri Taylan + description: |- + The Ata method (Yapar et al. (2019) ), an alternative to exponential smoothing (described in Yapar (2016) , + Yapar et al. (2017) ), is a new univariate time series forecasting method which provides innovative solutions to issues faced during the + initialization and optimization stages of existing forecasting methods. Forecasting performance of the Ata method is superior to existing methods both in terms of easy + implementation and accurate forecasting. It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend + and seasonal). This methodology performed well on the M3 and M4-competition data. This package was written based on Ali Sabri Taylan’s PhD dissertation. + date_publication: '2023-06-12' + bug_reports: https://github.com/alsabtay/ATAforecasting/issues + url: https://atamethod.wordpress.com/ + url_cran: https://CRAN.R-project.org/package=ATAforecasting + url_git: https://github.com/alsabtay/ATAforecasting +atakrig: + version: 0.9.8.1 + title: Area-to-Area Kriging + maintainer: Maogui Hu + description: 'Point-scale variogram deconvolution from irregular/regular spatial + support according to Goovaerts, P., (2008) ; ordinary + area-to-area (co)Kriging and area-to-point (co)Kriging.' + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=atakrig + url_git: '' +ATbounds: + version: 0.1.0 + title: Bounding Treatment Effects by Limited Information Pooling + maintainer: Sokbae Lee + description: |- + Estimation and inference methods for bounding average treatment effects (on the treated) that are valid under an unconfoundedness assumption. + The bounds are designed to be robust in challenging situations, for example, when the conditioning variables take on a large number of different values in the observed sample, or when the overlap condition is violated. + This robustness is achieved by only using limited "pooling" of information across observations. + For more details, see the paper by Lee and Weidner (2021), "Bounding Treatment Effects by Pooling Limited Information across Observations," . + date_publication: '2021-11-24' + bug_reports: https://github.com/ATbounds/ATbounds-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ATbounds + url_git: https://github.com/ATbounds/ATbounds-r/ +ATE.ERROR: + version: 1.0.0 + title: |- + Estimating ATE with Misclassified Outcomes and Mismeasured + Covariates + maintainer: Aryan Rezanezhad + description: 'Addressing measurement error in covariates and misclassification in + binary outcome variables within causal inference, the ''ATE.ERROR'' package implements + inverse probability weighted estimation methods proposed by Shu and Yi (2017, + ; 2019, ). These methods correct + errors to accurately estimate average treatment effects (ATE). The package includes + two main functions: ATE.ERROR.Y() for handling misclassification in the outcome + variable and ATE.ERROR.XY() for correcting both outcome misclassification and + covariate measurement error. It employs logistic regression for treatment assignment + and uses bootstrap sampling to calculate standard errors and confidence intervals, + with simulated datasets provided for practical demonstration.' + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ATE.ERROR + url_git: '' +AteMeVs: + version: 0.1.0 + title: |- + Average Treatment Effects with Measurement Error and Variable + Selection for Confounders + maintainer: Li-Pang Chen + description: A recent method proposed by Yi and Chen (2023) + is used to estimate the average treatment effects using noisy data containing + both measurement error and spurious variables. The package 'AteMeVs' contains + a set of functions that provide a step-by-step estimation procedure, including + the correction of the measurement error effects, variable selection for building + the model used to estimate the propensity scores, and estimation of the average + treatment effects. The functions contain multiple options for users to implement, + including different ways to correct for the measurement error effects, distinct + choices of penalty functions to do variable selection, and various regression + models to characterize propensity scores. + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AteMeVs + url_git: '' +atime: + version: 2025.1.21 + title: Asymptotic Timing + maintainer: Toby Hocking + description: |- + Computing and visualizing comparative + asymptotic timings of different algorithms and code versions. + Also includes functionality for comparing empirical timings with + expected references such as linear or quadratic, + + Also includes functionality for measuring asymptotic memory and other + quantities. + date_publication: '2025-01-21' + bug_reports: https://github.com/tdhock/atime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=atime + url_git: https://github.com/tdhock/atime +atlas: + version: 1.0.0 + title: Stanford 'ATLAS' Search Engine API + maintainer: Vladimir Polony + description: |- + Stanford 'ATLAS' (Advanced Temporal Search Engine) is a powerful tool that allows constructing + cohorts of patients extremely quickly and efficiently. This package is designed to interface directly + with an instance of 'ATLAS' search engine and facilitates API queries and data dumps. Prerequisite + is a good knowledge of the temporal language to be able to efficiently construct a query. + More information available at . + date_publication: '2018-08-10' + bug_reports: '' + url: https://shahlab.stanford.edu/start + url_cran: https://CRAN.R-project.org/package=atlas + url_git: '' +atlasapprox: + version: 0.1.0 + title: Cell Atlas Approximations + maintainer: Ying Xu + description: Provides an interface in R to cell atlas approximations. See the vignette + under "Getting started" for instructions. You can also explore the reference documentation + for specific functions. Additional interfaces and resources are available at . + date_publication: '2024-10-25' + bug_reports: https://github.com/fabilab/cell_atlas_approximations_API/issues + url: https://atlasapprox.readthedocs.io/en/latest/R/index.html + url_cran: https://CRAN.R-project.org/package=atlasapprox + url_git: https://github.com/fabilab/cell_atlas_approximations_API +AtlasMaker: + version: 0.1.0 + title: Make Multiple 'leaflet' Maps in 'Shiny' + maintainer: Rachel Greenlee + description: Simplify creating multiple, related 'leaflet' maps across tabs for + a 'shiny' application. Users build lists of any polygons, points, and polylines + needed for the project, use the map_server() function to assign built lists and + other chosen aesthetics into each tab, and the package leverages modules to generate + all map tabs. + date_publication: '2023-07-17' + bug_reports: https://github.com/rachel-greenlee/AtlasMaker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AtlasMaker + url_git: https://github.com/rachel-greenlee/AtlasMaker +AtmChile: + version: 1.0.4 + title: Download Air Quality and Meteorological Information of Chile + maintainer: Francisco Catalan Meyer + description: Download air quality and meteorological information of Chile from the + National Air Quality System (S.I.N.C.A.) dependent + on the Ministry of the Environment and the Meteorological Directorate of Chile + (D.M.C.) dependent on the Directorate General + of Civil Aeronautics. + date_publication: '2025-01-26' + bug_reports: https://github.com/franciscoxaxo/AtmChile/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AtmChile + url_git: https://github.com/franciscoxaxo/AtmChile +atmopt: + version: 0.1.0 + title: Analysis-of-Marginal-Tail-Means + maintainer: Simon Mak + description: Provides functions for implementing the Analysis-of-marginal-Tail-Means + (ATM) method, a robust optimization method for discrete black-box optimization. + Technical details can be found in Mak and Wu (2018+) . This + work was supported by USARO grant W911NF-17-1-0007. + date_publication: '2018-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=atmopt + url_git: '' +ATNr: + version: 1.1.0 + title: Run Allometric Trophic Networks Models + maintainer: Benoit Gauzens + description: Implements the differential equations associated to different versions + of Allometric Trophic Models (ATN) to estimate the temporal dynamics of species + biomasses in food webs. It offers several features to generate synthetic food + webs and to parametrise models as well as a wrapper to the ODE solver deSolve. + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ATNr + url_git: '' +atom4R: + version: 0.3-3 + title: Tools to Handle and Publish Metadata as 'Atom' XML Format + maintainer: Emmanuel Blondel + description: |- + Provides tools to read/write/publish metadata based on the 'Atom' XML syndication format. This includes + support of 'Dublin Core' XML implementation, and a client to API(s) implementing the 'AtomPub' 'SWORD' API specification. + date_publication: '2022-11-18' + bug_reports: https://github.com/eblondel/atom4R + url: '' + url_cran: https://CRAN.R-project.org/package=atom4R + url_git: https://github.com/eblondel/atom4R +atpolR: + version: 0.1.1 + title: ATPOL Grid Implementation + maintainer: Grzegorz Sapijaszko + description: |- + ATPOL is a rectangular grid system used for botanical studies in Poland. The ATPOL grid was developed in Institute of Botany, Jagiellonian University, Krakow, Poland in '70. Since then it is widely used to represent distribution of plants in Poland. + 'atpolR' provides functions to translate geographic coordinates to the grid and vice versa. It also allows to create a choreograph map. + date_publication: '2022-09-05' + bug_reports: https://github.com/gsapijaszko/atpolR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=atpolR + url_git: https://github.com/gsapijaszko/atpolR +ATQ: + version: 0.2.3 + title: Alert Time Quality - Evaluating Timely Epidemic Metrics + maintainer: Vinay Joshy + description: Provides tools for evaluating timely epidemic detection models within + school absenteeism-based surveillance systems. Introduces the concept of alert + time quality as an evaluation metric. Includes functions to simulate populations, + epidemics, and alert metrics associated with epidemic spread using population + census data. The methods are based on research published in Vanderkruk et al. + (2023) and Ward et al. (2019) . + date_publication: '2024-08-18' + bug_reports: https://github.com/vjoshy/ATQ_Surveillance_Package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ATQ + url_git: https://github.com/vjoshy/ATQ_Surveillance_Package +ATR: + version: 0.1-1 + title: Alternative Tree Representation + maintainer: Torsten Hothorn + description: |- + Plot party trees in left-right orientation instead of the + classical top-down layout. + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ATR + url_git: '' +atRisk: + version: 0.2.0 + title: At-Risk + maintainer: Quentin Lajaunie + description: The at-Risk (aR) approach is based on a two-step parametric estimation + procedure that allows to forecast the full conditional distribution of an economic + variable at a given horizon, as a function of a set of factors. These density + forecasts are then be used to produce coherent forecasts for any downside risk + measure, e.g., value-at-risk, expected shortfall, downside entropy. Initially + introduced by Adrian et al. (2019) to reveal the vulnerability + of economic growth to financial conditions, the aR approach is currently extensively + used by international financial institutions to provide Value-at-Risk (VaR) type + forecasts for GDP growth (Growth-at-Risk) or inflation (Inflation-at-Risk). This + package provides methods for estimating these models. Datasets for the US and + the Eurozone are available to allow testing of the Adrian et al. (2019) model. + This package constitutes a useful toolbox (data and functions) for private practitioners, + scholars as well as policymakers. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=atRisk + url_git: '' +atrrr: + version: 0.1.0 + title: Wrapper for the 'AT' Protocol Behind 'Bluesky' + maintainer: Johannes B. Gruber + description: |- + Wraps the 'AT' Protocol (Authenticated Transfer Protocol) behind + 'Bluesky' . Functions can be used for, among others, + retrieving posts and followers from the network or posting content. + date_publication: '2025-01-20' + bug_reports: https://github.com/JBGruber/atrrr/issues + url: https://jbgruber.github.io/atrrr/ + url_cran: https://CRAN.R-project.org/package=atrrr + url_git: https://github.com/JBGruber/atrrr +aTSA: + version: 3.1.2.1 + title: Alternative Time Series Analysis + maintainer: Debin Qiu + description: |- + Contains some tools for testing, analyzing time series data and + fitting popular time series models such as ARIMA, Moving Average and Holt + Winters, etc. Most functions also provide nice and clear outputs like SAS + does, such as identify, estimate and forecast, which are the same statements + in PROC ARIMA in SAS. + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aTSA + url_git: '' +attachment: + version: 0.4.4 + title: Deal with Dependencies + maintainer: Vincent Guyader + description: |- + Manage dependencies during package development. This can + retrieve all dependencies that are used in ".R" files in the "R/" + directory, in ".Rmd" files in "vignettes/" directory and in 'roxygen2' + documentation of functions. There is a function to update the + "DESCRIPTION" file of your package with 'CRAN' packages or any other + remote package. All functions to retrieve dependencies of ".R" + scripts and ".Rmd" or ".qmd" files can be used independently of a + package development. + date_publication: '2025-02-08' + bug_reports: https://github.com/ThinkR-open/attachment/issues + url: https://thinkr-open.github.io/attachment/ + url_cran: https://CRAN.R-project.org/package=attachment + url_git: https://github.com/ThinkR-open/attachment +attempt: + version: 0.3.1 + title: Tools for Defensive Programming + maintainer: Colin Fay + description: |- + Tools for defensive programming, inspired by 'purrr' mappers and + based on 'rlang'.'attempt' extends and facilitates defensive programming by + providing a consistent grammar, and provides a set of easy to use functions + for common tests and conditions. 'attempt' only depends on 'rlang', and + focuses on speed, so it can be easily integrated in other functions and + used in data analysis. + date_publication: '2020-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=attempt + url_git: https://github.com/ColinFay/attempt +attention: + version: 0.4.0 + title: Self-Attention Algorithm + maintainer: Bastiaan Quast + description: Self-Attention algorithm helper functions and demonstration vignettes + of increasing depth on how to construct the Self-Attention algorithm, this is + based on Vaswani et al. (2017) , Dan Jurafsky and + James H. Martin (2022, ISBN:978-0131873216) + "Speech and Language Processing (3rd ed.)" and Alex Graves (2020) + "Attention and Memory in Deep Learning". + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=attention + url_git: '' +attenuation: + version: 1.0.0 + title: Correcting for Attenuation Due to Measurement Error + maintainer: Jonas Moss + description: |- + Confidence curves, confidence intervals and p-values for + correlation coefficients corrected for attenuation due to measurement error. + Implements the methods described in Moss (2019, ). + date_publication: '2019-11-08' + bug_reports: https://github.com/JonasMoss/attenuation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=attenuation + url_git: https://github.com/JonasMoss/attenuation/ +attrib: + version: 2021.1.2 + title: Attributable Burden of Disease + maintainer: Richard Aubrey White + description: Provides functions for estimating the attributable burden of disease + due to risk factors. The posterior simulation is performed using arm::sim as described + in Gelman, Hill (2012) and the attributable burden + method is based on Nielsen, Krause, Molbak . + date_publication: '2021-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=attrib + url_git: '' +AUC: + version: 0.3.2 + title: |- + Threshold Independent Performance Measures for Probabilistic + Classifiers + maintainer: Michel Ballings + description: 'Various functions to compute the area under the curve of selected + measures: The area under the sensitivity curve (AUSEC), the area under the specificity + curve (AUSPC), the area under the accuracy curve (AUACC), and the area under the + receiver operating characteristic curve (AUROC). Support for visualization and + partial areas is included.' + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AUC + url_git: '' +auctestr: + version: 1.0.0 + title: Statistical Testing for AUC Data + maintainer: Josh Gardner + description: |- + Performs statistical testing to compare predictive + models based on multiple observations of the A' statistic (also known as + Area Under the Receiver Operating Characteristic Curve, or AUC). + Specifically, it implements a testing method based on the equivalence + between the A' statistic and the Wilcoxon statistic. + For more information, see Hanley and McNeil (1982) . + date_publication: '2017-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=auctestr + url_git: '' +auctionr: + version: 0.1.0 + title: Estimate First-Price Auction Model + maintainer: Alex MacKay + description: |- + Estimates a first-price auction model with conditionally independent + private values as described in MacKay (2020) . The + model allows for unobserved heterogeneity that is common to all bidders in + addition to observable heterogeneity. + date_publication: '2020-06-25' + bug_reports: https://github.com/ajmack/auctionr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=auctionr + url_git: https://github.com/ajmack/auctionr +audio: + version: 0.1-11 + title: Audio Interface for R + maintainer: Simon Urbanek + description: Interfaces to audio devices (mainly sample-based) from R to allow recording + and playback of audio. Built-in devices include Windows MM, Mac OS X AudioUnits + and PortAudio (the last one is very experimental). + date_publication: '2023-08-18' + bug_reports: '' + url: http://www.rforge.net/audio/ + url_cran: https://CRAN.R-project.org/package=audio + url_git: '' +audiometry: + version: 0.3.0 + title: Standard Conform Pure Tone Audiometry (PTA) Plots + maintainer: Bernhard Lehnert + description: Facilitates plotting audiometric data (mostly) by preparing the coordinate + system according to standards, given e. g. in American Speech-Language-Hearing + Association (2005), . + date_publication: '2021-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=audiometry + url_git: '' +audit: + version: 0.1-2 + title: Bounds for Accounting Populations + maintainer: Glen Meeden + description: |- + Find an upper bound for the total amount of overstatement + of assets in a set of accounts, or estimate the amount of sales tax + owed on a collection of transactions (Meeden and Sargent, 2007, + ). + date_publication: '2021-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=audit + url_git: '' +auditor: + version: 1.3.5 + title: Model Audit - Verification, Validation, and Error Analysis + maintainer: Alicja Gosiewska + description: |- + Provides an easy to use unified interface for creating validation plots for any model. + The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. + This visualizations allow to asses and compare the goodness of fit, performance, and similarity of models. + date_publication: '2023-10-30' + bug_reports: https://github.com/ModelOriented/auditor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=auditor + url_git: https://github.com/ModelOriented/auditor +audrex: + version: 2.0.1 + title: Automatic Dynamic Regression using Extreme Gradient Boosting + maintainer: Giancarlo Vercellino + description: Dynamic regression for time series using Extreme Gradient Boosting + with hyper-parameter tuning via Bayesian Optimization or Random Search. + date_publication: '2022-03-23' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/audrex + url_cran: https://CRAN.R-project.org/package=audrex + url_git: '' +audubon: + version: 0.5.2 + title: Japanese Text Processing Tools + maintainer: Akiru Kato + description: |- + A collection of Japanese text processing tools for filling + Japanese iteration marks, Japanese character type conversions, + segmentation by phrase, and text normalization which is based on rules + for the 'Sudachi' morphological analyzer and the 'NEologd' (Neologism + dictionary for 'MeCab'). These features are specific to Japanese and + are not implemented in 'ICU' (International Components for Unicode). + date_publication: '2024-04-27' + bug_reports: https://github.com/paithiov909/audubon/issues + url: https://paithiov909.github.io/audubon/ + url_cran: https://CRAN.R-project.org/package=audubon + url_git: https://github.com/paithiov909/audubon +augmentedRCBD: + version: 0.1.7 + title: Analysis of Augmented Randomised Complete Block Designs + maintainer: J. Aravind + description: |- + Functions for analysis of data generated from experiments in + augmented randomised complete block design according to Federer, W.T. + (1961) . Computes analysis of variance, adjusted + means, descriptive statistics, genetic variability statistics etc. + Further includes data visualization and report generation functions. + date_publication: '2023-08-19' + bug_reports: https://github.com/aravind-j/augmentedRCBD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=augmentedRCBD + url_git: https://github.com/aravind-j/augmentedRCBDhttps://CRAN.R-project.org/package=augmentedRCBDhttps://aravind-j.github.io/augmentedRCBD/https://doi.org/10.5281/zenodo.1310011 +augSIMEX: + version: 3.7.4 + title: |- + Analysis of Data with Mixed Measurement Error and + Misclassification in Covariates + maintainer: Qihuang Zhang + description: |- + Implementation of the augmented + Simulation-Extrapolation (SIMEX) algorithm proposed by Yi et al. (2015) + for analyzing the data with mixed measurement error and misclassification. The main + function provides a similar summary output as that of glm() function. Both parametric and + empirical SIMEX are considered in the package. + date_publication: '2020-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=augSIMEX + url_git: '' +auk: + version: 0.8.0 + title: eBird Data Extraction and Processing in R + maintainer: Matthew Strimas-Mackey + description: |- + Extract and process bird sightings records from + eBird (), an online tool for recording bird + observations. Public access to the full eBird database is via the + eBird Basic Dataset (EBD; see + for access), a downloadable text file. This package is an interface to + AWK for extracting data from the EBD based on taxonomic, spatial, or + temporal filters, to produce a manageable file size that can be + imported into R. + date_publication: '2025-01-14' + bug_reports: https://github.com/CornellLabofOrnithology/auk/issues + url: https://cornelllabofornithology.github.io/auk/ + url_cran: https://CRAN.R-project.org/package=auk + url_git: https://github.com/CornellLabofOrnithology/auk +aum: + version: 2024.6.19 + title: Area Under Minimum of False Positives and Negatives + maintainer: Toby Dylan Hocking + description: |- + Efficient algorithms + + for computing Area Under Minimum, + directional derivatives, and + line search optimization of a linear model, + with objective defined as either + max Area Under the Curve or + min Area Under Minimum. + date_publication: '2024-06-20' + bug_reports: https://github.com/tdhock/aum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aum + url_git: https://github.com/tdhock/aum +AurieLSHGaussian: + version: 0.2.0 + title: |- + Creates a Neighbourhood Using Locality Sensitive Hashing for + Gaussian Projections + maintainer: Aritra Banerjee + description: Uses locality sensitive hashing and creates a neighbourhood graph for + a data set and calculates the adjusted rank index value for the same. It uses + Gaussian random planes to decide the nature of a given point. Datar, Mayur, Nicole + Immorlica, Piotr Indyk, and Vahab S. Mirrokni(2004) . + date_publication: '2017-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AurieLSHGaussian + url_git: '' +auRoc: + version: 0.2-1 + title: Various Methods to Estimate the AUC + maintainer: Dai Feng + description: |- + Estimate the AUC using a variety of methods as follows: + (1) frequentist nonparametric methods based on the Mann-Whitney statistic or kernel methods. + (2) frequentist parametric methods using the likelihood ratio test based on higher-order + asymptotic results, the signed log-likelihood ratio test, the Wald test, + or the approximate ''t'' solution to the Behrens-Fisher problem. + (3) Bayesian parametric MCMC methods. + date_publication: '2020-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=auRoc + url_git: '' +ausplotsR: + version: 2.0.5 + title: TERN AusPlots Australian Ecosystem Monitoring Data + maintainer: Greg Guerin + description: Extraction, preparation, visualisation and analysis of TERN AusPlots + ecosystem monitoring data. Direct access to plot-based data on vegetation and + soils across Australia, including physical sample barcode numbers. Simple function + calls extract the data and merge them into species occurrence matrices for downstream + analysis, or calculate things like basal area and fractional cover. TERN AusPlots + is a national field plot-based ecosystem surveillance monitoring method and dataset + for Australia. The data have been collected across a national network of plots + and transects by the Terrestrial Ecosystem Research Network (TERN - ), + an Australian Government NCRIS-enabled project, and its Ecosystem Surveillance + platform (). + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ausplotsR + url_git: '' +AustralianPoliticians: + version: 0.1.0 + title: Provides Datasets About Australian Politicians + maintainer: Rohan Alexander + description: |- + Provides access to biographical and political data about Australian + federal politicians who served between 1901 and 2021. This enhances how + reproducible research is that uses this data. + date_publication: '2021-11-30' + bug_reports: https://github.com/RohanAlexander/AustralianPoliticians/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AustralianPoliticians + url_git: https://github.com/RohanAlexander/AustralianPoliticians +AUtests: + version: '0.99' + title: Approximate Unconditional and Permutation Tests + maintainer: Arjun Sondhi + description: |- + Performs approximate unconditional and permutation testing for + 2x2 contingency tables. Motivated by testing for disease association with rare + genetic variants in case-control studies. When variants are extremely rare, + these tests give better control of Type I error than standard tests. + date_publication: '2020-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AUtests + url_git: '' +auth0: + version: 0.2.3 + title: Authentication in Shiny with Auth0 + maintainer: Julio Trecenti + description: |- + Uses Auth0 API (see for more + information) to use a simple authentication system. It provides + tools to log in and out a shiny application using social networks or a list + of e-mails. + date_publication: '2023-03-26' + bug_reports: https://github.com/curso-r/auth0/issues + url: https://curso-r.github.io/auth0/ + url_cran: https://CRAN.R-project.org/package=auth0 + url_git: '' +authoritative: + version: 0.1.0 + title: Parse and Deduplicate Author Names + maintainer: Hugo Gruson + description: |- + Utilities to parse authors fields from DESCRIPTION files and + general purpose functions to deduplicate names in database, beyond the + specific case of R package authors. + date_publication: '2025-02-03' + bug_reports: https://github.com/epiverse-connect/authoritative/issues + url: '' + url_cran: https://CRAN.R-project.org/package=authoritative + url_git: https://github.com/epiverse-connect/authoritative +auto.pca: + version: '0.3' + title: Automatic Variable Reduction Using Principal Component Analysis + maintainer: Navinkumar Nedunchezhian + description: PCA done by eigenvalue decomposition of a data correlation matrix, + here it automatically determines the number of factors by eigenvalue greater than + 1 and it gives the uncorrelated variables based on the rotated component scores, + Such that in each principal component variable which has the high variance are + selected. It will be useful for non-statisticians in selection of variables. For + more information, see the + web page. + date_publication: '2017-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=auto.pca + url_git: '' +AutoAds: + version: 0.1.0 + title: Advertisement Metrics Calculation + maintainer: Ivan Nemtsev + description: 'Calculations of the most common metrics of automated advertisement + and plotting of them with trend and forecast. Calculations and description of + metrics is taken from different RTB platforms support documentation. Plotting + and forecasting is based on packages ''forecast'', described in Rob J Hyndman + and George Athanasopoulos (2021) "Forecasting: Principles and Practice" + and Rob J Hyndman et al "Documentation for ''forecast''" (2003) , + and ''ggplot2'', described in Hadley Wickham et al "Documentation for ''ggplot2''" + (2015) , and Hadley Wickham, Danielle Navarro, + and Thomas Lin Pedersen (2015) "ggplot2: Elegant Graphics for Data Analysis" .' + date_publication: '2023-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoAds + url_git: '' +autoBagging: + version: 0.1.0 + title: Learning to Rank Bagging Workflows with Metalearning + maintainer: Vitor Cerqueira + description: 'A framework for automated machine learning. Concretely, the focus + is on the optimisation of bagging workflows. A bagging workflows is composed by + three phases: (i) generation: which and how many predictive models to learn; (ii) + pruning: after learning a set of models, the worst ones are cut off from the ensemble; + and (iii) integration: how the models are combined for predicting a new observation. + autoBagging optimises these processes by combining metalearning and a learning + to rank approach to learn from metadata. It automatically ranks 63 bagging workflows + by exploiting past performance and dataset characterization. A complete description + of the method can be found in: Pinto, F., Cerqueira, V., Soares, C., Mendes-Moreira, + J. (2017): "autoBagging: Learning to Rank Bagging Workflows with Metalearning" + arXiv preprint arXiv:1706.09367.' + date_publication: '2017-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autoBagging + url_git: '' +autocogs: + version: 0.1.4 + title: Automatic Cognostic Summaries + maintainer: Ryan Hafen + description: Automatically calculates cognostic groups for plot objects and list + column plot objects. Results are returned in a nested data frame. + date_publication: '2021-05-29' + bug_reports: https://github.com/schloerke/autocogs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autocogs + url_git: https://github.com/schloerke/autocogs +autoCovariateSelection: + version: 1.0.0 + title: Automated Covariate Selection Using HDPS Algorithm + maintainer: Dennis Robert + description: |- + Contains functions to implement automated covariate selection using methods described in the + high-dimensional propensity score (HDPS) algorithm by Schneeweiss et.al. Covariate adjustment in real-world-observational-data (RWD) is important for + for estimating adjusted outcomes and this can be done by using methods such as, but not limited to, propensity score + matching, propensity score weighting and regression analysis. While these methods strive to statistically adjust for + confounding, the major challenge is in selecting the potential covariates that can bias the outcomes comparison estimates + in observational RWD (Real-World-Data). This is where the utility of automated covariate selection comes in. + The functions in this package help to implement the three major steps of automated covariate selection as described by + Schneeweiss et. al elsewhere. These three functions, in order of the steps required to execute automated covariate + selection are, get_candidate_covariates(), get_recurrence_covariates() and get_prioritised_covariates(). + In addition to these functions, a sample real-world-data from publicly available de-identified medical claims data is + also available for running examples and also for further exploration. The original article where the algorithm is described + by Schneeweiss et.al. (2009) . + date_publication: '2020-12-14' + bug_reports: https://github.com/technOslerphile/autoCovariateSelection/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoCovariateSelection + url_git: https://github.com/technOslerphile/autoCovariateSelection +AutoDeskR: + version: 0.1.5 + title: An Interface to the 'AutoDesk' 'API' Platform + maintainer: Paul Govan + description: |- + An interface to the 'AutoDesk' 'API' Platform including the Authentication + 'API' for obtaining authentication to the 'AutoDesk' Forge Platform, Data Management + 'API' for managing data across the platform's cloud services, Design Automation 'API' + for performing automated tasks on design files in the cloud, Model + Derivative 'API' for translating design files into different formats, sending + them to the viewer app, and extracting design data, and Viewer for rendering + 2D and 3D models. + date_publication: '2024-09-10' + bug_reports: https://github.com/paulgovan/AutoDeskR/issues + url: https://aps.autodesk.com + url_cran: https://CRAN.R-project.org/package=AutoDeskR + url_git: https://github.com/paulgovan/AutoDeskR +autoEnsemble: + version: '0.2' + title: Automated Stacked Ensemble Classifier for Severe Class Imbalance + maintainer: E. F. Haghish + description: |- + An AutoML algorithm is developed to construct homogeneous or + heterogeneous stacked ensemble models using specified base-learners. + Various criteria are employed to identify optimal models, enhancing + diversity among them and resulting in more robust stacked ensembles. + The algorithm optimizes the model by incorporating an increasing + number of top-performing models to create a diverse combination. + Presently, only models from 'h2o.ai' are supported. + date_publication: '2023-05-09' + bug_reports: https://github.com/haghish/autoEnsemble/issues + url: https://www.sv.uio.no/psi/english/people/academic/haghish/ + url_cran: https://CRAN.R-project.org/package=autoEnsemble + url_git: https://github.com/haghish/autoEnsemble +autoFC: + version: 0.2.0.1001 + title: Automatic Construction of Forced-Choice Tests + maintainer: Mengtong Li + description: |- + Forced-choice (FC) response has gained increasing popularity + and interest for its resistance to faking when well-designed (Cao & + Drasgow, 2019 ). To established well-designed + FC scales, typically each item within a block should measure different + trait and have similar level of social desirability (Zhang et al., + 2020 ). Recent study also suggests the + importance of high inter-item agreement of social desirability between + items within a block (Pavlov et al., 2021 ). + In addition to this, FC developers may + also need to maximize factor loading differences (Brown & + Maydeu-Olivares, 2011 ) or minimize item + location differences (Cao & Drasgow, 2019 ) + depending on scoring models. Decision of which items should be + assigned to the same block, termed item pairing, is thus critical to + the quality of an FC test. This pairing process is essentially an + optimization process which is currently carried out manually. However, + given that we often need to simultaneously meet multiple objectives, + manual pairing becomes impractical or even not feasible once the + number of latent traits and/or number of items per trait are + relatively large. To address these problems, autoFC is developed as a + practical tool for facilitating the automatic construction of FC tests + (Li et al., 2022 ), essentially + exempting users from the burden of manual item pairing and reducing + the computational costs and biases induced by simple ranking methods. + Given characteristics of each item (and item responses), FC measures can + be constructed either automatically based on user-defined pairing criteria + and weights, or based on exact specifications of each block (i.e., blueprint; + see Li et al., 2024 ). Users can also + generate simulated responses based on the Thurstonian Item Response Theory + model (Brown & Maydeu-Olivares, 2011 ) and + predict trait scores of simulated/actual respondents based on + an estimated model. + date_publication: '2024-02-17' + bug_reports: https://github.com/tspsyched/autoFC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoFC + url_git: https://github.com/tspsyched/autoFC +autoFRK: + version: 1.4.3 + title: Automatic Fixed Rank Kriging + maintainer: ShengLi Tzeng + description: |- + Automatic fixed rank kriging for (irregularly located) + spatial data using a class of basis functions with multi-resolution features + and ordered in terms of their resolutions. The model parameters are estimated + by maximum likelihood (ML) and the number of basis functions is determined + by Akaike's information criterion (AIC). For spatial data with either one + realization or independent replicates, the ML estimates and AIC are efficiently + computed using their closed-form expressions when no missing value occurs. Details + regarding the basis function construction, parameter estimation, and AIC calculation + can be found in Tzeng and Huang (2018) . For + data with missing values, the ML estimates are obtained using the expectation- + maximization algorithm. Apart from the number of basis functions, there are + no other tuning parameters, making the method fully automatic. Users can also + include a stationary structure in the spatial covariance, which utilizes + 'LatticeKrig' package. + date_publication: '2021-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autoFRK + url_git: '' +autogam: + version: 0.1.0 + title: Automate the Creation of Generalized Additive Models (GAMs) + maintainer: Chitu Okoli + description: This wrapper package for 'mgcv' makes it easier to create high-performing + Generalized Additive Models (GAMs). With its central function autogam(), by entering + just a dataset and the name of the outcome column as inputs, 'AutoGAM' tries to + automate the procedure of configuring a highly accurate GAM which performs at + reasonably high speed, even for large datasets. + date_publication: '2025-02-24' + bug_reports: https://github.com/tripartio/autogam/issues + url: https://tripartio.github.io/autogam/ + url_cran: https://CRAN.R-project.org/package=autogam + url_git: https://github.com/tripartio/autogam +autoGO: + version: 1.0.1 + title: |- + Auto-GO: Reproducible, Robust and High Quality Ontology + Enrichment Visualizations + maintainer: Fabio Ticconi + description: Auto-GO is a framework that enables automated, high quality Gene Ontology + enrichment analysis visualizations. It also features a handy wrapper for Differential + Expression analysis around the 'DESeq2' package described in Love et al. (2014) + . The whole framework is structured in different, + independent functions, in order to let the user decide which steps of the analysis + to perform and which plot to produce. + date_publication: '2025-02-27' + bug_reports: https://github.com/mpallocc/auto-go/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoGO + url_git: '' +autoharp: + version: 0.0.10 + title: Semi-Automatic Grading of R and Rmd Scripts + maintainer: Vik Gopal + description: |- + A customisable set of tools for assessing and grading + R or R-markdown scripts from students. It allows for checking correctness + of code output, runtime statistics and static code analysis. The latter + feature is made possible by representing R expressions using a tree + structure. + date_publication: '2021-11-12' + bug_reports: '' + url: https://singator.github.io/autoharp-docs/ + url_cran: https://CRAN.R-project.org/package=autoharp + url_git: '' +autohrf: + version: 1.1.3 + title: |- + Automated Generation of Data-Informed GLM Models in Task-Based + fMRI Data Analysis + maintainer: Jure Demšar + description: Analysis of task-related functional magnetic resonance imaging (fMRI) + activity at the level of individual participants is commonly based on general + linear modelling (GLM) that allows us to estimate to what extent the blood oxygenation + level dependent (BOLD) signal can be explained by task response predictors specified + in the GLM model. The predictors are constructed by convolving the hypothesised + timecourse of neural activity with an assumed hemodynamic response function (HRF). + To get valid and precise estimates of task response, it is important to construct + a model of neural activity that best matches actual neuronal activity. The construction + of models is most often driven by predefined assumptions on the components of + brain activity and their duration based on the task design and specific aims of + the study. However, our assumptions about the onset and duration of component + processes might be wrong and can also differ across brain regions. This can result + in inappropriate or suboptimal models, bad fitting of the model to the actual + data and invalid estimations of brain activity. Here we present an approach in + which theoretically driven models of task response are used to define constraints + based on which the final model is derived computationally using the actual data. + Specifically, we developed 'autohrf' — a package for the 'R' programming language + that allows for data-driven estimation of HRF models. The package uses genetic + algorithms to efficiently search for models that fit the underlying data well. + The package uses automated parameter search to find the onset and duration of + task predictors which result in the highest fitness of the resulting GLM based + on the fMRI signal under predefined restrictions. We evaluate the usefulness of + the 'autohrf' package on publicly available datasets of task-related fMRI activity. + Our results suggest that by using 'autohrf' users can find better task related + brain activity models in a quick and efficient manner. + date_publication: '2024-01-16' + bug_reports: https://github.com/demsarjure/autohrf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autohrf + url_git: https://github.com/demsarjure/autohrf +autoimage: + version: 2.2.3 + title: Multiple Heat Maps for Projected Coordinates + maintainer: Joshua French + description: |- + Functions for displaying multiple images or scatterplots with a color + scale, i.e., heat maps, possibly with projected coordinates. The + package relies on the base graphics system, so graphics are + rendered rapidly. + date_publication: '2021-03-16' + bug_reports: https://github.com/jfrench/autoimage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoimage + url_git: '' +autoimport: + version: 0.1.1 + title: Automatic Generation of @importFrom Tags + maintainer: Dan Chaltiel + description: |- + A toolbox to read all R files inside a package and + automatically generate @importFrom 'roxygen2' tags in the right place. + Includes a 'shiny' application to review the changes before applying them. + date_publication: '2025-02-03' + bug_reports: https://github.com/DanChaltiel/autoimport/issues + url: https://danchaltiel.github.io/autoimport/ + url_cran: https://CRAN.R-project.org/package=autoimport + url_git: https://github.com/DanChaltiel/autoimport +autokeras: + version: 1.0.12 + title: R Interface to 'AutoKeras' + maintainer: Juan Cruz Rodriguez + description: |- + R Interface to 'AutoKeras' . + 'AutoKeras' is an open source software library for Automated Machine + Learning (AutoML). The ultimate goal of AutoML is to provide easily + accessible deep learning tools to domain experts with limited data science + or machine learning background. 'AutoKeras' provides functions to + automatically search for architecture and hyperparameters of deep + learning models. + date_publication: '2021-01-17' + bug_reports: https://github.com/r-tensorflow/autokeras/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autokeras + url_git: https://github.com/r-tensorflow/autokeras +automagic: + version: 0.5.1 + title: |- + Automagically Document and Install Packages Necessary to Run R + Code + maintainer: Cole Brokamp + description: Parse R code in a given directory for R packages and attempt to install + them from CRAN or GitHub. Optionally use a dependencies file for tighter control + over which package versions to install. + date_publication: '2019-03-05' + bug_reports: https://github.com/cole-brokamp/automagic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=automagic + url_git: https://github.com/cole-brokamp/automagic +automap: + version: 1.1-16 + title: Automatic Interpolation Package + maintainer: Jon Olav Skoien + description: An automatic interpolation is done by automatically estimating the + variogram and then calling gstat. An overview is given by Hiemstra et al (2008) + . + date_publication: '2025-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=automap + url_git: '' +autometric: + version: 0.1.2 + title: Background Resource Logging + maintainer: William Michael Landau + description: |- + Intense parallel workloads can be difficult to monitor. + Packages 'crew.cluster', 'clustermq', and 'future.batchtools' + distribute hundreds of worker processes over multiple computers. + If a worker process exhausts its available memory, + it may terminate silently, leaving the underlying problem difficult + to detect or troubleshoot. + Using the 'autometric' package, a worker can proactively monitor + itself in a detached background thread. + The worker process itself runs normally, + and the thread writes to a log every few seconds. + If the worker terminates unexpectedly, 'autometric' can read and + visualize the log file to reveal potential resource-related + reasons for the crash. The 'autometric' package borrows heavily from + the methods of packages 'ps' and 'psutil'. + date_publication: '2024-11-15' + bug_reports: https://github.com/wlandau/autometric/issues + url: https://wlandau.github.io/autometric/ + url_cran: https://CRAN.R-project.org/package=autometric + url_git: https://github.com/wlandau/autometric +autoMFA: + version: 1.0.0 + title: Algorithms for Automatically Fitting MFA Models + maintainer: John Davey + description: |- + Provides methods for fitting the Mixture of Factor Analyzers (MFA) model automatically. + The MFA model is a mixture model where each sub-population is assumed to follow the Factor Analysis model. The Factor Analysis (FA) model is a latent variable model which assumes that observations are normally distributed, but imposes constraints on their covariance matrix. The MFA model contains two hyperparameters; g (the number of components in the mixture) and q (the number of factors in each component Factor Analysis model). Usually, the Expectation-Maximisation algorithm would be used to fit the MFA model, but this requires g and q to be known. This package treats g and q as unknowns and provides several methods which infer these values with as little input from the user as possible. + date_publication: '2021-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autoMFA + url_git: '' +automl: + version: 1.3.2 + title: Deep Learning with Metaheuristic + maintainer: Alex Boulangé + description: |- + Fits from simple regression to highly customizable deep neural networks + either with gradient descent or metaheuristic, using automatic hyper parameters + tuning and custom cost function. + A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization. + date_publication: '2020-01-16' + bug_reports: https://github.com/aboulaboul/automl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=automl + url_git: https://aboulaboul.github.io/automlhttps://github.com/aboulaboul/automl +autoMrP: + version: 1.0.6 + title: Improving MrP with Ensemble Learning + maintainer: Philipp Broniecki + description: |- + A tool that improves the prediction performance of multilevel + regression with post-stratification (MrP) by combining a number of machine + learning methods. For information on the method, please refer to Broniecki, + Wüest, Leemann (2020) ''Improving Multilevel Regression with + Post-Stratification Through Machine Learning (autoMrP)'' in the + 'Journal of Politics'. Final pre-print version: + . + date_publication: '2024-01-30' + bug_reports: https://github.com/retowuest/autoMrP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoMrP + url_git: https://github.com/retowuest/autoMrP +autonewsmd: + version: 0.0.9 + title: Auto-Generate Changelog using Conventional Commits + maintainer: Lorenz A. Kapsner + description: |- + Automatically generate a changelog file (NEWS.md / + CHANGELOG.md) from the git history using conventional commit messages + (). + date_publication: '2024-10-15' + bug_reports: https://github.com/kapsner/autonewsmd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autonewsmd + url_git: https://github.com/kapsner/autonewsmd +AutoPipe: + version: 0.1.6 + title: |- + Automated Transcriptome Classifier Pipeline: Comprehensive + Transcriptome Analysis + maintainer: Karam Daka + description: |- + An unsupervised fully-automated pipeline for transcriptome analysis or a supervised option to identify characteristic genes from predefined subclasses. + We rely on the 'pamr' clustering algorithm to cluster the Data and then draw a heatmap of the clusters with the most significant genes and the + least significant genes according to the 'pamr' algorithm. This way we get easy to grasp heatmaps that show us for each cluster which are the clusters most defining genes. + date_publication: '2019-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoPipe + url_git: '' +autoplotly: + version: 0.1.4 + title: |- + Automatic Generation of Interactive Visualizations for + Statistical Results + maintainer: Yuan Tang + description: |- + Functionalities to automatically generate interactive visualizations for + statistical results supported by 'ggfortify', such as time series, PCA, + clustering and survival analysis, with 'plotly.js' and + 'ggplot2' style. The generated visualizations can also be easily extended + using 'ggplot2' and 'plotly' syntax while staying interactive. + date_publication: '2021-04-18' + bug_reports: https://github.com/terrytangyuan/autoplotly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoplotly + url_git: https://github.com/terrytangyuan/autoplotly +Autoplotprotein: + version: '1.1' + title: Development of Visualization Tools for Protein Sequence + maintainer: Yao Geng + description: The image of the amino acid transform on the protein level is drawn, + and the automatic routing of the functional elements such as the domain and the + mutation site is completed. + date_publication: '2017-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Autoplotprotein + url_git: '' +AutoPlots: + version: 1.0.0 + title: Creating Echarts Visualizations as Easy as Possible + maintainer: Adrian Antico + description: 'Create beautiful and interactive visualizations in a single function + call. The ''data.table'' package is utilized to perform the data wrangling necessary + to prepare your data for the plot types you wish to build, along with allowing + fast processing for big data. There are two broad classes of plots available: + standard plots and machine learning evaluation plots. There are lots of parameters + available in each plot type function for customizing the plots (such as faceting) + and data wrangling (such as variable transformations and aggregation).' + date_publication: '2024-01-23' + bug_reports: https://github.com/AdrianAntico/AutoPlots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AutoPlots + url_git: https://github.com/AdrianAntico/AutoPlots +autoRasch: + version: 0.2.2 + title: Semi-Automated Rasch Analysis + maintainer: Feri Wijayanto + description: Performs Rasch analysis (semi-)automatically, which has been shown + to be comparable with the standard Rasch analysis (Feri Wijayanto et al. (2021) + , Feri Wijayanto et al. (2022) , + Feri Wijayanto et al. (2022) ). + date_publication: '2022-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autoRasch + url_git: '' +autoReg: + version: 0.3.3 + title: Automatic Linear and Logistic Regression and Survival Analysis + maintainer: Keon-Woong Moon + description: |- + Make summary tables for descriptive statistics and select explanatory variables + automatically in various regression models. Support linear models, generalized linear + models and cox-proportional hazard models. Generate publication-ready tables summarizing + result of regression analysis and plots. The tables and plots can be exported in "HTML", + "pdf('LaTex')", "docx('MS Word')" and "pptx('MS Powerpoint')" documents. + date_publication: '2023-11-14' + bug_reports: https://github.com/cardiomoon/autoReg/issues + url: https://cardiomoon.github.io/autoReg/ + url_cran: https://CRAN.R-project.org/package=autoReg + url_git: https://github.com/cardiomoon/autoReg +AutoregressionMDE: + version: '1.0' + title: Minimum Distance Estimation in Autoregressive Model + maintainer: Jiwoong Kim + description: Consider autoregressive model of order p where the distribution function + of innovation is unknown, but innovations are independent and symmetrically distributed. + The package contains a function named ARMDE which takes X (vector of n observations) + and p (order of the model) as input argument and returns minimum distance estimator + of the parameters in the model. + date_publication: '2015-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoregressionMDE + url_git: '' +AutoScore: + version: 1.0.0 + title: |- + An Interpretable Machine Learning-Based Automatic Clinical Score + Generator + maintainer: Feng Xie + description: 'A novel interpretable machine learning-based framework to automate + the development of a clinical scoring model for predefined outcomes. Our novel + framework consists of six modules: variable ranking with machine learning, variable + transformation, score derivation, model selection, domain knowledge-based score + fine-tuning, and performance evaluation.The The original AutoScore structure is + described in the research paper. A full tutorial can be found + here. Users or clinicians could seamlessly + generate parsimonious sparse-score risk models (i.e., risk scores), which can + be easily implemented and validated in clinical practice. We hope to see its application + in various medical case studies.' + date_publication: '2022-10-15' + bug_reports: https://github.com/nliulab/AutoScore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AutoScore + url_git: https://github.com/nliulab/AutoScore +autoScorecard: + version: 0.3.0 + title: Fully Automatic Generation of Scorecards + maintainer: Tai-Sen Zheng + description: |2- + + Provides an efficient suite of R tools for scorecard modeling, analysis, and visualization. + Including equal frequency binning, equidistant binning, + K-means binning, chi-square binning, decision tree binning, data screening, manual parameter modeling, + fully automatic generation of scorecards, etc. + This package is designed to make scorecard development easier and faster. + References include: + 1. . + 2. Dong-feng Li(Peking University),Class PPT. + 3. . + 4. . + date_publication: '2023-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autoScorecard + url_git: '' +Autoseed: + version: 0.1.0 + title: Retrieve Disease-Related Genes from Public Sources + maintainer: Jiawei Wu + description: |- + For researchers to quickly and comprehensively acquire disease genes, so as to understand the mechanism of disease, + we developed this program to acquire disease-related genes. + The data is integrated from three public databases. The three databases are 'eDGAR', 'DrugBank' + and 'MalaCards'. The 'eDGAR' is a comprehensive database, containing data on the relationship between disease and genes. + 'DrugBank' contains information on 13443 drugs and 5157 targets. 'MalaCards' integrates human disease information, including disease-related genes. + date_publication: '2020-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Autoseed + url_git: '' +autoshiny: + version: 0.0.3 + title: Automatic Transformation of an 'R' Function into a 'shiny' App + maintainer: Aleksander Rutkowski + description: Static code compilation of a 'shiny' app given an R function (into + 'ui.R' and 'server.R' files or into a 'shiny' app object). See examples at . + date_publication: '2023-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autoshiny + url_git: https://github.com/alekrutkowski/autoshiny +autoslider.core: + version: 0.2.3 + title: Slide Automation for Tables, Listings and Figures + maintainer: Joe Zhu + description: |- + The normal process of creating clinical study slides is that + a statistician manually type in the numbers from outputs and a + separate statistician to double check the typed in numbers. This + process is time consuming, resource intensive, and error prone. + Automatic slide generation is a solution to address these issues. It + reduces the amount of work and the required time when creating slides, + and reduces the risk of errors from manually typing or copying numbers + from the output to slides. It also helps users to avoid unnecessary + stress when creating large amounts of slide decks in a short time + window. + date_publication: '2025-01-17' + bug_reports: https://github.com/insightsengineering/autoslider.core/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoslider.core + url_git: https://github.com/insightsengineering/autoslider.core +autostats: + version: 0.4.1 + title: Auto Stats + maintainer: Harrison Tietze + description: Automatically do statistical exploration. Create formulas using 'tidyselect' + syntax, and then determine cross-validated model accuracy and variable contributions + using 'glm' and 'xgboost'. Contains additional helper functions to create and + modify formulas. Has a flagship function to quickly determine relationships between + categorical and continuous variables in the data set. + date_publication: '2024-06-04' + bug_reports: https://github.com/Harrison4192/autostats/issues + url: https://harrison4192.github.io/autostats/ + url_cran: https://CRAN.R-project.org/package=autostats + url_git: https://github.com/Harrison4192/autostats +AutoStepwiseGLM: + version: 0.2.0 + title: Builds Stepwise GLMs via Train and Test Approach + maintainer: Aaron England + description: Randomly splits data into testing and training sets. Then, uses stepwise + selection to fit numerous multiple regression models on the training data, and + tests them on the test data. Returned for each model are plots comparing model + Akaike Information Criterion (AIC), Pearson correlation coefficient (r) between + the predicted and actual values, Mean Absolute Error (MAE), and R-Squared among + the models. Each model is ranked relative to the other models by the model evaluation + metrics (i.e., AIC, r, MAE, and R-Squared) and the model with the best mean ranking + among the model evaluation metrics is returned. Model evaluation metric weights + for AIC, r, MAE, and R-Squared are taken in as arguments as aic_wt, r_wt, mae_wt, + and r_squ_wt, respectively. They are equally weighted as default but may be adjusted + relative to each other if the user prefers one or more metrics to the others, + Field, A. (2013, ISBN:978-1-4462-4918-5). + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoStepwiseGLM + url_git: '' +autostsm: + version: 3.1.5 + title: Automatic Structural Time Series Models + maintainer: Alex Hubbard + description: |- + Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. + Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" . + Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" . + date_publication: '2024-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=autostsm + url_git: '' +autothresholdr: + version: 1.4.2 + title: An R Port of the 'ImageJ' Plugin 'Auto Threshold' + maintainer: Rory Nolan + description: |- + Algorithms for automatically finding appropriate thresholds + for numerical data, with special functions for thresholding images. + Provides the 'ImageJ' 'Auto Threshold' plugin functionality to R + users. See and Landini et + al. (2017) . + date_publication: '2023-12-13' + bug_reports: https://github.com/rorynolan/autothresholdr/issues + url: https://rorynolan.github.io/autothresholdr/ + url_cran: https://CRAN.R-project.org/package=autothresholdr + url_git: https://github.com/rorynolan/autothresholdr#readme +AutoTransQF: + version: 0.1.3 + title: A Novel Automatic Shifted Log Transformation + maintainer: Yue Hu + description: A novel parametrization of log transformation and a shift parameter + to automate the transformation process are proposed in R package 'AutoTransQF' + based on Feng et al. (2016). Please read Feng et al. (2016) + for more details of the method. + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoTransQF + url_git: https://github.com/yyyuehhu/AutoTransQF +autoTS: + version: 0.9.11 + title: |- + Automatic Model Selection and Prediction for Univariate Time + Series + maintainer: Vivien Roussez + description: |- + Offers a set of functions to easily make predictions for univariate time series. + 'autoTS' is a wrapper of existing functions of the 'forecast' and 'prophet' packages, + harmonising their outputs in tidy dataframes and using default values for each. + The core function getBestModel() allows the user to effortlessly benchmark seven + algorithms along with a bagged estimator to identify which one performs the best + for a given time series. + date_publication: '2020-06-05' + bug_reports: https://github.com/vivienroussez/autots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=autoTS + url_git: https://github.com/vivienroussez/autoTS +autovi: + version: 0.4.1 + title: Auto Visual Inference with Computer Vision Models + maintainer: Weihao Li + description: Provides automated visual inference of residual plots using computer + vision models, facilitating diagnostic checks for classical normal linear regression + models. + date_publication: '2024-11-18' + bug_reports: https://github.com/TengMCing/autovi/issues + url: https://tengmcing.github.io/autovi/ + url_cran: https://CRAN.R-project.org/package=autovi + url_git: https://github.com/TengMCing/autovi/ +AutoWeatherIndices: + version: 0.1.0 + title: Calculating Weather Indices + maintainer: Achal Lama + description: Weather indices are formed from weather variables in this package. + The users can input any number of weather variables recorded over any number of + weeks. This package has no restriction on the number of weeks and weather variables + to be taken as input.The details of the method can be seen (i)'Joint effects of + weather variables on rice yields' by R. Agrawal, R. C. Jain and M. P. Jha in + Mausam, vol. 34, pp. 189-194, 1983,,(ii)'Improved + weather indices based Bayesian regression model for forecasting crop yield' by M. + Yeasin, K. N. Singh, A. Lama and B. Gurung in Mausam, vol. 72, pp.879-886, 2021,. + date_publication: '2022-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoWeatherIndices + url_git: '' +AutoWMM: + version: 1.0.1 + title: Perform the Weighted Multiplier Method on Trees + maintainer: Mallory J Flynn + description: When many possible multiplier method estimates of a target population + are available, a weighted sum of estimates from each back-calculated path can + be achieved with this package. Variance-minimizing weights are used and with + any admissible tree-structured data. The methodological basis used to create + this package can be found in Flynn (2023) . + date_publication: '2024-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AutoWMM + url_git: https://github.com/malfly/AutoWMM +AuxSurvey: + version: '1.0' + title: Survey Analysis with Auxiliary Discretized Variables + maintainer: Jungang Zou + description: 'Probability surveys often use auxiliary continuous data from administrative + records, but the utility of this data is diminished when it is discretized for + confidentiality. We provide a set of survey estimators to make full use of information + from the discretized variables. See Williams, S.Z., Zou, J., Liu, Y., Si, Y., + Galea, S. and Chen, Q. (2024), Improving Survey Inference Using Administrative + Records Without Releasing Individual-Level Continuous Data. Statistics in Medicine, + 43: 5803-5813. for details.' + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AuxSurvey + url_git: '' +av: + version: 0.9.4 + title: Working with Audio and Video in R + maintainer: Jeroen Ooms + description: |- + Bindings to 'FFmpeg' AV library for working with + audio and video in R. Generates high quality video from images or R graphics with + custom audio. Also offers high performance tools for reading raw audio, creating + 'spectrograms', and converting between countless audio / video formats. This package + interfaces directly to the C API and does not require any command line utilities. + date_publication: '2025-01-29' + bug_reports: https://github.com/ropensci/av/issues + url: https://ropensci.r-universe.dev/av + url_cran: https://CRAN.R-project.org/package=av + url_git: '' +available: + version: 1.1.0 + title: |- + Check if the Title of a Package is Available, Appropriate and + Interesting + maintainer: Gábor Csárdi + description: |- + Check if a given package name is available to use. It checks the + name's validity. Checks if it is used on 'GitHub', 'CRAN' and 'Bioconductor'. Checks + for unintended meanings by querying 'Wiktionary' and Wikipedia. + date_publication: '2022-07-10' + bug_reports: https://github.com/r-lib/available/issues + url: '' + url_cran: https://CRAN.R-project.org/package=available + url_git: https://github.com/r-lib/available +avar: + version: 0.1.3 + title: Allan Variance + maintainer: Stéphane Guerrier + description: Implements the allan variance and allan variance linear regression + estimator for latent time series models. More details about the method can be + found, for example, in Guerrier, S., Molinari, R., & Stebler, Y. (2016) . + date_publication: '2023-08-29' + bug_reports: https://github.com/SMAC-Group/avar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=avar + url_git: https://github.com/SMAC-Group/avar +averisk: + version: 1.0.3 + title: |- + Calculation of Average Population Attributable Fractions and + Confidence Intervals + maintainer: John Ferguson + description: |- + Average population attributable fractions are calculated for a set + of risk factors (either binary or ordinal valued) for both prospective and case- + control designs. Confidence intervals are found by Monte Carlo simulation. The + method can be applied to either prospective or case control designs, provided an + estimate of disease prevalence is provided. In addition to an exact calculation + of AF, an approximate calculation, based on randomly sampling permutations has + been implemented to ensure the calculation is computationally tractable when the + number of risk factors is large. + date_publication: '2017-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=averisk + url_git: '' +avesperu: + version: 0.0.3 + title: Access to the List of Birds Species of Peru + maintainer: Paul E. Santos Andrade + description: Allows access to the data found in the species list featured in the + renowned 'List of the Birds of Peru' Plenge, M. A. (2023) . + This publication stands as one of Peru's most comprehensive reviews of bird diversity. + The dataset incorporates detailed species accounts and has been meticulously structured + for effortless utilization within the R environment. + date_publication: '2024-12-05' + bug_reports: https://github.com/PaulESantos/avesperu/issues + url: https://paulesantos.github.io/avesperu/ + url_cran: https://CRAN.R-project.org/package=avesperu + url_git: https://github.com/PaulESantos/avesperu +AVGAS: + version: 0.1.0 + title: A Variable Selection using Genetic Algorithms + maintainer: Leiyue Li + description: We provide a stage-wise selection method using genetic algorithm which + can perform fast interaction selection in high-dimensional linear regression models + with two-way interaction effects under strong, weak, or no heredity condition. + Ye, C.,and Yang,Y. (2019) . + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AVGAS + url_git: '' +avidaR: + version: 1.2.1 + title: A Computational Biologist’s Toolkit To Get Data From 'avidaDB' + maintainer: Raúl Ortega + description: |- + Easy-to-use tools for performing complex queries on 'avidaDB', a + semantic database that stores genomic and transcriptomic data of + self-replicating computer programs (known as digital organisms) that mutate + and evolve within a user-defined computational environment. + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=avidaR + url_git: https://gitlab.com/fortunalab/avidaR +AvInertia: + version: 0.0.2 + title: Calculate the Inertial Properties of a Flying Bird + maintainer: Christina Harvey + description: |2- + + Tools to compute the center of gravity and moment of inertia tensor of any + flying bird. The tools function by modeling a bird as a composite structure + of simple geometric objects. This requires detailed morphological + measurements of bird specimens although those obtained for the associated + paper have been included in the package for use. Refer to the vignettes and + supplementary material for detailed information on the package function. + date_publication: '2022-03-24' + bug_reports: https://github.com/charvey23/AvInertia/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AvInertia + url_git: https://github.com/charvey23/AvInertia +aVirtualTwins: + version: 1.0.1 + title: Adaptation of Virtual Twins Method from Jared Foster + maintainer: Francois Vieille + description: Research of subgroups in random clinical trials with binary outcome + and two treatments groups. This is an adaptation of the Jared Foster method (). + date_publication: '2018-02-04' + bug_reports: https://github.com/prise6/aVirtualTwins/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aVirtualTwins + url_git: https://github.com/prise6/aVirtualTwins +avocado: + version: 0.1.0 + title: Weekly Hass Avocado Sales Summary + maintainer: Nikhil Agarwal + description: |- + Provides a weekly summary of Hass Avocado sales for the + contiguous US from January 2017 to November 2020. + See the package website for more information, documentation, + and examples. Data source: Haas Avocado Board + . + date_publication: '2020-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=avocado + url_git: '' +avotrex: + version: 1.3.0 + title: |- + A Global Dataset of Anthropogenic Extinct Birds and their + Traits: Phylogeny Builder + maintainer: Joseph Wayman + description: Grafts the extinct bird species from the 'Avotrex' database (Sayol + et al., in review) on to the 'BirdTree' phylogenies , using + a set of different commands. + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=avotrex + url_git: '' +awdb: + version: 0.1.1 + title: Query the USDA NWCC Air and Water Database REST API + maintainer: Kenneth Blake Vernon + description: |- + Query the four endpoints of the 'Air and Water Database (AWDB) REST + API' maintained by the National Water and Climate Center (NWCC) at the + United States Department of Agriculture (USDA). Endpoints include data, + forecast, reference-data, and metadata. The package is extremely light + weight, with 'Rust' via 'extendr' doing most of the heavy lifting to + deserialize and flatten deeply nested 'JSON' responses. The AWDB can be + found at . + date_publication: '2025-02-26' + bug_reports: https://github.com/kbvernon/awdb/issues + url: https://kbvernon.github.io/awdb/ + url_cran: https://CRAN.R-project.org/package=awdb + url_git: https://github.com/kbvernon/awdb +aweek: + version: 1.0.3 + title: Convert Dates to Arbitrary Week Definitions + maintainer: Zhian N. Kamvar + description: |- + Which day a week starts depends heavily on the either the local or + professional context. This package is designed to be a lightweight solution + to easily switching between week-based date definitions. + date_publication: '2022-10-06' + bug_reports: https://github.com/reconhub/aweek/issues/ + url: https://www.repidemicsconsortium.org/aweek/ + url_cran: https://CRAN.R-project.org/package=aweek + url_git: '' +aweSOM: + version: '1.3' + title: Interactive Self-Organizing Maps + maintainer: Julien Boelaert + description: Self-organizing maps (also known as SOM, see Kohonen (2001) ) + are a method for dimensionality reduction and clustering of continuous data. This + package introduces interactive (html) graphics for easier analysis of SOM results. + It also features an interactive interface, for push-button training and visualization + of SOM on numeric, categorical or mixed data, as well as tools to evaluate the + quality of SOM. + date_publication: '2022-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aweSOM + url_git: '' +awinR: + version: 0.1.0 + title: Get Data from 'Awin' via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from 'Awin' using + the 'Windsor.ai' API . + date_publication: '2022-11-30' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=awinR + url_git: '' +AWR: + version: 1.11.189-1 + title: '''AWS'' Java ''SDK'' for R' + maintainer: Gergely Daroczi + description: Make the compiled Java modules of the Amazon Web Services ('AWS') 'SDK' + available to be used in downstream R packages interacting with 'AWS'. See + for more information on the 'AWS' 'SDK' for Java. + date_publication: '2021-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AWR + url_git: https://github.com/daroczig/AWR +AWR.Kinesis: + version: 1.7.6 + title: Amazon 'Kinesis' Consumer Application for Stream Processing + maintainer: Gergely Daroczi + description: Fetching data from Amazon 'Kinesis' Streams using the Java-based 'MultiLangDaemon' + interacting with Amazon Web Services ('AWS') for easy stream processing from R. + For more information on 'Kinesis', see . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AWR.Kinesis + url_git: https://github.com/daroczig/AWR.Kinesis +aws: + version: 2.5-6 + title: Adaptive Weights Smoothing + maintainer: Joerg Polzehl + description: |- + We provide a collection of R-functions implementing + adaptive smoothing procedures in 1D, 2D and 3D. This includes the + Propagation-Separation Approach to adaptive smoothing, + the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter. + The package is described in detail in Polzehl J, Papafitsoros K, Tabelow K (2020). + Patch-Wise Adaptive Weights Smoothing in R. Journal of Statistical Software, 95(6), 1-27. + , + Usage of the package in MR imaging is illustrated in Polzehl and Tabelow (2023), + Magnetic Resonance Brain Imaging, 2nd Ed. Appendix A, Springer, Use R! Series. + . + date_publication: '2024-09-30' + bug_reports: '' + url: https://www.wias-berlin.de/people/polzehl/ + url_cran: https://CRAN.R-project.org/package=aws + url_git: '' +aws.alexa: + version: 0.1.8 + title: Client for the Amazon Alexa Web Information Services API + maintainer: Gaurav Sood + description: |- + Use the Amazon Alexa Web Information Services API to + find information about domains, including the kind of content + that they carry, how popular are they---rank and traffic history, + sites linking to them, among other things. See + for more information. + date_publication: '2020-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aws.alexa + url_git: '' +aws.comprehend: + version: 0.2.1 + title: Client for 'AWS Comprehend' + maintainer: Antoine Sachet + description: Client for 'AWS Comprehend' , a + cloud natural language processing service that can perform a number of quantitative + text analyses, including language detection, sentiment analysis, and feature extraction. + date_publication: '2020-03-18' + bug_reports: https://github.com/cloudyr/aws.comprehend/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.comprehend + url_git: https://github.com/cloudyr/aws.comprehend +aws.ec2metadata: + version: 0.2.0 + title: Get EC2 Instance Metadata + maintainer: Jonathan Stott + description: Retrieve Amazon EC2 instance metadata from within the running instance. + date_publication: '2019-07-15' + bug_reports: https://github.com/cloudyr/aws.ec2metadata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.ec2metadata + url_git: https://github.com/cloudyr/aws.ec2metadata +aws.ecx: + version: 1.0.5 + title: Communicating with AWS EC2 and ECS using AWS REST APIs + maintainer: Jiefei Wang + description: |2- + + Providing the functions for communicating with Amazon Web Services(AWS) + Elastic Compute Cloud(EC2) and Elastic Container Service(ECS). + The functions will have the prefix 'ecs_' or 'ec2_' depending on the class + of the API. The request will be sent via the REST API and the parameters are + given by the function argument. The credentials can be set via 'aws_set_credentials'. + The EC2 documentation can be found at + and ECS can be found at . + date_publication: '2022-01-26' + bug_reports: https://github.com/Jiefei-Wang/aws.ecx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.ecx + url_git: https://github.com/Jiefei-Wang/aws.ecx +aws.iam: + version: 0.1.8 + title: AWS IAM Client Package + maintainer: Simon Urbanek + description: |- + A simple client for the Amazon Web Services ('AWS') Identity + and Access Management ('IAM') 'API' . + date_publication: '2020-04-07' + bug_reports: https://github.com/cloudyr/aws.iam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.iam + url_git: https://github.com/cloudyr/aws.iam +aws.kms: + version: 0.1.4 + title: '''AWS Key Management Service'' Client Package' + maintainer: Simon Urbanek + description: Client package for the 'AWS Key Management Service' , + a cloud service for managing encryption keys. + date_publication: '2020-04-14' + bug_reports: https://github.com/cloudyr/aws.kms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.kms + url_git: https://github.com/cloudyr/aws.kms +aws.lambda: + version: 0.2.0 + title: AWS Lambda Client Package + maintainer: Jon Harmon + description: |- + A simple client package for the Amazon Web Services ('AWS') Lambda + API . + date_publication: '2020-04-15' + bug_reports: https://github.com/cloudyr/aws.lambda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.lambda + url_git: https://github.com/cloudyr/aws.lambda +aws.polly: + version: 0.1.5 + title: Client for AWS Polly + maintainer: Antoine Sachet + description: A client for AWS Polly , + a speech synthesis service. + date_publication: '2020-03-11' + bug_reports: https://github.com/cloudyr/aws.polly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.polly + url_git: https://github.com/cloudyr/aws.polly +aws.s3: + version: 0.3.21 + title: '''AWS S3'' Client Package' + maintainer: Simon Urbanek + description: |- + A simple client package for the Amazon Web Services ('AWS') Simple + Storage Service ('S3') 'REST' 'API' . + date_publication: '2020-04-07' + bug_reports: https://github.com/cloudyr/aws.s3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.s3 + url_git: https://github.com/cloudyr/aws.s3 +aws.signature: + version: 0.6.0 + title: Amazon Web Services Request Signatures + maintainer: Jonathan Stott + description: Generates version 2 and version 4 request signatures for Amazon Web + Services ('AWS') Application Programming Interfaces + ('APIs') and provides a mechanism for retrieving credentials from environment + variables, 'AWS' credentials files, and 'EC2' instance metadata. For use on 'EC2' + instances, users will need to install the suggested package 'aws.ec2metadata' + . + date_publication: '2020-06-01' + bug_reports: https://github.com/cloudyr/aws.signature/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.signature + url_git: https://github.com/cloudyr/aws.signature +aws.transcribe: + version: 0.1.3 + title: Client for 'AWS Transcribe' + maintainer: Antoine Sachet + description: Client for 'AWS Transcribe' , + a cloud transcription service that can convert an audio media file in English + and other languages into a text transcript. + date_publication: '2020-03-11' + bug_reports: https://github.com/cloudyr/aws.transcribe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.transcribe + url_git: https://github.com/cloudyr/aws.transcribe +aws.translate: + version: 0.1.4 + title: Client for 'AWS Translate' + maintainer: Antoine Sachet + description: A client for 'AWS Translate' , + a machine translation service that will convert a text input in one language into + a text output in another language. + date_publication: '2020-03-11' + bug_reports: https://github.com/cloudyr/aws.translate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=aws.translate + url_git: https://github.com/cloudyr/aws.translate +aws.wrfsmn: + version: 0.0.5 + title: Data Processing of SMN Hi-Res Weather Forecast from 'AWS' + maintainer: Gonzalo Diaz + description: |- + Exploration of Weather Research & Forecasting ('WRF') Model data + of Servicio Meteorologico Nacional (SMN) from Amazon Web Services + () cloud. The package + provides the possibility of data downloading, processing and correction + methods. It also has map management and series exploration of available + meteorological variables of 'WRF' forecast. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=aws.wrfsmn + url_git: '' +awsMethods: + version: 1.1-1 + title: |- + Class and Methods Definitions for Packages 'aws', 'adimpro', + 'fmri', 'dwi' + maintainer: Joerg Polzehl + description: Defines the method extract and provides 'openMP' support as needed + in several packages. + date_publication: '2019-05-08' + bug_reports: '' + url: http://www.wias-berlin.de/software/imaging/ + url_cran: https://CRAN.R-project.org/package=awsMethods + url_git: '' +axisandallies: + version: 0.1.1 + title: Axis and Allies Spring + maintainer: TJ Weaver + description: Simulates battles in the board game Axis and Allies Spring 1942, and + calculates your probability of winning a battle. This speeds the game up significantly. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=axisandallies + url_git: '' +AZIAD: + version: 0.0.3 + title: Analyzing Zero-Inflated and Zero-Altered Data + maintainer: Niloufar Dousti Mousavi + description: 'Description: Computes maximum likelihood estimates of general, zero-inflated, + and zero-altered models for discrete and continuous distributions. It also performs + Kolmogorov-Smirnov (KS) tests and likelihood ratio tests for general, zero-inflated, + and zero-altered data. Additionally, it obtains the inverse of the Fisher information + matrix and confidence intervals for the parameters of general, zero-inflated, + and zero-altered models. The package simulates random deviates from zero-inflated + or hurdle models to obtain maximum likelihood estimates. Based on the work of + Aldirawi et al. (2022) and Dousti Mousavi et + al. (2023) .' + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=AZIAD + url_git: '' +azlogr: + version: 0.0.6 + title: Logging in 'R' and Post to 'Azure Log Analytics' Workspace + maintainer: Vivek Atal + description: |- + It extends the functionality of 'logger' package. Additional + logging metadata can be configured to be collected. Logging messages are + displayed on console and optionally they are sent to 'Azure Log Analytics' + workspace in real-time. + date_publication: '2024-03-21' + bug_reports: https://github.com/atalv/azlogr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=azlogr + url_git: https://atalv.github.io/azlogr/https://github.com/atalv/azlogr/ +AzureAppInsights: + version: 0.3.1 + title: Include Azure Application Insights in Shiny Apps + maintainer: Stefan McKinnon Edwards + description: |- + Imports Azure Application Insights for web pages into Shiny apps + via Microsoft's JavaScript snippet. + Allows app developers to submit page tracking and submit events. + date_publication: '2023-06-13' + bug_reports: https://github.com/stefanedwards/AzureAppInsights/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureAppInsights + url_git: '' +AzureAuth: + version: 1.3.3 + title: Authentication Services for Azure Active Directory + maintainer: Hong Ooi + description: Provides Azure Active Directory (AAD) authentication functionality + for R users of Microsoft's 'Azure' cloud . Use this + package to obtain 'OAuth' 2.0 tokens for services including Azure Resource Manager, + Azure Storage and others. It supports both AAD v1.0 and v2.0, as well as multiple + authentication methods, including device code and resource owner grant. Tokens + are cached in a user-specific directory obtained using the 'rappdirs' package. + The interface is based on the 'OAuth' framework in the 'httr' package, but customised + and streamlined for Azure. Part of the 'AzureR' family of packages. + date_publication: '2021-09-13' + bug_reports: https://github.com/Azure/AzureAuth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureAuth + url_git: https://github.com/Azure/AzureAuthhttps://github.com/Azure/AzureR +AzureCognitive: + version: 1.0.1 + title: Interface to Azure Cognitive Services + maintainer: Hong Ooi + description: An interface to Azure Cognitive Services . + Both an 'Azure Resource Manager' interface, for deploying Cognitive Services resources, + and a client framework are supplied. While 'AzureCognitive' can be called by the + end-user, it is meant to provide a foundation for other packages that will support + specific services, like Computer Vision, Custom Vision, language translation, + and so on. Part of the 'AzureR' family of packages. + date_publication: '2020-10-15' + bug_reports: https://github.com/Azure/AzureCognitive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureCognitive + url_git: https://github.com/Azure/AzureCognitivehttps://github.com/Azure/AzureR +AzureContainers: + version: 1.3.2 + title: |- + Interface to 'Container Instances', 'Docker Registry' and + 'Kubernetes' in 'Azure' + maintainer: Hong Ooi + description: 'An interface to container functionality in Microsoft''s ''Azure'' + cloud: . Manage + ''Azure Container Instance'' (ACI), ''Azure Container Registry'' (ACR) and ''Azure + Kubernetes Service'' (AKS) resources, push and pull images, and deploy services. + On the client side, lightweight shells to the ''docker'', ''docker-compose'', + ''kubectl'' and ''helm'' commandline tools are provided. Part of the ''AzureR'' + family of packages.' + date_publication: '2021-07-09' + bug_reports: https://github.com/Azure/AzureContainers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureContainers + url_git: https://github.com/Azure/AzureContainershttps://github.com/Azure/AzureR +AzureCosmosR: + version: 1.0.0 + title: Interface to the 'Azure Cosmos DB' 'NoSQL' Database Service + maintainer: Hong Ooi + description: 'An interface to ''Azure CosmosDB'': . + On the admin side, ''AzureCosmosR'' provides functionality to create and manage + ''Cosmos DB'' instances in Microsoft''s ''Azure'' cloud. On the client side, it + provides an interface to the ''Cosmos DB'' SQL API, letting the user store and + query documents and attachments in ''Cosmos DB''. Part of the ''AzureR'' family + of packages.' + date_publication: '2021-01-18' + bug_reports: https://github.com/Azure/AzureCosmosR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureCosmosR + url_git: https://github.com/Azure/AzureCosmosRhttps://github.com/Azure/AzureR +AzureGraph: + version: 1.3.4 + title: Simple Interface to 'Microsoft Graph' + maintainer: Hong Ooi + description: 'A simple interface to the ''Microsoft Graph'' API . + ''Graph'' is a comprehensive framework for accessing data in various online Microsoft + services. This package was originally intended to provide an R interface only + to the ''Azure Active Directory'' part, with a view to supporting interoperability + of R and ''Azure'': users, groups, registered apps and service principals. However + it has since been expanded into a more general tool for interacting with Graph. + Part of the ''AzureR'' family of packages.' + date_publication: '2023-09-06' + bug_reports: https://github.com/Azure/AzureGraph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureGraph + url_git: https://github.com/Azure/AzureGraphhttps://github.com/Azure/AzureR +AzureKeyVault: + version: 1.0.5 + title: Key and Secret Management in 'Azure' + maintainer: Hong Ooi + description: 'Manage keys, certificates, secrets, and storage accounts in Microsoft''s + ''Key Vault'' service: . Provides + facilities to store and retrieve secrets, use keys to encrypt, decrypt, sign and + verify data, and manage certificates. Integrates with the ''AzureAuth'' package + to enable authentication with a certificate, and with the ''openssl'' package + for importing and exporting cryptographic objects. Part of the ''AzureR'' family + of packages.' + date_publication: '2021-09-16' + bug_reports: https://github.com/Azure/AzureKeyVault/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureKeyVault + url_git: https://github.com/Azure/AzureKeyVaulthttps://github.com/Azure/AzureR +AzureKusto: + version: 1.1.3 + title: Interface to 'Kusto'/'Azure Data Explorer' + maintainer: Alex Kyllo + description: 'An interface to ''Azure Data Explorer'', also known as ''Kusto'', + a fast, distributed data exploration service from Microsoft: . + Includes ''DBI'' and ''dplyr'' interfaces, with the latter modelled after the + ''dbplyr'' package, whereby queries are translated from R into the native ''KQL'' + query language and executed lazily. On the admin side, the package extends the + object framework provided by ''AzureRMR'' to support creation and deletion of + databases, and management of database principals. Part of the ''AzureR'' family + of packages.' + date_publication: '2023-10-12' + bug_reports: https://github.com/Azure/AzureKusto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureKusto + url_git: https://github.com/Azure/AzureKustohttps://github.com/Azure/AzureR +azuremlsdk: + version: 1.10.0 + title: Interface to the 'Azure Machine Learning' 'SDK' + maintainer: Diondra Peck + description: |- + Interface to the 'Azure Machine Learning' Software Development Kit + ('SDK'). Data scientists can use the 'SDK' to train, deploy, automate, and + manage machine learning models on the 'Azure Machine Learning' service. To + learn more about 'Azure Machine Learning' visit the website: + . + date_publication: '2020-09-22' + bug_reports: https://github.com/azure/azureml-sdk-for-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=azuremlsdk + url_git: https://github.com/azure/azureml-sdk-for-r +AzureQstor: + version: 1.0.1 + title: Interface to 'Azure Queue Storage' + maintainer: Hong Ooi + description: An interface to 'Azure Queue Storage'. This is a cloud service for + storing large numbers of messages, for example from automated sensors, that can + be accessed remotely via authenticated calls using HTTP or HTTPS. Queue storage + is often used to create a backlog of work to process asynchronously. Part of the + 'AzureR' family of packages. + date_publication: '2020-10-15' + bug_reports: https://github.com/Azure/AzureQstor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureQstor + url_git: https://github.com/Azure/AzureQstorhttps://github.com/Azure/AzureR +AzureRMR: + version: 2.4.4 + title: Interface to 'Azure Resource Manager' + maintainer: Hong Ooi + description: A lightweight but powerful R interface to the 'Azure Resource Manager' + REST API. The package exposes a comprehensive class framework and related tools + for creating, updating and deleting 'Azure' resource groups, resources and templates. + While 'AzureRMR' can be used to manage any 'Azure' service, it can also be extended + by other packages to provide extra functionality for specific services. Part of + the 'AzureR' family of packages. + date_publication: '2023-09-21' + bug_reports: https://github.com/Azure/AzureRMR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureRMR + url_git: https://github.com/Azure/AzureRMRhttps://github.com/Azure/AzureR +AzureStor: + version: 3.7.0 + title: Storage Management in 'Azure' + maintainer: Hong Ooi + description: 'Manage storage in Microsoft''s ''Azure'' cloud: . + On the admin side, ''AzureStor'' includes features to create, modify and delete + storage accounts. On the client side, it includes an interface to blob storage, + file storage, and ''Azure Data Lake Storage Gen2'': upload and download files + and blobs; list containers and files/blobs; create containers; and so on. Authenticated + access to storage is supported, via either a shared access key or a shared access + signature (SAS). Part of the ''AzureR'' family of packages.' + date_publication: '2022-05-25' + bug_reports: https://github.com/Azure/AzureStor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureStor + url_git: https://github.com/Azure/AzureStorhttps://github.com/Azure/AzureR +AzureTableStor: + version: 1.0.0 + title: Interface to the Table Storage Service in 'Azure' + maintainer: Hong Ooi + description: 'An interface to the table storage service in ''Azure'': . + Supplies functionality for reading and writing data stored in tables, both as + part of a storage account and from a ''CosmosDB'' database with the table service + API. Part of the ''AzureR'' family of packages.' + date_publication: '2020-11-05' + bug_reports: https://github.com/Azure/AzureTableStor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureTableStor + url_git: https://github.com/Azure/AzureTableStorhttps://github.com/Azure/AzureR +AzureVision: + version: 1.0.2 + title: Interface to Azure Computer Vision Services + maintainer: Hong Ooi + description: An interface to 'Azure Computer Vision' + and 'Azure Custom Vision' , + building on the low-level functionality provided by the 'AzureCognitive' package. + These services allow users to leverage the cloud to carry out visual recognition + tasks using advanced image processing models, without needing powerful hardware + of their own. Part of the 'AzureR' family of packages. + date_publication: '2020-10-17' + bug_reports: https://github.com/Azure/AzureVision/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureVision + url_git: https://github.com/Azure/AzureVisionhttps://github.com/Azure/AzureR +AzureVM: + version: 2.2.2 + title: Virtual Machines in 'Azure' + maintainer: Hong Ooi + description: 'Functionality for working with virtual machines (VMs) in Microsoft''s + ''Azure'' cloud: . + Includes facilities to deploy, startup, shutdown, and cleanly delete VMs and VM + clusters. Deployment configurations can be highly customised, and can make use + of existing resources as well as creating new ones. A selection of predefined + configurations is provided to allow easy deployment of commonly used Linux and + Windows images, including Data Science Virtual Machines. With a running VM, execute + scripts and install optional extensions. Part of the ''AzureR'' family of packages.' + date_publication: '2020-10-14' + bug_reports: https://github.com/Azure/AzureVM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureVM + url_git: https://github.com/Azure/AzureVMhttps://github.com/Azure/AzureR +AzureVMmetadata: + version: 1.0.1 + title: Interface to Azure Virtual Machine Instance Metadata + maintainer: Hong Ooi + description: A simple interface to the instance metadata for a virtual machine running + in Microsoft's 'Azure' cloud. This provides information about the VM's configuration, + such as its processors, memory, networking, storage, and so on. Part of the 'AzureR' + family of packages. + date_publication: '2020-10-14' + bug_reports: https://github.com/Azure/AzureVMmetadata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=AzureVMmetadata + url_git: https://github.com/Azure/AzureVMmetadatahttps://github.com/Azure/AzureR +b64: + version: 0.1.3 + title: Fast and Vectorized Base 64 Engine + maintainer: Josiah Parry + description: |- + Provides a fast, lightweight, and vectorized base 64 engine + to encode and decode character and raw vectors as well as files stored + on disk. Common base 64 alphabets are supported out of the box + including the standard, URL-safe, bcrypt, crypt, 'BinHex', and + IMAP-modified UTF-7 alphabets. Custom engines can be created to + support unique base 64 encoding and decoding needs. + date_publication: '2024-09-26' + bug_reports: https://github.com/extendr/b64/issues + url: https://extendr.github.io/b64/ + url_cran: https://CRAN.R-project.org/package=b64 + url_git: https://github.com/extendr/b64 +babel: + version: 0.3-0 + title: Ribosome Profiling Data Analysis + maintainer: Adam B. Olshen + description: Included here are babel routines for identifying unusual ribosome protected + fragment counts given mRNA counts. + date_publication: '2016-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=babel + url_git: '' +babelgene: + version: '22.9' + title: Gene Orthologs for Model Organisms in a Tidy Data Format + maintainer: Igor Dolgalev + description: |- + Genomic analysis of model organisms frequently requires the + use of databases based on human data or making comparisons to + patient-derived resources. This requires harmonization of gene names + into the same gene space. The 'babelgene' R package converts between + human and non-human gene orthologs/homologs. The package integrates + orthology assertion predictions sourced from multiple databases as + compiled by the HGNC Comparison of Orthology Predictions (HCOP) + (Wright et al. 2005 , Eyre et al. 2007 + , Seal et al. 2011 ). + date_publication: '2022-09-29' + bug_reports: https://github.com/igordot/babelgene/issues + url: https://igordot.github.io/babelgene/ + url_cran: https://CRAN.R-project.org/package=babelgene + url_git: '' +babelmixr2: + version: 0.1.6 + title: |- + Use 'nlmixr2' to Interact with Open Source and Commercial + Software + maintainer: Matthew Fidler + description: |- + Run other estimation and simulation software via the 'nlmixr2' (Fidler et al (2019) + ) interface including 'PKNCA', 'NONMEM' and 'Monolix'. While not required, you can + get/install the 'lixoftConnectors' package in the 'Monolix' installation, as + described at the following url + . When + 'lixoftConnectors' is available, 'Monolix' can be run directly instead of setting up + command line usage. + date_publication: '2025-01-20' + bug_reports: '' + url: https://nlmixr2.github.io/babelmixr2/ + url_cran: https://CRAN.R-project.org/package=babelmixr2 + url_git: https://github.com/nlmixr2/babelmixr2/ +babelwhale: + version: 1.2.0 + title: Talking to 'Docker' and 'Singularity' Containers + maintainer: Robrecht Cannoodt + description: |- + Provides a unified interface to interact with + 'docker' and 'singularity' containers. You can execute a command + inside a container, mount a volume or copy a file. + date_publication: '2023-07-14' + bug_reports: https://github.com/dynverse/babelwhale/issues + url: '' + url_cran: https://CRAN.R-project.org/package=babelwhale + url_git: https://github.com/dynverse/babelwhale +babette: + version: 2.3.4 + title: Control 'BEAST2' + maintainer: Richèl J.C. Bilderbeek + description: |- + 'BEAST2' () is a widely used + Bayesian phylogenetic tool, that uses DNA/RNA/protein data + and many model priors to create a posterior of jointly estimated + phylogenies and parameters. + 'BEAST2' is commonly accompanied by 'BEAUti 2', 'Tracer' and 'DensiTree'. + 'babette' provides for an alternative workflow of using + all these tools separately. This allows doing complex Bayesian + phylogenetics easily and reproducibly from 'R'. + date_publication: '2024-06-25' + bug_reports: https://github.com/ropensci/babette/issues + url: https://docs.ropensci.org/babette/(website) + url_cran: https://CRAN.R-project.org/package=babette + url_git: https://github.com/ropensci/babette +babynames: + version: 1.0.1 + title: US Baby Names 1880-2017 + maintainer: Hadley Wickham + description: |- + US baby names provided by the SSA. This package contains all + names used for at least 5 children of either sex. + date_publication: '2021-04-12' + bug_reports: https://github.com/hadley/babynames/issues + url: '' + url_cran: https://CRAN.R-project.org/package=babynames + url_git: https://github.com/hadley/babynames +babynamesIL: + version: 0.0.2 + title: Israel Baby Names 1948-2022 + maintainer: Aviezer Lifshitz + description: 'Israeli baby names provided by Israel''s Central Bureau of Statistics. + The package contains only names used for at least 5 children in at least one gender + and sector ("Jewish", "Muslim", "Christian", "Druze" and "Other"). Data was downloaded + from: .' + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=babynamesIL + url_git: https://github.com/aviezerl/babynamesIL +babyTimeR: + version: 0.1.0 + title: Parse Output from 'BabyTime' Application + maintainer: Dann Hekman + description: |- + 'BabyTime' is an application for tracking infant and toddler + care activities like sleeping, eating, etc. This package will take the + outputted .zip files and parse it into a usable list object with + cleaned data. It handles malformed and incomplete data gracefully and + is designed to parse one directory at a time. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=babyTimeR + url_git: '' +BACCO: + version: 2.1-0 + title: Bayesian Analysis of Computer Code Output (BACCO) + maintainer: Robin K. S. Hankin + description: |- + The BACCO bundle of packages is replaced by the BACCO + package, which provides a vignette that illustrates the constituent + packages (emulator, approximator, calibrator) in use. + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BACCO + url_git: '' +BACCT: + version: '1.0' + title: Bayesian Augmented Control for Clinical Trials + maintainer: Hongtao Zhang + description: Implements the Bayesian Augmented Control (BAC, a.k.a. Bayesian historical + data borrowing) method under clinical trial setting by calling 'Just Another Gibbs + Sampler' ('JAGS') software. In addition, the 'BACCT' package evaluates user-specified + decision rules by computing the type-I error/power, or probability of correct + go/no-go decision at interim look. The evaluation can be presented numerically + or graphically. Users need to have 'JAGS' 4.0.0 or newer installed due to a compatibility + issue with 'rjags' package. Currently, the package implements the BAC method for + binary outcome only. Support for continuous and survival endpoints will be added + in future releases. We would like to thank AbbVie's Statistical Innovation group + and Clinical Statistics group for their support in developing the 'BACCT' package. + date_publication: '2016-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BACCT + url_git: '' +bacistool: + version: 1.0.0 + title: |- + Bayesian Classification and Information Sharing (BaCIS) Tool for + the Design of Multi-Group Phase II Clinical Trials + maintainer: J. Jack Lee + description: |- + Provides the design of multi-group phase + II clinical trials with binary outcomes using the hierarchical Bayesian + classification and information sharing (BaCIS) model. Subgroups are classified + into two clusters on the basis of their outcomes mimicking the hypothesis + testing framework. Subsequently, information sharing takes place within + subgroups in the same cluster, rather than across all subgroups. This method can + be applied to the design and analysis of multi-group clinical trials with binary + outcomes. Reference: Nan Chen and J. Jack Lee (2019) . + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bacistool + url_git: '' +backbone: + version: 2.1.4 + title: Extracts the Backbone from Graphs + maintainer: Zachary Neal + description: |- + An implementation of methods for extracting an unweighted unipartite + graph (i.e. a backbone) from an unweighted unipartite graph, a weighted unipartite + graph, the projection of an unweighted bipartite graph, or the projection + of a weighted bipartite graph (Neal, 2022 ). + date_publication: '2024-05-09' + bug_reports: https://github.com/zpneal/backbone/issues + url: https://www.zacharyneal.com/backbone + url_cran: https://CRAN.R-project.org/package=backbone + url_git: https://github.com/zpneal/backbone +backpipe: + version: 0.2.3 + title: Backward Pipe (Right-to-Left) Operator + maintainer: Christopher Brown + description: |- + Provides a backward-pipe operator for 'magrittr' (%<%) or + 'pipeR' (%<<%) that allows for a performing operations from right-to-left. + This allows writing more legible code where right-to-left ordering is + natural. This is common with hierarchies and nested structures such as + trees, directories or markup languages (e.g. HTML and XML). + The package also includes a R-Studio add-in that can be bound to a keyboard + shortcut. + date_publication: '2018-06-26' + bug_reports: https://github.com/decisionpatterns/backpipe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=backpipe + url_git: https://github.com/decisionpatterns/backpipe +backports: + version: 1.5.0 + title: Reimplementations of Functions Introduced Since R-3.0.0 + maintainer: Michel Lang + description: |- + Functions introduced or changed since R v3.0.0 are re-implemented in this + package. The backports are conditionally exported in order to let R resolve + the function name to either the implemented backport, or the respective base + version, if available. Package developers can make use of new functions or + arguments by selectively importing specific backports to + support older installations. + date_publication: '2024-05-23' + bug_reports: https://github.com/r-lib/backports/issues + url: '' + url_cran: https://CRAN.R-project.org/package=backports + url_git: https://github.com/r-lib/backports +backShift: + version: 0.1.4.3 + title: Learning Causal Cyclic Graphs from Unknown Shift Interventions + maintainer: Christina Heinze-Deml + description: |- + Code for 'backShift', an algorithm to estimate the connectivity + matrix of a directed (possibly cyclic) graph with hidden variables. The + underlying system is required to be linear and we assume that observations + under different shift interventions are available. For more details, + see . + date_publication: '2020-05-06' + bug_reports: https://github.com/christinaheinze/backShift/issues + url: '' + url_cran: https://CRAN.R-project.org/package=backShift + url_git: https://github.com/christinaheinze/backShift +backtest: + version: 0.3-4 + title: |- + Exploring Portfolio-Based Conjectures About Financial + Instruments + maintainer: Daniel Gerlanc + description: |- + The backtest package provides facilities for exploring + portfolio-based conjectures about financial instruments + (stocks, bonds, swaps, options, et cetera). + date_publication: '2015-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=backtest + url_git: '' +backtestGraphics: + version: 0.1.8 + title: Interactive Graphics for Portfolio Data + maintainer: Yanrong Song + description: |- + Creates an interactive graphics + interface to visualize backtest results of different financial + instruments, such as equities, futures, and credit default swaps. + The package does not run backtests on the given data set but + displays a graphical explanation of the backtest results. Users can + look at backtest graphics for different instruments, investment + strategies, and portfolios. Summary statistics of different + portfolio holdings are shown in the left panel, and interactive + plots of profit and loss (P&L), net market value (NMV) and + gross market value (GMV) are displayed in the right panel. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=backtestGraphics + url_git: '' +baclava: + version: '1.0' + title: |- + Bayesian Analysis of Cancer Latency with Auxiliary Variable + Augmentation + maintainer: Shannon T. Holloway + description: |- + A novel data-augmentation Markov chain Monte Carlo sampling algorithm to fit a progressive compartmental model of disease in a Bayesian framework + Morsomme, R.N., Holloway, S.T., Ryser, M.D. and Xu J. (2024) . + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=baclava + url_git: '' +bacondecomp: + version: 0.1.1 + title: Goodman-Bacon Decomposition + maintainer: Evan Flack + description: |- + Decomposition for differences-in-differences with variation in + treatment timing from Goodman-Bacon (2018) . + date_publication: '2020-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bacondecomp + url_git: '' +BACprior: + version: 2.1.1 + title: Choice of Omega in the BAC Algorithm + maintainer: Denis Talbot + description: |- + The Bayesian Adjustment for Confounding (BAC) algorithm (Wang et al., 2012) + can be used to estimate the causal effect of a continuous exposure on a continuous outcome. + This package provides an approximate sensitivity analysis of BAC with regards to the + hyperparameter omega. BACprior also provides functions to guide the user in their choice + of an appropriate omega value. The method is based on Lefebvre, Atherton and Talbot (2014). + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BACprior + url_git: '' +bacr: + version: 1.0.1 + title: Bayesian Adjustment for Confounding + maintainer: Chi Wang + description: Estimating the average causal effect based on the Bayesian Adjustment + for Confounding (BAC) algorithm. + date_publication: '2016-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bacr + url_git: '' +badgen: + version: 1.0.1 + title: Fast and Simple Badge Generator + maintainer: Jeroen Ooms + description: |- + Bindings to 'badgen' to + generate beautiful 'svg' badges in R without internet access. Images can + be converted to 'png' using the 'rsvg' package as shown in examples. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/badgen/issues + url: https://jeroen.r-universe.dev/badgen + url_cran: https://CRAN.R-project.org/package=badgen + url_git: '' +badger: + version: 0.2.4 + title: Badge for R Package + maintainer: Guangchuang Yu + description: Query information and generate badge for using in README and GitHub + Pages. + date_publication: '2024-06-08' + bug_reports: https://github.com/GuangchuangYu/badger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=badger + url_git: https://github.com/GuangchuangYu/badger +baf: + version: 0.0.1 + title: Block Assignment Files + maintainer: Christopher T. Kenny + description: |- + Download and read US Census Bureau data relationship files. Provides + support for cleaning and using block assignment files since 2010, as described in + . + Also includes support for working with block equivalency files, used for years + outside of decennial census years. + date_publication: '2024-06-04' + bug_reports: '' + url: http://christophertkenny.com/baf/ + url_cran: https://CRAN.R-project.org/package=baf + url_git: https://github.com/christopherkenny/baf +baffle: + version: 0.2.2 + title: Make Waffle Plots with Base Graphics + maintainer: Jiří Moravec + description: |- + Waffle plots are rectangular pie charts that represent a quantity or abundances using + colored squares or other symbol. This makes them better at transmitting information as the + discrete number of squares is easier to read than the circular area of pie charts. + While the original waffle charts were rectangular with 10 rows and columns, with a single square + representing 1%, they are nowadays popular in various infographics to visualize any + proportional ratios. + date_publication: '2023-08-25' + bug_reports: https://github.com/j-moravec/baffle/issues + url: https://j-moravec.github.io/baffle/ + url_cran: https://CRAN.R-project.org/package=baffle + url_git: https://github.com/j-moravec/baffle +bage: + version: 0.9.0 + title: Bayesian Estimation and Forecasting of Age-Specific Rates + maintainer: John Bryant + description: |- + Fast Bayesian estimation and forecasting of age-specific + rates, probabilities, and means, based on 'Template Model Builder'. + date_publication: '2025-01-08' + bug_reports: https://github.com/bayesiandemography/bage/issues + url: https://bayesiandemography.github.io/bage/ + url_cran: https://CRAN.R-project.org/package=bage + url_git: https://github.com/bayesiandemography/bage +bagged.outliertrees: + version: 1.0.0 + title: Robust Explainable Outlier Detection Based on OutlierTree + maintainer: Rafael Santos + description: Bagged OutlierTrees is an explainable unsupervised outlier detection + method based on an ensemble implementation of the existing OutlierTree procedure + (Cortes, 2020). This implementation takes advantage of bootstrap aggregating (bagging) + to improve robustness by reducing the possible masking effect and subsequent high + variance (similarly to Isolation Forest), hence the name "Bagged OutlierTrees". + To learn more about the base procedure OutlierTree (Cortes, 2020), please refer + to . + date_publication: '2021-07-06' + bug_reports: https://github.com/RafaJPSantos/bagged.outliertrees/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bagged.outliertrees + url_git: https://github.com/RafaJPSantos/bagged.outliertrees +baggingbwsel: + version: '1.1' + title: |- + Bagging Bandwidth Selection in Kernel Density and Regression + Estimation + maintainer: Ruben Fernandez-Casal + description: |- + Bagging bandwidth selection methods for the Parzen-Rosenblatt and Nadaraya-Watson estimators. These + bandwidth selectors can achieve greater statistical precision than their non-bagged counterparts while being + computationally fast. See Barreiro-Ures et al. (2020) and + Barreiro-Ures et al. (2021) . + date_publication: '2024-07-27' + bug_reports: https://github.com/rubenfcasal/baggingbwsel/issues/ + url: https://rubenfcasal.github.io/baggingbwsel/ + url_cran: https://CRAN.R-project.org/package=baggingbwsel + url_git: https://github.com/rubenfcasal/baggingbwsel/ +baggr: + version: 0.7.8 + title: Bayesian Aggregate Treatment Effects + maintainer: Witold Wiecek + description: |- + Running and comparing meta-analyses of data with hierarchical + Bayesian models in Stan, including convenience functions for formatting + data, plotting and pooling measures specific to meta-analysis. This implements many models + from Meager (2019) . + date_publication: '2024-02-12' + bug_reports: https://github.com/wwiecek/baggr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=baggr + url_git: https://github.com/wwiecek/baggr +BAGofT: + version: 1.0.0 + title: A Binary Regression Adaptive Goodness-of-Fit Test (BAGofT) + maintainer: Jiawei Zhang + description: The BAGofT assesses the goodness-of-fit of binary classifiers. Details + can be found in Zhang, Ding and Yang (2021) . + date_publication: '2021-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BAGofT + url_git: '' +baguette: + version: 1.1.0 + title: Efficient Model Functions for Bagging + maintainer: Max Kuhn + description: |- + Tree- and rule-based models can be bagged + () using this package and their predictions + equations are stored in an efficient format to reduce the model + objects size and speed. + date_publication: '2025-01-28' + bug_reports: https://github.com/tidymodels/baguette/issues + url: https://baguette.tidymodels.org + url_cran: https://CRAN.R-project.org/package=baguette + url_git: https://github.com/tidymodels/baguette +bagyo: + version: 0.1.1 + title: Philippine Tropical Cyclones Data + maintainer: Ernest Guevarra + description: |- + The Philippines frequently experiences tropical cyclones (called + 'bagyo' in the Filipino language) because of its geographical position. + These cyclones typically bring heavy rainfall, leading to widespread + flooding, as well as strong winds that cause significant damage to human + life, crops, and property. Data on cyclones are collected and curated by the + Philippine Atmospheric, Geophysical, and Astronomical Services + Administration or 'PAGASA' and made available through its website + . + This package contains Philippine tropical cyclones data in a + machine-readable format. It is hoped that this data package provides an + interesting and unique dataset for data exploration and visualisation. + date_publication: '2024-04-18' + bug_reports: https://github.com/panukatan/bagyo/issues + url: https://panukatan.io/bagyo/ + url_cran: https://CRAN.R-project.org/package=bagyo + url_git: https://github.com/panukatan/bagyo +bahc: + version: 0.3.0 + title: |- + Filter Covariance and Correlation Matrices with + Bootstrapped-Averaged Hierarchical Ansatz + maintainer: Damien Challet + description: |- + A method to filter correlation and covariance matrices by averaging + bootstrapped filtered hierarchical clustering and boosting. See Ch. Bongiorno and D. Challet, + Covariance matrix filtering with bootstrapped hierarchies (2020) and + Ch. Bongiorno and D. Challet, Reactive Global Minimum Variance Portfolios with k-BAHC covariance cleaning + (2020) . + date_publication: '2020-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bahc + url_git: '' +BaHZING: + version: 1.0.0 + title: |- + Bayesian Hierarchical Zero-Inflated Negative Binomial Regression + with G-Computation + maintainer: Jesse Goodrich + description: |- + A Bayesian model for examining the association between + environmental mixtures and all Taxa measured in a hierarchical + microbiome dataset in a single integrated analysis. Compared with + analyzing the associations of environmental mixtures with each Taxa + individually, 'BaHZING' controls Type 1 error rates and provides more + stable effect estimates when dealing with small sample sizes. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BaHZING + url_git: '' +bain: + version: 0.2.11 + title: Bayes Factors for Informative Hypotheses + maintainer: Caspar J van Lissa + description: |- + Computes approximated adjusted fractional Bayes factors for + equality, inequality, and about equality constrained hypotheses. + For a tutorial on this method, see Hoijtink, Mulder, van Lissa, & Gu, + (2019) . For applications in structural equation + modeling, see: Van Lissa, Gu, Mulder, Rosseel, Van Zundert, & + Hoijtink, (2021) . For the statistical + underpinnings, see Gu, Mulder, and Hoijtink (2018) ; + Hoijtink, Gu, & Mulder, J. (2019) ; Hoijtink, Gu, + Mulder, & Rosseel, (2019) . + date_publication: '2024-06-12' + bug_reports: https://github.com/cjvanlissa/bain/ + url: https://informative-hypotheses.sites.uu.nl/software/bain/ + url_cran: https://CRAN.R-project.org/package=bain + url_git: '' +baizer: + version: 0.8.0 + title: Useful Functions for Data Processing + maintainer: William Song + description: |- + In ancient Chinese mythology, Bai Ze is a divine creature that knows the needs of everything. + 'baizer' provides data processing functions frequently used by the author. + Hope this package also knows what you want! + date_publication: '2023-10-19' + bug_reports: https://github.com/william-swl/baizer/issues + url: https://william-swl.github.io/baizer/ + url_cran: https://CRAN.R-project.org/package=baizer + url_git: https://github.com/william-swl/baizer +bakeoff: + version: 0.2.0 + title: Data from "The Great British Bake Off" + maintainer: Alison Hill + description: |- + Data about the bakers, challenges, and ratings + for "The Great British Bake Off", + from Wikipedia . + date_publication: '2022-10-21' + bug_reports: https://github.com/apreshill/bakeoff/issues + url: https://bakeoff.netlify.app/ + url_cran: https://CRAN.R-project.org/package=bakeoff + url_git: https://github.com/apreshill/bakeoff +baker: + version: 1.0.3 + title: '"Nested Partially Latent Class Models"' + maintainer: Zhenke Wu + description: |- + Provides functions to specify, fit and visualize + nested partially-latent class models ( + Wu, Deloria-Knoll, Hammitt, and Zeger (2016) ; + Wu, Deloria-Knoll, and Zeger (2017) ; + Wu and Chen (2021) ) for + inference of population disease etiology and individual diagnosis. In the motivating + Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities + of interest sum to one hundred percent, the PERCH scientists frequently refer to + them as population etiology pie and individual etiology pie, hence the name of the package. + date_publication: '2024-01-30' + bug_reports: https://github.com/zhenkewu/baker/issues + url: https://zhenkewu.com/baker/ + url_cran: https://CRAN.R-project.org/package=baker + url_git: https://github.com/zhenkewu/baker +bakR: + version: 1.0.1 + title: Analyze and Compare Nucleotide Recoding RNA Sequencing Datasets + maintainer: Isaac Vock + description: |- + Several implementations of a novel Bayesian hierarchical statistical model of nucleotide + recoding RNA-seq experiments (NR-seq; TimeLapse-seq, SLAM-seq, TUC-seq, etc.) + for analyzing and comparing NR-seq datasets (see 'Vock and Simon' (2023) ). + NR-seq is a powerful extension of RNA-seq that provides information about the kinetics + of RNA metabolism (e.g., RNA degradation rate constants), which is notably lacking + in standard RNA-seq data. The statistical model makes maximal use of these high-throughput + datasets by sharing information across transcripts to significantly improve + uncertainty quantification and increase statistical power. 'bakR' includes a maximally + efficient implementation of this model for conservative initial investigations of datasets. 'bakR' + also provides more highly powered implementations using the probabilistic programming language + 'Stan' to sample from the full posterior distribution. 'bakR' performs multiple-test + adjusted statistical inference with the output of these model implementations to + help biologists separate signal from background. Methods to automatically visualize key + results and detect batch effects are also provided. + date_publication: '2024-01-13' + bug_reports: https://github.com/simonlabcode/bakR/issues/ + url: https://simonlabcode.github.io/bakR/ + url_cran: https://CRAN.R-project.org/package=bakR + url_git: '' +BalanceCheck: + version: '0.2' + title: |- + Balance Check for Multiple Covariates in Matched Observational + Studies + maintainer: Hao Chen + description: Two practical tests are provided for assessing whether multiple covariates + in a treatment group and a matched control group are balanced in observational + studies. + date_publication: '2019-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BalanceCheck + url_git: '' +BalancedSampling: + version: 2.1.1 + title: Balanced and Spatially Balanced Sampling + maintainer: Anton Grafström + description: |- + Select balanced and spatially balanced probability samples in multi-dimensional spaces + with any prescribed inclusion probabilities. It contains fast (C++ via Rcpp) implementations of + the included sampling methods. The local pivotal method by Grafström, Lundström and Schelin (2012) + and spatially correlated Poisson sampling by Grafström (2012) + are included. Also the cube method (for balanced sampling) and + the local cube method (for doubly balanced sampling) are included, see Grafström and Tillé (2013) + . + date_publication: '2024-11-18' + bug_reports: '' + url: https://www.envisim.se/ + url_cran: https://CRAN.R-project.org/package=BalancedSampling + url_git: https://github.com/envisim/BalancedSampling/ +baldur: + version: 0.0.3 + title: Bayesian Hierarchical Modeling for Label-Free Proteomics + maintainer: Philip Berg + description: |- + Statistical decision in proteomics data using a hierarchical + Bayesian model. There are two regression models for describing the + mean-variance trend, a gamma regression or a latent gamma mixture + regression. The regression model is then used as an Empirical Bayes + estimator for the prior on the variance in a peptide. Further, it assumes + that each measurement has an uncertainty (increased variance) associated + with it that is also inferred. Finally, it tries to estimate the posterior + distribution (by Hamiltonian Monte Carlo) for the differences in means for + each peptide in the data. Once the posterior is inferred, it integrates the + tails to estimate the probability of error from which a statistical decision + can be made. + See Berg and Popescu for details (). + date_publication: '2023-09-18' + bug_reports: https://github.com/PhilipBerg/baldur/issues + url: '' + url_cran: https://CRAN.R-project.org/package=baldur + url_git: https://github.com/PhilipBerg/baldur +Ball: + version: 1.3.13 + title: |- + Statistical Inference and Sure Independence Screening via Ball + Statistics + maintainer: Jin Zhu + description: 'Hypothesis tests and sure independence screening (SIS) procedure based + on ball statistics, including ball divergence , ball covariance + , and ball correlation , + are developed to analyze complex data in metric spaces, e.g, shape, directional, + compositional and symmetric positive definite matrix data. The ball divergence + and ball covariance based distribution-free tests are implemented to detecting + distribution difference and association in metric spaces . + Furthermore, several generic non-parametric feature selection procedures based + on ball correlation, BCor-SIS and all of its variants, are implemented to tackle + the challenge in the context of ultra high dimensional data. A fast implementation + for large-scale multiple K-sample testing with ball divergence + is supported, which is particularly helpful for genome-wide association study.' + date_publication: '2023-02-12' + bug_reports: https://github.com/Mamba413/Ball/issues + url: https://mamba413.github.io/Ball/ + url_cran: https://CRAN.R-project.org/package=Ball + url_git: https://github.com/Mamba413/Ball +BALLI: + version: 0.2.0 + title: Expression RNA-Seq Data Analysis Based on Linear Mixed Model + maintainer: Kyungtaek Park + description: Analysis of gene expression RNA-seq data using Bartlett-Adjusted Likelihood-based + LInear model (BALLI). Based on likelihood ratio test, it provides comparisons + for effect of one or more variables. See Kyungtaek Park (2018) + for more information. + date_publication: '2019-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BALLI + url_git: '' +BallMapper: + version: 0.2.0 + title: The Ball Mapper Algorithm + maintainer: Pawel Dlotko + description: 'The core algorithm is described in "Ball mapper: a shape summary for + topological data analysis" by Pawel Dlotko, (2019) . Please + consult the following youtube video + the idea of functionality. Ball Mapper provide a topologically accurate summary + of a data in a form of an abstract graph. To create it, please provide the coordinates + of points (in the points array), values of a function of interest at those points + (can be initialized randomly if you do not have it) and the value epsilon which + is the radius of the ball in the Ball Mapper construction. It can be understood + as the minimal resolution on which we use to create the model of the data.' + date_publication: '2019-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BallMapper + url_git: '' +BaM: + version: 1.0.3 + title: |- + Functions and Datasets for "Bayesian Methods: A Social and + Behavioral Sciences Approach" + maintainer: Jeff Gill + description: 'Functions and datasets for Jeff Gill: "Bayesian Methods: A Social + and Behavioral Sciences Approach". First, Second, and Third Edition. Published + by Chapman and Hall/CRC (2002, 2007, 2014) .' + date_publication: '2022-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BaM + url_git: '' +bama: + version: 1.3.0 + title: High Dimensional Bayesian Mediation Analysis + maintainer: Mike Kleinsasser + description: |- + Perform mediation analysis in the presence of high-dimensional + mediators based on the potential outcome framework. Bayesian Mediation + Analysis (BAMA), developed by Song et al (2019) and + Song et al (2020) , + relies on two Bayesian sparse linear mixed models to simultaneously analyze + a relatively large number of mediators for a continuous exposure and outcome + assuming a small number of mediators are truly active. This sparsity + assumption also allows the extension of univariate mediator analysis by + casting the identification of active mediators as a variable selection + problem and applying Bayesian methods with continuous shrinkage priors on + the effects. + date_publication: '2023-01-24' + bug_reports: https://github.com/umich-cphds/bama/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bama + url_git: https://github.com/umich-cphds/bama +BAMBI: + version: 2.3.6 + title: Bivariate Angular Mixture Models + maintainer: Saptarshi Chakraborty + description: Fit (using Bayesian methods) and simulate mixtures of univariate and + bivariate angular distributions. Chakraborty and Wong (2021) . + date_publication: '2024-10-25' + bug_reports: https://github.com/c7rishi/BAMBI/issues + url: https://doi.org/10.18637/jss.v099.i11 + url_cran: https://CRAN.R-project.org/package=BAMBI + url_git: '' +bambooHR: + version: 0.1.1 + title: A Wrapper to the 'BambooHR' API + maintainer: Tom Bowling + description: |- + Enables a user to consume the 'BambooHR' API endpoints using R. The + actual URL of the API will depend on your company domain, and will be handled + by the package automatically once you setup the config file. The API documentation + can be found here . + date_publication: '2023-10-25' + bug_reports: https://github.com/MangoTheCat/bambooHR/issues + url: https://mangothecat.github.io/bambooHR/ + url_cran: https://CRAN.R-project.org/package=bambooHR + url_git: '' +bamdit: + version: 3.4.4 + title: Bayesian Meta-Analysis of Diagnostic Test Data + maintainer: Pablo Emilio Verde + description: Provides a new class of Bayesian meta-analysis models that incorporates + a model for internal and external validity bias. In this way, it is possible to + combine studies of diverse quality and different types. For example, we can combine + the results of randomized control trials (RCTs) with the results of observational + studies (OS). + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bamdit + url_git: '' +bamlss: + version: 1.2-5 + title: |- + Bayesian Additive Models for Location, Scale, and Shape (and + Beyond) + maintainer: Nikolaus Umlauf + description: |- + Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework. + The distribution parameters may capture location, scale, shape, etc. and every parameter may depend + on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. + The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2019) + and the R package in Umlauf, Klein, Simon, Zeileis (2021) + . + date_publication: '2024-10-11' + bug_reports: '' + url: http://www.bamlss.org/ + url_cran: https://CRAN.R-project.org/package=bamlss + url_git: '' +bamm: + version: 0.5.0 + title: |- + Species Distribution Models as a Function of Biotic, Abiotic and + Movement Factors (BAM) + maintainer: Luis Osorio-Olvera + description: |- + Species Distribution Modeling (SDM) is a practical + methodology that aims to estimate the area of distribution of a + species. However, most of the work has focused on estimating static + expressions of the correlation between environmental variables. The + outputs of correlative species distribution models can be interpreted + as maps of the suitable environment for a species but not generally as + maps of its actual distribution. Soberón and Peterson (2005) + presented the BAM scheme, a heuristic + framework that states that the occupied area of a species occurs on + sites that have been accessible through dispersal (M) and have both + favorable biotic (B) and abiotic conditions (A). The 'bamm' package + implements classes and functions to operate on each element of the BAM + and by using a cellular automata model where the occupied area of a + species at time t is estimated by the multiplication of three binary + matrices: one matrix represents movements (M), another abiotic -niche- + tolerances (A), and a third, biotic interactions (B). The theoretical + background of the package can be found in Soberón and Osorio-Olvera + (2023) . + date_publication: '2024-07-06' + bug_reports: https://github.com/luismurao/bamm/issues + url: https://luismurao.github.io/bamm/ + url_cran: https://CRAN.R-project.org/package=bamm + url_git: '' +BAMMtools: + version: 2.1.12 + title: |- + Analysis and Visualization of Macroevolutionary Dynamics on + Phylogenetic Trees + maintainer: Pascal Title + description: |- + Provides functions for analyzing and visualizing complex + macroevolutionary dynamics on phylogenetic trees. It is a companion + package to the command line program BAMM (Bayesian Analysis of + Macroevolutionary Mixtures) and is entirely oriented towards the analysis, + interpretation, and visualization of evolutionary rates. Functionality + includes visualization of rate shifts on phylogenies, estimating + evolutionary rates through time, comparing posterior distributions of + evolutionary rates across clades, comparing diversification models using + Bayes factors, and more. + date_publication: '2024-09-12' + bug_reports: '' + url: http://bamm-project.org/ + url_cran: https://CRAN.R-project.org/package=BAMMtools + url_git: '' +bamp: + version: 2.1.3 + title: Bayesian Age-Period-Cohort Modeling and Prediction + maintainer: Volker Schmid + description: Bayesian Age-Period-Cohort Modeling and Prediction using efficient + Markov Chain Monte Carlo Methods. This is the R version of the previous BAMP software + as described in Volker Schmid and Leonhard Held (2007) + Bayesian Age-Period-Cohort Modeling and Prediction - BAMP, Journal of Statistical + Software 21:8. This package includes checks of convergence using Gelman's R. + date_publication: '2022-10-18' + bug_reports: https://github.com/volkerschmid/bamp/issues + url: https://volkerschmid.github.io/bamp/ + url_cran: https://CRAN.R-project.org/package=bamp + url_git: '' +BANAM: + version: 0.2.2 + title: Bayesian Analysis of the Network Autocorrelation Model + maintainer: Joris Mulder + description: |- + The network autocorrelation model (NAM) can be used for studying the degree of social influence + regarding an outcome variable based on one or more known networks. + The degree of social influence is quantified via the network autocorrelation parameters. In case of a single + network, the Bayesian methods of Dittrich, Leenders, and Mulder + (2017) and Dittrich, Leenders, and Mulder (2019) + are implemented using a normal, flat, or independence + Jeffreys prior for the network autocorrelation. In the case of multiple + networks, the Bayesian methods of Dittrich, Leenders, and Mulder (2020) + are implemented using a multivariate normal prior for + the network autocorrelation parameters. Flat priors are implemented + for estimating the coefficients. For Bayesian testing of equality and order-constrained + hypotheses, the default Bayes factor of Gu, Mulder, and Hoijtink, (2018) + is used with the posterior mean and posterior covariance + matrix of the NAM parameters based on flat priors as input. + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BANAM + url_git: '' +bandicoot: + version: 1.0.0 + title: Light-Weight 'python'-Like Object-Oriented System + maintainer: Weihao Li + description: A light-weight object-oriented system with 'python'-like syntax which + supports multiple inheritances and incorporates a 'python'-like method resolution + order. + date_publication: '2024-03-09' + bug_reports: https://github.com/TengMCing/bandicoot/issues + url: https://tengmcing.github.io/bandicoot/ + url_cran: https://CRAN.R-project.org/package=bandicoot + url_git: https://github.com/TengMCing/bandicoot/ +bandit: + version: 0.5.1 + title: |- + Functions for Simple a/B Split Test and Multi-Armed Bandit + Analysis + maintainer: Markus Loecher + description: A set of functions for doing analysis of A/B split test data and web + metrics in general. + date_publication: '2022-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bandit + url_git: '' +banditpam: + version: 1.0-1 + title: Almost Linear-Time k-Medoids Clustering + maintainer: Balasubramanian Narasimhan + description: 'Interface to a high-performance implementation of k-medoids clustering + described in Tiwari, Zhang, Mayclin, Thrun, Piech and Shomorony (2020) "BanditPAM: + Almost Linear Time k-medoids Clustering via Multi-Armed Bandits" .' + date_publication: '2023-03-15' + bug_reports: https://github.com/motiwari/BanditPAM + url: '' + url_cran: https://CRAN.R-project.org/package=banditpam + url_git: '' +banditsCI: + version: 1.0.0 + title: Bandit-Based Experiments and Policy Evaluation + maintainer: Molly Offer-Westort + description: Frequentist inference on adaptively generated data. The methods implemented + are based on Zhan et al. (2021) and Hadad et al. + (2021) . For illustration, several functions for + simulating non-contextual and contextual adaptive experiments using Thompson sampling + are also supplied. + date_publication: '2024-11-29' + bug_reports: https://github.com/UChicago-pol-methods/banditsCI/issues + url: https://uchicago-pol-methods.github.io/banditsCI/ + url_cran: https://CRAN.R-project.org/package=banditsCI + url_git: https://github.com/UChicago-pol-methods/banditsCI +bandsfdp: + version: 1.1.0 + title: |- + Compute Upper Prediction Bounds on the FDP in Competition-Based + Setups + maintainer: Arya Ebadi + description: |- + Implements functions that calculate upper prediction + bounds on the false discovery proportion (FDP) in the list of discoveries + returned by competition-based setups, implementing Ebadi et al. (2022) + . Such setups include target-decoy competition (TDC) + in computational mass spectrometry and the knockoff construction in linear + regression (note this package typically uses the terminology of TDC). Included + is the standardized (TDC-SB) and uniform (TDC-UB) bound on TDC's FDP, and the + simultaneous standardized and uniform bands. Requires + pre-computed Monte Carlo statistics available at + . This data can be downloaded by + running the command 'devtools::install_github("uni-Arya/fdpbandsdata")' in R + and restarting R after installation. The size of this data is roughly 81Mb. + date_publication: '2023-05-12' + bug_reports: https://github.com/uni-Arya/bandsfdp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bandsfdp + url_git: https://github.com/uni-Arya/bandsfdp +banffIT: + version: 1.0.0 + title: |- + Automatize Diagnosis Standardized Assignation Using the Banff + Classification + maintainer: Guillaume Fabre + description: |- + Assigns standardized diagnoses using the Banff Classification + (Category 1 to 6 diagnoses, including Acute and Chronic active T-cell + mediated rejection as well as Active, Chronic active, and Chronic antibody + mediated rejection). The main function considers a minimal dataset + containing biopsies information in a specific format (described by a data + dictionary), verifies its content and format (based on the data dictionary), + assigns diagnoses, and creates a summary report. The package is developed on + the reference guide to the Banff classification of renal allograft pathology + Roufosse C, Simmonds N, Clahsen-van Groningen M, et al. A (2018) . + The full description of the Banff classification is available at . + date_publication: '2024-05-08' + bug_reports: https://github.com/PersonalizedTransplantCare/banffIT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=banffIT + url_git: https://github.com/PersonalizedTransplantCare/banffIT +bang: + version: 1.0.4 + title: Bayesian Analysis, No Gibbs + maintainer: Paul J. Northrop + description: |- + Provides functions for the Bayesian analysis of some simple + commonly-used models, without using Markov Chain Monte Carlo (MCMC) + methods such as Gibbs sampling. The 'rust' package + is used to simulate a random + sample from the required posterior distribution, using the generalized + ratio-of-uniforms method. See Wakefield, Gelfand and Smith (1991) + for details. At the moment three conjugate + hierarchical models are available: beta-binomial, gamma-Poisson and a 1-way + analysis of variance (ANOVA). + date_publication: '2024-07-17' + bug_reports: https://github.com/paulnorthrop/bang/issues + url: https://paulnorthrop.github.io/bang/ + url_cran: https://CRAN.R-project.org/package=bang + url_git: https://github.com/paulnorthrop/bang +bangladesh: + version: 1.0.0 + title: |- + Provides Ready to Use Shapefiles for Geographical Map of + Bangladesh + maintainer: Musaddiqur Rahman Ovi + description: |- + Usually, it is difficult to plot choropleth maps for Bangladesh in 'R'. + The 'bangladesh' package provides ready-to-use shapefiles for different administrative + regions of Bangladesh (e.g., Division, District, Upazila, and Union). + This package helps users to draw thematic maps of administrative regions + of Bangladesh easily as it comes with the 'sf' objects for the boundaries. + It also provides functions allowing users to efficiently get specific area + maps and center coordinates for regions. Users can also search for + a specific area and calculate the centroids of those areas. + date_publication: '2022-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bangladesh + url_git: '' +bannerCommenter: + version: 1.0.0 + title: Make Banner Comments with a Consistent Format + maintainer: Bill Venables + description: |- + A convenience package for use while drafting code. + It facilitates making stand-out comment lines decorated with + bands of characters. The input text strings are converted into + R comment lines, suitably formatted. These are then displayed in + a console window and, if possible, automatically transferred to a + clipboard ready for pasting into an R script. Designed to save + time when drafting R scripts that will need to be navigated and + maintained by other programmers. + date_publication: '2021-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bannerCommenter + url_git: '' +BANOVA: + version: 1.2.1 + title: Hierarchical Bayesian ANOVA Models + maintainer: Chen Dong + description: 'It covers several Bayesian Analysis of Variance (BANOVA) models used + in analysis of experimental designs in which both within- and between- subjects + factors are manipulated. They can be applied to data that are common in the behavioral + and social sciences. The package includes: Hierarchical Bayes ANOVA models with + normal response, t response, Binomial (Bernoulli) response, Poisson response, + ordered multinomial response and multinomial response variables. All models accommodate + unobserved heterogeneity by including a normal distribution of the parameters + across individuals. Outputs of the package include tables of sums of squares, + effect sizes and p-values, and tables of predictions, which are easily interpretable + for behavioral and social researchers. The floodlight analysis and mediation analysis + based on these models are also provided. BANOVA uses ''Stan'' and ''JAGS'' as + the computational platform. References: Dong and Wedel (2017) ; + Wedel and Dong (2020) .' + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BANOVA + url_git: '' +banter: + version: 0.9.6 + title: BioAcoustic eveNT classifiER + maintainer: Eric Archer + description: |- + Create a hierarchical acoustic event species classifier out of + multiple call type detectors as described in + Rankin et al (2017) . + date_publication: '2023-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=banter + url_git: '' +banxicoR: + version: 0.9.0 + title: Download Data from the Bank of Mexico + maintainer: Eduardo Flores + description: |- + Provides functions to scrape IQY calls to Bank of Mexico, + downloading and ordering the data conveniently. + date_publication: '2016-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=banxicoR + url_git: '' +baorista: + version: 0.2.1 + title: Bayesian Aoristic Analyses + maintainer: Enrico Crema + description: Provides an alternative approach to aoristic analyses for archaeological + datasets by fitting Bayesian parametric growth models and non-parametric random-walk + Intrinsic Conditional Autoregressive (ICAR) models on time frequency data (Crema + (2024)). It handles event typo-chronology based timespans + defined by start/end date as well as more complex user-provided vector of probabilities. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=baorista + url_git: '' +bapred: + version: '1.1' + title: |- + Batch Effect Removal and Addon Normalization (in Phenotype + Prediction using Gene Data) + maintainer: Roman Hornung + description: |- + Various tools dealing with batch effects, in particular enabling the + removal of discrepancies between training and test sets in prediction scenarios. + Moreover, addon quantile normalization and addon RMA normalization (Kostka & Spang, + 2008) is implemented to enable integrating the quantile normalization step into + prediction rules. The following batch effect removal methods are implemented: + FAbatch, ComBat, (f)SVA, mean-centering, standardization, Ratio-A and Ratio-G. + For each of these we provide an additional function which enables a posteriori + ('addon') batch effect removal in independent batches ('test data'). Here, the + (already batch effect adjusted) training data is not altered. For evaluating the + success of batch effect adjustment several metrics are provided. Moreover, the + package implements a plot for the visualization of batch effects using principal + component analysis. The main functions of the package for batch effect adjustment + are ba() and baaddon() which enable batch effect removal and addon batch effect + removal, respectively, with one of the seven methods mentioned above. Another + important function here is bametric() which is a wrapper function for all implemented + methods for evaluating the success of batch effect removal. For (addon) quantile + normalization and (addon) RMA normalization the functions qunormtrain(), + qunormaddon(), rmatrain() and rmaaddon() can be used. + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bapred + url_git: '' +BAR: + version: 0.1.1 + title: Bayesian Adaptive Randomization + maintainer: Chia-Wei Hsu + description: Bayesian adaptive randomization is also called outcome adaptive randomization, + which is increasingly used in clinical trials. + date_publication: '2022-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BAR + url_git: '' +BarBorGradient: + version: 1.0.5 + title: Function Minimum Approximator + maintainer: János Hevner + description: |- + Tool to find where a function has its lowest value(minimum). The + functions can be any dimensions. Recommended use is with eps=10^-10, but can be + run with 10^-20, although this depends on the function. Two more methods are in + this package, simple gradient method (Gradmod) and Powell method (Powell). These + are not recommended for use, their purpose are purely for comparison. + date_publication: '2017-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BarBorGradient + url_git: '' +barcode: + version: 1.3.0 + title: Render Barcode Distribution Plots + maintainer: John W. Emerson + description: |- + The function \code{barcode()} + produces a histogram-like plot of a distribution that shows + granularity in the data. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=barcode + url_git: '' +baRcodeR: + version: 0.1.7 + title: |- + Label Creation for Tracking and Collecting Data from Biological + Samples + maintainer: Robert Colautti + description: |- + Tools to generate unique identifier codes and + printable barcoded labels for the management of biological samples. + The creation of unique ID codes and printable PDF files can be + initiated by standard commands, user prompts, or through a GUI addin + for R Studio. Biologically informative codes can be included for + hierarchically structured sampling designs. + date_publication: '2022-04-01' + bug_reports: https://github.com/ropensci/baRcodeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=baRcodeR + url_git: https://docs.ropensci.org/baRcodeR/(website)https://github.com/ropensci/baRcodeR/ +BarcodingR: + version: 1.0-3 + title: Species Identification using DNA Barcodes + maintainer: Ai-bing ZHANG + description: To perform species identification using DNA barcodes. + date_publication: '2020-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BarcodingR + url_git: '' +bardr: + version: 0.0.9 + title: Complete Works of William Shakespeare in Tidy Format + maintainer: Zane Billings + description: |- + Provides R data structures for Shakespeare's complete works, + as provided by Project Gutenberg . + date_publication: '2021-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bardr + url_git: '' +BAREB: + version: 0.1.2 + title: A Bayesian Repulsive Biclustering Model for Periodontal Data + maintainer: Qingyang Liu + description: |- + Simultaneously clusters the Periodontal diseases (PD) patients + and their tooth sites after taking the patient- and site-level covariates into consideration. + 'BAREB' uses the determinantal point process (DPP) prior to induce diversity + among different biclusters to facilitate parsimony and interpretability. + Essentially, 'BAREB' is a cluster-wise linear model based on Yuliang (2020) . + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BAREB + url_git: '' +bark: + version: 1.0.5 + title: Bayesian Additive Regression Kernels + maintainer: Merlise Clyde + description: |- + Bayesian Additive Regression Kernels (BARK) provides + an implementation for non-parametric function estimation using Levy + Random Field priors for functions that may be represented as a + sum of additive multivariate kernels. Kernels are located at + every data point as in Support Vector Machines, however, coefficients + may be heavily shrunk to zero under the Cauchy process prior, or even, + set to zero. The number of active features is controlled by priors on + precision parameters within the kernels, permitting feature selection. For + more details see Ouyang, Z (2008) "Bayesian Additive Regression Kernels", + Duke University. PhD dissertation, Chapter 3 and Wolpert, R. L, Clyde, M.A, + and Tu, C. (2011) "Stochastic Expansions with Continuous Dictionaries Levy + Adaptive Regression Kernels, Annals of Statistics Vol (39) pages 1916-1962 + . + date_publication: '2024-10-05' + bug_reports: https://github.com/merliseclyde/bark/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bark + url_git: https://github.com/merliseclyde/bark +Barnard: + version: '1.8' + title: Barnard's Unconditional Test + maintainer: Kamil Erguler + description: Barnard's unconditional test for 2x2 contingency tables. + date_publication: '2016-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Barnard + url_git: https://github.com/kerguler/Barnard +barrks: + version: 1.0.1 + title: Calculate Bark Beetle Phenology Using Different Models + maintainer: Jakob Jentschke + description: |- + Calculate the bark beetle phenology based on raster data or + point-related data. There are multiple models implemented for two bark + beetle species. The models can be customized and their submodels (onset of + infestation, beetle development, diapause initiation, mortality) can be + combined. The following models are available in the package: + PHENIPS-Clim (first-time release in this package), + PHENIPS (Baier et al. 2007) , + RITY (Ogris et al. 2019) , + CHAPY (Ogris et al. 2020) , + BSO (Jakoby et al. 2019) , + Lange et al. (2008) , + Jönsson et al. (2011) . + The package may be expanded by models for other bark beetle species in the + future. + date_publication: '2024-11-04' + bug_reports: https://github.com/jjentschke/barrks/issues/ + url: https://jjentschke.github.io/barrks/ + url_cran: https://CRAN.R-project.org/package=barrks + url_git: https://github.com/jjentschke/barrks/ +BART: + version: 2.9.9 + title: Bayesian Additive Regression Trees + maintainer: Rodney Sparapani + description: Bayesian Additive Regression Trees (BART) provide flexible nonparametric + modeling of covariates for continuous, binary, categorical and time-to-event outcomes. For + more information see Sparapani, Spanbauer and McCulloch . + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BART + url_git: '' +bartCause: + version: 1.0-9 + title: Causal Inference using Bayesian Additive Regression Trees + maintainer: Vincent Dorie + description: Contains a variety of methods to generate typical causal inference + estimates using Bayesian Additive Regression Trees (BART) as the underlying regression + model (Hill (2012) ). + date_publication: '2024-09-16' + bug_reports: https://github.com/vdorie/bartCause/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bartCause + url_git: https://github.com/vdorie/bartCause +bartcs: + version: 1.2.2 + title: Bayesian Additive Regression Trees for Confounder Selection + maintainer: Yeonghoon Yoo + description: |- + Fit Bayesian Regression Additive Trees (BART) models to + select true confounders from a large set of potential confounders and + to estimate average treatment effect. For more information, see Kim et + al. (2023) . + date_publication: '2024-05-01' + bug_reports: https://github.com/yooyh/bartcs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bartcs + url_git: https://github.com/yooyh/bartcs +bartMachine: + version: 1.3.4.1 + title: Bayesian Additive Regression Trees + maintainer: Adam Kapelner + description: An advanced implementation of Bayesian Additive Regression Trees with + expanded features for data analysis and visualization. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bartMachine + url_git: '' +bartMachineJARs: + version: 1.2.1 + title: bartMachine JARs + maintainer: Adam Kapelner + description: 'These are bartMachine''s Java dependency libraries. Note: this package + has no functionality of its own and should not be installed as a standalone package + without bartMachine.' + date_publication: '2022-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bartMachineJARs + url_git: '' +bartMan: + version: 0.1.1 + title: Create Visualisations for BART Models + maintainer: Alan Inglis + description: Investigating and visualising Bayesian Additive Regression Tree (BART) + (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) + model fits. We construct conventional plots to analyze a model’s performance + and stability as well as create new tree-based plots to analyze variable importance, + interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes + (VSUP) to construct heatmaps that display variable importance and interactions + jointly using colour scale to represent posterior uncertainty. Our visualisations + are designed to work with the most popular BART R packages available, namely 'BART' + Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 , 'dbarts' (Vincent + Dorie 2023) , and 'bartMachine' (Adam + Kapelner and Justin Bleich 2016) . + date_publication: '2024-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bartMan + url_git: '' +baRulho: + version: 2.1.3 + title: Quantifying (Animal) Sound Degradation + maintainer: Marcelo Araya-Salas + description: Intended to facilitate acoustic analysis of (animal) sound transmission + experiments, which typically aim to quantify changes in signal structure when + transmitted in a given habitat by broadcasting and re-recording animal sounds + at increasing distances. The package offers a workflow with functions to prepare + the data set for analysis as well as to calculate and visualize several degradation + metrics, including blur ratio, signal-to-noise ratio, excess attenuation and envelope + correlation among others (Dabelsteen et al 1993 ). + date_publication: '2025-01-25' + bug_reports: https://github.com/ropensci/baRulho/issues + url: https://docs.ropensci.org/baRulho/ + url_cran: https://CRAN.R-project.org/package=baRulho + url_git: https://github.com/ropensci/baRulho +BAS: + version: 1.7.5 + title: |- + Bayesian Variable Selection and Model Averaging using Bayesian + Adaptive Sampling + maintainer: Merlise Clyde + description: |- + Package for Bayesian Variable Selection and Model Averaging + in linear models and generalized linear models using stochastic or + deterministic sampling without replacement from posterior + distributions. Prior distributions on coefficients are + from Zellner's g-prior or mixtures of g-priors + corresponding to the Zellner-Siow Cauchy Priors or the + mixture of g-priors from Liang et al (2008) + + for linear models or mixtures of g-priors from Li and Clyde + (2019) in generalized linear models. + Other model selection criteria include AIC, BIC and Empirical Bayes + estimates of g. Sampling probabilities may be updated based on the sampled + models using sampling w/out replacement or an efficient MCMC algorithm which + samples models using a tree structure of the model space + as an efficient hash table. See Clyde, Ghosh and Littman (2010) + for details on the sampling algorithms. + Uniform priors over all models or beta-binomial prior distributions on + model size are allowed, and for large p truncated priors on the model + space may be used to enforce sampling models that are full rank. + The user may force variables to always be included in addition to imposing + constraints that higher order interactions are included only if their + parents are included in the model. + This material is based upon work supported by the National Science + Foundation under Division of Mathematical Sciences grant 1106891. + Any opinions, findings, and + conclusions or recommendations expressed in this material are those of + the author(s) and do not necessarily reflect the views of the + National Science Foundation. + date_publication: '2024-11-28' + bug_reports: https://github.com/merliseclyde/BAS/issues + url: https://merliseclyde.github.io/BAS/ + url_cran: https://CRAN.R-project.org/package=BAS + url_git: https://github.com/merliseclyde/BAS +basad: + version: 0.3.0 + title: Bayesian Variable Selection with Shrinking and Diffusing Priors + maintainer: Qingyan Xiang + description: Provides a Bayesian variable selection approach using continuous spike + and slab prior distributions. The prior choices here are motivated by the shrinking + and diffusing priors studied in Narisetty & He (2014) . + date_publication: '2021-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basad + url_git: '' +base.rms: + version: '1.0' + title: Convert Regression Between Base Function and 'rms' Package + maintainer: Jing Zhang + description: |2- + + We perform linear, logistic, and cox regression using the base functions lm(), + glm(), and coxph() in the R software and the 'survival' package. Likewise, we + can use ols(), lrm() and cph() from the 'rms' package for the same + functionality. Each of these two sets of commands has a different focus. + In many cases, we need to use both sets of commands in the same situation, + e.g. we need to filter the full subset model using AIC, and we need to build + a visualization graph for the final model. 'base.rms' package can help you to switch + between the two sets of commands easily. + date_publication: '2020-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=base.rms + url_git: '' +base64: + version: 2.0.2 + title: Base64 Encoder and Decoder + maintainer: Jeroen Ooms + description: |- + Compatibility wrapper to replace the orphaned package. New + applications should use base64 encoders from 'jsonlite' or 'openssl' or + 'base64enc'. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=base64 + url_git: '' +base64enc: + version: 0.1-3 + title: Tools for base64 encoding + maintainer: Simon Urbanek + description: This package provides tools for handling base64 encoding. It is more + flexible than the orphaned base64 package. + date_publication: '2015-07-28' + bug_reports: '' + url: http://www.rforge.net/base64enc + url_cran: https://CRAN.R-project.org/package=base64enc + url_git: '' +base64url: + version: '1.4' + title: Fast and URL-Safe Base64 Encoder and Decoder + maintainer: Michel Lang + description: |- + In contrast to RFC3548, the 62nd character ("+") is replaced with + "-", the 63rd character ("/") is replaced with "_". Furthermore, the encoder + does not fill the string with trailing "=". The resulting encoded strings + comply to the regular expression pattern "[A-Za-z0-9_-]" and thus are + safe to use in URLs or for file names. + The package also comes with a simple base32 encoder/decoder suited for + case insensitive file systems. + date_publication: '2018-05-14' + bug_reports: https://github.com/mllg/base64url/issues + url: '' + url_cran: https://CRAN.R-project.org/package=base64url + url_git: https://github.com/mllg/base64url +baseballr: + version: 1.6.0 + title: Acquiring and Analyzing Baseball Data + maintainer: Saiem Gilani + description: |- + Provides numerous utilities for acquiring and analyzing + baseball data from online sources such as 'Baseball Reference' , + 'FanGraphs' , and the 'MLB Stats' API . + date_publication: '2024-01-16' + bug_reports: https://github.com/BillPetti/baseballr/issues + url: https://billpetti.github.io/baseballr/ + url_cran: https://CRAN.R-project.org/package=baseballr + url_git: https://github.com/BillPetti/baseballr +basecamb: + version: 1.1.5 + title: Utilities for Streamlined Data Import, Imputation and Modelling + maintainer: J. Peter Marquardt + description: |- + Provides functions streamlining the data analysis workflow: + Outsourcing data import, renaming and type casting to a *.csv. + Manipulating imputed datasets and fitting models on them. Summarizing models. + date_publication: '2024-04-22' + bug_reports: https://github.com/codeblue-team/basecamb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=basecamb + url_git: https://github.com/codeblue-team/basecamb +basedosdados: + version: 0.2.2 + title: '''Base Dos Dados'' R Client' + maintainer: Pedro Cavalcante + description: An R interface to the 'Base dos Dados' API ). + Authenticate your project, query our tables, save data to disk and memory, all + from R. + date_publication: '2023-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basedosdados + url_git: '' +basefun: + version: 1.2-2 + title: Infrastructure for Computing with Basis Functions + maintainer: Torsten Hothorn + description: Some very simple infrastructure for basis functions. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basefun + url_git: http://ctm.R-forge.R-project.org +baseline: + version: 1.3-5 + title: Baseline Correction of Spectra + maintainer: Kristian Hovde Liland + description: Collection of baseline correction algorithms, along with a framework + and a Tcl/Tk enabled GUI for optimising baseline algorithm parameters. Typical + use of the package is for removing background effects from spectra originating + from various types of spectroscopy and spectrometry, possibly optimizing this + with regard to regression or classification results. Correction methods include + polynomial fitting, weighted local smoothers and many more. + date_publication: '2023-11-18' + bug_reports: https://github.com/khliland/baseline/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=baseline + url_git: https://github.com/khliland/baseline/ +basemaps: + version: 0.0.8 + title: Accessing Spatial Basemaps in R + maintainer: Jakob Schwalb-Willmann + description: A lightweight package to access spatial basemaps from open sources + such as 'OpenStreetMap', 'Carto', 'Mapbox' and others in R. + date_publication: '2024-11-01' + bug_reports: https://github.com/16eagle/basemaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=basemaps + url_git: '' +basemodels: + version: 1.1.0 + title: Baseline Models for Classification and Regression + maintainer: Ying-Ju Chen + description: |- + Providing equivalent functions for the dummy + classifier and regressor used in 'Python' 'scikit-learn' library. Our goal + is to allow R users to easily identify baseline performance for their + classification and regression problems. Our baseline models use no + predictors, and are useful in cases of class imbalance, multiclass + classification, and when users want to quickly identify how much + improvement their statistical and machine learning models are over several + baseline models. We use a "better" default (proportional guessing) for + the dummy classifier than the 'Python' implementation ("prior", which is + the most frequent class in the training set). The functions in the + package can be used on their own, or introduce methods named + 'dummy_regressor' or 'dummy_classifier' that can be used within the + caret package pipeline. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basemodels + url_git: https://github.com/Ying-Ju/basemodels +baseq: + version: 0.1.4 + title: Basic Sequence Processing Tool for Biological Data + maintainer: Ambu Vijayan + description: Primarily created as an easy and understanding way to do basic sequences + surrounding the central dogma of molecular biology. + date_publication: '2023-05-03' + bug_reports: https://github.com/ambuvjyn/baseq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=baseq + url_git: https://github.com/ambuvjyn/baseq +BaseSet: + version: 1.0.0 + title: Working with Sets the Tidy Way + maintainer: Lluís Revilla Sancho + description: |- + Implements a class and methods to work with sets, doing + intersection, union, complementary sets, power sets, cartesian product + and other set operations in a "tidy" way. These set operations are + available for both classical sets and fuzzy sets. Import sets from + several formats or from other several data structures. + date_publication: '2025-02-17' + bug_reports: https://github.com/ropensci/BaseSet/issues + url: https://docs.ropensci.org/BaseSet/ + url_cran: https://CRAN.R-project.org/package=BaseSet + url_git: https://github.com/ropensci/BaseSet +BaseTempSeed: + version: 0.1.0 + title: |- + Estimation of Seed Germination Base Temperature in Thermal + Modelling + maintainer: Dr. Himadri Ghosh + description: All the seeds do not germinate at a single point in time due to physiological + mechanisms determined by temperature which vary among individual seeds in the + population. Seeds germinate by following accumulation of thermal time in degree + days/hours, quantified by multiplying the time of germination with excess of base + temperature required by each seed for its germination, which follows log-normal + distribution. The theoretical germination course can be obtained by regressing + the rate of germination at various fractions against temperature (Garcia et al., + 1982), where the fraction-wise regression lines intersect the temperature axis + at base temperature and the methodology of determining optimum base temperature + has been described by Ellis et al. (1987). This package helps to find the base + temperature of seed germination using algorithms of Garcia et al. (1982) and Ellis + et al. (1982) . + date_publication: '2023-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BaseTempSeed + url_git: '' +basetheme: + version: 0.1.3 + title: Themes for Base Graphics Plots + maintainer: Karolis Koncevičius + description: 'Functions to create and select graphical themes for the base plotting + system. Contains: 1) several custom pre-made themes 2) mechanism for creating + new themes by making persistent changes to the graphical parameters of base plots.' + date_publication: '2023-04-07' + bug_reports: https://github.com/karoliskoncevicius/basetheme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=basetheme + url_git: https://github.com/karoliskoncevicius/basetheme +basf: + version: 0.2.0 + title: Plot Simple Features with 'base' Sensibilities + maintainer: Michael Sumner + description: |- + Resurrects the standard plot for shapes established by the + 'base' and 'graphics' packages. This is suited to workflows that require + plotting using the established and traditional idioms of plotting spatially + coincident data where it belongs. This package depends on 'sf' and only replaces + the plot method. + date_publication: '2020-12-09' + bug_reports: https://github.com/mdsumner/basf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=basf + url_git: https://github.com/mdsumner/basf +basicdrm: + version: 0.3.0 + title: Fit Hill Dose Response Models + maintainer: Nathaniel Twarog + description: |- + Evaluate, fit, and analyze Hill dose response models (Goutelle et + al., 2008 ), also sometimes referred + to as four-parameter log-logistic models. Includes tools to invert Hill + models, select models based on the Akaike information criterion + (Akaike, 1974 ) or Bayesian information + criterion (Schwarz, 1978 ), and + construct bootstrapped confidence intervals both + on the Hill model parameters and values derived from the Hill model + parameters. + date_publication: '2024-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basicdrm + url_git: '' +basicMCMCplots: + version: 0.2.7 + title: |- + Trace Plots, Density Plots and Chain Comparisons for MCMC + Samples + maintainer: Daniel Turek + description: |- + Provides methods for examining posterior MCMC samples + from a single chain using trace plots and density plots, and from + multiple chains by comparing posterior medians and credible intervals + from each chain. These plotting functions have a variety of options, + such as figure sizes, legends, parameters to plot, and saving plots to file. + Functions interface with the NIMBLE software package, see + de Valpine, Turek, Paciorek, Anderson-Bergman, Temple Lang and Bodik (2017) + . + date_publication: '2021-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basicMCMCplots + url_git: '' +basicspace: + version: '0.25' + title: Recovering a Basic Space from Issue Scales + maintainer: Christopher Hare + description: Provides functions to estimate latent dimensions of choice and judgment + using Aldrich-McKelvey and Blackbox scaling methods, as described in Poole et + al. (2016, ). These techniques allow researchers (particularly + those analyzing political attitudes, public opinion, and legislative behavior) + to recover spatial estimates of political actors' ideal points and stimuli from + issue scale data, accounting for perceptual bias, multidimensional spaces, and + missing data. The package uses singular value decomposition and alternating least + squares (ALS) procedures to scale self-placement and perceptual data into a common + latent space for the analysis of ideological or evaluative dimensions. Functionality + also include tools for assessing model fit, handling complex survey data structures, + and reproducing simulated datasets for methodological validation. + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basicspace + url_git: '' +basictabler: + version: 1.0.2 + title: Construct Rich Tables for Output to 'HTML'/'Excel' + maintainer: Christopher Bailiss + description: |- + Easily create tables from data + frames/matrices. Create/manipulate tables + row-by-row, column-by-column or cell-by-cell. + Use common formatting/styling to output + rich tables as 'HTML', 'HTML widgets' or to + 'Excel'. + date_publication: '2021-06-26' + bug_reports: https://github.com/cbailiss/basictabler/issues + url: http://www.basictabler.org.uk/ + url_cran: https://CRAN.R-project.org/package=basictabler + url_git: https://github.com/cbailiss/basictabler +basifoR: + version: '0.4' + title: |- + Retrieval and Processing of the Spanish National Forest + Inventory + maintainer: Wilson Lara + description: Data sets of the Spanish National Forest Inventory + are processed to compute tree metrics and statistics. Function metrics2Vol() controls + most of the routines. + date_publication: '2021-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=basifoR + url_git: '' +BASiNET: + version: 0.0.5 + title: Classification of RNA Sequences using Complex Network Theory + maintainer: Fabricio Martins Lopes + description: It makes the creation of networks from sequences of RNA, with this + is done the abstraction of characteristics of these networks with a methodology + of threshold for the purpose of making a classification between the classes of + the sequences. There are four data present in the 'BASiNET' package, "sequences", + "sequences2", "sequences-predict" and "sequences2-predict" with 11, 10, 11 and + 11 sequences respectively. These sequences were taken from the data set used in + the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) , + these sequences are used to run examples. The BASiNET was published on Nucleic + Acids Research, (ITO, Eric; KATAHIRA, Isaque; VICENTE, Fábio; PEREIRA, Felipe; + LOPES, Fabrício, 2018) . + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BASiNET + url_git: '' +BASiNETEntropy: + version: 0.99.6 + title: |- + Classification of RNA Sequences using Complex Network and + Information Theory + maintainer: Fabricio Martins Lopes + description: It makes the creation of networks from sequences of RNA, with this + is done the abstraction of characteristics of these networks with a methodology + of maximum entropy for the purpose of making a classification between the classes + of the sequences. There are two data present in the 'BASiNET' package, "mRNA", + and "ncRNA" with 10 sequences. These sequences were taken from the data set used + in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) , + these sequences are used to run examples. + date_publication: '2023-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BASiNETEntropy + url_git: '' +BaSkePro: + version: 1.1.1 + title: Bayesian Model to Archaeological Faunal Skeletal Profiles + maintainer: Marco Vidal-Cordasco + description: 'Tool to perform Bayesian inference of carcass processing/transport + strategy and bone attrition from archaeofaunal skeletal profiles characterized + by percentages of MAU (Minimum Anatomical Units). The approach is based on a generative + model for skeletal profiles that replicates the two phases of formation of any + faunal assemblage: initial accumulation as a function of human transport strategies + and subsequent attrition.Two parameters define this model: 1) the transport preference + (alpha), which can take any value between - 1 (mostly axial contribution) and + 1 (mostly appendicular contribution) following strategies constructed as a function + of butchering efficiency of different anatomical elements and the results of ethnographic + studies, and 2) degree of attrition (beta), which can vary between 0 (no attrition) + and 10 (maximum attrition) and relates the survivorship of bone elements to their + maximum bone density. Starting from uniform prior probability distribution functions + of alpha and beta, a Monte Carlo Markov Chain sampling based on a random walk + Metropolis-Hasting algorithm is adopted to derive the posterior probability distribution + functions, which are then available for interpretation. During this process, the + likelihood of obtaining the observed percentages of MAU given a pair of parameter + values is estimated by the inverse of the Chi2 statistic, multiplied by the proportion + of elements within a 1 percent of the observed value. See Ana B. Marin-Arroyo, + David Ocio (2018)..' + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BaSkePro + url_git: '' +basket: + version: 0.10.11 + title: Basket Trial Analysis + maintainer: Michael J. Kane + description: Implementation of multisource exchangeability models for Bayesian analyses + of prespecified subgroups arising in the context of basket trial design and monitoring. The + R 'basket' package facilitates implementation of the binary, symmetric multi-source + exchangeability model (MEM) with posterior inference arising from both exact computation + and Markov chain Monte Carlo sampling. Analysis output includes full posterior + samples as well as posterior probabilities, highest posterior density (HPD) interval + boundaries, effective sample sizes (ESS), mean and median estimations, posterior + exchangeability probability matrices, and maximum a posteriori MEMs. In addition + to providing "basketwise" analyses, the package includes similar calculations + for "clusterwise" analyses for which subgroups are combined into meta-baskets, + or clusters, using graphical clustering algorithms that treat the posterior exchangeability + probabilities as edge weights. In addition plotting tools are provided to visualize + basket and cluster densities as well as their exchangeability. References include + Hyman, D.M., Puzanov, I., Subbiah, V., Faris, J.E., Chau, I., Blay, J.Y., Wolf, + J., Raje, N.S., Diamond, E.L., Hollebecque, A. and Gervais, R (2015) ; + Hobbs, B.P. and Landin, R. (2018) ; Hobbs, B.P., Kane, M.J., + Hong, D.S. and Landin, R. (2018) ; and Kaizer, A.M., + Koopmeiners, J.S. and Hobbs, B.P. (2017) . + date_publication: '2021-10-16' + bug_reports: https://github.com/kaneplusplus/basket/issues + url: '' + url_cran: https://CRAN.R-project.org/package=basket + url_git: https://github.com/kaneplusplus/basket +BasketballAnalyzeR: + version: 0.5.0 + title: Analysis and Visualization of Basketball Data + maintainer: Marco Sandri + description: |- + Contains data and code to accompany the book + P. Zuccolotto and M. Manisera (2020) Basketball Data Science. Applications with R. CRC Press. ISBN 9781138600799. + date_publication: '2020-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BasketballAnalyzeR + url_git: https://github.com/sndmrc/BasketballAnalyzeR +baskexact: + version: 1.0.1 + title: Analytical Calculation of Basket Trial Operating Characteristics + maintainer: Lukas Baumann + description: |- + Analytically calculates the operating characteristics of + single-stage and two-stage basket trials with equal sample sizes using the + power prior design by Baumann et al. (2024) + and the design by Fujikawa et al. (2020) . + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=baskexact + url_git: https://github.com/lbau7/baskexact +basksim: + version: 1.0.0 + title: |- + Simulation-Based Calculation of Basket Trial Operating + Characteristics + maintainer: Lukas Baumann + description: |- + Provides a unified syntax for the simulation-based comparison of different single-stage basket trial + designs with a binary endpoint and equal sample sizes in all baskets. Methods include the designs by + Baumann et al. (2024) , Fujikawa et al. (2020) , + Berry et al. (2020) , Neuenschwander et al. (2016) and + Psioda et al. (2021) . For the latter three designs, the functions are mostly + wrappers for functions provided by the packages 'bhmbasket' and 'bmabasket'. + date_publication: '2024-04-12' + bug_reports: https://github.com/lbau7/basksim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=basksim + url_git: https://github.com/lbau7/basksim +BASS: + version: 1.3.1 + title: Bayesian Adaptive Spline Surfaces + maintainer: Devin Francom + description: |- + Bayesian fitting and sensitivity analysis methods for adaptive + spline surfaces described in . Built to handle continuous and categorical inputs as well as + functional or scalar output. An extension of the methodology in Denison, Mallick + and Smith (1998) . + date_publication: '2023-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BASS + url_git: '' +BaSTA: + version: 2.0.1 + title: |- + Age-Specific Bayesian Survival Trajectory Analysis from + Incomplete Census or Capture-Recapture/Recovery Data + maintainer: Fernando Colchero + description: Estimates survival and mortality with covariates from census or capture-recapture/recovery + data in a Bayesian framework when many individuals are of unknown age. It includes + tools for data checking, model diagnostics and outputs such as life-tables and + plots, as described in Colchero, Jones, and Rebke (2012) + and Colchero et al. (2021) . + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BaSTA + url_git: '' +BAT: + version: 2.9.6 + title: Biodiversity Assessment Tools + maintainer: Pedro Cardoso + description: |- + Includes algorithms to assess alpha and beta diversity + in all their dimensions (taxonomic, phylogenetic and functional). + It allows performing a number of analyses based on species + identities/abundances, phylogenetic/functional distances, trees, + convex-hulls or kernel density n-dimensional hypervolumes + depicting species relationships. + Cardoso et al. (2015) . + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BAT + url_git: '' +batata: + version: 0.2.1 + title: Managing Packages Removal and Installation + maintainer: Mohamed El Fodil Ihaddaden + description: |2- + + Allows the user to manage easily R packages removal and installation. It offers many functions to display installed packages according to + specific dates and removes them if needed. The user is always prompted when running the removal functions in order to confirm + the required action. It also provides functions that will install 'Github' starred R packages whether available on 'CRAN' or not. + date_publication: '2021-03-08' + bug_reports: https://github.com/feddelegrand7/batata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=batata + url_git: https://github.com/feddelegrand7/batata +batch: + version: 1.1-5 + title: |- + Batching Routines in Parallel and Passing Command-Line Arguments + to R + maintainer: Thomas Hoffmann + description: Functions to allow you to easily pass command-line arguments into R, + and functions to aid in submitting your R code in parallel on a cluster and joining + the results afterward (e.g. multiple parameter values for simulations running + in parallel, splitting up a permutation test in parallel, etc.). See `parseCommandArgs(...)' + for the main example of how to use this package. + date_publication: '2018-04-16' + bug_reports: '' + url: http://sites.google.com/site/thomashoffmannproject/ + url_cran: https://CRAN.R-project.org/package=batch + url_git: '' +BatchExperiments: + version: 1.4.3 + title: Statistical Experiments on Batch Computing Clusters + maintainer: Michel Lang + description: |- + Extends the BatchJobs package to run statistical experiments on + batch computing clusters. For further details see the project web page. + date_publication: '2022-03-21' + bug_reports: https://github.com/tudo-r/BatchExperiments/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BatchExperiments + url_git: https://github.com/tudo-r/BatchExperiments +BatchGetSymbols: + version: 2.6.4 + title: Downloads and Organizes Financial Data for Multiple Tickers + maintainer: Marcelo Perlin + description: Makes it easy to download financial data from Yahoo Finance . + date_publication: '2022-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BatchGetSymbols + url_git: '' +BatchJobs: + version: '1.9' + title: Batch Computing with R + maintainer: Bernd Bischl + description: |- + Provides Map, Reduce and Filter variants to generate jobs on batch + computing systems like PBS/Torque, LSF, SLURM and Sun Grid Engine. + Multicore and SSH systems are also supported. For further details see the + project web page. + date_publication: '2022-03-21' + bug_reports: https://github.com/tudo-r/BatchJobs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BatchJobs + url_git: https://github.com/tudo-r/BatchJobs +batchLLM: + version: 0.2.0 + title: Batch Process LLM Text Completions Using a Data Frame + maintainer: Dylan Pieper + description: Batch process large language model (LLM) text completions using data + frame rows, with support for OpenAI's 'GPT' (), Anthropic's + 'Claude' (), and Google's 'Gemini' (). + Includes features such as local storage, metadata logging, API rate limiting delays, + and a 'shiny' app addin. + date_publication: '2024-10-14' + bug_reports: https://github.com/dylanpieper/batchLLM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=batchLLM + url_git: https://github.com/dylanpieper/batchLLM +batchmeans: + version: 1.0-4 + title: Consistent Batch Means Estimation of Monte Carlo Standard Errors + maintainer: John Hughes + description: |- + Provides consistent batch means estimation of Monte + Carlo standard errors. + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=batchmeans + url_git: '' +batchmix: + version: 2.2.1 + title: |- + Semi-Supervised Bayesian Mixture Models Incorporating Batch + Correction + maintainer: Stephen Coleman + description: |- + Semi-supervised and unsupervised Bayesian mixture models that + simultaneously infer the cluster/class structure and a batch correction. + Densities available are the multivariate normal and the multivariate t. + The model sampler is implemented in C++. This package is aimed at analysis of + low-dimensional data generated across several batches. See Coleman et al. + (2022) for details of the model. + date_publication: '2024-05-21' + bug_reports: https://github.com/stcolema/batchmix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=batchmix + url_git: https://github.com/stcolema/batchmix +batchscr: + version: 0.1.0 + title: Batch Script Helpers + maintainer: Sherry Zhao + description: |- + Handy frameworks, such as error handling and log generation, for batch scripts. + Use case: in scripts running in remote servers, set error handling mechanism for downloading and uploading and record operation log. + date_publication: '2019-05-06' + bug_reports: https://github.com/sherrisherry/batchscr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=batchscr + url_git: '' +batchtma: + version: 0.1.6 + title: Batch Effect Adjustments + maintainer: Konrad Stopsack + description: |- + Different adjustment methods for batch effects in biomarker data, + such as from tissue microarrays. Some methods attempt to retain differences + between batches that may be due to between-batch differences in "biological" + factors that influence biomarker values. + date_publication: '2021-12-06' + bug_reports: '' + url: https://stopsack.github.io/batchtma/ + url_cran: https://CRAN.R-project.org/package=batchtma + url_git: https://github.com/stopsack/batchtma +batchtools: + version: 0.9.17 + title: Tools for Computation on Batch Systems + maintainer: Michel Lang + description: |- + As a successor of the packages 'BatchJobs' and 'BatchExperiments', + this package provides a parallel implementation of the Map function for high + performance computing systems managed by schedulers 'IBM Spectrum LSF' + (), + 'OpenLava' (), 'Univa Grid Engine'/'Oracle Grid + Engine' (), 'Slurm' (), + 'TORQUE/PBS' + (), + or 'Docker Swarm' (). + A multicore and socket mode allow the parallelization on a local machines, + and multiple machines can be hooked up via SSH to create a makeshift + cluster. Moreover, the package provides an abstraction mechanism to define + large-scale computer experiments in a well-organized and reproducible way. + date_publication: '2023-04-20' + bug_reports: https://github.com/mllg/batchtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=batchtools + url_git: https://github.com/mllg/batchtools +bate: + version: 0.1.0 + title: Computes Bias-Adjusted Treatment Effect + maintainer: Deepankar Basu + description: |- + Compute bounds for the treatment effect + after adjusting for the presence of omitted variables in linear + econometric models, according to the method of Basu (2022) . + You supply the data, identify the outcome and + treatment variables and additional regressors. The main functions + will compute bounds for the bias-adjusted treatment effect. Many + plot functions allow easy visualization of results. + date_publication: '2022-03-28' + bug_reports: '' + url: https://rpubs.com/dbasu/bate/ + url_cran: https://CRAN.R-project.org/package=bate + url_git: https://github.com/dbasu-umass/bate/ +batman: + version: 0.1.0 + title: |- + Convert Categorical Representations of Logicals to Actual + Logicals + maintainer: Oliver Keyes + description: |- + Survey systems and other third-party data sources commonly use non-standard representations of logical values when + it comes to qualitative data - "Yes", "No" and "N/A", say. batman is a package designed to seamlessly convert these into logicals. + It is highly localised, and contains equivalents to boolean values in languages including German, French, Spanish, Italian, + Turkish, Chinese and Polish. + date_publication: '2015-10-26' + bug_reports: https://github.com/ironholds/batman/issues + url: '' + url_cran: https://CRAN.R-project.org/package=batman + url_git: https://github.com/ironholds/batman +batsch: + version: 0.1.1 + title: Real-Time PCR Data Sets by Batsch et al. (2008) + maintainer: Ramiro Magno + description: |- + Real-time quantitative polymerase chain reaction (qPCR) data + sets by Batsch et al. (2008) . This package + provides five data sets, one for each PCR target: (i) rat SLC6A14, + (ii) human SLC22A13, (iii) pig EMT, (iv) chicken ETT, and (v) human + GAPDH. Each data set comprises a five-point, four-fold dilution series. + For each concentration there are three replicates. Each amplification curve + is 45 cycles long. Original raw data file: + . + date_publication: '2024-04-22' + bug_reports: https://github.com/ramiromagno/batsch/issues + url: https://rmagno.eu/batsch/ + url_cran: https://CRAN.R-project.org/package=batsch + url_git: https://github.com/ramiromagno/batsch +BATSS: + version: 1.0.0 + title: |- + Bayesian Adaptive Trial Simulator Software (BATSS) for + Generalised Linear Models + maintainer: Dominique-Laurent Couturier + description: Defines operating characteristics of Bayesian Adaptive Trials considering + a generalised linear model response via Monte Carlo simulations of Bayesian GLM + fitted via integrated Laplace approximations (INLA). + date_publication: '2024-10-02' + bug_reports: '' + url: https://batss-dev.github.io/BATSS/ + url_cran: https://CRAN.R-project.org/package=BATSS + url_git: '' +batteryreduction: + version: 0.1.1 + title: An R Package for Data Reduction by Battery Reduction + maintainer: Chunqiao Luo + description: Battery reduction is a method used in data reduction. It uses Gram-Schmidt + orthogonal rotations to find out a subset of variables best representing the original + set of variables. + date_publication: '2015-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=batteryreduction + url_git: '' +BAwiR: + version: 1.3.4 + title: Analysis of Basketball Data + maintainer: Guillermo Vinue + description: |- + Collection of tools to work with European basketball data. Functions available are related to friendly + web scraping, data management and visualization. Data were obtained from , + and , following the instructions + of their respectives robots.txt files, when available. Box score data are available for the three leagues. + Play-by-play data are also available for the Spanish league. Methods for analysis include a population pyramid, + 2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, + team shooting plots, team four factors plots, cross-tables with the results of regular season games, + maps of nationalities, combinations of lineups, possessions-related variables, timeouts, + performance by periods, personal fouls and offensive rebounds. + Please see Vinue (2020) and Vinue (2024) . + date_publication: '2025-02-14' + bug_reports: '' + url: https://www.uv.es/vivigui/basketball_platform.html + url_cran: https://CRAN.R-project.org/package=BAwiR + url_git: '' +bayclumpr: + version: 0.1.0 + title: Bayesian Analysis of Clumped Isotope Datasets + maintainer: Cristian Roman Palacios + description: |- + Simulating synthetic clumped isotope dataset, fitting + linear regression models under Bayesian and non-Bayesian frameworks, + and generating temperature reconstructions for the same two approaches. + Please note that models implemented in this package are described + in Roman-Palacios et al. (2021) . + date_publication: '2023-03-29' + bug_reports: https://github.com/Tripati-Lab/bayclumpr/issues + url: https://bayclump.tripatilab.epss.ucla.edu/ + url_cran: https://CRAN.R-project.org/package=bayclumpr + url_git: '' +baycn: + version: 1.2.0 + title: Bayesian Inference for Causal Networks + maintainer: Evan A Martin + description: |- + A Bayesian hybrid approach for inferring Directed Acyclic Graphs + (DAGs) for continuous, discrete, and mixed data. The algorithm can use the + graph inferred by another more efficient graph inference method as input; + the input graph may contain false edges or undirected edges but can help + reduce the search space to a more manageable size. A Bayesian Markov chain + Monte Carlo algorithm is then used to infer the probability of direction and + absence for the edges in the network. + References: + Martin and Fu (2019) . + date_publication: '2020-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=baycn + url_git: '' +bayefdr: + version: 0.2.1 + title: |- + Bayesian Estimation and Optimisation of Expected False Discovery + Rate + maintainer: Alan O'Callaghan + description: |2- + + Implements the Bayesian FDR control described by + Newton et al. (2004), . + Allows optimisation and visualisation of expected error rates based on + tail posterior probability tests. + Based on code written by Catalina Vallejos for BASiCS, see + Beyond comparisons of means: understanding changes in gene expression at the + single-cell level Vallejos et al. (2016) . + date_publication: '2022-10-26' + bug_reports: https://github.com/VallejosGroup/bayefdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayefdr + url_git: https://github.com/VallejosGroup/bayefdr +Bayenet: + version: '0.2' + title: Bayesian Quantile Elastic Net for Genetic Study + maintainer: Xi Lu + description: As heavy-tailed error distribution and outliers in the response variable + widely exist, models which are robust to data contamination are highly demanded. + Here, we develop a novel robust Bayesian variable selection method with elastic + net penalty for quantile regression in genetic analysis. In particular, the spike-and-slab + priors have been incorporated to impose sparsity. An efficient Gibbs sampler has + been developed to facilitate computation.The core modules of the package have + been developed in 'C++' and R. + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bayenet + url_git: '' +bayes4psy: + version: 1.2.12 + title: User Friendly Bayesian Data Analysis for Psychology + maintainer: Jure Demšar + description: Contains several Bayesian models for data analysis of psychological + tests. A user friendly interface for these models should enable students and researchers + to perform professional level Bayesian data analysis without advanced knowledge + in programming and Bayesian statistics. This package is based on the Stan platform + (Carpenter et el. 2017 ). + date_publication: '2023-09-29' + bug_reports: https://github.com/bstatcomp/bayes4psy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayes4psy + url_git: https://github.com/bstatcomp/bayes4psy +bayesAB: + version: 1.1.3 + title: Fast Bayesian Methods for AB Testing + maintainer: Frank Portman + description: |- + A suite of functions that allow the user to analyze A/B test + data in a Bayesian framework. Intended to be a drop-in replacement for + common frequentist hypothesis test such as the t-test and chi-sq test. + date_publication: '2021-06-25' + bug_reports: https://github.com/FrankPortman/bayesAB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesAB + url_git: https://github.com/FrankPortman/bayesAB +bayesammi: + version: 0.3.0 + title: |- + Bayesian Estimation of the Additive Main Effects and + Multiplicative Interaction Model + maintainer: Muhammad Yaseen + description: Performs Bayesian estimation of the additive main effects and multiplicative + interaction (AMMI) model. The method is explained in Crossa, J., Perez-Elizalde, + S., Jarquin, D., Cotes, J.M., Viele, K., Liu, G. and Cornelius, P.L. (2011) (). + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesammi + url_git: '' +bayesanova: + version: '1.6' + title: |- + Bayesian Inference in the Analysis of Variance via Markov Chain + Monte Carlo in Gaussian Mixture Models + maintainer: Riko Kelter + description: Provides a Bayesian version of the analysis of variance based on a + three-component Gaussian mixture for which a Gibbs sampler produces posterior + draws. For details about the Bayesian ANOVA based on Gaussian mixtures, see Kelter + (2019) . + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesanova + url_git: '' +BayesARIMAX: + version: 0.1.1 + title: Bayesian Estimation of ARIMAX Model + maintainer: Achal Lama + description: The Autoregressive Integrated Moving Average (ARIMA) model is very + popular univariate time series model. Its application has been widened by the + incorporation of exogenous variable(s) (X) in the model and modified as ARIMAX + by Bierens (1987) . In this package we estimate + the ARIMAX model using Bayesian framework. + date_publication: '2020-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesARIMAX + url_git: '' +bayesassurance: + version: 0.1.0 + title: Bayesian Assurance Computation + maintainer: Jane Pan + description: |- + Computes Bayesian assurance under various + settings characterized by different assumptions and objectives, including + precision-based conditions, credible intervals, and goal functions. + All simulation-based functions included in this package rely on a two-stage + Bayesian method that assigns two distinct priors to evaluate the + probability of observing a positive outcome, which addresses subtle + limitations that take place when using the standard single-prior approach. + For more information, please refer to Pan and Banerjee (2021) + . + date_publication: '2022-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesassurance + url_git: https://github.com/jpan928/bayesassurance_rpackage +BayesAT: + version: 0.1.0 + title: Bayesian Adaptive Trial + maintainer: Yuan Zhong + description: Bayesian adaptive trial algorithm implements multiple-stage interim + analysis. Package includes data generating function, and Bayesian hypothesis testing + function. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesAT + url_git: '' +BayesBEKK: + version: 0.1.1 + title: Bayesian Estimation of Bivariate Volatility Model + maintainer: Achal Lama + description: The Multivariate Generalized Autoregressive Conditional Heteroskedasticity + (MGARCH) models are used for modelling the volatile multivariate data sets. In + this package a variant of MGARCH called BEKK (Baba, Engle, Kraft, Kroner) proposed + by Engle and Kroner (1995) has been used + to estimate the bivariate time series data using Bayesian technique. + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesBEKK + url_git: '' +BayesBinMix: + version: 1.4.1 + title: |- + Bayesian Estimation of Mixtures of Multivariate Bernoulli + Distributions + maintainer: Panagiotis Papastamoulis + description: Fully Bayesian inference for estimating the number of clusters and + related parameters to heterogeneous binary data. + date_publication: '2017-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesBinMix + url_git: '' +bayesbio: + version: 1.0.0 + title: |- + Miscellaneous Functions for Bioinformatics and Bayesian + Statistics + maintainer: Andrew McKenzie + description: |- + A hodgepodge of hopefully helpful functions. Two of these perform + shrinkage estimation: one using a simple weighted method where the user can + specify the degree of shrinkage required, and one using James-Stein shrinkage + estimation for the case of unequal variances. + date_publication: '2016-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesbio + url_git: '' +bayesboot: + version: 0.2.2 + title: An Implementation of Rubin's (1981) Bayesian Bootstrap + maintainer: Rasmus Bååth + description: |- + Functions for performing the Bayesian bootstrap as introduced by + Rubin (1981) and for summarizing the result. + The implementation can handle both summary statistics that works on a + weighted version of the data and summary statistics that works on a + resampled data set. + date_publication: '2018-06-29' + bug_reports: https://github.com/rasmusab/bayesboot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesboot + url_git: https://github.com/rasmusab/bayesboot +BayesBP: + version: '1.1' + title: Bayesian Estimation using Bernstein Polynomial Fits Rate Matrix + maintainer: Li-Syuan Hong + description: |- + Smoothed lexis diagrams with Bayesian method specifically tailored to cancer + incidence data. Providing to calculating slope and constructing credible interval. + LC Chien et al. (2015) . + LH Chien et al. (2017) . + date_publication: '2020-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesBP + url_git: '' +BayesCACE: + version: 1.2.3 + title: Bayesian Model for CACE Analysis + maintainer: Jinhui Yang + description: Performs CACE (Complier Average Causal Effect analysis) on either a + single study or meta-analysis of datasets with binary outcomes, using either complete + or incomplete noncompliance information. Our package implements the Bayesian methods + proposed in Zhou et al. (2019) , which introduces a Bayesian + hierarchical model for estimating CACE in meta-analysis of clinical trials with + noncompliance, and Zhou et al. (2021) , with + an application example on Epidural Analgesia. + date_publication: '2022-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesCACE + url_git: '' +BayesChange: + version: 1.1.2 + title: Bayesian Methods for Change Points Analysis + maintainer: Luca Danese + description: Perform change points detection on univariate and multivariate time + series according to the methods presented by Asael Fabian Martínez and Ramsés + H. Mena (2014) and Corradin, Danese and Ongaro (2022) . + It also clusters different types of time dependent data with common change points, + see "Model-based clustering of time-dependent observations with common structural + changes" (Corradin,Danese,KhudaBukhsh and Ongaro, 2024) + for details. + date_publication: '2025-02-21' + bug_reports: https://github.com/lucadanese/BayesChange/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesChange + url_git: https://github.com/lucadanese/BayesChange +BayesCombo: + version: '1.0' + title: Bayesian Evidence Combination + maintainer: Stanley E. Lazic + description: Combine diverse evidence across multiple studies to test a high level + scientific theory. The methods can also be used as an alternative to a standard + meta-analysis. + date_publication: '2017-02-08' + bug_reports: https://github.com/stanlazic/BayesCombo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesCombo + url_git: https://github.com/stanlazic/BayesCombo +BayesComm: + version: 0.1-2 + title: Bayesian Community Ecology Analysis + maintainer: Nick Golding + description: |- + Bayesian multivariate binary (probit) regression + models for analysis of ecological communities. + date_publication: '2015-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesComm + url_git: '' +bayescopulareg: + version: 0.1.3 + title: Bayesian Copula Regression + maintainer: Ethan Alt + description: |- + Tools for Bayesian copula generalized linear models (GLMs). + The sampling scheme is based on Pitt, Chan, and Kohn (2006) . + Regression parameters (including coefficients and dispersion parameters) are + estimated via the adaptive random walk Metropolis approach developed by + Haario, Saksman, and Tamminen (1999) . + The prior for the correlation matrix is based on Hoff (2007) . + date_publication: '2020-11-30' + bug_reports: https://github.com/ethan-alt/bayescopulareg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayescopulareg + url_git: https://github.com/ethan-alt/bayescopulareg +bayescount: + version: 0.9.99-9 + title: |- + Power Calculations and Bayesian Analysis of Count Distributions + and FECRT Data using MCMC + maintainer: Matthew Denwood + description: |- + A set of functions to allow analysis of count data (such + as faecal egg count data) using Bayesian MCMC methods. Returns + information on the possible values for mean count, coefficient + of variation and zero inflation (true prevalence) present in + the data. A complete faecal egg count reduction test (FECRT) + model is implemented, which returns inference on the true + efficacy of the drug from the pre- and post-treatment data + provided, using non-parametric bootstrapping as well as using + Bayesian MCMC. Functions to perform power analyses for faecal + egg counts (including FECRT) are also provided. + date_publication: '2023-12-08' + bug_reports: '' + url: https://bayescount.sourceforge.net + url_cran: https://CRAN.R-project.org/package=bayescount + url_git: '' +BayesCPclust: + version: 0.1.0 + title: |- + A Bayesian Approach for Clustering Constant-Wise Change-Point + Data + maintainer: Ana Carolina da Cruz + description: A Gibbs sampler algorithm was developed to estimate change points in + constant-wise data sequences while performing clustering simultaneously. The algorithm + is described in da Cruz, A. C. and de Souza, C. P. E "A Bayesian Approach for + Clustering Constant-wise Change-point Data" . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesCPclust + url_git: '' +BayesCR: + version: '2.1' + title: |- + Bayesian Analysis of Censored Regression Models Under Scale + Mixture of Skew Normal Distributions + maintainer: Aldo M. Garay + description: Propose a parametric fit for censored linear regression models based + on SMSN distributions, from a Bayesian perspective. Also, generates SMSN random + variables. + date_publication: '2017-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesCR + url_git: '' +bayesCT: + version: 0.99.3 + title: Simulation and Analysis of Adaptive Bayesian Clinical Trials + maintainer: Thevaa Chandereng + description: |- + Simulation and analysis of Bayesian adaptive clinical trials for binomial, Gaussian, and time-to-event data types, + incorporates historical data and allows early stopping for futility or early success. The package uses novel + and efficient Monte Carlo methods for estimating Bayesian posterior probabilities, evaluation of loss to follow up, + and imputation of incomplete data. The package has the functionality for dynamically incorporating historical data + into the analysis via the power prior or non-informative priors. + date_publication: '2020-07-01' + bug_reports: https://github.com/thevaachandereng/bayesCT/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=bayesCT + url_git: https://github.com/thevaachandereng/bayesCT/ +BayesCTDesign: + version: 0.6.1 + title: |- + Two Arm Bayesian Clinical Trial Design with and Without + Historical Control Data + maintainer: Barry Eggleston + description: A set of functions to help clinical trial researchers calculate power + and sample size for two-arm Bayesian randomized clinical trials that do or do + not incorporate historical control data. At some point during the design process, + a clinical trial researcher who is designing a basic two-arm Bayesian randomized + clinical trial needs to make decisions about power and sample size within the + context of hypothesized treatment effects. Through simulation, the simple_sim() + function will estimate power and other user specified clinical trial characteristics + at user specified sample sizes given user defined scenarios about treatment effect,control + group characteristics, and outcome. If the clinical trial researcher has access + to historical control data, then the researcher can design a two-arm Bayesian + randomized clinical trial that incorporates the historical data. In such a case, + the researcher needs to work through the potential consequences of historical + and randomized control differences on trial characteristics, in addition to working + through issues regarding power in the context of sample size, treatment effect + size, and outcome. If a researcher designs a clinical trial that will incorporate + historical control data, the researcher needs the randomized controls to be from + the same population as the historical controls. What if this is not the case + when the designed trial is implemented? During the design phase, the researcher + needs to investigate the negative effects of possible historic/randomized control + differences on power, type one error, and other trial characteristics. Using + this information, the researcher should design the trial to mitigate these negative + effects. Through simulation, the historic_sim() function will estimate power + and other user specified clinical trial characteristics at user specified sample + sizes given user defined scenarios about historical and randomized control differences + as well as treatment effects and outcomes. The results from historic_sim() and + simple_sim() can be printed with print_table() and graphed with plot_table() methods. Outcomes + considered are Gaussian, Poisson, Bernoulli, Lognormal, Weibull, and Piecewise + Exponential. The methods are described in Eggleston et al. (2021) . + date_publication: '2021-11-30' + bug_reports: https://github.com/begglest/BayesCTDesign/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesCTDesign + url_git: https://github.com/begglest/BayesCTDesign +bayesCureRateModel: + version: '1.3' + title: Bayesian Cure Rate Modeling for Time-to-Event Data + maintainer: Panagiotis Papastamoulis + description: A fully Bayesian approach in order to estimate a general family of + cure rate models under the presence of covariates, see Papastamoulis and Milienos + (2024) . The promotion time can be modelled (a) + parametrically using typical distributional assumptions for time to event data + (including the Weibull, Exponential, Gompertz, log-Logistic distributions), or + (b) semiparametrically using finite mixtures of distributions. In both cases, + user-defined families of distributions are allowed under some specific requirements. + Posterior inference is carried out by constructing a Metropolis-coupled Markov + chain Monte Carlo (MCMC) sampler, which combines Gibbs sampling for the latent + cure indicators and Metropolis-Hastings steps with Langevin diffusion dynamics + for parameter updates. The main MCMC algorithm is embedded within a parallel tempering + scheme by considering heated versions of the target posterior distribution. + date_publication: '2024-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesCureRateModel + url_git: https://github.com/mqbssppe/Bayesian_cure_rate_model +BayesCVI: + version: 1.0.1 + title: Bayesian Cluster Validity Index + maintainer: Onthada Preedasawakul + description: Algorithms for computing and generating plots with and without error + bars for Bayesian cluster validity index (BCVI) (O. Preedasawakul, and N. Wiroonsri, + A Bayesian Cluster Validity Index, Computational Statistics & Data Analysis, 202, + 108053, 2025. ) based on several underlying cluster + validity indexes (CVIs) including Calinski-Harabasz, Chou-Su-Lai, Davies-Bouldin, + Dunn, Pakhira-Bandyopadhyay-Maulik, Point biserial correlation, the score function, + Starczewski, and Wiroonsri indices for hard clustering, and Correlation Cluster + Validity, the generalized C, HF, KWON, KWON2, Modified Pakhira-Bandyopadhyay-Maulik, + Pakhira-Bandyopadhyay-Maulik, Tang, Wiroonsri-Preedasawakul, Wu-Li, and Xie-Beni + indices for soft clustering. The package is compatible with K-means, fuzzy C means, + EM clustering, and hierarchical clustering (single, average, and complete linkage). + Though BCVI is compatible with any underlying existing CVIs, we recommend users + to use either WI or WP as the underlying CVI. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesCVI + url_git: '' +BayesDA: + version: 2012.04-1 + title: Functions and Datasets for the book "Bayesian Data Analysis" + maintainer: Kjetil Halvorsen + description: Functions for Bayesian Data Analysis, with datasets fromthe + book "Bayesian data Analysis (second edition)" by Gelman,Carlin, Stern + and Rubin. Not all datasets yet, hopefullycompleted soon. + date_publication: '2012-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesDA + url_git: '' +bayesDccGarch: + version: 3.0.4 + title: |- + Methods and Tools for Bayesian Dynamic Conditional Correlation + GARCH(1,1) Model + maintainer: Jose Augusto Fiorucci + description: Bayesian estimation of dynamic conditional correlation GARCH model + for multivariate time series volatility (Fioruci, J.A., Ehlers, R.S. and Andrade-Filho, + M.G., (2014). . + date_publication: '2023-04-22' + bug_reports: https://github.com/jafiorucci/bayesDccGarch/issues + url: https://ui.adsabs.harvard.edu/abs/2014arXiv1412.2967F/abstract + url_cran: https://CRAN.R-project.org/package=bayesDccGarch + url_git: '' +BayesDesign: + version: 0.1.1 + title: Bayesian Single-Arm Design with Survival Endpoints + maintainer: Chia-Wei Hsu + description: The proposed event-driven approach for Bayesian two-stage single-arm + phase II trial design is a novel clinical trial design and can be regarded as + an extension of the Simon’s two-stage design with the time-to-event endpoint. + This design is motivated by cancer clinical trials with immunotherapy and molecularly + targeted therapy, in which time-to-event endpoint is often a desired endpoint. + date_publication: '2021-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesDesign + url_git: '' +bayesdfa: + version: 1.3.3 + title: Bayesian Dynamic Factor Analysis (DFA) with 'Stan' + maintainer: Eric J. Ward + description: |- + Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic + factor analysis is a dimension reduction tool for multivariate time series. + 'bayesdfa' extends conventional dynamic factor models in several ways. + First, extreme events may be estimated in the latent trend by modeling + process error with a student-t distribution. Second, alternative constraints + (including proportions are allowed). Third, the estimated + dynamic factors can be analyzed with hidden Markov models to evaluate + support for latent regimes. + date_publication: '2024-02-26' + bug_reports: https://github.com/fate-ewi/bayesdfa/issues + url: https://fate-ewi.github.io/bayesdfa/ + url_cran: https://CRAN.R-project.org/package=bayesdfa + url_git: '' +BayesDIP: + version: 0.1.1 + title: |- + Bayesian Decreasingly Informative Priors for Early Termination + Phase II Trials + maintainer: Chen Wang + description: |- + Provide early termination phase II trial designs with a + decreasingly informative prior (DIP) or a regular Bayesian prior + chosen by the user. The program can determine the minimum planned + sample size necessary to achieve the user-specified admissible + designs. The program can also perform power and expected sample size + calculations for the tests in early termination Phase II trials. + See Wang C and Sabo RT (2022) ; + Sabo RT (2014) . + date_publication: '2023-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesDIP + url_git: +BayesDissolution: + version: 0.2.1 + title: Bayesian Models for Dissolution Testing + maintainer: Tony Pourmohamad + description: Fits Bayesian models (amongst others) to dissolution data sets that + can be used for dissolution testing. The package was originally constructed to + include only the Bayesian models outlined in Pourmohamad et al. (2022) . + However, additional Bayesian and non-Bayesian models (based on bootstrapping and + generalized pivotal quanties) have also been added. More models may be added over + time. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesDissolution + url_git: '' +bayesdistreg: + version: 0.1.0 + title: Bayesian Distribution Regression + maintainer: Emmanuel Tsyawo + description: Implements Bayesian Distribution Regression methods. This package contains + functions for three estimators (non-asymptotic, semi-asymptotic and asymptotic) + and related routines for Bayesian Distribution Regression in Huang and Tsyawo + (2018) which is also the recommended reference to cite + for this package. The functions can be grouped into three (3) categories. The + first computes the logit likelihood function and posterior densities under uniform + and normal priors. The second contains Independence and Random Walk Metropolis-Hastings + Markov Chain Monte Carlo (MCMC) algorithms as functions and the third category + of functions are useful for semi-asymptotic and asymptotic Bayesian distribution + regression inference. + date_publication: '2019-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesdistreg + url_git: '' +BayesDLMfMRI: + version: 0.0.3 + title: Statistical Analysis for Task-Based Fmri Data + maintainer: Carlos Pérez + description: |- + The 'BayesDLMfMRI' package performs statistical analysis for task-based functional magnetic resonance imaging (fMRI) data at both individual and group levels. The analysis to detect brain activation at the individual level is based on modeling the fMRI signal using Matrix-Variate Dynamic Linear Models (MDLM). The analysis for the group stage is based on posterior distributions of the state parameter obtained from the modeling at the individual level. In this way, this package offers several R functions with different algorithms to perform inference on the state parameter to assess brain activation for both individual and group stages. Those functions allow for parallel computation when the analysis is performed for the entire brain as well as analysis at specific voxels when it is required. + References: Cardona-Jiménez (2021) ; + Cardona-Jiménez (2021) . + date_publication: '2023-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesDLMfMRI + url_git: https://github.com/JohnatanLAB/BayesDLMfMRI/ +bayesDP: + version: 1.3.7 + title: |- + Implementation of the Bayesian Discount Prior Approach for + Clinical Trials + maintainer: Graeme L. Hickey + description: |- + Functions for data augmentation using the Bayesian discount prior + method for single arm and two-arm clinical trials, as described in Haddad + et al. (2017) . The discount power prior + methodology was developed in collaboration with the The Medical Device + Innovation Consortium (MDIC) Computer Modeling & Simulation Working Group. + date_publication: '2025-01-12' + bug_reports: https://github.com/graemeleehickey/bayesDP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesDP + url_git: https://github.com/graemeleehickey/bayesDP +bayesEO: + version: 0.2.1 + title: Bayesian Smoothing of Remote Sensing Image Classification + maintainer: Gilberto Camara + description: |- + A Bayesian smoothing method for post-processing of remote + sensing image classification which refines the + labelling in a classified image in order to enhance its classification accuracy. + Combines pixel-based classification methods with a spatial post-processing + method to remove outliers and misclassified pixels. + date_publication: '2024-06-04' + bug_reports: https://github.com/e-sensing/bayesEO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesEO + url_git: https://github.com/e-sensing/bayesEO/ +BayesERtools: + version: 0.2.1 + title: Bayesian Exposure-Response Analysis Tools + maintainer: Kenta Yoshida + description: |- + Suite of tools that facilitate + exposure-response analysis using Bayesian methods. The package + provides a streamlined workflow for fitting types of models that are + commonly used in exposure-response analysis - linear and Emax for continuous + endpoints, logistic linear and logistic Emax for binary endpoints, as well + as performing simulation and visualization. Learn more about the workflow + at . + date_publication: '2025-02-12' + bug_reports: '' + url: https://genentech.github.io/BayesERtools/ + url_cran: https://CRAN.R-project.org/package=BayesERtools + url_git: '' +BayesESS: + version: 0.1.19 + title: Determining Effective Sample Size + maintainer: Jaejoon Song + description: |- + Determines effective sample size of a parametric prior distribution + in Bayesian models. For a web-based Shiny application related to this package, see . + date_publication: '2019-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesESS + url_git: '' +bayesestdft: + version: 1.0.0 + title: |- + Estimating the Degrees of Freedom of the Student's + t-Distribution under a Bayesian Framework + maintainer: Somjit Roy + description: A Bayesian framework to estimate the Student's t-distribution's degrees + of freedom is developed. Markov Chain Monte Carlo sampling routines are developed + as in to sample from the posterior distribution of + the degrees of freedom. A random walk Metropolis algorithm is used for sampling + when Jeffrey's and Gamma priors are endowed upon the degrees of freedom. In addition, + the Metropolis-adjusted Langevin algorithm for sampling is used under the Jeffrey's + prior specification. The Log-normal prior over the degrees of freedom is posed + as a viable choice with comparable performance in simulations and real-data application, + against other prior choices, where an Elliptical Slice Sampler is used to sample + from the concerned posterior. + date_publication: '2025-01-09' + bug_reports: https://github.com/Roy-SR-007/bayesestdft/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesestdft + url_git: https://github.com/Roy-SR-007/bayesestdft +BayesFactor: + version: 0.9.12-4.7 + title: Computation of Bayes Factors for Common Designs + maintainer: Richard D. Morey + description: |- + A suite of functions for computing + various Bayes factors for simple designs, including contingency tables, + one- and two-sample designs, one-way designs, general ANOVA designs, and + linear regression. + date_publication: '2024-01-24' + bug_reports: https://github.com/richarddmorey/BayesFactor/issues + url: https://richarddmorey.github.io/BayesFactor/ + url_cran: https://CRAN.R-project.org/package=BayesFactor + url_git: '' +BayesFBHborrow: + version: 2.0.2 + title: |- + Bayesian Dynamic Borrowing with Flexible Baseline Hazard + Function + maintainer: Darren Scott + description: |- + Allows Bayesian borrowing from a historical dataset for time-to- + event data. A flexible baseline hazard function is achieved via a piecewise + exponential likelihood with time varying split points and smoothing prior on the + historic baseline hazards. The method is described in Scott and Lewin (2024) + , and the software paper is in Axillus et al. + (2024) . + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesFBHborrow + url_git: '' +BayesFluxR: + version: 0.1.3 + title: Implementation of Bayesian Neural Networks + maintainer: Enrico Wegner + description: |- + Implementation of 'BayesFlux.jl' for R; It extends the famous + 'Flux.jl' machine learning library to Bayesian Neural Networks. + The goal is not to have the fastest production ready + library, but rather to allow more people to be able + to use and research on Bayesian Neural Networks. + date_publication: '2023-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesFluxR + url_git: '' +BayesFM: + version: 0.1.7 + title: Bayesian Inference for Factor Modeling + maintainer: Rémi Piatek + description: |- + Collection of procedures to perform Bayesian analysis on a variety + of factor models. Currently, it includes: "Bayesian Exploratory Factor + Analysis" (befa) from G. Conti, S. Frühwirth-Schnatter, J.J. Heckman, + R. Piatek (2014) , an approach to + dedicated factor analysis with stochastic search on the structure of the + factor loading matrix. The number of latent factors, as well as the + allocation of the manifest variables to the factors, are not fixed a priori + but determined during MCMC sampling. + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesFM + url_git: '' +BayesfMRI: + version: 0.3.11 + title: Spatial Bayesian Methods for Task Functional MRI Studies + maintainer: Amanda Mejia + description: |- + Performs a spatial Bayesian general linear model (GLM) for task + functional magnetic resonance imaging (fMRI) data on the cortical surface. + Additional models include group analysis and inference to detect thresholded + areas of activation. Includes direct support for the 'CIFTI' neuroimaging + file format. For more information see A. F. Mejia, Y. R. Yue, D. Bolin, F. + Lindgren, M. A. Lindquist (2020) and D. + Spencer, Y. R. Yue, D. Bolin, S. Ryan, A. F. Mejia (2022) + . + date_publication: '2023-12-18' + bug_reports: https://github.com/mandymejia/BayesfMRI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesfMRI + url_git: https://github.com/mandymejia/BayesfMRI +bayesforecast: + version: 1.0.1 + title: Bayesian Time Series Modeling with Stan + maintainer: Asael Alonzo Matamoros + description: |- + Fit Bayesian time series models using 'Stan' for full Bayesian inference. A wide range + of distributions and models are supported, allowing users to fit Seasonal ARIMA, ARIMAX, Dynamic + Harmonic Regression, GARCH, t-student innovation GARCH models, asymmetric GARCH, Random Walks, stochastic + volatility models for univariate time series. Prior specifications are flexible and explicitly encourage + users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed + and compared with typical visualization methods, information criteria such as loglik, AIC, BIC WAIC, Bayes + factor and leave-one-out cross-validation methods. References: Hyndman (2017) + ; Carpenter et al. (2017) . + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesforecast + url_git: '' +bayesGARCH: + version: 2.1.10 + title: |- + Bayesian Estimation of the GARCH(1,1) Model with Student-t + Innovations + maintainer: David Ardia + description: |- + Provides the bayesGARCH() function which performs the + Bayesian estimation of the GARCH(1,1) model with Student's t innovations as described in Ardia (2008) . + date_publication: '2021-05-16' + bug_reports: https://github.com/ArdiaD/bayesGARCH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesGARCH + url_git: https://github.com/ArdiaD/bayesGARCH +BayesGmed: + version: 0.0.3 + title: Bayesian Causal Mediation Analysis using 'Stan' + maintainer: Belay Birlie Yimer + description: Performs parametric mediation analysis using the Bayesian g-formula + approach for binary and continuous outcomes. The methodology is based on Comment + (2018) and a demonstration of its application can + be found at Yimer et al. (2022) . + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesGmed + url_git: '' +BayesGOF: + version: '5.2' + title: Bayesian Modeling via Frequentist Goodness-of-Fit + maintainer: Doug Fletcher + description: 'A Bayesian data modeling scheme that performs four interconnected + tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) + provides exploratory diagnostic for checking prior-data conflict; (iii) computes + the final statistical prior density estimate; and (iv) executes macro- and micro-inference. + Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized + Empirical Bayes via Frequentist Goodness of Fit" ().' + date_publication: '2018-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesGOF + url_git: '' +BayesGP: + version: 0.1.3 + title: |- + Efficient Implementation of Gaussian Process in Bayesian + Hierarchical Models + maintainer: Ziang Zhang + description: Implements Bayesian hierarchical models with flexible Gaussian process + priors, focusing on Extended Latent Gaussian Models and incorporating various + Gaussian process priors for Bayesian smoothing. Computations leverage finite element + approximations and adaptive quadrature for efficient inference. Methods are detailed + in Zhang, Stringer, Brown, and Stafford (2023) ; + Zhang, Stringer, Brown, and Stafford (2024) ; + Zhang, Brown, and Stafford (2023) ; and Stringer, + Brown, and Stafford (2021) . + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesGP + url_git: '' +BayesGPfit: + version: 1.1.0 + title: Fast Bayesian Gaussian Process Regression Fitting + maintainer: Jian Kang + description: Bayesian inferences on nonparametric regression via Gaussian Processes + with a modified exponential square kernel using a basis expansion approach. + date_publication: '2022-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesGPfit + url_git: '' +BayesGrowth: + version: 1.0.0 + title: Estimate Fish Growth Using MCMC Analysis + maintainer: Jonathan Smart + description: |- + Estimate fish length-at-age models using MCMC analysis with + 'rstan' models. This package allows a multimodel approach to growth fitting + to be applied to length-at-age data and is supported by further analyses to + determine model selection and result presentation. The core methods of this + package are presented in Smart and Grammer (2021) "Modernising fish and + shark growth curves with Bayesian length-at-age models". PLOS ONE 16(2): + e0246734 . + date_publication: '2023-11-21' + bug_reports: https://github.com/jonathansmart/BayesGrowth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesGrowth + url_git: https://github.com/jonathansmart/BayesGrowth +BayesGWQS: + version: 0.1.1 + title: Bayesian Grouped Weighted Quantile Sum Regression + maintainer: Matthew Carli + description: Fits Bayesian grouped weighted quantile sum (BGWQS) regressions for + one or more chemical groups with binary outcomes. Wheeler DC et al. (2019) . + date_publication: '2022-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesGWQS + url_git: '' +bayesian: + version: 1.0.1 + title: Bindings for Bayesian TidyModels + maintainer: Hamada S. Badr + description: |- + Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels' + via 'bayesian' . 'tidymodels' is a collection of + packages for machine learning; see Kuhn and Wickham (2020) ). + The technical details of 'brms' and 'Stan' are described in Bürkner (2017) + , Bürkner (2018) , + and Carpenter et al. (2017) . + date_publication: '2024-04-28' + bug_reports: https://github.com/hsbadr/bayesian/issues + url: https://hsbadr.github.io/bayesian/ + url_cran: https://CRAN.R-project.org/package=bayesian + url_git: https://github.com/hsbadr/bayesian +bayesianETAS: + version: 1.0.3 + title: Bayesian Estimation of the ETAS Model for Earthquake Occurrences + maintainer: Gordon J. Ross + description: The Epidemic Type Aftershock Sequence (ETAS) model is one of the best-performing + methods for modeling and forecasting earthquake occurrences. This package implements + Bayesian estimation routines to draw samples from the full posterior distribution + of the model parameters, given an earthquake catalog. The paper on which this + package is based is Gordon J. Ross - Bayesian Estimation of the ETAS Model for + Earthquake Occurrences (2016), available from the below URL. + date_publication: '2017-01-17' + bug_reports: '' + url: http://www.gordonjross.co.uk/bayesianetas.pdf + url_cran: https://CRAN.R-project.org/package=bayesianETAS + url_git: '' +BayesianFactorZoo: + version: 0.0.0.3 + title: |- + Bayesian Solutions for the Factor Zoo: We Just Ran Two + Quadrillion Models + maintainer: Jiantao Huang + description: 'Contains the functions to use the econometric methods in the paper + Bryzgalova, Huang, and Julliard (2023) . In this package, + we provide a novel Bayesian framework for analyzing linear asset pricing models: + simple, robust, and applicable to high-dimensional problems. For a stand-alone + model, we provide functions including BayesianFM() and BayesianSDF() to deliver + reliable price of risk estimates for both tradable and nontradable factors. For + competing factors and possibly nonnested models, we provide functions including + continuous_ss_sdf(), continuous_ss_sdf_v2(), and dirac_ss_sdf_pvalue() to analyze + high-dimensional models. If you use this package, please cite the paper. We are + thankful to Yunan Ding and Jingtong Zhang for their research assistance. Any errors + or omissions are the responsibility of the authors.' + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianFactorZoo + url_git: '' +BayesianFitForecast: + version: 1.0.0 + title: |- + Bayesian Parameter Estimation and Forecasting for + Epidemiological Models + maintainer: Gerardo Chowell + description: |- + Methods for Bayesian parameter estimation and forecasting in epidemiological models. + Functions enable model fitting using Bayesian methods and generate forecasts with uncertainty quantification. + Implements approaches described in and . + date_publication: '2024-12-05' + bug_reports: https://github.com/gchowell/BayesianFitForecast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianFitForecast + url_git: https://github.com/gchowell/BayesianFitForecast +Bayesiangammareg: + version: 0.1.0 + title: 'Bayesian Gamma Regression: Joint Mean and Shape Modeling' + maintainer: Arturo Camargo Lozano + description: Adjust the Gamma regression models from a Bayesian perspective described + by Cepeda and Urdinola (2012) , modeling the + parameters of mean and shape and using different link functions for the parameter + associated to the mean. And calculates different adjustment statistics such as + the Akaike information criterion and Bayesian information criterion. + date_publication: '2020-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bayesiangammareg + url_git: '' +BayesianGLasso: + version: 0.2.0 + title: Bayesian Graphical Lasso + maintainer: Patrick Trainor + description: Implements a data-augmented block Gibbs sampler for simulating the + posterior distribution of concentration matrices for specifying the topology and + parameterization of a Gaussian Graphical Model (GGM). This sampler was originally + proposed in Wang (2012) . + date_publication: '2017-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianGLasso + url_git: '' +BayesianLaterality: + version: 0.1.2 + title: |- + Predict Brain Asymmetry Based on Handedness and Dichotic + Listening + maintainer: Oystein Sorensen + description: |- + Functional differences between the cerebral hemispheres + are a fundamental characteristic of the human brain. Researchers + interested in studying these differences often infer underlying + hemispheric dominance for a certain function (e.g., language) from + laterality indices calculated from observed performance or brain + activation measures . However, any inference from observed measures + to latent (unobserved) classes has to consider the prior probability + of class membership in the population. The provided functions + implement a Bayesian model for predicting hemispheric dominance from + observed laterality indices (Sorensen and Westerhausen, Laterality: + Asymmetries of Body, Brain and Cognition, 2020, ). + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianLaterality + url_git: https://github.com/LCBC-UiO/BayesianLaterality +BayesianMCPMod: + version: 1.0.2 + title: |- + Simulate, Evaluate, and Analyze Dose Finding Trials with + Bayesian MCPMod + maintainer: Stephan Wojciekowski + description: |- + Bayesian MCPMod (Fleischer et al. (2022) + ) is an innovative method that improves the + traditional MCPMod by systematically incorporating historical data, + such as previous placebo group data. This R package offers functions + for simulating, analyzing, and evaluating Bayesian MCPMod trials with + normally distributed endpoints. It enables the assessment of trial + designs incorporating historical data across various true + dose-response relationships and sample sizes. Robust mixture prior + distributions, such as those derived with the Meta-Analytic-Predictive + approach (Schmidli et al. (2014) ), can be + specified for each dose group. Resulting mixture posterior + distributions are used in the Bayesian Multiple Comparison Procedure + and modeling steps. The modeling step also includes a weighted model + averaging approach (Pinheiro et al. (2014) ). + Estimated dose-response relationships can be bootstrapped and + visualized. + date_publication: '2025-02-06' + bug_reports: https://github.com/Boehringer-Ingelheim/BayesianMCPMod/issues + url: https://boehringer-ingelheim.github.io/BayesianMCPMod/ + url_cran: https://CRAN.R-project.org/package=BayesianMCPMod + url_git: https://github.com/Boehringer-Ingelheim/BayesianMCPMod +BayesianMediationA: + version: 1.0.1 + title: Bayesian Mediation Analysis + maintainer: Qingzhao Yu + description: We perform general mediation analysis in the Bayesian setting using + the methods described in Yu and Li (2022, ISBN:9780367365479). With the package, + the mediation analysis can be performed on different types of outcomes (e.g., + continuous, binary, categorical, or time-to-event), with default or user-defined + priors and predictive models. The Bayesian estimates and credible sets of mediation + effects are reported as analytic results. + date_publication: '2022-09-24' + bug_reports: '' + url: https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html + url_cran: https://CRAN.R-project.org/package=BayesianMediationA + url_git: '' +BayesianNetwork: + version: 0.3.2 + title: Bayesian Network Modeling and Analysis + maintainer: Paul Govan + description: |- + A "Shiny"" web application for creating interactive Bayesian Network models, + learning the structure and parameters of Bayesian networks, and utilities for classic + network analysis. + date_publication: '2024-07-12' + bug_reports: https://github.com/paulgovan/BayesianNetwork/issues + url: http://paulgovan.github.io/BayesianNetwork/ + url_cran: https://CRAN.R-project.org/package=BayesianNetwork + url_git: https://github.com/paulgovan/bayesiannetwork +BayesianPlatformDesignTimeTrend: + version: 1.2.3 + title: Simulate and Analyse Bayesian Platform Trial with Time Trend + maintainer: Ziyan Wang + description: |- + Simulating the sequential multi-arm multi-stage or platform trial with Bayesian approach using the 'rstan' package, which provides the R interface for the Stan. + This package supports fixed ratio and Bayesian adaptive randomization approaches for randomization. + Additionally, it allows for the study of time trend problems in platform trials. + There are demos available for a multi-arm multi-stage trial with two different null scenarios, as well as for Bayesian trial cutoff screening. + The Bayesian adaptive randomisation approaches are described in: + Trippa et al. (2012) and + Wathen et al. (2017) . + The randomisation algorithm is described in: + Zhao W . + The analysis methods of time trend effect in platform trial are described in: + Saville et al. (2022) and + Bofill Roig et al. (2022) . + date_publication: '2023-12-07' + bug_reports: https://github.com/ZXW834/BayesianPlatformDesignTimeTrend/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianPlatformDesignTimeTrend + url_git: https://github.com/ZXW834/BayesianPlatformDesignTimeTrend +BayesianPower: + version: 0.2.3 + title: |- + Sample Size and Power for Comparing Inequality Constrained + Hypotheses + maintainer: Fayette Klaassen + description: |- + A collection of methods to determine the required sample size for + the evaluation of inequality constrained hypotheses by means of a Bayes + factor. Alternatively, for a given sample size, the unconditional error + probabilities or the expected conditional error probabilities can be + determined. Additional material on the methods in this package is + available in Klaassen, F., Hoijtink, H. & Gu, X. (2019) + . + date_publication: '2020-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianPower + url_git: '' +BayesianReasoning: + version: 0.4.2 + title: Plot Positive and Negative Predictive Values for Medical Tests + maintainer: Gorka Navarrete + description: |- + Functions to plot and help understand positive and negative + predictive values (PPV and NPV), and their relationship with + sensitivity, specificity, and prevalence. See Akobeng, A.K. (2007) + for a theoretical overview of + the technical concepts and Navarrete et al. (2015) for a practical + explanation about the importance of their understanding + . + date_publication: '2023-11-14' + bug_reports: https://github.com/gorkang/BayesianReasoning/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianReasoning + url_git: https://github.com/gorkang/BayesianReasoning +BayesianTools: + version: 0.1.8 + title: |- + General-Purpose MCMC and SMC Samplers and Tools for Bayesian + Statistics + maintainer: Florian Hartig + description: |- + General-purpose MCMC and SMC samplers, as well as plot and + diagnostic functions for Bayesian statistics, with a particular focus on + calibrating complex system models. Implemented samplers include various + Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the + T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential + Monte Carlo (SMC) particle filter. + date_publication: '2023-01-30' + bug_reports: https://github.com/florianhartig/BayesianTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesianTools + url_git: https://github.com/florianhartig/BayesianTools +Bayesiantreg: + version: 1.0.1 + title: Bayesian t Regression for Modeling Mean and Scale Parameters + maintainer: Margarita Marin + description: Performs Bayesian t Regression where mean and scale parameters are + modeling by lineal regression structures, and the degrees of freedom parameters + are estimated. + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bayesiantreg + url_git: '' +bayesianVARs: + version: 0.1.5 + title: MCMC Estimation of Bayesian Vectorautoregressions + maintainer: Luis Gruber + description: |- + Efficient Markov Chain Monte Carlo (MCMC) algorithms for the + fully Bayesian estimation of vectorautoregressions (VARs) featuring + stochastic volatility (SV). Implements state-of-the-art shrinkage + priors following Gruber & Kastner (2023) . + Efficient equation-per-equation estimation following Kastner & Huber + (2020) and Carrerio et al. (2021) + . + date_publication: '2024-11-13' + bug_reports: https://github.com/luisgruber/bayesianVARs/issues + url: https://luisgruber.github.io/bayesianVARs/ + url_cran: https://CRAN.R-project.org/package=bayesianVARs + url_git: https://github.com/luisgruber/bayesianVARs +bayesImageS: + version: 0.6-1 + title: Bayesian Methods for Image Segmentation using a Potts Model + maintainer: Matt Moores + description: |- + Various algorithms for segmentation of 2D and 3D images, such + as computed tomography and satellite remote sensing. This package implements + Bayesian image analysis using the hidden Potts model with external field + prior of Moores et al. (2015) . + Latent labels are sampled using chequerboard updating or Swendsen-Wang. + Algorithms for the smoothing parameter include pseudolikelihood, path sampling, + the exchange algorithm, approximate Bayesian computation (ABC-MCMC and ABC-SMC), + and the parametric functional approximate Bayesian (PFAB) algorithm. Refer to + for an overview and also to + and for further details of specific algorithms. + date_publication: '2021-04-11' + bug_reports: https://bitbucket.org/Azeari/bayesimages/issues + url: https://mooresm.github.io/bayesImageS/ + url_cran: https://CRAN.R-project.org/package=bayesImageS + url_git: https://bitbucket.org/Azeari/bayesimages +BayesLCA: + version: '1.9' + title: Bayesian Latent Class Analysis + maintainer: Arthur White + description: |- + Bayesian Latent Class Analysis using several different + methods. + date_publication: '2020-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesLCA + url_git: '' +bayesLife: + version: 5.3-1 + title: Bayesian Projection of Life Expectancy + maintainer: Hana Sevcikova + description: Making probabilistic projections of life expectancy for all countries + of the world, using a Bayesian hierarchical model . + Subnational projections are also supported. + date_publication: '2024-12-06' + bug_reports: '' + url: https://bayespop.csss.washington.edu + url_cran: https://CRAN.R-project.org/package=bayesLife + url_git: '' +bayeslist: + version: 0.0.1.4 + title: Bayesian Analysis of List Experiments with Prior Information + maintainer: Xiao Lu + description: Estimates Bayesian models of list experiments with informative priors. + It includes functionalities to estimate different types of list experiment models + with varying prior information. See Lu and Traunmüller (2021) + for examples and details of estimation. + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayeslist + url_git: '' +bayeslm: + version: 1.0.1 + title: |- + Efficient Sampling for Gaussian Linear Regression with Arbitrary + Priors + maintainer: Jingyu He + description: Efficient sampling for Gaussian linear regression with arbitrary priors, + Hahn, He and Lopes (2018) . + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayeslm + url_git: https://github.com/JingyuHe/bayeslm +BayesLN: + version: 0.2.10 + title: Bayesian Inference for Log-Normal Data + maintainer: Aldo Gardini + description: Bayesian inference under log-normality assumption must be performed + very carefully. In fact, under the common priors for the variance, useful quantities + in the original data scale (like mean and quantiles) do not have posterior moments + that are finite (Fabrizi et al. 2012 ). This package allows + to easily carry out a proper Bayesian inferential procedure by fixing a suitable + distribution (the generalized inverse Gaussian) as prior for the variance. Functions + to estimate several kind of means (unconditional, conditional and conditional + under a mixed model) and quantiles (unconditional and conditional) are provided. + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesLN + url_git: '' +BayesLogit: + version: '2.1' + title: PolyaGamma Sampling + maintainer: Jesse Windle + description: Tools for sampling from the PolyaGamma distribution based on Polson, + Scott, and Windle (2013) . Useful for logistic + regression. + date_publication: '2019-09-26' + bug_reports: https://github.com/jwindle/BayesLogit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesLogit + url_git: https://github.com/jwindle/BayesLogit +bayeslongitudinal: + version: 0.1.0 + title: Adjust Longitudinal Regression Models Using Bayesian Methodology + maintainer: Edwin Javier Castillo Carreño + description: |- + Adjusts longitudinal regression models using Bayesian methodology + for covariance structures of composite symmetry (SC), + autoregressive ones of order 1 AR (1) and + autoregressive moving average of order (1,1) ARMA (1,1). + date_publication: '2017-07-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayeslongitudinal + url_git: '' +bayesm: + version: 3.1-6 + title: Bayesian Inference for Marketing/Micro-Econometrics + maintainer: Peter Rossi + description: |- + Covers many important models used + in marketing and micro-econometrics applications. + The package includes: + Bayes Regression (univariate or multivariate dep var), + Bayes Seemingly Unrelated Regression (SUR), + Binary and Ordinal Probit, + Multinomial Logit (MNL) and Multinomial Probit (MNP), + Multivariate Probit, + Negative Binomial (Poisson) Regression, + Multivariate Mixtures of Normals (including clustering), + Dirichlet Process Prior Density Estimation with normal base, + Hierarchical Linear Models with normal prior and covariates, + Hierarchical Linear Models with a mixture of normals prior and covariates, + Hierarchical Multinomial Logits with a mixture of normals prior + and covariates, + Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates, + Hierarchical Negative Binomial Regression Models, + Bayesian analysis of choice-based conjoint data, + Bayesian treatment of linear instrumental variables models, + Analysis of Multivariate Ordinal survey data with scale + usage heterogeneity (as in Rossi et al, JASA (01)), + Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see + Jiang, Manchanda, Rossi 2009) + For further reference, consult our book, Bayesian Statistics and + Marketing by Rossi, Allenby and McCulloch (Wiley first edition 2005 and second forthcoming) and Bayesian Non- and Semi-Parametric + Methods and Applications (Princeton U Press 2014). + date_publication: '2023-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesm + url_git: '' +BayesMallows: + version: 2.2.3 + title: Bayesian Preference Learning with the Mallows Rank Model + maintainer: Oystein Sorensen + description: |- + An implementation of the Bayesian version of the Mallows rank model + (Vitelli et al., Journal of Machine Learning Research, 2018 ; + Crispino et al., Annals of Applied Statistics, 2019 ; + Sorensen et al., R Journal, 2020 ; + Stein, PhD Thesis, 2023 ). Both Metropolis-Hastings + and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule, + Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be + analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well + as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the + posterior distributions of parameters are provided. The package also provides functions for estimating + the partition function (normalizing constant) of the Mallows rank model, both with the importance + sampling algorithm of Vitelli et al. and asymptotic approximation with the IPFP algorithm + (Mukherjee, Annals of Statistics, 2016 ). + date_publication: '2025-01-14' + bug_reports: https://github.com/ocbe-uio/BayesMallows/issues + url: https://ocbe-uio.github.io/BayesMallows/ + url_cran: https://CRAN.R-project.org/package=BayesMallows + url_git: https://github.com/ocbe-uio/BayesMallows +bayesMeanScale: + version: 0.2.1 + title: Bayesian Post-Estimation on the Mean Scale + maintainer: David M. Dalenberg + description: Computes Bayesian posterior distributions of predictions, marginal + effects, and differences of marginal effects for various generalized linear models. + Importantly, the posteriors are on the mean (response) scale, allowing for more + natural interpretation than summaries on the link scale. Also, predictions and + marginal effects of the count probabilities for Poisson and negative binomial + models can be computed. + date_publication: '2025-01-08' + bug_reports: https://github.com/dalenbe2/bayesMeanScale/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesMeanScale + url_git: https://github.com/dalenbe2/bayesMeanScale +bayesmeta: + version: '3.4' + title: Bayesian Random-Effects Meta-Analysis and Meta-Regression + maintainer: Christian Roever + description: A collection of functions allowing to derive the posterior distribution + of the model parameters in random-effects meta-analysis or meta-regression, and + providing functionality to evaluate joint and marginal posterior probability distributions, + predictive distributions, shrinkage effects, posterior predictive p-values, etc.; + For more details, see also Roever C (2020) , or Roever + C and Friede T (2022) . + date_publication: '2024-02-15' + bug_reports: '' + url: https://gitlab.gwdg.de/croever/bayesmeta + url_cran: https://CRAN.R-project.org/package=bayesmeta + url_git: '' +BayesMFSurv: + version: 0.1.0 + title: Bayesian Misclassified-Failure Survival Model + maintainer: Nicolas Schmidt + description: |- + Contains a split population survival estimator that models the + misclassification probability of failure versus right-censored events. + The split population survival estimator is described in + Bagozzi et al. (2019) . + date_publication: '2019-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesMFSurv + url_git: '' +bayesMig: + version: 1.0-0 + title: Bayesian Projection of Migration + maintainer: Hana Sevcikova + description: |- + Producing probabilistic projections of net migration rate for all countries of the world + or for subnational units using a Bayesian hierarchical model by Azose an Raftery (2015) . + date_publication: '2024-11-09' + bug_reports: '' + url: http://bayespop.csss.washington.edu + url_cran: https://CRAN.R-project.org/package=bayesMig + url_git: '' +bayesmix: + version: 0.7-6 + title: Bayesian Mixture Models with JAGS + maintainer: Bettina Gruen + description: Fits finite mixture models of univariate Gaussian distributions using + JAGS within a Bayesian framework. + date_publication: '2023-04-12' + bug_reports: '' + url: https://statmath.wu.ac.at/~gruen/BayesMix/ + url_cran: https://CRAN.R-project.org/package=bayesmix + url_git: '' +BayesMixSurv: + version: 0.9.3 + title: |- + Bayesian Mixture Survival Models using Additive + Mixture-of-Weibull Hazards, with Lasso Shrinkage and + Stratification + maintainer: Alireza S. Mahani + description: |- + Bayesian Mixture Survival Models using Additive Mixture-of-Weibull Hazards, with Lasso Shrinkage and + Stratification. As a Bayesian dynamic survival model, it relaxes the proportional-hazard assumption. Lasso shrinkage controls + overfitting, given the increase in the number of free parameters in the model due to presence of two Weibull components + in the hazard function. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesMixSurv + url_git: '' +bayesmlogit: + version: 1.0.1 + title: |- + A Multistate Life Table (MSLT) Methodology Based on Bayesian + Approach + maintainer: Xuezhixing Zhang + description: 'Create life tables with a Bayesian approach, which can be very useful + for modelling a complex health process when considering multiple predisposing + factors and multiple coexisting health conditions. Details for this method can + be found in: Lynch, Scott, et al., (2022) ; Zang, + Emma, et al., (2022) .' + date_publication: '2023-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesmlogit + url_git: '' +BayesMortalityPlus: + version: 0.2.4 + title: Bayesian Mortality Modelling + maintainer: Luiz Fernando Figueiredo + description: Fit Bayesian graduation mortality using the Heligman-Pollard model, + as seen in Heligman, L., & Pollard, J. H. (1980) + and Dellaportas, Petros, et al. (2001) , and dynamic + linear model (Campagnoli, P., Petris, G., and Petrone, S. (2009) ). + While Heligman-Pollard has parameters with a straightforward interpretation yielding + some rich analysis, the dynamic linear model provides a very flexible adjustment + of the mortality curves by controlling the discount factor value. Closing methods + for both Heligman-Pollard and dynamic linear model were also implemented according + to Dodd, Erengul, et al. (2018) . The Bayesian + Lee-Carter model is also implemented to fit historical mortality tables time series + to predict the mortality in the following years and to do improvement analysis, + as seen in Lee, R. D., & Carter, L. R. (1992) + and Pedroza, C. (2006) . + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesMortalityPlus + url_git: '' +bayesmove: + version: 0.2.1 + title: Non-Parametric Bayesian Analyses of Animal Movement + maintainer: Joshua Cullen + description: |- + Methods for assessing animal movement from telemetry and biologging + data using non-parametric Bayesian methods. This includes features for pre- + processing and analysis of data, as well as the visualization of results + from the models. This framework does not rely on standard parametric density + functions, which provides flexibility during model fitting. Further details + regarding part of this framework can be found in Cullen et al. (2021) . + date_publication: '2021-10-22' + bug_reports: https://github.com/joshcullen/bayesmove/issues + url: https://joshcullen.github.io/bayesmove/ + url_cran: https://CRAN.R-project.org/package=bayesmove + url_git: https://github.com/joshcullen/bayesmove +bayesMRM: + version: 2.4.0 + title: Bayesian Multivariate Receptor Modeling + maintainer: Man-Suk Oh + description: Bayesian analysis of multivariate receptor modeling. The package consists + of implementations of the methods of Park and Oh (2015) .The + package uses 'JAGS'(Just Another Gibbs Sampler) to generate Markov chain Monte + Carlo samples of parameters. + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesMRM + url_git: '' +BayesMultiMode: + version: 0.7.3 + title: Bayesian Mode Inference + maintainer: Paul Labonne + description: |- + A two-step Bayesian approach for mode inference following + Cross, Hoogerheide, Labonne and van Dijk (2024) ). + First, a mixture distribution is fitted on the data using a sparse finite + mixture (SFM) Markov chain Monte Carlo (MCMC) algorithm. The number of + mixture components does not have to be known; the size of the mixture is + estimated endogenously through the SFM approach. Second, the modes of the + estimated mixture at each MCMC draw are retrieved using algorithms + specifically tailored for mode detection. These estimates are then used to + construct posterior probabilities for the number of modes, their locations + and uncertainties, providing a powerful tool for mode inference. + date_publication: '2024-10-31' + bug_reports: https://github.com/paullabonne/BayesMultiMode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesMultiMode + url_git: https://github.com/paullabonne/BayesMultiMode +BayesMultMeta: + version: 0.1.1 + title: Bayesian Multivariate Meta-Analysis + maintainer: Erik Thorsén + description: |- + Objective Bayesian inference procedures for the parameters of the + multivariate random effects model with application to multivariate + meta-analysis. The posterior for the model parameters, namely the overall + mean vector and the between-study covariance matrix, are assessed by + constructing Markov chains based on the Metropolis-Hastings algorithms as + developed in Bodnar and Bodnar (2021) (). The + Metropolis-Hastings algorithm is designed under the assumption of the + normal distribution and the t-distribution when the Berger and Bernardo + reference prior and the Jeffreys prior are assigned to the model parameters. + Convergence properties of the generated Markov chains are investigated by + the rank plots and the split hat-R estimate based on the rank normalization, + which are proposed in Vehtari et al. (2021) (). + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesMultMeta + url_git: '' +bayesnec: + version: 2.1.3.0 + title: A Bayesian No-Effect- Concentration (NEC) Algorithm + maintainer: Rebecca Fisher + description: Implementation of No-Effect-Concentration estimation that uses 'brms' + (see Burkner (2017); Burkner (2018); + Carpenter 'et al.' (2017) to fit concentration(dose)-response + data using Bayesian methods for the purpose of estimating 'ECx' values, but more + particularly 'NEC' (see Fox (2010)), 'NSEC' + (see Fisher and Fox (2023)), and 'N(S)EC (see Fisher et + al. 2023). A full description of this package can be found + in Fisher 'et al.' (2024). This package expands and + supersedes an original version implemented in 'R2jags' (see Su and Yajima (2020); + Fisher et al. (2020)). + date_publication: '2024-08-19' + bug_reports: https://github.com/open-aims/bayesnec/issues + url: https://open-aims.github.io/bayesnec/ + url_cran: https://CRAN.R-project.org/package=bayesnec + url_git: '' +BayesNetBP: + version: 1.6.1 + title: Bayesian Network Belief Propagation + maintainer: Han Yu + description: 'Belief propagation methods in Bayesian Networks to propagate evidence + through the network. The implementation of these methods are based on the article: + Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks + . For details please see Yu et. + al. (2020) BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks + . The optional ''cyjShiny'' package for running the + Shiny app is available at . Please see + the example in the documentation of ''runBayesNetApp'' function for installing + ''cyjShiny'' package from GitHub.' + date_publication: '2022-05-08' + bug_reports: https://github.com/hyu-ub/BayesNetBP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesNetBP + url_git: '' +BayesNSGP: + version: 0.1.2 + title: Bayesian Analysis of Non-Stationary Gaussian Process Models + maintainer: Daniel Turek + description: Enables off-the-shelf functionality for fully Bayesian, nonstationary + Gaussian process modeling. The approach to nonstationary modeling involves a closed-form, + convolution-based covariance function with spatially-varying parameters; these + parameter processes can be specified either deterministically (using covariates + or basis functions) or stochastically (using approximate Gaussian processes). + Stationary Gaussian processes are a special case of our methodology, and we furthermore + implement approximate Gaussian process inference to account for very large spatial + data sets (Finley, et al (2017) ). Bayesian inference is carried + out using Markov chain Monte Carlo methods via the 'nimble' package, and posterior + prediction for the Gaussian process at unobserved locations is provided as a post-processing + step. + date_publication: '2022-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesNSGP + url_git: '' +BayesOrdDesign: + version: 0.1.2 + title: Bayesian Group Sequential Design for Ordinal Data + maintainer: Chengxue Zhong + description: |- + The proposed group-sequential trial design is based on Bayesian methods for ordinal endpoints, + including three methods, the proportional-odds-model (PO)-based, non-proportional-odds-model (NPO)-based, + and PO/NPO switch-model-based designs, which makes our proposed methods generic to be able to deal with + various scenarios. + Richard J. Barker, William A. Link (2013) . + Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L.Hofstetter (2018) . + Chengxue Zhong, Haitao Pan, Hongyu Miao (2021) . + date_publication: '2022-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesOrdDesign + url_git: '' +BayesPieceHazSelect: + version: 1.1.0 + title: |- + Variable Selection in a Hierarchical Bayesian Model for a Hazard + Function + maintainer: Andrew Chapple + description: |- + Fits a piecewise exponential hazard to survival data using a + Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive + formulation for the spatial dependency in the hazard rates for each piece. + This function uses Metropolis- Hastings-Green MCMC to allow the number of split + points to vary and also uses Stochastic Search Variable Selection to determine + what covariates drive the risk of the event. This function outputs trace plots + depicting the number of split points in the hazard and the number of variables + included in the hazard. The function saves all posterior quantities to the + desired path. + date_publication: '2017-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesPieceHazSelect + url_git: '' +bayesplay: + version: 0.9.3 + title: The Bayes Factor Playground + maintainer: Lincoln John Colling + description: |- + A lightweight modelling syntax for defining likelihoods and priors + and for computing Bayes factors for simple one parameter models. It includes + functionality for computing and plotting priors, likelihoods, and model + predictions. Additional functionality is included for computing and plotting + posteriors. + date_publication: '2023-04-13' + bug_reports: https://github.com/bayesplay/bayesplay/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesplay + url_git: https://github.com/bayesplay/bayesplay +bayesplot: + version: 1.11.1 + title: Plotting for Bayesian Models + maintainer: Jonah Gabry + description: |- + Plotting functions for posterior analysis, MCMC diagnostics, + prior and posterior predictive checks, and other visualizations + to support the applied Bayesian workflow advocated in + Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) . + The package is designed not only to provide convenient functionality + for users, but also a common set of functions that can be easily used by + developers working on a variety of R packages for Bayesian modeling, + particularly (but not exclusively) packages interfacing with 'Stan'. + date_publication: '2024-02-15' + bug_reports: https://github.com/stan-dev/bayesplot/issues/ + url: https://mc-stan.org/bayesplot/ + url_cran: https://CRAN.R-project.org/package=bayesplot + url_git: '' +bayespm: + version: 0.2.0 + title: Bayesian Statistical Process Monitoring + maintainer: Dimitrios Kiagias + description: 'The R-package bayespm implements Bayesian Statistical Process Control + and Monitoring (SPC/M) methodology. These methods utilize available prior information + and/or historical data, providing efficient online quality monitoring of a process, + in terms of identifying moderate/large transient shifts (i.e., outliers) or persistent + shifts of medium/small size in the process. These self-starting, sequentially + updated tools can also run under complete absence of any prior information. The + Predictive Control Charts (PCC) are introduced for the quality monitoring of data + from any discrete or continuous distribution that is a member of the regular exponential + family. The Predictive Ratio CUSUMs (PRC) are introduced for the Binomial, Poisson + and Normal data (a later version of the library will cover all the remaining distributions + from the regular exponential family). The PCC targets transient process shifts + of typically large size (a.k.a. outliers), while PRC is focused in detecting persistent + (structural) shifts that might be of medium or even small size. Apart from monitoring, + both PCC and PRC provide the sequentially updated posterior inference for the + monitored parameter. Bourazas K., Kiagias D. and Tsiamyrtzis P. (2022) "Predictive + Control Charts (PCC): A Bayesian approach in online monitoring of short runs" + , Bourazas K., Sobas F. and Tsiamyrtzis, P. + 2023. "Predictive ratio CUSUM (PRC): A Bayesian approach in online change point + detection of short runs" , Bourazas K., Sobas + F. and Tsiamyrtzis, P. 2023. "Design and properties of the predictive ratio cusum + (PRC) control charts" .' + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayespm + url_git: '' +bayesPO: + version: 0.5.0 + title: Bayesian Inference for Presence-Only Data + maintainer: Guido Alberti Moreira + description: |- + Presence-Only data is best modelled with a Point Process Model. + The work of Moreira and Gamerman (2022) provides + a way to use exact Bayesian inference to model this type of data, which is + implemented in this package. + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesPO + url_git: '' +bayesPop: + version: 11.0-2 + title: Probabilistic Population Projection + maintainer: Hana Sevcikova + description: Generating population projections for all countries of the world using + several probabilistic components, such as total fertility rate and life expectancy + (Raftery et al., 2012 ). + date_publication: '2025-02-22' + bug_reports: '' + url: https://bayespop.csss.washington.edu + url_cran: https://CRAN.R-project.org/package=bayesPop + url_git: '' +BayesPostEst: + version: 0.3.2 + title: Generate Postestimation Quantities for Bayesian MCMC Estimation + maintainer: Shana Scogin + description: An implementation of functions to generate and plot postestimation + quantities after estimating Bayesian regression models using Markov chain Monte + Carlo (MCMC). Functionality includes the estimation of the Precision-Recall curves + (see Beger, 2016 ), the implementation of the observed + values method of calculating predicted probabilities by Hanmer and Kalkan (2013) + , the implementation of the average value + method of calculating predicted probabilities (see King, Tomz, and Wittenberg, + 2000 ), and the generation and plotting of first differences + to summarize typical effects across covariates (see Long 1997, ISBN:9780803973749; + King, Tomz, and Wittenberg, 2000 ). This package can be used + with MCMC output generated by any Bayesian estimation tool including 'JAGS', 'BUGS', + 'MCMCpack', and 'Stan'. + date_publication: '2021-11-11' + bug_reports: https://github.com/ShanaScogin/BayesPostEst/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesPostEst + url_git: https://github.com/ShanaScogin/BayesPostEst +BayesPPD: + version: 1.1.3 + title: Bayesian Power Prior Design + maintainer: Yueqi Shen + description: |- + Bayesian power/type I error calculation and model fitting using + the power prior and the normalized power prior for generalized linear models. + Detailed examples of applying the package are available at . + Models for time-to-event outcomes are implemented in the R package 'BayesPPDSurv'. + The Bayesian clinical trial design methodology is described in Chen et al. (2011) + , and Psioda and Ibrahim (2019) + . The normalized power prior is described in Duan et al. (2006) + and Ibrahim et al. (2015) . + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesPPD + url_git: '' +BayesPPDSurv: + version: 1.0.3 + title: Bayesian Power Prior Design for Survival Data + maintainer: Yueqi Shen + description: |- + Bayesian power/type I error calculation and model fitting using + the power prior and the normalized power prior for proportional hazards models + with piecewise constant hazard. The methodology and examples of + applying the package are detailed in . + The Bayesian clinical trial design methodology is described in + Chen et al. (2011) , + and Psioda and Ibrahim (2019) . + The proportional hazards model with piecewise constant hazard is detailed in + Ibrahim et al. (2001) . + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesPPDSurv + url_git: '' +BayesProject: + version: '1.0' + title: Fast Projection Direction for Multivariate Changepoint Detection + maintainer: Georg Hahn + description: Implementations in 'cpp' of the BayesProject algorithm (see G. Hahn, + P. Fearnhead, I.A. Eckley (2020) ) which implements + a fast approach to compute a projection direction for multivariate changepoint + detection, as well as the sum-cusum and max-cusum methods, and a wild binary segmentation + wrapper for all algorithms. + date_publication: '2020-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesProject + url_git: '' +bayesQR: + version: '2.4' + title: Bayesian Quantile Regression + maintainer: Dries F. Benoit + description: Bayesian quantile regression using the asymmetric Laplace distribution, + both continuous as well as binary dependent variables are supported. The package + consists of implementations of the methods of Yu & Moyeed (2001) , + Benoit & Van den Poel (2012) and Al-Hamzawi, Yu & Benoit + (2012) . To speed up the calculations, the Markov + Chain Monte Carlo core of all algorithms is programmed in Fortran and called from + R. + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesQR + url_git: '' +bayesRecon: + version: 0.3.2 + title: Probabilistic Reconciliation via Conditioning + maintainer: Dario Azzimonti + description: |- + Provides methods for probabilistic reconciliation of hierarchical forecasts of time series. + The available methods include analytical Gaussian reconciliation (Corani et al., 2021) + , + MCMC reconciliation of count time series (Corani et al., 2024) + , + Bottom-Up Importance Sampling (Zambon et al., 2024) + , + methods for the reconciliation of mixed hierarchies (Mix-Cond and TD-cond) + (Zambon et al., 2024. The 40th Conference on Uncertainty in Artificial Intelligence, accepted). + date_publication: '2024-11-04' + bug_reports: https://github.com/IDSIA/bayesRecon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesRecon + url_git: https://github.com/IDSIA/bayesRecon +bayesreg: + version: '1.3' + title: Bayesian Regression Models with Global-Local Shrinkage Priors + maintainer: Daniel F. Schmidt + description: Fits linear or generalized linear regression models using Bayesian + global-local shrinkage prior hierarchies as described in Polson and Scott (2010) + . Provides an efficient implementation + of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, + Laplace, Student-t, Poisson or geometric distributed targets using the algorithms + summarized in Makalic and Schmidt (2016) . + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesreg + url_git: '' +Bayesrel: + version: 0.7.7 + title: Bayesian Reliability Estimation + maintainer: Julius M. Pfadt + description: |- + Functionality for reliability estimates. For 'unidimensional' tests: + Coefficient alpha, 'Guttman's' lambda-2/-4/-6, the Greatest lower + bound and coefficient omega_u ('unidimensional') in a Bayesian and a frequentist version. + For multidimensional tests: omega_t (total) and omega_h (hierarchical). + The results include confidence and credible intervals, the + probability of a coefficient being larger than a cutoff, + and a check for the factor models, necessary for the omega coefficients. + The method for the Bayesian 'unidimensional' estimates, except for omega_u, + is sampling from the posterior inverse 'Wishart' for the + covariance matrix based measures (see 'Murphy', 2007, + . + The Bayesian omegas (u, t, and h) are obtained by + 'Gibbs' sampling from the conditional posterior distributions of + (1) the single factor model, (2) the second-order factor model, (3) the bi-factor model, + (4) the correlated factor model + ('Lee', 2007, ). + date_publication: '2023-08-09' + bug_reports: https://github.com/juliuspfadt/Bayesrel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Bayesrel + url_git: https://github.com/juliuspfadt/Bayesrel +BayesRep: + version: 0.42.2 + title: Bayesian Analysis of Replication Studies + maintainer: Samuel Pawel + description: Provides tools for the analysis of replication studies using Bayes + factors (Pawel and Held, 2022) . + date_publication: '2023-06-29' + bug_reports: https://github.com/SamCH93/BayesRep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesRep + url_git: https://github.com/SamCH93/BayesRep +BayesRepDesign: + version: '0.42' + title: Bayesian Design of Replication Studies + maintainer: Samuel Pawel + description: Provides functionality for determining the sample size of replication + studies using Bayesian design approaches in the normal-normal hierarchical model + (Pawel et al., 2022) . + date_publication: '2023-05-03' + bug_reports: https://github.com/SamCH93/BayesRepDesign/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesRepDesign + url_git: https://github.com/SamCH93/BayesRepDesign +BayesReversePLLH: + version: '1.5' + title: Fits the Bayesian Piecewise Linear Log-Hazard Model + maintainer: Andrew G Chapple + description: Contains posterior samplers for the Bayesian piecewise linear log-hazard + and piecewise exponential hazard models, including Cox models. Posterior mean + restricted survival times are also computed for non-Cox an Cox models with only + treatment indicators. The ApproxMean() function can be used to estimate restricted + posterior mean survival times given a vector of patient covariates in the Cox + model. Functions included to return the posterior mean hazard and survival functions + for the piecewise exponential and piecewise linear log-hazard models. Chapple, + AG, Peak, T, Hemal, A (2020). Under Revision. + date_publication: '2022-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesReversePLLH + url_git: '' +BayesRGMM: + version: '2.2' + title: Bayesian Robust Generalized Mixed Models for Longitudinal Data + maintainer: Kuo-Jung Lee + description: To perform model estimation using MCMC algorithms with Bayesian methods + for incomplete longitudinal studies on binary and ordinal outcomes that are measured + repeatedly on subjects over time with drop-outs. Details about the method can + be found in the vignette or . + date_publication: '2022-05-10' + bug_reports: '' + url: https://sites.google.com/view/kuojunglee/r-packages + url_cran: https://CRAN.R-project.org/package=BayesRGMM + url_git: '' +bayesROE: + version: '0.2' + title: Bayesian Regions of Evidence + maintainer: Robert Miller + description: |- + Computation and visualization of Bayesian Regions of Evidence + to systematically evaluate the sensitivity of a superiority or + non-inferiority claim against any prior assumption of its assessors. + Methodological details are elaborated by Hoefler and Miller + (). Besides generic functions, the package also + provides an intuitive 'Shiny' application, that can be run in local R + environments. + date_publication: '2024-04-18' + bug_reports: https://github.com/waidschrat/bayesROE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesROE + url_git: https://github.com/waidschrat/bayesROE +BayesRS: + version: 0.1.3 + title: |- + Bayes Factors for Hierarchical Linear Models with Continuous + Predictors + maintainer: Mirko Thalmann + description: |- + Runs hierarchical linear Bayesian models. Samples from the posterior + distributions of model parameters in JAGS (Just Another Gibbs Sampler; + Plummer, 2017, ). Computes Bayes factors for group + parameters of interest with the Savage-Dickey density ratio (Wetzels, + Raaijmakers, Jakab, Wagenmakers, 2009, ). + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesRS + url_git: '' +bayesrules: + version: 0.0.2 + title: Datasets and Supplemental Functions from Bayes Rules! Book + maintainer: Mine Dogucu + description: |- + Provides datasets and functions used for analysis + and visualizations in the Bayes Rules! book (). + The package contains a set of functions that summarize and plot Bayesian models from some conjugate families + and another set of functions for evaluation of some Bayesian models. + date_publication: '2021-09-25' + bug_reports: https://github.com/bayes-rules/bayesrules/issues + url: https://bayes-rules.github.io/bayesrules/docs/ + url_cran: https://CRAN.R-project.org/package=bayesrules + url_git: https://github.com/bayes-rules/bayesrules/ +bayess: + version: '1.6' + title: Bayesian Essentials with R + maintainer: Jean-Michel Marin + description: |- + Allows the reenactment of the R programs used in + the book Bayesian Essentials with R without further programming. + R code being available as well, they can be modified by the user + to conduct one's own simulations. + Marin J.-M. and Robert C. P. (2014) . + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayess + url_git: https://github.com/jmm34/bayess +BayesS5: + version: '1.41' + title: |- + Bayesian Variable Selection Using Simplified Shotgun Stochastic + Search with Screening (S5) + maintainer: Minsuk Shin + description: |- + In p >> n settings, full posterior sampling using existing Markov chain Monte + Carlo (MCMC) algorithms is highly inefficient and often not feasible from a practical + perspective. To overcome this problem, we propose a scalable stochastic search algorithm that is called the Simplified Shotgun Stochastic Search (S5) and aimed at rapidly explore interesting regions of model space and finding the maximum a posteriori(MAP) model. Also, the S5 provides an approximation of posterior probability of each model (including the marginal inclusion probabilities). This algorithm is a part of an article titled "Scalable Bayesian Variable Selection Using Nonlocal Prior Densities in Ultrahigh-dimensional Settings" (2018) by Minsuk Shin, Anirban Bhattacharya, and Valen E. Johnson and "Nonlocal Functional Priors for Nonparametric Hypothesis Testing and High-dimensional Model Selection" (2020+) by Minsuk Shin and Anirban Bhattacharya. + date_publication: '2020-03-24' + bug_reports: '' + url: https://arxiv.org/abs/1507.07106v4 + url_cran: https://CRAN.R-project.org/package=BayesS5 + url_git: '' +BayesSampling: + version: 1.1.0 + title: Bayes Linear Estimators for Finite Population + maintainer: Pedro Soares Figueiredo + description: |- + Allows the user to apply the Bayes Linear approach to finite population with the Simple Random Sampling - BLE_SRS() - and + the Stratified Simple Random Sampling design - BLE_SSRS() - (both without replacement), to the Ratio estimator (using auxiliary + information) - BLE_Ratio() - and to categorical data - BLE_Categorical(). + The Bayes linear estimation approach is applied to a general linear regression model for finite population prediction in BLE_Reg() + and it is also possible to achieve the design based estimators using vague prior distributions. + Based on Gonçalves, K.C.M, Moura, F.A.S and Migon, H.S.(2014) . + date_publication: '2021-05-01' + bug_reports: '' + url: https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886 + url_cran: https://CRAN.R-project.org/package=BayesSampling + url_git: https://github.com/pedrosfig/BayesSampling +BayesSenMC: + version: 0.1.5 + title: |- + Different Models of Posterior Distributions of Adjusted Odds + Ratio + maintainer: Jinhui Yang + description: Generates different posterior distributions of adjusted odds ratio + under different priors of sensitivity and specificity, and plots the models for + comparison. It also provides estimations for the specifications of the models + using diagnostics of exposure status with a non-linear mixed effects model. It + implements the methods that are first proposed in + and . + date_publication: '2022-08-06' + bug_reports: https://github.com/formidify/BayesSenMC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesSenMC + url_git: https://github.com/formidify/BayesSenMC +BayesSUR: + version: 2.2-1 + title: |- + Bayesian Seemingly Unrelated Regression Models in + High-Dimensional Settings + maintainer: Zhi Zhao + description: Bayesian seemingly unrelated regression with general variable selection + and dense/sparse covariance matrix. The sparse seemingly unrelated regression + is described in Bottolo et al. (2021) , the software paper + is in Zhao et al. (2021) , and the model with random + effects is described in Zhao et al. (2024) . + date_publication: '2024-06-30' + bug_reports: https://github.com/mbant/BayesSUR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesSUR + url_git: https://github.com/mbant/BayesSUR +bayesSurv: + version: '3.8' + title: |- + Bayesian Survival Regression with Flexible Error and Random + Effects Distributions + maintainer: Arnošt Komárek + description: |- + Contains Bayesian implementations of the Mixed-Effects Accelerated Failure Time (MEAFT) models + for censored data. Those can be not only right-censored but also interval-censored, + doubly-interval-censored or misclassified interval-censored. The methods implemented in the package + have been published in Komárek and Lesaffre (2006, Stat. Modelling) , + Komárek, Lesaffre and Legrand (2007, Stat. in Medicine) , Komárek and Lesaffre (2007, Stat. Sinica) , Komárek and Lesaffre (2008, JASA) , + García-Zattera, Jara and Komárek (2016, Biometrics) . + date_publication: '2024-09-16' + bug_reports: '' + url: https://msekce.karlin.mff.cuni.cz/~komarek/ + url_cran: https://CRAN.R-project.org/package=bayesSurv + url_git: '' +BayesSurvival: + version: 0.2.0 + title: Bayesian Survival Analysis for Right Censored Data + maintainer: Stephanie van der Pas + description: |- + Performs unadjusted Bayesian survival analysis for right censored time-to-event data. The main function, BayesSurv(), computes the posterior mean and a credible band for the survival function and for the cumulative hazard, as well as the posterior mean for the hazard, starting from a piecewise exponential (histogram) prior with Gamma distributed heights that are either independent, or have a Markovian dependence structure. + A function, PlotBayesSurv(), is provided to easily create plots of the posterior means of the hazard, cumulative hazard and survival function, with a credible band accompanying the latter two. + The priors and samplers are described in more detail in Castillo and Van der Pas (2020) "Multiscale Bayesian survival analysis" . In that paper it is also shown that the credible bands for the survival function and the cumulative hazard can be considered confidence bands (under mild conditions) and thus offer reliable uncertainty quantification. + date_publication: '2021-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesSurvival + url_git: '' +BayesSurvive: + version: 0.0.2 + title: Bayesian Survival Models for High-Dimensional Data + maintainer: Zhi Zhao + description: An implementation of Bayesian survival models with graph-structured + selection priors for sparse identification of omics features predictive of survival + (Madjar et al., 2021 ) and its extension to use + a fixed graph via a Markov Random Field (MRF) prior for capturing known structure + of omics features, e.g. disease-specific pathways from the Kyoto Encyclopedia + of Genes and Genomes database. + date_publication: '2024-06-04' + bug_reports: https://github.com/ocbe-uio/BayesSurvive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesSurvive + url_git: https://github.com/ocbe-uio/BayesSurvive +bayest: + version: '1.5' + title: |- + Effect Size Targeted Bayesian Two-Sample t-Tests via Markov + Chain Monte Carlo in Gaussian Mixture Models + maintainer: Riko Kelter + description: Provides an Markov-Chain-Monte-Carlo algorithm for Bayesian t-tests + on the effect size. The underlying Gibbs sampler is based on a two-component Gaussian + mixture and approximates the posterior distributions of the effect size, the difference + of means and difference of standard deviations. A posterior analysis of the effect + size via the region of practical equivalence is provided, too. For more details + about the Gibbs sampler see Kelter (2019) . + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayest + url_git: '' +bayestestR: + version: 0.15.2 + title: |- + Understand and Describe Bayesian Models and Posterior + Distributions + maintainer: Dominique Makowski + description: |- + Provides utilities to describe posterior + distributions and Bayesian models. It includes point-estimates such as + Maximum A Posteriori (MAP), measures of dispersion (Highest Density + Interval - HDI; Kruschke, 2015 ) and + indices used for null-hypothesis testing (such as ROPE percentage, pd + and Bayes factors). References: Makowski et al. (2021) . + date_publication: '2025-02-07' + bug_reports: https://github.com/easystats/bayestestR/issues + url: https://easystats.github.io/bayestestR/ + url_cran: https://CRAN.R-project.org/package=bayestestR + url_git: '' +bayesTFR: + version: 7.4-4 + title: Bayesian Fertility Projection + maintainer: Hana Sevcikova + description: Making probabilistic projections of total fertility rate for all countries + of the world, using a Bayesian hierarchical model + . Subnational probabilistic projections are also supported + . + date_publication: '2024-11-08' + bug_reports: '' + url: https://bayespop.csss.washington.edu + url_cran: https://CRAN.R-project.org/package=bayesTFR + url_git: '' +BayesTools: + version: 0.2.18 + title: Tools for Bayesian Analyses + maintainer: František Bartoš + description: |- + Provides tools for conducting Bayesian analyses and Bayesian model averaging + (Kass and Raftery, 1995, , + Hoeting et al., 1999, ). The package contains + functions for creating a wide range of prior distribution objects, mixing posterior + samples from 'JAGS' and 'Stan' models, plotting posterior distributions, and etc... + The tools for working with prior distribution span from visualization, generating 'JAGS' + and 'bridgesampling' syntax to basic functions such as rng, quantile, and distribution functions. + date_publication: '2025-01-14' + bug_reports: https://github.com/FBartos/BayesTools/issues + url: https://fbartos.github.io/BayesTools/ + url_cran: https://CRAN.R-project.org/package=BayesTools + url_git: '' +BayesTree: + version: 0.3-1.5 + title: Bayesian Additive Regression Trees + maintainer: Robert McCulloch + description: |- + This is an implementation of BART:Bayesian Additive Regression Trees, + by Chipman, George, McCulloch (2010). + date_publication: '2024-01-30' + bug_reports: '' + url: https://www.rob-mcculloch.org + url_cran: https://CRAN.R-project.org/package=BayesTree + url_git: '' +BayesTreePrior: + version: 1.0.1 + title: Bayesian Tree Prior Simulation + maintainer: Alexia Jolicoeur-Martineau + description: Provides a way to simulate from the prior distribution of Bayesian + trees by Chipman et al. (1998) . The prior distribution of + Bayesian trees is highly dependent on the design matrix X, therefore using the + suggested hyperparameters by Chipman et al. (1998) is not + recommended and could lead to unexpected prior distribution. This work is part + of my master thesis (expected 2016). + date_publication: '2016-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesTreePrior + url_git: '' +BayesTwin: + version: '1.0' + title: Bayesian Analysis of Item-Level Twin Data + maintainer: Inga Schwabe + description: Bayesian analysis of item-level hierarchical twin data using an integrated + item response theory model. Analyses are based on Schwabe & van den Berg (2014) + , Molenaar & Dolan (2014) , + Schwabe, Jonker & van den Berg (2016) and Schwabe, + Boomsma & van den Berg (2016) . + date_publication: '2017-06-26' + bug_reports: https://github.com/ingaschwabe/BayesTwin + url: http://www.ingaschwabe.com + url_cran: https://CRAN.R-project.org/package=BayesTwin + url_git: '' +BayesVarSel: + version: 2.4.5 + title: |- + Bayes Factors, Model Choice and Variable Selection in Linear + Models + maintainer: Gonzalo Garcia-Donato + description: |- + Bayes factors and posterior probabilities in Linear models, + aimed at provide a formal Bayesian answer to testing and variable + selection problems. + date_publication: '2025-01-08' + bug_reports: https://github.com/comodin19/BayesVarSel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayesVarSel + url_git: https://github.com/comodin19/BayesVarSel +bayesvl: + version: 0.8.5 + title: |- + Visually Learning the Graphical Structure of Bayesian Networks + and Performing MCMC with 'Stan' + maintainer: Viet-Phuong La + description: 'Provides users with its associated functions for pedagogical purposes + in visually learning Bayesian networks and Markov chain Monte Carlo (MCMC) computations. + It enables users to: a) Create and examine the (starting) graphical structure + of Bayesian networks; b) Create random Bayesian networks using a dataset with + customized constraints; c) Generate ''Stan'' code for structures of Bayesian networks + for sampling the data and learning parameters; d) Plot the network graphs; e) + Perform Markov chain Monte Carlo computations and produce graphs for posteriors + checks. The package refers to one reference item, which describes the methods + and algorithms: Vuong, Quan-Hoang and La, Viet-Phuong (2019) + The ''bayesvl'' R package. Open Science Framework (May 18).' + date_publication: '2019-05-24' + bug_reports: https://github.com/sshpa/bayesvl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayesvl + url_git: https://github.com/sshpa/bayesvl +bayesWatch: + version: 0.1.3 + title: |- + Bayesian Change-Point Detection for Process Monitoring with + Fault Detection + maintainer: Alexander C. Murph + description: 'Bayes Watch fits an array of Gaussian Graphical Mixture Models to + groupings of homogeneous data in time, called regimes, which are modeled as the + observed states of a Markov process with unknown transition probabilities. In + doing so, Bayes Watch defines a posterior distribution on a vector of regime assignments, + which gives meaningful expressions on the probability of every possible change-point. Bayes + Watch also allows for an effective and efficient fault detection system that assesses + what features in the data where the most responsible for a given change-point. For + further details, see: Alexander C. Murph et al. (2023) .' + date_publication: '2024-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesWatch + url_git: '' +BayesX: + version: 0.3-3 + title: R Utilities Accompanying the Software Package BayesX + maintainer: Nikolaus Umlauf + description: |- + Functions for exploring and visualising estimation results + obtained with BayesX, a free software for estimating structured additive + regression models (). In addition, + functions that allow to read, write and manipulate map objects that are required in spatial + analyses performed with BayesX. + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BayesX + url_git: '' +BayesXsrc: + version: 3.0-5 + title: Distribution of the 'BayesX' C++ Sources + maintainer: Nikolaus Umlauf + description: |- + 'BayesX' performs Bayesian inference in structured additive regression (STAR) models. + The R package BayesXsrc provides the 'BayesX' command line tool for easy installation. + A convenient R interface is provided in package R2BayesX. + date_publication: '2024-03-15' + bug_reports: '' + url: https://www.uni-goettingen.de/de/bayesx/550513.html + url_cran: https://CRAN.R-project.org/package=BayesXsrc + url_git: '' +bayesZIB: + version: 0.0.5 + title: Bayesian Zero-Inflated Bernoulli Regression Model + maintainer: David Moriña Soler + description: |- + Fits a Bayesian zero-inflated Bernoulli regression model handling (potentially) different covariates for the zero-inflated + and non zero-inflated parts. See Moriña D, Puig P, Navarro A. (2021) . + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayesZIB + url_git: '' +bayfoxr: + version: 0.0.1 + title: Global Bayesian Foraminifera Core Top Calibration + maintainer: Steven Malevich + description: |- + A Bayesian, global planktic foraminifera core top calibration to + modern sea-surface temperatures. Includes four calibration models, + considering species-specific calibration parameters and seasonality. + date_publication: '2019-02-06' + bug_reports: https://github.com/brews/bayfoxr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bayfoxr + url_git: https://github.com/brews/bayfoxr/ +baygel: + version: 0.3.0 + title: |- + Bayesian Shrinkage Estimators for Precision Matrices in Gaussian + Graphical Models + maintainer: Jarod Smith + description: 'This R package offers block Gibbs samplers for the Bayesian (adaptive) + graphical lasso, ridge, and naive elastic net priors. These samplers facilitate + the simulation of the posterior distribution of precision matrices for Gaussian + distributed data and were originally proposed by: Wang (2012) ; + Smith et al. (2022) and Smith et al. (2023) , + respectively.' + date_publication: '2023-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=baygel + url_git: https://github.com/Jarod-Smithy/baygel +BayLum: + version: 0.3.2 + title: |- + Chronological Bayesian Models Integrating Optically Stimulated + Luminescence and Radiocarbon Age Dating + maintainer: Anne Philippe + description: 'Bayesian analysis of luminescence data and C-14 age estimates. Bayesian + models are based on the following publications: Combes, B. & Philippe, A. (2017) + and Combes et al. (2015) . + This includes, amongst others, data import, export, application of age models + and palaeodose model.' + date_publication: '2024-06-16' + bug_reports: https://github.com/crp2a/BayLum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BayLum + url_git: '' +bayMDS: + version: '2.0' + title: Bayesian Multidimensional Scaling and Choice of Dimension + maintainer: Man-Suk Oh + description: Bayesian approach to multidimensional scaling. The package consists + of implementations of the methods of Oh and Raftery (2001) . + date_publication: '2022-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bayMDS + url_git: '' +baymedr: + version: 0.1.1 + title: Computation of Bayes Factors for Common Biomedical Designs + maintainer: Maximilian Linde + description: |- + BAYesian inference for MEDical designs in R. Functions for the + computation of Bayes factors for common biomedical research designs. + Implemented are functions to test the equivalence (equiv_bf), + non-inferiority (infer_bf), and superiority (super_bf) of an experimental + group compared to a control group on a continuous outcome measure. Bayes + factors for these three tests can be computed based on raw data (x, y) or + summary statistics (n_x, n_y, mean_x, mean_y, sd_x, sd_y [or ci_margin + and ci_level]). + date_publication: '2021-03-28' + bug_reports: https://github.com/maxlinde/baymedr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=baymedr + url_git: https://github.com/maxlinde/baymedr +baystability: + version: 0.2.0 + title: |- + Bayesian Stability Analysis of Genotype by Environment + Interaction (GEI) + maintainer: Muhammad Yaseen + description: Performs general Bayesian estimation method of linear–bilinear models + for genotype × environment interaction. The method is explained in Perez-Elizalde, + S., Jarquin, D., and Crossa, J. (2011) (). + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=baystability + url_git: '' +BAYSTAR: + version: 0.2-10 + title: On Bayesian Analysis of Threshold Autoregressive Models + maintainer: Edward M.H. Lin + description: Fit two-regime threshold autoregressive (TAR) models by Markov chain + Monte Carlo methods. + date_publication: '2022-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BAYSTAR + url_git: '' +baytrends: + version: 2.0.12 + title: Long Term Water Quality Trend Analysis + maintainer: Erik W Leppo + description: |- + Enable users to evaluate long-term trends using a Generalized + Additive Modeling (GAM) approach. The model development includes selecting a + GAM structure to describe nonlinear seasonally-varying changes over time, + incorporation of hydrologic variability via either a river flow or salinity, + the use of an intervention to deal with method or laboratory changes + suspected to impact data values, and representation of left- and + interval-censored data. The approach has been applied to water quality data + in the Chesapeake Bay, a major estuary on the east coast of the United + States to provide insights to a range of management- and research-focused + questions. Methodology described in Murphy (2019) + . + date_publication: '2024-07-26' + bug_reports: https://github.com/tetratech/baytrends/issues + url: https://tetratech.github.io/baytrends/ + url_cran: https://CRAN.R-project.org/package=baytrends + url_git: https://github.com/tetratech/baytrends +bazar: + version: 1.0.11 + title: Miscellaneous Basic Functions + maintainer: Paul Poncet + description: |- + A collection of miscellaneous functions for + copying objects to the clipboard ('Copy'); + manipulating strings ('concat', 'mgsub', 'trim', 'verlan'); + loading or showing packages ('library_with_dep', 'require_with_dep', + 'sessionPackages'); + creating or testing for named lists ('nlist', 'as.nlist', 'is.nlist'), + formulas ('is.formula'), empty objects ('as.empty', 'is.empty'), + whole numbers ('as.wholenumber', 'is.wholenumber'); + testing for equality ('almost.equal', 'almost.zero') and computing + uniqueness ('almost.unique'); + getting modified versions of usual functions ('rle2', 'sumNA'); + making a pause or a stop ('pause', 'stopif'); + converting into a function ('as.fun'); + providing a C like ternary operator ('condition %?% true %:% false'); + finding packages and functions ('get_all_pkgs', 'get_all_funs'); + and others ('erase', '%nin%', 'unwhich', 'top', 'bot', 'normalize'). + date_publication: '2019-03-15' + bug_reports: https://github.com/paulponcet/bazar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bazar + url_git: https://github.com/paulponcet/bazar +BB: + version: 2019.10-1 + title: Solving and Optimizing Large-Scale Nonlinear Systems + maintainer: Paul Gilbert + description: |- + Barzilai-Borwein spectral methods for solving nonlinear + system of equations, and for optimizing nonlinear objective + functions subject to simple constraints. A tutorial style + introduction to this package is available in a vignette on the + CRAN download page or, when the package is loaded in an R + session, with vignette("BB"). + date_publication: '2019-10-18' + bug_reports: '' + url: http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.html + url_cran: https://CRAN.R-project.org/package=BB + url_git: '' +bbdetection: + version: '1.0' + title: Identification of Bull and Bear States of the Market + maintainer: Valeriy Zakamulin + description: |- + Implements two algorithms of detecting Bull and Bear markets in stock prices: the algorithm of Pagan and Sossounov (2002, ) and the algorithm of Lunde and Timmermann (2004, ). + The package also contains functions for printing out the dating of the Bull and Bear states of the market, the descriptive statistics of the states, and functions for plotting the results. + For the sake of convenience, the package includes the monthly and daily data on the prices (not adjusted for dividends) of the S&P 500 stock market index. + date_publication: '2021-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bbdetection + url_git: '' +BBEST: + version: 0.1-8 + title: Bayesian Estimation of Incoherent Neutron Scattering Backgrounds + maintainer: Anton Gagin + description: |- + We implemented a Bayesian-statistics approach for + subtraction of incoherent scattering from neutron total-scattering data. + In this approach, the estimated background signal associated with + incoherent scattering maximizes the posterior probability, which combines + the likelihood of this signal in reciprocal and real spaces with the prior + that favors smooth lines. The description of the corresponding approach + could be found at Gagin and Levin (2014) . + date_publication: '2020-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BBEST + url_git: '' +BBI: + version: 0.3.0 + title: Benthic Biotic Indices Calculation from Composition Data + maintainer: Tristan Cordier + description: |- + Set of functions to calculate Benthic Biotic Indices from + composition data, obtained whether from morphotaxonomic inventories or + sequencing data. Based on reference ecological weights publicly available for + a set of commonly used marine biotic indices, such as AMBI (A Marine Biotic Index, Borja et al., 2000) + NSI (Norwegian Sensitivity Index) and ISI (Indicator Species Index) (Rygg 2013, ). It provides the ecological quality status of the samples based on each BBI as well as the normalized Ecological Quality Ratio. + date_publication: '2018-10-17' + bug_reports: https://github.com/trtcrd/BBI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BBI + url_git: https://github.com/trtcrd/BBI +bbk: + version: 0.6.0 + title: Client for Central Bank APIs + maintainer: Maximilian Mücke + description: |- + A client for retrieving data and metadata from major central + bank APIs. It supports access to the 'Bundesbank SDMX Web Service API' + (), + the 'Swiss National Bank Data Portal' (), and the + 'European Central Bank Data Portal API' + (). + date_publication: '2025-02-02' + bug_reports: https://github.com/m-muecke/bbk/issues + url: https://m-muecke.github.io/bbk/ + url_cran: https://CRAN.R-project.org/package=bbk + url_git: https://github.com/m-muecke/bbk +bbknnR: + version: 1.1.1 + title: Perform Batch Balanced KNN in R + maintainer: Yuchen Li + description: A fast and intuitive batch effect removal tool for single-cell data. + BBKNN is originally used in the 'scanpy' python package, and now can be used with + 'Seurat' seamlessly. + date_publication: '2024-02-13' + bug_reports: https://github.com/ycli1995/bbknnR/issues + url: https://bbknn.readthedocs.io/en/latest/ + url_cran: https://CRAN.R-project.org/package=bbknnR + url_git: https://github.com/ycli1995/bbknnR +bbl: + version: 1.0.0 + title: Boltzmann Bayes Learner + maintainer: Jun Woo + description: |- + Supervised learning using Boltzmann Bayes model inference, + which extends naive Bayes model to include interactions. Enables + classification of data into multiple response groups based on a large + number of discrete predictors that can take factor values of + heterogeneous levels. Either pseudo-likelihood or mean field + inference can be used with L2 regularization, cross-validation, and + prediction on new data. + . + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bbl + url_git: '' +BBmisc: + version: '1.13' + title: Miscellaneous Helper Functions for B. Bischl + maintainer: Bernd Bischl + description: |- + Miscellaneous helper functions for and from B. Bischl and + some other guys, mainly for package development. + date_publication: '2022-09-29' + bug_reports: https://github.com/berndbischl/BBmisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BBmisc + url_git: https://github.com/berndbischl/BBmisc +bbmix: + version: 1.0.0 + title: Bayesian Model for Genotyping using RNA-Seq + maintainer: Elena Vigorito + description: 'The method models RNA-seq reads using a mixture of 3 beta-binomial + distributions to generate posterior probabilities for genotyping bi-allelic single + nucleotide polymorphisms. Elena Vigorito, Anne Barton, Costantino Pitzalis, Myles + J. Lewis and Chris Wallace (2023) "BBmix: + a Bayesian beta-binomial mixture model for accurate genotyping from RNA-sequencing."' + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bbmix + url_git: '' +bbmle: + version: 1.0.25.1 + title: Tools for General Maximum Likelihood Estimation + maintainer: Ben Bolker + description: Methods and functions for fitting maximum likelihood models in R. This + package modifies and extends the 'mle' classes in the 'stats4' package. + date_publication: '2023-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bbmle + url_git: https://github.com/bbolker/bbmle +bbnet: + version: 1.1.0 + title: Create Simple Predictive Models on Bayesian Belief Networks + maintainer: Victoria Dominguez Almela + description: A system to build, visualise and evaluate Bayesian belief networks. + The methods are described in Stafford et al. (2015) . + date_publication: '2025-01-23' + bug_reports: https://github.com/vda1r22/bbnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bbnet + url_git: https://github.com/vda1r22/bbnet +bbotk: + version: 1.5.0 + title: Black-Box Optimization Toolkit + maintainer: Marc Becker + description: |- + Features highly configurable search spaces via the 'paradox' + package and optimizes every user-defined objective function. The + package includes several optimization algorithms e.g. Random Search, + Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband + (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', + 'mlr3fselect' and 'miesmuschel'. + date_publication: '2024-12-17' + bug_reports: https://github.com/mlr-org/bbotk/issues + url: https://bbotk.mlr-org.com + url_cran: https://CRAN.R-project.org/package=bbotk + url_git: https://github.com/mlr-org/bbotk +bbreg: + version: 2.0.2 + title: |- + Bessel and Beta Regressions via Expectation-Maximization + Algorithm for Continuous Bounded Data + maintainer: Vinicius Mayrink + description: Functions to fit, via Expectation-Maximization (EM) algorithm, the + Bessel and Beta regressions to a data set with a bounded continuous response variable. + The Bessel regression is a new and robust approach proposed in the literature. + The EM version for the well known Beta regression is another major contribution + of this package. See details in the references Barreto-Souza, Mayrink and Simas + (2022) and Barreto-Souza, Mayrink and Simas (2020) . + date_publication: '2022-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bbreg + url_git: '' +bbw: + version: 0.3.0 + title: Blocked Weighted Bootstrap + maintainer: Ernest Guevarra + description: |- + The blocked weighted bootstrap (BBW) is an estimation technique + for use with data from two-stage cluster sampled surveys in which either + prior weighting (e.g. population-proportional sampling or PPS as used in + Standardized Monitoring and Assessment of Relief and Transitions or SMART + surveys) or posterior weighting (e.g. as used in rapid assessment method or + RAM and simple spatial sampling method or S3M surveys) is implemented. See + Cameron et al (2008) for application of + bootstrap to cluster samples. See Aaron et al (2016) + and Aaron et al (2016) + for application of the blocked weighted + bootstrap to estimate indicators from two-stage cluster sampled surveys. + date_publication: '2025-01-16' + bug_reports: https://github.com/rapidsurveys/bbw/issues + url: https://rapidsurveys.io/bbw/ + url_cran: https://CRAN.R-project.org/package=bbw + url_git: https://github.com/rapidsurveys/bbw +bc3net: + version: 1.0.4 + title: Gene Regulatory Network Inference with Bc3net + maintainer: Ricardo de Matos Simoes + description: 'Implementation of the BC3NET algorithm for gene regulatory network + inference (de Matos Simoes and Frank Emmert-Streib, Bagging Statistical Network + Inference from Large-Scale Gene Expression Data, PLoS ONE 7(3): e33624, ).' + date_publication: '2016-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bc3net + url_git: '' +BCA1SG: + version: 0.1.0 + title: |- + Block Coordinate Ascent with One-Step Generalized Rosen + Algorithm + maintainer: Wang Yudong + description: Implementing the Block Coordinate Ascent with One-Step Generalized + Rosen (BCA1SG) algorithm on the semiparametric models for panel count data, interval-censored + survival data, and degradation data. A comprehensive description of the BCA1SG + algorithm can be found in Wang et al. (2020) . + For details of the semiparametric models for panel count data, interval-censored + survival data, and degradation data, please see Wellner and Zhang (2007) , + Huang and Wellner (1997) , and Wang and Xu (2010) , + respectively. + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCA1SG + url_git: '' +bcaboot: + version: 0.2-3 + title: Bias Corrected Bootstrap Confidence Intervals + maintainer: Balasubramanian Narasimhan + description: Computation of bootstrap confidence intervals in an almost automatic + fashion as described in Efron and Narasimhan (2020, ). + date_publication: '2021-05-09' + bug_reports: https://github.com/bnaras/bcaboot/issues + url: https://bnaras.github.io/bcaboot/ + url_cran: https://CRAN.R-project.org/package=bcaboot + url_git: https://github.com/bnaras/bcaboot +BCBCSF: + version: 1.0-1 + title: Bias-Corrected Bayesian Classification with Selected Features + maintainer: Longhai Li + description: Fully Bayesian Classification with a subset of high-dimensional features, + such as expression levels of genes. The data are modeled with a hierarchical Bayesian + models using heavy-tailed t distributions as priors. When a large number of features + are available, one may like to select only a subset of features to use, typically + those features strongly correlated with the response in training cases. Such a + feature selection procedure is however invalid since the relationship between + the response and the features has be exaggerated by feature selection. This package + provides a way to avoid this bias and yield better-calibrated predictions for + future cases when one uses F-statistic to select features. + date_publication: '2015-09-26' + bug_reports: '' + url: http://math.usask.ca/~longhai + url_cran: https://CRAN.R-project.org/package=BCBCSF + url_git: '' +bcc: + version: '1.5' + title: Beta Control Charts + maintainer: Daniel Cerqueira + description: 'Applies Beta Control Charts to defined values. The Beta Chart presents + control limits based on the Beta probability distribution, making it suitable + for monitoring fraction data from a Binomial distribution as a replacement for + p-Charts. The Beta Chart has been applied in three real studies and compared with + control limits from three different schemes. The comparative analysis showed that: + (i) the Beta approximation to the Binomial distribution is more appropriate for + values confined within the [0, 1] interval; and (ii) the proposed charts are more + sensitive to the average run length (ARL) in both in-control and out-of-control + process monitoring. Overall, the Beta Charts outperform the Shewhart control charts + in monitoring fraction data. For more details, see Ângelo Márcio Oliveira Sant’Anna + and Carla Schwengber ten Caten (2012) .' + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcc + url_git: '' +BCC1997: + version: 0.1.1 + title: Calculation of Option Prices Based on a Universal Solution + maintainer: Haoran Zhang + description: Calculates the prices of European options based on the universal solution + provided by Bakshi, Cao and Chen (1997) . + This solution considers stochastic volatility, stochastic interest and random + jumps. Please cite their work if this package is used. + date_publication: '2017-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCC1997 + url_git: '' +BCClong: + version: 1.0.3 + title: Bayesian Consensus Clustering for Multiple Longitudinal Features + maintainer: Zhiwen Tan + description: |- + It is very common nowadays for a study to collect multiple + features and appropriately integrating multiple longitudinal features + simultaneously for defining individual clusters becomes increasingly + crucial to understanding population heterogeneity and predicting + future outcomes. 'BCClong' implements a Bayesian consensus clustering + (BCC) model for multiple longitudinal features via a generalized + linear mixed model. Compared to existing packages, several key + features make the 'BCClong' package appealing: (a) it allows + simultaneous clustering of mixed-type (e.g., continuous, discrete and + categorical) longitudinal features, (b) it allows each longitudinal + feature to be collected from different sources with measurements taken + at distinct sets of time points (known as irregularly sampled + longitudinal data), (c) it relaxes the assumption that all features + have the same clustering structure by estimating the feature-specific + (local) clusterings and consensus (global) clustering. + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCClong + url_git: '' +bccp: + version: 0.5.0 + title: Bias Correction under Censoring Plan + maintainer: Mahdi Teimouri + description: |- + Developed for the following tasks. Simulating, computing maximum likelihood + estimator, computing the Fisher information matrix, computing goodness-of-fit measures, + and correcting bias of the ML estimator for a wide range of distributions fitted to units + placed on progressive type-I interval censoring and progressive type-II censoring plans. + The methods of Cox and Snell (1968) and + bootstrap method for computing the bias-corrected maximum likelihood estimator. + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bccp + url_git: '' +BCDAG: + version: 1.1.3 + title: |- + Bayesian Structure and Causal Learning of Gaussian Directed + Graphs + maintainer: Alessandro Mascaro + description: |- + A collection of functions for structure learning of causal networks and estimation of joint causal effects from observational Gaussian data. Main algorithm consists of a Markov chain Monte Carlo scheme for posterior inference of causal structures, parameters and causal effects between variables. + References: + F. Castelletti and A. Mascaro (2021) , + F. Castelletti and A. Mascaro (2022) . + date_publication: '2025-02-28' + bug_reports: https://github.com/alesmascaro/BCDAG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BCDAG + url_git: https://github.com/alesmascaro/BCDAG +bcdata: + version: 0.5.0 + title: Search and Retrieve Data from the BC Data Catalogue + maintainer: Andy Teucher + description: |- + Search, query, and download tabular and + 'geospatial' data from the British Columbia Data Catalogue + (). Search catalogue data records + based on keywords, data licence, sector, data format, and B.C. + government organization. View metadata directly in R, download many + data formats, and query 'geospatial' data available via the B.C. + government Web Feature Service ('WFS') using 'dplyr' syntax. + date_publication: '2024-12-12' + bug_reports: https://github.com/bcgov/bcdata/issues + url: https://bcgov.github.io/bcdata/ + url_cran: https://CRAN.R-project.org/package=bcdata + url_git: https://github.com/bcgov/bcdata/ +BCDating: + version: 0.9.8 + title: Business Cycle Dating and Plotting Tools + maintainer: Majid Einian + description: Tools for Dating Business Cycles using Harding-Pagan (Quarterly Bry-Boschan) + method and various plotting features. + date_publication: '2019-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCDating + url_git: '' +BcDiag: + version: 1.0.10 + title: Diagnostics Plots for Bicluster Data + maintainer: Ewoud De Troyer + description: |- + Diagnostic tools based on two-way + anova and median-polish residual plots for Bicluster output + obtained from packages; "biclust" by Kaiser et al.(2008),"isa2" + by Csardi et al. (2010) and "fabia" by Hochreiter et al. + (2010). Moreover, It provides visualization tools for bicluster + output and corresponding non-bicluster rows- or columns + outcomes. It has also extended the idea of Kaiser et al.(2008) + which is, extracting bicluster output in a text format, by + adding two bicluster methods from the fabia and isa2 R + packages. + date_publication: '2015-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BcDiag + url_git: '' +BCEA: + version: 2.4.7 + title: Bayesian Cost Effectiveness Analysis + maintainer: Gianluca Baio + description: |- + Produces an economic evaluation of a sample of suitable variables of + cost and effectiveness / utility for two or more interventions, + e.g. from a Bayesian model in the form of MCMC simulations. + This package computes the most cost-effective alternative and + produces graphical summaries and probabilistic sensitivity analysis, + see Baio et al (2017) . + date_publication: '2025-01-14' + bug_reports: https://github.com/n8thangreen/BCEA/issues/ + url: https://gianluca.statistica.it/software/bcea/ + url_cran: https://CRAN.R-project.org/package=BCEA + url_git: https://github.com/giabaio/BCEA/ +BCEE: + version: 1.3.2 + title: The Bayesian Causal Effect Estimation Algorithm + maintainer: Denis Talbot + description: |- + A Bayesian model averaging approach to causal effect estimation + based on the BCEE algorithm. Currently supports binary or continuous + exposures and outcomes. For more details, see + Talbot et al. (2015) + Talbot and Beaudoin (2022) . + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCEE + url_git: '' +bcf: + version: 2.0.2 + title: Causal Inference using Bayesian Causal Forests + maintainer: Jared S. Murray + description: Causal inference for a binary treatment and continuous outcome using + Bayesian Causal Forests. See Hahn, Murray and Carvalho (2020) + for additional information. This implementation relies on code originally accompanying + Pratola et. al. (2013) . + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcf + url_git: '' +bcfrailph: + version: 0.1.1 + title: Semiparametric Bivariate Correlated Frailty Models Fit + maintainer: Mesfin Tsegaye + description: |- + Fit and simulate a semiparametric bivariate correlated frailty models with proportional + hazard structure. Frailty distributions, such as gamma and lognormal models are + supported. Bivariate gamma fit is obtained using the approach given in Iachine (1995) and + lognormal fit is based on the approach by + Ripatti and Palmgren (2000) . + date_publication: '2022-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcfrailph + url_git: '' +bcfrailphdv: + version: 0.1.1 + title: Bivariate Correlated Frailty Models with Varied Variances + maintainer: Mesfin Tsegaye + description: |- + Fit and simulate bivariate correlated frailty models with + proportional hazard structure. Frailty distributions, such as gamma and + lognormal models are supported for semiparametric procedures. Frailty variances of the two subjects + can be varied or equal. Details on the models are available in book of + Wienke (2011,ISBN:978-1-4200-7388-1). Bivariate gamma fit is obtained using the approach given + in Iachine (1995) with modifications. Lognormal fit is based on the approach + by Ripatti and Palmgren (2000) . Frailty distributions, + such as gamma, inverse gaussian and power variance frailty models are supported for parametric approach. + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcfrailphdv + url_git: '' +bcgam: + version: '1.0' + title: Bayesian Constrained Generalised Linear Models + maintainer: Cristian Oliva-Aviles + description: |- + Fits generalised partial linear regression models using a Bayesian approach, where shape and + smoothness constraints are imposed on nonparametrically modelled predictors through shape-restricted splines, and + no constraints are imposed on optional parametrically modelled covariates. See Meyer et al. (2011) + for more details. IMPORTANT: before installing 'bcgam', you need to install 'Rtools' (Windows) or 'Xcode' (Mac OS X). These are + required for the correct installation of 'nimble' (). + date_publication: '2018-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcgam + url_git: '' +BCgee: + version: 0.1.1 + title: |- + Bias-Corrected Estimates for Generalized Linear Models for + Dependent Data + maintainer: Nicola Lunardon + description: Provides bias-corrected estimates for the regression coefficients of + a marginal model estimated with generalized estimating equations. Details about + the bias formula used are in Lunardon, N., Scharfstein, D. (2017) . + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCgee + url_git: '' +BCHM: + version: '1.00' + title: Clinical Trial Calculation Based on BCHM Design + maintainer: J. Jack Lee + description: Users can estimate the treatment effect for multiple subgroups basket + trials based on the Bayesian Cluster Hierarchical Model (BCHM). In this model, + a Bayesian non-parametric method is applied to dynamically calculate the number + of clusters by conducting the multiple cluster classification based on subgroup + outcomes. Hierarchical model is used to compute the posterior probability of treatment + effect with the borrowing strength determined by the Bayesian non-parametric clustering + and the similarities between subgroups. To use this package, 'JAGS' software and + 'rjags' package are required, and users need to pre-install them. + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCHM + url_git: '' +Bchron: + version: 4.7.6 + title: |- + Radiocarbon Dating, Age-Depth Modelling, Relative Sea Level Rate + Estimation, and Non-Parametric Phase Modelling + maintainer: Andrew Parnell + description: |- + Enables quick calibration of radiocarbon dates under various + calibration curves (including user generated ones); age-depth modelling + as per the algorithm of Haslett and Parnell (2008) ; Relative sea level + rate estimation incorporating time uncertainty in polynomial regression + models (Parnell and Gehrels 2015) ; non-parametric phase modelling via + Gaussian mixtures as a means to determine the activity of a site + (and as an alternative to the Oxcal function SUM; currently + unpublished), and reverse calibration of dates from calibrated into + un-calibrated years (also unpublished). + date_publication: '2021-06-10' + bug_reports: https://github.com/andrewcparnell/Bchron/issues + url: https://andrewcparnell.github.io/Bchron/ + url_cran: https://CRAN.R-project.org/package=Bchron + url_git: '' +BClustLonG: + version: 0.1.3 + title: |- + A Dirichlet Process Mixture Model for Clustering Longitudinal + Gene Expression Data + maintainer: Jiehuan Sun + description: |- + Many clustering methods have been proposed, but + most of them cannot work for longitudinal gene expression data. + 'BClustLonG' is a package that allows us to perform clustering analysis for + longitudinal gene expression data. It adopts a linear-mixed effects framework + to model the trajectory of genes over time, while clustering is jointly + conducted based on the regression coefficients obtained from all genes. + To account for the correlations among genes and alleviate the + high dimensionality challenges, factor analysis models are adopted + for the regression coefficients. The Dirichlet process prior distribution + is utilized for the means of the regression coefficients to induce clustering. + This package allows users to specify which variables to use for clustering + (intercepts or slopes or both) and whether a factor analysis model is desired. + More details about this method can be found in Jiehuan Sun, et al. (2017) . + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BClustLonG + url_git: '' +bcmaps: + version: 2.2.1 + title: Map Layers and Spatial Utilities for British Columbia + maintainer: Andy Teucher + description: |- + Various layers of B.C., including administrative boundaries, + natural resource management boundaries, census boundaries etc. All + layers are available in BC Albers + () equal-area projection, + which is the B.C. government standard. The layers are sourced from the + British Columbia and Canadian government under open licenses, + including B.C. Data Catalogue (), the + Government of Canada Open Data Portal + (), and Statistics Canada + (). + date_publication: '2024-12-21' + bug_reports: https://github.com/bcgov/bcmaps/issues + url: https://bcgov.github.io/bcmaps/ + url_cran: https://CRAN.R-project.org/package=bcmaps + url_git: https://github.com/bcgov/bcmaps +bcmixed: + version: 0.1.4 + title: Mixed Effect Model with the Box-Cox Transformation + maintainer: Kazushi Maruo + description: |- + Inference on the marginal model of the mixed effect model with + the Box-Cox transformation and on the model median differences between + treatment groups for longitudinal randomized clinical trials. These + statistical methods are proposed by Maruo et al. (2017) + . + date_publication: '2020-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcmixed + url_git: '' +bcpa: + version: 1.3.2 + title: Behavioral Change Point Analysis of Animal Movement + maintainer: Eliezer Gurarie + description: |- + The Behavioral Change Point Analysis (BCPA) is a method of + identifying hidden shifts in the underlying parameters of a time series, + developed specifically to be applied to animal movement data which is + irregularly sampled. The method is based on: E. Gurarie, R. Andrews and + K. Laidre A novel method for identifying behavioural changes in animal + movement data (2009) Ecology Letters 12:5 395-408. A development version is + on . NOTE: the BCPA method may be useful + for any univariate, irregularly sampled Gaussian time-series, but animal + movement analysts are encouraged to apply correlated velocity change point + analysis as implemented in the smoove package, as of this writing on GitHub + at . An example of a univariate analysis + is provided in the UnivariateBCPA vignette. + date_publication: '2022-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bcpa + url_git: '' +bcputility: + version: 0.4.3 + title: Wrapper for SQL Server bcp Utility + maintainer: Thomas Roh + description: Provides functions to utilize a command line utility that does bulk + inserts and exports from SQL Server databases. + date_publication: '2024-05-09' + bug_reports: https://github.com/tomroh/bcputility/issues + url: https://bcputility.delveds.com + url_cran: https://CRAN.R-project.org/package=bcputility + url_git: https://github.com/tomroh/bcputility +BCRA: + version: 2.1.2 + title: Breast Cancer Risk Assessment + maintainer: Fanni Zhang + description: |- + Functions provide risk projections of invasive breast cancer based on Gail model according to National Cancer Institute's Breast Cancer Risk Assessment Tool algorithm for specified race/ethnic groups and age intervals. + Gail MH, Brinton LA, et al (1989) . + Marthew PB, Gail MH, et al (2016) . + date_publication: '2020-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCRA + url_git: '' +bcrm: + version: 0.5.4 + title: |- + Bayesian Continual Reassessment Method for Phase I + Dose-Escalation Trials + maintainer: Graham Wheeler + description: |- + Implements a wide variety of one- and two-parameter Bayesian CRM + designs. The program can run interactively, allowing the user to enter outcomes + after each cohort has been recruited, or via simulation to assess operating + characteristics. See Sweeting et al. (2013): . + date_publication: '2019-08-23' + bug_reports: https://github.com/mikesweeting/bcrm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bcrm + url_git: https://github.com/mikesweeting/bcrm +bcROCsurface: + version: 1.0-6 + title: |- + Bias-Corrected Methods for Estimating the ROC Surface of + Continuous Diagnostic Tests + maintainer: Duc-Khanh To + description: |- + The bias-corrected estimation methods for the receiver operating characteristics + ROC surface and the volume under ROC surfaces (VUS) under missing at random (MAR) + assumption. + date_publication: '2023-09-09' + bug_reports: https://github.com/toduckhanh/bcROCsurface/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bcROCsurface + url_git: https://github.com/toduckhanh/bcROCsurface +bcrypt: + version: 1.2.0 + title: '''Blowfish'' Key Derivation and Password Hashing' + maintainer: Jeroen Ooms + description: |- + Bindings to the 'blowfish' password hashing algorithm + derived from + the 'OpenBSD' implementation. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/bcrypt/issues + url: https://jeroen.r-universe.dev/bcrypt + url_cran: https://CRAN.R-project.org/package=bcrypt + url_git: '' +BCSub: + version: '0.5' + title: |- + A Bayesian Semiparametric Factor Analysis Model for Subtype + Identification (Clustering) + maintainer: Jiehuan Sun + description: |- + Gene expression profiles are commonly utilized to infer disease + subtypes and many clustering methods can be adopted for this task. + However, existing clustering methods may not perform well when + genes are highly correlated and many uninformative genes are included + for clustering. To deal with these challenges, we develop a novel + clustering method in the Bayesian setting. This method, called BCSub, + adopts an innovative semiparametric Bayesian factor analysis model + to reduce the dimension of the data to a few factor scores for + clustering. Specifically, the factor scores are assumed to follow + the Dirichlet process mixture model in order to induce clustering. + date_publication: '2017-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCSub + url_git: '' +BCT: + version: '1.2' + title: Bayesian Context Trees for Discrete Time Series + maintainer: Valentinian Mihai Lungu + description: 'An implementation of a collection of tools for exact Bayesian inference + with discrete times series. This package contains functions that can be used for + prediction, model selection, estimation, segmentation/change-point detection and + other statistical tasks. Specifically, the functions provided can be used for + the exact computation of the prior predictive likelihood of the data, for the + identification of the a posteriori most likely (MAP) variable-memory Markov models, + for calculating the exact posterior probabilities and the AIC and BIC scores of + these models, for prediction with respect to log-loss and 0-1 loss and segmentation/change-point + detection. Example data sets from finance, genetics, animal communication and + meteorology are also provided. Detailed descriptions of the underlying theory + and algorithms can be found in [Kontoyiannis et al. ''Bayesian Context Trees: + Modelling and exact inference for discrete time series.'' Journal of the Royal + Statistical Society: Series B (Statistical Methodology), April 2022. Available + at: [stat.ME], July 2020] and [Lungu et al. ''Change-point + Detection and Segmentation of Discrete Data using Bayesian Context Trees'' + [stat.ME], March 2022].' + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BCT + url_git: '' +bcv: + version: 1.0.2 + title: Cross-Validation for the SVD (Bi-Cross-Validation) + maintainer: Michal Burdukiewicz + description: |2- + + Methods for choosing the rank of an SVD (singular value decomposition) + approximation via cross validation. The package provides both Gabriel-style + "block" holdouts and Wold-style "speckled" holdouts. It also includes an + implementation of the SVDImpute algorithm. For more information about + Bi-cross-validation, see Owen & Perry's 2009 AoAS article + (at ) and Perry's 2009 PhD thesis + (at ). + date_publication: '2023-05-19' + bug_reports: https://github.com/michbur/bcv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bcv + url_git: https://github.com/michbur/bcv +bda: + version: 18.3.2 + title: Binned Data Analysis + maintainer: Bin Wang + description: |- + Algorithms developed for binned data analysis, + gene expression data analysis and + measurement error models for ordinal data analysis. + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bda + url_git: '' +BDAlgo: + version: 0.1.0 + title: Bloom Detecting Algorithm + maintainer: Stephane Karasiewicz + description: The Bloom Detecting Algorithm enables the detection of blooms within + a time series of species abundance and extracts 22 phenological variables. For + details, see Karasiewicz et al. (2022) . + date_publication: '2023-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BDAlgo + url_git: '' +bdc: + version: 1.1.5 + title: Biodiversity Data Cleaning + maintainer: Bruno Ribeiro + description: |- + It brings together several aspects of biodiversity + data-cleaning in one place. 'bdc' is organized in thematic modules + related to different biodiversity dimensions, including 1) Merge + datasets: standardization and integration of different datasets; 2) + Pre-filter: flagging and removal of invalid or non-interpretable + information, followed by data amendments; 3) Taxonomy: cleaning, + parsing, and harmonization of scientific names from several taxonomic + groups against taxonomic databases locally stored through the + application of exact and partial matching algorithms; 4) Space: + flagging of erroneous, suspect, and low-precision geographic + coordinates; and 5) Time: flagging and, whenever possible, correction + of inconsistent collection date. In addition, it contains + features to visualize, document, and report data quality – which is + essential for making data quality assessment transparent and + reproducible. The reference for the methodology is Bruno et al. (2022) + . + date_publication: '2024-12-17' + bug_reports: https://github.com/brunobrr/bdc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bdc + url_git: https://brunobrr.github.io/bdc/(website)https://github.com/brunobrr/bdc +bdDwC: + version: 0.1.15 + title: 'Darwinizer: Darwin Core (DwC) Field Names Standardization' + maintainer: Povilas Gibas + description: The 'shiny' application 'bdDwC' makes biodiversity data field names + Darwin Core compatible. + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdDwC + url_git: '' +bde: + version: 1.0.1.1 + title: Bounded Density Estimation + maintainer: Guzman Santafe + description: A collection of S4 classes which implements different methods to estimate + and deal with densities in bounded domains. That is, densities defined within + the interval [lower.limit, upper.limit], where lower.limit and upper.limit are + values that can be set by the user. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bde + url_git: '' +BDEsize: + version: '1.6' + title: |- + Efficient Determination of Sample Size in Balanced Design of + Experiments + maintainer: Jong Hee Chung + description: 'For a balanced design of experiments, this package calculates the + sample size required to detect a certain standardized effect size, under a significance + level. This package also provides three graphs; detectable standardized effect + size vs power, sample size vs detectable standardized effect size, and sample + size vs power, which show the mutual relationship between the sample size, power + and the detectable standardized effect size. The detailed procedure is described + in R. V. Lenth (2006-9) , Y. + B. Lim (1998), M. A. Kastenbaum, D. G. Hoel and K. O. Bowman (1970) , + and Douglas C. Montgomery (2013, ISBN: 0849323312).' + date_publication: '2021-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BDEsize + url_git: '' +BDgraph: + version: '2.73' + title: |- + Bayesian Structure Learning in Graphical Models using + Birth-Death MCMC + maintainer: Reza Mohammadi + description: Advanced statistical tools for Bayesian structure learning in undirected + graphical models, accommodating continuous, ordinal, discrete, count, and mixed + data. It integrates recent advancements in Bayesian graphical models as presented + in the literature, including the works of Mohammadi and Wit (2015) , + Mohammadi et al. (2021) , Dobra and Mohammadi + (2018) , and Mohammadi et al. (2023) . + date_publication: '2024-08-23' + bug_reports: '' + url: https://www.uva.nl/profile/a.mohammadi + url_cran: https://CRAN.R-project.org/package=BDgraph + url_git: '' +bdl: + version: 1.0.5 + title: Interface and Tools for 'BDL' API + maintainer: Krzysztof Kania + description: |- + Interface to Local Data Bank ('Bank Danych Lokalnych' - 'bdl') API + with set of useful tools like + quick plotting and map generating using data from bank. + date_publication: '2023-02-24' + bug_reports: https://github.com/statisticspoland/R_Package_to_API_BDL/issues + url: https://statisticspoland.github.io/R_Package_to_API_BDL/ + url_cran: https://CRAN.R-project.org/package=bdl + url_git: '' +bdlim: + version: 0.4.2 + title: Bayesian Distributed Lag Interaction Models + maintainer: Ander Wilson + description: Estimation and interpretation of Bayesian distributed lag interaction + models (BDLIMs). A BDLIM regresses a scalar outcome on repeated measures of exposure + and allows for modification by a categorical variable under four specific patterns + of modification. The main function is bdlim(). There are also summary and plotting + files. Details on methodology are described in Wilson et al. (2017) . + date_publication: '2024-06-12' + bug_reports: https://github.com/anderwilson/bdlim/issues/ + url: https://anderwilson.github.io/bdlim/ + url_cran: https://CRAN.R-project.org/package=bdlim + url_git: https://github.com/AnderWilson/bdlim/ +bdlp: + version: 0.9-2 + title: Transparent and Reproducible Artificial Data Generation + maintainer: Rainer Dangl + description: |- + The main function generateDataset() processes a user-supplied .R file that + contains metadata parameters in order to generate actual data. The metadata parameters + have to be structured in the form of metadata objects, the format of which is + outlined in the package vignette. This approach allows to generate artificial data + in a transparent and reproducible manner. + date_publication: '2021-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdlp + url_git: '' +bdots: + version: 1.2.5 + title: Bootstrapped Differences of Time Series + maintainer: Collin Nolte + description: |- + Analyze differences among time series curves with p-value + adjustment for multiple comparisons introduced in Oleson et al + (2015) . + date_publication: '2023-01-06' + bug_reports: https://github.com/collinn/bdots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bdots + url_git: https://github.com/collinn/bdots +BDP2: + version: 0.1.3 + title: |- + Bayesian Adaptive Designs for Phase II Trials with Binary + Endpoint + maintainer: Manuel Wiesenfarth + description: Tools and workflow to choose design parameters in Bayesian adaptive + single-arm phase II trial designs with binary endpoint (response, success) with + possible stopping for efficacy and futility at interim analyses. Also contains + routines to determine and visualize operating characteristics. See Kopp-Schneider + et al. (2018) . + date_publication: '2018-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BDP2 + url_git: '' +bdpar: + version: 3.1.0 + title: Big Data Preprocessing Architecture + maintainer: Miguel Ferreiro-Díaz + description: |2- + + Provide a tool to easily build customized data flows to pre-process large volumes + of information from different sources. To this end, 'bdpar' allows to (i) easily use and + create new functionalities and (ii) develop new data source extractors according to the + user needs. Additionally, the package provides by default a predefined data flow + to extract and pre-process the most relevant information (tokens, dates, ... ) from some textual + sources (SMS, Email, YouTube comments). + date_publication: '2023-12-12' + bug_reports: https://github.com/miferreiro/bdpar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bdpar + url_git: https://github.com/miferreiro/bdpar +bdpv: + version: '1.3' + title: Inference and Design for Predictive Values in Diagnostic Tests + maintainer: Frank Schaarschmidt + description: Computation of asymptotic confidence intervals for negative and positive + predictive values in binary diagnostic tests in case-control studies. Experimental + design for hypothesis tests on predictive values. + date_publication: '2019-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdpv + url_git: '' +bdrc: + version: 1.1.0 + title: Bayesian Discharge Rating Curves + maintainer: Solvi Rognvaldsson + description: Fits a discharge rating curve based on the power-law and the generalized + power-law from data on paired stage and discharge measurements in a given river + using a Bayesian hierarchical model as described in Hrafnkelsson et al. (2020) + . + date_publication: '2023-03-19' + bug_reports: https://github.com/sor16/bdrc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bdrc + url_git: '' +bdribs: + version: 1.0.4 + title: |- + Bayesian Detection of Potential Risk Using Inference on Blinded + Safety Data + maintainer: Saurabh Mukhopadhyay + description: |- + Implements Bayesian inference to detect signal from blinded + clinical trial when total number of adverse events of special + concerns and total risk exposures from all patients are available in the study. + For more details see the article by Mukhopadhyay et. al. (2018) + titled 'Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data', + in Pharmaceutical Statistics (to appear). + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdribs + url_git: '' +bdscale: + version: 2.0.0 + title: Remove Weekends and Holidays from ggplot2 Axes + maintainer: Dave Mills + description: Provides a continuous date scale, omitting weekends and holidays. + date_publication: '2016-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdscale + url_git: http://github.com/dvmlls/bdscale +bdsm: + version: 0.1.0 + title: Bayesian Dynamic Systems Modeling + maintainer: Marcin Dubel + description: |- + Implements methods for building and analyzing models based on panel + data as described in the paper by + Moral-Benito (2013, ). + The package provides functions to estimate dynamic panel data models + and analyze the results of the estimation. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdsm + url_git: '' +bdsmatrix: + version: 1.3-7 + title: Routines for Block Diagonal Symmetric Matrices + maintainer: Terry Therneau + description: This is a special case of sparse matrices, used by coxme. + date_publication: '2024-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdsmatrix + url_git: '' +bdsvd: + version: 0.2.1 + title: Block Structure Detection Using Singular Vectors + maintainer: Jan O. Bauer + description: Performs block diagonal covariance matrix detection using singular + vectors (BD-SVD), which can be extended to hierarchical variable clustering (HC-SVD). + The methods are described in Bauer (2024) + and Bauer (202X) . + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bdsvd + url_git: '' +BDWreg: + version: 1.3.0 + title: Bayesian Inference for Discrete Weibull Regression + maintainer: Hamed Haselimashhadi + description: A Bayesian regression model for discrete response, where the conditional + distribution is modelled via a discrete Weibull distribution. This package provides + an implementation of Metropolis-Hastings and Reversible-Jumps algorithms to draw + samples from the posterior. It covers a wide range of regularizations through + any two parameter prior. Examples are Laplace (Lasso), Gaussian (ridge), Uniform, + Cauchy and customized priors like a mixture of priors. An extensive visual toolbox + is included to check the validity of the results as well as several measures of + goodness-of-fit. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BDWreg + url_git: '' +BE: + version: 0.2.4 + title: Bioequivalence Study Data Analysis + maintainer: Kyun-Seop Bae + description: |- + Analyze bioequivalence study data with industrial strength. Sample size could be determined for various crossover designs, such as 2x2 design, 2x4 design, 4x4 design, Balaam design, Two-sequence dual design, and William design. + Reference: Chow SC, Liu JP. Design and Analysis of Bioavailability and Bioequivalence Studies. 3rd ed. (2009, ISBN:978-1-58488-668-6). + date_publication: '2023-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BE + url_git: '' +bea.R: + version: 1.0.6 + title: Bureau of Economic Analysis API + maintainer: Andrea Batch + description: |- + Provides an R interface for the Bureau of Economic Analysis (BEA) + API (see for + more information) that serves two core purposes - + 1. To Extract/Transform/Load data [beaGet()] from the BEA API as R-friendly + formats in the user's work space [transformation done by default in beaGet() + can be modified using optional parameters; see, too, bea2List(), bea2Tab()]. + 2. To enable the search of descriptive meta data [beaSearch()]. + Other features of the library exist mainly as intermediate methods + or are in early stages of development. + Important Note - You must have an API key to use this library. + Register for a key at . + date_publication: '2018-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bea.R + url_git: https://github.com/us-bea/bea.R +BEACH: + version: 1.3.1 + title: Biometric Exploratory Analysis Creation House + maintainer: Danni Yu + description: A platform is provided for interactive analyses with a goal of totally + easy to develop, deploy, interact, and explore (TEDDIE). Using this package, users + can create customized analyses and make them available to end users who can perform + interactive analyses and save analyses to RTF or HTML files. It allows developers + to focus on R code for analysis, instead of dealing with html or shiny code. + date_publication: '2019-02-11' + bug_reports: '' + url: https://www.pharmasug.org/proceedings/2018/AD/PharmaSUG-2018-AD05.pdf + url_cran: https://CRAN.R-project.org/package=BEACH + url_git: '' +beadplexr: + version: 0.5.0 + title: Analysis of Multiplex Cytometric Bead Assays + maintainer: Ulrik Stervbo + description: |- + Reproducible and automated analysis of multiplex bead assays such + as CBA (Morgan et al. 2004; ), LEGENDplex + (Yu et al. 2015; ), and MACSPlex (Miltenyi + Biotec 2014; Application note: Data acquisition and analysis without the + MACSQuant analyzer; + ). The + package provides functions for streamlined reading of fcs files, and + identification of bead clusters and analyte expression. The package eases + the calculation of standard curves and the subsequent calculation of the + analyte concentration. + date_publication: '2023-06-16' + bug_reports: https://gitlab.com/ustervbo/beadplexr/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=beadplexr + url_git: https://gitlab.com/ustervbo/beadplexr +beakr: + version: 0.4.3 + title: A Minimalist Web Framework for R + maintainer: Jonathan Callahan + description: |- + A minimalist web framework for developing application programming + interfaces in R that provides a flexible framework for handling common + HTTP-requests, errors, logging, and an ability to integrate any R code as + server middle-ware. + date_publication: '2021-04-06' + bug_reports: https://github.com/MazamaScience/beakr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=beakr + url_git: https://github.com/MazamaScience/beakr +BEAMR: + version: 1.1.0 + title: Bootstrap Evaluation of Association Matrices + maintainer: Anna Eames Seffernick + description: |- + A bootstrap-based approach to integrate multiple forms of + high dimensional genomic data with multiple clinical endpoints. This method + is used to find clinically meaningful groups of genomic features, such + as genes or pathways. A manuscript describing this method is in preparation. + date_publication: '2024-07-27' + bug_reports: https://github.com/annaSeffernick/BEAMR/issues + url: https://annaseffernick.github.io/BEAMR/ + url_cran: https://CRAN.R-project.org/package=BEAMR + url_git: https://github.com/annaSeffernick/BEAMR +beanplot: + version: 1.3.1 + title: |- + Visualization via Beanplots (Like Boxplot/Stripchart/Violin + Plot) + maintainer: Peter Kampstra + description: |- + Plots univariate comparison graphs, an alternative to + boxplot/stripchart/violin plot. + date_publication: '2022-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beanplot + url_git: '' +beans: + version: 0.1.0 + title: Data on Dried Beans + maintainer: Max Kuhn + description: |- + These data contain morphological image measurements for dried + beans from Koklu and Ozkan (2020) . + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beans + url_git: '' +beanz: + version: '3.1' + title: Bayesian Analysis of Heterogeneous Treatment Effect + maintainer: Chenguang Wang + description: |- + It is vital to assess the heterogeneity of treatment effects + (HTE) when making health care decisions for an individual patient or a group + of patients. Nevertheless, it remains challenging to evaluate HTE based + on information collected from clinical studies that are often designed and + conducted to evaluate the efficacy of a treatment for the overall population. + The Bayesian framework offers a principled and flexible approach to estimate + and compare treatment effects across subgroups of patients defined by their + characteristics. This package allows users to explore a wide range of Bayesian + HTE analysis models, and produce posterior inferences about HTE. See Wang et al. + (2018) for further details. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beanz + url_git: '' +bearishTrader: + version: 1.0.2 + title: Trading Strategies for Bearish Outlook + maintainer: MaheshP Kumar + description: |- + Stock, Options and Futures Trading Strategies for Traders and Investors with Bearish Outlook. The indicators, strategies, calculations, functions and all other discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. + Guy Cohen (“The Bible of Options Strategies (2nd ed.)”, 2015, ISBN: 9780133964028). + Juan A. Serur, Juan A. Serur (“151 Trading Strategies”, 2018, ISBN: 9783030027919). + Chartered Financial Analyst Institute ("Chartered Financial Analyst Program Curriculum 2020 Level I Volumes 1-6. (Vol. 5, pp. 385-453)", 2019, ISBN: 9781119593577). + John C. Hull (“Options, Futures, and Other Derivatives (11th ed.)”, 2022, ISBN: 9780136939979). + date_publication: '2022-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bearishTrader + url_git: '' +beast: + version: '1.1' + title: |- + Bayesian Estimation of Change-Points in the Slope of + Multivariate Time-Series + maintainer: Panagiotis Papastamoulis + description: Assume that a temporal process is composed of contiguous segments with + differing slopes and replicated noise-corrupted time series measurements are observed. + The unknown mean of the data generating process is modelled as a piecewise linear + function of time with an unknown number of change-points. The package infers the + joint posterior distribution of the number and position of change-points as well + as the unknown mean parameters per time-series by MCMC sampling. A-priori, the + proposed model uses an overfitting number of mean parameters but, conditionally + on a set of change-points, only a subset of them influences the likelihood. An + exponentially decreasing prior distribution on the number of change-points gives + rise to a posterior distribution concentrating on sparse representations of the + underlying sequence, but also available is the Poisson distribution. See Papastamoulis + et al (2017) for a detailed presentation of the method. + date_publication: '2018-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beast + url_git: '' +beastier: + version: 2.5.2 + title: Call 'BEAST2' + maintainer: Richèl J.C. Bilderbeek + description: |- + 'BEAST2' () is a widely used + Bayesian phylogenetic tool, that uses DNA/RNA/protein data + and many model priors to create a posterior of jointly estimated + phylogenies and parameters. + 'BEAST2' is a command-line tool. + This package provides a way to call 'BEAST2' + from an 'R' function call. + date_publication: '2024-10-06' + bug_reports: https://github.com/ropensci/beastier/issues + url: '' + url_cran: https://CRAN.R-project.org/package=beastier + url_git: https://docs.ropensci.org/beastier/(website)https://github.com/ropensci/beastier/ +BeastJar: + version: 1.10.6 + title: JAR Dependency for MCMC Using 'BEAST' + maintainer: Marc A. Suchard + description: |- + Provides JAR to perform Markov chain Monte Carlo (MCMC) inference using + the popular Bayesian Evolutionary Analysis by Sampling Trees 'BEAST' software library + of Suchard et al (2018) . 'BEAST' supports auto-tuning + Metropolis-Hastings, slice, Hamiltonian Monte Carlo and Sequential Monte Carlo + sampling for a large variety of composable standard and phylogenetic statistical + models using high performance computing. By placing the 'BEAST' JAR in this package, + we offer an efficient distribution system for 'BEAST' use by other R packages using + CRAN. + date_publication: '2020-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BeastJar + url_git: https://github.com/beast-dev/BeastJar +beastt: + version: 0.0.2 + title: |- + Bayesian Evaluation, Analysis, and Simulation Software Tools for + Trials + maintainer: Christina Fillmore + description: |- + Bayesian dynamic borrowing with covariate adjustment via inverse probability + weighting for simulations and data analyses in clinical trials. This makes it easy to use + propensity score methods to balance covariate distributions between external and internal + data. + date_publication: '2025-02-24' + bug_reports: https://github.com/GSK-Biostatistics/beastt/issues + url: https://gsk-biostatistics.github.io/beastt/ + url_cran: https://CRAN.R-project.org/package=beastt + url_git: https://github.com/GSK-Biostatistics/beastt +beautier: + version: 2.6.12 + title: '''BEAUti'' from R' + maintainer: Richèl J.C. Bilderbeek + description: |- + 'BEAST2' () is a widely used + Bayesian phylogenetic tool, that uses DNA/RNA/protein data + and many model priors to create a posterior of jointly estimated + phylogenies and parameters. + 'BEAUti 2' (which is part of 'BEAST2') is a GUI tool + that allows users to specify the many possible setups + and generates the XML file 'BEAST2' needs to run. + This package provides a way to create 'BEAST2' input + files without active user input, but using + R function calls instead. + date_publication: '2024-04-01' + bug_reports: https://github.com/ropensci/beautier/issues + url: https://docs.ropensci.org/beautier/ + url_cran: https://CRAN.R-project.org/package=beautier + url_git: https://github.com/ropensci/beautier +beaver: + version: 1.0.0 + title: |- + Bayesian Model Averaging of Covariate Adjusted Negative-Binomial + Dose-Response + maintainer: Hollins Showalter + description: |- + Dose-response modeling for negative-binomial distributed data with + a variety of dose-response models. Covariate adjustment and Bayesian + model averaging is supported. Functions are provided to easily obtain + inference on the dose-response relationship and plot the dose-response curve. + date_publication: '2024-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beaver + url_git: https://github.com/rich-payne/beaver +BED: + version: 1.6.0 + title: Biological Entity Dictionary (BED) + maintainer: Patrice Godard + description: |- + An interface for the 'Neo4j' database providing + mapping between different identifiers of biological entities. + This Biological Entity Dictionary (BED) + has been developed to address three main challenges. + The first one is related to the completeness of identifier mappings. + Indeed, direct mapping information provided by the different systems + are not always complete and can be enriched by mappings provided by other + resources. + More interestingly, direct mappings not identified by any of these + resources can be indirectly inferred by using mappings to a third reference. + For example, many human Ensembl gene ID are not directly mapped to any + Entrez gene ID but such mappings can be inferred using respective mappings + to HGNC ID. The second challenge is related to the mapping of deprecated + identifiers. Indeed, entity identifiers can change from one resource + release to another. The identifier history is provided by some resources, + such as Ensembl or the NCBI, but it is generally not used by mapping tools. + The third challenge is related to the automation of the mapping process + according to the relationships between the biological entities of interest. + Indeed, mapping between gene and protein ID scopes should not be done + the same way than between two scopes regarding gene ID. + Also, converting identifiers from different organisms should be possible + using gene orthologs information. + The method has been published by + Godard and van Eyll (2018) . + date_publication: '2024-11-09' + bug_reports: https://github.com/patzaw/BED/issues + url: https://patzaw.github.io/BED/ + url_cran: https://CRAN.R-project.org/package=BED + url_git: https://github.com/patzaw/BED +BEDASSLE: + version: 1.6.1 + title: |- + Quantifies Effects of Geo/Eco Distance on Genetic + Differentiation + maintainer: Gideon Bradburd + description: |- + Provides functions that allow users to quantify the relative + contributions of geographic and ecological distances to empirical patterns of genetic + differentiation on a landscape. Specifically, we use a custom Markov chain + Monte Carlo (MCMC) algorithm, which is used to estimate the parameters of the + inference model, as well as functions for performing MCMC diagnosis and assessing + model adequacy. + date_publication: '2024-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BEDASSLE + url_git: '' +BEDMatrix: + version: 2.0.4 + title: Extract Genotypes from a PLINK .bed File + maintainer: Alexander Grueneberg + description: |- + A matrix-like data structure that allows for efficient, + convenient, and scalable subsetting of binary genotype/phenotype files + generated by PLINK (), the whole + genome association analysis toolset, without loading the entire file into + memory. + date_publication: '2024-09-06' + bug_reports: https://github.com/QuantGen/BEDMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BEDMatrix + url_git: https://github.com/QuantGen/BEDMatrix +bedr: + version: 1.0.7 + title: |- + Genomic Region Processing using Tools Such as 'BEDTools', + 'BEDOPS' and 'Tabix' + maintainer: Paul C. Boutros + description: |- + Genomic regions processing using open-source command line tools such as 'BEDTools', 'BEDOPS' and 'Tabix'. + These tools offer scalable and efficient utilities to perform genome arithmetic e.g indexing, formatting and merging. + bedr API enhances access to these tools as well as offers additional utilities for genomic regions processing. + date_publication: '2019-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bedr + url_git: '' +BeeBDC: + version: 1.2.1 + title: Occurrence Data Cleaning + maintainer: James B. Dorey + description: |- + Flags and checks occurrence data that are in Darwin Core + format. The package includes generic functions and data as well as + some that are specific to bees. This package is meant to build upon + and be complimentary to other excellent occurrence cleaning packages, + including 'bdc' and 'CoordinateCleaner'. This package uses datasets + from several sources and particularly from the Discover Life Website, + created by Ascher and Pickering (2020). For further information, + please see the original publication and package website. Publication + - Dorey et al. (2023) and package + website - Dorey et al. (2023) . + date_publication: '2024-11-04' + bug_reports: https://github.com/jbdorey/BeeBDC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BeeBDC + url_git: https://jbdorey.github.io/BeeBDC/https://github.com/jbdorey/BeeBDC +beeca: + version: 0.2.0 + title: Binary Endpoint Estimation with Covariate Adjustment + maintainer: Alex Przybylski + description: |- + Performs estimation of marginal treatment effects for binary + outcomes when using logistic regression working models with covariate + adjustment (see discussions in Magirr et al (2024) ). + Implements the variance estimators of Ge et al (2011) + and Ye et al (2023) . + date_publication: '2024-11-12' + bug_reports: https://github.com/openpharma/beeca/issues + url: https://openpharma.github.io/beeca/ + url_cran: https://CRAN.R-project.org/package=beeca + url_git: '' +BeeGUTS: + version: 1.3.0 + title: |- + General Unified Threshold Model of Survival for Bees using + Bayesian Inference + maintainer: Benoit Goussen + description: |- + Tools to calibrate, validate, and make predictions with the + General Unified Threshold model of Survival adapted for Bee species. The + model is presented in the publication from Baas, J., Goussen, B., Miles, M., + Preuss, T.G., Roessing, I. (2022) and + Baas, J., Goussen, B., Taenzler, V., Roeben, V., Miles, M., Preuss, T.G., + van den Berg, S., Roessink, I. (2024) , and is based on the + GUTS framework Jager, T., Albert, C., Preuss, T.G. and Ashauer, R. (2011) + . + The authors are grateful to Bayer A.G. for its financial support. + date_publication: '2024-10-23' + bug_reports: https://github.com/bgoussen/BeeGUTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BeeGUTS + url_git: https://github.com/bgoussen/BeeGUTS +beepr: + version: '2.0' + title: Easily Play Notification Sounds on any Platform + maintainer: Rasmus Bååth + description: |- + The main function of this package is beep(), with the purpose to + make it easy to play notification sounds on whatever platform you are on. + It is intended to be useful, for example, if you are running a long analysis + in the background and want to know when it is ready. + date_publication: '2024-07-06' + bug_reports: https://github.com/rasmusab/beepr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=beepr + url_git: https://github.com/rasmusab/beepr +beeswarm: + version: 0.4.0 + title: The Bee Swarm Plot, an Alternative to Stripchart + maintainer: Aron Eklund + description: |- + The bee swarm plot is a one-dimensional scatter plot like + "stripchart", but with closely-packed, non-overlapping points. + date_publication: '2021-06-01' + bug_reports: https://github.com/aroneklund/beeswarm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=beeswarm + url_git: https://github.com/aroneklund/beeswarm +beezdemand: + version: 0.1.2 + title: Behavioral Economic Easy Demand + maintainer: Brent Kaplan + description: "Facilitates many of the analyses performed in studies of\nbehavioral + economic demand. The package supports commonly-used options for\nmodeling operant + demand including (1) data screening proposed by Stein,\nKoffarnus, Snider, Quisenberry, + & Bickel (2015; ),\n(2) fitting models of demand such + as linear (Hursh, Raslear, Bauman,\n& Black, 1989, ), + exponential\t(Hursh & Silberberg, 2008,\n) and + modified exponential (Koffarnus,\nFranck, Stein, & Bickel, 2015, ), + and (3) calculating\nnumerous measures\trelevant to applied behavioral economists + (Intensity,\nPmax, Omax). Also\tsupports plotting and comparing data." + date_publication: '2023-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beezdemand + url_git: https://github.com/brentkaplan/beezdemand +beezdiscounting: + version: 0.3.2 + title: Behavioral Economic Easy Discounting + maintainer: Brent A. Kaplan + description: |- + Facilitates some of the analyses performed in studies of + behavioral economic discounting. The package supports scoring of the 27-Item Monetary Choice + Questionnaire (see Kaplan et al., 2016; ), calculating k + values (Mazur's simple hyperbolic and exponential) using nonlinear regression, calculating + various Area Under the Curve (AUC) measures, plotting regression curves for both fit-to-group and + two-stage approaches, checking for unsystematic discounting + (Johnson & Bickel, 2008; ) and scoring of the + minute discounting task (see Koffarnus & Bickel, 2014; ) using the + Qualtrics 5-trial discounting template (see the Qualtrics Minute Discounting User Guide; + ), which is also available as a .qsf file in this package. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beezdiscounting + url_git: https://github.com/brentkaplan/beezdiscounting +befproj: + version: 0.1.1 + title: Makes a Local Population Projection + maintainer: Peter Thuresson + description: |- + This is a sub national population projection model for calculating + population development. The model uses a cohort component method. + Further reading: Stanley K. Smith: A Practitioner's Guide to State and + Local Population Projections. 2013. . + date_publication: '2020-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=befproj + url_git: '' +behaviorchange: + version: 0.5.5 + title: Tools for Behavior Change Researchers and Professionals + maintainer: Gjalt-Jorn Peters + description: |- + Contains specialised analyses and + visualisation tools for behavior change science. + These facilitate conducting determinant studies + (for example, using confidence interval-based + estimation of relevance, CIBER, or CIBERlite + plots, see Crutzen, Noijen & Peters (2017) + ), + systematically developing, reporting, + and analysing interventions (for example, using + Acyclic Behavior Change Diagrams), and reporting + about intervention effectiveness (for example, using + the Numbers Needed for Change, see Gruijters & Peters + (2017) ), and computing the + required sample size (using the Meaningful Change + Definition, see Gruijters & Peters (2020) + ). + This package is especially useful for + researchers in the field of behavior change or + health psychology and to behavior change + professionals such as intervention developers and + prevention workers. + date_publication: '2023-03-04' + bug_reports: https://gitlab.com/r-packages/behaviorchange/-/issues + url: https://r-packages.gitlab.io/behaviorchange + url_cran: https://CRAN.R-project.org/package=behaviorchange + url_git: '' +behavr: + version: 0.3.2 + title: Canonical Data Structure for Behavioural Data + maintainer: Quentin Geissmann + description: Implements an S3 class based on 'data.table' to store and process efficiently + ethomics (high-throughput behavioural) data. + date_publication: '2019-01-03' + bug_reports: https://github.com/rethomics/behavr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=behavr + url_git: https://github.com/rethomics/behavr +BEKKs: + version: 1.4.5 + title: Multivariate Conditional Volatility Modelling and Forecasting + maintainer: Markus J. Fülle + description: Methods and tools for estimating, simulating and forecasting of so-called + BEKK-models (named after Baba, Engle, Kraft and Kroner) based on the fast Berndt–Hall–Hall–Hausman + (BHHH) algorithm described in Hafner and Herwartz (2008) . + For an overview, we refer the reader to Fülle et al. (2024) . + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BEKKs + url_git: '' +belex: + version: 0.1.0 + title: Download Historical Data from the Belgrade Stock Exchange + maintainer: Milos Vilotic + description: Tools for downloading historical financial data from the www.belex.rs. + date_publication: '2016-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=belex + url_git: '' +belg: + version: 1.5.3 + title: Boltzmann Entropy of a Landscape Gradient + maintainer: Jakub Nowosad + description: |- + Calculates the Boltzmann entropy of a landscape gradient. + This package uses the analytical method created by Gao, P., Zhang, H. + and Li, Z., 2018 () and by Gao, P. and Li, Z., 2019 + (). It also extend the original ideas by + allowing calculations on data with missing values. + date_publication: '2022-12-15' + bug_reports: https://github.com/r-spatialecology/belg/issues + url: https://r-spatialecology.github.io/belg/ + url_cran: https://CRAN.R-project.org/package=belg + url_git: '' +BElikelihood: + version: '1.1' + title: Likelihood Method for Evaluating Bioequivalence + maintainer: Liping Du + description: A likelihood method is implemented to present evidence for evaluating + bioequivalence (BE). The functions use bioequivalence data [area under the blood + concentration-time curve (AUC) and peak concentration (Cmax)] from various crossover + designs commonly used in BE studies including a fully replicated, a partially + replicated design, and a conventional 2x2 crossover design. They will calculate + the profile likelihoods for the mean difference, total standard deviation ratio, + and within subject standard deviation ratio for a test and a reference drug. A + plot of a standardized profile likelihood can be generated along with the maximum + likelihood estimate and likelihood intervals, which present evidence for bioequivalence. + See Liping Du and Leena Choi (2015) . + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BElikelihood + url_git: '' +bellreg: + version: 0.0.2.2 + title: Count Regression Models Based on the Bell Distribution + maintainer: Fabio Demarqui + description: Bell regression models for count data with overdispersion. The implemented + models account for ordinary and zero-inflated regression models under both frequentist + and Bayesian approaches. Theoretical details regarding the models implemented + in the package can be found in Castellares et al. (2018) + and Lemonte et al. (2020) . + date_publication: '2024-10-23' + bug_reports: https://github.com/fndemarqui/bellreg/issues + url: https://fndemarqui.github.io/bellreg/ + url_cran: https://CRAN.R-project.org/package=bellreg + url_git: https://github.com/fndemarqui/bellreg +bench: + version: 1.1.4 + title: High Precision Timing of R Expressions + maintainer: Davis Vaughan + description: |- + Tools to accurately benchmark and analyze execution times for + R expressions. + date_publication: '2025-01-16' + bug_reports: https://github.com/r-lib/bench/issues + url: https://bench.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=bench + url_git: https://github.com/r-lib/bench +benchden: + version: 1.0.8 + title: 28 Benchmark Densities from Berlinet/Devroye (1994) + maintainer: Thoralf Mildenberger + description: Full implementation of the 28 distributions introduced as benchmarks + for nonparametric density estimation by Berlinet and Devroye (1994) . + Includes densities, cdfs, quantile functions and generators for samples as well + as additional information on features of the densities. Also contains the 4 histogram + densities used in Rozenholc/Mildenberger/Gather (2010) . + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=benchden + url_git: https://github.com/thmild/benchden +Benchmarking: + version: '0.33' + title: Benchmark and Frontier Analysis Using DEA and SFA + maintainer: Lars Otto + description: |- + Methods for frontier + analysis, Data Envelopment Analysis (DEA), under different + technology assumptions (fdh, vrs, drs, crs, irs, add/frh, and fdh+), + and using different efficiency measures (input based, output based, + hyperbolic graph, additive, super, and directional efficiency). Peers + and slacks are available, partial price information can be included, + and optimal cost, revenue and profit can be calculated. Evaluation of + mergers is also supported. Methods for graphing the technology sets + are also included. There is also support for comparative methods based + on Stochastic Frontier Analyses (SFA) and for convex nonparametric + least squares of convex functions (STONED). In general, the methods + can be used to solve not only standard models, but also many other + model variants. It complements the book, Bogetoft and Otto, + Benchmarking with DEA, SFA, and R, Springer-Verlag, 2011, but can of + course also be used as a stand-alone package. + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Benchmarking + url_git: '' +benchmarkme: + version: 1.0.8 + title: Crowd Sourced System Benchmarks + maintainer: Colin Gillespie + description: |- + Benchmark your CPU and compare against other CPUs. Also + provides functions for obtaining system specifications, such as RAM, + CPU type, and R version. + date_publication: '2022-06-12' + bug_reports: https://github.com/csgillespie/benchmarkme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=benchmarkme + url_git: https://github.com/csgillespie/benchmarkme +benchmarkmeData: + version: 1.0.4 + title: Data Set for the 'benchmarkme' Package + maintainer: Colin Gillespie + description: |- + Crowd sourced benchmarks from running the + 'benchmarkme' package. + date_publication: '2020-04-23' + bug_reports: https://github.com/csgillespie/benchmarkme-data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=benchmarkmeData + url_git: https://github.com/csgillespie/benchmarkme-data +benchr: + version: 0.2.5 + title: High Precise Measurement of R Expressions Execution Time + maintainer: Artem Klevtsov + description: |- + Provides infrastructure to accurately measure and compare + the execution time of R expressions. + date_publication: '2020-03-07' + bug_reports: https://gitlab.com/artemklevtsov/benchr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=benchr + url_git: https://gitlab.com/artemklevtsov/benchr +BEND: + version: '1.0' + title: Bayesian Estimation of Nonlinear Data (BEND) + maintainer: Corissa T. Rohloff + description: 'Provides a set of models to estimate nonlinear longitudinal data using + Bayesian estimation methods. These models include the: 1) Bayesian Piecewise Random + Effects Model (Bayes_PREM()) which estimates a piecewise random effects (mixture) + model for a given number of latent classes and a latent number of possible changepoints + in each class, and can incorporate class and outcome predictive covariates (see + Lamm (2022) and Lock et al., (2018) ), + 2) Bayesian Crossed Random Effects Model (Bayes_CREM()) which estimates a linear, + quadratic, exponential, or piecewise crossed random effects models where individuals + are changing groups over time (e.g., students and schools; see Rohloff et al., + (2024) ), and 3) Bayesian Bivariate Piecewise Random Effects + Model (Bayes_BPREM()) which estimates a bivariate piecewise random effects model + to jointly model two related outcomes (e.g., reading and math achievement; see + Peralta et al., (2022) ).' + date_publication: '2024-03-23' + bug_reports: https://github.com/crohlo/BEND/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BEND + url_git: https://github.com/crohlo/BEND +bender: + version: 0.1.1 + title: Bender Client + maintainer: Valentin Thorey + description: |- + R client for Bender Hyperparameters optimizer : + The R client allows you to communicate with the Bender API and therefore submit some new trials within your R script itself. + date_publication: '2019-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bender + url_git: '' +benford: + version: 1.0.1 + title: Benford's Analysis on Large Data Sets + maintainer: Vitor Hugo Moreau + description: Perform the Benford's Analysis to a data set in order to evaluate if + it contains human fabricated data. For more details on the method see Moreau, + 2021, Model Assist. Statist. Appl., 16 (2021) 73–79. . + date_publication: '2021-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=benford + url_git: '' +benford.analysis: + version: 0.1.5 + title: Benford Analysis for Data Validation and Forensic Analytics + maintainer: Carlos Cinelli + description: Provides tools that make it easier to validate data using Benford's + Law. + date_publication: '2018-12-21' + bug_reports: http://github.com/carloscinelli/benford.analysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=benford.analysis + url_git: http://github.com/carloscinelli/benford.analysis +BenfordTests: + version: 1.2.0 + title: Statistical Tests for Evaluating Conformity to Benford's Law + maintainer: Dieter William Joenssen + description: |- + Several specialized statistical tests and support functions + for determining if numerical data could conform to Benford's law. + date_publication: '2015-08-04' + bug_reports: '' + url: https://www.researchgate.net/profile/Dieter_Joenssen + url_cran: https://CRAN.R-project.org/package=BenfordTests + url_git: '' +bennu: + version: 0.3.0 + title: Bayesian Estimation of Naloxone Kit Number Under-Reporting + maintainer: Mike Irvine + description: |- + Bayesian model and associated tools for generating estimates of + total naloxone kit numbers distributed and used from naloxone kit orders + data. Provides functions for generating simulated data of naloxone kit use + and functions for generating samples from the posterior. + date_publication: '2023-09-14' + bug_reports: https://github.com/sempwn/bennu/issues + url: https://sempwn.github.io/bennu/ + url_cran: https://CRAN.R-project.org/package=bennu + url_git: '' +bentcableAR: + version: 0.3.1 + title: |- + Bent-Cable Regression for Independent Data or Autoregressive + Time Series + maintainer: Grace Chiu + description: |2- + + Included are two main interfaces, bentcable.ar() and + bentcable.dev.plot(), for fitting and diagnosing bent-cable + regressions for autoregressive time-series data (Chiu and + Lockhart 2010, ) or independent data (time + series or otherwise - Chiu, Lockhart and Routledge 2006, + ). Some components in the package + can also be used as stand-alone functions. The bent cable + (linear-quadratic-linear) generalizes the broken stick + (linear-linear), which is also handled by this package. Version + 0.2 corrected a glitch in the computation of confidence intervals + for the CTP. References that were updated from Versions 0.2.1 and + 0.2.2 appear in Version 0.2.3 and up. Version 0.3.0 improved + robustness of the error-message producing mechanism. Version 0.3.1 + improves the NAMESPACE file of the package. It is the author's + intention to distribute any future updates via GitHub. + date_publication: '2022-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bentcableAR + url_git: '' +benthos: + version: 1.3-8 + title: Marine Benthic Ecosystem Analysis + maintainer: Dennis Walvoort + description: |- + Preprocessing tools and biodiversity measures + (species abundance, species richness, population heterogeneity and + sensitivity) for analysing marine benthic data. See Van Loon et al. + (2015) for an application of + these tools. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=benthos + url_git: '' +BeQut: + version: 0.1.0 + title: Bayesian Estimation for Quantile Regression Mixed Models + maintainer: Antoine Barbieri + description: Using a Bayesian estimation procedure, this package fits linear quantile + regression models such as linear quantile models, linear quantile mixed models, + quantile regression joint models for time-to-event and longitudinal data. The + estimation procedure is based on the asymmetric Laplace distribution and the 'JAGS' + software is used to get posterior samples (Yang, Luo, DeSantis (2019) ). + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BeQut + url_git: '' +Bergm: + version: 5.0.7 + title: Bayesian Exponential Random Graph Models + maintainer: Alberto Caimo + description: |- + Bayesian analysis for exponential random graph models using + advanced computational algorithms. More information can be found at: + . + date_publication: '2023-12-06' + bug_reports: '' + url: https://acaimo.github.io/Bergm/ + url_cran: https://CRAN.R-project.org/package=Bergm + url_git: '' +BerkeleyForestsAnalytics: + version: 2.0.4 + title: Compute and Summarize Core Forest Metrics from Field Data + maintainer: Kea Rutherford + description: |- + A suite of open-source R functions designed to produce standard + metrics for forest management and ecology from forest inventory data. The + overarching goal is to minimize potential inconsistencies introduced by the + algorithms used to compute and summarize core forest metrics. Learn more + about the purpose of the package and the specific algorithms used in the + package at . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BerkeleyForestsAnalytics + url_git: https://github.com/kearutherford/BerkeleyForestsAnalytics +Bernadette: + version: 1.1.6 + title: Bayesian Inference and Model Selection for Stochastic Epidemics + maintainer: Lampros Bouranis + description: |- + Bayesian analysis for stochastic extensions of non-linear + dynamic systems using advanced computational algorithms. Described in Bouranis, L., Demiris, N., Kalogeropoulos, K., and Ntzoufras, I. (2022) . + date_publication: '2025-02-28' + bug_reports: https://github.com/bernadette-eu/Bernadette/issues/ + url: https://bernadette-eu.github.io/ + url_cran: https://CRAN.R-project.org/package=Bernadette + url_git: '' +berryFunctions: + version: 1.22.5 + title: Function Collection Related to Plotting and Hydrology + maintainer: Berry Boessenkool + description: |- + Draw horizontal histograms, color scattered points by 3rd dimension, + enhance date- and log-axis plots, zoom in X11 graphics, trace errors and warnings, + use the unit hydrograph in a linear storage cascade, convert lists to data.frames and arrays, + fit multiple functions. + date_publication: '2024-02-16' + bug_reports: https://github.com/brry/berryFunctions + url: '' + url_cran: https://CRAN.R-project.org/package=berryFunctions + url_git: https://github.com/brry/berryFunctions +bespatial: + version: 0.1.2 + title: Boltzmann Entropy for Spatial Data + maintainer: Jakub Nowosad + description: |- + Calculates several entropy metrics for spatial data + inspired by Boltzmann's entropy formula. + It includes metrics introduced by Cushman for landscape mosaics + (Cushman (2015) ), + and landscape gradients and point patterns + (Cushman (2021) ); by Zhao and Zhang for + landscape mosaics (Zhao and Zhang (2019) ); + and by Gao et al. for landscape gradients + (Gao et al. (2018) ; Gao and Li (2019) ). + date_publication: '2024-06-07' + bug_reports: https://github.com/Nowosad/bespatial/issues + url: https://jakubnowosad.com/bespatial/ + url_cran: https://CRAN.R-project.org/package=bespatial + url_git: '' +BeSS: + version: 2.0.4 + title: Best Subset Selection in Linear, Logistic and CoxPH Models + maintainer: Canhong Wen + description: An implementation of best subset selection in generalized linear model + and Cox proportional hazard model via the primal dual active set algorithm proposed + by Wen, C., Zhang, A., Quan, S. and Wang, X. (2020) . + The algorithm formulates coefficient parameters and residuals as primal and dual + variables and utilizes efficient active set selection strategies based on the + complementarity of the primal and dual variables. + date_publication: '2024-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BeSS + url_git: '' +Bessel: + version: 0.6-1 + title: Computations and Approximations for Bessel Functions + maintainer: Martin Maechler + description: |- + Computations for Bessel function for complex, real and partly + 'mpfr' (arbitrary precision) numbers; notably interfacing TOMS 644; + approximations for large arguments, experiments, etc. + date_publication: '2024-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bessel + url_git: https://specfun.r-forge.r-project.org/ +bestglm: + version: 0.37.3 + title: Best Subset GLM and Regression Utilities + maintainer: Yuanhao Lai + description: |- + Best subset glm using information criteria or cross-validation, + carried by using 'leaps' algorithm (Furnival and Wilson, 1974) + or complete enumeration (Morgan and Tatar, 1972) . + Implements PCR and PLS using AIC/BIC. + Implements one-standard deviation rule for use with the 'caret' package. + date_publication: '2020-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bestglm + url_git: '' +besthr: + version: 0.3.2 + title: Generating Bootstrap Estimation Distributions of HR Data + maintainer: Dan MacLean + description: |- + Creates plots showing scored HR experiments and plots of distribution of + means of ranks of HR score from bootstrapping. Authors (2019) . + date_publication: '2023-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=besthr + url_git: '' +Bestie: + version: 0.1.5 + title: Bayesian Estimation of Intervention Effects + maintainer: Jack Kuipers + description: An implementation of intervention effect estimation for DAGs (directed + acyclic graphs) learned from binary or continuous data. First, parameters are + estimated or sampled for the DAG and then interventions on each node (variable) + are propagated through the network (do-calculus). Both exact computation (for + continuous data or for binary data up to around 20 variables) and Monte Carlo + schemes (for larger binary networks) are implemented. + date_publication: '2022-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bestie + url_git: '' +bestNormalize: + version: 1.9.1 + title: Normalizing Transformation Functions + maintainer: Ryan Andrew Peterson + description: |- + Estimate a suite of normalizing transformations, including + a new adaptation of a technique based on ranks which can guarantee + normally distributed transformed data if there are no ties: ordered + quantile normalization (ORQ). ORQ normalization combines a rank-mapping + approach with a shifted logit approximation that allows + the transformation to work on data outside the original domain. It is + also able to handle new data within the original domain via linear + interpolation. The package is built to estimate the best normalizing + transformation for a vector consistently and accurately. It implements + the Box-Cox transformation, the Yeo-Johnson transformation, three types + of Lambert WxF transformations, and the ordered quantile normalization + transformation. It estimates the normalization efficacy of other + commonly used transformations, and it allows users to specify + custom transformations or normalization statistics. Finally, functionality + can be integrated into a machine learning workflow via recipes. + date_publication: '2023-08-18' + bug_reports: '' + url: https://petersonr.github.io/bestNormalize/ + url_cran: https://CRAN.R-project.org/package=bestNormalize + url_git: https://github.com/petersonR/bestNormalize +BESTree: + version: 0.5.2 + title: Branch-Exclusive Splits Trees + maintainer: Beaulac Cedric + description: |- + Decision tree algorithm with a major feature added. Allows for users to define an ordering on the partitioning process. + Resulting in Branch-Exclusive Splits Trees (BEST). Cedric Beaulac and Jeffrey S. Rosentahl (2019) . + date_publication: '2019-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BESTree + url_git: '' +bestridge: + version: 1.0.7 + title: A Comprehensive R Package for Best Subset Selection + maintainer: Liyuan Hu + description: The bestridge package is designed to provide a one-stand service for + users to successfully carry out best ridge regression in various complex situations + via the primal dual active set algorithm proposed by Wen, C., Zhang, A., Quan, + S. and Wang, X. (2020) . This package allows users + to perform the regression, classification, count regression and censored regression + for (ultra) high dimensional data, and it also supports advanced usages like group + variable selection and nuisance variable selection. + date_publication: '2021-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bestridge + url_git: '' +bestSDP: + version: 0.1.2 + title: |- + Burden Estimate of Common Communicable Diseases in Settlements + of Displaced Populations + maintainer: You Li + description: Provides a practical tool for estimating the burden of common communicable + diseases in settlements of displaced populations. An online version of the tool + can be found at . Estimates of + burden of disease aim to synthesize data about cause-specific morbidity and mortality + through a systematic approach that enables evidence-based decisions and comparisons + across settings. The focus of this tool is on four acute communicable diseases + and syndromes, including Acute respiratory infections, Acute diarrheal diseases, + Acute jaundice syndrome and Acute febrile illnesses. + date_publication: '2019-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bestSDP + url_git: '' +BET: + version: 0.5.4 + title: Binary Expansion Testing + maintainer: Wan Zhang + description: 'Nonparametric detection of nonuniformity and dependence with Binary + Expansion Testing (BET). See Kai Zhang (2019) BET on Independence, Journal of + the American Statistical Association, 114:528, 1620-1637, , + Kai Zhang, Wan Zhang, Zhigen Zhao, Wen Zhou. (2023). BEAUTY Powered BEAST, and + Wan Zhang, Zhigen Zhao, Michael Baiocchi, Yao Li, Kai Zhang. (2023) SorBET: A + Fast and Powerful Algorithm to Test Dependence of Variables, Techinical report.' + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BET + url_git: '' +betaBayes: + version: 1.0.1 + title: Bayesian Beta Regression + maintainer: Haiming Zhou + description: Provides a class of Bayesian beta regression models for the analysis + of continuous data with support restricted to an unknown finite support. The response + variable is modeled using a four-parameter beta distribution with the mean or + mode parameter depending linearly on covariates through a link function. When + the response support is known to be (0,1), the above class of models reduce to + traditional (0,1) supported beta regression models. Model choice is carried out + via the logarithm of the pseudo marginal likelihood (LPML), the deviance information + criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou + and Huang (2022) . + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=betaBayes + url_git: '' +BetaBit: + version: '2.2' + title: Mini Games from Adventures of Beta and Bit + maintainer: Przemyslaw Biecek + description: |- + Three games: proton, frequon and regression. Each one is a console-based data-crunching game for younger and older data scientists. + Act as a data-hacker and find Slawomir Pietraszko's credentials to the Proton server. + In proton you have to solve four data-based puzzles to find the login and password. + There are many ways to solve these puzzles. You may use loops, data filtering, ordering, aggregation or other tools. + Only basics knowledge of R is required to play the game, yet the more functions you know, the more approaches you can try. + In frequon you will help to perform statistical cryptanalytic attack on a corpus of ciphered messages. + This time seven sub-tasks are pushing the bar much higher. Do you accept the challenge? + In regression you will test your modeling skills in a series of eight sub-tasks. + Try only if ANOVA is your close friend. + It's a part of Beta and Bit project. + You will find more about the Beta and Bit project at . + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BetaBit + url_git: https://github.com/BetaAndBit/Charts +betacal: + version: 0.1.0 + title: Beta Calibration + maintainer: Telmo M Silva Filho + description: |- + Fit beta calibration models and obtain calibrated probabilities from + them. + date_publication: '2017-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=betacal + url_git: '' +betaclust: + version: 1.0.4 + title: |- + A Family of Beta Mixture Models for Clustering Beta-Valued DNA + Methylation Data + maintainer: Koyel Majumdar + description: A family of novel beta mixture models (BMMs) has been developed by + Majumdar et al. (2022) to appositely model the + beta-valued cytosine-guanine dinucleotide (CpG) sites, to objectively identify + methylation state thresholds and to identify the differentially methylated CpG + (DMC) sites using a model-based clustering approach. The family of beta mixture + models employs different parameter constraints applicable to different study settings. + The EM algorithm is used for parameter estimation, with a novel approximation + during the M-step providing tractability and ensuring computational feasibility. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=betaclust + url_git: '' +betaDelta: + version: 1.0.5 + title: Confidence Intervals for Standardized Regression Coefficients + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Generates confidence intervals for standardized regression coefficients + using delta method standard errors for models fitted by lm() + as described in Yuan and Chan (2011) + and Jones and Waller (2015) . + The package can also be used to generate confidence intervals for + differences of standardized regression coefficients + and as a general approach to performing the delta method. + A description of the package and code examples + are presented in Pesigan, Sun, and Cheung (2023) . + date_publication: '2024-04-14' + bug_reports: https://github.com/jeksterslab/betaDelta/issues + url: https://jeksterslab.github.io/betaDelta/ + url_cran: https://CRAN.R-project.org/package=betaDelta + url_git: https://github.com/jeksterslab/betaDelta +betafunctions: + version: 1.9.0 + title: |- + Functions for Working with Two- And Four-Parameter Beta + Probability Distributions and Psychometric Analysis of + Classifications + maintainer: Haakon Eidem Haakstad + description: |- + Package providing a number of functions for working with Two- and + Four-parameter Beta and closely related distributions (i.e., the Gamma- + Binomial-, and Beta-Binomial distributions). + Includes, among other things: + - d/p/q/r functions for Four-Parameter Beta distributions and Generalized + "Binomial" (continuous) distributions, and d/p/r- functions for Beta- + Binomial distributions. + - d/p/q/r functions for Two- and Four-Parameter Beta distributions + parameterized in terms of their means and variances rather than their + shape-parameters. + - Moment generating functions for Binomial distributions, Beta-Binomial + distributions, and observed value distributions. + - Functions for estimating classification accuracy and consistency, + making use of the Classical Test-Theory based 'Livingston and Lewis' (L&L) + and 'Hanson and Brennan' approaches. + A shiny app is available, providing a GUI for the L&L approach when used + for binary classifications. For url to the app, see documentation for the + LL.CA() function. + Livingston and Lewis (1995) . + Lord (1965) . + Hanson (1991) . + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=betafunctions + url_git: '' +betaMC: + version: 1.3.2 + title: Monte Carlo for Regression Effect Sizes + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Generates Monte Carlo confidence intervals + for standardized regression coefficients (beta) and other effect sizes, + including multiple correlation, semipartial correlations, + improvement in R-squared, squared partial correlations, + and differences in standardized regression coefficients, + for models fitted by lm(). + 'betaMC' combines ideas from Monte Carlo confidence intervals for the indirect effect + (Pesigan and Cheung, 2023 ) + and the sampling covariance matrix of regression coefficients + (Dudgeon, 2017 ) + to generate confidence intervals effect sizes in regression. + date_publication: '2024-04-14' + bug_reports: https://github.com/jeksterslab/betaMC/issues + url: https://jeksterslab.github.io/betaMC/ + url_cran: https://CRAN.R-project.org/package=betaMC + url_git: https://github.com/jeksterslab/betaMC +betaNB: + version: 1.0.5 + title: Bootstrap for Regression Effect Sizes + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Generates nonparametric bootstrap confidence intervals + (Efron and Tibshirani, 1993: ) + for standardized regression coefficients (beta) and other effect sizes, + including multiple correlation, semipartial correlations, + improvement in R-squared, squared partial correlations, + and differences in standardized regression coefficients, + for models fitted by lm(). + date_publication: '2025-01-10' + bug_reports: https://github.com/jeksterslab/betaNB/issues + url: https://jeksterslab.github.io/betaNB/ + url_cran: https://CRAN.R-project.org/package=betaNB + url_git: https://github.com/jeksterslab/betaNB +betapart: + version: '1.6' + title: |- + Partitioning Beta Diversity into Turnover and Nestedness + Components + maintainer: Andres Baselga + description: Functions to compute pair-wise dissimilarities (distance matrices) + and multiple-site dissimilarities, separating the turnover and nestedness-resultant + components of taxonomic (incidence and abundance based), functional and phylogenetic + beta diversity. + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=betapart + url_git: '' +BetaPASS: + version: 1.1-2 + title: Calculate Power and Sample Size with Beta Regression + maintainer: Jinpu Li + description: |- + Power calculations are a critical component of any research study to determine the + minimum sample size necessary to detect differences between multiple groups. + Researchers often work with data taking the form of proportions that can be modeled with + a beta distribution. Here we present an R package, 'BetaPASS', that perform power and + sample size calculations for data following a beta distribution with comparative + nonparametric output. This package allows flexibility with multiple options for link + functions to fit the data and graphing functionality for visual comparisons. + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BetaPASS + url_git: '' +betaper: + version: 1.1-2 + title: |- + Taxonomic Uncertainty on Multivariate Analyses of Ecological + Data + maintainer: Luis Cayuela + description: Permutational method to incorporate taxonomic uncertainty and some + functions to assess its effects on parameters of some widely used multivariate + methods in ecology, as explained in Cayuela et al. (2011) . + date_publication: '2020-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=betaper + url_git: '' +betareg: + version: 3.2-1 + title: Beta Regression + maintainer: Achim Zeileis + description: |- + Beta regression for modeling beta-distributed dependent variables on the open unit interval (0, 1), + e.g., rates and proportions, see Cribari-Neto and Zeileis (2010) . + Moreover, extended-support beta regression models can accommodate dependent variables with + boundary observations at 0 and/or 1. For the classical beta regression model, alternative specifications are + provided: Bias-corrected and bias-reduced estimation, finite mixture models, and recursive partitioning for + beta regression, see Grün, Kosmidis, and Zeileis (2012) . + date_publication: '2024-09-12' + bug_reports: https://topmodels.R-Forge.R-project.org/betareg/contact.html + url: '' + url_cran: https://CRAN.R-project.org/package=betareg + url_git: https://topmodels.R-Forge.R-project.org/betareg/ +betaSandwich: + version: 1.0.7 + title: |- + Robust Confidence Intervals for Standardized Regression + Coefficients + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Generates robust confidence intervals for standardized regression coefficients + using heteroskedasticity-consistent standard errors for models fitted by lm() + as described in Dudgeon (2017) . + The package can also be used to generate confidence intervals for R-squared, + adjusted R-squared, and differences of standardized regression coefficients. + A description of the package and code examples + are presented in Pesigan, Sun, and Cheung (2023) . + date_publication: '2024-04-14' + bug_reports: https://github.com/jeksterslab/betaSandwich/issues + url: https://jeksterslab.github.io/betaSandwich/ + url_cran: https://CRAN.R-project.org/package=betaSandwich + url_git: https://github.com/jeksterslab/betaSandwich +betaselectr: + version: 0.1.0 + title: Betas-Select in Structural Equation Models and Linear Models + maintainer: Shu Fai Cheung + description: |- + It computes betas-select, coefficients after standardization in + structural equation models and regression models, standardizing only selected + variables. Supports models with moderation, with product terms formed after + standardization. It also offers confidence intervals that account for + standardization, including bootstrap confidence intervals as proposed by + Cheung et al. (2022) . + date_publication: '2024-11-11' + bug_reports: https://github.com/sfcheung/betaselectr/issues + url: https://sfcheung.github.io/betaselectr/ + url_cran: https://CRAN.R-project.org/package=betaselectr + url_git: '' +betategarch: + version: '3.3' + title: |- + Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH + Models + maintainer: Genaro Sucarrat + description: Simulation, estimation and forecasting of first-order Beta-Skew-t-EGARCH + models with leverage (one-component, two-component, skewed versions). + date_publication: '2016-10-16' + bug_reports: '' + url: http://www.sucarrat.net/ + url_cran: https://CRAN.R-project.org/package=betategarch + url_git: '' +bethel: + version: '0.2' + title: Bethel's algorithm. + maintainer: Michele De Meo + description: The sample size according to the Bethel's procedure. + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bethel + url_git: '' +BETS: + version: 0.4.9 + title: Brazilian Economic Time Series + maintainer: Talitha Speranza + description: |- + It provides access to and information about the most important + Brazilian economic time series - from the Getulio Vargas Foundation , + the Central Bank of Brazil and the Brazilian Institute of Geography + and Statistics . It also presents tools for managing, analysing (e.g. + generating dynamic reports with a complete analysis of a series) and exporting + these time series. + date_publication: '2018-09-28' + bug_reports: https://github.com/nmecsys/BETS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BETS + url_git: https://github.com/nmecsys/BETS +bets.covid19: + version: 1.0.0 + title: The BETS Model for Early Epidemic Data + maintainer: Qingyuan Zhao + description: 'Implements likelihood inference for early epidemic analysis. BETS + is short for the four key epidemiological events being modeled: Begin of exposure, + End of exposure, time of Transmission, and time of Symptom onset. The package + contains a dataset of the trajectory of confirmed cases during the coronavirus + disease (COVID-19) early outbreak. More detail of the statistical methods can + be found in Zhao et al. (2020) .' + date_publication: '2020-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bets.covid19 + url_git: https://github.com/qingyuanzhao/bets.covid19 +BetterReg: + version: 0.2.0 + title: Better Statistics for OLS and Binomial Logistic Regression + maintainer: Chris Aberson + description: Provides squared semi partial correlations, tolerance, Mahalanobis, + Likelihood Ratio Chi Square, and Pseudo R Square. Aberson, C. L. (2022) . + date_publication: '2022-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BetterReg + url_git: '' +BeviMed: + version: '5.10' + title: Bayesian Evaluation of Variant Involvement in Mendelian Disease + maintainer: Daniel Greene + description: A fast integrative genetic association test for rare diseases based + on a model for disease status given allele counts at rare variant sites. Probability + of association, mode of inheritance and probability of pathogenicity for individual + variants are all inferred in a Bayesian framework - 'A Fast Association Test for + Identifying Pathogenic Variants Involved in Rare Diseases', Greene et al 2017 + . + date_publication: '2024-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BeviMed + url_git: '' +bexy: + version: 0.1.3 + title: Visualize and Parse the Output of 'BeXY' + maintainer: Madleina Caduff + description: Provides functions for summarizing and plotting the output of the command-line + tool 'BeXY' (), a tool that performs Bayesian + inference of sex chromosome karyotypes and sex-linked scaffolds from low-depth + sequencing data. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bexy + url_git: '' +BeyondBenford: + version: '1.4' + title: |- + Compare the Goodness of Fit of Benford's and Blondeau Da Silva's + Digit Distributions to a Given Dataset + maintainer: Blondeau Da Silva Stephane + description: 'Allows to compare the goodness of fit of Benford''s and Blondeau Da + Silva''s digit distributions in a dataset. It is used to check whether the data + distribution is consistent with theoretical distributions highlighted by Blondeau + Da Silva or not (through the dat.distr() function): this ideal theoretical distribution + must be at least approximately followed by the data for the use of Blondeau Da + Silva''s model to be well-founded. It also enables to plot histograms of digit + distributions, both observed in the dataset and given by the two theoretical approaches + (with the digit.ditr() function). Finally, it proposes to quantify the goodness + of fit via Pearson''s chi-squared test (with the chi2() function).' + date_publication: '2020-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BeyondBenford + url_git: '' +beyondWhittle: + version: 1.3.0 + title: Bayesian Spectral Inference for Time Series + maintainer: Renate Meyer + description: Implementations of Bayesian parametric, nonparametric and semiparametric + procedures for univariate and multivariate time series. The package is based on + the methods presented in C. Kirch et al (2018) , A. Meier + (2018) and Y. Tang et + al (2023) . It was supported by DFG grants KI 1443/3-1 + and KI 1443/3-2. + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=beyondWhittle + url_git: '' +bezier: + version: 1.1.2 + title: Toolkit for Bezier Curves and Splines + maintainer: Aaron Olsen + description: The bezier package is a toolkit for working with Bezier curves and + splines. The package provides functions for point generation, arc length estimation, + degree elevation and curve fitting. + date_publication: '2018-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bezier + url_git: '' +bfast: + version: 1.7.0 + title: Breaks for Additive Season and Trend + maintainer: Dainius Masiliūnas + description: |- + Decomposition of time series into + trend, seasonal, and remainder components with methods for detecting and + characterizing abrupt changes within the trend and seasonal components. 'BFAST' + can be used to analyze different types of satellite image time series and can + be applied to other disciplines dealing with seasonal or non-seasonal time + series, such as hydrology, climatology, and econometrics. The algorithm can be + extended to label detected changes with information on the parameters of the + fitted piecewise linear models. 'BFAST' monitoring functionality is described + in Verbesselt et al. (2010) . 'BFAST monitor' + provides functionality to detect disturbance in near real-time based on 'BFAST'- + type models, and is described in Verbesselt et al. (2012) . + 'BFAST Lite' approach is a flexible approach that handles missing data + without interpolation, and will be described in an upcoming paper. + Furthermore, different models can now be used to fit the + time series data and detect structural changes (breaks). + date_publication: '2024-10-22' + bug_reports: https://github.com/bfast2/bfast/issues + url: https://bfast2.github.io/ + url_cran: https://CRAN.R-project.org/package=bfast + url_git: '' +bfboinet: + version: 0.2.0 + title: |- + Backfill Bayesian Optimal Interval Design Using Efficacy and + Toxicity + maintainer: Jing Zhu + description: |- + The backfill Bayesian optimal interval design using efficacy and toxicity outcomes for + dose optimization (BF-BOIN-ET) design is a novel clinical trial design to allow patients to be + backfilled at lower doses during a dose-finding trial while prioritizing the dose-escalation + cohort to explore a higher dose. The advantages compared to the other designs in terms of the + percentage of correct optimal dose (OD) selection, reducing the sample size, and shortening the + duration of the trial, in various realistic setting. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bfboinet + url_git: '' +BFF: + version: 4.2.1 + title: Bayes Factor Functions + maintainer: Rachael Shudde + description: Bayes factors represent the ratio of probabilities assigned to data + by competing scientific hypotheses. However, one drawback of Bayes factors is + their dependence on prior specifications that define null and alternative hypotheses. + Additionally, there are challenges in their computation. To address these issues, + we define Bayes factor functions (BFFs) directly from common test statistics. + BFFs express Bayes factors as a function of the prior densities used to define + the alternative hypotheses. These prior densities are centered on standardized + effects, which serve as indices for the BFF. Therefore, BFFs offer a summary of + evidence in favor of alternative hypotheses that correspond to a range of scientifically + interesting effect sizes. Such summaries remove the need for arbitrary thresholds + to determine "statistical significance." BFFs are available in closed form and + can be easily computed from z, t, chi-squared, and F statistics. They depend on + hyperparameters "r" and "tau^2", which determine the shape and scale of the prior + distributions defining the alternative hypotheses. Plots of BFFs versus effect + size provide informative summaries of hypothesis tests that can be easily aggregated + across studies. + date_publication: '2024-07-28' + bug_reports: https://github.com/rshudde/BFF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BFF + url_git: https://github.com/rshudde/BFF +BFI: + version: 2.0.1 + title: Bayesian Federated Inference + maintainer: Hassan Pazira + description: The Bayesian Federated Inference ('BFI') method combines inference + results obtained from local data sets in the separate centers. In this version + of the package, the 'BFI' methodology is programmed for linear, logistic and survival + regression models. For GLMs, see Jonker, Pazira and Coolen (2024) ; + for survival models, see Pazira, Massa, Weijers, Coolen and Jonker (2024) ; + and for heterogeneous populations, see Jonker, Pazira and Coolen (2024) . + date_publication: '2024-07-04' + bug_reports: '' + url: https://hassanpazira.github.io/BFI/ + url_cran: https://CRAN.R-project.org/package=BFI + url_git: '' +bfp: + version: 0.0-48 + title: Bayesian Fractional Polynomials + maintainer: Daniel Sabanes Bove + description: |- + Implements the Bayesian paradigm for fractional + polynomial models under the assumption of normally distributed error terms, see + Sabanes Bove, D. and Held, L. (2011) . + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bfp + url_git: '' +BFpack: + version: 1.4.2 + title: Flexible Bayes Factor Testing of Scientific Expectations + maintainer: Joris Mulder + description: |- + Implementation of default Bayes factors + for testing statistical hypotheses under various statistical models. The package is + intended for applied quantitative researchers in the + social and behavioral sciences, medical research, + and related fields. The Bayes factor tests can be + executed for statistical models such as + univariate and multivariate normal linear models, + correlation analysis, generalized linear models, special cases of + linear mixed models, survival models, relational + event models. Parameters that can be tested are + location parameters (e.g., group means, regression coefficients), + variances (e.g., group variances), and measures of + association (e.g,. polychoric/polyserial/biserial/tetrachoric/product + moments correlations), among others. + The statistical underpinnings are + described in + O'Hagan (1995) , + De Santis and Spezzaferri (2001) , + Mulder and Xin (2022) , + Mulder and Gelissen (2019) , + Mulder (2016) , + Mulder and Fox (2019) , + Mulder and Fox (2013) , + Boeing-Messing, van Assen, Hofman, Hoijtink, and Mulder (2017) , + Hoijtink, Mulder, van Lissa, and Gu (2018) , + Gu, Mulder, and Hoijtink (2018) , + Hoijtink, Gu, and Mulder (2018) , and + Hoijtink, Gu, Mulder, and Rosseel (2018) . When using the + packages, please refer to the package Mulder et al. (2021) + and the relevant methodological papers. + date_publication: '2025-02-10' + bug_reports: https://github.com/jomulder/BFpack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BFpack + url_git: https://github.com/jomulder/BFpack +bfpwr: + version: 0.1.3 + title: Power and Sample Size Calculations for Bayes Factor Analysis + maintainer: Samuel Pawel + description: Implements z-test, t-test, and normal moment prior Bayes factors based + on summary statistics, along with functionality to perform corresponding power + and sample size calculations as described in Pawel and Held (2024) . + date_publication: '2024-10-28' + bug_reports: https://github.com/SamCH93/bfpwr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bfpwr + url_git: https://github.com/SamCH93/bfpwr +BFS: + version: 0.5.12 + title: Get Data from the Swiss Federal Statistical Office + maintainer: Felix Luginbuhl + description: Search and download data from the Swiss Federal Statistical Office + (BFS) APIs . + date_publication: '2024-12-09' + bug_reports: https://github.com/lgnbhl/BFS/issues + url: https://felixluginbuhl.com/BFS/ + url_cran: https://CRAN.R-project.org/package=BFS + url_git: https://github.com/lgnbhl/BFS/ +bfsl: + version: 0.2.0 + title: Best-Fit Straight Line + maintainer: Patrick Sturm + description: |- + How to fit a straight line through a set of points with errors in + both coordinates? The 'bfsl' package implements the York regression + (York, 2004 ). It provides unbiased estimates of the + intercept, slope and standard errors for the best-fit straight line to + independent points with (possibly correlated) normally distributed errors in + both x and y. Other commonly used errors-in-variables methods, such as + orthogonal distance regression, geometric mean regression or Deming regression + are special cases of the 'bfsl' solution. + date_publication: '2021-09-23' + bug_reports: https://github.com/pasturm/bfsl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bfsl + url_git: https://github.com/pasturm/bfsl +bfsMaps: + version: 1.99.3 + title: Plot Maps from Switzerland by Swiss Federal Statistical Office + maintainer: Andri Signorell + description: |- + At the Swiss Federal Statistical Office (SFSO), spatial maps of Switzerland are available free of charge as 'Cartographic bases for small-scale thematic mapping'. This package contains convenience functions to import ESRI (Environmental Systems Research Institute) shape files using the package 'sf' and to plot them easily and quickly without having to worry too much about the technical details. + It contains utilities to combine multiple areas to one single polygon and to find neighbours for single regions. For any point on a map, a special locator can be used to determine to which municipality, district or canton it belongs. + date_publication: '2023-06-30' + bug_reports: https://github.com/AndriSignorell/bfsMaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bfsMaps + url_git: https://github.com/AndriSignorell/bfsMaps/ +bfw: + version: 0.4.2 + title: Bayesian Framework for Computational Modeling + maintainer: Øystein Olav Skaar + description: |- + Derived from the work of Kruschke (2015, + ), the present package aims to provide a framework + for conducting Bayesian analysis using Markov chain Monte Carlo (MCMC) + sampling utilizing the Just Another Gibbs Sampler ('JAGS', Plummer, + 2003, ). The initial version + includes several modules for conducting Bayesian equivalents of + chi-squared tests, analysis of variance (ANOVA), multiple + (hierarchical) regression, softmax regression, and for fitting data + (e.g., structural equation modeling). + date_publication: '2022-02-22' + bug_reports: https://github.com/oeysan/bfw/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=bfw + url_git: https://github.com/oeysan/bfw/ +BGData: + version: 2.4.1 + title: A Suite of Packages for Analysis of Big Genomic Data + maintainer: Alexander Grueneberg + description: |- + An umbrella package providing a phenotype/genotype data structure + and scalable and efficient computational methods for large genomic datasets + in combination with several other packages: 'BEDMatrix', 'LinkedMatrix', + and 'symDMatrix'. + date_publication: '2023-03-22' + bug_reports: https://github.com/QuantGen/BGData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BGData + url_git: https://github.com/QuantGen/BGData +bgev: + version: '0.1' + title: Bimodal GEV Distribution with Location Parameter + maintainer: Thiago Sousa Developer + description: Density, distribution function, quantile function random generation + and estimation of bimodal GEV distribution given in Otiniano et al. (2023) . + This new generalization of the well-known GEV (Generalized Extreme Value) distribution + is useful for modeling heterogeneous bimodal data from different areas. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bgev + url_git: '' +bgeva: + version: 0.3-1 + title: Binary Generalized Extreme Value Additive Models + maintainer: Giampiero Marra + description: Routine for fitting regression models for binary rare events with linear + and nonlinear covariate effects when using the quantile function of the Generalized + Extreme Value random variable. + date_publication: '2017-05-19' + bug_reports: '' + url: http://www.ucl.ac.uk/statistics/people/giampieromarra + url_cran: https://CRAN.R-project.org/package=bgeva + url_git: '' +BGFD: + version: '0.1' + title: Bell-G and Complementary Bell-G Family of Distributions + maintainer: Michail Tsagris + description: |- + Evaluates the probability density function, cumulative distribution function, quantile function, random numbers, survival function, hazard rate function, and maximum likelihood estimates for the following distributions: Bell exponential, Bell extended exponential, Bell Weibull, Bell extended Weibull, Bell-Fisk, Bell-Lomax, Bell Burr-XII, Bell Burr-X, complementary Bell exponential, complementary Bell extended exponential, complementary Bell Weibull, complementary Bell extended Weibull, complementary Bell-Fisk, complementary Bell-Lomax, complementary Bell Burr-XII and complementary Bell Burr-X distribution. Related work includes: + a) Fayomi A., Tahir M. H., Algarni A., Imran M. and Jamal F. (2022). "A new useful exponential model with applications to quality control and + actuarial data". Computational Intelligence and Neuroscience, 2022. . + b) Alanzi, A. R., Imran M., Tahir M. H., Chesneau C., Jamal F. Shakoor S. and Sami, W. (2023). "Simulation analysis, + properties and applications on a new Burr XII model based on the Bell-X functionalities". AIMS Mathematics, 8(3): 6970-7004. . + c) Algarni A. (2022). "Group Acceptance Sampling Plan Based on New Compounded Three-Parameter Weibull Model". Axioms, 11(9): 438. . + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BGFD + url_git: '' +BGGE: + version: 0.6.5 + title: Bayesian Genomic Linear Models Applied to GE Genome Selection + maintainer: Italo Granato + description: |- + Application of genome prediction for a continuous variable, focused + on genotype by environment (GE) genomic selection models (GS). It consists a group of functions + that help to create regression kernels for some GE genomic models proposed by Jarquín et al. (2014) + and Lopez-Cruz et al. (2015) . Also, it computes genomic predictions based on Bayesian approaches. + The prediction function uses an orthogonal transformation of the data and specific priors + present by Cuevas et al. (2014) . + date_publication: '2018-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BGGE + url_git: '' +BGGM: + version: 2.1.5 + title: Bayesian Gaussian Graphical Models + maintainer: Philippe Rast + description: |- + Fit Bayesian Gaussian graphical models. The methods are separated into + two Bayesian approaches for inference: hypothesis testing and estimation. There are + extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, + and node wise predictability. These methods were recently introduced in the Gaussian + graphical model literature, including + Williams (2019) , + Williams and Mulder (2019) , + Williams, Rast, Pericchi, and Mulder (2019) . + date_publication: '2024-12-22' + bug_reports: https://github.com/donaldRwilliams/BGGM/issues + url: https://donaldrwilliams.github.io/BGGM/ + url_cran: https://CRAN.R-project.org/package=BGGM + url_git: '' +bggum: + version: 1.0.2 + title: |- + Bayesian Estimation of Generalized Graded Unfolding Model + Parameters + maintainer: JBrandon Duck-Mayr + description: |- + Provides a Metropolis-coupled Markov chain Monte Carlo sampler, + post-processing and parameter estimation functions, and plotting utilities + for the generalized graded unfolding model of Roberts, Donoghue, and + Laughlin (2000) . + date_publication: '2020-01-19' + bug_reports: https://github.com/duckmayr/bggum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bggum + url_git: https://github.com/duckmayr/bggum +BGLR: + version: 1.1.3 + title: Bayesian Generalized Linear Regression + maintainer: Paulino Perez Rodriguez + description: Bayesian Generalized Linear Regression. + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BGLR + url_git: '' +bgmfiles: + version: 0.0.6 + title: Example BGM Files for the Atlantis Ecosystem Model + maintainer: Michael D. Sumner + description: |- + A collection of box-geometry model (BGM) files for the Atlantis + ecosystem model. Atlantis is a deterministic, biogeochemical, + whole-of-ecosystem model (see for more information). + date_publication: '2016-08-10' + bug_reports: |2- + + https://github.com/AustralianAntarcticDivision/bgmfiles/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=bgmfiles + url_git: https://github.com/AustralianAntarcticDivision/bgmfiles/ +BGmisc: + version: 1.3.3 + title: An R Package for Extended Behavior Genetics Analysis + maintainer: S. Mason Garrison + description: |- + Provides functions for behavior genetics analysis, + including variance component model identification [Hunter et al. (2021) ], + calculation of relatedness coefficients using path-tracing methods + [Wright (1922) ; McArdle & McDonald (1984) ], + inference of relatedness, pedigree conversion, and simulation of multi-generational family data + [Lyu et al. (2024) ]. For a full overview, + see Garrison et al. (2025) . + date_publication: '2025-02-19' + bug_reports: https://github.com/R-Computing-Lab/BGmisc/issues + url: https://r-computing-lab.github.io/BGmisc/ + url_cran: https://CRAN.R-project.org/package=BGmisc + url_git: https://github.com/R-Computing-Lab/BGmisc/ +bgmm: + version: 1.8.5 + title: |- + Gaussian Mixture Modeling Algorithms and the Belief-Based + Mixture Modeling + maintainer: Przemyslaw Biecek + description: |- + Two partially supervised mixture modeling methods: + soft-label and belief-based modeling are implemented. + For completeness, we equipped the package also with the + functionality of unsupervised, semi- and fully supervised + mixture modeling. The package can be applied also to selection + of the best-fitting from a set of models with different + component numbers or constraints on their structures. + For detailed introduction see: + Przemyslaw Biecek, Ewa Szczurek, Martin Vingron, Jerzy + Tiuryn (2012), The R Package bgmm: Mixture Modeling with + Uncertain Knowledge, Journal of Statistical Software + . + date_publication: '2021-10-10' + bug_reports: '' + url: http://bgmm.molgen.mpg.de/ + url_cran: https://CRAN.R-project.org/package=bgmm + url_git: '' +bgms: + version: 0.1.4.2 + title: Bayesian Analysis of Networks of Binary and/or Ordinal Variables + maintainer: Maarten Marsman + description: 'Bayesian variable selection methods for analyzing the structure of + a Markov Random Field model for a network of binary and/or ordinal variables. + Details of the implemented methods can be found in: Marsman, van den Bergh, and + Haslbeck (in press) .' + date_publication: '2024-12-05' + bug_reports: https://github.com/MaartenMarsman/bgms/issues + url: https://maartenmarsman.github.io/bgms/ + url_cran: https://CRAN.R-project.org/package=bgms + url_git: '' +BGPhazard: + version: 2.1.1 + title: Markov Beta and Gamma Processes for Modeling Hazard Rates + maintainer: Emilio Akira Morones Ishikawa + description: |- + Computes the hazard rate estimate as described by + Nieto-Barajas & Walker (2002), Nieto-Barajas (2003), Nieto-Barajas & + Walker (2007) and Nieto-Barajas & Yin (2008). + date_publication: '2023-09-03' + bug_reports: https://github.com/EAMI91/BGPhazard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BGPhazard + url_git: https://github.com/EAMI91/BGPhazard +bgsmtr: + version: '0.7' + title: Bayesian Group Sparse Multi-Task Regression + maintainer: Yin Song + description: Implementation of Bayesian multi-task regression models and was developed + within the context of imaging genetics. The package can currently fit two models. + The Bayesian group sparse multi-task regression model of Greenlaw et al. (2017) + can be fit with implementation using Gibbs sampling. An extension of this model + developed by Song, Ge et al. to accommodate both spatial correlation as well as + correlation across brain hemispheres can also be fit using either mean-field variational + Bayes or Gibbs sampling. The model can also be used more generally for multivariate + (non-imaging) phenotypes with spatial correlation. + date_publication: '2019-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bgsmtr + url_git: '' +bgumbel: + version: 0.0.3 + title: Bimodal Gumbel Distribution + maintainer: Pedro C. Brom + description: Bimodal Gumbel distribution. General functions for performing extreme + value analysis. + date_publication: '2021-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bgumbel + url_git: '' +BGVAR: + version: 2.5.8 + title: Bayesian Global Vector Autoregressions + maintainer: Maximilian Boeck + description: 'Estimation of Bayesian Global Vector Autoregressions (BGVAR) with + different prior setups and the possibility to introduce stochastic volatility. + Built-in priors include the Minnesota, the stochastic search variable selection + and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, + M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: + a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 + . Post-processing functions allow for doing predictions, + structurally identify the model with short-run or sign-restrictions and compute + impulse response functions, historical decompositions and forecast error variance + decompositions. Plotting functions are also available. The package has a companion + paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global + Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, + Vol. 104(9), pp. 1-28 .' + date_publication: '2024-09-30' + bug_reports: https://github.com/mboeck11/BGVAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BGVAR + url_git: https://github.com/mboeck11/BGVAR +bgw: + version: 0.1.3 + title: Bunch-Gay-Welsch Statistical Estimation + maintainer: David S. Bunch + description: |- + Performs statistical estimation and inference-related computations + by accessing and executing modified versions of 'Fortran' subroutines + originally published in the Association for Computing Machinery (ACM) + journal Transactions on Mathematical Software (TOMS) by Bunch, Gay and + Welsch (1993) . The acronym 'BGW' (from the + authors' last names) will be used when making reference to technical + content (e.g., algorithm, methodology) that originally appeared in ACM TOMS. + A key feature of BGW is that it exploits the special structure of statistical + estimation problems within a trust-region-based optimization approach to + produce an estimation algorithm that is much more effective than the usual + practice of using optimization methods and codes originally developed for + general optimization. The 'bgw' package bundles 'R' wrapper (and related) + functions with modified 'Fortran' source code so that it can be compiled and + linked in the 'R' environment for fast execution. This version implements + a function ('bgw_mle.R') that performs maximum likelihood estimation (MLE) + for a user-provided model object that computes probabilities (a.k.a. + probability densities). The original motivation for producing this package + was to provide fast, efficient, and reliable MLE for discrete choice models + that can be called from the 'Apollo' choice modelling 'R' package ( + see ). Starting with the release of + Apollo 3.0, BGW is the default estimation package. However, estimation can also + be performed using BGW in a stand-alone fashion without using 'Apollo' + (as shown in simple examples included in the package). Note also that BGW + capabilities are not limited to MLE, and future extension to other estimators + (e.g., nonlinear least squares, generalized method of moments, etc.) is possible. + The 'Fortran' code included in 'bgw' was modified by one of the + original BGW authors (Bunch) under his rights as confirmed by direct + consultation with the ACM Intellectual Property and Rights Manager. See + . The main + requirement is clear citation of the original publication (see above). + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bgw + url_git: '' +BH: + version: 1.87.0-1 + title: Boost C++ Header Files + maintainer: Dirk Eddelbuettel + description: |- + Boost provides free peer-reviewed portable C++ source + libraries. A large part of Boost is provided as C++ template code + which is resolved entirely at compile-time without linking. This + package aims to provide the most useful subset of Boost libraries + for template use among CRAN packages. By placing these libraries in + this package, we offer a more efficient distribution system for CRAN + as replication of this code in the sources of other packages is + avoided. As of release 1.84.0-0, the following Boost libraries are + included: 'accumulators' 'algorithm' 'align' 'any' 'atomic' 'beast' + 'bimap' 'bind' 'circular_buffer' 'compute' 'concept' 'config' + 'container' 'date_time' 'detail' 'dynamic_bitset' 'exception' + 'flyweight' 'foreach' 'functional' 'fusion' 'geometry' 'graph' 'heap' + 'icl' 'integer' 'interprocess' 'intrusive' 'io' 'iostreams' + 'iterator' 'lambda2' 'math' 'move' 'mp11' 'mpl' 'multiprecision' + 'numeric' 'pending' 'phoenix' 'polygon' 'preprocessor' 'process' + 'propery_tree' 'qvm' 'random' 'range' 'scope_exit' 'smart_ptr' 'sort' + 'spirit' 'tuple' 'type_traits' 'typeof' 'unordered' 'url' 'utility' + 'uuid'. + date_publication: '2024-12-17' + bug_reports: https://github.com/eddelbuettel/bh/issues + url: https://dirk.eddelbuettel.com/code/bh.html + url_cran: https://CRAN.R-project.org/package=BH + url_git: https://github.com/eddelbuettel/bh +BHAI: + version: 0.99.2 + title: Estimate the Burden of Healthcare-Associated Infections + maintainer: Benedikt Zacher + description: Provides an approach which is based on the methodology of the Burden + of Communicable Diseases in Europe (BCoDE) and can be used for large and small + samples such as individual countries. The Burden of Healthcare-Associated Infections + (BHAI) is estimated in disability-adjusted life years, number of infections as + well as number of deaths per year. Results can be visualized with various plotting + functions and exported into tables. + date_publication: '2019-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BHAI + url_git: '' +Bhat: + version: 0.9-12 + title: General Likelihood Exploration + maintainer: Rafael Meza + description: |- + Provides functions for Maximum Likelihood + Estimation, Markov Chain Monte Carlo, finding confidence + intervals. The implementation is heavily based on the + original Fortran source code translated to R. + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bhat + url_git: '' +BHH2: + version: 2016.05.31 + title: Useful Functions for Box, Hunter and Hunter II + maintainer: Kjetil B.Halvorsen + description: |- + Functions and data sets reproducing some examples in + Box, Hunter and Hunter II. Useful for statistical design + of experiments, especially factorial experiments. + date_publication: '2016-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BHH2 + url_git: '' +bhm: + version: '1.18' + title: Biomarker Threshold Models + maintainer: Bingshu E. Chen + description: Contains tools to fit both predictive and prognostic biomarker effects + using biomarker threshold models and continuous threshold models. Evaluate the + treatment effect, biomarker effect and treatment-biomarker interaction using probability + index measurement. Test for treatment-biomarker interaction using residual bootstrap + method. + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bhm + url_git: '' +bhmbasket: + version: 0.9.5 + title: Bayesian Hierarchical Models for Basket Trials + maintainer: Stephan Wojciekowski + description: |- + Provides functions for the evaluation of basket + trial designs with binary endpoints. Operating characteristics of a + basket trial design are assessed by simulating trial data according to + scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and + assessing decision probabilities on stratum and trial-level based on Go / No-go decision making. + The package is build for high flexibility regarding decision rules, + number of interim analyses, number of strata, and recruitment. + The BHMs proposed by + Berry et al. (2013) + and Neuenschwander et al. (2016) , + as well as a model that combines both approaches are implemented. + Functions are provided to implement Bayesian decision rules as for example + proposed by Fisch et al. (2015) . + In addition, posterior point estimates (mean/median) and credible intervals + for response rates and some model parameters can be calculated. + For simulated trial data, bias and mean squared errors of posterior + point estimates for response rates can be provided. + date_publication: '2022-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bhmbasket + url_git: '' +BHMSMAfMRI: + version: '2.2' + title: |- + Bayesian Hierarchical Multi-Subject Multiscale Analysis of + Functional MRI (fMRI) Data + maintainer: Nilotpal Sanyal + description: Package BHMSMAfMRI performs Bayesian hierarchical multi-subject multiscale + analysis of fMRI data as described in Sanyal & Ferreira (2012) , + or other multiscale data, using wavelet-based prior that borrows strength across + subjects and provides posterior smoothed images of the effect sizes and samples + from the posterior distribution. + date_publication: '2024-06-12' + bug_reports: https://github.com/nilotpalsanyal/BHMSMAfMRI/issues + url: https://nilotpalsanyal.github.io/BHMSMAfMRI/ + url_cran: https://CRAN.R-project.org/package=BHMSMAfMRI + url_git: '' +BHSBVAR: + version: 3.1.1 + title: Structural Bayesian Vector Autoregression Models + maintainer: Paul Richardson + description: Provides a function for estimating the parameters of Structural Bayesian + Vector Autoregression models with the method developed by Baumeister and Hamilton + (2015) , Baumeister and Hamilton (2017) , + and Baumeister and Hamilton (2018) . Functions + for plotting impulse responses, historical decompositions, and posterior distributions + of model parameters are also provided. + date_publication: '2022-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BHSBVAR + url_git: '' +BI: + version: 1.2.0 + title: |- + Blinding Assessment Indexes for Randomized, Controlled, Clinical + Trials + maintainer: Marc Schwartz + description: |- + Generate the James Blinding Index, as described in James et al (1996) + and the Bang Blinding Index, + as described in Bang et al (2004) . + These are measures to assess whether or not satisfactory blinding has been + maintained in a randomized, controlled, clinical trial. These can be generated + for trial subjects, research coordinators and principal investigators, based + upon standardized questionnaires that have been administered, to assess whether + or not they can correctly guess to which treatment arm (e.g. placebo or treatment) + subjects were assigned at randomization. + date_publication: '2022-12-14' + bug_reports: https://github.com/marcschwartz/BI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BI + url_git: https://github.com/marcschwartz/BI +BiasCorrector: + version: 0.2.3 + title: A GUI to Correct Measurement Bias in DNA Methylation Analyses + maintainer: Lorenz A. Kapsner + description: |- + A GUI to correct measurement bias in DNA methylation + analyses. The 'BiasCorrector' package just wraps the functions + implemented in the 'R' package 'rBiasCorrection' into a shiny web + application in order to make them more easily accessible. Publication: + Kapsner et al. (2021) . + date_publication: '2024-10-17' + bug_reports: https://github.com/kapsner/BiasCorrector/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BiasCorrector + url_git: https://github.com/kapsner/BiasCorrector +BiasedUrn: + version: 2.0.12 + title: Biased Urn Model Distributions + maintainer: Agner Fog + description: |- + Statistical models of biased sampling in the form of + univariate and multivariate noncentral hypergeometric distributions, + including Wallenius' noncentral hypergeometric distribution and + Fisher's noncentral hypergeometric distribution. + See vignette("UrnTheory") for explanation of these distributions. + Literature: + Fog, A. (2008a). Calculation Methods for Wallenius' Noncentral Hypergeometric Distribution, Communications in Statistics, Simulation and Computation, 37(2) . + Fog, A. (2008b). Sampling methods for Wallenius’ and Fisher’s noncentral hypergeometric distributions, Communications in Statistics—Simulation and Computation, 37(2) + . + date_publication: '2024-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiasedUrn + url_git: '' +bib2df: + version: 1.1.2.0 + title: Parse a BibTeX File to a Data Frame + maintainer: Gianluca Baio + description: Parse a BibTeX file to a data.frame to make it accessible for further + analysis and visualization. + date_publication: '2024-05-16' + bug_reports: https://github.com/ropensci/bib2df/issues/ + url: https://docs.ropensci.org/bib2df/ + url_cran: https://CRAN.R-project.org/package=bib2df + url_git: https://github.com/ropensci/bib2df/ +BiBitR: + version: 0.3.1 + title: R Wrapper for Java Implementation of BiBit + maintainer: De Troyer Ewoud + description: |- + A simple R wrapper for the Java BiBit algorithm from "A + biclustering algorithm for extracting bit-patterns from binary datasets" + from Domingo et al. (2011) . An simple adaption for the BiBit algorithm which allows noise in the biclusters is also introduced as well as a function to guide the algorithm towards given (sub)patterns. Further, a workflow to derive noisy biclusters from discoverd larger column patterns is included as well. + date_publication: '2017-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiBitR + url_git: '' +biblio: + version: 0.0.10 + title: Interacting with BibTeX Databases + maintainer: Miguel Alvarez + description: Reading and writing BibTeX files using data frames in R sessions. + date_publication: '2024-06-07' + bug_reports: https://github.com/kamapu/biblio/issues + url: https://kamapu.github.io/biblio/ + url_cran: https://CRAN.R-project.org/package=biblio + url_git: '' +bibliometrix: + version: 4.3.2 + title: Comprehensive Science Mapping Analysis + maintainer: Massimo Aria + description: |- + Tool for quantitative research in scientometrics and bibliometrics. + It implements the comprehensive workflow for science mapping analysis proposed in Aria M. and + Cuccurullo C. (2017) . + 'bibliometrix' provides various routines for importing bibliographic data from 'SCOPUS', + 'Clarivate Analytics Web of Science' (), 'Digital Science Dimensions' + (), 'OpenAlex' (), 'Cochrane Library' (), 'Lens' (), + and 'PubMed' () databases, performing bibliometric analysis + and building networks for co-citation, coupling, scientific collaboration and co-word analysis. + date_publication: '2025-01-27' + bug_reports: https://github.com/massimoaria/bibliometrix/issues + url: https://www.bibliometrix.org + url_cran: https://CRAN.R-project.org/package=bibliometrix + url_git: https://github.com/massimoaria/bibliometrix +bibliometrixData: + version: 0.3.0 + title: Bibliometrix Example Datasets + maintainer: Massimo Aria + description: It contains some example datasets used in 'bibliometrix'. The data + are bibliographic datasets exported from the 'SCOPUS' () and + 'Clarivate Analytics Web of Science' () databases. + They can be used to test the different features of the package 'bibliometrix' + (). + date_publication: '2022-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bibliometrixData + url_git: '' +biblionetwork: + version: 0.1.0 + title: Create Different Types of Bibliometric Networks + maintainer: Aurélien Goutsmedt + description: 'Functions to find edges for bibliometric networks like bibliographic + coupling network, co-citation network and co-authorship network. The weights of + network edges can be calculated according to different methods, depending on the + type of networks, the type of nodes, and what you want to analyse. These functions + are optimized to be be used on large dataset. The package contains functions inspired + by: Leydesdorff, Loet and Park, Han Woo (2017) ; + Perianes-Rodriguez, Antonio, Ludo Waltman, and Nees Jan Van Eck (2016) ; + Sen, Subir K. and Shymal K. Gan (1983) ; + Shen, Si, Zhu, Danhao, Rousseau, Ronald, Su, Xinning and Wang, Dongbo (2019) ; + Zhao, Dangzhi and Strotmann, Andreas (2008) .' + date_publication: '2021-04-09' + bug_reports: https://github.com/agoutsmedt/biblionetwork/issues + url: https://agoutsmedt.github.io/biblionetwork/ + url_cran: https://CRAN.R-project.org/package=biblionetwork + url_git: https://github.com/agoutsmedt/biblionetwork +bibliorefer: + version: 0.1.1 + title: Generator of Main Scientific References + maintainer: Márcio Eustáquio + description: |- + Generates a list, with a size defined by the user, containing the main scientific references and the frequency distribution of authors and journals in the list obtained. + The database is a dataframe with academic production metadata made available by bibliographic collections such as Scopus, Web of Science, etc. + The temporal evolution of scientific production on a given topic is presented and ordered lists of articles are constructed by number of citations and of authors and journals by level of productivity. + Massimo Aria, Corrado Cuccurullo. (2017) . + Caibo Zhou, Wenyan Song. (2021) . + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bibliorefer + url_git: '' +biblioverlap: + version: 1.0.2 + title: Document-Level Matching Between Bibliographic Datasets + maintainer: Gabriel Vieira + description: |- + Identifies and visualizes document overlap in any number of bibliographic datasets. + This package implements the identification of overlapping documents through the exact match of a unique + identifier (e.g. Digital Object Identifier - DOI) and, for records where the identifier is absent, through a score calculated + from a set of fields commonly found in bibliographic datasets (Title, Source, Authors and Publication Year). + Additionally, it provides functions to visualize the results of the document matching through a Venn diagram + and/or UpSet plot, as well as a summary of the matching procedure. + date_publication: '2023-11-07' + bug_reports: https://github.com/gavieira/biblioverlap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biblioverlap + url_git: https://github.com/gavieira/biblioverlap +BibPlots: + version: 0.0.8 + title: Plot Functions for Use in Bibliometrics + maintainer: Robin Haunschild + description: Currently, the package provides several functions for plotting and + analyzing bibliometric data (JIF, Journal Impact Factor, and paper percentile + values), beamplots with citations and percentiles, and three plot functions to + visualize the result of a reference publication year spectroscopy (RPYS) analysis + performed in the free software 'CRExplorer' (see ). Further + extension to more plot variants is planned. + date_publication: '2021-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BibPlots + url_git: '' +bibs: + version: 1.1.1 + title: Bayesian Inference for the Birnbaum-Saunders Distribution + maintainer: Mahdi Teimouri + description: |- + Developed for the following tasks. 1- Simulating and computing the maximum likelihood + estimator for the Birnbaum-Saunders (BS) distribution, 2- Computing the Bayesian estimator for + the parameters of the BS distribution based on reference prior proposed by Xu and Tang (2010) + and conjugate prior. 3- Computing the Bayesian estimator for + the BS distribution based on conjugate prior. 4- Computing the Bayesian estimator for the BS + distribution based on Jeffrey prior given by Achcar (1993) + 5- Computing the Bayesian estimator for the BS distribution under progressive type-II censoring + scheme. + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bibs + url_git: '' +bibtex: + version: 0.5.1 + title: Bibtex Parser + maintainer: James Joseph Balamuta + description: Utility to parse a bibtex file. + date_publication: '2023-01-26' + bug_reports: https://github.com/ropensci/bibtex/issues + url: https://docs.ropensci.org/bibtex/ + url_cran: https://CRAN.R-project.org/package=bibtex + url_git: https://github.com/ropensci/bibtex +BiCausality: + version: 0.1.4 + title: Binary Causality Inference Framework + maintainer: Chainarong Amornbunchornvej + description: A framework to infer causality on binary data using techniques in frequent + pattern mining and estimation statistics. Given a set of individual vectors S={x} + where x(i) is a realization value of binary variable i, the framework infers empirical + causal relations of binary variables i,j from S in a form of causal graph G=(V,E) + where V is a set of nodes representing binary variables and there is an edge from + i to j in E if the variable i causes j. The framework determines dependency among + variables as well as analyzing confounding factors before deciding whether i causes + j. The publication of this package is at Chainarong Amornbunchornvej, Navaporn + Surasvadi, Anon Plangprasopchok, and Suttipong Thajchayapong (2023) . + date_publication: '2023-11-28' + bug_reports: https://github.com/DarkEyes/BiCausality/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BiCausality + url_git: https://github.com/DarkEyes/BiCausality +biClassify: + version: '1.3' + title: Binary Classification Using Extensions of Discriminant Analysis + maintainer: Alexander F. Lapanowski + description: |- + Implements methods for sample size + reduction within Linear and Quadratic Discriminant Analysis in Lapanowski and Gaynanova (2020) . + Also includes methods for non-linear discriminant analysis with simultaneous sparse feature selection in Lapanowski and Gaynanova (2019) PMLR 89:1704-1713. + date_publication: '2021-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biClassify + url_git: '' +biclust: + version: 2.0.3.1 + title: BiCluster Algorithms + maintainer: Sebastian Kaiser + description: |- + The main function biclust() provides several algorithms to + find biclusters in two-dimensional data: Cheng and Church (2000, ISBN:1-57735-115-0), + spectral (2003) , plaid model (2005) , xmotifs (2003) and bimax (2006) . In addition, the + package provides methods for data preprocessing (normalization + and discretisation), visualisation, and validation of bicluster + solutions. + date_publication: '2023-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biclust + url_git: '' +biclustermd: + version: 0.2.3 + title: Biclustering with Missing Data + maintainer: John Reisner + description: |- + Biclustering is a statistical learning technique that simultaneously + partitions and clusters rows and columns of a data matrix. Since the solution + space of biclustering is in infeasible to completely search with current + computational mechanisms, this package uses a greedy heuristic. The algorithm + featured in this package is, to the best our knowledge, the first biclustering + algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H., + Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information + Sciences, 510, 304–316. + date_publication: '2021-06-17' + bug_reports: https://github.com/jreisner/biclustermd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biclustermd + url_git: https://github.com/jreisner/biclustermd +BICORN: + version: 0.1.0 + title: Integrative Inference of De Novo Cis-Regulatory Modules + maintainer: Xi Chen + description: Prior transcription factor binding knowledge and target gene expression + data are integrated in a Bayesian framework for functional cis-regulatory module + inference. Using Gibbs sampling, we iteratively estimate transcription factor + associations for each gene, regulation strength for each binding event and the + hidden activity for each transcription factor. + date_publication: '2018-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BICORN + url_git: '' +BiDAG: + version: 2.1.4 + title: Bayesian Inference for Directed Acyclic Graphs + maintainer: Polina Suter + description: |- + Implementation of a collection of MCMC methods for Bayesian structure learning + of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient + inference on larger DAGs, the space of DAGs is pruned according to the data. To filter + the search space, the algorithm employs a hybrid approach, combining constraint-based + learning with search and score. A reduced search space is initially defined on the basis + of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with + search and score. Search and score is then performed following two approaches: + Order MCMC, or Partition MCMC. + The BGe score is implemented for continuous data and the BDe score is implemented + for binary data or categorical data. The algorithms may provide the maximum a posteriori + (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. + All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. + References: + J. Kuipers, P. Suter, G. Moffa (2022) , + N. Friedman and D. Koller (2003) , + J. Kuipers and G. Moffa (2017) , + M. Kalisch et al. (2012) , + D. Geiger and D. Heckerman (2002) , + P. Suter, J. Kuipers, G. Moffa, N.Beerenwinkel (2023) . + date_publication: '2023-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiDAG + url_git: '' +bidask: + version: 2.1.4 + title: |- + Efficient Estimation of Bid-Ask Spreads from Open, High, Low, + and Close Prices + maintainer: Emanuele Guidotti + description: |- + Implements the efficient estimator of bid-ask spreads from open, high, low, and close prices + described in Ardia, Guidotti, & Kroencke (JFE, 2024) . + It also provides an implementation of the estimators described in + Roll (JF, 1984) , + Corwin & Schultz (JF, 2012) , + and Abdi & Ranaldo (RFS, 2017) . + date_publication: '2025-02-26' + bug_reports: https://github.com/eguidotti/bidask/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bidask + url_git: https://github.com/eguidotti/bidask +BiDimRegression: + version: 2.0.1 + title: |- + Calculates the Bidimensional Regression Between Two 2D + Configurations + maintainer: Alexander Pastukhov + description: Calculates the bidimensional regression between two 2D configurations + following the approach by Tobler (1965). + date_publication: '2022-02-17' + bug_reports: https://github.com/alexander-pastukhov/bidim-regression/issues/ + url: https://alexander-pastukhov.github.io/bidim-regression/ + url_cran: https://CRAN.R-project.org/package=BiDimRegression + url_git: https://github.com/alexander-pastukhov/bidim-regression/ +BIEN: + version: 1.2.7 + title: |- + Tools for Accessing the Botanical Information and Ecology + Network Database + maintainer: Brian Maitner + description: Provides Tools for Accessing the Botanical Information and Ecology + Network Database. The BIEN database contains cleaned and standardized botanical + data including occurrence, trait, plot and taxonomic data (See + for more Information). This package provides functions that query the BIEN database + by constructing and executing optimized SQL queries. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BIEN + url_git: '' +BifactorIndicesCalculator: + version: 0.2.2 + title: Bifactor Indices Calculator + maintainer: David Dueber + description: The calculator computes bifactor indices such as explained common variance + (ECV), hierarchical Omega (OmegaH), percentage of uncontaminated correlations + (PUC), item explained common variance (I-ECV), and more. This package is an R + version of the 'Excel' based 'Bifactor Indices Calculator' (Dueber, 2017) + with added convenience features for directly utilizing output from several programs + that can fit confirmatory factor analysis or item response models. + date_publication: '2021-05-12' + bug_reports: https://github.com/ddueber/BifactorIndicesCalculator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BifactorIndicesCalculator + url_git: https://github.com/ddueber/BifactorIndicesCalculator +bife: + version: 0.7.2 + title: Binary Choice Models with Fixed Effects + maintainer: Amrei Stammann + description: |- + Estimates fixed effects binary choice models (logit and probit) with potentially many + individual fixed effects and computes average partial effects. Incidental parameter bias can be + reduced with an asymptotic bias correction proposed by Fernandez-Val (2009) + . + date_publication: '2022-08-11' + bug_reports: https://github.com/amrei-stammann/bife/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bife + url_git: https://github.com/amrei-stammann/bife +BIFIEsurvey: + version: 3.6-6 + title: Tools for Survey Statistics in Educational Assessment + maintainer: Alexander Robitzsch + description: |- + Contains tools for survey statistics (especially in educational + assessment) for datasets with replication designs (jackknife, + bootstrap, replicate weights; see Kolenikov, 2010; + Pfefferman & Rao, 2009a, 2009b, , + ); Shao, 1996, + ). + Descriptive statistics, linear and logistic regression, + path models for manifest variables with measurement error + correction and two-level hierarchical regressions for weighted + samples are included. Statistical inference can be conducted for + multiply imputed datasets and nested multiply imputed datasets + and is in particularly suited for the analysis of plausible values + (for details see George, Oberwimmer & Itzlinger-Bruneforth, 2016; + Bruneforth, Oberwimmer & Robitzsch, 2016; Robitzsch, Pham & + Yanagida, 2016). The package development was supported by BIFIE + (Federal Institute for Educational Research, Innovation and Development + of the Austrian School System; Salzburg, Austria). + date_publication: '2024-04-25' + bug_reports: '' + url: https://sites.google.com/view/alexander-robitzsch/software + url_cran: https://CRAN.R-project.org/package=BIFIEsurvey + url_git: https://github.com/alexanderrobitzsch/BIFIEsurvey +bifurcatingr: + version: 2.1.0 + title: Bifurcating Autoregressive Models + maintainer: Tamer Elbayoumi + description: |- + Estimation of bifurcating autoregressive models of any order, p, BAR(p) as well as several types of bias correction for the least squares estimators of the autoregressive parameters as described in Zhou and Basawa (2005) and Elbayoumi and Mostafa (2020) . Currently, the bias correction methods supported include bootstrap (single, double and fast-double) bias correction and linear-bias-function-based bias correction. Functions for generating and plotting bifurcating autoregressive data from any BAR(p) model are also included. This new version includes calculating several type of bias-corrected and -uncorrected confidence intervals for the least squares estimators of the autoregressive parameters as described in Elbayoumi and Mostafa (2023) + . + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bifurcatingr + url_git: '' +bigalgebra: + version: 1.1.2 + title: |- + 'BLAS' and 'LAPACK' Routines for Native R Matrices and + 'big.matrix' Objects + maintainer: Frederic Bertrand + description: Provides arithmetic functions for R matrix and 'big.matrix' objects + as well as functions for QR factorization, Cholesky factorization, General eigenvalue, + and Singular value decomposition (SVD). A method matrix multiplication and an + arithmetic method -for matrix addition, matrix difference- allows for mixed type + operation -a matrix class object and a big.matrix class object- and pure type + operation for two big.matrix class objects. + date_publication: '2024-09-23' + bug_reports: https://github.com/fbertran/bigalgebra/issues/ + url: https://fbertran.github.io/bigalgebra/ + url_cran: https://CRAN.R-project.org/package=bigalgebra + url_git: https://github.com/fbertran/bigalgebra/ +biganalytics: + version: 1.1.22 + title: Utilities for 'big.matrix' Objects from Package 'bigmemory' + maintainer: Michael J. Kane + description: |- + Extend the 'bigmemory' package with various analytics. + Functions 'bigkmeans' and 'binit' may also be used with native R objects. + For 'tapply'-like functions, the bigtabulate package may also be helpful. + For linear algebra support, see 'bigalgebra'. For mutex (locking) support + for advanced shared-memory usage, see 'synchronicity'. + date_publication: '2024-03-28' + bug_reports: '' + url: http://www.bigmemory.org + url_cran: https://CRAN.R-project.org/package=biganalytics + url_git: '' +bigassertr: + version: 0.1.6 + title: Assertion and Message Functions + maintainer: Florian Privé + description: |- + Enhanced message functions (cat() / message() / warning() / error()) + using wrappers around sprintf(). Also, multiple assertion functions + (e.g. to check class, length, values, files, arguments, etc.). + date_publication: '2023-01-10' + bug_reports: https://github.com/privefl/bigassertr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigassertr + url_git: https://github.com/privefl/bigassertr +bigBits: + version: '1.3' + title: Perform Boolean Operations on Large Numbers + maintainer: Carl Witthoft + description: A set of Boolean operators which accept integers of any size, in any + base from 2 to 36, including 2's complement format, and perform actions like "AND," + "OR", "NOT", "SHIFTR/L" etc. The output can be in any base specified. A direct + base to base converter is included. + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigBits + url_git: '' +bigchess: + version: 1.9.1 + title: |- + Read, Write, Manipulate, Explore Chess PGN Files and R API to + UCI Chess Engines + maintainer: Wojciech Rosa + description: Provides functions for reading *.PGN files with more than one game, + including large files without copying it into RAM (using 'ff' package or 'RSQLite' + package). Handle chess data and chess aggregated data, count figure moves statistics, + create player profile, plot winning chances, browse openings. Set of functions + of R API to communicate with UCI-protocol based chess engines. + date_publication: '2020-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigchess + url_git: '' +bigD: + version: 0.3.0 + title: Flexibly Format Dates and Times to a Given Locale + maintainer: Richard Iannone + description: |- + Format dates and times flexibly and to whichever locales + make sense. Parses dates, times, and date-times in various formats + (including string-based ISO 8601 constructions). The formatting syntax gives + the user many options for formatting the date and time output in a precise + manner. Time zones in the input can be expressed in multiple ways and there + are many options for formatting time zones in the output as well. Several of + the provided helper functions allow for automatic generation of locale-aware + formatting patterns based on date/time skeleton formats and standardized + date/time formats with varying specificity. + date_publication: '2024-11-08' + bug_reports: https://github.com/rstudio/bigD/issues + url: https://rstudio.github.io/bigD/ + url_cran: https://CRAN.R-project.org/package=bigD + url_git: https://github.com/rstudio/bigD +bigdatadist: + version: '1.1' + title: |- + Distances for Machine Learning and Statistics in the Context of + Big Data + maintainer: Gabriel Martos + description: Functions to compute distances between probability measures or any + other data object than can be posed in this way, entropy measures for samples + of curves, distances and depth measures for functional data, and the Generalized + Mahalanobis Kernel distance for high dimensional data. For further details about + the metrics please refer to Martos et al (2014) ; Martos + et al (2018) ; Hernandez et al (2018, submitted); Martos + et al (2018, submitted). + date_publication: '2018-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigdatadist + url_git: '' +BigDataPE: + version: 0.0.95 + title: Secure and Intuitive Access to 'BigDataPE' 'API' Datasets + maintainer: Andre Leite + description: Designed to simplify the process of retrieving datasets from the 'Big + Data PE' platform using secure token-based authentication. It provides functions + for securely storing, retrieving, and managing tokens associated with specific + datasets, as well as fetching and processing data using the 'httr2' package. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BigDataPE + url_git: +BIGDAWG: + version: 3.0.3 + title: Case-Control Analysis of Multi-Allelic Loci + maintainer: Steve Mack + description: Data sets and functions for chi-squared Hardy-Weinberg and case-control + association tests of highly polymorphic genetic data [e.g., human leukocyte antigen + (HLA) data]. Performs association tests at multiple levels of polymorphism (haplotype, + locus and HLA amino-acids) as described in Pappas DJ, Marin W, Hollenbach JA, + Mack SJ (2016) . Combines rare variants to a + common class to account for sparse cells in tables as described by Hollenbach + JA, Mack SJ, Thomson G, Gourraud PA (2012) . + date_publication: '2021-11-17' + bug_reports: https://github.com/IgDAWG/BIGDAWG/issues + url: http://tools.immunogenomics.org/ + url_cran: https://CRAN.R-project.org/package=BIGDAWG + url_git: https://github.com/IgDAWG/BIGDAWG +bigDM: + version: 0.5.5 + title: |- + Scalable Bayesian Disease Mapping Models for High-Dimensional + Data + maintainer: Aritz Adin + description: Implements several spatial and spatio-temporal scalable disease mapping + models for high-dimensional count data using the INLA technique for approximate + Bayesian inference in latent Gaussian models (Orozco-Acosta et al., 2021 ; + Orozco-Acosta et al., 2023 and Vicente et al., + 2023 ). The creation and develpment of this package + has been supported by Project MTM2017-82553-R (AEI/FEDER, UE) and Project PID2020-113125RB-I00/MCIN/AEI/10.13039/501100011033. + It has also been partially funded by the Public University of Navarra (project + PJUPNA2001). + date_publication: '2024-08-19' + bug_reports: https://github.com/spatialstatisticsupna/bigDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigDM + url_git: https://github.com/spatialstatisticsupna/bigDM +bigergm: + version: 1.2.4 + title: |- + Fit, Simulate, and Diagnose Hierarchical Exponential-Family + Models for Big Networks + maintainer: Cornelius Fritz + description: A toolbox for analyzing and simulating large networks based on hierarchical + exponential-family random graph models (HERGMs).'bigergm' implements the estimation + for large networks efficiently building on the 'lighthergm' and 'hergm' packages. + Moreover, the package contains tools for simulating networks with local dependence + to assess the goodness-of-fit. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigergm + url_git: '' +bigGP: + version: 0.1.8 + title: Distributed Gaussian Process Calculations + maintainer: Christopher Paciorek + description: |- + Distributes Gaussian process calculations across nodes + in a distributed memory setting, using Rmpi. The bigGP class + provides high-level methods for maximum likelihood with normal data, + prediction, calculation of uncertainty (i.e., posterior covariance + calculations), and simulation of realizations. In addition, bigGP + provides an API for basic matrix calculations with distributed + covariance matrices, including Cholesky decomposition, back/forwardsolve, + crossproduct, and matrix multiplication. + date_publication: '2023-04-25' + bug_reports: '' + url: https://doi.org/10.18637/jss.v063.i10 + url_cran: https://CRAN.R-project.org/package=bigGP + url_git: '' +BIGL: + version: 1.9.3 + title: Biochemically Intuitive Generalized Loewe Model + maintainer: Kathy Mutambanengwe + description: |- + Response surface methods for drug synergy analysis. Available + methods include generalized and classical Loewe formulations as well as Highest + Single Agent methodology. Response surfaces can be plotted in an interactive + 3-D plot and formal statistical tests for presence of synergistic effects are + available. Implemented methods and tests are described in the article + "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction + of the expected combined effect compatible with partial agonism and antagonism" + by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, + Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) + . + date_publication: '2024-08-01' + bug_reports: https://github.com/openanalytics/BIGL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BIGL + url_git: https://github.com/openanalytics/BIGL +biglasso: + version: 1.6.0 + title: Extending Lasso Model Fitting to Big Data + maintainer: Patrick Breheny + description: |- + Extend lasso and elastic-net model fitting for ultra + high-dimensional, multi-gigabyte data sets that cannot be loaded into + memory. Designed to be more memory- and computation-efficient than existing + lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing + the user to analyze big data analysis even on an ordinary laptop. + date_publication: '2024-04-21' + bug_reports: https://github.com/pbreheny/biglasso/issues + url: https://pbreheny.github.io/biglasso/index.html + url_cran: https://CRAN.R-project.org/package=biglasso + url_git: https://github.com/pbreheny/biglasso +bigleaf: + version: 0.8.2 + title: |- + Physical and Physiological Ecosystem Properties from Eddy + Covariance Data + maintainer: Juergen Knauer + description: |- + Calculation of physical (e.g. aerodynamic conductance, surface temperature), + and physiological (e.g. canopy conductance, water-use efficiency) ecosystem properties + from eddy covariance data and accompanying meteorological measurements. Calculations + assume the land surface to behave like a 'big-leaf' and return bulk ecosystem/canopy variables. + date_publication: '2022-08-22' + bug_reports: https://bitbucket.org/juergenknauer/bigleaf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigleaf + url_git: https://bitbucket.org/juergenknauer/bigleaf +biglm: + version: 0.9-3 + title: Bounded Memory Linear and Generalized Linear Models + maintainer: Thomas Lumley + description: Regression for data too large to fit in memory. + date_publication: '2024-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biglm + url_git: '' +biglmm: + version: 0.9-3 + title: Bounded Memory Linear and Generalized Linear Models + maintainer: Mark Purver + description: Regression for data too large to fit in memory. This package functions + exactly like the 'biglm' package, but works with later versions of R. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biglmm + url_git: '' +bigMap: + version: 2.3.1 + title: Big Data Mapping + maintainer: Joan Garriga + description: Unsupervised clustering protocol for large scale structured data, based + on a low dimensional representation of the data. Dimensionality reduction is performed + using a parallelized implementation of the t-Stochastic Neighboring Embedding + algorithm (Garriga J. and Bartumeus F. (2018), ). + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigMap + url_git: '' +bigmatch: + version: 0.6.4 + title: Making Optimal Matching Size-Scalable Using Optimal Calipers + maintainer: Ruoqi Yu + description: |- + Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists. The main functions in the 'bigmatch' package are optcal() to find the optimal caliper, optconstant() to find the optimal number of nearest neighbors, and nfmatch() to find a near-fine balance match with a caliper and a restriction on the number of nearest neighbors. + Yu, R., Silber, J. H., and Rosenbaum, P. R. (2020). . + date_publication: '2022-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigmatch + url_git: '' +bigmds: + version: 3.0.0 + title: Multidimensional Scaling for Big Data + maintainer: Cristian Pachón García + description: |- + MDS is a statistic tool for reduction of dimensionality, using as input a distance + matrix of dimensions n × n. When n is large, classical algorithms suffer from + computational problems and MDS configuration can not be obtained. + With this package, we address these problems by means of six algorithms, being two of them + original proposals: + - Landmark MDS proposed by De Silva V. and JB. Tenenbaum (2004). + - Interpolation MDS proposed by Delicado P. and C. Pachón-García (2021) + (original proposal). + - Reduced MDS proposed by Paradis E (2018). + - Pivot MDS proposed by Brandes U. and C. Pich (2007) + - Divide-and-conquer MDS proposed by Delicado P. and C. Pachón-García (2021) + (original proposal). + - Fast MDS, proposed by Yang, T., J. Liu, L. McMillan and W. Wang (2006). + date_publication: '2024-01-09' + bug_reports: https://github.com/pachoning/bigmds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigmds + url_git: https://github.com/pachoning/bigmds +bigmemory: + version: 4.6.4 + title: |- + Manage Massive Matrices with Shared Memory and Memory-Mapped + Files + maintainer: Michael J. Kane + description: |- + Create, store, access, and manipulate massive matrices. + Matrices are allocated to shared memory and may use memory-mapped + files. Packages 'biganalytics', 'bigtabulate', 'synchronicity', and + 'bigalgebra' provide advanced functionality. + date_publication: '2024-01-09' + bug_reports: https://github.com/kaneplusplus/bigmemory/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigmemory + url_git: https://github.com/kaneplusplus/bigmemory +bigmemory.sri: + version: 0.1.8 + title: A Shared Resource Interface for Bigmemory Project Packages + maintainer: Michael J. Kane + description: A shared resource interface for the bigmemory and synchronicity packages. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigmemory.sri + url_git: '' +bignum: + version: 0.3.2 + title: Arbitrary-Precision Integer and Floating-Point Mathematics + maintainer: David Hall + description: |- + Classes for storing and manipulating arbitrary-precision + integer vectors and high-precision floating-point vectors. These + extend the range and precision of the 'integer' and 'double' data + types found in R. This package utilizes the 'Boost.Multiprecision' C++ + library. It is specifically designed to work well with the 'tidyverse' + collection of R packages. + date_publication: '2023-05-04' + bug_reports: https://github.com/davidchall/bignum/issues + url: https://davidchall.github.io/bignum/ + url_cran: https://CRAN.R-project.org/package=bignum + url_git: https://github.com/davidchall/bignum +bigparallelr: + version: 0.3.2 + title: Easy Parallel Tools + maintainer: Florian Privé + description: |- + Utility functions for easy parallelism in R. Include some reexports + from other packages, utility functions for splitting and parallelizing over + blocks, and choosing and setting the number of cores used. + date_publication: '2021-10-02' + bug_reports: https://github.com/privefl/bigparallelr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigparallelr + url_git: https://github.com/privefl/bigparallelr +bigQF: + version: '1.6' + title: Quadratic Forms in Large Matrices + maintainer: Thomas Lumley + description: A computationally-efficient leading-eigenvalue approximation to tail + probabilities and quantiles of large quadratic forms, in particular for the Sequence + Kernel Association Test (SKAT) used in genomics . Also + provides stochastic singular value decomposition for dense or sparse matrices. + date_publication: '2021-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigQF + url_git: https://github.com/tslumley/bigQF +BigQuic: + version: 1.1-13 + title: Big Quadratic Inverse Covariance Estimation + maintainer: Khalid B. Kunji + description: |- + Use Newton's method, coordinate descent, and METIS clustering + to solve the L1 regularized Gaussian MLE inverse covariance + matrix estimation problem. + date_publication: '2022-11-19' + bug_reports: '' + url: https://bigdata.oden.utexas.edu/software/1035/http://glaros.dtc.umn.edu/gkhome/views/metishttps://www.pcg-random.org/download.htmlhttps://gcc.gnu.org/projects/gomp/ + url_cran: https://CRAN.R-project.org/package=BigQuic + url_git: '' +bigreadr: + version: 0.2.5 + title: Read Large Text Files + maintainer: Florian Privé + description: |- + Read large text files by splitting them in smaller files. + Package 'bigreadr' also provides some convenient wrappers around fread() + and fwrite() from package 'data.table'. + date_publication: '2022-12-06' + bug_reports: https://github.com/privefl/bigreadr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigreadr + url_git: https://github.com/privefl/bigreadr +bigReg: + version: 0.1.5 + title: Generalized Linear Models (GLM) for Large Data Sets + maintainer: Chibisi Chima-Okereke + description: |- + Allows the user to carry out GLM on very large + data sets. Data can be created using the data_frame() function and appended + to the object with object$append(data); data_frame and data_matrix objects + are available that allow the user to store large data on disk. The data is + stored as doubles in binary format and any character columns are transformed + to factors and then stored as numeric (binary) data while a look-up table is + stored in a separate .meta_data file in the same folder. The data is stored in + blocks and GLM regression algorithm is modified and carries out a MapReduce- + like algorithm to fit the model. The functions bglm(), and summary() + and bglm_predict() are available for creating and post-processing of models. + The library requires Armadillo installed on your system. It may not + function on windows since multi-core processing is done using mclapply() + which forks R on Unix/Linux type operating systems. + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigReg + url_git: '' +bigrquery: + version: 1.5.1 + title: An Interface to Google's 'BigQuery' 'API' + maintainer: Hadley Wickham + description: Easily talk to Google's 'BigQuery' database from R. + date_publication: '2024-03-14' + bug_reports: https://github.com/r-dbi/bigrquery/issues + url: https://bigrquery.r-dbi.org + url_cran: https://CRAN.R-project.org/package=bigrquery + url_git: https://github.com/r-dbi/bigrquery +bigrquerystorage: + version: 1.2.2 + title: An Interface to Google's 'BigQuery Storage' API + maintainer: Bruno Tremblay + description: |- + Easily talk to Google's 'BigQuery Storage' API from R + (). + date_publication: '2025-01-07' + bug_reports: https://github.com/meztez/bigrquerystorage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigrquerystorage + url_git: https://github.com/meztez/bigrquerystorage +bigsimr: + version: 0.12.0 + title: Fast Generation of High-Dimensional Random Vectors + maintainer: Alex Knudson + description: |- + Simulate multivariate data with arbitrary marginal distributions. + 'bigsimr' is a package for simulating high-dimensional multivariate data with + a target correlation and arbitrary marginal distributions via Gaussian copula. + It utilizes the Julia package 'Bigsimr.jl' for its core routines. + date_publication: '2024-02-21' + bug_reports: https://github.com/SchisslerGroup/Bigsimr.jl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigsimr + url_git: https://github.com/SchisslerGroup/r-bigsimr +bigsnpr: + version: 1.12.18 + title: Analysis of Massive SNP Arrays + maintainer: Florian Privé + description: |- + Easy-to-use, efficient, flexible and scalable tools for analyzing + massive SNP arrays. Privé et al. (2018) . + date_publication: '2024-11-26' + bug_reports: https://github.com/privefl/bigsnpr/issues + url: https://privefl.github.io/bigsnpr/ + url_cran: https://CRAN.R-project.org/package=bigsnpr + url_git: '' +bigsparser: + version: 0.7.3 + title: Sparse Matrix Format with Data on Disk + maintainer: Florian Privé + description: |- + Provide a sparse matrix format with data stored on disk, to be + used in both R and C++. This is intended for more efficient use of sparse + data in C++ and also when parallelizing, since data on disk does not need + copying. Only a limited number of features will be implemented. For now, + conversion can be performed from a 'dgCMatrix' or a 'dsCMatrix' from R + package 'Matrix'. A new compact format is also now available. + date_publication: '2024-09-06' + bug_reports: https://github.com/privefl/bigsparser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigsparser + url_git: https://github.com/privefl/bigsparser +bigsplines: + version: 1.1-1 + title: Smoothing Splines for Large Samples + maintainer: Nathaniel E. Helwig + description: 'Fits smoothing spline regression models using scalable algorithms + designed for large samples. Seven marginal spline types are supported: linear, + cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. + Random effects and parametric effects are also supported. Response can be Gaussian + or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.' + date_publication: '2018-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigsplines + url_git: '' +bigstatsr: + version: 1.6.1 + title: Statistical Tools for Filebacked Big Matrices + maintainer: Florian Privé + description: |- + Easy-to-use, efficient, flexible and scalable statistical tools. + Package bigstatsr provides and uses Filebacked Big Matrices via memory-mapping. + It provides for instance matrix operations, Principal Component Analysis, + sparse linear supervised models, utility functions and more + . + date_publication: '2024-09-09' + bug_reports: https://github.com/privefl/bigstatsr/issues + url: https://privefl.github.io/bigstatsr/ + url_cran: https://CRAN.R-project.org/package=bigstatsr + url_git: '' +bigstep: + version: 1.1.1 + title: Stepwise Selection for Large Data Sets + maintainer: Piotr Szulc + description: |- + Selecting linear and generalized linear models for large data sets + using modified stepwise procedure and modern selection criteria (like + modifications of Bayesian Information Criterion). Selection can be + performed on data which exceed RAM capacity. Bogdan et al., (2004) + . + date_publication: '2023-05-13' + bug_reports: https://github.com/pmszulc/bigstep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigstep + url_git: https://github.com/pmszulc/bigstep +bigSurvSGD: + version: 0.0.1 + title: Big Survival Analysis Using Stochastic Gradient Descent + maintainer: Aliasghar Tarkhan + description: Fits Cox model via stochastic gradient descent. This implementation + avoids computational instability of the standard Cox Model when dealing large + datasets. Furthermore, it scales up with large datasets that do not fit the memory. + It also handles large sparse datasets using proximal stochastic gradient descent + algorithm. For more details about the method, please see Aliasghar Tarkhan and + Noah Simon (2020) . + date_publication: '2020-10-01' + bug_reports: https://github.com/atarkhan/bigSurvSGD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigSurvSGD + url_git: '' +bigtabulate: + version: 1.1.9 + title: |- + Table, Apply, and Split Functionality for Matrix and + 'big.matrix' Objects + maintainer: Michael J. Kane + description: |- + Extend the bigmemory package with 'table', 'tapply', and 'split' + support for 'big.matrix' objects. The functions may also be used with native R + matrices for improving speed and memory-efficiency. + date_publication: '2022-04-11' + bug_reports: '' + url: http://www.bigmemory.org + url_cran: https://CRAN.R-project.org/package=bigtabulate + url_git: '' +bigtcr: + version: '1.1' + title: |- + Nonparametric Analysis of Bivariate Gap Time with Competing + Risks + maintainer: Chenguang Wang + description: |- + For studying recurrent disease and death with competing + risks, comparisons based on the well-known cumulative incidence function + can be confounded by different prevalence rates of the competing events. + Alternatively, comparisons of the conditional distribution of the survival + time given the failure event type are more relevant for investigating the + prognosis of different patterns of recurrence disease. This package implements + a nonparametric estimator for the conditional cumulative incidence function + and a nonparametric conditional bivariate cumulative incidence function for the + bivariate gap times proposed in Huang et al. (2016) . + date_publication: '2018-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigtcr + url_git: '' +bigtime: + version: 0.2.3 + title: Sparse Estimation of Large Time Series Models + maintainer: Ines Wilms + description: Estimation of large Vector AutoRegressive (VAR), Vector AutoRegressive + with Exogenous Variables X (VARX) and Vector AutoRegressive Moving Average (VARMA) + Models with Structured Lasso Penalties, see Nicholson, Wilms, Bien and Matteson + (2020) and Wilms, Basu, Bien and Matteson + (2021) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bigtime + url_git: https://github.com/ineswilms/bigtime +bigutilsr: + version: 0.3.4 + title: Utility Functions for Large-scale Data + maintainer: Florian Privé + description: |- + Utility functions for large-scale data. For now, package 'bigutilsr' + mainly includes functions for outlier detection and unbiased PCA projection. + date_publication: '2021-04-13' + bug_reports: https://github.com/privefl/bigutilsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bigutilsr + url_git: https://github.com/privefl/bigutilsr +BigVAR: + version: 1.1.2 + title: Dimension Reduction Methods for Multivariate Time Series + maintainer: Will Nicholson + description: Estimates VAR and VARX models with Structured Penalties using the methods + developed by Nicholson et al (2017) and + Nicholson et al (2020) . + date_publication: '2023-01-09' + bug_reports: https://github.com/wbnicholson/BigVAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BigVAR + url_git: https://github.com/wbnicholson/BigVAR +bikeshare14: + version: 0.1.4 + title: Bay Area Bike Share Trips in 2014 + maintainer: Arunkumar Srinivasan + description: |- + Anonymised Bay Area bike share trip data for the year 2014. + Also contains additional metadata on stations and weather. + date_publication: '2021-04-07' + bug_reports: https://github.com/arunsrinivasan/bikeshare14/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bikeshare14 + url_git: https://github.com/arunsrinivasan/bikeshare14 +bikm1: + version: 1.1.0 + title: |- + Co-Clustering Adjusted Rand Index and Bikm1 Procedure for + Contingency and Binary Data-Sets + maintainer: Valerie Robert + description: 'Co-clustering of the rows and columns of a contingency or binary matrix, + or double binary matrices and model selection for the number of row and column + clusters. Three models are considered: the Poisson latent block model for contingency + matrix, the binary latent block model for binary matrix and a new model we develop: + the multiple latent block model for double binary matrices. A new procedure named + bikm1 is implemented to investigate more efficiently the grid of numbers of clusters. + Then, the studied model selection criteria are the integrated completed likelihood + (ICL) and the Bayesian integrated likelihood (BIC). Finally, the co-clustering + adjusted Rand index (CARI) to measure agreement between co-clustering partitions + is implemented. Robert Valerie, Vasseur Yann, Brault Vincent (2021) .' + date_publication: '2021-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bikm1 + url_git: '' +bild: + version: 1.2-1 + title: A Package for BInary Longitudinal Data + maintainer: M. Helena Goncalves + description: |- + Performs logistic regression for binary longitudinal + data, allowing for serial dependence among observations from a given + individual and a random intercept term. Estimation is via maximization + of the exact likelihood of a suitably defined model. Missing values and + unbalanced data are allowed, with some restrictions. + M. Helena Goncalves et al.(2007) . + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bild + url_git: '' +billboard: + version: 0.1.0 + title: Contains Data of Billboard Hot 100 Songs + maintainer: Mikkel Freltoft Krogsholm + description: |- + Contains data sets regarding songs on the Billboard Hot 100 list + from 1960 to 2016. The data sets include the ranks for the given year, + musical features of a lot of the songs and lyrics for several of the songs + as well. + date_publication: '2017-09-04' + bug_reports: https://github.com/mikkelkrogsholm/billboard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=billboard + url_git: https://github.com/mikkelkrogsholm/billboard +billboarder: + version: 0.5.0 + title: Create Interactive Chart with the JavaScript 'Billboard' Library + maintainer: Victor Perrier + description: |- + Provides an 'htmlwidgets' interface to 'billboard.js', + a re-usable easy interface JavaScript chart library, based on D3 v4+. + Chart types include line charts, scatterplots, bar/lollipop charts, histogram/density plots, pie/donut charts and gauge charts. + All charts are interactive, and a proxy method is implemented to smoothly update a chart without rendering it again in 'shiny' apps. + date_publication: '2024-09-09' + bug_reports: https://github.com/dreamRs/billboarder/issues + url: https://dreamrs.github.io/billboarder/ + url_cran: https://CRAN.R-project.org/package=billboarder + url_git: https://github.com/dreamRs/billboarder +bimets: + version: 4.0.3 + title: Time Series and Econometric Modeling + maintainer: Andrea Luciani + description: Time series analysis, (dis)aggregation and manipulation, e.g. time + series extension, merge, projection, lag, lead, delta, moving and cumulative average + and product, selection by index, date and year-period, conversion to daily, monthly, + quarterly, (semi)annually. Simultaneous equation models definition, estimation, + simulation and forecasting with coefficient restrictions, error autocorrelation, + exogenization, add-factors, impact and interim multipliers analysis, conditional + equation evaluation, rational expectations, endogenous targeting and model renormalization, + structural stability, stochastic simulation and forecast, optimal control. + date_publication: '2024-11-25' + bug_reports: https://github.com/andrea-luciani/bimets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bimets + url_git: https://github.com/andrea-luciani/bimets +BimodalIndex: + version: 1.1.9 + title: The Bimodality Index + maintainer: Kevin R. Coombes + description: |- + Defines the functions used to compute the + bimodal index as defined by Wang et al. (2009) + , + . + date_publication: '2019-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BimodalIndex + url_git: http://oompa.r-forge.r-project.org/ +binancer: + version: 1.2.0 + title: API Client to 'Binance' + maintainer: Gergely Daróczi + description: 'R client to the ''Binance'' Public Rest API for data collection on + cryptocurrencies, portfolio management and trading: .' + date_publication: '2021-11-29' + bug_reports: '' + url: https://daroczig.github.io/binancer/ + url_cran: https://CRAN.R-project.org/package=binancer + url_git: '' +Binarize: + version: 1.3.1 + title: Binarization of One-Dimensional Data + maintainer: Hans Kestler + description: Provides methods for the binarization of one-dimensional data and some + visualization functions. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Binarize + url_git: '' +BinarybalancedCut: + version: '0.2' + title: Threshold Cut Point of Probability for a Binary Classifier Model + maintainer: Navinkumar Nedunchezhian + description: Allows to view the optimal probability cut-off point at which the Sensitivity + and Specificity meets and its a best way to minimize both Type-1 and Type-2 error + for a binary Classifier in determining the Probability threshold. + date_publication: '2017-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinarybalancedCut + url_git: '' +BinaryDosage: + version: 1.0.0 + title: Creates, Merges, and Reads Binary Dosage Files + maintainer: John Morrison + description: |- + Tools to create binary dosage from either VCF + or GEN files, merge binary dosage files, and read + binary dosage files. + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinaryDosage + url_git: '' +BinaryEMVS: + version: '0.1' + title: Variable Selection for Binary Data Using the EM Algorithm + maintainer: John Snyder + description: |- + Implements variable selection for high dimensional datasets with a binary response + variable using the EM algorithm. Both probit and logit models are supported. Also included + is a useful function to generate high dimensional data with correlated variables. + date_publication: '2016-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinaryEMVS + url_git: '' +BinaryEPPM: + version: '3.0' + title: |- + Mean and Scale-Factor Modeling of Under- And Over-Dispersed + Binary Data + maintainer: David M. Smith + description: |- + Under- and over-dispersed binary data are modeled using an extended Poisson + process model (EPPM) appropriate for binary data. A feature of the model is that the + under-dispersion relative to the binomial distribution only needs to be greater than + zero, but the over-dispersion is restricted compared to other distributional models + such as the beta and correlated binomials. Because of this, the examples focus on + under-dispersed data and how, in combination with the beta or correlated distributions, + flexible models can be fitted to data displaying both under- and over-dispersion. Using + Generalized Linear Model (GLM) terminology, the functions utilize linear predictors for + the probability of success and scale-factor with various link functions for p, and log + link for scale-factor, to fit a variety of models relevant to areas such as bioassay. + Details of the EPPM are in Faddy and Smith (2012) and + Smith and Faddy (2019) . + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinaryEPPM + url_git: '' +binaryGP: + version: '0.2' + title: |- + Fit and Predict a Gaussian Process Model with (Time-Series) + Binary Response + maintainer: Chih-Li Sung + description: Allows the estimation and prediction for binary Gaussian process model. + The mean function can be assumed to have time-series structure. The estimation + methods for the unknown parameters are based on penalized quasi-likelihood/penalized + quasi-partial likelihood and restricted maximum likelihood. The predicted probability + and its confidence interval are computed by Metropolis-Hastings algorithm. More + details can be seen in Sung et al (2017) . + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binaryGP + url_git: '' +binb: + version: 0.0.7 + title: '''binb'' is not ''Beamer''' + maintainer: Dirk Eddelbuettel + description: |- + A collection of 'LaTeX' styles using 'Beamer' customization for + pdf-based presentation slides in 'RMarkdown'. At present it contains + 'RMarkdown' adaptations of the LaTeX themes 'Metropolis' (formerly 'mtheme') + theme by Matthias Vogelgesang and others (now included in 'TeXLive'), the + 'IQSS' by Ista Zahn (which is included here), and the 'Monash' theme by + Rob J Hyndman. Additional (free) fonts may be needed: 'Metropolis' prefers + 'Fira', and 'IQSS' requires 'Libertinus'. + date_publication: '2024-07-06' + bug_reports: https://github.com/eddelbuettel/binb/issues + url: https://dirk.eddelbuettel.com/code/binb.html + url_cran: https://CRAN.R-project.org/package=binb + url_git: https://github.com/eddelbuettel/binb +BINCOR: + version: 0.2.0 + title: Estimate the Correlation Between Two Irregular Time Series + maintainer: Josué M. Polanco-Martínez + description: 'Estimate the correlation between two irregular time series that are + not necessarily sampled on identical time points. This program is also applicable + to the situation of two evenly spaced time series that are not on the same time + grid. ''BINCOR'' is based on a novel estimation approach proposed by Mudelsee + (2010, 2014) to estimate the correlation between two climate time series with + different timescales. The idea is that autocorrelation (AR1 process) allows to + correlate values obtained on different time points. ''BINCOR'' contains four functions: + bin_cor() (the main function to build the binned time series), plot_ts() (to plot + and compare the irregular and binned time series, cor_ts() (to estimate the correlation + between the binned time series) and ccf_ts() (to estimate the cross-correlation + between the binned time series).' + date_publication: '2018-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BINCOR + url_git: '' +binda: + version: 1.0.4 + title: Multi-Class Discriminant Analysis using Binary Predictors + maintainer: Korbinian Strimmer + description: |- + Implements functions for multi-class + discriminant analysis using binary predictors, for corresponding + variable selection, and for dichotomizing continuous data. + date_publication: '2021-11-20' + bug_reports: '' + url: https://strimmerlab.github.io/software/binda/ + url_cran: https://CRAN.R-project.org/package=binda + url_git: '' +bindata: + version: 0.9-22 + title: Generation of Artificial Binary Data + maintainer: Kurt Hornik + description: Generation of correlated artificial binary data. + date_publication: '2024-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bindata + url_git: '' +bindr: + version: 0.1.2 + title: Parametrized Active Bindings + maintainer: Kirill Müller + description: |- + Provides a simple interface for creating active bindings where the + bound function accepts additional arguments. + date_publication: '2024-11-21' + bug_reports: https://github.com/krlmlr/bindr/issues + url: https://krlmlr.github.io/bindr/ + url_cran: https://CRAN.R-project.org/package=bindr + url_git: https://github.com/krlmlr/bindr +bindrcpp: + version: 0.2.3 + title: An 'Rcpp' Interface to Active Bindings + maintainer: Kirill Müller + description: |- + Provides an easy way to fill an environment with active + bindings that call a C++ function. + date_publication: '2023-12-12' + bug_reports: https://github.com/krlmlr/bindrcpp/issues + url: https://krlmlr.github.io/bindrcpp/ + url_cran: https://CRAN.R-project.org/package=bindrcpp + url_git: https://github.com/krlmlr/bindrcpp +binequality: + version: 1.0.4 + title: Methods for Analyzing Binned Income Data + maintainer: Samuel V. Scarpino + description: Methods for model selection, model averaging, and calculating metrics, + such as the Gini, Theil, Mean Log Deviation, etc, on binned income data where + the topmost bin is right-censored. We provide both a non-parametric method, termed + the bounded midpoint estimator (BME), which assigns cases to their bin midpoints; + except for the censored bins, where cases are assigned to an income estimated + by fitting a Pareto distribution. Because the usual Pareto estimate can be inaccurate + or undefined, especially in small samples, we implement a bounded Pareto estimate + that yields much better results. We also provide a parametric approach, which + fits distributions from the generalized beta (GB) family. Because some GB distributions + can have poor fit or undefined estimates, we fit 10 GB-family distributions and + use multimodel inference to obtain definite estimates from the best-fitting distributions. + We also provide binned income data from all United States of America school districts, + counties, and states. + date_publication: '2018-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binequality + url_git: '' +binford: + version: 0.1.0 + title: Binford's Hunter-Gatherer Data + maintainer: Ben Marwick + description: |- + Binford's hunter-gatherer data includes more than 200 variables + coding aspects of hunter-gatherer subsistence, mobility, and social organization + for 339 ethnographically documented groups of hunter-gatherers. + date_publication: '2016-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binford + url_git: http://github.com/benmarwick/binford +binfunest: + version: 0.1.0 + title: |- + Estimates Parameters of Functions Driving Binomial Random + Variables + maintainer: Philip Shea + description: |- + Provides maximum likelihood estimates of the + performance parameters that drive a binomial distribution of observed + errors, and takes full advantage of zero error observations. High performance + communications systems typically have inherent noise sources and other + performance limitations that need to be estimated. Measurements made at + high signal to noise ratios typically result in zero + errors due to limitation in available measurement time. Package includes + theoretical performance functions for common modulation schemes (Proakis, + "Digital Communications" (1995, )), polarization shifted + QPSK (Agrell & Karlsson (2009, )), and utility + functions to work with the performance functions. + date_publication: '2022-09-09' + bug_reports: https://github.com/PhilShea/binfunest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=binfunest + url_git: https://github.com/PhilShea/binfunest +bingadsR: + version: 0.1.0 + title: Get Bing Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from bing Ads using + the 'Windsor.ai' API . + date_publication: '2022-10-29' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=bingadsR + url_git: '' +bingat: + version: '1.3' + title: Binary Graph Analysis Tools + maintainer: Berkley Shands + description: Tools to analyze binary graph objects. + date_publication: '2017-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bingat + url_git: '' +binGroup: + version: 2.2-1 + title: Evaluation and Experimental Design for Binomial Group Testing + maintainer: Frank Schaarschmidt + description: |- + Methods for estimation and hypothesis testing of proportions + in group testing designs: methods for estimating a proportion in a single + population (assuming sensitivity and specificity equal to 1 in designs + with equal group sizes), as well as hypothesis tests and + functions for experimental design for this situation. For + estimating one proportion or the difference of proportions, a + number of confidence interval methods are included, which can + deal with various different pool sizes. Further, regression + methods are implemented for simple pooling and matrix pooling + designs. + Methods for identification of positive items in group + testing designs: Optimal testing configurations can be found + for hierarchical and array-based algorithms. Operating + characteristics can be calculated for testing configurations + across a wide variety of situations. + date_publication: '2018-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binGroup + url_git: '' +binGroup2: + version: 1.3.1 + title: Identification and Estimation using Group Testing + maintainer: Brianna Hitt + description: |- + Methods for the group testing identification problem: 1) Operating + characteristics (e.g., expected number of tests) for commonly used + hierarchical and array-based algorithms, and 2) Optimal testing + configurations for these same algorithms. Methods for the group testing + estimation problem: 1) Estimation and inference procedures for an overall + prevalence, and 2) Regression modeling for commonly used hierarchical and + array-based algorithms. + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binGroup2 + url_git: '' +BinGSD: + version: '1.1' + title: |- + Calculate Boundaries and Conditional Power for Single Arm Group + Sequential Test with Binary Endpoint + maintainer: Lei Wang + description: Consider an at-most-K-stage group sequential design with only an upper + bound for the last analysis and non-binding lower bounds.With binary endpoint, + two kinds of test can be applied, asymptotic test based on normal distribution + and exact test based on binomial distribution. This package supports the computation + of boundaries and conditional power for single-arm group sequential test with + binary endpoint, via either asymptotic or exact test. The package also provides + functions to obtain boundary crossing probabilities given the design. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinGSD + url_git: '' +binhf: + version: 1.0-3 + title: Haar-Fisz Functions for Binomial Data + maintainer: Matt Nunes + description: Binomial Haar-Fisz transforms for Gaussianization as in Nunes and Nason + (2009). + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binhf + url_git: '' +binman: + version: 0.1.3 + title: A Binary Download Manager + maintainer: Ju Yeong Kim + description: |- + Tools and functions for managing the download of binary files. + Binary repositories are defined in 'YAML' format. Defining new + pre-download, download and post-download templates allow additional + repositories to be added. + date_publication: '2022-09-01' + bug_reports: https://github.com/ropensci/binman/issues + url: https://docs.ropensci.org/binman/ + url_cran: https://CRAN.R-project.org/package=binman + url_git: https://github.com/ropensci/binman +BinMat: + version: 0.1.5 + title: |- + Processes Binary Data Obtained from Fragment Analysis (Such as + AFLPs, ISSRs, and RFLPs) + maintainer: Clarke van Steenderen + description: 'A molecular genetics tool that processes binary data from fragment + analysis. It consolidates replicate sample pairs, outputs summary statistics, + and produces hierarchical clustering trees and nMDS plots. This package was developed + from the publication available here: . + The GUI version of this package is available on the R Shiny online server at: + or it is accessible via GitHub + by typing: shiny::runGitHub("BinMat", "clarkevansteenderen") into the console + in R. Two real-world datasets accompany the package: an AFLP dataset of Bunias + orientalis samples from Tewes et. al. (2017) , + and an ISSR dataset of Nymphaea specimens from Reid et. al. (2021) + . The authors of these publications are thanked for allowing the use of their + data.' + date_publication: '2022-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinMat + url_git: '' +binMto: + version: 0.0-7 + title: Many-to-One Comparisons of Proportions + maintainer: Frank Schaarschmidt + description: |- + Asymptotic simultaneous confidence intervals for comparison of many treatments with one control, + for the difference of binomial proportions, allows for Dunnett-like-adjustment, Bonferroni or unadjusted intervals. + Simulation of power of the above interval methods, approximate calculation of any-pair-power, and sample size + iteration based on approximate any-pair power. Exact conditional maximum test for many-to-one comparisons to a control. + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binMto + url_git: '' +BinNonNor: + version: 1.5.3 + title: Data Generation with Binary and Continuous Non-Normal Components + maintainer: Ran Gao + description: |- + Generation of multiple binary and continuous non-normal variables simultaneously + given the marginal characteristics and association structure based on the methodology + proposed by Demirtas et al. (2012) . + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinNonNor + url_git: '' +BinNor: + version: 2.3.3 + title: |- + Simultaneous Generation of Multivariate Binary and Normal + Variates + maintainer: Ran Gao + description: Generating multiple binary and normal variables simultaneously given + marginal characteristics and association structure based on the methodology proposed + by Demirtas and Doganay (2012) . + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinNor + url_git: '' +binom: + version: 1.1-1.1 + title: Binomial Confidence Intervals for Several Parameterizations + maintainer: Sundar Dorai-Raj + description: |- + Constructs confidence intervals on the probability of + success in a binomial experiment via several parameterizations. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binom + url_git: '' +binomCI: + version: '1.2' + title: Confidence Intervals for a Binomial Proportion + maintainer: Michail Tsagris + description: 'Twelve confidence intervals for one binomial proportion or a vector + of binomial proportions are computed. The confidence intervals are: Jeffreys, Wald, + Wald corrected, Wald, Blyth and Still, Agresti and Coull, Wilson, Score, Score + corrected, Wald logit, Wald logit corrected, Arcsine and Exact binomial. References + include, among others: Vollset, S. E. (1993). "Confidence intervals for a binomial + proportion". Statistics in Medicine, 12(9): 809-824. .' + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binomCI + url_git: '' +binomialRF: + version: 0.1.0 + title: Binomial Random Forest Feature Selection + maintainer: Samir Rachid Zaim + description: The 'binomialRF' is a new feature selection technique for decision + trees that aims at providing an alternative approach to identify significant feature + subsets using binomial distributional assumptions (Rachid Zaim, S., et al. (2019)) + . Treating each splitting variable selection as a set of exchangeable + correlated Bernoulli trials, 'binomialRF' then tests whether a feature is selected + more often than by random chance. + date_publication: '2020-03-26' + bug_reports: '' + url: https://www.biorxiv.org/content/10.1101/681973v1.abstract + url_cran: https://CRAN.R-project.org/package=binomialRF + url_git: '' +binomialtrend: + version: 0.0.0.3 + title: |- + Calculates the Statistical Significance of a Trend in a Set of + Measurements + maintainer: Matthew Cserhati + description: |- + Detection of a statistically significant trend in the data provided by the user. + This is based on the a signed test based on the binomial distribution. + The package returns a trend test value, T, and also a p-value. A T value + close to 1 indicates a rising trend, whereas a T value close to -1 indicates a decreasing + trend. A T value close to 0 indicates no trend. There is also a command to visualize + the trend. A test data set called gtsa_data is also available, which has global mean + temperatures for January, April, July, and October for the years 1851 to 2022. + Reference: Walpole, Myers, Myers, Ye. (2007, ISBN: 0-13-187711-9). + date_publication: '2022-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binomialtrend + url_git: '' +BinOrdNonNor: + version: 1.5.2 + title: Concurrent Generation of Binary, Ordinal and Continuous Data + maintainer: Ran Gao + description: Generation of samples from a mix of binary, ordinal and continuous + random variables with a pre-specified correlation matrix and marginal distributions. + The details of the method are explained in Demirtas et al. (2012) . + date_publication: '2021-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinOrdNonNor + url_git: '' +binovisualfields: + version: 0.1.1 + title: Depth-Dependent Binocular Visual Fields Simulation + maintainer: Ping Liu + description: Simulation and visualization depth-dependent integrated visual fields. + Visual fields are measured monocularly at a single depth, yet real-life activities + involve predominantly binocular vision at multiple depths. The package provides + functions to simulate and visualize binocular visual field impairment in a depth-dependent + fashion from monocular visual field results based on Ping Liu, Allison McKendrick, + Anna Ma-Wyatt, Andrew Turpin (2019) . At each location + and depth plane, sensitivities are linearly interpolated from corresponding locations + in monocular visual field and returned as the higher value of the two. Its utility + is demonstrated by evaluating DD-IVF defects associated with 12 glaucomatous archetypes + of 24-2 visual field pattern in the included 'shiny' apps. + date_publication: '2020-03-10' + bug_reports: '' + url: https://people.eng.unimelb.edu.au/aturpin/opi/index.html + url_cran: https://CRAN.R-project.org/package=binovisualfields + url_git: '' +binpackr: + version: 0.1.1 + title: Fast 1d Bin Packing + maintainer: Lukas Schneiderbauer + description: 'Implements the First Fit Decreasing algorithm to achieve one dimensional + heuristic bin packing. Runtime is of order O(n log(n)) where n is the number of + items to pack. See "The Art of Computer Programming Vol. 1" by Donald E. Knuth + (1997, ISBN: 0201896834) for more details.' + date_publication: '2023-12-06' + bug_reports: https://github.com/lschneiderbauer/binpackr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=binpackr + url_git: https://github.com/lschneiderbauer/binpackr +binr: + version: 1.1.1 + title: Cut Numeric Values into Evenly Distributed Groups + maintainer: Sergei Izrailev + description: |- + Implementation of algorithms for cutting numerical values + exhibiting a potentially highly skewed distribution into evenly distributed + groups (bins). This functionality can be applied for binning discrete + values, such as counts, as well as for discretization of continuous values, + for example, during generation of features used in machine learning + algorithms. + date_publication: '2022-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binr + url_git: https://github.com/jabiru/binr +BinSegBstrap: + version: 1.0-1 + title: Piecewise Smooth Regression by Bootstrapped Binary Segmentation + maintainer: Pein Florian + description: Provides methods for piecewise smooth regression. A piecewise smooth + signal is estimated by applying a bootstrapped test recursively (binary segmentation + approach). Each bootstrapped test decides whether the underlying signal is smooth + on the currently considered subsegment or contains at least one further change-point. + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BinSegBstrap + url_git: '' +binsegRcpp: + version: 2023.8.31 + title: Efficient Implementation of Binary Segmentation + maintainer: Toby Dylan Hocking + description: |- + Standard template library + containers are used to implement an efficient binary segmentation + algorithm, which is log-linear on average and quadratic in the + worst case. + date_publication: '2023-09-06' + bug_reports: https://github.com/tdhock/binsegRcpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=binsegRcpp + url_git: https://github.com/tdhock/binsegRcpp +binseqtest: + version: 1.0.4 + title: Exact Binary Sequential Designs and Analysis + maintainer: Michael P. Fay + description: For a series of binary responses, create stopping boundary with exact + results after stopping, allowing updating for missing assessments. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binseqtest + url_git: '' +binsmooth: + version: 0.2.2 + title: Generate PDFs and CDFs from Binned Data + maintainer: Dave Hunter + description: |- + Provides several methods for generating density functions + based on binned data. Methods include step function, recursive + subdivision, and optimized spline. Data are assumed to be nonnegative, + the top bin is assumed to have no upper bound, but the bin widths need + be equal. All PDF smoothing methods maintain the areas specified by + the binned data. (Equivalently, all CDF smoothing methods interpolate + the points specified by the binned data.) In practice, an estimate for + the mean of the distribution should be supplied as an optional argument. + Doing so greatly improves the reliability of statistics computed from + the smoothed density functions. Includes methods for estimating the Gini + coefficient, the Theil index, percentiles, and random deviates from a + smoothed distribution. Among the three methods, the optimized spline + (splinebins) is recommended for most purposes. The percentile and + random-draw methods should be regarded as experimental, and these methods + only support splinebins. + date_publication: '2020-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binsmooth + url_git: '' +binspp: + version: 0.1.26 + title: Bayesian Inference for Neyman-Scott Point Processes + maintainer: Remes Radim + description: |- + The Bayesian MCMC estimation of parameters for Thomas-type cluster + point process with various inhomogeneities. It allows for inhomogeneity in + (i) distribution of parent points, (ii) mean number of points in a cluster, + (iii) cluster spread. The package also allows for the Bayesian MCMC + algorithm for the homogeneous generalized Thomas process. The cluster size + is allowed to have a variance that is greater or less than the expected + value (cluster sizes are over or under dispersed). Details are described in + Dvořák, Remeš, Beránek & Mrkvička (2022) . + date_publication: '2022-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binspp + url_git: https://github.com/tomasmrkvicka/binspp +binsreg: + version: '1.1' + title: Binscatter Estimation and Inference + maintainer: Yingjie Feng + description: Provides tools for statistical analysis using the binscatter methods + developed by Cattaneo, Crump, Farrell and Feng (2024a) , + Cattaneo, Crump, Farrell and Feng (2024b) + and Cattaneo, Crump, Farrell and Feng (2024c) . + Binscatter provides a flexible way of describing the relationship between two + variables based on partitioning/binning of the independent variable of interest. + binsreg(), binsqreg() and binsglm() implement binscatter least squares regression, + quantile regression and generalized linear regression respectively, with particular + focus on constructing binned scatter plots. They also implement robust (pointwise + and uniform) inference of regression functions and derivatives thereof. binstest() + implements hypothesis testing procedures for parametric functional forms of and + nonparametric shape restrictions on the regression function. binspwc() implements + hypothesis testing procedures for pairwise group comparison of binscatter estimators. + binsregselect() implements data-driven procedures for selecting the number of + bins for binscatter estimation. All the commands allow for covariate adjustment, + smoothness restrictions and clustering. + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binsreg + url_git: '' +binst: + version: 0.2.1 + title: Data Preprocessing, Binning for Classification and Regression + maintainer: Chapman Siu + description: |- + Various supervised and unsupervised binning tools + including using entropy, recursive partition methods + and clustering. + date_publication: '2018-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=binst + url_git: https://github.com/jules-and-dave/binst +BINtools: + version: 0.2.0 + title: Bayesian BIN (Bias, Information, Noise) Model of Forecasting + maintainer: Ville Satopää + description: |- + A recently proposed Bayesian BIN model disentangles the underlying processes + that enable forecasters and forecasting methods to improve, decomposing forecasting accuracy into + three components: bias, partial information, and noise. By describing the differences between two + groups of forecasters, the model allows the user to carry out useful inference, such as calculating + the posterior probabilities of the treatment reducing bias, diminishing noise, or increasing information. + It also provides insight into how much tamping down bias and noise in judgment or enhancing the efficient + extraction of valid information from the environment improves forecasting accuracy. This package provides + easy access to the BIN model. For further information refer to the paper Ville A. Satopää, Marat Salikhov, + Philip E. Tetlock, and Barbara Mellers (2021) "Bias, Information, Noise: The BIN + Model of Forecasting" . + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BINtools + url_git: '' +bio.infer: + version: 1.3-6 + title: Predict Environmental Conditions from Biological Observations + maintainer: Lester L. Yuan + description: |- + Imports benthic count data, reformats this data, and + computes environmental inferences from this data. + date_publication: '2020-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bio.infer + url_git: '' +bio3d: + version: 2.4-5 + title: Biological Structure Analysis + maintainer: Barry Grant + description: |- + Utilities to process, organize and explore protein structure, + sequence and dynamics data. Features include the ability to read and write + structure, sequence and dynamic trajectory data, perform sequence and structure + database searches, data summaries, atom selection, alignment, superposition, + rigid core identification, clustering, torsion analysis, distance matrix + analysis, structure and sequence conservation analysis, normal mode analysis, + principal component analysis of heterogeneous structure data, and correlation + network analysis from normal mode and molecular dynamics data. In addition, + various utility functions are provided to enable the statistical and graphical + power of the R environment to work with biological sequence and structural data. + Please refer to the URLs below for more information. + date_publication: '2024-10-29' + bug_reports: '' + url: http://thegrantlab.org/bio3d/ + url_cran: https://CRAN.R-project.org/package=bio3d + url_git: https://bitbucket.org/Grantlab/bio3d/ +bioacoustics: + version: 0.2.8 + title: |- + Analyse Audio Recordings and Automatically Extract Animal + Vocalizations + maintainer: Jean Marchal + description: |- + Contains all the necessary tools to process audio recordings of + various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, + display audio signals, detect and extract automatically acoustic + features for further analysis such as classification. + date_publication: '2022-02-08' + bug_reports: https://github.com/wavx/bioacoustics/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=bioacoustics + url_git: https://github.com/wavx/bioacoustics/ +BiObjClass: + version: 0.1.0 + title: Classification of Algorithms + maintainer: Tiago Costa Soares + description: Implements the Bi-objective Lexicographical Classification method and + Performance Assessment Ratio at 10% metric for algorithm classification. Constructs + matrices representing algorithm performance under multiple criteria, facilitating + decision-making in algorithm selection and evaluation. Analyzes and compares algorithm + performance based on various metrics to identify the most suitable algorithms + for specific tasks. This package includes methods for algorithm classification + and evaluation, with examples provided in the documentation. Carvalho (2019) presents + a statistical evaluation of algorithmic computational experimentation with infeasible + solutions . Moreira and Carvalho (2023) analyze + power in preprocessing methodologies for datasets with missing values . + date_publication: '2024-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiObjClass + url_git: '' +biobricks: + version: 0.2.2 + title: Access Data Dependencies Installed Through 'Biobricks.ai' + maintainer: Thomas Luechtefeld + description: Provides an integrated data management solution for assets installed + via the 'Biobricks.ai' platform. Streamlines the process of loading and interacting + with diverse datasets in a consistent manner. A list of bricks is available at + . Documentation for 'Biobricks.ai' is available at + . + date_publication: '2023-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biobricks + url_git: '' +bioC.logs: + version: 1.2.1 + title: BioConductor Package Downloads Stats + maintainer: Marcelo Ponce + description: Download stats reported from the BioConductor.org stats website. + date_publication: '2023-01-06' + bug_reports: https://github.com/mponce0/bioC.logs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bioC.logs + url_git: https://github.com/mponce0/bioC.logs +BioCircos: + version: 0.3.4 + title: |- + Interactive Circular Visualization of Genomic Data using + 'htmlwidgets' and 'BioCircos.js' + maintainer: Loan Vulliard + description: |- + Implement in 'R' interactive Circos-like visualizations of genomic data, to map information + such as genetic variants, genomic fusions and aberrations to a circular genome, as proposed by the + 'JavaScript' library 'BioCircos.js', based on the 'JQuery' and 'D3' technologies. The output is by + default displayed in stand-alone HTML documents or in the 'RStudio' viewer pane. Moreover it can be + integrated in 'R Markdown' documents and 'Shiny' applications. + date_publication: '2019-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioCircos + url_git: https://github.com/lvulliard/BioCircos.R +bioclim: + version: 0.4.0 + title: Bioclimatic Analysis and Classification + maintainer: Roberto Serrano-Notivoli + description: |- + Using numeric or raster data, this package contains functions to + calculate: complete water balance, bioclimatic balance, bioclimatic + intensities, reports for individual locations, multi-layered rasters for + spatial analysis. + date_publication: '2023-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bioclim + url_git: '' +BiocManager: + version: 1.30.25 + title: Access the Bioconductor Project Package Repository + maintainer: Marcel Ramos + description: A convenient tool to install and update Bioconductor packages. + date_publication: '2024-08-28' + bug_reports: https://github.com/Bioconductor/BiocManager/issues + url: https://bioconductor.github.io/BiocManager/ + url_cran: https://CRAN.R-project.org/package=BiocManager + url_git: '' +biocompute: + version: 1.1.1 + title: Create and Manipulate BioCompute Objects + maintainer: Soner Koc + description: |- + Tools to create, validate, and export BioCompute Objects + described in King et al. (2019) . + Users can encode information in data frames, and compose + BioCompute Objects from the domains defined by the standard. + A checksum validator and a JSON schema validator are provided. + This package also supports exporting BioCompute Objects as JSON, + PDF, HTML, or 'Word' documents, and exporting to cloud-based platforms. + date_publication: '2022-05-03' + bug_reports: https://github.com/sbg/biocompute/issues + url: https://sbg.github.io/biocompute/ + url_cran: https://CRAN.R-project.org/package=biocompute + url_git: https://github.com/sbg/biocompute +BioCro: + version: 3.1.3 + title: Modular Crop Growth Simulations + maintainer: Justin M. McGrath + description: |- + A cross-platform representation of models as sets of equations + that facilitates modularity in model building and allows users to harness + modern techniques for numerical integration and data visualization. + Documentation is provided by several vignettes included in this package; + also see Lochocki et al. (2022) . + date_publication: '2024-04-30' + bug_reports: '' + url: https://biocro.github.io + url_cran: https://CRAN.R-project.org/package=BioCro + url_git: https://github.com/biocro/biocro +Biodem: + version: '0.5' + title: Biodemography Functions + maintainer: Federico Calboli + description: The Biodem package provides a number of functions for Biodemographic + analysis. + date_publication: '2021-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Biodem + url_git: '' +BiodiversityR: + version: 2.17-1.1 + title: Package for Community Ecology and Suitability Analysis + maintainer: Roeland Kindt + description: Graphical User Interface (via the R-Commander) and utility functions + (often based on the vegan package) for statistical analysis of biodiversity and + ecological communities, including species accumulation curves, diversity indices, + Renyi profiles, GLMs for analysis of species abundance and presence-absence, distance + matrices, Mantel tests, and cluster, constrained and unconstrained ordination + analysis. A book on biodiversity and community ecology analysis is available for + free download from the website. In 2012, methods for (ensemble) suitability modelling + and mapping were expanded in the package. + date_publication: '2025-01-21' + bug_reports: '' + url: http://www.worldagroforestry.org/output/tree-diversity-analysis + url_cran: https://CRAN.R-project.org/package=BiodiversityR + url_git: '' +biodosetools: + version: 3.6.1 + title: An R Shiny Application for Biological Dosimetry + maintainer: Alfredo Hernández + description: |- + A tool to perform all different statistical tests and calculations + needed by Biological Dosimetry Laboratories. + date_publication: '2022-11-16' + bug_reports: https://github.com/biodosetools-team/biodosetools/issues/ + url: https://biodosetools-team.github.io/biodosetools/ + url_cran: https://CRAN.R-project.org/package=biodosetools + url_git: https://github.com/biodosetools-team/biodosetools/ +BIOdry: + version: '0.9' + title: Multilevel Modeling of Dendroclimatical Fluctuations + maintainer: Wilson Lara + description: Multilevel ecological data series (MEDS) are sequences of observations + ordered according to temporal/spatial hierarchies that are defined by sample designs, + with sample variability confined to ecological factors. Dendroclimatic MEDS of + tree rings and climate are modeled into normalized fluctuations of tree growth + and aridity. Modeled fluctuations (model frames) are compared with Mantel correlograms + on multiple levels defined by sample design. Package implementation can be understood + by running examples in modelFrame(), and muleMan() functions. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BIOdry + url_git: '' +biogas: + version: '1.61' + title: Process Biogas Data and Predict Biogas Production + maintainer: Sasha D. Hafner + description: High- and low-level functions for processing biogas data and predicting + biogas production. Molar mass and calculated oxygen demand (COD') can be determined + from a chemical formula. Measured gas volume can be corrected for water vapor + and to (possibly user-defined) standard temperature and pressure. Gas quantity + can be converted between volume, mass, and moles. Gas composition, cumulative + production, or other variables can be interpolated to a specified time. Cumulative + biogas and methane production (and rates) can be calculated from raw data obtained + using volumetric, manometric, gravimetric, or gas density methods for any number + of bottles. With cumulative methane production data and data on bottle contents, + biochemical methane potential (BMP) or specific methane production (SMP) can be + calculated and summarized, including subtraction of the inoculum contribution + and normalization by substrate mass. Cumulative production and production rates + can be summarized in several different ways (e.g., omitting normalization) using + the same function. Biogas quantity and composition can be predicted from substrate + composition and additional, optional data. Inoculum and substrate mass can be + determined for planning BMP experiments. Finally, first-order models can be fit + to measurements in order to extract estimates of ultimate yield and kinetic constants. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biogas + url_git: '' +biogeom: + version: 1.4.3 + title: Biological Geometries + maintainer: Peijian Shi + description: Is used to simulate and fit biological geometries. 'biogeom' incorporates + several novel universal parametric equations that can generate the profiles of + bird eggs, flowers, linear and lanceolate leaves, seeds, starfish, and tree-rings + (Gielis (2003) ; Shi et al. (2020) ), + three growth-rate curves representing the ontogenetic growth trajectories of animals + and plants against time, and the axially symmetrical and integral forms of all + these functions (Shi et al. (2017) ; Shi + et al. (2021) ). The optimization method proposed by + Nelder and Mead (1965) was used to estimate model + parameters. 'biogeom' includes several real data sets of the boundary coordinates + of natural shapes, including avian eggs, fruit, lanceolate and ovate leaves, tree + rings, seeds, and sea stars,and can be potentially applied to other natural shapes. + 'biogeom' can quantify the conspecific or interspecific similarity of natural + outlines, and provides information with important ecological and evolutionary + implications for the growth and form of living organisms. Please see Shi et al. + (2022) for details. + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biogeom + url_git: '' +biogram: + version: 1.6.3 + title: N-Gram Analysis of Biological Sequences + maintainer: Michal Burdukiewicz + description: |- + Tools for extraction and analysis of various + n-grams (k-mers) derived from biological sequences (proteins + or nucleic acids). Contains QuiPT (quick permutation test) for fast + feature-filtering of the n-gram data. + date_publication: '2020-03-31' + bug_reports: https://github.com/michbur/biogram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biogram + url_git: https://github.com/michbur/biogram +biogrowth: + version: 1.0.5 + title: Modelling of Population Growth + maintainer: Alberto Garre + description: |- + Modelling of population growth under static and dynamic environmental conditions. + Includes functions for model fitting and making prediction under isothermal and + dynamic conditions. The methods (algorithms & models) are based on + predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)). + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biogrowth + url_git: '' +Bioi: + version: 0.2.10 + title: Biological Image Analysis + maintainer: Zachary Colburn + description: Single linkage clustering and connected component analyses are often + performed on biological images. 'Bioi' provides a set of functions for performing + these tasks. This functionality is implemented in several key functions that can + extend to from 1 to many dimensions. The single linkage clustering method implemented + here can be used on n-dimensional data sets, while connected component analyses + are limited to 3 or fewer dimensions. + date_publication: '2019-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bioi + url_git: '' +bioimagetools: + version: 1.1.8 + title: Tools for Microscopy Imaging + maintainer: Volker Schmid + description: |- + Tools for 3D imaging, mostly for biology/microscopy. + Read and write TIFF stacks. Functions for segmentation, filtering and analyzing 3D point patterns. + date_publication: '2022-05-28' + bug_reports: https://github.com/bioimaginggroup/bioimagetools/issues + url: https://bioimaginggroup.github.io/bioimagetools/ + url_cran: https://CRAN.R-project.org/package=bioimagetools + url_git: '' +bioinactivation: + version: 1.2.3 + title: Mathematical Modelling of (Dynamic) Microbial Inactivation + maintainer: Alberto Garre + description: |- + Functions for modelling microbial inactivation under + isothermal or dynamic conditions. The calculations are based on several mathematical models broadly + used by the scientific community and industry. Functions enable to make predictions for cases where the + kinetic parameters are known. It also implements functions for parameter estimation for isothermal and + dynamic conditions. The model fitting capabilities include an Adaptive Monte Carlo method for a Bayesian + approach to parameter estimation. + date_publication: '2019-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bioinactivation + url_git: '' +BioInsight: + version: 0.3.1 + title: Filter and Plot RNA Biotypes + maintainer: Luiz Antonio de Jesus Rocha + description: Analyze and plot the abundance of different RNA biotypes present in + a count matrix, this evaluation can be useful if you want to test different strategies + of normalization or analyze a particular biotype in a differential gene expression + analysis. + date_publication: '2021-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioInsight + url_git: '' +biolink: + version: 0.1.8 + title: Create Hyperlinks to Biological Databases and Resources + maintainer: Aaron Wolen + description: |- + Generate urls and hyperlinks to commonly used biological databases + and resources based on standard identifiers. This is primarily useful when + writing dynamic reports that reference things like gene symbols in text or + tables, allowing you to, for example, convert gene identifiers to hyperlinks + pointing to their entry in the 'NCBI' Gene database. Currently supports + 'NCBI' Gene, 'PubMed', Gene Ontology, 'KEGG', CRAN and Bioconductor. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biolink + url_git: '' +biologicalActivityIndices: + version: 0.1.0 + title: Biological Activity Indices + maintainer: Tanuj Misra + description: Ecological alteration of degraded lands can improve their sustainability + by addition of large amount of biomass to soil resulting in improved soil health. + Soil biological parameters (such as carbon, nitrogen and phosphorus cycling enzyme + activity) are reactive to minute variations in soils [Ghosh et al. (2021) + ]. Hence, biological activity index combining Urease, Alkaline Phosphatase, Dehydrogenase + (DHA) & Beta-Glucosidase activity will assist in detecting early changes in restored + land use systems [Patidar et al. (2023) ]. This + package helps to calculate Biological Activity Index (BAI) based on vectors of + Land Use System/treatment and control/reference Land Use System containing four + values of Urease, Alkaline Phosphatase, DHA & Beta-Glucosidase. (DHA), urease + (URE), fluorescein diacetate hydrolysis (FDA) and alkaline phosphatase (ALP) activities + are measured in soil samples using triphenyl tetrazolium chloride, urea, fluorescein + diacetate and p-nitro phenyl-phosphate as substrates, respectively. + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biologicalActivityIndices + url_git: '' +BioM2: + version: 1.1.1 + title: Biologically Explainable Machine Learning Framework + maintainer: Shunjie Zhang + description: Biologically Explainable Machine Learning Framework for Phenotype Prediction + using omics data described in Chen and Schwarz (2017) .Identifying + reproducible and interpretable biological patterns from high-dimensional omics + data is a critical factor in understanding the risk mechanism of complex disease. + As such, explainable machine learning can offer biological insight in addition + to personalized risk scoring.In this process, a feature space of biological pathways + will be generated, and the feature space can also be subsequently analyzed using + WGCNA (Described in Horvath and Zhang (2005) and + Langfelder and Horvath (2008) ) methods. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioM2 + url_git: '' +BioMark: + version: 0.4.5 + title: Find Biomarkers in Two-Class Discrimination Problems + maintainer: Ron Wehrens + description: 'Variable selection methods are provided for several classification + methods: the lasso/elastic net, PCLDA, PLSDA, and several t-tests. Two approaches + for selecting cutoffs can be used, one based on the stability of model coefficients + under perturbation, and the other on higher criticism.' + date_publication: '2015-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioMark + url_git: '' +biomartr: + version: 1.0.7 + title: Genomic Data Retrieval + maintainer: Hajk-Georg Drost + description: |- + Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized + way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome + retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', + and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database + (Smedley et al. (2009) ) allows users to retrieve + functional annotation for genomic loci. In addition, users can download entire databases such + as 'NCBI RefSeq' (Pruitt et al. (2007) ), 'NCBI nr', + 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) ), etc. with only one command. + date_publication: '2023-12-02' + bug_reports: https://github.com/ropensci/biomartr/issues + url: https://docs.ropensci.org/biomartr/ + url_cran: https://CRAN.R-project.org/package=biomartr + url_git: https://github.com/ropensci/biomartr +BIOMASS: + version: 2.2.3 + title: |- + Estimating Aboveground Biomass and Its Uncertainty in Tropical + Forests + maintainer: Dominique Lamonica + description: |- + Contains functions to estimate aboveground biomass/carbon and its uncertainty in tropical forests. + These functions allow to (1) retrieve and to correct taxonomy, (2) estimate wood density and its uncertainty, + (3) construct height-diameter models, (4) manage tree and plot coordinates, + (5) estimate the aboveground biomass/carbon at the stand level with associated uncertainty. + To cite 'BIOMASS', please use citation("BIOMASS"). + See more in the article of Réjou-Méchain et al. (2017) . + date_publication: '2025-02-24' + bug_reports: https://github.com/umr-amap/BIOMASS/issues/ + url: https://umr-amap.github.io/BIOMASS/ + url_cran: https://CRAN.R-project.org/package=BIOMASS + url_git: https://github.com/umr-amap/BIOMASS/ +biometryassist: + version: 1.2.1 + title: Functions to Assist Design and Analysis of Agronomic Experiments + maintainer: Sam Rogers + description: |- + Provides functions to aid in the design and analysis of + agronomic and agricultural experiments through easy access to + documentation and helper functions, especially for users who are + learning these concepts. While not required for most functionality, + this package enhances the `asreml` package which provides a + computationally efficient algorithm for fitting mixed models + using Residual Maximum Likelihood. It is a commercial package + that can be purchased as 'asreml-R' from 'VSNi' + , who will supply a zip file for local + installation/updating (see ). + date_publication: '2024-06-05' + bug_reports: https://github.com/biometryhub/biometryassist/issues + url: https://biometryhub.github.io/biometryassist/ + url_cran: https://CRAN.R-project.org/package=biometryassist + url_git: '' +biomod2: + version: 4.2-6-2 + title: Ensemble Platform for Species Distribution Modeling + maintainer: Maya Gueguen + description: |- + Functions for species distribution modeling, calibration and evaluation, + ensemble of models, ensemble forecasting and visualization. The package permits to run + consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) + dataset and to combine them in ensemble models and ensemble projections. Some bench of other + evaluation and visualization tools are also available within the package. + date_publication: '2025-01-24' + bug_reports: https://github.com/biomodhub/biomod2/issues + url: https://biomodhub.github.io/biomod2/ + url_cran: https://CRAN.R-project.org/package=biomod2 + url_git: '' +bionetdata: + version: '1.1' + title: Biological and Chemical Data Networks + maintainer: Giorgio Valentini + description: Data Package that includes several examples of chemical and biological + data networks, i.e. data graph structured. + date_publication: '2022-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bionetdata + url_git: '' +BioPET: + version: 0.2.2 + title: Biomarker Prognostic Enrichment Tool + maintainer: Jeremy Roth + description: Prognostic Enrichment is a clinical trial strategy of evaluating an + intervention in a patient population with a higher rate of the unwanted event + than the broader patient population (R. Temple (2010) ). + A higher event rate translates to a lower sample size for the clinical trial, + which can have both practical and ethical advantages. This package is a tool to + help evaluate biomarkers for prognostic enrichment of clinical trials. + date_publication: '2018-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioPET + url_git: '' +BioPETsurv: + version: 0.1.0 + title: Biomarker Prognostic Enrichment Tool for Time-to-Event Trial + maintainer: Si Cheng + description: |- + Prognostic Enrichment is a strategy of enriching a clinical trial for testing an intervention intended to prevent or delay an unwanted clinical event. A prognostically enriched trial enrolls only patients who are more likely to experience the unwanted clinical event than the broader patient population (R. Temple (2010) ). By testing the intervention in an enriched study population, the trial may be adequately powered with a smaller sample size, which can have both practical and ethical advantages. + This package provides tools to evaluate biomarkers for prognostic enrichment of clinical trials with survival/time-to-event outcomes. + date_publication: '2020-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioPETsurv + url_git: '' +biopixR: + version: 1.2.0 + title: Extracting Insights from Biological Images + maintainer: Tim Brauckhoff + description: |- + Combines the 'magick' and 'imager' packages to streamline image analysis, focusing on feature extraction and quantification from biological images, especially + microparticles. By providing high throughput pipelines and clustering capabilities, 'biopixR' facilitates efficient insight generation for researchers (Schneider J. et al. (2019) + ). + date_publication: '2024-11-11' + bug_reports: https://github.com/Brauckhoff/biopixR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biopixR + url_git: https://github.com/Brauckhoff/biopixR +BioPred: + version: 1.0.2 + title: An R Package for Biomarkers Analysis in Precision Medicine + maintainer: Zihuan Liu + description: Provides functions for training extreme gradient boosting model using + propensity score A-learning and weight-learning methods. For further details, + see Liu et al. (2024) . + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioPred + url_git: '' +BioProbability: + version: '1.0' + title: Probability in Biostatistics + maintainer: Paula Saavedra-Nieves + description: Several tools for analyzing diagnostic tests and 2x2 contingency tables + are provided. In particular, positive and negative predictive values for a diagnostic + tests can be calculated from prevalence, sensitivity and specificity values. For + contingency tables, relative risk and odds ratio measures are estimated. Furthermore, + confidence intervals are provided. + date_publication: '2020-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioProbability + url_git: '' +bioRad: + version: 0.8.1 + title: Biological Analysis and Visualization of Weather Radar Data + maintainer: Adriaan M. Dokter + description: |- + Extract, visualize and summarize aerial movements of birds and + insects from weather radar data. See Dokter, A. M. et al. (2018) + "bioRad: biological analysis and visualization of weather radar data" + for a software paper describing package and methodologies. + date_publication: '2024-07-30' + bug_reports: https://github.com/adokter/bioRad/issues + url: https://adriaandokter.com/bioRad/ + url_cran: https://CRAN.R-project.org/package=bioRad + url_git: https://github.com/adokter/bioRad/ +bioregion: + version: 1.2.0 + title: Comparison of Bioregionalisation Methods + maintainer: Maxime Lenormand + description: The main purpose of this package is to propose a transparent methodological + framework to compare bioregionalisation methods based on hierarchical and non-hierarchical + clustering algorithms (Kreft & Jetz (2010) ) + and network algorithms (Lenormand et al. (2019) and Leroy + et al. (2019) ). + date_publication: '2025-01-31' + bug_reports: https://github.com/bioRgeo/bioregion/issues + url: https://bioRgeo.github.io/bioregion/ + url_cran: https://CRAN.R-project.org/package=bioregion + url_git: https://github.com/bioRgeo/bioregion +BioRssay: + version: 1.1.0 + title: Analyze Bioassays and Probit Graphs + maintainer: Piyal Karunarathne + description: A robust framework for analyzing mortality data from bioassays for + one or several strains/lines/populations. + date_publication: '2022-08-09' + bug_reports: https://github.com/milesilab/BioRssay/issues/ + url: https://milesilab.github.io/BioRssay/ + url_cran: https://CRAN.R-project.org/package=BioRssay + url_git: '' +Bios2cor: + version: 2.2.2 + title: |- + From Biological Sequences and Simulations to Correlation + Analysis + maintainer: Marie Chabbert + description: 'Utilities for computation and analysis of correlation/covariation + in multiple sequence alignments and in side chain motions during molecular dynamics + simulations. Features include the computation of correlation/covariation scores + using a variety of scoring functions between either sequence positions in alignments + or side chain dihedral angles in molecular dynamics simulations and utilities + to analyze the correlation/covariation matrix through a variety of tools including + network representation and principal components analysis. In addition, several + utility functions are based on the R graphical environment to provide friendly + tools for help in data interpretation. Examples of sequence covariation analysis + are provided in: (1) Pele J, Moreau M, Abdi H, Rodien P, Castel H, Chabbert M + (2014) and (2) Taddese B, Deniaud M, Garnier A, Tiss + A, Guissouma H, Abdi H, Henrion D, Chabbert M (2018) . + An example of side chain correlated motion analysis is provided in: Taddese B, + Garnier A, Abdi H, Henrion D, Chabbert M (2020) . + This work was supported by the French National Research Agency (Grant number: + ANR-11-BSV2-026) and by GENCI (Grant number: 100567).' + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bios2cor + url_git: '' +bios2mds: + version: 1.2.3 + title: From Biological Sequences to Multidimensional Scaling + maintainer: Marie Chabbert + description: |- + Utilities dedicated to the analysis of + biological sequences by metric MultiDimensional Scaling with + projection of supplementary data. It contains functions for + reading multiple sequence alignment files, calculating distance + matrices, performing metric multidimensional scaling and + visualizing results. + date_publication: '2020-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bios2mds + url_git: '' +biosampleR: + version: 1.0.4 + title: |- + Biodiversity Index Calculation and Bootstrap Confidence Interval + Estimation + maintainer: Craig Eric Simpkins + description: 'Provides tools for the calculation of common biodiversity indices + from count data. Additionally, it incorporates bootstrapping techniques to generate + multiple samples, facilitating the estimation of confidence intervals around these + indices. Furthermore, the package allows for the exploration of how variation + in these indices changes with differing numbers of sites, making it a useful tool + with which to begin an ecological analysis. Methods are based on the following + references: Chao et al. (2014) , Chao and Colwell (2022) + , Hsieh, Ma,` and Chao (2016) .' + date_publication: '2023-09-13' + bug_reports: https://github.com/csim063/biosampleR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biosampleR + url_git: https://github.com/csim063/biosampleR +biosensors.usc: + version: '1.0' + title: Distributional Data Analysis Techniques for Biosensor Data + maintainer: Juan C. Vidal + description: |- + Unified and user-friendly framework for using new + distributional representations of biosensors data in different statistical modeling + tasks: regression models, hypothesis testing, cluster analysis, visualization, and + descriptive analysis. Distributional representations are a functional extension of + compositional time-range metrics and we have used them successfully so far in modeling + glucose profiles and accelerometer data. However, these functional representations can + be used to represent any biosensor data such as ECG or medical imaging such as fMRI. + Matabuena M, Petersen A, Vidal JC, Gude F. "Glucodensities: A new representation of + glucose profiles using distributional data analysis" (2021) + . + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biosensors.usc + url_git: '' +bioseq: + version: 0.1.4 + title: A Toolbox for Manipulating Biological Sequences + maintainer: Francois Keck + description: |- + Classes and functions to work with biological sequences (DNA, RNA and amino acid sequences). + Implements S3 infrastructure to work with biological sequences as described in Keck (2020) . + Provides a collection of functions to perform biological conversion among classes + (transcription, translation) and basic operations on sequences + (detection, selection and replacement based on positions or patterns). + The package also provides functions to import and export sequences from and to other package formats. + date_publication: '2022-09-06' + bug_reports: https://github.com/fkeck/bioseq/issues + url: https://fkeck.github.io/bioseq/ + url_cran: https://CRAN.R-project.org/package=bioseq + url_git: '' +biosignalEMG: + version: 2.1.0 + title: Tools for Electromyogram Signals (EMG) Analysis + maintainer: Antonio Guerrero + description: Data processing tools to compute the rectified, integrated and the + averaged EMG. Routines for automatic detection of activation phases. A routine + to compute and plot the ensemble average of the EMG. An EMG signal simulator for + general purposes. + date_publication: '2018-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biosignalEMG + url_git: '' +bioSNR: + version: '1.0' + title: |- + Bioacoustic Basic Operations with Decibels and the Passive Sonar + Equation + maintainer: Matthew Duggan + description: 'A beginners toolbox to help those in ecology who want to deepen their + understanding or utilize Bioacoustics in their work. The package has a number + of utilizations from calculating frequency from waveform, performing operations + in dB, and determining acoustic range of recorders. The majority of this package + is based on key concepts learned from the K. Lisa Yang Center for Conservation + Bioacoustics at Cornell University and their associated course: Introduction to + Bioacoustics course. More information can be found within the walk through vignettes + at .' + date_publication: '2023-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bioSNR + url_git: '' +biospear: + version: 1.0.2 + title: Biomarker Selection in Penalized Regression Models + maintainer: Stefan Michiels + description: 'Provides some tools for developing and validating prediction models, + estimate expected survival of patients and visualize them graphically. Most of + the implemented methods are based on penalized regressions such as: the lasso + (Tibshirani R (1996)), the elastic net (Zou H et al. (2005) ), + the adaptive lasso (Zou H (2006) ), the stability + selection (Meinshausen N et al. (2010) ), + some extensions of the lasso (Ternes et al. (2016) ), some + methods for the interaction setting (Ternes N et al. (2016) ), + or others. A function generating simulated survival data set is also provided.' + date_publication: '2018-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biospear + url_git: '' +biostat3: + version: 0.2.2 + title: |- + Utility Functions, Datasets and Extended Examples for Survival + Analysis + maintainer: Mark Clements + description: Utility functions, datasets and extended examples for survival analysis. + This extends a range of other packages, some simple wrappers for time-to-event + analyses, datasets, and extensive examples in HTML with R scripts. The package + also supports the course Biostatistics III entitled "Survival analysis for epidemiologists + in R". + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biostat3 + url_git: '' +Biostatistics: + version: 1.0.4 + title: Statistics Tutorials for Biologists + maintainer: Rob Knell + description: |- + Tutorials for statistics, aimed at biological scientists. + Subjects range from basic descriptive statistics + through to complex linear modelling. The tutorials + include text, videos, interactive coding exercises + and multiple choice quizzes. The package also + includes 19 datasets which are used in the + tutorials. + date_publication: '2022-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Biostatistics + url_git: '' +BioStatR: + version: 4.0.1 + title: Initiation à La Statistique Avec R + maintainer: Frederic Bertrand + description: Datasets and functions for the book "Initiation à la Statistique avec + R", F. Bertrand and M. Maumy-Bertrand (2022, ISBN:978-2100782826 Dunod, fourth + edition). + date_publication: '2023-03-21' + bug_reports: https://github.com/fbertran/BioStatR/issues/ + url: https://fbertran.github.io/BioStatR/ + url_cran: https://CRAN.R-project.org/package=BioStatR + url_git: https://github.com/fbertran/BioStatR/ +biostats101: + version: 0.1.1 + title: Practical Functions for Biostatistics Beginners + maintainer: Marina Mautner Wizentier + description: |- + A set of user-friendly functions designed to fill gaps in existing introductory biostatistics R tools, making it easier for newcomers to perform basic biostatistical analyses without needing advanced programming skills. + The methods implemented in this package are based on the works: + Connor (1987) + Fleiss, Levin, & Paik (2013, ISBN:978-1-118-62561-3) + Levin & Chen (1999) + McNemar (1947) . + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biostats101 + url_git: '' +BiostatsUHNplus: + version: 1.0.2 + title: Nested Data Summary, Adverse Events and REDCap + maintainer: Tyler Pittman + description: |- + Tools and code snippets for summarizing nested data, adverse events + and REDCap study information. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiostatsUHNplus + url_git: '' +biotic: + version: 0.1.2 + title: Calculation of Freshwater Biotic Indices + maintainer: Dr Rob Briers + description: |- + Calculates a range of UK freshwater invertebrate biotic indices + including BMWP, Whalley, WHPT, Habitat-specific BMWP, AWIC, LIFE and PSI. + date_publication: '2016-04-20' + bug_reports: https://github.com/robbriers/biotic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biotic + url_git: https://github.com/robbriers/biotic +BioTIMEr: + version: 0.2.3 + title: Tools to Use and Explore the 'BioTIME' Database + maintainer: Alban Sagouis + description: |- + The 'BioTIME' database was first published in + 2018 and inspired ideas, questions, project and research + article. To make it even more accessible, an R package + was created. + The 'BioTIMEr' package provides tools designed to interact with the + 'BioTIME' database. The functions provided include the 'BioTIME' recommended + methods for preparing (gridding and rarefaction) time series data, a + selection of standard biodiversity metrics (including species richness, + numerical abundance and exponential Shannon) alongside examples on how to + display change over time. It also includes a sample subset of both the query + and meta data, the full versions of which are freely available on the 'BioTIME' + website . + date_publication: '2024-07-31' + bug_reports: https://github.com/bioTIMEHub/BioTIMEr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BioTIMEr + url_git: https://github.com/bioTIMEHub/BioTIMEr +biotools: + version: '4.2' + title: |- + Tools for Biometry and Applied Statistics in Agricultural + Science + maintainer: Anderson Rodrigo da Silva + description: |- + Tools designed to perform and evaluate cluster analysis (including Tocher's algorithm), + discriminant analysis and path analysis (standard and under collinearity), as well as some + useful miscellaneous tools for dealing with sample size and optimum plot size calculations. + A test for seed sample heterogeneity is now available. Mantel's permutation test can be found in this package. + A new approach for calculating its power is implemented. biotools also contains tests for genetic covariance components. + Heuristic approaches for performing non-parametric spatial predictions of generic response variables and + spatial gene diversity are implemented. + date_publication: '2021-08-07' + bug_reports: https://github.com/arsilva87/biotools/issues + url: https://arsilva87.github.io/biotools/ + url_cran: https://CRAN.R-project.org/package=biotools + url_git: '' +BioVenn: + version: 1.1.3 + title: Create Area-Proportional Venn Diagrams from Biological Lists + maintainer: Tim Hulsen + description: Creates an area-proportional Venn diagram of 2 or 3 circles. 'BioVenn' + is the only R package that can automatically generate an accurate area-proportional + Venn diagram by having only lists of (biological) identifiers as input. Also offers + the option to map Entrez and/or Affymetrix IDs to Ensembl IDs. In SVG mode, text + and numbers can be dragged and dropped. Based on the BioVenn web interface available + at . Hulsen (2021) . + date_publication: '2021-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioVenn + url_git: '' +BioVizSeq: + version: 1.0.1 + title: Visualizing the Elements Within Bio-Sequences + maintainer: Shiqi Zhao + description: |- + Visualizing the types and distribution of elements within + bio-sequences. At the same time, We have developed a geom layer, + geom_rrect(), that can generate rounded rectangles. No external references + are used in the development of this package. + date_publication: '2025-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BioVizSeq + url_git: '' +bipartite: + version: '2.21' + title: |- + Visualising Bipartite Networks and Calculating Some (Ecological) + Indices + maintainer: Carsten F. Dormann + description: Functions to visualise webs and calculate a series of indices commonly + used to describe pattern in (ecological) webs. It focuses on webs consisting of + only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation + is important to get an idea of what we are actually looking at, while the indices + summarise different aspects of the web's topology. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bipartite + url_git: https://github.com/biometry/bipartite +bipartiteD3: + version: 0.3.2 + title: Interactive Bipartite Graphs + maintainer: Chris Terry + description: |- + Generates interactive bipartite graphs using the D3 library. + Designed for use with the 'bipartite' analysis package. + Includes open source 'viz-js' library + Adapted from examples at (released under GPL-3). + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bipartiteD3 + url_git: '' +BipartiteModularityMaximization: + version: 1.23.120.1 + title: |- + Partition Bipartite Network into Non-Overlapping Biclusters by + Optimizing Bipartite Modularity + maintainer: Weibin Zhang + description: Function bipmod() that partitions a bipartite network into non-overlapping + biclusters by maximizing bipartite modularity defined in Barber (2007) + using the bipartite version of the algorithm described in Treviño (2015) . + date_publication: '2023-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BipartiteModularityMaximization + url_git: '' +bipd: + version: '0.3' + title: Bayesian Individual Patient Data Meta-Analysis using 'JAGS' + maintainer: Michael Seo + description: We use a Bayesian approach to run individual patient data meta-analysis + and network meta-analysis using 'JAGS'. The methods incorporate shrinkage methods + and calculate patient-specific treatment effects as described in Seo et al. (2021) + . This package also includes user-friendly functions that + impute missing data in an individual patient data using mice-related packages. + date_publication: '2022-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bipd + url_git: '' +bipl5: + version: 1.0.2 + title: Construct Reactive Calibrated Axes Biplots + maintainer: Ruan Buys + description: |- + A modern view on the principal component analysis biplot with + calibrated axes. Create principal component analysis biplots rendered in + HTML with significant reactivity embedded within the plot. Furthermore, + the traditional biplot view is enhanced by translated axes with inter-class + kernel densities superimposed. For more information on biplots, see + Gower, J.C., Lubbe, S. and le Roux, N.J. (2011, ISBN: 978-0-470-01255-0). + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bipl5 + url_git: '' +biplotbootGUI: + version: '1.3' + title: Bootstrap on Classical Biplots and Clustering Disjoint Biplot + maintainer: Ana Belen Nieto Librero + description: A GUI with which the user can construct and interact with Bootstrap + methods on Classical Biplots and with Clustering and/or Disjoint Biplot. This + GUI is also aimed for estimate any numerical data matrix using the Clustering + and Disjoint Principal component (CDPCA) methodology. + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biplotbootGUI + url_git: '' +biplotEZ: + version: '2.2' + title: EZ-to-Use Biplots + maintainer: Sugnet Lubbe + description: |- + Provides users with an EZ-to-use platform for representing data + with biplots. Currently principal component analysis (PCA), canonical variate + analysis (CVA) and simple correspondence analysis (CA) biplots are included. + This is accompanied by various formatting + options for the samples and axes. Alpha-bags and concentration ellipses + are included for visual enhancements and interpretation. For an extensive + discussion on the topic, see Gower, J.C., Lubbe, S. and le Roux, N.J. + (2011, ISBN: 978-0-470-01255-0) Understanding Biplots. Wiley: Chichester. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biplotEZ + url_git: '' +birankr: + version: 1.0.1 + title: Ranking Nodes in Bipartite and Weighted Networks + maintainer: Brian Aronson + description: Highly efficient functions for estimating various rank (centrality) + measures of nodes in bipartite graphs (two-mode networks). Includes methods for + estimating HITS, CoHITS, BGRM, and BiRank with implementation primarily inspired + by He et al. (2016) . Also provides easy-to-use + tools for efficiently estimating PageRank in one-mode graphs, incorporating or + removing edge-weights during rank estimation, projecting two-mode graphs to one-mode, + and for converting edgelists and matrices to sparseMatrix format. Best of all, + the package's rank estimators can work directly with common formats of network + data including edgelists (class data.frame, data.table, or tbl_df) and adjacency + matrices (class matrix or dgCMatrix). + date_publication: '2020-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=birankr + url_git: '' +birdie: + version: 0.6.1 + title: Bayesian Instrumental Regression for Disparity Estimation + maintainer: Cory McCartan + description: |- + Bayesian models for accurately estimating conditional + distributions by race, using Bayesian Improved Surname Geocoding (BISG) + probability estimates of individual race. Implements the methods described + in McCartan, Fisher, Goldin, Ho and Imai (2024) . + date_publication: '2024-06-11' + bug_reports: https://github.com/CoryMcCartan/birdie/issues + url: https://corymccartan.com/birdie/ + url_cran: https://CRAN.R-project.org/package=birdie + url_git: https://github.com/CoryMcCartan/birdie +birdring: + version: '1.6' + title: Methods to Analyse Ring Re-Encounter Data + maintainer: Fraenzi Korner-Nievergelt + description: R functions to read EURING data and analyse re-encounter data of birds + marked by metal rings. For a tutorial, go to . + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=birdring + url_git: '' +birdscanR: + version: 0.3.0 + title: |- + Migration Traffic Rate Calculation Package for 'Birdscan MR1' + Radars + maintainer: Birgen Haest + description: Extract data from 'Birdscan MR1' 'SQL' vertical-looking radar databases, + filter, and process them to Migration Traffic Rates (#objects per hour and km) + or density (#objects per km3) of, for example birds, and insects. Object classifications + in the 'Birdscan MR1' databases are based on the dataset of Haest et al. (2021) + ). Migration Traffic Rates and densities can be calculated + separately for different height bins (with a height resolution of choice) as well + as over time periods of choice (e.g., 1/2 hour, 1 hour, 1 day, day/night, the + full time period of observation, and anything in between). Two plotting functions + are also included to explore the data in the 'SQL' databases and the resulting + Migration Traffic Rate results. For details on the Migration Traffic Rate calculation + procedures, see Schmid et al. (2019) . + date_publication: '2024-07-05' + bug_reports: https://github.com/BirdScanCommunity/birdscanR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=birdscanR + url_git: https://github.com/BirdScanCommunity/birdscanR +birk: + version: 2.1.2 + title: MA Birk's Functions + maintainer: Matthew A. Birk + description: |- + Collection of tools to make R more convenient. Includes tools to + summarize data using statistics not available with base R and manipulate + objects for analyses. + date_publication: '2016-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=birk + url_git: '' +birtr: + version: 1.0.0 + title: The R Package for "The Basics of Item Response Theory Using R" + maintainer: Seock-Ho Kim + description: 'R functions for "The Basics of Item Response Theory Using R" by Frank + B. Baker and Seock-Ho Kim (Springer, 2017, ISBN-13: 978-3-319-54204-1) including + iccplot(), icccal(), icc(), iccfit(), groupinv(), tcc(), ability(), tif(), and + rasch(). For example, iccplot() plots an item characteristic curve under the + two-parameter logistic model.' + date_publication: '2017-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=birtr + url_git: '' +BIS: + version: '0.4' + title: Programmatic Access to Bank for International Settlements Data + maintainer: Stefan Angrick + description: |- + Provides an interface to data provided by the Bank for + International Settlements , allowing for programmatic + retrieval of a large quantity of (central) banking data. + date_publication: '2025-01-14' + bug_reports: https://github.com/stefanangrick/BIS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BIS + url_git: https://github.com/stefanangrick/BIS +biscale: + version: 1.0.0 + title: Tools and Palettes for Bivariate Thematic Mapping + maintainer: Christopher Prener + description: |- + Provides a 'ggplot2' centric approach to bivariate mapping. This is a + technique that maps two quantities simultaneously rather than the single value + that most thematic maps display. The package provides a suite of tools + for calculating breaks using multiple different approaches, a selection of + palettes appropriate for bivariate mapping and scale functions for 'ggplot2' + calls that adds those palettes to maps. Tools for creating bivariate legends + are also included. + date_publication: '2022-05-27' + bug_reports: https://github.com/chris-prener/biscale/issues + url: https://chris-prener.github.io/biscale/ + url_cran: https://CRAN.R-project.org/package=biscale + url_git: '' +BISdata: + version: 0.2-3 + title: Download Data from the Bank for International Settlements (BIS) + maintainer: Enrico Schumann + description: |- + Functions for downloading data from the Bank for + International Settlements (BIS; ) in + Basel. Supported are only full datasets in (typically) CSV + format. The package is lightweight and without dependencies; + suggested packages are used only if data is to be transformed + into particular data structures, for instance into 'zoo' + objects. Downloaded data can optionally be cached, to avoid + repeated downloads of the same files. + date_publication: '2024-05-01' + bug_reports: '' + url: https://enricoschumann.net/R/packages/BISdata/ + url_cran: https://CRAN.R-project.org/package=BISdata + url_git: https://github.com/enricoschumann/BISdata +bisectr: + version: 0.1.0 + title: Tools to find bad commits with git bisect + maintainer: Winston Chang + description: Tools to find bad commits with git bisect. Seehttps://github.com/wch/bisectr + for examples and test scripttemplates. + date_publication: '2012-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bisectr + url_git: https://github.com/wch/bisectr +BiSEp: + version: '2.3' + title: Toolkit to Identify Candidate Synthetic Lethality + maintainer: Mark Wappett + description: |- + Enables the user to infer potential synthetic lethal relationships + by analysing relationships between bimodally distributed gene pairs in big + gene expression datasets. Enables the user to visualise these candidate + synthetic lethal relationships. + date_publication: '2024-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiSEp + url_git: '' +bispdep: + version: 1.0-2 + title: Statistical Tools for Bivariate Spatial Dependence Analysis + maintainer: Carlos Melo + description: A collection of functions to test spatial autocorrelation between variables, + including Moran I, Geary C and Getis G together with scatter plots, functions + for mapping and identifying clusters and outliers, functions associated with the + moments of the previous statistics that will allow testing whether there is bivariate + spatial autocorrelation, and a function that allows identifying (visualizing neighbours) + on the map, the neighbors of any region once the scheme of the spatial weights + matrix has been established. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bispdep + url_git: https://github.com/carlosm77/bispdep +bisque: + version: 1.0.2 + title: |- + Approximate Bayesian Inference via Sparse Grid Quadrature + Evaluation (BISQuE) for Hierarchical Models + maintainer: Joshua Hewitt + description: Implementation of the 'bisque' strategy for approximate Bayesian posterior + inference. See Hewitt and Hoeting (2019) for complete details. 'bisque' + combines conditioning with sparse grid quadrature rules to approximate marginal + posterior quantities of hierarchical Bayesian models. The resulting approximations + are computationally efficient for many hierarchical Bayesian models. The 'bisque' + package allows approximate posterior inference for custom models; users only need + to specify the conditional densities required for the approximation. + date_publication: '2020-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bisque + url_git: '' +BisqueRNA: + version: 1.0.5 + title: Decomposition of Bulk Expression with Single-Cell Sequencing + maintainer: Brandon Jew + description: |- + Provides tools to accurately estimate cell type abundances + from heterogeneous bulk expression. A reference-based method utilizes + single-cell information to generate a signature matrix and transformation + of bulk expression for accurate regression based estimates. A marker-based + method utilizes known cell-specific marker genes to measure relative + abundances across samples. + For more details, see Jew and Alvarez et al (2019) . + date_publication: '2021-05-23' + bug_reports: https://github.com/cozygene/bisque/issues + url: https://www.biorxiv.org/content/10.1101/669911v1 + url_cran: https://CRAN.R-project.org/package=BisqueRNA + url_git: '' +BisRNA: + version: 0.2.2 + title: Analysis of RNA Cytosine-5 Methylation + maintainer: Carine Legrand + description: |- + Bisulfite-treated RNA non-conversion in a set of samples is + analysed as follows : each sample's non-conversion distribution is + identified to a Poisson distribution. P-values adjusted for multiple + testing are calculated in each sample. Combined non-conversion P-values + and standard errors are calculated on the intersection of the set of + samples. For further details, see C Legrand, F Tuorto, M Hartmann, + R Liebers, D Jakob, M Helm and F Lyko (2017) . + date_publication: '2017-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BisRNA + url_git: '' +bistablehistory: + version: 1.1.2 + title: Cumulative History Analysis for Bistable Perception Time Series + maintainer: Alexander Pastukhov + description: |- + Estimates cumulative history for time-series for continuously + viewed bistable perceptual rivalry displays. Computes cumulative history + via a homogeneous first order differential process. I.e., it assumes + exponential growth/decay of the history as a function time and perceptually + dominant state, Pastukhov & Braun (2011) . + Supports Gamma, log normal, and normal distribution families. + Provides a method to compute history directly and example of using the + computation on a custom Stan code. + date_publication: '2023-09-13' + bug_reports: https://github.com/alexander-pastukhov/bistablehistory/issues/ + url: https://alexander-pastukhov.github.io/bistablehistory/ + url_cran: https://CRAN.R-project.org/package=bistablehistory + url_git: https://github.com/alexander-pastukhov/bistablehistory/ +bit: + version: 4.5.0.1 + title: Classes and Methods for Fast Memory-Efficient Boolean Selections + maintainer: Jens Oehlschlägel + description: |- + Provided are classes for boolean and skewed boolean vectors, + fast boolean methods, fast unique and non-unique integer sorting, + fast set operations on sorted and unsorted sets of integers, and + foundations for ff (range index, compression, chunked processing). + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bit + url_git: https://github.com/truecluster/bit +bit64: + version: 4.6.0-1 + title: A S3 Class for Vectors of 64bit Integers + maintainer: Michael Chirico + description: |- + Package 'bit64' provides serializable S3 atomic 64bit (signed) integers. + These are useful for handling database keys and exact counting in +-2^63. + WARNING: do not use them as replacement for 32bit integers, integer64 are not + supported for subscripting by R-core and they have different semantics when + combined with double, e.g. integer64 + double => integer64. + Class integer64 can be used in vectors, matrices, arrays and data.frames. + Methods are available for coercion from and to logicals, integers, doubles, + characters and factors as well as many elementwise and summary functions. + Many fast algorithmic operations such as 'match' and 'order' support inter- + active data exploration and manipulation and optionally leverage caching. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bit64 + url_git: https://github.com/r-lib/bit64 +bitmexr: + version: 0.3.3 + title: R Client for BitMEX + maintainer: Harry Fisher + description: |- + A client for cryptocurrency exchange BitMEX + including the ability to obtain historic + trade data and place, edit and cancel orders. BitMEX's Testnet and + live API are both supported. + date_publication: '2023-08-07' + bug_reports: https://github.com/hfshr/bitmexr/issues/ + url: https://hfshr.github.io/bitmexr/ + url_cran: https://CRAN.R-project.org/package=bitmexr + url_git: https://github.com/hfshr/bitmexr/ +bitops: + version: 1.0-9 + title: Bitwise Operations + maintainer: Martin Maechler + description: Functions for bitwise operations on integer vectors. + date_publication: '2024-10-03' + bug_reports: https://github.com/mmaechler/R-bitops/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bitops + url_git: https://github.com/mmaechler/R-bitops +BiTrinA: + version: 1.3.1 + title: Binarization and Trinarization of One-Dimensional Data + maintainer: Hans Kestler + description: Provides methods for the binarization and trinarization of one-dimensional + data and some visualization functions. + date_publication: '2023-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BiTrinA + url_git: '' +bitstreamio: + version: 0.1.0 + title: Read and Write Bits from Files, Connections and Raw Vectors + maintainer: Mike Cheng + description: |- + Bit-level reading and writing are necessary when dealing with + many file formats e.g. compressed data and binary files. Currently, R + connections are manipulated at the byte level. This package wraps existing + connections and raw vectors so that it is possible to read bits, bit sequences, + unaligned bytes and low-bit representations of integers. + date_publication: '2025-01-14' + bug_reports: https://github.com/coolbutuseless/bitstreamio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bitstreamio + url_git: https://github.com/coolbutuseless/bitstreamio +bittermelon: + version: 2.1.1 + title: Bitmap Tools + maintainer: Trevor L. Davis + description: Provides functions for creating, modifying, and displaying bitmaps + including printing them in the terminal. There is a special emphasis on monochrome + bitmap fonts and their glyphs as well as colored pixel art/sprites. Provides + native read/write support for the 'hex' and 'yaff' bitmap font formats and if + 'monobit' is installed can also read/write + several additional bitmap font formats. + date_publication: '2025-01-16' + bug_reports: https://github.com/trevorld/bittermelon/issues + url: https://trevorldavis.com/R/bittermelon/ + url_cran: https://CRAN.R-project.org/package=bittermelon + url_git: '' +Bivariate.Pareto: + version: 1.0.3 + title: Bivariate Pareto Models + maintainer: Jia-Han Shih + description: Perform competing risks analysis under bivariate Pareto models. See + Shih et al. (2019) for details. + date_publication: '2019-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bivariate.Pareto + url_git: '' +bivariateLeaflet: + version: 0.1.0 + title: Create Bivariate Choropleth Maps with 'Leaflet' + maintainer: Michael Duprey + description: |- + Creates bivariate choropleth maps using 'Leaflet'. This package provides + tools for visualizing the relationship between two variables through a color + matrix representation on an interactive map. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bivariateLeaflet + url_git: '' +bivariatemaps: + version: '1.7' + title: Creates Bivariate Maps + maintainer: Jose Hidasi-Neto + description: Contains functions mainly focused to plotting bivariate maps. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bivariatemaps + url_git: '' +BivGeo: + version: 2.0.1 + title: Basu-Dhar Bivariate Geometric Distribution + maintainer: Ricardo Puziol de Oliveira + description: Computes the joint probability mass function (pmf), the joint cumulative + function (cdf), the joint survival function (sf), the correlation coefficient, + the covariance, the cross-factorial moment and generate random deviates for the + Basu-Dhar bivariate geometric distribution as well the joint probability mass, + cumulative and survival function assuming the presence of a cure fraction given + by the standard bivariate mixture cure fraction model. The package also computes + the estimators based on the method of moments. + date_publication: '2019-01-03' + bug_reports: '' + url: Formoredetails + url_cran: https://CRAN.R-project.org/package=BivGeo + url_git: '' +bivgeom: + version: '1.0' + title: Roy's Bivariate Geometric Distribution + maintainer: Alessandro Barbiero + description: 'Implements Roy''s bivariate geometric model (Roy (1993) ): + joint probability mass function, distribution function, survival function, random + generation, parameter estimation, and more.' + date_publication: '2018-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bivgeom + url_git: '' +bivpois: + version: '1.1' + title: Bivariate Poisson Distribution + maintainer: Michail Tsagris + description: 'Maximum likelihood estimation, random values generation, density computation + and other functions for the bivariate Poisson distribution. References include: + Kawamura K. (1984). "Direct calculation of maximum likelihood estimator for the + bivariate Poisson distribution". Kodai Mathematical Journal, 7(2): 211--221. . + Kocherlakota S. and Kocherlakota K. (1992). "Bivariate discrete distributions". + CRC Press. . Karlis D. and Ntzoufras I. (2003). "Analysis + of sports data by using bivariate Poisson models". Journal of the Royal Statistical + Society: Series D (The Statistician), 52(3): 381--393. .' + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bivpois + url_git: '' +BivRec: + version: 1.2.1 + title: Bivariate Alternating Recurrent Event Data Analysis + maintainer: Sandra Castro-Pearson + description: |- + A collection of models for bivariate alternating recurrent event data analysis. + Includes non-parametric and semi-parametric methods. + date_publication: '2021-06-05' + bug_reports: https://github.com/SandraCastroPearson/BivRec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BivRec + url_git: https://github.com/SandraCastroPearson/BivRec +BivRegBLS: + version: 1.1.1 + title: |- + Tolerance Interval and EIV Regression - Method Comparison + Studies + maintainer: Bernard G Francq + description: 'Assess the agreement in method comparison studies by tolerance intervals + and errors-in-variables (EIV) regressions. The Ordinary Least Square regressions + (OLSv and OLSh), the Deming Regression (DR), and the (Correlated)-Bivariate Least + Square regressions (BLS and CBLS) can be used with unreplicated or replicated + data. The BLS() and CBLS() are the two main functions to estimate a regression + line, while XY.plot() and MD.plot() are the two main graphical functions to display, + respectively an (X,Y) plot or (M,D) plot with the BLS or CBLS results. Four hyperbolic + statistical intervals are provided: the Confidence Interval (CI), the Confidence + Bands (CB), the Prediction Interval and the Generalized prediction Interval. Assuming + no proportional bias, the (M,D) plot (Band-Altman plot) may be simplified by calculating + univariate tolerance intervals (beta-expectation (type I) or beta-gamma content + (type II)). Major updates from last version 1.0.0 are: title shortened, include + the new functions BLS.fit() and CBLS.fit() as shortcut of the, respectively, functions + BLS() and CBLS(). References: B.G. Francq, B. Govaerts (2016) , + B.G. Francq, B. Govaerts (2014) , B.G. Francq, + B. Govaerts (2014) , + B.G. Francq (2013), PhD Thesis, UCLouvain, Errors-in-variables regressions to + assess equivalence in method comparison studies, .' + date_publication: '2019-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BivRegBLS + url_git: '' +bivrp: + version: 1.2-2 + title: Bivariate Residual Plots with Simulation Polygons + maintainer: Rafael de Andrade Moral + description: Generates bivariate residual plots with simulation polygons for any + diagnostics and bivariate model from which functions to extract the desired diagnostics, + simulate new data and refit the models are available. + date_publication: '2020-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bivrp + url_git: '' +BivUnifBin: + version: 1.3.3 + title: |- + Generation of Bivariate Uniform Data and Its Relation to + Bivariate Binary Data + maintainer: Ran Gao + description: |- + Simulation of bivariate uniform data with a full range of correlations based on + two beta densities and computation of the tetrachoric correlation + (correlation of bivariate uniform data) from the phi coefficient + (correlation of bivariate binary data) and vice versa. + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BivUnifBin + url_git: '' +biwavelet: + version: 0.20.22 + title: Conduct Univariate and Bivariate Wavelet Analyses + maintainer: Tarik Gouhier + description: |- + This is a port of the WTC MATLAB package written by Aslak Grinsted + and the wavelet program written by Christopher Torrence and Gibert P. + Compo. This package can be used to perform univariate and bivariate + (cross-wavelet, wavelet coherence, wavelet clustering) analyses. + date_publication: '2024-08-17' + bug_reports: https://github.com/tgouhier/biwavelet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=biwavelet + url_git: https://github.com/tgouhier/biwavelet +biwt: + version: 1.0.1 + title: |- + Compute the Biweight Mean Vector and Covariance & Correlation + Matrice + maintainer: Jo Hardin + description: |- + Compute multivariate location, scale, and correlation + estimates based on Tukey's biweight M-estimator. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=biwt + url_git: '' +bizdays: + version: 1.0.17 + title: Business Days Calculations and Utilities + maintainer: Wilson Freitas + description: |- + Business days calculations based on a list of holidays and + nonworking weekdays. Quite useful for fixed income and derivatives pricing. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bizdays + url_git: https://github.com/wilsonfreitas/R-bizdays +bizicount: + version: 1.3.3 + title: Bivariate Zero-Inflated Count Models Using Copulas + maintainer: John Niehaus + description: |- + Maximum likelihood estimation of copula-based zero-inflated + (and non-inflated) Poisson and negative binomial count models, based on the + article . Supports Frank and Gaussian copulas. + Allows for mixed margins (e.g., one margin Poisson, the other zero-inflated + negative binomial), and several marginal link functions. Built-in methods for + publication-quality tables using 'texreg', post-estimation diagnostics using + 'DHARMa', and testing for marginal zero-modification via . + For information on copula regression for count data, see Genest and Nešlehová (2007) + as well as Nikoloulopoulos (2013) . + For information on zero-inflated count regression generally, see Lambert (1992) + . The author acknowledges + support by NSF DMS-1925119 and DMS-212324. + date_publication: '2024-05-01' + bug_reports: https://github.com/jmniehaus/bizicount/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bizicount + url_git: https://github.com/jmniehaus/bizicount +bkmr: + version: 0.2.2 + title: Bayesian Kernel Machine Regression + maintainer: Jennifer F. Bobb + description: |- + Implementation of a statistical approach + for estimating the joint health effects of multiple + concurrent exposures, as described in Bobb et al (2015) + . + date_publication: '2022-03-28' + bug_reports: https://github.com/jenfb/bkmr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bkmr + url_git: https://github.com/jenfb/bkmr +bkmrhat: + version: 1.1.3 + title: Parallel Chain Tools for Bayesian Kernel Machine Regression + maintainer: Alexander Keil + description: |- + Bayesian kernel machine regression (from the 'bkmr' package) + is a Bayesian semi-parametric generalized linear model approach under + identity and probit links. There are a number of functions in this + package that extend Bayesian kernel machine regression fits to allow + multiple-chain inference and diagnostics, which leverage functions + from the 'future', 'rstan', and 'coda' packages. Reference: Bobb, J. + F., Henn, B. C., Valeri, L., & Coull, B. A. (2018). Statistical + software for analyzing the health effects of multiple concurrent + exposures via Bayesian kernel machine regression. ; + . + date_publication: '2022-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bkmrhat + url_git: '' +BKT: + version: 0.1.0 + title: Bayesian Knowledge Tracing Model + maintainer: Yuhao Yuan + description: Fitting, cross-validating, and predicting with Bayesian Knowledge Tracing + (BKT) models. It is designed for analyzing educational datasets to trace student + knowledge over time. The package includes functions for fitting BKT models, evaluating + their performance using various metrics, and making predictions on new data. It + provides the similar functionality as the Python package pyBKT authored by Zachary + A. Pardos (zp@berkeley.edu) at . + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BKT + url_git: '' +BKTR: + version: 0.2.0 + title: Bayesian Kernelized Tensor Regression + maintainer: Julien Lanthier + description: |- + Facilitates scalable spatiotemporally varying coefficient + modelling with Bayesian kernelized tensor regression. + The important features of this package are: + (a) Enabling local temporal and spatial modeling of the relationship between + the response variable and covariates. + (b) Implementing the model described by Lei et al. (2023) . + (c) Using a Bayesian Markov Chain Monte Carlo (MCMC) algorithm to sample from the posterior + distribution of the model parameters. + (d) Employing a tensor decomposition to reduce the number of estimated parameters. + (e) Accelerating tensor operations and enabling graphics processing unit (GPU) acceleration + with the 'torch' package. + date_publication: '2024-08-18' + bug_reports: https://github.com/julien-hec/BKTR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BKTR + url_git: '' +BLA: + version: 1.0.1 + title: Boundary Line Analysis + maintainer: Chawezi Miti + description: |- + Fits boundary line models to datasets as proposed by Webb + (1972) and makes statistical + inferences about their parameters. Provides additional tools for + testing datasets for evidence of boundary presence and selecting + initial starting values for model optimization prior to fitting the + boundary line models. It also includes tools for conducting post-hoc + analyses such as predicting boundary values and identifying the most + limiting factor (Miti, Milne, Giller, Lark (2024) + ). This ensures a comprehensive + analysis for datasets that exhibit upper boundary structures. + date_publication: '2024-05-28' + bug_reports: https://github.com/chawezimiti/BLA/issues + url: https://chawezimiti.github.io/BLA/ + url_cran: https://CRAN.R-project.org/package=BLA + url_git: '' +blackbox: + version: 1.1.46 + title: Black Box Optimization and Exploration of Parameter Space + maintainer: François Rousset + description: Performs prediction of a response function from simulated response + values, allowing black-box optimization of functions estimated with some error. + Includes a simple user interface for such applications, as well as more specialized + functions designed to be called by the Migraine software (Rousset and Leblois, + 2012 ; Leblois et al., 2014 ; + and see URL). The latter functions are used for prediction of likelihood surfaces + and implied likelihood ratio confidence intervals, and for exploration of predictor + space of the surface. Prediction of the response is based on ordinary Kriging + (with residual error) of the input. Estimation of smoothing parameters is performed + by generalized cross-validation. + date_publication: '2023-12-08' + bug_reports: '' + url: https://kimura.univ-montp2.fr/~rousset/Migraine.htm + url_cran: https://CRAN.R-project.org/package=blackbox + url_git: '' +blackmarbler: + version: 0.2.4 + title: Black Marble Data and Statistics + maintainer: Robert Marty + description: Geographically referenced data and statistics of nighttime lights from + NASA Black Marble . + date_publication: '2025-01-07' + bug_reports: https://github.com/worldbank/blackmarbler/issues + url: https://worldbank.github.io/blackmarbler/ + url_cran: https://CRAN.R-project.org/package=blackmarbler + url_git: '' +blaise: + version: 1.3.11 + title: Read and Write FWF Files in the 'Blaise' Format + maintainer: Sjoerd Ophof + description: |- + Can be used to read and write a fwf with an accompanying 'Blaise' datamodel. + Blaise is the software suite built by Statistics Netherlands (CBS). It is essentially a + way to write and collect surveys and perform statistical analysis on the data. It stores its data in + fixed width format with an accompanying metadata file, this is the Blaise format. The package automatically + interprets this metadata and reads the file into an R dataframe. + When supplying a datamodel for writing, the dataframe will be automatically converted + to that format and checked for compatibility. + Supports dataframes, tibbles and LaF objects. + For more information about 'Blaise', see . + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blaise + url_git: '' +BlakerCI: + version: 1.0-6 + title: Blaker's Binomial and Poisson Confidence Limits + maintainer: Jan Klaschka + description: Fast and accurate calculation of Blaker's binomial and Poisson confidence + limits (and some related stuff). + date_publication: '2019-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BlakerCI + url_git: '' +BlandAltmanLeh: + version: 0.3.1 + title: Plots (Slightly Extended) Bland-Altman Plots + maintainer: Bernhard Lehnert + description: |- + Bland-Altman Plots using either base graphics or ggplot2, + augmented with confidence intervals, with detailed return values and + a sunflowerplot option for data with ties. + date_publication: '2015-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BlandAltmanLeh + url_git: '' +blandr: + version: 0.6.0 + title: Bland-Altman Method Comparison + maintainer: Deepankar Datta + description: |- + Carries out Bland Altman analyses (also known as a Tukey + mean-difference plot) as described by JM Bland and DG Altman in + 1986 . This package was created in + 2015 as existing Bland-Altman analysis functions did not calculate + confidence intervals. This package was created to rectify this, + and create reproducible plots. This package is also available as a module + for the 'jamovi' statistical spreadsheet (see + for more information). + date_publication: '2024-06-09' + bug_reports: https://github.com/deepankardatta/blandr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blandr + url_git: https://github.com/deepankardatta/blandr/ +blapsr: + version: 0.6.1 + title: Bayesian Inference with Laplace Approximations and P-Splines + maintainer: Oswaldo Gressani + description: |- + Laplace approximations and penalized B-splines are combined + for fast Bayesian inference in latent Gaussian models. The routines can be + used to fit survival models, especially proportional hazards and promotion + time cure models (Gressani, O. and Lambert, P. (2018) + ). The Laplace-P-spline methodology can also + be implemented for inference in (generalized) additive models + (Gressani, O. and Lambert, P. (2021) ). + See the associated website for more information and examples. + date_publication: '2022-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blapsr + url_git: '' +blaster: + version: 1.0.7 + title: Native R Implementation of an Efficient BLAST-Like Algorithm + maintainer: Manu Tamminen + description: |- + Implementation of an efficient BLAST-like sequence + comparison algorithm, written in 'C++11' and using + native R datatypes. Blaster is based on 'nsearch' - + Schmid et al (2018) . + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blaster + url_git: https://github.com/tamminenlab/blaster +blastula: + version: 0.3.5 + title: Easily Send HTML Email Messages + maintainer: Richard Iannone + description: |- + Compose and send out responsive HTML email messages that render + perfectly across a range of email clients and device sizes. Helper functions + let the user insert embedded images, web link buttons, and 'ggplot2' plot + objects into the message body. Messages can be sent through an 'SMTP' + server, through the 'RStudio Connect' service, or through the 'Mailgun' API + service . + date_publication: '2024-02-24' + bug_reports: https://github.com/rstudio/blastula/issues + url: https://pkgs.rstudio.com/blastula/ + url_cran: https://CRAN.R-project.org/package=blastula + url_git: https://github.com/rstudio/blastula +blatent: + version: 0.1.2 + title: Bayesian Latent Variable Models + maintainer: Jonathan Templin + description: Estimation of latent variable models using Bayesian methods. Currently + estimates the loglinear cognitive diagnosis model of Henson, Templin, and Willse + (2009) . + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blatent + url_git: '' +blavaan: + version: 0.5-8 + title: Bayesian Latent Variable Analysis + maintainer: Edgar Merkle + description: |- + Fit a variety of Bayesian latent variable models, including confirmatory + factor analysis, structural equation models, and latent growth curve models. References: Merkle & Rosseel (2018) ; Merkle et al. (2021) . + date_publication: '2025-01-08' + bug_reports: https://github.com/ecmerkle/blavaan/issues + url: https://ecmerkle.github.io/blavaan/ + url_cran: https://CRAN.R-project.org/package=blavaan + url_git: https://github.com/ecmerkle/blavaan +BLCOP: + version: 0.3.3 + title: Black-Litterman and Copula Opinion Pooling Frameworks + maintainer: Joe Russell + description: |- + An implementation of the Black-Litterman Model and Attilio + Meucci's copula opinion pooling framework as described in + Meucci, Attilio (2005) , + Meucci, Attilio (2006) and + Meucci, Attilio (2008) . + date_publication: '2021-01-25' + bug_reports: https://github.com/mangothecat/BLCOP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BLCOP + url_git: https://github.com/mangothecat/BLCOP +Blend: + version: 0.1.1.1 + title: |- + Robust Bayesian Longitudinal Regularized Semiparametric Mixed + Models + maintainer: Kun Fan + description: Our recently developed fully robust Bayesian semiparametric mixed-effect + model for high-dimensional longitudinal studies with heterogeneous observations + can be implemented through this package. This model can distinguish between time-varying + interactions and constant-effect-only cases to avoid model misspecifications. + Facilitated by spike-and-slab priors, this model leads to superior performance + in estimation, identification and statistical inference. In particular, robust + Bayesian inferences in terms of valid Bayesian credible intervals on both parametric + and nonparametric effects can be validated on finite samples. The Markov chain + Monte Carlo algorithms of the proposed and alternative models are efficiently + implemented in 'C++'. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Blend + url_git: https://github.com/kunfa/Blend +blender: + version: 0.1.2 + title: Analyze biotic homogenization of landscapes + maintainer: David J. Harris + description: Tools for assessing exotic species' contributions tolandscape + homogeneity using average pairwise Jaccard similarityand an analytical + approximation derived in Harris et al. (2011,"Occupancy is nine-tenths + of the law," The AmericanNaturalist). Also includes a randomization method + for assessingsources of model error. + date_publication: '2014-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blender + url_git: '' +Blendstat: + version: 1.0.5 + title: Joint Analysis of Experiments with Mixtures and Random Effects + maintainer: Paulo Cesar Ossani + description: Performs a joint analysis of experiments with mixtures and random effects, + taking on a process variable represented by a covariable. + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Blendstat + url_git: '' +blindrecalc: + version: 1.0.1 + title: Blinded Sample Size Recalculation + maintainer: Lukas Baumann + description: |- + Computation of key characteristics and plots for blinded sample size recalculation. + Continuous as well as binary endpoints are supported in superiority and non-inferiority trials. + See Baumann, Pilz, Kieser (2022) for a detailed description. + The implemented methods include the approaches by + Lu, K. (2019) , + Kieser, M. and Friede, T. (2000) , + Friede, T. and Kieser, M. (2004) , + Friede, T., Mitchell, C., Mueller-Veltern, G. (2007) , and + Friede, T. and Kieser, M. (2011) . + date_publication: '2023-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blindrecalc + url_git: https://github.com/imbi-heidelberg/blindrecalc +blindreview: + version: 2.0.0 + title: Enables Blind Review of Database + maintainer: William Fairweather + description: |- + Randomly reassigns the group identifications to one of the variables of the + database, say Treatment, and randomly reassigns the observation numbers of the dataset. + Reorders the observations according to these new numbers. Centers each group of Treatment + at the grand mean in order to further mask the treatment. An unmasking function is + provided so that the user can identify the potential outliers in terms of their original + values when blinding is no longer needed. It is suggested that a forward search procedure + be performed on the masked data. Details of some forward search functions may be found in + . + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blindreview + url_git: '' +blink: + version: 1.1.0 + title: Record Linkage for Empirically Motivated Priors + maintainer: Rebecca Steorts + description: 'An implementation of the model in Steorts (2015) , + which performs Bayesian entity resolution for categorical and text data, for any + distance function defined by the user. In addition, the precision and recall are + in the package to allow one to compare to any other comparable method such as + logistic regression, Bayesian additive regression trees (BART), or random forests. + The experiments are reproducible and illustrated using a simple vignette. LICENSE: + GPL-3 + file license.' + date_publication: '2020-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blink + url_git: '' +bliss: + version: 1.1.1 + title: Bayesian Functional Linear Regression with Sparse Step Functions + maintainer: Paul-Marie Grollemund + description: |- + A method for the Bayesian functional linear regression model (scalar-on-function), + including two estimators of the coefficient function and an estimator of its support. + A representation of the posterior distribution is also available. Grollemund P-M., Abraham C., + Baragatti M., Pudlo P. (2019) . + date_publication: '2024-07-17' + bug_reports: https://github.com/pmgrollemund/bliss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bliss + url_git: https://github.com/pmgrollemund/bliss +blit: + version: 0.1.0 + title: Bioinformatics Library for Integrated Tools + maintainer: Yun Peng + description: |- + An all-encompassing R toolkit designed to streamline the + process of calling various bioinformatics software and then performing data + analysis and visualization in R. With 'blit', users can easily integrate a + wide array of bioinformatics command line tools into their workflows, + leveraging the power of R for sophisticated data manipulation and graphical + representation. + date_publication: '2025-02-27' + bug_reports: https://github.com/WangLabCSU/blit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blit + url_git: https://github.com/WangLabCSU/blit +blm: + version: 2022.0.0.1 + title: Binomial Linear Regression + maintainer: S.Kovalchik + description: Implements regression models for binary data on the absolute risk scale. + These models are applicable to cohort and population-based case-control data. + date_publication: '2022-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blm + url_git: '' +blme: + version: 1.0-6 + title: Bayesian Linear Mixed-Effects Models + maintainer: Vincent Dorie + description: Maximum a posteriori estimation for linear and generalized linear mixed-effects + models in a Bayesian setting, implementing the methods of Chung, et al. (2013) + . Extends package 'lme4' (Bates, Maechler, Bolker, + and Walker (2015) ). + date_publication: '2024-09-07' + bug_reports: https://github.com/vdorie/blme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blme + url_git: https://github.com/vdorie/blme +blmeco: + version: '1.4' + title: |- + Data Files and Functions Accompanying the Book "Bayesian Data + Analysis in Ecology using R, BUGS and Stan" + maintainer: Fraenzi Korner-Nievergelt + description: Data files and functions accompanying the book Korner-Nievergelt, Roth, + von Felten, Guelat, Almasi, Korner-Nievergelt (2015) "Bayesian Data Analysis in + Ecology using R, BUGS and Stan", Elsevier, New York. + date_publication: '2019-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blmeco + url_git: '' +BLModel: + version: 1.0.2 + title: Black-Litterman Posterior Distribution + maintainer: Andrzej Palczewski + description: Posterior distribution in the Black-Litterman model is computed from + a prior distribution given in the form of a time series of asset returns and a + continuous distribution of views provided by the user as an external function. + date_publication: '2017-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLModel + url_git: '' +blob: + version: 1.2.4 + title: |- + A Simple S3 Class for Representing Vectors of Binary Data + ('BLOBS') + maintainer: Kirill Müller + description: |- + R's raw vector is useful for storing a single binary object. + What if you want to put a vector of them in a data frame? The 'blob' + package provides the blob object, a list of raw vectors, suitable for + use as a column in data frame. + date_publication: '2023-03-17' + bug_reports: https://github.com/tidyverse/blob/issues + url: https://blob.tidyverse.org + url_cran: https://CRAN.R-project.org/package=blob + url_git: https://github.com/tidyverse/blob +blockcluster: + version: 4.5.5 + title: |- + Co-Clustering Package for Binary, Categorical, Contingency and + Continuous Data-Sets + maintainer: Serge Iovleff + description: |- + Simultaneous clustering of rows and columns, usually designated by + biclustering, co-clustering or block clustering, is an important technique + in two way data analysis. It consists of estimating a mixture model which + takes into account the block clustering problem on both the individual and + variables sets. The 'blockcluster' package provides a bridge between the C++ + core library build on top of the 'STK++' library, and the R statistical + computing environment. This package allows to co-cluster binary + , contingency , + continuous and categorical data-sets + . It also provides utility functions to + visualize the results. This package may be useful for various applications + in fields of Data mining, Information retrieval, Biology, computer vision + and many more. More information about the project and comprehensive tutorial + can be found on the link mentioned in URL. + date_publication: '2024-02-23' + bug_reports: '' + url: https://gitlab.inria.fr/iovleff/blockcluster + url_cran: https://CRAN.R-project.org/package=blockcluster + url_git: '' +BlockCov: + version: 0.1.1 + title: Estimation of Large Block Covariance Matrices + maintainer: Marie Perrot-Dockès + description: |- + Computation of large covariance matrices having a block structure up to a permutation of their columns and rows + from a small number of samples with respect to the dimension of the matrix. + The method is described in the paper Perrot-Dockès et al. (2019) . + date_publication: '2019-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BlockCov + url_git: '' +blockCV: + version: 3.1-5 + title: |- + Spatial and Environmental Blocking for K-Fold and LOO + Cross-Validation + maintainer: Roozbeh Valavi + description: Creating spatially or environmentally separated folds for cross-validation + to provide a robust error estimation in spatially structured environments; Investigating + and visualising the effective range of spatial autocorrelation in continuous raster + covariates and point samples to find an initial realistic distance band to separate + training and testing datasets spatially described in Valavi, R. et al. (2019) + . + date_publication: '2024-11-01' + bug_reports: https://github.com/rvalavi/blockCV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blockCV + url_git: https://github.com/rvalavi/blockCV +blockForest: + version: 0.2.6 + title: |- + Block Forests: Random Forests for Blocks of Clinical and Omics + Covariate Data + maintainer: Marvin N. Wright + description: |- + A random forest variant 'block forest' ('BlockForest') tailored to the + prediction of binary, survival and continuous outcomes using block-structured + covariate data, for example, clinical covariates plus measurements of a certain + omics data type or multi-omics data, that is, data for which measurements of + different types of omics data and/or clinical data for each patient exist. Examples + of different omics data types include gene expression measurements, mutation data + and copy number variation measurements. + Block forest are presented in Hornung & Wright (2019). The package includes four + other random forest variants for multi-omics data: 'RandomBlock', 'BlockVarSel', + 'VarProb', and 'SplitWeights'. These were also considered in Hornung & Wright (2019), + but performed worse than block forest in their comparison study based on 20 real + multi-omics data sets. Therefore, we recommend to use block forest ('BlockForest') + in applications. The other random forest variants can, however, be consulted for + academic purposes, for example, in the context of further methodological + developments. + Reference: Hornung, R. & Wright, M. N. (2019) Block Forests: random forests for blocks of clinical and omics covariate data. BMC Bioinformatics 20:358. . + date_publication: '2023-03-31' + bug_reports: https://github.com/bips-hb/blockForest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blockForest + url_git: https://github.com/bips-hb/blockForest +blocklength: + version: 0.2.0 + title: |- + Select an Optimal Block-Length to Bootstrap Dependent Data + (Block Bootstrap) + maintainer: Alec Stashevsky + description: |- + A set of functions to select the optimal block-length for a + dependent bootstrap (block-bootstrap). Includes the Hall, Horowitz, and Jing + (1995) subsampling-based cross-validation method, the + Politis and White (2004) Spectral Density + Plug-in method, including the Patton, Politis, and White (2009) + correction, and the Lahiri, Furukawa, and Lee + (2007) nonparametric plug-in method, with + a corresponding set of S3 plot methods. + date_publication: '2025-02-17' + bug_reports: https://github.com/Alec-Stashevsky/blocklength/issues + url: https://alecstashevsky.com/r/blocklength + url_cran: https://CRAN.R-project.org/package=blocklength + url_git: https://github.com/Alec-Stashevsky/blocklength +blockmatrix: + version: '1.0' + title: 'blockmatrix: Tools to solve algebraic systems with partitionedmatrices' + maintainer: Emanuele Cordano + description: Some elementary matrix algebra tools are implemented to manageblock + matrices or partitioned matrix, i.e. "matrix of matrices"(http://en.wikipedia.org/wiki/Block_matrix). + The block matrix is heredefined as a new S3 object. In this package, some + methods for "matrix"object are rewritten for "blockmatrix" object. New + methods are implemented.This package was created to solve equation systems + with block matrices forthe analysis of environmental vector time series + .Bugs/comments/questions/collaboration of any kind are warmly welcomed. + date_publication: '2014-01-19' + bug_reports: '' + url: http://cri.gmpf.eu/Research/Sustainable-Agro-Ecosystems-and-Bioresources/Dynamics-in-the-agro-ecosystems/people/Emanuele-Cordano + url_cran: https://CRAN.R-project.org/package=blockmatrix + url_git: '' +BlockMissingData: + version: 0.1.0 + title: |- + Integrating Multi-Source Block-Wise Missing Data in Model + Selection + maintainer: Fei Xue + description: Model selection method with multiple block-wise imputation for block-wise + missing data; see Xue, F., and Qu, A. (2021) . + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BlockMissingData + url_git: '' +blockmodeling: + version: 1.1.5 + title: Generalized and Classical Blockmodeling of Valued Networks + maintainer: Aleš Žiberna + description: |- + This is primarily meant as an implementation of generalized blockmodeling for valued networks. + In addition, measures of similarity or dissimilarity based on structural equivalence and + regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: + Žiberna (2007), Žiberna (2008), + Žiberna (2014). + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blockmodeling + url_git: '' +BlockmodelingGUI: + version: 1.8.4 + title: GUI for the Generalised Blockmodeling of Valued Networks + maintainer: Fabio Ashtar Telarico + description: This app provides some useful tools for Offering an accessible GUI + for generalised blockmodeling of single-relation, one-mode networks. The user + can execute blockmodeling without having to write a line code by using the app's + visual helps. Moreover, there are several ways to visualisations networks and + their partitions. Finally, the results can be exported as if they were produced + by writing code. The development of this package is financially supported by the + Slovenian Research Agency (www.arrs.gov.si) within the research project J5-2557 + (Comparison and evaluation of different approaches to blockmodeling dynamic networks + by simulations with application to Slovenian co-authorship networks). + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BlockmodelingGUI + url_git: '' +blockmodels: + version: 1.1.5 + title: |- + Latent and Stochastic Block Model Estimation by a 'V-EM' + Algorithm + maintainer: Jean-Benoist Leger + description: |- + Latent and Stochastic Block Model estimation by a Variational EM algorithm. + Various probability distribution are provided (Bernoulli, + Poisson...), with or without covariates. + date_publication: '2021-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blockmodels + url_git: '' +blockrand: + version: '1.5' + title: Randomization for Block Random Clinical Trials + maintainer: Greg Snow + description: Create randomizations for block random clinical trials. Can also produce + a pdf file of randomization cards. + date_publication: '2020-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blockrand + url_git: '' +blocksdesign: + version: '4.9' + title: |- + Nested and Crossed Block Designs for Factorial and Unstructured + Treatment Sets + maintainer: Rodney Edmondson + description: |- + Constructs treatment and block designs for linear treatment models + with crossed or nested block factors. The treatment design can be any feasible + linear model and the block design can be any feasible combination of crossed or + nested block factors. The block design is a sum of one or more block factors + and the block design is optimized sequentially with the levels of each successive + block factor optimized conditional on all previously optimized block factors. + D-optimality is used throughout except for square or rectangular lattice block designs + which are constructed algebraically using mutually orthogonal Latin squares. + Crossed block designs with interaction effects are optimized using a weighting scheme + which allows for differential weighting of first and second-order block effects. + Outputs include a table showing the allocation of treatments to blocks and tables showing + the achieved D-efficiency factors for each block and treatment design. + Edmondson, R.N. Multi-level Block Designs for Comparative Experiments. + JABES 25, 500–522 (2020) . + date_publication: '2021-04-07' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=blocksdesign + url_git: '' +blockTools: + version: 0.6.6 + title: |- + Block, Assign, and Diagnose Potential Interference in Randomized + Experiments + maintainer: Ryan T. Moore + description: Blocks units into experimental blocks, with one unit per treatment + condition, by creating a measure of multivariate distance between all possible + pairs of units. Maximum, minimum, or an allowable range of differences between + units on one variable can be set. Randomly assign units to treatment conditions. + Diagnose potential interference between units assigned to different treatment + conditions. Write outputs to .tex and .csv files. For more information on the + methods implemented, see Moore (2012) . + date_publication: '2025-01-22' + bug_reports: '' + url: https://www.ryantmoore.org/html/software.blockTools.html + url_cran: https://CRAN.R-project.org/package=blockTools + url_git: '' +blocs: + version: 0.1.1 + title: Estimate and Visualize Voting Blocs' Partisan Contributions + maintainer: Cole Tanigawa-Lau + description: |- + Functions to combine data on voting blocs' + size, turnout, and vote choice to estimate each bloc's + vote contributions to the Democratic and Republican parties. + The package also includes functions for uncertainty estimation and + plotting. Users may define voting blocs along a discrete or continuous variable. + The package implements methods described in Grimmer, Marble, and Tanigawa-Lau (2023) . + date_publication: '2023-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blocs + url_git: '' +blogdown: + version: '1.20' + title: Create Blogs and Websites with R Markdown + maintainer: Yihui Xie + description: |- + Write blog posts and web pages in R Markdown. This package + supports the static site generator 'Hugo' () best, + and it also supports 'Jekyll' () and 'Hexo' + (). + date_publication: '2025-01-07' + bug_reports: https://github.com/rstudio/blogdown/issues + url: https://pkgs.rstudio.com/blogdown/ + url_cran: https://CRAN.R-project.org/package=blogdown + url_git: https://github.com/rstudio/blogdown +BLOQ: + version: 0.1-1 + title: Impute and Analyze Data with BLOQ Observations + maintainer: Vahid Nassiri + description: |- + It includes estimating the area under the concentrations + versus time curve (AUC) and its standard error for data with + Below the Limit of Quantification (BLOQ) observations. Two + approaches are implemented: direct estimation using censored maximum + likelihood, also by first imputing the BLOQ's + using various methods, then compute AUC and its standard + error using imputed data. Technical details can found in + Barnett, Helen Yvette, Helena Geys, Tom Jacobs, and Thomas Jaki. + "Methods for Non-Compartmental Pharmacokinetic Analysis With Observations + Below the Limit of Quantification." Statistics in Biopharmaceutical + Research (2020): 1-12. + (available online: + ). + date_publication: '2020-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLOQ + url_git: '' +blorr: + version: 0.3.1 + title: Tools for Developing Binary Logistic Regression Models + maintainer: Aravind Hebbali + description: |- + Tools designed to make it easier for beginner and intermediate users to build and validate + binary logistic regression models. Includes bivariate analysis, comprehensive regression output, + model fit statistics, variable selection procedures, model validation techniques and a 'shiny' + app for interactive model building. + date_publication: '2024-11-11' + bug_reports: https://github.com/rsquaredacademy/blorr/issues + url: https://blorr.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=blorr + url_git: https://github.com/rsquaredacademy/blorr +BLPestimatoR: + version: 0.3.4 + title: Performs a BLP Demand Estimation + maintainer: Daniel Brunner + description: Provides the estimation algorithm to perform the demand estimation + described in Berry, Levinsohn and Pakes (1995) . The routine + uses analytic gradients and offers a large number of implemented integration methods + and optimization routines. + date_publication: '2022-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLPestimatoR + url_git: '' +BLR: + version: '1.6' + title: Bayesian Linear Regression + maintainer: Paulino Perez Rodriguez + description: Bayesian Linear Regression. + date_publication: '2020-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLR + url_git: '' +blrm: + version: 1.0-2 + title: |- + Dose Escalation Design in Phase I Oncology Trial Using Bayesian + Logistic Regression Modeling + maintainer: Furong Sun + description: Design dose escalation using Bayesian logistic regression modeling + in Phase I oncology trial. + date_publication: '2022-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blrm + url_git: '' +BLRPM: + version: '1.0' + title: |- + Stochastic Rainfall Generator Bartlett-Lewis Rectangular Pulse + Model + maintainer: Christoph Ritschel + description: Due to a limited availability of observed high-resolution precipitation + records with adequate length, simulations with stochastic precipitation models + are used to generate series for subsequent studies [e.g. Khaliq and Cunmae, 1996, + , Vandenberghe et al., 2011, ]. + This package contains an R implementation of the original Bartlett-Lewis rectangular + pulse model (BLRPM), developed by Rodriguez-Iturbe et al. (1987) . + It contains a function for simulating a precipitation time series based on storms + and cells generated by the model with given or estimated model parameters. Additionally + BLRPM parameters can be estimated from a given or simulated precipitation time + series. The model simulations can be plotted in a three-layer plot including an + overview of generated storms and cells by the model (which can also be plotted + individually), a continuous step-function and a discrete precipitation time series + at a chosen aggregation level. + date_publication: '2017-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLRPM + url_git: '' +BLRShiny: + version: 0.1.0 + title: |- + Interactive Document for Working with Binary Logistic Regression + Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of binary logistic regression analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLRShiny + url_git: '' +BLRShiny2: + version: 0.1.0 + title: |- + Interactive Document for Working with Binary Logistic Regression + Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of binary logistic regression analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2020-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLRShiny2 + url_git: '' +blsBandit: + version: '0.1' + title: Data Viewer for Bureau of Labor Statistics Data + maintainer: Jeremy Fitzpatrick + description: Allows users to easily visualize data from the BLS (United States of + America Bureau of Labor Statistics) . Currently unemployment + data series U1-U6 are available. Not affiliated with the Bureau of Labor Statistics + or United States Government. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=blsBandit + url_git: '' +blscrapeR: + version: 4.0.1 + title: An API Wrapper for the United States Bureau of Labor Statistics + maintainer: Kris Eberwein + description: Scrapes various data from . The Bureau of Labor + Statistics is the statistical branch of the United States Department of Labor. + The package has additional functions to help parse, analyze and visualize the + data. + date_publication: '2024-03-17' + bug_reports: https://github.com/keberwein/blscrapeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blscrapeR + url_git: https://github.com/keberwein/blscrapeR +BLSM: + version: 0.1.0 + title: Bayesian Latent Space Model + maintainer: Alberto Donizetti + description: |- + Provides a Bayesian latent space + model for complex networks, either weighted or unweighted. + Given an observed input graph, the estimates for the latent coordinates + of the nodes are obtained through a Bayesian MCMC algorithm. + The overall likelihood of the graph depends on a fundamental probability + equation, which is defined so that ties are more likely to exist + between nodes whose latent space coordinates are close. + The package is mainly based on the model by Hoff, Raftery and Handcock (2002) + and contains some extra features + (e.g., removal of the Procrustean step, weights implemented as + coefficients of the latent distances, 3D plots). + The original code related to the above model was retrieved from + . + Users can inspect the MCMC simulation, create and customize insightful + graphical representations or apply clustering techniques. + date_publication: '2018-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BLSM + url_git: '' +blsR: + version: 0.5.0 + title: Make Requests from the Bureau of Labor Statistics API + maintainer: Guillermo Roditi Dominguez + description: |- + Implements v2 of the B.L.S. API for requests of survey information + and time series data through 3-tiered API that allows users to interact with + the raw API directly, create queries through a functional interface, and + re-shape the data structures returned to fit common uses. The API definition + is located at: . + date_publication: '2023-07-05' + bug_reports: https://github.com/groditi/blsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=blsR + url_git: https://github.com/groditi/blsR +bltm: + version: 0.1.0 + title: Bayesian Latent Threshold Modeling + maintainer: Julio Trecenti + description: |- + Fits latent threshold model for simulated data + and describes how to adjust model using real data. Implements algorithm + proposed by Nakajima and West (2013) . + This package has a function to generate data, a function to configure + priors and a function to fit the model. Examples may be checked inside + the demonstration files. + date_publication: '2019-07-18' + bug_reports: https://github.com/curso-r/bltm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bltm + url_git: https://github.com/curso-r/bltm +bluebike: + version: 0.0.3 + title: Blue Bike Comprehensive Data + maintainer: Ziyue Yang + description: |- + Facilitates the importation of the Boston Blue Bike trip data + since 2015. Functions include the computation of trip distances of + given trip data. It can also map the location of stations within a + given radius and calculate the distance to nearby stations. Data is + from . + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bluebike + url_git: '' +BlueCarbon: + version: 0.1.0 + title: |- + Estimation of Organic Carbon Stocks and Sequestration Rates from + Soil Core Data + maintainer: Nerea Piñeiro-Juncal + description: |- + Tools to estimate soil organic carbon stocks and sequestration rates + in blue carbon ecosystems. 'BlueCarbon' contains functions to estimate and correct + for core compaction, estimate sample thickness, estimate organic carbon content + from organic matter content, estimate organic carbon stocks and + sequestration rates, and visualize the error of carbon stock extrapolation. + date_publication: '2025-02-21' + bug_reports: https://github.com/EcologyR/BlueCarbon/issues + url: https://ecologyr.github.io/BlueCarbon/ + url_cran: https://CRAN.R-project.org/package=BlueCarbon + url_git: https://github.com/EcologyR/BlueCarbon +BlythStillCasellaCI: + version: 1.1.0 + title: Blyth-Still-Casella Exact Binomial Confidence Intervals + maintainer: Ron Yu + description: Computes Blyth-Still-Casella exact binomial confidence intervals based + on a refining procedure proposed by George Casella (1986) . + date_publication: '2024-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BlythStillCasellaCI + url_git: '' +BMA: + version: 3.18.20 + title: Bayesian Model Averaging + maintainer: Hana Sevcikova + description: |- + Package for Bayesian model averaging and variable selection for linear models, + generalized linear models and survival models (cox + regression). + date_publication: '2025-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BMA + url_git: https://github.com/hanase/BMA +bmabasket: + version: 0.1.2 + title: Bayesian Model Averaging for Basket Trials + maintainer: Matt Psioda + description: |- + An implementation of the Bayesian model averaging method + of Psioda and others (2019) for basket trials. + Contains a user-friendly wrapper for simulating basket trials under conditions + and analyzing them with a Bayesian model averaging approach. + date_publication: '2022-02-24' + bug_reports: https://github.com/ethan-alt/bmabasket/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bmabasket + url_git: https://github.com/ethan-alt/bmabasket +BMAmevt: + version: 1.0.5 + title: |- + Multivariate Extremes: Bayesian Estimation of the Spectral + Measure + maintainer: Leo Belzile + description: Toolkit for Bayesian estimation of the dependence structure in multivariate + extreme value parametric models, following Sabourin and Naveau (2014) + and Sabourin, Naveau and Fougeres (2013) . + date_publication: '2023-04-21' + bug_reports: https://github.com/lbelzile/BMAmevt/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=BMAmevt + url_git: '' +bmass: + version: 1.0.3 + title: Bayesian Multivariate Analysis of Summary Statistics + maintainer: Michael Turchin + description: |- + Multivariate tool for analyzing genome-wide association + study results in the form of univariate summary statistics. The + goal of 'bmass' is to comprehensively test all possible multivariate + models given the phenotypes and datasets provided. Multivariate + models are determined by assigning each phenotype to being either + Unassociated (U), Directly associated (D) or Indirectly associated + (I) with the genetic variant of interest. Test results for each model + are presented in the form of Bayes factors, thereby allowing direct + comparisons between models. The underlying framework implemented + here is based on the modeling developed in "A Unified Framework + for Association Analysis with Multiple Related Phenotypes", + M. Stephens (2013) . + date_publication: '2019-05-17' + bug_reports: https://github.com/mturchin20/bmass/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bmass + url_git: https://github.com/mturchin20/bmass +BMconcor: + version: 2.0.0 + title: CONCOR for Structural- And Regular-Equivalence Blockmodeling + maintainer: Fabio Ashtar Telarico + description: 'The four functions svdcp() (''cp'' for column partitioned), svdbip() + or svdbip2() (''bip'' for bipartitioned), and svdbips() (''s'' for a simultaneous + optimization of a set of ''r'' solutions), correspond to a singular value decomposition + (SVD) by blocks notion, by supposing each block depending on relative subspaces, + rather than on two whole spaces as usual SVD does. The other functions, based + on this notion, are relative to two column partitioned data matrices x and y defining + two sets of subsets x_i and y_j of variables and amount to estimate a link between + x_i and y_j for the pair (x_i, y_j) relatively to the links associated to all + the other pairs. These methods were first presented in: Lafosse R. & Hanafi M.,(1997) + and Hanafi M. & Lafosse, R. (2001) .' + date_publication: '2024-05-02' + bug_reports: '' + url: https://fatelarico.github.io/BMconcor/ + url_cran: https://CRAN.R-project.org/package=BMconcor + url_git: '' +bmem: + version: '2.1' + title: Mediation Analysis with Missing Data Using Bootstrap + maintainer: Zhiyong Zhang + description: 'Four methods for mediation analysis with missing data: Listwise deletion, + Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. + For MI and TS-ML, auxiliary variables can be included. Bootstrap confidence intervals + for mediation effects are obtained. The robust method is also implemented for + TS-ML. Since version 1.4, bmem adds the capability to conduct power analysis for + mediation models. Details about the methods used can be found in these articles. + Zhang and Wang (2003) . Zhang (2014) .' + date_publication: '2023-08-27' + bug_reports: '' + url: https://bigdatalab.nd.edu + url_cran: https://CRAN.R-project.org/package=bmem + url_git: '' +bmemLavaan: + version: '0.5' + title: Mediation Analysis with Missing Data and Non-Normal Data + maintainer: Zhiyong Zhang + description: 'Methods for mediation analysis with missing data and non-normal data + are implemented. For missing data, four methods are available: Listwise deletion, + Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. + For MI and TS-ML, auxiliary variables can be included to handle missing data. + For handling non-normal data, bootstrap and two-stage robust methods can be used. + Technical details of the methods can be found in Zhang and Wang (2013, ), + Zhang (2014, ), and Yuan and Zhang (2012, ).' + date_publication: '2022-05-28' + bug_reports: '' + url: https://bigdatalab.nd.edu + url_cran: https://CRAN.R-project.org/package=bmemLavaan + url_git: '' +bmet: + version: 0.1.0 + title: Bayesian Multigroup Equivalence Testing + maintainer: Tony Pourmohamad + description: |- + Calculates the necessary quantities to perform Bayesian multigroup equivalence testing. + Currently the package includes the Bayesian models and equivalence criteria outlined in Pourmohamad and Lee (2023) + , but more models and equivalence testing features may be added over time. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bmet + url_git: '' +bmgarch: + version: 2.0.0 + title: Bayesian Multivariate GARCH Models + maintainer: Philippe Rast + description: Fit Bayesian multivariate GARCH models using 'Stan' for full Bayesian + inference. Generate (weighted) forecasts for means, variances (volatility) and + correlations. Currently DCC(P,Q), CCC(P,Q), pdBEKK(P,Q), and BEKK(P,Q) parameterizations + are implemented, based either on a multivariate gaussian normal or student-t distribution. + DCC and CCC models are based on Engle (2002) + and Bollerslev (1990). The BEKK parameterization follows Engle and Kroner (1995) + while the pdBEKK as well as the estimation approach + for this package is described in Rast et al. (2020) . + The fitted models contain 'rstan' objects and can be examined with 'rstan' functions. + date_publication: '2023-09-12' + bug_reports: https://github.com/ph-rast/bmgarch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bmgarch + url_git: '' +bmggum: + version: 0.1.0 + title: Bayesian Multidimensional Generalized Graded Unfolding Model + maintainer: Naidan Tu + description: |- + Full Bayesian estimation of Multidimensional Generalized Graded Unfolding Model (MGGUM) using 'rstan' (See Stan Development Team (2020) ). + Functions are provided for estimation, result extraction, model fit statistics, and plottings. + date_publication: '2021-04-09' + bug_reports: https://github.com/Naidantu/bmggum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bmggum + url_git: https://github.com/Naidantu/bmggum +BMisc: + version: 1.4.8 + title: |- + Miscellaneous Functions for Panel Data, Quantiles, and Printing + Results + maintainer: Brantly Callaway + description: These are miscellaneous functions for working with panel data, quantiles, + and printing results. For panel data, the package includes functions for making + a panel data balanced (that is, dropping missing individuals that have missing + observations in any time period), converting id numbers to row numbers, and to + treat repeated cross sections as panel data under the assumption of rank invariance. For + quantiles, there are functions to make distribution functions from a set of data + points (this is particularly useful when a distribution function is created in + several steps), to combine distribution functions based on some external weights, + and to invert distribution functions. Finally, there are several other miscellaneous + functions for obtaining weighted means, weighted distribution functions, and weighted + quantiles; to generate summary statistics and their differences for two groups; + and to add or drop covariates from formulas. + date_publication: '2025-02-04' + bug_reports: https://github.com/bcallaway11/BMisc/issues + url: https://bcallaway11.github.io/BMisc/ + url_cran: https://CRAN.R-project.org/package=BMisc + url_git: '' +bmixture: + version: '1.7' + title: Bayesian Estimation for Finite Mixture of Distributions + maintainer: Reza Mohammadi + description: Provides statistical tools for Bayesian estimation of mixture distributions, + mainly a mixture of Gamma, Normal, and t-distributions. The package is implemented + based on the Bayesian literature for the finite mixture of distributions, including + Mohammadi and et al. (2013) and Mohammadi and + Salehi-Rad (2012) . + date_publication: '2021-05-11' + bug_reports: '' + url: https://www.uva.nl/profile/a.mohammadi + url_cran: https://CRAN.R-project.org/package=bmixture + url_git: '' +bmlm: + version: 1.3.15 + title: Bayesian Multilevel Mediation + maintainer: Matti Vuorre + description: Easy estimation of Bayesian multilevel mediation models with Stan. + date_publication: '2023-09-25' + bug_reports: https://github.com/mvuorre/bmlm/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=bmlm + url_git: https://github.com/mvuorre/bmlm/ +bmm: + version: 1.0.1 + title: Easy and Accessible Bayesian Measurement Models Using 'brms' + maintainer: Vencislav Popov + description: |- + Fit computational and measurement models using full Bayesian + inference. The package provides a simple and accessible interface by + translating complex domain-specific models into 'brms' syntax, a + powerful and flexible framework for fitting Bayesian regression models + using 'Stan'. The package is designed so that users can easily apply + state-of-the-art models in various research fields, and so that + researchers can use it as a new model development framework. + References: Frischkorn and Popov (2023) . + date_publication: '2024-05-27' + bug_reports: https://github.com/venpopov/bmm/issues + url: https://venpopov.github.io/bmm/ + url_cran: https://CRAN.R-project.org/package=bmm + url_git: https://github.com/venpopov/bmm +bmp: + version: '0.3' + title: Read Windows Bitmap (BMP) Images + maintainer: Gregory Jefferis + description: |- + Reads Windows BMP format images. Currently limited to 8 bit + greyscale images and 24,32 bit (A)RGB images. Pure R implementation without + external dependencies. + date_publication: '2017-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bmp + url_git: '' +BMRBr: + version: 0.2.0 + title: '''BMRB'' File Downloader' + maintainer: Xi Chen + description: |- + Nuclear magnetic resonance (NMR) is a highly versatile analytical technique for studying molecular configuration, conformation, + and dynamics, especially those of biomacromolecules such as proteins. Biological Magnetic Resonance Data Bank ('BMRB') is a repository + for Data from NMR Spectroscopy on Proteins, Peptides, Nucleic Acids, and other Biomolecules. Currently, 'BMRB' offers an R package + 'RBMRB' to fetch data, however, it doesn't easily offer individual data file downloading and storing in a local directory. When using + 'RBMRB', the data will stored as an R object, which fundamentally hinders the NMR researches to access the rich information from raw + data, for example, the metadata. Here, 'BMRBr' File Downloader ('BMRBr') offers a more fundamental, low level downloader, which will + download original deposited .str format file. This type of file contains information such as entry title, authors, citation, protein + sequences, and so on. + Many factors affect NMR experiment outputs, such as temperature, resonance sensitivity and etc., approximately 40% of the entries in the 'BMRB' have + chemical shift accuracy problems [1,2] Unfortunately, current reference correction methods are heavily dependent on the availability of + assigned protein chemical shifts or protein structure. This is my current research project is going to solve, which will be included + in the future release of the package. The current version of the package is sufficient and robust enough for downloading individual + 'BMRB' data file from the 'BMRB' database . The functionalities of this package includes but not limited: + * To simplifies NMR researches by combine data downloading and results analysis together. + * To allows NMR data reaches a broader audience that could utilize more than just chemical shifts but also metadata. + * To offer reference corrected data for entries without assignment or structure information (future release). + Reference: + [1] E.L. Ulrich, H. Akutsu, J.F. Doreleijers, Y. Harano, Y.E. Ioannidis, J. Lin, et al., BioMagResBank, Nucl. Acids Res. 36 (2008) D402–8. . + [2] L. Wang, H.R. Eghbalnia, A. Bahrami, J.L. Markley, Linear analysis of carbon-13 chemical shift differences and its application to the detection and correction of errors in referencing and spin system identifications, J. Biomol. NMR. 32 (2005) 13–22. . + date_publication: '2018-08-24' + bug_reports: https://github.com/billchenxi/BMRBr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BMRBr + url_git: https://github.com/billchenxi/BMRBr +BMRMM: + version: 1.0.1 + title: An Implementation of the Bayesian Markov (Renewal) Mixed Models + maintainer: Yutong Wu + description: 'The Bayesian Markov renewal mixed models take sequentially observed + categorical data with continuous duration times, being either state duration or + inter-state duration. These models comprehensively analyze the stochastic dynamics + of both state transitions and duration times under the influence of multiple exogenous + factors and random individual effect. The default setting flexibly models the + transition probabilities using Dirichlet mixtures and the duration times using + gamma mixtures. It also provides the flexibility of modeling the categorical sequences + using Bayesian Markov mixed models alone, either ignoring the duration times altogether + or dividing duration time into multiples of an additional category in the sequence + by a user-specific unit. The package allows extensive inference of the state transition + probabilities and the duration times as well as relevant plots and graphs. It + also includes a synthetic data set to demonstrate the desired format of input + data set and the utility of various functions. Methods for Bayesian Markov renewal + mixed models are as described in: Abhra Sarkar et al., (2018) + and Yutong Wu et al., (2022) .' + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BMRMM + url_git: '' +BMS: + version: 0.3.5 + title: Bayesian Model Averaging Library + maintainer: Stefan Zeugner + description: Bayesian Model Averaging for linear models with a wide choice of (customizable) + priors. Built-in priors include coefficient priors (fixed, hyper-g and empirical + priors), 5 kinds of model priors, moreover model sampling by enumeration or various + MCMC approaches. Post-processing functions allow for inferring posterior inclusion + and model probabilities, various moments, coefficient and predictive densities. + Plotting functions available for posterior model size, MCMC convergence, predictive + and coefficient densities, best models representation, BMA comparison. Also includes + Bayesian normal-conjugate linear model with Zellner's g prior, and assorted methods. + date_publication: '2022-08-09' + bug_reports: '' + url: http://bms.zeugner.eu + url_cran: https://CRAN.R-project.org/package=BMS + url_git: '' +bmscstan: + version: 1.2.1.0 + title: Bayesian Multilevel Single Case Models using 'Stan' + maintainer: Michele Scandola + description: |- + Analyse single case analyses against a control group. + Its purpose is to provide a flexible, with good power and + low first type error + approach that can manage at the same time controls' and patient's data. + The use of Bayesian statistics allows to test both the alternative and + null hypothesis. + Scandola, M., & Romano, D. (2020, August 3). + Scandola, M., & Romano, D. (2021). . + date_publication: '2022-09-04' + bug_reports: https://github.com/michelescandola/bmscstan + url: '' + url_cran: https://CRAN.R-project.org/package=bmscstan + url_git: https://github.com/michelescandola/bmscstan +bmstdr: + version: 0.7.9 + title: Bayesian Modeling of Spatio-Temporal Data with R + maintainer: Sujit K. Sahu + description: |- + Fits, validates and compares a number of Bayesian models for + spatial and space time point referenced and areal unit data. Model fitting + is done using several packages: 'rstan', 'INLA', 'spBayes', 'spTimer', + 'spTDyn', 'CARBayes' and 'CARBayesST'. Model comparison is performed using + the DIC and WAIC, and K-fold cross-validation where the user is free + to select their own subset of data rows for validation. Sahu (2022) + describes the methods in detail. + date_publication: '2023-12-18' + bug_reports: https://github.com/sujit-sahu/bmstdr/issues + url: https://www.sujitsahu.com + url_cran: https://CRAN.R-project.org/package=bmstdr + url_git: '' +BMT: + version: 0.1.0.3 + title: The BMT Distribution + maintainer: Camilo Jose Torres-Jimenez + description: Density, distribution, quantile function, random number generation + for the BMT (Bezier-Montenegro-Torres) distribution. Torres-Jimenez C.J. and Montenegro-Diaz + A.M. (2017) . Moments, descriptive measures and parameter conversion + for different parameterizations of the BMT distribution. Fit of the BMT distribution + to non-censored data by maximum likelihood, moment matching, quantile matching, + maximum goodness-of-fit, also known as minimum distance, maximum product of spacing, + also called maximum spacing, and minimum quantile distance, which can also be + called maximum quantile goodness-of-fit. Fit of univariate distributions for non-censored + data using maximum product of spacing estimation and minimum quantile distance + estimation is also included. + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BMT + url_git: '' +BMTAR: + version: 0.1.1 + title: Bayesian Approach for MTAR Models with Missing Data + maintainer: Andrey Duvan Rincon Torres + description: Implements parameter estimation using a Bayesian approach for Multivariate + Threshold Autoregressive (MTAR) models with missing data using Markov Chain Monte + Carlo methods. Performs the simulation of MTAR processes (mtarsim()), estimation + of matrix parameters and the threshold values (mtarns()), identification of the + autoregressive orders using Bayesian variable selection (mtarstr()), identification + of the number of regimes using Metropolised Carlin and Chib (mtarnumreg()) and + estimate missing data, coefficients and covariance matrices conditional on the + autoregressive orders, the threshold values and the number of regimes (mtarmissing()). + Calderon and Nieto (2017) . + date_publication: '2021-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BMTAR + url_git: '' +bnclassify: + version: 0.4.8 + title: Learning Discrete Bayesian Network Classifiers from Data + maintainer: Mihaljevic Bojan + description: State-of-the art algorithms for learning discrete Bayesian network + classifiers from data, including a number of those described in Bielza & Larranaga + (2014) , with functions for prediction, model evaluation + and inspection. + date_publication: '2024-03-13' + bug_reports: https://github.com/bmihaljevic/bnclassify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bnclassify + url_git: https://github.com/bmihaljevic/bnclassify +bndesr: + version: 1.0.4 + title: Access Data from the Brazilian Development Bank (BNDES) + maintainer: Igor Laltuf + description: Allows access to data on BNDES disbursements and contracts since 1995. + The package makes it easy to import data from the bank into R.. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bndesr + url_git: '' +bndovb: + version: '1.1' + title: Bounding Omitted Variable Bias Using Auxiliary Data + maintainer: Yujung Hwang + description: Functions to implement a Hwang(2021) estimator, + which bounds an omitted variable bias using auxiliary data. + date_publication: '2021-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bndovb + url_git: '' +bnlearn: + version: 5.0.2 + title: |- + Bayesian Network Structure Learning, Parameter Learning and + Inference + maintainer: Marco Scutari + description: |- + Bayesian network structure learning, parameter learning and inference. + This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, + Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu + Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, + Gaussian and conditional Gaussian networks, along with many score functions and + conditional independence tests. + The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. + Some utility functions (model comparison and manipulation, random data generation, arc + orientation testing, simple and advanced plots) are included, as well as support for + parameter estimation (maximum likelihood and Bayesian) and inference, conditional + probability queries, cross-validation, bootstrap and model averaging. + Development snapshots with the latest bugfixes are available from . + date_publication: '2025-01-07' + bug_reports: '' + url: https://www.bnlearn.com/ + url_cran: https://CRAN.R-project.org/package=bnlearn + url_git: '' +bnma: + version: 1.6.0 + title: Bayesian Network Meta-Analysis using 'JAGS' + maintainer: Michael Seo + description: Network meta-analyses using Bayesian framework following Dias et al. + (2013) . Based on the data input, creates prior, + model file, and initial values needed to run models in 'rjags'. Able to handle + binomial, normal and multinomial arm-level data. Can handle multi-arm trials and + includes methods to incorporate covariate and baseline risk effects. Includes + standard diagnostics and visualization tools to evaluate the results. + date_publication: '2024-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bnma + url_git: '' +bnmonitor: + version: 0.2.2 + title: An Implementation of Sensitivity Analysis in Bayesian Networks + maintainer: Manuele Leonelli + description: 'An implementation of sensitivity and robustness methods in Bayesian + networks in R. It includes methods to perform parameter variations via a variety + of co-variation schemes, to compute sensitivity functions and to quantify the + dissimilarity of two Bayesian networks via distances and divergences. It further + includes diagnostic methods to assess the goodness of fit of a Bayesian networks + to data, including global, node and parent-child monitors. Reference: M. Leonelli, + R. Ramanathan, R.L. Wilkerson (2022) .' + date_publication: '2024-09-23' + bug_reports: '' + url: https://manueleleonelli.github.io/bnmonitor/ + url_cran: https://CRAN.R-project.org/package=bnmonitor + url_git: https://github.com/manueleleonelli/bnmonitor +bnns: + version: 0.1.2 + title: Bayesian Neural Network with 'Stan' + maintainer: Swarnendu Chatterjee + description: 'Offers a flexible formula-based interface for building and training + Bayesian Neural Networks powered by ''Stan''. The package supports modeling complex + relationships while providing rigorous uncertainty quantification via posterior + distributions. With features like user chosen priors, clear predictions, and support + for regression, binary, and multi-class classification, it is well-suited for + applications in clinical trials, finance, and other fields requiring robust Bayesian + inference and decision-making. References: Neal(1996) .' + date_publication: '2025-01-13' + bug_reports: https://github.com/swarnendu-stat/bnns/issues + url: https://swarnendu-stat.github.io/bnns/ + url_cran: https://CRAN.R-project.org/package=bnns + url_git: https://github.com/swarnendu-stat/bnns +bnnSurvival: + version: 0.1.5 + title: Bagged k-Nearest Neighbors Survival Prediction + maintainer: Marvin N. Wright + description: |- + Implements a bootstrap aggregated (bagged) version of + the k-nearest neighbors survival probability prediction method (Lowsky et + al. 2013). In addition to the bootstrapping of training samples, the + features can be subsampled in each baselearner to break the correlation + between them. The Rcpp package is used to speed up the computation. + date_publication: '2017-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bnnSurvival + url_git: '' +bnpa: + version: 0.3.0 + title: Bayesian Networks & Path Analysis + maintainer: Elias Carvalho + description: |- + This project aims to enable the method of Path Analysis to infer causalities + from data. For this we propose a hybrid approach, which uses Bayesian network + structure learning algorithms from data to create the input file for creation of a + PA model. The process is performed in a semi-automatic way by our intermediate + algorithm, allowing novice researchers to create and evaluate their own PA models + from a data set. The references used for this project are: + Koller, D., & Friedman, N. (2009). Probabilistic graphical models: principles and techniques. MIT press. . + Nagarajan, R., Scutari, M., & Lèbre, S. (2013). Bayesian networks in r. Springer, 122, 125-127. Scutari, M., & Denis, J. B. . + Scutari M (2010). Bayesian networks: with examples in R. Chapman and Hall/CRC. . + Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1 - 36. . + date_publication: '2019-08-01' + bug_reports: '' + url: https://sites.google.com/site/bnparp/. + url_cran: https://CRAN.R-project.org/package=bnpa + url_git: '' +BNPdensity: + version: 2023.3.8 + title: |- + Ferguson-Klass Type Algorithm for Posterior Normalized Random + Measures + maintainer: Guillaume Kon Kam King + description: Bayesian nonparametric density estimation modeling mixtures by a Ferguson-Klass + type algorithm for posterior normalized random measures. + date_publication: '2023-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BNPdensity + url_git: '' +BNPmix: + version: 1.0.2 + title: Bayesian Nonparametric Mixture Models + maintainer: Riccardo Corradin + description: Functions to perform Bayesian nonparametric univariate and multivariate + density estimation and clustering, by means of Pitman-Yor mixtures, and dependent + Dirichlet process mixtures for partially exchangeable data. See Corradin et al. + (2021) for more details. + date_publication: '2022-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BNPmix + url_git: '' +bnpsd: + version: 1.3.13 + title: Simulate Genotypes from the BN-PSD Admixture Model + maintainer: Alejandro Ochoa + description: The Pritchard-Stephens-Donnelly (PSD) admixture model has k intermediate + subpopulations from which n individuals draw their alleles dictated by their individual-specific + admixture proportions. The BN-PSD model additionally imposes the Balding-Nichols + (BN) allele frequency model to the intermediate populations, which therefore evolved + independently from a common ancestral population T with subpopulation-specific + FST (Wright's fixation index) parameters. The BN-PSD model can be used to yield + complex population structures. This simulation approach is now extended to subpopulations + related by a tree. Method described in Ochoa and Storey (2021) . + date_publication: '2021-08-25' + bug_reports: https://github.com/StoreyLab/bnpsd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bnpsd + url_git: https://github.com/StoreyLab/bnpsd/ +BNPTSclust: + version: '2.0' + title: A Bayesian Nonparametric Algorithm for Time Series Clustering + maintainer: David Alejandro Martell Juarez + description: Performs the algorithm for time series clustering described in Nieto-Barajas + and Contreras-Cristan (2014). + date_publication: '2019-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BNPTSclust + url_git: '' +bnRep: + version: 0.0.2 + title: A Repository of Bayesian Networks from the Academic Literature + maintainer: Manuele Leonelli + description: 'A collection of Bayesian networks (discrete, Gaussian, and conditional + linear Gaussian) collated from recent academic literature. The ''bnRep_summary'' + object provides an overview of the Bayesian networks in the repository and the + package documentation includes details about the variables in each network. A + Shiny app to explore the repository can be launched with ''bnRep_app()'' and is + available online at . Reference: ''M. + Leonelli'' (2024) .' + date_publication: '2024-10-01' + bug_reports: https://github.com/manueleleonelli/bnRep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bnRep + url_git: https://github.com/manueleleonelli/bnRep +BNrich: + version: 0.1.1 + title: Pathway Enrichment Analysis Based on Bayesian Network + maintainer: Samaneh Maleknia + description: Maleknia et al. (2020) . A novel pathway + enrichment analysis package based on Bayesian network to investigate the topology + features of the pathways. firstly, 187 kyoto encyclopedia of genes and genomes + (KEGG) human non-metabolic pathways which their cycles were eliminated by biological + approach, enter in analysis as Bayesian network structures. The constructed Bayesian + network were optimized by the Least Absolute Shrinkage Selector Operator (lasso) + and the parameters were learned based on gene expression data. Finally, the impacted + pathways were enriched by Fisher’s Exact Test on significant parameters. + date_publication: '2020-04-04' + bug_reports: https://github.com/Samaneh-Bioinformatics/BNrich/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BNrich + url_git: https://github.com/Samaneh-Bioinformatics/BNrich +BNSL: + version: 0.1.4 + title: Bayesian Network Structure Learning + maintainer: Joe Suzuki + description: From a given data frame, this package learns its Bayesian network structure + based on a selected score. + date_publication: '2019-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BNSL + url_git: '' +BNSP: + version: 2.2.3 + title: Bayesian Non- And Semi-Parametric Model Fitting + maintainer: Georgios Papageorgiou + description: 'MCMC algorithms & processing functions for: 1. single response multiple + regression, see Papageorgiou, G. (2018) , 2. multivariate + response multiple regression, with nonparametric models for the means, the variances + and the correlation matrix, with variable selection, see Papageorgiou, G. and + Marshall, B. C. (2020) , 3. joint mean-covariance + models for multivariate responses, see Papageorgiou, G. (2022) , + and 4.Dirichlet process mixtures, see Papageorgiou, G. (2019) .' + date_publication: '2023-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BNSP + url_git: '' +bnstruct: + version: 1.0.15 + title: |- + Bayesian Network Structure Learning from Data with Missing + Values + maintainer: Alberto Franzin + description: |- + Bayesian Network Structure Learning from Data with Missing Values. + The package implements the Silander-Myllymaki complete search, + the Max-Min Parents-and-Children, the Hill-Climbing, the + Max-Min Hill-climbing heuristic searches, and the Structural + Expectation-Maximization algorithm. Available scoring functions are + BDeu, AIC, BIC. The package also implements methods for generating and using + bootstrap samples, imputed data, inference. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bnstruct + url_git: '' +bnviewer: + version: 0.1.6 + title: |- + Bayesian Networks Interactive Visualization and Explainable + Artificial Intelligence + maintainer: Robson Fernandes + description: |- + Bayesian networks provide an intuitive framework for probabilistic reasoning + and its graphical nature can be interpreted quite clearly. Graph based methods + of machine learning are becoming more popular because they offer a richer model + of knowledge that can be understood by a human in a graphical format. The 'bnviewer' + is an R Package that allows the interactive visualization of Bayesian Networks. + The aim of this package is to improve the Bayesian Networks visualization over + the basic and static views offered by existing packages. + date_publication: '2020-09-14' + bug_reports: '' + url: http://robsonfernandes.net/bnviewer/ + url_cran: https://CRAN.R-project.org/package=bnviewer + url_git: '' +boa: + version: 1.1.8-2 + title: Bayesian Output Analysis Program (BOA) for MCMC + maintainer: Brian J. Smith + description: |- + A menu-driven program and library of functions for carrying out + convergence diagnostics and statistical and graphical analysis of Markov + chain Monte Carlo sampling output. + date_publication: '2016-06-23' + bug_reports: '' + url: http://www.jstatsoft.org/v21/i11 + url_cran: https://CRAN.R-project.org/package=boa + url_git: '' +BoardGames: + version: 1.0.0 + title: Board Games and Tools for Building Board Games + maintainer: Derek Qiu + description: Tools for constructing board/grid based games, as well as readily available + game(s) for your entertainment. + date_publication: '2016-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoardGames + url_git: '' +bodenmiller: + version: 0.1.1 + title: Profiling of Peripheral Blood Mononuclear Cells using CyTOF + maintainer: Yann Abraham + description: This data package contains a subset of the Bodenmiller et al, Nat Biotech + 2012 dataset for testing single cell, high dimensional analysis and visualization + methods. + date_publication: '2021-04-11' + bug_reports: https://github.com/yannabraham/bodenmiller/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bodenmiller + url_git: https://github.com/yannabraham/bodenmiller +Bodi: + version: 0.1.0 + title: Boosting Diversity in Regression Ensembles + maintainer: Yannig Goude + description: A gradient boosting-based algorithm by incorporating a diversity term + to guide the gradient boosting iterations, see Bourel, Cugliari, Goude, Poggi + (2021) . + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bodi + url_git: '' +bodsr: + version: 0.1.0 + title: Call the Bus Open Data Service ('BODS') API Through R + maintainer: Francesca Bryden + description: |- + A wrapper to allow users to download Bus Open Data Service 'BODS' transport information from the API (). + This includes timetable and fare metadata (including links for full datasets), timetable data at line level, + and real-time location data. + date_publication: '2023-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bodsr + url_git: '' +bodycomp: + version: 1.0.0 + title: |- + Percent Body Fat Values Using Anthropometric Prediction + Equations + maintainer: Gleidson Mendes Rebouças + description: Skinfold measurements is one of the most popular and practical methods + for estimating percent body fat. Body composition is a term that describes the + relative proportions of fat, bone, and muscle mass in the human body. Following + the collection of skinfold measurements, regression analysis (a statistical procedure + used to predict a dependent variable based on one or more independent or predictor + variables) is used to estimate total percent body fat in humans. . + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bodycomp + url_git: '' +bodycompref: + version: 2.0.1 + title: Reference Values for CT-Assessed Body Composition + maintainer: J. Peter Marquardt + description: |- + Get z-scores, percentiles, absolute values, and percent of predicted of a reference cohort. + Functionality requires installing the data packages 'adiposerefdata' and 'musclerefdata'. + For more information on the underlying research, please visit our website which also includes a graphical interface. + The models and underlying data are described in + Marquardt JP et al.(planned publication 2025; reserved doi 10.1097/RLI.0000000000001104), + "Subcutaneous and Visceral adipose tissue Reference Values from Framingham Heart Study Thoracic and Abdominal CT", + *Investigative Radiology* + and + Tonnesen PE et al. (2023), + "Muscle Reference Values from Thoracic and Abdominal CT for Sarcopenia Assessment [column] The Framingham Heart Study", + *Investigative Radiology*, + . + date_publication: '2024-07-21' + bug_reports: '' + url: https://bodycomp-metrics.mgh.harvard.edu + url_cran: https://CRAN.R-project.org/package=bodycompref + url_git: https://github.com/p-mq/bodycompref +boggy: + version: 0.0.1 + title: Real-Time PCR Data Sets by Boggy et al. (2010) + maintainer: Ramiro Magno + description: |- + Real-time quantitative polymerase chain reaction (qPCR) data + sets by Boggy et al. (2008) . This package + provides a dilution series for one PCR target: a random sequence that + minimizes secondary structure and off-target primer binding. The data set + is a six-point, ten-fold dilution series. + For each concentration there are two replicates. Each amplification curve + is 40 cycles long. Original raw data file: + . + date_publication: '2024-04-25' + bug_reports: https://github.com/ramiromagno/boggy/issues + url: https://rmagno.eu/boggy/ + url_cran: https://CRAN.R-project.org/package=boggy + url_git: https://github.com/ramiromagno/boggy +boilerpipeR: + version: 1.3.2 + title: Interface to the Boilerpipe Java Library + maintainer: Mario Annau + description: |- + Generic Extraction of main text content from HTML files; removal + of ads, sidebars and headers using the boilerpipe + Java library. The + extraction heuristics from boilerpipe show a robust performance for a wide + range of web site templates. + date_publication: '2021-05-19' + bug_reports: https://github.com/mannau/boilerpipeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boilerpipeR + url_git: https://github.com/mannau/boilerpipeR +BOIN: + version: 2.7.2 + title: |- + Bayesian Optimal INterval (BOIN) Design for Single-Agent and + Drug- Combination Phase I Clinical Trials + maintainer: Ying Yuan + description: |- + The Bayesian optimal interval (BOIN) design is a novel phase I + clinical trial design for finding the maximum tolerated dose (MTD). It can be + used to design both single-agent and drug-combination trials. The BOIN design + is motivated by the top priority and concern of clinicians when testing a new + drug, which is to effectively treat patients and minimize the chance of exposing + them to subtherapeutic or overly toxic doses. The prominent advantage of the + BOIN design is that it achieves simplicity and superior performance at the same + time. The BOIN design is algorithm-based and can be implemented in a simple + way similar to the traditional 3+3 design. The BOIN design yields an average + performance that is comparable to that of the continual reassessment method + (CRM, one of the best model-based designs) in terms of selecting the MTD, but + has a substantially lower risk of assigning patients to subtherapeutic or overly + toxic doses. For tutorial, please check Yan et al. (2020) . + date_publication: '2021-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BOIN + url_git: '' +boinet: + version: 1.1.0 + title: |- + Conduct Simulation Study of Bayesian Optimal Interval Design + with BOIN-ET Family + maintainer: Yusuke Yamaguchi + description: 'Bayesian optimal interval based on both efficacy and toxicity outcomes + (BOIN-ET) design is a model-assisted oncology phase I/II trial design, aiming + to establish an optimal biological dose accounting for efficacy and toxicity in + the framework of dose-finding. Some extensions of BOIN-ET design are also available + to allow for time-to-event efficacy and toxicity outcomes based on cumulative + and pending data (time-to-event BOIN-ET: TITE-BOIN-ET), ordinal graded efficacy + and toxicity outcomes (generalized BOIN-ET: gBOIN-ET), and their combination (TITE-gBOIN-ET). + ''boinet'' is a package to implement the BOIN-ET design family and supports the + conduct of simulation studies to assess operating characteristics of BOIN-ET, + TITE-BOIN-ET, gBOIN-ET, and TITE-gBOIN-ET, where users can choose design parameters + in flexible and straightforward ways depending on their own application.' + date_publication: '2024-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boinet + url_git: '' +boiwsa: + version: 1.1.3 + title: Seasonal Adjustment of Weekly Data + maintainer: Tim Ginker + description: Perform seasonal adjustment of weekly data. The package provides a + user-friendly interface for computing seasonally adjusted estimates of weekly + data and includes functions for the creation of country-specific prior adjustment + variables, as well as diagnostic tools to assess the quality of the adjustments. + The method is described in more detail in Ginker (2023) . + date_publication: '2025-02-05' + bug_reports: https://github.com/timginker/boiwsa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boiwsa + url_git: https://github.com/timginker/boiwsa +BOJ: + version: 0.3.4 + title: Interface to Bank of Japan Statistics + maintainer: Stefan Angrick + description: |- + Provides an interface to Bank of Japan + statistics. + date_publication: '2025-01-19' + bug_reports: https://github.com/stefanangrick/BOJ/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BOJ + url_git: https://github.com/stefanangrick/BOJ +bolasso: + version: 0.3.0 + title: Model Consistent Lasso Estimation Through the Bootstrap + maintainer: Daniel Molitor + description: |- + Implements the bolasso algorithm for consistent variable selection + and estimation accuracy. Includes support for many parallel backends via the + future package. For details see: Bach (2008), + 'Bolasso: model consistent Lasso estimation through the bootstrap', + . + date_publication: '2024-12-08' + bug_reports: https://github.com/dmolitor/bolasso/issues + url: https://www.dmolitor.com/bolasso/ + url_cran: https://CRAN.R-project.org/package=bolasso + url_git: https://github.com/dmolitor/bolasso +bolsec: + version: 0.1.1 + title: Bolivian Securities + maintainer: Alvaro Tapia + description: Provides data import and offers 3 daily snapshot functions from securities + of varying prices traded on the Bolivian Securities Exchange, website . + The snapshots include a detailed list, scatter plot correlation, and descriptive + statistics table for the securities. + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bolsec + url_git: '' +Bolstad: + version: 0.2.42 + title: Functions for Elementary Bayesian Inference + maintainer: James Curran + description: A set of R functions and data sets for the book Introduction to Bayesian + Statistics, Bolstad, W.M. (2017), John Wiley & Sons ISBN 978-1-118-09156-2. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bolstad + url_git: '' +Bolstad2: + version: 1.0-29 + title: Bolstad Functions + maintainer: James Curran + description: A set of R functions and data sets for the book "Understanding Computational + Bayesian Statistics." This book was written by Bill (WM) Bolstad and published + in 2009 by John Wiley & Sons (ISBN 978-0470046098). + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bolstad2 + url_git: https://github.com/jmcurran/Bolstad2 +bolt4jr: + version: 1.4.0 + title: Interface for the 'Neo4j Bolt' Protocol + maintainer: Wanjun Gu + description: Querying, extracting, and processing large-scale network data from + Neo4j databases using the 'Neo4j Bolt' + protocol. This interface supports efficient data retrieval, batch processing for + large datasets, and seamless conversion of query results into R data frames, making + it ideal for bioinformatics, computational biology, and other graph-based applications. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bolt4jr + url_git: '' +BoltzMM: + version: 0.1.4 + title: Boltzmann Machines with MM Algorithms + maintainer: Andrew Thomas Jones + description: |- + Provides probability computation, data generation, + and model estimation for fully-visible Boltzmann machines. It follows the methods + described in Nguyen and Wood (2016a) + and Nguyen and Wood (2016b) . + date_publication: '2019-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoltzMM + url_git: '' +bondAnalyst: + version: 1.0.1 + title: Methods for Fixed-Income Valuation, Risk and Return + maintainer: MaheshP Kumar + description: |- + Bond Pricing and Fixed-Income Valuation of Selected Securities included here serve as a quick reference of Quantitative Methods for undergraduate courses on Fixed-Income and CFA Level I Readings on Fixed-Income Valuation, Risk and Return. + CFA Institute ("CFA Program Curriculum 2020 Level I Volumes 1-6. (Vol. 5, pp. 107-151, pp. 237-299)", 2019, ISBN: 9781119593577). + Barbara S. Petitt ("Fixed Income Analysis", 2019, ISBN: 9781119628132). + Frank J. Fabozzi ("Handbook of Finance: Financial Markets and Instruments", 2008, ISBN: 9780470078143). + Frank J. Fabozzi ("Fixed Income Analysis", 2007, ISBN: 9780470052211). + date_publication: '2022-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bondAnalyst + url_git: '' +BondValuation: + version: 0.1.1 + title: |- + Fixed Coupon Bond Valuation Allowing for Odd Coupon Periods and + Various Day Count Conventions + maintainer: Djatschenko Wadim + description: Analysis of large datasets of fixed coupon bonds, allowing for irregular + first and last coupon periods and various day count conventions. With this package + you can compute the yield to maturity, the modified and MacAulay durations and + the convexity of fixed-rate bonds. It provides the function AnnivDates, which + can be used to evaluate the quality of the data and return time-invariant properties + and temporal structure of a bond. + date_publication: '2022-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BondValuation + url_git: '' +BoneProfileR: + version: '3.1' + title: Tools to Study Bone Compactness + maintainer: Marc Girondot + description: |- + Bone Profiler is a scientific method and a software used to model + bone section for paleontological and ecological studies. See Girondot and Laurin + (2003) + and Gônet, Laurin and Girondot (2022) . + date_publication: '2024-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoneProfileR + url_git: '' +BonEV: + version: '1.0' + title: |- + An Improved Multiple Testing Procedure for Controlling False + Discovery Rates + maintainer: Dongmei Li + description: An improved multiple testing procedure for controlling false discovery + rates which is developed based on the Bonferroni procedure with integrated estimates + from the Benjamini-Hochberg procedure and the Storey's q-value procedure. It controls + false discovery rates through controlling the expected number of false discoveries. + date_publication: '2016-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BonEV + url_git: '' +bonn: + version: 1.0.2 + title: Access INKAR Database + maintainer: Moritz Marbach + description: Retrieve and import data from the INKAR database (Indikatoren und Karten + zur Raum- und Stadtentwicklung Datenbank, ) of the Federal + Office for Building and Regional Planning (BBSR) in Bonn using their JSON API. + date_publication: '2023-03-20' + bug_reports: https://github.com/sumtxt/bonn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bonn + url_git: https://github.com/sumtxt/bonn/ +bonsai: + version: 0.3.2 + title: Model Wrappers for Tree-Based Models + maintainer: Simon Couch + description: |- + Bindings for additional tree-based model engines for use with + the 'parsnip' package. Models include gradient boosted decision trees + with 'LightGBM' (Ke et al, 2017.), conditional inference trees and + conditional random forests with 'partykit' (Hothorn and Zeileis, 2015. + and Hothorn et al, 2006. ), and + accelerated oblique random forests with 'aorsf' (Jaeger et al, 2022 + ). + date_publication: '2025-02-11' + bug_reports: https://github.com/tidymodels/bonsai/issues + url: https://bonsai.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=bonsai + url_git: https://github.com/tidymodels/bonsai +bonsaiforest: + version: 0.1.1 + title: Shrinkage Based Forest Plots + maintainer: Isaac Gravestock + description: |- + Subgroup analyses are routinely performed in clinical trial + analyses. From a methodological perspective, two key issues of + subgroup analyses are multiplicity (even if only predefined subgroups + are investigated) and the low sample sizes of subgroups which lead to + highly variable estimates, see e.g. Yusuf et al (1991) + . This package implements + subgroup estimates based on Bayesian shrinkage priors, see Carvalho et + al (2019) . In + addition, estimates based on penalized likelihood inference are + available, based on Simon et al (2011) . + The corresponding shrinkage based forest plots address the + aforementioned issues and can complement standard forest plots in + practical clinical trial analyses. + date_publication: '2024-09-27' + bug_reports: https://github.com/insightsengineering/bonsaiforest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bonsaiforest + url_git: https://github.com/insightsengineering/bonsaiforest/ +boodist: + version: 1.0.0 + title: Some Distributions from the 'Boost' Library and More + maintainer: Stéphane Laurent + description: |- + Make some distributions from the 'C++' library 'Boost' + available in 'R'. In addition, the normal-inverse Gaussian distribution + and the generalized inverse Gaussian distribution are provided. The + distributions are represented by 'R6' classes. The method to sample from + the generalized inverse Gaussian distribution is the one given in + "Random variate generation for the generalized inverse Gaussian + distribution" Luc Devroye (2012) . + date_publication: '2023-08-10' + bug_reports: https://github.com/stla/boodist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boodist + url_git: https://github.com/stla/boodist +bookdown: + version: '0.42' + title: Authoring Books and Technical Documents with R Markdown + maintainer: Yihui Xie + description: Output formats and utilities for authoring books and technical documents + with R Markdown. + date_publication: '2025-01-07' + bug_reports: https://github.com/rstudio/bookdown/issues + url: https://pkgs.rstudio.com/bookdown/ + url_cran: https://CRAN.R-project.org/package=bookdown + url_git: https://github.com/rstudio/bookdown +BoolFilter: + version: 1.0.0 + title: |- + Optimal Estimation of Partially Observed Boolean Dynamical + Systems + maintainer: Levi McClenny + description: |- + Tools for optimal and approximate state estimation as well as + network inference of Partially-Observed Boolean Dynamical Systems. + date_publication: '2017-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoolFilter + url_git: '' +BoolNet: + version: 2.1.9 + title: Construction, Simulation and Analysis of Boolean Networks + maintainer: Hans A. Kestler + description: Functions to reconstruct, generate, and simulate synchronous, asynchronous, + probabilistic, and temporal Boolean networks. Provides also functions to analyze + and visualize attractors in Boolean networks . + date_publication: '2023-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoolNet + url_git: '' +Boom: + version: 0.9.15 + title: Bayesian Object Oriented Modeling + maintainer: Steven L. Scott + description: |- + A C++ library for Bayesian modeling, with an emphasis on Markov + chain Monte Carlo. Although boom contains a few R utilities (mainly plotting + functions), its primary purpose is to install the BOOM C++ library on your + system so that other packages can link against it. + date_publication: '2024-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Boom + url_git: '' +boomer: + version: 0.2.0 + title: Debugging Tools to Inspect the Intermediate Steps of a Call + maintainer: Antoine Fabri + description: |- + Provides debugging tools that let you inspect the + intermediate results of a call. The output looks as if we explode a + call into its parts hence the package name. + date_publication: '2024-07-09' + bug_reports: https://github.com/moodymudskipper/boomer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boomer + url_git: https://github.com/moodymudskipper/boomer +BoomSpikeSlab: + version: 1.2.6 + title: MCMC for Spike and Slab Regression + maintainer: Steven L. Scott + description: |- + Spike and slab regression with a variety of residual error + distributions corresponding to Gaussian, Student T, probit, logit, SVM, and a + few others. Spike and slab regression is Bayesian regression with prior + distributions containing a point mass at zero. The posterior updates the + amount of mass on this point, leading to a posterior distribution that is + actually sparse, in the sense that if you sample from it many coefficients are + actually zeros. Sampling from this posterior distribution is an elegant way + to handle Bayesian variable selection and model averaging. See + for an explanation of the Gaussian case. + date_publication: '2023-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoomSpikeSlab + url_git: '' +boostingDEA: + version: 0.1.0 + title: A Boosting Approach to Data Envelopment Analysis + maintainer: Maria D. Guillen + description: |- + Includes functions to estimate production frontiers + and make ideal output predictions in the Data Envelopment Analysis (DEA) + context using both standard models from DEA and Free Disposal Hull (FDH) + and boosting techniques. In particular, EATBoosting (Guillen et al., 2023 + ) and MARSBoosting. Moreover, the package + includes code for estimating several technical efficiency measures using + different models such as the input and output-oriented radial measures, the + input and output-oriented Russell measures, the Directional Distance + Function (DDF), the Weighted Additive Measure (WAM) and the Slacks-Based + Measure (SBM). + date_publication: '2023-05-15' + bug_reports: https://github.com/itsmeryguillen/boostingDEA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boostingDEA + url_git: https://github.com/itsmeryguillen/boostingDEA +BoostMLR: + version: 1.0.3 + title: Boosting for Multivariate Longitudinal Responses + maintainer: Amol Pande + description: Jointly models the multivariate longitudinal responses and multiple + covariates and time using gradient boosting approach. + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoostMLR + url_git: '' +boostrq: + version: 1.0.0 + title: Boosting Regression Quantiles + maintainer: Stefan Linner + description: |- + Boosting Regression Quantiles is a component-wise boosting algorithm, + that embeds all boosting steps in the well-established framework + of quantile regression. It is initialized with the corresponding quantile, + uses a quantile-specific learning rate, and uses quantile regression as its base learner. + The package implements this algorithm and allows cross-validation and stability selection. + date_publication: '2024-03-05' + bug_reports: https://github.com/stefanlinner/boostrq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boostrq + url_git: https://github.com/stefanlinner/boostrq +boot: + version: 1.3-31 + title: Bootstrap Functions (Originally by Angelo Canty for S) + maintainer: Alessandra R. Brazzale + description: |- + Functions and datasets for bootstrapping from the + book "Bootstrap Methods and Their Application" by A. C. Davison and + D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boot + url_git: '' +boot.heterogeneity: + version: 1.1.5 + title: A Bootstrap-Based Heterogeneity Test for Meta-Analysis + maintainer: Ge Jiang + description: Implements a bootstrap-based heterogeneity test for standardized mean + differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed + odds ratio (or) in meta-analysis studies. Depending on the presence of moderators, + this Monte Carlo based test can be implemented in the random- or mixed-effects + model. This package uses rma() function from the R package 'metafor' to obtain + parameter estimates and likelihoods, so installation of R package 'metafor' is + required. This approach refers to the studies of Anscombe (1956) , + Haldane (1940) , Hedges (1981) , + Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & + Fowler (2004) , Viechtbauer (2010) , + and Zuckerman (1994, ISBN:978-0521432009). + date_publication: '2021-10-23' + bug_reports: https://github.com/gabriellajg/boot.heterogeneity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boot.heterogeneity + url_git: https://github.com/gabriellajg/boot.heterogeneity/ +boot.pval: + version: '0.6' + title: Bootstrap p-Values + maintainer: Måns Thulin + description: Computation of bootstrap p-values through inversion of confidence intervals, + including convenience functions for regression models. + date_publication: '2025-01-14' + bug_reports: https://github.com/mthulin/boot.pval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boot.pval + url_git: https://github.com/mthulin/boot.pval +bootcluster: + version: 0.4.1 + title: Bootstrapping Estimates of Clustering Stability + maintainer: Tianmou Liu + description: Implementation of the bootstrapping approach for the estimation of + clustering stability and its application in estimating the number of clusters, + as introduced by Yu et al (2016). Implementation + of the non-parametric bootstrap approach to assessing the stability of module + detection in a graph, the extension for the selection of a parameter set that + defines a graph from data in a way that optimizes stability and the corresponding + visualization functions, as introduced by Tian et al (2021) . + Implemented out-of-bag stability estimation function and k-select Smin-based k-selection + function as introduced by Liu et al (2022) . Implemented + ensemble clustering method based-on k-means clustering method, spectral clustering + method and hierarchical clustering method. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootcluster + url_git: '' +bootComb: + version: 1.1.2 + title: Combine Parameter Estimates via Parametric Bootstrap + maintainer: Marc Henrion + description: |- + Propagate uncertainty from several estimates when combining these estimates via a function. + This is done by using the parametric bootstrap to simulate values from the distribution of each estimate to build up an empirical distribution of the combined parameter. + Finally either the percentile method is used or the highest density interval is chosen to derive a confidence interval for the combined parameter with the desired coverage. + Gaussian copulas are used for when parameters are assumed to be dependent / correlated. + References: Davison and Hinkley (1997,ISBN:0-521-57471-4) for the parametric bootstrap and percentile method, Gelman et al. (2014,ISBN:978-1-4398-4095-5) for the highest density interval, Stockdale et al. (2020) for an example of combining conditional prevalences. + date_publication: '2022-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootComb + url_git: '' +bootCT: + version: 2.1.0 + title: Bootstrapping the ARDL Tests for Cointegration + maintainer: Gianmarco Vacca + description: 'The bootstrap ARDL tests for cointegration is the main functionality + of this package. It also acts as a wrapper of the most commond ARDL testing procedures + for cointegration: the bound tests of Pesaran, Shin and Smith (PSS; 2001 - ) + and the asymptotic test on the independent variables of Sam, McNown and Goh (SMG: + 2019 - ). Bootstrap and bound tests are performed + under both the conditional and unconditional ARDL models.' + date_publication: '2024-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootCT + url_git: '' +bootES: + version: 1.3.1 + title: Bootstrap Confidence Intervals on Effect Sizes + maintainer: Daniel Gerlanc + description: Calculate robust measures of effect sizes using the bootstrap. + date_publication: '2024-11-11' + bug_reports: https://github.com/dgerlanc/bootES/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootES + url_git: https://github.com/dgerlanc/bootES +bootf2: + version: 0.4.1 + title: Simulation and Comparison of Dissolution Profiles + maintainer: Zhengguo Xu + description: |- + Compare dissolution profiles with confidence interval of similarity + factor f2 using bootstrap methodology as described in the literature, such as + Efron and Tibshirani (1993, ISBN:9780412042317), Davison and Hinkley (1997, + ISBN:9780521573917), and Shah et al. (1998) . + The package can also be used to simulate dissolution profiles based on + mathematical modelling and multivariate normal distribution. + date_publication: '2021-08-25' + bug_reports: https://github.com/zhengguoxu/bootf2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootf2 + url_git: https://github.com/zhengguoxu/bootf2 +bootGOF: + version: 0.1.0 + title: Bootstrap Based Goodness-of-Fit Tests + maintainer: Marsel Scheer + description: |- + Bootstrap based goodness-of-fit tests. It allows + to perform rigorous statistical tests to check if a chosen + model family is correct based on the marked empirical + process. The implemented algorithms are described in + (Dikta and Scheer (2021) ) + and can be applied + to generalized linear models without any further implementation + effort. As far as certain linearity conditions are fulfilled + the resampling scheme are also applicable beyond generalized + linear models. This is reflected in the software architecture + which allows to reuse the resampling scheme by implementing + only certain interfaces for models that are not supported + natively by the package. + date_publication: '2021-06-24' + bug_reports: https://github.com/MarselScheer/bootGOF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootGOF + url_git: https://github.com/MarselScheer/bootGOF +bootImpute: + version: 1.2.1 + title: Bootstrap Inference for Multiple Imputation + maintainer: Jonathan Bartlett + description: Bootstraps and imputes incomplete datasets. Then performs inference + on estimates obtained from analysing the imputed datasets as proposed by von Hippel + and Bartlett (2021) . + date_publication: '2023-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootImpute + url_git: '' +bootLR: + version: 1.0.2 + title: |- + Bootstrapped Confidence Intervals for (Negative) Likelihood + Ratio Tests + maintainer: Ari B. Friedman + description: Computes appropriate confidence intervals for the likelihood ratio + tests commonly used in medicine/epidemiology, using the method of Marill et al. + (2015) . It is particularly useful when the sensitivity + or specificity in the sample is 100%. Note that this does not perform the test + on nested models--for that, see 'epicalc::lrtest'. + date_publication: '2019-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootLR + url_git: '' +BootMRMR: + version: '0.1' + title: Bootstrap-MRMR Technique for Informative Gene Selection + maintainer: Samarendra Das + description: Selection of informative features like genes, transcripts, RNA seq, + etc. using Bootstrap Maximum Relevance and Minimum Redundancy technique from a + given high dimensional genomic dataset. Informative gene selection involves identification + of relevant genes and removal of redundant genes as much as possible from a large + gene space. Main applications in high-dimensional expression data analysis (e.g. + microarray data, NGS expression data and other genomics and proteomics applications). + date_publication: '2016-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BootMRMR + url_git: '' +bootnet: + version: '1.6' + title: Bootstrap Methods for Various Network Estimation Routines + maintainer: Sacha Epskamp + description: |- + Bootstrap methods to assess accuracy and stability of estimated network structures + and centrality indices . Allows for flexible + specification of any undirected network estimation procedure in R, and offers + default sets for various estimation routines. + date_publication: '2024-02-21' + bug_reports: https://github.com/SachaEpskamp/bootnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootnet + url_git: https://github.com/SachaEpskamp/bootnet +bootPLS: + version: 1.0.1 + title: Bootstrap Hyperparameter Selection for PLS Models and Extensions + maintainer: Frederic Bertrand + description: Several implementations of non-parametric stable bootstrap-based techniques + to determine the numbers of components for Partial Least Squares linear or generalized + linear regression models as well as and sparse Partial Least Squares linear or + generalized linear regression models. The package collects techniques that were + published in a book chapter (Magnanensi et al. 2016, 'The Multiple Facets of Partial + Least Squares and Related Methods', ) and two + articles (Magnanensi et al. 2017, 'Statistics and Computing', ) + and (Magnanensi et al. 2021, 'Frontiers in Applied Mathematics and Statistics', + ). + date_publication: '2024-09-24' + bug_reports: https://github.com/fbertran/bootPLS/issues/ + url: https://fbertran.github.io/bootPLS/ + url_cran: https://CRAN.R-project.org/package=bootPLS + url_git: https://github.com/fbertran/bootPLS/ +BootPR: + version: '1.0' + title: Bootstrap Prediction Intervals and Bias-Corrected Forecasting + maintainer: Jae H. Kim + description: Contains functions for bias-Corrected Forecasting and Bootstrap Prediction + Intervals for Autoregressive Time Series. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BootPR + url_git: '' +bootruin: + version: 1.2-4 + title: |- + A Bootstrap Test for the Probability of Ruin in the Classical + Risk Process + maintainer: Benjamin Baumgartner + description: We provide a framework for testing the probability of ruin in the classical + (compound Poisson) risk process. It also includes some procedures for assessing + and comparing the performance between the bootstrap test and the test using asymptotic + normality. + date_publication: '2016-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootruin + url_git: '' +bootStateSpace: + version: 1.0.2 + title: Bootstrap for State Space Models + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Provides a streamlined and user-friendly framework + for bootstrapping in state space models, + particularly when the number of subjects/units (n) exceeds one, + a scenario commonly encountered in social and behavioral sciences. + For an introduction to state space models in social and behavioral sciences, + refer to Chow, Ho, Hamaker, and Dolan (2010) . + date_publication: '2025-02-14' + bug_reports: https://github.com/jeksterslab/bootStateSpace/issues + url: https://jeksterslab.github.io/bootStateSpace/ + url_cran: https://CRAN.R-project.org/package=bootStateSpace + url_git: https://github.com/jeksterslab/bootStateSpace +bootStepAIC: + version: 1.3-0 + title: Bootstrap stepAIC + maintainer: Dimitris Rizopoulos + description: Model selection by bootstrapping the stepAIC() procedure. + date_publication: '2022-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootStepAIC + url_git: '' +bootstrap: + version: '2019.6' + title: Functions for the Book "An Introduction to the Bootstrap" + maintainer: Scott Kostyshak + description: |- + Software (bootstrap, cross-validation, jackknife) and data + for the book "An Introduction to the Bootstrap" by B. Efron and + R. Tibshirani, 1993, Chapman and Hall. This package is + primarily provided for projects already based on it, and for + support of the book. New projects should preferentially use the + recommended package "boot". + date_publication: '2019-06-17' + bug_reports: https://gitlab.com/scottkosty/bootstrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootstrap + url_git: https://gitlab.com/scottkosty/bootstrap +bootstrapFP: + version: 0.4.6 + title: Bootstrap Algorithms for Finite Population Inference + maintainer: Roberto Sichera + description: |- + Finite Population bootstrap algorithms to estimate the variance + of the Horvitz-Thompson estimator for single-stage sampling. + For a survey of bootstrap methods for finite populations, see Mashreghi et Al. (2016) . + date_publication: '2024-03-08' + bug_reports: https://github.com/rhobis/bootstrapFP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootstrapFP + url_git: '' +BootstrapQTL: + version: 1.0.5 + title: Bootstrap cis-QTL Method that Corrects for the Winner's Curse + maintainer: Scott Ritchie + description: |- + Identifies genome-related molecular traits with significant + evidence of genetic regulation and performs a bootstrap procedure to + correct estimated effect sizes for over-estimation present in cis-QTL + mapping studies (The "Winner's Curse"), described in Huang QQ *et al.* + 2018 . + date_publication: '2021-05-12' + bug_reports: https://github.com/sritchie73/bootstrapQTL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BootstrapQTL + url_git: '' +bootsurv: + version: 0.0.1 + title: Bootstrap Methods for Complete Survey Data + maintainer: Zeinab Mashreghi + description: Bootstrap resampling methods have been widely studied in the context + of survey data. This package implements various bootstrap resampling techniques + tailored for survey data, with a focus on stratified simple random sampling and + stratified two-stage cluster sampling. It provides tools for precise and consistent + bootstrap variance estimation for population totals, means, and quartiles. Additionally, + it enables easy generation of bootstrap samples for in-depth analysis. + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bootsurv + url_git: '' +bootSVD: + version: '1.1' + title: |- + Fast, Exact Bootstrap Principal Component Analysis for High + Dimensional Data + maintainer: Aaron Fisher + description: |- + Implements fast, exact bootstrap Principal Component Analysis and + Singular Value Decompositions for high dimensional data, as described in + (see also ). For data matrices that are too large to operate + on in memory, users can input objects with class 'ff' (see the 'ff' + package), where the actual data is stored on disk. In response, this + package will implement a block matrix algebra procedure for calculating the + principal components (PCs) and bootstrap PCs. Depending on options set by + the user, the 'parallel' package can be used to parallelize the calculation of + the bootstrap PCs. + date_publication: '2021-02-02' + bug_reports: '' + url: http://arxiv.org/abs/1405.0922 + url_cran: https://CRAN.R-project.org/package=bootSVD + url_git: '' +bootUR: + version: 1.0.4 + title: Bootstrap Unit Root Tests + maintainer: Stephan Smeekes + description: |- + Set of functions to perform various bootstrap unit root tests for both individual time series + (including augmented Dickey-Fuller test and union tests), multiple time series and panel data; see + Smeekes and Wilms (2023) , + Palm, Smeekes and Urbain (2008) , + Palm, Smeekes and Urbain (2011) , + Moon and Perron (2012) , + Smeekes and Taylor (2012) and + Smeekes (2015) for key references. + date_publication: '2024-05-20' + bug_reports: https://github.com/smeekes/bootUR/issues + url: https://smeekes.github.io/bootUR/ + url_cran: https://CRAN.R-project.org/package=bootUR + url_git: https://github.com/smeekes/bootUR +bootwar: + version: 0.2.1 + title: Nonparametric Bootstrap Test with Pooled Resampling Card Game + maintainer: Mackson Ncube + description: |- + The card game War is simple in its rules but can be lengthy. In + another domain, the nonparametric bootstrap test with pooled resampling + (nbpr) methods, as outlined in Dwivedi, Mallawaarachchi, and Alvarado (2017) , + is optimal for comparing paired or unpaired means in non-normal data, + especially for small sample size studies. However, many researchers are + unfamiliar with these methods. The 'bootwar' package bridges this gap by + enabling users to grasp the concepts of nbpr via Boot War, a variation of the + card game War designed for small samples. The package provides functions like + score_keeper() and play_round() to streamline gameplay and scoring. Once a + predetermined number of rounds concludes, users can employ the analyze_game() + function to derive game results. This function leverages the 'npboottprm' + package's nonparboot() to report nbpr results and, for comparative analysis, + also reports results from the 'stats' package's t.test() function. Additionally, + 'bootwar' features an interactive 'shiny' web application, bootwar(). This + offers a user-centric interface to experience Boot War, enhancing understanding + of nbpr methods across various distributions, sample sizes, number of bootstrap + resamples, and confidence intervals. + date_publication: '2023-10-01' + bug_reports: https://github.com/mightymetrika/bootwar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bootwar + url_git: https://github.com/mightymetrika/bootwar +BootWPTOS: + version: 1.2.1 + title: Test Stationarity using Bootstrap Wavelet Packet Tests + maintainer: Guy Nason + description: |- + Provides significance tests for second-order stationarity + for time series using bootstrap wavelet packet tests. + Provides functionality to visualize the time series with + the results of the hypothesis tests superimposed. + The methodology is described in Cardinali, A and Nason, G P (2016) + "Practical powerful wavelet packet tests for second-order stationarity." + Applied and Computational Harmonic Analysis, 44, 558-585 + . + date_publication: '2022-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BootWPTOS + url_git: '' +Boptbd: + version: 1.0.5 + title: Bayesian Optimal Block Designs + maintainer: Dibaba Bayisa Gemechu + description: |- + Computes Bayesian A- and D-optimal block designs under the linear mixed effects model settings + using block/array exchange algorithm of Debusho, Gemechu and Haines (2018) where the interest is in a + comparison of all possible elementary treatment contrasts. The package also provides an optional + method of using the graphical user interface (GUI) R package 'tcltk' to ensure that it is user friendly. + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Boptbd + url_git: '' +bor: + version: 0.1.0 + title: Transforming Behavioral Observation Records into Data Matrices + maintainer: David N Sousa + description: |- + Transforms focal observations' data, where different types of social interactions + can be recorded by multiple observers, into asymmetric data matrices. + Each cell in these matrices provides counts on the number of times + a specific type of social interaction was initiated by the row subject and + directed to the column subject. + date_publication: '2018-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bor + url_git: '' +boral: + version: 2.0.2 + title: Bayesian Ordination and Regression AnaLysis + maintainer: Francis K.C. Hui + description: 'Bayesian approaches for analyzing multivariate data in ecology. Estimation + is performed using Markov Chain Monte Carlo (MCMC) methods via Three. JAGS types + of models may be fitted: 1) With explanatory variables only, boral fits independent + column Generalized Linear Models (GLMs) to each column of the response matrix; + 2) With latent variables only, boral fits a purely latent variable model for model-based + unconstrained ordination; 3) With explanatory and latent variables, boral fits + correlated column GLMs with latent variables to account for any residual correlation + between the columns of the response matrix.' + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boral + url_git: '' +borrowr: + version: 0.2.0 + title: Estimate Causal Effects with Borrowing Between Data Sources + maintainer: Jeffrey A. Boatman + description: |- + Estimate population average treatment effects from a primary data source + with borrowing from supplemental sources. Causal estimation is done with either a + Bayesian linear model or with Bayesian additive regression trees (BART) to adjust + for confounding. Borrowing is done with multisource exchangeability models (MEMs). For + information on BART, see Chipman, George, & McCulloch (2010) . + For information on MEMs, see Kaizer, Koopmeiners, & + Hobbs (2018) . + date_publication: '2020-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=borrowr + url_git: '' +Boruta: + version: 8.0.0 + title: Wrapper Algorithm for All Relevant Feature Selection + maintainer: Miron Bartosz Kursa + description: |- + An all relevant feature selection wrapper algorithm. + It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows). + date_publication: '2022-11-12' + bug_reports: https://gitlab.com/mbq/Boruta/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Boruta + url_git: https://gitlab.com/mbq/Boruta/ +bosfr: + version: 0.1.0 + title: Computes Exact Bounds of Spearman's Footrule with Missing Data + maintainer: Yijin Zeng + description: Computes exact bounds of Spearman's footrule in the presence of missing + data, and performs independence test based on the bounds with controlled Type + I error regardless of the values of missing data. Suitable only for distinct, + univariate data where no ties is allowed. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bosfr + url_git: '' +BosonSampling: + version: 0.1.5 + title: Classical Boson Sampling + maintainer: Raphaël Clifford + description: |- + Classical Boson Sampling using the algorithm of + Clifford and Clifford (2017) . Also provides functions for + generating random unitary matrices, evaluation of matrix permanents (both + real and complex) and evaluation of complex permanent minors. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BosonSampling + url_git: '' +BoSSA: + version: '3.7' + title: A Bunch of Structure and Sequence Analysis + maintainer: Pierre Lefeuvre + description: Reads and plots phylogenetic placements. + date_publication: '2020-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoSSA + url_git: '' +bossR: + version: 1.0.4 + title: Biomarker Optimal Segmentation System + maintainer: Xuekui Zhang + description: The Biomarker Optimal Segmentation System R package, 'bossR', is designed + for precision medicine, helping to identify individual traits using biomarkers. + It focuses on determining the most effective cutoff value for a continuous biomarker, + which is crucial for categorizing patients into two groups with distinctly different + clinical outcomes. The package simultaneously finds the optimal cutoff from given + candidate values and tests its significance. Simulation studies demonstrate that + 'bossR' offers statistical power and false positive control non-inferior to the + permutation approach (considered the gold standard in this field), while being + hundreds of times faster. + date_publication: '2024-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bossR + url_git: '' +BOSSreg: + version: 0.2.0 + title: Best Orthogonalized Subset Selection (BOSS) + maintainer: Sen Tian + description: 'Best Orthogonalized Subset Selection (BOSS) is a least-squares (LS) + based subset selection method, that performs best subset selection upon an orthogonalized + basis of ordered predictors, with the computational effort of a single ordinary + LS fit. This package provides a highly optimized implementation of BOSS and estimates + a heuristic degrees of freedom for BOSS, which can be plugged into an information + criterion (IC) such as AICc in order to select the subset from candidates. It + provides various choices of IC, including AIC, BIC, AICc, Cp and GCV. It also + implements the forward stepwise selection (FS) with no additional computational + cost, where the subset of FS is selected via cross-validation (CV). CV is also + an option for BOSS. For details see: Tian, Hurvich and Simonoff (2021), "On the + Use of Information Criteria for Subset Selection in Least Squares Regression", + .' + date_publication: '2021-03-06' + bug_reports: https://github.com/sentian/BOSSreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BOSSreg + url_git: https://github.com/sentian/BOSSreg +botor: + version: 0.4.1 + title: '''AWS Python SDK'' (''boto3'') for R' + maintainer: Gergely Daróczi + description: Fork-safe, raw access to the 'Amazon Web Services' ('AWS') 'SDK' via + the 'boto3' 'Python' module, and convenient helper functions to query the 'Simple + Storage Service' ('S3') and 'Key Management Service' ('KMS'), partial support + for 'IAM', the 'Systems Manager Parameter Store' and 'Secrets Manager'. + date_publication: '2025-01-24' + bug_reports: https://github.com/daroczig/botor/issues + url: https://daroczig.github.io/botor/ + url_cran: https://CRAN.R-project.org/package=botor + url_git: '' +BoundaryStats: + version: 2.2.0 + title: Boundary Overlap Statistics + maintainer: Amy Luo + description: 'Analysis workflow for finding geographic boundaries of ecological + or landscape traits and comparing the placement of geographic boundaries of two + traits. If data are trait values, trait data are transformed to boundary intensities + based on approximate first derivatives across latitude and longitude. The package + includes functions to create custom null models based on the input data. The boundary + statistics are described in: Fortin, Drapeau, and Jacquez (1996) .' + date_publication: '2024-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BoundaryStats + url_git: '' +BoundEdgeworth: + version: 0.1.2.1 + title: Bound on the Error of the First-Order Edgeworth Expansion + maintainer: Alexis Derumigny + description: |- + Computes uniform bounds on the distance between + the cumulative distribution function of a standardized sum + of random variables and its first-order Edgeworth expansion, + following the article Derumigny, Girard, Guyonvarch (2021) + . + date_publication: '2023-06-16' + bug_reports: https://github.com/AlexisDerumigny/BoundEdgeworth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BoundEdgeworth + url_git: '' +boundingbox: + version: 1.0.1 + title: Create a Bounding Box in an Image + maintainer: David Stomski + description: |- + Generate ground truth cases for object localization algorithms. + Cycle through a list of images, select points around which to generate bounding + boxes and assign classifiers. Output the coordinates, and images annotated with + boxes and labels. For an example study that uses bounding boxes for image + localization and classification see Ibrahim, Badr, Abdallah, and Eissa (2012) + "Bounding Box Object Localization Based on Image Superpixelization" + . + date_publication: '2020-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boundingbox + url_git: +boussinesq: + version: 1.0.6 + title: Analytic Solutions for (Ground-Water) Boussinesq Equation + maintainer: Emanuele Cordano + description: |- + A collection of R functions were implemented + from published and available analytic solutions for the + One-Dimensional Boussinesq Equation (ground-water). In + particular, the function "beq.lin()" is the analytic solution of + the linearized form of Boussinesq Equation between two + different head-based boundary (Dirichlet) conditions; + "beq.song" is the non-linear power-series analytic solution of + the motion of a wetting front over a dry bedrock (Song at al, + 2007, see complete reference on function documentation). + Bugs/comments/questions/collaboration of any kind are warmly + welcomed. + date_publication: '2023-08-28' + bug_reports: '' + url: https://agupubs.onlinelibrary.wiley.com/doi/10.1002/wrcr.20072 + url_cran: https://CRAN.R-project.org/package=boussinesq + url_git: https://github.com/ecor/boussinesq +boutliers: + version: 1.1-2 + title: Outlier Detection and Influence Diagnostics for Meta-Analysis + maintainer: Hisashi Noma + description: Computational tools for outlier detection and influence diagnostics + of meta-analysis. Bootstrap distributions of the influence statistics are calculated, + and the thresholds to determine outliers are explicitly provided. + date_publication: '2023-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boutliers + url_git: '' +BoutrosLab.plotting.general: + version: 7.1.2 + title: Functions to Create Publication-Quality Plots + maintainer: Paul Boutros + description: 'Contains several plotting functions such as barplots, scatterplots, + heatmaps, as well as functions to combine plots and assist in the creation of + these plots. These functions will give users great ease of use and customization + options in broad use for biomedical applications, as well as general purpose plotting. + Each of the functions also provides valid default settings to make plotting data + more efficient and producing high quality plots with standard colour schemes simpler. + All functions within this package are capable of producing plots that are of the + quality to be presented in scientific publications and journals. P''ng et al.; + BPG: Seamless, automated and interactive visualization of scientific data; BMC + Bioinformatics 2019 .' + date_publication: '2024-10-04' + bug_reports: https://github.com/uclahs-cds/package-BoutrosLab-plotting-general/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BoutrosLab.plotting.general + url_git: https://github.com/uclahs-cds/package-BoutrosLab-plotting-general +box: + version: 1.2.0 + title: Write Reusable, Composable and Modular R Code + maintainer: Konrad Rudolph + description: |- + A modern module system for R. Organise code into hierarchical, + composable, reusable modules, and use it effortlessly across projects via a + flexible, declarative dependency loading syntax. + date_publication: '2024-02-06' + bug_reports: https://github.com/klmr/box/issues + url: https://klmr.me/box/ + url_cran: https://CRAN.R-project.org/package=box + url_git: https://github.com/klmr/box +box.linters: + version: 0.10.5 + title: Linters for 'box' Modules + maintainer: Ricardo Rodrigo Basa + description: |- + Static code analysis of 'box' modules. + The package enhances code quality by providing linters that check for common issues, + enforce best practices, and ensure consistent coding standards. + date_publication: '2024-09-10' + bug_reports: '' + url: https://appsilon.github.io/box.linters/ + url_cran: https://CRAN.R-project.org/package=box.linters + url_git: https://github.com/Appsilon/box.linters +box.lsp: + version: 0.1.3 + title: Provides 'box' Compatibility for 'languageserver' + maintainer: Ricardo Rodrigo Basa + description: |- + A 'box' compatible custom language parser for the 'languageserver' package to provide + completion and signature hints in code editors. + date_publication: '2024-09-19' + bug_reports: https://github.com/Appsilon/box.lsp/issues + url: https://appsilon.github.io/box.lsp/ + url_cran: https://CRAN.R-project.org/package=box.lsp + url_git: https://github.com/Appsilon/box.lsp +boxcoxmix: + version: '0.46' + title: |- + Box-Cox-Type Transformations for Linear and Logistic Models with + Random Effects + maintainer: Iago Giné-Vázquez + description: Box-Cox-type transformations for linear and logistic models with random + effects using non-parametric profile maximum likelihood estimation, as introduced + in Almohaimeed (2018) and Almohaimeed and Einbeck + (2022) . The main functions are 'optim.boxcox()' + for linear models with random effects and 'boxcoxtype()' for logistic models with + random effects. + date_publication: '2024-08-21' + bug_reports: https://gitlab.com/iagogv/boxcoxmix/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boxcoxmix + url_git: https://gitlab.com/iagogv/boxcoxmix +boxfilter: + version: '0.2' + title: Filter Noisy Data + maintainer: Thomas Ruf + description: Noise filter based on determining the proportion of neighboring points. + A false point will be rejected if it has only few neighbors, but accepted if the + proportion of neighbors in a rectangular frame is high. The size of the rectangular + frame as well as the cut-off value, i.e. of a minimum proportion of neighbor-points, + may be supplied or can be calculated automatically. Originally designed for the + cleaning of heart rates, but suitable for filtering any slowly-changing physiological + variable.For more information see Signer (2010). + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boxfilter + url_git: '' +boxly: + version: 0.1.1 + title: Interactive Box Plot + maintainer: Benjamin Wang + description: Interactive box plot using 'plotly' for clinical trial analysis. + date_publication: '2023-10-24' + bug_reports: https://github.com/Merck/boxly/issues + url: https://merck.github.io/boxly/ + url_cran: https://CRAN.R-project.org/package=boxly + url_git: https://github.com/Merck/boxly +boxplotcluster: + version: '0.3' + title: Clustering Method Based on Boxplot Statistics + maintainer: Gianmarco Alberti + description: 'Following Arroyo-Maté-Roque (2006), the function calculates the distance + between rows or columns of the dataset using the generalized Minkowski metric + as described by Ichino-Yaguchi (1994). The distance measure gives more weight + to differences between quartiles than to differences between extremes, making + it less sensitive to outliers. Further,the function calculates the silhouette + width (Rousseeuw 1987) for different numbers of clusters and selects the number + of clusters that maximizes the average silhouette width, unless a specific number + of clusters is provided by the user. The approach implemented in this package + is based on the following publications: Rousseeuw (1987) ; + Ichino-Yaguchi (1994) ; Arroyo-Maté-Roque (2006) .' + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boxplotcluster + url_git: '' +boxplotdbl: + version: 1.4.0 + title: Double Box Plot for Two-Axes Correlation + maintainer: Shinichiro Tomizono + description: |- + Correlation chart of two set (x and y) of data. + Using Quartiles with boxplot style. + Visualize the effect of factor. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=boxplotdbl + url_git: '' +boxr: + version: 0.3.6 + title: Interface for the 'Box.com API' + maintainer: Ian Lyttle + description: |- + An R interface for the remote file hosting service 'Box' + (). In addition to uploading and downloading files, + this package includes functions which mirror base R operations for local + files, (e.g. box_load(), box_save(), box_read(), box_setwd(), etc.), as well + as 'git' style functions for entire directories (e.g. box_fetch(), + box_push()). + date_publication: '2021-01-19' + bug_reports: https://github.com/r-box/boxr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=boxr + url_git: https://github.com/r-box/boxr/ +bp: + version: 2.1.0 + title: Blood Pressure Analysis in R + maintainer: John Schwenck + description: A comprehensive package to aid in the analysis of blood pressure data + of all forms by providing both descriptive and visualization tools for researchers. + date_publication: '2022-05-10' + bug_reports: https://github.com/johnschwenck/bp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bp + url_git: https://github.com/johnschwenck/bp +bpa: + version: 0.1.1 + title: Basic Pattern Analysis + maintainer: Brandon Greenwell + description: |- + Run basic pattern analyses on character sets, digits, or combined + input containing both characters and numeric digits. Useful for data + cleaning and for identifying columns containing multiple or nonstandard + formats. + date_publication: '2016-04-04' + bug_reports: https://github.com/bgreenwell/bpa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bpa + url_git: https://github.com/bgreenwell/bpa +bpAcc: + version: 0.0-2 + title: |- + Blood Pressure Device Accuracy Evaluation: Statistical + Considerations + maintainer: Victor Miranda + description: |- + A comprehensive statistical analysis of the accuracy of blood + pressure devices based on the method of AAMI/ANSI SP10 standards + developed by the AAMI Sphygmomanometer Committee for indirect + measurement of blood pressure, incorporated into IS0 81060-2. The + 'bpAcc' package gives the exact probability 'of accepting a device D' + derived from the join distribution of the sample standard deviation + and a non-linear transformation of the sample mean for a specified + sample size introduced by Chandel et al. (2023) and by the Association + for the Advancement of Medical Instrumentation (2003, ISBN:1-57020-183-8). + date_publication: '2024-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpAcc + url_git: '' +bpbounds: + version: 0.1.6 + title: |- + Nonparametric Bounds for the Average Causal Effect Due to Balke + and Pearl and Extensions + maintainer: Tom Palmer + description: |- + Implementation of the nonparametric bounds for the average + causal effect under an instrumental variable model by Balke and Pearl + (Bounds on Treatment Effects from Studies with Imperfect Compliance, + JASA, 1997, 92, 439, 1171-1176, ). The package + can calculate bounds for a binary outcome, a binary + treatment/phenotype, and an instrument with either 2 or 3 categories. + The package implements bounds for situations where these 3 variables + are measured in the same dataset (trivariate data) or where the + outcome and instrument are measured in one study and the + treatment/phenotype and instrument are measured in another study + (bivariate data). + date_publication: '2024-06-13' + bug_reports: https://github.com/remlapmot/bpbounds/issues + url: https://remlapmot.github.io/bpbounds/ + url_cran: https://CRAN.R-project.org/package=bpbounds + url_git: https://github.com/remlapmot/bpbounds +bpca: + version: 1.3-6 + title: |- + Biplot of Multivariate Data Based on Principal Components + Analysis + maintainer: José C. Faria + description: |- + Implements biplot (2d and 3d) of multivariate data based + on principal components analysis and diagnostic tools of the quality of the reduction. + date_publication: '2023-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpca + url_git: '' +bpcp: + version: 1.4.2 + title: Beta Product Confidence Procedure for Right Censored Data + maintainer: Michael P. Fay + description: Calculates nonparametric pointwise confidence intervals for the survival + distribution for right censored data, and for medians [Fay and Brittain ]. + Has two-sample tests for dissimilarity (e.g., difference, ratio or odds ratio) + in survival at a fixed time, and differences in medians [Fay, Proschan, and Brittain + ]. Basically, the package gives exact inference methods + for one- and two-sample exact inferences for Kaplan-Meier curves (e.g., generalizing + Fisher's exact test to allow for right censoring), which are especially important + for latter parts of the survival curve, small sample sizes or heavily censored + data. Includes mid-p options. + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpcp + url_git: '' +bpDir: + version: 0.1.2 + title: Boxplots for Directional Data + maintainer: Davide Buttarazzi + description: Functions for drawing boxplots for data on (the boundary of) a unit + circle (i.e., circular and axial data), from Buttarazzi D., Pandolfo G., Porzio + G.C. (2018) . + date_publication: '2021-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpDir + url_git: '' +bpgmm: + version: 1.0.9 + title: |- + Bayesian Model Selection Approach for Parsimonious Gaussian + Mixture Models + maintainer: Yaoxiang Li + description: |- + Model-based clustering using Bayesian parsimonious Gaussian mixture models. + MCMC (Markov chain Monte Carlo) are used for parameter estimation. The RJMCMC (Reversible-jump Markov chain Monte Carlo) is used for model selection. + GREEN et al. (1995) . + date_publication: '2022-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpgmm + url_git: '' +bplsr: + version: 1.0.3 + title: Bayesian partial least squares regression + maintainer: Szymon Urbas + description: |- + Fits the Bayesian partial least squares regression model + introduced in Urbas et al. (2024) . Suitable + for univariate and multivariate regression with high-dimensional data. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bplsr + url_git: '' +BPM: + version: 1.0.0 + title: Bayesian Purity Model to Estimate Tumor Purity + maintainer: Jianzhao Gao and Xiaodan Fan + description: |- + Bayesian purity model to estimate tumor purity using methylation + array data (DNA methylation Infinium 450K array data) without reference samples. + date_publication: '2018-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BPM + url_git: '' +bpmnR: + version: 0.1.1 + title: Support for BPMN (Business Process Management Notation) Models + maintainer: Gert Janssenswillen + description: Creating, rendering and writing BPMN diagrams . + Functionalities can be used to visualize and export BPMN diagrams created using + the 'pm4py' and 'bupaRminer' packages. Part of the 'bupaR' ecosystem. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpmnR + url_git: '' +bpmnVisualizationR: + version: 0.5.0 + title: Visualize Process Execution Data on 'BPMN' Diagrams + maintainer: Celine Souchet + description: To visualize the execution data of the processes on 'BPMN' (Business + Process Model and Notation) diagrams, using overlays, style customization and + interactions, with the 'bpmn-visualization' 'TypeScript' library. + date_publication: '2023-09-18' + bug_reports: https://github.com/process-analytics/bpmn-visualization-R/issues/ + url: https://process-analytics.github.io/bpmn-visualization-R/ + url_cran: https://CRAN.R-project.org/package=bpmnVisualizationR + url_git: https://github.com/process-analytics/bpmn-visualization-R/ +bpnreg: + version: 2.0.3 + title: Bayesian Projected Normal Regression Models for Circular Data + maintainer: Jolien Cremers + description: |- + Fitting Bayesian multiple and mixed-effect regression models for + circular data based on the projected normal distribution. Both continuous + and categorical predictors can be included. Sampling from the posterior is + performed via an MCMC algorithm. Posterior descriptives of all parameters, + model fit statistics and Bayes factors for hypothesis tests for inequality + constrained hypotheses are provided. See Cremers, Mulder & Klugkist (2018) + and Nuñez-Antonio & Guttiérez-Peña (2014) + . + date_publication: '2024-01-15' + bug_reports: https://github.com/joliencremers/bpnreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bpnreg + url_git: https://github.com/joliencremers/bpnreg +bpp: + version: 1.0.6 + title: Computations Around Bayesian Predictive Power + maintainer: Kaspar Rufibach + description: Implements functions to update Bayesian Predictive Power Computations + after not stopping a clinical trial at an interim analysis. Such an interim analysis + can either be blinded or unblinded. Code is provided for Normally distributed + endpoints with known variance, with a prominent example being the hazard ratio. + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpp + url_git: '' +bpr: + version: 1.0.8 + title: Fitting Bayesian Poisson Regression + maintainer: Laura D'Angelo + description: Posterior sampling and inference for Bayesian Poisson regression models. + The model specification makes use of Gaussian (or conditionally Gaussian) prior + distributions on the regression coefficients. Details on the algorithm are found + in D'Angelo and Canale (2023) . + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bpr + url_git: '' +BPrinStratTTE: + version: 0.0.7 + title: |- + Causal Effects in Principal Strata Defined by Antidrug + Antibodies + maintainer: Christian Stock + description: |- + Bayesian models to estimate causal effects of biological + treatments on time-to-event endpoints in clinical trials with principal + strata defined by the occurrence of antidrug antibodies. + The methodology is based on Frangakis and Rubin (2002) + and Imbens and Rubin (1997) + , and here adapted to a specific + time-to-event setting. + date_publication: '2024-04-13' + bug_reports: https://github.com/Boehringer-Ingelheim/BPrinStratTTE/issues + url: https://boehringer-ingelheim.github.io/BPrinStratTTE/ + url_cran: https://CRAN.R-project.org/package=BPrinStratTTE + url_git: https://github.com/Boehringer-Ingelheim/BPrinStratTTE +bqror: + version: 1.7.1 + title: Bayesian Quantile Regression for Ordinal Models + maintainer: Prajual Maheshwari + description: |- + Package provides functions for estimation and inference in Bayesian quantile regression with ordinal outcomes. An ordinal model with 3 or more outcomes (labeled OR1 model) is estimated by a combination of Gibbs sampling and Metropolis-Hastings (MH) algorithm. Whereas an ordinal model with exactly 3 outcomes (labeled OR2 model) is estimated using a Gibbs sampling algorithm. The summary output presents the posterior mean, posterior standard deviation, 95% credible intervals, and the inefficiency factors along with the two model comparison measures – logarithm of marginal likelihood and the deviance information criterion (DIC). The package also provides functions for computing the covariate effects and other functions that aids either the estimation or inference in quantile ordinal models. + Rahman, M. A. (2016).“Bayesian Quantile Regression for Ordinal Models.” Bayesian Analysis, 11(1): 1-24 . + Yu, K., and Moyeed, R. A. (2001). “Bayesian Quantile Regression.” Statistics and Probability Letters, 54(4): 437–447 . + Koenker, R., and Bassett, G. (1978).“Regression Quantiles.” Econometrica, 46(1): 33-50 . + Chib, S. (1995). “Marginal likelihood from the Gibbs output.” Journal of the American Statistical Association, 90(432):1313–1321, 1995. . + Chib, S., and Jeliazkov, I. (2001). “Marginal likelihood from the Metropolis-Hastings output.” Journal of the American Statistical Association, 96(453):270–281, 2001. . + date_publication: '2024-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bqror + url_git: https://github.com/prajual/bqror +bqtl: + version: 1.0-38 + title: Bayesian QTL Mapping Toolkit + maintainer: Charles C. Berry + description: |- + QTL mapping toolkit for inbred crosses and recombinant + inbred lines. Includes maximum likelihood and Bayesian tools. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bqtl + url_git: '' +bRacatus: + version: 2.0.0 + title: |- + A Method to Estimate the Accuracy and Biogeographical Status of + Georeferenced Biological Data + maintainer: Eduardo Arlé + description: 'Automated assessment of accuracy and geographical status of georeferenced + biological data. The methods rely on reference regions, namely checklists and + range maps. Includes functions to obtain data from the Global Biodiversity Information + Facility and from the Global Inventory of Floras and Traits + . Alternatively, the user can input their + own data. Furthermore, provides easy visualisation of the data and the results + through the plotting functions. Especially suited for large datasets. The reference + for the methodology is: Arlé et al. (under review).' + date_publication: '2024-05-03' + bug_reports: https://github.com/EduardoArle/bRacatus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bRacatus + url_git: https://github.com/EduardoArle/bRacatus +BRACE: + version: 0.1.0 + title: Bias Reduction Through Analysis of Competing Events (BRACE) + maintainer: Tuo Lin + description: |- + Adjusting the bias due to residual confounding (often called + treatment selection bias) in estimating the treatment effect in a + proportional hazard model, as described in Williamson et al. + (2022) . + date_publication: '2023-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BRACE + url_git: '' +bracer: + version: 1.2.2 + title: Brace Expansions + maintainer: Trevor L Davis + description: Performs brace expansions on strings. Made popular by Unix shells, + brace expansion allows users to concisely generate certain character vectors by + taking a single string and (recursively) expanding the comma-separated lists and + double-period-separated integer and character sequences enclosed within braces + in that string. The double-period-separated numeric integer expansion also supports + padding the resulting numbers with zeros. + date_publication: '2023-03-15' + bug_reports: https://github.com/trevorld/bracer/issues + url: https://trevorldavis.com/R/bracer/ + url_cran: https://CRAN.R-project.org/package=bracer + url_git: https://github.com/trevorld/bracer +BRACoD.R: + version: 0.0.2.0 + title: 'BRACoD: Bayesian Regression Analysis of Compositional Data' + maintainer: Adrian Verster + description: The goal of this method is to identify associations between bacteria + and an environmental variable in 16S or other compositional data. The environmental + variable is any variable which is measure for each microbiome sample, for example, + a butyrate measurement paired with every sample in the data. Microbiome data is + compositional, meaning that the total abundance of each sample sums to 1, and + this introduces severe statistical distortions. This method takes a Bayesian approach + to correcting for these statistical distortions, in which the total abundance + is treated as an unknown variable. This package runs the python implementation + using reticulate. + date_publication: '2022-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BRACoD.R + url_git: '' +brada: + version: '1.0' + title: Bayesian Response-Adaptive Design Analysis + maintainer: Riko Kelter + description: Provides access to a range of functions for analyzing, applying and + visualizing Bayesian response-adaptive trial designs for a binary endpoint. Includes + the predictive probability approach and the predictive evidence value designs + for binary endpoints. + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brada + url_git: '' +BradleyTerry2: + version: 1.1-2 + title: Bradley-Terry Models + maintainer: Heather Turner + description: Specify and fit the Bradley-Terry model, including structured versions + in which the parameters are related to explanatory variables through a linear + predictor and versions with contest-specific effects, such as a home advantage. + date_publication: '2020-02-03' + bug_reports: https://github.com/hturner/BradleyTerry2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BradleyTerry2 + url_git: https://github.com/hturner/BradleyTerry2 +braggR: + version: 0.1.1 + title: Calculate the Revealed Aggregator of Probability Predictions + maintainer: Ville Satopää + description: |2- + + Forecasters predicting the chances of a future event may disagree due to + differing evidence or noise. To harness the collective evidence of the crowd, + Ville Satopää (2021) "Regularized Aggregation of One-off Probability Predictions" + proposes a Bayesian + aggregator that is regularized by analyzing the forecasters' disagreement and ascribing + over-dispersion to noise. This aggregator requires no user intervention and can be computed + efficiently even for a large numbers of predictions. The author evaluates + the aggregator on subjective probability predictions collected during + a four-year forecasting tournament sponsored by the US intelligence community. + The aggregator improves the accuracy of simple averaging by around 20% and + other state-of-the-art aggregators by 10-25%. The advantage stems almost + exclusively from improved calibration. This aggregator -- know as "the revealed + aggregator" -- inputs a) forecasters' probability predictions (p) of a future binary event + and b) the forecasters' common prior (p0) of the future event. In this R-package, + the function sample_aggregator(p,p0,...) allows the user to calculate the revealed + aggregator. Its use is illustrated with a simple example. + date_publication: '2021-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=braggR + url_git: '' +braidReports: + version: 1.0.1 + title: |- + Visualize Combined Action Response Surfaces and Report BRAID + Analyses + maintainer: Nathaniel R. Twarog + description: |- + Provides functions to visualize combined action data in 'ggplot2'. + Also provides functions for producing full BRAID analysis reports with + custom layouts and aesthetics, using the BRAID method originally described + in Twarog et al. (2016) . + date_publication: '2024-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=braidReports + url_git: '' +braidrm: + version: 1.0.3 + title: Fitting Combined Action with the BRAID Response Surface Model + maintainer: Nathaniel R. Twarog + description: |- + Contains functions for evaluating, analyzing, and fitting combined + action dose response surfaces with the Bivariate Response to Additive + Interacting Doses (BRAID) model of combined action, along with tools for + implementing other combination analysis methods, including Bliss independence, + combination index, and additional response surface methods. + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=braidrm + url_git: '' +braids: + version: 1.0.0 + title: The Braid Groups + maintainer: Stéphane Laurent + description: |- + Deals with the braid groups. Includes creation of some + specific braids, group operations, free reduction, and Bronfman + polynomials. Braid theory has applications in fluid mechanics and + quantum physics. The code is adapted from the 'Haskell' library + 'combinat', and is based on Birman and Brendle (2005) + . + date_publication: '2024-04-28' + bug_reports: https://github.com/stla/braids/issues + url: '' + url_cran: https://CRAN.R-project.org/package=braids + url_git: https://github.com/stla/braids +BrailleR: + version: 1.0.2 + title: Improved Access for Blind Users + maintainer: A. Jonathan R. Godfrey + description: |- + Blind users do not have access to the graphical output from R + without printing the content of graphics windows to an embosser of + some kind. This is not as immediate as is required for efficient + access to statistical output. The functions here are created so that + blind people can make even better use of R. This includes the text + descriptions of graphs, convenience functions to replace the + functionality offered in many GUI front ends, and experimental + functionality for optimising graphical content to prepare it for + embossing as tactile images. + date_publication: '2023-07-10' + bug_reports: https://github.com/ajrgodfrey/BrailleR/issues + url: http://ajrgodfrey.github.io/BrailleR/ + url_cran: https://CRAN.R-project.org/package=BrailleR + url_git: https://github.com/ajrgodfrey/BrailleR +BrainCon: + version: 0.3.0 + title: Inference the Partial Correlations Based on Time Series Data + maintainer: Yunhaonan Yang + description: 'A statistical tool to inference the multi-level partial correlations + based on multi-subject time series data, especially for brain functional connectivity. + It combines both individual and population level inference by using the methods + of Qiu and Zhou. (2021) and Genovese and Wasserman. + (2006). It realizes two reliable estimation methods + of partial correlation coefficients, using scaled lasso and lasso. It can be used + to estimate individual- or population-level partial correlations, identify nonzero + ones, and find out unequal partial correlation coefficients between two populations.' + date_publication: '2023-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BrainCon + url_git: '' +brainGraph: + version: 3.1.0 + title: Graph Theory Analysis of Brain MRI Data + maintainer: Christopher G. Watson + description: |- + A set of tools for performing graph theory analysis of brain MRI + data. It works with data from a Freesurfer analysis (cortical thickness, + volumes, local gyrification index, surface area), diffusion tensor + tractography data (e.g., from FSL) and resting-state fMRI data (e.g., from + DPABI). It contains a graphical user interface for graph visualization and + data exploration, along with several functions for generating useful + figures. + date_publication: '2024-04-04' + bug_reports: https://groups.google.com/forum/?hl=en#!forum/brainGraph-help + url: '' + url_cran: https://CRAN.R-project.org/package=brainGraph + url_git: https://github.com/cwatson/brainGraph +brainKCCA: + version: 0.1.0 + title: |- + Region-Level Connectivity Network Construction via Kernel + Canonical Correlation Analysis + maintainer: Jian Kang + description: It is designed to calculate connection between (among) brain regions + and plot connection lines. Also, the summary function is included to summarize + group-level connectivity network. Kang, Jian (2016) . + date_publication: '2018-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brainKCCA + url_git: '' +brainR: + version: 1.6.0 + title: |- + Helper Functions to 'misc3d' and 'rgl' Packages for Brain + Imaging + maintainer: John Muschelli + description: |- + This includes functions for creating 3D and 4D images using + 'WebGL', 'rgl', and 'JavaScript' commands. + This package relies on the X toolkit ('XTK', + ). + date_publication: '2019-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brainR + url_git: '' +BranchGLM: + version: 3.0.1 + title: |- + Efficient Best Subset Selection for GLMs via Branch and Bound + Algorithms + maintainer: Jacob Seedorff + description: |- + Performs efficient and scalable glm best + subset selection using a novel implementation of a branch and bound algorithm. + To speed up the model fitting process, a range of optimization + methods are implemented in 'RcppArmadillo'. Parallel computation + is available using 'OpenMP'. + date_publication: '2024-09-28' + bug_reports: https://github.com/JacobSeedorff21/BranchGLM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BranchGLM + url_git: https://github.com/JacobSeedorff21/BranchGLM +Branching: + version: 0.9.7 + title: Simulation and Estimation for Branching Processes + maintainer: Camilo Jose Torres-Jimenez + description: Simulation and parameter estimation of multitype Bienayme - Galton + - Watson processes. + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Branching + url_git: '' +brandwatchR: + version: 0.3.0 + title: '''Brandwatch'' API to R' + maintainer: Donal Phipps + description: |- + Interact with the 'Brandwatch' API . + Allows you to authenticate to the API and obtain data for projects, queries, query groups tags and categories. + Also allows you to directly obtain mentions and aggregate data for a specified query or query group. + date_publication: '2018-08-13' + bug_reports: https://github.com/Phippsy/brandwatchR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=brandwatchR + url_git: https://github.com/Phippsy/brandwatchR +brant: + version: 0.3-0 + title: Test for Parallel Regression Assumption + maintainer: Benjamin Schlegel + description: 'Tests the parallel regression assumption wit the brant test by Brant + (1990) for ordinal logit models generated with the function + polr() from the package ''MASS''.' + date_publication: '2020-09-22' + bug_reports: '' + url: https://benjaminschlegel.ch/r/brant/ + url_cran: https://CRAN.R-project.org/package=brant + url_git: '' +braQCA: + version: 1.4.11.27 + title: |- + Bootstrapped Robustness Assessment for Qualitative Comparative + Analysis + maintainer: Burrel Vann Jr + description: |- + Test the robustness of a user's Qualitative Comparative Analysis + solutions to randomness, using the bootstrapped assessment: baQCA(). This + package also includes a function that provides recommendations for improving + solutions to reach typical significance levels: brQCA(). Data included + come from McVeigh et al. (2014) . + date_publication: '2024-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=braQCA + url_git: '' +brassica: + version: 1.0.2 + title: 1970s BASIC Interpreter + maintainer: Mike Lee + description: |- + Executes BASIC programs from the 1970s, for historical and + educational purposes. This enables famous examples of early machine + learning, artificial intelligence, natural language processing, cellular + automata, and so on, to be run in their original form. + date_publication: '2022-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brassica + url_git: '' +bratteli: + version: 1.0.0 + title: Deal with Bratteli Graphs + maintainer: Stéphane Laurent + description: |- + Utilities for Bratteli graphs. A tree is an example of a Bratteli + graph. The package provides a function which generates a 'LaTeX' file + that renders the given Bratteli graph. It also provides functions to + compute the dimensions of the vertices, the intrinsic kernels and the + intrinsic distances. Intrinsic kernels and distances were introduced + by Vershik (2014) . + date_publication: '2023-12-20' + bug_reports: https://github.com/stla/bratteliR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bratteli + url_git: https://github.com/stla/bratteliR +bravo: + version: 3.2.2 + title: Bayesian Screening and Variable Selection + maintainer: Dongjin Li + description: Performs Bayesian variable screening and selection for ultra-high dimensional + linear regression models. + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bravo + url_git: '' +BrazilCrime: + version: 0.2.1 + title: Accesses Brazilian Public Security Data from SINESP Since 2015 + maintainer: Giovanni Vargette + description: Allows access to data from the Brazilian Public Security Information + System (SINESP) by state and municipality. . + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BrazilCrime + url_git: '' +BrazilMet: + version: 0.2.0 + title: |- + Download and Processing of Automatic Weather Stations (AWS) Data + of INMET-Brazil + maintainer: Roberto Filgueiras + description: A compilation of functions to download and processing AWS data of INMET-Brazil, + with the purpose of reference evapotranspiration (ETo) estimation. The package + aims to make meteorological and agricultural data analysis more parsimonious. + date_publication: '2022-10-27' + bug_reports: https://github.com/FilgueirasR/BrazilMet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BrazilMet + url_git: '' +BRBVS: + version: 0.2.1 + title: |- + Variable Selection and Ranking in Copula Survival Models + Affected by General Censoring Scheme + maintainer: Danilo Petti + description: |- + Performs variable selection and ranking based on several measures for the class of copula survival model(s) in high dimensional domain. + The package is based on the class of copula survival model(s) implemented in the 'GJRM' package. + date_publication: '2024-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BRBVS + url_git: '' +BRcal: + version: 1.0.1 + title: Boldness-Recalibration of Binary Events + maintainer: Adeline P. Guthrie + description: Boldness-recalibration maximally spreads out probability predictions + while maintaining a user specified level of calibration, facilitated the brcal() + function. Supporting functions to assess calibration via Bayesian and Frequentist + approaches, Maximum Likelihood Estimator (MLE) recalibration, Linear in Log Odds + (LLO)-adjust via any specified parameters, and visualize results are also provided. + Methodological details can be found in Guthrie & Franck (2024) . + date_publication: '2024-10-14' + bug_reports: https://github.com/apguthrie/BRcal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BRcal + url_git: https://github.com/apguthrie/BRcal +brclimr: + version: 0.2.0 + title: |- + Fetch Zonal Statistics of Weather Indicators for Brazilian + Municipalities + maintainer: Raphael Saldanha + description: |- + Fetches zonal statistics from weather indicators that were calculated for each municipality in Brazil using data from the BR-DWGD and TerraClimate projects. + Zonal statistics such as mean, maximum, minimum, standard deviation, and sum were computed by taking into account the data cells that intersect the boundaries of each municipality and stored in Parquet files. This procedure was carried out for all Brazilian municipalities, and for all available dates, for every indicator available in the weather products (BR-DWGD and TerraClimate projects). This package queries on-line the already calculated statistics on the Parquet files and returns easy-to-use data.frames. + date_publication: '2024-04-04' + bug_reports: '' + url: https://rfsaldanha.github.io/brclimr/ + url_cran: https://CRAN.R-project.org/package=brclimr + url_git: https://github.com/rfsaldanha/brclimr +BRDT: + version: 0.1.0 + title: Binomial Reliability Demonstration Tests + maintainer: Suiyao Chen + description: |- + This is an implementation of design methods for binomial reliability demonstration tests (BRDTs) with failure count data. + The acceptance decision uncertainty of BRDT has been quantified and the impacts of the uncertainty on related reliability assurance activities such as reliability growth (RG) and warranty services (WS) are evaluated. + This package is associated with the work from the published paper "Optimal Binomial Reliability Demonstration Tests Design under Acceptance Decision Uncertainty" by Suiyao Chen et al. (2020) . + date_publication: '2020-06-09' + bug_reports: https://github.com/ericchen12377/BRDT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BRDT + url_git: https://github.com/ericchen12377/BRDT +brea: + version: 0.3.1 + title: Bayesian Recurrent Events Analysis + maintainer: Adam J King + description: Functions to produce MCMC samples for posterior inference in semiparametric + Bayesian discrete time competing risks recurrent events models and multistate + models. + date_publication: '2024-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brea + url_git: '' +bread: + version: 0.4.1 + title: Analyze Big Files Without Loading Them in Memory + maintainer: Vincent Guegan + description: |- + A simple set of wrapper functions for data.table::fread() that allows subsetting or + filtering rows and selecting columns of table-formatted files too large for the available RAM. + 'b stands for 'big files'. + bread makes heavy use of Unix commands like 'grep', 'sed', 'wc', 'awk' and 'cut'. They are available + by default in all Unix environments. + For Windows, you need to install those commands externally in order to simulate a + Unix environment and make sure that the executables are in the Windows PATH variable. + To my knowledge, the simplest ways are to install 'RTools', 'Git' or 'Cygwin'. If they have been + correctly installed (with the expected registry entries), they should be detected on loading + the package and the correct directories will be added automatically to the PATH. + date_publication: '2023-06-26' + bug_reports: https://github.com/MagicHead99/bread/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bread + url_git: https://github.com/MagicHead99/bread/ +BREADR: + version: 1.0.2 + title: |- + Estimates Degrees of Relatedness (Up to the Second Degree) for + Extreme Low-Coverage Data + maintainer: Jono Tuke + description: |- + The goal of the package is to provide an easy-to-use method + for estimating degrees of relatedness (up to the second degree) + for extreme low-coverage data. The package also allows users to + quantify and visualise the level of confidence in the estimated + degrees of relatedness. + date_publication: '2024-09-09' + bug_reports: https://github.com/jonotuke/BREADR/issues + url: https://jonotuke.github.io/BREADR/ + url_cran: https://CRAN.R-project.org/package=BREADR + url_git: https://github.com/jonotuke/BREADR +breakaway: + version: 4.8.4 + title: Species Richness Estimation and Modeling + maintainer: Amy D Willis + description: Understanding the drivers of microbial diversity is an important frontier + of microbial ecology, and investigating the diversity of samples from microbial + ecosystems is a common step in any microbiome analysis. 'breakaway' is the premier + package for statistical analysis of microbial diversity. 'breakaway' implements + the latest and greatest estimates of species richness, described in Willis and + Bunge (2015) , Willis et al. (2017) , + and Willis (2016) , as well as the most commonly used estimates, + including the objective Bayes approach described in Barger and Bunge (2010) . + date_publication: '2022-11-22' + bug_reports: https://github.com/adw96/breakaway/issues + url: https://adw96.github.io/breakaway/ + url_cran: https://CRAN.R-project.org/package=breakaway + url_git: '' +breakDown: + version: 0.2.2 + title: Model Agnostic Explainers for Individual Predictions + maintainer: Przemyslaw Biecek + description: |- + Model agnostic tool for decomposition of predictions from black boxes. + Break Down Table shows contributions of every variable to a final prediction. + Break Down Plot presents variable contributions in a concise graphical way. + This package work for binary classifiers and general regression models. + date_publication: '2024-03-11' + bug_reports: https://github.com/pbiecek/breakDown/issues + url: https://pbiecek.github.io/breakDown/ + url_cran: https://CRAN.R-project.org/package=breakDown + url_git: '' +breakfast: + version: '2.5' + title: |- + Methods for Fast Multiple Change-Point/Break-Point Detection and + Estimation + maintainer: Yining Chen + description: A developing software suite for multiple change-point and change-point-type + feature detection/estimation (data segmentation) in data sequences. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=breakfast + url_git: '' +breakpoint: + version: '1.2' + title: |- + An R Package for Multiple Break-Point Detection via the + Cross-Entropy Method + maintainer: Priyadarshana W.J.R.M. + description: Implements the Cross-Entropy (CE) method, which is a model based stochastic + optimization technique to estimate both the number and their corresponding locations + of break-points in continuous and discrete measurements (Priyadarshana and Sofronov + (2015), Priyadarshana and Sofronov (2012a), Priyadarshana and Sofronov (2012b)). + date_publication: '2016-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=breakpoint + url_git: https://github.com/madawaweer/breakpoint +BreakPoints: + version: '1.2' + title: Identify Breakpoints in Series of Data + maintainer: Santiago I. Hurtado + description: Compute Buishand Range Test, Pettit Test, SNHT, Student t-test, and + Mann-Whitney Rank Test, to identify breakpoints in series. For all functions NA + is allowed. Since all of the mention methods identify only one breakpoint in a + series, a general function to look for N breakpoint is given. Also, the Yamamoto + test for climate jump is available. Alexandersson, H. (1986) , + Buishand, T. (1982) , Hurtado, S. I., Zaninelli, + P. G., & Agosta, E. A. (2020) , Mann, H. B., + Whitney, D. R. (1947) , Pettitt, A. N. (1979) , + Ruxton, G. D., jul (2006) , Yamamoto, R., Iwashima, + T., Kazadi, S. N., & Hoshiai, M. (1985) . + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BreakPoints + url_git: '' +breathtestcore: + version: 0.8.9 + title: Core Functions to Read and Fit 13c Time Series from Breath Tests + maintainer: Dieter Menne + description: |- + Reads several formats of 13C data (IRIS/Wagner, + BreathID) and CSV. Creates artificial sample data for testing. Fits + Maes/Ghoos, Bluck-Coward self-correcting formula using 'nls', 'nlme'. + Methods to fit breath test curves with Bayesian Stan methods are + refactored to package 'breathteststan'. For a Shiny GUI, see package + 'dmenne/breathtestshiny' on github. + date_publication: '2025-01-08' + bug_reports: https://github.com/dmenne/breathtestcore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=breathtestcore + url_git: https://github.com/dmenne/breathtestcore +breathteststan: + version: 0.8.9 + title: Stan-Based Fit to Gastric Emptying Curves + maintainer: Dieter Menne + description: |- + Stan-based curve-fitting function + for use with package 'breathtestcore' by the same author. + Stan functions are refactored here for easier testing. + date_publication: '2025-01-08' + bug_reports: https://github.com/dmenne/breathteststan/issues + url: https://dmenne.github.io/breathteststan/ + url_cran: https://CRAN.R-project.org/package=breathteststan + url_git: https://github.com/dmenne/breathteststan +bReeze: + version: 0.4-4 + title: Functions for Wind Resource Assessment + maintainer: Christian Graul + description: |- + A collection of functions to analyse, visualize and interpret wind data + and to calculate the potential energy production of wind turbines. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bReeze + url_git: https://github.com/chgrl/bReeze +BRETIGEA: + version: 1.0.3 + title: Brain Cell Type Specific Gene Expression Analysis + maintainer: Andrew McKenzie + description: Analysis of relative cell type proportions in bulk gene expression + data. Provides a well-validated set of brain cell type-specific marker genes derived + from multiple types of experiments, as described in McKenzie (2018) . + For brain tissue data sets, there are marker genes available for astrocytes, endothelial + cells, microglia, neurons, oligodendrocytes, and oligodendrocyte precursor cells, + derived from each of human, mice, and combination human/mouse data sets. However, + if you have access to your own marker genes, the functions can be applied to bulk + gene expression data from any tissue. Also implements multiple options for relative + cell type proportion estimation using these marker genes, adapting and expanding + on approaches from the 'CellCODE' R package described in Chikina (2015) . + The number of cell type marker genes used in a given analysis can be increased + or decreased based on your preferences and the data set. Finally, provides functions + to use the estimates to adjust for variability in the relative proportion of cell + types across samples prior to downstream analyses. + date_publication: '2021-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BRETIGEA + url_git: '' +brew: + version: 1.0-10 + title: Templating Framework for Report Generation + maintainer: Greg Hunt + description: |- + Implements a templating framework for mixing text and R code + for report generation. brew template syntax is similar to PHP, Ruby's + erb module, Java Server Pages, and Python's psp module. + date_publication: '2023-12-16' + bug_reports: https://github.com/gregfrog/brew/issues + url: '' + url_cran: https://CRAN.R-project.org/package=brew + url_git: https://github.com/gregfrog/brew +brglm: + version: 0.7.2 + title: Bias Reduction in Binomial-Response Generalized Linear Models + maintainer: Ioannis Kosmidis + description: Fit generalized linear models with binomial responses using either + an adjusted-score approach to bias reduction or maximum penalized likelihood where + penalization is by Jeffreys invariant prior. These procedures return estimates + with improved frequentist properties (bias, mean squared error) that are always + finite even in cases where the maximum likelihood estimates are infinite (data + separation). Fitting takes place by fitting generalized linear models on iteratively + updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility + is provided by the fact that custom pseudo-data representations can be specified + and used for model fitting. Functions are provided for the construction of confidence + intervals for the reduced-bias estimates. + date_publication: '2021-04-22' + bug_reports: https://github.com/ikosmidis/brglm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=brglm + url_git: https://github.com/ikosmidis/brglm +brglm2: + version: 0.9.2 + title: Bias Reduction in Generalized Linear Models + maintainer: Ioannis Kosmidis + description: Estimation and inference from generalized linear models based on various + methods for bias reduction and maximum penalized likelihood with powers of the + Jeffreys prior as penalty. The 'brglmFit' fitting method can achieve reduction + of estimation bias by solving either the mean bias-reducing adjusted score equations + in Firth (1993) and Kosmidis and Firth (2009) , + or the median bias-reduction adjusted score equations in Kenne et al. (2017) , + or through the direct subtraction of an estimate of the bias of the maximum likelihood + estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) + . See Kosmidis et al (2020) + for more details. Estimation in all cases takes place via a quasi Fisher scoring + algorithm, and S3 methods for the construction of of confidence intervals for + the reduced-bias estimates are provided. In the special case of generalized linear + models for binomial and multinomial responses (both ordinal and nominal), the + adjusted score approaches to mean and media bias reduction have been found to + return estimates with improved frequentist properties, that are also always finite, + even in cases where the maximum likelihood estimates are infinite (e.g. complete + and quasi-complete separation; see Kosmidis and Firth, 2020 , + for a proof for mean bias reduction in logistic regression). + date_publication: '2023-10-11' + bug_reports: https://github.com/ikosmidis/brglm2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=brglm2 + url_git: https://github.com/ikosmidis/brglm2 +brickset: + version: 2025.0.0 + title: Interface with the Brickset API for Getting Data About LEGO Sets + maintainer: Jason Bryer + description: |- + Interface with the 'Brickset' API + for + getting data about LEGO sets. Data sets that can be used for teaching + and learning without the need of a 'Brickset' account and API key are + also included. Includes all LEGO since through the end of 2023. + date_publication: '2025-02-25' + bug_reports: https://github.com/jbryer/brickset/issues + url: https://jbryer.github.io/brickset/ + url_cran: https://CRAN.R-project.org/package=brickset + url_git: https://github.com/jbryer/brickset +brickster: + version: 0.2.6 + title: R Toolkit for 'Databricks' + maintainer: Zac Davies + description: |- + Collection of utilities that improve using 'Databricks' from R. + Primarily functions that wrap specific 'Databricks' APIs + (), 'RStudio' connection pane support, quality + of life functions to make 'Databricks' simpler to use. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brickster + url_git: https://github.com/databrickslabs/brickster +bridgedist: + version: 0.1.3 + title: |- + An Implementation of the Bridge Distribution with Logit-Link as + in Wang and Louis (2003) + maintainer: Bruce Swihart + description: |- + An implementation of the bridge distribution with logit-link in + R. In Wang and Louis (2003) , such a univariate + bridge distribution was derived as the distribution of the random intercept that + 'bridged' a marginal logistic regression and a conditional logistic regression. + The conditional and marginal regression coefficients are a scalar multiple + of each other. Such is not the case if the random intercept distribution was + Gaussian. + date_publication: '2024-10-18' + bug_reports: https://github.com/swihart/bridgedist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bridgedist + url_git: https://github.com/swihart/bridgedist +bridger: + version: 0.1.0 + title: Bridge Hand Generator with Criteria Selector + maintainer: Jason Kaplan + description: Produce bridge hands, allowing parameters for hands to offer specific + for bidding sequences. + date_publication: '2021-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bridger + url_git: https://github.com/CommoditiesAI/bridger +bridger2: + version: 0.1.0 + title: Genome-Wide RNA Degradation Analysis Using BRIC-Seq Data + maintainer: Naoto Imamachi + description: |- + BRIC-seq is a genome-wide approach for determining RNA stability in mammalian cells. + This package provides a series of functions for performing quality check of your BRIC-seq data, + calculation of RNA half-life for each transcript and comparison of RNA half-lives between two conditions. + date_publication: '2016-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bridger2 + url_git: '' +bridgesampling: + version: 1.1-2 + title: Bridge Sampling for Marginal Likelihoods and Bayes Factors + maintainer: Quentin F. Gronau + description: |- + Provides functions for estimating marginal likelihoods, Bayes + factors, posterior model probabilities, and normalizing constants in general, + via different versions of bridge sampling (Meng & Wong, 1996, + ). + Gronau, Singmann, & Wagenmakers (2020) . + date_publication: '2021-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bridgesampling + url_git: https://github.com/quentingronau/bridgesampling +bridgr: + version: 0.1.1 + title: Bridging Data Frequencies for Timely Economic Forecasts + maintainer: Marc Burri + description: Implements bridge models for nowcasting and forecasting macroeconomic + variables by linking high-frequency indicator variables (e.g., monthly data) to + low-frequency target variables (e.g., quarterly GDP). Simplifies forecasting and + aggregating indicator variables to match the target frequency, enabling timely + predictions ahead of official data releases. For more on bridge models, see Baffigi, + A., Golinelli, R., & Parigi, G. (2004) , Burri + (2023) or Schumacher (2016) + . + date_publication: '2024-12-13' + bug_reports: https://github.com/marcburri/bridgr/issues + url: https://marcburri.github.io/bridgr/ + url_cran: https://CRAN.R-project.org/package=bridgr + url_git: https://github.com/marcburri/bridgr +brif: + version: 1.4.1 + title: A Tree and Forest Tool for Classification and Regression + maintainer: Yanchao Liu + description: Build decision trees and random forests for classification and regression. + The implementation strikes a balance between minimizing computing efforts and + maximizing the expected predictive accuracy, thus scales well to large data sets. + Multi-threading is available through 'OpenMP' . + date_publication: '2023-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brif + url_git: '' +briKmeans: + version: '1.0' + title: |- + Package for Brik, Fabrik and Fdebrik Algorithms to Initialise + Kmeans + maintainer: Aurora Torrente + description: |- + Implementation of the BRIk, FABRIk and FDEBRIk algorithms + to initialise k-means. These methods are intended for the + clustering of multivariate and functional data, respectively. + They make use of the Modified Band Depth and bootstrap to + identify appropriate initial seeds for k-means, which are + proven to be better options than many techniques in the + literature. Torrente and Romo (2021) + It makes use of the functions kma and kma.similarity, from the + archived package fdakma, by Alice Parodi et al. + date_publication: '2022-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=briKmeans + url_git: '' +BRINDA: + version: 0.1.5 + title: |- + Computation of BRINDA Adjusted Micronutrient Biomarkers for + Inflammation + maintainer: Hanqi Luo + description: Inflammation can affect many micronutrient biomarkers and can thus + lead to incorrect diagnosis of individuals and to over- or under-estimate the + prevalence of deficiency in a population. Biomarkers Reflecting Inflammation and + Nutritional Determinants of Anemia (BRINDA) is a multi-agency and multi-country + partnership designed to improve the interpretation of nutrient biomarkers in settings + of inflammation and to generate context-specific estimates of risk factors for + anemia (Suchdev (2016) ). In the past few years, BRINDA + published a series of papers to provide guidance on how to adjust micronutrient + biomarkers, retinol binding protein, serum retinol, serum ferritin by Namaste + (2020), soluble transferrin receptor (sTfR), serum zinc, serum and Red Blood Cell + (RBC) folate, and serum B-12, using inflammation markers, alpha-1-acid glycoprotein + (AGP) and/or C-Reactive Protein (CRP) by Namaste (2020) , + Rohner (2017) , McDonald (2020) , + and Young (2020) . The BRINDA inflammation adjustment + method mainly focuses on Women of Reproductive Age (WRA) and Preschool-age Children + (PSC); however, the general principle of the BRINDA method might apply to other + population groups. The BRINDA R package is a user-friendly all-in-one R package + that uses a series of functions to implement BRINDA adjustment method, as described + above. The BRINDA R package will first carry out rigorous checks and provides + users guidance to correct data or input errors (if they occur) prior to inflammation + adjustments. After no errors are detected, the package implements the BRINDA inflammation + adjustment for up to five micronutrient biomarkers, namely retinol-binding-protein, + serum retinol, serum ferritin, sTfR, and serum zinc (when appropriate), using + inflammation indicators of AGP and/or CRP for various population groups. Of note, + adjustment for serum and RBC folate and serum B-12 is not included in the R package, + since evidence shows that no adjustment is needed for these micronutrient biomarkers + in either WRA or PSC groups (Young (2020) ). + date_publication: '2022-10-16' + bug_reports: https://github.com/hanqiluo/BRINDA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BRINDA + url_git: https://github.com/hanqiluo/BRINDA +brinton: + version: 0.2.7 + title: A Graphical EDA Tool + maintainer: Pere Millán-Martínez + description: |- + An automated graphical exploratory data analysis (EDA) tool that introduces: + a.) wideplot graphics for exploring the structure of a dataset through a grid of variables + and graphic types. + b.) longplot graphics, which present the entire catalog of available graphics for representing + a particular variable using a grid of graphic types and variations on these types. + c.) plotup function, which presents a particular graphic for a specific variable of a dataset. + The plotup() function also makes it possible to obtain the code used to generate the graphic, + meaning that the user can adjust its properties as needed. + d.) matrixplot graphics that is a grid of a particular graphic showing bivariate relationships + between all pairs of variables of a certain(s) type(s) in a multivariate data set. + date_publication: '2023-01-07' + bug_reports: https://github.com/sciencegraph/brinton/issues + url: https://sciencegraph.github.io/brinton/ + url_cran: https://CRAN.R-project.org/package=brinton + url_git: https://github.com/sciencegraph/brinton +brio: + version: 1.1.5 + title: Basic R Input Output + maintainer: Gábor Csárdi + description: |- + Functions to handle basic input output, these functions + always read and write UTF-8 (8-bit Unicode Transformation Format) + files and provide more explicit control over line endings. + date_publication: '2024-04-24' + bug_reports: https://github.com/r-lib/brio/issues + url: https://brio.r-lib.org + url_cran: https://CRAN.R-project.org/package=brio + url_git: https://github.com/r-lib/brio +briqr: + version: 0.1.0 + title: Interface to the 'Briq' API + maintainer: David Rubinger + description: |- + An interface to the 'Briq' API . 'Briq' is + a tool that aims to promote employee engagement by helping employees + recognize and reward each other. Employees can praise and thank one another + (for achieving a company goal, for example) by giving virtual credits (known + as 'briqs' or 'bqs') that can be redeemed for various rewards. The 'Briq' + API lets you create, read, update and delete users, user groups, + transactions and messages. This package provides functions that simplify + getting the users, user groups and transactions of your organization into R. + date_publication: '2019-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=briqr + url_git: '' +BRISC: + version: 1.0.6 + title: Fast Inference for Large Spatial Datasets using BRISC + maintainer: Arkajyoti Saha + description: Fits bootstrap with univariate spatial regression models using Bootstrap + for Rapid Inference on Spatial Covariances (BRISC) for large datasets using nearest + neighbor Gaussian processes detailed in Saha and Datta (2018) . + date_publication: '2024-10-02' + bug_reports: https://github.com/ArkajyotiSaha/BRISC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BRISC + url_git: https://github.com/ArkajyotiSaha/BRISC +brisk: + version: 0.1.0 + title: Bayesian Benefit Risk Analysis + maintainer: Richard Payne + description: |- + Quantitative methods for benefit-risk analysis help to condense + complex decisions into a univariate metric describing the overall benefit + relative to risk. One approach is to use the multi-criteria decision + analysis framework (MCDA), as in Mussen, Salek, and Walker + (2007) . Bayesian benefit-risk + analysis incorporates uncertainty through posterior distributions which are + inputs to the benefit-risk framework. The brisk package provides functions + to assist with Bayesian benefit-risk analyses, such as MCDA. + Users input posterior samples, utility functions, weights, and the package + outputs quantitative benefit-risk scores. The posterior of the benefit-risk + scores for each group can be compared. Some plotting capabilities are also + included. + date_publication: '2022-08-31' + bug_reports: https://github.com/rich-payne/brisk/issues + url: https://rich-payne.github.io/brisk/ + url_cran: https://CRAN.R-project.org/package=brisk + url_git: '' +BRL: + version: 0.1.0 + title: Beta Record Linkage + maintainer: Mauricio Sadinle + description: Implementation of the record linkage methodology proposed by Sadinle + (2017) . It handles the bipartite record linkage + problem, where two duplicate-free datafiles are to be merged. + date_publication: '2020-01-13' + bug_reports: https://github.com/msadinle/BRL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BRL + url_git: https://github.com/msadinle/BRL +brlrmr: + version: 0.1.7 + title: Bias Reduction with Missing Binary Response + maintainer: Arnab Maity + description: Provides two main functions, il() and fil(). The il() function implements + the EM algorithm developed by Ibrahim and Lipsitz (1996) + to estimate the parameters of a logistic regression model with the missing response + when the missing data mechanism is nonignorable. The fil() function implements + the algorithm proposed by Maity et. al. (2017+) + to reduce the bias produced by the method of Ibrahim and Lipsitz (1996) . + date_publication: '2019-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brlrmr + url_git: '' +brm: + version: 1.1.1 + title: Binary Regression Model + maintainer: Mark Clements + description: Fits novel models for the conditional relative risk, risk difference + and odds ratio . + date_publication: '2020-06-17' + bug_reports: http://github.com/mclements/brm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=brm + url_git: http://github.com/mclements/brm +brms: + version: 2.22.0 + title: Bayesian Regression Models using 'Stan' + maintainer: Paul-Christian Bürkner + description: |- + Fit Bayesian generalized (non-)linear multivariate multilevel models + using 'Stan' for full Bayesian inference. A wide range of distributions + and link functions are supported, allowing users to fit -- among others -- + linear, robust linear, count data, survival, response times, ordinal, + zero-inflated, hurdle, and even self-defined mixture models all in a + multilevel context. Further modeling options include both theory-driven and + data-driven non-linear terms, auto-correlation structures, censoring and + truncation, meta-analytic standard errors, and quite a few more. + In addition, all parameters of the response distribution can be predicted + in order to perform distributional regression. Prior specifications are + flexible and explicitly encourage users to apply prior distributions that + actually reflect their prior knowledge. Models can easily be evaluated and + compared using several methods assessing posterior or prior predictions. + References: Bürkner (2017) ; + Bürkner (2018) ; + Bürkner (2021) ; Carpenter et al. (2017) + . + date_publication: '2024-09-23' + bug_reports: https://github.com/paul-buerkner/brms/issues + url: https://discourse.mc-stan.org/ + url_cran: https://CRAN.R-project.org/package=brms + url_git: https://github.com/paul-buerkner/brms +brms.mmrm: + version: 1.1.1 + title: Bayesian MMRMs using 'brms' + maintainer: William Michael Landau + description: |- + The mixed model for repeated measures (MMRM) is a popular + model for longitudinal clinical trial data with continuous endpoints, + and 'brms' is a powerful and versatile package for fitting Bayesian + regression models. The 'brms.mmrm' R package leverages 'brms' to run + MMRMs, and it supports a simplified interfaced to reduce difficulty + and align with the best practices of the life sciences. References: + Bürkner (2017) , Mallinckrodt (2008) + . + date_publication: '2024-10-02' + bug_reports: https://github.com/openpharma/brms.mmrm/issues + url: https://openpharma.github.io/brms.mmrm/ + url_cran: https://CRAN.R-project.org/package=brms.mmrm + url_git: https://github.com/openpharma/brms.mmrm +brmsmargins: + version: 0.2.0 + title: Bayesian Marginal Effects for 'brms' Models + maintainer: Joshua F. Wiley + description: Calculate Bayesian marginal effects, average marginal effects, and + marginal coefficients (also called population averaged coefficients) for models + fit using the 'brms' package including fixed effects, mixed effects, and location + scale models. These are based on marginal predictions that integrate out random + effects if necessary (see for example and ). + date_publication: '2022-05-18' + bug_reports: https://github.com/JWiley/brmsmargins/issues + url: https://joshuawiley.com/brmsmargins/ + url_cran: https://CRAN.R-project.org/package=brmsmargins + url_git: https://github.com/JWiley/brmsmargins +brnn: + version: 0.9.3 + title: Bayesian Regularization for Feed-Forward Neural Networks + maintainer: Paulino Perez Rodriguez + description: Bayesian regularization for feed-forward neural networks. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brnn + url_git: '' +Brobdingnag: + version: 1.2-9 + title: Very Large Numbers in R + maintainer: Robin K. S. Hankin + description: |- + Very large numbers in R. Real numbers are held + using their natural logarithms, plus a logical flag indicating + sign. Functionality for complex numbers is also provided. The + package includes a vignette that gives a step-by-step + introduction to using S4 methods. + date_publication: '2022-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Brobdingnag + url_git: https://github.com/RobinHankin/Brobdingnag +BrokenAdaptiveRidge: + version: 1.0.0 + title: Broken Adaptive Ridge Regression with Cyclops + maintainer: Marc A. Suchard + description: |- + Approximates best-subset selection (L0) regression with + an iteratively adaptive Ridge (L2) penalty for large-scale models. + This package uses Cyclops for an efficient implementation and the + iterative method is described in Kawaguchi et al (2020) + and Li et al (2021) + . + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BrokenAdaptiveRidge + url_git: '' +brokenstick: + version: 2.5.0 + title: Broken Stick Model for Irregular Longitudinal Data + maintainer: Stef van Buuren + description: |- + Data on multiple individuals through time are often sampled at + times that differ between persons. Irregular observation times can severely + complicate the statistical analysis of the data. The broken stick model + approximates each subject’s trajectory by one or more connected line segments. + The times at which segments connect (breakpoints) are identical for all + subjects and under control of the user. A well-fitting broken stick model + effectively transforms individual measurements made at irregular times into + regular trajectories with common observation times. Specification of the + model requires three variables: time, measurement and subject. The + model is a special case of the linear mixed model, with time as a linear + B-spline and subject as the grouping factor. The main assumptions are: + subjects are exchangeable, trajectories between consecutive breakpoints are + straight, random effects follow a multivariate normal distribution, and + unobserved data are missing at random. The package contains functions for + fitting the broken stick model to data, for predicting curves in new data + and for plotting broken stick estimates. The package supports two + optimization methods, and includes options to structure the + variance-covariance matrix of the random effects. The analyst may use the + software to smooth growth curves by a series of connected straight lines, to + align irregularly observed curves to a common time grid, to create synthetic + curves at a user-specified set of breakpoints, to estimate the time-to-time + correlation matrix and to predict future observations. See + for additional documentation on background, + methodology and applications. + date_publication: '2023-03-22' + bug_reports: https://github.com/growthcharts/brokenstick/issues + url: doi:10.18637/jss.v106.i07 + url_cran: https://CRAN.R-project.org/package=brokenstick + url_git: '' +brolgar: + version: 1.0.1 + title: Browse Over Longitudinal Data Graphically and Analytically in R + maintainer: Nicholas Tierney + description: |- + Provides a framework of tools to summarise, visualise, and explore + longitudinal data. It builds upon the tidy time series data frames used in the + 'tsibble' package, and is designed to integrate within the 'tidyverse', and + 'tidyverts' (for time series) ecosystems. The methods implemented include + calculating features for understanding longitudinal data, including + calculating summary statistics such as quantiles, medians, and numeric ranges, + sampling individual series, identifying individual series representative of a + group, and extending the facet system in 'ggplot2' to facilitate exploration of samples of data. These methods are + fully described in the paper "brolgar: An R package to Browse Over + Longitudinal Data Graphically and Analytically in R", Nicholas Tierney, + Dianne Cook, Tania Prvan (2020) . + date_publication: '2024-05-10' + bug_reports: https://github.com/njtierney/brolgar/issues + url: https://brolgar.njtierney.com/ + url_cran: https://CRAN.R-project.org/package=brolgar + url_git: https://github.com/njtierney/brolgar +broman: + version: '0.84' + title: Karl Broman's R Code + maintainer: Karl W Broman + description: |- + Miscellaneous R functions, including functions related to + graphics (mostly for base graphics), permutation tests, running + mean/median, and general utilities. + date_publication: '2024-05-18' + bug_reports: https://github.com/kbroman/broman/issues + url: '' + url_cran: https://CRAN.R-project.org/package=broman + url_git: https://github.com/kbroman/broman +broom: + version: 1.0.7 + title: Convert Statistical Objects into Tidy Tibbles + maintainer: Simon Couch + description: |- + Summarizes key information about statistical + objects in tidy tibbles. This makes it easy to report results, create + plots and consistently work with large numbers of models at once. + Broom provides three verbs that each provide different types of + information about a model. tidy() summarizes information about model + components such as coefficients of a regression. glance() reports + information about an entire model, such as goodness of fit measures + like AIC and BIC. augment() adds information about individual + observations to a dataset, such as fitted values or influence + measures. + date_publication: '2024-09-26' + bug_reports: https://github.com/tidymodels/broom/issues + url: https://broom.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=broom + url_git: https://github.com/tidymodels/broom +broom.helpers: + version: 1.19.0 + title: Helpers for Model Coefficients Tibbles + maintainer: Joseph Larmarange + description: |- + Provides suite of functions to work with regression model + 'broom::tidy()' tibbles. The suite includes functions to group + regression model terms by variable, insert reference and header rows + for categorical variables, add variable labels, and more. + date_publication: '2025-01-29' + bug_reports: https://github.com/larmarange/broom.helpers/issues + url: https://larmarange.github.io/broom.helpers/ + url_cran: https://CRAN.R-project.org/package=broom.helpers + url_git: https://github.com/larmarange/broom.helpers +broom.mixed: + version: 0.2.9.6 + title: Tidying Methods for Mixed Models + maintainer: Ben Bolker + description: |- + Convert fitted objects from various R mixed-model packages + into tidy data frames along the lines of the 'broom' package. + The package provides three + S3 generics for each model: tidy(), which summarizes a model's statistical findings such as + coefficients of a regression; augment(), which adds columns to the original + data such as predictions, residuals and cluster assignments; and glance(), which + provides a one-row summary of model-level statistics. + date_publication: '2024-10-15' + bug_reports: https://github.com/bbolker/broom.mixed/issues + url: '' + url_cran: https://CRAN.R-project.org/package=broom.mixed + url_git: https://github.com/bbolker/broom.mixed +brotli: + version: 1.3.1 + title: A Compression Format Optimized for the Web + maintainer: Jeroen Ooms + description: |- + A lossless compressed data format that uses a combination + of the LZ77 algorithm and Huffman coding . + Brotli is similar in speed to deflate (gzip) but offers more dense compression. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/brotli/issues + url: https://jeroen.r-universe.dev/brotli + url_cran: https://CRAN.R-project.org/package=brotli + url_git: '' +BrownDog: + version: 0.2.1 + title: Brown Dog R Interface + maintainer: Yan Zhao + description: |- + An R interface for the Brown Dog which allows researchers to leverage Brown Dog Services + that provides modules to identify the conversion options for a file, to convert file to appropriate + format, or to extract data from a file. See for more information. + date_publication: '2017-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BrownDog + url_git: '' +brpop: + version: 0.6.0 + title: Brazilian Population Estimatives + maintainer: Raphael Saldanha + description: Functions to handle and aggregate population estimates for Brazilian + municipalities by sex and age groups. + date_publication: '2025-02-24' + bug_reports: https://github.com/rfsaldanha/brpop/issues + url: https://rfsaldanha.github.io/brpop/ + url_cran: https://CRAN.R-project.org/package=brpop + url_git: '' +Brq: + version: '3.0' + title: Bayesian Analysis of Quantile Regression Models + maintainer: Rahim Alhamzawi (University of Al-Qadisiyah) + description: Bayesian estimation and variable selection for quantile regression + models. + date_publication: '2020-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Brq + url_git: '' +brsim: + version: '0.3' + title: Brainerd-Robinson Similarity Coefficient Matrix + maintainer: Gianmarco Alberti + description: Provides the facility to calculate the Brainerd-Robinson similarity + coefficient for the rows of an input table, and to calculate the significance + of each coefficient based on a permutation approach; a heatmap is produced to + visually represent the similarity matrix. Optionally, hierarchical agglomerative + clustering can be performed and the silhouette method is used to identify an optimal + number of clusters; the results of the clustering can be optionally used to sort + the heatmap. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brsim + url_git: '' +bruceR: + version: '2024.6' + title: Broadly Useful Convenient and Efficient R Functions + maintainer: Han-Wu-Shuang Bao + description: |- + Broadly useful convenient and efficient R functions + that bring users concise and elegant R data analyses. + This package includes easy-to-use functions for + (1) basic R programming + (e.g., set working directory to the path of currently opened file; + import/export data from/to files in any format; + print tables to Microsoft Word); + (2) multivariate computation + (e.g., compute scale sums/means/... with reverse scoring); + (3) reliability analyses and factor analyses; + (4) descriptive statistics and correlation analyses; + (5) t-test, multi-factor analysis of variance (ANOVA), + simple-effect analysis, and post-hoc multiple comparison; + (6) tidy report of statistical models + (to R Console and Microsoft Word); + (7) mediation and moderation analyses (PROCESS); + and (8) additional toolbox for statistics and graphics. + date_publication: '2024-06-13' + bug_reports: https://github.com/psychbruce/bruceR/issues + url: https://psychbruce.github.io/bruceR/ + url_cran: https://CRAN.R-project.org/package=bruceR + url_git: '' +BRugs: + version: 0.9-2.1 + title: Interface to the 'OpenBUGS' MCMC Software + maintainer: Uwe Ligges + description: Fully-interactive R interface to the 'OpenBUGS' software for Bayesian + analysis using MCMC sampling. Runs natively and stably in 32-bit R under Windows. Versions + running on x86Linux and on 64-bit R under Windows are in "beta" status and less + efficient. + date_publication: '2024-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BRugs + url_git: '' +brulee: + version: 0.4.0 + title: High-Level Modeling Functions with 'torch' + maintainer: Max Kuhn + description: |- + Provides high-level modeling functions to define and train + models using the 'torch' R package. Models include linear, logistic, + and multinomial regression as well as multilayer perceptrons. + date_publication: '2025-01-30' + bug_reports: https://github.com/tidymodels/brulee/issues + url: https://brulee.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=brulee + url_git: https://github.com/tidymodels/brulee +bruneimap: + version: 0.3.1 + title: Maps and Spatial Data of Brunei + maintainer: Haziq Jamil + description: Provides spatial data for mapping Brunei, including boundaries for + districts, mukims, and kampongs, as well as locations of key infrastructure such + as masjids, hospitals, clinics, and schools. The package supports researchers, + analysts, and developers working with Brunei’s geographic and demographic data, + offering a quick and accessible foundation for creating maps and conducting spatial + studies. + date_publication: '2024-12-20' + bug_reports: https://github.com/Bruneiverse/bruneimap/issues + url: https://bruneiverse.github.io/bruneimap/ + url_cran: https://CRAN.R-project.org/package=bruneimap + url_git: https://github.com/Bruneiverse/bruneimap +brunnermunzel: + version: '2.0' + title: (Permuted) Brunner-Munzel Test + maintainer: Toshiaki Ara + description: |- + Provides the functions for Brunner-Munzel test and + permuted Brunner-Munzel test, + which enable to use formula, matrix, and table as argument. + These functions are based on Brunner and Munzel (2000) + + and Neubert and Brunner (2007) , + and are written with FORTRAN. + date_publication: '2022-08-07' + bug_reports: https://github.com/toshi-ara/brunnermunzel/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=brunnermunzel + url_git: https://github.com/toshi-ara/brunnermunzel +BRVM: + version: 5.3.0 + title: |- + Retrieve Historical Data of Companies Listed on the 'BRVM' Stock + Exchange + maintainer: Sessie Koffi Frederic + description: Provide real-time access to data from the Regional Securities Exchange + SA(), commonly known as the 'BRVM' stock exchange. The + goal is to facilitate data access for users of the R programming language. The + package includes a variety of data that can be accessed by calling functions. + date_publication: '2024-02-21' + bug_reports: '' + url: https://rpubs.com/Fredysessie/Readme_BRVM_Stock + url_cran: https://CRAN.R-project.org/package=BRVM + url_git: '' +brxx: + version: 0.1.2 + title: Bayesian Test Reliability Estimation + maintainer: Joshua Ray Tanzer + description: |- + When samples contain missing data, are small, or are suspected of bias, + estimation of scale reliability may not be trustworthy. A recommended solution + for this common problem has been Bayesian model estimation. Bayesian methods + rely on user specified information from historical data or researcher intuition + to more accurately estimate the parameters. This package provides a user friendly + interface for estimating test reliability. Here, reliability is modeled as a beta + distributed random variable with shape parameters alpha=true score variance and + beta=error variance (Tanzer & Harlow, 2020) . + date_publication: '2021-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=brxx + url_git: '' +bs4cards: + version: 0.1.1 + title: Generate Bootstrap Cards + maintainer: Danielle Navarro + description: |- + Allows the user to generate bootstrap cards within + R markdown documents. Intended for use in conjunction with + R markdown HTML outputs and other formats that support the + bootstrap 4 library. + date_publication: '2021-11-30' + bug_reports: https://github.com/djnavarro/bs4cards/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bs4cards + url_git: https://github.com/djnavarro/bs4cards +bs4Dash: + version: 2.3.4 + title: A 'Bootstrap 4' Version of 'shinydashboard' + maintainer: David Granjon + description: |- + Make 'Bootstrap 4' Shiny dashboards. Use the full power + of 'AdminLTE3', a dashboard template built on top of 'Bootstrap 4' + . + date_publication: '2024-09-03' + bug_reports: https://github.com/RinteRface/bs4Dash/issues + url: https://bs4dash.rinterface.com/ + url_cran: https://CRAN.R-project.org/package=bs4Dash + url_git: https://github.com/RinteRface/bs4Dash +BSagri: + version: 0.1-10 + title: Safety Assessment in Agricultural Field Trials + maintainer: Frank Schaarschmidt + description: |- + Collection of functions, data sets and code examples + for evaluations of field trials with the objective of equivalence assessment. + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSagri + url_git: '' +bsam: + version: 1.1.3 + title: Bayesian State-Space Models for Animal Movement + maintainer: Ian Jonsen + description: |- + Tools to fit Bayesian state-space models to animal tracking data. Models are provided for location + filtering, location filtering and behavioural state estimation, and their hierarchical versions. + The models are primarily intended for fitting to ARGOS satellite tracking data but options exist to fit + to other tracking data types. For Global Positioning System data, consider the 'moveHMM' package. + Simplified Markov Chain Monte Carlo convergence diagnostic plotting is provided but users are encouraged + to explore tools available in packages such as 'coda' and 'boa'. + date_publication: '2020-09-01' + bug_reports: https://github.com/ianjonsen/bsam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bsam + url_git: +bsamGP: + version: 1.2.5 + title: Bayesian Spectral Analysis Models using Gaussian Process Priors + maintainer: Beomjo Park + description: |- + Contains functions to perform Bayesian inference + using a spectral analysis of Gaussian process priors. + Gaussian processes are represented with a Fourier series + based on cosine basis functions. Currently the package + includes parametric linear models, partial linear additive + models with/without shape restrictions, generalized linear + additive models with/without shape restrictions, and + density estimation model. To maximize computational + efficiency, the actual Markov chain Monte Carlo sampling + for each model is done using codes written in FORTRAN 90. + This software has been developed using funding supported by + Basic Science Research Program through the National Research + Foundation of Korea (NRF) funded by the Ministry of Education + (no. NRF-2016R1D1A1B03932178 and no. NRF-2017R1D1A3B03035235). + date_publication: '2024-03-18' + bug_reports: '' + url: http://statlab2.korea.ac.kr/software/bsamgp + url_cran: https://CRAN.R-project.org/package=bsamGP + url_git: '' +bscui: + version: 0.1.5 + title: Build SVG Custom User Interface + maintainer: Patrice Godard + description: |- + Render SVG as interactive figures to display contextual + information, with selectable and clickable user interface elements. + These figures can be seamlessly integrated into 'rmarkdown' and 'Quarto' + documents, as well as 'shiny' applications, allowing manipulation of elements + and reporting actions performed on them. + Additional features include pan, zoom in/out functionality, and the ability + to export the figures in SVG or PNG formats. + date_publication: '2024-03-31' + bug_reports: https://github.com/patzaw/bscui/issues + url: https://patzaw.github.io/bscui/ + url_cran: https://CRAN.R-project.org/package=bscui + url_git: https://github.com/patzaw/bscui/ +BSDA: + version: 1.2.2 + title: Basic Statistics and Data Analysis + maintainer: Alan T. Arnholt + description: |- + Data sets for book "Basic Statistics and Data Analysis" by + Larry J. Kitchens. + date_publication: '2023-09-18' + bug_reports: https://github.com/alanarnholt/BSDA/issues + url: https://alanarnholt.github.io/BSDA/ + url_cran: https://CRAN.R-project.org/package=BSDA + url_git: https://github.com/alanarnholt/BSDA +bsearchtools: + version: 0.0.61 + title: Binary Search Tools + maintainer: Marco Giuliano + description: Exposes the binary search functions of the C++ standard library (std::lower_bound, + std::upper_bound) plus other convenience functions, allowing faster lookups on + sorted vectors. + date_publication: '2017-02-22' + bug_reports: https://github.com/digEmAll/bsearchtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bsearchtools + url_git: https://github.com/digEmAll/bsearchtools +bsgof: + version: 0.23.8 + title: Birnbaum-Saunders Goodness-of-Fit Test + maintainer: Chanseok Park + description: Performs goodness of fit test for the Birnbaum-Saunders distribution + and provides the maximum likelihood estimate and the method-of-moments estimate. + For more details, see Park and Wang (2013) . This work was supported + by the National Research Foundation of Korea (NRF) grants funded by the Korea + government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528). + date_publication: '2023-08-24' + bug_reports: https://GitHub.com/AppliedStat/R/issues + url: https://AppliedStat.GitHub.io/R/ + url_cran: https://CRAN.R-project.org/package=bsgof + url_git: '' +BSGW: + version: 0.9.4 + title: |- + Bayesian Survival Model with Lasso Shrinkage Using Generalized + Weibull Regression + maintainer: Alireza S. Mahani + description: Bayesian survival model using Weibull regression on both scale and + shape parameters. Dependence of shape parameter on covariates permits deviation + from proportional-hazard assumption, leading to dynamic - i.e. non-constant with + time - hazard ratios between subjects. Bayesian Lasso shrinkage in the form of + two Laplace priors - one for scale and one for shape coefficients - allows for + many covariates to be included. Cross-validation helper functions can be used + to tune the shrinkage parameters. Monte Carlo Markov Chain (MCMC) sampling using + a Gibbs wrapper around Radford Neal's univariate slice sampler (R package MfUSampler) + is used for coefficient estimation. + date_publication: '2022-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSGW + url_git: '' +bshazard: + version: '1.2' + title: Nonparametric Smoothing of the Hazard Function + maintainer: Paola Rebora + description: |- + The function estimates the hazard function non parametrically from a survival object (possibly adjusted for covariates). + The smoothed estimate is based on B-splines from the perspective of generalized linear mixed models. Left truncated and right censoring data are allowed. + The package is based on the work in Rebora P (2014) . + date_publication: '2024-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bshazard + url_git: '' +bSi: + version: 1.0.0 + title: |- + Modeling and Computing Biogenic Silica ('bSi') from Inland and + Pelagic Sediments + maintainer: George Okoko + description: A collection of integrated tools designed to seamlessly interact with + each other for the analysis of biogenic silica 'bSi' in inland and marine sediments. + These tools share common data representations and follow a consistent 'API' design. + The primary goal of the 'bSi' package is to simplify the installation process, + facilitate data loading, and enable the analysis of multiple samples for biogenic + silica fluxes. This package is designed to enhance the efficiency and coherence + of the entire 'bSi' analytic workflow, from data loading to model construction + and visualization tailored towards reconstructing productivity in aquatic ecosystems. + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bSi + url_git: '' +bsicons: + version: 0.1.2 + title: Easily Work with 'Bootstrap' Icons + maintainer: Carson Sievert + description: |- + Easily use 'Bootstrap' icons inside 'Shiny' apps and 'R + Markdown' documents. More generally, icons can be inserted in any + 'htmltools' document through inline 'SVG'. + date_publication: '2023-11-04' + bug_reports: https://github.com/rstudio/bsicons/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bsicons + url_git: https://github.com/rstudio/bsicons +bSims: + version: 0.3-2 + title: Agent-Based Bird Point Count Simulator + maintainer: Peter Solymos + description: |- + A highly scientific and utterly addictive + bird point count simulator + to test statistical assumptions, aid survey design, + and have fun while doing it (Solymos 2024 ). + The simulations follow time-removal and distance sampling models + based on Matsuoka et al. (2012) , + Solymos et al. (2013) , + and Solymos et al. (2018) , + and sound attenuation experiments by + Yip et al. (2017) . + date_publication: '2024-05-21' + bug_reports: https://github.com/psolymos/bSims/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bSims + url_git: https://github.com/psolymos/bSims +bsitar: + version: 0.3.2 + title: |- + Bayesian Super Imposition by Translation and Rotation Growth + Curve Analysis + maintainer: Satpal Sandhu + description: |- + The Super Imposition by Translation and Rotation (SITAR) model + is a shape-invariant nonlinear mixed effect model that fits a natural cubic + spline mean curve to the growth data and aligns individual-specific growth + curves to the underlying mean curve via a set of random effects (see Cole, + 2010 for details). The non-Bayesian version of the + SITAR model can be fit by using the already available R package 'sitar'. While + the 'sitar' package allows modelling of a single outcome only, the 'bsitar' + package offers great flexibility in fitting models of varying complexities, + including joint modelling of multiple outcomes such as height and weight + (multivariate model). Additionally, the 'bsitar' package allows for the simultaneous + analysis of an outcome separately for subgroups defined by a factor variable such + as gender. This is achieved by fitting separate models for each subgroup + (for example males and females for gender variable). An advantage of this approach + is that posterior draws for each subgroup are part of a single model object, + making it possible to compare coefficients across subgroups and test hypotheses. + Since the 'bsitar' package is a front-end to the R package 'brms', it offers excellent + support for post-processing of posterior draws via various functions that are + directly available from the 'brms' package. In addition, the 'bsitar' package + includes various customized functions that allow for the visualization of distance + (increase in size with age) and velocity (change in growth rate as a function of age), + as well as the estimation of growth spurt parameters such as age at peak growth velocity + and peak growth velocity. + date_publication: '2025-02-07' + bug_reports: https://github.com/Sandhu-SS/bsitar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bsitar + url_git: https://github.com/Sandhu-SS/bsitar +bskyr: + version: 0.2.0 + title: Interact with 'Bluesky' Social + maintainer: Christopher T. Kenny + description: |- + Collect data from and make posts on 'Bluesky' Social + via the Hypertext Transfer Protocol (HTTP) Application Programming + Interface (API), as documented at . This + further supports broader queries to the Authenticated Transfer (AT) Protocol + which 'Bluesky' Social relies on. Data is returned in a + tidy format and posts can be made using a simple interface. + date_publication: '2025-02-09' + bug_reports: https://github.com/christopherkenny/bskyr/issues + url: http://christophertkenny.com/bskyr/ + url_cran: https://CRAN.R-project.org/package=bskyr + url_git: https://github.com/christopherkenny/bskyr +BSL: + version: 3.2.5 + title: Bayesian Synthetic Likelihood + maintainer: Leah F. South + description: |- + Bayesian synthetic likelihood (BSL, Price et al. (2018) ) + is an alternative to standard, non-parametric approximate Bayesian + computation (ABC). BSL assumes a multivariate normal distribution + for the summary statistic likelihood and it is suitable when the + distribution of the model summary statistics is sufficiently regular. + This package provides a Metropolis Hastings Markov chain Monte Carlo + implementation of four methods (BSL, uBSL, semiBSL and BSLmisspec) and two + shrinkage estimators (graphical lasso and Warton's estimator). + uBSL (Price et al. (2018) ) uses + an unbiased estimator to the normal density. A semi-parametric version + of BSL (semiBSL, An et al. (2018) ) is more robust + to non-normal summary statistics. BSLmisspec (Frazier et al. 2019 + ) estimates the Gaussian synthetic likelihood whilst + acknowledging that there may be incompatibility between the model and the + observed summary statistic. Shrinkage estimation can help to decrease the + number of model simulations when the dimension of the summary statistic is + high (e.g., BSLasso, An et al. (2019) ). + Extensions to this package are planned. For a journal article describing how + to use this package, see An et al. (2022) . + date_publication: '2022-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSL + url_git: '' +bslib: + version: 0.9.0 + title: Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown' + maintainer: Carson Sievert + description: |- + Simplifies custom 'CSS' styling of both 'shiny' and + 'rmarkdown' via 'Bootstrap' 'Sass'. Supports 'Bootstrap' 3, 4 and 5 as + well as their various 'Bootswatch' themes. An interactive widget is + also provided for previewing themes in real time. + date_publication: '2025-01-30' + bug_reports: https://github.com/rstudio/bslib/issues + url: https://rstudio.github.io/bslib/ + url_cran: https://CRAN.R-project.org/package=bslib + url_git: https://github.com/rstudio/bslib +BsMD: + version: '2023.920' + title: Bayes Screening and Model Discrimination + maintainer: Ernesto Barrios + description: Bayes screening and model discrimination follow-up designs. + date_publication: '2023-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BsMD + url_git: '' +bsnsing: + version: 1.0.1 + title: Build Decision Trees with Optimal Multivariate Splits + maintainer: Yanchao Liu + description: Functions for training an optimal decision tree classifier, making + predictions and generating latex code for plotting. Works for two-class and multi-class + classification problems. The algorithm seeks the optimal Boolean rule consisting + of multiple variables to split a node, resulting in shorter trees. Use bsnsing() + to build a tree, predict() to make predictions and plot() to plot the tree into + latex and PDF. See Yanchao Liu (2022) for technical details. + Source code and more data sets are at . + date_publication: '2022-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bsnsing + url_git: '' +BSPADATA: + version: 1.1.0 + title: Bayesian Proposal to Fit Spatial Econometric Models + maintainer: Jorge Sicacha-Parada + description: |- + The purpose of this package is to fit the three Spatial Econometric Models proposed + in Anselin (1988, ISBN:9024737354) in the homoscedastic and the heteroscedatic case. The fit is made through MCMC algorithms + and observational working variables approach. + date_publication: '2022-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSPADATA + url_git: '' +BSPBSS: + version: 1.0.5 + title: Bayesian Spatial Blind Source Separation + maintainer: Ben Wu + description: 'Gibbs sampling for Bayesian spatial blind source separation (BSP-BSS). + BSP-BSS is designed for spatially dependent signals in high dimensional and large-scale + data, such as neuroimaging. The method assumes the expectation of the observed + images as a linear mixture of multiple sparse and piece-wise smooth latent source + signals, and constructs a Bayesian nonparametric prior by thresholding Gaussian + processes. Details can be found in our paper: Wu et al. (2022+) "Bayesian Spatial + Blind Source Separation via the Thresholded Gaussian Process" .' + date_publication: '2022-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSPBSS + url_git: '' +bspcov: + version: 1.0.1 + title: Bayesian Sparse Estimation of a Covariance Matrix + maintainer: Kyeongwon Lee + description: |- + Provides functions which perform Bayesian estimations of + a covariance matrix for multivariate normal data. Assumes that + the covariance matrix is sparse or band matrix and positive-definite. + This software has been developed using funding supported by + Basic Science Research Program through the National Research + Foundation of Korea ('NRF') funded by the Ministry of Education + ('RS-2023-00211979', 'NRF-2022R1A5A7033499', 'NRF-2020R1A4A1018207' + and 'NRF-2020R1C1C1A01013338'). + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bspcov + url_git: https://github.com/statjs/bspcov +bspec: + version: '1.6' + title: Bayesian Spectral Inference + maintainer: Christian Roever + description: Bayesian inference on the (discrete) power spectrum of time series. + date_publication: '2022-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bspec + url_git: '' +bspline: + version: 2.3.0 + title: B-Spline Interpolation and Regression + maintainer: Serguei Sokol + description: |- + Build and use B-splines for interpolation and regression. + In case of regression, equality constraints as well as monotonicity + and/or positivity of B-spline weights can be imposed. Moreover, + knot positions (not only spline weights) can be part of + optimized parameters too. For this end, 'bspline' is able to calculate + Jacobian of basis vectors as function of knot positions. User is provided with + functions calculating spline values at arbitrary points. These + functions can be differentiated and integrated to obtain B-splines calculating + derivatives/integrals at any point. B-splines of this package can + simultaneously operate on a series of curves sharing the same set of + knots. 'bspline' is written with concern about computing + performance that's why the basis and Jacobian calculation is implemented in C++. + The rest is implemented in R but without notable impact on computing speed. + date_publication: '2025-02-05' + bug_reports: https://github.com/MathsCell/bspline/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bspline + url_git: https://github.com/MathsCell/bspline +bsplinePsd: + version: 0.6.0 + title: |- + Bayesian Nonparametric Spectral Density Estimation Using + B-Spline Priors + maintainer: Matthew C. Edwards + description: Implementation of a Metropolis-within-Gibbs MCMC algorithm to flexibly + estimate the spectral density of a stationary time series. The algorithm updates + a nonparametric B-spline prior using the Whittle likelihood to produce pseudo-posterior + samples and is based on the work presented in Edwards, M.C., Meyer, R. and Christensen, + N., Statistics and Computing (2018). . + date_publication: '2018-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bsplinePsd + url_git: '' +bsplus: + version: 0.1.4 + title: Adds Functionality to the R Markdown + Shiny Bootstrap Framework + maintainer: Ian Lyttle + description: |- + The Bootstrap framework lets you add some JavaScript functionality to your web site by + adding attributes to your HTML tags - Bootstrap takes care of the JavaScript + . If you are using R Markdown or Shiny, you can + use these functions to create collapsible sections, accordion panels, modals, tooltips, + popovers, and an accordion sidebar framework (not described at Bootstrap site). + Please note this package was designed for Bootstrap 3.3. + date_publication: '2022-11-16' + bug_reports: https://github.com/ijlyttle/bsplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bsplus + url_git: https://github.com/ijlyttle/bsplus +bspm: + version: 0.5.7 + title: Bridge to System Package Manager + maintainer: Iñaki Ucar + description: |- + Enables binary package installations on Linux distributions. + Provides functions to manage packages via the distribution's package + manager. Also provides transparent integration with R's install.packages() + and a fallback mechanism. When installed as a system package, interacts + with the system's package manager without requiring administrative + privileges via an integrated D-Bus service; otherwise, uses sudo. + Currently, the following backends are supported: DNF, APT, ALPM. + date_publication: '2024-04-10' + bug_reports: https://github.com/cran4linux/bspm/issues + url: https://cran4linux.github.io/bspm/ + url_cran: https://CRAN.R-project.org/package=bspm + url_git: '' +bspmma: + version: 0.1-2 + title: Bayesian Semiparametric Models for Meta-Analysis + maintainer: Deborah Burr + description: The main functions carry out Gibbs' sampler routines for nonparametric + and semiparametric Bayesian models for random effects meta-analysis. + date_publication: '2019-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bspmma + url_git: '' +bsreg: + version: 0.0.2 + title: Bayesian Spatial Regression Models + maintainer: Nikolas Kuschnig + description: Fit Bayesian models with a focus on the spatial econometric models. + date_publication: '2022-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bsreg + url_git: '' +BSS: + version: 0.1.0 + title: Brownian Semistationary Processes + maintainer: Phillip Murray + description: |- + Efficient simulation of Brownian semistationary (BSS) processes using the hybrid simulation scheme, as described in + Bennedsen, Lunde, Pakkannen (2017) , as well as functions to fit BSS processes + to data, and functions to estimate the stochastic volatility process of a BSS process. + date_publication: '2020-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSS + url_git: '' +BSSasymp: + version: 1.2-3 + title: |- + Asymptotic Covariance Matrices of Some BSS Mixing and Unmixing + Matrix Estimates + maintainer: Klaus Nordhausen + description: 'Functions to compute the asymptotic covariance matrices of mixing + and unmixing matrix estimates of the following blind source separation (BSS) methods: + symmetric and squared symmetric FastICA, regular and adaptive deflation-based + FastICA, FOBI, JADE, AMUSE and deflation-based and symmetric SOBI. Also functions + to estimate these covariances based on data are available.' + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSSasymp + url_git: '' +bssm: + version: 2.0.2 + title: |- + Bayesian Inference of Non-Linear and Non-Gaussian State Space + Models + maintainer: Jouni Helske + description: |- + Efficient methods for Bayesian inference of state space models + via Markov chain Monte Carlo (MCMC) based on parallel + importance sampling type weighted estimators + (Vihola, Helske, and Franks, 2020, ), + particle MCMC, and its delayed acceptance version. + Gaussian, Poisson, binomial, negative binomial, and Gamma + observation densities and basic stochastic volatility models + with linear-Gaussian state dynamics, as well as general non-linear Gaussian + models and discretised diffusion models are supported. + See Helske and Vihola (2021, ) for details. + date_publication: '2023-10-27' + bug_reports: https://github.com/helske/bssm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bssm + url_git: https://github.com/helske/bssm +bssn: + version: '1.0' + title: Birnbaum-Saunders Model + maintainer: Rocio Paola Maehara + description: It provides the density, distribution function, quantile function, + random number generator, reliability function, failure rate, likelihood function, + moments and EM algorithm for Maximum Likelihood estimators, also empirical quantile + and generated envelope for a given sample, all this for the three parameter Birnbaum-Saunders + model based on Skew-Normal Distribution. Also, it provides the random number generator + for the mixture of Birnbaum-Saunders model based on Skew-Normal distribution. + Additionally, we incorporate the EM algorithm based on the assumption that the + error term follows a finite mixture of Sinh-normal distributions. + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bssn + url_git: '' +BSSoverSpace: + version: 0.1.0 + title: |- + Blind Source Separation for Multivariate Spatial Data using + Eigen Analysis + maintainer: Sixing Hao + description: Provides functions for blind source separation over multivariate spatial + data, and useful statistics for evaluating performance of estimation on mixing + matrix. 'BSSoverSpace' is based on an eigen analysis of a positive definite matrix + defined in terms of multiple normalized spatial local covariance matrices, and + thus can handle moderately high-dimensional random fields. This package is an + implementation of the method described in Zhang, Hao and Yao (2022). + date_publication: '2022-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSSoverSpace + url_git: '' +BSSprep: + version: '0.1' + title: Whitening Data as Preparation for Blind Source Separation + maintainer: Markus Matilainen + description: Whitening is the first step of almost all blind source separation (BSS) + methods. A fast implementation of whitening for BSS is implemented to serve as + a lightweight dependency for packages providing BSS methods. + date_publication: '2021-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BSSprep + url_git: '' +bst: + version: 0.3-24 + title: Gradient Boosting + maintainer: Zhu Wang + description: Functional gradient descent algorithm for a variety of convex and non-convex + loss functions, for both classical and robust regression and classification problems. + See Wang (2011) , Wang (2012) , + Wang (2018) , Wang (2018) . + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bst + url_git: '' +bsTools: + version: 1.0.5 + title: Create HTML Content with Bootstrap 5 Classes and Layouts + maintainer: Timothy Conwell + description: |- + Functions are pre-configured to utilize Bootstrap 5 classes and + HTML structures to create Bootstrap-styled HTML quickly and easily. Includes + functions for creating common Bootstrap elements such as containers, rows, cols, + navbars, etc. Intended to be used with the html5 package. Learn more at + . + date_publication: '2022-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bsTools + url_git: '' +bstrl: + version: 1.0.2 + title: Bayesian Streaming Record Linkage + maintainer: Ian Taylor + description: Perform record linkage on streaming files using recursive Bayesian + updating. + date_publication: '2022-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bstrl + url_git: '' +bsts: + version: 0.9.10 + title: Bayesian Structural Time Series + maintainer: Steven L. Scott + description: |- + Time series regression using dynamic linear models fit using + MCMC. See Scott and Varian (2014) , among many + other sources. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bsts + url_git: '' +BSTZINB: + version: 2.0.0 + title: Association Among Disease Counts and Socio-Environmental Factors + maintainer: Suman Majumder + description: Estimation of association between disease or death counts (e.g. COVID-19) + and socio-environmental risk factors using a zero-inflated Bayesian spatiotemporal + model. Non-spatiotemporal models and/or models without zero-inflation are also + included for comparison. Functions to produce corresponding maps are also included. + See Chakraborty et al. (2022) for more details + on the method. + date_publication: '2025-01-30' + bug_reports: https://github.com/SumanM47/BSTZINB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BSTZINB + url_git: https://github.com/SumanM47/BSTZINB +bsub: + version: 1.1.0 + title: Submitter and Monitor of the 'LSF Cluster' + maintainer: Zuguang Gu + description: |- + It submits R code/R scripts/shell commands to 'LSF cluster' + (, the 'bsub' system) without + leaving R. There is also an interactive 'shiny' app for monitoring the job status. + date_publication: '2021-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bsub + url_git: https://github.com/jokergoo/bsub +bsvars: + version: '3.2' + title: Bayesian Estimation of Structural Vector Autoregressive Models + maintainer: Tomasz Woźniak + description: Provides fast and efficient procedures for Bayesian analysis of Structural + Vector Autoregressions. This package estimates a wide range of models, including + homo-, heteroskedastic, and non-normal specifications. Structural models can be + identified by adjustable exclusion restrictions, time-varying volatility, or non-normality. + They all include a flexible three-level equation-specific local-global hierarchical + prior distribution for the estimated level of shrinkage for autoregressive and + structural parameters. Additionally, the package facilitates predictive and structural + analyses such as impulse responses, forecast error variance and historical decompositions, + forecasting, verification of heteroskedasticity, non-normality, and hypotheses + on autoregressive parameters, as well as analyses of structural shocks, volatilities, + and fitted values. Beautiful plots, informative summary functions, and extensive + documentation including the vignette by Woźniak (2024) + complement all this. The implemented techniques align closely with those presented + in Lütkepohl, Shang, Uzeda, & Woźniak (2024) , + Lütkepohl & Woźniak (2020) , and Song & Woźniak + (2021) . The 'bsvars' package is aligned + regarding objects, workflows, and code structure with the R package 'bsvarSIGNs' + by Wang & Woźniak (2024) , and they constitute + an integrated toolset. + date_publication: '2024-10-24' + bug_reports: https://github.com/bsvars/bsvars/issues + url: https://bsvars.org/bsvars/ + url_cran: https://CRAN.R-project.org/package=bsvars + url_git: '' +bsvarSIGNs: + version: '2.0' + title: Bayesian SVARs with Sign, Zero, and Narrative Restrictions + maintainer: Xiaolei Wang + description: Implements state-of-the-art algorithms for the Bayesian analysis of + Structural Vector Autoregressions (SVARs) identified by sign, zero, and narrative + restrictions. The core model is based on a flexible Vector Autoregression with + estimated hyper-parameters of the Minnesota prior and the dummy observation priors + as in Giannone, Lenza, Primiceri (2015) . The sign restrictions + are implemented employing the methods proposed by Rubio-Ramírez, Waggoner & Zha + (2010) , while identification through sign + and zero restrictions follows the approach developed by Arias, Rubio-Ramírez, + & Waggoner (2018) . Furthermore, our tool provides algorithms + for identification via sign and narrative restrictions, in line with the methods + introduced by Antolín-Díaz and Rubio-Ramírez (2018) . + Users can also estimate a model with sign, zero, and narrative restrictions imposed + at once. The package facilitates predictive and structural analyses using impulse + responses, forecast error variance and historical decompositions, forecasting + and conditional forecasting, as well as analyses of structural shocks and fitted + values. All this is complemented by colourful plots, user-friendly summary functions, + and comprehensive documentation including the vignette by Wang & Woźniak (2024) + . The 'bsvarSIGNs' package is aligned regarding + objects, workflows, and code structure with the R package 'bsvars' by Woźniak + (2024) , and they constitute an integrated toolset. + It was granted the Di Cook Open-Source Statistical Software Award by the Statistical + Society of Australia in 2024. + date_publication: '2025-01-30' + bug_reports: https://github.com/bsvars/bsvarSIGNs/issues + url: https://bsvars.org/bsvarSIGNs/ + url_cran: https://CRAN.R-project.org/package=bsvarSIGNs + url_git: '' +BSW: + version: 0.1.1 + title: |- + Fitting a Log-Binomial Model using the Bekhit-Schöpe-Wagenpfeil + (BSW) Algorithm + maintainer: Adam Bekhit + description: Implements a modified Newton-type algorithm (BSW algorithm) for solving + the maximum likelihood estimation problem in fitting a log-binomial model under + linear inequality constraints. + date_publication: '2021-03-22' + bug_reports: https://github.com/adam-bec/BSW/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BSW + url_git: https://github.com/adam-bec/BSW +bsynth: + version: '1.0' + title: Bayesian Synthetic Control + maintainer: Ignacio Martinez + description: |- + Implements the Bayesian Synthetic Control method for causal inference + in comparative case studies. This package provides tools for estimating + treatment effects in settings with a single treated unit and multiple control + units, allowing for uncertainty quantification and flexible modeling of + time-varying effects. The methodology is based on the paper by Vives and + Martinez (2022) . + date_publication: '2024-06-25' + bug_reports: https://github.com/google/bsynth/issues + url: https://arxiv.org/abs/2206.01779 + url_cran: https://CRAN.R-project.org/package=bsynth + url_git: https://github.com/google/bsynth +BT: + version: '0.4' + title: (Adaptive) Boosting Trees Algorithm + maintainer: Gireg Willame + description: |- + Performs (Adaptive) Boosting Trees for Poisson distributed response variables, using log-link function. + The code approach is similar to the one used in 'gbm'/'gbm3'. Moreover, each tree in the expansion is built thanks to the 'rpart' package. + This package is based on following books and articles + Denuit, M., Hainaut, D., Trufin, J. (2019) + Denuit, M., Hainaut, D., Trufin, J. (2019) + Denuit, M., Hainaut, D., Trufin, J. (2019) + Denuit, M., Hainaut, D., Trufin, J. (2022) + Denuit, M., Huyghe, J., Trufin, J. (2022) + Denuit, M., Trufin, J., Verdebout, T. (2022) . + date_publication: '2023-08-19' + bug_reports: https://github.com/GiregWillame/BT/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=BT + url_git: https://github.com/GiregWillame/BT/ +BTdecayLasso: + version: 0.1.1 + title: |- + Bradley-Terry Model with Exponential Time Decayed Log-Likelihood + and Adaptive Lasso + maintainer: Yunpeng Zhou + description: We utilize the Bradley-Terry Model to estimate the abilities of teams + using paired comparison data. For dynamic approximation of current rankings, we + employ the Exponential Decayed Log-likelihood function, and we also apply the + Lasso penalty for variance reduction and grouping. The main algorithm applies + the Augmented Lagrangian Method described by Masarotto and Varin (2012) . + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BTdecayLasso + url_git: '' +btergm: + version: 1.10.12 + title: |- + Temporal Exponential Random Graph Models by Bootstrapped + Pseudolikelihood + maintainer: Philip Leifeld + description: Temporal Exponential Random Graph Models (TERGM) estimated by maximum + pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte + Carlo maximum likelihood. Goodness of fit assessment for ERGMs, TERGMs, and SAOMs. + Micro-level interpretation of ERGMs and TERGMs. The methods are described in Leifeld, + Cranmer and Desmarais (2018), JStatSoft . + date_publication: '2024-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=btergm + url_git: https://github.com/leifeld/btergm +BTLLasso: + version: 0.1-13 + title: Modelling Heterogeneity in Paired Comparison Data + maintainer: Gunther Schauberger + description: Performs 'BTLLasso' as described by Schauberger and Tutz (2019) + and Schauberger and Tutz (2017) . BTLLasso is a + method to include different types of variables in paired comparison models and, + therefore, to allow for heterogeneity between subjects. Variables can be subject-specific, + object-specific and subject-object-specific and can have an influence on the attractiveness/strength + of the objects. Suitable L1 penalty terms are used to cluster certain effects + and to reduce the complexity of the models. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BTLLasso + url_git: '' +BTM: + version: 0.3.7 + title: Biterm Topic Models for Short Text + maintainer: Jan Wijffels + description: |- + Biterm Topic Models find topics in collections of short texts. + It is a word co-occurrence based topic model that learns topics by modeling word-word co-occurrences patterns which are called biterms. + This in contrast to traditional topic models like Latent Dirichlet Allocation and Probabilistic Latent Semantic Analysis + which are word-document co-occurrence topic models. + A biterm consists of two words co-occurring in the same short text window. + This context window can for example be a twitter message, a short answer on a survey, a sentence of a text or a document identifier. + The techniques are explained in detail in the paper 'A Biterm Topic Model For Short Text' by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Xueqi Cheng (2013) . + date_publication: '2023-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BTM + url_git: https://github.com/bnosac/BTM +BTSPAS: + version: 2024.11.1 + title: Bayesian Time-Stratified Population Analysis + maintainer: Carl J Schwarz + description: |- + Provides advanced Bayesian methods to estimate + abundance and run-timing from temporally-stratified + Petersen mark-recapture experiments. Methods include + hierarchical modelling of the capture probabilities + and spline smoothing of the daily run size. Theory + described in Bonner and Schwarz (2011) + . + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BTSPAS + url_git: https://github.com/cschwarz-stat-sfu-ca/BTSPAS +BTSR: + version: 0.1.5 + title: Bounded Time Series Regression + maintainer: Taiane Schaedler Prass + description: |- + Simulate, estimate and forecast a wide range of regression based dynamic models for bounded time series, covering the most commonly applied models in the literature. The main calculations are done in 'FORTRAN', which translates into very fast algorithms. The main references are + Bayer et al. (2017) , + Pumi et al. (2019) , + Pumi et al. (2021) and + Pumi et al. (2022) . + date_publication: '2023-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BTSR + url_git: '' +BTtest: + version: 0.10.3 + title: Estimate the Number of Factors in Large Nonstationary Datasets + maintainer: Paul Haimerl + description: |- + Large panel data sets are often subject to common trends. However, it can be difficult to determine the exact number of these common factors and analyse their properties. + The package implements the Barigozzi and Trapani (2022) test, which not only provides an efficient way of estimating the number of common factors in large nonstationary panel data sets, but also gives further insights on factor classes. The routine identifies the existence of (i) a factor subject to a linear trend, (ii) the number of zero-mean I(1) and (iii) zero-mean I(0) factors. + Furthermore, the package includes the Integrated Panel Criteria by Bai (2004) that provide a complementary measure for the number of factors. + date_publication: '2024-08-28' + bug_reports: https://github.com/Paul-Haimerl/BTtest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BTtest + url_git: https://github.com/Paul-Haimerl/BTtest +BTTL: + version: 1.0.0 + title: Bradley-Terry Transfer Learning + maintainer: Sjoerd Hermes + description: Implements the methodological developments found in Hermes, van Heerwaarden, + and Behrouzi (2024) , and allows for the statistical + modeling of multi-attribute pairwise comparison data. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BTTL + url_git: '' +BTYD: + version: 2.4.3 + title: Implementing BTYD Models with the Log Sum Exp Patch + maintainer: Gabi Huiber + description: |- + Functions for data preparation, parameter estimation, scoring, and plotting for the + BG/BB (Fader, Hardie, and Shang 2010 ), + BG/NBD (Fader, Hardie, and Lee 2005 ) and + Pareto/NBD and Gamma/Gamma (Fader, Hardie, and Lee 2005 ) models. + date_publication: '2021-11-17' + bug_reports: https://github.com/ghuiber/BTYD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BTYD + url_git: '' +BTYDplus: + version: 1.2.0 + title: |- + Probabilistic Models for Assessing and Predicting your Customer + Base + maintainer: Michael Platzer + description: |- + Provides advanced statistical methods to describe and predict customers' + purchase behavior in a non-contractual setting. It uses historic transaction records to fit a + probabilistic model, which then allows to compute quantities of managerial interest on a cohort- + as well as on a customer level (Customer Lifetime Value, Customer Equity, P(alive), etc.). This + package complements the BTYD package by providing several additional buy-till-you-die models, that + have been published in the marketing literature, but whose implementation are complex and non-trivial. + These models are: NBD [Ehrenberg (1959) ], MBG/NBD [Batislam et al (2007) + ], (M)BG/CNBD-k [Reutterer et al (2020) + ], Pareto/NBD (HB) [Abe (2009) ] + and Pareto/GGG [Platzer and Reutterer (2016) ]. + date_publication: '2021-01-21' + bug_reports: https://github.com/mplatzer/BTYDplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BTYDplus + url_git: https://github.com/mplatzer/BTYDplus#readme +bubbleHeatmap: + version: 0.1.1 + title: Produces 'bubbleHeatmap' Plots for Visualising Metabolomics Data + maintainer: Ruth Boxall + description: |- + Plotting package based on the grid system, combining elements of + a bubble plot and heatmap to conveniently display two numerical variables, + (represented by color and size) grouped by categorical variables on the x + and y axes. This is a useful alternative to a forest plot when the data can + be grouped in two dimensions, such as predictors x outcomes. It has + particular advantages for visualising the metabolic measures produced by + the 'Nightingale Health' metabolomics platform, and templates are included + for automatically generating figures from these datasets. + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bubbleHeatmap + url_git: '' +bubblyr: + version: 0.1.2 + title: Beautiful Bubbles for 'shiny' and 'rmarkdown' Backgrounds + maintainer: Mohamed El Fodil Ihaddaden + description: Creates bubbles within 'shiny' and 'rmarkdown' backgrounds using the + 'bubbly-bg' 'JavaScript' library. + date_publication: '2020-07-29' + bug_reports: https://github.com/feddelegrand7/bubblyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bubblyr + url_git: https://github.com/feddelegrand7/bubblyr +BUCSS: + version: 1.2.1 + title: Bias and Uncertainty Corrected Sample Size + maintainer: Ken Kelley + description: |- + Bias- and Uncertainty-Corrected Sample Size. BUCSS implements a method of correcting for publication bias and + uncertainty when planning sample sizes in a future study from an original study. See Anderson, Kelley, & Maxwell (2017; Psychological Science, 28, 1547-1562). + date_publication: '2020-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BUCSS + url_git: '' +Buddle: + version: 2.0.1 + title: |- + A Deep Learning for Statistical Classification and Regression + Analysis with Random Effects + maintainer: Jiwoong Kim + description: 'Statistical classification and regression have been popular among + various fields and stayed in the limelight of scientists of those fields. Examples + of the fields include clinical trials where the statistical classification of + patients is indispensable to predict the clinical courses of diseases. Considering + the negative impact of diseases on performing daily tasks, correctly classifying + patients based on the clinical information is vital in that we need to identify + patients of the high-risk group to develop a severe state and arrange medical + treatment for them at an opportune moment. Deep learning - a part of artificial + intelligence - has gained much attention, and research on it burgeons during past + decades: see, e.g, Kazemi and Mirroshandel (2018) . + It is a veritable technique which was originally designed for the classification, + and hence, the Buddle package can provide sublime solutions to various challenging + classification and regression problems encountered in the clinical trials. The + Buddle package is based on the back-propagation algorithm - together with various + powerful techniques such as batch normalization and dropout - which performs a + multi-layer feed-forward neural network: see Krizhevsky et. al (2017) , + Schmidhuber (2015) and LeCun et al. (1998) + for more details. This package contains two main functions: + TrainBuddle() and FetchBuddle(). TrainBuddle() builds a feed-forward neural network + model and trains the model. FetchBuddle() recalls the trained model which is the + output of TrainBuddle(), classifies or regresses given data, and make a final + prediction for the data.' + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Buddle + url_git: '' +buildmer: + version: '2.11' + title: |- + Stepwise Elimination and Term Reordering for Mixed-Effects + Regression + maintainer: Cesko C. Voeten + description: |- + Finds the largest possible regression model that will still converge + for various types of regression analyses (including mixed models and generalized + additive models) and then optionally performs stepwise elimination similar to the + forward and backward effect-selection methods in SAS, based on the change in + log-likelihood or its significance, Akaike's Information Criterion, the Bayesian + Information Criterion, the explained deviance, or the F-test of the change in R². + date_publication: '2023-10-25' + bug_reports: https://gitlab.com/cvoeten/buildmer/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=buildmer + url_git: '' +buildr: + version: 0.1.1 + title: Organize & Run Build Scripts Comfortably + maintainer: Jan Netik + description: |- + Working with reproducible reports or any other + similar projects often require to run the script that builds the + output file in a specified way. 'buildr' can help you organize, modify + and comfortably run those scripts. The package provides a set of + functions that interactively guides you through the process and that + are available as 'RStudio' Addin, meaning you can set up the keyboard + shortcuts, enabling you to choose and run the desired build script + with one keystroke anywhere anytime. + date_publication: '2022-08-13' + bug_reports: https://github.com/netique/buildr/issues/ + url: https://netique.github.io/buildr/ + url_cran: https://CRAN.R-project.org/package=buildr + url_git: '' +BuildSys: + version: 1.1.2 + title: System for Building and Debugging C/C++ Dynamic Libraries + maintainer: Paavo Jumppanen + description: |- + A build system based on 'GNU make' that creates and + maintains (simply) make files in an R session and provides + GUI debugging support through 'Microsoft Visual Code'. + date_publication: '2021-06-16' + bug_reports: https://github.com/pjumppanen/BuildSys/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BuildSys + url_git: https://github.com/pjumppanen/BuildSys +bujar: + version: 0.2-11 + title: |- + Buckley-James Regression for Survival Data with High-Dimensional + Covariates + maintainer: Zhu Wang + description: Buckley-James regression for right-censoring survival data with high-dimensional + covariates. Implementations for survival data include boosting with componentwise + linear least squares, componentwise smoothing splines, regression trees and MARS. + Other high-dimensional tools include penalized regression for survival data. See + Wang and Wang (2010) . + date_publication: '2023-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bujar + url_git: '' +bulkAnalyseR: + version: 1.1.0 + title: Interactive Shiny App for Bulk Sequencing Data + maintainer: Ilias Moutsopoulos + description: |- + Given an expression matrix from a bulk sequencing experiment, + pre-processes it and creates a shiny app for interactive data + analysis and visualisation. The app contains quality checks, + differential expression analysis, volcano and cross plots, + enrichment analysis and gene regulatory network inference, + and can be customised to contain more panels by the user. + date_publication: '2022-12-15' + bug_reports: https://github.com/Core-Bioinformatics/bulkAnalyseR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bulkAnalyseR + url_git: https://github.com/Core-Bioinformatics/bulkAnalyseR +bulkQC: + version: '1.1' + title: |- + Quality Control and Outlier Identification in Bulk for + Multicenter Trials + maintainer: Joseph Rigdon + description: Multicenter randomized trials involve the collection and analysis of + data from numerous study participants across multiple sites. Outliers may be present. + To identify outliers, this package examines data at the individual level (univariate + and multivariate) and site-level (with and without covariate adjustment). Methods + are outlined in further detail in Rigdon et al (to appear). + date_publication: '2024-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bulkQC + url_git: '' +bulkreadr: + version: 1.1.1 + title: The Ultimate Tool for Reading Data in Bulk + maintainer: Ezekiel Ogundepo + description: |- + Designed to simplify and streamline the process of reading + and processing large volumes of data in R, this package offers a + collection of functions tailored for bulk data operations. It enables + users to efficiently read multiple sheets from Microsoft Excel and + Google Sheets workbooks, as well as various CSV files from a + directory. The data is returned as organized data frames, facilitating + further analysis and manipulation. Ideal for handling extensive data + sets or batch processing tasks, bulkreadr empowers users to manage + data in bulk effortlessly, saving time and effort in data preparation + workflows. Additionally, the package seamlessly works with labelled + data from SPSS and Stata. + date_publication: '2024-05-26' + bug_reports: https://github.com/gbganalyst/bulkreadr/issues + url: https://gbganalyst.github.io/bulkreadr/ + url_cran: https://CRAN.R-project.org/package=bulkreadr + url_git: https://github.com/gbganalyst/bulkreadr +bulletcp: + version: 1.0.0 + title: |- + Automatic Groove Identification via Bayesian Changepoint + Detection + maintainer: Nathaniel Garton + description: |- + Provides functionality to automatically detect groove locations via a Bayesian changepoint detection method to be used in the data preprocessing step + of forensic bullet matching algorithms. The methods in this package are based on those in Stephens (1994) . Bayesian changepoint detection will simply be an option + in the function from the package 'bulletxtrctr' which identifies the groove locations. + date_publication: '2019-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bulletcp + url_git: '' +bulletr: + version: '0.1' + title: Algorithms for Matching Bullet Lands + maintainer: Eric Hare + description: |- + Analyze bullet lands using nonparametric methods. We provide a + reading routine for x3p files (see for more + information) and a host of analysis functions designed to assess the + probability that two bullets were fired from the same gun barrel. + date_publication: '2017-04-26' + bug_reports: https://github.com/erichare/bulletr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bulletr + url_git: https://github.com/erichare/bulletr +bullishTrader: + version: 1.0.1 + title: Bullish Trading Strategies Through Graphs + maintainer: MaheshP Kumar + description: |- + Stock, Options and Futures Trading Strategies for Traders and Investors with Bullish Outlook are represented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. + Guy Cohen (“The Bible of Options Strategies (2nd ed.)”, 2015, ISBN: 9780133964028). + Zura Kakushadze, Juan A. Serur (“151 Trading Strategies”, 2018, ISBN: 9783030027919). + John C. Hull (“Options, Futures, and Other Derivatives (11th ed.)”, 2022, ISBN: 9780136939979). + date_publication: '2022-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bullishTrader + url_git: '' +bullseye: + version: 0.1.2 + title: |- + Visualising Multiple Pairwise Variable Correlations and Other + Scores + maintainer: Catherine Hurley + description: |- + We provide a tidy data structure and visualisations for multiple or grouped variable correlations, + general association measures scagnostics and other pairwise scores suitable for numerical, ordinal and nominal variables. + Supported measures include distance correlation, maximal information, ace correlation, Kendall's tau, and polychoric correlation. + date_publication: '2025-01-28' + bug_reports: '' + url: https://cbhurley.github.io/bullseye/ + url_cran: https://CRAN.R-project.org/package=bullseye + url_git: https://github.com/cbhurley/bullseye +bullwhipgame: + version: 0.1.0 + title: Bullwhip Effect Demo in Shiny + maintainer: Marlene Marchena + description: The bullwhipgame is an educational game that has as purpose the illustration + and exploration of the bullwhip effect,i.e, the increase in demand variability + along the supply chain. Marchena Marlene (2010) . + date_publication: '2018-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bullwhipgame + url_git: '' +bumbl: + version: 1.0.3 + title: Tools for Modeling Bumblebee Colony Growth and Decline + maintainer: Eric R. Scott + description: Bumblebee colonies grow during worker production, then decline after + switching to production of reproductive individuals (drones and gynes). This + package provides tools for modeling and visualizing this pattern by identifying + a switchpoint with a growth rate before and a decline rate after the switchpoint. + The mathematical models fit by bumbl are described in Crone and Williams (2016) + . + date_publication: '2023-03-08' + bug_reports: https://github.com/Aariq/bumbl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bumbl + url_git: https://github.com/Aariq/bumbl +bumblebee: + version: 0.1.0 + title: |- + Quantify Disease Transmission Within and Between Population + Groups + maintainer: Lerato E Magosi + description: |- + A simple tool to quantify the amount of transmission + of an infectious disease of interest occurring within and between + population groups. 'bumblebee' uses counts of observed directed + transmission pairs, identified phylogenetically from deep-sequence data or + from epidemiological contacts, to quantify transmission flows within and + between population groups accounting for sampling heterogeneity. Population + groups might include: geographical areas (e.g. communities, regions), + demographic groups (e.g. age, gender) or arms of a randomized clinical + trial. See the 'bumblebee' website for statistical theory, documentation + and examples . + date_publication: '2021-05-11' + bug_reports: https://github.com/magosil86/bumblebee/issues + url: https://magosil86.github.io/bumblebee/ + url_cran: https://CRAN.R-project.org/package=bumblebee + url_git: '' +bunching: + version: 0.8.6 + title: Estimate Bunching + maintainer: Panos Mavrokonstantis + description: |- + Implementation of the bunching estimator for kinks and notches. + Allows for flexible estimation of counterfactual (e.g. controlling for round number bunching, accounting for other bunching masses within bunching window, fixing bunching point to be minimum, maximum or median value in its bin, etc.). + It produces publication-ready plots in the style followed since Chetty et al. (2011) , with lots of functionality to set plot options. + date_publication: '2022-08-24' + bug_reports: https://github.com/mavpanos/bunching/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bunching + url_git: https://github.com/mavpanos/bunching +bunchr: + version: 1.2.0 + title: Analyze Bunching in a Kink or Notch Setting + maintainer: Itai Trilnick + description: |- + View and analyze data where bunching is expected. Estimate counter- + factual distributions. For earnings data, estimate the compensated + elasticity of earnings w.r.t. the net-of-tax rate. + date_publication: '2017-01-30' + bug_reports: http://github.com/trilnick/bunchr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bunchr + url_git: http://github.com/trilnick/bunchr +bundesbank: + version: 0.1-12 + title: Download Data from Bundesbank + maintainer: Enrico Schumann + description: |- + Download data from the time-series + databases of the Bundesbank, the German central + bank. See the overview at the Bundesbank website + () + for available series. The package provides only a + single function, getSeries(), which supports both + traditional and real-time datasets; it will also + download meta data if available. Downloaded data + can automatically be arranged in various formats, + such as data frames or 'zoo' series. The data + may optionally be cached, so as to avoid repeated + downloads of the same series. + date_publication: '2024-04-19' + bug_reports: '' + url: http://enricoschumann.net/R/packages/bundesbank/index.htm + url_cran: https://CRAN.R-project.org/package=bundesbank + url_git: https://github.com/enricoschumann/bundesbank +bundesligR: + version: 0.1.0 + title: All Final Tables of the Bundesliga + maintainer: Philipp Ottolinger + description: All final tables of Germany's highest football (soccer!) league, the + Bundesliga. Contains data from 1964 to 2016. + date_publication: '2016-08-12' + bug_reports: https://github.com/ottlngr/bundesligR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bundesligR + url_git: https://github.com/ottlngr/bundesligR +bundle: + version: 0.1.2 + title: Serialize Model Objects with a Consistent Interface + maintainer: Julia Silge + description: |- + Typically, models in 'R' exist in memory and can be saved via + regular 'R' serialization. However, some models store information in + locations that cannot be saved using 'R' serialization alone. The goal + of 'bundle' is to provide a common interface to capture this + information, situate it within a portable object, and restore it for + use in new settings. + date_publication: '2024-11-12' + bug_reports: https://github.com/rstudio/bundle/issues + url: https://rstudio.github.io/bundle/ + url_cran: https://CRAN.R-project.org/package=bundle + url_git: https://github.com/rstudio/bundle +bupaR: + version: 0.5.4 + title: Business Process Analysis in R + maintainer: Gert Janssenswillen + description: Comprehensive Business Process Analysis toolkit. Creates S3-class for + event log objects, and related handler functions. Imports related packages for + filtering event data, computation of descriptive statistics, handling of 'Petri + Net' objects and visualization of process maps. See also packages 'edeaR','processmapR', + 'eventdataR' and 'processmonitR'. + date_publication: '2024-03-28' + bug_reports: '' + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=bupaR + url_git: https://github.com/bupaverse/bupaR/ +bupaverse: + version: 0.1.0 + title: Easily Install and Load the 'bupaverse' + maintainer: Gert Janssenswillen + description: |- + The 'bupaverse' is an open-source, integrated suite of R-packages for handling and analysing business process data, + developed by the Business Informatics research group at Hasselt University, Belgium. Profoundly inspired by the 'tidyverse' package, + the 'bupaverse' package is designed to facilitate the installation and loading of multiple 'bupaverse' packages in a single step. + Learn more about 'bupaverse' at the homepage. + date_publication: '2022-10-06' + bug_reports: '' + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=bupaverse + url_git: https://github.com/bupaverse/bupaverse/ +burgle: + version: 0.1.2 + title: '''Burgle'': Stealing the Necessary Parts of Model Objects' + maintainer: Paul R. Gunsalus + description: Provides a way to reduce model objects to necessary parts, making them + easier to work with, store, share and simulate multiple values for new responses + while allowing for parameter uncertainty. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=burgle + url_git: '' +burnr: + version: 0.6.1 + title: Forest Fire History Analysis + maintainer: Steven Malevich + description: Tools to read, write, parse, and analyze forest fire history data (e.g. + FHX). Described in Malevich et al. (2018) . + date_publication: '2022-03-01' + bug_reports: https://github.com/ltrr-arizona-edu/burnr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=burnr + url_git: https://github.com/ltrr-arizona-edu/burnr/ +bursa: + version: 0.1.0 + title: R Wrapper for Bursa Municipality Open Data Portal + maintainer: Ozancan Ozdemir + description: Call the data wrappers for Bursa Metropolitan Municipality's Open Data + Portal . This will return all datasets stored + in different formats. + date_publication: '2023-08-29' + bug_reports: https://github.com/ozancanozdemir/bursa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bursa + url_git: https://github.com/ozancanozdemir/bursa +BurStFin: + version: '1.3' + title: Burns Statistics Financial + maintainer: Pat Burns + description: |- + A suite of functions for finance, including the estimation + of variance matrices via a statistical factor model or + Ledoit-Wolf shrinkage. + date_publication: '2022-04-18' + bug_reports: '' + url: https://www.burns-stat.com/ + url_cran: https://CRAN.R-project.org/package=BurStFin + url_git: '' +BurStMisc: + version: '1.1' + title: Burns Statistics Miscellaneous + maintainer: Pat Burns + description: Script search, corner, genetic optimization, permutation tests, write + expect test. + date_publication: '2016-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BurStMisc + url_git: '' +bursts: + version: 1.0-2 + title: Markov Model for Bursty Behavior in Streams + maintainer: Jeff Binder + description: An implementation of Jon Kleinberg's burst detection algorithm (Kleinberg + (2003) ). Uses an infinite Markov model to detect + periods of increased activity in a series of discrete events with known times, + and provides a simple visualization of the results. + date_publication: '2022-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bursts + url_git: '' +busdater: + version: 0.2.0 + title: Standard Date Calculations for Business + maintainer: Mick Mioduszewski + description: |- + Get a current financial year, start of current + month, End of current month, start of financial year and end of it. + Allow for offset from the date. + date_publication: '2019-01-30' + bug_reports: https://github.com/mickmioduszewski/busdater/issues + url: https://mickmioduszewski.github.io/busdater/ + url_cran: https://CRAN.R-project.org/package=busdater + url_git: https://github.com/mickmioduszewski/busdater/ +bushtucker: + version: 0.1.0 + title: '''I''m a Celebrity Get Me Out of Here'' Data' + maintainer: Chris Brownlie + description: |- + Data on the first 24 seasons of the UK TV show 'I'm a Celebrity, + Get Me Out of Here', broadcast from 2002-2024. Taken from the Wikipedia pages + for each season and the main page available at + . + date_publication: '2025-02-11' + bug_reports: https://github.com/chrisbrownlie/bushtucker/issues + url: https://chrisbrownlie.github.io/bushtucker/ + url_cran: https://CRAN.R-project.org/package=bushtucker + url_git: '' +BusinessDuration: + version: 0.2.0 + title: Calculates Business Duration Between Two Dates + maintainer: Gnaneshwar G + description: Calculates business duration between two dates. This excluding weekends, + public holidays and non-business hours. + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BusinessDuration + url_git: '' +businessPlanR: + version: 0.1-0 + title: Simple Modelling Tools for Business Plans + maintainer: Meik Michalke + description: |- + A collection of S4 classes, methods and functions to create + and visualize business plans. Different types of cash flows can be + defined, which can then be used and tabulated to create profit and + loss statements, cash flow plans, investment and depreciation + schedules, loan amortization schedules, etc. The methods are + designed to produce handsome tables in both PDF and HTML using + 'RMarkdown' or 'Shiny'. + date_publication: '2023-08-15' + bug_reports: https://github.com/C3S/businessPlanR/issues + url: https://www.c3s.cc + url_cran: https://CRAN.R-project.org/package=businessPlanR + url_git: '' +butcher: + version: 0.3.4 + title: Model Butcher + maintainer: Julia Silge + description: |- + Provides a set of S3 generics to axe components of fitted + model objects and help reduce the size of model objects saved to disk. + date_publication: '2024-04-11' + bug_reports: https://github.com/tidymodels/butcher/issues + url: https://butcher.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=butcher + url_git: https://github.com/tidymodels/butcher +butterflyOptions: + version: 1.0.1 + title: Trading Butterfly Options Strategies + maintainer: MaheshP Kumar + description: |- + Trading of Butterfly Options Strategies is represented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. + Guy Cohen (“The Bible of Options Strategies (2nd ed.)”, 2015, ISBN: 9780133964028). + Zura Kakushadze, Juan A. Serur (“151 Trading Strategies”, 2018, ISBN: 9783030027919). + John C. Hull (“Options, Futures, and Other Derivatives (11th ed.)”, 2022, ISBN: 9780136939979). + date_publication: '2022-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=butterflyOptions + url_git: '' +BuyseTest: + version: 3.0.5 + title: Generalized Pairwise Comparisons + maintainer: Brice Ozenne + description: Implementation of the Generalized Pairwise Comparisons (GPC) as defined + in Buyse (2010) for complete observations, and extended + in Peron (2018) to deal with right-censoring. GPC + compare two groups of observations (intervention vs. control group) regarding + several prioritized endpoints to estimate the probability that a random observation + drawn from one group performs better/worse/equivalently than a random observation + drawn from the other group. Summary statistics such as the net treatment benefit, + win ratio, or win odds are then deduced from these probabilities. Confidence intervals + and p-values are obtained based on asymptotic results (Ozenne 2021 ), + non-parametric bootstrap, or permutations. The software enables the use of thresholds + of minimal importance difference, stratification, non-prioritized endpoints (O + Brien test), and can handle right-censoring and competing-risks. + date_publication: '2024-10-13' + bug_reports: https://github.com/bozenne/BuyseTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BuyseTest + url_git: https://github.com/bozenne/BuyseTest +Bvalue: + version: '1.0' + title: B-Value and Empirical Equivalence Bound + maintainer: Yi Zhao + description: 'Calculates B-value and empirical equivalence bound. B-value is defined + as the maximum magnitude of a confidence interval; and the empirical equivalence + bound is the minimum B-value at a certain level. A new two-stage procedure for + hypothesis testing is proposed, where the first stage is conventional hypothesis + testing and the second is an equivalence testing procedure using the introduced + empirical equivalence bound. See Zhao et al. (2019) "B-Value and Empirical Equivalence + Bound: A New Procedure of Hypothesis Testing" for details.' + date_publication: '2020-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Bvalue + url_git: '' +BVAR: + version: 1.0.5 + title: Hierarchical Bayesian Vector Autoregression + maintainer: Nikolas Kuschnig + description: |- + Estimation of hierarchical Bayesian vector autoregressive models + following Kuschnig & Vashold (2021) . + Implements hierarchical prior selection for conjugate priors in the fashion + of Giannone, Lenza & Primiceri (2015) . + Functions to compute and identify impulse responses, calculate forecasts, + forecast error variance decompositions and scenarios are available. + Several methods to print, plot and summarise results facilitate analysis. + date_publication: '2024-02-16' + bug_reports: https://github.com/nk027/bvar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BVAR + url_git: https://github.com/nk027/bvar +bvarsv: + version: '1.1' + title: |- + Bayesian Analysis of a Vector Autoregressive Model with + Stochastic Volatility and Time-Varying Parameters + maintainer: Fabian Krueger + description: R/C++ implementation of the model proposed by Primiceri ("Time Varying + Structural Vector Autoregressions and Monetary Policy", Review of Economic Studies, + 2005), with functionality for computing posterior predictive distributions and + impulse responses. + date_publication: '2015-11-25' + bug_reports: '' + url: https://sites.google.com/site/fk83research/code + url_cran: https://CRAN.R-project.org/package=bvarsv + url_git: '' +bvartools: + version: 0.2.4 + title: |- + Bayesian Inference of Vector Autoregressive and Error Correction + Models + maintainer: Franz X. Mohr + description: 'Assists in the set-up of algorithms for Bayesian inference of vector + autoregressive (VAR) and error correction (VEC) models. Functions for posterior + simulation, forecasting, impulse response analysis and forecast error variance + decomposition are largely based on the introductory texts of Chan, Koop, Poirier + and Tobias (2019, ISBN: 9781108437493), Koop and Korobilis (2010) + and Luetkepohl (2006, ISBN: 9783540262398).' + date_publication: '2024-01-08' + bug_reports: https://github.com/franzmohr/bvartools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bvartools + url_git: https://github.com/franzmohr/bvartools +BVARverse: + version: 0.0.1 + title: Tidy Bayesian Vector Autoregression + maintainer: Lukas Vashold + description: |- + Functions to prepare tidy objects from estimated models via 'BVAR' + (see Kuschnig & Vashold, 2019 ) and + visualisation thereof. Bridges the gap between estimating models with 'BVAR' + and plotting the results in a more sophisticated way with 'ggplot2' as well + as passing them on in a tidy format. + date_publication: '2020-09-22' + bug_reports: https://github.com/nk027/bvarverse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BVARverse + url_git: https://github.com/nk027/bvarverse +bvhar: + version: 2.2.2 + title: Bayesian Vector Heterogeneous Autoregressive Modeling + maintainer: Young Geun Kim + description: |- + Tools to model and forecast multivariate time series + including Bayesian Vector heterogeneous autoregressive (VHAR) model + by Kim & Baek (2023) (). + 'bvhar' can model Vector Autoregressive (VAR), VHAR, Bayesian VAR (BVAR), and Bayesian VHAR (BVHAR) models. + date_publication: '2025-02-28' + bug_reports: https://github.com/ygeunkim/bvhar/issues + url: https://ygeunkim.github.io/package/bvhar/ + url_cran: https://CRAN.R-project.org/package=bvhar + url_git: https://github.com/ygeunkim/bvhar +bvls: + version: '1.4' + title: The Stark-Parker algorithm for bounded-variable least squares + maintainer: Katharine M. Mullen + description: An R interface to the Stark-Parker implementation of analgorithm + for bounded-variable least squares + date_publication: '2013-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bvls + url_git: '' +bvpa: + version: 1.0.0 + title: Bivariate Pareto Distribution + maintainer: Biplab Paul + description: |- + Implements the EM algorithm with one-step Gradient Descent method to estimate + the parameters of the Block-Basu bivariate Pareto distribution with location + and scale. We also found parametric bootstrap and asymptotic confidence + intervals based on the observed Fisher information of scale and shape parameters, + and exact confidence intervals for location parameters. Details are in + Biplab Paul and Arabin Kumar Dey (2023) + "An EM algorithm for absolutely continuous Marshall-Olkin bivariate Pareto + distribution with location and scale"; + E L Lehmann and George Casella (1998) "Theory of Point Estimation"; + Bradley Efron and R J Tibshirani (1994) + "An Introduction to the Bootstrap"; + A P Dempster, N M Laird and D B Rubin + (1977) "Maximum Likelihood from Incomplete + Data via the EM Algorithm". + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bvpa + url_git: '' +BVSNLP: + version: 1.1.9 + title: |- + Bayesian Variable Selection in High Dimensional Settings using + Nonlocal Priors + maintainer: Amir Nikooienejad + description: |- + Variable/Feature selection in high or ultra-high dimensional + settings has gained a lot of attention recently specially in cancer genomic + studies. This package provides a Bayesian approach to tackle this problem, + where it exploits mixture of point masses at zero and nonlocal priors to + improve the performance of variable selection and coefficient estimation. + product moment (pMOM) and product inverse moment (piMOM) nonlocal priors + are implemented and can be used for the analyses. This package performs + variable selection for binary response and survival time response datasets + which are widely used in biostatistic and bioinformatics community. + Benefiting from parallel computing ability, it reports necessary outcomes + of Bayesian variable selection such as Highest Posterior Probability Model + (HPPM), Median Probability Model (MPM) and posterior inclusion probability + for each of the covariates in the model. The option to use Bayesian Model + Averaging (BMA) is also part of this package that can be exploited for + predictive power measurements in real datasets. + date_publication: '2020-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BVSNLP + url_git: '' +bwd: + version: 0.1.0 + title: Backward Procedure for Change-Point Detection + maintainer: Seung Jun Shin + description: Implements a backward procedure for single and multiple change point + detection proposed by Shin et al. . The backward approach is + particularly useful to detect short and sparse signals which is common in copy + number variation (CNV) detection. + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bwd + url_git: '' +bWGR: + version: 2.2.13 + title: Bayesian Whole-Genome Regression + maintainer: Alencar Xavier + description: |- + Whole-genome regression methods on Bayesian framework fitted via EM + or Gibbs sampling, single step (), + univariate and multivariate (, ), + with optional kernel term and sampling techniques (). + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bWGR + url_git: '' +BWGS: + version: 0.2.1 + title: BreedWheat Genomic Selection Pipeline + maintainer: Bangyou Zheng + description: |- + Package for Breed Wheat Genomic Selection Pipeline. + The R package 'BWGS' is developed by Louis Gautier Tran and Gilles Charmet . + This repository is forked from original repository + and modified as a R package. + date_publication: '2021-09-23' + bug_reports: https://github.com/byzheng/BWGS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BWGS + url_git: https://github.com/byzheng/BWGS +bwimage: + version: '1.3' + title: Describe Image Patterns in Natural Structures + maintainer: Carlos Biagolini-Jr. + description: A computational tool to describe patterns in black and white images + from natural structures. 'bwimage' implemented functions for exceptionally broad + subject. For instance, 'bwimage' provide examples that range from calculation + of canopy openness, description of patterns in vertical vegetation structure, + to patterns in bird nest structure. + date_publication: '2020-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bwimage + url_git: '' +BwQuant: + version: 0.1.0 + title: Bandwidth Selectors for Local Linear Quantile Regression + maintainer: Mercedes Conde-Amboage + description: Bandwidth selectors for local linear quantile regression, including + cross-validation and plug-in methods. The local linear quantile regression estimate + is also implemented. + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=BwQuant + url_git: '' +bws: + version: 0.1.0 + title: Bayesian Weighted Sums + maintainer: Phuc H. Nguyen + description: |- + An interface to the Bayesian Weighted Sums model implemented in 'RStan'. + It estimates the summed effect of multiple, often moderately to highly correlated, + continuous predictors. Its applications can be found in analysis of exposure mixtures. + The model was proposed by Hamra, Maclehose, Croen, Kauffman, and + Newschaffer (2021) . + This implementation includes an extension to model binary outcome. + date_publication: '2022-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bws + url_git: '' +BWStest: + version: 0.2.3 + title: Baumgartner Weiss Schindler Test of Equal Distributions + maintainer: Steven E. Pav + description: |- + Performs the 'Baumgartner-Weiss-Schindler' two-sample test of equal + probability distributions, . Also performs + similar rank-based tests for equal probability distributions due to + Neuhauser and + Murakami . + date_publication: '2023-10-10' + bug_reports: https://github.com/shabbychef/BWStest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=BWStest + url_git: https://github.com/shabbychef/BWStest +bwsTools: + version: 1.2.0 + title: Tools for Case 1 Best-Worst Scaling (MaxDiff) Designs + maintainer: Mark White + description: |- + Tools to design best-worst scaling designs (i.e., balanced incomplete block designs) and + to analyze data from these designs, using aggregate and individual methods such as: difference + scores, Louviere, Lings, Islam, Gudergan, & Flynn (2013) ; + analytical estimation, Lipovetsky & Conklin (2014) ; empirical + Bayes, Lipovetsky & Conklin (2015) ; Elo, Hollis (2018) + ; and network-based measures. + date_publication: '2020-08-26' + bug_reports: https://github.com/markhwhiteii/bwsTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bwsTools + url_git: https://github.com/markhwhiteii/bwsTools +bysykkel: + version: 0.3.1 + title: Get City Bike Data from Norway + maintainer: Iman Ghayoornia + description: |- + Functions to get and download city bike data from + the website and API service of each city bike service in Norway. The + package aims to reduce time spent on getting Norwegian city bike data, + and lower barriers to start analyzing it. The data is retrieved from + Oslo City Bike, Bergen City Bike, and Trondheim City Bike. The data is + made available under NLOD 2.0 . + date_publication: '2020-04-19' + bug_reports: http://github.com/imangR/bysykkel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=bysykkel + url_git: http://github.com/imangR/bysykkel +bytescircle: + version: 1.1.2 + title: Statistics About Bytes Contained in a File as a Circle Plot + maintainer: Roberto S. Galende + description: |- + Shows statistics about bytes contained in a file + as a circle graph of deviations from mean in sigma increments. + The function can be useful for statistically analyze the content of files + in a glimpse: text files are shown as a green centered crown, compressed + and encrypted files should be shown as equally distributed variations with + a very low CV (sigma/mean), and other types of files can be classified between + these two categories depending on their text vs binary content, which can be + useful to quickly determine how information is stored inside them (databases, + multimedia files, etc). + date_publication: '2021-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bytescircle + url_git: '' +bzinb: + version: 1.0.8 + title: Bivariate Zero-Inflated Negative Binomial Model Estimator + maintainer: Hunyong Cho + description: Provides a maximum likelihood estimation of Bivariate Zero-Inflated + Negative Binomial (BZINB) model or the nested model parameters. Also estimates + the underlying correlation of the a pair of count data. See Cho, H., Liu, C., + Preisser, J., and Wu, D. (In preparation) for details. + date_publication: '2024-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=bzinb + url_git: '' +c060: + version: 0.3-0 + title: |- + Extended Inference for Lasso and Elastic-Net Regularized Cox and + Generalized Linear Models + maintainer: Frederic Bertrand + description: The c060 package provides additional functions to perform stability + selection, model validation and parameter tuning for glmnet models. + date_publication: '2023-03-23' + bug_reports: https://github.com/fbertran/c060/issues/ + url: https://fbertran.github.io/c060/ + url_cran: https://CRAN.R-project.org/package=c060 + url_git: https://github.com/fbertran/c060/ +C19dNUTS: + version: 1.0.1 + title: Dataset of Regional COVID-19 Deaths per 100,000 Pop (NUTS) + maintainer: Thomas Wieland + description: Dataset containing cumulative COVID-19 deaths (absolute and per 100,000 + pop) at the regional level (mostly NUTS 3) for 31 EU/EFTA countries. + date_publication: '2022-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=C19dNUTS + url_git: '' +c212: + version: 1.0.1 + title: |- + Methods for Detecting Safety Signals in Clinical Trials Using + Body-Systems (System Organ Classes) + maintainer: Raymond Carragher + description: |- + Provides a self-contained set of methods to aid clinical trial + safety investigators, statisticians and researchers, in the early + detection of adverse events using groupings by body-system or system + organ class. This work was supported by the Engineering and Physical + Sciences Research Council (UK) (EPSRC) [award reference 1521741] and + Frontier Science (Scotland) Ltd. The package title c212 is in reference + to the original Engineering and Physical Sciences Research Council (UK) + funded project which was named CASE 2/12. + date_publication: '2024-11-05' + bug_reports: https://github.com/rcarragh/c212/issues + url: '' + url_cran: https://CRAN.R-project.org/package=c212 + url_git: https://github.com/rcarragh/c212 +c2c: + version: 0.1.0 + title: |- + Compare Two Classifications or Clustering Solutions of Varying + Structure + maintainer: Mitchell Lyons + description: |- + Compare two classifications or clustering solutions that may or may + not have the same number of classes, and that might have hard or soft + (fuzzy, probabilistic) membership. Calculate various metrics to assess how + the clusters compare to each other. The calculations are simple, but provide + a handy tool for users unfamiliar with matrix multiplication. This package + is not geared towards traditional accuracy assessment for classification/ + mapping applications - the motivating use case is for comparing a + probabilistic clustering solution to a set of reference or existing class + labels that could have any number of classes (that is, without having to + degrade the probabilistic clustering to hard classes). + date_publication: '2017-07-23' + bug_reports: https://github.com/mitchest/c2c/issues + url: '' + url_cran: https://CRAN.R-project.org/package=c2c + url_git: https://github.com/mitchest/c2c/ +c2z: + version: 0.2.0 + title: A Reference Manager + maintainer: Øystein Olav Skaar + description: |- + 'Cristin' to 'Zotero' ('c2z') aims at obtaining total + dominion over 'Cristin' ('Current Research Information SysTem in + Norway') and 'Zotero'. The package enables manipulating 'Zotero' + libraries using 'R'. Import references from 'Cristin', 'Regjeringen', + 'CRAN', 'ISBN' ('Alma', 'LoC'), and 'DOI' ('CrossRef', 'DataCite') to + a 'Zotero' library. Add, edit, copy, or delete items, including + attachments and collections, and export references to 'BibLaTeX' (and + other formats). + date_publication: '2023-08-10' + bug_reports: https://github.com/oeysan/c2z/issues/ + url: https://oeysan.github.io/c2z/ + url_cran: https://CRAN.R-project.org/package=c2z + url_git: https://github.com/oeysan/c2z/ +c3: + version: 0.3.0 + title: '''C3.js'' Chart Library' + maintainer: Matt Johnson + description: |- + Create interactive charts with the 'C3.js' charting library. All plot + types in 'C3.js' are available and include line, bar, scatter, and mixed geometry plots. Plot + annotations, labels and axis are highly adjustable. Interactive web based charts can be embedded + in R Markdown documents or Shiny web applications. + date_publication: '2020-03-16' + bug_reports: https://github.com/mrjoh3/c3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=c3 + url_git: https://github.com/mrjoh3/c3 +c3net: + version: 1.1.1.1 + title: Inferring Large-Scale Gene Networks with C3NET + maintainer: Gokmen Altay + description: |- + Allows inferring gene regulatory networks + with direct physical interactions from microarray expression + data using C3NET. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=c3net + url_git: '' +C443: + version: 3.4.0 + title: See a Forest for the Trees + maintainer: Aniek Sies + description: Get insight into a forest of classification trees, by calculating similarities + between the trees, and subsequently clustering them. Each cluster is represented + by it's most central cluster member. The package implements the methodology described + in Sies & Van Mechelen (2020) . + date_publication: '2023-06-21' + bug_reports: https://github.com/KULeuven-PPW-OKPIV/C443/issues + url: '' + url_cran: https://CRAN.R-project.org/package=C443 + url_git: https://github.com/KULeuven-PPW-OKPIV/C443 +C50: + version: 0.1.8 + title: C5.0 Decision Trees and Rule-Based Models + maintainer: Max Kuhn + description: |- + C5.0 decision trees and rule-based models for pattern + recognition that extend the work of Quinlan (1993, + ISBN:1-55860-238-0). + date_publication: '2023-02-08' + bug_reports: https://github.com/topepo/C5.0/issues + url: https://topepo.github.io/C5.0/ + url_cran: https://CRAN.R-project.org/package=C50 + url_git: '' +ca: + version: 0.71.1 + title: Simple, Multiple and Joint Correspondence Analysis + maintainer: Oleg Nenadic + description: Computation and visualization of simple, multiple and joint correspondence + analysis. + date_publication: '2020-01-24' + bug_reports: '' + url: http://www.carme-n.org/ + url_cran: https://CRAN.R-project.org/package=ca + url_git: '' +CA3variants: + version: 3.3.1 + title: Three-Way Correspondence Analysis Variants + maintainer: Rosaria Lombardo + description: |- + Provides four variants of three-way correspondence analysis (ca): + three-way symmetrical ca, three-way non-symmetrical ca, three-way ordered symmetrical ca + and three-way ordered non-symmetrical ca. + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CA3variants + url_git: '' +cabinets: + version: 0.6.0 + title: Project Specific Workspace Organization Templates + maintainer: Nick Williams + description: |- + Creates project specific directory and file templates that are + written to a .Rprofile file. Upon starting a new R session, these templates + can be used to streamline the creation of new directories that are + standardized to the user's preferences and can include the initiation of a + git repository, an RStudio R project, and project-local dependency management + with the 'renv' package. + date_publication: '2020-11-07' + bug_reports: https://github.com/nt-williams/cabinets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cabinets + url_git: https://github.com/nt-williams/cabinets +cabootcrs: + version: 2.1.0 + title: |- + Bootstrap Confidence Regions for Simple and Multiple + Correspondence Analysis + maintainer: Trevor Ringrose + description: |- + Performs simple correspondence analysis on a two-way contingency table, + or multiple correspondence analysis (homogeneity analysis) + on data with p categorical variables, + and produces bootstrap-based elliptical confidence regions around the + projected coordinates for the category points. + Includes routines to plot the results in a variety of styles. + Also reports the standard numerical output for correspondence analysis. + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cabootcrs + url_git: '' +cacc: + version: 0.1.1 + title: Conjunctive Analysis of Case Configurations + maintainer: Asier Moneva + description: A set of functions to conduct Conjunctive Analysis of Case Configurations + (CACC) as described in Miethe, Hart, and Regoeczi (2008) , + and identify and quantify situational clustering in dominant case configurations + as described in Hart (2019) . Initially conceived + as an exploratory technique for multivariate analysis of categorical data, CACC + has developed to include formal statistical tests that can be applied in a wide + variety of contexts. This technique allows examining composite profiles of different + units of analysis in an alternative way to variable-oriented methods. + date_publication: '2024-10-03' + bug_reports: https://github.com/amoneva/cacc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cacc + url_git: https://github.com/amoneva/cacc +cache: + version: 0.0.3 + title: Cache and Retrieve Computation Results + maintainer: Olivier Binette + description: Easily cache and retrieve computation results. The package works seamlessly + across interactive R sessions, R scripts and Rmarkdown documents. + date_publication: '2022-03-26' + bug_reports: https://github.com/OlivierBinette/cache/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cache + url_git: https://github.com/OlivierBinette/cache +cachem: + version: 1.1.0 + title: Cache R Objects with Automatic Pruning + maintainer: Winston Chang + description: |- + Key-value stores with automatic pruning. Caches can limit + either their total size or the age of the oldest object (or both), + automatically pruning objects to maintain the constraints. + date_publication: '2024-05-16' + bug_reports: '' + url: https://cachem.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=cachem + url_git: https://github.com/r-lib/cachem +CACIMAR: + version: 1.0.0 + title: |- + Cross-Species Analysis of Cell Identities, Markers and + Regulations + maintainer: Junyao Jiang + description: A toolkit to perform cross-species analysis based on scRNA-seq data. + This package contains 5 main features. (1) identify Markers in each cluster. (2) + Cell type annotation (3) identify conserved markers. (4) identify conserved cell + types. (5) identify conserved modules of regulatory networks. + date_publication: '2022-05-18' + bug_reports: https://github.com/jiang-junyao/CACIMAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CACIMAR + url_git: https://github.com/jiang-junyao/CACIMAR +cacIRT: + version: '1.4' + title: |- + Classification Accuracy and Consistency under Item Response + Theory + maintainer: Quinn N. Lathrop + description: Computes classification accuracy and consistency indices under Item + Response Theory. Implements the total score IRT-based methods in Lee, Hanson & + Brennen (2002) and Lee (2010), the IRT-based methods in Rudner (2001, 2005), and + the total score nonparametric methods in Lathrop & Cheng (2014). For dichotomous + and polytomous tests. + date_publication: '2015-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cacIRT + url_git: '' +CaDENCE: + version: 1.2.5 + title: |- + Conditional Density Estimation Network Construction and + Evaluation + maintainer: Alex J. Cannon + description: Parameters of a user-specified probability distribution are modelled + by a multi-layer perceptron artificial neural network. This framework can be used + to implement probabilistic nonlinear models including mixture density networks, + heteroscedastic regression models, zero-inflated models, etc. following Cannon + (2012) . + date_publication: '2017-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CaDENCE + url_git: '' +CADF: + version: '0.1' + title: Customer Analytics Data Formatting + maintainer: Ludwig Steven + description: Converts customer transaction data (ID, purchase date) into a R6 class + called customer. The class stores various customer analytics calculations at + the customer level. The package also contains functionality to convert data in + the R6 class to data.frames that can serve as inputs for various customer analytics + models. + date_publication: '2024-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CADF + url_git: '' +CADFtest: + version: 0.3-3 + title: |- + A Package to Perform Covariate Augmented Dickey-Fuller Unit Root + Tests + maintainer: Claudio Lupi + description: |- + Hansen's (1995) Covariate-Augmented + Dickey-Fuller (CADF) test. The only required argument is y, the + Tx1 time series to be tested. If no stationary covariate X is + passed to the procedure, then an ordinary ADF test is + performed. The p-values of the test are computed using the + procedure illustrated in Lupi (2009). + date_publication: '2017-06-02' + bug_reports: '' + url: http://www.jstatsoft.org/v32/i02 + url_cran: https://CRAN.R-project.org/package=CADFtest + url_git: '' +caesar: + version: 1.1.0 + title: Encrypts and Decrypts Strings + maintainer: Jacob Kaplan + description: |- + Encrypts and decrypts strings using either the Caesar cipher or a + pseudorandom number generation (using set.seed()) method. + date_publication: '2020-09-03' + bug_reports: https://github.com/jacobkap/caesar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caesar + url_git: https://github.com/jacobkap/caesar +CAESAR.Suite: + version: 0.1.0 + title: |- + CAESAR: a Cross-Technology and Cross-Resolution Framework for + Spatial Omics Annotation + maintainer: Xiao Zhang + description: Biotechnology in spatial omics has advanced rapidly over the past few + years, enhancing both throughput and resolution. However, existing annotation + pipelines in spatial omics predominantly rely on clustering methods, lacking the + flexibility to integrate extensive annotated information from single-cell RNA + sequencing (scRNA-seq) due to discrepancies in spatial resolutions, species, or + modalities. Here we introduce the CAESAR suite, an open-source software package + that provides image-based spatial co-embedding of locations and genomic features. + It uniquely transfers labels from scRNA-seq reference, enabling the annotation + of spatial omics datasets across different technologies, resolutions, species, + and modalities, based on the conserved relationship between signature genes and + cells/locations at an appropriate level of granularity. Notably, CAESAR enriches + location-level pathways, allowing for the detection of gradual biological pathway + activation within spatially defined domain types. More details on the methods + related to our paper currently under submission. A full reference to the paper + will be provided in future versions once the paper is published. + date_publication: '2024-09-16' + bug_reports: https://github.com/XiaoZhangryy/CAESAR.Suite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CAESAR.Suite + url_git: https://github.com/XiaoZhangryy/CAESAR.Suite +caffsim: + version: 0.2.2 + title: |- + Simulation of Plasma Caffeine Concentrations by Using Population + Pharmacokinetic Model + maintainer: Sungpil Han + description: Simulate plasma caffeine concentrations using population pharmacokinetic + model described in Lee, Kim, Perera, McLachlan and Bae (2015) . + date_publication: '2017-08-28' + bug_reports: https://github.com/asancpt/caffsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caffsim + url_git: https://github.com/asancpt/caffsim +CAGR: + version: 1.1.0 + title: Compound Annual Growth Rate + maintainer: Debopam Rakshit + description: A time series usually does not have a uniform growth rate. Compound + Annual Growth Rate measures the average annual growth over a given period. More + details can be found in Bardhan et al. (2022) . + date_publication: '2024-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CAGR + url_git: '' +cAIC4: + version: '1.0' + title: Conditional Akaike Information Criterion for 'lme4' and 'nlme' + maintainer: David Ruegamer + description: |- + Provides functions for the estimation of the conditional Akaike + information in generalized mixed-effect models fitted with (g)lmer() + from 'lme4', lme() from 'nlme' and gamm() from 'mgcv'. + For a manual on how to use 'cAIC4', see Saefken et al. (2021) . + date_publication: '2021-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cAIC4 + url_git: '' +CAinterprTools: + version: 1.1.0 + title: |- + Graphical Aid in Correspondence Analysis Interpretation and + Significance Testings + maintainer: Gianmarco Alberti + description: 'Allows to plot a number of information related to the interpretation + of Correspondence Analysis'' results. It provides the facility to plot the contribution + of rows and columns categories to the principal dimensions, the quality of points + display on selected dimensions, the correlation of row and column categories to + selected dimensions, etc. It also allows to assess which dimension(s) is important + for the data structure interpretation by means of different statistics and tests. + The package also offers the facility to plot the permuted distribution of the + table total inertia as well as of the inertia accounted for by pairs of selected + dimensions. Different facilities are also provided that aim to produce interpretation-oriented + scatterplots. Reference: Alberti 2015 .' + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CAinterprTools + url_git: '' +Cairo: + version: 1.6-2 + title: |- + R Graphics Device using Cairo Graphics Library for Creating + High-Quality Bitmap (PNG, JPEG, TIFF), Vector (PDF, SVG, + PostScript) and Display (X11 and Win32) Output + maintainer: Simon Urbanek + description: R graphics device using cairographics library that can be used to create + high-quality vector (PDF, PostScript and SVG) and bitmap output (PNG,JPEG,TIFF), + and high-quality rendering in displays (X11 and Win32). Since it uses the same + back-end for all output, copying across formats is WYSIWYG. Files are created + without the dependence on X11 or other external programs. This device supports + alpha channel (semi-transparent drawing) and resulting images can contain transparent + and semi-transparent regions. It is ideal for use in server environments (file + output) and as a replacement for other devices that don't have Cairo's capabilities + such as alpha support or anti-aliasing. Backends are modular such that any subset + of backends is supported. + date_publication: '2023-11-28' + bug_reports: '' + url: http://www.rforge.net/Cairo/ + url_cran: https://CRAN.R-project.org/package=Cairo + url_git: '' +CAISEr: + version: 1.0.17 + title: Comparison of Algorithms with Iterative Sample Size Estimation + maintainer: Felipe Campelo + description: |- + Functions for performing experimental comparisons of algorithms + using adequate sample sizes for power and accuracy. Implements the + methodology originally presented in Campelo and Takahashi (2019) + + for the comparison of two algorithms, and later generalised in + Campelo and Wanner (Submitted, 2019) . + date_publication: '2022-11-16' + bug_reports: https://github.com/fcampelo/CAISEr/issues + url: https://fcampelo.github.io/CAISEr/ + url_cran: https://CRAN.R-project.org/package=CAISEr + url_git: '' +calACS: + version: 2.2.2 + title: Calculations for All Common Subsequences + maintainer: Alan Gu + description: Implements several string comparison algorithms, including calACS (count + all common subsequences), lenACS (calculate the lengths of all common subsequences), + and lenLCS (calculate the length of the longest common subsequence). Some algorithms + differentiate between the more strict definition of subsequence, where a common + subsequence cannot be separated by any other items, from its looser counterpart, + where a common subsequence can be interrupted by other items. This difference + is shown in the suffix of the algorithm (-Strict vs -Loose). For example, q-w + is a common subsequence of q-w-e-r and q-e-w-r on the looser definition, but not + on the more strict definition. calACSLoose Algorithm from Wang, H. All common + subsequences (2007) IJCAI International Joint Conference on Artificial Intelligence, + pp. 635-640. + date_publication: '2016-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=calACS + url_git: '' +CALANGO: + version: 1.0.20 + title: Comparative Analysis with Annotation-Based Genomic Components + maintainer: Felipe Campelo + description: |- + A first-principle, phylogeny-aware comparative genomics tool for + investigating associations between terms used to annotate genomic + components (e.g., Pfam IDs, Gene Ontology terms,) with quantitative + or rank variables such as number of cell types, genome size, or + density of specific genomic elements. See the project website for + more information, documentation and examples, and + for the full paper. + date_publication: '2024-09-05' + bug_reports: https://github.com/fcampelo/CALANGO/issues/ + url: https://labpackages.github.io/CALANGO/ + url_cran: https://CRAN.R-project.org/package=CALANGO + url_git: '' +CalcThemAll.PRM: + version: 1.1.1 + title: |- + Calculate Pesticide Risk Metric (PRM) Values from Multiple + Pesticides...Calc Them All + maintainer: Alexander Bezzina + description: |- + Contains functions which can be used to calculate Pesticide Risk Metric + values in aquatic environments from concentrations of multiple pesticides with known species sensitive + distributions (SSDs). Pesticides provided by this package have all be validated + however if the user has their own pesticides with SSD values they can append them + to the pesticide_info table to include them in estimates. + date_publication: '2024-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CalcThemAll.PRM + url_git: '' +Calculator.LR.FNs: + version: '1.3' + title: Calculator for LR Fuzzy Numbers + maintainer: Abbas Parchami + description: Arithmetic operations scalar multiplication, addition, subtraction, + multiplication and division of LR fuzzy numbers (which are on the basis of extension + principle) have a complicate form for using in fuzzy Statistics, fuzzy Mathematics, + machine learning, fuzzy data analysis and etc. Calculator for LR Fuzzy Numbers + package relieve and aid applied users to achieve a simple and closed form for + some complicated operator based on LR fuzzy numbers and also the user can easily + draw the membership function of the obtained result by this package. + date_publication: '2018-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Calculator.LR.FNs + url_git: '' +calculus: + version: 1.0.1 + title: High Dimensional Numerical and Symbolic Calculus + maintainer: Emanuele Guidotti + description: 'Efficient C++ optimized functions for numerical and symbolic calculus + as described in Guidotti (2022) . It includes basic + arithmetic, tensor calculus, Einstein summing convention, fast computation of + the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, + multivariate Hermite polynomials, high-order derivatives, ordinary differential + equations, differential operators (Gradient, Jacobian, Hessian, Divergence, Curl, + Laplacian) and numerical integration in arbitrary orthogonal coordinate systems: + cartesian, polar, spherical, cylindrical, parabolic or user defined by custom + scale factors.' + date_publication: '2023-03-09' + bug_reports: https://github.com/eguidotti/calculus/issues + url: https://calculus.eguidotti.com + url_cran: https://CRAN.R-project.org/package=calculus + url_git: '' +calcUnique: + version: 0.1.2 + title: Simple Wrapper for Computationally Expensive Functions + maintainer: Stephen Froehlich + description: |- + This is a one-function package that will pass only unique values to a computationally-expensive function that returns an output of the same length as the input. + In importing and working with tidy data, it is common to have index columns, often including time stamps that are far from unique. Some functions to work with these such as text conversion to other variable types (e.g. as.POSIXct()), various grep()-based functions, and often the cut() function are relatively slow when working with tens of millions of rows or more. + date_publication: '2020-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=calcUnique + url_git: https://github.com/stephenbfroehlich/calcUnique +calendar: + version: 0.2.0 + title: |- + Create, Read, Write, and Work with 'iCalendar' Files, Calendars + and Scheduling Data + maintainer: Robin Lovelace + description: |- + Provides function to create, read, write, and work with + 'iCalendar' files (which typically have '.ics' or '.ical' extensions), + and the scheduling data, calendars and timelines of people, + organisations and other entities that they represent. 'iCalendar' is + an open standard for exchanging calendar and scheduling information + between users and computers, described at . + date_publication: '2024-08-20' + bug_reports: https://github.com/ATFutures/calendar/issues + url: https://atfutures.github.io/calendar/ + url_cran: https://CRAN.R-project.org/package=calendar + url_git: https://github.com/atfutures/calendar +calendR: + version: '1.2' + title: Ready to Print Monthly and Yearly Calendars Made with 'ggplot2' + maintainer: José Carlos Soage González + description: Contains the function calendR() for creating fully customizable monthly + and yearly calendars (colors, fonts, formats, ...) and even heatmap calendars. + In addition, it allows saving the calendars in ready to print A4 format PDF files. + date_publication: '2023-10-05' + bug_reports: '' + url: https://r-coder.com/ + url_cran: https://CRAN.R-project.org/package=calendR + url_git: '' +calendRio: + version: 0.2.1 + title: '''calendR'' Fork with Additional Features (Backwards Compatible)' + maintainer: Marcel Schilling + description: |- + Fork of 'calendR' R package to generate ready to print + calendars with 'ggplot2' (see ) + with additional features (backwards compatible). + 'calendRio' provides a 'calendR()' function that serves as a drop-in + replacement for the upstream version but allows for additional + parameters unlocking extra functionality. + date_publication: '2024-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=calendRio + url_git: '' +CALF: + version: 1.0.17 + title: Coarse Approximation Linear Function + maintainer: John Ford + description: Contains greedy algorithms for coarse approximation linear functions. + date_publication: '2022-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CALF + url_git: '' +CALIBERrfimpute: + version: 1.0-7 + title: Multiple Imputation Using MICE and Random Forest + maintainer: Anoop Shah + description: Functions to impute using random forest under full conditional specifications + (multivariate imputation by chained equations). The methods are described in Shah + and others (2014) . + date_publication: '2022-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CALIBERrfimpute + url_git: '' +calibmsm: + version: 1.1.1 + title: |- + Calibration Plots for the Transition Probabilities from + Multistate Models + maintainer: Alexander Pate + description: |- + Assess the calibration of an existing (i.e. previously developed) multistate + model through calibration plots. + Calibration is assessed using one of three methods. 1) Calibration methods for + binary logistic regression models applied at a fixed time point in conjunction + with inverse probability of censoring weights. 2) Calibration methods for + multinomial logistic regression models applied at a fixed time point in conjunction + with inverse probability of censoring weights. 3) Pseudo-values estimated using + the Aalen-Johansen estimator of observed risk. All methods are applied in conjunction + with landmarking when required. These calibration plots evaluate the calibration + (in a validation cohort of interest) of the transition probabilities estimated from an + existing multistate model. While package development has focused on multistate + models, calibration plots can be produced for any model which utilises information + post baseline to update predictions (e.g. dynamic models); competing risks models; + or standard single outcome survival models, where predictions can be made at + any landmark time. Please see Pate et al. (2024) + and Pate et al. (2024) . + date_publication: '2024-06-14' + bug_reports: '' + url: https://alexpate30.github.io/calibmsm/ + url_cran: https://CRAN.R-project.org/package=calibmsm + url_git: '' +calibrar: + version: 0.9.0 + title: Automated Parameter Estimation for Complex Models + maintainer: Ricardo Oliveros-Ramos + description: |- + General optimisation and specific tools for the parameter estimation (i.e. calibration) of complex models, including stochastic ones. It implements generic functions that can be used for fitting any type of models, especially those with non-differentiable objective functions, with the same syntax as base::optim. + It supports multiple phases estimation (sequential parameter masking), constrained optimization (bounding box restrictions) and automatic parallel computation of numerical gradients. + Some common maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs is provided. + See for more details. + date_publication: '2024-02-14' + bug_reports: https://github.com/roliveros-ramos/calibrar/issues + url: https://roliveros-ramos.github.io/calibrar/ + url_cran: https://CRAN.R-project.org/package=calibrar + url_git: '' +calibrate: + version: 1.7.7 + title: Calibration of Scatterplot and Biplot Axes + maintainer: Jan Graffelman + description: |- + Package for drawing calibrated scales with tick marks on (non-orthogonal) + variable vectors in scatterplots and biplots. Also provides some functions for biplot creation and + for multivariate analysis such as principal coordinate analysis. + date_publication: '2020-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=calibrate + url_git: '' +calibrateBinary: + version: '0.1' + title: Calibration for Computer Experiments with Binary Responses + maintainer: Chih-Li Sung + description: Performs the calibration procedure proposed by Sung et al. (2018+) + . This calibration method is particularly useful when the outputs + of both computer and physical experiments are binary and the estimation for the + calibration parameters is of interest. + date_publication: '2018-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=calibrateBinary + url_git: '' +CalibrateSSB: + version: 1.3.0 + title: Weighting and Estimation for Panel Data with Non-Response + maintainer: Oyvind Langsrud + description: Functions to calculate weights, estimates of changes and corresponding + variance estimates for panel data with non-response. Partially overlapping samples + are handled. Initially, weights are calculated by linear calibration. By default, + the survey package is used for this purpose. It is also possible to use ReGenesees, + which can be installed from . Variances + of linear combinations (changes and averages) and ratios are calculated from a + covariance matrix based on residuals according to the calibration model. The methodology + was presented at the conference, The Use of R in Official Statistics, and is described + in Langsrud (2016) . + date_publication: '2020-08-04' + bug_reports: https://github.com/statisticsnorway/CalibrateSSB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CalibrateSSB + url_git: https://github.com/statisticsnorway/CalibrateSSB +calibrationband: + version: 0.2.1 + title: Calibration Bands + maintainer: Marius Puke + description: Package to assess the calibration of probabilistic classifiers using + confidence bands for monotonic functions. Besides testing the classical goodness-of-fit + null hypothesis of perfect calibration, the confidence bands calculated within + that package facilitate inverted goodness-of-fit tests whose rejection allows + for a sought-after conclusion of a sufficiently well-calibrated model. The package + creates flexible graphical tools to perform these tests. For construction details + see also Dimitriadis, Dümbgen, Henzi, Puke, Ziegel (2022) . + date_publication: '2022-08-09' + bug_reports: '' + url: https://marius-cp.github.io/calibrationband/ + url_cran: https://CRAN.R-project.org/package=calibrationband + url_git: https://github.com/marius-cp/calibrationband +CalibrationCurves: + version: 2.0.4 + title: Calibration Performance + maintainer: De Cock Bavo + description: Plots calibration curves and computes statistics for assessing calibration + performance. See De Cock Campo (2023) and Van + Calster et al. (2016) . + date_publication: '2025-01-18' + bug_reports: '' + url: https://bavodc.github.io/websiteCalibrationCurves/ + url_cran: https://CRAN.R-project.org/package=CalibrationCurves + url_git: '' +calibrator: + version: 1.2-8 + title: Bayesian Calibration of Complex Computer Codes + maintainer: Robin K. S. Hankin + description: |- + Performs Bayesian calibration of computer models as per + Kennedy and O'Hagan 2001. The package includes routines to find the + hyperparameters and parameters; see the help page for stage1() for a + worked example using the toy dataset. A tutorial is provided in the + calex.Rnw vignette; and a suite of especially simple one dimensional + examples appears in inst/doc/one.dim/. + date_publication: '2019-03-07' + bug_reports: https://github.com/RobinHankin/calibrator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=calibrator + url_git: https://github.com/RobinHankin/calibrator.git +CalibratR: + version: 0.1.2 + title: Mapping ML Scores to Calibrated Predictions + maintainer: Dominik Heider + description: 'Transforms your uncalibrated Machine Learning scores to well-calibrated + prediction estimates that can be interpreted as probability estimates. The implemented + BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015, ISBN:0-262-51129-0). + Please cite this paper: Schwarz J and Heider D, Bioinformatics 2019, 35(14):2458-2465.' + date_publication: '2019-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CalibratR + url_git: '' +calidad: + version: 0.7.0 + title: Assesses the Quality of Estimates Made by Complex Sample Designs + maintainer: Klaus Lehmann + description: |- + Assesses the quality of estimates made by complex sample designs, + following the methodology developed by the National Institute of Statistics Chile (2020, ) + and by Economic Commission for Latin America and + Caribbean (2020, ), (2024, ). + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=calidad + url_git: '' +callback: + version: 0.1.1 + title: Computes Statistics from Discrimination Experimental Data + maintainer: Emmanuel Duguet + description: In discrimination experiments candidates are sent on the same test + (e.g. job, house rental) and one examines whether they receive the same outcome. + The number of non negative answers are first examined in details looking for outcome + differences. Then various answering rates and their exacts confidence intervals + are computed. Last, exact and asymptotic discrimination tests are performed. Graphical + methods are also available. + date_publication: '2024-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=callback + url_git: '' +callme: + version: 0.1.11 + title: Easily Compile and Call Inline 'C' Functions + maintainer: Mike Cheng + description: |- + Compile inline 'C' code and easily call with + automatically generated wrapper functions. By allowing user-defined headers + and compilation flags (preprocessor, compiler and linking flags) the user + can configure optimization options and linking to third party + libraries. Multiple functions may be defined in a single block of code - which + may be defined in a string or a path to a source file. + date_publication: '2024-11-28' + bug_reports: https://github.com/coolbutuseless/callme/issues + url: https://coolbutuseless.github.io/package/callme/ + url_cran: https://CRAN.R-project.org/package=callme + url_git: https://github.com/coolbutuseless/callme +callr: + version: 3.7.6 + title: Call R from R + maintainer: Gábor Csárdi + description: |- + It is sometimes useful to perform a computation in a separate + R process, without affecting the current R process at all. This + packages does exactly that. + date_publication: '2024-03-25' + bug_reports: https://github.com/r-lib/callr/issues + url: https://callr.r-lib.org + url_cran: https://CRAN.R-project.org/package=callr + url_git: https://github.com/r-lib/callr +callsync: + version: 0.2.3 + title: |- + Recording Synchronisation, Call Detection and Assignment, Audio + Analysis + maintainer: Simeon Q. Smeele + description: |- + Intended to analyse recordings from multiple microphones (e.g., backpack + microphones in captive setting). It allows users to align recordings even if there is non-linear + drift of several minutes between them. A call detection and assignment pipeline can be used + to find vocalisations and assign them to the vocalising individuals (even if the vocalisation + is picked up on multiple microphones). The tracing and measurement functions allow for detailed + analysis of the vocalisations and filtering of noise. Finally, the package includes a function + to run spectrographic cross correlation, which can be used to compare vocalisations. It also + includes multiple other functions related to analysis of vocal behaviour. + date_publication: '2024-05-24' + bug_reports: https://github.com/simeonqs/callsync/issues + url: '' + url_cran: https://CRAN.R-project.org/package=callsync + url_git: https://github.com/simeonqs/callsync +calmate: + version: 0.13.0 + title: |- + Improved Allele-Specific Copy Number of SNP Microarrays for + Downstream Segmentation + maintainer: Henrik Bengtsson + description: The CalMaTe method calibrates preprocessed allele-specific copy number + estimates (ASCNs) from DNA microarrays by controlling for single-nucleotide polymorphism-specific + allelic crosstalk. The resulting ASCNs are on average more accurate, which increases + the power of segmentation methods for detecting changes between copy number states + in tumor studies including copy neutral loss of heterozygosity. CalMaTe applies + to any ASCNs regardless of preprocessing method and microarray technology, e.g. + Affymetrix and Illumina. + date_publication: '2022-03-08' + bug_reports: https://github.com/HenrikBengtsson/calmate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=calmate + url_git: https://github.com/HenrikBengtsson/calmate/ +calmr: + version: 0.6.1 + title: Canonical Associative Learning Models and their Representations + maintainer: Victor Navarro + description: Implementations of canonical associative learning models, with tools + to run experiment simulations, estimate model parameters, and compare model representations. + Experiments and results are represented using S4 classes and methods. + date_publication: '2024-03-14' + bug_reports: https://github.com/victor-navarro/calmr/issues + url: https://victornavarro.org/calmr/ + url_cran: https://CRAN.R-project.org/package=calmr + url_git: https://github.com/victor-navarro/calmr +calpassapi: + version: 0.0.3 + title: R Interface to Access CalPASS API + maintainer: Vinh Nguyen + description: |- + Implements methods for querying data from CalPASS using its API. + CalPASS Plus. MMAP API V1. . + date_publication: '2020-08-06' + bug_reports: https://github.com/vinhdizzo/calpassapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=calpassapi + url_git: https://github.com/vinhdizzo/calpassapi +CalSim: + version: 0.5.4 + title: The Calibration Simplex + maintainer: Johannes Resin + description: Generates the calibration simplex (a generalization of the reliability + diagram) for three-category probability forecasts, as proposed by Wilks (2013) + . + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CalSim + url_git: '' +camcorder: + version: 0.1.0 + title: Record Your Plot History + maintainer: Ellis Hughes + description: |- + Record and generate a 'gif' of your 'R' sessions plots. When creating + a visualization, there is inevitably iteration and refinement that occurs. + Automatically save the plots made to a specified directory, previewing them + as they would be saved. Then combine all plots generated into a 'gif' + to show the plot refinement over time. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=camcorder + url_git: '' +CamelUp: + version: 2.0.3 + title: |- + 'CamelUp' Board Game as a Teaching Aid for Introductory + Statistics + maintainer: Michael Czekanski + description: Implements the board game 'CamelUp' for use in introductory statistics + classes using a Shiny app. + date_publication: '2021-02-20' + bug_reports: https://github.com/mczekanski1/Camel-Up/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CamelUp + url_git: '' +camerondata: + version: 1.0.0 + title: |- + Datasets from "Microeconometrics: Methods and Applications" by + Cameron and Trivedi + maintainer: Juliana Vega-Lacorte + description: |- + Quick and easy access to datasets that let you replicate the + empirical examples in Cameron and Trivedi (2005) "Microeconometrics: Methods and + Applications" (ISBN: 9780521848053).The data are available as soon as you install + and load the package (lazy-loading) as data frames. The documentation includes + reference to chapter sections and page numbers where the datasets are used. + date_publication: '2022-03-21' + bug_reports: https://github.com/juvlac/camerondata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=camerondata + url_git: https://github.com/juvlac/camerondata +CAMML: + version: 1.0.0 + title: |- + Cell-Typing using Variance Adjusted Mahalanobis Distances with + Multi-Labeling + maintainer: Courtney Schiebout + description: Creates multi-label cell-types for single-cell RNA-sequencing data + based on weighted VAM scoring of cell-type specific gene sets. Schiebout, Frost + (2022) . + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CAMML + url_git: '' +campaignmanageR: + version: 0.1.0 + title: Connect to Campaign Manager via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect marketing data from Campaign Manager using the 'Windsor.ai' + API . + date_publication: '2022-10-19' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=campaignmanageR + url_git: '' +campfin: + version: 1.0.11 + title: Wrangle Campaign Finance Data + maintainer: Kiernan Nicholls + description: |- + Explore and normalize American campaign finance + data. Created by the Investigative Reporting Workshop to facilitate + work on The Accountability Project, an effort to collect public data + into a central, standard database that is more easily searched: + . + date_publication: '2023-10-20' + bug_reports: https://github.com/irworkshop/campfin/issues + url: https://irworkshop.github.io/campfin/ + url_cran: https://CRAN.R-project.org/package=campfin + url_git: https://github.com/irworkshop/campfin +campsis: + version: 1.6.0 + title: Generic PK/PD Simulation Platform CAMPSIS + maintainer: Nicolas Luyckx + description: |- + A generic, easy-to-use and intuitive + pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on R + packages 'rxode2' and 'mrgsolve'. CAMPSIS provides an abstraction + layer over the underlying processes of writing a PK/PD model, + assembling a custom dataset and running a simulation. CAMPSIS has a + strong dependency to the R package 'campsismod', which allows to + read/write a model from/to files and adapt it further on the fly in + the R environment. Package 'campsis' allows the user to assemble a + dataset in an intuitive manner. Once the user’s dataset is ready, the + package is in charge of preparing the simulation, calling 'rxode2' or + 'mrgsolve' (at the user's choice) and returning the results, for the + given model, dataset and desired simulation settings. + date_publication: '2025-02-09' + bug_reports: https://github.com/Calvagone/campsis/issues + url: https://calvagone.github.io/ + url_cran: https://CRAN.R-project.org/package=campsis + url_git: https://github.com/Calvagone/campsis +campsismod: + version: 1.2.0 + title: Generic Implementation of a PK/PD Model + maintainer: Nicolas Luyckx + description: |- + A generic, easy-to-use and expandable implementation of a + pharmacokinetic (PK) / pharmacodynamic (PD) model based on the S4 + class system. This package allows the user to read/write a + pharmacometric model from/to files and adapt it further on the fly in + the R environment. For this purpose, this package provides an + intuitive API to add, modify or delete equations, ordinary + differential equations (ODE's), model parameters or compartment + properties (like infusion duration or rate, bioavailability and + initial values). Finally, this package also provides a useful export + of the model for use with simulation packages 'rxode2' and 'mrgsolve'. + This package is designed and intended to be used with package + 'campsis', a PK/PD simulation platform built on top of 'rxode2' and + 'mrgsolve'. + date_publication: '2025-02-07' + bug_reports: https://github.com/Calvagone/campsismod/issues + url: https://calvagone.github.io/ + url_cran: https://CRAN.R-project.org/package=campsismod + url_git: https://github.com/Calvagone/campsismod +camsRad: + version: 0.3.0 + title: Client for CAMS Radiation Service + maintainer: Lukas Lundstrom + description: |- + Copernicus Atmosphere Monitoring Service (CAMS) radiations service + provides time series of global, direct, and diffuse irradiations on horizontal + surface, and direct irradiation on normal plane for the actual weather + conditions as well as for clear-sky conditions. + The geographical coverage is the field-of-view of the Meteosat satellite, + roughly speaking Europe, Africa, Atlantic Ocean, Middle East. The time coverage + of data is from 2004-02-01 up to 2 days ago. Data are available with a time step + ranging from 15 min to 1 month. For license terms and to create an account, + please see . + date_publication: '2016-11-30' + bug_reports: https://github.com/ropenscilabs/camsRad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=camsRad + url_git: https://github.com/ropenscilabs/camsRad +camtrapdp: + version: 0.3.1 + title: Read and Manipulate Camera Trap Data Packages + maintainer: Peter Desmet + description: |- + Read and manipulate Camera Trap Data Packages ('Camtrap DP'). + 'Camtrap DP' () is a data exchange format + for camera trap data. With 'camtrapdp' you can read, filter and + transform data (including to Darwin Core) before further analysis in + e.g. 'camtraptor' or 'camtrapR'. + date_publication: '2024-07-05' + bug_reports: https://github.com/inbo/camtrapdp/issues + url: https://inbo.github.io/camtrapdp/ + url_cran: https://CRAN.R-project.org/package=camtrapdp + url_git: https://github.com/inbo/camtrapdp +camtrapR: + version: 2.3.0 + title: |- + Camera Trap Data Management and Preparation of Occupancy and + Spatial Capture-Recapture Analyses + maintainer: Juergen Niedballa + description: Management of and data extraction from camera trap data in wildlife + studies. The package provides a workflow for storing and sorting camera trap photos + (and videos), tabulates records of species and individuals, and creates detection/non-detection + matrices for occupancy and spatial capture-recapture analyses with great flexibility. + In addition, it can visualise species activity data and provides simple mapping + functions with GIS export. + date_publication: '2024-02-26' + bug_reports: https://groups.google.com/forum/#!forum/camtrapr + url: https://jniedballa.github.io/camtrapR/ + url_cran: https://CRAN.R-project.org/package=camtrapR + url_git: https://github.com/jniedballa/camtrapR +canadamaps: + version: '0.1' + title: Maps of the Political and Administrative Divisions of Canada + maintainer: Mauricio Vargas Sepulveda + description: |- + Terrestrial maps with simplified topologies for Census Divisions, + Agricultural Regions, Economic Regions, Federal Electoral Divisions and + Provinces. + date_publication: '2021-11-29' + bug_reports: https://github.com/pachadotdev/canadamaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=canadamaps + url_git: https://github.com/pachadotdev/canadamaps/ +canadianmaps: + version: 2.0.0 + title: Effortlessly Create Stunning Canadian Maps + maintainer: Joelle Cayen + description: Simple and seamless access to a variety of 'StatCan' shapefiles for + mapping Canadian provinces, regions, forward sortation areas, census divisions, + and subdivisions using the popular 'ggplot2' package. + date_publication: '2024-04-02' + bug_reports: https://github.com/joellecayen/canadianmaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=canadianmaps + url_git: https://github.com/joellecayen/canadianmaps +canaper: + version: 1.0.1 + title: Categorical Analysis of Neo- And Paleo-Endemism + maintainer: Joel H. Nitta + description: |- + Provides functions to analyze the spatial distribution of + biodiversity, in particular categorical analysis of neo- and paleo-endemism + (CANAPE) as described in Mishler et al (2014) . + 'canaper' conducts statistical tests to determine the types of endemism that + occur in a study area while accounting for the evolutionary relationships of + species. + date_publication: '2023-05-04' + bug_reports: https://github.com/ropensci/canaper/issues + url: https://docs.ropensci.org/canaper/ + url_cran: https://CRAN.R-project.org/package=canaper + url_git: https://github.com/ropensci/canaper +cancensus: + version: 0.5.7 + title: |- + Access, Retrieve, and Work with Canadian Census Data and + Geography + maintainer: Dmitry Shkolnik + description: |- + Integrated, convenient, and uniform access to Canadian + Census data and geography retrieved using the 'CensusMapper' API. This package produces analysis-ready + tidy data frames and spatial data in multiple formats, as well as convenience functions + for working with Census variables, variable hierarchies, and region selection. API + keys are freely available with free registration at . + Census data and boundary geometries are reproduced and distributed on an "as + is" basis with the permission of Statistics Canada (Statistics Canada 2001; 2006; + 2011; 2016; 2021). + date_publication: '2024-02-10' + bug_reports: https://github.com/mountainMath/cancensus/issues + url: https://mountainmath.github.io/cancensus/ + url_cran: https://CRAN.R-project.org/package=cancensus + url_git: https://github.com/mountainMath/cancensus +CancerEvolutionVisualization: + version: 2.0.1 + title: Publication Quality Phylogenetic Tree Plots + maintainer: Paul Boutros + description: Generates tree plots with precise branch lengths, gene annotations, + and cellular prevalence. The package handles complex tree structures (angles, + lengths, etc.) and can be further refined as needed by the user. + date_publication: '2023-11-21' + bug_reports: https://github.com/uclahs-cds/package-CancerEvolutionVisualization/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CancerEvolutionVisualization + url_git: https://github.com/uclahs-cds/package-CancerEvolutionVisualization +cancerGI: + version: 1.0.1 + title: Analyses of Cancer Gene Interaction + maintainer: Audrey Q. Fu + description: 'Functions to perform the following analyses: i) inferring epistasis + from RNAi double knockdown data; ii) identifying gene pairs of multiple mutation + patterns; iii) assessing association between gene pairs and survival; and iv) + calculating the smallworldness of a graph (e.g., a gene interaction network). Data + and analyses are described in Wang, X., Fu, A. Q., McNerney, M. and White, K. + P. (2014). Widespread genetic epistasis among breast cancer genes. Nature Communications. + 5 4828. .' + date_publication: '2023-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cancerGI + url_git: '' +CancerGram: + version: 1.0.0 + title: Prediction of Anticancer Peptides + maintainer: Michal Burdukiewicz + description: |- + Predicts anticancer peptides using random forests trained on the + n-gram encoded peptides. The implemented algorithm can be accessed from + both the command line and shiny-based GUI. The CancerGram model is too large + for CRAN and it has to be downloaded separately from the repository: + . For more information see: + Burdukiewicz et al. (2020) . + date_publication: '2020-11-19' + bug_reports: https://github.com/BioGenies/CancerGram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CancerGram + url_git: https://github.com/BioGenies/CancerGram +cancerR: + version: 0.1.0 + title: Classification of Cancer Using Administrative Data + maintainer: Giancarlo Di Giuseppe + description: |- + Classifies the type of cancer using routinely collected data + commonly found in cancer registries from pathology reports. The + package implements the International Classification of Diseases for + Oncology, 3rd Edition site (topography), histology (morphology), and behaviour codes of neoplasms to classify cancer type + . + Classification in children utilize the International Classification of Childhood Cancer by Steliarova-Foucher et al. (2005) . + Adolescent and young adult cancer classification is based on Barr et al. (2020) . + date_publication: '2024-09-15' + bug_reports: https://github.com/giancarlodigi/cancerR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cancerR + url_git: https://github.com/giancarlodigi/cancerR +cancerscreening: + version: 1.1.1 + title: Streamline Access to Cancer Screening Data + maintainer: David Kariuki + description: |- + Retrieve cancer screening data for cervical, breast and colorectal + cancers from the Kenya Health Information System in a + consistent way. + date_publication: '2024-06-12' + bug_reports: https://github.com/damurka/cancerscreening/issues + url: https://cancerscreening.damurka.com + url_cran: https://CRAN.R-project.org/package=cancerscreening + url_git: https://github.com/damurka/cancerscreening +candisc: + version: 0.9.0 + title: |- + Visualizing Generalized Canonical Discriminant and Canonical + Correlation Analysis + maintainer: Michael Friendly + description: |- + Functions for computing and visualizing + generalized canonical discriminant analyses and canonical correlation analysis + for a multivariate linear model. + Traditional canonical discriminant analysis is restricted to a one-way 'MANOVA' + design and is equivalent to canonical correlation analysis between a set of quantitative + response variables and a set of dummy variables coded from the factor variable. + The 'candisc' package generalizes this to higher-way 'MANOVA' designs + for all factors in a multivariate linear model, + computing canonical scores and vectors for each term. The graphic functions provide low-rank (1D, 2D, 3D) + visualizations of terms in an 'mlm' via the 'plot.candisc' and 'heplot.candisc' methods. Related plots are + now provided for canonical correlation analysis when all predictors are quantitative. + date_publication: '2024-05-06' + bug_reports: https://github.com/friendly/candisc/issues + url: https://friendly.github.io/candisc/ + url_cran: https://CRAN.R-project.org/package=candisc + url_git: https://github.com/friendly/candisc/ +Canek: + version: 0.2.5 + title: Batch Correction of Single Cell Transcriptome Data + maintainer: Martin Loza + description: |- + Non-linear/linear hybrid method for batch-effect correction + that uses Mutual Nearest Neighbors (MNNs) to identify similar cells between + datasets. Reference: Loza M. et al. (NAR Genomics and Bioinformatics, 2020) . + date_publication: '2023-12-08' + bug_reports: https://github.com/MartinLoza/Canek/issues + url: https://martinloza.github.io/Canek/ + url_cran: https://CRAN.R-project.org/package=Canek + url_git: '' +Canopy: + version: 1.3.0 + title: |- + Accessing Intra-Tumor Heterogeneity and Tracking Longitudinal + and Spatial Clonal Evolutionary History by Next-Generation + Sequencing + maintainer: Yuchao Jiang + description: |- + A statistical framework and computational procedure for identifying + the sub-populations within a tumor, determining the mutation profiles of each + subpopulation, and inferring the tumor's phylogenetic history. The input are + variant allele frequencies (VAFs) of somatic single nucleotide alterations + (SNAs) along with allele-specific coverage ratios between the tumor and matched + normal sample for somatic copy number alterations (CNAs). These quantities can + be directly taken from the output of existing software. Canopy provides a + general mathematical framework for pooling data across samples and sites to + infer the underlying parameters. For SNAs that fall within CNA regions, Canopy + infers their temporal ordering and resolves their phase. When there are + multiple evolutionary configurations consistent with the data, Canopy outputs + all configurations along with their confidence assessment. + date_publication: '2017-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Canopy + url_git: https://github.com/yuchaojiang/Canopy +canprot: + version: 2.0.0 + title: Chemical Analysis of Proteins + maintainer: Jeffrey Dick + description: |- + Chemical analysis of proteins based on their amino acid + compositions. Amino acid compositions can be read from FASTA files and used to + calculate chemical metrics including carbon oxidation state and stoichiometric + hydration state, as described in Dick et al. (2020) . + Other properties that can be calculated include protein length, grand average of + hydropathy (GRAVY), isoelectric point (pI), molecular weight (MW), standard + molal volume (V0), and metabolic costs (Akashi and Gojobori, 2002 + ; Wagner, 2005 ; + Zhang et al., 2018 ). A database of amino acid + compositions of human proteins derived from UniProt is provided. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=canprot + url_git: https://github.com/jedick/canprot +cansim: + version: '0.4' + title: Accessing Statistics Canada Data Table and Vectors + maintainer: Jens von Bergmann + description: |- + Searches for, accesses, and retrieves Statistics Canada data + tables, as well as individual vectors, as tidy data frames. + This package enriches the tables with metadata, deals + with encoding issues, allows for bilingual English or French language data retrieval, and bundles + convenience functions to make it easier to work with retrieved table data. For more efficient data + access the package allows for caching data in a local database and database level filtering, data + manipulation and summarizing. + date_publication: '2025-02-24' + bug_reports: https://github.com/mountainMath/cansim/issues + url: https://mountainmath.github.io/cansim/ + url_cran: https://CRAN.R-project.org/package=cansim + url_git: https://github.com/mountainMath/cansim +CANSIM2R: + version: 1.14.1 + title: Directly Extracts Complete CANSIM Data Tables + maintainer: Marco Lugo + description: Extract CANSIM (Statistics Canada) tables and transform them into readily + usable data in panel (wide) format. It can also extract more than one table at + a time and produce the resulting merge by time period and geographical region. + date_publication: '2018-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CANSIM2R + url_git: '' +canvasXpress: + version: 1.50.5 + title: Visualization Package for CanvasXpress in R + maintainer: Connie Brett + description: |- + Enables creation of visualizations using the CanvasXpress framework + in R. CanvasXpress is a standalone JavaScript library for reproducible research + with complete tracking of data and end-user modifications stored in a single + PNG image that can be played back. See for more + information. + date_publication: '2024-06-23' + bug_reports: https://github.com/neuhausi/canvasXpress/issues + url: '' + url_cran: https://CRAN.R-project.org/package=canvasXpress + url_git: https://github.com/neuhausi/canvasXpress +canvasXpress.data: + version: 1.34.2 + title: Datasets for the 'canvasXpress' Package + maintainer: Connie Brett + description: |- + Contains the prepared data that is needed for the 'shiny' application examples in the + 'canvasXpress' package. This package also includes datasets used for automated 'testthat' tests. + Scotto L, Narayan G, Nandula SV, Arias-Pulido H et al. (2008) . + Davis S, Meltzer PS (2007) . + date_publication: '2021-06-29' + bug_reports: https://github.com/neuhausi/canvasXpress.data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=canvasXpress.data + url_git: https://github.com/neuhausi/canvasXpress.data +cape: + version: 3.1.2 + title: |- + Combined Analysis of Pleiotropy and Epistasis for Diversity + Outbred Mice + maintainer: Anna Tyler + description: |- + Combined Analysis of Pleiotropy and Epistasis infers predictive + networks between genetic variants and phenotypes. It can be used with + standard two-parent populations as well as multi-parent populations, such + as the Diversity Outbred (DO) mice, Collaborative Cross (CC) mice, or the + multi-parent advanced generation intercross (MAGIC) population of Arabidopsis + thaliana. It uses complementary information of pleiotropic gene variants across + different phenotypes to resolve models of epistatic interactions between alleles. + To do this, cape reparametrizes main effect and interaction coefficients from + pairwise variant regressions into directed influence parameters. These + parameters describe how alleles influence each other, in terms of suppression + and enhancement, as well as how gene variants influence phenotypes. All of the + final interactions are reported as directed interactions between pairs of + parental alleles. For detailed descriptions of the methods used in this package + please see the following references. + Carter, G. W., Hays, M., Sherman, A. & Galitski, T. (2012) . + Tyler, A. L., Lu, W., Hendrick, J. J., Philip, V. M. & Carter, G. W. (2013) . + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cape + url_git: '' +caper: + version: 1.0.3 + title: Comparative Analyses of Phylogenetics and Evolution in R + maintainer: David Orme + description: Functions for performing phylogenetic comparative analyses. + date_publication: '2023-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caper + url_git: '' +capesData: + version: 0.0.1 + title: Data on Scholarships in CAPES International Mobility Programs + maintainer: Leonardo Biazoli + description: Information on activities to promote scholarships in Brazil and abroad + for international mobility programs, recorded in Capes' computerized payment systems. + The CAPES database refers to international mobility programs for the period from + 2010 to 2019 . + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=capesData + url_git: '' +capesR: + version: 0.1.0 + title: Access to CAPES Data + maintainer: Hugo Vasconcelos Medeiros + description: |- + Provides simplified access to the data from the Catalog of Theses and Dissertations + of the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES, ) + for the years 1987 through 2022. The dataset includes variables such as Higher Education + Institution (institution), Area of Concentration (area), Graduate Program Name (program_name), + Type of Work (type), Language of Work (language), Author Identification (author), Abstract + (abstract), Advisor Identification (advisor), Development Region (region), State (state). + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=capesR + url_git: +capitalR: + version: 1.3.0 + title: |- + Capital Budgeting Analysis, Annuity Loan Calculations and + Amortization Schedules + maintainer: John T. Buynak + description: |- + Provides Capital Budgeting Analysis functionality and the essential Annuity loan functions. + Also computes Loan Amortization Schedules including schedules with irregular payments. + date_publication: '2019-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=capitalR + url_git: '' +capl: + version: '1.42' + title: Compute and Visualize CAPL-2 Scores and Interpretations + maintainer: Joel Barnes + description: |- + A toolkit for computing and visualizing CAPL-2 + (Canadian Assessment of Physical Literacy, Second Edition; + ) scores and interpretations from raw data. + date_publication: '2022-04-08' + bug_reports: https://github.com/barnzilla/capl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=capl + url_git: https://github.com/barnzilla/capl +caplot: + version: '0.2' + title: Correspondence Analysis with Geometric Frequency Interpretation + maintainer: Gianmarco Alberti + description: Performs Correspondence Analysis on the given dataframe and plots the + results in a scatterplot that emphasizes the geometric interpretation aspect of + the analysis, following Borg-Groenen (2005) and Yelland (2010). It is particularly + useful for highlighting the relationships between a selected row (or column) category + and the column (or row) categories. See Borg-Groenen (2005, ISBN:978-0-387-28981-6); + Yelland (2010) . + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caplot + url_git: '' +capm: + version: 0.14.0 + title: Companion Animal Population Management + maintainer: Oswaldo Santos Baquero + description: |- + Quantitative analysis to support companion animal population + management. Some functions assist survey sampling tasks (calculate sample + size for simple and complex designs, select sampling units and estimate + population parameters) while others assist the modelling of population + dynamics. For demographic characterizations and population management + evaluations see: "Baquero, et al." (2018), + . For modelling of + population dynamics see: "Baquero et al." (2016), + . For sampling methods + see: "Levy PS & Lemeshow S" (2013), "ISBN-10: 0470040076"; + "Lumley" (2010), "ISBN: 978-0-470-28430-8". + date_publication: '2019-10-24' + bug_reports: '' + url: http://oswaldosantos.github.io/capm + url_cran: https://CRAN.R-project.org/package=capm + url_git: '' +capn: + version: 1.0.0 + title: Capital Asset Pricing for Nature + maintainer: Seong Do Yun + description: 'Implements approximation methods for natural capital asset prices + suggested by Fenichel and Abbott (2014) in Journal of the + Associations of Environmental and Resource Economists (JAERE), Fenichel et al. + (2016) in Proceedings of the National Academy of + Sciences (PNAS), and Yun et al. (2017) in PNAS (accepted), and their extensions: + creating Chebyshev polynomial nodes and grids, calculating basis of Chebyshev + polynomials, approximation and their simulations for: V-approximation (single + and multiple stocks, PNAS), P-approximation (single stock, PNAS), and Pdot-approximation + (single stock, JAERE). Development of this package was generously supported by + the Knobloch Family Foundation.' + date_publication: '2017-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=capn + url_git: '' +CaPO4Sim: + version: 0.2.1 + title: |- + A Virtual Patient Simulator in the Context of Calcium and + Phosphate Homeostasis + maintainer: David Granjon + description: |- + Explore calcium (Ca) and phosphate (Pi) homeostasis with two novel 'Shiny' apps, + building upon on a previously published mathematical model written in C, + to ensure efficient computations. The underlying model is accessible + here . + The first application explores the fundamentals of Ca-Pi homeostasis, + while the second provides interactive case studies for in-depth exploration of the topic, + thereby seeking to foster student engagement and an integrative understanding of Ca-Pi regulation. + date_publication: '2024-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CaPO4Sim + url_git: '' +captr: + version: 0.3.0 + title: Client for the Captricity API + maintainer: Gaurav Sood + description: |- + Get text from images of text using Captricity Optical Character + Recognition (OCR) API. Captricity allows you to get text from handwritten + forms --- think surveys --- and other structured paper documents. And it can + output data in form a delimited file keeping field information intact. For more + information, read . + date_publication: '2017-04-15' + bug_reports: http://github.com/soodoku/captR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=captr + url_git: http://github.com/soodoku/captR +capushe: + version: 1.1.2 + title: CAlibrating Penalities Using Slope HEuristics + maintainer: Vincent Brault + description: Calibration of penalized criteria for model selection. The calibration + methods available are based on the slope heuristics. + date_publication: '2023-11-27' + bug_reports: '' + url: http://www.math.u-psud.fr/~brault/capushe.html + url_cran: https://CRAN.R-project.org/package=capushe + url_git: '' +car: + version: 3.1-3 + title: Companion to Applied Regression + maintainer: John Fox + description: |- + Functions to Accompany J. Fox and S. Weisberg, + An R Companion to Applied Regression, Third Edition, Sage, 2019. + date_publication: '2024-09-27' + bug_reports: '' + url: https://www.john-fox.ca/Companion/index.html + url_cran: https://CRAN.R-project.org/package=car + url_git: https://r-forge.r-project.org/projects/car/ +caracas: + version: 2.1.1 + title: Computer Algebra + maintainer: Mikkel Meyer Andersen + description: |- + Computer algebra via the 'SymPy' library (). + This makes it possible to solve equations symbolically, + find symbolic integrals, symbolic sums and other important quantities. + date_publication: '2023-11-30' + bug_reports: https://github.com/r-cas/caracas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caracas + url_git: https://github.com/r-cas/caracas +caRamel: + version: '1.4' + title: Automatic Calibration by Evolutionary Multi Objective Algorithm + maintainer: Fabrice Zaoui + description: |- + The caRamel optimizer has been developed to meet the requirement for an automatic calibration procedure that delivers a family of parameter sets + that are optimal with regard to a multi-objective target (Monteil et al. ). + date_publication: '2024-07-29' + bug_reports: https://github.com/fzao/caRamel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caRamel + url_git: https://github.com/fzao/caRamel +carat: + version: 2.2.1 + title: Covariate-Adaptive Randomization for Clinical Trials + maintainer: Xiaoqing Ye + description: 'Provides functions and command-line user interface to generate allocation + sequence by covariate-adaptive randomization for clinical trials. The package + currently supports six covariate-adaptive randomization procedures. Three hypothesis + testing methods that are valid and robust under covariate-adaptive randomization + are also available in the package to facilitate the inference for treatment effect + under the included randomization procedures. Additionally, the package provides + comprehensive and efficient tools to allow one to evaluate and compare the performance + of randomization procedures and tests based on various criteria. See Ma W, Ye + X, Tu F, and Hu F (2023) for details.' + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=carat + url_git: '' +CARBayes: + version: 6.1.1 + title: Spatial Generalised Linear Mixed Models for Areal Unit Data + maintainer: Duncan Lee + description: Implements a class of univariate and multivariate spatial generalised + linear mixed models for areal unit data, with inference in a Bayesian setting + using Markov chain Monte Carlo (MCMC) simulation using a single or multiple Markov + chains. The response variable can be binomial, Gaussian, multinomial, Poisson + or zero-inflated Poisson (ZIP), and spatial autocorrelation is modelled by a set + of random effects that are assigned a conditional autoregressive (CAR) prior distribution. + A number of different models are available for univariate spatial data, including + models with no random effects as well as random effects modelled by different + types of CAR prior, including the BYM model (Besag et al., 1991, ) + and Leroux model (Leroux et al., 2000, ). Additionally, a + multivariate CAR (MCAR) model for multivariate spatial data is available, as is + a two-level hierarchical model for modelling data relating to individuals within + areas. Full details are given in the vignette accompanying this package. The initial + creation of this package was supported by the Economic and Social Research Council + (ESRC) grant RES-000-22-4256, and on-going development has been supported by the + Engineering and Physical Science Research Council (EPSRC) grant EP/J017442/1, + ESRC grant ES/K006460/1, Innovate UK / Natural Environment Research Council (NERC) + grant NE/N007352/1 and the TB Alliance. + date_publication: '2024-03-08' + bug_reports: https://github.com/duncanplee/CARBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CARBayes + url_git: https://github.com/duncanplee/CARBayes +CARBayesdata: + version: '3.0' + title: |- + Data Used in the Vignettes Accompanying the CARBayes and + CARBayesST Packages + maintainer: Duncan Lee + description: Spatio-temporal data from Scotland used in the vignettes accompanying + the CARBayes (spatial modelling) and CARBayesST (spatio-temporal modelling) packages. + Most of the data relate to the set of 271 Intermediate Zones (IZ) that make up + the 2001 definition of the Greater Glasgow and Clyde health board. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CARBayesdata + url_git: '' +CARBayesST: + version: '4.0' + title: |- + Spatio-Temporal Generalised Linear Mixed Models for Areal Unit + Data + maintainer: Duncan Lee + description: Implements a class of univariate and multivariate spatio-temporal generalised + linear mixed models for areal unit data, with inference in a Bayesian setting + using Markov chain Monte Carlo (MCMC) simulation. The response variable can be + binomial, Gaussian, or Poisson, but for some models only the binomial and Poisson + data likelihoods are available. The spatio-temporal autocorrelation is modelled + by random effects, which are assigned conditional autoregressive (CAR) style + prior distributions. A number of different random effects structures are available, + including models similar to Rushworth et al. (2014) . + Full details are given in the vignette accompanying this package. The creation + and development of this package was supported by the Engineering and Physical + Sciences Research Council (EPSRC) grants EP/J017442/1 and EP/T004878/1 and the + Medical Research Council (MRC) grant MR/L022184/1. + date_publication: '2023-10-30' + bug_reports: https://github.com/duncanplee/CARBayesST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CARBayesST + url_git: https://github.com/duncanplee/CARBayesST +carbonate: + version: 0.1.4 + title: Interact with 'carbon.js' + maintainer: Jonathan Sidi + description: |- + Create beautiful images of source code using + 'carbon.js'. + date_publication: '2022-08-26' + bug_reports: https://github.com/yonicd/carbonate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=carbonate + url_git: https://github.com/yonicd/carbonate +carbondate: + version: 1.0.1 + title: Calibration and Summarisation of Radiocarbon Dates + maintainer: Timothy J Heaton + description: |2- + + Performs Bayesian non-parametric calibration of multiple related radiocarbon determinations, and summarises the calendar age information to plot their joint calendar age density (see Heaton (2022) ). + Also models the occurrence of radiocarbon samples as a variable-rate (inhomogeneous) Poisson process, plotting the posterior estimate for the occurrence rate of the samples over calendar time, and providing information about potential change points. + date_publication: '2024-01-31' + bug_reports: https://github.com/TJHeaton/carbondate/issues + url: https://tjheaton.github.io/carbondate/ + url_cran: https://CRAN.R-project.org/package=carbondate + url_git: https://github.com/TJHeaton/carbondate +carbonr: + version: 0.2.1 + title: Calculate Carbon-Equivalent Emissions + maintainer: Lily Clements + description: Provides a flexible tool for calculating carbon-equivalent emissions. + Mostly using data from the UK Government's Greenhouse Gas Conversion Factors report + , + it facilitates transparent emissions calculations for various sectors, including + travel, accommodation, and clinical activities. The package is designed for easy + integration into R workflows, with additional support for 'shiny' applications + and community-driven extensions. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=carbonr + url_git: '' +carcass: + version: '1.7' + title: Estimation of the Number of Fatalities from Carcass Searches + maintainer: Fraenzi Korner-Nievergelt + description: The number of bird or bat fatalities from collisions with buildings, + towers or wind energy turbines can be estimated based on carcass searches and + experimentally assessed carcass persistence times and searcher efficiency. Functions + for estimating the probability that a bird or bat that died is found by a searcher + are provided. Further functions calculate the posterior distribution of the number + of fatalities based on the number of carcasses found and the estimated detection + probability. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=carcass + url_git: '' +card: + version: 0.1.1 + title: Cardiovascular Applications in Research Data + maintainer: Anish S. Shah + description: |- + A collection of cardiovascular research datasets and analytical + tools, including methods for cardiovascular procedural data, such as + electrocardiography, echocardiography, and catheterization data. Additional + methods exist for analysis of procedural billing codes. + date_publication: '2024-11-06' + bug_reports: https://github.com/shah-in-boots/card/issues + url: '' + url_cran: https://CRAN.R-project.org/package=card + url_git: '' +card.pro: + version: 2.3.0 + title: Lightweight Modern & Responsive Card Component for 'shiny' + maintainer: Obinna Obianom + description: Responsive and modern 'HTML' card essentials for 'shiny' applications + and dashboards. This novel card component in 'Bootstrap' provides a flexible and + extensible content container with multiple variants and options for building robust + 'R' based apps e.g for graph build or machine learning projects. The features + rely on a combination of 'JQuery' and 'CSS' styles to improve + the card functionality. + date_publication: '2025-01-15' + bug_reports: https://github.com/oobianom/card.pro/issues + url: https://cardpro.rpkg.net + url_cran: https://CRAN.R-project.org/package=card.pro + url_git: '' +carData: + version: 3.0-5 + title: Companion to Applied Regression Data Sets + maintainer: John Fox + description: |2- + + Datasets to Accompany J. Fox and S. Weisberg, + An R Companion to Applied Regression, Third Edition, Sage (2019). + date_publication: '2022-01-06' + bug_reports: '' + url: https://socialsciences.mcmaster.ca/jfox/Books/Companion/index.html + url_cran: https://CRAN.R-project.org/package=carData + url_git: https://r-forge.r-project.org/projects/car/ +cardidates: + version: 0.4.9 + title: Identification of Cardinal Dates in Ecological Time Series + maintainer: Thomas Petzoldt + description: |- + Identification of cardinal dates + (begin, time of maximum, end of mass developments) + in ecological time series using fitted Weibull functions. + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cardidates + url_git: http://cardidates.r-forge.r-project.org +cardinalR: + version: 0.1.1 + title: Collection of Data Structures + maintainer: Jayani P.G. Lakshika + description: |- + A collection of simple simulation datasets designed for + generating Nonlinear Dimension Reduction representations + techniques such as t-distributed Stochastic Neighbor Embedding, + and Uniform Manifold Approximation and Projection. These + datasets serve as a valuable resource for understanding the + reliability of Nonlinear Dimension Reduction representations in various contexts. + date_publication: '2024-04-16' + bug_reports: https://github.com/JayaniLakshika/cardinalR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cardinalR + url_git: https://github.com/JayaniLakshika/cardinalR +cards: + version: 0.5.1 + title: Analysis Results Data + maintainer: Daniel D. Sjoberg + description: |- + Construct CDISC (Clinical Data Interchange Standards + Consortium) compliant Analysis Results Data objects. These objects are + used and re-used to construct summary tables, visualizations, and + written reports. The package also exports utilities for working with + these objects and creating new Analysis Results Data objects. + date_publication: '2025-03-01' + bug_reports: https://github.com/insightsengineering/cards/issues + url: https://insightsengineering.github.io/cards/ + url_cran: https://CRAN.R-project.org/package=cards + url_git: https://github.com/insightsengineering/cards +cardx: + version: 0.2.3 + title: Extra Analysis Results Data Utilities + maintainer: Daniel D. Sjoberg + description: |- + Create extra Analysis Results Data (ARD) summary objects. + The package supplements the simple ARD functions from the 'cards' + package, exporting functions to put statistical results in the ARD + format. These objects are used and re-used to construct summary + tables, visualizations, and written reports. + date_publication: '2025-02-18' + bug_reports: https://github.com/insightsengineering/cardx/issues + url: https://insightsengineering.github.io/cardx/ + url_cran: https://CRAN.R-project.org/package=cardx + url_git: https://github.com/insightsengineering/cardx/ +care: + version: 1.1.11 + title: High-Dimensional Regression and CAR Score Variable Selection + maintainer: Korbinian Strimmer + description: |- + Implements the regression approach + of Zuber and Strimmer (2011) "High-dimensional regression and variable + selection using CAR scores" SAGMB 10: 34, . + CAR scores measure the correlation between the response and the + Mahalanobis-decorrelated predictors. The squared CAR score is a + natural measure of variable importance and provides a canonical + ordering of variables. This package provides functions for estimating + CAR scores, for variable selection using CAR scores, and for estimating + corresponding regression coefficients. Both shrinkage as well as + empirical estimators are available. + date_publication: '2021-11-21' + bug_reports: '' + url: https://strimmerlab.github.io/software/care/ + url_cran: https://CRAN.R-project.org/package=care + url_git: '' +care4cmodel: + version: 1.0.3 + title: Carbon-Related Assessment of Silvicultural Concepts + maintainer: Peter Biber + description: |- + A simulation model and accompanying functions that support + assessing silvicultural concepts on the forest estate level with a focus on + the CO2 uptake by wood growth and CO2 emissions by forest operations. For + achieving this, a virtual forest estate area is split into the areas covered + by typical phases of the silvicultural concept of interest. Given initial + area shares of these phases, the dynamics of these areas is simulated. The + typical carbon stocks and flows which are known for all phases are + attributed post-hoc to the areas and upscaled to the estate level. CO2 + emissions by forest operations are estimated based on the amounts and + dimensions of the harvested timber. Probabilities of damage events are taken + into account. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=care4cmodel + url_git: '' +caRecall: + version: 0.1.0 + title: Government of Canada Vehicle Recalls Database API Wrapper + maintainer: Nathan Smith + description: |- + Provides API access to the Government of Canada Vehicle Recalls + Database used by the Defect + Investigations and Recalls Division for vehicles, tires, and child car + seats. The API wrapper provides access to recall summary information + searched using make, model, and year range, as well as detailed recall + information searched using recall number. + date_publication: '2021-02-16' + bug_reports: https://github.com/WraySmith/caRecall/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caRecall + url_git: https://github.com/WraySmith/caRecall +CareDensity: + version: 0.1.0 + title: |- + Calculate the Care Density or Fragmented Care Density Given a + Patient-Sharing Network + maintainer: Robin Denz + description: |- + Given a patient-sharing network, calculate either the classic care density as + proposed by Pollack et al. (2013) or the + fragmented care density as proposed by Engels et al. (2024) . + By utilizing the 'igraph' and 'data.table' packages, the provided functions scale well for + very large graphs. + date_publication: '2024-11-18' + bug_reports: https://github.com/RobinDenz1/CareDensity/issues + url: https://robindenz1.github.io/CareDensity/ + url_cran: https://CRAN.R-project.org/package=CareDensity + url_git: https://github.com/RobinDenz1/CareDensity +careless: + version: 1.2.2 + title: Procedures for Computing Indices of Careless Responding + maintainer: Richard Yentes + description: |- + When taking online surveys, participants sometimes respond to items + without regard to their content. These types of responses, referred to as + careless or insufficient effort responding, constitute significant problems + for data quality, leading to distortions in data analysis and hypothesis + testing, such as spurious correlations. The 'R' package 'careless' provides + solutions designed to detect such careless / insufficient effort responses + by allowing easy calculation of indices proposed in the literature. It + currently supports the calculation of longstring, even-odd consistency, + psychometric synonyms/antonyms, Mahalanobis distance, and intra-individual + response variability (also termed inter-item standard deviation). + For a review of these methods, see Curran (2016) . + date_publication: '2023-10-01' + bug_reports: https://github.com/ryentes/careless/issues + url: '' + url_cran: https://CRAN.R-project.org/package=careless + url_git: https://github.com/ryentes/careless/ +caresid: + version: '0.1' + title: Correspondence Analysis Plot and Associations Visualisation + maintainer: Gianmarco Alberti + description: Performs a Correspondence Analysis (CA) on a contingency table and + creates a scatterplot of the row and column points on the selected dimensions. + Optionally, the function can add segments to the plot to visualize significant + associations between row and column categories on the basis of positive (unadjusted) + standardized residuals larger than a given threshold. + date_publication: '2023-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caresid + url_git: '' +caret: + version: 7.0-1 + title: Classification and Regression Training + maintainer: Max Kuhn + description: |- + Misc functions for training and plotting classification and + regression models. + date_publication: '2024-12-10' + bug_reports: https://github.com/topepo/caret/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caret + url_git: https://github.com/topepo/caret/ +caretEnsemble: + version: 4.0.1 + title: Ensembles of Caret Models + maintainer: Zachary A. Deane-Mayer + description: |- + Functions for creating ensembles of caret models: caretList() + and caretStack(). caretList() is a convenience function for fitting multiple + caret::train() models to the same dataset. caretStack() will make linear or + non-linear combinations of these models, using a caret::train() model as a + meta-model. + date_publication: '2024-09-12' + bug_reports: https://github.com/zachmayer/caretEnsemble/issues + url: http://zachmayer.github.io/caretEnsemble/ + url_cran: https://CRAN.R-project.org/package=caretEnsemble + url_git: https://github.com/zachmayer/caretEnsemble +caretForecast: + version: 0.1.1 + title: |- + Conformal Time Series Forecasting Using State of Art Machine + Learning Algorithms + maintainer: Resul Akay + description: |- + Conformal time series forecasting using the caret infrastructure. + It provides access to state-of-the-art machine learning models for forecasting + applications. The hyperparameter of each model is selected based on time + series cross-validation, and forecasting is done recursively. + date_publication: '2022-10-24' + bug_reports: https://github.com/Akai01/caretForecast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caretForecast + url_git: https://github.com/Akai01/caretForecast +carfima: + version: 2.0.2 + title: |- + Continuous-Time Fractionally Integrated ARMA Process for + Irregularly Spaced Long-Memory Time Series Data + maintainer: Hyungsuk Tak + description: We provide a toolbox to fit a continuous-time fractionally integrated + ARMA process (CARFIMA) on univariate and irregularly spaced time series data via + both frequentist and Bayesian machinery. A general-order CARFIMA(p, H, q) model + for p>q is specified in Tsai and Chan (2005) + and it involves p+q+2 unknown model parameters, i.e., p AR parameters, q MA parameters, + Hurst parameter H, and process uncertainty (standard deviation) sigma. Also, the + model can account for heteroscedastic measurement errors, if the information about + measurement error standard deviations is known. The package produces their maximum + likelihood estimates and asymptotic uncertainties using a global optimizer called + the differential evolution algorithm. It also produces posterior samples of the + model parameters via Metropolis-Hastings within a Gibbs sampler equipped with + adaptive Markov chain Monte Carlo. These fitting procedures, however, may produce + numerical errors if p>2. The toolbox also contains a function to simulate discrete + time series data from CARFIMA(p, H, q) process given the model parameters and + observation times. + date_publication: '2020-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=carfima + url_git: '' +cargo: + version: 0.4.9 + title: Develop R Packages using Rust + maintainer: David B. Dahl + description: |- + A framework is provided to develop R packages using 'Rust' with + minimal overhead, and more wrappers are easily added. Help is provided to use 'Cargo' in a manner + consistent with CRAN policies. 'Rust' code can also be embedded directly in an R script. The package is not official, affiliated with, + nor endorsed by the Rust project. + date_publication: '2023-07-17' + bug_reports: https://github.com/dbdahl/cargo-framework/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cargo + url_git: https://github.com/dbdahl/cargo-framework(repository) +caribou: + version: 1.1-1 + title: Estimation of Caribou Abundance Based on Radio Telemetry Data + maintainer: Louis-Paul Rivest + description: |- + Estimation of population size of migratory caribou herds based on large scale + aggregations monitored by radio telemetry. It implements the methodology found + in the article by Rivest et al. (1998) about caribou abundance estimation. It + also includes a function based on the Lincoln-Petersen Index as applied to + radio telemetry data by White and Garrott (1990). + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caribou + url_git: '' +CarletonStats: + version: '2.2' + title: Functions for Statistics Classes at Carleton College + maintainer: Adam Loy + description: |- + Includes commands for bootstrapping and permutation tests, a + command for created grouped bar plots, and a demo of the + quantile-normal plot for data drawn from different distributions. + date_publication: '2023-08-22' + bug_reports: https://github.com/aloy/CarletonStats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CarletonStats + url_git: https://github.com/aloy/CarletonStats +Carlson: + version: 3.0.0 + title: Carlson Elliptic Integrals and Incomplete Elliptic Integrals + maintainer: Stéphane Laurent + description: |- + Evaluation of the Carlson elliptic integrals and the + incomplete elliptic integrals with complex arguments. The + implementations use Carlson's algorithms . + Applications of elliptic integrals include probability distributions, + geometry, physics, mechanics, electrodynamics, statistical mechanics, + astronomy, geodesy, geodesics on conics, and magnetic field + calculations. + date_publication: '2023-11-10' + bug_reports: https://github.com/stla/Carlson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Carlson + url_git: https://github.com/stla/Carlson +CARM: + version: 1.1.0 + title: |- + Covariate-Adjusted Adaptive Randomization via + Mahalanobis-Distance + maintainer: Fanglu Chen + description: In randomized controlled trial (RCT), balancing covariate is often + one of the most important concern. CARM package provides functions to balance + the covariates and generate allocation sequence by covariate-adjusted Adaptive + Randomization via Mahalanobis-distance (ARM) for RCT. About what ARM is and how + it works please see Y. Qin, Y. Li, W. Ma, H. Yang, and F. Hu (2022). "Adaptive + randomization via Mahalanobis distance" Statistica Sinica. . + In addition, the package is also suitable for the randomization process of multi-arm + trials. For details, please see Yang H, Qin Y, Wang F, et al. (2023). "Balancing + covariates in multi-arm trials via adaptive randomization" Computational Statistics + & Data Analysis.. + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CARM + url_git: '' +CARME: + version: 0.1.1 + title: CAR-MM Modelling in Stan + maintainer: Marco Gramatica + description: '''Stan'' based functions to estimate CAR-MM models. These models allow + to estimate Generalised Linear Models with CAR (conditional autoregressive) spatial + random effects for spatially and temporally misaligned data, provided a suitable + Multiple Membership matrix. The main references are Gramatica, Liverani and Congdon + (2023) , Petrof, Neyens, Nuyts, Nackaerts, Nemery and Faes + (2020) and Gramatica, Congdon and Liverani .' + date_publication: '2023-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CARME + url_git: '' +CARMS: + version: 1.0.1 + title: Continuous Time Markov Rate Modeling for Reliability Analysis + maintainer: Jacob Ormerod + description: 'Emulation of an application originally created by Paul Pukite. Computer + Aided Rate Modeling and Simulation. Jan Pukite and Paul Pukite, (1998, ISBN 978-0-7803-3482), + William J. Stewart, (1994, ISBN: 0-691-03699-3).' + date_publication: '2024-04-04' + bug_reports: '' + url: http://www.openreliability.org + url_cran: https://CRAN.R-project.org/package=CARMS + url_git: '' +caROC: + version: 0.1.5 + title: Continuous Biomarker Evaluation with Adjustment of Covariates + maintainer: Ziyi Li + description: Compute covariate-adjusted specificity at controlled sensitivity level, + or covariate-adjusted sensitivity at controlled specificity level, or covariate-adjust + receiver operating characteristic curve, or covariate-adjusted thresholds at controlled + sensitivity/specificity level. All statistics could also be computed for specific + sub-populations given their covariate values. Methods are described in Ziyi Li, + Yijian Huang, Datta Patil, Martin G. Sanda (2021+) "Covariate adjustment in continuous + biomarker assessment". + date_publication: '2021-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caROC + url_git: '' +caroline: + version: 0.9.9 + title: |- + A Collection of Database, Data Structure, Visualization, and + Utility Functions for R + maintainer: David Schruth + description: |- + The caroline R library contains dozens of functions useful + for: database migration (dbWriteTable2), database style joins & + aggregation (nerge, groupBy, & bestBy), data structure + conversion (nv, tab2df), legend table making (sstable & leghead), + automatic legend positioning for scatter and box plots (), + plot annotation (labsegs & mvlabs), data visualization + (pies, sparge, confound.grid & raPlot), character string manipulation (m & pad), + file I/O (write.delim), batch scripting, data exploration, and more. + The package's greatest contributions lie in the database style merge, + aggregation and interface functions as well as in it's extensive + use and propagation of row, column and vector names in most functions. + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caroline + url_git: '' +carpenter: + version: 0.2.2 + title: Build Common Tables of Summary Statistics for Reports + maintainer: Luke Johnston + description: |- + Mainly used to build tables that are commonly presented for + bio-medical/health research, such as basic characteristic tables or + descriptive statistics. + date_publication: '2019-02-05' + bug_reports: https://github.com/lwjohnst86/carpenter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=carpenter + url_git: https://github.com/lwjohnst86/carpenter +carrier: + version: 0.1.1 + title: Isolate Functions for Remote Execution + maintainer: Lionel Henry + description: |- + Sending functions to remote processes can be wasteful of + resources because they carry their environments with them. With the + carrier package, it is easy to create functions that are isolated from + their environment. These isolated functions, also called crates, print + at the console with their total size and can be easily tested locally + before being sent to a remote. + date_publication: '2023-04-28' + bug_reports: https://github.com/r-lib/carrier/issues + url: '' + url_cran: https://CRAN.R-project.org/package=carrier + url_git: https://github.com/r-lib/carrier +CARRoT: + version: 3.0.2 + title: |- + Predicting Categorical and Continuous Outcomes Using One in Ten + Rule + maintainer: Alina Bazarova + description: Predicts categorical or continuous outcomes while concentrating on + a number of key points. These are Cross-validation, Accuracy, Regression and Rule + of Ten or "one in ten rule" (CARRoT), and, in addition to it R-squared statistics, + prior knowledge on the dataset etc. It performs the cross-validation specified + number of times by partitioning the input into training and test set and fitting + linear/multinomial/binary regression models to the training set. All regression + models satisfying chosen constraints are fitted and the ones with the best predictive + power are given as an output. Best predictive power is understood as highest accuracy + in case of binary/multinomial outcomes, smallest absolute and relative errors + in case of continuous outcomes. For binary case there is also an option of finding + a regression model which gives the highest AUROC (Area Under Receiver Operating + Curve) value. The option of parallel toolbox is also available. Methods are described + in Peduzzi et al. (1996) , Rhemtulla et al. + (2012) , Riley et al. (2018) , Riley + et al. (2019) . + date_publication: '2023-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CARRoT + url_git: '' +carSurv: + version: 1.0.0 + title: Correlation-Adjusted Regression Survival (CARS) Scores + maintainer: Thomas Welchowski + description: Contains functions to estimate the Correlation-Adjusted Regression + Survival (CARS) Scores. The method is described in Welchowski, T. and Zuber, V. + and Schmid, M., (2018), Correlation-Adjusted Regression Survival Scores for High-Dimensional + Variable Selection, . + date_publication: '2018-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=carSurv + url_git: '' +cartograflow: + version: 1.0.5 + title: Filtering Matrix for Flow Mapping + maintainer: Sylvain Blondeau + description: |- + Functions to prepare and filter an origin-destination matrix for thematic flow mapping purposes. + This comes after Bahoken, Francoise (2016), Mapping flow matrix a contribution, PhD in Geography - Territorial sciences. See Bahoken (2017) . + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cartograflow + url_git: https://github.com/fbahoken/cartogRaflow +cartogram: + version: 0.3.0 + title: Create Cartograms with R + maintainer: Sebastian Jeworutzki + description: Construct continuous and non-contiguous area cartograms. + date_publication: '2023-05-26' + bug_reports: https://github.com/sjewo/cartogram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cartogram + url_git: https://github.com/sjewo/cartogram +cartogramR: + version: 1.2-0 + title: Continuous Cartogram + maintainer: Pierre-Andre Cornillon + description: |- + Procedures for making continuous cartogram. Procedures available are: + flow based cartogram (Gastner & Newman (2004) ), + fast flow based cartogram (Gastner, Seguy & More (2018) ), + rubber band based cartogram (Dougenik et al. (1985) + ). + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cartogramR + url_git: '' +cartographer: + version: 0.2.1 + title: Turn Place Names into Map Data + maintainer: Carl Suster + description: |- + A tool for easily matching spatial data when you have a list of + place/region names. You might have a data frame that came from a + spreadsheet tracking some data by suburb or state. This package can + convert it into a spatial data frame ready for plotting. The actual map + data is provided by other packages (or your own code). + date_publication: '2024-01-28' + bug_reports: https://github.com/cidm-ph/cartographer/issues + url: https://cidm-ph.github.io/cartographer/ + url_cran: https://CRAN.R-project.org/package=cartographer + url_git: https://github.com/cidm-ph/cartographer +cartographr: + version: 0.2.2 + title: Crafting Print-Ready Maps and Layered Visualizations + maintainer: David Willinger + description: Simplifying the creation of print-ready maps, this package offers a + user-friendly interface derived from 'ggplot2' for handling OpenStreetMap data. + It streamlines the map-making process, allowing users to focus on the story their + maps tell. Transforming raw geospatial data into informative visualizations is + made easy with simple features 'sf' geometries. Whether for urban planning, environmental + studies, or impactful public presentations, this tool facilitates straightforward + and effective map creation. Enhance the dissemination of spatial information with + high-quality, narrative-driven visualizations! + date_publication: '2024-06-28' + bug_reports: https://github.com/da-wi/cartographr/issues + url: https://da-wi.github.io/cartographr/ + url_cran: https://CRAN.R-project.org/package=cartographr + url_git: https://github.com/da-wi/cartographr +cartography: + version: 3.1.4 + title: Thematic Cartography + maintainer: Timothée Giraud + description: |- + Create and integrate maps in your R workflow. This package helps + to design cartographic representations such as proportional symbols, + choropleth, typology, flows or discontinuities maps. It also offers several + features that improve the graphic presentation of maps, for instance, map + palettes, layout elements (scale, north arrow, title...), labels or legends. + See Giraud and Lambert (2017) . + date_publication: '2023-09-14' + bug_reports: https://github.com/riatelab/cartography/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=cartography + url_git: https://github.com/riatelab/cartography/ +Cascade: + version: '2.1' + title: |- + Selection, Reverse-Engineering and Prediction in Cascade + Networks + maintainer: Frederic Bertrand + description: A modeling tool allowing gene selection, reverse engineering, and prediction + in cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, + M. (2014) . + date_publication: '2022-11-28' + bug_reports: https://github.com/fbertran/Cascade/issues/ + url: https://fbertran.github.io/Cascade/ + url_cran: https://CRAN.R-project.org/package=Cascade + url_git: https://github.com/fbertran/Cascade/ +CascadeData: + version: '1.4' + title: Experimental Data of Cascade Experiments in Genomics + maintainer: Frederic Bertrand + description: These experimental expression data (5 leukemic 'CLL' B-lymphocyte of + aggressive form from 'GSE39411', ), after B-cell + receptor stimulation, are used as examples by packages such as the 'Cascade' one, + a modeling tool allowing gene selection, reverse engineering, and prediction in + cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, + M. (2014) . + date_publication: '2022-11-28' + bug_reports: https://github.com/fbertran/CascadeData/issues/ + url: https://fbertran.github.io/CascadeData/ + url_cran: https://CRAN.R-project.org/package=CascadeData + url_git: https://github.com/fbertran/CascadeData/ +cascadeSelect: + version: 1.1.0 + title: A Cascade Select Input for 'Shiny' + maintainer: Stéphane Laurent + description: |- + Provides a cascade select widget for usage in 'Shiny' + applications. This is useful for selection of hierarchical choices + (e.g. continent, country, city). It is taken from the 'JavaScript' + library 'PrimeReact'. + date_publication: '2023-06-15' + bug_reports: https://github.com/stla/cascadeSelect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cascadeSelect + url_git: https://github.com/stla/cascadeSelect +cascadess: + version: 0.2.0 + title: A Style Pronoun for 'htmltools' Tags + maintainer: Nathan Teetor + description: |- + Apply styles to tag elements directly and with the .style + pronoun. Using the pronoun, styles are created within the context of a tag + element. Change borders, backgrounds, text, margins, layouts, and more. + date_publication: '2024-10-24' + bug_reports: https://github.com/nteetor/cascadess/issues + url: https://nteetor.github.io/cascadess/ + url_cran: https://CRAN.R-project.org/package=cascadess + url_git: https://github.com/nteetor/cascadess +CASCORE: + version: 0.1.2 + title: Covariate Assisted Spectral Clustering on Ratios of Eigenvectors + maintainer: Yaofang Hu + description: |- + Functions for implementing the novel algorithm CASCORE, which is designed to detect latent community structure in graphs with node covariates. This algorithm can handle models such as the covariate-assisted degree corrected stochastic block model (CADCSBM). CASCORE specifically addresses the disagreement between the community structure inferred from the adjacency information and the community structure inferred from the covariate information. For more detailed information, please refer to the reference paper: Yaofang Hu and Wanjie Wang (2022) . + In addition to CASCORE, this package includes several classical community detection algorithms that are compared to CASCORE in our paper. These algorithms are: Spectral Clustering On Ratios-of Eigenvectors (SCORE), normalized PCA, ordinary PCA, network-based clustering, covariates-based clustering and covariate-assisted spectral clustering (CASC). By providing these additional algorithms, the package enables users to compare their performance with CASCORE in community detection tasks. + date_publication: '2023-07-02' + bug_reports: '' + url: https://arxiv.org/abs/2306.15616 + url_cran: https://CRAN.R-project.org/package=CASCORE + url_git: '' +cascsim: + version: '0.4' + title: Casualty Actuarial Society Individual Claim Simulator + maintainer: Kailan Shang + description: |- + It is an open source insurance claim simulation engine sponsored + by the Casualty Actuarial Society. It generates individual insurance claims + including open claims, reopened claims, incurred but not reported claims + and future claims. It also includes claim data fitting functions to help set + simulation assumptions. It is useful for claim level reserving analysis. + Parodi (2013) . + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cascsim + url_git: '' +casebase: + version: 0.10.6 + title: |- + Fitting Flexible Smooth-in-Time Hazards and Risk Functions via + Logistic and Multinomial Regression + maintainer: Sahir Bhatnagar + description: |- + Fit flexible and fully parametric hazard regression models to survival data with single event type or multiple + competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms + of time and its interactions with other predictors for time-dependent hazards and hazard ratios. From the + fitted hazard model, we provide functions to readily calculate and plot cumulative incidence and survival + curves for a given covariate profile. This approach accommodates any log-linear hazard function of + prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide + a plot method for visualizing incidence density via population time plots. Based on the case-base sampling + approach of Hanley and Miettinen (2009) , Saarela and Arjas (2015) , + and Saarela (2015) . + date_publication: '2024-08-17' + bug_reports: https://github.com/sahirbhatnagar/casebase/issues + url: https://sahirbhatnagar.com/casebase/ + url_cran: https://CRAN.R-project.org/package=casebase + url_git: '' +CaseBasedReasoning: + version: '0.3' + title: Case Based Reasoning + maintainer: Simon Mueller + description: Case-based reasoning is a problem-solving methodology that involves + solving a new problem by referring to the solution of a similar problem in a large + set of previously solved problems. The key aspect of Case Based Reasoning is to + determine the problem that "most closely" matches the new problem at hand. This + is achieved by defining a family of distance functions and using these distance + functions as parameters for local averaging regression estimates of the final + result. The optimal distance function is chosen based on a specific error measure + used in regression estimation. This approach allows for efficient problem-solving + by leveraging past experiences and adapting solutions from similar cases. The + underlying concept is inspired by the work of Dippon J. (2002) . + date_publication: '2023-05-02' + bug_reports: https://github.com/sipemu/case-based-reasoning/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CaseBasedReasoning + url_git: https://github.com/sipemu/case-based-reasoning +CaseCohortCoxSurvival: + version: 0.0.36 + title: Case-Cohort Cox Survival Inference + maintainer: Lola Etievant + description: |- + Cox model inference for relative hazard and covariate-specific pure risk estimated + from stratified and unstratified case-cohort data as described in + Etievant, L., Gail, M.H. (Lifetime Data Analysis, 2024) . + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CaseCohortCoxSurvival + url_git: '' +caseMatch: + version: 1.1.0 + title: Identify Similar Cases for Qualitative Case Studies + maintainer: Rich Nielsen + description: Allows users to identify similar cases for qualitative case studies + using statistical matching methods. + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caseMatch + url_git: '' +cases: + version: 0.2.0 + title: Stratified Evaluation of Subgroup Classification Accuracy + maintainer: Max Westphal + description: Enables simultaneous statistical inference for the accuracy of multiple + classifiers in multiple subgroups (strata). For instance, allows to perform multiple + comparisons in diagnostic accuracy studies with co-primary endpoints sensitivity + and specificity (Westphal M, Zapf A. Statistical inference for diagnostic test + accuracy studies with multiple comparisons. Statistical Methods in Medical Research. + 2024;0(0). ). + date_publication: '2025-01-09' + bug_reports: https://github.com/maxwestphal/cases/issues + url: https://maxwestphal.github.io/cases/ + url_cran: https://CRAN.R-project.org/package=cases + url_git: https://github.com/maxwestphal/cases +casino: + version: 0.1.0 + title: Play Casino Games + maintainer: Anthony Pileggi + description: |- + Play casino games in the R console, + including poker, blackjack, and a slot machine. + Try to build your fortune before you succumb to the gambler's ruin! + date_publication: '2019-01-17' + bug_reports: https://github.com/anthonypileggi/casino/issues + url: https://anthonypileggi.github.io/casino + url_cran: https://CRAN.R-project.org/package=casino + url_git: https://github.com/anthonypileggi/casino +CASMAP: + version: 0.6.1 + title: |- + Detection of Statistically Significant Combinations of SNPs in + Association Mapping + maintainer: Dean Bodenham + description: A significant pattern mining-based toolbox for region-based genome-wide + association studies and higher-order epistasis analyses, implementing the methods + described in Llinares-López et al. (2017) . + date_publication: '2020-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CASMAP + url_git: '' +CASMI: + version: 2.0.0 + title: '''CASMI''-Based Functions' + maintainer: Jingyi (Catherine) Shi + description: Contains Coverage Adjusted Standardized Mutual Information ('CASMI')-based + functions. 'CASMI' is a fundamental concept of a series of methods. For more information + about 'CASMI' and 'CASMI'-related methods, please refer to the corresponding publications + (e.g., a feature selection method, Shi, J., Zhang, J., & Ge, Y. (2019) , + and a dataset quality measurement method, Shi, J., Zhang, J., & Ge, Y. (2019) + ) or contact the package author for the latest + updates. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CASMI + url_git: '' +cassandRa: + version: 0.2.0 + title: |- + Finds Missing Links and Metric Confidence Intervals in + Ecological Bipartite Networks + maintainer: Chris Terry + description: |- + Provides methods to deal with under sampling in ecological bipartite networks from + Terry and Lewis (2020) Ecology Includes + tools to fit a variety of statistical network models and sample coverage estimators to highlight most likely + missing links. Also includes simple functions to resample from observed networks to generate confidence + intervals for common ecological network metrics. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cassandRa + url_git: '' +cassowaryr: + version: 2.0.2 + title: Compute Scagnostics on Pairs of Numeric Variables in a Data Set + maintainer: Harriet Mason + description: |- + Computes a range of scatterplot diagnostics (scagnostics) on pairs + of numerical variables in a data set. A range of scagnostics, including graph + and association-based scagnostics described by Leland Wilkinson and Graham + Wills (2008) and association-based + scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be + computed. Summary and plotting functions are provided. + date_publication: '2024-09-13' + bug_reports: https://github.com/numbats/cassowaryr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cassowaryr + url_git: https://github.com/numbats/cassowaryr +CAST: + version: 1.0.3 + title: '''caret'' Applications for Spatial-Temporal Models' + maintainer: Hanna Meyer + description: Supporting functionality to run 'caret' with spatial or spatial-temporal + data. 'caret' is a frequently used package for model training and prediction using + machine learning. CAST includes functions to improve spatial or spatial-temporal + modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor + distance matching' cross-validation to estimate the performance of spatial prediction + models and allows for spatial variable selection to selects suitable predictor + variables in view to their contribution to the spatial model performance. CAST + further includes functionality to estimate the (spatial) area of applicability + of prediction models. Methods are described in Meyer et al. (2018) ; + Meyer et al. (2019) ; Meyer and Pebesma (2021) + ; Milà et al. (2022) ; + Meyer and Pebesma (2022) ; Linnenbrink et al. + (2023) ; Schumacher et al. (2024) . + The package is described in detail in Meyer et al. (2024) . + date_publication: '2025-01-09' + bug_reports: https://github.com/HannaMeyer/CAST/issues/ + url: https://hannameyer.github.io/CAST/ + url_cran: https://CRAN.R-project.org/package=CAST + url_git: https://github.com/HannaMeyer/CAST +castor: + version: 1.8.3 + title: Efficient Phylogenetics on Large Trees + maintainer: Stilianos Louca + description: 'Efficient phylogenetic analyses on massive phylogenies comprising + up to millions of tips. Functions include pruning, rerooting, calculation of most-recent + common ancestors, calculating distances from the tree root and calculating pairwise + distances. Calculation of phylogenetic signal and mean trait depth (trait conservatism), + ancestral state reconstruction and hidden character prediction of discrete characters, + simulating and fitting models of trait evolution, fitting and simulating diversification + models, dating trees, comparing trees, and reading/writing trees in Newick format. + Citation: Louca, Stilianos and Doebeli, Michael (2017) .' + date_publication: '2024-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=castor + url_git: '' +cat: + version: 0.0-9 + title: |- + Analysis and Imputation of Categorical-Variable Datasets with + Missing Values + maintainer: Fernando Tusell + description: Performs analysis of categorical-variable with missing values. Implements + methods from Schafer, JL, Analysis of Incomplete Multivariate Data, Chapman and + Hall. + date_publication: '2023-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cat + url_git: '' +cat2cat: + version: 0.4.7 + title: |- + Handling an Inconsistently Coded Categorical Variable in a + Longitudinal Dataset + maintainer: Maciej Nasinski + description: |2- + + Unifying an inconsistently coded categorical variable between two different time points in accordance with a mapping table. + The main rule is to replicate the observation if it could be assigned to a few categories. + Then using frequencies or statistical methods to approximate the probabilities of being assigned to each of them. + This procedure was invented and implemented in the paper by Nasinski, Majchrowska, and Broniatowska (2020) . + date_publication: '2024-01-22' + bug_reports: https://github.com/Polkas/cat2cat/issues + url: https://polkas.github.io/cat2cat/ + url_cran: https://CRAN.R-project.org/package=cat2cat + url_git: https://github.com/Polkas/cat2cat +cata: + version: 0.1.0.27 + title: Analysis of Check-All-that-Apply (CATA) Data + maintainer: J.C. Castura + description: Package contains functions for analyzing check-all-that-apply (CATA) + data from consumer and sensory tests. Cochran's Q test, McNemar's test, and Penalty-Lift + analysis are provided; for details, see Meyners, Castura & Carr (2013) . + Cluster analysis can be performed using b-cluster analysis, then evaluated using + various measures; for details, see Castura, Meyners, Varela & Næs (2022) . + Methods are adapted to cluster consumers based on their product-related hedonic + responses; for details, see Castura, Meyners, Pohjanheimo, Varela & Næs (2023) + . Permutation tests based on the L1-norm methods are provided; + for details, see Chaya, Castura & Greenacre (2025) . + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cata + url_git: '' +catalog: + version: 0.1.1 + title: Access the 'Spark Catalog' API via 'sparklyr' + maintainer: Nathan Eastwood + description: Gain access to the 'Spark Catalog' API making use of the 'sparklyr' + API. 'Catalog' + is the interface for managing a metastore (aka metadata catalog) of relational + entities (e.g. database(s), tables, functions, table columns and temporary views). + date_publication: '2022-08-22' + bug_reports: https://github.com/nathaneastwood/catalog/issues + url: https://nathaneastwood.github.io/catalog/ + url_cran: https://CRAN.R-project.org/package=catalog + url_git: https://github.com/nathaneastwood/catalog +catalytic: + version: 0.1.0 + title: Tools for Applying Catalytic Priors in Statistical Modeling + maintainer: Dongming Huang + description: To improve estimation accuracy and stability in statistical modeling, + catalytic prior distributions are employed, integrating observed data with synthetic + data generated from a simpler model's predictive distribution. This approach enhances + model robustness, stability, and flexibility in complex data scenarios. The catalytic + prior distributions are introduced by 'Huang et al.' (2020, ), + Li and Huang (2023, ). + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catalytic + url_git: '' +CatastRo: + version: 0.4.0 + title: Interface to the API 'Sede Electronica Del Catastro' + maintainer: Diego Hernangómez + description: |- + Access public spatial data available under the 'INSPIRE' + directive. Tools for downloading references and addresses of + properties, as well as map images. + date_publication: '2024-06-02' + bug_reports: https://github.com/rOpenSpain/CatastRo/issues + url: https://ropenspain.github.io/CatastRo/ + url_cran: https://CRAN.R-project.org/package=CatastRo + url_git: https://github.com/rOpenSpain/CatastRo +catch: + version: 1.0.1 + title: Covariate-Adjusted Tensor Classification in High-Dimensions + maintainer: Yuqing Pan + description: 'Performs classification and variable selection on high-dimensional + tensors (multi-dimensional arrays) after adjusting for additional covariates (scalar + or vectors) as CATCH model in Pan, Mai and Zhang (2018) . The + low-dimensional covariates and the high-dimensional tensors are jointly modeled + to predict a categorical outcome in a multi-class discriminant analysis setting. + The Covariate-Adjusted Tensor Classification in High-dimensions (CATCH) model + is fitted in two steps: (1) adjust for the covariates within each class; and (2) + penalized estimation with the adjusted tensor using a cyclic block coordinate + descent algorithm. The package can provide a solution path for tuning parameter + in the penalized estimation step. Special case of the CATCH model includes linear + discriminant analysis model and matrix (or tensor) discriminant analysis without + covariates.' + date_publication: '2021-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catch + url_git: '' +catcont: + version: 0.5.0 + title: |- + Test, Identify, Select and Mutate Categorical or Continuous + Values + maintainer: Christopher Brown + description: |- + Methods and utilities for testing, identifying, selecting and + mutating objects as categorical or continous types. These functions work on both + atomic vectors as well as recursive objects: data.frames, data.tables, + tibbles, lists, etc.. + date_publication: '2018-06-25' + bug_reports: https://github.com/decisionpatterns/catcont/issues + url: '' + url_cran: https://CRAN.R-project.org/package=catcont + url_git: https://github.com/decisionpatterns/catconthttp://www.decisionpatterns.com +catdap: + version: 1.3.7 + title: Categorical Data Analysis Program Package + maintainer: Masami Saga + description: |- + Categorical data analysis by AIC. The methodology is described in + Sakamoto (1992) . + date_publication: '2023-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catdap + url_git: '' +catdata: + version: 1.2.4 + title: Categorical Data + maintainer: Gunther Schauberger + description: This R-package contains examples from the book "Regression for Categorical + Data", Tutz 2012, Cambridge University Press. The names of the examples refer + to the chapter and the data set that is used. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catdata + url_git: '' +CatDataAnalysis: + version: 0.1-5 + title: Datasets for Categorical Data Analysis by Agresti + maintainer: Charles J. Geyer + description: |- + Datasets used in the book "Categorical Data Analysis" + by Agresti (2012, ISBN:978-0-470-46363-5) but not printed in the book. + Datasets and help pages were automatically produced from the source + by the R script foo.R, + which can be found in the GitHub repository. + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CatDataAnalysis + url_git: https://github.com/cjgeyer/CatDataAnalysis +CatDyn: + version: 1.1-1 + title: Fishery Stock Assessment by Catch Dynamics Models + maintainer: Ruben H. Roa-Ureta + description: Based on fishery Catch Dynamics instead of fish Population Dynamics + (hence CatDyn) and using high-frequency or medium-frequency catch in biomass or + numbers, fishing nominal effort, and mean fish body weight by time step, from + one or two fishing fleets, estimate stock abundance, natural mortality rate, and + fishing operational parameters. It includes methods for data organization, plotting + standard exploratory and analytical plots, predictions, for 100 types of models + of increasing complexity, and 72 likelihood models for the data. + date_publication: '2019-01-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CatDyn + url_git: '' +categoryEncodings: + version: 1.4.3 + title: Category Variable Encodings + maintainer: Juraj Szitas + description: |- + Simple, fast, and automatic encodings for category data using + a data.table backend. Most of the methods are an implementation + of "Sufficient Representation for Categorical Variables" by + Johannemann, Hadad, Athey, Wager (2019) , + particularly their mean, sparse principal component analysis, + low rank representation, and multinomial logit encodings. + date_publication: '2020-03-02' + bug_reports: https://github.com/JSzitas/categoryEncodings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=categoryEncodings + url_git: https://github.com/JSzitas/categoryEncodings +CatEncoders: + version: 0.1.1 + title: Encoders for Categorical Variables + maintainer: nl zhang + description: Contains some commonly used categorical variable encoders, such as + 'LabelEncoder' and 'OneHotEncoder'. Inspired by the encoders implemented in Python + 'sklearn.preprocessing' package (see ). + date_publication: '2017-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CatEncoders + url_git: '' +catfun: + version: 0.1.4 + title: Categorical Data Analysis + maintainer: Nick Williams + description: Includes wrapper functions around existing functions for the analysis + of categorical data and introduces functions for calculating risk differences + and matched odds ratios. R currently supports a wide variety of tools for the + analysis of categorical data. However, many functions are spread across a variety + of packages with differing syntax and poor compatibility with each another. prop_test() + combines the functions binom.test(), prop.test() and BinomCI() into one output. + prop_power() allows for power and sample size calculations for both balanced and + unbalanced designs. riskdiff() is used for calculating risk differences and matched_or() + is used for calculating matched odds ratios. For further information on methods + used that are not documented in other packages see Nathan Mantel and William Haenszel + (1959) and Alan Agresti (2002) . + date_publication: '2019-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catfun + url_git: '' +cati: + version: 0.99.4 + title: 'Community Assembly by Traits: Individuals and Beyond' + maintainer: Adrien Taudiere + description: Detect and quantify community assembly processes using trait values + of individuals or populations, the T-statistics and other metrics, and dedicated + null models. + date_publication: '2022-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cati + url_git: https://github.com/adrientaudiere/cati +catIrt: + version: 0.5.1 + title: Simulate IRT-Based Computerized Adaptive Tests + maintainer: Steven Nydick + description: |- + Functions designed to simulate data that conform to basic + unidimensional IRT models (for now 3-parameter binary response models + and graded response models) along with Post-Hoc CAT simulations of + those models given various item selection methods, ability estimation + methods, and termination criteria. See + Wainer (2000) , + van der Linden & Pashley (2010) , + and Eggen (1999) for more details. + date_publication: '2022-05-25' + bug_reports: https://github.com/swnydick/catIrt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=catIrt + url_git: https://github.com/swnydick/catIrt +catlearn: + version: '1.0' + title: Formal Psychological Models of Categorization and Learning + maintainer: Andy Wills + description: Formal psychological models of categorization and learning, independently-replicated + data sets against which to test them, and simulation archives. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catlearn + url_git: '' +catmap: + version: 1.6.4 + title: Case-Control and TDT Meta-Analysis Package + maintainer: Thomas Quinn + description: |- + Although many software tools can perform meta-analyses on genetic case-control data, + none of these apply to combined case-control and family-based (TDT) studies. This package conducts + fixed-effects (with inverse variance weighting) and random-effects [DerSimonian and Laird (1986) + ] meta-analyses on combined genetic data. Specifically, this package + implements a fixed-effects model [Kazeem and Farrall (2005) ] + and a random-effects model [Nicodemus (2008) ] for combined studies. + date_publication: '2017-06-29' + bug_reports: http://github.com/tpq/catmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=catmap + url_git: http://github.com/tpq/catmap +catmaply: + version: 0.9.4 + title: Heatmap for Categorical Data using 'plotly' + maintainer: Yves Mauron + description: |- + Methods and plotting functions for displaying categorical data on an + interactive heatmap using 'plotly'. Provides functionality for strictly + categorical heatmaps, heatmaps illustrating categorized continuous data + and annotated heatmaps. Also, there are various options to interact with the x-axis + to prevent overlapping axis labels, e.g. via simple sliders or range sliders. + Besides the viewer pane, resulting plots can be saved as a standalone HTML file, + embedded in 'R Markdown' documents or in a 'Shiny' app. + date_publication: '2024-01-30' + bug_reports: https://github.com/VerkehrsbetriebeZuerich/catmaply/issues + url: https://verkehrsbetriebezuerich.github.io/catmaply/ + url_cran: https://CRAN.R-project.org/package=catmaply + url_git: https://github.com/VerkehrsbetriebeZuerich/catmaply +caTools: + version: 1.18.3 + title: 'Tools: Moving Window Statistics, GIF, Base64, ROC AUC, etc' + maintainer: Michael Dietze + description: |- + Contains several basic utility functions including: moving + (rolling, running) window statistic functions, read/write for + GIF and ENVI binary files, fast calculation of AUC, LogitBoost + classifier, base64 encoder/decoder, round-off-error-free sum + and cumsum, etc. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=caTools + url_git: '' +CatPredi: + version: '1.3' + title: |- + Optimal Categorisation of Continuous Variables in Prediction + Models + maintainer: Irantzu Barrio + description: Allows the user to categorise a continuous predictor variable in a + logistic or a Cox proportional hazards regression setting, by maximising the discriminative + ability of the model. I Barrio, I Arostegui, MX Rodriguez-Alvarez, JM Quintana + (2015) . I Barrio, MX Rodriguez-Alvarez, L Meira-Machado, + C Esteban, I Arostegui (2017) . + date_publication: '2022-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CatPredi + url_git: '' +catR: + version: '3.17' + title: |- + Generation of IRT Response Patterns under Computerized Adaptive + Testing + maintainer: Cheng Hua + description: Provides routines for the generation of response patterns under unidimensional + dichotomous and polytomous computerized adaptive testing (CAT) framework. It holds + many standard functions to estimate ability, select the first item(s) to administer + and optimally select the next item, as well as several stopping rules. Options + to control for item exposure and content balancing are also available (Magis and + Barrada (2017) ). + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catR + url_git: '' +CatReg: + version: 2.0.3 + title: |- + Solution Paths for Linear and Logistic Regression Models with + Categorical Predictors, with SCOPE Penalty + maintainer: Daniel Grose + description: Computes solutions for linear and logistic regression models with potentially + high-dimensional categorical predictors. This is done by applying a nonconvex + penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The + scaling of the solution paths is selected automatically. Includes functionality + for selecting tuning parameter lambda by k-fold cross-validation and early termination + based on information criteria. Solutions are computed by cyclical block-coordinate + descent, iterating an innovative dynamic programming algorithm to compute exact + solutions for each block. + date_publication: '2021-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CatReg + url_git: '' +catregs: + version: 1.2.2 + title: Post-Estimation Functions for Generalized Linear Mixed Models + maintainer: David Melamed + description: 'Several functions for working with mixed effects regression models + for limited dependent variables. The functions facilitate post-estimation of model + predictions or margins, and comparisons between model predictions for assessing + or probing moderation. Additional helper functions facilitate model comparisons + and implements simulation-based inference for model predictions of alternative-specific + outcome models. See also, Melamed and Doan (2024, ISBN: 978-1032509518).' + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catregs + url_git: '' +cats: + version: 1.0.2 + title: Cohort Platform Trial Simulation + maintainer: Elias Laurin Meyer + description: |- + Cohort plAtform Trial Simulation whereby every cohort consists of two arms, + control and experimental treatment. Endpoints are co-primary binary endpoints and + decisions are made using either Bayesian or frequentist decision rules. + Realistic trial trajectories are simulated and the operating characteristics of the + designs are calculated. + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cats + url_git: '' +catseyes: + version: 0.2.5 + title: |- + Create Catseye Plots Illustrating the Normal Distribution of the + Means + maintainer: Clark Andersen + description: |- + Provides the tools to produce catseye plots, principally + by catseyesplot() function which calls R's standard plot() function internally, or alternatively + by the catseyes() function to overlay the catseye plot onto an existing + R plot window. Catseye plots illustrate the normal distribution of the mean (picture a + normal bell curve reflected over its base and rotated 90 degrees), with a shaded confidence + interval; they are an intuitive way of illustrating and comparing normally distributed estimates, + and are arguably a superior alternative to standard confidence intervals, since they show the full + distribution rather than fixed quantile bounds. The catseyesplot and catseyes functions require + pre-calculated means and standard errors (or standard deviations), provided as numeric vectors; + this allows the flexibility of obtaining this information from a variety of sources, such as + direct calculation or prediction from a model. Catseye plots, as illustrations of the + normal distribution of the means, are described in Cumming (2013 & 2014). + Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 27, 7-29. pmid:24220629. + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=catseyes + url_git: '' +catsim: + version: 0.2.4 + title: Binary and Categorical Image Similarity Index + maintainer: Geoffrey Thompson + description: |- + Computes a structural similarity metric (after the style of + MS-SSIM for images) for binary and categorical 2D and 3D images. Can be + based on accuracy (simple matching), Cohen's kappa, Rand index, adjusted + Rand index, Jaccard index, Dice index, normalized mutual information, or + adjusted mutual information. In addition, has fast computation + of Cohen's kappa, the Rand indices, and the two mutual informations. + Implements the methods of Thompson and Maitra (2020) . + date_publication: '2024-10-01' + bug_reports: https://github.com/gzt/catsim/issues + url: https://gzt.github.io/catsim/ + url_cran: https://CRAN.R-project.org/package=catsim + url_git: '' +catSurv: + version: 1.5.0 + title: Computerized Adaptive Testing for Survey Research + maintainer: Erin Rossiter + description: Provides methods of computerized adaptive testing for survey researchers. See + Montgomery and Rossiter (2020) . Includes functionality + for data fit with the classic item response methods including the latent trait + model, Birnbaum`s three parameter model, the graded response, and the generalized + partial credit model. Additionally, includes several ability parameter estimation + and item selection routines. During item selection, all calculations are done + in compiled C++ code. + date_publication: '2022-12-03' + bug_reports: https://github.com/erossiter/catSurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=catSurv + url_git: '' +CATT: + version: '2.0' + title: The Cochran-Armitage Trend Test + maintainer: Zhicheng Du + description: This function conducts the Cochran-Armitage trend test to a 2 by k + contingency table. It will report the test statistic (Z) and p-value.A linear + trend in the frequencies will be calculated, because the weights (0,1,2) will + be used by default. + date_publication: '2017-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CATT + url_git: '' +CATTexact: + version: 0.1.1 + title: |- + Computation of the p-Value for the Exact Conditional + Cochran-Armitage Trend Test + maintainer: Dominic Edelmann + description: |- + Provides functions for computing the one-sided p-values of the Cochran-Armitage trend test + statistic for the asymptotic and the exact conditional test. The computation of the p-value for the exact test + is performed using an algorithm following an idea by Mehta, et al. (1992) . + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CATTexact + url_git: '' +cauchypca: + version: '1.3' + title: |- + Robust Principal Component Analysis Using the Cauchy + Distribution + maintainer: Michail Tsagris + description: 'A new robust principal component analysis algorithm is implemented + that relies upon the Cauchy Distribution. The algorithm is suitable for high dimensional + data even if the sample size is less than the number of variables. The methodology + is described in this paper: Fayomi A., Pantazis Y., Tsagris M. and Wood A.T.A. + (2024). "Cauchy robust principal component analysis with applications to high-dimensional + data sets". Statistics and Computing, 34: 26. .' + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cauchypca + url_git: '' +cauphy: + version: 1.0.3 + title: Trait Evolution on Phylogenies Using the Cauchy Process + maintainer: Paul Bastide + description: |- + The Cauchy Process can model pulsed continuous trait evolution + on phylogenies. The likelihood is tractable, and is used for parameter + inference and ancestral trait reconstruction. + See Bastide and Didier (2023) . + date_publication: '2024-10-01' + bug_reports: https://github.com/gilles-didier/cauphy/issues + url: https://gilles-didier.github.io/cauphy/ + url_cran: https://CRAN.R-project.org/package=cauphy + url_git: '' +causact: + version: 0.5.7 + title: Fast, Easy, and Visual Bayesian Inference + maintainer: Adam Fleischhacker + description: |- + Accelerate Bayesian analytics workflows in 'R' through interactive modelling, + visualization, and inference. Define probabilistic graphical models using directed + acyclic graphs (DAGs) as a unifying language for business stakeholders, statisticians, + and programmers. This package relies on interfacing with the 'numpyro' python package. + date_publication: '2025-01-15' + bug_reports: https://github.com/flyaflya/causact/issues + url: https://www.causact.com/ + url_cran: https://CRAN.R-project.org/package=causact + url_git: https://github.com/flyaflya/causact +causal.decomp: + version: 0.1.0 + title: Causal Decomposition Analysis + maintainer: Suyeon Kang + description: We implement causal decomposition analysis using the methods proposed + by Park, Lee, and Qin (2020) and Park, Kang, and Lee (2021+) . + This package allows researchers to use the multiple-mediator-imputation, single-mediator-imputation, + and product-of-coefficients regression methods to estimate the initial disparity, + disparity reduction, and disparity remaining. It also allows to make the inference + conditional on baseline covariates. We also implement sensitivity analysis for + the causal decomposition analysis using R-squared values as sensitivity parameters + (Park, Kang, Lee, and Ma, 2023). + date_publication: '2023-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causal.decomp + url_git: '' +causalBatch: + version: 1.3.0 + title: Causal Batch Effects + maintainer: Eric W. Bridgeford + description: Software which provides numerous functionalities for detecting and + removing group-level effects from high-dimensional scientific data which, when + combined with additional assumptions, allow for causal conclusions, as-described + in our manuscripts Bridgeford et al. (2024) and + Bridgeford et al. (2023) . Also provides a number + of useful utilities for generating simulations and balancing covariates across + multiple groups/batches of data via matching and propensity trimming for more + than two groups. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causalBatch + url_git: https://github.com/neurodata/causal_batch +causalCmprsk: + version: 2.0.0 + title: |- + Nonparametric and Cox-Based Estimation of Average Treatment + Effects in Competing Risks + maintainer: Bella Vakulenko-Lagun + description: Estimation of average treatment effects (ATE) of point interventions + on time-to-event outcomes with K competing risks (K can be 1). The method uses + propensity scores and inverse probability weighting for emulation of baseline + randomization, which is described in Charpignon et al. (2022) . + date_publication: '2023-07-04' + bug_reports: https://github.com/Bella2001/causalCmprsk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=causalCmprsk + url_git: https://github.com/Bella2001/causalCmprsk +causaldata: + version: 0.1.4 + title: Example Data Sets for Causal Inference Textbooks + maintainer: Nick Huntington-Klein + description: |- + Example data sets to run the example + problems from causal inference textbooks. Currently, contains data + sets for Huntington-Klein, Nick (2021 and 2025) "The Effect" , first and second edition, + Cunningham, Scott (2021 and 2025, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape", + and Hernán, Miguel and James Robins (2020) "Causal Inference: What If" + . + date_publication: '2024-10-24' + bug_reports: https://github.com/NickCH-K/causaldata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=causaldata + url_git: https://github.com/NickCH-K/causaldata +causalDisco: + version: 0.9.1 + title: Tools for Causal Discovery on Observational Data + maintainer: Anne Helby Petersen + description: |- + Various tools for inferring causal models from observational data. The package + includes an implementation of the temporal Peter-Clark (TPC) algorithm. Petersen, Osler + and Ekstrøm (2021) . It also includes general tools + for evaluating differences in adjacency matrices, which can be used for evaluating + performance of causal discovery procedures. + date_publication: '2022-05-12' + bug_reports: https://github.com/annennenne/causalDisco/issues + url: '' + url_cran: https://CRAN.R-project.org/package=causalDisco + url_git: https://github.com/annennenne/causalDisco +causaldrf: + version: 0.4.2 + title: Estimating Causal Dose Response Functions + maintainer: Douglas Galagate + description: Functions and data to estimate causal dose response functions given + continuous, ordinal, or binary treatments. A description of the methods is given + in Galagate (2016) . + date_publication: '2022-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causaldrf + url_git: '' +causaleffect: + version: 1.3.15 + title: |- + Deriving Expressions of Joint Interventional Distributions and + Transport Formulas in Causal Models + maintainer: Santtu Tikka + description: Functions for identification and transportation of causal effects. + Provides a conditional causal effect identification algorithm (IDC) by Shpitser, + I. and Pearl, J. (2006) , an + algorithm for transportability from multiple domains with limited experiments + by Bareinboim, E. and Pearl, J. (2014) , + and a selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015) + . All of the previously mentioned + algorithms are based on a causal effect identification algorithm by Tian , J. + (2002) . + date_publication: '2022-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causaleffect + url_git: https://github.com/santikka/causaleffect/ +CausalGAM: + version: 0.1-4 + title: Estimation of Causal Effects with Generalized Additive Models + maintainer: Kevin Quinn + description: |- + Implements various estimators for average + treatment effects - an inverse probability weighted (IPW) estimator, + an augmented inverse probability weighted (AIPW) estimator, and a standard + regression estimator - that make use of generalized additive models for + the treatment assignment model and/or outcome model. See: Glynn, Adam N. + and Kevin M. Quinn. 2010. "An Introduction to the Augmented Inverse + Propensity Weighted Estimator." Political Analysis. 18: 36-56. + date_publication: '2017-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CausalGAM + url_git: '' +CausalGPS: + version: 0.5.0 + title: |- + Matching on Generalized Propensity Scores with Continuous + Exposures + maintainer: Naeem Khoshnevis + description: |- + Provides a framework for estimating causal effects of a continuous + exposure using observational data, and implementing matching and weighting + on the generalized propensity score. + Wu, X., Mealli, F., Kioumourtzoglou, M.A., Dominici, F. and Braun, D., 2022. + Matching on generalized propensity scores with continuous exposures. Journal + of the American Statistical Association, pp.1-29. + date_publication: '2024-06-19' + bug_reports: https://github.com/NSAPH-Software/CausalGPS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CausalGPS + url_git: https://github.com/NSAPH-Software/CausalGPS +causalHyperGraph: + version: 0.1.0 + title: Drawing Causal Hypergraphs + maintainer: Mathias Ambuehl + description: Draws causal hypergraph plots from models output by configurational + comparative methods such as Coincidence Analysis (CNA) or Qualitative Comparative + Analysis (QCA). + date_publication: '2024-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causalHyperGraph + url_git: '' +CausalImpact: + version: 1.3.0 + title: |- + Inferring Causal Effects using Bayesian Structural Time-Series + Models + maintainer: Alain Hauser + description: |- + Implements a Bayesian approach to causal impact estimation in time + series, as described in Brodersen et al. (2015) . + See the package documentation on GitHub + to get started. + date_publication: '2022-11-09' + bug_reports: '' + url: https://google.github.io/CausalImpact/ + url_cran: https://CRAN.R-project.org/package=CausalImpact + url_git: '' +CausalMBSTS: + version: 0.1.1 + title: MBSTS Models for Causal Inference and Forecasting + maintainer: Fiammetta Menchetti + description: |- + Infers the causal effect of an intervention on a multivariate response through the use of Multivariate + Bayesian Structural Time Series models (MBSTS) as described in Menchetti & Bojinov (2020) . + The package also includes functions for model building and forecasting. + date_publication: '2021-10-05' + bug_reports: https://github.com/FMenchetti/CausalMBSTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CausalMBSTS + url_git: '' +CausalMetaR: + version: 0.1.2 + title: Causally Interpretable Meta-Analysis + maintainer: Sean McGrath + description: Provides robust and efficient methods for estimating causal effects + in a target population using a multi-source dataset, including those of Dahabreh + et al. (2019) , Robertson et al. (2021) , + and Wang et al. (2024) . The multi-source data + can be a collection of trials, observational studies, or a combination of both, + which have the same data structure (outcome, treatment, and covariates). The target + population can be based on an internal dataset or an external dataset where only + covariate information is available. The causal estimands available are average + treatment effects and subgroup treatment effects. See Wang et al. (2024) + for a detailed guide on using the package. + date_publication: '2024-06-04' + bug_reports: https://github.com/ly129/CausalMetaR/issues + url: https://arxiv.org/abs/2402.04341 + url_cran: https://CRAN.R-project.org/package=CausalMetaR + url_git: https://github.com/ly129/CausalMetaR +CausalModels: + version: 0.2.0 + title: Causal Inference Modeling for Estimation of Causal Effects + maintainer: Joshua Anderson + description: |2- + + Provides an array of statistical models common in causal inference such as + standardization, IP weighting, propensity matching, outcome regression, and doubly-robust + estimators. Estimates of the average treatment effects from each model are given with the + standard error and a 95% Wald confidence interval (Hernan, Robins (2020) ). + date_publication: '2022-11-23' + bug_reports: https://github.com/ander428/CausalModels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CausalModels + url_git: https://github.com/ander428/CausalModels +causaloptim: + version: 1.0.0 + title: |- + An Interface to Specify Causal Graphs and Compute Bounds on + Causal Effects + maintainer: Michael C Sachs + description: |- + When causal quantities are not identifiable from the observed data, it still may be possible + to bound these quantities using the observed data. We outline a class of problems for which the + derivation of tight bounds is always a linear programming problem and can therefore, at least + theoretically, be solved using a symbolic linear optimizer. We extend and generalize the + approach of Balke and Pearl (1994) and we provide + a user friendly graphical interface for setting up such problems via directed acyclic + graphs (DAG), which only allow for problems within this class to be depicted. The user can + then define linear constraints to further refine their assumptions to meet their specific + problem, and then specify a causal query using a text interface. The program converts this + user defined DAG, query, and constraints, and returns tight bounds. The bounds can be + converted to R functions to evaluate them for specific datasets, and to latex code for + publication. The methods and proofs of tightness and validity of the bounds are described in + a paper by Sachs, Jonzon, Gabriel, and Sjölander (2022) + . + date_publication: '2024-10-17' + bug_reports: https://github.com/sachsmc/causaloptim/issues/ + url: https://sachsmc.github.io/causaloptim/ + url_cran: https://CRAN.R-project.org/package=causaloptim + url_git: '' +causalOT: + version: 1.0.2 + title: Optimal Transport Weights for Causal Inference + maintainer: Eric Dunipace + description: |- + Uses optimal transport distances to find probabilistic + matching estimators for causal inference. + These methods are described in Dunipace, Eric (2021) . + The package will build the weights, estimate treatment effects, and + calculate confidence intervals via the methods described in the paper. + The package also supports several other methods as described in the help + files. + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causalOT + url_git: '' +causalPAF: + version: 1.2.5 + title: Causal Effect for Population Attributable Fractions (PAF) + maintainer: Maurice O'Connell + description: |- + Calculates population attributable fraction causal effects. + The 'causalPAF' package contains a suite of functions for causal + analysis calculations of population attributable fractions (PAF) given + a causal diagram which apply both: Pathway-specific population + attributable fractions (PS-PAFs) O’Connell and Ferguson (2022) + and Sequential population attributable + fractions Ferguson, O’Connell, and O’Donnell (2020) + . Results are presentable in both + table and plot format. + date_publication: '2022-08-19' + bug_reports: https://github.com/MauriceOConnell/causalPAF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=causalPAF + url_git: https://github.com/MauriceOConnell/causalPAF +causalQual: + version: 1.0.0 + title: Causal Inference for Qualitative Outcomes + maintainer: Riccardo Di Francesco + description: |- + Implements the framework introduced in Di Francesco and Mellace (2025) , shifting the focus to well-defined and interpretable + estimands that quantify how treatment affects the probability distribution over outcome categories. It supports selection-on-observables, instrumental variables, + regression discontinuity, and difference-in-differences designs. + date_publication: '2025-02-24' + bug_reports: '' + url: https://riccardo-df.github.io/causalQual/ + url_cran: https://CRAN.R-project.org/package=causalQual + url_git: '' +CausalQueries: + version: 1.3.3 + title: Make, Update, and Query Binary Causal Models + maintainer: Till Tietz + description: 'Users can declare causal models over binary nodes, update beliefs + about causal types given data, and calculate arbitrary queries. Updating is implemented + in ''stan''. See Humphreys and Jacobs, 2023, Integrated Inferences () + and Pearl, 2009 Causality ().' + date_publication: '2025-02-22' + bug_reports: https://github.com/integrated-inferences/CausalQueries/issues + url: https://integrated-inferences.github.io/CausalQueries/ + url_cran: https://CRAN.R-project.org/package=CausalQueries + url_git: '' +causalsens: + version: 0.1.3 + title: |- + Selection Bias Approach to Sensitivity Analysis for Causal + Effects + maintainer: Matthew Blackwell + description: The causalsens package provides functions to perform sensitivity analyses + and to study how various assumptions about selection bias affects estimates of + causal effects. + date_publication: '2024-03-18' + bug_reports: '' + url: https://www.mattblackwell.org/software/causalsens/ + url_cran: https://CRAN.R-project.org/package=causalsens + url_git: '' +causalSLSE: + version: 0.3-1 + title: Semiparametric Least Squares Inference for Causal Effects + maintainer: Pierre Chausse Developer + description: Several causal effects are measured using least squares regressions + and basis function approximations. Backward and forward selection methods based + on different criteria are used to select the basis functions. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causalSLSE + url_git: '' +causalweight: + version: 1.1.1 + title: |- + Estimation Methods for Causal Inference Based on Inverse + Probability Weighting + maintainer: Hugo Bodory + description: Various estimators of causal effects based on inverse probability weighting, + doubly robust estimation, and double machine learning. Specifically, the package + includes methods for estimating average treatment effects, direct and indirect + effects in causal mediation analysis, and dynamic treatment effects. The models + refer to studies of Froelich (2007) , Huber + (2012) , Huber (2014) , + Huber (2014) , Froelich and Huber (2017) , + Hsu, Huber, Lee, and Lettry (2020) , and others. + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=causalweight + url_git: '' +CausCor: + version: 0.1.3 + title: Calculate Correlations and Estimate Causality + maintainer: Tomomi Sugiyama + description: |- + This tool performs pairwise correlation analysis and estimate causality. + Particularly, it is useful for detecting the metabolites that would be altered by the gut bacteria. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CausCor + url_git: https://github.com/sugym/CausCor +CautiousLearning: + version: 1.0.1 + title: |- + Control Charts with Guaranteed In-Control Performance and + Cautious Parameters Learning + maintainer: Giovanna Capizzi + description: |- + Design and use of control charts for detecting mean changes + based on a delayed updating of the in-control parameter estimates. + See Capizzi and Masarotto (2019) for the + description of the method. + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CautiousLearning + url_git: '' +CAvariants: + version: '6.0' + title: Correspondence Analysis Variants + maintainer: Rosaria Lombardo + description: |- + Provides six variants of two-way correspondence analysis (ca): + simple ca, singly ordered ca, doubly ordered ca, non symmetrical ca, + singly ordered non symmetrical ca, and doubly ordered non symmetrical + ca. + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CAvariants + url_git: '' +caviarpd: + version: 0.3.13 + title: Cluster Analysis via Random Partition Distributions + maintainer: David B. Dahl + description: |- + Cluster analysis is performed using pairwise distance information and a random partition distribution. The method is + implemented for two random partition distributions. It draws samples and then obtains and plots clustering estimates. + An implementation of a selection algorithm is provided for the mass parameter of the partition distribution. Since + pairwise distances are the principal input to this procedure, it is most comparable to the hierarchical and k-medoids + clustering methods. The method is Dahl, Andros, Carter (2022+) . + date_publication: '2024-09-06' + bug_reports: https://github.com/dbdahl/caviarpd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=caviarpd + url_git: https://github.com/dbdahl/caviarpd +CB2: + version: 1.3.4 + title: CRISPR Pooled Screen Analysis using Beta-Binomial Test + maintainer: Hyun-Hwan Jeong + description: |- + Provides functions for hit gene identification and quantification of sgRNA (single-guided RNA) abundances for CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) pooled screen data analysis. + Details are in Jeong et al. (2019) and Baggerly et al. (2003) . + date_publication: '2020-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CB2 + url_git: '' +cba: + version: 0.2-25 + title: Clustering for Business Analytics + maintainer: Christian Buchta + description: Implements clustering techniques such as Proximus and Rock, utility + functions for efficient computation of cross distances and data manipulation. + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cba + url_git: '' +cbanalysis: + version: 0.2.0 + title: Coffee Break Descriptive Analysis + maintainer: Sandip Kumar Gupta + description: A set of functions that helps you to generate descriptive statistics + based on the variable types. + date_publication: '2017-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cbanalysis + url_git: '' +cbass: + version: '0.1' + title: Classification -- Bayesian Adaptive Smoothing Splines + maintainer: Frank Marrs + description: Fit multiclass Classification version of Bayesian Adaptive Smoothing + Splines (CBASS) to data using reversible jump MCMC. The multiclass classification + problem consists of a response variable that takes on unordered categorical values + with at least three levels, and a set of inputs for each response variable. The + CBASS model consists of a latent multivariate probit formulation, and the means + of the latent Gaussian random variables are specified using adaptive regression + splines. The MCMC alternates updates of the latent Gaussian variables and the + spline parameters. All the spline parameters (variables, signs, knots, number + of interactions), including the number of basis functions used to model each latent + mean, are inferred. Functions are provided to process inputs, initialize the chain, + run the chain, and make predictions. Predictions are made on a probabilistic basis, + where, for a given input, the probabilities of each categorical value are produced. + See Marrs and Francom (2023) "Multiclass classification using Bayesian multivariate + adaptive regression splines" Under review. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cbass + url_git: '' +cbbinom: + version: 0.2.0 + title: Continuous Analog of a Beta-Binomial Distribution + maintainer: Xiurui Zhu + description: Implementation of the d/p/q/r family of functions for a continuous + analog to the standard discrete beta-binomial with continuous size parameter and + continuous support with x in [0, size + 1]. + date_publication: '2024-10-17' + bug_reports: https://github.com/zhuxr11/cbbinom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cbbinom + url_git: https://github.com/zhuxr11/cbbinom +CBCgrps: + version: 2.8.2 + title: Compare Baseline Characteristics Between Groups + maintainer: Zhongheng Zhang + description: Compare baseline characteristics between two or more groups. The variables + being compared can be factor and numeric variables. The function will automatically + judge the type and distribution of the variables, and make statistical description + and bivariate analysis. + date_publication: '2021-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBCgrps + url_git: '' +cbcTools: + version: 0.5.0 + title: |- + Choice-Based Conjoint Experiment Design Generation and Power + Evaluation in R + maintainer: John Helveston + description: Design and evaluate choice-based conjoint survey experiments. Generate + a variety of survey designs, including random designs, full factorial designs, + orthogonal designs, D-optimal designs, and Bayesian D-efficient designs as well + as designs with "no choice" options and "labeled" (also known as "alternative + specific") designs. Conveniently inspect the design balance and overlap, and simulate + choice data for a survey design either randomly or according to a multinomial + or mixed logit utility model defined by user-provided prior parameters. Conduct + a power analysis for a given survey design by estimating the same model on different + subsets of the data to simulate different sample sizes. Full factorial and orthogonal + designs are obtained using the 'DoE.base' package (Grömping, 2018) . + D-optimal designs are obtained using the 'AlgDesign' package (Wheeler, 2022) . + Bayesian D-efficient designs are obtained using the 'idefix' package (Traets et + al, 2020) . Choice simulation and model estimation + in power analyses are handled using the 'logitr' package (Helveston, 2023) . + date_publication: '2023-07-12' + bug_reports: https://github.com/jhelvy/cbcTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cbcTools + url_git: https://github.com/jhelvy/cbcTools +cbinom: + version: '1.6' + title: Continuous Analog of a Binomial Distribution + maintainer: Dan Dalthorp + description: Implementation of the d/p/q/r family of functions for a continuous + analog to the standard discrete binomial with continuous size parameter and continuous + support with x in [0, size + 1], following Ilienko (2013) . + date_publication: '2021-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cbinom + url_git: '' +cbioportalR: + version: 1.1.1 + title: Browse and Query Clinical and Genomic Data from cBioPortal + maintainer: Karissa Whiting + description: |- + Provides R users with direct access to genomic and clinical data from the 'cBioPortal' web resource via user-friendly + functions that wrap 'cBioPortal's' existing API endpoints . Users can browse and query genomic data on mutations, + copy number alterations and fusions, as well as data on tumor mutational burden ('TMB'), + microsatellite instability status ('MSI'), 'FACETS' and select clinical data points (depending on the study). + See and Gao et al., (2013) for more information on the cBioPortal web resource. + date_publication: '2024-11-20' + bug_reports: https://github.com/karissawhiting/cbioportalR/issues + url: https://www.karissawhiting.com/cbioportalR/ + url_cran: https://CRAN.R-project.org/package=cbioportalR + url_git: https://github.com/karissawhiting/cbioportalR +cbl: + version: 0.1.3 + title: Causal Discovery under a Confounder Blanket + maintainer: David Watson + description: |- + Methods for learning causal relationships among a set of + foreground variables X based on signals from a (potentially much + larger) set of background variables Z, which are known non-descendants + of X. The confounder blanket learner (CBL) uses sparse regression + techniques to simultaneously perform many conditional independence + tests, with complementary pairs stability selection to guarantee + finite sample error control. CBL is sound and complete with respect to + a so-called "lazy oracle", and works with both linear and nonlinear + systems. For details, see Watson & Silva (2022) . + date_publication: '2022-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cbl + url_git: https://github.com/dswatson/cbl +CBnetworkMA: + version: 0.1.0 + title: Contrast-Based Bayesian Network Meta Analysis + maintainer: Garritt L. Page + description: |- + A function that facilitates fitting three types of models + for contrast-based Bayesian Network Meta Analysis. The first model is that which + is described in Lu and Ades (2006) . The other two + models are based on a Bayesian nonparametric methods that permit ties when comparing + treatment or for a treatment effect to be exactly equal to zero. In addition to the + model fits, the package provides a summary of the interplay between treatment + effects based on the procedure described in Barrientos, Page, and Lin (2023) + . + date_publication: '2024-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBnetworkMA + url_git: '' +CBPE: + version: 0.1.0 + title: Correlation-Based Penalized Estimators + maintainer: Mina Norouzirad + description: Provides correlation-based penalty estimators for both linear and logistic + regression models by implementing a new regularization method that incorporates + correlation structures within the data. This method encourages a grouping effect + where strongly correlated predictors tend to be in or out of the model together. + See Tutz and Ulbricht (2009) and Algamal and Lee + (2015) . + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBPE + url_git: https://github.com/mnrzrad/CBPE +CBPS: + version: '0.23' + title: Covariate Balancing Propensity Score + maintainer: Christian Fong + description: |- + Implements the covariate balancing propensity score (CBPS) proposed + by Imai and Ratkovic (2014) . The propensity score is + estimated such that it maximizes the resulting covariate balance as well as the + prediction of treatment assignment. The method, therefore, avoids an iteration + between model fitting and balance checking. The package also implements optimal + CBPS from Fan et al. (in-press) , + several extensions of the CBPS beyond the cross-sectional, binary treatment setting. + They include the CBPS for longitudinal settings so that it can be used in + conjunction with marginal structural models from Imai and Ratkovic (2015) + , treatments with three- and four-valued treatment + variables, continuous-valued treatments from Fong, Hazlett, and Imai (2018) + , propensity score estimation with a large number of + covariates from Ning, Peng, and Imai (2020) , and the situation + with multiple distinct binary treatments administered simultaneously. In the future + it will be extended to other settings including the generalization of experimental + and instrumental variable estimates. + date_publication: '2022-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBPS + url_git: '' +cbq: + version: 0.2.0.3 + title: Conditional Binary Quantile Models + maintainer: Xiao LU + description: Estimates conditional binary quantile models developed by Lu (2020) + . The estimation procedure is implemented based on Markov + chain Monte Carlo methods. + date_publication: '2023-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cbq + url_git: '' +CBRT: + version: 0.1.1 + title: CBRT Data on Turkish Economy + maintainer: Erol Taymaz + description: |- + The Central Bank of the Republic of Turkey (CBRT) provides one of + the most comprehensive time series databases on the Turkish economy. The 'CBRT' + package provides functions for accessing the CBRT's electronic data delivery + system . It contains the lists of all data + categories and data groups for searching the available variables (data series). + As of November 3, 2024, there were 40,826 variables in the dataset. The lists + of data categories and data groups can be updated by the user at any time. A + specific variable, a group of variables, or all variables in a data group can + be downloaded at different frequencies using a variety of aggregation methods. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBRT + url_git: https://github.com/etaymaz/CBRT +cbsodataR: + version: '1.1' + title: Statistics Netherlands (CBS) Open Data API Client + maintainer: Edwin de Jonge + description: |- + The data and meta data from Statistics + Netherlands () can be browsed and downloaded. The client uses + the open data API of Statistics Netherlands. + date_publication: '2024-09-25' + bug_reports: https://github.com/edwindj/cbsodataR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cbsodataR + url_git: https://github.com/edwindj/cbsodataR +CBSr: + version: 1.0.5 + title: |- + Fits Cubic Bezier Spline Functions to Intertemporal and Risky + Choice Data + maintainer: Sangil Lee + description: Uses monotonically constrained Cubic Bezier Splines (CBS) to approximate + latent utility functions in intertemporal choice and risky choice data. For more + information, see Lee, Glaze, Bradlow, and Kable . + date_publication: '2021-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBSr + url_git: '' +CBT: + version: '1.0' + title: Confidence Bound Target Algorithm + maintainer: Shouri Hu + description: 'The Confidence Bound Target (CBT) algorithm is designed for infinite + arms bandit problem. It is shown that CBT algorithm achieves the regret lower + bound for general reward distributions. Reference: Hock Peng Chan and Shouri Hu + (2018) .' + date_publication: '2018-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CBT + url_git: '' +CC: + version: '1.0' + title: Control Charts + maintainer: W.John Braun + description: 'Tools for creating and visualizing statistical process control charts. + Control charts are used for monitoring measurement processes, such as those occurring + in manufacturing. The objective is to monitor the history of such processes and + flag outlying measurements: out-of-control signals. Montgomery, D. (2009, ISBN:978-0-470-16992-6) + contains an extensive discussion of the methodology.' + date_publication: '2019-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CC + url_git: '' +CCA: + version: 1.2.2 + title: Canonical Correlation Analysis + maintainer: Sébastien Déjean + description: |- + Provides a set of functions that extend the + 'cancor' function with new numerical and graphical outputs. It + also include a regularized extension of the canonical + correlation analysis to deal with datasets with more variables + than observations. + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCA + url_git: '' +CCAMLRGIS: + version: 4.2.1 + title: Antarctic Spatial Data Manipulation + maintainer: Stephane Thanassekos + description: |- + Loads and creates spatial data, including layers and tools that are relevant + to the activities of the Commission for the Conservation of Antarctic Marine Living + Resources. Provides two categories of functions: load functions and create functions. + Load functions are used to import existing spatial layers from the online CCAMLR GIS + such as the ASD boundaries. Create functions are used to create layers from user data + such as polygons and grids. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCAMLRGIS + url_git: https://github.com/ccamlr/CCAMLRGIS#ccamlrgis-r-package +ccaPP: + version: 0.3.4 + title: (Robust) Canonical Correlation Analysis via Projection Pursuit + maintainer: Andreas Alfons + description: |- + Canonical correlation analysis and maximum correlation via + projection pursuit, as well as fast implementations of correlation + estimators, with a focus on robust and nonparametric methods. + date_publication: '2024-09-04' + bug_reports: https://github.com/aalfons/ccaPP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ccaPP + url_git: https://github.com/aalfons/ccaPP +cccd: + version: '1.6' + title: Class Cover Catch Digraphs + maintainer: David J. Marchette + description: |- + Class Cover Catch Digraphs, neighborhood graphs, and + relatives. + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cccd + url_git: '' +cccm: + version: 0.1.0 + title: Crossed Classification Credibility Model + maintainer: Muhlis Ozdemir + description: Calculates the credit debt for the next period based on the available + data using the cross-classification credibility model. + date_publication: '2022-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cccm + url_git: '' +cccp: + version: 0.3-1 + title: Cone Constrained Convex Problems + maintainer: Bernhard Pfaff + description: Routines for solving convex optimization problems with cone constraints + by means of interior-point methods. The implemented algorithms are partially ported + from CVXOPT, a Python module for convex optimization (see + for more information). + date_publication: '2023-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cccp + url_git: '' +cccrm: + version: 3.0.4 + title: |- + Concordance Correlation Coefficient for Repeated (and + Non-Repeated) Measures + maintainer: Josep Lluis Carrasco + description: Estimates the Concordance Correlation Coefficient to assess agreement. + The scenarios considered are non-repeated measures, non-longitudinal repeated + measures (replicates) and longitudinal repeated measures. It also includes the + estimation of the one-way intraclass correlation coefficient also known as reliability + index. The estimation approaches implemented are variance components and U-statistics + approaches. Description of methods can be found in Fleiss (1986) + and Carrasco et al. (2013) . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cccrm + url_git: '' +CCd: + version: '1.1' + title: The Cauchy-Cacoullos (Discrete Cauchy) Distribution + maintainer: Michail Tsagris + description: 'Maximum likelihood estimation of the Cauchy-Cacoullos (discrete Cauchy) + distribution. Probability mass, distribution and quantile function are also included. + The reference paper is: Papadatos N. (2022). "The Characteristic Function of the + Discrete Cauchy Distribution in Memory of T. Cacoullos". Journal of Statistical + Theory Practice, 16(3): 47. .' + date_publication: '2024-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCd + url_git: '' +ccda: + version: 1.1.1 + title: Combined Cluster and Discriminant Analysis + maintainer: Solt Kovacs + description: 'Implements the combined cluster and discriminant analysis method for + finding homogeneous groups of data with known origin as described in Kovacs et. + al (2014): Classification into homogeneous groups using combined cluster and discriminant + analysis (CCDA). Environmental Modelling & Software. .' + date_publication: '2019-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccda + url_git: '' +ccdR: + version: 1.1.0 + title: Utilities for Interacting with the 'CTX' APIs + maintainer: Paul Kruse + description: |- + Access chemical, hazard, bioactivity, and exposure data from the + Computational Toxicology and Exposure ('CTX') APIs + . 'ccdR' was developed to streamline the + process of accessing the information available through the 'CTX' APIs + without requiring prior knowledge of how to use APIs. Most data is also + available on the CompTox Chemical Dashboard ('CCD') + and other resources found at the + EPA Computational Toxicology and Exposure Online Resources + . + date_publication: '2024-07-09' + bug_reports: https://github.com/USEPA/ccdR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ccdR + url_git: https://github.com/USEPA/ccdR +cchs: + version: 0.4.5 + title: |- + Cox Model for Case-Cohort Data with Stratified + Subcohort-Selection + maintainer: E. Jones + description: Contains a function, also called 'cchs', that calculates Estimator + III of Borgan et al (2000), . This estimator is for + fitting a Cox proportional hazards model to data from a case-cohort study where + the subcohort was selected by stratified simple random sampling. + date_publication: '2024-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cchs + url_git: '' +cchsflow: + version: 2.1.0 + title: Transforming and Harmonizing CCHS Variables + maintainer: Kitty Chen + description: |- + Supporting the use of the Canadian Community Health Survey + (CCHS) by transforming variables from each cycle into harmonized, + consistent versions that span survey cycles (currently, 2001 to + 2018). CCHS data used in this library is accessed and adapted in + accordance to the Statistics Canada Open Licence Agreement. This + package uses rec_with_table(), which was developed from 'sjmisc' + rec(). Lüdecke D (2018). "sjmisc: Data and Variable Transformation + Functions". Journal of Open Source Software, 3(26), 754. + . + date_publication: '2022-05-26' + bug_reports: https://github.com/Big-Life-Lab/cchsflow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cchsflow + url_git: https://github.com/Big-Life-Lab/cchsflow +ccid: + version: 1.2.0 + title: |- + Cross-Covariance Isolate Detect: a New Change-Point Method for + Estimating Dynamic Functional Connectivity + maintainer: Andreas Anastasiou + description: |- + Provides efficient implementation of the Cross-Covariance + Isolate Detect (CCID) methodology for the estimation of the number + and location of multiple change-points in the second-order + (cross-covariance or network) structure of multivariate, possibly + high-dimensional time series. The method is motivated by the detection + of change points in functional connectivity networks for functional + magnetic resonance imaging (fMRI), electroencephalography (EEG), + magentoencephalography (MEG) and electrocorticography (ECoG) data. The + main routines in the package have been extensively tested on fMRI data. + For details on the CCID methodology, please see Anastasiou et + al (2022), Cross-covariance isolate detect: A new change-point method for + estimating dynamic functional connectivity. Medical Image Analysis, Volume + 75. + date_publication: '2022-02-01' + bug_reports: https://github.com/Anastasiou-Andreas/ccid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ccid + url_git: https://github.com/Anastasiou-Andreas/ccid +cclust: + version: 0.6-26 + title: Convex Clustering Methods and Clustering Indexes + maintainer: Kurt Hornik + description: |- + Convex Clustering methods, including K-means algorithm, + On-line Update algorithm (Hard Competitive Learning) and Neural Gas + algorithm (Soft Competitive Learning), and calculation of several + indexes for finding the number of clusters in a data set. + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cclust + url_git: '' +CCM: + version: '1.2' + title: Correlation Classification Method + maintainer: Garrett M. Dancik + description: Classification method described in Dancik et al (2011) + that classifies a sample according to the class with the maximum mean (or any + other function of) correlation between the test and training samples with known + classes. + date_publication: '2018-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCM + url_git: '' +ccmEstimator: + version: 1.0.0 + title: Comparative Causal Mediation Estimation + maintainer: Xiaohan Wu + description: Functions to perform comparative causal mediation analysis to compare + the mediation effects of different treatments via a common mediator. Results contain + the estimates and confidence intervals for the two comparative causal mediation + analysis estimands, as well as the ATE and ACME for each treatment. Functions + provided in the package will automatically assess the comparative causal mediation + analysis scope conditions (i.e. for each comparative causal mediation estimand, + a numerator and denominator that are both estimated with the desired statistical + significance and of the same sign). Results will be returned for each comparative + causal mediation estimand only if scope conditions are met for it. See details + in Bansak(2020). + date_publication: '2021-09-28' + bug_reports: https://github.com/xiw021/ccmEstimator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ccmEstimator + url_git: https://github.com/xiw021/ccmEstimator +ccmm: + version: '1.0' + title: Compositional Mediation Model + maintainer: Michael B. Sohn + description: 'Estimate the direct and indirect (mediation) effects of treatment + on the outcome when intermediate variables (mediators) are compositional and high-dimensional. + Sohn, M.B. and Li, H. (2017). Compositional Mediation Analysis for Microbiome + Studies. (AOAS: In revision).' + date_publication: '2017-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccmm + url_git: '' +CCMMR: + version: 0.2.1 + title: Minimization of the Convex Clustering Loss Function + maintainer: Daniel Touw + description: Implements the convex clustering through majorization-minimization + (CCMM) algorithm described in Touw, Groenen, and Terada (2022) + to perform minimization of the convex clustering loss function. + date_publication: '2024-11-07' + bug_reports: https://github.com/djwtouw/CCMMR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=CCMMR + url_git: https://github.com/djwtouw/CCMMR/ +ccmReportR: + version: 0.1.0 + title: Wraps 'CCM' with Utility Functions + maintainer: James Lane + description: Provides a set of functions to perform queries against the 'CCM' API + . + date_publication: '2021-02-11' + bug_reports: https://github.com/DurhamRegionHARP/ccmReportR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ccmReportR + url_git: https://github.com/DurhamRegionHARP/ccmReportR +ccoptimalmatch: + version: 0.1.0 + title: Implementation of Case-Control Optimal Matching + maintainer: Pavlos Mamouris + description: |- + Cases are matched to controls in an efficient, optimal and computationally flexible way. It uses + the idea of sub-sampling in the level of the case, by creating pseudo-observations of controls. The + user can select between replacement and without replacement, the number of controls, and several covariates + to match upon. See Mamouris (2021) for an overview. + date_publication: '2021-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccoptimalmatch + url_git: '' +ccostr: + version: 0.1.0 + title: Estimation of Mean Costs in Censored Data + maintainer: Lars Boerty + description: |- + Implementation of estimators for inferring + the mean of censored cost data. Including the estimators + BT from Bang and Tsiatis (2000) and + ZT from Zhao and Tian (2001) . + date_publication: '2019-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccostr + url_git: '' +CCP: + version: '1.2' + title: Significance Tests for Canonical Correlation Analysis (CCA) + maintainer: Uwe Menzel + description: Significance tests are provided for canonical correlation analysis, + including asymptotic tests and a Monte Carlo method. + date_publication: '2022-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCP + url_git: '' +ccpsyc: + version: 0.2.6 + title: Methods for Cross-Cultural Psychology + maintainer: Johannes Karl + description: With the development of new cross-cultural methods this package is + intended to combine multiple functions automating and simplifying functions providing + a unified analysis approach for commonly employed methods. + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccpsyc + url_git: '' +ccRemover: + version: 1.0.4 + title: |- + Removes the Cell-Cycle Effect from Single-Cell RNA-Sequencing + Data + maintainer: Jun Li + description: |- + Implements a method for identifying and removing + the cell-cycle effect from scRNA-Seq data. The description of the + method is in Barron M. and Li J. (2016) . Identifying and removing + the cell-cycle effect from single-cell RNA-Sequencing data. Submitted. + Different from previous methods, ccRemover implements a mechanism that + formally tests whether a component is cell-cycle related or not, and thus + while it often thoroughly removes the cell-cycle effect, it preserves + other features/signals of interest in the data. + date_publication: '2017-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccRemover + url_git: '' +ccrs: + version: 0.1.0 + title: Correct and Cluster Response Style Biased Data + maintainer: Mariko Takagishi + description: 'Functions for performing Correcting and Clustering response-style-biased + preference data (CCRS). The main functions are correct.RS() for correcting for + response styles, and ccrs() for simultaneously correcting and content-based clustering. + The procedure begin with making rank-ordered boundary data from the given preference + matrix using a function called create.ccrsdata(). Then in correct.RS(), the response + style is corrected as follows: the rank-ordered boundary data are smoothed by + I-spline functions, the given preference data are transformed by the smoothed + functions. The resulting data matrix, which is considered as bias-corrected data, + can be used for any data analysis methods. If one wants to cluster respondents + based on their indicated preferences (content-based clustering), ccrs() can be + applied to the given (response-style-biased) preference data, which simultaneously + corrects for response styles and clusters respondents based on the contents. Also, + the correction result can be checked by plot.crs() function.' + date_publication: '2019-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccrs + url_git: '' +ccrtm: + version: 0.1.6 + title: Coupled Chain Radiative Transfer Models + maintainer: Marco D. Visser + description: A set of radiative transfer models to quantitatively describe the absorption, + reflectance and transmission of solar energy in vegetation, and model remotely + sensed spectral signatures of vegetation at distinct spatial scales (leaf,canopy + and stand). The main principle behind ccrtm is that many radiative transfer models + can form a coupled chain, basically models that feed into each other in a linked + chain (from leaf, to canopy, to stand, to atmosphere). It allows the simulation + of spectral datasets in the solar spectrum (400-2500nm) using leaf models as PROSPECT5, + 5b, and D which can be coupled with canopy models as 'FLIM', 'SAIL' and 'SAIL2'. + Currently, only a simple atmospheric model ('skyl') is implemented. Jacquemoud + et al 2008 provide the most comprehensive overview of these models . + date_publication: '2021-02-26' + bug_reports: https://github.com/MarcoDVisser/ccrtm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ccrtm + url_git: https://github.com/MarcoDVisser/ccrtm +CCSRfind: + version: 0.1.0 + title: Convert ICD-10 Codes to CCSR Codes + maintainer: Mark Ramos + description: 'Provides a tool for matching ICD-10 codes to corresponding Clinical + Classification Software Refined (CCSR) codes. The main function, CCSRfind(), identifies + each CCSR code that applies to an individual given their diagnosis codes. It also + provides a summary of CCSR codes that are matched to a dataset. The package contains + 3 datasets: ''DXCCSR'' (mapping of ICD-10 codes to CCSR codes), ''Legend'' (conversion + of DXCCSR to CCSRfind-usable format for CCSR codes with less than or equal to + 1000 ICD-10 diagnosis codes), and ''LegendExtend'' (conversion of DXCCSR to CCSRfind-usable + format for CCSR codes with more than 1000 ICD-10 dx codes). The disc() function + applies grepl() (''base'') to multiple columns and is used in CCSRfind().' + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCSRfind + url_git: '' +ccss: + version: '1.0' + title: Cluster Circular Systematic Sampling + maintainer: Abhibhav Sharma + description: Draws systematic samples from a population that follows linear trend. + The function returns a matrix comprising of the required samples as its column + vectors. The samples produced are highly efficient and the inter sampling variance + is minimum. The scheme will be useful in various field like Bioinformatics where + the samples are expensive and must be precise in reflecting the population by + possessing least sampling variance. + date_publication: '2019-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccss + url_git: '' +ccTensor: + version: 1.0.2 + title: CUR/CX Tensor Decomposition + maintainer: Koki Tsuyuzaki + description: CUR/CX decomposition factorizes a matrix into two factor matrices and + Multidimensional CX Decomposition factorizes a tensor into a core tensor and some + factor matrices. See the reference section of GitHub README.md , + for details of the methods. + date_publication: '2021-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ccTensor + url_git: https://github.com/rikenbit/ccTensor +cctest: + version: 1.2.0 + title: Canonical Correlations and Tests of Independence + maintainer: Robert Schlicht + description: |- + A simple interface for multivariate correlation analysis that unifies various classical + statistical procedures including t-tests, tests in univariate and multivariate linear models, + parametric and nonparametric tests for correlation, Kruskal-Wallis tests, common approximate + versions of Wilcoxon rank-sum and signed rank tests, chi-squared tests of independence, score + tests of particular hypotheses in generalized linear models, canonical correlation analysis and + linear discriminant analysis. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cctest + url_git: '' +cctools: + version: 0.1.2 + title: |- + Tools for the Continuous Convolution Trick in Nonparametric + Estimation + maintainer: Thomas Nagler + description: |- + Implements the uniform scaled beta distribution and + the continuous convolution kernel density estimator. + date_publication: '2019-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cctools + url_git: '' +CCWeights: + version: 0.1.6 + title: Perform Weighted Linear Regression for Calibration Curve + maintainer: Yonghui Dong + description: |- + Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. + In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements. + date_publication: '2021-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CCWeights + url_git: '' +cd: + version: 0.1.0 + title: CD Data for Entity Resolution + maintainer: Rebecca Steorts + description: Duplicated music data (pre-processed and formatted) for entity resolution. + The total size of the data set is 9763. There are respective gold standard records + that are labeled and can be considered as a unique identifier. + date_publication: '2020-10-22' + bug_reports: https://github.com/resteorts/cd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cd + url_git: https://github.com/resteorts/cd +cdata: + version: 1.2.1 + title: Fluid Data Transformations + maintainer: John Mount + description: |- + Supplies higher-order coordinatized data specification and fluid transform operators that include pivot and anti-pivot as special cases. + The methodology is describe in 'Zumel', 2018, "Fluid data reshaping with 'cdata'", , . + This package introduces the idea of explicit control table specification of data transforms. + Works on in-memory data or on remote data using 'rquery' and 'SQL' database interfaces. + date_publication: '2023-08-20' + bug_reports: https://github.com/WinVector/cdata/issues + url: https://winvector.github.io/cdata/ + url_cran: https://CRAN.R-project.org/package=cdata + url_git: https://github.com/WinVector/cdata/ +CDatanet: + version: 2.2.1 + title: Econometrics of Network Data + maintainer: Aristide Houndetoungan + description: Simulating and estimating peer effect models and network formation + models. The class of peer effect models includes linear-in-means models (Lee, + 2004; ), Tobit models (Xu and Lee, 2015; + ), and discrete numerical data models (Houndetoungan, + 2024; ). The network formation models include pair-wise + regressions with degree heterogeneity (Graham, 2017; ) + and exponential random graph models (Mele, 2017; ). + date_publication: '2025-01-07' + bug_reports: https://github.com/ahoundetoungan/CDatanet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CDatanet + url_git: https://github.com/ahoundetoungan/CDatanet +cdcatR: + version: 1.0.6 + title: Cognitive Diagnostic Computerized Adaptive Testing + maintainer: Miguel A. Sorrel + description: Provides a set of functions for conducting cognitive diagnostic computerized + adaptive testing applications (Chen, 2009) ). It + includes different item selection rules such us the global discrimination index + (Kaplan, de la Torre, and Barrada (2015) ) and the + nonparametric selection method (Chang, Chiu, and Tsai (2019) ), + as well as several stopping rules. Functions for generating item banks and responses + are also provided. To guide item bank calibration, model comparison at the item + level can be conducted using the two-step likelihood ratio test statistic by Sorrel, + de la Torre, Abad and Olea (2017) . + date_publication: '2022-05-25' + bug_reports: https://github.com/miguel-sorrel/cdcatR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdcatR + url_git: https://github.com/miguel-sorrel/cdcatR +CDCPLACES: + version: 1.1.9 + title: Access the 'CDC PLACES' API + maintainer: Brenden Smith + description: |- + Allows users to seamlessly query several 'CDC PLACES' APIs () + by geography, state, measure, and release year. This package also contains a + function to explore the available measures for each release year. + date_publication: '2025-02-10' + bug_reports: '' + url: https://brendensm.github.io/CDCPLACES/ + url_cran: https://CRAN.R-project.org/package=CDCPLACES + url_git: https://github.com/brendensm/CDCPLACES +cdcsis: + version: 2.0.5 + title: |- + Conditional Distance Correlation Based Feature Screening and + Conditional Independence Inference + maintainer: Canhong Wen + description: Conditional distance correlation + is a novel conditional dependence measurement of two multivariate random variables + given a confounding variable. This package provides conditional distance correlation, + performs the conditional distance correlation sure independence screening procedure + for ultrahigh dimensional data , + and conducts conditional distance covariance test for conditional independence + assumption of two multivariate variable. + date_publication: '2024-08-23' + bug_reports: https://github.com/Mamba413/cdcsis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdcsis + url_git: https://github.com/Mamba413/cdcsis +cder: + version: 0.3-1 + title: Interface to the California Data Exchange Center (CDEC) + maintainer: Michael Koohafkan + description: |- + Connect to the California Data Exchange Center (CDEC) + Web Service . 'CDEC' provides a centralized + database to store, process, and exchange real-time hydrologic information + gathered by various cooperators throughout California. The 'CDEC' Web Service + provides a data download + service for accessing historical records. + date_publication: '2023-02-22' + bug_reports: https://github.com/mkoohafkan/cder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cder + url_git: https://github.com/mkoohafkan/cder +cdfquantreg: + version: 1.3.1-2 + title: Quantile Regression for Random Variables on the Unit Interval + maintainer: Yiyun Shou + description: |- + Employs a two-parameter family of + distributions for modelling random variables on the (0, 1) interval by + applying the cumulative distribution function (cdf) of one parent + distribution to the quantile function of another. + date_publication: '2023-09-03' + bug_reports: https://ummlab.wordpress.com/resources/cdfquantreg-bugs-report/ + url: '' + url_cran: https://CRAN.R-project.org/package=cdfquantreg + url_git: '' +CDFt: + version: '1.2' + title: Downscaling and Bias Correction via Non-Parametric CDF-Transform + maintainer: Mathieu Vrac + description: 'Statistical downscaling and bias correction (model output statistics) + method based on cumulative distribution functions (CDF) transformation. See Michelangeli, + Vrac, Loukos (2009) Probabilistic downscaling approaches: Application to wind + cumulative distribution functions. Geophysical Research Letters, 36, L11708, . + ; and Vrac, Drobinski, Merlo, Herrmann, Lavaysse, Li, Somot (2012) Dynamical and + statistical downscaling of the French Mediterranean climate: uncertainty assessment. + Nat. Hazards Earth Syst. Sci., 12, 2769-2784, www.nat-hazards-earth-syst-sci.net/12/2769/2012/, + .' + date_publication: '2021-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CDFt + url_git: '' +cdgd: + version: 0.3.5 + title: Causal Decomposition of Group Disparities + maintainer: Ang Yu + description: |- + The framework of causal decomposition of group disparities developed by + Yu and Elwert (2023) + . + This package implements the decomposition estimators + that are based on efficient influence functions. For the + nuisance functions of the estimators, both parametric and + nonparametric options are provided, as well as manual options in case + the default models are not satisfying. + date_publication: '2024-04-15' + bug_reports: https://github.com/ang-yu/cdgd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdgd + url_git: https://github.com/ang-yu/cdgd +CDGHMM: + version: 0.1.1 + title: Hidden Markov Models for Multivariate Panel Data + maintainer: Mackenzie R. Neal + description: Estimates hidden Markov models from the family of Cholesky-decomposed + Gaussian hidden Markov models (CDGHMM) under various missingness schemes. This + family improves upon estimation of traditional Gaussian HMMs by introducing parsimony, + as well as, controlling for dropped out observations and non-random missingness. + See Neal, Sochaniwsky and McNicholas (2024) . + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CDGHMM + url_git: '' +cdid: + version: 0.1.1 + title: The Chained Difference-in-Differences + maintainer: David Benatia + description: Extends the 'did' package to improve efficiency and handling of unbalanced + panel data. Bellego, Benatia, and Dortet-Bernadet (2024), "The Chained Difference-in-Differences", + Journal of Econometrics, . + date_publication: '2025-01-27' + bug_reports: https://github.com/joelcuerrier/cdid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdid + url_git: https://github.com/joelcuerrier/cdid +cdlei: + version: '1.0' + title: Cause-Deleted Life Expectancy Improvement Procedure + maintainer: Alicja Wolny-Dominiak + description: The concept of cause-deleted life expectancy improvement is statistic + designed to quantify the increase in life expectancy if a certain cause of death + is removed. See Adamic, P. (2015) (). + date_publication: '2020-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cdlei + url_git: '' +cdlTools: + version: '1.13' + title: Tools to Download and Work with USDA Cropscape Data + maintainer: Jonathan Lisic + description: |- + Downloads USDA National Agricultural Statistics Service (NASS) + cropscape data for a specified state. Utilities for fips, abbreviation, + and name conversion are also provided. Full functionality requires an + internet connection, but data sets can be cached for later off-line use. + date_publication: '2024-03-23' + bug_reports: https://github.com/jlisic/cdlTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdlTools + url_git: https://github.com/jlisic/cdlTools +CDM: + version: 8.2-6 + title: Cognitive Diagnosis Modeling + maintainer: Alexander Robitzsch + description: |2- + + Functions for cognitive diagnosis modeling and multidimensional item response modeling + for dichotomous and polytomous item responses. This package enables the estimation of + the DINA and DINO model (Junker & Sijtsma, 2001, ), + the multiple group (polytomous) GDINA model (de la Torre, 2011, + ), the multiple choice DINA model (de la Torre, 2009, + ), the general diagnostic model (GDM; von Davier, 2008, + ), the structured latent class model (SLCA; Formann, 1992, + ) and regularized latent class analysis + (Chen, Li, Liu, & Ying, 2017, ). + See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) + or Robitzsch and George (2019, ) + for further details on estimation and the package structure. + For tutorials on how to use the CDM package see + George and Robitzsch (2015, ) as well as + Ravand and Robitzsch (2015). + date_publication: '2022-08-25' + bug_reports: https://github.com/alexanderrobitzsch/CDM/issues?state=open + url: https://sites.google.com/site/alexanderrobitzsch2/software + url_cran: https://CRAN.R-project.org/package=CDM + url_git: https://github.com/alexanderrobitzsch/CDM +CDMConnector: + version: 2.0.0 + title: Connect to an OMOP Common Data Model + maintainer: Adam Black + description: |- + Provides tools for working with observational health data in the + Observational Medical Outcomes Partnership (OMOP) Common Data Model format with a pipe friendly syntax. + Common data model database table references are stored in a single compound object along with metadata. + date_publication: '2025-02-22' + bug_reports: https://github.com/darwin-eu/CDMConnector/issues + url: https://darwin-eu.github.io/CDMConnector/ + url_cran: https://CRAN.R-project.org/package=CDMConnector + url_git: https://github.com/darwin-eu/CDMConnector +cdmTools: + version: 1.0.5 + title: Useful Tools for Cognitive Diagnosis Modeling + maintainer: Pablo Nájera + description: Provides useful tools for cognitive diagnosis modeling (CDM). The package + includes functions for empirical Q-matrix estimation and validation, such as the + Hull method (Nájera, Sorrel, de la Torre, & Abad, 2021, ) + and the discrete factor loading method (Wang, Song, & Ding, 2018, ). + It also contains dimensionality assessment procedures for CDM, including parallel + analysis and automated fit comparison as explored in Nájera, Abad, and Sorrel + (2021, ). Other relevant methods and features for + CDM applications, such as the restricted DINA model (Nájera et al., 2023; ), + the general nonparametric classification method (Chiu et al., 2018; ), + and corrected estimation of the classification accuracy via multiple imputation + (Kreitchmann et al., 2022; ) are also available. + Lastly, the package provides some useful functions for CDM simulation studies, + such as random Q-matrix generation and detection of complete/identified Q-matrices. + date_publication: '2024-01-08' + bug_reports: https://github.com/pablo-najera/cdmTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdmTools + url_git: https://github.com/pablo-najera/cdmTools +cdom: + version: 0.1.0 + title: R Functions to Model CDOM Spectra + maintainer: Philippe Massicotte + description: Wrapper functions to model and extract various quantitative information + from absorption spectra of chromophoric dissolved organic matter (CDOM). + date_publication: '2016-03-04' + bug_reports: https://github.com/PMassicotte/cdom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cdom + url_git: https://github.com/PMassicotte/cdom +cdparcoord: + version: 1.0.1 + title: Top Frequency-Based Parallel Coordinates + maintainer: Norm Matloff + description: |- + Parallel coordinate plotting with resolutions for large data sets + and missing values. + date_publication: '2019-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cdparcoord + url_git: '' +cdrcR: + version: 0.1.1 + title: Load 'CDRC' Data + maintainer: Alessia Calafiore + description: A wrapper for the 'CDRC' 'API' that returns data frames or 'sf' of + 'CDRC' data. The 'API' web reference is:. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cdrcR + url_git: '' +cds: + version: 1.0.3 + title: Constrained Dual Scaling for Detecting Response Styles + maintainer: Pieter Schoonees + description: |- + This is an implementation of constrained dual scaling for + detecting response styles in categorical data, including utility functions. The + procedure involves adding additional columns to the data matrix representing the + boundaries between the rating categories. The resulting matrix is then doubled + and analyzed by dual scaling. One-dimensional solutions are sought which provide + optimal scores for the rating categories. These optimal scores are constrained + to follow monotone quadratic splines. Clusters are introduced within which the + response styles can vary. The type of response style present in a cluster can + be diagnosed from the optimal scores for said cluster, and this can be used to + construct an imputed version of the data set which adjusts for response styles. + date_publication: '2016-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cds + url_git: '' +CDsampling: + version: 0.1.4 + title: '''CDsampling'': Constraint Sampling in Paid Research Studies' + maintainer: Yifei Huang + description: In the context of paid research studies and clinical trials, budget + considerations and patient sampling from available populations are subject to + inherent constraints. We introduce the 'CDsampling' package, which integrates + optimal design theories within the framework of constrained sampling. This package + offers the possibility to find both D-optimal approximate and exact allocations + for samplings with or without constraints. Additionally, it provides functions + to find constrained uniform sampling as a robust sampling strategy with limited + model information. Our package offers functions for the computation of the Fisher + information matrix under generalized linear models (including regular linear regression + model) and multinomial logistic models.To demonstrate the applications, we also + provide a simulated dataset and a real dataset embedded in the package. Yifei + Huang, Liping Tong, and Jie Yang (2025). + date_publication: '2025-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CDsampling + url_git: '' +CDSE: + version: 0.2.1 + title: '''Copernicus Data Space Ecosystem'' API Wrapper' + maintainer: Zivan Karaman + description: |- + Provides interface to the 'Copernicus Data Space Ecosystem' API + , mainly for searching the catalog of available + data from Copernicus Sentinel missions and obtaining the images for just the area of interest + based on selected spectral bands. The package uses the 'Sentinel Hub' REST API interface + that provides access to various + satellite imagery archives. It allows you to access raw satellite data, rendered images, + statistical analysis, and other features. + This package is in no way officially related to or endorsed by Copernicus. + date_publication: '2024-08-31' + bug_reports: https://github.com/zivankaraman/CDSE/issues + url: https://zivankaraman.github.io/CDSE/ + url_cran: https://CRAN.R-project.org/package=CDSE + url_git: https://github.com/zivankaraman/CDSE +CDSS: + version: 0.2-0 + title: Course-Dependent Skill Structures + maintainer: Cord Hockemeyer + description: |- + Deriving skill structures from skill assignment + data for courses (sets of learning objects). + date_publication: '2023-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CDSS + url_git: '' +CDVI: + version: 0.1.0 + title: |- + Cuddy-Della Valle Index for Capturing the Instability in Time + Series Data + maintainer: Dr. S. Vishnu Shankar + description: Cuddy-Della valle index gives the degree of instability present in + the data by accommodating the effect of a trend. The adjusted R squared value + of the best fitted model is chosen. The index is obtained by multiplying the coefficient + of variation with square root of one minus the adjusted R-squared value. This + package has been developed using concept of Shankar et al. (2022). + date_publication: '2024-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CDVI + url_git: '' +CDVineCopulaConditional: + version: 0.1.1 + title: Sampling from Conditional C- and D-Vine Copulas + maintainer: Emanuele Bevacqua + description: |- + Provides tools for sampling from a conditional copula density decomposed via + Pair-Copula Constructions as C- or D- vine. Here, the vines which can be used for such a + sampling are those which sample as first the conditioning variables (when following the + sampling algorithms shown in Aas et al. (2009) ). + The used sampling algorithm is presented and discussed in Bevacqua et al. (2017) + , and it is a modified version of that from Aas et al. (2009) + . A function is available to select the best vine + (based on information criteria) among those which allow for such a conditional sampling. + The package includes a function to compare scatterplot matrices and pair-dependencies of + two multivariate datasets. + date_publication: '2017-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CDVineCopulaConditional + url_git: '' +ceas: + version: 1.3.0 + title: Cellular Energetics Analysis Software + maintainer: Rachel House + description: |- + Measuring cellular energetics is essential to understanding a + matrix’s (e.g. cell, tissue or biofluid) metabolic state. The Agilent + Seahorse machine is a common method to measure real-time cellular + energetics, but existing analysis tools are highly manual or lack + functionality. The Cellular Energetics Analysis Software (ceas) R package + fills this analytical gap by providing modular and automated Seahorse data + analysis and visualization using the methods described by Mookerjee et al. + (2017) . + date_publication: '2024-12-21' + bug_reports: https://github.com/jamespeapen/ceas/issues/ + url: https://jamespeapen.github.io/ceas/ + url_cran: https://CRAN.R-project.org/package=ceas + url_git: https://github.com/jamespeapen/ceas/ +CEC: + version: 0.11.2 + title: Cross-Entropy Clustering + maintainer: Simon Garnier + description: |- + Splits data into Gaussian type clusters using the Cross-Entropy + Clustering ('CEC') method. This method allows for the simultaneous use of + various types of Gaussian mixture models, for performing the reduction of + unnecessary clusters, and for discovering new clusters by splitting them. + 'CEC' is based on the work of Spurek, P. and Tabor, J. (2014) + . + date_publication: '2024-10-10' + bug_reports: '' + url: https://swarm-lab.github.io/cec/ + url_cran: https://CRAN.R-project.org/package=CEC + url_git: https://github.com/swarm-lab/cec +CEDA: + version: 1.1.1 + title: CRISPR Screen and Gene Expression Differential Analysis + maintainer: Lianbo Yu + description: |- + Provides analytical methods for analyzing CRISPR screen data + at different levels of gene expression. Multi-component normal mixture models + and EM algorithms are used for modeling. + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CEDA + url_git: '' +CEEMDANML: + version: 0.1.0 + title: CEEMDAN Decomposition Based Hybrid Machine Learning Models + maintainer: Mr. Sandip Garai + description: Noise in the time-series data significantly affects the accuracy of + the Machine Learning (ML) models (Artificial Neural Network and Support Vector + Regression are considered here). Complete Ensemble Empirical Mode Decomposition + with Adaptive Noise (CEEMDAN) decomposes the time series data into sub-series + and help to improve the model performance. The models can achieve higher prediction + accuracy than the traditional ML models. Two models have been provided here for + time series forecasting. More information may be obtained from Garai and Paul + (2023) . + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CEEMDANML + url_git: '' +ceg: + version: 0.1.0 + title: Chain Event Graph + maintainer: Pier Taranti + description: |- + Create and learn Chain Event Graph (CEG) models using a Bayesian + framework. It provides us with a Hierarchical Agglomerative algorithm to + search the CEG model space. + The package also includes several facilities for visualisations of the + objects associated with a CEG. The CEG class can represent a range of + relational data types, and supports arbitrary vertex, edge and graph + attributes. A Chain Event Graph is a tree-based graphical model that + provides a powerful graphical interface through which domain experts can + easily translate a process into sequences of observed events using plain + language. CEGs have been a useful class of graphical model especially to + capture context-specific conditional independences. References: Collazo R, + Gorgen C, Smith J. Chain Event Graph. CRC Press, ISBN 9781498729604, 2018 + (forthcoming); and Barday LM, Collazo RA, Smith JQ, Thwaites PA, Nicholson AE. + The Dynamic Chain Event Graph. Electronic Journal of Statistics, 9 (2) 2130-2169 + . + date_publication: '2017-11-27' + bug_reports: https://github.com/ptaranti/ceg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ceg + url_git: https://github.com/ptaranti/ceg +CEGO: + version: 2.4.4 + title: Combinatorial Efficient Global Optimization + maintainer: Martin Zaefferer + description: |- + Model building, surrogate model + based optimization and Efficient Global Optimization in combinatorial + or mixed search spaces. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CEGO + url_git: '' +celestial: + version: 1.4.6 + title: |- + Collection of Common Astronomical Conversion Routines and + Functions + maintainer: Aaron Robotham + description: Contains a number of common astronomy conversion routines, particularly + the HMS and degrees schemes, which can be fiddly to convert between on mass due + to the textural nature of the former. It allows users to coordinate match datasets + quickly. It also contains functions for various cosmological calculations. + date_publication: '2018-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=celestial + url_git: '' +cellKey: + version: 1.0.2 + title: |- + Consistent Perturbation of Statistical Frequency- And Magnitude + Tables + maintainer: Bernhard Meindl + description: |- + Data from statistical agencies and other institutions often + need to be protected before they can be published. This package + can be used to perturb statistical tables in a consistent way. The + main idea is to add - at the micro data level - a record key for each + unit. Based on these keys, for any cell in a statistical table a + cell key is computed as a function on the record keys contributing to + a specific cell. Values that are added to the cell in order to perturb + it are derived from a lookup-table that maps values of cell keys to + specific perturbation values. The theoretical basis for the methods + implemented can be found in Thompson, Broadfoot and Elazar + (2013) + which was extended and enhanced by Giessing and Tent + (2019) . + date_publication: '2023-11-24' + bug_reports: https://github.com/sdcTools/userSupport/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cellKey + url_git: https://github.com/sdcTools/cellKey +cellOrigins: + version: 0.1.3 + title: Finds RNASeq Source Tissues Using In Situ Hybridisation Data + maintainer: David Molnar + description: Finds the most likely originating tissue(s) and developmental stage(s) + of tissue-specific RNA sequencing data. The package identifies both pure transcriptomes + and mixtures of transcriptomes. The most likely identity is found through comparisons + of the sequencing data with high-throughput in situ hybridisation patterns. Typical + uses are the identification of cancer cell origins, validation of cell culture + strain identities, validation of single-cell transcriptomes, and validation of + identity and purity of flow-sorting and dissection sequencing products. + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cellOrigins + url_git: '' +cellpypes: + version: 0.3.0 + title: Cell Type Pipes for Single-Cell RNA Sequencing Data + maintainer: Felix Frauhammer + description: |- + Annotate single-cell RNA sequencing data manually based on + marker gene thresholds. + Find cell type rules (gene+threshold) through exploration, + use the popular piping operator '%>%' to reconstruct complex + cell type hierarchies. + 'cellpypes' models technical noise to find positive and negative cells for + a given expression threshold and returns cell type labels or pseudobulks. + Cite this package as Frauhammer (2022) and + visit for tutorials and newest + features. + date_publication: '2024-01-27' + bug_reports: https://github.com/FelixTheStudent/cellpypes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cellpypes + url_git: https://github.com/FelixTheStudent/cellpypes +cellranger: + version: 1.1.0 + title: Translate Spreadsheet Cell Ranges to Rows and Columns + maintainer: Jennifer Bryan + description: |- + Helper functions to work with spreadsheets and the "A1:D10" style + of cell range specification. + date_publication: '2016-07-27' + bug_reports: https://github.com/rsheets/cellranger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cellranger + url_git: https://github.com/rsheets/cellranger +celltrackR: + version: 1.2.1 + title: Motion Trajectory Analysis + maintainer: Johannes Textor + description: |- + Methods for analyzing (cell) motion in two or three dimensions. + Available measures include displacement, confinement ratio, autocorrelation, + straightness, turning angle, and fractal dimension. Measures can be applied to entire tracks, + steps, or subtracks with varying length. While the methodology has been developed for + cell trajectory analysis, it is applicable to anything that moves including animals, + people, or vehicles. + Some of the methodology implemented in this packages was described by: + Beauchemin, Dixit, and Perelson (2007) , + Beltman, Maree, and de Boer (2009) , + Gneiting and Schlather (2004) , + Mokhtari, Mech, Zitzmann, Hasenberg, Gunzer, and Figge (2013) , + Moreau, Lemaitre, Terriac, Azar, Piel, Lennon-Dumenil, and Bousso (2012) , + Textor, Peixoto, Henrickson, Sinn, von Andrian, and Westermann (2011) , + Textor, Sinn, and de Boer (2013) , + Textor, Henrickson, Mandl, von Andrian, Westermann, de Boer, and Beltman (2014) . + date_publication: '2024-08-26' + bug_reports: '' + url: http://www.motilitylab.net + url_cran: https://CRAN.R-project.org/package=celltrackR + url_git: '' +cellularautomata: + version: 0.1.0 + title: Cellular Automata + maintainer: Vlad Tarko + description: |- + Create cellular automata from 'Wolfram' rules. Allows the creation + of 'Wolfram' style plots, as well as of animations. Easy to create multiple + plots, for example the output of a rule with different initial states, + or the output of many different rules from the same state. The output + of a cellular automaton is given as a matrix, making it easy to try to + explore the possibility of predicting its time evolution using various + statistical tools available in R. + Wolfram S. (2002, ISBN:1579550088) "A New Kind of Science". + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cellularautomata + url_git: '' +cellVolumeDist: + version: '1.4' + title: |- + Functions to Fit Cell Volume Distributions and Thereby Estimate + Cell Growth Rates and Division Times + maintainer: Katharine M. Mullen + description: |- + Implements a methodology for using cell volume + distributions to estimate cell growth rates and division times + that is described in the paper entitled, "Cell Volume + Distributions Reveal Cell Growth Rates and Division Times", by + Michael Halter, John T. Elliott, Joseph B. Hubbard, Alessandro + Tona and Anne L. Plant, which is in press in the Journal of + Theoretical Biology. In order to reproduce the analysis used + to obtain Table 1 in the paper, execute the command + "example(fitVolDist)". + date_publication: '2022-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cellVolumeDist + url_git: '' +cellWise: + version: 2.5.3 + title: Analyzing Data with Cellwise Outliers + maintainer: Jakob Raymaekers + description: |- + Tools for detecting cellwise outliers and robust methods to analyze + data which may contain them. Contains the implementation of the algorithms described in + Rousseeuw and Van den Bossche (2018) (open access) + Hubert et al. (2019) (open access), + Raymaekers and Rousseeuw (2021) (open access), + Raymaekers and Rousseeuw (2021) (open access), + Raymaekers and Rousseeuw (2021) (open access), + Raymaekers and Rousseeuw (2022) (open access) + Rousseeuw (2022) (open access). + Examples can be found in the vignettes: + "DDC_examples", "MacroPCA_examples", "wrap_examples", "transfo_examples", + "DI_examples", "cellMCD_examples" , "Correspondence_analysis_examples", + and "cellwise_weights_examples". + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cellWise + url_git: '' +cem: + version: 1.1.31 + title: Coarsened Exact Matching + maintainer: Stefano M. Iacus + description: |- + Implementation of the Coarsened Exact Matching algorithm discussed + along with its properties in + Iacus, King, Porro (2011) ; + Iacus, King, Porro (2012) and + Iacus, King, Porro (2019) . + date_publication: '2022-09-08' + bug_reports: '' + url: https://gking.harvard.edu/cem + url_cran: https://CRAN.R-project.org/package=cem + url_git: '' +cemco: + version: '0.2' + title: Fit 'CemCO' Algorithm + maintainer: Andre Fujita + description: '''CemCO'' algorithm, a model-based (Gaussian) clustering algorithm + that removes/minimizes the effects of undesirable covariates during the clustering + process both in cluster centroids and in cluster covariance structures (Relvas + C. & Fujita A., (2020) ).' + date_publication: '2023-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cemco + url_git: '' +CenBAR: + version: 0.1.1 + title: Broken Adaptive Ridge AFT Model with Censored Data + maintainer: Zhihua Sun + description: |- + Broken adaptive ridge estimator for censored data is used to + select variables and estimate their coefficients in the semi-parametric + accelerated failure time model for right-censored survival data. + date_publication: '2020-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CenBAR + url_git: '' +cencrne: + version: 1.0.0 + title: |- + Consistent Estimation of the Number of Communities via + Regularized Network Embedding + maintainer: Mingyang Ren + description: |- + The network analysis plays an important role in numerous application domains including biomedicine. + Estimation of the number of communities is a fundamental and critical issue in network analysis. Most existing studies assume that the number of communities is known a priori, or lack of rigorous theoretical guarantee on the estimation consistency. This method proposes a regularized network embedding model to simultaneously estimate the community structure and the number of communities in a unified formulation. + The proposed model equips network embedding with a novel composite regularization term, which pushes the embedding vector towards its center and collapses similar community centers with each other. A rigorous theoretical analysis is conducted, establishing asymptotic consistency in terms of community detection and estimation of the number of communities. + Reference: + Ren, M., Zhang S. and Wang J. (2022). "Consistent Estimation of the Number of Communities via Regularized Network Embedding". Biometrics, . + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cencrne + url_git: '' +cenGAM: + version: 0.5.3 + title: Censored Regression with Smooth Terms + maintainer: Zhou Fang + description: Implementation of Tobit type I and type II families for censored regression + using the 'mgcv' package, based on methods detailed in Woods (2016) . + date_publication: '2017-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cenGAM + url_git: '' +cenROC: + version: 2.0.0 + title: Estimating Time-Dependent ROC Curve and AUC for Censored Data + maintainer: Kassu Mehari Beyene + description: |- + Contains functions to estimate a smoothed and a non-smoothed (empirical) time-dependent + receiver operating characteristic curve and the corresponding area under the receiver + operating characteristic curve and the optimal cutoff point for the right and interval + censored survival data. See Beyene and El Ghouch (2020) and Beyene + and El Ghouch (2022) . + date_publication: '2023-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cenROC + url_git: '' +censable: + version: 0.0.5 + title: Making Census Data More Usable + maintainer: Christopher T. Kenny + description: |- + Creates a common framework for organizing, naming, and gathering + population, age, race, and ethnicity data from the Census Bureau. Accesses + the API . Provides + tools for adding information to existing data to line up with Census data. + date_publication: '2022-11-19' + bug_reports: https://github.com/christopherkenny/censable/issues + url: https://christophertkenny.com/censable/ + url_cran: https://CRAN.R-project.org/package=censable + url_git: https://github.com/christopherkenny/censable +censCov: + version: 1.0-0 + title: Linear Regression with a Randomly Censored Covariate + maintainer: Sy Han (Steven) Chiou + description: |- + Implementations of threshold regression approaches for linear + regression models with a covariate subject to random censoring, + including deletion threshold regression and completion threshold regression. + Reverse survival regression, which flip the role of response variable and the + covariate, is also considered. + date_publication: '2017-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=censCov + url_git: '' +CensMFM: + version: '3.1' + title: Finite Mixture of Multivariate Censored/Missing Data + maintainer: Francisco H. C. de Alencar + description: It fits finite mixture models for censored or/and missing data using + several multivariate distributions. Point estimation and asymptotic inference + (via empirical information matrix) are offered as well as censored data generation. + Pairwise scatter and contour plots can be generated. Possible multivariate distributions + are the well-known normal, Student-t and skew-normal distributions. This package + is an complement of Lachos, V. H., Moreno, E. J. L., Chen, K. & Cabral, C. R. + B. (2017) for the multivariate skew-normal case. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CensMFM + url_git: '' +censo2017: + version: 0.6.2 + title: |- + Base de Datos de Facil Acceso del Censo 2017 de Chile (2017 + Chilean Census Easy Access Database) + maintainer: Mauricio Vargas + description: |- + Provee un acceso conveniente a mas de 17 millones de registros + de la base de datos del Censo 2017. Los datos fueron importados desde + el DVD oficial del INE usando el Convertidor REDATAM creado por Pablo De + Grande. Esta paquete esta documentado intencionalmente en castellano + asciificado para que funcione sin problema en diferentes plataformas. + (Provides convenient access to more than 17 million records from the + Chilean Census 2017 database. The datasets were imported from the official + DVD provided by the Chilean National Bureau of Statistics by using the + REDATAM converter created by Pablo De Grande and in addition it includes the + maps accompanying these datasets.) + date_publication: '2023-04-25' + bug_reports: https://github.com/ropensci/censo2017/issues/ + url: https://docs.ropensci.org/censo2017/ + url_cran: https://CRAN.R-project.org/package=censo2017 + url_git: '' +censobr: + version: 0.4.1 + title: Download Data from Brazil's Population Census + maintainer: Rafael H. M. Pereira + description: |- + Easy access to data from Brazil's population censuses. The package + provides a simple and efficient way to download and read the data + sets and the documentation of all the population censuses taken in + and after 1960 in the country. The package is built on top of the + 'Arrow' platform , which allows + users to work with larger-than-memory census data using 'dplyr' + familiar functions. . + date_publication: '2025-02-28' + bug_reports: https://github.com/ipeaGIT/censobr/issues + url: https://ipeagit.github.io/censobr/ + url_cran: https://CRAN.R-project.org/package=censobr + url_git: https://github.com/ipeaGIT/censobr +censorcopula: + version: '2.0' + title: Estimate Parameter of Bivariate Copula + maintainer: Yan Li + description: |- + Implement an interval censor method + to break ties when using data with ties to fitting a + bivariate copula. + date_publication: '2016-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=censorcopula + url_git: '' +censored: + version: 0.3.3 + title: '''parsnip'' Engines for Survival Models' + maintainer: Hannah Frick + description: |- + Engines for survival models from the 'parsnip' package. These + include parametric models (e.g., Jackson (2016) + ), semi-parametric (e.g., Simon et al + (2011) ), and tree-based models (e.g., + Buehlmann and Hothorn (2007) ). + date_publication: '2025-02-14' + bug_reports: https://github.com/tidymodels/censored/issues + url: https://censored.tidymodels.org + url_cran: https://CRAN.R-project.org/package=censored + url_git: https://github.com/tidymodels/censored +censReg: + version: 0.5-38 + title: Censored Regression (Tobit) Models + maintainer: Arne Henningsen + description: |- + Maximum Likelihood estimation of censored regression (Tobit) models + with cross-sectional and panel data. + date_publication: '2024-05-20' + bug_reports: https://r-forge.r-project.org/projects/sampleselection/ + url: http://www.sampleSelection.org + url_cran: https://CRAN.R-project.org/package=censReg + url_git: '' +CensSpatial: + version: '3.6' + title: Censored Spatial Models + maintainer: Alejandro Ordonez + description: It fits linear regression models for censored spatial data. It provides + different estimation methods as the SAEM (Stochastic Approximation of Expectation + Maximization) algorithm and seminaive that uses Kriging prediction to estimate + the response at censored locations and predict new values at unknown locations. + It also offers graphical tools for assessing the fitted model. More details can + be found in Ordonez et al. (2018) . + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CensSpatial + url_git: '' +Census2016: + version: 0.2.0 + title: Data from the Australian Census 2016 + maintainer: Hugh Parsonage + description: Contains selected variables from the time series profiles for statistical + areas level 2 from the 2006, 2011, and 2016 censuses of population and housing, + Australia. Also provides methods for viewing the questions asked for convenience + during analysis. + date_publication: '2017-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Census2016 + url_git: '' +censusapi: + version: 0.8.0 + title: Retrieve Data from the Census APIs + maintainer: Hannah Recht + description: |- + A wrapper for the U.S. Census Bureau APIs that returns data frames of + Census data and metadata. Available datasets include the + Decennial Census, American Community Survey, Small Area Health Insurance Estimates, + Small Area Income and Poverty Estimates, Population Estimates and Projections, and more. + date_publication: '2022-08-09' + bug_reports: https://github.com/hrecht/censusapi/issues + url: https://www.hrecht.com/censusapi/ + url_cran: https://CRAN.R-project.org/package=censusapi + url_git: https://github.com/hrecht/censusapi +censusr: + version: 0.0.4 + title: Collect Data from the Census API + maintainer: Greg Macfarlane + description: |- + Use the US Census API to collect summary data tables + for SF1 and ACS datasets at arbitrary geographies. + date_publication: '2018-01-25' + bug_reports: https://github.com/transportfoundry/censusr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=censusr + url_git: https://github.com/transportfoundry/censusr +centerline: + version: '0.1' + title: Extract Centerline from Closed Polygons + maintainer: Anatoly Tsyplenkov + description: |- + Generates skeletons of closed 2D polygons using Voronoi diagrams. + It provides methods for 'sf', 'terra', and 'geos' objects to + compute polygon centerlines based on the generated skeletons. + Voronoi, G. (1908) . + date_publication: '2024-09-26' + bug_reports: https://github.com/atsyplenkov/centerline/issues + url: '' + url_cran: https://CRAN.R-project.org/package=centerline + url_git: https://github.com/atsyplenkov/centerline +centiserve: + version: 1.0.0 + title: Find Graph Centrality Indices + maintainer: Mahdi Jalili + description: Calculates centrality indices additional to the 'igraph' package centrality + functions. + date_publication: '2017-07-15' + bug_reports: http://www.centiserver.org/?q1=contact + url: http://www.centiserver.org/ + url_cran: https://CRAN.R-project.org/package=centiserve + url_git: '' +centr: + version: 0.2.2 + title: Weighted and Unweighted Spatial Centers + maintainer: Ryan Zomorrodi + description: |- + Generate mean and median weighted or unweighted spatial centers. + Functions are analogous to their identically named counterparts within + 'ArcGIS Pro'. Median center methodology based off of Kuhn and Kuenne + (1962) . + date_publication: '2025-02-07' + bug_reports: https://github.com/ryanzomorrodi/centR/issues + url: https://ryanzomorrodi.github.io/centr/ + url_cran: https://CRAN.R-project.org/package=centr + url_git: https://github.com/ryanzomorrodi/centR +centrifugeR: + version: 0.1.7 + title: Non-Trivial Balance of Centrifuge Rotors + maintainer: Duy Nghia Pham + description: |- + Find the numbers of test tubes that can be balanced in centrifuge + rotors and show various ways to load them. Refer to Pham (2020) + for more information on package functionality. + date_publication: '2022-12-15' + bug_reports: https://github.com/phamdn/centrifugeR/issues + url: https://phamdn.shinyapps.io/centrifugeR/ + url_cran: https://CRAN.R-project.org/package=centrifugeR + url_git: '' +CEOdata: + version: 1.3.1.1 + title: |- + Datasets of the CEO (Centre d'Estudis d'Opinio) for Opinion + Polls in Catalonia + maintainer: Xavier Fernández-i-Marín + description: |- + Easy and convenient access to the datasets of the + "Centre d'Estudis d'Opinio", the Catalan institution for polling and public + opinion. The package uses the data stored in the servers of the CEO and returns + it in a tidy format. + date_publication: '2023-07-06' + bug_reports: https://github.com/ceopinio/CEOdata/issues/ + url: https://ceo.gencat.cat/ca/inici/ + url_cran: https://CRAN.R-project.org/package=CEOdata + url_git: https://github.com/ceopinio/CEOdata/ +CEoptim: + version: '1.3' + title: Cross-Entropy R Package for Optimization + maintainer: Benoit Liquet + description: Optimization solver based on the Cross-Entropy method. + date_publication: '2023-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CEoptim + url_git: '' +CePa: + version: 0.8.1 + title: Centrality-Based Pathway Enrichment + maintainer: Zuguang Gu + description: |- + It aims to find significant pathways through + network topology information. It has several advantages compared + with current pathway enrichment tools. First, pathway node instead + of single gene is taken as the basic unit when analysing networks + to meet the fact that genes must be constructed into complexes to + hold normal functions. Second, multiple network centrality measures are + applied simultaneously to measure importance of nodes from different + aspects to make a full view on the biological system. CePa extends + standard pathway enrichment methods, which include both over-representation + analysis procedure and gene-set analysis procedure. + . + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CePa + url_git: https://github.com/jokergoo/CePa +cepiigeodist: + version: '0.1' + title: CEPII's GeoDist Datasets + maintainer: Mauricio Vargas + description: |- + Provides data on countries and their main city or agglomeration and + the different distance measures and dummy variables indicating whether two + countries are contiguous, share a common language or a colonial + relationship. The reference article for these datasets is Mayer and Zignago + (2011) . + date_publication: '2020-09-18' + bug_reports: https://github.com/pachamaltese/cepiigeodist/issues/ + url: https://pacha.dev/cepiigeodist/ + url_cran: https://CRAN.R-project.org/package=cepiigeodist + url_git: '' +cepp: + version: '1.7' + title: Context Driven Exploratory Projection Pursuit + maintainer: Mohit Dayal + description: Functions and Data to support Context Driven Exploratory Projection + Pursuit. + date_publication: '2016-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cepp + url_git: '' +cepR: + version: 0.1.2 + title: Busca CEPs Brasileiros + maintainer: Robert Myles McDonnell + description: |2- + + Retorna detalhes de dados de CEPs brasileiros, bairros, logradouros + e tal. (Returns info of Brazilian postal codes, city names, addresses + and so on.) + date_publication: '2020-09-19' + bug_reports: https://github.com/RobertMyles/cepR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cepR + url_git: https://github.com/RobertMyles/cepR +cepreader: + version: 1.2-2 + title: Read 'CEP' and Legacy 'CANOCO' Files + maintainer: Jari Oksanen + description: |- + Read Condensed Cornell Ecology Program ('CEP') and legacy + 'CANOCO' files into R data frames. + date_publication: '2023-06-25' + bug_reports: https://github.com/vegandevs/cepreader/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cepreader + url_git: https://github.com/vegandevs/cepreader/ +cepumd: + version: 2.1.0 + title: Calculate Consumer Expenditure Survey (CE) Annual Estimates + maintainer: Arcenis Rojas + description: |- + Provides functions and data files to help CE Public-Use + Microdata (PUMD) users calculate annual estimated expenditure means, + standard errors, and quantiles according to the methods used by the CE with + PUMD. For more information on the CE please visit . + For further reading on CE estimate calculations please see the CE + Calculation section of the U.S. Bureau of Labor Statistics (BLS) Handbook of + Methods at . For + further information about CE PUMD please visit + . + date_publication: '2024-03-18' + bug_reports: https://github.com/arcenis-r/cepumd/issues + url: https://arcenis-r.github.io/cepumd/ + url_cran: https://CRAN.R-project.org/package=cepumd + url_git: https://github.com/arcenis-r/cepumd +cequre: + version: '1.5' + title: Censored Quantile Regression & Monotonicity-Respecting Restoring + maintainer: Yijian Huang + description: Perform censored quantile regression of Huang (2010) , + and restore monotonicity respecting via adaptive interpolation for dynamic regression + of Huang (2017) . The monotonicity-respecting + restoration applies to general dynamic regression models including (uncensored + or censored) quantile regression model, additive hazards model, and dynamic survival + models of Peng and Huang (2007) , among others. + date_publication: '2023-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cequre + url_git: '' +ceramic: + version: 0.9.5 + title: Download Online Imagery Tiles + maintainer: Michael Sumner + description: |- + Download imagery tiles to a standard cache and load the data into raster objects. + Facilities for 'AWS' terrain terrain and 'Mapbox' + servers are provided. + date_publication: '2024-02-27' + bug_reports: https://github.com/hypertidy/ceramic/issues + url: https://hypertidy.github.io/ceramic/ + url_cran: https://CRAN.R-project.org/package=ceramic + url_git: '' +cercospoRa: + version: 0.0.1 + title: |- + Process Based Epidemiological Model for Cercospora Leaf Spot of + Sugar Beet + maintainer: Paul Melloy + description: |- + Estimates sugar beet canopy closure with remotely sensed leaf area + index and estimates when action might be needed to protect the crop from a + Leaf Spot epidemic with a negative prognosis model based on published + models. + date_publication: '2024-12-13' + bug_reports: https://github.com/PaulMelloy/cercospoRa/issues + url: https://paul.melloy.com.au/cercospoRa/ + url_cran: https://CRAN.R-project.org/package=cercospoRa + url_git: https://github.com/PaulMelloy/cercospoRa +cereal: + version: 0.1.0 + title: Serialize 'vctrs' Objects to 'JSON' + maintainer: Julia Silge + description: |- + The 'vctrs' package provides a concept of vector prototype + that can be especially useful when deploying models and code. Serialize + these object prototypes to 'JSON' so they can be used to check and coerce + data in production systems, and deserialize 'JSON' back to the correct + object prototypes. + date_publication: '2023-06-09' + bug_reports: https://github.com/r-lib/cereal/issues + url: https://r-lib.github.io/cereal/ + url_cran: https://CRAN.R-project.org/package=cereal + url_git: https://github.com/r-lib/cereal/ +CERFIT: + version: 0.1.0 + title: Causal Effect Random Forest of Interaction Tress + maintainer: Justin Thorp + description: Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which + is a modification of the Random Forest algorithm where each split is chosen to + maximize subgroup treatment heterogeneity. Doing this allows it to estimate the + individualized treatment effect for each observation in either randomized controlled + trial (RCT) or observational data. For more information see X. Su, A. T. Peña, + L. Liu, and R. A. Levine (2018) . + date_publication: '2022-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CERFIT + url_git: '' +CerioliOutlierDetection: + version: 1.1.15 + title: |- + Outlier Detection Using the Iterated RMCD Method of Cerioli + (2010) + maintainer: Christopher G. Green + description: |- + Implements the iterated RMCD method of Cerioli (2010) + for multivariate outlier detection via robust Mahalanobis distances. Also + provides the finite-sample RMCD method discussed in the paper, as well as + the methods provided in Hardin and Rocke (2005) + and Green and Martin (2017) . + See also Chapter 2 of Green (2017) . + date_publication: '2024-06-23' + bug_reports: '' + url: https://christopherggreen.github.io/CerioliOutlierDetection/ + url_cran: https://CRAN.R-project.org/package=CerioliOutlierDetection + url_git: '' +CeRNASeek: + version: 2.1.3 + title: Identification and Analysis of ceRNA Regulation + maintainer: Mengying Zhang + description: |- + Provides several functions to identify and analyse miRNA sponge, including + popular methods for identifying miRNA sponge interactions, two types + of global ceRNA regulation prediction methods and four types of context-specific + prediction methods( Li Y et al.(2017) ), which are based + on miRNA-messenger RNA regulation alone, or by integrating heterogeneous data, + respectively. In addition, For predictive ceRNA relationship pairs, this package + provides several downstream analysis algorithms, including regulatory network + analysis and functional annotation analysis, as well as survival prognosis analysis + based on expression of ceRNA ternary pair. + date_publication: '2020-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CeRNASeek + url_git: '' +ceRtainty: + version: 1.0.0 + title: Certainty Equivalent + maintainer: Ariel Soto-Caro + description: |- + Compute the certainty equivalents and premium risks + as tools for risk-efficiency analysis. For more technical information, please refer to: Hardaker, Richardson, Lien, & Schumann (2004) , and Richardson, & Outlaw (2008) . + date_publication: '2019-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ceRtainty + url_git: '' +Certara.NLME8: + version: 3.0.1 + title: Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine + maintainer: James Craig + description: |- + Perform Nonlinear Mixed-Effects (NLME) Modeling using Certara's + NLME-Engine. Access the same Maximum Likelihood engines used in the Phoenix + platform, including algorithms for parametric methods, individual, and pooled + data analysis . + The Quasi-Random Parametric Expectation-Maximization Method (QRPEM) is also + supported . Execution + is supported both locally or on remote machines. Remote execution includes + support for Linux Sun Grid Engine (SGE), Terascale Open-source Resource and + Queue Manager (TORQUE) grids, Linux and Windows multicore, and individual runs. + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Certara.NLME8 + url_git: '' +Certara.R: + version: 1.1.0 + title: |- + Easily Install Pharmacometric Packages and Shiny Applications + Developed by Certara + maintainer: James Craig + description: |- + A convenient set of wrapper functions to install + pharmacometric packages and Shiny applications developed by Certara + PMX and Integrated Drug Development (iDD). The functions ensure the + successful installation of packages from non-standard repositories. + date_publication: '2023-12-14' + bug_reports: https://github.com/certara/R-Certara/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Certara.R + url_git: https://github.com/certara/R-Certara +Certara.RDarwin: + version: 1.1.1 + title: |- + Interface for 'pyDarwin' Machine Learning Pharmacometric Model + Development + maintainer: James Craig + description: |- + Utilities that support the usage of 'pyDarwin' () for ease of setup + and execution of a machine learning based pharmacometric model search with Certara's Non-Linear Mixed Effects (NLME) + modeling engine. + date_publication: '2025-02-25' + bug_reports: '' + url: https://certara.github.io/R-Darwin/ + url_cran: https://CRAN.R-project.org/package=Certara.RDarwin + url_git: '' +Certara.RsNLME: + version: 3.0.1 + title: Pharmacometric Modeling + maintainer: James Craig + description: |- + Facilitate Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling + and simulation with powerful tools for Nonlinear Mixed-Effects (NLME) + modeling. The package provides access to the same advanced Maximum Likelihood + algorithms used by the NLME-Engine in the Phoenix platform. These tools support + a range of analyses, from parametric methods to individual and pooled data + analysis . + Execution is supported both locally or on remote machines. + date_publication: '2024-11-20' + bug_reports: '' + url: https://certara.github.io/R-RsNLME/ + url_cran: https://CRAN.R-project.org/package=Certara.RsNLME + url_git: '' +Certara.RsNLME.ModelBuilder: + version: 3.0.1 + title: Pharmacometric Model Building Using 'shiny' + maintainer: James Craig + description: |- + Develop Nonlinear Mixed Effects (NLME) models for pharmacometrics using a 'shiny' + interface. The Pharmacometric Modeling Language (PML) code updates in real time given + changes to user inputs. Models can be executed using the 'Certara.RsNLME' package. + Additional support to generate the underlying 'Certara.RsNLME' code to recreate + the corresponding model in R is provided in the user interface. + date_publication: '2024-12-20' + bug_reports: '' + url: https://certara.github.io/R-RsNLME-model-builder/ + url_cran: https://CRAN.R-project.org/package=Certara.RsNLME.ModelBuilder + url_git: '' +Certara.RsNLME.ModelExecutor: + version: 3.0.1 + title: Execute Pharmacometric Models Using 'shiny' + maintainer: James Craig + description: |- + Execute Nonlinear Mixed Effects (NLME) models for pharmacometrics using a 'shiny' + interface. Specify engine parameters and select from different run options, including + simple estimation, stepwise covariate search, bootstrapping, simulation, visual predictive + check, and more. Models are executed using the 'Certara.RsNLME' package. + date_publication: '2025-01-07' + bug_reports: '' + url: https://certara.github.io/R-RsNLME-model-executor/ + url_cran: https://CRAN.R-project.org/package=Certara.RsNLME.ModelExecutor + url_git: '' +Certara.VPCResults: + version: 3.0.2 + title: Generate Visual Predictive Checks (VPC) Using 'shiny' + maintainer: James Craig + description: |- + Utilize the 'shiny' interface to parameterize a Visual Predictive Check (VPC), + including selecting from different binning or binless methods and performing stratification, + censoring, and prediction correction. Generate the underlying 'tidyvpc' and 'ggplot2' code + directly from the user interface and download R or Rmd scripts to reproduce the VPCs in R. + date_publication: '2024-12-02' + bug_reports: '' + url: https://certara.github.io/R-VPCResults/ + url_cran: https://CRAN.R-project.org/package=Certara.VPCResults + url_git: '' +Certara.Xpose.NLME: + version: 2.0.2 + title: |- + Enhances 'xpose' Diagnostics for Pharmacometric Models from + 'Certara.RsNLME' and Phoenix NLME + maintainer: James Craig + description: |- + Facilitates the creation of 'xpose' data objects from Nonlinear Mixed + Effects (NLME) model outputs produced by 'Certara.RsNLME' or Phoenix NLME. This + integration enables users to utilize all 'ggplot2'-based plotting functions available + in 'xpose' for thorough model diagnostics and data visualization. Additionally, the + package introduces specialized plotting functions tailored for covariate model + evaluation, extending the analytical capabilities beyond those offered by 'xpose' alone. + date_publication: '2025-01-28' + bug_reports: '' + url: https://certara.github.io/R-Xpose-NLME/ + url_cran: https://CRAN.R-project.org/package=Certara.Xpose.NLME + url_git: '' +ceser: + version: 1.0.0 + title: Cluster Estimated Standard Errors + maintainer: Diogo Ferrari + description: Implementation of the Cluster Estimated Standard Errors (CESE) proposed + in Jackson (2020) to compute clustered standard errors + of linear coefficients in regression models with grouped data. + date_publication: '2020-11-09' + bug_reports: https://github.com/DiogoFerrari/ceser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ceser + url_git: https://github.com/DiogoFerrari/ceser +cesR: + version: 0.1.0 + title: Access the Canadian Election Study Datasets + maintainer: Paul A. Hodgetts + description: |- + Makes accessing and loading the Canadian Election Study (, , ) surveys into the R workspace more efficient by + downloading a requested survey and loading it as a data object. This removes the need to locate, download, load, + and change working directories when working with the Canadian Election Study surveys. + date_publication: '2021-11-23' + bug_reports: https://github.com/hodgettsp/cesR/issues + url: https://hodgettsp.github.io/cesR/ + url_cran: https://CRAN.R-project.org/package=cesR + url_git: '' +cetcolor: + version: 0.2.0 + title: CET Perceptually Uniform Colour Maps + maintainer: James Balamuta + description: |- + Collection of perceptually uniform colour maps made by Peter Kovesi + (2015) "Good Colour Maps: How to Design Them" + at the Centre for Exploration Targeting (CET). + date_publication: '2018-07-10' + bug_reports: https://github.com/coatless/cetcolor/issues + url: http://thecoatlessprofessor.com/projects/cetcolor/ + url_cran: https://CRAN.R-project.org/package=cetcolor + url_git: https://github.com/coatless/cetcolor +ceterisParibus: + version: '0.6' + title: Ceteris Paribus Profiles + maintainer: Przemyslaw Biecek + description: |- + Ceteris Paribus Profiles (What-If Plots) are designed to present model + responses around selected points in a feature space. + For example around a single prediction for an interesting observation. + Plots are designed to work in a model-agnostic fashion, they are working + for any predictive Machine Learning model and allow for model comparisons. + Ceteris Paribus Plots supplement the Break Down Plots from 'breakDown' package. + date_publication: '2024-11-21' + bug_reports: https://github.com/pbiecek/ceterisParibus/issues + url: https://pbiecek.github.io/ceterisParibus/ + url_cran: https://CRAN.R-project.org/package=ceterisParibus + url_git: '' +cfa: + version: 0.10-1 + title: Configural Frequency Analysis (CFA) + maintainer: Patrick Mair + description: Analysis of configuration frequencies for simple and repeated measures, + multiple-samples CFA, hierarchical CFA, bootstrap CFA, functional CFA, Kieser-Victor + CFA, and Lindner's test using a conventional and an accelerated algorithm. + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cfa + url_git: '' +CFAcoop: + version: 1.0.0 + title: 'Colony Formation Assay: Taking into Account Cellular Cooperation' + maintainer: Daniel Samaga + description: |- + Cellular cooperation compromises the plating efficiency-based + analysis of clonogenic survival data. This tool provides functions that + enable a robust analysis of colony formation assay (CFA) data in presence + or absence of cellular cooperation. + The implemented method has been described + in Brix et al. (2020). (Brix, N., Samaga, D., Hennel, R. et al. + "The clonogenic assay: robustness of plating efficiency-based analysis is + strongly compromised by cellular cooperation." Radiat Oncol 15, 248 (2020). + ) + Power regression for parameter estimation, calculation of survival + fractions, uncertainty analysis and plotting functions are provided. + date_publication: '2021-06-11' + bug_reports: https://github.com/ZytoHMGU/CFAcoop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CFAcoop + url_git: https://github.com/ZytoHMGU/CFAcoop +CFC: + version: 1.2.0 + title: Cause-Specific Framework for Competing-Risk Analysis + maintainer: Alireza S. Mahani + description: |- + Numerical integration of cause-specific survival curves to arrive at cause-specific cumulative incidence functions, + with three usage modes: 1) Convenient API for parametric survival regression followed by competing-risk analysis, 2) API for + CFC, accepting user-specified survival functions in R, and 3) Same as 2, but accepting survival functions in C++. For + mathematical details and software tutorial, see Mahani and Sharabiani (2019) . + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CFC + url_git: '' +cfda: + version: 0.12.1 + title: Categorical Functional Data Analysis + maintainer: Quentin Grimonprez + description: |- + Package for the analysis of categorical functional data. + The main purpose is to compute an encoding (real functional variable) for each state . + It also provides functions to perform basic statistical analysis on categorical functional data. + date_publication: '2025-01-24' + bug_reports: https://github.com/modal-inria/cfda/issues + url: https://modal-inria.github.io/cfda/ + url_cran: https://CRAN.R-project.org/package=cfda + url_git: '' +cfdecomp: + version: 0.4.0 + title: 'Counterfactual Decomposition: MC Integration of the G-Formula' + maintainer: Maarten Jacob Bijlsma + description: Provides a set of functions for counterfactual decomposition (cfdecomp). + The functions available in this package decompose differences in an outcome attributable + to a mediating variable (or sets of mediating variables) between groups based + on counterfactual (causal inference) theory. By using Monte Carlo (MC) integration + (simulations based on empirical estimates from multivariable models) we provide + added flexibility compared to existing (analytical) approaches, at the cost of + computational power or time. The added flexibility means that we can decompose + difference between groups in any outcome or and with any mediator (any variable + type and distribution). See Sudharsanan & Bijlsma (2019) + for more information. + date_publication: '2021-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cfdecomp + url_git: '' +CFF: + version: '1.0' + title: Simple Similarity for User-Based Collaborative Filtering Systems + maintainer: Farimah Houshmand Nanehkaran + description: |- + A simple, fast algorithm to find the neighbors and similarities of users in user-based filtering systems, + to break free from the complex computation of existing similarity formulas and the ability to solve big data. + date_publication: '2020-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CFF + url_git: '' +cffdrs: + version: 1.9.0 + title: Canadian Forest Fire Danger Rating System + maintainer: Brett Moore + description: |- + This project provides a group of new functions to calculate + the outputs of the two main components of the Canadian Forest Fire + Danger Rating System (CFFDRS) Van Wagner and Pickett (1985) + ) at various time + scales: the Fire Weather Index (FWI) System Wan Wagner (1985) + and the Fire Behaviour + Prediction (FBP) System Forestry Canada Fire Danger Group (1992) + . Some functions + have two versions, table and raster based. + date_publication: '2024-02-22' + bug_reports: https://r-forge.r-project.org/tracker/?func=browse&group_id=1970&atid=5372 + url: '' + url_cran: https://CRAN.R-project.org/package=cffdrs + url_git: https://r-forge.r-project.org/projects/cffdrs/ +cffr: + version: 1.2.0 + title: Generate Citation File Format ('cff') Metadata for R Packages + maintainer: Diego Hernangómez + description: |- + The Citation File Format version 1.2.0 + is a human and machine readable file + format which provides citation metadata for software. This package + provides core utilities to generate and validate this metadata. + date_publication: '2025-01-25' + bug_reports: https://github.com/ropensci/cffr/issues + url: https://docs.ropensci.org/cffr/ + url_cran: https://CRAN.R-project.org/package=cffr + url_git: https://github.com/ropensci/cffr +cfid: + version: 0.1.7 + title: Identification of Counterfactual Queries in Causal Models + maintainer: Santtu Tikka + description: |- + Facilitates the identification of counterfactual queries in + structural causal models via the ID* and IDC* algorithms + by Shpitser, I. and Pearl, J. (2007, 2008) , + . + Provides a simple interface for defining causal diagrams and counterfactual + conjunctions. Construction of parallel worlds graphs and counterfactual graphs + is carried out automatically based on the counterfactual query and the causal + diagram. See Tikka, S. (2023) for a tutorial of + the package. + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cfid + url_git: https://github.com/santikka/cfid +CFilt: + version: 0.3.0 + title: Recommendation by Collaborative Filtering + maintainer: Jessica Kubrusly + description: |- + Provides methods and functions to implement a Recommendation + System based on Collaborative Filtering Methodology. + See Aggarwal (2016) for an overview. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CFilt + url_git: '' +cfma: + version: '1.0' + title: Causal Functional Mediation Analysis + maintainer: Yi Zhao + description: 'Performs causal functional mediation analysis (CFMA) for functional + treatment, functional mediator, and functional outcome. This package includes + two functional mediation model types: (1) a concurrent mediation model and (2) + a historical influence mediation model. See Zhao et al. (2018), Functional Mediation + Analysis with an Application to Functional Magnetic Resonance Imaging Data, + for details.' + date_publication: '2018-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cfma + url_git: '' +cfmortality: + version: 0.3.0 + title: |- + Cystic Fibrosis Survival Prediction Model Based on Stanojevic + Model + maintainer: Amin Adibi + description: Allows clinicians to predict survival probabilities over the next two + years for cystic fibrosis patients, based on the clinical prediction models published + in Stanojevic et al. (2019) . + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cfmortality + url_git: '' +CFO: + version: 2.2.0 + title: CFO-Type Designs in Phase I/II Clinical Trials + maintainer: Jialu Fang + description: 'In phase I clinical trials, the primary objective is to ascertain + the maximum tolerated dose (MTD) corresponding to a specified target toxicity + rate. The subsequent phase II trials are designed to examine the potential efficacy + of the drug based on the MTD obtained from the phase I trials, with the aim of + identifying the optimal biological dose (OBD). The ''CFO'' package facilitates + the implementation of dose-finding trials by utilizing calibration-free odds type + (CFO-type) designs. Specifically, it encompasses the calibration-free odds (CFO) + (Jin and Yin (2022) ), randomized CFO (rCFO), precision + CFO (pCFO), two-dimensional CFO (2dCFO) (Wang et al. (2023) ), + time-to-event CFO (TITE-CFO) (Jin and Yin (2023) ), fractional + CFO (fCFO), accumulative CFO (aCFO), TITE-aCFO, and f-aCFO (Fang and Yin (2024) + ). It supports phase I/II trials for the CFO design and + only phase I trials for the other CFO-type designs. The ‘CFO'' package accommodates + diverse CFO-type designs, allowing users to tailor the approach based on factors + such as dose information inclusion, handling of late-onset toxicity, and the nature + of the target drug (single-drug or drug-combination). The functionalities embedded + in ''CFO'' package include the determination of the dose level for the next cohort, + the selection of the MTD for a real trial, and the execution of single or multiple + simulations to obtain operating characteristics. Moreover, these functions are + equipped with early stopping and dose elimination rules to address safety considerations. + Users have the flexibility to choose different distributions, thresholds, and + cohort sizes among others for their specific needs. The output of the ''CFO'' + package can be summary statistics as well as various plots for better visualization. + An interactive web application for CFO is available at the provided URL.' + date_publication: '2024-11-15' + bug_reports: '' + url: https://clinicaltrialdesign.shinyapps.io/cfoapp + url_cran: https://CRAN.R-project.org/package=CFO + url_git: '' +cforward: + version: 0.1.0 + title: Forward Selection using Concordance/C-Index + maintainer: John Muschelli + description: |- + Performs forward model selection, using the C-index/concordance + in survival analysis models. + date_publication: '2021-03-29' + bug_reports: https://github.com/muschellij2/cforward/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cforward + url_git: https://github.com/muschellij2/cforward +cfr: + version: 0.2.0 + title: Estimate Disease Severity and Case Ascertainment + maintainer: Adam Kucharski + description: |- + Estimate the severity of a disease and ascertainment of + cases, as discussed in Nishiura et al. (2009) + . + date_publication: '2025-02-21' + bug_reports: https://github.com/epiverse-trace/cfr/issues + url: https://epiverse-trace.github.io/cfr/ + url_cran: https://CRAN.R-project.org/package=cfr + url_git: https://github.com/epiverse-trace/cfr +cft: + version: 1.0.0 + title: Climate Futures Toolbox + maintainer: Erick Verleye + description: Developed as a collaboration between Earth lab and the North Central + Climate Adaptation Science Center to help users gain insights from available climate + data. Includes tools and instructions for downloading climate data via a 'USGS' + API and then organizing those data for visualization and analysis that drive insight. + Web interface for 'USGS' API can be found at . + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cft + url_git: https://github.com/earthlab/cft-CRAN +CFtime: + version: 1.5.0 + title: Using CF-Compliant Calendars with Climate Projection Data + maintainer: Patrick Van Laake + description: |- + Support for all calendars as specified in the Climate and Forecast + (CF) Metadata Conventions for climate and forecasting data. The CF Metadata + Conventions is widely used for distributing files with climate observations + or projections, including the Coupled Model Intercomparison Project (CMIP) + data used by climate change scientists and the Intergovernmental Panel on + Climate Change (IPCC). This package specifically allows the user to work + with any of the CF-compliant calendars (many of which are not compliant with + POSIXt). The CF time coordinate is formally defined in the CF Metadata + Conventions document available at . + date_publication: '2025-01-15' + bug_reports: https://github.com/pvanlaake/CFtime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CFtime + url_git: https://github.com/pvanlaake/CFtime +cg: + version: 1.0-3 + title: Compare Groups, Analytically and Graphically + maintainer: Bill Pikounis + description: Comprehensive data analysis software, and the name "cg" stands for + "compare groups." Its genesis and evolution are driven by common needs to compare + administrations, conditions, etc. in medicine research and development. The current + version provides comparisons of unpaired samples, i.e. a linear model with one + factor of at least two levels. It also provides comparisons of two paired samples. + Good data graphs, modern statistical methods, and useful displays of results are + emphasized. + date_publication: '2016-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cg + url_git: '' +cgaim: + version: 1.0.1 + title: Constrained Groupwise Additive Index Models + maintainer: Pierre Masselot + description: Fits constrained groupwise additive index models and provides functions + for inference and interpretation of these models. The method is described in Masselot, + Chebana, Campagna, Lavigne, Ouarda, Gosselin (2022) "Constrained groupwise additive + index models" . + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cgaim + url_git: '' +cgal4h: + version: 0.1.0 + title: '''CGAL'' Version 4 C++ Header Files' + maintainer: Ahmadou Dicko + description: |- + 'CGAL' is a C++ library that aims to provide easy access to efficient and + reliable algorithms in computational geometry. Since its version 4, 'CGAL' can be used + as standalone header-only library and is available under a double GPL-3|LGPL license. + . + date_publication: '2020-06-30' + bug_reports: https://gitlab.com/dickoa/cgal4h/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cgal4h + url_git: https://gitlab.com/dickoa/cgal4h +cgam: + version: '1.23' + title: Constrained Generalized Additive Model + maintainer: Xiyue Liao + description: A constrained generalized additive model is fitted by the cgam routine. + Given a set of predictors, each of which may have a shape or order restrictions, + the maximum likelihood estimator for the constrained generalized additive model + is found using an iteratively re-weighted cone projection algorithm. The ShapeSelect + routine chooses a subset of predictor variables and describes the component relationships + with the response. For each predictor, the user needs only specify a set of possible + shape or order restrictions. A model selection method chooses the shapes and orderings + of the relationships as well as the variables. The cone information criterion + (CIC) is used to select the best combination of variables and shapes. A genetic + algorithm may be used when the set of possible models is large. In addition, the + cgam routine implements a two-dimensional isotonic regression using warped-plane + splines without additivity assumptions. It can also fit a convex or concave regression + surface with triangle splines without additivity assumptions. See Liao X, Meyer + MC (2019) for more details. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cgam + url_git: '' +cgAUC: + version: 1.2.1 + title: Calculate AUC-type measure when gold standard is continuous andthe + corresponding optimal linear combination of variables withrespect to it. + maintainer: Yu-chia Chang + description: The cgAUC can calculate the AUC-type measure of Obuchowski(2006) when + gold standard is continuous, and find the optimal linear combination of variables + with respect to this measure. + date_publication: '2014-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cgAUC + url_git: '' +CGE: + version: 0.3.3 + title: Computing General Equilibrium + maintainer: LI Wu + description: 'Developing general equilibrium models, computing general equilibrium + and simulating economic dynamics with structural dynamic models in LI (2019, ISBN: + 9787521804225) "General Equilibrium and Structural Dynamics: Perspectives of New + Structural Economics. Beijing: Economic Science Press". When developing complex + general equilibrium models, GE package should be used in addition to this package.' + date_publication: '2020-05-24' + bug_reports: https://github.com/LiWuR/CGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CGE + url_git: '' +CGGP: + version: 1.0.4 + title: Composite Grid Gaussian Processes + maintainer: Collin Erickson + description: |- + Run computer experiments using the adaptive composite grid + algorithm with a Gaussian process model. + The algorithm works best when running an experiment that can evaluate thousands + of points from a deterministic computer simulation. + This package is an implementation of a forthcoming paper by Plumlee, + Erickson, Ankenman, et al. For a preprint of the paper, + contact the maintainer of this package. + date_publication: '2024-01-23' + bug_reports: https://github.com/CollinErickson/CGGP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CGGP + url_git: https://github.com/CollinErickson/CGGP +cglasso: + version: 2.0.7 + title: |- + Conditional Graphical LASSO for Gaussian Graphical Models with + Censored and Missing Values + maintainer: Luigi Augugliaro + description: 'Conditional graphical lasso estimator is an extension of the graphical + lasso proposed to estimate the conditional dependence structure of a set of p + response variables given q predictors. This package provides suitable extensions + developed to study datasets with censored and/or missing values. Standard conditional + graphical lasso is available as a special case. Furthermore, the package provides + an integrated set of core routines for visualization, analysis, and simulation + of datasets with censored and/or missing values drawn from a Gaussian graphical + model. Details about the implemented models can be found in Augugliaro et al. + (2023) , Augugliaro et al. (2020b) , + Augugliaro et al. (2020a) , Yin et al. (2001) + and Stadler et al. (2012) .' + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cglasso + url_git: '' +cglm: + version: '1.1' + title: Fits Conditional Generalized Linear Models + maintainer: Arvid Sjolander + description: Estimates the ratio of the regression coefficients and the dispersion + parameter in conditional generalized linear models for clustered data. + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cglm + url_git: '' +cgmanalysis: + version: 3.0.2 + title: Clean and Analyze Continuous Glucose Monitor Data + maintainer: Tim Vigers + description: This code provides several different functions for cleaning and analyzing + continuous glucose monitor data. Currently it works with 'Dexcom', 'iPro 2', 'Diasend', + 'Libre', or 'Carelink' data. The cleandata() function takes a directory of CGM + data files and prepares them for analysis. cgmvariables() iterates through a directory + of cleaned CGM data files and produces a single spreadsheet with data for each + file in either rows or columns. The column format of this spreadsheet is compatible + with REDCap data upload. cgmreport() also iterates through a directory of cleaned + data, and produces PDFs of individual and aggregate AGP plots. Please visit + to download the new-user guide. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cgmanalysis + url_git: '' +CGManalyzer: + version: 1.3.1 + title: Continuous Glucose Monitoring Data Analyzer + maintainer: Xinzheng Dong + description: 'Contains all of the functions necessary for the complete analysis + of a continuous glucose monitoring study and can be applied to data measured by + various existing ''CGM'' devices such as ''FreeStyle Libre'', ''Glutalor'', ''Dexcom'' + and ''Medtronic CGM''. It reads a series of data files, is able to convert various + formats of time stamps, can deal with missing values, calculates both regular + statistics and nonlinear statistics, and conducts group comparison. It also displays + results in a concise format. Also contains two unique features new to ''CGM'' + analysis: one is the implementation of strictly standard mean difference and the + class of effect size; the other is the development of a new type of plot called + antenna plot. It corresponds to ''Zhang XD''(2018)''s + article ''CGManalyzer: an R package for analyzing continuous glucose monitoring + studies''.' + date_publication: '2023-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CGManalyzer + url_git: '' +cgmquantify: + version: 0.1.0 + title: Analyzing Glucose and Glucose Variability + maintainer: Maria Henriquez + description: |- + Continuous glucose monitoring (CGM) systems provide real-time, + dynamic glucose information by tracking interstitial glucose values + throughout the day. Glycemic variability, also known as glucose variability, + is an established risk factor for hypoglycemia (Kovatchev) and + has been shown to be a risk factor in diabetes complications. + Over 20 metrics of glycemic variability have been identified. + Here, we provide functions to calculate glucose summary metrics, + glucose variability metrics (as defined in clinical publications), + and visualizations to visualize trends in CGM data. + Cho P, Bent B, Wittmann A, et al. (2020) + American Diabetes Association (2020) + Kovatchev B (2019) + Kovdeatchev BP (2017) + Tamborlane W V., Beck RW, Bode BW, et al. (2008) + Umpierrez GE, P. Kovatchev B (2018) . + date_publication: '2021-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cgmquantify + url_git: '' +CGNM: + version: 0.9.1 + title: Cluster Gauss-Newton Method + maintainer: Yasunori Aoki + description: 'Find multiple solutions of a nonlinear least squares problem. Cluster + Gauss-Newton method does not assume uniqueness of the solution of the nonlinear + least squares problem and compute multiple minimizers. Please cite the following + paper when this software is used in your research: Aoki et al. (2020) . + Cluster Gauss–Newton method. Optimization and Engineering, 1-31. Please cite + the following paper when profile likelihood plot is drawn with this software and + used in your research: Aoki and Sugiyama (2024) . Cluster + Gauss-Newton method for a quick approximation of profile likelihood: With application + to physiologically-based pharmacokinetic models. CPT Pharmacometrics Syst Pharmacol.13(1):54-67.' + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CGNM + url_git: '' +CGP: + version: 2.1-1 + title: Composite Gaussian Process Models + maintainer: Shan Ba + description: Fit composite Gaussian process (CGP) models as described in Ba and + Joseph (2012) "Composite Gaussian Process Models for Emulating Expensive Functions", + Annals of Applied Statistics. The CGP model is capable of approximating complex + surfaces that are not second-order stationary. Important functions in this package + are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP. + date_publication: '2018-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CGP + url_git: '' +CGPfunctions: + version: 0.6.3 + title: |- + Powell Miscellaneous Functions for Teaching and Learning + Statistics + maintainer: Chuck Powell + description: Miscellaneous functions useful for teaching statistics as well as actually + practicing the art. They typically are not new methods but rather wrappers around + either base R or other packages. + date_publication: '2020-11-12' + bug_reports: https://github.com/ibecav/CGPfunctions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CGPfunctions + url_git: https://github.com/ibecav/CGPfunctions +CGR: + version: 0.1.0 + title: |- + Compound Growth Rate for Capturing the Growth Rate Over the + Period + maintainer: Dr. S. Vishnu Shankar + description: The compound growth rate indicates the percentage change of a specific + variable over a defined period. It is calculated using non-linear models, particularly + the exponential model. To estimate the compound growth rates, the growth model + is first converted to semilog form and then analyzed using Ordinary Least Squares + (OLS) regression. This package has been developed using concept of Shankar et + al. (2022). + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CGR + url_git: '' +cgwtools: + version: '4.1' + title: Miscellaneous Tools + maintainer: Carl Witthoft + description: Functions for performing quick observations or evaluations of data, + including a variety of ways to list objects by size, class, etc. The functions + 'seqle' and 'reverse.seqle' mimic the base 'rle' but can search for linear sequences. + The function 'splatnd' allows the user to generate zero-argument commands without + the need for 'makeActiveBinding' . Functions provided to convert from any base + to any other base, and to find the n-th greatest max or n-th least min. In addition, + functions which mimic Unix shell commands, including 'head', 'tail' ,'pushd' ,and + 'popd'. Various other goodies included as well. + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cgwtools + url_git: '' +ch: + version: 0.1.0.2 + title: About some Small Functions + maintainer: Hailong Chai + description: |- + The solution to some common problems is proposed, + as well as a summary of some small functions. In particular, + it provides a useful function for some problems in chemistry. + For example, monoa(), monob() and mono() function can be used + to calculate The pH of weak acid/base. + The ggpng() function can save the PNG format with transparent background. + The period_table() function will show the periodic table. Also the + show_ruler() function will show the ruler. + The show_color() function is funny and easier to show colors. + I also provide the symb() function to generate multiple symbols at once. + The csv2vcf() function provides an easy method to generate a file. + The sym2poly() and sym2coef() function can extract coefficients from + polynomials. + date_publication: '2021-07-09' + bug_reports: https://github.com/tsiamut/ch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ch + url_git: https://github.com/tsiamut/ch +chainbinomial: + version: 0.1.5 + title: Chain Binomial Models for Analysis of Infectious Disease Data + maintainer: Jonas Christoffer Lindstrøm + description: |- + Implements the chain binomial model for analysis of infectious disease data. + Contains functions for calculating probabilities of the final size of infectious + disease outbreaks using the method from D. Ludwig (1975) + and for outbreaks that are not + concluded, from Lindstrøm et al. (2024) . The package + also contains methods for estimation and regression analysis of + secondary attack rates. + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chainbinomial + url_git: '' +ChainLadder: + version: 0.2.20 + title: |- + Statistical Methods and Models for Claims Reserving in General + Insurance + maintainer: Markus Gesmann + description: |- + Various statistical methods and models which are + typically used for the estimation of outstanding claims reserves + in general insurance, including those to estimate the claims + development result as required under Solvency II. + date_publication: '2025-02-06' + bug_reports: https://github.com/mages/ChainLadder/issues + url: https://mages.github.io/ChainLadder/ + url_cran: https://CRAN.R-project.org/package=ChainLadder + url_git: '' +chameleon: + version: 0.2-3 + title: Automatic Colors for Multi-Dimensional Data + maintainer: Oren Ben-Kiki + description: Assign distinct colors to arbitrary multi-dimensional data, considering + its structure. + date_publication: '2022-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chameleon + url_git: '' +chandwich: + version: 1.1.6 + title: Chandler-Bate Sandwich Loglikelihood Adjustment + maintainer: Paul J. Northrop + description: |- + Performs adjustments of a user-supplied independence loglikelihood + function using a robust sandwich estimator of the parameter covariance + matrix, based on the methodology in Chandler and Bate (2007) + . This can be used for cluster correlated data + when interest lies in the parameters of the marginal distributions or for + performing inferences that are robust to certain types of model + misspecification. Functions for profiling the adjusted loglikelihoods are + also provided, as are functions for calculating and plotting confidence + intervals, for single model parameters, and confidence regions, for pairs + of model parameters. Nested models can be compared using an adjusted + likelihood ratio test. + date_publication: '2023-08-25' + bug_reports: https://github.com/paulnorthrop/chandwich/issues + url: https://paulnorthrop.github.io/chandwich/ + url_cran: https://CRAN.R-project.org/package=chandwich + url_git: https://github.com/paulnorthrop/chandwich +changepoint: + version: '2.3' + title: Methods for Changepoint Detection + maintainer: Rebecca Killick + description: Implements various mainstream and specialised changepoint methods for + finding single and multiple changepoints within data. Many popular non-parametric + and frequentist methods are included. The cpt.mean(), cpt.var(), cpt.meanvar() + functions should be your first point of call. + date_publication: '2024-11-04' + bug_reports: https://github.com/rkillick/changepoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=changepoint + url_git: https://github.com/rkillick/changepoint/ +changepoint.geo: + version: 1.0.2 + title: Geometrically Inspired Multivariate Changepoint Detection + maintainer: Rebecca Killick + description: 'Implements the high-dimensional changepoint detection method GeomCP + and the related mappings used for changepoint detection. These methods view the + changepoint problem from a geometrical viewpoint and aim to extract relevant geometrical + features in order to detect changepoints. The geomcp() function should be your + first point of call. References: Grundy et al. (2020) .' + date_publication: '2023-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=changepoint.geo + url_git: https://github.com/grundy95/changepoint.geo/ +changepoint.influence: + version: 1.0.2 + title: |- + Package to Calculate the Influence of the Data on a Changepoint + Segmentation + maintainer: Rebecca Killick + description: Allows users to input their data, segmentation and function used for + the segmentation (and additional arguments) and the package calculates the influence + of the data on the changepoint locations, see Wilms et al. (2022) . Currently + this can only be used with the changepoint package functions to identify changes, + but we plan to extend this. There are options for different types of graphics + to assess the influence. + date_publication: '2024-02-20' + bug_reports: https://github.com/rkillick/changepoint.influence/issues + url: '' + url_cran: https://CRAN.R-project.org/package=changepoint.influence + url_git: https://github.com/rkillick/changepoint.influence/ +changepoint.np: + version: 1.0.5 + title: Methods for Nonparametric Changepoint Detection + maintainer: Daniel Grose + description: Implements the multiple changepoint algorithm PELT with a nonparametric + cost function based on the empirical distribution of the data. This package extends + the changepoint package (see Killick, R and Eckley, I (2014) + ). + date_publication: '2022-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=changepoint.np + url_git: '' +changepointGA: + version: 0.1.0 + title: Changepoint Detection via Modified Genetic Algorithm + maintainer: Mo Li + description: The Genetic Algorithm (GA) is used to perform changepoint analysis + in time series data. The package also includes an extended island version of GA, + as described in Lu, Lund, and Lee (2010, ). By mimicking + the principles of natural selection and evolution, GA provides a powerful stochastic + search technique for solving combinatorial optimization problems. In 'changepointGA', + each chromosome represents a changepoint configuration, including the number and + locations of changepoints, hyperparameters, and model parameters. The package + employs genetic operators—selection, crossover, and mutation—to iteratively improve + solutions based on the given fitness (objective) function. Key features of 'changepointGA' + include encoding changepoint configurations in an integer format, enabling dynamic + and simultaneous estimation of model hyperparameters, changepoint configurations, + and associated parameters. The detailed algorithmic implementation can be found + in the package vignettes and in the paper of Li (2024, ). + date_publication: '2025-02-17' + bug_reports: https://github.com/mli171/changepointGA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=changepointGA + url_git: https://github.com/mli171/changepointGA +changepoints: + version: 1.1.0 + title: A Collection of Change-Point Detection Methods + maintainer: Haotian Xu + description: 'Performs a series of offline and/or online change-point detection + algorithms for 1) univariate mean: , ; + 2) univariate polynomials: ; 3) univariate and multivariate + nonparametric settings: , ; + 4) high-dimensional covariances: ; 5) high-dimensional + networks with and without missing values: , , + ; 6) high-dimensional linear regression models: , + ; 7) high-dimensional vector autoregressive models: ; + 8) high-dimensional self exciting point processes: ; 9) dependent + dynamic nonparametric random dot product graphs: ; 10) univariate + mean against adversarial attacks: .' + date_publication: '2022-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=changepoints + url_git: https://github.com/HaotianXu/changepoints +changepointsVar: + version: 0.1.1 + title: Change-Points Detections for Changes in Variance + maintainer: Gianluca Sottile + description: Detection of change-points for variance of heteroscedastic Gaussian + variables with piecewise constant variance function. Adelfio, G. (2012), Change-point + detection for variance piecewise constant models, Communications in Statistics, + Simulation and Computation, 41:4, 437-448, . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=changepointsVar + url_git: '' +ChangePointTaylor: + version: '0.3' + title: Identify Changes in Mean + maintainer: Michael Marks + description: 'A basic implementation of the change in mean detection method outlined + in: Taylor, Wayne A. (2000) . + The package recursively uses the mean-squared error change point calculation to + identify candidate change points. The candidate change points are then re-estimated + and Taylor''s backwards elimination process is then employed to come up with a + final set of change points. Many of the underlying functions are written in C++ + for improved performance.' + date_publication: '2024-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChangePointTaylor + url_git: '' +ChangepointTesting: + version: '1.1' + title: Change Point Estimation for Clustered Signals + maintainer: Shannon T. Holloway + description: |- + A multiple testing procedure for clustered alternative hypotheses. + It is assumed that the p-values under the null hypotheses follow U(0,1) and + that the distributions of p-values from the alternative hypotheses are + stochastically smaller than U(0,1). By aggregating information, this + method is more sensitive to detecting signals of low magnitude than + standard methods. Additionally, sporadic small p-values appearing + within a null hypotheses sequence are avoided by averaging on the + neighboring p-values. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChangepointTesting + url_git: '' +changepointTests: + version: 0.1.7 + title: Change Point Tests for Joint Distributions and Copulas + maintainer: Bruno N Remillard + description: Change point tests for joint distributions and copulas using pseudo-observations + with multipliers or bootstrap. The processes used here have been defined in Bucher, + Kojadinovic, Rohmer & Segers and Nasri & Remillard + . + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=changepointTests + url_git: '' +changer: + version: 0.0.5 + title: Change R Package Name + maintainer: Jouni Helske + description: Changing the name of an existing R package is annoying but common task + especially in the early stages of package development. This package (mostly) automates + this task. + date_publication: '2022-05-03' + bug_reports: https://github.com/helske/changer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=changer + url_git: https://github.com/helske/changer +changeS: + version: 1.0.1 + title: S-Curve Fit for Changepoint Analysis + maintainer: Norm Matloff + description: |- + Estimation of changepoints using an "S-curve" + approximation. Formation of confidence intervals for changepoint + locations and magnitudes. Both abrupt and gradual changes can be + modeled. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=changeS + url_git: https://github.com/matloff/changeS +ChannelAttribution: + version: 2.0.7 + title: Markov Model for Online Multi-Channel Attribution + maintainer: Davide Altomare + description: Advertisers use a variety of online marketing channels to reach consumers + and they want to know the degree each channel contributes to their marketing success. + This is called online multi-channel attribution problem. This package contains + a probabilistic algorithm for the attribution problem. The model uses a k-order + Markov representation to identify structural correlations in the customer journey + data. The package also contains three heuristic algorithms (first-touch, last-touch + and linear-touch approach) for the same problem. The algorithms are implemented + in C++. + date_publication: '2023-05-17' + bug_reports: '' + url: https://channelattribution.io + url_cran: https://CRAN.R-project.org/package=ChannelAttribution + url_git: '' +ChannelAttributionApp: + version: '1.3' + title: Shiny Web Application for the Multichannel Attribution Problem + maintainer: Davide Altomare + description: Shiny Web Application for the Multichannel Attribution Problem. It + is a user-friendly graphical interface for package 'ChannelAttribution'. + date_publication: '2020-07-14' + bug_reports: '' + url: http://www.channelattribution.net + url_cran: https://CRAN.R-project.org/package=ChannelAttributionApp + url_git: '' +chantrics: + version: 1.0.0 + title: Loglikelihood Adjustments for Econometric Models + maintainer: Theo Bruckbauer + description: |- + Adjusts the loglikelihood of common econometric models for + clustered data based on the estimation process suggested in + Chandler and Bate (2007) , using the 'chandwich' + package , and provides + convenience functions for inference on the adjusted models. + date_publication: '2021-09-29' + bug_reports: https://github.com/tbruckbauer/chantrics/issues + url: https://chantrics.theobruckbauer.eu + url_cran: https://CRAN.R-project.org/package=chantrics + url_git: https://github.com/tbruckbauer/chantrics +Chaos01: + version: 1.2.1 + title: 0-1 Test for Chaos + maintainer: Tomas Martinovic + description: |- + Computes and visualize the results of the 0-1 test for chaos proposed + by Gottwald and Melbourne (2004) . The algorithm is + available in parallel for the independent values of parameter c. Additionally, + fast RQA is added to distinguish chaos from noise. + date_publication: '2019-08-21' + bug_reports: '' + url: https://code.it4i.cz/ADAS/Chaos01 + url_cran: https://CRAN.R-project.org/package=Chaos01 + url_git: '' +ChaosGame: + version: '1.4' + title: Chaos Game + maintainer: Marco Tschimpke + description: The main objective of the package is to enter a word of at least two + letters based on which an Iterated Function System with Probabilities is constructed, + and a two-dimensional fractal containing the chosen word infinitely often is generated + via the Chaos Game. Additionally, the package allows to project the two-dimensional + fractal on several three-dimensional surfaces and to transform the fractal into + another fractal with uniform marginals. + date_publication: '2022-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChaosGame + url_git: '' +charcuterie: + version: 0.0.6 + title: Handle Strings as Vectors of Characters + maintainer: Jonathan Carroll + description: |- + Creates a new chars class which looks like a string but is actually + a vector of individual characters, making 'strings' iterable. This class + enables vector operations on 'strings' such as reverse, sort, head, and set + operations. + date_publication: '2024-11-07' + bug_reports: https://github.com/jonocarroll/charcuterie/issues + url: https://jonocarroll.github.io/charcuterie/ + url_cran: https://CRAN.R-project.org/package=charcuterie + url_git: https://github.com/jonocarroll/charcuterie +charlatan: + version: 0.6.1 + title: Make Fake Data + maintainer: Roel M. Hogervorst + description: |- + Make fake data that looks realistic, supporting addresses, + person names, dates, + times, colors, coordinates, currencies, digital object identifiers + ('DOIs'), jobs, phone numbers, 'DNA' sequences, doubles and integers + from distributions and within a range. + date_publication: '2024-10-17' + bug_reports: https://github.com/ropensci/charlatan/issues + url: https://docs.ropensci.org/charlatan/ + url_cran: https://CRAN.R-project.org/package=charlatan + url_git: https://github.com/ropensci/charlatan +charlesschwabapi: + version: 1.0.4 + title: Wrapper Functions Around 'Charles Schwab Individual Trader API' + maintainer: Nick Bultman + description: For those wishing to interact with the 'Charles Schwab Individual Trader + API' () with R in + a simplified manner, this package offers wrapper functions around authentication + and the available API calls to streamline the process. + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=charlesschwabapi + url_git: '' +chartql: + version: 0.1.0 + title: Simplified Language for Plots and Charts + maintainer: Rohail Syed + description: 'Provides a very simple syntax for the user to generate custom plot(s) + without having to remember complicated ''ggplot2'' syntax. The ''chartql'' package + uses ''ggplot2'' and manages all the syntax complexities internally. As an example, + to generate a bar chart of company sales faceted by product category further faceted + by season of the year, we simply write: "CHART bar X category, season Y sales".' + date_publication: '2019-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chartql + url_git: https://github.com/rmsyed/chartql +chartreview: + version: '1.0' + title: Adaptive Multi-Wave Sampling for Efficient Chart Validation + maintainer: Georg Hahn + description: Functionality to perform adaptive multi-wave sampling for efficient + chart validation. Code allows one to define strata, adaptively sample using several + types of confidence bounds for the quantity of interest (Lai's confidence bands, + Bayesian credible intervals, normal confidence intervals), and sampling strategies + (random sampling, stratified random sampling, Neyman's sampling, see Neyman (1934) + and Neyman (1938) ). + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chartreview + url_git: '' +chatAI4R: + version: 0.3.6 + title: Chat-Based Interactive Artificial Intelligence for R + maintainer: Satoshi Kume + description: |- + The Large Language Model (LLM) represents a groundbreaking advancement + in data science and programming, and also allows us to extend the world of R. + A seamless interface for integrating the 'OpenAI' Web APIs into R is provided in this package. + This package leverages LLM-based AI techniques, enabling efficient knowledge discovery and data analysis + (see 'OpenAI' Web APIs details ). + The previous functions such as seamless translation and image generation have been moved + to other packages 'deepRstudio' and 'stableDiffusion4R'. + date_publication: '2025-02-12' + bug_reports: https://github.com/kumeS/chatAI4R/issues + url: https://kumes.github.io/chatAI4R/ + url_cran: https://CRAN.R-project.org/package=chatAI4R + url_git: https://github.com/kumeS/chatAI4R +chatgpt: + version: 0.2.3 + title: Interface to 'ChatGPT' from R + maintainer: Juan Cruz Rodriguez + description: |- + 'OpenAI's 'ChatGPT' coding assistant for 'RStudio'. A set + of functions and 'RStudio' addins that aim to help the R developer in tedious coding tasks. + date_publication: '2023-05-05' + bug_reports: https://github.com/jcrodriguez1989/chatgpt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chatgpt + url_git: https://github.com/jcrodriguez1989/chatgpt +chatRater: + version: 1.0.0 + title: Rating Text Using Large Language Models + maintainer: Shiyang Zheng + description: Generates ratings for textual stimuli using large language models. + It allows users to evaluate idioms and similar texts by combining context, prompts, + and stimulus inputs. The package supports both 'OpenAI' and 'DeepSeek' APIs by + enabling users to switch models simply by specifying the model parameter. It implements + methods for constructing the request payload and parsing numeric ratings from + the model outputs. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chatRater + url_git: '' +chattr: + version: 0.2.1 + title: Interact with Large Language Models in 'RStudio' + maintainer: Edgar Ruiz + description: |- + Enables user interactivity with large-language models ('LLM') inside + the 'RStudio' integrated development environment (IDE). The user can + interact with the model using the 'shiny' app included in this package, or + directly in the 'R' console. It comes with back-ends for 'OpenAI', 'GitHub' + 'Copilot', and 'LlamaGPT'. + date_publication: '2025-01-30' + bug_reports: https://github.com/mlverse/chattr/issues + url: https://mlverse.github.io/chattr/ + url_cran: https://CRAN.R-project.org/package=chattr + url_git: https://github.com/mlverse/chattr +cheapr: + version: 1.0.1 + title: Simple Functions to Save Time and Memory + maintainer: Nick Christofides + description: |- + Fast and memory-efficient (or 'cheap') tools to facilitate + efficient programming, saving time and memory. It aims to provide + 'cheaper' alternatives to common base R functions, as well as some + additional functions. + date_publication: '2025-02-12' + bug_reports: https://github.com/NicChr/cheapr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cheapr + url_git: '' +cheatsheet: + version: 0.1.2 + title: Download R Cheat Sheets Locally + maintainer: Brad Lindblad + description: A simple package to grab cheat sheets and save them to your local computer. + date_publication: '2023-05-01' + bug_reports: https://github.com/bradlindblad/cheatsheet/issues + url: https://bradlindblad.github.io/cheatsheet/ + url_cran: https://CRAN.R-project.org/package=cheatsheet + url_git: '' +checkarg: + version: 0.1.0 + title: Check the Basic Validity of a (Function) Argument + maintainer: Ivo Van Walle Developer + description: |- + Utility functions that allow checking the basic validity of a function argument or any other value, + including generating an error and assigning a default in a single line of code. The main purpose of + the package is to provide simple and easily readable argument checking to improve code robustness. + date_publication: '2017-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=checkarg + url_git: '' +CheckDigit: + version: 1.0.0 + title: Calculate and Verify Check Digits + maintainer: Justin Brantley + description: |- + Check digits are used like file hashes to verify that a + number has been transcribed accurately. The functions provided by this + package help to calculate and verify check digits according to various + algorithms. + date_publication: '2022-04-24' + bug_reports: https://gitlab.com/fascinatingfingers/checkdigit/-/issues + url: https://fascinatingfingers.gitlab.io/checkdigit + url_cran: https://CRAN.R-project.org/package=CheckDigit + url_git: https://gitlab.com/fascinatingfingers/checkdigit +checkdown: + version: 0.0.12 + title: Check-Fields and Check-Boxes for 'rmarkdown' + maintainer: George Moroz + description: |- + Creates auto-grading check-fields and check-boxes for 'rmarkdown' + or 'quarto' HTML. It can be used in class, when teacher share materials + and tasks, so students can solve some problems and check their work. In + contrast to the 'learnr' package, the 'checkdown' package works serverlessly + without 'shiny'. + date_publication: '2023-10-27' + bug_reports: https://github.com/agricolamz/checkdown/issues + url: https://agricolamz.github.io/checkdown/ + url_cran: https://CRAN.R-project.org/package=checkdown + url_git: '' +checked: + version: 0.2.4 + title: Systematically Run R CMD Checks + maintainer: Szymon Maksymiuk + description: |- + Systematically Run R checks against multiple packages. Checks are run in + parallel with strategies to minimize dependency installation. Provides + out of the box interface for running reverse dependency check. + date_publication: '2024-10-25' + bug_reports: https://github.com/Genentech/checked/issues + url: https://Genentech.github.io/checked/ + url_cran: https://CRAN.R-project.org/package=checked + url_git: https://github.com/Genentech/checked +checker: + version: 0.1.3 + title: Checks 'R' Configuration Set Up Correctly Before Class + maintainer: Richard J. Telford + description: |- + Checks that students have the correct version of 'R', 'R' packages, + 'RStudio' and other dependencies installed, and that the recommended 'RStudio' + configuration has been applied. + date_publication: '2023-04-26' + bug_reports: https://github.com/richardjtelford/checker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=checker + url_git: https://github.com/richardjtelford/checker/ +checkglobals: + version: 0.1.3 + title: Static Analysis of R-Code Dependencies + maintainer: Joris Chau + description: A minimal R-package to approximately detect global and imported functions + or variables from R-source code or R-packages by static code analysis. + date_publication: '2025-02-06' + bug_reports: https://github.com/JorisChau/checkglobals/issues + url: https://jorischau.github.io/checkglobals/ + url_cran: https://CRAN.R-project.org/package=checkglobals + url_git: https://github.com/JorisChau/checkglobals +checkhelper: + version: 0.1.1 + title: Deal with Check Outputs + maintainer: Sebastien Rochette + description: |- + Deal with packages 'check' outputs and reduce the risk of + rejection by 'CRAN' by following policies. + date_publication: '2024-01-22' + bug_reports: https://github.com/ThinkR-open/checkhelper/issues + url: https://thinkr-open.github.io/checkhelper/ + url_cran: https://CRAN.R-project.org/package=checkhelper + url_git: https://github.com/ThinkR-open/checkhelper +checkLuhn: + version: 1.1.0 + title: Checks if a Number is Valid Using the Luhn Algorithm + maintainer: Adam Deacon + description: |- + Confirms if the number is Luhn compliant. + Can check if credit card, IMEI number or any other Luhn based number is correct. + For more info see: . + date_publication: '2018-09-24' + bug_reports: https://github.com/adamjdeacon/checkLuhn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=checkLuhn + url_git: https://github.com/adamjdeacon/checkLuhn +checkmate: + version: 2.3.2 + title: Fast and Versatile Argument Checks + maintainer: Michel Lang + description: |- + Tests and assertions to perform frequent argument checks. A + substantial part of the package was written in C to minimize any worries + about execution time overhead. + date_publication: '2024-07-29' + bug_reports: https://github.com/mllg/checkmate/issues + url: https://mllg.github.io/checkmate/ + url_cran: https://CRAN.R-project.org/package=checkmate + url_git: https://github.com/mllg/checkmate +checkpoint: + version: 1.0.2 + title: |- + Install Packages from Snapshots on the Checkpoint Server for + Reproducibility + maintainer: Folashade Daniel + description: |- + The goal of checkpoint is to solve the problem of package + reproducibility in R. Specifically, checkpoint allows you to install packages + as they existed on CRAN on a specific snapshot date as if you had a CRAN time + machine. To achieve reproducibility, the checkpoint() function installs the + packages required or called by your project and scripts to a local library + exactly as they existed at the specified point in time. Only those packages + are available to your project, thereby avoiding any package updates that came + later and may have altered your results. In this way, anyone using checkpoint's + checkpoint() can ensure the reproducibility of your scripts or projects at any + time. To create the snapshot archives, once a day (at midnight UTC) Microsoft + refreshes the Austria CRAN mirror on the "Microsoft R Archived Network" + server (). Immediately after completion + of the rsync mirror process, the process takes a snapshot, thus creating the + archive. Snapshot archives exist starting from 2014-09-17. + date_publication: '2022-01-28' + bug_reports: https://github.com/RevolutionAnalytics/checkpoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=checkpoint + url_git: https://github.com/RevolutionAnalytics/checkpoint +checkthat: + version: 0.1.0 + title: Intuitive Unit Testing Tools for Data Manipulation + maintainer: Ian Cero + description: |- + Provides a lightweight data validation and testing toolkit for R. + Its guiding philosophy is that adding code-based data checks to users' + existing workflow should be both quick and intuitive. The suite of + functions included therefore mirror the common data checks many users + already perform by hand or by eye. Additionally, the 'checkthat' package is + optimized to work within 'tidyverse' data manipulation pipelines. + date_publication: '2023-09-12' + bug_reports: https://github.com/iancero/checkthat/issues + url: https://iancero.github.io/checkthat/ + url_cran: https://CRAN.R-project.org/package=checkthat + url_git: https://github.com/iancero/checkthat +cheddar: + version: 0.1-639 + title: Analysis and Visualisation of Ecological Communities + maintainer: Lawrence Hudson + description: Provides a flexible, extendable representation of an ecological community + and a range of functions for analysis and visualisation, focusing on food web, + body mass and numerical abundance data. Allows inter-web comparisons such as examining + changes in community structure over environmental, temporal or spatial gradients. + date_publication: '2024-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cheddar + url_git: https://github.com/quicklizard99/cheddar/ +cheem: + version: 0.4.0.0 + title: Interactively Explore Local Explanations with the Radial Tour + maintainer: Nicholas Spyrison + description: |- + Given a non-linear model, calculate the local explanation. + We purpose view the data space, explanation + space, and model residuals as ensemble graphic interactive on a shiny + application. After an observation of interest is identified, the normalized + variable importance of the local explanation is used as a 1D projection + basis. The support of the local explanation is then explored by changing + the basis with the use of the radial tour ; + . + date_publication: '2023-11-08' + bug_reports: https://github.com/nspyrison/cheem/issues + url: https://nspyrison.github.io/cheem/ + url_cran: https://CRAN.R-project.org/package=cheem + url_git: https://github.com/nspyrison/cheem/ +cheese: + version: 0.1.2 + title: Tools for Working with Data During Statistical Analysis + maintainer: Alex Zajichek + description: Contains tools for working with data during statistical analysis, promoting + flexible, intuitive, and reproducible workflows. There are functions designated + for specific statistical tasks such building a custom univariate descriptive table, + computing pairwise association statistics, etc. These are built on a collection + of data manipulation tools designed for general use that are motivated by the + functional programming concept. + date_publication: '2023-01-06' + bug_reports: '' + url: https://zajichek.github.io/cheese/ + url_cran: https://CRAN.R-project.org/package=cheese + url_git: https://github.com/zajichek/cheese/ +chem.databases: + version: 1.0.0 + title: Collection of 3 Chemical Databases from Public Sources + maintainer: Irucka Embry + description: |- + Contains the Multi-Species Acute Toxicity Database (CAS & SMILES + columns only) [United States (US) Department of Health and Human Services + (DHHS) National Institutes of Health (NIH) National Cancer Institute (NCI), + "Multi-Species Acute Toxicity Database", + ] combined with the + Toxic Substances Control Act (TSCA) Inventory [United States Environmental + Protection Agency (US EPA), "Toxic Substances Control Act (TSCA) Chemical + Substance Inventory", + ] + and the Agency for Toxic Substances and Disease Registry (ATSDR) Database + [United States (US) Department of Health and Human Services (DHHS) Centers + for Disease Control and Prevention (CDC)/Agency for Toxic Substances and + Disease Registry (ATSDR), "Agency for Toxic Substances and Disease Registry + (ATSDR) Database", + ] + in 2 data sets. One data set has a focus on the latter 2 databases and one + data set focuses on the former database. Also contains the collection of + chemical data from Wikipedia compiled in the US EPA CompTox Chemicals + Dashboard [United States Environmental Protection Agency (US EPA) / + Wikimedia Foundation, Inc. "CompTox Chemicals Dashboard v2.2.1", + ]. + date_publication: '2023-09-21' + bug_reports: https://gitlab.com/iembry/chem.databases/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chem.databases + url_git: https://gitlab.com/iembry/chem.databases +chem16S: + version: 1.2.0 + title: Chemical Metrics for Microbial Communities + maintainer: Jeffrey Dick + description: |- + Combines taxonomic classifications of high-throughput 16S rRNA + gene sequences with reference proteomes of archaeal and bacterial taxa to + generate amino acid compositions of community reference proteomes. Calculates + chemical metrics including carbon oxidation state ('Zc'), stoichiometric + oxidation and hydration state ('nO2' and 'nH2O'), H/C, N/C, O/C, and S/C + ratios, grand average of hydropathicity ('GRAVY'), isoelectric point ('pI'), + protein length, and average molecular weight of amino acid residues. Uses + precomputed reference proteomes for archaea and bacteria derived from the + Genome Taxonomy Database ('GTDB'). Also includes reference proteomes derived + from the NCBI Reference Sequence ('RefSeq') database and manual mapping from + the 'RDP Classifier' training set to 'RefSeq' taxonomy as described by Dick and + Tan (2023) . Processes taxonomic + classifications in 'RDP Classifier' format or OTU tables in 'phyloseq-class' + objects from the Bioconductor package 'phyloseq'. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chem16S + url_git: https://github.com/jedick/chem16S +chemCal: + version: 0.2.3 + title: Calibration Functions for Analytical Chemistry + maintainer: Johannes Ranke + description: |- + Simple functions for plotting linear + calibration functions and estimating standard errors for measurements + according to the Handbook of Chemometrics and Qualimetrics: Part A + by Massart et al. (1997) There are also functions estimating the limit + of detection (LOD) and limit of quantification (LOQ). + The functions work on model objects from - optionally weighted - linear + regression (lm) or robust linear regression ('rlm' from the 'MASS' package). + date_publication: '2022-04-01' + bug_reports: https://github.com/jranke/chemCal/issues + url: https://pkgdown.jrwb.de/chemCal/ + url_cran: https://CRAN.R-project.org/package=chemCal + url_git: '' +chemdeg: + version: 0.1.4 + title: Analysis of Chemical Degradation Kinetic Data + maintainer: Matteo Migliorini + description: |- + A collection of functions that have been developed to assist + experimenter in modeling chemical degradation kinetic data. The + selection of the appropriate degradation model and parameter + estimation is carried out automatically as far as possible and is + driven by a rigorous statistical interpretation of the results. The + package integrates already available goodness-of-fit statistics for + nonlinear models. In addition it allows data fitting with the + nonlinear first-order multi-target (FOMT) model. + date_publication: '2024-06-25' + bug_reports: https://github.com/migliomatte/chemdeg/issues + url: https://migliomatte.github.io/chemdeg/ + url_cran: https://CRAN.R-project.org/package=chemdeg + url_git: https://github.com/migliomatte/chemdeg +CHEMIST: + version: 0.1.5 + title: |- + Causal Inference with High-Dimensional Error-Prone Covariates + and Misclassified Treatments + maintainer: Wei-Hsin Hsu + description: |2- + + We aim to deal with the average treatment effect (ATE), where the data are + subject to high-dimensionality and measurement error. This package primarily contains two + functions, which are used to generate artificial data and estimate ATE with high-dimensional + and error-prone data accommodated. + date_publication: '2023-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CHEMIST + url_git: '' +chemodiv: + version: 0.3.0 + title: Analysing Chemodiversity of Phytochemical Data + maintainer: Hampus Petrén + description: |- + Quantify and visualise various measures of chemical diversity and + dissimilarity, for phytochemical compounds and other sets of chemical + composition data. Importantly, these measures can incorporate biosynthetic + and/or structural properties of the chemical compounds, resulting in a more + comprehensive quantification of diversity and dissimilarity. For details, + see Petrén, Köllner and Junker (2023) . + date_publication: '2023-08-17' + bug_reports: https://github.com/hpetren/chemodiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chemodiv + url_git: https://github.com/hpetren/chemodiv +chemometrics: + version: 1.4.4 + title: Multivariate Statistical Analysis in Chemometrics + maintainer: Peter Filzmoser + description: R companion to the book "Introduction to Multivariate Statistical Analysis + in Chemometrics" written by K. Varmuza and P. Filzmoser (2009). + date_publication: '2023-08-25' + bug_reports: '' + url: http://cstat.tuwien.ac.at/filz/ + url_cran: https://CRAN.R-project.org/package=chemometrics + url_git: '' +ChemoSpec: + version: 6.1.10 + title: Exploratory Chemometrics for Spectroscopy + maintainer: Bryan A. Hanson + description: |- + A collection of functions for top-down exploratory data analysis + of spectral data including nuclear magnetic resonance (NMR), infrared (IR), + Raman, X-ray fluorescence (XRF) and other similar types of spectroscopy. + Includes functions for plotting and inspecting spectra, peak alignment, + hierarchical cluster analysis (HCA), principal components analysis (PCA) and + model-based clustering. Robust methods appropriate for this type of + high-dimensional data are available. ChemoSpec is designed for structured + experiments, such as metabolomics investigations, where the samples fall into + treatment and control groups. Graphical output is formatted consistently for + publication quality plots. ChemoSpec is intended to be very user friendly and + to help you get usable results quickly. A vignette covering typical operations + is available. + date_publication: '2024-02-03' + bug_reports: https://github.com/bryanhanson/ChemoSpec/issues + url: https://bryanhanson.github.io/ChemoSpec/ + url_cran: https://CRAN.R-project.org/package=ChemoSpec + url_git: '' +ChemoSpec2D: + version: 0.5.0 + title: Exploratory Chemometrics for 2D Spectroscopy + maintainer: Bryan A. Hanson + description: A collection of functions for exploratory chemometrics of 2D spectroscopic + data sets such as COSY (correlated spectroscopy) and HSQC (heteronuclear single + quantum coherence) 2D NMR (nuclear magnetic resonance) spectra. 'ChemoSpec2D' + deploys methods aimed primarily at classification of samples and the identification + of spectral features which are important in distinguishing samples from each other. + Each 2D spectrum (a matrix) is treated as the unit of observation, and thus the + physical sample in the spectrometer corresponds to the sample from a statistical + perspective. In addition to chemometric tools, a few tools are provided for plotting + 2D spectra, but these are not intended to replace the functionality typically + available on the spectrometer. 'ChemoSpec2D' takes many of its cues from 'ChemoSpec' + and tries to create consistent graphical output and to be very user friendly. + date_publication: '2021-10-11' + bug_reports: https://github.com/bryanhanson/ChemoSpec2D/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ChemoSpec2D + url_git: https://github.com/bryanhanson/ChemoSpec2D +ChemoSpecUtils: + version: 1.0.4 + title: Functions Supporting Packages ChemoSpec and ChemoSpec2D + maintainer: Bryan A. Hanson + description: Functions supporting the common needs of packages 'ChemoSpec' and 'ChemoSpec2D'. + date_publication: '2024-01-31' + bug_reports: https://github.com/bryanhanson/ChemoSpecUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ChemoSpecUtils + url_git: https://github.com/bryanhanson/ChemoSpecUtils +ChernoffDist: + version: 0.1.0 + title: Chernoff's Distribution + maintainer: Haitian Xie + description: Computes Chernoff's distribution based on the method in Piet Groeneboom + & Jon A Wellner (2001) Computing Chernoff's Distribution, Journal of Computational + and Graphical Statistics, 10:2, 388-400, . Chernoff's + distribution is defined as the distribution of the maximizer of the two-sided + Brownian motion minus quadratic drift. That is, Z = argmax (B(t)-t^2). + date_publication: '2023-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChernoffDist + url_git: '' +cherry: + version: 0.6-15 + title: Multiple Testing Methods for Exploratory Research + maintainer: Jelle Goeman + description: |- + Provides an alternative approach to multiple testing + by calculating a simultaneous upper confidence bounds for the + number of true null hypotheses among any subset of the hypotheses of interest, + using the methods of Goeman and Solari (2011) . + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cherry + url_git: '' +cherryblossom: + version: 0.1.0 + title: Cherry Blossom Run Race Results + maintainer: Mine Çetinkaya-Rundel + description: Race results of the Cherry Blossom Run, which is an annual road race + that takes place in Washington, DC. + date_publication: '2020-06-25' + bug_reports: https://github.com/OpenIntroStat/cherryblossom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cherryblossom + url_git: https://github.com/OpenIntroStat/cherryblossom +chess: + version: 1.0.1 + title: Read, Write, Create and Explore Chess Games + maintainer: C. Lente + description: |- + This is an opinionated wrapper around the + python-chess package. It allows users to read and write PGN files as + well as create and explore game trees such as the ones seen in chess + books. + date_publication: '2020-12-04' + bug_reports: https://github.com/curso-r/chess/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chess + url_git: https://github.com/curso-r/chess +chessboard: + version: '0.1' + title: Create Network Connections Based on Chess Moves + maintainer: Nicolas Casajus + description: |- + Provides functions to work with directed (asymmetric) and + undirected (symmetric) spatial networks. It makes the creation of + connectivity matrices easier, i.e. a binary matrix of dimension n x n, where + n is the number of nodes (sampling units) indicating the presence (1) or + the absence (0) of an edge (link) between pairs of nodes. Different network + objects can be produced by 'chessboard': node list, neighbor list, edge + list, connectivity matrix. It can also produce objects that will be used + later in Moran's Eigenvector Maps (Dray et al. (2006) ) + and Asymetric Eigenvector Maps (Blanchet et al. (2008) ), + methods available in the package 'adespatial' (Dray et al. (2023) + ). This work is part of the + FRB-CESAB working group Bridge + . + date_publication: '2023-10-14' + bug_reports: https://github.com/frbcesab/chessboard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chessboard + url_git: https://github.com/frbcesab/chessboard +ChessGmooG: + version: 0.1.0 + title: FIDE Chess Players Ratings for 2015 and 2020 + maintainer: Antony Unwin + description: Datasets of the International Chess Federation's player ratings and + country information analysed in the book Antony Unwin (2024, ISBN:978-0367674007) + "Getting (more out of) Graphics". + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChessGmooG + url_git: '' +chest: + version: 0.3.7 + title: Change-in-Estimate Approach to Assess Confounding Effects + maintainer: Zhiqiang Wang + description: |- + Applies the change-in-effect estimate method to assess confounding + effects in medical and epidemiological research (Greenland & Pearce (2016) + ). It starts with a crude model + including only the outcome and exposure variables. At each of the subsequent + steps, one variable which creates the largest change among the remaining variables + is selected. This process is repeated until all variables have been entered into + the model (Wang Z. Stata Journal 2007; 7, Number 2, pp. 183–196). Currently, the 'chest' + package has functions for linear regression, logistic regression, negative + binomial regression, Cox proportional hazards model and conditional logistic + regression. + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chest + url_git: '' +ChestVolume: + version: 1.0.1 + title: Estimate the Chest Volume with Markers Data + maintainer: Wai-Hang Kwong + description: Provides tools to process and analyze chest expansion using 3D marker + data from motion capture systems. Includes functions for data processing, marker + position adjustment, volume calculation using convex hulls, and visualization + in 2D and 3D. Barber et al. (1996) . TAMIYA Hiroyuki + et al. (2021) . + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChestVolume + url_git: '' +chevron: + version: 0.2.10 + title: Standard TLGs for Clinical Trials Reporting + maintainer: Joe Zhu + description: |- + Provide standard tables, listings, and graphs (TLGs) + libraries used in clinical trials. This package implements a structure + to reformat the data with 'dunlin', create reporting tables using + 'rtables' and 'tern' with standardized input arguments to enable quick + generation of standard outputs. In addition, it also provides + comprehensive data checks and script generation functionality. + date_publication: '2025-02-20' + bug_reports: https://github.com/insightsengineering/chevron/issues + url: https://insightsengineering.github.io/chevron/ + url_cran: https://CRAN.R-project.org/package=chevron + url_git: https://github.com/insightsengineering/chevron/ +chi: + version: '0.1' + title: The Chi Distribution + maintainer: David Kahle + description: |- + Light weight implementation of the standard distribution + functions for the chi distribution, wrapping those for the chi-squared + distribution in the stats package. + date_publication: '2017-05-07' + bug_reports: https://github.com/dkahle/chi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chi + url_git: https://github.com/dkahle/chi +chicane: + version: 0.1.8 + title: Capture Hi-C Analysis Engine + maintainer: Syed Haider + description: Toolkit for processing and calling interactions in capture Hi-C data. + Converts BAM files into counts of reads linking restriction fragments, and identifies + pairs of fragments that interact more than expected by chance. Significant interactions + are identified by comparing the observed read count to the expected background + rate from a count regression model. + date_publication: '2021-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chicane + url_git: '' +childdevdata: + version: 1.1.0 + title: Child Development Data + maintainer: Stef van Buuren + description: |- + Measuring child development starts by collecting responses to + developmental milestones, such as "able to sit" or "says two words". + There are many ways to combine such responses into summaries. + The package bundles publicly available datasets with individual milestone + data for children aged 0-5 years, with the aim of supporting the construction, + evaluation, validation and interpretation of methodologies that aggregate + milestone data into informative measures of child development. + date_publication: '2021-04-15' + bug_reports: '' + url: https://d-score.org/childdevdata/ + url_cran: https://CRAN.R-project.org/package=childdevdata + url_git: https://github.com/d-score/childdevdata +childesr: + version: 0.2.3 + title: Accessing the 'CHILDES' Database + maintainer: Mika Braginsky + description: |- + Tools for connecting to 'CHILDES', an open repository for + transcripts of parent-child interaction. For more information on the + underlying data, see . + date_publication: '2022-01-27' + bug_reports: https://github.com/langcog/childesr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=childesr + url_git: https://github.com/langcog/childesr +childfree: + version: 0.0.3 + title: Access and Harmonize Childfree Demographic Data + maintainer: Zachary Neal + description: Reads demographic data from a variety of public data sources, extracting + and harmonizing variables useful for the study of childfree individuals. The identification + of childfree individuals and those with other family statuses uses Neal & Neal's + (2024) "A Framework for Studying Adults who Neither have Nor Want Children" ; + A pre-print is available at . + date_publication: '2024-09-04' + bug_reports: https://github.com/zpneal/childfree/issues + url: https://www.zacharyneal.com/childfree + url_cran: https://CRAN.R-project.org/package=childfree + url_git: https://github.com/zpneal/childfree +childsds: + version: 0.9.8 + title: Data and Methods Around Reference Values in Pediatrics + maintainer: Mandy Vogel + description: |- + Calculation of standard deviation scores and percentiles adduced from different + standards (WHO, UK, Germany, Italy, China, etc). Also, references for laboratory values in + children and adults are available, e.g., serum lipids, iron-related blood parameters, IGF, liver enzymes. See package documentation for full list. + date_publication: '2025-01-28' + bug_reports: https://git.sc.uni-leipzig.de/my221hepi/childsds/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=childsds + url_git: '' +chilemapas: + version: 0.3.0 + title: |- + Mapas de las Divisiones Politicas y Administrativas de Chile + (Maps of the Political and Administrative Divisions of Chile) + maintainer: Mauricio Vargas + description: |- + Mapas terrestres con topologias simplificadas. Estos mapas no + tienen precision geodesica, por lo que aplica el DFL-83 de 1979 de la Republica + de Chile y se consideran referenciales sin validez legal. + No se incluyen los territorios antarticos y bajo ningun evento estos mapas + significan que exista una cesion u ocupacion de territorios soberanos en + contra del Derecho Internacional por parte de Chile. Esta paquete esta + documentado intencionalmente en castellano asciificado para que funcione sin + problema en diferentes plataformas. + (Terrestrial maps with simplified toplogies. These maps lack geodesic + precision, therefore DFL-83 1979 of the Republic of Chile applies and are + considered to have no legal validity. + Antartic territories are excluded and under no event these maps mean + there is a cession or occupation of sovereign territories against International + Laws from Chile. This package was intentionally documented in asciified + spanish to make it work without problem on different platforms.) + date_publication: '2022-07-14' + bug_reports: https://github.com/pachadotdev/chilemapas/issues/ + url: https://pacha.dev/chilemapas/ + url_cran: https://CRAN.R-project.org/package=chilemapas + url_git: '' +ChillModels: + version: 1.0.2 + title: Processing Chill and Heat Models for Temperate Fruit Trees + maintainer: Rafael Henrique Pertille + description: 'Calculates the chilling and heat accumulation for studies of the temperate + fruit trees. The models in this package are: Utah (Richardson et al., 1974, ISSN:0018-5345), + Positive Chill Units - PCU (Linsley-Noaks et al., 1995, ISSN:1017-0316), GDH-A + - Growing Degree Hours by Anderson et al.(1986, ISSN:0567-7572), GDH-R - Growing + Degree Hours by Richardson et al.(1975, ISSN:0018-5345), North Carolina (Shaltout + e Unrath, 1983, ISSN:0003-1062), Landsberg Model (Landsberg, 1974, ISSN:0305-7364), + Q10 Model (Bidabe, 1967, ISSN:0031-9368), Jones Model (Jones et al., 2013 ), + Low-Chill Model (Gilreath and Buchanan, 1981, ISSN:0003-1062), Model for Cherry + "Sweetheart" (Guak and Nielsen, 2013 ), Model for + apple "Gala" (Guak and Nielsen, 2013 ), Taiwan + Model (Lu et al., 2012 ), Dynamic Model (Fishman + et al., 1987, ISSN:0022-5193) adapted from the function Dynamic_Model() of the + ''chillR'' package (Luedeling, 2018), Unified Model (Chuine et al., 2016 ) + and Heat Restriction model.' + date_publication: '2020-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChillModels + url_git: '' +chillR: + version: '0.76' + title: |- + Statistical Methods for Phenology Analysis in Temperate Fruit + Trees + maintainer: Eike Luedeling + description: |- + The phenology of plants (i.e. the timing of their annual life + phases) depends on climatic cues. For temperate trees and many other plants, + spring phases, such as leaf emergence and flowering, have been found to result + from the effects of both cool (chilling) conditions and heat. Fruit tree + scientists (pomologists) have developed some metrics to quantify chilling + and heat (e.g. see Luedeling (2012) ). + 'chillR' contains functions for processing temperature records into + chilling (Chilling Hours, Utah Chill Units and Chill Portions) and heat units + (Growing Degree Hours). Regarding chilling metrics, Chill Portions are often + considered the most promising, but they are difficult to calculate. This package + makes it easy. 'chillR' also contains procedures for conducting a PLS analysis + relating phenological dates (e.g. bloom dates) to either mean temperatures or + mean chill and heat accumulation rates, based on long-term weather and phenology + records (Luedeling and Gassner (2012) ). + As of version 0.65, it also includes functions for generating weather + scenarios with a weather generator, for conducting climate change analyses + for temperature-based climatic metrics and for plotting results from such + analyses. Since version 0.70, 'chillR' contains a function for interpolating + hourly temperature records. + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chillR + url_git: '' +chinese.misc: + version: 0.2.3 + title: Miscellaneous Tools for Chinese Text Mining and More + maintainer: Jiang Wu + description: |- + Efforts are made to make Chinese text mining easier, faster, and robust to errors. + Document term matrix can be generated by only one line of code; detecting encoding, + segmenting and removing stop words are done automatically. + Some convenient tools are also supplied. + date_publication: '2020-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chinese.misc + url_git: https://github.com/githubwwwjjj/chinese.misc/blob/master/README.md +ChineseNames: + version: '2023.8' + title: Chinese Name Database 1930-2008 + maintainer: Han-Wu-Shuang Bao + description: |2- + + A database of Chinese surnames and Chinese given names (1930-2008). + This database contains nationwide frequency statistics of + 1,806 Chinese surnames and 2,614 Chinese characters used in given names, + covering about 1.2 billion Han Chinese population + (96.8% of the Han Chinese household-registered population + born from 1930 to 2008 and still alive in 2008). + This package also contains a function for computing multiple features of + Chinese surnames and Chinese given names for scientific research (e.g., + name uniqueness, name gender, name valence, and name warmth/competence). + date_publication: '2023-08-08' + bug_reports: https://github.com/psychbruce/ChineseNames/issues + url: https://psychbruce.github.io/ChineseNames/ + url_cran: https://CRAN.R-project.org/package=ChineseNames + url_git: '' +chipPCR: + version: 1.0-2 + title: Toolkit of Helper Functions to Pre-Process Amplification Data + maintainer: Stefan Roediger + description: 'A collection of functions to pre-process amplification curve data + from polymerase chain reaction (PCR) or isothermal amplification reactions. Contains + functions to normalize and baseline amplification curves, to detect both the start + and end of an amplification reaction, several smoothers (e.g., LOWESS, moving + average, cubic splines, Savitzky-Golay), a function to detect false positive amplification + reactions and a function to determine the amplification efficiency. Quantification + point (Cq) methods include the first (FDM) and second approximate derivative maximum + (SDM) methods (calculated by a 5-point-stencil) and the cycle threshold method. + Data sets of experimental nucleic acid amplification systems (''VideoScan HCU'', + capillary convective PCR (ccPCR)) and commercial systems are included. Amplification + curves were generated by helicase dependent amplification (HDA), ccPCR or PCR. + As detection system intercalating dyes (EvaGreen, SYBR Green) and hydrolysis probes + (TaqMan) were used. For more information see: Roediger et al. (2015) .' + date_publication: '2021-03-05' + bug_reports: https://github.com/PCRuniversum/chipPCR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chipPCR + url_git: https://github.com/PCRuniversum/chipPCR +chirps: + version: 0.1.4 + title: API Client for CHIRPS and CHIRTS + maintainer: Kauê de Sousa + description: |- + API Client for the Climate Hazards Center 'CHIRPS' and 'CHIRTS'. + The 'CHIRPS' data is a quasi-global (50°S – 50°N) high-resolution + (0.05 arc-degrees) rainfall data set, which incorporates satellite imagery + and in-situ station data to create gridded rainfall time series for trend + analysis and seasonal drought monitoring. 'CHIRTS' is a quasi-global + (60°S – 70°N), high-resolution data set of daily maximum and minimum + temperatures. For more details on 'CHIRPS' and 'CHIRTS' data please visit + its official home page . + date_publication: '2022-01-13' + bug_reports: https://github.com/ropensci/chirps/issues + url: https://docs.ropensci.org/chirps/ + url_cran: https://CRAN.R-project.org/package=chirps + url_git: '' +chisq.posthoc.test: + version: 0.1.2 + title: |- + A Post Hoc Analysis for Pearson's Chi-Squared Test for Count + Data + maintainer: Daniel Ebbert + description: 'Perform post hoc analysis based on residuals of Pearson''s Chi-squared + Test for Count Data based on T. Mark Beasley & Randall E. Schumacker (1995) .' + date_publication: '2019-10-25' + bug_reports: https://github.com/ebbertd/chisq.posthoc.test/issues + url: http://chisq-posthoc-test.ebbert.nrw/ + url_cran: https://CRAN.R-project.org/package=chisq.posthoc.test + url_git: '' +chisquare: + version: 1.1.1 + title: |- + Chi-Square and G-Square Test of Independence, Power and Residual + Analysis, Measures of Categorical Association + maintainer: Gianmarco Alberti + description: Provides the facility to perform the chi-square and G-square test of + independence, calculates the retrospective power of the traditional chi-square + test, compute permutation and Monte Carlo p-value, and provides measures of association + for tables of any size such as Phi, Phi corrected, odds ratio with 95 percent + CI and p-value, Yule' Q and Y, adjusted contingency coefficient, Cramer's V, V + corrected, V standardised, bias-corrected V, W, Cohen's w, Goodman-Kruskal's lambda, + and tau. It also calculates standardised, moment-corrected standardised, and adjusted + standardised residuals, and their significance, as well as the Quetelet Index, + IJ association factor, and adjusted standardised counts. It also computes the + chi-square-maximising version of the input table. Different outputs are returned + in nicely formatted tables. + date_publication: '2024-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chisquare + url_git: '' +chk: + version: 0.10.0 + title: Check User-Supplied Function Arguments + maintainer: Joe Thorley + description: |- + For developers to check user-supplied function arguments. It + is designed to be simple, fast and customizable. Error messages + follow the tidyverse style guide. + date_publication: '2025-01-24' + bug_reports: https://github.com/poissonconsulting/chk/issues/ + url: https://poissonconsulting.github.io/chk/ + url_cran: https://CRAN.R-project.org/package=chk + url_git: https://github.com/poissonconsulting/chk +chkptstanr: + version: 0.1.1 + title: Checkpoint MCMC Sampling with 'Stan' + maintainer: Donald Williams + description: |- + Fit Bayesian models in Stan + with checkpointing, that is, the ability to stop the MCMC sampler at + will, and then pick right back up where the MCMC sampler left off. + Custom 'Stan' models can be fitted, or the popular package 'brms' + can be used to generate the 'Stan' code. This + package is fully compatible with the R packages 'brms', 'posterior', 'cmdstanr', + and 'bayesplot'. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chkptstanr + url_git: '' +chlorpromazineR: + version: 0.2.0 + title: Convert Antipsychotic Doses to Chlorpromazine Equivalents + maintainer: Eric Brown + description: |- + As different antipsychotic medications have different potencies, + the doses of different medications cannot be directly compared. Various + strategies are used to convert doses into a common reference so that + comparison is meaningful. Chlorpromazine (CPZ) has historically been used + as a reference medication into which other antipsychotic doses can be + converted, as "chlorpromazine-equivalent doses". Using conversion keys + generated from widely-cited scientific papers, e.g. Gardner et. al 2010 + and Leucht et al. 2016 + , antipsychotic doses are converted + to CPZ (or any specified antipsychotic) equivalents. The use of the package + is described in the included vignette. Not for clinical use. + date_publication: '2021-03-14' + bug_reports: https://github.com/ropensci/chlorpromazineR/issues + url: https://docs.ropensci.org/chlorpromazineR/ + url_cran: https://CRAN.R-project.org/package=chlorpromazineR + url_git: https://github.com/ropensci/chlorpromazineR +CHMM: + version: 0.1.1 + title: Coupled Hidden Markov Models + maintainer: Julie Aubert + description: |- + An exact and a variational inference for + coupled Hidden Markov Models applied to the joint detection of copy number variations. + date_publication: '2017-09-29' + bug_reports: http://github.com/julieaubert/CHMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CHMM + url_git: http://github.com/julieaubert/CHMM +CHNCapitalStock: + version: 0.1.1 + title: Compute Chinese Capital Stocks + maintainer: Pu Chen + description: Compute Chinese capital stocks in provinces level, based on Zhang (2008) + . + date_publication: '2023-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CHNCapitalStock + url_git: https://github.com/common2016/CapitalStock +chngpt: + version: 2024.11-15 + title: Estimation and Hypothesis Testing for Threshold Regression + maintainer: Youyi Fong + description: Threshold regression models are also called two-phase regression, broken-stick + regression, split-point regression, structural change models, and regression kink + models, with and without interaction terms. Methods for both continuous and discontinuous + threshold models are included, but the support for the former is much greater. + This package is described in Fong, Huang, Gilbert and Permar (2017) + and the package vignette. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chngpt + url_git: '' +CHNOSZ: + version: 2.1.0 + title: Thermodynamic Calculations and Diagrams for Geochemistry + maintainer: Jeffrey Dick + description: |- + An integrated set of tools for thermodynamic calculations in + aqueous geochemistry and geobiochemistry. Functions are provided for writing + balanced reactions to form species from user-selected basis species and for + calculating the standard molal properties of species and reactions, including + the standard Gibbs energy and equilibrium constant. Calculations of the + non-equilibrium chemical affinity and equilibrium chemical activity of species + can be portrayed on diagrams as a function of temperature, pressure, or + activity of basis species; in two dimensions, this gives a maximum affinity or + predominance diagram. The diagrams have formatted chemical formulas and axis + labels, and water stability limits can be added to Eh-pH, oxygen fugacity- + temperature, and other diagrams with a redox variable. The package has been + developed to handle common calculations in aqueous geochemistry, such as + solubility due to complexation of metal ions, mineral buffers of redox or pH, + and changing the basis species across a diagram ("mosaic diagrams"). CHNOSZ + also implements a group additivity algorithm for the standard thermodynamic + properties of proteins. + date_publication: '2024-02-11' + bug_reports: '' + url: https://www.chnosz.net/ + url_cran: https://CRAN.R-project.org/package=CHNOSZ + url_git: https://r-forge.r-project.org/projects/chnosz/ +choiceDes: + version: 0.9-3 + title: Design Functions for Choice Studies + maintainer: Jack Horne + description: Design functions for DCMs and other types of choice studies (including + MaxDiff and other tradeoffs). + date_publication: '2018-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=choiceDes + url_git: '' +ChoiceModelR: + version: 1.3.1 + title: Choice Modeling in R + maintainer: John V Colias + description: Implements an MCMC algorithm to estimate a hierarchical multinomial + logit model with a normal heterogeneity distribution. The algorithm uses a hybrid + Gibbs Sampler with a random walk metropolis step for the MNL coefficients for + each unit. Dependent variable may be discrete or continuous. Independent variables + may be discrete or continuous with optional order constraints. Means of the distribution + of heterogeneity can optionally be modeled as a linear function of unit characteristics + variables. + date_publication: '2024-10-10' + bug_reports: '' + url: https://www.decisionanalyst.com/ + url_cran: https://CRAN.R-project.org/package=ChoiceModelR + url_git: '' +CHOIRBM: + version: 0.0.2 + title: Plots the CHOIR Body Map + maintainer: Eric Cramer + description: |- + Collection of utility functions for visualizing + body map data collected with the Collaborative Health Outcomes + Information Registry. + date_publication: '2021-02-15' + bug_reports: https://github.com/emcramer/CHOIRBM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CHOIRBM + url_git: https://github.com/emcramer/CHOIRBM +cholera: + version: 0.8.0 + title: Amend, Augment and Aid Analysis of John Snow's Cholera Map + maintainer: Peter Li + description: |- + Amends errors, augments data and aids analysis of John Snow's map + of the 1854 London cholera outbreak. + date_publication: '2023-03-01' + bug_reports: https://github.com/lindbrook/cholera/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cholera + url_git: https://github.com/lindbrook/cholera +CholWishart: + version: 1.1.4 + title: Cholesky Decomposition of the Wishart Distribution + maintainer: Geoffrey Thompson + description: |- + Sampling from the Cholesky factorization of a Wishart random + variable, sampling from the inverse Wishart distribution, sampling from + the Cholesky factorization of an inverse Wishart random variable, sampling + from the pseudo Wishart distribution, sampling from the generalized + inverse Wishart distribution, computing densities for the Wishart + and inverse Wishart distributions, and computing the multivariate gamma + and digamma functions. Provides a header file so the C functions can be + called directly from other programs. + date_publication: '2024-09-30' + bug_reports: https://github.com/gzt/CholWishart/issues + url: https://gzt.github.io/CholWishart/ + url_cran: https://CRAN.R-project.org/package=CholWishart + url_git: '' +chooseGCM: + version: 1.0.2 + title: |- + Selecting General Circulation Models for Species Distribution + Modeling + maintainer: Luíz Esser + description: |- + Methods to help selecting General Circulation Models (GCMs) + in the context of projecting models to future scenarios. It is provided + clusterization algorithms, distance and correlation metrics, as well as + a tailor-made algorithm to detect the optimum subset of GCMs that recreate + the environment of all GCMs as proposed in Esser et al. (2025) . + date_publication: '2025-01-16' + bug_reports: https://github.com/luizesser/chooseGCM/issues + url: https://luizesser.github.io/chooseGCM/ + url_cran: https://CRAN.R-project.org/package=chooseGCM + url_git: https://github.com/luizesser/chooseGCM +choosepc: + version: '1.0' + title: |- + Choose the Number of Principal Components via Recistruction + Error + maintainer: Michail Tsagris + description: 'One way to choose the number of principal components is via the reconstruction + error. This package is designed mainly for this purpose. Graphical representation + is also supported, plus some other principal component analysis related functions. + References include: Jolliffe I.T. (2002). Principal Component Analysis. + and Mardia K.V., Kent J.T. and Bibby J.M. (1979). Multivariate Analysis. ISBN: + 978-0124712522. London: Academic Press.' + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=choosepc + url_git: '' +choplump: + version: 1.1.2 + title: Permutation Test for Some Positive and Many Zero Responses + maintainer: Michael P. Fay + description: Calculates permutation tests that can be powerful for comparing two + groups with some positive but many zero responses (see Follmann, Fay, and Proschan + ). + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=choplump + url_git: '' +chopthin: + version: 0.2.2 + title: The Chopthin Resampler + maintainer: Axel Gandy + description: |- + Resampling is a standard step in particle filtering and in + sequential Monte Carlo. This package implements the chopthin resampler, which + keeps a bound on the ratio between the largest and the smallest weights after + resampling. + date_publication: '2017-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chopthin + url_git: '' +ChoR: + version: 0.0-4 + title: Chordalysis R Package + maintainer: Matthieu Herrmann + description: |2- + + Learning the structure of graphical models from datasets with thousands of variables. + More information about the research papers detailing the theory behind Chordalysis is available at + (KDD 2016, SDM 2015, ICDM 2014, ICDM 2013). + The R package development site is . + date_publication: '2018-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ChoR + url_git: '' +chords: + version: 0.95.4 + title: Estimation in Respondent Driven Samples + maintainer: Jonathan Rosenblatt + description: Maximum likelihood estimation in respondent driven samples. + date_publication: '2017-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chords + url_git: '' +chores: + version: 0.1.0 + title: A Collection of Large Language Model Assistants + maintainer: Simon Couch + description: |- + Provides a collection of ergonomic large language model assistants + designed to help you complete repetitive, hard-to-automate tasks quickly. + After selecting some code, press the keyboard shortcut you've chosen to + trigger the package app, select an assistant, and watch your chore be + carried out. While the package ships with a number of chore helpers for R + package development, users can create custom helpers just by writing some + instructions in a markdown file. + date_publication: '2025-02-21' + bug_reports: https://github.com/simonpcouch/chores/issues + url: https://simonpcouch.github.io/chores/ + url_cran: https://CRAN.R-project.org/package=chores + url_git: https://github.com/simonpcouch/chores +choroplethrAdmin1: + version: 1.1.1 + title: Contains an Administrative-Level-1 Map of the World + maintainer: Ari Lamstein + description: |- + Contains an administrative-level-1 map of the world. + Administrative-level-1 is the generic term for the largest sub-national + subdivision of a country. This package was created for use with the + choroplethr package. + date_publication: '2017-02-22' + bug_reports: '' + url: http://www.arilamstein.com/open-source + url_cran: https://CRAN.R-project.org/package=choroplethrAdmin1 + url_git: '' +choroplethrMaps: + version: 1.0.1 + title: Contains Maps Used by the 'choroplethr' Package + maintainer: Ari Lamstein + description: |- + Contains 3 maps. 1) US States 2) US Counties 3) Countries of the + world. + date_publication: '2017-01-31' + bug_reports: '' + url: http://www.arilamstein.com/open-source + url_cran: https://CRAN.R-project.org/package=choroplethrMaps + url_git: '' +chouca: + version: 0.1.99 + title: A Stochastic Cellular Automaton Engine + maintainer: Alexandre Genin + description: |- + An engine for stochastic cellular automata. It provides a high-level + interface to declare a model, which can then be simulated by various backends + (Genin et al. (2023) ). + date_publication: '2024-03-07' + bug_reports: https://github.com/alexgenin/chouca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chouca + url_git: https://github.com/alexgenin/chouca +christmas: + version: 1.4.0 + title: Generation of Different Animated Christmas Cards + maintainer: Jose Barrera-Gomez + description: |- + Generation of different Christmas cards, most of them being + animated. Most of the cards can be generated in three languages (English, + Catalan and Spanish). The collection started in 2009. + date_publication: '2024-12-10' + bug_reports: '' + url: https://sites.google.com/view/josebarrera/ + url_cran: https://CRAN.R-project.org/package=christmas + url_git: '' +chromConverter: + version: 0.2.1 + title: Chromatographic File Converter + maintainer: Ethan Bass + description: Reads chromatograms from binary formats into R objects. Currently supports + conversion of 'Agilent ChemStation', 'Agilent MassHunter', and 'ThermoRaw' files + as well as various text-based formats. Utilizes file parsers from external libraries, + such as 'Aston' , 'Entab' , + and 'ThermoRawFileParser' . + date_publication: '2022-07-11' + bug_reports: https://github.com/ethanbass/chromConverter/issues + url: https://ethanbass.github.io/chromConverter/ + url_cran: https://CRAN.R-project.org/package=chromConverter + url_git: https://github.com/ethanbass/chromConverter +chromer: + version: '0.8' + title: Interface to Chromosome Counts Database API + maintainer: Karl W Broman + description: |- + A programmatic interface to the Chromosome Counts Database + (), Rice et al. (2014) . + This package is part of the 'ROpenSci' suite (). + date_publication: '2024-03-27' + bug_reports: https://github.com/ropensci/chromer/issues + url: https://docs.ropensci.org/chromer/ + url_cran: https://CRAN.R-project.org/package=chromer + url_git: https://github.com/ropensci/chromer +chromoMap: + version: 4.1.1 + title: Interactive Genomic Visualization of Biological Data + maintainer: Lakshay Anand + description: |- + Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions + of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces + a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data + associated with chromosome elements (like gene expression) in the form of heat colors which can be highly + advantageous in the scientific interpretations and research work. Because of the large size of the chromosomes, + it is impractical to visualize each element on the same plot. However, the plot provides a magnified view for each + of chromosome locus to render additional information and visualization specific for that location. You can map + thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings + (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the + chromosome at a location showing each mapped element in sequential order. The package provide multiple features + like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. + The plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R 'Shiny' applications. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chromoMap + url_git: '' +chromote: + version: 0.4.0 + title: Headless Chrome Web Browser Interface + maintainer: Winston Chang + description: |- + An implementation of the 'Chrome DevTools Protocol', for + controlling a headless Chrome web browser. + date_publication: '2025-01-25' + bug_reports: https://github.com/rstudio/chromote/issues + url: https://rstudio.github.io/chromote/ + url_cran: https://CRAN.R-project.org/package=chromote + url_git: https://github.com/rstudio/chromote +chromseq: + version: 0.1.3 + title: Split Chromosome 'Fasta' File + maintainer: Shaoqian Ma + description: |- + Chromosome files in the 'Fasta' format usually contain large sequences like human genome. + Sometimes users have to split these chromosomes into different files according to their + chromosome number. The 'chromseq' can help to handle this. So the selected chromosome sequence can be + used for downstream analysis like motif finding. Howard Y. Chang(2019) + . + date_publication: '2020-05-11' + bug_reports: https://github.com/MSQ-123/chromseq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chromseq + url_git: https://github.com/MSQ-123/chromseq +chron: + version: 2.3-62 + title: Chronological Objects which Can Handle Dates and Times + maintainer: Kurt Hornik + description: Provides chronological objects which can handle dates and times. + date_publication: '2024-12-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chron + url_git: '' +chronicle: + version: '0.3' + title: Grammar for Creating R Markdown Reports + maintainer: Philippe Heymans Smith + description: A system for creating R Markdown reports with a sequential syntax. + date_publication: '2021-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chronicle + url_git: '' +chronicler: + version: 0.2.2 + title: Add Logging to Functions + maintainer: Bruno Rodrigues + description: |- + Decorate functions to make them return enhanced output. The enhanced output consists in an object of type + 'chronicle' containing the result of the function applied to its arguments, as well as a log detailing when the function + was run, what were its inputs, what were the errors (if the function failed to run) and other useful information. + Tools to handle decorated functions are included, such as a forward pipe operator that makes chaining decorated functions possible. + date_publication: '2024-03-20' + bug_reports: https://github.com/b-rodrigues/chronicler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chronicler + url_git: '' +chronochrt: + version: 0.1.3 + title: Creating Chronological Charts + maintainer: Thomas Rose + description: Easy way to draw chronological charts from tables, aiming to include + an intuitive environment for anyone new to R. Includes 'ggplot2' geoms and theme + for chronological charts. + date_publication: '2024-01-14' + bug_reports: https://gitlab.com/archaeothommy/chronochrt/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chronochrt + url_git: https://gitlab.com/archaeothommy/chronochrt +chronosphere: + version: 0.6.1 + title: Evolving Earth System Variables + maintainer: Adam T. Kocsis + description: The implemented functions allow the query, download, and import of + remotely-stored and version-controlled data items. The inherent meta-database + maps data files and import code to programming classes and allows access to these + items via files deposited in public repositories. The purpose of the project is + to increase reproducibility and establish version tracking of results from (paleo)environmental/ecological + research. + date_publication: '2023-08-17' + bug_reports: https://github.com/chronosphere-info/r_client/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chronosphere + url_git: '' +chunked: + version: 0.6.0 + title: Chunkwise Text-File Processing for 'dplyr' + maintainer: Edwin de Jonge + description: |- + Data stored in text file can be processed chunkwise using 'dplyr' commands. These + are recorded and executed per data chunk, so large files can be processed with + limited memory using the 'LaF' package. + date_publication: '2022-03-07' + bug_reports: https://github.com/edwindj/chunked/issues + url: '' + url_cran: https://CRAN.R-project.org/package=chunked + url_git: https://github.com/edwindj/chunked +chunkhooks: + version: 0.0.1 + title: Chunk Hooks for 'R Markdown' + maintainer: Atsushi Yasumoto + description: |2- + + Set chunk hooks for 'R Markdown' documents , + and improve user experience. + For example, change units of figure sizes, benchmark chunks, and number + lines on code blocks. + date_publication: '2020-08-05' + bug_reports: '' + url: https://chunkhooks.atusy.net + url_cran: https://CRAN.R-project.org/package=chunkhooks + url_git: https://github.com/atusy/chunkhooks +chunkR: + version: 1.1.1 + title: Read Tables in Chunks + maintainer: Leandro Roser + description: Read tables chunk by chunk using a C++ backend and a simple R interface. + date_publication: '2018-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chunkR + url_git: '' +chyper: + version: 0.3.1 + title: Functions for Conditional Hypergeometric Distributions + maintainer: William Nickols + description: 'An implementation of the probability mass function, cumulative density + function, quantile function, random number generator, maximum likelihood estimator, + and p-value generator from a conditional hypergeometric distribution: the distribution + of how many items are in the overlap of all samples when samples of arbitrary + size are each taken without replacement from populations of arbitrary size.' + date_publication: '2021-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=chyper + url_git: '' +cia: + version: 1.0.0 + title: Learn and Apply Directed Acyclic Graphs for Causal Inference + maintainer: Mathew Varidel + description: Causal Inference Assistance (CIA) for performing causal inference within + the structural causal modelling framework. Structure learning is performed using + partition Markov chain Monte Carlo (Kuipers & Moffa, 2017) and several additional + functions have been added to help with causal inference. Kuipers and Moffa (2017) + . + date_publication: '2024-11-13' + bug_reports: https://github.com/SpaceOdyssey/cia/issues + url: https://spaceodyssey.github.io/cia/ + url_cran: https://CRAN.R-project.org/package=cia + url_git: '' +CIAAWconsensus: + version: '1.3' + title: Isotope Ratio Meta-Analysis + maintainer: Juris Meija + description: Calculation of consensus values for atomic weights, isotope amount + ratios, and isotopic abundances with the associated uncertainties using multivariate + meta-regression approach for consensus building. + date_publication: '2018-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIAAWconsensus + url_git: '' +CIARA: + version: 0.1.0 + title: Cluster Independent Algorithm for Rare Cell Types Identification + maintainer: Gabriele Lubatti + description: Identification of markers of rare cell types by looking at genes whose + expression is confined in small regions of the expression space . + date_publication: '2022-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIARA + url_git: '' +CICA: + version: 1.1.1 + title: Clusterwise Independent Component Analysis + maintainer: Jeffrey Durieux + description: Clustering multi-subject resting state functional Magnetic Resonance + Imaging data. This methods enables the clustering of subjects based on multi-subject + resting state functional Magnetic Resonance Imaging data. Objects are clustered + based on similarities and differences in cluster-specific estimated components + obtained by Independent Component Analysis. + date_publication: '2024-07-14' + bug_reports: '' + url: https://www.sciencedirect.com/science/article/pii/S0165027022002448 + url_cran: https://CRAN.R-project.org/package=CICA + url_git: '' +ciCalibrate: + version: 0.42.2 + title: Calibration of Confidence Intervals to Support Intervals + maintainer: Samuel Pawel + description: Provides functionality for computing support intervals for univariate + parameters based on confidence intervals or parameter estimates with standard + errors (Pawel et al., 2022) . + date_publication: '2023-04-26' + bug_reports: https://github.com/SamCH93/ciCalibrate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ciCalibrate + url_git: https://github.com/SamCH93/ciCalibrate +ciccr: + version: 0.3.0 + title: Causal Inference in Case-Control and Case-Population Studies + maintainer: Sokbae Lee + description: |- + Estimation and inference methods for causal relative and attributable risk in case-control and case-population studies + under the monotone treatment response and monotone treatment selection assumptions. + For more details, see the paper by Jun and Lee (2023), + "Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," , + accepted for publication in Journal of Business & Economic Statistics. + date_publication: '2023-10-20' + bug_reports: https://github.com/sokbae/ciccr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ciccr + url_git: https://github.com/sokbae/ciccr/ +cicerone: + version: 1.0.4 + title: Provide Tours of 'Shiny' Applications + maintainer: John Coene + description: Provide step by step guided tours of 'Shiny' applications. + date_publication: '2021-01-10' + bug_reports: https://github.com/JohnCoene/cicerone/issues + url: https://cicerone.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=cicerone + url_git: '' +CICI: + version: 0.9.4 + title: |- + Causal Inference with Continuous (Multiple Time Point) + Interventions + maintainer: Michael Schomaker + description: Estimation of counterfactual outcomes for multiple values of continuous + interventions at different time points, and plotting of causal dose-response curves. + Details are given in Schomaker, McIlleron, Denti, Diaz (2024) . + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CICI + url_git: '' +CIDER: + version: 0.99.4 + title: Meta-Clustering for scRNA-Seq Integration and Evaluation + maintainer: Zhiyuan Hu + description: |- + A workflow of (a) meta-clustering based on + inter-group similarity measures and (b) a ground-truth-free test metric to + assess the biological correctness of integration in real datasets. See Hu Z, + Ahmed A, Yau C (2021) for + more details. + date_publication: '2025-02-07' + bug_reports: https://github.com/zhiyuan-hu-lab/CIDER/issues + url: https://zhiyuan-hu-lab.github.io/CIDER/ + url_cran: https://CRAN.R-project.org/package=CIDER + url_git: https://github.com/zhiyuan-hu-lab/CIDER +CIEE: + version: 0.1.1 + title: |- + Estimating and Testing Direct Effects in Directed Acyclic Graphs + using Estimating Equations + maintainer: Stefan Konigorski + description: In many studies across different disciplines, detailed measures of + the variables of interest are available. If assumptions can be made regarding + the direction of effects between the assessed variables, this has to be considered + in the analysis. The functions in this package implement the novel approach CIEE + (causal inference using estimating equations; Konigorski et al., 2018, ) + for estimating and testing the direct effect of an exposure variable on a primary + outcome, while adjusting for indirect effects of the exposure on the primary outcome + through a secondary intermediate outcome and potential factors influencing the + secondary outcome. The underlying directed acyclic graph (DAG) of this considered + model is described in the vignette. CIEE can be applied to studies in many different + fields, and it is implemented here for the analysis of a continuous primary outcome + and a time-to-event primary outcome subject to censoring. CIEE uses estimating + equations to obtain estimates of the direct effect and robust sandwich standard + error estimates. Then, a large-sample Wald-type test statistic is computed for + testing the absence of the direct effect. Additionally, standard multiple regression, + regression of residuals, and the structural equation modeling approach are implemented + for comparison. + date_publication: '2018-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIEE + url_git: '' +cif: + version: 0.1.1 + title: Cointegrated ICU Forecasting + maintainer: Paolo Paruolo + description: Set of forecasting tools to predict ICU beds using a Vector Error Correction + model with a single cointegrating vector. Method described in Berta, P. Lovaglio, + P.G. Paruolo, P. Verzillo, S., 2020. "Real Time Forecasting of Covid-19 Intensive + Care Units demand" Health, Econometrics and Data Group (HEDG) Working Papers 20/16, + HEDG, Department of Economics, University of York, . + date_publication: '2022-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cif + url_git: '' +CIfinder: + version: 2.0.0 + title: Estimate the Confidence Intervals for Predictive Values + maintainer: Dadong Zhang + description: 'Computes confidence intervals for the positive predictive value (PPV) + and negative predictive value (NPV) based on varied scenarios. In situations where + the proportion of diseased subjects does not correspond to the disease prevalence + (e.g. case-control studies), this package provides two types of solutions: 1) + five methods for estimating confidence intervals for PPV and NPV via ratio of + two binomial proportions including Gart & Nam (1988), Walter (1975), MOVER-J (Laud, + 2017), Fieller (1954), and Bootstrap (Efron, 1979); 2) three direct methods that + compute the confidence intervals including Pepe (2003), Zhou (2007), and Delta. + In prospective studies where the proportion of diseased subjects is an unbiased + estimate of the disease prevalence, this package provides several methods for + calculating the confidence intervals for PPV and NPV including Clopper-Pearson, + Wald, Wilson, Agresti-Coull, and Beta. See the Details and References sections + in the corresponding functions.' + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIfinder + url_git: '' +cifti: + version: 0.4.5 + title: |- + Toolbox for Connectivity Informatics Technology Initiative + ('CIFTI') Files + maintainer: John Muschelli + description: |- + Functions for the input/output and visualization of + medical imaging data in the form of 'CIFTI' files + . + date_publication: '2018-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cifti + url_git: '' +ciftiTools: + version: 0.17.4 + title: Tools for Reading, Writing, Viewing and Manipulating CIFTI Files + maintainer: Amanda Mejia + description: |- + CIFTI files contain brain imaging data in "grayordinates," which + represent the gray matter as cortical surface vertices (left and right) and + subcortical voxels (cerebellum, basal ganglia, and other deep gray matter). + 'ciftiTools' provides a unified environment for reading, writing, + visualizing and manipulating CIFTI-format data. It supports the "dscalar," + "dlabel," and "dtseries" intents. Grayordinate data is read in as a "xifti" + object, which is structured for convenient access to the data and metadata, + and includes support for surface geometry files to enable + spatially-dependent functionality such as static or interactive + visualizations and smoothing. + date_publication: '2025-01-23' + bug_reports: https://github.com/mandymejia/ciftiTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ciftiTools + url_git: https://github.com/mandymejia/ciftiTools +CIM: + version: 1.0.0 + title: Compositional Impact of Migration + maintainer: Nikos Patias + description: |- + Produces statistical indicators of the impact of migration on the socio-demographic + composition of an area. Three measures can be used: ratios, percentages and the Duncan index + of dissimilarity. The input data files are assumed to be in an origin-destination matrix format, + with each cell representing a flow count between an origin and a destination area. Columns are expected + to represent origins, and rows are expected to represent destinations. The first row and column are + assumed to contain labels for each area. See Rodriguez-Vignoli and Rowe (2018) + for technical details. + date_publication: '2019-01-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIM + url_git: '' +cimir: + version: 0.4-1 + title: Interface to the CIMIS Web API + maintainer: Michael Koohafkan + description: |- + Connect to the California Irrigation Management + Information System (CIMIS) Web API. See the CIMIS main page + and web API documentation + for more information. + date_publication: '2021-02-17' + bug_reports: https://github.com/mkoohafkan/cimir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cimir + url_git: https://github.com/mkoohafkan/cimir +CIMPLE: + version: 0.1.0 + title: |- + Analysis of Longitudinal Electronic Health Record (EHR) Data + with Possibly Informative Observational Time + maintainer: Howard Baik + description: Analyzes longitudinal Electronic Health Record (EHR) data with possibly + informative observational time. These methods are grouped into two classes depending + on the inferential task. One group focuses on estimating the effect of an exposure + on a longitudinal biomarker while the other group assesses the impact of a longitudinal + biomarker on time-to-diagnosis outcomes. The accompanying paper is Du et al (2024) + . + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIMPLE + url_git: '' +CIMTx: + version: 1.2.0 + title: Causal Inference for Multiple Treatments with a Binary Outcome + maintainer: Jiayi Ji + description: Different methods to conduct causal inference for multiple treatments + with a binary outcome, including regression adjustment, vector matching, Bayesian + additive regression trees, targeted maximum likelihood and inverse probability + of treatment weighting using different generalized propensity score models such + as multinomial logistic regression, generalized boosted models and super learner. + For more details, see the paper by Hu et al. . + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIMTx + url_git: '' +cinaR: + version: 0.2.3 + title: A Computational Pipeline for Bulk 'ATAC-Seq' Profiles + maintainer: Onur Karakaslar + description: |- + Differential analyses and Enrichment pipeline for bulk 'ATAC-seq' data + analyses. This package combines different packages to have an ultimate package + for both data analyses and visualization of 'ATAC-seq' data. Methods are described in + 'Karakaslar et al.' (2021) . + date_publication: '2022-05-18' + bug_reports: https://github.com/eonurk/cinaR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=cinaR + url_git: https://github.com/eonurk/cinaR/ +cinaRgenesets: + version: 0.1.1 + title: Ready-to-Use Curated Gene Sets for 'cinaR' + maintainer: Onur Karakaslar + description: Immune related gene sets provided along with the 'cinaR' package. + date_publication: '2021-01-22' + bug_reports: https://github.com/eonurk/cinaR-genesets/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=cinaRgenesets + url_git: https://github.com/eonurk/cinaR-genesets +CINE: + version: 0.1.3 + title: Classification International Normalized of Education + maintainer: Jorge L. C. Musaja + description: Function using lemmatization to classify educational programs according + to the CINE(Classification International Normalized of Education) for Peru. + date_publication: '2022-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CINE + url_git: https://github.com/musajajorge/CINE +CINID: + version: 1.3-0 + title: Curculionidae INstar IDentification + maintainer: Aurelie Siberchicot + description: Method for identifying the instar of Curculionid larvae from the observed + distribution of the headcapsule size of mature larvae. + date_publication: '2020-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CINID + url_git: '' +CINmetrics: + version: 0.1.0 + title: Calculate Chromosomal Instability Metrics + maintainer: Vishal H. Oza + description: |- + Implement various chromosomal instability metrics. 'CINmetrics' (Chromosomal INstability metrics) provides functions to + calculate various chromosomal instability metrics on masked Copy Number Variation(CNV) data at individual sample level. The + chromosomal instability metrics have been implemented as described in the following studies: + Baumbusch LO et al. 2013 , + Davidson JM et al. 2014 , + Chin SF et al. 2007 . + date_publication: '2021-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CINmetrics + url_git: '' +CINNA: + version: 1.2.2 + title: Deciphering Central Informative Nodes in Network Analysis + maintainer: Minoo Ashtiani + description: 'Computing, comparing, and demonstrating top informative centrality + measures within a network. "CINNA: an R/CRAN package to decipher Central Informative + Nodes in Network Analysis" provides a comprehensive overview of the package functionality + Ashtiani et al. (2018) .' + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CINNA + url_git: '' +cinterpolate: + version: 1.0.2 + title: Interpolation From C + maintainer: Rich FitzJohn + description: |- + Simple interpolation methods designed to be used from C + code. Supports constant, linear and spline interpolation. An R + wrapper is included but this package is primarily designed to be + used from C code using 'LinkingTo'. The spline calculations are + classical cubic interpolation, e.g., Forsythe, Malcolm and Moler + (1977) . + date_publication: '2024-09-13' + bug_reports: https://github.com/mrc-ide/cinterpolate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cinterpolate + url_git: https://github.com/mrc-ide/cinterpolate +CIPerm: + version: 0.2.3 + title: |- + Computationally-Efficient Confidence Intervals for Mean Shift + from Permutation Methods + maintainer: Jerzy Wieczorek + description: |- + Implements computationally-efficient construction of + confidence intervals from permutation or randomization tests + for simple differences in means, + based on Nguyen (2009) . + date_publication: '2022-06-21' + bug_reports: https://github.com/ColbyStatSvyRsch/CIPerm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CIPerm + url_git: https://github.com/ColbyStatSvyRsch/CIPerm/ +cipheR: + version: 1.0.0 + title: Encryption and Decryption with Text Ciphers + maintainer: Gus Lipkin + description: |- + Encrypts and decrypts using basic ciphers. None of + these should be used in place of real encryption using state of the art tools. + The ciphers included use methods described in the ciphers's Wikipedia and + cryptography hobby websites. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cipheR + url_git: '' +ciphertext: + version: 0.1.1 + title: Classical Cryptography Methods for Words and Phrases + maintainer: Luigi Annicchiarico + description: |- + Classical cryptography methods for words and brief phrases. + Substitution, transposition and concealment (null) ciphers are available, like + Caesar, Vigenère, Atbash, affine, simple substitution, Playfair, + rail fence, Scytale, single column, bifid, trifid, and Polybius ciphers. + date_publication: '2025-01-10' + bug_reports: https://github.com/Luigi-Annic/ciphertext/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ciphertext + url_git: https://github.com/Luigi-Annic/ciphertext +CIplot: + version: '1.0' + title: Functions to Plot Confidence Interval + maintainer: Toshiaki Ara + description: |- + Plot confidence interval from the objects of statistical tests such as + t.test(), var.test(), cor.test(), prop.test() and fisher.test() ('htest' class), + Tukey test [TukeyHSD()], Dunnett test [glht() in 'multcomp' package], + logistic regression [glm()], and Tukey or Games-Howell test [posthocTGH() in + 'userfriendlyscience' package]. + Users are able to set the styles of lines and points. + This package contains the function to calculate odds ratios and their confidence + intervals from the result of logistic regression. + date_publication: '2017-08-14' + bug_reports: https://github.com/toshi-ara/CIplot/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=CIplot + url_git: https://github.com/toshi-ara/CIplot +CIpostSelect: + version: 0.2.1 + title: Confidence Interval Post-Selection of Variable + maintainer: Boubacar DIALLO + description: Calculates confidence intervals after variable selection using repeated + data splits. The package offers methods to address the challenges of post-selection + inference, ensuring more accurate confidence intervals in models involving variable + selection. The two main functions are 'lmps', which records the different models + selected across multiple data splits as well as the corresponding coefficient + estimates, and 'cips', which takes the lmps object as input to select variables + and perform inferences using two types of voting. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIpostSelect + url_git: '' +cir: + version: 2.5.1 + title: Centered Isotonic Regression and Dose-Response Utilities + maintainer: Assaf P. Oron + description: 'Isotonic regression (IR) and its improvement: centered isotonic regression + (CIR). CIR is recommended in particular with small samples. Also, interval estimates + for both, and additional utilities such as plotting dose-response data. For dev + version and change history, see GitHub assaforon/cir.' + date_publication: '2025-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cir + url_git: '' +circacompare: + version: 0.2.0 + title: Analyses of Circadian Data + maintainer: Rex Parsons + description: |- + Uses non-linear regression to statistically compare two circadian rhythms. + Groups are only compared if both are rhythmic (amplitude is non-zero). + Performs analyses regarding mesor, phase, and amplitude, reporting on estimates and statistical differences, for each, between groups. + Details can be found in Parsons et al (2020) . + date_publication: '2024-01-09' + bug_reports: '' + url: https://rwparsons.github.io/circacompare/ + url_cran: https://CRAN.R-project.org/package=circacompare + url_git: '' +CirceR: + version: 1.3.3 + title: Construct Cohort Inclusion and Restriction Criteria Expressions + maintainer: Chris Knoll + description: |- + Wraps the 'CIRCE' () 'Java' + library allowing cohort definition expressions to be edited and converted to + 'Markdown' or 'SQL'. + date_publication: '2024-04-18' + bug_reports: https://github.com/OHDSI/CirceR/issues/ + url: https://ohdsi.github.io/CirceR/ + url_cran: https://CRAN.R-project.org/package=CirceR + url_git: https://github.com/OHDSI/CirceR/ +circhelp: + version: '1.1' + title: Circular Analyses Helper Functions + maintainer: Andrey Chetverikov + description: Light-weight functions for computing descriptive statistics in different + circular spaces (e.g., 2pi, 180, or 360 degrees), to handle angle-dependent biases, + pad circular data, and more. Specifically aimed for psychologists and neuroscientists + analyzing circular data. Basic methods are based on Jammalamadaka and SenGupta + (2001) , removal of cardinal biases is based on the approach + introduced in van Bergen, Ma, Pratte, & Jehee (2015) and + Chetverikov and Jehee (2023) . + date_publication: '2024-07-04' + bug_reports: https://github.com/achetverikov/circhelp/issues + url: https://achetverikov.github.io/circhelp/index.html + url_cran: https://CRAN.R-project.org/package=circhelp + url_git: https://github.com/achetverikov/circhelp +circle: + version: 0.7.3 + title: R Client Package for Circle CI + maintainer: Patrick Schratz + description: |- + Tools for interacting with the 'Circle CI' API + (). Besides executing common tasks + such as querying build logs and restarting builds, this package also + helps setting up permissions to deploy from builds. + date_publication: '2024-07-31' + bug_reports: https://github.com/ropensci/circle/issues + url: https://docs.ropensci.org/circle/ + url_cran: https://CRAN.R-project.org/package=circle + url_git: https://github.com/ropensci/circle +CirclesIntersections: + version: '1.1' + title: Algorithm for Computation of the Intersection Areas of N Circles + maintainer: Hugo Salinas + description: |- + Implementation of Librino, Levorato, and Zorzi (2014) + algorithm for computation of the intersection areas of an arbitrary number of circles. + date_publication: '2023-02-23' + bug_reports: https://github.com/hugosal/CirclesIntersections/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CirclesIntersections + url_git: https://github.com/hugosal/CirclesIntersections +circlesplot: + version: 1.1.0 + title: Visualize Proportions with Circles in a Plot + maintainer: BenSt099 + description: |- + Method for visualizing proportions between objects of different sizes. + The proportions are drawn as circles with different diameters, which makes them ideal + for visualizing proportions between planets. + date_publication: '2024-02-20' + bug_reports: https://github.com/BenSt099/circlesplot/issues + url: https://benst099.github.io/circlesplot/ + url_cran: https://CRAN.R-project.org/package=circlesplot + url_git: https://github.com/BenSt099/circlesplot +circletyper: + version: 1.0.2 + title: Curve Text Elements in 'Shiny' Using 'CircleType.js' + maintainer: Etienne Bacher + description: Enables curving text elements in 'Shiny' apps. + date_publication: '2022-09-21' + bug_reports: https://github.com/etiennebacher/circletyper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=circletyper + url_git: https://github.com/etiennebacher/circletyper +circlize: + version: 0.4.16 + title: Circular Visualization + maintainer: Zuguang Gu + description: |- + Circular layout is an efficient way for the visualization of huge + amounts of information. Here this package provides an implementation + of circular layout generation in R as well as an enhancement of available + software. The flexibility of the package is based on the usage of low-level + graphics functions such that self-defined high-level graphics can be easily + implemented by users for specific purposes. Together with the seamless + connection between the powerful computational and visual environment in R, + it gives users more convenience and freedom to design figures for + better understanding complex patterns behind multiple dimensional data. + The package is described in Gu et al. 2014 . + date_publication: '2024-02-20' + bug_reports: '' + url: https://jokergoo.github.io/circlize_book/book/ + url_cran: https://CRAN.R-project.org/package=circlize + url_git: https://github.com/jokergoo/circlize +circlus: + version: 0.0.2 + title: Clustering and Simulation of Spherical Cauchy and PKBD Models + maintainer: Lukas Sablica + description: Provides tools for estimation and clustering of spherical data, seamlessly + integrated with the 'flexmix' package. Includes the necessary M-step implementations + for both Poisson Kernel-Based Distribution (PKBD) and spherical Cauchy distribution. + Additionally, the package provides random number generators for PKBD and spherical + Cauchy distribution. Methods are based on Golzy M., Markatou M. (2020) , + Kato S., McCullagh P. (2020) and Sablica L., Hornik K., + Leydold J. (2023) . + date_publication: '2025-02-19' + bug_reports: https://github.com/lsablica/circlus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=circlus + url_git: https://github.com/lsablica/circlus +CircMLE: + version: 0.3.0 + title: Maximum Likelihood Analysis of Circular Data + maintainer: Robert Fitak + description: |- + A series of wrapper functions to + implement the 10 maximum likelihood models of animal orientation + described by Schnute and Groot (1992) . The + functions also include the ability to use different optimizer + methods and calculate various model selection metrics (i.e., AIC, + AICc, BIC). The ability to perform variants of the Hermans-Rasson test and + Pycke test is also included as described in Landler et al. (2019) + . The latest version also includes a new + method to calculate circular-circular and circular-linear distance correlations. + date_publication: '2020-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircMLE + url_git: '' +CircNNTSR: + version: '2.3' + title: |- + Statistical Analysis of Circular Data using Nonnegative + Trigonometric Sums (NNTS) Models + maintainer: Maria Mercedes Gregorio-Dominguez + description: Includes functions for the analysis of circular data using distributions + based on Nonnegative Trigonometric Sums (NNTS). The package includes functions + for calculation of densities and distributions, for the estimation of parameters, + for plotting and more. + date_publication: '2023-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircNNTSR + url_git: '' +CircNNTSRmult: + version: 0.1.0 + title: Multivariate Circular Data using MNNTS Models + maintainer: Maria Mercedes Gregorio-Dominguez + description: A collection of utilities for the statistical analysis of multivariate + circular data using distributions based on Multivariate Nonnegative Trigonometric + Sums (MNNTS). The package includes functions for calculation of densities and + distributions, for the estimation of parameters, and more. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircNNTSRmult + url_git: '' +CircNNTSRSymmetric: + version: 0.1.0 + title: Circular Data using Symmetric NNTS Models + maintainer: Maria Mercedes Gregorio-Dominguez + description: The statistical analysis of circular data using distributions based + on symmetric Nonnegative Trigonometric Sums (NNTS). It includes functions to perform + empirical analysis and estimate the parameters of density functions. Fernandez-Duran, + J.J. and Gregorio-Dominguez, M.M. (2025), "Multimodal Symmetric Circular Distributions + Based on Nonnegative Trigonometric Sums and a Likelihood Ratio Test for Reflective + Symmetry", . + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircNNTSRSymmetric + url_git: '' +CircOutlier: + version: 3.2.3 + title: Detection of Outliers in Circular-Circular Regression + maintainer: Azade Ghazanfarihesari + description: Detection of outliers in circular-circular regression models, modifying + its and estimating of models parameters. + date_publication: '2016-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircOutlier + url_git: '' +CircSpaceTime: + version: 0.9.0 + title: Spatial and Spatio-Temporal Bayesian Model for Circular Data + maintainer: Mario Santoro + description: |- + Implementation of Bayesian models for spatial and spatio-temporal + interpolation of circular data using Gaussian Wrapped and Gaussian Projected distributions. + We developed the methods described in Jona Lasinio G. et al. (2012) , + Wang F. et al. (2014) and + Mastrantonio G. et al. (2016) . + date_publication: '2019-06-06' + bug_reports: https://github.com/santoroma/CircSpaceTime + url: '' + url_cran: https://CRAN.R-project.org/package=CircSpaceTime + url_git: https://github.com/santoroma/CircSpaceTime +CircStats: + version: 0.2-6 + title: Circular Statistics, from "Topics in Circular Statistics" (2001) + maintainer: Claudio Agostinelli + description: |- + Circular Statistics, from "Topics in Circular Statistics" + (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific. + date_publication: '2018-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircStats + url_git: '' +circular: + version: 0.5-1 + title: Circular Statistics + maintainer: Eduardo García-Portugués + description: Circular Statistics, from "Topics in circular Statistics" (2001) S. + Rao Jammalamadaka and A. SenGupta, World Scientific. + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=circular + url_git: '' +CircularDDM: + version: 0.1.0 + title: Circular Drift-Diffusion Model + maintainer: Yi-Shin Lin + description: Circular drift-diffusion model for continuous reports. + date_publication: '2018-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircularDDM + url_git: '' +circularEV: + version: 0.1.1 + title: Extreme Value Analysis for Circular Data + maintainer: Evandro Konzen + description: |- + General functions for performing extreme value analysis on a circular + domain as part of the statistical methodology in the paper by Konzen, E., + Neves, C., and Jonathan, P. (2021). Modeling nonstationary extremes of storm severity: Comparing parametric and semiparametric inference. Environmetrics, 32(4), e2667. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=circularEV + url_git: '' +CircularSilhouette: + version: 0.0.1 + title: Fast Silhouette on Circular or Linear Data Clusters + maintainer: Joe Song + description: |- + Calculating silhouette information for clusters on + circular or linear data using fast algorithms. These algorithms run in + linear time on sorted data, in contrast to quadratic time by the + definition of silhouette. When used together with the fast and optimal + circular clustering method FOCC (Debnath & Song 2021) + implemented in R package 'OptCirClust', + circular silhouette can be maximized to find the optimal number of + circular clusters; it can also be used to estimate the period of noisy + periodical data. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CircularSilhouette + url_git: '' +circumplex: + version: 1.0.0 + title: Analysis and Visualization of Circular Data + maintainer: Jeffrey Girard + description: |- + Circumplex models, which organize constructs in a circle around two + underlying dimensions, are popular for studying interpersonal functioning, + mood/affect, and vocational preferences/environments. This package provides + tools for analyzing and visualizing circular data, including scoring + functions for relevant instruments and a generalization of the bootstrapped + structural summary method from Zimmermann & Wright (2017) + and functions for creating publication-ready + tables and figures from the results. + date_publication: '2024-10-28' + bug_reports: https://github.com/jmgirard/circumplex/issues + url: http://circumplex.jmgirard.com/ + url_cran: https://CRAN.R-project.org/package=circumplex + url_git: https://github.com/jmgirard/circumplex +cirls: + version: 0.3.1 + title: Constrained Iteratively Reweighted Least Squares + maintainer: Pierre Masselot + description: Routines to fit generalized linear models with constrained coefficients, + along with inference on the coefficients. Designed to be used in conjunction with + the base glm() function. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cirls + url_git: https://github.com/PierreMasselot/cirls +cIRT: + version: 1.3.2 + title: Choice Item Response Theory + maintainer: James Joseph Balamuta + description: |- + Jointly model the accuracy of cognitive responses and item choices + within a Bayesian hierarchical framework as described by Culpepper and + Balamuta (2015) . In addition, the package + contains the datasets used within the analysis of the paper. + date_publication: '2022-02-21' + bug_reports: https://github.com/tmsalab/cIRT/issues + url: https://tmsalab.github.io/cIRT/ + url_cran: https://CRAN.R-project.org/package=cIRT + url_git: https://github.com/tmsalab/cIRT +CIS.DGLM: + version: 0.1.0 + title: Covariates, Interaction, and Selection for DGLM + maintainer: Yishi Wang + description: An implementation of double generalized linear model (DGLM) building + with variable selection procedures and handling of interaction terms and other + complex situations. We also provide a method of handling convergence issues within + the dglm() function. The package offers a simulation function for generating simulated + data for testing purposes and utilizes the forward stepwise variable selection + procedure in model-building. It also provides a new custom bootstrap function + for mean and standard deviation estimation and functions for building crossplots + and squareplots from a data set. + date_publication: '2022-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CIS.DGLM + url_git: '' +cisp: + version: 0.1.0 + title: A Correlation Indicator Based on Spatial Patterns + maintainer: Wenbo Lv + description: Use the spatial association marginal contributions derived from spatial + stratified heterogeneity to capture the degree of correlation between spatial + patterns. + date_publication: '2024-11-21' + bug_reports: https://github.com/stscl/cisp/issues + url: https://stscl.github.io/cisp/ + url_cran: https://CRAN.R-project.org/package=cisp + url_git: https://github.com/stscl/cisp +cit: + version: 2.3.2 + title: Causal Inference Test + maintainer: Joshua Millstein + description: |- + A likelihood-based hypothesis testing approach is implemented for + assessing causal mediation. Described in Millstein, Chen, and Breton (2016), + , it could be used to test for mediation + of a known causal association between a DNA variant, the 'instrumental variable', + and a clinical outcome or phenotype by gene expression or DNA methylation, the + potential mediator. Another example would be testing mediation of the effect + of a drug on a clinical outcome by the molecular target. The hypothesis test + generates a p-value or permutation-based FDR value with confidence intervals + to quantify uncertainty in the causal inference. The outcome can be represented + by either a continuous or binary variable, the potential mediator is continuous, + and the instrumental variable can be continuous or binary and is not limited to + a single variable but may be a design matrix representing multiple variables. + date_publication: '2024-06-28' + bug_reports: https://github.com/USCbiostats/cit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cit + url_git: https://github.com/USCbiostats/cit +CITAN: + version: 2022.1.1 + title: CITation ANalysis Toolpack + maintainer: Marek Gagolewski + description: |- + Supports quantitative + research in scientometrics and bibliometrics. Provides + various tools for preprocessing bibliographic + data retrieved, e.g., from Elsevier's SciVerse Scopus, + computing bibliometric impact of individuals, + or modelling phenomena encountered in the social sciences. + This package is deprecated, see 'agop' instead. + date_publication: '2022-03-21' + bug_reports: https://github.com/gagolews/CITAN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CITAN + url_git: https://github.com/gagolews/CITAN +citation: + version: 0.8.2 + title: Software Citation Tools + maintainer: Jan Philipp Dietrich + description: A collection of functions to extract citation information from 'R' + packages and to deal with files in 'citation file format' (), + extending the functionality already provided by the citation() function in the + 'utils' package. + date_publication: '2023-03-30' + bug_reports: https://github.com/pik-piam/citation/issues + url: https://doi.org/10.5281/zenodo.3813429 + url_cran: https://CRAN.R-project.org/package=citation + url_git: https://github.com/pik-piam/citation +citationchaser: + version: 0.0.4 + title: Perform Forward and Backwards Chasing in Evidence Syntheses + maintainer: Neal Haddaway + description: |- + In searching for research articles, we often want to + obtain lists of references from across studies, and also obtain lists + of articles that cite a particular study. In systematic reviews, this + supplementary search technique is known as 'citation chasing': forward + citation chasing looks for all records citing one or more articles of + known relevance; backward citation chasing looks for all records + referenced in one or more articles. Traditionally, this process would + be done manually, and the resulting records would need to be checked + one-by-one against included studies in a review to identify potentially + relevant records that should be included in a review. This package + contains functions to automate this process by making use of the + Lens.org API. An input article list can be used to return a list of + all referenced records, and/or all citing records in the Lens.org + database (consisting of PubMed, PubMed Central, CrossRef, Microsoft + Academic Graph and CORE; ). + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=citationchaser + url_git: '' +citecorp: + version: 0.3.0 + title: Client for the Open Citations Corpus + maintainer: Scott Chamberlain + description: |- + Client for the Open Citations Corpus (). + Includes a set of functions for getting one identifier type from another, + as well as getting references and citations for a given identifier. + date_publication: '2020-04-16' + bug_reports: https://github.com/ropenscilabs/citecorp/issues + url: https://docs.ropensci.org/citecorp/(docs) + url_cran: https://CRAN.R-project.org/package=citecorp + url_git: https://github.com/ropenscilabs/citecorp(devel) +cities: + version: 0.1.3 + title: Clinical Trials with Intercurrent Events Simulator + maintainer: Ahmad Hakeem Abdul Wahab + description: Simulates clinical trials and summarizes causal effects and treatment + policy estimands in the presence of intercurrent events in a transparent and intuitive + manner. + date_publication: '2023-08-08' + bug_reports: '' + url: https://hakeemwahabapp.shinyapps.io/cities/ + url_cran: https://CRAN.R-project.org/package=cities + url_git: '' +CITMIC: + version: 0.1.2 + title: Estimation of Cell Infiltration Based on Cell Crosstalk + maintainer: Junwei Han + description: A systematic biology tool was developed to identify cell infiltration + via an Individualized Cell crosstalk network. 'CITMIC' first constructed a weighted + cell crosstalk network by integrating Cell-target interaction information, biological + process data from the Gene Ontology (GO) database, and gene transcriptomic data + in a specific sample, and then, it used a network propagation algorithm on the + network to identify cell infiltration for the sample. Ultimately, cell infiltration + in the patient dataset was obtained by normalizing the centrality scores of the + cells. + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CITMIC + url_git: '' +citmre: + version: 0.1.0 + title: Colombian Index Tool Market Rate Exchange + maintainer: David Rodríguez + description: Downloads the Representative Market Rate Exchange (RMRE) from the + source. Allows setting the data series in time frequencies, splitting the time + series through start and end functions, transforming the data set in log returns + or levels, and making a Dynamic graph. + date_publication: '2024-04-19' + bug_reports: https://github.com/DavRodEcon/citmre/issues + url: https://davrodecon.github.io/citmre/ + url_cran: https://CRAN.R-project.org/package=citmre + url_git: https://github.com/DavRodEcon/citmre +cito: + version: '1.1' + title: Building and Training Neural Networks + maintainer: Maximilian Pichler + description: The 'cito' package provides a user-friendly interface for training + and interpreting deep neural networks (DNN). 'cito' simplifies the fitting of + DNNs by supporting the familiar formula syntax, hyperparameter tuning under cross-validation, + and helps to detect and handle convergence problems. DNNs can be trained on CPU, + GPU and MacOS GPUs. In addition, 'cito' has many downstream functionalities such + as various explainable AI (xAI) metrics (e.g. variable importance, partial dependence + plots, accumulated local effect plots, and effect estimates) to interpret trained + DNNs. 'cito' optionally provides confidence intervals (and p-values) for all xAI + metrics and predictions. At the same time, 'cito' is computationally efficient + because it is based on the deep learning framework 'torch'. The 'torch' package + is native to R, so no Python installation or other API is required for this package. + date_publication: '2024-03-18' + bug_reports: https://github.com/citoverse/cito/issues + url: https://citoverse.github.io/cito/ + url_cran: https://CRAN.R-project.org/package=cito + url_git: '' +ciTools: + version: 0.6.1 + title: |- + Confidence or Prediction Intervals, Quantiles, and Probabilities + for Statistical Models + maintainer: John Haman + description: |- + Functions to append confidence intervals, prediction intervals, + and other quantities of interest to data frames. All appended quantities + are for the response variable, after conditioning on the model and covariates. + This package has a data frame first syntax that allows for easy piping. + Currently supported models include (log-) linear, (log-) linear mixed, + generalized linear models, generalized linear mixed models, and + accelerated failure time models. + date_publication: '2020-10-25' + bug_reports: https://github.com/jthaman/ciTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ciTools + url_git: https://github.com/jthaman/ciTools +citrus: + version: 1.0.2 + title: Customer Intelligence Tool for Rapid Understandable Segmentation + maintainer: Dom Clarke + description: |- + A tool to easily run and visualise supervised and unsupervised state of the art customer segmentation. + It is built like a pipeline covering the 3 main steps in a segmentation project: pre-processing, modelling, and plotting. + Users can either run the pipeline as a whole, or choose to run any one of the three individual steps. + It is equipped with a supervised option (tree optimisation) and an unsupervised option (k-clustering) as default models. + date_publication: '2022-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=citrus + url_git: '' +ciu: + version: 0.6.0 + title: Contextual Importance and Utility + maintainer: Kary Främling + description: |- + Implementation of the Contextual Importance and Utility + (CIU) concepts for Explainable AI (XAI). A recent description of CIU + can be found in e.g. Främling (2020) . + date_publication: '2022-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ciu + url_git: '' +ciuupi: + version: 1.2.3 + title: Confidence Intervals Utilizing Uncertain Prior Information + maintainer: Paul Kabaila + description: |- + Computes a confidence interval for a specified linear combination of the + regression parameters in a linear regression model with iid normal errors + with known variance when there is uncertain prior information that a distinct + specified linear combination of the regression parameters takes a given + value. This confidence interval, found by numerical nonlinear constrained + optimization, has the required minimum coverage and utilizes this uncertain + prior information through desirable expected length properties. + This confidence interval has the following three practical applications. + Firstly, if the error variance has been accurately estimated from previous + data then it may be treated as being effectively known. Secondly, for + sufficiently large (dimension of the response vector) minus (dimension of + regression parameter vector), greater than or equal to 30 (say), + if we replace the assumed known value of the error variance by its usual + estimator in the formula for the confidence interval then the resulting + interval has, to a very good approximation, the same coverage probability + and expected length properties as when the error variance is known. Thirdly, + some more complicated models can be approximated by the linear regression + model with error variance known when certain unknown parameters are replaced + by estimates. This confidence interval is described in + Mainzer, R. and Kabaila, P. + (2019) , and is a member of the family of + confidence intervals proposed by Kabaila, P. and Giri, K. (2009) + . + date_publication: '2024-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ciuupi + url_git: '' +ciuupi2: + version: 1.0.1 + title: Kabaila and Giri (2009) Confidence Interval + maintainer: Paul Kabaila + description: |2- + + Computes a confidence interval for a specified linear combination of + the regression parameters in a linear regression model with iid normal + errors with unknown variance when there is uncertain prior information + that a distinct specified linear combination of the regression + parameters takes a specified number. This confidence interval, found by + numerical nonlinear constrained optimization, has the required minimum coverage + and utilizes this uncertain prior information through desirable + expected length properties. This confidence interval is proposed by + Kabaila, P. and Giri, K. (2009) . + date_publication: '2021-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ciuupi2 + url_git: '' +civ: + version: 0.1.0 + title: Categorical Instrumental Variables + maintainer: Thomas Wiemann + description: |- + Implementation of the categorical instrumental variable (CIV) + estimator proposed by Wiemann (2023) . CIV allows for optimal instrumental + variable estimation in settings with relatively few observations per + category. To obtain valid inference in these challenging settings, CIV + leverages a regularization assumption that implies existence of a latent + categorical variable with fixed finite support achieving the same first + stage fit as the observed instrument. + date_publication: '2023-12-08' + bug_reports: https://github.com/thomaswiemann/civ/issues + url: '' + url_cran: https://CRAN.R-project.org/package=civ + url_git: https://github.com/thomaswiemann/civ +civis: + version: 3.1.2 + title: R Client for the 'Civis Platform API' + maintainer: Peter Cooman + description: |- + A convenient interface for making + requests directly to the 'Civis Platform API' . + Full documentation available 'here' . + date_publication: '2023-03-31' + bug_reports: https://github.com/civisanalytics/civis-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=civis + url_git: https://github.com/civisanalytics/civis-r +ciw: + version: 0.0.2 + title: Watch the CRAN Incoming Directories + maintainer: Dirk Eddelbuettel + description: |- + Directory reads and summaries are provided for one or more of the subdirectories + of the directory, and a compact summary object is returned. + The package name is a contraption of 'CRAN Incoming Watcher'. + date_publication: '2024-03-20' + bug_reports: https://github.com/eddelbuettel/ciw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ciw + url_git: https://github.com/eddelbuettel/ciw +CJAMP: + version: 0.1.1 + title: Copula-Based Joint Analysis of Multiple Phenotypes + maintainer: Stefan Konigorski + description: We provide a computationally efficient and robust implementation of + the recently proposed C-JAMP (Copula-based Joint Analysis of Multiple Phenotypes) + method (Konigorski et al., 2019, submitted). C-JAMP allows estimating and testing + the association of one or multiple predictors on multiple outcomes in a joint + model, and is implemented here with a focus on large-scale genome-wide association + studies with two phenotypes. The use of copula functions allows modeling a wide + range of multivariate dependencies between the phenotypes, and previous results + are supporting that C-JAMP can increase the power of association studies to identify + associated genetic variants in comparison to existing methods (Konigorski, Yilmaz, + Pischon, 2016, ; Konigorski, Yilmaz, Bull, 2014, + ). In addition to the C-JAMP functions, functions + are available to generate genetic and phenotypic data, to compute the minor allele + frequency (MAF) of genetic markers, and to estimate the phenotypic variance explained + by genetic markers. + date_publication: '2019-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CJAMP + url_git: '' +cjar: + version: 0.2.0 + title: R Client for 'Customer Journey Analytics' ('CJA') API + maintainer: Ben Woodard + description: |- + Connect and pull data from the 'CJA' API, which powers 'CJA Workspace' . + The package was developed with the analyst in mind and will + continue to be developed with the guiding principles of iterative, + repeatable, timely analysis. New features are actively being + developed and we value your feedback and contribution to the process. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cjar + url_git: '' +cjbart: + version: 0.3.2 + title: Heterogeneous Effects Analysis of Conjoint Experiments + maintainer: Thomas Robinson + description: A tool for analyzing conjoint experiments using Bayesian Additive Regression + Trees ('BART'), a machine learning method developed by Chipman, George and McCulloch + (2010) . This tool focuses specifically on estimating, + identifying, and visualizing the heterogeneity within marginal component effects, + at the observation- and individual-level. It uses a variable importance measure + ('VIMP') with delete-d jackknife variance estimation, following Ishwaran and Lu + (2019) , to obtain bias-corrected estimates of which variables + drive heterogeneity in the predicted individual-level effects. + date_publication: '2023-09-06' + bug_reports: https://github.com/tsrobinson/cjbart/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cjbart + url_git: https://github.com/tsrobinson/cjbart +CJIVE: + version: 0.1.0 + title: Canonical Joint and Individual Variation Explained (CJIVE) + maintainer: Raphiel Murden + description: |- + Joint and Individual Variation Explained (JIVE) is a method for decomposing multiple datasets obtained on the same subjects into + shared structure, structure unique to each dataset, and noise. The two most common implementations are R.JIVE, an iterative + approach, and AJIVE, which uses principal angle analysis. JIVE estimates subspaces but interpreting these subspaces can be + challenging with AJIVE or R.JIVE. We expand upon insights into AJIVE as a canonical correlation analysis (CCA) of principal component + scores. This reformulation, which we call CJIVE, 1) provides an ordering of joint components by the degree of correlation between + corresponding canonical variables; 2) uses a computationally efficient permutation test for the number of joint components, which + provides a p-value for each component; and 3) can be used to predict subject scores for out-of-sample observations. + Please cite the following article when utilizing this package: + Murden, R., Zhang, Z., Guo, Y., & Risk, B. (2022) . + date_publication: '2023-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CJIVE + url_git: '' +cjoint: + version: 2.1.1 + title: AMCE Estimator for Conjoint Experiments + maintainer: Anton Strezhnev + description: |- + An R implementation of the Average Marginal Component-specific + Effects (AMCE) estimator presented in Hainmueller, J., Hopkins, D., and Yamamoto + T. (2014) Causal Inference in Conjoint Analysis: Understanding Multi-Dimensional + Choices via Stated Preference Experiments. Political Analysis 22(1):1-30. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cjoint + url_git: '' +ckanr: + version: 0.7.0 + title: |- + Client for the Comprehensive Knowledge Archive Network ('CKAN') + API + maintainer: Francisco Alves + description: |- + Client for 'CKAN' API (). Includes interface + to 'CKAN' 'APIs' for search, list, show for packages, organizations, and + resources. In addition, provides an interface to the 'datastore' API. + date_publication: '2023-03-17' + bug_reports: https://github.com/ropensci/ckanr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ckanr + url_git: https://docs.ropensci.org/ckanr/(website)https://github.com/ropensci/ckanr(devel) +CKAT: + version: 0.1.0 + title: Composite Kernel Association Test for Pharmacogenetics Studies + maintainer: Hong Zhang + description: Composite Kernel Association Test (CKAT) is a flexible and robust kernel + machine based approach to jointly test the genetic main effect and gene-treatment + interaction effect for a set of single-nucleotide polymorphisms (SNPs) in pharmacogenetics + (PGx) assessments embedded within randomized clinical trials. + date_publication: '2019-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CKAT + url_git: '' +CKLRT: + version: 0.2.3 + title: |- + Composite Kernel Machine Regression Based on Likelihood Ratio + Test + maintainer: Haoyu Zhang + description: 'Composite Kernel Machine Regression based on Likelihood Ratio Test + (CKLRT): in this package, we develop a kernel machine regression framework to + model the overall genetic effect of a SNP-set, considering the possible GE interaction. + Specifically, we use a composite kernel to specify the overall genetic effect + via a nonparametric function and we model additional covariates parametrically + within the regression framework. The composite kernel is constructed as a weighted + average of two kernels, one corresponding to the genetic main effect and one corresponding + to the GE interaction effect. We propose a likelihood ratio test (LRT) and a restricted + likelihood ratio test (RLRT) for statistical significance. We derive a Monte Carlo + approach for the finite sample distributions of LRT and RLRT statistics. (N. Zhao, + H. Zhang, J. Clark, A. Maity, M. Wu. Composite Kernel Machine Regression based + on Likelihood Ratio Test with Application for Combined Genetic and Gene-environment + Interaction Effect (Submitted).)' + date_publication: '2018-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CKLRT + url_git: '' +Ckmeans.1d.dp: + version: 4.3.5 + title: Optimal, Fast, and Reproducible Univariate Clustering + maintainer: Joe Song + description: |- + Fast, optimal, and reproducible weighted univariate + clustering by dynamic programming. Four problems are solved, including + univariate k-means (Wang & Song 2011) + (Song & Zhong 2020) , k-median, + k-segments, and multi-channel weighted k-means. Dynamic programming + is used to minimize the sum of (weighted) within-cluster distances + using respective metrics. Its advantage over heuristic clustering in + efficiency and accuracy is pronounced when there are many clusters. + Multi-channel weighted k-means groups multiple univariate + signals into k clusters. An auxiliary function generates histograms + adaptive to patterns in data. This package provides a powerful set + of tools for univariate data analysis with guaranteed optimality, + efficiency, and reproducibility, useful for peak calling on temporal, + spatial, and spectral data. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ckmeans.1d.dp + url_git: '' +CKMRpop: + version: 0.1.3 + title: |- + Forward-in-Time Simulation and Tallying of Pairwise + Relationships + maintainer: Eric C. Anderson + description: |- + Provides an R wrapper around the program 'spip' + (), a C + program for the simulation of pedigrees within age-structured populations + with user-specified life histories. Also includes a variety + of functions to parse 'spip' output to compile information about + related pairs amongst simulated, sampled individuals, to assess + the feasibility and potential accuracy of close-kin mark-recapture (CKMR). + Full documentation + and vignettes are mirrored at + and can be read online there. + date_publication: '2021-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CKMRpop + url_git: '' +CLA: + version: 0.96-3 + title: Critical Line Algorithm in Pure R + maintainer: Martin Maechler + description: |- + Implements 'Markowitz' Critical Line Algorithm ('CLA') for classical + mean-variance portfolio optimization, see Markowitz (1952) . + Care has been taken for correctness in light of previous buggy implementations. + date_publication: '2024-07-29' + bug_reports: '' + url: https://gitlab.math.ethz.ch/maechler/CLA/ + url_cran: https://CRAN.R-project.org/package=CLA + url_git: '' +Claddis: + version: 0.7.0 + title: Measuring Morphological Diversity and Evolutionary Tempo + maintainer: Graeme T. Lloyd + description: |- + Measures morphological diversity from discrete character data and + estimates evolutionary tempo on phylogenetic trees. Imports morphological + data from #NEXUS (Maddison et al. (1997) ) + format with read_nexus_matrix(), and writes to both #NEXUS and TNT format + (Goloboff et al. (2008) ). Main + functions are test_rates(), which implements AIC and likelihood + ratio tests for discrete character rates introduced across Lloyd et al. + (2012) , Brusatte et al. (2014) + , Close et al. (2015) + , and Lloyd (2016) , + and calculate_morphological_distances(), which implements multiple discrete + character distance metrics from Gower (1971) , Wills + (1998) , Lloyd (2016) , + and Hopkins and St John (2018) . This also + includes the GED correction from Lehmann et al. (2019) + . Multiple functions implement morphospace plots: + plot_chronophylomorphospace() implements Sakamoto and Ruta (2012) + , plot_morphospace() implements Wills et + al. (1994) , plot_changes_on_tree() + implements Wang and Lloyd (2016) , and + plot_morphospace_stack() implements Foote (1993) + . Other functions include + safe_taxonomic_reduction(), which implements Wilkinson (1995) + , map_dollo_changes() implements + the Dollo stochastic character mapping of Tarver et al. (2018) + , and estimate_ancestral_states() implements + the ancestral state options of Lloyd (2018) . + calculate_tree_length() and reconstruct_ancestral_states() implements + the generalised algorithms from Swofford and Maddison (1992; no doi). + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Claddis + url_git: '' +cladoRcpp: + version: 0.15.1 + title: C++ Implementations of Phylogenetic Cladogenesis Calculations + maintainer: Nicholas J. Matzke + description: 'Various cladogenesis-related calculations that are slow in pure R + are implemented in C++ with Rcpp. These include the calculation of the probability + of various scenarios for the inheritance of geographic range at the divergence + events on a phylogenetic tree, and other calculations necessary for models which + are not continuous-time markov chains (CTMC), but where change instead occurs + instantaneously at speciation events. Typically these models must assess the + probability of every possible combination of (ancestor state, left descendent + state, right descendent state). This means that there are up to (# of states)^3 + combinations to investigate, and in biogeographical models, there can easily be + hundreds of states, so calculation time becomes an issue. C++ implementation + plus clever tricks (many combinations can be eliminated a priori) can greatly + speed the computation time over naive R implementations. CITATION INFO: This + package is the result of my Ph.D. research, please cite the package if you use + it! Type: citation(package="cladoRcpp") to get the citation information.' + date_publication: '2018-11-21' + bug_reports: '' + url: http://phylo.wikidot.com/biogeobears + url_cran: https://CRAN.R-project.org/package=cladoRcpp + url_git: '' +ClaimsProblems: + version: 0.2.1 + title: Analysis of Conflicting Claims + maintainer: Iago Núñez Lugilde + description: The analysis of conflicting claims arises when an amount has to be + divided among a set of agents with claims that exceed what is available. A rule + is a way of selecting a division among the claimants. This package computes the + main rules introduced in the literature from the old times until nowadays. The + inventory of rules covers the proportional and the adjusted proportional rules, + the constrained equal awards and the constrained equal losses rules, the constrained + egalitarian, the Piniles’ and the minimal overlap rules, the random arrival and + the Talmud rules. Besides, the Dominguez and Thomson and the average of awards + rules are also included. All of them can be found in the book of W. Thomson (2019), + 'How to divide when there isn't enough. From Aristotle, the Talmud, and Maimonides + to the axiomatics of resource allocation', with the exception of the average of + awards rule (Mirás Calvo et al. (2022), ). In + addition, graphical diagrams allow the user to represent, among others, the set + of awards, the paths of awards, and the schedules of awards of a rule, and some + indexes. A good understanding of the similarities and the differences of the rules + is useful for a better decision making. Therefore this package could be helpful + to students, researchers and managers alike. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClaimsProblems + url_git: '' +clam: + version: 2.6.2 + title: Classical Age-Depth Modelling of Cores from Deposits + maintainer: Maarten Blaauw + description: Performs 'classical' age-depth modelling of dated sediment deposits + - prior to applying more sophisticated techniques such as Bayesian age-depth modelling. + Any radiocarbon dated depths are calibrated. Age-depth models are constructed + by sampling repeatedly from the dated levels, each time drawing age-depth curves. + Model types include linear interpolation, linear or polynomial regression, and + a range of splines. See Blaauw (2010) . + date_publication: '2025-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clam + url_git: '' +ClamR: + version: 2.1-3 + title: Time Series Modeling for Climate Change Proxies + maintainer: Jonathan M. Lees + description: Implementation of the Wilkinson and Ivany (2002) approach to paleoclimate + analysis, applied to isotope data extracted from clams. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClamR + url_git: '' +clap: + version: 0.1.0 + title: Detecting Class Overlapping Regions in Multidimensional Data + maintainer: Priyanga Dilini Talagala + description: The issue of overlapping regions in multidimensional data arises when + different classes or clusters share similar feature representations, making it + challenging to delineate distinct boundaries between them accurately. This package + provides methods for detecting and visualizing these overlapping regions using + partitional clustering techniques based on nearest neighbor distances. + date_publication: '2024-06-28' + bug_reports: https://github.com/pridiltal/clap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clap + url_git: https://github.com/pridiltal/clap +clarabel: + version: 0.10.0 + title: Interior Point Conic Optimization Solver + maintainer: Balasubramanian Narasimhan + description: A versatile interior point solver that solves linear programs (LPs), + quadratic programs (QPs), second-order cone programs (SOCPs), semidefinite programs + (SDPs), and problems with exponential and power cone constraints (). + For quadratic objectives, unlike interior point solvers based on the standard + homogeneous self-dual embedding (HSDE) model, Clarabel handles quadratic objective + without requiring any epigraphical reformulation of its objective function. It + can therefore be significantly faster than other HSDE-based solvers for problems + with quadratic objective functions. Infeasible problems are detected using using + a homogeneous embedding technique. + date_publication: '2025-02-18' + bug_reports: https://github.com/oxfordcontrol/clarabel-r/issues + url: https://oxfordcontrol.github.io/clarabel-r/ + url_cran: https://CRAN.R-project.org/package=clarabel + url_git: '' +clarifai: + version: 0.4.2 + title: Access to Clarifai API + maintainer: Gaurav Sood + description: |- + Get description of images from Clarifai API. For more information, + see . Clarifai uses a large deep learning cloud to come + up with descriptive labels of the things in an image. It also provides how + confident it is about each of the labels. + date_publication: '2017-04-12' + bug_reports: http://github.com/soodoku/clarifai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clarifai + url_git: http://github.com/soodoku/clarifai +clarify: + version: 0.2.1 + title: Simulation-Based Inference for Regression Models + maintainer: Noah Greifer + description: Performs simulation-based inference as an alternative to the delta + method for obtaining valid confidence intervals and p-values for regression post-estimation + quantities, such as average marginal effects and predictions at representative + values. This framework for simulation-based inference is especially useful when + the resulting quantity is not normally distributed and the delta method approximation + fails. The methodology is described in King, Tomz, and Wittenberg (2000) . + 'clarify' is meant to replace some of the functionality of the archived package + 'Zelig'; see the vignette "Translating Zelig to clarify" for replicating this + functionality. + date_publication: '2024-05-30' + bug_reports: https://github.com/iqss/clarify/issues + url: https://iqss.github.io/clarify/ + url_cran: https://CRAN.R-project.org/package=clarify + url_git: https://github.com/iqss/clarify +clarkeTest: + version: 0.2.0 + title: Distribution-Free Tests of Non-Nested Models + maintainer: Dave Armstrong + description: |- + Implementation of Clarke's distribution-free test of + non-nested models. Currently supported model functions are: + lm(), glm() ('binomial', 'poisson', 'negative binomial' links), + polr() ('MASS'), clm() ('ordinal'), and multinom() ('nnet'). + For more information on the test, see Clarke (2007) + . + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clarkeTest + url_git: '' +class: + version: 7.3-23 + title: Functions for Classification + maintainer: Brian Ripley + description: |- + Various functions for classification, including k-nearest + neighbour, Learning Vector Quantization and Self-Organizing Maps. + date_publication: '2025-01-01' + bug_reports: '' + url: http://www.stats.ox.ac.uk/pub/MASS4/ + url_cran: https://CRAN.R-project.org/package=class + url_git: '' +ClassComparison: + version: 3.3.5 + title: |- + Classes and Methods for "Class Comparison" Problems on + Microarrays + maintainer: Kevin R. Coombes + description: |- + Defines the classes used for "class comparison" problems + in the OOMPA project (). Class + comparison includes tests for differential expression; see Simon's + book for details on typical problem types. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClassComparison + url_git: http://oompa.r-forge.r-project.org/ +ClassDiscovery: + version: 3.4.5 + title: |- + Classes and Methods for "Class Discovery" with Microarrays or + Proteomics + maintainer: Kevin R. Coombes + description: |- + Defines the classes used for "class discovery" problems + in the OOMPA project (). Class + discovery primarily consists of unsupervised clustering methods with + attempts to assess their statistical significance. + date_publication: '2024-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClassDiscovery + url_git: http://oompa.r-forge.r-project.org/ +classGraph: + version: 0.7-6 + title: Construct Graphs of S4 Class Hierarchies + maintainer: Martin Maechler + description: |- + Construct directed graphs of S4 class hierarchies and + visualize them. In general, these graphs typically are DAGs (directed + acyclic graphs), often simple trees in practice. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=classGraph + url_git: '' +classicaltest: + version: 0.7.0 + title: Classical Test Theory (CTT) Analysis + maintainer: Andrés Christiansen + description: Functions for classical test theory analysis, following methods presented + by Wu et al. (2006) . + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=classicaltest + url_git: '' +classifierplots: + version: 1.4.0 + title: |- + Generates a Visualization of Classifier Performance as a Grid of + Diagnostic Plots + maintainer: Aaron Defazio + description: |2- + + Generates a visualization of binary classifier performance as a grid of + diagnostic plots with just one function call. Includes ROC curves, + prediction density, accuracy, precision, recall and calibration plots, all using + ggplot2 for easy modification. + Debug your binary classifiers faster and easier! + date_publication: '2020-10-13' + bug_reports: https://github.com/adefazio/classifierplots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=classifierplots + url_git: https://github.com/adefazio/classifierplots +classifly: + version: 0.4.1 + title: Explore Classification Models in High Dimensions + maintainer: Hadley Wickham + description: |- + Given $p$-dimensional training data containing $d$ groups + (the design space), a classification algorithm (classifier) predicts + which group new data belongs to. Generally the input to these + algorithms is high dimensional, and the boundaries between groups will + be high dimensional and perhaps curvilinear or multi-faceted. This + package implements methods for understanding the division of space + between the groups. + date_publication: '2022-05-20' + bug_reports: '' + url: http://had.co.nz/classifly + url_cran: https://CRAN.R-project.org/package=classifly + url_git: '' +classInt: + version: 0.4-11 + title: Choose Univariate Class Intervals + maintainer: Roger Bivand + description: Selected commonly used methods for choosing univariate class intervals + for mapping or other graphics purposes. + date_publication: '2025-01-08' + bug_reports: https://github.com/r-spatial/classInt/issues/ + url: https://r-spatial.github.io/classInt/ + url_cran: https://CRAN.R-project.org/package=classInt + url_git: https://github.com/r-spatial/classInt/ +classmap: + version: 1.2.3 + title: Visualizing Classification Results + maintainer: Jakob Raymaekers + description: |- + Tools to visualize the results of a classification of cases. + The graphical displays include stacked plots, silhouette plots, quasi residual plots, and class maps. + Implements the techniques described and illustrated in Raymaekers, Rousseeuw and Hubert (2021), Class maps for visualizing classification results, Technometrics, appeared online. + (open access) and Raymaekers and Rousseeuw (2021), + Silhouettes and quasi residual plots for neural nets and tree-based classifiers, + . Examples can be found in the vignettes: + "Discriminant_analysis_examples","K_nearest_neighbors_examples", + "Support_vector_machine_examples", "Rpart_examples", "Random_forest_examples", + and "Neural_net_examples". + date_publication: '2023-04-23' + bug_reports: '' + url: https://doi.org/10.1080/00401706.2021.1927849 + url_cran: https://CRAN.R-project.org/package=classmap + url_git: '' +CLAST: + version: 1.0.1 + title: Exact Confidence Limits after a Sequential Trial + maintainer: Chris J. Lloyd + description: The user first provides design vectors n, a and b as well as null (p0) + and alternative (p1) benchmark values for the probability of success. The key + function "mv.plots.SM()" calculates mean values of exact upper and lower limits + based on four different rank ordering methods. These plots form the basis of selecting + a rank ordering. The function "inference()" calculates exact limits from a provided + realisation and ordering choice. For more information, see "Exact confidence limits + after a group sequential single arm binary trial" by Lloyd, C.J. (2020), Statistics + in Medicine, Volume 38, 2389-2399, . + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CLAST + url_git: '' +clc: + version: 1.0.0 + title: CORINE Land Cover Data and Styles + maintainer: Jose Samos + description: |- + Streamline the management, analysis, and visualization of + CORINE Land Cover data. Addresses challenges associated with its + classification system and related styles, such as color mappings and + descriptive labels. + date_publication: '2024-12-10' + bug_reports: https://github.com/josesamos/clc/issues + url: https://josesamos.github.io/clc/ + url_cran: https://CRAN.R-project.org/package=clc + url_git: https://github.com/josesamos/clc +cld2: + version: 1.2.5 + title: Google's Compact Language Detector 2 + maintainer: Jeroen Ooms + description: |- + Bindings to Google's C++ library Compact Language Detector 2 + (see for more information). Probabilistically + detects over 80 languages in plain text or HTML. For mixed-language input it returns the + top three detected languages and their approximate proportion of the total classified + text bytes (e.g. 80% English and 20% French out of 1000 bytes). There is also a 'cld3' + package on CRAN which uses a neural network model instead. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/cld2/issues + url: https://docs.ropensci.org/cld2/https://ropensci.r-universe.dev/cld2 + url_cran: https://CRAN.R-project.org/package=cld2 + url_git: '' +cld3: + version: 1.6.1 + title: Google's Compact Language Detector 3 + maintainer: Jeroen Ooms + description: |- + Google's Compact Language Detector 3 is a neural network model for language + identification and the successor of 'cld2' (available from CRAN). The algorithm is still + experimental and takes a novel approach to language detection with different properties + and outcomes. It can be useful to combine this with the Bayesian classifier results + from 'cld2'. See for more information. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/cld3/issues + url: https://docs.ropensci.org/cld3/https://ropensci.r-universe.dev/cld3 + url_cran: https://CRAN.R-project.org/package=cld3 + url_git: '' +clda: + version: '0.1' + title: Convolution-Based Linear Discriminant Analysis + maintainer: Grover E. Castro Guzman + description: Contains a time series classification method that obtains a set of + filters that maximize the between-class and minimize the within-class distances. + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clda + url_git: '' +clean: + version: 2.0.0 + title: Fast and Easy Data Cleaning + maintainer: Matthijs S. Berends + description: |- + A wrapper around the new 'cleaner' package, that allows + data cleaning functions for classes 'logical', 'factor', 'numeric', + 'character', 'currency' and 'Date' to make data cleaning fast and + easy. Relying on very few dependencies, it provides smart guessing, + but with user options to override anything if needed. + date_publication: '2020-06-01' + bug_reports: https://github.com/msberends/cleaner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clean + url_git: https://github.com/msberends/cleaner +CleanBSequences: + version: 2.3.0 + title: Curing of Biological Sequences + maintainer: Florencia I. Pozzi + description: |- + Curates biological sequences massively, quickly, without errors and + without internet connection. Biological sequences curing is performed by + aligning the forward and / or revers primers or ends of cloning vectors with the sequences + to be cleaned. After the alignment, new subsequences are generated without biological fragment + not desired by the user. + Pozzi et al (2020) . + date_publication: '2024-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CleanBSequences + url_git: '' +cleancall: + version: 0.1.3 + title: C Resource Cleanup via Exit Handlers + maintainer: Gábor Csárdi + description: |- + Wrapper of .Call() that runs exit handlers to clean up C + resources. Helps managing C (non-R) resources while using the R API. + date_publication: '2022-10-26' + bug_reports: https://github.com/r-lib/cleancall/issues + url: https://r-lib.github.io/cleancall/ + url_cran: https://CRAN.R-project.org/package=cleancall + url_git: https://github.com/r-lib/cleancall#readme +cleandata: + version: 0.3.0 + title: |- + To Inspect and Manipulate Data; and to Keep Track of This + Process + maintainer: Sherry Zhao + description: |- + Functions to work with data frames to prepare data for further analysis. + The functions for imputation, encoding, partitioning, and other manipulation can produce log files to keep track of process. + date_publication: '2018-12-01' + bug_reports: https://github.com/sherrisherry/cleandata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cleandata + url_git: https://github.com/sherrisherry/cleandata +cleanepi: + version: 1.0.2 + title: Clean and Standardize Epidemiological Data + maintainer: Karim Mané + description: |- + Cleaning and standardizing tabular data package, tailored + specifically for curating epidemiological data. It streamlines various data + cleaning tasks that are typically expected when working with datasets in + epidemiology. It returns the processed data in the same format, ensuring + seamless integration into existing workflows. Additionally, it generates a + comprehensive report detailing the outcomes of each cleaning task. + date_publication: '2024-06-17' + bug_reports: https://github.com/epiverse-trace/cleanepi/issues + url: https://epiverse-trace.github.io/cleanepi/ + url_cran: https://CRAN.R-project.org/package=cleanepi + url_git: https://github.com/epiverse-trace/cleanepi +cleaner: + version: 1.5.5 + title: Fast and Easy Data Cleaning + maintainer: Matthijs S. Berends + description: |- + Data cleaning functions for classes logical, + factor, numeric, character, currency and Date to make + data cleaning fast and easy. Relying on very few dependencies, it + provides smart guessing, but with user options to override + anything if needed. + date_publication: '2024-11-19' + bug_reports: https://github.com/msberends/cleaner/issues + url: https://msberends.github.io/cleaner/ + url_cran: https://CRAN.R-project.org/package=cleaner + url_git: https://github.com/msberends/cleaner +Cleanet: + version: 1.0.0 + title: |- + Automated Doublet Detection and Classification for Cytometry + Data + maintainer: Matei Ionita + description: Automated method for doublet detection in flow or mass cytometry data, + based on simulating doublets and finding events whose protein expression patterns + are similar to the simulated doublets. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Cleanet + url_git: '' +cleangeo: + version: 0.3-1 + title: Cleaning Geometries from Spatial Objects + maintainer: Emmanuel Blondel + description: |2- + + Provides a set of utility tools to inspect spatial objects, facilitate + handling and reporting of topology errors and geometry validity issue with sp objects. + Finally, it provides a geometry cleaner that will fix all geometry problems, + and eliminate (at least reduce) the likelihood of having issues when doing + spatial data processing. + date_publication: '2023-09-01' + bug_reports: https://github.com/eblondel/cleangeo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cleangeo + url_git: https://github.com/eblondel/cleangeo +CleaningValidation: + version: '1.0' + title: |- + Cleaning Validation Functions for Pharmaceutical Cleaning + Process + maintainer: Xiande Yang + description: Provides essential Cleaning Validation functions for complying with + pharmaceutical cleaning process regulatory standards. The package includes non-parametric + methods to analyze drug active-ingredient residue (DAR), cleaning agent residue + (CAR), and microbial colonies (Mic) for non-Poisson distributions. Additionally, + Poisson methods are provided for Mic analysis when Mic data follow a Poisson distribution. + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CleaningValidation + url_git: https://github.com/ChandlerXiandeYang/CleaningValidation +cleanNLP: + version: 3.1.0 + title: A Tidy Data Model for Natural Language Processing + maintainer: Taylor B. Arnold + description: |- + Provides a set of fast tools for converting a textual corpus into + a set of normalized tables. Users may make use of the 'udpipe' back end with + no external dependencies, or a Python back ends with 'spaCy' . + Exposed annotation tasks include tokenization, part of speech tagging, named + entity recognition, and dependency parsing. + date_publication: '2024-05-20' + bug_reports: https://github.com/statsmaths/cleanNLP/issues + url: https://statsmaths.github.io/cleanNLP/ + url_cran: https://CRAN.R-project.org/package=cleanNLP + url_git: '' +cleanr: + version: 1.4.0 + title: Helps You to Code Cleaner + maintainer: Andreas Dominik Cullmann + description: |- + Check your R code for some of the most common + layout flaws. Many tried to teach us how to write code less dreadful, + be it implicitly as B. W. Kernighan and D. M. Ritchie (1988) + in 'The C Programming Language' did, be it + explicitly as R.C. Martin (2008) in 'Clean Code: + A Handbook of Agile Software Craftsmanship' did. So we should check + our code for files too long or wide, functions with too many lines, + too wide lines, too many arguments or too many levels of nesting. + Note: This is not a static code analyzer like pylint or the like. + Checkout instead. + date_publication: '2023-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cleanr + url_git: https://gitlab.com/fvafrcu/cleanr +cleanrmd: + version: 0.1.1 + title: Clean Class-Less 'R Markdown' HTML Documents + maintainer: Garrick Aden-Buie + description: |- + A collection of clean 'R Markdown' HTML document templates + using classy-looking classless CSS styles. These documents use a + minimal set of dependencies but still look great, making them suitable + for use a package vignettes or for sharing results via email. + date_publication: '2023-05-19' + bug_reports: https://github.com/gadenbuie/cleanrmd/issues + url: https://pkg.garrickadenbuie.com/cleanrmd/ + url_cran: https://CRAN.R-project.org/package=cleanrmd + url_git: https://github.com/gadenbuie/cleanrmd +cleanTS: + version: 0.1.2 + title: Testbench for Univariate Time Series Cleaning + maintainer: Mayur Shende + description: |- + A reliable and efficient tool for cleaning univariate time + series data. It implements reliable and efficient procedures for + automating the process of cleaning univariate time series data. + The package provides integration with already developed and deployed + tools for missing value imputation and outlier detection. It also + provides a way of visualizing large time-series data in different + resolutions. + date_publication: '2023-07-06' + bug_reports: https://github.com/Mayur1009/cleanTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cleanTS + url_git: https://github.com/Mayur1009/cleanTS +cleaR: + version: 0.0.4 + title: Clean the R Console and Environment + maintainer: Jonathan M. Mang + description: |- + Small package to clean the R console and the R environment + with the call of just one function. + date_publication: '2022-07-19' + bug_reports: https://github.com/joundso/cleaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cleaR + url_git: https://github.com/joundso/cleaR +clespr: + version: 1.1.2 + title: Composite Likelihood Estimation for Spatial Data + maintainer: Ting Fung (Ralph) Ma + description: Composite likelihood approach is implemented to estimating statistical + models for spatial ordinal and proportional data based on Feng et al. (2014) . + Parameter estimates are identified by maximizing composite log-likelihood functions + using the limited memory BFGS optimization algorithm with bounding constraints, + while standard errors are obtained by estimating the Godambe information matrix. + date_publication: '2018-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clespr + url_git: '' +clevr: + version: 0.1.2 + title: Clustering and Link Prediction Evaluation in R + maintainer: Neil Marchant + description: |- + Tools for evaluating link prediction and clustering algorithms + with respect to ground truth. Includes efficient implementations of + common performance measures such as pairwise precision/recall, + cluster homogeneity/completeness, variation of information, + Rand index etc. + date_publication: '2023-09-16' + bug_reports: https://github.com/cleanzr/clevr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clevr + url_git: https://github.com/cleanzr/clevr +clhs: + version: 0.9.0 + title: Conditioned Latin Hypercube Sampling + maintainer: Pierre Roudier + description: Conditioned Latin hypercube sampling, as published by Minasny and McBratney + (2006) . This method proposes to stratify sampling + in presence of ancillary data. An extension of this method, which propose to associate + a cost to each individual and take it into account during the optimisation process, + is also proposed (Roudier et al., 2012, ). + date_publication: '2021-10-14' + bug_reports: https://github.com/pierreroudier/clhs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clhs + url_git: https://github.com/pierreroudier/clhs/ +cli: + version: 3.6.4 + title: Helpers for Developing Command Line Interfaces + maintainer: Gábor Csárdi + description: |- + A suite of tools to build attractive command line interfaces + ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, + etc. Supports custom themes via a 'CSS'-like language. It also + contains a number of lower level 'CLI' elements: rules, boxes, trees, + and 'Unicode' symbols with 'ASCII' alternatives. It support ANSI + colors and text styles as well. + date_publication: '2025-02-13' + bug_reports: https://github.com/r-lib/cli/issues + url: https://cli.r-lib.org + url_cran: https://CRAN.R-project.org/package=cli + url_git: https://github.com/r-lib/cli +cliapp: + version: 0.1.2 + title: Create Rich Command Line Applications + maintainer: Gábor Csárdi + description: |- + Create rich command line applications, with colors, headings, + lists, alerts, progress bars, etc. It uses CSS for custom themes. + This package is now superseded by the 'cli' package. Please use 'cli' + instead in new projects. + date_publication: '2024-04-24' + bug_reports: https://github.com/r-lib/cliapp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cliapp + url_git: https://github.com/r-lib/cliapp#readme +clickableImageMap: + version: '1.0' + title: Implement 'tableGrob' Object as a Clickable Image Map + maintainer: Barry Zeeberg + description: |- + Implement 'tableGrob' object as a clickable image map. + The 'clickableImageMap' package is designed to be more convenient and more configurable than the edit() function. + Limitations that I have encountered with edit() are cannot control + (1) positioning + (2) size + (3) appearance and formatting of fonts + In contrast, when the table is implemented as a 'tableGrob', all of these features are controllable. + In particular, the 'ggplot2' grid system allows exact positioning of the table relative to + other graphics etc. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clickableImageMap + url_git: '' +clickb: + version: '0.1' + title: Web Data Analysis by Bayesian Mixture of Markov Models + maintainer: Furio Urso + description: Designed for web usage data analysis, it implements tools to process + web sequences and identify web browsing profiles through sequential classification. + Sequences' clusters are identified by using a model-based approach, specifically + mixture of discrete time first-order Markov models for categorical web sequences. + A Bayesian approach is used to estimate model parameters and identify sequences + classification as proposed by Fruehwirth-Schnatter and Pamminger (2010) . + date_publication: '2023-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clickb + url_git: '' +ClickClust: + version: 1.1.6 + title: Model-Based Clustering of Categorical Sequences + maintainer: Volodymyr Melnykov + description: Clustering categorical sequences by means of finite mixtures with Markov + model components is the main utility of ClickClust. The package also allows detecting + blocks of equivalent states by forward and backward state selection procedures. + date_publication: '2023-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClickClust + url_git: '' +ClickClustCont: + version: 0.1.7 + title: Mixtures of Continuous Time Markov Models + maintainer: Michael P.B. Gallaugher + description: Provides an expectation maximization (EM) algorithm to fit a mixture + of continuous time Markov models for use with clickstream or other sequence type + data. Gallaugher, M.P.B and McNicholas, P.D. (2018) . + date_publication: '2019-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClickClustCont + url_git: '' +ClickHouseHTTP: + version: 0.3.3 + title: A Simple HTTP Database Interface to 'ClickHouse' + maintainer: Patrice Godard + description: |- + 'ClickHouse' () + is an open-source, high performance columnar + OLAP (online analytical processing of queries) database management system + for real-time analytics using SQL. This 'DBI' backend + relies on the 'ClickHouse' HTTP interface and support HTTPS protocol. + date_publication: '2024-04-18' + bug_reports: https://github.com/patzaw/ClickHouseHTTP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClickHouseHTTP + url_git: https://github.com/patzaw/ClickHouseHTTP +clickR: + version: 0.9.45 + title: |- + Semi-Automatic Preprocessing of Messy Data with Change Tracking + for Dataset Cleaning + maintainer: David Hervas Marin + description: |- + Tools for assessing data quality, performing exploratory analysis, and + semi-automatic preprocessing of messy data with change tracking for integral dataset cleaning. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clickR + url_git: '' +clickstream: + version: 1.3.3 + title: Analyzes Clickstreams Based on Markov Chains + maintainer: Michael Scholz + description: |- + A set of tools to read, analyze and write lists of click sequences + on websites (i.e., clickstream). A click can be represented by a number, + character or string. Clickstreams can be modeled as zero- (only computes + occurrence probabilities), first- or higher-order Markov chains. + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clickstream + url_git: '' +clidamonger: + version: 1.3.0 + title: |- + Monthly Climate Data for Germany, Usable for Heating and Cooling + Calculations + maintainer: Jens Calisti + description: |- + This data package contains monthly climate data in Germany, it can be used for heating and + cooling calculations (external temperature, heating / cooling days, solar radiation). + date_publication: '2025-02-07' + bug_reports: https://github.com/IWUGERMANY/clidamonger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clidamonger + url_git: https://github.com/IWUGERMANY/clidamonger +clidatajp: + version: 0.5.2 + title: Data from Japan Meteorological Agency + maintainer: Toshikazu Matsumura + description: |- + Includes climate data from Japan Meteorological Agency ('JMA') . + Can download climate data from 'JMA'. + date_publication: '2023-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clidatajp + url_git: https://github.com/matutosi/clidatajphttps://github.com/matutosi/clidatajp/tree/develop(devel) +cliff: + version: 0.1.2 + title: Execute Command Line Programs Interactively + maintainer: Randy Lai + description: Execute command line programs and format results for interactive use. + It is based on the package 'processx' so it does not use shell to start up the + process like system() and system2(). It also provides a simpler and cleaner interface + than processx::run(). + date_publication: '2021-11-02' + bug_reports: https://github.com/RTagBot/cliff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cliff + url_git: https://github.com/RTagBot/cliff +clifford: + version: 1.0-8 + title: Arbitrary Dimensional Clifford Algebras + maintainer: Robin K. S. Hankin + description: |- + A suite of routines for Clifford algebras, using the + 'Map' class of the Standard Template Library. Canonical + reference: Hestenes (1987, ISBN 90-277-1673-0, "Clifford algebra + to geometric calculus"). Special cases including Lorentz transforms, + quaternion multiplication, and Grassman algebra, are discussed. + Conformal geometric algebra theory is implemented. Uses 'disordR' + discipline. + date_publication: '2022-08-13' + bug_reports: https://github.com/RobinHankin/clifford/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clifford + url_git: https://github.com/RobinHankin/clifford +clifro: + version: 3.2-5 + title: Easily Download and Visualise Climate Data from CliFlo + maintainer: Blake Seers + description: |- + CliFlo is a web portal to the New Zealand National Climate + Database and provides public access (via subscription) to around 6,500 + various climate stations (see for more + information). Collating and manipulating data from CliFlo + (hence clifro) and importing into R for further analysis, exploration and + visualisation is now straightforward and coherent. The user is required to + have an internet connection, and a current CliFlo subscription (free) if + data from stations, other than the public Reefton electronic weather + station, is sought. + date_publication: '2021-05-24' + bug_reports: https://github.com/ropensci/clifro/issues + url: https://docs.ropensci.org/clifro/ + url_cran: https://CRAN.R-project.org/package=clifro + url_git: https://github.com/ropensci/clifro +CliftLRD: + version: 0.1-1 + title: |- + Complex-Valued Wavelet Lifting Estimators of the Hurst Exponent + for Irregularly Sampled Time Series + maintainer: Matt Nunes + description: Implementation of Hurst exponent estimators based on complex-valued + lifting wavelet energy from Knight, M. I and Nunes, M. A. (2018) . + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CliftLRD + url_git: '' +clikcorr: + version: '1.0' + title: Censoring Data and Likelihood-Based Correlation Estimation + maintainer: Yanming Li + description: A profile likelihood based method of estimation and inference on the + correlation coefficient of bivariate data with different types of censoring and + missingness. + date_publication: '2016-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clikcorr + url_git: '' +climaemet: + version: 1.4.0 + title: Climate AEMET Tools + maintainer: Diego Hernangómez + description: |- + Tools to download the climatic data of the Spanish + Meteorological Agency (AEMET) directly from R using their API and + create scientific graphs (climate charts, trend analysis of climate + time series, temperature and precipitation anomalies maps, warming + stripes graphics, climatograms, etc.). + date_publication: '2024-08-28' + bug_reports: https://github.com/rOpenSpain/climaemet/issues + url: https://ropenspain.github.io/climaemet/ + url_cran: https://CRAN.R-project.org/package=climaemet + url_git: https://github.com/rOpenSpain/climaemet +climate: + version: 1.2.2 + title: Interface to Download Meteorological (and Hydrological) Datasets + maintainer: Bartosz Czernecki + description: |- + Automatize downloading of meteorological and hydrological data from publicly available repositories: + OGIMET (), + University of Wyoming - atmospheric vertical profiling data (), + Polish Institute of Meteorology and Water Management - National Research Institute (), + and National Oceanic & Atmospheric Administration (NOAA). + This package also allows for searching geographical coordinates for each observation and calculate distances to the nearest stations. + date_publication: '2024-12-20' + bug_reports: https://github.com/bczernecki/climate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=climate + url_git: https://github.com/bczernecki/climate +climateStability: + version: 0.1.4 + title: Estimating Climate Stability from Climate Model Data + maintainer: Hannah Owens + description: |- + Climate stability measures are not formalized in the literature and + tools for generating stability metrics from existing data are nascent. + This package provides tools for calculating climate stability from raster data + encapsulating climate change as a series of time slices. The methods follow + Owens and Guralnick Biodiversity Informatics. + date_publication: '2022-10-01' + bug_reports: https://github.com/hannahlowens/climateStability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=climateStability + url_git: https://github.com/hannahlowens/climateStability +climatol: + version: 4.1.0 + title: Climate Tools (Series Homogenization and Derived Products) + maintainer: Jose A. Guijarro + description: Functions for the quality control, homogenization and missing data + filling of climatological series and to obtain climatological summaries and grids + from the results. Also functions to display wind-roses, meteograms, Walter&Lieth + diagrams, and more. + date_publication: '2024-03-22' + bug_reports: '' + url: https://climatol.eu + url_cran: https://CRAN.R-project.org/package=climatol + url_git: '' +climatrends: + version: '0.5' + title: Climate Variability Indices for Ecological Modelling + maintainer: Kauê de Sousa + description: |- + Supports analysis of trends in climate change, + ecological and crop modelling. + date_publication: '2023-01-06' + bug_reports: https://github.com/agrdatasci/climatrends/issues + url: https://agrdatasci.github.io/climatrends/ + url_cran: https://CRAN.R-project.org/package=climatrends + url_git: '' +ClimClass: + version: 2.1.0 + title: Climate Classification According to Several Indices + maintainer: Emanuele Eccel + description: |- + Classification of climate according to Koeppen - Geiger, of aridity + indices, of continentality indices, of water balance after Thornthwaite, of + viticultural bioclimatic indices. Drawing climographs: Thornthwaite, Peguy, + Bagnouls-Gaussen. + date_publication: '2016-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClimClass + url_git: '' +CLimd: + version: 0.1.0 + title: Generating Rainfall Rasters from IMD NetCDF Data + maintainer: Nobin Chandra Paul + description: |- + The developed function is a comprehensive tool for the analysis of India Meteorological Department (IMD) NetCDF rainfall data. Specifically designed to process high-resolution daily + gridded rainfall datasets. It provides four key functions to process IMD NetCDF rainfall data and create rasters for various temporal scales, including annual, seasonal, monthly, and weekly + rainfall. For method details see, Malik, A. (2019).. It supports different aggregation methods, such as sum, min, max, mean, and standard deviation. These functions + are designed for spatio-temporal analysis of rainfall patterns, trend analysis,geostatistical modeling of rainfall variability, identifying rainfall anomalies and extreme events and can be an input + for hydrological and agricultural models. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CLimd + url_git: '' +clime: + version: 0.5.0 + title: |- + Constrained L1-Minimization for Inverse (Covariance) Matrix + Estimation + maintainer: Xi (Rossi) Luo + description: A robust constrained L1 minimization method for estimating a large + sparse inverse covariance matrix (aka precision matrix), and recovering its support + for building graphical models. The computation uses linear programming. The + method was published in TT Cai, W Liu, X Luo (2011) . + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clime + url_git: '' +climetrics: + version: 1.0-15 + title: Climate Change Metrics + maintainer: Shirin Taheri + description: A framework that facilitates spatio-temporal analysis of climate dynamics + through exploring and measuring different dimensions of climate change in space + and time. + date_publication: '2024-04-18' + bug_reports: https://github.com/shirintaheri/climetrics/issues/ + url: https://r-gis.net/ + url_cran: https://CRAN.R-project.org/package=climetrics + url_git: '' +climextRemes: + version: 0.3.1 + title: Tools for Analyzing Climate Extremes + maintainer: Christopher Paciorek + description: |- + Functions for fitting GEV and POT (via point process fitting) + models for extremes in climate data, providing return values, return + probabilities, and return periods for stationary and nonstationary models. + Also provides differences in return values and differences in log return + probabilities for contrasts of covariate values. Functions for estimating risk + ratios for event attribution analyses, including uncertainty. Under the hood, + many of the functions use functions from 'extRemes', including for fitting the + statistical models. Details are given in Paciorek, Stone, and Wehner (2018) + . + date_publication: '2023-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=climextRemes + url_git: https://bitbucket.org/lbl-cascade/climextremes-dev +ClimInd: + version: 0.1-3 + title: Climate Indices + maintainer: Fergus Reig-Gracia + description: 'Computes 138 standard climate indices at monthly, seasonal and annual + resolution. These indices were selected, based on their direct and significant + impacts on target sectors, after a thorough review of the literature in the field + of extreme weather events and natural hazards. Overall, the selected indices characterize + different aspects of the frequency, intensity and duration of extreme events, + and are derived from a broad set of climatic variables, including surface air + temperature, precipitation, relative humidity, wind speed, cloudiness, solar radiation, + and snow cover. The 138 indices have been classified as follow: Temperature based + indices (42), Precipitation based indices (22), Bioclimatic indices (21), Wind-based + indices (5), Aridity/ continentality indices (10), Snow-based indices (13), Cloud/radiation + based indices (6), Drought indices (8), Fire indices (5), Tourism indices (5).' + date_publication: '2021-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClimInd + url_git: https://gitlab.com/indecis-eu/indecis +ClimMobTools: + version: '1.4' + title: API Client for the 'ClimMob' Platform + maintainer: Kauê de Sousa + description: |- + API client for 'ClimMob', an open source software for decentralized + large-N trials with the 'tricot' approach . + Developed by van Etten et al. (2019) , it turns the + research paradigm on its head; instead of a few researchers designing complicated + trials to compare several technologies in search of the best solutions for the + target environment, it enables many participants to carry out reasonably simple + experiments that taken together can offer even more information. 'ClimMobTools' + enables project managers to deep explore and analyse their 'ClimMob' data in R. + date_publication: '2025-01-16' + bug_reports: https://github.com/agrdatasci/ClimMobTools/issues + url: https://agrdatasci.github.io/ClimMobTools/ + url_cran: https://CRAN.R-project.org/package=ClimMobTools + url_git: '' +ClimProjDiags: + version: 0.3.3 + title: Set of Tools to Compute Various Climate Indices + maintainer: Victòria Agudetse + description: |- + Set of tools to compute metrics and indices for climate analysis. + The package provides functions to compute extreme indices, evaluate the + agreement between models and combine theses models into an ensemble. Multi-model + time series of climate indices can be computed either after averaging the 2-D + fields from different models provided they share a common grid or by combining + time series computed on the model native grid. Indices can be assigned weights + and/or combined to construct new indices. + date_publication: '2024-01-26' + bug_reports: https://earth.bsc.es/gitlab/es/ClimProjDiags/-/issues + url: https://earth.bsc.es/gitlab/es/ClimProjDiags + url_cran: https://CRAN.R-project.org/package=ClimProjDiags + url_git: '' +climwin: + version: 1.2.3 + title: Climate Window Analysis + maintainer: Liam D. Bailey + description: |- + Contains functions to detect and visualise periods of climate + sensitivity (climate windows) for a given biological response. + Please see van de Pol et al. (2016) + and Bailey and van de Pol (2016) for details. + date_publication: '2020-05-26' + bug_reports: https://github.com/LiamDBailey/climwin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=climwin + url_git: https://github.com/LiamDBailey/climwin +clinDataReview: + version: 1.6.1 + title: Clinical Data Review Tool + maintainer: Laure Cougnaud + description: |- + Creation of interactive tables, listings and figures ('TLFs') + and associated report for exploratory analysis of data in a clinical trial, + e.g. for clinical oversight activities. + Interactive figures include sunburst, treemap, scatterplot, line plot and + barplot of counts data. + Interactive tables include table of summary statistics + (as counts of adverse events, enrollment table) and listings. + Possibility to compare data (summary table or listing) across two data batches/sets. + A clinical data review report is created via study-specific configuration + files and template 'R Markdown' reports contained in the package. + date_publication: '2024-06-18' + bug_reports: https://github.com/openanalytics/clinDataReview/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clinDataReview + url_git: https://github.com/openanalytics/clinDataReview +clinDR: + version: 2.4.1 + title: |- + Simulation and Analysis Tools for Clinical Dose Response + Modeling + maintainer: Neal Thomas + description: |- + Bayesian and ML Emax model fitting, graphics and simulation for clinical dose + response. The summary data from the dose response meta-analyses in + Thomas, Sweeney, and Somayaji (2014) and + Thomas and Roy (2016) + Wu, Banerjee, Jin, Menon, Martin, and Heatherington(2017) + are included + in the package. The prior distributions for the Bayesian analyses default to + the posterior predictive distributions derived from these references. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clinDR + url_git: '' +clinfun: + version: 1.1.5 + title: Clinical Trial Design and Data Analysis Functions + maintainer: Venkatraman E. Seshan + description: |- + Utilities to make your clinical collaborations easier if not + fun. It contains functions for designing studies such as Simon + 2-stage and group sequential designs and for data analysis such + as Jonckheere-Terpstra test and estimating survival quantiles. + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clinfun + url_git: '' +clinicalomicsdbR: + version: 1.0.5 + title: |- + Interface with the 'ClinicalOmicsDB' API, Allowing for Easy Data + Downloading and Importing + maintainer: John Elizarraras + description: Provides an interface to the 'ClinicalOmicsDB' API, allowing for easy + data downloading and importing. 'ClinicalOmicsDB' is a database of clinical and + 'omics' data from cancer patients. The database is accessible at . + date_publication: '2024-06-26' + bug_reports: https://github.com/bzhanglab/clinicalomicsdbR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clinicalomicsdbR + url_git: https://github.com/bzhanglab/clinicalomicsdbR +clinicalsignificance: + version: 2.1.0 + title: |- + A Toolbox for Clinical Significance Analyses in Intervention + Studies + maintainer: Benedikt Claus + description: |- + A clinical significance analysis can be used to determine if an + intervention has a meaningful or practical effect for patients. You provide + a tidy data set plus a few more metrics and this package will take care of + it to make your results publication ready. Accompanying package to + Claus et al. . + date_publication: '2024-12-02' + bug_reports: https://github.com/pedscience/clinicalsignificance/issues + url: https://pedscience.github.io/clinicalsignificance/ + url_cran: https://CRAN.R-project.org/package=clinicalsignificance + url_git: https://github.com/pedscience/clinicalsignificance +ClinicalTrialSummary: + version: 1.1.1 + title: Summary Measures for Clinical Trials with Survival Outcomes + maintainer: Daewoo Pak + description: |- + Provides estimates of several summary measures for clinical trials including + the average hazard ratio, the weighted average hazard ratio, the restricted + superiority probability ratio, the restricted mean survival difference and + the ratio of restricted mean times lost, based on the short-term and + long-term hazard ratio model (Yang, 2005 ) + which accommodates various non-proportional hazards scenarios. The inference + procedures and the asymptotic results for the summary measures are discussed + in Yang (2018, ). + date_publication: '2019-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClinicalTrialSummary + url_git: '' +ClinicalUtilityRecal: + version: 0.1.0 + title: |- + Recalibration Methods for Improved Clinical Utility of Risk + Scores + maintainer: Anu Mishra + description: Recalibrate risk scores (predicting binary outcomes) to improve clinical + utility of risk score using weighted logistic or constrained logistic recalibration + methods. Additionally, produces plots to assess the potential for recalibration + to improve the clinical utility of a risk model. Methods are described in detail + in Mishra, A. (2019) "Methods for Risk Markers that Incorporate Clinical Utility" + . + date_publication: '2020-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClinicalUtilityRecal + url_git: '' +clinmon: + version: 0.6.0 + title: Hemodynamic Calculations from Clinical Monitoring + maintainer: Markus Harboe Olsen + description: |2- + + Every research team have their own script for calculation of hemodynamic indexes. + This package makes it possible to insert a long-format dataframe, and add both + periods of interest (trigger-periods), and delete artifacts with deleter-files. + date_publication: '2021-02-04' + bug_reports: https://github.com/lilleoel/clinmon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clinmon + url_git: https://github.com/lilleoel/clinmon +clinPK: + version: 0.13.0 + title: Clinical Pharmacokinetics Toolkit + maintainer: Ron Keizer + description: |- + Provides equations commonly used in clinical + pharmacokinetics and clinical pharmacology, such as equations + for dose individualization, compartmental pharmacokinetics, + drug exposure, anthropomorphic calculations, clinical + chemistry, and conversion of common clinical parameters. Where + possible and relevant, it provides multiple published and + peer-reviewed equations within the respective R function. + date_publication: '2024-02-23' + bug_reports: '' + url: https://insightrx.github.io/clinPK/ + url_cran: https://CRAN.R-project.org/package=clinPK + url_git: https://github.com/InsightRX/clinPK +clinsig: + version: '1.2' + title: Clinical Significance Functions + maintainer: Jim Lemon + description: Functions for calculating clinical significance. + date_publication: '2016-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clinsig + url_git: '' +ClinSigMeasures: + version: '1.2' + title: Clinical Significance Measures + maintainer: Mike Malek-Ahmadi + description: Provides measures of effect sizes for summarized continuous variables + as well as diagnostic accuracy statistics for 2x2 table data. Includes functions + for Cohen's d, robust effect size, Cohen's q, partial eta-squared, coefficient + of variation, odds ratio, likelihood ratios, sensitivity, specificity, positive + and negative predictive values, Youden index, number needed to treat, number needed + to diagnose, and predictive summary index. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClinSigMeasures + url_git: '' +clinspacy: + version: 1.0.2 + title: |- + Clinical Natural Language Processing using 'spaCy', 'scispaCy', + and 'medspaCy' + maintainer: Karandeep Singh + description: |- + Performs biomedical named entity recognition, + Unified Medical Language System (UMLS) concept mapping, and negation + detection using the Python 'spaCy', 'scispaCy', and 'medspaCy' packages, and + transforms extracted data into a wide format for inclusion in machine + learning models. The development of the 'scispaCy' package is described by + Neumann (2019) . The 'medspacy' package uses + 'ConText', an algorithm for determining the context of clinical statements + described by Harkema (2009) . Clinspacy + also supports entity embeddings from 'scispaCy' and UMLS 'cui2vec' concept + embeddings developed by Beam (2018) . + date_publication: '2021-03-20' + bug_reports: https://github.com/ML4LHS/clinspacy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clinspacy + url_git: https://github.com/ML4LHS/clinspacy +clintools: + version: 0.9.10.1 + title: Tools for Clinical Research + maintainer: Markus Harboe Olsen + description: |2- + + Every research team have their own script for data management, statistics and + most importantly hemodynamic indices. The purpose is to standardize scripts + utilized in clinical research. The hemodynamic indices can be used in a long-format dataframe, + and add both periods of interest (trigger-periods), and delete artifacts with deleter-files. + Transfer function analysis (Claassen et al. (2016) ) and + Mx (Czosnyka et al. (1996) ) can be calculated using this package. + date_publication: '2023-12-11' + bug_reports: https://github.com/lilleoel/clintools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clintools + url_git: https://github.com/lilleoel/clintools +ClinTrialPredict: + version: 0.0.4 + title: |- + Predicting and Simulating Clinical Trial with Time-to-Event + Endpoint + maintainer: Yang Ding + description: Predict the course of clinical trial with a time-to-event endpoint + for both two-arm and single-arm design. Each of the four primary study design + parameters (the expected number of observed events, the number of subjects enrolled, + the observation time, and the censoring parameter) can be derived analytically + given the other three parameters. And the simulation datasets can be generated + based on the design settings. + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClinTrialPredict + url_git: '' +clintrialx: + version: 0.1.0 + title: Connect and Work with Clinical Trials Data Sources + maintainer: Indraneel Chakraborty + description: Are you spending too much time fetching and managing clinical trial + data? Struggling with complex queries and bulk data extraction? What if you could + simplify this process with just a few lines of code? Introducing 'clintrialx' + - Fetch clinical trial data from sources like 'ClinicalTrials.gov' + and the 'Clinical Trials Transformation Initiative - Access to Aggregate Content + of ClinicalTrials.gov' database , supporting + pagination and bulk downloads. Also, you can generate HTML reports based on the + data obtained from the sources! + date_publication: '2024-09-03' + bug_reports: '' + url: http://www.indraneelchakraborty.com/clintrialx/ + url_cran: https://CRAN.R-project.org/package=clintrialx + url_git: '' +clinUtils: + version: 0.2.0 + title: General Utility Functions for Analysis of Clinical Data + maintainer: Laure Cougnaud + description: |- + Utility functions to facilitate the import, + the reporting and analysis of clinical data. + Example datasets in 'SDTM' and 'ADaM' format, containing a subset of patients/domains + from the 'CDISC Pilot 01 study' are also available as R datasets to demonstrate + the package functionalities. + date_publication: '2024-05-17' + bug_reports: https://github.com/openanalytics/clinUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clinUtils + url_git: https://github.com/openanalytics/clinUtils +cliot: + version: 0.2.0 + title: Clinical Indices and Outcomes Tools + maintainer: Neel Agarwal + description: Collection of indices and tools relating to cardiovascular, nephrology, + and hepatic research that aid epidemiological chort or retrospective chart review + with big data. All indices and tools take commonly used lab values and patient + demographics and measurements to compute various risk and predictive values for + survival. References to original literature and validation contained in each function + documentation. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cliot + url_git: '' +clipp: + version: 1.1.1 + title: Calculating Likelihoods by Pedigree Paring + maintainer: James Dowty + description: |- + A fast and general implementation of the Elston-Stewart algorithm + that can calculate the likelihoods of large and complex pedigrees. + References for the Elston-Stewart algorithm are + Elston & Stewart (1971) , + Lange & Elston (1975) and + Cannings et al. (1978) . + date_publication: '2022-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clipp + url_git: '' +clipr: + version: 0.8.0 + title: Read and Write from the System Clipboard + maintainer: Matthew Lincoln + description: |- + Simple utility functions to read from and write to + the Windows, OS X, and X11 clipboards. + date_publication: '2022-02-22' + bug_reports: https://github.com/mdlincoln/clipr/issues + url: http://matthewlincoln.net/clipr/ + url_cran: https://CRAN.R-project.org/package=clipr + url_git: https://github.com/mdlincoln/clipr +CliquePercolation: + version: 0.4.0 + title: Clique Percolation for Networks + maintainer: Jens Lange + description: |- + Clique percolation community detection for weighted and + unweighted networks as well as threshold and plotting functions. + For more information see Farkas et al. (2007) + and Palla et al. (2005) . + date_publication: '2022-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CliquePercolation + url_git: '' +clisymbols: + version: 1.2.0 + title: Unicode Symbols at the R Prompt + maintainer: Gábor Csárdi + description: |- + A small subset of Unicode symbols, that are useful + when building command line applications. They fall back to + alternatives on terminals that do not support Unicode. + Many symbols were taken from the 'figures' 'npm' package + (see ). + date_publication: '2017-05-21' + bug_reports: https://github.com/gaborcsardi/clisymbols/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clisymbols + url_git: https://github.com/gaborcsardi/clisymbols +CLME: + version: 2.0-12 + title: Constrained Inference for Linear Mixed Effects Models + maintainer: Casey M. Jelsema + description: |- + Estimation and inference for linear models where some or all of the + fixed-effects coefficients are subject to order restrictions. This package uses + the robust residual bootstrap methodology for inference, and can handle some + structure in the residual variance matrix. + date_publication: '2020-06-07' + bug_reports: https://github.com/jelsema/CLME/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CLME + url_git: '' +clmplus: + version: 1.0.0 + title: Tool-Box of Chain Ladder Plus Models + maintainer: Gabriele Pittarello + description: Implementation of the age-period-cohort models for the claim development + presented in the manuscript 'Replicating and extending chain-ladder via an age-period-cohort + structure on the claim development in a run-off triangle' . + date_publication: '2024-05-15' + bug_reports: https://github.com/gpitt71/clmplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clmplus + url_git: https://github.com/gpitt71/clmplus +clock: + version: 0.7.2 + title: Date-Time Types and Tools + maintainer: Davis Vaughan + description: |- + Provides a comprehensive library for date-time manipulations + using a new family of orthogonal date-time classes (durations, time + points, zoned-times, and calendars) that partition responsibilities so + that the complexities of time zones are only considered when they are + really needed. Capabilities include: date-time parsing, formatting, + arithmetic, extraction and updating of components, and rounding. + date_publication: '2025-01-21' + bug_reports: https://github.com/r-lib/clock/issues + url: https://clock.r-lib.org + url_cran: https://CRAN.R-project.org/package=clock + url_git: https://github.com/r-lib/clock +clockify: + version: 0.1.6 + title: A Wrapper for the 'Clockify' API + maintainer: Andrew B. Collier + description: A wrapper for the Clockify API , making + it possible to query, insert and update time keeping data. + date_publication: '2024-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clockify + url_git: '' +clogitboost: + version: '1.1' + title: Boosting Conditional Logit Model + maintainer: Haolun Shi + description: A set of functions to fit a boosting conditional logit model. + date_publication: '2015-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clogitboost + url_git: '' +clogitL1: + version: '1.5' + title: |- + Fitting Exact Conditional Logistic Regression with Lasso and + Elastic Net Penalties + maintainer: Stephen Reid + description: Tools for the fitting and cross validation of exact conditional logistic + regression models with lasso and elastic net penalties. Uses cyclic coordinate + descent and warm starts to compute the entire path efficiently. + date_publication: '2019-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clogitL1 + url_git: '' +cloneRate: + version: 0.2.3 + title: Estimate Growth Rates from Phylogenetic Trees + maintainer: Brian Johnson + description: |- + Quickly estimate the net growth rate of a + population or clone whose growth can be approximated by a birth-death + branching process. Input should be phylogenetic tree(s) of clone(s) with + edge lengths corresponding to either time or mutations. Based on + coalescent results in Johnson et al. (2023) . Simulation + techniques as well as growth rate methods build on prior work from + Lambert A. (2018) and Stadler T. (2009) + . + date_publication: '2023-09-22' + bug_reports: https://github.com/bdj34/cloneRate/issues + url: https://bdj34.github.io/cloneRate/ + url_cran: https://CRAN.R-project.org/package=cloneRate + url_git: https://github.com/bdj34/cloneRate +CloneSeeker: + version: 1.0.11 + title: Seeking and Finding Clones in Copy Number and Sequencing Data + maintainer: Kevin R. Coombes + description: |- + Defines the classes and functions used to simulate and + to analyze data sets describing copy number variants and, + optionally, sequencing mutations in order to detect clonal subsets. + See Zucker et al. (2019) . + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CloneSeeker + url_git: http://oompa.r-forge.r-project.org/ +CLONETv2: + version: 2.2.1 + title: Clonality Estimates in Tumor + maintainer: Yari Ciani + description: 'Analyze data from next-generation sequencing experiments on genomic + samples. ''CLONETv2'' offers a set of functions to compute allele specific copy + number and clonality from segmented data and SNPs position pileup. The package + has also calculated the clonality of single nucleotide variants given read counts + at mutated positions. The package has been developed at the laboratory of Computational + and Functional Oncology, Department of CIBIO, University of Trento (Italy), under + the supervision of prof Francesca Demichelis. References: Prandi et al. (2014) + ; Carreira et al. (2014) ; + Romanel et al. (2015) .' + date_publication: '2021-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CLONETv2 + url_git: '' +clordr: + version: 1.7.0 + title: |- + Composite Likelihood Inference and Diagnostics for Replicated + Spatial Ordinal Data + maintainer: Ting Fung (Ralph) Ma + description: 'Composite likelihood parameter estimate and asymptotic covariance + matrix are calculated for the spatial ordinal data with replications, where spatial + ordinal response with covariate and both spatial exponential covariance within + subject and independent and identically distributed measurement error. Parameter + estimation can be performed by either solving the gradient function or maximizing + composite log-likelihood. Parametric bootstrapping is used to estimate the Godambe + information matrix and hence the asymptotic standard error and covariance matrix + with parallel processing option. Moreover, the proposed surrogate residual, which + extends the results of Liu and Zhang (2017) , + can act as a useful tool for model diagnostics.' + date_publication: '2022-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clordr + url_git: '' +closeloop: + version: 0.1.0 + title: Integrate Single-Arm Observational Data in Network Meta Analysis + maintainer: Shubhram Pandey + description: Calculate the distance between single-arm observational studies using + covariate information to remove heterogeneity in Network Meta-Analysis (NMA) of + randomized clinical trials. Facilitate the inclusion of observational data in + NMA, enhancing the comprehensiveness and robustness of comparative effectiveness + research. Schmitz (2018) . + date_publication: '2024-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=closeloop + url_git: https://github.com/heorlytics/closeloop +cloudfs: + version: 0.1.3 + title: Streamlined Interface to Interact with Cloud Storage Platforms + maintainer: Iaroslav Domin + description: |- + A unified interface for simplifying cloud storage interactions, + including uploading, downloading, reading, and writing files, with functions + for both 'Google Drive' () and 'Amazon S3' + (). + date_publication: '2024-05-07' + bug_reports: https://github.com/g6t/cloudfs/issues + url: https://g6t.github.io/cloudfs/ + url_cran: https://CRAN.R-project.org/package=cloudfs + url_git: https://github.com/g6t/cloudfs +cloudml: + version: 0.6.1 + title: Interface to the Google Cloud Machine Learning Platform + maintainer: Daniel Falbel + description: |- + Interface to the Google Cloud Machine Learning Platform + , which provides cloud tools for training machine + learning models. + date_publication: '2019-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cloudml + url_git: '' +cloudos: + version: 0.4.0 + title: R Client Library for CloudOS + maintainer: Sangram Keshari Sahu + description: |- + The 'CloudOS' client library for R makes it easy to interact with + CloudOS in the R environment for analysis. + date_publication: '2023-03-17' + bug_reports: https://github.com/lifebit-ai/cloudos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cloudos + url_git: https://github.com/lifebit-ai/cloudos +cloudstoR: + version: 0.2.0 + title: Simplifies Access to Cloudstor API + maintainer: Taren Sanders + description: Access Cloudstor via their WebDAV API. This package can read, write, + and navigate Cloudstor from R. + date_publication: '2022-01-16' + bug_reports: https://github.com/pdparker/cloudstoR/issues + url: https://pdparker.github.io/cloudstoR/ + url_cran: https://CRAN.R-project.org/package=cloudstoR + url_git: https://github.com/pdparker/cloudstoR +cloudUtil: + version: 0.1.12 + title: Cloud Utilization Plots + maintainer: Christian Panse + description: Provides means of plots for comparing utilization data of compute systems. + date_publication: '2016-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cloudUtil + url_git: '' +clptheory: + version: 0.1.0 + title: Compute Price of Production and Labor Values + maintainer: Deepankar Basu + description: |- + Computes the uniform rate of profit, the vector of price of + production and the vector of labor values; and also compute measures of deviation + between relative prices of production and relative values. + . You provide the + input-output data and 'clptheory' does the calculations for you. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clptheory + url_git: https://github.com/dbasu-umass/clptheory/ +clr: + version: 0.1.2 + title: Curve Linear Regression via Dimension Reduction + maintainer: Amandine Pierrot + description: |- + A new methodology for linear regression with both curve response + and curve regressors, which is described in Cho, Goude, Brossat and Yao + (2013) and (2015) + . The key idea behind this methodology is + dimension reduction based on a singular value decomposition in a Hilbert + space, which reduces the curve regression problem to several scalar linear + regression problems. + date_publication: '2019-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clr + url_git: '' +clrng: + version: 0.0.5 + title: Parallel Random Number Generation on GPU + maintainer: Ruoyong Xu + description: |- + Builds on 'gpuR' and utilizes the 'clRNG' ('OpenCL') library to provide efficient tools to generate independent random numbers in parallel on a GPU and + save the results as 'R' objects, ensuring high-quality random numbers even when 'R' is used interactively or in an ad-hoc manner. + Includes Fisher's simulation method adapted from Patefield, William M (1981) and + 'MRG31k3p' Random Number Generator from 'clRNG' library by Advanced Micro Devices, Inc. (2015) . + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clrng + url_git: '' +CLSIEP15: + version: 0.1.0 + title: |- + Clinical and Laboratory Standards Institute (CLSI) EP15-A3 + Calculations + maintainer: Claucio Antonio Rank Filho + description: Calculations of "EP15-A3 document. A manual for user verification of + precision and estimation of bias" CLSI (2014, ISBN:1-56238-966-1). + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CLSIEP15 + url_git: '' +clttools: + version: '1.3' + title: Central Limit Theorem Experiments (Theoretical and Simulation) + maintainer: Simiao Ye + description: Central limit theorem experiments presented by data frames or plots. + Functions include generating theoretical sample space, corresponding probability, + and simulated results as well. + date_publication: '2016-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clttools + url_git: '' +clubpro: + version: 0.6.2 + title: Classification Using Binary Procrustes Rotation + maintainer: Timothy Beechey + description: |- + Implements a classification method described by Grice (2011, ISBN:978-0-12-385194-9) using + binary procrustes rotation; a simplified version of procrustes rotation. + date_publication: '2024-06-07' + bug_reports: https://github.com/timbeechey/clubpro/issues + url: https://timbeechey.github.io/clubpro/ + url_cran: https://CRAN.R-project.org/package=clubpro + url_git: '' +clubSandwich: + version: 0.5.11 + title: |- + Cluster-Robust (Sandwich) Variance Estimators with Small-Sample + Corrections + maintainer: James Pustejovsky + description: |- + Provides several cluster-robust variance estimators (i.e., + sandwich estimators) for ordinary and weighted least squares linear regression + models, including the bias-reduced linearization estimator introduced by Bell + and McCaffrey (2002) + and + developed further by Pustejovsky and Tipton (2017) + . The package includes functions for estimating + the variance- covariance matrix and for testing single- and multiple- + contrast hypotheses based on Wald test statistics. Tests of single regression + coefficients use Satterthwaite or saddle-point corrections. Tests of multiple- + contrast hypotheses use an approximation to Hotelling's T-squared distribution. + Methods are provided for a variety of fitted models, including lm() and mlm + objects, glm(), geeglm() (from package 'geepack'), ivreg() (from package 'AER'), ivreg() (from package 'ivreg' when + estimated by ordinary least squares), plm() (from package 'plm'), gls() and + lme() (from 'nlme'), lmer() (from `lme4`), robu() (from 'robumeta'), and rma.uni() + and rma.mv() (from 'metafor'). + date_publication: '2024-06-20' + bug_reports: https://github.com/jepusto/clubSandwich/issues + url: http://jepusto.github.io/clubSandwich/ + url_cran: https://CRAN.R-project.org/package=clubSandwich + url_git: '' +clue: + version: 0.3-66 + title: Cluster Ensembles + maintainer: Kurt Hornik + description: CLUster Ensembles. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clue + url_git: '' +ClueR: + version: 1.4.2 + title: Cluster Evaluation + maintainer: Pengyi Yang + description: |- + CLUster Evaluation (CLUE) is a computational method for identifying + optimal number of clusters in a given time-course dataset clustered by + cmeans or kmeans algorithms and subsequently identify key kinases or + pathways from each cluster. Its implementation in R is called ClueR. + See README on for more details. + P Yang et al. (2015) . + date_publication: '2023-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClueR + url_git: '' +clugenr: + version: 1.0.3 + title: Multidimensional Cluster Generation Using Support Lines + maintainer: Nuno Fachada + description: |- + An implementation of the clugen algorithm for generating + multidimensional clusters with arbitrary distributions. Each cluster is + supported by a line segment, the position, orientation and length of which + guide where the respective points are placed. This package is described in + Fachada & de Andrade (2023) . + date_publication: '2024-01-11' + bug_reports: https://github.com/clugen/clugenr/issues + url: https://clugen.github.io/clugenr/ + url_cran: https://CRAN.R-project.org/package=clugenr + url_git: https://github.com/clugen/clugenr +CluMP: + version: 0.8.1 + title: Clustering of Micro Panel Data + maintainer: Jan Fojtik + description: Two-step feature-based clustering method designed for micro panel (longitudinal) + data with the artificial panel data generator. See Sobisek, Stachova, Fojtik (2018) + . + date_publication: '2020-11-27' + bug_reports: '' + url: https://arxiv.org/ftp/arxiv/papers/1807/1807.05926.pdf + url_cran: https://CRAN.R-project.org/package=CluMP + url_git: '' +ClusBoot: + version: 1.2.2 + title: |- + Bootstrap a Clustering Solution to Establish the Stability of + the Clusters + maintainer: Sugnet Lubbe + description: |- + Providing a cluster allocation for n samples, either with an $n \times p$ data matrix or an $n \times n$ distance + matrix, a bootstrap procedure is performed. The proportion of bootstrap replicates where a pair of samples + cluster in the same cluster indicates who tightly the samples in a particular cluster clusters together. + date_publication: '2024-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClusBoot + url_git: '' +cluscov: + version: 1.1.0 + title: Clustered Covariate Regression + maintainer: Emmanuel S Tsyawo + description: |- + Clustered covariate regression enables estimation and inference in + both linear and non-linear models with linear predictor functions even when the + design matrix is column rank deficient. Routines in this package implement algorithms + in Soale and Tsyawo (2019) . + date_publication: '2019-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cluscov + url_git: '' +clusEvol: + version: 1.0.0 + title: A Procedure for Cluster Evolution Analytics + maintainer: Víctor Morales-Oñate + description: Cluster Evolution Analytics allows us to use exploratory what if questions + in the sense that the present information of an object is plugged-in a dataset + in a previous time frame so that we can explore its evolution (and of its neighbors) + to the present. See the URL for the papers associated with this package, as for + instance, Morales-Oñate and Morales-Oñate (2024) . + date_publication: '2024-02-26' + bug_reports: https://github.com/vmoprojs/clusEvol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clusEvol + url_git: https://github.com/vmoprojs/clusEvol +ClusPred: + version: 1.1.0 + title: |- + Simultaneous Semi-Parametric Estimation of Clustering and + Regression + maintainer: Matthieu Marbac + description: Parameter estimation of regression models with fixed group effects, + when the group variable is missing while group-related variables are available. + Parametric and semi-parametric approaches described in Marbac et al. (2020) + are implemented. + date_publication: '2021-12-02' + bug_reports: '' + url: https://arxiv.org/abs/2012.14159 + url_cran: https://CRAN.R-project.org/package=ClusPred + url_git: '' +clusrank: + version: 1.0-4 + title: Wilcoxon Rank Tests for Clustered Data + maintainer: Wenjie Wang + description: |- + Non-parametric tests (Wilcoxon rank sum test and Wilcoxon signed rank test) + for clustered data documented in + Jiang et. al (2020) . + date_publication: '2024-02-17' + bug_reports: https://github.com/wenjie2wang/clusrank/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clusrank + url_git: https://github.com/wenjie2wang/clusrank +ClusROC: + version: 1.0.2 + title: |- + ROC Analysis in Three-Class Classification Problems for + Clustered Data + maintainer: Duc-Khanh To + description: |- + Statistical methods for ROC surface analysis in three-class classification problems for clustered data and in presence of covariates. In particular, the package allows to obtain covariate-specific point and interval estimation for: + (i) true class fractions (TCFs) at fixed pairs of thresholds; + (ii) the ROC surface; + (iii) the volume under ROC surface (VUS); + (iv) the optimal pairs of thresholds. + Methods considered in points (i), (ii) and (iv) are proposed and discussed in To et al. (2022) . Referring to point (iv), three different selection criteria are implemented: Generalized Youden Index (GYI), Closest to Perfection (CtP) and Maximum Volume (MV). Methods considered in point (iii) are proposed and discussed in Xiong et al. (2018) . Visualization tools are also provided. We refer readers to the articles cited above for all details. + date_publication: '2022-11-17' + bug_reports: https://github.com/toduckhanh/ClusROC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClusROC + url_git: https://github.com/toduckhanh/ClusROC +ClussCluster: + version: 0.1.0 + title: |- + Simultaneous Detection of Clusters and Cluster-Specific Genes in + High-Throughput Transcriptome Data + maintainer: Li Jun + description: "Implements a new method 'ClussCluster' descried in Ge Jiang and Jun + Li, \"Simultaneous Detection of Clusters and Cluster-Specific Genes in High-throughput + Transcriptome Data\" (Unpublished).\nSimultaneously perform clustering analysis + and signature \tgene selection on high-dimensional transcriptome data sets. \tTo + do so, 'ClussCluster' incorporates a Lasso-type \tregularization penalty term + to the objective function of K-\tmeans so that cell-type-specific signature genes + can be \tidentified while clustering the cells." + date_publication: '2019-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClussCluster + url_git: '' +clust.bin.pair: + version: 0.1.2 + title: Statistical Methods for Analyzing Clustered Matched Pair Data + maintainer: Dan Gopstein + description: |- + Tests, utilities, and case studies for analyzing significance in + clustered binary matched-pair data. The central function clust.bin.pair uses + one of several tests to calculate a Chi-square statistic. Implemented are the + tests Eliasziw (1991) , Obuchowski (1998) + , + Durkalski (2003) , and Yang (2010) + with McNemar (1947) + included for comparison. The utility functions nested.to.contingency and + paired.to.contingency convert data between various useful formats. Thyroids + and psychiatry are the canonical datasets from Obuchowski and Petryshen (1989) + respectively. + date_publication: '2018-02-15' + bug_reports: https://github.com/dgopstein/clust.bin.pair/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clust.bin.pair + url_git: https://github.com/dgopstein/clust.bin.pair +clustAnalytics: + version: 0.5.5 + title: Cluster Evaluation on Graphs + maintainer: Martí Renedo Mirambell + description: |- + Evaluates the stability and significance of clusters on 'igraph' graphs. + Supports weighted and unweighted graphs. Implements the cluster evaluation methods + defined by Arratia A, Renedo M (2021) . Also includes an + implementation of the Reduced Mutual Information introduced by Newman et al. (2020) + . + date_publication: '2024-02-18' + bug_reports: https://github.com/martirm/clustAnalytics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clustAnalytics + url_git: https://github.com/martirm/clustAnalytics +ClustAssess: + version: 1.0.0 + title: Tools for Assessing Clustering + maintainer: Andi Munteanu + description: |- + A set of tools for evaluating clustering robustness using + proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) + ), as well as similarity across methods + and method stability using element-centric clustering comparison (Gates et + al. (2019) ). Additionally, this package + enables stability-based parameter assessment for graph-based clustering + pipelines typical in single-cell data analysis. + date_publication: '2025-01-31' + bug_reports: https://github.com/Core-Bioinformatics/ClustAssess/issues + url: https://core-bioinformatics.github.io/ClustAssess/ + url_cran: https://CRAN.R-project.org/package=ClustAssess + url_git: https://github.com/Core-Bioinformatics/ClustAssess +ClustBlock: + version: 4.0.0 + title: Clustering of Datasets + maintainer: Fabien Llobell + description: Hierarchical and partitioning algorithms to cluster blocks of variables. + The partitioning algorithm includes an option called noise cluster to set aside + atypical blocks of variables. The CLUSTATIS method (for quantitative blocks) (Llobell, + Cariou, Vigneau, Labenne & Qannari (2020) , + Llobell, Vigneau & Qannari (2019) ) and the + CLUSCATA method (for Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne + & Qannari (2019) , Llobell, Giacalone, Labenne + & Qannari (2019) ) are the core of this package. + The CATATIS methods allows to compute some indices and tests to control the quality + of CATA data. Multivariate analysis and clustering of subjects for quantitative + multiblock data, CATA, RATA, Free Sorting and JAR experiments are available. Clustering + of rows in multi-block context (notably with ClusMB strategy) is also included. + date_publication: '2024-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClustBlock + url_git: '' +ClusTCR2: + version: 1.7.3.01 + title: |- + Identifying Similar T Cell Receptor Hyper-Variable Sequences + with 'ClusTCR2' + maintainer: Kerry A. Mullan + description: Enhancing T cell receptor (TCR) sequence analysis, 'ClusTCR2', based + on 'ClusTCR' python program, leverages Hamming distance to compare the complement-determining + region three (CDR3) sequences for sequence similarity, variable gene (V gene) + and length. The second step employs the Markov Cluster Algorithm to identify clusters + within an undirected graph, providing a summary of amino acid motifs and matrix + for generating network plots. Tailored for single-cell RNA-seq data with integrated + TCR-seq information, 'ClusTCR2' is integrated into the Single Cell TCR and Expression + Grouped Ontologies (STEGO) R application or 'STEGO.R'. See the two publications + for more details. Sebastiaan Valkiers, Max Van Houcke, Kris Laukens, Pieter Meysman + (2021) , Kerry A. Mullan, My Ha, Sebastiaan + Valkiers, Nicky de Vrij, Benson Ogunjimi, Kris Laukens, Pieter Meysman (2023) + . + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClusTCR2 + url_git: '' +clustcurv: + version: 2.0.2 + title: Determining Groups in Multiples Curves + maintainer: Nora M. Villanueva + description: |- + A method for determining groups in multiple + curves with an automatic selection of their number based on k-means or + k-medians algorithms. The selection of the optimal number is provided by + bootstrap methods. The methodology can be applied both in regression and survival framework. + Implemented methods are: + Grouping multiple survival curves described by Villanueva et al. (2018) . + date_publication: '2024-10-25' + bug_reports: https://github.com/noramvillanueva/clustcurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clustcurv + url_git: https://github.com/noramvillanueva/clustcurv +clustEff: + version: 0.3.1 + title: Clusters of Effects Curves in Quantile Regression Models + maintainer: Gianluca Sottile + description: Clustering method to cluster both effects curves, through quantile + regression coefficient modeling, and curves in functional data analysis. Sottile + G. and Adelfio G. (2019) . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustEff + url_git: '' +cluster: + version: 2.1.8 + title: |- + "Finding Groups in Data": Cluster Analysis Extended Rousseeuw et + al. + maintainer: Martin Maechler + description: |- + Methods for Cluster analysis. Much extended the original from + Peter Rousseeuw, Anja Struyf and Mia Hubert, + based on Kaufman and Rousseeuw (1990) "Finding Groups in Data". + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cluster + url_git: '' +cluster.datasets: + version: 1.0-1 + title: Cluster Analysis Data Sets + maintainer: Frederick Novomestky + description: A collection of data sets for teaching cluster analysis. + date_publication: '2013-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cluster.datasets + url_git: '' +Cluster.OBeu: + version: 1.2.3 + title: Cluster Analysis 'OpenBudgets.eu' + maintainer: Kleanthis Koupidis + description: Estimate and return the needed parameters for visualisations designed + for 'OpenBudgets' data. Calculate cluster analysis measures + in Budget data of municipalities across Europe, according to the 'OpenBudgets' + data model. It involves a set of techniques and algorithms used to find and divide + the data into groups of similar observations. Also, can be used generally to extract + visualisation parameters convert them to 'JSON' format and use them as input in + a different graphical interface. + date_publication: '2019-12-17' + bug_reports: https://github.com/okgreece/Cluster.OBeu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Cluster.OBeu + url_git: https://github.com/okgreece/Cluster.OBeu +clusterability: + version: 0.1.1.0 + title: Performs Tests for Cluster Tendency of a Data Set + maintainer: Zachariah Neville + description: |- + Test for cluster tendency (clusterability) of a data set. + The methods implemented - reducing the data set to a single dimension using principal component analysis or computing + pairwise distances, and performing a multimodality test like the Dip Test or Silverman's Critical Bandwidth Test - + are described in Adolfsson, Ackerman, and Brownstein (2019) . Such methods can inform whether clustering algorithms + are appropriate for a data set. + date_publication: '2020-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusterability + url_git: '' +ClusterBootstrap: + version: 1.1.2 + title: |- + Analyze Clustered Data with Generalized Linear Models using the + Cluster Bootstrap + maintainer: Mathijs Deen + description: Provides functionality for the analysis of clustered data using the + cluster bootstrap. + date_publication: '2021-02-16' + bug_reports: https://github.com/mathijsdeen/ClusterBootstrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClusterBootstrap + url_git: https://github.com/mathijsdeen/ClusterBootstrap +clusterCrit: + version: 1.3.0 + title: Clustering Indices + maintainer: Iago Giné-Vázquez + description: Package providing functions for computing a collection of clustering + validation or quality criteria and partition comparison indices. + date_publication: '2023-11-23' + bug_reports: https://gitlab.com/iagogv/clusterCrit/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clusterCrit + url_git: https://gitlab.com/iagogv/clusterCrit +ClusteredMutations: + version: 1.0.1 + title: Location and Visualization of Clustered Somatic Mutations + maintainer: David Lora + description: Identification and visualization of groups of closely spaced mutations + in the DNA sequence of cancer genome. The extremely mutated zones are searched + in the symmetric dissimilarity matrix using the anti-Robinson matrix properties. + Different data sets are obtained to describe and plot the clustered mutations + information. + date_publication: '2016-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClusteredMutations + url_git: '' +clusterGeneration: + version: 1.3.8 + title: Random Cluster Generation (with Specified Degree of Separation) + maintainer: Weiliang Qiu + description: |- + We developed the clusterGeneration package to provide functions + for generating random clusters, generating random + covariance/correlation matrices, + calculating a separation index (data and population version) + for pairs of clusters or cluster distributions, and 1-D and 2-D + projection plots to visualize clusters. The package also + contains a function to generate random clusters based on + factorial designs with factors such as degree of separation, + number of clusters, number of variables, number of noisy + variables. + date_publication: '2023-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusterGeneration + url_git: '' +ClusterGVis: + version: 0.1.2 + title: One-Step to Cluster and Visualize Gene Expression Data + maintainer: Jun Zhang + description: Streamlining the clustering and visualization of time-series gene expression + data from RNA-Seq experiments, this tool supports fuzzy c-means and k-means clustering + algorithms. It is compatible with outputs from widely-used packages such as 'Seurat', + 'Monocle', and 'WGCNA', enabling seamless downstream visualization and analysis. + See Lokesh Kumar and Matthias E Futschik (2007) for + more details. + date_publication: '2025-02-14' + bug_reports: https://github.com/junjunlab/ClusterGVis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClusterGVis + url_git: '' +clusterhap: + version: '0.1' + title: Clustering Genotypes in Haplotypes + maintainer: Gaston Quero + description: |- + One haplotype is a combination of SNP + (Single Nucleotide Polymorphisms) within the QTL (Quantitative Trait Loci). + clusterhap groups together all individuals of a population with the same haplotype. + Each group contains individual with the same allele in each SNP, + whether or not missing data. Thus, clusterhap groups individuals, + that to be imputed, have a non-zero probability of having the same alleles + in the entire sequence of SNP's. Moreover, clusterhap calculates such + probability from relative frequencies. + date_publication: '2016-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusterhap + url_git: '' +clusterHD: + version: 1.0.2 + title: Tools for Clustering High-Dimensional Data + maintainer: Jakob Raymaekers + description: |- + Tools for clustering high-dimensional data. + In particular, it contains the methods described in + , + . + date_publication: '2022-08-10' + bug_reports: '' + url: https://arxiv.org/abs/2010.00950 + url_cran: https://CRAN.R-project.org/package=clusterHD + url_git: '' +Clustering: + version: 1.7.10 + title: Techniques for Evaluating Clustering + maintainer: Luis Alfonso Perez Martos + description: 'The design of this package allows us to run different clustering packages + and compare the results between them, to determine which algorithm behaves best + from the data provided. See Martos, L.A.P., García-Vico, Á.M., González, P. et + al.(2023) "Clustering: an R library to facilitate + the analysis and comparison of cluster algorithms.", Martos, L.A.P., García-Vico, + Á.M., González, P. et al. "A Multiclustering Evolutionary Hyperrectangle-Based + Algorithm" and L.A.P., García-Vico, Á.M., González, + P. et al. "An Evolutionary Fuzzy System for Multiclustering in Data Streaming" + .' + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Clustering + url_git: https://github.com/laperez/clustering +clustering.sc.dp: + version: '1.1' + title: |- + Optimal Distance-Based Clustering for Multidimensional Data with + Sequential Constraint + maintainer: Tibor Szkaliczki + description: 'A dynamic programming algorithm for optimal clustering multidimensional + data with sequential constraint. The algorithm minimizes the sum of squares of + within-cluster distances. The sequential constraint allows only subsequent items + of the input data to form a cluster. The sequential constraint is typically required + in clustering data streams or items with time stamps such as video frames, GPS + signals of a vehicle, movement data of a person, e-pen data, etc. The algorithm + represents an extension of ''Ckmeans.1d.dp'' to multiple dimensional spaces. Similarly + to the one-dimensional case, the algorithm guarantees optimality and repeatability + of clustering. Method clustering.sc.dp() can find the optimal clustering if the + number of clusters is known. Otherwise, methods findwithinss.sc.dp() and backtracking.sc.dp() + can be used. See Szkaliczki, T. (2016) "clustering.sc.dp: Optimal Clustering with + Sequential Constraint by Using Dynamic Programming" + for more information.' + date_publication: '2023-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustering.sc.dp + url_git: '' +clusterMI: + version: '1.5' + title: Cluster Analysis with Missing Values by Multiple Imputation + maintainer: Vincent Audigier + description: |- + Allows clustering of incomplete observations by addressing missing values using multiple imputation. For achieving this goal, the methodology consists in three steps, following Audigier and Niang 2022 . I) Missing data imputation using dedicated models. Four multiple imputation methods are proposed, two are based on joint modelling and two are fully sequential methods, as discussed in Audigier et al. (2021) . II) cluster analysis of imputed data sets. Six clustering methods are available (distances-based or model-based), but custom methods can also be easily used. III) Partition pooling. The set of partitions is aggregated using Non-negative Matrix Factorization based method. An associated instability measure is computed by bootstrap (see Fang, Y. and Wang, J., 2012 ). Among applications, this instability measure can be used to choose a number of clusters with missing values. + The package also proposes several diagnostic tools to tune the number of imputed data sets, to tune the number of iterations in fully sequential imputation, to check the fit of imputation models, etc. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusterMI + url_git: '' +clustermole: + version: 1.1.1 + title: |- + Unbiased Single-Cell Transcriptomic Data Cell Type + Identification + maintainer: Igor Dolgalev + description: Assignment of cell type labels to single-cell RNA sequencing (scRNA-seq) + clusters is often a time-consuming process that involves manual inspection of + the cluster marker genes complemented with a detailed literature search. This + is especially challenging when unexpected or poorly described populations are + present. The clustermole R package provides methods to query thousands of human + and mouse cell identity markers sourced from a variety of databases. + date_publication: '2024-01-08' + bug_reports: https://github.com/igordot/clustermole/issues + url: https://igordot.github.io/clustermole/ + url_cran: https://CRAN.R-project.org/package=clustermole + url_git: '' +clustermq: + version: 0.9.7 + title: |- + Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, + PBS/Torque) + maintainer: Michael Schubert + description: |- + Evaluate arbitrary function calls using workers on HPC schedulers + in single line of code. All processing is done on the network without + accessing the file system. Remote schedulers are supported via SSH. + date_publication: '2025-02-09' + bug_reports: https://github.com/mschubert/clustermq/issues + url: https://mschubert.github.io/clustermq/ + url_cran: https://CRAN.R-project.org/package=clustermq + url_git: '' +clusternomics: + version: 0.1.1 + title: Integrative Clustering for Heterogeneous Biomedical Datasets + maintainer: Evelina Gabasova + description: |- + Integrative context-dependent clustering for heterogeneous + biomedical datasets. Identifies local clustering structures in related + datasets, and a global clusters that exist across the datasets. + date_publication: '2017-03-14' + bug_reports: https://github.com/evelinag/clusternomics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clusternomics + url_git: https://github.com/evelinag/clusternomics +ClusterR: + version: 1.3.3 + title: |- + Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids + and Affinity Propagation Clustering + maintainer: Lampros Mouselimis + description: 'Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and + affinity propagation clustering with the option to plot, validate, predict (new + data) and estimate the optimal number of clusters. The package takes advantage + of ''RcppArmadillo'' to speed up the computationally intensive parts of the functions. + For more information, see (i) "Clustering in an Object-Oriented Environment" by + Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, + ; (ii) "Web-scale k-means clustering" by D. Sculley + (2010), ACM Digital Library, ; (iii) "Armadillo: + a template-based C++ library for linear algebra" by Sanderson et al (2016), The + Journal of Open Source Software, ; (iv) "Clustering by + Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science + 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, .' + date_publication: '2024-06-18' + bug_reports: https://github.com/mlampros/ClusterR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClusterR + url_git: https://github.com/mlampros/ClusterR +ClusterRankTest: + version: '1.0' + title: Rank Tests for Clustered Data + maintainer: Sandipan Dutta + description: Nonparametric rank based tests (rank-sum tests and signed-rank tests) + for clustered data, especially useful for clusters having informative cluster + size and intra-cluster group size. + date_publication: '2016-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClusterRankTest + url_git: '' +clusterRepro: + version: '0.9' + title: Reproducibility of Gene Expression Clusters + maintainer: Rob Tibshirani + description: |- + This is a function for validating microarray clusters via reproducibility, + based on the paper referenced below. + date_publication: '2018-10-15' + bug_reports: '' + url: https://www.ncbi.nlm.nih.gov/pubmed/16613834. + url_cran: https://CRAN.R-project.org/package=clusterRepro + url_git: '' +clusterSEs: + version: 2.6.5 + title: Calculate Cluster-Robust p-Values and Confidence Intervals + maintainer: Justin Esarey + description: |- + Calculate p-values and confidence intervals using cluster-adjusted + t-statistics (based on Ibragimov and Muller (2010) , pairs cluster bootstrapped t-statistics, and wild cluster bootstrapped t-statistics (the latter two techniques based on Cameron, Gelbach, and Miller (2008) . Procedures are included for use with GLM, ivreg, plm (pooling or fixed effects), and mlogit models. + date_publication: '2021-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusterSEs + url_git: '' +clusterSim: + version: 0.51-5 + title: Searching for Optimal Clustering Procedure for a Data Set + maintainer: Andrzej Dudek + description: "Distance measures (GDM1, GDM2,\tSokal-Michener, Bray-Curtis, for symbolic + interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, + Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap,\tDavies-Bouldin),\tdata + normalization formulas (metric data, interval-valued symbolic data), data generation + (typical and non-typical data), HINoV method,\treplication analysis, linear ordering + methods, spectral clustering, agreement indices between two partitions, plot functions + (for categorical and symbolic interval-valued data).\n(MILLIGAN, G.W., COOPER, + M.C. (1985) ,\nHUBERT, L., ARABIE, P. (1985) ,\nRAND, + W.M. (1971) ,\nJAJUGA, K., WALESIAK, M. (2000) + ,\nMILLIGAN, G.W., COOPER, M.C. (1988) ,\nJAJUGA, + K., WALESIAK, M., BAK, A. (2003) ,\nDAVIES, + D.L., BOULDIN, D.W. (1979) ,\nCALINSKI, T., HARABASZ, + J. (1974) ,\nHUBERT, L. (1974) ,\nTIBSHIRANI, + R., WALTHER, G., HASTIE, T. (2001) ,\nBRECKENRIDGE, + J.N. (2000) ,\nWALESIAK, M., DUDEK, A. (2008) + )." + date_publication: '2024-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusterSim + url_git: '' +ClusterStability: + version: 1.0.4 + title: |- + Assessment of Stability of Individual Objects or Clusters in + Partitioning Solutions + maintainer: Etienne Lord + description: |- + Allows one to assess the stability of individual objects, clusters + and whole clustering solutions based on repeated runs of the K-means and K-medoids + partitioning algorithms. + date_publication: '2023-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClusterStability + url_git: '' +clustertend: + version: '1.7' + title: Check the Clustering Tendency + maintainer: Kevin Wright + description: Calculate some statistics aiming to help analyzing the clustering tendency + of given data. In the first version, Hopkins statistic is implemented. See Hopkins + and Skellam (1954) . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustertend + url_git: '' +ClusterVAR: + version: 0.0.8 + title: Fitting Latent Class Vector-Autoregressive (VAR) Models + maintainer: Anja Ernst + description: Estimates latent class vector-autoregressive models via EM algorithm + on time-series data for model-based clustering and classification. Includes model + selection criteria for selecting the number of lags and clusters. + date_publication: '2024-12-09' + bug_reports: https://github.com/anieBee/ClusterVAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClusterVAR + url_git: '' +ClustGeo: + version: '2.1' + title: Hierarchical Clustering with Spatial Constraints + maintainer: Marie Chavent + description: |- + Implements a Ward-like hierarchical clustering + algorithm including soft spatial/geographical constraints. + date_publication: '2021-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClustGeo + url_git: '' +ClustImpute: + version: 0.2.4 + title: K-Means Clustering with Build-in Missing Data Imputation + maintainer: Oliver Pfaffel + description: This k-means algorithm is able to cluster data with missing values + and as a by-product completes the data set. The implementation can deal with missing + values in multiple variables and is computationally efficient since it iteratively + uses the current cluster assignment to define a plausible distribution for missing + value imputation. Weights are used to shrink early random draws for missing values + (i.e., draws based on the cluster assignments after few iterations) towards the + global mean of each feature. This shrinkage slowly fades out after a fixed number + of iterations to reflect the increasing credibility of cluster assignments. See + the vignette for details. + date_publication: '2021-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClustImpute + url_git: '' +clustlearn: + version: 1.0.0 + title: Learn Clustering Techniques Through Examples and Code + maintainer: Eduardo Ruiz Sabajanes + description: |- + Clustering methods, which (if asked) can provide step-by-step + explanations of the algorithms used, as described in Ezugwu et. al., (2022) + ; and datasets to test them on, which + highlight the strengths and weaknesses of each technique, as presented in + the clustering section of 'scikit-learn' (Pedregosa et al., 2011) + . + date_publication: '2023-09-14' + bug_reports: https://github.com/Ediu3095/clustlearn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=clustlearn + url_git: https://github.com/Ediu3095/clustlearn +ClustMC: + version: 0.1.1 + title: Cluster-Based Multiple Comparisons + maintainer: Santiago Garcia Sanchez + description: |- + Multiple comparison techniques are typically applied following an F + test from an ANOVA to decide which means are significantly different from + one another. As an alternative to traditional methods, cluster analysis + can be performed to group the means of different treatments into + non-overlapping clusters. Treatments in different groups are considered + statistically different. Several approaches have been proposed, with varying + clustering methods and cut-off criteria. This package implements + cluster-based multiple comparisons tests and also provides a visual + representation in the form of a dendrogram. Di Rienzo, J. A., Guzman, A. W., + & Casanoves, F. (2002) . Bautista, M. G., Smith, D. + W., & Steiner, R. L. (1997) . + date_publication: '2024-08-27' + bug_reports: https://github.com/SGS2000/ClustMC/issues + url: https://sgs2000.github.io/ClustMC/ + url_cran: https://CRAN.R-project.org/package=ClustMC + url_git: https://github.com/SGS2000/ClustMC +clustMD: + version: 1.2.1 + title: Model Based Clustering for Mixed Data + maintainer: Damien McParland + description: |- + Model-based clustering of mixed data (i.e. data which consist of + continuous, binary, ordinal or nominal variables) using a parsimonious + mixture of latent Gaussian variable models. + date_publication: '2017-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustMD + url_git: '' +clustMixType: + version: 0.4-2 + title: k-Prototypes Clustering for Mixed Variable-Type Data + maintainer: Gero Szepannek + description: |- + Functions to perform k-prototypes partitioning clustering for + mixed variable-type data according to Z.Huang (1998): Extensions to the k-Means + Algorithm for Clustering Large Data Sets with Categorical Variables, Data Mining + and Knowledge Discovery 2, 283-304. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustMixType + url_git: '' +clustNet: + version: 1.2.0 + title: Network-Based Clustering + maintainer: Fritz Bayer + description: Network-based clustering using a Bayesian network mixture model with + optional covariate adjustment. + date_publication: '2024-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustNet + url_git: '' +ClustOfVar: + version: '1.1' + title: Clustering of Variables + maintainer: Marie Chavent + description: Cluster analysis of a set of variables. Variables can be quantitative, + qualitative or a mixture of both. + date_publication: '2017-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClustOfVar + url_git: '' +ClusTorus: + version: 0.2.2 + title: Prediction and Clustering on the Torus by Conformal Prediction + maintainer: Seungki Hong + description: |- + Provides various tools of for clustering multivariate angular + data on the torus. The package provides angular + adaptations of usual clustering methods such as the k-means + clustering, pairwise angular distances, which can be used as an + input for distance-based clustering algorithms, and implements + clustering based on the conformal prediction framework. Options + for the conformal scores include scores based on a kernel density + estimate, multivariate von Mises mixtures, and naive k-means clusters. + Moreover, the package provides some basic data handling tools for + angular data. + date_publication: '2022-01-04' + bug_reports: https://github.com/sungkyujung/ClusTorus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ClusTorus + url_git: https://github.com/sungkyujung/ClusTorus +clustra: + version: 0.2.1 + title: Clustering Longitudinal Trajectories + maintainer: George Ostrouchov + description: |- + Clusters longitudinal trajectories over time (can be unequally + spaced, unequal length time series and/or partially overlapping series) on + a common time axis. Performs k-means clustering on a single continuous + variable measured over time, where each mean is defined by a thin plate + spline fit to all points in a cluster. Distance is MSE across trajectory + points to cluster spline. Provides graphs of derived cluster splines, + silhouette plots, and Adjusted Rand Index evaluations of the number + of clusters. Scales well to large data with multicore parallelism available + to speed computation. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustra + url_git: '' +clusTransition: + version: '1.0' + title: Monitor Changes in Cluster Solutions of Dynamic Datasets + maintainer: Muhammad Atif + description: |- + Monitor and trace changes in clustering solutions of accumulating datasets + at successive time points. The clusters can adopt External and Internal transition at + succeeding time points. The External transitions comprise of Survived, Merged, Split, + Disappeared, and newly Emerged candidates. In contrast, Internal transition includes changes + in location and cohesion of the survived clusters. The package uses MONIC framework developed by + Spiliopoulou, Ntoutsi, Theodoridis, and Schult (2006) . + date_publication: '2021-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clusTransition + url_git: '' +clustrd: + version: 1.4.0 + title: Methods for Joint Dimension Reduction and Clustering + maintainer: Angelos Markos + description: A class of methods that combine dimension reduction and clustering + of continuous, categorical or mixed-type data (Markos, Iodice D'Enza and van de + Velden 2019; ). For continuous data, the package contains + implementations of factorial K-means (Vichi and Kiers 2001; ) + and reduced K-means (De Soete and Carroll 1994; ); + both methods that combine principal component analysis with K-means clustering. + For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane + 2006; ), i-FCB (Iodice D'Enza and Palumbo 2013, + ) and Cluster Correspondence Analysis (van de Velden, + Iodice D'Enza and Palumbo 2017; ), which combine + multiple correspondence analysis with K-means. For mixed-type data, it provides + mixed Reduced K-means and mixed Factorial K-means (van de Velden, Iodice D'Enza + and Markos 2019; ), which combine PCA for mixed-type data + with K-means. + date_publication: '2022-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustrd + url_git: '' +clustree: + version: 0.5.1 + title: Visualise Clusterings at Different Resolutions + maintainer: Luke Zappia + description: |- + Deciding what resolution to use can be a difficult question when + approaching a clustering analysis. One way to approach this problem is to + look at how samples move as the number of clusters increases. This package + allows you to produce clustering trees, a visualisation for interrogating + clusterings as resolution increases. + date_publication: '2023-11-05' + bug_reports: https://github.com/lazappi/clustree/issues + url: https://lazappi.github.io/clustree/ + url_cran: https://CRAN.R-project.org/package=clustree + url_git: https://github.com/lazappi/clustree +clustringr: + version: '1.0' + title: Cluster Strings by Edit-Distance + maintainer: Dan S. Reznik + description: |- + Returns an edit-distance based clusterization of an input vector of strings. + Each cluster will contain a set of strings w/ small mutual edit-distance + (e.g., Levenshtein, optimum-sequence-alignment, Damerau-Levenshtein), as computed by + stringdist::stringdist(). The set of all mutual edit-distances is then used by + graph algorithms (from package 'igraph') to single out subsets of high connectivity. + date_publication: '2019-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustringr + url_git: '' +CLUSTShiny: + version: 0.1.0 + title: Interactive Document for Working with Cluster Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of cluster analysis using 'rmarkdown' + and 'shiny' packages. Runtime examples are provided in the package function as + well as at . + date_publication: '2019-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CLUSTShiny + url_git: '' +clustTMB: + version: 0.1.0 + title: Spatio-Temporal Finite Mixture Model using 'TMB' + maintainer: Andrea M. Havron + description: |- + Fits a spatio-temporal finite mixture model using 'TMB'. + Covariate, spatial and temporal random effects can be incorporated + into the gating formula using multinomial logistic regression, the + expert formula using a generalized linear mixed model framework, or + both. + date_publication: '2024-10-14' + bug_reports: https://github.com/Andrea-Havron/clustTMB/issues + url: https://andrea-havron.github.io/clustTMB/ + url_cran: https://CRAN.R-project.org/package=clustTMB + url_git: https://github.com/Andrea-Havron/clustTMB +clustur: + version: 0.1.1 + title: Clustering + maintainer: Patrick Schloss + description: 'A tool that implements the clustering algorithms from ''mothur'' (Schloss + PD et al. (2009) ). ''clustur'' make use of the cluster() + and make.shared() command from ''mothur''. Our cluster() function has five different + algorithms implemented: ''OptiClust'', ''furthest'', ''nearest'', ''average'', + and ''weighted''. ''OptiClust'' is an optimized clustering method for Operational + Taxonomic Units, and you can learn more here, (Westcott SL, Schloss PD (2017) + ). The make.shared() command is always applied + at the end of the clustering command. This functionality allows us to generate + and create clustering and abundance data efficiently.' + date_publication: '2024-11-25' + bug_reports: https://github.com/SchlossLab/clustur/issues + url: http://www.schlosslab.org/clustur/ + url_cran: https://CRAN.R-project.org/package=clustur + url_git: https://github.com/SchlossLab/clustur +ClustVarLV: + version: 2.1.1 + title: Clustering of Variables Around Latent Variables + maintainer: Evelyne Vigneau + description: Functions for the clustering of variables around Latent Variables, + for 2-way or 3-way data. Each cluster of variables, which may be defined as a + local or directional cluster, is associated with a latent variable. External variables + measured on the same observations or/and additional information on the variables + can be taken into account. A "noise" cluster or sparse latent variables can also + be defined. + date_publication: '2022-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClustVarLV + url_git: '' +clustvarsel: + version: 2.3.4 + title: Variable Selection for Gaussian Model-Based Clustering + maintainer: Luca Scrucca + description: Variable selection for Gaussian model-based clustering as implemented + in the 'mclust' package. The methodology allows to find the (locally) optimal + subset of variables in a data set that have group/cluster information. A greedy + or headlong search can be used, either in a forward-backward or backward-forward + direction, with or without sub-sampling at the hierarchical clustering stage for + starting 'mclust' models. By default the algorithm uses a sequential search, but + parallelisation is also available. + date_publication: '2020-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clustvarsel + url_git: '' +ClusVis: + version: 1.2.0 + title: |- + Gaussian-Based Visualization of Gaussian and Non-Gaussian + Model-Based Clustering + maintainer: Matthieu Marbac + description: Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based + Clustering done on any type of data. Visualization is based on the probabilities + of classification. + date_publication: '2019-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ClusVis + url_git: '' +clv: + version: 0.3-2.4 + title: Cluster Validation Techniques + maintainer: Lukasz Nieweglowski + description: |- + Package contains most of the popular internal and external + cluster validation methods ready to use for the most of the + outputs produced by functions coming from package "cluster". + Package contains also functions and examples of usage for + cluster stability approach that might be applied to algorithms + implemented in "cluster" package as well as user defined + clustering algorithms. + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clv + url_git: '' +clValid: + version: '0.7' + title: Validation of Clustering Results + maintainer: Vasyl Pihur + description: 'Statistical and biological validation of clustering results. This + package implements Dunn Index, Silhouette, Connectivity, Stability, BHI and BSI. + Further information can be found in Brock, G et al. (2008) .' + date_publication: '2021-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=clValid + url_git: '' +CLVTools: + version: 0.11.2 + title: Tools for Customer Lifetime Value Estimation + maintainer: Patrick Bachmann + description: |- + A set of state-of-the-art probabilistic modeling approaches to derive estimates of individual customer lifetime values (CLV). + Commonly, probabilistic approaches focus on modelling 3 processes, i.e. individuals' attrition, transaction, and spending process. + Latent customer attrition models, which are also known as "buy-'til-you-die models", model the attrition as well as the transaction process. + They are used to make inferences and predictions about transactional patterns of individual customers such as their future purchase behavior. + Moreover, these models have also been used to predict individuals’ long-term engagement in activities such as playing an online game or + posting to a social media platform. The spending process is usually modelled by a separate probabilistic model. Combining these results yields in + lifetime values estimates for individual customers. + This package includes fast and accurate implementations of various probabilistic models for non-contractual settings + (e.g., grocery purchases or hotel visits). All implementations support time-invariant covariates, which can be used to control for e.g., + socio-demographics. If such an extension has been proposed in literature, we further provide the possibility to control for time-varying + covariates to control for e.g., seasonal patterns. + Currently, the package includes the following latent attrition models to model individuals' attrition and transaction process: + [1] Pareto/NBD model (Pareto/Negative-Binomial-Distribution), + [2] the Extended Pareto/NBD model (Pareto/Negative-Binomial-Distribution with time-varying covariates), + [3] the BG/NBD model (Beta-Gamma/Negative-Binomial-Distribution) and the + [4] GGom/NBD (Gamma-Gompertz/Negative-Binomial-Distribution). + Further, we provide an implementation of the Gamma/Gamma model to model the spending process of individuals. + date_publication: '2024-12-02' + bug_reports: https://github.com/bachmannpatrick/CLVTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CLVTools + url_git: https://github.com/bachmannpatrick/CLVTools +cmaes: + version: 1.0-12 + title: Covariance Matrix Adapting Evolutionary Strategy + maintainer: Olaf Mersmann + description: Single objective optimization using a CMA-ES. + date_publication: '2022-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmaes + url_git: '' +cmaesr: + version: 1.0.3 + title: Covariance Matrix Adaptation Evolution Strategy + maintainer: Jakob Bossek + description: |- + Pure R implementation of the Covariance Matrix Adaptation - + Evolution Strategy (CMA-ES) with optional restarts (IPOP-CMA-ES). + date_publication: '2016-12-04' + bug_reports: https://github.com/jakobbossek/cmaesr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cmaesr + url_git: https://github.com/jakobbossek/cmaesr +cmahalanobis: + version: 0.5.0 + title: |- + Calculate Distance Measures for a Given List of Data Frames with + Factors + maintainer: Flavio Gioia + description: It provides functions that calculate Mahalanobis distance, Euclidean + distance, Manhattan distance, Chebyshev distance, Hamming distance, Canberra distance, + Minkowski distance, Cosine distance, Bhattacharyya distance, Jaccard distance, + Hellinger distance, Bray-Curtis distance, Sorensen-Dice distance between each + pair of species in a list of data frames. These metrics are fundamental in various + fields, such as cluster analysis, classification, and other applications of machine + learning and data mining, where assessing similarity or dissimilarity between + data is crucial. The package is designed to be flexible and easily integrated + into data analysis workflows, providing reliable tools for evaluating distances + in multidimensional contexts. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmahalanobis + url_git: '' +CMAPSS: + version: 0.1.1 + title: Commercial Modular Aero-Propulsion System Simulation Data Set + maintainer: Morteza Amini + description: Contains the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) + data set. + date_publication: '2021-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMAPSS + url_git: '' +CMapViz: + version: 0.1.0 + title: |- + Representation Tool For Output Of Connectivity Map (CMap) + Analysis + maintainer: Raphaël Bonnet + description: |- + Automatically displays graphical visualization for exported data table (permutated results) from Connectivity Map (CMap) (2006) . + It allows the representation of the statistics (p-value and enrichment) according to each cell lines in the form of a bubble plot. + date_publication: '2019-11-07' + bug_reports: https://github.com/Peyronlab/CMapViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CMapViz + url_git: '' +cmaRs: + version: 0.1.3 + title: |- + Implementation of the Conic Multivariate Adaptive Regression + Splines in R + maintainer: Ceyda Yazici + description: |- + An implementation of 'Conic Multivariate Adaptive Regression Splines (CMARS)' in R. + See Weber et al. (2011) CMARS: a new contribution to nonparametric regression with + multivariate adaptive regression splines supported by continuous optimization, + . It constructs models by using the terms + obtained from the forward step of MARS and then estimates parameters by using + 'Tikhonov' regularization and conic quadratic optimization. It is possible to + construct models for prediction and binary classification. It provides performance + measures for the model developed. The package needs the optimisation software 'MOSEK' + to construct the models. Please follow the instructions in + 'Rmosek' for the installation. + date_publication: '2023-07-04' + bug_reports: https://github.com/yaziciceyda/cmaRs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cmaRs + url_git: '' +CMatching: + version: '2.4' + title: Matching Algorithms for Causal Inference with Clustered Data + maintainer: Massimo Cannas + description: Provides functions to perform matching algorithms for causal inference + with clustered data, as described in B. Arpino and M. Cannas (2016) . + Pure within-cluster and preferential within-cluster matching are implemented. + Both algorithms provide causal estimates with cluster-adjusted estimates of standard + errors. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMatching + url_git: '' +cmbClust: + version: 0.0.1 + title: Conditional Mixture Modeling and Model-Based Clustering + maintainer: Yang Wang + description: Conditional mixture model fitted via EM (Expectation Maximization) + algorithm for model-based clustering, including parsimonious procedure, optimal + conditional order exploration, and visualization. + date_publication: '2022-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmbClust + url_git: '' +cmce: + version: 0.1.0 + title: |- + Computer Model Calibration for Deterministic and Stochastic + Simulators + maintainer: Matthew T. Pratola + description: |- + Implements the Bayesian calibration model described + in Pratola and Chkrebtii (2018) for stochastic + and deterministic simulators. Additive and multiplicative discrepancy models + are currently supported. See for + more information and examples. + date_publication: '2018-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmce + url_git: '' +cmcR: + version: 0.1.11 + title: An Implementation of the 'Congruent Matching Cells' Method + maintainer: Joe Zemmels + description: |- + An open-source implementation of the 'Congruent Matching Cells' + method for cartridge case identification as proposed by Song (2013) as well + as an extension of the method proposed by Tong et al. (2015) . + Provides a wide range of pre, inter, and post-processing options when + working with cartridge case scan data and their associated comparisons. See + the cmcR package website for more details and examples. + date_publication: '2022-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmcR + url_git: '' +cmdfun: + version: 1.0.2 + title: Framework for Building Interfaces to Shell Commands + maintainer: Spencer Nystrom + description: |- + Writing interfaces to command line software is cumbersome. + 'cmdfun' provides a framework for building function calls to seamlessly + interface with shell commands by allowing lazy evaluation of command line arguments. + 'cmdfun' also provides methods for handling user-specific paths to tool installs or secrets like API keys. + Its focus is to equally serve package builders who wish to wrap command line software, and to help analysts stay inside + R when they might usually leave to execute non-R software. + date_publication: '2020-10-10' + bug_reports: https://github.com/snystrom/cmdfun + url: https://snystrom.github.io/cmdfun/ + url_cran: https://CRAN.R-project.org/package=cmdfun + url_git: https://github.com/snystrom/cmdfun +cmenet: + version: 0.1.2 + title: Bi-Level Selection of Conditional Main Effects + maintainer: Simon Mak + description: Provides functions for implementing cmenet - a bi-level variable selection + method for conditional main effects (see Mak and Wu (2018) ). + CMEs are reparametrized interaction effects which capture the conditional impact + of a factor at a fixed level of another factor. Compared to traditional two-factor + interactions, CMEs can quantify more interpretable interaction effects in many + problems. The current implementation performs variable selection on only binary + CMEs; we are working on an extension for the continuous setting. + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmenet + url_git: '' +CMF: + version: 1.0.3 + title: Collective Matrix Factorization + maintainer: Felix Held + description: "Collective matrix factorization (CMF) finds joint low-rank\nrepresentations + for a collection of matrices with shared row or column\nentities. This code learns + a variational Bayesian approximation for CMF,\nsupporting multiple likelihood + potentials and missing data, while\nidentifying both factors shared by multiple + matrices and factors private\nfor each matrix. For further details on the method + see\nKlami et al. (2014) .\nThe package can also be used to learn + Bayesian canonical correlation\nanalysis (CCA) and group factor analysis (GFA) + models, both of which are\nspecial cases of CMF. This is likely to be useful for + people looking for\nCCA and GFA solutions supporting missing data and non-Gaussian + likelihoods.\nSee Klami et al. (2013) \nand\tVirtanen + et al. (2012) \nfor details + on Bayesian CCA and GFA, respectively." + date_publication: '2022-08-09' + bug_reports: https://github.com/cyianor/CMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CMF + url_git: '' +cmfrec: + version: 3.5.1-3 + title: Collective Matrix Factorization for Recommender Systems + maintainer: David Cortes + description: |- + Collective matrix factorization (a.k.a. multi-view or multi-way factorization, + Singh, Gordon, (2008) ) tries to approximate a (potentially very sparse + or having many missing values) matrix 'X' as the product of two low-dimensional matrices, + optionally aided with secondary information matrices about rows and/or columns of 'X', + which are also factorized using the same latent components. + The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. + Implements extensions of the original model (Cortes, (2018) ) and can produce + different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, + (2008) ), the 'weighted-lambda-regularization' model, + (Zhou, Wilkinson, Schreiber, Pan, (2008) ), + or the enhanced model with 'implicit features' (Rendle, Zhang, + Koren, (2019) ), with or without side information. Can use gradient-based + procedures or alternating-least squares procedures (Koren, Bell, Volinsky, (2009) + ), with either a Cholesky solver, a faster conjugate gradient solver + (Takacs, Pilaszy, Tikk, (2011) ), or a non-negative + coordinate descent solver (Franc, Hlavac, Navara, (2005) ), + providing efficient methods for sparse and dense data, and mixtures thereof. + Supports L1 and L2 regularization in the main models, + offers alternative most-popular and content-based models, and implements functionality + for cold-start recommendations and imputation of 2D data. + date_publication: '2023-12-09' + bug_reports: https://github.com/david-cortes/cmfrec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cmfrec + url_git: https://github.com/david-cortes/cmfrec +CMFsurrogate: + version: '1.0' + title: Calibrated Model Fusion Approach to Combine Surrogate Markers + maintainer: Layla Parast + description: Uses a calibrated model fusion approach to optimally combine multiple + surrogate markers. Specifically, two initial estimates of optimal composite scores + of the markers are obtained; the optimal calibrated combination of the two estimated + scores is then constructed which ensures both validity of the final combined score + and optimality with respect to the proportion of treatment effect explained (PTE) + by the final combined score. The primary function, pte.estimate.multiple(), estimates + the PTE of the identified combination of multiple surrogate markers. Details are + described in Wang et al (2022) . + date_publication: '2022-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMFsurrogate + url_git: '' +CMGFM: + version: '1.1' + title: Covariate-Augumented Generalized Factor Model + maintainer: Wei Liu + description: Covariate-augumented generalized factor model is designed to account + for cross-modal heterogeneity, capture nonlinear dependencies among the data, + incorporate additional information, and provide excellent interpretability while + maintaining high computational efficiency. + date_publication: '2024-06-25' + bug_reports: https://github.com/feiyoung/CMGFM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CMGFM + url_git: '' +cmhc: + version: 0.2.10 + title: Access, Retrieve, and Work with CMHC Data + maintainer: Jens von Bergmann + description: Wrapper around the Canadian Mortgage and Housing Corporation (CMHC) + web interface. It enables programmatic and reproducible access to a wide variety + of housing data from CMHC. + date_publication: '2025-02-04' + bug_reports: https://github.com/mountainMath/cmhc/issues + url: https://mountainmath.github.io/cmhc/ + url_cran: https://CRAN.R-project.org/package=cmhc + url_git: https://github.com/mountainMath/cmhc +CMHNPA: + version: 1.1.1 + title: Cochran-Mantel-Haenszel and Nonparametric ANOVA + maintainer: G. C. Livingston Jr + description: 'Cochran-Mantel-Haenszel methods (Cochran (1954) ; + Mantel and Haenszel (1959) ; Landis et al. (1978) ) + are a suite of tests applicable to categorical data. A competitor to those tests + is the procedure of Nonparametric ANOVA which was initially introduced in Rayner + and Best (2013) . The methodology was then extended in + Rayner et al. (2015) . This package employs functions + related to both methodologies and serves as an accompaniment to the book: An Introduction + to Cochran–Mantel–Haenszel and Non-Parametric ANOVA. The package also contains + the data sets used in that text.' + date_publication: '2023-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMHNPA + url_git: '' +CMHSU: + version: 0.0.6.9 + title: |- + Mental Health Status, Substance Use Status and their Concurrent + Status in North American Healthcare Administrative Databases + maintainer: Chel Hee Lee + description: 'Patients'' Mental Health (MH) status, Substance Use (SU) status, and + concurrent MH/SU status in the American/Canadian Healthcare Administrative Databases + can be identified. The detection is based on given parameters of interest by clinicians + including the list of plausible ICD MH/SU codes (3/4/5 characters), the required + number of visits of hospital for MH/SU , the required number of visits of service + physicians for MH/SU, and the maximum time span within MH visits, within SU visits, + and, between MH and SU visits. Methods are described in: Khan S , + Keen C, et al. (2021) , Lavergne MR, et al. (2022) , + Casillas, S M, et al. (2022) , CIHI (2022) , + CDC (2024) , WHO (2019) .' + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMHSU + url_git: '' +cml: + version: 0.2.2 + title: Conditional Manifold Learning + maintainer: Anh Tuan Bui + description: Finds a low-dimensional embedding of high-dimensional data, conditioning + on available manifold information. The current version supports conditional MDS + (based on either conditional SMACOF in Bui (2021) or closed-form + solution in Bui (2022) ) and conditional ISOMAP + in Bui (2021) . + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cml + url_git: '' +CMLS: + version: 1.0-1 + title: Constrained Multivariate Least Squares + maintainer: Nathaniel E. Helwig + description: Solves multivariate least squares (MLS) problems subject to constraints + on the coefficients, e.g., non-negativity, orthogonality, equality, inequality, + monotonicity, unimodality, smoothness, etc. Includes flexible functions for solving + MLS problems subject to user-specified equality and/or inequality constraints, + as well as a wrapper function that implements 24 common constraint options. Also + does k-fold or generalized cross-validation to tune constraint options for MLS + problems. See ten Berge (1993, ISBN:9789066950832) for an overview of MLS problems, + and see Goldfarb and Idnani (1983) for a discussion of + the underlying quadratic programming algorithm. + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMLS + url_git: '' +cmm: + version: '1.0' + title: Categorical Marginal Models + maintainer: L. A. van der Ark + description: |- + Quite extensive package for maximum likelihood estimation and + weighted least squares estimation of categorical marginal models (CMMs; + e.g., Bergsma and Rudas, 2002, . + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmm + url_git: '' +cmmr: + version: 1.0.3 + title: CEU Mass Mediator RESTful API + maintainer: Yaoxiang Li + description: |- + CEU (CEU San Pablo University) Mass Mediator is an on-line tool for aiding researchers in + performing metabolite annotation. 'cmmr' (CEU Mass Mediator RESTful API) allows + for programmatic access in R: batch search, batch advanced search, MS/MS (tandem mass spectrometry) search, etc. + For more information about the API Endpoint please go to . + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmmr + url_git: https://github.com/YaoxiangLi/cmmr +CMMs: + version: 1.0.0 + title: Compositional Mediation Model + maintainer: Ziqiang Lin + description: A compositional mediation model for continuous outcome and binary outcomes + to deal with mediators that are compositional data. Lin, Ziqiang et al. (2022) + . + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMMs + url_git: '' +cmna: + version: 1.0.5 + title: Computational Methods for Numerical Analysis + maintainer: James Howard + description: |- + Provides the source and examples for James P. Howard, II, + "Computational Methods for Numerical Analysis with R," + , a book on numerical + methods in R. + date_publication: '2021-07-14' + bug_reports: https://github.com/k3jph/cmna-pkg/issues + url: https://jameshoward.us/cmna/ + url_cran: https://CRAN.R-project.org/package=cmna + url_git: '' +cmocean: + version: 0.3-2 + title: Beautiful Colour Maps for Oceanography + maintainer: Ivan Krylov + description: |- + Perceptually uniform palettes for commonly used + variables in oceanography as functions taking an integer + and producing character vectors of colours. + See Thyng, K.M., Greene, C.A., Hetland, R.D., Zimmerle, H.M. + and S.F. DiMarco (2016) for + the guidelines adhered to when creating the palettes. + date_publication: '2024-08-30' + bug_reports: https://github.com/aitap/cmocean/issues + url: https://matplotlib.org/cmocean/ + url_cran: https://CRAN.R-project.org/package=cmocean + url_git: '' +CMplot: + version: 4.5.1 + title: Circle Manhattan Plot + maintainer: LiLin-Yin + description: 'Manhattan plot, a type of scatter plot, was widely used to display + the association results. However, it is usually time-consuming and laborious for + a non-specialist user to write scripts and adjust parameters of an elaborate plot. + Moreover, the ever-growing traits measured have necessitated the integration of + results from different Genome-wide association study researches. Circle Manhattan + Plot is the first open R package that can lay out. Genome-wide association study + P-value results in both traditional rectangular patterns, QQ-plot and novel circular + ones. United in only one bull''s eye style plot, association results from multiple + traits can be compared interactively, thereby to reveal both similarities and + differences between signals. Additional functions include: highlight signals, + a group of SNPs, chromosome visualization and candidate genes around SNPs.' + date_publication: '2024-01-19' + bug_reports: https://github.com/YinLiLin/CMplot/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=CMplot + url_git: https://github.com/YinLiLin/CMplot +cmprsk: + version: 2.2-12 + title: Subdistribution Analysis of Competing Risks + maintainer: Bob Gray + description: |- + Estimation, testing and regression modeling of + subdistribution functions in competing risks, as described in Gray + (1988), A class of K-sample tests for comparing the cumulative + incidence of a competing risk, Ann. Stat. 16:1141-1154 + , and Fine JP and + Gray RJ (1999), A proportional hazards model for the subdistribution + of a competing risk, JASA, 94:496-509, . + date_publication: '2024-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmprsk + url_git: '' +cmprskcoxmsm: + version: 0.2.1 + title: Use IPW to Estimate Treatment Effect under Competing Risks + maintainer: Yiran Zhang + description: 'Uses inverse probability weighting methods to estimate treatment effect + under marginal structure model for the cause-specific hazard of competing risk + events. Estimates also the cumulative incidence function (i.e. risk) of the potential + outcomes, and provides inference on risk difference and risk ratio. Reference: + Kalbfleisch & Prentice (2002); Hernan et al (2001).' + date_publication: '2021-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmprskcoxmsm + url_git: '' +cmprskQR: + version: 0.9.2 + title: Analysis of Competing Risks Using Quantile Regressions + maintainer: Stephan Dlugosz + description: |- + Estimation, testing and regression modeling of + subdistribution functions in competing risks using quantile regressions, + as described in Peng and Fine (2009) . + date_publication: '2019-09-15' + bug_reports: https://bitbucket.org/sdlugosz/cmprskqr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cmprskQR + url_git: https://bitbucket.org/sdlugosz/cmprskqr +cmpsR: + version: 0.1.2 + title: R Implementation of Congruent Matching Profile Segments Method + maintainer: Wangqian Ju + description: |- + This is an open-source implementation of the Congruent Matching Profile + Segments (CMPS) method (Chen et al. 2019). + In general, it can be used for objective comparison of striated tool marks, and in our + examples, we specifically use it for bullet signatures comparisons. The CMPS score is + expected to be large if two signatures are similar. So it can also be considered as a + feature that measures the similarity of two bullet signatures. + date_publication: '2022-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmpsR + url_git: '' +cmR: + version: '1.1' + title: Analysis of Cardiac Magnetic Resonance Images + maintainer: Volker Schmid + description: Computes maximum response from Cardiac Magnetic Resonance Images using + spatial and voxel wise spline based Bayesian model. This is an implementation + of the methods described in Schmid (2011) "Voxel-Based + Adaptive Spatio-Temporal Modelling of Perfusion Cardiovascular MRI". IEEE TMI + 30(7) p. 1305 - 1313. + date_publication: '2023-07-19' + bug_reports: https://github.com/bioimaginggroup/cmR/issues + url: https://bioimaginggroup.github.io/cmr/ + url_cran: https://CRAN.R-project.org/package=cmR + url_git: '' +cmrutils: + version: 1.3.1 + title: Misc Functions of the Center for Mathematical Research + maintainer: Andrey Paramonov + description: |- + A collection of useful helper routines developed by + students of the Center for Mathematical Research, Stankin, + Moscow. + date_publication: '2018-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmrutils + url_git: https://github.com/aparamon/cmrutils +cms: + version: 0.1.0 + title: Calculate Medicare Reimbursement + maintainer: Vigneshwar Subramanian + description: |- + Uses the 'CMS' application programming interface + to provide users databases containing yearly + Medicare reimbursement rates in the United States. Data can be acquired + for the entire United States or only for specific localities. Currently, + support is only provided for the Medicare Physician Fee Schedule, + but support will be expanded for other 'CMS' databases in future versions. + date_publication: '2020-09-10' + bug_reports: https://github.com/subramv/cms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cms + url_git: https://github.com/subramv/cms +cmsaf: + version: 3.5.2 + title: A Toolbox for CM SAF NetCDF Data + maintainer: Steffen Kothe + description: |- + The Satellite Application Facility on Climate Monitoring (CM SAF) + is a ground segment of the European Organization for the Exploitation of + Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application + Facilities. The CM SAF contributes to the sustainable monitoring of the climate + system by providing essential climate variables related to the energy and water + cycle of the atmosphere (). It is a joint cooperation of eight + National Meteorological and Hydrological Services. + The 'cmsaf' R-package includes a 'shiny' based interface for an easy application of + the 'cmsafops' and 'cmsafvis' packages - the CM SAF R Toolbox. The Toolbox offers an + easy way to prepare, manipulate, analyse and visualize CM SAF NetCDF formatted data. + Other CF conform NetCDF data with time, longitude and latitude dimension should be + applicable, but there is no guarantee for an error-free application. + CM SAF climate data records are provided for free via (). + Detailed information and test data are provided on the CM SAF webpage + (). + date_publication: '2024-09-27' + bug_reports: https://github.com/cmsaf/cmsaf-r-tools/issues + url: https://www.cmsaf.eu + url_cran: https://CRAN.R-project.org/package=cmsaf + url_git: '' +cmsafops: + version: 1.4.0 + title: Tools for CM SAF NetCDF Data + maintainer: Steffen Kothe + description: |- + The Satellite Application Facility on Climate Monitoring (CM SAF) + is a ground segment of the European Organization for the Exploitation of + Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application + Facilities. The CM SAF contributes to the sustainable monitoring of the climate + system by providing essential climate variables related to the energy and water + cycle of the atmosphere (). It is a joint cooperation of eight + National Meteorological and Hydrological Services. + The 'cmsafops' R-package provides a collection of R-operators for the analysis and + manipulation of CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, + longitude and latitude dimension should be applicable, but there is no guarantee for + an error-free application. + CM SAF climate data records are provided for free via (). + Detailed information and test data are provided on the CM SAF webpage + (). + date_publication: '2024-04-26' + bug_reports: https://github.com/cmsaf/cmsaf-r-tools/issues + url: https://www.cmsaf.eu + url_cran: https://CRAN.R-project.org/package=cmsafops + url_git: '' +cmsafvis: + version: 1.2.9 + title: Tools to Visualize CM SAF NetCDF Data + maintainer: Steffen Kothe + description: |- + The Satellite Application Facility on Climate Monitoring (CM SAF) + is a ground segment of the European Organization for the Exploitation of + Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application + Facilities. The CM SAF contributes to the sustainable monitoring of the climate + system by providing essential climate variables related to the energy and water + cycle of the atmosphere (). It is a joint cooperation of eight + National Meteorological and Hydrological Services. + The 'cmsafvis' R-package provides a collection of R-operators for the analysis and + visualization of CM SAF NetCDF data. + CM SAF climate data records are provided for free via (). + Detailed information and test data are provided on the CM SAF webpage + (). + date_publication: '2024-09-30' + bug_reports: https://github.com/cmsaf/cmsaf-r-tools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cmsafvis + url_git: '' +CMShiny: + version: 0.1.0 + title: Interactive Document for Working with Confusion Matrix + maintainer: Kartikeya Bolar + description: An interactive document on the topic of confusion matrix analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CMShiny + url_git: '' +cmstatr: + version: 0.10.0 + title: Statistical Methods for Composite Material Data + maintainer: Stefan Kloppenborg + description: |- + An implementation of the statistical methods commonly + used for advanced composite materials in aerospace applications. + This package focuses on calculating basis values (lower tolerance + bounds) for material strength properties, as well as performing the + associated diagnostic tests. This package provides functions for + calculating basis values assuming several different distributions, + as well as providing functions for non-parametric methods of computing + basis values. Functions are also provided for testing the hypothesis + that there is no difference between strength and modulus data from an + alternate sample and that from a "qualification" or "baseline" sample. + For a discussion of these statistical methods and their use, see the + Composite Materials Handbook, Volume 1 (2012, ISBN: 978-0-7680-7811-4). + Additional details about this package are available in the paper by + Kloppenborg (2020, ). + date_publication: '2024-11-19' + bug_reports: https://github.com/cmstatr/cmstatr/issues + url: https://www.cmstatr.net/ + url_cran: https://CRAN.R-project.org/package=cmstatr + url_git: https://github.com/cmstatr/cmstatr +cmstatrExt: + version: 0.4.0 + title: More Statistical Methods for Composite Material Data + maintainer: Stefan Kloppenborg + description: |- + A companion package to + 'cmstatr' . 'cmstatr' contains + statistical methods that are published in the Composite Materials Handbook, + Volume 1 (2012, ISBN: 978-0-7680-7811-4), while 'cmstatrExt' contains + statistical methods that are not included in that handbook. + date_publication: '2024-05-07' + bug_reports: https://github.com/cmstatr/cmstatrExt/issues + url: https://cmstatrExt.cmstatr.net + url_cran: https://CRAN.R-project.org/package=cmstatrExt + url_git: https://github.com/cmstatr/cmstatrExt +cmtest: + version: 0.1-2 + title: Conditional Moments Test + maintainer: Yves Croissant + description: Conditional moments test, as proposed by Newey (1985) and Tauchen (1985) , useful to detect specification + violations for models estimated by maximum likelihood. Methods for probit and + tobit models are provided. + date_publication: '2022-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cmtest + url_git: '' +cmvnorm: + version: 1.0-7 + title: The Complex Multivariate Gaussian Distribution + maintainer: Robin K. S. Hankin + description: Various utilities for the complex multivariate Gaussian distribution + and complex Gaussian processes. + date_publication: '2022-01-31' + bug_reports: https://github.com/RobinHankin/cmvnorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cmvnorm + url_git: https://github.com/RobinHankin/cmvnorm +cna: + version: 3.6.2 + title: Causal Modeling with Coincidence Analysis + maintainer: Mathias Ambuehl + description: Provides comprehensive functionalities for causal modeling with Coincidence + Analysis (CNA), which is a configurational comparative method of causal data analysis + that was first introduced in Baumgartner (2009) , + and generalized in Baumgartner & Ambuehl (2018) . CNA + is designed to recover INUS-causation from data, which is particularly relevant + for analyzing processes featuring conjunctural causation (component causation) + and equifinality (alternative causation). CNA is currently the only method for + INUS-discovery that allows for multiple effects (outcomes/endogenous factors), + meaning it can analyze common-cause and causal chain structures. + date_publication: '2024-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cna + url_git: '' +CNAIM: + version: 2.1.4 + title: Common Network Asset Indices Methodology (CNAIM) + maintainer: Mohsin Vindhani + description: |- + Implementation of the CNAIM standard in R. Contains a series of + algorithms which determine the probability of failure, consequences of + failure and monetary risk associated with electricity distribution + companies' assets such as transformers and cables. Results are visualized + in an easy-to-understand risk matrix. + date_publication: '2022-08-31' + bug_reports: https://github.com/Utiligize/CNAIM/issues + url: https://www.cnaim.io/ + url_cran: https://CRAN.R-project.org/package=CNAIM + url_git: '' +cnaOpt: + version: 0.5.2 + title: |- + Optimizing Consistency and Coverage in Configurational Causal + Modeling + maintainer: Mathias Ambuehl + description: This is an add-on to the 'cna' package + comprising various functions for optimizing consistency and coverage scores of + models of configurational comparative methods as Coincidence Analysis (CNA) and + Qualitative Comparative Analysis (QCA). The function conCovOpt() calculates con-cov + optima, selectMax() selects con-cov maxima among the con-cov optima, DNFbuild() + can be used to build models actually reaching those optima, and findOutcomes() + identifies those factor values in analyzed data that can be modeled as outcomes. + For a theoretical introduction to these functions see Baumgartner and Ambuehl + (2021) . + date_publication: '2022-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cnaOpt + url_git: '' +cnbdistr: + version: 1.0.1 + title: Conditional Negative Binomial Distribution + maintainer: Xiaotian Zhu + description: Provided R functions for working with the Conditional Negative Binomial + distribution. + date_publication: '2017-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cnbdistr + url_git: '' +cncaGUI: + version: '1.1' + title: Canonical Non-Symmetrical Correspondence Analysis in R + maintainer: Ana Belen Nieto Librero + description: |- + A GUI with which users can construct and interact + with Canonical Correspondence Analysis and Canonical Non-Symmetrical Correspondence Analysis and provides inferential results by using Bootstrap Methods. + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cncaGUI + url_git: '' +cnd: + version: 0.1.0 + title: Create and Register Conditions + maintainer: Jordan Mark Barbone + description: |- + An interface for creating new condition generators objects. + Generators are special functions that can be saved in registries and linked + to other functions. Utilities for documenting your generators, and new + conditions is provided for package development. + date_publication: '2025-02-26' + bug_reports: https://github.com/jmbarbone/cnd/issues + url: https://jmbarbone.github.io/cnd/ + url_cran: https://CRAN.R-project.org/package=cnd + url_git: https://github.com/jmbarbone/cnd +CNID: + version: 2.0.2 + title: Get Basic Information from Chinese ID Number + maintainer: Xinyuan Chu + description: |- + The Chinese ID number contains a lot of information, + this package helps you get the region, date of birth, age, + age based on year, gender, zodiac, constellation information from + the Chinese ID number. + date_publication: '2025-02-28' + bug_reports: https://gitlab.com/chuxinyuan/cnid/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CNID + url_git: https://gitlab.com/chuxinyuan/cnid +CNLTreg: + version: 0.1-2 + title: Complex-Valued Wavelet Lifting for Signal Denoising + maintainer: Matt Nunes + description: Implementations of recent complex-valued wavelet shrinkage procedures + for smoothing irregularly sampled signals, see Hamilton et al (2018) . + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CNLTreg + url_git: '' +CNLTtsa: + version: 0.1-2 + title: |- + Complex-Valued Wavelet Lifting for Univariate and Bivariate Time + Series Analysis + maintainer: Matt Nunes + description: Implementations of recent complex-valued wavelet spectral procedures + for analysis of irregularly sampled signals, see Hamilton et al (2018) . + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CNLTtsa + url_git: '' +cnmap: + version: 0.1.0 + title: China Map Data from AutoNavi Map + maintainer: Panfeng Zhang + description: According to the code or the name of the administrative division at + the county level and above provided by the Ministry of Civil Affairs of the People's + Republic of China in 2022 (), + get the map file online from the website of AutoNavi Map (). + date_publication: '2024-04-02' + bug_reports: https://github.com/PanfengZhang/cnmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cnmap + url_git: https://github.com/PanfengZhang/cnmap +cNORM: + version: 3.4.0 + title: Continuous Norming + maintainer: Wolfgang Lenhard + description: |- + A comprehensive toolkit for generating continuous test norms in + psychometrics and biometrics, and analyzing model fit. The package offers both + distribution-free modeling using Taylor polynomials and parametric modeling + using the beta-binomial distribution. Originally developed for achievement + tests, it is applicable to a wide range of mental, physical, or other test + scores dependent on continuous or discrete explanatory variables. The package + provides several advantages: It minimizes deviations from representativeness + in subsamples, interpolates between discrete levels of explanatory variables, + and significantly reduces the required sample size compared to conventional + norming per age group. cNORM enables graphical and analytical evaluation of + model fit, accommodates a wide range of scales including those with negative + and descending values, and even supports conventional norming. It generates + norm tables including confidence intervals. It also includes methods for + addressing representativeness issues through Iterative Proportional Fitting. + date_publication: '2024-11-04' + bug_reports: https://github.com/WLenhard/cNORM/issues + url: https://www.psychometrica.de/cNorm_en.html + url_cran: https://CRAN.R-project.org/package=cNORM + url_git: https://github.com/WLenhard/cNORM +CNprep: + version: '2.2' + title: Pre-Process DNA Copy Number (CN) Data for Detection of CN Events + maintainer: Guoli Sun + description: |- + DNA copy number data evaluation using both their initial form + (copy number as a noisy function of genomic position) and their + approximation by a piecewise-constant function (segmentation), + for the purpose of identifying genomic regions where the copy number + differs from the norm. + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CNprep + url_git: '' +CNPS: + version: 1.0.0 + title: Nonparametric Statistics + maintainer: JiaSheng Zhang + description: |- + We unify various nonparametric hypothesis testing problems in a framework of permutation testing, enabling hypothesis testing on multi-sample, multidimensional data and contingency tables. Most of the functions available in the R environment to implement permutation tests are single functions constructed for specific test problems; to facilitate the use of the package, the package encapsulates similar tests in a categorized manner, greatly improving ease of use. + We will all provide functions for self-selected permutation scoring methods and self-selected p-value calculation methods (asymptotic, exact, and sampling). For two-sample tests, we will provide mean tests and estimate drift sizes; we will provide tests on variance; we will provide paired-sample tests; we will provide correlation coefficient tests under three measures. For multi-sample problems, we will provide both ordinary and ordered alternative test problems. For multidimensional data, we will implement multivariate means (including ordered alternatives) and multivariate pairwise tests based on four statistics; the components with significant differences are also calculated. For contingency tables, we will perform permutation chi-square test or ordered alternative. + date_publication: '2021-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CNPS + url_git: '' +cnum: + version: 0.1.5 + title: Chinese Numerals Processing + maintainer: Elgar Teo + description: |- + Chinese numerals processing in R, such as conversion between + Chinese numerals and Arabic numerals as well as detection and extraction of + Chinese numerals in character objects and string. This package supports + the casual scale naming system and the respective SI prefix systems used + in mainland China and Taiwan: + "The State Council's Order on the Unified Implementation of Legal Measurement Units in Our Country" + The State Council of the People's Republic of China (1984) + "Names, Definitions and Symbols of the Legal Units of Measurement and the Decimal Multiples and Submultiples" + Ministry of Economic Affairs (2019) . + date_publication: '2025-01-11' + bug_reports: https://github.com/elgarteo/cnum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cnum + url_git: https://github.com/elgarteo/cnum/ +CNVRG: + version: 1.0.0 + title: Dirichlet Multinomial Modeling of Relative Abundance Data + maintainer: Joshua Harrison + description: Implements Dirichlet multinomial modeling of relative abundance data + using functionality provided by the 'Stan' software. The purpose of this package + is to provide a user friendly way to interface with 'Stan' that is suitable for + those new to modeling. For more regarding the modeling mathematics and computational + techniques we use see our publication in Molecular Ecology Resources titled 'Dirichlet + multinomial modeling outperforms alternatives for analysis of ecological count + data' (Harrison et al. 2020 ). + date_publication: '2021-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CNVRG + url_git: '' +CNVScope: + version: 3.7.2 + title: |- + A Versatile Toolkit for Copy Number Variation Relationship Data + Analysis and Visualization + maintainer: James Dalgleish + description: Provides the ability to create interaction maps, discover CNV map domains + (edges), gene annotate interactions, and create interactive visualizations of + these CNV interaction maps. + date_publication: '2022-03-30' + bug_reports: https://github.com/jamesdalg/CNVScope/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=CNVScope + url_git: https://github.com/jamesdalg/CNVScope/ +coala: + version: 0.7.2 + title: A Framework for Coalescent Simulation + maintainer: Dirk Metzler + description: |- + Coalescent simulators can rapidly simulate biological sequences + evolving according to a given model of evolution. + You can use this package to specify such models, to conduct the simulations + and to calculate additional statistics from the results (Staab, Metzler, + 2016 ). + It relies on existing simulators for doing the simulation, and currently + supports the programs 'ms', 'msms' and 'scrm'. It also supports finite-sites + mutation models by combining the simulators with the program 'seq-gen'. + Coala provides functions for calculating certain summary statistics, which + can also be applied to actual biological data. + One possibility to import data is through the 'PopGenome' package + (). + date_publication: '2024-03-04' + bug_reports: https://github.com/statgenlmu/coala/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coala + url_git: https://github.com/statgenlmu/coala +coalescentMCMC: + version: 0.4-4 + title: MCMC Algorithms for the Coalescent + maintainer: Emmanuel Paradis + description: Flexible framework for coalescent analyses in R. It includes a main + function running the MCMC algorithm, auxiliary functions for tree rearrangement, + and some functions to compute population genetic parameters. Extended description + can be found in Paradis (2020) . For details on the + MCMC algorithm, see Kuhner et al. (1995) and + Drummond et al. (2002) . + date_publication: '2022-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coalescentMCMC + url_git: '' +COAP: + version: '1.2' + title: |- + High-Dimensional Covariate-Augmented Overdispersed Poisson + Factor Model + maintainer: Wei Liu + description: |- + A covariate-augmented overdispersed Poisson factor model is proposed to jointly perform a high-dimensional Poisson factor analysis and estimate a large coefficient matrix for overdispersed count data. + More details can be referred to Liu et al. (2024) . + date_publication: '2024-05-02' + bug_reports: https://github.com/feiyoung/COAP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=COAP + url_git: https://github.com/feiyoung/COAP +coarseDataTools: + version: 0.6-6 + title: Analysis of Coarsely Observed Data + maintainer: Nicholas G. Reich + description: |- + Functions to analyze coarse data. + Specifically, it contains functions to (1) fit parametric accelerated + failure time models to interval-censored survival time data, and (2) + estimate the case-fatality ratio in scenarios with under-reporting. + This package's development was motivated by applications to infectious + disease: in particular, problems with estimating the incubation period and + the case fatality ratio of a given disease. Sample data files are included + in the package. See Reich et al. (2009) , + Reich et al. (2012) , and + Lessler et al. (2009) . + date_publication: '2021-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coarseDataTools + url_git: '' +CoastlineFD: + version: 1.1.2 + title: Calculation of the Fractal Dimension of a Coastline + maintainer: Zhao Shiqi + description: Calculating the fractal dimension of a coastline using the boxes and + dividers methods. + date_publication: '2024-01-14' + bug_reports: https://github.com/redworld123/CoastlineFD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CoastlineFD + url_git: https://github.com/redworld123/CoastlineFD +coat: + version: 0.2.0 + title: Conditional Method Agreement Trees (COAT) + maintainer: Alexander Hapfelmeier + description: |- + Agreement of continuously scaled measurements made by two techniques, devices or methods is usually + evaluated by the well-established Bland-Altman analysis or plot. Conditional method agreement trees (COAT), + proposed by Karapetyan, Zeileis, Henriksen, and Hapfelmeier (2023) , + embed the Bland-Altman analysis in the framework of recursive partitioning to explore heterogeneous method + agreement in dependence of covariates. COAT can also be used to perform a Bland-Altman test for differences + in method agreement. + date_publication: '2023-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coat + url_git: '' +cobalt: + version: 4.5.5 + title: Covariate Balance Tables and Plots + maintainer: Noah Greifer + description: |- + Generate balance tables and plots for covariates of groups preprocessed through + matching, weighting or subclassification, for example, using propensity scores. Includes + integration with 'MatchIt', 'WeightIt', 'MatchThem', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', + 'cem', 'sbw', and 'designmatch' for assessing balance on the output of their preprocessing + functions. Users can also specify data for balance assessment not generated through + the above packages. Also included are methods for assessing balance in clustered or + multiply imputed data sets or data sets with multi-category, continuous, or longitudinal treatments. + date_publication: '2024-04-02' + bug_reports: https://github.com/ngreifer/cobalt/issues + url: https://ngreifer.github.io/cobalt/ + url_cran: https://CRAN.R-project.org/package=cobalt + url_git: https://github.com/ngreifer/cobalt +cobiclust: + version: 0.1.2 + title: |- + Biclustering via Latent Block Model Adapted to Overdispersed + Count Data + maintainer: Julie Aubert + description: |- + Implementation of a probabilistic method for biclustering + adapted to overdispersed count data. It is a Gamma-Poisson Latent + Block Model. It also implements two selection criteria in order to + select the number of biclusters. + date_publication: '2024-02-16' + bug_reports: https://github.com/julieaubert/cobiclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cobiclust + url_git: https://github.com/julieaubert/cobiclust +cobs: + version: 1.3-9 + title: Constrained B-Splines (Sparse Matrix Based) + maintainer: Martin Maechler + description: |- + Qualitatively Constrained (Regression) Smoothing Splines via + Linear Programming and Sparse Matrices. + date_publication: '2024-12-19' + bug_reports: https://r-forge.r-project.org/R/?group_id=846 + url: https://www2.nau.edu/PinNg/cobs.html + url_cran: https://CRAN.R-project.org/package=cobs + url_git: https://curves-etc.r-forge.r-project.org/ +coca: + version: 1.1.0 + title: Cluster-of-Clusters Analysis + maintainer: Alessandra Cabassi + description: Contains the R functions needed to perform Cluster-Of-Clusters Analysis + (COCA) and Consensus Clustering (CC). For further details please see Cabassi + and Kirk (2020) . + date_publication: '2020-07-06' + bug_reports: http://github.com/acabassi/coca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coca + url_git: http://github.com/acabassi/coca +cocktailApp: + version: 0.2.3 + title: '''shiny'' App to Discover Cocktails' + maintainer: Steven E. Pav + description: |- + A 'shiny' app to discover cocktails. The + app allows one to search for cocktails by ingredient, + filter on rating, and number of ingredients. The + package also contains data with the ingredients of + nearly 26 thousand cocktails scraped from the web. + date_publication: '2023-07-19' + bug_reports: https://github.com/shabbychef/cocktailApp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cocktailApp + url_git: https://github.com/shabbychef/cocktailApp +CoClust: + version: 0.3-2 + title: Copula Based Cluster Analysis + maintainer: Francesca Marta Lilja Di Lascio + description: A copula based clustering algorithm that finds clusters according to + the complex multivariate dependence structure of the data generating process. + The updated version of the algorithm is described in Di Lascio, F.M.L. and Giannerini, + S. (2016). "Clustering dependent observations with copula functions". Statistical + Papers, p.1-17. . + date_publication: '2017-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoClust + url_git: '' +coconots: + version: 1.1.3 + title: Convolution-Closed Models for Count Time Series + maintainer: Manuel Huth + description: Useful tools for fitting, validating, and forecasting of practical + convolution-closed time series models for low counts are provided. Marginal distributions + of the data can be modeled via Poisson and Generalized Poisson innovations. Regression + effects can be modelled via time varying innovation rates. The models are described + in Jung and Tremayne (2011) and the model + assessment tools are presented in Czado et al. (2009) , + Gneiting and Raftery (2007) and, Tsay (1992) + . + date_publication: '2023-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coconots + url_git: '' +cocons: + version: 0.1.4 + title: |- + Covariate-Based Covariance Functions for Nonstationary Spatial + Modeling + maintainer: Federico Blasi + description: |- + Estimation, prediction, and simulation of nonstationary Gaussian process with modular covariate-based covariance functions. + Sources of nonstationarity, such as spatial mean, variance, geometric anisotropy, smoothness, and nugget, can be considered based on spatial characteristics. + An induced compact-supported nonstationary covariance function is provided, enabling fast and memory-efficient computations when handling densely sampled domains. + date_publication: '2024-12-12' + bug_reports: https://github.com/blasif/cocons/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cocons + url_git: '' +cocoon: + version: 0.2.0 + title: Extract, Format, and Print Statistical Output + maintainer: Jeffrey R. Stevens + description: |- + Provides functions that format statistical output in a way that + can be inserted into R Markdown documents. This is analogous to the + apa_print() functions in the 'papaja' package but prints Markdown + or LaTeX syntax. + date_publication: '2025-01-29' + bug_reports: https://github.com/JeffreyRStevens/cocoon/issues + url: https://jeffreyrstevens.github.io/cocoon/ + url_cran: https://CRAN.R-project.org/package=cocoon + url_git: https://github.com/JeffreyRStevens/cocoon +cocor: + version: 1.1-4 + title: Comparing Correlations + maintainer: Birk Diedenhofen + description: Statistical tests for the comparison between two correlations based + on either independent or dependent groups. Dependent correlations can either be + overlapping or nonoverlapping. A web interface is available on the website . + A plugin for the R GUI and IDE RKWard is included. Please install RKWard from + to use this feature. The respective R package 'rkward' + cannot be installed directly from a repository, as it is a part of RKWard. + date_publication: '2022-06-28' + bug_reports: '' + url: http://comparingcorrelations.org + url_cran: https://CRAN.R-project.org/package=cocor + url_git: '' +cocorresp: + version: 0.4-5 + title: Co-Correspondence Analysis Methods + maintainer: Gavin L. Simpson + description: Fits predictive and symmetric co-correspondence analysis (CoCA) models + to relate one data matrix to another data matrix. More specifically, CoCA maximises + the weighted covariance between the weighted averaged species scores of one community + and the weighted averaged species scores of another community. CoCA attempts to + find patterns that are common to both communities. + date_publication: '2024-10-06' + bug_reports: https://github.com/gavinsimpson/cocorresp/issues + url: https://gavinsimpson.github.io/cocorresp/ + url_cran: https://CRAN.R-project.org/package=cocorresp + url_git: '' +cocosoR: + version: 0.1.0 + title: CoCoSo - Combined Compromise Solution Method for MCDA + maintainer: Sergio Floquet + description: Provides a set of functions to implement the Combined Compromise Solution + (CoCoSo) Method created by Yazdani, Zarate, Zavadskas and Turskis (2019) . + This method is based on an integrated simple additive weighting and compromise + exponentially weighted product model. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cocosoR + url_git: '' +cocotest: + version: 1.0.3 + title: Dependence Condition Test Using Ranked Correlation Coefficients + maintainer: Jiangtao Gou + description: |- + A common misconception is that the Hochberg procedure comes up with adequate overall type I error control when test statistics are positively correlated. However, unless the test statistics follow some standard distributions, the Hochberg procedure requires a more stringent positive dependence assumption, beyond mere positive correlation, to ensure valid overall type I error control. To fill this gap, we formulate statistical tests grounded in rank correlation coefficients to validate fulfillment of the positive dependence through stochastic ordering (PDS) condition. + See Gou, J., Wu, K. and Chen, O. Y. (2024). Rank correlation coefficient based tests on positive dependence through stochastic ordering with application in cancer studies, Technical Report. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cocotest + url_git: '' +cocron: + version: 1.0-1 + title: Statistical Comparisons of Two or more Alpha Coefficients + maintainer: Birk Diedenhofen + description: |- + Statistical tests for the comparison between two or more alpha + coefficients based on either dependent or independent groups of individuals. + A web interface is available at http://comparingcronbachalphas.org. A plugin + for the R GUI and IDE RKWard is included. Please install RKWard from https:// + rkward.kde.org to use this feature. The respective R package 'rkward' cannot be + installed directly from a repository, as it is a part of RKWard. + date_publication: '2016-03-12' + bug_reports: '' + url: http://comparingcronbachalphas.org + url_cran: https://CRAN.R-project.org/package=cocron + url_git: '' +coda: + version: 0.19-4.1 + title: Output Analysis and Diagnostics for MCMC + maintainer: Martyn Plummer + description: |- + Provides functions for summarizing and plotting the + output from Markov Chain Monte Carlo (MCMC) simulations, as + well as diagnostic tests of convergence to the equilibrium + distribution of the Markov chain. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coda + url_git: '' +coda.base: + version: 0.5.5 + title: A Basic Set of Functions for Compositional Data Analysis + maintainer: Marc Comas-Cufí + description: |- + A minimum set of functions to perform compositional data analysis + using the log-ratio approach introduced by John Aitchison (1982). Main functions + have been implemented in c++ for better performance. + date_publication: '2023-11-25' + bug_reports: '' + url: https://mcomas.net/coda.base/ + url_cran: https://CRAN.R-project.org/package=coda.base + url_git: https://github.com/mcomas/coda.base +coda4microbiome: + version: 0.2.4 + title: Compositional Data Analysis for Microbiome Studies + maintainer: Toni Susin + description: Functions for microbiome data analysis that take into account its compositional + nature. Performs variable selection through penalized regression for both, cross-sectional + and longitudinal studies, and for binary and continuous outcomes. + date_publication: '2024-07-17' + bug_reports: https://github.com/malucalle/coda4microbiome/issues + url: https://malucalle.github.io/coda4microbiome/ + url_cran: https://CRAN.R-project.org/package=coda4microbiome + url_git: '' +codacore: + version: 0.0.4 + title: Learning Sparse Log-Ratios for Compositional Data + maintainer: Elliott Gordon-Rodriguez + description: |- + In the context of high-throughput genetic data, + CoDaCoRe identifies a set of sparse biomarkers that are + predictive of a response variable of interest (Gordon-Rodriguez + et al., 2021) . More + generally, CoDaCoRe can be applied to any regression problem + where the independent variable is Compositional (CoDa), to + derive a set of scale-invariant log-ratios (ILR or SLR) that + are maximally associated to a dependent variable. + date_publication: '2022-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codacore + url_git: '' +CoDaImpact: + version: 0.1.0 + title: Interpreting CoDa Regression Models + maintainer: Lukas Dargel + description: |2- + + Provides methods for interpreting CoDa (Compositional Data) regression models along the lines of "Pairwise share ratio interpretations of compositional regression models" (Dargel and Thomas-Agnan 2024) . + The new methods include variation scenarios, elasticities, elasticity differences and share ratio elasticities. + These tools are independent of log-ratio transformations and allow an interpretation in the original space of shares. + 'CoDaImpact' is designed to be used with the 'compositions' package and its ecosystem. + date_publication: '2024-03-23' + bug_reports: https://github.com/LukeCe/CoDaImpact/issues + url: https://lukece.github.io/CoDaImpact/ + url_cran: https://CRAN.R-project.org/package=CoDaImpact + url_git: https://github.com/LukeCe/CoDaImpact +codalm: + version: 0.1.2 + title: |- + Transformation-Free Linear Regression for Compositional Outcomes + and Predictors + maintainer: Jacob Fiksel + description: |- + Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2021) + for transformation-free linear regression for compositional outcomes and predictors. + date_publication: '2021-07-26' + bug_reports: https://github.com/jfiksel/codalm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=codalm + url_git: https://github.com/jfiksel/codalm +CoDaLoMic: + version: 0.1.0 + title: Compositional Models to Longitudinal Microbiome Data + maintainer: Irene Creus Martí + description: Implementation of models to analyse compositional microbiome time series + taking into account the interaction between groups of bacteria. The models implemented + are described in Creus-Martí et al (2018, ISBN:978-84-09-07541-6), Creus-Martí + et al (2021) and Creus-Martí et al (2022) . + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoDaLoMic + url_git: '' +codaredistlm: + version: 0.1.0 + title: Compositional Data Linear Models with Composition Redistribution + maintainer: Ty Stanford + description: Provided data containing an outcome variable, compositional variables + and additional covariates (optional); linearly regress the outcome variable on + an isometric log ratio (ilr) transformation of the linearly dependent compositional + variables. The package provides predictions (with confidence intervals) in the + change (delta) in the outcome/response variable based on the multiple linear regression + model and evenly spaced reallocations of the compositional values. The compositional + data analysis approach implemented is outlined in Dumuid et al. (2017a) + and Dumuid et al. (2017b) . + date_publication: '2022-12-22' + bug_reports: https://github.com/tystan/codaredistlm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=codaredistlm + url_git: https://github.com/tystan/codaredistlm +CodataGS: + version: '1.43' + title: Genomic Prediction Using SNP Codata + maintainer: Lars Ronnegard + description: Computes genomic breeding values using external information on the + markers. The package fits a linear mixed model with heteroscedastic random effects, + where the random effect variance is fitted using a linear predictor and a log + link. The method is described in Mouresan, Selle and Ronnegard (2019) . + date_publication: '2019-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CodataGS + url_git: '' +cOde: + version: 1.1.1 + title: Automated C Code Generation for 'deSolve', 'bvpSolve' + maintainer: Daniel Kaschek + description: |- + Generates all necessary C functions allowing the user to work with + the compiled-code interface of ode() and bvptwp(). The implementation supports + "forcings" and "events". Also provides functions to symbolically compute + Jacobians, sensitivity equations and adjoint sensitivities being the basis for + sensitivity analysis. + date_publication: '2022-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cOde + url_git: '' +codebook: + version: 0.9.6 + title: Automatic Codebooks from Metadata Encoded in Dataset Attributes + maintainer: Ruben Arslan + description: |- + Easily automate the following tasks to describe data frames: + Summarise the distributions, and labelled missings of variables graphically + and using descriptive statistics. + For surveys, compute and summarise reliabilities (internal consistencies, + retest, multilevel) for psychological scales. + Combine this information with metadata (such as item labels and labelled + values) that is derived from R attributes. + To do so, the package relies on 'rmarkdown' partials, so you can generate + HTML, PDF, and Word documents. + Codebooks are also available as tables (CSV, Excel, etc.) and in JSON-LD, so + that search engines can find your data and index the metadata. + The metadata are also available at your fingertips via RStudio Addins. + date_publication: '2025-01-08' + bug_reports: https://github.com/rubenarslan/codebook/issues + url: https://rubenarslan.github.io/codebook/ + url_cran: https://CRAN.R-project.org/package=codebook + url_git: https://github.com/rubenarslan/codebook +codebookr: + version: 0.1.8 + title: Create Codebooks from Data Frames + maintainer: Brad Cannell + description: Quickly and easily create codebooks (i.e. data dictionaries) directly + from a data frame. + date_publication: '2024-02-19' + bug_reports: https://github.com/brad-cannell/codebookr/issues + url: https://brad-cannell.github.io/codebookr/ + url_cran: https://CRAN.R-project.org/package=codebookr + url_git: https://github.com/brad-cannell/codebookr +codebreaker: + version: 1.0.1 + title: Retro Logic Game + maintainer: Roland Krasser + description: |- + Logic game in the style of the early 1980s home computers + that can be played in the R console. This game is inspired by + Mastermind, a game that became popular in the 1970s. + Can you break the code? + date_publication: '2023-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codebreaker + url_git: https://github.com/rolkra/codebreaker +codeCollection: + version: 0.1.3 + title: Collection of Codes with Labels + maintainer: Jari Haukka + description: 'Includes several classifications such as International Statistical + Classification of Diseases and Related Health Problems 10th Revision (ICD10), Anatomical + Therapeutic Chemical (ATC) Classification, The International Classification of + Diseases for Oncology (ICD-O-3), and International Classification of Primary + Care (ICPC). Includes function that adds descriptive label to code value. Depending + on classification following languages are available: English, Finnish, Swedish, + and Latin.' + date_publication: '2023-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codeCollection + url_git: '' +codecountR: + version: 0.0.4.7 + title: Counting Codes in a Text and Preparing Data for Analysis + maintainer: Philippe Cohard + description: 'Data analysis often requires coding, especially when data are collected + through interviews, observations, or questionnaires. As a result, code counting + and data preparation are essential steps in the analysis process. Analysts may + need to count the codes in a text (Tokenization, counting of pre-established codes, + computing the co-occurrence matrix by line) and prepare the data (e.g., min-max + normalization, Z-score, robust scaling, Box-Cox transformation, and non-parametric + bootstrap). For the Box-Cox transformation (Box & Cox, 1964, ), + the optimal Lambda is determined using the log-likelihood method. Non-parametric + bootstrap involves randomly sampling data with replacement. Two random number + generators are also integrated: a Lehmer congruential generator for uniform distribution + and a Box-Muller generator for normal distribution. Package for educational purposes.' + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codecountR + url_git: '' +CodeDepends: + version: 0.6.6 + title: |- + Analysis of R Code for Reproducible Research and Code + Comprehension + maintainer: Gabriel Becker + description: |- + Tools for analyzing R expressions + or blocks of code and determining the dependencies between them. + It focuses on R scripts, but can be used on the bodies of functions. + There are many facilities including the ability to summarize or get a high-level + view of code, determining dependencies between variables, code improvement + suggestions. + date_publication: '2024-04-07' + bug_reports: https://github.com/duncantl/CodeDepends/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CodeDepends + url_git: https://github.com/duncantl/CodeDepends +codelist: + version: 0.1.0 + title: Working with Code Lists + maintainer: Jan van der Laan + description: |- + Functions for working with code lists and vectors with codes. These + are an alternative for factor that keep track of both the codes and labels. + Methods allow for transforming between codes and labels. Also supports + hierarchical code lists. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codelist + url_git: '' +CodelistGenerator: + version: 3.4.0 + title: Identify Relevant Clinical Codes and Evaluate Their Use + maintainer: Edward Burn + description: Generate a candidate code list for the Observational Medical Outcomes + Partnership (OMOP) common data model based on string matching. For a given search + strategy, a candidate code list will be returned. + date_publication: '2025-02-19' + bug_reports: '' + url: https://darwin-eu.github.io/CodelistGenerator/ + url_cran: https://CRAN.R-project.org/package=CodelistGenerator + url_git: '' +codemeta: + version: 0.1.1 + title: A Smaller 'codemetar' Package + maintainer: Carl Boettiger + description: |- + The 'Codemeta' Project defines a 'JSON-LD' format + for describing software metadata, as detailed at + . This package provides core utilities + to generate this metadata with a minimum of dependencies. + date_publication: '2021-12-22' + bug_reports: https://github.com/cboettig/codemeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=codemeta + url_git: https://github.com/cboettig/codemeta +codemetar: + version: 0.3.5 + title: Generate 'CodeMeta' Metadata for R Packages + maintainer: Carl Boettiger + description: |- + The 'Codemeta' Project defines a 'JSON-LD' format + for describing software metadata, as detailed at + . This package provides utilities to + generate, parse, and modify 'codemeta.json' files automatically for R + packages, as well as tools and examples for working with + 'codemeta.json' 'JSON-LD' more generally. + date_publication: '2022-09-02' + bug_reports: https://github.com/ropensci/codemetar/issues + url: https://docs.ropensci.org/codemetar/ + url_cran: https://CRAN.R-project.org/package=codemetar + url_git: https://github.com/ropensci/codemetar +codename: + version: 0.5.0 + title: |- + Generation of Code Names for Organizations, People, Projects, + and Whatever Else + maintainer: Steve Miller + description: |- + This creates code names that a user can consider for their organizations, their projects, themselves, people + in their organizations or projects, or whatever else. The user can also supply a numeric seed (and even a character seed) + for maximum reproducibility. Use is simple and the code names produced come in various types too, contingent on what the + user may be desiring as a code name or nickname. + date_publication: '2023-02-06' + bug_reports: https://github.com/svmiller/codename/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=codename + url_git: https://github.com/svmiller/codename +codep: + version: 1.2-4 + title: Multiscale Codependence Analysis + maintainer: Guillaume Guénard + description: Computation of Multiscale Codependence Analysis and spatial eigenvector + maps. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codep + url_git: '' +coder: + version: 0.13.10 + title: |- + Deterministic Categorization of Items Based on External Code + Data + maintainer: Erik Bulow + description: |2- + + Fast categorization of items based on external code data identified by + regular expressions. A typical use case considers patient with medically coded + data, such as codes from the International Classification of Diseases ('ICD') or + the Anatomic Therapeutic Chemical ('ATC') classification system. + Functions of the package relies on a triad of objects: (1) case data with unit + id:s and possible dates of interest; (2) external code data for corresponding + units in (1) and with optional dates of interest and; (3) a classification + scheme ('classcodes' object) with regular expressions to identify and + categorize relevant codes from (2). + It is easy to introduce new classification schemes ('classcodes' objects) or + to use default schemes included in the package. Use cases includes patient + categorization based on 'comorbidity indices' such as 'Charlson', 'Elixhauser', + 'RxRisk V', or the 'comorbidity-polypharmacy' score (CPS), as well as adverse + events after hip and knee replacement surgery. + date_publication: '2023-03-14' + bug_reports: https://github.com/ropensci/coder/issues + url: https://docs.ropensci.org/coder/ + url_cran: https://CRAN.R-project.org/package=coder + url_git: '' +codetools: + version: 0.2-20 + title: Code Analysis Tools for R + maintainer: Luke Tierney + description: Code analysis tools for R. + date_publication: '2024-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codetools + url_git: https://gitlab.com/luke-tierney/codetools +codewhere: + version: 0.1.1 + title: Find the Location of an R Package's Code + maintainer: Nic Crane + description: |- + Find the location of the code for an R package based on the package's name or string representation. + Checks on 'CRAN' based on information in the 'URL' field or 'BioConductor' and 'GitHub' based on constructing + a URL, and verifies all paths via testing for a successful response. This can be useful when automating static + code analysis based on a list of package names, and similar tasks. + date_publication: '2024-06-04' + bug_reports: https://github.com/thisisnic/codewhere/issues + url: https://thisisnic.github.io/codewhere/ + url_cran: https://CRAN.R-project.org/package=codewhere + url_git: https://github.com/thisisnic/codewhere/ +codexcopd: + version: 0.1.0 + title: |- + The CODEX (Comorbidity, Obstruction, Dyspnea, and Previous + Severe Exacerbations) Index: Short and Medium-Term Prognosis in + Patients Hospitalized for Chronic Obstructive Pulmonary Disease + (COPD) Exacerbations + maintainer: Amin Adibi + description: Predicts 3 to 12 months prognosis in Chronic Obstructive Pulmonary + Disease (COPD) patients hospitalized for severe exacerbations, as described in + Almagro et al. (2014) . + date_publication: '2020-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codexcopd + url_git: '' +codez: + version: 1.0.0 + title: |- + Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on + Tensorflow + maintainer: Giancarlo Vercellino + description: Proposes Seq2seq Time-Feature Analysis using an Encoder-Decoder to + project into latent space and a Forward Network to predict the next sequence. + date_publication: '2022-09-23' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/codez + url_cran: https://CRAN.R-project.org/package=codez + url_git: '' +codified: + version: 0.3.0 + title: Produce Standard/Formalized Demographics Tables + maintainer: Will Beasley + description: |- + Augment clinical data with metadata to create + output used in conventional publications and reports. + date_publication: '2022-08-12' + bug_reports: https://github.com/OuhscBbmc/codified/issues + url: https://ouhscbbmc.github.io/codified/ + url_cran: https://CRAN.R-project.org/package=codified + url_git: https://github.com/OuhscBbmc/codified +CoDiNA: + version: 1.1.2 + title: Co-Expression Differential Network Analysis + maintainer: Deisy Morselli Gysi + description: 'Categorize links and nodes from multiple networks in 3 categories: + Common links (alpha) specific links (gamma), and different links (beta). Also + categorizes the links into sub-categories and groups. The package includes a visualization + tool for the networks. More information about the methodology can be found at: + Gysi et. al., 2018 .' + date_publication: '2020-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoDiNA + url_git: '' +codingMatrices: + version: 0.4.0 + title: Alternative Factor Coding Matrices for Linear Model Formulae + maintainer: Bill Venables + description: |- + A collection of coding functions as alternatives to the standard + functions in the stats package, which have names starting with 'contr.'. Their + main advantage is that they provide a consistent method for defining marginal + effects in factorial models. In a simple one-way ANOVA model the + intercept term is always the simple average of the class means. + date_publication: '2023-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=codingMatrices + url_git: '' +codyn: + version: 2.0.5 + title: Community Dynamics Metrics + maintainer: Matthew B. Jones + description: |- + Univariate and multivariate temporal and spatial diversity indices, + rank abundance curves, and community stability measures. The functions + implement measures that are either explicitly temporal and include the + option to calculate them over multiple replicates, or spatial and include + the option to calculate them over multiple time points. Functions fall into + five categories: static diversity indices, temporal diversity indices, + spatial diversity indices, rank abundance curves, and community stability + measures. The diversity indices are temporal and spatial analogs to + traditional diversity indices. Specifically, the package includes functions + to calculate community richness, evenness and diversity at a given point in + space and time. In addition, it contains functions to calculate species + turnover, mean rank shifts, and lags in community similarity between two + time points. Details of the methods are available in + Hallett et al. (2016) and Avolio + et al. (2019) . + date_publication: '2020-12-01' + bug_reports: https://github.com/NCEAS/codyn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=codyn + url_git: https://github.com/NCEAS/codyn/ +coefa: + version: 1.0.3 + title: Meta Analysis of Factor Analysis Based on CO-Occurrence Matrices + maintainer: Xijian Zheng + description: |- + Provide a series of functions to conduct a meta analysis of + factor analysis based on co-occurrence matrices. The tool can be used to + solve the factor structure (i.e. inner structure of a construct, or scale) + debate in several disciplines, such as psychology, psychiatry, management, + education so on. References: Shafer (2005) ; + Shafer (2006) ; Loeber and Schmaling (1985) . + date_publication: '2023-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coefa + url_git: '' +coefficientalpha: + version: 0.7.2 + title: |- + Robust Coefficient Alpha and Omega with Missing and Non-Normal + Data + maintainer: Zhiyong Zhang + description: Cronbach's alpha and McDonald's omega are widely used reliability or + internal consistency measures in social, behavioral and education sciences. Alpha + is reported in nearly every study that involves measuring a construct through + multiple test items. The package 'coefficientalpha' calculates coefficient alpha + and coefficient omega with missing data and non-normal data. Robust standard errors + and confidence intervals are also provided. A test is also available to test the + tau-equivalent and homogeneous assumptions. Since Version 0.5, the bootstrap confidence + intervals were added. + date_publication: '2023-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coefficientalpha + url_git: '' +coefplot: + version: 1.2.8 + title: Plots Coefficients from Fitted Models + maintainer: Jared P. Lander + description: Plots the coefficients from model objects. This very quickly shows + the user the point estimates and confidence intervals for fitted models. + date_publication: '2022-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coefplot + url_git: '' +coenocliner: + version: 0.2-3 + title: Coenocline Simulation + maintainer: Gavin L. Simpson + description: |- + Simulate species occurrence and abundances (counts) along + gradients. + date_publication: '2021-02-14' + bug_reports: https://github.com/gavinsimpson/coenocliner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coenocliner + url_git: https://github.com/gavinsimpson/coenocliner/ +coenoflex: + version: 2.2-0 + title: Gradient-Based Coenospace Vegetation Simulator + maintainer: David W. Roberts + description: |- + Simulates the composition of samples of vegetation + according to gradient-based vegetation theory. Features a + flexible algorithm incorporating competition and complex + multi-gradient interaction. + date_publication: '2016-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coenoflex + url_git: '' +cofad: + version: 0.3.2 + title: Contrast Analyses for Factorial Designs + maintainer: Johannes Titz + description: |- + Contrast analysis for factorial designs provides an + alternative to the traditional ANOVA approach, offering the distinct + advantage of testing targeted hypotheses. The foundation of this + package is primarily rooted in the works of Rosenthal, Rosnow, and + Rubin (2000, ISBN: 978-0521659802) as well as Sedlmeier and Renkewitz + (2018, ISBN: 978-3868943214). + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cofad + url_git: https://github.com/johannes-titz/cofad +cofeatureR: + version: 1.1.1 + title: Generate Cofeature Matrices + maintainer: Fong Chun Chan + description: |- + Generate cofeature (feature by sample) matrices. The package + utilizes ggplot2::geom_tile() to generate the matrix allowing for easy + additions from the base matrix. + date_publication: '2018-06-24' + bug_reports: https://github.com/tinyheero/cofeatureR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cofeatureR + url_git: https://github.com/tinyheero/cofeatureR +coffee: + version: 0.4.3 + title: Chronological Ordering for Fossils and Environmental Events + maintainer: Maarten Blaauw + description: While individual calibrated radiocarbon dates can span several centuries, + combining multiple dates together with any chronological constraints can make + a chronology much more robust and precise. This package uses Bayesian methods + to enforce the chronological ordering of radiocarbon and other dates, for example + for trees with multiple radiocarbon dates spaced at exactly known intervals (e.g., + 10 annual rings). For methods see Christen 2003 . Another + example is sites where the relative chronological position of the dates is taken + into account - the ages of dates further down a site must be older than those + of dates further up (Buck, Kenworthy, Litton and Smith 1991 ; + Nicholls and Jones 2001 ). The paper accompanying + this R package is Blaauw et al. 2024 . + date_publication: '2024-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coffee + url_git: https://github.com/Maarten14C/coffee +cofid: + version: 1.0.0 + title: Copepod Fish Interaction Database + maintainer: Angel Robles + description: |- + A curated list of copepod-fish ecological interaction records. + It contains the taxonomy of the copepod and the fish and the publication + from which the information was obtained. This database contains only marine + and brackish water fish species. It excludes fish species that inhabit only + freshwater. + date_publication: '2024-05-28' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=cofid + url_git: '' +coga: + version: 1.2.2 + title: Convolution of Gamma Distributions + maintainer: Chaoran Hu + description: |- + Evaluation for density and distribution function of convolution of gamma + distributions in R. Two related exact methods and one approximate method are + implemented with efficient algorithm and C++ code. A quick guide for choosing + correct method and usage of this package is given in package vignette. For the + detail of methods used in this package, we refer the user to + Mathai(1982), + Moschopoulos(1984), + Barnabani(2017), + Hu et al.(2020). + date_publication: '2024-01-10' + bug_reports: https://github.com/ChaoranHu/coga/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coga + url_git: https://github.com/ChaoranHu/coga +cogirt: + version: 1.0.0 + title: Cognitive Testing Using Item Response Theory + maintainer: Michael Thomas + description: Psychometrically analyze latent individual differences related to tasks, + interventions, or maturational/aging effects in the context of experimental or + longitudinal cognitive research using methods first described by Thomas et al. + (2020) . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cogirt + url_git: '' +coglasso: + version: 1.0.2 + title: |- + Collaborative Graphical Lasso - Multi-Omics Network + Reconstruction + maintainer: Alessio Albanese + description: |- + Reconstruct networks from multi-omics data sets with the + collaborative graphical lasso (coglasso) algorithm described in Albanese, A., + Kohlen, W., and Behrouzi, P. (2024) . Build multiple networks + using the coglasso() function, select the best one with stars_coglasso(). + date_publication: '2024-04-03' + bug_reports: https://github.com/DrQuestion/coglasso/issues + url: https://drquestion.github.io/coglasso/ + url_cran: https://CRAN.R-project.org/package=coglasso + url_git: https://github.com/DrQuestion/coglasso +cogmapr: + version: 0.9.3 + title: Cognitive Mapping Tools Based on Coding of Textual Sources + maintainer: Frédéric M. Vanwindekens + description: Functions for building cognitive maps based on qualitative data. Inputs + are textual sources (articles, transcription of qualitative interviews of agents,...). + These sources have been coded using relations and are linked to (i) a table describing + the variables (or concepts) used for the coding and (ii) a table describing the + sources (typology of agents, ...). Main outputs are Individual Cognitive Maps + (ICM), Social Cognitive Maps (all sources or group of sources) and a list of quotes + linked to relations. This package is linked to the work done during the PhD of + Frederic M. Vanwindekens (CRA-W / UCL) hold the 13 of May 2014 at University of + Louvain in collaboration with the Walloon Agricultural Research Centre (project + MIMOSA, MOERMAN fund). + date_publication: '2022-01-04' + bug_reports: https://gitlab.com/FrdVnW/cogmapr/-/issues + url: https://frdvnw.gitlab.io/cogmapr/ + url_cran: https://CRAN.R-project.org/package=cogmapr + url_git: '' +cognitoR: + version: 1.0.5 + title: Authentication for 'Shiny' Apps with 'Amazon Cognito' + maintainer: Pablo Pagnone + description: Provides authentication for Shiny applications using 'Amazon Cognito' + ( ). + date_publication: '2024-01-30' + bug_reports: https://github.com/chi2labs/cognitoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cognitoR + url_git: '' +CohensdpLibrary: + version: 0.5.11 + title: Cohen's D_p Computation with Confidence Intervals + maintainer: Denis Cousineau + description: 'Computing Cohen''s d_p in any experimental designs (between-subject, + within-subject, and single-group design). Cousineau (2022) ; + Cohen (1969, ISBN: 0-8058-0283-5).' + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CohensdpLibrary + url_git: '' +cohetsurr: + version: '1.0' + title: Assessing Complex Heterogeneity in Surrogacy + maintainer: Rebecca Knowlton + description: 'Provides functions to assess and test for complex heterogeneity in + the utility of a surrogate marker with respect to multiple baseline covariates, + using both a parametric model and a semiparametric two-step model. More details + will be available in the future in: Knowlton, R., Tian, L., Parast, L. (2024) + ``A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate + Marker."' + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cohetsurr + url_git: '' +CohortAlgebra: + version: 0.3.1 + title: |- + Use of Interval Algebra to Create New Cohort(s) from Existing + Cohorts + maintainer: Gowtham Rao + description: |- + This software tool is designed to generate new cohorts utilizing data from + previously instantiated cohorts. It employs interval algebra operators such as UNION, + INTERSECT, and MINUS to manipulate the data within the instantiated cohorts and + create new cohorts. + date_publication: '2025-02-23' + bug_reports: https://github.com/OHDSI/CohortAlgebra/issues + url: https://ohdsi.github.io/CohortAlgebra/ + url_cran: https://CRAN.R-project.org/package=CohortAlgebra + url_git: '' +cohortBuilder: + version: 0.3.0 + title: Data Source Agnostic Filtering Tools + maintainer: Krystian Igras + description: |- + Common API for filtering data stored in different data models. + Provides multiple filter types and reproducible R code. + Works standalone or with 'shinyCohortBuilder' as the GUI for interactive Shiny apps. + date_publication: '2024-09-25' + bug_reports: '' + url: https://r-world-devs.github.io/cohortBuilder/ + url_cran: https://CRAN.R-project.org/package=cohortBuilder + url_git: https://github.com/r-world-devs/cohortBuilder/ +CohortCharacteristics: + version: 0.4.0 + title: |- + Summarise and Visualise Characteristics of Patients in the OMOP + CDM + maintainer: Marti Catala + description: |- + Summarise and visualise the characteristics of patients in data + mapped to the Observational Medical Outcomes Partnership (OMOP) common data + model (CDM). + date_publication: '2024-11-26' + bug_reports: https://github.com/darwin-eu/CohortCharacteristics/issues + url: https://darwin-eu.github.io/CohortCharacteristics/ + url_cran: https://CRAN.R-project.org/package=CohortCharacteristics + url_git: '' +CohortConstructor: + version: 0.3.5 + title: Build and Manipulate Study Cohorts Using a Common Data Model + maintainer: Edward Burn + description: |- + Create and manipulate study cohorts in data mapped to the + Observational Medical Outcomes Partnership Common Data Model. + date_publication: '2025-02-16' + bug_reports: '' + url: https://ohdsi.github.io/CohortConstructor/ + url_cran: https://CRAN.R-project.org/package=CohortConstructor + url_git: https://github.com/OHDSI/CohortConstructor +CohortExplorer: + version: 0.1.0 + title: Explorer of Profiles of Patients in a Cohort + maintainer: Gowtham Rao + description: |- + This software tool is designed to extract data from a randomized subset of individuals + within a cohort and make it available for exploration in a shiny application environment. It + retrieves date-stamped, event-level records from one or more data sources that represent patient + data in the Observational Medical Outcomes Partnership (OMOP) data model format. This tool + features a user-friendly interface that enables users to efficiently explore the extracted + profiles, thereby facilitating applications, such as reviewing structured profiles. + date_publication: '2023-10-23' + bug_reports: https://github.com/OHDSI/CohortExplorer/issues + url: https://ohdsi.github.io/CohortExplorer/ + url_cran: https://CRAN.R-project.org/package=CohortExplorer + url_git: https://github.com/OHDSI/CohortExplorer +CohortGenerator: + version: 0.11.2 + title: Cohort Generation for the OMOP Common Data Model + maintainer: Anthony Sena + description: |- + Generate cohorts and subsets using an Observational + Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. + Cohorts are defined using 'CIRCE' () or + SQL compatible with 'SqlRender' (). + date_publication: '2024-09-30' + bug_reports: https://github.com/OHDSI/CohortGenerator/issues + url: https://ohdsi.github.io/CohortGenerator/ + url_cran: https://CRAN.R-project.org/package=CohortGenerator + url_git: https://github.com/OHDSI/CohortGenerator +CohortPlat: + version: 1.0.5 + title: Simulation of Cohort Platform Trials for Combination Treatments + maintainer: Elias Laurin Meyer + description: |- + A collection of functions dedicated to simulating staggered entry platform + trials whereby the treatment under investigation is a combination of two + active compounds. In order to obtain approval for this combination therapy, + superiority of the combination over the two active compounds and superiority + of the two active compounds over placebo need to be demonstrated. + A more detailed description of the design can be found in + Meyer et al. and a manual in Meyer et al. . + date_publication: '2022-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CohortPlat + url_git: '' +cohorts: + version: 1.0.1 + title: Cohort Analysis Made Easy + maintainer: Peer Christensen + description: Functions to simplify the process of preparing event and transaction + for cohort analysis. + date_publication: '2022-05-15' + bug_reports: https://github.com/PeerChristensen/cohorts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cohorts + url_git: https://github.com/PeerChristensen/cohorts +CohortSurvival: + version: 0.6.2 + title: Estimate Survival from Common Data Model Cohorts + maintainer: Edward Burn + description: Estimate survival using data mapped to the Observational Medical Outcomes + Partnership common data model. Survival can be estimated based on user-defined + study cohorts. + date_publication: '2025-01-22' + bug_reports: '' + url: https://darwin-eu-dev.github.io/CohortSurvival/ + url_cran: https://CRAN.R-project.org/package=CohortSurvival + url_git: '' +CohortSymmetry: + version: 0.2.2 + title: |- + Sequence Symmetry Analysis Using the Observational Medical + Outcomes Partnership Common Data Model + maintainer: Xihang Chen + description: |- + Calculating crude sequence ratio, adjusted sequence ratio and + confidence intervals using data mapped to the Observational Medical + Outcomes Partnership Common Data Model. + date_publication: '2025-03-01' + bug_reports: https://github.com/OHDSI/CohortSymmetry/issues + url: https://ohdsi.github.io/CohortSymmetry/ + url_cran: https://CRAN.R-project.org/package=CohortSymmetry + url_git: '' +cohorttools: + version: 0.1.6 + title: Cohort Data Analyses + maintainer: Jari Haukka + description: Functions to make lifetables and to calculate hazard function estimate + using Poisson regression model with splines. Includes function to draw simple + flowchart of cohort study. Function boxesLx() makes boxes of transition rates + between states. It utilizes 'Epi' package 'Lexis' data. + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cohorttools + url_git: '' +CoImp: + version: 2.0.2 + title: Parametric and Non-Parametric Copula-Based Imputation Methods + maintainer: Francesca Marta Lilja Di Lascio + description: 'Copula-based imputation methods: parametric and non-parametric algorithms + for missing multivariate data through conditional copulas.' + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoImp + url_git: '' +coin: + version: 1.4-3 + title: Conditional Inference Procedures in a Permutation Test Framework + maintainer: Torsten Hothorn + description: |- + Conditional inference procedures for the general independence + problem including two-sample, K-sample (non-parametric ANOVA), + correlation, censored, ordered and multivariate problems described + in . + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coin + url_git: http://coin.r-forge.r-project.org +coinmarketcapr: + version: '0.4' + title: Get 'Cryptocurrencies' Market Cap Prices from Coin Market Cap + maintainer: AbdulMajedRaja RS + description: Extract and monitor price and market cap of 'Cryptocurrencies' from + 'Coin Market Cap' . + date_publication: '2022-02-27' + bug_reports: https://github.com/amrrs/coinmarketcapr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coinmarketcapr + url_git: https://github.com/amrrs/coinmarketcapr +Coinprofile: + version: 0.1.9 + title: Coincident Profile + maintainer: Wilmer Martinez + description: |- + Builds the + coincident profile proposed by Martinez, W and Nieto, Fabio H and Poncela, P (2016) + . + This methodology studies the relationship between a couple of + time series based on the the set of turning points of each + time series. The coincident profile establishes if two time + series are coincident, or one of them leads the second. + date_publication: '2019-08-25' + bug_reports: https://github.com/WilmerMartinezR/Coinprofile/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Coinprofile + url_git: https://github.com/WilmerMartinezR/Coinprofile +COINr: + version: 1.1.14 + title: Composite Indicator Construction and Analysis + maintainer: William Becker + description: |- + A comprehensive high-level package, for composite indicator construction and analysis. It is a "development environment" + for composite indicators and scoreboards, which includes utilities for construction (indicator selection, denomination, imputation, + data treatment, normalisation, weighting and aggregation) and analysis (multivariate analysis, correlation plotting, short cuts for + principal component analysis, global sensitivity analysis, and more). A composite indicator is completely encapsulated inside a single + hierarchical list called a "coin". This allows a fast and efficient work flow, as well as making quick copies, testing methodological variations and making comparisons. + It also includes many plotting options, both statistical (scatter plots, distribution plots) as well as for presenting results. + date_publication: '2024-05-21' + bug_reports: https://github.com/bluefoxr/COINr/issues + url: https://bluefoxr.github.io/COINr/ + url_cran: https://CRAN.R-project.org/package=COINr + url_git: '' +cointmonitoR: + version: 0.1.0 + title: |- + Consistent Monitoring of Stationarity and Cointegrating + Relationships + maintainer: Philipp Aschersleben + description: |- + We propose a consistent monitoring procedure to detect a + structural change from a cointegrating relationship to a spurious + relationship. The procedure is based on residuals from modified least + squares estimation, using either Fully Modified, Dynamic or Integrated + Modified OLS. It is inspired by Chu et al. (1996) in + that it is based on parameter estimation on a pre-break "calibration" period + only, rather than being based on sequential estimation over the full sample. + See the discussion paper for further information. + This package provides the monitoring procedures for both the cointegration + and the stationarity case (while the latter is just a special case of the + former one) as well as printing and plotting methods for a clear + presentation of the results. + date_publication: '2016-06-14' + bug_reports: https://github.com/aschersleben/cointmonitoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cointmonitoR + url_git: https://github.com/aschersleben/cointmonitoR +cointReg: + version: 0.2.0 + title: Parameter Estimation and Inference in a Cointegrating Regression + maintainer: Philipp Aschersleben + description: |- + Cointegration methods are widely used in empirical macroeconomics + and empirical finance. It is well known that in a cointegrating + regression the ordinary least squares (OLS) estimator of the + parameters is super-consistent, i.e. converges at rate equal to the + sample size T. When the regressors are endogenous, the limiting + distribution of the OLS estimator is contaminated by so-called second + order bias terms, see e.g. Phillips and Hansen (1990) . + The presence of these bias terms renders inference difficult. Consequently, + several modifications to OLS that lead to zero mean Gaussian mixture + limiting distributions have been proposed, which in turn make + standard asymptotic inference feasible. These methods include + the fully modified OLS (FM-OLS) approach of Phillips and Hansen + (1990) , the dynamic OLS (D-OLS) approach of Phillips + and Loretan (1991) , Saikkonen (1991) + and Stock and Watson (1993) + and the new estimation approach called integrated + modified OLS (IM-OLS) of Vogelsang and Wagner (2014) + . The latter is based on an augmented + partial sum (integration) transformation of the regression model. IM-OLS is + similar in spirit to the FM- and D-OLS approaches, with the key difference + that it does not require estimation of long run variance matrices and avoids + the need to choose tuning parameters (kernels, bandwidths, lags). However, + inference does require that a long run variance be scaled out. + This package provides functions for the parameter estimation and inference + with all three modified OLS approaches. That includes the automatic + bandwidth selection approaches of Andrews (1991) and + of Newey and West (1994) as well as the calculation of + the long run variance. + date_publication: '2016-06-14' + bug_reports: https://github.com/aschersleben/cointReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cointReg + url_git: https://github.com/aschersleben/cointReg +cold: + version: 2.0-3 + title: Count Longitudinal Data + maintainer: M. Helena Goncalves + description: |- + Performs regression analysis for longitudinal count data, + allowing for serial dependence among observations from a given + individual and two dimensional random effects on the linear predictor. + Estimation is via maximization of the exact likelihood of a suitably + defined model. Missing values and unbalanced data are allowed. + Details can be found in the accompanying scientific papers: + Goncalves & Cabral (2021, Journal of Statistical Software, + ) and Goncalves et al. + (2007, Computational Statistics & Data Analysis, + ). + date_publication: '2021-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cold + url_git: '' +colf: + version: 0.1.3 + title: Constrained Optimization on Linear Function + maintainer: Theo Boutaris + description: |- + Performs least squares constrained optimization on a linear objective function. It contains + a number of algorithms to choose from and offers a formula syntax similar to lm(). + date_publication: '2017-10-09' + bug_reports: https://github.com/LyzandeR/colf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colf + url_git: https://github.com/LyzandeR/colf +collapse: + version: 2.0.19 + title: Advanced and Fast Data Transformation + maintainer: Sebastian Krantz + description: |- + A C/C++ based package for advanced data transformation and + statistical computing in R that is extremely fast, class-agnostic, robust and + programmer friendly. Core functionality includes a rich set of S3 generic grouped + and weighted statistical functions for vectors, matrices and data frames, which + provide efficient low-level vectorizations, OpenMP multithreading, and skip missing + values by default. These are integrated with fast grouping and ordering algorithms + (also callable from C), and efficient data manipulation functions. The package also + provides a flexible and rigorous approach to time series and panel data in R. + It further includes fast functions for common statistical procedures, detailed + (grouped, weighted) summary statistics, powerful tools to work with nested data, + fast data object conversions, functions for memory efficient R programming, and + helpers to effectively deal with variable labels, attributes, and missing data. + It is well integrated with base R classes, 'dplyr'/'tibble', 'data.table', 'sf', 'units', + 'plm' (panel-series and data frames), and 'xts'/'zoo'. + date_publication: '2025-01-09' + bug_reports: https://github.com/SebKrantz/collapse/issues + url: https://sebkrantz.github.io/collapse/ + url_cran: https://CRAN.R-project.org/package=collapse + url_git: '' +CollapseLevels: + version: 0.3.0 + title: Collapses Levels, Computes Information Value and WoE + maintainer: Krishanu Mukherjee + description: |- + Contains functions to help in selecting and exploring features ( or variables ) in binary classification problems. + Provides functions to compute and display information value and weight of evidence (WoE) of the variables , and to convert numeric variables to categorical variables by binning. + Functions are also provided to determine which levels ( or categories ) of a categorical variable can be collapsed (or combined ) based on their response rates. + The functions provided only work for binary classification problems. + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CollapseLevels + url_git: '' +collapsibleTree: + version: 0.1.8 + title: Interactive Collapsible Tree Diagrams using 'D3.js' + maintainer: Adeel Khan + description: |2- + + Interactive Reingold-Tilford tree diagrams created using 'D3.js', where every node can be expanded and collapsed by clicking on it. + Tooltips and color gradients can be mapped to nodes using a numeric column in the source data frame. + See 'collapsibleTree' website for more information and examples. + date_publication: '2023-11-13' + bug_reports: https://github.com/AdeelK93/collapsibleTree/issues + url: https://AdeelK93.github.io/collapsibleTree/ + url_cran: https://CRAN.R-project.org/package=collapsibleTree + url_git: https://github.com/AdeelK93/collapsibleTree +collateral: + version: 0.5.2 + title: Quickly Evaluate Captured Side Effects + maintainer: James Goldie + description: Map functions while capturing results, errors, warnings, messages and + other output tidily, then filter and summarise data frames or lists on the basis + of those side effects. + date_publication: '2021-10-25' + bug_reports: https://github.com/jimjam-slam/collateral/issues + url: https://collateral.jamesgoldie.dev + url_cran: https://CRAN.R-project.org/package=collateral + url_git: https://github.com/jimjam-slam/collateral +collatz: + version: 1.0.0 + title: Functions Related to the Collatz/Syracuse/3n+1 Problem + maintainer: Nathan Levett + description: |- + Provides the basic functionality to interact with the Collatz conjecture. + The parameterisation uses the same (P,a,b) notation as Conway's generalisations. + Besides the function and reverse function, there is also functionality to retrieve + the hailstone sequence, the "stopping time"/"total stopping time", or tree-graph. + The only restriction placed on parameters is that both P and a can't be 0. + For further reading, see . + date_publication: '2022-09-05' + bug_reports: https://github.com/Skenvy/Collatz/issues/new/choose + url: https://skenvy.github.io/Collatz/R/ + url_cran: https://CRAN.R-project.org/package=collatz + url_git: https://github.com/Skenvy/Collatz +collections: + version: 0.3.7 + title: High Performance Container Data Types + maintainer: Randy Lai + description: |- + Provides high performance container data types such + as queues, stacks, deques, dicts and ordered dicts. Benchmarks + have + shown that these containers are asymptotically more efficient than + those offered by other packages. + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=collections + url_git: https://github.com/randy3k/collections/ +collegeScorecard: + version: 0.2.0 + title: US College Scorecard Data + maintainer: Garrick Aden-Buie + description: |- + Provides a tidied subset of the US College Scorecard dataset, + containing institutional characteristics, enrollment, student aid, + costs, and student outcomes at institutions of higher education in the + United States. + date_publication: '2025-02-13' + bug_reports: https://github.com/gadenbuie/scorecard-db/issues + url: https://collegescorecard.ed.gov/data/ + url_cran: https://CRAN.R-project.org/package=collegeScorecard + url_git: https://github.com/gadenbuie/scorecard-db +collett: + version: 0.1.0 + title: |- + Datasets from "Modelling Survival Data in Medical Research" by + Collett + maintainer: Mark Clements + description: Datasets for the book entitled "Modelling Survival Data in Medical + Research" by Collett (2023) . The datasets provide + extensive examples of time-to-event data. + date_publication: '2025-01-09' + bug_reports: https://github.com/mclements/collett/issues + url: '' + url_cran: https://CRAN.R-project.org/package=collett + url_git: https://github.com/mclements/collett +collidr: + version: 0.1.3 + title: |- + Check for Namespace Collisions Across Packages and Functions on + CRAN + maintainer: Steve Condylios + description: |- + Check for namespace collisions between a string input (your function or package name) + and half a million packages and functions on CRAN. + date_publication: '2020-10-03' + bug_reports: https://github.com/collidrpackage/collidr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=collidr + url_git: https://github.com/collidrpackage/collidr +collin: + version: 0.0.4 + title: |- + Visualization the Effects of Collinearity in Distributed Lag + Models and Other Linear Models + maintainer: Jose Barrera-Gomez + description: |- + Tool to assessing whether the results of a study could be influenced by + collinearity. Simulations under a given hypothesized truth regarding effects of an + exposure on the outcome are used and the resulting curves of lagged effects are + visualized. A user's manual is provided, which includes detailed examples (e.g. a + cohort study looking for windows of vulnerability to air pollution, a time series + study examining the linear association of air pollution with hospital admissions, + and a time series study examining the non-linear association between temperature and + mortality). The methods are described in Basagana and Barrera-Gomez (2021) . + date_publication: '2023-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=collin + url_git: '' +collinear: + version: 2.0.0 + title: Automated Multicollinearity Management + maintainer: Blas M. Benito + description: 'Effortless multicollinearity management in data frames with both numeric + and categorical variables for statistical and machine learning applications. The + package simplifies multicollinearity analysis by combining four robust methods: + 1) target encoding for categorical variables (Micci-Barreca, D. 2001 ); + 2) automated feature prioritization to prevent key variable loss during filtering; + 3) pairwise correlation for all variable combinations (numeric-numeric, numeric-categorical, + categorical-categorical); and 4) fast computation of variance inflation factors.' + date_publication: '2024-11-08' + bug_reports: https://github.com/blasbenito/collinear/issues + url: https://blasbenito.github.io/collinear/ + url_cran: https://CRAN.R-project.org/package=collinear + url_git: '' +CollocInfer: + version: 1.0.5 + title: Collocation Inference for Dynamic Systems + maintainer: Giles Hooker + description: |- + These functions implement collocation-inference + for continuous-time and discrete-time stochastic processes. + They provide model-based smoothing, gradient-matching, + generalized profiling and forwards prediction error methods. + date_publication: '2024-11-05' + bug_reports: '' + url: http://www.gileshooker.com + url_cran: https://CRAN.R-project.org/package=CollocInfer + url_git: '' +collpcm: + version: '1.4' + title: Collapsed Latent Position Cluster Model for Social Networks + maintainer: Jason Wyse + description: Markov chain Monte Carlo based inference routines for collapsed latent + position cluster models or social networks, which includes searches over the model + space (number of clusters in the latent position cluster model). The label switching + algorithm used is that of Nobile and Fearnside (2007) + which relies on the algorithm of Carpaneto and Toth (1980) . + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=collpcm + url_git: '' +collUtils: + version: 1.0.5 + title: Auxiliary Package for Package 'CollapsABEL' + maintainer: Kaiyin Zhong + description: Provides some low level functions for processing PLINK input and output + files. + date_publication: '2016-03-31' + bug_reports: https://bitbucket.org/kindlychung/collutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=collUtils + url_git: https://bitbucket.org/kindlychung/collutils +colmozzie: + version: 1.1.1 + title: Dengue Cases and Climate Variables in Colombo Sri Lanka + maintainer: Thiyanga Talagala + description: Weekly notified dengue cases and climate variables in Colombo district + Sri Lanka from 2008/ week-52 to 2014/ week-21. + date_publication: '2018-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colmozzie + url_git: '' +coloc: + version: 5.2.3 + title: Colocalisation Tests of Two Genetic Traits + maintainer: Chris Wallace + description: |- + Performs the colocalisation tests described in + Giambartolomei et al (2013) , + Wallace (2020) , + Wallace (2021) . + date_publication: '2023-10-03' + bug_reports: https://github.com/chr1swallace/coloc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coloc + url_git: https://github.com/chr1swallace/coloc +colocalization: + version: 1.0.2 + title: Normalized Spatial Intensity Correlation + maintainer: Hui Zhang + description: Calculate the colocalization index, NSInC, in two different ways as + described in the paper (Liu et al., 2019. Manuscript submitted for publication.) + for multiple-species spatial data which contain the precise locations and membership + of each spatial point. The two main functions are nsinc.d() and nsinc.z(). They + provide the Pearson’s correlation coefficients of signal proportions in different + memberships within a concerned proximity of every signal (or every base signal + if single direction colocalization is considered) across all (base) signals using + two different ways of normalization. The proximity sizes could be an individual + value or a range of values, where the default ranges of values are different for + the two functions. + date_publication: '2020-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colocalization + url_git: '' +colocalized: + version: 0.2.0 + title: Clusters of Colocalized Sequences + maintainer: Stefan Golas + description: |- + Also abbreviates to "CCSeq". Finds clusters of colocalized sequences in .bed annotation files + up to a specified cut-off distance. Two sequences are colocalized if they + are within the cut-off distance of each other, and clusters are sets of + sequences where each sequence is colocalized to at least one other sequence + in the cluster. For a set of .bed annotation tables provided in a list + along with a cut-off distance, the program will output a file containing + the locations of each cluster. Annotated .bed files are from + the 'pwmscan' application at . + Personal machines might crash or take excessively long depending + on the number of annotated sequences in each file and whether chromsearch() + or gensearch() is used. + date_publication: '2019-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colocalized + url_git: '' +colocPropTest: + version: 0.9.1 + title: Proportional Testing for Colocalisation Analysis + maintainer: Chris Wallace + description: |- + Colocalisation analysis tests whether two traits share a causal + genetic variant in a specified genomic region. Proportional testing for + colocalisation has been previously proposed + [Wallace (2013) ], but is reimplemented here to + overcome barriers to its adoption. Its use is complementary to the fine- + mapping based colocalisation method in the 'coloc' package, and may be used in + particular to identify false "H3" conclusions in 'coloc'. + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colocPropTest + url_git: '' +colocr: + version: 0.1.1 + title: |- + Conduct Co-Localization Analysis of Fluorescence Microscopy + Images + maintainer: Mahmoud Ahmed + description: |- + Automate the co-localization analysis of fluorescence microscopy + images. Selecting regions of interest, extract pixel intensities from + the image channels and calculate different co-localization statistics. The + methods implemented in this package are based on Dunn et al. (2011) + . + date_publication: '2020-05-08' + bug_reports: https://github.com/ropensci/colocr/issues + url: https://docs.ropensci.org/colocr + url_cran: https://CRAN.R-project.org/package=colocr + url_git: https://github.com/ropensci/colocr +ColombiAPI: + version: 0.1.1 + title: Access Colombia's Public Data via 'API-Colombia' + maintainer: Renzo Caceres Rossi + description: |- + Provides a seamless interface to access diverse public data about + Colombia through the 'API-Colombia', a RESTful API. The package enables users + to explore various aspects of Colombia, including general information, + geography, and cultural insights. It includes five API-related functions to + retrieve data on topics such as Colombia's general information, airports, + departments, regions, and presidents. Additionally, 'ColombiAPI' offers a + built-in function to view the datasets available within the package. The + package also includes curated datasets covering Bogota air stations, + business and holiday dates, public schools, Colombian coffee exports, + cannabis licenses, Medellin rainfall, and malls in Bogota, making it a + comprehensive tool for exploring Colombia's data. For more details on the + 'API-Colombia', see . + date_publication: '2025-02-16' + bug_reports: https://github.com/lightbluetitan/colombiapi/issues + url: https://lightbluetitan.github.io/colombiapi/ + url_cran: https://CRAN.R-project.org/package=ColombiAPI + url_git: https://github.com/lightbluetitan/colombiapi +ColOpenData: + version: 0.3.1 + title: Download Colombian Demographic, Climate and Geospatial Data + maintainer: Maria Camila Tavera-Cifuentes + description: |- + Downloads wrangled Colombian socioeconomic, geospatial,population + and climate data from DANE (National + Administrative Department of Statistics) and IDEAM + (Institute of Hydrology, Meteorology and Environmental Studies). It solves + the problem of Colombian data being issued in different web pages and sources by + using functions that allow the user to select the desired database and + download it without having to do the exhausting acquisition process. + date_publication: '2024-10-30' + bug_reports: https://github.com/epiverse-trace/ColOpenData/issues + url: https://epiverse-trace.github.io/ColOpenData/ + url_cran: https://CRAN.R-project.org/package=ColOpenData + url_git: https://github.com/epiverse-trace/ColOpenData +colorblindcheck: + version: 1.0.2 + title: Check Color Palettes for Problems with Color Vision Deficiency + maintainer: Jakub Nowosad + description: |- + Compare color palettes with simulations of color vision deficiencies - deuteranopia, protanopia, and tritanopia. + It includes calculation of distances between colors, and creating summaries of differences between a color palette and simulations of color vision deficiencies. + This work was inspired by the blog post at . + date_publication: '2023-05-13' + bug_reports: https://github.com/Nowosad/colorblindcheck/issues + url: https://jakubnowosad.com/colorblindcheck/ + url_cran: https://CRAN.R-project.org/package=colorblindcheck + url_git: '' +colorBlindness: + version: 0.1.9 + title: Safe Color Set for Color Blindness + maintainer: Jianhong Ou + description: |- + Provide the safe color set for color blindness, + the simulator of protanopia, deuteranopia. + The color sets are collected from: + Wong, B. (2011) , and + . + The simulations of the appearance of the colors to color-deficient + viewers were based on algorithms in + Vienot, F., Brettel, H. and Mollon, J.D. (1999) + . + The cvdPlot() function to generate 'ggplot' grobs of simulations + were modified from . + date_publication: '2021-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorBlindness + url_git: '' +colorDF: + version: 0.1.7 + title: Colorful Data Frames in R Terminal + maintainer: January Weiner + description: |- + Colorful Data Frames in the terminal. The new class does + change the behaviour of any of the objects, but adds a style + definition and a print method. Using ANSI escape codes, it + colors the terminal output of data frames. Some column types + (such as p-values and identifiers) are automatically + recognized. + date_publication: '2022-09-26' + bug_reports: '' + url: https://january3.github.io/colorDF/ + url_cran: https://CRAN.R-project.org/package=colorDF + url_git: https://github.com/january3/colorDF/ +colordistance: + version: 1.1.2 + title: Distance Metrics for Image Color Similarity + maintainer: Hannah Weller + description: |- + Loads and displays images, selectively masks specified background + colors, bins pixels by color using either data-dependent or + automatically generated color bins, quantitatively measures color + similarity among images using one of several distance metrics for + comparing pixel color clusters, and clusters images by object color + similarity. Uses CIELAB, RGB, or HSV color spaces. Originally written + for use with organism coloration (reef fish color diversity, butterfly + mimicry, etc), but easily applicable for any image set. + date_publication: '2021-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colordistance + url_git: '' +colorednoise: + version: 1.1.2 + title: Simulate Temporally Autocorrelated Populations + maintainer: July Pilowsky + description: |- + Temporally autocorrelated populations are correlated in their vital rates (growth, death, etc.) from year to year. It is very common for populations, whether they be bacteria, plants, or humans, to be temporally autocorrelated. This poses a challenge for stochastic population modeling, because a temporally correlated population will behave differently from an uncorrelated one. + This package provides tools for simulating populations with white noise (no temporal autocorrelation), red noise (positive temporal autocorrelation), and blue noise (negative temporal autocorrelation). The algebraic formulation for autocorrelated noise comes from Ruokolainen et al. (2009) . Models for unstructured populations and for structured populations (matrix models) are available. + date_publication: '2024-02-28' + bug_reports: https://github.com/japilo/colorednoise/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colorednoise + url_git: '' +colorfast: + version: 1.0.1 + title: |- + Fast Conversion of R Colors to Color Component Values and Native + Packed Integer Format + maintainer: Mike Cheng + description: |- + Color values in R are often represented as strings of hexadecimal + colors or named colors. This package offers fast conversion of + these color representations to either an array of red/green/blue/alpha values + or to the packed integer format used in native raster objects. Functions + for conversion are also exported at the 'C' level for use in other packages. + This fast conversion + of colors is implemented using an order-preserving minimal perfect hash + derived from Majewski et al (1996) "A Family of Perfect Hashing Methods" + . + date_publication: '2025-01-13' + bug_reports: https://github.com/coolbutuseless/colorfast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colorfast + url_git: https://github.com/coolbutuseless/colorfast +colorfindr: + version: 0.1.4 + title: |- + Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format + Images + maintainer: David Zumbach + description: |- + Extracts colors from various image types, returns customized reports and plots treemaps + and 3D scatterplots of image compositions. Color palettes can also be created. + date_publication: '2019-02-01' + bug_reports: https://github.com/zumbov2/colorfindr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colorfindr + url_git: '' +colorhcplot: + version: 1.3.1 + title: Colorful Hierarchical Clustering Dendrograms + maintainer: Damiano Fantini + description: Build dendrograms with sample groups highlighted by different colors. + Visualize results of hierarchical clustering analyses as dendrograms whose leaves + and labels are colored according to sample grouping. Assess whether data point + grouping aligns to naturally occurring clusters. + date_publication: '2018-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorhcplot + url_git: '' +colorist: + version: 0.1.3 + title: Coloring Wildlife Distributions in Space-Time + maintainer: Matthew Strimas-Mackey + description: |- + Color and visualize wildlife distributions in + space-time using raster data. In addition to enabling display of + sequential change in distributions through the use of small multiples, + 'colorist' provides functions for extracting several features of + interest from a sequence of distributions and for visualizing those + features using HCL (hue-chroma-luminance) color palettes. Resulting + maps allow for "fair" visual comparison of intensity values (e.g., + occurrence, abundance, or density) across space and time and can be + used to address questions about where, when, and how consistently a + species, group, or individual is likely to be found. + date_publication: '2024-04-29' + bug_reports: https://github.com/mstrimas/colorist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colorist + url_git: https://github.com/mstrimas/colorist +colorizer: + version: 0.1.0 + title: Colorize Old Images Using the 'DeOldify' Image Colorization API + maintainer: David Zumbach + description: |- + Call the 'DeOldify' image + colorization API on 'DeepAI' + to colorize black and white images. + date_publication: '2020-11-06' + bug_reports: https://github.com/zumbov2/colorizer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colorizer + url_git: https://github.com/zumbov2/colorizer +colormap: + version: 0.1.4 + title: Color Palettes using Colormaps Node Module + maintainer: Bhaskar Karambelkar + description: Allows to generate colors from palettes defined in the colormap module + of 'Node.js'. (see for more information). + In total it provides 44 distinct palettes made from sequential and/or diverging + colors. In addition to the pre defined palettes you can also specify your own + set of colors. There are also scale functions that can be used with 'ggplot2'. + date_publication: '2016-11-15' + bug_reports: https://github.com/bhaskarvk/colormap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colormap + url_git: https://github.com/bhaskarvk/colormap +ColorNameR: + version: 0.1.0 + title: Give Colors a Name + maintainer: Marco Sánchez Beeckman + description: |- + A tool for transforming coordinates in a color space to common + color names using data from the Royal Horticultural Society and the + International Union for the Protection of New Varieties of Plants. + date_publication: '2021-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ColorNameR + url_git: https://github.com/msanchez-beeckman/ColorNameR +colorpatch: + version: 0.1.2 + title: Optimized Rendering of Fold Changes and Confidence Values + maintainer: Andre Mueller + description: |- + Shows color patches for encoding fold changes (e.g. log ratios) together with confidence values + within a single diagram. This is especially useful for rendering gene expression data as well as + other types of differential experiments. In addition to different rendering methods (ggplot extensions) + functionality for perceptually optimizing color palettes are provided. + Furthermore the package provides extension methods of the colorspace color-class in order to + simplify the work with palettes (a.o. length, as.list, and append are supported). + date_publication: '2017-06-10' + bug_reports: '' + url: http://sysbio.uni-ulm.de/?Software:colorpatch + url_cran: https://CRAN.R-project.org/package=colorpatch + url_git: '' +colorplane: + version: 0.5.0 + title: |- + Basic S4 Classes and Methods for Mapping Between Numeric Values + and Colors + maintainer: Bradley R Buchsbaum + description: A simple set of classes and methods for mapping between scalar intensity + values and colors. There is also support for layering maps on top of one another + using alpha composition. + date_publication: '2023-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorplane + url_git: '' +colorr: + version: 1.0.0 + title: Color Palettes for EPL, MLB, NBA, NHL, and NFL Teams + maintainer: Charles Crabtree + description: Color palettes for EPL, MLB, NBA, NHL, and NFL teams. + date_publication: '2017-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorr + url_git: '' +colorRamp2: + version: 0.1.0 + title: Generate Color Mapping Functions + maintainer: Zuguang Gu + description: |- + A color mapping is generated according to the break values and corresponding colors. + Other colors are generated by interpolating in a certain color space. The functions were part + of the 'circlize' package . + date_publication: '2022-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorRamp2 + url_git: https://github.com/jokergoo/colorRamp2 +colorRamps: + version: 2.3.4 + title: Builds Color Tables + maintainer: Gregory Jefferis + description: Builds gradient color maps. + date_publication: '2024-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorRamps + url_git: '' +colorrepel: + version: 0.4.1 + title: |- + Repel Visually Similar Colors for Colorblind Users in Various + Plots + maintainer: Rui Fu + description: Iterate and repel visually similar colors away in various 'ggplot2' + plots. When many groups are plotted at the same time on multiple axes, for instance + stacked bars or scatter plots, effectively ordering colors becomes difficult. + This tool iterates through color combinations to find the best solution to maximize + visual distinctness of nearby groups, so plots are more friendly toward colorblind + users. This is achieved by two distance measurements, distance between groups + within the plot, and CIELAB color space distances between colors as described + in Carter et al., (2018) . + date_publication: '2025-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorrepel + url_git: https://github.com/raysinensis/color_repel +colors3d: + version: 1.0.1 + title: Generate 2D and 3D Color Palettes + maintainer: Matthew Kling + description: Generate multivariate color palettes to represent two-dimensional or + three-dimensional data in graphics (in contrast to standard color palettes that + represent just one variable). You tell 'colors3d' how to map color space onto + your data, and it gives you a color for each data point. You can then use these + colors to make plots in base 'R', 'ggplot2', or other graphics frameworks. + date_publication: '2023-10-31' + bug_reports: https://github.com/matthewkling/colors3d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colors3d + url_git: https://github.com/matthewkling/colors3d +colorscience: + version: 1.0.9 + title: Color Science Methods and Data + maintainer: Glenn Davis + description: |- + Methods and data for color science - color conversions by observer, + illuminant, and gamma. Color matching functions and chromaticity diagrams. + Color indices, color differences, and spectral data conversion/analysis. + This package is deprecated and will someday be removed; for reasons and details please see the README file. + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorscience + url_git: '' +colorsGen: + version: 1.0.0 + title: Generation of Random Colors + maintainer: Stéphane Laurent + description: |- + Generation of random colors, possibly with a given hue or a + given luminosity. This is a port of the JavaScript library + 'randomColor' . + date_publication: '2023-10-28' + bug_reports: https://github.com/stla/colorsGen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colorsGen + url_git: https://github.com/stla/colorsGen +colorspace: + version: 2.1-1 + title: A Toolbox for Manipulating and Assessing Colors and Palettes + maintainer: Achim Zeileis + description: |- + Carries out mapping between assorted color spaces including RGB, HSV, HLS, + CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB, and polar CIELAB. + Qualitative, sequential, and diverging color palettes based on HCL colors + are provided along with corresponding ggplot2 color scales. + Color palette choice is aided by an interactive app (with either a Tcl/Tk + or a shiny graphical user interface) and shiny apps with an HCL color picker and a + color vision deficiency emulator. Plotting functions for displaying + and assessing palettes include color swatches, visualizations of the + HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation + functions include: desaturation, lightening/darkening, mixing, and + simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly). + Details can be found on the project web page at + and in the accompanying scientific paper: Zeileis et al. (2020, Journal of Statistical + Software, ). + date_publication: '2024-07-26' + bug_reports: https://colorspace.R-Forge.R-project.org/contact.html + url: https://hclwizard.org/ + url_cran: https://CRAN.R-project.org/package=colorspace + url_git: https://colorspace.R-Forge.R-project.org/ +colorSpec: + version: 1.7-0 + title: Color Calculations with Emphasis on Spectral Data + maintainer: Glenn Davis + description: |- + Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. + Build complex systems from simpler parts using a spectral product algebra. For light sources, + compute CCT, CRI, SSI, and IES TM-30 reports. For object colors, compute optimal colors and Logvinenko coordinates. + Work with the standard CIE illuminants and color matching functions, and read spectra from + text files, including CGATS files. Estimate a spectrum from its response. A user guide and 9 vignettes are included. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colorSpec + url_git: '' +Colossus: + version: '1.2' + title: |- + "Risk Model Regression and Analysis with Complex Non-Linear + Models" + maintainer: Eric Giunta + description: Performs survival analysis using general non-linear models. Risk models + can be the sum or product of terms. Each term is the product of exponential/linear + functions of covariates. Additionally sub-terms can be defined as a sum of exponential, + linear threshold, and step functions. Cox Proportional hazards , + Poisson , and Fine-Gray competing + risks + regression are supported. This work was sponsored by NASA Grant 80NSSC19M0161 + through a subcontract from the National Council on Radiation Protection and Measurements + (NCRP). The computing for this project was performed on the Beocat Research Cluster + at Kansas State University, which is funded in part by NSF grants CNS-1006860, + EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109. + date_publication: '2025-02-13' + bug_reports: https://github.com/ericgiunta/Colossus/issues + url: https://ericgiunta.github.io/Colossus/ + url_cran: https://CRAN.R-project.org/package=Colossus + url_git: https://github.com/ericgiunta/Colossus +colouR: + version: 0.1.1 + title: Create Colour Palettes from Images + maintainer: Alan Inglis + description: Can take in images in either .jpg, .jpeg, or .png format and creates + a colour palette of the most frequent colours used in the image. Also provides + some custom colour palettes. + date_publication: '2023-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colouR + url_git: '' +colourlovers: + version: 0.3.6 + title: R Client for the COLOURlovers API + maintainer: Andrew Heiss + description: |- + Provides access to the COLOURlovers + API, which offers color inspiration and color palettes. + date_publication: '2020-12-09' + bug_reports: https://github.com/andrewheiss/colourlovers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colourlovers + url_git: https://github.com/andrewheiss/colourlovers +colourpicker: + version: 1.3.0 + title: |- + A Colour Picker Tool for Shiny and for Selecting Colours in + Plots + maintainer: Dean Attali + description: |- + A colour picker that can be used as an input in 'Shiny' apps + or Rmarkdown documents. The colour picker supports alpha opacity, custom + colour palettes, and many more options. A Plot Colour Helper tool is + available as an 'RStudio' Addin, which helps you pick colours to use in your + plots. A more generic Colour Picker 'RStudio' Addin is also provided to let + you select colours to use in your R code. + date_publication: '2023-08-21' + bug_reports: https://github.com/daattali/colourpicker/issues + url: https://daattali.com/shiny/colourInput/ + url_cran: https://CRAN.R-project.org/package=colourpicker + url_git: https://github.com/daattali/colourpicker +colourvalues: + version: 0.3.9 + title: Assigns Colours to Values + maintainer: David Cooley + description: |- + Maps one of the viridis colour palettes, or a user-specified palette to values. + Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith, + and were set as the default palette for the 'Python' 'Matplotlib' library . + Other palettes available in this library have been derived from + 'RColorBrewer' and + 'colorspace' packages. + date_publication: '2023-04-11' + bug_reports: https://github.com/SymbolixAU/colourvalues/issues + url: https://symbolixau.github.io/colourvalues/ + url_cran: https://CRAN.R-project.org/package=colourvalues + url_git: '' +colourvision: + version: 2.1.0 + title: Colour Vision Models + maintainer: Felipe Malheiros Gawryszewski + description: Colour vision models, colour spaces and colour thresholds. Provides + flexibility to build user-defined colour vision models for n number of photoreceptor + types. Includes Vorobyev & Osorio (1998) Receptor Noise Limited models , + Chittka (1992) colour hexagon , and Endler & Mielke (2005) + model . Models have been extended to accept + any number of photoreceptor types. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=colourvision + url_git: '' +COLP: + version: 1.0.0 + title: Causal Discovery for Categorical Data with Label Permutation + maintainer: Yang Ni + description: Discover causality for bivariate categorical data. This package aims + to enable users to discover causality for bivariate observational categorical + data. See Ni, Y. (2022) "Bivariate Causal Discovery for Categorical + Data via Classification with Optimal Label Permutation. Advances in Neural Information + Processing Systems 35 (in press)". + date_publication: '2022-09-29' + bug_reports: https://github.com/nySTAT/COLP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=COLP + url_git: https://github.com/nySTAT/COLP +cols: + version: '1.5' + title: Constrained Ordinary Least Squares + maintainer: Michail Tsagris + description: 'Constrained ordinary least squares is performed. One constraint is + that all beta coefficients (including the constant) cannot be negative. They can + be either 0 or strictly positive. Another constraint is that the sum of the beta + coefficients equals a constant. References: Hansen, B. E. (2022). Econometrics, + Princeton University Press. .' + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cols + url_git: '' +cols4all: + version: '0.8' + title: Colors for all + maintainer: Martijn Tennekes + description: Color palettes for all people, including those with color vision deficiency. + Popular color palette series have been organized by type and have been scored + on several properties such as color-blind-friendliness and fairness (i.e. do colors + stand out equally?). Own palettes can also be loaded and analysed. Besides the + common palette types (categorical, sequential, and diverging) it also includes + cyclic and bivariate color palettes. Furthermore, a color for missing values is + assigned to each palette. + date_publication: '2024-10-16' + bug_reports: https://github.com/mtennekes/cols4all/issues + url: https://mtennekes.github.io/cols4all/ + url_cran: https://CRAN.R-project.org/package=cols4all + url_git: https://github.com/mtennekes/cols4all +colt: + version: 0.1.1 + title: Command-Line Color Themes + maintainer: Stefan Fleck + description: |2- + + A collection of command-line color styles based on the 'crayon' + package. 'Colt' styles are defined in themes that can easily be switched, to + ensure command line output looks nice on dark as well as light consoles. + date_publication: '2017-10-10' + bug_reports: https://github.com/s-fleck/colt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=colt + url_git: https://github.com/s-fleck/colt +comat: + version: 0.9.5 + title: Creates Co-Occurrence Matrices of Spatial Data + maintainer: Jakub Nowosad + description: |- + Builds co-occurrence matrices based on spatial raster data. + It includes creation of weighted co-occurrence matrices (wecoma) and + integrated co-occurrence matrices + (incoma; Vadivel et al. (2007) ). + date_publication: '2023-11-28' + bug_reports: https://github.com/Nowosad/comat/issues + url: https://jakubnowosad.com/comat/ + url_cran: https://CRAN.R-project.org/package=comat + url_git: '' +comato: + version: '1.1' + title: Analysis of Concept Maps and Concept Landscapes + maintainer: Andreas Muehling + description: Provides methods for the import/export and automated analysis of concept + maps and concept landscapes (sets of concept maps). + date_publication: '2018-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=comato + url_git: '' +COMBAT: + version: 0.0.4 + title: A Combined Association Test for Genes using Summary Statistics + maintainer: Minghui Wang + description: Genome-wide association studies (GWAS) have been widely used for identifying + common variants associated with complex diseases. Due to the small effect sizes + of common variants, the power to detect individual risk variants is generally + low. Complementary to SNP-level analysis, a variety of gene-based association + tests have been proposed. However, the power of existing gene-based tests is often + dependent on the underlying genetic models, and it is not known a priori which + test is optimal. Here we proposed COMBined Association Test (COMBAT) to incorporate + strengths from multiple existing gene-based tests, including VEGAS, GATES and + simpleM. Compared to individual tests, COMBAT shows higher overall performance + and robustness across a wide range of genetic models. The algorithm behind this + method is described in Wang et al (2017) . + date_publication: '2018-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COMBAT + url_git: '' +combat.enigma: + version: 1.1.1 + title: |- + Fit and Apply ComBat, LMM, or Prescaling Harmonization for + ENIGMA and Other Multisite MRI Data + maintainer: Joaquim Radua + description: Fit and apply ComBat, linear mixed-effects models (LMM), or prescaling + to harmonize magnetic resonance imaging (MRI) data from different sites. Briefly, + these methods remove differences between sites due to using different scanning + devices, and LMM additionally tests linear hypotheses. As detailed in the manual, + the original ComBat function was first modified for the harmonization of MRI data + (Fortin et al. (2017) ) and then modified + again to create separate functions for fitting and applying the harmonization + and allow missing values and constant rows for its use within the Enhancing Neuro + Imaging Genetics through Meta-Analysis (ENIGMA) Consortium (Radua et al. (2020) + ); this package includes the latter version. + LMM calls "lme" massively considering specific brain imaging details. Finally, + prescaling is a good option for fMRI, where different devices can have varying + units of measurement. + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=combat.enigma + url_git: '' +ComBatFamQC: + version: 1.0.4 + title: Comprehensive Batch Effect Diagnostics and Harmonization + maintainer: Zheng Ren + description: Provides a comprehensive framework for batch effect diagnostics, harmonization, + and post-harmonization downstream analysis. Features include interactive visualization + tools, robust statistical tests, and a range of harmonization techniques. Additionally, + 'ComBatFamQC' enables the creation of life-span age trend plots with estimated + age-adjusted centiles and facilitates the generation of covariate-corrected residuals + for analytical purposes. Methods for harmonization are based on approaches described + in Johnson et al., (2007) , Beer et al., (2020) + , Pomponio et al., (2020) , + and Chen et al., (2021) . + date_publication: '2025-01-25' + bug_reports: https://github.com/Zheng206/ComBatFamQC/issues + url: https://zheng206.github.io/ComBatQC-Web/ + url_cran: https://CRAN.R-project.org/package=ComBatFamQC + url_git: https://github.com/Zheng206/ComBatFamQC +combinat: + version: 0.0-8 + title: combinatorics utilities + maintainer: Vince Carey + description: routines for combinatorics + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=combinat + url_git: '' +combinationpvalues: + version: 0.1.4 + title: Combination of Independent P-Values + maintainer: Breya McGlown + description: 'Provides access to six fundamental statistics that can be used for + the purpose of combination p-values. All methods used can referenced here: Heard + & Rubin-Delanchy (2017) .' + date_publication: '2021-09-03' + bug_reports: https://github.com/StatsGirl/Master2021/issues + url: '' + url_cran: https://CRAN.R-project.org/package=combinationpvalues + url_git: https://github.com/StatsGirl/Master2021/tree/main/R +combinatorics: + version: 0.1.0 + title: Introduction to Some Combinatorial Relations + maintainer: Anik Paul + description: 'Determining the value of Stirling numbers of 1st kind and 2nd kind,references: + Bóna,Miklós(2017,ISBN 9789813148840).' + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=combinatorics + url_git: '' +combinedevents: + version: 0.1.1 + title: Calculate Scores and Marks for Track and Field Combined Events + maintainer: Katie Frank + description: |- + Includes functions to calculate scores and marks for track and + field combined events competitions. The functions are based on the scoring + tables for combined events set forth by the International Association of + Athletics Federation (2001). + date_publication: '2021-02-03' + bug_reports: https://github.com/katie-frank/combinedevents/issues + url: https://katie-frank.github.io/combinedevents/ + url_cran: https://CRAN.R-project.org/package=combinedevents + url_git: https://github.com/katie-frank/combinedevents +CombinePortfolio: + version: '0.4' + title: |- + Estimation of Optimal Portfolio Weights by Combining Simple + Portfolio Strategies + maintainer: Florian Ziel + description: Estimation of optimal portfolio weights as combination of simple portfolio + strategies, like the tangency, global minimum variance (GMV) or naive (1/N) portfolio. + It is based on a utility maximizing 8-fund rule. Popular special cases like the + Kan-Zhou(2007) 2-fund and 3-fund rule or the Tu-Zhou(2011) estimator are nested. + date_publication: '2019-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CombinePortfolio + url_git: '' +combinIT: + version: 2.0.0 + title: A Combined Interaction Test for Unreplicated Two-Way Tables + maintainer: Hossein Haghbin + description: 'There are several non-functional-form-based interaction tests for + testing interaction in unreplicated two-way layouts. However, no single test can + detect all patterns of possible interaction and the tests are sensitive to a particular + pattern of interaction. This package combines six non-functional-form-based interaction + tests for testing additivity. These six tests were proposed by Boik (1993) , + Piepho (1994), Kharrati-Kopaei and Sadooghi-Alvandi (2007) , + Franck et al. (2013) , Malik et al. (2016) + and Kharrati-Kopaei and Miller (2016) . The + p-values of these six tests are combined by Bonferroni, Sidak, Jacobi polynomial + expansion, and the Gaussian copula methods to provide researchers with a testing + approach which leverages many existing methods to detect disparate forms of non-additivity. + This package is based on the following published paper: Shenavari and Kharrati-Kopaei + (2018) "A Method for Testing Additivity in Unreplicated Two-Way Layouts Based + on Combining Multiple Interaction Tests". In addition, several sentences in help + files or descriptions were copied from that paper.' + date_publication: '2022-10-21' + bug_reports: https://github.com/haghbinh/combinIT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=combinIT + url_git: https://github.com/haghbinh/combinIT +CombinS: + version: 1.1-1 + title: Construction Methods of some Series of PBIB Designs + maintainer: Mohamed Laib + description: Series of partially balanced incomplete block designs (PBIB) based + on the combinatory method (S) introduced in (Imane Rezgui et al, 2014) ; + and it gives their associated U-type design. + date_publication: '2016-11-23' + bug_reports: '' + url: '''www.sites.google.com/site/mohamedlaibwebpage''' + url_cran: https://CRAN.R-project.org/package=CombinS + url_git: '' +combiroc: + version: 0.3.4 + title: Selection and Ranking of Omics Biomarkers Combinations Made Easy + maintainer: Riccardo L. Rossi + description: Provides functions and a workflow to easily and powerfully calculating + specificity, sensitivity and ROC curves of biomarkers combinations. Allows to + rank and select multi-markers signatures as well as to find the best performing + sub-signatures, now also from single-cell RNA-seq datasets. The method used was + first published as a Shiny app and described in Mazzara et al. (2017) + and further described in Bombaci & Rossi (2019) , + and widely expanded as a package as presented in the bioRxiv pre print Ferrari + et al. . + date_publication: '2023-07-06' + bug_reports: https://github.com/ingmbioinfo/combiroc/issues + url: https://doi.org/10.1101/2022.01.17.476603 + url_cran: https://CRAN.R-project.org/package=combiroc + url_git: https://github.com/ingmbioinfo/combiroc +combiter: + version: 1.0.3 + title: Combinatorics Iterators + maintainer: Kota Mori + description: |- + Provides iterators for combinations, permutations, subsets, and + Cartesian product, which allow one to go through all elements without creating a + huge set of all possible values. + date_publication: '2017-12-04' + bug_reports: https://github.com/kota7/combiter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=combiter + url_git: https://github.com/kota7/combiter +COMBO: + version: 1.2.0 + title: Correcting Misclassified Binary Outcomes in Association Studies + maintainer: Kimberly Hochstedler Webb + description: |- + Use frequentist and Bayesian methods to estimate parameters from a + binary outcome misclassification model. These methods correct for the problem + of "label switching" by assuming that the sum of outcome sensitivity and + specificity is at least 1. A description of the analysis methods is + available in Hochstedler and Wells (2023) . + date_publication: '2024-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COMBO + url_git: '' +comclim: + version: 0.9.6 + title: Community Climate Statistics + maintainer: Benjamin Blonder + description: Computes community climate statistics for volume and mismatch using + species' climate niches either unscaled or scaled relative to a regional species + pool. These statistics can be used to describe biogeographic patterns and infer + community assembly processes. Includes a vignette outlining usage. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=comclim + url_git: '' +cometExactTest: + version: 0.1.5 + title: |- + Exact Test from the Combinations of Mutually Exclusive + Alterations (CoMEt) Algorithm + maintainer: Max Leiserson + description: An algorithm for identifying combinations of mutually exclusive alterations + in cancer genomes. CoMEt represents the mutations in a set M of k genes with a + 2^k dimensional contingency table, and then computes the tail probability of observing + T(M) exclusive alterations using an exact statistical test. + date_publication: '2018-01-29' + bug_reports: '' + url: http://compbio.cs.brown.edu/projects/comet + url_cran: https://CRAN.R-project.org/package=cometExactTest + url_git: '' +cometr: + version: 0.4.0 + title: '''Comet'' API for R' + maintainer: Nimrod Lahav + description: |- + A convenient 'R' wrapper to the 'Comet' API, which is a cloud + platform allowing you to track, compare, explain and optimize machine + learning experiments and models. Experiments can be viewed on the 'Comet' + online dashboard at . + date_publication: '2023-10-19' + bug_reports: https://github.com/comet-ml/cometr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cometr + url_git: https://github.com/comet-ml/cometr +comets: + version: 0.1-1 + title: Covariance Measure Tests for Conditional Independence + maintainer: Lucas Kook + description: |- + Covariance measure tests for conditional independence testing + against conditional covariance and nonlinear conditional mean alternatives. + The package implements versions of the generalised covariance measure test + (Shah and Peters, 2020, ) and projected covariance + measure test (Lundborg et al., 2023, ). The + tram-GCM test, for censored responses, is implemented including the Cox + model and survival forests (Kook et al., 2024, + ). Application examples to variable + significance testing and modality selection can be found in Kook and + Lundborg (2024, ). + date_publication: '2025-01-31' + bug_reports: https://github.com/LucasKook/comets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comets + url_git: https://github.com/LucasKook/comets +comf: + version: 0.1.12 + title: Models and Equations for Human Comfort Research + maintainer: Marcel Schweiker + description: Calculation of various common and less common comfort indices such + as predicted mean vote or the two node model. Converts physical variables such + as relative to absolute humidity and evaluates the performance of comfort indices. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=comf + url_git: '' +comFuncs: + version: 0.0.6 + title: Commonly Used Functions for R Shiny Applications + maintainer: Hanming Tu + description: |- + A set of common functions to be used for displaying messages, checking variables, + finding absolute paths, starting applications, etc. More functions will be added later. + date_publication: '2022-08-27' + bug_reports: https://github.com/TuCai/comFuncs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comFuncs + url_git: https://github.com/TuCai/comFuncs +ComICS: + version: 1.0.4 + title: Computational Methods for Immune Cell-Type Subsets + maintainer: Yael Steuerman + description: Provided are Computational methods for Immune Cell-type Subsets, including:(1) + DCQ (Digital Cell Quantifier) to infer global dynamic changes in immune cell quantities + within a complex tissue; and (2) VoCAL (Variation of Cell-type Abundance Loci) + a deconvolution-based method that utilizes transcriptome data to infer the quantities + of immune-cell types, and then uses these quantitative traits to uncover the underlying + DNA loci. + date_publication: '2018-05-13' + bug_reports: '' + url: http://dcq.tau.ac.il/ + url_cran: https://CRAN.R-project.org/package=ComICS + url_git: '' +CoMiRe: + version: '0.8' + title: Convex Mixture Regression + maintainer: Antonio Canale + description: Posterior inference under the convex mixture regression (CoMiRe) models + introduced by Canale, Durante, and Dunson (2018) . + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoMiRe + url_git: '' +COMIX: + version: 1.0.0 + title: Coarsened Mixtures of Hierarchical Skew Kernels + maintainer: S. Gorsky + description: Bayesian fit of a Dirichlet Process Mixture with hierarchical multivariate + skew normal kernels and coarsened posteriors. For more information, see Gorsky, + Chan and Ma (2020) . + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COMIX + url_git: '' +COMMA: + version: 1.1.1 + title: Correcting Misclassified Mediation Analysis + maintainer: Kimberly Webb + description: |- + Use three methods to estimate parameters from a mediation analysis + with a binary misclassified mediator. These methods correct for the problem + of "label switching" using Youden's J criteria. A detailed description of the + analysis methods is available in Webb and Wells (2024), "Effect estimation in + the presence of a misclassified binary mediator" . + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COMMA + url_git: '' +commafree: + version: 0.2.0 + title: Call Functions Without Commas Between Arguments + maintainer: Tomasz Kalinowski + description: |- + Provides the "comma-free call" operator: '%(%'. Use it to call a + function without commas between the arguments. Just replace the '(' + with '%(%' in a function call, supply your arguments as standard R + expressions enclosed by '{ }', and be free of commas (for that call). + date_publication: '2024-04-19' + bug_reports: https://github.com/t-kalinowski/commafree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=commafree + url_git: https://github.com/t-kalinowski/commafree +CommEcol: + version: 1.8.1 + title: Community Ecology Analyses + maintainer: Adriano Sanches Melo + description: Autosimilarity curves, standardization of spatial extent, dissimilarity + indexes that overweight rare species, phylogenetic and functional (pairwise and + multisample) dissimilarity indexes and nestedness for phylogenetic, functional + and other diversity metrics. The methods for phylogenetic and functional nestedness + is described in Melo, Cianciaruso and Almeida-Neto (2014) . + This should be a complement to available packages, particularly 'vegan'. + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CommEcol + url_git: '' +CommKern: + version: 1.0.1 + title: Network-Based Communities and Kernel Machine Methods + maintainer: Alexandria Jensen + description: Analysis of network community objects with applications to neuroimaging + data. There are two main components to this package. The first is the hierarchical + multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm + specifically tailored to the unique issues within brain connectivity. The other + is a suite of semiparametric kernel machine methods that allow for statistical + inference to be performed to test for potential associations between these community + structures and an outcome of interest (binary or continuous). + date_publication: '2022-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CommKern + url_git: https://github.com/aljensen89/CommKern +common: + version: 1.1.3 + title: Solutions for Common Problems in Base R + maintainer: David Bosak + description: |- + Contains functions for solving commonly encountered problems while + programming in R. This package is intended to provide a lightweight + supplement to Base R, and will be useful for almost any R user. + date_publication: '2024-04-05' + bug_reports: https://github.com/dbosak01/common/issues + url: https://common.r-sassy.org + url_cran: https://CRAN.R-project.org/package=common + url_git: https://github.com/dbosak01/common +CommonDataModel: + version: 1.0.1 + title: OMOP CDM DDL and Documentation Generator + maintainer: Clair Blacketer + description: Generates the scripts required to create an Observational Medical Outcomes + Partnership (OMOP) Common Data Model (CDM) database and associated documentation + for supported database platforms. Leverages the 'SqlRender' package to convert + the Data Definition Language (DDL) script written in parameterized Structured + Query Language (SQL) to the other supported dialects. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CommonDataModel + url_git: '' +CommonJavaJars: + version: 1.1-0 + title: Useful Libraries for Building a Java Based GUI under R + maintainer: Kornelius Rohmeyer + description: Useful libraries for building a Java based GUI under R are provided. + date_publication: '2024-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CommonJavaJars + url_git: http://gsrmtp.r-forge.r-project.org/ +commonmark: + version: 1.9.2 + title: High Performance CommonMark and Github Markdown Rendering in R + maintainer: Jeroen Ooms + description: |- + The CommonMark specification defines + a rationalized version of markdown syntax. This package uses the 'cmark' + reference implementation for converting markdown text into various formats + including html, latex and groff man. In addition it exposes the markdown + parse tree in xml format. Also includes opt-in support for GFM extensions + including tables, autolinks, and strikethrough text. + date_publication: '2024-10-04' + bug_reports: https://github.com/r-lib/commonmark/issues + url: https://docs.ropensci.org/commonmark/https://ropensci.r-universe.dev/commonmark + url_cran: https://CRAN.R-project.org/package=commonmark + url_git: '' +CommonMean.Copula: + version: 1.0.4 + title: Common Mean Vector under Copula Models + maintainer: Jia-Han Shih + description: Estimate bivariate common mean vector under copula models with known + correlation. In the current version, available copulas are the Clayton, Gumbel, + Frank, Farlie-Gumbel-Morgenstern (FGM), and normal copulas. See Shih et al. (2019) + and Shih et al. (2021) for + details under the FGM and general copulas, respectively. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CommonMean.Copula + url_git: '' +commonsMath: + version: 1.2.8 + title: JAR Files of the Apache Commons Mathematics Library + maintainer: David B. Dahl + description: '''Java'' JAR files for the Apache Commons Mathematics Library for + use by users and other packages.' + date_publication: '2023-08-17' + bug_reports: https://github.com/dbdahl/commonsMath/issues + url: '' + url_cran: https://CRAN.R-project.org/package=commonsMath + url_git: https://github.com/dbdahl/commonsMath +communication: + version: '0.1' + title: |- + Feature Extraction and Model Estimation for Audio of Human + Speech + maintainer: Christopher Lucas + description: |- + Provides fast, easy feature extraction of human speech and model estimation + with hidden Markov models. Flexible extraction of phonetic features and their + derivatives, with necessary preprocessing options like feature standardization. + Communication can estimate supervised and unsupervised hidden Markov models with + these features, with cross validation and corrections for auto-correlation in + features. Methods developed in Knox and Lucas (2021) . + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=communication + url_git: '' +comorbidity: + version: 1.1.0 + title: Computing Comorbidity Scores + maintainer: Alessandro Gasparini + description: |- + Computing comorbidity indices and scores such as the weighted Charlson + score (Charlson, 1987 ) and the Elixhauser + comorbidity score (Elixhauser, 1998 ) + using ICD-9-CM or ICD-10 codes (Quan, 2005 ). + Australian and Swedish modifications of the Charlson Comorbidity Index are available + as well (Sundararajan, 2004 and Ludvigsson, 2021 + ), together with different weighting algorithms for both + the Charlson and Elixhauser comorbidity scores. + date_publication: '2024-07-16' + bug_reports: https://github.com/ellessenne/comorbidity/issues + url: https://ellessenne.github.io/comorbidity/ + url_cran: https://CRAN.R-project.org/package=comorbidity + url_git: https://github.com/ellessenne/comorbidity +comorbidPGS: + version: 0.3.4 + title: |- + Assessing Predisposition Between Phenotypes using Polygenic + Scores + maintainer: Vincent Pascat + description: |- + Using polygenic scores (PGS, or PRS/GRS for binary outcomes), + this package allows to investigate shared predisposition between different + conditions, and do fast association analysis, export plots and views + of the PGS distribution using 'ggplot2' object. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=comorbidPGS + url_git: '' +comorosmaps: + version: 1.0.0 + title: Comoro Islands Maps + maintainer: Housni Hassani + description: Maps of Comoro Islands. Layers include the country coastline, each + island coastline and administrative regions boundaries. + date_publication: '2022-06-06' + bug_reports: https://github.com/hhousni/comorosmaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comorosmaps + url_git: https://github.com/hhousni/comorosmaps +Comp2ROC: + version: 1.1.4 + title: Compare Two ROC Curves that Intersect + maintainer: Ana C. Braga + description: Comparison of two ROC curves through the methodology proposed by Ana + C. Braga. + date_publication: '2016-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Comp2ROC + url_git: '' +comparator: + version: 0.1.2 + title: Comparison Functions for Clustering and Record Linkage + maintainer: Neil Marchant + description: |- + Implements functions for comparing strings, sequences and + numeric vectors for clustering and record linkage applications. + Supported comparison functions include: generalized edit distances + for comparing sequences/strings, Monge-Elkan similarity for fuzzy + comparison of token sets, and L-p distances for comparing numeric + vectors. Where possible, comparison functions are implemented in + C/C++ to ensure good performance. + date_publication: '2022-03-16' + bug_reports: https://github.com/ngmarchant/comparator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comparator + url_git: https://github.com/ngmarchant/comparator +compare: + version: 0.2-6 + title: Comparing Objects for Differences + maintainer: Paul Murrell + description: |- + Functions to compare a model object to a comparison object. + If the objects are not identical, the functions can be instructed to + explore various modifications of the objects (e.g., sorting rows, + dropping names) to see if the modified versions are identical. + date_publication: '2015-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=compare + url_git: '' +compareC: + version: 1.3.2 + title: |- + Compare Two Correlated C Indices with Right-Censored Survival + Outcome + maintainer: Le Kang + description: Proposed by Harrell, the C index or concordance C, is considered an + overall measure of discrimination in survival analysis between a survival outcome + that is possibly right censored and a predictive-score variable, which can represent + a measured biomarker or a composite-score output from an algorithm that combines + multiple biomarkers. This package aims to statistically compare two C indices + with right-censored survival outcome, which commonly arise from a paired design + and thus resulting two correlated C indices. + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=compareC + url_git: '' +CompareCausalNetworks: + version: 0.2.6.2 + title: Interface to Diverse Estimation Methods of Causal Networks + maintainer: Christina Heinze-Deml + description: |- + Unified interface for the estimation of causal networks, including + the methods 'backShift' (from package 'backShift'), 'bivariateANM' (bivariate + additive noise model), 'bivariateCAM' (bivariate causal additive model), + 'CAM' (causal additive model) (from package 'CAM'; the package is + temporarily unavailable on the CRAN repository; formerly available versions + can be obtained from the archive), 'hiddenICP' (invariant + causal prediction with hidden variables), 'ICP' (invariant causal prediction) + (from package 'InvariantCausalPrediction'), 'GES' (greedy equivalence + search), 'GIES' (greedy interventional equivalence search), 'LINGAM', 'PC' (PC + Algorithm), 'FCI' (fast causal inference), + 'RFCI' (really fast causal inference) (all from package 'pcalg') and + regression. + date_publication: '2020-02-17' + bug_reports: https://github.com/christinaheinze/CompareCausalNetworks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CompareCausalNetworks + url_git: https://github.com/christinaheinze/CompareCausalNetworks +CompAREdesign: + version: 2.3.1 + title: |- + Statistical Functions for the Design of Studies with Composite + Endpoints + maintainer: Marta Bofill Roig + description: It has been designed to calculate the required sample size in randomized + clinical trials with composite endpoints. It also calculates the expected effect + and the probability of observing the composite endpoint, among others. The methodology + can be found in Bofill & Gómez (2019) and Gómez & Lagakos + (2013) . + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompAREdesign + url_git: '' +compareDF: + version: 2.3.5 + title: |- + Do a Git Style Diff of the Rows Between Two Dataframes with + Similar Structure + maintainer: Alex Joseph + description: |- + Compares two dataframes which have the same column + structure to show the rows that have changed. Also gives a git style diff format + to quickly see what has changed in addition to summary statistics. + date_publication: '2022-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=compareDF + url_git: '' +compareGroups: + version: 4.9.1 + title: Descriptive Analysis by Groups + maintainer: Isaac Subirana + description: Create data summaries for quality control, extensive reports for exploring + data, as well as publication-ready univariate or bivariate tables in several formats + (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise + the distribution of your data (boxplots, barplots, normality-plots, etc.). Display + statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate + tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending + on the nature of the described variable (normal, non-normal or qualitative). Summarize + genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies + and performing Hardy-Weinberg Equilibrium tests among other typical statistics + and tests for these kind of data. + date_publication: '2024-10-30' + bug_reports: '' + url: https://isubirana.github.io/compareGroups/index.html + url_cran: https://CRAN.R-project.org/package=compareGroups + url_git: '' +compareMCMCs: + version: 0.6.0 + title: Compare MCMC Efficiency from 'nimble' and/or Other MCMC Engines + maintainer: Perry de Valpine + description: Manages comparison of MCMC performance metrics from multiple MCMC algorithms. + These may come from different MCMC configurations using the 'nimble' package or + from other packages. Plug-ins for JAGS via 'rjags' and Stan via 'rstan' are provided. + It is possible to write plug-ins for other packages. Performance metrics are held + in an MCMCresult class along with samples and timing data. It is easy to apply + new performance metrics. Reports are generated as html pages with figures comparing + sets of runs. It is possible to configure the html pages, including providing + new figure components. + date_publication: '2024-10-01' + bug_reports: https://github.com/nimble-dev/compareMCMCs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=compareMCMCs + url_git: https://github.com/nimble-dev/compareMCMCs +CompareMultipleModels: + version: 0.1.0 + title: Finding the Best Model Using Eight Metrics Values + maintainer: Mr. Sandip Garai + description: 'In statistical modeling, multiple models need to be compared based + on certain criteria. The method described here uses eight metrics from ''AllMetrics'' + package. ‘input_df’ is the data frame (at least two columns for comparison) containing + metrics values in different rows of a column (which denotes a particular model’s + performance). First five metrics are expected to be minimum and last three metrics + are expected to be maximum for a model to be considered good. Firstly, every metric + value (among first five) is searched in every columns and minimum values are denoted + as ‘MIN’ and other values are denoted as ‘NA’. Secondly, every metric (among last + three) is searched in every columns and maximum values are denoted as ‘MAX’ and + other values are denoted as ‘NA’. ‘output_df’ contains the similar number of rows + (which is 8) and columns (which is number of models to be compared) as of ‘input_df’. + Values in ‘output_df’ are corresponding ‘NA’, ‘MIN’ or ‘MAX’. Finally, the column + containing minimum number of ‘NA’ values is denoted as the best column. ‘min_NA_col’ + gives the name of the best column (model). ‘min_NA_values’ are the corresponding + metrics values. ‘BestColumn_metrics’ is the data frame (dimension: 1*8) containing + different metrics of the best column (model). ‘best_column_results’ is the final + result (a list) containing all of these output elements. In special case, if two + columns having equal ''NA'', it will be checked among these two column which one + is having least ''NA'' in first five rows and will be inferred as the best. More + details about ''AllMetrics'' can be found in Garai (2023) .' + date_publication: '2023-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompareMultipleModels + url_git: '' +comparer: + version: 0.2.4 + title: Compare Output and Run Time + maintainer: Collin Erickson + description: |- + Quickly run experiments to compare the run time and output of + code blocks. The function mbc() can make fast comparisons of code, + and will calculate statistics comparing the resulting outputs. + It can be used to compare model fits to the same data or + see which function runs faster. + The R6 class ffexp$new() runs a function using all possible combinations + of selected inputs. This is useful for comparing the effect of + different parameter values. It can also run in parallel and + automatically save intermediate results, which is very useful + for long computations. + date_publication: '2024-10-02' + bug_reports: https://github.com/CollinErickson/comparer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comparer + url_git: https://github.com/CollinErickson/comparer +CompareTests: + version: '1.3' + title: Correct for Verification Bias in Diagnostic Accuracy & Agreement + maintainer: Hormuzd Katki + description: 'A standard test is observed on all specimens. We treat the second + test (or sampled test) as being conducted on only a stratified sample of specimens. Verification + Bias is this situation when the specimens for doing the second (sampled) test + is not under investigator control. We treat the total sample as stratified two-phase + sampling and use inverse probability weighting. We estimate diagnostic accuracy + (category-specific classification probabilities; for binary tests reduces to specificity + and sensitivity, and also predictive values) and agreement statistics (percent + agreement, percent agreement by category, Kappa (unweighted), Kappa (quadratic + weighted) and symmetry tests (reduces to McNemar''s test for binary tests)). See: + Katki HA, Li Y, Edelstein DW, Castle PE. Estimating the agreement and diagnostic + accuracy of two diagnostic tests when one test is conducted on only a subsample + of specimens. Stat Med. 2012 Feb 28; 31(5) .' + date_publication: '2024-12-12' + bug_reports: '' + url: https://dceg.cancer.gov/about/staff-directory/katki-hormuzd + url_cran: https://CRAN.R-project.org/package=CompareTests + url_git: '' +comparison: + version: 1.0.8 + title: Multivariate Likelihood Ratio Calculation and Evaluation + maintainer: James Curran + description: Functions for calculating and evaluating likelihood ratios from uni/multivariate + continuous observations. + date_publication: '2023-08-25' + bug_reports: https://github.com/jmcurran/comparison/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comparison + url_git: https://github.com/jmcurran/comparison +ComparisonSurv: + version: 1.1.1 + title: Comparison of Survival Curves Between Two Groups + maintainer: Zheng Chen + description: Various statistical methods for survival analysis in comparing survival + curves between two groups, including overall hypothesis tests described in Li + et al. (2015) and Huang et al. (2020) , + fixed-point tests in Klein et al. (2007) , short-term tests, + and long-term tests in Logan et al. (2008) . + Some commonly used descriptive statistics and plots are also included. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ComparisonSurv + url_git: '' +compas: + version: 0.1.1 + title: Conformational Manipulations of Protein Atomic Structures + maintainer: Samuel W.K. Wong + description: Manipulate and analyze 3-D structural geometry of Protein Data Bank + (PDB) files. + date_publication: '2022-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=compas + url_git: '' +compdb: + version: 0.0.1 + title: Generate Compilation Database for Use with 'Clang' Tools + maintainer: Felix Held + description: |- + Many modern C/C++ development tools in the 'clang' toolchain, + such as 'clang-tidy' or 'clangd', rely on the presence of a compilation database + in JSON format . + This package temporarily injects additional build flags into the R build + process to generate such a compilation database. + date_publication: '2025-01-31' + bug_reports: https://github.com/cyianor/r-compdb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=compdb + url_git: https://github.com/cyianor/r-compdb +CompDist: + version: '1.0' + title: Multisection Composite Distributions + maintainer: Saralees Nadarajah + description: 'Computes density function, cumulative distribution function, quantile + function and random numbers for a multisection composite distribution specified + by the user. Also fits the user specified distribution to a given data set. More + details of the package can be found in the following paper submitted to the R + journal Wiegand M and Nadarajah S (2017) CompDist: Multisection composite distributions.' + date_publication: '2017-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompDist + url_git: '' +comperank: + version: 0.1.1 + title: Ranking Methods for Competition Results + maintainer: Evgeni Chasnovski + description: |- + Compute ranking and rating based on competition + results. Methods of different nature are implemented: with fixed + Head-to-Head structure, with variable Head-to-Head structure and with + iterative nature. All algorithms are taken from the book 'Who’s #1?: + The science of rating and ranking' by Amy N. Langville and Carl D. + Meyer (2012, ISBN:978-0-691-15422-0). + date_publication: '2020-03-03' + bug_reports: https://github.com/echasnovski/comperank/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comperank + url_git: https://github.com/echasnovski/comperank +comperes: + version: 0.2.7 + title: Manage Competition Results + maintainer: Evgeni Chasnovski + description: |- + Tools for storing and managing competition results. + Competition is understood as a set of games in which players gain some + abstract scores. There are two ways for storing results: in long (one + row per game-player) and wide (one row per game with fixed amount of + players) formats. This package provides functions for creation and + conversion between them. Also there are functions for computing their + summary and Head-to-Head values for players. They leverage grammar of + data manipulation from 'dplyr'. + date_publication: '2023-02-28' + bug_reports: https://github.com/echasnovski/comperes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comperes + url_git: https://github.com/echasnovski/comperes +competitiontoolbox: + version: 0.7.1 + title: A Graphical User Interface for Antitrust and Trade Practitioners + maintainer: Charles Taragin + description: |- + A graphical user interface for simulating the effects of mergers, tariffs, and quotas under an + assortment of different economic models. The interface is powered by the 'Shiny' web application framework from + 'RStudio'. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=competitiontoolbox + url_git: https://github.com/luciu5/competitiontoolbox +CompExpDes: + version: 1.0.6 + title: Computer Experiment Designs + maintainer: Ashutosh Dalal + description: In computer experiments space-filling designs are having great impact. + Most popularly used space-filling designs are Uniform designs (UDs), Latin hypercube + designs (LHDs) etc. For further references one can see Mckay (1979) + and Fang (1980) . In this package, + we have provided algorithms for generate efficient LHDs and UDs. Here, generated + LHDs are efficient as they possess lower value of Maxpro measure, Phi_p value + and Maximum Absolute Correlation (MAC) value based on the weightage given to each + criterion. On the other hand, the produced UDs are having good space-filling property + as they always attain the lower bound of Discrete Discrepancy measure. Further, + some useful functions added in this package for adding more value to this package. + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompExpDes + url_git: '' +CompGR: + version: 0.1.3 + title: Complete Annual Growth Rate Generator + maintainer: Ashis Ranjan Udgata + description: It is designed to streamline the process of calculating complete annual + growth rates with user-friendly functions and robust algorithms. It enables researchers + and analysts to effortlessly generate precise growth rate estimates for their + data. For method details see, Sharma, M.K.(2013) . + It offers a comprehensive suite of functions and customisable parameters. Equipped + to handle varying complexities in data structures. It empowers users to uncover + insightful growth dynamics and make informed decisions. + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompGR + url_git: '' +Compind: + version: '3.2' + title: Composite Indicators Functions + maintainer: Francesco Vidoli + description: 'A collection of functions to calculate Composite Indicators methods, + focusing, in particular, on the normalisation and weighting-aggregation steps, + as described in OECD Handbook on constructing composite indicators: methodology + and user guide, 2008, ''Vidoli'' and ''Fusco'' and ''Mazziotta'' , + ''Mazziotta'' and ''Pareto'' (2016) , ''Van Puyenbroeck + and ''Rogge'' and other authors.' + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Compind + url_git: '' +compindexR: + version: 0.1.3 + title: Calculates Composite Index + maintainer: Olgun Aydin + description: It uses the first-order sensitivity index to measure whether the weights + assigned by the creator of the composite indicator match the actual importance + of the variables. Moreover, the variance inflation factor is used to reduce the + set of correlated variables. In the case of a discrepancy between the importance + and the assigned weight, the script determines weights that allow adjustment of + the weights to the intended impact of variables. If the optimised weights are + unable to reflect the desired importance, the highly correlated variables are + reduced, taking into account variance inflation factor. The final outcome of the + script is the calculated value of the composite indicator based on optimal weights + and a reduced set of variables, and the linear ordering of the analysed objects. + date_publication: '2023-11-26' + bug_reports: https://github.com/olgnaydn/compindexR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=compindexR + url_git: https://github.com/olgnaydn/compindexR +compindPCA: + version: 0.1.0 + title: |- + Computation of Relative Weights of Variables and Composite Index + Values Based on PCA + maintainer: Rajeev Ranjan Kumar + description: It helps in development of a principal component analysis based composite + index by assigning weights to variables and combining the weighted variables. + For method details see Sendhil, R., Jha, A., Kumar, A. and Singh, S. (2018). , + and Wu, T. (2021). . + date_publication: '2023-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=compindPCA + url_git: '' +completejourney: + version: 1.1.0 + title: Retail Shopping Data + maintainer: Brad Boehmke + description: |- + Retail shopping transactions for 2,469 households over one year. + Originates from the 84.51° Complete Journey 2.0 source files + which also includes useful metadata on + products, coupons, campaigns, and promotions. + date_publication: '2019-09-28' + bug_reports: https://github.com/bradleyboehmke/completejourney/issues + url: '' + url_cran: https://CRAN.R-project.org/package=completejourney + url_git: https://github.com/bradleyboehmke/completejourney +complexity: + version: 1.1.2 + title: |- + Calculate the Proportion of Permutations in Line with an + Informative Hypothesis + maintainer: M. A. J. Zondervan-Zwijnenburg + description: 'Allows for the easy computation of complexity: the proportion of the + parameter space in line with the hypothesis by chance. The package comes with + a Shiny application in which the calculations can be conducted as well.' + date_publication: '2022-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=complexity + url_git: '' +complexlm: + version: 1.1.2 + title: Linear Fitting for Complex Valued Data + maintainer: William Ryan + description: Tools for linear fitting with complex variables. Includes ordinary + least-squares (zlm()) and robust M-estimation (rzlm()), and complex methods for + oft used generics. Originally adapted from the rlm() functions of 'MASS' and the + lm() functions of 'stats'. + date_publication: '2024-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=complexlm + url_git: https://github.com/QuantumOfMoose/complexlm +complexNet: + version: 0.2.0 + title: Complex Network Generation + maintainer: Marco Smolla + description: |- + Providing a set of functions to easily generate and iterate complex networks. + The functions can be used to generate realistic networks with a wide range of different clustering, density, and average path length. + For more information consult research articles by Amiyaal Ilany and Erol Akcay (2016) and Ilany and Erol Akcay (2016) , which have inspired many methods in this package. + date_publication: '2022-11-10' + bug_reports: https://github.com/marcosmolla/complexNet/issues + url: https://marcosmolla.github.io/complexNet/ + url_cran: https://CRAN.R-project.org/package=complexNet + url_git: https://github.com/marcosmolla/complexNet +complexplus: + version: '2.1' + title: Functions of Complex or Real Variable + maintainer: Albert Dorador + description: Extension of several functions to the complex domain, including the + matrix exponential and logarithm, and the determinant. + date_publication: '2017-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=complexplus + url_git: '' +ComplexUpset: + version: 1.3.3 + title: Create Complex UpSet Plots Using 'ggplot2' Components + maintainer: Michał Krassowski + description: |- + UpSet plots are an improvement over Venn Diagram for set overlap visualizations. + Striving to bring the best of the 'UpSetR' and 'ggplot2', this package offers a way to create + complex overlap visualisations, using simple and familiar tools, i.e. geoms of 'ggplot2'. + For introduction to UpSet concept, see Lex et al. (2014) . + date_publication: '2021-12-11' + bug_reports: https://github.com/krassowski/complex-upset/issues + url: https://krassowski.github.io/complex-upset/ + url_cran: https://CRAN.R-project.org/package=ComplexUpset + url_git: https://github.com/krassowski/complex-upset +complmrob: + version: 0.7.0 + title: Robust Linear Regression with Compositional Data as Covariates + maintainer: David Kepplinger + description: |- + Robust regression methods for compositional data. + The distribution of the estimates can be approximated with various bootstrap + methods. These bootstrap methods are available for the compositional as well + as for standard robust regression estimates. This allows for direct + comparison between them. + date_publication: '2019-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=complmrob + url_git: https://github.com/dakep/complmrob +CompMix: + version: 0.1.0 + title: |- + A Comprehensive Toolkit for Environmental Mixtures Analysis + ('CompMix') + maintainer: Wei Hao + description: 'Quantitative characterization of the health impacts associated with + exposure to chemical mixtures has received considerable attention in current environmental + and epidemiological studies. ''CompMix'' package allows practitioners to estimate + the health impacts from exposure to chemical mixtures data through various statistical + approaches, including Lasso, Elastic net, Bayeisan kernel machine regression (BKMR), + hierNet, Quantile g-computation, Weighted quantile sum (WQS) and Random forest. + Hao W, Cathey A, Aung M, Boss J, Meeker J, Mukherjee B. (2024) "Statistical methods + for chemical mixtures: a practitioners guide". .' + date_publication: '2024-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompMix + url_git: '' +CompModels: + version: 0.3.0 + title: Pseudo Computer Models for Optimization + maintainer: Tony Pourmohamad + description: A suite of computer model test functions that can be used to test and + evaluate algorithms for Bayesian (also known as sequential) optimization. Some + of the functions have known functional forms, however, most are intended to serve + as black-box functions where evaluation requires running computer code that reveals + little about the functional forms of the objective and/or constraints. The primary + goal of the package is to provide users (especially those who do not have access + to real computer models) a source of reproducible and shareable examples that + can be used for benchmarking algorithms. The package is a living repository, and + so more functions will be added over time. For function suggestions, please do + contact the author of the package. + date_publication: '2022-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompModels + url_git: '' +COMPoissonReg: + version: 0.8.1 + title: Conway-Maxwell Poisson (COM-Poisson) Regression + maintainer: Andrew Raim + description: |- + Fit Conway-Maxwell Poisson (COM-Poisson or CMP) regression models + to count data (Sellers & Shmueli, 2010) . The + package provides functions for model estimation, dispersion testing, and + diagnostics. Zero-inflated CMP regression (Sellers & Raim, 2016) + is also supported. + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COMPoissonReg + url_git: https://github.com/lotze/COMPoissonReg +CompositeReliability: + version: 1.0.3 + title: |- + Determine the Composite Reliability of a Naturalistic, + Unbalanced Dataset + maintainer: Joyce Moonen - van Loon + description: The reliability of assessment tools is a crucial aspect of monitoring + student performance in various educational settings. It ensures that the assessment + outcomes accurately reflect a student's true level of performance. However, when + assessments are combined, determining composite reliability can be challenging, + especially for naturalistic and unbalanced datasets. This package provides an + easy-to-use solution for calculating composite reliability for different assessment + types. It allows for the inclusion of weight per assessment type and produces + extensive G- and D-study results with graphical interpretations. Overall, our + approach enhances the reliability of composite assessments, making it suitable + for various education contexts. + date_publication: '2023-08-21' + bug_reports: https://github.com/jmoonen/CompositeReliability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CompositeReliability + url_git: https://github.com/jmoonen/CompositeReliability +compositeReliabilityInNestedDesigns: + version: 1.0.4 + title: |- + Optimizing the Composite Reliability in Multivariate Nested + Designs + maintainer: Joyce Moonen - van Loon + description: The reliability of assessment tools is a crucial aspect of monitoring + student performance in various educational settings. It ensures that the assessment + outcomes accurately reflect a student's true level of performance. However, when + assessments are combined, determining composite reliability can be challenging, + especially for naturalistic and unbalanced datasets in nested design as is often + the case for Workplace-Based Assessments. This package is designed to estimate + composite reliability in nested designs using multivariate generalizability theory + and enhance the analysis of assessment data. The package allows for the inclusion + of weight per assessment type and produces extensive G- and D-study results with + graphical interpretations, and options to find the set of weights that maximizes + the composite reliability or minimizes the standard error of measurement (SEM). + date_publication: '2024-09-21' + bug_reports: https://github.com/jmoonen/compositeReliabilityInNestedDesigns/issues + url: '' + url_cran: https://CRAN.R-project.org/package=compositeReliabilityInNestedDesigns + url_git: https://github.com/jmoonen/compositeReliabilityInNestedDesigns +Compositional: + version: '7.3' + title: Compositional Data Analysis + maintainer: Michail Tsagris + description: |- + Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. We further include functions for percentages (or proportions). + The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include: + a) Tsagris M.T., Preston S. and Wood A.T.A. (2011). "A data-based power transformation for compositional data". Fourth International International Workshop on Compositional Data Analysis. + b) Tsagris M. (2014). "The k-NN algorithm for compositional data: a revised approach with and without zero values present". Journal of Data Science, 12(3): 519--534. . + c) Tsagris M. (2015). "A novel, divergence based, regression for compositional data". Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. . + d) Tsagris M. (2015). "Regression analysis with compositional data containing zero values". Chilean Journal of Statistics, 6(2): 47--57. . + e) Tsagris M., Preston S. and Wood A.T.A. (2016). "Improved supervised classification for compositional data using the alpha-transformation". Journal of Classification, 33(2): 243--261. . + f) Tsagris M., Preston S. and Wood A.T.A. (2017). "Nonparametric hypothesis testing for equality of means on the simplex". Journal of Statistical Computation and Simulation, 87(2): 406--422. . + g) Tsagris M. and Stewart C. (2018). "A Dirichlet regression model for compositional data with zeros". Lobachevskii Journal of Mathematics, 39(3): 398--412. . + h) Alenazi A. (2019). "Regression for compositional data with compositional data as predictor variables with or without zero values". Journal of Data Science, 17(1): 219--238. . + i) Tsagris M. and Stewart C. (2020). "A folded model for compositional data analysis". Australian and New Zealand Journal of Statistics, 62(2): 249--277. . + j) Alenazi A.A. (2022). "f-divergence regression models for compositional data". Pakistan Journal of Statistics and Operation Research, 18(4): 867--882. . + k) Tsagris M. and Stewart C. (2022). "A Review of Flexible Transformations for Modeling Compositional Data". In Advances and Innovations in Statistics and Data Science, pp. 225--234. . + l) Alenazi A. (2023). "A review of compositional data analysis and recent advances". Communications in Statistics--Theory and Methods, 52(16): 5535--5567. . + m) Tsagris M., Alenazi A. and Stewart C. (2023). "Flexible non-parametric regression models for compositional response data with zeros". Statistics and Computing, 33(106). . + n) Tsagris. M. (2025). "Constrained least squares simplicial-simplicial regression". Statistics and Computing, 35(27). . + o) Sevinc V. and Tsagris. M. (2024). "Energy Based Equality of Distributions Testing for Compositional Data". . + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Compositional + url_git: '' +CompositionalML: + version: '1.0' + title: Machine Learning with Compositional Data + maintainer: Michail Tsagris + description: 'Machine learning algorithms for predictor variables that are compositional + data and the response variable is either continuous or categorical. Specifically, + the Boruta variable selection algorithm, random forest, support vector machines + and projection pursuit regression are included. Relevant papers include: Tsagris + M.T., Preston S. and Wood A.T.A. (2011). "A data-based power transformation for + compositional data". Fourth International International Workshop on Compositional + Data Analysis. and Alenazi, A. (2023). "A review + of compositional data analysis and recent advances". Communications in Statistics--Theory + and Methods, 52(16): 5535--5567. .' + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompositionalML + url_git: '' +CompositionalRF: + version: '1.0' + title: Multivariate Random Forest with Compositional Responses + maintainer: Michail Tsagris + description: Non linear regression with compositional responses and Euclidean predictors + is performed. The compositional data are first transformed using the additive + log-ratio transformation, and then the multivariate random forest of Rahman R., + Otridge J. and Pal R. (2017), , is applied. + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompositionalRF + url_git: '' +compositions: + version: 2.0-8 + title: Compositional Data Analysis + maintainer: K. Gerald van den Boogaart + description: |- + Provides functions for the consistent analysis of compositional + data (e.g. portions of substances) and positive numbers (e.g. concentrations) + in the way proposed by J. Aitchison and V. Pawlowsky-Glahn. + date_publication: '2024-01-31' + bug_reports: '' + url: http://www.stat.boogaart.de/compositions/ + url_cran: https://CRAN.R-project.org/package=compositions + url_git: '' +compound.Cox: + version: '3.32' + title: |- + Univariate Feature Selection and Compound Covariate for + Predicting Survival, Including Copula-Based Analyses for + Dependent Censoring + maintainer: Takeshi Emura + description: |- + Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). + Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) , + statistical methods in Emura et al (2012 PLoS ONE) , + Emura & Chen (2016 Stat Methods Med Res) , and Emura et al (2019). + Algorithms for generating correlated gene expressions are also available. + Estimation of survival functions via copula-graphic (CG) estimators is also implemented, which is useful for + sensitivity analyses under dependent censoring (Yeh et al 2023 Biomedicines) and + factorial survival analyses (Emura et al 2024 Stat Methods Med Res) . + date_publication: '2025-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=compound.Cox + url_git: '' +CompoundEvents: + version: 0.3.0 + title: Statistical Modeling of Compound Events + maintainer: Zengchao Hao + description: Tools for extracting occurrences, assessing potential driving factors, + predicting occurrences, and quantifying impacts of compound events in hydrology + and climatology. Please see Hao Zengchao et al. (2019) . + date_publication: '2024-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompoundEvents + url_git: '' +CompPareto: + version: 0.1.0 + title: Discrete Composite Distributions with Pareto Tails + maintainer: Bowen Liu + description: Contains the probability density function, cumulative distribution + function, quantile function, and random number generator for composite and discrete + composite distributions with Pareto tails. The detailed description of the methods + and the applications of the methods can be found in Bowen Liu, Malwane M.A. Ananda + (2023) . + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompPareto + url_git: '' +CompQuadForm: + version: 1.4.3 + title: Distribution Function of Quadratic Forms in Normal Variables + maintainer: P. Lafaye de Micheaux + description: Computes the distribution function of quadratic forms in normal variables + using Imhof's method, Davies's algorithm, Farebrother's algorithm or Liu et al.'s + algorithm. + date_publication: '2017-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompQuadForm + url_git: '' +CompR: + version: '1.0' + title: Paired Comparison Data Analysis + maintainer: Michel Semenou + description: Different tools for describing and analysing paired comparison data + are presented. Main methods are estimation of products scores according Bradley + Terry Luce model. A segmentation of the individual could be conducted on the basis + of a mixture distribution approach. The number of classes can be tested by the + use of Monte Carlo simulations. This package deals also with multi-criteria paired + comparison data. + date_publication: '2015-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CompR + url_git: '' +comprehenr: + version: 0.6.10 + title: List Comprehensions + maintainer: Gregory Demin + description: |- + Provides 'Python'-style list comprehensions. + List comprehension expressions use usual loops (for(), while() and repeat()) and + usual if() as list producers. In many cases it gives more concise notation than + standard "*apply + filter" strategy. + date_publication: '2021-01-31' + bug_reports: https://github.com/gdemin/comprehenr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comprehenr + url_git: https://github.com/gdemin/comprehenr +compute.es: + version: 0.2-5 + title: Compute Effect Sizes + maintainer: AC Del Re + description: |- + Several functions are available for calculating the most + widely used effect sizes (ES), along with their variances, confidence + intervals and p-values. The output includes ES's of d (mean difference), g + (unbiased estimate of d), r (correlation coefficient), z' (Fisher's z), and + OR (odds ratio and log odds ratio). In addition, NNT (number needed to + treat), U3, CLES (Common Language Effect Size) and Cliff's Delta are + computed. This package uses recommended formulas as described in The + Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & + Valentine, 2009). + date_publication: '2020-04-01' + bug_reports: '' + url: http://acdelre.com + url_cran: https://CRAN.R-project.org/package=compute.es + url_git: '' +ComradesM: + version: 0.1.1 + title: The Comrades Marathon 1921 to 2019 + maintainer: Antony Unwin + description: Datasets related to the Comrades Marathon used in the book Antony + Unwin (2024, ISBN:978-0367674007) "Getting (more out of) Graphics". The main dataset + contains the times of every runner that finished in the time limit for each year + the race was run. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ComradesM + url_git: '' +ComRiskModel: + version: 0.2.0 + title: Fitting of Complementary Risk Models + maintainer: Muhammad Imran + description: |- + Evaluates the probability density function (PDF), cumulative distribution function (CDF), quantile function (QF), random numbers and maximum likelihood estimates (MLEs) of well-known complementary binomial-G, complementary negative binomial-G and complementary geometric-G families of distributions taking baseline models such as exponential, extended exponential, Weibull, extended Weibull, Fisk, Lomax, Burr-XII and Burr-X. The functions also allow computing the goodness-of-fit measures namely the Akaike-information-criterion (AIC), the Bayesian-information-criterion (BIC), the minimum value of the negative log-likelihood (-2L) function, Anderson-Darling (A) test, Cramer-Von-Mises (W) test, Kolmogorov-Smirnov test, P-value and convergence status. Moreover, some commonly used data sets from the fields of actuarial, reliability, and medical science are also provided. Related works include: + a) Tahir, M. H., & Cordeiro, G. M. (2016). Compounding of distributions: a survey and new generalized classes. Journal of Statistical Distributions and Applications, 3, 1-35. + . + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ComRiskModel + url_git: '' +comsimitv: + version: 0.1.5 + title: Flexible Framework for Simulating Community Assembly + maintainer: Zoltan Botta-Dukat + description: |- + Flexible framework for trait-based simulation of community assembly, where components could be replaced by user-defined function and that + allows variation of traits within species. + date_publication: '2021-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=comsimitv + url_git: '' +comstab: + version: 0.0.3 + title: Partitioning the Drivers of Stability of Ecological Communities + maintainer: Jules Segrestin + description: |- + Contains the basic functions to apply the unified framework + for partitioning the drivers of stability of ecological communities. + Segrestin et al. (2024) . + date_publication: '2024-04-26' + bug_reports: https://github.com/jsegrestin/comstab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=comstab + url_git: https://github.com/jsegrestin/comstab +comtradr: + version: 1.0.3 + title: Interface with the United Nations Comtrade API + maintainer: Paul Bochtler + description: |- + Interface with and extract data from the United Nations 'Comtrade' + API . 'Comtrade' provides country level shipping + data for a variety of commodities, these functions allow for easy API query + and data returned as a tidy data frame. + date_publication: '2024-11-15' + bug_reports: https://github.com/ropensci/comtradr/issues + url: https://docs.ropensci.org/comtradr/ + url_cran: https://CRAN.R-project.org/package=comtradr + url_git: https://github.com/ropensci/comtradr +con2aqi: + version: 0.1.0 + title: Calculate the AQI from Pollutant Concentration + maintainer: Zhicheng Du + description: |- + To calculate the AQI (Air Quality Index) from pollutant concentration data. + O3, PM2.5, PM10, CO, SO2, and NO2 are available currently. + The method can be referenced at Environmental Protection Agency, United States as follows: + EPA (2016) . + date_publication: '2018-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=con2aqi + url_git: '' +con2lki: + version: 0.1.0 + title: Calculate the Dutch Air Quality Index (LKI) + maintainer: Mark Baas + description: |- + Calculates the dutch air quality index (LKI). This index was + created on the basis of scientific studies of the health effects of air + pollution. From these studies it can be deduced at what concentrations a + certain percentage of the population can be affected. For more information + see: . + date_publication: '2021-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=con2lki + url_git: '' +Conake: + version: 1.0.1 + title: Continuous Associated Kernel Estimation + maintainer: W. E. Wansouwé + description: 'Continuous smoothing of probability density function on a compact + or semi-infinite support is performed using four continuous associated kernels: + extended beta, gamma, lognormal and reciprocal inverse Gaussian. The cross-validation + technique is also implemented for bandwidth selection.' + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Conake + url_git: '' +concatenate: + version: 1.0.0 + title: Human-Friendly Text from Unknown Strings + maintainer: James Dunham + description: Simple functions for joining strings. Construct human-friendly messages + whose elements aren't known in advance, like in stop, warning, or message, from + clean code. + date_publication: '2016-05-08' + bug_reports: https://github.com/jamesdunham/concatenate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=concatenate + url_git: https://github.com/jamesdunham/concatenate +concatipede: + version: 1.0.1 + title: Easy Concatenation of Fasta Sequences + maintainer: Matteo Vecchi + description: |- + Concatenation of multiple sequence alignments based on a + correspondence table that can be edited in Excel . + date_publication: '2021-08-06' + bug_reports: https://github.com/tardipede/concatipede/issues + url: https://tardipede.github.io/concatipede/ + url_cran: https://CRAN.R-project.org/package=concatipede + url_git: https://github.com/tardipede/concatipede +concaveman: + version: 1.1.0 + title: A Very Fast 2D Concave Hull Algorithm + maintainer: Joël Gombin + description: The concaveman function ports the 'concaveman' () + library from 'mapbox'. It computes the concave polygon(s) for one or several set + of points. + date_publication: '2020-05-11' + bug_reports: http://www.github.com/joelgombin/concaveman/issues + url: https://joelgombin.github.io/concaveman/ + url_cran: https://CRAN.R-project.org/package=concaveman + url_git: http://www.github.com/joelgombin/concaveman/ +conclust: + version: '1.1' + title: Pairwise Constraints Clustering + maintainer: Tran Khanh Hiep + description: 'There are 4 main functions in this package: ckmeans(), lcvqe(), mpckm() + and ccls(). They take an unlabeled dataset and two lists of must-link and cannot-link + constraints as input and produce a clustering as output.' + date_publication: '2016-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conclust + url_git: '' +concom: + version: 1.0.0 + title: Connected Components of an Undirected Graph + maintainer: Stéphane Laurent + description: |- + Provides a function for fast computation of the connected + components of an undirected graph (though not faster than the + components() function of the 'igraph' package) from the edges or the + adjacency matrix of the graph. Based on this one, a function to + compute the connected components of a triangle 'rgl' mesh is also + provided. + date_publication: '2022-06-15' + bug_reports: https://github.com/stla/concom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=concom + url_git: https://github.com/stla/concom +ConconiAnaerobicThresholdTest: + version: 1.0.0 + title: Conconi Estimate of Anaerobic Threshold from a TCX File + maintainer: Levi Waldron + description: |- + Analyzes data from a Conconi et al. (1996) + treadmill fitness test where speed is augmented by a constant amount every + set number of seconds to estimate the anaerobic (lactate) threshold speed + and heart rate. It reads a TCX file, allows optional removal observations + from before and after the actual test, fits a change-point linear model + where the change-point is the estimate of the lactate threshold, and plots + the data points and fit model. Details of administering the fitness test are + provided in the package vignette. Functions work by default for Garmin + Connect TCX exports but may require additional data preparation for heart + rate, time, and speed data from other sources. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConconiAnaerobicThresholdTest + url_git: https://github.com/waldronlab/ConconiAnaerobicThresholdTest +concordance: + version: 2.0.0 + title: Product Concordance + maintainer: Steven Liao + description: |- + A set of utilities for matching products in different + classification codes used in international trade + research. It supports concordance between the Harmonized + System (HS0, HS1, HS2, HS3, HS4, HS5, HS combined), the Standard + International Trade Classification (SITC1, SITC2, SITC3, SITC4), + the North American Industry Classification System (NAICS combined), + as well as the Broad Economic Categories (BEC), the International + Standard of Industrial Classification (ISIC), and the Standard Industrial + Classification (SIC). It also provides code nomenclature/descriptions + look-up, Rauch classification look-up (via concordance to SITC2), and + trade elasticity look-up (via concordance to HS0 or SITC3 + codes). + date_publication: '2020-04-24' + bug_reports: https://github.com/insongkim/concordance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=concordance + url_git: '' +ConcordanceTest: + version: 1.0.3 + title: |- + An Alternative to the Kruskal-Wallis Based on the Kendall Tau + Distance + maintainer: Laura Anton-Sanchez + description: 'The Concordance Test is a non-parametric method for testing whether + two o more samples originate from the same distribution. It extends the Kendall + Tau correlation coefficient when there are only two groups. For details, see Alcaraz + J., Anton-Sanchez L., Monge J.F. (2022) The Concordance Test, an Alternative to + Kruskal-Wallis Based on the Kendall-tau Distance: An R Package. The R Journal + 14, 26–53 .' + date_publication: '2024-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConcordanceTest + url_git: '' +concorR: + version: 0.2.1 + title: CONCOR and Supplemental Functions + maintainer: Adrienne Traxler + description: |- + Contains the CONCOR (CONvergence of iterated CORrelations) + algorithm and a series of supplemental functions for easy running, + plotting, and blockmodeling. The CONCOR algorithm is used on social network + data to identify network positions based off a definition of structural + equivalence; see Breiger, Boorman, and Arabie (1975) + and Wasserman and Faust's book Social + Network Analysis: Methods and Applications (1994). This version allows + multiple relationships for the same set of nodes and uses both incoming and + outgoing ties to find positions. + date_publication: '2020-11-25' + bug_reports: https://github.com/ATraxLab/concorR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=concorR + url_git: https://github.com/ATraxLab/concorR +concstats: + version: 0.1.6 + title: Market Structure, Concentration and Inequality Measures + maintainer: Andreas Schneider + description: |- + Based on individual market shares of all participants in a + market or space, the package offers a set of different structural and + concentration measures frequently - and not so frequently - used in research + and in practice. Measures can be calculated in groups or individually. + The calculated measure or the resulting vector in table format should help + practitioners make more informed decisions. Methods used in this package are + from: + 1. Chang, E. J., Guerra, S. M., de Souza Penaloza, R. A. & Tabak, B. M. + (2005) "Banking concentration: the Brazilian case". + 2. Cobham, A. and A. Summer (2013). "Is It All About the Tails? The + Palma Measure of Income Inequality". + 3. Garcia Alba Idunate, P. (1994). "Un Indice de dominancia para el + analisis de la estructura de los mercados". + 4. Ginevicius, R. and S. Cirba (2009). "Additive measurement of market + concentration" . + 5. Herfindahl, O. C. (1950), "Concentration in the steel industry" + (PhD thesis). + 6. Hirschmann, A. O. (1945), "National power and structure of foreign + trade". + 7. Melnik, A., O. Shy, and R. Stenbacka (2008), "Assessing market dominance" + . + 8. Palma, J. G. (2006). "Globalizing Inequality: 'Centrifugal' and + 'Centripetal' Forces at Work". + 9. Shannon, C. E. (1948). "A Mathematical Theory of Communication". + 10. Simpson, E. H. (1949). "Measurement of Diversity" + . + date_publication: '2023-03-30' + bug_reports: https://github.com/ropensci/concstats/issues/ + url: https://docs.ropensci.org/concstats/(website) + url_cran: https://CRAN.R-project.org/package=concstats + url_git: https://github.com/ropensci/concstats/ +CONCUR: + version: '1.4' + title: Copy Number Profile Curve-Based Association Test + maintainer: Shannon T. Holloway + description: |- + Implements a kernel-based association test for copy number + variation (CNV) aggregate analysis + in a certain genomic region (e.g., gene set, chromosome, or genome) that is + robust to the within-locus and across-locus etiological heterogeneity, and + bypass the need to define a "locus" unit for CNVs. + Brucker, A., et al. (2020) . + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CONCUR + url_git: '' +cond: + version: 1.2-3.1 + title: |- + Approximate Conditional Inference for Logistic and Loglinear + Models + maintainer: Alessandra R. Brazzale + description: |- + Higher order likelihood-based inference for logistic and + loglinear models. + date_publication: '2018-04-16' + bug_reports: '' + url: http://statwww.epfl.ch/AA/ + url_cran: https://CRAN.R-project.org/package=cond + url_git: '' +condathis: + version: 0.1.1 + title: Run Any CLI Tool on a 'Conda' Environment + maintainer: Lucio Queiroz + description: |- + Simplifies the execution of command line interface (CLI) + tools within isolated and reproducible environments. It enables users + to effortlessly manage 'Conda' environments, execute command line + tools, handle dependencies, and ensure reproducibility in their data + analysis workflows. + date_publication: '2025-01-23' + bug_reports: https://github.com/luciorq/condathis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=condathis + url_git: https://github.com/luciorq/condathis +CondCopulas: + version: 0.1.4.1 + title: Estimation and Inference for Conditional Copula Models + maintainer: Alexis Derumigny + description: |- + Provides functions for the estimation of conditional copulas models, + various estimators of conditional Kendall's tau + (proposed in Derumigny and Fermanian (2019a, 2019b, 2020) + , + , + ), + and test procedures for the simplifying assumption + (proposed in Derumigny and Fermanian (2017) + and Derumigny, Fermanian and Min (2022) ). + date_publication: '2024-09-03' + bug_reports: https://github.com/AlexisDerumigny/CondCopulas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CondCopulas + url_git: https://github.com/AlexisDerumigny/CondCopulas +condensr: + version: 1.0.0 + title: Academic Group Website Generator + maintainer: Michael Lydeamore + description: |- + Helps automate 'Quarto' website creation for small academic groups. + Builds a database-like structure of people, projects and publications, linking + them together with a string-based ID system. Then, provides functions to automate + production of clean markdown for these structures, and in-built CSS formatting + using CSS flexbox. + date_publication: '2023-08-30' + bug_reports: '' + url: http://www.michaellydeamore.com/condensr/ + url_cran: https://CRAN.R-project.org/package=condensr + url_git: '' +condformat: + version: 0.10.1 + title: Conditional Formatting in Data Frames + maintainer: Sergio Oller Moreno + description: |- + Apply and visualize conditional formatting to data frames in R. + It renders a data frame with cells formatted according to + criteria defined by rules, using a tidy evaluation syntax. The table is + printed either opening a web browser or within the 'RStudio' viewer if + available. The conditional formatting rules allow to highlight cells + matching a condition or add a gradient background to a given column. This + package supports both 'HTML' and 'LaTeX' outputs in 'knitr' reports, and + exporting to an 'xlsx' file. + date_publication: '2023-10-08' + bug_reports: https://github.com/zeehio/condformat/issues + url: https://zeehio.github.io/condformat/ + url_cran: https://CRAN.R-project.org/package=condformat + url_git: https://github.com/zeehio/condformat +condGEE: + version: 0.2.0 + title: |- + Parameter Estimation in Conditional GEE for Recurrent Event Gap + Times + maintainer: David Clement + description: Solves for the mean parameters, the variance parameter, and their asymptotic + variance in a conditional GEE for recurrent event gap times, as described by Clement + and Strawderman (2009) in the journal Biostatistics. Makes a parametric assumption + for the length of the censored gap time. + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=condGEE + url_git: '' +CondIndTests: + version: 0.1.5 + title: Nonlinear Conditional Independence Tests + maintainer: Christina Heinze-Deml + description: |- + Code for a variety of nonlinear conditional independence tests: + Kernel conditional independence test (Zhang et al., UAI 2011, ), + Residual Prediction test (based on Shah and Buehlmann, ), + Invariant environment prediction, + Invariant target prediction, + Invariant residual distribution test, + Invariant conditional quantile prediction (all from Heinze-Deml et al., ). + date_publication: '2019-11-12' + bug_reports: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CondIndTests + url_git: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests +condir: + version: 0.1.4 + title: Computation of P Values and Bayes Factors for Conditioning Data + maintainer: Angelos-Miltiadis Krypotos + description: Set of functions for the easy analyses of conditioning data. + date_publication: '2023-09-22' + bug_reports: https://github.com/AngelosPsy/condir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=condir + url_git: https://github.com/AngelosPsy/condir +CondiS: + version: 0.1.2 + title: Censored Data Imputation for Direct Modeling + maintainer: Yizhuo Wang + description: Impute the survival times for censored observations based on their + conditional survival distributions derived from the Kaplan-Meier estimator. 'CondiS' + can replace the censored observations with the best approximations from the statistical + model, allowing for direct application of machine learning-based methods. When + covariates are available, 'CondiS' is extended by incorporating the covariate + information through machine learning-based regression modeling ('CondiS_X'), which + can further improve the imputed survival time. + date_publication: '2022-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CondiS + url_git: '' +conditionalProbNspades: + version: '1.0' + title: Conditional Probabilities of Distributions Across Hearts Hands + maintainer: Barry Zeeberg + description: Provides some tabulated data to be be referred to in a discussion in + a vignette accompanying my upcoming R package 'playWholeHandDriverPassParams'. + In addition to that specific purpose, these may also provide data and illustrate + some computational approaches that are relevant to card games like hearts or bridge.This + package refers to authentic data from Gregory Stoll , + and details of performing the probability calculations from Jeremy L. Martin . + date_publication: '2024-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conditionalProbNspades + url_git: '' +conditionz: + version: 0.1.0 + title: Control How Many Times Conditions are Thrown + maintainer: Scott Chamberlain + description: |- + Provides ability to control how many times in function + calls conditions are thrown (shown to the user). Includes control of + warnings and messages. + date_publication: '2019-04-24' + bug_reports: http://github.com/ropenscilabs/conditionz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conditionz + url_git: https://github.com/ropenscilabs/conditionz +condMVNorm: + version: '2020.1' + title: Conditional Multivariate Normal Distribution + maintainer: Ravi Varadhan + description: Computes conditional multivariate normal densities, probabilities, + and random deviates. + date_publication: '2020-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=condMVNorm + url_git: '' +CondMVT: + version: 0.1.0 + title: |- + Conditional Multivariate t Distribution, Expectation + Maximization Algorithm, and Its Stochastic Variants + maintainer: Paul Kinyanjui + description: Computes conditional multivariate t probabilities, random deviates, + and densities. It can also be used to create missing values at random in a dataset, + resulting in a missing at random (MAR) mechanism. Inbuilt in the package are the + Expectation-Maximization (EM), Monte Carlo EM, and Stochastic EM algorithms for + imputation of missing values in datasets assuming the multivariate t distribution. + See Kinyanjui, Tamba, Orawo, and Okenye (2020), and Kinyanjui, + Tamba, and Okenye(2021) + for more details. + date_publication: '2022-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CondMVT + url_git: '' +condor: + version: 3.0.0 + title: Interact with 'Condor' from R via SSH + maintainer: Arni Magnusson + description: |- + Interact with 'Condor' from R via SSH connection. Files are first + uploaded from user machine to submitter machine, and the job is then submitted + from the submitter machine to 'Condor'. Functions are provided to submit, + list, and download 'Condor' jobs from R. 'Condor' is an open source + high-throughput computing software framework for distributed parallelization + of computationally intensive tasks. + date_publication: '2024-11-12' + bug_reports: '' + url: https://htcondor.org + url_cran: https://CRAN.R-project.org/package=condor + url_git: https://github.com/PacificCommunity/ofp-sam-condor +condorOptions: + version: 1.0.1 + title: Trading Condor Options Strategies + maintainer: MaheshP Kumar + description: |- + Trading of Condor Options Strategies is represented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. + Guy Cohen (“The Bible of Options Strategies (2nd ed.)”, 2015, ISBN: 9780133964028). + Zura Kakushadze, Juan A. Serur (“151 Trading Strategies”, 2018, ISBN: 9783030027919). + John C. Hull (“Options, Futures, and Other Derivatives (11th ed.)”, 2022, ISBN: 9780136939979). + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=condorOptions + url_git: '' +condSURV: + version: 2.0.4 + title: |- + Estimation of the Conditional Survival Function for Ordered + Multivariate Failure Time Data + maintainer: Marta Sestelo + description: |- + Method to implement some newly developed methods for the + estimation of the conditional survival function. See Meira-Machado, + Sestelo and Goncalves (2016) . + date_publication: '2023-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=condSURV + url_git: '' +condTruncMVN: + version: 0.0.2 + title: Conditional Truncated Multivariate Normal Distribution + maintainer: Paul M. Hargarten + description: Computes the density and probability for the conditional truncated + multivariate normal (Horrace (2005) p. 4, ). Also + draws random samples from this distribution. + date_publication: '2020-09-17' + bug_reports: https://github.com/phargarten2/condTruncMVN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=condTruncMVN + url_git: '' +conductor: + version: 0.1.1 + title: Create Tours in 'Shiny' Apps Using 'Shepherd.js' + maintainer: Etienne Bacher + description: |- + Enable the use of 'Shepherd.js' to create tours in 'Shiny' + applications. + date_publication: '2022-08-28' + bug_reports: https://github.com/etiennebacher/conductor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conductor + url_git: https://github.com/etiennebacher/conductor +condvis: + version: 0.5-1 + title: Conditional Visualization for Statistical Models + maintainer: Mark O'Connell + description: |- + Exploring fitted models by interactively taking 2-D and 3-D + sections in data space. + date_publication: '2018-09-13' + bug_reports: https://github.com/markajoc/condvis/issues + url: http://markajoc.github.io/condvis/ + url_cran: https://CRAN.R-project.org/package=condvis + url_git: '' +condvis2: + version: 0.1.2 + title: |- + Interactive Conditional Visualization for Supervised and + Unsupervised Models in Shiny + maintainer: Catherine Hurley + description: |- + Constructs a shiny app function with interactive displays for conditional visualization of models, + data and density functions. An extended version of package 'condvis'. + Catherine B. Hurley, Mark O'Connell,Katarina Domijan (2021) . + date_publication: '2022-09-14' + bug_reports: https://github.com/cbhurley/condvis2/issues + url: https://cbhurley.github.io/condvis2/ + url_cran: https://CRAN.R-project.org/package=condvis2 + url_git: https://github.com/cbhurley/condvis2 +coneproj: + version: '1.20' + title: |- + Primal or Dual Cone Projections with Routines for Constrained + Regression + maintainer: Xiyue Liao + description: Routines doing cone projection and quadratic programming, as well as + doing estimation and inference for constrained parametric regression and shape-restricted + regression problems. See Mary C. Meyer (2013) + for more details. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coneproj + url_git: '' +conf: + version: 1.9.1 + title: Visualization and Analysis of Statistical Measures of Confidence + maintainer: Christopher Weld + description: |- + Enables: (1) plotting two-dimensional confidence regions, (2) coverage analysis + of confidence region simulations, (3) calculating confidence intervals and the associated + actual coverage for binomial proportions, (4) calculating the support values and the + probability mass function of the Kaplan-Meier product-limit estimator, and (5) plotting + the actual coverage function associated with a confidence interval for the survivor + function from a randomly right-censored data set. Each is given in greater detail next. + (1) Plots the two-dimensional confidence region for probability distribution parameters + (supported distribution suffixes: cauchy, gamma, invgauss, logis, llogis, lnorm, norm, unif, + weibull) corresponding to a user-given complete or right-censored dataset and level of + significance. The crplot() algorithm plots more points in areas of greater curvature to + ensure a smooth appearance throughout the confidence region boundary. An alternative + heuristic plots a specified number of points at roughly uniform intervals along its boundary. + Both heuristics build upon the radial profile log-likelihood ratio technique for plotting + confidence regions given by Jaeger (2016) , and + are detailed in a publication by Weld et al. (2019) . + (2) Performs confidence region coverage simulations for a random sample drawn from a user- + specified parametric population distribution, or for a user-specified dataset and point of + interest with coversim(). (3) Calculates confidence interval bounds for a binomial proportion + with binomTest(), calculates the actual coverage with binomTestCoverage(), and plots the + actual coverage with binomTestCoveragePlot(). Calculates confidence interval bounds for the + binomial proportion using an ensemble of constituent confidence intervals with + binomTestEnsemble(). Calculates confidence interval bounds for the binomial proportion using + a complete enumeration of all possible transitions from one actual coverage acceptance curve + to another which minimizes the root mean square error for n <= 15 and follows the transitions + for well-known confidence intervals for n > 15 using binomTestMSE(). (4) The km.support() + function calculates the support values of the Kaplan-Meier product-limit estimator for a given + sample size n using an induction algorithm described in Qin et al. (2023) + . The km.outcomes() function generates a matrix + containing all possible outcomes (all possible sequences of failure times and right-censoring + times) of the value of the Kaplan-Meier product-limit estimator for a particular sample size + n. The km.pmf() function generates the probability mass function for the support values of + the Kaplan-Meier product-limit estimator for a particular sample size n, probability of + observing a failure h at the time of interest expressed as the cumulative probability + percentile associated with X = min(T, C), where T is the failure time and C is the censoring + time under a random-censoring scheme. The km.surv() function generates multiple probability + mass functions of the Kaplan-Meier product-limit estimator for the same arguments as those + given for km.pmf(). (5) The km.coverage() function plots the actual coverage function + associated with a confidence interval for the survivor function from a randomly right-censored + data set for one or more of the following confidence intervals: Greenwood, log-minus-log, + Peto, arcsine, and exponential Greenwood. The actual coverage function is plotted for a + small number of items on test, stated coverage, failure rate, and censoring rate. The + km.coverage() function can print an optional table containing all possible + failure/censoring orderings, along with their contribution to the actual coverage function. + date_publication: '2024-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conf + url_git: '' +conf.design: + version: 2.0.0 + title: Construction of factorial designs + maintainer: Bill Venables + description: This small library contains a series of simple tools forconstructing + and manipulating confounded and fractionalfactorial designs. + date_publication: '2013-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conf.design + url_git: '' +confcons: + version: 0.3.1 + title: Confidence and Consistency of Predictive Distribution Models + maintainer: Ákos Bede-Fazekas + description: |- + Calculate confidence and consistency that measure the + goodness-of-fit and transferability of predictive/potential distribution + models (including species distribution models) as described by Somodi & + Bede-Fazekas et al. (2024) . + date_publication: '2024-03-17' + bug_reports: https://github.com/bfakos/confcons/issues + url: https://bfakos.github.io/confcons/ + url_cran: https://CRAN.R-project.org/package=confcons + url_git: https://github.com/bfakos/confcons +confidence: + version: 1.1-2 + title: Confidence Estimation of Environmental State Classifications + maintainer: Dennis Walvoort + description: |- + Functions for estimating and reporting multi-year averages and + corresponding confidence intervals and distributions. A potential use case + is reporting the chemical and ecological status of surface waters according + to the European Water Framework Directive. + date_publication: '2017-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=confidence + url_git: '' +ConfidenceEllipse: + version: 1.0.0 + title: Computation of 2D and 3D Elliptical Joint Confidence Regions + maintainer: Christian L. Goueguel + description: Computing elliptical joint confidence regions at a specified confidence + level. It provides the flexibility to estimate either classical or robust confidence + regions, which can be visualized in 2D or 3D plots. The classical approach assumes + normality and uses the mean and covariance matrix to define the confidence regions. + Alternatively, the robustified version employs estimators like minimum covariance + determinant (MCD) and M-estimator, making them less sensitive to outliers and + departures from normality. Furthermore, the functions allow users to group the + dataset based on categorical variables and estimate separate confidence regions + for each group. This capability is particularly useful for exploring potential + differences or similarities across subgroups within a dataset. Varmuza and Filzmoser + (2009, ISBN:978-1-4200-5947-2). Johnson and Wichern (2007, ISBN:0-13-187715-1). + Raymaekers and Rousseeuw (2019) . + date_publication: '2024-04-22' + bug_reports: https://github.com/ChristianGoueguel/ConfidenceEllipse/issues + url: https://christiangoueguel.github.io/ConfidenceEllipse/ + url_cran: https://CRAN.R-project.org/package=ConfidenceEllipse + url_git: https://github.com/ChristianGoueguel/ConfidenceEllipse +config: + version: 0.3.2 + title: Manage Environment Specific Configuration Values + maintainer: Andrie de Vries + description: |- + Manage configuration values across multiple environments (e.g. + development, test, production). Read values using a function that determines + the current environment and returns the appropriate value. + date_publication: '2023-08-30' + bug_reports: https://github.com/rstudio/config/issues + url: https://rstudio.github.io/config/ + url_cran: https://CRAN.R-project.org/package=config + url_git: https://github.com/rstudio/config +ConfigParser: + version: 1.0.0 + title: Package to Parse an INI File, Including Variable Interpolation + maintainer: Holger Hoefling + description: |- + Enhances the 'ini' package by adding the ability to interpolate variables. + The INI configuration file is read into an R6 ConfigParser object (loosely inspired by Pythons ConfigParser module) + and the keys can be read, where '%(....)s' instances are interpolated by other included options or outside variables. + date_publication: '2017-08-22' + bug_reports: https://github.com/hhoeflin/ConfigParser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ConfigParser + url_git: https://github.com/hhoeflin/ConfigParser +configr: + version: 0.3.5 + title: |- + An Implementation of Parsing and Writing Configuration File + (JSON/INI/YAML/TOML) + maintainer: Jianfeng Li + description: |2- + + Implements the JSON, INI, YAML and TOML parser for R setting and writing of configuration file. The functionality of this package is similar to that of package 'config'. + date_publication: '2020-07-17' + bug_reports: https://github.com/Miachol/configr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=configr + url_git: https://github.com/Miachol/configr +configural: + version: 0.1.5 + title: Multivariate Profile Analysis + maintainer: Brenton M. Wiernik + description: R functions for criterion profile analysis, Davison and Davenport (2002) + and meta-analytic criterion profile analysis, + Wiernik, Wilmot, Davison, and Ones (2020) . Sensitivity + analyses to aid in interpreting criterion profile analysis results are also included. + date_publication: '2024-03-18' + bug_reports: https://github.com/bwiernik/configural/issues + url: '' + url_cran: https://CRAN.R-project.org/package=configural + url_git: '' +confinterpret: + version: 1.0.0 + title: Descriptive Interpretations of Confidence Intervals + maintainer: Jim Vine + description: |- + Produces descriptive interpretations of confidence intervals. + Includes (extensible) support for various test types, specified as sets + of interpretations dependent on where the lower and upper confidence limits + sit. Provides plotting functions for graphical display of interpretations. + date_publication: '2017-10-03' + bug_reports: https://github.com/jimvine/confinterpret/issues + url: '' + url_cran: https://CRAN.R-project.org/package=confinterpret + url_git: https://github.com/jimvine/confinterpret +confintr: + version: 1.0.2 + title: Confidence Intervals + maintainer: Michael Mayer + description: |- + Calculates classic and/or bootstrap confidence intervals for + many parameters such as the population mean, variance, interquartile + range (IQR), median absolute deviation (MAD), skewness, kurtosis, + Cramer's V, odds ratio, R-squared, quantiles (incl. median), + proportions, different types of correlation measures, difference in + means, quantiles and medians. Many of the classic confidence intervals + are described in Smithson, M. (2003, ISBN: 978-0761924999). Bootstrap + confidence intervals are calculated with the R package 'boot'. Both + one- and two-sided intervals are supported. + date_publication: '2023-06-04' + bug_reports: https://github.com/mayer79/confintr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=confintr + url_git: https://github.com/mayer79/confintr +confintROB: + version: 1.0-1 + title: |- + Confidence Intervals for Robust and Classical Linear Mixed Model + Estimators + maintainer: Fabio Mason + description: 'The main function calculates confidence intervals (CI) for Mixed Models, + utilizing both classical estimators from the lmer() function in the ''lme4'' package + and robust estimators from the rlmer() function in the ''robustlmm'' package, + as well as the varComprob() function in the ''robustvarComp'' package. Three methods + are available: the classical Wald method, the wild bootstrap, and the parametric + bootstrap. Bootstrap methods offer flexibility in obtaining lower and upper bounds + through percentile or BCa methods. More details are given in Mason, F., Cantoni, + E., & Ghisletta, P. (2021) and Mason, F., Cantoni, E., + & Ghisletta, P. (2024) .' + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=confintROB + url_git: '' +ConfIntVariance: + version: 1.0.2 + title: |- + Confidence Interval for the Univariate Population Variance + without Normality Assumption + maintainer: Mathias Fuchs + description: Surrounds the usual sample variance of a univariate numeric sample + with a confidence interval for the population variance. This has been done so + far only under the assumption that the underlying distribution is normal. Under + the hood, this package implements the unique least-variance unbiased estimator + of the variance of the sample variance, in a formula that is equivalent to estimating + kurtosis and square of the population variance in an unbiased way and combining + them according to the classical formula into an estimator of the variance of the + sample variance. Both the sample variance and the estimator of its variance are + U-statistics. By the theory of U-statistic, the resulting estimator is unique. + See Fuchs, Krautenbacher (2016) and the references + therein for an overview of unbiased estimation of variances of U-statistics. + date_publication: '2019-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConfIntVariance + url_git: '' +conflicted: + version: 1.2.0 + title: An Alternative Conflict Resolution Strategy + maintainer: Hadley Wickham + description: |- + R's default conflict management system gives the most + recently loaded package precedence. This can make it hard to detect + conflicts, particularly when they arise because a package update + creates ambiguity that did not previously exist. 'conflicted' takes a + different approach, making every conflict an error and forcing you to + choose which function to use. + date_publication: '2023-02-01' + bug_reports: https://github.com/r-lib/conflicted/issues + url: https://conflicted.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=conflicted + url_git: https://github.com/r-lib/conflicted +conflr: + version: 0.1.1 + title: Client for 'Confluence' API + maintainer: Hiroaki Yutani + description: |- + Provides utilities for working with various 'Confluence' API + , including a + functionality to convert an R Markdown document to 'Confluence' format and + upload it to 'Confluence' automatically. + date_publication: '2020-04-08' + bug_reports: https://github.com/line/conflr/issues + url: https://line.github.io/conflr/ + url_cran: https://CRAN.R-project.org/package=conflr + url_git: https://github.com/line/conflr +ConfMatrix: + version: 0.1.0 + title: Confusion Matrix + maintainer: Silverio Vilchez-Lopez + description: |- + Thematic quality indices are provided to facilitate the evaluation + and quality control of geospatial data products (e.g. thematic maps, remote + sensing classifications, etc.). The indices offered are based on the + so-called confusion matrix. This matrix is constructed by comparing the + assigned classes or attributes of a set of pairs of positions or objects + in the product and the ground truth. In this package it is considered that + the classes of the ground truth correspond to the columns and that the + classes of the product to be valued correspond to the rows. The package + offers two object classes with their methods: 'ConfMatrix' (Confusion + matrix) and 'QCCS' (Quality Control Columns Set). The 'ConfMatrix' class of + objects offers more than 20 methods based on the confusion matrix. The + 'QCCS' class of objects offers a different perspective in which the ground + truth is considered to allow the values of the column marginals to be fixed, + see Ariza López et al. (2019) and Canran Liu et al. + (2007) for more details. The package was + created with 'R6'. + date_publication: '2024-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConfMatrix + url_git: '' +conformalbayes: + version: 0.1.2 + title: Jackknife(+) Predictive Intervals for Bayesian Models + maintainer: Cory McCartan + description: |- + Provides functions to construct finite-sample calibrated predictive + intervals for Bayesian models, following the approach in Barber et al. + (2021) . These intervals are calculated efficiently + using importance sampling for the leave-one-out residuals. By default, + the intervals will also reflect the relative uncertainty in the Bayesian + model, using the locally-weighted conformal methods of Lei et al. (2018) + . + date_publication: '2022-08-12' + bug_reports: https://github.com/CoryMcCartan/conformalbayes/issues + url: https://corymccartan.com/conformalbayes/ + url_cran: https://CRAN.R-project.org/package=conformalbayes + url_git: https://github.com/CoryMcCartan/conformalbayes +conformalClassification: + version: 1.0.0 + title: |- + Transductive and Inductive Conformal Predictions for + Classification Problems + maintainer: Niharika Gauraha + description: Implementation of transductive conformal prediction (see Vovk, 2013, + ) and inductive conformal prediction (see Balasubramanian + et al., 2014, ISBN:9780124017153) for classification problems. + date_publication: '2017-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conformalClassification + url_git: '' +conformalInference.fd: + version: 1.1.1 + title: |- + Tools for Conformal Inference for Regression in Multivariate + Functional Setting + maintainer: Paolo Vergottini + description: |- + It computes full conformal, split conformal and multi split + conformal prediction regions when the response has functional nature. + Moreover, the package also contain a plot function to visualize the + output of the split conformal. + To guarantee consistency, the package structure mimics the univariate + 'conformalInference' package of professor Ryan Tibshirani. + The main references for the code are: + Diquigiovanni, Fontana, and Vantini (2021) , + Diquigiovanni, Fontana, and Vantini (2021) , + Solari, and Djordjilovic (2021) . + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conformalInference.fd + url_git: https://github.com/ryantibs/conformal +conformalInference.multi: + version: 1.1.1 + title: |- + Conformal Inference Tools for Regression with Multivariate + Response + maintainer: Paolo Vergottini + description: |- + It computes full conformal, split conformal and multi split + conformal prediction regions when the response variable is + multivariate (i.e. dimension is greater than one). Moreover, the + package also contain plot functions to visualize the output of the + full and split conformal functions. + To guarantee consistency, the package structure mimics the univariate 'conformalInference' + package of professor Ryan Tibshirani. + The main references for the code are: + Lei et al. (2016) , + Diquigiovanni, Fontana, and Vantini (2021) , + Diquigiovanni, Fontana, and Vantini (2021) , + Solari, and Djordjilovic (2021) . + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conformalInference.multi + url_git: https://github.com/ryantibs/conformal +conformalpvalue: + version: 0.1.0 + title: Computes Conformal p-Values + maintainer: Chhavi Tyagi + description: Computes marginal conformal p-values using conformal prediction in + binary classification tasks. Conformal prediction is a framework that augments + machine learning algorithms with a measure of uncertainty, in the form of prediction + regions that attain a user-specified level of confidence. This package specifically + focuses on providing conformal p-values that can be used to assess the confidence + of the classification predictions. For more details, see Tyagi and Guo (2023) + . + date_publication: '2023-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conformalpvalue + url_git: '' +ConformalSmallest: + version: '1.0' + title: Efficient Tuning-Free Conformal Prediction + maintainer: Yachong Yang + description: An implementation of efficiency first conformal prediction (EFCP) and + validity first conformal prediction (VFCP) that demonstrates both validity (coverage + guarantee) and efficiency (width guarantee). To learn how to use it, check the + vignettes for a quick tutorial. The package is based on the work by Yang Y., Kuchibhotla + A.,(2021) . + date_publication: '2021-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConformalSmallest + url_git: https://github.com/Elsa-Yang98/ConformalSmallest +confreq: + version: 1.6.1-1 + title: Configural Frequencies Analysis Using Log-Linear Modeling + maintainer: Joerg-Henrik Heine + description: |- + Offers several functions for Configural Frequencies + Analysis (CFA), which is a useful statistical tool for the analysis of + multiway contingency tables. CFA was introduced by G. A. Lienert as + 'Konfigurations Frequenz Analyse - KFA'. Lienert, G. A. (1971). + Die Konfigurationsfrequenzanalyse: I. Ein neuer Weg zu Typen und Syndromen. + Zeitschrift für Klinische Psychologie und Psychotherapie, 19(2), 99–115. + date_publication: '2022-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=confreq + url_git: '' +confSAM: + version: '0.2' + title: |- + Estimates and Bounds for the False Discovery Proportion, by + Permutation + maintainer: Jesse Hemerik + description: |- + For multiple testing. + Computes estimates and confidence bounds for the + False Discovery Proportion (FDP), the fraction of false positives among + all rejected hypotheses. + The methods in the package use permutations of the data. Doing so, they + take into account the dependence structure in the data. + date_publication: '2018-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=confSAM + url_git: '' +ConfusionTableR: + version: 1.0.4 + title: Confusion Matrix Toolset + maintainer: Gary Hutson + description: |- + Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists. + The intended usage is to allow the tool to work with the outputs of machine learning classification models. + This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs. + This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time. + Traditionally, this approach has been used for highlighting model representation and feature slippage. + date_publication: '2021-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConfusionTableR + url_git: '' +ConfZIC: + version: 1.0.1 + title: |- + Confidence Envelopes for Model Selection Criteria Based on + Minimum ZIC + maintainer: I.M.L. Nadeesha Jayaweera + description: Narrow down the number of models to look at in model selection using + the confidence envelopes based on the minimum ZIC (Generalized Information Criteria) + values for regression and time series data. Functions involve the computation + of multivariate normal-probabilities with covariance matrices based on minimum + ZIC inverting the CDF of the minimum ZIC. It involves both the computation of + singular and non-singular probabilities as described in Genz (1992) <[https:doi.org/10.2307/1390838]https:doi.org/10.2307/1390838>. + date_publication: '2023-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConfZIC + url_git: '' +congress: + version: 0.0.3 + title: Access the Congress.gov API + maintainer: Christopher T. Kenny + description: |- + Download and read data on United States congressional proceedings. + Data is read from the Library of Congress's Congress.gov Application Programming + Interface (). Functions + exist for all version 3 endpoints, including for bills, amendments, congresses, + summaries, members, reports, communications, nominations, and treaties. + date_publication: '2024-01-09' + bug_reports: https://github.com/christopherkenny/congress/issues + url: https://christophertkenny.com/congress/ + url_cran: https://CRAN.R-project.org/package=congress + url_git: https://github.com/christopherkenny/congress +CongressData: + version: 1.5.4 + title: A Functional Tool for 'CongressData' + maintainer: Caleb Lucas + description: A tool that imports, subsets, and exports the 'CongressData' dataset. + 'CongressData' contains approximately 800 variables concerning all US congressional + districts with data back to 1789. The dataset tracks district characteristics, + members of Congress, and the political behavior of those members. Users with only + a basic understanding of R can subset this data across multiple dimensions, export + their search results, identify the citations associated with their searches, and + more. + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CongressData + url_git: '' +CongreveLamsdell2016: + version: 1.0.3 + title: Distance Metrics for Trees Generated by Congreve and Lamsdell + maintainer: Martin R. Smith + description: |- + Includes the 100 datasets simulated by Congreve and Lamsdell (2016) + , and analyses of the partition and quartet distance of + reconstructed trees from the generative tree, as analysed by Smith (2019) + . + date_publication: '2024-02-23' + bug_reports: https://github.com/ms609/CongreveLamsdell2016/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CongreveLamsdell2016 + url_git: https://github.com/ms609/CongreveLamsdell2016 +CoNI: + version: 0.1.0 + title: Correlation Guided Network Integration (CoNI) + maintainer: José Manuel Monroy Kuhn + description: Integrates two numerical omics data sets from the same samples using + partial correlations. The output can be represented as a network, bipartite graph + or a hypergraph structure. The method used in the package refers to Klaus et al + (2021) . + date_publication: '2021-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoNI + url_git: '' +conicfit: + version: 1.0.4 + title: |- + Algorithms for Fitting Circles, Ellipses and Conics Based on the + Work by Prof. Nikolai Chernov + maintainer: Jose Gama + description: Geometric circle fitting with Levenberg-Marquardt (a, b, R), Levenberg-Marquardt + reduced (a, b), Landau, Spath and Chernov-Lesort. Algebraic circle fitting with + Taubin, Kasa, Pratt and Fitzgibbon-Pilu-Fisher. Geometric ellipse fitting with + ellipse LMG (geometric parameters) and conic LMA (algebraic parameters). Algebraic + ellipse fitting with Fitzgibbon-Pilu-Fisher and Taubin. + date_publication: '2015-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conicfit + url_git: '' +Conigrave: + version: 0.4.4 + title: Flexible Tools for Multiple Imputation + maintainer: James Conigrave + description: |- + Provides a set of tools that can be used across 'data.frame' and + 'imputationList' objects. + date_publication: '2019-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Conigrave + url_git: '' +conjoint: + version: '1.41' + title: An Implementation of Conjoint Analysis Method + maintainer: Tomasz Bartlomowicz + description: This is a simple R package that allows to measure the stated preferences + using traditional conjoint analysis method. + date_publication: '2018-07-26' + bug_reports: '' + url: http://keii.ue.wroc.pl/conjoint + url_cran: https://CRAN.R-project.org/package=conjoint + url_git: '' +ConjointChecks: + version: 0.2.0 + title: |- + Implementation of a Method to Check the Cancellation Axioms of + Additive Conjoint Measurement + maintainer: Ben Domingue + description: Implementation of a procedure---Domingue (2012) , + Domingue (2014) ; see also Karabatsos (2001) + and Kyngdon (2011) ---to test the single and double + cancellation axioms of conjoint measure in data that is dichotomously coded and + measured with error. + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConjointChecks + url_git: https://github.com/ben-domingue/ConjointChecks +conjurer: + version: 1.7.1 + title: A Parametric Method for Generating Synthetic Data + maintainer: Sidharth Macherla + description: Generates synthetic data distributions to enable testing various modelling + techniques in ways that real data does not allow. Noise can be added in a controlled + manner such that the data seems real. This methodology is generic and therefore + benefits both the academic and industrial research. + date_publication: '2023-01-18' + bug_reports: https://github.com/SidharthMacherla/conjurer/issues + url: https://www.foyi.co.nz/posts/documentation/documentationconjurer/ + url_cran: https://CRAN.R-project.org/package=conjurer + url_git: '' +conleyreg: + version: 0.1.7 + title: Estimations using Conley Standard Errors + maintainer: Christian Düben + description: |- + Functions calculating Conley (1999) standard errors. The package started by merging and extending multiple packages and + other published scripts on this econometric technique. It strongly emphasizes computational optimization. Details are available in the function documentation and in + the vignette. + date_publication: '2022-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conleyreg + url_git: '' +conmet: + version: 0.1.0 + title: Construct Measurement Evaluation Tool + maintainer: Leander De Schutter + description: With this package you can run 'ConMET' locally in R. 'ConMET' is an + R-shiny application that facilitates performing and evaluating confirmatory factor + analyses (CFAs) and is useful for running and reporting typical measurement models + in applied psychology and management journals. 'ConMET' automatically creates, + compares and summarizes CFA models. Most common fit indices (E.g., CFI and SRMR) + are put in an overview table. ConMET also allows to test for common method variance. + The application is particularly useful for teaching and instruction of measurement + issues in survey research. The application uses the 'lavaan' package (Rosseel, + 2012) to run CFAs. + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conmet + url_git: '' +ConNEcT: + version: 0.7.27 + title: Contingency Measure-Based Networks for Binary Time Series + maintainer: Nadja Bodner + description: 'The ConNEcT approach investigates the pairwise association strength + of binary time series by calculating contingency measures and depicts the results + in a network. The package includes features to explore and visualize the data. + To calculate the pairwise concurrent or temporal sequenced relationship between + the variables, the package provides seven contingency measures (proportion of + agreement, classical & corrected Jaccard, Cohen''s kappa, phi correlation coefficient, + odds ratio, and log odds ratio), however, others can easily be implemented. The + package also includes non-parametric significance tests, that can be applied to + test whether the contingency value quantifying the relationship between the variables + is significantly higher than chance level. Most importantly this test accounts + for auto-dependence and relative frequency.See Bodner et al.(2021) .Finally, + a network can be drawn. Variables depicted the nodes of the network, with the + node size adapted to the prevalence. The association strength between the variables + defines the undirected (concurrent) or directed (temporal sequenced) links between + the nodes. The results of the non-parametric significance test can be included + by depicting either all links or only the significant ones. Tutorial see Bodner + et al.(2021) .' + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConNEcT + url_git: '' +connectapi: + version: 0.6.0 + title: Utilities for Interacting with the 'Posit Connect' Server API + maintainer: Toph Allen + description: |- + Provides a helpful 'R6' class and methods for interacting with + the 'Posit Connect' Server API along with some meaningful utility functions + for regular tasks. API documentation varies by 'Posit Connect' installation + and version, but the latest documentation is also hosted publicly at + . + date_publication: '2025-02-11' + bug_reports: https://github.com/posit-dev/connectapi/issues + url: https://posit-dev.github.io/connectapi/ + url_cran: https://CRAN.R-project.org/package=connectapi + url_git: https://github.com/posit-dev/connectapi +connectcreds: + version: 0.1.0 + title: Manage 'OAuth' Credentials from 'Posit Connect' + maintainer: Aaron Jacobs + description: |- + A toolkit for making use of credentials mediated by 'Posit + Connect'. It handles the details of communicating with the Connect API + correctly, 'OAuth' token caching, and refresh behaviour. + date_publication: '2025-01-31' + bug_reports: https://github.com/posit-dev/connectcreds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=connectcreds + url_git: https://github.com/posit-dev/connectcreds +ConnectednessApproach: + version: 1.0.4 + title: Connectedness Approach + maintainer: David Gabauer + description: The estimation of static and dynamic connectedness measures is created + in a modular and user-friendly way. Besides, the time domain connectedness approaches, + this package further allows to estimate the frequency connectedness approach, + the joint spillover index and the extended joint connectedness approach. In addition, + all connectedness frameworks can be based upon orthogonalized and generalized + VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR and TVP-VAR models. Furthermore, + the package includes the conditional, decomposed and partial connectedness measures + as well as the pairwise connectedness index, influence index and corrected total + connectedness index. Finally, a battery of datasets are available allowing to + replicate a variety of connectedness papers. + date_publication: '2025-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConnectednessApproach + url_git: '' +connections: + version: 0.2.0 + title: Integrates with the 'RStudio' Connections Pane and 'pins' + maintainer: Edgar Ruiz + description: |- + Enables 'DBI' compliant packages to integrate with the 'RStudio' connections + pane, and the 'pins' package. It automates the display of schemata, tables, views, as well + as the preview of the table's top 1000 records. + date_publication: '2023-12-18' + bug_reports: https://github.com/rstudio/connections/issues + url: https://rstudio.github.io/connections/ + url_cran: https://CRAN.R-project.org/package=connections + url_git: https://github.com/rstudio/connections +connectoModa: + version: 1.0.0 + title: Download Data from Moda + maintainer: Idrissa DABO + description: Connect to WFP's Moda platform to R, download data, and obtain the + list of individuals with access to the project along with their access level. + date_publication: '2024-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=connectoModa + url_git: '' +connectwidgets: + version: 0.2.1 + title: Organize and Curate Your Content Within 'Posit Connect' + maintainer: Brian Smith + description: |- + A collection of helper functions and 'htmlwidgets' to help publishers + curate content collections on 'Posit Connect'. The components, + Card, Grid, Table, Search, and Filter can be used to produce a + showcase page or gallery contained within a static or interactive + R Markdown page. + date_publication: '2023-09-20' + bug_reports: https://github.com/rstudio/connectwidgets/issues + url: https://rstudio.github.io/connectwidgets/ + url_cran: https://CRAN.R-project.org/package=connectwidgets + url_git: https://github.com/rstudio/connectwidgets +ConnMatTools: + version: 0.3.5 + title: Tools for Working with Connectivity Data + maintainer: David M. Kaplan + description: |- + Collects several different methods for analyzing and + working with connectivity data in R. Though primarily oriented towards + marine larval dispersal, many of the methods are general and useful for + terrestrial systems as well. + date_publication: '2020-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConnMatTools + url_git: https://github.com/dmkaplan2000/ConnMatTools.git +conogive: + version: 1.0.0 + title: Congeneric Normal-Ogive Model + maintainer: Jonas Moss + description: |- + The congeneric normal-ogive model is a popular model for + psychometric data (McDonald, R. P. (1997) ). + This model estimates the model, calculates theoretical and concrete + reliability coefficients, and predicts the latent variable of the model. + This is the companion package to Moss (2020) . + date_publication: '2020-06-30' + bug_reports: https://github.com/JonasMoss/conogive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conogive + url_git: https://github.com/JonasMoss/conogive +conos: + version: 1.5.2 + title: Clustering on Network of Samples + maintainer: Evan Biederstedt + description: Wires together large collections of single-cell RNA-seq datasets, which + allows for both the identification of recurrent cell clusters and the propagation + of information between datasets in multi-sample or atlas-scale collections. 'Conos' + focuses on the uniform mapping of homologous cell types across heterogeneous sample + collections. For instance, users could investigate a collection of dozens of peripheral + blood samples from cancer patients combined with dozens of controls, which perhaps + includes samples of a related tissue such as lymph nodes. This package interacts + with data available through the 'conosPanel' package, which is available in a + 'drat' repository. To access this data package, see the instructions at . + The size of the 'conosPanel' package is approximately 12 MB. + date_publication: '2024-02-26' + bug_reports: https://github.com/kharchenkolab/conos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conos + url_git: https://github.com/kharchenkolab/conos +conover.test: + version: 1.1.6 + title: Conover-Iman Test of Multiple Comparisons Using Rank Sums + maintainer: Alexis Dinno + description: Computes the Conover-Iman test (1979) for 0th-order stochastic dominance + and reports the results among multiple pairwise comparisons after a Kruskal-Wallis + omnibus test for i0th-order stochastic dominance among k groups (Kruskal and Wallis, + 1952). conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman + t-test-statistic of the rank differences. The null hypothesis for each pairwise + comparison is that the probability of observing a randomly selected value from + the first group that is larger than a randomly selected value from the second + group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney + rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, + and the distributions are assumed identical except for a difference in location, + Conover-Iman test may be understood as a test for median difference and for mean + difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly + valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected. + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conover.test + url_git: '' +conquer: + version: 1.3.3 + title: Convolution-Type Smoothed Quantile Regression + maintainer: Xiaoou Pan + description: Estimation and inference for conditional linear quantile regression + models using a convolution smoothed approach. In the low-dimensional setting, + efficient gradient-based methods are employed for fitting both a single model + and a regression process over a quantile range. Normal-based and (multiplier) + bootstrap confidence intervals for all slope coefficients are constructed. In + high dimensions, the conquer method is complemented with flexible types of penalties + (Lasso, elastic-net, group lasso, sparse group lasso, scad and mcp) to deal with + complex low-dimensional structures. + date_publication: '2023-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conquer + url_git: https://github.com/XiaoouPan/conquer +conquestr: + version: 1.4.5 + title: An R Package to Extend 'ACER ConQuest' + maintainer: Dan Cloney + description: |- + Extends 'ACER ConQuest' through a family of functions + designed to improve graphical outputs and help with advanced analysis + (e.g., differential item functioning). Allows R users to call + 'ACER ConQuest' from within R and read 'ACER ConQuest' System Files + (generated by the command `put` ). + Requires 'ACER ConQuest' version 5.40 or later. + A demonstration version can be downloaded from . + date_publication: '2025-02-19' + bug_reports: '' + url: https://www.acer.org/au/conquest + url_cran: https://CRAN.R-project.org/package=conquestr + url_git: '' +conrad: + version: 1.0.0.1 + title: |- + Client for the Microsoft's 'Cognitive Services Text to Speech + REST' API + maintainer: Howard Baek + description: |- + Convert text into synthesized speech and get a list of supported voices for a region. + Microsoft's 'Cognitive Services Text to Speech REST' API + supports neural text to speech voices, which support specific languages and dialects that are identified by locale. + date_publication: '2024-08-19' + bug_reports: https://github.com/fhdsl/conrad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conrad + url_git: https://github.com/fhdsl/conrad +ConsensusClustering: + version: 1.5.0 + title: Consensus Clustering + maintainer: Behnam Yousefi + description: 'Clustering, or cluster analysis, is a widely used technique in bioinformatics + to identify groups of similar biological data points. Consensus clustering is + an extension to clustering algorithms that aims to construct a robust result from + those clustering features that are invariant under different sources of variation. + For the reference, please cite the following paper: Yousefi, Melograna, et. al., + (2023) .' + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConsensusClustering + url_git: '' +ConsensusOPLS: + version: 1.1.0 + title: Consensus OPLS for Multi-Block Data Fusion + maintainer: Van Du T. Tran + description: |- + Merging data from multiple sources is a relevant approach for + comprehensively evaluating complex systems. However, the inherent problems + encountered when analyzing single tables are amplified with the generation + of multi-block datasets, and finding the relationships between data layers + of increasing complexity constitutes a challenging task. For that purpose, + a generic methodology is proposed by combining the strength of established + data analysis strategies, i.e. multi-block approaches and the Orthogonal + Partial Least Squares (OPLS) framework to provide an efficient tool for the + fusion of data obtained from multiple sources. The package enables quick + and efficient implementation of the consensus OPLS model for any horizontal + multi-block data structures (observation-based matching). Moreover, it + offers an interesting range of metrics and graphics to help to determine + the optimal number of components and check the validity of the model + through permutation tests. Interpretation tools include score and loading + plots, Variable Importance in Projection (VIP), functionality predict for + SHAP computing, and performance coefficients such as R2, Q2, and DQ2 + coefficients. + J. Boccard and D.N. Rutledge (2013) . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConsensusOPLS + url_git: '' +conserveR: + version: 1.0.4 + title: |- + Identifying Conservation Prioritization Methods Based on Data + Availability + maintainer: Alexander Zizka + description: Helping biologists to choose the most suitable approach to link their + research to conservation. After answering few questions on the data available, + geographic and taxonomic scope, 'conserveR' ranks existing methods for conservation + prioritization and systematic conservation planning by suitability. The methods + data base of 'conserveR' contains 133 methods for conservation prioritization + based on a systematic review of > 12,000 scientific publications from the fields + of spatial conservation prioritization, systematic conservation planning, biogeography + and ecology. + date_publication: '2021-08-02' + bug_reports: https://github.com/azizka/conserveR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conserveR + url_git: https://github.com/azizka/conserveR +consibiocloudclient: + version: 1.0.0 + title: A Client for the 'Consibio Cloud' API + maintainer: Tobias Nordahl + description: |- + Enable seamless interaction with 'Consibio Cloud' + 'API' + . This package provides tools + to query data from resources like projects, elements, devices, and + datalogs. + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=consibiocloudclient + url_git: '' +consolechoice: + version: 1.1.1 + title: |- + An Easy and Quick Way to Loop a Character Vector as a Menu in + the Console + maintainer: John Piper + description: |- + A fast way to loop a character vector or file names as a menu in the console for the + user to choose an option. + date_publication: '2022-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=consolechoice + url_git: '' +consort: + version: 1.2.2 + title: Create Consort Diagram + maintainer: Alim Dayim + description: To make it easy to create CONSORT diagrams for the transparent reporting + of participant allocation in randomized, controlled clinical trials. This is done + by creating a standardized disposition data, and using this data as the source + for the creation a standard CONSORT diagram. Human effort by supplying text labels + on the node can also be achieved. + date_publication: '2024-06-04' + bug_reports: https://github.com/adayim/consort/issues + url: '' + url_cran: https://CRAN.R-project.org/package=consort + url_git: https://github.com/adayim/consort/ +consortr: + version: 0.9.1 + title: Interactive Consort Flow Diagrams + maintainer: Daniel Backenroth + description: Shiny app for creating interactive consort flow diagrams and other + types of flow diagrams, see Moher, Schulz and Altman (2001) . + date_publication: '2021-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=consortr + url_git: '' +ConSpline: + version: '1.2' + title: |- + Partial Linear Least-Squares Regression using Constrained + Splines + maintainer: Mary C Meyer + description: Given response y, continuous predictor x, and covariate matrix, the + relationship between E(y) and x is estimated with a shape constrained regression + spline. Function outputs fits and various types of inference. + date_publication: '2017-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConSpline + url_git: '' +ConsRank: + version: 2.1.4 + title: |- + Compute the Median Ranking(s) According to the Kemeny's + Axiomatic Approach + maintainer: Antonio D'Ambrosio + description: |- + Compute the median ranking according to the Kemeny's axiomatic approach. + Rankings can or cannot contain ties, rankings can be both complete or incomplete. + The package contains both branch-and-bound algorithms and heuristic solutions recently proposed. + The searching space of the solution can either be restricted to the universe of the permutations or unrestricted to all possible ties. + The package also provide some useful utilities for deal with preference rankings, including both element-weight Kemeny distance and correlation coefficient. + This release declare as deprecated some functions that are still in the package for compatibility. Next release will not contains these functions. + Please type '?ConsRank-deprecated' + Essential references: + Emond, E.J., and Mason, D.W. (2002) ; + D'Ambrosio, A., Amodio, S., and Iorio, C. (2015) ; + Amodio, S., D'Ambrosio, A., and Siciliano R. (2016) ; + D'Ambrosio, A., Mazzeo, G., Iorio, C., and Siciliano, R. (2017) ; + Albano, A., and Plaia, A. (2021) . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConsRank + url_git: '' +ConsRankClass: + version: 1.0.1 + title: Classification and Clustering of Preference Rankings + maintainer: Antonio D'Ambrosio + description: |- + Tree-based classification and soft-clustering method for preference rankings, with tools for external validation of fuzzy clustering. + It contains the recursive partitioning algorithm for preference rankings, non-parametric tree-based method for a matrix of preference rankings as a response variable. It contains also the distribution-free soft clustering method for preference rankings, namely the K-median cluster component analysis (CCA). + The package depends on the 'ConsRank' R package. + Options for validate the tree-based method are both test-set procedure and V-fold cross validation. + The package contains the routines to compute the adjusted concordance index (a fuzzy version of the adjusted rand index) and the normalized degree of concordance (the corresponding fuzzy version of the rand index). + Essential references: + D'Ambrosio, A., Amodio, S., Iorio, C., Pandolfo, G., and Siciliano, R. (2021) + D'Ambrosio, A., and Heiser, W.J. (2019) ; + D'Ambrosio, A., and Heiser W.J. (2016) ; + Hullermeier, E., Rifqi, M., Henzgen, S., and Senge, R. (2012) . + date_publication: '2021-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConsRankClass + url_git: '' +ConsReg: + version: 0.1.0 + title: |- + Fits Regression & ARMA Models Subject to Constraints to the + Coefficient + maintainer: Josep Puig + description: |- + Fits or generalized linear models either a regression with Autoregressive moving-average (ARMA) errors for time series data. + The package makes it easy to incorporate constraints into the model's coefficients. + The model is specified by an objective function (Gaussian, Binomial or Poisson) or an ARMA order (p,q), + a vector of bound constraints + for the coefficients (i.e beta1 > 0) and the possibility to incorporate restrictions + among coefficients (i.e beta1 > beta2). + The references of this packages are the same as 'stats' package for glm() and arima() functions. + See Brockwell, P. J. and Davis, R. A. (1996, ISBN-10: 9783319298528). + For the different optimizers implemented, it is recommended to consult the documentation of the corresponding packages. + date_publication: '2020-04-05' + bug_reports: https://github.com/puigjos/ConsReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ConsReg + url_git: https://github.com/puigjos/ConsReg +consrq: + version: '1.0' + title: Constrained Quantile Regression + maintainer: Michail Tsagris + description: 'Constrained quantile regression is performed. One constraint is that + all beta coefficients (including the constant) cannot be negative, they can be + either 0 or strictly positive. Another constraint is that the beta coefficients + lie within an interval. References: Koenker R. (2005) Quantile Regression, Cambridge + University Press. .' + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=consrq + url_git: '' +constants: + version: 1.0.1 + title: Reference on Constants, Units and Uncertainty + maintainer: Iñaki Ucar + description: |- + CODATA internationally recommended values of the fundamental + physical constants, provided as symbols for direct use within the R language. + Optionally, the values with uncertainties and/or units are also provided if + the 'errors', 'units' and/or 'quantities' packages are installed. + The Committee on Data for Science and Technology (CODATA) is an + interdisciplinary committee of the International Council for Science which + periodically provides the internationally accepted set of values of the + fundamental physical constants. This package contains the "2018 CODATA" + version, published on May 2019: + Eite Tiesinga, Peter J. Mohr, David B. Newell, and Barry N. Taylor (2020) + . + date_publication: '2021-02-25' + bug_reports: https://github.com/r-quantities/constants/issues + url: '' + url_cran: https://CRAN.R-project.org/package=constants + url_git: https://github.com/r-quantities/constants +constellation: + version: 0.2.0 + title: Identify Event Sequences Using Time Series Joins + maintainer: Mark Sendak + description: |- + Examine any number of time series data frames to identify + instances in which various criteria are met within specified time + frames. In clinical medicine, these types of events are often + called "constellations of signs and symptoms", because a single + condition depends on a series of events occurring within a certain + amount of time of each other. This package was written to work with + any number of time series data frames and is optimized for speed + to work well with data frames with millions of rows. + date_publication: '2018-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=constellation + url_git: https://github.com/marksendak/constellation +constrainedKriging: + version: 0.2-11 + title: |- + Constrained, Covariance-Matching Constrained and Universal Point + or Block Kriging + maintainer: Andreas Papritz + description: 'Provides functions for efficient computation of non-linear spatial + predictions with local change of support (Hofer, C. and Papritz, A. (2011) "constrainedKriging: + An R-package for customary, constrained and covariance-matching constrained point + or block kriging" ). This package supplies functions + for two-dimensional spatial interpolation by constrained (Cressie, N. (1993) "Aggregation + in geostatistical problems" ), covariance-matching + constrained (Aldworth, J. and Cressie, N. (2003) "Prediction of nonlinear spatial + functionals" ) and universal (external drift) + Kriging for points or blocks of any shape from data with a non-stationary mean + function and an isotropic weakly stationary covariance function. The linear spatial + interpolation methods, constrained and covariance-matching constrained Kriging, + provide approximately unbiased prediction for non-linear target values under change + of support. This package extends the range of tools for spatial predictions available + in R and provides an alternative to conditional simulation for non-linear spatial + prediction problems with local change of support.' + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=constrainedKriging + url_git: '' +conStruct: + version: 1.0.6 + title: |- + Models Spatially Continuous and Discrete Population Genetic + Structure + maintainer: Gideon Bradburd + description: |- + A method for modeling genetic data as a combination of discrete + layers, within each of which relatedness may decay continuously with geographic + distance. This package contains code for running analyses (which are implemented + in the modeling language 'rstan') and visualizing and interpreting output. See the + paper for more details on the model and its utility. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=conStruct + url_git: '' +constructive: + version: 1.1.0 + title: Display Idiomatic Code to Construct Most R Objects + maintainer: Antoine Fabri + description: |- + Prints code that can be used to recreate R objects. In a + sense it is similar to 'base::dput()' or 'base::deparse()' but + 'constructive' strives to use idiomatic constructors. + date_publication: '2025-01-10' + bug_reports: https://github.com/cynkra/constructive/issues + url: https://cynkra.github.io/constructive/ + url_cran: https://CRAN.R-project.org/package=constructive + url_git: https://github.com/cynkra/constructive +contactdata: + version: 1.1.0 + title: Social Contact Matrices for 177 Countries + maintainer: Hugo Gruson + description: |- + Data package for the supplementary data in Prem et al. (2017) + and Prem et al. + . + Provides easy access to contact data for 177 countries, for use in + epidemiological, demographic or social sciences research. + date_publication: '2024-09-25' + bug_reports: https://github.com/bisaloo/contactdata/issues + url: https://hugogruson.fr/contactdata/ + url_cran: https://CRAN.R-project.org/package=contactdata + url_git: https://github.com/bisaloo/contactdata +container: + version: 1.0.5 + title: Extending Base 'R' Lists + maintainer: Roman Pahl + description: |- + Extends the functionality of base 'R' lists and + provides specialized data structures 'deque', + 'set', 'dict', and 'dict.table', the latter to extend the 'data.table' + package. + date_publication: '2024-12-02' + bug_reports: https://github.com/rpahl/container/issues + url: https://rpahl.github.io/container/ + url_cran: https://CRAN.R-project.org/package=container + url_git: https://github.com/rpahl/container +ContaminatedMixt: + version: 1.3.8 + title: Clustering and Classification with the Contaminated Normal + maintainer: Angelo Mazza + description: |- + Fits mixtures of multivariate contaminated normal distributions + (with eigen-decomposed scale matrices) via the expectation conditional- + maximization algorithm under a clustering or classification paradigm + Methods are described in Antonio Punzo, Angelo Mazza, and Paul D McNicholas (2018) . + date_publication: '2023-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ContaminatedMixt + url_git: '' +contentid: + version: 0.0.19 + title: An Interface for Content-Based Identifiers + maintainer: Carl Boettiger + description: |- + An interface for creating, registering, and resolving content-based + identifiers for data management. Content-based identifiers rely on + the 'cryptographic' hashes to refer to the files they identify, thus, + anyone possessing the file can compute the identifier using a + well-known standard algorithm, such as 'SHA256'. By registering + a URL at which the content is accessible to a public archive (such as + Hash Archive) or depositing data in a scientific repository such 'Zenodo', + 'DataONE' or 'SoftwareHeritage', the content identifier can serve + many functions typically associated with A Digital Object Identifier + ('DOI'). Unlike location-based identifiers like 'DOIs', content-based + identifiers permit the same content to be registered in many locations. + date_publication: '2025-01-21' + bug_reports: https://github.com/cboettig/contentid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=contentid + url_git: https://github.com/cboettig/contentid +conText: + version: 1.4.3 + title: '''a la Carte'' on Text (ConText) Embedding Regression' + maintainer: Pedro L. Rodriguez + description: |- + A fast, flexible and transparent framework to estimate context-specific word and short document embeddings using the 'a la carte' + embeddings approach developed by Khodak et al. (2018) and evaluate hypotheses about covariate effects on embeddings using + the regression framework developed by Rodriguez et al. (2021). + date_publication: '2023-02-09' + bug_reports: https://github.com/prodriguezsosa/ConText/issues + url: '' + url_cran: https://CRAN.R-project.org/package=conText + url_git: https://github.com/prodriguezsosa/EmbeddingRegression +contfrac: + version: 1.1-12 + title: Continued Fractions + maintainer: Robin K. S. Hankin + description: Various utilities for evaluating continued fractions. + date_publication: '2018-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=contfrac + url_git: https://github.com/RobinHankin/contfrac.git +contFracR: + version: 1.2.1 + title: Continued Fraction Generators and Evaluators + maintainer: Carl Witthoft + description: Converts numbers to continued fractions and back again. A solver for + Pell's Equation is provided. The method for calculating roots in continued fraction + form is provided without published attribution in such places as Professor Emeritus + Jonathan Lubin, and his post to StackOverflow, + , or Professor Ron Knott, e.g., + . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=contFracR + url_git: '' +contingency: + version: 0.0.10 + title: Discrete Multivariate Probability Distributions + maintainer: Robin Evans + description: |- + Provides an object class for dealing with many multivariate + probability distributions at once, useful for simulation. + date_publication: '2022-11-18' + bug_reports: https://github.com/rje42/contingency/issues + url: '' + url_cran: https://CRAN.R-project.org/package=contingency + url_git: https://github.com/rje42/contingency +contingencytables: + version: 3.0.1 + title: Statistical Analysis of Contingency Tables + maintainer: Waldir Leoncio + description: Provides functions to perform statistical inference of data organized + in contingency tables. This package is a companion to the "Statistical Analysis + of Contingency Tables" book by Fagerland et al. . + date_publication: '2024-08-29' + bug_reports: https://github.com/ocbe-uio/contingencytables/issues + url: https://contingencytables.com/https://ocbe-uio.github.io/contingencytables/ + url_cran: https://CRAN.R-project.org/package=contingencytables + url_git: '' +contoureR: + version: 1.0.5 + title: Contouring of Non-Regular Three-Dimensional Data + maintainer: Nicholas Hamilton + description: Create contour lines for a non regular series of points, potentially + from a non-regular canvas. + date_publication: '2015-08-25' + bug_reports: '' + url: http://contoureR.com + url_cran: https://CRAN.R-project.org/package=contoureR + url_git: '' +ContourFunctions: + version: 0.1.2 + title: Create Contour Plots from Data or a Function + maintainer: Collin Erickson + description: |- + Provides functions for making contour plots. + The contour plot can be created from grid data, a function, + or a data set. If non-grid data is given, then a Gaussian + process is fit to the data and used to create the contour plot. + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ContourFunctions + url_git: https://github.com/CollinErickson/ContourFunctions +contourPlot: + version: 0.2.0 + title: Plots x,y,z Co-Ordinates in a Contour Map + maintainer: Tony Murphy + description: Plots a set of x,y,z co-ordinates in a contour map. Designed to be + similar to plots in base R so additional elements can be added using lines(), + points() etc. This package is intended to be better suited, than existing packages, + to displaying circular shaped plots such as those often seen in the semi-conductor + industry. + date_publication: '2020-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=contourPlot + url_git: '' +contrast: + version: 0.24.2 + title: A Collection of Contrast Methods + maintainer: Alan O'Callaghan + description: One degree of freedom contrasts for 'lm', 'glm', 'gls', and 'geese' + objects. + date_publication: '2022-10-05' + bug_reports: https://github.com/Alanocallaghan/contrast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=contrast + url_git: https://github.com/Alanocallaghan/contrast +contrastable: + version: 1.0.2 + title: Consistent Contrast Coding for Factors + maintainer: Thomas Sostarics + description: Quickly set and summarize contrasts for factors prior to regression analyses. + Intended comparisons, baseline conditions, and intercepts can be explicitly set + and documented without the user needing to directly manipulate matrices. Reviews + and introductions for contrast coding are available in Brehm and Alday (2022) + and Schad et al. (2020). + date_publication: '2024-10-01' + bug_reports: https://github.com/tsostarics/contrastable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=contrastable + url_git: https://github.com/tsostarics/contrastable +conTree: + version: 0.3-1 + title: Contrast Trees and Boosting + maintainer: Balasubramanian Narasimhan + description: |- + Contrast trees represent a new approach for assessing the + accuracy of many types of machine learning estimates that are not + amenable to standard (cross) validation methods; see "Contrast + trees and distribution boosting", Jerome H. Friedman (2020) + . In situations where inaccuracies + are detected, boosted contrast trees can often improve + performance. Functions are provided to to build such trees in + addition to a special case, distribution boosting, an assumption + free method for estimating the full probability distribution of an + outcome variable given any set of joint input predictor variable + values. + date_publication: '2023-11-22' + bug_reports: https://github.com/bnaras/conTree/issues + url: https://jhfhub.github.io/conTree_tutorial/ + url_cran: https://CRAN.R-project.org/package=conTree + url_git: '' +ContRespPP: + version: 0.4.2 + title: |- + Predictive Probability for a Continuous Response with an ANOVA + Structure + maintainer: Victoria Sieck + description: |- + A Bayesian approach to using + predictive probability in an ANOVA construct with a continuous normal response, + when threshold values must be obtained for the question of interest to be + evaluated as successful (Sieck and Christensen (2021) ). + The Bayesian Mission Mean (BMM) is used to evaluate a question + of interest (that is, a mean that randomly selects combination of factor levels + based on their probability of occurring instead of averaging over the factor + levels, as in the grand mean). Under this construct, in contrast to a Gibbs + sampler (or Metropolis-within-Gibbs sampler), a two-stage sampling method is + required. The nested sampler determines the conditional posterior distribution + of the model parameters, given Y, and the outside sampler determines the marginal + posterior distribution of Y (also commonly called the predictive distribution for Y). + This approach provides a sample from the joint posterior distribution of Y and + the model parameters, while also accounting for the threshold value that must be + obtained in order for the question of interest to be evaluated as successful. + date_publication: '2022-10-15' + bug_reports: https://github.com/jcliff89/ContRespPP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ContRespPP + url_git: https://github.com/jcliff89/ContRespPP +contribution: + version: 0.2.2 + title: A Tiny Contribution Table Generator Based on 'ggplot2' + maintainer: Shixiang Wang + description: |- + Contribution table for credit assignment based on 'ggplot2'. + This can improve the author contribution information in academic journals and personal CV. + date_publication: '2022-03-23' + bug_reports: https://github.com/openbiox/contribution/issues + url: '' + url_cran: https://CRAN.R-project.org/package=contribution + url_git: https://github.com/openbiox/contribution +control: + version: 0.2.5 + title: A Control Systems Toolbox + maintainer: Ben C. Ubah + description: Solves control systems problems relating to time/frequency response, + LTI systems design and analysis, transfer function manipulations, and system conversion. + date_publication: '2017-12-12' + bug_reports: https://github.com/benubah/control/issues + url: '' + url_cran: https://CRAN.R-project.org/package=control + url_git: '' +controlfunctionIV: + version: 0.1.1 + title: |- + Control Function Methods with Possibly Invalid Instrumental + Variables + maintainer: Zijian Guo + description: Inference with control function methods for nonlinear outcome models + when the model is known ('Guo and Small' (2016) ) and when unknown + but semiparametric ('Li and Guo' (2021) ). + date_publication: '2022-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=controlfunctionIV + url_git: https://github.com/zijguo/controlfunctionIV +controlTest: + version: 1.1.0 + title: Quantile Comparison for Two-Sample Right-Censored Survival Data + maintainer: Eric S. Kawaguchi + description: Nonparametric two-sample procedure for comparing survival quantiles. + date_publication: '2017-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=controlTest + url_git: '' +contsurvplot: + version: 0.2.1 + title: |- + Visualize the Effect of a Continuous Variable on a Time-to-Event + Outcome + maintainer: Robin Denz + description: |- + Graphically display the (causal) effect of a continuous variable on a time-to-event outcome + using multiple different types of plots based on g-computation. Those functions + include, among others, survival area plots, survival contour plots, survival quantile plots and + 3D surface plots. Due to the use of g-computation, all plot allow confounder-adjustment naturally. + For details, see Robin Denz, Nina Timmesfeld (2023) . + date_publication: '2023-08-15' + bug_reports: https://github.com/RobinDenz1/contsurvplot/issues + url: https://robindenz1.github.io/contsurvplot/ + url_cran: https://CRAN.R-project.org/package=contsurvplot + url_git: https://github.com/RobinDenz1/contsurvplot +contTimeCausal: + version: '1.1' + title: Continuous Time Causal Models + maintainer: Shannon T. Holloway + description: |- + Implements the semiparametric efficient estimators of + continuous-time causal models for time-varying treatments and confounders + in the presence of dependent censoring (including structural failure time + model and Cox proportional hazards marginal structural model). + S. Yang, K. Pieper, and F. Cools (2019) . + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=contTimeCausal + url_git: '' +convdistr: + version: 1.6.2 + title: Convolute Probabilistic Distributions + maintainer: Aponte John + description: |- + Convolute probabilistic distributions using the random generator + function of each distribution. A new random number generator function is created that + perform the mathematical operation on the individual random samples from the + random generator function of each distribution. See the documentation for examples. + date_publication: '2024-05-05' + bug_reports: '' + url: https://johnaponte.github.io/convdistr/ + url_cran: https://CRAN.R-project.org/package=convdistr + url_git: https://github.com/johnaponte/convdistr +ConvergenceClubs: + version: 2.2.5 + title: Finding Convergence Clubs + maintainer: Roberto Sichera + description: Functions for clustering regions that form convergence clubs, according + to the definition of Phillips and Sul (2009) . A package + description is available in Sichera and Pizzuto (2019). + date_publication: '2024-01-27' + bug_reports: https://github.com/rhobis/ConvergenceClubs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ConvergenceClubs + url_git: '' +ConvergenceConcepts: + version: 1.2.3 + title: Seeing Convergence Concepts in Action + maintainer: Pierre Lafaye De Micheaux + description: |- + This is a pedagogical package, designed to help students understanding convergence of + random variables. It provides a way to investigate interactively various modes of + convergence (in probability, almost surely, in law and in mean) of a sequence of i.i.d. + random variables. Visualisation of simulated sample paths is possible through interactive + plots. The approach is illustrated by examples and exercises through the function + 'investigate', as described in + Lafaye de Micheaux and Liquet (2009) . + The user can study his/her own sequences of random variables. + date_publication: '2022-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConvergenceConcepts + url_git: '' +convergEU: + version: 0.7.3.2 + title: Monitoring Convergence of EU Countries + maintainer: Eleonora Peruffo + description: |- + Indicators and measures by country and time describe + what happens at economic and social levels. This package provides + functions to calculate several measures of convergence after imputing + missing values. The automated downloading of Eurostat data, + followed by the production of country fiches and indicator fiches, + makes possible to produce automated reports. + The Eurofound report () + "Upward convergence in the EU: Concepts, measurements and indicators", + 2018, is a detailed presentation of convergence. + date_publication: '2024-01-21' + bug_reports: '' + url: https://www.eurofound.europa.eu/system/files/2022-04/introduction-to-the-convergeu-package-0.6.4-tutorial-v2-apr2022.pdf + url_cran: https://CRAN.R-project.org/package=convergEU + url_git: '' +conversim: + version: 0.1.0 + title: Conversation Similarity Analysis + maintainer: Chao Liu + description: |- + Analyze and compare conversations using various similarity measures + including topic, lexical, semantic, structural, stylistic, sentiment, + participant, and timing similarities. Supports both pairwise conversation + comparisons and analysis of multiple dyads. Methods are based on established research: + Topic modeling: Blei et al. (2003) ; + Landauer et al. (1998) ; + Lexical similarity: Jaccard (1912) ; + Semantic similarity: Salton & Buckley (1988) ; + Mikolov et al. (2013) ; + Pennington et al. (2014) ; + Structural and stylistic analysis: Graesser et al. (2004) ; + Sentiment analysis: Rinker (2019) . + date_publication: '2024-09-20' + bug_reports: https://github.com/chaoliu-cl/conversim/issues + url: http://liu-chao.site/conversim/ + url_cran: https://CRAN.R-project.org/package=conversim + url_git: https://github.com/chaoliu-cl/conversim +convertBCD: + version: '1.0' + title: |- + Convert Decimal to Binary-Coded Decimal (BCD) Form and Vice + Versa + maintainer: Carl Witthoft + description: Convert BCD (raw bytes) to decimal numbers and vice versa. BCD format + is used to preserve decimals exactly, as opposed to the binary rounding errors + inherent in "numeric" or "floating-point" formats. + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=convertBCD + url_git: '' +convertbonds: + version: 0.1.0 + title: Use the Given Parameters to Calculate the European Option Value + maintainer: Tai-Sen Zheng + description: Calculate the theoretical value of convertible bonds by given parameters, + including B-S theory and Monte Carlo method. + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=convertbonds + url_git: '' +convertid: + version: 0.1.10 + title: |- + Convert Gene IDs Between Each Other and Fetch Annotations from + Biomart + maintainer: Vidal Fey + description: |- + Gene Symbols or Ensembl Gene IDs are converted using the Bimap interface in 'AnnotationDbi' in convertId2() but + that function is only provided as fallback mechanism for the most common use cases in data analysis. The main function + in the package is convert.bm() which queries BioMart using the full capacity of the API provided through the + 'biomaRt' package. Presets and defaults are provided for convenience but all "marts", "filters" and "attributes" + can be set by the user. Function convert.alias() converts Gene Symbols to Aliases and vice versa and function likely_symbol() + attempts to determine the most likely current Gene Symbol. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=convertid + url_git: '' +ConvertPar: + version: '0.1' + title: Estimating IRT Parameters via Machine Learning Algorithms + maintainer: Eda Akdogdu Yildiz + description: A tool to estimate IRT item parameters (2 PL) using CTT-based item + statistics from small samples via artificial neural networks and regression trees. + date_publication: '2022-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ConvertPar + url_git: '' +convertr: + version: '0.1' + title: Convert Between Units + maintainer: Gordon Shotwell + description: |- + Provides conversion functionality between a broad range of + scientific, historical, and industrial unit types. + date_publication: '2016-10-13' + bug_reports: https://github.com/GShotwell/convertr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=convertr + url_git: '' +convevol: + version: 2.2.1 + title: Analysis of Convergent Evolution + maintainer: C. Tristan Stayton + description: 'Quantifies and assesses the significance of convergent evolution using + multiple methods and measures as described in Stayton (2015) + and Grossnickle et al. 2023. Also displays results in various ways.' + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=convevol + url_git: '' +convey: + version: 1.0.1 + title: Income Concentration Analysis with Complex Survey Samples + maintainer: Anthony Damico + description: |- + Variance estimation on indicators of income concentration and + poverty using complex sample survey designs. Wrapper around the + 'survey' package. + date_publication: '2024-10-16' + bug_reports: https://github.com/ajdamico/convey/issues + url: https://www.convey-r.org/ + url_cran: https://CRAN.R-project.org/package=convey + url_git: '' +Convolutioner: + version: 0.1.0 + title: Convolution of Data + maintainer: Federico Maria Vivaldi + description: |- + General functions for convolutions of data. Moving average, running median, and other filters are available. + Bibliography regarding the functions can be found in the following text. + Richard G. Brereton (2003) . + date_publication: '2021-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Convolutioner + url_git: '' +convoSPAT: + version: 1.2.7 + title: Convolution-Based Nonstationary Spatial Modeling + maintainer: Mark D. Risser + description: |- + Fits convolution-based nonstationary + Gaussian process models to point-referenced spatial data. The nonstationary + covariance function allows the user to specify the underlying correlation + structure and which spatial dependence parameters should be allowed to + vary over space: the anisotropy, nugget variance, and process variance. + The parameters are estimated via maximum likelihood, using a local + likelihood approach. Also provided are functions to fit stationary spatial + models for comparison, calculate the Kriging predictor and standard errors, + and create various plots to visualize nonstationarity. + date_publication: '2021-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=convoSPAT + url_git: http://github.com/markdrisser/convoSPAT +cooccur: + version: '1.3' + title: Probabilistic Species Co-Occurrence Analysis in R + maintainer: Daniel M. Griffith + description: This R package applies the probabilistic model of species co-occurrence + (Veech 2013) to a set of species distributed among a set of survey or sampling + sites. The algorithm calculates the observed and expected frequencies of co-occurrence + between each pair of species. The expected frequency is based on the distribution + of each species being random and independent of the other species. The analysis + returns the probabilities that a more extreme (either low or high) value of co-occurrence + could have been obtained by chance. The package also includes functions for visualizing + species co-occurrence results and preparing data for downstream analyses. + date_publication: '2016-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cooccur + url_git: '' +CooccurrenceAffinity: + version: '1.0' + title: Affinity in Co-Occurrence Data + maintainer: Kumar Mainali + description: |- + Computes a novel metric of affinity between two entities based on their co-occurrence + (using binary presence/absence data). The metric and its MLE, alpha hat, were advanced in + Mainali, Slud, et al, 2021 . Various types of confidence intervals and median interval + were developed in Mainali and Slud, 2022 . + date_publication: '2023-05-03' + bug_reports: https://github.com/kpmainali/CooccurrenceAffinity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CooccurrenceAffinity + url_git: https://github.com/kpmainali/CooccurrenceAffinity +cookiecutter: + version: 0.1.0 + title: Generate Project Files from a Template + maintainer: Felix Henninger + description: |- + Generate project files and directories following a pre-made template. + You can specify variables to customize file names and content, and + flexibly adapt the template to your needs. 'cookiecutter' for 'R' + implements a subset of the excellent 'cookiecutter' package for the + 'Python' programming language (), and + aims to be largely compatible with the original 'cookiecutter' template + format. + date_publication: '2023-09-08' + bug_reports: https://github.com/FelixHenninger/cookiecutter/issues + url: https://felixhenninger.github.io/cookiecutter/ + url_cran: https://CRAN.R-project.org/package=cookiecutter + url_git: https://github.com/felixhenninger/cookiecutter/ +cookiemonster: + version: 0.0.3 + title: Your Friendly Solution to Managing Browser Cookies + maintainer: Johannes B. Gruber + description: |- + A convenient tool to store and format browser cookies and use them + in 'HTTP' requests (for example, through 'httr2', 'httr' or 'curl'). + date_publication: '2023-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cookiemonster + url_git: '' +cookies: + version: 0.2.3 + title: Use Browser Cookies with 'shiny' + maintainer: Jon Harmon + description: |- + Browser cookies are name-value pairs that are saved in a + user's browser by a website. Cookies allow websites to persist + information about the user and their use of the website. Here we + provide tools for working with cookies in 'shiny' apps, in part by + wrapping the 'js-cookie' JavaScript library + . + date_publication: '2023-10-02' + bug_reports: https://github.com/r4ds/cookies/issues + url: https://r4ds.github.io/cookies/ + url_cran: https://CRAN.R-project.org/package=cookies + url_git: https://github.com/r4ds/cookies +CoOL: + version: 1.1.2 + title: Causes of Outcome Learning + maintainer: Andreas Rieckmann + description: 'Implementing the computational phase of the Causes of Outcome Learning + approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, + Rod, Ekstrom. 2022. Causes of outcome learning: A causal inference-inspired machine + learning approach to disentangling common combinations of potential causes of + a health outcome. International Journal of Epidemiology . + The optional ''ggtree'' package can be obtained through Bioconductor.' + date_publication: '2022-05-24' + bug_reports: '' + url: https://bioconductor.org + url_cran: https://CRAN.R-project.org/package=CoOL + url_git: '' +cooltools: + version: '2.4' + title: Practical Tools for Scientific Computations and Visualizations + maintainer: Danail Obreschkow + description: Collection of routines for efficient scientific computations in physics + and astrophysics. These routines include utility functions, numerical computation + tools, as well as visualisation tools. They can be used, for example, for generating + random numbers from spherical and custom distributions, information and entropy + analysis, special Fourier transforms, two-point correlation estimation (e.g. as + in Landy & Szalay (1993) ), binning & gridding of point sets, + 2D interpolation, Monte Carlo integration, vector arithmetic and coordinate transformations. + Also included is a non-exhaustive list of important constants and cosmological + conversion functions. The graphics routines can be used to produce and export + publication-ready scientific plots and movies, e.g. as used in Obreschkow et al. + (2020, MNRAS Vol 493, Issue 3, Pages 4551–4569). These routines include special + color scales, projection functions, and bitmap handling routines. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cooltools + url_git: '' +coop: + version: 0.6-3 + title: |- + Co-Operation: Fast Covariance, Correlation, and Cosine + Similarity Operations + maintainer: Drew Schmidt + description: |- + Fast implementations of the co-operations: covariance, + correlation, and cosine similarity. The implementations are + fast and memory-efficient and their use is resolved + automatically based on the input data, handled by R's S3 + methods. Full descriptions of the algorithms and benchmarks + are available in the package vignettes. + date_publication: '2021-09-19' + bug_reports: https://github.com/wrathematics/coop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coop + url_git: https://github.com/wrathematics/coop +CoopGame: + version: 0.2.2 + title: Important Concepts of Cooperative Game Theory + maintainer: Jochen Staudacher + description: |- + The theory of cooperative games with transferable utility offers + useful insights into the way parties can share gains from cooperation and + secure sustainable agreements, see e.g. one of the books by Chakravarty, + Mitra and Sarkar (2015, ISBN:978-1107058798) or by Driessen (1988, + ISBN:978-9027727299) for more details. A comprehensive set of tools for + cooperative game theory with transferable utility is provided. Users can + create special families of cooperative games, like e.g. bankruptcy games, + cost sharing games and weighted voting games. There are functions to check + various game properties and to compute five different set-valued solution + concepts for cooperative games. A large number of point-valued solution + concepts is available reflecting the diverse application areas of + cooperative game theory. Some of these point-valued solution concepts can + be used to analyze weighted voting games and measure the influence of + individual voters within a voting body. There are routines for visualizing + both set-valued and point-valued solutions in the case of three or four + players. + date_publication: '2021-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoopGame + url_git: '' +CoordinateCleaner: + version: 3.0.1 + title: |- + Automated Cleaning of Occurrence Records from Biological + Collections + maintainer: Alexander Zizka + description: |- + Automated flagging of common spatial and temporal + errors in biological and paleontological collection data, for the use + in conservation, ecology and paleontology. Includes automated tests to + easily flag (and exclude) records assigned to country or province + centroid, the open ocean, the headquarters of the Global Biodiversity + Information Facility, urban areas or the location of biodiversity + institutions (museums, zoos, botanical gardens, universities). + Furthermore identifies per species outlier coordinates, zero + coordinates, identical latitude/longitude and invalid coordinates. + Also implements an algorithm to identify data sets with a significant + proportion of rounded coordinates. Especially suited for large data + sets. The reference for the methodology is: Zizka et al. (2019) + . + date_publication: '2023-10-24' + bug_reports: https://github.com/ropensci/CoordinateCleaner/issues + url: https://ropensci.github.io/CoordinateCleaner/ + url_cran: https://CRAN.R-project.org/package=CoordinateCleaner + url_git: '' +CooRTweet: + version: 2.1.0 + title: Coordinated Networks Detection on Social Media + maintainer: Nicola Righetti + description: Detects a variety of coordinated actions on social media and outputs + the network of coordinated users along with related information. + date_publication: '2025-01-09' + bug_reports: https://github.com/nicolarighetti/CooRTweet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CooRTweet + url_git: https://github.com/nicolarighetti/CooRTweet +copBasic: + version: 2.2.7 + title: General Bivariate Copula Theory and Many Utility Functions + maintainer: William Asquith + description: |- + Extensive functions for bivariate copula (bicopula) computations and related operations + for bicopula theory. The lower, upper, product, and select other bicopula are implemented along + with operations including the diagonal, survival copula, dual of a copula, co-copula, and + numerical bicopula density. Level sets, horizontal and vertical sections are supported. Numerical + derivatives and inverses of a bicopula are provided through which simulation is implemented. + Bicopula composition, convex combination, asymmetry extension, and products also are provided. + Support extends to the Kendall Function as well as the Lmoments thereof. Kendall Tau, + Spearman Rho and Footrule, Gini Gamma, Blomqvist Beta, Hoeffding Phi, Schweizer- + Wolff Sigma, tail dependency, tail order, skewness, and bivariate Lmoments are implemented, and + positive/negative quadrant dependency, left (right) increasing (decreasing) are available. + Other features include Kullback-Leibler Divergence, Vuong Procedure, spectral measure, and + Lcomoments for inference, maximum likelihood, and AIC, BIC, and RMSE for goodness-of-fit. + date_publication: '2025-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copBasic + url_git: '' +copCAR: + version: 2.0-4 + title: Fitting the copCAR Regression Model for Discrete Areal Data + maintainer: John Hughes + description: |- + Provides tools for fitting the copCAR (Hughes, 2015) + regression model for discrete + areal data. Three types of estimation are supported (continuous + extension, composite marginal likelihood, and distributional transform), + for three types of outcomes (Bernoulli, negative binomial, and Poisson). + date_publication: '2021-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copCAR + url_git: '' +copcor: + version: 2024.7-31 + title: Correlates of Protection and Correlates of Risk Functions + maintainer: Youyi Fong + description: Correlates of protection (CoP) and correlates of risk (CoR) study the + immune biomarkers associated with an infectious disease outcome, e.g. COVID or + HIV-1 infection. This package contains shared functions for analyzing CoP and + CoR, including bootstrapping procedures, competing risk estimation, and bootstrapping + marginalized risks. + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copcor + url_git: '' +CopCTS: + version: 1.0.0 + title: |- + Copula-Based Semiparametric Analysis for Time Series Data with + Detection Limits + maintainer: Fuyuan David Li + description: |- + Semiparametric estimation for censored time series + with lower detection limit. The latent response is a sequence of + stationary process with Markov property + of order one. + Estimation of copula parameter(COPC) and Conditional quantile estimation + are included for five available copula functions. + Copula selection methods based on L2 distance from empirical copula function + are also included. + date_publication: '2018-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopCTS + url_git: '' +cope: + version: 0.2.3 + title: Coverage Probability Excursion (CoPE) Sets + maintainer: Max Sommerfeld + description: |- + Provides functions to compute and plot Coverage + Probability Excursion (CoPE) sets + for real valued functions on a 2-dimensional domain. CoPE sets are obtained + from repeated noisy observations of the function on the entire domain. + They are designed to bound the excursion + set of the target function at a given level from above and below with + a predefined probability. The target + function can be a parameter in spatially-indexed linear regression. + Support by NIH grant R01 CA157528 is gratefully acknowledged. + date_publication: '2017-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cope + url_git: '' +copent: + version: '0.5' + title: Estimating Copula Entropy and Transfer Entropy + maintainer: MA Jian + description: The nonparametric methods for estimating copula entropy, transfer entropy, + and the statistics for multivariate normality test and two-sample test are implemented. + The methods for estimating transfer entropy and the statistics for multivariate + normality test and two-sample test are based on the method for estimating copula + entropy. The method for change point detection with copula entropy based two-sample + test is also implemented. Please refer to Ma and Sun (2011) , + Ma (2019) , Ma (2022) , + Ma (2023) , and Ma (2024) + for more information. + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copent + url_git: https://github.com/majianthu/copent +CopernicusDEM: + version: 1.0.5 + title: Copernicus Digital Elevation Models + maintainer: Lampros Mouselimis + description: Copernicus Digital Elevation Model datasets (DEM) of 90 and 30 meters + resolution using the 'awscli' command line tool. The Copernicus (DEM) is included + in the Registry of Open Data on 'AWS (Amazon Web Services)' and represents the + surface of the Earth including buildings, infrastructure and vegetation. + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopernicusDEM + url_git: https://github.com/mlampros/CopernicusDEM +CopernicusMarine: + version: 0.2.4 + title: |- + Search Download and Handle Data from Copernicus Marine Service + Information + maintainer: Pepijn de Vries + description: |- + Subset and download data from EU Copernicus Marine + Service Information: . + Import data on the oceans physical and biogeochemical state + from Copernicus into R without the need of external software. + date_publication: '2024-12-22' + bug_reports: https://github.com/pepijn-devries/CopernicusMarine/issues + url: https://pepijn-devries.github.io/CopernicusMarine/ + url_cran: https://CRAN.R-project.org/package=CopernicusMarine + url_git: https://github.com/pepijn-devries/CopernicusMarine +cophescan: + version: 1.4.1 + title: Adaptation of the Coloc Method for PheWAS + maintainer: Ichcha Manipur + description: |- + A Bayesian method for Phenome-wide association studies (PheWAS) that identifies causal associations between genetic variants and traits, while simultaneously addressing confounding due to linkage disequilibrium. For details see + Manipur et al (2023) . + date_publication: '2024-06-11' + bug_reports: https://github.com/ichcha-m/cophescan/issues + url: https://ichcha-m.github.io/cophescan/ + url_cran: https://CRAN.R-project.org/package=cophescan + url_git: https://github.com/ichcha-m/cophescan +coppeCosenzaR: + version: 0.1.3 + title: COPPE-Cosenza Fuzzy Hierarchy Model + maintainer: Pier Taranti + description: |- + The program implements the COPPE-Cosenza Fuzzy Hierarchy Model. + The model was based on the evaluation of local alternatives, representing + regional potentialities, so as to fulfill demands of economic projects. + After defining demand profiles in terms of their technological coefficients, + the degree of importance of factors is defined so as to represent + the productive activity. The method can detect a surplus of supply without + the restriction of the distance of classical algebra, defining a hierarchy + of location alternatives. In COPPE-Cosenza Model, the distance between + factors is measured in terms of the difference between grades of memberships + of the same factors belonging to two or more sets under comparison. The + required factors are classified under the following linguistic variables: + Critical (CR); Conditioning (C); Little Conditioning (LC); and Irrelevant + (I). And the alternatives can assume the following linguistic variables: + Excellent (Ex), Good (G), Regular (R), Weak (W), Empty (Em), Zero (Z) and + Inexistent (In). The model also provides flexibility, allowing different + aggregation rules to be performed and defined by the Decision Maker. Such + feature is considered in this package, allowing the user to define other + aggregation matrices, since it considers the same linguistic variables + mentioned. + date_publication: '2017-10-28' + bug_reports: https://github.com/ptaranti/coppeCosenzaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coppeCosenzaR + url_git: https://github.com/ptaranti/coppeCosenzaR +copre: + version: 0.2.1 + title: Tools for Nonparametric Martingale Posterior Sampling + maintainer: Blake Moya + description: |- + Performs Bayesian nonparametric density estimation using Martingale + posterior distributions including the Copula Resampling (CopRe) algorithm. + Also included are a Gibbs sampler for the marginal Gibbs-type mixture model and + an extension to include full uncertainty quantification via a predictive + sequence resampling (SeqRe) algorithm. The CopRe and SeqRe samplers generate + random nonparametric distributions as output, leading to complete nonparametric + inference on posterior summaries. Routines for calculating arbitrary + functionals from the sampled distributions are included as well as an important + algorithm for finding the number and location of modes, which can then be used + to estimate the clusters in the data using, for example, k-means. + Implements work developed in Moya B., Walker S. G. (2022). + , Fong, E., Holmes, C., Walker, S. G. (2021) + , and Escobar M. D., West, M. (1995) + . + date_publication: '2024-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copre + url_git: '' +cops: + version: 1.12-1 + title: Cluster Optimized Proximity Scaling + maintainer: Thomas Rusch + description: 'Multidimensional scaling (MDS) methods that aim at pronouncing the + clustered appearance of the configuration (Rusch, Mair & Hornik, 2021, ). + They achieve this by transforming proximities/distances with explicit power functions + and penalizing the fitting criterion with a clusteredness index, the OPTICS Cordillera + (Rusch, Hornik & Mair, 2018, ). There are two + variants: One for finding the configuration directly (COPS-C) with given explicit + power transformations and implicit ratio, interval and non-metric optimal scaling + transformations (Borg & Groenen, 2005, ISBN:978-0-387-28981-6), and one for using + the augmented fitting criterion to find optimal hyperparameters for the explicit + transformations (P-COPS). The package contains various functions, wrappers, methods + and classes for fitting, plotting and displaying a large number of different MDS + models (most of the functionality in smacofx) in the COPS framework. The package + further contains a function for pattern search optimization, the ``Adaptive Luus-Jaakola + Algorithm'''' (Rusch, Mair & Hornik, 2021,) + and a functions to calculate the phi-distances for count data or histograms.' + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cops + url_git: https://r-forge.r-project.org/projects/stops/ +CopSens: + version: 0.1.0 + title: |- + Copula-Based Sensitivity Analysis for Observational Causal + Inference + maintainer: Jiajing Zheng + description: |- + Implements the copula-based sensitivity analysis method, + as discussed in Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding + , with Gaussian copula adopted in particular. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopSens + url_git: https://github.com/JiajingZ/CopSens +copula: + version: 1.1-5 + title: Multivariate Dependence with Copulas + maintainer: Martin Maechler + description: |- + Classes (S4) of commonly used elliptical, Archimedean, + extreme-value and other copula families, as well as their rotations, + mixtures and asymmetrizations. Nested Archimedean copulas, related + tools and special functions. Methods for density, distribution, random + number generation, bivariate dependence measures, Rosenblatt transform, + Kendall distribution function, perspective and contour plots. Fitting of + copula models with potentially partly fixed parameters, including + standard errors. Serial independence tests, copula specification tests + (independence, exchangeability, radial symmetry, extreme-value + dependence, goodness-of-fit) and model selection based on + cross-validation. Empirical copula, smoothed versions, and + non-parametric estimators of the Pickands dependence function. + date_publication: '2025-02-09' + bug_reports: https://r-forge.r-project.org/tracker/?func=add&group_id=2140&atid=5417 + url: '' + url_cran: https://CRAN.R-project.org/package=copula + url_git: https://copula.r-forge.r-project.org/ +Copula.Markov: + version: '2.9' + title: |- + Copula-Based Estimation and Statistical Process Control for + Serially Correlated Time Series + maintainer: Takeshi Emura + description: |- + Estimation and statistical process control are performed under + copula-based time-series models. + Available are statistical methods in Long and Emura (2014 JCSA), + Emura et al. (2017 Commun Stat-Simul) , + Huang and Emura (2021 Commun Stat-Simul) , + Lin et al. (2021 Comm Stat-Simul) , + Sun et al. (2020 JSS Series in Statistics), + and Huang and Emura (2021, in revision). + date_publication: '2021-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Copula.Markov + url_git: '' +Copula.Markov.survival: + version: 1.0.0 + title: Copula Markov Model with Dependent Censoring + maintainer: Xin-Wei Huang + description: Perform likelihood estimation and corresponding analysis under the + copula-based Markov chain model for serially dependent event times with a dependent + terminal event. Available are statistical methods in Huang, Wang and Emura (2020, + JJSD accepted). + date_publication: '2020-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Copula.Markov.survival + url_git: '' +Copula.surv: + version: '1.8' + title: Analysis of Bivariate Survival Data Based on Copulas + maintainer: Takeshi Emura + description: |- + Simulating bivariate survival data from copula models. + Estimation of the association parameter in copula models. + Two different ways to estimate the association parameter in copula models are implemented. + A goodness-of-fit test for a given copula model is implemented. + See Emura, Lin and Wang (2010) for details. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Copula.surv + url_git: '' +copulaboost: + version: 0.1.0 + title: |- + Fitting Additive Copula Regression Models for Binary Outcome + Regression + maintainer: Simon Boge Brant + description: |- + Additive copula regression for regression + problems with binary outcome via gradient boosting + [Brant, Hobæk Haff (2022); ]. The fitting process + includes a specialised model selection algorithm for each component, where + each component is found (by greedy optimisation) among all the D-vines with + only Gaussian pair-copulas of a fixed dimension, as specified by the user. + When the variables and structure have been selected, the algorithm then + re-fits the component where the pair-copula distributions can be different + from Gaussian, if specified. + date_publication: '2022-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copulaboost + url_git: '' +CopulaCenR: + version: 1.2.4 + title: Copula-Based Regression Models for Multivariate Censored Data + maintainer: Tao Sun + description: |- + Copula-based regression models for multivariate censored data, including + bivariate right-censored data, bivariate interval-censored data, and right/interval-censored + semi-competing risks data. Currently supports Clayton, Gumbel, Frank, Joe, AMH and + Copula2 copula models. For marginal models, it supports parametric (Weibull, Loglogistic, + Gompertz) and semiparametric (Cox and transformation) models. Includes methods for + convenient prediction and plotting. Also provides a bivariate time-to-event simulation + function and an information ratio-based goodness-of-fit test for copula. Method details + can be found in Sun et.al (2019) Lifetime Data Analysis, Sun et.al (2021) Biostatistics, + Sun et.al (2022) Statistical Methods in Medical Research, Sun et.al (2022) Biometrics, and + Sun et al. (2023+) JRSSC. + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopulaCenR + url_git: '' +copulaData: + version: 0.0-2 + title: Data Sets for Copula Modeling + maintainer: Marius Hofert + description: |- + Data sets used for copula modeling in addition to those in + the R package 'copula'. These include a random subsample from the US National + Education Longitudinal Study (NELS) of 1988 and nursing home data from + Wisconsin. + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copulaData + url_git: https://copula.r-forge.r-project.org/ +CopulaGAMM: + version: 0.4.1 + title: Copula-Based Mixed Regression Models + maintainer: Bruno N Remillard + description: Estimation of 2-level factor copula-based regression models for clustered + data where the response variable can be either discrete or continuous. + date_publication: '2023-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopulaGAMM + url_git: '' +CopulaInference: + version: 0.5.0 + title: |- + Estimation and Goodness-of-Fit of Copula-Based Models with + Arbitrary Distributions + maintainer: Bouchra R. Nasri + description: 'Estimation and goodness-of-fit functions for copula-based models of + bivariate data with arbitrary distributions (discrete, continuous, mixture of + both types). The copula families considered here are the Gaussian, Student, Clayton, + Frank, Gumbel, Joe, Plackett, BB1, BB6, BB7,BB8, together with the following non-central + squared copula families in Nasri (2020) : ncs-gaussian, + ncs-clayton, ncs-gumbel, ncs-frank, ncs-joe, and ncs-plackett. For theoretical + details, see, e.g., Nasri and Remillard (2023) .' + date_publication: '2023-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopulaInference + url_git: '' +copulareg: + version: 0.1.0 + title: Copula Regression + maintainer: Simon Boge Brant + description: |2- + + Fits multivariate models in an R-vine pair copula construction framework, + in such a way that the conditional copula can be easily evaluated. + In addition, the package implements functionality to compute or approximate + the conditional expectation via the conditional copula. + date_publication: '2021-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copulareg + url_git: '' +CopulaREMADA: + version: 1.7.3 + title: |- + Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic + Test Accuracy Studies + maintainer: Aristidis K. Nikoloulopoulos + description: The bivariate copula mixed model for meta-analysis of diagnostic test + accuracy studies in Nikoloulopoulos (2015) and Nikoloulopoulos + (2018) . The vine copula mixed model for meta-analysis + of diagnostic test accuracy studies accounting for disease prevalence in Nikoloulopoulos + (2017) and also accounting for non-evaluable subjects + in Nikoloulopoulos (2020) . The hybrid vine copula + mixed model for meta-analysis of diagnostic test accuracy case-control and cohort + studies in Nikoloulopoulos (2018) . The D-vine copula + mixed model for meta-analysis and comparison of two diagnostic tests in Nikoloulopoulos + (2019) . The multinomial quadrivariate D-vine copula + mixed model for meta-analysis of diagnostic tests with non-evaluable subjects + in Nikoloulopoulos (2020) . The one-factor copula + mixed model for joint meta-analysis of multiple diagnostic tests in Nikoloulopoulos + (2022) . The multinomial six-variate 1-truncated D-vine + copula mixed model for meta-analysis of two diagnostic tests accounting for within + and between studies dependence in Nikoloulopoulos (2024) . + The 1-truncated D-vine copula mixed models for meta-analysis of diagnostic accuracy + studies without a gold standard (Nikoloulopoulos, 2024). + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CopulaREMADA + url_git: '' +copulaSim: + version: 0.0.1 + title: Virtual Patient Simulation by Copula Invariance Property + maintainer: Pei-Shan Yen + description: To optimize clinical trial designs and data analysis methods consistently + through trial simulation, we need to simulate multivariate mixed-type virtual + patient data independent of designs and analysis methods under evaluation. To + make the outcome of optimization more realistic, relevant empirical patient level + data should be utilized when it’s available. However, a few problems arise in + simulating trials based on small empirical data, where the underlying marginal + distributions and their dependence structure cannot be understood or verified + thoroughly due to the limited sample size. To resolve this issue, we use the copula + invariance property, which can generate the joint distribution without making + a strong parametric assumption. The function copula.sim can generate virtual patient + data with optional data validation methods that are based on energy distance and + ball divergence measurement. The function compare.copula.sim can conduct comparison + of marginal mean and covariance of simulated data. To simulate patient-level data + from a hypothetical treatment arm that would perform differently from the observed + data, the function new.arm.copula.sim can be used to generate new multivariate + data with the same dependence structure of the original data but with a shifted + mean vector. + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=copulaSim + url_git: https://github.com/psyen0824/copulaSim +copyseparator: + version: 1.2.0 + title: Assembling Long Gene Copies from Short Read Data + maintainer: Lei Yang + description: Assembles two or more gene copies from short-read Next-Generation Sequencing + data. Works best when there are only two gene copies and read length >=250 base + pairs. High and relatively even coverage are important. + date_publication: '2022-11-25' + bug_reports: https://github.com/LeiYang-Fish/copyseparator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=copyseparator + url_git: https://github.com/LeiYang-Fish/copyseparator +COR: + version: 0.2.0 + title: The COR for Optimal Subset Selection in Distributed Estimation + maintainer: Guangbao Guo + description: An algorithm of optimal subset selection, related to Covariance matrices, + observation matrices and Response vectors (COR) to select the optimal subsets + in distributed estimation. The philosophy of the package is described in Guo G. + (2024) . + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COR + url_git: '' +cora: + version: 0.1.0 + title: Cora Data for Entity Resolution + maintainer: Rebecca Steorts + description: 'Duplicated publication data (pre-processed and formatted) for entity + resolution. This data set contains a total of 1879 records. The following variables + are included in the data set: id, title, book title, authors, address, date, year, + editor, journal, volume, pages, publisher, institution, type, tech, note. The + data set has a respective gold data set that provides information on which records + match based on id.' + date_publication: '2020-10-13' + bug_reports: https://github.com/resteorts/cora/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cora + url_git: https://github.com/resteorts/cora +coRanking: + version: 0.2.5 + title: Co-Ranking Matrix + maintainer: Guido Kraemer + description: |- + Calculates the co-ranking matrix to assess the + quality of a dimensionality reduction. + date_publication: '2024-09-30' + bug_reports: https://github.com/gdkrmr/coRanking/issues + url: https://coranking.guido-kraemer.com/ + url_cran: https://CRAN.R-project.org/package=coRanking + url_git: '' +corazon: + version: 0.1.0 + title: Apply 'colorffy' Color Gradients Within 'shiny' Elements + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to apply nice color gradients to 'shiny' elements. + The gradients are extracted from the 'colorffy' website. See . + date_publication: '2020-06-28' + bug_reports: https://github.com/feddelegrand7/corazon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=corazon + url_git: https://github.com/feddelegrand7/corazon +CorBin: + version: 1.0.0 + title: |- + Generate High-Dimensional Binary Data with Correlation + Structures + maintainer: Shuang Song + description: We design algorithms with linear time complexity with respect to the + dimension for three commonly studied correlation structures, including exchangeable, + decaying-product and K-dependent correlation structures, and extend the algorithms + to generate binary data of general non-negative correlation matrices with quadratic + time complexity. Jiang, W., Song, S., Hou, L. and Zhao, H. "A set of efficient + methods to generate high-dimensional binary data with specified correlation structures." + The American Statistician. See for a detailed + presentation of the method. + date_publication: '2020-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CorBin + url_git: '' +corbouli: + version: 0.1.4 + title: Corbae-Ouliaris Frequency Domain Filtering + maintainer: Christos Adam + description: |- + Corbae-Ouliaris frequency domain filtering. According to + Corbae and Ouliaris (2006) , + this is a solution for extracting cycles from time series, like + business cycles etc. when filtering. This method is valid for both + stationary and non-stationary time series. + date_publication: '2025-01-09' + bug_reports: https://github.com/cadam00/corbouli/issues + url: https://cadam00.github.io/corbouli/ + url_cran: https://CRAN.R-project.org/package=corbouli + url_git: https://github.com/cadam00/corbouli +corclass: + version: 0.2.1 + title: Correlational Class Analysis + maintainer: Andrei Boutyline + description: Perform a correlational class analysis of the data, resulting in a + partition of the data into separate modules. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corclass + url_git: '' +cord: + version: 0.1.1 + title: Community Estimation in G-Models via CORD + maintainer: Xi (Rossi) LUO + description: Partition data points (variables) into communities/clusters, similar + to clustering algorithms, such as k-means and hierarchical clustering. This package + implements a clustering algorithm based on a new metric CORD, defined for high + dimensional parametric or semi-parametric distributions. Read http://arxiv.org/abs/1508.01939 + for more details. + date_publication: '2015-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cord + url_git: '' +cordillera: + version: 1.0-3 + title: Calculation of the OPTICS Cordillera + maintainer: Thomas Rusch + description: Functions for calculating the OPTICS Cordillera. The OPTICS Cordillera + measures the amount of 'clusteredness' in a numeric data matrix within a distance-density + based framework for a given minimum number of points comprising a cluster, as + described in Rusch, Hornik, Mair (2018) . We + provide an R native version with methods for printing, summarizing, and plotting + the result. + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cordillera + url_git: https://r-forge.r-project.org/projects/stops/ +CORE: + version: '3.2' + title: Cores of Recurrent Events + maintainer: Guoli Sun + description: |- + Given a collection of intervals with integer start and end + positions, find recurrently targeted regions and estimate the significance + of finding. Randomization is implemented by parallel methods, either + using local host machines, or submitting grid engine jobs. + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CORE + url_git: '' +coreCollection: + version: 0.9.5 + title: Core Collection + maintainer: Matthijs Brouwer + description: |2- + + Create a custom sized Core Collection based on a distance matrix and applying + the A-NE (accession nearest entry), E-NE (entry nearest entry) or E-E (entry entry) method + as introduced in Jansen and van Hintum (2007) and + further elaborated on in Odong, T.L. (2012) . + Optionally a list of preselected accessions to be included into the core can be set. + For each accession in the computed core, if available nearby accessions are retrievable + that can be used as an alternative. + date_publication: '2022-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coreCollection + url_git: '' +coreCT: + version: 1.3.3 + title: |- + Programmatic Analysis of Sediment Cores Using Computed + Tomography Imaging + maintainer: Troy D. Hill + description: 'Computed tomography (CT) imaging is a powerful tool for understanding + the composition of sediment cores. This package streamlines and accelerates the + analysis of CT data generated in the context of environmental science. Included + are tools for processing raw DICOM images to characterize sediment composition + (sand, peat, etc.). Root analyses are also enabled, including measures of external + surface area and volumes for user-defined root size classes. For a detailed description + of the application of computed tomography imaging for sediment characterization, + see: Davey, E., C. Wigand, R. Johnson, K. Sundberg, J. Morris, and C. Roman. (2011) + .' + date_publication: '2021-02-05' + bug_reports: https://github.com/troyhill/coreCT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coreCT + url_git: https://github.com/troyhill/coreCT +corehunter: + version: 3.2.3 + title: Multi-Purpose Core Subset Selection + maintainer: Herman De Beukelaer + description: |- + Core Hunter is a tool to sample diverse, representative subsets from large germplasm + collections, with minimum redundancy. Such so-called core collections have applications in plant + breeding and genetic resource management in general. Core Hunter can construct cores based on + genetic marker data, phenotypic traits or precomputed distance matrices, optimizing one of many + provided evaluation measures depending on the precise purpose of the core (e.g. high diversity, + representativeness, or allelic richness). In addition, multiple measures can be simultaneously + optimized as part of a weighted index to bring the different perspectives closer together. + The Core Hunter library is implemented in Java 8 as an open source project (see + ). + date_publication: '2023-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corehunter + url_git: '' +CORElearn: + version: 1.57.3.1 + title: Classification, Regression and Feature Evaluation + maintainer: Marko Robnik-Sikonja + description: |- + A suite of machine learning algorithms written in C++ with the R + interface contains several learning techniques for classification and regression. + Predictive models include e.g., classification and regression trees with + optional constructive induction and models in the leaves, random forests, kNN, + naive Bayes, and locally weighted regression. All predictions obtained with these + models can be explained and visualized with the 'ExplainPrediction' package. + This package is especially strong in feature evaluation where it contains several variants of + Relief algorithm and many impurity based attribute evaluation functions, e.g., Gini, + information gain, MDL, and DKM. These methods can be used for feature selection + or discretization of numeric attributes. + The OrdEval algorithm and its visualization is used for evaluation + of data sets with ordinal features and class, enabling analysis according to the + Kano model of customer satisfaction. + Several algorithms support parallel multithreaded execution via OpenMP. + The top-level documentation is reachable through ?CORElearn. + date_publication: '2024-11-04' + bug_reports: '' + url: http://lkm.fri.uni-lj.si/rmarko/software/ + url_cran: https://CRAN.R-project.org/package=CORElearn + url_git: '' +corels: + version: 0.0.5 + title: |- + R Binding for the 'Certifiably Optimal RulE ListS (Corels)' + Learner + maintainer: Dirk Eddelbuettel + description: |- + The 'Certifiably Optimal RulE ListS (Corels)' learner by + Angelino et al described in provides interpretable decision + rules with an optimality guarantee, and is made available to R with this package. + See the file 'AUTHORS' for a list of copyright holders and contributors. + date_publication: '2024-12-04' + bug_reports: https://github.com/corels/rcppcorels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=corels + url_git: https://github.com/corels/rcppcorels +CoreMicrobiomeR: + version: 0.1.0 + title: Identification of Core Microbiome + maintainer: Mohammad Samir Farooqi + description: The Core Microbiome refers to the group of microorganisms that are + consistently present in a particular environment, habitat, or host species. These + microorganisms play a crucial role in the functioning and stability of that ecosystem. + Identifying these microorganisms can contribute to the emerging field of personalized + medicine. The 'CoreMicrobiomeR' is designed to facilitate the identification, + statistical testing, and visualization of this group of microorganisms.This package + offers three key functions to analyze and visualize microbial community data. + This package has been developed based on the research papers published by Pereira + et al.(2018) and Beule L, Karlovsky P. (2020) + . + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoreMicrobiomeR + url_git: '' +coreNLP: + version: 0.4-3 + title: Wrappers Around Stanford CoreNLP Tools + maintainer: Taylor Arnold + description: |- + Provides a minimal interface for applying + annotators from the 'Stanford CoreNLP' java library. Methods + are provided for tasks such as tokenisation, part of speech + tagging, lemmatisation, named entity recognition, coreference + detection and sentiment analysis. + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coreNLP + url_git: '' +coreSim: + version: 0.2.4 + title: |- + Core Functionality for Simulating Quantities of Interest from + Generalised Linear Models + maintainer: Christopher Gandrud + description: |- + Core functions for simulating quantities of interest + from generalised linear models (GLM). This package will form the backbone of + a series of other packages that improve the interpretation of GLM estimates. + date_publication: '2017-05-15' + bug_reports: https://github.com/christophergandrud/coreSim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coreSim + url_git: '' +corHMM: + version: '2.8' + title: Hidden Markov Models of Character Evolution + maintainer: Jeremy Beaulieu + description: Fits hidden Markov models of discrete character evolution which allow + different transition rate classes on different portions of a phylogeny. Beaulieu + et al (2013) . + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corHMM + url_git: '' +corkscrew: + version: '1.1' + title: Preprocessor for Data Modeling + maintainer: Santhosh Sasanapuri + description: |- + Includes binning categorical variables into lesser number of categories based on t-test, converting categorical variables into continuous features + using the mean of the response variable for the respective categories, understanding the relationship between the response variable and predictor variables + using data transformations. + date_publication: '2015-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corkscrew + url_git: '' +corlink: + version: 1.0.0 + title: |- + Record Linkage, Incorporating Imputation for Missing Agreement + Patterns, and Modeling Correlation Patterns Between Fields + maintainer: John Ferguson + description: A matrix of agreement patterns and counts for record pairs is the input + for the procedure. An EM algorithm is used to impute plausible values for missing + record pairs. A second EM algorithm, incorporating possible correlations between + per-field agreement, is used to estimate posterior probabilities that each pair + is a true match - i.e. constitutes the same individual. + date_publication: '2016-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corlink + url_git: '' +CorMID: + version: 0.3.1 + title: Correct Mass Isotopologue Distribution Vectors + maintainer: Jan Lisec + description: |- + In metabolic flux experiments tracer molecules (often glucose + containing labelled carbon) are incorporated in compounds measured + using mass spectrometry. The mass isotopologue distributions of these + compounds needs to be corrected for natural abundance of labelled + carbon and other effects, which are specific on the compound and + ionization technique applied. This package provides functions to + correct such effects in gas chromatography atmospheric pressure + chemical ionization mass spectrometry analyses. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CorMID + url_git: https://github.com/janlisec/CorMID +corncob: + version: 0.4.1 + title: |- + Count Regression for Correlated Observations with the + Beta-Binomial + maintainer: Amy D Willis + description: Statistical modeling for correlated count data using the beta-binomial + distribution, described in Martin et al. (2020) . It + allows for both mean and overdispersion covariates. + date_publication: '2024-01-10' + bug_reports: https://github.com/statdivlab/corncob/issues + url: https://statdivlab.github.io/corncob/ + url_cran: https://CRAN.R-project.org/package=corncob + url_git: https://github.com/statdivlab/corncob +CornerstoneR: + version: 2.0.2 + title: |- + Collection of Scripts for Interface Between 'Cornerstone' and + 'R' + maintainer: Gerrith Djaja + description: |- + Collection of generic 'R' scripts which enable you to use existing 'R' routines in 'Cornerstone'. + + The desktop application 'Cornerstone' () + is a data analysis software provided by 'camLine' that empowers engineering teams to find solutions even faster. + The engineers incorporate intensified hands-on statistics into their projects. + They benefit from an intuitive and uniquely designed graphical Workmap concept: you design + experiments (DoE) and explore data, analyze dependencies, and find answers you can act upon, + immediately, interactively, and without any programming. + + While 'Cornerstone's' interface to the statistical programming language 'R' has been available + since version 6.0, the latest interface with 'R' is even much more efficient. + 'Cornerstone' release 7.1.1 allows you to integrate user defined 'R' packages directly into the + standard 'Cornerstone' GUI. + Your engineering team stays in 'Cornerstone's' graphical working environment and can apply 'R' + routines, immediately and without the need to deal with programming code. + Additionally, your 'R' programming team develops corresponding 'R' packages detached from + 'Cornerstone' in their favorite 'R' environment. + + Learn how to use 'R' packages in 'Cornerstone' 7.1.1 on 'camLineTV' YouTube channel + () (available in German). + date_publication: '2020-08-28' + bug_reports: https://gitlab.com/camLine/CornerstoneR/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CornerstoneR + url_git: https://gitlab.com/camLine/CornerstoneR/-/issues +cornet: + version: 1.0.0 + title: Penalised Regression for Dichotomised Outcomes + maintainer: Armin Rauschenberger + description: Implements lasso and ridge regression for dichotomised outcomes (), + i.e., numerical outcomes that were transformed to binary outcomes. Such artificial + binary outcomes indicate whether an underlying measurement is greater than a threshold. + date_publication: '2024-09-26' + bug_reports: https://github.com/rauschenberger/cornet/issues + url: https://rauschenberger.github.io/cornet/ + url_cran: https://CRAN.R-project.org/package=cornet + url_git: https://github.com/rauschenberger/cornet +coro: + version: 1.1.0 + title: '''Coroutines'' for R' + maintainer: Lionel Henry + description: |- + Provides 'coroutines' for R, a family of functions that can + be suspended and resumed later on. This includes 'async' functions + (which await) and generators (which yield). 'Async' functions are + based on the concurrency framework of the 'promises' package. + Generators are based on a dependency free iteration protocol defined + in 'coro' and are compatible with iterators from the 'reticulate' + package. + date_publication: '2024-11-05' + bug_reports: https://github.com/r-lib/coro/issues + url: https://coro.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=coro + url_git: https://github.com/r-lib/coro +coroICA: + version: 1.0.2 + title: |- + Confounding Robust Independent Component Analysis for Noisy and + Grouped Data + maintainer: Niklas Pfister + description: Contains an implementation of a confounding robust independent component + analysis (ICA) for noisy and grouped data. The main function coroICA() performs + a blind source separation, by maximizing an independence across sources and allows + to adjust for varying confounding based on user-specified groups. Additionally, + the package contains the function uwedge() which can be used to approximately + jointly diagonalize a list of matrices. For more details see the project website + . + date_publication: '2020-05-15' + bug_reports: https://github.com/sweichwald/coroICA-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coroICA + url_git: https://github.com/sweichwald/coroICA-R +corona: + version: 0.3.0 + title: Coronavirus ('Rona') Data Exploration + maintainer: Jo van Schalkwyk + description: Manipulate and view coronavirus data and other societally relevant + data at a basic level. + date_publication: '2020-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corona + url_git: '' +coronavirus: + version: 0.4.1 + title: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset + maintainer: Rami Krispin + description: 'Provides a daily summary of the Coronavirus (COVID-19) cases by state/province. + Data source: Johns Hopkins University Center for Systems Science and Engineering + (JHU CCSE) Coronavirus .' + date_publication: '2023-03-19' + bug_reports: https://github.com/RamiKrispin/coronavirus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coronavirus + url_git: https://github.com/RamiKrispin/coronavirus +corpcor: + version: 1.6.10 + title: Efficient Estimation of Covariance and (Partial) Correlation + maintainer: Korbinian Strimmer + description: |- + Implements a James-Stein-type shrinkage estimator for + the covariance matrix, with separate shrinkage for variances and correlations. + The details of the method are explained in Schafer and Strimmer (2005) + and Opgen-Rhein and Strimmer (2007) + . The approach is both computationally as well + as statistically very efficient, it is applicable to "small n, large p" data, + and always returns a positive definite and well-conditioned covariance matrix. + In addition to inferring the covariance matrix the package also provides + shrinkage estimators for partial correlations and partial variances. + The inverse of the covariance and correlation matrix + can be efficiently computed, as well as any arbitrary power of the + shrinkage correlation matrix. Furthermore, functions are available for fast + singular value decomposition, for computing the pseudoinverse, and for + checking the rank and positive definiteness of a matrix. + date_publication: '2021-09-16' + bug_reports: '' + url: https://strimmerlab.github.io/software/corpcor/ + url_cran: https://CRAN.R-project.org/package=corpcor + url_git: '' +corpmetrics: + version: '1.0' + title: |- + Tools for Valuation, Financial Metrics and Modeling in Corporate + Finance + maintainer: Pavlos Pantatosakis + description: Balance sheet and income statement metrics, investment analysis methods, + valuation methods, loan amortization schedules, and Capital Asset Pricing Model. + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corpmetrics + url_git: '' +corpora: + version: '0.6' + title: Statistics and Data Sets for Corpus Frequency Data + maintainer: Stephanie Evert + description: |- + Utility functions for the statistical analysis of corpus frequency data. + This package is a companion to the open-source course "Statistical Inference: + A Gentle Introduction for Computational Linguists and Similar Creatures" ('SIGIL'). + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corpora + url_git: http://SIGIL.R-Forge.R-Project.org/ +corporaexplorer: + version: 0.9.0 + title: A 'Shiny' App for Exploration of Text Collections + maintainer: Kristian Lundby Gjerde + description: |- + Facilitates dynamic exploration of text collections through an + intuitive graphical user interface and the power of regular expressions. + The package contains 1) a helper function to convert a data frame to a + 'corporaexplorerobject' and 2) a 'Shiny' app for fast and flexible exploration + of a 'corporaexplorerobject'. The package also includes demo apps with which + one can explore Jane Austen's novels and the State of the Union Addresses + (data from the 'janeaustenr' and 'sotu' packages respectively). + date_publication: '2024-09-02' + bug_reports: https://github.com/kgjerde/corporaexplorer/issues + url: https://kgjerde.github.io/corporaexplorer/ + url_cran: https://CRAN.R-project.org/package=corporaexplorer + url_git: https://github.com/kgjerde/corporaexplorer +CoRpower: + version: 1.0.4 + title: |- + Power Calculations for Assessing Correlates of Risk in Clinical + Efficacy Trials + maintainer: Michal Juraska + description: Calculates power for assessment of intermediate biomarker responses + as correlates of risk in the active treatment group in clinical efficacy trials, + as described in Gilbert, Janes, and Huang, Power/Sample Size Calculations for + Assessing Correlates of Risk in Clinical Efficacy Trials (2016, Statistics in + Medicine). The methods differ from past approaches by accounting for the level + of clinical treatment efficacy overall and in biomarker response subgroups, which + enables the correlates of risk results to be interpreted in terms of potential + correlates of efficacy/protection. The methods also account for inter-individual + variability of the observed biomarker response that is not biologically relevant + (e.g., due to technical measurement error of the laboratory assay used to measure + the biomarker response), which is important because power to detect a specified + correlate of risk effect size is heavily affected by the biomarker's measurement + error. The methods can be used for a general binary clinical endpoint model with + a univariate dichotomous, trichotomous, or continuous biomarker response measured + in active treatment recipients at a fixed timepoint after randomization, with + either case-cohort Bernoulli sampling or case-control without-replacement sampling + of the biomarker (a baseline biomarker is handled as a trivial special case). + In a specified two-group trial design, the computeN() function can initially be + used for calculating additional requisite design parameters pertaining to the + target population of active treatment recipients observed to be at risk at the + biomarker sampling timepoint. Subsequently, the power calculation employs an inverse + probability weighted logistic regression model fitted by the tps() function in + the 'osDesign' package. Power results as well as the relationship between the + correlate of risk effect size and treatment efficacy can be visualized using various + plotting functions. To link power calculations for detecting a correlate of risk + and a correlate of treatment efficacy, a baseline immunogenicity predictor (BIP) + can be simulated according to a specified classification rule (for dichotomous + or trichotomous BIPs) or correlation with the biomarker response (for continuous + BIPs), then outputted along with biomarker response data under assignment to treatment, + and clinical endpoint data for both treatment and placebo groups. + date_publication: '2020-11-17' + bug_reports: https://github.com/mjuraska/CoRpower/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CoRpower + url_git: https://github.com/mjuraska/CoRpower +corpustools: + version: 0.5.1 + title: Managing, Querying and Analyzing Tokenized Text + maintainer: Kasper Welbers + description: |- + Provides text analysis in R, focusing on the use of a tokenized text format. In this format, the positions of tokens are maintained, and each token can be annotated (e.g., part-of-speech tags, dependency relations). + Prominent features include advanced Lucene-like querying for specific tokens or contexts (e.g., documents, sentences), + similarity statistics for words and documents, exporting to DTM for compatibility with many text analysis packages, + and the possibility to reconstruct original text from tokens to facilitate interpretation. + date_publication: '2023-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corpustools + url_git: https://github.com/kasperwelbers/corpustools +corr2D: + version: 1.0.3 + title: Implementation of 2D Correlation Analysis in R + maintainer: Robert Geitner + description: |- + Implementation of two-dimensional (2D) correlation analysis based + on the Fourier-transformation approach described by Isao Noda (I. Noda + (1993) ). Additionally there are two plot + functions for the resulting correlation matrix: The first one creates + colored 2D plots, while the second one generates 3D plots. + date_publication: '2022-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corr2D + url_git: '' +corrarray: + version: 1.2.0 + title: Correlation Arrays and 2-Sample Correlation Matrices + maintainer: Rohan Reddy Tummala + description: |- + The goal of 'corrarray' is to create a multi-sample + correlation array by combining the correlation matrices of a data set + stratified by a grouping variable. + For two specified levels of the variable, 'corrarray' displays one level's + correlation matrix in the lower triangular matrix and the other level's + correlation matrix in the upper triangular matrix. + Such an output can enable visualization of correlations from two samples + in a single correlation matrix or corrgram. + date_publication: '2020-08-26' + bug_reports: https://github.com/Medicine1/corrarray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=corrarray + url_git: https://github.com/Medicine1/corrarray +CorrBin: + version: 1.6.2 + title: Nonparametrics with Clustered Binary and Multinomial Data + maintainer: Aniko Szabo + description: |- + Implements non-parametric analyses for clustered + binary and multinomial data. The elements of the cluster are assumed + exchangeable, and identical joint distribution (also known as marginal + compatibility, or reproducibility) is assumed for clusters of different + sizes. A trend test based on stochastic ordering is implemented. + Szabo A, George EO. (2010) ; + George EO, Cheon K, Yuan Y, Szabo A (2016) . + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CorrBin + url_git: '' +corrcoverage: + version: 1.2.1 + title: |- + Correcting the Coverage of Credible Sets from Bayesian Genetic + Fine Mapping + maintainer: Anna Hutchinson + description: |- + Using a computationally efficient method, the package can + be used to find the corrected coverage estimate of a credible set + of putative causal variants from Bayesian genetic fine-mapping. + The package can also be used to obtain a corrected credible set + if required; that is, the smallest set of variants required such + that the corrected coverage estimate of the resultant credible set is + within some user defined accuracy of the desired coverage. + Maller et al. (2012) , + Wakefield (2009) , + Fortune and Wallace (2018) . + date_publication: '2019-12-06' + bug_reports: https://github.com/annahutch/corrcoverage/issues + url: https://annahutch.github.io/corrcoverage + url_cran: https://CRAN.R-project.org/package=corrcoverage + url_git: '' +corrDNA: + version: 1.0.1 + title: |- + Finding Associations in Position-Wise Aligned DNA Sequence + Dataset + maintainer: Prabina Kumar Meher + description: Can be useful for finding associations among different positions in + a position-wise aligned sequence dataset. The approach adopted for finding associations + among positions is based on the latent multivariate normal distribution. + date_publication: '2018-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corrDNA + url_git: '' +correctedAUC: + version: 0.0.3 + title: Correcting AUC for Measurement Error + maintainer: Weiliang Qiu + description: Correcting area under ROC (AUC) for measurement error based on probit-shift + model. + date_publication: '2016-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=correctedAUC + url_git: '' +CorrectedFDR: + version: '1.1' + title: Correcting False Discovery Rates + maintainer: Abbas Rahal + description: |- + There are many estimators of false discovery rate. In this package we compute the Nonlocal False + Discovery Rate (NFDR) and the estimators of local false discovery rate: Corrected False discovery + Rate (CFDR), Re-ranked False Discovery rate (RFDR) and the blended estimator. + Bickel, D.R., Rahal, A. (2019) . + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CorrectedFDR + url_git: '' +CorrectOverloadedPeaks: + version: 1.3.5 + title: Correct Overloaded Peaks from GC-APCI-MS Data + maintainer: Jan Lisec + description: |- + Analyzes and modifies metabolomics raw data (generated using + Gas Chromatography-Atmospheric Pressure Chemical Ionization-Mass Spectrometry) + to correct overloaded signals, i.e. ion intensities exceeding detector + saturation leading to a cut-off peak. Data in 'xcmsRaw' format are + accepted as input and 'mzXML' files can be processed alternatively. + Overloaded signals are detected automatically and modified using an Gaussian + or an Isotopic-Ratio approach. Quality control plots are generated and + corrected data are stored within the original 'xcmsRaw' or 'mzXML' + respectively to allow further processing. + date_publication: '2025-02-27' + bug_reports: https://github.com/janlisec/CorrectOverloadedPeaks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CorrectOverloadedPeaks + url_git: https://github.com/janlisec/CorrectOverloadedPeaks +correctR: + version: 0.3.1 + title: |- + Corrected Test Statistics for Comparing Machine Learning Models + on Correlated Samples + maintainer: Trent Henderson + description: |- + Calculate a set of corrected test statistics for cases when samples + are not independent, such as when classification accuracy values are obtained + over resamples or through k-fold cross-validation, as proposed by Nadeau and Bengio (2003) + and presented in Bouckaert and Frank (2004) . + date_publication: '2025-02-05' + bug_reports: https://github.com/hendersontrent/correctR/issues + url: https://hendersontrent.github.io/correctR/ + url_cran: https://CRAN.R-project.org/package=correctR + url_git: '' +correlatio: + version: 0.1.0 + title: Visualize Details Behind Pearson's Correlation Coefficient + maintainer: Marcel Miché + description: 'Helps visualizing what is summarized in Pearson''s correlation coefficient. + That is, it visualizes its main constituent, namely the distances of the single + values to their respective mean. The visualization thereby shows what the etymology + of the word correlation contains: In pairwise combination, bringing back (see + package Vignette for more details). I hope that the ''correlatio'' package may + benefit some people in understanding and critically evaluating what Pearson''s + correlation coefficient summarizes in a single number, i.e., to what degree and + why Pearson''s correlation coefficient may (or may not) be warranted as a measure + of association.' + date_publication: '2025-02-18' + bug_reports: https://github.com/mmiche/correlatio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=correlatio + url_git: https://github.com/mmiche/correlatio +correlation: + version: 0.8.6 + title: Methods for Correlation Analysis + maintainer: Brenton M. Wiernik + description: |- + Lightweight package for computing different kinds + of correlations, such as partial correlations, Bayesian correlations, + multilevel correlations, polychoric correlations, biweight + correlations, distance correlations and more. Part of the 'easystats' + ecosystem. References: Makowski et al. (2020) . + date_publication: '2024-10-26' + bug_reports: https://github.com/easystats/correlation/issues + url: https://easystats.github.io/correlation/ + url_cran: https://CRAN.R-project.org/package=correlation + url_git: '' +correlationfunnel: + version: 0.2.0 + title: |- + Speed Up Exploratory Data Analysis (EDA) with the Correlation + Funnel + maintainer: Matt Dancho + description: |2- + + Speeds up exploratory data analysis (EDA) + by providing a succinct workflow and interactive visualization tools for understanding + which features have relationships to target (response). Uses binary correlation analysis + to determine relationship. Default correlation method is the Pearson method. + Lian Duan, W Nick Street, Yanchi Liu, Songhua Xu, and Brook Wu (2014) . + date_publication: '2020-06-09' + bug_reports: https://github.com/business-science/correlationfunnel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=correlationfunnel + url_git: https://github.com/business-science/correlationfunnel +correlbinom: + version: 0.0.1 + title: Correlated Binomial Probabilities + maintainer: Gary Witt + description: Calculates the probabilities of k successes given n trials of a binomial + random variable with non-negative correlation across trials. The function takes + as inputs the scalar values the level of correlation or association between trials, + the success probability, the number of trials, an optional input specifying the + number of bits of precision used in the calculation, and an optional input specifying + whether the calculation approach to be used is from Witt (2014) + or from Kuk (2004) . The output is a (trials+1)-dimensional + vector containing the likelihoods of 0, 1, ..., trials successes. + date_publication: '2017-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=correlbinom + url_git: '' +Correlplot: + version: 1.1.0 + title: A Collection of Functions for Graphing Correlation Matrices + maintainer: Jan Graffelman + description: 'Routines for the graphical representation of correlation matrices + by means of correlograms, MDS maps and biplots obtained by PCA, PFA or WALS (weighted + alternating least squares); See Graffelman & De Leeuw (2023) .' + date_publication: '2024-01-23' + bug_reports: '' + url: http://www-eio.upc.es/~jan/ + url_cran: https://CRAN.R-project.org/package=Correlplot + url_git: '' +correspondenceTables: + version: 0.7.4 + title: |- + Creating Correspondence Tables Between Two Statistical + Classifications + maintainer: Mátyás Mészáros + description: |2- + + A candidate correspondence table between two classifications can be created when there are correspondence tables leading from the first classification to the second one via intermediate 'pivot' classifications. + The correspondence table between two statistical classifications can be updated when one of the classifications gets updated to a new version. + date_publication: '2022-09-27' + bug_reports: https://github.com/eurostat/correspondenceTables/issues + url: '' + url_cran: https://CRAN.R-project.org/package=correspondenceTables + url_git: https://github.com/eurostat/correspondenceTables +corrfuns: + version: '1.2' + title: Correlation Coefficient Related Functions + maintainer: Michail Tsagris + description: 'Many correlation coefficient related functions are offered, such as + correlations, partial correlations and hypothesis testing using asymptotic tests + and computer intensive methods (bootstrap and permutation). References include + Mardia K.V., Kent J.T. and Bibby J.M. (1979). "Multivariate Analysis". ISBN: 978-0124712522. + London: Academic Press and Owen A. B. (2001). "Empirical likelihood". Chapman + and Hall/CRC Press. ISBN: 9781584880714.' + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corrfuns + url_git: '' +corrgram: + version: '1.14' + title: Plot a Correlogram + maintainer: Kevin Wright + description: |- + Calculates correlation of variables and displays the results + graphically. Included panel functions can display points, shading, ellipses, and + correlation values with confidence intervals. See Friendly (2002) . + date_publication: '2021-04-29' + bug_reports: https://github.com/kwstat/corrgram/issues/ + url: https://kwstat.github.io/corrgram/ + url_cran: https://CRAN.R-project.org/package=corrgram + url_git: '' +corrgrapher: + version: 1.0.4 + title: |- + Explore Correlations Between Variables in a Machine Learning + Model + maintainer: Pawel Morgen + description: |- + When exploring data or models we often examine variables one by one. + This analysis is incomplete if the relationship between these variables is + not taken into account. The 'corrgrapher' package facilitates simultaneous + exploration of the Partial Dependence Profiles and the correlation between + variables in the model. + The package 'corrgrapher' is a part of the 'DrWhy.AI' universe. + date_publication: '2020-10-13' + bug_reports: https://github.com/ModelOriented/corrgrapher/issues + url: https://modeloriented.github.io/corrgrapher/ + url_cran: https://CRAN.R-project.org/package=corrgrapher + url_git: https://github.com/ModelOriented/corrgrapher +corrMCT: + version: 0.2.0 + title: Correlated Weighted Hochberg + maintainer: Xin-Wei Huang + description: |- + Perform additional multiple testing procedure methods to p.adjust(), + such as weighted Hochberg (Tamhane, A. C., & Liu, L., 2008) , + ICC adjusted Bonferroni method (Shi, Q., Pavey, E. S., & Carter, R. E., 2012) + and a new correlation corrected weighted Hochberg for correlated + endpoints. + date_publication: '2024-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corrMCT + url_git: '' +corrmeta: + version: 1.0.0 + title: Correlated Meta-Analysis + maintainer: Woo Seok Jung + description: |- + Performs Correlated Meta-Analysis ('corrmeta') across multiple OMIC + scans, accounting for hidden non-independencies between elements of the + scans due to overlapping samples, related samples, or other information. + For more information about the method, refer to the paper + Province MA. (2013) . + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corrmeta + url_git: '' +CorrMixed: + version: '1.1' + title: |- + Estimate Correlations Between Repeatedly Measured Endpoints + (E.g., Reliability) Based on Linear Mixed-Effects Models + maintainer: Wim Van der Elst + description: In clinical practice and research settings in medicine and the behavioral + sciences, it is often of interest to quantify the correlation of a continuous + endpoint that was repeatedly measured (e.g., test-retest correlations, ICC, etc.). + This package allows for estimating these correlations based on mixed-effects models. + Part of this software has been developed using funding provided from the European + Union's 7th Framework Programme for research, technological development and demonstration + under Grant Agreement no 602552. + date_publication: '2022-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CorrMixed + url_git: '' +corrplot: + version: '0.95' + title: Visualization of a Correlation Matrix + maintainer: Taiyun Wei + description: Provides a visual exploratory tool on correlation matrix that supports + automatic variable reordering to help detect hidden patterns among variables. + date_publication: '2024-10-14' + bug_reports: https://github.com/taiyun/corrplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=corrplot + url_git: https://github.com/taiyun/corrplot +corrr: + version: 0.4.4 + title: Correlations in R + maintainer: Max Kuhn + description: |- + A tool for exploring correlations. It makes it possible to + easily perform routine tasks when exploring correlation matrices such + as ignoring the diagonal, focusing on the correlations of certain + variables against others, or rearranging and visualizing the matrix in + terms of the strength of the correlations. + date_publication: '2022-08-16' + bug_reports: https://github.com/tidymodels/corrr/issues + url: https://corrr.tidymodels.org + url_cran: https://CRAN.R-project.org/package=corrr + url_git: https://github.com/tidymodels/corrr +corrsieve: + version: 1.6-9 + title: Software for Summarising and Evaluating STRUCTURE Output + maintainer: Michael G. Campana + description: Statistical summary of STRUCTURE output. STRUCTURE is a K-means clustering + method for inferring population structure and assigning individuals to populations + using genetic data. Pritchard JK, Stephens M, Donnelly PJ (2000) . + . + date_publication: '2022-05-02' + bug_reports: https://github.com/campanam/rCorrSieve + url: '' + url_cran: https://CRAN.R-project.org/package=corrsieve + url_git: https://github.com/campanam/rCorrSieve +corrtable: + version: 0.1.1 + title: |- + Creates and Saves Out a Correlation Table with Significance + Levels Indicated + maintainer: Laura Lambert + description: |- + After using this, a publication-ready correlation table with p-values + indicated will be created. The input can be a full data frame; any + string and Boolean terms will be dropped as part of functionality. Correlations and + p-values are calculated using the 'Hmisc' framework. Output of the + correlation_matrix() function is a table of strings; this gets saved out to a '.csv2' + with the save_correlation_matrix() function for easy insertion into a paper. + For more details about the process, consult + . + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corrtable + url_git: '' +CorrToolBox: + version: 1.6.4 + title: |- + Modeling Correlational Magnitude Transformations in + Discretization Contexts + maintainer: Ran Gao + description: Modeling the correlation transitions under specified distributional + assumptions within the realm of discretization in the context of the latency and + threshold concepts. The details of the method are explained in Demirtas, H. and + Vardar-Acar, C. (2017) . + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CorrToolBox + url_git: '' +corrViz: + version: 0.1.0 + title: Visualise Correlations + maintainer: Alan Inglis + description: An investigative tool designed to help users visualize correlations + between variables in their datasets. This package aims to provide an easy and + effective way to explore and visualize these correlations, making it easier to + interpret and communicate results. + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corrViz + url_git: '' +corset: + version: 0.1-5 + title: Arbitrary Bounding of Series and Time Series Objects + maintainer: Fran Urbano + description: |- + Set of methods to constrain numerical series and time series within + arbitrary boundaries. + date_publication: '2023-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corset + url_git: '' +corTest: + version: 1.0.7 + title: Robust Tests for Equal Correlation + maintainer: Danyang Yu + description: 'There are 6 novel robust tests for equal correlation. They are all + based on logistic regressions. The score statistic U is proportion to difference + of two correlations based on different types of correlation in 6 methods. The + ST1() is based on Pearson correlation. ST2() improved ST1() by using median absolute + deviation. ST3() utilized type M correlation and ST4() used Spearman correlation. ST5() + and ST6() used two different ways to combine ST3() and ST4(). We highly recommend + ST5() according to the article titled ''''New Statistical Methods for Constructing + Robust Differential Correlation Networks to characterize the interactions among + microRNAs'''' published in Scientific Reports. Please see the reference: Yu et + al. (2019) .' + date_publication: '2020-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corTest + url_git: '' +corTESTsrd: + version: 1.0-0 + title: Significance Testing of Rank Cross-Correlations under SRD + maintainer: David Lun + description: |- + Significance test of Spearman's Rho or Kendall's Tau + between short-range dependent random variables. + date_publication: '2022-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corTESTsrd + url_git: '' +corto: + version: 1.2.4 + title: Inference of Gene Regulatory Networks + maintainer: Federico M. Giorgi + description: |- + We present 'corto' (Correlation Tool), a simple package to infer + gene regulatory networks and visualize master regulators from gene expression + data using DPI (Data Processing Inequality) and bootstrapping to recover edges. + An initial step is performed to calculate all significant + edges between a list of source nodes (centroids) and target genes. + Then all triplets containing two centroids and one target are tested + in a DPI step which removes edges. A bootstrapping process then calculates + the robustness of the network, eventually re-adding edges previously removed by DPI. + The algorithm has been optimized to run outside a computing cluster, using a fast correlation + implementation. The package finally provides functions to calculate network enrichment + analysis from RNA-Seq and ATAC-Seq signatures as described in the article by + Giorgi lab (2020) . + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corto + url_git: '' +corx: + version: 1.0.7.2 + title: Create and Format Correlation Matrices + maintainer: James Conigrave + description: Create correlation (or partial correlation) matrices. Correlation matrices + are formatted with significance stars based on user preferences. Matrices of coefficients, + p-values, and number of pairwise observations are returned. Send resultant formatted + matrices to the clipboard to be pasted into excel and other programs. A plot method + allows users to visualize correlation matrices created with 'corx'. + date_publication: '2023-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=corx + url_git: https://github.com/conig/corx +cosa: + version: 2.1.0 + title: Bound Constrained Optimal Sample Size Allocation + maintainer: Metin Bulus + description: |2- + + Implements bound constrained optimal sample size allocation (BCOSSA) framework described in Bulus & Dong (2021) for power analysis of multilevel regression discontinuity designs (MRDDs) and multilevel randomized trials (MRTs) with continuous outcomes. + Minimum detectable effect size (MDES) and power computations for MRDDs allow polynomial functional form specification for the score variable (with or without interaction with the treatment indicator). See Bulus (2021) . + date_publication: '2021-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cosa + url_git: '' +cosimmr: + version: 1.0.12 + title: Fast Fitting of Stable Isotope Mixing Models with Covariates + maintainer: Emma Govan + description: 'Fast fitting of Stable Isotope Mixing Models in R. Allows for the + inclusion of covariates. Also has built-in summary functions and plot functions + which allow for the creation of isospace plots. Variational Bayes is used to fit + these models, methods as described in: Tran et al., (2021) .' + date_publication: '2024-05-31' + bug_reports: '' + url: https://emmagovan.github.io/cosimmr/ + url_cran: https://CRAN.R-project.org/package=cosimmr + url_git: https://github.com/emmagovan/cosimmr +cosinor: + version: 1.2.3 + title: Tools for Estimating and Predicting the Cosinor Model + maintainer: Michael Sachs + description: |- + A set of simple functions that transforms longitudinal + data to estimate the cosinor linear model as described in Tong (1976). + Methods are given to summarize the mean, amplitude and acrophase, to + predict the mean annual outcome value, and to test the coefficients. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cosinor + url_git: https://github.com/sachsmc/cosinor +cosinor2: + version: 0.2.1 + title: Extended Tools for Cosinor Analysis of Rhythms + maintainer: Augustin Mutak + description: Statistical procedures for calculating population–mean cosinor, non–stationary + cosinor, estimation of best–fitting period, tests of population rhythm differences + and more. See Cornélissen, G. (2014). . + date_publication: '2018-10-15' + bug_reports: https://github.com/amutak/cosinor2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cosinor2 + url_git: https://github.com/amutak/cosinor2 +cosmicsig: + version: 1.1.1 + title: |- + Mutational Signatures from COSMIC (Catalogue of Somatic + Mutations in Cancer) + maintainer: Steven Rozen + description: |- + A data package with 2 main package variables: 'signature' and 'etiology'. + The 'signature' variable contains the latest mutational signature profiles + released on COSMIC for 3 mutation + types: + * Single base substitutions in the context of preceding and following bases, + * Doublet base substitutions, and + * Small insertions and deletions. + The 'etiology' variable provides the known or hypothesized causes of signatures. + 'cosmicsig' stands for COSMIC signatures. Please run ?'cosmicsig' for more + information. + date_publication: '2023-08-30' + bug_reports: https://github.com/Rozen-Lab/cosmicsig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cosmicsig + url_git: https://github.com/Rozen-Lab/cosmicsig +cosmoFns: + version: 1.1-1 + title: Functions for Cosmological Distances, Times, Luminosities, Etc + maintainer: Andrew Harris + description: Package encapsulates standard expressions for distances, times, luminosities, + and other quantities useful in observational cosmology, including molecular line + observations. Currently coded for a flat universe only. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cosmoFns + url_git: '' +CoSMoS: + version: 2.1.0 + title: Complete Stochastic Modelling Solution + maintainer: Kevin Shook + description: Makes univariate, multivariate, or random fields simulations precise + and simple. Just select the desired time series or random fields’ properties and + it will do the rest. CoSMoS is based on the framework described in Papalexiou + (2018, ), extended for random fields in Papalexiou + and Serinaldi (2020, ), and further advanced in Papalexiou + et al. (2021, ) to allow fine-scale space-time simulation + of storms (or even cyclone-mimicking fields). + date_publication: '2021-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoSMoS + url_git: https://github.com/TycheLab/CoSMoS +cosso: + version: 2.1-2 + title: |- + Fit Regularized Nonparametric Regression Models Using COSSO + Penalty + maintainer: Isaac Ray + description: |- + The COSSO regularization method automatically + estimates and selects important function components by a + soft-thresholding penalty in the context of smoothing spline + ANOVA models. Implemented models include mean regression, + quantile regression, logistic regression and the Cox regression + models. + date_publication: '2023-03-08' + bug_reports: '' + url: https://arxiv.org/abs/math/0702659 + url_cran: https://CRAN.R-project.org/package=cosso + url_git: '' +COST: + version: 0.1.0 + title: Copula-Based Semiparametric Models for Spatio-Temporal Data + maintainer: Yanlin Tang + description: |- + Parameter estimation, one-step ahead forecast and new location + prediction methods for spatio-temporal data. + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COST + url_git: '' +costat: + version: 2.4.1 + title: Time Series Costationarity Determination + maintainer: Guy Nason + description: |- + Contains functions that can determine whether a time series + is second-order stationary or not (and hence evidence for + locally stationarity). Given two non-stationary series (i.e. + locally stationary series) this package can then discover + time-varying linear combinations that are second-order stationary. + Cardinali, A. and Nason, G.P. (2013) + . + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=costat + url_git: '' +costsensitive: + version: 0.1.2.10 + title: Cost-Sensitive Multi-Class Classification + maintainer: David Cortes + description: |- + Reduction-based techniques for cost-sensitive multi-class classification, in which each observation has a different cost for classifying it into one class, and the goal is to predict the class with the minimum expected cost for each new observation. + Implements Weighted All-Pairs (Beygelzimer, A., Langford, J., & Zadrozny, B., 2008, ), Weighted One-Vs-Rest (Beygelzimer, A., Dani, V., Hayes, T., Langford, J., & Zadrozny, B., 2005, ) and Regression One-Vs-Rest. + Works with arbitrary classifiers taking observation weights, or with regressors. Also implements cost-proportionate rejection sampling for working with classifiers + that don't accept observation weights. + date_publication: '2019-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=costsensitive + url_git: https://github.com/david-cortes/costsensitive +CoTiMA: + version: 0.8.0 + title: Continuous Time Meta-Analysis ('CoTiMA') + maintainer: Markus Homberg + description: |- + The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from + studies that used different time intervals. Different time intervals between measurement occasions impose problems for + meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common + fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or + intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different + time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package + 'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e., + continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical + model comparisons and significance tests are then performed on the continuous time parameter estimates. 'CoTiMA' also allows + analysis of publication bias (Egger's test, PET-PEESE estimates, zcurve analysis etc.) and analysis of statistical power + (post hoc power, required sample sizes). + See Dormann, C., Guthier, C., & Cortina, J. M. (2019) . + and Guthier, C., Dormann, C., & Voelkle, M. C. (2020) . + date_publication: '2024-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoTiMA + url_git: https://github.com/CoTiMA/CoTiMA +cotram: + version: 0.5-2 + title: Count Transformation Models + maintainer: Sandra Siegfried + description: |- + Count transformation models featuring + parameters interpretable as discrete hazard ratios, odds ratios, + reverse-time discrete hazard ratios, or transformed expectations. + An appropriate data transformation for a count outcome and + regression coefficients are simultaneously estimated by maximising + the exact discrete log-likelihood using the computational framework + provided in package 'mlt', technical details are given in + Siegfried & Hothorn (2020) . + The package also contains an experimental implementation of + multivariate count transformation models with an application + to multi-species distribution models . + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cotram + url_git: http://ctm.R-forge.R-project.org +cotrend: + version: 1.0.2 + title: Consistent Co-Trending Rank Selection + maintainer: A. Christian Silva + description: |- + Implements cointegration/co-trending rank selection + algorithm in Guo and Shintani (2013) "Consistent + co-trending rank selection when both stochastic and nonlinear + deterministic trends are present". + The Econometrics Journal 16: 473-483 + . + Numbered examples correspond to Feb 2011 preprint + . + date_publication: '2019-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cotrend + url_git: '' +COUNT: + version: 1.3.4 + title: Functions, Data and Code for Count Data + maintainer: Andrew Robinson + description: Functions, data and code for Hilbe, J.M. 2011. Negative Binomial Regression, + 2nd Edition (Cambridge University Press) and Hilbe, J.M. 2014. Modeling Count + Data (Cambridge University Press). + date_publication: '2016-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COUNT + url_git: '' +countcolors: + version: 0.9.1 + title: Locates and Counts Pixels Within Color Range(s) in Images + maintainer: Hannah Weller + description: |- + Counts colors within color range(s) in images, and + provides a masked version of the image with targeted pixels + changed to a different color. Output includes the locations + of the pixels in the images, and the proportion of the image + within the target color range with optional background masking. + Users can specify multiple color ranges for masking. + date_publication: '2019-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countcolors + url_git: '' +countdata: + version: '1.3' + title: The Beta-Binomial Test for Count Data + maintainer: Thang Pham + description: The beta-binomial test is used for significance analysis of independent + samples by Pham et al. (2010) . The inverted + beta-binomial test is used for paired sample testing, e.g. pre-treatment and post-treatment + data, by Pham and Jimenez (2012) . + date_publication: '2023-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countdata + url_git: '' +countDM: + version: 0.1.0 + title: Estimation of Count Data Models + maintainer: Muhammad Imran + description: The maximum likelihood estimation (MLE) of the count data models along + with standard error of the estimates and Akaike information model section criterion + are provided. The functions allow to compute the MLE for the following distributions + such as the Bell distribution, the Borel distribution, the Poisson distribution, + zero inflated Bell distribution, zero inflated Bell Touchard distribution, zero + inflated Poisson distribution, zero one inflated Bell distribution and zero one + inflated Poisson distribution. Moreover, the probability mass function (PMF), + distribution function (CDF), quantile function (QF) and random numbers generation + of the Bell Touchard and zero inflated Bell Touchard distribution are also provided. + date_publication: '2023-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countDM + url_git: '' +countdown: + version: 0.4.0 + title: |- + A Countdown Timer for HTML Presentations, Documents, and Web + Apps + maintainer: Garrick Aden-Buie + description: |- + A simple countdown timer for slides and HTML documents + written in 'R Markdown' or 'Quarto'. Integrates fully into 'Shiny' + apps. Countdown to something amazing. + date_publication: '2022-08-16' + bug_reports: https://github.com/gadenbuie/countdown/issues + url: https://pkg.garrickadenbuie.com/countdown/ + url_cran: https://CRAN.R-project.org/package=countdown + url_git: https://github.com/gadenbuie/countdown +Counterfactual: + version: '1.2' + title: Estimation and Inference Methods for Counterfactual Analysis + maintainer: Ivan Fernandez-Val + description: Implements the estimation and inference methods for counterfactual + analysis described in Chernozhukov, Fernandez-Val and Melly (2013) + "Inference on Counterfactual Distributions," Econometrica, 81(6). The counterfactual + distributions considered are the result of changing either the marginal distribution + of covariates related to the outcome variable of interest, or the conditional + distribution of the outcome given the covariates. They can be applied to estimate + quantile treatment effects and wage decompositions. + date_publication: '2020-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Counterfactual + url_git: '' +counterfactuals: + version: 0.1.6 + title: Counterfactual Explanations + maintainer: Susanne Dandl + description: |- + Modular and unified R6-based interface for counterfactual explanation methods. + The following methods are currently implemented: Burghmans et al. (2022) , + Dandl et al. (2020) and Wexler et al. (2019) . + Optional extensions allow these methods to be applied to a variety of models and use cases. + Once generated, the counterfactuals can be analyzed and visualized by provided functionalities. + date_publication: '2024-10-17' + bug_reports: https://github.com/dandls/counterfactuals/issues + url: '' + url_cran: https://CRAN.R-project.org/package=counterfactuals + url_git: https://github.com/dandls/counterfactuals +Counternull: + version: 0.2.12 + title: Randomization-Based Inference + maintainer: Mabene Yasmine + description: |- + Randomization-Based Inference for customized experiments. + Computes Fisher-Exact P-Values alongside null randomization + distributions. Retrieves counternull sets and generates counternull + distributions. Computes Fisher Intervals and Fisher-Adjusted P-Values. + Package includes visualization of randomization distributions and Fisher + Intervals. Users can input custom test statistics and their own methods for + randomization. + Rosenthal and Rubin (1994) . + date_publication: '2024-02-24' + bug_reports: https://github.com/ymabene/Counternull/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Counternull + url_git: https://github.com/ymabene/Counternull +countfitteR: + version: '1.4' + title: |- + Comprehensive Automatized Evaluation of Distribution Models for + Count Data + maintainer: Jaroslaw Chilimoniuk + description: |- + A large number of measurements generate count data. This is a statistical data type + that only assumes non-negative integer values and is generated by counting. Typically, counting + data can be found in biomedical applications, such as the analysis of DNA double-strand breaks. + The number of DNA double-strand breaks can be counted in individual cells using various + bioanalytical methods. For diagnostic applications, it is relevant to record the distribution of + the number data in order to determine their biomedical significance (Roediger, S. et al., 2018. + Journal of Laboratory and Precision Medicine. ). The software + offers functions for a comprehensive automated evaluation of distribution models of count + data. In addition to programmatic interaction, a graphical user interface (web server) + is included, which enables fast and interactive data-scientific analyses. The user is supported + in selecting the most suitable counting distribution for his own data set. + date_publication: '2020-09-30' + bug_reports: https://github.com/BioGenies/countfitteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=countfitteR + url_git: https://github.com/BioGenies/countfitteR +countgmifs: + version: 0.0.2 + title: Discrete Response Regression for High-Dimensional Data + maintainer: Kellie Archer + description: Provides a function for fitting Poisson and negative binomial regression + models when the number of parameters exceeds the sample size, using the the generalized + monotone incremental forward stagewise method. + date_publication: '2020-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countgmifs + url_git: '' +countHMM: + version: 0.1.0 + title: |- + Penalized Estimation of Flexible Hidden Markov Models for Time + Series of Counts + maintainer: Timo Adam + description: 'Provides tools for penalized estimation of flexible hidden Markov + models for time series of counts w/o the need to specify a (parametric) family + of distributions. These include functions for model fitting, model checking, and + state decoding. For details, see Adam, T., Langrock, R., and Weiß, C.H. (2019): + Penalized Estimation of Flexible Hidden Markov Models for Time Series of Counts. + .' + date_publication: '2019-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countHMM + url_git: '' +countland: + version: 0.1.2 + title: |- + Analysis of Biological Count Data, Especially from Single-Cell + RNA-Seq + maintainer: Church Samuel H. + description: |- + A set of functions for applying a + restricted linear algebra to the analysis of + count-based data. See the accompanying preprint + manuscript: "Normalizing need not be the norm: + count-based math for analyzing single-cell data" + Church et al (2022) + This tool is specifically designed to analyze + count matrices from single cell RNA sequencing + assays. The tools implement several count-based + approaches for standard steps in single-cell + RNA-seq analysis, including scoring genes and cells, + comparing cells and clustering, calculating differential + gene expression, and several methods for rank + reduction. There are many opportunities for further + optimization that may prove useful in the analysis of + other data. We provide the source code freely + available at + and encourage users and developers to fork the code for + their own purposes. + date_publication: '2024-02-01' + bug_reports: https://github.com/shchurch/countland/issues + url: '' + url_cran: https://CRAN.R-project.org/package=countland + url_git: https://github.com/shchurch/countland +countprop: + version: 1.0.1 + title: |- + Calculate Model-Based Metrics of Proportionality on Count-Based + Compositional Data + maintainer: Kevin McGregor + description: Calculates metrics of proportionality using the logit-normal multinomial + model. It can also provide empirical and plugin estimates of these metrics. + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countprop + url_git: '' +Countr: + version: 3.5.8 + title: Flexible Univariate Count Models Based on Renewal Processes + maintainer: Georgi N. Boshnakov + description: |- + Flexible univariate count models based on renewal processes. The + models may include covariates and can be specified with familiar formula + syntax as in glm() and package 'flexsurv'. The methodology is described by + Kharrat et all (2019) (included as vignette + 'Countr_guide' in the package). + If the suggested package 'pscl' is not available from CRAN, it can be + installed with 'remotes::install_github("cran/pscl")'. It is no longer used + by the functions in this package but is needed for some of the extended + examples. + date_publication: '2024-01-14' + bug_reports: https://github.com/GeoBosh/Countr/issues + url: https://geobosh.github.io/Countr/(doc) + url_cran: https://CRAN.R-project.org/package=Countr + url_git: https://github.com/GeoBosh/Countr(devel) +countries: + version: 1.2.1 + title: Deal with Country Data in an Easy Way + maintainer: Francesco Saverio Bellelli + description: |- + Wrangle country data more effectively and quickly. + This package contains functions to easily identify and convert country names, + download country information, merge country data from different sources, + and make quick world maps. + date_publication: '2025-02-22' + bug_reports: https://github.com/fbellelli/countries/issues + url: https://fbellelli.github.io/countries/ + url_cran: https://CRAN.R-project.org/package=countries + url_git: https://github.com/fbellelli/countries +countrycode: + version: 1.6.0 + title: Convert Country Names and Country Codes + maintainer: Vincent Arel-Bundock + description: |- + Standardize country names, convert them into one of 40 + different coding schemes, convert between coding schemes, and assign + region descriptors. + date_publication: '2024-03-22' + bug_reports: https://github.com/vincentarelbundock/countrycode/issues + url: https://vincentarelbundock.github.io/countrycode/ + url_cran: https://CRAN.R-project.org/package=countrycode + url_git: '' +CountsEPPM: + version: '3.1' + title: Mean and Variance Modeling of Count Data + maintainer: David M. Smith + description: Modeling under- and over-dispersed count data using extended Poisson + process models as in the article Faddy and Smith (2011) + . + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CountsEPPM + url_git: '' +countsplit: + version: 4.0.0 + title: Splitting a Count Matrix into Independent Folds + maintainer: Anna Neufeld + description: Implements the count splitting methodology from Neufeld et al. (2022) + and Neufeld et al. (2023) . + Intended for turning a matrix of single-cell RNA sequencing counts, or similar + count datasets, into independent folds that can be used for training/testing or + cross validation. Assumes that the entries in the matrix are from a Poisson or + a negative binomial distribution. + date_publication: '2023-08-24' + bug_reports: https://github.com/anna-neufeld/countsplit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=countsplit + url_git: https://github.com/anna-neufeld/countsplit +countSTAR: + version: 1.0.2 + title: Flexible Modeling of Count Data + maintainer: Brian King + description: |- + For Bayesian and classical inference and prediction with count-valued data, + Simultaneous Transformation and Rounding (STAR) Models provide a flexible, interpretable, + and easy-to-use approach. STAR models the observed count data using a rounded + continuous data model and incorporates a transformation for greater flexibility. + Implicitly, STAR formalizes the commonly-applied yet incoherent procedure of + (i) transforming count-valued data and subsequently + (ii) modeling the transformed data using Gaussian models. + STAR is well-defined for count-valued data, which is reflected in predictive accuracy, + and is designed to account for zero-inflation, bounded or censored data, and over- or underdispersion. + Importantly, STAR is easy to combine with existing MCMC or point estimation + methods for continuous data, which allows seamless adaptation of continuous data + models (such as linear regressions, additive models, BART, random forests, + and gradient boosting machines) for count-valued data. The package also includes several + methods for modeling count time series data, namely via warped Dynamic Linear Models. + For more details and background on these methodologies, see the works of + Kowal and Canale (2020) , + Kowal and Wu (2022) , + King and Kowal (2022) , and + Kowal and Wu (2023) . + date_publication: '2023-06-30' + bug_reports: https://github.com/bking124/countSTAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=countSTAR + url_git: https://bking124.github.io/countSTAR/https://github.com/bking124/countSTAR +countToFPKM: + version: '1.0' + title: |- + Convert Counts to Fragments per Kilobase of Transcript per + Million (FPKM) + maintainer: Ahmed Alhendi + description: 'Implements the algorithm described in Trapnell,C. et al. (2010) . This function takes read counts matrix of RNA-Seq data, feature + lengths which can be retrieved using ''biomaRt'' package, and the mean fragment + lengths which can be calculated using the ''CollectInsertSizeMetrics(Picard)'' + tool. It then returns a matrix of FPKM normalised data by library size and feature + effective length. It also provides the user with a quick and reliable function + to generate FPKM heatmap plot of the highly variable features in RNA-Seq dataset.' + date_publication: '2019-04-07' + bug_reports: https://github.com/AAlhendi1707/countToFPKM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=countToFPKM + url_git: https://github.com/AAlhendi1707/countToFPKM +countTransformers: + version: 0.0.6 + title: Transform Counts in RNA-Seq Data Analysis + maintainer: Zeyu Zhang + description: 'Provide data transformation functions to transform counts in RNA-seq + data analysis. Please see the reference: Zhang Z, Yu D, Seo M, Hersh CP, Weiss + ST, Qiu W. (2019) .' + date_publication: '2019-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countTransformers + url_git: '' +countts: + version: 0.1.0 + title: Thomson Sampling for Zero-Inflated Count Outcomes + maintainer: Tanujit Chakraborty + description: 'A specialized tool is designed for assessing contextual bandit algorithms, + particularly those aimed at handling overdispersed and zero-inflated count data. + It offers a simulated testing environment that includes various models like Poisson, + Overdispersed Poisson, Zero-inflated Poisson, and Zero-inflated Overdispersed + Poisson. The package is capable of executing five specific algorithms: Linear + Thompson sampling with log transformation on the outcome, Thompson sampling Poisson, + Thompson sampling Negative Binomial, Thompson sampling Zero-inflated Poisson, + and Thompson sampling Zero-inflated Negative Binomial. Additionally, it can generate + regret plots to evaluate the performance of contextual bandit algorithms. This + package is based on the algorithms by Liu et al. (2023) .' + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=countts + url_git: '' +coursekata: + version: 0.18.1 + title: Packages and Functions for 'CourseKata' Courses + maintainer: Adam Blake + description: |- + Easily install and load all packages and functions used in + 'CourseKata' courses. Aid teaching with helper functions and augment + generic functions to provide cohesion between the network of packages. + Learn more about 'CourseKata' at . + date_publication: '2024-12-12' + bug_reports: https://github.com/coursekata/coursekata-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coursekata + url_git: https://github.com/coursekata/coursekata-r +covadap: + version: 1.0.1 + title: Implement Covariate-Adaptive Randomization + maintainer: Rosamarie Frieri + description: |- + Implementing seven Covariate-Adaptive Randomization to assign patients to two treatments. + Three of these procedures can also accommodate quantitative and mixed covariates. Given a set of covariates, the user can + generate a single sequence of allocations or replicate the design multiple times by simulating the patients' covariate + profiles. At the end, an extensive assessment of the performance of the randomization procedures is provided, calculating + several imbalance measures. See Baldi Antognini A, Frieri R, Zagoraiou M and Novelli M (2022) for details. + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covadap + url_git: '' +covafillr: + version: 0.4.4 + title: |- + Local Polynomial Regression of State Dependent Covariates in + State-Space Models + maintainer: Christoffer Moesgaard Albertsen + description: Facilitates local polynomial regression for state dependent covariates + in state-space models. The functionality can also be used from 'C++' based model + builder tools such as 'Rcpp'/'inline', 'TMB', or 'JAGS'. + date_publication: '2019-11-22' + bug_reports: https://github.com/calbertsen/covafillr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covafillr + url_git: https://github.com/calbertsen/covafillr +covalchemy: + version: 1.0.0 + title: |- + Constructing Joint Distributions with Control Over Statistical + Properties + maintainer: Naman Agrawal + description: |- + Synthesizing joint distributions from marginal densities, focusing on controlling key statistical properties such as correlation for continuous data, mutual information for categorical data, and inducing Simpson's Paradox. Generate datasets with specified correlation structures for continuous variables, adjust mutual information between categorical variables, and manipulate subgroup correlations to intentionally create Simpson's Paradox. + Joe (1997) + Sklar (1959) . + date_publication: '2024-11-21' + bug_reports: https://github.com/namanlab/covalchemy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covalchemy + url_git: https://github.com/namanlab/covalchemy +covatest: + version: 1.2.3 + title: Tests on Properties of Space-Time Covariance Functions + maintainer: Sandra De Iaco + description: |- + Tests on properties of space-time covariance functions. + Tests on symmetry, separability and for assessing + different forms of non-separability are available. Moreover tests on + some classes of covariance functions, such that the classes of + product-sum models, Gneiting models and integrated product models have + been provided. It is the companion R package to the papers of + Cappello, C., De Iaco, S., Posa, D., 2018, Testing the type of non-separability + and some classes of space-time covariance function models + and Cappello, C., De Iaco, S., Posa, D., 2020, covatest: an R package for + selecting a class of space-time covariance functions . + date_publication: '2023-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covatest + url_git: '' +covBM: + version: 0.1.0 + title: Brownian Motion Processes for 'nlme'-Models + maintainer: Oliver Stirrup + description: |- + Allows Brownian motion, fractional Brownian motion, + and integrated Ornstein-Uhlenbeck process components to + be added to linear and non-linear mixed effects models + using the structures and methods of the 'nlme' package. + date_publication: '2015-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covBM + url_git: '' +CovCombR: + version: '1.0' + title: Combine Partial Covariance / Relationship Matrices + maintainer: Deniz Akdemir + description: |- + Combine partial covariance matrices using a Wishart-EM algorithm. + Methods are described in the November 2019 article by Akdemir et al. + . + It can be used to combine partially overlapping covariance matrices + from independent trials, partially overlapping multi-view relationship + data from genomic experiments, partially overlapping Gaussian graphs + described by their covariance structures. + High dimensional covariance estimation, + multi-view data integration. + high dimensional covariance graph estimation. + date_publication: '2020-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CovCombR + url_git: '' +covdepGE: + version: 1.0.1 + title: Covariate Dependent Graph Estimation + maintainer: Jacob Helwig + description: A covariate-dependent approach to Gaussian graphical modeling as described + in Dasgupta et al. (2022). Employs a novel weighted pseudo-likelihood approach + to model the conditional dependence structure of data as a continuous function + of an extraneous covariate. The main function, covdepGE::covdepGE(), estimates + a graphical representation of the conditional dependence structure via a block + mean-field variational approximation, while several auxiliary functions (inclusionCurve(), + matViz(), and plot.covdepGE()) are included for visualizing the resulting estimates. + date_publication: '2022-09-16' + bug_reports: https://github.com/JacobHelwig/covdepGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covdepGE + url_git: https://github.com/JacobHelwig/covdepGE +coveffectsplot: + version: 1.0.6 + title: Produce Forest Plots to Visualize Covariate Effects + maintainer: Samer Mouksassi + description: |- + Produce forest plots to visualize covariate effects using either + the command line or an interactive 'Shiny' application. + date_publication: '2025-01-12' + bug_reports: https://github.com/smouksassi/coveffectsplot/issues + url: https://smouksassi.github.io/coveffectsplot/ + url_cran: https://CRAN.R-project.org/package=coveffectsplot + url_git: https://github.com/smouksassi/coveffectsplot +covequal: + version: 0.1.0 + title: Test for Equality of Covariance Matrices + maintainer: Maxime Turgeon + description: |- + Computes p-values using the largest root test using + an approximation to the null distribution by Johnstone (2008) . + date_publication: '2017-10-14' + bug_reports: http://github.com/turgeonmaxime/covequal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covequal + url_git: http://github.com/turgeonmaxime/covequal +COveR: + version: 1.1.0 + title: Clustering with Overlaps + maintainer: Nicolas Hiot + description: |- + Provide functions for overlaps clustering, fuzzy clustering and interval-valued data manipulation. The package implement the following algorithms: + OKM (Overlapping Kmeans) from Cleuziou, G. (2007) ; + NEOKM (Non-exhaustive overlapping Kmeans) from Whang, J. J., Dhillon, I. S., and Gleich, D. F. (2015) ; + Fuzzy Cmeans from Bezdek, J. C. (1981) ; + Fuzzy I-Cmeans from de A.T. De Carvalho, F. (2005) . + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=COveR + url_git: '' +coveR2: + version: 1.0.0 + title: Process Digital Cover Photography Images of Tree Crowns + maintainer: Francesco Chianucci + description: |- + Process Digital Cover Photography images of tree canopies to get canopy attributes like Foliage Cover and Leaf Area Index. + Detailed description of the methods in Chianucci et al. (2022) . + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coveR2 + url_git: '' +covfefe: + version: 0.1.0 + title: Covfefy Any Word, Sentence or Speech + maintainer: Michael Kirchner + description: |- + Converts any word, sentence or speech into Trump's infamous + "covfefe" format. Reference: . + Inspiration thanks to: . + date_publication: '2017-06-06' + bug_reports: https://github.com/mkirch/covfefe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covfefe + url_git: https://github.com/mkirch/covfefe +covglasso: + version: 1.0.3 + title: Sparse Covariance Matrix Estimation + maintainer: Michael Fop + description: Direct sparse covariance matrix estimation via the covariance graphical + lasso by Bien, Tibshirani (2011) using the fast coordinate + descent algorithm of Wang (2014) . + date_publication: '2021-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covglasso + url_git: '' +COVID19: + version: 3.0.3 + title: R Interface to COVID-19 Data Hub + maintainer: Emanuele Guidotti + description: |- + Provides a daily summary of COVID-19 cases, deaths, recovered, tests, + vaccinations, and hospitalizations for 230+ countries, 760+ regions, + and 12000+ administrative divisions of lower level. + Includes policy measures, mobility data, and geospatial identifiers. + Data source: COVID-19 Data Hub . + date_publication: '2023-02-28' + bug_reports: https://github.com/covid19datahub/COVID19/issues + url: https://covid19datahub.io + url_cran: https://CRAN.R-project.org/package=COVID19 + url_git: '' +covid19.analytics: + version: 2.1.3.3 + title: Load and Analyze Live Data from the COVID-19 Pandemic + maintainer: Marcelo Ponce + description: Load and analyze updated time series worldwide data of reported cases + for the Novel Coronavirus Disease (COVID-19) from different sources, including + the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) + data repository , "Our World in Data" + among several others. The datasets reporting the COVID-19 + cases are available in two main modalities, as a time series sequences and aggregated + data for the last day with greater spatial resolution. Several analysis, visualization + and modelling functions are available in the package that will allow the user + to compute and visualize total number of cases, total number of changes and growth + rate globally or for an specific geographical location, while at the same time + generating models using these trends; generate interactive visualizations and + generate Susceptible-Infected-Recovered (SIR) model for the disease spread. + date_publication: '2023-10-15' + bug_reports: https://github.com/mponce0/covid19.analytics/issues + url: https://mponce0.github.io/covid19.analytics/ + url_cran: https://CRAN.R-project.org/package=covid19.analytics + url_git: '' +covid19br: + version: 0.1.8 + title: Brazilian COVID-19 Pandemic Data + maintainer: Fabio Demarqui + description: Set of functions to import COVID-19 pandemic data into R. The Brazilian + COVID-19 data, obtained from the official Brazilian repository at , + is available at country, region, state, and city-levels. The package also downloads + the world-level COVID-19 data from the John Hopkins University's repository. + date_publication: '2023-10-15' + bug_reports: https://github.com/fndemarqui/covid19br/issues + url: https://fndemarqui.github.io/covid19br/ + url_cran: https://CRAN.R-project.org/package=covid19br + url_git: '' +covid19dbcand: + version: 0.1.1 + title: |- + Selected 'Drugbank' Drugs for COVID-19 Treatment Related Data in + R Format + maintainer: Mohammed Ali + description: |- + Provides different datasets parsed from 'Drugbank' + database using 'dbparser' package. + It is a smaller version from 'dbdataset' package. It contains only information + about COVID-19 possible treatment. + date_publication: '2020-08-26' + bug_reports: https://github.com/MohammedFCIS/covid19dbcand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covid19dbcand + url_git: https://github.com/MohammedFCIS/covid19dbcand +covid19france: + version: 0.1.0 + title: Cases of COVID-19 in France + maintainer: Amanda Dobbyn + description: |- + Imports and cleans 'opencovid19-fr' + data on COVID-19 in France. + date_publication: '2020-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covid19france + url_git: '' +covid19india: + version: 0.1.4 + title: Pulling Clean Data from Covid19india.org + maintainer: Max Salvatore + description: |- + Pull raw and pre-cleaned versions of national and state-level + COVID-19 time-series data from covid19india.org . + Easily obtain and merge case count data, testing data, and vaccine data. + Also assists in calculating the time-varying effective reproduction number + with sensible parameters for COVID-19. + date_publication: '2021-10-09' + bug_reports: https://github.com/maxsal/covid19india/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covid19india + url_git: https://github.com/maxsal/covid19india +covid19italy: + version: 0.3.1 + title: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Italy Dataset + maintainer: Rami Krispin + description: 'Provides a daily summary of the Coronavirus (COVID-19) cases in Italy + by country, region and province level. Data source: Presidenza del Consiglio dei + Ministri - Dipartimento della Protezione Civile .' + date_publication: '2021-07-28' + bug_reports: https://github.com/RamiKrispin/covid19italy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covid19italy + url_git: https://github.com/RamiKrispin/covid19italy +covid19sf: + version: 0.1.2 + title: The Covid19 San Francisco Dataset + maintainer: Rami Krispin + description: 'Provides a verity of summary tables of the Covid19 cases in San Francisco. + Data source: San Francisco, Department of Public Health - Population Health Division + .' + date_publication: '2021-12-19' + bug_reports: https://github.com/RamiKrispin/covid19sf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covid19sf + url_git: https://github.com/RamiKrispin/covid19sf +covid19srilanka: + version: 1.1.0 + title: |- + The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data in Sri + Lanka + maintainer: Thiyanga S. Talagala + description: 'Provides a daily counts of the Coronavirus (COVID19) cases by districts + and country. Data source: Epidemiological Unit, Ministry of Health, Sri Lanka + .' + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covid19srilanka + url_git: '' +covid19swiss: + version: 0.1.0 + title: COVID-19 Cases in Switzerland and Principality of Liechtenstein + maintainer: Rami Krispin + description: 'Provides a daily summary of the Coronavirus (COVID-19) cases in Switzerland + cantons and Principality of Liechtenstein. Data source: Specialist Unit for Open + Government Data Canton of Zurich .' + date_publication: '2020-09-18' + bug_reports: https://github.com/Covid19R/covid19swiss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covid19swiss + url_git: https://github.com/Covid19R/covid19swiss +covid19tunisia: + version: 0.1.0 + title: Cases of COVID-19 in Tunisia + maintainer: Mouna Belaid + description: |- + Data personally collected about the spread of COVID-19 (SARS-COV-2) in Tunisia + . + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covid19tunisia + url_git: https://github.com/MounaBelaid/covid19tunisia +covid19us: + version: 0.1.9 + title: Cases of COVID-19 in the United States + maintainer: Amanda Dobbyn + description: |- + A wrapper around the 'COVID Tracking Project API' + providing data on cases of COVID-19 + in the US. + date_publication: '2022-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covid19us + url_git: '' +covidcast: + version: 0.5.2 + title: Client for Delphi's 'COVIDcast Epidata' API + maintainer: Alex Reinhart + description: |- + Tools for Delphi's 'COVIDcast Epidata' API: data access, maps and + time series plotting, and basic signal processing. The API includes a + collection of numerous indicators relevant to the COVID-19 pandemic in the + United States, including official reports, de-identified aggregated medical + claims data, large-scale surveys of symptoms and public behavior, and + mobility data, typically updated daily and at the county level. All data + sources are documented at + . + date_publication: '2023-07-12' + bug_reports: https://github.com/cmu-delphi/covidcast/issues + url: https://cmu-delphi.github.io/covidcast/covidcastR/ + url_cran: https://CRAN.R-project.org/package=covidcast + url_git: https://github.com/cmu-delphi/covidcast +COVIDIBGE: + version: 0.2.2 + title: Downloading, Reading and Analyzing PNAD COVID19 Microdata + maintainer: Gabriel Assuncao + description: |- + Provides tools for downloading, reading and analyzing the COVID19 National + Household Sample Survey - PNAD COVID19, a household survey from Brazilian Institute + of Geography and Statistics - IBGE. The data must be downloaded from the official + website . Further analysis must be made using package 'survey'. + date_publication: '2024-02-01' + bug_reports: https://github.com/Gabriel-Assuncao/COVIDIBGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=COVIDIBGE + url_git: '' +CovidMutations: + version: 0.1.3 + title: |- + Mutation Analysis Toolkit for COVID-19 (Coronavirus Disease + 2019) + maintainer: Shaoqian Ma + description: |- + A feasible framework for mutation analysis and reverse transcription + polymerase chain reaction (RT-PCR) assay evaluation of COVID-19, including + mutation profile visualization, statistics and mutation ratio of each assay. + The mutation ratio is conducive to evaluating the coverage of RT-PCR assays in + large-sized samples. Mercatelli, D. and Giorgi, F. M. (2020) + . + date_publication: '2020-09-18' + bug_reports: https://github.com/MSQ-123/CovidMutations/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CovidMutations + url_git: https://github.com/MSQ-123/CovidMutations +covidmx: + version: 0.7.7 + title: Descarga y analiza datos de COVID-19 en México + maintainer: Rodrigo Zepeda-Tello + description: |- + Herramientas para el análisis de datos de COVID-19 en México. Descarga y analiza + los datos para COVID-19 de la Direccion General de Epidemiología de México (DGE) + , + la Red de Infecciones Respiratorias Agudas Graves (Red IRAG) + y la Iniciativa Global + para compartir todos los datos de influenza (GISAID) + . + English: Downloads and analyzes data of COVID-19 from the Mexican General + Directorate of Epidemiology (DGE), the Network of + Severe Acute Respiratory Infections (IRAG network),and the Global + Initiative on Sharing All Influenza Data GISAID. + date_publication: '2023-02-17' + bug_reports: https://github.com/RodrigoZepeda/covidmx/issues + url: https://rodrigozepeda.github.io/covidmx/ + url_cran: https://CRAN.R-project.org/package=covidmx + url_git: https://github.com/RodrigoZepeda/covidmx +covidnor: + version: 2023.05.18 + title: Public COVID-19 Data for Norway + maintainer: Chi Zhang + description: Publicly available COVID-19 data for Norway cleaned and merged into + one dataset, including PCR confirmed cases, tests, hospitalisation and vaccination. + date_publication: '2023-05-26' + bug_reports: https://github.com/csids/covidnor/issues + url: https://www.csids.no/covidnor/ + url_cran: https://CRAN.R-project.org/package=covidnor + url_git: https://github.com/csids/covidnor +covidprobability: + version: 0.1.0 + title: Estimate the Unit-Wide Probability of COVID-19 + maintainer: Eric Brown + description: |- + We propose a method to estimate the probability of an + undetected case of COVID-19 in a defined setting, when a given number of + people have been exposed, with a given pretest probability of having + COVID-19 as a result of that exposure. Since we are interested in undetected + COVID-19, we assume no person has developed symptoms (which would warrant + further investigation) and that everyone was tested on a given day, and all + tested negative. + date_publication: '2021-02-11' + bug_reports: https://github.com/eebrown/covidprobability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covidprobability + url_git: https://github.com/eebrown/covidprobability +covidsymptom: + version: 1.0.0 + title: COVID Symptom Study Sweden Open Dataset + maintainer: Hugo Fitipaldi + description: |- + The COVID Symptom Study is a non-commercial project that uses + a free mobile app to facilitate real-time data collection of symptoms, + exposures, and risk factors related to COVID19. The package allows + easy access to summary statistics data from COVID Symptom Study + Sweden. + date_publication: '2024-05-02' + bug_reports: https://github.com/hugofitipaldi/covidsymptom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covidsymptom + url_git: https://github.com/hugofitipaldi/covidsymptom +covKCD: + version: '0.1' + title: |- + Covariance Estimation for Matrix Data with the Kronecker-Core + Decomposition + maintainer: Peter Hoff + description: Matrix-variate covariance estimation via the Kronecker-core decomposition. + Computes the Kronecker and core covariance matrices corresponding to an arbitrary + covariance matrix, and provides an empirical Bayes covariance estimator that adaptively + shrinks towards the space of separable covariance matrices. For details, see Hoff, + McCormack and Zhang (2022) "Core Shrinkage Covariance Estimation + for Matrix-variate data". + date_publication: '2022-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covKCD + url_git: '' +covr: + version: 3.6.4 + title: Test Coverage for Packages + maintainer: Jim Hester + description: |- + Track and report code coverage for your package and (optionally) + upload the results to a coverage service like 'Codecov' or + 'Coveralls' . Code coverage is a measure of the amount of + code being exercised by a set of tests. It is an indirect measure of test + quality and completeness. This package is compatible with any testing + methodology or framework and tracks coverage of both R code and compiled + C/C++/FORTRAN code. + date_publication: '2023-11-09' + bug_reports: https://github.com/r-lib/covr/issues + url: https://covr.r-lib.org + url_cran: https://CRAN.R-project.org/package=covr + url_git: https://github.com/r-lib/covr +covRobust: + version: 1.1-3 + title: Robust Covariance Estimation via Nearest Neighbor Cleaning + maintainer: Hana Sevcikova + description: |- + The cov.nnve() function implements robust covariance estimation + by the nearest neighbor variance estimation (NNVE) method of + Wang and Raftery (2002) . + date_publication: '2017-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covRobust + url_git: '' +CovSel: + version: 1.2.1 + title: Model-Free Covariate Selection + maintainer: Jenny Häggström + description: Model-free selection of covariates under unconfoundedness for situations + where the parameter of interest is an average causal effect. This package is based + on model-free backward elimination algorithms proposed in de Luna, Waernbaum + and Richardson (2011). Marginal co-ordinate hypothesis testing is used in situations + where all covariates are continuous while kernel-based smoothing appropriate for + mixed data is used otherwise. + date_publication: '2015-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CovSel + url_git: '' +covsep: + version: 1.1.0 + title: |- + Tests for Determining if the Covariance Structure of + 2-Dimensional Data is Separable + maintainer: Shahin Tavakoli + description: |- + Functions for testing if the covariance structure of 2-dimensional data + (e.g. samples of surfaces X_i = X_i(s,t)) is separable, i.e. if covariance(X) = + C_1 x C_2. + A complete descriptions of the implemented tests can be found in the paper + Aston, John A. D.; Pigoli, Davide; Tavakoli, Shahin. Tests for separability in + nonparametric covariance operators of random surfaces. Ann. Statist. 45 (2017), + no. 4, 1431--1461. . + date_publication: '2018-05-06' + bug_reports: '' + url: http://arxiv.org/abs/1505.02023 + url_cran: https://CRAN.R-project.org/package=covsep + url_git: '' +covsim: + version: 1.1.0 + title: VITA, IG and PLSIM Simulation for Given Covariance and Marginals + maintainer: Njaal Foldnes + description: |- + Random sampling from distributions with user-specified population covariance matrix. Marginal information may be fully + specified, for which the package implements the VITA (VIne-To-Anything) algorithm + Grønneberg and Foldnes (2017) . See also Grønneberg, Foldnes and Marcoulides (2022) . + Alternatively, marginal skewness and kurtosis may be specified, for which the package + implements the IG (independent generator) and PLSIM (piecewise linear) algorithms, see Foldnes and Olsson (2016) and + Foldnes and Grønneberg (2021) , respectively. + date_publication: '2024-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=covsim + url_git: '' +covTestR: + version: 0.1.4 + title: Covariance Matrix Tests + maintainer: Ben Barnard + description: |- + Testing functions for Covariance Matrices. These tests include high-dimension homogeneity of covariance + matrix testing described by Schott (2007) and high-dimensional one-sample tests of + covariance matrix structure described by Fisher, et al. (2010) . Covariance matrix + tests use C++ to speed performance and allow larger data sets. + date_publication: '2018-08-17' + bug_reports: https://github.com/BenBarnard/covTestR/issues + url: https://covtestr.bearstatistics.com + url_cran: https://CRAN.R-project.org/package=covTestR + url_git: '' +CovTools: + version: 0.5.4 + title: Statistical Tools for Covariance Analysis + maintainer: Kisung You + description: |- + Covariance is of universal prevalence across various disciplines within statistics. + We provide a rich collection of geometric and inferential tools for convenient analysis of + covariance structures, topics including distance measures, mean covariance estimator, + covariance hypothesis test for one-sample and two-sample cases, and covariance estimation. + For an introduction to covariance in multivariate statistical analysis, + see Schervish (1987) . + date_publication: '2021-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CovTools + url_git: https://github.com/kisungyou/CovTools +covtracer: + version: 0.0.1 + title: Contextualizing Tests + maintainer: Doug Kelkhoff + description: |- + Dissects a package environment or 'covr' coverage object in order to cross + reference tested code with the lines that are evaluated, as well as linking + those evaluated lines to the documentation that they are described within. + Connecting these three pieces of information provides a mechanism of + linking tests to documented behaviors. + date_publication: '2024-07-08' + bug_reports: https://github.com/genentech/covtracer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=covtracer + url_git: https://github.com/genentech/covtracer +cowbell: + version: 0.1.0 + title: |- + Performs Segmented Linear Regression on Two Independent + Variables + maintainer: Christoph Luerig + description: |- + Implements a specific form of segmented linear regression + with two independent variables. The visualization of that function looks + like a quarter segment of a cowbell giving the package its name. + The package has been specifically constructed for the case where minimum + and maximum value of the dependent and two independent variables + are known a prior, which is usually the case + when those values are derived from Likert scales. + date_publication: '2017-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cowbell + url_git: '' +cowplot: + version: 1.1.3 + title: Streamlined Plot Theme and Plot Annotations for 'ggplot2' + maintainer: Claus O. Wilke + description: |2- + + Provides various features that help with creating publication-quality figures + with 'ggplot2', such as a set of themes, functions to align plots and arrange + them into complex compound figures, and functions that make it easy to annotate + plots and or mix plots with images. The package was originally written for + internal use in the Wilke lab, hence the name (Claus O. Wilke's plot package). + It has also been used extensively in the book Fundamentals of Data + Visualization. + date_publication: '2024-01-22' + bug_reports: https://github.com/wilkelab/cowplot/issues + url: https://wilkelab.org/cowplot/ + url_cran: https://CRAN.R-project.org/package=cowplot + url_git: '' +cowsay: + version: 1.0.0 + title: Messages, Warnings, Strings with Ascii Animals + maintainer: Scott Chamberlain + description: |- + Allows printing of character strings as messages/warnings/etc. + with ASCII animals, including cats, cows, frogs, chickens, ghosts, + and more. + date_publication: '2024-12-05' + bug_reports: https://github.com/sckott/cowsay/issues + url: https://sckott.github.io/cowsay/ + url_cran: https://CRAN.R-project.org/package=cowsay + url_git: https://github.com/sckott/cowsay +CoxAIPW: + version: 0.0.3 + title: |- + Doubly Robust Inference for Cox Marginal Structural Model with + Informative Censoring + maintainer: Jiyu Luo + description: 'Doubly robust estimation and inference of log hazard ratio under the + Cox marginal structural model with informative censoring. An augmented inverse + probability weighted estimator that involves 3 working models, one for conditional + failure time T, one for conditional censoring time C and one for propensity score. + Both models for T and C can depend on both a binary treatment A and additional + baseline covariates Z, while the propensity score model only depends on Z. With + the help of cross-fitting techniques, achieves the rate-doubly robust property + that allows the use of most machine learning or non-parametric methods for all + 3 working models, which are not permitted in classic inverse probability weighting + or doubly robust estimators. When the proportional hazard assumption is violated, + CoxAIPW estimates a causal estimated that is a weighted average of the time-varying + log hazard ratio. Reference: Luo, J. (2023). Statistical Robustness - Distributed + Linear Regression, Informative Censoring, Causal Inference, and Non-Proportional + Hazards [Unpublished doctoral dissertation]. University of California San Diego.; + Luo & Xu (2022) ; Rava (2021) .' + date_publication: '2023-09-20' + bug_reports: https://github.com/charlesluo1002/CoxAIPW/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CoxAIPW + url_git: https://github.com/charlesluo1002/CoxAIPW +CoxBcv: + version: 0.0.1.0 + title: |- + Bias-Corrected Sandwich Variance Estimators for Marginal Cox + Analysis of Cluster Randomized Trials + maintainer: Xueqi Wang + description: The implementation of bias-corrected sandwich variance estimators for + the analysis of cluster randomized trials with time-to-event outcomes using the + marginal Cox model, proposed by Wang et al. (under review). + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoxBcv + url_git: '' +coxed: + version: 0.3.3 + title: |- + Duration-Based Quantities of Interest for the Cox Proportional + Hazards Model + maintainer: '"Kropko, Jonathan"' + description: Functions for generating, simulating, and visualizing expected durations + and marginal changes in duration from the Cox proportional hazards model as described + in Kropko and Harden (2017) and Harden and Kropko + (2018) . + date_publication: '2020-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coxed + url_git: https://github.com/jkropko/coxed +coxerr: + version: '1.1' + title: Cox Regression with Dependent Error in Covariates + maintainer: Yijian Huang + description: Perform the functional modeling methods of Huang and Wang (2018) + to accommodate dependent error in covariates of the proportional hazards model. + The adopted measurement error model has minimal assumptions on the dependence + structure, and an instrumental variable is supposed to be available. + date_publication: '2023-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coxerr + url_git: '' +CoxICPen: + version: 1.1.0 + title: Variable Selection for Cox's Model with Interval-Censored Data + maintainer: Qiwei Wu + description: Perform variable selection for Cox regression model with interval-censored + data. Can deal with both low-dimensional and high-dimensional data. Case-cohort + design can be incorporated. Two sets of covariates scenario can also be considered. + The references are listed in the URL below. + date_publication: '2021-02-23' + bug_reports: '' + url: https://doi.org/10.1080/01621459.2018.1537922 + url_cran: https://CRAN.R-project.org/package=CoxICPen + url_git: '' +coxme: + version: 2.2-22 + title: Mixed Effects Cox Models + maintainer: Terry M. Therneau + description: |- + Fit Cox proportional hazards models containing both + fixed and random effects. The random effects can have a general form, of which + familial interactions (a "kinship" matrix) is a particular special case. + Note that the simplest case of a mixed effects Cox model, i.e. a single random + per-group intercept, is also called a "frailty" model. The approach is based + on Ripatti and Palmgren, Biometrics 2002. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coxme + url_git: '' +Coxmos: + version: 1.1.1 + title: Cox MultiBlock Survival + maintainer: Pedro Salguero García + description: |- + This software package provides Cox survival analysis for high-dimensional and multiblock datasets. + It encompasses a suite of functions dedicated from the classical Cox regression to newest analysis, + including Cox proportional hazards model, Stepwise Cox regression, and Elastic-Net Cox regression, + Sparse Partial Least Squares Cox regression (sPLS-COX) incorporating three distinct strategies, + and two Multiblock-PLS Cox regression (MB-sPLS-COX) methods. This tool is designed to adeptly handle + high-dimensional data, and provides tools for cross-validation, plot generation, and additional resources + for interpreting results. While references are available within the corresponding functions, + key literature is mentioned below. + Terry M Therneau (2024) , + Noah Simon et al. (2011) , + Philippe Bastien et al. (2005) , + Philippe Bastien (2008) , + Philippe Bastien et al. (2014) , + Kassu Mehari Beyene and Anouar El Ghouch (2020) , + Florian Rohart et al. (2017) . + date_publication: '2025-02-06' + bug_reports: https://github.com/BiostatOmics/Coxmos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Coxmos + url_git: https://github.com/BiostatOmics/Coxmos +coxphf: + version: 1.13.4 + title: Cox Regression with Firth's Penalized Likelihood + maintainer: Georg Heinze + description: |- + Implements Firth's penalized maximum likelihood bias reduction method for Cox regression + which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function), see + Heinze and Schemper (2001) and Heinze and Dunkler (2008). + The program fits profile penalized likelihood confidence intervals which were proved to outperform + Wald confidence intervals. + date_publication: '2023-08-11' + bug_reports: https://github.com/georgheinze/coxphf/issues/ + url: https://cemsiis.meduniwien.ac.at/kb/wf/software/statistische-software/fccoxphf/ + url_cran: https://CRAN.R-project.org/package=coxphf + url_git: '' +coxphm: + version: 0.1.0 + title: Time-to-Event Data Analysis with Missing Survival Times + maintainer: Yunro Chung + description: Fits a pseudo Cox proprotional hazards model that allow us to analyze + time-to-event data when survival times are missing for control groups. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coxphm + url_git: '' +coxphSGD: + version: 0.2.1 + title: |- + Stochastic Gradient Descent log-Likelihood Estimation in Cox + Proportional Hazards Model + maintainer: Marcin Kosinski + description: Estimate coefficients of Cox proportional hazards model using stochastic + gradient descent algorithm for batch data. + date_publication: '2017-07-05' + bug_reports: https://github.com/MarcinKosinski/coxphSGD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coxphSGD + url_git: https://github.com/MarcinKosinski/coxphSGD/blob/master/README.md +coxphw: + version: 4.0.3 + title: Weighted Estimation in Cox Regression + maintainer: Daniela Dunkler + description: |- + Implements weighted estimation in Cox regression as proposed by + Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, + ) and as described in Dunkler, Ploner, Schemper and + Heinze (Journal of Statistical Software, 2018, ). + Weighted Cox regression provides unbiased average hazard ratio + estimates also in case of non-proportional hazards. + Approximated generalized concordance probability an effect size measure for clear-cut + decisions can be obtained. + The package provides options to estimate time-dependent effects conveniently by + including interactions of covariates with arbitrary functions of time, with or without + making use of the weighting option. + date_publication: '2023-11-28' + bug_reports: https://github.com/biometrician/coxphw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coxphw + url_git: https://github.com/biometrician/coxphw +CoxPlus: + version: 1.1.1 + title: |- + Cox Regression (Proportional Hazards Model) with Multiple Causes + and Mixed Effects + maintainer: Jing Peng + description: A high performance package estimating Cox Model when an even has more + than one causes. It also supports random and fixed effects, tied events, and time-varying + variables. + date_publication: '2015-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoxPlus + url_git: '' +CoxR2: + version: '1.0' + title: |- + R-Squared Measure Based on Partial LR Statistic, for the Cox PH + Regression Model + maintainer: Hyeri You + description: Calculate the R-squared, aka explained randomness, based on the partial + likelihood ratio statistic under the Cox Proportional Hazard model [J O'Quigley, + R Xu, J Stare (2005) ]. + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CoxR2 + url_git: '' +coxrobust: + version: 1.0.1 + title: Fit Robustly Proportional Hazards Regression Model + maintainer: Shana Scogin + description: An implementation of robust estimation in Cox model. Functionality + includes fitting efficiently and robustly Cox proportional hazards regression + model in its basic form, where explanatory variables are time independent with + one event per subject. Method is based on a smooth modification of the partial + likelihood. + date_publication: '2022-04-06' + bug_reports: https://github.com/ShanaScogin/coxrobust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coxrobust + url_git: https://github.com/ShanaScogin/coxrobust +coxrt: + version: 1.0.3 + title: Cox Proportional Hazards Regression for Right-Truncated Data + maintainer: Bella Vakulenko-Lagun + description: Fits Cox regression based on retrospectively ascertained times-to-event. + The method uses Inverse-Probability-Weighting estimating equations. + date_publication: '2020-01-07' + bug_reports: https://github.com/Bella2001/coxrt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=coxrt + url_git: https://github.com/Bella2001/coxrt +coxsei: + version: '0.3' + title: Fitting a CoxSEI Model + maintainer: Feng Chen + description: Fit a CoxSEI (Cox type Self-Exciting Intensity) model to right-censored + counting process data. + date_publication: '2020-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=coxsei + url_git: '' +CP: + version: '1.8' + title: Conditional Power Calculations + maintainer: Andreas Kuehnapfel + description: |- + Functions for calculating the conditional power + for different models in survival time analysis + within randomized clinical trials + with two different treatments to be compared + and survival as an endpoint. + date_publication: '2023-05-19' + bug_reports: '' + url: https://www.genstat.imise.uni-leipzig.de/ + url_cran: https://CRAN.R-project.org/package=CP + url_git: '' +cp4p: + version: 0.3.6 + title: Calibration Plot for Proteomics + maintainer: Quentin Giai Gianetto + description: Functions to check whether a vector of p-values respects the assumptions + of FDR (false discovery rate) control procedures and to compute adjusted p-values. + date_publication: '2019-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cp4p + url_git: '' +cpa: + version: 1.0.1 + title: Confirmatory Path Analysis Through 'd-sep' Tests + maintainer: Alessandro Bellino + description: Functions to test and compare causal models using Confirmatory Path + Analysis. + date_publication: '2022-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cpa + url_git: '' +CPAT: + version: 0.1.0 + title: Change Point Analysis Tests + maintainer: Curtis Miller + description: 'Implements several statistical tests for structural change, specifically + the tests featured in Horváth, Rice and Miller (in press): CUSUM (with weighted/trimmed + variants), Darling-Erdös, Hidalgo-Seo, Andrews, and the new Rényi-type test.' + date_publication: '2018-12-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPAT + url_git: '' +CPBayes: + version: 1.1.0 + title: |- + Bayesian Meta Analysis for Studying Cross-Phenotype Genetic + Associations + maintainer: Arunabha Majumdar + description: |- + A Bayesian meta-analysis method for studying cross-phenotype + genetic associations. It uses summary-level data across multiple phenotypes to + simultaneously measure the evidence of aggregate-level pleiotropic association + and estimate an optimal subset of traits associated with the risk locus. CPBayes + is based on a spike and slab prior. The methodology is available from: A Majumdar, T Haldar, S Bhattacharya, JS Witte (2018) . + date_publication: '2020-12-02' + bug_reports: https://github.com/ArunabhaCodes/CPBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CPBayes + url_git: https://github.com/ArunabhaCodes/CPBayes +CPC: + version: 2.6.0 + title: Implementation of Cluster-Polarization Coefficient + maintainer: Isaac Mehlhaff + description: |- + Implements cluster-polarization coefficient for measuring distributional + polarization in single or multiple dimensions, as well as associated functions. + Contains support for hierarchical clustering, k-means, partitioning around medoids, + density-based spatial clustering with noise, and manually imposed cluster membership. + Mehlhaff (forthcoming) . + date_publication: '2024-04-08' + bug_reports: https://github.com/imehlhaff/CPC/issues + url: https://imehlhaff.net/CPC/ + url_cran: https://CRAN.R-project.org/package=CPC + url_git: '' +CPCAT: + version: 1.0.0 + title: The Closure Principle Computational Approach Test + maintainer: René Lehmann + description: P-values and no/lowest observed (adverse) effect concentration values + derived from the closure principle computational approach test (Lehmann, R. et + al. (2015) ) are provided. The package contains + functions to generate intersection hypotheses according to the closure principle + (Bretz, F., Hothorn, T., Westfall, P. (2010) ), an + implementation of the computational approach test (Ching-Hui, C., Nabendu, P., + Jyh-Jiuan, L. (2010) ) and the combination of + both, that is, the closure principle computational approach test. + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPCAT + url_git: '' +cPCG: + version: '1.0' + title: |- + Efficient and Customized Preconditioned Conjugate Gradient + Method for Solving System of Linear Equations + maintainer: Yongwen Zhuang + description: Solves system of linear equations using (preconditioned) conjugate + gradient algorithm, with improved efficiency using Armadillo templated 'C++' linear + algebra library, and flexibility for user-specified preconditioning method. Please + check for latest updates. + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cPCG + url_git: '' +cpd: + version: 0.3.3 + title: Complex Pearson Distributions + maintainer: Silverio Vilchez-Lopez + description: Probability mass function, distribution function, quantile function + and random generation for the Complex Triparametric Pearson (CTP) and Complex + Biparametric Pearson (CBP) distributions developed by Rodriguez-Avi et al (2003) + , Rodriguez-Avi et al (2004) + and Olmo-Jimenez et al (2018) . The package + also contains maximum-likelihood fitting functions for these models. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cpd + url_git: '' +CPE: + version: 1.6.3 + title: Concordance Probability Estimates in Survival Analysis + maintainer: Qianxing Mo + description: Concordance probability estimate (CPE) is a commonly used performance + measure in survival analysis that evaluates the predictive accuracy of a survival + model. It measures how well a model can distinguish between pairs of individuals + with different survival times. Specifically, it calculate the proportion of all + pairs of individuals whose predicted survival times are correctly ordered. + date_publication: '2023-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPE + url_git: '' +cpfa: + version: 1.1-7 + title: Classification with Parallel Factor Analysis + maintainer: Matthew A. Snodgress + description: 'Classification using Richard A. Harshman''s Parallel Factor Analysis-1 + (Parafac) model or Parallel Factor Analysis-2 (Parafac2) model fit to a three-way + or four-way data array. See Harshman and Lundy (1994): . + Uses component weights from one mode of a Parafac or Parafac2 model as features + to tune parameters for one or more classification methods via a k-fold cross-validation + procedure. Allows for constraints on different tensor modes. Supports penalized + logistic regression, support vector machine, random forest, feed-forward neural + network, regularized discriminant analysis, and gradient boosting machine. Supports + binary and multiclass classification. Predicts class labels or class probabilities + and calculates multiple classification performance measures. Implements parallel + computing via the ''parallel'' and ''doParallel'' packages.' + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cpfa + url_git: '' +CpGassoc: + version: '2.70' + title: Association Between Methylation and a Phenotype of Interest + maintainer: R Barfield + description: Is designed to test for association between methylation at CpG sites + across the genome and a phenotype of interest, adjusting for any relevant covariates. + The package can perform standard analyses of large datasets very quickly with + no need to impute the data. It can also handle mixed effects models with chip + or batch entering the model as a random intercept. Also includes tools to apply + quality control filters, perform permutation tests, and create QQ plots, manhattan + plots, and scatterplots for individual CpG sites. + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CpGassoc + url_git: '' +CpGFilter: + version: '1.1' + title: |- + CpG Filtering Method Based on Intra-Class Correlation + Coefficients + maintainer: Jun Chen + description: Filter CpGs based on Intra-class Correlation Coefficients (ICCs) when + replicates are available. ICCs are calculated by fitting linear mixed effects + models to all samples including the un-replicated samples. Including the large + number of un-replicated samples improves ICC estimates dramatically. The method + accommodates any replicate design. + date_publication: '2017-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CpGFilter + url_git: '' +CPGLIB: + version: 1.1.1 + title: Competing Proximal Gradients Library + maintainer: Anthony Christidis + description: |- + Functions to generate ensembles of generalized linear models using + competing proximal gradients. The optimal sparsity and diversity + tuning parameters are selected via an alternating grid search. + date_publication: '2022-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPGLIB + url_git: '' +cpi: + version: 0.1.5 + title: Conditional Predictive Impact + maintainer: Marvin N. Wright + description: |- + A general test for conditional independence in supervised learning + algorithms as proposed by Watson & Wright (2021) . + Implements a conditional variable importance measure which can be applied to any supervised + learning algorithm and loss function. Provides statistical inference procedures without + parametric assumptions and applies equally well to continuous and categorical predictors + and outcomes. + date_publication: '2024-11-25' + bug_reports: https://github.com/bips-hb/cpi/issues + url: https://bips-hb.github.io/cpi/ + url_cran: https://CRAN.R-project.org/package=cpi + url_git: https://github.com/bips-hb/cpi +cplm: + version: 0.7-12.1 + title: Compound Poisson Linear Models + maintainer: Yanwei (Wayne) Zhang + description: Likelihood-based and Bayesian methods for various compound Poisson + linear models based on Zhang, Yanwei (2013) . + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cplm + url_git: https://github.com/actuaryzhang/cplm +cplots: + version: 0.5-0 + title: Plots for Circular Data + maintainer: Yong Wang + description: Provides functions to produce some circular plots for circular data, + in a height- or area-proportional manner. They include bar plots, smooth density + plots, stacked dot plots, histograms, multi-class stacked smooth density plots, + and multi-class stacked histograms. + date_publication: '2022-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cplots + url_git: '' +cpm: + version: '2.3' + title: |- + Sequential and Batch Change Detection Using Parametric and + Nonparametric Methods + maintainer: Gordon J. Ross + description: Sequential and batch change detection for univariate data streams, + using the change point model framework. Functions are provided to allow nonparametric + distribution-free change detection in the mean, variance, or general distribution + of a given sequence of observations. Parametric change detection methods are also + provided for Gaussian, Bernoulli and Exponential sequences. Both the batch (Phase + I) and sequential (Phase II) settings are supported, and the sequences may contain + either a single or multiple change points. A full description of this package + is available in Ross, G.J (2015) - "Parametric and nonparametric sequential change + detection in R" available at . + date_publication: '2020-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cpm + url_git: '' +CPMCGLM: + version: '1.2' + title: |- + Correction of the P-Value after Multiple Coding in Generalized + Linear Models + maintainer: Jeremie Riou + description: We propose to determine the correction of the significance level after + multiple coding of an explanatory variable in Generalized Linear Model. The different + methods of correction of the p-value are the Single step Bonferroni procedure, + and resampling based methods developed by P.H.Westfall in 1993. Resampling methods + are based on the permutation and the parametric bootstrap procedure. If some continuous, + and dichotomous transformations are performed this package offers an exact correction + of the p-value developed by B.Liquet & D.Commenges in 2005. The naive method with + no correction is also available. + date_publication: '2017-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPMCGLM + url_git: '' +CpmERCCutoff: + version: 1.0.0 + title: Calculation of Log2 Counts per Million Cutoff from ERCC Controls + maintainer: Kristen Steenbergen + description: Implementation of the empirical method to derive log2 counts per million + (CPM) cutoff to filter out lowly expressed genes using ERCC spike-ins as described + in Goll and Bosinger et.al (2022). This package + utilizes the synthetic mRNA control pairs developed by the External RNA Controls + Consortium (ERCC) (ERCC 1 / ERCC 2) that are spiked into sample pairs at known + ratios at various absolute abundances. The relationship between the observed + and expected fold changes is then used to empirically determine an optimal log2 + CPM cutoff for filtering out lowly expressed genes. + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CpmERCCutoff + url_git: '' +cpmr: + version: 0.1.0 + title: Connectome Predictive Modelling in R + maintainer: Liang Zhang + description: |- + Connectome Predictive Modelling (CPM) (Shen et al. (2017) + ) is a method to predict individual + differences in behaviour from brain functional connectivity. 'cpmr' + provides a simple yet efficient implementation of this method. + date_publication: '2024-10-06' + bug_reports: https://github.com/psychelzh/cpmr/issues + url: https://psychelzh.github.io/cpmr/ + url_cran: https://CRAN.R-project.org/package=cpmr + url_git: https://github.com/psychelzh/cpmr +CPNCoverageAnalysis: + version: 1.1.0 + title: Conceptual Properties Norming Studies as Parameter Estimation + maintainer: Sebastian Moreno + description: Implementation of conceptual properties norming studies, including + estimates of CPNs parameters with their corresponding variances and estimates + for the sampling process, and a sampling property function based on a modified + empirical distribution from the original data. + date_publication: '2021-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPNCoverageAnalysis + url_git: '' +cpop: + version: 1.0.7 + title: Detection of Multiple Changes in Slope in Univariate Time-Series + maintainer: Daniel Grose + description: Detects multiple changes in slope using the CPOP dynamic programming + approach of Fearnhead, Maidstone, and Letchford (2019) . + This method finds the best continuous piecewise linear fit to data under a criterion + that measures fit to data using the residual sum of squares, but penalizes complexity + based on an L0 penalty on changes in slope. Further information regarding the + use of this package with detailed examples can be found in Fearnhead and Grose + (2024) . + date_publication: '2024-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cpop + url_git: '' +CPoptim: + version: 0.1.0 + title: Convex Partition Optimisation + maintainer: Erick G.G. de Paz + description: |- + Convex Partition is a black-box optimisation algorithm for single + objective real-parameters functions. The basic principle is to progressively + estimate and exploit a regression tree similar to a CART (Classification and + Regression Tree) of the objective function. For more details see + 'de Paz' (2024) and + 'Loh' (2011) . + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPoptim + url_git: '' +CPP: + version: 0.1.0 + title: Composition of Probabilistic Preferences (CPP) + maintainer: Luiz O. Gavião + description: CPP is a multiple criteria decision method to evaluate alternatives + on complex decision making problems, by a probabilistic approach. The CPP was + created and expanded by Sant'Anna, Annibal P. (2015) . + date_publication: '2018-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPP + url_git: '' +cpp11: + version: 0.5.1 + title: A C++11 Interface for R's C Interface + maintainer: Davis Vaughan + description: |- + Provides a header only, C++11 interface to R's C + interface. Compared to other approaches 'cpp11' strives to be safe + against long jumps from the C API as well as C++ exceptions, conform + to normal R function semantics and supports interaction with 'ALTREP' + vectors. + date_publication: '2024-12-04' + bug_reports: https://github.com/r-lib/cpp11/issues + url: https://cpp11.r-lib.org + url_cran: https://CRAN.R-project.org/package=cpp11 + url_git: https://github.com/r-lib/cpp11 +cpp11armadillo: + version: 0.4.4 + title: An 'Armadillo' Interface + maintainer: Mauricio Vargas Sepulveda + description: |- + Provides function declarations and inline function definitions that + facilitate communication between R and the 'Armadillo' 'C++' library for + linear algebra and scientific computing. This implementation is detailed + in Vargas Sepulveda and Schneider Malamud (2024) + . + date_publication: '2025-02-20' + bug_reports: https://github.com/pachadotdev/cpp11armadillo/issues + url: https://pacha.dev/cpp11armadillo/ + url_cran: https://CRAN.R-project.org/package=cpp11armadillo + url_git: https://github.com/pachadotdev/cpp11armadillo +cpp11bigwig: + version: 0.1.1 + title: Read bigWig and bigBed Files + maintainer: Jay Hesselberth + description: |- + Read bigWig and bigBed files using "libBigWig" + . Provides lightweight access + to the binary bigWig and bigBed formats developed by the UCSC Genome + Browser group. + date_publication: '2025-01-19' + bug_reports: https://github.com/rnabioco/cpp11bigwig/issues + url: https://rnabioco.github.io/cpp11bigwig/ + url_cran: https://CRAN.R-project.org/package=cpp11bigwig + url_git: https://github.com/rnabioco/cpp11bigwig +cpp11eigen: + version: 0.2.0 + title: An 'Eigen' Interface + maintainer: Mauricio Vargas Sepulveda + description: |- + Provides function declarations and inline function definitions that + facilitate communication between R and the 'Eigen' 'C++' library for + linear algebra and scientific computing. + date_publication: '2024-09-04' + bug_reports: https://github.com/pachadotdev/cpp11eigen/issues + url: https://pacha.dev/cpp11eigen/ + url_cran: https://CRAN.R-project.org/package=cpp11eigen + url_git: https://github.com/pachadotdev/cpp11eigen +cpp11qpdf: + version: 1.3.5 + title: Split, Combine and Compress PDF Files + maintainer: Mauricio Vargas Sepulveda + description: |- + Bindings to 'qpdf': + 'qpdf' () is a an open-source PDF rendering + library that allows to conduct content-preserving transformations of PDF + files such as split, combine, and compress PDF files. + date_publication: '2024-12-19' + bug_reports: https://github.com/pachadotdev/cpp11qpdf/issues + url: https://pacha.dev/cpp11qpdf/ + url_cran: https://CRAN.R-project.org/package=cpp11qpdf + url_git: '' +cppcheckR: + version: 1.0.0 + title: Check 'C' and 'C++' Files using 'Cppcheck' + maintainer: Stéphane Laurent + description: |- + Allow to run 'Cppcheck' () + on 'C' and 'C++' files with a 'R' command or a 'RStudio' addin. The report + appears in the 'RStudio' viewer pane as a formatted 'HTML' file. It is + also possible to get this report with a 'shiny' application. 'Cppcheck' + can spot many error types and it can also give some recommendations on the + code. + date_publication: '2022-06-10' + bug_reports: https://github.com/stla/cppcheckR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cppcheckR + url_git: https://github.com/stla/cppcheckR +cppdoubles: + version: 0.3.0 + title: Fast Relative Comparisons of Floating Point Numbers in 'C++' + maintainer: Nick Christofides + description: |- + Compare double-precision floating point vectors using + relative differences. All equality operations are calculated using + 'cpp11'. + date_publication: '2024-11-12' + bug_reports: https://github.com/NicChr/cppdoubles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cppdoubles + url_git: '' +cppRouting: + version: '3.1' + title: |- + Algorithms for Routing and Solving the Traffic Assignment + Problem + maintainer: Vincent Larmet + description: |- + Calculation of distances, shortest paths and isochrones on weighted graphs using several variants of Dijkstra algorithm. + Proposed algorithms are unidirectional Dijkstra (Dijkstra, E. W. (1959) ), + bidirectional Dijkstra (Goldberg, Andrew & Fonseca F. Werneck, Renato (2005) ), + A* search (P. E. Hart, N. J. Nilsson et B. Raphael (1968) ), + new bidirectional A* (Pijls & Post (2009) ), + Contraction hierarchies (R. Geisberger, P. Sanders, D. Schultes and D. Delling (2008) ), + PHAST (D. Delling, A.Goldberg, A. Nowatzyk, R. Werneck (2011) ). + Algorithms for solving the traffic assignment problem are All-or-Nothing assignment, + Method of Successive Averages, + Frank-Wolfe algorithm (M. Fukushima (1984) ), + Conjugate and Bi-Conjugate Frank-Wolfe algorithms (M. Mitradjieva, P. O. Lindberg (2012) ), + Algorithm-B (R. B. Dial (2006) ). + date_publication: '2022-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cppRouting + url_git: https://github.com/vlarmet/cppRouting +cpr: + version: 0.4.0 + title: Control Polygon Reduction + maintainer: Peter DeWitt + description: |- + Implementation of the Control Polygon Reduction and Control Net + Reduction methods for finding parsimonious B-spline regression models. + date_publication: '2024-02-15' + bug_reports: https://github.com/dewittpe/cpr/issues + url: http://www.peteredewitt.com/cpr/ + url_cran: https://CRAN.R-project.org/package=cpr + url_git: https://github.com/dewittpe/cpr/ +cprobit: + version: 1.0.2 + title: Conditional Probit Model for Analysing Continuous Outcomes + maintainer: Ning Yilin + description: |- + Implements the three-step workflow for robust analysis of change in + two repeated measurements of continuous outcomes, described in Ning et al. + (in press), "Robust estimation of the effect of an exposure on the change in + a continuous outcome", BMC Medical Research Methodology. + date_publication: '2020-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cprobit + url_git: '' +cprr: + version: 0.2.0 + title: Functions for Working with Danish CPR Numbers + maintainer: Jacob Anhøj + description: |- + Calculate date of birth, age, and gender, and generate anonymous + sequence numbers from CPR numbers. + . + date_publication: '2019-03-17' + bug_reports: http://github.com/anhoej/cprr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cprr + url_git: http://github.com/anhoej/cprr +cPseudoMaRg: + version: 1.0.1 + title: Constructs a Correlated Pseudo-Marginal Sampler + maintainer: Taylor Brown + description: The primary function makeCPMSampler() generates a sampler function + which performs the correlated pseudo-marginal method of Deligiannidis, Doucet + and Pitt (2017) . If the 'rho=' argument of makeCPMSampler() + is set to 0, then the generated sampler function performs the original pseudo-marginal + method of Andrieu and Roberts (2009) . The sampler function + is constructed with the user's choice of prior, parameter proposal distribution, + and the likelihood approximation scheme. Note that this algorithm is not automatically + tuned--each one of these arguments must be carefully chosen. + date_publication: '2021-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cPseudoMaRg + url_git: '' +cpsR: + version: 1.0.0 + title: Load CPS Microdata into R Using the 'Census Bureau Data' API + maintainer: Matt Saenz + description: |- + Load Current Population Survey (CPS) microdata into R using the + 'Census Bureau Data' API + (), including basic + monthly CPS and CPS ASEC microdata. + date_publication: '2023-09-09' + bug_reports: https://github.com/matt-saenz/cpsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cpsR + url_git: https://github.com/matt-saenz/cpsR +cpss: + version: 0.0.3 + title: Change-Point Detection by Sample-Splitting Methods + maintainer: Guanghui Wang + description: |- + Implements multiple change searching algorithms for a variety of + frequently considered parametric change-point models. In particular, it + integrates a criterion proposed by Zou, Wang and Li (2020) + to select the number of change-points in a + data-driven fashion. Moreover, it also provides interfaces for + user-customized change-point models with one's own cost function and + parameter estimation routine. It is easy to get started with the + cpss.* set of functions by accessing their documentation pages + (e.g., ?cpss). + date_publication: '2022-08-22' + bug_reports: https://github.com/ghwang-nk/cpss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cpss + url_git: https://github.com/ghwang-nk/cpss +CPsurv: + version: 1.0.0 + title: Nonparametric Change Point Estimation for Survival Data + maintainer: Stefanie Krügel + description: Nonparametric change point estimation for survival data based on p-values + of exact binomial tests. + date_publication: '2017-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CPsurv + url_git: '' +cpsurvsim: + version: 1.2.2 + title: Simulating Survival Data from Change-Point Hazard Distributions + maintainer: Camille Hochheimer + description: |- + Simulates time-to-event data + with type I right censoring using two methods: the inverse CDF + method and our proposed memoryless method. The latter method + takes advantage of the memoryless property of survival and + simulates a separate distribution between change-points. We + include two parametric distributions: exponential and Weibull. + Inverse CDF method draws on the work of Rainer Walke (2010), + . + date_publication: '2023-09-05' + bug_reports: https://github.com/camillejo/cpsurvsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cpsurvsim + url_git: https://github.com/camillejo/cpsurvsim +cpsvote: + version: 0.1.0 + title: A Toolbox for Using the CPS’s Voting and Registration Supplement + maintainer: Jay Lee + description: |- + Provides automated methods for downloading, recoding, and merging + selected years of the Current Population Survey's Voting and Registration + Supplement, a large N national survey about registration, voting, and + non-voting in United States federal elections. Provides documentation for + appropriate use of sample weights to generate statistical estimates, + drawing from Hur & Achen (2013) and McDonald (2018) + . + date_publication: '2020-11-05' + bug_reports: https://github.com/Reed-EVIC/cpsvote/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cpsvote + url_git: https://github.com/Reed-EVIC/cpsvote +cpt: + version: 1.0.2 + title: Classification Permutation Test + maintainer: Johann Gagnon-Bartsch + description: Non-parametric test for equality of multivariate distributions. Trains + a classifier to classify (multivariate) observations as coming from one of several + distributions. If the classifier is able to classify the observations better + than would be expected by chance (using permutation inference), then the null + hypothesis that the distributions are equal is rejected. + date_publication: '2018-10-30' + bug_reports: '' + url: http://dept.stat.lsa.umich.edu/~johanngb + url_cran: https://CRAN.R-project.org/package=cpt + url_git: '' +cptcity: + version: 1.1.1 + title: '''cpt-city'' Colour Gradients' + maintainer: Sergio Ibarra-Espinosa + description: Incorporates colour gradients from the 'cpt-city' web archive available + at . + date_publication: '2024-12-02' + bug_reports: https://github.com/ibarraespinosa/cptcity/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=cptcity + url_git: https://github.com/ibarraespinosa/cptcity +CptNonPar: + version: 0.2.1 + title: |- + Nonparametric Change Point Detection for Multivariate Time + Series + maintainer: Euan T. McGonigle + description: |- + Implements the nonparametric moving sum procedure for detecting + changes in the joint characteristic function (NP-MOJO) for multiple change + point detection in multivariate time series. See McGonigle, E. T., Cho, H. + (2023) for description of the NP-MOJO methodology. + date_publication: '2024-04-23' + bug_reports: https://github.com/EuanMcGonigle/CptNonPar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CptNonPar + url_git: https://github.com/EuanMcGonigle/CptNonPar +cqrReg: + version: 1.2.1 + title: Quantile, Composite Quantile Regression and Regularized Versions + maintainer: Jueyu Gao + description: Estimate quantile regression(QR) and composite quantile regression + (cqr) and with adaptive lasso penalty using interior point (IP), majorize and + minimize(MM), coordinate descent (CD), and alternating direction method of multipliers + algorithms(ADMM). + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cqrReg + url_git: '' +cquad: + version: '2.3' + title: |- + Conditional Maximum Likelihood for Quadratic Exponential Models + for Binary Panel Data + maintainer: Francesco Bartolucci + description: |- + Estimation, based on conditional maximum likelihood, of the quadratic exponential + model proposed by Bartolucci, F. & Nigro, V. (2010, Econometrica) + and of a simplified and a modified version of this model. The quadratic exponential model + is suitable for the analysis of binary longitudinal data when state dependence (further + to the effect of the covariates and a time-fixed individual intercept) has to be taken + into account. Therefore, this is an alternative to the dynamic logit model having the + advantage of easily allowing conditional inference in order to eliminate the individual + intercepts and then getting consistent estimates of the parameters of main interest + (for the covariates and the lagged response). The simplified version of this model + does not distinguish, as the original model does, between the last time occasion + and the previous occasions. The modified version formulates in a different way the + interaction terms and it may be used to test in a easy way state dependence as shown + in Bartolucci, F., Nigro, V. & Pigini, C. (2018, Econometric Reviews) . + The package also includes estimation of the dynamic logit model by a pseudo conditional + estimator based on the quadratic exponential model, as proposed by + Bartolucci, F. & Nigro, V. (2012, Journal of Econometrics) . + For large time dimensions of the panel, the computation of the proposed models involves a + recursive function from Krailo M. D., & Pike M. C. (1984, Journal of the Royal + Statistical Society. Series C (Applied Statistics)) and Bartolucci F., Valentini, F. & Pigini C. + (2021, Computational Economics . + date_publication: '2023-02-28' + bug_reports: https://github.com/fravale/cquad_dev/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cquad + url_git: https://github.com/fravale/cquad_dev/(developmentrepository) +CR2: + version: 0.2.1 + title: |- + Compute Cluster Robust Standard Errors with Degrees of Freedom + Adjustments + maintainer: Francis Huang + description: 'Estimate different types of cluster robust standard errors (CR0, CR1, + CR2) with degrees of freedom adjustments. Standard errors are computed based on + ''Liang and Zeger'' (1986) and Bell and ''McCaffrey'' + . + Functions used in Huang and Li , Huang, ''Wiedermann'', + and ''Zhang'' , and Huang, ''Zhang'', and Li + (forthcoming: Journal of Research on Educational Effectiveness).' + date_publication: '2023-01-09' + bug_reports: https://github.com/flh3/CR2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CR2 + url_git: https://github.com/flh3/CR2 +CRABS: + version: 1.2.0 + title: Congruent Rate Analyses in Birth-Death Scenarios + maintainer: Bjørn Tore Kopperud + description: Features tools for exploring congruent phylogenetic birth-death models. + It can construct the pulled speciation- and net-diversification rates from a reference + model. Given alternative speciation- or extinction rates, it can construct new + models that are congruent with the reference model. Functionality is included + to sample new rate functions, and to visualize the distribution of one congruence + class. See also Louca & Pennell (2020) . + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CRABS + url_git: https://github.com/afmagee/CRABS +cragg: + version: 0.0.1 + title: Tests for Weak Instruments in R + maintainer: Beniamino Green + description: Implements Cragg-Donald (1993) and + Stock and Yogo (2005) tests for weak instruments + in R. + date_publication: '2021-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cragg + url_git: '' +cramer: + version: 0.9-4 + title: |- + Multivariate Nonparametric Cramer-Test for the + Two-Sample-Problem + maintainer: Carsten Franz + description: |- + Provides R routine for the so called two-sample + Cramer-Test. This nonparametric two-sample-test on equality + of the underlying distributions can be applied to + multivariate data as well as univariate data. It offers two + possibilities to approximate the critical value both of which + are included in this package. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cramer + url_git: '' +crandep: + version: 0.3.11 + title: Network Analysis of Dependencies of CRAN Packages + maintainer: Clement Lee + description: The dependencies of CRAN packages can be analysed in a network fashion. + For each package we can obtain the packages that it depends, imports, suggests, + etc. By iterating this procedure over a number of packages, we can build, visualise, + and analyse the dependency network, enabling us to have a bird's-eye view of the + CRAN ecosystem. One aspect of interest is the number of reverse dependencies of + the packages, or equivalently the in-degree distribution of the dependency network. + This can be fitted by the power law and/or an extreme value mixture distribution + , of which functions are provided. + date_publication: '2024-12-06' + bug_reports: https://github.com/clement-lee/crandep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crandep + url_git: https://github.com/clement-lee/crandep +crane: + version: 0.1.0 + title: Supplements the 'gtsummary' Package for Pharmaceutical Reporting + maintainer: Daniel D. Sjoberg + description: |- + Tables summarizing clinical trial results are often complex + and require detailed tailoring prior to submission to a health + authority. The 'crane' package supplements the functionality of the + 'gtsummary' package for creating these often highly bespoke tables in + the pharmaceutical industry. + date_publication: '2025-02-24' + bug_reports: https://github.com/insightsengineering/crane/issues + url: https://insightsengineering.github.io/crane/ + url_cran: https://CRAN.R-project.org/package=crane + url_git: https://github.com/insightsengineering/crane +crank: + version: 1.1-2 + title: Completing Ranks + maintainer: Jim Lemon + description: Functions for completing and recalculating rankings and sorting. + date_publication: '2019-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crank + url_git: '' +cranlike: + version: 1.0.3 + title: Tools for 'CRAN'-Like Repositories + maintainer: Gábor Csárdi + description: |- + A set of functions to manage 'CRAN'-like repositories + efficiently. + date_publication: '2024-04-24' + bug_reports: https://github.com/r-hub/cranlike/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cranlike + url_git: https://github.com/r-hub/cranlike +cranlogs: + version: 2.1.1 + title: Download Logs from the 'RStudio' 'CRAN' Mirror + maintainer: Gábor Csárdi + description: |- + 'API' to the database of 'CRAN' package downloads from the + 'RStudio' 'CRAN mirror'. The database itself is at , + see for the raw 'API'. + date_publication: '2019-04-29' + bug_reports: https://github.com/r-hub/cranlogs/issues + url: https://r-hub.github.io/cranlogs + url_cran: https://CRAN.R-project.org/package=cranlogs + url_git: https://github.com/r-hub/cranlogs +cranly: + version: 0.6.0 + title: Package Directives and Collaboration Networks in CRAN + maintainer: Ioannis Kosmidis + description: Core visualizations and summaries for the CRAN package database. The + package provides comprehensive methods for cleaning up and organizing the information + in the CRAN package database, for building package directives networks (depends, + imports, suggests, enhances, linking to) and collaboration networks, producing + package dependence trees, and for computing useful summaries and producing interactive + visualizations from the resulting networks and summaries. The resulting networks + can be coerced to 'igraph' objects + for further analyses and modelling. + date_publication: '2022-08-26' + bug_reports: https://github.com/ikosmidis/cranly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cranly + url_git: https://github.com/ikosmidis/cranly +CRANsearcher: + version: 1.0.0 + title: |- + RStudio Addin for Searching Packages in CRAN Database Based on + Keywords + maintainer: Agustin Calatroni + description: One of the strengths of R is its vast package ecosystem. Indeed, R + packages extend from visualization to Bayesian inference and from spatial analyses + to pharmacokinetics (). There is probably + not an area of quantitative research that isn't represented by at least one R + package. At the time of this writing, there are more than 10,000 active CRAN packages. + Because of this massive ecosystem, it is important to have tools to search and + learn about packages related to your personal R needs. For this reason, we developed + an RStudio addin capable of searching available CRAN packages directly within + RStudio. + date_publication: '2017-06-26' + bug_reports: https://github.com/RhoInc/CRANsearcher/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CRANsearcher + url_git: https://github.com/RhoInc/CRANsearcher +crassmat: + version: 0.0.6 + title: Conditional Random Sampling Sparse Matrices + maintainer: Nick Kunz + description: Conducts conditional random sampling on observed values in sparse matrices. + Useful for training and test set splitting sparse matrices prior to model fitting + in cross-validation procedures and estimating the predictive accuracy of data + imputation methods, such as matrix factorization or singular value decomposition + (SVD). Although designed for applications with sparse matrices, CRASSMAT can also + be applied to complete matrices, as well as to those containing missing values. + date_publication: '2019-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crassmat + url_git: '' +crawl: + version: 2.3.0 + title: |- + Fit Continuous-Time Correlated Random Walk Models to Animal + Movement Data + maintainer: Devin S. Johnson + description: |- + Fit continuous-time correlated random walk models with time indexed + covariates to animal telemetry data. The model is fit using the Kalman-filter on + a state space version of the continuous-time stochastic movement process. + date_publication: '2022-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crawl + url_git: '' +crayon: + version: 1.5.3 + title: Colored Terminal Output + maintainer: Gábor Csárdi + description: |- + The crayon package is now superseded. Please use the 'cli' + package for new projects. Colored terminal output on terminals that + support 'ANSI' color and highlight codes. It also works in 'Emacs' + 'ESS'. 'ANSI' color support is automatically detected. Colors and + highlighting can be combined and nested. New styles can also be + created easily. This package was inspired by the 'chalk' 'JavaScript' + project. + date_publication: '2024-06-20' + bug_reports: https://github.com/r-lib/crayon/issues + url: https://r-lib.github.io/crayon/ + url_cran: https://CRAN.R-project.org/package=crayon + url_git: https://github.com/r-lib/crayon +crayons: + version: 0.0.3 + title: Color Palettes from Crayon Boxes + maintainer: Christopher T. Kenny + description: |- + Provides color palettes based on crayon colors since the early 1900s. + Colors are based on various crayon colors, sets, and promotional palettes, most of + which can be found at . All + palettes are discrete palettes and are not necessarily color-blind friendly. + Provides scales for 'ggplot2' for discrete coloring. + date_publication: '2024-03-21' + bug_reports: https://github.com/christopherkenny/crayons/issues + url: http://christophertkenny.com/crayons/ + url_cran: https://CRAN.R-project.org/package=crayons + url_git: https://github.com/christopherkenny/crayons +crc32c: + version: 0.0.2 + title: Cyclic Redundancy Check with CPU-Specific Acceleration + maintainer: Dirk Eddelbuettel + description: |- + Hardware-based support for 'CRC32C' cyclic redundancy checksum function + is made available for 'x86_64' systems with 'SSE2' support as well as for 'arm64', + and detected at build-time via 'cmake' with a software-based fallback. This + functionality is exported at the 'C'-language level for use by other packages. + 'CRC32C' is described in 'RFC 3270' at + and is based on 'Castagnoli et al' . + date_publication: '2023-05-11' + bug_reports: https://github.com/eddelbuettel/crc32c/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crc32c + url_git: https://github.com/google/crc32c +crch: + version: 1.2-1 + title: Censored Regression with Conditional Heteroscedasticity + maintainer: Achim Zeileis + description: |- + Different approaches to censored or truncated regression with + conditional heteroscedasticity are provided. First, continuous + distributions can be used for the (right and/or left censored or truncated) + response with separate linear predictors for the mean and variance. + Second, cumulative link models for ordinal data + (obtained by interval-censoring continuous data) can be employed for + heteroscedastic extended logistic regression (HXLR). In the latter type of + models, the intercepts depend on the thresholds that define the intervals. + Infrastructure for working with censored or truncated normal, logistic, + and Student-t distributions, i.e., d/p/q/r functions and distributions3 + objects. + date_publication: '2024-09-16' + bug_reports: https://topmodels.R-Forge.R-project.org/crch/contact.html + url: '' + url_cran: https://CRAN.R-project.org/package=crch + url_git: https://topmodels.R-Forge.R-project.org/crch/ +crctStepdown: + version: 0.5.2 + title: Univariate Analysis of Cluster Trials with Multiple Outcomes + maintainer: Sam Watson + description: |- + Frequentist statistical inference for cluster randomised trials with + multiple outcomes that controls the family-wise error rate and provides nominal + coverage of confidence sets. A full description of the methods can be found in Watson et al. (2023) . + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crctStepdown + url_git: '' +CRE: + version: 0.2.7 + title: |- + Interpretable Discovery and Inference of Heterogeneous Treatment + Effects + maintainer: Falco Joannes Bargagli Stoffi + description: |- + Provides a new method for interpretable heterogeneous + treatment effects characterization in terms of decision rules + via an extensive exploration of heterogeneity patterns by an + ensemble-of-trees approach, enforcing high stability in the + discovery. It relies on a two-stage pseudo-outcome regression, and + it is supported by theoretical convergence guarantees. Bargagli-Stoffi, + F. J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble: + Interpretable Discovery and Inference of Heterogeneous Treatment Effects. + arXiv preprint . + date_publication: '2024-10-19' + bug_reports: https://github.com/NSAPH-Software/CRE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CRE + url_git: https://github.com/NSAPH-Software/CRE +CREAM: + version: 1.1.1 + title: Clustering of Genomic Regions Analysis Method + maintainer: Benjamin Haibe-Kains + description: |- + Provides a new method for identification of clusters of genomic + regions within chromosomes. Primarily, it is used for calling clusters of + cis-regulatory elements (COREs). 'CREAM' uses genome-wide maps of genomic regions + in the tissue or cell type of interest, such as those generated from chromatin-based + assays including DNaseI, ATAC or ChIP-Seq. 'CREAM' considers proximity of the elements + within chromosomes of a given sample to identify COREs in the following steps: + 1) It identifies window size or the maximum allowed distance between the elements + within each CORE, 2) It identifies number of elements which should be clustered + as a CORE, 3) It calls COREs, 4) It filters the COREs with lowest order which + does not pass the threshold considered in the approach. + date_publication: '2018-06-06' + bug_reports: https://github.com/bhklab/CREAM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CREAM + url_git: https://github.com/bhklab/CREAM +createLogicalPCM: + version: 0.1.0 + title: |- + Create Logical Pairwise Comparison Matrix for the Analytic + Hierarchy Process + maintainer: Amarnath Bose + description: Create Pairwise Comparison Matrices for use in the Analytic Hierarchy + Process. The Pairwise Comparison Matrix created will be a logical matrix, which + unlike a random comparison matrix, is similar to what a rational decision maker + would create on the basis of a preference vector for the alternatives considered. + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=createLogicalPCM + url_git: '' +credentials: + version: 2.0.2 + title: Tools for Managing SSH and Git Credentials + maintainer: Jeroen Ooms + description: |- + Setup and retrieve HTTPS and SSH credentials for use with 'git' and + other services. For HTTPS remotes the package interfaces the 'git-credential' + utility which 'git' uses to store HTTP usernames and passwords. For SSH + remotes we provide convenient functions to find or generate appropriate SSH + keys. The package both helps the user to setup a local git installation, and + also provides a back-end for git/ssh client libraries to authenticate with + existing user credentials. + date_publication: '2024-10-04' + bug_reports: https://github.com/r-lib/credentials/issues + url: https://docs.ropensci.org/credentials/https://r-lib.r-universe.dev/credentials + url_cran: https://CRAN.R-project.org/package=credentials + url_git: '' +CRediTas: + version: 0.2.0 + title: Generate CRediT Author Statements + maintainer: Josep Pueyo-Ros + description: |- + A tiny package to generate CRediT author statements (). + It provides three functions: create a template, read it back and generate the CRediT author statement in a text file. + date_publication: '2023-04-13' + bug_reports: https://github.com/ropensci/CRediTas/issues/ + url: https://docs.ropensci.org/CRediTas/ + url_cran: https://CRAN.R-project.org/package=CRediTas + url_git: https://github.com/ropensci/CRediTas/ +creditmodel: + version: 1.3.1 + title: Toolkit for Credit Modeling, Analysis and Visualization + maintainer: Dongping Fan + description: |2- + + Provides a highly efficient R tool suite for Credit Modeling, Analysis and Visualization.Contains infrastructure functionalities such as data exploration and preparation, missing values treatment, outliers treatment, variable derivation, variable selection, dimensionality reduction, grid search for hyper parameters, data mining and visualization, model evaluation, strategy analysis etc. This package is designed to make the development of binary classification models (machine learning based models as well as credit scorecard) simpler and faster. The references including: 1 Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS; 2 Bezdek, James C.FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences (0098-3004),. + date_publication: '2022-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=creditmodel + url_git: '' +creditr: + version: 0.6.2 + title: Credit Default Swaps + maintainer: Yanrong Song + description: |- + Price credit default swaps using + 'C' code from the International Swaps and Derivatives + Association CDS Standard Model. See + + for more information about the model and + + for license details for the 'C' code. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=creditr + url_git: https://github.com/yanrong-stacy-song/creditr +CreditRisk: + version: 0.1.7 + title: |- + Evaluation of Credit Risk with Structural and Reduced Form + Models + maintainer: Alessandro Cimarelli + description: 'Evaluation of default probability of sovereign and corporate entities + based on structural or intensity based models and calibration on market Credit + Default Swap quotes. References: Damiano Brigo, Massimo Morini, Andrea Pallavicini + (2013) . Print ISBN: 9780470748466, Online ISBN: 9781118818589. + © 2013 John Wiley & Sons Ltd.' + date_publication: '2024-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CreditRisk + url_git: '' +CREDS: + version: 0.1.0 + title: Calibrated Ratio Estimator under Double Sampling Design + maintainer: Dr. Sadikul Islam + description: Population ratio estimator (calibrated) under two-phase random sampling + design has gained enormous popularity in the recent time. This package provides + functions for estimation population ratio (calibrated) under two phase sampling + design, including the approximate variance of the ratio estimator. The improved + ratio estimator can be applicable for both the case, when auxiliary data is available + at unit level or aggregate level (eg., mean or total) for first phase sampled. + Calibration weight of each unit of the second phase sample was calculated. Single + and combined inclusion probabilities were also estimated for both phases under + two phase random [simple random sampling without replacement (SRSWOR)] sampling. + The improved ratio estimator's percentage coefficient of variation was also determined + as a measure of accuracy. This package has been developed based on the theoretical + development of Islam et al. (2021) and Ozgul (2020) . + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CREDS + url_git: '' +credsubs: + version: 1.1.1 + title: Credible Subsets + maintainer: Patrick Schnell + description: Functions for constructing simultaneous credible bands and identifying + subsets via the "credible subsets" (also called "credible subgroups") method. + Package documentation includes the vignette included in this package, and the + paper by Schnell, Fiecas, and Carlin (2020, ). + date_publication: '2020-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=credsubs + url_git: '' +credule: + version: 0.1.4 + title: Credit Default Swap Functions + maintainer: Bertrand Le Nezet + description: It provides functions to bootstrap Credit Curves from market quotes + (Credit Default Swap - CDS - spreads) and price Credit Default Swaps - CDS. + date_publication: '2020-05-10' + bug_reports: https://github.com/blenezet/credule/issues + url: '' + url_cran: https://CRAN.R-project.org/package=credule + url_git: https://github.com/blenezet/credule +creepyalien: + version: 1.0.0 + title: Puzzle Game for the R Console + maintainer: Roland Krasser + description: |- + Puzzle game that can be played in the R console. + Help the alien to find the ship. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=creepyalien + url_git: https://github.com/rolkra/creepyalien +crew: + version: 1.0.0 + title: A Distributed Worker Launcher Framework + maintainer: William Michael Landau + description: |- + In computationally demanding analysis projects, + statisticians and data scientists asynchronously + deploy long-running tasks to distributed systems, + ranging from traditional clusters to cloud services. + The 'NNG'-powered 'mirai' R package by Gao (2023) + is a sleek + and sophisticated scheduler that + efficiently processes these intense workloads. + The 'crew' package extends 'mirai' with a unifying + interface for third-party worker launchers. + Inspiration also comes from packages. + 'future' by Bengtsson (2021) , + 'rrq' by FitzJohn and Ashton (2023) , + 'clustermq' by Schubert (2019) ), + and 'batchtools' by Lang, Bischel, and Surmann (2017) + . + date_publication: '2025-02-03' + bug_reports: https://github.com/wlandau/crew/issues + url: https://wlandau.github.io/crew/ + url_cran: https://CRAN.R-project.org/package=crew + url_git: https://github.com/wlandau/crew +crew.aws.batch: + version: 0.0.8 + title: A Crew Launcher Plugin for AWS Batch + maintainer: William Michael Landau + description: |- + In computationally demanding analysis projects, + statisticians and data scientists asynchronously + deploy long-running tasks to distributed systems, + ranging from traditional clusters to cloud services. + The 'crew.aws.batch' package extends the 'mirai'-powered + 'crew' package with a worker launcher plugin for AWS Batch. + Inspiration also comes from packages 'mirai' by Gao (2023) + , + 'future' by Bengtsson (2021) , + 'rrq' by FitzJohn and Ashton (2023) , + 'clustermq' by Schubert (2019) ), + and 'batchtools' by Lang, Bischl, and Surmann (2017). + . + date_publication: '2025-02-05' + bug_reports: https://github.com/wlandau/crew.aws.batch/issues + url: https://wlandau.github.io/crew.aws.batch/ + url_cran: https://CRAN.R-project.org/package=crew.aws.batch + url_git: https://github.com/wlandau/crew.aws.batch +crew.cluster: + version: 0.3.4 + title: |- + Crew Launcher Plugins for Traditional High-Performance Computing + Clusters + maintainer: William Michael Landau + description: |- + In computationally demanding analysis projects, + statisticians and data scientists asynchronously + deploy long-running tasks to distributed systems, + ranging from traditional clusters to cloud services. + The 'crew.cluster' package extends the 'mirai'-powered + 'crew' package with worker launcher plugins for traditional + high-performance computing systems. + Inspiration also comes from packages 'mirai' by Gao (2023) + , + 'future' by Bengtsson (2021) , + 'rrq' by FitzJohn and Ashton (2023) , + 'clustermq' by Schubert (2019) ), + and 'batchtools' by Lang, Bischl, and Surmann (2017). + . + date_publication: '2025-02-05' + bug_reports: https://github.com/wlandau/crew.cluster/issues + url: https://wlandau.github.io/crew.cluster/ + url_cran: https://CRAN.R-project.org/package=crew.cluster + url_git: https://github.com/wlandau/crew.cluster +crfsuite: + version: 0.4.2 + title: |- + Conditional Random Fields for Labelling Sequential Data in + Natural Language Processing + maintainer: Jan Wijffels + description: |- + Wraps the 'CRFsuite' library allowing users + to fit a Conditional Random Field model and to apply it on existing data. + The focus of the implementation is in the area of Natural Language Processing where this R package allows you to easily build and apply models + for named entity recognition, text chunking, part of speech tagging, intent recognition or classification of any category you have in mind. Next to training, a small web application + is included in the package to allow you to easily construct training data. + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crfsuite + url_git: https://github.com/bnosac/crfsuite +cricketdata: + version: 0.2.3 + title: International Cricket Data + maintainer: Rob Hyndman + description: |- + Data on international and other major cricket matches from + ESPNCricinfo and Cricsheet . + This package provides some functions to download the data into tibbles ready + for analysis. + date_publication: '2023-08-29' + bug_reports: https://github.com/robjhyndman/cricketdata/issues + url: https://pkg.robjhyndman.com/cricketdata/ + url_cran: https://CRAN.R-project.org/package=cricketdata + url_git: https://github.com/robjhyndman/cricketdata +cricketr: + version: 0.0.26 + title: |- + Analyze Cricketers and Cricket Teams Based on ESPN Cricinfo + Statsguru + maintainer: Tinniam V Ganesh + description: |- + Tools for analyzing performances of cricketers based on stats in + ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs + and Twenty20 matches of both batsmen and bowlers. The package can also be used to + analyze team performances. + date_publication: '2021-03-23' + bug_reports: https://github.com/tvganesh/cricketr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cricketr + url_git: https://github.com/tvganesh/cricketr +crimCV: + version: 1.0.0 + title: Group-Based Modelling of Longitudinal Data + maintainer: Jason D. Nielsen + description: A finite mixture of Zero-Inflated Poisson (ZIP) models for analyzing + criminal trajectories. + date_publication: '2023-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crimCV + url_git: '' +crimedata: + version: 0.3.5 + title: Access Crime Data from the Open Crime Database + maintainer: Matthew Ashby + description: |- + Gives convenient access to publicly available police-recorded open + crime data from large cities in the United States that are included in the + Crime Open Database . + date_publication: '2023-11-09' + bug_reports: https://github.com/mpjashby/crimedata/issues + url: http://pkgs.lesscrime.info/crimedata/ + url_cran: https://CRAN.R-project.org/package=crimedata + url_git: https://github.com/mpjashby/crimedata +crimedatasets: + version: 0.1.0 + title: A Comprehensive Collection of Crime-Related Datasets + maintainer: Renzo Caceres Rossi + description: |- + A comprehensive collection of datasets exclusively focused on crimes, criminal activities, and related topics. + This package serves as a valuable resource for researchers, analysts, and students interested in crime analysis, + criminology, social and economic studies related to criminal behavior. Datasets span global and local contexts, + with a mix of tabular and spatial data. + date_publication: '2024-12-02' + bug_reports: https://github.com/lightbluetitan/crimedatasets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crimedatasets + url_git: https://github.com/lightbluetitan/crimedatasets +crimeutils: + version: 0.5.1 + title: |- + A Comprehensive Set of Functions to Clean, Analyze, and Present + Crime Data + maintainer: Jacob Kaplan + description: |- + A collection of functions that make it easier to understand crime (or other) + data, and assist others in understanding it. The package helps you read data + from various sources, clean it, fix column names, and graph the data. + date_publication: '2022-12-07' + bug_reports: https://github.com/jacobkap/crimeutils/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=crimeutils + url_git: https://github.com/jacobkap/crimeutils/ +crisp: + version: 1.0.0 + title: |- + Fits a Model that Partitions the Covariate Space into Blocks in + a Data- Adaptive Way + maintainer: Ashley Petersen + description: |- + Implements convex regression with interpretable sharp partitions + (CRISP), which considers the problem of predicting an outcome variable on the basis of two covariates, using an interpretable yet non-additive model. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. More details are provided in Petersen, A., Simon, N., and Witten, D. (2016). Convex Regression with Interpretable Sharp Partitions. Journal of Machine Learning Research, 17(94): 1-31 . + date_publication: '2017-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crisp + url_git: '' +crispRdesignR: + version: 1.1.7 + title: Guide Sequence Design for CRISPR/Cas9 + maintainer: Dylan Beeber + description: |- + Designs guide sequences for CRISPR/Cas9 genome editing and + provides information on sequence features pertinent to guide + efficiency. Sequence features include annotated off-target + predictions in a user-selected genome and a predicted efficiency + score based on the model described in Doench et al. (2016) + . Users are able to import additional genomes + and genome annotation files to use when searching and annotating + off-target hits. All guide sequences and off-target data can be + generated through the 'R' console with sgRNA_Design() or through + 'crispRdesignR's' user interface with crispRdesignRUI(). CRISPR + (Clustered Regularly Interspaced Short Palindromic Repeats) and the + associated protein Cas9 refer to a technique used in genome editing. + date_publication: '2023-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crispRdesignR + url_git: +criticality: + version: 0.9.3 + title: Modeling Fissile Material Operations in Nuclear Facilities + maintainer: William Zywiec + description: |- + A collection of functions for modeling fissile material operations in nuclear facilities, + based on Zywiec et al (2021) . + date_publication: '2023-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=criticality + url_git: '' +criticalpath: + version: 0.2.1 + title: An Implementation of the Critical Path Method + maintainer: Rubens Jose Rosa + description: |2- + + An R implementation of the Critical Path Method (CPM). + CPM is a method used to estimate the minimum project duration and determine + the amount of scheduling flexibility on the logical network paths within the + schedule model. The flexibility is in terms of early start, early finish, + late start, late finish, total float and free float. Beside, it permits + to quantify the complexity of network diagram through the analysis of + topological indicators. Finally, it permits to change the activities duration + to perform what-if scenario analysis. The package was built based on following + references: To make topological sorting and other graph operation, we use + Csardi, G. & Nepusz, T. (2005) + ; + For schedule concept, the reference was Project Management Institute (2017) + ; + For standards terms, we use Project Management Institute (2017) + ; + For algorithms on Critical Path Method development, we use + Vanhoucke, M. (2013) and + Vanhoucke, M. (2014) ; + And, finally, for topological definitions, we use + Vanhoucke, M. (2009) . + date_publication: '2022-03-13' + bug_reports: https://github.com/rubens2005/criticalpath/issues + url: https://rubensjoserosa.com/criticalpath + url_cran: https://CRAN.R-project.org/package=criticalpath + url_git: https://github.com/rubens2005/criticalpath +critpath: + version: 0.2.2 + title: Setting the Critical Path in Project Management + maintainer: Adam Kucharski + description: 'Solving the problem of project management using CPM (Critical Path + Method), PERT (Program Evaluation and Review Technique) and LESS (Least Cost Estimating + and Scheduling) methods. The package sets the critical path, schedule and Gantt + chart. In addition, it allows to draw a graph even with marked critical activities. + For more information about project management see: Taha H. A. "Operations Research. + An Introduction" (2017, ISBN:978-1-292-16554-7), Rama Murthy P. "Operations Research" + (2007, ISBN:978-81-224-2944-2), Yuval Cohen & Arik Sadeh (2006) "A New Approach + for Constructing and Generating AOA Networks", Journal of Engineering, Computing + and Architecture 1. 1-13, Konarzewska I., Jewczak M., Kucharski A. (2020, + ISBN:978-83-8220-112-3), Miszczyńska D., Miszczyński M. "Wybrane metody badań + operacyjnych" (2000, ISBN:83-907712-0-9).' + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=critpath + url_git: '' +crm12Comb: + version: 0.1.9 + title: Phase I/II CRM Based Drug Combination Design + maintainer: Junying Wang + description: 'Implements the adaptive designs for integrated phase I/II trials of + drug combinations via continual reassessment method (CRM) to evaluate toxicity + and efficacy simultaneously for each enrolled patient cohort based on Bayesian + inference. It supports patients assignment guidance in a single trial using current + enrolled data, as well as conducting extensive simulation studies to evaluate + operating characteristics before the trial starts. It includes various link functions + such as empiric, one-parameter logistic, two-parameter logistic, and hyperbolic + tangent, as well as considering multiple prior distributions of the parameters + like normal distribution, gamma distribution and exponential distribution to accommodate + diverse clinical scenarios. Method using Bayesian framework with empiric link + function is described in: Wages and Conaway (2014) .' + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crm12Comb + url_git: '' +CRMetrics: + version: 0.3.2 + title: Cell Ranger Output Filtering and Metrics Visualization + maintainer: Rasmus Rydbirk + description: Sample and cell filtering as well as visualisation of output metrics + from 'Cell Ranger' by Grace X.Y. Zheng et al. (2017) . + 'CRMetrics' allows for easy plotting of output metrics across multiple samples + as well as comparative plots including statistical assessments of these. 'CRMetrics' + allows for easy removal of ambient RNA using 'SoupX' by Matthew D Young and Sam + Behjati (2020) or 'CellBender' by Stephen J + Fleming et al. (2022) . Furthermore, it is possible to preprocess + data using 'Pagoda2' by Nikolas Barkas et al. (2021) + or 'Seurat' by Yuhan Hao et al. (2021) followed + by embedding of cells using 'Conos' by Nikolas Barkas et al. (2019) . + Finally, doublets can be detected using 'scrublet' by Samuel L. Wolock et al. + (2019) or 'DoubletDetection' by Gayoso et al. + (2020) . In the end, cells are filtered based on user + input for use in downstream applications. + date_publication: '2024-11-08' + bug_reports: https://github.com/khodosevichlab/CRMetrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CRMetrics + url_git: https://github.com/khodosevichlab/CRMetrics +crmn: + version: 0.0.21 + title: CCMN and Other Normalization Methods for Metabolomics Data + maintainer: Henning Redestig + description: |- + Implements the Cross-contribution Compensating Multiple + standard Normalization (CCMN) method described in Redestig et + al. (2009) Analytical Chemistry + and other normalization algorithms. + date_publication: '2020-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crmn + url_git: https://github.com/hredestig/crmn +crmPack: + version: 1.0.6 + title: Object-Oriented Implementation of CRM Designs + maintainer: Daniel Sabanes Bove + description: |- + Implements a wide range of model-based dose + escalation designs, ranging from classical and modern continual + reassessment methods (CRMs) based on dose-limiting toxicity endpoints to + dual-endpoint designs taking into account a biomarker/efficacy outcome. The + focus is on Bayesian inference, making it very easy to setup a new design + with its own JAGS code. However, it is also possible to implement 3+3 + designs for comparison or models with non-Bayesian estimation. The whole + package is written in a modular form in the S4 class system, making it very + flexible for adaptation to new models, escalation or stopping rules. + date_publication: '2024-06-26' + bug_reports: https://github.com/openpharma/crmPack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crmPack + url_git: https://github.com/openpharma/crmPack +crmReg: + version: 1.0.2 + title: Cellwise Robust M-Regression and SPADIMO + maintainer: Sebastiaan Hoppner + description: Method for fitting a cellwise robust linear M-regression model (CRM, + Filzmoser et al. (2020) ) that yields both a map + of cellwise outliers consistent with the linear model, and a vector of regression + coefficients that is robust against vertical outliers and leverage points. As + a by-product, the method yields an imputed data set that contains estimates of + what the values in cellwise outliers would need to amount to if they had fit the + model. The package also provides diagnostic tools for analyzing casewise and cellwise + outliers using sparse directions of maximal outlyingness (SPADIMO, Debruyne et + al. (2019) ). + date_publication: '2020-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crmReg + url_git: '' +crochet: + version: 2.3.0 + title: |- + Implementation Helper for '[' and '[<-' of Custom Matrix-Like + Types + maintainer: Alexander Grueneberg + description: |- + Functions to help implement the extraction / subsetting / indexing + function '[' and replacement function '[<-' of custom matrix-like types + (based on S3, S4, etc.), modeled as closely to the base matrix class as + possible (with tests to prove it). + date_publication: '2020-05-20' + bug_reports: https://github.com/agrueneberg/crochet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crochet + url_git: https://github.com/agrueneberg/crochet +cromwellDashboard: + version: 0.5.1 + title: A Dashboard to Visualize Scientific Workflows in 'Cromwell' + maintainer: Xiaowei Zhan + description: |- + A dashboard supports the usage of 'cromwell'. + 'Cromwell' is a scientific workflow engine for command line users. + This package utilizes 'cromwell' REST APIs and provides these convenient + functions: timing diagrams for running workflows, 'cromwell' engine status, + a tabular workflow list. For more information about 'cromwell', + visit . + date_publication: '2018-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cromwellDashboard + url_git: '' +Cronbach: + version: '0.2' + title: Cronbach's Alpha + maintainer: Michail Tsagris + description: Cronbach's alpha and various formulas for confidence intervals. The + relevant paper is Tsagris M., Frangos C.C. and Frangos C.C. (2013). "Confidence + intervals for Cronbach's reliability coefficient". Recent Techniques in Educational + Science, 14-16 May, Athens, Greece. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Cronbach + url_git: '' +crone: + version: 0.1.1 + title: Structural Crystallography in 1d + maintainer: James Foadi + description: |- + Functions to carry out the most important crystallographic calculations for crystal + structures made of 1d Gaussian-shaped atoms, especially useful for methods development. + Main reference: E. Smith, G. Evans, J. Foadi (2017) . + date_publication: '2019-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crone + url_git: '' +cronologia: + version: 0.2.0 + title: |- + Create an HTML Vertical Timeline from a Data Frame in + 'rmarkdown' and 'shiny' + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Creates an HTML vertical timeline from a data frame as an input for + 'rmarkdown' documents and 'shiny' applications. + date_publication: '2021-04-22' + bug_reports: https://github.com/feddelegrand7/cronologia/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cronologia + url_git: https://github.com/feddelegrand7/cronologia +cronR: + version: 0.6.5 + title: Schedule R Scripts and Processes with the 'cron' Job Scheduler + maintainer: Jan Wijffels + description: |- + Create, edit, and remove 'cron' jobs on your unix-alike system. The package provides a set of easy-to-use wrappers + to 'crontab'. It also provides an RStudio add-in to easily launch and schedule your scripts. + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cronR + url_git: https://github.com/bnosac/cronR +crop: + version: 0.0-3 + title: Graphics Cropping Tool + maintainer: Marius Hofert + description: |- + A device closing function which is able to crop graphics (e.g., + PDF, PNG files) on Unix-like operating systems with the required underlying + command-line tools installed. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crop + url_git: '' +CropBreeding: + version: 0.1.0 + title: Stability Analysis in Crop Breeding + maintainer: Prity Kumari + description: |- + Provides tools for crop breeding analysis including Genetic Coefficient of Variation (GCV), + Phenotypic Coefficient of Variation (PCV), heritability, genetic advance calculations, stability + analysis using the Eberhart-Russell model, two-way ANOVA for genotype-environment interactions, + and Additive Main Effects and Multiplicative Interaction (AMMI) analysis. These tools are developed + for crop breeding research and stability evaluation under various environmental conditions. + The methods are based on established statistical and biometrical principles. + Refer to Eberhart and Russell (1966) for stability parameters, + Fisher (1935) "The Design of Experiments" , Falconer (1996) "Introduction to Quantitative Genetics" + , and Singh and Chaudhary (1985) "Biometrical Methods in Quantitative Genetic Analysis" + for foundational methodologies. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CropBreeding + url_git: '' +cropcircles: + version: 0.2.4 + title: Crops an Image to a Circle + maintainer: Daniel Oehm + description: |- + Images are cropped to a circle with a transparent background. The function takes a + vector of images, either local or from a link, and circle crops the image. Paths to the + cropped image are returned for plotting with 'ggplot2'. Also includes cropping to a hexagon, + heart, parallelogram, and square. + date_publication: '2023-12-03' + bug_reports: https://github.com/doehm/cropcircles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cropcircles + url_git: https://github.com/doehm/cropcircles +cropdatape: + version: 1.0.0 + title: Open Data of Agricultural Production of Crops of Peru + maintainer: Omar Benites-Alfaro + description: |- + Provides peruvian agricultural production data from the Agriculture Minestry of Peru (MINAGRI). The first version includes + 6 crops: rice, quinoa, potato, sweet potato, tomato and wheat; all of them across 24 departments. Initially, in excel files which has been transformed + and assembled using tidy data principles, i.e. each variable is in a column, each observation is a row and each value is in a cell. + The variables variables are sowing and harvest area per crop, yield, production and price per plot, every one year, from 2004 to 2014. + date_publication: '2017-03-02' + bug_reports: https://github.com/omarbenites/cropdatape/issues + url: http://siea.minagri.gob.pe/siea/?q=publicaciones/anuarios-estadisticos + url_cran: https://CRAN.R-project.org/package=cropdatape + url_git: https://github.com/omarbenites/cropdatape +cropDemand: + version: 1.0.3 + title: Spatial Crop Water Demand for Brazil + maintainer: Roberto Filgueiras + description: Estimation of crop water demand can be processed via this package. + As example, the data from 'TerraClimate' dataset () + calibrated with automatic weather stations of National Meteorological Institute + of Brazil is available in a coarse spatial resolution to do the crop water demand. + However, the user have also the option to download the variables directly from + 'TerraClimate' repository with the download.terraclimate function and access + the original 'TerraClimate' products. If the user believes that is necessary calibrate + the variables, there is another function to do it. Lastly, the estimation of the + crop water demand present in this package can be run for all the Brazilian territory + with 'TerraClimate' dataset. + date_publication: '2023-10-13' + bug_reports: https://github.com/FilgueirasR/cropDemand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cropDemand + url_git: '' +cropgrowdays: + version: 0.2.1 + title: Crop Growing Degree Days and Agrometeorological Calculations + maintainer: Peter Baker + description: |- + Calculate agrometeorological variables for crops + including growing degree days (McMaster, GS & Wilhelm, WW + (1997) ), cumulative + rainfall, number of stress days and cumulative or mean + radiation and evaporation. Convert dates to day of year + and vice versa. Also, download curated and interpolated + Australian weather data from the Queensland Government + DES longpaddock website + . This data is + freely available under the Creative Commons 4.0 licence. + date_publication: '2024-03-12' + bug_reports: https://gitlab.com/petebaker/cropgrowdays/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cropgrowdays + url_git: https://gitlab.com/petebaker/cropgrowdays/ +crops: + version: 1.0.3 + title: Changepoints for a Range of Penalties (CROPS) + maintainer: Daniel Grose + description: Implements the Changepoints for a Range of Penalties (CROPS) algorithm + of Haynes et al. (2017) for finding all of + the optimal segmentations for multiple penalty values over a continuous range. + date_publication: '2022-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crops + url_git: '' +CropScapeR: + version: 1.1.5 + title: Access Cropland Data Layer Data via the 'CropScape' Web Service + maintainer: Bowen Chen + description: Interface to easily access Cropland Data Layer (CDL) data for any area + of interest via the 'CropScape' web service. + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CropScapeR + url_git: '' +CropWaterBalance: + version: 0.2.0 + title: Climate Water Balance for Irrigation Purposes + maintainer: Gabriel Constantino Blain + description: |- + Calculates daily climate water balance for irrigation purposes and + also calculates the reference evapotranspiration (ET) using three methods, + Penman and Monteith (Allen et al. 1998, ISBN:92-5-104219-5); + Priestley and Taylor (1972) ; or Hargreaves and Samani (1985) + . Users may specify a management allowed depletion + (MAD), which is used to suggest when to irrigate. The functionality allows + for the use of crop and water stress coefficients as well. + date_publication: '2024-04-18' + bug_reports: https://github.com/gabrielblain/CropWaterBalance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CropWaterBalance + url_git: https://github.com/gabrielblain/CropWaterBalance +cropZoning: + version: 1.0.3 + title: Climate Crop Zoning Based in Air Temperature for Brazil + maintainer: Roberto Filgueiras + description: Climate crop zoning based in minimum and maximum air temperature. The + data used in the package are from 'TerraClimate' dataset (), + but, it have been calibrated with automatic weather stations of National Meteorological + Institute of Brazil. The climate crop zoning of this package can be run for all + the Brazilian territory. + date_publication: '2023-10-10' + bug_reports: https://github.com/FilgueirasR/cropZoning/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cropZoning + url_git: '' +CrossCarry: + version: 0.4.0 + title: Analysis of Data from a Crossover Design with GEE + maintainer: Nelson Alirio Cruz Gutierrez + description: 'Analyze data from a crossover design using generalized estimation + equations (GEE), including carryover effects and various correlation structures + based on the Kronecker product. It contains functions for semiparametric estimates + of carry-over effects in repeated measures and allows estimation of complex carry-over + effects. Related work includes: a) Cruz N.A., Melo O.O., Martinez C.A. (2023). + "CrossCarry: An R package for the analysis of data from a crossover design with + GEE". . b) Cruz N.A., Melo O.O., Martinez C.A. + (2023). "A correlation structure for the analysis of Gaussian and non-Gaussian + responses in crossover experimental designs with repeated measures". + and c) Cruz N.A., Melo O.O., Martinez C.A. (2023). "Semiparametric generalized + estimating equations for repeated measurements in cross-over designs". .' + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CrossCarry + url_git: '' +CrossClustering: + version: 4.1.2 + title: A Partial Clustering Algorithm + maintainer: Paola Tellaroli + description: |- + Provide the 'CrossClustering' algorithm (Tellaroli et al. + (2016) ), which is a partial + clustering algorithm that combines the Ward's minimum variance and + Complete Linkage algorithms, providing automatic estimation of a + suitable number of clusters and identification of outlier elements. + date_publication: '2024-05-14' + bug_reports: https://github.com/CorradoLanera/CrossClustering/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CrossClustering + url_git: '' +crossdes: + version: 1.1-2 + title: Construction of Crossover Designs + maintainer: Bjoern Bornkamp + description: |- + Contains functions for the construction of carryover + balanced crossover designs. In addition contains functions to + check given designs for balance. + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossdes + url_git: '' +crosshap: + version: 1.4.0 + title: Local Haplotype Clustering and Visualization + maintainer: Jacob Marsh + description: |- + A local haplotyping visualization toolbox to capture major patterns + of co-inheritance between clusters of linked variants, whilst connecting findings + to phenotypic and demographic traits across individuals. 'crosshap' enables users + to explore and understand genomic variation across a trait-associated region. + For an example of successful local haplotype analysis, see Marsh et al. (2022) + . + date_publication: '2024-03-31' + bug_reports: https://github.com/jacobimarsh/crosshap/issues + url: https://jacobimarsh.github.io/crosshap/ + url_cran: https://CRAN.R-project.org/package=crosshap + url_git: '' +crosslag: + version: 0.1.0 + title: Perform Linear or Nonlinear Cross Lag Analysis + maintainer: Yaxin Li + description: |- + Linear or nonlinear cross-lagged panel model can be built from input data. Users can choose the appropriate method from three methods for constructing nonlinear cross lagged models. These three methods include polynomial regression, generalized additive model and generalized linear mixed model.In addition, a function for determining linear relationships is provided. + Relevant knowledge of cross lagged models can be learned through the paper by Fredrik Falkenström (2024) and the paper by A Gasparrini (2010) . + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crosslag + url_git: '' +crossmap: + version: 0.4.0 + title: Apply Functions to All Combinations of List Elements + maintainer: Alexander Rossell Hayes + description: |- + Provides an extension to the 'purrr' family of mapping + functions to apply a function to each combination of elements in a + list of inputs. Also includes functions for automatically detecting + output type in mapping functions, finding every combination of + elements of lists or rows of data frames, and applying multiple models + to multiple subsets of a dataset. + date_publication: '2023-01-12' + bug_reports: https://github.com/rossellhayes/crossmap/issues + url: https://crossmap.rossellhayes.com + url_cran: https://CRAN.R-project.org/package=crossmap + url_git: https://github.com/rossellhayes/crossmap +crossmatch: + version: 1.4-0 + title: The Cross-Match Test + maintainer: Marieke Stolte + description: |- + Performs the cross-match test that is an exact, + distribution free test of equality of 2 high dimensional multivariate distributions. + The input is a distance matrix and the labels of + the two groups to be compared, the output is the number of + cross-matches and a p-value. See Rosenbaum (2005) . + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossmatch + url_git: '' +crossnma: + version: 1.3.0 + title: Cross-Design & Cross-Format Network Meta-Analysis and Regression + maintainer: Guido Schwarzer + description: |- + Network meta-analysis and meta-regression (allows + including up to three covariates) for individual participant data, + aggregate data, and mixtures of both formats using the three-level + hierarchical model. Each format can come from randomized controlled + trials or non-randomized studies or mixtures of both. Estimates are + generated in a Bayesian framework using JAGS. The implemented models + are described by Hamza et al. 2023 . + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossnma + url_git: https://github.com/htx-r/crossnma +Crossover: + version: 0.1-22 + title: Analysis and Search of Crossover Designs + maintainer: Kornelius Rohmeyer + description: |- + Generate and analyse crossover designs from combinatorial or search algorithms as well as from literature and a GUI to + access them. + date_publication: '2024-03-25' + bug_reports: https://github.com/kornl/Crossover/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Crossover + url_git: https://github.com/kornl/Crossover/wiki +crossrun: + version: 0.1.1 + title: Joint Distribution of Number of Crossings and Longest Run + maintainer: Tore Wentzel-Larsen + description: |- + Joint distribution of number of crossings and the + longest run in a series of independent Bernoulli trials. The + computations uses an iterative procedure where computations + are based on results from shorter series. The procedure + conditions on the start value and partitions by further + conditioning on the position of the first crossing (or none). + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossrun + url_git: https://github.com/ToreWentzel-Larsen/crossrun +crosstable: + version: 0.8.1 + title: Crosstables for Descriptive Analyses + maintainer: Dan Chaltiel + description: |- + Create descriptive tables for continuous and categorical variables. + Apply summary statistics and counting function, with or without a grouping variable, and create beautiful reports using 'rmarkdown' or 'officer'. + You can also compute effect sizes and statistical tests if needed. + date_publication: '2024-11-01' + bug_reports: https://github.com/DanChaltiel/crosstable/issues/ + url: https://danchaltiel.github.io/crosstable/ + url_cran: https://CRAN.R-project.org/package=crosstable + url_git: https://github.com/DanChaltiel/crosstable/ +Crosstabs.Loglinear: + version: 0.1.1 + title: Cross Tabulation and Loglinear Analyses of Categorical Data + maintainer: Brian O'Connor + description: |- + Provides 'SPSS'- and 'SAS'-like output for cross tabulations of two + categorical variables (CROSSTABS) and for hierarchical loglinear analyses + of two or more categorical variables (LOGLINEAR). The methods are described in + Agresti (2013, ISBN:978-0-470-46363-5), + Ajzen & Walker (2021, ISBN:9780429330308), + Field (2018, ISBN:9781526440273), + Norusis (2012, ISBN:978-0-321-74843-0), + Nussbaum (2015, ISBN:978-1-84872-603-1), + Stevens (2009, ISBN:978-0-8058-5903-4), + Tabachnik & Fidell (2019, ISBN:9780134790541), and + von Eye & Mun (2013, ISBN:978-1-118-14640-8). + date_publication: '2022-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Crosstabs.Loglinear + url_git: '' +crosstalk: + version: 1.2.1 + title: Inter-Widget Interactivity for HTML Widgets + maintainer: Carson Sievert + description: |- + Provides building blocks for allowing HTML widgets to communicate + with each other, with Shiny or without (i.e. static .html files). Currently + supports linked brushing and filtering. + date_publication: '2023-11-23' + bug_reports: https://github.com/rstudio/crosstalk/issues + url: https://rstudio.github.io/crosstalk/ + url_cran: https://CRAN.R-project.org/package=crosstalk + url_git: https://github.com/rstudio/crosstalk +crosstalkr: + version: 1.0.5 + title: |- + Analysis of Graph-Structured Data with a Focus on + Protein-Protein Interaction Networks + maintainer: Davis Weaver + description: Provides a general toolkit for drug target identification. We include + functionality to reduce large graphs to subgraphs and prioritize nodes. In addition + to being optimized for use with generic graphs, we also provides support to analyze + protein-protein interactions networks from online repositories. For more details + on core method, refer to Weaver et al. (2021) . + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crosstalkr + url_git: '' +crossurr: + version: 1.1.1 + title: |- + Cross-Fitting for Doubly Robust Evaluation of High-Dimensional + Surrogate Markers + maintainer: Denis Agniel + description: |- + Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebaut R & Parast L (2022). + "Doubly robust evaluation of high-dimensional surrogate markers", Biostatistics . You can use these methods to determine how much of the overall treatment effect is explained by a (possibly high-dimensional) set of surrogate markers. + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossurr + url_git: '' +CrossVA: + version: 1.0.0 + title: |- + Verbal Autopsy Data Transformation for InSilicoVA and InterVA5 + Algorithms + maintainer: Jason Thomas + description: |- + Enables transformation of Verbal Autopsy data collected with the WHO 2016 questionnaire (versions 1.4.1 & 1.5.1) + or the WHO 2014 questionnaire for automated coding of Cause of Death using the InSilicoVA (data.type = "WHO2016") and + InterVA5 algorithms. Previous versions of this package supported user-supplied mappings (via the map_records function), but + this functionality has been removed. This package is made available by WHO and the Bloomberg Data for Health Initiative. + date_publication: '2021-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CrossVA + url_git: '' +crossval: + version: 1.0.5 + title: Generic Functions for Cross Validation + maintainer: Korbinian Strimmer + description: |- + Contains generic functions for performing + cross validation and for computing diagnostic errors. + date_publication: '2023-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossval + url_git: '' +CrossValidate: + version: 2.3.4 + title: |- + Classes and Methods for Cross Validation of "Class Prediction" + Algorithms + maintainer: Kevin R. Coombes + description: |- + Defines classes and methods to cross-validate various + binary classification algorithms used for "class prediction" + problems. + date_publication: '2019-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CrossValidate + url_git: http://oompa.r-forge.r-project.org +crossvalidationCP: + version: '1.1' + title: Cross-Validation for Change-Point Regression + maintainer: Pein Florian + description: Implements the cross-validation methodology from Pein and Shah (2021) + . Can be customised by providing different cross-validation + criteria, estimators for the change-point locations and local parameters, and + freely chosen folds. Pre-implemented estimators and criteria are available. It + also includes our own implementation of the COPPS procedure . + date_publication: '2023-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossvalidationCP + url_git: '' +crosswalkr: + version: 0.2.6 + title: Rename and Encode Data Frames Using External Crosswalk Files + maintainer: Benjamin Skinner + description: |- + A pair of functions for renaming and encoding data frames + using external crosswalk files. It is especially useful when + constructing master data sets from multiple smaller data + sets that do not name or encode variables consistently + across files. Based on similar commands in 'Stata'. + date_publication: '2020-01-08' + bug_reports: https://github.com/btskinner/crosswalkr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crosswalkr + url_git: https://github.com/btskinner/crosswalkr +crossword.r: + version: 0.3.6 + title: Generating Crosswords from Word Lists + maintainer: Peter Meissner + description: Generate crosswords from a list of words. + date_publication: '2019-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crossword.r + url_git: '' +crov: + version: 0.3.0 + title: |- + Constrained Regression Model for an Ordinal Response and Ordinal + Predictors + maintainer: Javier Espinosa + description: Fits a constrained regression model for an ordinal response with ordinal + predictors and possibly others, Espinosa and Hennig (2019) . + The parameter estimates associated with an ordinal predictor are constrained to + be monotonic. If a monotonicity direction (isotonic or antitonic) is not specified + for an ordinal predictor by the user, then one of the available methods will either + establish it or drop the monotonicity assumption. Two monotonicity tests are also + available to test the null hypothesis of monotonicity over a set of parameters + associated with an ordinal predictor. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crov + url_git: '' +crplyr: + version: 0.4.0 + title: A 'dplyr' Interface for Crunch + maintainer: Greg Freedman Ellis + description: |- + In order to facilitate analysis of datasets hosted on the Crunch + data platform , the 'crplyr' package implements 'dplyr' + methods on top of the Crunch backend. The usual methods 'select', 'filter', + 'group_by', 'summarize', and 'collect' are implemented in such a way as to + perform as much computation on the server and pull as little data locally + as possible. + date_publication: '2023-03-21' + bug_reports: https://github.com/Crunch-io/crplyr/issues + url: https://crunch.io/r/crplyr/ + url_cran: https://CRAN.R-project.org/package=crplyr + url_git: https://github.com/Crunch-io/crplyr +crqa: + version: 2.0.6 + title: |- + Unidimensional and Multidimensional Methods for Recurrence + Quantification Analysis + maintainer: Moreno I. Coco + description: |- + Auto, Cross and Multi-dimensional recurrence quantification analysis. + Different methods for computing recurrence, cross vs. multidimensional + or profile iti.e., only looking at the diagonal recurrent points, + as well as functions for optimization and plotting are proposed. + in-depth measures of the whole cross-recurrence plot, + Please refer to Coco and others (2021) , + Coco and Dale (2014) + and Wallot (2018) + for further details about the method. + date_publication: '2024-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crqa + url_git: '' +crrcbcv: + version: '1.0' + title: |- + Bias-Corrected Variance for Competing Risks Regression with + Clustered Data + maintainer: Xinyuan Chen + description: |2- + + A user friendly function 'crrcbcv' to compute bias-corrected variances for competing risks regression models using proportional subdistribution hazards with small-sample clustered data. Four types of bias correction are included: the MD-type bias correction by Mancl and DeRouen (2001) , the KC-type bias correction by Kauermann and Carroll (2001) , the FG-type bias correction by Fay and Graubard (2001) , and the MBN-type bias correction by Morel, Bokossa, and Neerchal (2003) . + date_publication: '2021-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crrcbcv + url_git: '' +crrSC: + version: 1.1.2 + title: Competing Risks Regression for Stratified and Clustered Data + maintainer: Aurelien Latouche + description: |- + Extension of 'cmprsk' to Stratified and Clustered data. + A goodness of fit test for Fine-Gray model is also provided. + Methods are detailed in the following articles: Zhou et al. (2011) , + Zhou et al. (2012) , + Zhou et al. (2013) . + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crrSC + url_git: '' +crrstep: + version: 2024.1.1 + title: |- + Stepwise Covariate Selection for the Fine & Gray Competing Risks + Regression Model + maintainer: Ravi Varadhan + description: Performs forward and backwards stepwise regression for the Proportional + subdistribution hazards model in competing risks (Fine & Gray 1999). Procedure + uses AIC, BIC and BICcr as selection criteria. BICcr has a penalty of k = log(n*), + where n* is the number of primary events. + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crrstep + url_git: '' +crs: + version: 0.15-38 + title: Categorical Regression Splines + maintainer: Jeffrey S. Racine + description: Regression splines that handle a mix of continuous and categorical + (discrete) data often encountered in applied settings. I would like to gratefully + acknowledge support from the Natural Sciences and Engineering Research Council + of Canada (NSERC, ), the Social Sciences and Humanities + Research Council of Canada (SSHRC, ), and the Shared + Hierarchical Academic Research Computing Network (SHARCNET, ). + We would also like to acknowledge the contributions of the GNU GSL authors. In + particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated + support for quantile knots (in addition to uniform knots), providing missing functionality + for derivatives, and for extending the splines beyond their endpoints. + date_publication: '2024-09-29' + bug_reports: https://github.com/JeffreyRacine/R-Package-crs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crs + url_git: https://github.com/JeffreyRacine/R-Package-crs +crseEventStudy: + version: 1.2.2 + title: |- + A Robust and Powerful Test of Abnormal Stock Returns in + Long-Horizon Event Studies + maintainer: Siegfried Köstlmeier + description: Based on Dutta et al. (2018) , this + package provides their standardized test for abnormal returns in long-horizon + event studies. The methods used improve the major weaknesses of size, power, and + robustness of long-run statistical tests described in Kothari/Warner (2007) . + Abnormal returns are weighted by their statistical precision (i.e., standard deviation), + resulting in abnormal standardized returns. This procedure efficiently captures + the heteroskedasticity problem. Clustering techniques following Cameron et al. + (2011) are adopted for computing cross-sectional + correlation robust standard errors. The statistical tests in this package therefore + accounts for potential biases arising from returns' cross-sectional correlation, + autocorrelation, and volatility clustering without power loss. + date_publication: '2022-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crseEventStudy + url_git: https://github.com/skoestlmeier/crseEventStudy +crsmeta: + version: 0.3.0 + title: Extract Coordinate System Metadata + maintainer: Michael Sumner + description: |- + Obtain coordinate system metadata from various data formats. There + are functions to extract a 'CRS' (coordinate reference system, + ) in 'EPSG' (European + Petroleum Survey Group, ), 'PROJ4' , + or 'WKT2' (Well-Known Text 2, + ) forms. This is + purely for getting simple metadata from in-memory formats, please use other + tools for out of memory data sources. + date_publication: '2020-03-29' + bug_reports: https://github.com/hypertidy/crsmeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crsmeta + url_git: https://github.com/hypertidy/crsmeta +crsnls: + version: '0.2' + title: |- + Nonlinear Regression Parameters Estimation by 'CRS4HC' and + 'CRS4HCe' + maintainer: Tomáš Goryl + description: |- + Functions for nonlinear regression parameters estimation by algorithms based on Controlled Random Search algorithm. + Both functions (crs4hc(), crs4hce()) adapt current search strategy by four heuristics competition. In addition, crs4hce() improves adaptability by adaptive stopping condition. + date_publication: '2016-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crsnls + url_git: '' +crso: + version: 0.1.1 + title: Cancer Rule Set Optimization ('crso') + maintainer: Michael Klein + description: |- + An algorithm for identifying candidate driver combinations in cancer. CRSO + is based on a theoretical model of cancer in which a cancer rule + is defined to be a collection of two or more events (i.e., alterations) that are minimally + sufficient to cause cancer. A cancer rule set is a set of cancer rules that collectively + are assumed to account for all of ways to cause cancer in the population. In CRSO every + event is designated explicitly as a passenger or driver within each patient. + Each event is associated with a patient-specific, event-specific passenger penalty, + reflecting how unlikely the event would have happened by chance, i.e., as a passenger. + CRSO evaluates each rule set by assigning all samples to a rule in the rule set, + or to the null rule, and then calculating the total statistical penalty from all + unassigned event. CRSO uses a three phase procedure find the best rule set of + fixed size K for a range of Ks. A core rule set is then identified from among + the best rule sets of size K as the rule set that best balances rule set size and + statistical penalty. + Users should consult the 'crso' vignette for an example walk through of a full CRSO run. + The full description, of the CRSO algorithm is presented in: + Klein MI, Cannataro V, Townsend J, Stern DF and Zhao H. "Identifying combinations of cancer driver in individual patients." + BioRxiv 674234 [Preprint]. June 19, 2019. . + Please cite this article if you use 'crso'. + date_publication: '2019-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crso + url_git: '' +crsra: + version: 0.2.3 + title: Tidying and Analyzing 'Coursera' Research Export Data + maintainer: Aboozar Hadavand + description: |- + Tidies and performs preliminary analysis of 'Coursera' research + export data. These export data can be downloaded by anyone who has classes + on Coursera and wants to analyze the data. Coursera is one of the leading + providers of MOOCs and was launched in January 2012. With over 25 million + learners, Coursera is the most popular provider in the world being followed + by EdX, the MOOC provider that was a result of a collaboration between + Harvard University and MIT, with over 10 million users. Coursera has over + 150 university partners from 29 countries and offers a total of 2000+ + courses from computer science to philosophy. Besides, Coursera offers 180+ + specialization, Coursera's credential system, and four fully online Masters + degrees. For more information about Coursera check Coursera's + About page on . + date_publication: '2018-05-05' + bug_reports: https://github.com/jhudsl/crsra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=crsra + url_git: '' +crsuggest: + version: '0.4' + title: |- + Obtain Suggested Coordinate Reference System Information for + Spatial Data + maintainer: Kyle Walker + description: |- + Uses data from the 'EPSG' Registry to look up suitable coordinate reference + system transformations for spatial datasets in R. Returns a data frame with 'CRS' codes + that can be used for 'CRS' transformation and mapping projects. Please see + the 'EPSG' Dataset Terms of Use at for more information. + date_publication: '2022-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crsuggest + url_git: '' +crt2power: + version: 1.1.0 + title: Designing Cluster-Randomized Trials with Two Co-Primary Outcomes + maintainer: Melody Owen + description: Provides methods for powering cluster-randomized trials with two co-primary + outcomes using five key design techniques. Includes functions for calculating + required sample size and statistical power. For more details on methodology, see + Li et al. (2020) , Pocock et al. (1987) , + Vickerstaff et al. (2019) , and Yang et al. (2022) + . + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crt2power + url_git: https://github.com/melodyaowen/crt2power +CRTConjoint: + version: 0.1.0 + title: |- + Conditional Randomization Testing (CRT) Approach for Conjoint + Analysis + maintainer: Dae Woong Ham + description: Computes p-value according to the CRT using the HierNet test statistic. + For more details, see Ham, Imai, Janson (2022) "Using Machine Learning to Test + Causal Hypotheses in Conjoint Analysis" . + date_publication: '2022-06-09' + bug_reports: https://github.com/daewoongham97/CRTConjoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CRTConjoint + url_git: https://github.com/daewoongham97/CRTConjoint +CRTgeeDR: + version: 2.0.1 + title: |- + Doubly Robust Inverse Probability Weighted Augmented GEE + Estimator + maintainer: Melanie Prague + description: Implements a semi-parametric GEE estimator accounting for missing data + with Inverse-probability weighting (IPW) and for imbalance in covariates with + augmentation (AUG). The estimator IPW-AUG-GEE is Doubly robust (DR). + date_publication: '2022-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CRTgeeDR + url_git: '' +CRTSize: + version: '1.2' + title: Sample Size Estimation Functions for Cluster Randomized Trials + maintainer: Michael A Rotondi + description: Sample size estimation in cluster (group) randomized trials. Contains + traditional power-based methods, empirical smoothing (Rotondi and Donner, 2009), + and updated meta-analysis techniques (Rotondi and Donner, 2012). + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CRTSize + url_git: '' +CRTspat: + version: 1.3.2 + title: Workflow for Cluster Randomised Trials with Spillover + maintainer: Thomas Smith + description: Design, workflow and statistical analysis of Cluster Randomised Trials + of (health) interventions where there may be spillover between the arms (see ). + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CRTspat + url_git: '' +crul: + version: 1.5.0 + title: HTTP Client + maintainer: Scott Chamberlain + description: |- + A simple HTTP client, with tools for making HTTP requests, + and mocking HTTP requests. The package is built on R6, and takes + inspiration from Ruby's 'faraday' gem (). + The package name is a play on curl, the widely used command line tool + for HTTP, and this package is built on top of the R package 'curl', an + interface to 'libcurl' (). + date_publication: '2024-07-19' + bug_reports: https://github.com/ropensci/crul/issues + url: https://docs.ropensci.org/crul/ + url_cran: https://CRAN.R-project.org/package=crul + url_git: https://github.com/ropensci/crul +crumble: + version: 0.1.2 + title: Flexible and General Mediation Analysis Using Riesz Representers + maintainer: Nicholas Williams + description: |- + Implements a modern, unified estimation strategy for common + mediation estimands (natural effects, organic effects, interventional effects, + and recanting twins) in combination with modified treatment policies as + described in Liu, Williams, Rudolph, and Díaz (2024) + . Estimation makes use of recent advancements + in Riesz-learning to estimate a set of required nuisance parameters with + deep learning. The result is the capability to estimate mediation effects with + binary, categorical, continuous, or multivariate exposures with + high-dimensional mediators and mediator-outcome confounders using machine + learning. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crumble + url_git: '' +crunch: + version: 1.30.4 + title: Crunch.io Data Tools + maintainer: Greg Freedman Ellis + description: |- + The Crunch.io service provides a cloud-based + data store and analytic engine, as well as an intuitive web interface. + Using this package, analysts can interact with and manipulate Crunch + datasets from within R. Importantly, this allows technical researchers to + collaborate naturally with team members, managers, and clients who prefer a + point-and-click interface. + date_publication: '2024-01-17' + bug_reports: https://github.com/Crunch-io/rcrunch/issues + url: https://crunch.io/r/crunch/ + url_cran: https://CRAN.R-project.org/package=crunch + url_git: https://github.com/Crunch-io/rcrunch +crunchy: + version: 0.3.3 + title: Shiny Apps on Crunch + maintainer: Greg Freedman Ellis + description: |- + To facilitate building custom dashboards on the Crunch data + platform , the 'crunchy' package provides tools for + working with 'shiny'. These tools include utilities to manage authentication + and authorization automatically and custom stylesheets to help match the + look and feel of the Crunch web application. The package also includes + several gadgets for use in 'RStudio'. + date_publication: '2021-01-13' + bug_reports: https://github.com/Crunch-io/crunchy/issues + url: https://crunch.io/r/crunchy/ + url_cran: https://CRAN.R-project.org/package=crunchy + url_git: https://github.com/Crunch-io/crunchy +cruts: + version: '1.1' + title: |- + Interface to Climatic Research Unit Time-Series Version 3.21 + Data + maintainer: Benjamin M. Taylor + description: |- + Functions for reading in and manipulating CRU TS3.21: Climatic + Research Unit (CRU) Time-Series (TS) Version 3.21 data. + date_publication: '2020-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cruts + url_git: '' +CruzPlot: + version: 1.4.9 + title: Plot Shipboard DAS Data + maintainer: Sam Woodman + description: |- + A utility program oriented to create maps, plot data, and do basic data summaries of DAS data files. + These files are typically, but do not have to be + DAS data + produced by the Southwest Fisheries Science Center (SWFSC) program 'WinCruz'. + date_publication: '2024-07-18' + bug_reports: https://github.com/swfsc/CruzPlot/issues/ + url: https://swfsc.github.io/CruzPlot/ + url_cran: https://CRAN.R-project.org/package=CruzPlot + url_git: https://github.com/swfsc/CruzPlot/ +crwbmetareg: + version: '1.0' + title: Cluster Robust Wild Bootstrap Meta Regression + maintainer: Michail Tsagris + description: 'In meta regression sometimes the studies have multiple effects that + are correlated. For this reason cluster robust standard errors must be computed. + However, since the clusters are unbalanced the wild bootstrap is suggested. See + Oczkowski E. and Doucouliagos H. (2015). "Wine prices and quality ratings: a meta-regression + analysis". American Journal of Agricultural Economics, 97(1): 103--121. + and Cameron A. C., Gelbach J. B. and Miller D. L. (2008). "Bootstrap-based improvements + for inference with clustered errors". The Review of Economics and Statistics, + 90(3): 414--427. .' + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=crwbmetareg + url_git: '' +CRWRM: + version: 0.0.1 + title: Changing the Reference Group without Re-Running the Model + maintainer: Ziqiang Lin + description: To re-calculate the coefficients and the standard deviation when changing + the reference group. + date_publication: '2019-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CRWRM + url_git: '' +cry: + version: 0.5.1 + title: Statistics for Structural Crystallography + maintainer: James Foadi + description: |- + Reading and writing of files in the most commonly used formats of + structural crystallography. It includes functions to work with a variety + of statistics used in this field and functions to perform basic + crystallographic computing. References: D. G. Waterman, J. Foadi, G. Evans + (2011) . + date_publication: '2022-10-10' + bug_reports: '' + url: https://jfoadi.github.io/cry/ + url_cran: https://CRAN.R-project.org/package=cry + url_git: '' +crypto2: + version: 2.0.3 + title: Download Crypto Currency Data from 'CoinMarketCap' without 'API' + maintainer: Sebastian Stoeckl + description: Retrieves crypto currency information and historical prices as well + as information on the exchanges they are listed on. Historical data contains daily + open, high, low and close values for all crypto currencies. All data is scraped + from via their 'web-api'. + date_publication: '2024-10-11' + bug_reports: '' + url: https://sstoeckl.github.io/crypto2/ + url_cran: https://CRAN.R-project.org/package=crypto2 + url_git: https://github.com/sstoeckl/crypto2 +cryptography: + version: 1.0.0 + title: Encrypts and Decrypts Text Ciphers + maintainer: Piaras Fahey + description: Playfair, Four-Square, Scytale, Columnar Transposition and Autokey + methods. Further explanation on methods of classical cryptography can be found + at Wikipedia; (). + date_publication: '2023-07-08' + bug_reports: https://github.com/PiarasFahey/cryptography/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cryptography + url_git: https://github.com/PiarasFahey/cryptography +cryptoQuotes: + version: 1.3.2 + title: |- + Open Access to Cryptocurrency Market Data, Sentiment Indicators + and Interactive Charts + maintainer: Serkan Korkmaz + description: |- + This high-level API client provides open access to cryptocurrency market data, sentiment indicators, and interactive charting tools. + The data is sourced from major cryptocurrency exchanges via 'curl' and returned in 'xts'-format. The data comes in open, high, low, and close (OHLC) format with flexible granularity, ranging from seconds to months. + This flexibility makes it ideal for developing and backtesting trading strategies or conducting detailed market analysis. + date_publication: '2024-11-07' + bug_reports: https://github.com/serkor1/cryptoQuotes/issues + url: https://serkor1.github.io/cryptoQuotes/ + url_cran: https://CRAN.R-project.org/package=cryptoQuotes + url_git: https://github.com/serkor1/cryptoQuotes +cryptorng: + version: 0.1.4 + title: Access System Cryptographic Pseudorandom Number Generators + maintainer: Mike Cheng + description: |- + Generate random numbers from the Cryptographically Secure Pseudorandom + Number Generator (CSPRNG) provided by the underlying operating system. + System CSPRNGs are seeded internally by the OS with entropy it gathers + from the system hardware. The following system functions are used: + arc4random_buf() on macOS and BSD; BCryptgenRandom() on Windows; + Sys_getrandom() on Linux. + date_publication: '2024-06-02' + bug_reports: https://github.com/coolbutuseless/cryptorng/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cryptorng + url_git: https://github.com/coolbutuseless/cryptorng +cryptotrackr: + version: 1.3.3 + title: An Interface to Crypto Data Sources + maintainer: Trevor French + description: |- + Allows you to connect to data sources across the + crypto ecosystem. This data can enable a range of activity such as + portfolio tracking, programmatic trading, or industry analysis. The + package is described in French (2024) . + date_publication: '2024-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cryptotrackr + url_git: '' +cryptoverse: + version: 0.1.0 + title: Visualization and Analytics for the Cryptoverse + maintainer: Vivian R. Steiger + description: Providing data to quickly visualize and analyze data from several cryptocurrencies. + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cryptoverse + url_git: '' +cryptowatchR: + version: 0.2.0 + title: An API Wrapper for 'Cryptowatch' + maintainer: Lorenz Brachtendorf + description: An API wrapper for 'Cryptowatch' to get prices and other information + (e.g., volume, trades, order books, bid and ask prices, live quotes, and more) + about cryptocurrencies and crypto exchanges. See + for a detailed documentation. + date_publication: '2021-06-09' + bug_reports: https://github.com/lorenzbr/cryptowatchR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cryptowatchR + url_git: https://github.com/lorenzbr/cryptowatchR +CryptRndTest: + version: 1.2.7 + title: Statistical Tests for Cryptographic Randomness + maintainer: Haydar Demirhan + description: |- + Performs cryptographic randomness tests on a sequence of random + integers or bits. Included tests are greatest common divisor, birthday spacings, + book stack, adaptive chi-square, topological binary, and three random walk + tests (Ryabko and Monarev, 2005) . Tests except greatest common divisor and birthday spacings are not + covered by standard test suites. In addition to the chi-square goodness-of-fit + test, results of Anderson-Darling, Kolmogorov-Smirnov, and Jarque-Bera tests are + also generated by some of the cryptographic randomness tests. + date_publication: '2022-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CryptRndTest + url_git: '' +cryst: + version: 0.1.0 + title: Calculate the Relative Crystallinity of Starch by XRD and FTIR + maintainer: Claudio Pozo Valenzuela + description: Functions to calculate the relative crystallinity of starch by X-ray + Diffraction (XRD) and Infrared Spectroscopy (FTIR). Starch is biosynthesized by + plants in the form of granules semicrystalline. For XRD, the relative crystallinity + is obtained by separating the crystalline peaks from the amorphous scattering + region. For FTIR, the relative crystallinity is achieved by setting of a Gaussian + holocrystalline-peak in the 800-1300 cm-1 region of FTIR spectrum of starch which + is divided into amorphous region and crystalline region. The relative crystallinity + of native starch granules varies from 14 of 45 percent. This package was supported + by FONDECYT 3150630 and CIPA Conicyt-Regional R08C1002 is gratefully acknowledged. + date_publication: '2016-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cryst + url_git: '' +csa: + version: 0.7.1 + title: |- + A Cross-Scale Analysis Tool for Model-Observation Visualization + and Integration + maintainer: Yannis Markonis + description: Integration of Earth system data from various sources is a challenging + task. Except for their qualitative heterogeneity, different data records exist + for describing similar Earth system process at different spatio-temporal scales. + Data inter-comparison and validation are usually performed at a single spatial + or temporal scale, which could hamper the identification of potential discrepancies + in other scales. 'csa' package offers a simple, yet efficient, graphical method + for synthesizing and comparing observed and modelled data across a range of spatio-temporal + scales. Instead of focusing at specific scales, such as annual means or original + grid resolution, we examine how their statistical properties change across spatio-temporal + continuum. + date_publication: '2023-10-24' + bug_reports: https://github.com/imarkonis/csa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=csa + url_git: https://github.com/imarkonis/csa +csalert: + version: 2024.6.24 + title: Alerts from Public Health Surveillance Data + maintainer: Richard Aubrey White + description: Helps create alerts and determine trends by using various methods to + analyze public health surveillance data. The primary analysis method is based + upon a published analytics strategy by Benedetti (2019) . + date_publication: '2024-06-24' + bug_reports: https://github.com/csids/csalert/issues + url: https://www.csids.no/csalert/ + url_cran: https://CRAN.R-project.org/package=csalert + url_git: https://github.com/csids/csalert +csampling: + version: 1.2-2.1 + title: Functions for Conditional Simulation in Regression-Scale Models + maintainer: Alessandra R. Brazzale + description: |- + Monte Carlo conditional inference for the parameters of a + linear nonnormal regression model. + date_publication: '2018-04-16' + bug_reports: '' + url: http://statwww.epfl.ch/AA/ + url_cran: https://CRAN.R-project.org/package=csampling + url_git: '' +CsChange: + version: 0.1.7 + title: Testing for Change in C-Statistic + maintainer: Zhicheng Du + description: Calculate the confidence interval and p value for change in C-statistic. + The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. + The confidence interval was calculated by using the bootstrap method. The p value + was calculated by using the Z testing method. Please refer to the article of Peter + Ganz et al. (2016) . + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CsChange + url_git: '' +csci: + version: 0.9.3 + title: Current Status Confidence Intervals + maintainer: Michael P. Fay + description: Calculates pointwise confidence intervals for the cumulative distribution + function of the event time for current status data, data where each individual + is assessed at one time to see if they had the event or not by the assessment + time. + date_publication: '2020-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csci + url_git: '' +CSclone: + version: '1.0' + title: Bayesian Nonparametric Modeling in R + maintainer: Peter Wu + description: |- + Germline and somatic locus data which contain the total read depth and B allele + read depth using Bayesian model (Dirichlet Process) to cluster. Meanwhile, the cluster + model can deal with the SNVs mutation and the CNAs mutation. + date_publication: '2016-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSclone + url_git: '' +CSCNet: + version: 0.1.2 + title: |- + Fitting and Tuning Regularized Cause-Specific Cox Models with + Elastic-Net Penalty + maintainer: Shahin Roshani + description: Flexible tools to fit, tune and obtain absolute risk predictions from + regularized cause-specific cox models with elastic-net penalty. + date_publication: '2022-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSCNet + url_git: '' +csdata: + version: 2024.4.26 + title: Structural Data for Norway + maintainer: Richard Aubrey White + description: Datasets relating to population in municipalities, municipality/county + matching, and how different municipalities have merged/redistricted over time + from 2006 to 2024. + date_publication: '2024-04-26' + bug_reports: https://github.com/csids/csdata/issues + url: https://www.csids.no/csdata/ + url_cran: https://CRAN.R-project.org/package=csdata + url_git: https://github.com/csids/csdata +cSEM: + version: 0.6.0 + title: Composite-Based Structural Equation Modeling + maintainer: Florian Schuberth + description: |- + Estimate, assess, test, and study linear, nonlinear, hierarchical + and multigroup structural equation models using composite-based approaches + and procedures, including estimation techniques such as partial least squares + path modeling (PLS-PM) and its derivatives (PLSc, ordPLSc, robustPLSc), + generalized structured component analysis (GSCA), generalized structured + component analysis with uniqueness terms (GSCAm), generalized canonical + correlation analysis (GCCA), principal component analysis (PCA), + factor score regression (FSR) using sum score, regression or + Bartlett scores (including bias correction using Croon’s approach), + as well as several tests and typical postestimation procedures + (e.g., verify admissibility of the estimates, assess the model fit, + test the model fit etc.). + date_publication: '2025-02-25' + bug_reports: https://github.com/FloSchuberth/cSEM/issues/ + url: https://floschuberth.github.io/cSEM/ + url_cran: https://CRAN.R-project.org/package=cSEM + url_git: https://github.com/FloSchuberth/cSEM/ +CSeqpat: + version: 0.1.2 + title: Frequent Contiguous Sequential Pattern Mining of Text + maintainer: Anantha Janakiraman + description: Mines contiguous sequential patterns in text. + date_publication: '2018-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSeqpat + url_git: '' +CSESA: + version: 1.2.0 + title: CRISPR-Based Salmonella Enterica Serotype Analyzer + maintainer: Xia Zhang + description: Salmonella enterica is a major cause of bacterial food-borne disease + worldwide. Serotype identification is the most commonly used typing method to + characterize Salmonella isolates. However, experimental serotyping needs great + cost on manpower and resources. Recently, we found that the newly incorporated + spacer in the clustered regularly interspaced short palindromic repeat (CRISPR) + could serve as an effective marker for typing of Salmonella. It was further revealed + by Li et. al (2014) that recognized types based on + the combination of two newly incorporated spacer in both CRISPR loci showed high + accordance with serotypes. Here, we developed an R package 'CSESA' to predict + the serotype based on this finding. Considering it’s time saving and of high accuracy, + we recommend to predict the serotypes of unknown Salmonella isolates using 'CSESA' + before doing the traditional serotyping. + date_publication: '2019-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSESA + url_git: '' +CSGo: + version: 0.6.7 + title: Collecting Counter Strike Global Offensive Data + maintainer: Adson Costanzi + description: An implementation of calls designed to collect and organize in an easy + way the data from the Steam API specifically for the Counter-Strike Global Offensive + Game (CS Go) . + date_publication: '2021-05-07' + bug_reports: https://github.com/adsoncostanzifilho/CSGo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CSGo + url_git: https://github.com/adsoncostanzifilho/CSGo +cshapes: + version: '2.0' + title: The CShapes 2.0 Dataset and Utilities + maintainer: Luc Girardin + description: Package for CShapes 2.0, a GIS dataset of country borders (1886-today). + Includes functions for data extraction and the computation of distance matrices + and -lists. + date_publication: '2021-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cshapes + url_git: '' +CSHShydRology: + version: 1.4.2 + title: Canadian Hydrological Analyses + maintainer: Kevin Shook + description: A collection of user-submitted functions to aid in the analysis of + hydrological data, particularly for users in Canada. The functions focus on the + use of Canadian data sets, and are suited to Canadian hydrology, such as the important + cold region hydrological processes and will work with Canadian hydrological models. + The functions are grouped into several themes, currently including Statistical + hydrology, Basic data manipulations, Visualization, and Spatial hydrology. Functions + developed by the Floodnet project are also included. CSHShydRology has been developed + with the assistance of the Canadian Society for Hydrological Sciences (CSHS) which + is an affiliated society of the Canadian Water Resources Association (CWRA). As + of version 1.2.6, functions now fail gracefully when attempting to download data + from a url which is unavailable. + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSHShydRology + url_git: https://github.com/CSHS-hydRology/CSHShydRology +CSIndicators: + version: 1.1.1 + title: |- + Climate Services' Indicators Based on Sub-Seasonal to Decadal + Predictions + maintainer: Victòria Agudetse + description: |- + Set of generalised tools for the flexible computation of climate + related indicators defined by the user. Each method represents a specific + mathematical approach which is combined with the possibility to select an + arbitrary time period to define the indicator. This enables a wide range of + possibilities to tailor the most suitable indicator for each particular climate + service application (agriculture, food security, energy, water management, ...). + This package is intended for sub-seasonal, seasonal and decadal climate + predictions, but its methods are also applicable to other time-scales, + provided the dimensional structure of the input is maintained. Additionally, + the outputs of the functions in this package are compatible with 'CSTools'. + This package is described in 'Pérez-Zanón et al. (2023) + ' and it was developed in the context of + 'H2020 MED-GOLD' (776467) and 'S2S4E' (776787) projects. See 'Lledó et al. (2019) + ' and 'Chou et al., 2023 + ' for details. + date_publication: '2024-01-24' + bug_reports: https://earth.bsc.es/gitlab/es/csindicators/-/issues + url: https://earth.bsc.es/gitlab/es/csindicators/ + url_cran: https://CRAN.R-project.org/package=CSIndicators + url_git: '' +csmaps: + version: 2023.5.22 + title: Preformatted Maps of Norway that Don't Need Geolibraries + maintainer: Richard Aubrey White + description: |- + Provides datasets containing preformatted maps of Norway at + the county, municipality, and ward (Oslo only) level for redistricting in + 2024, 2020, 2018, and 2017. Multiple layouts are provided (normal, split, + and with an insert for Oslo), allowing the user to rapidly create choropleth + maps of Norway without any geolibraries. + date_publication: '2023-05-23' + bug_reports: https://github.com/csids/csmaps/issues + url: https://www.csids.no/csmaps/ + url_cran: https://CRAN.R-project.org/package=csmaps + url_git: https://github.com/csids/csmaps +CSMES: + version: 1.0.1 + title: |- + Cost-Sensitive Multi-Criteria Ensemble Selection for Uncertain + Cost Conditions + maintainer: Koen W. De Bock + description: Functions for cost-sensitive multi-criteria ensemble selection (CSMES) + (as described in De bock et al. (2020) ) for cost-sensitive + learning under unknown cost conditions. + date_publication: '2023-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSMES + url_git: '' +csmGmm: + version: 0.3.0 + title: Conditionally Symmetric Multidimensional Gaussian Mixture Model + maintainer: Ryan Sun + description: Implements the conditionally symmetric multidimensional Gaussian mixture + model (csmGmm) for large-scale testing of composite null hypotheses in genetic + association applications such as mediation analysis, pleiotropy analysis, and + replication analysis. In such analyses, we typically have J sets of K test statistics + where K is a small number (e.g. 2 or 3) and J is large (e.g. 1 million). For each + one of the J sets, we want to know if we can reject all K individual nulls. Please + see the vignette for a quickstart guide. The paper describing these methods is + "Testing a Large Number of Composite Null Hypotheses Using Conditionally Symmetric + Multidimensional Gaussian Mixtures in Genome-Wide Studies" by Sun R, McCaw Z, + & Lin X (2024, ). The paper is accepted and + published online (but not yet in print) in the Journal of the American Statistical + Association as of Dec 1 2024. + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csmGmm + url_git: '' +csmpv: + version: 1.0.3 + title: |- + Biomarker Confirmation, Selection, Modelling, Prediction, and + Validation + maintainer: Aixiang Jiang + description: |2- + + There are diverse purposes such as biomarker confirmation, novel biomarker discovery, constructing predictive models, model-based prediction, and validation. + It handles binary, continuous, and time-to-event outcomes at the sample or patient level. + - Biomarker confirmation utilizes established functions like glm() from 'stats', coxph() from 'survival', surv_fit(), and ggsurvplot() from 'survminer'. + - Biomarker discovery and variable selection are facilitated by three LASSO-related functions LASSO2(), LASSO_plus(), and LASSO2plus(), leveraging the 'glmnet' R package with additional steps. + - Eight versatile modeling functions are offered, each designed for predictive models across various outcomes and data types. + 1) LASSO2(), LASSO_plus(), LASSO2plus(), and LASSO2_reg() perform variable selection using LASSO methods and construct predictive models based on selected variables. + 2) XGBtraining() employs 'XGBoost' for model building and is the only function not involving variable selection. + 3) Functions like LASSO2_XGBtraining(), LASSOplus_XGBtraining(), and LASSO2plus_XGBtraining() combine LASSO-related variable selection with 'XGBoost' for model construction. + - All models support prediction and validation, requiring a testing dataset comparable to the training dataset. + Additionally, the package introduces XGpred() for risk prediction based on survival data, with the XGpred_predict() function available for predicting risk groups in new datasets. + The methodology is based on our new algorithms and various references: + - Hastie et al. (1992, ISBN 0 534 16765-9), + - Therneau et al. (2000, ISBN 0-387-98784-3), + - Kassambara et al. (2021) , + - Friedman et al. (2010) , + - Simon et al. (2011) , + - Harrell (2023) , + - Harrell (2023) , + - Chen and Guestrin (2016) , + - Aoki et al. (2023) . + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csmpv + url_git: '' +csn: + version: 1.1.3 + title: Closed Skew-Normal Distribution + maintainer: Dmitry Pavlyuk + description: |- + Provides functions for computing the density + and the log-likelihood function of closed-skew normal variates, + and for generating random vectors sampled from this distribution. + See Gonzalez-Farias, G., Dominguez-Molina, J., and Gupta, A. (2004). + The closed skew normal distribution, + Skew-elliptical distributions and their applications: a journey beyond normality, + Chapman and Hall/CRC, Boca Raton, FL, pp. 25-42. + date_publication: '2015-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csn + url_git: '' +csodata: + version: 1.5.0 + title: Download Data from the CSO 'PxStat' API + maintainer: Conor Crowley + description: |- + Imports 'PxStat' data in JSON-stat format and (optionally) reshapes it into wide + format. The Central Statistics Office (CSO) is the national statistical institute of Ireland + and 'PxStat' is the CSOs online database of Official Statistics. This database contains current + and historical data series compiled from CSO statistical releases and is accessed at + . + The CSO 'PxStat' Application Programming Interface (API), which is accessed in this package, provides + access to 'PxStat' data in JSON-stat format at . + This dissemination tool allows developers machine to machine access to CSO 'PxStat' data. + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csodata + url_git: https://github.com/CSOIreland/csodata +cspec: + version: 0.1.2 + title: Complete Discrete Fourier Transform (DFT) and Periodogram + maintainer: Junho Yang + description: 'Calculate the predictive discrete Fourier transform, complete discrete + Fourier transform, complete periodogram, and tapered complete periodogram. This + algorithm is based on the preprint "Spectral methods for small sample time series: + A complete periodogram approach" (2020) by Sourav Das, Suhasini Subba Rao, and + Junho Yang.' + date_publication: '2020-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cspec + url_git: '' +cspp: + version: 0.3.3 + title: A Tool for the Correlates of State Policy Project Data + maintainer: Caleb Lucas + description: A tool that imports, subsets, visualizes, and exports the Correlates + of State Policy Project dataset assembled by Marty P. Jordan and Matt Grossmann + (2020) . The Correlates + data contains over 2000 variables across more than 100 years that pertain to state + politics and policy in the United States. Users with only a basic understanding + of R can subset this data across multiple dimensions, export their search results, + create map visualizations, export the citations associated with their searches, + and more. + date_publication: '2022-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cspp + url_git: '' +csppData: + version: 0.2.61 + title: 'Data Only: The Correlates of State Policy Project Dataset' + maintainer: Caleb Lucas + description: Contains the Correlates of State Policy Project dataset (+ codebook) + assembled by Marty P. Jordan and Matt Grossmann (2020) + used by the 'cspp' package. The Correlates data contains over 3000 variables across + more than 100 years that pertain to state politics and policy in the United States. + date_publication: '2022-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csppData + url_git: '' +csquares: + version: 0.1.0 + title: Concise Spatial Query and Representation System (c-Squares) + maintainer: Pepijn de Vries + description: |- + Encode and decode c-squares, from and to simple feature (sf) + or spatiotemporal arrays (stars) objects. Use c-squares codes to quickly + join or query spatial data. + date_publication: '2024-08-29' + bug_reports: https://github.com/pepijn-devries/csquares/issues + url: https://pepijn-devries.github.io/csquares/ + url_cran: https://CRAN.R-project.org/package=csquares + url_git: https://github.com/pepijn-devries/csquares/ +csranks: + version: 1.2.3 + title: Statistical Tools for Ranks + maintainer: Daniel Wilhelm + description: |- + Account for uncertainty when working with ranks. + Estimate standard errors consistently in linear regression with ranked variables. + Construct confidence sets of various kinds for positions of populations in a ranking + based on values of a certain feature and their estimation errors. + Theory based on Mogstad, Romano, Shaikh, and Wilhelm (2023) and + Chetverikov and Wilhelm (2023) . + date_publication: '2024-09-12' + bug_reports: https://github.com/danielwilhelm/R-CS-ranks/issues + url: https://danielwilhelm.github.io/R-CS-ranks/ + url_cran: https://CRAN.R-project.org/package=csranks + url_git: https://github.com/danielwilhelm/R-CS-ranks +cssTools: + version: '1.0' + title: Cognitive Social Structure Tools + maintainer: Deniz Yenigun + description: A collection of tools for estimating a network from a random sample + of cognitive social structure (CSS) slices. Also contains functions for evaluating + a CSS in terms of various error types observed in each slice. + date_publication: '2016-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cssTools + url_git: '' +cstab: + version: 0.2-2 + title: |- + Selection of Number of Clusters via Normalized Clustering + Instability + maintainer: Jonas M. B. Haslbeck + description: |- + Selection of the number of clusters in cluster analysis using + stability methods. + date_publication: '2018-06-19' + bug_reports: https://github.com/jmbh/cstab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cstab + url_git: '' +CSTE: + version: 3.0.0 + title: Covariate Specific Treatment Effect (CSTE) Curve + maintainer: Wenjie Hu + description: |- + A uniform statistical inferential tool in making individualized treatment decisions, which implements the methods of Ma et al. (2017) + and Guo et al. (2021). It uses a flexible semiparametric modeling strategy for heterogeneous treatment effect estimation in high-dimensional settings and can gave valid confidence bands. Based on it, one can find the subgroups of patients that benefit from each treatment, thereby making individualized treatment selection. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSTE + url_git: '' +cstidy: + version: 2023.5.24 + title: Helpful Functions for Cleaning Surveillance Data + maintainer: Richard Aubrey White + description: Helpful functions for the cleaning and manipulation of surveillance + data, especially with regards to the creation and validation of panel data from + individual level surveillance data. + date_publication: '2023-05-24' + bug_reports: https://github.com/csids/cstidy/issues + url: https://www.csids.no/cstidy/ + url_cran: https://CRAN.R-project.org/package=cstidy + url_git: https://github.com/csids/cstidy +cstime: + version: 2023.5.3 + title: Date and Time Functions for Public Health Purposes + maintainer: Chi Zhang + description: Provides easy and consistent time conversion for public health purposes. + The time conversion functions provided here are between date, ISO week, ISO yearweek, + ISO year, calendar month/year, season, season week. + date_publication: '2023-05-15' + bug_reports: https://github.com/csids/cstime/issues + url: https://www.csids.no/cstime/ + url_cran: https://CRAN.R-project.org/package=cstime + url_git: https://github.com/csids/cstime +CSTools: + version: 5.2.0 + title: |- + Assessing Skill of Climate Forecasts on Seasonal-to-Decadal + Timescales + maintainer: Victoria Agudetse + description: |- + Exploits dynamical seasonal forecasts in order to provide + information relevant to stakeholders at the seasonal timescale. The package + contains process-based methods for forecast calibration, bias correction, + statistical and stochastic downscaling, optimal forecast combination and + multivariate verification, as well as basic and advanced tools to obtain + tailored products. This package was developed in the context of the 'ERA4CS' + project 'MEDSCOPE' and the 'H2020 S2S4E' project and includes contributions from + 'ArticXchange' project founded by 'EU-PolarNet 2'. + 'Pérez-Zanón et al. (2022) '. + 'Doblas-Reyes et al. (2005) '. + 'Mishra et al. (2018) '. + 'Sanchez-Garcia et al. (2019) '. + 'Straus et al. (2007) '. + 'Terzago et al. (2018) '. + 'Torralba et al. (2017) '. + 'D'Onofrio et al. (2014) '. + 'Verfaillie et al. (2017) '. + 'Van Schaeybroeck et al. (2019) '. + 'Yiou et al. (2013) '. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CSTools + url_git: '' +csurvey: + version: '1.10' + title: Constrained Regression for Survey Data + maintainer: Xiyue Liao + description: Domain mean estimation with monotonicity or block monotone constraints. + See Xu X, Meyer MC and Opsomer JD (2021) for more + details. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csurvey + url_git: '' +csutil: + version: 2023.4.25 + title: Common Base-R Problems Relating to Lists + maintainer: Richard Aubrey White + description: |- + Utility functions that help with common base-R problems relating to lists. + Lists in base-R are very flexible. This package provides functions to quickly and easily + characterize types of lists. That is, to identify if all elements in a list + are null, data.frames, lists, or fully named lists. Other functionality is provided + for the handling of lists, such as the easy splitting of lists into equally sized + groups, and the unnesting of data.frames within fully named lists. + date_publication: '2023-04-25' + bug_reports: https://github.com/csids/csutil/issues + url: https://www.csids.no/csutil/ + url_cran: https://CRAN.R-project.org/package=csutil + url_git: https://github.com/csids/csutil +csv: + version: 0.6.2 + title: Read and Write CSV Files with Selected Conventions + maintainer: Tim Bergsma + description: |- + Reads and writes CSV with selected conventions. + Uses the same generic function for reading and writing to promote consistent formats. + date_publication: '2022-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csv + url_git: '' +csvread: + version: 1.2.3 + title: Fast Specialized CSV File Loader + maintainer: Sergei Izrailev + description: |- + Functions for loading large (10M+ lines) CSV + and other delimited files, similar to read.csv, but typically faster and + using less memory than the standard R loader. While not entirely general, + it covers many common use cases when the types of columns in the CSV file + are known in advance. In addition, the package provides a class 'int64', + which represents 64-bit integers exactly when reading from a file. The + latter is useful when working with 64-bit integer identifiers exported from + databases. The CSV file loader supports common column types including + 'integer', 'double', 'string', and 'int64', leaving further type + transformations to the user. + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=csvread + url_git: https://github.com/jabiru/csvread +csvwr: + version: 0.1.7 + title: Read and Write CSV on the Web (CSVW) Tables and Metadata + maintainer: Robin Gower + description: |- + Provide functions for reading and writing CSVW - i.e. CSV tables and JSON metadata. + The metadata helps interpret CSV by setting the types and variable names. + date_publication: '2022-11-21' + bug_reports: https://github.com/Robsteranium/csvwr/issues + url: https://robsteranium.github.io/csvwr/ + url_cran: https://CRAN.R-project.org/package=csvwr + url_git: https://github.com/Robsteranium/csvwr +csvy: + version: 0.3.0 + title: Import and Export CSV Data with a YAML Metadata Header + maintainer: Thomas J. Leeper + description: Support for import from and export to the CSVY file format. CSVY is + a file format that combines the simplicity of CSV (comma-separated values) with + the metadata of other plain text and binary formats (JSON, XML, Stata, etc.) by + placing a YAML header on top of a regular CSV. + date_publication: '2018-08-01' + bug_reports: https://github.com/leeper/csvy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=csvy + url_git: https://github.com/leeper/csvy +cta: + version: 1.3.0 + title: Contingency Table Analysis Based on ML Fitting of MPH Models + maintainer: Qiansheng Zhu + description: |- + Contingency table analysis is performed based on maximum likelihood (ML) fitting of + multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models. + See Lang (2004) and Lang (2005) + for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood- + based (cell- and link-specific) residuals; and cell probability and expected count estimates along + with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood, + score, power-divergence--confidence intervals for contingency table estimands, when table + probabilities are potentially subject to equality constraints. For test-inversion intervals, see + Lang (2008) and Zhu (2020) . + date_publication: '2021-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cta + url_git: '' +ctablerseh: + version: 1.1.2 + title: |- + Processing Survey Data with Confidence Intervals Like 'SPSS' + Software + maintainer: Asy-Syaja'ul Haqqul Amin + description: Processes survey data and displays estimation results along with the + relative standard error in a table, including the number of samples and also uses + a t-distribution approach to compute confidence intervals, similar to 'SPSS' (Statistical + Package for the Social Sciences) software. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctablerseh + url_git: '' +CTAShiny: + version: 0.1.0 + title: Interactive Application for Working with Contingency Tables + maintainer: Kartikeya Bolar + description: An interactive application for working with contingency Tables. The + application has a template for solving contingency table problems like chisquare + test of independence,association plot between two categorical variables. Runtime + examples are provided in the package function as well as at . + date_publication: '2019-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTAShiny + url_git: '' +ctbi: + version: 2.0.5 + title: A Procedure to Clean, Decompose and Aggregate Timeseries + maintainer: Francois Ritter + description: 'Clean, decompose and aggregate univariate time series following the + procedure "Cyclic/trend decomposition using bin interpolation" and the Logbox + method for flagging outliers, both detailed in Ritter, F.: Technical note: A procedure + to clean, decompose, and aggregate time series, Hydrol. Earth Syst. Sci., 27, + 349–361, , 2023.' + date_publication: '2023-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctbi + url_git: https://github.com/fritte2/ctbi +CTD: + version: '1.3' + title: A Method for 'Connecting The Dots' in Weighted Graphs + maintainer: Varduhi Petrosyan + description: 'A method for pattern discovery in weighted graphs as outlined in Thistlethwaite + et al. (2021) . Two use cases are achieved: + 1) Given a weighted graph and a subset of its nodes, do the nodes show significant + connectedness? 2) Given a weighted graph and two subsets of its nodes, are the + subsets close neighbors or distant?' + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTD + url_git: '' +ctf: + version: 0.1.0 + title: Read and Write Column Text Format (CTF) + maintainer: Clark Fitzgerald + description: |2- + + Column Text Format (CTF) is a new tabular data format designed for simplicity and performance. + CTF is the simplest column store you can imagine: plain text files for each column in a table, and a metadata file. + The underlying plain text means the data is human readable and familiar to programmers, unlike specialized binary formats. + CTF is faster than row oriented formats like CSV when loading a subset of the columns in a table. + This package provides functions to read and write CTF data from R. + date_publication: '2021-07-07' + bug_reports: https://github.com/julianofhernandez/ctf + url: '' + url_cran: https://CRAN.R-project.org/package=ctf + url_git: https://github.com/julianofhernandez/ctf +ctgdist: + version: 0.1.0 + title: Likert Category Distance Calculator + maintainer: Huseyin Yildiz + description: It is assumed that psychological distances between the categories are + equal for the measurement instruments consisted of polytomously scored items. + According to Muraki, this assumption must be tested. In the examination process + of this assumption, the fit indexes are obtained and evaluated. This package provides + that this assumption is removed. By with this package, the converted scale values + of all items in a measurement instrument can be calculated by estimating a category + parameter set for each item. Thus, the calculations can be made without any need + to usage of the common category parameter set. Through this package, the psychological + distances of the items are scaled. The scaling of a category parameter set for + each item cause differentiation of score of the categories will be got from items. + Also, the total measurement instrument score of an individual can be calculated + according to the scaling of item score categories by with this package.This package + provides that the place of individuals related to the structure to be measured + with a measurement instrument consisted of polytomously scored items can be reveal + more accurately. In this way, it is thought that the results obtained about individuals + can be made more sensitive, and the differences between individuals can be revealed + more accurately. On the other hand, it can be argued that more accurate evidences + can be obtained regarding the psychometric properties of the measurement instruments. + date_publication: '2020-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctgdist + url_git: '' +ctgt: + version: 2.0.1 + title: Closed Testing with Globaltest for Pathway Analysis + maintainer: Ningning Xu + description: A shortcut procedure is proposed to implement closed testing for large-scale + multiple testings, especially with the global test. This shortcut is asymptotically + equivalent to closed testing and post hoc. Users could detect any possible sets + of features or pathways with family-wise error rate controlled. The global test + is powerful to detect associations between a group of features and an outcome + of interest. + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctgt + url_git: '' +cthist: + version: 2.1.11 + title: Clinical Trial Registry History + maintainer: Benjamin Gregory Carlisle + description: |- + Retrieves historical versions of clinical trial registry + entries from . Package functionality + and implementation for v 1.0.0 is documented in Carlisle (2022) + . + date_publication: '2024-07-17' + bug_reports: https://github.com/bgcarlisle/cthist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cthist + url_git: https://github.com/bgcarlisle/cthist +cthreshER: + version: 1.1.0 + title: Continuous Threshold Expectile Regression + maintainer: Feipeng Zhang + description: |- + Estimation and inference methods for the continuous threshold expectile regression. + It can fit the continuous threshold expectile regression and test the existence of change point, + for the paper, "Feipeng Zhang and Qunhua Li (2016). A continuous threshold expectile regression, submitted." + date_publication: '2016-11-10' + bug_reports: '' + url: https://arxiv.org/abs/1611.02609 + url_cran: https://CRAN.R-project.org/package=cthreshER + url_git: '' +ctl: + version: 1.0.0-10 + title: Correlated Trait Locus Mapping + maintainer: Danny Arends + description: |- + Identification and network inference of genetic loci associated + with correlation changes in quantitative traits (called correlated trait loci, CTLs). + Arends et al. (2016) . + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctl + url_git: '' +CTM: + version: '0.2' + title: A Text Mining Toolkit for Chinese Document + maintainer: Jim Liu + description: The CTM package is designed to solve problems of text mining and is + specific for Chinese document. + date_publication: '2016-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTM + url_git: '' +ctmcd: + version: 1.4.4 + title: |- + Estimating the Parameters of a Continuous-Time Markov Chain from + Discrete-Time Data + maintainer: Marius Pfeuffer + description: Estimation of Markov generator matrices from discrete-time observations. + The implemented approaches comprise diagonal and weighted adjustment of matrix + logarithm based candidate solutions as in Israel (2001) + as well as a quasi-optimization approach. Moreover, the expectation-maximization + algorithm and the Gibbs sampling approach of Bladt and Sorensen (2005) + are included. + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctmcd + url_git: '' +ctmcmove: + version: 1.2.10 + title: |- + Modeling Animal Movement with Continuous-Time Discrete-Space + Markov Chains + maintainer: Ephraim Hanks + description: Software to facilitates taking movement data in xyt format and pairing + it with raster covariates within a continuous time Markov chain (CTMC) framework. As + described in Hanks et al. (2015) , this allows flexible + modeling of movement in response to covariates (or covariate gradients) with model + fitting possible within a Poisson GLM framework. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctmcmove + url_git: '' +cTMed: + version: 1.0.6 + title: Continuous Time Mediation + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Calculates standard errors and confidence intervals for effects in continuous-time mediation models. This package extends the work of + Deboeck and Preacher (2015) and + Ryan and Hamaker (2021) + by providing methods to generate standard errors and confidence intervals for the total, direct, and indirect effects in these models. + date_publication: '2025-02-21' + bug_reports: https://github.com/jeksterslab/cTMed/issues + url: https://jeksterslab.github.io/cTMed/ + url_cran: https://CRAN.R-project.org/package=cTMed + url_git: https://github.com/jeksterslab/cTMed +ctmle: + version: 0.1.2 + title: Collaborative Targeted Maximum Likelihood Estimation + maintainer: Cheng Ju + description: Implements the general template for collaborative targeted maximum + likelihood estimation. It also provides several commonly used C-TMLE instantiation, + like the vanilla/scalable variable-selection C-TMLE (Ju et al. (2017) ) + and the glmnet-C-TMLE algorithm (Ju et al. (2017) ). + date_publication: '2019-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctmle + url_git: '' +ctmm: + version: 1.2.0 + title: Continuous-Time Movement Modeling + maintainer: Christen H. Fleming + description: |- + Functions for identifying, fitting, and applying continuous-space, continuous-time stochastic-process movement models to animal tracking data. + The package is described in Calabrese et al (2016) , with models and methods based on those introduced and detailed in + Fleming & Calabrese et al (2014) , + Fleming et al (2014) , + Fleming et al (2015) , + Fleming et al (2015) , + Fleming et al (2016) , + Péron & Fleming et al (2016) , + Fleming & Calabrese (2017) , + Péron et al (2017) , + Fleming et al (2017) , + Fleming et al (2018) , + Winner & Noonan et al (2018) , + Fleming et al (2019) , + Noonan & Fleming et al (2019) , + Fleming et al (2020) , + Noonan et al (2021) , + Fleming et al (2022) , + Silva et al (2022) , + Alston & Fleming et al (2023) . + date_publication: '2023-09-23' + bug_reports: '' + url: https://groups.google.com/g/ctmm-user + url_cran: https://CRAN.R-project.org/package=ctmm + url_git: https://github.com/ctmm-initiative/ctmm +ctmva: + version: 1.4.0 + title: Continuous-Time Multivariate Analysis + maintainer: Biplab Paul + description: |- + Implements a basis function or functional data analysis framework + for several techniques of multivariate analysis in continuous-time + setting. Specifically, we introduced continuous-time analogues of + several classical techniques of multivariate analysis, such as + principal component analysis, canonical correlation analysis, + Fisher linear discriminant analysis, K-means clustering, and so + on. Details are in Biplab Paul, Philip T. Reiss and Erjia Cui (2023) + "Continuous-time multivariate analysis" . + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctmva + url_git: '' +CTNote: + version: 0.1.0 + title: CTN Outcomes, Treatments, and Endpoints + maintainer: Gabriel Odom + description: |- + The Clinical Trials Network (CTN) of the U.S. National Institute + of Drug Abuse sponsored the CTN-0094 research team to harmonize data sets + from three nationally-representative clinical trials for opioid use disorder + (OUD). The CTN-0094 team herein provides a coded collection of trial outcomes + and endpoints used in various OUD clinical trials over the past 50 years. + These coded outcome functions are used to contrast and cluster different + clinical outcome functions based on daily or weekly patient urine screenings. + Note that we abbreviate urine drug screen as "UDS" and urine opioid screen as + "UOS". For the example data sets (based on clinical trials data harmonized by + the CTN-0094 research team), UDS and UOS are largely interchangeable. + date_publication: '2022-10-03' + bug_reports: https://github.com/CTN-0094/CTNote/issues + url: https://ctn-0094.github.io/CTNote/ + url_cran: https://CRAN.R-project.org/package=CTNote + url_git: '' +cTOST: + version: 1.0.1 + title: |- + Finite Sample Correction of the Two One-Sided Tests in the + Univariate Framework + maintainer: Younes Boulaguiem + description: A system containing easy-to-use tools to compute the bioequivalence + assessment in the univariate framework using the methods proposed in Boulaguiem + et al. (2023) . + date_publication: '2025-02-10' + bug_reports: https://github.com/yboulag/cTOST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cTOST + url_git: https://github.com/yboulag/cTOST +ctpm: + version: 1.0.1 + title: Continuous-Time Phylogenetic Modeling + maintainer: Michael J. Noonan + description: |- + Functions for identifying, fitting, and applying continuous-time stochastic models to phylogenetic data. + The package is based on methods introduced in + Noonan et al. (2021) . + date_publication: '2021-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctpm + url_git: https://github.com/NoonanM/ctpm +ctqr: + version: '2.1' + title: Censored and Truncated Quantile Regression + maintainer: Paolo Frumento + description: Estimation of quantile regression models for survival data. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctqr + url_git: '' +ctrdata: + version: 1.20.0 + title: Retrieve and Analyze Clinical Trials in Public Registers + maintainer: Ralf Herold + description: |- + A system for querying, retrieving and analyzing + protocol- and results-related information on clinical trials from + four public registers, the 'European Union Clinical Trials Register' + ('EUCTR', ), + 'ClinicalTrials.gov' ( and also + translating queries the retired classic interface), the + 'ISRCTN' () and the + 'European Union Clinical Trials Information System' + ('CTIS', ). + Trial information is downloaded, converted and stored in a database + ('PostgreSQL', 'SQLite', 'DuckDB' or 'MongoDB'; via package 'nodbi'). + Documents in registers associated with trials can also be downloaded. + Other functions identify deduplicated records, + easily find and extract variables (fields) of interest even + from complex nested data as used by the registers, + merge variables and update queries. + The package can be used for meta-analysis and trend-analysis of + the design and conduct as well as of the results of clinical trials. + date_publication: '2024-12-14' + bug_reports: https://github.com/rfhb/ctrdata/issues + url: https://rfhb.github.io/ctrdata/ + url_cran: https://CRAN.R-project.org/package=ctrdata + url_git: '' +ctrialsgov: + version: 0.2.5 + title: |- + Query Data from U.S. National Library of Medicine's Clinical + Trials Database + maintainer: Taylor Arnold + description: |- + Tools to create and query database from the U.S. National Library + of Medicine's Clinical Trials database . Functions + provide access a variety of techniques for searching the data using range + queries, categorical filtering, and by searching for full-text keywords. + Minimal graphical tools are also provided for interactively exploring the + constructed data. + date_publication: '2021-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctrialsgov + url_git: '' +CTRing: + version: 0.1.0 + title: Density Profiles of Wood from CT Scan Images + maintainer: Robert Schneider + description: Computerized tomography (CT) can be used to assess certain wood properties + when wood disks or logs are scanned. Wood density profiles (i.e. variations of + wood density from pith to bark) can yield important information used for studies + in forest resource assessment, wood quality and dendrochronology studies. The + first step consists in transforming grey values from the scan images to density + values. The packages then proposes a unique method to automatically locate the + pith by combining an adapted Hough Transform method and a one-dimensional edge + detector. Tree ring profiles (average ring density, earlywood and latewood density, + ring width and percent latewood for each ring) are then obtained. + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTRing + url_git: '' +ctrlGene: + version: 1.0.1 + title: Assess the Stability of Candidate Housekeeping Genes + maintainer: Shanliang Zhong + description: A simple way to assess the stability of candidate housekeeping genes + is implemented in this package. + date_publication: '2019-07-04' + bug_reports: '' + url: http://www.bioinf.com.cn/ + url_cran: https://CRAN.R-project.org/package=ctrlGene + url_git: '' +ctsem: + version: 3.10.2 + title: Continuous Time Structural Equation Modelling + maintainer: Charles Driver + description: |- + Hierarchical continuous (and discrete) time state space modelling, for linear + and nonlinear systems measured by continuous variables, with limited support for + binary data. The subject specific dynamic system is modelled as a stochastic + differential equation (SDE) or difference equation, measurement models are typically multivariate normal factor models. + Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default. + Nonlinearities, (state dependent parameters) and random effects on all parameters + are possible, using either max likelihood / max a posteriori optimization + (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. + See + for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian + linear SDE approach, + see . + Exogenous inputs may also be included, for an overview of such possibilities see . + Stan based functions are not available on 32 bit Windows systems at present. + contains some tutorial blog posts. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctsem + url_git: https://github.com/cdriveraus/ctsem +ctsemOMX: + version: 1.0.6 + title: Continuous Time SEM - 'OpenMx' Based Functions + maintainer: Charles Driver + description: |- + Original 'ctsem' (continuous time structural equation modelling) + functionality, based on the 'OpenMx' software, as described in + Driver, Oud, Voelkle (2017) , with updated details in vignette. + Combines stochastic differential equations representing latent processes with + structural equation measurement models. These functions were split off from + the main package of 'ctsem', as the main package uses the 'rstan' package as a backend now -- + offering estimation options from max likelihood to Bayesian. + There are nevertheless use cases for the wide format SEM style approach as offered here, + particularly when there are no individual differences in observation timing and the + number of individuals is large. For the main 'ctsem' package, see . + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctsemOMX + url_git: https://github.com/cdriveraus/ctsemOMX +ctsfeatures: + version: 1.2.2 + title: Analyzing Categorical Time Series + maintainer: Angel Lopez-Oriona + description: |- + An implementation of several functions for feature extraction in + categorical time series datasets. Specifically, some features related to + marginal distributions and serial dependence patterns can be computed. These + features can be used to feed clustering and classification algorithms for + categorical time series, among others. The package also includes some + interesting datasets containing biological sequences. Practitioners from a + broad variety of fields could benefit from the general framework provided + by 'ctsfeatures'. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctsfeatures + url_git: '' +CTShiny: + version: 0.1.0 + title: |- + Interactive Document for Working with Classification Tree + Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of classification tree analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTShiny + url_git: '' +CTShiny2: + version: 0.1.0 + title: |- + Interactive Document for Working with Classification Tree + Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of classification tree analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2020-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTShiny2 + url_git: '' +CTT: + version: 2.3.3 + title: Classical Test Theory Functions + maintainer: John T. Willse + description: A collection of common test and item analyses from a classical test + theory (CTT) framework. Analyses can be applied to both dichotomous and polytomous + data. Functions provide reliability analyses (alpha), item statistics, disctractor + analyses, disattenuated correlations, scoring routines, and empirical ICCs. + date_publication: '2018-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTT + url_git: '' +CTTinShiny: + version: 0.1.0 + title: Shiny Interface for the CTT Package + maintainer: John T. Willse + description: A Shiny interface developed in close coordination with the CTT package, + providing a GUI that guides the user through CTT analyses. + date_publication: '2018-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTTinShiny + url_git: '' +CTTShiny: + version: '0.1' + title: Classical Test Theory via Shiny + maintainer: William Kyle Hamilton + description: Interactive shiny application for running classical test theory (item + analysis). + date_publication: '2015-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTTShiny + url_git: '' +CTTvis: + version: 0.1.1 + title: Visualize Item Metrics of the Classical Test Theory Framework + maintainer: Tarid Wongvorachan + description: |- + Visualizes results of item analysis such as item difficulty, + item discrimination, and coefficient alpha for ease of result communication. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTTvis + url_git: https://github.com/TaridWong/CTTvis +ctv: + version: 0.9-6 + title: CRAN Task Views + maintainer: Achim Zeileis + description: |- + Infrastructure for task views to CRAN-style repositories: Querying task views and installing the associated + packages (client-side tools), generating HTML pages and storing task view information in the repository + (server-side tools). + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ctv + url_git: https://github.com/cran-task-views/ctv/ +CTxCC: + version: 0.2.0 + title: |- + Multivariate Normal Mean Monitoring Through Critical-to-X + Control Chart + maintainer: Dr. Diana Barraza-Barraza + description: A comprehensive set of functions designed for multivariate mean monitoring + using the Critical-to-X Control Chart. These functions enable the determination + of optimal control limits based on a specified in-control Average Run Length (ARL), + the calculation of out-of-control ARL for a given control limit, and post-signal + analysis to identify the specific variable responsible for a detected shift in + the mean. This suite of tools provides robust support for precise and effective + process monitoring and analysis. + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CTxCC + url_git: '' +ctxR: + version: 1.1.0 + title: Utilities for Interacting with the 'CTX' APIs + maintainer: Paul Kruse + description: |- + Access chemical, hazard, bioactivity, and exposure data from the + Computational Toxicology and Exposure ('CTX') APIs + . + 'ctxR' was developed to streamline the process of accessing the information + available through the 'CTX' APIs without requiring prior knowledge of how to + use APIs. Most data is also available on the CompTox Chemical Dashboard + ('CCD') and other resources found at the + EPA Computational Toxicology and Exposure Online Resources + . + date_publication: '2025-01-08' + bug_reports: https://github.com/USEPA/ctxR/issues + url: https://usepa.github.io/ctxR/ + url_cran: https://CRAN.R-project.org/package=ctxR + url_git: https://github.com/USEPA/ctxR +ctypesio: + version: 0.1.2 + title: |- + Read and Write Standard 'C' Types from Files, Connections and + Raw Vectors + maintainer: Mike Cheng + description: |- + Interacting with binary files can be difficult because R's types + are a subset of what is generally supported by 'C'. This package provides a + suite of functions for reading and writing binary data (with files, connections, + and raw vectors) using 'C' type descriptions. These functions convert data + between 'C' types and R types while checking for values outside the + type limits, 'NA' values, etc. + date_publication: '2025-01-18' + bug_reports: https://github.com/coolbutuseless/ctypesio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ctypesio + url_git: https://github.com/coolbutuseless/ctypesio +cuadramelo: + version: 1.0.0 + title: Matrix Balancing and Rounding + maintainer: Miguel Serrano + description: Balancing and rounding matrices subject to restrictions. Adjustment + of matrices so that columns and rows add up to given vectors, rounding of a matrix + while keeping the column and/or row totals, performing these by blocks... + date_publication: '2024-10-10' + bug_reports: '' + url: https://mserrano-ine.github.io/cuadramelo/ + url_cran: https://CRAN.R-project.org/package=cuadramelo + url_git: '' +CUB: + version: 1.1.5 + title: A Class of Mixture Models for Ordinal Data + maintainer: Rosaria Simone + description: For ordinal rating data, estimate and test models within the family + of CUB models and their extensions (where CUB stands for Combination of a discrete + Uniform and a shifted Binomial distributions); Simulation routines, plotting facilities + and fitting measures are also provided. + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CUB + url_git: '' +cubar: + version: 1.1.0 + title: Codon Usage Bias Analysis + maintainer: Hong Zhang + description: |- + A suite of functions for rapid and flexible analysis of codon + usage bias. It provides in-depth analysis at the codon level, including + relative synonymous codon usage (RSCU), tRNA weight calculations, machine + learning predictions for optimal or preferred codons, and visualization of + codon-anticodon pairing. Additionally, it can calculate various gene- + specific codon indices such as codon adaptation index (CAI), effective + number of codons (ENC), fraction of optimal codons (Fop), tRNA adaptation + index (tAI), mean codon stabilization coefficients (CSCg), and GC contents + (GC/GC3s/GC4d). It also supports both standard and non-standard genetic + code tables found in NCBI, as well as custom genetic code tables. + date_publication: '2024-12-07' + bug_reports: https://github.com/mt1022/cubar/issues + url: https://mt1022.github.io/cubar/ + url_cran: https://CRAN.R-project.org/package=cubar + url_git: https://github.com/mt1022/cubar +cubature: + version: 2.1.1 + title: Adaptive Multivariate Integration over Hypercubes + maintainer: Balasubramanian Narasimhan + description: |- + R wrappers around the cubature C library of Steven + G. Johnson for adaptive multivariate integration over hypercubes + and the Cuba C library of Thomas Hahn for deterministic and + Monte Carlo integration. Scalar and vector interfaces for + cubature and Cuba routines are provided; the vector interfaces + are highly recommended as demonstrated in the package + vignette. + date_publication: '2024-07-14' + bug_reports: https://github.com/bnaras/cubature/issues + url: https://bnaras.github.io/cubature/ + url_cran: https://CRAN.R-project.org/package=cubature + url_git: '' +cubble: + version: 1.0.0 + title: A Vector Spatio-Temporal Data Structure for Data Analysis + maintainer: H. Sherry Zhang + description: 'A spatiotemperal data object in a relational data structure to separate + the recording of time variant/ invariant variables. See the Journal of Statistical + Software reference: .' + date_publication: '2024-08-27' + bug_reports: https://github.com/huizezhang-sherry/cubble/issues + url: https://huizezhang-sherry.github.io/cubble/ + url_cran: https://CRAN.R-project.org/package=cubble + url_git: https://github.com/huizezhang-sherry/cubble +cubelyr: + version: 1.0.2 + title: A Data Cube 'dplyr' Backend + maintainer: Hadley Wickham + description: |- + An implementation of a data cube extracted out of 'dplyr' for + backward compatibility. + date_publication: '2022-11-07' + bug_reports: https://github.com/hadley/cubelyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cubelyr + url_git: https://github.com/hadley/cubelyr +cubeview: + version: 0.2.0 + title: View 3D Raster Cubes Interactively + maintainer: Tim Appelhans + description: |- + Creates a 3D data cube view of a RasterStack/Brick, typically a + collection/array of RasterLayers (along z-axis) with the same geographical + extent (x and y dimensions) and resolution, provided by package 'raster'. + Slices through each dimension (x/y/z), freely adjustable in location, + are mapped to the visible sides of the cube. The cube can be freely rotated. + Zooming and panning can be used to focus on different areas of the cube. + date_publication: '2019-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cubeview + url_git: '' +cubfits: + version: 0.1-4 + title: Codon Usage Bias Fits + maintainer: Wei-Chen Chen + description: |- + Estimating mutation and selection coefficients on synonymous + codon bias usage based on models of ribosome overhead cost (ROC). + Multinomial logistic regression and Markov Chain Monte Carlo are used to + estimate and predict protein production rates with/without the presence + of expressions and measurement errors. Work flows with examples for + simulation, estimation and prediction processes are also provided + with parallelization speedup. The whole framework is tested with + yeast genome and gene expression data of Yassour, et al. (2009) + . + date_publication: '2021-11-07' + bug_reports: https://github.com/snoweye/cubfits/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cubfits + url_git: https://github.com/snoweye/cubfits +cubicBsplines: + version: 1.0.0 + title: Computation of a Cubic B-Spline Basis and Its Derivatives + maintainer: Philippe Lambert + description: Computation of a cubic B-spline basis for arbitrary knots. It also + provides the 1st and 2nd derivatives, as well as the integral of the basis elements. + It is used by the author to fit penalized B-spline models, see e.g. Jullion, A. + and Lambert, P. (2006) , Lambert, P. and Eilers, + P.H.C. (2009) and, more recently, Lambert, P. + (2021) . It is inspired by the algorithm developed + by de Boor, C. (1977) . + date_publication: '2021-07-13' + bug_reports: '' + url: http://www.statsoc.ulg.ac.be/ + url_cran: https://CRAN.R-project.org/package=cubicBsplines + url_git: '' +cubing: + version: 1.0-5 + title: Rubik's Cube Solving + maintainer: Alec Stephenson + description: |- + Functions for visualizing, animating, solving and + analyzing the Rubik's cube. Includes data structures for + solvable and unsolvable cubes, random moves and random + state scrambles and cubes, 3D displays and animations + using 'OpenGL', patterned cube generation, and lightweight + solvers. See Rokicki, T. (2008) for the + Kociemba solver. + date_publication: '2018-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cubing + url_git: '' +Cubist: + version: 0.4.4 + title: Rule- And Instance-Based Regression Modeling + maintainer: Max Kuhn + description: |- + Regression modeling using rules with added instance-based + corrections. + date_publication: '2024-07-02' + bug_reports: https://github.com/topepo/Cubist/issues + url: https://topepo.github.io/Cubist/ + url_cran: https://CRAN.R-project.org/package=Cubist + url_git: https://github.com/topepo/Cubist +cucumber: + version: 1.2.0 + title: Behavior-Driven Development for R + maintainer: Jakub Sobolewski + description: |- + Write executable specifications in a natural language that describes how your code should behave. + Write specifications in feature files using 'Gherkin' language and execute them using functions implemented in R. + Use them as an extension to your 'testthat' tests to provide a high level description of how your code works. + date_publication: '2025-02-24' + bug_reports: https://github.com/jakubsob/cucumber/issues + url: https://jakubsob.github.io/cucumber/ + url_cran: https://CRAN.R-project.org/package=cucumber + url_git: https://github.com/jakubsob/cucumber +cuda.ml: + version: 0.3.2 + title: R Interface for the RAPIDS cuML Suite of Libraries + maintainer: Daniel Falbel + description: |- + R interface for RAPIDS cuML (), + a suite of GPU-accelerated machine learning libraries powered by CUDA + (). + date_publication: '2022-01-08' + bug_reports: https://github.com/mlverse/cuda.ml/issues + url: https://mlverse.github.io/cuda.ml/ + url_cran: https://CRAN.R-project.org/package=cuda.ml + url_git: '' +CUFF: + version: '1.9' + title: Charles's Utility Function using Formula + maintainer: Charles-Édouard Giguère + description: |- + Utility functions that provides wrapper to descriptive base functions + like cor, mean and table. It makes use of the formula interface to pass + variables to functions. It also provides operators to concatenate (%+%), to + repeat (%n%) and manage character vectors for nice display. + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CUFF + url_git: https://github.com/giguerch/CUFF +cultevo: + version: 1.0.2 + title: Tools, Measures and Statistical Tests for Cultural Evolution + maintainer: Kevin Stadler + description: Provides tools for measuring the compositionality of signalling systems + (in particular the information-theoretic measure due to Spike (2016) + and the Mantel test for distance matrix correlation (after Dietz 1983) ), + functions for computing string and meaning distance matrices as well as an implementation + of the Page test for monotonicity of ranks (Page 1963) + with exact p-values up to k = 22. + date_publication: '2018-04-24' + bug_reports: https://github.com/kevinstadler/cultevo/issues + url: https://kevinstadler.github.io/cultevo/ + url_cran: https://CRAN.R-project.org/package=cultevo + url_git: '' +CUMP: + version: '2.0' + title: Analyze Multivariate Phenotypes by Combining Univariate Results + maintainer: Shuo Li + description: Combining Univariate Association Test Results of Multiple Phenotypes + for Detecting Pleiotropy. + date_publication: '2016-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CUMP + url_git: '' +cumprinc: + version: '0.1' + title: Functions Centered Around Microsoft Excel Cumprinc Function + maintainer: Jason Richardson + description: |- + Provides similar functionality to 'Microsoft Excel' 'CUMPRINC' function . + Returns principal remaining at a given month, principal paid in a month, and accumulated principal paid at a given month based on original loan amount, + monthly interest rate, and term of loan. + date_publication: '2022-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cumprinc + url_git: '' +cumSeg: + version: '1.3' + title: Change Point Detection in Genomic Sequences + maintainer: Vito M.R. Muggeo + description: |- + Estimation of number and location of change points in + mean-shift (piecewise constant) models. Particularly useful (but not confined) to + model genomic sequences of continuous measurements. + date_publication: '2020-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cumSeg + url_git: '' +cumstats: + version: '1.0' + title: Cumulative Descriptive Statistics + maintainer: Arturo Erdely + description: Cumulative descriptive statistics for (arithmetic, geometric, harmonic) + mean, median, mode, variance, skewness and kurtosis. + date_publication: '2017-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cumstats + url_git: '' +cumulcalib: + version: 0.0.1 + title: Cumulative Calibration Assessment for Prediction Models + maintainer: Mohsen Sadatsafavi + description: Tools for visualization of, and inference on, the calibration of prediction + models on the cumulative domain. This provides a method for evaluating calibration + of risk prediction models without having to group the data or use tuning parameters + (e.g., loess bandwidth). This package implements the methodology described in + Sadatsafavi and Patkau (2024) . The core of the package + is cumulcalib(), which takes in vectors of binary responses and predicted risks. + The plot() and summary() methods are implemented for the results returned by cumulcalib(). + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cumulcalib + url_git: https://github.com/resplab/cumulcalib +cumulocityr: + version: 0.1.0 + title: Client for the 'Cumulocity' API + maintainer: Dmitriy Bolotov + description: Access the 'Cumulocity' API and retrieve data on devices, measurements, + and events. Documentation for the API can be found at . + date_publication: '2019-10-20' + bug_reports: https://github.com/SoftwareAG/cumulocityr/issues + url: https://softwareag.github.io/cumulocityr/ + url_cran: https://CRAN.R-project.org/package=cumulocityr + url_git: https://github.com/SoftwareAG/cumulocityr +cuperdec: + version: 1.1.0 + title: Cumulative Percent Decay Curve Generator + maintainer: James A. Fellows Yates + description: |- + Calculates and visualises cumulative percent 'decay' curves, + which are typically calculated from metagenomic taxonomic profiles. + These can be used to estimate the level of expected 'endogenous' taxa + at different abundance levels retrieved from metagenomic samples, when + comparing to samples of known sampling site or source. Method + described in Fellows Yates, J. A. et. al. (2021) Proceedings of the + National Academy of Sciences USA . + date_publication: '2021-09-12' + bug_reports: https://github.com/jfy133/cuperdec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cuperdec + url_git: https://github.com/jfy133/cuperdec +cuRe: + version: 1.1.1 + title: Parametric Cure Model Estimation + maintainer: Lasse Hjort Jakobsen + description: Contains functions for estimating generalized parametric mixture and + non-mixture cure models , loss of lifetime, mean + residual lifetime, and crude event probabilities. + date_publication: '2023-07-03' + bug_reports: https://github.com/LasseHjort/cuRe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cuRe + url_git: https://github.com/LasseHjort/cuRe +CureAuxSP: + version: 0.0.1 + title: |- + Mixture Cure Models with Auxiliary Subgroup Survival + Probabilities + maintainer: Jie Ding + description: Estimate mixture cure models with subgroup survival probabilities as + auxiliary information. A reference of the underlying methods is Jie Ding, Jialiang + Li and Xiaoguang Wang (2024) . + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CureAuxSP + url_git: +CureDepCens: + version: 0.1.0 + title: Dependent Censoring Regression Models with Cure Fraction + maintainer: Silvana Schneider + description: Cure dependent censoring regression models for long-term survival multivariate + data. These models are based on extensions of the frailty models, capable to accommodating + the cure fraction and the dependence between failure and censoring times, with + Weibull and piecewise exponential marginal distributions. Theoretical details + regarding the models implemented in the package can be found in Schneider et al. + (2022) . + date_publication: '2023-06-27' + bug_reports: https://github.com/GabrielGrandemagne/CureDepCens/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CureDepCens + url_git: https://github.com/GabrielGrandemagne/CureDepCens +curephEM: + version: 0.3.0 + title: NPMLE for Logistic-Cox Cure-Rate Model + maintainer: Jue (Marquis) Hou + description: |- + Expectation-Maximization (EM) algorithm for point estimation and variance estimation to + the nonparametric maximum likelihood estimator (NPMLE) for + logistic-Cox cure-rate model with left truncation and right- + censoring. See Hou, Chambers and Xu (2017) . + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=curephEM + url_git: '' +cureplots: + version: 1.1.1 + title: CURE (Cumulative Residual) Plots + maintainer: Guillermo Basulto-Elias + description: Creates 'ggplot2' Cumulative Residual (CURE) plots to check the goodness-of-fit + of a count model; or the tables to create a customized version. A dataset of crashes + in Washington state is available for illustrative purposes. + date_publication: '2024-10-30' + bug_reports: https://github.com/gbasulto/cureplots/issues + url: https://gbasulto.github.io/cureplots/ + url_cran: https://CRAN.R-project.org/package=cureplots + url_git: https://github.com/gbasulto/cureplots +curesurv: + version: 0.1.1 + title: |- + Mixture and Non Mixture Parametric Cure Models to Estimate Cure + Indicators + maintainer: Juste Goungounga + description: Fits a variety of cure models using excess hazard modeling methodology + such as the mixture model proposed by Phillips et al. (2002) + The Weibull distribution is used to represent the survival function of the uncured + patients; Fits also non-mixture cure model such as the time-to-null excess hazard + model proposed by Boussari et al. (2020) . + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=curesurv + url_git: '' +curl: + version: 6.2.1 + title: A Modern and Flexible Web Client for R + maintainer: Jeroen Ooms + description: |- + Bindings to 'libcurl' for performing fully + configurable HTTP/FTP requests where responses can be processed in memory, on + disk, or streaming via the callback or connection interfaces. Some knowledge + of 'libcurl' is recommended; for a more-user-friendly web client see the + 'httr2' package which builds on this package with http specific tools and logic. + date_publication: '2025-02-19' + bug_reports: https://github.com/jeroen/curl/issues + url: https://jeroen.r-universe.dev/curl + url_cran: https://CRAN.R-project.org/package=curl + url_git: '' +currencyapi: + version: 0.1.0 + title: Client for the 'currencyapi.com' Currency Conversion API + maintainer: Dominik Kukacka + description: An R client for the 'currencyapi.com' currency conversion API. The + API requires registration of an API key. Basic features are free, some require + a paid subscription. You can find the full API documentation at + . + date_publication: '2023-05-08' + bug_reports: '' + url: https://currencyapi.com + url_cran: https://CRAN.R-project.org/package=currencyapi + url_git: '' +currentSurvival: + version: '1.1' + title: Estimation of CCI and CLFS Functions + maintainer: Eva Koritakova + description: |- + The currentSurvival package contains functions for + the estimation of the current cumulative incidence (CCI) and + the current leukaemia-free survival (CLFS). The CCI is the + probability that a patient is alive and in any disease + remission (e.g. complete cytogenetic remission in chronic + myeloid leukaemia) after initiating his or her therapy (e.g. + tyrosine kinase therapy for chronic myeloid leukaemia). The + CLFS is the probability that a patient is alive and in any + disease remission after achieving the first disease remission. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=currentSurvival + url_git: '' +CurricularAnalytics: + version: 1.0.0 + title: Exploring and Analyzing Academic Curricula + maintainer: Daniel Krasnov + description: Provides an implementation of ‘Curricular Analytics’, a framework for + analyzing and quantifying the complexity of academic curricula. Curricula are + modelled as directed acyclic graphs and analytics are provided based on path lengths + and edge density. This work directly comes from Heileman et al. (2018) . + date_publication: '2024-05-29' + bug_reports: https://github.com/Danyulll/CurricularAnalytics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CurricularAnalytics + url_git: https://github.com/Danyulll/CurricularAnalytics +currr: + version: 0.1.2 + title: Apply Mapping Functions in Frequent Saving + maintainer: Marcell Granat + description: Implementations of the family of map() functions with frequent saving + of the intermediate results. The contained functions let you start the evaluation + of the iterations where you stopped (reading the already evaluated ones from + cache), and work with the currently evaluated iterations while remaining ones + are running in a background job. Parallel computing is also easier with the workers + parameter. + date_publication: '2023-02-17' + bug_reports: https://github.com/MarcellGranat/currr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=currr + url_git: https://github.com/MarcellGranat/currr +curry: + version: 0.1.1 + title: Partial Function Application with %<%, %-<%, and %><% + maintainer: Thomas Lin Pedersen + description: |- + Partial application is the process of reducing the arity of a + function by fixing one or more arguments, thus creating a new function + lacking the fixed arguments. The curry package provides three different ways + of performing partial function application by fixing arguments from either + end of the argument list (currying and tail currying) or by fixing multiple + named arguments (partial application). This package provides this + functionality through the %<%, %-<%, and %><% operators which allows for + a programming style comparable to modern functional languages. Compared + to other implementations such a purrr::partial() the operators in curry + composes functions with named arguments, aiding in autocomplete etc. + date_publication: '2016-09-28' + bug_reports: https://github.com/thomasp85/curry/issues + url: '' + url_cran: https://CRAN.R-project.org/package=curry + url_git: https://github.com/thomasp85/curry +cursr: + version: 0.1.0 + title: Cursor and Terminal Manipulation + maintainer: Chris Mann + description: |- + A toolbox for developing applications, games, simulations, or + agent-based models in the R terminal. Included functions allow users to move the + cursor around the terminal screen, change text colors and attributes, clear the + screen, hide and show the cursor, map key presses to functions, draw shapes and curves, + among others. Most functionalities require users to be in a terminal (not the R GUI). + date_publication: '2021-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cursr + url_git: '' +curstatCI: + version: 0.1.1 + title: Confidence Intervals for the Current Status Model + maintainer: Kim Hendrickx + description: |- + Computes the maximum likelihood estimator, the smoothed maximum likelihood + estimator and pointwise bootstrap confidence intervals for the distribution + function under current status data. + Groeneboom and Hendrickx (2017) . + date_publication: '2017-10-12' + bug_reports: https://github.com/kimhendrickx/curstatCI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=curstatCI + url_git: https://github.com/kimhendrickx/curstatCI +curtailment: + version: 0.2.6 + title: Finds Binary Outcome Designs Using Stochastic Curtailment + maintainer: Martin Law + description: 'Finds single- and two-arm designs using stochastic curtailment, as + described by Law et al. (2022) and Law et + al. (2021) respectively. Designs can be single-stage or + multi-stage. Non-stochastic curtailment is possible as a special case. Desired + error-rates, maximum sample size and lower and upper anticipated response rates + are inputted and suitable designs are returned with operating characteristics. + Stopping boundaries and visualisations are also available. The package can find + designs using other approaches, for example designs by Simon (1989) + and Mander and Thompson (2010) . Other features: + compare and visualise designs using a weighted sum of expected sample sizes under + the null and alternative hypotheses and maximum sample size; visualise any binary + outcome design.' + date_publication: '2023-10-25' + bug_reports: https://github.com/martinlaw/curtailment/issues + url: '' + url_cran: https://CRAN.R-project.org/package=curtailment + url_git: https://github.com/martinlaw/curtailment +curvecomp: + version: 0.1.0 + title: Multiple Curve Comparisons Using Parametric Bootstrap + maintainer: Christopher Murphy + description: Performs multiple comparison procedures on curve observations among + different treatment groups. The methods are applicable in a variety of situations + (such as independent groups with equal or unequal sample sizes, or repeated measures) + by using parametric bootstrap. References to these procedures can be found at + Konietschke, Gel, and Brunner (2014) and Westfall + (2011) . + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=curvecomp + url_git: '' +curveDepth: + version: 0.1.0.9 + title: Tukey Curve Depth and Distance in the Space of Curves + maintainer: Pavlo Mozharovskyi + description: |- + Data recorded as paths or trajectories may be suitably described + by curves, which are independent of their parametrization. For the space of + such curves, the package provides functionalities for reading curves, sampling + points on curves, calculating distance between curves and for computing Tukey + curve depth of a curve w.r.t. to a bundle of curves. For details see + Lafaye De Micheaux, Mozharovskyi, and Vimond (2019) . + date_publication: '2019-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=curveDepth + url_git: '' +curvHDR: + version: 1.2-2 + title: Filtering of Flow Cytometry Samples + maintainer: Matt Wand + description: |- + Filtering, also known as gating, of flow cytometry samples using + the curvHDR method, which is described in Naumann, U., Luta, G. and + Wand, M.P. (2010) . + date_publication: '2023-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=curvHDR + url_git: '' +curvir: + version: 0.1.1 + title: Specify Reserve Demand Curves + maintainer: Nikolaos Kourentzes + description: Automatic specification and estimation of reserve demand curves for + central bank operations. The package can help to choose the best demand curve + and identify additional explanatory variables. Various plot and predict options + are included. For more details, see Chen et al. (2023) . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=curvir + url_git: '' +cusp: + version: 2.3.8 + title: Cusp-Catastrophe Model Fitting Using Maximum Likelihood + maintainer: Raoul P. P. P. Grasman + description: |- + Cobb's maximum likelihood method for cusp-catastrophe modeling + (Grasman, van der Maas, and Wagenmakers (2009) ; + Cobb (1981), Behavioral Science, 26(1), 75-78). Includes a cusp() function for model + fitting, and several utility functions for plotting, and for comparing the + model to linear regression and logistic curve models. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cusp + url_git: '' +custom.gauss.quad: + version: 1.0.0 + title: Custom Made Gauss Quadrature Nodes and Weights + maintainer: Paul Kabaila + description: |2- + + Use the high-precision arithmetic provided by the R package 'Rmpfr' + to compute a custom-made Gauss quadrature nodes and weights, + with up to 33 nodes, using a moment-based method via moment + determinants. Paul Kabaila (2022) . + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=custom.gauss.quad + url_git: '' +CustomDerivative: + version: 0.1.1 + title: Pricing Various Types of Custom Derivatives + maintainer: Amit Kumar Jha + description: A versatile R package for creating and pricing custom derivatives to + suit your financial needs. + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CustomDerivative + url_git: '' +CustomerScoringMetrics: + version: 1.0.0 + title: |- + Evaluation Metrics for Customer Scoring Models Depending on + Binary Classifiers + maintainer: Koen W. De Bock + description: 'Functions for evaluating and visualizing predictive model performance + (specifically: binary classifiers) in the field of customer scoring. These metrics + include lift, lift index, gain percentage, top-decile lift, F1-score, expected + misclassification cost and absolute misclassification cost. See Berry & Linoff + (2004, ISBN:0-471-47064-3), Witten and Frank (2005, 0-12-088407-0) and Blattberg, + Kim & Neslin (2008, ISBN:978–0–387–72578–9) for details. Visualization functions + are included for lift charts and gain percentage charts. All metrics that require + class predictions offer the possibility to dynamically determine cutoff values + for transforming real-valued probability predictions into class predictions.' + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CustomerScoringMetrics + url_git: '' +customiser: + version: 0.1.1 + title: Use R Markdown to Write your "Rprofile" + maintainer: James Laird-Smith + description: |- + A simple way to write ".Rprofile" code in an R Markdown file and + have it knit to the correct location for your operating system. + date_publication: '2024-07-08' + bug_reports: https://github.com/jameslairdsmith/customiser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=customiser + url_git: https://github.com/jameslairdsmith/customiser +customizedTraining: + version: '1.3' + title: |- + Customized Training for Lasso and Elastic-Net Regularized + Generalized Linear Models + maintainer: Scott Powers + description: |- + Customized training is a simple technique for transductive + learning, when the test covariates are known at the time of training. The + method identifies a subset of the training set to serve as the training set + for each of a few identified subsets in the training set. This package + implements customized training for the glmnet() and cv.glmnet() functions. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=customizedTraining + url_git: '' +CustosAscensor: + version: 0.1.0 + title: Costs Allocation for the Installation of an Elevator + maintainer: Iago Montero Nunez + description: Calculate the distribution of costs for the installation of an elevator + based on the different distribution rules. + date_publication: '2020-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CustosAscensor + url_git: '' +cusum: + version: 0.4.1 + title: |- + Cumulative Sum (CUSUM) Charts for Monitoring of Hospital + Performance + maintainer: Lena Hubig + description: |- + Provides functions for constructing and evaluating + CUSUM charts and RA-CUSUM charts with focus on false signal probability. + date_publication: '2019-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cusum + url_git: '' +cusumcharter: + version: 0.1.0 + title: Easier CUSUM Control Charts + maintainer: John MacKintosh + description: |- + Create CUSUM (cumulative sum) statistics from a vector or dataframe. + Also create single or faceted CUSUM control charts, with or without control limits. + Accepts vector, dataframe, tibble or data.table inputs. + date_publication: '2021-11-15' + bug_reports: https://github.com/johnmackintosh/cusumcharter/issues + url: https://johnmackintosh.github.io/cusumcharter/ + url_cran: https://CRAN.R-project.org/package=cusumcharter + url_git: https://github.com/johnmackintosh/cusumcharter +CUSUMdesign: + version: 1.1.5 + title: |- + Compute Decision Interval and Average Run Length for CUSUM + Charts + maintainer: Boxiang Wang + description: 'Computation of decision intervals (H) and average run lengths (ARL) + for CUSUM charts. Details of the method are seen in Hawkins and Olwell (2012): + Cumulative sum charts and charting for quality improvement, Springer Science & + Business Media.' + date_publication: '2020-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CUSUMdesign + url_git: '' +cutoff: + version: '1.3' + title: Seek the Significant Cutoff Value + maintainer: Jing Zhang + description: |- + Seek the significant cutoff value for a continuous variable, which will + be transformed into a classification, for linear regression, + logistic regression, logrank analysis and cox regression. First of all, + all combinations will be gotten by combn() function. Then n.per argument, + abbreviated of total number percentage, will be used to remove the combination + of smaller data group. In logistic, Cox regression and logrank analysis, + we will also use p.per argument, patient percentage, to filter the lower + proportion of patients in each group. Finally, p value in regression + results will be used to get the significant combinations and output + relevant parameters. In this package, there is no limit to the number of + cutoff points, which can be 1, 2, 3 or more. Still, we provide 2 methods, + typical Bonferroni and Duglas G (1994) , to + adjust the p value, Missing values will be deleted by na.omit() function + before analysis. + date_publication: '2019-12-20' + bug_reports: https://github.com/yikeshu0611/cutoff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cutoff + url_git: https://github.com/yikeshu0611/cutoff +CUtools: + version: 0.1.0 + title: Clinical Utility Tools to Analyze a Predictive Model + maintainer: Luis Mariano Esteban + description: Package to analyze the clinical utility of a biomarker. It provides + the clinical utility curve, clinical utility table, efficacy of a biomarker, clinical + efficacy curve and tests to compare efficacy between markers. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CUtools + url_git: '' +cutpointr: + version: 1.2.0 + title: |- + Determine and Evaluate Optimal Cutpoints in Binary + Classification Tasks + maintainer: Christian Thiele + description: |- + Estimate cutpoints that optimize a specified metric in binary classification tasks + and validate performance using bootstrapping. Some methods for more robust cutpoint + estimation are supported, e.g. a parametric method assuming normal distributions, + bootstrapped cutpoints, and smoothing of the metric values per cutpoint using + Generalized Additive Models. Various plotting functions are included. For an overview + of the package see Thiele and Hirschfeld (2021) . + date_publication: '2024-12-10' + bug_reports: https://github.com/thie1e/cutpointr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cutpointr + url_git: https://github.com/thie1e/cutpointr +CutpointsOEHR: + version: 0.1.2 + title: |- + Optimal Equal-HR Method to Find Two Cutpoints for U-Shaped + Relationships in Cox Model + maintainer: Yimin Chen + description: Use optimal equal-HR method to determine two optimal cutpoints of a + continuous predictor that has a U-shaped relationship with survival outcomes based + on Cox regression model. The optimal equal-HR method estimates two optimal cut-points + that have approximately the same log hazard value based on Cox regression model + and divides individuals into different groups according to their HR values. + date_publication: '2018-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CutpointsOEHR + url_git: '' +cv: + version: 2.0.3 + title: Cross-Validating Regression Models + maintainer: Georges Monette + description: |- + Cross-validation methods of regression models that exploit features of various + modeling functions to improve speed. Some of the methods implemented in the package are + novel, as described in the package vignettes; for general introductions to cross-validation, + see, for example, Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani + (2021, ISBN 978-1-0716-1417-4, Secs. 5.1, 5.3), "An Introduction to Statistical Learning with + Applications in R, Second Edition", and Trevor Hastie, Robert Tibshirani, + and Jerome Friedman (2009, ISBN 978-0-387-84857-0, Sec. 7.10), "The Elements of Statistical + Learning, Second Edition". + date_publication: '2024-09-22' + bug_reports: https://github.com/gmonette/cv/issues + url: https://gmonette.github.io/cv/ + url_cran: https://CRAN.R-project.org/package=cv + url_git: '' +cvap: + version: 0.1.5 + title: Citizen Voting Age Population + maintainer: Christopher T. Kenny + description: Works with the Citizen Voting Age Population special tabulation from + the US Census Bureau . + Provides tools to download and process raw data. Also provides a downloading interface + to processed data. Implements a very basic approach to estimate block level citizen + voting age population from block group data. + date_publication: '2024-03-21' + bug_reports: https://github.com/christopherkenny/cvap/issues + url: https://christophertkenny.com/cvap/ + url_cran: https://CRAN.R-project.org/package=cvap + url_git: https://github.com/christopherkenny/cvap +cvar: + version: '0.5' + title: |- + Compute Expected Shortfall and Value at Risk for Continuous + Distributions + maintainer: Georgi N. Boshnakov + description: |- + Compute expected shortfall (ES) and Value at Risk (VaR) from a + quantile function, distribution function, random number generator or + probability density function. ES is also known as Conditional Value at + Risk (CVaR). Virtually any continuous distribution can be specified. + The functions are vectorized over the arguments. The computations are + done directly from the definitions, see e.g. Acerbi and Tasche (2002) + . Some support for GARCH models is provided, + as well. + date_publication: '2022-11-03' + bug_reports: https://github.com/GeoBosh/cvar/issues + url: https://geobosh.github.io/cvar/(doc) + url_cran: https://CRAN.R-project.org/package=cvar + url_git: https://github.com/GeoBosh/cvar(devel) +cvasi: + version: 1.4.0 + title: Calibration, Validation, and Simulation of TKTD Models + maintainer: Nils Kehrein + description: |- + Eases the use of ecotoxicological effect models. Can simulate + common toxicokinetic-toxicodynamic (TK/TD) models such as + General Unified Threshold models of Survival (GUTS) and Lemna. It can + derive effects and effect profiles (EPx) from scenarios. It supports the + use of 'tidyr' workflows employing the pipe symbol. Time-consuming + tasks can be parallelized. + date_publication: '2025-02-28' + bug_reports: https://github.com/cvasi-tktd/cvasi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cvasi + url_git: https://github.com/cvasi-tktd/cvasi +cvAUC: + version: 1.1.4 + title: Cross-Validated Area Under the ROC Curve Confidence Intervals + maintainer: Erin LeDell + description: Tools for working with and evaluating cross-validated area under the + ROC curve (AUC) estimators. The primary functions of the package are ci.cvAUC + and ci.pooled.cvAUC, which report cross-validated AUC and compute confidence intervals + for cross-validated AUC estimates based on influence curves for i.i.d. and pooled + repeated measures data, respectively. One benefit to using influence curve based + confidence intervals is that they require much less computation time than bootstrapping + methods. The utility functions, AUC and cvAUC, are simple wrappers for functions + from the ROCR package. + date_publication: '2022-01-17' + bug_reports: https://github.com/ledell/cvAUC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cvAUC + url_git: https://github.com/ledell/cvAUC +cvCovEst: + version: 1.2.2 + title: Cross-Validated Covariance Matrix Estimation + maintainer: Philippe Boileau + description: |- + An efficient cross-validated approach for covariance matrix + estimation, particularly useful in high-dimensional settings. This + method relies upon the theory of high-dimensional loss-based covariance + matrix estimator selection developed by Boileau et al. (2022) + to identify the optimal estimator + from among a prespecified set of candidates. + date_publication: '2024-02-17' + bug_reports: https://github.com/PhilBoileau/cvCovEst/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cvCovEst + url_git: https://github.com/PhilBoileau/cvCovEst +cvcrand: + version: 0.1.1 + title: Efficient Design and Analysis of Cluster Randomized Trials + maintainer: Hengshi Yu + description: |- + Constrained randomization by Raab and Butcher (2001) + is suitable for cluster randomized trials (CRTs) with a + small number of clusters (e.g., 20 or fewer). The procedure of + constrained randomization is based on the baseline values of some + cluster-level covariates specified. The intervention effect on + the individual outcome can then be analyzed through + clustered permutation test introduced by Gail, et al. (1996) . + Motivated from Li, et al. (2016) , the package performs constrained randomization on the baseline + values of cluster-level covariates and clustered permutation test on the individual-level outcomes for cluster randomized trials. + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvcrand + url_git: '' +CVD: + version: 1.0.2 + title: Color Vision Deficiencies + maintainer: Jose Gama + description: Methods for color vision deficiencies (CVD), to help understanding + and mitigating issues with CVDs and to generate tests for diagnosis and interpretation. + date_publication: '2016-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CVD + url_git: '' +cvdprevent: + version: 0.2.1 + title: Wrapper for the 'CVD Prevent' Application Programming Interface + maintainer: Craig Parylo + description: |- + Provides an R wrapper to the 'CVD Prevent' application + programming interface (API). Users can make API requests through + built-in R functions. The Cardiovascular Disease Prevention Audit + (CVDPREVENT) is an England-wide primary care audit that automatically + extracts routinely held GP health data. + . + date_publication: '2025-02-01' + bug_reports: https://github.com/craig-parylo/cvdprevent/issues + url: https://craig-parylo.github.io/cvdprevent/ + url_cran: https://CRAN.R-project.org/package=cvdprevent + url_git: https://github.com/craig-parylo/cvdprevent +cvequality: + version: 0.2.0 + title: |- + Tests for the Equality of Coefficients of Variation from + Multiple Groups + maintainer: Ben Marwick + description: Contains functions for testing for significant differences between + multiple coefficients of variation. Includes Feltz and Miller's (1996) + asymptotic test and Krishnamoorthy and Lee's (2014) + modified signed-likelihood ratio test. See the vignette for more, including full + details of citations. + date_publication: '2019-01-07' + bug_reports: https://github.com/benmarwick/cvequality/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cvequality + url_git: https://github.com/benmarwick/cvequality +cvGEE: + version: 0.3-0 + title: Cross-Validated Predictions from GEE + maintainer: Dimitris Rizopoulos + description: Calculates predictions from generalized estimating equations and internally + cross-validates them using the logarithmic, quadratic and spherical proper scoring + rules; Kung-Yee Liang and Scott L. Zeger (1986) . + date_publication: '2019-07-23' + bug_reports: https://github.com/drizopoulos/cvGEE/issues + url: https://drizopoulos.github.io/cvGEE/ + url_cran: https://CRAN.R-project.org/package=cvGEE + url_git: https://github.com/drizopoulos/cvGEE +CVglasso: + version: '1.0' + title: Lasso Penalized Precision Matrix Estimation + maintainer: Matt Galloway + description: |- + Estimates a lasso penalized precision matrix via the blockwise coordinate descent (BCD). This package is a simple wrapper around the popular 'glasso' package that extends and enhances its capabilities. These enhancements include built-in cross validation and visualizations. + See Friedman et al (2008) for details regarding the estimation method. + date_publication: '2018-06-04' + bug_reports: https://github.com/MGallow/CVglasso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CVglasso + url_git: https://github.com/MGallow/CVglasso +cvLM: + version: 1.0.4 + title: Cross-Validation for Linear & Ridge Regression Models + maintainer: Philip Nye + description: 'Efficient implementations of cross-validation techniques for linear + and ridge regression models, leveraging ''C++'' code with ''Rcpp'', ''RcppParallel'', + and ''Eigen'' libraries. It supports leave-one-out, generalized, and K-fold cross-validation + methods, utilizing ''Eigen'' matrices for high performance. Methodology references: + Hastie, Tibshirani, and Friedman (2009) .' + date_publication: '2024-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvLM + url_git: '' +cvmaPLFAM: + version: 0.1.0 + title: |- + Cross-Validation Model Averaging for Partial Linear Functional + Additive Models + maintainer: Shishi Liu + description: |- + Produce an averaging estimate/prediction by combining all candidate models for partial linear functional additive models, + using multi-fold cross-validation criterion. More details can be referred to Shishi Liu and Jingxiao Zhang. (2021) . + date_publication: '2023-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvmaPLFAM + url_git: '' +cvmdisc: + version: 0.1.0 + title: Cramer von Mises Tests for Discrete or Grouped Distributions + maintainer: Shaun Zheng Sun + description: Implements Cramer-von Mises Statistics for testing fit to (1) fully + specified discrete distributions as described in Choulakian, Lockhart and Stephens + (1994) (2) discrete distributions with unknown parameters + that must be estimated from the sample data, see Spinelli & Stephens (1997) + and Lockhart, Spinelli and Stephens (2007) (3) grouped + continuous distributions with Unknown Parameters, see Spinelli (2001) . + Maximum likelihood estimation (MLE) is used to estimate the parameters. The package + computes the Cramer-von Mises Statistics, Anderson-Darling Statistics and the + Watson-Stephens Statistics and their p-values. + date_publication: '2019-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvmdisc + url_git: '' +cvmgof: + version: 1.0.3 + title: Cramer-von Mises Goodness-of-Fit Tests + maintainer: Romain Azais + description: |- + It is devoted to Cramer-von Mises goodness-of-fit tests. + It implements three statistical methods based on Cramer-von Mises statistics to estimate and test a regression model. + date_publication: '2021-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvmgof + url_git: '' +CvmortalityMult: + version: 1.0.9 + title: Cross-Validation for Multi-Population Mortality Models + maintainer: David Atance + description: |- + Implementation of cross-validation method for testing the forecasting accuracy of several multi-population mortality models. The family of multi-population includes several multi-population mortality models proposed through the actuarial and demography literature. The package includes functions for fitting and forecast the mortality rates of several populations. Additionally, we include functions for testing the forecasting accuracy of different multi-population models. + References. + Atance, D., Debon, A., and Navarro, E. (2020) . + Bergmeir, C. & Benitez, J.M. (2012) . + Debon, A., Montes, F., & Martinez-Ruiz, F. (2011) . + Lee, R.D. & Carter, L.R. (1992) . + Russolillo, M., Giordano, G., & Haberman, S. (2011) . + Santolino, M. (2023) . + date_publication: '2025-02-13' + bug_reports: https://github.com/davidAtance/CvmortalityMult/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CvmortalityMult + url_git: https://github.com/davidAtance/CvmortalityMult +cvms: + version: 1.6.3 + title: Cross-Validation for Model Selection + maintainer: Ludvig Renbo Olsen + description: |- + Cross-validate one or multiple regression and classification models + and get relevant evaluation metrics in a tidy format. Validate the + best model on a test set and compare it to a baseline evaluation. + Alternatively, evaluate predictions from an external model. Currently + supports regression and classification (binary and multiclass). + Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R., + & Wambugu M. (2019, ISBN: 9781838550134). + date_publication: '2025-01-14' + bug_reports: https://github.com/ludvigolsen/cvms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cvms + url_git: https://github.com/ludvigolsen/cvms +CVR: + version: 0.1.1 + title: Canonical Variate Regression + maintainer: Chongliang Luo + description: |- + Perform canonical variate regression (CVR) for two sets of covariates and a univariate + response, with regularization and weight parameters tuned by cross validation. + date_publication: '2017-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CVR + url_git: '' +CVrisk: + version: 1.1.1 + title: Compute Risk Scores for Cardiovascular Diseases + maintainer: Victor Castro + description: |- + Calculate various cardiovascular disease risk scores from the + Framingham Heart Study (FHS), the American College of Cardiology (ACC), + and the American Heart Association (AHA) as described in D’agostino, et al + (2008) , Goff, et al (2013) + , and Mclelland, et al (2015) + . + date_publication: '2023-08-19' + bug_reports: https://github.com/vcastro/CVrisk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CVrisk + url_git: https://github.com/vcastro/CVrisk +cvsem: + version: 1.0.0 + title: SEM Model Comparison with K-Fold Cross-Validation + maintainer: Anna Wysocki + description: The goal of 'cvsem' is to provide functions that allow for comparing + Structural Equation Models (SEM) using cross-validation. Users can specify multiple + SEMs using 'lavaan' syntax. 'cvsem' computes the Kullback Leibler (KL) Divergence + between 1) the model implied covariance matrix estimated from the training data + and 2) the sample covariance matrix estimated from the test data described in + Cudeck, Robert & Browne (1983) . The KL Divergence + is computed for each of the specified SEMs allowing for the models to be compared + based on their prediction errors. + date_publication: '2022-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvsem + url_git: '' +CVST: + version: 0.2-3 + title: Fast Cross-Validation via Sequential Testing + maintainer: Tammo Krueger + description: The fast cross-validation via sequential testing (CVST) procedure is + an improved cross-validation procedure which uses non-parametric testing coupled + with sequential analysis to determine the best parameter set on linearly increasing + subsets of the data. By eliminating under-performing candidates quickly and keeping + promising candidates as long as possible, the method speeds up the computation + while preserving the capability of a full cross-validation. Additionally to the + CVST the package contains an implementation of the ordinary k-fold cross-validation + with a flexible and powerful set of helper objects and methods to handle the overall + model selection process. The implementations of the Cochran's Q test with permutations + and the sequential testing framework of Wald are generic and can therefore also + be used in other contexts. + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CVST + url_git: '' +CVThresh: + version: 1.1.2 + title: Level-Dependent Cross-Validation Thresholding + maintainer: Donghoh Kim + description: |- + The level-dependent cross-validation method is implemented + for the selection of thresholding + value in wavelet shrinkage. This procedure is implemented + by coupling a conventional cross validation with an + imputation method due to a limitation of data length, + a power of 2. It can be easily applied to classical + leave-one-out and k-fold cross validation. + Since the procedure is computationally fast, + a level-dependent cross validation can be performed for + wavelet shrinkage of various data such as a data + with correlated errors. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CVThresh + url_git: '' +cvTools: + version: 0.3.3 + title: Cross-Validation Tools for Regression Models + maintainer: Andreas Alfons + description: |- + Tools that allow developers to write functions for + cross-validation with minimal programming effort and assist + users with model selection. + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvTools + url_git: '' +cvwrapr: + version: '1.0' + title: Tools for Cross Validation + maintainer: Kenneth Tay + description: |- + Tools for performing cross-validation (CV). The main function is a + general purpose wrapper that performs k-fold CV for any tuning parameter in + any supervised learning method. The package also has a function that + computes the loss incurred by a set of predictions for a variety of loss + functions and model families. + date_publication: '2021-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cvwrapr + url_git: '' +CVXR: + version: 1.0-15 + title: Disciplined Convex Optimization + maintainer: Anqi Fu + description: |- + An object-oriented modeling language for disciplined + convex programming (DCP) as described in Fu, Narasimhan, and Boyd + (2020, ). It allows the user to + formulate convex optimization problems in a natural way following + mathematical convention and DCP rules. The system analyzes the + problem, verifies its convexity, converts it into a canonical + form, and hands it off to an appropriate solver to obtain the + solution. Interfaces to solvers on CRAN and elsewhere are + provided, both commercial and open source. + date_publication: '2024-11-07' + bug_reports: https://github.com/cvxgrp/CVXR/issues + url: https://cvxr.rbind.io + url_cran: https://CRAN.R-project.org/package=CVXR + url_git: '' +cwot: + version: 0.1.0 + title: Cauchy Weighted Joint Test for Pharmacogenetics Analysis + maintainer: Hong Zhang + description: A flexible and robust joint test of the single nucleotide polymorphism + (SNP) main effect and genotype-by-treatment interaction effect for continuous + and binary endpoints. Two analytic procedures, Cauchy weighted joint test (CWOT) + and adaptively weighted joint test (AWOT), are proposed to accurately calculate + the joint test p-value. The proposed methods are evaluated through extensive simulations + under various scenarios. The results show that the proposed AWOT and CWOT control + type I error well and outperform existing methods in detecting the most interesting + signal patterns in pharmacogenetics (PGx) association studies. For reference, + see Hong Zhang, Devan Mehrotra and Judong Shen (2022) . + date_publication: '2022-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cwot + url_git: '' +CWT: + version: 0.2.1 + title: Continuous Wavelet Transformation for Spectroscopy + maintainer: J. Antonio Guzmán Q. + description: |- + Fast application of Continuous Wavelet Transformation ('CWT') on time + series with special attention to spectroscopy. It is written using + data.table and 'C++' language and in some functions it is possible to + use parallel processing to speed-up the computation over samples. Currently, + only the second derivative of a Gaussian wavelet function is implemented. + date_publication: '2024-06-28' + bug_reports: https://github.com/Antguz/CWT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=CWT + url_git: https://github.com/Antguz/CWT +cxhull: + version: 0.7.4 + title: Convex Hull + maintainer: Stéphane Laurent + description: |- + Computes the convex hull in arbitrary dimension, based on the + Qhull library (). The package provides a + complete description of the convex hull: edges, ridges, facets, + adjacencies. Triangulation is optional. + date_publication: '2023-10-24' + bug_reports: https://github.com/stla/cxhull/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cxhull + url_git: https://github.com/stla/cxhull +cxr: + version: 1.1.1 + title: A Toolbox for Modelling Species Coexistence in R + maintainer: David Garcia-Callejas + description: |- + Recent developments in modern coexistence theory have + advanced our understanding on how species are able to persist and + co-occur with other species at varying abundances. However, applying + this mathematical framework to empirical data is still challenging, + precluding a larger adoption of the theoretical tools developed by + empiricists. This package provides a complete toolbox for modelling + interaction effects between species, and calculate fitness and niche + differences. The functions are flexible, may accept covariates, and + different fitting algorithms can be used. A full description of the + underlying methods is available in García-Callejas, D., Godoy, O., and + Bartomeus, I. (2020) . Furthermore, the + package provides a series of functions to calculate dynamics for + stage-structured populations across sites. + date_publication: '2023-10-26' + bug_reports: https://github.com/RadicalCommEcol/cxr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cxr + url_git: https://github.com/RadicalCommEcol/cxr +cxxfunplus: + version: 1.0.2 + title: Extend 'cxxfunction' by Saving the Dynamic Shared Objects + maintainer: Jiqiang Guo + description: |- + Extend 'cxxfunction' by saving the dynamic shared objects + for reusing across R sessions. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cxxfunplus + url_git: https://github.com/maverickg/cxxfunplus +cyclestreets: + version: 1.0.3 + title: Cycle Routing and Data for Cycling Advocacy + maintainer: Robin Lovelace + description: |- + An interface to the cycle routing/data services provided by + 'CycleStreets', a not-for-profit social enterprise and advocacy + organisation. The application programming interfaces (APIs) provided + by 'CycleStreets' are documented at + (). The focus of this package is + the journey planning API, which aims to emulate the routes taken by a + knowledgeable cyclist. An innovative feature of the routing service + of its provision of fastest, quietest and balanced profiles. These + represent routes taken to minimise time, avoid traffic and compromise + between the two, respectively. + date_publication: '2024-12-04' + bug_reports: https://github.com/cyclestreets/cyclestreets-r/issues + url: https://rpackage.cyclestreets.net/ + url_cran: https://CRAN.R-project.org/package=cyclestreets + url_git: https://github.com/cyclestreets/cyclestreets-r +cyclocomp: + version: 1.1.1 + title: Cyclomatic Complexity of R Code + maintainer: Gabor Csardi + description: |- + Cyclomatic complexity is a software metric (measurement), + used to indicate the complexity of a program. It is a quantitative + measure of the number of linearly independent paths through a program's + source code. It was developed by Thomas J. McCabe, Sr. in 1976. + date_publication: '2023-08-30' + bug_reports: https://github.com/gaborcsardi/cyclocomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cyclocomp + url_git: https://github.com/gaborcsardi/cyclocomp +cycloids: + version: 1.0.2 + title: |- + Tools for Calculating Hypocycloids, Epicycloids, Hypotrochoids, + and Epitrochoids + maintainer: Peter Biber + description: |- + Tools for calculating coordinate representations of + hypocycloids, epicyloids, hypotrochoids, and epitrochoids + (altogether called 'cycloids' here) with different scaling + and positioning options. The cycloids can be visualised with + any appropriate graphics function in R. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cycloids + url_git: '' +cyclomort: + version: 1.0.2 + title: Survival Modeling with a Periodic Hazard Function + maintainer: Eliezer Gurarie + description: Modeling periodic mortality (or other time-to event) processes from + right-censored data. Given observations of a process with a known period (e.g. + 365 days, 24 hours), functions determine the number, intensity, timing, and duration + of peaks of periods of elevated hazard within a period. The underlying model + is a mixed wrapped Cauchy function fitted using maximum likelihoods (details in + Gurarie et al. (2020) ). The development of these + tools was motivated by the strongly seasonal mortality patterns observed in many + wild animal populations, such that the respective periods of higher mortality + can be identified as "mortality seasons". + date_publication: '2020-08-20' + bug_reports: https://github.com/EliGurarie/cyclomort/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cyclomort + url_git: https://github.com/EliGurarie/cyclomort +Cyclops: + version: 3.5.0 + title: |- + Cyclic Coordinate Descent for Logistic, Poisson and Survival + Analysis + maintainer: Marc A. Suchard + description: |- + This model fitting tool incorporates cyclic coordinate descent and + majorization-minimization approaches to fit a variety of regression models + found in large-scale observational healthcare data. Implementations focus + on computational optimization and fine-scale parallelization to yield + efficient inference in massive datasets. Please see: + Suchard, Simpson, Zorych, Ryan and Madigan (2013) . + date_publication: '2024-12-02' + bug_reports: https://github.com/ohdsi/cyclops/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Cyclops + url_git: https://github.com/ohdsi/cyclops +cyclotomic: + version: 1.3.0 + title: The Field of Cyclotomic Numbers + maintainer: Stéphane Laurent + description: |- + The cyclotomic numbers are complex numbers that can be + thought of as the rational numbers extended with the roots of unity. They + are represented exactly, enabling exact computations. They contain the + Gaussian rationals (complex numbers with rational real and imaginary + parts) as well as the square roots of all rational numbers. They also + contain the sine and cosine of all rational multiples of pi. The + algorithms implemented in this package are taken from the 'Haskell' + package 'cyclotomic', whose algorithms are adapted from code by Martin + Schoenert and Thomas Breuer in the 'GAP' project + (). Cyclotomic numbers have applications in + number theory, algebraic geometry, algebraic number theory, coding + theory, and in the theory of graphs and combinatorics. They have + connections to the theory of modular functions and modular curves. + date_publication: '2023-11-02' + bug_reports: https://github.com/stla/cyclotomic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cyclotomic + url_git: https://github.com/stla/cyclotomic +cyjShiny: + version: 1.0.42 + title: Cytoscape.js Shiny Widget (cyjShiny) + maintainer: Augustin Luna + description: Wraps cytoscape.js as a shiny widget. cytoscape.js + is a Javascript-based graph theory (network) library for visualization and analysis. + This package supports the visualization of networks with custom visual styles + and several available layouts. Demo Shiny applications are provided in the package + code. + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cyjShiny + url_git: '' +cylcop: + version: 0.2.0 + title: Circular-Linear Copulas with Angular Symmetry for Movement Data + maintainer: Florian Hodel + description: |- + Classes (S4) of circular-linear, symmetric copulas with corresponding + methods, extending the 'copula' package. These copulas are especially useful + for modeling correlation in discrete-time movement data. Methods for density, + (conditional) distribution, random number generation, bivariate dependence + measures and fitting parameters using maximum likelihood and other + approaches. The package also contains methods for visualizing movement data + and copulas. + date_publication: '2022-10-29' + bug_reports: https://github.com/r-lib/devtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cylcop + url_git: https://github.com/r-lib/devtools +cymruservices: + version: 0.5.0 + title: |- + Query 'Team Cymru' 'IP' Address, Autonomous System Number + ('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware' + Hash Data Services + maintainer: Bob Rudis + description: |- + A toolkit for querying 'Team Cymru' 'IP' + address, Autonomous System Number ('ASN'), Border Gateway Protocol ('BGP'), Bogon + and 'Malware' Hash Data Services. + date_publication: '2018-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=cymruservices + url_git: '' +cyphr: + version: 1.1.7 + title: High Level Encryption Wrappers + maintainer: Rich FitzJohn + description: |- + Encryption wrappers, using low-level support from + 'sodium' and 'openssl'. 'cyphr' tries to smooth over some pain + points when using encryption within applications and data analysis + by wrapping around differences in function names and arguments in + different encryption providing packages. It also provides + high-level wrappers for input/output functions for seamlessly + adding encryption to existing analyses. + date_publication: '2025-02-07' + bug_reports: https://github.com/ropensci/cyphr/issues + url: https://docs.ropensci.org/cyphr/ + url_cran: https://CRAN.R-project.org/package=cyphr + url_git: https://github.com/ropensci/cyphr +cystiSim: + version: 0.1.0 + title: Agent-Based Model for Taenia_solium Transmission and Control + maintainer: Brecht Devleesschauwer + description: The cystiSim package provides an agent-based model for Taenia solium + transmission and control. cystiSim was developed within the framework of CYSTINET, + the European Network on taeniosis/cysticercosis, COST ACTION TD1302. + date_publication: '2016-05-15' + bug_reports: https://github.com/brechtdv/cystiSim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cystiSim + url_git: https://github.com/brechtdv/cystiSim +CytobankAPI: + version: 2.2.1 + title: Cytobank API Wrapper for R + maintainer: Stu Blair + description: |- + Tools to interface with Cytobank's API via R, organized by + endpoints that represent various areas of Cytobank functionality. Learn more + about Cytobank at . + date_publication: '2023-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=CytobankAPI + url_git: '' +cytofan: + version: 0.1.0 + title: Plot Fan Plots for Cytometry Data using 'ggplot2' + maintainer: Yann Abraham + description: |- + An implementation of Fan plots for cytometry data in 'ggplot2'. + For reference see Britton, E.; Fisher, P. & J. Whitley (1998) The Inflation Report Projections: Understanding the Fan Chart + ). + date_publication: '2018-07-30' + bug_reports: https://github.com/yannabraham/cytofan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cytofan + url_git: https://github.com/yannabraham/cytofan +cytometree: + version: 2.0.2 + title: Automated Cytometry Gating and Annotation + maintainer: Boris P Hejblum + description: |- + Given the hypothesis of a bi-modal distribution of cells for + each marker, the algorithm constructs a binary tree, the nodes of which are + subpopulations of cells. At each node, observed cells and markers are modeled + by both a family of normal distributions and a family of bi-modal normal mixture + distributions. Splitting is done according to a normalized difference of AIC + between the two families. Method is detailed in: Commenges, Alkhassim, Gottardo, + Hejblum & Thiebaut (2018) . + date_publication: '2019-12-04' + bug_reports: https://github.com/sistm/Cytometree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cytometree + url_git: '' +cytominer: + version: 0.2.2 + title: Methods for Image-Based Cell Profiling + maintainer: Shantanu Singh + description: |- + Typical morphological profiling datasets have millions of cells + and hundreds of features per cell. When working with this data, you must + clean the data, normalize the features to make them comparable across + experiments, transform the features, select features based on their + quality, and aggregate the single-cell data, if needed. 'cytominer' makes + these steps fast and easy. Methods used in practice in the field are + discussed in Caicedo (2017) . An overview of the + field is presented in Caicedo (2016) . + date_publication: '2020-05-09' + bug_reports: https://github.com/cytomining/cytominer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=cytominer + url_git: https://github.com/cytomining/cytominer +CytOpT: + version: 0.9.4 + title: |- + Optimal Transport for Gating Transfer in Cytometry Data with + Domain Adaptation + maintainer: Boris Hejblum + description: |- + Supervised learning from a source distribution (with known segmentation into cell sub-populations) + to fit a target distribution with unknown segmentation. It relies regularized optimal transport to directly + estimate the different cell population proportions from a biological sample characterized with flow cytometry + measurements. It is based on the regularized Wasserstein metric to compare cytometry measurements from + different samples, thus accounting for possible mis-alignment of a given cell population across sample + (due to technical variability from the technology of measurements). Supervised learning technique based + on the Wasserstein metric that is used to estimate an optimal re-weighting of class proportions in a + mixture model Details are presented in Freulon P, Bigot J and Hejblum BP (2021) . + date_publication: '2022-02-09' + bug_reports: '' + url: https://sistm.github.io/CytOpT-R/ + url_cran: https://CRAN.R-project.org/package=CytOpT + url_git: https://github.com/sistm/CytOpT-R/ +CytoSimplex: + version: 0.1.1 + title: |- + Simplex Visualization of Cell Fate Similarity in Single-Cell + Data + maintainer: Yichen Wang + description: |- + Create simplex plots to visualize the similarity between + single-cells and selected clusters in a 1-/2-/3-simplex space. + Velocity information can be added as an additional layer. + See Liu J, Wang Y et al (2023) for more details. + date_publication: '2023-12-15' + bug_reports: '' + url: https://welch-lab.github.io/CytoSimplex/ + url_cran: https://CRAN.R-project.org/package=CytoSimplex + url_git: https://github.com/welch-lab/CytoSimplex +czechrates: + version: 0.2.5 + title: Czech Interest & Foreign Exchange Rates + maintainer: Jindra Lacko + description: Interface to interest and foreign exchange rates published by the Czech + National Bank. + date_publication: '2024-05-06' + bug_reports: https://github.com/jla-data/czechrates/issues + url: '' + url_cran: https://CRAN.R-project.org/package=czechrates + url_git: https://github.com/jla-data/czechrates +czso: + version: 0.4.1 + title: Use Open Data from the Czech Statistical Office in R + maintainer: Petr Bouchal + description: |- + Get programmatic access to the open data provided by the + Czech Statistical Office (CZSO, ). + date_publication: '2024-07-20' + bug_reports: https://github.com/petrbouchal/czso/issues + url: https://petrbouchal.xyz/czso/ + url_cran: https://CRAN.R-project.org/package=czso + url_git: https://github.com/petrbouchal/czso +D2MCS: + version: 1.0.1 + title: Data Driving Multiple Classifier System + maintainer: Miguel Ferreiro-Díaz + description: |2- + + Provides a novel framework to able to automatically develop and deploy + an accurate Multiple Classifier System based on the feature-clustering + distribution achieved from an input dataset. 'D2MCS' was developed focused on + four main aspects: (i) the ability to determine an effective method to + evaluate the independence of features, (ii) the identification of the + optimal number of feature clusters, (iii) the training and tuning of ML + models and (iv) the execution of voting schemes to combine the outputs of + each classifier comprising the Multiple Classifier System. + date_publication: '2022-08-23' + bug_reports: https://github.com/drordas/D2MCS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=D2MCS + url_git: https://github.com/drordas/D2MCS +D3GB: + version: '2.0' + title: Interactive Genome Browser + maintainer: Carlos Prieto + description: Creates interactive genome browser. It joins the data analysis power + of 'R' and the visualization libraries of 'JavaScript' in one package. Barrios, + D. & Prieto, C. (2017) . + date_publication: '2024-05-30' + bug_reports: '' + url: http://d3gb.usal.es + url_cran: https://CRAN.R-project.org/package=D3GB + url_git: '' +D3mirt: + version: 2.0.4 + title: Descriptive 3D Multidimensional Item Response Theory Modelling + maintainer: Erik Forsberg + description: For identifying, estimating, and plotting descriptive multidimensional + item response theory models, restricted to 3D and dichotomous or polytomous data + that fit the two-parameter logistic model or the graded response model. The method + is foremost explorative and centered around the plot function that exposes item + characteristics and constructs, represented by vector arrows, located in a three-dimensional + interactive latent space. The results can be useful for item-level analysis as + well as test development. + date_publication: '2024-06-22' + bug_reports: https://github.com/ForsbergPyschometrics/D3mirt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=D3mirt + url_git: https://github.com/ForsbergPyschometrics/D3mirt +d3Network: + version: 0.5.2.1 + title: Tools for creating D3 JavaScript network, tree, dendrogram, andSankey + graphs from R + maintainer: Christopher Gandrud + description: 'This packages is intended to make it easy to create D3 JavaScriptnetwork, + tree, dendrogram, and Sankey graphs from R using data frames.!!! NOTE: + Active development has moved to the networkD3 package. !!!' + date_publication: '2015-01-31' + bug_reports: https://github.com/christophergandrud/d3Network/issues + url: http://christophergandrud.github.io/d3Network/ + url_cran: https://CRAN.R-project.org/package=d3Network + url_git: '' +D3partitionR: + version: 0.5.0 + title: Interactive Charts of Nested and Hierarchical Data with 'D3.js' + maintainer: Antoine Guillot + description: Builds interactive 'd3.js' hierarchical visualisation easily. D3partitionR + makes it easy to build and customize sunburst, circle treemap, treemap, partition + chart, ... + date_publication: '2017-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=D3partitionR + url_git: '' +d3plus: + version: 0.1.0 + title: Seamless 'D3Plus' Integration + maintainer: Mauricio Vargas + description: Provides functions that offer seamless 'D3Plus' integration. The examples + provided here are taken from the official 'D3Plus' website . + date_publication: '2017-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=d3plus + url_git: '' +d3po: + version: 0.5.5 + title: |- + Fast and Beautiful Interactive Visualization for 'Markdown' and + 'Shiny' + maintainer: Mauricio Vargas Sepulveda + description: |- + Apache licensed alternative to 'Highcharter' which provides + functions for both fast and beautiful interactive visualization for 'Markdown' + and 'Shiny'. + date_publication: '2023-06-19' + bug_reports: https://github.com/pachadotdev/d3po/issues + url: https://pacha.dev/d3po/ + url_cran: https://CRAN.R-project.org/package=d3po + url_git: '' +d3r: + version: 1.1.0 + title: '''d3.js'' Utilities for R' + maintainer: Kent Russell + description: |- + Provides a suite of functions to help ease the use of 'd3.js' in R. + These helpers include 'htmltools::htmlDependency' functions, hierarchy + builders, and conversion tools for 'partykit', 'igraph,' 'table', + and 'data.frame' R objects into the 'JSON' that 'd3.js' expects. + date_publication: '2023-10-02' + bug_reports: https://github.com/timelyportfolio/d3r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=d3r + url_git: https://github.com/timelyportfolio/d3r +d3Tree: + version: 0.3.0 + title: |- + Create Interactive Collapsible Trees with the JavaScript 'D3' + Library + maintainer: Jonathan Sidi + description: |- + Create and customize interactive collapsible 'D3' trees using the 'D3' + JavaScript library and the 'htmlwidgets' package. These trees can be used + directly from the R console, from 'RStudio', in Shiny apps and R Markdown documents. + When in Shiny the tree layout is observed by the server and can be used as a reactive filter + of structured data. + date_publication: '2024-01-29' + bug_reports: https://github.com/yonicd/d3Tree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=d3Tree + url_git: https://github.com/yonicd/d3Tree +d4storagehub4R: + version: 0.4-4 + title: Interface to 'D4Science' 'StorageHub' API + maintainer: Emmanuel Blondel + description: |- + Provides an interface to 'D4Science' 'StorageHub' API (). Allows to get user profile, and perform + actions over the 'StorageHub' (workspace) including creation of folders, files management (upload/update/deletion/sharing), and listing of + stored resources. + date_publication: '2024-04-15' + bug_reports: https://github.com/eblondel/d4storagehub4R/issues + url: https://www.d4science.org/ + url_cran: https://CRAN.R-project.org/package=d4storagehub4R + url_git: https://github.com/eblondel/d4storagehub4R +D4TAlink.light: + version: 2.1.17 + title: FAIR Data - Workflow Management + maintainer: Gregoire Thomas + description: |- + Tools, methods and processes for the management + of analysis workflows. These lightweight solutions facilitate + structuring R&D activities. These solutions were developed to comply + with Good Documentation Practice (GDP), + with FAIR principles as discussed by Jacobsen et al. (2017) , + and with ALCOA+ principles as proposed by the U.S. FDA. + date_publication: '2024-12-02' + bug_reports: https://bitbucket.org/SQ4/d4talink.light/issues + url: https://www.d4ta.link/ + url_cran: https://CRAN.R-project.org/package=D4TAlink.light + url_git: https://bitbucket.org/SQ4/d4talink.light +DA: + version: 1.2.0 + title: Discriminant Analysis for Evolutionary Inference + maintainer: Xinghu Qin + description: Discriminant Analysis (DA) for evolutionary inference (Qin, X. et al, + 2020, ), especially for population genetic + structure and community structure inference. This package incorporates the commonly + used linear and non-linear, local and global supervised learning approaches (discriminant + analysis), including Linear Discriminant Analysis of Kernel Principal Components + (LDAKPC), Local (Fisher) Linear Discriminant Analysis (LFDA), Local (Fisher) Discriminant + Analysis of Kernel Principal Components (LFDAKPC) and Kernel Local (Fisher) Discriminant + Analysis (KLFDA). These discriminant analyses can be used to do ecological and + evolutionary inference, including demography inference, species identification, + and population/community structure inference. + date_publication: '2021-07-12' + bug_reports: https://github.com/xinghuq/DA/issues + url: https://xinghuq.github.io/DA/index.html + url_cran: https://CRAN.R-project.org/package=DA + url_git: '' +DAAG: + version: 1.25.6 + title: Data Analysis and Graphics Data and Functions + maintainer: W. John Braun + description: |- + Functions and data sets used in examples and exercises in the + text Maindonald, J.H. and Braun, W.J. (2003, 2007, 2010) "Data + Analysis and Graphics Using R", and in an upcoming Maindonald, + Braun, and Andrews text that builds on this earlier text. + date_publication: '2024-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DAAG + url_git: https://gitlab.com/daagur/DAAG +DAAGbio: + version: 0.63-4 + title: |- + Data Sets and Functions, for Demonstrations with Expression + Arrays and Gene Sequences + maintainer: John Maindonald + description: Data sets and functions, for the display of gene expression array (microarray) + data, and for demonstrations with such data. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DAAGbio + url_git: https://github.com/jhmaindonald/DAAGbio/ +daarem: + version: '0.7' + title: |- + Damped Anderson Acceleration with Epsilon Monotonicity for + Accelerating EM-Like Monotone Algorithms + maintainer: Nicholas Henderson + description: Implements the DAAREM method for accelerating the convergence of slow, + monotone sequences from smooth, fixed-point iterations such as the EM algorithm. + For further details about the DAAREM method, see Henderson, N.C. and Varadhan, + R. (2019) . + date_publication: '2022-03-23' + bug_reports: '' + url: https://doi.org/10.1080/10618600.2019.1594835 + url_cran: https://CRAN.R-project.org/package=daarem + url_git: '' +dabestr: + version: 2025.3.14 + title: Data Analysis using Bootstrap-Coupled Estimation + maintainer: Yishan Mai + description: |- + Data Analysis using Bootstrap-Coupled ESTimation. Estimation + statistics is a simple framework that avoids the pitfalls of + significance testing. It uses familiar statistical concepts: means, + mean differences, and error bars. More importantly, it focuses on the + effect size of one's experiment/intervention, as opposed to a false + dichotomy engendered by P values. An estimation plot has two key + features: 1. It presents all datapoints as a swarmplot, which orders + each point to display the underlying distribution. 2. It presents the + effect size as a bootstrap 95% confidence interval on a separate but + aligned axes. Estimation plots are introduced in Ho et al., Nature + Methods 2019, 1548-7105. . The + free-to-view PDF is located at + . + date_publication: '2025-02-26' + bug_reports: '' + url: https://acclab.github.io/dabestr/ + url_cran: https://CRAN.R-project.org/package=dabestr + url_git: https://github.com/ACCLAB/dabestr +dabr: + version: 0.0.4 + title: Database Management with R + maintainer: Roberto Villegas-Diaz + description: |- + Provides functions to manage databases: select, update, insert, + and delete records, list tables, backup tables as CSV files, and import + CSV files as tables. + date_publication: '2022-10-17' + bug_reports: https://github.com/special-uor/dabr/issues/ + url: https://special-uor.github.io/dabr/ + url_cran: https://CRAN.R-project.org/package=dabr + url_git: https://github.com/special-uor/dabr/ +dacc: + version: 0.0-6 + title: Detection and Attribution Analysis of Climate Change + maintainer: Yan Li + description: |- + Conduct detection and attribution of climate change using methods including optimal fingerprinting via + generalized total least squares or estimating equation approach from Ma et al. (2023) . + Provide shrinkage estimators for covariance matrix from Ledoit and Wolf (2004) , + and Ledoit and Wolf (2017) . + date_publication: '2025-01-24' + bug_reports: https://github.com/LiYanStat/dacc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dacc + url_git: https://github.com/LiYanStat/dacc +DACF: + version: 1.0.0 + title: Data Analysis with Ceiling and/or Floor Data + maintainer: Qimin Liu + description: An implementation of data analytic methods in R for analyses for data + with ceiling/floor effects. The package currently includes functions for mean/variance + estimation and mean comparison tests. Implemented methods are from Aitkin (1964) + and Liu & Wang (in prep). + date_publication: '2018-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DACF + url_git: '' +dad: + version: 4.1.5 + title: Three-Way / Multigroup Data Analysis Through Densities + maintainer: Pierre Santagostini + description: The data consist of a set of variables measured on several groups of + individuals. To each group is associated an estimated probability density function. + The package provides tools to create or manage such data and functional methods + (principal component analysis, multidimensional scaling, cluster analysis, discriminant + analysis...) for such probability densities. + date_publication: '2024-11-22' + bug_reports: https://forgemia.inra.fr/dad/dad/-/issues + url: https://forgemia.inra.fr/dad/dad + url_cran: https://CRAN.R-project.org/package=dad + url_git: '' +dadjoke: + version: '1.0' + title: Displays a Dad Joke + maintainer: Shambhavi Priyam + description: Displays a terrible joke, the kind only dads crack. + date_publication: '2020-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dadjoke + url_git: '' +dadjokeapi: + version: 1.0.2 + title: Return a Random Dad Joke + maintainer: Jeffrey Hollister + description: |- + What is funnier than a dad joke? A dad joke in R! This package + utilizes the API for and returns dad jokes from + several API endpoints. + date_publication: '2021-03-01' + bug_reports: https://github.com/jhollist/dadjokeapi/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=dadjokeapi + url_git: https://github.com/jhollist/dadjokeapi/ +dados: + version: 0.1.0 + title: Translate Datasets to Portuguese + maintainer: Riva Quiroga + description: |- + Este pacote traduz os seguintes + conjuntos de dados: 'airlines', 'airports', 'ames_raw', 'AwardsManagers', + 'babynames', 'Batting', 'diamonds', 'faithful', 'fueleconomy', + 'Fielding', 'flights', 'gapminder', 'gss_cat', 'iris', 'Managers', + 'mpg', 'mtcars', 'atmos', 'penguins', 'People, 'Pitching', 'pixarfilms','planes', + 'presidential', 'table1', 'table2', 'table3', 'table4a', 'table4b', + 'table5', 'vehicles', 'weather', 'who'. English: It provides a + Portuguese translated version of the datasets listed above. + date_publication: '2022-02-24' + bug_reports: https://github.com/cienciadedatos/dados/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dados + url_git: https://github.com/cienciadedatos/dados +dae: + version: 3.2.30 + title: Functions Useful in the Design and ANOVA of Experiments + maintainer: Chris Brien + description: |- + The content falls into the following groupings: (i) Data, (ii) + Factor manipulation functions, (iii) Design functions, (iv) ANOVA functions, (v) + Matrix functions, (vi) Projector and canonical efficiency functions, and (vii) + Miscellaneous functions. There is a vignette describing how to use the + design functions for randomizing and assessing designs available as a + vignette called 'DesignNotes'. The ANOVA functions facilitate the extraction of + information when the 'Error' function has been used in the call to 'aov'. + The package 'dae' can also be installed from + . + date_publication: '2024-12-01' + bug_reports: https://github.com/briencj/dae/issues + url: http://chris.brien.name + url_cran: https://CRAN.R-project.org/package=dae + url_git: '' +daewr: + version: 1.2-11 + title: Design and Analysis of Experiments with R + maintainer: John Lawson + description: Contains Data frames and functions used in the book "Design and Analysis + of Experiments with R", Lawson(2015) ISBN-13:978-1-4398-6813-3. + date_publication: '2023-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=daewr + url_git: '' +daff: + version: 1.1.1 + title: Diff, Patch and Merge for Data.frames + maintainer: Edwin de Jonge + description: |- + Diff, patch and merge for data frames. Document changes in data + sets and use them to apply patches. Changes to data can be made visible by using + render_diff(). The 'V8' package is used to wrap the 'daff.js' 'JavaScript' library + which is included in the package. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=daff + url_git: https://github.com/edwindj/daff +dafishr: + version: 1.0.1 + title: Download, Wrangle, and Analyse Vessel Monitoring System Data + maintainer: Fabio Favoretto + description: |- + Allows to download, clean and analyse raw Vessel Monitoring System, VMS, data from + Mexican government. You can use the vms_download() function to + download raw data, or you can use the sample_dataset provided within + the package. You can follow the tutorial in the vignette available at + . + date_publication: '2024-07-22' + bug_reports: https://github.com/CBMC-GCMP/dafishr/issues/ + url: https://cbmc-gcmp.github.io/dafishr/ + url_cran: https://CRAN.R-project.org/package=dafishr + url_git: https://github.com/CBMC-GCMP/dafishr +dafs: + version: 1.0-38 + title: Data Analysis for Forensic Scientists + maintainer: James Curran + description: 'Data and miscellanea to support the book "Introduction to Data analysis + with R for Forensic Scientists." This book was written by James Curran and published + by CRC Press in 2010 (ISBN: 978-1-4200-8826-7).' + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dafs + url_git: '' +dagirlite: + version: 0.1.0 + title: |- + Spatial Vector Data for Danmarks Administrative Geografiske + Inddeling DAGI + maintainer: Lars Boerty + description: |- + Compressed spatial vector data originally from saved as Simple + Features, SF, objects with data on population, age and gender from Statistics Denmark . + date_publication: '2021-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dagirlite + url_git: '' +dagitty: + version: 0.3-4 + title: Graphical Analysis of Structural Causal Models + maintainer: Johannes Textor + description: |- + A port of the web-based software 'DAGitty', available at + , for analyzing structural causal models + (also known as directed acyclic graphs or DAGs). + This package computes covariate adjustment sets for estimating causal + effects, enumerates instrumental variables, derives testable + implications (d-separation and vanishing tetrads), generates equivalent + models, and includes a simple facility for data simulation. + date_publication: '2023-12-07' + bug_reports: https://github.com/jtextor/dagitty/issues + url: https://www.dagitty.net + url_cran: https://CRAN.R-project.org/package=dagitty + url_git: https://github.com/jtextor/dagitty +dagR: + version: 1.2.1 + title: 'Directed Acyclic Graphs: Analysis and Data Simulation' + maintainer: Lutz P Breitling + description: |- + Draw, manipulate, and evaluate directed + acyclic graphs and simulate corresponding data, as described in International Journal of Epidemiology 50(6):1772-1777. + date_publication: '2022-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dagR + url_git: '' +dagwood: + version: 0.1.4 + title: DAGs with Omitted Objects Displayed (DAGWOOD) + maintainer: Noah Haber + description: DAGs With Omitted Objects Displayed (DAGWOOD) is a framework to help + reveal key hidden assumptions in a causal DAG. This package provides an implementation + of the DAGWOOD algorithm. Further description can be found in Haber et al (2022) + . + date_publication: '2022-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dagwood + url_git: '' +dail: + version: 1.5.2 + title: Data from Access to Information Law + maintainer: Igor Laltuf + description: Downloads the public data available from the Brazilian Access to Information + Law and and performs a search on information requests and appeals made since 2015. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dail + url_git: '' +DAIME: + version: 2.1.3 + title: Effects of Changing Deposition Rates + maintainer: Niklas Hohmann + description: Reverse and model the effects of changing deposition rates on geological + data and rates. Based on Hohmann (2018) . + date_publication: '2020-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DAIME + url_git: '' +daiquiri: + version: 1.1.1 + title: Data Quality Reporting for Temporal Datasets + maintainer: T. Phuong Quan + description: |- + Generate reports that enable quick visual review of + temporal shifts in record-level data. Time series plots showing aggregated + values are automatically created for each data field (column) depending on its + contents (e.g. min/max/mean values for numeric data, no. of distinct + values for categorical data), as well as overviews for missing values, + non-conformant values, and duplicated rows. The resulting reports are shareable + and can contribute to forming a transparent record of the entire analysis process. + It is designed with Electronic Health Records in mind, but can be used for + any type of record-level temporal data (i.e. tabular data where each row represents + a single "event", one column contains the "event date", and other columns + contain any associated values for the event). + date_publication: '2023-07-18' + bug_reports: https://github.com/ropensci/daiquiri/issues + url: https://ropensci.github.io/daiquiri/ + url_cran: https://CRAN.R-project.org/package=daiquiri + url_git: https://github.com/ropensci/daiquiri +daiR: + version: 1.0.1 + title: Interface with Google Cloud Document AI API + maintainer: Thomas Hegghammer + description: |- + R interface for the Google Cloud Services 'Document AI API' + with additional tools for + output file parsing and text reconstruction. 'Document AI' is a + powerful server-based OCR service that extracts text and tables from + images and PDF files with high accuracy. 'daiR' gives R users + programmatic access to this service and additional tools to handle + and visualize the output. See the package website + for more information and examples. + date_publication: '2024-11-13' + bug_reports: https://github.com/Hegghammer/daiR/issues + url: https://dair.info + url_cran: https://CRAN.R-project.org/package=daiR + url_git: https://github.com/Hegghammer/daiR +DAISIE: + version: 4.5.0 + title: |- + Dynamical Assembly of Islands by Speciation, Immigration and + Extinction + maintainer: Rampal S. Etienne + description: |- + Simulates and computes the (maximum) likelihood of a dynamical + model of island biota assembly through speciation, immigration and + extinction. See Valente et al. (2015) . + date_publication: '2025-02-05' + bug_reports: https://github.com/rsetienne/DAISIE/issues + url: https://rsetienne.github.io/DAISIE/ + url_cran: https://CRAN.R-project.org/package=DAISIE + url_git: https://github.com/rsetienne/DAISIE +DAISIEprep: + version: 1.0.0 + title: |- + Extracts Phylogenetic Island Community Data from Phylogenetic + Trees + maintainer: Joshua W. Lambert + description: |- + Extracts colonisation and branching times of island + species to be used for analysis in the R package 'DAISIE'. It uses + phylogenetic and endemicity data to extract the separate island colonists + and store them. + date_publication: '2024-12-18' + bug_reports: https://github.com/joshwlambert/DAISIEprep/issues + url: https://joshwlambert.github.io/DAISIEprep/ + url_cran: https://CRAN.R-project.org/package=DAISIEprep + url_git: https://github.com/joshwlambert/DAISIEprep +DAKS: + version: 2.1-3 + title: Data Analysis and Knowledge Spaces + maintainer: Ali Uenlue + description: |- + Functions and an example dataset for the psychometric theory of + knowledge spaces. This package implements data analysis methods and + procedures for simulating data and quasi orders and transforming different + formulations in knowledge space theory. See package?DAKS for an overview. + date_publication: '2016-06-06' + bug_reports: '' + url: http://www.meb.edu.tum.de + url_cran: https://CRAN.R-project.org/package=DAKS + url_git: '' +DALEX: + version: 2.4.3 + title: moDel Agnostic Language for Exploration and eXplanation + maintainer: Przemyslaw Biecek + description: |- + Any unverified black box model is the path to failure. Opaqueness leads to distrust. + Distrust leads to ignoration. Ignoration leads to rejection. + DALEX package xrays any model and helps to explore and explain its behaviour. + Machine Learning (ML) models are widely used and have various applications in classification + or regression. Models created with boosting, bagging, stacking or similar techniques are often + used due to their high performance. But such black-box models usually lack direct interpretability. + DALEX package contains various methods that help to understand the link between input variables + and model output. Implemented methods help to explore the model on the level of a single instance + as well as a level of the whole dataset. + All model explainers are model agnostic and can be compared across different models. + DALEX package is the cornerstone for 'DrWhy.AI' universe of packages for visual model exploration. + Find more details in (Biecek 2018) . + date_publication: '2023-01-15' + bug_reports: https://github.com/ModelOriented/DALEX/issues + url: https://modeloriented.github.io/DALEX/ + url_cran: https://CRAN.R-project.org/package=DALEX + url_git: '' +DALEXtra: + version: 2.3.0 + title: Extension for 'DALEX' Package + maintainer: Szymon Maksymiuk + description: |- + Provides wrapper of various machine learning models. + In applied machine learning, there + is a strong belief that we need to strike a balance + between interpretability and accuracy. + However, in field of the interpretable machine learning, + there are more and more new ideas for explaining black-box models, + that are implemented in 'R'. + 'DALEXtra' creates 'DALEX' Biecek (2018) explainer for many type of models + including those created using 'python' 'scikit-learn' and 'keras' libraries, and 'java' 'h2o' library. + Important part of the package is Champion-Challenger analysis and innovative approach + to model performance across subsets of test data presented in Funnel Plot. + date_publication: '2023-05-26' + bug_reports: https://github.com/ModelOriented/DALEXtra/issues + url: https://ModelOriented.github.io/DALEXtra/ + url_cran: https://CRAN.R-project.org/package=DALEXtra + url_git: https://github.com/ModelOriented/DALEXtra +DALSM: + version: 0.9.1 + title: Nonparametric Double Additive Location-Scale Model (DALSM) + maintainer: Philippe Lambert + description: Fit of a double additive location-scale model with a nonparametric + error distribution from possibly right- or interval censored data. The additive + terms in the location and dispersion submodels, as well as the unknown error distribution + in the location-scale model, are estimated using Laplace P-splines. For more details, + see Lambert (2021) . + date_publication: '2023-10-02' + bug_reports: https://github.com/plambertULiege/DALSM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DALSM + url_git: +daltoolbox: + version: 1.1.727 + title: Leveraging Experiment Lines to Data Analytics + maintainer: Eduardo Ogasawara + description: The natural increase in the complexity of current research experiments + and data demands better tools to enhance productivity in Data Analytics. The package + is a framework designed to address the modern challenges in data analytics workflows. + The package is inspired by Experiment Line concepts. It aims to provide seamless + support for users in developing their data mining workflows by offering a uniform + data model and method API. It enables the integration of various data mining activities, + including data preprocessing, classification, regression, clustering, and time + series prediction. It also offers options for hyper-parameter tuning and supports + integration with existing libraries and languages. Overall, the package provides + researchers with a comprehensive set of functionalities for data science, promoting + ease of use, extensibility, and integration with various tools and libraries. + Information on Experiment Line is based on Ogasawara et al. (2009) . + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=daltoolbox + url_git: https://github.com/cefet-rj-dal/daltoolbox +daltoolboxdp: + version: 1.0.777 + title: Data Pre-Processing Extensions + maintainer: Eduardo Ogasawara + description: An important aspect of data analytics is related to data management + support for artificial intelligence. It is related to preparing data correctly. + This package provides extensions to support data preparation in terms of both + data sampling and data engineering. Overall, the package provides researchers + with a comprehensive set of functionalities for data science based on experiment + lines, promoting ease of use, extensibility, and integration with various tools + and libraries. Information on Experiment Line is based on Ogasawara et al. (2009) + . + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=daltoolboxdp + url_git: https://github.com/cefet-rj-dal/daltoolboxdp +DALY: + version: 1.5.0 + title: |- + The DALY Calculator - Graphical User Interface for Probabilistic + DALY Calculation in R + maintainer: Brecht Devleesschauwer + description: |- + The DALY Calculator is a free, open-source Graphical User + Interface (GUI) for stochastic disability-adjusted life year + (DALY) calculation. + date_publication: '2016-11-26' + bug_reports: https://github.com/brechtdv/DALY/issues + url: http://daly.cbra.be + url_cran: https://CRAN.R-project.org/package=DALY + url_git: '' +dam: + version: 0.0.1 + title: Data Analysis Metabolomics + maintainer: Slavik Koval + description: A collection of functions which aim to assist common computational + workflow for analysis of matabolomic data.. + date_publication: '2016-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dam + url_git: '' +damAOI: + version: '0.1' + title: |- + Create an 'Area of Interest' Around a Constructed Dam for + Comparative Impact Evaluations + maintainer: Chris Littleboy + description: |- + Define a spatial 'Area of Interest' (AOI) around a constructed dam using hydrology data. + Dams have environmental and social impacts, both positive and negative. + Current analyses of dams have no consistent way to specify at what spatial extent we should evaluate these impacts. + 'damAOI' implements methods to adjust reservoir polygons to match satellite-observed surface water areas, plot upstream and downstream rivers using elevation data and accumulated river flow, and draw buffers clipped by river basins around reservoirs and relevant rivers. + This helps to consistently determine the areas which could be impacted by dam construction, facilitating comparative analysis and informed infrastructure investments. + date_publication: '2024-07-12' + bug_reports: https://github.com/chrislittleboy/damaoi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=damAOI + url_git: https://github.com/chrislittleboy/damaoi +DamiaNN: + version: 1.0.0 + title: Neural Network Numerai + maintainer: Damian Siniakowicz + description: Interactively train neural networks on Numerai, , + data. Generate tournament predictions and write them to a CSV. + date_publication: '2016-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DamiaNN + url_git: '' +DAMOCLES: + version: '2.3' + title: |- + Dynamic Assembly Model of Colonization, Local Extinction and + Speciation + maintainer: Rampal S. Etienne + description: Simulates and computes (maximum) likelihood of a dynamical model of + community assembly that takes into account phylogenetic history. + date_publication: '2020-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DAMOCLES + url_git: '' +dampack: + version: 1.0.2.1000 + title: Decision-Analytic Modeling Package + maintainer: David Garibay + description: |- + A suite of functions for analyzing and visualizing the health economic outputs of mathematical models. + This package was developed with funding from the National Institutes of Allergy and Infectious Diseases of the + National Institutes of Health under award no. R01AI138783. The content of this package is solely the + responsibility of the authors and does not necessarily represent the official views of the National Institutes + of Health. The theoretical underpinnings of 'dampack''s functionality are detailed in Hunink et al. (2014) + . + date_publication: '2024-09-30' + bug_reports: https://github.com/DARTH-git/dampack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dampack + url_git: https://github.com/DARTH-git/dampack +damr: + version: 0.3.7 + title: Interface to Drosophila Activity Monitor System Result Files + maintainer: Quentin Geissmann + description: Loads behavioural data from the widely used Drosophila Activity Monitor + System (DAMS, TriKinetics ) into the rethomics framework. + date_publication: '2020-11-16' + bug_reports: https://github.com/rethomics/damr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=damr + url_git: https://github.com/rethomics/damr +dams: + version: 0.3.0 + title: |- + Dams in the United States from the National Inventory of Dams + (NID) + maintainer: Joseph Stachelek + description: |- + The single largest source of dams in the United States is the + National Inventory of Dams (NID) from the US + Army Corps of Engineers. Entire data from the NID cannot be obtained all at + once and NID's website limits extraction of more than a couple of thousand + records at a time. Moreover, selected data from the NID's user interface + cannot not be saved to a file. In order to make the analysis of this data + easier, all the data from NID was extracted manually. Subsequently, the raw + data was checked for potential errors and cleaned. This package provides + sample cleaned data from the NID and provides functionality to access the + entire cleaned NID data. + date_publication: '2020-05-20' + bug_reports: http://www.github.com/jsta/dams/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dams + url_git: https://github.com/jsta/dams +DandEFA: + version: '1.6' + title: Dandelion Plot for R-Mode Exploratory Factor Analysis + maintainer: Artur Manukyan + description: Contains the function used to create the Dandelion Plot. Dandelion + Plot is a visualization method for R-mode Exploratory Factor Analysis. + date_publication: '2016-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DandEFA + url_git: '' +dang: + version: 0.0.16 + title: '''Dang'' Associated New Goodies' + maintainer: Dirk Eddelbuettel + description: A collection of utility functions. + date_publication: '2023-12-02' + bug_reports: https://github.com/eddelbuettel/dang/issues + url: https://dirk.eddelbuettel.com/code/dang.html + url_cran: https://CRAN.R-project.org/package=dang + url_git: https://github.com/eddelbuettel/dang +dani: + version: 0.1-1 + title: Design and Analysis of Non-Inferiority Trials + maintainer: Matteo Quartagno + description: |- + Provides tools to help the design and analysis of resilient non-inferiority trials. These include functions for sample size + calculations and analyses of trials, with either a risk difference, risk ratio or arc-sine difference margin, and a function to run simulations to + design a trial with the methods described in Quartagno et al. (2019) . + date_publication: '2020-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dani + url_git: '' +DanielBiostatistics10th: + version: 0.2.6 + title: Functions for Wayne W. Daniel's Biostatistics, Tenth Edition + maintainer: Tingting Zhan + description: |- + Functions to accompany Wayne W. Daniel's Biostatistics: A + Foundation for Analysis in the Health Sciences, Tenth Edition. + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DanielBiostatistics10th + url_git: '' +dann: + version: 1.0.0 + title: Discriminant Adaptive Nearest Neighbor Classification + maintainer: Greg McMahan + description: |- + Discriminant Adaptive Nearest Neighbor Classification is a + variation of k nearest neighbors where the shape of the neighborhood is + data driven. This package implements dann and sub_dann from + Hastie (1996) . + date_publication: '2023-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dann + url_git: '' +danstat: + version: 0.2.0 + title: R Client for the Statistics Denmark Databank API + maintainer: Valeri Voev + description: |- + The purpose of the package is to enable an R function interface into the Statistics Denmark Databank API mainly for research purposes. + The Statistics Denmark Databank API has four endpoints, see here for more information and testing the API in their console: . + This package mimics the structure of the API and provides four main functions to match the functionality of the API endpoints. + date_publication: '2022-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=danstat + url_git: '' +dapper: + version: 1.0.1 + title: Data Augmentation for Private Posterior Estimation + maintainer: Kevin Eng + description: |- + A data augmentation based sampler for conducting privacy-aware Bayesian inference. The dapper_sample() + function takes an existing sampler as input and automatically constructs + a privacy-aware sampler. The process of constructing a sampler is simplified + through the specification of four independent modules, allowing for + easy comparison between different privacy mechanisms by only swapping + out the relevant modules. Probability mass functions + for the discrete Gaussian and discrete Laplacian are provided to facilitate + analyses dealing with privatized count data. The output of dapper_sample() + can be analyzed using many of the same tools from the 'rstan' ecosystem. For methodological details + on the sampler see Ju et al. (2022) , + and for details on the discrete Gaussian and discrete Laplacian distributions see + Canonne et al. (2020) . + date_publication: '2024-10-29' + bug_reports: https://github.com/mango-empire/dapper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dapper + url_git: https://github.com/mango-empire/dapper +daqapo: + version: 0.3.2 + title: Data Quality Assessment for Process-Oriented Data + maintainer: Niels Martin + description: Provides a variety of methods to identify data quality issues in process-oriented + data, which are useful to verify data quality in a process mining context. Builds + on the class for activity logs implemented in the package 'bupaR'. Methods to + identify data quality issues either consider each activity log entry independently + (e.g. missing values, activity duration outliers,...), or focus on the relation + amongst several activity log entries (e.g. batch registrations, violations of + the expected activity order,...). + date_publication: '2022-07-14' + bug_reports: https://github.com/bupaverse/daqapo/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=daqapo + url_git: https://github.com/bupaverse/daqapo/ +DArand: + version: 0.0.1.2 + title: Differential Analysis with Random Reference Genes + maintainer: Dorota Desaulle + description: Differential Analysis of short RNA transcripts that can be modeled + by either Poisson or Negative binomial distribution. The statistical methodology + implemented in this package is based on the random selection of references genes + (Desaulle et al. (2021) ). + date_publication: '2022-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DArand + url_git: '' +Dark: + version: 0.9.9 + title: The Analysis of Dark Adaptation Data + maintainer: Jeremiah MF Kelly + description: |- + The recovery of visual sensitivity in a dark environment is known + as dark adaptation. In a clinical or research setting the recovery is typically + measured after a dazzling flash of light and can be described by the Mahroo, + Lamb and Pugh (MLP) model of dark adaptation. The functions in this package take + dark adaptation data and use nonlinear regression to find the parameters of the + model that 'best' describe the data. They do this by firstly, generating rapid + initial objective estimates of data adaptation parameters, then a multi-start + algorithm is used to reduce the possibility of a local minimum. There is also a + bootstrap method to calculate parameter confidence intervals. The functions rely + upon a 'dark' list or object. This object is created as the first step in the + workflow and parts of the object are updated as it is processed. + date_publication: '2025-01-14' + bug_reports: https://github.com/emkayoh/Dark/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Dark + url_git: https://github.com/emkayoh/Dark +DarkDiv: + version: 0.3.0 + title: Estimating Dark Diversity and Site-Specific Species Pools + maintainer: Carlos P. Carmona + description: |- + Estimation of dark diversity and site-specific species pools using species co-occurrences. + It includes implementations of probabilistic dark diversity based on the + Hypergeometric distribution, as well as estimations based on the Beals index, + which can be transformed to binary predictions using different thresholds, + or transformed into a favorability index. All methods include the possibility of + using a calibration dataset that is used to estimate the indication matrix + between pairs of species, or to estimate dark diversity directly on a single + dataset. See De Caceres and Legendre (2008) , + Lewis et al. (2016) , + Partel et al. (2011) , Real et al. (2017) + for further information. + date_publication: '2020-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DarkDiv + url_git: '' +darksky: + version: 1.3.0 + title: Tools to Work with the 'Dark Sky' 'API' + maintainer: Bob Rudis + description: |- + Provides programmatic access to the 'Dark Sky' 'API' + , which provides current or historical global + weather conditions. + date_publication: '2017-09-20' + bug_reports: https://github.com/hrbrmstr/darksky/issues + url: '' + url_cran: https://CRAN.R-project.org/package=darksky + url_git: https://github.com/hrbrmstr/darksky +dartR.base: + version: '0.98' + title: Analysing 'SNP' and 'Silicodart' Data - Basic Functions + maintainer: Bernd Gruber + description: |- + Facilitates the import and analysis of 'SNP' (single nucleotide 'polymorphism') + and 'silicodart' (presence/absence) data. The main focus is on data generated by 'DarT' + (Diversity Arrays Technology), however, data from other sequencing platforms can be used + once 'SNP' or related fragment presence/absence data from any source is imported. Genetic + datasets are stored in a derived 'genlight' format (package 'adegenet'), that allows for + a very compact storage of data and metadata. Functions are available for + importing and exporting of 'SNP' and 'silicodart' data, for reporting on and + filtering on various criteria (e.g. 'callrate', 'heterozygosity', 'reproducibility', + maximum allele frequency). Additional functions are available for visualization + (e.g. Principle Coordinate Analysis) and creating a spatial representation + using maps. 'dartR.base' is the 'base' package of the 'dartRverse' suits of packages. + To install the other packages, we recommend to install the 'dartRverse' package, that + supports the installation of all packages in the 'dartRverse'. + If you want to cite 'dartR', you find the information by typing citation('dartR.base') + in the console. + date_publication: '2024-09-19' + bug_reports: https://groups.google.com/g/dartr?pli=1 + url: https://green-striped-gecko.github.io/dartR/ + url_cran: https://CRAN.R-project.org/package=dartR.base + url_git: '' +dartR.captive: + version: 1.0.2 + title: Analysing 'SNP' Data to Support Captive Breeding + maintainer: Bernd Gruber + description: |- + Functions are provided that facilitate the analysis of SNP + (single nucleotide polymorphism) data to answer questions regarding + captive breeding and relatedness between individuals. 'dartR.captive' + is part of the 'dartRverse' suit of packages. + Gruber et al. (2018) . + Mijangos et al. (2022) . + date_publication: '2025-02-18' + bug_reports: https://groups.google.com/g/dartr?pli=1 + url: https://green-striped-gecko.github.io/dartR/ + url_cran: https://CRAN.R-project.org/package=dartR.captive + url_git: '' +dartR.data: + version: 1.0.8 + title: Auxiliary Data Package for Our Main Package 'dartR' + maintainer: Bernd Gruber + description: |- + Data package for 'dartR'. Provides data sets to run examples in 'dartR'. + This was necessary due to the size limit imposed by 'CRAN'. The data in 'dartR.data' + is needed to run the examples provided in the 'dartR' functions. + All available data sets are either based on actual data (but reduced in size) + and/or simulated data sets to allow the fast execution of examples and demonstration + of the functions. + date_publication: '2024-05-30' + bug_reports: https://groups.google.com/g/dartr?pli=1 + url: '' + url_cran: https://CRAN.R-project.org/package=dartR.data + url_git: https://github.com/green-striped-gecko/dartR.data +dartR.popgen: + version: 1.0.0 + title: |- + Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide + Restriction Fragment Analysis + maintainer: Bernd Gruber + description: |- + Facilitates the analysis of SNP (single nucleotide polymorphism) + and silicodart (presence/absence) data. 'dartR.popgen' provides a suit of + functions to analyse such data in a population genetics context. It provides + several functions to calculate population genetic metrics and to study + population structure. Quite a few functions need additional software to be + able to run (gl.run.structure(), gl.blast(), gl.LDNe()). You find detailed description + in the help pages how to download and link the packages so the function can + run the software. 'dartR.popgen' is part of the the 'dartRverse' suit of packages. + Gruber et al. (2018) . + Mijangos et al. (2022) . + date_publication: '2024-06-27' + bug_reports: https://groups.google.com/g/dartr?pli=1 + url: https://green-striped-gecko.github.io/dartR/ + url_cran: https://CRAN.R-project.org/package=dartR.popgen + url_git: '' +dartR.sexlinked: + version: 1.0.5 + title: Analysing SNP Data to Identify Sex-Linked Markers + maintainer: Diana Robledo-Ruiz + description: |- + Identifies, filters and exports sex linked markers using 'SNP' + (single nucleotide polymorphism) data. To install the other packages, we + recommend to install the 'dartRverse' package, that supports the installation of all packages in the 'dartRverse'. + If you want understand the applied rational to identify sexlinked markers + and/or want to cite 'dartR.sexlinked', you find the information by typing + citation('dartR.sexlinked') in the console. + date_publication: '2024-06-24' + bug_reports: https://groups.google.com/g/dartr?pli=1 + url: https://green-striped-gecko.github.io/dartR/ + url_cran: https://CRAN.R-project.org/package=dartR.sexlinked + url_git: '' +dartR.sim: + version: '0.70' + title: Computer Simulations of 'SNP' Data + maintainer: Jose L. Mijangos + description: Allows to simulate SNP data using genlight objects. For example, it + is straight forward to simulate a simple drift scenario with exchange of individuals + between two populations or create a new genlight object based on allele frequencies + of an existing genlight object. + date_publication: '2023-11-20' + bug_reports: https://github.com/green-striped-gecko/dartR.sim/issues + url: https://green-striped-gecko.github.io/dartR/ + url_cran: https://CRAN.R-project.org/package=dartR.sim + url_git: https://github.com/green-striped-gecko/dartR.sim +dartR.spatial: + version: '0.78' + title: |- + Applying Landscape Genomic Methods on 'SNP' and 'Silicodart' + Data + maintainer: Bernd Gruber + description: |- + Provides landscape genomic functions to analyse 'SNP' (single nuclear + polymorphism) data, such as least cost path analysis and isolation by distance. + Therefore each sample needs to have coordinate data attached (lat/lon) to be + able to run most of the functions. 'dartR.spatial' is a package that belongs + to the 'dartRverse' suit of packages and depends on 'dartR.base' and 'dartR.data'. + date_publication: '2023-11-15' + bug_reports: https://groups.google.com/g/dartr?pli=1 + url: https://green-striped-gecko.github.io/dartR/ + url_cran: https://CRAN.R-project.org/package=dartR.spatial + url_git: '' +dartRverse: + version: 1.0.6 + title: Install and Load the 'dartRverse' Suits of Packages + maintainer: Bernd Gruber + description: |- + Provides a single function that supports the installation of all packages + belonging to the 'dartRverse'. The 'dartRverse' is a set of packages that work + together to analyse SNP (single nuclear polymorphism) data. All packages aim to have a similar 'look and feel' + and are based on the same type of data structure ('genlight'), with additional + metadata for loci and individuals (samples). For more information visit the + 'GitHub' pages . + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dartRverse + url_git: https://github.com/green-striped-gecko/dartRverse +dashboardthemes: + version: 1.1.6 + title: |- + Customise the Appearance of 'shinydashboard' Applications using + Themes + maintainer: Nik Lilovski + description: |- + Allows manual creation of themes and logos to be used in + applications created using the 'shinydashboard' package. Removes the need to + change the underlying css code by wrapping it into a set of convenient R + functions. + date_publication: '2022-07-13' + bug_reports: https://github.com/nik01010/dashboardthemes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dashboardthemes + url_git: https://github.com/nik01010/dashboardthemes +Dasst: + version: 0.3.4 + title: Tools for Reading, Processing and Writing 'DSSAT' Files + maintainer: Homero Lozza + description: |- + Provides methods for reading, displaying, + processing and writing files originally arranged for + the 'DSSAT-CSM' fixed width format. The 'DSSAT-CSM' + cropping system model is described at J.W. Jones, + G. Hoogenboomb, C.H. Porter, K.J. Boote, W.D. Batchelor, + L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, + J.T. Ritchie (2003) . + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dasst + url_git: '' +dat: + version: 0.5.0 + title: Tools for Data Manipulation + maintainer: Sebastian Warnholz + description: |- + An implementation of common higher order functions with syntactic + sugar for anonymous function. Provides also a link to 'dplyr' and + 'data.table' for common transformations on data frames to work around non + standard evaluation by default. + date_publication: '2020-05-15' + bug_reports: https://github.com/wahani/dat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dat + url_git: '' +data.table: + version: 1.17.0 + title: Extension of `data.frame` + maintainer: Tyson Barrett + description: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, + fast add/modify/delete of columns by group using no copies at all, list columns, + friendly and fast character-separated-value read/write. Offers a natural and flexible + syntax, for faster development. + date_publication: '2025-02-22' + bug_reports: https://github.com/Rdatatable/data.table/issues + url: https://r-datatable.com + url_cran: https://CRAN.R-project.org/package=data.table + url_git: https://github.com/Rdatatable/data.table +data.table.threads: + version: 1.0.1 + title: Analyze Multi-Threading Performance for 'data.table' Functions + maintainer: Anirban Chetia + description: |- + Assists in finding the most suitable thread count for the various + 'data.table' routines that support parallel processing. + date_publication: '2024-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=data.table.threads + url_git: https://github.com/Anirban166/data.table.threads +data.tree: + version: 1.1.0 + title: General Purpose Hierarchical Data Structure + maintainer: Christoph Glur + description: |- + Create tree structures from hierarchical data, and traverse the + tree in various orders. Aggregate, cumulate, print, plot, convert to and from + data.frame and more. Useful for decision trees, machine learning, finance, + conversion from and to JSON, and many other applications. + date_publication: '2023-11-12' + bug_reports: https://github.com/gluc/data.tree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=data.tree + url_git: https://github.com/gluc/data.tree +data.validator: + version: 0.2.1 + title: Automatic Data Validation and Reporting + maintainer: Marcin Dubel + description: |- + Validate dataset by columns and rows using convenient predicates inspired by 'assertr' package. + Generate good looking HTML report or print console output to display in logs of your data processing pipeline. + date_publication: '2023-12-11' + bug_reports: https://github.com/Appsilon/data.validator/issues + url: https://appsilon.github.io/data.validator/ + url_cran: https://CRAN.R-project.org/package=data.validator + url_git: https://github.com/Appsilon/data.validator +data360r: + version: 1.0.9 + title: Wrapper for 'TCdata360' and 'Govdata360' API + maintainer: Ramin Aliyev + description: |- + Makes it easy to engage with the Application Program Interface (API) + of the 'TCdata360' and 'Govdata360' platforms at + and , respectively. + These application program interfaces provide access to over 5000 trade, competitiveness, and governance + indicator data, metadata, and related information from sources + both inside and outside the World Bank Group. + Package functions include easier download of data sets, metadata, and + related information, as well as searching based on user-inputted query. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=data360r + url_git: https://github.com/mrpsonglao/data360r +DatabaseConnector: + version: 6.4.0 + title: Connecting to Various Database Platforms + maintainer: Martijn Schuemie + description: |- + An R 'DataBase Interface' ('DBI') compatible interface to various database platforms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', + 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Impala', 'Google BigQuery', 'Snowflake', 'Spark', 'SQLite', + and 'InterSystems IRIS'). Also includes support for fetching data as 'Andromeda' objects. Uses either 'Java Database Connectivity' ('JDBC') or + other 'DBI' drivers to connect to databases. + date_publication: '2025-01-30' + bug_reports: https://github.com/OHDSI/DatabaseConnector/issues + url: https://ohdsi.github.io/DatabaseConnector/ + url_cran: https://CRAN.R-project.org/package=DatabaseConnector + url_git: https://github.com/OHDSI/DatabaseConnector +DatabaseConnectorJars: + version: 1.1.0 + title: JAR Dependencies for the 'DatabaseConnector' Package + maintainer: Martijn Schuemie + description: Provides external JAR dependencies for the 'DatabaseConnector' package. + date_publication: '2019-04-07' + bug_reports: https://github.com/OHDSI/DatabaseConnectorJars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DatabaseConnectorJars + url_git: https://github.com/OHDSI/DatabaseConnectorJars +DatabionicSwarm: + version: 2.0.0 + title: Swarm Intelligence for Self-Organized Clustering + maintainer: Michael Thrun + description: 'Algorithms implementing populations of agents that interact with one + another and sense their environment may exhibit emergent behavior such as self-organization + and swarm intelligence. Here, a swarm system called Databionic swarm (DBS) is + introduced which was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence + for Self-Organized Clustering" (2020), Artificial Intelligence, . + DBS is able to adapt itself to structures of high-dimensional data such as natural + clusters characterized by distance and/or density based structures in the data + space. The first module is the parameter-free projection method called Pswarm + (Pswarm()), which exploits the concepts of self-organization and emergence, game + theory, swarm intelligence and symmetry considerations. The second module is the + parameter-free high-dimensional data visualization technique, which generates + projected points on the topographic map with hypsometric tints defined by the + generalized U-matrix (GeneratePswarmVisualization()). The third module is the + clustering method itself with non-critical parameters (DBSclustering()). Clustering + can be verified by the visualization and vice versa. The term DBS refers to the + method as a whole. It enables even a non-professional in the field of data mining + to apply its algorithms for visualization and/or clustering to data sets with + completely different structures drawn from diverse research fields. The comparison + to common projection methods can be found in the book of Thrun, M.C.: "Projection + Based Clustering through Self-Organization and Swarm Intelligence" (2018) .' + date_publication: '2024-06-20' + bug_reports: https://github.com/Mthrun/DatabionicSwarm/issues + url: https://www.deepbionics.org/ + url_cran: https://CRAN.R-project.org/package=DatabionicSwarm + url_git: '' +DataClean: + version: '1.0' + title: Data Cleaning + maintainer: Xiaorui(Jeremy) Zhu + description: |- + Includes functions that researchers or practitioners may use to clean + raw data, transferring html, xlsx, txt data file into other formats. And it + also can be used to manipulate text variables, extract numeric variables from + text variables and other variable cleaning processes. It is originated from a + author's project which focuses on creative performance in online education + environment. The resulting paper of that study will be published soon. + date_publication: '2016-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataClean + url_git: '' +datacleanr: + version: 1.0.3 + title: Interactive and Reproducible Data Cleaning + maintainer: Alexander Hurley + description: |- + Flexible and efficient cleaning of data with interactivity. + 'datacleanr' facilitates best practices in data analyses and reproducibility with built-in features and by translating interactive/manual operations to code. + The package is designed for interoperability, and so seamlessly fits into reproducible analyses pipelines in 'R'. + date_publication: '2021-11-18' + bug_reports: https://github.com/the-Hull/datacleanr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datacleanr + url_git: https://github.com/the-Hull/datacleanr +DataCombine: + version: 0.2.21 + title: Tools for Easily Combining and Cleaning Data Sets + maintainer: Christopher Gandrud + description: |- + Tools for combining and cleaning data sets, particularly + with grouped and time series data. + date_publication: '2016-04-13' + bug_reports: https://github.com/christophergandrud/DataCombine/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DataCombine + url_git: '' +dataCompare: + version: 1.0.5 + title: A 'shiny' App to Compare Two Data Frames + maintainer: Sergio Ewane Ebouele + description: |- + A tool developed with the 'Golem' framework which provides + an easier way to check cells differences between two data + frames. The user provides two data frames for comparison, + selects IDs variables identifying each row of input data, + then clicks a button to perform the comparison. Several + 'R' package functions are used to describe the data + and perform the comparison in the server of the + application. The main ones are comparedf() from 'arsenal' + and skim() from 'skimr'. For more details see the + description of comparedf() from the 'arsenal' package and + that of skim() from the 'skimr' package. + date_publication: '2024-11-28' + bug_reports: https://github.com/seewe/dataCompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataCompare + url_git: https://github.com/seewe/dataCompare +dataCompareR: + version: 0.1.4 + title: Compare Two Data Frames and Summarise the Difference + maintainer: Sarah Johnston + description: |- + Easy comparison of two tabular data + objects in R. Specifically designed to show differences between two sets of + data in a useful way that should make it easier to understand the differences, + and if necessary, help you work out how to remedy them. Aims + to offer a more useful output than all.equal() when your two data sets do not + match, but isn't intended to replace all.equal() as a way to test for equality. + date_publication: '2021-11-23' + bug_reports: https://github.com/capitalone/dataCompareR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataCompareR + url_git: https://github.com/capitalone/dataCompareR +datacutr: + version: 0.2.3 + title: SDTM Datacut + maintainer: Tim Barnett + description: |- + Supports the process of applying a cut to Standard Data Tabulation Model (SDTM), + as part of the analysis of specific points in time of the data, normally as part of + investigation into clinical trials. The functions support different approaches of + cutting to the different domains of SDTM normally observed. + date_publication: '2025-02-03' + bug_reports: https://github.com/pharmaverse/datacutr/issues + url: https://pharmaverse.github.io/datacutr/ + url_cran: https://CRAN.R-project.org/package=datacutr + url_git: https://github.com/pharmaverse/datacutr +datadictionary: + version: 1.0.0 + title: Create a Data Dictionary + maintainer: Bethany Jones + description: |- + Creates a data dictionary from any dataframe or tibble in your R environment. + You can opt to add variable labels. You can write the object directly to Excel. + date_publication: '2023-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datadictionary + url_git: '' +datadogr: + version: 0.1.2 + title: R Client for 'Datadog' API + maintainer: Hiroaki Yutani + description: Query for metrics from 'Datadog' () via + its API. + date_publication: '2018-05-17' + bug_reports: https://github.com/yutannihilation/K9/issues + url: https://yutannihilation.github.io/K9 + url_cran: https://CRAN.R-project.org/package=datadogr + url_git: '' +datadriftR: + version: 1.0.0 + title: Concept Drift Detection Methods for Stream Data + maintainer: Ugur Dar + description: |- + A system designed for detecting concept drift in streaming datasets. It offers a comprehensive suite of statistical methods to detect concept drift, including methods for monitoring changes in data distributions + over time. The package supports several tests, such as Drift Detection Method (DDM), Early Drift Detection Method (EDDM), Hoeffding Drift Detection Methods (HDDM_A, HDDM_W), Kolmogorov-Smirnov test-based Windowing (KSWIN) + and Page Hinkley (PH) tests. The methods implemented in this package are based on established research and have been demonstrated to be effective in real-time data analysis. For more details on the methods, + please check to the following sources. Kobylińska et al. (2023) , S. Kullback & R.A. Leibler (1951) , Gama et al. (2004) , Baena-Garcia et al. (2006) , + Frías-Blanco et al. (2014) , Raab et al. (2020) , Page (1954) , Montiel et al. (2018) . + date_publication: '2025-01-09' + bug_reports: https://github.com/ugurdar/datadriftR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datadriftR + url_git: https://github.com/ugurdar/datadriftR +DataEditR: + version: 0.1.5 + title: |- + An Interactive Editor for Viewing, Entering, Filtering & Editing + Data + maintainer: Dillon Hammill + description: |- + An interactive editor built on 'rhandsontable' to allow the + interactive viewing, entering, filtering and editing of data in R + . + date_publication: '2022-03-08' + bug_reports: https://github.com/DillonHammill/DataEditR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DataEditR + url_git: https://github.com/DillonHammill/DataEditR +DataExplorer: + version: 0.8.3 + title: Automate Data Exploration and Treatment + maintainer: Boxuan Cui + description: |- + Automated data exploration process for analytic tasks and predictive modeling, so + that users could focus on understanding data and extracting insights. The package scans and + analyzes each variable, and visualizes them with typical graphical techniques. Common + data processing methods are also available to treat and format data. + date_publication: '2024-01-24' + bug_reports: https://github.com/boxuancui/DataExplorer/issues + url: http://boxuancui.github.io/DataExplorer/ + url_cran: https://CRAN.R-project.org/package=DataExplorer + url_git: '' +DataFakeR: + version: 0.1.3 + title: Generate Fake Data for Relational Databases + maintainer: Krystian Igras + description: |- + Based on provided database description and/or database connection + generate data sample preserving source structure. + date_publication: '2023-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataFakeR + url_git: https://github.com/openpharma/DataFakeR +dataframeexplorer: + version: 1.0.2 + title: Familiarity with Dataframes Before Data Manipulation + maintainer: Ashrith Reddy + description: Real life data is muddy, fuzzy and unpredictable. This makes data manipulations + tedious and bringing the data to right shape alone is a major chunk of work. Functions + in this package help us get an understanding of dataframes to dramatically reduces + data coding time. + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dataframeexplorer + url_git: '' +datafsm: + version: 0.2.4 + title: Estimating Finite State Machine Models from Data + maintainer: Jonathan M. Gilligan + description: |- + Automatic generation of finite state machine models of dynamic + decision-making that both have strong predictive power and are + interpretable in human terms. We use an efficient model representation and + a genetic algorithm-based estimation process to generate simple + deterministic approximations that explain most of the structure of complex + stochastic processes. We have applied the software to empirical data, and + demonstrated it's ability to recover known data-generating processes by + simulating data with agent-based models and correctly deriving the + underlying decision models for multiple agent models and degrees of + stochasticity. + date_publication: '2021-05-29' + bug_reports: https://github.com/jonathan-g/datafsm/issues + url: https://jonathan-g.github.io/datafsm/ + url_cran: https://CRAN.R-project.org/package=datafsm + url_git: https://github.com/jonathan-g/datafsm +DataGraph: + version: 1.2.14 + title: Export Data from 'R' to 'DataGraph' + maintainer: David Adalsteinsson + description: Functions to pipe data from 'R' to 'DataGraph', a graphing and analysis + application for mac OS. Create a live connection using either '.dtable' or '.dtbin' + files that can be read by 'DataGraph'. Can save a data frame, collection of data + frames and sequences of data frames and individual vectors. For more information + see . + date_publication: '2023-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataGraph + url_git: '' +DataLoader: + version: '1.3' + title: Import Multiple File Types + maintainer: Srivenkatesh Gandhi + description: |- + Functions to import multiple files of multiple data file types ('.xlsx', '.xls', '.csv', '.txt') + from a given directory into R data frames. + date_publication: '2015-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataLoader + url_git: '' +dataMaid: + version: 1.4.1 + title: |- + A Suite of Checks for Identification of Potential Errors in a + Data Frame as Part of the Data Screening Process + maintainer: Claus Thorn Ekstrøm + description: |- + Data screening is an important first step of any statistical + analysis. dataMaid auto generates a customizable data report with a thorough + summary of the checks and the results that a human can use to identify possible + errors. It provides an extendable suite of test for common potential + errors in a dataset. + date_publication: '2021-10-08' + bug_reports: https://github.com/ekstroem/dataMaid/issues + url: https://doi.org/10.18637/jss.v090.i06 + url_cran: https://CRAN.R-project.org/package=dataMaid + url_git: https://github.com/ekstroem/dataMaid +datamedios: + version: 1.1.0 + title: Scraping Chilean Media + maintainer: Exequiel Trujillo + description: |- + A system for extracting news from Chilean media, + specifically through Web Scapping from Chilean media. The package allows for news searches using search phrases and date filters, + and returns the results in a structured format, ready for analysis. + Additionally, it includes functions to clean the extracted data, visualize it, and + store it in databases. All of this can be done automatically, facilitating the collection and analysis of relevant + information from Chilean media. + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datamedios + url_git: '' +dataMeta: + version: 0.1.1 + title: Create and Append a Data Dictionary for an R Dataset + maintainer: Dania M. Rodriguez + description: Designed to create a basic data dictionary and append to the original + dataset's attributes list. The package makes use of a tidy dataset and creates + a data frame that will serve as a linker that will aid in building the dictionary. + The dictionary is then appended to the list of the original dataset's attributes. + The user will have the option of entering variable and item descriptions by writing + code or use alternate functions that will prompt the user to add these. + date_publication: '2017-08-12' + bug_reports: https://github.com/dmrodz/dataMeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataMeta + url_git: https://github.com/dmrodz/dataMeta +DataMetProcess: + version: 1.0.3 + title: Meteorological Data Processing + maintainer: Wagner Martins dos Santos + description: Set of tools aimed at processing meteorological data, converting hourly + recorded data to daily, monthly and annual data. + date_publication: '2024-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataMetProcess + url_git: https://github.com/wagnnerms97/DataMetProcess +datamods: + version: 1.5.3 + title: Modules to Import and Manipulate Data in 'Shiny' + maintainer: Victor Perrier + description: |- + 'Shiny' modules to import data into an application or 'addin' + from various sources, and to manipulate them after that. + date_publication: '2024-10-02' + bug_reports: https://github.com/dreamRs/datamods/issues + url: https://dreamrs.github.io/datamods/ + url_cran: https://CRAN.R-project.org/package=datamods + url_git: https://github.com/dreamRs/datamods +dataMojo: + version: 1.0.0 + title: Reshape Data Table + maintainer: Jiena McLellan + description: A grammar of data manipulation with 'data.table', providing a consistent + a series of utility functions that help you solve the most common data manipulation + challenges. + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dataMojo + url_git: '' +datana: + version: 1.0.5 + title: Datasets and Functions to Accompany Analisis De Datos Con R + maintainer: Christian Salas-Eljatib + description: |- + Datasets and functions to accompany the book 'Analisis de datos con el programa + estadistico R: una introduccion aplicada' by Salas-Eljatib (2021, ISBN: 9789566086109). + The package helps carry out data management, exploratory analyses, and model fitting. + date_publication: '2024-09-07' + bug_reports: '' + url: https://eljatib.com/rlibro + url_cran: https://CRAN.R-project.org/package=datana + url_git: '' +datanugget: + version: 1.3.1 + title: Create, and Refine Data Nuggets + maintainer: Yajie Duan + description: |- + Creating, and refining data nuggets. + Data nuggets reduce a large dataset into a small collection of nuggets of + data, each containing a center (location), weight (importance), and scale + (variability) parameter. Data nugget centers are created by choosing + observations in the dataset which are as equally spaced apart as possible. + Data nugget weights are created by counting the number observations + closest to a given data nugget center. We then say the data nugget + 'contains' these observations and the data nugget center is recalculated + as the mean of these observations. Data nugget scales are created by + calculating the trace of the covariance matrix of the observations + contained within a data nugget divided by the dimension of the dataset. + Data nuggets are refined by 'splitting' data nuggets which have scales or + shapes (defined as the ratio of the two largest eigenvalues of the + covariance matrix of the observations contained within the data nugget) + Reference paper: [1] Beavers, T. E., Cheng, G., Duan, Y., Cabrera, J., Lubomirski, M., Amaratunga, D., & Teigler, J. E. (2024). Data Nuggets: A Method for Reducing Big Data While Preserving Data Structure. Journal of Computational and Graphical Statistics, 1-21. [2] Cherasia, K. E., Cabrera, J., Fernholz, L. T., & Fernholz, R. (2022). Data Nuggets in Supervised Learning. \emph{In Robust and Multivariate Statistical Methods: Festschrift in Honor of David E. Tyler} (pp. 429-449). Cham: Springer International Publishing. + date_publication: '2024-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datanugget + url_git: '' +dataonderivatives: + version: 0.4.0 + title: Easily Source Publicly Available Data on Derivatives + maintainer: Imanuel Costigan + description: |- + Post Global Financial Crisis derivatives reforms have lifted + the veil off over-the-counter (OTC) derivative markets. Swap Execution + Facilities (SEFs) and Swap Data Repositories (SDRs) now publish data + on swaps that are traded on or reported to those facilities + (respectively). This package provides you the ability to get this data + from supported sources. + date_publication: '2022-01-04' + bug_reports: https://github.com/imanuelcostigan/dataonderivatives/issues + url: http://imanuelcostigan.github.io/dataonderivatives/ + url_cran: https://CRAN.R-project.org/package=dataonderivatives + url_git: https://github.com/imanuelcostigan/dataonderivatives +dataone: + version: 2.2.2 + title: R Interface to the DataONE REST API + maintainer: Matthew B. Jones + description: |- + Provides read and write access to data and metadata from + the DataONE network of data repositories. + Each DataONE repository implements a consistent repository application + programming interface. Users call methods in R to access these remote + repository functions, such as methods to query the metadata catalog, get + access to metadata for particular data packages, and read the data objects + from the data repository. Users can also insert and update data objects on + repositories that support these methods. + date_publication: '2022-06-10' + bug_reports: https://github.com/DataONEorg/rdataone/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataone + url_git: https://github.com/DataONEorg/rdataone +datapack: + version: 1.4.1 + title: |- + A Flexible Container to Transport and Manipulate Data and + Associated Resources + maintainer: Matthew B. Jones + description: |- + Provides a flexible container to transport and manipulate complex + sets of data. These data may consist of multiple data files and associated + meta data and ancillary files. Individual data objects have associated system + level meta data, and data files are linked together using the OAI-ORE standard + resource map which describes the relationships between the files. The OAI- + ORE standard is described at . Data packages + can be serialized and transported as structured files that have been created + following the BagIt specification. The BagIt specification is described at + . + date_publication: '2022-06-10' + bug_reports: https://github.com/ropensci/datapack/issues + url: https://docs.ropensci.org/datapack/ + url_cran: https://CRAN.R-project.org/package=datapack + url_git: https://github.com/ropensci/datapack +DataPackageR: + version: 0.16.1 + title: Construct Reproducible Analytic Data Sets as R Packages + maintainer: Dave Slager + description: |- + A framework to help construct R data packages in a + reproducible manner. Potentially time consuming processing of raw data + sets into analysis ready data sets is done in a reproducible manner + and decoupled from the usual 'R CMD build' process so that data sets + can be processed into R objects in the data package and the data + package can then be shared, built, and installed by others without the + need to repeat computationally costly data processing. The package + maintains data provenance by turning the data processing scripts into + package vignettes, as well as enforcing documentation and version + checking of included data objects. Data packages can be version + controlled on 'GitHub', and used to share data for manuscripts, + collaboration and reproducible research. + date_publication: '2024-09-17' + bug_reports: https://github.com/ropensci/DataPackageR/issues + url: https://docs.ropensci.org/DataPackageR/ + url_cran: https://CRAN.R-project.org/package=DataPackageR + url_git: https://github.com/ropensci/DataPackageR +datapasta: + version: 3.1.0 + title: R Tools for Data Copy-Pasta + maintainer: Miles McBain + description: RStudio addins and R functions that make copy-pasting vectors and tables + to text painless. + date_publication: '2020-01-17' + bug_reports: https://github.com/milesmcbain/datapasta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datapasta + url_git: https://github.com/milesmcbain/datapasta +dataprep: + version: 0.1.5 + title: Efficient and Flexible Data Preprocessing Tools + maintainer: Chun-Sheng Liang + description: |- + Efficiently and flexibly preprocess data using a set of data filtering, deletion, and interpolation tools. + These data preprocessing methods are developed based on the principles of completeness, accuracy, threshold method, and linear interpolation and through the setting of constraint conditions, time completion & recovery, and fast & efficient calculation and grouping. + Key preprocessing steps include deletions of variables and observations, outlier removal, and missing values (NA) interpolation, which are dependent on the incomplete and dispersed degrees of raw data. + They clean data more accurately, keep more samples, and add no outliers after interpolation, compared with ordinary methods. + Auto-identification of consecutive NA via run-length based grouping is used in observation deletion, outlier removal, and NA interpolation; + thus, new outliers are not generated in interpolation. Conditional extremum is proposed to realize point-by-point weighed outlier removal that saves non-outliers from being removed. + Plus, time series interpolation with values to refer to within short periods further ensures reliable interpolation. + These methods are based on and improved from the reference: Liang, C.-S., Wu, H., Li, H.-Y., Zhang, Q., Li, Z. & He, K.-B. (2020) . + date_publication: '2022-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dataprep + url_git: '' +dataPreparation: + version: 1.1.1 + title: Automated Data Preparation + maintainer: Emmanuel-Lin Toulemonde + description: Do most of the painful data preparation for a data science project + with a minimum amount of code; Take advantages of 'data.table' efficiency and + use some algorithmic trick in order to perform data preparation in a time and + RAM efficient way. + date_publication: '2023-07-04' + bug_reports: https://github.com/ELToulemonde/dataPreparation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataPreparation + url_git: '' +dataquieR: + version: 2.5.0 + title: Data Quality in Epidemiological Research + maintainer: Stephan Struckmann + description: |- + Data quality assessments guided by a + 'data quality framework introduced by Schmidt and colleagues, 2021' + target the + data quality dimensions integrity, completeness, consistency, and + accuracy. The scope of applicable functions rests on the + availability of extensive metadata which can be provided in + spreadsheet tables. Either standardized (e.g. as 'html5' reports) or + individually tailored reports can be generated. For an introduction + into the specification of corresponding metadata, please refer to the + 'package website' + . + date_publication: '2025-02-20' + bug_reports: https://gitlab.com/libreumg/dataquier/-/issues + url: https://dataquality.qihs.uni-greifswald.de/ + url_cran: https://CRAN.R-project.org/package=dataquieR + url_git: '' +datardis: + version: 0.0.5 + title: Data from the Doctor Who Series + maintainer: Jonathan Kitt + description: Explore data related to the Doctor Who TV series. + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datardis + url_git: '' +dataReporter: + version: 1.0.2 + title: Reproducible Data Screening Checks and Report of Possible Errors + maintainer: Claus Thorn Ekstrøm + description: |- + Data screening is an important first step of any statistical + analysis. 'dataReporter' auto generates a customizable data report with a thorough + summary of the checks and the results that a human can use to identify possible + errors. It provides an extendable suite of test for common potential + errors in a dataset. See Petersen AH, Ekstrøm CT (2019). "dataMaid: Your Assistant for Documenting Supervised Data Quality Screening in R." _Journal of Statistical Software_, *90*(6), 1-38 for more information. + date_publication: '2021-11-11' + bug_reports: https://github.com/ekstroem/dataReporter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataReporter + url_git: https://github.com/ekstroem/dataReporter +dataresqc: + version: 1.1.1 + title: C3S Quality Control Tools for Historical Climate Data + maintainer: Yuri Brugnara + description: Quality control and formatting tools developed for the Copernicus Data + Rescue Service. The package includes functions to handle the Station Exchange + Format (SEF), various statistical tests for climate data at daily and sub-daily + resolution, as well as functions to plot the data. For more information and documentation + see . + date_publication: '2023-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dataresqc + url_git: '' +dataRetrieval: + version: 2.7.18 + title: |- + Retrieval Functions for USGS and EPA Hydrology and Water Quality + Data + maintainer: Laura DeCicco + description: |- + Collection of functions to help retrieve U.S. Geological Survey + and U.S. Environmental Protection Agency water quality and + hydrology data from web services. Data are discovered from + National Water Information System and . + Water quality data are obtained from the Water Quality Portal . + date_publication: '2025-02-27' + bug_reports: https://github.com/DOI-USGS/dataRetrieval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataRetrieval + url_git: '' +datarium: + version: 0.1.0 + title: Data Bank for Statistical Analysis and Visualization + maintainer: Alboukadel Kassambara + description: |- + Contains data organized by topics: categorical data, regression model, + means comparisons, independent and repeated measures ANOVA, mixed ANOVA and ANCOVA. + date_publication: '2019-05-21' + bug_reports: https://github.com/kassambara/datarium/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datarium + url_git: '' +datarobot: + version: 2.18.6 + title: '''DataRobot'' Predictive Modeling API' + maintainer: AJ Alon + description: For working with the 'DataRobot' predictive modeling platform's API + . + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datarobot + url_git: '' +datasailr: + version: 0.8.11 + title: Row by Row Data Processing Tool, Using 'DataSailr' Script + maintainer: Toshihiro Umehara + description: A row by row data processing tool. You can write data processing code + in 'DataSailr' script which is specially intended for data manipulation. The package + uses 'libsailr' (C/C++ library) for its 'DataSailr' code parsing and its execution. + date_publication: '2022-11-13' + bug_reports: https://github.com/niceume/datasailr + url: https://datasailr.io + url_cran: https://CRAN.R-project.org/package=datasailr + url_git: '' +datasauRus: + version: 0.1.9 + title: Datasets from the Datasaurus Dozen + maintainer: Colin Gillespie + description: |- + The Datasaurus Dozen is a set of datasets with the same + summary statistics. They retain the same summary statistics despite + having radically different distributions. The datasets represent a + larger and quirkier object lesson that is typically taught via + Anscombe's Quartet (available in the 'datasets' package). Anscombe's + Quartet contains four very different distributions with the same + summary statistics and as such highlights the value of visualisation + in understanding data, over and above summary statistics. As well as + being an engaging variant on the Quartet, the data is generated in a + novel way. The simulated annealing process used to derive datasets + from the original Datasaurus is detailed in "Same Stats, Different + Graphs: Generating Datasets with Varied Appearance and Identical + Statistics through Simulated Annealing" . + date_publication: '2025-01-23' + bug_reports: https://github.com/jumpingrivers/datasauRus/issues + url: https://jumpingrivers.github.io/datasauRus/ + url_cran: https://CRAN.R-project.org/package=datasauRus + url_git: https://github.com/jumpingrivers/datasauRus +dataSDA: + version: 0.1.0 + title: Data Sets for Symbolic Data Analysis + maintainer: Han-Ming Wu + description: Collects a diverse range of symbolic data and offers a comprehensive + set of functions that facilitate the conversion of traditional data into the symbolic + data format. + date_publication: '2023-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dataSDA + url_git: '' +dataseries: + version: 0.2.0 + title: Switzerland's Data Series in One Place + maintainer: Christoph Sax + description: Download and import time series from , a + comprehensive and up-to-date collection of open data from Switzerland. + date_publication: '2017-04-29' + bug_reports: https://github.com/christophsax/dataseries + url: http://www.dataseries.org + url_cran: https://CRAN.R-project.org/package=dataseries + url_git: '' +dataset: + version: 0.3.4 + title: Create Data Frames that are Easier to Exchange and Reuse + maintainer: Daniel Antal + description: |- + The aim of the 'dataset' package is to make tidy datasets easier to release, + exchange and reuse. It organizes and formats data frame 'R' objects into well-referenced, + well-described, interoperable datasets into release and reuse ready form. + date_publication: '2024-12-23' + bug_reports: https://github.com/dataobservatory-eu/dataset/issues/ + url: https://dataset.dataobservatory.eu/ + url_cran: https://CRAN.R-project.org/package=dataset + url_git: '' +datasetjson: + version: 0.3.0 + title: Read and Write CDISC Dataset JSON Files + maintainer: Mike Stackhouse + description: Read, construct and write CDISC (Clinical Data Interchange Standards + Consortium) Dataset JSON (JavaScript Object Notation) files, while validating + per the Dataset JSON schema file, as described in CDISC (2023) . + date_publication: '2025-01-30' + bug_reports: https://github.com/atorus-research/datasetjson/issues/ + url: https://atorus-research.github.io/datasetjson/ + url_cran: https://CRAN.R-project.org/package=datasetjson + url_git: '' +datasets.load: + version: 2.3.0 + title: Graphical Interface for Loading Datasets + maintainer: Bastiaan quast + description: Graphical interface for loading datasets in RStudio from all installed + (including unloaded) packages, also includes command line interfaces. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datasets.load + url_git: '' +datasetsICR: + version: '1.0' + title: Datasets from the Book "An Introduction to Clustering with R" + maintainer: Paolo Giordani + description: Companion to the book "An Introduction to Clustering with R" by P. + Giordani, M.B. Ferraro and F. Martella (Springer, Singapore, 2020). The datasets + are used in some case studies throughout the text. + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datasetsICR + url_git: '' +DataSetsUni: + version: '0.1' + title: A Collection of Univariate Data Sets + maintainer: Muhammad Imran + description: 'A collection of widely used univariate data sets of various applied + domains on applications of distribution theory. The functions allow researchers + and practitioners to quickly, easily, and efficiently access and use these data + sets. The data are related to different applied domains and as follows: Bio-medical, + survival analysis, medicine, reliability analysis, hydrology, actuarial science, + operational research, meteorology, extreme values, quality control, engineering, + finance, sports and economics. The total 100 data sets are documented along with + associated references for further details and uses.' + date_publication: '2023-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataSetsUni + url_git: '' +DataSpaceR: + version: 0.7.7 + title: Interface to 'the CAVD DataSpace' + maintainer: Jason Taylor + description: |- + Provides a convenient API interface to access immunological data + within 'the CAVD DataSpace'(), a data sharing + and discovery tool that facilitates exploration of HIV immunological data + from pre-clinical and clinical HIV vaccine studies. + date_publication: '2025-02-20' + bug_reports: https://github.com/ropensci/DataSpaceR/issues + url: https://docs.ropensci.org/DataSpaceR/ + url_cran: https://CRAN.R-project.org/package=DataSpaceR + url_git: https://github.com/ropensci/DataSpaceR +dataspice: + version: 1.1.0 + title: Create Lightweight Schema.org Descriptions of Data + maintainer: Bryce Mecum + description: |- + The goal of 'dataspice' is to make it easier for researchers to + create basic, lightweight, and concise metadata files for their datasets. + These basic files can then be used to make useful information available during + analysis, create a helpful dataset "README" webpage, and produce more complex + metadata formats to aid dataset discovery. Metadata fields are based on + the 'Schema.org' and 'Ecological Metadata Language' standards. + date_publication: '2021-05-16' + bug_reports: https://github.com/ropensci/dataspice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dataspice + url_git: https://github.com/ropensci/dataspice +DatAssim: + version: '1.0' + title: Data Assimilation + maintainer: Svetlana Saarela + description: For estimation of a variable of interest using Kalman filter by incorporating + results from previous assessments, i.e. through development weighted estimates + where weights are assigned inversely proportional to the variance of existing + and new estimates. For reference see Ehlers et al. (2017) . + date_publication: '2017-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DatAssim + url_git: '' +datastat: + version: 0.1.0 + title: Dataset for Statistical Analysis + maintainer: Atchanut Rattanalertnusorn + description: |- + Data are essential in statistical analysis. + This data package consists of four datasets for descriptive statistics, two datasets for statistical hypothesis testing, and two datasets for regression analysis. + All of the datasets are based on Rattanalertnusorn, A. (2024) . + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datastat + url_git: '' +datastepr: + version: 0.0.2 + title: An Implementation of a SAS-Style Data Step + maintainer: Brandon Taylor + description: |- + Based on a SAS data step. This allows for row-wise dynamic building + of data, iteratively importing slices of existing dataframes, conducting + analyses, and exporting to a results frame. This is particularly useful for + differential or time-series analyses, which are often not well suited to vector- + based operations. + date_publication: '2016-08-20' + bug_reports: https://github.com/bramtayl/datastepr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datastepr + url_git: https://github.com/bramtayl/datastepr +DatastreamDSWS2R: + version: 1.9.10 + title: Provides a Link Between the 'LSEG Datastream' System and R + maintainer: Charles Cara + description: |- + Provides a set of functions and a class to connect, extract and + upload information from the 'LSEG Datastream' database. This + package uses the 'DSWS' API and server used by the 'Datastream DFO addin'. + Details of this API are available at . + Please report issues at . + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DatastreamDSWS2R + url_git: '' +DatastreamR: + version: 2.0.4 + title: Datastream API + maintainer: LSEG (Datastream) + description: Access Datastream content through ., + our historical financial database with over 35 million individual instruments + or indicators across all major asset classes, including over 19 million active + economic indicators. It features 120 years of data, across 175 countries – the + information you need to interpret market trends, economic cycles, and the impact + of world events. Data spans bond indices, bonds, commodities, convertibles, + credit default swaps, derivatives, economics, energy, equities, equity indices, + ESG, estimates, exchange rates, fixed income, funds, fundamentals, interest rates, + and investment trusts. Unique content includes I/B/E/S Estimates, Worldscope Fundamentals, + point-in-time data, and Reuters Polls. Alongside the content, sit a set of + powerful analytical tools for exploring relationships between different asset + types, with a library of customizable analytical functions. In-house timeseries + can also be uploaded using the package to comingle with Datastream maintained + datasets, use with these analytical tools and displayed in Datastream’s flexible + charting facilities in Microsoft Office. + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DatastreamR + url_git: '' +DataSum: + version: 0.1.0 + title: Comprehensive Data Summarization for Statistical Analysis + maintainer: Uzair Javid Khan + description: Summarizing data frames by calculating various statistical measures, + including measures of central tendency, dispersion, skewness(), kurtosis(), and + normality tests. The package leverages the 'moments' package for calculating statistical + moments and related measures, the 'dplyr' package for data manipulation, and the + 'nortest' package for normality testing. 'DataSum' includes functions such as + getmode() for finding the mode(s) of a data vector, shapiro_normality_test() for + performing the Shapiro-Wilk test (Shapiro & Wilk 1965 ) + (or the Anderson-Darling test when the data length is outside the valid range + for the Shapiro-Wilk test) (Stephens 1974 ), + Datum() for generating a comprehensive summary of a data vector with various statistics + (including data type, sample size, mean, mode, median, variance, standard deviation, + maximum, minimum, range, skewness(), kurtosis(), and normality test result) (Joanes + & Gill 1998 ), and DataSumm() for applying the Datum() + function to each column of a data frame. Emphasizing the importance of normality + testing, the package provides robust tools to validate whether data follows a + normal distribution, a fundamental assumption in many statistical analyses and + models. + date_publication: '2024-08-28' + bug_reports: https://github.com/Uzairkhan11w/DataSum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DataSum + url_git: https://github.com/Uzairkhan11w/DataSum +dataverifyr: + version: 0.1.8 + title: |- + A Lightweight, Flexible, and Fast Data Validation Package that + Can Handle All Sizes of Data + maintainer: David Zimmermann-Kollenda + description: |- + Allows you to define rules which can be used to verify a given + dataset. + The package acts as a thin wrapper around more powerful data packages such + as 'dplyr', 'data.table', 'arrow', and 'DBI' ('SQL'), which do the heavy lifting. + date_publication: '2024-01-10' + bug_reports: https://github.com/DavZim/dataverifyr/issues + url: https://davzim.github.io/dataverifyr/ + url_cran: https://CRAN.R-project.org/package=dataverifyr + url_git: https://github.com/DavZim/dataverifyr +dataverse: + version: 0.3.14 + title: Client for Dataverse 4+ Repositories + maintainer: Shiro Kuriwaki + description: |- + Provides access to Dataverse APIs (versions 4-5), + enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0, + use the archived 'dvn' package . + date_publication: '2024-05-13' + bug_reports: https://github.com/iqss/dataverse-client-r/issues + url: https://iqss.github.io/dataverse-client-r/ + url_cran: https://CRAN.R-project.org/package=dataverse + url_git: https://github.com/iqss/dataverse-client-r +DataVisualizations: + version: 1.3.3 + title: Visualizations of High-Dimensional Data + maintainer: Michael Thrun + description: 'Gives access to data visualisation methods that are relevant from + the data scientist''s point of view. The flagship idea of ''DataVisualizations'' + is the mirrored density plot (MD-plot) for either classified or non-classified + multivariate data published in Thrun, M.C. et al.: "Analyzing the Fine Structure + of Distributions" (2020), PLoS ONE, . The MD-plot + outperforms the box-and-whisker diagram (box plot), violin plot and bean plot + and geom_violin plot of ggplot2. Furthermore, a collection of various visualization + methods for univariate data is provided. In the case of exploratory data analysis, + ''DataVisualizations'' makes it possible to inspect the distribution of each feature + of a dataset visually through a combination of four methods. One of these methods + is the Pareto density estimation (PDE) of the probability density function (pdf). + Additionally, visualizations of the distribution of distances using PDE, the scatter-density + plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman + plot are presented here. Pertaining to classified high-dimensional data, a number + of visualizations are described, such as f.ex. the heat map and silhouette plot. + A political map of the world or Germany can be visualized with the additional + information defined by a classification of countries or regions. By extending + the political map further, an uncomplicated function for a Choropleth map can + be used which is useful for measurements across a geographic area. For categorical + features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, + become usable. More detailed explanations are found in the book by Thrun, M.C.: + "Projection-Based Clustering through Self-Organization and Swarm Intelligence" + (2018) .' + date_publication: '2025-01-26' + bug_reports: https://github.com/Mthrun/DataVisualizations/issues + url: https://www.deepbionics.org/ + url_cran: https://CRAN.R-project.org/package=DataVisualizations + url_git: '' +DataViz: + version: 0.2.8 + title: Data Visualisation Using an HTML Page and 'D3.js' + maintainer: Timothy Bell + description: Gives access to data visualisation methods that are relevant from the + statistician's point of view. Using 'D3''s existing data visualisation tools to + empower R language and environment. The throw chart method is a line chart used + to illustrate paired data sets (such as before-after, male-female). + date_publication: '2019-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DataViz + url_git: '' +datawizard: + version: 1.0.0 + title: Easy Data Wrangling and Statistical Transformations + maintainer: Etienne Bacher + description: |- + A lightweight package to assist in key steps involved in any data + analysis workflow: (1) wrangling the raw data to get it in the needed form, + (2) applying preprocessing steps and statistical transformations, and + (3) compute statistical summaries of data properties and distributions. + It is also the data wrangling backend for packages in 'easystats' ecosystem. + References: Patil et al. (2022) . + date_publication: '2025-01-10' + bug_reports: https://github.com/easystats/datawizard/issues + url: https://easystats.github.io/datawizard/ + url_cran: https://CRAN.R-project.org/package=datawizard + url_git: '' +datazoom.amazonia: + version: 1.1.0 + title: Simplify Access to Data from the Amazon Region + maintainer: Igor Rigolon Veiga + description: |- + Functions to download and treat data regarding the Brazilian + Amazon region from a variety of official sources. + date_publication: '2023-12-12' + bug_reports: '' + url: https://www.econ.puc-rio.br/datazoom/ + url_cran: https://CRAN.R-project.org/package=datazoom.amazonia + url_git: '' +date: + version: 1.2-42 + title: Functions for Handling Dates + maintainer: Kurt Hornik + description: Functions for handling dates. + date_publication: '2023-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=date + url_git: '' +dateback: + version: 1.0.5 + title: |- + Collect and Install R Packages on a Specified Date with + Dependencies + maintainer: Ryota Suzuki + description: |- + Works as a virtual CRAN snapshot for source packages. + It automatically downloads and installs 'tar.gz' files with dependencies, + all of which were available on a specific day. + date_publication: '2024-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dateback + url_git: https://github.com/r-suzuki/dateback +datefixR: + version: 1.7.0 + title: Standardize Dates in Different Formats or with Missing Data + maintainer: Nathan Constantine-Cooke + description: |- + There are many different formats dates are commonly + represented with: the order of day, month, or year can differ, + different separators ("-", "/", or whitespace) can be used, months can + be numerical, names, or abbreviations and year given as two digits or + four. 'datefixR' takes dates in all these different formats and + converts them to R's built-in date class. If 'datefixR' cannot + standardize a date, such as because it is too malformed, then the user + is told which date cannot be standardized and the corresponding ID for + the row. 'datefixR' also allows the imputation of missing days and + months with user-controlled behavior. + date_publication: '2024-09-08' + bug_reports: https://github.com/ropensci/datefixR/issues + url: https://docs.ropensci.org/datefixR/ + url_cran: https://CRAN.R-project.org/package=datefixR + url_git: https://github.com/ropensci/datefixR +daterangepicker: + version: 0.2.0 + title: Create a Shiny Date-Range Input + maintainer: Sebastian Gatscha + description: A Shiny Input for date-ranges, which pops up two calendars for selecting + dates, times, or predefined ranges like "Last 30 Days". It wraps the JavaScript + library 'daterangepicker' which is available at . + date_publication: '2023-05-10' + bug_reports: https://github.com/trafficonese/daterangepicker/issues + url: https://www.daterangepicker.com + url_cran: https://CRAN.R-project.org/package=daterangepicker + url_git: https://github.com/trafficonese/daterangepicker/ +datetime: + version: 0.1.4 + title: Nominal Dates, Times, and Durations + maintainer: Tim Bergsma + description: |- + Provides methods for working with nominal dates, times, and + durations. Base R has sophisticated facilities for handling time, but these + can give unexpected results if, for example, timezone is not handled properly. + This package provides a more casual approach to support cases which + do not require rigorous treatment. It systematically deconstructs the + concepts origin and timezone, and de-emphasizes the display of seconds. It + also converts among nominal durations such as seconds, hours, days, and weeks. + See '?datetime' and '?duration' for examples. Adapted from 'metrumrg' + . + date_publication: '2018-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datetime + url_git: '' +datetimeoffset: + version: 0.4.1 + title: |- + Datetimes with Optional UTC Offsets and/or Heterogeneous Time + Zones + maintainer: Trevor L. Davis + description: |- + Supports import/export for a number of datetime string standards + and R datetime classes often including + lossless re-export of + any original reduced precision including 'ISO 8601' and + 'pdfmark' datetime strings. + Supports local/global datetimes with optional UTC offsets and/or (possibly heterogeneous) time zones + with up to nanosecond precision. + date_publication: '2025-01-11' + bug_reports: https://github.com/trevorld/r-datetimeoffset/issues + url: https://trevorldavis.com/R/datetimeoffset/ + url_cran: https://CRAN.R-project.org/package=datetimeoffset + url_git: https://github.com/trevorld/r-datetimeoffset +DateTimeRangePicker: + version: 1.1.0 + title: A Datetime Range Picker Widget for Usage in 'Shiny' Applications + maintainer: Stéphane Laurent + description: |- + Provides a datetime range picker widget for usage in 'Shiny'. + It creates a calendar allowing to select a start date and an end date + as well as two fields allowing to select a start time and an end time. + date_publication: '2023-09-03' + bug_reports: https://github.com/stla/DateTimeRangePicker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DateTimeRangePicker + url_git: https://github.com/stla/DateTimeRangePicker +datetimeutils: + version: 0.6-4 + title: Utilities for Dates and Times + maintainer: Enrico Schumann + description: |- + Utilities for handling dates and times, such + as selecting particular days of the week or month, + formatting timestamps as required by RSS feeds, or + converting timestamp representations of other software + (such as 'MATLAB' and 'Excel') to R. The package is + lightweight (no dependencies, pure R implementations) and + relies only on R's standard classes to represent dates + and times ('Date' and 'POSIXt'); it aims to provide + efficient implementations, through vectorisation and the + use of R's native numeric representations of timestamps + where possible. + date_publication: '2024-04-01' + bug_reports: '' + url: http://enricoschumann.net/R/packages/datetimeutils/ + url_cran: https://CRAN.R-project.org/package=datetimeutils + url_git: https://github.com/enricoschumann/datetimeutils +datetoiso: + version: 0.2.0 + title: |- + Modify Dates to ISO Standard ("International Organization for + Standardization") + maintainer: Lukasz Andrzejewski + description: Transfer any date type to ISO standard. Package recognizes dates in + given data frame and transform to ISO format. Only one date format can be applied + within one data frame column. + date_publication: '2023-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=datetoiso + url_git: https://github.com/andzoluk +dateutils: + version: 0.1.5 + title: Date Utils + maintainer: Seth Leonard + description: Utilities for mixed frequency data. In particular, use to aggregate + and normalize tabular mixed frequency data, index dates to end of period, and + seasonally adjust tabular data. + date_publication: '2021-11-10' + bug_reports: https://github.com/macroeconomicdata/dateutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dateutils + url_git: https://github.com/macroeconomicdata/dateutils +datoramar: + version: 0.1.0 + title: Interface to the 'Datorama' API + maintainer: Kade Killary + description: |- + A thin wrapper around the 'Datorama' API. + Ideal for analyzing marketing data from . + date_publication: '2017-12-20' + bug_reports: https://github.com/beigebrucewayne/datoramar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datoramar + url_git: https://github.com/beigebrucewayne/datoramar +datos: + version: 0.5.1 + title: Traduce al Español Varios Conjuntos de Datos de Práctica + maintainer: Riva Quiroga + description: |- + Provee una versión traducida de los siguientes + conjuntos de datos: 'airlines', 'airports', 'AwardsManagers', + 'babynames', 'Batting', 'credit_data', 'diamonds', 'faithful', 'fueleconomy', + 'Fielding', 'flights', 'gapminder', 'gss_cat', 'iris', 'Managers', + 'mpg', 'mtcars', 'atmos', 'palmerpenguins', 'People, 'Pitching', 'planes', + 'presidential', 'table1', 'table2', 'table3', 'table4a', 'table4b', + 'table5', 'vehicles', 'weather', 'who'. English: It provides a + Spanish translated version of the datasets listed above. + date_publication: '2023-07-17' + bug_reports: https://github.com/cienciadedatos/datos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datos + url_git: https://github.com/cienciadedatos/datos +datplot: + version: 1.1.1 + title: |- + Preparation of Object Dating Ranges for Density Plots (Aoristic + Analysis) + maintainer: Lisa Steinmann + description: |- + Converting date ranges into dating 'steps' eases the + visualization of changes in e.g. pottery consumption, style and other + variables over time. This package provides tools to process and + prepare data for visualization and employs the concept of aoristic + analysis. + date_publication: '2023-11-18' + bug_reports: https://github.com/lsteinmann/datplot/issues + url: https://lsteinmann.github.io/datplot/ + url_cran: https://CRAN.R-project.org/package=datplot + url_git: https://github.com/lsteinmann/datplot +datr: + version: 0.1.0 + title: '''Dat'' Protocol Interface' + maintainer: Chris Hartgerink + description: Interface with the 'Dat' p2p network protocol . + Clone archives from the network, share your own files, and install packages from + the network. + date_publication: '2018-03-26' + bug_reports: https://github.com/libscie/datr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datr + url_git: https://github.com/libscie/datr +datrProfile: + version: 0.1.0 + title: Column Profile for Tables and Datasets + maintainer: Arnaldo Vitaliano + description: |- + Profiles datasets (collecting statistics and informative summaries + about that data) on data frames and 'ODBC' tables: maximum, minimum, mean, standard deviation, nulls, + distinct values, data patterns, data/format frequencies. + date_publication: '2019-08-02' + bug_reports: https://github.com/avitaliano/datrProfile/issues + url: '' + url_cran: https://CRAN.R-project.org/package=datrProfile + url_git: https://github.com/avitaliano/datrProfile +dauphin: + version: 0.3.2 + title: Compact Standard for Australian Phone Numbers + maintainer: Hugh Parsonage + description: |- + Phone numbers are often represented as strings because there + is no obvious and suitable native representation for them. This leads + to high memory use and a lack of standard representation. The package + provides integer representation of Australian phone numbers with optional + raw vector calling code. The package name is an extension of 'au' and 'ph'. + date_publication: '2024-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dauphin + url_git: '' +Davies: + version: 1.2-0 + title: The Davies Quantile Function + maintainer: Robin K. S. Hankin + description: Various utilities for the Davies distribution. + date_publication: '2022-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Davies + url_git: '' +dawai: + version: 1.2.7 + title: Discriminant Analysis with Additional Information + maintainer: David Conde + description: |- + In applications it is usual that some additional information is available. This package dawai (an acronym + for Discriminant Analysis With Additional Information) performs linear and quadratic discriminant analysis with + additional information expressed as inequality restrictions among the populations means. It also computes several + estimations of the true error rate. + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dawai + url_git: '' +dawaR: + version: 0.3.0 + title: An API Wrapper for 'DAWA' - 'The Danish Address Web API' + maintainer: Aleksander Bang-Larsen + description: |- + Functions for interacting with all sections of + the official 'Danish Address Web API' (also known as 'DAWA') + . The development of this package is + completely independent from the government agency, Klimadatastyrelsen, + who maintains the API. + date_publication: '2025-02-13' + bug_reports: https://github.com/aleksanderbl29/dawaR/issues + url: https://dawar.aleksanderbl.dk/ + url_cran: https://CRAN.R-project.org/package=dawaR + url_git: https://github.com/aleksanderbl29/dawaR +daymetr: + version: 1.7.1 + title: Interface to the 'Daymet' Web Services + maintainer: Koen Hufkens + description: |- + Programmatic interface to the 'Daymet' web services + (). Allows for easy downloads of + 'Daymet' climate data directly to your R workspace or your computer. + Routines for both single pixel data downloads and + gridded (netCDF) data are provided. + date_publication: '2023-09-15' + bug_reports: https://github.com/bluegreen-labs/daymetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=daymetr + url_git: https://github.com/bluegreen-labs/daymetr +daySupply: + version: 0.1.0 + title: Calculating Days' Supply and Daily Dose of Prescriptions + maintainer: Abdollah Safari + description: 'Allows clinicians and researchers to compute daily dose (and subsequently + days'' supply) for prescription refills using the following methods: Fixed window, + fixed tablet, defined daily dose (DDD), and Random Effects Warfarin Days'' Supply + (REWarDS). Daily dose is the computed dose that the patient takes every day. For + medications with fixed dosing (e.g. direct oral anticoagulants) this is known + and does not need to be estimated. For medications with varying dose such as warfarin, + however, the daily dose should be assumed or estimated to allow measurement of + drug exposure. Days’ supply is the number of days that patients’ supply of medication + will last after each prescription fill. Estimating days’ supply is necessary to + calculate drug exposure. The package computes days’ supply and daily dose at both + the prescription and patient levels. Results at the prescription level are denoted + with “-Rx-” and those at patient level are denoted with “-Pt-”.' + date_publication: '2021-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=daySupply + url_git: '' +dbacf: + version: 0.2.8 + title: Autocovariance Estimation via Difference-Based Methods + maintainer: Inder Tecuapetla-Gómez + description: |- + Provides methods for (auto)covariance/correlation function estimation + in change point regression with stationary errors circumventing the pre-estimation + of the underlying signal of the observations. Generic, first-order, (m+1)-gapped, + difference-based autocovariance function estimator is based on M. Levine and I. Tecuapetla-Gómez (2023) . Bias-reducing, second-order, (m+1)-gapped, + difference-based estimator is based on I. Tecuapetla-Gómez and A. Munk (2017) + . Robust autocovariance estimator for change point regression with autoregressive errors is based on S. Chakar et al. (2017) . + It also includes a general projection-based method for covariance matrix estimation. + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbacf + url_git: '' +dbarts: + version: 0.9-30 + title: Discrete Bayesian Additive Regression Trees Sampler + maintainer: Vincent Dorie + description: Fits Bayesian additive regression trees (BART; Chipman, George, and + McCulloch (2010) ) while allowing the updating of predictors + or response so that BART can be incorporated as a conditional model in a Gibbs/Metropolis-Hastings + sampler. Also serves as a drop-in replacement for package 'BayesTree'. + date_publication: '2024-12-03' + bug_reports: https://github.com/vdorie/dbarts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbarts + url_git: https://github.com/vdorie/dbarts +dbcsp: + version: 0.0.2.1 + title: Distance-Based Common Spatial Patterns + maintainer: Itsaso Rodríguez-Moreno + description: |- + A way to apply Distance-Based Common Spatial Patterns + (DB-CSP) techniques in different fields, both classical Common Spatial + Patterns (CSP) as well as DB-CSP. The method is composed of two + phases: applying the DB-CSP algorithm and performing a classification. + The main idea behind the CSP is to use a linear transform to project + data into low-dimensional subspace with a projection matrix, in such a + way that each row consists of weights for signals. This transformation + maximizes the variance of two-class signal matrices.The dbcsp object + is created to compute the projection vectors. For exploratory and + descriptive purpose, plot and boxplot functions can be used. Functions + train, predict and selectQ are implemented for the classification + step. + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbcsp + url_git: '' +DBCVindex: + version: '1.4' + title: Calculates the Density-Based Clustering Validation (DBCV) Index + maintainer: Davide Chicco + description: 'A metric called ''Density-Based Clustering Validation index'' (DBCV) + index to evaluate clustering results, following the + ''R'' implementation by Pablo Andretta Jaskowiak. Original ''DBCV'' index article: + Moulavi, D., Jaskowiak, P. A., Campello, R. J., Zimek, A., and Sander, J. (April + 2014), "Density-based clustering validation", Proceedings of SDM 2014 -- the 2014 + SIAM International Conference on Data Mining (pp. 839-847), .' + date_publication: '2025-02-19' + bug_reports: https://github.com/davidechicco/DBCVindex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DBCVindex + url_git: https://github.com/davidechicco/DBCVindex +dbd: + version: 0.0-22 + title: Discretised Beta Distribution + maintainer: Rolf Turner + description: |- + Tools for working with a new versatile + discrete distribution, the db ("discretised Beta") + distribution. This package provides density (probability), + distribution, inverse distribution (quantile) and random + data generation functions for the db family. It provides + functions to effect conveniently maximum likelihood + estimation of parameters, and a variety of useful plotting + functions. It provides goodness of fit tests and functions + to calculate the Fisher information, different estimates of + the hessian of the log likelihood and Monte Carlo estimation + of the covariance matrix of the maximum likelihood parameter + estimates. In addition it provides analogous tools for + working with the beta-binomial distribution which has been + proposed as a competitor to the db distribution. + date_publication: '2021-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbd + url_git: '' +DBEST: + version: '1.8' + title: Detecting Breakpoints and Estimating Segments in Trend + maintainer: Hristo Tomov + description: 'A program for analyzing vegetation time series, with two algorithms: + 1) change detection algorithm that detects trend changes, determines their type + (abrupt or non-abrupt), and estimates their timing, magnitude, number, and direction; + 2) generalization algorithm that simplifies the temporal trend into main features. + The user can set the number of major breakpoints or magnitude of greatest changes + of interest for detection, and can control the generalization process by setting + an additional parameter of generalization-percentage.' + date_publication: '2017-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBEST + url_git: '' +DBfit: + version: '2.0' + title: |- + A Double Bootstrap Method for Analyzing Linear Models with + Autoregressive Errors + maintainer: Shaofeng Zhang + description: |- + Computes the double bootstrap as discussed in McKnight, McKean, and Huitema (2000) . + The double bootstrap method provides a better fit for a linear model with autoregressive errors than ARIMA when the sample size is small. + date_publication: '2021-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBfit + url_git: '' +dbflobr: + version: 0.2.2 + title: Read and Write Files to SQLite Databases + maintainer: Evan Amies-Galonski + description: |- + Reads and writes files to SQLite databases + as flobs (a flob is a blob that + preserves the file extension). + date_publication: '2022-08-19' + bug_reports: https://github.com/poissonconsulting/dbflobr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbflobr + url_git: https://github.com/poissonconsulting/dbflobr +dbGaPCheckup: + version: 1.1.0 + title: dbGaP Checkup + maintainer: Lacey W. Heinsberg + description: Contains functions that check for formatting of the Subject Phenotype + data set and data dictionary as specified by the National Center for Biotechnology + Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) . + date_publication: '2023-09-27' + bug_reports: https://github.com/lwheinsberg/dbGaPCheckup/issues + url: https://lwheinsberg.github.io/dbGaPCheckup/ + url_cran: https://CRAN.R-project.org/package=dbGaPCheckup + url_git: https://github.com/lwheinsberg/dbGaPCheckup +dbglm: + version: 1.0.0 + title: Generalised Linear Models by Subsampling and One-Step Polishing + maintainer: Shangqing Cao + description: Fast fitting of generalised linear models on moderately large datasets, + by taking an initial sample, fitting in memory, then evaluating the score function + for the full data in the database. Thomas Lumley . + date_publication: '2021-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbglm + url_git: '' +DBHC: + version: 0.0.3 + title: Sequence Clustering with Discrete-Output HMMs + maintainer: Gabriel Budel + description: |- + Provides an implementation of a mixture of hidden Markov models + (HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering + (DBHC) algorithm. The DBHC algorithm is an HMM Clustering + algorithm that finds a mixture of discrete-output HMMs while using + heuristics based on Bayesian Information Criterion (BIC) to search for the + optimal number of HMM states and the optimal number of clusters. + date_publication: '2022-12-22' + bug_reports: https://github.com/gabybudel/DBHC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DBHC + url_git: https://github.com/gabybudel/DBHC +dbhydroR: + version: 0.2-8 + title: '''DBHYDRO'' Hydrologic and Water Quality Data' + maintainer: Joseph Stachelek + description: |- + Client for programmatic access to the South Florida Water + Management District's 'DBHYDRO' database at + , with functions + for accessing hydrologic and water quality data. + date_publication: '2021-02-21' + bug_reports: https://github.com/ropensci/dbhydroR/issues + url: https://docs.ropensci.org/dbhydroR/ + url_cran: https://CRAN.R-project.org/package=dbhydroR + url_git: https://github.com/ropensci/dbhydroR +DBI: + version: 1.2.3 + title: R Database Interface + maintainer: Kirill Müller + description: |- + A database interface definition for communication between R + and relational database management systems. All classes in this + package are virtual and need to be extended by the various R/DBMS + implementations. + date_publication: '2024-06-02' + bug_reports: https://github.com/r-dbi/DBI/issues + url: https://dbi.r-dbi.org + url_cran: https://CRAN.R-project.org/package=DBI + url_git: https://github.com/r-dbi/DBI +dbi.table: + version: 1.0.3 + title: Database Queries Using 'data.table' Syntax + maintainer: Kjell P. Konis + description: |- + Query database tables over a 'DBI' connection using 'data.table' syntax. + Attach database schemas to the search path. Automatically merge using foreign + key constraints. + date_publication: '2025-02-04' + bug_reports: https://github.com/kjellpk/dbi.table/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbi.table + url_git: https://github.com/kjellpk/dbi.table +DBItest: + version: 1.8.2 + title: Testing DBI Backends + maintainer: Kirill Müller + description: |- + A helper that tests DBI back ends for conformity to the + interface. + date_publication: '2024-12-07' + bug_reports: https://github.com/r-dbi/DBItest/issues + url: https://dbitest.r-dbi.org + url_cran: https://CRAN.R-project.org/package=DBItest + url_git: https://github.com/r-dbi/DBItest +dblcens: + version: 1.1.9 + title: |- + Compute the NPMLE of Distribution Function from Doubly Censored + Data, Plus the Empirical Likelihood Ratio for F(T) + maintainer: Yifan Yang + description: 'Doubly censored data, as described in Chang and Yang (1987) ), are commonly seen in many fields. We use EM algorithm + to compute the non-parametric MLE (NPMLE) of the cummulative probability function/survival + function and the two censoring distributions. One can also specify a constraint + F(T)=C, it will return the constrained NPMLE and the -2 log empirical likelihood + ratio for this constraint. This can be used to test the hypothesis about the constraint + and, by inverting the test, find confidence intervals for probability or quantile + via empirical likelihood ratio theorem. Influence functions of hat F may also + be calculated, but currently, the it may be slow.' + date_publication: '2023-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dblcens + url_git: https://github.com/yfyang86/dblcens/ +dBlockmodeling: + version: 0.2.3 + title: |- + Deterministic Blockmodeling of Signed, One-Mode and Two-Mode + Networks + maintainer: Aleš Žiberna + description: It contains functions to apply blockmodeling of signed (positive and + negative weights are assigned to the links), one-mode and valued one-mode and + two-mode (two sets of nodes are considered, e.g. employees and organizations) + networks (Brusco et al. (2019) ). + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dBlockmodeling + url_git: '' +dblr: + version: 0.1.0 + title: Discrete Boosting Logistic Regression + maintainer: Nailong Zhang + description: |- + Trains logistic regression model by discretizing continuous variables via gradient boosting approach. The proposed method tries to achieve a tradeoff between interpretation and prediction accuracy for logistic regression by discretizing the continuous variables. The variable binning is accomplished in a supervised fashion. The model trained by this package is still a single + logistic regression model, but not a sequence of logistic regression models. The fitted model + object returned from the model training consists of two tables. One table is used to give the + boundaries of bins for each continuous variable as well as the corresponding coefficients, + and the other one is used for discrete variables. This package can also be used for binning + continuous variables for other statistical analysis. + date_publication: '2017-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dblr + url_git: '' +dbMC: + version: 1.0.0 + title: |- + Confidence Interval for Matrix Completion via De-Biased + Estimator + maintainer: The Tien Mai + description: 'Implements the de-biased estimator for low-rank matrix completion + and provides confidence intervals for entries of interest. See: by Chen et al. + (2019) , Mai (2021) .' + date_publication: '2021-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbMC + url_git: '' +DBModelSelect: + version: 0.2.0 + title: Distribution-Based Model Selection + maintainer: Scott H. Koeneman + description: |- + Perform model selection using distribution and probability-based methods, + including standardized AIC, BIC, and AICc. These standardized information criteria + allow one to perform model selection in a way similar to the prevalent "Rule of 2" + method, but formalize the method to rely on probability theory. A novel goodness-of-fit + procedure for assessing linear regression models is also available. This test relies on + theoretical properties of the estimated error variance for a normal linear regression + model, and employs a bootstrap procedure to assess the null hypothesis that the fitted + model shows no lack of fit. For more information, see Koeneman and Cavanaugh (2023) + . Functionality to perform all subsets linear or generalized linear + regression is also available. + date_publication: '2023-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBModelSelect + url_git: https://github.com/shkoeneman/DBModelSelect +dbmss: + version: 2.9-2 + title: Distance-Based Measures of Spatial Structures + maintainer: Eric Marcon + description: |- + Simple computation of spatial statistic functions of distance to characterize the spatial structures of mapped objects, following Marcon, Traissac, Puech, and Lang (2015) . + Includes classical functions (Ripley's K and others) and more recent ones used by spatial economists (Duranton and Overman's Kd, Marcon and Puech's M). + Relies on 'spatstat' for some core calculation. + date_publication: '2024-08-24' + bug_reports: https://github.com/EricMarcon/dbmss/issues/ + url: https://ericmarcon.github.io/dbmss/ + url_cran: https://CRAN.R-project.org/package=dbmss + url_git: https://github.com/EricMarcon/dbmss/ +dbnlearn: + version: 0.1.0 + title: |- + Dynamic Bayesian Network Structure Learning, Parameter Learning + and Forecasting + maintainer: Robson Fernandes + description: |- + It allows to learn the structure of univariate time series, learning parameters and forecasting. + Implements a model of Dynamic Bayesian Networks with temporal windows, + with collections of linear regressors for Gaussian nodes, + based on the introductory texts of Korb and Nicholson (2010) and + Nagarajan, Scutari and Lèbre (2013) . + date_publication: '2020-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbnlearn + url_git: '' +DBNMFrank: + version: 0.1.0 + title: Rank Selection for Non-Negative Matrix Factorization + maintainer: Yun Cai + description: Given the non-negative data and its distribution, the package estimates + the rank parameter for Non-negative Matrix Factorization. The method is based + on hypothesis testing, using a deconvolved bootstrap distribution to assess the + significance level accurately despite the large amount of optimization error. + The distribution of the non-negative data can be either Normal distributed or + Poisson distributed. + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBNMFrank + url_git: '' +dbnR: + version: 0.7.9 + title: Dynamic Bayesian Network Learning and Inference + maintainer: David Quesada + description: |- + Learning and inference over dynamic Bayesian networks of arbitrary + Markovian order. Extends some of the functionality offered by the 'bnlearn' + package to learn the networks from data and perform exact inference. + It offers three structure learning algorithms for dynamic Bayesian networks: + Trabelsi G. (2013) , Santos F.P. and Maciel C.D. (2014) + , Quesada D., Bielza C. and Larrañaga P. (2021) + . It also offers the possibility to perform + forecasts of arbitrary length. A tool for visualizing the structure of the + net is also provided via the 'visNetwork' package. + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbnR + url_git: https://github.com/dkesada/dbnR +dbparser: + version: 2.0.3 + title: Drugs Databases Parser + maintainer: Mohammed Ali + description: |- + This tool is for parsing public drug databases such as 'DrugBank' XML database . + The parsed data are then returned in a proper 'R' object called 'dvobject'. + date_publication: '2024-04-20' + bug_reports: https://github.com/ropensci/dbparser/issues + url: https://docs.ropensci.org/dbparser/ + url_cran: https://CRAN.R-project.org/package=dbparser + url_git: https://github.com/ropensci/dbparser +dbplot: + version: 0.3.3 + title: Simplifies Plotting Data Inside Databases + maintainer: Edgar Ruiz + description: |- + Leverages 'dplyr' to process the calculations of a plot inside a database. + This package provides helper functions that abstract the work at three levels: + outputs a 'ggplot', outputs the calculations, outputs the formula + needed to calculate bins. + date_publication: '2020-02-07' + bug_reports: https://github.com/edgararuiz/dbplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbplot + url_git: https://github.com/edgararuiz/dbplot +dbplyr: + version: 2.5.0 + title: A 'dplyr' Back End for Databases + maintainer: Hadley Wickham + description: |- + A 'dplyr' back end for databases that allows you to work with + remote database tables as if they are in-memory data frames. Basic + features works with any database that has a 'DBI' back end; more + advanced features require 'SQL' translation to be provided by the + package author. + date_publication: '2024-03-19' + bug_reports: https://github.com/tidyverse/dbplyr/issues + url: https://dbplyr.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=dbplyr + url_git: https://github.com/tidyverse/dbplyr +DBR: + version: 1.4.1 + title: Discrete Beta Regression + maintainer: Alireza Mahani + description: |- + Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen in survey responses. + Estimation is done via Markov Chain Monte Carlo sampling, using a Gibbs wrapper around univariate slice sampler + (Neal (2003) ), as implemented in the R package MfUSampler + (Mahani and Sharabiani (2017) ). + date_publication: '2023-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBR + url_git: '' +dbscan: + version: 1.2.2 + title: |- + Density-Based Spatial Clustering of Applications with Noise + (DBSCAN) and Related Algorithms + maintainer: Michael Hahsler + description: |- + A fast reimplementation of several density-based algorithms + of the DBSCAN family. Includes the clustering algorithms DBSCAN + (density-based spatial clustering of applications with noise) and + HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering + points to identify the clustering structure), shared nearest neighbor + clustering, and the outlier detection algorithms LOF (local outlier + factor) and GLOSH (global-local outlier score from hierarchies). The + implementations use the kd-tree data structure (from library ANN) for + faster k-nearest neighbor search. An R interface to fast kNN and + fixed-radius NN search is also provided. Hahsler, Piekenbrock and + Doran (2019) . + date_publication: '2025-01-26' + bug_reports: https://github.com/mhahsler/dbscan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbscan + url_git: https://github.com/mhahsler/dbscan +dbstats: + version: 2.0.2 + title: Distance-Based Statistics + maintainer: Eva Boj + description: Prediction methods where explanatory information is coded as a matrix + of distances between individuals. Distances can either be directly input as a + distances matrix, a squared distances matrix, an inner-products matrix or computed + from observed predictors. + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbstats + url_git: '' +DBTC: + version: 0.1.0 + title: Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis + maintainer: Robert G Young + description: First using 'dada2' R tools to analyse metabarcode data, the 'DBTC' + package then uses the BLAST algorithm to search unknown sequences against local + databases, and then takes reduced matched results and provides best taxonomic + assignments. + date_publication: '2024-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBTC + url_git: +DBTCShiny: + version: 0.1.2 + title: |- + Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis 'shiny' + Application + maintainer: Robert G Young + description: Metabarcoding analysis using the 'DBTC' package is implemented here + using 'shiny' in an interactive graphical user interface to conduct Metabarcode + analyses and visualize and filter results. + date_publication: '2024-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DBTCShiny + url_git: +dbw: + version: 1.1.4 + title: Doubly Robust Distribution Balancing Weighting Estimation + maintainer: Hiroto Katsumata + description: Implements the doubly robust distribution balancing weighting proposed + by Katsumata (2024) , which improves the augmented inverse + probability weighting (AIPW) by estimating propensity scores with estimating equations + suitable for the pre-specified parameter of interest (e.g., the average treatment + effects or the average treatment effects on the treated) and estimating outcome + models with the estimated inverse probability weights. It also implements the + covariate balancing propensity score proposed by Imai and Ratkovic (2014) + and the entropy balancing weighting proposed by Hainmueller (2012) , + both of which use covariate balancing conditions in propensity score estimation. + The point estimate of the parameter of interest and its uncertainty as well as + coefficients for propensity score estimation and outcome regression are produced + using the M-estimation. The same functions can be used to estimate average outcomes + in missing outcome cases. + date_publication: '2024-08-28' + bug_reports: https://github.com/hirotokatsumata/dbw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbw + url_git: https://github.com/hirotokatsumata/dbw +dbWebForms: + version: 0.1.0 + title: Produce R Functions to Create HTML Forms Based on SQL Meta Data + maintainer: Timothy Conwell + description: |- + Offers meta programming style tools to generate configurable R functions that produce HTML forms based on table input and SQL meta data. + Also generates functions for collecting the parameters of those HTML forms after they are submitted. Useful for + quickly generating HTML forms based on existing SQL tables. To use the resultant functions, the output files containing those functions must + be read into the R environment (perhaps using base::source()). + date_publication: '2021-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dbWebForms + url_git: '' +dbx: + version: 0.3.2 + title: A Fast, Easy-to-Use Database Interface + maintainer: Andrew Kane + description: Provides select, insert, update, upsert, and delete database operations. + Supports 'PostgreSQL', 'MySQL', 'SQLite', and more, and plays nicely with the + 'DBI' package. + date_publication: '2024-06-03' + bug_reports: https://github.com/ankane/dbx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dbx + url_git: https://github.com/ankane/dbx +dc3net: + version: 1.2.0 + title: |- + Inferring Condition-Specific Networks via Differential Network + Inference + maintainer: Gokmen Altay + description: Performs differential network analysis to infer disease specific gene + networks. + date_publication: '2017-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dc3net + url_git: '' +DCCA: + version: 0.1.1 + title: Detrended Fluctuation and Detrended Cross-Correlation Analysis + maintainer: Taiane Schaedler Prass + description: |- + A collection of functions to perform Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA). + This package implements the results presented in Prass, T.S. and Pumi, G. (2019). "On the behavior of the DFA and DCCA in trend-stationary processes" . + date_publication: '2020-01-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCCA + url_git: '' +DCchoice: + version: 0.2.0 + title: Analyzing Dichotomous Choice Contingent Valuation Data + maintainer: Hideo Aizaki + description: |- + Functions for analyzing dichotomous choice contingent + valuation (CV) data. It provides functions for estimating parametric and + nonparametric models for single-, one-and-one-half-, and double-bounded + CV data. For details, see Aizaki et al. (2022) . + date_publication: '2023-07-10' + bug_reports: '' + url: http://www.agr.hokudai.ac.jp/spmur/ + url_cran: https://CRAN.R-project.org/package=DCchoice + url_git: '' +dccmidas: + version: 0.1.2 + title: |- + DCC Models with GARCH and GARCH-MIDAS Specifications in the + Univariate Step, RiskMetrics, Moving Covariance and Scalar and + Diagonal BEKK Models + maintainer: Vincenzo Candila + description: 'Estimates a variety of Dynamic Conditional Correlation (DCC) models. + More in detail, the ''dccmidas'' package allows the estimation of the corrected + DCC (cDCC) of Aielli (2013) , the DCC-MIDAS + of Colacito et al. (2011) , the Asymmetric + DCC of Cappiello et al. , and the Dynamic Equicorrelation + (DECO) of Engle and Kelly (2012) . ''dccmidas'' + offers the possibility of including standard GARCH , + GARCH-MIDAS and Double Asymmetric GARCH-MIDAS + models in the univariate estimation. Moreover, also the scalar and diagonal BEKK + models can be estimated. Finally, the package + calculates also the var-cov matrix under two non-parametric models: the Moving + Covariance and the RiskMetrics specifications.' + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dccmidas + url_git: '' +dccpp: + version: 0.1.0 + title: Fast Computation of Distance Correlations + maintainer: Jonathan Berrisch + description: Fast computation of the distance covariance 'dcov' and distance correlation + 'dcor'. The computation cost is only O(n log(n)) for the distance correlation + (see Chaudhuri, Hu (2019) ). + The functions are written entirely in C++ to speed up the computation. + date_publication: '2023-09-27' + bug_reports: https://github.com/BerriJ/dccpp/issues + url: https://dccpp.berrisch.biz/ + url_cran: https://CRAN.R-project.org/package=dccpp + url_git: https://github.com/BerriJ/dccpp +DCEM: + version: 2.0.5 + title: |- + Clustering Big Data using Expectation Maximization Star (EM*) + Algorithm + maintainer: Sharma Parichit + description: |- + Implements the Improved Expectation Maximisation EM* and the traditional EM algorithm for clustering + big data (gaussian mixture models for both multivariate and univariate datasets). This version + implements the faster alternative-EM* that expedites convergence via structure based data segregation. + The implementation supports both random and K-means++ based initialization. Reference: Parichit Sharma, + Hasan Kurban, Mehmet Dalkilic (2022) . Hasan Kurban, + Mark Jenne, Mehmet Dalkilic (2016) . + date_publication: '2022-01-16' + bug_reports: https://github.com/parichit/DCEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DCEM + url_git: https://github.com/parichit/DCEM +DCEmgmt: + version: 0.0.1 + title: DCE Data Reshaping and Processing + maintainer: Daniel Perez-Troncoso + description: Prepare the results of a DCE to be analysed through choice models.'DCEmgmt' + reshapes DCE data from wide to long format considering the special characteristics + of a DCE. 'DCEmgmt' includes the function 'DCEestm' which estimates choice models + once the database has been reshaped with 'DCEmgmt'. + date_publication: '2021-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCEmgmt + url_git: '' +DCEtool: + version: 1.1.0 + title: Efficient and Accessible Discrete Choice Experiments + maintainer: Daniel Perez Troncoso + description: 'Design, conduct and analyze ''DCEs'' from a virtual interface in shiny. + Reference: Perez-Troncoso, D. (2022) .' + date_publication: '2023-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCEtool + url_git: '' +DCG: + version: 0.9.3 + title: |- + Data Cloud Geometry (DCG): Using Random Walks to Find Community + Structure in Social Network Analysis + maintainer: Jessica Vandeleest + description: |- + Data cloud geometry (DCG) applies random walks in finding community structures for social networks. + Fushing, VanderWaal, McCowan, & Koehl (2013) (). + date_publication: '2019-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCG + url_git: '' +DChaos: + version: 0.1-7 + title: Chaotic Time Series Analysis + maintainer: Julio E. Sandubete + description: |- + Chaos theory has been hailed as a revolution of thoughts and attracting ever increasing + attention of many scientists from diverse disciplines. Chaotic systems are nonlinear deterministic + dynamic systems which can behave like an erratic and apparently random motion. A relevant field + inside chaos theory and nonlinear time series analysis is the detection of a chaotic behaviour + from empirical time series data. One of the main features of chaos is the well known initial value + sensitivity property. Methods and techniques related to test the hypothesis of chaos try to quantify + the initial value sensitive property estimating the Lyapunov exponents. The DChaos package + provides different useful tools and efficient algorithms which test robustly the hypothesis of chaos + based on the Lyapunov exponent in order to know if the data generating process behind time series + behave chaotically or not. + date_publication: '2023-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DChaos + url_git: '' +dChipIO: + version: 0.1.5 + title: Methods for Reading dChip Files + maintainer: Henrik Bengtsson + description: Functions for reading DCP and CDF.bin files generated by the dChip + software. + date_publication: '2016-01-13' + bug_reports: https://github.com/HenrikBengtsson/dChipIO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dChipIO + url_git: https://github.com/HenrikBengtsson/dChipIO +dcifer: + version: 1.2.1 + title: Genetic Relatedness Between Polyclonal Infections + maintainer: Inna Gerlovina + description: |- + An implementation of Dcifer (Distance for complex infections: fast estimation of relatedness), an identity by descent (IBD) based method to calculate genetic relatedness between polyclonal infections from biallelic and multiallelic data. The package includes functions that format and preprocess the data, implement the method, and visualize the results. + Gerlovina et al. (2022) . + date_publication: '2023-12-12' + bug_reports: '' + url: https://eppicenter.github.io/dcifer/ + url_cran: https://CRAN.R-project.org/package=dcifer + url_git: https://github.com/EPPIcenter/dcifer +DCL: + version: 0.1.2 + title: Claims Reserving under the Double Chain Ladder Model + maintainer: Maria Dolores Martinez-Miranda + description: Statistical modelling and forecasting in claims reserving in non-life + insurance under the Double Chain Ladder framework by Martinez-Miranda, Nielsen + and Verrall (2012). + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCL + url_git: '' +DCLEAR: + version: 1.0.13 + title: Distance Based Cell Lineage Reconstruction + maintainer: Il-Youp Kwak + description: |- + R codes for distance based cell lineage reconstruction. Our methods won both sub-challenges 2 and 3 of the Allen Institute Cell Lineage Reconstruction DREAM Challenge in 2020. + References: Gong et al. (2021) , Gong et al. (2022) . + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCLEAR + url_git: https://github.com/ikwak2/DCLEAR +dclone: + version: 2.3-2 + title: Data Cloning and MCMC Tools for Maximum Likelihood Methods + maintainer: Peter Solymos + description: |- + Low level functions for implementing + maximum likelihood estimating procedures for + complex models using data cloning and Bayesian + Markov chain Monte Carlo methods + as described in Solymos 2010 . + Sequential and parallel MCMC support + for 'JAGS', 'WinBUGS', 'OpenBUGS', and 'Stan'. + date_publication: '2023-07-03' + bug_reports: https://github.com/datacloning/dclone/issues + url: https://groups.google.com/forum/#!forum/dclone-users + url_cran: https://CRAN.R-project.org/package=dclone + url_git: https://github.com/datacloning/dclone +dclust: + version: 0.1.0 + title: Divisive Hierarchical Clustering + maintainer: Shaun Wilkinson + description: |- + Contains a single function dclust() for divisive hierarchical clustering based on + recursive k-means partitioning (k = 2). Useful for clustering large datasets + where computation of a n x n distance matrix is not feasible (e.g. n > 10,000 records). + For further information see Steinbach, Karypis and Kumar (2000) . + date_publication: '2019-09-05' + bug_reports: http://github.com/shaunpwilkinson/dclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dclust + url_git: http://github.com/shaunpwilkinson/dclust +DCluster: + version: 0.2-10 + title: Functions for the Detection of Spatial Clusters of Diseases + maintainer: Virgilio Gómez-Rubio + description: |- + A set of functions for the detection of spatial clusters + of disease using count data. Bootstrap is used to estimate + sampling distributions of statistics. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCluster + url_git: '' +DClusterm: + version: 1.0-1 + title: Model-Based Detection of Disease Clusters + maintainer: Virgilio Gomez-Rubio + description: |- + Model-based methods for the detection of disease clusters + using GLMs, GLMMs and zero-inflated models. These methods are described + in 'V. Gómez-Rubio et al.' (2019) and + 'V. Gómez-Rubio et al.' (2018) . + date_publication: '2020-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DClusterm + url_git: '' +dcm2: + version: 1.0.2 + title: |- + Calculating the M2 Model Fit Statistic for Diagnostic + Classification Models + maintainer: Jeffrey Hoover + description: |- + A collection of functions for calculating the M2 model fit + statistic for diagnostic classification models as described by Liu et al. + (2016) . These functions provide multiple + sources of information for model fit according to the M2 statistic, + including the M2 statistic, the *p* value for that M2 statistic, and the + Root Mean Square Error of Approximation based on the M2 statistic. + date_publication: '2023-03-21' + bug_reports: https://github.com/atlas-aai/dcm2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dcm2 + url_git: https://github.com/atlas-aai/dcm2 +dcmle: + version: 0.4-1 + title: Hierarchical Models Made Easy with Data Cloning + maintainer: Peter Solymos + description: |- + S4 classes around infrastructure provided by the + 'coda' and 'dclone' packages to make package development easy as a breeze + with data cloning for hierarchical models. + date_publication: '2023-07-04' + bug_reports: https://github.com/datacloning/dcmle/issues + url: https://groups.google.com/forum/#!forum/dclone-users + url_cran: https://CRAN.R-project.org/package=dcmle + url_git: https://github.com/datacloning/dcmle +dcmodify: + version: 0.9.0 + title: Modify Data Using Externally Defined Modification Rules + maintainer: Mark van der Loo + description: |- + Data cleaning scripts typically contain a lot of 'if this change that' + type of statements. Such statements are typically condensed expert knowledge. + With this package, such 'data modifying rules' are taken out of the code and + become in stead parameters to the work flow. This allows one to maintain, document, + and reason about data modification rules as separate entities. + date_publication: '2024-03-28' + bug_reports: https://github.com/data-cleaning/dcmodify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dcmodify + url_git: https://github.com/data-cleaning/dcmodify +DCODE: + version: '1.0' + title: |- + List Linear n-Peptide Constraints for Overlapping Protein + Regions + maintainer: Sophie Lebre + description: 'Traversal graph algorithm for listing linear n-peptide constraints + for overlapping protein regions. (Lebre and Gascuel, The combinatorics of overlapping + genes, freely available from arXiv at : http://arxiv.org/abs/1602.04971).' + date_publication: '2016-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCODE + url_git: '' +dcortools: + version: 0.1.6 + title: |- + Providing Fast and Flexible Functions for Distance Correlation + Analysis + maintainer: Dominic Edelmann + description: Provides methods for distance covariance and distance correlation (Szekely, + et al. (2007) ), generalized version thereof (Sejdinovic, + et al. (2013) ) and corresponding tests (Berschneider, + Bottcher (2018) . Distance standard deviation methods (Edelmann, + et al. (2020) ) and distance correlation methods for survival + endpoints (Edelmann, et al. (2021) ) are also included. + date_publication: '2022-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dcortools + url_git: '' +dcorVS: + version: '1.1' + title: Variable Selection Algorithms Using the Distance Correlation + maintainer: Michail Tsagris + description: 'The ''FBED'' and ''mmpc'' variable selection algorithms have been + implemented using the distance correlation. The references include: Tsamardinos + I., Aliferis C. F. and Statnikov A. (2003). "Time and sample efficient discovery + of Markovblankets and direct causal relations". In Proceedings of the ninth ACM + SIGKDD international Conference. . Borboudakis G. and + Tsamardinos I. (2019). "Forward-backward selection with early dropping". Journal + of Machine Learning Research, 20(8): 1--39. . Huo + X. and Szekely G.J. (2016). "Fast computing for distance covariance". Technometrics, + 58(4): 435--447. .' + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dcorVS + url_git: '' +dcov: + version: 0.1.1 + title: A Fast Implementation of Distance Covariance + maintainer: Hang Weiqiang + description: Efficient methods for computing distance covariance and relevant statistics. + See Székely et al.(2007) ; Székely and Rizzo (2013) + ; Székely and Rizzo (2014) ; + Huo and Székely (2016) . + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dcov + url_git: '' +dCovTS: + version: '1.4' + title: Distance Covariance and Correlation for Time Series Analysis + maintainer: Michail Tsagris + description: |- + Computing and plotting the distance covariance and correlation function of a univariate or a multivariate time series. Both versions of biased and unbiased estimators of distance covariance and correlation are provided. Test statistics for testing pairwise independence are also implemented. Some data sets are also included. References include: + a) Edelmann Dominic, Fokianos Konstantinos and Pitsillou Maria (2019). 'An Updated Literature Review of Distance Correlation and Its Applications to Time Series'. International Statistical Review, 87(2): 237--262. . + b) Fokianos Konstantinos and Pitsillou Maria (2018). 'Testing independence for multivariate time series via the auto-distance correlation matrix'. Biometrika, 105(2): 337--352. . + c) Fokianos Konstantinos and Pitsillou Maria (2017). 'Consistent testing for pairwise dependence in time series'. Technometrics, 59(2): 262--270. . + d) Pitsillou Maria and Fokianos Konstantinos (2016). 'dCovTS: Distance Covariance/Correlation for Time Series'. R Journal, 8(2):324-340. . + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dCovTS + url_git: '' +DCPO: + version: 0.5.3 + title: Dynamic Comparative Public Opinion + maintainer: Frederick Solt + description: 'Estimates latent variables of public opinion cross-nationally and + over time from sparse and incomparable survey data. ''DCPO'' uses a population-level + graded response model with country-specific item bias terms. Sampling is conducted + with ''Stan''. References: Solt (2020) .' + date_publication: '2020-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCPO + url_git: '' +DCSmooth: + version: 1.1.2 + title: |- + Nonparametric Regression and Bandwidth Selection for Spatial + Models + maintainer: Bastian Schaefer + description: |- + Nonparametric smoothing techniques for data on a lattice and + functional time series. Smoothing is done via kernel regression or + local polynomial regression, a bandwidth selection procedure based on + an iterative plug-in algorithm is implemented. This package allows for + modeling a dependency structure of the error terms of the + nonparametric regression model. Methods used in this paper are + described in Feng/Schaefer (2021) + , Schaefer/Feng (2021) + . + date_publication: '2021-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DCSmooth + url_git: '' +dcsvm: + version: 0.0.1 + title: Density Convoluted Support Vector Machines + maintainer: Boxiang Wang + description: Implements an efficient algorithm for solving sparse-penalized support + vector machines with kernel density convolution. This package is designed for + high-dimensional classification tasks, supporting lasso (L1) and elastic-net penalties + for sparse feature selection and providing options for tuning kernel bandwidth + and penalty weights. The 'dcsvm' is applicable to fields such as bioinformatics, + image analysis, and text classification, where high-dimensional data commonly + arise. Learn more about the methodology and algorithm at Wang, Zhou, Gu, and Zou + (2023) . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dcsvm + url_git: '' +dcTensor: + version: 1.3.0 + title: Discrete Matrix/Tensor Decomposition + maintainer: Koki Tsuyuzaki + description: Semi-Binary and Semi-Ternary Matrix Decomposition are performed based + on Non-negative Matrix Factorization (NMF) and Singular Value Decomposition (SVD). + For the details of the methods, see the reference section of GitHub README.md + . + date_publication: '2024-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dcTensor + url_git: https://github.com/rikenbit/dcTensor +dCUR: + version: 1.0.1 + title: Dimension Reduction with Dynamic CUR + maintainer: Cesar Gamboa + description: |- + Dynamic CUR (dCUR) boosts the CUR decomposition (Mahoney MW., Drineas P. (2009) ) varying the k, the number of columns and rows used, and its final purposes to help find the stage, which minimizes the relative error to reduce matrix dimension. + The goal of CUR Decomposition is to give a better interpretation of the matrix decomposition employing proper variable selection in the data matrix, in a way that yields a simplified structure. Its origins come from analysis in genetics. + The goal of this package is to show an alternative to variable selection (columns) or individuals (rows). The idea proposed consists of adjusting the probability distributions to the leverage scores and selecting the best columns and rows that minimize the reconstruction error of the matrix approximation ||A-CUR||. It also includes a method that recalibrates the relative importance of the leverage scores according to an external variable of the user's interest. + date_publication: '2023-10-18' + bug_reports: '' + url: https://www.cesargamboasanabria.com + url_cran: https://CRAN.R-project.org/package=dCUR + url_git: '' +dcurver: + version: 0.9.2 + title: Utility Functions for Davidian Curves + maintainer: Oğuzhan Öğreden + description: |- + A Davidian curve defines a seminonparametric density, whose shape and flexibility can be tuned by + easy to estimate parameters. Since a special case of a Davidian curve is the standard normal density, + Davidian curves can be used for relaxing normality assumption in statistical applications (Zhang & Davidian, 2001) + . This package provides the density function, the gradient of + the loglikelihood and a random generator for Davidian curves. + date_publication: '2020-11-04' + bug_reports: https://github.com/oguzhanogreden/dcurver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dcurver + url_git: https://github.com/oguzhanogreden/dcurver +dcurves: + version: 0.5.0 + title: Decision Curve Analysis for Model Evaluation + maintainer: Daniel D. Sjoberg + description: |- + Diagnostic and prognostic models are typically evaluated with + measures of accuracy that do not address clinical consequences. + Decision-analytic techniques allow assessment of clinical outcomes, + but often require collection of additional information may be + cumbersome to apply to models that yield a continuous result. Decision + curve analysis is a method for evaluating and comparing prediction + models that incorporates clinical consequences, requires only the data + set on which the models are tested, and can be applied to models that + have either continuous or dichotomous results. See the following references + for details on the methods: Vickers (2006) , + Vickers (2008) , + and Pfeiffer (2020) . + date_publication: '2024-07-23' + bug_reports: https://github.com/ddsjoberg/dcurves/issues + url: https://www.danieldsjoberg.com/dcurves/ + url_cran: https://CRAN.R-project.org/package=dcurves + url_git: https://github.com/ddsjoberg/dcurves +ddalpha: + version: 1.3.16 + title: Depth-Based Classification and Calculation of Data Depth + maintainer: Oleksii Pokotylo + description: Contains procedures for depth-based supervised learning, which are + entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and + Mozharovskyi, 2014 ). The training data sample + is transformed by a statistical depth function to a compact low-dimensional space, + where the final classification is done. It also offers an extension to functional + data and routines for calculating certain notions of statistical depth functions. + 50 multivariate and 5 functional classification problems are included. (Pokotylo, + Mozharovskyi and Dyckerhoff, 2019 ). + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddalpha + url_git: '' +ddc: + version: 1.0.1 + title: Distance Density Clustering Algorithm + maintainer: Ruizhe Ma + description: A distance density clustering (DDC) algorithm in R. DDC uses dynamic + time warping (DTW) to compute a similarity matrix, based on which cluster centers + and cluster assignments are found. DDC inherits dynamic time warping (DTW) arguments + and constraints. The cluster centers are centroid points that are calculated using + the DTW Barycenter Averaging (DBA) algorithm. The clustering process is divisive. + At each iteration, cluster centers are updated and data is reassigned to cluster + centers. Early stopping is possible. The output includes cluster centers and clustering + assignment, as described in the paper (Ma et al (2017) ). + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddc + url_git: '' +DDD: + version: 5.2.2 + title: Diversity-Dependent Diversification + maintainer: Rampal S. Etienne + description: |2- + + Implements maximum likelihood and bootstrap methods based on + the diversity-dependent birth-death process to test whether + speciation or extinction are diversity-dependent, under various + models including various types of key innovations. + See Etienne et al. 2012, Proc. Roy. Soc. B 279: 1300-1309, + , + Etienne & Haegeman 2012, Am. Nat. 180: E75-E89, + , + Etienne et al. 2016. Meth. Ecol. Evol. 7: 1092-1099, + and + Laudanno et al. 2021. Syst. Biol. 70: 389–407, + . + Also contains functions to simulate the diversity-dependent + process. + date_publication: '2023-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDD + url_git: '' +dde: + version: 1.0.7 + title: Solve Delay Differential Equations + maintainer: Rich FitzJohn + description: |- + Solves ordinary and delay differential equations, where + the objective function is written in either R or C. Suitable only + for non-stiff equations, the solver uses a 'Dormand-Prince' method + that allows interpolation of the solution at any point. This + approach is as described by Hairer, Norsett and Wanner (1993) + . Support is also included for iterating + difference equations. + date_publication: '2024-09-23' + bug_reports: https://github.com/mrc-ide/dde/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dde + url_git: https://github.com/mrc-ide/dde +ddecompose: + version: 1.0.0 + title: Detailed Distributional Decomposition + maintainer: Samuel Meier + description: |- + Implements the Oaxaca-Blinder decomposition method and generalizations of it that decompose differences in distributional statistics beyond the mean. + The function ob_decompose() decomposes differences in the mean outcome between two groups into one part explained by different covariates (composition effect) and into another part due to differences in the way covariates are linked to the outcome variable (structure effect). The function further divides the two effects into the contribution of each covariate and allows for weighted doubly robust decompositions. For distributional statistics beyond the mean, the function performs the recentered influence function (RIF) decomposition proposed by Firpo, Fortin, and Lemieux (2018). + The function dfl_decompose() divides differences in distributional statistics into an composition effect and a structure effect using inverse probability weighting as introduced by DiNardo, Fortin, and Lemieux (1996). The function also allows to sequentially decompose the composition effect into the contribution of single covariates. + References: + Firpo, Sergio, Nicole M. Fortin, and Thomas Lemieux. (2018) . "Decomposing Wage Distributions Using Recentered Influence Function Regressions." + Fortin, Nicole M., Thomas Lemieux, and Sergio Firpo. (2011) . "Decomposition Methods in Economics." + DiNardo, John, Nicole M. Fortin, and Thomas Lemieux. (1996) . "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach." + Oaxaca, Ronald. (1973) . "Male-Female Wage Differentials in Urban Labor Markets." + Blinder, Alan S. (1973) . "Wage Discrimination: Reduced Form and Structural Estimates." + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddecompose + url_git: '' +DDHFm: + version: 1.1.4 + title: |- + Variance Stabilization by Data-Driven Haar-Fisz (for + Microarrays) + maintainer: Guy Nason + description: |- + Contains the normalizing and variance stabilizing + Data-Driven Haar-Fisz algorithm. Also contains related algorithms + for simulating from certain microarray gene intensity models and + evaluation of certain transformations. Contains cDNA and shipping + credit flow data. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDHFm + url_git: '' +ddi: + version: 0.1.0 + title: The Data Defect Index for Samples that May not be IID + maintainer: Shiro Kuriwaki + description: |- + Implements Meng's data defect index (ddi), which represents + the degree of sample bias relative to an iid sample. The data defect + correlation (ddc) represents the correlation between the outcome of interest + and the selection into the sample; when the sample selection is independent + across the population, the ddc is zero. Details are in Meng (2018) + , "Statistical Paradises and Paradoxes in Big Data (I): + Law of Large Populations, Big Data Paradox, and the 2016 US Presidential + Election." Survey estimates from the Cooperative Congressional Election Study + (CCES) is included to replicate the article's results. + date_publication: '2020-01-26' + bug_reports: http://github.com/kuriwaki/ddi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ddi + url_git: https://github.com/kuriwaki/ddi +ddiv: + version: 0.1.1 + title: Data Driven I-v Feature Extraction + maintainer: Megan M. Morbitzer + description: |- + The Data Driven I-V Feature Extraction is used to extract + Current-Voltage (I-V) features from I-V curves. I-V curves indicate the + relationship between current and voltage for a solar cell or Photovoltaic (PV) + modules. The I-V features such as maximum power point (Pmp), shunt resistance (Rsh), + series resistance (Rs),short circuit current (Isc), open circuit voltage (Voc), + fill factor (FF), current at maximum power (Imp) and voltage at maximum power(Vmp) + contain important information of the performance for PV modules. The traditional + method uses the single diode model to model I-V curves and extract I-V features. + This package does not use the diode model, but uses data-driven a method which + select different linear parts of the I-V curves to extract I-V features. + This method also uses a sampling method to calculate uncertainties when extracting + I-V features. Also, because of the partially shaded array, "steps" occurs in + I-V curves. The "Segmented Regression" method is used to identify steps in I-V curves. + This material is based upon work supported by the U.S. Department of Energy’s + Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy + Technologies Office (SETO) Agreement Number DE-EE0007140. Further information can be + found in the following paper. + [1] Ma, X. et al, 2019. + . + date_publication: '2021-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddiv + url_git: '' +DDIwR: + version: '0.19' + title: DDI with R + maintainer: Adrian Dusa + description: |- + Useful functions for various DDI (Data Documentation Initiative) + related inputs and outputs. Converts data files to and from DDI, SPSS, + Stata, SAS, R and Excel, including user declared missing values. + date_publication: '2024-12-10' + bug_reports: https://github.com/dusadrian/DDIwR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DDIwR + url_git: https://github.com/dusadrian/DDIwR +DDL: + version: 1.0.2 + title: Doubly Debiased Lasso (DDL) + maintainer: Zijian Guo + description: Statistical inference for the regression coefficients in high-dimensional + linear models with hidden confounders. The Doubly Debiased Lasso method was proposed + in . + date_publication: '2023-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDL + url_git: '' +DDM: + version: 1.0-0 + title: Death Registration Coverage Estimation + maintainer: Tim Riffe + description: A set of three two-census methods to the estimate the degree of death + registration coverage for a population. Implemented methods include the Generalized + Growth Balance method (GGB), the Synthetic Extinct Generation method (SEG), and + a hybrid of the two, GGB-SEG. Each method offers automatic estimation, but users + may also specify exact parameters or use a graphical interface to guess parameters + in the traditional way if desired. + date_publication: '2017-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDM + url_git: '' +ddml: + version: 0.3.0 + title: Double/Debiased Machine Learning + maintainer: Thomas Wiemann + description: |- + Estimate common causal parameters using double/debiased machine + learning as proposed by Chernozhukov et al. (2018) . + 'ddml' simplifies estimation based on (short-)stacking as discussed in + Ahrens et al. (2024) , which leverages multiple base + learners to increase robustness to the underlying data generating process. + date_publication: '2024-10-02' + bug_reports: https://github.com/thomaswiemann/ddml/issues + url: https://thomaswiemann.com/ddml/ + url_cran: https://CRAN.R-project.org/package=ddml + url_git: https://github.com/thomaswiemann/ddml +ddp: + version: 0.0.3 + title: Desirable Dietary Pattern + maintainer: Weksi Budiaji + description: |- + The desirable Dietary Pattern (DDP)/ PPH score + measures the variety of food consumption. The (weighted) score is calculated + based on the type of food. This package is intended to calculate + the DDP/ PPH score that is faster than traditional method via + a manual calculation by BKP (2017) and is simpler than the nutrition survey + . The database to create weights and baseline values + is the Indonesia national survey in 2017. + date_publication: '2021-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddp + url_git: '' +ddpca: + version: '1.1' + title: Diagonally Dominant Principal Component Analysis + maintainer: Fan Yang + description: Efficient procedures for fitting the DD-PCA (Ke et al., 2019, ) by + decomposing a large covariance matrix into a low-rank matrix plus a diagonally + dominant matrix. The implementation of DD-PCA includes the convex approach using + the Alternating Direction Method of Multipliers (ADMM) and the non-convex approach + using the iterative projection algorithm. Applications of DD-PCA to large covariance + matrix estimation and global multiple testing are also included in this package. + date_publication: '2019-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddpca + url_git: '' +ddpcr: + version: 1.15.2 + title: |- + Analysis and Visualization of Droplet Digital PCR in R and on + the Web + maintainer: Dean Attali + description: |- + An interface to explore, analyze, and visualize droplet digital PCR + (ddPCR) data in R. This is the first non-proprietary software for analyzing + two-channel ddPCR data. An interactive tool was also created and is available + online to facilitate this analysis for anyone who is not comfortable with + using R. + date_publication: '2023-08-20' + bug_reports: https://github.com/daattali/ddpcr/issues + url: https://daattali.com/shiny/ddpcr/ + url_cran: https://CRAN.R-project.org/package=ddpcr + url_git: https://github.com/daattali/ddpcr +ddplot: + version: 0.0.1 + title: Create D3 Based SVG Graphics + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Create 'D3' based 'SVG' ('Scalable Vector Graphics') graphics using a simple 'R' API. + The package aims to simplify + the creation of many 'SVG' plot types using a straightforward 'R' API. + The package relies on the 'r2d3' 'R' package and the 'D3' 'JavaScript' library. + See and respectively. + date_publication: '2022-12-02' + bug_reports: https://github.com/feddelegrand7/ddplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ddplot + url_git: https://github.com/feddelegrand7/ddplot +DDPM: + version: 0.1.0 + title: Data Sets for Discrete Probability Models + maintainer: Muhammad Imran + description: A wide collection of univariate discrete data sets from various applied + domains related to distribution theory. The functions allow quick, easy, and efficient + access to 100 univariate discrete data sets. The data are related to different + applied domains, including medical, reliability analysis, engineering, manufacturing, + occupational safety, geological sciences, terrorism, psychology, agriculture, + environmental sciences, road traffic accidents, demography, actuarial science, + law, and justice. The documentation, along with associated references for further + details and uses, is presented. + date_publication: '2023-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDPM + url_git: '' +DDPNA: + version: 0.3.3 + title: |- + Disease-Drived Differential Proteins Co-Expression Network + Analysis + maintainer: Kefu Liu + description: |- + Functions designed to connect disease-related differential proteins and + co-expression network. It provides the basic statics analysis included t test, ANOVA analysis. + The network construction is not offered by the package, you can used 'WGCNA' package which you + can learn in Peter et al. (2008) . It also provides module analysis + included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and + hub analysis. + date_publication: '2024-03-14' + bug_reports: https://github.com/liukf10/DDPNA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DDPNA + url_git: https://github.com/liukf10/DDPNA +DDPstar: + version: 1.0-1 + title: |- + Density Regression via Dirichlet Process Mixtures of Normal + Structured Additive Regression Models + maintainer: Maria Xose Rodriguez-Alvarez + description: Implements a flexible, versatile, and computationally tractable model + for density regression based on a single-weights dependent Dirichlet process mixture + of normal distributions model for univariate continuous responses. The model assumes + an additive structure for the mean of each mixture component and the effects of + continuous covariates are captured through smooth nonlinear functions. The key + components of our modelling approach are penalised B-splines and their bivariate + tensor product extension. The proposed method can also easily deal with parametric + effects of categorical covariates, linear effects of continuous covariates, interactions + between categorical and/or continuous covariates, varying coefficient terms, and + random effects. Please see Rodriguez-Alvarez, Inacio et al. (2025) for more details. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDPstar + url_git: '' +DDRTree: + version: 0.1.5 + title: Learning Principal Graphs with DDRTree + maintainer: Xiaojie Qiu + description: Provides an implementation of the framework of reversed graph embedding + (RGE) which projects data into a reduced dimensional space while constructs a + principal tree which passes through the middle of the data simultaneously. DDRTree + shows superiority to alternatives (Wishbone, DPT) for inferring the ordering as + well as the intrinsic structure of the single cell genomics data. In general, + it could be used to reconstruct the temporal progression as well as bifurcation + structure of any datatype. + date_publication: '2017-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DDRTree + url_git: '' +ddsPLS: + version: 1.2.1 + title: Data-Driven Sparse Partial Least Squares + maintainer: Hadrien Lorenzo + description: |- + A sparse Partial Least Squares implementation which uses soft-threshold + estimation of the covariance matrices and therein introduces + sparsity. Number of components and regularization coefficients are automatically set. + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddsPLS + url_git: '' +ddst: + version: '1.4' + title: Data Driven Smooth Tests + maintainer: Przemyslaw Biecek + description: |- + Smooth testing of goodness of fit. These tests are data + driven (alternative hypothesis is dynamically selected based on data). In this + package you will find various tests for exponent, Gaussian, Gumbel and uniform + distribution. + date_publication: '2016-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ddst + url_git: '' +ddtlcm: + version: 0.2.1 + title: |- + Latent Class Analysis with Dirichlet Diffusion Tree Process + Prior + maintainer: Mengbing Li + description: |- + Implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. + Reference: Li et al. (2023) . + date_publication: '2024-04-04' + bug_reports: https://github.com/limengbinggz/ddtlcm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ddtlcm + url_git: https://github.com/limengbinggz/ddtlcm +deadband: + version: 0.1.0 + title: Statistical Deadband Algorithms Comparison + maintainer: Nunzio Torrisi + description: Statistical deadband algorithms are based on the Send-On-Delta concept + as in Miskowicz(2006,). A collection of functions compare + effectiveness and fidelity of sampled signals using statistical deadband algorithms. + date_publication: '2016-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deadband + url_git: '' +deal: + version: 1.2-42 + title: Learning Bayesian Networks with Mixed Variables + maintainer: Claus Dethlefsen + description: |- + Bayesian networks with continuous and/or discrete + variables can be learned and compared from data. The method is described in Boettcher and Dethlefsen (2003), . + date_publication: '2022-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deal + url_git: '' +deaR: + version: 1.4.1 + title: Conventional and Fuzzy Data Envelopment Analysis + maintainer: Vicente Bolos + description: 'Set of functions for Data Envelopment Analysis. It runs both classic + and fuzzy DEA models. See: Banker, R.; Charnes, A.; Cooper, W.W. (1984). , + Charnes, A.; Cooper, W.W.; Rhodes, E. (1978). + and Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). .' + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deaR + url_git: '' +debar: + version: 0.1.1 + title: A Post-Clustering Denoiser for COI-5P Barcode Data + maintainer: Cameron M. Nugent + description: |- + The 'debar' sequence processing pipeline is designed for denoising high throughput + sequencing data for the animal DNA barcode marker cytochrome c oxidase I (COI). The package + is designed to detect and correct insertion and deletion errors within sequencer outputs. + This is accomplished through comparison of input sequences against a profile hidden Markov + model (PHMM) using the Viterbi algorithm (for algorithm details see Durbin et al. 1998, + ISBN: 9780521629713). Inserted base pairs are removed and deleted base pairs are accounted + for through the introduction of a placeholder character. Since the PHMM is a probabilistic + representation of the COI barcode, corrections are not always perfect. For this reason + 'debar' censors base pairs adjacent to reported indel sites, turning them into placeholder + characters (default is 7 base pairs in either direction, this feature can be disabled). + Testing has shown that this censorship results in the correct sequence length being restored, + and erroneous base pairs being masked the vast majority of the time (>95%). + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=debar + url_git: '' +DEBBI: + version: 0.1.0 + title: Differential Evolution-Based Bayesian Inference + maintainer: Brendan Matthew Galdo + description: Bayesian inference algorithms based on the population-based "differential + evolution" (DE) algorithm. Users can obtain posterior mode (MAP) estimates via + DEMAP, posterior samples via DEMCMC, and variational approximations via DEVI. + date_publication: '2022-05-17' + bug_reports: https://github.com/bmgaldo/DEBBI + url: '' + url_cran: https://CRAN.R-project.org/package=DEBBI + url_git: https://github.com/bmgaldo/DEBBI +debest: + version: 0.1.0 + title: Duration Estimation for Biomarker Enrichment Studies and Trials + maintainer: Hong Zhang + description: A general framework using mixture Weibull distributions to accurately + predict biomarker-guided trial duration accounting for heterogeneous population. + Extensive simulations are performed to evaluate the impact of heterogeneous population + and the dynamics of biomarker characteristics and disease on the study duration. + Several influential parameters including median survival time, enrollment rate, + biomarker prevalence and effect size are identified. Efficiency gains of biomarker-guided + trials can be quantitatively compared to the traditional all-comers design. For + reference, see Zhang et al. (2024) . + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=debest + url_git: '' +DebiasInfer: + version: '0.2' + title: |- + Efficient Inference on High-Dimensional Linear Model with + Missing Outcomes + maintainer: Yikun Zhang + description: |- + A statistically and computationally efficient debiasing method for conducting valid inference on the high-dimensional linear regression function with missing outcomes. + The reference paper is Zhang, Giessing, and Chen (2023) . + date_publication: '2023-10-09' + bug_reports: https://github.com/zhangyk8/Debias-Infer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DebiasInfer + url_git: https://github.com/zhangyk8/Debias-Infer/ +deBif: + version: 0.1.9 + title: Bifurcation Analysis of Ordinary Differential Equation Systems + maintainer: Andre M. de Roos + description: |- + Shiny application that performs bifurcation and phaseplane analysis of systems of ordinary + differential equations. The package allows for computation of equilibrium curves as a function of + a single free parameter, detection of transcritical, saddle-node and hopf bifurcation points along + these curves, and computation of curves representing these transcritical, saddle-node and hopf + bifurcation points as a function of two free parameters. The shiny-based GUI allows visualization + of the results in both 2D- and 3D-plots. The implemented methods for solution localisation and curve + continuation are based on the book "Elements of applied bifurcation theory" (Kuznetsov, Y. A., 1995; + ISBN: 0-387-94418-4). + date_publication: '2025-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deBif + url_git: '' +deBInfer: + version: 0.4.4 + title: Bayesian Inference for Differential Equations + maintainer: Philipp H Boersch-Supan + description: |- + A Bayesian framework for parameter inference in differential equations. + This approach offers a rigorous methodology for parameter inference as well as + modeling the link between unobservable model states and parameters, and + observable quantities. Provides templates for the DE model, the + observation model and data likelihood, and the model parameters and their prior + distributions. A Markov chain Monte Carlo (MCMC) procedure processes these inputs + to estimate the posterior distributions of the parameters and any derived + quantities, including the model trajectories. Further functionality is provided + to facilitate MCMC diagnostics and the visualisation of the posterior distributions + of model parameters and trajectories. + date_publication: '2022-11-17' + bug_reports: https://github.com/pboesu/debinfer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=deBInfer + url_git: https://github.com/pboesu/debinfer +debkeepr: + version: 0.1.1 + title: Analysis of Non-Decimal Currencies and Double-Entry Bookkeeping + maintainer: Jesse Sadler + description: |- + Analysis of historical non-decimal currencies and value + systems that use tripartite or tetrapartite systems such as pounds, + shillings, and pence. It introduces new vector classes to represent + non-decimal currencies, making them compatible with numeric classes, + and provides functions to work with these classes in data frames in + the context of double-entry bookkeeping. + date_publication: '2023-03-22' + bug_reports: https://github.com/jessesadler/debkeepr/issues + url: https://jessesadler.github.io/debkeepr/ + url_cran: https://CRAN.R-project.org/package=debkeepr + url_git: https://github.com/jessesadler/debkeepr +DeBoinR: + version: '1.0' + title: |- + Box-Plots and Outlier Detection for Probability Density + Functions + maintainer: Alexander C. Murph + description: 'Orders a data-set consisting of an ensemble of probability density + functions on the same x-grid. Visualizes a box-plot of these functions based + on the notion of distance determined by the user. Reports outliers based on the + distance chosen and the scaling factor for an interquartile range rule. For further + details, see: Alexander C. Murph et al. (2023). "Visualization and Outlier Detection + for Probability Density Function Ensembles." .' + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DeBoinR + url_git: '' +debugme: + version: 1.2.0 + title: Debug R Packages + maintainer: Gábor Csárdi + description: |- + Specify debug messages as special string constants, and + control debugging of packages via environment variables. + date_publication: '2024-04-25' + bug_reports: https://github.com/r-lib/debugme/issues + url: https://r-lib.github.io/debugme/ + url_cran: https://CRAN.R-project.org/package=debugme + url_git: https://github.com/r-lib/debugme#readme +debugr: + version: 0.0.1 + title: |- + Debug Tool to Watch Objects/Expressions While Running an R + Script + maintainer: Joachim Zuckarelli + description: |- + Tool to print out the value of R objects/expressions while running + an R script. Outputs can be made dependent on user-defined conditions/criteria. + Debug messages only appear when a global option for debugging is set. + This way, 'debugr' code can even remain in the debugged code for later use + without any negative effects during normal runtime. + date_publication: '2018-07-30' + bug_reports: https://github.com/jsugarelli/debugr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=debugr + url_git: https://github.com/jsugarelli/debugr/ +DeCAFS: + version: 3.3.3 + title: Detecting Changes in Autocorrelated and Fluctuating Signals + maintainer: Gaetano Romano + description: Detect abrupt changes in time series with local fluctuations as a random + walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, + G., Runge, V., Fearnhead, P. (2021) . + date_publication: '2023-01-06' + bug_reports: https://github.com/gtromano/DeCAFS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DeCAFS + url_git: '' +DECIDE: + version: '1.3' + title: DEComposition of Indirect and Direct Effects + maintainer: Christiana Kartsonaki + description: |- + Calculates various estimates for measures of educational + differentials, the relative importance of primary and secondary + effects in the creation of such differentials and compares the + estimates obtained from two datasets. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DECIDE + url_git: '' +decido: + version: 0.3.0 + title: Bindings for 'Mapbox' Ear Cutting Triangulation Library + maintainer: Michael Sumner + description: |- + Provides constrained triangulation of polygons. Ear cutting (or + ear clipping) applies constrained triangulation by successively 'cutting' + triangles from a polygon defined by path/s. Holes are supported by introducing + a bridge segment between polygon paths. This package wraps the 'header-only' + library 'earcut.hpp' which includes + a reference to the method used by Held, M. (2001) . + date_publication: '2020-05-19' + bug_reports: https://github.com/hypertidy/decido/issues + url: https://hypertidy.github.io/decido + url_cran: https://CRAN.R-project.org/package=decido + url_git: '' +decision: + version: 0.1.0 + title: Statistical Decision Analysis + maintainer: Partha Sarathi Bishnu + description: Contains a function called dmur() which accepts four parameters like + possible values, probabilities of the values, selling cost and preparation cost. + The dmur() function generates various numeric decision parameters like MEMV (Maximum + (optimum) expected monitory value), best choice, EPPI (Expected profit with perfect + information), EVPI (Expected value of the perfect information), EOL (Expected + opportunity loss), which facilitate effective decision-making. + date_publication: '2016-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=decision + url_git: '' +decisionSupport: + version: '1.114' + title: Quantitative Support of Decision Making under Uncertainty + maintainer: Eike Luedeling + description: |- + Supporting the quantitative analysis of binary welfare based + decision making processes using Monte Carlo simulations. Decision support + is given on two levels: (i) The actual decision level is to choose between + two alternatives under probabilistic uncertainty. This package calculates + the optimal decision based on maximizing expected welfare. (ii) The meta + decision level is to allocate resources to reduce the uncertainty in the + underlying decision problem, i.e to increase the current information to + improve the actual decision making process. This problem is dealt with + using the Value of Information Analysis. The Expected Value of + Information for arbitrary prospective estimates can be calculated as + well as Individual Expected Value of Perfect Information. + The probabilistic calculations are done via Monte Carlo + simulations. This Monte Carlo functionality can be used on its own. + date_publication: '2024-04-08' + bug_reports: '' + url: http://www.worldagroforestry.org/ + url_cran: https://CRAN.R-project.org/package=decisionSupport + url_git: '' +deckgl: + version: 0.3.0 + title: An R Interface to 'deck.gl' + maintainer: Stefan Kuethe + description: |- + Makes 'deck.gl' , a WebGL-powered open-source JavaScript framework + for visual exploratory data analysis of large datasets, available within R via the 'htmlwidgets' package. + Furthermore, it supports basemaps from 'mapbox' via + 'mapbox-gl-js' . + date_publication: '2023-02-19' + bug_reports: https://github.com/crazycapivara/deckgl/issues/ + url: https://crazycapivara.github.io/deckgl/ + url_cran: https://CRAN.R-project.org/package=deckgl + url_git: https://github.com/crazycapivara/deckgl/ +declared: + version: '0.25' + title: Functions for Declared Missing Values + maintainer: Adrian Dusa + description: |- + A zero dependency package containing functions to declare labels + and missing values, coupled with associated functions to create (weighted) + tables of frequencies and various other summary measures. + Some of the base functions have been rewritten to make use of the specific + information about the missing values, most importantly to distinguish + between empty NA and declared NA values. + Some functions have similar functionality with the corresponding ones from + packages "haven" and "labelled". The aim is to ensure as much compatibility + as possible with these packages, while offering an alternative in the + objects of class "declared". + date_publication: '2024-09-08' + bug_reports: https://github.com/dusadrian/declared/issues + url: '' + url_cran: https://CRAN.R-project.org/package=declared + url_git: https://github.com/dusadrian/declared +DeclareDesign: + version: 1.0.10 + title: Declare and Diagnose Research Designs + maintainer: Graeme Blair + description: |- + Researchers can characterize and learn about the properties of + research designs before implementation using `DeclareDesign`. Ex ante + declaration and diagnosis of designs can help researchers clarify the + strengths and limitations of their designs and to improve their + properties, and can help readers evaluate a research strategy prior + to implementation and without access to results. It can also make it + easier for designs to be shared, replicated, and critiqued. + date_publication: '2024-04-21' + bug_reports: https://github.com/DeclareDesign/DeclareDesign/issues + url: https://declaredesign.org/r/declaredesign/ + url_cran: https://CRAN.R-project.org/package=DeclareDesign + url_git: https://github.com/DeclareDesign/DeclareDesign +decode: + version: '1.2' + title: Differential Co-Expression and Differential Expression Analysis + maintainer: Thomas Lui + description: Integrated differential expression (DE) and differential co-expression + (DC) analysis on gene expression data based on DECODE (DifferEntial CO-expression + and Differential Expression) algorithm. + date_publication: '2015-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=decode + url_git: '' +decoder: + version: 1.2.2 + title: Decode Coded Variables to Plain Text and the Other Way Around + maintainer: Erik Bulow + description: |- + Main function "decode" is used to decode coded key values to plain + text. Function "code" can be used to code plain text to code if there is a + 1:1 relation between the two. The concept relies on 'keyvalue' objects used + for translation. There are several 'keyvalue' objects included in the areas + of geographical regional codes, administrative health care unit codes, + diagnosis codes and more. It is also easy to extend the use by arbitrary + code sets. + date_publication: '2020-04-22' + bug_reports: https://www.bitbucket.com/cancercentrum/decoder/issues + url: https://www.bitbucket.com/cancercentrum/decoder + url_cran: https://CRAN.R-project.org/package=decoder + url_git: '' +decompDL: + version: 0.1.0 + title: |- + Decomposition Based Deep Learning Models for Time Series + Forecasting + maintainer: Kapil Choudhary + description: Hybrid model is the most promising forecasting method by combining + decomposition and deep learning techniques to improve the accuracy of time series + forecasting. Each decomposition technique decomposes a time series into a set + of intrinsic mode functions (IMFs), and the obtained IMFs are modelled and forecasted + separately using the deep learning models. Finally, the forecasts of all IMFs + are combined to provide an ensemble output for the time series. The prediction + ability of the developed models are calculated using international monthly price + series of maize in terms of evaluation criteria like root mean squared error, + mean absolute percentage error and, mean absolute error. For method details see + Choudhary, K. et al. (2023). . + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=decompDL + url_git: '' +decompML: + version: 0.1.1 + title: Decomposition Based Machine Learning Model + maintainer: Kapil Choudhary + description: The hybrid model is a highly effective forecasting approach that integrates + decomposition techniques with machine learning to enhance time series prediction + accuracy. Each decomposition technique breaks down a time series into multiple + intrinsic mode functions (IMFs), which are then individually modeled and forecasted + using machine learning algorithms. The final forecast is obtained by aggregating + the predictions of all IMFs, producing an ensemble output for the time series. + The performance of the developed models is evaluated using international monthly + maize price data, assessed through metrics such as root mean squared error (RMSE), + mean absolute percentage error (MAPE), and mean absolute error (MAE). For method + details see Choudhary, K. et al. (2023). . + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=decompML + url_git: '' +decomposedPSF: + version: '0.2' + title: |- + Time Series Prediction with PSF and Decomposition Methods (EMD + and EEMD) + maintainer: Neeraj Bokde + description: |- + Predict future values with hybrid combinations of Pattern Sequence based + Forecasting (PSF), Autoregressive Integrated Moving Average (ARIMA), Empirical Mode + Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) methods based + hybrid methods. + date_publication: '2022-05-01' + bug_reports: '' + url: https://www.neerajbokde.in/software/ + url_cran: https://CRAN.R-project.org/package=decomposedPSF + url_git: '' +DecomposeR: + version: 1.0.6 + title: Empirical Mode Decomposition for Cyclostratigraphy + maintainer: Sebastien Wouters + description: |- + Tools to apply Ensemble Empirical Mode + Decomposition (EEMD) for cyclostratigraphy purposes. Mainly: a new + algorithm, extricate, that performs EEMD in seconds, a linear interpolation + algorithm using the greatest rational common divisor of depth or time, + different algorithms to compute instantaneous amplitude, frequency and + ratios of frequencies, and functions to verify and visualise the outputs. + The functions were developed during the CRASH project (Checking the + Reproducibility of Astrochronology in the Hauterivian). When using for + publication please cite Wouters, S., Crucifix, M., Sinnesael, M., Da Silva, + A.C., Zeeden, C., Zivanovic, M., Boulvain, F., Devleeschouwer, X., 2022, + "A decomposition approach to cyclostratigraphic signal processing". + Earth-Science Reviews 225 (103894). + . + date_publication: '2023-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DecomposeR + url_git: '' +decompr: + version: 6.4.0 + title: Global Value Chain Decomposition + maintainer: Bastiaan Quast + description: |- + Three global value chain (GVC) decompositions are implemented. + The Leontief decomposition derives the value added origin of exports by + country and industry as in Hummels, Ishii and Yi (2001). The Koopman, + Wang and Wei (2014) decomposition splits country-level exports into 9 + value added components, and the Wang, Wei and Zhu (2013) decomposition + splits bilateral exports into 16 value added components. Various GVC + indicators based on these decompositions are computed in the + complimentary 'gvc' package. + --- References: --- + Hummels, D., Ishii, J., & Yi, K. M. (2001). The nature and growth of + vertical specialization in world trade. Journal of international + Economics, 54(1), 75-96. + Koopman, R., Wang, Z., & Wei, S. J. (2014). Tracing value-added and double + counting in gross exports. American Economic Review, 104(2), 459-94. + Wang, Z., Wei, S. J., & Zhu, K. (2013). Quantifying international production + sharing at the bilateral and sector levels (No. w19677). + National Bureau of Economic Research. + date_publication: '2022-06-19' + bug_reports: https://github.com/bquast/decompr/issues + url: https://qua.st/decompr/ + url_cran: https://CRAN.R-project.org/package=decompr + url_git: https://github.com/bquast/decompr +deconvolveR: + version: 1.2-1 + title: Empirical Bayes Estimation Strategies + maintainer: Balasubramanian Narasimhan + description: |- + Empirical Bayes methods for learning prior distributions from data. + An unknown prior distribution (g) has yielded (unobservable) parameters, each of + which produces a data point from a parametric exponential family (f). The goal + is to estimate the unknown prior ("g-modeling") by deconvolution and Empirical + Bayes methods. Details and examples are in the paper by Narasimhan and Efron + (2020, ). + date_publication: '2020-08-30' + bug_reports: https://github.com/bnaras/deconvolveR/issues + url: https://bnaras.github.io/deconvolveR/ + url_cran: https://CRAN.R-project.org/package=deconvolveR + url_git: '' +decor: + version: 1.0.2 + title: Retrieve Code Decorations + maintainer: Davis Vaughan + description: |- + Retrieves code comment decorations for C++ + languages of the form '\\ [[xyz]]', which are used for automated + wrapping of C++ functions. + date_publication: '2023-07-01' + bug_reports: https://github.com/r-lib/decor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=decor + url_git: https://github.com/r-lib/decor +DecorateR: + version: 0.1.2 + title: Fit and Deploy DECORATE Trees + maintainer: Matthias Bogaert + description: |- + DECORATE (Diverse Ensemble Creation by Oppositional Relabeling + of Artificial Training Examples) builds an ensemble of J48 trees by recursively + adding artificial samples of the training data ("Melville, P., & Mooney, R. J. (2005) "). + date_publication: '2020-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DecorateR + url_git: '' +decorators: + version: 0.3.0 + title: |- + Extend the Behaviour of a Function without Explicitly Modifying + it + maintainer: Harel Lustiger + description: |- + A decorator is a function that receives a function, extends + its behaviour, and returned the altered function. Any caller that uses + the decorated function uses the same interface as it were the + original, undecorated function. Decorators serve two primary uses: (1) + Enhancing the response of a function as it sends data to a second + component; (2) Supporting multiple optional behaviours. An example of + the first use is a timer decorator that runs a function, outputs its + execution time on the console, and returns the original function's + result. An example of the second use is input type validation + decorator that during running time tests whether the caller has passed + input arguments of a particular class. Decorators can reduce + execution time, say by memoization, or reduce bugs by adding defensive + programming routines. + date_publication: '2022-09-30' + bug_reports: https://github.com/tidylab/decorators/issues + url: https://tidylab.github.io/decorators/ + url_cran: https://CRAN.R-project.org/package=decorators + url_git: https://github.com/tidylab/decorators +decp: + version: 0.1.2 + title: Complete Change Point Analysis + maintainer: Vasileios Pavlopoulos + description: Provides a comprehensive approach for identifying and estimating change + points in multivariate time series through various statistical methods. Implements + the multiple change point detection methodology from Ryan & Killick (2023) + and a novel estimation methodology from Fotopoulos et al. (2023) + generalized to fit the detection methodologies. Performs both detection and estimation + of change points, providing visualization and summary information of the estimation + process for each detected change point. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=decp + url_git: '' +Deducer: + version: 0.7-9 + title: A Data Analysis GUI for R + maintainer: Ian Fellows + description: An intuitive, cross-platform graphical data analysis system. It uses + menus and dialogs to guide the user efficiently through the data manipulation + and analysis process, and has an excel like spreadsheet for easy data frame visualization + and editing. Deducer works best when used with the Java based R GUI JGR, but the + dialogs can be called from the command line. Dialogs have also been integrated + into the Windows Rgui. + date_publication: '2015-12-29' + bug_reports: '' + url: http://www.deducer.org/manual.htmlhttp://www.fellstat.com + url_cran: https://CRAN.R-project.org/package=Deducer + url_git: '' +deducorrect: + version: 1.3.7 + title: |- + Deductive Correction, Deductive Imputation, and Deterministic + Correction + maintainer: Mark van der Loo + description: A collection of methods for automated data cleaning where all actions + are logged. + date_publication: '2015-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deducorrect + url_git: https://github.com/data-cleaning/deducorrect +deductive: + version: 1.0.1 + title: Data Correction and Imputation Using Deductive Methods + maintainer: Mark van der Loo + description: |- + Attempt to repair inconsistencies and missing values in + data records by using information from valid values and + validation rules restricting the data. + date_publication: '2025-02-06' + bug_reports: https://github.com/data-cleaning/deductive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=deductive + url_git: https://github.com/data-cleaning/deductive +DeductiveR: + version: 1.1.0 + title: Deductive Rational Method + maintainer: Alonso Arriagada + description: 'Apply the Deductive Rational Method to a monthly series of flow or + precipitation data to fill in missing data. The method is as described in: Campos, + D.F., (1984, ISBN:9686194444).' + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DeductiveR + url_git: '' +deduped: + version: 0.2.0 + title: Making "Deduplicated" Functions + maintainer: Or Gadish + description: |- + Contains one main function deduped() which speeds up slow, + vectorized functions by only performing computations on the unique values + of the input and expanding the results at the end. + date_publication: '2023-11-07' + bug_reports: https://github.com/orgadish/deduped/issues + url: '' + url_cran: https://CRAN.R-project.org/package=deduped + url_git: https://github.com/orgadish/deduped +dedupewider: + version: 0.1.0 + title: Deduplication Across Multiple Columns + maintainer: Grzegorz Smoliński + description: |- + Duplicated data can exist in different rows and columns and user may need to + treat observations (rows) connected by duplicated data as one observation, + e.g. companies can belong to one family (and thus: be one company) by sharing + some telephone numbers. This package allows to find connected rows + based on data on chosen columns and collapse it into one row. + date_publication: '2021-10-28' + bug_reports: https://github.com/gsmolinski/dedupewider/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dedupewider + url_git: https://github.com/gsmolinski/dedupewider +deep: + version: 0.1.0 + title: A Neural Networks Framework + maintainer: Brian + description: |- + Explore neural networks in a layer oriented way, the framework + is intended to give the user total control of the + internals of a net without much effort. Use classes like PerceptronLayer + to create a layer of Percetron neurons, and specify how many you want. The + package does all the tricky stuff internally leaving you focused in what + you want. I wrote this package during a neural networks course to help me + with the problem set. + date_publication: '2019-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deep + url_git: '' +deepdep: + version: 0.4.3 + title: Visualise and Explore the Deep Dependencies of R Packages + maintainer: Dominik Rafacz + description: |- + Provides tools for exploration of R package dependencies. + The main deepdep() function allows to acquire deep dependencies of any package and plot them in an elegant way. + It also adds some popularity measures for the packages e.g. in the form of download count through the 'cranlogs' package. + Uses the CRAN metadata database and Bioconductor metadata . + Other data acquire functions are: get_dependencies(), get_downloads() and get_description(). + The deepdep_shiny() function runs shiny application that helps to produce a nice 'deepdep' plot. + date_publication: '2024-03-12' + bug_reports: https://github.com/DominikRafacz/deepdep/issues + url: https://dominikrafacz.github.io/deepdep/ + url_cran: https://CRAN.R-project.org/package=deepdep + url_git: https://github.com/DominikRafacz/deepdep +deepdive: + version: 1.0.4 + title: Deep Learning for General Purpose + maintainer: Rajesh Balakirshnan + description: Aims to provide simple intuitive functions to create quick prototypes + of artificial neural network or deep learning models. In addition novel ensemble + models like 'deeptree' and 'deepforest' has been included which combines decision + trees and neural network. + date_publication: '2021-07-10' + bug_reports: '' + url: https://rajeshb24.github.io/deepdive/ + url_cran: https://CRAN.R-project.org/package=deepdive + url_git: '' +deepgmm: + version: 0.2.1 + title: Deep Gaussian Mixture Models + maintainer: Suren Rathnayake + description: |- + Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) + provide a generalization of classical Gaussian mixtures + to multiple layers. Each layer contains a set of latent variables that follow a mixture of + Gaussian distributions. To avoid overparameterized solutions, dimension reduction is + applied at each layer by way of factor models. + date_publication: '2022-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deepgmm + url_git: https://github.com/suren-rathnayake/deepgmm +deepgp: + version: 1.1.3 + title: Bayesian Deep Gaussian Processes using MCMC + maintainer: Annie S. Booth + description: |- + Performs Bayesian posterior inference for deep Gaussian processes + following Sauer, Gramacy, and Higdon (2023, ). See Sauer + (2023, ) for comprehensive methodological + details and for a variety of + coding examples. Models are trained through MCMC including elliptical + slice sampling of latent Gaussian layers and Metropolis-Hastings + sampling of kernel hyperparameters. Vecchia-approximation for faster + computation is implemented following Sauer, Cooper, and Gramacy + (2023, ). Optional monotonic warpings are implemented + following Barnett et al. (2024, ). Downstream tasks include sequential design + through active learning Cohn/integrated mean squared error + (ALC/IMSE; Sauer, Gramacy, and Higdon, 2023), optimization through + expected improvement (EI; Gramacy, Sauer, and Wycoff, 2022 ), + and contour location through entropy + (Booth, Renganathan, and Gramacy, 2024 ). Models + extend up to three layers deep; a one layer model is equivalent to typical + Gaussian process regression. Incorporates OpenMP and SNOW parallelization + and utilizes C/C++ under the hood. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deepgp + url_git: '' +DeepLearningCausal: + version: 0.0.104 + title: Causal Inference with Super Learner and Deep Neural Networks + maintainer: Nguyen K. Huynh + description: |- + Functions to estimate Conditional Average Treatment Effects (CATE) + and Population Average Treatment Effects on the Treated (PATT) from + experimental or observational data using the Super Learner (SL) ensemble + method and Deep neural networks. The package first provides functions to + implement meta-learners such as the Single-learner (S-learner) and + Two-learner (T-learner) described in Künzel et al. (2019) + for estimating the CATE. The S- and T-learner + are each estimated using the SL ensemble method and deep neural networks. It + then provides functions to implement the Ottoboni and Poulos (2020) + PATT-C estimator to obtain the PATT from + experimental data with noncompliance by using the SL ensemble method and + deep neural networks. + date_publication: '2024-07-30' + bug_reports: https://github.com/hknd23/DeepLearningCausal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DeepLearningCausal + url_git: https://github.com/hknd23/DeepLearningCausal +deeplr: + version: 2.0.1 + title: Interface to the 'DeepL' Translation API + maintainer: David Zumbach + description: |- + A wrapper for the 'DeepL' Pro API , a web service + for translating texts between different languages. A DeepL API developer account is required + to use the service (see ). + date_publication: '2023-11-08' + bug_reports: https://github.com/zumbov2/deeplr/issues + url: https://www.deepl.com/translator + url_cran: https://CRAN.R-project.org/package=deeplr + url_git: '' +deepMOU: + version: 0.1.1 + title: |- + Clustering of Short Texts by Mixture of Unigrams and Its Deep + Extensions + maintainer: Martin D'Ippolito + description: Functions providing an easy and intuitive way for fitting and clusters + data using the Mixture of Unigrams models by means the Expectation-Maximization + algorithm (Nigam, K. et al. (2000). ), Mixture of + Dirichlet-Multinomials estimated by Gradient Descent (Anderlucci, Viroli (2020) + ) and Deep Mixture of Multinomials whose estimates + are obtained with Gibbs sampling scheme (Viroli, Anderlucci (2020) ). + There are also functions for graphical representation of clusters obtained. + date_publication: '2021-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deepMOU + url_git: '' +deepnet: + version: 0.2.1 + title: Deep Learning Toolkit in R + maintainer: Xiao Rong + description: |- + Implement some deep learning architectures and neural network + algorithms, including BP,RBM,DBN,Deep autoencoder and so on. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deepnet + url_git: '' +deepNN: + version: '1.2' + title: Deep Learning + maintainer: Benjamin Taylor + description: 'Implementation of some Deep Learning methods. Includes multilayer + perceptron, different activation functions, regularisation strategies, stochastic + gradient descent and dropout. Thanks go to the following references for helping + to inspire and develop the package: Ian Goodfellow, Yoshua Bengio, Aaron Courville, + Francis Bach (2016, ISBN:978-0262035613) Deep Learning. Terrence J. Sejnowski + (2018, ISBN:978-0262038034) The Deep Learning Revolution. Grant Sanderson (3brown1blue) + Neural + Networks YouTube playlist. Michael A. Nielsen + Neural Networks and Deep Learning.' + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deepNN + url_git: '' +deepredeff: + version: 0.1.1 + title: Deep Learning Prediction of Effectors + maintainer: Ruth Kristianingsih + description: |- + A tool that contains trained deep learning models + for predicting effector proteins. 'deepredeff' has been trained to + identify effector proteins using a set of known experimentally + validated effectors from either bacteria, fungi, or oomycetes. + Documentation is available via several vignettes, and the paper by + Kristianingsih and MacLean (2020) . + date_publication: '2021-07-16' + bug_reports: https://github.com/ruthkr/deepredeff/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=deepredeff + url_git: https://github.com/ruthkr/deepredeff/ +deepregression: + version: 2.2.0 + title: Fitting Deep Distributional Regression + maintainer: David Ruegamer + description: |- + Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as + proposed by Ruegamer et al. (2023) . + Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deepregression + url_git: '' +deepRstudio: + version: 0.0.9 + title: |- + Seamless Language Translation in 'RStudio' using 'DeepL' API and + 'Rstudioapi' + maintainer: Satoshi Kume + description: |- + Enhancing cross-language compatibility within the 'RStudio' environment and supporting seamless language understanding, + the 'deepRstudio' package leverages the power of the 'DeepL' API (see ) to enable seamless, fast, + accurate, and affordable translation of code comments, documents, and text. This package offers the ability to translate selected text + into English (EN), as well as from English into various languages, namely Japanese (JA), Chinese (ZH), Spanish (ES), + French (FR), Russian (RU), Portuguese (PT), and Indonesian (ID). With much of the text being written in English, the emphasis + is on compatibility from English. It is also designed for developers working on multilingual projects and data analysts collaborating + with international teams, simplifying the translation process and making code more accessible and comprehensible to people with + diverse language backgrounds. This package uses the 'rstudioapi' package and 'DeepL' API, and is simply implemented, executed + from addins or via shortcuts on 'RStudio'. With just a few steps, content can be translated between supported languages, promoting better + collaboration and expanding the global reach of work. The functionality of this package works only on 'RStudio' using 'rstudioapi'. + date_publication: '2023-09-13' + bug_reports: https://github.com/kumeS/deepRstudio/issues + url: https://kumes.github.io/deepRstudio/ + url_cran: https://CRAN.R-project.org/package=deepRstudio + url_git: https://github.com/kumeS/deepRstudio +deeptime: + version: 2.1.0 + title: Plotting Tools for Anyone Working in Deep Time + maintainer: William Gearty + description: |- + Extends the functionality of other plotting packages (notably 'ggplot2') + to help facilitate the plotting of data over long time intervals, including, + but not limited to, geological, evolutionary, and ecological data. The + primary goal of 'deeptime' is to enable users to add highly customizable + timescales to their visualizations. Other functions are also included to + assist with other areas of deep time visualization. + date_publication: '2024-10-25' + bug_reports: https://github.com/willgearty/deeptime/issues + url: https://williamgearty.com/deeptime/ + url_cran: https://CRAN.R-project.org/package=deeptime + url_git: https://github.com/willgearty/deeptime +deeptimedata: + version: 1.0.0 + title: Geologic Pattern Data from FGDC Used in 'deeptime' + maintainer: William Gearty + description: |- + Geologic pattern data from . + Access functions are provided in the accompanying package 'deeptime'. + date_publication: '2024-10-25' + bug_reports: https://github.com/willgearty/deeptimedata/issues + url: http://williamgearty.com/deeptimedata/ + url_cran: https://CRAN.R-project.org/package=deeptimedata + url_git: https://github.com/willgearty/deeptimedata +deeptrafo: + version: 1.0-0 + title: Fitting Deep Conditional Transformation Models + maintainer: Lucas Kook + description: |- + Allows for the specification of deep conditional transformation + models (DCTMs) and ordinal neural network transformation models, as + described in Baumann et al (2021) and + Kook et al (2022) . Extensions such as + autoregressive DCTMs (Ruegamer et al, 2023, ) + and transformation ensembles (Kook et al, 2022, ) + are implemented. The software package is described in Kook et al (2024, + ). + date_publication: '2024-12-03' + bug_reports: https://github.com/neural-structured-additive-learning/deeptrafo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=deeptrafo + url_git: https://github.com/neural-structured-additive-learning/deeptrafo +DEET: + version: 1.0.12 + title: Differential Expression Enrichment Tool + maintainer: Dustin Sokolowski + description: 'Abstract of Manuscript. Differential gene expression analysis using + RNA sequencing (RNA-seq) data is a standard approach for making biological discoveries. + Ongoing large-scale efforts to process and normalize publicly available gene expression + data enable rapid and systematic reanalysis. While several powerful tools systematically + process RNA-seq data, enabling their reanalysis, few resources systematically + recompute differentially expressed genes (DEGs) generated from individual studies. + We developed a robust differential expression analysis pipeline to recompute 3162 + human DEG lists from The Cancer Genome Atlas, Genotype-Tissue Expression Consortium, + and 142 studies within the Sequence Read Archive. After measuring the accuracy + of the recomputed DEG lists, we built the Differential Expression Enrichment Tool + (DEET), which enables users to interact with the recomputed DEG lists. DEET, available + through CRAN and RShiny, systematically queries which of the recomputed DEG lists + share similar genes, pathways, and TF targets to their own gene lists. DEET identifies + relevant studies based on shared results with the user’s gene lists, aiding in + hypothesis generation and data-driven literature review. Sokolowski, Dustin J., + et al. "Differential Expression Enrichment Tool (DEET): an interactive atlas of + human differential gene expression." Nucleic Acids Research Genomics and Bioinformatics + (2023).' + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEET + url_git: '' +DEEVD: + version: 1.2.3 + title: Density Estimation by Extreme Value Distributions + maintainer: Javaria Ahmad Khan + description: |- + Provides mean squared error (MSE) and plot the kernel densities related to extreme value distributions with their estimated values. + By using Gumbel and Weibull Kernel. See Salha et al. (2014) and Khan and Akbar (2021) . + date_publication: '2021-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEEVD + url_git: '' +default: + version: 1.0.0 + title: Change the Default Arguments in R Functions + maintainer: Nick Golding + description: |- + A simple syntax to change the default values for function + arguments, whether they are in packages or defined locally. + date_publication: '2017-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=default + url_git: '' +defineOptions: + version: '0.9' + title: Define and Parse Command Line Options + maintainer: Toshihiro Umehara + description: Parses command line arguments and supplies values to scripts. Users + can specify names to which parsed inputs are assigned, value types into which + inputs are cast, long options or short options, input splitters and callbacks + that define how options should be specified and how input values are supplied. + date_publication: '2023-10-28' + bug_reports: https://github.com/niceume/defineOptions + url: '' + url_cran: https://CRAN.R-project.org/package=defineOptions + url_git: https://github.com/niceume/defineOptions +defineR: + version: 0.0.4 + title: Creates Define XML Documents + maintainer: David Bosak + description: |- + Creates 'define.xml' documents used for regulatory + submissions based on spreadsheet metadata. Can also help + create metadata and generate HTML data explorer. + date_publication: '2022-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=defineR + url_git: '' +deFit: + version: 0.3.0 + title: Fitting Differential Equations to Time Series Data + maintainer: Yueqin Hu + description: Use numerical optimization to fit ordinary differential equations (ODEs) + to time series data to examine the dynamic relationships between variables or + the characteristics of a dynamical system. It can now be used to estimate the + parameters of ODEs up to second order, and can also apply to multilevel systems. + See for details. + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deFit + url_git: '' +deflateBR: + version: 1.1.2 + title: Deflate Nominal Brazilian Reais + maintainer: Fernando Meireles + description: Simple functions to deflate nominal Brazilian Reais using several popular + price indexes downloaded from the Brazilian Institute for Applied Economic Research. + date_publication: '2018-09-28' + bug_reports: https://github.com/meirelesff/deflatebr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=deflateBR + url_git: https://github.com/meirelesff/deflatebr/ +deflist: + version: 0.2.0 + title: |- + Deferred List - A Read-Only List-Like Object with Deferred + Access + maintainer: Bradley Buchsbaum + description: |- + Implements the 'deflist' class, a read-only list-like object that accesses its elements via a function. + The 'deflist' class can be used to model deferred access to data or computations by routing indexed list access to a function. + This approach is particularly useful when sequential list-like access to data is required but holding all the data in memory at once is not feasible. + The package also provides utilities for memoisation and caching to optimize access to frequently requested elements. + date_publication: '2023-04-27' + bug_reports: '' + url: https://bbuchsbaum.github.io/deflist/ + url_cran: https://CRAN.R-project.org/package=deflist + url_git: '' +deforestable: + version: 3.1.1 + title: Classify RGB Images into Forest or Non-Forest + maintainer: Dmitry Otryakhin + description: |- + Implements two out-of box classifiers presented in for + distinguishing forest and non-forest terrain images. Under these algorithms, there are + frequentist approaches: one parametric, using stable distributions, and another one- + non-parametric, using the squared Mahalanobis distance. The package also contains functions for + data handling and building of new classifiers as well as some test data set. + date_publication: '2022-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deforestable + url_git: '' +deform: + version: 1.0.0 + title: Spatial Deformation and Dimension Expansion Gaussian Processes + maintainer: Ben Youngman + description: Methods for fitting nonstationary Gaussian process models by spatial + deformation, as introduced by Sampson and Guttorp (1992) , + and by dimension expansion, as introduced by Bornn et al. (2012) . + Low-rank thin-plate regression splines, as developed in Wood, S.N. (2003) , + are used to either transform co-ordinates or create new latent dimensions. + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deform + url_git: '' +deformula: + version: 0.1.2 + title: |- + Integration of One-Dimensional Functions with Double Exponential + Formulas + maintainer: Hiroyuki Okamura + description: |- + Numerical quadrature of functions of one variable over a finite + or infinite interval with double exponential formulas. + date_publication: '2022-05-30' + bug_reports: https://github.com/okamumu/deformula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=deformula + url_git: https://github.com/okamumu/deformula/ +degday: + version: 0.4.0 + title: Compute Degree Days + maintainer: Andy Lyons + description: |- + Compute degree days from daily min and max temperatures for + modeling plant and insect development. + date_publication: '2022-09-13' + bug_reports: https://github.com/ucanr-igis/degday/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=degday + url_git: https://github.com/ucanr-igis/degday/ +DEGRE: + version: 0.2.0 + title: |- + Inferring Differentially Expressed Genes using Generalized + Linear Mixed Models + maintainer: Douglas Terra Machado + description: Genes that are differentially expressed between two or more experimental + conditions can be detected in RNA-Seq. A high biological variability may impact + the discovery of these genes once it may be divergent between the fixed effects. + However, this variability can be covered by the random effects. 'DEGRE' was designed + to identify the differentially expressed genes considering fixed and random effects + on individuals. These effects are identified earlier in the experimental design + matrix. 'DEGRE' has the implementation of preprocessing procedures to clean the + near zero gene reads in the count matrix, normalize by 'RLE' published in the + 'DESeq2' package, 'Love et al. (2014)' and it + fits a regression for each gene using the Generalized Linear Mixed Model with + the negative binomial distribution, followed by a Wald test to assess the regression + coefficients. + date_publication: '2022-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEGRE + url_git: '' +degreenet: + version: 1.3-6 + title: Models for Skewed Count Distributions Relevant to Networks + maintainer: Mark S. Handcock + description: Likelihood-based inference for skewed count distributions, typically + of degrees used in network modeling. "degreenet" is a part of the "statnet" suite + of packages for network analysis. See Jones and Handcock . + date_publication: '2024-09-25' + bug_reports: '' + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=degreenet + url_git: '' +degross: + version: 0.9.0 + title: Density Estimation from GROuped Summary Statistics + maintainer: Philippe Lambert + description: Estimation of a density from grouped (tabulated) summary statistics + evaluated in each of the big bins (or classes) partitioning the support of the + variable. These statistics include class frequencies and central moments of order + one up to four. The log-density is modelled using a linear combination of penalised + B-splines. The multinomial log-likelihood involving the frequencies adds up to + a roughness penalty based on the differences in the coefficients of neighbouring + B-splines and the log of a root-n approximation of the sampling density of the + observed vector of central moments in each class. The so-obtained penalized log-likelihood + is maximized using the EM algorithm to get an estimate of the spline parameters + and, consequently, of the variable density and related quantities such as quantiles, + see Lambert, P. (2021) for details. + date_publication: '2021-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=degross + url_git: '' +DEHOGT: + version: 0.99.0 + title: |- + Differentially Expressed Heterogeneous Overdispersion Gene Test + for Count Data + maintainer: Arlina Shen + description: |- + Implements a generalized linear model approach for detecting + differentially expressed genes across treatment groups in count data. The + package supports both quasi-Poisson and negative binomial models to handle + over-dispersion, ensuring robust identification of differential expression. + It allows for the inclusion of treatment effects and gene-wise covariates, + as well as normalization factors for accurate scaling across samples. + Additionally, it incorporates statistical significance testing with + options for p-value adjustment and log2 fold range thresholds, + making it suitable for RNA-seq analysis as described in by + Xu et al., (2024) . + date_publication: '2024-09-13' + bug_reports: https://github.com/ahshen26/DEHOGT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DEHOGT + url_git: https://github.com/ahshen26/DEHOGT +deident: + version: 1.0.0 + title: Persistent Data Anonymization Pipeline + maintainer: Robert Cook + description: |- + A framework for the replicable removal of personally identifiable data + (PID) in data sets. The package implements a suite of methods to suit different + data types based on the suggestions of Garfinkel (2015) + and the ICO "Guidelines on Anonymization" (2012) . + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deident + url_git: '' +dejaVu: + version: 0.3.1 + title: Multiple Imputation for Recurrent Events + maintainer: Jonathan Bartlett + description: |- + Performs reference based multiple imputation of recurrent event data + based on a negative binomial regression model, as described + by Keene et al (2014) . + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dejaVu + url_git: '' +Delaporte: + version: 8.4.1 + title: Statistical Functions for the Delaporte Distribution + maintainer: Avraham Adler + description: |- + Provides probability mass, distribution, quantile, random-variate + generation, and method-of-moments parameter-estimation functions for the + Delaporte distribution with parameterization based on Vose (2008) + . The Delaporte is a discrete probability distribution + which can be considered the convolution of a negative binomial distribution + with a Poisson distribution. Alternatively, it can be considered a counting + distribution with both Poisson and negative binomial components. It has been + studied in actuarial science as a frequency distribution which has more + variability than the Poisson, but less than the negative binomial. + date_publication: '2024-06-17' + bug_reports: https://github.com/aadler/Delaporte/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Delaporte + url_git: https://github.com/aadler/Delaporte +delayed: + version: 0.5.0 + title: A Framework for Parallelizing Dependent Tasks + maintainer: Jeremy Coyle + description: |- + Mechanisms to parallelize dependent tasks in a manner that + optimizes the compute resources available. It provides access to "delayed" + computations, which may be parallelized using futures. It is, to an extent, + a facsimile of the 'Dask' library (), for the 'Python' + language. + date_publication: '2024-04-29' + bug_reports: https://github.com/tlverse/delayed/issues + url: https://tlverse.org/delayed/ + url_cran: https://CRAN.R-project.org/package=delayed + url_git: '' +DelayedEffect.Design: + version: 1.1.3 + title: |- + Sample Size and Power Calculations using the APPLE, SEPPLE, + APPLE+ and SEPPLE+ Methods + maintainer: Bill Wheeler + description: Provides sample size and power calculations when the treatment time-lag + effect is present and the lag duration is either homogeneous across the individual + subject, or varies heterogeneously from individual to individual within a certain + domain and following a specific pattern. The methods used are described in Xu, + Z., Zhen, B., Park, Y., & Zhu, B. (2017) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DelayedEffect.Design + url_git: '' +deldir: + version: 2.0-4 + title: Delaunay Triangulation and Dirichlet (Voronoi) Tessellation + maintainer: Rolf Turner + description: "Calculates the Delaunay triangulation and the Dirichlet\nor Voronoi + tessellation (with respect to the entire plane) of\na planar point set. Plots + triangulations and tessellations in\nvarious ways. Clips tessellations to sub-windows. + Calculates\nperimeters of tessellations. Summarises information about\nthe tiles + of the tessellation.\tCalculates the centroidal\nVoronoi (Dirichlet) tessellation + using Lloyd's algorithm." + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deldir + url_git: '' +Delta: + version: 0.2.0.3 + title: Measure of Agreement Between Two Raters + maintainer: Antonio Rodriguez + description: |- + Measure of agreement delta was originally by Martín & Femia (2004) . + Since then has been considered as agreement measure for different + fields, since their behavior is usually better than the usual kappa index + by Cohen (1960) . The main issue with delta + is that can not be computed by hand contrary to kappa. The current algorithm + is based on the Version 5 of the delta windows program that can be found on + . + date_publication: '2019-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Delta + url_git: '' +deltaccd: + version: 1.0.2 + title: Quantify Rhythmic Gene Co-Expression Relative to a Reference + maintainer: Jake Hughey + description: |- + Infer progression of circadian rhythms in transcriptome data in + which samples are not labeled with time of day and coverage of the circadian + cycle may be incomplete. See Shilts et al. (2018) . + date_publication: '2022-02-11' + bug_reports: '' + url: https://deltaccd.hugheylab.org + url_cran: https://CRAN.R-project.org/package=deltaccd + url_git: https://github.com/hugheylab/deltaccd +DeltaMAN: + version: 0.5.0 + title: Delta Measurement of Agreement for Nominal Data + maintainer: Ana D. Maldonado + description: Analysis of agreement for nominal data between two raters using the + Delta model. This model is proposed as an alternative to the widespread measure + Cohen kappa coefficient, which performs poorly when the marginal distributions + are very asymmetric (Martin-Andres and Femia-Marzo (2004), ; + Martin-Andres and Femia-Marzo (2008) ). The package + also contains a function to perform a massive analysis of multiple raters against + a gold standard. A shiny app is also provided to obtain the measures of nominal + agreement between two raters. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DeltaMAN + url_git: '' +deltaPlotR: + version: '1.6' + title: |- + Identification of Dichotomous Differential Item Functioning + (DIF) using Angoff's Delta Plot Method + maintainer: David Magis + description: The deltaPlotR package implements Angoff's Delta Plot method to detect + dichotomous DIF. Several detection thresholds are included, either from multivariate + normality assumption or by prior determination. Item purification is supported + (Magis and Facon (2014) ). + date_publication: '2018-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deltaPlotR + url_git: '' +DELTD: + version: 2.6.8 + title: Kernel Density Estimation using Lifetime Distributions + maintainer: Javaria Ahmad Khan + description: |- + A collection of asymmetrical kernels belong to lifetime distributions for kernel density estimation is presented. + Mean Squared Errors (MSE) are calculated for estimated curves. For this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull. + For details see Chen (2000a,b), Jin and Kawczak (2003) and Salha et al. (2014) . + date_publication: '2022-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DELTD + url_git: '' +DEM: + version: 0.0.0.2 + title: |- + The Distributed EM Algorithms in Multivariate Gaussian Mixture + Models + maintainer: Qian Wang + description: The distributed expectation maximization algorithms are used to solve + parameters of multivariate Gaussian mixture models. The philosophy of the package + is described in Guo, G. (2022) . + date_publication: '2022-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEM + url_git: '' +dematel: + version: 0.1.0 + title: Decision Making Trial and Evaluation Laboratory Technique in R + maintainer: Muhlis Ozdemir + description: Developed to Solve the Multi-Criteria Decision Making Problems with + Decision Making Trial and Evaluation Laboratory Technique in R. + date_publication: '2021-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dematel + url_git: '' +demic: + version: 2.0.0 + title: Dynamic Estimator of Microbial Communities + maintainer: Charlie Bushman + description: |- + Multi-sample algorithm based on contigs and coverage values, to + infer the relative distances of contigs from the replication origin and to + accurately compare bacterial growth rates between samples. Yuan Gao and + Hongzhe Li (2018) . + date_publication: '2024-01-22' + bug_reports: https://github.com/Ulthran/DEMIC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=demic + url_git: https://github.com/Ulthran/DEMIC +deming: + version: 1.4-1 + title: |- + Deming, Theil-Sen, Passing-Bablock and Total Least Squares + Regression + maintainer: Terry Therneau + description: Generalized Deming regression, Theil-Sen regression and Passing-Bablock + regression functions. + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deming + url_git: '' +DemoDecomp: + version: 1.14.1 + title: Decompose Demographic Functions + maintainer: Tim Riffe + description: 'Three general demographic decomposition methods: Pseudo-continuous + decomposition proposed by Horiuchi, Wilmoth, and Pletcher (2008) , + stepwise replacement decomposition proposed by Andreev, Shkolnikov and Begun (2002) + , and lifetable response experiments proposed by + Caswell (1989) .' + date_publication: '2024-09-20' + bug_reports: https://github.com/timriffe/DemoDecomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DemoDecomp + url_git: '' +demodelr: + version: 1.0.1 + title: Simulating Differential Equations with Data + maintainer: John Zobitz + description: |- + Designed to support the visualization, numerical computation, + qualitative analysis, model-data fusion, and stochastic simulation for + autonomous systems of differential equations. Euler and Runge-Kutta methods + are implemented, along with tools to visualize the two-dimensional + phaseplane. Likelihood surfaces and a simple Markov Chain Monte Carlo + parameter estimator can be used for model-data fusion of differential + equations and empirical models. The Euler-Maruyama method is provided for + simulation of stochastic differential equations. The package was originally + written for internal use to support teaching by Zobitz, and refined to + support the text "Exploring modeling with data and differential equations + using R" by John Zobitz (2021) . + date_publication: '2022-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=demodelr + url_git: '' +demogR: + version: 0.6.0 + title: Analysis of Age-Structured Demographic Models + maintainer: Hana Sevcikova + description: Construction and analysis of matrix population models in R. + date_publication: '2018-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=demogR + url_git: '' +DemografixeR: + version: 0.1.1 + title: Extrapolate Gender, Age and Nationality of a Name + maintainer: Matthias Brenninkmeijer + description: Connects to the , and + APIs to estimate gender, age and nationality of a first name. + date_publication: '2020-05-06' + bug_reports: https://github.com/matbmeijer/DemografixeR/issues + url: https://matbmeijer.github.io/DemografixeR + url_cran: https://CRAN.R-project.org/package=DemografixeR + url_git: https://github.com/matbmeijer/DemografixeR +demoGraphic: + version: 0.1.0 + title: |- + Providing Demographic Table with the P-Value, Standardized Mean + Difference Value + maintainer: Loan Robinson + description: The Demographic Table in R combines contingency table for categorical + variables, mean and standard deviation for continuous variables. t-test, chi-square + test and Fisher's exact test calculated the p-value of two groups. The standardized + mean difference were performed with 95 % confident interval, and writing table + into document file. + date_publication: '2019-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=demoGraphic + url_git: '' +DemographicTable: + version: 0.1.10 + title: Creating Demographic Table + maintainer: Tingting Zhan + description: |- + Functions for creating demographic + table of simple summary statistics and + comparison(s) over one or more groups. + Returned value is printed via package + 'flextable'. + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DemographicTable + url_git: '' +demography: + version: '2.0' + title: Forecasting Mortality, Fertility, Migration and Population Data + maintainer: Rob Hyndman + description: |- + Functions for demographic analysis including lifetable + calculations; Lee-Carter modelling; functional data analysis of + mortality rates, fertility rates, net migration numbers; and + stochastic population forecasting. + date_publication: '2023-02-08' + bug_reports: https://github.com/robjhyndman/demography/issues + url: https://pkg.robjhyndman.com/demography/ + url_cran: https://CRAN.R-project.org/package=demography + url_git: https://github.com/robjhyndman/demography +demoKde: + version: 1.0.1 + title: Kernel Density Estimation for Demonstration Purposes + maintainer: Bill Venables + description: |- + Demonstration code showing how (univariate) kernel + density estimates are computed, at least conceptually, + and allowing users to experiment with different kernels, + should they so wish. The method used follows directly + the definition, but gains efficiency by replacing the + observations by frequencies in a very fine grid covering + the sample range. A canonical reference is + B. W. Silverman, (1998) . + NOTE: the density function in the + stats package uses a more sophisticated method based on the + fast Fourier transform and that function should be used if + computational efficiency is a prime consideration. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=demoKde + url_git: '' +DemoKin: + version: 1.0.3 + title: Estimate Population Kin Distribution + maintainer: Iván Williams + description: |- + Estimate population kin counts and its distribution by type, age and sex. + The package implements one-sex and two-sex framework for studying living-death availability, + with time varying rates or not, and multi-stage model. + date_publication: '2023-06-05' + bug_reports: https://github.com/IvanWilli/DemoKin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DemoKin + url_git: https://github.com/IvanWilli/DemoKin +demoShiny: + version: '0.1' + title: Runs a 'Shiny' App as Demo or Lists All Demo 'Shiny' Apps + maintainer: Sigbert Klinke + description: Mimics the demo functionality for 'Shiny' apps in a package. Apps stored + to the package subdirectory inst/shiny can be called by demoShiny(topic). + date_publication: '2020-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=demoShiny + url_git: '' +DEMOVA: + version: '1.0' + title: |- + DEvelopment (of Multi-Linear QSPR/QSAR) MOdels VAlidated using + Test Set + maintainer: Vinca Prana + description: 'Tool for the development of multi-linear QSPR/QSAR models (Quantitative + structure-property/activity relationship). Theses models are used in chemistry, + biology and pharmacy to find a relationship between the structure of a molecule + and its property (such as activity, toxicology but also physical properties). + The various functions of this package allows: selection of descriptors based of + variances, intercorrelation and user expertise; selection of the best multi-linear + regression in terms of correlation and robustness; methods of internal validation + (Leave-One-Out, Leave-Many-Out, Y-scrambling) and external using test sets.' + date_publication: '2016-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEMOVA + url_git: '' +demu: + version: 0.3.0 + title: Optimal Design Emulators via Point Processes + maintainer: Matthew T. Pratola + description: |- + Implements the Determinantal point process (DPP) based optimal design + emulator described in Pratola, Lin and Craigmile (2018) for + Gaussian process regression models. See + for more information and examples. + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=demu + url_git: '' +dendextend: + version: 1.19.0 + title: Extending 'dendrogram' Functionality in R + maintainer: Tal Galili + description: |- + Offers a set of functions for extending + 'dendrogram' objects in R, letting you visualize and compare trees of + 'hierarchical clusterings'. You can (1) Adjust a tree's graphical parameters + - the color, size, type, etc of its branches, nodes and labels. (2) + Visually and statistically compare different 'dendrograms' to one another. + date_publication: '2024-11-15' + bug_reports: https://github.com/talgalili/dendextend/issues + url: https://talgalili.github.io/dendextend/ + url_cran: https://CRAN.R-project.org/package=dendextend + url_git: https://github.com/talgalili/dendextend/ +dendRoAnalyst: + version: 0.1.5 + title: A Tool for Processing and Analyzing Dendrometer Data + maintainer: Sugam Aryal + description: There are various functions for managing and cleaning data before the + application of different approaches. This includes identifying and erasing sudden + jumps in dendrometer data not related to environmental change, identifying the + time gaps of recordings, and changing the temporal resolution of data to different + frequencies. Furthermore, the package calculates daily statistics of dendrometer + data, including the daily amplitude of tree growth. Various approaches can be + applied to separate radial growth from daily cyclic shrinkage and expansion due + to uptake and loss of stem water. In addition, it identifies periods of consecutive + days with user-defined climatic conditions in daily meteorological data, then + check what trees are doing during that period. + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dendRoAnalyst + url_git: '' +dendroextras: + version: 0.2.3 + title: Extra Functions to Cut, Label and Colour Dendrogram Clusters + maintainer: Gregory Jefferis + description: |- + Provides extra functions to manipulate dendrograms + that build on the base functions provided by the 'stats' package. The main + functionality it is designed to add is the ability to colour all the edges + in an object of class 'dendrogram' according to cluster membership i.e. each + subtree is coloured, not just the terminal leaves. In addition it provides + some utility functions to cut 'dendrogram' and 'hclust' objects and to + set/get labels. + date_publication: '2018-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dendroextras + url_git: '' +dendrometeR: + version: 1.1.1 + title: Analyzing Dendrometer Data + maintainer: Marko Smiljanic + description: |- + Various functions to import, verify, process and plot + high-resolution dendrometer data using daily and stem-cycle approaches + as described in Deslauriers et al, 2007 . + For more details about the package please see: + Van der Maaten et al. 2016 . + date_publication: '2025-02-21' + bug_reports: https://github.com/smiljanicm/dendrometeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dendrometeR + url_git: https://github.com/smiljanicm/dendrometeR +dendrometry: + version: 0.0.2 + title: Forest Estimations and Dendrometric Computations + maintainer: Narcisse Yehouenou + description: |- + Computation of dendrometric and structural + parameters from forest inventory data. The objective is to provide an + user-friendly R package for researchers, ecologists, foresters, + statisticians, loggers and others persons who deal with forest inventory + data. Useful conversion of angle value from degree to radian, conversion from + angle to slope (in percentage) and their reciprocals as well as principal + angle determination are also included. Position and dispersion parameters + usually found in forest studies are implemented. The package contains + Fibonacci series, its extensions and the Golden Number computation. + Useful references are Arcadius Y. J. Akossou, Soufianou Arzouma, + Eloi Y. Attakpa, Noël H. Fonton and Kouami Kokou (2013) + and W. Bonou, R. Glele Kakaï, A.E. Assogbadjo, H.N. Fonton, B. Sinsin (2009) + . + date_publication: '2023-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dendrometry + url_git: '' +dendroNetwork: + version: 0.5.4 + title: |- + Create Networks of Dendrochronological Series using Pairwise + Similarity + maintainer: Ronald Visser + description: Creating dendrochronological networks based on the similarity between + tree-ring series or chronologies. The package includes various functions to compare + tree-ring curves building upon the 'dplR' package. The networks can be used to + visualise and understand the relations between tree-ring curves. These networks + are also very useful to estimate the provenance of wood as described in Visser + (2021) or wood-use within a structure/context/site as described + in Visser and Vorst (2022) . + date_publication: '2024-04-30' + bug_reports: https://github.com/ropensci/dendroNetwork/issues + url: https://ropensci.github.io/dendroNetwork/ + url_cran: https://CRAN.R-project.org/package=dendroNetwork + url_git: https://github.com/ropensci/dendroNetwork +DendroSync: + version: 0.1.4 + title: |- + A Set of Tools for Calculating Spatial Synchrony Between + Tree-Ring Chronologies + maintainer: Josu G. Alday + description: |- + Provides functions for the calculation and plotting of synchrony in + tree growth from tree-ring width chronologies (TRW index). It combines + variance-covariance (VCOV) mixed modelling with functions that quantify + the degree to which the TRW chronologies contain a common temporal + signal. It also implements temporal trends in spatial synchrony using a + moving window. These methods can also be used with other kind of ecological + variables that have temporal autocorrelation corrected. + date_publication: '2022-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DendroSync + url_git: https://bitbucket.org/josucham/dendrosync/src/issues/ +dendroTools: + version: 1.2.13 + title: |- + Linear and Nonlinear Methods for Analyzing Daily and Monthly + Dendroclimatological Data + maintainer: Jernej Jevsenak + description: |- + Provides novel dendroclimatological methods, primarily used by the + Tree-ring research community. There are four core functions. The first one is + daily_response(), which finds the optimal sequence of days that are related + to one or more tree-ring proxy records. Similar function is daily_response_seascorr(), + which implements partial correlations in the analysis of daily response functions. + For the enthusiast of monthly data, there is monthly_response() function. + The last core function is compare_methods(), which effectively compares several + linear and nonlinear regression algorithms on the task of climate reconstruction. + date_publication: '2024-04-26' + bug_reports: https://github.com/jernejjevsenak/dendroTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dendroTools + url_git: https://github.com/jernejjevsenak/dendroTools +DendSer: + version: 1.0.2 + title: 'Dendrogram Seriation: Ordering for Visualisation' + maintainer: Catherine Hurley + description: Re-arranges a dendrogram to optimize visualisation-based cost functions. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DendSer + url_git: '' +dendsort: + version: 0.3.4 + title: Modular Leaf Ordering Methods for Dendrogram Nodes + maintainer: Evan Biederstedt + description: 'An implementation of functions to optimize ordering of nodes in a + dendrogram, without affecting the meaning of the dendrogram. A dendrogram can + be sorted based on the average distance of subtrees, or based on the smallest + distance value. These sorting methods improve readability and interpretability + of tree structure, especially for tasks such as comparison of different distance + measures or linkage types and identification of tight clusters and outliers. As + a result, it also introduces more meaningful reordering for a coupled heatmap + visualization. This method is described in "dendsort: modular leaf ordering methods + for dendrogram representations in R", F1000Research 2014, 3: 177 .' + date_publication: '2021-04-20' + bug_reports: https://github.com/evanbiederstedt/dendsort/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dendsort + url_git: https://github.com/evanbiederstedt/dendsort +denguedatahub: + version: 2.1.1 + title: A Tidy Format Datasets of Dengue by Country + maintainer: Thiyanga S. Talagala + description: Provides a weekly, monthly, yearly summary of dengue cases by state/ + province/ country. + date_publication: '2024-09-22' + bug_reports: https://github.com/thiyangt/denguedatahub/issues + url: https://denguedatahub.netlify.app/ + url_cran: https://CRAN.R-project.org/package=denguedatahub + url_git: '' +denim: + version: 1.0.0 + title: |- + Generate and Simulate Deterministic Discrete-Time Compartmental + Models + maintainer: Anh Phan + description: R package to build and simulate deterministic discrete-time compartmental + models that can be non-Markov. Length of stay in each compartment can be defined + to follow a parametric distribution (d_exponential(), d_gamma(), d_weibull(), + d_lognormal()) or a non-parametric distribution (nonparametric()). Other supported + types of transition from one compartment to another includes fixed transition + (constant()), multinomial (multinomial()), fixed transition probability (transprob()). + date_publication: '2024-06-05' + bug_reports: https://github.com/thinhong/denim/issues + url: https://drthinhong.com/denim/ + url_cran: https://CRAN.R-project.org/package=denim + url_git: https://github.com/thinhong/denim +denoiSeq: + version: 0.1.1 + title: Differential Expression Analysis Using a Bottom-Up Model + maintainer: Gershom Buri + description: Given count data from two conditions, it determines which transcripts + are differentially expressed across the two conditions using Bayesian inference + of the parameters of a bottom-up model for PCR amplification. This model is developed + in Ndifon Wilfred, Hilah Gal, Eric Shifrut, Rina Aharoni, Nissan Yissachar, Nir + Waysbort, Shlomit Reich Zeliger, Ruth Arnon, and Nir Friedman (2012), , + and results in a distribution for the counts that is a superposition of the binomial + and negative binomial distribution. + date_publication: '2018-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=denoiSeq + url_git: '' +denoiseR: + version: 1.0.2 + title: Regularized Low Rank Matrix Estimation + maintainer: Julie Josse + description: |- + Estimate a low rank matrix from noisy data using singular values + thresholding and shrinking functions. Impute missing values with matrix completion. The method is described in . + date_publication: '2020-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=denoiseR + url_git: '' +denovolyzeR: + version: 0.2.0 + title: Statistical Analyses of De Novo Genetic Variants + maintainer: James Ware + description: |- + An integrated toolset for the analysis of de novo (sporadic) + genetic sequence variants. denovolyzeR implements a mutational model that + estimates the probability of a de novo genetic variant arising in each human + gene, from which one can infer the expected number of de novo variants in a + given population size. Observed variant frequencies can then be compared against + expectation in a Poisson framework. denovolyzeR provides a suite of functions + to implement these analyses for the interpretation of de novo variation in human + disease. + date_publication: '2016-08-01' + bug_reports: http://github.com/jamesware/denovolyzeR/issues + url: http://denovolyzeR.org + url_cran: https://CRAN.R-project.org/package=denovolyzeR + url_git: '' +denseFLMM: + version: 0.1.2 + title: Functional Linear Mixed Models for Densely Sampled Data + maintainer: Jona Cederbaum + description: Estimation of functional linear mixed models for densely sampled data + based on functional principal component analysis. + date_publication: '2018-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=denseFLMM + url_git: '' +densEstBayes: + version: 1.0-2.2 + title: Density Estimation via Bayesian Inference Engines + maintainer: Matt P. Wand + description: 'Bayesian density estimates for univariate continuous random samples + are provided using the Bayesian inference engine paradigm. The engine options + are: Hamiltonian Monte Carlo, the no U-turn sampler, semiparametric mean field + variational Bayes and slice sampling. The methodology is described in Wand and + Yu (2020) .' + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=densEstBayes + url_git: '' +densitr: + version: '0.2' + title: Analysing Density Profiles from Resistance Drilling of Trees + maintainer: Luka Krajnc + description: |- + Provides various tools for analysing density profiles + obtained by resistance drilling. It can load individual or + multiple files and trim the starting and ending part of each + density profile. Tools are also provided to trim profiles + manually, to remove the trend from measurements using several + methods, to plot the profiles and to detect tree rings + automatically. Written with a focus on forestry use of resistance + drilling in standing trees. + date_publication: '2022-03-22' + bug_reports: https://github.com/krajnc/densitr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=densitr + url_git: https://github.com/krajnc/densitr +densityarea: + version: 0.1.0 + title: Polygons of Bivariate Density Distributions + maintainer: Josef Fruehwald + description: |- + With bivariate data, it is possible to calculate + 2-dimensional kernel density estimates that return polygons at given + levels of probability. 'densityarea' returns these polygons for + analysis, including for calculating their area. + date_publication: '2023-10-02' + bug_reports: https://github.com/JoFrhwld/densityarea/issues + url: https://jofrhwld.github.io/densityarea/ + url_cran: https://CRAN.R-project.org/package=densityarea + url_git: https://github.com/JoFrhwld/densityarea +densityClust: + version: 0.3.3 + title: Clustering by Fast Search and Find of Density Peaks + maintainer: Thomas Lin Pedersen + description: |- + An improved implementation (based on k-nearest neighbors) of + the density peak clustering algorithm, originally described by Alex + Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large + datasets (> 100,000 samples) very efficiently. It was initially implemented + by Thomas Lin Pedersen, with inputs from Sean Hughes and later improved by + Xiaojie Qiu to handle large datasets with kNNs. + date_publication: '2024-01-29' + bug_reports: https://github.com/thomasp85/densityClust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=densityClust + url_git: https://github.com/thomasp85/densityClust +DensParcorr: + version: '1.1' + title: |- + Dens-Based Method for Partial Correlation Estimation in Large + Scale Brain Networks + maintainer: Yikai Wang + description: Provide a Dens-based method for estimating functional connection in + large scale brain networks using partial correlation. + date_publication: '2018-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DensParcorr + url_git: '' +densratio: + version: 0.2.1 + title: Density Ratio Estimation + maintainer: Koji Makiyama + description: |- + Density ratio estimation. + The estimated density ratio function can be used in many applications such as + anomaly detection, change-point detection, covariate shift adaptation. + The implemented methods are uLSIF (Hido et al. (2011) ), + RuLSIF (Yamada et al. (2011) ), + and KLIEP (Sugiyama et al. (2007) ). + date_publication: '2019-06-30' + bug_reports: https://github.com/hoxo-m/densratio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=densratio + url_git: https://github.com/hoxo-m/densratio +denstrip: + version: 1.5.4 + title: |- + Density Strips and Other Methods for Compactly Illustrating + Distributions + maintainer: Christopher Jackson + description: Graphical methods for compactly illustrating probability distributions, + including density strips, density regions, sectioned density plots and varying + width strips. + date_publication: '2018-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=denstrip + url_git: '' +denvax: + version: 0.1.2 + title: Simple Dengue Test and Vaccinate Cost Thresholds + maintainer: Carl A. B. Pearson + description: |- + Provides the mathematical model described by "Serostatus Testing & Dengue Vaccine Cost-Benefit Thresholds" + in . Using the functions in the package, + that analysis can be repeated using sample life histories, either synthesized from local seroprevalence data + using other functions in this package (as in the manuscript) or from some other source. + The package provides a vignette which walks through the analysis in the publication, as well as a function + to generate a project skeleton for such an analysis. + date_publication: '2019-12-01' + bug_reports: https://gitlab.com/cabp_LSHTM/denvax/issues + url: '' + url_cran: https://CRAN.R-project.org/package=denvax + url_git: https://gitlab.com/cabp_LSHTM/denvax +DEoptim: + version: 2.2-8 + title: Global Optimization by Differential Evolution + maintainer: Katharine Mullen + description: |- + Implements the Differential Evolution algorithm for global + optimization of a real-valued function of a real-valued parameter + vector as described in Mullen et al. (2011) . + date_publication: '2022-11-11' + bug_reports: https://github.com/ArdiaD/DEoptim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DEoptim + url_git: https://github.com/ArdiaD/DEoptim +DEoptimR: + version: 1.1-3-1 + title: Differential Evolution Optimization in Pure R + maintainer: Eduardo L. T. Conceicao + description: |- + Differential Evolution (DE) stochastic heuristic algorithms for + global optimization of problems with and without general constraints. + The aim is to curate a collection of its variants that + (1) do not sacrifice simplicity of design, + (2) are essentially tuning-free, and + (3) can be efficiently implemented directly in the R language. + Currently, it provides implementations of the algorithms 'jDE' by + Brest et al. (2006) for single-objective + optimization and 'NCDE' by Qu et al. (2012) + for multimodal optimization (single-objective problems with + multiple solutions). + date_publication: '2024-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEoptimR + url_git: svn://svn.r-forge.r-project.org/svnroot/robustbase/pkg/DEoptimR +depcache: + version: 0.1-2 + title: Cache R Expressions, Taking Their Dependencies into Account + maintainer: Ivan Krylov + description: |- + Hash an expression with its dependencies and store its + value, reloading it from a file as long as both the expression and + its dependencies stay the same. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=depcache + url_git: '' +DepCens: + version: 0.2.3 + title: Dependent Censoring Regression Models + maintainer: Silvana Schneider + description: Dependent censoring regression models for survival multivariate data. + These models are based on extensions of the frailty models, capable to accommodating + the dependence between failure and censoring times, with Weibull and piecewise + exponential marginal distributions. Theoretical details regarding the models implemented + in the package can be found in Schneider et al. (2019) . + date_publication: '2023-03-26' + bug_reports: https://github.com/GabrielGrandemagne/DepCens/issues + url: https://gabrielgrandemagne.github.io/DepCens/ + url_cran: https://CRAN.R-project.org/package=DepCens + url_git: https://github.com/GabrielGrandemagne/DepCens +depCensoring: + version: 0.1.5 + title: Statistical Methods for Survival Data with Dependent Censoring + maintainer: Negera Wakgari Deresa + description: |- + Several statistical methods for analyzing survival data under various forms of dependent + censoring are implemented in the package. In addition to accounting for dependent censoring, it + offers tools to adjust for unmeasured confounding factors. The implemented approaches allow + users to estimate the dependency between survival time and dependent censoring time, based + solely on observed survival data. For more details on the methods, refer to Deresa and Van + Keilegom (2021) , Czado and Van Keilegom (2023) + , Crommen et al. (2024) , + Deresa and Van Keilegom (2024) and Willems et al. (2024+) + and Ding and Van Keilegom (2024). + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=depCensoring + url_git: '' +depcoeff: + version: 0.0.1 + title: Dependency Coefficients + maintainer: Eckhard Liebscher + description: Functions to compute coefficients measuring the dependence of two or + more than two variables. The functions can be deployed to gain information about + functional dependencies of the variables with emphasis on monotone functions. + The statistics describe how well one response variable can be approximated by + a monotone function of other variables. In regression analysis the variable selection + is an important issue. In this framework the functions could be useful tools in + modeling the regression function. Detailed explanations on the subject can be + found in papers Liebscher (2014) ; Liebscher (2017) + ; Liebscher (2019, submitted). + date_publication: '2020-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=depcoeff + url_git: '' +depend.truncation: + version: '3.0' + title: |- + Statistical Methods for the Analysis of Dependently Truncated + Data + maintainer: Takeshi Emura + description: |- + Estimation and testing methods for dependently truncated data. + Semi-parametric methods are based on Emura et al. (2011), Emura & Wang (2012), + and Emura & Murotani (2015). + Parametric approaches are based on Emura & Konno (2012) and Emura & Pan (2017). + A regression approach is based on Emura & Wang (2016). Quasi-independence tests are based on Emura & Wang (2010). + Right-truncated data for Japanese male centenarians are given by Emura & Murotani (2015). + date_publication: '2018-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=depend.truncation + url_git: '' +depigner: + version: 0.9.1 + title: A Utility Package to Help you Deal with "Pignas" + maintainer: Corrado Lanera + description: |- + Pigna [_pìn'n'a_] is the Italian word for pine cone. In + jargon, it is used to identify a task which is boring, banal, + annoying, painful, frustrating and maybe even with a not so beautiful + or rewarding result, just like the obstinate act of trying to + challenge yourself in extracting pine nuts from a pine cone, provided + that, in the end, you will find at least one inside it. Here you can + find a backpack of functions to be used to solve small everyday + problems of coding or analyzing (clinical) data, which would be + normally solved using quick-and-dirty patches. You will be able to + convert 'Hmisc' and 'rms' summary()es into data.frames ready to be + rendered by 'pander' and 'knitr'. You can access easy-to-use wrappers + to activate essential but useful progress bars (from 'progress') into + your loops or functionals. Easy setup and control Telegram's bots + (from 'telegram.bot') to send messages or to divert error messages to + a Telegram's chat. You also have some utilities helping you in the + development of packages, like the activation of the same user + interface of 'usethis' into your package, or call polite functions to + ask a user to install other packages. Finally, you find a set of + thematic sets of packages you may use to set up new environments + quickly, installing them in a single call. + date_publication: '2023-04-24' + bug_reports: https://github.com/CorradoLanera/depigner/issues + url: https://corradolanera.github.io/depigner/ + url_cran: https://CRAN.R-project.org/package=depigner + url_git: https://github.com/CorradoLanera/depigner +DepLogo: + version: 1.2.1 + title: Dependency Logo + maintainer: Jan Grau + description: Plots dependency logos from a set of aligned input sequences. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DepLogo + url_git: '' +DEploid: + version: 0.5.7 + title: Deconvolute Mixed Genomes with Unknown Proportions + maintainer: Joe Zhu + description: |- + Traditional phasing programs are limited to diploid organisms. + Our method modifies Li and Stephens algorithm with Markov chain Monte Carlo + (MCMC) approaches, and builds a generic framework that allows haplotype searches + in a multiple infection setting. This package is primarily developed as part of + the Pf3k project, which is a global collaboration using the latest + sequencing technologies to provide a high-resolution view of natural variation + in the malaria parasite Plasmodium falciparum. Parasite DNA are extracted from + patient blood sample, which often contains more than one parasite strain, with + unknown proportions. This package is used for deconvoluting mixed haplotypes, + and reporting the mixture proportions from each sample. + date_publication: '2025-01-20' + bug_reports: https://github.com/DEploid-dev/DEploid-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DEploid + url_git: https://github.com/DEploid-dev/DEploid-r +DEploid.utils: + version: 0.0.1 + title: '''DEploid'' Data Analysis and Results Interpretation' + maintainer: Joe Zhu + description: |- + 'DEploid' (Zhu et.al. 2018 ) + is designed for deconvoluting mixed genomes with unknown + proportions. Traditional phasing programs are limited to diploid organisms. + Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo + (MCMC) approaches, and builds a generic framework that allows haloptype + searches in a multiple infection setting. This package provides R functions + to support data analysis and results interpretation. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEploid.utils + url_git: '' +depmixS4: + version: 1.5-0 + title: |- + Dependent Mixture Models - Hidden Markov Models of GLMs and + Other Distributions in S4 + maintainer: Ingmar Visser + description: Fits latent (hidden) Markov models on mixed categorical and continuous + (time series) data, otherwise known as dependent mixture models, see Visser & + Speekenbrink (2010, ). + date_publication: '2021-05-12' + bug_reports: '' + url: https://depmix.github.io/ + url_cran: https://CRAN.R-project.org/package=depmixS4 + url_git: '' +DEPONS2R: + version: 1.2.6 + title: Read, Plot and Analyse Output from the DEPONS Model + maintainer: Jacob Nabe-Nielsen + description: Methods for analyzing population dynamics and movement tracks simulated + using the DEPONS model (v.3.0), for manipulating input + raster files, shipping routes and for analyzing sound propagated from ships. + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEPONS2R + url_git: '' +depower: + version: 2025.1.20 + title: Power Analysis for Differential Expression Studies + maintainer: Brett Klamer + description: |- + Provides a convenient framework to simulate, test, power, and visualize + data for differential expression studies with lognormal or negative binomial + outcomes. Supported designs are two-sample comparisons of independent or + dependent outcomes. Power may be summarized in the context of controlling the + per-family error rate or family-wise error rate. Negative binomial methods are + described in Yu, Fernandez, and Brock (2017) + and Yu, Fernandez, and Brock (2020) . + date_publication: '2025-01-23' + bug_reports: '' + url: https://brettklamer.com/work/depower/ + url_cran: https://CRAN.R-project.org/package=depower + url_git: https://bitbucket.org/bklamer/depower/ +deprivateR: + version: 0.1.0 + title: |- + Calculating and Analyzing Measures of Deprivation in the United + States + maintainer: Christopher Prener + description: |- + Provides a unified framework to building Area Deprivation Index (ADI), + Social Vulnerability Index (SVI), and Neighborhood Deprivation Index (NDI) + deprivation measures and accessing related data from the U.S. Census Bureau + such as Gini coefficient data. Tools are also available for calculating percentiles, + quantiles, and for creating clear map breaks for data visualization. + date_publication: '2025-01-29' + bug_reports: https://github.com/pfizer-opensource/deprivateR/issues + url: https://pfizer-opensource.github.io/deprivateR/ + url_cran: https://CRAN.R-project.org/package=deprivateR + url_git: '' +deps: + version: 0.4.0 + title: Dependency Management with 'roxygen'-Style Comments + maintainer: Peter Solymos + description: |- + Manage your source code dependencies + by decorating your existing R code with special, + 'roxygen'-style comments. + date_publication: '2024-07-07' + bug_reports: https://github.com/analythium/deps/issues + url: https://hub.analythium.io/deps/ + url_cran: https://CRAN.R-project.org/package=deps + url_git: https://github.com/analythium/deps +depth.plot: + version: '0.1' + title: Multivariate Analogy of Quantiles + maintainer: Somedip Karmakar + description: Could be used to obtain spatial depths, spatial ranks and outliers + of multivariate random variables. Could also be used to visualize DD-plots (a + multivariate generalization of QQ-plots). + date_publication: '2015-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=depth.plot + url_git: '' +DepthProc: + version: 2.1.5 + title: Statistical Depth Functions for Multivariate Analysis + maintainer: Zygmunt Zawadzki + description: |- + Data depth concept offers a variety of powerful and user friendly + tools for robust exploration and inference for multivariate data. The offered + techniques may be successfully used in cases of lack of our knowledge on + parametric models generating data due to their nature. The + package consist of among others implementations of several data depth techniques + involving multivariate quantile-quantile plots, multivariate scatter estimators, + multivariate Wilcoxon tests and robust regressions. + date_publication: '2022-02-03' + bug_reports: https://github.com/zzawadz/DepthProc/issues + url: https://www.depthproc.zstat.pl/ + url_cran: https://CRAN.R-project.org/package=DepthProc + url_git: https://github.com/zzawadz/DepthProc +depthTools: + version: '0.7' + title: Depth Tools Package + maintainer: Aurora Torrente + description: |- + Implementation of different statistical tools for the + description and analysis of gene expression data based on the + concept of data depth, namely, the scale curves for + visualizing the dispersion of one or various groups of samples + (e.g. types of tumors), a rank test to decide whether two groups + of samples come from a single distribution and two methods of + supervised classification techniques, the DS and TAD methods. + All these techniques are based on the Modified Band Depth, which + is a recent notion of depth with a low computational cost, what + renders it very appropriate for high dimensional data such as + gene expression data. + date_publication: '2021-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=depthTools + url_git: '' +DER: + version: '1.0' + title: Income Polarization Index + maintainer: Michail Tsagris + description: 'The DER (or PaF) income polarization index as proposed by Duclos J. + Y., Esteban, J. and Ray D. (2004). "Polarization: concepts, measurement, estimation". + Econometrica, 72(6): 1737--1772. . The index + may be computed for a single or for a range of values of the alpha-parameter. + Bootstrapping is also available.' + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DER + url_git: '' +DeRezende.Ferreira: + version: 0.1.0 + title: Zero Coupon Yield Curve Modelling + maintainer: Oleksandr Castello + description: |- + Modeling the zero coupon yield curve using the dynamic De Rezende and + Ferreira (2011) five factor model with variable + or fixed decaying parameters. For explanatory purposes, the package also + includes various short datasets of interest rates for the BRICS countries. + date_publication: '2019-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DeRezende.Ferreira + url_git: '' +Deriv: + version: 4.1.6 + title: Symbolic Differentiation + maintainer: Serguei Sokol + description: |- + R-based solution for symbolic differentiation. It admits + user-defined function as well as function substitution + in arguments of functions to be differentiated. Some symbolic + simplification is part of the work. + date_publication: '2024-09-13' + bug_reports: https://github.com/sgsokol/Deriv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Deriv + url_git: '' +derivmkts: + version: 0.2.5 + title: Functions and R Code to Accompany Derivatives Markets + maintainer: Robert McDonald + description: |- + A set of pricing and expository functions that should + be useful in teaching a course on financial derivatives. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=derivmkts + url_git: '' +DES: + version: 1.0.0 + title: Discrete Event Simulation + maintainer: Norm Matloff + description: |- + Discrete event simulation (DES) involves modeling of systems + having discrete, i.e. abrupt, state changes. For instance, when a job + arrives to a queue, the queue length abruptly increases by 1. This + package is an R implementation of the event-oriented approach to DES; + see the tutorial in Matloff (2008) + . + date_publication: '2017-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DES + url_git: '' +desc: + version: 1.4.3 + title: Manipulate DESCRIPTION Files + maintainer: Gábor Csárdi + description: |- + Tools to read, write, create, and manipulate DESCRIPTION + files. It is intended for packages that create or manipulate other + packages. + date_publication: '2023-12-10' + bug_reports: https://github.com/r-lib/desc/issues + url: https://desc.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=desc + url_git: https://github.com/r-lib/desc +descomponer: + version: '1.6' + title: Seasonal Adjustment by Frequency Analysis + maintainer: Francisco Parra + description: Decompose a time series into seasonal, trend and irregular components + using transformations to amplitude-frequency domain. + date_publication: '2021-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=descomponer + url_git: '' +descr: + version: 1.1.8 + title: Descriptive Statistics + maintainer: Jakson Aquino + description: |- + Weighted frequency and contingency tables of categorical + variables and of the comparison of the mean value of a numerical + variable by the levels of a factor, and methods to produce xtable + objects of the tables and to plot them. There are also functions to + facilitate the character encoding conversion of objects, to quickly + convert fixed width files into csv ones, and to export a data.frame to + a text file with the necessary R and SPSS codes to reread the data. + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=descr + url_git: https://github.com/jalvesaq/descr +describedata: + version: 0.1.1 + title: Miscellaneous Descriptive Functions + maintainer: Craig McGowan + description: |- + Helper functions for descriptive tasks such as making print-friendly bivariate + tables, sample size flow counts, and visualizing sample distributions. Also + contains 'R' approximations of some common 'SAS' and 'Stata' functions such + as 'PROC MEANS' from 'SAS' and 'ladder', 'gladder', and 'pwcorr' from 'Stata'. + date_publication: '2025-01-10' + bug_reports: https://github.com/craigjmcgowan/describedata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=describedata + url_git: https://github.com/craigjmcgowan/describedata +DescribeDF: + version: 0.2.1 + title: Description of a Data Frame + maintainer: Sandip Garai + description: Helps to describe a data frame in hand. Has been developed during PhD + work of the maintainer. More information may be obtained from Garai and Paul (2023) + . + date_publication: '2023-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DescribeDF + url_git: '' +DescribeDisplay: + version: 0.2.11 + title: An Interface to the 'DescribeDisplay' 'GGobi' Plugin + maintainer: Dianne Cook + description: |- + Produce publication quality graphics from output of 'GGobi' + describe display plugin. + date_publication: '2023-08-25' + bug_reports: https://github.com/ggobi/DescribeDisplay/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DescribeDisplay + url_git: https://github.com/ggobi/DescribeDisplay +describer: + version: 0.2.0 + title: Describe Data in R Using Common Descriptive Statistics + maintainer: Paul Hendricks + description: |- + Allows users to quickly and easily describe data using + common descriptive statistics. + date_publication: '2015-09-17' + bug_reports: https://github.com/paulhendricks/describer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=describer + url_git: https://github.com/paulhendricks/describer +descriptio: + version: '1.3' + title: Descriptive Statistical Analysis + maintainer: Nicolas Robette + description: 'Description of statistical associations between two variables : measures + of local and global association between variables (phi, Cramér V, correlations, + eta-squared, Goodman and Kruskal tau, permutation tests, etc.), multiple graphical + representations of the associations between two variables (using ''ggplot2'') + and weighted statistics.' + date_publication: '2024-03-07' + bug_reports: https://github.com/nicolas-robette/descriptio/issues + url: https://nicolas-robette.github.io/descriptio/ + url_cran: https://CRAN.R-project.org/package=descriptio + url_git: https://github.com/nicolas-robette/descriptio +DescriptiveRepresentationCalculator: + version: 1.1.0 + title: Characterizing Observed and Expected Representation + maintainer: Connor Jerzak + description: A system for analyzing descriptive representation, especially for comparing + the composition of a political body to the population it represents. Users can + compute the expected degree of representation for a body under a random sampling + model, the expected degree of representation variability, as well as representation + scores from observed political bodies. The package is based on Gerring, Jerzak, + and Oncel (2024) . + date_publication: '2025-01-14' + bug_reports: https://github.com/cjerzak/DescriptiveRepresentationCalculator-software/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DescriptiveRepresentationCalculator + url_git: https://github.com/cjerzak/DescriptiveRepresentationCalculator-software/ +DescriptiveStats.OBeu: + version: 1.3.2 + title: Descriptive Statistics 'OpenBudgets.eu' + maintainer: Kleanthis Koupidis + description: Estimate and return the needed parameters for visualizations designed + for 'OpenBudgets.eu' datasets. Calculate descriptive + statistical measures in budget data of municipalities across Europe, according + to the 'OpenBudgets.eu' data model. There are functions for measuring central + tendency and dispersion of amount variables along with their distributions and + correlations and the frequencies of categorical variables for a given dataset. + Also, can be used generally to other datasets, to extract visualization parameters, + convert them to 'JSON' format and use them as input in a different graphical interface. + date_publication: '2020-05-04' + bug_reports: https://github.com/okgreece/DescriptiveStats.OBeu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DescriptiveStats.OBeu + url_git: https://github.com/okgreece/DescriptiveStats.OBeu +DescriptiveWH: + version: 1.0.3 + title: Descriptive Statistics + maintainer: William Herrera-Caceres + description: Exploratory analysis of a data base. Using the functions of this package + is possible to filter the data set detecting atypical values (outliers) and to + perform exploratory analysis through visual inspection or dispersion measures. + With this package you can explore the structure of your data using several parameters + at the same time joining statistical parameters with different graphics. Finally, + this package aid to confirm or reject the hypothesis that your data structure + presents a normal distribution. Therefore this package is useful to get a previous + insight of your data before to carry out statistical analysis. + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DescriptiveWH + url_git: https://github.com/William-HC/DescriptiveWH +descriptr: + version: 0.6.0 + title: Generate Descriptive Statistics + maintainer: Aravind Hebbali + description: |- + Generate descriptive statistics such as measures of location, + dispersion, frequency tables, cross tables, group summaries and multiple + one/two way tables. + date_publication: '2024-11-08' + bug_reports: https://github.com/rsquaredacademy/descriptr/issues + url: https://descriptr.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=descriptr + url_git: https://github.com/rsquaredacademy/descriptr +DescrTab2: + version: 2.1.16 + title: Publication Quality Descriptive Statistics Tables + maintainer: Jan Meis + description: |- + Provides functions to create descriptive statistics tables for continuous and categorical variables. + By default, summary statistics such as mean, standard deviation, quantiles, minimum and maximum for continuous + variables and relative and absolute frequencies for categorical variables are calculated. 'DescrTab2' features a sophisticated algorithm to + choose appropriate test statistics for your data and provides p-values. On top of this, confidence intervals for group + differences of appropriated summary measures are automatically produces for two-group comparison. + Tables generated by 'DescrTab2' can be integrated in a variety of document formats, including .html, .tex and .docx documents. + 'DescrTab2' also allows printing tables to console and saving table objects for later use. + date_publication: '2022-09-06' + bug_reports: https://github.com/imbi-heidelberg/DescrTab2/issues + url: https://imbi-heidelberg.github.io/DescrTab2/ + url_cran: https://CRAN.R-project.org/package=DescrTab2 + url_git: '' +descstat: + version: 0.1-2 + title: Tools for Descriptive Statistics + maintainer: Yves Croissant + description: A toolbox for descriptive statistics, based on the computation of frequency + and contingency tables. Several statistical functions and plot methods are provided + to describe univariate or bivariate distributions of factors, integer series and + numerical series either provided as individual values or as bins. + date_publication: '2021-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=descstat + url_git: '' +descstatsr: + version: 0.1.0 + title: Descriptive Univariate Statistics + maintainer: Harish Kumar + description: |- + It generates summary statistics on the input dataset using different descriptive univariate + statistical measures on entire data or at a group level. Though there are other packages which does + similar job but each of these are deficient in one form or other, in the measures generated, in + treating numeric, character and date variables alike, no functionality to view these measures on a + group level or the way the output is represented. Given the foremost role of the descriptive statistics + in any of the exploratory data analysis or solution development, there is a need for a more constructive, + structured and refined version over these packages. This is the idea behind the package and it brings + together all the required descriptive measures to give an initial understanding of the data quality, + distribution in a faster,easier and elaborative way.The function brings an additional capability to be + able to generate these statistical measures on the entire dataset or at a group level. It calculates measures + of central tendency (mean, median), distribution (count, proportion), dispersion (min, max, quantile, + standard deviation, variance) and shape (skewness, kurtosis). Addition to these measures, it provides information on + the data type, count on no. of rows, unique entries and percentage of missing entries. More importantly the measures + are generated based on the data types as required by them,rather than applying numerical measures on character and + data variables and vice versa. Output as a dataframe object gives a very neat representation, which often is useful + when working with a large number of columns. It can easily be exported as csv and analyzed further or presented as a + summary report for the data. + date_publication: '2018-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=descstatsr + url_git: '' +desctable: + version: 0.3.0 + title: Produce Descriptive and Comparative Tables Easily + maintainer: Maxime Wack + description: |- + Easily create descriptive and comparative tables. + It makes use and integrates directly with the tidyverse family of packages, and pipes. + Tables are produced as (nested) dataframes for easy manipulation. + date_publication: '2022-03-24' + bug_reports: https://github.com/desctable/desctable/issues + url: https://desctable.github.io + url_cran: https://CRAN.R-project.org/package=desctable + url_git: '' +DescTools: + version: 0.99.59 + title: Tools for Descriptive Statistics + maintainer: Andri Signorell + description: A collection of miscellaneous basic statistic functions and convenience + wrappers for efficiently describing data. The author's intention was to create + a toolbox, which facilitates the (notoriously time consuming) first descriptive + tasks in data analysis, consisting of calculating descriptive statistics, drawing + graphical summaries and reporting the results. The package contains furthermore + functions to produce documents using MS Word (or PowerPoint) and functions to + import data from Excel. Many of the included functions can be found scattered + in other packages and other sources written partly by Titans of R. The reason + for collecting them here, was primarily to have them consolidated in ONE instead + of dozens of packages (which themselves might depend on other packages which are + not needed at all), and to provide a common and consistent interface as far as + function and arguments naming, NA handling, recycling rules etc. are concerned. + Google style guides were used as naming rules (in absence of convincing alternatives). + The 'BigCamelCase' style was consequently applied to functions borrowed from contributed + R packages as well. + date_publication: '2025-01-26' + bug_reports: https://github.com/AndriSignorell/DescTools/issues + url: https://andrisignorell.github.io/DescTools/ + url_cran: https://CRAN.R-project.org/package=DescTools + url_git: https://github.com/AndriSignorell/DescTools/ +DescToolsAddIns: + version: '1.12' + title: Interactive Functions to be Used as Shortcuts in 'RStudio' + maintainer: Andri Signorell + description: '''RStudio'' as of recently offers the option to define addins and + assign shortcuts to them. This package contains addins for a few most frequently + used functions in a data scientist''s (at least mine) daily work (like str(), + example(), plot(), head(), view(), Desc()). Most of these functions will use the + current selection in the editor window and send the specific command to the console + while instantly executing it. Assigning shortcuts to these addins will save you + quite a few keystrokes.' + date_publication: '2024-10-30' + bug_reports: https://github.com/AndriSignorell/DescToolsAddIns/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DescToolsAddIns + url_git: https://github.com/AndriSignorell/DescToolsAddIns/ +deseats: + version: 1.1.0 + title: |- + Data-Driven Locally Weighted Regression for Trend and + Seasonality in TS + maintainer: Dominik Schulz + description: |- + Various methods for the identification of trend and seasonal + components in time series (TS) are provided. Among them is a data-driven locally + weighted regression approach with automatically selected bandwidth for + equidistant short-memory time series. The approach is a + combination / extension of the algorithms by + Feng (2013) and Feng, Y., Gries, T., + and Fritz, M. (2020) and a brief + description of this new method is provided in the package documentation. + Furthermore, the package allows its users to apply the base model of the + Berlin procedure, version 4.1, as described in Speth (2004) . + Permission to include this procedure was kindly provided by the Federal + Statistical Office of Germany. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deseats + url_git: '' +Design.parameters: + version: 0.1.0 + title: Parameters of the Experimental Designs + maintainer: Vinaykumar L.N. + description: Here, a function has been developed to generate parameters of the input + designs, as well as incidence matrices. This is a general function that can be + used to investigate the characterization properties of any block design. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Design.parameters + url_git: '' +DesignCTPB: + version: 1.1.3 + title: Design Clinical Trials with Potential Biomarker Effect + maintainer: Yitao Lu + description: Applying 'CUDA' 'GPUs' via 'Numba' for optimal clinical design. It + allows the user to utilize a 'reticulate' 'Python' environment and run intensive + Monte Carlo simulation to get the optimal cutoff for the clinical design with + potential biomarker effect, which can guide the realistic clinical trials. + date_publication: '2021-09-21' + bug_reports: https://github.com/ubcxzhang/DesignCTPB/issues + url: YLu(2020) + url_cran: https://CRAN.R-project.org/package=DesignCTPB + url_git: https://github.com/ubcxzhang/DesignCTPB +designer: + version: 0.3.0 + title: '''Shiny'' UI Prototype Builder' + maintainer: Ashley Baldry + description: |- + A 'shiny' application that enables the user to create a + prototype UI, being able to drag and drop UI components before being + able to save or download the equivalent R code. + date_publication: '2023-08-20' + bug_reports: https://github.com/ashbaldry/designer/issues + url: https://ashbaldry.github.io/designer/ + url_cran: https://CRAN.R-project.org/package=designer + url_git: '' +designit: + version: 0.5.0 + title: Blocking and Randomization for Experimental Design + maintainer: Iakov I. Davydov + description: |2- + + Intelligently assign samples to batches in order to reduce batch effects. + Batch effects can have a significant impact on data analysis, especially + when the assignment of samples to batches coincides with the contrast + groups being studied. By defining a batch container and a scoring function + that reflects the contrasts, this package allows users to assign samples in + a way that minimizes the potential impact of batch effects on the + comparison of interest. Among other functionality, we provide an + implementation for OSAT score by Yan et al. (2012, + ). + date_publication: '2024-03-21' + bug_reports: https://github.com/BEDApub/designit/issues + url: https://bedapub.github.io/designit/ + url_cran: https://CRAN.R-project.org/package=designit + url_git: https://github.com/BEDApub/designit/ +DesignLibrary: + version: 0.1.10 + title: Library of Research Designs + maintainer: Jasper Cooper + description: |2- + + A simple interface to build designs using the package 'DeclareDesign'. + In one line of code, users can specify the parameters of individual + designs and diagnose their properties. The designers can also be used + to compare performance of a given design across a range of combinations + of parameters, such as effect size, sample size, and assignment probabilities. + date_publication: '2021-10-18' + bug_reports: '' + url: https://declaredesign.org/r/designlibrary/ + url_cran: https://CRAN.R-project.org/package=DesignLibrary + url_git: https://github.com/DeclareDesign/DesignLibrary +designmatch: + version: 0.5.4 + title: Matched Samples that are Balanced and Representative by Design + maintainer: Jose R. Zubizarreta + description: Includes functions for the construction of matched samples that are + balanced and representative by design. Among others, these functions can be used + for matching in observational studies with treated and control units, with cases + and controls, in related settings with instrumental variables, and in discontinuity + designs. Also, they can be used for the design of randomized experiments, for + example, for matching before randomization. By default, 'designmatch' uses the + 'highs' optimization solver, but its performance is greatly enhanced by the 'Gurobi' + optimization solver and its associated R interface. For their installation, please + follow the instructions at + and . We + have also included directions in the gurobi_installation file in the inst folder. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=designmatch + url_git: '' +designr: + version: 0.1.13 + title: Balanced Factorial Designs + maintainer: Maximilian M. Rabe + description: Generate balanced factorial designs with crossed and nested random + and fixed effects . + date_publication: '2023-05-05' + bug_reports: https://github.com/mmrabe/designr/issues + url: https://maxrabe.com/designr + url_cran: https://CRAN.R-project.org/package=designr + url_git: '' +designsize: + version: 0.1.0 + title: Sample Size Calculation of Various Study Designs + maintainer: Atanu Bhattacharjee + description: |- + Different sample size calculations with different study designs. + These techniques are explained by Chow (2007) + . + date_publication: '2021-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=designsize + url_git: '' +desiR: + version: 1.2.2 + title: |- + Desirability Functions for Ranking, Selecting, and Integrating + Data + maintainer: Stanley E. Lazic + description: |- + Functions for (1) ranking, selecting, and prioritising genes, + proteins, and metabolites from high dimensional biology experiments, (2) + multivariate hit calling in high content screens, and (3) combining data + from diverse sources. + date_publication: '2021-04-16' + bug_reports: https://github.com/stanlazic/desiR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=desiR + url_git: https://github.com/stanlazic/desiR +desirability: + version: '2.1' + title: Function Optimization and Ranking via Desirability Functions + maintainer: Max Kuhn + description: S3 classes for multivariate optimization using the desirability function + by Derringer and Suich (1980). + date_publication: '2016-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=desirability + url_git: https://github.com/topepo/desirability +desirability2: + version: 0.0.1 + title: Desirability Functions for Multiparameter Optimization + maintainer: Max Kuhn + description: |- + In-line functions for multivariate optimization via desirability + functions (Derringer and Suich, 1980, ) + with easy use within 'dplyr' pipelines. + date_publication: '2023-05-11' + bug_reports: '' + url: https://desirability2.tidymodels.org + url_cran: https://CRAN.R-project.org/package=desirability2 + url_git: https://github.com/tidymodels/desirability2 +desk: + version: 1.1.2 + title: Didactic Econometrics Starter Kit + maintainer: Soenke Hoffmann + description: |- + Written to help undergraduate as well as graduate students to get started + with R for basic econometrics without the need to import specific functions + and datasets from many different sources. Primarily, the package is meant to + accompany the German textbook Auer, L.v., Hoffmann, S., Kranz, T. (2024, + ISBN: 978-3-662-68263-0) from which the exercises cover all the topics from the textbook + Auer, L.v. (2023, ISBN: 978-3-658-42699-6). + date_publication: '2024-12-20' + bug_reports: https://github.com/OvGU-SH/desk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=desk + url_git: https://github.com/OvGU-SH/desk +desla: + version: 0.3.0 + title: Desparsified Lasso Inference for Time Series + maintainer: Robert Adamek + description: Calculates the desparsified lasso as originally introduced in van de + Geer et al. (2014) , and provides inference suitable for + high-dimensional time series, based on the long run covariance estimator in Adamek + et al. (2020) . Also estimates high-dimensional local projections + by the desparsified lasso, as described in Adamek et al. (2022) . + date_publication: '2023-06-29' + bug_reports: https://github.com/RobertAdamek/desla/issues + url: '' + url_cran: https://CRAN.R-project.org/package=desla + url_git: https://github.com/RobertAdamek/desla +deSolve: + version: '1.40' + title: |- + Solvers for Initial Value Problems of Differential Equations + ('ODE', 'DAE', 'DDE') + maintainer: Thomas Petzoldt + description: |- + Functions that solve initial value problems of a system + of first-order ordinary differential equations ('ODE'), of + partial differential equations ('PDE'), of differential + algebraic equations ('DAE'), and of delay differential + equations. The functions provide an interface to the FORTRAN + functions 'lsoda', 'lsodar', 'lsode', 'lsodes' of the 'ODEPACK' + collection, to the FORTRAN functions 'dvode', 'zvode' and 'daspk' + and a C-implementation of solvers of the 'Runge-Kutta' family with + fixed or variable time steps. The package contains routines + designed for solving 'ODEs' resulting from 1-D, 2-D and 3-D + partial differential equations ('PDE') that have been converted + to 'ODEs' by numerical differencing. + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deSolve + url_git: http://desolve.r-forge.r-project.org/ +despair: + version: 0.1.1 + title: |- + Motivational Quotes and Shakespearean Bard–bits for Personal + Projects + maintainer: JP Monteagudo + description: Generate motivational quotes and Shakespearean word combinations (bard–bits) + that a user can consider for their personal projects. Each of the package functions + takes two arguments, cat which default to any, and a a numeric or character seed + to ensure reproducible results. + date_publication: '2024-10-24' + bug_reports: https://github.com/jpmonteagudo28/despair/issues + url: '' + url_cran: https://CRAN.R-project.org/package=despair + url_git: https://github.com/jpmonteagudo28/despair +desplot: + version: '1.10' + title: Plotting Field Plans for Agricultural Experiments + maintainer: Kevin Wright + description: A function for plotting maps of agricultural field experiments that + are laid out in grids. See Ryder (1981) . + date_publication: '2023-03-09' + bug_reports: https://github.com/kwstat/desplot/issues + url: https://kwstat.github.io/desplot/ + url_cran: https://CRAN.R-project.org/package=desplot + url_git: '' +details: + version: 0.4.0 + title: Create Details HTML Tag for Markdown and Package Documentation + maintainer: Jonathan Sidi + description: |- + Create a details HTML tag around R objects to place + in a Markdown, 'Rmarkdown' and 'roxygen2' documentation. + date_publication: '2025-02-09' + bug_reports: https://github.com/yonicd/details/issues + url: '' + url_cran: https://CRAN.R-project.org/package=details + url_git: https://github.com/yonicd/details +detect: + version: 0.4-6 + title: Analyzing Wildlife Data with Detection Error + maintainer: Peter Solymos + description: |- + Models for analyzing site occupancy and count data models + with detection error, including single-visit based models, + conditional distance sampling and time-removal models. + Package development was supported by the + Alberta Biodiversity Monitoring Institute + and the Boreal Avian Modelling Project. + date_publication: '2023-03-08' + bug_reports: https://github.com/psolymos/detect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=detect + url_git: https://github.com/psolymos/detect +detectnorm: + version: 1.0.0 + title: Detect Nonnormality in Meta-Analysis without Raw Data + maintainer: Rongwei Sun + description: 'Non-normality could greatly distort the meta-analytic results, according + to the simulation in Sun and Cheung (2020) . + This package aims to detect non-normality for two independent groups with only + limited descriptive statistics, including mean, standard deviation, minimum, and + maximum.' + date_publication: '2022-07-16' + bug_reports: https://github.com/irissun/detectnorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=detectnorm + url_git: https://github.com/irissun/detectnorm +detector: + version: 0.1.0 + title: Detect Data Containing Personally Identifiable Information + maintainer: Paul Hendricks + description: |- + Allows users to quickly and easily detect data containing + Personally Identifiable Information (PII) through convenience functions. + date_publication: '2015-08-28' + bug_reports: https://github.com/paulhendricks/detector/issues + url: '' + url_cran: https://CRAN.R-project.org/package=detector + url_git: https://github.com/paulhendricks/detector +detectors: + version: 0.1.0 + title: Prediction Data from GPT Detectors + maintainer: Simon Couch + description: |- + Researchers carried out a series of experiments passing a number + of essays to different GPT detection models. Juxtaposing detector predictions + for papers written by native and non-native English writers, the authors argue + that GPT detectors disproportionately classify real writing from non-native + English writers as AI-generated. + date_publication: '2023-10-26' + bug_reports: '' + url: https://simonpcouch.github.io/detectors/ + url_cran: https://CRAN.R-project.org/package=detectors + url_git: '' +detectR: + version: 0.3.0 + title: Change Point Detection + maintainer: Changryong Baek + description: |- + Time series analysis of network connectivity. Detects and visualizes change points between networks. + Methods included in the package are discussed in depth in Baek, C., Gates, K. M., Leinwand, B., Pipiras, V. (2021) + "Two sample tests for high-dimensional auto-covariances" + and Baek, C., Gampe, M., Leinwand B., Lindquist K., Hopfinger J. and Gates K. (2023) + “Detecting functional connectivity changes in fMRI data” . + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=detectR + url_git: https://github.com/crbaek/detectR +detectRUNS: + version: 0.9.6 + title: |- + Detect Runs of Homozygosity and Runs of Heterozygosity in + Diploid Genomes + maintainer: Filippo Biscarini + description: |- + Detection of runs of homozygosity and of heterozygosity + in diploid genomes using two methods: sliding windows (Purcell et al (2007) + ) and consecutive runs (Marras et al (2015) + ). + date_publication: '2019-10-24' + bug_reports: https://github.com/bioinformatics-ptp/detectRUNS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=detectRUNS + url_git: https://github.com/bioinformatics-ptp/detectRUNS/tree/master/detectRUNS +detectseparation: + version: '0.3' + title: |- + Detect and Check for Separation and Infinite Maximum Likelihood + Estimates + maintainer: Ioannis Kosmidis + description: Provides pre-fit and post-fit methods for detecting separation and + infinite maximum likelihood estimates in generalized linear models with categorical + responses. The pre-fit methods apply on binomial-response generalized liner models + such as logit, probit and cloglog regression, and can be directly supplied as + fitting methods to the glm() function. They solve the linear programming problems + for the detection of separation developed in Konis (2007, ) + using 'ROI' or 'lpSolveAPI' . + The post-fit methods apply to models with categorical responses, including binomial-response + generalized linear models and multinomial-response models, such as baseline category + logits and adjacent category logits models; for example, the models implemented + in the 'brglm2' package. The post-fit + methods successively refit the model with increasing number of iteratively reweighted + least squares iterations, and monitor the ratio of the estimated standard error + for each parameter to what it has been in the first iteration. According to the + results in Lesaffre & Albert (1989, ), divergence + of those ratios indicates data separation. + date_publication: '2022-08-26' + bug_reports: https://github.com/ikosmidis/detectseparation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=detectseparation + url_git: https://github.com/ikosmidis/detectseparation +DetLifeInsurance: + version: 0.1.3 + title: Life Insurance Premium and Reserves Valuation + maintainer: Joaquin Auza + description: 'Methods for valuation of life insurance premiums and reserves (including + variable-benefit and fractional coverage) based on "Actuarial Mathematics" by + Bowers, H.U. Gerber, J.C. Hickman, D.A. Jones and C.J. Nesbitt (1997, ISBN: 978-0938959465), + "Actuarial Mathematics for Life Contingent Risks" by Dickson, David C. M., Hardy, + Mary R. and Waters, Howard R (2009) and "Life + Contingencies" by Jordan, C. W (1952) . It also + contains functions for equivalent interest and discount rate calculation, present + and future values of annuities, and loan amortization schedule.' + date_publication: '2020-09-12' + bug_reports: https://github.com/JoaquinAuza/DetLifeInsurance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DetLifeInsurance + url_git: https://github.com/JoaquinAuza/DetLifeInsurance +DetMCD: + version: 0.0.5 + title: |- + Implementation of the DetMCD Algorithm (Robust and Deterministic + Estimation of Location and Scatter) + maintainer: Vakili Kaveh + description: Implementation of DetMCD, a new algorithm for robust and deterministic + estimation of location and scatter. The benefits of robust and deterministic estimation + are explained in Hubert, Rousseeuw and Verdonck (2012) . + date_publication: '2018-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DetMCD + url_git: '' +detourr: + version: 0.1.0 + title: Portable and Performant Tour Animations + maintainer: Casper Hart + description: Provides 2D and 3D tour animations as HTML widgets. The user can interact + with the widgets using orbit controls, tooltips, brushing, and timeline controls. + Linked brushing is supported using 'crosstalk', and widgets can be embedded in + Shiny apps or HTML documents. + date_publication: '2022-06-20' + bug_reports: https://github.com/casperhart/detourr/issues + url: https://casperhart.github.io/detourr/ + url_cran: https://CRAN.R-project.org/package=detourr + url_git: '' +detpack: + version: 1.1.3 + title: |- + Density Estimation and Random Number Generation with + Distribution Element Trees + maintainer: Daniel Meyer + description: 'Density estimation for possibly large data sets and conditional/unconditional + random number generation or bootstrapping with distribution element trees. The + function ''det.construct'' translates a dataset into a distribution element tree. + To evaluate the probability density based on a previously computed tree at arbitrary + query points, the function ''det.query'' is available. The functions ''det1'' + and ''det2'' provide density estimation and plotting for one- and two-dimensional + datasets. Conditional/unconditional smooth bootstrapping from an available distribution + element tree can be performed by ''det.rnd''. For more details on distribution + element trees, see: Meyer, D.W. (2016) or Meyer, D.W., Statistics + and Computing (2017) and Meyer, D.W. (2017) + or Meyer, D.W., Journal of Computational and Graphical Statistics (2018) .' + date_publication: '2019-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=detpack + url_git: '' +DetR: + version: 0.0.5 + title: |- + Suite of Deterministic and Robust Algorithms for Linear + Regression + maintainer: Kaveh Vakili + description: |- + DetLTS, DetMM (and DetS) Algorithms for Deterministic, Robust + Linear Regression. + date_publication: '2018-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DetR + url_git: '' +detrendeR: + version: 1.0.5 + title: |- + A Graphical User Interface (GUI) to Visualize and Analyze + Dendrochronological Data + maintainer: Filipe Campelo + description: |- + A Graphical User Interface (GUI) to import, save, detrend and + perform standard tree-ring analyses. The interactive detrending allows the user to check how + well the detrending curve fits each time-series and change it when needed. + date_publication: '2022-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=detrendeR + url_git: '' +detrendr: + version: 0.6.15 + title: Detrend Images + maintainer: Rory Nolan + description: |- + Detrend fluorescence microscopy image series for fluorescence + fluctuation and correlation spectroscopy ('FCS' and 'FFS') analysis. + This package contains functionality published in a 2016 paper + but it has been extended since + then with the Robin Hood algorithm and thus contains unpublished work. + date_publication: '2023-03-04' + bug_reports: https://github.com/rorynolan/detrendr/issues + url: https://rorynolan.github.io/detrendr/ + url_cran: https://CRAN.R-project.org/package=detrendr + url_git: https://github.com/rorynolan/detrendr#readme +deTS: + version: '1.0' + title: Tissue-Specific Enrichment Analysis + maintainer: Guangsheng Pei + description: 'Tissue-specific enrichment analysis to assess lists of candidate genes + or RNA-Seq expression profiles. Pei G., Dai Y., Zhao Z. Jia P. (2019) deTS: Tissue-Specific + Enrichment Analysis to decode tissue specificity. Bioinformatics, In submission.' + date_publication: '2019-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=deTS + url_git: '' +detzrcr: + version: 0.3.1 + title: Compare Detrital Zircon Suites + maintainer: Magnus Kristoffersen + description: |- + Compare detrital zircon suites by uploading univariate, + U-Pb age, or bivariate, U-Pb age and Lu-Hf data, in a 'shiny'-based + user-interface. Outputs publication quality figures using 'ggplot2', and + tables of statistics currently in use in the detrital zircon geochronology + community. + date_publication: '2020-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=detzrcr + url_git: https://github.com/magnuskristoffersen/detzrcr +devEMF: + version: '4.5' + title: EMF Graphics Output Device + maintainer: Philip Johnson + description: Output graphics to EMF+/EMF. + date_publication: '2024-07-26' + bug_reports: https://github.com/plfjohnson/devEMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=devEMF + url_git: https://github.com/plfjohnson/devEMF +devFunc: + version: '0.1' + title: Clear and Condense Argument Check for User-Defined Functions + maintainer: Robin Van Oirbeek + description: A concise check of the format of one or multiple input arguments (data + type, length or value) is provided. Since multiple input arguments can be tested + simultaneously, a lengthly list of checks at the beginning of your function can + be avoided, hereby enhancing the readability and maintainability of your code. + date_publication: '2018-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=devFunc + url_git: '' +devoid: + version: 0.1.2 + title: A Graphic Device that Does Nothing + maintainer: Thomas Lin Pedersen + description: |- + Provides a non-drawing graphic device for benchmarking purpose. + In order to properly benchmark graphic drawing code it is necessary + to factor out the device implementation itself so that results are not + related to the specific graphics device used during benchmarking. The + 'devoid' package implements a graphic device that accepts all the required + calls from R's graphic engine but performs no action. Apart from + benchmarking it is unlikely that this device has any practical use. + date_publication: '2023-04-25' + bug_reports: https://github.com/r-lib/devoid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=devoid + url_git: https://github.com/r-lib/devoid +Devore7: + version: 0.7.6 + title: Data sets from Devore's "Prob and Stat for Eng (7th ed)" + maintainer: John Verzani + description: Data sets and sample analyses from Jay L. Devore (2008),"Probability + and Statistics for Engineering and the Sciences(7th ed)", Thomson. + date_publication: '2014-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Devore7 + url_git: '' +devRate: + version: 0.2.4 + title: |- + Quantify the Relationship Between Development Rate and + Temperature in Ectotherms + maintainer: Francois Rebaudo + description: |- + A set of functions to quantify the relationship between development + rate and temperature and to build phenological models. The package comprises + a set of models and estimated parameters borrowed from a literature review + in ectotherms. The methods and literature review are described in Rebaudo + et al. (2018) , Rebaudo and Rabhi (2018) + , and Regnier et al. (2021) . + An example can be found in Rebaudo et al. (2017) + . + date_publication: '2023-08-24' + bug_reports: https://github.com/frareb/devRate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=devRate + url_git: https://github.com/frareb/devRate/ +devtools: + version: 2.4.5 + title: Tools to Make Developing R Packages Easier + maintainer: Jennifer Bryan + description: Collection of package development tools. + date_publication: '2022-10-11' + bug_reports: https://github.com/r-lib/devtools/issues + url: https://devtools.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=devtools + url_git: https://github.com/r-lib/devtools +DevTreatRules: + version: 1.1.0 + title: Develop Treatment Rules with Observational Data + maintainer: Jeremy Roth + description: 'Develop and evaluate treatment rules based on: (1) the standard indirect + approach of split-regression, which fits regressions separately in both treatment + groups and assigns an individual to the treatment option under which predicted + outcome is more desirable; (2) the direct approach of outcome-weighted-learning + proposed by Yingqi Zhao, Donglin Zeng, A. John Rush, and Michael Kosorok (2012) + ; (3) the direct approach, which we refer to + as direct-interactions, proposed by Shuai Chen, Lu Tian, Tianxi Cai, and Menggang + Yu (2017) . Please see the vignette for a walk-through + of how to start with an observational dataset whose design is understood scientifically + and end up with a treatment rule that is trustworthy statistically, along with + an estimation of rule benefit in an independent sample.' + date_publication: '2020-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DevTreatRules + url_git: '' +DEXiR: + version: 1.0.2 + title: '''DEXi'' Library' + maintainer: Marko Bohanec + description: |- + A software package for using 'DEXi' models. 'DEXi' models are + hierarchical qualitative multi-criteria decision models developed according to the method + DEX (Decision EXpert, ), + using the program 'DEXi' () or + 'DEXiWin' (). + A typical workflow with 'DEXiR' consists of: + (1) reading a '.dxi' file, previously made using the 'DEXi' software (function read_dexi()), + (2) making a data frame containing input values of one or more decision alternatives, + (3) evaluating those alternatives (function evaluate()), + (4) analyzing alternatives (selective_explanation(), plus_minus(), compare_alternatives()), + (5) drawing charts. + 'DEXiR' is restricted to using models produced externally by the 'DEXi' software and does not + provide functionality for creating and/or editing 'DEXi' models directly in 'R'. + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DEXiR + url_git: '' +dexisensitivity: + version: 1.0.1 + title: '''DEXi'' Decision Tree Analysis and Visualization' + maintainer: Nicolas Cavan + description: |- + Provides a versatile toolkit for analyzing and visualizing 'DEXi' (Decision EXpert for education) + decision trees, facilitating multi-criteria decision analysis directly within R. Users can + read .dxi files, manipulate decision trees, and evaluate various scenarios. It supports sensitivity + analysis through Monte Carlo simulations, one-at-a-time approaches, and variance-based + methods, helping to discern the impact of input variations. Additionally, it includes functionalities + for generating sampling plans and an array of visualization options for decision trees and + analysis results. A distinctive feature is the synoptic table plot, aiding in the efficient + comparison of scenarios. Whether for in-depth decision modeling or sensitivity analysis, this + package stands as a comprehensive solution. Definition of sensitivity analyses available in + Carpani, Bergez and Monod (2012) and detailed description of the package soon available in Alaphilippe, Allart, Carpani, Cavan, Monod + and Bergez (submitted to Software Impacts). + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dexisensitivity + url_git: '' +dexter: + version: 1.5.0 + title: Data Management and Analysis of Tests + maintainer: Jesse Koops + description: A system for the management, assessment, and psychometric analysis + of data from educational and psychological tests. + date_publication: '2024-07-05' + bug_reports: https://github.com/dexter-psychometrics/dexter/issues + url: https://dexter-psychometrics.github.io/dexter/ + url_cran: https://CRAN.R-project.org/package=dexter + url_git: '' +dextergui: + version: 0.2.6 + title: A Graphical User Interface for Dexter + maintainer: Jesse Koops + description: |- + Classical Test and Item analysis, + Item Response analysis and data management for educational and psychological tests. + date_publication: '2022-06-21' + bug_reports: https://github.com/dexter-psychometrics/dexter/issues + url: https://dexter-psychometrics.github.io/dexter/ + url_cran: https://CRAN.R-project.org/package=dextergui + url_git: '' +dexterMST: + version: 0.9.6 + title: CML and Bayesian Calibration of Multistage Tests + maintainer: Timo Bechger + description: |- + Conditional Maximum Likelihood Calibration and data management of multistage tests. + Supports polytomous items and incomplete designs with linear as well as multistage tests. + Extended Nominal Response and Interaction models, DIF and profile analysis. + See Robert J. Zwitser and Gunter Maris (2015). + date_publication: '2023-12-05' + bug_reports: https://github.com/dexter-psychometrics/dexter/issues + url: https://dexter-psychometrics.github.io/dexter/ + url_cran: https://CRAN.R-project.org/package=dexterMST + url_git: '' +df2yaml: + version: 0.3.1 + title: Convert Dataframe to 'YAML' + maintainer: Yabing Song + description: |- + The 'df2yaml' aims to simplify the process of converting 'dataframe' to 'YAML' . + The 'dataframe' with multiple key columns and one value column will be converted to the multi-level hierarchy. + date_publication: '2023-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=df2yaml + url_git: '' +DFA: + version: 1.0.0 + title: Detrended Fluctuation Analysis + maintainer: Victor Barreto Mesquita + description: Containing the Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation + Analysis (DCCA), Detrended Cross-Correlation Coefficient (rhoDCCA), Delta Amplitude + Detrended Cross-Correlation Coefficient (DeltarhoDCCA), log amplitude Detrended + Fluctuation Analysis (DeltalogDFA), and the Activity Balance Index, it also includes + two DFA automatic methods for identifying crossover points and a Deltalog automatic + method for identifying reference channels. + date_publication: '2024-02-22' + bug_reports: https://github.com/victormesquita40/DFA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DFA + url_git: '' +DFA.CANCOR: + version: 0.3.6 + title: Linear Discriminant Function and Canonical Correlation Analysis + maintainer: Brian P. O'Connor + description: |- + Produces SPSS- and SAS-like output for linear discriminant + function analysis and canonical correlation analysis. The methods are described in + Manly & Alberto (2017, ISBN:9781498728966), + Rencher (2002, ISBN:0-471-41889-7), and + Tabachnik & Fidell (2019, ISBN:9780134790541). + date_publication: '2024-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DFA.CANCOR + url_git: '' +dfadjust: + version: 1.1.0 + title: Degrees of Freedom Adjustment for Robust Standard Errors + maintainer: Michal Kolesár + description: |- + Computes small-sample degrees of freedom adjustment for + heteroskedasticity robust standard errors, and for clustered standard errors + in linear regression. See Imbens and Kolesár (2016) + for a discussion of these adjustments. + date_publication: '2024-12-18' + bug_reports: https://github.com/kolesarm/Robust-Small-Sample-Standard-Errors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfadjust + url_git: https://github.com/kolesarm/Robust-Small-Sample-Standard-Errors +DFBA: + version: 0.1.0 + title: Distribution-Free Bayesian Analysis + maintainer: Daniel H. Barch + description: |- + A set of functions to perform distribution-free Bayesian analyses. + Included are Bayesian analogues to the frequentist Mann-Whitney U + test, the Wilcoxon Signed-Ranks test, Kendall's Tau Rank + Correlation Coefficient, Goodman and Kruskal's Gamma, McNemar's + Test, the binomial test, the sign test, the median test, as well as + distribution-free methods for testing contrasts among condition and + for computing Bayes factors for hypotheses. The package also + includes procedures to estimate the power of distribution-free + Bayesian tests based on data simulations using various probability + models for the data. The set of functions provide data analysts + with a set of Bayesian procedures that avoids requiring parametric + assumptions about measurement error and is robust to problem of + extreme outlier scores. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DFBA + url_git: '' +dfcomb: + version: 3.1-4 + title: Phase I/II Adaptive Dose-Finding Design for Combination Studies + maintainer: Jacques-Henri Jourdan + description: |- + Phase I/II adaptive dose-finding design for combination + studies where toxicity rates are supposed to increase with both agents. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfcomb + url_git: '' +dfCompare: + version: 1.0.0 + title: Compare Two Dataframes and Return Adds, Changes, and Deletes + maintainer: Shawn Waldroff + description: |- + Compares two dataframes with a common key + and returns the delta records. The package will return + three dataframes that contain the added, changed, + and deleted records. + date_publication: '2017-05-29' + bug_reports: https://github.com/swaldroff/DFCompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfCompare + url_git: https://github.com/swaldroff/DFCompare +dfcrm: + version: 0.2-2.1 + title: Dose-Finding by the Continual Reassessment Method + maintainer: Jimmy Duong + description: |- + Provides functions to run the CRM and + TITE-CRM in phase I trials and calibration tools for trial + planning purposes. + date_publication: '2019-01-26' + bug_reports: '' + url: http://www.columbia.edu/~yc632 + url_cran: https://CRAN.R-project.org/package=dfcrm + url_git: '' +DFD: + version: 0.3.0 + title: |- + Extract Drugs from Differential Expression Data from LINCS + Database + maintainer: Mohamed Soudy + description: Get Drug information from given differential expression profile. The + package search for the bioactive compounds from reference databases such as LINCS + containing the genome-wide gene expression signature (GES) from tens of thousands + of drug and genetic perturbations (Subramanian et al. (2017) ). + date_publication: '2025-02-11' + bug_reports: https://github.com/MohmedSoudy/DFD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DFD + url_git: https://github.com/MohmedSoudy/DFD +dfdr: + version: 0.2.0 + title: Automatic Differentiation of Simple Functions + maintainer: Konrad Krämer + description: |- + Implementation of automatically computing derivatives + of functions (see Mailund Thomas (2017) ). Moreover, calculating gradients, Hessian and Jacobian matrices is possible. + date_publication: '2023-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfdr + url_git: '' +dfeR: + version: 1.0.1 + title: Common Department for Education Analysis Tasks + maintainer: Cam Race + description: |- + Preferred methods for common analytical tasks that are + undertaken across the Department, including number formatting, project + templates and curated reference data. + date_publication: '2025-01-15' + bug_reports: https://github.com/dfe-analytical-services/dfeR/issues + url: https://dfe-analytical-services.github.io/dfeR/ + url_cran: https://CRAN.R-project.org/package=dfeR + url_git: https://github.com/dfe-analytical-services/dfeR +dfexpand: + version: 0.0.2 + title: |- + Automatically Expand Delimited Column Values into Multiple + Binary Columns with 'dfexpand' + maintainer: Jeffery Painter + description: Implements an algorithm to effortlessly split a column in an R data + frame filled with multiple values separated by delimiters. This automates the + process of creating separate columns for each unique value, transforming them + into binary outcomes. + date_publication: '2023-10-18' + bug_reports: https://github.com/jlpainter/dfexpand/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=dfexpand + url_git: https://github.com/jlpainter/dfexpand +dfidx: + version: 0.1-0 + title: Indexed Data Frames + maintainer: Yves Croissant + description: Provides extended data frames, with a special data frame column which + contains two indexes, with potentially a nesting structure. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfidx + url_git: '' +DFIT: + version: '1.1' + title: Differential Functioning of Items and Tests + maintainer: Victor H. Cervantes + description: |- + A set of functions to perform Raju, van der Linden and Fleer's + (1995, ) Differential Functioning of Items + and Tests (DFIT) analyses. It includes functions to use the Monte Carlo Item + Parameter Replication approach (Oshima, Raju, & Nanda, 2006, ) + for obtaining the associated statistical significance + tests cut-off points. They may also be used for a priori and post-hoc power + calculations (Cervantes, 2017, ). + date_publication: '2021-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DFIT + url_git: '' +dfmeta: + version: 1.0.0 + title: Meta-Analysis of Phase I Dose-Finding Early Clinical Trials + maintainer: Artemis Toumazi + description: 'Meta-analysis approaches for Phase I dose finding early phases clinical + trials in order to better suit requirements in terms of maximum tolerated dose + (MTD) and maximal dose regimen (MDR). This package has currently three different + approaches: (a) an approach proposed by Zohar et al, 2011, + (denoted as ZKO), (b) the Variance Weighted pooling analysis (called VarWT) and + (c) the Random Effects Model Based (REMB) algorithm, where user can input his/her + own model based approach or use the existing random effect logistic regression + model (named as glimem) through the ''dfmeta'' package.' + date_publication: '2018-03-27' + bug_reports: http://github.com/artemis-toumazi/dfmeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfmeta + url_git: http://github.com/artemis-toumazi/dfmeta +dfmirroR: + version: 2.1.0 + title: |- + Simulate a Data Frame Mirroring an Input and Produce Shareable + Simulation Code + maintainer: Jacob Patterson-Stein + description: The 'dfmirroR' package allows users to input a data frame, simulate + some number of observations based on specified columns of that data frame, and + then outputs a string that contains the code to re-create the simulation. The + goal is to both provide workable test data sets and provide users with the information + they need to set up reproducible examples with team members. This package was + created out of a need to share examples in cases where data are private and where + a full data frame is not needed for testing or coordinating. + date_publication: '2024-01-26' + bug_reports: https://github.com/jacobpstein/dfmirroR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfmirroR + url_git: https://github.com/jacobpstein/dfmirroR +dfms: + version: 0.2.2 + title: Dynamic Factor Models + maintainer: Sebastian Krantz + description: |- + Efficient estimation of Dynamic Factor Models using the Expectation Maximization (EM) algorithm + or Two-Step (2S) estimation, supporting datasets with missing data. The estimation options follow advances in the + econometric literature: either running the Kalman Filter and Smoother once with initial values from PCA - + 2S estimation as in Doz, Giannone and Reichlin (2011) - or via iterated + Kalman Filtering and Smoothing until EM convergence - following Doz, Giannone and Reichlin (2012) + - or using the adapted EM algorithm of Banbura and Modugno (2014) , + allowing arbitrary patterns of missing data. The implementation makes heavy use of the 'Armadillo' 'C++' library and + the 'collapse' package, providing for particularly speedy estimation. A comprehensive set of methods supports + interpretation and visualization of the model as well as forecasting. Information criteria to choose the number + of factors are also provided - following Bai and Ng (2002) . + date_publication: '2024-06-09' + bug_reports: https://github.com/SebKrantz/dfms/issues + url: https://sebkrantz.github.io/dfms/ + url_cran: https://CRAN.R-project.org/package=dfms + url_git: '' +dfmta: + version: 1.7-6 + title: Phase I/II Adaptive Dose-Finding Design for MTA + maintainer: Jacques-Henri Jourdan + description: |- + Phase I/II adaptive dose-finding design for single-agent + Molecularly Targeted Agent (MTA), according to the paper "Phase + I/II Dose-Finding Design for Molecularly Targeted Agent: Plateau + Determination using Adaptive Randomization", Riviere Marie-Karelle et + al. (2016) . + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfmta + url_git: '' +dfoliatR: + version: 0.3.0 + title: |- + Detection and Analysis of Insect Defoliation Signals in Tree + Rings + maintainer: Chris Guiterman + description: |- + Tools to identify, quantify, analyze, and visualize growth + suppression events in tree rings that are often produced by insect + defoliation. Described in Guiterman et al. (2020) . + date_publication: '2023-08-09' + bug_reports: https://github.com/chguiterman/dfoliatR/issues + url: https://chguiterman.github.io/dfoliatR/ + url_cran: https://CRAN.R-project.org/package=dfoliatR + url_git: '' +dfoptim: + version: 2023.1.0 + title: Derivative-Free Optimization + maintainer: Ravi Varadhan + description: Derivative-Free optimization algorithms. These algorithms do not require + gradient information. More importantly, they can be used to solve non-smooth optimization + problems. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfoptim + url_git: '' +Dforest: + version: 0.4.2 + title: Decision Forest + maintainer: Leihong Wu + description: |- + Provides R-implementation of Decision forest algorithm, which combines the predictions of + multiple independent decision tree models for a consensus decision. In particular, Decision Forest is a novel + pattern-recognition method which can be used to analyze: (1) DNA microarray data; + (2) Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) data; and + (3) Structure-Activity Relation (SAR) data. + In this package, three fundamental functions are provided, as (1)DF_train, (2)DF_pred, and (3)DF_CV. + run Dforest() to see more instructions. + Weida Tong (2003) . + date_publication: '2017-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dforest + url_git: '' +dformula: + version: '1.0' + title: Data Manipulation using Formula + maintainer: Alessio Serafini + description: A tool for manipulating data using the generic formula. A single formula + allows to easily add, replace and remove variables before running the analysis. + date_publication: '2023-12-01' + bug_reports: https://github.com/serafinialessio/dformula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dformula + url_git: https://github.com/serafinialessio/dformula +dfped: + version: '1.1' + title: |- + Extrapolation and Bridging of Adult Information in Early Phase + Dose-Finding Paediatrics Studies + maintainer: Artemis Toumazi + description: 'A unified method for designing and analysing dose-finding trials in + paediatrics, while bridging information from adults, is proposed in the ''dfped'' + package. The dose range can be calculated under three extrapolation methods: linear, + allometry and maturation adjustment, using pharmacokinetic (PK) data. To do this, + it is assumed that target exposures are the same in both populations. The working + model and prior distribution parameters of the dose-toxicity and dose-efficacy + relationships can be obtained using early phase adult toxicity and efficacy data + at several dose levels through ''dfped'' package. Priors are used into the dose + finding process through a Bayesian model selection or adaptive priors, to facilitate + adjusting the amount of prior information to differences between adults and children. + This calibrates the model to adjust for misspecification if the adult and paediatric + data are very different. User can use his/her own Bayesian model written in Stan + code through the ''dfped'' package. A template of this model is proposed in the + examples of the corresponding R functions in the package. Finally, in this package + you can find a simulation function for one trial or for more than one trial. These + methods are proposed by Petit et al, (2016) .' + date_publication: '2018-03-27' + bug_reports: http://github.com/artemis-toumazi/dfped/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfped + url_git: http://github.com/artemis-toumazi/dfped +dfphase1: + version: 1.2.0 + title: |- + Phase I Control Charts (with Emphasis on Distribution-Free + Methods) + maintainer: Giovanna Capizzi + description: |- + Statistical methods for retrospectively detecting changes + in location and/or dispersion of univariate and multivariate + variables. Data values are assumed to be independent, can be + individual (one observation at each instant of time) or subgrouped + (more than one observation at each instant of time). + Control limits are computed, often using a permutation approach, + so that a prescribed false alarm probability is guaranteed + without making any parametric assumptions on the stable + (in-control) distribution. See G. Capizzi and G. Masarotto (2018) + for an introduction to the package. + date_publication: '2023-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfphase1 + url_git: '' +dfr: + version: 0.1.4 + title: Dual Feature Reduction for SGL + maintainer: Fabio Feser + description: Implementation of the Dual Feature Reduction (DFR) approach for the + Sparse Group Lasso (SGL) and the Adaptive Sparse Group Lasso (aSGL) (Feser and + Evangelou (2024) ). The DFR approach is a feature + reduction approach that applies strong screening to reduce the feature space before + optimisation, leading to speed-up improvements for fitting SGL (Simon et al. (2013) + ) and aSGL (Mendez-Civieta et al. (2020) + and Poignard (2020) ) models. DFR is implemented + using the Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018) + ) algorithm, with linear and logistic SGL models + supported, both of which can be fit using k-fold cross-validation. Dense and sparse + input matrices are supported. + date_publication: '2025-02-06' + bug_reports: https://github.com/ff1201/dfr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfr + url_git: https://github.com/ff1201/dfr +dfrr: + version: 0.1.5 + title: Dichotomized Functional Response Regression + maintainer: Fatemeh Asgari + description: Implementing Function-on-Scalar Regression model in which the response + function is dichotomized and observed sparsely. This package provides smooth estimations + of functional regression coefficients and principal components for the dichotomized + functional response regression (dfrr) model. + date_publication: '2023-05-31' + bug_reports: https://github.com/asgari-fatemeh/dfrr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfrr + url_git: https://github.com/asgari-fatemeh/dfrr +dfsaneacc: + version: 1.0.3 + title: |- + Accelerated Derivative-Free Method for Large-Scale Nonlinear + Systems of Equations + maintainer: John L. Gardenghi + description: |- + Secant acceleration applied to derivative-free Spectral + Residual Methods for solving large-scale nonlinear systems of + equations. The main reference follows: E. G. Birgin and + J. M. Martinez (2022) . + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dfsaneacc + url_git: '' +dfvad: + version: 0.3.6 + title: Diewert and Fox's Method of Value Added Growth Decomposition + maintainer: Shipei Zeng + description: |- + Decomposing value added growth into explanatory factors. + A cost constrained value added function is defined to specify the + production frontier. Industry estimates can also be aggregated using + a weighted average approach. + Details about the methodology and data can be found in Diewert and Fox (2018) + + and Zeng, Parsons, Diewert and Fox (2018) + . + date_publication: '2021-10-15' + bug_reports: https://github.com/shipei-zeng/dfvad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dfvad + url_git: https://github.com/shipei-zeng/dfvad +dga: + version: 2.0.1 + title: Capture-Recapture Estimation using Bayesian Model Averaging + maintainer: Olivier Binette + description: Performs Bayesian model averaging for capture-recapture. This includes + code to stratify records, check the strata for suitable overlap to be used for + capture-recapture, and some functions to plot the estimated population size. + date_publication: '2021-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dga + url_git: '' +dGAselID: + version: '1.2' + title: |- + Genetic Algorithm with Incomplete Dominance for Feature + Selection + maintainer: Nicolae Teodor Melita + description: |- + Feature selection from high dimensional data using a diploid + genetic algorithm with Incomplete Dominance for genotype to phenotype mapping + and Random Assortment of chromosomes approach to recombination. + date_publication: '2017-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dGAselID + url_git: '' +DGEAR: + version: 0.1.4 + title: Differential Gene Expression Analysis with R + maintainer: Koushik Bardhan + description: Analyses gene expression data derived from experiments to detect differentially + expressed genes by employing the concept of majority voting with five different + statistical models. It includes functions for differential expression analysis, + significance testing, etc. It simplifies the process of uncovering meaningful + patterns and trends within gene expression data, aiding researchers in downstream + analysis. Boyer, R.S., Moore, J.S. (1991) . + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DGEAR + url_git: '' +DGEobj: + version: 1.1.2 + title: Differential Gene Expression (DGE) Analysis Results Data Object + maintainer: Connie Brett + description: |2- + + Provides a flexible container to manage and annotate Differential Gene + Expression (DGE) analysis results (Smythe et. al (2015) ). + The DGEobj has data slots for row (gene), col (samples), assays (matrix n-rows + by m-samples dimensions) and metadata (not keyed to row, col, or assays). + A set of accessory functions to deposit, query and retrieve subsets of a data + workflow has been provided. Attributes are used to capture metadata such as + species and gene model, including reproducibility information such that a 3rd + party can access a DGEobj history to see how each data object was created or + modified. Since the DGEobj is customizable and extensible it is not limited + to RNA-seq analysis types of workflows -- it can accommodate nearly any data + analysis workflow that starts from a matrix of assays (rows) by samples (columns). + date_publication: '2022-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DGEobj + url_git: '' +DGEobj.utils: + version: 1.0.6 + title: Differential Gene Expression (DGE) Analysis Utility Toolkit + maintainer: Connie Brett + description: |2- + + Provides a function toolkit to facilitate reproducible RNA-Seq Differential Gene Expression (DGE) + analysis (Law (2015) ). The tools include both analysis + work-flow and utility functions: mapping/unit conversion, count normalization, accounting for + unknown covariates, and more. This is a complement/cohort to the 'DGEobj' package that + provides a flexible container to manage and annotate Differential Gene Expression analysis results. + date_publication: '2022-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DGEobj.utils + url_git: '' +dggridR: + version: 3.1.0 + title: Discrete Global Grids + maintainer: Sebastian Krantz + description: Spatial analyses involving binning require that every bin have the + same area, but this is impossible using a rectangular grid laid over the Earth + or over any projection of the Earth. Discrete global grids use hexagons, triangles, + and diamonds to overcome this issue, overlaying the Earth with equally-sized bins. + This package provides utilities for working with discrete global grids, along + with utilities to aid in plotting such data. + date_publication: '2024-07-26' + bug_reports: https://github.com/r-barnes/dggridR/ + url: '' + url_cran: https://CRAN.R-project.org/package=dggridR + url_git: https://github.com/r-barnes/dggridR/ +dglars: + version: 2.1.7 + title: Differential Geometric Least Angle Regression + maintainer: Luigi Augugliaro + description: Differential geometric least angle regression method for fitting sparse + generalized linear models. In this version of the package, the user can fit models + specifying Gaussian, Poisson, Binomial, Gamma and Inverse Gaussian family. Furthermore, + several link functions can be used to model the relationship between the conditional + expected value of the response variable and the linear predictor. The solution + curve can be computed using an efficient predictor-corrector or a cyclic coordinate + descent algorithm, as described in the paper linked to via the URL below. + date_publication: '2023-10-09' + bug_reports: '' + url: https://www.jstatsoft.org/v59/i08/. + url_cran: https://CRAN.R-project.org/package=dglars + url_git: '' +dglm: + version: 1.8.6 + title: Double Generalized Linear Models + maintainer: Gordon Smyth + description: |- + Model fitting and evaluation tools for double generalized linear + models (DGLMs). This class of models uses one generalized linear model (GLM) + to fit the specified response and a second GLM to fit the deviance of the first + model. + date_publication: '2023-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dglm + url_git: '' +DGLMExtPois: + version: 0.2.3 + title: Double Generalized Linear Models Extending Poisson Regression + maintainer: Francisco Martinez + description: |- + Model estimation, dispersion testing and diagnosis of hyper-Poisson + Saez-Castillo, A.J. and Conde-Sanchez, A. (2013) + and Conway-Maxwell-Poisson Huang, A. (2017) + regression models. + date_publication: '2023-09-04' + bug_reports: https://github.com/franciscomartinezdelrio/DGLMExtPois/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DGLMExtPois + url_git: https://github.com/franciscomartinezdelrio/DGLMExtPois +DGM: + version: 1.7.4 + title: Dynamic Graphical Models + maintainer: Simon Schwab + description: |2- + + Dynamic graphical models for multivariate time series data to estimate directed + dynamic networks in functional magnetic resonance imaging (fMRI), see Schwab et + al. (2017) . + date_publication: '2021-12-05' + bug_reports: https://github.com/schw4b/DGM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DGM + url_git: https://github.com/schw4b/DGM +dgof: + version: 1.5.1 + title: Discrete Goodness-of-Fit Tests + maintainer: Taylor B. Arnold + description: |- + A revision to the stats::ks.test() function and the associated + ks.test.Rd help page. With one minor exception, it does not change the + existing behavior of ks.test(), and it adds features necessary + for doing one-sample tests with hypothesized discrete + distributions. The package also contains cvm.test(), for doing + one-sample Cramer-von Mises goodness-of-fit tests. + date_publication: '2024-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dgof + url_git: '' +DGP4LCF: + version: 1.0.0 + title: Dependent Gaussian Processes for Longitudinal Correlated Factors + maintainer: Jiachen Cai + description: 'Functionalities for analyzing high-dimensional and longitudinal biomarker + data to facilitate precision medicine, using a joint model of Bayesian sparse + factor analysis and dependent Gaussian processes. This paper illustrates the method + in detail: J Cai, RJB Goudie, C Starr, BDM Tom (2023) .' + date_publication: '2024-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DGP4LCF + url_git: '' +dgpsi: + version: 2.5.0 + title: |- + Interface to 'dgpsi' for Deep and Linked Gaussian Process + Emulations + maintainer: Deyu Ming + description: |- + Interface to the 'python' package 'dgpsi' for Gaussian process, deep Gaussian process, + and linked deep Gaussian process emulations of computer models and networks using stochastic imputation (SI). + The implementations follow Ming & Guillas (2021) and + Ming, Williamson, & Guillas (2023) and + Ming & Williamson (2023) . To get started with the package, + see . + date_publication: '2024-12-14' + bug_reports: https://github.com/mingdeyu/dgpsi-R/issues + url: https://mingdeyu.github.io/dgpsi-R/ + url_cran: https://CRAN.R-project.org/package=dgpsi + url_git: https://github.com/mingdeyu/dgpsi-R +dgumbel: + version: 1.0.1 + title: The Gumbel Distribution Functions and Gradients + maintainer: Berent Ånund Strømnes Lunde + description: |- + Gumbel distribution functions (De Haan L. (2007) + ) implemented with the techniques of automatic + differentiation (Griewank A. (2008) ). + With this tool, a user should be able to quickly model extreme + events for which the Gumbel distribution is the domain of attraction. + The package makes available the density function, the distribution + function the quantile function and a random generating function. In + addition, it supports gradient functions. The package combines 'Adept' + (C++ templated automatic differentiation) (Hogan R. (2017) + ) and 'Eigen' (templated matrix-vector + library) for fast computations of both objective functions and exact + gradients. It relies on 'RcppEigen' for easy access to 'Eigen' and + bindings to R. + date_publication: '2020-04-16' + bug_reports: https://github.com/blunde1/dgumbel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dgumbel + url_git: https://github.com/blunde1/dgumbel +DHARMa: + version: 0.4.7 + title: |- + Residual Diagnostics for Hierarchical (Multi-Level / Mixed) + Regression Models + maintainer: Florian Hartig + description: |- + The 'DHARMa' package uses a simulation-based approach to create + readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed + models. Currently supported are linear and generalized linear (mixed) models from 'lme4' + (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive', and 'spaMM'; phylogenetic + linear models from 'phylolm' (classes 'phylolm' and 'phyloglm'); generalized additive + models ('gam' from 'mgcv'); 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and + 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations + from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. + The resulting residuals are standardized to values between 0 and 1 and can be interpreted + as intuitively as residuals from a linear regression. The package also provides a number of + plot and test functions for typical model misspecification problems, such as + over/underdispersion, zero-inflation, and residual spatial, phylogenetic and temporal autocorrelation. + date_publication: '2024-10-18' + bug_reports: https://github.com/florianhartig/DHARMa/issues + url: http://florianhartig.github.io/DHARMa/ + url_cran: https://CRAN.R-project.org/package=DHARMa + url_git: '' +DHBins: + version: '1.1' + title: Hexmaps for NZ District Health Boards + maintainer: Thomas Lumley + description: Draws stylized choropleth maps -- hexagonal maps and triangular multiclass + hex maps -- for New Zealand District Health Boards and Regional Council areas. + These allow faceted, coloured displays of quantitative information for comparison + across District Health Boards or Regional Councils. The preprint Lumley (2019) + is based on the methods in this package. + date_publication: '2019-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DHBins + url_git: '' +dhga: + version: '0.1' + title: Differential Hub Gene Analysis + maintainer: Samarendra Das + description: Identification of hub genes in a gene co-expression network from gene + expression data. The differential network analysis for two contrasting conditions + leads to the identification of various types of hubs like Housekeeping, Unique + to stress (Disease) and Unique to control (Normal) hub genes. + date_publication: '2016-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dhga + url_git: '' +dhglm: + version: '2.0' + title: Double Hierarchical Generalized Linear Models + maintainer: Maengseok Noh + description: Implements double hierarchical generalized linear models in which the + mean, dispersion parameters for variance of random effects, and residual variance + (overdispersion) can be further modeled as random-effect models. + date_publication: '2018-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dhglm + url_git: '' +DHS.rates: + version: 0.9.2 + title: Calculates Demographic Indicators + maintainer: Mahmoud Elkasabi + description: |- + Calculates key indicators such as fertility rates (Total Fertility Rate (TFR), General Fertility Rate (GFR), + and Age Specific Fertility Rate (ASFR)) using Demographic and Health Survey (DHS) women/individual data, + childhood mortality probabilities and rates such as Neonatal Mortality Rate (NNMR), Post-neonatal Mortality Rate (PNNMR), + Infant Mortality Rate (IMR), Child Mortality Rate (CMR), and Under-five Mortality Rate (U5MR), and adult mortality indicators + such as the Age Specific Mortality Rate (ASMR), Age Adjusted Mortality Rate (AAMR), Age Specific Maternal Mortality Rate (ASMMR), + Age Adjusted Maternal Mortality Rate (AAMMR), Age Specific Pregnancy Related Mortality Rate (ASPRMR), + Age Adjusted Pregnancy Related Mortality Rate (AAPRMR), Maternal Mortality Ratio (MMR) and Pregnancy Related Mortality Ratio (PRMR). + In addition to the indicators, the 'DHS.rates' package estimates sampling errors indicators such as Standard Error (SE), + Design Effect (DEFT), Relative Standard Error (RSE) and Confidence Interval (CI). + The package is developed according to the DHS methodology of calculating the fertility indicators and + the childhood mortality rates outlined in the + "Guide to DHS Statistics" (Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018, ) + and the DHS methodology of estimating the sampling errors indicators outlined in + the "DHS Sampling and Household Listing Manual" (ICF International 2012, ). + date_publication: '2024-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DHS.rates + url_git: '' +dhsage: + version: 0.1.0 + title: |- + Reproductive Age Female Data of Various Demographic Health + Surveys + maintainer: Muhammad Imran + description: We provide 70 data sets of females of reproductive age from 19 Asian + countries, ranging in age from 15 to 49. The data sets are extracted from demographic + and health surveys that were conducted over an extended period of time. Moreover, + the functions also provide Whipple’s index as well as age reporting quality such + as very rough, rough, approximate, accurate, and highly accurate. + date_publication: '2023-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dhsage + url_git: '' +dHSIC: + version: '2.1' + title: Independence Testing via Hilbert Schmidt Independence Criterion + maintainer: Niklas Pfister + description: |- + Contains an implementation of the + d-variable Hilbert Schmidt independence criterion + and several hypothesis tests based on it, as described + in Pfister et al. (2017) . + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dHSIC + url_git: '' +DHSr: + version: 0.1.0 + title: |- + Create Large Scale Repeated Regression Summary Statistics + Dataset and Visualization Seamlessly + maintainer: Arnab Samanta + description: Mapping, spatial analysis, and statistical modeling of microdata from + sources such as the Demographic and Health Surveys + and Integrated Public Use Microdata Series . It can also + be extended to other datasets. The package supports spatial correlation index + construction and visualization, along with empirical Bayes approximation of regression + coefficients in a multistage setup. The main functionality is repeated regression + — for example, if we have to run regression for n groups, the group ID should + be vertically composed into the variable for the parameter `location_var`. It + can perform various kinds of regression, such as Generalized Regression Models, + logit, probit, and more. Additionally, it can incorporate interaction effects. + The key benefit of the package is its ability to store the regression results + performed repeatedly on a dataset by the group ID, along with respective p-values + and map those estimates. + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DHSr + url_git: '' +di: + version: 1.1.4 + title: Deficit Index (DI) + maintainer: Ilya Y. Zhbannikov + description: |- + A set of utilities for calculating the Deficit (frailty) Index (DI) in gerontological studies. + The deficit index was first proposed by Arnold Mitnitski and Kenneth Rockwood + and represents a proxy measure of aging and also can be served as + a sensitive predictor of survival. For more information, see + (i)"Accumulation of Deficits as a Proxy Measure of Aging" + by Arnold B. Mitnitski et al. (2001), + The Scientific World Journal 1, ; + (ii) "Frailty, fitness and late-life mortality in relation to chronological and biological age" + by Arnold B Mitnitski et al. (2001), + BMC Geriatrics2002 2(1), . + date_publication: '2018-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=di + url_git: '' +diagis: + version: 0.2.3 + title: |- + Diagnostic Plot and Multivariate Summary Statistics of Weighted + Samples from Importance Sampling + maintainer: Jouni Helske + description: |- + Fast functions for effective sample size, weighted multivariate + mean, variance, and quantile computation, and weight diagnostic plot for + generic importance sampling type or other probability weighted samples. + date_publication: '2023-09-05' + bug_reports: https://github.com/helske/diagis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diagis + url_git: https://github.com/helske/diagis/ +diagL1: + version: 1.0.0 + title: |- + Routines for Fit, Inference and Diagnostics in Linear L1 and LAD + Models + maintainer: Kevin Allan Sales Rodrigues + description: 'Diagnostics for linear L1 regression (also known as LAD - Least Absolute + Deviations), including: estimation, confidence intervals, tests of hypotheses, + measures of leverage, methods of diagnostics for L1 regression, special diagnostics + graphs and measures of leverage. The algorithms are based in Dielman (2005) , + Elian et al. (2000) and Dodge (1997) . + This package builds on the ''quantreg'' package, which is a well-established package + for tuning quantile regression models. There are also tests to verify if the errors + have a Laplace distribution based on the work of Puig and Stephens (2000) .' + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diagL1 + url_git: '' +diagmeta: + version: 0.5-1 + title: |- + Meta-Analysis of Diagnostic Accuracy Studies with Several + Cutpoints + maintainer: Guido Schwarzer + description: Provides methods by Steinhauser et al. (2016) + for meta-analysis of diagnostic accuracy studies with several cutpoints. + date_publication: '2022-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diagmeta + url_git: https://github.com/guido-s/diagmeta +diagonals: + version: 6.4.0 + title: Block Diagonal Extraction or Replacement + maintainer: Bastiaan Quast + description: |- + Several tools for handling block-matrix diagonals and similar + constructs are implemented. Block-diagonal matrices can be extracted or removed + using two small functions implemented here. In addition, non-square matrices + are supported. Block diagonal matrices occur when two dimensions of a data set + are combined along one edge of a matrix. For example, trade-flow data in the + 'decompr' and 'gvc' packages have each country-industry combination occur along + both edges of the matrix. + date_publication: '2022-06-19' + bug_reports: https://github.com/bquast/diagonals/issues + url: https://qua.st/diagonals + url_cran: https://CRAN.R-project.org/package=diagonals + url_git: https://github.com/bquast/diagonals +diagram: + version: 1.6.5 + title: |- + Functions for Visualising Simple Graphs (Networks), Plotting + Flow Diagrams + maintainer: Karline Soetaert + description: |- + Visualises simple graphs (networks) based on a transition matrix, utilities to plot flow diagrams, + visualising webs, electrical networks, etc. + Support for the book "A practical guide to ecological modelling - + using R as a simulation platform" + by Karline Soetaert and Peter M.J. Herman (2009), Springer. + and the book "Solving Differential Equations in R" + by Karline Soetaert, Jeff Cash and Francesca Mazzia (2012), Springer. + Includes demo(flowchart), demo(plotmat), demo(plotweb). + date_publication: '2020-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diagram + url_git: '' +DiagrammeR: + version: 1.0.11 + title: Graph/Network Visualization + maintainer: Richard Iannone + description: |- + Build graph/network structures using functions for stepwise + addition and deletion of nodes and edges. Work with data available in + tables for bulk addition of nodes, edges, and associated metadata. Use + graph selections and traversals to apply changes to specific nodes or + edges. A wide selection of graph algorithms allow for the analysis of + graphs. Visualize the graphs and take advantage of any aesthetic + properties assigned to nodes and edges. + date_publication: '2024-02-02' + bug_reports: https://github.com/rich-iannone/DiagrammeR/issues + url: https://rich-iannone.github.io/DiagrammeR/ + url_cran: https://CRAN.R-project.org/package=DiagrammeR + url_git: https://github.com/rich-iannone/DiagrammeR +DiagrammeRsvg: + version: '0.1' + title: Export DiagrammeR Graphviz Graphs as SVG + maintainer: Richard Iannone + description: Allows for export of DiagrammeR Graphviz objects to SVG. + date_publication: '2016-02-04' + bug_reports: https://github.com/rich-iannone/DiagrammeRsvg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiagrammeRsvg + url_git: https://github.com/rich-iannone/DiagrammeRsvg +DiallelAnalysisR: + version: 0.6.0 + title: Diallel Analysis with R + maintainer: Muhammad Yaseen + description: 'Performs Diallel Analysis with R using Griffing''s and Hayman''s approaches. + Four different Methods (1: Method-I (Parents + F1''s + reciprocals); 2: Method-II + (Parents and one set of F1''s); 3: Method-III (One set of F1''s and reciprocals); + 4: Method-IV (One set of F1''s only)) and two Models (1: Fixed Effects Model; + 2: Random Effects Model) can be applied using Griffing''s approach.' + date_publication: '2024-09-13' + bug_reports: https://github.com/myaseen208/DiallelAnalysisR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiallelAnalysisR + url_git: '' +dialr: + version: 0.4.2 + title: Parse, Format, and Validate International Phone Numbers + maintainer: Danny Smith + description: |- + Parse, format, and validate international phone + numbers using Google's 'libphonenumber' java library, + . + date_publication: '2023-10-16' + bug_reports: https://github.com/socialresearchcentre/dialr/issues + url: https://socialresearchcentre.github.io/dialr/ + url_cran: https://CRAN.R-project.org/package=dialr + url_git: https://github.com/socialresearchcentre/dialr +dialrjars: + version: 8.13.36 + title: Required 'libphonenumber' jars for the 'dialr' Package + maintainer: Danny Smith + description: |- + Collects 'libphonenumber' jars required for the + 'dialr' package. + date_publication: '2024-05-03' + bug_reports: https://github.com/socialresearchcentre/dialrjars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dialrjars + url_git: https://github.com/socialresearchcentre/dialrjars +dials: + version: 1.4.0 + title: Tools for Creating Tuning Parameter Values + maintainer: Hannah Frick + description: |- + Many models contain tuning parameters (i.e. parameters that + cannot be directly estimated from the data). These tools can be used + to define objects for creating, simulating, or validating values for + such parameters. + date_publication: '2025-02-13' + bug_reports: https://github.com/tidymodels/dials/issues + url: https://dials.tidymodels.org + url_cran: https://CRAN.R-project.org/package=dials + url_git: https://github.com/tidymodels/dials +diaplt: + version: 1.4.0 + title: Beads Summary Plot of Ranges + maintainer: Shinichiro Tomizono + description: |- + Visualize one-factor data frame. + Beads plot consists of diamonds of each factor of each data series. + A diamond indicates average and range. + Look over a data frame with many numeric columns and a factor column. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diaplt + url_git: '' +diario: + version: 0.1.0 + title: '''R'' Interface to the ''Diariodeobras'' Application' + maintainer: Andre Leite + description: Provides a set of functions for securely storing 'API' tokens and interacting + with the system. Includes convenient wrappers around + the 'httr2' package to perform authenticated requests, retrieve project details, + tasks, reports, and more. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diario + url_git: +diathor: + version: 0.1.5 + title: Calculate Ecological Information and Diatom Based Indices + maintainer: Joaquin Cochero + description: |- + Calculate multiple biotic indices using diatoms from environmental samples. Diatom species are recognized by their species' name using a heuristic search, and their ecological data is retrieved from multiple sources. + It includes number/shape of chloroplasts diversity indices, size classes, ecological guilds, and multiple biotic indices. + It outputs both a dataframe with all the results and plots of all the obtained data in a defined output folder. + - Sample data was taken from Nicolosi Gelis, Cochero & Gómez (2020, ). + - The package uses the 'Diat.Barcode' database to calculate morphological and ecological information by Rimet & Couchez (2012, ),and the combined classification of guilds and size classes established by B-Béres et al. (2017, ). + - Current diatom-based biotic indices include the DES index by Descy (1979) + - EPID index by Dell'Uomo (1996, ISBN: 3950009002) + - IDAP index by Prygiel & Coste (1993, ) + - ID-CH index by Hürlimann & Niederhauser (2007) + - IDP index by Gómez & Licursi (2001, ) + - ILM index by Leclercq & Maquet (1987) + - IPS index by Coste (1982) + - LOBO index by Lobo, Callegaro, & Bender (2002, ISBN:9788585869908) + - SLA by Sládeček (1986, ) + - TDI index by Kelly, & Whitton (1995, ) + - SPEAR(herbicide) index by Wood, Mitrovic, Lim, Warne, Dunlop, & Kefford (2019, ) + - PBIDW index by Castro-Roa & Pinilla-Agudelo (2014) + - DISP index by Stenger-Kovács et al. (2018, ) + - EDI index by Chamorro et al. (2024, ) + - DDI index by Álvarez-Blanco et al. (2013, ) + - PDISE index by Kahlert et al. (2023, ). + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diathor + url_git: '' +dibble: + version: 0.3.1 + title: Dimensional Data Frames + maintainer: Mizuki Uchida + description: |- + Provides a 'dibble' that implements data cubes (derived from + 'dimensional tibble'), and allows broadcasting by dimensional names. + date_publication: '2025-02-06' + bug_reports: https://github.com/UchidaMizuki/dibble/issues + url: https://uchidamizuki.github.io/dibble/ + url_cran: https://CRAN.R-project.org/package=dibble + url_git: https://github.com/UchidaMizuki/dibble +dice: + version: '1.2' + title: Calculate probabilities of various dice-rolling events + maintainer: Dylan Arena + description: This package provides utilities to calculate the probabilities of various + dice-rolling events, such as the probability of rolling a four-sided die six times + and getting a 4, a 3, and either a 1 or 2 among the six rolls (in any order); + the probability of rolling two six-sided dice three times and getting a 10 on + the first roll, followed by a 4 on the second roll, followed by anything but a + 7 on the third roll; or the probabilities of each possible sum of rolling five + six-sided dice, dropping the lowest two rolls, and summing the remaining dice. + date_publication: '2014-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dice + url_git: '' +DiceDesign: + version: '1.10' + title: Designs of Computer Experiments + maintainer: Celine Helbert + description: Space-Filling Designs and space-filling criteria (distance-based and + uniformity-based), with emphasis to computer experiments; . + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiceDesign + url_git: '' +DiceEval: + version: 1.6.1 + title: Construction and Evaluation of Metamodels + maintainer: C. Helbert + description: 'Estimation, validation and prediction of models of different types + : linear models, additive models, MARS,PolyMARS and Kriging.' + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiceEval + url_git: '' +DiceKriging: + version: 1.6.0 + title: Kriging Methods for Computer Experiments + maintainer: Olivier Roustant + description: 'Estimation, validation and prediction of kriging models. Important + functions : km, print.km, plot.km, predict.km.' + date_publication: '2021-02-23' + bug_reports: '' + url: https://dicekrigingclub.github.io/www/ + url_cran: https://CRAN.R-project.org/package=DiceKriging + url_git: '' +DICEM: + version: 0.1.0 + title: Directness and Intensity of Conflict Expression + maintainer: Michael Yeomans + description: A Natural Language Processing Model trained to detect directness and + intensity during conflict. See . + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DICEM + url_git: '' +DiceOptim: + version: 2.1.1 + title: Kriging-Based Optimization for Computer Experiments + maintainer: Victor Picheny + description: Efficient Global Optimization (EGO) algorithm as described in "Roustant + et al. (2012)" and adaptations for problems with noise + ("Picheny and Ginsbourger, 2012") , parallel infill, + and problems with constraints. + date_publication: '2021-02-02' + bug_reports: '' + url: http://dice.emse.fr/ + url_cran: https://CRAN.R-project.org/package=DiceOptim + url_git: '' +diceplot: + version: 0.1.4 + title: High Dimensional Categorical Data Visualization + maintainer: Matthias Flotho + description: Easy visualization for datasets with more than two categorical variables + and additional continuous variables. 'diceplot' is particularly useful for exploring + complex categorical data in the context of pathway analysis across multiple conditions. + For a detailed documentation please visit . + date_publication: '2024-11-20' + bug_reports: https://github.com/maflot/Diceplot/issues + url: https://dice-and-domino-plot.readthedocs.io/en/latest/ + url_cran: https://CRAN.R-project.org/package=diceplot + url_git: https://github.com/maflot/Diceplot +diceR: + version: 3.0.0 + title: Diverse Cluster Ensemble in R + maintainer: Derek Chiu + description: |- + Performs cluster analysis using an ensemble clustering + framework, Chiu & Talhouk (2018) . + Results from a diverse set of algorithms are pooled together using + methods such as majority voting, K-Modes, LinkCluE, and CSPA. There + are options to compare cluster assignments across algorithms using + internal and external indices, visualizations such as heatmaps, and + significance testing for the existence of clusters. + date_publication: '2025-02-05' + bug_reports: https://github.com/AlineTalhouk/diceR/issues + url: https://alinetalhouk.github.io/diceR/ + url_cran: https://CRAN.R-project.org/package=diceR + url_git: https://github.com/AlineTalhouk/diceR/ +DiceView: + version: 3.1-0 + title: |- + Methods for Visualization of Computer Experiments Design and + Surrogate + maintainer: Yann Richet + description: View 2D/3D sections, contour plots, mesh of excursion sets for computer + experiments designs, surrogates or test functions. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiceView + url_git: https://github.com/IRSN/DiceView +dichromat: + version: 2.0-0.1 + title: Color Schemes for Dichromats + maintainer: Thomas Lumley + description: |- + Collapse red-green or green-blue distinctions to simulate + the effects of different types of color-blindness. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dichromat + url_git: '' +DICOMread: + version: 0.0.0.3 + title: Reading and Saving DICOM Image Files + maintainer: Shu Jiang + description: This function provides an interface between 'Matlab' and 'R' in facilitating + fast processing for reading and saving DICOM images. + date_publication: '2021-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DICOMread + url_git: '' +DIconvex: + version: 1.0.0 + title: Finding Patterns of Monotonicity and Convexity in Data + maintainer: Liudmila Karagyaur + description: Given an initial set of points, this package minimizes the number + of elements to discard from this set such that there exists at least one monotonic + and convex mapping within pre-specified upper and lower bounds. + date_publication: '2018-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIconvex + url_git: '' +Dict: + version: 0.1.0 + title: R6 Based Key-Value Dictionary Implementation + maintainer: Shun Asai + description: A key-value dictionary data structure based on R6 class which is designed + to be similar usages with other languages dictionary (e.g. 'Python') with reference + semantics and extendabilities by R6. + date_publication: '2020-06-02' + bug_reports: https://github.com/five-dots/Dict/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Dict + url_git: https://github.com/five-dots/Dict +dictionar6: + version: 0.1.3 + title: R6 Dictionary Interface + maintainer: Raphael Sonabend + description: Efficient object-oriented R6 dictionary capable of holding objects + of any class, including R6. Typed and untyped dictionaries are provided as well + as the 'usual' dictionary methods that are available in other OOP languages, for + example listing keys, items, values, and methods to get/set these. + date_publication: '2021-09-13' + bug_reports: https://github.com/xoopR/dictionar6/issues + url: https://xoopR.github.io/dictionar6/ + url_cran: https://CRAN.R-project.org/package=dictionar6 + url_git: https://github.com/xoopR/dictionar6/ +dictionaRy: + version: 0.1.1 + title: Retrieve the Dictionary Definitions of English Words + maintainer: Steve Condylios + description: |- + An R interface to the 'Free Dictionary API' + , + . Retrieve + dictionary definitions for English words, as well + as additional information including phonetics, part of speech, origins, + audio pronunciation, example usage, synonyms and antonyms, returned in + 'tidy' format for ease of use. + date_publication: '2022-01-10' + bug_reports: https://github.com/stevecondylios/dictionaRy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dictionaRy + url_git: https://github.com/stevecondylios/dictionaRy +did: + version: 2.1.2 + title: Treatment Effects with Multiple Periods and Groups + maintainer: Brantly Callaway + description: The standard Difference-in-Differences (DID) setup involves two periods + and two groups -- a treated group and untreated group. Many applications of DID + methods involve more than two periods and have individuals that are treated at + different points in time. This package contains tools for computing average treatment + effect parameters in Difference in Differences setups with more than two periods + and with variation in treatment timing using the methods developed in Callaway + and Sant'Anna (2021) . The main parameters + are group-time average treatment effects which are the average treatment effect + for a particular group at a a particular time. These can be aggregated into a + fewer number of treatment effect parameters, and the package deals with the cases + where there is selective treatment timing, dynamic treatment effects, calendar + time effects, or combinations of these. There are also functions for testing + the Difference in Differences assumption, and plotting group-time average treatment + effects. + date_publication: '2022-07-20' + bug_reports: '' + url: https://bcallaway11.github.io/did/ + url_cran: https://CRAN.R-project.org/package=did + url_git: https://github.com/bcallaway11/did/ +did2s: + version: 1.0.2 + title: Two-Stage Difference-in-Differences Following Gardner (2021) + maintainer: Kyle Butts + description: Estimates Two-way Fixed Effects difference-in-differences/event-study + models using the approach proposed by Gardner (2021) . + To avoid the problems caused by OLS estimation of the Two-way Fixed Effects model, + this function first estimates the fixed effects and covariates using untreated + observations and then in a second stage, estimates the treatment effects. + date_publication: '2023-04-07' + bug_reports: '' + url: https://kylebutts.github.io/did2s/ + url_cran: https://CRAN.R-project.org/package=did2s + url_git: '' +DidacticBoost: + version: 0.1.1 + title: A Simple Implementation and Demonstration of Gradient Boosting + maintainer: David Shaub + description: |- + A basic, clear implementation of tree-based gradient boosting + designed to illustrate the core operation of boosting models. Tuning + parameters (such as stochastic subsampling, modified learning rate, or + regularization) are not implemented. The only adjustable parameter is the + number of training rounds. If you are looking for a high performance boosting + implementation with tuning parameters, consider the 'xgboost' package. + date_publication: '2016-04-19' + bug_reports: https://github.com/dashaub/DidacticBoost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DidacticBoost + url_git: https://github.com/dashaub/DidacticBoost +didec: + version: 0.1.0 + title: Directed Dependence Coefficient + maintainer: Yuping Wang + description: |- + Directed Dependence Coefficient (didec) is a measure of directed dependence. Multivariate Feature Ordering by Conditional Independence (MFOCI) is a variable selection algorithm based on didec. Hierarchical Variable Clustering (VarClustPartition) is a variable clustering method based on didec. For more information, see the paper by + Ansari and Fuchs (2024, ), and the paper by + Fuchs and Wang (2024, ). + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=didec + url_git: '' +Diderot: + version: '0.13' + title: Bibliographic Network Analysis + maintainer: Christian Vincenot + description: Enables the user to build a citation network/graph from bibliographic + data and, based on modularity and heterocitation metrics, assess the degree of + awareness/cross-fertilization between two corpora/communities. This toolset is + optimized for Scopus data. + date_publication: '2020-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Diderot + url_git: '' +DiDforBigData: + version: '1.0' + title: |- + A Big Data Implementation of Difference-in-Differences + Estimation with Staggered Treatment + maintainer: Bradley Setzler + description: Provides a big-data-friendly and memory-efficient difference-in-differences + estimator for staggered (and non-staggered) treatment contexts. + date_publication: '2023-04-03' + bug_reports: https://github.com/setzler/DiDforBigData/issues + url: https://setzler.github.io/DiDforBigData/ + url_cran: https://CRAN.R-project.org/package=DiDforBigData + url_git: '' +DIDHAD: + version: 1.0.1 + title: |- + Difference-in-Differences in Heterogeneous Adoption Designs with + Quasi Stayers + maintainer: Diego Ciccia + description: Estimation of Difference-in-Differences (DiD) estimators from de Chaisemartin + and D'Haultfoeuille (2024) in Heterogeneous Adoption + Designs with no stayers but with quasi stayers. + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIDHAD + url_git: '' +didimputation: + version: 0.3.0 + title: Imputation Estimator from Borusyak, Jaravel, and Spiess (2021) + maintainer: Kyle Butts + description: Estimates Two-way Fixed Effects difference-in-differences/event-study + models using the imputation-based approach proposed by Borusyak, Jaravel, and + Spiess (2021). + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=didimputation + url_git: '' +DIDmultiplegt: + version: 2.0.0 + title: Estimators DID with Multiple Groups and Periods + maintainer: Diego Ciccia + description: Estimators of Difference-in-Differences based on de Chaisemartin and + D'Haultfoeuille. + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIDmultiplegt + url_git: '' +DIDmultiplegtDYN: + version: 2.1.2 + title: |- + Estimation in Difference-in-Difference Designs with Multiple + Groups and Periods + maintainer: Diego Ciccia + description: Estimation of heterogeneity-robust difference-in-differences estimators, + with a binary, discrete, or continuous treatment, in designs where past treatments + may affect the current outcome. + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIDmultiplegtDYN + url_git: https://github.com/chaisemartinPackages/did_multiplegt_dyn +didrooRFM: + version: 1.0.0 + title: Compute Recency Frequency Monetary Scores for your Customer Data + maintainer: Satish Hariharan + description: |- + This hosts the findRFM function which generates RFM scores on a 1-5 point scale for + customer transaction data. The function consumes a data frame with Transaction Number, + Customer ID, Date of Purchase (in date format) and Amount of Purchase as the attributes. + The function returns a data frame with RFM data for the sales information. + date_publication: '2017-05-27' + bug_reports: https://goo.gl/forms/BU7rb8HmgTSeWZE02 + url: '' + url_cran: https://CRAN.R-project.org/package=didrooRFM + url_git: '' +diemr: + version: 1.4.3 + title: Diagnostic Index Expectation Maximisation in R + maintainer: Natalia Martinkova + description: |- + Likelihood-based genome polarisation finds which alleles of genomic markers + belong to which side of the barrier. + Co-estimates which individuals belong to either side of the barrier and barrier strength. + Uses expectation maximisation in likelihood framework. The method is described in + Baird et al. (2023) . + date_publication: '2025-01-20' + bug_reports: https://github.com/StuartJEBaird/diem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diemr + url_git: '' +dietr: + version: 1.1.6-1 + title: Diet Estimated Trophic Levels + maintainer: Samuel R. Borstein + description: Estimates fractional trophic level from quantitative and qualitative + diet data and calculates electivity indices in R. Borstein (2020) . + date_publication: '2025-01-23' + bug_reports: https://github.com/sborstein/dietr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dietr + url_git: https://github.com/sborstein/dietr +diezeit: + version: 0.1-0 + title: R Interface to the ZEIT ONLINE Content API + maintainer: Christian Graul + description: A wrapper for the ZEIT ONLINE Content API, available at . + 'diezeit' gives access to articles and corresponding metadata from the ZEIT archive + and from ZEIT ONLINE. A personal API key is required for usage. + date_publication: '2015-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diezeit + url_git: '' +DIFboost: + version: '0.3' + title: |- + Detection of Differential Item Functioning (DIF) in Rasch Models + by Boosting Techniques + maintainer: Gunther Schauberger + description: Performs detection of Differential Item Functioning using the method + DIFboost as proposed by Schauberger and Tutz (2016) . + date_publication: '2020-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIFboost + url_git: '' +difconet: + version: 1.0-4 + title: Differential Coexpressed Networks + maintainer: Victor Trevino + description: |- + Estimation of DIFferential COexpressed NETworks using diverse and user metrics. + This package is basically used for three functions related to the estimation + of differential coexpression. + First, to estimate differential coexpression where + the coexpression is estimated, by default, by Spearman correlation. For this, + a metric to compare two correlation distributions is needed. The package includes + 6 metrics. Some of them needs a threshold. A new metric can also be specified as + a user function with specific parameters (see difconet.run). The significance is + be estimated by permutations. + Second, to generate datasets with controlled differential correlation data. This + is done by either adding noise, or adding specific correlation structure. + Third, to show the results of differential correlation analyses. Please see + for further information. + date_publication: '2017-05-31' + bug_reports: '' + url: http://bioinformatica.mty.itesm.mx/difconet + url_cran: https://CRAN.R-project.org/package=difconet + url_git: '' +diffcor: + version: 0.8.4 + title: Fisher's z-Tests Concerning Differences Between Correlations + maintainer: Christian Blötner + description: Computations of Fisher's z-tests concerning different kinds of correlation + differences. The 'diffpwr' family entails approaches to estimating statistical + power via Monte Carlo simulations. Important to note, the Pearson correlation + coefficient is sensitive to linear association, but also to a host of statistical + issues such as univariate and bivariate outliers, range restrictions, and heteroscedasticity + (e.g., Duncan & Layard, 1973 ; Wilcox, 2013 ). + Thus, every power analysis requires that specific statistical prerequisites are + fulfilled and can be invalid if the prerequisites do not hold. To this end, the + 'bootcor' family provides bootstrapping confidence intervals for the incorporated + correlation difference tests. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diffcor + url_git: '' +DiffCorr: + version: 0.4.4 + title: |- + Analyzing and Visualizing Differential Correlation Networks in + Biological Data + maintainer: Atsushi Fukushima + description: |- + A method for identifying pattern changes between 2 + experimental conditions in correlation networks (e.g., gene + co-expression networks), which builds on a commonly used association + measure, such as Pearson's correlation coefficient. This package + includes functions to calculate correlation matrices for + high-dimensional dataset and to test differential correlation, which + means the changes in the correlation relationship among variables + (e.g., genes and metabolites) between 2 experimental conditions. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiffCorr + url_git: '' +diffdf: + version: 1.1.1 + title: Dataframe Difference Tool + maintainer: Craig Gower-Page + description: |- + Functions for comparing two data.frames against + each other. The core functionality is to provide a detailed breakdown of any differences + between two data.frames as well as providing utility functions to help narrow down the + source of problems and differences. + date_publication: '2024-09-24' + bug_reports: https://github.com/gowerc/diffdf/issues + url: https://gowerc.github.io/diffdf/ + url_cran: https://CRAN.R-project.org/package=diffdf + url_git: https://github.com/gowerc/diffdf/ +diffdfs: + version: 0.9.0 + title: Compute the Difference Between Data Frames + maintainer: Riaz Arbi + description: Shows you which rows have changed between two data frames with the + same column structure. Useful for diffing slowly mutating data. + date_publication: '2022-08-09' + bug_reports: https://github.com/riazarbi/diffdfs + url: '' + url_cran: https://CRAN.R-project.org/package=diffdfs + url_git: '' +diffee: + version: 1.1.0 + title: |- + Fast and Scalable Learning of Sparse Changes in High-Dimensional + Gaussian Graphical Model Structure + maintainer: Beilun Wang + description: 'This is an R implementation of Fast and Scalable Learning of Sparse + Changes in High-Dimensional Gaussian Graphical Model Structure (DIFFEE). The DIFFEE + algorithm can be used to fast estimate the differential network between two related + datasets. For instance, it can identify differential gene network from datasets + of case and control. By performing data-driven network inference from two high-dimensional + data sets, this tool can help users effectively translate two aggregated data + blocks into knowledge of the changes among entities between two Gaussian Graphical + Model. Please run demo(diffeeDemo) to learn the basic functions provided by this + package. For further details, please read the original paper: Beilun Wang, Arshdeep + Sekhon, Yanjun Qi (2018) .' + date_publication: '2018-07-03' + bug_reports: https://github.com/QData/DIFFEE + url: '' + url_cran: https://CRAN.R-project.org/package=diffee + url_git: https://github.com/QData/DIFFEE +diffEnrich: + version: 0.1.2 + title: |- + Given a List of Gene Symbols, Performs Differential Enrichment + Analysis + maintainer: Harry Smith + description: |- + Compare functional enrichment between two experimentally-derived groups of genes or proteins (Peterson, DR., et al.(2018)) . Given a list of gene symbols, 'diffEnrich' will + perform differential enrichment analysis using the Kyoto Encyclopedia of Genes + and Genomes (KEGG) REST API. This package provides a number of functions that are + intended to be used in a pipeline. Briefly, the user provides a KEGG formatted species id for either human, mouse or rat, and the package will + download and clean species specific ENTREZ gene IDs and map them to their respective + KEGG pathways by accessing KEGG's REST API. KEGG's API is used to guarantee the most up-to-date pathway data from KEGG. Next, the user will identify significantly + enriched pathways from two gene sets, and finally, the user will identify + pathways that are differentially enriched between the two gene sets. In addition to + the analysis pipeline, this package also provides a plotting function. + date_publication: '2022-06-27' + bug_reports: https://github.com/SabaLab/diffEnrich/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffEnrich + url_git: https://github.com/SabaLab/diffEnrich +diffeqr: + version: 2.1.0 + title: Solving Differential Equations (ODEs, SDEs, DDEs, DAEs) + maintainer: Christopher Rackauckas + description: |- + An interface to 'DifferentialEquations.jl' from the R programming language. + It has unique high performance methods for solving ordinary differential equations (ODE), stochastic differential equations (SDE), + delay differential equations (DDE), differential-algebraic equations (DAE), and more. Much of the functionality, + including features like adaptive time stepping in SDEs, are unique and allow for multiple orders of magnitude speedup over more common methods. + Supports GPUs, with support for CUDA (NVIDIA), AMD GPUs, Intel oneAPI GPUs, and Apple's Metal (M-series chip GPUs). + 'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users. For more information, + see Rackauckas and Nie (2017) . + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diffeqr + url_git: https://github.com/SciML/diffeqr +diffeR: + version: 0.0-8 + title: |- + Metrics of Difference for Comparing Pairs of Maps or Pairs of + Variables + maintainer: Ali Santacruz + description: Metrics of difference for comparing pairs of variables or pairs of + maps representing real or categorical variables at original and multiple resolutions. + date_publication: '2023-08-22' + bug_reports: https://github.com/amsantac/diffeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffeR + url_git: https://github.com/amsantac/diffeR +diffeRenTES: + version: 0.3.2 + title: Computation of TES-Based Cell Differentiation Trees + maintainer: Michele Braccini + description: |- + Computes the ATM (Attractor Transition Matrix) structure and + the tree-like structure describing the cell differentiation process + (based on the Threshold Ergodic Set concept introduced by Serra and + Villani), starting from the Boolean networks with synchronous updating + scheme of the 'BoolNet' R package. TESs (Threshold Ergodic Sets) are + the mathematical abstractions that represent the different cell types + arising during ontogenesis. TESs and the powerful model of biological + differentiation based on Boolean networks to which it belongs have + been firstly described in "A Dynamical Model of Genetic Networks for + Cell Differentiation" Villani M, Barbieri A, Serra R (2011) A + Dynamical Model of Genetic Networks for Cell Differentiation. PLOS ONE + 6(3): e17703. + date_publication: '2022-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diffeRenTES + url_git: '' +diffIRT: + version: '1.5' + title: Diffusion IRT Models for Response and Response Time Data + maintainer: Dylan Molenaar + description: |- + Package to fit diffusion-based IRT models to response and + response time data. Models are fit using marginal maximum + likelihood. Parameter restrictions (fixed value and equality + constraints) are possible. In addition, factor scores (person drift + rate and person boundary separation) can be estimated. Model fit + assessment tools are also available. The traditional diffusion model + can be estimated as well. + date_publication: '2015-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diffIRT + url_git: '' +diffmatchpatch: + version: 0.1.0 + title: String Diff, Match, and Patch Utilities + maintainer: Colin Rundel + description: |- + A wrapper for Google's 'diff-match-patch' library. It provides basic tools + for computing diffs, finding fuzzy matches, and constructing / applying patches to strings. + date_publication: '2021-04-16' + bug_reports: https://github.com/rundel/diffmatchpatch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffmatchpatch + url_git: https://github.com/rundel/diffmatchpatch +DiffNet: + version: 1.0.2 + title: |- + Identifying Significant Node Scores using Network Diffusion + Algorithm + maintainer: Farzaneh Firoozbakht + description: Designed for network analysis, leveraging the personalized PageRank + algorithm to calculate node scores in a given graph. This innovative approach + allows users to uncover the importance of nodes based on a customized perspective, + making it particularly useful in fields like bioinformatics, social network analysis, + and more. + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiffNet + url_git: '' +diffobj: + version: 0.3.5 + title: Diffs for R Objects + maintainer: Brodie Gaslam + description: |- + Generate a colorized diff of two R objects for an intuitive + visualization of their differences. + date_publication: '2021-10-05' + bug_reports: https://github.com/brodieG/diffobj/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffobj + url_git: https://github.com/brodieG/diffobj +diffpriv: + version: 0.4.2 + title: Easy Differential Privacy + maintainer: Benjamin Rubinstein + description: |- + An implementation of major general-purpose mechanisms for privatizing + statistics, models, and machine learners, within the framework of differential + privacy of Dwork et al. (2006) . Example mechanisms + include the Laplace mechanism for releasing numeric aggregates, and the + exponential mechanism for releasing set elements. A sensitivity sampler + (Rubinstein & Alda, 2017) permits sampling target + non-private function sensitivity; combined with the generic mechanisms, it + permits turn-key privatization of arbitrary programs. + date_publication: '2017-07-18' + bug_reports: https://github.com/brubinstein/diffpriv/issues + url: http://brubinstein.github.io/diffpriv + url_cran: https://CRAN.R-project.org/package=diffpriv + url_git: https://github.com/brubinstein/diffpriv +diffr: + version: '0.1' + title: Display Differences Between Two Files using Codediff Library + maintainer: John Muschelli + description: |- + An R interface to the 'codediff' JavaScript library (a copy of which is included in the package, + see for information). + Allows for visualization of the difference between 2 files, usually text files or R scripts, in a browser. + date_publication: '2017-02-27' + bug_reports: https://github.com/muschellij2/diffr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffr + url_git: '' +diffusion: + version: 0.4.0 + title: Forecast the Diffusion of New Products + maintainer: Oliver Schaer + description: |- + Various diffusion models to forecast new product growth. Currently + the package contains Bass, Gompertz, Gamma/Shifted Gompertz and Weibull curves. See + Meade and Islam (2006) . + date_publication: '2024-04-16' + bug_reports: https://github.com/mamut86/diffusion/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffusion + url_git: https://github.com/mamut86/diffusion +diffusionMap: + version: 1.2.0 + title: Diffusion Map + maintainer: Robrecht Cannoodt + description: |- + Implements diffusion map method of data + parametrization, including creation and visualization of + diffusion map, clustering with diffusion K-means and + regression using adaptive regression model. + Richards (2009) . + date_publication: '2019-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diffusionMap + url_git: https://github.com/rcannood/diffusionMap +diffval: + version: 1.1.0 + title: Vegetation Patterns + maintainer: Tiago Monteiro-Henriques + description: |- + Find, visualize and explore patterns of differential taxa in + vegetation data (namely in a phytosociological table), using the + Differential Value (DiffVal). Patterns are searched through + mathematical optimization algorithms. Ultimately, Total Differential + Value (TDV) optimization aims at obtaining classifications of + vegetation data based on differential taxa, as in the traditional + geobotanical approach. The Gurobi optimizer, as well as the R package + 'gurobi', can be installed from + . The useful + vignette Gurobi Installation Guide, from package 'prioritizr', can be + found here: + . + date_publication: '2023-03-09' + bug_reports: https://gitlab.com/point-veg/diffval/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diffval + url_git: https://gitlab.com/point-veg/diffval +diffviewer: + version: 0.1.2 + title: HTML Widget to Show File Differences + maintainer: Hadley Wickham + description: |- + A HTML widget that shows differences between files (text, + images, and data frames). + date_publication: '2024-06-12' + bug_reports: https://github.com/r-lib/diffviewer/issues + url: https://diffviewer.r-lib.org + url_cran: https://CRAN.R-project.org/package=diffviewer + url_git: https://github.com/r-lib/diffviewer +DiffXTables: + version: 0.1.3 + title: Pattern Analysis Across Contingency Tables + maintainer: Joe Song + description: |- + Statistical hypothesis testing of pattern heterogeneity + via differences in underlying distributions across multiple + contingency tables. Five tests are included: the comparative + chi-squared test (Song et al. 2014) + (Zhang et al. 2015) , the Sharma-Song + test (Sharma et al. 2021) , + the heterogeneity test, the marginal-change test (Sharma et al. + 2020) , and the strength test + (Sharma et al. 2020) . Under the + null hypothesis that row and column variables are statistically + independent and joint distributions are equal, their test + statistics all follow an asymptotically chi-squared distribution. + A comprehensive type analysis categorizes the relation among the + contingency tables into type null, 0, 1, and 2 (Sharma et al. + 2020) . They can identify + heterogeneous patterns that differ in either the first order + (marginal) or the second order (differential departure from + independence). Second-order differences reveal more + fundamental changes than first-order differences across + heterogeneous patterns. + date_publication: '2021-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiffXTables + url_git: '' +DIFlasso: + version: 1.0-4 + title: |- + A Penalty Approach to Differential Item Functioning in Rasch + Models + maintainer: Gunther Schauberger + description: Performs DIFlasso as proposed by Tutz and Schauberger (2015) , + a method to detect DIF (Differential Item Functioning) in Rasch Models. It can + handle settings with many variables and also metric variables. + date_publication: '2020-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIFlasso + url_git: '' +DIFM: + version: '1.0' + title: Dynamic ICAR Spatiotemporal Factor Models + maintainer: Hwasoo Shin + description: Bayesian factor models are effective tools for dimension reduction. + This is especially applicable to multivariate large-scale datasets. It allows + researchers to understand the latent factors of the data which are the linear + or non-linear combination of the variables. Dynamic Intrinsic Conditional Autocorrelative + Priors (ICAR) Spatiotemporal Factor Models 'DIFM' package provides function to + run Markov Chain Monte Carlo (MCMC), evaluation methods and visual plots from + Shin and Ferreira (2023). Our method is a class + of Bayesian factor model which can account for spatial and temporal correlations. + By incorporating these correlations, the model can capture specific behaviors + and provide predictions. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIFM + url_git: '' +difNLR: + version: 1.5.0 + title: DIF and DDF Detection by Non-Linear Regression Models + maintainer: Adela Hladka + description: Detection of differential item functioning (DIF) among dichotomously + scored items and differential distractor functioning (DDF) among unscored items + with non-linear regression procedures based on generalized logistic regression + models (Hladka & Martinkova, 2020, ). + date_publication: '2024-12-19' + bug_reports: https://github.com/adelahladka/difNLR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=difNLR + url_git: '' +DIFplus: + version: '1.1' + title: |- + Multilevel Mantel-Haenszel Statistics for Differential Item + Functioning Detection + maintainer: Shenghai Dai + description: |- + Clustered or multilevel data structures are common in the assessment of differential item functioning (DIF), particularly in the context of large-scale assessment programs. This package allows users to implement extensions of the Mantel-Haenszel DIF detection procedures in the presence of multilevel data based on the work of Begg (1999) , Begg & Paykin (2001) , + and French & Finch (2013) . + date_publication: '2020-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIFplus + url_git: '' +difR: + version: '5.1' + title: |- + Collection of Methods to Detect Dichotomous Differential Item + Functioning (DIF) + maintainer: David Magis + description: Provides a collection of standard methods to detect differential item + functioning among dichotomously scored items. Methods for uniform and non-uniform + DIF, based on test-score or IRT methods, for comparing two or more than two groups + of respondents, are available (Magis, Beland, Tuerlinckx and De Boeck,A General + Framework and an R Package for the Detection of Dichotomous Differential Item + Functioning, Behavior Research Methods, 42, 2010, 847-862 ). + date_publication: '2020-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=difR + url_git: '' +DIFshiny: + version: 0.1.0 + title: Differential Item Functioning via Shiny Application + maintainer: Huseyin Yildiz + description: Differential Item Functioning (DIF) Analysis with shiny application + interfaces. You can run the functions in this package without any arguments and + perform your DIF analysis using user-friendly interfaces. + date_publication: '2021-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIFshiny + url_git: '' +DIFtree: + version: 3.1.6 + title: |- + Item Focussed Trees for the Identification of Items in + Differential Item Functioning + maintainer: Moritz Berger + description: Item focussed recursive partitioning for simultaneous selection of + items and variables that induce Differential Item Functioning (DIF) in dichotomous + or polytomous items. + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIFtree + url_git: '' +digest: + version: 0.6.37 + title: Create Compact Hash Digests of R Objects + maintainer: Dirk Eddelbuettel + description: |- + Implementation of a function 'digest()' for the creation of hash + digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', + 'xxhash', 'murmurhash', 'spookyhash', 'blake3', 'crc32c', 'xxh3_64', and 'xxh3_128' + algorithms) permitting easy comparison of R language objects, as well as functions + such as'hmac()' to create hash-based message authentication code. Please note that + this package is not meant to be deployed for cryptographic purposes for which more + comprehensive (and widely tested) libraries such as 'OpenSSL' should be used. + date_publication: '2024-08-19' + bug_reports: https://github.com/eddelbuettel/digest/issues + url: https://dirk.eddelbuettel.com/code/digest.html + url_cran: https://CRAN.R-project.org/package=digest + url_git: https://github.com/eddelbuettel/digest +digiRhythm: + version: '2.4' + title: Analyzing Animal's Rhythmicity + maintainer: Hassan-Roland Nasser + description: |- + Analyze and visualize the rhythmic behavior of animals using the + degree of functional coupling (See Scheibe (1999) ), + compute and visualize harmonic power, actograms, average activity and diurnality + index. + date_publication: '2024-12-19' + bug_reports: '' + url: https://nasserdr.github.io/digiRhythm/ + url_cran: https://CRAN.R-project.org/package=digiRhythm + url_git: '' +digitalPCR: + version: 1.1.0 + title: Estimate Copy Number for Digital PCR + maintainer: Xutao Deng + description: The assay sensitivity is the minimum number of copies that the digital + PCR assay can detect. Users provide serial dilution results in the format of counts + of positive and total reaction wells. The output is the estimated assay sensitivity + and the copy number per well in the initial dilute. + date_publication: '2016-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=digitalPCR + url_git: '' +digitize: + version: 0.0.4 + title: Use Data from Published Plots in R + maintainer: Jaime Ashander + description: |- + Import data from a digital image; it requires user input for + calibration and to locate the data points. The end result is similar to + 'DataThief' and other other programs that 'digitize' published plots or + graphs. + date_publication: '2016-08-27' + bug_reports: https://github.com/tpoisot/digitize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=digitize + url_git: https://github.com/tpoisot/digitize/ +digitTests: + version: 0.1.2 + title: Tests for Detecting Irregular Digit Patterns + maintainer: Koen Derks + description: Provides statistical tests and support functions for detecting irregular + digit patterns in numerical data. The package includes tools for extracting digits + at various locations in a number, tests for repeated values, and (Bayesian) tests + of digit distributions. + date_publication: '2022-06-16' + bug_reports: https://github.com/koenderks/digitTests/issues + url: https://koenderks.github.io/digitTests/ + url_cran: https://CRAN.R-project.org/package=digitTests + url_git: https://github.com/koenderks/digitTests +DIGSS: + version: 1.0.2 + title: Determination of Intervals Using Georeferenced Survey Simulation + maintainer: Mark Hubbe + description: Simulation tool to estimate the rate of success that surveys possessing + user-specific characteristics have in identifying archaeological sites (or any + groups of clouds of objects), given specific parameters of survey area, survey + methods, and site properties. The survey approach used is largely based on the + work of Kintigh (1988) . + date_publication: '2021-08-04' + bug_reports: https://github.com/markhubbe/DIGSS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DIGSS + url_git: https://github.com/markhubbe/DIGSS +dilp: + version: 1.1.0 + title: Reconstruct Paleoclimate and Paleoecology with Leaf Physiognomy + maintainer: Matthew J. Butrim + description: |- + Use leaf physiognomic methods to reconstruct mean annual + temperature (MAT), mean annual precipitation (MAP), and leaf dry mass + per area (Ma), along with other useful quantitative leaf traits. Methods + in this package described in Lowe et al. (in review). + date_publication: '2024-04-05' + bug_reports: https://github.com/mjbutrim/dilp/issues + url: https://mjbutrim.github.io/dilp/ + url_cran: https://CRAN.R-project.org/package=dilp + url_git: https://github.com/mjbutrim/dilp +DIME: + version: 1.3.0 + title: Differential Identification using Mixture Ensemble + maintainer: Cenny Taslim + description: |- + A robust identification of differential binding sites method for analyzing ChIP-seq (Chromatin Immunoprecipitation Sequencing) + comparing two samples that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) + allowing for flexible modeling of data. Methods for Differential Identification using Mixture Ensemble (DIME) is described in: + Taslim et al., (2011) . + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIME + url_git: '' +dimensio: + version: 0.12.0 + title: Multivariate Data Analysis + maintainer: Nicolas Frerebeau + description: |- + Simple Principal Components Analysis (PCA) and (Multiple) + Correspondence Analysis (CA) based on the Singular Value Decomposition + (SVD). This package provides S4 classes and methods to compute, + extract, summarize and visualize results of multivariate data + analysis. It also includes methods for partial bootstrap validation + described in Greenacre (1984, ISBN: 978-0-12-299050-2) and Lebart et + al. (2006, ISBN: 978-2-10-049616-7). + date_publication: '2025-02-25' + bug_reports: https://codeberg.org/tesselle/dimensio/issues + url: https://codeberg.org/tesselle/dimensio + url_cran: https://CRAN.R-project.org/package=dimensio + url_git: '' +dimensionsR: + version: 0.0.3 + title: |- + Gathering Bibliographic Records from 'Digital Science + Dimensions' Using 'DSL' API + maintainer: Massimo Aria + description: A set of tools to extract bibliographic content from 'Digital Science + Dimensions' using 'DSL' API . + date_publication: '2022-02-07' + bug_reports: https://github.com/massimoaria/dimensionsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dimensionsR + url_git: https://github.com/massimoaria/dimensionsR +DImodels: + version: 1.3.2 + title: Diversity-Interactions (DI) Models + maintainer: Rafael de Andrade Moral + description: The 'DImodels' package is suitable for analysing data from biodiversity + and ecosystem function studies using the Diversity-Interactions (DI) modelling + approach introduced by Kirwan et al. (2009) . Suitable + data will contain proportions for each species and a community-level response + variable, and may also include additional factors, such as blocks or treatments. + The package can perform data manipulation tasks, such as computing pairwise interactions + (the DI_data() function), can perform an automated model selection process (the + autoDI() function) and has the flexibility to fit a wide range of user-defined + DI models (the DI() function). + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DImodels + url_git: '' +DImodelsMulti: + version: 1.1.1 + title: |- + Fit Multivariate Diversity-Interactions Models with Repeated + Measures + maintainer: Laura Byrne + description: An add-on package to 'DImodels' for the fitting of biodiversity and + ecosystem function relationship study data with multiple ecosystem function responses + and/or time points. This package uses the multivariate and repeated measures Diversity-Interactions + (DI) methods developed by Kirwan et al. (2009) , Finn et + al. (2013) , and Dooley et al. (2015) . + date_publication: '2024-05-08' + bug_reports: '' + url: https://dimodels.com + url_cran: https://CRAN.R-project.org/package=DImodelsMulti + url_git: https://github.com/DI-LauraByrne/DImodelsMulti +DImodelsVis: + version: 1.0.1 + title: |- + Visualising and Interpreting Statistical Models Fit to + Compositional Data + maintainer: Rishabh Vishwakarma + description: Statistical models fit to compositional data are often difficult to + interpret due to the sum to 1 constraint on data variables. 'DImodelsVis' provides + novel visualisations tools to aid with the interpretation of models fit to compositional + data. All visualisations in the package are created using the 'ggplot2' plotting + framework and can be extended like every other 'ggplot' object. + date_publication: '2024-02-26' + bug_reports: '' + url: https://rishvish.github.io/DImodelsVis/ + url_cran: https://CRAN.R-project.org/package=DImodelsVis + url_git: '' +DIMORA: + version: 0.3.6 + title: Diffusion Models R Analysis + maintainer: Savio Andrea + description: 'The implemented methods are: Standard Bass model, Generalized Bass + model (with rectangular shock, exponential shock, and mixed shock. You can choose + to add from 1 to 3 shocks), Guseo-Guidolin model and Variable Potential Market + model, and UCRCD model. The Bass model consists of a simple differential equation + that describes the process of how new products get adopted in a population, the + Generalized Bass model is a generalization of the Bass model in which there is + a "carrier" function x(t) that allows to change the speed of time sliding. In + some real processes the reachable potential of the resource available in a temporal + instant may appear to be not constant over time, because of this we use Variable + Potential Market model, in which the Guseo-Guidolin has a particular specification + for the market function. The UCRCD model (Unbalanced Competition and Regime Change + Diachronic) is a diffusion model used to capture the dynamics of the competitive + or collaborative transition.' + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIMORA + url_git: '' +dina: + version: 2.0.0 + title: Bayesian Estimation of DINA Model + maintainer: James Joseph Balamuta + description: |- + Estimate the Deterministic Input, Noisy "And" Gate (DINA) + cognitive diagnostic model parameters using the Gibbs sampler described + by Culpepper (2015) . + date_publication: '2019-02-01' + bug_reports: https://github.com/tmsalab/dina/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dina + url_git: https://github.com/tmsalab/dina +dinamic: + version: 1.0.1 + title: |- + A Method to Analyze Recurrent DNA Copy Number Aberrations in + Tumors + maintainer: Vonn Walter + description: |- + In tumor tissue, underlying genomic instability can lead to DNA copy number alterations, + e.g., copy number gains or losses. Sporadic copy number alterations occur randomly throughout the + genome, whereas recurrent alterations are observed in the same genomic region across multiple + independent samples, perhaps because they provide a selective growth advantage. + This package implements the DiNAMIC procedure for assessing the statistical significance of + recurrent DNA copy number aberrations (Bioinformatics (2011) 27(5) 678 - 685). + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dinamic + url_git: '' +DiNAMIC.Duo: + version: 1.0.2 + title: Finding Recurrent DNA Copy Number Alterations and Differences + maintainer: Vonn Walter + description: |- + In tumor tissue, underlying genomic instability can lead to DNA copy number alterations, + e.g., copy number gains or losses. Sporadic copy number alterations occur randomly throughout the + genome, whereas recurrent alterations are observed in the same genomic region across multiple + independent samples, perhaps because they provide a selective growth advantage. Here we use + cyclic shift permutations to identify recurrent copy number alterations in a single cohort or + recurrent copy number differences in two cohorts based on a common set of genomic markers. + Additional functionality is provided to perform downstream analyses, including the creation of + summary files and graphics. DiNAMIC.Duo builds upon the original DiNAMIC package of Walter et al. + (2011) and leverages the theory developed in Walter et al. + (2015) . An article describing DiNAMIC.Duo by Walter et al. (2022) + can be found at . + date_publication: '2023-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiNAMIC.Duo + url_git: '' +dineq: + version: 0.1.0 + title: Decomposition of (Income) Inequality + maintainer: René Schulenberg + description: |- + Decomposition of (income) inequality by population sub groups. + For a decomposition on a single variable the mean log deviation can be used + (see Mookherjee Shorrocks (1982) ). + For a decomposition on multiple variables a regression based technique can be + used (see Fields (2003) ). + Recentered influence function regression for marginal effects of the (income + or wealth) distribution (see Firpo et al. (2009) ). + Some extensions to inequality functions to handle weights and/or missings. + date_publication: '2018-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dineq + url_git: '' +dineR: + version: 1.0.1 + title: Differential Network Estimation in R + maintainer: Ricardo Daniel Marques Salgado + description: An efficient and convenient set of functions to perform differential + network estimation through the use of alternating direction method of multipliers + optimization with a variety of loss functions. + date_publication: '2021-11-15' + bug_reports: https://github.com/RicSalgado/dineR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dineR + url_git: https://github.com/RicSalgado/dineR +dint: + version: 2.1.5 + title: A Toolkit for Year-Quarter, Year-Month and Year-Isoweek Dates + maintainer: Stefan Fleck + description: |- + S3 classes and methods to create and work + with year-quarter, year-month and year-isoweek vectors. Basic + arithmetic operations (such as adding and subtracting) are supported, + as well as formatting and converting to and from standard R date + types. + date_publication: '2024-11-20' + bug_reports: https://github.com/s-fleck/dint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dint + url_git: https://github.com/s-fleck/dint +DiPALM: + version: '1.2' + title: Differential Pattern Analysis via Linear Modeling + maintainer: Ryan C. Sartor + description: 'Individual gene expression patterns are encoded into a series of eigenvector + patterns (''WGCNA'' package). Using the framework of linear model-based differential + expression comparisons (''limma'' package), time-course expression patterns for + genes in different conditions are compared and analyzed for significant pattern + changes. For reference, see: Greenham K, Sartor RC, Zorich S, Lou P, Mockler TC + and McClung CR. eLife. 2020 Sep 30;9(4). .' + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiPALM + url_git: '' +DiPhiSeq: + version: 0.2.0 + title: |- + Robust Tests for Differential Dispersion and Differential + Expression in RNA-Sequencing Data + maintainer: Jun Li + description: |- + Implements the algorithm described in Jun Li and Alicia T. Lamere, + "DiPhiSeq: Robust comparison of expression levels on RNA-Seq data with large sample sizes" (Unpublished). + Detects not only genes that show different + average expressions ("differential expression", DE), but also genes that show different + diversities of expressions in different groups ("differentially dispersed", DD). DD genes + can be important clinical markers. 'DiPhiSeq' uses a redescending penalty on the + quasi-likelihood function, and thus has superior robustness against outliers and other noise. + Updates from version 0.1.0: (1) Added the option of using adaptive initial value for phi. + (2) Added a function for estimating the proportion of outliers in the data. + (3) Modified the input parameter names for clarity, and modified the output format for the main function. + date_publication: '2018-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiPhiSeq + url_git: '' +dipm: + version: '1.9' + title: Depth Importance in Precision Medicine (DIPM) Method + maintainer: Cai Li + description: |- + An implementation by Chen, Li, and Zhang (2022) of the Depth Importance in Precision Medicine (DIPM) method + in Chen and Zhang (2022) and Chen and + Zhang (2020) . The DIPM method is a classification + tree that searches for subgroups with especially poor or strong performance in a given treatment group. + date_publication: '2022-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dipm + url_git: '' +DiPs: + version: 0.6.4 + title: |- + Directional Penalties for Optimal Matching in Observational + Studies + maintainer: Ruoqi Yu + description: |- + Improves the balance of optimal matching with near-fine balance by giving penalties on the unbalanced covariates with the unbalanced directions. Many directional penalties can also be viewed as Lagrange multipliers, pushing a matched sample in the direction of satisfying a linear constraint that would not be satisfied without penalization. + Yu and Rosenbaum (2019) . + date_publication: '2022-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiPs + url_git: '' +dipsaus: + version: 0.3.0 + title: A Dipping Sauce for Data Analysis and Visualizations + maintainer: Zhengjia Wang + description: |- + Works as an "add-on" to packages like 'shiny', 'future', as well as + 'rlang', and provides utility functions. Just like dipping sauce adding + flavors to potato chips or pita bread, 'dipsaus' for data analysis and + visualizations adds handy functions and enhancements to popular packages. + The goal is to provide simple solutions that are frequently asked for + online, such as how to synchronize 'shiny' inputs without freezing the app, + or how to get memory size on 'Linux' or 'MacOS' system. The enhancements + roughly fall into these four categories: 1. 'shiny' input widgets; 2. + high-performance computing using the 'future' package; 3. + modify R calls and convert among numbers, strings, and other objects. 4. + utility functions to get system information such like CPU chip-set, memory + limit, etc. + date_publication: '2024-12-17' + bug_reports: https://github.com/dipterix/dipsaus/issues + url: https://dipterix.org/dipsaus/ + url_cran: https://CRAN.R-project.org/package=dipsaus + url_git: https://github.com/dipterix/dipsaus +diptest: + version: 0.77-1 + title: Hartigan's Dip Test Statistic for Unimodality - Corrected + maintainer: Martin Maechler + description: |- + Compute Hartigan's dip test statistic for unimodality / + multimodality and provide a test with simulation based p-values, where + the original public code has been corrected. + date_publication: '2024-04-10' + bug_reports: https://github.com/mmaechler/diptest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diptest + url_git: https://github.com/mmaechler/diptest +dipw: + version: 0.1.0 + title: Debiased Inverse Propensity Score Weighting + maintainer: Yuhao Wang + description: |- + Estimation of the average treatment effect when controlling for + high-dimensional confounders using debiased inverse propensity score + weighting (DIPW). DIPW relies on the propensity score following a sparse + logistic regression model, but the regression curves are not required to be + estimable. Despite this, our package also allows the users to estimate + the regression curves and take the estimated curves as input to our + methods. Details of the methodology can be found in Yuhao Wang and + Rajen D. Shah (2020) "Debiased Inverse Propensity Score Weighting for + Estimation of Average Treatment Effects with High-Dimensional Confounders" + . The package relies on the optimisation + software 'MOSEK' which must be installed separately; + see the documentation for 'Rmosek'. + date_publication: '2020-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dipw + url_git: '' +Dire: + version: 2.2.0 + title: Linear Regressions with a Latent Outcome Variable + maintainer: Paul Bailey + description: Fit latent variable linear models, estimating score distributions for + groups of people, following Cohen and Jiang (1999) . In this + model, a latent distribution is conditional on students item response, item characteristics, + and conditioning variables the user includes. This latent trait is then integrated + out. This software is intended to fit the same models as the existing software + 'AM' . As of version 2, also allows the user to draw plausible + values. + date_publication: '2023-10-26' + bug_reports: https://github.com/American-Institutes-for-Research/Dire/issues + url: https://american-institutes-for-research.github.io/Dire/ + url_cran: https://CRAN.R-project.org/package=Dire + url_git: '' +DIRECT: + version: 1.1.0 + title: |- + Bayesian Clustering of Multivariate Data Under the + Dirichlet-Process Prior + maintainer: Audrey Q. Fu + description: A Bayesian clustering method for replicated time series or replicated + measurements from multiple experimental conditions, e.g., time-course gene expression + data. It estimates the number of clusters directly from the data using a Dirichlet-process + prior. See Fu, A. Q., Russell, S., Bray, S. and Tavare, S. (2013) Bayesian clustering + of replicated time-course gene expression data with weak signals. The Annals of + Applied Statistics. 7(3) 1334-1361. . + date_publication: '2023-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIRECT + url_git: '' +DirectedClustering: + version: 1.0.0 + title: Directed Weighted Clustering Coefficient + maintainer: Gian Paolo Clemente + description: |- + Allows the computation of clustering coefficients for directed and weighted networks by using different approaches. + It allows to compute clustering coefficients that are not present in 'igraph' package. + A description of clustering coefficients can be found in "Directed clustering in weighted networks: a new perspective", Clemente, G.P., Grassi, R. (2017), + . + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DirectedClustering + url_git: '' +DirectEffects: + version: '0.3' + title: |- + Estimating Controlled Direct Effects for Explaining Causal + Findings + maintainer: Matthew Blackwell + description: A set of functions to estimate the controlled direct effect of treatment + fixing a potential mediator to a specific value. Implements the sequential g-estimation + estimator described in Vansteelandt (2009) + and Acharya, Blackwell, and Sen (2016) and the + telescope matching estimator described in Blackwell and Strezhnev (2020) . + date_publication: '2024-10-04' + bug_reports: https://github.com/mattblackwell/DirectEffects/issues + url: https://mattblackwell.github.io/DirectEffects/ + url_cran: https://CRAN.R-project.org/package=DirectEffects + url_git: '' +Directional: + version: '7.1' + title: A Collection of Functions for Directional Data Analysis + maintainer: Michail Tsagris + description: |- + A collection of functions for directional data (including massive data, with millions of observations) analysis. + Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. + The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). + Other references include: + a) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. . + b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. . + c) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. . + d) Tsagris M. and Alenazi A. (2024). "An investigation of hypothesis testing procedures for circular and spherical mean vectors". Communications in Statistics-Simulation and Computation, 53(3): 1387--1408. . + e) Yu Z. and Huang X. (2024). A new parameterization for elliptically symmetric angular Gaussian distributions of arbitrary dimension. Electronic Journal of Statistics, 18(1): 301--334. . + f) Tsagris M. and Alzeley O. (2024). "Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling". Australian & New Zealand Journal of Statistics (Accepted for publication). . + g) Tsagris M., Papastamoulis P. and Kato S. (2024). "Directional data analysis: spherical Cauchy or Poisson kernel-based distribution". Statistics and Computing (Accepted for publication). . + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Directional + url_git: '' +directlabels: + version: 2024.1.21 + title: Direct Labels for Multicolor Plots + maintainer: Toby Dylan Hocking + description: |- + An extensible framework + for automatically placing direct labels onto multicolor 'lattice' or + 'ggplot2' plots. + Label positions are described using Positioning Methods + which can be re-used across several different plots. + There are heuristics for examining "trellis" and "ggplot" objects + and inferring an appropriate Positioning Method. + date_publication: '2024-01-24' + bug_reports: https://github.com/tdhock/directlabels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=directlabels + url_git: https://github.com/tdhock/directlabels +directotree: + version: 1.0.0 + title: Creates an Interactive Tree Structure of a Directory + maintainer: Louis Sirugue + description: |- + Represents the content of a directory as an interactive collapsible tree. Offers + the possibility to assign a text (e.g., a 'Readme.txt') to each folder + (represented as a clickable node), so that when the user hovers the pointer + over a node, the corresponding text is displayed as a tooltip. + date_publication: '2018-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=directotree + url_git: '' +directPA: + version: 1.5.1 + title: Direction Analysis for Pathways and Kinases + maintainer: Pengyi Yang + description: |- + Direction analysis is a set of tools designed to identify + combinatorial effects of multiple treatments/conditions on pathways + and kinases profiled by microarray, RNA-seq, proteomics, or phosphoproteomics + data. See Yang P et al (2014) ; and Yang P et al. (2016) . + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=directPA + url_git: '' +DirectStandardisation: + version: '1.3' + title: Adjusted Means and Proportions by Direct Standardisation + maintainer: Christiana Kartsonaki + description: Calculate adjusted means and proportions of a variable by groups defined + by another variable by direct standardisation, standardised to the structure of + the dataset. + date_publication: '2020-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DirectStandardisation + url_git: '' +dirichletprocess: + version: 0.4.2 + title: Build Dirichlet Process Objects for Bayesian Modelling + maintainer: Dean Markwick + description: |- + Perform nonparametric Bayesian analysis using Dirichlet + processes without the need to program the inference algorithms. + Utilise included pre-built models or specify custom + models and allow the 'dirichletprocess' package to handle the + Markov chain Monte Carlo sampling. + Our Dirichlet process objects can act as building blocks for a variety + of statistical models including and not limited to: density estimation, + clustering and prior distributions in hierarchical models. + See Teh, Y. W. (2011) + , + among many other sources. + date_publication: '2023-08-25' + bug_reports: https://github.com/dm13450/dirichletprocess/issues + url: https://dm13450.github.io/dirichletprocess/ + url_cran: https://CRAN.R-project.org/package=dirichletprocess + url_git: https://github.com/dm13450/dirichletprocess +DirichletReg: + version: 0.7-1 + title: Dirichlet Regression + maintainer: Marco Johannes Maier + description: Implements Dirichlet regression models. + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DirichletReg + url_git: https://github.com/maiermarco/DirichletReghttps://CRAN.R-project.org/package=DirichletReg +dirmcmc: + version: 1.3.3 + title: Directional Metropolis Hastings Algorithm + maintainer: Abhirup Mallik + description: |- + Implementation of Directional Metropolis Hastings Algorithm for + MCMC. + date_publication: '2017-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dirmcmc + url_git: '' +DIRMR: + version: 0.5.0 + title: |- + Distributed Imputation for Random Effects Models with Missing + Responses + maintainer: Guangbao Guo + description: By adding over-relaxation factor to PXEM (Parameter Expanded Expectation + Maximization) method, the MOPXEM (Monotonically Overrelaxed Parameter Expanded + Expectation Maximization) method is obtained. Compare it with the existing EM + (Expectation-Maximization)-like methods. Then, distribute and process five methods + and compare them, achieving good performance in convergence speed and result quality.The + philosophy of the package is described in Guo G. (2022) . + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DIRMR + url_git: '' +dirmult: + version: 0.1.3-5 + title: Estimation in Dirichlet-Multinomial Distribution + maintainer: Torben Tvedebrink + description: Estimate parameters in Dirichlet-Multinomial and compute log-likelihoods. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dirmult + url_git: '' +DirStats: + version: 0.1.10 + title: Nonparametric Methods for Directional Data + maintainer: Eduardo García-Portugués + description: |- + Nonparametric kernel density estimation, bandwidth selection, + and other utilities for analyzing directional data. Implements the estimator + in Bai, Rao and Zhao (1987) , the + cross-validation bandwidth selectors in Hall, Watson and Cabrera (1987) + and the plug-in bandwidth selectors in + García-Portugués (2013) . + date_publication: '2024-06-13' + bug_reports: https://github.com/egarpor/DirStats + url: '' + url_cran: https://CRAN.R-project.org/package=DirStats + url_git: https://github.com/egarpor/DirStats +dirttee: + version: 1.0.2 + title: Distributional Regression for Time to Event Data + maintainer: Alexander Seipp + description: |- + Semiparametric distributional regression methods (expectile, + quantile and mode regression) for time-to-event variables with + right-censoring; uses inverse probability of censoring weights or + accelerated failure time models with auxiliary likelihoods. Expectile + regression using inverse probability of censoring weights has been + introduced in Seipp et al. (2021) ``Weighted Expectile Regression for + Right-Censored Data'' , mode regression for + time-to-event variables has been introduced in Seipp et al. (2022) + ``Flexible Semiparametric Mode Regression for Time-to-Event Data'' + . + date_publication: '2023-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dirttee + url_git: '' +disagg2: + version: 0.1.0 + title: Support Functions for Time Series Analysis Book + maintainer: Erin Hodgess + description: |- + Contains the support functions for the Time Series Analysis book. + We present a function to calculate MSE and MAE for inputs + of actual and forecast values. We also have the code for + disaggregation as found in Wei and Stram + (1990, ), + and Hodgess and Wei (1996, "Temporal Disaggregation of Time + Series"). + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disagg2 + url_git: '' +disaggR: + version: 1.0.5.3 + title: Two-Steps Benchmarks for Time Series Disaggregation + maintainer: Pauline Meinzel + description: |- + The twoStepsBenchmark() and threeRuleSmooth() functions allow you to + disaggregate a low-frequency time series with higher frequency time series, + using the French National Accounts methodology. The aggregated sum of the + resulting time series is strictly equal to the low-frequency time series within the + benchmarking window. Typically, the low-frequency time series is an annual one, + unknown for the last year, and the high frequency one is either quarterly or + monthly. See "Methodology of quarterly national accounts", Insee Méthodes + N°126, by Insee (2012, ISBN:978-2-11-068613-8, ). + date_publication: '2024-07-11' + bug_reports: https://github.com/InseeFr/disaggR/issues + url: https://inseefr.github.io/disaggR/ + url_cran: https://CRAN.R-project.org/package=disaggR + url_git: '' +DisaggregateTS: + version: 3.0.1 + title: High-Dimensional Temporal Disaggregation + maintainer: Kaveh Salehzadeh Nobari + description: |- + Provides tools for temporal disaggregation, including: + (1) High-dimensional and low-dimensional series generation for simulation studies; + (2) A toolkit for temporal disaggregation and benchmarking using low-dimensional indicator series + as proposed by Dagum and Cholette (2006, ISBN:978-0-387-35439-2); + (3) Novel techniques by Mosley, Gibberd, and Eckley (2022, ) + for disaggregating low-frequency series in the presence of high-dimensional indicator matrices. + date_publication: '2024-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DisaggregateTS + url_git: '' +disaggregation: + version: 0.4.0 + title: Disaggregation Modelling + maintainer: Tim Lucas + description: |- + Fits disaggregation regression models using 'TMB' ('Template Model + Builder'). When the response data are aggregated to polygon level but + the predictor variables are at a higher resolution, these models can be + useful. Regression models with spatial random fields. The package is + described in detail in Nandi et al. (2023) . + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disaggregation + url_git: '' +disastr.api: + version: 1.0.6 + title: Wrapper for the UN OCHA ReliefWeb Disaster Events API + maintainer: Christoph Dworschak + description: Access and manage the application programming interface (API) of the + United Nations Office for the Coordination of Humanitarian Affairs' (OCHA) ReliefWeb + disaster events at . The package requires a minimal + number of dependencies. It offers functionality to retrieve a user-defined sample + of disaster events from ReliefWeb, providing an easy alternative to scraping the + ReliefWeb website. It enables a seamless integration of regular data updates into + the research work flow. + date_publication: '2024-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disastr.api + url_git: '' +disbayes: + version: 1.1.0 + title: Bayesian Multi-State Modelling of Chronic Disease Burden Data + maintainer: Christopher Jackson + description: Estimation of incidence and case fatality for a chronic disease, given + partial information, using a multi-state model. Given data on age-specific mortality + and either incidence or prevalence, Bayesian inference is used to estimate the + posterior distributions of incidence, case fatality, and functions of these such + as prevalence. The methods are described in Jackson et al. (2023) . + date_publication: '2023-09-09' + bug_reports: https://github.com/chjackson/disbayes/issues + url: https://chjackson.github.io/disbayes/ + url_cran: https://CRAN.R-project.org/package=disbayes + url_git: '' +discAUC: + version: 1.0.3 + title: Linear and Non-Linear AUC for Discounting Data + maintainer: Jonathan E. Friedel + description: |- + Area under the curve (AUC; Myerson et al., 2001) + is a popular measure used in discounting research. Although the calculation of + AUC is standardized, there are differences in AUC based on some assumptions. + For example, Myerson et al. (2001) + assumed that (with delay discounting data) a researcher would impute an + indifference point at zero delay equal to the value of the larger, later outcome. + However, this practice is not clearly followed. This imputed zero-delay indifference + point plays an important role in log and ordinal versions of AUC. + Ordinal and log versions of AUC are described by Borges et al. (2016). + The package can calculate all three versions of AUC [and includes a new version: IHS(AUC)], + impute indifference points when x = 0, calculate ordinal AUC in the case of Halton + sampling of x-values, and account for probability discounting AUC. + date_publication: '2024-10-10' + bug_reports: https://github.com/jefriedel/discAUC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=discAUC + url_git: https://github.com/jefriedel/discAUC +DIscBIO: + version: 1.2.2 + title: |- + A User-Friendly Pipeline for Biomarker Discovery in Single-Cell + Transcriptomics + maintainer: Waldir Leoncio + description: |- + An open, multi-algorithmic pipeline for easy, fast and efficient + analysis of cellular sub-populations and the molecular signatures that + characterize them. The pipeline consists of four successive steps: data + pre-processing, cellular clustering with pseudo-temporal ordering, defining + differential expressed genes and biomarker identification. More details on + Ghannoum et. al. (2021) . This package implements + extensions of the work published by Ghannoum et. al. (2019) + . + date_publication: '2023-11-06' + bug_reports: https://github.com/ocbe-uio/DIscBIO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DIscBIO + url_git: https://github.com/ocbe-uio/DIscBIO +discFA: + version: 1.0.1 + title: Discrete Factor Analysis + maintainer: Reza A. Belaghi + description: Discrete factor analysis for dependent Poisson and negative binomial + models with truncation, zero inflation, and zero inflated truncation. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discFA + url_git: '' +discfrail: + version: '0.1' + title: |- + Cox Models for Time-to-Event Data with Nonparametric Discrete + Group-Specific Frailties + maintainer: Francesca Gasperoni + description: Functions for fitting Cox proportional hazards models for grouped time-to-event + data, where the shared group-specific frailties have a discrete nonparametric + distribution. The methods proposed in the package is described by Gasperoni, F., + Ieva, F., Paganoni, A. M., Jackson, C. H., Sharples, L. (2018) . + There are also functions for simulating from these models, with a nonparametric + or a parametric baseline hazard function. + date_publication: '2019-03-13' + bug_reports: https://github.com/fgaspe04/discfrail/issues + url: '' + url_cran: https://CRAN.R-project.org/package=discfrail + url_git: https://github.com/fgaspe04/discfrail +discharge: + version: 1.0.0 + title: Fourier Analysis of Discharge Data + maintainer: Samarth Shah + description: |- + Computes discrete fast Fourier transform of river discharge data and the derived metrics. + The methods are described in J. L. Sabo, D. M. Post (2008) and J. L. Sabo, A. Ruhi, G. W. Holtgrieve, V. Elliott, M. E. Arias, P. B. Ngor, T. A. Räsänsen, S. Nam (2017) . + date_publication: '2019-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discharge + url_git: '' +disclap: + version: 1.5.1 + title: Discrete Laplace Exponential Family + maintainer: Mikkel Meyer Andersen + description: The discrete Laplace exponential family for use in fitting generalized + linear models. + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disclap + url_git: '' +disclapmix: + version: 1.7.4 + title: Discrete Laplace Mixture Inference using the EM Algorithm + maintainer: Mikkel Meyer Andersen + description: Make inference in a mixture of discrete Laplace distributions using + the EM algorithm. This can e.g. be used for modelling the distribution of Y chromosomal + haplotypes as described in [1, 2] (refer to the URL section). + date_publication: '2022-06-29' + bug_reports: https://github.com/mikldk/disclapmix/issues + url: http://dx.doi.org/10.1016/j.jtbi.2013.03.009https://arxiv.org/abs/1304.2129 + url_cran: https://CRAN.R-project.org/package=disclapmix + url_git: '' +disclapmix2: + version: 0.6.1 + title: |- + Mixtures of Discrete Laplace Distributions using Numerical + Optimisation + maintainer: Maarten Kruijver + description: Fit a mixture of Discrete Laplace distributions using plain numerical + optimisation. This package has similar applications as the 'disclapmix' package + that uses an EM algorithm. + date_publication: '2023-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disclapmix2 + url_git: '' +disclosuR: + version: 0.6.0 + title: Text Conversion from Nexis Uni PDFs to R Data Frames + maintainer: Jonas Röttger + description: Transform 'newswire' and earnings call transcripts as PDF obtained + from 'Nexis Uni' to R data frames. Various 'newswires' and 'FairDisclosure' earnings + call formats are supported. Further, users can apply several pre-defined dictionaries + on the data based on Graffin et al. (2016) and Gamache + et al. (2015). + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disclosuR + url_git: '' +discnorm: + version: 0.2.1 + title: Test for Discretized Normality in Ordinal Data + maintainer: Njål Foldnes + description: |- + Tests whether multivariate ordinal data may stem from discretizing a multivariate normal distribution. + The test is described by Foldnes and Grønneberg (2019) . + In addition, an adjusted polychoric correlation estimator is provided that takes marginal knowledge into account, + as described by Grønneberg and Foldnes (2022) . + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discnorm + url_git: '' +discord: + version: 1.1.0 + title: Functions for Discordant Kinship Modeling + maintainer: S. Mason Garrison + description: Functions for discordant kinship modeling (and other sibling-based + quasi-experimental designs). Currently, the package contains data restructuring + functions and functions for generating biometrically informed data for kin pairs. + date_publication: '2021-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discord + url_git: https://github.com/R-Computing-Lab/discord +DiSCos: + version: 0.1.1 + title: Distributional Synthetic Controls Estimation + maintainer: David Van Dijcke + description: The method of synthetic controls is a widely-adopted tool for evaluating + causal effects of policy changes in settings with observational data. In many + settings where it is applicable, researchers want to identify causal effects of + policy changes on a treated unit at an aggregate level while having access to + data at a finer granularity. This package implements a simple extension of the + synthetic controls estimator, developed in Gunsilius (2023) , + that takes advantage of this additional structure and provides nonparametric estimates + of the heterogeneity within the aggregate unit. The idea is to replicate the quantile + function associated with the treated unit by a weighted average of quantile functions + of the control units. The package contains tools for aggregating and plotting + the resulting distributional estimates, as well as for carrying out inference + on them. + date_publication: '2024-07-23' + bug_reports: https://github.com/Davidvandijcke/DiSCos/issues + url: http://www.davidvandijcke.com/DiSCos/ + url_cran: https://CRAN.R-project.org/package=DiSCos + url_git: https://github.com/Davidvandijcke/DiSCos +discourseGT: + version: 1.2.0 + title: |- + Analyze Group Patterns using Graph Theory in Educational + Settings + maintainer: Qi Cui + description: |- + Analyzes group patterns using discourse analysis data with + graph theory mathematics. Takes the order of which individuals talk + and converts it to a network edge and weight list. Returns the + density, centrality, centralization, and subgroup information for each + group. Based on the analytical framework laid out in Chai et al. + (2019) . + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discourseGT + url_git: '' +discoveR: + version: 3.1.7 + title: Exploratory Data Analysis System + maintainer: Oldemar Rodriguez + description: Performs an exploratory data analysis through a 'shiny' interface. + It includes basic methods such as the mean, median, mode, normality test, among + others. It also includes clustering techniques such as Principal Components Analysis, + Hierarchical Clustering and the K-Means Method. + date_publication: '2025-02-12' + bug_reports: https://github.com/PROMiDAT/discoveR/issues + url: https://promidat.website/ + url_cran: https://CRAN.R-project.org/package=discoveR + url_git: https://github.com/PROMiDAT/discoveR +discoverableresearch: + version: 0.0.1 + title: Checks Title, Abstract and Keywords to Optimise Discoverability + maintainer: Neal Haddaway + description: |- + A suite of tools are provided here to support authors in making their research more discoverable. + check_keywords() - this function checks the keywords to assess whether they are already represented in the + title and abstract. check_fields() - this function compares terminology used across the title, abstract + and keywords to assess where terminological diversity (i.e. the use of synonyms) could increase the likelihood + of the record being identified in a search. The function looks for terms in the title and abstract that also + exist in other fields and highlights these as needing attention. suggest_keywords() - this function takes a + full text document and produces a list of unigrams, bigrams and trigrams (1-, 2- or 2-word phrases) + present in the full text after removing stop words (words with a low utility in natural language processing) + that do not occur in the title or abstract that may be suitable candidates for keywords. suggest_title() - + this function takes a full text document and produces a list of the most frequently used unigrams, bigrams + and trigrams after removing stop words that do not occur in the abstract or keywords that may be suitable + candidates for title words. check_title() - this function carries out a number of sub tasks: 1) it compares + the length (number of words) of the title with the mean length of titles in major bibliographic databases to + assess whether the title is likely to be too short; 2) it assesses the proportion of stop words in the title + to highlight titles with low utility in search engines that strip out stop words; 3) it compares the title + with a given sample of record titles from an .ris import and calculates a similarity score based on phrase + overlap. This highlights the level of uniqueness of the title. This version of the package also contains + functions currently in a non-CRAN package called 'litsearchr' . + date_publication: '2020-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discoverableresearch + url_git: '' +DiscreteDatasets: + version: 0.1.2 + title: Example Data Sets for Use with Discrete Statistical Tests + maintainer: Florian Junge + description: |- + Provides several data sets for use with discrete statistical tests + and discrete multiple testing procedures. Some of them are also available as a + four-column version, so that each row represents a 2x2 table. + date_publication: '2025-01-24' + bug_reports: https://github.com/DISOhda/DiscreteDatasets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteDatasets + url_git: https://github.com/DISOhda/DiscreteDatasets +DiscreteDists: + version: 1.0.0 + title: Discrete Statistical Distributions + maintainer: Freddy Hernandez-Barajas + description: Implementation of new discrete statistical distributions. Each distribution + includes the traditional functions as well as an additional function called the + family function, which can be used to estimate parameters within the 'gamlss' + framework. + date_publication: '2024-09-13' + bug_reports: https://github.com/fhernanb/DiscreteDists/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteDists + url_git: https://github.com/fhernanb/DiscreteDists +DiscreteDLM: + version: 1.0.0 + title: |- + Bayesian Distributed Lag Model Fitting for Binary and Count + Response Data + maintainer: Daniel Dempsey + description: Tools for fitting Bayesian Distributed Lag Models (DLMs) to longitudinal + response data that is a count or binary. Count data is fit using negative binomial + regression and binary is fit using quantile regression. The contribution of the + lags are fit via b-splines. In addition, infers the predictor inclusion uncertainty. + Multimomial models are not supported. Based on Dempsey and Wyse (2025) . + date_publication: '2025-02-06' + bug_reports: https://github.com/DanDempsey/DiscreteDLM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteDLM + url_git: https://github.com/DanDempsey/DiscreteDLM +DiscreteFDR: + version: 2.1.0 + title: |- + FDR Based Multiple Testing Procedures with Adaptation for + Discrete Tests + maintainer: Florian Junge + description: |- + Implementations of the multiple testing procedures for discrete + tests described in the paper Döhler, Durand and Roquain (2018) "New FDR + bounds for discrete and heterogeneous tests" . The + main procedures of the paper (HSU and HSD), their adaptive counterparts + (AHSU and AHSD), and the HBR variant are available and are coded to take as + input the results of a test procedure from package 'DiscreteTests', or a set + of observed p-values and their discrete support under their nulls. A + shortcut function to obtain such p-values and supports is also provided, + along with a wrapper allowing to apply discrete procedures directly to data. + date_publication: '2024-12-14' + bug_reports: https://github.com/DISOhda/DiscreteFDR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteFDR + url_git: https://github.com/DISOhda/DiscreteFDR +discretefit: + version: 0.1.2 + title: Simulated Goodness-of-Fit Tests for Discrete Distributions + maintainer: Josh McCormick + description: |- + Implements fast Monte Carlo simulations for + goodness-of-fit (GOF) tests for discrete distributions. This + includes tests based on the Chi-squared statistic, the + log-likelihood-ratio (G^2) statistic, the Freeman-Tukey + (Hellinger-distance) statistic, the Kolmogorov-Smirnov + statistic, the Cramer-von Mises statistic as described in + Choulakian, Lockhart and Stephens (1994) , + and the root-mean-square statistic, see Perkins, + Tygert, and Ward (2011) . + date_publication: '2022-01-25' + bug_reports: https://github.com/josh-mc/discretefit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=discretefit + url_git: https://github.com/josh-mc/discretefit +DiscreteFWER: + version: 1.0.0 + title: |- + FWER-Based Multiple Testing Procedures with Adaptation for + Discrete Tests + maintainer: Florian Junge + description: |- + Implementations of several multiple testing procedures that control + the family-wise error rate (FWER) designed specifically for discrete tests. + Included are discrete adaptations of the Bonferroni, Holm, Hochberg and + Šidák procedures as described in the papers Döhler (2010) "Validation of + credit default probabilities using multiple-testing procedures" + and Zhu & Guo (2019) "Family-Wise Error Rate + Controlling Procedures for Discrete Data" + . The main procedures of this package + take as input the results of a test procedure from package 'DiscreteTests' + or a set of observed p-values and their discrete support under their nulls. + A shortcut function to apply discrete procedures directly to data is also + provided. + date_publication: '2024-11-27' + bug_reports: https://github.com/DISOhda/DiscreteFWER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteFWER + url_git: https://github.com/DISOhda/DiscreteFWER +DiscreteGapStatistic: + version: 1.0.0 + title: An Extension of the Gap Statistic for Ordinal/Categorical Data + maintainer: Eduardo Cortes + description: The gap statistic approach is extended to estimate the number of clusters + for categorical response format data. This approach and accompanying software + is designed to be used with the output of any clustering algorithm and with distances + specifically designed for categorical (i.e. multiple choice) or ordinal survey + response data. + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteGapStatistic + url_git: https://github.com/ecortesgomez/DiscreteGapStatistic +DiscreteInverseWeibull: + version: 1.0.2 + title: Discrete Inverse Weibull Distribution + maintainer: Alessandro Barbiero + description: Probability mass function, distribution function, quantile function, + random generation and parameter estimation for the discrete inverse Weibull distribution. + date_publication: '2016-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteInverseWeibull + url_git: '' +DiscreteLaplace: + version: 1.1.1 + title: Discrete Laplace Distributions + maintainer: Alessandro Barbiero + description: Probability mass function, distribution function, quantile function, + random generation and estimation for the skew discrete Laplace distributions. + date_publication: '2016-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteLaplace + url_git: '' +DiscreteQvalue: + version: '1.1' + title: Improved q-Values for Discrete Uniform and Homogeneous Tests + maintainer: Marta Cousido Rocha + description: We consider a multiple testing procedure used in many modern applications + which is the q-value method proposed by Storey and Tibshirani (2003), . + The q-value method is based on the false discovery rate (FDR), hence versions + of the q-value method can be defined depending on which estimator of the proportion + of true null hypotheses, p0, is plugged in the FDR estimator. We implement the + q-value method based on two classical pi0 estimators, and furthermore, we propose + and implement three versions of the q-value method for homogeneous discrete uniform + P-values based on pi0 estimators which take into account the discrete distribution + of the P-values. + date_publication: '2020-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteQvalue + url_git: '' +DiscreteTests: + version: 0.2.1 + title: |- + Vectorised Computation of P-Values and Their Supports for + Several Discrete Statistical Tests + maintainer: Florian Junge + description: |- + Provides vectorised functions for computing p-values of various + common discrete statistical tests, as described e.g. in Agresti (2002) + , including their distributions. Exact and + approximate computation methods are provided. For exact p-values, several + procedures of determining two-sided p-values are included, which are + outlined in more detail in Hirji (2006) . + date_publication: '2024-10-27' + bug_reports: https://github.com/DISOhda/DiscreteTests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteTests + url_git: https://github.com/DISOhda/DiscreteTests +DiscreteWeibull: + version: '1.1' + title: Discrete Weibull Distributions (Type 1 and 3) + maintainer: Alessandro Barbiero + description: Probability mass function, distribution function, quantile function, + random generation and parameter estimation for the type I and III discrete Weibull + distributions. + date_publication: '2015-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiscreteWeibull + url_git: '' +discretization: + version: 1.0-1.1 + title: Data Preprocessing, Discretization for Classification + maintainer: HyunJi Kim + description: |- + A collection of supervised discretization + algorithms. It can also be grouped in terms of top-down or + bottom-up, implementing the discretization algorithms. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discretization + url_git: '' +discrim: + version: 1.0.1 + title: Model Wrappers for Discriminant Analysis + maintainer: Emil Hvitfeldt + description: |- + Bindings for additional classification models for use with + the 'parsnip' package. Models include flavors of discriminant + analysis, such as linear (Fisher (1936) + ), regularized (Friedman + (1989) ), and flexible (Hastie, + Tibshirani, and Buja (1994) ), as + well as naive Bayes classifiers (Hand and Yu (2007) + ). + date_publication: '2023-03-08' + bug_reports: https://github.com/tidymodels/discrim/issues + url: https://discrim.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=discrim + url_git: https://github.com/tidymodels/discrim +discrtr: + version: 0.0.1 + title: |- + A Companion Package for the Book "Discrete Choice Analysis with + 'R'" + maintainer: Antonio Paez + description: |- + Templates and data files to support "Discrete Choice Analysis with R", + Páez, A. and Boisjoly, G. (2023) . + date_publication: '2023-02-24' + bug_reports: https://github.com/paezha/discrtr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=discrtr + url_git: https://github.com/paezha/discrtr +discSurv: + version: 2.0.0 + title: Discrete Time Survival Analysis + maintainer: Thomas Welchowski + description: |- + Provides data transformations, estimation utilities, + predictive evaluation measures and simulation functions for discrete time + survival analysis. + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discSurv + url_git: '' +discursive: + version: 0.1.1 + title: |- + Measuring Discursive Sophistication in Open-Ended Survey + Responses + maintainer: Patrick Kraft + description: 'A simple approach to measure political sophistication based on open-ended + survey responses. Discursive sophistication captures the complexity of individual + attitude expression by quantifying its relative size, range, and constraint. For + more information on the measurement approach see: Kraft, Patrick W. 2023. "Women + Also Know Stuff: Challenging the Gender Gap in Political Sophistication." American + Political Science Review (forthcoming).' + date_publication: '2023-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=discursive + url_git: '' +disdat: + version: 1.0-1 + title: Data for Comparing Species Distribution Modeling Methods + maintainer: Roozbeh Valavi + description: Easy access to species distribution data for 6 regions in the world, + for a total of 226 anonymised species. These data are described and made available + by Elith et al (2020) to compare species distribution + modelling methods. + date_publication: '2023-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disdat + url_git: '' +diseasemapping: + version: 2.0.6 + title: Modelling Spatial Variation in Disease Risk for Areal Data + maintainer: Patrick Brown + description: |- + Formatting of population and case data, calculation of Standardized + Incidence Ratios, and fitting the BYM model using 'INLA'. For details see Brown (2015) . + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diseasemapping + url_git: '' +diseasystore: + version: 0.3.1 + title: Feature Stores for the 'diseasy' Framework + maintainer: Rasmus Skytte Randløv + description: |- + Simple feature stores and tools for creating personalised feature stores. + 'diseasystore' powers feature stores which can automatically link and aggregate features to a given stratification + level. These feature stores are automatically time-versioned (powered by the 'SCDB' package) and allows you to easily + and dynamically compute features as part of your continuous integration. + date_publication: '2025-02-28' + bug_reports: https://github.com/ssi-dk/diseasystore/issues + url: https://ssi-dk.github.io/diseasystore/ + url_cran: https://CRAN.R-project.org/package=diseasystore + url_git: https://github.com/ssi-dk/diseasystore +DisHet: + version: 1.0.0 + title: |- + Estimate the Gene Expression Levels and Component Proportions of + the Normal, Stroma (Immune) and Tumor Components of Bulk Tumor + Samples + maintainer: Tao Wang + description: Model cell type heterogeneity of bulk renal cell carcinoma. The observed + gene expression in bulk tumor sample is modeled by a log-normal distribution with + the location parameter structured as a linear combination of the component-specific + gene expressions. + date_publication: '2018-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DisHet + url_git: '' +DisimForMixed: + version: '0.2' + title: Calculate Dissimilarity Matrix for Dataset with Mixed Attributes + maintainer: Hasanthi A. Pathberiya + description: Implement the methods proposed by Ahmad & Dey (2007) + in calculating the dissimilarity matrix at the presence of mixed attributes. This + Package includes functions to discretize quantitative variables, calculate conditional + probability for each pair of attribute values, distance between every pair of + attribute values, significance of attributes, calculate dissimilarity between + each pair of objects. + date_publication: '2016-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DisimForMixed + url_git: '' +DisImpact: + version: 0.0.21 + title: |- + Calculates Disproportionate Impact When Binary Success Data are + Disaggregated by Subgroups + maintainer: Vinh Nguyen + description: |- + Implements methods for calculating disproportionate impact: the percentage point gap, proportionality index, and the 80% index. + California Community Colleges Chancellor's Office (2017). Percentage Point Gap Method. . + California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans. . + date_publication: '2022-10-10' + bug_reports: https://github.com/vinhdizzo/DisImpact/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DisImpact + url_git: https://github.com/vinhdizzo/DisImpact +disk.frame: + version: 0.8.3 + title: Larger-than-RAM Disk-Based Data Manipulation Framework + maintainer: Dai ZJ + description: |- + A disk-based data manipulation tool for working with + large-than-RAM datasets. Aims to lower the barrier-to-entry for + manipulating large datasets by adhering closely to popular and + familiar data manipulation paradigms like 'dplyr' verbs and + 'data.table' syntax. + date_publication: '2023-08-24' + bug_reports: https://github.com/DiskFrame/disk.frame/issues + url: https://diskframe.com + url_cran: https://CRAN.R-project.org/package=disk.frame + url_git: '' +dismo: + version: 1.3-16 + title: Species Distribution Modeling + maintainer: Robert J. Hijmans + description: Methods for species distribution modeling, that is, predicting the + environmental similarity of any site to that of the locations of known occurrences + of a species. + date_publication: '2024-11-25' + bug_reports: https://github.com/rspatial/dismo/issues/ + url: https://rspatial.org/raster/sdm/ + url_cran: https://CRAN.R-project.org/package=dismo + url_git: '' +disordR: + version: 0.9-8-4 + title: Non-Ordered Vectors + maintainer: Robin K. S. Hankin + description: |- + Functionality for manipulating values of associative + maps. The package is a dependency for mvp-type + packages that use the STL map class: it traps + plausible idiom that is ill-defined (implementation-specific) and + returns an informative error, rather than returning a possibly + incorrect result. To cite the package in publications please use + Hankin (2022) . + date_publication: '2024-11-13' + bug_reports: https://github.com/RobinHankin/disordR/issues + url: https://robinhankin.github.io/disordR/ + url_cran: https://CRAN.R-project.org/package=disordR + url_git: https://github.com/RobinHankin/disordR +disparityfilter: + version: 2.2.3 + title: Disparity Filter Algorithm for Weighted Networks + maintainer: Alessandro Bessi + description: |- + The disparity filter algorithm is a network reduction technique to + identify the 'backbone' structure of a weighted network without destroying + its multi-scale nature. The algorithm is documented in M. Angeles Serrano, + Marian Boguna and Alessandro Vespignani in "Extracting the multiscale + backbone of complex weighted networks", Proceedings of the National Academy + of Sciences 106 (16), 2009. This implementation of the algorithm supports + both directed and undirected networks. + date_publication: '2016-04-19' + bug_reports: https://github.com/alessandrobessi/disparityfilter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=disparityfilter + url_git: https://github.com/alessandrobessi/disparityfilter +dispeRse: + version: '1.1' + title: Simulation of Demic Diffusion with Environmental Constraints + maintainer: Jonas Gregorio de Souza + description: |- + Simulates demic diffusion building on models previously developed + for the expansion of Neolithic and other food-producing economies during + the Holocene (Fort et al. (2012) , Souza et al. + (2021) ). Growth and emigration are modelled as + density-dependent processes using logistic growth and an asymptotic threshold + model. Environmental and terrain layers, which can change over time, affect + carrying capacity, growth and mobility. Multiple centres of origin with + their respective starting times can be specified. + date_publication: '2023-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dispeRse + url_git: '' +displease: + version: 1.0.0 + title: Numeric and Color Sequences with Non-Linear Interpolation + maintainer: Mike Cheng + description: |- + When visualising changes between two values over time, a strict + linear interpolation can look jarring and unnatural. By applying a non-linear + easing to the transition, the motion between values can appear smoother and + more natural. This package includes functions for applying such non-linear + easings to colors and numeric values, and is useful where smooth animated movement + and transitions are desired. + date_publication: '2024-12-16' + bug_reports: https://github.com/coolbutuseless/displease/issues + url: '' + url_cran: https://CRAN.R-project.org/package=displease + url_git: https://github.com/coolbutuseless/displease +dispmod: + version: '1.2' + title: Modelling Dispersion in GLM + maintainer: Luca Scrucca + description: Functions for estimating Gaussian dispersion regression models (Aitkin, + 1987 ), overdispersed binomial logit models (Williams, 1987 + ), and overdispersed Poisson log-linear models (Breslow, + 1984 ), using a quasi-likelihood approach. + date_publication: '2018-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dispmod + url_git: '' +disposables: + version: 1.0.3 + title: Create Disposable R Packages for Testing + maintainer: Gábor Csárdi + description: |- + Create disposable R packages for testing. + You can create, install and load multiple R packages with a single + function call, and then unload, uninstall and destroy them with another + function call. This is handy when testing how some R code or an R package + behaves with respect to other packages. + date_publication: '2017-03-20' + bug_reports: https://github.com/gaborcsardi/disposables/issues + url: '' + url_cran: https://CRAN.R-project.org/package=disposables + url_git: https://github.com/gaborcsardi/disposables +dispositionEffect: + version: 1.0.1 + title: Analysis of Disposition Effect on Financial Portfolios + maintainer: Marco Zanotti + description: |- + Evaluate the presence of disposition effect and others irrational + investor's behaviors based solely on investor's transactions and financial + market data. Experimental data can also be used to perform the analysis. + Four different methodologies are implemented to account for the different + nature of human behaviors on financial markets. + Novel analyses such as portfolio driven and time series disposition effect + are also allowed. + date_publication: '2022-05-30' + bug_reports: https://github.com/marcozanotti/dispositionEffect/issues + url: https://marcozanotti.github.io/dispositionEffect/ + url_cran: https://CRAN.R-project.org/package=dispositionEffect + url_git: https://github.com/marcozanotti/dispositionEffect +dispRity: + version: '1.9' + title: Measuring Disparity + maintainer: Thomas Guillerme + description: A modular package for measuring disparity (multidimensional space occupancy). + Disparity can be calculated from any matrix defining a multidimensional space. + The package provides a set of implemented metrics to measure properties of the + space and allows users to provide and test their own metrics. The package also + provides functions for looking at disparity in a serial way (e.g. disparity through + time) or per groups as well as visualising the results. Finally, this package + provides several statistical tests for disparity analysis. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dispRity + url_git: https://github.com/TGuillerme/dispRity +disprofas: + version: 0.2.0 + title: Non-Parametric Dissolution Profile Analysis + maintainer: Pius Dahinden + description: |- + Similarity of dissolution profiles is assessed using the + similarity factor f2 according to the EMA guideline (European + Medicines Agency 2010) "On the investigation of bioequivalence". + Dissolution profiles are regarded as similar if the f2 value is + between 50 and 100. For the applicability of the similarity factor f2, + the variability between profiles needs to be within certain limits. + Often, this constraint is violated. One possibility in this situation + is to resample the measured profiles in order to obtain a bootstrap + estimate of f2 (Shah et al. (1998) ). + Other alternatives are the model-independent non-parametric + multivariate confidence region (MCR) procedure (Tsong et al. (1996) + ) or the T2-test for equivalence + procedure (Hoffelder (2016) + ). Functions for + estimation of f1, f2, bootstrap f2, MCR / T2-test for equivalence + procedure are implemented. + date_publication: '2024-06-10' + bug_reports: https://github.com/piusdahinden/disprofas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=disprofas + url_git: https://github.com/piusdahinden/disprofas +disprose: + version: 0.1.6 + title: Discriminating Probes Selection + maintainer: Elena Filatova + description: 'Set of tools for molecular probes selection and design of a microarray, + e.g. the assessment of physical and chemical properties, blast performance, selection + according to sensitivity and selectivity. Methods used in package are described + in: Lorenz R., Stephan H.B., Höner zu Siederdissen C. et al. (2011) ; + Camacho C., Coulouris G., Avagyan V. et al. (2009) .' + date_publication: '2022-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disprose + url_git: '' +dissCqN: + version: 0.1.0 + title: Multiple Assemblage Dissimilarity for Orders q = 0-N + maintainer: Mark Murphy + description: |- + Calculate multiple or pairwise dissimilarity for orders q = 0-N + (CqN; Chao et al. 2008 ) for a set of species assemblages or + interaction networks. + date_publication: '2021-10-14' + bug_reports: https://github.com/murphymv/dissCqN/issues + url: https://murphymv.github.io/dissCqN/ + url_cran: https://CRAN.R-project.org/package=dissCqN + url_git: https://github.com/murphymv/dissCqN +dissever: + version: 0.2-3 + title: Spatial Downscaling using the Dissever Algorithm + maintainer: Pierre Roudier + description: |- + Spatial downscaling of coarse grid mapping to fine grid + mapping using predictive covariates and a model fitted using the 'caret' + package. The original dissever algorithm was published by Malone et al. + (2012) , and extended by Roudier et al. + (2017) . + date_publication: '2018-04-20' + bug_reports: https://github.com/pierreroudier/dissever/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dissever + url_git: https://github.com/pierreroudier/dissever +DiSSMod: + version: 1.0.0 + title: Fitting Sample Selection Models for Discrete Response Variables + maintainer: Sang Kyu Lee + description: |- + Tools to fit sample selection models in case of discrete response + variables, through a parametric formulation which represents a natural + extension of the well-known Heckman selection model are provided in the + package. The response variable can be of Bernoulli, Poisson or Negative + Binomial type. The sample selection mechanism allows to choose among a + Normal, Logistic or Gumbel distribution. + date_publication: '2019-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiSSMod + url_git: '' +Distance: + version: 2.0.0 + title: Distance Sampling Detection Function and Abundance Estimation + maintainer: Laura Marshall + description: |- + A simple way of fitting detection functions to distance sampling + data for both line and point transects. Adjustment term selection, left and + right truncation as well as monotonicity constraints and binning are + supported. Abundance and density estimates can also be calculated (via a + Horvitz-Thompson-like estimator) if survey area information is provided. See + Miller et al. (2019) for more information on + methods and for example analyses. + date_publication: '2024-10-24' + bug_reports: https://github.com/DistanceDevelopment/Distance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Distance + url_git: https://github.com/DistanceDevelopment/Distance/ +distanceHD: + version: '1.2' + title: Distance Metrics for High-Dimensional Clustering + maintainer: Jung Ae Lee + description: We provide three distance metrics for measuring the separation between + two clusters in high-dimensional spaces. The first metric is the centroid distance, + which calculates the Euclidean distance between the centers of the two groups. + The second is a ridge Mahalanobis distance, which incorporates a ridge correction + constant, alpha, to ensure that the covariance matrix is invertible. The third + metric is the maximal data piling distance, which computes the orthogonal distance + between the affine spaces spanned by each class. These three distances are asymptotically + interconnected and are applicable in tasks such as discrimination, clustering, + and outlier detection in high-dimensional settings. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distanceHD + url_git: '' +distances: + version: 0.1.11 + title: Tools for Distance Metrics + maintainer: Fredrik Savje + description: Provides tools for constructing, manipulating and using distance metrics. + date_publication: '2024-07-31' + bug_reports: https://github.com/fsavje/distances/issues + url: '' + url_cran: https://CRAN.R-project.org/package=distances + url_git: https://github.com/fsavje/distances +distanceto: + version: 0.0.3 + title: Calculate Distance to Features + maintainer: Alec L. Robitaille + description: |- + Calculates distances from point locations to features. + The usual approach for eg. resource selection function analyses is to + generate a complete distance to features surface then sample it with your + observed and random points. Since these raster based approaches can be + pretty costly with large areas, and often lead to memory issues in R, + the distanceto package opts to compute these distances using + efficient, vector based approaches. As a helper, there's a decidedly + low-res raster based approach for visually inspecting your region's + distance surface. But the workhorse is distance_to. + date_publication: '2023-06-01' + bug_reports: https://github.com/robitalec/distance-to/issues + url: https://robitalec.github.io/distance-to/ + url_cran: https://CRAN.R-project.org/package=distanceto + url_git: https://github.com/robitalec/distance-to +distantia: + version: 2.0.2 + title: |- + Advanced Toolset for Efficient Time Series Dissimilarity + Analysis + maintainer: Blas M. Benito + description: Fast C++ implementation of Dynamic Time Warping for time series dissimilarity + analysis, with applications in environmental monitoring and sensor data analysis, + climate science, signal processing and pattern recognition, and financial data + analysis. Built upon the ideas presented in Benito and Birks (2020) , + provides tools for analyzing time series of varying lengths and structures, including + irregular multivariate time series. Key features include individual variable contribution + analysis, restricted permutation tests for statistical significance, and imputation + of missing data via GAMs. Additionally, the package provides an ample set of tools + to prepare and manage time series data. + date_publication: '2025-02-01' + bug_reports: https://github.com/BlasBenito/distantia/issues + url: https://blasbenito.github.io/distantia/ + url_cran: https://CRAN.R-project.org/package=distantia + url_git: '' +DistatisR: + version: 1.1.1 + title: DiSTATIS Three Way Metric Multidimensional Scaling + maintainer: Herve Abdi + description: Implement DiSTATIS and CovSTATIS (three-way multidimensional scaling). DiSTATIS + and CovSTATIS are used to analyze multiple distance/covariance matrices collected + on the same set of observations. These methods are based on Abdi, H., Williams, + L.J., Valentin, D., & Bennani-Dosse, M. (2012) . + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DistatisR + url_git: '' +distcomp: + version: 1.3-3 + title: Computations over Distributed Data without Aggregation + maintainer: Balasubramanian Narasimhan + description: |- + Implementing algorithms and fitting models when sites (possibly remote) share + computation summaries rather than actual data over HTTP with a master R process (using + 'opencpu', for example). A stratified Cox model and a singular value decomposition are + provided. The former makes direct use of code from the R 'survival' package. (That is, + the underlying Cox model code is derived from that in the R 'survival' package.) + Sites may provide data via several means: CSV files, Redcap API, etc. An extensible + design allows for new methods to be added in the future and includes facilities + for local prototyping and testing. Web applications are provided (via 'shiny') for + the implemented methods to help in designing and deploying the computations. + date_publication: '2022-09-01' + bug_reports: '' + url: http://dx.doi.org/10.18637/jss.v077.i13 + url_cran: https://CRAN.R-project.org/package=distcomp + url_git: '' +distcrete: + version: 1.0.3 + title: Discrete Distribution Approximations + maintainer: Steph Locke + description: |- + Creates discretised versions of continuous + distribution functions by mapping continuous values + to an underlying discrete grid, based on a (uniform) + frequency of discretisation, a valid discretisation + point, and an integration range. For a review of + discretisation methods, see + Chakraborty (2015) . + date_publication: '2017-11-23' + bug_reports: https://github.com/reconhub/distcrete/issues + url: '' + url_cran: https://CRAN.R-project.org/package=distcrete + url_git: https://github.com/reconhub/distcrete +distdichoR: + version: 0.1-1 + title: |- + Distributional Method for the Dichotomisation of Continuous + Outcomes + maintainer: Odile Sauzet + description: |- + Contains a range of functions covering the present + development of the distributional method for the dichotomisation of continuous outcomes. + The method provides estimates with standard error of a comparison of proportions + (difference, odds ratio and risk ratio) derived, with similar precision, from a comparison of means. + See the URL below or for more information. + date_publication: '2018-09-24' + bug_reports: '' + url: https://arxiv.org/abs/1809.03279 + url_cran: https://CRAN.R-project.org/package=distdichoR + url_git: '' +distfree.cr: + version: 1.5.1 + title: Distribution-Free Confidence Region + maintainer: Zhiqiu Hu + description: Constructs confidence regions without the need to know the sampling + distribution of bivariate data. The method was proposed by Zhiqiu Hu & Rong-cai + Yang (2013) . + date_publication: '2018-06-15' + bug_reports: '' + url: http://statgen.ualberta.ca + url_cran: https://CRAN.R-project.org/package=distfree.cr + url_git: '' +distfreereg: + version: 1.0.1 + title: Distribution-Free Goodness-of-Fit Testing for Regression + maintainer: Jesse Miller + description: |- + Implements distribution-free goodness-of-fit regression testing for + the mean structure of parametric models introduced in Khmaladze (2021) + . + date_publication: '2024-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distfreereg + url_git: '' +distfromq: + version: 1.0.4 + title: Reconstruct a Distribution from a Collection of Quantiles + maintainer: Evan Ray + description: |- + Given a set of predictive quantiles from a distribution, + estimate the distribution and create `d`, `p`, `q`, and `r` functions + to evaluate its density function, distribution function, and quantile + function, and generate random samples. On the interior of the provided + quantiles, an interpolation method such as a monotonic cubic spline is + used; the tails are approximated by a location-scale family. + date_publication: '2024-09-13' + bug_reports: '' + url: http://reichlab.io/distfromq/ + url_cran: https://CRAN.R-project.org/package=distfromq + url_git: '' +distill: + version: '1.6' + title: '''R Markdown'' Format for Scientific and Technical Writing' + maintainer: Christophe Dervieux + description: |- + Scientific and technical article format for the web. + 'Distill' articles feature attractive, reader-friendly typography, + flexible layout options for visualizations, and full support for + footnotes and citations. + date_publication: '2023-10-06' + bug_reports: https://github.com/rstudio/distill/issues + url: https://pkgs.rstudio.com/distill + url_cran: https://CRAN.R-project.org/package=distill + url_git: https://github.com/rstudio/distill +distillery: + version: 1.2-2 + title: |- + Method Functions for Confidence Intervals and to Distill + Information from an Object + maintainer: Eric Gilleland + description: 'Some very simple method functions for confidence interval calculation, + bootstrap resampling aimed at atmospheric science applications, and to distill + pertinent information from a potentially complex object; primarily used in common + with packages extRemes and SpatialVx. To reference this package and for a tutorial + on the bootstrap functions, please see Gilleland (2020) + and Gilleland (2020) .' + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distillery + url_git: '' +distillML: + version: 0.1.0.13 + title: |- + Model Distillation and Interpretability Methods for Machine + Learning Models + maintainer: Theo Saarinen + description: |- + Provides several methods for model distillation and interpretability + for general black box machine learning models and treatment effect estimation + methods. For details on the algorithms implemented, see + Brian Cho, Theo F. Saarinen, Jasjeet S. Sekhon, Simon Walter. + date_publication: '2023-03-25' + bug_reports: https://github.com/forestry-labs/distillML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=distillML + url_git: https://github.com/forestry-labs/distillML +distinctiveness: + version: 1.0.1 + title: Distinctiveness Centrality + maintainer: Andrea Fronzetti Colladon + description: |- + Calculates Distinctiveness Centrality in social networks. + For formulas and descriptions, see Fronzetti Colladon and Naldi (2020) . + date_publication: '2023-10-15' + bug_reports: '' + url: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233276 + url_cran: https://CRAN.R-project.org/package=distinctiveness + url_git: https://github.com/iandreafc/distinctiveness-R +disto: + version: 0.2.0 + title: |- + Unified Interface to Distance, Dissimilarity, Similarity + Matrices + maintainer: KS Srikanth + description: Provides a high level API to interface over sources storing distance, + dissimilarity, similarity matrices with matrix style extraction, replacement and + other utilities. Currently, in-memory dist object backend is supported. + date_publication: '2018-08-02' + bug_reports: https://github.com/talegari/disto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=disto + url_git: https://github.com/talegari/disto +distops: + version: 0.1.0 + title: Usual Operations for Distance Matrices in R + maintainer: Aymeric Stamm + description: |- + It provides the subset operator for dist objects and a function to + compute medoid(s) that are fully parallelized leveraging the 'RcppParallel' + package. It also provides functions for package developers to easily + implement their own parallelized dist() function using a custom 'C++'-based + distance function. + date_publication: '2024-01-23' + bug_reports: https://github.com/lmjl-alea/distops/issues + url: https://lmjl-alea.github.io/distops/ + url_cran: https://CRAN.R-project.org/package=distops + url_git: https://github.com/lmjl-alea/distops +distory: + version: 1.4.5 + title: Distance Between Phylogenetic Histories + maintainer: Emmanuel Paradis + description: |- + Geodesic distance between phylogenetic trees and + associated functions. The theoretical background of 'distory' + is published in Billera et al. (2001) "Geometry of the space of + phylogenetic trees." . + date_publication: '2024-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distory + url_git: '' +DistPlotter: + version: 0.0.2 + title: |- + A Graphical User Interface for Plotting Common Univariate + Distributions + maintainer: Christopher Casement + description: |- + Package including an interactive Shiny application for plotting + common univariate distributions. + date_publication: '2022-03-10' + bug_reports: https://github.com/ccasement/DistPlotter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DistPlotter + url_git: https://github.com/ccasement/DistPlotter +distr: + version: 2.9.7 + title: Object Oriented Implementation of Distributions + maintainer: Peter Ruckdeschel + description: S4-classes and methods for distributions. + date_publication: '2025-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distr + url_git: http://distr.r-forge.r-project.org/ +distrDoc: + version: 2.8.5 + title: Documentation for 'distr' Family of R Packages + maintainer: Peter Ruckdeschel + description: |- + Provides documentation in form of a common vignette to packages 'distr', + 'distrEx', 'distrMod', 'distrSim', 'distrTEst', 'distrTeach', and 'distrEllipse'. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrDoc + url_git: http://distr.r-forge.r-project.org/ +distreg.vis: + version: 1.7.5 + title: |- + Framework for the Visualization of Distributional Regression + Models + maintainer: Stanislaus Stadlmann + description: Functions for visualizing distributional regression models fitted using + the 'gamlss', 'bamlss' or 'betareg' R package. The core of the package consists + of a 'shiny' application, where the model results can be interactively explored + and visualized. + date_publication: '2023-10-27' + bug_reports: https://github.com/Stan125/distreg.vis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=distreg.vis + url_git: https://github.com/Stan125/distreg.vis +distrEllipse: + version: 2.8.4 + title: S4 Classes for Elliptically Contoured Distributions + maintainer: Peter Ruckdeschel + description: |- + Distribution (S4-)classes for elliptically contoured distributions (based on + package 'distr'). + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrEllipse + url_git: http://distr.r-forge.r-project.org/ +distrEx: + version: 2.9.6 + title: Extensions of Package 'distr' + maintainer: Matthias Kohl + description: Extends package 'distr' by functionals, distances, and conditional + distributions. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrEx + url_git: http://distr.r-forge.r-project.org/ +DISTRIB: + version: '1.0' + title: |- + Four Essential Functions for Statistical Distributions Analysis: + A New Functional Approach + maintainer: Abbas Parchami + description: A different way for calculating pdf/pmf, cdf, quantile and random data + such that the user is able to consider the name of related distribution as an + argument and so easily can changed by a changing argument by user. It must be + mentioned that the core and computation base of package 'DISTRIB' is package 'stats'. + Although similar functions are introduced previously in package 'stats', but the + package 'DISTRIB' has some special applications in some special computational + programs. + date_publication: '2016-12-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DISTRIB + url_git: '' +Distributacalcul: + version: 0.4.0 + title: Probability Distribution Functions + maintainer: Alec James van Rassel + description: |- + Calculates expected values, variance, different moments (kth + moment, truncated mean), stop-loss, mean excess loss, Value-at-Risk (VaR) + and Tail Value-at-Risk (TVaR) as well as some density and cumulative + (survival) functions of continuous, discrete and compound distributions. + This package also includes a visual 'Shiny' component to enable students + to visualize distributions and understand the impact of their parameters. + This package is intended to expand the 'stats' package so as + to enable students to develop an intuition for probability. + date_publication: '2024-01-10' + bug_reports: https://github.com/alec42/Distributacalcul_Package/issues + url: https://alec42.github.io/Distributacalcul_Package/ + url_cran: https://CRAN.R-project.org/package=Distributacalcul + url_git: '' +distributional: + version: 0.5.0 + title: Vectorised Probability Distributions + maintainer: Mitchell O'Hara-Wild + description: |- + Vectorised distribution objects with tools for manipulating, + visualising, and using probability distributions. Designed to allow model + prediction outputs to return distributions rather than their parameters, + allowing users to directly interact with predictive distributions in a + data-oriented workflow. In addition to providing generic replacements for + p/d/q/r functions, other useful statistics can be computed including means, + variances, intervals, and highest density regions. + date_publication: '2024-09-17' + bug_reports: https://github.com/mitchelloharawild/distributional/issues + url: https://pkg.mitchelloharawild.com/distributional/ + url_cran: https://CRAN.R-project.org/package=distributional + url_git: https://github.com/mitchelloharawild/distributional +DistributionIV: + version: 0.1.0 + title: Distributional Instrumental Variable (DIV) Model + maintainer: Anastasiia Holovchak + description: |- + Distributional instrumental variable (DIV) model + for estimation of the interventional distribution of the outcome Y under a + do-intervention on the treatment X. Instruments, predictors and targets can + be univariate or multivariate. Functionality includes estimation of the (conditional) + interventional mean and quantiles, as well as sampling from the fitted (conditional) + interventional distribution. + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DistributionIV + url_git: '' +DistributionOptimization: + version: 1.2.6 + title: Distribution Optimization + maintainer: Florian Lerch + description: 'Fits Gaussian Mixtures by applying evolution. As fitness function + a mixture of the chi square test for distributions and a novel measure for approximating + the common area under curves between multiple Gaussians is used. The package presents + an alternative to the commonly used Likelihood Maximization as is used in Expectation + Maximization. The algorithm and applications of this package are published under: + Lerch, F., Ultsch, A., Lotsch, J. (2020) . The + evolution is based on the ''GA'' package: Scrucca, L. (2013) + while the Gaussian Mixture Logic stems from ''AdaptGauss'': Ultsch, A, et al. + (2015) .' + date_publication: '2020-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DistributionOptimization + url_git: '' +distributions3: + version: 0.2.2 + title: Probability Distributions as S3 Objects + maintainer: Alex Hayes + description: |- + Tools to create and manipulate probability distributions + using S3. Generics pdf(), cdf(), quantile(), and random() provide + replacements for base R's d/p/q/r style functions. Functions and + arguments have been named carefully to minimize confusion for students + in intro stats courses. The documentation for each distribution + contains detailed mathematical notes. + date_publication: '2024-09-16' + bug_reports: https://github.com/alexpghayes/distributions3/issues + url: https://alexpghayes.github.io/distributions3/ + url_cran: https://CRAN.R-project.org/package=distributions3 + url_git: https://github.com/alexpghayes/distributions3 +distributionsrd: + version: 0.0.6 + title: Distribution Fitting and Evaluation + maintainer: Ruben Dewitte + description: A library of density, distribution function, quantile function, (bounded) + raw moments and random generation for a collection of distributions relevant for + the firm size literature. Additionally, the package contains tools to fit these + distributions using maximum likelihood and evaluate these distributions based + on (i) log-likelihood ratio and (ii) deviations between the empirical and parametrically + implied moments of the distributions. We add flexibility by allowing the considered + distributions to be combined into piecewise composite or finite mixture distributions, + as well as to be used when truncated. See Dewitte (2020) + for a description and application of methods available in this package. + date_publication: '2020-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distributionsrd + url_git: '' +DistributionTest: + version: '1.1' + title: Powerful Goodness-of-Fit Tests Based on the Likelihood Ratio + maintainer: Ning Cui + description: Provides new types of omnibus tests which are generally much more powerful + than traditional tests (including the Kolmogorov-Smirnov, Cramer-von Mises and + Anderson-Darling tests),see Zhang (2002) . + date_publication: '2020-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DistributionTest + url_git: '' +DistributionUtils: + version: 0.6-1 + title: Distribution Utilities + maintainer: David Scott + description: |- + Utilities are provided which are of use in the + packages I have developed for dealing with + distributions. Currently these packages are GeneralizedHyperbolic, + VarianceGamma, and SkewHyperbolic and NormalLaplace. Each of these + packages requires DistributionUtils. Functionality includes sample + skewness and kurtosis, log-histogram, tail plots, moments by + integration, changing the point about which a moment is + calculated, functions for testing distributions using inversion + tests and the Massart inequality. Also includes an implementation + of the incomplete Bessel K function. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DistributionUtils + url_git: '' +distrMod: + version: 2.9.7 + title: Object Oriented Implementation of Probability Models + maintainer: Peter Ruckdeschel + description: |- + Implements S4 classes for probability models based on packages 'distr' and + 'distrEx'. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrMod + url_git: http://distr.r-forge.r-project.org/ +distro: + version: 0.1.0 + title: Linux Distribution Properties + maintainer: Neal Richardson + description: |- + In order to provide unified access to Linux distribution details + in R, this package wraps the various files and commands that may exist + on a system. It is similar in spirit to the 'lsb_release' command and the + 'Python' package of the same name. + date_publication: '2020-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distro + url_git: '' +distrom: + version: 1.0.1 + title: Distributed Multinomial Regression + maintainer: Nelson Rayl + description: 'Fast distributed/parallel estimation for multinomial logistic regression + via Poisson factorization and the ''gamlr'' package. For details see: Taddy (2015, + AoAS), Distributed Multinomial Regression, .' + date_publication: '2022-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrom + url_git: https://github.com/TaddyLab/distrom +distrr: + version: 0.0.6 + title: Estimate and Manage Empirical Distributions + maintainer: Sandro Petrillo Burri + description: |- + Tools to estimate and manage empirical distributions, + which should work with survey data. One of the main features is the + possibility to create data cubes of estimated statistics, that include + all the combinations of the variables of interest (see for example functions + dcc5() and dcc6()). + date_publication: '2020-07-14' + bug_reports: '' + url: https://gibonet.github.io/distrr + url_cran: https://CRAN.R-project.org/package=distrr + url_git: https://github.com/gibonet/distrr +distrRmetrics: + version: 2.8.3 + title: Distribution Classes for Distributions from Rmetrics + maintainer: Peter Ruckdeschel + description: |- + S4-distribution classes based on package distr for distributions from packages + 'fBasics' and 'fGarch'. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrRmetrics + url_git: http://distr.r-forge.r-project.org/ +distrSim: + version: 2.8.5 + title: Simulation Classes Based on Package 'distr' + maintainer: Peter Ruckdeschel + description: |- + S4-classes for setting up a coherent framework for simulation within the distr + family of packages. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrSim + url_git: http://distr.r-forge.r-project.org/ +distrTeach: + version: 2.9.2 + title: |- + Extensions of Package 'distr' for Teaching + Stochastics/Statistics in Secondary School + maintainer: Peter Ruckdeschel + description: |- + Provides flexible examples of LLN and CLT for teaching purposes in secondary + school. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrTeach + url_git: http://distr.r-forge.r-project.org/ +distrTEst: + version: 2.8.3 + title: Estimation and Testing Classes Based on Package 'distr' + maintainer: Peter Ruckdeschel + description: |- + Evaluation (S4-)classes based on package distr for evaluating procedures + (estimators/tests) at data/simulation in a unified way. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distrTEst + url_git: http://distr.r-forge.r-project.org/ +distTails: + version: 0.1.2 + title: A Collection of Full Defined Distribution Tails + maintainer: Sergi Vilardell + description: A full definition for Weibull tails and Full-Tails Gamma and tools + for fitting these distributions to empirical tails. This package build upon the + paper by del Castillo, Joan & Daoudi, Jalila & Serra, Isabel. (2012) . + date_publication: '2019-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=distTails + url_git: https://github.com/SergiVilardell/distTails +disttools: + version: 0.1.8 + title: Distance Object Manipulation Tools + maintainer: Zachary Colburn + description: Provides convenient methods for accessing the data in 'dist' objects + with minimal memory and computational overhead. 'disttools' can be used to extract + the distance between any pair or combination of points encoded by a 'dist' object + using only the indices of those points. This is an improvement over existing functionality, + which requires either coercing a 'dist' object into a matrix or calculating the + one dimensional index corresponding to a pair of observations. Coercion to a matrix + is undesirable because doing so doubles the amount of memory required for storage. + In contrast, there is no inherent downside to the latter solution. However, in + part due to several edge cases, correctly and efficiently implementing such a + solution can be challenging. 'disttools' abstracts away these challenges and provides + a simple interface to access the data in a 'dist' object using the latter approach. + date_publication: '2022-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=disttools + url_git: '' +dittodb: + version: 0.1.8 + title: A Test Environment for Database Requests + maintainer: Jonathan Keane + description: |- + Testing and documenting code that communicates with remote + databases can be painful. Although the interaction with R is usually relatively + simple (e.g. data(frames) passed to and from a database), because they rely on + a separate service and the data there, testing them can be difficult to set up, + unsustainable in a continuous integration environment, or impossible without + replicating an entire production cluster. This package addresses that by + allowing you to make recordings from your database interactions and then play + them back while testing (or in other contexts) all without needing to spin up + or have access to the database your code would typically connect to. + date_publication: '2024-04-09' + bug_reports: https://github.com/ropensci/dittodb/issues + url: https://dittodb.jonkeane.com/ + url_cran: https://CRAN.R-project.org/package=dittodb + url_git: https://github.com/ropensci/dittodb +dittoViz: + version: 1.0.3 + title: User Friendly Data Visualization + maintainer: Daniel Bunis + description: |- + A comprehensive visualization toolkit built with coders of all + skill levels and color-vision impaired audiences in mind. It allows creation + of finely-tuned, publication-quality figures from single function calls. + Visualizations include scatter plots, compositional bar plots, violin, box, + and ridge plots, and more. Customization ranges from size and title + adjustments to discrete-group circling and labeling, hidden data overlay + upon cursor hovering via ggplotly() conversion, and many more, all with + simple, discrete inputs. Color blindness friendliness is powered by legend + adjustments (enlarged keys), and by allowing the use of shapes or + letter-overlay in addition to the carefully selected dittoColors(). + date_publication: '2025-02-25' + bug_reports: https://github.com/dtm2451/dittoViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dittoViz + url_git: https://github.com/dtm2451/dittoViz +div: + version: 0.3.1 + title: Report on Diversity and Inclusion in a Corporate Setting + maintainer: Philippe J.S. De Brouwer + description: |- + Facilitate the analysis of teams in a corporate setting: + assess the diversity per grade and job, present the results, + search for bias (in hiring and/or promoting processes). + It also provides methods to simulate the effect of bias, random team-data, etc. + White paper: 'Philippe J.S. De Brouwer' (2021) . + Book (chapter 36): 'Philippe J.S. De Brouwer' (2020, ISBN:978-1-119-63272-6) and 'Philippe J.S. De Brouwer' (2020) . + date_publication: '2021-05-06' + bug_reports: https://github.com/DrPhilippeDB/div/issues/ + url: http://www.de-brouwer.com/div/ + url_cran: https://CRAN.R-project.org/package=div + url_git: '' +divDyn: + version: 0.8.3 + title: Diversity Dynamics using Fossil Sampling Data + maintainer: Adam T. Kocsis + description: 'Functions to describe sampling and diversity dynamics of fossil occurrence + datasets (e.g. from the Paleobiology Database). The package includes methods to + calculate range- and occurrence-based metrics of taxonomic richness, extinction + and origination rates, along with traditional sampling measures. A powerful subsampling + tool is also included that implements frequently used sampling standardization + methods in a multiple bin-framework. The plotting of time series and the occurrence + data can be simplified by the functions incorporated in the package, as well as + other calculations, such as environmental affinities and extinction selectivity + testing. Details can be found in: Kocsis, A.T.; Reddin, C.J.; Alroy, J. and Kiessling, + W. (2019) .' + date_publication: '2024-11-21' + bug_reports: https://github.com/divDyn/r-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=divDyn + url_git: '' +DivE: + version: '1.3' + title: Diversity Estimator + maintainer: Daniel Laydon + description: Contains functions for the 'DivE' estimator . + The 'DivE' estimator is a heuristic approach to estimate the number of classes + or the number of species (species richness) in a population. + date_publication: '2023-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DivE + url_git: '' +diveMove: + version: 1.6.4 + title: Dive Analysis and Calibration + maintainer: Sebastian P. Luque + description: |- + Utilities to represent, visualize, filter, analyse, and summarize + time-depth recorder (TDR) data. Miscellaneous functions for + handling location data are also provided. + date_publication: '2024-10-13' + bug_reports: https://github.com/spluque/diveMove/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diveMove + url_git: https://github.com/spluque/diveMove +divent: + version: 0.5-2 + title: Entropy Partitioning to Measure Diversity + maintainer: Eric Marcon + description: |- + Measurement and partitioning of diversity, based on Tsallis entropy, following Marcon and Herault (2015) . + 'divent' provides functions to estimate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity. + date_publication: '2025-02-10' + bug_reports: https://github.com/EricMarcon/divent/issues + url: https://ericmarcon.github.io/divent/ + url_cran: https://CRAN.R-project.org/package=divent + url_git: https://github.com/EricMarcon/divent +diveR: + version: 0.1.2 + title: Easily Install and Load Interactive Data Visualization Tools + maintainer: R. Wayne Oldford + description: |- + A suite of 'loon' related packages providing data analytic tools for + Direct Interactive Visual Exploration in R ('diveR'). + These tools work with and complement those of the 'tidyverse' suite, + extending the grammar of 'ggplot2' to become a grammar of interactive + graphics. + The suite provides many visual tools designed for moderately (100s of variables) + high dimensional data analysis, through 'zenplots' and novel tools in 'loon', and + extends the 'ggplot2' grammar to provide parallel coordinates, Andrews plots, and arbitrary + glyphs through 'ggmulti'. + The 'diveR' package gathers together and installs all these related packages + in a single step. + date_publication: '2021-09-28' + bug_reports: https://github.com/great-northern-diver/diver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diveR + url_git: https://github.com/great-northern-diver/diver/ +diverge: + version: 2.0.6 + title: |- + Evolutionary Trait Divergence Between Sister Species and Other + Paired Lineages + maintainer: Sean A. S. Anderson + description: Compares the fit of alternative models of continuous trait differentiation + between sister species and other paired lineages. Differences in trait means between + two lineages arise as they diverge from a common ancestor, and alternative processes + of evolutionary divergence are expected to leave unique signatures in the distribution + of trait differentiation in datasets comprised of many lineage pairs. Models include + approximations of divergent selection, drift, and stabilizing selection. A variety + of model extensions facilitate the testing of process-to-pattern hypotheses. Users + supply trait data and divergence times for each lineage pair. The fit of alternative + models is compared in a likelihood framework. + date_publication: '2022-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diverge + url_git: '' +diverse: + version: 0.1.5 + title: Diversity Measures for Complex Systems + maintainer: Miguel R. Guevara + description: Computes the most common diversity measures used in social and other + sciences, and includes new measures from interdisciplinary research. + date_publication: '2017-03-23' + bug_reports: https://github.com/mguevara/diverse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=diverse + url_git: https://github.com/mguevara/diverse +DiversificationR: + version: 0.1.0 + title: Econometric Tools to Measure Portfolio Diversification + maintainer: Jean-Baptiste Hasse + description: Diversification is one of the most important concepts in portfolio + management. This framework offers scholars, practitioners and policymakers a useful + toolbox to measure diversification. Specifically, this framework provides recent + diversification measures from the recent literature. These diversification measures + are based on the works of Rudin and Morgan (2006) , + Choueifaty and Coignard (2008) , Vermorken et al. + (2012) , Flores et al. (2017) , + Calvet et al. (2007) , and Candelon, Fuerst and Hasse (2020). + date_publication: '2021-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DiversificationR + url_git: '' +diversitree: + version: 0.10-1 + title: Comparative 'Phylogenetic' Analyses of Diversification + maintainer: Richard G. FitzJohn + description: |- + Contains a number of comparative 'phylogenetic' methods, + mostly focusing on analysing diversification and character + evolution. Contains implementations of 'BiSSE' (Binary State + 'Speciation' and Extinction) and its unresolved tree extensions, + 'MuSSE' (Multiple State 'Speciation' and Extinction), 'QuaSSE', + 'GeoSSE', and 'BiSSE-ness' Other included methods include Markov + models of discrete and continuous trait evolution and constant rate + 'speciation' and extinction. + date_publication: '2024-10-02' + bug_reports: '' + url: https://www.zoology.ubc.ca/prog/diversitree/ + url_cran: https://CRAN.R-project.org/package=diversitree + url_git: '' +diversityForest: + version: 0.5.0 + title: |- + Innovative Complex Split Procedures in Random Forests Through + Candidate Split Sampling + maintainer: Roman Hornung + description: |- + Implementations of three diversity forest (DF) (Hornung, 2022, + ) variants. + The DF algorithm is a split-finding approach that allows complex split procedures to + be realized in random forest variants. + The three DF variants implemented are: + 1. interaction forests (IFs) (Hornung & Boulesteix, 2022, ): + Model quantitative and qualitative interaction effects using bivariable splitting. + Come with the Effect Importance Measure (EIM), which can be used to identify variable + pairs that have well-interpretable quantitative and qualitative interaction effects + with high predictive relevance. + 2. multi forests (MuFs) (Hornung & Hapfelmeier, 2024, ): + Model multi-class outcomes using multi-way and binary splitting. Come with two + variable importance measures (VIMs): The multi-class VIM measures the degree to which + the variables are specifically associated with one or more outcome classes, and the + discriminatory VIM, similar to conventional VIMs, measures the overall influence + strength of the variables. + 3. the basic form of diversity forests that uses conventional univariable, binary + splitting (Hornung, 2022). + Except for multi forests, which are tailored for multi-class outcomes, all included + diversity forest variants support categorical, metric, and survival outcomes. + The package also includes plotting functions that make it possible to learn about the + forms of the effects identified using IFs and MuFs. + This is a fork of the R package 'ranger' (main author: Marvin N. Wright), which + implements random forests using an efficient C++ implementation. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=diversityForest + url_git: '' +divest: + version: 1.1.1 + title: Get Images Out of DICOM Format Quickly + maintainer: Jon Clayden + description: |- + Provides tools to sort DICOM-format medical image files, and + convert them to NIfTI-1 format. + date_publication: '2024-10-20' + bug_reports: https://github.com/jonclayden/divest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=divest + url_git: https://github.com/jonclayden/divest +divo: + version: 1.0.2 + title: |- + Tools for Analysis of Diversity and Similarity in Biological + Systems + maintainer: Maciej Pietrzak + description: |- + A set of tools for empirical analysis of diversity (a number + and frequency of different types in a population) and similarity + (a number and frequency of shared types in two populations) in + biological or ecological systems. + date_publication: '2025-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=divo + url_git: '' +divraster: + version: 1.0.4 + title: Diversity Metrics Calculations for Rasterized Data + maintainer: Flávio M. M. Mota + description: Alpha and beta diversity for taxonomic (TD), functional (FD), and phylogenetic + (PD) dimensions based on rasters. Spatial and temporal beta diversity can be partitioned + into replacement and richness difference components. It also calculates standardized + effect size for FD and PD alpha diversity and the average individual traits across + multilayer rasters. The layers of the raster represent species, while the cells + represent communities. Methods details can be found at Cardoso et al. 2022 + and Heming et al. 2023 . + date_publication: '2023-10-10' + bug_reports: https://github.com/flaviomoc/divraster/issues + url: https://flaviomoc.github.io/divraster/ + url_cran: https://CRAN.R-project.org/package=divraster + url_git: https://github.com/flaviomoc/divraster +divseg: + version: 0.0.5 + title: Calculate Diversity and Segregation Indices + maintainer: Christopher T. Kenny + description: Implements common measures of diversity and spatial segregation. This + package has tools to compute the majority of measures are reviewed in Massey and + Denton (1988) . Multiple common measures of within-geography + diversity are implemented as well. All functions operate on data frames with a + 'tidyselect' based workflow. + date_publication: '2022-12-17' + bug_reports: https://github.com/christopherkenny/divseg/issues + url: https://christophertkenny.com/divseg/ + url_cran: https://CRAN.R-project.org/package=divseg + url_git: https://github.com/christopherkenny/divseg/ +divvy: + version: 1.0.0 + title: Spatial Subsampling of Biodiversity Occurrence Data + maintainer: Gawain Antell + description: |- + Divide taxonomic occurrence data into geographic regions of fair + comparison, with three customisable methods to standardise area and extent. + Calculate common biodiversity and range-size metrics on subsampled data. + Background theory and practical considerations for the methods are described + in Antell and others (2023) . + date_publication: '2023-10-26' + bug_reports: https://github.com/GawainAntell/divvy/issues + url: https://gawainantell.github.io/divvy/ + url_cran: https://CRAN.R-project.org/package=divvy + url_git: https://github.com/GawainAntell/divvy +dixon: + version: 0.0-9 + title: Nearest Neighbour Contingency Table Analysis + maintainer: Marcelino de la Cruz Rot + description: Function to test spatial segregation and association based in contingency + table analysis of nearest neighbour counts following Dixon (2002) . + Some 'Fortran' code has been included to the original dixon2002() function of + the 'ecespa' package to improve speed. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dixon + url_git: '' +dixonTest: + version: 1.0.4 + title: Dixon's Ratio Test for Outlier Detection + maintainer: Thorsten Pohlert + description: |- + For outlier detection in small and normally distributed + samples the ratio test of Dixon (Q-test) can be used. Density, + distribution function, quantile function and random generation + for Dixon's ratio statistics are provided as wrapper functions. + The core applies McBane's Fortran functions + that use Gaussian quadrature for a numerical solution. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dixonTest + url_git: '' +diyar: + version: 0.5.1 + title: Record Linkage and Epidemiological Case Definitions in 'R' + maintainer: Olisaeloka Nsonwu + description: |- + An R package for iterative and batched record linkage, + and applying epidemiological case definitions. + 'diyar' can be used for deterministic and probabilistic record linkage, + or multistage record linkage combining both approaches. + It features the implementation of nested match criteria, and mechanisms to + address missing data and conflicting matches during stepwise record linkage. + Case definitions are implemented by assigning records to groups based on + match criteria such as person or place, and overlapping time or duration of + events e.g. sample collection dates or periods of hospital stays. + Matching records are assigned a unique group ID. Index and duplicate records + are removed or further analyses as required. + date_publication: '2023-11-12' + bug_reports: https://github.com/OlisaNsonwu/diyar/issues + url: https://olisansonwu.github.io/diyar/index.html + url_cran: https://CRAN.R-project.org/package=diyar + url_git: '' +DIZtools: + version: 1.0.1 + title: Lightweight Utilities for 'DIZ' R Package Development + maintainer: Jonathan M. Mang + description: |- + Lightweight utility functions used for the R package + development infrastructure inside the data integration centers ('DIZ') + to standardize and facilitate repetitive tasks such as setting up a + database connection or issuing notification messages and to avoid + redundancy. + date_publication: '2023-09-18' + bug_reports: https://github.com/miracum/misc-diztools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DIZtools + url_git: https://github.com/miracum/misc-diztools +DIZutils: + version: 0.1.3 + title: Utilities for 'DIZ' R Package Development + maintainer: Jonathan M. Mang + description: |- + Utility functions used for the R package development + infrastructure inside the data integration centers ('DIZ') to + standardize and facilitate repetitive tasks such as setting up a + database connection or issuing notification messages and to avoid + redundancy. + date_publication: '2024-11-26' + bug_reports: https://github.com/miracum/misc-dizutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DIZutils + url_git: https://github.com/miracum/misc-dizutils +DJL: + version: '3.9' + title: Distance Measure Based Judgment and Learning + maintainer: Dong-Joon Lim + description: |- + Implements various decision support tools related to the Econometrics & Technometrics. + Subroutines include correlation reliability test, Mahalanobis distance measure for outlier detection, combinatorial search (all possible subset regression), non-parametric efficiency analysis measures: DDF (directional distance function), DEA (data envelopment analysis), HDF (hyperbolic distance function), SBM (slack-based measure), and SF (shortage function), benchmarking, Malmquist productivity analysis, risk analysis, technology adoption model, new product target setting, network DEA, dynamic DEA, intertemporal budgeting, etc. + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DJL + url_git: '' +dkanr: + version: 0.1.3 + title: Client for the 'DKAN' API + maintainer: Tony Fujs + description: Provides functions to facilitate access to the 'DKAN' API (), + including the 'DKAN' REST API (metadata), and the 'DKAN' datastore API (data). + Includes functions to list, create, retrieve, update, and delete datasets and + resources nodes. It also includes functions to search and retrieve data from the + 'DKAN' datastore. + date_publication: '2019-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dkanr + url_git: '' +dLagM: + version: 1.1.13 + title: Time Series Regression Models with Distributed Lag Models + maintainer: Haydar Demirhan + description: Provides time series regression models with one predictor using finite + distributed lag models, polynomial (Almon) distributed lag models, geometric distributed + lag models with Koyck transformation, and autoregressive distributed lag models. + It also consists of functions for computation of h-step ahead forecasts from these + models. See Demirhan (2020)() and Baltagi (2011)() + for more information. + date_publication: '2023-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dLagM + url_git: '' +DLASSO: + version: 2.0.2 + title: |- + Implementation of Adaptive or Non-Adaptive Differentiable Lasso + and SCAD Penalties in Linear Models + maintainer: Hamed Haseli Mashhadi + description: An implementation of the differentiable lasso (dlasso) and SCAD (dSCAD) + using iterative ridge algorithm. This package allows selecting the tuning parameter + by AIC, BIC, GIC and GIC. + date_publication: '2017-06-08' + bug_reports: '' + url: http://hamedhaseli.webs.com + url_cran: https://CRAN.R-project.org/package=DLASSO + url_git: '' +dlbayes: + version: 0.1.0 + title: |- + Use Dirichlet Laplace Prior to Solve Linear Regression Problem + and Do Variable Selection + maintainer: Shijia Zhang + description: |- + The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: + utility functions in implementing Dirichlet-Laplace priors such as visualization; + scalability in Bayesian linear regression; + penalized credible regions for variable selection. + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dlbayes + url_git: '' +DLEGFM: + version: 0.4.0 + title: Distributed Loading Estimation for General Factor Model + maintainer: Guangbao Guo + description: The load estimation method is based on a general factor model to solve + the estimates of load and specific variance. The philosophy of the package is + described in Guangbao Guo. (2022). . + date_publication: '2024-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DLEGFM + url_git: '' +dlib: + version: 1.0.3.1 + title: Allow Access to the 'Dlib' C++ Library + maintainer: Jan Wijffels + description: |- + Interface for 'Rcpp' users to 'dlib' which is a + 'C++' toolkit containing machine learning algorithms and computer vision tools. + It is used in a wide range of domains including robotics, embedded devices, + mobile phones, and large high performance computing environments. This package + allows R users to use 'dlib' through 'Rcpp'. + date_publication: '2020-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dlib + url_git: '' +dlim: + version: 0.1.0 + title: Distributed Lag Interaction Model + maintainer: Danielle Demateis + description: Collection of functions for fitting and interpreting distributed lag + interaction models (DLIM). A DLIM regresses a scalar outcome on repeated measures + of exposure and allows for modification by a continuous variable. Includes a dlim() + function for fitting, predict() function for inference, and plotting functions + for visualization. Details on methodology are described in Demateis et al. (2024) + . + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dlim + url_git: '' +DLL: + version: 1.0.0 + title: Decorrelated Local Linear Estimator + maintainer: Zijian Guo + description: |- + Implementation of the Decorrelated Local Linear estimator proposed + in . It constructs the confidence interval for the derivative + of the function of interest under the high-dimensional sparse additive model. + date_publication: '2022-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DLL + url_git: https://github.com/zijguo/HighDim-Additive-Inference +dlm: + version: 1.1-6.1 + title: Bayesian and Likelihood Analysis of Dynamic Linear Models + maintainer: Giovanni Petris + description: |- + Provides routines for Maximum likelihood, + Kalman filtering and smoothing, and Bayesian + analysis of Normal linear State Space models, also known as + Dynamic Linear Models. + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dlm + url_git: '' +DLMtool: + version: 6.0.6 + title: Data-Limited Methods Toolkit + maintainer: Adrian Hordyk + description: |- + A collection of data-limited management procedures that can be evaluated + with management strategy evaluation with the 'MSEtool' package, or applied to + fishery data to provide management recommendations. + date_publication: '2022-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DLMtool + url_git: '' +dlmtree: + version: 1.0.0 + title: Bayesian Treed Distributed Lag Models + maintainer: Daniel Mork + description: 'Estimation of distributed lag models (DLMs) based on a Bayesian additive + regression trees framework. Includes several extensions of DLMs: treed DLMs and + distributed lag mixture models (Mork and Wilson, 2023) ; + treed distributed lag nonlinear models (Mork and Wilson, 2022) ; + heterogeneous DLMs (Mork, et. al., 2024) ; + monotone DLMs (Mork and Wilson, 2024) . The package also + includes visualization tools and a ''shiny'' interface to help interpret results.' + date_publication: '2024-05-31' + bug_reports: https://github.com/danielmork/dlmtree/issues + url: https://danielmork.github.io/dlmtree/ + url_cran: https://CRAN.R-project.org/package=dlmtree + url_git: https://github.com/danielmork/dlmtree +dlnm: + version: 2.4.7 + title: Distributed Lag Non-Linear Models + maintainer: Antonio Gasparrini + description: Collection of functions for distributed lag linear and non-linear models. + date_publication: '2021-10-07' + bug_reports: '' + url: http://www.ag-myresearch.com/package-dlnm + url_cran: https://CRAN.R-project.org/package=dlnm + url_git: https://github.com/gasparrini/dlnm +dlookr: + version: 0.6.3 + title: Tools for Data Diagnosis, Exploration, Transformation + maintainer: Choonghyun Ryu + description: |- + A collection of tools that support data diagnosis, exploration, and transformation. + Data diagnostics provides information and visualization of missing values, outliers, and unique + and negative values to help you understand the distribution and quality of your data. + Data exploration provides information and visualization of the descriptive statistics of + univariate variables, normality tests and outliers, correlation of two variables, + and the relationship between the target variable and predictor. Data transformation supports binning + for categorizing continuous variables, imputes missing values and outliers, and resolves skewness. + And it creates automated reports that support these three tasks. + date_publication: '2024-02-07' + bug_reports: https://github.com/choonghyunryu/dlookr/issues + url: https://choonghyunryu.github.io/dlookr/ + url_cran: https://CRAN.R-project.org/package=dlookr + url_git: https://github.com/choonghyunryu/dlookr/ +DLPCA: + version: 0.0.5 + title: The Distributed Local PCA Algorithm + maintainer: Guangbao Guo + description: Algorithm to handle with optimal subset selection for distributed local + principal component analysis. The philosophy of the package is described in Guo + G. (2020) . + date_publication: '2022-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DLPCA + url_git: '' +dlr: + version: 1.0.1 + title: Download and Cache Files Safely + maintainer: Jon Harmon + description: |- + The goal of dlr is to provide a friendly wrapper around the common + pattern of downloading a file if that file does not already exist locally. + date_publication: '2021-09-18' + bug_reports: https://github.com/macmillancontentscience/dlr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dlr + url_git: https://github.com/macmillancontentscience/dlr +dlsem: + version: 2.4.6 + title: Distributed-Lag Linear Structural Equation Models + maintainer: Alessandro Magrini + description: Inference functionalities for distributed-lag linear structural equation + models (DLSEMs). DLSEMs are Markovian structural causal models where each factor + of the joint probability distribution is a distributed-lag linear regression with + constrained lag shapes (Magrini, 2018 ; Magrini et + al., 2019 ). DLSEMs account for temporal delays + in the dependence relationships among the variables through a single parameter + per covariate, thus allowing to perform dynamic causal inference in a feasible + fashion. Endpoint-constrained quadratic, quadratic decreasing, linearly decreasing + and gamma lag shapes are available. + date_publication: '2020-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dlsem + url_git: '' +dlstats: + version: 0.1.7 + title: Download Stats of R Packages + maintainer: Guangchuang Yu + description: |- + Monthly download stats of 'CRAN' and 'Bioconductor' packages. + Download stats of 'CRAN' packages is from the 'RStudio' 'CRAN mirror', see . + 'Bioconductor' package download stats is at . + date_publication: '2023-05-24' + bug_reports: https://github.com/GuangchuangYu/dlstats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dlstats + url_git: https://github.com/GuangchuangYu/dlstats +dm: + version: 1.0.11 + title: Relational Data Models + maintainer: Kirill Müller + description: |- + Provides tools for working with multiple related + tables, stored as data frames or in a relational database. Multiple + tables (data and metadata) are stored in a compound object, which can + then be manipulated with a pipe-friendly syntax. + date_publication: '2024-11-25' + bug_reports: https://github.com/cynkra/dm/issues + url: https://dm.cynkra.com/ + url_cran: https://CRAN.R-project.org/package=dm + url_git: https://github.com/cynkra/dm +dma: + version: 1.4-0 + title: Dynamic Model Averaging + maintainer: Hana Sevcikova + description: |- + Dynamic model averaging for binary and continuous + outcomes. + date_publication: '2018-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dma + url_git: '' +dmai: + version: 0.5.0 + title: Divisia Monetary Aggregates Index + maintainer: Muhammad Yaseen + description: Functions to calculate Divisia monetary aggregates index as given in + Barnett, W. A. (1980) (). + date_publication: '2024-03-23' + bug_reports: '' + url: https://myaseen208.com/dmai/ + url_cran: https://CRAN.R-project.org/package=dmai + url_git: https://github.com/myaseen208/dmai/ +dmbc: + version: 1.0.3 + title: Model Based Clustering of Binary Dissimilarity Measurements + maintainer: Sergio Venturini + description: |- + Functions for fitting a Bayesian model for grouping binary + dissimilarity matrices in homogeneous clusters. Currently, it includes + methods only for binary data (). + date_publication: '2024-09-24' + bug_reports: https://github.com/sergioventurini/dmbc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dmbc + url_git: '' +DMCfun: + version: 4.0.1 + title: Diffusion Model of Conflict (DMC) in Reaction Time Tasks + maintainer: Ian G. Mackenzie + description: |- + DMC model simulation detailed in Ulrich, R., Schroeter, H., Leuthold, H., & Birngruber, T. (2015). + Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions. + Cognitive Psychology, 78, 148-174. Ulrich et al. (2015) . + Decision processes within choice reaction-time (CRT) tasks are often modelled using evidence accumulation models (EAMs), + a variation of which is the Diffusion Decision Model (DDM, for a review, see Ratcliff & McKoon, 2008). + Ulrich et al. (2015) introduced a Diffusion Model for Conflict tasks (DMC). The DMC model combines common + features from within standard diffusion models with the addition of superimposed controlled and automatic activation. + The DMC model is used to explain distributional reaction time (and error rate) patterns in common behavioural + conflict-like tasks (e.g., Flanker task, Simon task). This R-package implements the DMC model and provides functionality + to fit the model to observed data. Further details are provided in the following paper: + Mackenzie, I.G., & Dudschig, C. (2021). DMCfun: An R package for fitting Diffusion Model of Conflict (DMC) to reaction + time and error rate data. Methods in Psychology, 100074. . + date_publication: '2024-09-16' + bug_reports: '' + url: https://www.sciencedirect.com/science/article/pii/S259026012100031X + url_cran: https://CRAN.R-project.org/package=DMCfun + url_git: https://github.com/igmmgi/DMCfun +dmetatools: + version: 1.1.1 + title: |- + Computational Tools for Meta-Analysis of Diagnostic Accuracy + Test + maintainer: Hisashi Noma + description: Computational tools for meta-analysis of diagnostic accuracy test. + Bootstrap-based computational methods of the confidence interval for AUC of summary + ROC curve and some related AUC-based inference methods are available (Noma et + al. (2021) ). + date_publication: '2023-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dmetatools + url_git: '' +dml: + version: 1.1.0 + title: Distance Metric Learning in R + maintainer: Yuan Tang + description: The state-of-the-art algorithms for distance metric learning, including + global and local methods such as Relevant Component Analysis, Discriminative Component + Analysis, Local Fisher Discriminant Analysis, etc. These distance metric learning + methods are widely applied in feature extraction, dimensionality reduction, clustering, + classification, information retrieval, and computer vision problems. + date_publication: '2015-08-29' + bug_reports: https://github.com/terrytangyuan/dml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dml + url_git: https://github.com/terrytangyuan/dml +dmlalg: + version: 1.0.2 + title: Double Machine Learning Algorithms + maintainer: Corinne Emmenegger + description: |- + Implementation of double machine learning (DML) algorithms in R, + based on Emmenegger and Buehlmann (2021) "Regularizing Double Machine Learning + in Partially Linear Endogenous Models" and Emmenegger and + Buehlmann (2021) "Double Machine Learning for Partially + Linear Mixed-Effects Models with Repeated Measurements". + First part: our goal is to perform inference for the linear parameter in partially + linear models with confounding variables. + The standard DML estimator of the linear parameter has a two-stage least + squares interpretation, which can lead to a large variance and overwide + confidence intervals. + We apply regularization to reduce the variance of the estimator, + which produces narrower confidence intervals that are approximately valid. + Nuisance terms can be flexibly estimated with machine learning algorithms. + Second part: our goal is to estimate and perform inference for the linear + coefficient in a partially linear mixed-effects model + with DML. Machine learning algorithms allows us to incorporate more + complex interaction structures and high-dimensional variables. + date_publication: '2022-02-03' + bug_reports: '' + url: https://gitlab.math.ethz.ch/ecorinne/dmlalg.git + url_cran: https://CRAN.R-project.org/package=dmlalg + url_git: '' +dmm: + version: 3.1-1 + title: Dyadic Mixed Model for Pedigree Data + maintainer: Neville Jackson + description: |- + Mixed model analysis for quantitative genetics + with multi-trait responses and pedigree-based partitioning + of individual variation into a range of environmental and + genetic variance components for individual and + maternal effects. Method documented in dmmOverview.pdf; dmm is an + implementation of dispersion mean model described by + Searle et al. (1992) "Variance Components", Wiley, NY. + 'DMM' can do 'MINQUE', 'bias-corrected-ML', and 'REML' variance component estimates. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dmm + url_git: '' +DMMF: + version: 0.5.2.0 + title: Daily Based Morgan-Morgan-Finney (DMMF) Soil Erosion Model + maintainer: Kwanghun Choi + description: Implements the daily based Morgan-Morgan-Finney (DMMF) soil erosion + model (Choi et al., 2017 ) for estimating surface runoff + and sediment budgets from a field or a catchment on a daily basis. + date_publication: '2023-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DMMF + url_git: '' +dMod: + version: 1.0.2 + title: Dynamic Modeling and Parameter Estimation in ODE Models + maintainer: Daniel Kaschek + description: |- + The framework provides functions to generate ODEs of reaction + networks, parameter transformations, observation functions, residual functions, + etc. The framework follows the paradigm that derivative information should be + used for optimization whenever possible. Therefore, all major functions produce + and can handle expressions for symbolic derivatives. The methods used in dMod + were published in Kaschek et al, 2019, . + date_publication: '2021-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dMod + url_git: '' +DMQ: + version: 0.1.2 + title: Dynamic Multiple Quantile (DMQ) Model + maintainer: Leopoldo Catania + description: Perform estimation, prediction, and simulations using the Dynamic Multiple + Quantile model of Catania and Luati (2023) . + Can be used to estimate a set of conditional time-varying quantiles of a time + series that do not cross. + date_publication: '2023-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DMQ + url_git: '' +dmri.tracking: + version: 0.1.0 + title: DiST - Diffusion Direction Smoothing and Tracking + maintainer: Seungyong Hwang + description: It provides functions to apply the deterministic tracking algorithm + - DiST (Wong et al 2016) and to plot tractography results. + date_publication: '2021-06-09' + bug_reports: https://github.com/vic-dragon/dmri.tracking/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dmri.tracking + url_git: https://github.com/vic-dragon/dmri.tracking +DMRnet: + version: 0.4.0 + title: |- + Delete or Merge Regressors Algorithms for Linear and Logistic + Model Selection and High-Dimensional Data + maintainer: Szymon Nowakowski + description: 'Model selection algorithms for regression and classification, where + the predictors can be continuous or categorical and the number of regressors may + exceed the number of observations. The selected model consists of a subset of + numerical regressors and partitions of levels of factors. Szymon Nowakowski, Piotr + Pokarowski, Wojciech Rejchel and Agnieszka Sołtys, 2023. Improving Group Lasso + for High-Dimensional Categorical Data. In: Computational Science – ICCS 2023. + Lecture Notes in Computer Science, vol 14074, p. 455-470. Springer, Cham. . + Aleksandra Maj-Kańska, Piotr Pokarowski and Agnieszka Prochenka, 2015. Delete + or merge regressors for linear model selection. Electronic Journal of Statistics + 9(2): 1749-1778. . Piotr Pokarowski and Jan Mielniczuk, + 2015. Combined l1 and greedy l0 penalized least squares for linear model selection. + Journal of Machine Learning Research 16(29): 961-992. . + Piotr Pokarowski, Wojciech Rejchel, Agnieszka Sołtys, Michał Frej and Jan Mielniczuk, + 2022. Improving Lasso for model selection and prediction. Scandinavian Journal + of Statistics, 49(2): 831–863. .' + date_publication: '2023-08-07' + bug_reports: https://github.com/SzymonNowakowski/DMRnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DMRnet + url_git: https://github.com/SzymonNowakowski/DMRnet +dMrs: + version: 1.0.0 + title: Competing Risk in Dependent Net Survival Analysis + maintainer: Paul Little + description: |- + Provides statistical tools for + analyzing net and relative survival, with a key feature + of relaxing the assumption of independent censoring and + incorporating the effect of dependent competing risks. + It employs a copula-based methodology, specifically the + Archimedean copula, to simulate data, conduct survival + analysis, and offer comparisons with other methods. + This approach is detailed in the work of + Adatorwovor et al. (2022) . + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dMrs + url_git: '' +DMtest: + version: 1.0.0 + title: Differential Methylation Tests (DMtest) + maintainer: James Dai + description: Several tests for differential methylation in methylation array data, + including one-sided differential mean and variance test. Methods used in the package + refer to Dai, J, Wang, X, Chen, H and others (2021) "Incorporating increased variability + in discovering cancer methylation markers", Biostatistics, submitted. + date_publication: '2021-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DMtest + url_git: '' +DMTL: + version: 0.1.2 + title: Tools for Applying Distribution Mapping Based Transfer Learning + maintainer: Saugato Rahman Dhruba + description: |2- + + Implementation of a transfer learning framework employing distribution mapping based domain transfer. Uses the renowned concept of histogram matching (see Gonzalez and Fittes (1977) , Gonzalez and Woods (2008) ) and extends it to include distribution measures like kernel density estimates (KDE; see Wand and Jones (1995) , Jones et al. (1996) . + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DNAmixturesLite + url_git: '' +DNAmotif: + version: 0.1.1 + title: DNA Sequence Motifs + maintainer: Subham Ghosh + description: Motifs within biological sequences show a significant role. This package + utilizes a user-defined threshold value (window size and similarity) to create + consensus segments or motifs through local alignment of dynamic programming with + gap and it calculates the frequency of each identified motif, offering a detailed + view of their prevalence within the dataset. It allows for thorough exploration + and understanding of sequence patterns and their biological importance. + date_publication: '2024-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DNAmotif + url_git: '' +dnapath: + version: 0.7.6 + title: Differential Network Analysis using Gene Pathways + maintainer: Tyler Grimes + description: Integrates pathway information into the differential network analysis + of two gene expression datasets as described in Grimes, Potter, and Datta (2019) + . Provides summary functions to break down the + results at the pathway, gene, or individual connection level. The differential + networks for each pathway of interest can be plotted, and the visualization will + highlight any differentially expressed genes and all of the gene-gene associations + that are significantly differentially connected. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dnapath + url_git: '' +DNAseqtest: + version: '1.0' + title: Generating and Testing DNA Sequences + maintainer: Hasinur Rahaman Khan + description: Generates DNA sequences based on Markov model techniques for matched + sequences. This can be generalized to several sequences. The sequences (taxa) + are then arranged in an evolutionary tree (phylogenetic tree) depicting how taxa + diverge from their common ancestors. This gives the tests and estimation methods + for the parameters of different models. Standard phylogenetic methods assume stationarity, + homogeneity and reversibility for the Markov processes, and often impose further + restrictions on the parameters. + date_publication: '2016-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DNAseqtest + url_git: '' +DNAtools: + version: 0.2-4 + title: Tools for Analysing Forensic Genetic DNA Data + maintainer: Mikkel Meyer Andersen + description: |- + Computationally efficient tools for comparing all pairs of profiles + in a DNA database. The expectation and covariance of the summary statistic + is implemented for fast computing. Routines for estimating proportions of + close related individuals are available. The use of wildcards (also called F- + designation) is implemented. Dedicated functions ease plotting the results. + See Tvedebrink et al. (2012) . + Compute the distribution of the numbers of alleles in DNA mixtures. + See Tvedebrink (2013) . + date_publication: '2022-03-17' + bug_reports: https://github.com/mikldk/DNAtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DNAtools + url_git: '' +dndR: + version: 2.0.0 + title: Dungeons & Dragons Functions for Players and Dungeon Masters + maintainer: Nicholas Lyon + description: |- + The goal of 'dndR' is to provide a suite of Dungeons & Dragons related functions. + This package is meant to be useful both to players and Dungeon Masters (DMs). + All functions currently focus on Fifth Edition (a.k.a. "5e") but once the next edition is published functions will likely be expanded to include any rule changes. + date_publication: '2024-04-26' + bug_reports: https://github.com/njlyon0/dndR/issues + url: https://njlyon0.github.io/dndR/ + url_cran: https://CRAN.R-project.org/package=dndR + url_git: '' +DNetFinder: + version: '1.1' + title: |- + Estimating Differential Networks under Semiparametric Gaussian + Graphical Models + maintainer: Qingyang Zhang + description: Provides a modified hierarchical test (Liu (2017) ) + for detecting the structural difference between two Semiparametric Gaussian graphical + models. The multiple testing procedure asymptotically controls the false discovery + rate (FDR) at a user-specified level. To construct the test statistic, a truncated + estimator is used to approximate the transformation functions and two R functions + including lassoGGM() and lassoNPN() are provided to compute the lasso estimates + of the regression coefficients. + date_publication: '2023-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DNetFinder + url_git: '' +dng: + version: 0.2.1 + title: Distributions and Gradients + maintainer: Jiayue Zeng + description: |- + Provides density, distribution function, quantile function and random + generation for the split normal and split-t distributions, and computes their + mean, variance, skewness and kurtosis for the two distributions (Li, F, + Villani, M. and Kohn, R. (2010) ). + date_publication: '2018-06-27' + bug_reports: https://github.com/feng-li/dng/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dng + url_git: https://github.com/feng-li/dng/ +DNMF: + version: 1.4.2 + title: Discriminant Non-Negative Matrix Factorization + maintainer: Zhilong Jia + description: 'Discriminant Non-Negative Matrix Factorization aims to extend the + Non-negative Matrix Factorization algorithm in order to extract features that + enforce not only the spatial locality, but also the separability between classes + in a discriminant manner. It refers to three article, Zafeiriou, Stefanos, et + al. "Exploiting discriminant information in nonnegative matrix factorization with + application to frontal face verification." Neural Networks, IEEE Transactions + on 17.3 (2006): 683-695. Kim, Bo-Kyeong, and Soo-Young Lee. "Spectral Feature + Extraction Using dNMF for Emotion Recognition in Vowel Sounds." Neural Information + Processing. Springer Berlin Heidelberg, 2013. and Lee, Soo-Young, Hyun-Ah Song, + and Shun-ichi Amari. "A new discriminant NMF algorithm and its application to + the extraction of subtle emotional differences in speech." Cognitive neurodynamics + 6.6 (2012): 525-535.' + date_publication: '2022-05-10' + bug_reports: https://github.com/zhilongjia/DNMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DNMF + url_git: https://github.com/zhilongjia/DNMF +dnn: + version: 0.0.6 + title: Deep Neural Network Tools for Probability and Statistic Models + maintainer: Bingshu E. Chen + description: Contains tools to build deep neural network with flexible users define + loss function and probability models. Several applications included in this package + are, 1) The (deepAFT) model, a deep neural network model for accelerated failure + time (AFT) model for survival data. 2) The (deepGLM) model, a deep neural network + model for generalized linear model (glm) for continuous, categorical and Poisson + data. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dnn + url_git: '' +DNNSIM: + version: 0.1.1 + title: Single-Index Neural Network for Skewed Heavy-Tailed Data + maintainer: Qingyang Liu + description: Provides a deep neural network model with a monotonic increasing single + index function tailored for periodontal disease studies. The residuals are assumed + to follow a skewed T distribution, a skewed normal distribution, or a normal distribution. + More details can be found at Liu, Huang, and Bai (2024) . + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DNNSIM + url_git: '' +dnr: + version: 0.3.5 + title: |- + Simulate Dynamic Networks using Exponential Random Graph Models + (ERGM) Family + maintainer: Abhirup Mallik + description: |- + Functions are provided to fit temporal lag models to dynamic + networks. The models are build on top of exponential random graph models (ERGM) framework. There are + functions for simulating or forecasting networks for future time points. + Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, . + date_publication: '2020-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dnr + url_git: '' +do: + version: 2.0.0.1 + title: Data Operator + maintainer: Jing Zhang + description: |- + Flexibly convert data between long and wide format using just two + functions: reshape_toLong() and reshape_toWide(). + date_publication: '2024-09-11' + bug_reports: https://github.com/yikeshu0611/do/issues + url: '' + url_cran: https://CRAN.R-project.org/package=do + url_git: https://github.com/yikeshu0611/do +do3PCA: + version: 1.0.0 + title: Probabilistic Phylogenetic Principal Component Analysis + maintainer: Daniel Caetano + description: Estimates probabilistic phylogenetic Principal Component Analysis (PCA) + and non-phylogenetic probabilistic PCA. Provides methods to implement alternative + models of trait evolution including Brownian motion (BM), Ornstein-Uhlenbeck (OU), + Early Burst (EB), and Pagel's lambda. Also provides flexible biplot functions. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=do3PCA + url_git: '' +dobin: + version: 1.0.4 + title: Dimension Reduction for Outlier Detection + maintainer: Sevvandi Kandanaarachchi + description: |- + A dimension reduction technique for outlier detection. DOBIN: a Distance + based Outlier BasIs using Neighbours, constructs a set of basis vectors for outlier + detection. This is not an outlier detection method; rather it is a pre-processing + method for outlier detection. It brings outliers to the fore-front using fewer basis + vectors (Kandanaarachchi, Hyndman 2020) . + date_publication: '2022-08-25' + bug_reports: '' + url: https://sevvandi.github.io/dobin/ + url_cran: https://CRAN.R-project.org/package=dobin + url_git: '' +dobson: + version: '0.4' + title: Data from the GLM Book by Dobson and Barnett + maintainer: Adrian Barnett + description: 'Example datasets from the book "An Introduction to Generalised Linear + Models" (Year: 2018, ISBN:9781138741515) by Dobson and Barnett.' + date_publication: '2018-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dobson + url_git: '' +doBy: + version: 4.6.25 + title: Groupwise Statistics, LSmeans, Linear Estimates, Utilities + maintainer: Søren Højsgaard + description: |- + Utility package containing: + 1) Facilities for working with grouped data: 'do' something to data + stratified 'by' some variables. + 2) LSmeans (least-squares means), general linear estimates. + 3) Restrict functions to a smaller domain. + 4) Miscellaneous other utilities. + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doBy + url_git: https://github.com/hojsgaard/doBy +doc2concrete: + version: 0.6.0 + title: Measuring Concreteness in Natural Language + maintainer: Mike Yeomans + description: Models for detecting concreteness in natural language. This package + is built in support of Yeomans (2021) , which + reviews linguistic models of concreteness in several domains. Here, we provide + an implementation of the best-performing domain-general model (from Brysbaert + et al., (2014) ) as well as two pre-trained models + for the feedback and plan-making domains. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doc2concrete + url_git: '' +doc2vec: + version: 0.2.0 + title: Distributed Representations of Sentences, Documents and Topics + maintainer: Jan Wijffels + description: |- + Learn vector representations of sentences, paragraphs or documents by using the 'Paragraph Vector' algorithms, + namely the distributed bag of words ('PV-DBOW') and the distributed memory ('PV-DM') model. + The techniques in the package are detailed in the paper "Distributed Representations of Sentences and Documents" by Mikolov et al. (2014), available at . + The package also provides an implementation to cluster documents based on these embedding using a technique called top2vec. + Top2vec finds clusters in text documents by combining techniques to embed documents and words and density-based clustering. + It does this by embedding documents in the semantic space as defined by the 'doc2vec' algorithm. Next it maps + these document embeddings to a lower-dimensional space using the 'Uniform Manifold Approximation and Projection' (UMAP) clustering algorithm + and finds dense areas in that space using a 'Hierarchical Density-Based Clustering' technique (HDBSCAN). These dense + areas are the topic clusters which can be represented by the corresponding topic vector which is an aggregate of the + document embeddings of the documents which are part of that topic cluster. In the same semantic space similar words can + be found which are representative of the topic. + More details can be found in the paper 'Top2Vec: Distributed Representations of Topics' by D. Angelov available at . + date_publication: '2021-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doc2vec + url_git: https://github.com/bnosac/doc2vec +dockerfiler: + version: 0.2.4 + title: Easy Dockerfile Creation from R + maintainer: Colin Fay + description: |- + Build a Dockerfile straight from your R session. + 'dockerfiler' allows you to create step by step a Dockerfile, and + provide convenient tools to wrap R code inside this Dockerfile. + date_publication: '2024-08-23' + bug_reports: https://github.com/ThinkR-open/dockerfiler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dockerfiler + url_git: https://github.com/ThinkR-open/dockerfiler +DockerParallel: + version: 1.0.4 + title: |- + Using the Docker Container to Create R Workers on Local or Cloud + Platform + maintainer: Jiefei Wang + description: |- + This is the core package that provides both the user API and developer API to deploy + the parallel cluster on the cloud using the container service. The user can call + clusterPreset() to define the cloud service provider and container and makeDockerCluster() + to create the cluster. The developer should see "developer's cookbook" on how to define + the cloud provider and container. + date_publication: '2021-06-23' + bug_reports: https://github.com/Jiefei-Wang/DockerParallel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DockerParallel + url_git: https://github.com/Jiefei-Wang/DockerParallel +docket: + version: '1.33' + title: Insert R Data into 'Word' Documents + maintainer: Jonathan Conrad + description: Populate data from an R environment into '.doc' and '.docx' templates. + Create a template document in a program such as 'Word', and add strings encased + in guillemet characters to create flags («example»). Use getDictionary() to create + a dictionary of flags and replacement values, then call docket() to generate a + populated document. + date_publication: '2024-07-12' + bug_reports: https://github.com/JonathanConrad98/docket/issues + url: '' + url_cran: https://CRAN.R-project.org/package=docket + url_git: https://github.com/JonathanConrad98/docket +docknitr: + version: 1.0.1 + title: Use Docker Images to Process Rmarkdown Blocks + maintainer: Ben Artin + description: |- + Gives you the ability to use arbitrary Docker images + (including custom ones) to process Rmarkdown code chunks. + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=docknitr + url_git: '' +doconv: + version: 0.3.2 + title: Document Conversion to 'PDF' or 'PNG' + maintainer: David Gohel + description: |- + It provides the ability to generate images from documents + of different types. Three main features are provided: functions for + generating document thumbnails, functions for performing visual tests + of documents and a function for updating fields and table of contents + of a 'Microsoft Word' or 'RTF' document. In order to work, 'LibreOffice' must be + installed on the machine and or 'Microsoft Word'. If the latter is + available, it can be used to produce PDF documents or images + identical to the originals; otherwise, 'LibreOffice' is used and + the rendering can be sometimes different from the original + documents. + date_publication: '2023-02-09' + bug_reports: https://github.com/ardata-fr/doconv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=doconv + url_git: '' +docopt: + version: 0.7.1 + title: Command-Line Interface Specification Language + maintainer: Edwin de Jonge + description: |- + Define a command-line interface by just giving it + a description in the specific format. + date_publication: '2020-06-24' + bug_reports: https://github.com/docopt/docopt.R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=docopt + url_git: https://github.com/docopt/docopt.R +docopulae: + version: 0.4.0 + title: Optimal Designs for Copula Models + maintainer: Andreas Rappold + description: |- + A direct approach to optimal designs for copula models based on + the Fisher information. Provides flexible functions for building joint PDFs, + evaluating the Fisher information and finding optimal designs. It includes an + extensible solution to summation and integration called 'nint', functions for + transforming, plotting and comparing designs, as well as a set of tools for + common low-level tasks. + date_publication: '2018-10-26' + bug_reports: https://github.com/arappold/docopulae/issues + url: '' + url_cran: https://CRAN.R-project.org/package=docopulae + url_git: http://www.tandfonline.com/doi/full/10.1080/02331888.2015.1111892https://github.com/arappold/docopulae +docore: + version: '1.0' + title: Utility Functions for Scientific Coding + maintainer: Danail Obreschkow + description: Basic routines used in scientific coding, such as timing routines, + vector/array handing functions and I/O support routines. + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=docore + url_git: '' +Docovt: + version: '0.1' + title: Distributed Online Covariance Matrix Tests + maintainer: Guangbao Guo + description: Distributed Online Covariance Matrix Tests is a powerful tool designed + to efficiently process and analyze distributed datasets. It enables users to perform + covariance matrix tests in an online, distributed manner, making it highly suitable + for large-scale data analysis. By leveraging advanced computational techniques, + 'Docovt' ensures robust and scalable solutions for statistical analysis, particularly + in scenarios where data is dispersed across multiple nodes or sources. This package + is ideal for researchers and practitioners working with high-dimensional data, + providing a flexible and efficient framework for covariance matrix estimation + and hypothesis testing. The philosophy of 'Docovt' is described in Guo G.(2025) + . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Docovt + url_git: '' +docstring: + version: 1.0.0 + title: Provides Docstring Capabilities to R Functions + maintainer: Dason Kurkiewicz + description: |- + Provides the ability to display something analogous to + Python's docstrings within R. By allowing the user to document + their functions as comments at the beginning of their function + without requiring putting the function into a package we allow + more users to easily provide documentation for their functions. + The documentation can be viewed just like any other help files + for functions provided by packages as well. + date_publication: '2017-03-24' + bug_reports: https://github.com/dasonk/docstring/issues?state=open + url: '' + url_cran: https://CRAN.R-project.org/package=docstring + url_git: https://github.com/dasonk/docstring +doctest: + version: 0.3.0 + title: Generate Tests from Examples Using 'roxygen' and 'testthat' + maintainer: David Hugh-Jones + description: Creates 'testthat' tests from 'roxygen' examples using simple tags. + date_publication: '2024-01-11' + bug_reports: https://github.com/hughjonesd/doctest/issues + url: https://hughjonesd.github.io/doctest/ + url_cran: https://CRAN.R-project.org/package=doctest + url_git: '' +document: + version: 4.0.0 + title: Run 'roxygen2' on (Chunks of) Single Code Files + maintainer: Andreas Dominik Cullmann + description: |- + Have you ever been tempted to create 'roxygen2'-style documentation + comments for one of your functions that was not part of one of your + packages (yet)? + This is exactly what this package is about: running 'roxygen2' on + (chunks of) a single code file. + date_publication: '2023-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=document + url_git: https://gitlab.com/fvafrcu/document +documenter: + version: 0.1.3 + title: Documents Files + maintainer: Zachary Colburn + description: It is sometimes necessary to create documentation for all files in + a directory. Doing so by hand can be very tedious. This task is made fast and + reproducible using the functionality of 'documenter'. It aggregates all text files + in a directory and its subdirectories into a single word document in a semi-automated + fashion. + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=documenter + url_git: '' +docuSignr: + version: 0.0.3 + title: Connect to 'DocuSign' API + maintainer: Carl Ganz + description: |- + Connect to the 'DocuSign' Rest API , + which supports embedded signing, and sending of documents. + date_publication: '2017-10-22' + bug_reports: https://github.com/CannaData/docuSignr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=docuSignr + url_git: https://github.com/CannaData/docuSignr +docxtractr: + version: 0.6.5 + title: |- + Extract Data Tables and Comments from 'Microsoft' 'Word' + Documents + maintainer: Bob Rudis + description: |- + 'Microsoft Word' 'docx' files provide an 'XML' structure that is fairly + straightforward to navigate, especially when it applies to 'Word' tables and + comments. Tools are provided to determine table count/structure, comment count + and also to extract/clean tables and comments from 'Microsoft Word' 'docx' documents. + There is also nascent support for '.doc' and '.pptx' files. + date_publication: '2020-07-05' + bug_reports: https://gitlab.com/hrbrmstr/docxtractr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=docxtractr + url_git: http://gitlab.com/hrbrmstr/docxtractr +dodgr: + version: 0.4.1 + title: Distances on Directed Graphs + maintainer: Mark Padgham + description: |- + Distances on dual-weighted directed graphs using + priority-queue shortest paths (Padgham (2019) ). + Weighted directed graphs have weights from A to B which may differ + from those from B to A. Dual-weighted directed graphs have two sets + of such weights. A canonical example is a street network to be used + for routing in which routes are calculated by weighting distances + according to the type of way and mode of transport, yet lengths of + routes must be calculated from direct distances. + date_publication: '2024-07-07' + bug_reports: https://github.com/UrbanAnalyst/dodgr/issues + url: https://urbananalyst.github.io/dodgr/ + url_cran: https://CRAN.R-project.org/package=dodgr + url_git: https://github.com/UrbanAnalyst/dodgr +DoE.base: + version: 1.2-4 + title: |- + Full Factorials, Orthogonal Arrays and Base Utilities for DoE + Packages + maintainer: Ulrike Groemping + description: Creates full factorial experimental designs and designs based on orthogonal + arrays for (industrial) experiments. Provides diverse quality criteria. Provides + utility functions for the class design, which is also used by other packages for + designed experiments. + date_publication: '2023-11-14' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/DoE/ + url_cran: https://CRAN.R-project.org/package=DoE.base + url_git: '' +DoE.MIParray: + version: 1.0-1 + title: Creation of Arrays by Mixed Integer Programming + maintainer: Ulrike Groemping + description: '''CRAN'' packages ''DoE.base'' and ''Rmosek'' and non-''CRAN'' package + ''gurobi'' are enhanced with functionality for the creation of optimized arrays + for experimentation, where optimization is in terms of generalized minimum aberration. + It is also possible to optimally extend existing arrays to larger run size. The + package writes ''MPS'' (Mathematical Programming System) files for use with any + mixed integer optimization software that can process such files. If at least one + of the commercial products ''Gurobi'' or ''Mosek'' (free academic licenses available + for both) is available, the package also creates arrays by optimization. For installing + ''Gurobi'' and its R package ''gurobi'', follow instructions at + and (or + higher version). For installing ''Mosek'' and its R package ''Rmosek'', follow + instructions at and , + or use the functionality in the stump CRAN R package ''Rmosek''.' + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DoE.MIParray + url_git: '' +DoE.wrapper: + version: '0.12' + title: Wrapper Package for Design of Experiments Functionality + maintainer: Ulrike Groemping + description: |- + Various kinds of designs for + (industrial) experiments can be created. The package uses, and sometimes enhances, + design generation routines from other packages. + So far, response surface designs from package 'rsm', Latin hypercube + samples from packages 'lhs' and 'DiceDesign', and + D-optimal designs from package 'AlgDesign' have been implemented. + date_publication: '2023-08-21' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/DoE/ + url_cran: https://CRAN.R-project.org/package=DoE.wrapper + url_git: '' +doebioresearch: + version: 0.1.0 + title: Analysis of Design of Experiments for Biological Research + maintainer: Raj Popat + description: Performs analysis of popular experimental designs used in the field + of biological research. The designs covered are completely randomized design, + randomized complete block design, factorial completely randomized design, factorial + randomized complete block design, split plot design, strip plot design and latin + square design. The analysis include analysis of variance, coefficient of determination, + normality test of residuals, standard error of mean, standard error of difference + and multiple comparison test of means. The package has functions for transformation + of data and yield data conversion. Some datasets are also added in order to facilitate + examples. + date_publication: '2020-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doebioresearch + url_git: '' +DOEM: + version: 0.0.0.1 + title: |- + The Distributed Online Expectation Maximization Algorithms to + Solve Parameters of Poisson Mixture Models + maintainer: Qian Wang + description: The distributed online expectation maximization algorithms are used + to solve parameters of Poisson mixture models. The philosophy of the package is + described in Guo, G. (2022) . + date_publication: '2022-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DOEM + url_git: '' +DoEstRare: + version: '0.2' + title: |- + Rare Variant Association Test Based on Position Density + Estimation + maintainer: Elodie Persyn + description: Rare variant association test integrating variant position information. + It aims to identify the presence of clusters of disease-risk variants in specific + gene regions. For more details, please read the publication from Persyn et al. + (2017) . + date_publication: '2017-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DoEstRare + url_git: '' +doex: + version: '1.2' + title: The One-Way Heteroscedastic ANOVA Tests + maintainer: Mustafa CAVUS + description: Contains the heteroscedastic ANOVA tests for normal and two-parameter + exponential distributed populations. For normal distributions, Alexander-Govern + test by Alexandern and Govern (1994) , Alvandi et al. Generalized + F test by Alvandi et al. (2012) , Approximate + F test by Asiribo and Gurland (1990) , Box F test + by Box (1954) , Brown-Forsythe test by Brown and + Forsythe (1974) , B2 test by Ozdemir and Kurt (2006) , + Cochran F test by Cochran (1937) , + Fiducial Approach test by Li et al. (2011) , Generalized + F test by Weerahandi (1995) , Johansen F test by Johansen + (1980) , Modified Brown-Forsythe test by Mehrotra + (1997) , Modified Welch test by Hartung et al.(2002) + , One-Stage test by Chen and Chen (1998) , + One-Stage Range test by Chen and Chen (2000) , + Parametric Bootstrap test by Krishnamoorhty et al.(2007) , + Permutation F test by Berry and Mielke (2002) , + Scott-Smith test by Scott and Smith (1971) , Welch test by + Welch(1951) , and Welch-Aspin test by Aspin (1948) . + These tests are used to test the equality of group means under unequal variance. + Also, a modified version of Generalized F-test is improved to test the equality + of non-normal group means under unequal variances and a revised version of Generalized + F-test is given to test the equality of non-normal group means caused by skewness. + Furthermore, it consists some procedures for testing equality of several two-parameter + exponentially distributed population means under unequal scale parameters such + as generalized p-value, parametric bootstrap and fiducial approach test by Malekzadeh + and Jafari (2019) . There is also Hsieh test + by Hsieh (1986) for testing equality of location parameters + of two-parameter exponentially distributed populations under unequal scale parameters. + date_publication: '2019-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doex + url_git: '' +doFuture: + version: 1.0.1 + title: Use Foreach to Parallelize via the Future Framework + maintainer: Henrik Bengtsson + description: The 'future' package provides a unifying parallelization framework + for R that supports many parallel and distributed backends. The 'foreach' package + provides a powerful API for iterating over an R expression in parallel. The 'doFuture' + package brings the best of the two together. There are two alternative ways to + use this package. The recommended approach is to use 'y <- foreach(...) %dofuture% + { ... }', which does not require using 'registerDoFuture()' and has many advantages + over '%dopar%'. The alternative is the traditional 'foreach' approach by registering + the 'foreach' adapter 'registerDoFuture()' and so that 'y <- foreach(...) %dopar% + { ... }' runs in parallelizes with the 'future' framework. + date_publication: '2023-12-20' + bug_reports: https://github.com/HenrikBengtsson/doFuture/issues + url: https://doFuture.futureverse.org + url_cran: https://CRAN.R-project.org/package=doFuture + url_git: https://github.com/HenrikBengtsson/doFuture +dogesr: + version: 0.5.0 + title: Work with the Doges/Dogaresse Dataset + maintainer: Juan Julián Merelo-Guervós + description: Work with data on Venetian doges and dogaresse and the noble families + of the Republic of Venice, and use it for social network analysis, as used in + Merelo (2022) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dogesr + url_git: '' +Dogoftest: + version: '0.1' + title: |- + Distributed Online Goodness-of-Fit Tests for Distributed + Datasets + maintainer: Guangbao Guo + description: Distributed Online Goodness-of-Fit Test can process the distributed datasets. + The philosophy of the package is described in Guo G.(2024) . + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dogoftest + url_git: '' +doMC: + version: 1.3.8 + title: Foreach Parallel Adaptor for 'parallel' + maintainer: Folashade Daniel + description: |- + Provides a parallel backend for the %dopar% function using + the multicore functionality of the parallel package. + date_publication: '2022-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doMC + url_git: '' +dominanceanalysis: + version: 2.1.0 + title: Dominance Analysis + maintainer: Claudio Bustos Navarrete + description: |- + Dominance analysis is a method that allows to compare the + relative importance of predictors in multiple regression models: + ordinary least squares, generalized linear models, + hierarchical linear models, beta regression and dynamic linear models. + The main principles and methods of + dominance analysis are described in + Budescu, D. V. (1993) and + Azen, R., & Budescu, D. V. (2003) + for ordinary least squares regression. Subsequently, the extensions + for multivariate regression, logistic regression and + hierarchical linear models were described in + Azen, R., & Budescu, D. V. (2006) , + Azen, R., & Traxel, N. (2009) and + Luo, W., & Azen, R. (2013) , + respectively. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dominanceanalysis + url_git: '' +domino: + version: 0.3.1 + title: R Console Bindings for the 'Domino Command-Line Client' + maintainer: Nick Elprin + description: |- + A wrapper on top of the 'Domino Command-Line Client'. It lets you + run 'Domino' commands (e.g., "run", "upload", "download") directly from your + R environment. Under the hood, it uses R's system function to run the 'Domino' + executable, which must be installed as a prerequisite. 'Domino' is a service + that makes it easy to run your code on scalable hardware, with integrated + version control and collaboration features designed for analytical workflows + (see for more information). + date_publication: '2017-11-22' + bug_reports: '' + url: http://www.dominodatalab.com + url_cran: https://CRAN.R-project.org/package=domino + url_git: '' +DominoDataR: + version: 0.2.3 + title: '''Domino Data R SDK''' + maintainer: Gabriel Haim + description: |- + A wrapper on top of the 'Domino Data Python SDK' library. It lets + you query and access 'Domino Data Sources' directly from your R environment. + Under the hood, 'Domino Data R SDK' leverages the API provided by the + 'Domino Data Python SDK', which must be installed as a prerequisite. + 'Domino' is a platform that makes it easy to run your code on scalable + hardware, with integrated version control and collaboration features + designed for analytical workflows. See + + for more information. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DominoDataR + url_git: https://github.com/dominodatalab/DominoDataR +domir: + version: 1.2.0 + title: Tools to Support Relative Importance Analysis + maintainer: Joseph Luchman + description: |- + Methods to apply decomposition-based relative importance + analysis for R functions. This package supports the application of + decomposition methods by providing 'lapply'- or 'Map'-like meta-functions that + compute dominance analysis (Azen, R., & Budescu, D. V. (2003) + ; Grömping, U. (2007) + ) an extension of Shapley value regression + (Lipovetsky, S., & Conklin, M. (2001) ) + based on the values returned from other functions. + date_publication: '2024-05-04' + bug_reports: https://github.com/jluchman/domir/issues + url: https://jluchman.github.io/domir/ + url_cran: https://CRAN.R-project.org/package=domir + url_git: https://github.com/jluchman/domir +doMPI: + version: 0.2.2 + title: Foreach Parallel Adaptor for the Rmpi Package + maintainer: Steve Weston + description: |- + Provides a parallel backend for the %dopar% function using + the Rmpi package. + date_publication: '2017-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doMPI + url_git: '' +donut: + version: 1.0.3 + title: Nearest Neighbour Search with Variables on a Torus + maintainer: Paul J. Northrop + description: |- + Finds the k nearest neighbours in a dataset of specified points, + adding the option to wrap certain variables on a torus. The user chooses + the algorithm to use to find the nearest neighbours. Two such algorithms, + provided by the packages 'RANN' , + and 'nabor' , are suggested. + date_publication: '2023-09-02' + bug_reports: https://github.com/paulnorthrop/donut/issues + url: https://paulnorthrop.github.io/donut/ + url_cran: https://CRAN.R-project.org/package=donut + url_git: https://github.com/paulnorthrop/donut +donutsk: + version: 0.1.1 + title: Construct Advanced Donut Charts + maintainer: Dmitry Kibalnikov + description: Build donut/pie charts with 'ggplot2' layer by layer, exploiting the + advantages of polar symmetry. Leverage layouts to distribute labels effectively. + Connect labels to donut segments using pins. Streamline annotation and highlighting. + date_publication: '2024-04-22' + bug_reports: https://github.com/dkibalnikov/donutsk/issues + url: https://dkibalnikov.github.io/donutsk/ + url_cran: https://CRAN.R-project.org/package=donutsk + url_git: https://github.com/dkibalnikov/donutsk +doofa: + version: '1.0' + title: Designs for Order-of-Addition Experiments + maintainer: Baidya Nath Mandal + description: |- + A facility to generate efficient designs for order-of-additions experiments under pair-wise-order model, see Dennis K. J. Lin and Jiayu Peng (2019)."Order-of-addition + experiments: A review and some new thoughts". Quality Engineering, 31:1, 49-59, . It also provides a facility to generate component + orthogonal arrays under component position model, see Jian-Feng Yang, Fasheng Sun & Hongquan Xu (2020): "A Component Position Model, Analysis and + Design for Order-of-Addition Experiments". Technometrics, . + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doofa + url_git: '' +doolkit: + version: 1.42.2 + title: Exploration of Dental Surface Topography + maintainer: Ghislain Thiery + description: |- + Tools for exploring the topography of 3d triangle meshes. + The functions were developed with dental surfaces in mind, but could be + applied to any triangle mesh of class 'mesh3d'. More specifically, 'doolkit' + allows to isolate the border of a mesh, or a subpart of the mesh using the + polygon networks method; crop a mesh; compute basic descriptors (elevation, + orientation, footprint area); compute slope, angularity and relief index + (Ungar and Williamson (2000) ; + Boyer (2008) ), inclination and occlusal + relief index or gamma (Guy et al. (2013) ), + OPC (Evans et al. (2007) ), OPCR (Wilson et al. + (2012) ), DNE (Bunn et al. (2011) ; + Pampush et al. (2016) ), form factor (Horton + (1932) ), basin elongation (Schum (1956) + ), lemniscate ratio + (Chorley et al; (1957) ), enamel-dentine distance + (Guy et al. (2015) ; Thiery et al. (2017) + ), absolute crown strength (Schwartz et al. + (2020) ), relief rate (Thiery et al. (2019) + ) and area-relative curvature; draw cumulative + profiles of a topographic variable; and map a variable over a 3d triangle + mesh. + date_publication: '2023-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doolkit + url_git: '' +doParabar: + version: 1.0.2 + title: '''foreach'' Parallel Adapter for ''parabar'' Backends' + maintainer: Mihai Constantin + description: |- + Provides a 'foreach' parallel adapter for 'parabar' backends. This + package offers a minimal implementation of the '%dopar%' operator, enabling + users to run 'foreach' loops in parallel, leveraging the parallel and + progress-tracking capabilities of the 'parabar' package. Learn more about + 'parabar' and 'doParabar' at . + date_publication: '2024-12-19' + bug_reports: https://github.com/mihaiconstantin/doParabar/issues + url: https://parabar.mihaiconstantin.com/articles/foreach + url_cran: https://CRAN.R-project.org/package=doParabar + url_git: https://github.com/mihaiconstantin/doParabar +doParallel: + version: 1.0.17 + title: Foreach Parallel Adaptor for the 'parallel' Package + maintainer: Folashade Daniel + description: |- + Provides a parallel backend for the %dopar% function using + the parallel package. + date_publication: '2022-02-07' + bug_reports: https://github.com/RevolutionAnalytics/doparallel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=doParallel + url_git: https://github.com/RevolutionAnalytics/doparallel +DOPE: + version: 2.1.0 + title: Drug Ontology Parsing Engine + maintainer: Raymond Balise + description: |- + Provides information on drug names (brand, + generic and street) for drugs tracked by the DEA. There are functions that + will search synonyms and return the drug names and types. The vignettes + have extensive information on the work done to create the data for the package. + date_publication: '2021-06-18' + bug_reports: https://github.com/CTN-0094/DOPE/issues + url: https://ctn-0094.github.io/DOPE/ + url_cran: https://CRAN.R-project.org/package=DOPE + url_git: https://github.com/CTN-0094/DOPE +doRedis: + version: 3.0.2 + title: '''Foreach'' Parallel Adapter Using the ''Redis'' Database' + maintainer: B. W. Lewis + description: Create and manage fault-tolerant task queues for the 'foreach' package + using the 'Redis' key/value database. + date_publication: '2023-05-02' + bug_reports: https://github.com/bwlewis/doRedis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=doRedis + url_git: '' +doremi: + version: 1.0.0 + title: Dynamics of Return to Equilibrium During Multiple Inputs + maintainer: Mongin Denis + description: |- + Provides models to fit the dynamics of a regulated system experiencing exogenous inputs. + The underlying models use differential equations and linear mixed-effects regressions to estimate the + coefficients of the equation. With them, the functions can provide an estimated signal. + The package provides simulation and analysis functions and also print, summary, plot and predict methods, + adapted to the function outputs, for easy implementation and presentation of results. + date_publication: '2021-01-29' + bug_reports: https://github.com/dcourvoisier/doremi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=doremi + url_git: https://github.com/dcourvoisier/doremi +doRNG: + version: 1.8.6.1 + title: Generic Reproducible Parallel Backend for 'foreach' Loops + maintainer: Renaud Gaujoux + description: |- + Provides functions to perform + reproducible parallel foreach loops, using independent + random streams as generated by L'Ecuyer's combined + multiple-recursive generator [L'Ecuyer (1999), ]. + It enables to easily convert standard '%dopar%' loops into + fully reproducible loops, independently of the number + of workers, the task scheduling strategy, or the chosen + parallel environment and associated foreach backend. + date_publication: '2025-01-13' + bug_reports: https://github.com/renozao/doRNG/issues + url: https://renozao.github.io/doRNG/ + url_cran: https://CRAN.R-project.org/package=doRNG + url_git: '' +DOS: + version: 1.0.0 + title: Design of Observational Studies + maintainer: Paul Rosenbaum + description: 'Contains data sets, examples and software from the book Design of + Observational Studies by Paul R. Rosenbaum, New York: Springer, , + ISBN 978-1-4419-1212-1.' + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DOS + url_git: '' +DOS2: + version: 0.5.2 + title: Design of Observational Studies, Companion to the Second Edition + maintainer: Paul Rosenbaum + description: Contains data sets, examples and software from the Second Edition of + "Design of Observational Studies"; see Rosenbaum, P.R. (2010) . + date_publication: '2019-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DOS2 + url_git: '' +dosearch: + version: 1.0.11 + title: |- + Causal Effect Identification from Multiple Incomplete Data + Sources + maintainer: Santtu Tikka + description: |- + Identification of causal effects from arbitrary observational and + experimental probability distributions via do-calculus and standard + probability manipulations using a search-based algorithm by + Tikka, Hyttinen and Karvanen (2021) . + Allows for the presence of mechanisms related to selection bias + (Bareinboim and Tian, 2015) , + transportability (Bareinboim and Pearl, 2014) + , + missing data (Mohan, Pearl, and Tian, 2013) + ) and arbitrary combinations + of these. Also supports identification in the presence of context-specific + independence (CSI) relations through labeled directed acyclic graphs + (LDAG). For details on CSIs see (Corander et al., 2019) + . + date_publication: '2024-07-16' + bug_reports: https://github.com/santikka/dosearch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dosearch + url_git: https://github.com/santikka/dosearch +dosedesignR: + version: 0.3.0 + title: Interactive Designing of Dose Finding Studies + maintainer: T. Schmelter + description: Provides the user with an interactive application which can be used + to facilitate the planning of dose finding studies by applying the theory of optimal + experimental design. + date_publication: '2023-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dosedesignR + url_git: '' +DoseFinding: + version: 1.2-1 + title: Planning and Analyzing Dose Finding Experiments + maintainer: Marius Thomas + description: |- + The DoseFinding package provides functions for the design and analysis + of dose-finding experiments (with focus on pharmaceutical Phase + II clinical trials). It provides functions for: multiple contrast + tests, fitting non-linear dose-response models (using Bayesian and + non-Bayesian estimation), calculating optimal designs and an + implementation of the MCPMod methodology (Pinheiro et al. (2014) + ). + date_publication: '2024-08-23' + bug_reports: https://github.com/openpharma/DoseFinding/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DoseFinding + url_git: https://github.com/openpharma/DoseFinding +doseminer: + version: 0.1.2 + title: Extract Drug Dosages from Free-Text Prescriptions + maintainer: David Selby + description: Utilities for converting unstructured electronic prescribing instructions + into structured medication data. Extracts drug dose, units, daily dosing frequency + and intervals from English-language prescriptions. Based on Karystianis et al. + (2015) . + date_publication: '2021-07-19' + bug_reports: https://github.com/Selbosh/doseminer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=doseminer + url_git: '' +doseSens: + version: 0.1.0 + title: |- + Conduct Sensitivity Analysis with Continuous Exposures and + Binary Outcomes + maintainer: Jeffrey Zhang + description: Performs sensitivity analysis for the sharp null and attributable effects + in matched studies with continuous exposures and binary outcomes as described + in Zhang, Small, Heng (2024) . Two of the functions require + installation of the 'Gurobi' optimizer. Please see + for guidance. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doseSens + url_git: '' +doSNOW: + version: 1.0.20 + title: Foreach Parallel Adaptor for the 'snow' Package + maintainer: Folashade Daniel + description: |- + Provides a parallel backend for the %dopar% function using + the snow package of Tierney, Rossini, Li, and Sevcikova. + date_publication: '2022-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doSNOW + url_git: '' +DOSPortfolio: + version: 0.1.0 + title: Dynamic Optimal Shrinkage Portfolio + maintainer: Erik Thorsén + description: |2- + + Constructs dynamic optimal shrinkage estimators for the weights of the global + minimum variance portfolio which are reconstructed at given reallocation + points as derived in Bodnar, Parolya, and Thorsén (2021) (). + Two dynamic shrinkage estimators are available in this package. One using + overlapping samples while the other use nonoverlapping samples. + date_publication: '2021-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DOSPortfolio + url_git: https://github.com/Statistics-In-Portfolio-Theory/DOSportfolio +dosresmeta: + version: 2.0.1 + title: Multivariate Dose-Response Meta-Analysis + maintainer: Alessio Crippa + description: |- + Estimates dose-response relations from summarized dose-response + data and to combines them according to principles of (multivariate) + random-effects models. + date_publication: '2017-09-12' + bug_reports: https://github.com/alecri/dosresmeta/issues + url: https://alecri.github.io/software/dosresmeta.html + url_cran: https://CRAN.R-project.org/package=dosresmeta + url_git: '' +dostats: + version: 1.3.3 + title: Compute Statistics Helper Functions + maintainer: Andrew Redd + description: |- + A small package containing helper utilities for creating functions + for computing statistics. + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dostats + url_git: https://github.com/halpo/dostats +DOT: + version: '0.1' + title: Render and Export DOT Graphs in R + maintainer: E. F. Haghish + description: |- + Renders DOT diagram markup language in R and also provides the possibility to + export the graphs in PostScript and SVG (Scalable Vector Graphics) formats. + In addition, it supports literate programming packages such as 'knitr' and + 'rmarkdown'. + date_publication: '2016-04-16' + bug_reports: http://github.com/haghish/DOT + url: http://haghish.com/dot + url_cran: https://CRAN.R-project.org/package=DOT + url_git: '' +dotCall64: + version: '1.2' + title: Enhanced Foreign Function Interface Supporting Long Vectors + maintainer: Reinhard Furrer + description: |- + Provides .C64(), which is an enhanced version of .C() + and .Fortran() from the foreign function interface. .C64() supports long + vectors, arguments of type 64-bit integer, and provides a mechanism to + avoid unnecessary copies of read-only and write-only arguments. This + makes it a convenient and fast interface to C/C++ and Fortran code. + date_publication: '2024-10-04' + bug_reports: https://git.math.uzh.ch/reinhard.furrer/dotCall64/-/issues + url: https://git.math.uzh.ch/reinhard.furrer/dotCall64 + url_cran: https://CRAN.R-project.org/package=dotCall64 + url_git: '' +dotenv: + version: 1.0.3 + title: Load Environment Variables from '.env' + maintainer: Gábor Csárdi + description: |- + Load configuration from a '.env' file, that is + in the current working directory, into environment variables. + date_publication: '2021-04-22' + bug_reports: https://github.com/gaborcsardi/dotenv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dotenv + url_git: https://github.com/gaborcsardi/dotenv +dotgen: + version: 0.1.1 + title: Gene-Set Analysis via Decorrelation by Orthogonal Transformation + maintainer: Xiaoran Tong + description: Decorrelates a set of summary statistics (i.e., Z-scores or P-values + per SNP) via Decorrelation by Orthogonal Transformation (DOT) approach and performs + gene-set analyses by combining transformed statistic values; operations are performed + with algorithms that rely only on the association summary results and the linkage + disequilibrium (LD). For more details on DOT and its power, see Olga (2020) . + date_publication: '2024-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dotgen + url_git: https://github.com/xiaoran831213/dotgen +dotprofile: + version: 0.0.1 + title: Create and Manage Configuration Profiles + maintainer: Jean-Mathieu Potvin + description: |- + A toolbox to create and manage metadata files and + configuration profiles: files used to configure the parameters and + initial settings for some computer programs. + date_publication: '2021-11-23' + bug_reports: https://github.com/jeanmathieupotvin/dotprofile/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=dotprofile + url_git: https://github.com/jeanmathieupotvin/dotprofile +dots: + version: 0.0.2 + title: Dot Density Maps + maintainer: Christopher T. Kenny + description: |- + Generate point data for representing people within spatial data. This + collects a suite of tools for creating simple dot density maps. Several functions + from different spatial packages are standardized to take the same arguments so + that they can be easily substituted for each other. + date_publication: '2022-07-15' + bug_reports: https://github.com/christopherkenny/dots/issues + url: http://christophertkenny.com/dots/ + url_cran: https://CRAN.R-project.org/package=dots + url_git: https://github.com/christopherkenny/dots +dotsViolin: + version: 0.0.1 + title: Dot Plots Mimicking Violin Plots + maintainer: Fernando Roa + description: |- + Modifies dot plots to have different sizes of dots mimicking violin plots and identifies + modes or peaks for them based on frequency and kernel density estimates + (Rosenblatt, 1956) (Parzen, 1962) . + date_publication: '2023-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dotsViolin + url_git: '' +dotty: + version: 0.1.0 + title: The Unpacking Dot Operator + maintainer: Kevin Ushey + description: |- + Provides a `.` object which can be used for unpacking + assignments. For example, `.[rows, columns] <- dim(cars)` could be used to + pull the number of rows and number of columns from `dim(cars)` into + individual variables `rows` and `columns` in a single step. + date_publication: '2024-08-30' + bug_reports: '' + url: https://kevinushey.github.io/dotty/ + url_cran: https://CRAN.R-project.org/package=dotty + url_git: '' +dotwhisker: + version: 0.8.3 + title: Dot-and-Whisker Plots of Regression Results + maintainer: Yue Hu + description: Create quick and easy dot-and-whisker plots of regression results. + It takes as input either (1) a coefficient table in standard form or (2) one (or + a list of) fitted model objects (of any type that has methods implemented in the + 'parameters' package). It returns 'ggplot' objects that can be further customized + using tools from the 'ggplot2' package. The package also includes helper functions + for tasks such as rescaling coefficients or relabeling predictor variables. See + more methodological discussion of the visualization and data management methods + used in this package in Kastellec and Leoni (2007) + and Gelman (2008) . + date_publication: '2024-09-27' + bug_reports: https://github.com/fsolt/dotwhisker/issues + url: https://fsolt.org/dotwhisker/ + url_cran: https://CRAN.R-project.org/package=dotwhisker + url_git: '' +doubcens: + version: '1.1' + title: |- + Survivor Function Estimation for Doubly Interval-Censored + Failure Time Data + maintainer: James McVittie + description: Contains the discrete nonparametric survivor function estimation algorithm + of De Gruttola and Lagakos for doubly interval-censored failure time data and + the discrete nonparametric survivor function estimation algorithm of Sun for doubly + interval-censored left-truncated failure time data [Victor De Gruttola & Stephen + W. Lagakos (1989) ] [Jianguo Sun (1995) ]. + date_publication: '2017-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doubcens + url_git: '' +double.truncation: + version: '1.8' + title: Analysis of Doubly-Truncated Data + maintainer: Takeshi Emura + description: |- + Likelihood-based inference methods with doubly-truncated data are developed under various models. + Nonparametric models are based on Efron and Petrosian (1999) and + Emura, Konno, and Michimae (2015) . + Parametric models from the special exponential family (SEF) are based on + Hu and Emura (2015) and + Emura, Hu and Konno (2017) . + The parametric location-scale models are based on Dorre et al. (2021) . + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=double.truncation + url_git: '' +DoubleCone: + version: '1.1' + title: Test Against Parametric Regression Function + maintainer: Mary C Meyer + description: Performs hypothesis tests concerning a regression function in a least-squares + model, where the null is a parametric function, and the alternative is the union + of large-dimensional convex polyhedral cones. See Bodhisattva Sen and Mary C Meyer + (2016) for more details. + date_publication: '2017-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DoubleCone + url_git: '' +DoubleExpSeq: + version: '1.1' + title: |- + Differential Exon Usage Test for RNA-Seq Data via Empirical + Bayes Shrinkage of the Dispersion Parameter + maintainer: Sean Ruddy + description: Differential exon usage test for RNA-Seq data via an empirical Bayes + shrinkage method for the dispersion parameter the utilizes inclusion-exclusion + data to analyze the propensity to skip an exon across groups. The input data consists + of two matrices where each row represents an exon and the columns represent the + biological samples. The first matrix is the count of the number of reads expressing + the exon for each sample. The second matrix is the count of the number of reads + that either express the exon or explicitly skip the exon across the samples, a.k.a. + the total count matrix. Dividing the two matrices yields proportions representing + the propensity to express the exon versus skipping the exon for each sample. + date_publication: '2015-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DoubleExpSeq + url_git: '' +DoubleML: + version: 1.0.1 + title: Double Machine Learning in R + maintainer: Philipp Bach + description: |- + Implementation of the double/debiased machine learning framework of + Chernozhukov et al. (2018) for partially linear + regression models, partially linear instrumental variable regression models, + interactive regression models and interactive instrumental variable + regression models. 'DoubleML' allows estimation of the nuisance parts in + these models by machine learning methods and computation of the Neyman + orthogonal score functions. 'DoubleML' is built on top of 'mlr3' and the + 'mlr3' ecosystem. The object-oriented implementation of 'DoubleML' based on + the 'R6' package is very flexible. More information available in the + publication in the Journal of Statistical Software: . + date_publication: '2024-06-05' + bug_reports: https://github.com/DoubleML/doubleml-for-r/issues + url: https://docs.doubleml.org/stable/index.html + url_cran: https://CRAN.R-project.org/package=DoubleML + url_git: https://github.com/DoubleML/doubleml-for-r/ +doublIn: + version: 0.2.0 + title: |- + Estimate Incubation or Latency Time using Doubly Interval + Censored Observations + maintainer: Vera Arntzen + description: Visualize contact tracing data using a 'shiny' app and estimate the + incubation or latency time of an infectious disease respecting the following characteristics + in the analysis; (i) doubly interval censoring with (partly) overlapping or distinct + windows; (ii) an infection risk corresponding to exponential growth; (iii) right + truncation allowing for individual truncation times; (iv) different choices concerning + the family of the distribution. For our earlier work, we refer to Arntzen et al. + (2023) . A paper describing our approach in detail will + follow. + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doublIn + url_git: '' +doubt: + version: 0.1.0 + title: Enable Operators Containing the '?' Symbol + maintainer: Antoine Fabri + description: |- + Overload utils::'?' to build unary and binary operators from existing functions, + piping operators of different precedence, and flexible syntaxes. + date_publication: '2020-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doubt + url_git: '' +douconca: + version: 1.2.2 + title: |- + Double Constrained Correspondence Analysis for Trait-Environment + Analysis in Ecology + maintainer: Bart-Jan van Rossum + description: |- + Double constrained correspondence analysis (dc-CA) analyzes + (multi-)trait (multi-)environment ecological data by using the 'vegan' + package and native R code. Throughout the two step algorithm of ter Braak + et al. (2018) is used. This algorithm combines and extends community- + (sample-) and species-level analyses, i.e. the usual community weighted + means (CWM)-based regression analysis and the species-level analysis of + species-niche centroids (SNC)-based regression analysis. The two steps use + canonical correspondence analysis to regress the abundance data on to the + traits and (weighted) redundancy analysis to regress the CWM of the + orthonormalized traits on to the environmental predictors. The function + dc_CA() has an option to divide the abundance data of a site by the site + total, giving equal site weights. This division has the advantage that the + multivariate analysis corresponds with an unweighted (multi-trait) + community-level analysis, instead of being weighted. The first step of + the algorithm uses vegan::cca(). The second step uses wrda() but + vegan::rda() if the site weights are equal. This version has a predict() + function. For details see ter Braak et al. 2018 + . + date_publication: '2024-12-02' + bug_reports: https://github.com/Biometris/douconca/issues + url: https://zenodo.org/records/13970152 + url_cran: https://CRAN.R-project.org/package=douconca + url_git: https://github.com/Biometris/douconca +doudpackage: + version: 2.1.0 + title: Create Elegant Table 1 in HTML for Bio-Statistics + maintainer: Edouard Baudouin + description: |- + Creates the "table one" of bio-medical papers. Fill it with your data and the name of the variable which you'll make the group(s) out of and it will make univariate, bivariate analysis and parse it into HTML. + It also allows you to visualize all your data with graphic representation. + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=doudpackage + url_git: '' +DOvalidation: + version: 1.1.0 + title: |- + Kernel Hazard Estimation with Best One-Sided and Double + One-Sided Cross-Validation + maintainer: Maria Dolores Martinez-Miranda + description: 'Local linear hazard estimator and its multiplicatively bias correction, + including three bandwidth selection methods: best one-sided cross-validation, + double one-sided cross-validation, and standard cross-validation.' + date_publication: '2017-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DOvalidation + url_git: '' +DOVE: + version: '1.10' + title: Durability of Vaccine Efficacy + maintainer: Shannon T. Holloway + description: |- + Implements maximum likelihood methods for + evaluating the durability of vaccine efficacy in a randomized, + placebo-controlled clinical trial with staggered enrollment of participants + and potential crossover of placebo recipients before the end of the trial. + Lin, D. Y., Zeng, D., and Gilbert, P. B. (2021) + + and + Lin, D. Y., Gu, Y., Zeng, D., Janes, H. E., and Gilbert, P. B. (2021) + . + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DOVE + url_git: '' +Dowd: + version: '0.12' + title: |- + Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's + Book Measuring Market Risk + maintainer: Dinesh Acharya + description: |- + 'Kevin Dowd's' book Measuring Market Risk is a widely read book + in the area of risk measurement by students and + practitioners alike. As he claims, 'MATLAB' indeed might have been the most + suitable language when he originally wrote the functions, but, + with growing popularity of R it is not entirely + valid. As 'Dowd's' code was not intended to be error free and were mainly + for reference, some functions in this package have inherited those + errors. An attempt will be made in future releases to identify and correct + them. 'Dowd's' original code can be downloaded from www.kevindowd.org/measuring-market-risk/. + It should be noted that 'Dowd' offers both + 'MMR2' and 'MMR1' toolboxes. Only 'MMR2' was ported to R. 'MMR2' is more + recent version of 'MMR1' toolbox and they both have mostly similar + function. The toolbox mainly contains different parametric and non + parametric methods for measurement of market risk as well as + backtesting risk measurement methods. + date_publication: '2016-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dowd + url_git: '' +downlit: + version: 0.4.4 + title: Syntax Highlighting and Automatic Linking + maintainer: Hadley Wickham + description: |- + Syntax highlighting of R code, specifically designed for the + needs of 'RMarkdown' packages like 'pkgdown', 'hugodown', and + 'bookdown'. It includes linking of function calls to their + documentation on the web, and automatic translation of ANSI escapes in + output to the equivalent HTML. + date_publication: '2024-06-10' + bug_reports: https://github.com/r-lib/downlit/issues + url: https://downlit.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=downlit + url_git: https://github.com/r-lib/downlit +downloader: + version: '0.4' + title: Download Files over HTTP and HTTPS + maintainer: Winston Chang + description: |- + Provides a wrapper for the download.file function, + making it possible to download files over HTTPS on Windows, Mac OS X, and + other Unix-like platforms. The 'RCurl' package provides this functionality + (and much more) but can be difficult to install because it must be compiled + with external dependencies. This package has no external dependencies, so + it is much easier to install. + date_publication: '2015-07-09' + bug_reports: https://github.com/wch/downloader/issues + url: '' + url_cran: https://CRAN.R-project.org/package=downloader + url_git: https://github.com/wch/downloader +downloadthis: + version: 0.4.1 + title: Implement Download Buttons in 'rmarkdown' + maintainer: Felipe Mattioni Maturana + description: Implement download buttons in HTML output from 'rmarkdown' without + the need for 'runtime:shiny'. + date_publication: '2024-10-14' + bug_reports: https://github.com/fmmattioni/downloadthis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=downloadthis + url_git: https://github.com/fmmattioni/downloadthis +downscale: + version: 5.0.0 + title: Downscaling Species Occupancy + maintainer: Charles Marsh + description: Uses species occupancy at coarse grain sizes to predict species occupancy + at fine grain sizes. Ten models are provided to fit and extrapolate the occupancy-area + relationship, as well as methods for preparing atlas data for modelling. See Marsh + et. al. (2018) . + date_publication: '2023-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=downscale + url_git: https://github.com/charliem2003/downscale +downsize: + version: 0.2.3 + title: A Tool to Downsize Large Analysis Projects for Testing + maintainer: William Michael Landau + description: |- + Toggles the test and production versions of a large + data analysis project. + date_publication: '2023-03-16' + bug_reports: https://github.com/wlandau/downsize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=downsize + url_git: https://github.com/wlandau/downsize +dowser: + version: '2.3' + title: B Cell Receptor Phylogenetics Toolkit + maintainer: Kenneth Hoehn + description: |- + Provides a set of functions for inferring, visualizing, and analyzing B cell phylogenetic trees. + Provides methods to 1) reconstruct unmutated ancestral sequences, + 2) build B cell phylogenetic trees using multiple methods, + 3) visualize trees with metadata at the tips, + 4) reconstruct intermediate sequences, + 5) detect biased ancestor-descendant relationships among metadata types + Workflow examples available at documentation site (see URL). + Citations: + Hoehn et al (2022) , + Hoehn et al (2021) . + date_publication: '2024-10-22' + bug_reports: https://bitbucket.org/kleinstein/dowser/issues + url: https://dowser.readthedocs.io + url_cran: https://CRAN.R-project.org/package=dowser + url_git: '' +DOYPAColors: + version: 0.0.2 + title: Don't Overthink Your Palette of Colors + maintainer: Jorge Mestre + description: |- + Access diverse 'ggplot2'-compatible color palettes for + simplified data visualization. + date_publication: '2024-09-03' + bug_reports: https://github.com/jmestret/DOYPAColors/issues + url: https://jmestret.github.io/DOYPAColors/ + url_cran: https://CRAN.R-project.org/package=DOYPAColors + url_git: https://github.com/jmestret/DOYPAColors +dparser: + version: 1.3.1-13 + title: Port of 'Dparser' Package + maintainer: Matthew Fidler + description: |- + A Scannerless GLR parser/parser generator. Note that GLR standing for "generalized LR", where L stands for "left-to-right" and + R stands for "rightmost (derivation)". For more information see . This parser is based on the Tomita + (1987) algorithm. (Paper can be found at ). + The original 'dparser' package documentation can be found at . This allows you to add mini-languages to R (like + rxode2's ODE mini-language Wang, Hallow, and James 2015 ) or to parse other languages like 'NONMEM' to automatically translate + them to R code. To use this in your code, add a LinkingTo dparser in your DESCRIPTION file and instead of using #include use + #include . This also provides a R-based port of the make_dparser command called + mkdparser(). Additionally you can parse an arbitrary grammar within R using the dparse() function, which works on most OSes and is mainly for grammar + testing. The fastest parsing, of course, occurs at the C level, and is suggested. + date_publication: '2024-10-22' + bug_reports: https://github.com/nlmixr2/dparser-R/issues/ + url: https://nlmixr2.github.io/dparser-R/ + url_cran: https://CRAN.R-project.org/package=dparser + url_git: https://github.com/nlmixr2/dparser-R/ +dpasurv: + version: 0.1.0 + title: |- + Dynamic Path Analysis of Survival Data via Aalen's Additive + Hazards Model + maintainer: Matthias Kormaksson + description: Dynamic path analysis with estimation of the corresponding direct, + indirect, and total effects, based on Fosen et al., (2006) . + The main outcome of interest is a counting process from survival analysis (or + recurrent events) data. At each time of event, ordinary linear regression is used + to estimate the relation between the covariates, while Aalen's additive hazard + model is used for the regression of the counting process on the covariates. + date_publication: '2024-09-02' + bug_reports: '' + url: http://opensource.nibr.com/dpasurv/ + url_cran: https://CRAN.R-project.org/package=dpasurv + url_git: '' +DPBBM: + version: 0.2.5 + title: Dirichlet Process Beta-Binomial Mixture + maintainer: Lin Zhang + description: |- + Beta-binomial Mixture Model is used to infer the pattern from count data. + It can be used for clustering of RNA methylation sequencing data. + date_publication: '2016-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DPBBM + url_git: '' +dpcc: + version: 1.0.0 + title: Dynamic Programming for Convex Clustering + maintainer: Bingyuan Zhang + description: Use dynamic programming method to solve l1 convex clustering with identical + weights. + date_publication: '2021-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dpcc + url_git: '' +dPCP: + version: 2.0.1 + title: Automated Analysis of Multiplex Digital PCR Data + maintainer: Alfonso De Falco + description: |- + The automated clustering and quantification of the digital PCR + data is based on the combination of 'DBSCAN' (Hahsler et al. (2019) + ) and 'c-means' (Bezdek et al. (1981) + ) algorithms. + The analysis is independent of multiplexing geometry, dPCR system, + and input amount. + The details about input data and parameters are available in the + vignette. + date_publication: '2023-08-12' + bug_reports: https://github.com/alfodefalco/dPCP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dPCP + url_git: https://github.com/alfodefalco/dPCP +Dpit: + version: '1.0' + title: Distribution Pitting + maintainer: Harry Joo + description: 'Compares distributions with one another in terms of their fit to each + sample in a dataset that contains multiple samples, as described in Joo, Aguinis, + and Bradley (in press). Users can examine the fit of seven distributions per sample: + pure power law, lognormal, exponential, power law with an exponential cutoff, + normal, Poisson, and Weibull. Automation features allow the user to compare all + distributions for all samples with a single command line, which creates a separate + row containing results for each sample until the entire dataset has been analyzed.' + date_publication: '2017-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dpit + url_git: '' +dpkg: + version: 0.6.1 + title: Create, Stow, and Read Data Packages + maintainer: Cole Brokamp + description: Data frame, tibble, or tbl objects are converted to data package objects + using specific metadata labels (name, version, title, homepage, description). + A data package object ('dpkg') can be written to disk as a 'parquet' file or released + to a 'GitHub' repository. Data package objects can be read into R from online + repositories and downloaded files are cached locally across R sessions. + date_publication: '2025-01-08' + bug_reports: https://github.com/cole-brokamp/dpkg/issues + url: https://cole-brokamp.github.io/dpkg/ + url_cran: https://CRAN.R-project.org/package=dpkg + url_git: https://github.com/cole-brokamp/dpkg +dplR: + version: 1.7.8 + title: Dendrochronology Program Library in R + maintainer: Andy Bunn + description: |- + Perform tree-ring analyses such as detrending, chronology + building, and cross dating. Read and write standard file formats + used in dendrochronology. + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dplR + url_git: https://github.com/OpenDendro/dplR +dplyr: + version: 1.1.4 + title: A Grammar of Data Manipulation + maintainer: Hadley Wickham + description: |- + A fast, consistent tool for working with data frame like + objects, both in memory and out of memory. + date_publication: '2023-11-17' + bug_reports: https://github.com/tidyverse/dplyr/issues + url: https://dplyr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=dplyr + url_git: https://github.com/tidyverse/dplyr +dplyrAssist: + version: 0.1.0 + title: |- + RStudio Addin for Teaching and Learning Data Manipulation Using + 'dplyr' + maintainer: Keon-Woong Moon + description: |- + An RStudio addin for teaching and learning data manipulation using the 'dplyr' package. + You can learn each steps of data manipulation by clicking your mouse without coding. + You can get resultant data (as a 'tibble') and the code for data manipulation. + date_publication: '2017-09-04' + bug_reports: https://github.com/cardiomoon/dplyrAssist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dplyrAssist + url_git: https://github.com/cardiomoon/dplyrAssist +dpm: + version: 1.2.0 + title: Dynamic Panel Models Fit with Maximum Likelihood + maintainer: Jacob A. Long + description: |- + Implements the dynamic panel models described by Allison, Williams, + and Moral-Benito (2017 ) in R. + This class of models uses structural equation modeling to specify dynamic + (lagged dependent variable) models with fixed effects for panel data. + Additionally, models may have predictors that are only weakly exogenous, i.e., + are affected by prior values of the dependent variable. Options also allow for + random effects, dropping the lagged dependent variable, and a number of other + specification choices. + date_publication: '2024-01-16' + bug_reports: https://github.com/jacob-long/dpm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dpm + url_git: https://github.com/jacob-long/dpm +dpmr: + version: 0.1.9 + title: Data Package Manager for R + maintainer: Christopher Gandrud + description: |- + Create, install, and summarise data packages that follow + the Open Knowledge Foundation's Data Package Protocol. + date_publication: '2016-03-07' + bug_reports: https://github.com/christophergandrud/dpmr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dpmr + url_git: '' +DPP: + version: 0.1.2 + title: |- + Inference of Parameters of Normal Distributions from a Mixture + of Normals + maintainer: Luis M. Avila + description: |- + This MCMC method takes a data numeric vector (Y) and assigns the elements of Y + to a (potentially infinite) number of normal distributions. The individual normal distributions from a mixture of normals can be inferred. + Following the method described in Escobar (1994) we use a Dirichlet Process Prior (DPP) to describe stochastically our prior assumptions about the dimensionality of the data. + date_publication: '2018-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DPP + url_git: '' +DPpack: + version: 0.2.2 + title: Differentially Private Statistical Analysis and Machine Learning + maintainer: Spencer Giddens + description: |- + An implementation of common statistical analysis and models with + differential privacy (Dwork et al., 2006a) + guarantees. The package contains, for example, functions providing + differentially private computations of mean, variance, median, histograms, + and contingency tables. It also implements some statistical models and + machine learning algorithms such as linear regression (Kifer et al., 2012) + + and SVM (Chaudhuri et al., 2011) + . In addition, it implements + some popular randomization mechanisms, including + the Laplace mechanism (Dwork et al., 2006a) + , Gaussian mechanism (Dwork et al., 2006b) + , analytic Gaussian mechanism (Balle & Wang, 2018) + , and exponential mechanism + (McSherry & Talwar, 2007) . + date_publication: '2024-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DPpack + url_git: '' +dppmix: + version: 0.1.1 + title: Determinantal Point Process Mixture Models + maintainer: David J. H. Shih + description: |- + Multivariate Gaussian mixture model with a determinant point + process prior to promote the discovery of parsimonious components from + observed data. See Xu, Mueller, Telesca (2016) . + date_publication: '2020-01-14' + bug_reports: https://bitbucket.org/djhshih/dppmix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dppmix + url_git: https://bitbucket.org/djhshih/dppmix +DPQ: + version: 0.5-9 + title: Density, Probability, Quantile ('DPQ') Computations + maintainer: Martin Maechler + description: |- + Computations for approximations and alternatives for the 'DPQ' + (Density (pdf), Probability (cdf) and Quantile) functions for probability + distributions in R. + Primary focus is on (central and non-central) beta, gamma and related + distributions such as the chi-squared, F, and t. + -- + For several distribution functions, provide functions implementing formulas from + Johnson, Kotz, and Kemp (1992) and + Johnson, Kotz, and Balakrishnan (1995) for discrete or continuous + distributions respectively. + This is for the use of researchers in these numerical approximation + implementations, notably for my own use in order to improve standard + R pbeta(), qgamma(), ..., etc: {'"dpq"'-functions}. + date_publication: '2024-08-23' + bug_reports: https://r-forge.r-project.org/tracker/?atid=2462&group_id=611 + url: '' + url_cran: https://CRAN.R-project.org/package=DPQ + url_git: https://specfun.r-forge.r-project.org/ +DPQmpfr: + version: 0.3-3 + title: |- + DPQ (Density, Probability, Quantile) Distribution Computations + using MPFR + maintainer: Martin Maechler + description: |- + An extension to the 'DPQ' package with computations for 'DPQ' + (Density (pdf), Probability (cdf) and Quantile) functions, where + the functions here partly use the 'Rmpfr' package and hence the + underlying 'MPFR' and 'GMP' C libraries. + date_publication: '2024-08-19' + bug_reports: https://r-forge.r-project.org/tracker/?atid=2462&group_id=611 + url: '' + url_cran: https://CRAN.R-project.org/package=DPQmpfr + url_git: https://specfun.r-forge.r-project.org/ +dprop: + version: 0.1.0 + title: Computation of Some Important Distributional Properties + maintainer: Muhammad Imran + description: Generally, most of the packages specify the probability density function, + cumulative distribution function, quantile function, and random numbers generation + of the probability distributions. The present package allows to compute some important + distributional properties, including the first four ordinary and central moments, + Pearson's coefficient of skewness and kurtosis, the mean and variance, coefficient + of variation, median, and quartile deviation at some parametric values of several + well-known and extensively used probability distributions. + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dprop + url_git: '' +dpseg: + version: 0.1.1 + title: Piecewise Linear Segmentation by Dynamic Programming + maintainer: Rainer Machne + description: |- + Piecewise linear segmentation of ordered data by a + dynamic programming algorithm. The algorithm was developed for time + series data, e.g. growth curves, and for genome-wide read-count data + from next generation sequencing, but is broadly applicable. + Generic implementations of dynamic programming routines allow + to scan for optimal segmentation parameters and test custom + segmentation criteria ("scoring functions"). + date_publication: '2020-08-17' + bug_reports: https://gitlab.com/raim/dpseg/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dpseg + url_git: https://gitlab.com/raim/dpseg/ +DPTM: + version: 1.6.0 + title: Dynamic Panel Multiple Threshold Model with Fixed Effects + maintainer: Bai Hujie + description: Compute the fixed effects dynamic panel threshold model suggested by + Ramírez-Rondán (2020) , and dynamic panel linear + model suggested by Hsiao et al. (2002) , where + maximum likelihood type estimators are used. Multiple threshold estimation based + on Markov Chain Monte Carlo (MCMC) is allowed, and model selection of linear model, + threshold model and multiple threshold model is also allowed. + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DPTM + url_git: https://github.com/HujieBai/DPTM +DPtree: + version: 1.0.1 + title: Dirichlet-Based Polya Tree + maintainer: Shaoyang Ning + description: |- + Contains functions to perform copula estimation + by the non-parametric Bayesian method, + Dirichlet-based Polya Tree. See Ning (2018) . + date_publication: '2018-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DPtree + url_git: '' +DQAgui: + version: 0.2.6 + title: Graphical User Interface for Data Quality Assessment + maintainer: Lorenz A. Kapsner + description: |- + A graphical user interface (GUI) to the functions implemented + in the R package 'DQAstats'. Publication: Mang et al. (2021) + . + date_publication: '2025-02-07' + bug_reports: https://github.com/miracum/dqa-dqagui/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DQAgui + url_git: https://github.com/miracum/dqa-dqagui +DQAstats: + version: 0.3.7 + title: Core Functions for Data Quality Assessment + maintainer: Lorenz A. Kapsner + description: |- + Perform data quality assessment ('DQA') of electronic health + records ('EHR'). Publication: Kapsner et al. (2021) + . + date_publication: '2025-02-07' + bug_reports: https://github.com/miracum/dqa-dqastats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DQAstats + url_git: https://github.com/miracum/dqa-dqastats +dqrng: + version: 0.4.1 + title: Fast Pseudo Random Number Generators + maintainer: Ralf Stubner + description: |- + Several fast random number generators are provided as C++ + header only libraries: The PCG family by O'Neill (2014 + ) as well as + the Xoroshiro / Xoshiro family by Blackman and Vigna (2021 + ). In addition fast functions for generating random + numbers according to a uniform, normal and exponential distribution + are included. The latter two use the Ziggurat algorithm originally + proposed by Marsaglia and Tsang (2000, ). + The fast sampling methods support unweighted sampling both with and without + replacement. These functions are exported to R and as a C++ interface and are + enabled for use with the default 64 bit generator from the PCG family, + Xoroshiro128+/++/** and Xoshiro256+/++/** as well as the 64 bit version of the + 20 rounds Threefry engine (Salmon et al., 2011, ) + as provided by the package 'sitmo'. + date_publication: '2024-05-28' + bug_reports: https://github.com/daqana/dqrng/issues + url: https://daqana.github.io/dqrng/ + url_cran: https://CRAN.R-project.org/package=dqrng + url_git: https://github.com/daqana/dqrng +dQTG.seq: + version: 1.0.2 + title: |- + A BSA Software for Detecting All Types of QTLs in BC, DH, RIL + and F2 + maintainer: Yuan-Ming Zhang + description: 'The new (dQTG.seq1 and dQTG.seq2) and existing (SmoothLOD, G'', deltaSNP + and ED) bulked segregant analysis methods are used to identify various types of + quantitative trait loci for complex traits via extreme phenotype individuals in + bi-parental segregation populations (F2, backcross, doubled haploid and recombinant + inbred line). The numbers of marker alleles in extreme low and high pools are + used in existing methods to identify trait-related genes, while the numbers of + marker alleles and genotypes in extreme low and high pools are used in the new + methods to construct a new statistic Gw for identifying trait-related genes. dQTG-seq2 + is feasible to identify extremely over-dominant and small-effect genes in F2. + Li P, Li G, Zhang YW, Zuo JF, Liu JY, Zhang YM (2022, ).' + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dQTG.seq + url_git: '' +dr: + version: 3.0.10 + title: Methods for Dimension Reduction for Regression + maintainer: Sanford Weisberg + description: |- + Functions, methods, and datasets for fitting dimension + reduction regression, using slicing (methods SAVE and SIR), Principal + Hessian Directions (phd, using residuals and the response), and an + iterative IRE. Partial methods, that condition on categorical + predictors are also available. A variety of tests, and stepwise + deletion of predictors, is also included. Also included is + code for computing permutation tests of dimension. Adding additional + methods of estimating dimension is straightforward. + For documentation, see the vignette in the package. With version 3.0.4, + the arguments for dr.step have been modified. + date_publication: '2015-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dr + url_git: '' +DR.SC: + version: '3.4' + title: Joint Dimension Reduction and Spatial Clustering + maintainer: Wei Liu + description: |- + Joint dimension reduction and spatial clustering is conducted for + Single-cell RNA sequencing and spatial transcriptomics data, and more details can be referred to + Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou, Xingjie Shi and Jin Liu. (2022) . It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well. + date_publication: '2024-03-19' + bug_reports: https://github.com/feiyoung/DR.SC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DR.SC + url_git: https://github.com/feiyoung/DR.SC +dr4pl: + version: 2.0.0 + title: |- + Dose Response Data Analysis using the 4 Parameter Logistic (4pl) + Model + maintainer: Justin T. Landis + description: Models the relationship between dose levels and responses in a pharmacological + experiment using the 4 Parameter Logistic model. Traditional packages on dose-response + modelling such as 'drc' and 'nplr' often draw errors due to convergence failure + especially when data have outliers or non-logistic shapes. This package provides + robust estimation methods that are less affected by outliers and other initialization + methods that work well for data lacking logistic shapes. We provide the bounds + on the parameters of the 4PL model that prevent parameter estimates from diverging + or converging to zero and base their justification in a statistical principle. + These methods are used as remedies to convergence failure problems. Gadagkar, + S. R. and Call, G. B. (2015) Ritz, C. and Baty, + F. and Streibig, J. C. and Gerhard, D. (2015) . + date_publication: '2021-08-17' + bug_reports: https://bitbucket.org/dittmerlab/dr4pl/issues?status=new&status=open + url: '' + url_cran: https://CRAN.R-project.org/package=dr4pl + url_git: https://bitbucket.org/dittmerlab/dr4pl +dracor: + version: 0.2.6 + title: Decode Draco Format 3D Mesh Data + maintainer: Gregory Jefferis + description: |- + Decodes meshes and point cloud data encoded by the Draco mesh + compression library from Google. Note that this is only designed for basic + decoding and not intended as a full scale wrapping of the Draco library. + date_publication: '2023-01-29' + bug_reports: https://github.com/natverse/dracor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dracor + url_git: https://github.com/natverse/dracor +dragonking: + version: 0.1.0 + title: Statistical Tools to Identify Dragon Kings + maintainer: Raoul Wadhwa + description: |- + Statistical tests and test statistics to identify events in a + dataset that are dragon kings (DKs). The statistical methods in this + package were reviewed in Wheatley & Sornette (2015) . + date_publication: '2018-06-18' + bug_reports: https://github.com/rrrlw/dragonking/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dragonking + url_git: https://github.com/rrrlw/dragonking +dragracer: + version: 0.1.7 + title: Data Sets for RuPaul's Drag Race + maintainer: Steve Miller + description: |- + These are data sets for the hit TV show, RuPaul's Drag Race. + Data right now include episode-level data, contestant-level data, and + episode-contestant-level data. This is a work in progress, and a love letter + of a kind to RuPaul's Drag Race and the performers that have appeared on the show. + This may not be the most productive use of my time, but I have tenure and what + are you going to do about it? I think there is at least some value in this package + if it allows the show's fandom to learn more about the R programming language + around its contents. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dragracer + url_git: '' +dragulaR: + version: 0.3.1 + title: |- + Drag and Drop Elements in 'Shiny' using 'Dragula Javascript + Library' + maintainer: Zygmunt Zawadzki + description: Move elements between containers in 'Shiny' without explicitly using + 'JavaScript'. It can be used to build custom inputs or to change the positions + of user interface elements like plots or tables. + date_publication: '2018-06-17' + bug_reports: https://github.com/zzawadz/dragulaR/issues + url: https://dragular.zstat.pl/ + url_cran: https://CRAN.R-project.org/package=dragulaR + url_git: '' +drake: + version: 7.13.11 + title: A Pipeline Toolkit for Reproducible Computation at Scale + maintainer: William Michael Landau + description: |- + A general-purpose computational engine for data + analysis, drake rebuilds intermediate data objects when their + dependencies change, and it skips work when the results are already up + to date. Not every execution starts from scratch, there is native + support for parallel and distributed computing, and completed projects + have tangible evidence that they are reproducible. Extensive + documentation, from beginner-friendly tutorials to practical examples + and more, is available at the reference website + and the online manual + . + date_publication: '2024-12-04' + bug_reports: https://github.com/ropensci/drake/issues + url: https://docs.ropensci.org/drake/ + url_cran: https://CRAN.R-project.org/package=drake + url_git: https://github.com/ropensci/drake +DramaAnalysis: + version: 3.0.2 + title: Analysis of Dramatic Texts + maintainer: Nils Reiter + description: |- + Analysis of preprocessed dramatic texts, with respect to literary research. + The package provides functions to analyze and visualize information about characters, + stage directions, the dramatic structure and the text itself. + The dramatic texts are expected to be in CSV format, which can be installed from within + the package, sample texts are provided. The package and the reasoning behind it are described in + Reiter et al. (2017) . + date_publication: '2020-09-18' + bug_reports: https://github.com/quadrama/DramaAnalysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DramaAnalysis + url_git: https://github.com/quadrama/DramaAnalysis +drape: + version: 0.0.2 + title: Doubly Robust Average Partial Effects + maintainer: Harvey Klyne + description: Doubly robust average partial effect estimation. This implementation + contains methods for adding additional smoothness to plug-in regression procedures + and for estimating score functions using smoothing splines. Details of the method + can be found in Harvey Klyne and Rajen D. Shah (2023) . + date_publication: '2024-11-28' + bug_reports: https://github.com/harveyklyne/drape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drape + url_git: '' +drat: + version: 0.2.5 + title: '''Drat'' R Archive Template' + maintainer: Dirk Eddelbuettel + description: |- + Creation and use of R Repositories via helper functions + to insert packages into a repository, and to add repository information + to the current R session. Two primary types of repositories are support: + gh-pages at GitHub, as well as local repositories on either the same machine + or a local network. Drat is a recursive acronym: Drat R Archive Template. + date_publication: '2024-10-21' + bug_reports: https://github.com/eddelbuettel/drat/issues + url: https://dirk.eddelbuettel.com/code/drat.html + url_cran: https://CRAN.R-project.org/package=drat + url_git: https://github.com/eddelbuettel/drat +draw: + version: 1.0.0 + title: Wrapper Functions for Producing Graphics + maintainer: Richard Wen + description: |- + A set of user-friendly wrapper functions for creating consistent graphics and diagrams with lines, common shapes, text, and page settings. + Compatible with and based on the R 'grid' package. + date_publication: '2018-07-30' + bug_reports: https://github.com/rrwen/draw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=draw + url_git: https://github.com/rrwen/draw +drawer: + version: 0.2.0.1 + title: An Interactive HTML Image Editing Tool + maintainer: Le Zhang + description: |- + An interactive image editing tool that can be added as part of the HTML in Shiny, + R markdown or any type of HTML document. Often times, plots, photos are embedded + in the web application/file. 'drawer' can take screenshots of these image-like elements, or + any part of the HTML document and send to an image editing space called 'canvas' to allow users + immediately edit the screenshot(s) within the same document. Users can quickly + combine, compare different screenshots, upload their own images + and maybe make a scientific figure. + date_publication: '2022-08-19' + bug_reports: https://github.com/lz100/drawer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drawer + url_git: https://github.com/lz100/drawer +DRaWR: + version: 1.0.3 + title: Discriminative Random Walk with Restart + maintainer: Charles Blatti + description: |- + We present DRaWR, a network-based method for ranking genes or + properties related to a given gene set. Such related genes or properties are + identified from among the nodes of a large, heterogeneous network of biological + information. Our method involves a random walk with restarts, performed on + an initial network with multiple node and edge types, preserving more of the + original, specific property information than current methods that operate + on homogeneous networks. In this first stage of our algorithm, we find the + properties that are the most relevant to the given gene set and extract a + subnetwork of the original network, comprising only the relevant properties. We + then rerank genes by their similarity to the given gene set, based on a second + random walk with restarts, performed on the above subnetwork. + date_publication: '2022-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DRaWR + url_git: '' +drawsample: + version: 1.0.1 + title: Draw Samples with the Desired Properties from a Data Set + maintainer: Kubra Atalay Kabasakal + description: |- + A tool to sample data with the desired properties.Samples can be + drawn by purposive sampling with determining distributional + conditions, such as deviation from normality (skewness and kurtosis), + and sample size in quantitative research studies. + For purposive sampling, a researcher has something in mind and participants that + fit the purpose of the study are included (Etikan,Musa, & Alkassim, 2015) + .Purposive sampling can be useful for answering + many research questions (Klar & Leeper, 2019) + . + date_publication: '2022-09-05' + bug_reports: https://github.com/atalay-k/drawsample/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drawsample + url_git: https://github.com/atalay-k/drawsample +DRAYL: + version: '1.0' + title: Computation of Rayleigh Densities of Arbitrary Dimension + maintainer: Martin Wiegand + description: |- + We offer an implementation of the series representation put + forth in "A series representation for multidimensional + Rayleigh distributions" by Wiegand and Nadarajah . Furthermore we have implemented an + integration approach proposed by Beaulieu et al. for 3 and + 4-dimensional Rayleigh densities (Beaulieu, Zhang, "New + simplest exact forms for the 3D and 4D multivariate Rayleigh + PDFs with applications to antenna array geometrics", ). + date_publication: '2019-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DRAYL + url_git: '' +DrBats: + version: 0.1.6 + title: 'Data Representation: Bayesian Approach That''s Sparse' + maintainer: Benedicte Fontez + description: |- + Feed longitudinal data into a Bayesian Latent Factor Model to obtain + a low-rank representation. Parameters are estimated using a Hamiltonian + Monte Carlo algorithm with STAN. See G. Weinrott, B. Fontez, N. Hilgert and + S. Holmes, "Bayesian Latent Factor Model for Functional Data Analysis", + Actes des JdS 2016. + date_publication: '2022-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DrBats + url_git: '' +drc: + version: 3.0-1 + title: Analysis of Dose-Response Curves + maintainer: Christian Ritz + description: Analysis of dose-response data is made available through a suite of + flexible and versatile model fitting and after-fitting functions. + date_publication: '2016-08-30' + bug_reports: '' + url: http://www.bioassay.dk + url_cran: https://CRAN.R-project.org/package=drc + url_git: '' +drcarlate: + version: 1.2.0 + title: Improving Estimation Efficiency in CAR with Imperfect Compliance + maintainer: Mingxin Zhang + description: |- + We provide a list of functions for replicating the results of the Monte Carlo simulations and empirical application of Jiang et al. (2022). + In particular, we provide corresponding functions for generating the three types of random data described in this paper, as well as all the estimation strategies. + Detailed information about the data generation process and estimation strategy can be found in Jiang et al. (2022) . + date_publication: '2023-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drcarlate + url_git: '' +drclust: + version: '0.1' + title: Simultaneous Clustering and (or) Dimensionality Reduction + maintainer: Ionel Prunila + description: 'Methods for simultaneous clustering and dimensionality reduction such + as: Double k-means, Reduced k-means, Factorial k-means, Clustering with Disjoint + PCA but also methods for exclusively dimensionality reduction: Disjoint PCA, Disjoint + FA. The statistical methods implemented refer to the following articles: de Soete + G., Carroll J. (1994) "K-means clustering in a low-dimensional Euclidean space" + ; Vichi M. (2001) "Double k-means Clustering + for Simultaneous Classification of Objects and Variables" + ; Vichi M., Kiers H.A.L. (2001) "Factorial k-means analysis for two-way data" + ; Vichi M., Saporta G. (2009) "Clustering + and disjoint principal component analysis" ; + Vichi M. (2017) "Disjoint factor analysis with cross-loadings" .' + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drclust + url_git: '' +drcSeedGerm: + version: 1.0.1 + title: Utilities for Data Analyses in Seed Germination/Emergence Assays + maintainer: Andrea Onofri + description: Utility functions to be used to analyse datasets obtained from seed + germination/emergence assays. Fits several types of seed germination/emergence + models, including those reported in Onofri et al. (2018) "Hydrothermal-time-to-event + models for seed germination", European Journal of Agronomy, 101, 129-139 . + Contains several datasets for practicing. + date_publication: '2023-05-16' + bug_reports: '' + url: https://www.statforbiology.com + url_cran: https://CRAN.R-project.org/package=drcSeedGerm + url_git: '' +drcte: + version: 1.0.30 + title: Statistical Approaches for Time-to-Event Data in Agriculture + maintainer: Andrea Onofri + description: A specific and comprehensive framework for the analyses of time-to-event + data in agriculture. Fit non-parametric and parametric time-to-event models. Compare + time-to-event curves for different experimental groups. Plots and other displays. + It is particularly tailored to the analyses of data from germination and emergence + assays. The methods are described in Onofri et al. (2020) "A unified framework + for the analysis of germination, emergence, and other time-to-event data in weed + science"", Weed Science, 70, 259-271 . + date_publication: '2023-05-08' + bug_reports: '' + url: https://www.statforbiology.com + url_cran: https://CRAN.R-project.org/package=drcte + url_git: '' +drda: + version: 2.0.5 + title: Dose-Response Data Analysis + maintainer: Alberto Pessia + description: |- + Fit logistic functions to observed dose-response continuous + data and evaluate goodness-of-fit measures. See Malyutina A., Tang J., + and Pessia A. (2023) . + date_publication: '2025-01-16' + bug_reports: https://github.com/albertopessia/drda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drda + url_git: https://github.com/albertopessia/drda +DRDID: + version: 1.2.0 + title: Doubly Robust Difference-in-Differences Estimators + maintainer: Pedro H. C. Sant'Anna + description: |- + Implements the locally efficient doubly robust difference-in-differences (DiD) + estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) + . The estimator combines inverse probability weighting and outcome + regression estimators (also implemented in the package) to form estimators with + more attractive statistical properties. Two different estimation methods can be used + to estimate the nuisance functions. + date_publication: '2024-10-07' + bug_reports: https://github.com/pedrohcgs/DRDID/issues + url: https://psantanna.com/DRDID/ + url_cran: https://CRAN.R-project.org/package=DRDID + url_git: https://github.com/pedrohcgs/DRDID +DrDimont: + version: 0.1.4 + title: Drug Response Prediction from Differential Multi-Omics Networks + maintainer: Katharina Baum + description: |- + While it has been well established that drugs affect and help + patients differently, personalized drug response predictions remain + challenging. Solutions based on single omics measurements have been proposed, + and networks provide means to incorporate molecular interactions into reasoning. + However, how to integrate the wealth of information contained in multiple omics + layers still poses a complex problem. + We present a novel network analysis pipeline, DrDimont, Drug response prediction + from Differential analysis of multi-omics networks. It allows for comparative + conclusions between two conditions and translates them into differential drug + response predictions. DrDimont focuses on molecular interactions. It establishes + condition-specific networks from correlation within an omics layer that are + then reduced and combined into heterogeneous, multi-omics molecular networks. + A novel semi-local, path-based integration step ensures integrative conclusions. + Differential predictions are derived from comparing the condition-specific + integrated networks. DrDimont's predictions are explainable, i.e., molecular + differences that are the source of high differential drug scores can be retrieved. + Our proposed pipeline leverages multi-omics data for differential predictions, + e.g. on drug response, and includes prior information on interactions. + The case study presented in the vignette uses data published by + Krug (2020) . The package license applies only + to the software and explicitly not to the included data. + date_publication: '2022-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DrDimont + url_git: '' +DRDRtest: + version: '0.1' + title: |- + A Nonparametric Doubly Robust Test for Continuous Treatment + Effect + maintainer: Guangwei Weng + description: |- + Implement the statistical test proposed in Weng et al. (2021) to test whether + the average treatment effect curve is constant and whether a discrete covariate is a significant effect modifier. + date_publication: '2021-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DRDRtest + url_git: '' +dreamer: + version: 3.2.0 + title: Dose Response Models for Bayesian Model Averaging + maintainer: Richard Daniel Payne + description: |- + Fits dose-response models utilizing a Bayesian model + averaging approach as outlined in Gould (2019) + for both continuous and binary responses. Longitudinal dose-response modeling + is also supported in a Bayesian model averaging framework as outlined in + Payne, Ray, and Thomann (2024) + . Functions + for plotting and calculating various posterior quantities + (e.g. posterior mean, quantiles, probability of minimum efficacious dose, + etc.) are also implemented. Copyright Eli Lilly and Company (2019). + date_publication: '2024-12-19' + bug_reports: https://github.com/rich-payne/dreamer/issues + url: https://rich-payne.github.io/dreamer/ + url_cran: https://CRAN.R-project.org/package=dreamer + url_git: https://github.com/rich-payne/dreamer +dreamerr: + version: 1.4.0 + title: Error Handling Made Easy + maintainer: Laurent Berge + description: |- + Set of tools to facilitate package development and make R a more user-friendly place. Mostly for developers (or anyone who writes/shares functions). Provides a simple, powerful and flexible way to check the arguments passed to functions. + The developer can easily describe the type of argument needed. If the user provides a wrong argument, then an informative error message is prompted with the requested type and the problem clearly stated--saving the user a lot of time in debugging. + date_publication: '2023-12-21' + bug_reports: https://github.com/lrberge/dreamerr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dreamerr + url_git: '' +DREGAR: + version: 0.1.3.0 + title: |- + Regularized Estimation of Dynamic Linear Regression in the + Presence of Autocorrelated Residuals (DREGAR) + maintainer: Hamed Haselimashhadi + description: A penalized/non-penalized implementation for dynamic regression in + the presence of autocorrelated residuals (DREGAR) using iterative penalized/ordinary + least squares. It applies Mallows CP, AIC, BIC and GCV to select the tuning parameters. + date_publication: '2017-03-10' + bug_reports: '' + url: http://hamedhaseli.webs.com. + url_cran: https://CRAN.R-project.org/package=DREGAR + url_git: '' +drf: + version: 1.1.0 + title: Distributional Random Forests + maintainer: Loris Michel + description: An implementation of distributional random forests as introduced in + Cevid & Michel & Meinshausen & Buhlmann (2020) . + date_publication: '2021-03-29' + bug_reports: https://github.com/lorismichel/drf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drf + url_git: https://github.com/lorismichel/drf +drgee: + version: 1.1.10 + title: Doubly Robust Generalized Estimating Equations + maintainer: Johan Zetterqvist + description: |- + Fit restricted mean models for the conditional association + between an exposure and an outcome, given covariates. Three methods + are implemented: O-estimation, where a nuisance model for the + association between the covariates and the outcome is used; + E-estimation where a nuisance model for the association + between the covariates and the exposure is used, and doubly robust (DR) + estimation where both nuisance models are used. In DR-estimation, + the estimates will be consistent when at least one of the nuisance + models is correctly specified, not necessarily both. For more information, see Zetterqvist and Sjölander (2015) . + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drgee + url_git: '' +drglm: + version: '1.1' + title: |- + Fitting Linear and Generalized Linear Models in "Divide and + Recombine" Approach to Large Data Sets + maintainer: Md. Mahadi Hassan Nayem + description: 'To overcome the memory limitations for fitting linear (LM) and Generalized + Linear Models (GLMs) to large data sets, this package implements the Divide and + Recombine (D&R) strategy. It basically divides the entire large data set into + suitable subsets manageable in size and then fits model to each subset. Finally, + results from each subset are aggregated to obtain the final estimate. This package + also supports fitting GLMs to data sets that cannot fit into memory and provides + methods for fitting GLMs under linear regression, binomial regression, Poisson + regression, and multinomial logistic regression settings. Respective models are + fitted using different D&R strategies as described by: Xi, Lin, and Chen (2009) + , Xi, Lin and Chen (2006) , + Zuo and Li (2018) , Karim, M.R., Islam, M.A. (2019) + .' + date_publication: '2024-07-30' + bug_reports: '' + url: https://nayemmh.github.io/drglm/ + url_cran: https://CRAN.R-project.org/package=drglm + url_git: '' +DRHotNet: + version: '2.3' + title: Differential Risk Hotspots in a Linear Network + maintainer: Alvaro Briz-Redon + description: Performs the identification of differential risk hotspots (Briz-Redon + et al. 2019) along a linear network. Given a marked + point pattern lying on the linear network, the method implemented uses a network-constrained + version of kernel density estimation (McSwiggan et al. 2017) + to approximate the probability of occurrence across space for the type of event + specified by the user through the marks of the pattern (Kelsall and Diggle 1995) + . The goal is to detect microzones of the linear network + where the type of event indicated by the user is overrepresented. + date_publication: '2023-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DRHotNet + url_git: '' +drhur: + version: 1.1.0 + title: Learning R with Dr. Hu + maintainer: Yue Hu + description: Tutarials of R learning easily and happily. + date_publication: '2023-05-17' + bug_reports: https://github.com/sammo3182/drhur/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drhur + url_git: '' +drhutools: + version: 1.0.0 + title: Political Science Academic Research Gears + maintainer: Yue Hu + description: Using these tools to simplify the research process of political science + and other social sciences. The current version can create folder system for academic + project in political science, calculate psychological trait scores, visualize + experimental and spatial data, and set up color-blind palette, functions used + in academic research of political psychology or political science in general. + date_publication: '2024-12-05' + bug_reports: https://github.com/sammo3182/drhutools/issues + url: https://www.drhuyue.site/software/drhutools/ + url_cran: https://CRAN.R-project.org/package=drhutools + url_git: '' +DriftBurstHypothesis: + version: 0.4.0.1 + title: Calculates the Test-Statistic for the Drift Burst Hypothesis + maintainer: Emil Sjoerup + description: 'Calculates the T-Statistic for the drift burst hypothesis from the + working paper Christensen, Oomen and Reno (2018) . The + authors'' MATLAB code is available upon request, see: .' + date_publication: '2020-07-13' + bug_reports: https://github.com/emilsjoerup/DriftBurstHypothesis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DriftBurstHypothesis + url_git: https://github.com/emilsjoerup/DriftBurstHypothesis +dRiftDM: + version: 0.2.1 + title: Estimating (Time-Dependent) Drift Diffusion Models + maintainer: Valentin Koob + description: |- + Fit and explore Drift Diffusion Models (DDMs), + a common tool in psychology for describing decision processes in simple + tasks. It can handle both time-independent and time-dependent DDMs. You + either choose prebuilt models or create your own, and the package takes + care of model predictions and parameter estimation. Model predictions + are derived via the numerical solutions provided by Richter, Ulrich, and + Janczyk (2023, ). + date_publication: '2025-01-08' + bug_reports: https://github.com/bucky2177/dRiftDM/issues + url: https://bucky2177.github.io/dRiftDM/ + url_cran: https://CRAN.R-project.org/package=dRiftDM + url_git: https://github.com/bucky2177/dRiftDM +drifter: + version: 0.2.1 + title: Concept Drift and Concept Shift Detection for Predictive Models + maintainer: Przemyslaw Biecek + description: |- + Concept drift refers to the change in the data distribution or + in the relationships between variables over time. + 'drifter' calculates distances between variable distributions or + variable relations and identifies both types of drift. + Key functions are: + calculate_covariate_drift() checks distance between corresponding variables in two datasets, + calculate_residuals_drift() checks distance between residual distributions for two models, + calculate_model_drift() checks distance between partial dependency profiles for two models, + check_drift() executes all checks against drift. + 'drifter' is a part of the 'DrWhy.AI' universe (Biecek 2018) . + date_publication: '2019-05-31' + bug_reports: https://github.com/ModelOriented/drifter/issues + url: https://ModelOriented.github.io/drifter/ + url_cran: https://CRAN.R-project.org/package=drifter + url_git: '' +DrillR: + version: '0.1' + title: R Driver for Apache Drill + maintainer: Hanbing Yang + description: Provides a R driver for Apache Drill, which + could connect to the Apache Drill cluster + or drillbit and get + result(in data frame) from the SQL query and check the current configuration status. + This link contains more information about Apache + Drill. + date_publication: '2016-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DrillR + url_git: '' +drimmR: + version: 1.0.1 + title: Estimation, Simulation and Reliability of Drifting Markov Models + maintainer: Nicolas Vergne + description: |- + Performs the drifting Markov models (DMM) which are + non-homogeneous Markov models designed for modeling the heterogeneities of + sequences in a more flexible way than homogeneous Markov chains or even + hidden Markov models. In this context, we developed an R package dedicated to + the estimation, simulation and the exact computation of associated reliability + of drifting Markov models. The implemented methods are described in + Vergne, N. (2008), and + Barbu, V.S., Vergne, N. (2019) . + date_publication: '2021-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drimmR + url_git: '' +DrImpute: + version: '1.0' + title: Imputing Dropout Events in Single-Cell RNA-Sequencing Data + maintainer: Il-Youp Kwak + description: R codes for imputing dropout events. Many statistical methods in cell + type identification, visualization and lineage reconstruction do not account for + dropout events ('PCAreduce', 'SC3', 'PCA', 't-SNE', 'Monocle', 'TSCAN', etc). + 'DrImpute' can improve the performance of such software by imputing dropout events. + date_publication: '2017-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DrImpute + url_git: https://github.com/ikwak2/DrImpute +DRIP: + version: '2.3' + title: Discontinuous Regression and Image Processing + maintainer: Yicheng Kang + description: |- + A collection of functions that perform jump regression + and image analysis such as denoising, deblurring and + jump detection. The implemented methods are based on + the following research: Qiu, P. (1998) , + Qiu, P. and Yandell, B. (1997) , + Qiu, P. (2009) , + Kang, Y. and Qiu, P. (2014) , + Qiu, P. and Kang, Y. (2015) , + Kang, Y., Mukherjee, P.S. and Qiu, P. (2018) , + Kang, Y. (2020) . + date_publication: '2024-11-21' + bug_reports: https://github.com/kangy10/DRIP/issues + url: https://miamioh.edu/fsb/directory/?up=/directory/kangy10 + url_cran: https://CRAN.R-project.org/package=DRIP + url_git: https://github.com/kangy10/DRIP +driveR: + version: 0.4.1 + title: Prioritizing Cancer Driver Genes Using Genomics Data + maintainer: Ege Ulgen + description: |- + Cancer genomes contain large numbers of somatic alterations but few + genes drive tumor development. Identifying cancer driver genes is critical + for precision oncology. Most of current approaches either identify driver + genes based on mutational recurrence or using estimated scores predicting + the functional consequences of mutations. 'driveR' is a tool for + personalized or batch analysis of genomic data for driver gene prioritization + by combining genomic information and prior biological knowledge. As features, + 'driveR' uses coding impact metaprediction scores, non-coding impact scores, + somatic copy number alteration scores, hotspot gene/double-hit gene + condition, 'phenolyzer' gene scores and memberships to cancer-related KEGG + pathways. It uses these features to estimate cancer-type-specific + probability for each gene of being a cancer driver using the related task of + a multi-task learning classification model. The method is described in detail + in Ulgen E, Sezerman OU. 2021. driveR: driveR: a novel method for + prioritizing cancer driver genes using somatic genomics data. BMC + Bioinformatics . + date_publication: '2023-08-19' + bug_reports: https://github.com/egeulgen/driveR/issues + url: https://egeulgen.github.io/driveR/ + url_cran: https://CRAN.R-project.org/package=driveR + url_git: https://github.com/egeulgen/driveR/ +droll: + version: 0.1.0 + title: Analyze Roll Distributions + maintainer: C. Lente + description: |- + A toolkit for parsing dice notation, analyzing rolls, + calculating success probabilities, and plotting outcome distributions. + date_publication: '2021-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=droll + url_git: '' +DRomics: + version: 2.6-2 + title: Dose Response for Omics + maintainer: Aurelie Siberchicot + description: Several functions are provided for dose-response (or concentration-response) + characterization from omics data. 'DRomics' is especially dedicated to omics data + obtained using a typical dose-response design, favoring a great number of tested + doses (or concentrations) rather than a great number of replicates (no need of + replicates). 'DRomics' provides functions 1) to check, normalize and or transform + data, 2) to select monotonic or biphasic significantly responding items (e.g. + probes, metabolites), 3) to choose the best-fit model among a predefined family + of monotonic and biphasic models to describe each selected item, 4) to derive + a benchmark dose or concentration and a typology of response from each fitted + curve. In the available version data are supposed to be single-channel microarray + data in log2, RNAseq data in raw counts, or already pretreated continuous omics + data (such as metabolomic data) in log scale. In order to link responses across + biological levels based on a common method, 'DRomics' also handles apical data + as long as they are continuous and follow a normal distribution for each dose + or concentration, with a common standard error. For further details see Delignette-Muller + et al (2023) and Larras et al (2018) . + date_publication: '2024-10-16' + bug_reports: https://github.com/lbbe-software/DRomics/issues + url: https://lbbe.univ-lyon1.fr/fr/dromics + url_cran: https://CRAN.R-project.org/package=DRomics + url_git: '' +drone: + version: 1.0.0 + title: Data for Data Visualisation Geometries Encyclopedia + maintainer: Thiyanga S. Talagala + description: This is the companion package to the Data Visualization Geometries + Encyclopedia, providing seamless access to the associated data. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drone + url_git: '' +dropout: + version: 2.2.0 + title: Handling Incomplete Responses in Survey Data Analysis + maintainer: Hendrik Mann + description: Offers robust tools to identify and manage incomplete responses in + survey datasets, thereby enhancing the quality and reliability of research findings. + date_publication: '2024-10-16' + bug_reports: https://github.com/hendr1km/dropout/issues + url: https://hendr1km.github.io/dropout/ + url_cran: https://CRAN.R-project.org/package=dropout + url_git: https://github.com/hendr1km/dropout +dropR: + version: 1.0.3 + title: Dropout Analysis by Condition + maintainer: Annika Tave Overlander + description: 'Analysis and visualization of dropout between conditions in surveys + and (online) experiments. Features include computation of dropout statistics, + comparing dropout between conditions (e.g. Chi square), analyzing survival (e.g. + Kaplan-Meier estimation), comparing conditions with the most different rates of + dropout (Kolmogorov-Smirnov) and visualizing the result of each in designated + plotting functions. Sources: Andrea Frick, Marie-Terese Baechtiger & Ulf-Dietrich + Reips (2001) ; + Ulf-Dietrich Reips (2002) "Standards for Internet-Based Experimenting" .' + date_publication: '2024-07-03' + bug_reports: '' + url: https://iscience-kn.github.io/dropR/ + url_cran: https://CRAN.R-project.org/package=dropR + url_git: https://github.com/iscience-kn/dropR +droptest: + version: 0.1.3 + title: Simulates LOX Drop Testing + maintainer: Chad Ross + description: |- + Generates simulated data representing the LOX drop testing + process (also known as impact testing). A simulated process allows for + accelerated study of test behavior. Functions are provided to simulate + trials, test series, and groups of test series. Functions for creating plots + specific to this process are also included. Test attributes and criteria can + be set arbitrarily. This work is not endorsed by or affiliated with NASA. + See "ASTM G86-17, Standard Test Method for Determining Ignition Sensitivity + of Materials to Mechanical Impact in Ambient Liquid Oxygen and Pressurized + Liquid and Gaseous Oxygen Environments" . + date_publication: '2018-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=droptest + url_git: https://github.com/chadr/droptest +drord: + version: 1.0.1 + title: Doubly-Robust Estimators for Ordinal Outcomes + maintainer: David Benkeser + description: |- + Efficient covariate-adjusted estimators of quantities that are useful for + establishing the effects of treatments on ordinal outcomes. + date_publication: '2021-05-20' + bug_reports: https://github.com/benkeser/drord/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drord + url_git: https://github.com/benkeser/drord +drought: + version: '1.2' + title: Statistical Modeling and Assessment of Drought + maintainer: Zengchao Hao + description: Provide tools for drought monitoring based on univariate and multivariate + drought indicators.Statistical drought prediction based on Ensemble Streamflow + Prediction (ESP), drought risk assessments, and drought propagation are also provided. + Please see Hao Zengchao et al. (2017) . + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drought + url_git: '' +drpop: + version: 0.0.3 + title: Efficient and Doubly Robust Population Size Estimation + maintainer: Manjari Das + description: Estimation of the total population size from capture-recapture data + efficiently and with low bias implementing the methods from Das M, Kennedy EH, + and Jewell NP (2021) . The estimator is doubly robust against + errors in the estimation of the intermediate nuisance parameters. Users can choose + from the flexible estimation models provided in the package, or use any other + preferred model. + date_publication: '2021-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drpop + url_git: '' +DRquality: + version: 0.2.1 + title: Quality Measurements for Dimensionality Reduction + maintainer: Michael Thrun + description: 'Several quality measurements for investigating the performance of + dimensionality reduction methods are provided here. In addition a new quality + measurement called Gabriel classification error is made accessible, which was + published in Thrun, M. C., Märte, J., & Stier, Q: "Analyzing Quality Measurements + for Dimensionality Reduction" (2023), Machine Learning and Knowledge Extraction + (MAKE), .' + date_publication: '2023-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DRquality + url_git: '' +DRR: + version: 0.0.4 + title: Dimensionality Reduction via Regression + maintainer: Guido Kraemer + description: |- + An Implementation of Dimensionality Reduction + via Regression using Kernel Ridge Regression. + date_publication: '2020-02-12' + bug_reports: https://github.com/gdkrmr/DRR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DRR + url_git: https://github.com/gdkrmr/DRR +drtmle: + version: 1.1.2 + title: Doubly-Robust Nonparametric Estimation and Inference + maintainer: David Benkeser + description: |- + Targeted minimum loss-based estimators of counterfactual means and + causal effects that are doubly-robust with respect both to consistency and + asymptotic normality (Benkeser et al (2017), ; MJ + van der Laan (2014), ). + date_publication: '2023-01-05' + bug_reports: https://github.com/benkeser/drtmle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drtmle + url_git: https://github.com/benkeser/drtmle +drugDemand: + version: 0.1.3 + title: Drug Demand Forecasting + maintainer: Kaifeng Lu + description: Performs drug demand forecasting by modeling drug dispensing data while + taking into account predicted enrollment and treatment discontinuation dates. + The gap time between randomization and the first drug dispensing visit is modeled + using interval-censored exponential, Weibull, log-logistic, or log-normal distributions + (Anderson-Bergman (2017) ). The number of skipped visits + is modeled using Poisson, zero-inflated Poisson, or negative binomial distributions + (Zeileis, Kleiber & Jackman (2008) ). The gap time + between two consecutive drug dispensing visits given the number of skipped visits + is modeled using linear regression based on least squares or least absolute deviations + (Birkes & Dodge (1993, ISBN:0-471-56881-3)). The number of dispensed doses is + modeled using linear or linear mixed-effects models (McCulloch & Searle (2001, + ISBN:0-471-19364-X)). + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drugDemand + url_git: '' +drugdevelopR: + version: 1.0.2 + title: Utility-Based Optimal Phase II/III Drug Development Planning + maintainer: Lukas D. Sauer + description: |- + Plan optimal sample size allocation and go/no-go decision rules + for phase II/III drug development programs with time-to-event, binary or + normally distributed endpoints when assuming fixed treatment effects or a + prior distribution for the treatment effect, using methods from Kirchner et al. + (2016) and Preussler (2020). Optimal is in the sense of + maximal expected utility, where the utility is a function taking into account + the expected cost and benefit of the program. It is possible to extend to more + complex settings with bias correction (Preussler S et al. (2020) + ), multiple phase III trials (Preussler et + al. (2019) ), multi-arm trials (Preussler et al. + (2019) ), and multiple endpoints + (Kieser et al. (2018) ). + date_publication: '2025-01-14' + bug_reports: https://github.com/Sterniii3/drugdevelopR/issues + url: https://sterniii3.github.io/drugdevelopR/ + url_cran: https://CRAN.R-project.org/package=drugdevelopR + url_git: https://github.com/Sterniii3/drugdevelopR +DrugExposureDiagnostics: + version: 1.1.1 + title: Diagnostics for OMOP Common Data Model Drug Records + maintainer: Ger Inberg + description: Ingredient specific diagnostics for drug exposure records in the Observational + Medical Outcomes Partnership (OMOP) common data model. + date_publication: '2025-02-06' + bug_reports: https://github.com/darwin-eu/DrugExposureDiagnostics/issues + url: https://darwin-eu.github.io/DrugExposureDiagnostics/ + url_cran: https://CRAN.R-project.org/package=DrugExposureDiagnostics + url_git: https://github.com/darwin-eu/DrugExposureDiagnostics +drugprepr: + version: 0.0.4 + title: |- + Prepare Electronic Prescription Record Data to Estimate Drug + Exposure + maintainer: David Selby + description: Prepare prescription data (such as from the Clinical Practice Research + Datalink) into an analysis-ready format, with start and stop dates for each patient's + prescriptions. Based on Pye et al (2018) . + date_publication: '2021-11-09' + bug_reports: https://github.com/belayb/drugprepr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=drugprepr + url_git: '' +drugsens: + version: 0.1.0 + title: |- + Automated Analysis of 'QuPath' Output Data and Metadata + Extraction + maintainer: Flavio Lombardo + description: |- + A comprehensive toolkit for analyzing microscopy data output from 'QuPath' software. + Provides functionality for automated data processing, metadata extraction, and statistical + analysis of imaging results. The methodology implemented in this package is based on + Labrosse et al. (2024) "Protocol for quantifying drug + sensitivity in 3D patient-derived ovarian cancer models", which describes the complete + workflow for drug sensitivity analysis in patient-derived cancer models. + date_publication: '2025-01-16' + bug_reports: https://git.scicore.unibas.ch/ovca-research/drugsens/-/issues + url: https://git.scicore.unibas.ch/ovca-research/drugsens/ + url_cran: https://CRAN.R-project.org/package=drugsens + url_git: '' +DrugSim2DR: + version: 0.1.1 + title: Predict Drug Functional Similarity to Drug Repurposing + maintainer: Junwei Han + description: A systematic biology tool was developed to repurpose drugs via a drug-drug + functional similarity network. 'DrugSim2DR' first predict drug-drug functional + similarity in the context of specific disease, and then using the similarity + constructed a weighted drug similarity network. Finally, it used a network propagation + algorithm on the network to identify drugs with significant target abnormalities + as candidate drugs. + date_publication: '2023-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DrugSim2DR + url_git: '' +DrugUtilisation: + version: 0.8.2 + title: |- + Summarise Patient-Level Drug Utilisation in Data Mapped to the + OMOP Common Data Model + maintainer: Martí Català + description: |- + Summarise patient-level drug utilisation cohorts using data mapped + to the Observational Medical Outcomes Partnership (OMOP) common data model. + New users and prevalent users cohorts can be generated and their + characteristics, indication and drug use summarised. + date_publication: '2025-01-16' + bug_reports: https://github.com/darwin-eu/DrugUtilisation/issues + url: https://darwin-eu.github.io/DrugUtilisation/ + url_cran: https://CRAN.R-project.org/package=DrugUtilisation + url_git: '' +drumr: + version: 0.1.0 + title: Turn R into a Drum Machine + maintainer: James Martherus + description: |- + Includes various functions for playing drum sounds. beat() plays a drum sound + from one of the six included drum kits. tempo() sets spacing between calls to beat() + in bpm. Together the two functions can be used to create many different drum patterns. + date_publication: '2019-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=drumr + url_git: '' +DRviaSPCN: + version: 0.1.5 + title: Drug Repurposing in Cancer via a Subpathway Crosstalk Network + maintainer: Junwei Han + description: A systematic biology tool was developed to repurpose drugs via a subpathway + crosstalk network. The operation modes include 1) calculating centrality scores + of SPs in the context of gene expression data to reflect the influence of SP crosstalk, + 2) evaluating drug-disease reverse association based on disease- and drug-induced + SPs weighted by the SP crosstalk, 3) identifying cancer candidate drugs through + perturbation analysis. There are also several functions used to visualize the + results. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DRviaSPCN + url_git: '' +ds: + version: '4.0' + title: Descriptive Statistics + maintainer: Emmanuel Arnhold + description: Performs various analyzes of descriptive statistics, including correlations, + graphics and tables. + date_publication: '2019-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ds + url_git: '' +ds4psy: + version: 1.0.0 + title: Data Science for Psychologists + maintainer: Hansjoerg Neth + description: All datasets and functions required for the examples and exercises + of the book "Data Science for Psychologists" (by Hansjoerg Neth, Konstanz University, + 2022), available at . The book and course + introduce principles and methods of data science to students of psychology and + other biological or social sciences. The 'ds4psy' package primarily provides datasets, + but also functions for data generation and manipulation (e.g., of text and time + data) and graphics that are used in the book and its exercises. All functions + included in 'ds4psy' are designed to be explicit and instructive, rather than + efficient or elegant. + date_publication: '2023-09-15' + bug_reports: https://github.com/hneth/ds4psy/issues + url: https://bookdown.org/hneth/ds4psy/ + url_cran: https://CRAN.R-project.org/package=ds4psy + url_git: https://github.com/hneth/ds4psy/ +dsa: + version: 1.0.12 + title: Seasonal Adjustment of Daily Time Series + maintainer: Daniel Ollech + description: |- + Seasonal- and calendar adjustment of time series + with daily frequency using the DSA approach developed by Ollech, + Daniel (2018): Seasonal adjustment of daily time series. Bundesbank + Discussion Paper 41/2018. + date_publication: '2021-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dsa + url_git: '' +DSAIDE: + version: 0.9.6 + title: |- + Dynamical Systems Approach to Infectious Disease Epidemiology + (Ecology/Evolution) + maintainer: Andreas Handel + description: |- + Exploration of simulation models (apps) of various infectious disease transmission dynamics scenarios. + The purpose of the package is to help individuals learn + about infectious disease epidemiology (ecology/evolution) from a dynamical systems perspective. + All apps include explanations of the underlying models and instructions on what to do with the models. + date_publication: '2023-08-23' + bug_reports: https://github.com/ahgroup/DSAIDE/issues + url: https://ahgroup.github.io/DSAIDE/ + url_cran: https://CRAN.R-project.org/package=DSAIDE + url_git: https://github.com/ahgroup/DSAIDE/ +DSAIRM: + version: 0.9.6 + title: Dynamical Systems Approach to Immune Response Modeling + maintainer: Andreas Handel + description: |- + Simulation models (apps) of various within-host immune response scenarios. + The purpose of the package is to help individuals learn + about within-host infection and immune response modeling from a dynamical systems perspective. + All apps include explanations of the underlying models and instructions on what to do with the models. + date_publication: '2023-08-23' + bug_reports: https://github.com/ahgroup/DSAIRM/issues + url: https://ahgroup.github.io/DSAIRM/ + url_cran: https://CRAN.R-project.org/package=DSAIRM + url_git: https://github.com/ahgroup/DSAIRM/ +DSAM: + version: 1.0.2 + title: Data Splitting Algorithms for Model Developments + maintainer: Junyi Chen + description: |- + Providing six different algorithms that can be used to split the + available data into training, test and validation subsets with similar distribution + for hydrological model developments. The dataSplit() function will help you divide + the data according to specific requirements, and you can refer to the par.default() + function to set the parameters for data splitting. The getAUC() function will help + you measure the similarity of distribution features between the data subsets. + For more information about the data splitting algorithms, please refer to: + Chen et al. (2022) , + Zheng et al. (2022) . + date_publication: '2024-01-29' + bug_reports: https://github.com/lark-max/DSAM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DSAM + url_git: https://github.com/lark-max/DSAM +dsample: + version: 0.91.3.4 + title: Discretization-Based Direct Random Sample Generation + maintainer: Chel Hee Lee + description: 'Discretization-based random sampling algorithm that is useful for + a complex model in high dimension is implemented. The normalizing constant of + a target distribution is not needed. Posterior summaries are compared with those + by ''OpenBUGS''. The method is described: Wang and Lee (2014) + and exercised in Lee (2009) .' + date_publication: '2023-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dsample + url_git: '' +dsb: + version: 1.0.4 + title: Normalize & Denoise Droplet Single Cell Protein Data (CITE-Seq) + maintainer: Matthew Mulè + description: 'This lightweight R package provides a method for normalizing and denoising + protein expression data from droplet based single cell experiments. Raw protein + Unique Molecular Index (UMI) counts from sequencing DNA-conjugated antibody derived + tags (ADT) in droplets (e.g. ''CITE-seq'') have substantial measurement noise. + Our experiments and computational modeling revealed two major components of this + noise: 1) protein-specific noise originating from ambient, unbound antibody encapsulated + in droplets that can be accurately inferred via the expected protein counts detected + in empty droplets, and 2) droplet/cell-specific noise revealed via the shared + variance component associated with isotype antibody controls and background protein + counts in each cell. This package normalizes and removes both of these sources + of noise from raw protein data derived from methods such as ''CITE-seq'', ''REAP-seq'', + ''ASAP-seq'', ''TEA-seq'', ''proteogenomic'' data from the Mission Bio platform, + etc. See the vignette for tutorials on how to integrate dsb with ''Seurat'' and + ''Bioconductor'' and how to use dsb in ''Python''. Please see our paper Mulè M.P., + Martins A.J., and Tsang J.S. Nature Communications 2022 + for more details on the method.' + date_publication: '2024-06-16' + bug_reports: https://github.com/niaid/dsb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsb + url_git: https://github.com/niaid/dsb +DSBayes: + version: 2023.1.0 + title: Bayesian Subgroup Analysis in Clinical Trials + maintainer: Ravi Varadhan + description: 'Calculate posterior modes and credible intervals of parameters of + the Dixon-Simon model for subgroup analysis (with binary covariates) in clinical + trials. For details of the methodology, please refer to D.O. Dixon and R. Simon + (1991), Biometrics, 47: 871-881.' + date_publication: '2023-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DSBayes + url_git: '' +dscore: + version: 1.9.0 + title: D-Score for Child Development + maintainer: Stef van Buuren + description: |- + The D-score summarizes the child's performance on a set of + milestones into a single number. The package implements four Rasch model + keys to convert milestone scores into a D-score. It provides tools to + calculate the D-score and its precision from the child's milestone scores, + to convert the D-score into the Development-for-Age Z-score (DAZ) + using age-conditional references, and to map milestone names into a + generic 9-position item naming convention. + date_publication: '2024-06-13' + bug_reports: https://github.com/d-score/dscore/issues + url: https://d-score.org/dscore/ + url_cran: https://CRAN.R-project.org/package=dscore + url_git: https://github.com/d-score/dscore +dscoreMSM: + version: 0.1.0 + title: Survival Proximity Score Matching in Multi-State Survival Model + maintainer: Atanu Bhattacharjee + description: Implements survival proximity score matching in multi-state survival + models. Includes tools for simulating survival data and estimating transition-specific + coxph models with frailty terms. The primary methodological work on multistate + censored data modeling using propensity score matching has been published by Bhattacharjee + et al.(2024) . + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dscoreMSM + url_git: '' +dsdp: + version: 0.1.1 + title: Density Estimation with Semidefinite Programming + maintainer: Satoshi Kakihara + description: |- + The models of probability density functions are Gaussian or + exponential distributions with polynomial correction terms. + Using a maximum likelihood method, 'dsdp' computes parameters of Gaussian + or exponential distributions together with degrees of polynomials by + a grid search, and coefficient of polynomials by a variant of semidefinite + programming. It adopts Akaike Information Criterion for model selection. + See a vignette for a tutorial and more on our 'Github' repository + . + date_publication: '2023-02-11' + bug_reports: https://github.com/tsuchiya-lab/dsdp/issues + url: https://tsuchiya-lab.github.io/dsdp/ + url_cran: https://CRAN.R-project.org/package=dsdp + url_git: '' +dsem: + version: 1.5.0 + title: Fit Dynamic Structural Equation Models + maintainer: James Thorson + description: |- + Applies dynamic structural equation models to time-series data + with generic and simplified specification for simultaneous and lagged + effects. Methods are described in Thorson et al. (2024) + "Dynamic structural equation models synthesize ecosystem dynamics + constrained by ecological mechanisms." + date_publication: '2025-02-13' + bug_reports: https://github.com/James-Thorson-NOAA/dsem/issues + url: https://james-thorson-noaa.github.io/dsem/ + url_cran: https://CRAN.R-project.org/package=dsem + url_git: '' +DSI: + version: 1.7.1 + title: '''DataSHIELD'' Interface' + maintainer: Yannick Marcon + description: |- + 'DataSHIELD' is an infrastructure and series of R packages that + enables the remote and 'non-disclosive' analysis of sensitive research data. + This package defines the API that is to be implemented by 'DataSHIELD' compliant + data repositories. + date_publication: '2024-11-03' + bug_reports: https://github.com/datashield/DSI/issues + url: https://datashield.github.io/DSI/ + url_cran: https://CRAN.R-project.org/package=DSI + url_git: https://github.com/datashield/DSI/ +dsims: + version: 1.0.5 + title: Distance Sampling Simulations + maintainer: Laura Marshall + description: |- + Performs distance sampling simulations. 'dsims' repeatedly generates + instances of a user defined population within a given survey region. It then + generates realisations of a survey design and simulates the detection process. + The data are then analysed so that the results can be compared for accuracy + and precision across all replications. This process allows users to optimise + survey designs for their specific set of survey conditions. The effects of + uncertainty in population distribution or parameters can be investigated + under a number of simulations so that users can be confident that they have + achieved a robust survey design before deploying vessels into the field. The + distance sampling designs used in this package from 'dssd' are detailed in + Chapter 7 of Advanced Distance Sampling, Buckland et. al. (2008, ISBN-13: + 978-0199225873). General distance sampling methods are detailed in Introduction + to Distance Sampling: Estimating Abundance of Biological Populations, Buckland + et. al. (2004, ISBN-13: 978-0198509271). Find out more about estimating + animal/plant abundance with distance sampling at . + date_publication: '2024-12-20' + bug_reports: https://github.com/DistanceDevelopment/dsims/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsims + url_git: https://github.com/DistanceDevelopment/dsims +DSjobtracker: + version: 2.0.0 + title: |- + What Skills and Qualifications are Required for Data Science + Related Jobs? + maintainer: Thiyanga S. Talagala + description: Dataset containing information about job listings for data science + job roles. + date_publication: '2023-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DSjobtracker + url_git: https://github.com/thiyangt/DSjobtracker +DSL: + version: 0.1-7 + title: Distributed Storage and List + maintainer: Stefan Theussl + description: An abstract DList class helps storing large list-type objects in a + distributed manner. Corresponding high-level functions and methods for handling + distributed storage (DStorage) and lists allows for processing such DLists on + distributed systems efficiently. In doing so it uses a well defined storage backend + implemented based on the DStorage class. + date_publication: '2020-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DSL + url_git: '' +dslabs: + version: 0.8.0 + title: Data Science Labs + maintainer: Rafael A. Irizarry + description: Datasets and functions that can be used for data analysis practice, + homework and projects in data science courses and workshops. 26 datasets are available + for case studies in data visualization, statistical inference, modeling, linear + regression, data wrangling and machine learning. + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dslabs + url_git: '' +dsld: + version: 0.2.2 + title: Data Science Looks at Discrimination + maintainer: Norm Matloff + description: |- + Statistical and graphical tools for detecting and measuring + discrimination and bias, be it racial, gender, age or other. + Detection and remediation of bias in machine learning algorithms. + 'Python' interfaces available. + date_publication: '2024-09-13' + bug_reports: https://github.com/matloff/dsld/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsld + url_git: https://github.com/matloff/dsld +dslice: + version: 1.2.2 + title: Dynamic Slicing + maintainer: Chao Ye + description: Dynamic slicing is a method designed for dependency detection between + a categorical variable and a continuous variable. It could be applied for non-parametric + hypothesis testing and gene set enrichment analysis. + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dslice + url_git: '' +DSLite: + version: 1.4.0 + title: '''DataSHIELD'' Implementation on Local Datasets' + maintainer: Yannick Marcon + description: |- + 'DataSHIELD' is an infrastructure and series of R packages that + enables the remote and 'non-disclosive' analysis of sensitive research data. + This 'DataSHIELD Interface' implementation is for analyzing datasets living + in the current R session. The purpose of this is primarily for lightweight + 'DataSHIELD' analysis package development. + date_publication: '2022-10-07' + bug_reports: https://github.com/datashield/DSLite/issues/ + url: https://datashield.github.io/DSLite/ + url_cran: https://CRAN.R-project.org/package=DSLite + url_git: https://github.com/datashield/DSLite/ +dsm: + version: 2.3.3 + title: Density Surface Modelling of Distance Sampling Data + maintainer: Laura Marshall + description: |- + Density surface modelling of line transect data. A Generalized + Additive Model-based approach is used to calculate spatially-explicit estimates + of animal abundance from distance sampling (also presence/absence and strip + transect) data. Several utility functions are provided for model checking, + plotting and variance estimation. + date_publication: '2022-08-20' + bug_reports: https://github.com/DistanceDevelopment/dsm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsm + url_git: https://github.com/DistanceDevelopment/dsm +dsmisc: + version: 0.3.3 + title: Data Science Box of Pandora Miscellaneous + maintainer: Peter Meissner + description: |- + Tool collection for common and not so common data science use cases. This includes + custom made algorithms for data management as well as value calculations that are hard to find + elsewhere because of their specificity but would be a waste to get lost nonetheless. + Currently available functionality: find + sub-graphs in an edge list data.frame, find mode or modes in a vector of values, extract + (a) specific regular expression group(s), generate ISO time stamps that play well with + file names, or generate URL parameter lists by expanding value combinations. + date_publication: '2020-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dsmisc + url_git: '' +dsmmR: + version: 1.0.5 + title: Estimation and Simulation of Drifting Semi-Markov Models + maintainer: Ioannis Mavrogiannis + description: |- + Performs parametric and non-parametric estimation and simulation of + drifting semi-Markov processes. The definition of parametric and non-parametric + model specifications is also possible. Furthermore, three different types of + drifting semi-Markov models are considered. These models differ in the number + of transition matrices and sojourn time distributions used for the computation + of a number of semi-Markov kernels, which in turn characterize the drifting + semi-Markov kernel. For the parametric model estimation and specification, + several discrete distributions are considered for the sojourn times: Uniform, + Poisson, Geometric, Discrete Weibull and Negative Binomial. The non-parametric + model specification makes no assumptions about the shape of the sojourn time + distributions. Semi-Markov models are described in: + Barbu, V.S., Limnios, N. (2008) . + Drifting Markov models are described in: + Vergne, N. (2008) . + Reliability indicators of Drifting Markov models are described in: + Barbu, V. S., Vergne, N. (2019) . + We acknowledge the DATALAB Project + (financed by the + European Union with the European Regional Development fund (ERDF) and by + the Normandy Region) and the HSMM-INCA Project (financed by the French + Agence Nationale de la Recherche (ANR) under grant ANR-21-CE40-0005). + date_publication: '2024-07-28' + bug_reports: https://github.com/Mavrogiannis-Ioannis/dsmmR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsmmR + url_git: https://github.com/Mavrogiannis-Ioannis/dsmmR +DSMolgenisArmadillo: + version: 2.0.9 + title: '''DataSHIELD'' Client for ''MOLGENIS Armadillo''' + maintainer: Mariska Slofstra + description: |- + 'DataSHIELD' is an infrastructure and series of R packages that + enables the remote and 'non-disclosive' analysis of sensitive research data. + This package is the 'DataSHIELD' interface implementation to analyze data + shared on a 'MOLGENIS Armadillo' server. 'MOLGENIS Armadillo' is a + light-weight 'DataSHIELD' server using a file store and an 'RServe' server. + date_publication: '2024-07-09' + bug_reports: https://github.com/molgenis/molgenis-r-datashield/issues/ + url: https://molgenis.github.io/molgenis-r-datashield/ + url_cran: https://CRAN.R-project.org/package=DSMolgenisArmadillo + url_git: https://github.com/molgenis/molgenis-r-datashield/ +dsmSearch: + version: 1.1.1 + title: DSM and LiDAR downloader + maintainer: Xiaohao Yang + description: |- + A collection of functions to search and donwload + DSM (Digital Surface Model) and LiDAR (Light Detection and Ranging) data via APIs, + including 'OpenTopography' and + 'TNMAccess' . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dsmSearch + url_git: '' +DSOpal: + version: 1.4.0 + title: '''DataSHIELD'' Implementation for ''Opal''' + maintainer: Yannick Marcon + description: |- + 'DataSHIELD' is an infrastructure and series of R packages that + enables the remote and 'non-disclosive' analysis of sensitive research data. + This package is the 'DataSHIELD' interface implementation for 'Opal', which is + the data integration application for biobanks by 'OBiBa'. Participant data, once + collected from any data source, must be integrated and stored in a central + data repository under a uniform model. 'Opal' is such a central repository. + It can import, process, validate, query, analyze, report, and export data. + 'Opal' is the reference implementation of the 'DataSHIELD' infrastructure. + date_publication: '2022-10-06' + bug_reports: https://github.com/datashield/DSOpal/issues/ + url: https://datashield.github.io/DSOpal/ + url_cran: https://CRAN.R-project.org/package=DSOpal + url_git: https://github.com/datashield/DSOpal/ +dsos: + version: 0.1.2 + title: Dataset Shift with Outlier Scores + maintainer: Vathy M. Kamulete + description: |- + Test for no adverse shift in two-sample comparison when we + have a training set, the reference distribution, and a test set. The + approach is flexible and relies on a robust and powerful test + statistic, the weighted AUC. Technical details are in Kamulete, V. M. + (2021) . Modern notions of outlyingness such as + trust scores and prediction uncertainty can be used as the underlying + scores for example. + date_publication: '2023-02-19' + bug_reports: https://github.com/vathymut/dsos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsos + url_git: https://github.com/vathymut/dsos +DSpoty: + version: 0.1.0 + title: Get 'Spotify' API Multiple Information + maintainer: Alberto Almuiña + description: |- + You can retrieve 'Spotify' API Information such as artists, albums, tracks, features tracks, recommendations or related artists. + This package allows you to search all the information by name and also includes a distance based algorithm to find similar songs. + More information: . + date_publication: '2020-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DSpoty + url_git: https://github.com/AlbertoAlmuinha/DSpoty +dsrTest: + version: 1.0.0 + title: |- + Tests and Confidence Intervals on Directly Standardized Rates + for Several Methods + maintainer: Michael Nelson + description: |- + Perform a test of a simple null hypothesis about a + directly standardized rate and obtain the matching confidence + interval using a choice of methods. + date_publication: '2022-06-20' + bug_reports: https://github.com/mnelsonr/dsrTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dsrTest + url_git: https://github.com/mnelsonr/dsrTest +DSSAT: + version: 0.0.9 + title: A Comprehensive R Interface for the DSSAT Cropping Systems Model + maintainer: Phillip D. Alderman + description: |- + The purpose of this package is to provide a comprehensive + R interface to the Decision Support System for Agrotechnology + Transfer Cropping Systems Model (DSSAT-CSM; see for more information). + The package provides cross-platform functions to read and + write input files, run DSSAT-CSM, and read output files. + date_publication: '2024-02-19' + bug_reports: https://github.com/palderman/DSSAT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DSSAT + url_git: '' +dssd: + version: 1.0.2 + title: Distance Sampling Survey Design + maintainer: Laura Marshall + description: |- + Creates survey designs for distance sampling surveys. These + designs can be assessed for various effort and coverage statistics. + Once the user is satisfied with the design characteristics they can + generate a set of transects to use in their distance sampling survey. + Many of the designs implemented in this R package were first made + available in our 'Distance' for Windows software and are detailed in + Chapter 7 of Advanced Distance Sampling, Buckland et. al. (2008, + ISBN-13: 978-0199225873). Find out more about estimating animal/plant + abundance with distance sampling at . + date_publication: '2023-11-17' + bug_reports: https://github.com/DistanceDevelopment/dssd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dssd + url_git: '' +DSSP: + version: 0.1.1 + title: Implementation of the Direct Sampling Spatial Prior + maintainer: Gentry White + description: |- + Draw samples from the direct sampling spatial prior model as + described in G. White, D. Sun, P. Speckman (2019) . The basic model assumes a Gaussian + likelihood and derives a spatial prior based on thin-plate splines. + date_publication: '2022-07-12' + bug_reports: https://github.com/gentrywhite/DSSP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DSSP + url_git: https://github.com/gentrywhite/DSSP +dst: + version: 1.8.0 + title: Using the Theory of Belief Functions + maintainer: Peiyuan Zhu + description: Using the Theory of Belief Functions for evidence calculus. Basic probability + assignments, or mass functions, can be defined on the subsets of a set of possible + values and combined. A mass function can be extended to a larger frame. Marginalization, + i.e. reduction to a smaller frame can also be done. These features can be combined + to analyze small belief networks and take into account situations where information + cannot be satisfactorily described by probability distributions. + date_publication: '2024-09-03' + bug_reports: https://github.com/RAPLER/dst-1/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dst + url_git: '' +dstabledist: + version: 0.1.0 + title: The Discrete Stable Distribution Functions + maintainer: Krutto Annika + description: Probability generating function, formulae for the probabilities (discrete + density) and random generation for discrete stable random variables. + date_publication: '2023-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dstabledist + url_git: '' +DstarM: + version: 0.4.0 + title: Analyze Two Choice Reaction Time Data with the D*M Method + maintainer: Don van den Bergh + description: 'A collection of functions to estimate parameters of a diffusion model + via a D*M analysis. Build in models are: the Ratcliff diffusion model, the RWiener + diffusion model, and Linear Ballistic Accumulator models. Custom models functions + can be specified as long as they have a density function.' + date_publication: '2020-08-28' + bug_reports: https://github.com/vandenman/DstarM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DstarM + url_git: https://github.com/vandenman/DstarM +dstat: + version: 1.0.4 + title: |- + Conditional Sensitivity Analysis for Matched Observational + Studies + maintainer: Paul R. Rosenbaum + description: A d-statistic tests the null hypothesis of no treatment effect in a + matched, nonrandomized study of the effects caused by treatments. A d-statistic + focuses on subsets of matched pairs that demonstrate insensitivity to unmeasured + bias in such an observational study, correcting for double-use of the data by + conditional inference. This conditional inference can, in favorable circumstances, + substantially increase the power of a sensitivity analysis (Rosenbaum (2010) ). There + are two examples, one concerning unemployment from Lalive et al. (2006) , + the other concerning smoking and periodontal disease from Rosenbaum (2017) . + date_publication: '2019-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dstat + url_git: '' +dstat2x2xk: + version: 0.2.0 + title: Demonstrated Insensitivity to Bias in 2x2xK Contingency Tables + maintainer: Paul R. Rosenbaum + description: For an observational study with binary treatment, binary outcome and + K strata, implements a d-statistic that uses those strata most insensitive to + unmeasured bias in treatment assignment. The package + has one function, dstat2x2xk. + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dstat2x2xk + url_git: '' +dSTEM: + version: 2.0-1 + title: Multiple Testing of Local Extrema for Detection of Change Points + maintainer: Zhibing He + description: Simultaneously detect the number and locations of change points in + piecewise linear models under stationary Gaussian noise allowing autocorrelated + random noise. The core idea is to transform the problem of detecting change points + into the detection of local extrema (local maxima and local minima)through kernel + smoothing and differentiation of the data sequence, see Cheng et al. (2020) . + A low-computational and fast algorithm call 'dSTEM' is introduced to detect change + points based on the 'STEM' algorithm in D. Cheng and A. Schwartzman (2017) . + date_publication: '2023-06-21' + bug_reports: '' + url: https://doi.org/10.1214/20-EJS1751 + url_cran: https://CRAN.R-project.org/package=dSTEM + url_git: '' +dsTidyverse: + version: 1.0.4 + title: '''DataSHIELD'' ''Tidyverse'' Serverside Package' + maintainer: Tim Cadman + description: Implementation of selected 'Tidyverse' functions within 'DataSHIELD', + an open-source federated analysis solution in R. Currently, DataSHIELD contains + very limited tools for data manipulation, so the aim of this package is to improve + the researcher experience by implementing essential functions for data manipulation, + including subsetting, filtering, grouping, and renaming variables. This is the + serverside package which should be installed on the server holding the data, and + is used in conjuncture with the clientside package 'dsTidyverseClient' which is + installed in the local R environment of the analyst. For more information, see + and . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dsTidyverse + url_git: '' +dsTidyverseClient: + version: 1.0.2 + title: '''DataSHIELD'' ''Tidyverse'' Clientside Package' + maintainer: Tim Cadman + description: Implementation of selected 'Tidyverse' functions within 'DataSHIELD', + an open-source federated analysis solution in R. Currently, 'DataSHIELD' contains + very limited tools for data manipulation, so the aim of this package is to improve + the researcher experience by implementing essential functions for data manipulation, + including subsetting, filtering, grouping, and renaming variables. This is the + clientside package which should be installed locally, and is used in conjuncture + with the serverside package 'dsTidyverse' which is installed on the remote server + holding the data. For more information, see , + and . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dsTidyverseClient + url_git: '' +dSVA: + version: '1.0' + title: Direct Surrogate Variable Analysis + maintainer: Seunggeun (Shawn) Lee + description: Functions for direct surrogate variable analysis, which can identify + hidden factors in high-dimensional biomedical data. + date_publication: '2017-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dSVA + url_git: '' +DSWE: + version: 1.8.2 + title: Data Science for Wind Energy + maintainer: Yu Ding + description: |- + Data science methods used in wind energy applications. + Current functionalities include creating a multi-dimensional power curve model, + performing power curve function comparison, covariate matching, and energy decomposition. + Relevant works for the developed functions are: + funGP() - Prakash et al. (2022) , + AMK() - Lee et al. (2015) , + tempGP() - Prakash et al. (2022) , + ComparePCurve() - Ding et al. (2021) , + deltaEnergy() - Latiffianti et al. (2022) , + syncSize() - Latiffianti et al. (2022) , + imptPower() - Latiffianti et al. (2022) , + All other functions - Ding (2019, ISBN:9780429956508). + date_publication: '2024-02-17' + bug_reports: https://github.com/TAMU-AML/DSWE-Package/issues + url: https://aml.engr.tamu.edu/book-dswe/ + url_cran: https://CRAN.R-project.org/package=DSWE + url_git: https://github.com/TAMU-AML/DSWE-Package +DT: + version: '0.33' + title: A Wrapper of the JavaScript Library 'DataTables' + maintainer: Joe Cheng + description: |- + Data objects in R can be rendered as HTML tables using the + JavaScript library 'DataTables' (typically via R Markdown or Shiny). The + 'DataTables' library has been included in this R package. The package name + 'DT' is an abbreviation of 'DataTables'. + date_publication: '2024-04-04' + bug_reports: https://github.com/rstudio/DT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DT + url_git: https://github.com/rstudio/DT +Dtableone: + version: 1.1.0 + title: Tabular Comparison of Paired Diagnostic Tests + maintainer: Youngmi Park + description: Offers statistical methods to compare diagnostic performance between + two binary diagnostic tests on the same subject in clinical studies. Includes + functions for generating formatted tables to display diagnostic outcomes, facilitating + a clear and comprehensive comparison directly through the R console. Inspired + by and extending the functionalities of the 'DTComPair', 'tableone', and 'gtsummary' + packages. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dtableone + url_git: '' +dtangle: + version: 2.0.9 + title: Cell Type Deconvolution from Gene Expressions + maintainer: Gregory Hunt + description: Deconvolving cell types from high-throughput gene profiling data. For + more information on dtangle see Hunt et al. (2019) . + date_publication: '2019-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dtangle + url_git: '' +DTAplots: + version: 1.0.2.5 + title: |- + Creates Plots Accompanying Bayesian Diagnostic Test Accuracy + Meta-Analyses + maintainer: Ian Schiller + description: Function to create forest plots. Functions to use posterior samples + from Bayesian bivariate meta-analysis model, Bayesian hierarchical summary receiver + operating characteristic (HSROC) meta-analysis model or Bayesian latent class + (LC) meta-analysis model to create Summary Receiver Operating Characteristic (SROC) + plots using methods described by Harbord et al (2007). + date_publication: '2021-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTAplots + url_git: '' +DTAT: + version: 0.3-7 + title: Dose Titration Algorithm Tuning + maintainer: David C. Norris + description: |- + Dose Titration Algorithm Tuning (DTAT) is a methodologic framework + allowing dose individualization to be conceived as a continuous + learning process that begins in early-phase clinical trials and + continues throughout drug development, on into clinical practice. + This package includes code that researchers may use to reproduce + or extend key results of the DTAT research programme, plus tools + for trialists to design and simulate a '3+3/PC' dose-finding study. + Please see Norris (2017a) and + Norris (2017c) . + date_publication: '2024-05-25' + bug_reports: '' + url: https://precisionmethods.guru/ + url_cran: https://CRAN.R-project.org/package=DTAT + url_git: '' +DTAXG: + version: 0.1.0 + title: Diagnostic Test Assessment in the Absence of Gold Standard + maintainer: Zhicheng Du + description: |- + To calculate the sensitivity and specificity in the absence of gold standard using the Bayesian method. + The Bayesian method can be referenced at Haiyan Gu and Qiguang Chen (1999) . + date_publication: '2019-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTAXG + url_git: '' +dTBM: + version: '3.0' + title: |- + Multi-Way Spherical Clustering via Degree-Corrected Tensor Block + Models + maintainer: Jiaxin Hu + description: Implement weighted higher-order initialization and angle-based iteration + for multi-way spherical clustering under degree-corrected tensor block model. + See reference Jiaxin Hu and Miaoyan Wang (2023) . + date_publication: '2023-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dTBM + url_git: '' +dtComb: + version: 1.0.4 + title: Statistical Combination of Diagnostic Tests + maintainer: Gokmen Zararsiz + description: |- + A system for combining two diagnostic tests using various approaches + that include statistical and machine-learning-based methodologies. + These approaches are divided into four groups: linear combination + methods, non-linear combination methods, mathematical operators, + and machine learning algorithms. See + the website + for more information, documentation, and examples. + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dtComb + url_git: https://github.com/gokmenzararsiz/dtComb +DTComPair: + version: 1.2.6 + title: Comparison of Binary Diagnostic Tests in a Paired Study Design + maintainer: Christian Stock + description: Comparison of the accuracy of two binary diagnostic tests in a "paired" + study design, i.e. when each test is applied to each subject in the study. + date_publication: '2024-09-24' + bug_reports: https://github.com/chstock/DTComPair/issues + url: https://chstock.github.io/DTComPair/ + url_cran: https://CRAN.R-project.org/package=DTComPair + url_git: https://github.com/chstock/DTComPair +DtD: + version: 0.2.2 + title: Distance to Default + maintainer: Benjamin Christoffersen + description: |- + Provides fast methods to work with Merton's distance to default + model introduced in Merton (1974) . + The methods includes simulation and estimation of the parameters. + date_publication: '2020-02-11' + bug_reports: https://github.com/boennecd/DtD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DtD + url_git: '' +DTDA: + version: 3.0.1 + title: Doubly Truncated Data Analysis + maintainer: Carla Moreira + description: |- + Implementation of different algorithms for analyzing + randomly truncated data, one-sided and two-sided (i.e. doubly) + truncated data. It serves to compute empirical cumulative + distributions and also kernel density and hazard functions + using different bandwidth selectors. + Several real data sets are included. + date_publication: '2022-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTDA + url_git: '' +DTDA.cif: + version: 1.0.2 + title: Doubly Truncated Data Analysis, Cumulative Incidence Functions + maintainer: José Carlos Soage González + description: Nonparametric estimator of the cumulative incidences of competing risks + under double truncation. The estimator generalizes the Efron-Petrosian NPMLE (Non-Parametric + Maximun Likelihood Estimator) to the competing risks setting. Efron, B. and Petrosian, + V. (1999) . + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTDA.cif + url_git: '' +DTDA.ni: + version: 1.0.1 + title: Doubly Truncated Data Analysis, Non Iterative + maintainer: José Carlos Soage González + description: Non-iterative estimator for the cumulative distribution of a doubly + truncated variable. de Uña-Álvarez J. (2018) . + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTDA.ni + url_git: https://github.com/sidoruvigo/DTDA.ni +dtgiw: + version: 1.0.0 + title: Discrete Transmuted Generalized Inverse Weibull Distribution + maintainer: Atchanut Rattanalertnusorn + description: 'The Discrete Transmuted Generalized Inverse Weibull (DTGIW) distribution + is a new distribution for count data analysis. The DTGIW is discrete distribution + based on Atchanut and Sirinapa (2021). .' + date_publication: '2022-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dtgiw + url_git: '' +dti: + version: 1.5.4.3 + title: Analysis of Diffusion Weighted Imaging (DWI) Data + maintainer: Karsten Tabelow + description: |- + Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging + modality, that measures diffusion of water in tissues like the human + brain. The package contains R-functions to process diffusion-weighted + data. The functionality includes diffusion tensor imaging (DTI), + diffusion kurtosis imaging (DKI), modeling for high angular resolution + diffusion weighted imaging (HARDI) using Q-ball-reconstruction and + tensor mixture models, several methods for structural adaptive + smoothing including POAS and msPOAS, and a streamline fiber tracking + for tensor and tensor mixture models. + The package provides functionality to manipulate and visualize results + in 2D and 3D. + date_publication: '2024-09-26' + bug_reports: '' + url: https://www.wias-berlin.de/research/ats/imaging/ + url_cran: https://CRAN.R-project.org/package=dti + url_git: '' +dtmapi: + version: 0.0.2 + title: Fetching Data from the 'Displacement Tracking Matrix' + maintainer: Luong Bang Tran + description: Allows humanitarian community, academia, media, government, and non-governmental + organizations to utilize the data collected by the 'Displacement Tracking Matrix' + (), a unit in the International Organization for Migration. + This also provides non-sensitive Internally Displaced Person figures, aggregated + at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller + administrative areas) levels. + date_publication: '2024-09-17' + bug_reports: '' + url: https://displacement-tracking-matrix.github.io/dtmapi-R/ + url_cran: https://CRAN.R-project.org/package=dtmapi + url_git: https://github.com/Displacement-Tracking-Matrix/dtmapi-R +DTMCPack: + version: 0.1-3 + title: |- + Suite of Functions Related to Discrete-Time Discrete-State + Markov Chains + maintainer: William Nicholson + description: A series of functions which aid in both simulating and determining + the properties of finite, discrete-time, discrete state markov chains. Two functions + (DTMC, MultDTMC) produce n iterations of a Markov Chain(s) based on transition + probabilities and an initial distribution. The function FPTime determines the + first passage time into each state. The function statdistr determines the stationary + distribution of a Markov Chain. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTMCPack + url_git: '' +dtp: + version: 0.1.0 + title: Dynamic Panel Threshold Model + maintainer: Taha Zaghdoudi + description: 'Compute the dynamic threshold panel model suggested by (Stephanie + Kremer, Alexander Bick and Dieter Nautz (2013) ) + in which they extended the (Hansen (1999) ) + original static panel threshold estimation and the Caner and (Hansen (2004) ) + cross-sectional instrumental variable threshold model, where generalized methods + of moments type estimators are used.' + date_publication: '2018-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dtp + url_git: '' +dtpcrm: + version: 0.1.1 + title: Dose Transition Pathways for Continual Reassessment Method + maintainer: Christina Yap + description: |- + Provides the dose transition pathways (DTP) to project in advance + the doses recommended by a model-based design for subsequent patients (stay, + escalate, deescalate or stop early) using all the accumulated toxicity + information; See Yap et al (2017) . DTP + can be used as a design and an operational tool and can be displayed as a + table or flow diagram. The 'dtpcrm' package also provides the modified + continual reassessment method (CRM) and time-to-event CRM (TITE-CRM) with + added practical considerations to allow stopping early when there is + sufficient evidence that the lowest dose is too toxic and/or there is a + sufficient number of patients dosed at the maximum tolerated dose. + date_publication: '2019-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dtpcrm + url_git: '' +dtplyr: + version: 1.3.1 + title: Data Table Back-End for 'dplyr' + maintainer: Hadley Wickham + description: |- + Provides a data.table backend for 'dplyr'. The goal of + 'dtplyr' is to allow you to write 'dplyr' code that is automatically + translated to the equivalent, but usually much faster, data.table + code. + date_publication: '2023-03-22' + bug_reports: https://github.com/tidyverse/dtplyr/issues + url: https://dtplyr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=dtplyr + url_git: https://github.com/tidyverse/dtplyr +dtrackr: + version: 0.4.6 + title: Track your Data Pipelines + maintainer: Robert Challen + description: |- + Track and + document 'dplyr' data pipelines. As you filter, mutate, and join your + way through a data set, 'dtrackr' seamlessly keeps track of your data + flow and makes publication ready documentation of a data pipeline simple. + date_publication: '2024-10-21' + bug_reports: https://github.com/terminological/dtrackr/issues + url: https://terminological.github.io/dtrackr/index.html + url_cran: https://CRAN.R-project.org/package=dtrackr + url_git: https://github.com/terminological/dtrackr +dtreg: + version: 1.1.1 + title: |- + Interact with Data Type Registries and Create Machine-Readable + Data + maintainer: Olga Lezhnina + description: |- + You can load a schema from a DTR (data type registry) as an R + object. Use this schema to write your data in JSON-LD (JavaScript + Object Notation for Linked Data) format to make it machine readable. + date_publication: '2025-02-15' + bug_reports: https://gitlab.com/TIBHannover/orkg/dtreg-r/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dtreg + url_git: https://gitlab.com/TIBHannover/orkg/dtreg-r +DTRKernSmooth: + version: 1.1.0 + title: |- + Estimate and Make Inference About Optimal Treatment Regimes via + Smoothed Methods + maintainer: Yunan Wu + description: 'Methods to estimate the optimal treatment regime among all linear + regimes via smoothed estimation methods, and construct element-wise confidence + intervals for the optimal linear treatment regime vector, as well as the confidence + interval for the optimal value via wild bootstrap procedures, if the population + follows treatments recommended by the optimal linear regime. See more details + in: Wu, Y. and Wang, L. (2021), "Resampling-based Confidence Intervals for Model-free + Robust Inference on Optimal Treatment Regimes", Biometrics, 77: 465– 476, .' + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTRKernSmooth + url_git: '' +DTRlearn2: + version: '1.1' + title: |- + Statistical Learning Methods for Optimizing Dynamic Treatment + Regimes + maintainer: Yuan Chen + description: We provide a comprehensive software to estimate general K-stage DTRs + from SMARTs with Q-learning and a variety of outcome-weighted learning methods. + Penalizations are allowed for variable selection and model regularization. With + the outcome-weighted learning scheme, different loss functions - SVM hinge loss, + SVM ramp loss, binomial deviance loss, and L2 loss - are adopted to solve the + weighted classification problem at each stage; augmentation in the outcomes is + allowed to improve efficiency. The estimated DTR can be easily applied to a new + sample for individualized treatment recommendations or DTR evaluation. + date_publication: '2020-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTRlearn2 + url_git: '' +DTRreg: + version: '2.2' + title: |- + DTR Estimation and Inference via G-Estimation, Dynamic WOLS, + Q-Learning, and Dynamic Weighted Survival Modeling (DWSurv) + maintainer: Shannon T. Holloway + description: |- + Dynamic treatment regime estimation and inference via G-estimation, + dynamic weighted ordinary least squares (dWOLS) and Q-learning. Inference via + bootstrap and recursive sandwich estimation. Estimation and + inference for survival outcomes via Dynamic Weighted Survival Modeling (DWSurv). + Extension to continuous treatment variables. Wallace et al. (2017) + ; Simoneau et al. (2020) + . + date_publication: '2024-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTRreg + url_git: '' +dtrSurv: + version: '1.4' + title: Dynamic Treatment Regimes for Survival Analysis + maintainer: Shannon T. Holloway + description: Provides methods for estimating multi-stage optimal dynamic treatment + regimes for survival outcomes with dependent censoring. Cho, H., Holloway, S. + T., and Kosorok, M. R. (2020) . + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dtrSurv + url_git: '' +DTSEA: + version: 0.0.3 + title: Drug Target Set Enrichment Analysis + maintainer: Junwei Han + description: 'It is a novel tool used to identify the candidate drugs against a + particular disease based on the drug target set enrichment analysis. It assumes + the most effective drugs are those with a closer affinity in the protein-protein + interaction network to the specified disease. (See Gómez-Carballa et al. (2022) + and Feng et al. (2022) + for disease expression profiles; see Wishart et al. (2018) + and Gaulton et al. (2017) for drug target information; + see Kanehisa et al. (2021) for the details of KEGG + database.)' + date_publication: '2022-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTSEA + url_git: '' +DTSg: + version: 2.0.0 + title: |- + A Class for Working with Time Series Data Based on 'data.table' + and 'R6' with Largely Optional Reference Semantics + maintainer: Gerold Hepp + description: |- + Basic time series functionalities such as listing of missing + values, application of arbitrary aggregation as well as rolling (asymmetric) + window functions and automatic detection of periodicity. As it is mainly + based on 'data.table', it is fast and (in combination with the 'R6' package) + offers reference semantics. In addition to its native R6 interface, it + provides an S3 interface for those who prefer the latter. Finally yet + importantly, its functional approach allows for incorporating + functionalities from many other packages. + date_publication: '2025-01-20' + bug_reports: https://github.com/gisler/DTSg/issues + url: https://gisler.github.io/DTSg/ + url_cran: https://CRAN.R-project.org/package=DTSg + url_git: '' +DTSR: + version: 0.1.0 + title: Distributed Trimmed Scores Regression for Handling Missing Data + maintainer: Guangbao Guo + description: Provides functions for handling missing data using Distributed Trimmed + Scores Regression and other imputation methods. It includes facilities for data + imputation, evaluation metrics, and clustering analysis. It is designed to work + in distributed computing environments to handle large datasets efficiently. The + philosophy of the package is described in Guo G. (2024) . + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTSR + url_git: '' +dtt: + version: 0.1-2 + title: Discrete Trigonometric Transforms + maintainer: Lukasz Komsta + description: This package provides functions for 1D and 2D DiscreteCosine + Transform (DCT), Discrete Sine Transform (DST) andDiscrete Hartley Transform + (DHT). + date_publication: '2013-12-30' + bug_reports: '' + url: http://www.komsta.net/ + url_cran: https://CRAN.R-project.org/package=dtt + url_git: '' +dttr2: + version: 0.5.2 + title: Manipulate Date, POSIXct and hms Vectors + maintainer: Ayla Pearson + description: |- + Manipulates date ('Date'), date time ('POSIXct') and time + ('hms') vectors. Date/times are considered discrete and are floored + whenever encountered. Times are wrapped and time zones are maintained + unless explicitly altered by the user. + date_publication: '2024-09-26' + bug_reports: https://github.com/poissonconsulting/dttr2/issues + url: https://poissonconsulting.github.io/dttr2/ + url_cran: https://CRAN.R-project.org/package=dttr2 + url_git: https://github.com/poissonconsulting/dttr2 +dtts: + version: 0.1.3 + title: '''data.table'' Time-Series' + maintainer: Dirk Eddelbuettel + description: High-frequency time-series support via 'nanotime' and 'data.table'. + date_publication: '2024-07-18' + bug_reports: https://github.com/eddelbuettel/dtts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dtts + url_git: '' +dtw: + version: 1.23-1 + title: Dynamic Time Warping Algorithms + maintainer: Toni Giorgino + description: |- + A comprehensive implementation of dynamic time warping + (DTW) algorithms in R. DTW computes the optimal (least cumulative + distance) alignment between points of two time series. Common DTW + variants covered include local (slope) and global (window) + constraints, subsequence matches, arbitrary distance definitions, + normalizations, minimum variance matching, and so on. Provides + cumulative distances, alignments, specialized plot styles, etc., + as described in Giorgino (2009) . + date_publication: '2022-09-19' + bug_reports: '' + url: https://dynamictimewarping.github.io/ + url_cran: https://CRAN.R-project.org/package=dtw + url_git: http://dtw.r-forge.r-project.org/ +DTWBI: + version: '1.1' + title: Imputation of Time Series Based on Dynamic Time Warping + maintainer: Emilie Poisson-Caillault + description: Functions to impute large gaps within time series based on Dynamic + Time Warping methods. It contains all required functions to create large missing + consecutive values within time series and to fill them, according to the paper + Phan et al. (2017), . Performance criteria are + added to compare similarity between two signals (query and reference). + date_publication: '2018-07-11' + bug_reports: '' + url: http://mawenzi.univ-littoral.fr/DTWBI/ + url_cran: https://CRAN.R-project.org/package=DTWBI + url_git: '' +dtwclust: + version: 6.0.0 + title: |- + Time Series Clustering Along with Optimizations for the Dynamic + Time Warping Distance + maintainer: Alexis Sarda + description: |- + Time series clustering along with optimized techniques related + to the Dynamic Time Warping distance and its corresponding lower bounds. + Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole + clustering are available. Functionality can be easily extended with + custom distance measures and centroid definitions. Implementations of + DTW barycenter averaging, a distance based on global alignment kernels, + and the soft-DTW distance and centroid routines are also provided. + All included distance functions have custom loops optimized for the + calculation of cross-distance matrices, including parallelization support. + Several cluster validity indices are included. + date_publication: '2024-07-23' + bug_reports: https://github.com/asardaes/dtwclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dtwclust + url_git: https://github.com/asardaes/dtwclust +DTwrappers: + version: 0.0.2 + title: |- + Simplified Data Analysis with Wrapper Functions for the + 'Data.Table' Package + maintainer: Mayur Bansal + description: Provides functionality for users who are learning R or the techniques + of data analysis. Written as a collection of wrapper functions, the 'DTwrapper' + package facilitates many core operations of data processing. This is achieved + with relatively few requirements about the order of the processing steps or knowledge + of specialized syntax. 'DTwrappers' creates coding results along with translations + to data.table's code. This enables users to benefit from the speed and efficiency + of data.table's calculations. Furthermore, the package also provides the translated + code for educational purposes so that users can review working examples of coding + syntax and calculations. + date_publication: '2021-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTwrappers + url_git: '' +DTwrappers2: + version: 0.0.3 + title: Extensions of 'DTwrappers' + maintainer: Srivastav Budugutta + description: Offers functionality which provides methods for data analyses and cleaning + that can be flexibly applied across multiple variables and in groups. These include + cleaning accidental text, contingent calculations, counting missing data, and + building summarizations of the data. + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DTwrappers2 + url_git: '' +DTWUMI: + version: '1.0' + title: |- + Imputation of Multivariate Time Series Based on Dynamic Time + Warping + maintainer: POISSON-CAILLAULT Emilie + description: 'Functions to impute large gaps within multivariate time series based + on Dynamic Time Warping methods. Gaps of size 1 or inferior to a defined threshold + are filled using simple average and weighted moving average respectively. Larger + gaps are filled using the methodology provided by Phan et al. (2017) : + a query is built immediately before/after a gap and a moving window is used to + find the most similar sequence to this query using Dynamic Time Warping. To lower + the calculation time, similar sequences are pre-selected using global features. + Contrary to the univariate method (package ''DTWBI''), these global features are + not estimated over the sequence containing the gap(s), but a feature matrix is + built to summarize general features of the whole multivariate signal. Once the + most similar sequence to the query has been identified, the adjacent sequence + to this window is used to fill the gap considered. This function can deal with + multiple gaps over all the sequences componing the input multivariate signal. + However, for better consistency, large gaps at the same location over all sequences + should be avoided.' + date_publication: '2018-07-13' + bug_reports: '' + url: http://mawenzi.univ-littoral.fr/DTWUMI/ + url_cran: https://CRAN.R-project.org/package=DTWUMI + url_git: '' +dual: + version: 0.0.5 + title: Automatic Differentiation with Dual Numbers + maintainer: Luca Sartore + description: |- + Automatic differentiation is achieved by using dual numbers without + providing hand-coded gradient functions. The output value of a mathematical + function is returned with the values of its exact first derivative + (or gradient). For more details see Baydin, Pearlmutter, Radul, and Siskind + (2018) . + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dual + url_git: '' +dualScale: + version: 1.0.0 + title: Dual Scaling Analysis of Data + maintainer: Roberto de la Banda + description: 'Dual Scaling, developed by Professor Shizuhiko Nishisato (1994, ISBN: + 0-9691785-3-6), is a fundamental technique in multivariate analysis used for data + scaling and correspondence analysis. Its utility lies in its ability to represent + multidimensional data in a lower-dimensional space, making it easier to visualize + and understand underlying patterns in complex data. This technique has been implemented + to handle various types of data, including Contingency and Frequency data (CF), + Multiple-Choice data (MC), Sorting data (SO), Paired-Comparison data (PC), and + Rank-Order data (RO), providing users with a powerful tool to explore relationships + between variables and observations in various fields, from sociology to ecology, + enabling deeper and more efficient analysis of multivariate datasets.' + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dualScale + url_git: '' +dualtrees: + version: 0.1.5 + title: Decimated and Undecimated 2D Complex Dual-Tree Wavelet Transform + maintainer: Sebastian Buschow + description: An implementation of the decimated two-dimensional complex dual-tree + wavelet transform as described in Kingsbury (1999) + and Selesnick et al. (2005) . Also includes the + undecimated version and spectral bias correction described in Nelson et al. (2018) + . The code is partly based on the 'dtcwt' Python + library. + date_publication: '2023-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dualtrees + url_git: '' +duawranglr: + version: 0.6.7 + title: Securely Wrangle Dataset According to Data Usage Agreement + maintainer: Benjamin Skinner + description: |- + Create shareable data sets from raw data files that + contain protected elements. Relying on master crosswalk + files that list restricted variables, package functions + warn users about possible violations of data usage + agreement and prevent writing protected elements. + date_publication: '2021-04-15' + bug_reports: https://github.com/btskinner/duawranglr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=duawranglr + url_git: https://github.com/btskinner/duawranglr +dub: + version: 0.2.0 + title: Unpacking Assignment for Lists via Pattern Matching + maintainer: Eugene Ha + description: |- + Provides an operator for assigning nested components of a list to + names via a concise pattern matching syntax. This is especially convenient for + assigning individual names to the multiple values that a function may return + in the form of a list, and for extracting deeply nested list components. + date_publication: '2018-10-27' + bug_reports: https://github.com/egnha/dub/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dub + url_git: https://github.com/egnha/dub +duckdb: + version: 1.2.0 + title: DBI Package for the DuckDB Database Management System + maintainer: Kirill Müller + description: |- + The DuckDB project is an embedded analytical data management + system with support for the Structured Query Language (SQL). This + package includes all of DuckDB and an R Database Interface (DBI) + connector. + date_publication: '2025-02-21' + bug_reports: https://github.com/duckdb/duckdb-r/issues + url: https://r.duckdb.org/ + url_cran: https://CRAN.R-project.org/package=duckdb + url_git: https://github.com/duckdb/duckdb-r +duckdbfs: + version: 0.0.9 + title: |- + High Performance Remote File System, Database and 'Geospatial' + Access Using 'duckdb' + maintainer: Carl Boettiger + description: |- + Provides friendly wrappers for creating 'duckdb'-backed connections + to tabular datasets ('csv', parquet, etc) on local or remote file systems. + This mimics the behaviour of "open_dataset" in the 'arrow' package, + but in addition to 'S3' file system also generalizes to any list of 'http' URLs. + date_publication: '2024-12-17' + bug_reports: https://github.com/cboettig/duckdbfs/issues + url: https://cboettig.github.io/duckdbfs/ + url_cran: https://CRAN.R-project.org/package=duckdbfs + url_git: https://github.com/cboettig/duckdbfs +duckduckr: + version: 1.0.0 + title: Simple Client for the DuckDuckGo Instant Answer API + maintainer: Schumacher Dirk + description: Programmatic access to the DuckDuckGo Instant Answer API . + date_publication: '2017-04-07' + bug_reports: https://github.com/dirkschumacher/duckduckr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=duckduckr + url_git: https://github.com/dirkschumacher/duckduckr +duckplyr: + version: 1.0.1 + title: A 'DuckDB'-Backed Version of 'dplyr' + maintainer: Kirill Müller + description: |- + A drop-in replacement for 'dplyr', powered by 'DuckDB' for + performance. Offers convenient utilities for working with in-memory and + larger-than-memory data while retaining full 'dplyr' compatibility. + date_publication: '2025-02-27' + bug_reports: https://github.com/tidyverse/duckplyr/issues + url: https://duckplyr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=duckplyr + url_git: https://github.com/tidyverse/duckplyr +duet: + version: 0.1.1 + title: |- + Analysing Non-Verbal Communication in Dyadic Interactions from + Video Data + maintainer: Themis Efthimiou + description: |- + Analyzes non-verbal communication by processing data extracted + from video recordings of dyadic interactions. It supports integration + with open source tools, currently limited to 'OpenPose' (Cao et al. (2019) + ), converting its outputs into CSV format + for further analysis. The package includes functions for data pre-processing, + visualization, and computation of motion indices such as velocity, acceleration, + and jerkiness (Cook et al. (2013) ), facilitating + the analysis of non-verbal cues in paired interactions and contributing to + research on human communication dynamics. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=duet + url_git: '' +duke: + version: 0.0.3 + title: Creating a Color-Blind Friendly Duke Color Package + maintainer: Aidan Gildea + description: Generates visualizations with Duke’s official suite of colors in a + color blind friendly way. + date_publication: '2023-12-15' + bug_reports: https://github.com/aidangildea/duke/issues + url: https://aidangildea.github.io/duke/ + url_cran: https://CRAN.R-project.org/package=duke + url_git: https://github.com/aidangildea/duke +dumbbell: + version: '0.1' + title: Displaying Changes Between Two Points Using Dumbbell Plots + maintainer: Foo Cheung + description: Creates a Dumbbell Plot. + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dumbbell + url_git: https://github.com/foocheung2/dumbbell +dummy: + version: 0.1.3 + title: |- + Automatic Creation of Dummies with Support for Predictive + Modeling + maintainer: Michel Ballings + description: Efficiently create dummies of all factors and character vectors in + a data frame. Support is included for learning the categories on one data set + (e.g., a training set) and deploying them on another (e.g., a test set). + date_publication: '2015-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dummy + url_git: '' +dundermifflin: + version: 0.1.1 + title: The Office Quotes on-Demand + maintainer: Tyler Bradley + description: |- + Provides functions to randomly select, return, and print + quotes or entire scenes from the American version of + the show the Office. Receive laughs from one of of the + greatest sitcoms of all time on demand. Add these functions + to your '.Rprofile' to get a good laugh everytime you start + a new R session. + date_publication: '2020-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dundermifflin + url_git: '' +dunlin: + version: 0.1.9 + title: Preprocessing Tools for Clinical Trial Data + maintainer: Joe Zhu + description: |- + A collection of functions to preprocess data and organize + them in a format amenable to use by chevron. + date_publication: '2025-02-20' + bug_reports: https://github.com/insightsengineering/dunlin/issues + url: https://insightsengineering.github.io/dunlin/ + url_cran: https://CRAN.R-project.org/package=dunlin + url_git: https://github.com/insightsengineering/dunlin/ +dunn.test: + version: 1.3.6 + title: Dunn's Test of Multiple Comparisons Using Rank Sums + maintainer: Alexis Dinno + description: Computes Dunn's test (1964) for stochastic dominance and reports the + results among multiple pairwise comparisons after a Kruskal-Wallis test for 0th-order + stochastic dominance among k groups (Kruskal and Wallis, 1952). 'dunn.test' makes + k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations + to the actual rank statistics. The null hypothesis for each pairwise comparison + is that the probability of observing a randomly selected value from the first + group that is larger than a randomly selected value from the second group equals + one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney + rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, + and the distributions are assumed identical except for a difference in location, + Dunn's test may be understood as a test for median difference and for mean difference. + 'dunn.test' accounts for tied ranks. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dunn.test + url_git: '' +dupiR: + version: 1.2.1 + title: Bayesian Inference from Count Data using Discrete Uniform Priors + maintainer: Federico Comoglio + description: We consider a set of sample counts obtained by sampling arbitrary fractions + of a finite volume containing an homogeneously dispersed population of identical + objects. This package implements a Bayesian derivation of the posterior probability + distribution of the population size using a binomial likelihood and non-conjugate, + discrete uniform priors under sampling with or without replacement. This can be + used for a variety of statistical problems involving absolute quantification under + uncertainty. See Comoglio et al. (2013) . + date_publication: '2024-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dupiR + url_git: '' +dupNodes: + version: 0.3.0 + title: |- + Computes DNSLbetweenness, a Betweenness Measure that Includes + Self-Loops + maintainer: Juan Julián Merelo-Guervós + description: |- + Computes a new measure, DNSL betweenness, via the creation + of a new graph from an existing one, duplicating nodes + with self-loops. This betweenness centrality does not drop this + essential information. Implements + Merelo & Molinari (2024) . + date_publication: '2024-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dupNodes + url_git: '' +dupree: + version: 0.3.0 + title: Identify Duplicated R Code in a Project + maintainer: Russ Hyde + description: |- + Identifies code blocks that have a high level of similarity + within a set of R files. + date_publication: '2020-04-21' + bug_reports: https://github.com/russHyde/dupree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dupree + url_git: https://github.com/russHyde/dupree +Durga: + version: '2.0' + title: Effect Size Estimation and Visualisation + maintainer: Jim McLean + description: |- + An easy-to-use yet powerful system for plotting grouped data effect sizes. + Various types of effect size can be estimated, then plotted together with a + representation of the original data. Select from many possible data representations + (box plots, violin plots, raw data points etc.), and combine as desired. + 'Durga' plots are implemented in base R, so are compatible with base R methods + for combining plots, such as 'layout()'. See Khan & McLean (2023) + . + date_publication: '2023-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Durga + url_git: https://github.com/KhanKawsar/EstimationPlot +dverse: + version: 0.2.0 + title: Document a Universe of Packages + maintainer: Mauro Lepore + description: |- + Creates a data frame containing the metadata associated with + the documentation of a collection of R packages. It allows for linking + topic names to their corresponding documentation online. If you + maintain a universe meta-package, it helps create a comprehensive + reference for its website. + date_publication: '2024-12-08' + bug_reports: https://github.com/maurolepore/dverse/issues + url: https://maurolepore.github.io/dverse/ + url_cran: https://CRAN.R-project.org/package=dverse + url_git: https://github.com/maurolepore/dverse +DVHmetrics: + version: 0.4.2 + title: Analyze Dose-Volume Histograms and Check Constraints + maintainer: Daniel Wollschlaeger + description: |- + Functionality for analyzing dose-volume histograms (DVH) + in radiation oncology: Read DVH text files, calculate DVH + metrics as well as generalized equivalent uniform dose (gEUD), + biologically effective dose (BED), equivalent dose in 2 Gy + fractions (EQD2), normal tissue complication probability + (NTCP), and tumor control probability (TCP). Show DVH + diagrams, check and visualize quality assurance constraints + for the DVH. Includes web-based graphical user interface. + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DVHmetrics + url_git: https://github.com/dwoll/DVHmetrics/ +dvir: + version: 3.3.0 + title: Disaster Victim Identification + maintainer: Magnus Dehli Vigeland + description: |- + Joint DNA-based disaster victim identification (DVI), as + described in Vigeland and Egeland (2021) + . Identification is performed by + optimising the joint likelihood of all victim samples and reference + individuals. Individual identification probabilities, conditional on + all available information, are derived from the joint solution in the + form of posterior pairing probabilities. 'dvir' is part of the + 'pedsuite' collection of packages for pedigree analysis. + date_publication: '2024-09-09' + bug_reports: https://github.com/magnusdv/dvir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dvir + url_git: https://github.com/magnusdv/dvir +dvmisc: + version: 1.1.4 + title: Convenience Functions, Moving Window Statistics, and Graphics + maintainer: Dane R. Van Domelen + description: Contains functions that do something convenient (e.g. create BMI categories), + functions for calculating moving-window statistics efficiently, and functions + for generating various figures (e.g. histograms with fitted probability mass/density + function). + date_publication: '2019-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dvmisc + url_git: '' +dvqcc: + version: 0.1.0 + title: Dynamic VAR - Based Control Charts for Batch Process Monitoring + maintainer: Danilo Marcondes Filho + description: A set of control charts for batch processes based on the VAR model. + The package contains the implementation of T2.var and W.var control charts based + on VAR model coefficients using the couple vectors theory. In each time-instant + the VAR coefficients are estimated from a historical in-control dataset and a + decision rule is made for online classifying of a new batch data. Those charts + allow efficient online monitoring since the very first time-instant. The offline + version is available too. In order to evaluate the chart's performance, this package + contains functions to generate batch data for offline and online monitoring.See + in Danilo Marcondes Filho and Marcio Valk (2020) . + date_publication: '2020-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dvqcc + url_git: '' +dwctaxon: + version: 2.0.3 + title: Edit and Validate Darwin Core Taxon Data + maintainer: Joel H. Nitta + description: |- + Edit and validate taxonomic data in compliance with Darwin Core + standards (Darwin Core 'Taxon' class ). + date_publication: '2023-12-13' + bug_reports: https://github.com/ropensci/dwctaxon/issues + url: https://docs.ropensci.org/dwctaxon/ + url_cran: https://CRAN.R-project.org/package=dwctaxon + url_git: https://github.com/ropensci/dwctaxon +DWDLargeR: + version: 0.2-0 + title: |- + Fast Algorithms for Large Scale Generalized Distance Weighted + Discrimination + maintainer: Xin-Yee Lam + description: |- + Solving large scale distance weighted discrimination. + The main algorithm is a symmetric Gauss-Seidel based alternating direction method of multipliers (ADMM) method. See Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018) for more details. + date_publication: '2024-08-19' + bug_reports: '' + url: https://arxiv.org/pdf/1604.05473 + url_cran: https://CRAN.R-project.org/package=DWDLargeR + url_git: '' +dwdradar: + version: 0.2.10 + title: Read Binary Radar Files from 'DWD' (German Weather Service) + maintainer: Berry Boessenkool + description: |- + The 'DWD' provides gridded radar data for Germany in binary format. + 'dwdradar' reads these files and enables a fast conversion into numerical format. + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dwdradar + url_git: '' +dwlm: + version: 0.1.0 + title: Doubly Weighted Linear Model + maintainer: Hugo Gasca-Aragon + description: This linear model solution is useful when both predictor and response + have associated uncertainty. The doubly weights linear model solution is invariant + on which quantity is used as predictor or response. Based on the results by Reed(1989) + and Ripley & Thompson(1987) . + date_publication: '2019-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dwlm + url_git: '' +DWLS: + version: 0.1.0 + title: |- + Gene Expression Deconvolution Using Dampened Weighted Least + Squares + maintainer: Adriana Sistig + description: |- + The rapid development of single-cell transcriptomic technologies + has helped uncover the cellular heterogeneity within cell populations. + However, bulk RNA-seq continues to be the main workhorse for quantifying + gene expression levels due to technical simplicity and low cost. To most + effectively extract information from bulk data given the new knowledge + gained from single-cell methods, we have developed a novel algorithm to + estimate the cell-type composition of bulk data from a single-cell + RNA-seq-derived cell-type signature. Comparison with existing methods using + various real RNA-seq data sets indicates that our new approach is more + accurate and comprehensive than previous methods, especially for the + estimation of rare cell types. More importantly,our method can detect + cell-type composition changes in response to external perturbations, + thereby providing a valuable, cost-effective method for dissecting the + cell-type-specific effects of drug treatments or condition changes. + As such, our method is applicable to a wide range of biological and + clinical investigations. Dampened weighted least squares ('DWLS') is an + estimation method for gene expression deconvolution, in which the cell-type + composition of a bulk RNA-seq data set is computationally inferred. + This method corrects common biases towards cell types that are + characterized by highly expressed genes and/or are highly prevalent, to + provide accurate detection across diverse cell types. See: + for more + information about the development of 'DWLS' and the methods behind our + functions. + date_publication: '2022-05-24' + bug_reports: https://github.com/sistia01/DWLS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DWLS + url_git: https://github.com/sistia01/DWLS +dwp: + version: '1.1' + title: Density-Weighted Proportion + maintainer: Daniel Dalthorp + description: Fit a Poisson regression to carcass distance data and integrate over + the searched area at a wind farm to estimate the fraction of carcasses falling + in the searched area and format the output for use as the dwp parameter in the + 'GenEst' or 'eoa' package for estimating bird and bat mortality, following Dalthorp, + et al. (2022) . + date_publication: '2023-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dwp + url_git: '' +DWreg: + version: '2.0' + title: Parametric Regression for Discrete Response + maintainer: Veronica Vinciotti + description: Regression for a discrete response, where the conditional distribution + is modelled via a discrete Weibull distribution. + date_publication: '2016-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DWreg + url_git: '' +dyads: + version: 1.2.1 + title: Dyadic Network Analysis + maintainer: Bonne J.H. Zijlstra + description: 'Contains functions for the MCMC simulation of dyadic network models + j2 (Zijlstra, 2017, ) and p2 (Van Duijn, Snijders + & Zijlstra, 2004, ), the multilevel p2 + model (Zijlstra, Van Duijn & Snijders (2009) ), + and the bidirectional (multilevel) counterpart of the the multilevel p2 model + as described in Zijlstra, Van Duijn & Snijders (2009) , + the (multilevel) b2 model.' + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dyads + url_git: '' +dycdtools: + version: 0.4.4 + title: |- + Calibration Assistant and Post-Processing Tool for Aquatic + Ecosystem Model DYRESM-CAEDYM + maintainer: Songyan Yu + description: Dynamic Reservoir Simulation Model (DYRESM) and Computational Aquatic + Ecosystem Dynamics Model (CAEDYM) model development, including assisting with + calibrating selected model parameters and visualising model output through time + series plot, profile plot, contour plot, and scatter plot. For more details, see + Yu et al. (2023) . + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dycdtools + url_git: https://github.com/SongyanYu/dycdtools +dydea: + version: 0.1.0 + title: Detection of Chaotic and Regular Intervals in the Data + maintainer: Radek Halfar + description: |- + Finds regular and chaotic intervals in the data using + the 0-1 test for chaos proposed by Gottwald and Melbourne (2004) + . + date_publication: '2019-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dydea + url_git: '' +dygraphs: + version: 1.1.1.6 + title: Interface to 'Dygraphs' Interactive Time Series Charting Library + maintainer: Petr Shevtsov + description: |- + An R interface to the 'dygraphs' JavaScript charting library + (a copy of which is included in the package). Provides rich facilities + for charting time-series data in R, including highly configurable + series- and axis-display and interactive features like zoom/pan and + series/point highlighting. + date_publication: '2018-07-11' + bug_reports: https://github.com/rstudio/dygraphs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dygraphs + url_git: https://github.com/rstudio/dygraphs +Dykstra: + version: 1.0-0 + title: Quadratic Programming using Cyclic Projections + maintainer: Nathaniel E. Helwig + description: Solves quadratic programming problems using Richard L. Dykstra's cyclic + projection algorithm. Routine allows for a combination of equality and inequality + constraints. See Dykstra (1983) for details. + date_publication: '2018-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Dykstra + url_git: '' +DYM: + version: '0.2' + title: Did You Mean? + maintainer: Kosei Abe + description: |- + Add a "Did You Mean" feature to the R interactive. With this + package, error messages for misspelled input of variable names or package names + suggest what you really want to do in addition to notification of the mistake. + date_publication: '2016-01-22' + bug_reports: https://github.com/kos59125/DYM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DYM + url_git: '' +DyMEP: + version: 0.1.2 + title: Dynamic Multi Environment Phenology-Model + maintainer: Flavian Tschurr + description: Mechanistically models/predicts the phenology (macro-phases) of 10 + crop plants (trained on a big dataset over 80 years derived from the German weather + service (DWD) ). Can be applied for remote sensing purposes, + dynamically check the best subset of available covariates for the given dataset + and crop. + date_publication: '2024-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DyMEP + url_git: '' +dymo: + version: 1.1.0 + title: |- + Dynamic Mode Decomposition for Multivariate Time Feature + Prediction + maintainer: Giancarlo Vercellino + description: An application of Dynamic Mode Decomposition for prediction of time + features. Automatic search for the best model across the space of all possible + feature combinations and ranks of Singular Value Decomposition. + date_publication: '2022-05-05' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/dymo + url_cran: https://CRAN.R-project.org/package=dymo + url_git: '' +dyn: + version: 0.2-9.6 + title: Time Series Regression + maintainer: M. Leeds + description: |- + Time series regression. The dyn class interfaces ts, + irts(), zoo() and zooreg() time series classes to lm(), glm(), + loess(), quantreg::rq(), MASS::rlm(), MCMCpack::MCMCregress(), + quantreg::rq(), randomForest::randomForest() and other regression + functions allowing those functions to be used with time series + including specifications that may contain lags, diffs and + missing values. + date_publication: '2018-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dyn + url_git: '' +dyn.log: + version: 0.4.0 + title: |- + Dynamic Logging for R Inspired by Configuration Driven + Development + maintainer: Brandon Moretz + description: |- + A comprehensive and dynamic configuration driven logging package for R. While there + are several excellent logging solutions already in the R ecosystem, I always feel constrained + in some way by each of them. Every project is designed differently to solve it's domain specific problem, + and ultimately the utility of a logging solution is its ability to adapt to this design. This is the + raison d'être for 'dyn.log': to provide a modular design, template mechanics and a configuration-based + integration model, so that the logger can integrate deeply into your design, even though it knows + nothing about it. + date_publication: '2022-03-14' + bug_reports: https://github.com/bmoretz/dyn.log/issues + url: https://bmoretz.github.io/dyn.log/ + url_cran: https://CRAN.R-project.org/package=dyn.log + url_git: '' +dynamac: + version: 0.1.12 + title: Dynamic Simulation and Testing for Single-Equation ARDL Models + maintainer: Soren Jordan + description: While autoregressive distributed lag (ARDL) models allow for extremely + flexible dynamics, interpreting substantive significance of complex lag structures + remains difficult. This package is designed to assist users in dynamically simulating + and plotting the results of various ARDL models. It also contains post-estimation + diagnostics, including a test for cointegration when estimating the error-correction + variant of the autoregressive distributed lag model (Pesaran, Shin, and Smith + 2001 ). + date_publication: '2022-11-17' + bug_reports: https://github.com/andyphilips/dynamac/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynamac + url_git: https://github.com/andyphilips/dynamac/ +dynamAedes: + version: 2.2.9 + title: |- + A Unified Mechanistic Model for the Population Dynamics of + Invasive Aedes Mosquitoes + maintainer: Matteo Marcantonio + description: 'Generalised model for population dynamics of invasive Aedes mosquitoes. + Rationale and model structure are described here: Da Re et al. (2021) + and Da Re et al. (2022) .' + date_publication: '2024-03-12' + bug_reports: https://github.com/mattmar/dynamAedes + url: https://mattmar.github.io/dynamAedes/ + url_cran: https://CRAN.R-project.org/package=dynamAedes + url_git: '' +dynamic: + version: 1.1.0 + title: DFI Cutoffs for Latent Variable Models + maintainer: Melissa G. Wolf + description: |- + Returns dynamic fit index (DFI) cutoffs for latent variable models + that are tailored to the user's model statement, model type, and sample size. + This is the counterpart of the Shiny Application, . + date_publication: '2022-02-28' + bug_reports: https://github.com/melissagwolf/dynamic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynamic + url_git: https://github.com/melissagwolf/dynamic +dynamicSDM: + version: 1.3.4 + title: |- + Species Distribution and Abundance Modelling at High + Spatio-Temporal Resolution + maintainer: Rachel Dobson + description: A collection of novel tools for generating species distribution and + abundance models (SDM) that are dynamic through both space and time. These highly + flexible functions incorporate spatial and temporal aspects across key SDM stages; + including when cleaning and filtering species occurrence data, generating pseudo-absence + records, assessing and correcting sampling biases and autocorrelation, extracting + explanatory variables and projecting distribution patterns. Throughout, functions + utilise Google Earth Engine and Google Drive to minimise the computing power and + storage demands associated with species distribution modelling at high spatio-temporal + resolution. + date_publication: '2024-06-28' + bug_reports: https://github.com/r-a-dobson/dynamicSDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynamicSDM + url_git: https://github.com/r-a-dobson/dynamicSDM +dynamicTreeCut: + version: 1.63-1 + title: |- + Methods for Detection of Clusters in Hierarchical Clustering + Dendrograms + maintainer: Peter Langfelder + description: Contains methods for detection of clusters in hierarchical clustering + dendrograms. + date_publication: '2016-03-11' + bug_reports: '' + url: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/BranchCutting/ + url_cran: https://CRAN.R-project.org/package=dynamicTreeCut + url_git: '' +dynamite: + version: 1.5.5 + title: |- + Bayesian Modeling and Causal Inference for Multivariate + Longitudinal Data + maintainer: Santtu Tikka + description: |- + Easy-to-use and efficient interface for + Bayesian inference of complex panel (time series) data using dynamic + multivariate panel models by Helske and Tikka (2024) + . The package supports joint modeling of + multiple measurements per individual, time-varying and time-invariant + effects, and a wide range of discrete and continuous distributions. + Estimation of these dynamic multivariate panel models is carried out via + 'Stan'. For an in-depth tutorial of the package, see + (Tikka and Helske, 2024) . + date_publication: '2024-11-15' + bug_reports: https://github.com/ropensci/dynamite/issues/ + url: https://docs.ropensci.org/dynamite/ + url_cran: https://CRAN.R-project.org/package=dynamite + url_git: https://github.com/ropensci/dynamite/ +DynaRankR: + version: 1.1.0 + title: Inferring Longitudinal Dominance Hierarchies + maintainer: Eli D. Strauss + description: Provides functions for inferring longitudinal dominance hierarchies, + which describe dominance relationships and their dynamics in a single latent hierarchy + over time. Strauss & Holekamp (in press). + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DynaRankR + url_git: https://github.com/straussed/DynaRankR +DynareR: + version: 0.1.5 + title: |- + Bringing the Power of 'Dynare' to 'R', 'R Markdown', and + 'Quarto' + maintainer: Sagiru Mati + description: It allows running 'Dynare' program from base R, R Markdown and Quarto. + 'Dynare' is a software platform for handling a wide class of economic models, + in particular dynamic stochastic general equilibrium ('DSGE') and overlapping + generations ('OLG') models. This package does not only integrate R and Dynare + but also serves as a 'Dynare' Knit-Engine for 'knitr' package. The package requires + 'Dynare' () and 'Octave' (). Write + all your 'Dynare' commands in R or R Markdown chunk. + date_publication: '2024-10-26' + bug_reports: https://github.com/sagirumati/DynareR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DynareR + url_git: '' +dynaSpec: + version: 1.0.2 + title: Dynamic Spectrogram Visualizations + maintainer: Marcelo Araya-Salas + description: A set of tools to generate dynamic spectrogram visualizations in video + format. + date_publication: '2024-09-29' + bug_reports: https://github.com/maRce10/dynaSpec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynaSpec + url_git: https://github.com/maRce10/dynaSpec +DYNATE: + version: '0.1' + title: Dynamic Aggregation Testing + maintainer: Xuechan Li + description: A multiple testing procedure aims to find the rare-variant association + regions. When variants are rare, the single variant association test approach + suffers from low power. To improve testing power, the procedure dynamically and + hierarchically aggregates smaller genome regions to larger ones and performs multiple + testing for disease associations with a controlled node-level false discovery + rate. This method are members of the family of ancillary information assisted + recursive testing introduced in Pura, Li, Chan and Xie (2021) + and Li, Sung and Xie (2021) . + date_publication: '2022-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DYNATE + url_git: '' +dynatop: + version: 0.2.3 + title: An Implementation of Dynamic TOPMODEL Hydrological Model in R + maintainer: Paul Smith + description: An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed + hydrological model originally proposed by Beven and Freer (2001) . + The 'dynatop' package implements code for simulating models which can be created + using the 'dynatopGIS' package. + date_publication: '2022-10-10' + bug_reports: https://github.com/waternumbers/dynatop/issues + url: https://waternumbers.github.io/dynatop/ + url_cran: https://CRAN.R-project.org/package=dynatop + url_git: https://github.com/waternumbers/dynatop +dynatopGIS: + version: 0.2.5 + title: |- + Algorithms for Helping Build Dynamic TOPMODEL Implementations + from Spatial Data + maintainer: Paul Smith + description: A set of algorithms based on Quinn et al. (1991) + for processing river network and digital elevation data to build implementations + of Dynamic TOPMODEL, a semi-distributed hydrological model proposed in Beven and + Freer (2001) . The 'dynatop' package implements simulation + code for Dynamic TOPMODEL based on the output of 'dynatopGIS'. + date_publication: '2023-05-11' + bug_reports: https://github.com/waternumbers/dynatopGIS/issues + url: https://waternumbers.github.io/dynatopGIS/ + url_cran: https://CRAN.R-project.org/package=dynatopGIS + url_git: https://github.com/waternumbers/dynatopGIS +dynaTree: + version: 1.2-17 + title: Dynamic Trees for Learning and Design + maintainer: Robert B. Gramacy + description: |- + Inference by sequential Monte Carlo for + dynamic tree regression and classification models + with hooks provided for sequential design and optimization, + fully online learning with drift, variable selection, and + sensitivity analysis of inputs. Illustrative + examples from the original dynamic trees paper + (Gramacy, Taddy & Polson (2011); ) are facilitated + by demos in the package; see demo(package="dynaTree"). + date_publication: '2024-08-22' + bug_reports: '' + url: https://bobby.gramacy.com/r_packages/dynaTree/ + url_cran: https://CRAN.R-project.org/package=dynaTree + url_git: '' +dynBiplotGUI: + version: 1.1.6 + title: Full Interactive GUI for Dynamic Biplot in R + maintainer: Jaime Egido + description: |- + A GUI to solve dynamic biplots and classical biplot. Try matrices + of 2-way and 3-way. The GUI can be run in multiple languages. + date_publication: '2020-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynBiplotGUI + url_git: '' +DynClust: + version: '3.24' + title: |- + Denoising and Clustering for Dynamical Image Sequence (2D or + 3D)+t + maintainer: Yves Rozenholc + description: A two-stage procedure for the denoising and clustering of stack of + noisy images acquired over time. Clustering only assumes that the data contain + an unknown but small number of dynamic features. The method first denoises the + signals using local spatial and full temporal information. The clustering step + uses the previous output to aggregate voxels based on the knowledge of their spatial + neighborhood. Both steps use a single keytool based on the statistical comparison + of the difference of two signals with the null signal. No assumption is therefore + required on the shape of the signals. The data are assumed to be normally distributed + (or at least follow a symmetric distribution) with a known constant variance. + Working pixelwise, the method can be time-consuming depending on the size of the + data-array but harnesses the power of multicore cpus. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DynClust + url_git: '' +dynConfiR: + version: 0.0.4 + title: Dynamic Models for Confidence and Response Time Distributions + maintainer: Sebastian Hellmann + description: |- + Provides density functions for the joint distribution of + choice, response time and confidence for discrete confidence judgments + as well as functions for parameter fitting, prediction and simulation + for various dynamical models of decision confidence. All models are + explained in detail by Hellmann et al. (2023; + Preprint available at , published version: ). Implemented models are the dynaViTE model, + dynWEV model, the 2DSD model (Pleskac & Busemeyer, 2010, ), + and various race models. C++ code for dynWEV and 2DSD is based on the + 'rtdists' package by Henrik Singmann. + date_publication: '2024-01-29' + bug_reports: https://github.com/SeHellmann/dynConfiR + url: https://sehellmann.github.io/dynConfiR/ + url_cran: https://CRAN.R-project.org/package=dynConfiR + url_git: https://github.com/SeHellmann/dynConfiR +dynCorr: + version: 1.1.0 + title: Dynamic Correlation Package + maintainer: Joel Dubin + description: |- + Computes dynamical correlation estimates and percentile + bootstrap confidence intervals for pairs of longitudinal + responses, including consideration of lags and derivatives. + date_publication: '2017-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynCorr + url_git: '' +dyndimred: + version: 1.0.4 + title: Dimensionality Reduction Methods in a Common Format + maintainer: Robrecht Cannoodt + description: |2- + + Provides a common interface for applying dimensionality reduction methods, + such as Principal Component Analysis ('PCA'), Independent Component Analysis ('ICA'), diffusion maps, + Locally-Linear Embedding ('LLE'), t-distributed Stochastic Neighbor Embedding ('t-SNE'), + and Uniform Manifold Approximation and Projection ('UMAP'). + Has built-in support for sparse matrices. + date_publication: '2021-03-23' + bug_reports: https://github.com/dynverse/dyndimred/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dyndimred + url_git: https://github.com/dynverse/dyndimred +dynetNLAResistance: + version: 0.1.0 + title: Resisting Neighbor Label Attack in a Dynamic Network + maintainer: Jiaqi Tang + description: An anonymization algorithm to resist neighbor label attack in a dynamic + network. + date_publication: '2016-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynetNLAResistance + url_git: '' +DynForest: + version: 1.2.0 + title: Random Forest with Multivariate Longitudinal Predictors + maintainer: Anthony Devaux + description: |- + Based on random forest principle, 'DynForest' is able to include + multiple longitudinal predictors to provide individual predictions. + Longitudinal predictors are modeled through the random forest. The + methodology is fully described for a survival outcome in: + Devaux, Helmer, Genuer & Proust-Lima (2023) + . + date_publication: '2024-10-23' + bug_reports: https://github.com/anthonydevaux/DynForest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=DynForest + url_git: https://github.com/anthonydevaux/DynForest +dyngen: + version: 1.0.5 + title: |- + A Multi-Modal Simulator for Spearheading Single-Cell Omics + Analyses + maintainer: Robrecht Cannoodt + description: |- + A novel, multi-modal simulation engine for + studying dynamic cellular processes at single-cell resolution. 'dyngen' + is more flexible than current single-cell simulation engines. It + allows better method development and benchmarking, thereby stimulating + development and testing of novel computational methods. Cannoodt et + al. (2021) . + date_publication: '2022-10-12' + bug_reports: https://github.com/dynverse/dyngen/issues + url: https://dyngen.dynverse.org + url_cran: https://CRAN.R-project.org/package=dyngen + url_git: https://github.com/dynverse/dyngen +dynlm: + version: 0.3-6 + title: Dynamic Linear Regression + maintainer: Achim Zeileis + description: Dynamic linear models and time series regression. + date_publication: '2019-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynlm + url_git: '' +dynmix: + version: '2.1' + title: Estimation of Dynamic Finite Mixtures + maintainer: Krzysztof Drachal + description: 'Allows to perform the dynamic mixture estimation with state-space + components and normal regression components, and clustering with normal mixture. + Quasi-Bayesian estimation, as well as, that based on the Kerridge inaccuracy approximation + are implemented. Main references: Nagy and Suzdaleva (2013) ; + Nagy et al. (2011) .' + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynmix + url_git: '' +DynNom: + version: '5.1' + title: Visualising Statistical Models using Dynamic Nomograms + maintainer: Amirhossein Jalali + description: 'Demonstrate the results of a statistical model object as a dynamic + nomogram in an RStudio panel or web browser. The package provides two generics + functions: DynNom, which display statistical model objects as a dynamic nomogram; + DNbuilder, which builds required scripts to publish a dynamic nomogram on a web + server such as the . Current version of ''DynNom'' + supports stats::lm, stats::glm, survival::coxph, rms::ols, rms::Glm, rms::lrm, + rms::cph, and mgcv::gam model objects.' + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DynNom + url_git: '' +dynpanel: + version: 0.1.0 + title: Dynamic Panel Data Models + maintainer: Taha Zaghdoudi + description: Computes the first stage GMM estimate of a dynamic linear model with + p lags of the dependent variables. + date_publication: '2016-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynpanel + url_git: '' +dynparam: + version: 1.0.2 + title: Creating Meta-Information for Parameters + maintainer: Robrecht Cannoodt + description: |- + Provides tools for describing parameters of algorithms in an abstract way. + Description can include an id, a description, a domain (range or list of values), + and a default value. 'dynparam' can also convert parameter sets to a 'ParamHelpers' format, + in order to be able to use 'dynparam' in conjunction with 'mlrMBO'. + date_publication: '2021-01-04' + bug_reports: https://github.com/dynverse/dynparam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynparam + url_git: https://github.com/dynverse/dynparam +dynpred: + version: 0.1.2 + title: |- + Companion Package to "Dynamic Prediction in Clinical Survival + Analysis" + maintainer: Hein Putter + description: The dynpred package contains functions for dynamic prediction in survival + analysis. + date_publication: '2015-07-13' + bug_reports: '' + url: http://www.msbi.nl/putter + url_cran: https://CRAN.R-project.org/package=dynpred + url_git: '' +dynprog: + version: 0.1.1 + title: Dynamic Programming Domain-Specific Language + maintainer: Thomas Mailund + description: |- + A domain-specific language for specifying translating recursions + into dynamic-programming algorithms. See + for a description + of dynamic programming. + date_publication: '2019-12-09' + bug_reports: https://github.com/mailund/dynprog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynprog + url_git: https://github.com/mailund/dynprog +dynr: + version: 0.1.16-105 + title: Dynamic Models with Regime-Switching + maintainer: Michael D. Hunter + description: |- + Intensive longitudinal data have become increasingly prevalent in + various scientific disciplines. Many such data sets are noisy, multivariate, + and multi-subject in nature. The change functions may also be continuous, + or continuous but interspersed with periods of discontinuities (i.e., + showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an + R package that implements a set of computationally efficient algorithms for + handling a broad class of linear and nonlinear discrete- and continuous-time + models with regime-switching properties under the constraint of linear + Gaussian measurement functions. The discrete-time models can generally + take on the form of a state-space or difference equation model. The + continuous-time models are generally expressed as a set of ordinary or + stochastic differential equations. All estimation and computations are + performed in C, but users are provided with the option to specify the + model of interest via a set of simple and easy-to-learn model specification + functions in R. Model fitting can be performed using single-subject time + series data or multiple-subject longitudinal data. Ou, Hunter, & Chow + (2019) provided a detailed introduction to the + interface and more information on the algorithms. + date_publication: '2023-11-28' + bug_reports: '' + url: https://dynrr.github.io/ + url_cran: https://CRAN.R-project.org/package=dynr + url_git: https://github.com/mhunter1/dynr +dynRB: + version: '0.18' + title: Dynamic Range Boxes + maintainer: Marco Tschimpke + description: Improves the concept of multivariate range boxes, which is highly susceptible + for outliers and does not consider the distribution of the data. The package uses + dynamic range boxes to overcome these problems. + date_publication: '2022-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=dynRB + url_git: '' +dynsim: + version: 1.2.3 + title: Dynamic Simulations of Autoregressive Relationships + maintainer: Christopher Gandrud + description: |- + Dynamic simulations and graphical depictions of autoregressive + relationships. + date_publication: '2021-06-20' + bug_reports: https://github.com/christophergandrud/dynsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynsim + url_git: '' +dynsurv: + version: 0.4-7 + title: Dynamic Models for Survival Data + maintainer: Wenjie Wang + description: |- + Time-varying coefficient models for interval censored and + right censored survival data including + 1) Bayesian Cox model with time-independent, time-varying or + dynamic coefficients for right censored and interval censored data studied by + Sinha et al. (1999) and + Wang et al. (2013) , + 2) Spline based time-varying coefficient Cox model for right censored data + proposed by Perperoglou et al. (2006) , and + 3) Transformation model with time-varying coefficients for right censored data + using estimating equations proposed by + Peng and Huang (2007) . + date_publication: '2024-07-08' + bug_reports: https://github.com/wenjie2wang/dynsurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynsurv + url_git: https://github.com/wenjie2wang/dynsurv +dyntaper: + version: '1.1' + title: Dynamic Stem Profile Models, AKA Tree Taper Equations + maintainer: Oscar Garcia + description: |- + Performs calculations with tree taper (or stem + profile) equations, including model fitting. The package + implements the methods from García, O. (2015) "Dynamic + modelling of tree form" + . + The models are parsimonious, describe well the tree bole shape + over its full length, and are consistent with wood formation + mechanisms through time. + date_publication: '2022-08-14' + bug_reports: https://github.com/ogarciav/dyntaper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dyntaper + url_git: https://github.com/ogarciav/dyntaper +DynTxRegime: + version: '4.15' + title: Methods for Estimating Optimal Dynamic Treatment Regimes + maintainer: Shannon T. Holloway + description: |- + Methods to estimate dynamic treatment regimes using Interactive + Q-Learning, Q-Learning, weighted learning, and value-search methods based on + Augmented Inverse Probability Weighted Estimators and Inverse Probability + Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for + Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., + Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DynTxRegime + url_git: '' +dynutils: + version: 1.0.11 + title: Common Functionality for the 'dynverse' Packages + maintainer: Robrecht Cannoodt + description: |2- + + Provides common functionality for the 'dynverse' packages. + 'dynverse' is created to support the development, execution, and benchmarking of trajectory inference methods. + For more information, check out . + date_publication: '2022-10-11' + bug_reports: https://github.com/dynverse/dynutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynutils + url_git: https://github.com/dynverse/dynutils +dynwrap: + version: 1.2.4 + title: Representing and Inferring Single-Cell Trajectories + maintainer: Robrecht Cannoodt + description: |- + Provides functionality to infer trajectories from single-cell data, + represent them into a common format, and adapt them. Other biological information + can also be added, such as cellular grouping, RNA velocity and annotation. + Saelens et al. (2019) . + date_publication: '2023-07-19' + bug_reports: https://github.com/dynverse/dynwrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=dynwrap + url_git: https://github.com/dynverse/dynwrap +dySEM: + version: 1.1.1 + title: Dyadic Structural Equation Modeling + maintainer: John Sakaluk + description: |- + Scripting of structural equation models via 'lavaan' for + Dyadic Data Analysis, and helper functions for supplemental + calculations, tabling, and model visualization. Current models + supported include Dyadic Confirmatory Factor Analysis, the Actor–Partner + Interdependence Model (observed and latent), the Common Fate Model + (observed and latent), Mutual Influence Model (latent), and the Bifactor + Dyadic Model (latent). + date_publication: '2025-01-07' + bug_reports: https://github.com/jsakaluk/dySEM/issues + url: https://jsakaluk.github.io/dySEM/ + url_cran: https://CRAN.R-project.org/package=dySEM + url_git: https://github.com/jsakaluk/dySEM +DysPIA: + version: '1.3' + title: Dysregulated Pathway Identification Analysis + maintainer: Limei Wang + description: It is used to identify dysregulated pathways based on a pre-ranked + gene pair list. A fast algorithm is used to make the computation really fast. + The data in package 'DysPIAData' is needed. + date_publication: '2020-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DysPIA + url_git: '' +DysPIAData: + version: 0.1.2 + title: Background and Pathway Data Used in 'DysPIA' + maintainer: Limei Wang + description: This dataset includes Background and Pathway data used in package 'DysPIA'. + date_publication: '2021-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DysPIAData + url_git: '' +DySS: + version: '1.0' + title: Dynamic Screening Systems + maintainer: Lu You + description: |- + In practice, we will encounter problems where the longitudinal performance of processes needs to be monitored over time. + Dynamic screening systems (DySS) are methods that aim to identify and give signals to processes with poor performance as early as possible. + This package is designed to implement dynamic screening systems and the related methods. + References: + Qiu, P. and Xiang, D. (2014) ; + Qiu, P. and Xiang, D. (2015) ; + Li, J. and Qiu, P. (2016) ; + Li, J. and Qiu, P. (2017) ; + You, L. and Qiu, P. (2019) ; + Qiu, P., Xia, Z., and You, L. (2020) ; + You, L., Qiu, A., Huang, B., and Qiu, P. (2020) ; + You, L. and Qiu, P. (2021) . + date_publication: '2022-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=DySS + url_git: '' +e1071: + version: 1.7-16 + title: |- + Misc Functions of the Department of Statistics, Probability + Theory Group (Formerly: E1071), TU Wien + maintainer: David Meyer + description: |- + Functions for latent class analysis, short time Fourier + transform, fuzzy clustering, support vector machines, + shortest path computation, bagged clustering, naive Bayes + classifier, generalized k-nearest neighbour ... + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=e1071 + url_git: '' +E4tools: + version: 0.1.1 + title: |- + Management and Processing Tools for Data Produced by the + Empatica E4 + maintainer: Evan Kleiman + description: Process and manage the data from the Empatica E4. All functions operate + on the EDA data stream, but other streams will be added soon. The Empatica E4 + is a wearable physiological monitor made by Empatica (Empatica is not associated + with any of this code). You can find more information about the E4 at Empatica's + website . + date_publication: '2019-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=E4tools + url_git: '' +eadrm: + version: 0.1.4 + title: Fitting Dose-Response Models Using an Evolutionary Algorithm + maintainer: Eric Bair + description: |- + Fits dose-response models using an evolutionary + algorithm to estimate the model parameters. The procedure currently + can fit 3-parameter, 4-parameter, and 5-parameter log-logistic models + as well as exponential models. Functions are also provided to plot, + make predictions, and calculate confidence intervals for the resulting + models. For details see "Nonlinear Dose-response Modeling of + High-Throughput Screening Data Using an Evolutionary Algorithm", + Ma, J., Bair, E., Motsinger-Reif, A.; Dose-Response + 18(2):1559325820926734 (2020) . + date_publication: '2022-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eadrm + url_git: '' +eaf: + version: 2.5.1 + title: Plots of the Empirical Attainment Function + maintainer: Manuel López-Ibáñez + description: Computation and visualization of the empirical attainment function + (EAF) for the analysis of random sets in multi-criterion optimization. M. López-Ibáñez, + L. Paquete, and T. Stützle (2010) . + date_publication: '2024-08-19' + bug_reports: https://github.com/MLopez-Ibanez/eaf/issues + url: https://mlopez-ibanez.github.io/eaf/ + url_cran: https://CRAN.R-project.org/package=eaf + url_git: https://github.com/MLopez-Ibanez/eaf +Eagle: + version: '2.5' + title: Multiple Locus Association Mapping on a Genome-Wide Scale + maintainer: Andrew George + description: An implementation of multiple-locus association mapping on a genome-wide + scale. 'Eagle' can handle inbred and outbred study populations, populations of + arbitrary unknown complexity, and data larger than the memory capacity of the + computer. Since 'Eagle' is based on linear mixed models, it is best suited to + the analysis of data on continuous traits. However, it can tolerate non-normal + data. 'Eagle' reports, as its findings, the best set of snp in strongest association + with a trait. For users unfamiliar with R, to perform an analysis, run 'OpenGUI()'. + This opens a web browser to the menu-driven user interface for the input of data, + and for performing genome-wide analysis. + date_publication: '2021-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Eagle + url_git: http://eagle.r-forge.r-project.org +EAinference: + version: 0.2.3 + title: Estimator Augmentation and Simulation-Based Inference + maintainer: Seunghyun Min + description: |- + Estimator augmentation methods for statistical inference on high-dimensional data, + as described in Zhou, Q. (2014) + and Zhou, Q. and Min, S. (2017) . + It provides several simulation-based inference methods: (a) Gaussian and + wild multiplier bootstrap for lasso, group lasso, scaled lasso, scaled group + lasso and their de-biased estimators, (b) importance sampler for approximating + p-values in these methods, (c) Markov chain Monte Carlo lasso sampler with + applications in post-selection inference. + date_publication: '2017-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EAinference + url_git: '' +eAnalytics: + version: 0.3.1 + title: Dynamic Web-Based Analytics for the Energy Industry + maintainer: Paul Govan + description: |- + A 'Shiny' web application for energy industry analytics. + Take an overview of the industry, measure Key Performance Indicators, + identify changes in the industry over time, and discover new relationships in the data. + date_publication: '2024-09-12' + bug_reports: https://github.com/paulgovan/eAnalytics/issues + url: http://paulgovan.github.io/eAnalytics/ + url_cran: https://CRAN.R-project.org/package=eAnalytics + url_git: https://github.com/paulgovan/eAnalytics +earlygating: + version: '1.1' + title: Properties of Bayesian Early Gating Designs + maintainer: Elias Laurin Meyer + description: |- + Computes the most important properties of four 'Bayesian' early gating + designs (two single arm and two randomized controlled designs), such + as minimum required number of successes in the experimental group to + make a GO decision, operating characteristics and average operating + characteristics with respect to the sample size. + These might aid in deciding what design to use for the early phase trial. + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=earlygating + url_git: '' +earlyR: + version: 0.0.5 + title: |- + Estimation of Transmissibility in the Early Stages of a Disease + Outbreak + maintainer: Thibaut Jombart + description: Implements a simple, likelihood-based estimation of the reproduction + number (R0) using a branching process with a Poisson likelihood. This model requires + knowledge of the serial interval distribution, and dates of symptom onsets. Infectiousness + is determined by weighting R0 by the probability mass function of the serial interval + on the corresponding day. It is a simplified version of the model introduced by + Cori et al. (2013) . + date_publication: '2020-10-27' + bug_reports: https://github.com/reconhub/earlyR/issues + url: https://www.repidemicsconsortium.org/earlyR/ + url_cran: https://CRAN.R-project.org/package=earlyR + url_git: '' +earlywarnings: + version: 1.1.29 + title: Early Warning Signals for Critical Transitions in Time Series + maintainer: Vasilis Dakos + description: |- + The Early-Warning-Signals Toolbox provides methods for estimating + statistical changes in time series that can be used for identifying nearby + critical transitions. + date_publication: '2022-10-10' + bug_reports: '' + url: http://www.early-warning-signals.org + url_cran: https://CRAN.R-project.org/package=earlywarnings + url_git: '' +earth: + version: 5.3.4 + title: Multivariate Adaptive Regression Splines + maintainer: Stephen Milborrow + description: |- + Build regression models using the techniques in Friedman's + papers "Fast MARS" and "Multivariate Adaptive Regression + Splines" . + (The term "MARS" is trademarked and thus not used in + the name of the package.) + date_publication: '2024-10-05' + bug_reports: '' + url: http://www.milbo.users.sonic.net/earth/ + url_cran: https://CRAN.R-project.org/package=earth + url_git: '' +earthdatalogin: + version: 0.0.2 + title: NASA 'EarthData' Login Utilities + maintainer: Carl Boettiger + description: |- + Providing easy, portable access to NASA 'EarthData' products + through the use of bearer tokens. Much of NASA's public data catalogs hosted + and maintained by its 12 Distributed Active Archive Centers ('DAACs') are + now made available on the Amazon Web Services 'S3' storage. However, + accessing this data through the standard 'S3' API is restricted to only to + compute resources running inside 'us-west-2' Data Center in Portland, Oregon, + which allows NASA to avoid being charged data egress rates. This package + provides public access to the data from any networked device by using the + 'EarthData' login application programming interface (API), + , + providing convenient authentication and access to cloud-hosted NASA 'EarthData' + products. This makes access to a wide range of earth observation data from + any location straight forward and compatible with R packages that are + widely used with cloud native earth observation data (such as 'terra', + 'sf', etc.) + date_publication: '2023-12-15' + bug_reports: https://github.com/boettiger-lab/earthdatalogin/issues + url: https://boettiger-lab.github.io/earthdatalogin/ + url_cran: https://CRAN.R-project.org/package=earthdatalogin + url_git: https://github.com/boettiger-lab/earthdatalogin +earthtide: + version: 0.1.7 + title: |- + Parallel Implementation of 'ETERNA 3.40' for Prediction and + Analysis of Earth Tides + maintainer: Jonathan Kennel + description: |- + This is a port of 'Fortran ETERNA 3.4' + by H.G. Wenzel + for calculating synthetic Earth tides using the + Hartmann and Wenzel (1994) or + Kudryavtsev (2004) tidal catalogs. + date_publication: '2025-01-27' + bug_reports: https://github.com/jkennel/earthtide/issues + url: '' + url_cran: https://CRAN.R-project.org/package=earthtide + url_git: https://github.com/jkennel/earthtide +earthtones: + version: 0.1.1 + title: Derive a Color Palette from a Particular Location on Earth + maintainer: Will Cornwell + description: |- + Downloads a satellite image via Google Maps/Earth (these are + originally from a variety of aerial photography sources), + translates the image into a perceptually uniform color space, + runs one of a few different clustering algorithms on the colors in the image + searching for a user-supplied number of colors, + and returns the resulting color palette. + date_publication: '2019-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=earthtones + url_git: '' +Ease: + version: 0.1.2 + title: Simulating Explicit Population Genetics Models + maintainer: Ehouarn Le Faou + description: |- + Implementation in a simple and efficient way of fully customisable population genetics simulations, + considering multiple loci that have epistatic interactions. Specifically suited to the modelling of + multilocus nucleocytoplasmic systems (with both diploid and haploid loci), it is nevertheless possible + to simulate purely diploid (or purely haploid) genetic models. + Examples of models that can be simulated with Ease are numerous, for example models of genetic + incompatibilities as presented by Marie-Orleach et al. (2022) . + Many others are conceivable, although few are actually explored, Ease having been developed + in particular to provide a solution so that these kinds of models can be simulated simply. + date_publication: '2022-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ease + url_git: '' +easy.glmnet: + version: '1.0' + title: Functions to Simplify the Use of 'glmnet' for Machine Learning + maintainer: Joaquim Radua + description: 'Provides several functions to simplify using the ''glmnet'' package: + converting data frames into matrices ready for ''glmnet''; b) imputing missing + variables multiple times; c) fitting and applying prediction models straightforwardly; + d) assigning observations to folds in a balanced way; e) cross-validate the models; + f) selecting the most representative model across imputations and folds; and g) + getting the relevance of the model regressors; as described in several publications: + Solanes et al. (2022) , Palau et al. (2023) , + Sobregrau et al. (2024) .' + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easy.glmnet + url_git: '' +easy.utils: + version: 0.1.0 + title: Frequently Used Functions for Easy R Programming + maintainer: Yuchen Li + description: Some utility functions for validation and data manipulation. These + functions can be helpful to reduce internal codes everywhere in package development. + date_publication: '2025-02-19' + bug_reports: https://github.com/ycli1995/easy.utils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easy.utils + url_git: https://github.com/ycli1995/easy.utils +EasyABC: + version: 1.5.2 + title: Efficient Approximate Bayesian Computation Sampling Schemes + maintainer: Nicolas Dumoulin + description: Enables launching a series of simulations of a computer code from the + R session, and to retrieve the simulation outputs in an appropriate format for + post-processing treatments. Five sequential sampling schemes and three coupled-to-MCMC + schemes are implemented. + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EasyABC + url_git: http://easyabc.r-forge.r-project.org/ +easyAHP: + version: 0.1.1 + title: Analytic Hierarchy Process (AHP) + maintainer: Zhicheng Du + description: Given the scores from decision makers, the analytic hierarchy process + can be conducted easily. + date_publication: '2017-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyAHP + url_git: '' +easyalluvial: + version: 0.3.2 + title: Generate Alluvial Plots with a Single Line of Code + maintainer: Bjoern Koneswarakantha + description: |- + Alluvial plots are similar to sankey diagrams and visualise categorical data + over multiple dimensions as flows. (Rosvall M, Bergstrom CT (2010) Mapping Change in + Large Networks. PLoS ONE 5(1): e8694. + Their graphical grammar however is a bit more complex then that of a regular x/y + plots. The 'ggalluvial' package made a great job of translating that grammar into + 'ggplot2' syntax and gives you many options to tweak the appearance of an alluvial + plot, however there still remains a multi-layered complexity that makes it difficult + to use 'ggalluvial' for explorative data analysis. 'easyalluvial' provides a simple + interface to this package that allows you to produce a decent alluvial plot from any + dataframe in either long or wide format from a single line of code while also handling + continuous data. It is meant to allow a quick visualisation of entire dataframes + with a focus on different colouring options that can make alluvial plots a great + tool for data exploration. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyalluvial + url_git: https://github.com/erblast/easyalluvial/ +easyanova: + version: '11.0' + title: Analysis of Variance and Other Important Complementary Analyses + maintainer: Emmanuel Arnhold + description: |- + Perform analysis of variance and other important complementary + analyses. The functions are easy to use. Performs analysis in various + designs, with balanced and unbalanced data. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyanova + url_git: '' +easybgm: + version: 0.2.1 + title: Extracting and Visualizing Bayesian Graphical Models + maintainer: Karoline Huth + description: |- + Fit and visualize the results of a Bayesian analysis of networks commonly found in psychology. + The package supports fitting cross-sectional network models fitted using the packages 'BDgraph', 'bgms' and 'BGGM'. + The package provides the parameter estimates, posterior inclusion probabilities, inclusion Bayes factor, and the + posterior density of the parameters. In addition, for 'BDgraph' and 'bgms' it allows to assess the posterior + structure space. Furthermore, the package comes with an extensive suite for visualizing results. + date_publication: '2024-10-17' + bug_reports: https://github.com/KarolineHuth/easybgm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easybgm + url_git: https://github.com/KarolineHuth/easybgm +easybio: + version: 1.1.1 + title: |- + Comprehensive Single-Cell Annotation and Transcriptomic Analysis + Toolkit + maintainer: Wei Cui + description: 'Provides a comprehensive toolkit for single-cell annotation with the + ''CellMarker2.0'' database (see Xia Li, Peng Wang, Yunpeng Zhang (2023) ). Streamlines biological label assignment in single-cell + RNA-seq data and facilitates transcriptomic analysis, including preparation of + TCGA and GEO + datasets, differential expression analysis and visualization of enrichment analysis + results. Additional utility functions support various bioinformatics workflows. + See Wei Cui (2024) for more details.' + date_publication: '2025-02-12' + bug_reports: https://github.com/person-c/easybio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easybio + url_git: https://github.com/person-c/easybio +easycensus: + version: 1.1.3 + title: Quickly Find, Extract, and Marginalize U.S. Census Tables + maintainer: Cory McCartan + description: |- + Extracting desired data using the proper Census variable names can + be time-consuming. This package takes the pain out of that process by + providing functions to quickly locate variables and download labeled tables + from the Census APIs (). + date_publication: '2025-02-20' + bug_reports: https://github.com/CoryMcCartan/easycensus/issues + url: https://corymccartan.com/easycensus/ + url_cran: https://CRAN.R-project.org/package=easycensus + url_git: https://github.com/CoryMcCartan/easycensus/ +easyclimate: + version: 0.2.2 + title: Easy Access to High-Resolution Daily Climate Data for Europe + maintainer: Verónica Cruz-Alonso + description: |- + Get high-resolution (1 km) daily climate data (precipitation, + minimum and maximum temperatures) for points and polygons within + Europe. + date_publication: '2024-11-22' + bug_reports: https://github.com/VeruGHub/easyclimate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easyclimate + url_git: https://github.com/VeruGHub/easyclimate +easyCODA: + version: 0.40.2 + title: Compositional Data Analysis in Practice + maintainer: Michael Greenacre + description: |- + Univariate and multivariate methods for compositional data + analysis, based on logratios. The package implements the approach in the + book Compositional Data Analysis in Practice by Michael Greenacre (2018), + where accent is given to simple pairwise logratios. Selection can be made + of logratios that account for a maximum percentage of logratio variance. + Various multivariate analyses of logratios are included in the package. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyCODA + url_git: https://github.com/michaelgreenacre/CODAinPractice/ +easycsv: + version: 1.0.8 + title: Load Multiple 'csv' and 'txt' Tables + maintainer: Dror Bogin + description: |- + Allows users to easily read multiple comma separated tables and create a data frame under the same name. + Is able to read multiple comma separated tables from a local directory, a zip file or a zip file on a remote directory. + date_publication: '2018-05-21' + bug_reports: https://github.com/bogind/easycsv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easycsv + url_git: https://github.com/bogind/easycsv +easydb: + version: 1.1.0 + title: Easily Connect to Common Types of Databases + maintainer: Sam El-Kamand + description: |- + A unified interface for connecting to databases ('SQLite', 'MySQL', 'PostgreSQL'). + Just provide the database name and the package will ask you questions + to help you configure the connection and setup your credentials. Once + database configuration and connection has been set up once, you won't + have to do it ever again. + date_publication: '2023-03-06' + bug_reports: https://github.com/selkamand/easydb/issues + url: https://selkamand.github.io/easydb/ + url_cran: https://CRAN.R-project.org/package=easydb + url_git: https://github.com/selkamand/easydb +easyDes: + version: '6.0' + title: An Easy Way to Descriptive Analysis + maintainer: Zhicheng Du + description: |2- + + Descriptive analysis is essential for publishing medical articles. + This package provides an easy way to conduct the descriptive analysis. + 1. Both numeric and factor variables can be handled. For numeric variables, normality test will be applied to choose the parametric and nonparametric test. + 2. Both two or more groups can be handled. For groups more than two, the post hoc test will be applied, 'Tukey' for the numeric variables and 'FDR' for the factor variables. + 3. T test, ANOVA or Fisher test can be forced to apply. + 4. Mean and standard deviation can be forced to display. + date_publication: '2021-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyDes + url_git: '' +EasyDescribe: + version: 0.1.2 + title: A Convenient Way of Descriptive Statistics + maintainer: Xiuquan Nie + description: |- + Descriptive Statistics is essential for publishing articles. This package can perform + descriptive statistics according to different data types. If the data is a continuous variable, + the mean and standard deviation or median and quartiles are automatically output; if the data + is a categorical variable, the number and percentage are automatically output. In addition, + if you enter two variables in this package, the two variables will be described and their + relationships will be tested automatically according to their data types. For example, + if one of the two input variables is a categorical variable, another variable will be described + hierarchically based on the categorical variable and the statistical differences between + different groups will be compared using appropriate statistical methods. And for groups of + more than two, the post hoc test will be applied. For more information on the methods we used, + please see the following references: + Libiseller, C. and Grimvall, A. (2002) , + Patefield, W. M. (1981) , + Hope, A. C. A. (1968) , + Mehta, C. R. and Patel, N. R. (1983) , + Mehta, C. R. and Patel, N. R. (1986) , + Clarkson, D. B., Fan, Y. and Joe, H. (1993) , + Cochran, W. G. (1954) , + Armitage, P. (1955) , + Szabo, A. (2016) , + David, F. B. (1972) , + Joanes, D. N. and Gill, C. A. (1998) , + Dunn, O. J. (1964) , + Copenhaver, M. D. and Holland, B. S. (1988) , + Chambers, J. M., Freeny, A. and Heiberger, R. M. (1992) , + Shaffer, J. P. (1995) , + Myles, H. and Douglas, A. W. (1973) , + Rahman, M. and Tiwari, R. (2012) , + Thode, H. J. (2002) , + Jonckheere, A. R. (1954) , + Terpstra, T. J. (1952) . + date_publication: '2023-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EasyDescribe + url_git: '' +easylabel: + version: 0.3.3 + title: Interactive Scatter Plot and Volcano Plot Labels + maintainer: Myles Lewis + description: |- + Interactive labelling of scatter plots, volcano plots and + Manhattan plots using a 'shiny' and 'plotly' interface. Users can hover + over points to see where specific points are located and click points + on/off to easily label them. Labels can be dragged around the plot to place + them optimally. Plots can be exported directly to PDF for publication. For + plots with large numbers of points, points can optionally be rasterized as a + bitmap, while all other elements (axes, text, labels & lines) are preserved + as vector objects. This can dramatically reduce file size for plots with + millions of points such as Manhattan plots, and is ideal for publication. + date_publication: '2025-02-06' + bug_reports: https://github.com/myles-lewis/easylabel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easylabel + url_git: https://github.com/myles-lewis/easylabel +EasyMx: + version: 0.3-2 + title: Easy Model-Builder Functions for 'OpenMx' + maintainer: Michael D. Hunter + description: |- + Utilities for building certain kinds of common matrices and models in + the extended structural equation modeling package, 'OpenMx'. + date_publication: '2023-01-30' + bug_reports: https://bitbucket.org/mhunter/easymx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EasyMx + url_git: https://bitbucket.org/mhunter/easymx +easyNCDF: + version: 0.1.2 + title: |- + Tools to Easily Read/Write NetCDF Files into/from + Multidimensional R Arrays + maintainer: An-Chi Ho + description: |- + Set of wrappers for the 'ncdf4' package to simplify and extend its + reading/writing capabilities into/from multidimensional R arrays. + date_publication: '2023-06-02' + bug_reports: https://earth.bsc.es/gitlab/es/easyNCDF/-/issues + url: https://earth.bsc.es/gitlab/es/easyNCDF + url_cran: https://CRAN.R-project.org/package=easyNCDF + url_git: '' +easynls: + version: '5.0' + title: Easy Nonlinear Model + maintainer: Emmanuel Arnhold + description: Fit and plot some nonlinear models. + date_publication: '2017-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easynls + url_git: '' +easyORtables: + version: 0.0.1 + title: Easy Odds Ratio Tables + maintainer: Neil Mehta + description: Creates text, 'LaTeX', Markdown, or Bootstrap-styled HTML-formatted + odds ratio tables with confidence intervals for multiple logistic regression models. + date_publication: '2024-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyORtables + url_git: '' +easypackages: + version: 0.1.0 + title: Easy Loading and Installing of Packages + maintainer: Jake Sherman + description: |- + Easily load and install multiple packages from different sources, + including CRAN and GitHub. The libraries function allows you to load or attach + multiple packages in the same function call. The packages function will load one + or more packages, and install any packages that are not installed on your system + (after prompting you). Also included is a from_import function that allows you + to import specific functions from a package into the global environment. + date_publication: '2016-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easypackages + url_git: '' +easypower: + version: 1.0.2 + title: Sample Size Estimation for Experimental Designs + maintainer: Aaron McGarvey + description: |- + Power analysis is used in the estimation of sample sizes for + experimental designs. Most programs and R packages will only output the highest + recommended sample size to the user. Often the user input can be complicated + and computing multiple power analyses for different treatment comparisons can + be time consuming. This package simplifies the user input and allows the user + to view all of the sample size recommendations or just the ones they want to see. + The calculations used to calculate the recommended sample sizes are from the + 'pwr' package. + date_publication: '2024-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easypower + url_git: '' +easyPSID: + version: 0.1.2 + title: |- + Reading, Formatting, and Organizing the Panel Study of Income + Dynamics (PSID) + maintainer: Brian Aronson + description: Provides various functions for reading and preparing the Panel Study + of Income Dynamics (PSID) for longitudinal analysis, including functions that + read the PSID's fixed width format files directly into R, rename all of the PSID's + longitudinal variables so that recurring variables have consistent names across + years, simplify assembling longitudinal datasets from cross sections of the PSID + Family Files, and export the resulting PSID files into file formats common among + other statistical programming languages ('SAS', 'STATA', and 'SPSS'). + date_publication: '2021-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyPSID + url_git: '' +easyPubMed: + version: '2.13' + title: Search and Retrieve Scientific Publication Records from PubMed + maintainer: Damiano Fantini + description: Query NCBI Entrez and retrieve PubMed records in XML or text format. + Process PubMed records by extracting and aggregating data from selected fields. + A large number of records can be easily downloaded via this simple-to-use interface + to the NCBI PubMed API. + date_publication: '2019-03-29' + bug_reports: '' + url: https://www.data-pulse.com/dev_site/easypubmed/ + url_cran: https://CRAN.R-project.org/package=easyPubMed + url_git: '' +easyr: + version: 0.5-11 + title: Helpful Functions from Oliver Wyman Actuarial Consulting + maintainer: Bryce Chamberlain + description: |- + Makes difficult operations easy. Includes these types of functions: + shorthand, type conversion, data wrangling, and work flow. + Also includes some helpful data objects: NA strings, U.S. state list, color blind charting colors. + Built and shared by Oliver Wyman Actuarial Consulting. Accepting proposed contributions through GitHub. + date_publication: '2023-03-09' + bug_reports: https://github.com/oliver-wyman-actuarial/easyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easyr + url_git: https://github.com/oliver-wyman-actuarial/easyr +easyreg: + version: '4.0' + title: Easy Regression + maintainer: Emmanuel Arnhold + description: |- + Performs analysis of regression in simple designs with quantitative treatments, + including mixed models and non linear models. + date_publication: '2019-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easyreg + url_git: '' +easySdcTable: + version: 1.0.7 + title: |- + Easy Interface to the Statistical Disclosure Control Package + 'sdcTable' Extended with Own Implementation of + 'GaussSuppression' + maintainer: Øyvind Langsrud + description: |- + The main function, ProtectTable(), performs table suppression according to a + frequency rule with a data set as the only required input. Within this function, + protectTable(), protect_linked_tables() or runArgusBatchFile() in package 'sdcTable' is called. + Lists of level-hierarchy (parameter 'dimList') and other required input to these functions + are created automatically. + The suppression method Gauss (default) is implemented independently of 'sdcTable'. + The function, PTgui(), starts a graphical user interface based on the 'shiny' package. + date_publication: '2022-12-22' + bug_reports: https://github.com/statisticsnorway/easySdcTable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easySdcTable + url_git: https://github.com/statisticsnorway/easySdcTable +easySimData: + version: 0.1.0 + title: A Wrapper of 'simdata' Package + maintainer: Han Zhang + description: |- + Simulating data according to marginal distributions and + pairwise correlation. This is a wrapper for the 'simdata' package to make it + easier to use. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=easySimData + url_git: '' +easystats: + version: 0.7.4 + title: |- + Framework for Easy Statistical Modeling, Visualization, and + Reporting + maintainer: Daniel Lüdecke + description: |- + A meta-package that installs and loads a set of packages from + 'easystats' ecosystem in a single step. This collection of packages provide + a unifying and consistent framework for statistical modeling, visualization, + and reporting. Additionally, it provides articles targeted at instructors for + teaching 'easystats', and a dashboard targeted at new R users for easily + conducting statistical analysis by accessing summary results, model fit indices, + and visualizations with minimal programming. + date_publication: '2025-02-06' + bug_reports: https://github.com/easystats/easystats/issues + url: https://easystats.github.io/easystats/ + url_cran: https://CRAN.R-project.org/package=easystats + url_git: '' +easysurv: + version: 2.0.1 + title: Simplify Survival Data Analysis and Model Fitting + maintainer: Niall Davison + description: |- + Inspect survival data, plot Kaplan-Meier curves, assess the + proportional hazards assumption, fit parametric survival models, + predict and plot survival and hazards, and export the outputs to + Excel. A simple interface for fitting survival models using + 'flexsurv::flexsurvreg()', 'flexsurv::flexsurvspline()', + 'flexsurvcure::flexsurvcure()', and 'survival::survreg()'. + date_publication: '2024-06-21' + bug_reports: https://github.com/Maple-Health-Group/easysurv/issues + url: https://maple-health-group.github.io/easysurv/ + url_cran: https://CRAN.R-project.org/package=easysurv + url_git: https://github.com/Maple-Health-Group/easysurv +easySVG: + version: 0.1.0 + title: An Easy SVG Basic Elements Generator + maintainer: Yuting Dai + description: |- + This SVG elements generator can easily generate + SVG elements such as rect, line, circle, ellipse, polygon, + polyline, text and group. Also, it can combine and + output SVG elements into a SVG file. + date_publication: '2018-01-09' + bug_reports: https://github.com/ytdai/easySVG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=easySVG + url_git: https://github.com/ytdai/easySVG +easyVerification: + version: 0.4.5 + title: Ensemble Forecast Verification for Large Data Sets + maintainer: Jonas Bhend + description: |- + Set of tools to simplify application of atomic forecast + verification metrics for (comparative) verification of ensemble forecasts + to large data sets. The forecast metrics are imported from the + 'SpecsVerification' package, and additional forecast metrics are provided + with this package. Alternatively, new user-defined forecast scores can be + implemented using the example scores provided and applied using the + functionality of this package. + date_publication: '2023-08-15' + bug_reports: https://github.com/jonasbhend/easyVerification/issues + url: https://www.meteoswiss.admin.ch + url_cran: https://CRAN.R-project.org/package=easyVerification + url_git: https://github.com/jonasbhend/easyVerification +eat: + version: 0.1.4 + title: Efficiency Analysis Trees + maintainer: Miriam Esteve + description: |- + Functions are provided to determine production frontiers and technical + efficiency measures through non-parametric techniques based upon regression trees. + The package includes code for estimating radial input, output, directional and + additive measures, plotting graphical representations of the scores and the production + frontiers by means of trees, and determining rankings of importance of input variables + in the analysis. Additionally, an adaptation of Random Forest by a set of individual + Efficiency Analysis Trees for estimating technical efficiency is also included. More + details in: . + date_publication: '2023-01-10' + bug_reports: https://github.com/MiriamEsteve/EAT/issues + url: https://efficiencytools.wordpress.com/ + url_cran: https://CRAN.R-project.org/package=eat + url_git: '' +eatATA: + version: 1.1.2 + title: Create Constraints for Small Test Assembly Problems + maintainer: Benjamin Becker + description: |- + Provides simple functions to create constraints for small test assembly problems + (e.g. van der Linden (2005, ISBN: 978-0-387-29054-6)) using sparse matrices. Currently, + 'GLPK', 'lpSolve', 'Symphony', and 'Gurobi' are supported as solvers. The 'gurobi' package is not available from + any mainstream repository; see . + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eatATA + url_git: https://github.com/beckerbenj/eatATA +eatDB: + version: 0.5.0 + title: Spreadsheet Interface for Relational Databases + maintainer: Benjamin Becker + description: Use 'SQLite3' as a database system via a complete SQL free R interface, + treating the data as if it was a single spreadsheet. + date_publication: '2021-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eatDB + url_git: '' +eatGADS: + version: 1.1.1 + title: Data Management of Large Hierarchical Data + maintainer: Benjamin Becker + description: Import 'SPSS' data, handle and change 'SPSS' meta data, store and access + large hierarchical data in 'SQLite' data bases. + date_publication: '2024-10-09' + bug_reports: '' + url: https://beckerbenj.github.io/eatGADS/ + url_cran: https://CRAN.R-project.org/package=eatGADS + url_git: https://github.com/beckerbenj/eatGADS +EATME: + version: 0.1.0 + title: |- + Exponentially Weighted Moving Average with Adjustments to + Measurement Error + maintainer: Cheng-Kuan Lin Developer + description: 'The univariate statistical quality control tool aims to address measurement + error effects when constructing exponentially weighted moving average p control + charts. The method primarily focuses on binary random variables, but it can be + applied to any continuous random variables by using sign statistic to transform + them to discrete ones. With the correction of measurement error effects, we can + obtain the corrected control limits of exponentially weighted moving average p + control chart and reasonably adjusted exponentially weighted moving average p + control charts. The methods in this package can be found in some relevant references, + such as Chen and Yang (2022) ; Yang et al. (2011) ; + Yang and Arnold (2014) ; Yang (2016) + and Yang and Arnold (2016) .' + date_publication: '2022-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EATME + url_git: '' +eatRep: + version: 0.15.1 + title: Educational Assessment Tools for Replication Methods + maintainer: Sebastian Weirich + description: |- + Replication methods to compute some basic statistic operations (means, standard deviations, + frequency tables, percentiles, mean comparisons using weighted effect coding, generalized linear models, + and linear multilevel models) in complex survey designs comprising multiple imputed or nested imputed + variables and/or a clustered sampling structure which both deserve special procedures at least in + estimating standard errors. See the package documentation for a more detailed description along with references. + date_publication: '2025-02-10' + bug_reports: '' + url: https://weirichs.github.io/eatRep/ + url_cran: https://CRAN.R-project.org/package=eatRep + url_git: https://github.com/weirichs/eatRep +eatTools: + version: 0.7.8 + title: |- + Miscellaneous Functions for the Analysis of Educational + Assessments + maintainer: Sebastian Weirich + description: |- + Miscellaneous functions for data cleaning and data analysis of educational assessments. Includes functions for descriptive + analyses, character vector manipulations and weighted statistics. Mainly a lightweight dependency for the packages 'eatRep', + 'eatGADS', 'eatPrep' and 'eatModel' (which will be subsequently submitted to 'CRAN'). + The function for defining (weighted) contrasts in weighted effect coding refers to + te Grotenhuis et al. (2017) . + Functions for weighted statistics refer to + Wolter (2007) . + date_publication: '2024-12-18' + bug_reports: '' + url: https://weirichs.github.io/eatTools/ + url_cran: https://CRAN.R-project.org/package=eatTools + url_git: https://github.com/weirichs/eatTools +eba: + version: 1.10-0 + title: Elimination-by-Aspects Models + maintainer: Florian Wickelmaier + description: |- + Fitting and testing multi-attribute probabilistic choice + models, especially the Bradley-Terry-Luce (BTL) model (Bradley & + Terry, 1952 ; Luce, 1959), + elimination-by-aspects (EBA) models (Tversky, 1972 ), + and preference tree (Pretree) models (Tversky & Sattath, 1979 + ). + date_publication: '2020-11-20' + bug_reports: '' + url: http://www.mathpsy.uni-tuebingen.de/wickelmaier + url_cran: https://CRAN.R-project.org/package=eba + url_git: '' +ebal: + version: 0.1-8 + title: Entropy Reweighting to Create Balanced Samples + maintainer: Jens Hainmueller + description: Package implements entropy balancing, a data preprocessing procedure + described in Hainmueller (2008, ) that allows users to + reweight a dataset such that the covariate distributions in the reweighted data + satisfy a set of user specified moment conditions. This can be useful to create + balanced samples in observational studies with a binary treatment where the control + group data can be reweighted to match the covariate moments in the treatment group. + Entropy balancing can also be used to reweight a survey sample to known characteristics + from a target population. + date_publication: '2022-06-09' + bug_reports: '' + url: https://web.stanford.edu/~jhain/ + url_cran: https://CRAN.R-project.org/package=ebal + url_git: '' +EBASE: + version: 1.1.0 + title: |- + Estuarine Bayesian Single-Station Estimation Method for + Ecosystem Metabolism + maintainer: Marcus Beck + description: |- + Estimate ecosystem metabolism in a Bayesian framework for + individual water quality monitoring stations with continuous dissolved + oxygen time series. A mass balance equation is used that provides + estimates of parameters for gross primary production, respiration, + and gas exchange. Methods adapted from Grace et al. (2015) + and Wanninkhof (2014) . + Details in Beck et al. (2024) . + date_publication: '2024-09-25' + bug_reports: https://github.com/fawda123/EBASE/issues + url: https://fawda123.github.io/EBASE/ + url_cran: https://CRAN.R-project.org/package=EBASE + url_git: https://github.com/fawda123/EBASE/ +EbayesThresh: + version: 1.4-12 + title: Empirical Bayes Thresholding and Related Methods + maintainer: Peter Carbonetto + description: |- + Empirical Bayes thresholding using the methods developed + by I. M. Johnstone and B. W. Silverman. The basic problem is to + estimate a mean vector given a vector of observations of the mean + vector plus white noise, taking advantage of possible sparsity in + the mean vector. Within a Bayesian formulation, the elements of + the mean vector are modelled as having, independently, a + distribution that is a mixture of an atom of probability at zero + and a suitable heavy-tailed distribution. The mixing parameter can + be estimated by a marginal maximum likelihood approach. This leads + to an adaptive thresholding approach on the original data. + Extensions of the basic method, in particular to wavelet + thresholding, are also implemented within the package. + date_publication: '2017-08-08' + bug_reports: https://github.com/stephenslab/EbayesThresh/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EbayesThresh + url_git: https://github.com/stephenslab/EbayesThresh +EBCHS: + version: 0.1.0 + title: An Empirical Bayes Method for Chi-Squared Data + maintainer: Lilun Du + description: We provide the main R functions to compute the posterior interval for + the noncentrality parameter of the chi-squared distribution. The skewness estimate + of the posterior distribution is also available to improve the coverage rate of + posterior intervals. Details can be found in Du and Hu (2020) . + date_publication: '2021-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EBCHS + url_git: https://github.com/dulilun/EBCHS +ebci: + version: 1.0.0 + title: Robust Empirical Bayes Confidence Intervals + maintainer: Michal Kolesár + description: |- + Computes empirical Bayes confidence estimators and confidence + intervals in a normal means model. The intervals are robust in the sense + that they achieve correct coverage regardless of the distribution of the + means. If the means are treated as fixed, the intervals have an average + coverage guarantee. The implementation is based on Armstrong, Kolesár and + Plagborg-Møller (2020) . + date_publication: '2021-09-06' + bug_reports: https://github.com/kolesarm/ebci/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ebci + url_git: https://github.com/kolesarm/ebci +EBcoBART: + version: 1.1.1 + title: Co-Data Learning for Bayesian Additive Regression Trees + maintainer: Jeroen M. Goedhart + description: |- + Estimate prior variable weights for Bayesian Additive Regression + Trees (BART). These weights correspond to the probabilities of the variables + being selected in the splitting rules of the sum-of-trees. + Weights are estimated using empirical Bayes and external information on + the explanatory variables (co-data). + BART models are fitted using the 'dbarts' 'R' package. + See Goedhart and others (2023) for details. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EBcoBART + url_git: https://github.com/JeroenGoedhart/EBcoBART +ebdbNet: + version: 1.2.8 + title: Empirical Bayes Estimation of Dynamic Bayesian Networks + maintainer: Andrea Rau + description: |- + Infer the adjacency matrix of a + network from time course data using an empirical Bayes + estimation procedure based on Dynamic Bayesian Networks. + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ebdbNet + url_git: https://github.com/andreamrau/ebdbNet +EBEN: + version: '5.2' + title: Empirical Bayesian Elastic Net + maintainer: Anhui Huang + description: |- + Provides the Empirical Bayesian Elastic Net for handling multicollinearity in generalized linear regression models. As a special case of the 'EBglmnet' + package (also available on CRAN), this package encourages a grouping effects to select relevant variables and estimate the corresponding non-zero effects. + date_publication: '2024-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EBEN + url_git: '' +ebGenotyping: + version: 2.0.1 + title: |- + Genotyping and SNP Detection using Next Generation Sequencing + Data + maintainer: Gongyi Huang<53hgy@163.com> + description: Genotyping the population using next generation sequencing data is + essentially important for the rare variant detection. In order to distinguish + the genomic structural variation from sequencing error, we propose a statistical + model which involves the genotype effect through a latent variable to depict the + distribution of non-reference allele frequency data among different samples and + different genome loci, while decomposing the sequencing error into sample effect + and positional effect. An ECM algorithm is implemented to estimate the model parameters, + and then the genotypes and SNPs are inferred based on the empirical Bayes method. + date_publication: '2016-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ebGenotyping + url_git: '' +ebirdst: + version: 3.2022.3 + title: Access and Analyze eBird Status and Trends Data Products + maintainer: Matthew Strimas-Mackey + description: |- + Tools for accessing and analyzing eBird Status and + Trends Data Products + (). eBird + () is a global database of bird observations + collected by member of the public. eBird Status and Trends uses these + data to model global bird distributions, abundances, and population trends + at a high spatial and temporal resolution. + date_publication: '2024-03-05' + bug_reports: https://github.com/ebird/ebirdst/issues + url: https://ebird.github.io/ebirdst/ + url_cran: https://CRAN.R-project.org/package=ebirdst + url_git: https://github.com/ebird/ebirdst +EBMAforecast: + version: 1.0.32 + title: |- + Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs + Sampling or EM-Algorithms + maintainer: Florian M. Hollenbach + description: Create forecasts from multiple predictions using ensemble Bayesian + model averaging (EBMA). EBMA models can be estimated using an expectation maximization + (EM) algorithm or as fully Bayesian models via Gibbs sampling. The methods in + this package are Montgomery, Hollenbach, and Ward (2015) + and Montgomery, Hollenbach, and Ward (2012) . + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EBMAforecast + url_git: https://github.com/fhollenbach/EBMA/ +ebmc: + version: 1.0.1 + title: Ensemble-Based Methods for Class Imbalance Problem + maintainer: '"Hsiang Hao, Chen"' + description: 'Four ensemble-based methods (SMOTEBoost, RUSBoost, UnderBagging, and + SMOTEBagging) for class imbalance problem are implemented for binary classification. + Such methods adopt ensemble methods and data re-sampling techniques to improve + model performance in presence of class imbalance problem. One special feature + offers the possibility to choose multiple supervised learning algorithms to build + weak learners within ensemble models. References: Nitesh V. Chawla, Aleksandar + Lazarevic, Lawrence O. Hall, and Kevin W. Bowyer (2003) , + Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, and Amri Napolitano (2010) + , R. Barandela, J. S. Sanchez, R. M. Valdovinos + (2003) , Shuo Wang and Xin Yao (2009) , + Yoav Freund and Robert E. Schapire (1997) .' + date_publication: '2022-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ebmc + url_git: '' +ebmstate: + version: 0.1.5 + title: Empirical Bayes Multi-State Cox Model + maintainer: Rui Costa + description: Implements an empirical Bayes, multi-state Cox model for survival analysis. + Run "?'ebmstate-package'" for details. See also Schall (1991) . + date_publication: '2024-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ebmstate + url_git: '' +ebnm: + version: 1.1-2 + title: Solve the Empirical Bayes Normal Means Problem + maintainer: Peter Carbonetto + description: |- + Provides simple, fast, and stable functions to fit the normal + means model using empirical Bayes. For available models and details, see + function ebnm(). A detailed introduction to the package is provided + by Willwerscheid and Stephens (2021) . + date_publication: '2023-10-12' + bug_reports: https://github.com/stephenslab/ebnm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ebnm + url_git: https://github.com/stephenslab/ebnm +EBPRS: + version: 2.1.0 + title: Derive Polygenic Risk Score Based on Emprical Bayes Theory + maintainer: Shuang Song + description: EB-PRS is a novel method that leverages information for effect sizes + across all the markers to improve the prediction accuracy. No parameter tuning + is needed in the method, and no external information is needed. This R-package + provides the calculation of polygenic risk scores from the given training summary + statistics and testing data. We can use EB-PRS to extract main information, estimate + Empirical Bayes parameters, derive polygenic risk scores for each individual + in testing data, and evaluate the PRS according to AUC and predictive r2. See + Song et al. (2020) for a detailed presentation + of the method. + date_publication: '2020-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EBPRS + url_git: '' +EBrank: + version: 1.0.0 + title: Empirical Bayes Ranking + maintainer: John Ferguson + description: Empirical Bayes ranking applicable to parallel-estimation settings + where the estimated parameters are asymptotically unbiased and normal, with known + standard errors. A mixture normal prior for each parameter is estimated using + Empirical Bayes methods, subsequentially ranks for each parameter are simulated + from the resulting joint posterior over all parameters (The marginal posterior + densities for each parameter are assumed independent). Finally, experiments are + ordered by expected posterior rank, although computations minimizing other plausible + rank-loss functions are also given. + date_publication: '2017-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EBrank + url_git: '' +ebreg: + version: 0.1.3 + title: Implementation of the Empirical Bayes Method + maintainer: Yiqi Tang + description: Implements a Bayesian-like approach to the high-dimensional sparse + linear regression problem based on an empirical or data-dependent prior distribution, + which can be used for estimation/inference on the model parameters, variable selection, + and prediction of a future response. The method was first presented in Martin, + Ryan and Mess, Raymond and Walker, Stephen G (2017) . More + details focused on the prediction problem are given in Martin, Ryan and Tang, + Yiqi (2019) . + date_publication: '2021-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ebreg + url_git: '' +eBsc: + version: '4.17' + title: '"Empirical Bayes Smoothing Splines with Correlated Errors"' + maintainer: Francisco Rosales + description: Presents a statistical method that uses a recursive algorithm for signal + extraction. The method handles a non-parametric estimation for the correlation + of the errors. See "Krivobokova", "Serra", "Rosales" and "Klockmann" (2021) + for details. + date_publication: '2023-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eBsc + url_git: '' +ebTobit: + version: 1.0.2 + title: Empirical Bayesian Tobit Matrix Estimation + maintainer: Alton Barbehenn + description: |- + Estimation tools for multidimensional Gaussian means using + empirical Bayesian g-modeling. Methods are able to handle fully observed data as + well as left-, right-, and interval-censored observations (Tobit + likelihood); descriptions of these methods can be found in Barbehenn and + Zhao (2023) . Additional, lower-level functionality based + on Kiefer and Wolfowitz (1956) and Jiang and + Zhang (2009) is provided that can be used to + accelerate many empirical Bayes and nonparametric maximum likelihood + problems. + date_publication: '2024-05-03' + bug_reports: https://github.com/barbehenna/ebTobit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ebTobit + url_git: https://github.com/barbehenna/ebTobit +ebvcube: + version: 0.3.3 + title: Working with netCDF for Essential Biodiversity Variables + maintainer: Luise Quoss + description: |- + The concept of Essential Biodiversity Variables (EBV, ) + comes with a data structure based on the Network Common Data Form (netCDF). + The 'ebvcube' 'R' package provides functionality to easily create, access and + visualise this data. The EBV netCDFs can be downloaded from the EBV Data + Portal: Christian Langer/ iDiv (2020) . + date_publication: '2024-12-17' + bug_reports: https://github.com/EBVcube/ebvcube/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ebvcube + url_git: https://github.com/EBVCube/ebvcube +ec50estimator: + version: 0.1.0 + title: An Automated Way to Estimate EC50 for Stratified Datasets + maintainer: Kaique dos S. Alves + description: |- + An implementation for estimating Effective control to 50% of growth + inhibition (EC50) for multi isolates and stratified datasets. It implements + functions from the drc package in a way that is displayed a tidy data.frame + as output. Info about the drc package is available in Ritz C, Baty F, Streibig JC, + Gerhard D (2015) . + date_publication: '2020-09-15' + bug_reports: https://github.com/AlvesKS/ec50estimator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ec50estimator + url_git: https://github.com/AlvesKS/ec50estimator +ecan: + version: 0.2.1 + title: Ecological Analysis and Visualization + maintainer: Toshikazu Matsumura + description: |- + Support ecological analyses such as ordination and clustering. + Contains consistent and easy wrapper functions of 'stat', 'vegan', and + 'labdsv' packages, and visualisation functions of ordination and clustering. + date_publication: '2023-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecan + url_git: https://github.com/matutosi/ecanhttps://github.com/matutosi/ecan/tree/develop(devel) +eCAR: + version: 0.1.2 + title: Eigenvalue CAR Models + maintainer: Garritt L. Page + description: |- + Fits Leroux model in spectral domain to estimate causal spatial effect as detailed in + Guan, Y; Page, G.L.; Reich, B.J.; Ventrucci, M.; Yang, S; (2020) . + Both the parametric and semi-parametric models are available. The semi-parametric model + relies on 'INLA'. The 'INLA' package can be obtained from . + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eCAR + url_git: https://github.com/gpage2990/eCAR +ecb: + version: 0.4.2 + title: |- + Programmatic Access to the European Central Bank's Statistical + Data Warehouse + maintainer: Eric Persson + description: |- + Provides an interface to the 'European Central Bank's Statistical + Data Warehouse' API , allowing for programmatic + retrieval of a vast quantity of statistical data. + date_publication: '2023-04-20' + bug_reports: '' + url: https://sdw.ecb.europa.eu/ + url_cran: https://CRAN.R-project.org/package=ecb + url_git: '' +ecce: + version: 3.0.2 + title: |- + Translate English Sentence into Chinese, or Translate Chinese + Sentence into English + maintainer: Xinyuan Chu + description: |- + If translate English or Chinese sentence, there is a faster + way for R user. You can pass in an English or Chinese sentence, ecce + package support both English and Chinese translation. It also support + browse translation results in website. In addition, also support obtain + the pinyin of the Chinese character, you can more easily understand + the pronunciation of the Chinese character. + date_publication: '2024-06-27' + bug_reports: https://gitlab.com/chuxinyuan/ecce/-/issues + url: https://cxy.cc/rproj/ecce/ + url_cran: https://CRAN.R-project.org/package=ecce + url_git: https://gitlab.com/chuxinyuan/ecce +Ecdat: + version: 0.4-2 + title: Data Sets for Econometrics + maintainer: Spencer Graves + description: Data sets for econometrics, including political science. + date_publication: '2022-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ecdat + url_git: '' +ecdfHT: + version: 0.1.1 + title: Empirical CDF for Heavy Tailed Data + maintainer: John P Nolan + description: |- + Computes and plots a transformed empirical CDF (ecdf) as a + diagnostic for heavy tailed data, specifically data with power law decay on the + tails. Routines for annotating the plot, comparing data to a model, fitting a + nonparametric model, and some multivariate extensions are given. + date_publication: '2016-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecdfHT + url_git: '' +eCerto: + version: 0.5.14 + title: Statistical Tests for the Production of Reference Materials + maintainer: Jan Lisec + description: |- + The production of certified reference materials (CRMs) requires + various statistical tests depending on the task and recorded data to ensure + that reported values of CRMs are appropriate. + Often these tests are performed according to the procedures described in + 'ISO GUIDE 35:2017'. The 'eCerto' package contains a 'Shiny' app which + provides functionality to load, process, report and backup data recorded + during CRM production and facilitates following the recommended procedures. + It is described in Lisec et al (2023) and + can also be accessed online without + package installation. + date_publication: '2024-09-02' + bug_reports: https://github.com/janlisec/eCerto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eCerto + url_git: https://github.com/janlisec/eCerto +ecespa: + version: 1.1-17 + title: Functions for Spatial Point Pattern Analysis + maintainer: Marcelino de la Cruz Rot + description: 'Some wrappers, functions and data sets for for spatial point pattern + analysis (mainly based on ''spatstat''), used in the book "Introduccion al Analisis + Espacial de Datos en Ecologia y Ciencias Ambientales: Metodos y Aplicaciones" + and in the papers by De la Cruz et al. (2008) + and Olano et al. (2009) .' + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecespa + url_git: '' +Ecfun: + version: 0.3-6 + title: Functions for 'Ecdat' + maintainer: Spencer Graves + description: |- + Functions and vignettes to update + data sets in 'Ecdat' and to create, manipulate, + plot, and analyze those and similar data sets. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ecfun + url_git: '' +ECG: + version: 0.5.2 + title: Center of Gravity Methods + maintainer: Hugo Gasca-Aragon + description: |- + Implementation of the Centre of Gravity method and the Extrapolated Centre of Gravity method. It supports replicated observations. + Cameron, D.G., et al (1982) + JCGM (2008) . + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ECG + url_git: '' +ECGofTestDx: + version: '0.5' + title: |- + A Goodness-of-Fit Test for Elliptical Distributions with + Diagnostic Capabilities + maintainer: Pierre Lafaye De Micheaux + description: |- + A goodness-of-fit test for elliptical distributions with diagnostic + capabilities. Gilles R. Ducharme, Pierre Lafaye de Micheaux (2020) . + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ECGofTestDx + url_git: '' +ech: + version: 0.1.3 + title: Downloading and Processing Microdata from ECH-INE (Uruguay) + maintainer: Gabriela Mathieu + description: 'A consistent tool for downloading ECH data, processing them and generating + new indicators: poverty, education, employment, etc. All data are downloaded from + the official site of the National Institute of Statistics at .' + date_publication: '2023-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ech + url_git: '' +ECharts2Shiny: + version: 0.2.13 + title: |- + Embedding Interactive Charts Generated with ECharts Library into + Shiny Applications + maintainer: Xiaodong Deng + description: Embed interactive charts to their Shiny applications. These charts + will be generated by ECharts library developed by Baidu (). + Current version supports line chart, bar chart, pie chart, scatter plot, gauge, + word cloud, radar chart, tree map, and heat map. + date_publication: '2017-12-11' + bug_reports: https://github.com/XD-DENG/ECharts2Shiny/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ECharts2Shiny + url_git: https://github.com/XD-DENG/ECharts2Shiny +echarts4r: + version: 0.4.5 + title: Create Interactive Graphs with 'Echarts JavaScript' Version 5 + maintainer: David Munoz Tord + description: |- + Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes + 36 chart types, themes, 'Shiny' proxies and animations. + date_publication: '2023-06-16' + bug_reports: https://github.com/JohnCoene/echarts4r/issues/ + url: https://echarts4r.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=echarts4r + url_git: https://github.com/JohnCoene/echarts4r +echarty: + version: 1.6.6 + title: Minimal R/Shiny Interface to JavaScript Library 'ECharts' + maintainer: Larry Helgason + description: Deliver the full functionality of 'ECharts' with minimal overhead. + 'echarty' users build R lists for 'ECharts' API. Lean set of powerful commands. + date_publication: '2025-01-15' + bug_reports: https://github.com/helgasoft/echarty/issues/ + url: https://helgasoft.github.io/echarty/ + url_cran: https://CRAN.R-project.org/package=echarty + url_git: '' +echelon: + version: 0.2.0 + title: |- + The Echelon Analysis and the Detection of Spatial Clusters using + Echelon Scan Method + maintainer: Fumio Ishioka + description: Functions for the echelon analysis proposed by Myers et al. (1997) + , and the detection of spatial clusters using echelon + scan method proposed by Kurihara (2003) . + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=echelon + url_git: '' +eChem: + version: 1.0.0 + title: Simulations for Electrochemistry Experiments + maintainer: David Harvey + description: |- + Simulates cyclic voltammetry, linear-sweep voltammetry + (both with and without stirring of the solution), and single-pulse + and double-pulse chronoamperometry and chronocoulometry + experiments using the implicit finite difference method outlined in + Gosser (1993, ISBN: 9781560810261) and in Brown (2015) + . Additional functions provide + ways to display and to examine the results of these simulations. + The primary purpose of this package is to provide tools for + use in courses in analytical chemistry. + date_publication: '2018-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eChem + url_git: https://github.com/dtharvey/eChem +echo: + version: 0.1.0 + title: Echo Code Evaluations + maintainer: Jordan Mark Barbone + description: |- + Capture code evaluations and script executions by expressions, + outputs, and condition calls for logging. + date_publication: '2023-05-25' + bug_reports: https://github.com/jmbarbone/echo/issues + url: https://jmbarbone.github.io/echo/ + url_cran: https://CRAN.R-project.org/package=echo + url_git: https://github.com/jmbarbone/echo +echo.find: + version: 4.0.1 + title: |- + Finding Rhythms Using Extended Circadian Harmonic Oscillators + (ECHO) + maintainer: Jennifer Hurley + description: |- + Provides a function (echo_find()) designed to find rhythms + from data using extended harmonic oscillators. For more information, + see H. De los Santos et al. (2020) . + date_publication: '2020-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=echo.find + url_git: https://github.com/delosh653/ECHO +echogram: + version: 0.1.2 + title: Echogram Visualisation and Analysis + maintainer: Héctor Villalobos + description: Easily import multi-frequency acoustic data stored in 'HAC' files (see + for more information on the format), + and produce echogram visualisations with predefined or customized color palettes. + It is also possible to merge consecutive echograms; mask or delete unwanted echogram + areas; model and subtract background noise; and more important, develop, test + and interpret different combinations of frequencies in order to perform acoustic + filtering of the echogram's data. + date_publication: '2019-12-16' + bug_reports: https://github.com/hvillalo/echogram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=echogram + url_git: https://github.com/hvillalo/echogram +echoice2: + version: 0.2.4 + title: Choice Models with Economic Foundation + maintainer: Nino Hardt + description: Implements choice models based on economic theory, including estimation + using Markov chain Monte Carlo (MCMC), prediction, and more. Its usability is + inspired by ideas from 'tidyverse'. Models include versions of the Hierarchical + Multinomial Logit and Multiple Discrete-Continous (Volumetric) models with and + without screening. The foundations of these models are described in Allenby, Hardt + and Rossi (2019) . Models with conjunctive screening + are described in Kim, Hardt, Kim and Allenby (2022) . + Models with set-size variation are described in Hardt and Kurz (2020) . + date_publication: '2023-11-20' + bug_reports: https://github.com/ninohardt/echoice2/issues + url: http://ninohardt.de/echoice2/ + url_cran: https://CRAN.R-project.org/package=echoice2 + url_git: https://github.com/ninohardt/echoice2 +echor: + version: 0.1.9 + title: Access EPA 'ECHO' Data + maintainer: Michael Schramm + description: |- + An R interface to United States Environmental + Protection Agency (EPA) Environmental Compliance + History Online ('ECHO') Application Program Interface + (API). 'ECHO' provides information about EPA permitted + facilities, discharges, and other reporting info + associated with permitted entities. Data are obtained + from . + date_publication: '2023-06-22' + bug_reports: https://github.com/mps9506/echor/issues + url: https://mps9506.github.io/echor/ + url_cran: https://CRAN.R-project.org/package=echor + url_git: https://github.com/mps9506/echor +echos: + version: 1.0.1 + title: Echo State Networks for Time Series Modeling and Forecasting + maintainer: Alexander Häußer + description: |- + Provides a lightweight implementation of functions and methods for + fast and fully automatic time series modeling and forecasting using Echo + State Networks (ESNs). + date_publication: '2025-02-11' + bug_reports: https://github.com/ahaeusser/echos/issues + url: https://ahaeusser.github.io/echos/ + url_cran: https://CRAN.R-project.org/package=echos + url_git: https://github.com/ahaeusser/echos +ecic: + version: 0.0.4 + title: Extended Changes-in-Changes + maintainer: Frederic Kluser + description: |- + Extends the Changes-in-Changes model a la Athey and Imbens + (2006) to multiple cohorts and + time periods, which generalizes difference-in-differences estimation + techniques to the entire distribution. Computes quantile treatment + effects for every possible two-by-two combination in ecic(). Then, + aggregating all bootstrap runs adds the standard errors in + summary_ecic(). Results can be plotted with plot_ecic() aggregated + over all cohort-group combinations or in an event-study style for + either individual periods or individual quantiles. + date_publication: '2025-01-20' + bug_reports: https://github.com/frederickluser/ecic/issues + url: https://frederickluser.github.io/ecic/ + url_cran: https://CRAN.R-project.org/package=ecic + url_git: '' +ecipex: + version: '1.1' + title: |- + Efficient Calculation of Fine Structure Isotope Patterns via + Fourier Transforms of Simplex-Based Elemental Models + maintainer: Andreas Ipsen + description: |- + Provides a function that quickly computes the fine structure + isotope patterns of a set of chemical formulas to a given degree of + accuracy (up to the limit set by errors in floating point arithmetic). A + data-set comprising the masses and isotopic abundances of individual + elements is also provided and calculation of isotopic gross structures + is also supported. + date_publication: '2020-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecipex + url_git: '' +ECLRMC: + version: '1.0' + title: Ensemble Correlation-Based Low-Rank Matrix Completion + maintainer: Mahdi Ghadamyari + description: Ensemble correlation-based low-rank matrix completion method (ECLRMC) + is an extension to the LRMC based methods. Traditionally, the LRMC based methods + give identical importance to the whole data which results in emphasizing on the + commonality of the data and overlooking the subtle but crucial differences. This + method aims to overcome the equality assumption problem that exists in the current + LRMS based methods. Ensemble correlation-based low-rank matrix completion (ECLRMC) + takes consideration of the specific characteristic of each sample and performs + LRMC on the set of samples with a strong correlation. It uses an ensemble learning + method to improve the imputation performance. Since each sample is analyzed independently + this method can be parallelized by distributing imputation across many computation + units or GPU platforms. This package provides three different methods (LRMC, CLRMC + and ECLRMC) for data imputation. There is also an NRMS function for evaluating + the result. Chen, Xiaobo, et al (2017) . + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ECLRMC + url_git: '' +eclust: + version: 0.1.0 + title: |- + Environment Based Clustering for Interpretable Predictive Models + in High Dimensional Data + maintainer: Sahir Rai Bhatnagar + description: |- + Companion package to the paper: An analytic approach for + interpretable predictive models in high dimensional data, in the presence of + interactions with exposures. Bhatnagar, Yang, Khundrakpam, Evans, Blanchette, Bouchard, Greenwood (2017) . + This package includes an algorithm for clustering high dimensional data that can be affected by an environmental factor. + date_publication: '2017-01-26' + bug_reports: https://github.com/sahirbhatnagar/eclust/issues + url: http://sahirbhatnagar.com/eclust/ + url_cran: https://CRAN.R-project.org/package=eclust + url_git: https://github.com/sahirbhatnagar/eclust/ +ecm: + version: 7.2.0 + title: Build Error Correction Models + maintainer: Gaurav Bansal + description: Functions for easy building of error correction models (ECM) for time + series regression. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecm + url_git: https://github.com/gaurbans/ecm +ecmwfr: + version: 2.0.3 + title: Interface to 'ECMWF' and 'CDS' Data Web Services + maintainer: Koen Hufkens + description: |- + Programmatic interface to the European Centre for Medium-Range + Weather Forecasts dataset web services (ECMWF; ) + and Copernicus's Data Stores. Allows for easy downloads of weather + forecasts and climate reanalysis data in R. Data stores covered include the Climate Data Store (CDS; + ), Atmosphere Data Store (ADS; + ) and Early Warning Data Store (CEMS; + ). + date_publication: '2025-02-10' + bug_reports: https://github.com/bluegreen-labs/ecmwfr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecmwfr + url_git: https://github.com/bluegreen-labs/ecmwfr +ecocbo: + version: 0.12.0 + title: Calculating Optimum Sampling Effort in Community Ecology + maintainer: Arturo Sanchez-Porras + description: |- + A system for calculating the optimal sampling effort, based on the ideas of + "Ecological cost-benefit optimization" as developed by A. Underwood (1997, + ISBN 0 521 55696 1). Data is obtained from simulated ecological communities with + prep_data() which formats and arranges the initial data, and then the + optimization follows the following procedure of four functions: (1) scompvar() + calculates the variation components necessary for (2) sim_cbo() to calculate + the optimal combination of number of sites and samples depending on either + an economic budget or on a desired statistical accuracy. Additionally, (3) + sim_beta() estimates statistical power and type 2 error by using Permutational + Multivariate Analysis of Variance, and (6) plot_power() represents the + results of the previous function. + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecocbo + url_git: '' +ecochange: + version: 2.9.3.2 + title: |- + Integrating Ecosystem Remote Sensing Products to Derive EBV + Indicators + maintainer: Wilson Lara Henao + description: Essential Biodiversity Variables (EBV) are state variables with dimensions + on time, space, and biological organization that document biodiversity change. + Freely available ecosystem remote sensing products (ERSP) are downloaded and integrated + with data for national or regional domains to derive indicators for EBV in the + class ecosystem structure (Pereira et al., 2013) , + including horizontal ecosystem extents, fragmentation, and information-theory + indices. To process ERSP, users must provide a polygon or geographic administrative + data map. Downloadable ERSP include Global Surface Water (Peckel et al., 2016) + , Forest Change (Hansen et al., 2013) , + and Continuous Tree Cover data (Sexton et al., 2013) . + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecochange + url_git: '' +ecocomDP: + version: 1.3.2 + title: Tools to Create, Use, and Convert ecocomDP Data + maintainer: Colin Smith + description: |- + Work with the Ecological Community Data Design Pattern. 'ecocomDP' + is a flexible data model for harmonizing ecological community surveys, in a + research question agnostic format, from source data published across + repositories, and with methods that keep the derived data up-to-date as the + underlying sources change. Described in O'Brien et al. (2021), + . + date_publication: '2024-08-16' + bug_reports: https://github.com/EDIorg/ecocomDP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecocomDP + url_git: https://github.com/EDIorg/ecocomDP +ecoCopula: + version: 1.0.2 + title: Graphical Modelling and Ordination using Copulas + maintainer: Gordana Popovic + description: |- + Creates 'graphs' of species associations (interactions) and ordination biplots from + co-occurrence data by fitting discrete gaussian copula graphical models. Methods described in + Popovic, GC., Hui, FKC., Warton, DI., (2018) . + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecoCopula + url_git: '' +ecode: + version: 0.1.0 + title: Ordinary Differential Equation Systems in Ecology + maintainer: Haoran Wu + description: |- + A framework to simulate ecosystem dynamics through ordinary differential equations (ODEs). + You create an ODE model, tells 'ecode' to explore its behaviour, and perform numerical + simulations on the model. 'ecode' also allows you to fit model parameters by machine learning + algorithms. Potential users include researchers who are interested in the dynamics of ecological + community and biogeochemical cycles. + date_publication: '2024-07-02' + bug_reports: https://github.com/HaoranPopEvo/ecode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecode + url_git: https://github.com/HaoranPopEvo/ecode +EcoDiet: + version: 2.0.1 + title: Estimating a Diet Matrix from Biotracer and Stomach Content Data + maintainer: Pierre-Yves Hernvann + description: |- + Biotracers and stomach content analyses are combined in a Bayesian hierarchical model + to estimate a probabilistic topology matrix (all trophic link probabilities) and a diet matrix + (all diet proportions). + The package relies on the JAGS software and the 'jagsUI' package to run a Markov chain Monte Carlo + approximation of the different variables. + date_publication: '2024-03-25' + bug_reports: https://github.com/pyhernvann/EcoDiet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EcoDiet + url_git: https://github.com/pyhernvann/EcoDiet +ecodist: + version: 2.1.3 + title: Dissimilarity-Based Functions for Ecological Analysis + maintainer: Sarah Goslee + description: Dissimilarity-based analysis functions including ordination and Mantel + test functions, intended for use with spatial and community ecological data. The + original package description is in Goslee and Urban (2007) , + with further statistical detail in Goslee (2010) . + date_publication: '2023-10-30' + bug_reports: https://github.com/phiala/ecodist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecodist + url_git: '' +EcoEnsemble: + version: 1.1.0 + title: A General Framework for Combining Ecosystem Models + maintainer: Michael A. Spence + description: 'Fit and sample from the ensemble model described in Spence et al (2018): + "A general framework for combining ecosystem models".' + date_publication: '2024-08-19' + bug_reports: https://github.com/CefasRepRes/EcoEnsemble/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EcoEnsemble + url_git: https://github.com/CefasRepRes/EcoEnsemble +Ecohydmod: + version: 1.0.0 + title: Ecohydrological Modelling + maintainer: Rodolfo Souza + description: Simulates the soil water balance (soil moisture, evapotranspiration, + leakage and runoff), rainfall series by using the marked Poisson process and the + vegetation growth through the normalized difference vegetation index (NDVI). Please + see Souza et al. (2016) . + date_publication: '2017-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ecohydmod + url_git: '' +EcoIndR: + version: '2.0' + title: Ecological Indicators + maintainer: Castor Guisande Gonzalez + description: Calculates several indices, such as of diversity, fluctuation, etc., + and they are used to estimate ecological indicators. + date_publication: '2023-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EcoIndR + url_git: '' +ECoL: + version: 0.3.0 + title: Complexity Measures for Supervised Problems + maintainer: Luis Garcia + description: |- + Provides measures to characterize the complexity of classification + and regression problems based on aspects that quantify the linearity of the + data, the presence of informative feature, the sparsity and dimensionality + of the datasets. This package provides bug fixes, generalizations and + implementations of many state of the art measures. The measures are + described in the papers: Lorena et al. (2019) and + Lorena et al. (2018) . + date_publication: '2019-11-05' + bug_reports: https://github.com/lpfgarcia/ECoL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ECoL + url_git: https://github.com/lpfgarcia/ECoL/ +ecolMod: + version: 1.2.6.4 + title: |- + "A Practical Guide to Ecological Modelling - Using R as a + Simulation Platform" + maintainer: Karline Soetaert + description: |- + Figures, data sets and examples from the book "A practical guide to ecological modelling - using R as a simulation platform" by Karline Soetaert and Peter MJ Herman (2009). Springer. + All figures from chapter x can be generated by "demo(chapx)", where x = 1 to 11. + The R-scripts of the model examples discussed in the book are in subdirectory "examples", ordered per chapter. + Solutions to model projects are in the same subdirectories. + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecolMod + url_git: '' +ecolottery: + version: 1.0.0 + title: Coalescent-Based Simulation of Ecological Communities + maintainer: François Munoz + description: |- + Coalescent-Based Simulation of Ecological Communities as proposed + by Munoz et al. (2017) . The package includes + a tool for estimating parameters of community assembly by using Approximate + Bayesian Computation. + date_publication: '2017-07-03' + bug_reports: https://github.com/frmunoz/ecolottery/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecolottery + url_git: https://github.com/frmunoz/ecolottery +ecolRxC: + version: 0.1.1-10 + title: |- + Ecological Inference of RxC Tables by Latent Structure + Approaches + maintainer: Jose M. Pavía + description: |- + Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) from aggregate data building on Thomsen (1987) and Park (2008) approaches. + References: + Park, W.-H. (2008). ''Ecological Inference and Aggregate Analysis of Election''. PhD Dissertation. University of Michigan. + Thomsen, S.R. (1987, ISBN:87-7335-037-2). ''Danish Elections 1920 79: a Logit Approach to Ecological Analysis and Inference''. Politica, Aarhus, Denmark. + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecolRxC + url_git: '' +ecolTest: + version: 0.0.1 + title: Community Ecology Tests + maintainer: Hugo Salinas + description: Functions and data sets to perform and demonstrate community ecology + statistical tests, including Hutcheson's t-test (Hutcheson (1970) , + Zar (2010) ISBN:9780321656865). + date_publication: '2021-02-15' + bug_reports: https://github.com/hugosal/ecolTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecolTest + url_git: https://github.com/hugosal/ecolTest +EcoMetrics: + version: 0.1.1 + title: Econometrics Model Building + maintainer: Mutua Kilai + description: |- + An intuitive and user-friendly package designed to aid undergraduate students in understanding and applying econometric methods in their studies, + Tailored specifically for Econometrics and Regression Modeling courses, it provides a practical toolkit for modeling and analyzing econometric data with detailed inference capabilities. + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EcoMetrics + url_git: '' +EconAndProdEfficiency: + version: 0.1.0 + title: Economic and Production Efficiency + maintainer: Tanuj Misra + description: Production efficiency and economic efficiency are crucial concepts + in agriculture/horticulture for sustainable and profitable practices. It helps + to determine the optimal use of resources to maximize outputs and profitability. + Production efficiency focuses on the optimal use of resources to produce goods, + while economic efficiency ensures these goods are produced and allocated in a + way that maximizes economic welfare. Production efficiency and economic efficiency + are calculated with the help of the formula given by (Kumar et al., 2017) . + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EconAndProdEfficiency + url_git: '' +EconDemand: + version: '1.0' + title: General Analysis of Various Economics Demand Systems + maintainer: Tianhao Wu + description: Tools for general properties including price, quantity, elasticity, + convexity, marginal revenue and manifold of various economics demand systems including + Linear, Translog, CES, LES and CREMR. + date_publication: '2016-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EconDemand + url_git: '' +econet: + version: 1.0.0.1 + title: Estimation of Parameter-Dependent Network Centrality Measures + maintainer: Valerio Leone Sciabolazza + description: Provides methods for estimating parameter-dependent network centrality + measures with linear-in-means models. Both non linear least squares and maximum + likelihood estimators are implemented. The methods allow for both link and node + heterogeneity in network effects, endogenous network formation and the presence + of unconnected nodes. The routines also compare the explanatory power of parameter-dependent + network centrality measures with those of standard measures of network centrality. + Benefits and features of the 'econet' package are illustrated using data from + Battaglini and Patacchini (2018) and Battaglini, Patacchini, and Leone Sciabolazza + (2020). For additional details, see the vignette . + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=econet + url_git: '' +EcoNetGen: + version: 0.2.4 + title: Simulate and Sample from Ecological Interaction Networks + maintainer: Carl Boettiger + description: |- + Randomly generate a wide range of interaction networks with + specified size, average degree, modularity, and topological + structure. Sample nodes and links from within simulated networks + randomly, by degree, by module, or by abundance. Simulations + and sampling routines are implemented in 'FORTRAN', providing + efficient generation times even for large networks. Basic + visualization methods also included. Algorithms implemented + here are described in de Aguiar et al. (2017) . + date_publication: '2023-08-27' + bug_reports: https://github.com/cboettig/EcoNetGen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EcoNetGen + url_git: https://github.com/cboettig/EcoNetGen +econetwork: + version: 0.7.0 + title: Analyzing Ecological Networks + maintainer: Vincent Miele + description: A collection of advanced tools, methods and models specifically designed for analyzing + different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic + (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their + variability in time and space. Statistical models are developed to describe and + understand the mechanisms that determine species interactions, and to decipher + the organization of these ecological networks (Ohlmann et al. (2019) , + Gonzalez et al. (2020) , Miele et al. (2021) , + Botella et al (2021) ). + date_publication: '2022-10-21' + bug_reports: '' + url: https://plmlab.math.cnrs.fr/econetproject/econetwork + url_cran: https://CRAN.R-project.org/package=econetwork + url_git: '' +EconGeo: + version: '2.0' + title: |- + Computing Key Indicators of the Spatial Distribution of Economic + Activities + maintainer: Pierre-Alexandre Balland + description: Computes a series of indices commonly used in the fields of economic + geography, economic complexity, and evolutionary economics to describe the location, + distribution, spatial organization, structure, and complexity of economic activities. + Functions include basic spatial indicators such as the location quotient, the + Krugman specialization index, the Herfindahl or the Shannon entropy indices but + also more advanced functions to compute different forms of normalized relatedness + between economic activities or network-based measures of economic complexity. + Most of the functions use matrix calculus and are based on bipartite (incidence) + matrices consisting of region - industry pairs. These are described in Balland + (2017) . + date_publication: '2023-06-26' + bug_reports: https://github.com/PABalland/EconGeo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EconGeo + url_git: https://github.com/PABalland/EconGeo +economiccomplexity: + version: 2.0.0 + title: Computational Methods for Economic Complexity + maintainer: Mauricio Vargas Sepulveda + description: |- + A wrapper of different methods from Linear Algebra for the equations + introduced in The Atlas of Economic Complexity and related literature. This + package provides standard matrix and graph output that can be used seamlessly + with other packages. See for a summary + of these methods and its evolution in literature. + date_publication: '2024-12-13' + bug_reports: https://github.com/pachadotdev/economiccomplexity/issues/ + url: https://pacha.dev/economiccomplexity/ + url_cran: https://CRAN.R-project.org/package=economiccomplexity + url_git: '' +econullnetr: + version: 0.2.1 + title: Null Model Analysis for Ecological Networks + maintainer: Ian Vaughan + description: |- + Tools for using null models to analyse ecological + networks (e.g. food webs, flower-visitation networks, seed-dispersal + networks) and detect resource preferences or non-random interactions among + network nodes. Tools are provided to run null models, test for and plot + preferences, plot and analyse bipartite networks, and export null model + results in a form compatible with other network analysis packages. The + underlying null model was developed by Agusti et al. (2003) Molecular + Ecology and the full application to + ecological networks by Vaughan et al. (2018) econullnetr: an R package + using null models to analyse the structure of ecological networks and + identify resource selection. Methods in Ecology & Evolution, + . + date_publication: '2021-06-02' + bug_reports: https://github.com/ivaughan/econullnetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=econullnetr + url_git: '' +ecopower: + version: 0.2.0 + title: Power Estimates and Equivalence Testing for Multivariate Data + maintainer: Michelle Lim + description: |- + Estimates power by simulation for multivariate + abundance data to be used for sample size estimates. Multivariate + equivalence testing by simulation from a Gaussian copula model. + The package also provides functions for parameterising multivariate effect + sizes and simulating multivariate abundance data jointly. The discrete + Gaussian copula approach is described in + Popovic et al. (2018) . + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecopower + url_git: '' +ecoreg: + version: 0.2.5 + title: Ecological Regression using Aggregate and Individual Data + maintainer: Christopher Jackson + description: |- + Estimating individual-level covariate-outcome associations + using aggregate data ("ecological inference") or a combination of + aggregate and individual-level data ("hierarchical related regression"). + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecoreg + url_git: '' +ecoregime: + version: 0.2.0 + title: Analysis of Ecological Dynamic Regimes + maintainer: Martina Sánchez-Pinillos + description: |- + A toolbox for implementing the Ecological Dynamic Regime framework + (Sánchez-Pinillos et al., 2023 ) to characterize and + compare groups of ecological trajectories in multidimensional spaces defined + by state variables. The package includes the RETRA-EDR algorithm to identify + representative trajectories, functions to generate, summarize, and visualize + representative trajectories, and several metrics to quantify the distribution + and heterogeneity of trajectories in an ecological dynamic regime and quantify + the dissimilarity between two or more ecological dynamic regimes. The package + also includes a set of functions to assess ecological resilience based on + ecological dynamic regimes (Sánchez-Pinillos et al., 2024 ). + date_publication: '2024-04-17' + bug_reports: https://github.com/MSPinillos/ecoregime/issues + url: https://mspinillos.github.io/ecoregime/ + url_cran: https://CRAN.R-project.org/package=ecoregime + url_git: https://github.com/MSPinillos/ecoregime +ecorest: + version: 2.0.0 + title: Conducts Analyses Informing Ecosystem Restoration Decisions + maintainer: S. Kyle McKay + description: |- + Three sets of data and functions for informing ecosystem restoration + decisions, particularly in the context of the U.S. Army Corps of Engineers. + First, model parameters are compiled as a data set and associated metadata + for over 300 habitat suitability models developed by the U.S. Fish and + Wildlife Service (USFWS 1980, ). + Second, functions for conducting habitat suitability analyses both for the + models described above as well as generic user-specified model parameterizations. + Third, a suite of decision support tools for conducting cost-effectiveness and + incremental cost analyses (Robinson et al. 1995, IWR Report 95-R-1, U.S. + Army Corps of Engineers). + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecorest + url_git: '' +ecos: + version: 0.1.6 + title: Economic Statistics System of the Bank of Korea + maintainer: Seokhoon Joo + description: |- + API wrapper to download statistical information from the Economic + Statistics System (ECOS) of the Bank of Korea + . + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecos + url_git: '' +ecosim: + version: 1.3-4 + title: Toolbox for Aquatic Ecosystem Modeling + maintainer: Peter Reichert + description: |- + Classes and methods for implementing aquatic ecosystem models, + for running these models, and for visualizing their results. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecosim + url_git: '' +ECOSolveR: + version: 0.5.5 + title: Embedded Conic Solver in R + maintainer: Balasubramanian Narasimhan + description: |- + R interface to the Embedded COnic Solver (ECOS), an efficient + and robust C library for convex problems. Conic and equality + constraints can be specified in addition to integer and + boolean variable constraints for mixed-integer problems. This + R interface is inspired by the python interface and has + similar calling conventions. + date_publication: '2023-05-15' + bug_reports: https://github.com/bnaras/ECOSolveR/issues + url: https://bnaras.github.io/ECOSolveR/ + url_cran: https://CRAN.R-project.org/package=ECOSolveR + url_git: '' +ecospace: + version: 1.4.2 + title: |- + Simulating Community Assembly and Ecological Diversification + Using Ecospace Frameworks + maintainer: Phil Novack-Gottshall + description: |- + Implements stochastic simulations of community assembly (ecological + diversification) using customizable ecospace frameworks (functional trait + spaces). Provides a wrapper to calculate common ecological disparity and + functional ecology statistical dynamics as a function of species richness. + Functions are written so they will work in a parallel-computing environment. + date_publication: '2020-06-13' + bug_reports: https://github.com/pnovack-gottshall/ecospace/issues + url: http://www.ben.edu/faculty/pnovack-gottshall/index.html + url_cran: https://CRAN.R-project.org/package=ecospace + url_git: https://github.com/pnovack-gottshall/ecospace +ecospat: + version: 4.1.2 + title: Spatial Ecology Miscellaneous Methods + maintainer: Olivier Broennimann + description: Collection of R functions and data sets for the support of spatial + ecology analyses with a focus on pre, core and post modelling analyses of species + distribution, niche quantification and community assembly. Written by current + and former members and collaborators of the ecospat group of Antoine Guisan, Department + of Ecology and Evolution (DEE) and Institute of Earth Surface Dynamics (IDYST), + University of Lausanne, Switzerland. Read Di Cola et al. (2016) + for details. + date_publication: '2025-01-31' + bug_reports: https://github.com/ecospat/ecospat/issues + url: https://www.unil.ch/ecospat/home/menuguid/ecospat-resources/tools.html + url_cran: https://CRAN.R-project.org/package=ecospat + url_git: '' +ecostate: + version: 0.2.0 + title: State-Space Mass-Balance Model for Marine Ecosystems + maintainer: James T. Thorson + description: |- + Fits a state-space mass-balance model for marine ecosystems, + which implements dynamics derived from + 'Ecopath with Ecosim' + while fitting to time-series of fishery catch, biomass indices, + age-composition samples, and weight-at-age data. Package + 'ecostate' fits biological parameters (e.g., equilibrium mass) + and measurement parameters (e.g., catchability coefficients) + jointly with residual variation in process errors, and can include + Bayesian priors for parameters. + date_publication: '2024-11-25' + bug_reports: https://github.com/James-Thorson-NOAA/ecostate/issues + url: https://james-thorson-noaa.github.io/ecostate/ + url_cran: https://CRAN.R-project.org/package=ecostate + url_git: '' +ecostats: + version: 1.2.1 + title: Code and Data Accompanying the Eco-Stats Text (Warton 2022) + maintainer: David Warton + description: Functions and data supporting the Eco-Stats text (Warton, 2022, Springer), + and solutions to exercises. Functions include tools for using simulation envelopes + in diagnostic plots, and a function for diagnostic plots of multivariate linear + models. Datasets mentioned in the package are included here (where not available + elsewhere) and there is a vignette for each chapter of the text with solutions + to exercises. + date_publication: '2024-07-04' + bug_reports: '' + url: https://dwarton.github.io/ecostats/ + url_cran: https://CRAN.R-project.org/package=ecostats + url_git: '' +ecostatscale: + version: '1.1' + title: Statistical Scaling Functions for Ecological Systems + maintainer: Adam Clark + description: Implementation of the scaling functions presented in "General statistical + scaling laws for stability in ecological systems" by Clark et al in Ecology Letters + . Includes functions for extrapolating variability, resistance, + and resilience across spatial and ecological scales, as well as a basic simulation + function for producing time series, and a regression routine for generating unbiased + parameter estimates. See the main text of the paper for more details. + date_publication: '2023-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecostatscale + url_git: '' +EcotoneFinder: + version: 0.2.3 + title: Characterising and Locating Ecotones and Communities + maintainer: Antoine Bagnaro + description: Analytical methods to locate and characterise ecotones, ecosystems + and environmental patchiness along ecological gradients. Methods are implemented + for isolated sampling or for space/time series. It includes Detrended Correspondence + Analysis (Hill & Gauch (1980) ), fuzzy clustering (De + Cáceres et al. (2010) ), biodiversity indices + (Jost (2006) ), and network analyses (Epskamp + et al. (2012) ) - as well as tools to explore the number + of clusters in the data. Functions to produce synthetic ecological datasets are + also provided. + date_publication: '2021-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EcotoneFinder + url_git: '' +ecotox: + version: 1.4.4 + title: Analysis of Ecotoxicology + maintainer: Benjamin L Hlina + description: |- + A simple approach to using a probit or logit analysis to calculate + lethal concentration (LC) or time (LT) and the appropriate fiducial + confidence limits desired for selected LC or LT for + ecotoxicology studies (Finney 1971; Wheeler et al. 2006; + Robertson et al. 2007). The simplicity of 'ecotox' comes from the + syntax it implies within its functions which are similar to functions + like glm() and lm(). In addition to the simplicity of the syntax, + a comprehensive data frame is produced which gives the user a + predicted LC or LT value for the desired level and a suite of important + parameters such as fiducial confidence limits and slope. + Finney, D.J. (1971, ISBN: 052108041X); + Wheeler, M.W., Park, R.M., and Bailer, A.J. (2006) ; + Robertson, J.L., Savin, N.E., Russell, R.M., and Preisler, H.K. + (2007, ISBN: 0849323312). + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecotox + url_git: '' +ecotoxicology: + version: 1.0.1 + title: Methods for Ecotoxicology + maintainer: Jose Gama + description: |- + Implementation of the EPA's Ecological Exposure Research Division (EERD) tools (discontinued in 1999) for Probit and Trimmed Spearman-Karber Analysis. + Probit and Spearman-Karber methods from Finney's book "Probit analysis a statistical treatment of the sigmoid response curve" with options for most accurate results or identical results to the book. + Probit and all the tables from Finney's book (code-generated, not copied) with the generating functions included. + Control correction: Abbott, Schneider-Orelli, Henderson-Tilton, Sun-Shepard. + Toxicity scales: Horsfall-Barratt, Archer, Gauhl-Stover, Fullerton-Olsen, etc. + date_publication: '2015-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecotoxicology + url_git: '' +ECOTOXr: + version: 1.1.1 + title: Download and Extract Data from US EPA's ECOTOX Database + maintainer: Pepijn de Vries + description: |- + The US EPA ECOTOX database is a freely available database + with a treasure of aquatic and terrestrial ecotoxicological data. + As the online search interface doesn't come with an API, this + package provides the means to easily access and search the database + in R. To this end, all raw tables are downloaded from the EPA website + and stored in a local SQLite database . + date_publication: '2024-09-20' + bug_reports: https://github.com/pepijn-devries/ECOTOXr/issues + url: https://pepijn-devries.github.io/ECOTOXr/ + url_cran: https://CRAN.R-project.org/package=ECOTOXr + url_git: https://github.com/pepijn-devries/ECOTOXr +ecotraj: + version: 0.1.1 + title: Ecological Trajectory Analysis + maintainer: Miquel De Cáceres + description: |- + Assists ecologists in the analysis of temporal changes of + ecosystems, defined as trajectories on a chosen multivariate space, by providing a set of + trajectory metrics and visual representations [De Caceres et al. (2019) ; + and Sturbois et al. (2021) ]. Includes functions + to estimate metrics for individual trajectories (length, directionality, angles, ...) as well as + metrics to relate pairs of trajectories (dissimilarity and convergence). Functions are also + provided to estimate the ecological quality of ecosystem with respect to reference conditions + [Sturbois et al. (2023) ]. + date_publication: '2023-10-30' + bug_reports: '' + url: https://emf-creaf.github.io/ecotraj/ + url_cran: https://CRAN.R-project.org/package=ecotraj + url_git: '' +EcoTroph: + version: 1.6.1 + title: An Implementation of the EcoTroph Ecosystem Modelling Approach + maintainer: Jerome Guitton + description: An approach and software for modelling marine and freshwater ecosystems. + It is articulated entirely around trophic levels. EcoTroph's key displays are + bivariate plots, with trophic levels as the abscissa, and biomass flows or related + quantities as ordinates. Thus, trophic ecosystem functioning can be modelled as + a continuous flow of biomass surging up the food web, from lower to higher trophic + levels, due to predation and ontogenic processes. Such an approach, wherein species + as such disappear, may be viewed as the ultimate stage in the use of the trophic + level metric for ecosystem modelling, providing a simplified but potentially useful + caricature of ecosystem functioning and impacts of fishing. This version contains + catch trophic spectrum analysis (CTSA) function and corrected versions of the + mf.diagnosis and create.ETmain functions. + date_publication: '2022-04-13' + bug_reports: '' + url: http://sirs.agrocampus-ouest.fr/EcoTroph/ + url_cran: https://CRAN.R-project.org/package=EcoTroph + url_git: '' +ecoval: + version: 1.2.9 + title: Procedures for Ecological Assessment of Surface Waters + maintainer: Nele Schuwirth + description: |- + Functions for evaluating and visualizing + ecological assessment procedures for surface waters + containing physical, chemical and biological assessments + in the form of value functions. + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecoval + url_git: '' +EcoVirtual: + version: '1.1' + title: Simulation of Ecological Models + maintainer: Alexandre Adalardo de Oliveira + description: |- + Computer simulations of classical ecological models as a + learning resource. + date_publication: '2018-10-11' + bug_reports: '' + url: http//ecovirtual.ib.usp.br + url_cran: https://CRAN.R-project.org/package=EcoVirtual + url_git: '' +ecp: + version: 3.1.6 + title: |- + Non-Parametric Multiple Change-Point Analysis of Multivariate + Data + maintainer: Wenyu Zhang + description: |- + Implements various procedures for finding + multiple change-points from Matteson D. et al (2013) + , Zhang W. et al (2017) + , Arlot S. et al (2019). + Two methods make use of dynamic + programming and pruning, with no distributional + assumptions other than the existence of certain absolute + moments in one method. Hierarchical and exact search methods + are included. All methods return the set of estimated change- + points as well as other summary information. + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecp + url_git: '' +ecpc: + version: 3.1.1 + title: Flexible Co-Data Learning for High-Dimensional Prediction + maintainer: Mirrelijn M. van Nee + description: |- + Fit linear, logistic and Cox survival regression models penalised with adaptive multi-group ridge penalties. + The multi-group penalties correspond to groups of covariates defined by (multiple) co-data sources. + Group hyperparameters are estimated with an empirical Bayes method of moments, penalised with an extra level of hyper shrinkage. + Various types of hyper shrinkage may be used for various co-data. + Co-data may be continuous or categorical. + The method accommodates inclusion of unpenalised covariates, posterior selection of covariates and multiple data types. + The model fit is used to predict for new samples. + The name 'ecpc' stands for Empirical Bayes, Co-data learnt, Prediction and Covariate selection. + See Van Nee et al. (2020) . + date_publication: '2023-02-27' + bug_reports: '' + url: http://dx.doi.org/10.1002/sim.9162 + url_cran: https://CRAN.R-project.org/package=ecpc + url_git: '' +ecpdist: + version: 0.2.1 + title: Extended Chen-Poisson Lifetime Distribution + maintainer: Ana Abreu + description: |- + Computes the Extended Chen-Poisson (ecp) distribution, survival, + density, hazard, cumulative hazard and quantile functions. It also allows + to generate a pseudo-random sample from this distribution. The corresponding + graphics are available. Functions to obtain measures of skewness and + kurtosis, k-th raw moments, conditional k-th moments and mean + residual life function were added. For details about ecp distribution, see + Sousa-Ferreira, I., Abreu, A.M. & Rocha, C. (2023). + . + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ecpdist + url_git: +ecr: + version: 2.1.1 + title: Evolutionary Computation in R + maintainer: Jakob Bossek + description: Framework for building evolutionary algorithms for both single- and + multi-objective continuous or discrete optimization problems. A set of predefined + evolutionary building blocks and operators is included. Moreover, the user can + easily set up custom objective functions, operators, building blocks and representations + sticking to few conventions. The package allows both a black-box approach for + standard tasks (plug-and-play style) and a much more flexible white-box approach + where the evolutionary cycle is written by hand. + date_publication: '2023-03-08' + bug_reports: https://github.com/jakobbossek/ecr2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ecr + url_git: https://github.com/jakobbossek/ecr2 +ectotemp: + version: 0.2.0 + title: |- + Quantitative Estimates of Small Ectotherm Temperature Regulation + Effectiveness + maintainer: Wouter Beukema + description: 'Easy and rapid quantitative estimation of small terrestrial ectotherm + temperature regulation effectiveness in R. ectotemp is built on classical formulas + that evaluate temperature regulation by means of various indices, inaugurated + by Hertz et al. (1993) . Options for bootstrapping and permutation + testing are included to test hypotheses about divergence between organisms, species + or populations.' + date_publication: '2020-07-16' + bug_reports: https://github.com/wouterbeukema/ectotemp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ectotemp + url_git: '' +ECTSVR: + version: 0.1.0 + title: Cointegration Based Support Vector Regression Model + maintainer: Pankaj Das + description: The cointegration based support vector regression model enables researchers + to use data obtained from the cointegrating vector as input in the support vector + regression model. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ECTSVR + url_git: '' +ECTTDNN: + version: 0.1.0 + title: Cointegration Based Timedelay Neural Network Model + maintainer: Pankaj Das + description: This cointegration based Time Delay Neural Network Model hybrid model + allows the researcher to make use of the information extracted by the cointegrating + vector as an input in the neural network model. + date_publication: '2021-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ECTTDNN + url_git: '' +Ecume: + version: 0.9.2 + title: |- + Equality of 2 (or k) Continuous Univariate and Multivariate + Distributions + maintainer: Hector Roux de Bezieux + description: |- + We implement (or re-implements in R) a variety of statistical + tools. They are focused on non-parametric two-sample (or k-sample) + distribution comparisons in the univariate or multivariate case. See + the vignette for more info. + date_publication: '2024-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ecume + url_git: '' +eCV: + version: 0.0.2 + title: |- + Enhanced Coefficient of Variation and IDR Extensions for + Reproducibility Assessment + maintainer: Agustin Gonzalez-Reymundez + description: |2- + + Reproducibility assessment is essential in extracting reliable scientific + insights from high-throughput experiments. While the Irreproducibility + Discovery Rate (IDR) method has been instrumental in assessing + reproducibility, its standard implementation is constrained to handling + only two replicates. Package 'eCV' introduces an enhanced Coefficient of + Variation (eCV) metric to assess the likelihood of omic features being + reproducible. Additionally, it offers alternatives to the Irreproducible + Discovery Rate (IDR) calculations for multi-replicate experiments. + These tools are valuable for analyzing high-throughput data in genomics + and other omics fields. The methods implemented in 'eCV' are described + in Gonzalez-Reymundez et al., (2023) . + date_publication: '2024-01-19' + bug_reports: https://github.com/eclipsebio/eCV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eCV + url_git: https://github.com/eclipsebio/eCV +ed50: + version: 0.1.1 + title: Estimate ED50 and Its Confidence Interval + maintainer: Yongbo Gan + description: |- + Functions of five estimation method for ED50 (50 percent effective dose) are provided, and they are respectively + Dixon-Mood method (1948) , Choi's original turning point method (1990) and it's modified version given by + us, as well as logistic regression and isotonic regression. Besides, the package also supports + comparison between two estimation results. + date_publication: '2019-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ed50 + url_git: '' +ed50simulation: + version: 0.1.1 + title: Estimate ED50 and Its Confidence Interval + maintainer: Fengru Wang + description: |- + Functions of five estimation method for ED50 (50 percent effective dose) are provided, and they are respectively + Dixon-Mood method (1948) , Choi's original turning point method (1990) and it's modified version given by + us, as well as logistic regression and isotonic regression. Besides, the package also supports + comparison between two estimation results. + date_publication: '2019-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ed50simulation + url_git: '' +eda4treeR: + version: 1.1.0 + title: Experimental Design and Analysis for Tree Improvement + maintainer: Muhammad Yaseen + description: Provides data sets and R Codes for E.R. Williams, C.E. Harwood and + A.C. Matheson (2023). Experimental Design and Analysis for Tree Improvement, CSIRO + Publishing. + date_publication: '2024-09-13' + bug_reports: https://github.com/myaseen208/eda4treeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eda4treeR + url_git: https://github.com/MYaseen208/eda4treeRhttps://CRAN.R-project.org/package=eda4treeRhttps://myaseen208.com/eda4treeR/https://myaseen208.com/EDATR/ +EDCimport: + version: 0.5.2 + title: Import Data from EDC Software + maintainer: Dan Chaltiel + description: A convenient toolbox to import data exported from Electronic Data Capture + (EDC) software 'TrialMaster'. + date_publication: '2024-11-14' + bug_reports: https://github.com/DanChaltiel/EDCimport/issues + url: https://danchaltiel.github.io/EDCimport/ + url_cran: https://CRAN.R-project.org/package=EDCimport + url_git: https://github.com/DanChaltiel/EDCimport +edcpR: + version: 1.0.1 + title: Ecological Data Collection and Processing Package + maintainer: Ward Fonteyn + description: This is the course package for the exercise portion of the "Ecological + Data Collection and Processing" course. + date_publication: '2021-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edcpR + url_git: '' +eddington: + version: 4.2.0 + title: Compute a Cyclist's Eddington Number + maintainer: Paul Egeler + description: |- + Compute a cyclist's Eddington number, including efficiently + computing cumulative E over a vector. A cyclist's Eddington number + + is the maximum number satisfying the condition such that a cyclist has + ridden E miles or greater on E distinct days. The algorithm in this package + is an improvement over the conventional approach because both summary + statistics and cumulative statistics can be computed in linear time, since + it does not require initial sorting of the data. These functions may also be + used for computing h-indices for authors, a metric described by Hirsch (2005) + . Both are specific applications of computing + the side length of a Durfee square . + date_publication: '2024-08-16' + bug_reports: https://github.com/pegeler/eddington2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eddington + url_git: https://github.com/pegeler/eddington2 +edeaR: + version: 0.9.4 + title: Exploratory and Descriptive Event-Based Data Analysis + maintainer: Gert Janssenswillen + description: Exploratory and descriptive analysis of event based data. Provides + methods for describing and selecting process data, and for preparing event log + data for process mining. Builds on the S3-class for event logs implemented in + the package 'bupaR'. + date_publication: '2023-04-27' + bug_reports: https://github.com/bupaverse/edeaR/issues/ + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=edeaR + url_git: https://github.com/bupaverse/edeaR/ +edecob: + version: 1.2.2 + title: Event Detection Using Confidence Bounds + maintainer: Zheng Chen Man + description: |- + Detects sustained change in digital bio-marker data using + simultaneous confidence bands. Accounts for noise using an auto-regressive + model. Based on Buehlmann (1998) "Sieve bootstrap for smoothing in + nonstationary time series" . + date_publication: '2022-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edecob + url_git: '' +edf: + version: 1.0.0 + title: Read Data from European Data Format (EDF and EDF+) Files + maintainer: Andreas Henelius + description: |- + Import physiologic data stored in + the European Data Format (EDF and EDF+) into R. + Both EDF and EDF+ files are supported. Discontinuous + EDF+ files are not yet supported. + date_publication: '2016-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edf + url_git: https://github.com/bwrc/edf +edfReader: + version: 1.2.1 + title: Reading EDF(+) and BDF(+) Files + maintainer: Jan Vis + description: |- + Reads European Data Format files EDF and EDF+, see , + BioSemi Data Format files BDF, see , + and BDF+ files, see . + The files are read in two steps: first the header is read + and then the signals (using the header object as a parameter). + date_publication: '2019-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edfReader + url_git: '' +EDFtest: + version: 0.1.0 + title: Goodness of Fit Based on Empirical Distribution Function + maintainer: Li Yao + description: 'This repository contains software for the calculation of goodness-of-fit + test statistics and their P-values. The three statistics computed are the Empirical + Distribution function statistics called Cramer-von Mises, Anderson-Darling, and + Watson statistics. The statistics and their P-values can be used to assess an + assumed distribution.The following distributions are available: Uniform, Normal, + Gamma, Logistic, Laplace, Weibull, Extreme Value, and Exponential.' + date_publication: '2021-10-25' + bug_reports: https://github.com/LiYao-sfu/EDFtest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EDFtest + url_git: '' +edfun: + version: 0.2.0 + title: Creating Empirical Distribution Functions + maintainer: Tal Galili + description: |- + Easily creating empirical distribution functions from data: 'dfun', 'pfun', + 'qfun' and 'rfun'. + date_publication: '2016-08-27' + bug_reports: https://github.com/talgalili/edfun/issues + url: https://www.r-statistics.com/tag/edfun/ + url_cran: https://CRAN.R-project.org/package=edfun + url_git: https://github.com/talgalili/edfun/ +edgar: + version: 2.0.7 + title: |- + Tool for the U.S. SEC EDGAR Retrieval and Parsing of Corporate + Filings + maintainer: Gunratan Lonare + description: |- + In the USA, companies file different forms with the U.S. + Securities and Exchange Commission (SEC) through EDGAR (Electronic + Data Gathering, Analysis, and Retrieval system). The EDGAR + database automated system collects all the different necessary + filings and makes it publicly available. This package facilitates + retrieving, storing, searching, and parsing of all the available + filings on the EDGAR server. It downloads filings from SEC + server in bulk with a single query. Additionally, it provides + various useful functions: extracts 8-K triggering events, extract + "Business (Item 1)" and "Management's Discussion and Analysis(Item 7)" + sections of annual statements, searches filings for desired + keywords, provides sentiment measures, parses filing header + information, and provides HTML view of SEC filings. + date_publication: '2023-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edgar + url_git: '' +edgarWebR: + version: 1.1.0 + title: SEC Filings Access + maintainer: Micah J Waldstein + description: |- + A set of methods to access and parse live filing information from the + U.S. Securities and Exchange Commission (SEC - ) including + company and fund filings along with all associated metadata. + date_publication: '2021-04-24' + bug_reports: https://github.com/mwaldstein/edgarWebR/issues + url: https://mwaldstein.github.io/edgarWebR/ + url_cran: https://CRAN.R-project.org/package=edgarWebR + url_git: https://github.com/mwaldstein/edgarWebR +edgebundle: + version: 0.4.2 + title: |- + Algorithms for Bundling Edges in Networks and Visualizing Flow + and Metro Maps + maintainer: David Schoch + description: Implements several algorithms for bundling edges in networks and flow + and metro map layouts. This includes force directed edge bundling , + a flow algorithm based on Steiner trees and + a multicriteria optimization method for metro map layouts . + date_publication: '2023-12-16' + bug_reports: https://github.com/schochastics/edgebundle/issues + url: https://schochastics.github.io/edgebundle/ + url_cran: https://CRAN.R-project.org/package=edgebundle + url_git: https://github.com/schochastics/edgebundle +edgebundleR: + version: 0.1.4 + title: Circle Plot with Bundled Edges + maintainer: Garth Tarr + description: |- + Generates interactive circle plots with the nodes around the + circumference and linkages between the connected nodes using hierarchical + edge bundling via the D3 JavaScript library. See for more + information on D3. + date_publication: '2016-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edgebundleR + url_git: https://github.com/garthtarr/edgebundleR +edgeCorr: + version: '1.0' + title: Spatial Edge Correction + maintainer: Glenna Nightingale + description: Facilitates basic spatial edge correction to point pattern data. + date_publication: '2016-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edgeCorr + url_git: '' +edgedata: + version: 0.2.0 + title: Datasets that Support the EDGE Server DIY Logic + maintainer: Ethan Brockmann + description: "Datasets from most recent CCIIO DIY entry\nin a tidy format. These + support the Centers for Medicare and Medicaid\nServices' (CMS) risk adjustment + Do-It-Yourself (DIY) process, which allows\nhealth insurance issuers to calculate + member risk profiles under the Health\nand Human Services-Hierarchical Condition + Categories (HHS-HCC) regression\nmodel. This regression model is used to calculate + risk adjustment transfers.\nRisk adjustment is a selection mitigation program + implemented under the\nPatient Protection and Affordable Care Act (ACA or Obamacare) + in the USA.\nUnder the ACA, health insurance issuers submit claims data to CMS\tin + order\nfor CMS to calculate a risk score under the HHS-HCC regression model.\nHowever, + CMS does not inform issuers of their average risk score until after\nthe data + submission deadline. These data sets can be used by issuers to\ncalculate their + average risk score mid-year. More information about risk\nadjustment and the HHS-HCC + model can be found here:\n." + date_publication: '2021-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edgedata + url_git: '' +edibble: + version: 1.1.1 + title: Encapsulating Elements of Experimental Design + maintainer: Emi Tanaka + description: |- + A system to facilitate designing comparative (and non-comparative) experiments using the + grammar of experimental designs . + An experimental design is treated as an intermediate, mutable object that is + built progressively by fundamental experimental components like units, treatments, and their relation. + The system aids in experimental planning, management and workflow. + date_publication: '2024-05-06' + bug_reports: https://github.com/emitanaka/edibble/issues + url: https://edibble.emitanaka.org/ + url_cran: https://CRAN.R-project.org/package=edibble + url_git: https://github.com/emitanaka/edibble +ediblecity: + version: 0.2.1 + title: Modeling Urban Agriculture at City Scale + maintainer: Josep Pueyo-Ros + description: The purpose of this package is to estimate the potential of urban agriculture + to contribute to addressing several urban challenges at the city-scale. Within + this aim, we selected 8 indicators directly related to one or several urban challenges. + Also, a function is provided to compute new scenarios of urban agriculture. Methods + are described by Pueyo-Ros, Comas & Corominas (2023) . + date_publication: '2023-07-16' + bug_reports: https://github.com/icra/ediblecity/issues + url: https://icra.github.io/ediblecity/ + url_cran: https://CRAN.R-project.org/package=ediblecity + url_git: https://github.com/icra/ediblecity +edina: + version: 0.1.1 + title: |- + Bayesian Estimation of an Exploratory Deterministic Input, Noisy + and Gate Model + maintainer: James Joseph Balamuta + description: |- + Perform a Bayesian estimation of the exploratory + deterministic input, noisy and gate (EDINA) + cognitive diagnostic model described by Chen et al. (2018) + . + date_publication: '2020-03-25' + bug_reports: https://github.com/tmsalab/edina/issues + url: '' + url_cran: https://CRAN.R-project.org/package=edina + url_git: https://github.com/tmsalab/edina +EDISON: + version: 1.1.1 + title: Network Reconstruction and Changepoint Detection + maintainer: Frank Dondelinger + description: |- + Package EDISON (Estimation of Directed Interactions from + Sequences Of Non-homogeneous gene expression) runs an MCMC + simulation to reconstruct networks from time series data, using + a non-homogeneous, time-varying dynamic Bayesian network. + Networks segments and changepoints are inferred concurrently, + and information sharing priors provide a reduction of the + inference uncertainty. + date_publication: '2016-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EDISON + url_git: '' +editbl: + version: 1.1.0 + title: |- + 'DT' Extension for CRUD (Create, Read, Update, Delete) + Applications in 'shiny' + maintainer: Jasper Schelfhout + description: The core of this package is a function eDT() which enhances DT::datatable() + such that it can be used to interactively modify data in 'shiny'. By the use of + generic 'dplyr' methods it supports many types of data storage, with relational + databases ('dbplyr') being the main use case. + date_publication: '2025-01-31' + bug_reports: https://github.com/openanalytics/editbl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=editbl + url_git: https://github.com/openanalytics/editbl +editData: + version: 0.1.8 + title: '''RStudio'' Addin for Editing a ''data.frame''' + maintainer: Keon-Woong Moon + description: |- + An 'RStudio' addin for editing a 'data.frame' or a 'tibble'. You can delete, add or update a 'data.frame' + without coding. You can get resultant data as a 'data.frame'. In the package, modularized 'shiny' app codes are provided. + These modules are intended for reuse across applications. + date_publication: '2021-04-02' + bug_reports: https://github.com/cardiomoon/editData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=editData + url_git: https://github.com/cardiomoon/editData +eDITH: + version: 1.0.0 + title: Model Transport of Environmental DNA in River Networks + maintainer: Luca Carraro + description: |- + Runs the eDITH (environmental DNA Integrating Transport + and Hydrology) model, which implements a mass balance of environmental DNA (eDNA) + transport at a river network scale coupled with a species distribution model + to obtain maps of species distribution. eDITH can work with both eDNA concentration + (e.g., obtained via quantitative polymerase chain reaction) or metabarcoding + (read count) data. Parameter estimation can be performed via Bayesian techniques + (via the 'BayesianTools' package) or optimization algorithms. An interface to the + 'DHARMa' package for posterior predictive checks is provided. See Carraro and + Altermatt (2024) for a package introduction; + Carraro et al. (2018) and Carraro et al. (2020) + for methodological details. + date_publication: '2024-05-24' + bug_reports: https://github.com/lucarraro/eDITH/issues + url: https://lucarraro.github.io/eDITH/ + url_cran: https://CRAN.R-project.org/package=eDITH + url_git: https://github.com/lucarraro/eDITH +editrules: + version: 2.9.5 + title: Parsing, Applying, and Manipulating Data Cleaning Rules + maintainer: Edwin de Jonge + description: |- + Please note: active development has moved to packages 'validate' + and 'errorlocate'. Facilitates reading and manipulating (multivariate) data + restrictions (edit rules) on numerical and categorical data. Rules can be + defined with common R syntax and parsed to an internal (matrix-like format). + Rules can be manipulated with variable elimination and value substitution + methods, allowing for feasibility checks and more. Data can be tested against + the rules and erroneous fields can be found based on Fellegi and Holt's + generalized principle. Rules dependencies can be visualized with using the + 'igraph' package. + date_publication: '2024-05-04' + bug_reports: https://github.com/data-cleaning/editrules/issues + url: '' + url_cran: https://CRAN.R-project.org/package=editrules + url_git: https://github.com/data-cleaning/editrules +EDIutils: + version: 1.0.3 + title: An API Client for the Environmental Data Initiative Repository + maintainer: Colin Smith + description: A client for the Environmental Data Initiative repository REST API. + The 'EDI' data repository is for + publication and reuse of ecological data with emphasis on metadata accuracy and + completeness. It is built upon the 'PASTA+' software stack + and was developed in collaboration with the US 'LTER' Network . + 'EDIutils' includes functions to search and access existing data, evaluate and + upload new data, and assist other data management tasks common to repository users. + date_publication: '2023-10-10' + bug_reports: https://github.com/ropensci/EDIutils/issues + url: https://docs.ropensci.org/EDIutils/ + url_cran: https://CRAN.R-project.org/package=EDIutils + url_git: https://github.com/ropensci/EDIutils +edl: + version: '1.1' + title: |- + Toolbox for Error-Driven Learning Simulations with Two-Layer + Networks + maintainer: Jacolien van Rij + description: 'Error-driven learning (based on the Widrow & Hoff (1960) + learning rule, and essentially the same as Rescorla-Wagner''s learning equations + (Rescorla & Wagner, 1972, ISBN: 0390718017), which are also at the core of Naive + Discrimination Learning, (Baayen et al, 2011, ) can be used + to explain bottom-up human learning (Hoppe et al, ), + but is also at the core of artificial neural networks applications in the form + of the Delta rule. This package provides a set of functions for building small-scale + simulations to investigate the dynamics of error-driven learning and it''s interaction + with the structure of the input. For modeling error-driven learning using the + Rescorla-Wagner equations the package ''ndl'' (Baayen et al, 2011, ) + is available on CRAN at . However, the + package currently only allows tracing of a cue-outcome combination, rather than + returning the learned networks. To fill this gap, we implemented a new package + with a few functions that facilitate inspection of the networks for small error + driven learning simulations. Note that our functions are not optimized for training + large data sets (no parallel processing), as they are intended for small scale + simulations and course examples. (Consider the python implementation ''pyndl'' + for that purpose.)' + date_publication: '2021-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edl + url_git: '' +edlibR: + version: 1.0.2 + title: |- + R Integration for Edlib, the C/C++ Library for Exact Pairwise + Sequence Alignment using Edit (Levenshtein) Distance + maintainer: Evan Biederstedt + description: 'Bindings to edlib, a lightweight performant C/C++ library for exact + pairwise sequence alignment using edit distance (Levenshtein distance). The algorithm + computes the optimal alignment path, but also can be used to find only the start + and/or end of the alignment path for convenience. Edlib was designed to be ultrafast + and require little memory, with the capability to handle very large sequences. + Three alignment methods are supported: global (Needleman-Wunsch), infix (Hybrid + Wunsch), and prefix (Semi-Hybrid Wunsch). The original C/C++ library is described + in "Edlib: a C/C++ library for fast, exact sequence alignment using edit distance", + M. Šošić, M. Šikić, .' + date_publication: '2024-02-23' + bug_reports: https://github.com/evanbiederstedt/edlibR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=edlibR + url_git: https://github.com/evanbiederstedt/edlibR +eDMA: + version: 1.5-3 + title: Dynamic Model Averaging with Grid Search + maintainer: Leopoldo Catania + description: Perform dynamic model averaging with grid search as in Dangl and Halling + (2012) using parallel computing. + date_publication: '2018-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eDMA + url_git: '' +edmdata: + version: 1.3.0 + title: Data Sets for Psychometric Modeling + maintainer: James Joseph Balamuta + description: |- + Collection of data sets from various assessments that can be used to + evaluate psychometric models. These data sets have been analyzed in the + following papers that introduced new methodology as part of the application section: + Jimenez, A., Balamuta, J. J., & Culpepper, S. A. (2023) , + Culpepper, S. A., & Balamuta, J. J. (2021) , + Yinghan Chen et al. (2021) , + Yinyin Chen et al. (2020) , + Culpepper, S. A. (2019a) , + Culpepper, S. A. (2019b) , + Culpepper, S. A., & Chen, Y. (2019) , + Culpepper, S. A., & Balamuta, J. J. (2017) , + and Culpepper, S. A. (2015) . + date_publication: '2024-10-02' + bug_reports: https://github.com/tmsalab/edmdata/issues + url: https://tmsalab.github.io/edmdata/ + url_cran: https://CRAN.R-project.org/package=edmdata + url_git: https://github.com/tmsalab/edmdata/ +eDNAjoint: + version: 0.3.1 + title: |- + Joint Modeling of Traditional and Environmental DNA Survey Data + in a Bayesian Framework + maintainer: Abigail G. Keller + description: 'Models integrate environmental DNA (eDNA) detection data and traditional + survey data to jointly estimate species catch rate (see package vignette: ). + Models can be used with count data via traditional survey methods (i.e., trapping, + electrofishing, visual) and replicated eDNA detection/nondetection data via polymerase + chain reaction (i.e., PCR or qPCR) from multiple survey locations. Estimated parameters + include probability of a false positive eDNA detection, a site-level covariates + that scale the sensitivity of eDNA surveys relative to traditional surveys, and + catchability coefficients for traditional gear types. Models are implemented with + a Bayesian framework (Markov chain Monte Carlo) using the ''Stan'' probabilistic + programming language.' + date_publication: '2025-01-25' + bug_reports: https://github.com/ropensci/eDNAjoint/issues + url: https://docs.ropensci.org/eDNAjoint/ + url_cran: https://CRAN.R-project.org/package=eDNAjoint + url_git: https://github.com/ropensci/eDNAjoint +EDNE.EQ: + version: '1.0' + title: Implements the EDNE-Test for Equivalence + maintainer: Thomas Hoffelder + description: |- + Package implements the EDNE-test for equivalence + according to Hoffelder et al. (2015) . + "EDNE" abbreviates "Euclidean Distance between the + Non-standardized Expected values". + The EDNE-test for equivalence is a multivariate two-sample equivalence test. + Distance measure of the test is the Euclidean distance. + The test is an asymptotically valid test for the family of distributions + fulfilling the assumptions of the multivariate central limit theorem + (see Hoffelder et al.,2015). + The function EDNE.EQ() implements the EDNE-test for equivalence + according to Hoffelder et al. (2015). + The function EDNE.EQ.dissolution.profiles() implements a variant + of the EDNE-test for equivalence analyses of dissolution profiles + (see Suarez-Sharp et al.,2020 ). + EDNE.EQ.dissolution.profiles() checks whether the quadratic mean of the + differences of the expected values of both dissolution profile populations + is statistically significantly smaller than 10 [\% of label claim]. + The current regulatory standard approach for equivalence analyses of + dissolution profiles is the similarity factor f2. + The statistical hypotheses underlying EDNE.EQ.dissolution.profiles() + coincide with the hypotheses for f2 (see Hoffelder et al.,2015, + Suarez-Sharp et al., 2020). + date_publication: '2020-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EDNE.EQ + url_git: '' +EDOIF: + version: 0.1.3 + title: Empirical Distribution Ordering Inference Framework (EDOIF) + maintainer: Chainarong Amornbunchornvej + description: A non-parametric framework based on estimation statistics principle. + Its main purpose is to infer orders of empirical distributions from different + categories based on a probability of finding a value in one distribution that + is greater than an expectation of another distribution. Given a set of ordered-pair + of real-category values the framework is capable of 1) inferring orders of domination of categories and representing orders in the + form of a graph; 2) estimating magnitude of difference between a pair of + categories in forms of mean-difference confidence intervals; and 3) visualizing domination orders and magnitudes of difference + of categories. The publication of this package is at Chainarong Amornbunchornvej, + Navaporn Surasvadi, Anon Plangprasopchok, and Suttipong Thajchayapong (2020) . + date_publication: '2021-03-28' + bug_reports: https://github.com/DarkEyes/EDOIF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EDOIF + url_git: https://github.com/DarkEyes/EDOIF +EDOtrans: + version: 0.2.5 + title: Euclidean Distance-Optimized Data Transformation + maintainer: Jorn Lotsch + description: A data transformation method which takes into account the special property + of scale non-invariance with a breakpoint at 1 of the Euclidean distance. + date_publication: '2024-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EDOtrans + url_git: '' +edstan: + version: 1.0.6 + title: Stan Models for Item Response Theory + maintainer: Daniel C. Furr + description: |- + Provides convenience functions and pre-programmed Stan models + related to item response theory. Its purpose is to make fitting + common item response theory models using Stan easy. + date_publication: '2017-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=edstan + url_git: '' +EdSurvey: + version: 4.0.7 + title: Analysis of NCES Education Survey and Assessment Data + maintainer: Paul Bailey + description: 'Read in and analyze functions for education survey and assessment + data from the National Center for Education Statistics (NCES) , + including National Assessment of Educational Progress (NAEP) data + and data from the International Assessment Database: Organisation for Economic + Co-operation and Development (OECD) , including Programme + for International Student Assessment (PISA), Teaching and Learning International + Survey (TALIS), Programme for the International Assessment of Adult Competencies + (PIAAC), and International Association for the Evaluation of Educational Achievement + (IEA) , including Trends in International Mathematics and + Science Study (TIMSS), TIMSS Advanced, Progress in International Reading Literacy + Study (PIRLS), International Civic and Citizenship Study (ICCS), International + Computer and Information Literacy Study (ICILS), and Civic Education Study (CivEd).' + date_publication: '2024-06-27' + bug_reports: https://github.com/American-Institutes-for-Research/EdSurvey/issues + url: https://www.air.org/project/nces-data-r-project-edsurvey + url_cran: https://CRAN.R-project.org/package=EdSurvey + url_git: '' +educationdata: + version: 0.1.3 + title: |- + Retrieve Records from the Urban Institute's Education Data + Portal API + maintainer: Erika Tyagi + description: |- + Allows R users to retrieve and parse data from the Urban + Institute's Education Data API into a + 'data.frame' for analysis. + date_publication: '2022-09-29' + bug_reports: https://github.com/UrbanInstitute/education-data-package-r/issues + url: https://urbaninstitute.github.io/education-data-package-r/ + url_cran: https://CRAN.R-project.org/package=educationdata + url_git: '' +educationR: + version: 0.1.0 + title: A Comprehensive Collection of Educational Datasets + maintainer: Renzo Caceres Rossi + description: |- + Provides a comprehensive collection of datasets related to education, + covering topics such as student performance, learning methods, test scores, + absenteeism, and other educational metrics. This package serves as a resource + for educational researchers, data analysts, and statisticians to explore and + analyze data in the field of education. + date_publication: '2024-12-05' + bug_reports: https://github.com/lightbluetitan/educationr/issues + url: https://lightbluetitan.github.io/educationr/ + url_cran: https://CRAN.R-project.org/package=educationR + url_git: https://github.com/lightbluetitan/educationr +educineq: + version: 0.1.0 + title: Compute and Decompose Inequality in Education + maintainer: Vanesa Jorda + description: |- + Easily compute education inequality measures and the distribution + of educational attainments for any group of countries, using the data set + developed in Jorda, V. and Alonso, JM. (2017) . + The package offers the possibility to compute not only the Gini index, but + also generalized entropy measures for different values of the sensitivity + parameter. In particular, the package includes functions to compute the + mean log deviation, which is more sensitive to the bottom part of the + distribution; the Theil’s entropy measure, equally sensitive to all parts + of the distribution; and finally, the GE measure when the sensitivity + parameter is set equal to 2, which gives more weight to differences in + higher education. The decomposition of these measures in the components + between-country and within-country inequality is also provided. Two + graphical tools are also provided, to analyse the evolution of the + distribution of educational attainments: The cumulative distribution + function and the Lorenz curve. + date_publication: '2017-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=educineq + url_git: '' +edwards97: + version: 0.1.1 + title: Langmuir Semi-Empirical Coagulation Model + maintainer: Dewey Dunnington + description: |- + Implements the Edwards (1997) + Langmuir-based semi-empirical coagulation model, which predicts the concentration + of organic carbon remaining in water after treatment with an Al- or Fe-based + coagulant. Data and methods are provided to optimise empirical coefficients. + date_publication: '2022-09-01' + bug_reports: https://github.com/paleolimbot/edwards97/issues + url: https://paleolimbot.github.io/edwards97/ + url_cran: https://CRAN.R-project.org/package=edwards97 + url_git: https://github.com/paleolimbot/edwards97 +EEAaq: + version: 1.0.0 + title: |- + Handle Air Quality Data from the European Environment Agency + Data Portal + maintainer: Paolo Maranzano + description: |- + This software downloads and manages air quality data from the European Environmental Agency (EEA) dataflow (). + See the web page for details on the EEA's Air Quality Download Service. + The package allows dynamically mapping the stations, summarising and time aggregating the measurements and building spatial interpolation maps. + See the web page for further information on EEA activities and history. + Further details, as well as, an extended vignette of the main functions included in the package, are available at the GitHub web page dedicated to the project. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EEAaq + url_git: https://github.com/PaoloMaranzano/EEAaq_R +eefAnalytics: + version: 1.1.5 + title: |- + Robust Analytical Methods for Evaluating Educational + Interventions using Randomised Controlled Trials Designs + maintainer: Germaine Uwimpuhwe + description: Analysing data from evaluations of educational interventions using + a randomised controlled trial design. Various analytical tools to perform sensitivity + analysis using different methods are supported (e.g. frequentist models with bootstrapping + and permutations options, Bayesian models). The included commands can be used + for simple randomised trials, cluster randomised trials and multisite trials. + The methods can also be used more widely beyond education trials. This package + can be used to evaluate other intervention designs using Frequentist and Bayesian + multilevel models. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eefAnalytics + url_git: '' +eegkit: + version: 1.0-4 + title: Toolkit for Electroencephalography Data + maintainer: Nathaniel E. Helwig + description: Analysis and visualization tools for electroencephalography (EEG) data. + Includes functions for (i) plotting EEG data, (ii) filtering EEG data, (iii) smoothing + EEG data; (iv) frequency domain (Fourier) analysis of EEG data, (v) Independent + Component Analysis of EEG data, and (vi) simulating event-related potential EEG + data. + date_publication: '2018-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eegkit + url_git: '' +eegkitdata: + version: '1.1' + title: Electroencephalography Toolkit Datasets + maintainer: Nathaniel E. Helwig + description: Contains the example EEG data used in the package eegkit. Also contains + code for easily creating larger EEG datasets from the EEG Database on the UCI + Machine Learning Repository. + date_publication: '2022-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eegkitdata + url_git: '' +EEM: + version: 1.1.1 + title: |- + Read and Preprocess Fluorescence Excitation-Emission Matrix + (EEM) Data + maintainer: Vipavee Trivittayasil + description: Read raw EEM data and prepares them for further analysis. + date_publication: '2016-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EEM + url_git: https://github.com/chengvt/EEM +eemdARIMA: + version: 0.1.0 + title: EEMD Based Auto Regressive Integrated Moving Average Model + maintainer: Rajeev Ranjan Kumar + description: Forecasting time series with different decomposition based ARIMA models. + For method details see Yu L, Wang S, Lai KK (2008). . + date_publication: '2022-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eemdARIMA + url_git: '' +EEMDelm: + version: 0.1.1 + title: |- + Ensemble Empirical Mode Decomposition and Its Variant Based ELM + Model + maintainer: Girish Kumar Jha + description: Forecasting univariate time series with different decomposition based + Extreme Learning Machine models. For method details see Yu L, Wang S, Lai KK (2008). + , Parida M, Behera MK, Nayak N (2018). . + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EEMDelm + url_git: '' +EEMDlstm: + version: 0.1.0 + title: EEMD Based LSTM Model for Time Series Forecasting + maintainer: Kapil Choudhary + description: Forecasting univariate time series with ensemble empirical mode decomposition + (EEMD) with long short-term memory (LSTM). For method details see Jaiswal, R. + et al. (2022). . + date_publication: '2022-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EEMDlstm + url_git: '' +EEMDSVR: + version: 0.1.0 + title: |- + Ensemble Empirical Mode Decomposition and Its Variant Based + Support Vector Regression Model + maintainer: Pankaj Das + description: Application of Ensemble Empirical Mode Decomposition and its variant + based Support Vector regression model for univariate time series forecasting. + For method details see Das (2020).. + date_publication: '2021-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EEMDSVR + url_git: '' +eemdTDNN: + version: 0.1.0 + title: EEMD and Its Variant Based Time Delay Neural Network Model + maintainer: Kapil Choudhary + description: Forecasting univariate time series with different decomposition based + time delay neural network models. For method details see Yu L, Wang S, Lai KK + (2008). . + date_publication: '2021-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eemdTDNN + url_git: '' +EEML: + version: 0.1.1 + title: Ensemble Explainable Machine Learning Models + maintainer: Dr. Ranjit Kumar Paul + description: We introduced a novel ensemble-based explainable machine learning model + using Model Confidence Set (MCS) and two stage Technique for Order of Preference + by Similarity to Ideal Solution (TOPSIS) algorithm. The model combined the predictive + capabilities of different machine-learning models and integrates the interpretability + of explainability methods. To develop the proposed algorithm, a two-stage Technique + for Order of Preference by Similarity to Ideal Solution (TOPSIS) framework was + employed. The package has been developed using the algorithm of Paul et al. (2023) + and Yeasin and Paul (2024) . + date_publication: '2024-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EEML + url_git: '' +eemR: + version: 1.0.1 + title: |- + Tools for Pre-Processing Emission-Excitation-Matrix (EEM) + Fluorescence Data + maintainer: Philippe Massicotte + description: |- + Provides various tools for preprocessing Emission-Excitation-Matrix (EEM) for Parallel Factor Analysis (PARAFAC). Different + methods are also provided to calculate common metrics such as humification index and fluorescence index. + date_publication: '2019-06-26' + bug_reports: https://github.com/PMassicotte/eemR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eemR + url_git: https://github.com/PMassicotte/eemR +eeptools: + version: 1.2.5 + title: Convenience Functions for Education Data + maintainer: Jared E. Knowles + description: |- + Collection of convenience functions to make working with + administrative records easier and more consistent. Includes functions to + clean strings, and identify cut points. Also includes three example data + sets of administrative education records for learning how to process records + with errors. + date_publication: '2023-06-01' + bug_reports: https://github.com/jknowles/eeptools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eeptools + url_git: https://github.com/jknowles/eeptools +eesim: + version: 0.1.0 + title: Simulate and Evaluate Time Series for Environmental Epidemiology + maintainer: Brooke Anderson + description: |- + Provides functions to create simulated time series of environmental + exposures (e.g., temperature, air pollution) and health outcomes for use in + power analysis and simulation studies in environmental epidemiology. This + package also provides functions to evaluate the results of simulation studies + based on these simulated time series. This work was supported by a grant + from the National Institute of Environmental Health Sciences (R00ES022631) and + a fellowship from the Colorado State University Programs for Research and + Scholarly Excellence. + date_publication: '2017-06-03' + bug_reports: http://github.com/sakoehler7/eesim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eesim + url_git: http://github.com/sakoehler7/eesim +EESPCA: + version: 0.7.0 + title: |- + Eigenvectors from Eigenvalues Sparse Principal Component + Analysis (EESPCA) + maintainer: H. Robert Frost + description: |- + Contains logic for computing sparse principal components via the EESPCA method, + which is based on an approximation of the eigenvector/eigenvalue identity. + Includes logic to support execution of the TPower and rifle sparse PCA methods, + as well as logic to estimate the sparsity parameters used by EESPCA, TPower and rifle + via cross-validation to minimize the out-of-sample reconstruction error. + H. Robert Frost (2021) . + date_publication: '2022-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EESPCA + url_git: '' +ef: + version: 1.2.0 + title: Modelling Framework for the Estimation of Salmonid Abundance + maintainer: Colin Millar + description: |- + A set of functions to estimate capture probabilities and + densities from multipass pass removal data. + date_publication: '2020-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ef + url_git: '' +EFA.dimensions: + version: 0.1.8.4 + title: |- + Exploratory Factor Analysis Functions for Assessing + Dimensionality + maintainer: Brian P. O'Connor + description: |- + Functions for eleven procedures for determining the number of + factors, including functions for parallel analysis and the minimum average partial + test. There are also functions for conducting principal components analysis, principal + axis factor analysis, maximum likelihood factor analysis, image factor analysis, + and extension factor analysis, all of which can take raw data or correlation matrices + as input and with options for conducting the analyses using Pearson correlations, + Kendall correlations, Spearman correlations, gamma correlations, or polychoric + correlations. Varimax rotation, promax rotation, and Procrustes rotations can be + performed. Additional functions focus on the factorability of a correlation matrix, + the congruences between factors from different datasets, the assessment of local + independence, the assessment of factor solution complexity, and internal consistency. + Auerswald & Moshagen (2019, ISSN:1939-1463); + Field, Miles, & Field (2012, ISBN:978-1-4462-0045-2); + Mulaik (2010, ISBN:978-1-4200-9981-2); + O'Connor (2000, ); + O'Connor (2001, ISSN:0146-6216). + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EFA.dimensions + url_git: '' +EFA.MRFA: + version: 1.1.2 + title: Dimensionality Assessment Using Minimum Rank Factor Analysis + maintainer: David Navarro-Gonzalez + description: |- + Performs parallel analysis (Timmerman & Lorenzo-Seva, 2011 + ) and hull method (Lorenzo-Seva, Timmerman, & Kiers, + 2011 ) for assessing the dimensionality + of a set of variables using minimum rank factor analysis (see ten Berge & + Kiers, 1991 for more information). The package + also includes the option to compute minimum rank factor analysis by + itself, as well as the greater lower bound calculation. + date_publication: '2021-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EFA.MRFA + url_git: '' +EFAfactors: + version: 1.2.1 + title: Determining the Number of Factors in Exploratory Factor Analysis + maintainer: Haijiang Qin + description: Provides a collection of standard factor retention methods in Exploratory + Factor Analysis (EFA), making it easier to determine the number of factors. Traditional + methods such as the scree plot by Cattell (1966) , + Kaiser-Guttman Criterion (KGC) by Guttman (1954) and + Kaiser (1960) , and flexible Parallel Analysis + (PA) by Horn (1965) based on eigenvalues form PCA or + EFA are readily available. This package also implements several newer methods, + such as the Empirical Kaiser Criterion (EKC) by Braeken and van Assen (2017) , + Comparison Data (CD) by Ruscio and Roche (2012) , and Hull + method by Lorenzo-Seva et al. (2011) , as well + as some AI-based methods like Comparison Data Forest (CDF) by Goretzko and Ruscio + (2024) and Factor Forest (FF) by Goretzko and + Buhner (2020) . Additionally, it includes a deep neural + network (DNN) trained on large-scale datasets that can efficiently and reliably + determine the number of factors. + date_publication: '2025-02-17' + bug_reports: '' + url: https://haijiangqin.com/EFAfactors/ + url_cran: https://CRAN.R-project.org/package=EFAfactors + url_git: '' +EFAtools: + version: 0.4.5 + title: |- + Fast and Flexible Implementations of Exploratory Factor Analysis + Tools + maintainer: Markus Steiner + description: Provides functions to perform exploratory factor analysis (EFA) procedures + and compare their solutions. The goal is to provide state-of-the-art factor retention + methods and a high degree of flexibility in the EFA procedures. This way, for + example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, + functions for Schmid-Leiman transformation and the computation of omegas are provided. + To speed up the analyses, some of the iterative procedures, like principal axis + factoring (PAF), are implemented in C++. + date_publication: '2024-12-22' + bug_reports: https://github.com/mdsteiner/EFAtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EFAtools + url_git: https://github.com/mdsteiner/EFAtools +EFAutilities: + version: 2.1.3 + title: Utility Functions for Exploratory Factor Analysis + maintainer: Guangjian Zhang + description: A number of utility function for exploratory factor analysis are included + in this package. In particular, it computes standard errors for parameter estimates + and factor correlations under a variety of conditions. + date_publication: '2023-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EFAutilities + url_git: '' +efdm: + version: 0.2.1 + title: |- + Simulate Forest Resources with the European Forestry Dynamics + Model + maintainer: Mikko Kuronen + description: |- + An implementation of European Forestry Dynamics Model (EFDM) and + an estimation algorithm for the transition probabilities. + The EFDM is a large-scale forest model that simulates the development of + the forest and estimates volume of wood harvested for any given forested + area. This estimate can be broken down by, for example, species, site + quality, management regime and ownership category. + See Packalen et al. (2015) . + date_publication: '2023-08-17' + bug_reports: https://github.com/mikkoku/efdm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=efdm + url_git: https://github.com/mikkoku/efdm +EFDR: + version: '1.3' + title: |- + Wavelet-Based Enhanced FDR for Detecting Signals from Complete + or Incomplete Spatially Aggregated Data + maintainer: Andrew Zammit-Mangion + description: |- + Enhanced False Discovery Rate (EFDR) is a tool to detect anomalies + in an image. The image is first transformed into the wavelet domain in + order to decorrelate any noise components, following which the coefficients + at each resolution are standardised. Statistical tests (in a multiple + hypothesis testing setting) are then carried out to find the anomalies. The + power of EFDR exceeds that of standard FDR, which would carry out tests on + every wavelet coefficient: EFDR choose which wavelets to test based on a + criterion described in Shen et al. (2002). The package also provides + elementary tools to interpolate spatially irregular data onto a grid of the + required size. The work is based on Shen, X., Huang, H.-C., and Cressie, N. + 'Nonparametric hypothesis testing for a spatial signal.' Journal of the + American Statistical Association 97.460 (2002): 1122-1140. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EFDR + url_git: https://github.com/andrewzm/EFDR/ +eff2: + version: 1.0.2 + title: Efficient Least Squares for Total Causal Effects + maintainer: Richard Guo + description: |- + Estimate a total causal effect from observational data under + linearity and causal sufficiency. The observational data is supposed to + be generated from a linear structural equation model (SEM) with independent + and additive noise. The underlying causal DAG associated the SEM is required + to be known up to a maximally oriented partially directed graph (MPDAG), + which is a general class of graphs consisting of both directed and + undirected edges, including CPDAGs (i.e., essential graphs) and DAGs. Such + graphs are usually obtained with structure learning algorithms with added + background knowledge. The program is able to estimate every identified + effect, including single and multiple treatment variables. Moreover, the + resulting estimate has the minimal asymptotic covariance (and hence + shortest confidence intervals) among all estimators that are based on the + sample covariance. + date_publication: '2024-01-26' + bug_reports: https://github.com/richardkwo/eff2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eff2 + url_git: https://github.com/richardkwo/eff2 +effClust: + version: 0.8.0 + title: Calculate Effective Number of Clusters for a Linear Model + maintainer: Joe Ritter + description: Calculates the (approximate) effective number of clusters for a regression + model, as described in Carter, Schnepel, and Steigerwald (2017) . The + effective number of clusters is a statistic to assess the reliability of asymptotic + inference when sampling or treatment assignment is clustered. Methods are implemented + for stats::lm(), plm::plm(), and fixest::feols(). There is also a formula method. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=effClust + url_git: '' +EffectLiteR: + version: 0.5-1 + title: Average and Conditional Effects + maintainer: Axel Mayer + description: |- + Use structural equation modeling to estimate average and + conditional effects of a treatment variable on an outcome variable, taking into + account multiple continuous and categorical covariates. + date_publication: '2024-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EffectLiteR + url_git: https://github.com/amayer2010/EffectLiteR +effectplots: + version: 0.2.1 + title: Effect Plots + maintainer: Michael Mayer + description: |- + High-performance implementation of various effect plots + useful for regression and probabilistic classification tasks. The + package includes partial dependence plots (Friedman, 2021, + ), accumulated local effect plots and + M-plots (both from Apley and Zhu, 2016, ), as + well as plots that describe the statistical associations between model + response and features. It supports visualizations with either + 'ggplot2' or 'plotly', and is compatible with most models, including + 'Tidymodels', models wrapped in 'DALEX' explainers, or models with + case weights. + date_publication: '2025-01-11' + bug_reports: https://github.com/mayer79/effectplots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=effectplots + url_git: https://github.com/mayer79/effectplots +effectR: + version: 1.0.2 + title: Predicts Oomycete Effectors + maintainer: Javier Tabima + description: Predicts cytoplasmic effector proteins using genomic data by searching + for motifs of interest using regular expression searches and hidden Markov models + (HMM) based in Haas et al. (2009) . + date_publication: '2018-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=effectR + url_git: '' +effects: + version: 4.2-2 + title: Effect Displays for Linear, Generalized Linear, and Other Models + maintainer: John Fox + description: |2- + + Graphical and tabular effect displays, e.g., of interactions, for + various statistical models with linear predictors. + date_publication: '2022-07-13' + bug_reports: '' + url: https://socialsciences.mcmaster.ca/jfox/ + url_cran: https://CRAN.R-project.org/package=effects + url_git: '' +effectsize: + version: 1.0.0 + title: Indices of Effect Size + maintainer: Mattan S. Ben-Shachar + description: |- + Provide utilities to work with indices of effect size for a wide + variety of models and hypothesis tests (see list of supported models using + the function 'insight::supported_models()'), allowing computation of and + conversion between indices such as Cohen's d, r, odds, etc. + References: Ben-Shachar et al. (2020) . + date_publication: '2024-12-10' + bug_reports: https://github.com/easystats/effectsize/issues/ + url: https://easystats.github.io/effectsize/ + url_cran: https://CRAN.R-project.org/package=effectsize + url_git: '' +effectsizescr: + version: 0.1.0 + title: Indices for Single-Case Research + maintainer: Isabella Giammusso + description: Parametric and nonparametric statistics for single-case design. Regarding + nonparametric statistics, the index suggested by Parker, Vannest, Davis and Sauber + (2011) was included. It combines both nonoverlap + and trend to estimate the effect size of a treatment in a single case design. + date_publication: '2018-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=effectsizescr + url_git: '' +EffectStars: + version: 1.9-1 + title: Visualization of Categorical Response Models + maintainer: Gunther Schauberger + description: 'Notice: The package EffectStars2 provides a more up-to-date implementation + of effect stars! EffectStars provides functions to visualize regression models + with categorical response as proposed by Tutz and Schauberger (2013) . + The effects of the variables are plotted with star plots in order to allow for + an optical impression of the fitted model.' + date_publication: '2019-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EffectStars + url_git: '' +EffectStars2: + version: 0.1-3 + title: Effect Stars + maintainer: Gunther Schauberger + description: Provides functions for the method of effect stars as proposed by Tutz + and Schauberger (2013) . Effect stars can be + used to visualize estimates of parameters corresponding to different groups, for + example in multinomial logit models. Beside the main function 'effectstars' there + exist methods for special objects, for example for 'vglm' objects from the 'VGAM' + package. + date_publication: '2019-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EffectStars2 + url_git: '' +EffectTreat: + version: '1.1' + title: Prediction of Therapeutic Success + maintainer: Wim Van der Elst + description: In personalized medicine, one wants to know, for a given patient and + his or her outcome for a predictor (pre-treatment variable), how likely it is + that a treatment will be more beneficial than an alternative treatment. This package + allows for the quantification of the predictive causal association (i.e., the + association between the predictor variable and the individual causal effect of + the treatment) and related metrics. Part of this software has been developed using + funding provided from the European Union's 7th Framework Programme for research, + technological development and demonstration under Grant Agreement no 602552. + date_publication: '2020-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EffectTreat + url_git: '' +EfficientMaxEigenpair: + version: 0.1.4 + title: Efficient Initials for Computing the Maximal Eigenpair + maintainer: Xiao-Jun Mao + description: |- + An implementation for using efficient initials to compute the + maximal eigenpair in R. It provides three algorithms to find the efficient + initials under two cases: the tridiagonal matrix case and the general matrix + case. Besides, it also provides two algorithms for the next to the maximal eigenpair under + these two cases. + date_publication: '2017-10-23' + bug_reports: http://github.com/mxjki/EfficientMaxEigenpair/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EfficientMaxEigenpair + url_git: http://github.com/mxjki/EfficientMaxEigenpair +efflog: + version: '1.0' + title: The Causal Effects for a Causal Loglinear Model + maintainer: Gloria Gheno + description: Fitting a causal loglinear model and calculating the causal effects + for a causal loglinear model with the multiplicative interaction or without the + multiplicative interaction, obtaining the natural direct, indirect and the total + effect. It calculates also the cell effect, which is a new interaction effect. + date_publication: '2015-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=efflog + url_git: '' +effsize: + version: 0.8.1 + title: Efficient Effect Size Computation + maintainer: Marco Torchiano + description: |- + A collection of functions to compute the standardized + effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha-Delaney A). + The computation algorithms have been optimized to allow efficient computation even + with very large data sets. + date_publication: '2020-10-05' + bug_reports: https://github.com/mtorchiano/effsize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=effsize + url_git: https://github.com/mtorchiano/effsize/ +eFRED: + version: 0.1.0 + title: Fetch Data from the Federal Reserve Economic Database + maintainer: Chris Mann + description: |2- + + Interact with the FRED API, , + to fetch observations across economic series; + find information about different economic sources, releases, series, etc.; + conduct searches by series name, attributes, or tags; and determine the + latest updates. Includes functions for creating panels of related variables + with minimal effort and datasets containing data sources, releases, and + popular FRED tags. + date_publication: '2021-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eFRED + url_git: '' +EFS: + version: 1.0.3 + title: Tool for Ensemble Feature Selection + maintainer: Ursula Neumann + description: |- + Provides a function to check the + importance of a feature based on a dependent classification + variable. An ensemble of feature selection methods + is used to determine the normalized importance value of + all features. Combining these methods in one function + (building the cumulative importance values) provides a + stable feature selection tool. This selection + can also be viewed in a barplot using the barplot_fs() function + and proved using the evaluation function efs_eval(). + date_publication: '2017-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EFS + url_git: '' +ega: + version: 2.0.0 + title: Error Grid Analysis + maintainer: Daniel Schmolze + description: |- + Functions for assigning Clarke or Parkes (Consensus) error grid + zones to blood glucose values, and for plotting both types of error grids + in both mg/mL and mmol/L units. + date_publication: '2017-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ega + url_git: '' +EGAnet: + version: 2.1.0 + title: |- + Exploratory Graph Analysis – a Framework for Estimating the + Number of Dimensions in Multivariate Data using Network + Psychometrics + maintainer: Hudson Golino + description: |- + Implements the Exploratory Graph Analysis (EGA) framework for dimensionality + and psychometric assessment. EGA estimates the number of dimensions in + psychological data using network estimation methods and community detection + algorithms. A bootstrap method is provided to assess the stability of dimensions + and items. Fit is evaluated using the Entropy Fit family of indices. Unique + Variable Analysis evaluates the extent to which items are locally dependent (or + redundant). Network loadings provide similar information to factor loadings and + can be used to compute network scores. A bootstrap and permutation approach are + available to assess configural and metric invariance. Hierarchical structures + can be detected using Hierarchical EGA. Time series and intensive longitudinal + data can be analyzed using Dynamic EGA, supporting individual, group, and + population level assessments. + date_publication: '2024-11-09' + bug_reports: https://github.com/hfgolino/EGAnet/issues + url: https://r-ega.net + url_cran: https://CRAN.R-project.org/package=EGAnet + url_git: '' +egcm: + version: 1.0.13 + title: Engle-Granger Cointegration Models + maintainer: Matthew Clegg + description: |- + An easy-to-use implementation of the Engle-Granger + two-step procedure for identifying pairs of cointegrated series. It is + geared towards the analysis of pairs of securities. Summary and plot + functions are provided, and the package is able to fetch closing prices of + securities from Yahoo. A variety of unit root tests are supported, and + an improved unit root test is included. + date_publication: '2023-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=egcm + url_git: '' +egg: + version: 0.4.5 + title: |- + Extensions for 'ggplot2': Custom Geom, Custom Themes, Plot + Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel + Size + maintainer: Baptiste Auguie + description: Miscellaneous functions to help customise 'ggplot2' objects. High-level + functions are provided to post-process 'ggplot2' layouts and allow alignment between + plot panels, as well as setting panel sizes to fixed values. Other functions include + a custom 'geom', and helper functions to enforce symmetric scales or add tags + to facetted plots. + date_publication: '2019-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=egg + url_git: '' +eggCounts: + version: '2.4' + title: Hierarchical Modelling of Faecal Egg Counts + maintainer: Craig Wang + description: |- + An implementation of Bayesian hierarchical models + for faecal egg count data to assess anthelmintic + efficacy. Bayesian inference is done via MCMC sampling using 'Stan' . + date_publication: '2023-10-14' + bug_reports: '' + url: https://www.math.uzh.ch/pages/eggcount/ + url_cran: https://CRAN.R-project.org/package=eggCounts + url_git: '' +eglhmm: + version: 0.1-3 + title: Extended Generalised Linear Hidden Markov Models + maintainer: Rolf Turner + description: |- + Fits a variety of hidden Markov models, structured + in an extended generalized linear model framework. See + T. Rolf Turner, Murray A. Cameron, and Peter J. Thomson + (1998) , and + Rolf Turner (2008) + and the references cited therein. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eglhmm + url_git: '' +EGM: + version: 0.1.0 + title: Evaluating Cardiac Electrophysiology Signals + maintainer: Anish S. Shah + description: |- + A system for importing electrophysiological signal, based + on the 'Waveform Database (WFDB)' software package, written by Moody et al + 2022 . A wrapper for utilizing 'WFDB' functions for + reading and writing signal data, as well as functions for visualization and + analysis are provided. A stable and broadly compatible class for working + with signal data, supporting the reading in of cardiac electrophysiogical + files such as intracardiac electrograms, is introduced. + date_publication: '2024-05-23' + bug_reports: https://github.com/shah-in-boots/EGM/issues + url: https://shah-in-boots.github.io/EGM/ + url_cran: https://CRAN.R-project.org/package=EGM + url_git: '' +EgoCor: + version: 1.3.2 + title: Simple Presentation of Estimated Exponential Semi-Variograms + maintainer: Julia Dyck + description: |- + User friendly interface based on the R package 'gstat' to fit + exponential parametric models to empirical semi-variograms in order to + model the spatial correlation structure of health data. Geo-located + health outcomes of survey participants may be used to model spatial + effects on health in an ego-centred approach. The package contains a + range of functions to help explore the spatial structure of the data + as well as visualize the fit of exponential models for various + metaparameter combinations with respect to the number of lag intervals + and maximal distance. Furthermore, the outcome of interest can be + adjusted for covariates by fitting a linear regression in a + preliminary step before the semi-variogram fitting process. + date_publication: '2025-01-25' + bug_reports: https://github.com/julia-dyck/EgoCor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EgoCor + url_git: https://github.com/julia-dyck/EgoCor +egor: + version: 1.24.2 + title: Import and Analyse Ego-Centered Network Data + maintainer: Till Krenz + description: |- + Tools for importing, analyzing and visualizing ego-centered + network data. Supports several data formats, including the export formats of + 'EgoNet', 'EgoWeb 2.0' and 'openeddi'. An interactive (shiny) app for the + intuitive visualization of ego-centered networks is provided. Also included + are procedures for creating and visualizing Clustered Graphs + (Lerner 2008 ). + date_publication: '2024-02-02' + bug_reports: https://github.com/tilltnet/egor/issues + url: https://egor.tillt.net/ + url_cran: https://CRAN.R-project.org/package=egor + url_git: https://github.com/tilltnet/egor +EGRET: + version: 3.0.10 + title: Exploration and Graphics for RivEr Trends + maintainer: Laura DeCicco + description: |- + Statistics and graphics for streamflow history, + water quality trends, and the statistical modeling algorithm: Weighted + Regressions on Time, Discharge, and Season (WRTDS). + date_publication: '2024-11-20' + bug_reports: https://github.com/DOI-USGS/EGRET/issues + url: https://pubs.usgs.gov/tm/04/a10/ + url_cran: https://CRAN.R-project.org/package=EGRET + url_git: '' +EGRETci: + version: 2.0.4 + title: Exploration and Graphics for RivEr Trends Confidence Intervals + maintainer: Laura DeCicco + description: |- + Collection of functions to evaluate uncertainty of results from + water quality analysis using the Weighted Regressions on Time Discharge and + Season (WRTDS) method. This package is an add-on to the EGRET package that + performs the WRTDS analysis. The WRTDS modeling + method was initially introduced and discussed in Hirsch et al. (2010) , + and expanded in Hirsch and De Cicco (2015) . The + paper describing the uncertainty and confidence interval calculations + is Hirsch et al. (2015) . + date_publication: '2021-04-13' + bug_reports: https://github.com/USGS-R/EGRETci/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EGRETci + url_git: https://github.com/USGS-R/EGRETci +EGRNi: + version: 0.1.6 + title: Ensemble Gene Regulatory Network Inference + maintainer: Chiranjib Sarkar + description: |- + Gene regulatory network constructed using combined score obtained from + individual network inference method. The combined score measures the significance + of edges in the ensemble network. Fisher's weighted method has been implemented to + combine the outcomes of different methods based on the probability values. + The combined score follows chi-square distribution with 2n degrees of freedom. . + date_publication: '2022-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EGRNi + url_git: '' +eGST: + version: 1.0.0 + title: |- + Leveraging eQTLs to Identify Individual-Level Tissue of Interest + for a Complex Trait + maintainer: Arunabha Majumdar + description: 'Genetic predisposition for complex traits is often manifested through + multiple tissues of interest at different time points in the development. As an + example, the genetic predisposition for obesity could be manifested through inherited + variants that control metabolism through regulation of genes expressed in the + brain and/or through the control of fat storage in the adipose tissue by dysregulation + of genes expressed in adipose tissue. We present a method eGST (eQTL-based genetic + subtyper) that integrates tissue-specific eQTLs with GWAS data for a complex trait + to probabilistically assign a tissue of interest to the phenotype of each individual + in the study. eGST estimates the posterior probability that an individual''s phenotype + can be assigned to a tissue based on individual-level genotype data of tissue-specific + eQTLs and marginal phenotype data in a genome-wide association study (GWAS) cohort. + Under a Bayesian framework of mixture model, eGST employs a maximum a posteriori + (MAP) expectation-maximization (EM) algorithm to estimate the tissue-specific + posterior probability across individuals. Methodology is available from: A Majumdar, + C Giambartolomei, N Cai, MK Freund, T Haldar, T Schwarz, J Flint, B Pasaniuc (2019) + .' + date_publication: '2019-07-02' + bug_reports: https://github.com/ArunabhaCodes/eGST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eGST + url_git: https://github.com/ArunabhaCodes/eGST +eha: + version: 2.11.5 + title: Event History Analysis + maintainer: Göran Broström + description: |- + Parametric proportional hazards fitting with left truncation and + right censoring for common families of distributions, piecewise constant + hazards, and discrete models. Parametric accelerated failure time models + for left truncated and right censored data. Proportional hazards + models for tabular and register data. Sampling of risk sets in Cox + regression, selections in the Lexis diagram, bootstrapping. + Broström (2022) . + date_publication: '2024-09-20' + bug_reports: https://github.com/goranbrostrom/eha/issues + url: https://ehar.se/r/eha/ + url_cran: https://CRAN.R-project.org/package=eha + url_git: '' +ehaGoF: + version: 0.1.1 + title: Calculates Goodness of Fit Statistics + maintainer: Alper Gulbe + description: Calculates 15 different goodness of fit criteria. These are; standard + deviation ratio (SDR), coefficient of variation (CV), relative root mean square + error (RRMSE), Pearson's correlation coefficients (PC), root mean square error + (RMSE), performance index (PI), mean error (ME), global relative approximation + error (RAE), mean relative approximation error (MRAE), mean absolute percentage + error (MAPE), mean absolute deviation (MAD), coefficient of determination (R-squared), + adjusted coefficient of determination (adjusted R-squared), Akaike's information + criterion (AIC), corrected Akaike's information criterion (CAIC), Mean Square + Error (MSE), Bayesian Information Criterion (BIC) and Normalized Mean Square Error + (NMSE). + date_publication: '2020-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ehaGoF + url_git: '' +eHDPrep: + version: 1.3.3 + title: Quality Control and Semantic Enrichment of Datasets + maintainer: Ian Overton + description: |- + A tool for the preparation and enrichment of health datasets for analysis (Toner et al. (2023) ). Provides functionality for assessing data quality and for improving the reliability and machine interpretability of a dataset. + 'eHDPrep' also enables semantic enrichment of a dataset where metavariables are discovered from the relationships between input variables determined from user-provided ontologies. + date_publication: '2023-06-05' + bug_reports: https://github.com/overton-group/eHDPrep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eHDPrep + url_git: https://github.com/overton-group/eHDPrep +ehelp: + version: 1.2.1 + title: Enhanced Help to Enable "Docstring"-Comments in Users Functions + maintainer: Marcelo Ponce + description: By overloading the R help() function, this package allows users to + use "docstring" style comments within their own defined functions. The package + also provides additional functions to mimic the R basic example() function and + the prototyping of packages. + date_publication: '2023-01-06' + bug_reports: https://github.com/mponce0/eHelp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ehelp + url_git: https://github.com/mponce0/eHelp +eHOF: + version: '1.16' + title: Extended HOF (Huisman-Olff-Fresco) Models + maintainer: Florian Jansen + description: Extended and enhanced hierarchical logistic regression models (called + Huisman-Olff-Fresco in biology, see Huisman et al. 1993 Journal of Vegetation + Science ) models. Response curves along one-dimensional + gradients including no response, monotone, plateau, unimodal and bimodal models. + date_publication: '2024-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eHOF + url_git: '' +EHR: + version: 0.4-11 + title: Electronic Health Record (EHR) Data Processing and Analysis Tool + maintainer: Leena Choi + description: |- + Process and analyze electronic health record (EHR) data. The 'EHR' + package provides modules to perform diverse medication-related studies using + data from EHR databases. Especially, the package includes modules to perform + pharmacokinetic/pharmacodynamic (PK/PD) analyses using EHRs, as outlined in + Choi, Beck, McNeer, Weeks, Williams, James, Niu, Abou-Khalil, Birdwell, Roden, + Stein, Bejan, Denny, and Van Driest (2020) . Additional + modules will be added in future. In addition, this package provides various + functions useful to perform Phenome Wide Association Study (PheWAS) to explore + associations between drug exposure and phenotypes obtained from EHR data, as + outlined in Choi, Carroll, Beck, Mosley, Roden, Denny, and Van Driest (2018) + . + date_publication: '2022-12-19' + bug_reports: '' + url: https://choileena.github.io/ + url_cran: https://CRAN.R-project.org/package=EHR + url_git: '' +EHRmuse: + version: 0.0.2.1 + title: |- + Multi-Cohort Selection Bias Correction using IPW and AIPW + Methods + maintainer: Michael Kleinsasser + description: |- + Comprehensive toolkit for addressing selection + bias in binary disease models across diverse non-probability samples, each + with unique selection mechanisms. It utilizes Inverse Probability Weighting + (IPW) and Augmented Inverse Probability Weighting (AIPW) methods to reduce + selection bias effectively in multiple non-probability cohorts by integrating + data from either individual-level or summary-level external sources. The + package also provides a variety of variance estimation techniques. Please + refer to Kundu et al. . + date_publication: '2025-01-28' + bug_reports: https://github.com/Ritoban1/EHRmuse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EHRmuse + url_git: https://github.com/Ritoban1/EHRmuse +EHRtemporalVariability: + version: 1.2.1 + title: Delineating Temporal Dataset Shifts in Electronic Health Records + maintainer: Carlos Sáez + description: |- + Functions to delineate temporal dataset shifts in Electronic Health + Records through the projection and visualization of dissimilarities + among data temporal batches. This is done through the estimation of + data statistical distributions over time and their projection in + non-parametric statistical manifolds, uncovering the patterns of the + data latent temporal variability. 'EHRtemporalVariability' is + particularly suitable for multi-modal data and categorical variables + with a high number of values, common features of biomedical data where + traditional statistical process control or time-series methods may not + be appropriate. 'EHRtemporalVariability' allows you to explore and + identify dataset shifts through visual analytics formats such as + Data Temporal heatmaps and Information Geometric Temporal (IGT) plots. + An additional 'EHRtemporalVariability' Shiny app can be used to load + and explore the package results and even to allow the use of these + functions to those users non-experienced in R coding. (Sáez et al. 2020) + . + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EHRtemporalVariability + url_git: https://github.com/hms-dbmi/EHRtemporalVariability +ehymet: + version: 0.1.1 + title: |- + Methodologies for Functional Data Based on the Epigraph and + Hypograph Indices + maintainer: Belen Pulido + description: |- + Implements methods for functional data analysis based on the epigraph + and hypograph indices. These methods transform + functional datasets, whether in one or multiple dimensions, into multivariate + datasets. The transformation involves applying the epigraph, hypograph, and + their modified versions to both the original curves and their first and second + derivatives. The calculation of these indices is tailored to the dimensionality + of the functional dataset, with special considerations for dependencies between + dimensions in multidimensional cases. This approach extends traditional multivariate + data analysis techniques to the functional data setting. A key application of + this package is the EHyClus method, which enhances clustering analysis for + functional data across one or multiple dimensions using the epigraph and + hypograph indices. See Pulido et al. (2023) + and Pulido et al. (2024) . + date_publication: '2024-11-26' + bug_reports: https://github.com/bpulidob/ehymet/issues + url: https://bpulidob.github.io/ehymet/ + url_cran: https://CRAN.R-project.org/package=ehymet + url_git: https://github.com/bpulidob/ehymet +ei: + version: 1.3-3 + title: Ecological Inference + maintainer: James Honaker + description: 'Software accompanying Gary King''s book: A Solution to the Ecological + Inference Problem. (1997). Princeton University Press. ISBN 978-0691012407.' + date_publication: '2016-11-05' + bug_reports: '' + url: http://gking.harvard.edu/eiR + url_cran: https://CRAN.R-project.org/package=ei + url_git: '' +ei.Datasets: + version: 0.0.1-3 + title: Real Datasets for Assessing Ecological Inference Algorithms + maintainer: Jose M. Pavía + description: |- + Provides more than 550 data sets of actual election results. + Each of the data sets includes aggregate party and candidate outcomes at the voting + unit (polling stations) level and two-way cross-tabulated results at the district level. + These data sets can be used to assess ecological inference algorithms devised + for estimating RxC (global) ecological contingency tables using exclusively aggregate results + from voting units. + Reference: + Pavía (2022) . + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ei.Datasets + url_git: '' +eia: + version: 0.4.2 + title: |- + API Wrapper for U.S. Energy Information Administration ('EIA') + Open Data + maintainer: Matthew Hoff + description: |- + Provides API access to data from the U.S. Energy Information Administration ('EIA') . + Use of the EIA's API and this package requires a free API key obtainable at . + This package includes functions for searching the EIA data directory and returning time series and geoset time series datasets. + Datasets returned by these functions are provided by default in a tidy format, or alternatively, in more raw formats. + It also offers helper functions for working with EIA date strings and time formats and for inspecting different summaries of series metadata. + The package also provides control over API key storage and caching of API request results. + date_publication: '2024-04-15' + bug_reports: https://github.com/ropensci/eia/issues + url: https://docs.ropensci.org/eia/ + url_cran: https://CRAN.R-project.org/package=eia + url_git: https://github.com/ropensci/eia +EIAapi: + version: 0.1.2 + title: Query Data from the 'EIA' API + maintainer: Rami Krispin + description: Provides a function to query and extract data from the 'US Energy Information + Administration' ('EIA') API V2 . The 'EIA' API + provides a variety of information, in a time series format, about the energy sector + in the US. The API is open, free, and requires an access key and registration + at . + date_publication: '2023-08-13' + bug_reports: https://github.com/RamiKrispin/EIAapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EIAapi + url_git: https://github.com/RamiKrispin/EIAapi +eiCircles: + version: 0.0.1-7 + title: |- + Ecological Inference of RxC Tables by Overdispersed-Multinomial + Models + maintainer: Jose M. Pavía + description: |- + Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) from aggregate data using the model described in Forcina et al. (2012), as extension of the model proposed in Brown and Payne (1986). Allows incorporation of covariates. + References: + Brown, P. and Payne, C. (1986). ''Aggregate data, ecological regression and voting transitions''. Journal of the American Statistical Association, 81, 453–460. . + Forcina, A., Gnaldi, M. and Bracalente, B. (2012). ''A revised Brown and Payne model of voting behaviour applied to the 2009 elections in Italy''. Statistical Methods & Applications, 21, 109–119. . + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eiCircles + url_git: '' +eicm: + version: 1.0.3 + title: Explicit Interaction Community Models + maintainer: Miguel Porto + description: |- + Model fitting and species biotic interaction network topology selection for explicit + interaction community models. Explicit interaction community models are an extension of binomial + linear models for joint modelling of species communities, that incorporate both the effects of + species biotic interactions and the effects of missing covariates. Species interactions are modelled + as direct effects of each species on each of the others, and are estimated alongside the effects of + missing covariates, modelled as latent factors. The package includes a penalized maximum likelihood + fitting function, and a genetic algorithm for selecting the most parsimonious species interaction + network topology. + date_publication: '2023-05-05' + bug_reports: https://github.com/miguel-porto/eicm + url: '' + url_cran: https://CRAN.R-project.org/package=eicm + url_git: https://github.com/miguel-porto/eicm +eider: + version: 1.0.0 + title: Declarative Feature Extraction from Tabular Data Records + maintainer: Camila Rangel Smith + description: Extract features from tabular data in a declarative fashion, with a + focus on processing medical records. Features are specified as JSON and are independently + processed before being joined. Input data can be provided as CSV files or as data + frames. This setup ensures that data is transformed in a modular and reproducible + manner, and allows the same pipeline to be easily applied to new data. + date_publication: '2024-05-13' + bug_reports: https://github.com/alan-turing-institute/eider/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eider + url_git: https://github.com/alan-turing-institute/eider +EIEntropy: + version: 0.0.1.3 + title: Ecological Inference Applying Entropy + maintainer: Silvia María Franco Anaya + description: 'Implements two estimations related to the foundations of info metrics + applied to ecological inference. These methodologies assess the lack of disaggregated + data and provide an approach to obtaining disaggregated territorial-level data. + For more details, see the following references: Fernández-Vázquez, E., Díaz-Dapena, + A., Rubiera-Morollón, F. et al. (2020) "Spatial Disaggregation of Social Indicators: + An Info-Metrics Approach." . Díaz-Dapena, A., + Fernández-Vázquez, E., Rubiera-Morollón, F., & Vinuela, A. (2021) "Mapping poverty + at the local level in Europe: A consistent spatial disaggregation of the AROPE + indicator for France, Spain, Portugal and the United Kingdom." .' + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EIEntropy + url_git: '' +eiExpand: + version: 1.0.5 + title: Utilities for Expanding Functionality of 'eiCompare' + maintainer: Rachel Carroll + description: |- + Augments the 'eiCompare' package's Racially Polarized Voting (RPV) + functionality to streamline analyses and visualizations used to support + voting rights and redistricting litigation. The package implements methods + described in Barreto, M., Collingwood, L., Garcia-Rios, S., & Oskooii, K. A. (2022). + "Estimating Candidate Support in Voting Rights Act Cases: Comparing Iterative + EI and EI-R×C Methods" . + date_publication: '2023-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eiExpand + url_git: '' +eigenmodel: + version: '1.11' + title: |- + Semiparametric Factor and Regression Models for Symmetric + Relational Data + maintainer: Peter Hoff + description: |- + Estimation of the parameters in a model for + symmetric relational data (e.g., the above-diagonal part of a + square matrix), using a model-based eigenvalue decomposition + and regression. Missing data is accommodated, and a posterior + mean for missing data is calculated under the assumption that + the data are missing at random. The marginal distribution of + the relational data can be arbitrary, and is fit with an + ordered probit specification. See Hoff (2007) + for details on the model. + date_publication: '2019-05-28' + bug_reports: '' + url: https://pdhoff.github.io/ + url_cran: https://CRAN.R-project.org/package=eigenmodel + url_git: '' +EigenR: + version: 1.3.0 + title: Complex Matrix Algebra with 'Eigen' + maintainer: Stéphane Laurent + description: |- + Matrix algebra using the 'Eigen' C++ library: determinant, + rank, inverse, pseudo-inverse, kernel and image, QR decomposition, + Cholesky decomposition, Schur decomposition, Hessenberg decomposition, + linear least-squares problems. Also provides matrix functions such as + exponential, logarithm, power, sine and cosine. Complex matrices are + supported. + date_publication: '2024-04-28' + bug_reports: https://github.com/stla/EigenR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EigenR + url_git: https://github.com/stla/EigenR +eikosograms: + version: 0.1.1 + title: The Picture of Probability + maintainer: Wayne Oldford + description: |- + An eikosogram (ancient Greek for probability picture) divides the unit square + into rectangular regions whose areas, sides, and widths, represent various probabilities + associated with the values of one or more categorical variates. + Rectangle areas are joint probabilities, widths are always marginal (though possibly joint + margins, i.e. marginal joint distributions of two or more variates), and heights of rectangles + are always conditional probabilities. + Eikosograms embed the rules of probability and are useful for introducing elementary probability + theory, including axioms, marginal, conditional, and joint probabilities, and their + relationships (including Bayes theorem as a completely trivial consequence). + They are markedly superior to Venn diagrams for this purpose, especially in distinguishing + probabilistic independence, mutually exclusive events, coincident events, and associations. + They also are useful for identifying and understanding conditional independence structure. + As data analysis tools, eikosograms display categorical data in a manner similar + to Mosaic plots, especially when only two variates are involved (the only case in which + they are essentially identical, though eikosograms purposely disallow spacing between rectangles). + Unlike Mosaic plots, eikosograms do not alternate axes as each new categorical variate + (beyond two) is introduced. + Instead, only one categorical variate, designated the "response", presents on the vertical axis + and all others, designated the "conditioning" variates, appear on the horizontal. + In this way, conditional probability appears only as height and marginal probabilities as widths. + The eikosogram is therefore much better suited to a response model analysis (e.g. logistic model) + than is a Mosaic plot. + Mosaic plots are better suited to log-linear style modelling as in discrete multivariate analysis. + Of course, eikosograms are also suited to discrete multivariate analysis with each variate in turn + appearing as the response. + This makes it better suited than Mosaic plots to discrete graphical models based on conditional + independence graphs (i.e. "Bayesian Networks" or "BayesNets"). + The eikosogram and its superiority to Venn diagrams in teaching probability is described in + W.H. Cherry and R.W. Oldford (2003) , + its value in exploring conditional independence structure and relation to graphical and log-linear models + is described in R.W. Oldford (2003) , + and a number of problems, puzzles, and paradoxes that are easily explained with eikosograms are given in + R.W. Oldford (2003) . + date_publication: '2018-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eikosograms + url_git: https://github.com/rwoldford/eikosograms +eimpute: + version: 0.2.4 + title: Efficiently Impute Large Scale Incomplete Matrix + maintainer: Zhe Gao + description: Efficiently impute large scale matrix with missing values via its unbiased + low-rank matrix approximation. Our main approach is Hard-Impute algorithm proposed + in , which achieves highly computational + advantage by truncated singular-value decomposition. + date_publication: '2024-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eimpute + url_git: '' +einet: + version: 0.1.0 + title: Effective Information and Causal Emergence + maintainer: Travis Byrum + description: |- + Methods and utilities for causal emergence. + Used to explore and compute various information theory metrics for networks, such as effective information, effectiveness and causal emergence. + date_publication: '2020-04-23' + bug_reports: https://github.com/travisbyrum/einet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=einet + url_git: https://github.com/travisbyrum/einet +einsum: + version: 0.1.2 + title: Einstein Summation + maintainer: Constantin Ahlmann-Eltze + description: |- + The summation notation suggested by Einstein (1916) is a + concise mathematical notation that implicitly sums over repeated indices of n-dimensional arrays. Many ordinary + matrix operations (e.g. transpose, matrix multiplication, scalar product, 'diag()', trace etc.) + can be written using Einstein notation. The notation is particularly convenient for + expressing operations on arrays with more than two dimensions because the + respective operators ('tensor products') might not have a standardized name. + date_publication: '2023-08-28' + bug_reports: https://github.com/const-ae/einsum/issues + url: https://const-ae.github.io/einsum/ + url_cran: https://CRAN.R-project.org/package=einsum + url_git: '' +eiopaR: + version: 0.1.1 + title: Access to RFR (Risk-Free Rate) Curves Produced by the EIOPA + maintainer: Mehdi Echchelh + description: Provides EIOPA (European Insurance And Occupational Pensions Authority) + risk-free rates. Please note that the author of this package is not affiliated + with EIOPA. The data is accessed through a REST API available at . + date_publication: '2021-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eiopaR + url_git: '' +eiopt2: + version: 0.1.1-6 + title: |- + Ecological Inference for RxC Tables via Nonlinear Quadratic + Optimization + maintainer: Jose M. Pavía + description: |- + Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) + from aggregate data by simultaneously minimizing Euclidean row-standardized + unit-to-global distances. + Acknowledgements: + The authors wish to thank Generalitat Valenciana, Consellería de Educación, Cultura, Universidades y Empleo (grant CIAICO/2023/031) for supporting this research. + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eiopt2 + url_git: '' +eiPack: + version: 0.2-2 + title: Ecological Inference and Higher-Dimension Data Management + maintainer: Michael Kellermann + description: |- + Provides methods for analyzing R by C ecological contingency + tables using the extreme case analysis, ecological regression, + and Multinomial-Dirichlet ecological inference models. Also + provides tools for manipulating higher-dimension data objects. + date_publication: '2023-02-18' + bug_reports: '' + url: http://www.olivialau.org/software/ + url_cran: https://CRAN.R-project.org/package=eiPack + url_git: '' +eirm: + version: '0.5' + title: |- + Explanatory Item Response Modeling for Dichotomous and + Polytomous Items + maintainer: Okan Bulut + description: Analysis of dichotomous and polytomous response data using the explanatory + item response modeling framework, as described in Bulut, Gorgun, & Yildirim-Erbasli + (2021) , Stanke & Bulut (2019) , + and De Boeck & Wilson (2004) . Generalized linear + mixed modeling is used for estimating the effects of item-related and person-related + variables on dichotomous and polytomous item responses. + date_publication: '2021-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eirm + url_git: https://github.com/okanbulut/eirm +eive: + version: 3.1.3 + title: |- + An Algorithm for Reducing Errors-in-Variable Bias in Simple and + Multiple Linear Regressions + maintainer: Mehmet Hakan Satman + description: Performs a compact genetic algorithm search to reduce errors-in-variables + bias in linear regression. The algorithm estimates the regression parameters with + lower biases and higher variances but mean-square errors (MSEs) are reduced. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eive + url_git: '' +eivtools: + version: 0.1-8 + title: Measurement Error Modeling Tools + maintainer: J.R. Lockwood + description: This includes functions for analysis with error-prone covariates, including + deconvolution, latent regression and errors-in-variables regression. It implements + methods by Rabe-Hesketh et al. (2003) , Lockwood + and McCaffrey (2014) , and Lockwood and McCaffrey + (2017) , among others. + date_publication: '2018-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eivtools + url_git: '' +EIX: + version: 1.2.0 + title: Explain Interactions in 'XGBoost' + maintainer: Szymon Maksymiuk + description: |- + Structure mining from 'XGBoost' and 'LightGBM' models. + Key functionalities of this package cover: visualisation of tree-based ensembles models, + identification of interactions, measuring of variable importance, + measuring of interaction importance, explanation of single prediction + with break down plots (based on 'xgboostExplainer' and 'iBreakDown' packages). + To download the 'LightGBM' use the following link: . + 'EIX' is a part of the 'DrWhy.AI' universe. + date_publication: '2021-03-23' + bug_reports: https://github.com/ModelOriented/EIX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EIX + url_git: https://github.com/ModelOriented/EIX +eixport: + version: 0.6.2 + title: Export Emissions to Atmospheric Models + maintainer: Sergio Ibarra-Espinosa + description: Emissions are the mass of pollutants released into the atmosphere. + Air quality models need emissions data, with spatial and temporal distribution, + to represent air pollutant concentrations. This package, eixport, creates inputs + for the air quality models 'WRF-Chem' Grell et al (2005) , + 'MUNICH' Kim et al (2018) , 'BRAMS-SPM' Freitas + et al (2005) and 'RLINE' Snyder et al (2013) + . See the 'eixport' website () + for more information, documentations and examples. More details in Ibarra-Espinosa + et al (2018) . + date_publication: '2024-09-23' + bug_reports: https://github.com/atmoschem/eixport/issues/ + url: https://atmoschem.github.io/eixport/ + url_cran: https://CRAN.R-project.org/package=eixport + url_git: '' +EKMCMC: + version: 1.1.2 + title: MCMC Procedures for Estimating Enzyme Kinetics Constants + maintainer: Hyukpyo Hong + description: |- + Functions for estimating catalytic constant and Michaelis-Menten constant + for enzyme kinetics model using Metropolis-Hasting algorithm within Gibbs + sampler based on the Bayesian framework. + date_publication: '2021-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EKMCMC + url_git: '' +eks: + version: 1.0.7 + title: Tidy and Geospatial Kernel Smoothing + maintainer: Tarn Duong + description: Extensions of the kernel smoothing functions from the 'ks' package + for compatibility with the tidyverse and geospatial ecosystems . + date_publication: '2025-01-15' + bug_reports: '' + url: https://www.mvstat.net/mvksa/ + url_cran: https://CRAN.R-project.org/package=eks + url_git: '' +EL: + version: '1.3' + title: Two-Sample Empirical Likelihood + maintainer: Janis Gredzens + description: 'Empirical likelihood (EL) inference for two-sample problems. The following + statistics are included: the difference of two-sample means, smooth Huber estimators, + quantile (qdiff) and cumulative distribution functions (ddiff), probability-probability + (P-P) and quantile-quantile (Q-Q) plots as well as receiver operating characteristic + (ROC) curves. EL calculations are based on J. Valeinis, E. Cers (2011) .' + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EL + url_git: '' +EL2Surv: + version: '1.1' + title: Empirical Likelihood (EL) for Comparing Two Survival Functions + maintainer: Guo-You Lan + description: Functions for computing critical values and implementing the one-sided/two-sided + EL tests. + date_publication: '2018-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EL2Surv + url_git: '' +elaborator: + version: 1.3.4 + title: A 'shiny' Application for Exploring Laboratory Data + maintainer: Bodo Kirsch + description: A novel concept for generating knowledge and gaining insights into + laboratory data. You will be able to efficiently and easily explore your laboratory + data from different perspectives. Janitza, S., Majumder, M., Mendolia, F., Jeske, + S., & Kulmann, H. (2021) . + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elaborator + url_git: https://github.com/openpharma/elaborator +elasdics: + version: 1.1.3 + title: Elastic Analysis of Sparse, Dense and Irregular Curves + maintainer: Lisa Steyer + description: |- + Provides functions to align curves and to compute mean curves based on the + elastic distance defined in the square-root-velocity framework. For more details on + this framework see Srivastava and Klassen (2016, ). + For more theoretical details on our methods and algorithms see + Steyer et al. (2023, ) and Steyer et al. (2023, ). + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elasdics + url_git: '' +elasso: + version: '1.1' + title: |- + Enhanced Least Absolute Shrinkage and Selection Operator + Regression Model + maintainer: Pi Guo + description: |- + Performs some enhanced variable selection algorithms + based on the least absolute shrinkage and selection operator for regression model. + date_publication: '2015-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elasso + url_git: '' +elastes: + version: 0.1.7 + title: |- + Elastic Full Procrustes Means for Sparse and Irregular Planar + Curves + maintainer: Manuel Pfeuffer + description: "Provides functions for the computation of functional elastic shape\nmeans + over sets of open planar curves. The package is particularly suitable for\nsettings + where these curves are only sparsely and irregularly observed. It uses\na novel + approach for elastic shape mean estimation, where planar curves are\ntreated as + complex functions and a full Procrustes mean is estimated from the\ncorresponding + smoothed Hermitian covariance surface. This is combined with the\nmethods for + elastic mean estimation proposed in Steyer, Stöcker, Greven\t(2022)\n. + See Stöcker et. al. (2022) for details." + date_publication: '2023-08-21' + bug_reports: https://github.com/mpff/elastes/issues + url: https://mpff.github.io/elastes/ + url_cran: https://CRAN.R-project.org/package=elastes + url_git: https://github.com/mpff/elastes +elastic: + version: 1.2.0 + title: General Purpose Interface to 'Elasticsearch' + maintainer: Scott Chamberlain + description: |- + Connect to 'Elasticsearch', a 'NoSQL' database built on the 'Java' + Virtual Machine. Interacts with the 'Elasticsearch' 'HTTP' API + (), including functions for + setting connection details to 'Elasticsearch' instances, loading bulk data, + searching for documents with both 'HTTP' query variables and 'JSON' based body + requests. In addition, 'elastic' provides functions for interacting with API's + for 'indices', documents, nodes, clusters, an interface to the cat API, and + more. + date_publication: '2021-03-16' + bug_reports: https://github.com/ropensci/elastic/issues + url: https://docs.ropensci.org/elastic/(website) + url_cran: https://CRAN.R-project.org/package=elastic + url_git: https://github.com/ropensci/elastic +elasticnet: + version: '1.3' + title: Elastic-Net for Sparse Estimation and Sparse PCA + maintainer: Hui Zou + description: |- + Provides functions for fitting the entire + solution path of the Elastic-Net and also provides functions + for doing sparse PCA. + date_publication: '2020-05-15' + bug_reports: '' + url: http://users.stat.umn.edu/~zouxx019/ + url_cran: https://CRAN.R-project.org/package=elasticnet + url_git: '' +elec: + version: 0.1.2.2 + title: Collection of Functions for Statistical Election Audits + maintainer: Luke Mirarix + description: |- + This is a (somewhat bizarre) collection of functions written to do + various sorts of statistical election audits. There are also + functions to generate simulated voting data, including methods to simulation different types + of voting errors which allow for simulations for checking the characteristics of + these methods. + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elec + url_git: '' +EleChemr: + version: 1.2.0 + title: Electrochemical Reactions Simulation + maintainer: Federico Maria Vivaldi + description: |- + Digital simulation of electrochemical processes. + Each function allows for implicit and explicit solution of the differential equation using methods like Euler, Backwards implicit, Runge Kutta 4, Crank Nicholson and Backward differentiation formula as well as different number of points for derivative approximation. Several electrochemical processes can be simulated such as: Chronoamperometry, Potential Step, Linear Sweep, Cyclic Voltammetry, Cyclic Voltammetry with electrochemical reaction followed by chemical reaction (EC mechanism) and CV with two following electrochemical reaction (EE mechanism). In update 1.1.0 has been added a general purpose CV function that allow to simulate up to 4 EE mechanism combined with chemical reaction for each species.Update 1.2.0 improved the accuracy of the measurements and allow personalized data resolution for simulation. + Bibliography regarding this methods can be found in the following texts. + Dieter Britz, Jorg Strutwolf (2016) . + Allen J. Bard, Larry R. Faulkner (2000) . + date_publication: '2021-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EleChemr + url_git: '' +elect: + version: '1.2' + title: Estimation of Life Expectancies Using Multi-State Models + maintainer: Ardo van den Hout + description: Functions to compute state-specific and marginal life expectancies. + The computation is based on a fitted continuous-time multi-state model that includes + an absorbing death state; see Van den Hout (2017, ISBN:9781466568402). The fitted + multi-state model model should be estimated using the 'msm' package using age + as the time-scale. + date_publication: '2019-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elect + url_git: '' +ElectDecomp: + version: 0.0.1-8 + title: Decomposition of Seats-to-Votes Distortions + maintainer: Jose M. Pavía + description: |- + Analyses districted electoral systems of any magnitude by computing district-party conversion ratios and seats-to-votes deviations, decomposing the sources of deviation. Traditional indexes are also computed. + References: + Kedar, O., Harsgor, L. and Sheinerman, R.A. (2016). . + Penades, A and Pavia, J.M. (2025) ''The decomposition of seats-to-votes distortion in elections: mean, variance, malapportionment and participation''. + Acknowledgements: + The authors wish to thank Consellería de Educación, Cultura, Universidades y Empleo, Generalitat Valenciana (grant CIACO/2023/031) for supporting this research. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ElectDecomp + url_git: '' +elections: + version: 1.0.1 + title: USA Presidential Elections Data + maintainer: Willem M. van der Wal + description: This includes a dataset on the outcomes of the USA presidential elections + since 1920, and various predictors, as used in . + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elections + url_git: '' +electionsBR: + version: 0.5.0 + title: R Functions to Download and Clean Brazilian Electoral Data + maintainer: Denisson Silva + description: |- + Offers a set of functions to easily download and clean + Brazilian electoral data from the Superior Electoral Court and 'CepespData' websites. + Among other features, the package retrieves data on local and + federal elections for all positions (city councilor, mayor, state deputy, + federal deputy, governor, and president) aggregated by + state, city, and electoral zones. + date_publication: '2024-11-17' + bug_reports: https://github.com/silvadenisson/electionsBR/issues + url: https://electionsbr.com/novo/ + url_cran: https://CRAN.R-project.org/package=electionsBR + url_git: '' +electivity: + version: 1.0.2 + title: Algorithms for Electivity Indices + maintainer: Desi Quintans + description: |- + Provides all electivity algorithms (including Vanderploeg and Scavia + electivity) that were examined in Lechowicz (1982) , + plus the example data that were provided for moth resource utilisation. + date_publication: '2019-08-20' + bug_reports: https://github.com/DesiQuintans/electivity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=electivity + url_git: https://github.com/DesiQuintans/electivity +electoral: + version: 0.1.3 + title: Allocating Seats Methods and Party System Scores + maintainer: Jorge Albuja + description: |- + Highest averages & largest remainders allocating seats methods and + several party system scores. + Implemented highest averages allocating seats methods are D'Hondt, Webster, + Danish, Imperiali, Hill-Huntington, Dean, Modified Sainte-Lague, + equal proportions and Adams. + Implemented largest remainders allocating seats methods are Hare, Droop, + Hangenbach-Bischoff, Imperial, modified Imperial and quotas & remainders. + The main advantage of this package is that ties are always reported + and not incorrectly allocated. + Party system scores provided are competitiveness, concentration, + effective number of parties, party nationalization score, + party system nationalization score and volatility. + References: + Gallagher (1991) . + Norris (2004, ISBN:0-521-82977-1). + Consejo Nacional Electoral del Ecuador (2014). + Laakso & Taagepera (1979) . + Jones & Mainwaring (2003) . + Pedersen (1979) . + Golosov (2010) . + Golosov (2014) . + date_publication: '2022-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=electoral + url_git: '' +elevatr: + version: 0.99.0 + title: Access Elevation Data from Various APIs + maintainer: Jeffrey Hollister + description: |- + Several web services are available that provide access to elevation + data. This package provides access to many of those services and + returns elevation data either as an 'sf' simple features object + from point elevation services or as a 'raster' object from raster + elevation services. In future versions, 'elevatr' will drop + support for 'raster' and will instead return 'terra' objects. + Currently, the package supports access to the Amazon Web Services + Terrain Tiles , + the Open Topography Global Datasets + API , and the USGS + Elevation Point Query Service . + date_publication: '2023-09-12' + bug_reports: https://github.com/jhollist/elevatr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=elevatr + url_git: https://github.com/jhollist/elevatr/ +ElevDistr: + version: 1.0.9 + title: Calculate the Distance to the Nearest Local Treeline + maintainer: Livio Bätscher + description: |- + A method to calculate the distance to the climatic tree line + for large data sets of coordinates (World Geodetic System 1984) with + geographical uncertainty. The default thresholds and the treeline definition + is based on Paulsen and Körner (2014) , users + are free to decide what climate layers they would like to use. + date_publication: '2024-10-07' + bug_reports: https://github.com/LivioBaetscher/ElevDistr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ElevDistr + url_git: https://github.com/LivioBaetscher/ElevDistr +elexr: + version: '1.0' + title: Load Associated Press Election Results with Elex + maintainer: Geoff Hing + description: Provides R access to election results data. Wraps elex (https://github.com/newsdev/elex/), + a Python package and command line tool for fetching and parsing Associated Press + election results. + date_publication: '2016-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elexr + url_git: '' +elfDistr: + version: 1.0.0 + title: |- + Kumaraswamy Complementary Weibull Geometric (Kw-CWG) Probability + Distribution + maintainer: Matheus H. J. Saldanha + description: |- + Density, distribution function, quantile function + and random generation for the Kumaraswamy Complementary Weibull + Geometric (Kw-CWG) lifetime probability distribution proposed + in Afify, A.Z. et al (2017) . + date_publication: '2019-10-07' + bug_reports: https://github.com/matheushjs/elfDistr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=elfDistr + url_git: https://github.com/matheushjs/elfDistr +elgbd: + version: 0.9.0 + title: Empirical Likelihood for General Block Designs + maintainer: Eunseop Kim + description: |- + Performs hypothesis testing for general block designs with + empirical likelihood. The core computational routines are implemented + using the 'Eigen' 'C++' library and 'RcppEigen' interface, with + 'OpenMP' for parallel computation. Details of the methods are given in + Kim, MacEachern, and Peruggia (2023) + . This work was supported by the + U.S. National Science Foundation under Grants No. SES-1921523 and + DMS-2015552. + date_publication: '2024-02-04' + bug_reports: https://github.com/markean/elgbd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=elgbd + url_git: https://github.com/markean/elgbd +elhmc: + version: 1.2.1 + title: |- + Sampling from a Empirical Likelihood Bayesian Posterior of + Parameters Using Hamiltonian Monte Carlo + maintainer: Sanjay Chaudhuri + description: |- + A tool to draw samples from a Empirical Likelihood Bayesian posterior + of parameters using Hamiltonian Monte Carlo. + date_publication: '2024-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elhmc + url_git: '' +ELISAtools: + version: 0.1.5 + title: ELISA Data Analysis with Batch Correction + maintainer: Feng Feng + description: |- + To run data analysis for enzyme-link immunosorbent assays (ELISAs). + Either the five- or four-parameter logistic model will be fitted for data of single ELISA. + Moreover, the batch effect correction/normalization will be carried out, when there are more than one batches of ELISAs. + Feng (2018) . + date_publication: '2021-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ELISAtools + url_git: '' +elisr: + version: 0.1.1 + title: Exploratory Likert Scaling + maintainer: Steven Bißantz + description: |- + An alternative to Exploratory Factor Analysis (EFA) for + metrical data in R. Drawing on characteristics of classical test + theory, Exploratory Likert Scaling (ELiS) supports the user exploring + multiple one-dimensional data structures. In common research practice, + however, EFA remains the go-to method to uncover the (underlying) + structure of a data set. Orthogonal dimensions and the potential of + overextraction are often accepted as side effects. As described in + Müller-Schneider (2001) ), ELiS confronts + these problems. As a result, 'elisr' provides the platform to fully + exploit the exploratory potential of the multiple scaling approach + itself. + date_publication: '2021-05-15' + bug_reports: https://github.com/sbissantz/elisr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=elisr + url_git: https://github.com/sbissantz/elisr +eList: + version: 0.2.0 + title: List Comprehension and Tools + maintainer: Chris Mann + description: |2- + + Create list comprehensions (and other types of comprehension) similar to those in + 'python', 'haskell', and other languages. List comprehension in 'R' converts a + regular for() loop into a vectorized lapply() function. Support for looping + with multiple variables, parallelization, and across non-standard objects included. Package + also contains a variety of functions to help with list comprehension. + date_publication: '2021-01-22' + bug_reports: https://github.com/cmann3/eList/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eList + url_git: '' +elitism: + version: 1.1.1 + title: |- + Equipment for Logarithmic and Linear Time Stepwise Multiple + Hypothesis Testing + maintainer: Jiangtao Gou + description: |- + Recently many new p-value based multiple test procedures have been proposed, and these new methods are more powerful than the widely used Hochberg procedure. These procedures strongly control the familywise error rate (FWER). This is a comprehensive collection of p-value based FWER-control stepwise multiple test procedures, including six procedure families and thirty multiple test procedures. In this collection, the conservative Hochberg procedure, linear time Hommel procedures, asymptotic Rom procedure, Gou-Tamhane-Xi-Rom procedures, and Quick procedures are all developed in recent five years since 2014. The package name "elitism" is an acronym of "e"quipment for "l"ogarithmic and l"i"near "ti"me "s"tepwise "m"ultiple hypothesis testing. + See Gou, J. (2022), "Quick multiple test procedures and p-value adjustments", Statistics in Biopharmaceutical Research 14(4), 636-650. + date_publication: '2023-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elitism + url_git: '' +Elja: + version: 1.0.0 + title: |- + Linear, Logistic and Generalized Linear Models Regressions for + the EnvWAS/EWAS Approach + maintainer: Marwan El Homsi + description: |- + Tool for Environment-Wide Association Studies (EnvWAS / EWAS) + which are repeated analysis. It includes three functions. One function for + linear regression, a second for logistic regression and a last one for + generalized linear models. + date_publication: '2023-07-03' + bug_reports: https://github.com/EHMarwan/Elja/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Elja + url_git: https://github.com/EHMarwan/Elja +elliplot: + version: 1.3.0 + title: Ellipse Summary Plot of Quantiles + maintainer: Shinichiro Tomizono + description: |- + Correlation chart of two set (x and y) of data. + Using Quantiles. Visualize the effect of factor. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elliplot + url_git: '' +ellipse: + version: 0.5.0 + title: |- + Functions for Drawing Ellipses and Ellipse-Like Confidence + Regions + maintainer: Duncan Murdoch + description: |- + Contains various routines for drawing + ellipses and ellipse-like confidence regions, implementing the plots + described in Murdoch and Chow (1996, ). There are + also routines implementing the profile plots described in Bates and + Watts (1988, ). + date_publication: '2023-07-20' + bug_reports: https://github.com/dmurdoch/ellipse/issues + url: https://dmurdoch.github.io/ellipse/ + url_cran: https://CRAN.R-project.org/package=ellipse + url_git: https://github.com/dmurdoch/ellipse +ellipsis: + version: 0.3.2 + title: Tools for Working with ... + maintainer: Hadley Wickham + description: |- + The ellipsis is a powerful tool for extending functions. Unfortunately + this power comes at a cost: misspelled arguments will be silently ignored. + The ellipsis package provides a collection of functions to catch problems + and alert the user. + date_publication: '2021-04-29' + bug_reports: https://github.com/r-lib/ellipsis/issues + url: https://ellipsis.r-lib.org + url_cran: https://CRAN.R-project.org/package=ellipsis + url_git: https://github.com/r-lib/ellipsis +ElliptCopulas: + version: 0.1.4.1 + title: Inference of Elliptical Distributions and Copulas + maintainer: Alexis Derumigny + description: |- + Provides functions for the simulation and + the nonparametric estimation of elliptical distributions, + meta-elliptical copulas and trans-elliptical distributions, + following the article Derumigny and Fermanian (2022) . + date_publication: '2024-09-09' + bug_reports: https://github.com/AlexisDerumigny/ElliptCopulas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ElliptCopulas + url_git: https://github.com/AlexisDerumigny/ElliptCopulas +elliptic: + version: 1.4-0 + title: Weierstrass and Jacobi Elliptic Functions + maintainer: Robin K. S. Hankin + description: |2- + + A suite of elliptic and related functions including Weierstrass and + Jacobi forms. Also includes various tools for manipulating and + visualizing complex functions. + date_publication: '2019-03-14' + bug_reports: https://github.com/RobinHankin/elliptic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=elliptic + url_git: https://github.com/RobinHankin/elliptic.git +ellipticalsymmetry: + version: 0.1.2 + title: Elliptical Symmetry Tests + maintainer: Marko Palangetic + description: |- + Given the omnipresence of the assumption of elliptical symmetry, it is essential to be able to test whether that assumption actually holds true or not for the data + at hand. This package provides several statistical tests for elliptical symmetry that are described in Babic et al. (2021) . + date_publication: '2021-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ellipticalsymmetry + url_git: '' +ellmer: + version: 0.1.1 + title: Chat with Large Language Models + maintainer: Hadley Wickham + description: |- + Chat with large language models from a range of providers + including 'Claude' , 'OpenAI' + , and more. Supports streaming, asynchronous + calls, tool calling, and structured data extraction. + date_publication: '2025-02-07' + bug_reports: https://github.com/tidyverse/ellmer/issues + url: https://ellmer.tidyverse.org + url_cran: https://CRAN.R-project.org/package=ellmer + url_git: https://github.com/tidyverse/ellmer +elmNNRcpp: + version: 1.0.4 + title: The Extreme Learning Machine Algorithm + maintainer: Lampros Mouselimis + description: 'Training and predict functions for Single Hidden-layer Feedforward + Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The + ELM algorithm differs from the traditional gradient-based algorithms for very + short training times (it doesn''t need any iterative tuning, this makes learning + time very fast) and there is no need to set any other parameters like learning + rate, momentum, epochs, etc. This is a reimplementation of the ''elmNN'' package + using ''RcppArmadillo'' after the ''elmNN'' package was archived. For more information, + see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu + Zhu, Chee-Kheong Siew (2006), Elsevier B.V, .' + date_publication: '2022-01-28' + bug_reports: https://github.com/mlampros/elmNNRcpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=elmNNRcpp + url_git: https://github.com/mlampros/elmNNRcpp +ELMR: + version: '1.0' + title: Extreme Machine Learning (ELM) + maintainer: Alessio Petrozziello + description: Training and prediction functions are provided for the Extreme Learning + Machine algorithm (ELM). The ELM use a Single Hidden Layer Feedforward Neural + Network (SLFN) with random generated weights and no gradient-based backpropagation. + The training time is very short and the online version allows to update the model + using small chunk of the training set at each iteration. The only parameter to + tune is the hidden layer size and the learning function. + date_publication: '2015-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ELMR + url_git: '' +ELMSO: + version: 1.0.1 + title: |- + Implementation of the Efficient Large-Scale Online Display + Advertising Algorithm + maintainer: Courtney Paulson + description: |- + An implementation of the algorithm described in "Efficient Large- + Scale Internet Media Selection Optimization for Online Display Advertising" + by Paulson, Luo, and James (Journal of Marketing Research 2018; see URL below + for journal text/citation and + for a full-text version of the paper). The algorithm here is designed to + allocate budget across a set of online advertising opportunities using a + coordinate-descent approach, but it can be used in any resource-allocation + problem with a matrix of visitation (in the case of the paper, website page- + views) and channels (in the paper, websites). The package contains allocation + functions both in the presence of bidding, when allocation is dependent on + channel-specific cost curves, and when advertising costs are fixed at each channel. + date_publication: '2020-01-18' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=ELMSO + url_git: '' +eLNNpairedCov: + version: 0.3.2 + title: Model-Based Gene Selection for Paired Data + maintainer: Yixin Zhang + description: Model-based clustering for paired data based on the regression of a + mixture of Bayesian hierarchical models on covariates. Zhang et al. (2023) . + date_publication: '2024-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eLNNpairedCov + url_git: '' +elo: + version: 3.0.2 + title: Ranking Teams by Elo Rating and Comparable Methods + maintainer: Ethan Heinzen + description: |- + A flexible framework for calculating Elo ratings and resulting + rankings of any two-team-per-matchup system (chess, sports leagues, 'Go', + etc.). This implementation is capable of evaluating a variety of matchups, + Elo rating updates, and win probabilities, all based on the basic Elo + rating system. It also includes methods to benchmark performance, + including logistic regression and Markov chain models. + date_publication: '2023-08-23' + bug_reports: https://github.com/eheinzen/elo/issues + url: https://eheinzen.github.io/elo/ + url_cran: https://CRAN.R-project.org/package=elo + url_git: https://github.com/eheinzen/elo +EloChoice: + version: 0.29.4 + title: Preference Rating for Visual Stimuli Based on Elo Ratings + maintainer: Christof Neumann + description: Allows calculating global scores for characteristics of visual stimuli + as assessed by human raters. Stimuli are presented as sequence of pairwise comparisons + ('contests'), during each of which a rater expresses preference for one stimulus + over the other (forced choice). The algorithm for calculating global scores is + based on Elo rating, which updates individual scores after each single pairwise + contest. Elo rating is widely used to rank chess players according to their performance. + Its core feature is that dyadic contests with expected outcomes lead to smaller + changes of participants' scores than outcomes that were unexpected. As such, Elo + rating is an efficient tool to rate individual stimuli when a large number of + such stimuli are paired against each other in the context of experiments where + the goal is to rank stimuli according to some characteristic of interest. Clark + et al (2018) provide details. + date_publication: '2019-07-04' + bug_reports: https://github.com/gobbios/EloChoice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EloChoice + url_git: https://github.com/gobbios/EloChoice +EloOptimized: + version: 0.3.2 + title: Optimized Elo Rating Method for Obtaining Dominance Ranks + maintainer: Joseph Feldblum + description: |- + Provides an implementation of the maximum likelihood methods for deriving + Elo scores as published in Foerster, Franz et al. (2016) . + date_publication: '2024-05-21' + bug_reports: https://github.com/jtfeld/EloOptimized/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EloOptimized + url_git: https://github.com/jtfeld/EloOptimized +EloRating: + version: 0.46.18 + title: Animal Dominance Hierarchies by Elo Rating + maintainer: Christof Neumann + description: Provides functions to quantify animal dominance hierarchies. The major + focus is on Elo rating and its ability to deal with temporal dynamics in dominance + interaction sequences. For static data, David's score and de Vries' I&SI are also + implemented. In addition, the package provides functions to assess transitivity, + linearity and stability of dominance networks. See Neumann et al (2011) + for an introduction. + date_publication: '2024-07-15' + bug_reports: https://github.com/gobbios/EloRating/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EloRating + url_git: https://github.com/gobbios/EloRating +EloSteepness: + version: 0.5.0 + title: |- + Bayesian Dominance Hierarchy Steepness via Elo Rating and + David's Scores + maintainer: Christof Neumann + description: Obtain Bayesian posterior distributions of dominance hierarchy steepness + (Neumann and Fischer (2023) ). Steepness estimation + is based on Bayesian implementations of either Elo-rating or David's scores. + date_publication: '2023-09-21' + bug_reports: https://github.com/gobbios/EloSteepness/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EloSteepness + url_git: https://github.com/gobbios/EloSteepness +elrm: + version: 1.2.6 + title: Exact Logistic Regression via MCMC + maintainer: David Zamar + description: |- + Implements a Markov Chain Monte Carlo algorithm to approximate + exact conditional inference for logistic regression models. Exact + conditional inference is based on the distribution of the sufficient + statistics for the parameters of interest given the sufficient statistics + for the remaining nuisance parameters. Using model formula notation, users + specify a logistic model and model terms of interest for exact inference. + See Zamar et al. (2007) for more details. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=elrm + url_git: '' +elsa: + version: 1.1-28 + title: Entropy-Based Local Indicator of Spatial Association + maintainer: Babak Naimi + description: 'A framework that provides the methods for quantifying entropy-based + local indicator of spatial association (ELSA) that can be used for both continuous + and categorical data. In addition, this package offers other methods to measure + local indicators of spatial associations (LISA). Furthermore, global spatial structure + can be measured using a variogram-like diagram, called entrogram. For more information, + please check that paper: Naimi, B., Hamm, N. A., Groen, T. A., Skidmore, A. K., + Toxopeus, A. G., & Alibakhshi, S. (2019) .' + date_publication: '2020-03-19' + bug_reports: https://github.com/babaknaimi/elsa/issues/ + url: http://r-gis.net + url_cran: https://CRAN.R-project.org/package=elsa + url_git: '' +ELT: + version: '1.7' + title: Experience Life Tables + maintainer: Wassim Youssef + description: Build experience life tables. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ELT + url_git: '' +eltr: + version: 0.1.0 + title: Utilise Catastrophe Model Event Loss Table Outputs + maintainer: Randhir Bilkhu + description: Provides a tool to run Monte Carlo simulation of catastrophe model + event loss tables, using a Poisson frequency and Beta severity distribution. + date_publication: '2021-01-16' + bug_reports: https://github.com/RandhirBilkhu/eltr/issues + url: https://randhirbilkhu.github.io/eltr/ + url_cran: https://CRAN.R-project.org/package=eltr + url_git: https://github.com/RandhirBilkhu/eltr +ELYP: + version: 0.7-5 + title: |- + Empirical Likelihood Analysis for the Cox Model and + Yang-Prentice (2005) Model + maintainer: Mai Zhou + description: |- + Empirical likelihood ratio tests for the Yang and Prentice (short/long term hazards ratio) models. + Empirical likelihood tests within a Cox model, for parameters defined via + both baseline hazard function and regression parameters. + date_publication: '2018-08-19' + bug_reports: '' + url: http://www.ms.uky.edu/~mai/EmpLik.html + url_cran: https://CRAN.R-project.org/package=ELYP + url_git: '' +em: + version: 1.0.0 + title: Generic EM Algorithm + maintainer: Dongjie Wu + description: |- + A generic function for running the Expectation-Maximization (EM) algorithm + within a maximum likelihood framework, based on Dempster, Laird, and Rubin (1977) + is implemented. It can be applied after a model fitting using R's existing functions and packages. + date_publication: '2023-01-11' + bug_reports: https://github.com/wudongjie/em/issues + url: '' + url_cran: https://CRAN.R-project.org/package=em + url_git: https://github.com/wudongjie/em +EM.Fuzzy: + version: '1.0' + title: |- + EM Algorithm for Maximum Likelihood Estimation by Non-Precise + Information + maintainer: Abbas Parchami + description: The EM algorithm is a powerful tool for computing maximum likelihood + estimates with incomplete data. This package will help to applying EM algorithm + based on triangular and trapezoidal fuzzy numbers (as two kinds of incomplete + data). A method is proposed for estimating the unknown parameter in a parametric + statistical model when the observations are triangular or trapezoidal fuzzy numbers. + This method is based on maximizing the observed-data likelihood defined as the + conditional probability of the fuzzy data; for more details and formulas see Denoeux + (2011) . + date_publication: '2018-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EM.Fuzzy + url_git: '' +emailjsr: + version: 0.0.2 + title: '''emailjs'' Support' + maintainer: Changwoo Lim + description: Use 'emailjs' API easily in 'R'. This package is not official. . + You can send e-mail with 'emailjs' with function, based on 'httr'. You can also + make a 'shiny' ui and server function. It can be used for making feedback form, + inquiry, and so on. + date_publication: '2022-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emailjsr + url_git: '' +emailvalidation: + version: 0.1.0 + title: Client for the 'emailalvalidation.io' E-Mail Validation API + maintainer: Dominik Kukacka + description: An R client for the 'emailvalidation.io' e-mail verification API. The + API requires registration of an API key. Basic features are free, some require + a paid subscription. You can find the full API documentation at + . + date_publication: '2023-05-11' + bug_reports: '' + url: https://emailvalidation.io + url_cran: https://CRAN.R-project.org/package=emailvalidation + url_git: '' +EMAR: + version: 1.0.0 + title: Empirical Model Assessment + maintainer: Friday Nwabueze Ogana + description: "A tool that allows users to generate various indices for evaluating + statistical models. The fitstat() function computes indices based on the fitting + data. The valstat() function computes indices based on the validation data set. + Both fitstat() and valstat() will return 16 indices SSR: residual sum of squares, + TRE: total relative error, Bias: mean bias, MRB: mean relative bias, MAB: mean + absolute bias, MAPE: mean absolute percentage error, MSE: mean squared\terror, + RMSE: root mean square error, Percent.RMSE: percentage root mean squared error, + R2: coefficient of determination, R2adj: adjusted coefficient of determination, + APC: Amemiya's prediction criterion, logL: Log-likelihood, AIC: Akaike information + criterion, AICc: corrected Akaike information criterion, BIC: Bayesian information + criterion, HQC: Hannan-Quin information criterion. The\tlower the better for the + SSR, TRE, Bias, MRB, MAB, MAPE, MSE, RMSE, Percent.RMSE, APC, AIC, AICc, BIC and + HQC indices. The higher the better for R2 and R2adj indices. Petre Stoica, P., + Selén, Y. (2004) \\n Zhou et al. (2023) \\n + Ogana, F.N., Ercanli, I. (2021) \\n Musabbikhah + et al. (2019) ." + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMAR + url_git: '' +EMAS: + version: 0.2.2 + title: Epigenome-Wide Mediation Analysis Study + maintainer: Xiuquan Nie + description: |- + DNA methylation is essential for human, and environment can change the DNA methylation + and affect body status. Epigenome-Wide Mediation Analysis Study (EMAS) can find + potential mediator CpG sites between exposure (x) and outcome (y) in epigenome-wide. + For more information on the methods we used, please see the following references: + Tingley, D. (2014) , + Turner, S. D. (2018) , + Rosseel, D. (2012) . + date_publication: '2022-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMAS + url_git: '' +emayili: + version: 0.9.3 + title: Send Email Messages + maintainer: Andrew B. Collier + description: A light, simple tool for sending emails with minimal dependencies. + date_publication: '2025-02-07' + bug_reports: https://github.com/datawookie/emayili/issues + url: https://datawookie.github.io/emayili/ + url_cran: https://CRAN.R-project.org/package=emayili + url_git: '' +emBayes: + version: 0.1.6 + title: Robust Bayesian Variable Selection via Expectation-Maximization + maintainer: Yuwen Liu + description: Variable selection methods have been extensively developed for analyzing + highdimensional omics data within both the frequentist and Bayesian frameworks. + This package provides implementations of the spike-and-slab quantile (group) LASSO + which have been developed along the line of Bayesian hierarchical models but deeply + rooted in frequentist regularization methods by utilizing Expectation–Maximization + (EM) algorithm. The spike-and-slab quantile LASSO can handle data irregularity + in terms of skewness and outliers in response variables, compared to its non-robust + alternative, the spike-and-slab LASSO, which has also been implemented in the + package. In addition, procedures for fitting the spike-and-slab quantile group + LASSO and its non-robust counterpart have been implemented in the form of quantile/least-square + varying coefficient mixed effect models for high-dimensional longitudinal data. + The core module of this package is developed in 'C++'. + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emBayes + url_git: '' +EMbC: + version: 2.0.4 + title: Expectation-Maximization Binary Clustering + maintainer: Joan Garriga + description: Unsupervised, multivariate, binary clustering for meaningful annotation + of data, taking into account the uncertainty in the data. A specific constructor + for trajectory analysis in movement ecology yields behavioural annotation of trajectories + based on estimated local measures of velocity and turning angle, eventually with + solar position covariate as a daytime indicator, ("Expectation-Maximization Binary + Clustering for Behavioural Annotation"). + date_publication: '2023-10-03' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=EMbC + url_git: '' +embed: + version: 1.1.5 + title: Extra Recipes for Encoding Predictors + maintainer: Emil Hvitfeldt + description: |- + Predictors can be converted to one or more numeric + representations using a variety of methods. Effect encodings using + simple generalized linear models or + nonlinear models can be used. There + are also functions for dimension reduction and other approaches. + date_publication: '2025-01-23' + bug_reports: https://github.com/tidymodels/embed/issues + url: https://embed.tidymodels.org + url_cran: https://CRAN.R-project.org/package=embed + url_git: https://github.com/tidymodels/embed +EmbedSOM: + version: '2.2' + title: Fast Embedding Guided by Self-Organizing Map + maintainer: Mirek Kratochvil + description: |- + Provides a smooth mapping of multidimensional points into + low-dimensional space defined by a self-organizing map. Designed to work + with 'FlowSOM' and flow-cytometry use-cases. See Kratochvil et al. (2019) + . + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EmbedSOM + url_git: https://github.com/exaexa/EmbedSOM +embryogrowth: + version: '9.5' + title: Tools to Analyze the Thermal Reaction Norm of Embryo Growth + maintainer: Marc Girondot + description: Tools to analyze the embryo growth and the sexualisation thermal reaction + norms. See for tsd functions; see + for thermal reaction norm of embryo growth. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=embryogrowth + url_git: '' +EMC2: + version: 2.1.0 + title: Bayesian Hierarchical Analysis of Cognitive Models of Choice + maintainer: Niek Stevenson + description: |- + Fit Bayesian (hierarchical) cognitive models + using a linear modeling language interface using particle metropolis Markov + chain Monte Carlo sampling with Gibbs steps. The diffusion decision model (DDM), + linear ballistic accumulator model (LBA), racing diffusion model (RDM), and the lognormal + race model (LNR) are supported. Additionally, users can specify their own likelihood + function and/or choose for non-hierarchical + estimation, as well as for a diagonal, blocked or full multivariate normal + group-level distribution to test individual differences. Prior specification + is facilitated through methods that visualize the (implied) prior. + A wide range of plotting functions assist in assessing model convergence and + posterior inference. Models can be easily evaluated using functions + that plot posterior predictions or using relative model comparison metrics + such as information criteria or Bayes factors. + References: Stevenson et al. (2024) . + date_publication: '2024-10-14' + bug_reports: https://github.com/ampl-psych/EMC2/issues + url: https://ampl-psych.github.io/EMC2/ + url_cran: https://CRAN.R-project.org/package=EMC2 + url_git: https://github.com/ampl-psych/EMC2 +emcAdr: + version: '1.2' + title: Evolutionary Version of the Metropolis-Hastings Algorithm + maintainer: Jules Bangard + description: |- + Provides computational methods for detecting adverse high-order drug interactions + from individual case safety reports using statistical techniques, + allowing the exploration of higher-order interactions among drug cocktails. + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emcAdr + url_git: '' +EMCluster: + version: 0.2-17 + title: |- + EM Algorithm for Model-Based Clustering of Finite Mixture + Gaussian Distribution + maintainer: Wei-Chen Chen + description: |- + EM algorithms and several efficient + initialization methods for model-based clustering of finite + mixture Gaussian distribution with unstructured dispersion + in both of unsupervised and semi-supervised learning. + date_publication: '2025-01-09' + bug_reports: https://github.com/snoweye/EMCluster/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EMCluster + url_git: https://github.com/snoweye/EMCluster +EMD: + version: 1.5.9 + title: Empirical Mode Decomposition and Hilbert Spectral Analysis + maintainer: Donghoh Kim + description: |- + For multiscale analysis, this package carries out empirical mode decomposition and Hilbert spectral + analysis. For usage of EMD, see Kim and Oh, 2009 (Kim, D and Oh, H.-S. (2009) EMD: A Package for Empirical + Mode Decomposition and Hilbert Spectrum, The R Journal, 1, 40-46). + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMD + url_git: '' +EMDANNhybrid: + version: 0.2.0 + title: |- + Empirical Mode Decomposition Based Artificial Neural Network + Model + maintainer: Pankaj Das + description: Application of empirical mode decomposition based artificial neural + network model for nonlinear and non stationary univariate time series forecasting. + For method details see (i) Choudhury (2019) ; + (ii) Das (2020) . + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMDANNhybrid + url_git: '' +emdbook: + version: 1.3.13 + title: Support Functions and Data for "Ecological Models and Data" + maintainer: Ben Bolker + description: Auxiliary functions and data sets for "Ecological Models and Data", + a book presenting maximum likelihood estimation and related topics for ecologists + (ISBN 978-0-691-12522-0). + date_publication: '2023-07-03' + bug_reports: '' + url: https://www.math.mcmaster.ca/bolker/emdbook + url_cran: https://CRAN.R-project.org/package=emdbook + url_git: '' +emdi: + version: 2.2.2 + title: Estimating and Mapping Disaggregated Indicators + maintainer: Soeren Pannier + description: |- + Functions that support estimating, assessing and mapping regional + disaggregated indicators. So far, estimation methods comprise direct estimation, + the model-based unit-level approach Empirical Best Prediction (see "Small area + estimation of poverty indicators" by Molina and Rao (2010) ), + the area-level model (see "Estimates of income for small places: An + application of James-Stein procedures to Census Data" by Fay and Herriot (1979) + ) and various extensions of it (adjusted variance + estimation methods, log and arcsin transformation, spatial, robust and measurement + error models), as well as their precision estimates. The assessment of the used model + is supported by a summary and diagnostic plots. For a suitable presentation of + estimates, map plots can be easily created. Furthermore, results can easily be + exported to excel. For a detailed description of the package and the methods used + see "The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators" + by Kreutzmann et al. (2019) and the second package vignette + "A Framework for Producing Small Area Estimates Based on Area-Level Models in R". + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emdi + url_git: https://github.com/SoerenPannier/emdi +emdist: + version: 0.3-3 + title: Earth Mover's Distance + maintainer: Simon Urbanek + description: Package providing calculation of Earth Mover's Distance (EMD). + date_publication: '2023-08-18' + bug_reports: '' + url: http://www.rforge.net/emd + url_cran: https://CRAN.R-project.org/package=emdist + url_git: '' +EMDSVRhybrid: + version: 0.2.0 + title: |- + Empirical Mode Decomposition Based Support Vector Regression + Model + maintainer: Pankaj Das + description: 'Description: Application of empirical mode decomposition based support + vector regression model for nonlinear and non stationary univariate time series + forecasting. For method details see (i) Choudhury (2019) ; + (ii) Das (2020) ; (iii) + Das (2023) .' + date_publication: '2023-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMDSVRhybrid + url_git: '' +emery: + version: 0.5.1 + title: Accuracy Statistic Estimation for Imperfect Gold Standards + maintainer: Corie Drake + description: |- + Produce maximum likelihood estimates of common accuracy statistics + for multiple measurement methods when a gold standard is not available. An R + implementation of the expectation maximization algorithms described in Zhou et + al. (2011) with additional functions for creating + simulated data and visualizing results. Supports binary, ordinal, and + continuous measurement methods. + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emery + url_git: '' +emg: + version: 1.0.9 + title: Exponentially Modified Gaussian (EMG) Distribution + maintainer: Shawn Garbett + description: Provides basic distribution functions for a mixture model of a Gaussian + and exponential distribution. + date_publication: '2020-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emg + url_git: '' +EMgaussian: + version: 0.2.1 + title: |- + Expectation-Maximization Algorithm for Multivariate Normal + (Gaussian) with Missing Data + maintainer: Carl F. Falk + description: |- + Initially designed to distribute code for estimating the Gaussian + graphical model with Lasso regularization, also known as the graphical lasso + (glasso), using an Expectation-Maximization (EM) algorithm based on work by + Städler and Bühlmann (2012) . As a byproduct, + code for estimating means and covariances (or the precision matrix) under a + multivariate normal (Gaussian) distribution is also available. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMgaussian + url_git: '' +emhawkes: + version: 0.9.7 + title: Exponential Multivariate Hawkes Model + maintainer: Kyungsub Lee + description: |- + Simulate and fitting exponential multivariate Hawkes model. + This package simulates a multivariate Hawkes model, introduced by Hawkes (1971) , with an exponential kernel and fits the parameters from the data. + Models with the constant parameters, as well as complex dependent structures, can also be simulated and estimated. + The estimation is based on the maximum likelihood method, introduced by introduced by Ozaki (1979) , with 'maxLik' package. + date_publication: '2023-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emhawkes + url_git: '' +EmiR: + version: 1.0.4 + title: Evolutionary Minimizer for R + maintainer: Lorenzo Sostero + description: |- + A C++ implementation of the following evolutionary + algorithms: Bat Algorithm (Yang, 2010 ), + Cuckoo Search (Yang, 2009 ), + Genetic Algorithms (Holland, 1992, ISBN:978-0262581110), + Gravitational Search Algorithm (Rashedi et al., 2009 ), + Grey Wolf Optimization (Mirjalili et al., 2014 ), + Harmony Search (Geem et al., 2001 ), + Improved Harmony Search (Mahdavi et al., 2007 ), + Moth-flame Optimization (Mirjalili, 2015 ), + Particle Swarm Optimization (Kennedy et al., 2001 ISBN:1558605959), + Simulated Annealing (Kirkpatrick et al., 1983 ), + Whale Optimization Algorithm (Mirjalili and Lewis, 2016 ). + 'EmiR' can be used not only for unconstrained optimization problems, but also + in presence of inequality constrains, and variables restricted to be integers. + date_publication: '2022-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EmiR + url_git: '' +emIRT: + version: 0.0.14 + title: EM Algorithms for Estimating Item Response Theory Models + maintainer: Kosuke Imai + description: |- + Various Expectation-Maximization (EM) algorithms are implemented for item + response theory (IRT) models. The package includes IRT models for binary and ordinal + responses, along with dynamic and hierarchical IRT models with binary responses. The + latter two models are fitted using variational EM. The package also includes + variational network and text scaling models. The algorithms are described in Imai, Lo, + and Olmsted (2016) . + date_publication: '2024-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emIRT + url_git: '' +EmissV: + version: 0.665.9.0 + title: Tools for Create Emissions for Air Quality Models + maintainer: Daniel Schuch + description: |- + Processing tools to create emissions for use in numerical air + quality models. Emissions can be calculated both using emission factors + and activity data (Schuch et al 2018) or using + pollutant inventories (Schuch et al., 2018) . + Functions to process individual point emissions, line emissions and + area emissions of pollutants are available as well as methods to + incorporate alternative data for Spatial distribution of emissions + such as satellite images (Gavidia-Calderon et. al, 2018) + or openstreetmap data + (Andrade et al, 2015) . + date_publication: '2025-01-24' + bug_reports: https://github.com/atmoschem/EmissV/issues + url: https://atmoschem.github.io/EmissV/ + url_cran: https://CRAN.R-project.org/package=EmissV + url_git: '' +EmiStatR: + version: 1.2.3.0 + title: |- + Emissions and Statistics in R for Wastewater and Pollutants in + Combined Sewer Systems + maintainer: J.A. Torres-Matallana + description: |- + Provides a fast and parallelised calculator to estimate combined wastewater emissions. + It supports the planning and design of urban drainage systems, without the requirement of + extensive simulation tools. The 'EmiStatR' package implements modular R methods. This enables + to add new functionalities through the R framework. + date_publication: '2021-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EmiStatR + url_git: '' +EMJMCMC: + version: 1.5.0 + title: |- + Evolutionary Mode Jumping Markov Chain Monte Carlo Expert + Toolbox + maintainer: Waldir Leoncio + description: Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm + from Hubin, A., Storvik, G. (2018) , Genetically + Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & + Frommlet, F. (2020) , Hubin, A., Storvik, G., & Frommlet, + F. (2021) , and Hubin, A., Heinze, G., & De Bin, R. + (2023) , and Reversible Genetically Modified + Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, + G. (2021) , which allow for estimating posterior + model probabilities and Bayesian model averaging across a wide set of Bayesian + models including linear, generalized linear, generalized linear mixed, generalized + nonlinear, generalized nonlinear mixed, and logic regression models. + date_publication: '2024-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMJMCMC + url_git: '' +EML: + version: 2.0.6.1 + title: Read and Write Ecological Metadata Language Files + maintainer: Carl Boettiger + description: |- + Work with Ecological Metadata Language ('EML') files. + 'EML' is a widely used metadata standard in the ecological and + environmental sciences, described in Jones et al. (2006), + . + date_publication: '2022-04-28' + bug_reports: https://github.com/ropensci/EML/issues + url: https://docs.ropensci.org/EML/ + url_cran: https://CRAN.R-project.org/package=EML + url_git: https://github.com/ropensci/EML/ +emld: + version: 0.5.1 + title: Ecological Metadata as Linked Data + maintainer: Carl Boettiger + description: |- + This is a utility for transforming Ecological Metadata Language + ('EML') files into 'JSON-LD' and back into 'EML.' Doing so creates a + list-based representation of 'EML' in R, so that 'EML' data can easily + be manipulated using standard 'R' tools. This makes this package an + effective backend for other 'R'-based tools working with 'EML.' By + abstracting away the complexity of 'XML' Schema, developers can + build around native 'R' list objects and not have to worry about satisfying + many of the additional constraints of set by the schema (such as element + ordering, which is handled automatically). Additionally, the 'JSON-LD' + representation enables the use of developer-friendly 'JSON' parsing and + serialization that may facilitate the use of 'EML' in contexts outside of 'R,' + as well as the informatics-friendly serializations such as 'RDF' and + 'SPARQL' queries. + date_publication: '2020-09-27' + bug_reports: https://github.com/ropensci/emld/issues + url: https://docs.ropensci.org/emld/ + url_cran: https://CRAN.R-project.org/package=emld + url_git: https://github.com/ropensci/emld +EMLI: + version: 0.2.0 + title: |- + Computationally Efficient Maximum Likelihood Identification of + Linear Dynamical Systems + maintainer: Vytautas Dulskis + description: Provides implementations of computationally efficient maximum likelihood + parameter estimation algorithms for models that represent linear dynamical systems. + Currently, one such algorithm is implemented for the one-dimensional cumulative + structural equation model with shock-error output measurement equation and assumptions + of normality and independence. The corresponding scientific paper is yet to be + published, therefore the relevant reference will be provided later. + date_publication: '2022-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMLI + url_git: '' +EMMAgeo: + version: 0.9.7 + title: End-Member Modelling of Grain-Size Data + maintainer: Michael Dietze + description: |- + End-member modelling analysis of grain-size data is an approach + to unmix a data set's underlying distributions and their contribution to + the data set. EMMAgeo provides deterministic and robust protocols for + that purpose. + date_publication: '2019-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMMAgeo + url_git: '' +emmeans: + version: 1.10.7 + title: Estimated Marginal Means, aka Least-Squares Means + maintainer: Russell V. Lenth + description: |- + Obtain estimated marginal means (EMMs) for many linear, generalized + linear, and mixed models. Compute contrasts or linear functions of EMMs, + trends, and comparisons of slopes. Plots and other displays. + Least-squares means are discussed, and the term "estimated marginal means" + is suggested, in Searle, Speed, and Milliken (1980) Population marginal means + in the linear model: An alternative to least squares means, The American + Statistician 34(4), 216-221 . + date_publication: '2025-01-31' + bug_reports: https://github.com/rvlenth/emmeans/issues + url: https://rvlenth.github.io/emmeans/ + url_cran: https://CRAN.R-project.org/package=emmeans + url_git: '' +EMMIXgene: + version: 0.1.4 + title: |- + A Mixture Model-Based Approach to the Clustering of Microarray + Expression Data + maintainer: Andrew Thomas Jones + description: |- + Provides unsupervised selection and clustering of microarray data + using mixture models. Following the methods described in McLachlan, Bean and + Peel (2002) a subset of genes are selected + based one the likelihood ratio statistic for the test of one versus two + components when fitting mixtures of t-distributions to the expression data + for each gene. The dimensionality of this gene subset is further reduced through + the use of mixtures of factor analyzers, allowing the tissue samples to be + clustered by fitting mixtures of normal distributions. + date_publication: '2024-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMMIXgene + url_git: '' +EMMIXmfa: + version: 2.0.14 + title: Mixture Models with Component-Wise Factor Analyzers + maintainer: Suren Rathnayake + description: |- + We provide functions to fit finite mixtures of multivariate normal or t-distributions to + data with various factor analytic structures adopted for the covariance/scale matrices. The + factor analytic structures available include mixtures of factor analyzers and mixtures of common + factor analyzers. The latter approach is so termed because the matrix of factor loadings is + common to components before the component-specific rotation of the component factors to + make them white noise. Note that the component-factor loadings are not common after + this rotation. Maximum likelihood estimators of model parameters are obtained via the + Expectation-Maximization algorithm. See descriptions of the algorithms used in + McLachlan GJ, Peel D (2000) + McLachlan GJ, Peel D (2000) + McLachlan GJ, Peel D, Bean RW (2003) + McLachlan GJ, Bean RW, Ben-Tovim Jones L (2007) + Baek J, McLachlan GJ, Flack LK (2010) + Baek J, McLachlan GJ (2011) + McLachlan GJ, Baek J, Rathnayake SI (2011) . + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMMIXmfa + url_git: https://github.com/suren-rathnayake/EMMIXmfa +EMMIXSSL: + version: 1.1.1 + title: |- + Semi-Supervised Gaussian Mixture Model with a Missing-Data + Mechanism + maintainer: Ziyang Lyu + description: The algorithm of semi-supervised learning based on finite Gaussian + mixture models with a missing-data mechanism is designed for a fitting g-class + Gaussian mixture model via maximum likelihood (ML). It is proposed to treat the + labels of the unclassified features as missing-data and to introduce a framework + for their missing as in the pioneering work of Rubin (1976) for missing in incomplete + data analysis. This dependency in the missingness pattern can be leveraged to + provide additional information about the optimal classifier as specified by Bayes’ + rule. + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMMIXSSL + url_git: '' +EMMLi: + version: 0.0.3 + title: A Maximum Likelihood Approach to the Analysis of Modularity + maintainer: Tim Lucas + description: |- + Fit models of modularity to morphological landmarks. Perform model + selection on results. Fit models with a single within-module correlation or + with separate within-module correlations fitted to each module. + date_publication: '2017-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMMLi + url_git: https://github.com/timcdlucas/EMMLi +EMMREML: + version: '3.1' + title: Fitting Mixed Models with Known Covariance Structures + maintainer: Deniz Akdemir + description: The main functions are 'emmreml', and 'emmremlMultiKernel'. 'emmreml' + solves a mixed model with known covariance structure using the 'EMMA' algorithm. 'emmremlMultiKernel' + is a wrapper for 'emmreml' to handle multiple random components with known covariance + structures. The function 'emmremlMultivariate' solves a multivariate gaussian + mixed model with known covariance structure using the 'ECM' algorithm. + date_publication: '2015-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMMREML + url_git: '' +emoa: + version: 0.5-3 + title: Evolutionary Multiobjective Optimization Algorithms + maintainer: Olaf Mersmann + description: |- + Collection of building blocks for the design and analysis + of evolutionary multiobjective optimization algorithms. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emoa + url_git: https://github.com/olafmersmann/emoa/ +emoji: + version: 16.0.0 + title: Data and Function to Work with Emojis + maintainer: Emil Hvitfeldt + description: |- + Contains data about emojis with relevant metadata, and + functions to work with emojis when they are in strings. + date_publication: '2024-10-28' + bug_reports: https://github.com/EmilHvitfeldt/emoji/issues + url: https://emilhvitfeldt.github.io/emoji/ + url_cran: https://CRAN.R-project.org/package=emoji + url_git: https://github.com/EmilHvitfeldt/emoji +emojifont: + version: 0.5.5 + title: Emoji and Font Awesome in Graphics + maintainer: Guangchuang Yu + description: |- + An implementation of using emoji and fontawesome for using in both + base and 'ggplot2' graphics. + date_publication: '2021-04-20' + bug_reports: https://github.com/GuangchuangYu/emojifont/issues + url: '' + url_cran: https://CRAN.R-project.org/package=emojifont + url_git: https://github.com/GuangchuangYu/emojifont +emon: + version: 1.3.2 + title: Tools for Environmental and Ecological Survey Design + maintainer: Jon Barry + description: |- + Statistical tools for environmental and ecological surveys. + Simulation-based power and precision analysis; detection probabilities from + different survey designs; visual fast count estimation. + date_publication: '2017-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emon + url_git: '' +emov: + version: 0.1.1 + title: Eye Movement Analysis Package for Fixation and Saccade Detection + maintainer: Simon Schwab + description: Fixation and saccade detection in eye movement recordings. This package + implements a dispersion-based algorithm (I-DT) proposed by Salvucci & Goldberg + (2000) which detects fixation duration and position. + date_publication: '2016-04-04' + bug_reports: https://github.com/schw4b/emov/issues + url: '' + url_cran: https://CRAN.R-project.org/package=emov + url_git: https://github.com/schw4b/emov +EMP: + version: 2.0.5 + title: Expected Maximum Profit Classification Performance Measure + maintainer: Cristian Bravo + description: Functions for estimating EMP (Expected Maximum Profit Measure) in Credit + Risk Scoring and Customer Churn Prediction, according to Verbraken et al (2013, + 2014) , . + date_publication: '2019-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMP + url_git: '' +EMpeaksR: + version: 0.3.1 + title: Conducting the Peak Fitting Based on the EM Algorithm + maintainer: Tarojiro Matsumura + description: 'The peak fitting of spectral data is performed by using the frame + work of EM algorithm. We adapted the EM algorithm for the peak fitting of spectral + data set by considering the weight of the intensity corresponding to the measurement + energy steps (Matsumura, T., Nagamura, N., Akaho, S., Nagata, K., & Ando, Y. + (2019, 2021 and 2023) , + . The package efficiently estimates the parameters + of Gaussian mixture model during iterative calculation between E-step and M-step, + and the parameters are converged to a local optimal solution. This package can + support the investigation of peak shift with two advantages: (1) a large amount + of data can be processed at high speed; and (2) stable and automatic calculation + can be easily performed.' + date_publication: '2023-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMpeaksR + url_git: '' +emphatic: + version: 0.1.8 + title: Exploratory Analysis of Tabular Data using Colour Highlighting + maintainer: Mike Cheng + description: |- + Tools for exploratory analysis of tabular data using colour + highlighting. Highlighting is displayed in any console supporting 'ANSI' + colours, and can be converted to 'HTML', 'typst', 'latex' and 'SVG'. + 'quarto' and 'rmarkdown' rendering are directly supported. It is + also possible to add colour to regular expression matches and + highlight differences between two arbitrary R objects. + date_publication: '2024-05-28' + bug_reports: https://github.com/coolbutuseless/emphatic/issues + url: https://coolbutuseless.github.io/package/emphatic/ + url_cran: https://CRAN.R-project.org/package=emphatic + url_git: https://github.com/coolbutuseless/emphatic +empichar: + version: 1.0.1 + title: |- + Evaluates the Empirical Characteristic Function for Multivariate + Samples + maintainer: Guillermo Basulto-Elias + description: |- + Evaluates the empirical characteristic function of univariate and multivariate samples. + This package uses 'RcppArmadillo' for fast evaluation. It is also possible to export the code to be used in other packages at 'C++' level. + date_publication: '2023-12-08' + bug_reports: https://github.com/gbasulto/empichar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=empichar + url_git: https://github.com/gbasulto/empichar +EmpiricalCalibration: + version: 3.1.4 + title: |- + Routines for Performing Empirical Calibration of Observational + Study Estimates + maintainer: Martijn Schuemie + description: |- + Routines for performing empirical calibration of observational + study estimates. By using a set of negative control hypotheses we can + estimate the empirical null distribution of a particular observational + study setup. This empirical null distribution can be used to compute a + calibrated p-value, which reflects the probability of observing an + estimated effect size when the null hypothesis is true taking both random + and systematic error into account. A similar approach can be used to + calibrate confidence intervals, using both negative and positive controls. + For more details, see Schuemie et al. (2013) and + Schuemie et al. (2018) . + date_publication: '2025-02-14' + bug_reports: https://github.com/OHDSI/EmpiricalCalibration/issues + url: https://ohdsi.github.io/EmpiricalCalibration/ + url_cran: https://CRAN.R-project.org/package=EmpiricalCalibration + url_git: https://github.com/OHDSI/EmpiricalCalibration +emplik: + version: 1.3-2 + title: Empirical Likelihood Ratio for Censored/Truncated Data + maintainer: Mai Zhou + description: |- + Empirical likelihood ratio tests and confidence intervals for means/quantiles/hazards + from possibly censored and/or truncated data. In particular, the empirical likelihood + for the Kaplan-Meier/Nelson-Aalen estimator. Now does AFT regression too. + date_publication: '2024-12-06' + bug_reports: '' + url: https://www.ms.uky.edu/~mai/EmpLik.html + url_cran: https://CRAN.R-project.org/package=emplik + url_git: '' +emplik2: + version: '1.33' + title: |- + Empirical Likelihood Ratio Test for Two-Sample U-Statistics with + Censored Data + maintainer: Mai Zhou + description: |- + Calculates the empirical likelihood ratio and p-value for a mean-type hypothesis + (or multiple mean-type hypotheses) based on two samples with possible censored data. + date_publication: '2024-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emplik2 + url_git: '' +emplikAUC: + version: '0.4' + title: |- + Empirical Likelihood Ratio Test/Confidence Interval for AUC or + pAUC + maintainer: Mai Zhou + description: |- + Test hypotheses and construct confidence intervals for AUC (area under Receiver + Operating Characteristic curve) and pAUC (partial area under ROC curve), from the + given two samples of test data with disease/healthy subjects. The method used is + based on TWO SAMPLE empirical likelihood and PROFILE empirical likelihood, as described in + . + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=emplikAUC + url_git: '' +ems: + version: 1.3.11 + title: |- + Epimed Solutions Collection for Data Editing, Analysis, and + Benchmark of Health Units + maintainer: Lunna Borges + description: |- + Collection of functions related to benchmark with prediction models + for data analysis and editing of clinical and epidemiological data. + date_publication: '2021-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ems + url_git: '' +EMSaov: + version: '2.3' + title: The Analysis of Variance with EMS + maintainer: Eun-Kyung Lee + description: Provides the analysis of variance table including the expected mean + squares (EMS) for various types of experimental design. When some variables are + random effects or we use special experimental design such as nested design, repeated-measures + design, or split-plot design, it is not easy to find the appropriate test, especially + denominator for F-statistic which depends on EMS. + date_publication: '2018-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMSaov + url_git: '' +EMSC: + version: 0.9.4 + title: Extended Multiplicative Signal Correction + maintainer: Kristian Hovde Liland + description: |- + Background correction of spectral like data. Handles variations in + scaling, polynomial baselines, interferents, constituents and replicate variation. + Parameters for corrections are stored for further analysis, and spectra are corrected + accordingly. + date_publication: '2024-03-11' + bug_reports: https://github.com/khliland/EMSC/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=EMSC + url_git: https://github.com/khliland/EMSC/ +EMSNM: + version: '1.0' + title: EM Algorithm for Sigmoid Normal Model + maintainer: Linsui Deng + description: It provides a method based on EM algorithm to estimate the parameter + of a mixture model, Sigmoid-Normal Model, where the samples come from several + normal distributions (also call them subgroups) whose mean is determined by co-variable + Z and coefficient alpha while the variance are homogeneous. Meanwhile, the subgroup + each item belongs to is determined by co-variables X and coefficient eta through + Sigmoid link function which is the extension of Logistic Link function. It uses + bootstrap to estimate the standard error of parameters. When sample is indeed + separable, removing estimation with abnormal sigma, the estimation of alpha is + quite well. I used this method to explore the subgroup structure of HIV patients + and it can be used in other domains where exists subgroup structure. + date_publication: '2019-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMSNM + url_git: '' +EMSS: + version: 1.1.1 + title: Some EM-Type Estimation Methods for the Heckman Selection Model + maintainer: Sang Kyu Lee + description: 'Some EM-type algorithms to estimate parameters for the well-known + Heckman selection model are provided in the package. Such algorithms are as follow: + ECM(Expectation/Conditional Maximization), ECM(NR)(the Newton-Raphson method is + adapted to the ECM) and ECME(Expectation/Conditional Maximization Either). Since + the algorithms are based on the EM algorithm, they also have EM’s main advantages, + namely, stability and ease of implementation. Further details and explanations + of the algorithms can be found in Zhao et al. (2020) .' + date_publication: '2022-01-10' + bug_reports: https://github.com/SangkyuStat/EMSS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EMSS + url_git: https://github.com/SangkyuStat/EMSS +emstreeR: + version: 3.1.2 + title: |- + Tools for Fast Computing and Visualizing Euclidean Minimum + Spanning Trees + maintainer: Allan Quadros + description: |- + Fast and easily computes an Euclidean Minimum Spanning Tree (EMST) from data, + relying on the R API for 'mlpack' - the C++ Machine Learning Library (Curtin et. al., 2013). + 'emstreeR' uses the Dual-Tree Boruvka (March, Ram, Gray, 2010, ), + which is theoretically and empirically the fastest algorithm for computing an EMST. This package also provides + functions and an S3 method for readily visualizing Minimum Spanning Trees (MST) using either the + style of the 'base', 'scatterplot3d', or 'ggplot2' libraries; and functions to export the MST output to shapefiles. + date_publication: '2023-11-14' + bug_reports: https://github.com/allanvc/emstreeR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=emstreeR + url_git: '' +EMT: + version: 1.3.1 + title: |- + Exact Multinomial Test: Goodness-of-Fit Test for Discrete + Multivariate Data + maintainer: Uwe Menzel + description: |- + Goodness-of-fit tests for discrete multivariate data. It is + tested if a given observation is likely to have occurred under + the assumption of an ab-initio model. Monte Carlo methods are provided to + make the package capable of solving high-dimensional problems. + date_publication: '2024-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EMT + url_git: '' +emulator: + version: 1.2-24 + title: Bayesian Emulation of Computer Programs + maintainer: Robin K. S. Hankin + description: |2- + + Allows one to estimate the output of a computer program, + as a function of the input parameters, without actually running it. + The computer program is assumed to be a Gaussian process, whose + parameters are estimated using Bayesian techniques that give a PDF of + expected program output. This PDF is conditional on a training set + of runs, each consisting of a point in parameter space and the model + output at that point. The emphasis is on complex codes that take + weeks or months to run, and that have a large number of undetermined + input parameters; many climate prediction models fall into this + class. The emulator essentially determines Bayesian posterior + estimates of the PDF of the output of a model, conditioned on results + from previous runs and a user-specified prior linear model. The + package includes functionality to evaluate quadratic forms + efficiently. + date_publication: '2024-03-22' + bug_reports: https://github.com/RobinHankin/emulator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=emulator + url_git: https://github.com/RobinHankin/emulator +emuR: + version: 2.5.0 + title: Main Package of the EMU Speech Database Management System + maintainer: Markus Jochim + description: |- + Provide the EMU Speech Database Management System (EMU-SDMS) with + database management, data extraction, data preparation and data + visualization facilities. See + for more details. + date_publication: '2024-03-15' + bug_reports: https://github.com/IPS-LMU/emuR/issues + url: https://ips-lmu.github.io/The-EMU-SDMS-Manual/ + url_cran: https://CRAN.R-project.org/package=emuR + url_git: https://github.com/IPS-LMU/emuR +EncDNA: + version: 1.0.2 + title: Encoding of Nucleotide Sequences into Numeric Feature Vectors + maintainer: Prabina Kumar Meher + description: We describe fifteen different splice site sequence encoding schemes + that have been used in earlier studies for mapping of splice site sequences into + numeric feature vectors. These encoding schemes will also be helpful for transforming + other nucleotide sequences into numeric forms, provided they are of equal length. + These encoding schemes will help the computational biologist working in the field + of classification (binary or multiclass) or prediction involving nucleic acid + sequences of equal length. + date_publication: '2019-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EncDNA + url_git: '' +eNchange: + version: '1.0' + title: Ensemble Methods for Multiple Change-Point Detection + maintainer: Karolos K. Korkas + description: Implements a segmentation algorithm for multiple change-point detection + in univariate time series using the Ensemble Binary Segmentation of Korkas (2020) + . + date_publication: '2020-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eNchange + url_git: '' +encode: + version: 0.3.6 + title: Represent Ordered Lists and Pairs as Strings + maintainer: Tim Bergsma + description: |- + Interconverts between ordered lists and compact string notation. + Useful for capturing code lists, and pair-wise codes and decodes, for text storage. + Analogous to factor levels and labels. Generics encode() and decode() + perform interconversion, while codes() and decodes() extract components of an encoding. + The function encoded() checks whether something is interpretable as an encoding. + If a vector has an encoded 'guide' attribute, as_factor() uses it to coerce to factor. + date_publication: '2019-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=encode + url_git: '' +EncompassTest: + version: '0.22' + title: |- + Direct Multi-Step Forecast Based Comparison of Nested Models via + an Encompassing Test + maintainer: Rong Peng + description: The encompassing test is developed based on multi-step-ahead predictions + of two nested models as in Pitarakis, J. (2023) . + The statistics are standardised to a normal distribution, and the null hypothesis + is that the larger model contains no additional useful information. P-values will + be provided in the output. + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EncompassTest + url_git: '' +encryptedRmd: + version: 0.2.1 + title: Encrypt Html Reports Using 'Libsodium' + maintainer: Dirk Schumacher + description: |- + Create encrypted html files that are fully self contained and do + not require any additional software. Using the package you can encrypt + arbitrary html files and also directly create encrypted 'rmarkdown' html reports. + date_publication: '2020-12-09' + bug_reports: https://github.com/dirkschumacher/encryptedRmd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=encryptedRmd + url_git: https://github.com/dirkschumacher/encryptedRmd +encryptr: + version: 0.1.3 + title: |- + Easily Encrypt and Decrypt Data Frame/Tibble Columns or Files + using RSA Public/Private Keys + maintainer: Ewen Harrison + description: |- + It is important to ensure that sensitive data is protected. + This straightforward package is aimed at the end-user. + Strong RSA encryption using a public/private key pair is used to encrypt data frame or tibble columns. + A public key can be shared to allow others to encrypt data to be sent to you. + This is particularly aimed a healthcare settings so patient data can be pseudonymised. + date_publication: '2019-04-25' + bug_reports: https://github.com/SurgicalInformatics/encryptr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=encryptr + url_git: https://github.com/SurgicalInformatics/encryptr +enderecobr: + version: 0.4.1 + title: |- + Padronizador de Endereços Brasileiros (Brazilian Addresses + Standardizer) + maintainer: Daniel Herszenhut + description: |- + Padroniza endereços brasileiros a partir de diferentes + critérios. Os métodos de padronização incluem apenas manipulações + básicas de strings, não oferecendo suporte a correspondências + probabilísticas entre strings. (Standardizes brazilian addresses using + different criteria. Standardization methods include only basic string + manipulation, not supporting probabilistic matches between strings.) + date_publication: '2025-02-18' + bug_reports: https://github.com/ipeaGIT/enderecobr/issues + url: https://ipeagit.github.io/enderecobr/ + url_cran: https://CRAN.R-project.org/package=enderecobr + url_git: https://github.com/ipeaGIT/enderecobr +endogeneity: + version: 2.1.4 + title: Recursive Two-Stage Models to Address Endogeneity + maintainer: Jing Peng + description: Various recursive two-stage models to address the endogeneity issue + of treatment variables in observational study or mediators in experiments. The + details of the models are discussed in Peng (2023) . + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=endogeneity + url_git: '' +endogenous: + version: '1.0' + title: Classical Simultaneous Equation Models + maintainer: Andrew J. Spieker + description: Likelihood-based approaches to estimate linear regression parameters + and treatment effects in the presence of endogeneity. Specifically, this package + includes James Heckman's classical simultaneous equation models-the sample selection + model for outcome selection bias and hybrid model with structural shift for endogenous + treatment. For more information, see the seminal paper of Heckman (1978) + in which the details of these models are provided. This package accommodates repeated + measures on subjects with a working independence approach. The hybrid model further + accommodates treatment effect modification. + date_publication: '2016-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=endogenous + url_git: '' +endorse: + version: 1.6.2 + title: |- + Bayesian Measurement Models for Analyzing Endorsement + Experiments + maintainer: Yuki Shiraito + description: Fit the hierarchical and non-hierarchical Bayesian measurement models + proposed by Bullock, Imai, and Shapiro (2011) to analyze + endorsement experiments. Endorsement experiments are a survey methodology for + eliciting truthful responses to sensitive questions. This methodology is helpful + when measuring support for socially sensitive political actors such as militant + groups. The model is fitted with a Markov chain Monte Carlo algorithm and produces + the output containing draws from the posterior distribution. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=endorse + url_git: https://github.com/SensitiveQuestions/endorse/ +endoSwitch: + version: 1.0.0 + title: Endogenous Switching Regression Models + maintainer: Bowen Chen + description: Maximum likelihood estimation of endogenous switching regression models + from Heckman (1979) and estimation of treatment effects. + date_publication: '2020-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=endoSwitch + url_git: https://github.com/cbw1243/endoSwitch +endtoend: + version: '2.29' + title: Transmissions and Receptions in an End to End Network + maintainer: Christian E. Galarza + description: Computes the expectation of the number of transmissions and receptions + considering an End-to-End transport model with limited number of retransmissions + per packet. It provides theoretical results and also estimated values based on + Monte Carlo simulations. It is also possible to consider random data and ACK probabilities. + date_publication: '2019-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=endtoend + url_git: '' +energy: + version: 1.7-12 + title: 'E-Statistics: Multivariate Inference via the Energy of Data' + maintainer: Maria Rizzo + description: |- + E-statistics (energy) tests and statistics for multivariate and univariate inference, + including distance correlation, one-sample, two-sample, and multi-sample tests for + comparing multivariate distributions, are implemented. Measuring and testing + multivariate independence based on distance correlation, partial distance correlation, + multivariate goodness-of-fit tests, k-groups and hierarchical clustering based on energy + distance, testing for multivariate normality, distance components (disco) for non-parametric + analysis of structured data, and other energy statistics/methods are implemented. + date_publication: '2024-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=energy + url_git: https://github.com/mariarizzo/energy +EnergyOnlineCPM: + version: '1.0' + title: |- + Distribution Free Multivariate Control Chart Based on Energy + Test + maintainer: Yafei Xu + description: Provides a function for distribution free control chart based on the + change point model, for multivariate statistical process control. The main constituent + of the chart is the energy test that focuses on the discrepancy between empirical + characteristic functions of two random vectors. This new control chart highlights + in three aspects. Firstly, it is distribution free, requiring no knowledge of + the random processes. Secondly, this control chart can monitor mean and variance + simultaneously. Thirdly it is devised for multivariate time series which is more + practical in real data application. Fourthly, it is designed for online detection + (Phase II), which is central for real time surveillance of stream data. For more + information please refer to O. Okhrin and Y.F. Xu (2017) . + date_publication: '2017-10-02' + bug_reports: '' + url: https://sites.google.com/site/EnergyOnlineCPM/ + url_cran: https://CRAN.R-project.org/package=EnergyOnlineCPM + url_git: '' +energyr: + version: 0.1.3 + title: |- + Data Published by the United States Federal Energy Regulatory + Commission + maintainer: Paul Govan + description: |- + Data published by the United States Federal Energy Regulatory Commission including + electric company financial data, natural gas company financial data, + hydropower plant data, liquified natural gas plant data, oil company financial data + natural gas company financial data, and natural gas storage field data. + date_publication: '2024-07-08' + bug_reports: https://github.com/paulgovan/energyr/issues + url: http://paulgovan.github.io/energyr/ + url_cran: https://CRAN.R-project.org/package=energyr + url_git: https://github.com/paulgovan/energyr +enerscape: + version: 1.1.0 + title: Compute Energy Landscapes + maintainer: Emilio Berti + description: Compute energy landscapes using a digital elevation model raster and + body mass of animals. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=enerscape + url_git: '' +enetLTS: + version: 1.1.0 + title: |- + Robust and Sparse Methods for High Dimensional Linear and Binary + and Multinomial Regression + maintainer: Fatma Sevinc Kurnaz + description: Fully robust versions of the elastic net estimator are introduced for + linear and binary and multinomial regression, in particular high dimensional data. + The algorithm searches for outlier free subsets on which the classical elastic + net estimators can be applied. A reweighting step is added to improve the statistical + efficiency of the proposed estimators. Selecting appropriate tuning parameters + for elastic net penalties are done via cross-validation. + date_publication: '2022-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=enetLTS + url_git: '' +english: + version: 1.2-6 + title: Translate Integers into English + maintainer: Bill Venables + description: |- + Allow numbers to be presented in an English language + version, one, two, three, ... Ordinals are also available, + first, second, third, ... and indefinite article choice, "a" or "an". + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=english + url_git: '' +EngrEcon: + version: 1.0.0 + title: |- + Engineering Economics Analysis for Engineering Projects Cost + Analysis + maintainer: Liya Abera + description: |- + Computing economic analysis in civil infrastructure and + ecosystem restoration projects is a typical activity. This package contains Standard + cost engineering and engineering economics methods that are applied to convert between + present, future, and annualized costs. Newnan D. (2020) “Engineering Economic Analysis”. + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EngrEcon + url_git: GitHub() +engression: + version: 0.1.4 + title: Engression Modelling + maintainer: Nicolai Meinshausen + description: |- + Fits engression models for nonlinear distributional regression. Predictors and targets can be univariate or multivariate. Functionality includes estimation of conditional mean, estimation of conditional quantiles, or sampling from the fitted distribution. Training is done full-batch on CPU (the python version offers GPU-accelerated stochastic gradient descent). Based on "Engression: Extrapolation for nonlinear regression?" by Xinwei Shen and Nicolai Meinshausen (2023). Also supports classification (experimental). + . + date_publication: '2023-11-22' + bug_reports: https://github.com/xwshen51/engression/issues + url: '' + url_cran: https://CRAN.R-project.org/package=engression + url_git: https://github.com/xwshen51/engression/ +EngrExpt: + version: 0.1-8 + title: Data sets from "Introductory Statistics for EngineeringExperimentation" + maintainer: Douglas Bates + description: Datasets from Nelson, Coffin and Copeland "IntroductoryStatistics + for Engineering Experimentation" (Elsevier, 2003)with sample code. + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EngrExpt + url_git: '' +ENMeval: + version: 2.0.5 + title: Automated Tuning and Evaluations of Ecological Niche Models + maintainer: Jamie M. Kass + description: 'Runs ecological niche models over all combinations of user-defined + settings (i.e., tuning), performs cross validation to evaluate models, and returns + data tables to aid in selection of optimal model settings that balance goodness-of-fit + and model complexity. Also has functions to partition data spatially (or not) + for cross validation, to plot multiple visualizations of results, to run null + models to estimate significance and effect sizes of performance metrics, and to + calculate range overlap between model predictions, among others. The package was + originally built for Maxent models (Phillips et al. 2006, Phillips et al. 2017), + but the current version allows possible extensions for any modeling algorithm. + The extensive vignette, which guides users through most package functionality + but unfortunately has a file size too big for CRAN, can be found here on the package''s + Github Pages website: .' + date_publication: '2025-02-11' + bug_reports: '' + url: https://jamiemkass.github.io/ENMeval/ + url_cran: https://CRAN.R-project.org/package=ENMeval + url_git: '' +enmpa: + version: 0.1.9 + title: Ecological Niche Modeling using Presence-Absence Data + maintainer: Luis F. Arias-Giraldo + description: |- + A set of tools to perform Ecological Niche Modeling with + presence-absence data. It includes algorithms for data partitioning, + model fitting, calibration, evaluation, selection, and prediction. + Other functions help to explore signals of ecological niche using univariate + and multivariate analyses, and model features such as variable response + curves and variable importance. Unique characteristics of this package are + the ability to exclude models with concave quadratic responses, and the + option to clamp model predictions to specific variables. These tools are + implemented following principles proposed in + Cobos et al., (2022) , + Cobos et al., (2019) , + and Peterson et al., (2008) . + date_publication: '2024-12-20' + bug_reports: https://github.com/Luisagi/enmpa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=enmpa + url_git: https://github.com/Luisagi/enmpa +enmSdmX: + version: 1.2.10 + title: Species Distribution Modeling and Ecological Niche Modeling + maintainer: Adam B. Smith + description: |- + Implements species distribution modeling and ecological niche + modeling, including: bias correction, spatial cross-validation, model + evaluation, raster interpolation, biotic "velocity" (speed and + direction of movement of a "mass" represented by a raster), interpolating + across a time series of rasters, and use of spatially imprecise records. + The heart of the package is a set of "training" functions which + automatically optimize model complexity based number of available + occurrences. These algorithms include MaxEnt, MaxNet, boosted regression + trees/gradient boosting machines, generalized additive models, + generalized linear models, natural splines, and random forests. To enhance + interoperability with other modeling packages, no new classes are created. + The package works with 'PROJ6' geodetic objects and coordinate reference + systems. + date_publication: '2024-12-11' + bug_reports: https://github.com/adamlilith/enmSdmX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=enmSdmX + url_git: https://github.com/adamlilith/enmSdmX +ENMTools: + version: 1.1.2 + title: Analysis of Niche Evolution using Niche and Distribution Models + maintainer: Dan Warren + description: Constructing niche models and analyzing patterns of niche evolution. Acts + as an interface for many popular modeling algorithms, and allows users to conduct + Monte Carlo tests to address basic questions in evolutionary ecology and biogeography. Warren, + D.L., R.E. Glor, and M. Turelli (2008) + Glor, R.E., and D.L. Warren (2011) Warren, + D.L., R.E. Glor, and M. Turelli (2010) + Cardillo, M., and D.L. Warren (2016) D.L. Warren, L.J. + Beaumont, R. Dinnage, and J.B. Baumgartner (2019) . + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ENMTools + url_git: '' +enpls: + version: '6.1' + title: Ensemble Partial Least Squares Regression + maintainer: Nan Xiao + description: |- + An algorithmic framework for measuring feature importance, + outlier detection, model applicability domain evaluation, + and ensemble predictive modeling with (sparse) + partial least squares regressions. + date_publication: '2019-05-18' + bug_reports: https://github.com/nanxstats/enpls/issues + url: https://nanx.me/enpls/ + url_cran: https://CRAN.R-project.org/package=enpls + url_git: https://github.com/nanxstats/enpls +EnrichIntersect: + version: '0.7' + title: Enrichment Analysis and Intersecting Sankey Diagram + maintainer: Zhi Zhao + description: A flexible tool for enrichment analysis based on user-defined sets. + It allows users to perform over-representation analysis of the custom sets among + any specified ranked feature list, hence making enrichment analysis applicable + to various types of data from different scientific fields. 'EnrichIntersect' also + enables an interactive means to visualize identified associations based on, for + example, the mix-lasso model (Zhao et al., 2022 ) + or similar methods. + date_publication: '2024-03-14' + bug_reports: https://github.com/ocbe-uio/EnrichIntersect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EnrichIntersect + url_git: https://github.com/ocbe-uio/EnrichIntersect +enrichR: + version: '3.4' + title: Provides an R Interface to 'Enrichr' + maintainer: Wajid Jawaid + description: Provides an R interface to all 'Enrichr' databases. 'Enrichr' is a + web-based tool for analysing gene sets and returns any enrichment of common annotated + biological features. Quoting from their website 'Enrichment analysis is a computational + method for inferring knowledge about an input gene set by comparing it to annotated + gene sets representing prior biological knowledge.' See + for further details. + date_publication: '2025-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=enrichR + url_git: '' +enrichwith: + version: 0.3.1 + title: Methods to Enrich R Objects with Extra Components + maintainer: Ioannis Kosmidis + description: Provides the "enrich" method to enrich list-like R objects with new, + relevant components. The current version has methods for enriching objects of + class 'family', 'link-glm', 'lm', 'glm' and 'betareg'. The resulting objects preserve + their class, so all methods associated with them still apply. The package also + provides the 'enriched_glm' function that has the same interface as 'glm' but + results in objects of class 'enriched_glm'. In addition to the usual components + in a `glm` object, 'enriched_glm' objects carry an object-specific simulate method + and functions to compute the scores, the observed and expected information matrix, + the first-order bias, as well as model densities, probabilities, and quantiles + at arbitrary parameter values. The package can also be used to produce customizable + source code templates for the structured implementation of methods to compute + new components and enrich arbitrary objects. + date_publication: '2020-01-10' + bug_reports: https://github.com/ikosmidis/enrichwith/issues + url: '' + url_cran: https://CRAN.R-project.org/package=enrichwith + url_git: https://github.com/ikosmidis/enrichwith +EnsCat: + version: '1.1' + title: Clustering of Categorical Data + maintainer: Saeid Amiri + description: |- + An implementation of the clustering methods of categorical data + discussed in Amiri, S., Clarke, B., and Clarke, J. (2015). Clustering categorical + data via ensembling dissimilarity matrices. Preprint . + date_publication: '2017-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnsCat + url_git: '' +EnsembleBase: + version: 1.0.4 + title: |- + Extensible Package for Parallel, Batch Training of Base Learners + for Ensemble Modeling + maintainer: Alireza S. Mahani + description: Extensible S4 classes and methods for batch training of regression + and classification algorithms such as Random Forest, Gradient Boosting Machine, + Neural Network, Support Vector Machines, K-Nearest Neighbors, Penalized Regression + (L1/L2), and Bayesian Additive Regression Trees. These algorithms constitute a + set of 'base learners', which can subsequently be combined together to form ensemble + predictions. This package provides cross-validation wrappers to allow for downstream + application of ensemble integration techniques, including best-error selection. + All base learner estimation objects are retained, allowing for repeated prediction + calls without the need for re-training. For large problems, an option is provided + to save estimation objects to disk, along with prediction methods that utilize + these objects. This allows users to train and predict with large ensembles of + base learners without being constrained by system RAM. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnsembleBase + url_git: '' +ensembleBMA: + version: 5.1.8 + title: |- + Probabilistic Forecasting using Ensembles and Bayesian Model + Averaging + maintainer: Chris Fraley + description: |- + Bayesian Model Averaging to create probabilistic forecasts + from ensemble forecasts and weather observations + . + date_publication: '2022-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ensembleBMA + url_git: '' +EnsembleCV: + version: '0.8' + title: |- + Extensible Package for Cross-Validation-Based Integration of + Base Learners + maintainer: Alireza S. Mahani + description: Extends the base classes and methods of EnsembleBase package for cross-validation-based + integration of base learners. Default implementation calculates average of repeated + CV errors, and selects the base learner / configuration with minimum average error. + The package takes advantage of the file method provided in EnsembleBase package + for writing estimation objects to disk in order to circumvent RAM bottleneck. + Special save and load methods are provided to allow estimation objects to be saved + to permanent files on disk, and to be loaded again into temporary files in a later + R session. The package can be extended, e.g. by adding variants of the current + implementation. + date_publication: '2016-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnsembleCV + url_git: '' +ensembleMOS: + version: 0.8.2 + title: Ensemble Model Output Statistics + maintainer: Sandor Baran + description: |- + Ensemble Model Output Statistics to create probabilistic + forecasts from ensemble forecasts and weather observations. + date_publication: '2018-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ensembleMOS + url_git: '' +EnsemblePCReg: + version: 1.1.4 + title: |- + Extensible Package for Principal-Component-Regression-Based + Heterogeneous Ensemble Meta-Learning + maintainer: Alireza S. Mahani + description: Extends the base classes and methods of 'EnsembleBase' package for + Principal-Components-Regression-based (PCR) integration of base learners. Default + implementation uses cross-validation error to choose the optimal number of PC + components for the final predictor. The package takes advantage of the file method + provided in 'EnsembleBase' package for writing estimation objects to disk in order + to circumvent RAM bottleneck. Special save and load methods are provided to allow + estimation objects to be saved to permanent files on disk, and to be loaded again + into temporary files in a later R session. Users and developers can extend the + package by extending the generic methods and classes provided in 'EnsembleBase' + package as well as this package. + date_publication: '2022-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnsemblePCReg + url_git: '' +EnsemblePenReg: + version: '0.7' + title: |- + Extensible Classes and Methods for Penalized-Regression-Based + Integration of Base Learners + maintainer: Alireza S. Mahani + description: Extending the base classes and methods of EnsembleBase package for + Penalized-Regression-based (Ridge and Lasso) integration of base learners. Default + implementation uses cross-validation error to choose the optimal lambda (shrinkage + parameter) for the final predictor. The package takes advantage of the file method + provided in EnsembleBase package for writing estimation objects to disk in order + to circumvent RAM bottleneck. Special save and load methods are provided to allow + estimation objects to be saved to permanent files on disk, and to be loaded again + into temporary files in a later R session. Users and developers can extend the + package by extending the generic methods and classes provided in EnsembleBase + package as well as this package. + date_publication: '2016-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnsemblePenReg + url_git: '' +ensemblepp: + version: 1.0-0 + title: Ensemble Postprocessing Data Sets + maintainer: Jakob Messner + description: Data sets for the chapter "Ensemble Postprocessing with R" of the book + Stephane Vannitsem, Daniel S. Wilks, and Jakob W. Messner (2018) "Statistical + Postprocessing of Ensemble Forecasts", Elsevier, 362pp. These data sets contain + temperature and precipitation ensemble weather forecasts and corresponding observations + at Innsbruck/Austria. Additionally, a demo with the full code of the book chapter + is provided. + date_publication: '2019-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ensemblepp + url_git: '' +ensembleTax: + version: 1.1.1 + title: Ensemble Taxonomic Assignments of Amplicon Sequencing Data + maintainer: Dylan Catlett + description: |- + Creates ensemble taxonomic assignments of amplicon sequencing data + in R using outputs of multiple taxonomic assignment algorithms and/or + reference databases. Includes flexible algorithms for mapping taxonomic + nomenclatures onto one another and for computing ensemble taxonomic + assignments. + date_publication: '2021-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ensembleTax + url_git: '' +enshuman: + version: 1.0.0 + title: Human Gene Annotation Data from 'Ensembl' + maintainer: Thorhildur Juliusdottir + description: Gene information from 'Ensembl' genome builds 'GRCh38.p14' and 'GRCh37.p13' + to use with the 'topr' package. The datasets were originally downloaded from + and + and converted into the format required by the 'topr' package. See + to see the required format. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=enshuman + url_git: '' +ensr: + version: 0.1.0 + title: Elastic Net SearcheR + maintainer: Peter DeWitt + description: |- + Elastic net regression models are controlled by two parameters, + lambda, a measure of shrinkage, and alpha, a metric defining the model's + location on the spectrum between ridge and lasso regression. + glmnet provides tools for selecting lambda via cross + validation but no automated methods for selection of alpha. Elastic Net + SearcheR automates the simultaneous selection of both lambda and alpha. + Developed, in part, with support by NICHD R03 HD094912. + date_publication: '2019-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ensr + url_git: https://github.com/dewittpe/ensr +entropart: + version: 1.6-16 + title: Entropy Partitioning to Measure Diversity + maintainer: Eric Marcon + description: |- + Measurement and partitioning of diversity, based on Tsallis entropy, following Marcon and Herault (2015) . + 'entropart' provides functions to calculate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity. + Estimation-bias corrections are available. + date_publication: '2025-02-07' + bug_reports: https://github.com/EricMarcon/entropart/issues/ + url: https://ericmarcon.github.io/entropart/ + url_cran: https://CRAN.R-project.org/package=entropart + url_git: https://github.com/EricMarcon/entropart/ +EntropicStatistics: + version: 0.1.0 + title: Functions Based on Entropic Statistics + maintainer: Jialin Zhang (JZ) + description: Contains methods for data analysis in entropic perspective. These entropic + perspective methods are nonparametric, and perform better on non-ordinal data. + Currently, the package has a function HeatMap() for visualizing distributional + characteristics among multiple populations (groups). + date_publication: '2023-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EntropicStatistics + url_git: '' +entropy: + version: 1.3.1 + title: Estimation of Entropy, Mutual Information and Related Quantities + maintainer: Korbinian Strimmer + description: |- + Implements various estimators of entropy for discrete random + variables, including the shrinkage estimator by Hausser and Strimmer (2009), + the maximum likelihood and the Millow-Madow estimator, various Bayesian + estimators, and the Chao-Shen estimator. It also offers an R interface to the + NSB estimator. Furthermore, the package provides functions for estimating the + Kullback-Leibler divergence, the chi-squared divergence, mutual information, + and the chi-squared divergence of independence. It also computes the + G statistic and the chi-squared statistic and corresponding p-values. + Furthermore, there are functions for discretizing continuous random variables. + date_publication: '2021-10-02' + bug_reports: '' + url: https://strimmerlab.github.io/software/entropy/ + url_cran: https://CRAN.R-project.org/package=entropy + url_git: '' +EntropyEstimation: + version: 1.2.1 + title: Estimation of Entropy and Related Quantities + maintainer: Michael Grabchak + description: Contains methods for the estimation of Shannon's entropy, variants + of Renyi's entropy, mutual information, Kullback-Leibler divergence, and generalized + Simpson's indices. The estimators used have a bias that decays exponentially fast. + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EntropyEstimation + url_git: '' +EntropyMCMC: + version: 1.0.4 + title: |- + MCMC Simulation and Convergence Evaluation using Entropy and + Kullback-Leibler Divergence Estimation + maintainer: Didier Chauveau + description: Tools for Markov Chain Monte Carlo (MCMC) simulation and performance + analysis. Simulate MCMC algorithms including adaptive MCMC, evaluate their convergence + rate, and compare candidate MCMC algorithms for a same target density, based on + entropy and Kullback-Leibler divergence criteria. MCMC algorithms can be simulated + using provided functions, or imported from external codes. This package is based + upon work starting with Chauveau, D. and Vandekerkhove, P. (2013) + and next articles. + date_publication: '2019-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EntropyMCMC + url_git: '' +entrymodels: + version: 0.2.1 + title: Estimate Entry Models + maintainer: Guilherme Jardim + description: Tools for measuring empirically the effects of entry in concentrated + markets, based in Bresnahan and Reiss (1991) . + date_publication: '2020-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=entrymodels + url_git: '' +envalysis: + version: 0.7.0 + title: Miscellaneous Functions for Environmental Analyses + maintainer: Zacharias Steinmetz + description: |- + Small toolbox for data analyses in environmental chemistry and + ecotoxicology. Provides, for example, calibration() to calculate calibration + curves and corresponding limits of detection (LODs) and limits of + quantification (LOQs) according to German DIN 32645 (2008). texture() makes + it easy to estimate soil particle size distributions from hydrometer + measurements (ASTM D422-63, 2007). + date_publication: '2024-03-20' + bug_reports: https://github.com/zsteinmetz/envalysis/issues + url: https://zsteinmetz.de/envalysis/ + url_cran: https://CRAN.R-project.org/package=envalysis + url_git: https://github.com/zsteinmetz/envalysis +EnvCpt: + version: 1.1.3 + title: |- + Detection of Structural Changes in Climate and Environment Time + Series + maintainer: Rebecca Killick + description: Tools for automatic model selection and diagnostics for Climate and + Environmental data. In particular the envcpt() function does automatic model + selection between a variety of trend, changepoint and autocorrelation models. The + envcpt() function should be your first port of call. + date_publication: '2021-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnvCpt + url_git: https://github.com/rkillick/EnvCpt/ +envDocument: + version: 2.4.1 + title: Document the R Working Environment + maintainer: Donald Jackson + description: |- + Prints out information about the R working environment + (system, R version,loaded and attached packages and versions) from a single + function "env_doc()". Optionally adds information on git repository, + tags, commits and remotes (if available). + date_publication: '2019-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=envDocument + url_git: https://github.com/dgJacks0n/envDocument +enveomics.R: + version: 1.10.0 + title: Various Utilities for Microbial Genomics and Metagenomics + maintainer: Luis M. Rodriguez-R + description: |- + A collection of functions for microbial ecology and other + applications of genomics and metagenomics. Companion package for the + Enveomics Collection (Rodriguez-R, L.M. and Konstantinidis, K.T., 2016 + ). + date_publication: '2025-02-11' + bug_reports: '' + url: http://enve-omics.ce.gatech.edu/enveomics/ + url_cran: https://CRAN.R-project.org/package=enveomics.R + url_git: '' +envi: + version: 1.0.0 + title: |- + Environmental Interpolation using Spatial Kernel Density + Estimation + maintainer: Ian D. Buller + description: |- + Estimates an ecological niche using occurrence data, covariates, and kernel + density-based estimation methods. For a single species with presence and absence data, + the 'envi' package uses the spatial relative risk function that is estimated using the + 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: + Davies et al. (2018) . Details about kernel density estimation can + be found in J. F. Bithell (1990) . More information about + relative risk functions using kernel density estimation can be found in J. F. Bithell + (1991) . + date_publication: '2024-11-06' + bug_reports: https://github.com/lance-waller-lab/envi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=envi + url_git: https://github.com/lance-waller-lab/envi +enviGCMS: + version: 0.8.0 + title: GC/LC-MS Data Analysis for Environmental Science + maintainer: Miao YU + description: Gas/Liquid Chromatography-Mass Spectrometer(GC/LC-MS) Data Analysis + for Environmental Science. This package covered topics such molecular isotope + ratio, matrix effects and Short-Chain Chlorinated Paraffins analysis etc. in environmental + analysis. + date_publication: '2025-01-14' + bug_reports: https://github.com/yufree/enviGCMS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=enviGCMS + url_git: https://github.com/yufree/enviGCMS +enviPat: + version: '2.6' + title: |- + Isotope Pattern, Profile and Centroid Calculation for Mass + Spectrometry + maintainer: Martin Loos + description: |- + Fast and very memory-efficient calculation of isotope patterns, + subsequent convolution to theoretical envelopes (profiles) plus valley + detection and centroidization or intensoid calculation. Batch processing, + resolution interpolation, wrapper, adduct calculations and molecular + formula parsing. + Loos, M., Gerber, C., Corona, F., Hollender, J., Singer, H. (2015) + . + date_publication: '2022-10-21' + bug_reports: https://github.com/blosloos/enviPat/issues + url: https://www.envipat.eawag.ch/ + url_cran: https://CRAN.R-project.org/package=enviPat + url_git: '' +envir: + version: 0.3.0 + title: Manage R Environments Better + maintainer: Tomasz Kalinowski + description: 'Provides a small set of functions for managing R environments, with + defaults designed to encourage usage patterns that scale well to larger code bases. + It provides: import_from(), a flexible way to assign bindings that defaults to + the current environment; include(), a vectorized alternative to base::source() + that also default to the current environment; and attach_eval() and attach_source(), + a way to evaluate expressions in attached environments. Together, these (and other) + functions pair to provide a robust alternative to base::library() and base::source().' + date_publication: '2024-04-19' + bug_reports: https://github.com/t-kalinowski/envir/issues + url: https://t-kalinowski.github.io/envir/ + url_cran: https://CRAN.R-project.org/package=envir + url_git: '' +envirem: + version: '3.0' + title: Generation of ENVIREM Variables + maintainer: Pascal Title + description: Generation of bioclimatic rasters that are complementary to the typical + 19 bioclim variables. + date_publication: '2023-08-25' + bug_reports: https://github.com/ptitle/envirem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=envirem + url_git: https://github.com/ptitle/envirem +EnviroPRA2: + version: 1.0.1 + title: Environmental Probabilistic Risk Assessment Tools + maintainer: Fernando Barrio-Parra + description: 'It contains functions for dose calculation for different routes, fitting + data to probability distributions, random number generation (Monte Carlo simulation) + and calculation of systemic and carcinogenic risks. For more information see the + publication: Barrio-Parra et al. (2019) "Human-health probabilistic risk assessment: + the role of exposure factors in an urban garden scenario" .' + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnviroPRA2 + url_git: '' +envnames: + version: 0.4.1 + title: Keep Track of User-Defined Environment Names + maintainer: Daniel Mastropietro + description: |- + Set of functions to keep track and find objects in user-defined environments + by identifying environments by name --which cannot be retrieved with the built-in function environmentName(). + The package also provides functionality to obtain simplified information about function calling chains + and to get an object's memory address. + date_publication: '2020-12-08' + bug_reports: https://github.com/mastropi/envnames/issues + url: '' + url_cran: https://CRAN.R-project.org/package=envnames + url_git: https://github.com/mastropi/envnames +EnvNicheR: + version: '1.5' + title: Niche Estimation + maintainer: Castor Guisande Gonzalez + description: 'A plot overlying the niche of multiple species is obtained: 1) to + determine the niche conditions which favor a higher species richness, 2) to create + a box plot with the range of environmental variables of the species, 3) to obtain + a list of species in an area of the niche selected by the user and, 4) to estimate + niche overlap among the species.' + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnvNicheR + url_git: '' +EnvNJ: + version: 0.1.3 + title: Whole Genome Phylogenies Using Sequence Environments + maintainer: Juan Carlos Aledo + description: |- + Contains utilities for the analysis of protein sequences in a phylogenetic context. + Allows the generation of phylogenetic trees base on protein sequences in an alignment-independent way. + Two different methods have been implemented. One approach is based on the frequency analysis of n-grams, + previously described in Stuart et al. (2002) . The other approach is based on the species-specific neighborhood preference around amino acids. Features include the conversion of a protein set into a vector + reflecting these neighborhood preferences, pairwise distances (dissimilarity) between these vectors, + and the generation of trees based on these distance matrices. + date_publication: '2021-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EnvNJ + url_git: '' +envoutliers: + version: 1.1.0 + title: Methods for Identification of Outliers in Environmental Data + maintainer: Martina Campulova + description: 'Three semi-parametric methods for detection of outliers in environmental + data based on kernel regression and subsequent analysis of smoothing residuals. + The first method (Campulova, Michalek, Mikuska and Bokal (2018) ) + analyzes the residuals using changepoint analysis, the second method is based + on control charts (Campulova, Veselik and Michalek (2017) ) + and the third method (Holesovsky, Campulova and Michalek (2018) ) + analyzes the residuals using extreme value theory (Holesovsky, Campulova and Michalek + (2018) ).' + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=envoutliers + url_git: '' +envstat: + version: 0.0.3 + title: Configurable Reporting on your External Compute Environment + maintainer: Mark Sellors + description: |- + Runs a series of configurable tests against a user's compute + environment. This can be used for checking that things like a specific + directory or an environment variable is available before you start an analysis. + Alternatively, you can use the package's situation report when filing error + reports with your compute infrastructure. + date_publication: '2022-06-14' + bug_reports: https://github.com/sellorm/envstat/issues + url: https://envstat.sellorm.com + url_cran: https://CRAN.R-project.org/package=envstat + url_git: '' +EnvStats: + version: 3.0.0 + title: Package for Environmental Statistics, Including US EPA Guidance + maintainer: Alexander Kowarik + description: |- + Graphical and statistical analyses of environmental data, with + focus on analyzing chemical concentrations and physical parameters, usually in + the context of mandated environmental monitoring. Major environmental + statistical methods found in the literature and regulatory guidance documents, + with extensive help that explains what these methods do, how to use them, + and where to find them in the literature. Numerous built-in data sets from + regulatory guidance documents and environmental statistics literature. Includes + scripts reproducing analyses presented in the book "EnvStats: An R Package for + Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, + ). + date_publication: '2024-08-24' + bug_reports: '' + url: https://alexkowa.github.io/EnvStats/ + url_cran: https://CRAN.R-project.org/package=EnvStats + url_git: https://github.com/alexkowa/EnvStats +envvar: + version: 0.1.2 + title: |- + Make Working with Environment Variables Easier and More + Consistent + maintainer: Brian Connelly + description: |- + A collection of functions that allows for easy and consistent use + of environment variables. This includes setting, checking, retrieving, + transforming, and validating values stored in environment variables. + date_publication: '2024-08-17' + bug_reports: https://github.com/briandconnelly/envvar/issues + url: https://briandconnelly.github.io/envvar/ + url_cran: https://CRAN.R-project.org/package=envvar + url_git: https://github.com/briandconnelly/envvar +eoa3: + version: 1.0.0.2 + title: |- + Wildlife Mortality Estimator for Low Fatality Rates and + Imperfect Detection + maintainer: Daniel Dalthorp + description: Evidence of Absence software (EoA) is a user-friendly application for + estimating bird and bat fatalities at wind farms and designing search protocols. + The software is particularly useful in addressing whether the number of fatalities + has exceeded a given threshold and what search parameters are needed to give assurance + that thresholds were not exceeded. The models are applicable even when zero carcasses + have been found in searches, following Huso et al. (2015) , + Dalthorp et al. (2017) , and Dalthorp and Huso (2015) . + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eoa3 + url_git: '' +eodhdR2: + version: 0.5.1 + title: Official R API for Fetching Data from 'EODHD' + maintainer: Marcelo S. Perlin + description: |- + Second and backward-incompatible version of R package 'eodhd' , extended with a cache and quota system, + also offering functions for cleaning and aggregating the financial data. + date_publication: '2024-09-12' + bug_reports: https://github.com/EodHistoricalData/R-Library-for-financial-data-2024/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eodhdR2 + url_git: https://github.com/EodHistoricalData/R-Library-for-financial-data-2024 +eoffice: + version: 0.2.2 + title: |- + Export or Graph and Tables to 'Microsoft' Office and Import + Figures and Tables + maintainer: Kai Guo + description: |- + Provides wrap functions to export and import graphics and + data frames in R to 'microsoft' office. And This package also + provide write out figures with lots of different formats. + Since people may work on the platform without GUI support, the package + also provide function to easily write out figures + to lots of different type of formats. Now this package provide function + to extract colors from all types of figures and pdf files. + date_publication: '2022-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eoffice + url_git: '' +eoR: + version: 0.4.0 + title: Data Management Package (Exposure and Occurrence Data in R) + maintainer: Rainer Walke + description: |- + This data management package provides some helper + classes for publicly available data sources (HMD, DESTATIS) in + Demography. Similar to ideas developed in the Bioconductor + project we strive to encapsulate data in easy + to use S4 objects. + If original data is provided in a text file, the resulting S4 + object contains all information from that text file. But the + information is somehow structured (header, footer, etc). + Further the classes provide methods to make a subset for selected + calendar years or selected regions. The resulting subset + objects still contain the original header and footer information. + date_publication: '2019-11-10' + bug_reports: '' + url: https://github.molgen.mpg.de/walke/eoR + url_cran: https://CRAN.R-project.org/package=eoR + url_git: '' +epade: + version: 0.5.1 + title: Easy Plots + maintainer: Andreas Schulz + description: A collection of nice plotting functions directly from a data.frame + with limited customisation possibilities. + date_publication: '2022-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epade + url_git: '' +epandist: + version: 1.1.1 + title: |- + Statistical Functions for the Censored and Uncensored + Epanechnikov Distribution + maintainer: Mathias Borritz Milfeldt + description: Analyzing censored variables usually requires the use of optimization + algorithms. This package provides an alternative algebraic approach to the task + of determining the expected value of a random censored variable with a known censoring + point. Likewise this approach allows for the determination of the censoring point + if the expected value is known. These results are derived under the assumption + that the variable follows an Epanechnikov kernel distribution with known mean + and range prior to censoring. Statistical functions related to the uncensored + Epanechnikov distribution are also provided by this package. + date_publication: '2016-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epandist + url_git: '' +epanet2toolkit: + version: 1.0.8 + title: Call 'EPANET' Functions to Simulate Pipe Networks + maintainer: Bradley Eck + description: |- + Enables simulation of water piping networks using 'EPANET'. + The package provides functions from the 'EPANET' programmer's toolkit as R + functions so that basic or customized simulations can be carried out from R. + The package uses 'EPANET' version 2.2 from Open Water Analytics + . + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epanet2toolkit + url_git: https://github.com/bradleyjeck/epanet2toolkit +epanetReader: + version: 0.7.3 + title: Read Epanet Files into R + maintainer: Bradley Eck + description: |- + Reads water network simulation data in 'Epanet' text-based + '.inp' and '.rpt' formats into R. Also reads results from 'Epanet-msx'. + Provides basic summary information and plots. The README file has a + quick introduction. See + for more information on the Epanet software for modeling + hydraulic and water quality behavior of water piping systems. + date_publication: '2018-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epanetReader + url_git: https://github.com/bradleyjeck/epanetReader +epca: + version: 1.1.0 + title: Exploratory Principal Component Analysis + maintainer: Fan Chen + description: |2- + + Exploratory principal component analysis for large-scale dataset, including sparse principal component analysis and sparse matrix approximation. + date_publication: '2023-07-10' + bug_reports: https://github.com/fchen365/epca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epca + url_git: https://github.com/fchen365/epca +ePCR: + version: 0.11.0 + title: Ensemble Penalized Cox Regression for Survival Prediction + maintainer: Teemu Daniel Laajala + description: The top-performing ensemble-based Penalized Cox Regression (ePCR) framework + developed during the DREAM 9.5 mCRPC Prostate Cancer Challenge + presented in Guinney J, Wang T, Laajala TD, et al. (2017) + is provided here-in, together with the corresponding follow-up work. While initially + aimed at modeling the most advanced stage of prostate cancer, metastatic Castration-Resistant + Prostate Cancer (mCRPC), the modeling framework has subsequently been extended + to cover also the non-metastatic form of advanced prostate cancer (CRPC). Readily + fitted ensemble-based model S4-objects are provided, and a simulated example dataset + based on a real-life cohort is provided from the Turku University Hospital, to + illustrate the use of the package. Functionality of the ePCR methodology relies + on constructing ensembles of strata in patient cohorts and averaging over them, + with each ensemble member consisting of a highly optimized penalized/regularized + Cox regression model. Various cross-validation and other modeling schema are provided + for constructing novel model objects. + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ePCR + url_git: '' +epe4md: + version: 0.1.4 + title: |- + EPE's 4MD Model to Forecast the Adoption of Distributed + Generation + maintainer: Gabriel Konzen + description: EPE's (Empresa de Pesquisa Energética) 4MD (Modelo de Mercado da Micro + e Minigeração Distribuída - Micro and Mini Distributed Generation Market Model) + model to forecast the adoption of Distributed Generation. Given the user's assumptions, + it is possible to estimate how many consumer units will have distributed generation + in Brazil over the next 10 years, for example. In addition, it is possible to + estimate the installed capacity, the amount of investments that will be made in + the country and the monthly energy contribution of this type of generation. . + date_publication: '2023-07-05' + bug_reports: '' + url: https://epe-gov-br.github.io/epe4md/ + url_cran: https://CRAN.R-project.org/package=epe4md + url_git: '' +eph: + version: 1.0.2 + title: |- + Argentina's Permanent Household Survey Data and Manipulation + Utilities + maintainer: Carolina Pradier + description: |- + Tools to download and manipulate the Permanent Household Survey from Argentina + (EPH is the Spanish acronym for Permanent Household Survey). + e.g: get_microdata() for downloading the datasets, get_poverty_lines() for downloading the official poverty baskets, + calculate_poverty() for the calculation of stating if a household is in poverty or not, following the official methodology. + organize_panels() is used to concatenate observations from different periods, and organize_labels() + adds the official labels to the data. The implemented methods are based on INDEC (2016) . + As this package works with the argentinian Permanent Household Survey and its main audience is from this country, + the documentation was written in Spanish. + date_publication: '2024-06-23' + bug_reports: https://github.com/ropensci/eph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eph + url_git: https://github.com/ropensci/eph +Epi: + version: '2.59' + title: Statistical Analysis in Epidemiology + maintainer: Bendix Carstensen + description: |- + Functions for demographic and epidemiological analysis in + the Lexis diagram, i.e. register and cohort follow-up data. In + particular representation, manipulation, rate estimation and + simulation for multistate data - the Lexis suite of functions, which + includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. + Contains functions for Age-Period-Cohort and Lee-Carter modeling and + a function for interval censored data and some useful functions for + tabulation and plotting, as well as a number of epidemiological data + sets. + date_publication: '2025-01-13' + bug_reports: '' + url: http://bendixcarstensen.com/Epi/ + url_cran: https://CRAN.R-project.org/package=Epi + url_git: '' +epibasix: + version: '1.5' + title: |- + Elementary Epidemiological Functions for Epidemiology and + Biostatistics + maintainer: Michael A Rotondi + description: "Contains elementary tools for analysis of\ncommon epidemiological + problems, ranging from sample size\nestimation, through 2x2 contingency table + analysis and basic\nmeasures of agreement (kappa, sensitivity/specificity).\nAppropriate + print and summary statements are also written to\nfacilitate interpretation wherever + possible. Source code is \tcommented throughout to facilitate modification. The + target audience includes advanced undergraduate and graduate students\nin epidemiology + or biostatistics courses, and clinical researchers." + date_publication: '2018-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epibasix + url_git: '' +epicasting: + version: 0.1.0 + title: |- + Ewnet: An Ensemble Wavelet Neural Network for Forecasting and + Epicasting + maintainer: Tanujit Chakraborty + description: |- + Method and tool for generating time series forecasts using + an ensemble wavelet-based auto-regressive neural network architecture. This method provides + additional support of exogenous variables and also generates confidence interval. This + package provides EWNet model for time series forecasting based on the algorithm by + Panja, et al. (2022) and Panja, et al. (2023) . + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epicasting + url_git: '' +epichains: + version: 0.1.1 + title: |- + Simulating and Analysing Transmission Chain Statistics Using + Branching Process Models + maintainer: James M. Azam + description: |- + Provides methods to simulate and analyse the size and length + of branching processes with an arbitrary offspring distribution. These + can be used, for example, to analyse the distribution of chain sizes + or length of infectious disease outbreaks, as discussed in Farrington + et al. (2003) . + date_publication: '2024-10-14' + bug_reports: https://github.com/epiverse-trace/epichains/issues + url: https://epiverse-trace.github.io/epichains/ + url_cran: https://CRAN.R-project.org/package=epichains + url_git: https://github.com/epiverse-trace/epichains +epiCleanr: + version: 0.2.0 + title: A Tidy Solution for Epidemiological Data + maintainer: Mohamed A. Yusuf + description: Offers a tidy solution for epidemiological data. It houses a range + of functions for epidemiologists and public health data wizards for data management + and cleaning. + date_publication: '2023-09-28' + bug_reports: https://github.com/truenomad/epiCleanr/issues + url: https://truenomad.github.io/epiCleanr/ + url_cran: https://CRAN.R-project.org/package=epiCleanr + url_git: https://github.com/truenomad/epiCleanr +epicmodel: + version: 0.2.0 + title: Causal Modeling in Epidemiology + maintainer: Felix Forster + description: |- + Create causal models for use in epidemiological studies, + including sufficient-component cause models as introduced by + Rothman (1976) . + date_publication: '2024-12-11' + bug_reports: https://github.com/forsterepi/epicmodel/issues + url: https://forsterepi.github.io/epicmodel/ + url_cran: https://CRAN.R-project.org/package=epicmodel + url_git: https://github.com/forsterepi/epicmodel +epiCo: + version: 1.0.1 + title: Statistical and Viz Tools for Vector-Borne Diseases in Colombia + maintainer: Juan D. Umaña + description: |- + Provides statistical and visualization tools for the analysis + of demographic indicators, and spatio-temporal behavior and + characterization of outbreaks of vector-borne diseases (VBDs) in + Colombia. It implements travel times estimated in Bravo-Vega C., + Santos-Vega M., & Cordovez J.M. (2022), and the endemic channel method + (Bortman, M. (1999) ). + date_publication: '2025-01-15' + bug_reports: https://github.com/epiverse-trace/epiCo/issues + url: https://epiverse-trace.github.io/epiCo/ + url_cran: https://CRAN.R-project.org/package=epiCo + url_git: https://github.com/epiverse-trace/epiCo +epicontacts: + version: 1.1.4 + title: Handling, Visualisation and Analysis of Epidemiological Contacts + maintainer: Finlay Campbell + description: A collection of tools for representing epidemiological contact data, + composed of case line lists and contacts between cases. Also contains procedures + for data handling, interactive graphics, and statistics. + date_publication: '2024-04-30' + bug_reports: https://github.com/reconhub/epicontacts/issues + url: https://www.repidemicsconsortium.org/epicontacts/ + url_cran: https://CRAN.R-project.org/package=epicontacts + url_git: '' +EpiContactTrace: + version: 0.18.0 + title: Epidemiological Tool for Contact Tracing + maintainer: Stefan Widgren + description: |- + Routines for epidemiological contact tracing + and visualisation of network of contacts. + date_publication: '2024-10-04' + bug_reports: https://github.com/stewid/EpiContactTrace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EpiContactTrace + url_git: https://github.com/stewid/EpiContactTrace +EpiCurve: + version: 2.4-2 + title: Plot an Epidemic Curve + maintainer: Jean Pierre Decorps + description: Creates simple or stacked epidemic curves for hourly, daily, weekly + or monthly outcome data. + date_publication: '2021-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiCurve + url_git: https://github.com/IamKDO/EpiCurve +epidata: + version: 0.4.0 + title: |- + Tools to Retrieve Economic Policy Institute Data Library + Extracts + maintainer: Bob Rudis + description: |- + The Economic Policy Institute () provides + researchers, media, and the public with easily accessible, up-to-date, and + comprehensive historical data on the American labor force. It is compiled + from Economic Policy Institute analysis of government data sources. Use + it to research wages, inequality, and other economic indicators over time + and among demographic groups. Data is usually updated monthly. + date_publication: '2020-08-26' + bug_reports: https://github.com/hrbrmstr/epidata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epidata + url_git: https://gitlab.com/hrbrmstr/epidata +epidatr: + version: 1.2.0 + title: Client for Delphi's 'Epidata' API + maintainer: David Weber + description: 'The Delphi ''Epidata'' API provides real-time access to epidemiological + surveillance data for influenza, ''COVID-19'', and other diseases for the USA + at various geographical resolutions, both from official government sources such + as the Center for Disease Control (CDC) and Google Trends and private partners + such as Facebook and Change ''Healthcare''. It is built and maintained by the + Carnegie Mellon University Delphi research group. To cite this API: David C. Farrow, + Logan C. Brooks, Aaron ''Rumack'', Ryan J. ''Tibshirani'', ''Roni'' ''Rosenfeld'' + (2015). Delphi ''Epidata'' API. .' + date_publication: '2024-06-20' + bug_reports: https://github.com/cmu-delphi/epidatr/issues + url: https://cmu-delphi.github.io/epidatr/ + url_cran: https://CRAN.R-project.org/package=epidatr + url_git: https://github.com/cmu-delphi/epidatr +epiDisplay: + version: 3.5.0.2 + title: Epidemiological Data Display Package + maintainer: Virasakdi Chongsuvivatwong + description: Package for data exploration and result presentation. Full 'epicalc' + package with data management functions is available at ''. + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epiDisplay + url_git: '' +epidm: + version: 1.0.4 + title: UK Epidemiological Data Management + maintainer: Alex Bhattacharya + description: |- + Contains utilities and functions for the cleaning, processing and + management of patient level public health data for surveillance + and analysis held by the UK Health Security Agency, UKHSA. + date_publication: '2022-07-11' + bug_reports: https://github.com/alexbhatt/epidm/issues + url: https://alexbhatt.github.io/epidm/ + url_cran: https://CRAN.R-project.org/package=epidm + url_git: https://github.com/alexbhatt/epidm +EpiDynamics: + version: 0.3.1 + title: Dynamic Models in Epidemiology + maintainer: Oswaldo Santos Baquero + description: |- + Mathematical models of infectious diseases in humans and animals. + Both, deterministic and stochastic models can be simulated and plotted. + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiDynamics + url_git: https://github.com/oswaldosantos/EpiDynamics +EpiEstim: + version: 2.2-4 + title: Estimate Time Varying Reproduction Numbers from Epidemic Curves + maintainer: Anne Cori + description: |- + Tools to quantify transmissibility throughout + an epidemic from the analysis of time series of incidence as described in + Cori et al. (2013) and Wallinga and Teunis (2004) + . + date_publication: '2021-01-07' + bug_reports: https://github.com/mrc-ide/EpiEstim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EpiEstim + url_git: https://github.com/mrc-ide/EpiEstim +epifitter: + version: 0.3.0 + title: Analysis and Simulation of Plant Disease Progress Curves + maintainer: Kaique dos S. Alves + description: |- + Analysis and visualization of plant disease progress curve data. Functions for + fitting two-parameter population dynamics models (exponential, monomolecular, logistic + and Gompertz) to proportion data for single or multiple epidemics using either linear + or no-linear regression. Statistical and visual outputs are provided to aid in model + selection. Synthetic curves can be simulated for any of the models given the parameters. + See Laurence V. Madden, Gareth Hughes, and Frank van den Bosch (2007) + for further information on the methods. + date_publication: '2021-06-14' + bug_reports: https://github.com/AlvesKS/epifitter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epifitter + url_git: https://github.com/AlvesKS/epifitter +epiflows: + version: 0.2.1 + title: Predicting Disease Spread from Flow Data + maintainer: Pawel Piatkowski + description: |- + Provides functions and classes designed to handle and visualise + epidemiological flows between locations. Also contains a statistical method + for predicting disease spread from flow data initially described in + Dorigatti et al. (2017) . + This package is part of the RECON () + toolkit for outbreak analysis. + date_publication: '2023-04-09' + bug_reports: https://github.com/reconhub/epiflows/issues + url: https://www.repidemicsconsortium.org/epiflows/ + url_cran: https://CRAN.R-project.org/package=epiflows + url_git: '' +EpiForsk: + version: 0.1.1 + title: |- + Code Sharing at the Department of Epidemiological Research at + Statens Serum Institut + maintainer: Kim Daniel Jakobsen + description: |- + This is a collection of assorted functions and examples collected + from various projects. Currently we have functionalities for simplifying + overlapping time intervals, Charlson comorbidity score constructors for + Danish data, getting frequency for multiple variables, getting standardized + output from logistic and log-linear regressions, sibling design linear + regression functionalities a method for calculating the confidence intervals + for functions of parameters from a GLM, Bayes equivalent for hypothesis + testing with asymptotic Bayes factor, and several help functions for + generalized random forest analysis using 'grf'. + date_publication: '2024-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiForsk + url_git: '' +epigraphdb: + version: 0.2.3 + title: Interface Package for the 'EpiGraphDB' Platform + maintainer: Yi Liu + description: |- + The interface package to access data from the + 'EpiGraphDB' platform. + It provides easy access to the 'EpiGraphDB' platform with functions that + query the corresponding REST endpoints on the API + and return the response data in the 'tibble' data frame format. + date_publication: '2022-01-14' + bug_reports: https://github.com/MRCIEU/epigraphdb-r/issues + url: https://mrcieu.github.io/epigraphdb-r/ + url_cran: https://CRAN.R-project.org/package=epigraphdb + url_git: '' +epigrowthfit: + version: 0.15.4 + title: Nonlinear Mixed Effects Models of Epidemic Growth + maintainer: Mikael Jagan + description: |- + Maximum likelihood estimation of nonlinear mixed effects models of + epidemic growth using Template Model Builder ('TMB'). Enables + joint estimation for collections of disease incidence time series, + including time series that describe multiple epidemic waves. + Supports a set of widely used phenomenological models: exponential, + logistic, Richards (generalized logistic), subexponential, + and Gompertz. Provides methods for interrogating model objects + and several auxiliary functions, including one for computing basic + reproduction numbers from fitted values of the initial exponential + growth rate. + Preliminary versions of this software were applied + in Ma et al. (2014) and + in Earn et al. (2020) . + date_publication: '2025-02-19' + bug_reports: https://github.com/davidearn/epigrowthfit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epigrowthfit + url_git: https://github.com/davidearn/epigrowthfit +EpiILM: + version: 1.5.2 + title: Spatial and Network Based Individual Level Models for Epidemics + maintainer: Waleed Almutiry + description: 'Provides tools for simulating from discrete-time individual level + models for infectious disease data analysis. This epidemic model class contains + spatial and contact-network based models with two disease types: Susceptible-Infectious + (SI) and Susceptible-Infectious-Removed (SIR).' + date_publication: '2020-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiILM + url_git: https://github.com/waleedalmutiry/EpiILM +EpiILMCT: + version: 1.1.7 + title: |- + Continuous Time Distance-Based and Network-Based Individual + Level Models for Epidemics + maintainer: Waleed Almutiry + description: Provides tools for simulating from continuous-time individual level + models of disease transmission, and carrying out infectious disease data analyses + with the same models. The epidemic models considered are distance-based and/or + contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed + (SINR) compartmental frameworks. . + date_publication: '2021-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiILMCT + url_git: https://github.com/waleedalmutiry/EpiILMCT/ +EpiInvert: + version: 0.3.1 + title: Variational Techniques in Epidemiology + maintainer: Luis Alvarez + description: |- + Using variational techniques we address some epidemiological + problems as the incidence curve decomposition by inverting the renewal + equation as described in Alvarez et al. (2021) + and Alvarez et al. (2022) or the estimation of + the functional relationship between epidemiological indicators. We also + propose a learning method for the short time forecast of the trend + incidence curve as described in + Morel et al. (2022) . + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiInvert + url_git: https://github.com/lalvarezmat/EpiInvert +epikit: + version: 0.1.6 + title: Miscellaneous Helper Tools for Epidemiologists + maintainer: Zhian N. Kamvar + description: |- + Contains tools for formatting inline code, renaming redundant + columns, aggregating age categories, adding survey weights, finding the earliest + date of an event, plotting z-curves, generating population counts and + calculating proportions with confidence intervals. This is part of the + 'R4Epis' project . + date_publication: '2024-01-23' + bug_reports: https://github.com/R4EPI/epikit/issues + url: https://r4epis.netlify.app + url_cran: https://CRAN.R-project.org/package=epikit + url_git: https://github.com/R4EPI/epikit +epilogi: + version: '1.2' + title: The 'epilogi' Variable Selection Algorithm for Continuous Data + maintainer: Michail Tsagris + description: 'The ''epilogi'' variable selection algorithm is implemented for the + case of continuous response and predictor variables. The relevant paper is: Lakiotaki + K., Papadovasilakis Z., Lagani V., Fafalios S., Charonyktakis P., Tsagris M. and + Tsamardinos I. (2023). "Automated machine learning for Genome Wide Association + Studies". Bioinformatics, 39(9): btad545. .' + date_publication: '2024-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epilogi + url_git: '' +EpiLPS: + version: 1.3.0 + title: |- + A Fast and Flexible Bayesian Tool for Estimating Epidemiological + Parameters + maintainer: Oswaldo Gressani + description: |- + Estimation of epidemiological parameters with + Laplacian-P-splines following the methodology of Gressani et al. (2022) + . + date_publication: '2024-03-08' + bug_reports: https://github.com/oswaldogressani/EpiLPS/issues + url: + url_cran: https://CRAN.R-project.org/package=EpiLPS + url_git: '' +epimdr: + version: 0.6-5 + title: 'Functions and Data for "Epidemics: Models and Data in R"' + maintainer: Ottar N. Bjornstad + description: 'Functions, data sets and shiny apps for "Epidemics: Models and Data + in R" by Ottar N. Bjornstad (ISBN 978-3-319-97487-3) . + The package contains functions to study the S(E)IR model, spatial and age-structured + SIR models; time-series SIR and chain-binomial stochastic models; catalytic disease + models; coupled map lattice models of spatial transmission and network models + for social spread of infection. The package is also an advanced quantitative companion + to the coursera Epidemics Massive Online Open Course .' + date_publication: '2020-01-25' + bug_reports: https://github.com/objornstad/epimdr/issues + url: https://www.springer.com/gp/book/9783319974866 + url_cran: https://CRAN.R-project.org/package=epimdr + url_git: https://github.com/objornstad/epimdr +epimdr2: + version: 1.0-9 + title: |- + Functions and Data for "Epidemics: Models and Data in R (2nd + Edition)" + maintainer: Ottar N. Bjornstad + description: 'Functions, data sets and shiny apps for "Epidemics: Models and Data + in R (2nd edition)" by Ottar N. Bjornstad (2022, ISBN: 978-3-031-12055-8) . + The package contains functions to study the Susceptible-Exposed-Infected-Removed + SEIR model, spatial and age-structured Susceptible-Infected-Removed SIR models; + time-series SIR and chain-binomial stochastic models; catalytic disease models; + coupled map lattice models of spatial transmission and network models for social + spread of infection. The package is also an advanced quantitative companion to + the ''Coursera'' Epidemics Massive Online Open Course .' + date_publication: '2022-12-15' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=epimdr2 + url_git: +EpiModel: + version: 2.5.0 + title: Mathematical Modeling of Infectious Disease Dynamics + maintainer: Samuel Jenness + description: |- + Tools for simulating mathematical models of infectious disease dynamics. + Epidemic model classes include deterministic compartmental models, stochastic + individual-contact models, and stochastic network models. Network models use the + robust statistical methods of exponential-family random graph models (ERGMs) + from the Statnet suite of software packages in R. Standard templates for epidemic + modeling include SI, SIR, and SIS disease types. EpiModel features an API for + extending these templates to address novel scientific research aims. Full + methods for EpiModel are detailed in Jenness et al. (2018, ). + date_publication: '2024-10-11' + bug_reports: https://github.com/EpiModel/EpiModel/issues/ + url: https://www.epimodel.org/ + url_cran: https://CRAN.R-project.org/package=EpiModel + url_git: '' +epinet: + version: 2.1.11 + title: Epidemic/Network-Related Tools + maintainer: Chris Groendyke + description: A collection of epidemic/network-related tools. Simulates transmission + of diseases through contact networks. Performs Bayesian inference on network and + epidemic parameters, given epidemic data. + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epinet + url_git: '' +epinetr: + version: '0.96' + title: Epistatic Network Modelling with Forward-Time Simulation + maintainer: Dion Detterer + description: |- + Allows for forward-in-time simulation of epistatic networks with associated + phenotypic output. + date_publication: '2022-03-10' + bug_reports: https://github.com/diondetterer/epinetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epinetr + url_git: https://github.com/diondetterer/epinetr +EpiNow2: + version: 1.7.1 + title: |- + Estimate Real-Time Case Counts and Time-Varying Epidemiological + Parameters + maintainer: Sebastian Funk + description: |- + Estimates the time-varying reproduction number, + rate of spread, and doubling time using a range of open-source tools + (Abbott et al. (2020) ), and + current best practices (Gostic et al. (2020) + ). It aims to help users avoid some + of the limitations of naive implementations in a framework that is + informed by community feedback and is actively supported. + date_publication: '2025-02-19' + bug_reports: https://github.com/epiforecasts/EpiNow2/issues + url: https://epiforecasts.io/EpiNow2/ + url_cran: https://CRAN.R-project.org/package=EpiNow2 + url_git: https://github.com/epiforecasts/EpiNow2 +epiomics: + version: 1.2.0 + title: Analysis of Omics Data in Observational Studies + maintainer: Jesse Goodrich + description: |- + A collection of fast and flexible functions for analyzing + omics data in observational studies. Multiple different approaches for + integrating multiple environmental/genetic factors, omics data, and/or + phenotype data are implemented. This includes functions for performing + omics wide association studies with one or more variables of interest + as the exposure or outcome; a function for performing a meet in the + middle analysis for linking exposures, omics, and outcomes (as + described by Chadeau-Hyam et al., (2010) + ); and a function for performing a + mixtures analysis across all omics features using quantile-based + g-Computation (as described by Keil et al., (2019) + ). + date_publication: '2025-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epiomics + url_git: '' +epiparameter: + version: 0.4.1 + title: |- + Classes and Helper Functions for Working with Epidemiological + Parameters + maintainer: Joshua W. Lambert + description: |- + Classes and helper functions for loading, extracting, converting, + manipulating, plotting and aggregating epidemiological parameters for infectious diseases. + Epidemiological parameters extracted from the literature are loaded from the 'epiparameterDB' + R package. + date_publication: '2025-01-24' + bug_reports: https://github.com/epiverse-trace/epiparameter/issues + url: https://epiverse-trace.github.io/epiparameter/ + url_cran: https://CRAN.R-project.org/package=epiparameter + url_git: https://github.com/epiverse-trace/epiparameter/ +epiparameterDB: + version: 0.1.0 + title: Database of Epidemiological Parameters + maintainer: Joshua W. Lambert + description: |- + A data package containing a database of epidemiological + parameters. It stores the data for the 'epiparameter' R package. + Epidemiological parameter estimates are extracted from the literature. + date_publication: '2024-11-28' + bug_reports: https://github.com/epiverse-trace/epiparameterDB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epiparameterDB + url_git: https://github.com/epiverse-trace/epiparameterDB/ +epiphy: + version: 0.5.0 + title: Analysis of Plant Disease Epidemics + maintainer: Christophe Gigot + description: |- + A toolbox to make it easy to analyze plant disease epidemics. It + provides a common framework for plant disease intensity data recorded over + time and/or space. Implemented statistical methods are currently mainly + focused on spatial pattern analysis (e.g., aggregation indices, Taylor and + binary power laws, distribution fitting, SADIE and 'mapcomp' methods). See + Laurence V. Madden, Gareth Hughes, Franck van den Bosch (2007) + for further information on these methods. + Several data sets that were mainly published in plant disease epidemiology + literature are also included in this package. + date_publication: '2023-11-16' + bug_reports: https://github.com/chgigot/epiphy/issues + url: https://chgigot.github.io/epiphy/ + url_cran: https://CRAN.R-project.org/package=epiphy + url_git: https://github.com/chgigot/epiphy +epiR: + version: 2.0.80 + title: Tools for the Analysis of Epidemiological Data + maintainer: Mark Stevenson + description: Tools for the analysis of epidemiological and surveillance data. Contains + functions for directly and indirectly adjusting measures of disease frequency, + quantifying measures of association on the basis of single or multiple strata + of count data presented in a contingency table, computation of confidence intervals + around incidence risk and incidence rate estimates and sample size calculations + for cross-sectional, case-control and cohort studies. Surveillance tools include + functions to calculate an appropriate sample size for 1- and 2-stage representative + freedom surveys, functions to estimate surveillance system sensitivity and functions + to support scenario tree modelling analyses. + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epiR + url_git: '' +EpiReport: + version: 1.0.2 + title: Epidemiological Report + maintainer: Lore Merdrignac + description: |- + Drafting an epidemiological report in 'Microsoft Word' format for a given disease, + similar to the Annual Epidemiological Reports published by the European Centre + for Disease Prevention and Control. Through standalone functions, it is specifically + designed to generate each disease specific output presented in these reports and includes: + - Table with the distribution of cases by Member State over the last five years; + - Seasonality plot with the distribution of cases at the European Union / European Economic Area level, + by month, over the past five years; + - Trend plot with the trend and number of cases at the European Union / European Economic Area level, + by month, over the past five years; + - Age and gender bar graph with the distribution of cases at the European Union / European Economic Area level. + Two types of datasets can be used: + - The default dataset of dengue 2015-2019 data; + - Any dataset specified as described in the vignette. + date_publication: '2021-07-05' + bug_reports: '' + url: https://www.ecdc.europa.eu/en/all-topics-z/surveillance-and-disease-data/annual-epidemiological-reports-aers + url_cran: https://CRAN.R-project.org/package=EpiReport + url_git: '' +episcan: + version: 0.0.1 + title: Scan Pairwise Epistasis + maintainer: Beibei Jiang + description: 'Searching genomic interactions with linear/logistic regression in + a high-dimensional dataset is a time-consuming task. This package provides some + efficient ways to scan epistasis in genome-wide interaction studies (GWIS). Both + case-control status (binary outcome) and quantitative phenotype (continuous outcome) + are supported (the main references: 1. Kam-Thong, T., D. Czamara, K. Tsuda, K. + Borgwardt, C. M. Lewis, A. Erhardt-Lehmann, B. Hemmer, et al. (2011). . + 2. Kam-Thong, T., B. Pütz, N. Karbalai, B. Müller-Myhsok, and K. Borgwardt. (2011). .)' + date_publication: '2018-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=episcan + url_git: '' +EpiSemble: + version: 0.1.1 + title: |- + Ensemble Based Machine Learning Approach for Predicting + Methylation States + maintainer: Dipro Sinha + description: DNA methylation (6mA) is a major epigenetic process by which alteration + in gene expression took place without changing the DNA sequence. Predicting these + sites in-vitro is laborious, time consuming as well as costly. This 'EpiSemble' + package is an in-silico pipeline for predicting DNA sequences containing the 6mA + sites. It uses an ensemble-based machine learning approach by combining Support + Vector Machine (SVM), Random Forest (RF) and Gradient Boosting approach to predict + the sequences with 6mA sites in it. This package has been developed by using the + concept of Chen et al. (2019) . + date_publication: '2023-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiSemble + url_git: '' +episensr: + version: 1.3.0 + title: Basic Sensitivity Analysis of Epidemiological Results + maintainer: Denis Haine + description: |- + Basic sensitivity analysis of the observed relative risks adjusting + for unmeasured confounding and misclassification of the + exposure/outcome, or both. It follows the bias analysis methods and + examples from the book by Lash T.L, Fox M.P, and Fink A.K. + "Applying Quantitative Bias Analysis to Epidemiologic Data", + ('Springer', 2021). + date_publication: '2023-08-30' + bug_reports: https://github.com/dhaine/episensr/issues + url: https://dhaine.github.io/episensr/ + url_cran: https://CRAN.R-project.org/package=episensr + url_git: https://github.com/dhaine/episensr +EpiSignalDetection: + version: 0.1.2 + title: Signal Detection Analysis + maintainer: Lore Merdrignac + description: |- + Exploring time series for signal detection. It is specifically designed + to detect possible outbreaks using infectious disease surveillance data + at the European Union / European Economic Area or country level. + Automatic detection tools used are presented in the paper + "Monitoring count time series in R: aberration detection in public health surveillance", + by Salmon (2016) . + The package includes: + - Signal Detection tool, an interactive 'shiny' application + in which the user can import external data and perform basic signal detection analyses; + - An automated report in HTML format, presenting the results of the time series analysis in tables and graphs. + This report can also be stratified by population characteristics (see 'Population' variable). + This project was funded by the European Centre for Disease Prevention and Control. + date_publication: '2021-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiSignalDetection + url_git: https://github.com/EU-ECDC/EpiSignalDetection +EpiSimR: + version: '1.1' + title: |- + A 'Shiny' App to Simulate the Dynamics of Epidemic and Endemic + Diseases Spread + maintainer: Nassim AYAD + description: |- + The 'EpiSimR' package provides an interactive 'shiny' app based on deterministic compartmental + mathematical modeling for simulating and visualizing the dynamics of epidemic and endemic disease spread. + It allows users to explore various intervention strategies, including vaccination and isolation, + by adjusting key epidemiological parameters. The methodology follows the approach described by + Brauer (2008) . Thanks to 'shiny' package. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiSimR + url_git: '' +EpiStats: + version: 1.6-2 + title: Tools for Epidemiologists + maintainer: Lore Merdrignac + description: |- + Provides set of functions aimed at epidemiologists. + The package includes commands for measures of association and impact for case control studies and cohort studies. + It may be particularly useful for outbreak investigations including univariable analysis and stratified analysis. + The functions for cohort studies include the CS(), CSTable() and CSInter() commands. + The functions for case control studies include the CC(), CCTable() and CCInter() commands. + References - Cornfield, J. 1956. A statistical problem arising from retrospective studies. In Vol. 4 of Proceedings of the Third Berkeley Symposium, ed. J. Neyman, 135-148. Berkeley, CA - University of California Press. + Woolf, B. 1955. On estimating the relation between blood group disease. + Annals of Human Genetics 19 251-253. Reprinted in Evolution of Epidemiologic Ideas Annotated Readings on Concepts and Methods, ed. S. Greenland, pp. 108-110. + Newton Lower Falls, MA Epidemiology Resources. + Gilles Desve & Peter Makary, 2007. 'CSTABLE Stata module to calculate summary table for cohort study' Statistical Software Components S456879, Boston College Department of Economics. + Gilles Desve & Peter Makary, 2007. 'CCTABLE Stata module to calculate summary table for case-control study' Statistical Software Components S456878, Boston College Department of Economics. + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiStats + url_git: '' +EpistemicGameTheory: + version: 0.1.2 + title: Constructing an Epistemic Model for the Games with Two Players + maintainer: Bilge Baser + description: Constructing an epistemic model such that, for every player i and for + every choice c(i) which is optimal, there is one type that expresses common belief + in rationality. + date_publication: '2017-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpistemicGameTheory + url_git: '' +epitab: + version: 0.2.2 + title: Flexible Contingency Tables for Epidemiology + maintainer: Stuart Lacy + description: |- + Builds contingency tables that cross-tabulate multiple + categorical variables and also calculates various summary measures. + Export to a variety of formats is supported, including: 'HTML', + 'LaTeX', and 'Excel'. + date_publication: '2018-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epitab + url_git: https://github.com/stulacy/epitab +EpiTest: + version: 1.0.0 + title: Test for Gene x Gene Interactions in Bi-Parental Populations + maintainer: Simon Rio + description: |- + Provides functions to test for gene x gene interactions in a + bi-parental population of inbred lines. The data are fitted with the + mixed linear model described in Rio et al. (2022) , + that accounts for gene x gene interactions + at both the fixed effect and variance levels. The package also + provides graphical tools to display the gene x gene interaction trend at + the mean level and the variance component analysis. + date_publication: '2022-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EpiTest + url_git: '' +epitools: + version: 0.5-10.1 + title: Epidemiology Tools + maintainer: Adam Omidpanah + description: Tools for training and practicing epidemiologists including methods + for two-way and multi-way contingency tables. + date_publication: '2020-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epitools + url_git: '' +epitrix: + version: 0.4.0 + title: Small Helpers and Tricks for Epidemics Analysis + maintainer: Thibaut Jombart + description: A collection of small functions useful for epidemics analysis and infectious + disease modelling. This includes computation of basic reproduction numbers from + growth rates, generation of hashed labels to anonymize data, and fitting discretized + Gamma distributions. + date_publication: '2023-01-13' + bug_reports: https://github.com/reconhub/epitrix/issues + url: http://www.repidemicsconsortium.org/epitrix/ + url_cran: https://CRAN.R-project.org/package=epitrix + url_git: '' +epitweetr: + version: 2.2.16 + title: Early Detection of Public Health Threats from 'Twitter' Data + maintainer: Laura Espinosa + description: It allows you to automatically monitor trends of tweets by time, place + and topic aiming at detecting public health threats early through the detection + of signals (e.g. an unusual increase in the number of tweets). It was designed + to focus on infectious diseases, and it can be extended to all hazards or other + fields of study by modifying the topics and keywords. More information is available + in the 'epitweetr' peer-review publication (doi:10.2807/1560-7917.ES.2022.27.39.2200177). + date_publication: '2023-11-15' + bug_reports: https://github.com/EU-ECDC/epitweetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epitweetr + url_git: https://github.com/EU-ECDC/epitweetr +epiworldR: + version: 0.6.1.0 + title: Fast Agent-Based Epi Models + maintainer: Andrew Pulsipher + description: A flexible framework for Agent-Based Models (ABM), the 'epiworldR' + package provides methods for prototyping disease outbreaks and transmission models + using a 'C++' backend, making it very fast. It supports multiple epidemiological + models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed + (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary + mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility + rates as a function of agents' features, providing great complexity for the model + dynamics. Furthermore, 'epiworldR' is ideal for simulation studies featuring large + populations. + date_publication: '2025-01-28' + bug_reports: https://github.com/UofUEpiBio/epiworldR/issues + url: https://uofuepibio.github.io/epiworldR/ + url_cran: https://CRAN.R-project.org/package=epiworldR + url_git: https://github.com/UofUEpiBio/epiworldR +epiworldRShiny: + version: 0.1-0 + title: A 'shiny' Wrapper of the R Package 'epiworldR' + maintainer: Derek Meyer + description: R 'shiny' web apps for epidemiological Agent-Based Models. It provides + a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR' + (Meyer et al., 2023) . Some of the main features of the + package include the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered + (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' + provides a web-based user interface for running various epidemiological ABMs, + simulating interventions, and visualizing results interactively. + date_publication: '2024-06-05' + bug_reports: https://github.com/UofUEpiBio/epiworldRShiny/issues/ + url: https://uofuepibio.github.io/epiworldRShiny/ + url_cran: https://CRAN.R-project.org/package=epiworldRShiny + url_git: https://github.com/UofUEpiBio/epiworldRShiny/ +epizootic: + version: 1.0.0 + title: |- + Spatially Explicit Population Models of Disease Transmission in + Wildlife + maintainer: July Pilowsky + description: |- + This extension of the pattern-oriented modeling framework of the + 'poems' package provides a collection of modules and functions customized + for modeling disease transmission on a population scale in a spatiotemporally + explicit manner. This includes seasonal time steps, dispersal functions that + track disease state of dispersers, results objects that store disease states, + and a population simulator that includes disease dynamics. + date_publication: '2024-10-02' + bug_reports: https://github.com/viralemergence/epizootic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epizootic + url_git: https://github.com/viralemergence/epizootic +EPLSIM: + version: 0.1.0 + title: |- + Partial Linear Single Index Models for Environmental Mixture + Analysis + maintainer: Yuyan Wang + description: Collection of ancillary functions and utilities for Partial Linear + Single Index Models for Environmental mixture analyses, which currently provides + functions for scalar outcomes. The outputs of these functions include the single + index function, single index coefficients, partial linear coefficients, mixture + overall effect, exposure main and interaction effects, and differences of quartile + effects. In the future, we will add functions for binary, ordinal, Poisson, survival, + and longitudinal outcomes, as well as models for time-dependent exposures. See + Wang et al (2020) for an overview. + date_publication: '2023-03-08' + bug_reports: https://github.com/YuyanWangSixTwo/EPLSIM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EPLSIM + url_git: https://github.com/YuyanWangSixTwo/EPLSIM +eplusr: + version: 0.16.2 + title: |- + A Toolkit for Using Whole Building Simulation Program + 'EnergyPlus' + maintainer: Hongyuan Jia + description: |- + A rich toolkit of using the whole building + simulation program 'EnergyPlus'(), which + enables programmatic navigation, modification of 'EnergyPlus' models + and makes it less painful to do parametric simulations and analysis. + date_publication: '2023-08-25' + bug_reports: https://github.com/hongyuanjia/eplusr/issues + url: https://hongyuanjia.github.io/eplusr/ + url_cran: https://CRAN.R-project.org/package=eplusr + url_git: https://github.com/hongyuanjia/eplusr +eply: + version: 0.1.2 + title: Apply a Function Over Expressions + maintainer: William Michael Landau + description: Evaluate a function over a data frame of expressions. + date_publication: '2018-04-06' + bug_reports: https://github.com/wlandau/eply/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eply + url_git: https://github.com/wlandau/eply +epm: + version: 1.1.4 + title: EcoPhyloMapper + maintainer: Pascal Title + description: 'Facilitates the aggregation of species'' geographic ranges from vector + or raster spatial data, and that enables the calculation of various morphological + and phylogenetic community metrics across geography. Citation: Title, PO, DL Swiderski + and ML Zelditch (2022) .' + date_publication: '2025-02-14' + bug_reports: https://github.com/ptitle/epm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epm + url_git: https://github.com/ptitle/epm +epmrob: + version: '0.1' + title: Robust Estimation of Probit Models with Endogeneity + maintainer: Mikhail Zhelonkin + description: Package provides a set of tools for robust estimation and inference + for probit model with endogenous covariates. The current version contains a robust + two-step estimator. For technical details, see Naghi, Varadi and Zhelonkin (2022), + . + date_publication: '2023-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epmrob + url_git: '' +epo: + version: 0.1.0 + title: Enhanced Portfolio Optimization (EPO) + maintainer: Bernardo Reckziegel + description: |- + Implements the Enhanced Portfolio Optimization (EPO) method as + described in Pedersen, Babu and Levine (2021) + . + date_publication: '2023-08-17' + bug_reports: https://github.com/Reckziegel/epo/issues + url: https://reckziegel.github.io/epo/ + url_cran: https://CRAN.R-project.org/package=epo + url_git: https://github.com/Reckziegel/epo +epocakir: + version: 0.9.9 + title: Clinical Coding of Patients with Kidney Disease + maintainer: Alwin Wang + description: |- + Clinical coding and diagnosis of patients with kidney using + clinical practice guidelines. The guidelines used are the evidence-based + KDIGO guidelines, see for more information. + This package covers acute kidney injury (AKI), anemia, and + chronic kidney disease (CKD). + date_publication: '2023-01-06' + bug_reports: https://github.com/alwinw/epocakir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epocakir + url_git: https://github.com/alwinw/epocakir +eponge: + version: 0.1.0 + title: Keep Your Environment Clean + maintainer: Krzysztof Joachimiak + description: |- + Provides a set of functions, which facilitates removing objects from an environment. + It allows to delete objects specified with regular expression or with other conditions (e.g. if object is numeric), + using one function call. + date_publication: '2020-03-24' + bug_reports: https://github.com/krzjoa/eponge/issues + url: https://krzjoa.github.io/eponge/ + url_cran: https://CRAN.R-project.org/package=eponge + url_git: https://github.com/krzjoa/eponge +epos: + version: '1.1' + title: Epilepsy Ontologies' Similarities + maintainer: Bernd Mueller + description: Analysis and visualization of similarities between epilepsy ontologies + based on text mining results by comparing ranked lists of co-occurring drug terms + in the BioASQ corpus. The ranked result lists of neurological drug terms co-occurring + with terms from the epilepsy ontologies EpSO, ESSO, EPILONT, EPISEM and FENICS + undergo further analysis. The source data to create the ranked lists of drug names + is produced using the text mining workflows described in Mueller, Bernd and Hagelstein, + Alexandra (2016) , Mueller, Bernd et al. (2017) , + Mueller, Bernd and Rebholz-Schuhmann, Dietrich (2020) , + and Mueller, Bernd et al. (2022) . + date_publication: '2024-03-15' + bug_reports: https://github.com/bernd-mueller/epos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epos + url_git: https://github.com/bernd-mueller/epos +epoxy: + version: 1.0.0 + title: String Interpolation for Documents, Reports and Apps + maintainer: Garrick Aden-Buie + description: |- + Extra strength 'glue' for data-driven templates. String + interpolation for 'Shiny' apps or 'R Markdown' and 'knitr'-powered + 'Quarto' documents, built on the 'glue' and 'whisker' packages. + date_publication: '2023-09-20' + bug_reports: https://github.com/gadenbuie/epoxy/issues + url: https://pkg.garrickadenbuie.com/epoxy/ + url_cran: https://CRAN.R-project.org/package=epoxy + url_git: https://github.com/gadenbuie/epoxy +epr: + version: '3.0' + title: Easy Polynomial Regression + maintainer: Emmanuel Arnhold + description: Performs analysis of polynomial regression in simple designs with quantitative + treatments. + date_publication: '2017-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epr + url_git: '' +epsiwal: + version: 0.1.0 + title: Exact Post Selection Inference with Applications to the Lasso + maintainer: Steven E. Pav + description: |- + Implements the conditional estimation procedure of + Lee, Sun, Sun and Taylor (2016) . + This procedure allows hypothesis testing on the mean of + a normal random vector subject to linear constraints. + date_publication: '2019-07-02' + bug_reports: https://github.com/shabbychef/epsiwal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epsiwal + url_git: https://github.com/shabbychef/epsiwal +EPT: + version: 0.7.6 + title: Ensemble Patch Transform, Visualization and Decomposition + maintainer: Donghoh Kim + description: 'For multiscale analysis, this package carries out ensemble patch transform, + its visualization and multiscale decomposition. The detailed procedure is described + in Kim et al. (2020), and Oh and Kim (2020). D. Kim, G. Choi, H.-S. Oh, Ensemble + patch transformation: a flexible framework for decomposition and filtering of + signal, EURASIP Journal on Advances in Signal Processing 30 (2020) 1-27 . + H.-S. Oh, D. Kim, Image decomposition by bidimensional ensemble patch transform, + Pattern Recognition Letters 135 (2020) 173-179 .' + date_publication: '2022-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EPT + url_git: '' +epubr: + version: 0.6.5 + title: Read EPUB File Metadata and Text + maintainer: Matthew Leonawicz + description: |- + Provides functions supporting the reading and parsing of internal e-book content from EPUB files. + The 'epubr' package provides functions supporting the reading and parsing of internal e-book content from EPUB files. + E-book metadata and text content are parsed separately and joined together in a tidy, nested tibble data frame. + E-book formatting is not completely standardized across all literature. + It can be challenging to curate parsed e-book content across an arbitrary collection of e-books + perfectly and in completely general form, to yield a singular, consistently formatted output. + Many EPUB files do not even contain all the same pieces of information in their respective metadata. + EPUB file parsing functionality in this package is intended for relatively general application to arbitrary EPUB e-books. + However, poorly formatted e-books or e-books with highly uncommon formatting may not work with this package. + There may even be cases where an EPUB file has DRM or some other property that makes it impossible to read with 'epubr'. + Text is read 'as is' for the most part. The only nominal changes are minor substitutions, for example curly quotes changed to straight quotes. + Substantive changes are expected to be performed subsequently by the user as part of their text analysis. + Additional text cleaning can be performed at the user's discretion, such as with functions from packages like 'tm' or 'qdap'. + date_publication: '2024-09-11' + bug_reports: https://github.com/ropensci/epubr/issues + url: https://docs.ropensci.org/epubr/ + url_cran: https://CRAN.R-project.org/package=epubr + url_git: https://github.com/ropensci/epubr +epwshiftr: + version: 0.1.4 + title: Create Future 'EnergyPlus' Weather Files using 'CMIP6' Data + maintainer: Hongyuan Jia + description: |2- + + Query, download climate change projection data from the 'CMIP6' (Coupled + Model Intercomparison Project Phase 6) project + in the 'ESGF' (Earth System Grid Federation) + platform , and create future 'EnergyPlus' + Weather ('EPW') files adjusted from climate changes + using data from Global Climate Models ('GCM'). + date_publication: '2024-03-12' + bug_reports: https://github.com/ideas-lab-nus/epwshiftr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=epwshiftr + url_git: https://github.com/ideas-lab-nus/epwshiftr +EPX: + version: 1.0.4 + title: Ensemble of Phalanxes + maintainer: Jabed Tomal + description: |- + An ensemble method for the statistical detection of + a rare class in two-class classification problems. The method uses an + ensemble of classifiers where the constituent + models of the ensemble use disjoint subsets (phalanxes) of explanatory + variables. We provide an implementation of the phalanx-formation algorithm. + Please see Tomal et al. (2015) , + Tomal et al. (2016) , and + Tomal et al. (2019) for more details. + date_publication: '2021-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EPX + url_git: '' +epxToR: + version: 0.4-1 + title: Import 'Epidata' XML Files '.epx' + maintainer: Jean Pierre Decorps + description: Import data from 'Epidata' XML files '.epx' and convert it to R data + structures. + date_publication: '2020-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=epxToR + url_git: '' +eq5d: + version: 0.15.7 + title: |- + Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index + Scores + maintainer: Fraser Morton + description: |- + EQ-5D is a popular health related quality of life instrument used + in the clinical and economic evaluation of health care. Developed by the + EuroQol group , the instrument consists of two + components: health state description and evaluation. For the description + component a subject self-rates their health in terms of five dimensions; + mobility, self-care, usual activities, pain/discomfort, and + anxiety/depression using either a three-level (EQ-5D-3L, + ) or a five-level + (EQ-5D-5L, ) + scale. Frequently the scores on these five dimensions are converted to a + single utility index using country specific value sets, which can be used + in the clinical and economic evaluation of health care as well as in + population health surveys. The eq5d package provides methods to calculate + index scores from a subject's dimension scores. 32 TTO and 11 VAS EQ-5D-3L + value sets including those for countries in Szende et al (2007) + and Szende et al (2014) + , 46 EQ-5D-5L EQ-VT value sets, the + EQ-5D-5L crosswalk value sets developed by van Hout et al. (2012) + , the crosswalk value sets for Bermuda, Jordan and + Russia and the reverse crosswalk value sets. 10 EQ-5D-Y value sets are also + included as are the NICE 'DSU' age-sex based EQ-5D-3L to EQ-5D-5L and + EQ-5D-5L to EQ-5D-3L mappings. Methods are also included for the analysis + of EQ-5D profiles, including those from the book "Methods for Analyzing and + Reporting EQ-5D data" by Devlin et al. (2020) + . Additionally a shiny web tool is included + to enable the calculation, visualisation and automated statistical analysis + of EQ-5D data via a web browser using EQ-5D dimension scores stored in CSV + or Excel files. + date_publication: '2025-02-28' + bug_reports: https://github.com/fragla/eq5d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eq5d + url_git: https://github.com/fragla/eq5d +eq5dsuite: + version: 1.0.0 + title: Manipulating and Analysing EQ-5d Data + maintainer: Kim Rand + description: |- + The EQ-5D is a widely-used standarized instrument for measuring Health Related Quality Of Life (HRQOL), + developed by the EuroQol group . It assesses five dimensions; mobility, self-care, + usual activities, pain/discomfort, and anxiety/depression, using either a three-level (EQ-5D-3L) or five-level (EQ-5D-5L) scale. + Scores from these dimensions are commonly converted into a single utility index using country-specific value sets, + which are critical in clinical and economic evaluations of healthcare and in population health surveys. + The eq5dsuite package enables users to calculate utility index values for the EQ-5D instruments, + including crosswalk utilities using the original crosswalk developed by van Hout et al. (2012) + (mapping EQ-5D-5L responses to EQ-5D-3L index values), or the recently developed reverse crosswalk + by van Hout et al. (2021) (mapping EQ-5D-3L responses + to EQ-5D-5L index values). Users are allowed to add and/or remove user-defined value sets. + Additionally, the package provides tools to analyze EQ-5D data according to the recommended + guidelines outlined in "Methods for Analyzing and Reporting EQ-5D data" by Devlin et al. (2020) . + date_publication: '2024-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eq5dsuite + url_git: '' +EQL: + version: 1.0-1 + title: Extended-Quasi-Likelihood-Function (EQL) + maintainer: Thorn Thaler + description: |- + Computation of the EQL for a given family of variance + functions, Saddlepoint-approximations and related auxiliary + functions (e.g. Hermite polynomials). + date_publication: '2019-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EQL + url_git: '' +equalCovs: + version: '1.0' + title: Testing the Equality of Two Covariance Matrices + maintainer: Jun Li + description: Tests the equality of two covariance matrices, used in paper "Two sample + tests for high dimensional covariance matrices." Li and Chen (2012) . + date_publication: '2018-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=equalCovs + url_git: '' +Equalden.HD: + version: 1.2.1 + title: Testing the Equality of a High Dimensional Set of Densities + maintainer: Marta Cousido Rocha + description: The equality of a large number k of densities is tested by measuring + the L2 distance between the corresponding kernel density estimators and the one + based on the pooled sample. The test even works for sample sizes as small as 2. + date_publication: '2024-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Equalden.HD + url_git: '' +EQUALrepeat: + version: 0.4.0 + title: |- + Algorithm Driven Time Series Analysis for Researchers without + Coding Skills + maintainer: Kurinchi Gurusamy + description: Support functions for R-based 'EQUAL-STATS' software which automatically + classifies the data and performs appropriate statistical tests. 'EQUAL-STATS' + software is a shiny application with an user-friendly interface to perform complex + statistical analysis. Gurusamy,K (2024). + date_publication: '2024-09-06' + bug_reports: '' + url: https://sites.google.com/view/equal-group/home + url_cran: https://CRAN.R-project.org/package=EQUALrepeat + url_git: '' +EQUALSTATS: + version: 0.5.0 + title: |- + Algorithm Driven Statistical Analysis for Researchers without + Coding Skills + maintainer: Kurinchi Gurusamy + description: Support functions for R-based 'EQUAL-STATS' software which automatically + classifies the data and performs appropriate statistical tests. 'EQUAL-STATS' + software is a shiny application with an user-friendly interface to perform complex + statistical analysis. Gurusamy,K (2024). + date_publication: '2024-09-23' + bug_reports: '' + url: https://sites.google.com/view/equal-group/home + url_cran: https://CRAN.R-project.org/package=EQUALSTATS + url_git: '' +equaltestMI: + version: 0.6.1 + title: |- + Examine Measurement Invariance via Equivalence Testing and + Projection Method + maintainer: Ge Jiang + description: Functions for examining measurement invariance via equivalence testing + are included in this package. The traditionally used RMSEA (Root Mean Square Error + of Approximation) cutoff values are adjusted based on simulation results. In addition, + a projection-based method is implemented to test the equality of latent factor + means across groups without assuming the equality of intercepts. For more information, + see Yuan, K. H., & Chan, W. (2016) , Deng, L., & Yuan, + K. H. (2016) , and Jiang, G., Mai, Y., & Yuan, + K. H. (2017) . + date_publication: '2021-01-06' + bug_reports: https://github.com/gabriellajg/equaltestMI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=equaltestMI + url_git: '' +equatags: + version: 0.2.1 + title: Equations to 'XML' + maintainer: David Gohel + description: |- + Provides function to transform latex math expressions + into format 'HTML' or 'Office Open XML Math'. The 'XML' + result can then be included in 'HTML', 'Microsoft Word' + documents or 'Microsoft PowerPoint' presentations by using + a 'Markdown' document or the R package 'officer'. + date_publication: '2024-05-24' + bug_reports: https://github.com/ardata-fr/equatags/issues + url: '' + url_cran: https://CRAN.R-project.org/package=equatags + url_git: '' +equate: + version: 2.0.8 + title: Observed-Score Linking and Equating + maintainer: Anthony Albano + description: |- + Contains methods for observed-score linking + and equating under the single-group, equivalent-groups, + and nonequivalent-groups with anchor test(s) designs. + Equating types include identity, mean, linear, general + linear, equipercentile, circle-arc, and composites of + these. Equating methods include synthetic, nominal + weights, Tucker, Levine observed score, Levine true + score, Braun/Holland, frequency estimation, and chained + equating. Plotting and summary methods, and methods for + multivariate presmoothing and bootstrap error estimation + are also provided. + date_publication: '2022-06-07' + bug_reports: https://github.com/talbano/equate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=equate + url_git: https://github.com/talbano/equate +equateIRT: + version: 2.5.1 + title: IRT Equating Methods + maintainer: Michela Battauz + description: |- + Computation of direct, chain and average (bisector) equating coefficients with + standard errors using Item Response Theory (IRT) methods for dichotomous items + (Battauz (2013) , + Battauz (2015) ). + Test scoring can be performed by true score equating and observed score equating methods. + DIF detection can be performed using a Wald-type test + (Battauz (2019) ). + The package includes tests to assess the stability of the equating transformations + (Battauz(2022) ). + date_publication: '2024-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=equateIRT + url_git: '' +equateMultiple: + version: 1.1.1 + title: Equating of Multiple Forms + maintainer: Michela Battauz + description: Equating of multiple forms using Item Response Theory (IRT) methods + (Battauz M. (2017) , Battauz and 'Leoncio' (2023) + , Haberman S. J. (2009) ). + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=equateMultiple + url_git: '' +equatiomatic: + version: 0.3.3 + title: Transform Models into 'LaTeX' Equations + maintainer: Philippe Grosjean + description: |- + The goal of 'equatiomatic' is to reduce the pain + associated with writing 'LaTeX' formulas from fitted models. The + primary function of the package, extract_eq(), takes a fitted model + object as its input and returns the corresponding 'LaTeX' code for the + model. + date_publication: '2024-05-26' + bug_reports: https://github.com/datalorax/equatiomatic/issues + url: https://datalorax.github.io/equatiomatic/ + url_cran: https://CRAN.R-project.org/package=equatiomatic + url_git: https://github.com/datalorax/equatiomatic +equiBSPD: + version: 0.1.0 + title: Equivalent Estimation Balanced Split Plot Designs + maintainer: Bijoy Chanda + description: In agricultural, post-harvest and processing, engineering and industrial + experiments factors are often differentiated with ease with which they can change + from experimental run to experimental run. This is due to the fact that one or + more factors may be expensive or time consuming to change i.e. hard-to-change + factors. These factors restrict the use of complete randomization as it may make + the experiment expensive and time consuming. Split plot designs can be used for + such situations. In general model estimation of split plot designs require the + use of generalized least squares (GLS). However for some split-plot designs ordinary + least squares (OLS) estimates are equivalent to generalized least squares (GLS) + estimates. These types of designs are known in literature as equivalent-estimation + split-plot design. For method details see, Macharia, H. and Goos, P.(2010) .Balanced + split plot designs are designs which have an equal number of subplots within every + whole plot. This package used to construct equivalent estimation balanced split + plot designs for different experimental set ups along with different statistical + criteria to measure the performance of these designs. It consist of the function + equivalent_BSPD(). + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=equiBSPD + url_git: '' +equil2: + version: 1.0.0 + title: Calculate Urinary Saturation with the EQUIL2 Algorithm + maintainer: Bill Denney + description: |- + Saturation of ionic substances in urine is calculated based on + sodium, potassium, calcium, magnesium, ammonia, chloride, phosphate, sulfate, + oxalate, citrate, ph, and urate. This program is intended for research use, + only. The code within is translated from EQUIL2 Visual Basic code based on + Werness, et al (1985) "EQUIL2: a BASIC computer program for the calculation + of urinary saturation" to R. The Visual + Basic code was kindly provided by Dr. John Lieske of the Mayo Clinic. + date_publication: '2022-12-20' + bug_reports: '' + url: https://billdenney.github.io/equil2/ + url_cran: https://CRAN.R-project.org/package=equil2 + url_git: '' +EquiSurv: + version: 0.1.0 + title: |- + Modeling, Confidence Intervals and Equivalence of Survival + Curves + maintainer: Kathrin Moellenhoff + description: |- + We provide a non-parametric and a parametric approach to investigate the equivalence (or non-inferiority) of two survival curves, obtained from two given datasets. The test is based on the creation of confidence intervals at pre-specified time points. + For the non-parametric approach, the curves are given by Kaplan-Meier curves and the variance for calculating the confidence intervals is obtained by Greenwood's formula. + The parametric approach is based on estimating the underlying distribution, where the user can choose between a Weibull, Exponential, Gaussian, Logistic, Log-normal or a Log-logistic distribution. Estimates for the variance for calculating the confidence bands are obtained by a (parametric) bootstrap approach. For this bootstrap censoring is assumed to be exponentially distributed and estimates are obtained from the datasets under consideration. + All details can be found in K.Moellenhoff and A.Tresch: Survival analysis under non-proportional hazards: investigating non-inferiority or equivalence in time-to-event data . + date_publication: '2020-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EquiSurv + url_git: '' +EquiTrends: + version: 1.0.0 + title: |- + Equivalence Testing for Pre-Trends in Difference-in-Differences + Designs + maintainer: Ties Bos + description: Testing for parallel trends is crucial in the Difference-in-Differences + framework. To this end, this package performs equivalence testing in the context + of Difference-in-Differences estimation. It allows users to test if pre-treatment + trends in the treated group are “equivalent” to those in the control group. Here, + “equivalence” means that rejection of the null hypothesis implies that a function + of the pre-treatment placebo effects (maximum absolute, average or root mean squared + value) does not exceed a pre-specified threshold below which trend differences + are considered negligible. The package is based on the theory developed in Dette + & Schumann (2024) . + date_publication: '2024-09-03' + bug_reports: https://github.com/TiesBos/EquiTrends/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EquiTrends + url_git: https://github.com/TiesBos/EquiTrends +equivalence: + version: 0.7.2 + title: Provides Tests and Graphics for Assessing Tests of Equivalence + maintainer: Andrew Robinson + description: |- + Provides statistical tests and graphics for assessing tests + of equivalence. Such tests have similarity as the alternative + hypothesis instead of the null. Sample data sets are included. + date_publication: '2016-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=equivalence + url_git: '' +equivalenceTest: + version: 0.0.1.1 + title: Equivalence Test for the Means of Two Normal Distributions + maintainer: Chao Wang + description: Two methods for performing equivalence test for the means of two (test + and reference) normal distributions are implemented. The null hypothesis of the + equivalence test is that the absolute difference between the two means are greater + than or equal to the equivalence margin and the alternative is that the absolute + difference is less than the margin. Given that the margin is often difficult to + obtain a priori, it is assumed to be a constant multiple of the standard deviation + of the reference distribution. The first method assumes a fixed margin which is + a constant multiple of the estimated standard deviation of the reference data + and whose variability is ignored. The second method takes into account the margin + variability. In addition, some tools to summarize and illustrate the data and + test results are included to facilitate the evaluation of the data and interpretation + of the results. + date_publication: '2019-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=equivalenceTest + url_git: '' +EQUIVNONINF: + version: 1.0.2 + title: Testing for Equivalence and Noninferiority + maintainer: Stefan Wellek + description: |- + Making available in R the complete set of programs accompanying S. Wellek's (2010) monograph + ''Testing Statistical Hypotheses of Equivalence and Noninferiority. Second Edition'' + (Chapman&Hall/CRC). + date_publication: '2021-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EQUIVNONINF + url_git: '' +equivUMP: + version: 0.1.1 + title: Uniformly Most Powerful Invariant Tests of Equivalence + maintainer: Thoralf Mildenberger + description: |- + Implementation of uniformly most powerful invariant equivalence + tests for one- and two-sample problems (paired and unpaired) as described + in Wellek (2010, ISBN:978-1-4398-0818-4). Also one-sided alternatives + (non-inferiority and non-superiority tests) are supported. Basically a variant + of a t-test with (relaxed) null and alternative hypotheses exchanged. + date_publication: '2019-04-13' + bug_reports: https://github.com/thmild/equivUMP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=equivUMP + url_git: https://github.com/thmild/equivUMP +ER: + version: 1.1.1 + title: Effect + Residual Modelling + maintainer: Kristian Hovde Liland + description: Multivariate modeling of data after deflation of interfering effects. + EF Mosleth et al. (2021) and EF Mosleth et al. + (2020) . + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ER + url_git: '' +era: + version: 0.5.0 + title: Year-Based Time Scales + maintainer: Joe Roe + description: |- + Provides a consistent representation of year-based time scales as a + numeric vector with an associated 'era'. There are built-in era definitions + for many year numbering systems used in contemporary and historic calendars + (e.g. Common Era, Islamic 'Hijri' years); year-based time scales used in + archaeology, astronomy, geology, and other palaeosciences (e.g. + Before Present, SI-prefixed 'annus'); and support for arbitrary user-defined + eras. Years can converted from any one era to another using a generalised + transformation function. Methods are also provided for robust casting and + coercion between years and other numeric types, type-stable arithmetic with + years, and pretty-printing in tables. + date_publication: '2024-11-20' + bug_reports: https://github.com/joeroe/era/issues + url: https://era.joeroe.io + url_cran: https://CRAN.R-project.org/package=era + url_git: https://github.com/joeroe/era +erah: + version: 2.0.1 + title: |- + Automated Spectral Deconvolution, Alignment, and Metabolite + Identification in GC/MS-Based Untargeted Metabolomics + maintainer: Xavier Domingo-Almenara + description: Automated compound deconvolution, alignment across samples, and identification + of metabolites by spectral library matching in Gas Chromatography - Mass spectrometry + (GC-MS) untargeted metabolomics. Outputs a table with compound names, matching + scores and the integrated area of the compound for each sample. Package implementation + is described in Domingo-Almenara et al. (2016) . + date_publication: '2023-12-20' + bug_reports: https://github.com/xdomingoal/erah-devel/issues + url: http://metsyslab.com/ + url_cran: https://CRAN.R-project.org/package=erah + url_git: '' +eratosthenes: + version: 0.0.2 + title: Archaeological Synchronism + maintainer: Stephen A. Collins-Elliott + description: Estimates unknown historical or archaeological dates subject to relationships + with other dates and absolute constraints, derived as marginal densities from + the full joint conditional distribution. Includes rule-based estimation of the + production dates of artifact types. Collins-Elliott (2024) . + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eratosthenes + url_git: '' +ercv: + version: 1.0.1 + title: Fitting Tails by the Empirical Residual Coefficient of Variation + maintainer: Isabel Serra + description: |- + Provides a methodology simple and trustworthy for the analysis of extreme values and multiple threshold tests for a generalized Pareto distribution, together + with an automatic threshold selection algorithm. See del Castillo, J, Daoudi, J and Lockhart, R (2014) . + date_publication: '2019-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ercv + url_git: '' +ERDbuilder: + version: 1.0.0 + title: Entity Relationship Diagrams Builder + maintainer: Guillermo Basulto-Elias + description: Build entity relationship diagrams (ERD) to specify the nature of the + relationship between tables in a database. + date_publication: '2024-04-01' + bug_reports: https://github.com/gbasulto/ERDbuilder/issues + url: https://gbasulto.github.io/ERDbuilder/ + url_cran: https://CRAN.R-project.org/package=ERDbuilder + url_git: https://github.com/gbasulto/ERDbuilder +erer: + version: '4.0' + title: Empirical Research in Economics with R + maintainer: Changyou Sun + description: Several functions, datasets, and sample codes related to empirical + research in economics are included. They cover the marginal effects for binary + or ordered choice models, static and dynamic Almost Ideal Demand System (AIDS) + models, and a typical event analysis in finance. + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=erer + url_git: '' +ergm: + version: 4.8.1 + title: |- + Fit, Simulate and Diagnose Exponential-Family Models for + Networks + maintainer: Pavel N. Krivitsky + description: An integrated set of tools to analyze and simulate networks based on + exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet + suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, + and Morris (2008) and Krivitsky, Hunter, Morris, and + Klumb (2023) . + date_publication: '2025-01-21' + bug_reports: https://github.com/statnet/ergm/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=ergm + url_git: '' +ergm.count: + version: 4.1.2 + title: |- + Fit, Simulate and Diagnose Exponential-Family Models for + Networks with Count Edges + maintainer: Pavel N. Krivitsky + description: A set of extensions for the 'ergm' package to fit weighted networks + whose edge weights are counts. See Krivitsky (2012) and + Krivitsky, Hunter, Morris, and Klumb (2023) . + date_publication: '2024-06-16' + bug_reports: https://github.com/statnet/ergm.count/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=ergm.count + url_git: '' +ergm.ego: + version: 1.1.2 + title: |- + Fit, Simulate and Diagnose Exponential-Family Random Graph + Models to Egocentrically Sampled Network Data + maintainer: Pavel N. Krivitsky + description: Utilities for managing egocentrically sampled network data and a wrapper + around the 'ergm' package to facilitate ERGM inference and simulation from such + data. See Krivitsky and Morris (2017) . + date_publication: '2025-02-12' + bug_reports: https://github.com/statnet/ergm.ego/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=ergm.ego + url_git: '' +ergm.multi: + version: 0.2.1.1 + title: |- + Fit, Simulate and Diagnose Exponential-Family Models for + Multiple or Multilayer Networks + maintainer: Pavel N. Krivitsky + description: A set of extensions for the 'ergm' package to fit multilayer/multiplex/multirelational + networks and samples of multiple networks. 'ergm.multi' is a part of the Statnet + suite of packages for network analysis. See Krivitsky, Koehly, and Marcum (2020) + and Krivitsky, Coletti, and Hens (2023) . + date_publication: '2024-11-05' + bug_reports: https://github.com/statnet/ergm.multi/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=ergm.multi + url_git: '' +ergm.rank: + version: 4.1.1 + title: |- + Fit, Simulate and Diagnose Exponential-Family Models for + Rank-Order Relational Data + maintainer: Pavel N. Krivitsky + description: A set of extensions for the 'ergm' package to fit weighted networks + whose edge weights are ranks. See Krivitsky and Butts (2017) + and Krivitsky, Hunter, Morris, and Klumb (2023) . + date_publication: '2024-06-16' + bug_reports: https://github.com/statnet/ergm.rank/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=ergm.rank + url_git: '' +ergMargins: + version: '1.3' + title: Process Analysis for Exponential Random Graph Models + maintainer: Scott Duxbury + description: |- + Calculates marginal effects and conducts process analysis in exponential family random graph models (ERGM). + Includes functions to conduct mediation and moderation analyses and to diagnose + multicollinearity. + URL: . + BugReports: . + Duxbury, Scott W (2021) . + Long, J. Scott, and Sarah Mustillo (2018) . + Mize, Trenton D. (2019) . + Karlson, Kristian Bernt, Anders Holm, and Richard Breen (2012) . + Duxbury, Scott W (2018) . + Duxbury, Scott W, Jenna Wertsching (2023) . + Huang, Peng, Carter Butts (2023) . + date_publication: '2024-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ergMargins + url_git: '' +ergmgp: + version: 0.1-2 + title: Tools for Modeling ERGM Generating Processes + maintainer: Carter T. Butts + description: Provides tools for simulating draws from continuous time processes + with well-defined exponential family random graph (ERGM) equilibria, i.e. ERGM + generating processes (EGPs). A number of EGPs are supported, including the families + identified in Butts (2023) , as are functions + for hazard calculation and timing calibration. + date_publication: '2024-10-09' + bug_reports: https://github.com/statnet/ergmgp/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=ergmgp + url_git: '' +ergmharris: + version: '1.0' + title: Local Health Department network data set + maintainer: Jenine K. Harris + description: Data for use with the Sage Introduction to ExponentialRandom + Graph Modeling text by Jenine K. Harris. Network dataset consists of + 1283 local health departments and thecommunication links among them along + with several attributes. + date_publication: '2013-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ergmharris + url_git: '' +ergmito: + version: 0.3-1 + title: Exponential Random Graph Models for Small Networks + maintainer: George Vega Yon + description: |- + Simulation and estimation of Exponential Random Graph Models (ERGMs) + for small networks using exact statistics as shown in Vega Yon et al. (2020) + . As a difference from the 'ergm' + package, 'ergmito' circumvents using Markov-Chain Maximum Likelihood Estimator + (MC-MLE) and instead uses Maximum Likelihood Estimator (MLE) to fit ERGMs + for small networks. As exhaustive enumeration is computationally feasible for + small networks, this R package takes advantage of this and provides tools for + calculating likelihood functions, and other relevant functions, directly, + meaning that in many cases both estimation and simulation of ERGMs for + small networks can be faster and more accurate than simulation-based + algorithms. + date_publication: '2023-06-14' + bug_reports: https://github.com/muriteams/ergmito/issues + url: https://muriteams.github.io/ergmito/ + url_cran: https://CRAN.R-project.org/package=ergmito + url_git: '' +erify: + version: 0.6.0 + title: Check Arguments and Generate Readable Error Messages + maintainer: Renfei Mao + description: |- + Provides several validator functions for checking if arguments + passed by users have valid types, lengths, etc. and for generating + informative and well-formatted error messages in a consistent style. Also + provides tools for users to create their own validator functions. The + error message style used is adopted from + . + date_publication: '2024-06-30' + bug_reports: '' + url: https://flujoo.github.io/erify/ + url_cran: https://CRAN.R-project.org/package=erify + url_git: https://github.com/flujoo/erify +ErlangC: + version: 0.1.0 + title: Solve Erlang-C Model + maintainer: Damonsoul + description: Provides a set of functions to solve Erlang-C model. The Erlang C formula + was invented by the Danish Mathematician A.K. Erlang and is used to calculate + the number of advisors and the service level. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ErlangC + url_git: '' +eRm: + version: 1.0-6 + title: Extended Rasch Modeling + maintainer: Patrick Mair + description: Fits Rasch models (RM), linear logistic test models (LLTM), rating + scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), + and linear partial credit models (LPCM). Missing values are allowed in the data + matrix. Additional features are the ML estimation of the person parameters, Andersen's + LR-test, item-specific Wald test, Martin-Loef-Test, nonparametric Monte-Carlo + Tests, itemfit and personfit statistics including infit and outfit measures, ICC + and other plots, automated stepwise item elimination, simulation module for various + binary data matrices. + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eRm + url_git: '' +ern: + version: 2.1.2 + title: Effective Reproduction Number Estimation + maintainer: David Champredon + description: |- + Estimate the effective reproduction number from wastewater + and clinical data sources. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ern + url_git: '' +ERP: + version: '2.2' + title: Significance Analysis of Event-Related Potentials Data + maintainer: David Causeur + description: Functions for signal detection and identification designed for Event-Related + Potentials (ERP) data in a linear model framework. The functional F-test proposed + in Causeur, Sheu, Perthame, Rufini (2018, submitted) for analysis of variance + issues in ERP designs is implemented for signal detection (tests for mean difference + among groups of curves in One-way ANOVA designs for example). Once an experimental + effect is declared significant, identification of significant intervals is achieved + by the multiple testing procedures reviewed and compared in Sheu, Perthame, Lee + and Causeur (2016, ). Some of the methods gathered in + the package are the classical FDR- and FWER-controlling procedures, also available + using function p.adjust. The package also implements the Guthrie-Buchwald procedure + (Guthrie and Buchwald, 1991 ), which accounts + for the auto-correlation among t-tests to control erroneous detection of short + intervals. The Adaptive Factor-Adjustment method is an extension of the method + described in Causeur, Chu, Hsieh and Sheu (2012, ). + It assumes a factor model for the correlation among tests and combines adaptively + the estimation of the signal and the updating of the dependence modelling (see + Sheu et al., 2016, for further details). + date_publication: '2019-12-13' + bug_reports: '' + url: http://erpinr.org + url_cran: https://CRAN.R-project.org/package=ERP + url_git: '' +erp.easy: + version: 1.1.0 + title: Event-Related Potential (ERP) Data Exploration Made Easy + maintainer: Travis Moore + description: |- + A set of user-friendly functions to aid in organizing, plotting + and analyzing event-related potential (ERP) data. Provides an easy-to-learn + method to explore ERP data. Should be useful to those without a background + in computer programming, and to those who are new to ERPs (or new to the + more advanced ERP software available). Emphasis has been placed on highly + automated processes using functions with as few arguments as possible. + Expects processed (cleaned) data. + date_publication: '2017-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=erp.easy + url_git: https://github.com/mooretm/erp.easy +ERPeq: + version: 0.1.0 + title: Probabilistic Hazard Assessment + maintainer: Emrah Altun + description: Computes the probability density and cumulative distribution functions + of fourteen distributions used for the probabilistic hazard assessment. Estimates + the model parameters of the distributions using the maximum likelihood and reports + the goodness-of-fit statistics. The recurrence interval estimations of earthquakes + are computed for each distribution. + date_publication: '2023-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ERPeq + url_git: '' +ERPM: + version: 0.2.0 + title: Exponential Random Partition Models + maintainer: Marion Hoffman + description: |- + Simulates and estimates the Exponential Random Partition Model presented + in the paper Hoffman, Block, and Snijders (2023) . + It can also be used to estimate longitudinal partitions, following the model + proposed in Hoffman and Chabot (2023) . + The model is an exponential family distribution on the space of partitions + (sets of non-overlapping groups) and is called in reference to the Exponential + Random Graph Models (ERGM) for networks. + date_publication: '2024-05-10' + bug_reports: https://github.com/stocnet/ERPM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ERPM + url_git: https://github.com/stocnet/ERPM +errorist: + version: 0.1.2 + title: Automatically Search Errors or Warnings + maintainer: James Balamuta + description: |- + Provides environment hooks that obtain errors and warnings which + occur during the execution of code to automatically search for solutions. + date_publication: '2023-11-14' + bug_reports: https://github.com/coatless-rpkg/errorist/issues + url: https://r-pkg.thecoatlessprofessor.com/errorist/ + url_cran: https://CRAN.R-project.org/package=errorist + url_git: https://github.com/coatless-rpkg/errorist +errorlocate: + version: 1.1.1 + title: Locate Errors with Validation Rules + maintainer: Edwin de Jonge + description: |- + Errors in data can be located and removed using validation rules from package + 'validate'. See also Van der Loo and De Jonge (2018) , + chapter 7. + date_publication: '2023-09-30' + bug_reports: https://github.com/data-cleaning/errorlocate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=errorlocate + url_git: https://github.com/data-cleaning/errorlocate +errors: + version: 0.4.3 + title: Uncertainty Propagation for R Vectors + maintainer: Iñaki Ucar + description: |- + Support for measurement errors in R vectors, matrices and arrays: + automatic uncertainty propagation and reporting. + Documentation about 'errors' is provided in the paper by Ucar, Pebesma & + Azcorra (2018, ), included in this package as a + vignette; see 'citation("errors")' for details. + date_publication: '2025-01-18' + bug_reports: https://github.com/r-quantities/errors/issues + url: https://r-quantities.github.io/errors/ + url_cran: https://CRAN.R-project.org/package=errors + url_git: https://github.com/r-quantities/errors +errum: + version: 0.0.3 + title: Exploratory Reduced Reparameterized Unified Model Estimation + maintainer: James Joseph Balamuta + description: |- + Perform a Bayesian estimation of the exploratory reduced + reparameterized unified model (ErRUM) described by Culpepper and Chen (2018) + . + date_publication: '2020-03-20' + bug_reports: https://github.com/tmsalab/errum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=errum + url_git: https://github.com/tmsalab/errum +ERSA: + version: 0.1.4 + title: Exploratory Regression 'Shiny' App + maintainer: Catherine B. Hurley + description: Constructs a 'shiny' app function with interactive displays for summary + and analysis of variance regression tables, and parallel coordinate plots of data + and residuals. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ERSA + url_git: '' +eRTG3D: + version: 0.7.0 + title: Empirically Informed Random Trajectory Generation in 3-D + maintainer: Merlin Unterfinger + description: |- + Creates realistic random trajectories in a 3-D space between two given fix points, so-called conditional empirical random walks (CERWs). The trajectory generation is based on empirical distribution functions extracted from observed trajectories (training data) and thus reflects the geometrical movement characteristics of the mover. A digital elevation model (DEM), representing the Earth's surface, and a background layer of probabilities (e.g. food sources, uplift potential, waterbodies, etc.) can be used to influence the trajectories. + Unterfinger M (2018). "3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk". Master's thesis, University of Zurich. . + Technitis G, Weibel R, Kranstauber B, Safi K (2016). "An algorithm for empirically informed random trajectory generation between two endpoints". GIScience 2016: Ninth International Conference on Geographic Information Science, 9, online. . + date_publication: '2022-02-25' + bug_reports: https://github.com/munterfi/eRTG3D/issues/ + url: https://munterfi.github.io/eRTG3D/ + url_cran: https://CRAN.R-project.org/package=eRTG3D + url_git: https://github.com/munterfi/eRTG3D/ +es.dif: + version: 1.0.2 + title: Compute Effect Sizes of the Difference + maintainer: Satoshi Aoki + description: Computes various effect sizes of the difference, their variance, and + confidence interval. This package treats Cohen's d, Hedges' d, biased/unbiased + c (an effect size between a mean and a constant) and e (an effect size between + means without assuming the variance equality). + date_publication: '2020-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=es.dif + url_git: '' +esaddle: + version: 0.0.7 + title: Extended Empirical Saddlepoint Density Approximations + maintainer: Matteo Fasiolo + description: Tools for fitting the Extended Empirical Saddlepoint (EES) density + of Fasiolo et al. (2018) . + date_publication: '2021-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=esaddle + url_git: https://github.com/mfasiolo/esaddle +esaps: + version: 0.2.2 + title: Indicators of Electoral Systems and Party Systems + maintainer: Nicolas Schmidt + description: |- + It allows structuring electoral data of different size and structure + to calculate various indicators frequently used in the studies of electoral systems and party systems. + Indicators of electoral volatility, electoral disproportionality, party nationalization and the + effective number of parties are included. + date_publication: '2021-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=esaps + url_git: https://github.com/Nicolas-Schmidt/esaps +esback: + version: 0.3.1 + title: Expected Shortfall Backtesting + maintainer: Sebastian Bayer + description: |- + Implementations of the expected shortfall backtests of Bayer and Dimitriadis (2020) + as well as other well known backtests from the literature. Can be used to assess the correctness of forecasts of the + expected shortfall risk measure which is e.g. used in the banking and finance industry for quantifying the market risk + of investments. A special feature of the backtests of Bayer and Dimitriadis (2020) + is that they only require forecasts of the expected shortfall, which is in striking contrast to all other existing + backtests, making them particularly attractive for practitioners. + date_publication: '2023-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=esback + url_git: '' +esc: + version: 0.5.1 + title: Effect Size Computation for Meta Analysis + maintainer: Daniel Lüdecke + description: |- + Implementation of the web-based 'Practical Meta-Analysis Effect Size + Calculator' from David B. Wilson () + in R. Based on the input, the effect size can be returned as standardized mean + difference, Cohen's f, Hedges' g, Pearson's r or Fisher's + transformation z, odds ratio or log odds, or eta squared effect size. + date_publication: '2019-12-04' + bug_reports: https://github.com/strengejacke/esc/issues + url: https://strengejacke.github.io/esc + url_cran: https://CRAN.R-project.org/package=esc + url_git: '' +escalation: + version: 0.1.10 + title: A Modular Approach to Dose-Finding Clinical Trials + maintainer: Kristian Brock + description: |- + Methods for working with dose-finding clinical trials. We provide + implementations of many dose-finding clinical trial designs, including the + continual reassessment method (CRM) by O'Quigley et al. (1990) + , the toxicity probability interval (TPI) design by Ji + et al. (2007) , the modified TPI (mTPI) design + by Ji et al. (2010) , the Bayesian optimal + interval design (BOIN) by Liu & Yuan (2015) , EffTox + by Thall & Cook (2004) ; the design of + Wages & Tait (2015) , and the 3+3 + described by Korn et al. (1994) . All designs + are implemented with a common interface. We also offer optional additional + classes to tailor the behaviour of all designs, including avoiding skipping + doses, stopping after n patients have been treated at the recommended dose, + stopping when a toxicity condition is met, or demanding that n patients are + treated before stopping is allowed. By daisy-chaining together these classes + using the pipe operator from 'magrittr', it is simple to tailor the + behaviour of a dose-finding design so it behaves how the trialist wants. + Having provided a flexible interface for specifying designs, we then provide + functions to run simulations and calculate dose-paths for future cohorts of + patients. + date_publication: '2024-06-27' + bug_reports: https://github.com/brockk/escalation/issues + url: https://brockk.github.io/escalation/ + url_cran: https://CRAN.R-project.org/package=escalation + url_git: https://github.com/brockk/escalation +esci: + version: 1.0.7 + title: Estimation Statistics with Confidence Intervals + maintainer: Robert Calin-Jageman + description: A collection of functions and 'jamovi' module for the estimation approach + to inferential statistics, the approach which emphasizes effect sizes, interval + estimates, and meta-analysis. Nearly all functions are based on 'statpsych' and + 'metafor'. This package is still under active development, and breaking changes + are likely, especially with the plot and hypothesis test functions. Data sets + are included for all examples from Cumming & Calin-Jageman (2024) . + date_publication: '2025-02-22' + bug_reports: https://github.com/rcalinjageman/esci/issues/ + url: https://rcalinjageman.github.io/esci/ + url_cran: https://CRAN.R-project.org/package=esci + url_git: https://github.com/rcalinjageman/esci/ +EScvtmle: + version: 0.0.2 + title: |- + Experiment-Selector CV-TMLE for Integration of Observational and + RCT Data + maintainer: Lauren Eyler Dang + description: The experiment selector cross-validated targeted maximum likelihood + estimator (ES-CVTMLE) aims to select the experiment that optimizes the bias-variance + tradeoff for estimating a causal average treatment effect (ATE) where different + experiments may include a randomized controlled trial (RCT) alone or an RCT combined + with real-world data. Using cross-validation, the ES-CVTMLE separates the selection + of the optimal experiment from the estimation of the ATE for the chosen experiment. + The estimated bias term in the selector is a function of the difference in conditional + mean outcome under control for the RCT compared to the combined experiment. In + order to help include truly unbiased external data in the analysis, the estimated + average treatment effect on a negative control outcome may be added to the bias + term in the selector. For more details about this method, please see Dang et al. + (2022) . + date_publication: '2023-01-05' + bug_reports: https://github.com/Lauren-EylerDang/EScvtmle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EScvtmle + url_git: https://github.com/Lauren-EylerDang/EScvtmle/tree/main +esDesign: + version: 1.0.3 + title: Adaptive Enrichment Designs with Sample Size Re-Estimation + maintainer: Zhao Yang + description: |- + Software of 'esDesign' is developed to implement the adaptive + enrichment designs with sample size re-estimation presented in + Lin et al. (2021) . In details, + three-proposed trial designs are provided, including the AED1-SSR (or ES1-SSR), + AED2-SSR (or ES2-SSR) and AED3-SSR (or ES3-SSR). In addition, this package + also contains several widely used adaptive designs, such as the Marker + Sequential Test (MaST) design proposed Freidlin et al. + (2014) , the adaptive enrichment designs + without early stopping (AED or ES), the sample size re-estimation + procedure (SSR) based on the conditional power proposed by + Proschan and Hunsberger (1995), and some useful functions. + In details, we can calculate the futility and/or efficacy stopping + boundaries, the sample size required, calibrate the value of the threshold + of the difference between subgroup-specific test statistics, conduct the + simulation studies in AED, SSR, AED1-SSR, AED2-SSR and AED3-SSR. + date_publication: '2021-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=esDesign + url_git: '' +eSDM: + version: 0.4.4 + title: Ensemble Tool for Predictions from Species Distribution Models + maintainer: Sam Woodman + description: |- + A tool which allows users to create and evaluate ensembles + of species distribution model (SDM) predictions. + Functionality is offered through R functions or a GUI (R Shiny app). + This tool can assist users in identifying spatial uncertainties and + making informed conservation and management decisions. The package is + further described in Woodman et al (2019) . + date_publication: '2024-10-07' + bug_reports: https://github.com/swfsc/eSDM/issues/ + url: https://swfsc.github.io/eSDM/ + url_cran: https://CRAN.R-project.org/package=eSDM + url_git: https://github.com/swfsc/eSDM/ +eseis: + version: 0.8.0 + title: Environmental Seismology Toolbox + maintainer: Michael Dietze + description: |- + Environmental seismology is a scientific field that studies the + seismic signals, emitted by Earth surface processes. This package + provides all relevant functions to read/write seismic data files, prepare, + analyse and visualise seismic data, and generate reports of the processing + history. + date_publication: '2024-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eseis + url_git: '' +eselect: + version: '1.1' + title: |- + Adaptive Clinical Trial Designs with Endpoint Selection and + Sample Size Reassessment + maintainer: Marta Bofill Roig + description: Endpoint selection and sample size reassessment for multiple binary + endpoints based on blinded and/or unblinded data. Trial design that allows an + adaptive modification of the primary endpoint based on blinded information obtained + at an interim analysis. The decision rule chooses the endpoint with the lower + estimated required sample size. Additionally, the sample size is reassessed using + the estimated event probabilities and correlation between endpoints. The implemented + design is proposed in Bofill Roig, M., Gómez Melis, G., Posch, M., and Koenig, + F. (2022). . + date_publication: '2023-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eselect + url_git: '' +esem: + version: 2.0.0 + title: Exploratory Structural Equation Modeling ESEM + maintainer: Maria Prokofieva + description: |- + A collection of functions developed to support the tutorial on using Exploratory Structural Equiation Modeling (ESEM) (Asparouhov & Muthén, 2009) ) with Longitudinal Study of Australian Children (LSAC) dataset (Mohal et al., 2023) . + The package uses 'tidyverse','psych', 'lavaan','semPlot' and provides additional functions to conduct ESEM. + The package provides general functions to complete ESEM, including esem_c(), creation of target matrix (if it is used) make_target(), generation of the Confirmatory Factor Analysis (CFA) model syntax esem_cfa_syntax(). + A sample data is provided - the package includes a sample data of the Strengths and Difficulties Questionnaire of the Longitudinal Study of Australian Children (SDQ LSAC) in sdq_lsac(). + 'ESEM' package vignette presents the tutorial demonstrating the use of ESEM on SDQ LSAC data. + date_publication: '2023-07-05' + bug_reports: https://github.com/maria-pro/esem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=esem + url_git: https://github.com/maria-pro/esem +esemifar: + version: 2.0.1 + title: Smoothing Long-Memory Time Series + maintainer: Dominik Schulz + description: |- + The nonparametric trend and its derivatives in equidistant time + series (TS) with long-memory errors can be estimated. The + estimation is conducted via local polynomial regression using an + automatically selected bandwidth obtained by a built-in iterative plug-in + algorithm or a bandwidth fixed by the user. + The smoothing methods of the package are described in Letmathe, S., Beran, + J. and Feng, Y., (2023) . + date_publication: '2024-05-07' + bug_reports: '' + url: https://wiwi.uni-paderborn.de/en/dep4/feng/ + url_cran: https://CRAN.R-project.org/package=esemifar + url_git: '' +ESG: + version: '1.3' + title: A Package for Asset Projection + maintainer: Wassim Youssef + description: |- + Presents a "Scenarios" class containing + general parameters, risk parameters and projection results. + Risk parameters are gathered together into a ParamsScenarios + sub-object. The general process for using this package is to + set all needed parameters in a Scenarios object, use the + customPathsGeneration method to proceed to the projection, then + use xxx_PriceDistribution() methods to get asset prices. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ESG + url_git: '' +eshrink: + version: 0.1.2 + title: Shrinkage for Effect Estimation + maintainer: Joshua Keller + description: |- + Computes shrinkage estimators for regression problems. Selects + penalty parameter by minimizing bias and variance in the effect estimate, where bias and variance are estimated from the posterior predictive distribution. See Keller and Rice (2017) for more details. + date_publication: '2020-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eshrink + url_git: '' +eSIR: + version: 0.4.2 + title: Extended State-Space SIR Models + maintainer: Michael Kleinsasser + description: |- + An implementation of extended state-space SIR models developed by + Song Lab at UM school of Public Health. There are several functions available + by 1) including a time-varying transmission modifier, 2) adding a time-dependent + quarantine compartment, 3) adding a time-dependent antibody-immunization compartment. + Wang L. (2020) . + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eSIR + url_git: '' +esmisc: + version: 0.0.3 + title: Misc Functions of Eduard Szöcs + maintainer: Eduard Szöcs + description: |- + Misc functions programmed by Eduard Szöcs. + Provides read_regnie() to read gridded precipitation data from German Weather + Service (DWD, see for more information). + date_publication: '2017-01-11' + bug_reports: https://github.com/EDiLD/esmisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=esmisc + url_git: https://github.com/EDiLD/esmisc +esmprep: + version: 0.2.0 + title: |- + Data Preparation During and After the Use of the Experience + Sampling Methodology (ESM) + maintainer: Marcel Miché + description: Support in preparing a raw ESM dataset for statistical analysis. Preparation + includes the handling of errors (mostly due to technological reasons) and the + generating of new variables that are necessary and/or helpful in meeting the conditions + when statistically analyzing ESM data. The functions in 'esmprep' are meant to + hierarchically lead from bottom, i.e. the raw (separated) ESM dataset(s), to top, + i.e. a single ESM dataset ready for statistical analysis. This hierarchy evolved + out of my personal experience in working with ESM data. + date_publication: '2019-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=esmprep + url_git: https://github.com/mmiche/esmprep +esmtools: + version: 1.0.1 + title: Preprocessing Experience Sampling Method (ESM) Data + maintainer: Jordan Revol + description: |- + Tailored explicitly for Experience Sampling Method (ESM) + data, it contains a suite of functions designed to simplify + preprocessing steps and create subsequent reporting. It empowers + users with capabilities to extract critical insights during + preprocessing, conducts thorough data quality assessments (e.g., design + and sampling scheme checks, compliance rate, careless responses), and + generates visualizations and concise summary tables tailored + specifically for ESM data. Additionally, it streamlines the creation + of informative and interactive preprocessing reports, enabling + researchers to transparently share their dataset preprocessing + methodologies. Finally, it is part of a larger ecosystem which + includes a framework and a web gallery + (). + date_publication: '2024-03-13' + bug_reports: https://gitlab.kuleuven.be/ppw-okpiv/researchers/u0148925/esmtools/-/issues + url: https://gitlab.kuleuven.be/ppw-okpiv/researchers/u0148925/esmtools/ + url_cran: https://CRAN.R-project.org/package=esmtools + url_git: '' +espadon: + version: 1.10.0 + title: Easy Study of Patient DICOM Data in Oncology + maintainer: Cathy Fontbonne + description: Exploitation, processing and 2D-3D visualization of DICOM-RT files + (structures, dosimetry, imagery) for medical physics and clinical research, in + a patient-oriented perspective. + date_publication: '2025-02-05' + bug_reports: '' + url: https://espadon.cnrs.fr + url_cran: https://CRAN.R-project.org/package=espadon + url_git: '' +esquisse: + version: 2.1.0 + title: Explore and Visualize Your Data Interactively + maintainer: Victor Perrier + description: |- + A 'shiny' gadget to create 'ggplot2' figures interactively with drag-and-drop to map your variables to different aesthetics. + You can quickly visualize your data accordingly to their type, export in various formats, + and retrieve the code to reproduce the plot. + date_publication: '2025-02-21' + bug_reports: https://github.com/dreamRs/esquisse/issues + url: https://dreamrs.github.io/esquisse/ + url_cran: https://CRAN.R-project.org/package=esquisse + url_git: https://github.com/dreamRs/esquisse +esreg: + version: 0.6.2 + title: Joint Quantile and Expected Shortfall Regression + maintainer: Sebastian Bayer + description: |2- + + Simultaneous modeling of the quantile and the expected shortfall of a response variable given + a set of covariates, see Dimitriadis and Bayer (2019) . + date_publication: '2023-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=esreg + url_git: '' +ess: + version: 1.1.2 + title: Efficient Stepwise Selection in Decomposable Models + maintainer: Mads Lindskou + description: |- + An implementation of the ESS algorithm following Amol Deshpande, Minos Garofalakis, + Michael I Jordan (2013) . The ESS algorithm + is used for model selection in decomposable graphical models. + date_publication: '2021-05-31' + bug_reports: https://github.com/mlindsk/ess/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ess + url_git: https://github.com/mlindsk/ess +essentials: + version: 0.1.0 + title: Essential Functions not Included in Base R + maintainer: Andrew Simmons + description: |- + Functions for converting objects to scalars (vectors of length 1) + and a more inclusive definition of data that can be interpreted as numbers + (numeric and complex alike). + date_publication: '2021-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=essentials + url_git: '' +essHist: + version: 1.2.2 + title: The Essential Histogram + maintainer: Housen Li + description: Provide an optimal histogram, in the sense of probability density estimation + and features detection, by means of multiscale variational inference. In other + words, the resulting histogram servers as an optimal density estimator, and meanwhile + recovers the features, such as increases or modes, with both false positive and + false negative controls. Moreover, it provides a parsimonious representation in + terms of the number of blocks, which simplifies data interpretation. The only + assumption for the method is that data points are independent and identically + distributed, so it applies to fairly general situations, including continuous + distributions, discrete distributions, and mixtures of both. For details see Li, + Munk, Sieling and Walther (2016) . + date_publication: '2019-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=essHist + url_git: '' +essurvey: + version: 1.0.8 + title: Download Data from the European Social Survey on the Fly + maintainer: Jorge Cimentada + description: Download data from the European Social Survey directly from their website + . There are two families of functions that + allow you to download and interactively check all countries and rounds available. + date_publication: '2022-01-09' + bug_reports: https://github.com/ropensci/essurvey/issues + url: https://docs.ropensci.org/essurvey/ + url_cran: https://CRAN.R-project.org/package=essurvey + url_git: https://github.com/ropensci/essurvey +estadistica: + version: 0.2.3 + title: Fundamentos De Estadistica Descriptiva e Inferencial + maintainer: Vicente Coll-Serrano + description: 'Este paquete pretende apoyar el proceso enseñanza-aprendizaje de estadística + descriptiva e inferencial. Las funciones contenidas en el paquete ''estadistica'' + cubren los conceptos básicos estudiados en un curso introductorio. Muchos conceptos + son ilustrados con gráficos dinámicos o web apps para facilitar su comprensión. + This package aims to help the teaching-learning process of descriptive and inferential + statistics. The functions contained in the package ''estadistica'' cover the basic + concepts studied in a statistics introductory course. Many concepts are illustrated + with dynamic graphs or web apps to make the understanding easier. See: Esteban + et al. (2005, ISBN: 9788497323741), Newbold et al.(2019, ISBN:9781292315034 ), + Murgui et al. (2002, ISBN:9788484424673) .' + date_publication: '2023-05-15' + bug_reports: '' + url: https://www.uv.es/estadistic/ + url_cran: https://CRAN.R-project.org/package=estadistica + url_git: '' +estatapi: + version: 0.4.0 + title: R Interface to e-Stat API + maintainer: Hiroaki Yutani + description: Provides an interface to e-Stat API, the one-stop service for official + statistics of the Japanese government. + date_publication: '2020-04-12' + bug_reports: https://github.com/yutannihilation/estatapi/issues + url: https://yutannihilation.github.io/estatapi/ + url_cran: https://CRAN.R-project.org/package=estatapi + url_git: '' +EstCRM: + version: '1.6' + title: Calibrating Parameters for the Samejima's Continuous IRT Model + maintainer: Cengiz Zopluoglu + description: Estimates item and person parameters for the Continuous Response Model + (CRM; Samejima, 1973, ), computes item fit residual statistics, + draws empirical 3D item category response curves, draws theoretical 3D item category + response curves, and generates data under the CRM for simulation studies. + date_publication: '2022-09-16' + bug_reports: '' + url: https://cengiz.me/ + url_cran: https://CRAN.R-project.org/package=EstCRM + url_git: '' +ESTER: + version: 0.2.0 + title: Efficient Sequential Testing with Evidence Ratios + maintainer: Ladislas Nalborczyk + description: |- + An implementation of sequential testing that uses evidence ratios + computed from the weights of a set of models. These weights correspond either + to Akaike weights computed from the Akaike Information Criterion (AIC) or the + Bayesian Information Criterion (BIC) and following Burnham & Anderson + (2004, ) recommendations, or to pseudo-BMA + weights computed from the WAIC or the LOO-IC of models fitted + with 'brms' and following Yao et al. (2017, ). + date_publication: '2017-12-10' + bug_reports: https://github.com/lnalborczyk/ESTER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ESTER + url_git: https://github.com/lnalborczyk/ESTER +estimability: + version: 1.5.1 + title: Tools for Assessing Estimability of Linear Predictions + maintainer: Russell Lenth + description: |- + Provides tools for determining estimability of linear functions + of regression coefficients, and 'epredict' methods that handle + non-estimable cases correctly. Estimability theory is discussed in + many linear-models textbooks including Chapter 3 of Monahan, JF (2008), + "A Primer on Linear Models", Chapman and Hall (ISBN 978-1-4200-6201-4). + date_publication: '2024-05-12' + bug_reports: https://github.com/rvlenth/estimability/issues + url: https://rvlenth.github.io/estimability/ + url_cran: https://CRAN.R-project.org/package=estimability + url_git: https://github.com/rvlenth/estimability +EstimateGroupNetwork: + version: 0.3.1 + title: Perform the Joint Graphical Lasso and Selects Tuning Parameters + maintainer: Giulio Costantini + description: Can be used to simultaneously estimate networks (Gaussian Graphical + Models) in data from different groups or classes via Joint Graphical Lasso. Tuning + parameters are selected via information criteria (AIC / BIC / extended BIC) or + cross validation. + date_publication: '2021-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EstimateGroupNetwork + url_git: '' +estimateW: + version: 0.0.1 + title: Estimation of Spatial Weight Matrices + maintainer: Tamas Krisztin + description: Bayesian estimation of spatial weight matrices in spatial econometric + panel models. Allows for estimation of spatial autoregressive (SAR), spatial Durbin + (SDM), and spatially lagged explanatory variable (SLX) type specifications featuring + an unknown spatial weight matrix. Methodological details are given in Krisztin + and Piribauer (2022) . + date_publication: '2022-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=estimateW + url_git: '' +EstimationTools: + version: 4.0.0 + title: |- + Maximum Likelihood Estimation for Probability Functions from + Data Sets + maintainer: Jaime Mosquera + description: |- + Total Time on Test plot and routines for parameter estimation of + any lifetime distribution implemented in R via maximum likelihood (ML) given + a data set. It is implemented thinking on parametric survival analysis, but + it feasible to use in parameter estimation of probability density or mass + functions in any field. The main routines 'maxlogL' and 'maxlogLreg' are + wrapper functions specifically developed for ML estimation. There are + included optimization procedures such as 'nlminb' and 'optim' from base + package, and 'DEoptim' Mullen (2011) . Standard + errors are estimated with 'numDeriv' Gilbert (2011) + or the option 'Hessian = TRUE' + of 'optim' function. + date_publication: '2022-12-10' + bug_reports: https://github.com/Jaimemosg/EstimationTools/issues + url: https://jaimemosg.github.io/EstimationTools/ + url_cran: https://CRAN.R-project.org/package=EstimationTools + url_git: https://github.com/Jaimemosg/EstimationTools +estimators: + version: 0.8.5 + title: Parameter Estimation + maintainer: Ioannis Oikonomidis + description: |- + Implements estimation methods for parameters of common + distribution families. The common d, p, q, r function family for each + distribution is enriched with the ll, e, and v counterparts, computing + the log-likelihood, performing estimation, and calculating the asymptotic + variance - covariance matrix, respectively. Parameter estimation is + performed analytically whenever possible. + date_publication: '2024-05-16' + bug_reports: https://github.com/thechibo/estimators/issues + url: https://thechibo.github.io/estimators/ + url_cran: https://CRAN.R-project.org/package=estimators + url_git: '' +estimatr: + version: 1.0.6 + title: Fast Estimators for Design-Based Inference + maintainer: Graeme Blair + description: Fast procedures for small set of commonly-used, design-appropriate + estimators with robust standard errors and confidence intervals. Includes estimators + for linear regression, instrumental variables regression, difference-in-means, + Horvitz-Thompson estimation, and regression improving precision of experimental + estimates by interacting treatment with centered pre-treatment covariates introduced + by Lin (2013) . + date_publication: '2025-02-28' + bug_reports: https://github.com/DeclareDesign/estimatr/issues + url: https://declaredesign.org/r/estimatr/ + url_cran: https://CRAN.R-project.org/package=estimatr + url_git: https://github.com/DeclareDesign/estimatr +EstimDiagnostics: + version: 0.0.3 + title: Diagnostic Tools and Unit Tests for Statistical Estimators + maintainer: Dmitry Otryakhin + description: Extension of 'testthat' package to make unit tests on empirical distributions + of estimators and functions for diagnostics of their finite-sample performance. + date_publication: '2021-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EstimDiagnostics + url_git: https://gitlab.com/Dmitry_Otryakhin/diagnostics-and-tests-for-statistical-estimators +estimraw: + version: 1.0.0 + title: |- + Estimation of Four-Fold Table Cell Frequencies (Raw Data) from + Effect Size Measures + maintainer: Bernardo Sousa-Pinto + description: Estimation of four-fold table cell frequencies (raw data) from risk + ratios (relative risks), risk differences and odds ratios. While raw data can + be useful for doing meta-analysis, such data is often not provided by primary + studies (with summary statistics being solely presented). Therefore, based on + summary statistics (namely, risk ratios, risk differences and odds ratios), this + package estimates the value of each cell in a 2x2 table according to the equations + described in Di Pietrantonj C (2006) . + date_publication: '2020-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=estimraw + url_git: '' +estmeansd: + version: 1.0.1 + title: |- + Estimating the Sample Mean and Standard Deviation from Commonly + Reported Quantiles in Meta-Analysis + maintainer: Sean McGrath + description: |- + Implements the methods of McGrath et al. (2020) + and Cai et al. (2021) + for estimating the sample mean and standard + deviation from commonly reported quantiles in meta-analysis. These methods + can be applied to studies that report the sample median, sample size, and + one or both of (i) the sample minimum and maximum values and (ii) the first + and third quartiles. The corresponding standard error estimators described + by McGrath et al. (2023) are also included. + date_publication: '2023-12-14' + bug_reports: https://github.com/stmcg/estmeansd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=estmeansd + url_git: https://github.com/stmcg/estmeansd +EstMix: + version: 1.0.1 + title: Tumor Clones Percentage Estimations + maintainer: Xuan You + description: Includes R functions for the estimation of tumor clones percentages + for both snp data and (whole) genome sequencing data. See Cheng, Y., Dai, J. Y., + Paulson, T. G., Wang, X., Li, X., Reid, B. J., & Kooperberg, C. (2017). Quantification + of multiple tumor clones using gene array and sequencing data. The Annals of Applied + Statistics, 11(2), 967-991, for more details. + date_publication: '2018-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EstMix + url_git: '' +estprod: + version: '1.2' + title: Estimation of Production Functions + maintainer: Rodrigo R Remédio + description: |- + Estimation of production functions by the Olley-Pakes, Levinsohn-Petrin and Wooldridge methodologies. + The package aims to reproduce the results obtained with the Stata's user written opreg and levpet commands. + The first was originally proposed by Olley, G.S. and Pakes, A. (1996) . + The second by Levinsohn, J. and Petrin, A. (2003) . + And the third by Wooldridge (2009) . + date_publication: '2020-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=estprod + url_git: '' +esvis: + version: 0.3.1 + title: Visualization and Estimation of Effect Sizes + maintainer: Daniel Anderson + description: |- + A variety of methods are provided to estimate and visualize + distributional differences in terms of effect sizes. Particular emphasis + is upon evaluating differences between two or more distributions across + the entire scale, rather than at a single point (e.g., differences in + means). For example, Probability-Probability (PP) plots display the + difference between two or more distributions, matched by their empirical + CDFs (see Ho and Reardon, 2012; ), allowing + for examinations of where on the scale distributional differences are + largest or smallest. The area under the PP curve (AUC) is an effect-size + metric, corresponding to the probability that a randomly selected + observation from the x-axis distribution will have a higher value + than a randomly selected observation from the y-axis distribution. + Binned effect size plots are also available, in which the distributions + are split into bins (set by the user) and separate effect sizes (Cohen's + d) are produced for each bin - again providing a means to evaluate the + consistency (or lack thereof) of the difference between two or more + distributions at different points on the scale. Evaluation of empirical + CDFs is also provided, with built-in arguments for providing annotations + to help evaluate distributional differences at specific points (e.g., + semi-transparent shading). All function take a consistent argument + structure. Calculation of specific effect sizes is also possible. The + following effect sizes are estimable: (a) Cohen's d, (b) Hedges' g, + (c) percentage above a cut, (d) transformed (normalized) percentage above + a cut, (e) area under the PP curve, and (f) the V statistic (see Ho, + 2009; ), which essentially transforms the + area under the curve to standard deviation units. By default, effect sizes + are calculated for all possible pairwise comparisons, but a reference + group (distribution) can be specified. + date_publication: '2020-04-30' + bug_reports: https://github.com/datalorax/esvis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=esvis + url_git: https://github.com/datalorax/esvis +et.nwfva: + version: 0.1.1 + title: Forest Yield Tables for Northwest Germany and their Application + maintainer: Robert Nuske + description: |- + The new yield tables developed by the Northwest German Forest + Research Institute (NW-FVA) provide a forest management tool for the five + main commercial tree species oak, beech, spruce, Douglas-fir and pine for + northwestern Germany. The new method applied for deriving yield tables + combines measurements of growth and yield trials with growth simulations + using a state-of-the-art single-tree growth simulator. By doing so, the new + yield tables reflect the current increment level and the recommended + graduated thinning from above is the underlying management concept. The yield + tables are provided along with methods for deriving the site index and for + interpolating between age and site indices and extrapolating beyond age and + site index ranges. The inter-/extrapolations are performed traditionally by + the rule of proportion or with a functional approach. + date_publication: '2022-11-22' + bug_reports: https://github.com/rnuske/et.nwfva/issues + url: '' + url_cran: https://CRAN.R-project.org/package=et.nwfva + url_git: https://github.com/rnuske/et.nwfva +etable: + version: 1.3.1 + title: Easy Table + maintainer: Andreas Schulz + description: Creates simple to highly customized tables for a wide selection of + descriptive statistics, with or without weighting the data. + date_publication: '2021-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=etable + url_git: '' +ETAS: + version: 0.6.1.1 + title: Modeling Earthquake Data Using 'ETAS' Model + maintainer: Abdollah Jalilian + description: |- + Fits the space-time Epidemic Type Aftershock Sequence + ('ETAS') model to earthquake catalogs using a stochastic 'declustering' + approach. The 'ETAS' model is a 'spatio-temporal' marked point process + model and a special case of the 'Hawkes' process. The package is based + on a Fortran program by 'Jiancang Zhuang' + (available at ), + which is modified and translated into C++ and C such that it + can be called from R. Parallel computing with 'OpenMP' is possible + on supported platforms. + date_publication: '2024-09-23' + bug_reports: https://github.com/jalilian/ETAS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ETAS + url_git: https://github.com/jalilian/ETAS +ETASbootstrap: + version: 0.2.0 + title: |- + Bootstrap Confidence Interval Estimation for 'ETAS' Model + Parameters + maintainer: Renjie Peng + description: |- + The 2-D spatial and temporal Epidemic Type Aftershock Sequence ('ETAS') Model is + widely used to 'decluster' earthquake data catalogs. Usually, the calculation of standard + errors of the 'ETAS' model parameter estimates is based on the Hessian matrix derived from + the log-likelihood function of the fitted model. However, when an 'ETAS' model is fitted to + a local data set over a time period that is limited or short, the standard errors based on + the Hessian matrix may be inaccurate. It follows that the asymptotic confidence intervals + for parameters may not always be reliable. As an alternative, this package allows for the + construction of bootstrap confidence intervals based on empirical quantiles for the parameters + of the 2-D spatial and temporal 'ETAS' model. This version improves on Version 0.1.0 of the + package by enabling the study space window (renamed 'study region') to be polygonal rather + than merely rectangular. A Japan earthquake data catalog is used in a second example to + illustrate this new feature. + date_publication: '2024-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ETASbootstrap + url_git: '' +etasFLP: + version: 2.2.2 + title: |- + Mixed FLP and ML Estimation of ETAS Space-Time Point Processes + for Earthquake Description + maintainer: Marcello Chiodi + description: 'Estimation of the components of an ETAS (Epidemic Type Aftershock + Sequence) model for earthquake description. Non-parametric background seismicity + can be estimated through FLP (Forward Likelihood Predictive). New version 2.0.0: + covariates have been introduced to explain the effects of external factors on + the induced seismicity; the parametrization has been changed; Chiodi, Adelfio + (2017).' + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=etasFLP + url_git: '' +ETC: + version: '1.5' + title: Equivalence to Control + maintainer: Mario Hasler + description: |- + Treatments of a one-way layout, being equivalent to a control, + can be selected with this package. Bonferroni adjusted "two one-sided + t-tests" (TOST) and related simultaneous confidence intervals are given for + both differences or ratios of means of normally distributed data. For the + case of equal variances and balanced sample sizes for the treatment groups, + the single-step procedure of Bofinger and Bofinger (1995) + can be chosen. For non-normal data, + the Wilcoxon test is applied. + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ETC + url_git: '' +ethnobotanyR: + version: 0.1.9 + title: Calculate Quantitative Ethnobotany Indices + maintainer: Cory Whitney + description: 'An implementation of the quantitative ethnobotany indices in R. The + goal is to provide an easy-to-use platform for ethnobotanists to assess the cultural + significance of plant species based on informant consensus. The package closely + follows the paper by Tardio and Pardo-de-Santayana (2008). Tardio, J., and M. + Pardo-de-Santayana, 2008. Cultural Importance Indices: A Comparative Analysis + Based on the Useful Wild Plants of Southern Cantabria (Northern Spain) 1. Economic + Botany, 62(1), 24-39. .' + date_publication: '2022-12-17' + bug_reports: https://github.com/CWWhitney/ethnobotanyR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ethnobotanyR + url_git: '' +EthSEQ: + version: 3.0.2 + title: |- + Ethnicity Annotation from Whole-Exome and Targeted Sequencing + Data + maintainer: Alessandro Romanel + description: Reliable and rapid ethnicity annotation from whole exome and targeted + sequencing data. + date_publication: '2023-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EthSEQ + url_git: '' +etl: + version: 0.4.1 + title: Extract-Transform-Load Framework for Medium Data + maintainer: Benjamin S. Baumer + description: |- + A predictable and pipeable framework for performing ETL + (extract-transform-load) operations on publicly-accessible medium-sized data + set. This package sets up the method structure and implements generic + functions. Packages that depend on this package download specific data sets + from the Internet, clean them up, and import them into a local or remote + relational database management system. + date_publication: '2023-10-12' + bug_reports: https://github.com/beanumber/etl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=etl + url_git: https://github.com/beanumber/etl +ETLUtils: + version: '1.5' + title: |- + Utility Functions to Execute Standard Extract/Transform/Load + Operations (using Package 'ff') on Large Data + maintainer: Jan Wijffels + description: |- + Provides functions to facilitate the use of the 'ff' package + in interaction with big data in 'SQL' databases (e.g. in 'Oracle', 'MySQL', + 'PostgreSQL', 'Hive') by allowing easy importing directly into 'ffdf' objects + using 'DBI', 'RODBC' and 'RJDBC'. Also contains some basic utility functions to + do fast left outer join merging based on 'match', factorisation of data and a + basic function for re-coding vectors. + date_publication: '2020-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ETLUtils + url_git: https://github.com/jwijffels/ETLUtils +etm: + version: 1.1.1 + title: Empirical Transition Matrix + maintainer: Mark Clements + description: The etm (empirical transition matrix) package permits to estimate the + matrix of transition probabilities for any time-inhomogeneous multi-state model + with finite state space using the Aalen-Johansen estimator. Functions for data + preparation and for displaying are also included (Allignol et al., 2011 ). + Functionals of the Aalen-Johansen estimator, e.g., excess length-of-stay in an + intermediate state, can also be computed (Allignol et al. 2011 ). + date_publication: '2020-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=etm + url_git: '' +etrader: + version: 0.1.5 + title: '''ETRADE'' API Interface for R' + maintainer: Anthony Balentine + description: |- + Use R to interface with the 'ETRADE' API . + Functions include authentication, trading, quote requests, account information, and option + chains. A user will need an ETRADE brokerage account and 'ETRADE' API approval. See README + for authentication process and examples. + date_publication: '2023-01-05' + bug_reports: https://github.com/exploringfinance/etrader/issues + url: https://exploringfinance.github.io/etrader/ + url_cran: https://CRAN.R-project.org/package=etrader + url_git: '' +etree: + version: 0.1.0 + title: |- + Classification and Regression with Structured and Mixed-Type + Data + maintainer: Riccardo Giubilei + description: |- + Implementation of Energy Trees, a statistical model to perform + classification and regression with structured and mixed-type data. The + model has a similar structure to Conditional Trees, but brings in Energy + Statistics to test independence between variables that are possibly + structured and of different nature. Currently, the package covers functions + and graphs as structured covariates. It builds upon 'partykit' to + provide functionalities for fitting, printing, plotting, and predicting with + Energy Trees. Energy Trees are described in Giubilei et al. (2022) + . + date_publication: '2022-07-16' + bug_reports: https://github.com/ricgbl/etree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=etree + url_git: https://github.com/ricgbl/etree +ETRep: + version: 1.1.0 + title: |- + Analysis of Elliptical Tubes Under the Relative Curvature + Condition + maintainer: Mohsen Taheri Shalmani + description: 'Analysis of elliptical tubes with applications in biological modeling. + The package is based on the references: Taheri, M., Pizer, S. M., & Schulz, J. + (2024) "The Mean Shape under the Relative Curvature Condition." arXiv . + Mohsen Taheri Shalmani (2024) "Shape Statistics via Skeletal Structures", PhD + Thesis, University of Stavanger, Norway . Key + features include constructing discrete elliptical tubes, calculating transformations, + validating structures under the Relative Curvature Condition (RCC), computing + means, and generating simulations. Supports intrinsic and non-intrinsic mean calculations + and transformations, size estimation, plotting, and random sample generation based + on a reference tube. The intrinsic approach relies on the interior path of the + original non-convex space, incorporating the RCC, while the non-intrinsic approach + uses a basic robotic arm transformation that disregards the RCC.' + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ETRep + url_git: https://github.com/MohsenTaheriShalmani/Elliptical_Tubes +etrm: + version: 1.0.1 + title: Energy Trading and Risk Management + maintainer: Anders D. Sleire + description: |- + Provides a collection of functions to perform core tasks within + Energy Trading and Risk Management (ETRM). Calculation of maximum smoothness + forward price curves for electricity and natural gas contracts with flow delivery, as presented in + F. E. Benth, S. Koekebakker, and F. Ollmar (2007) + and F. E. Benth, J. S. Benth, and S. Koekebakker (2008) . + Portfolio insurance trading strategies for price risk management in the forward market, see + F. Black (1976) , + T. Bjork (2009) , + F. Black and R. W. Jones (1987) and + H. E. Leland (1980) . + date_publication: '2021-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=etrm + url_git: '' +etrunct: + version: '0.1' + title: Computes Moments of Univariate Truncated t Distribution + maintainer: Matthew Stephens + description: |- + Computes moments of univariate truncated t distribution. + There is only one exported function, e_trunct(), which should be seen for details. + date_publication: '2016-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=etrunct + url_git: '' +etwfe: + version: 0.5.0 + title: Extended Two-Way Fixed Effects + maintainer: Grant McDermott + description: |- + Convenience functions for implementing extended two-way + fixed effect regressions a la Wooldridge (2021, 2023) + , . + date_publication: '2024-12-16' + bug_reports: https://github.com/grantmcdermott/etwfe/issues + url: https://grantmcdermott.com/etwfe/ + url_cran: https://CRAN.R-project.org/package=etwfe + url_git: '' +EuclideanSD: + version: 0.1.0 + title: An Euclidean View of Center and Spread + maintainer: Siddhanta Phuyal + description: |- + Illustrates the concepts developed in Sarkar and Rashid (2019, ISSN:0025-5742) . + This package helps a user guess four things (mean, MD, scaled MSD, and RMSD) before they get the SD. + 1) The package displays the Empirical Cumulative Distribution Function (ECDF) of + the given data. The user must choose the value of the mean by equating the areas of + two colored (blue and green) regions. The package gives feedback to improve the choice + until it is correct. Alternatively, the reader may continue with a different guess for + the center (not necessarily the mean). + 2) The user chooses the values of the Mean Deviation (MD) based on the ECDF of the deviations + by equating the areas of two newly colored (blue and green) regions, with feedback from the + package until the user guesses correctly. + 3) The user chooses the Scaled Mean Squared Deviation (MSD) based on the ECDF of the scaled + square deviations by equating the areas of two newly colored (blue and green) regions, with + feedback from the package until the user guesses correctly. + 4) The user chooses the Root Mean Squared Deviation (RMSD) by ensuring that its intersection + with the ECDF of the deviations is at the same height as the intersection between the scaled + MSD and the ECDF of the scaled squared deviations. Additionally, the intersection of two + blue lines (the green dot) should fall on the vertical line at the maximum deviation. + 5) Finally, if the mean is chosen correctly, only then the user can view the population + SD (the same as the RMSD) and the sample SD (sqrt(n/(n-1))*RMSD) by clicking the respective + buttons. If the mean is chosen incorrectly, the user is asked to correct it. + date_publication: '2021-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EuclideanSD + url_git: '' +Euclimatch: + version: 1.0.2 + title: Euclidean Climatch Algorithm + maintainer: Justin A. G. Hubbard + description: 'An interface for performing climate matching using the Euclidean "Climatch" + algorithm. Functions provide a vector of climatch scores (0-10) for each location + (i.e., grid cell) within the recipient region, the percent of climatch scores + >= a threshold value, and mean climatch score. Tools for parallelization and visualizations + are also provided. Note that the floor function that rounds the climatch score + down to the nearest integer has been removed in this implementation and the “Climatch” + algorithm, also referred to as the “Climate” algorithm, is described in: Crombie, + J., Brown, L., Lizzio, J., & Hood, G. (2008). “Climatch user manual”. The method + for the percent score is described in: Howeth, J.G., Gantz, C.A., Angermeier, + P.L., Frimpong, E.A., Hoff, M.H., Keller, R.P., Mandrak, N.E., Marchetti, M.P., + Olden, J.D., Romagosa, C.M., and Lodge, D.M. (2016). .' + date_publication: '2024-10-03' + bug_reports: https://github.com/JustinHubbard/Euclimatch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Euclimatch + url_git: '' +eudract: + version: 1.0.3 + title: |- + Creates Safety Results Summary in XML to Upload to EudraCT, or + ClinicalTrials.gov + maintainer: Simon Bond + description: 'The remit of the European Clinical Trials Data Base (EudraCT + ), or ClinicalTrials.gov , is to provide open access + to summaries of all registered clinical trial results; thus aiming to prevent + non-reporting of negative results and provide open-access to results to inform + future research. The amount of information required and the format of the results, + however, imposes a large extra workload at the end of studies on clinical trial + units. In particular, the adverse-event-reporting component requires entering: + each unique combination of treatment group and safety event; for every such event + above, a further 4 pieces of information (body system, number of occurrences, + number of subjects, number exposed) for non-serious events, plus an extra three + pieces of data for serious adverse events (numbers of causally related events, + deaths, causally related deaths). This package prepares the required statistics + needed by EudraCT and formats them into the precise requirements to directly upload + an XML file into the web portal, with no further data entry by hand.' + date_publication: '2025-01-13' + bug_reports: https://github.com/shug0131/eudraCT/issues + url: https://shug0131.github.io/eudraCT/ + url_cran: https://CRAN.R-project.org/package=eudract + url_git: '' +eufmdis.adapt: + version: 0.1.0 + title: Analyse 'EuFMDiS' Output Files via a Shiny App + maintainer: Ian Kopacka + description: |- + Analyses 'EuFMDiS' output files in a Shiny App. The distributions of + relevant output parameters are described in form of tables (quantiles) and plots. + The App is called using eufmdis.adapt::run_adapt(). + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eufmdis.adapt + url_git: '' +EUfootball: + version: 0.0.1 + title: Football Match Data of European Leagues + maintainer: Hendrik van der Wurp + description: |- + Contains match results from seven European men's football leagues, namely Premier League (England), Ligue 1 (France), + Bundesliga (Germany), Serie A (Italy), Primera Division (Spain), Eredivisie (The Netherlands), Super Lig (Turkey). + Includes Seasons 2010/2011 until 2019/2020 and a set of interesting covariates. Can be used all purposes. + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EUfootball + url_git: '' +eulerr: + version: 7.0.2 + title: Area-Proportional Euler and Venn Diagrams with Ellipses + maintainer: Johan Larsson + description: |- + Generate area-proportional Euler diagrams + using numerical optimization. An Euler diagram is a generalization of a Venn + diagram, relaxing the criterion that all interactions need to be + represented. Diagrams may be fit with ellipses and circles via + a wide range of inputs and can be visualized in numerous ways. + date_publication: '2024-03-28' + bug_reports: https://github.com/jolars/eulerr/issues + url: https://jolars.github.io/eulerr/ + url_cran: https://CRAN.R-project.org/package=eulerr + url_git: https://github.com/jolars/eulerr +eummd: + version: 0.2.0 + title: Efficient Univariate Maximum Mean Discrepancy + maintainer: Dean Bodenham + description: Computes maximum mean discrepancy two-sample test for univariate data + using the Laplacian kernel, as described in Bodenham and Kawahara (2023) . + The p-value is computed using permutations. Also includes implementation for computing + the robust median difference statistic 'Q_n' from Croux and Rousseeuw (1992) + based on Johnson and Mizoguchi (1978) . + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eummd + url_git: '' +eunis.habitats: + version: 0.1.0 + title: EUNIS Habitat Classification + maintainer: Ramiro Magno + description: |- + The EUNIS habitat classification is a comprehensive pan-European + system for habitat identification + . + This is an R data package providing the EUNIS classification system. + The classification is hierarchical and covers all types of habitats from + natural to artificial, from terrestrial to freshwater and marine. The + habitat types are identified by specific codes, names and descriptions and + come with schema crosswalks to other habitat typologies. + date_publication: '2023-07-11' + bug_reports: https://github.com/ramiromagno/eunis.habitats/issues + url: https://rmagno.eu/eunis.habitats/ + url_cran: https://CRAN.R-project.org/package=eunis.habitats + url_git: https://github.com/ramiromagno/eunis.habitats +Eunomia: + version: 2.0.0 + title: |- + Standard Dataset Manager for Observational Medical Outcomes + Partnership Common Data Model Sample Datasets + maintainer: Frank DeFalco + description: Facilitates access to sample datasets from the 'EunomiaDatasets' repository + (). + date_publication: '2024-04-23' + bug_reports: https://github.com/OHDSI/Eunomia/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Eunomia + url_git: https://github.com/OHDSI/Eunomia +eurlex: + version: 0.4.8 + title: Retrieve Data on European Union Law + maintainer: Michal Ovadek + description: Access to data on European Union laws and court decisions made easy + with pre-defined 'SPARQL' queries and 'GET' requests. See Ovadek (2021) + . + date_publication: '2024-07-03' + bug_reports: https://github.com/michalovadek/eurlex/issues + url: https://michalovadek.github.io/eurlex/ + url_cran: https://CRAN.R-project.org/package=eurlex + url_git: https://github.com/michalovadek/eurlex +eurocordexr: + version: 0.2.5 + title: |- + Makes it Easier to Work with Daily 'netCDF' from EURO-CORDEX + RCMs + maintainer: Michael Matiu + description: |- + Daily 'netCDF' data from e.g. regional climate models (RCMs) are not trivial + to work with. This package, which relies on 'data.table', makes it easier + to deal with large data from RCMs, such as from EURO-CORDEX + (, ). It has + functions to extract single grid cells from rotated pole grids as well as + the whole array in long format. Can handle non-standard calendars (360, + noleap) and interpolate them to a standard one. Potentially works with many + CF-conform 'netCDF' files. + date_publication: '2025-01-07' + bug_reports: https://github.com/mitmat/eurocordexr/issues + url: https://mitmat.github.io/eurocordexr/ + url_cran: https://CRAN.R-project.org/package=eurocordexr + url_git: https://github.com/mitmat/eurocordexr +eurodata: + version: 1.7.0 + title: Fast and Easy Eurostat Data Import and Search + maintainer: Aleksander Rutkowski + description: |- + Interface to Eurostat’s API (SDMX 2.1) with fast data.table-based import of + data, labels, and metadata. On top of the core functionality, data search and data + description/comparison functions are also provided. + Use — a point-and-click app for rapid and + easy generation of richly-commented R code — to import a Eurostat dataset or its subset + (based on the eurodata::importData() function). + date_publication: '2023-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eurodata + url_git: https://github.com/alekrutkowski/eurodata/ +euroleaguer: + version: 0.2.0 + title: '''Euroleague basketball API''' + maintainer: Flavio Leccese + description: Unofficial API wrapper for 'Euroleague' and 'Eurocup' basketball API + (), it allows to retrieve + real-time and historical standard and advanced statistics about competitions, + teams, players and games. + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=euroleaguer + url_git: https://github.com/FlavioLeccese92/euroleaguer/ +europeanaR: + version: 0.1.0 + title: |- + Interact with Metadata Records and Media on the Europeana + Repository + maintainer: Alexandros Kouretsis + description: |- + Interact with the Europeana Data Model via a variety of API + endpoints that contains digital collections from thousands of institutions + around Europe. This translates to millions of Cultural Heritage Objects in the + form of image, text, video, sound and 3D, accompanied by rich metadata. The + Data Model design principles are based on the core principles and best + practices of the Semantic Web and Linked Data efforts to which Europeana + contributes (see, e.g., Doerr, Martin, et al. The europeana data model (edm). + World Library and Information Congress: 76th IFLA general conference + and assembly. Vol. 10. 2010.). The package also provides methods for bulk + downloads of specific subsets of items, including both their metadata + and their associated media files. + date_publication: '2022-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=europeanaR + url_git: https://github.com/AleKoure/europeanaR +europepmc: + version: 0.4.3 + title: R Interface to the Europe PubMed Central RESTful Web Service + maintainer: Najko Jahn + description: |- + An R Client for the Europe PubMed Central RESTful Web Service + (see for more information). It + gives access to both metadata on life science literature and open access + full texts. Europe PMC indexes all PubMed content and other literature + sources including Agricola, a bibliographic database of citations to the + agricultural literature, or Biological Patents. In addition to bibliographic + metadata, the client allows users to fetch citations and reference lists. + Links between life-science literature and other EBI databases, including + ENA, PDB or ChEMBL are also accessible. No registration or API key is + required. See the vignettes for usage examples. + date_publication: '2023-09-20' + bug_reports: https://github.com/ropensci/europepmc/issues + url: https://docs.ropensci.org/europepmc/ + url_cran: https://CRAN.R-project.org/package=europepmc + url_git: https://github.com/ropensci/europepmc/ +europop: + version: 0.3.1 + title: Historical Populations of European Cities, 1500-1800 + maintainer: Matthew Lincoln + description: |- + This dataset contains population estimates of all European cities + with at least 10,000 inhabitants during the period 1500-1800. These data are + adapted from Jan De Vries, "European Urbanization, 1500-1800" (1984). + date_publication: '2017-02-24' + bug_reports: https://github.com/mdlincoln/europop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=europop + url_git: https://github.com/mdlincoln/europop +eurostat: + version: 4.0.0 + title: Tools for Eurostat Open Data + maintainer: Leo Lahti + description: |- + Tools to download data from the Eurostat database + together with search and manipulation + utilities. + date_publication: '2023-12-19' + bug_reports: https://github.com/rOpenGov/eurostat/issues + url: https://ropengov.github.io/eurostat/ + url_cran: https://CRAN.R-project.org/package=eurostat + url_git: https://github.com/rOpenGov/eurostat +eva: + version: 0.2.6 + title: Extreme Value Analysis with Goodness-of-Fit Testing + maintainer: Brian Bader + description: |- + Goodness-of-fit tests for selection of r in the r-largest order + statistics (GEVr) model. Goodness-of-fit tests for threshold selection in the + Generalized Pareto distribution (GPD). Random number generation and density functions + for the GEVr distribution. Profile likelihood for return level estimation + using the GEVr and Generalized Pareto distributions. P-value adjustments for + sequential, multiple testing error control. Non-stationary fitting of GEVr and + GPD. + Bader, B., Yan, J. & Zhang, X. (2016) . + Bader, B., Yan, J. & Zhang, X. (2018) . + date_publication: '2020-11-15' + bug_reports: https://github.com/brianbader/eva_package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eva + url_git: https://github.com/brianbader/eva_package +eva3dm: + version: 0.99.1 + title: Evaluation of 3D Meteorological and Air Quality Models + maintainer: Daniel Schuch + description: Provides tools for post-process, evaluate and visualize results from + 3d Meteorological and Air Quality models against point observations (i.e. surface + stations) and grid (i.e. satellite) observations. + date_publication: '2024-11-25' + bug_reports: https://github.com/Schuch666/eva3dm/issues/ + url: https://schuch666.github.io/eva3dm/ + url_cran: https://CRAN.R-project.org/package=eva3dm + url_git: '' +evabic: + version: 0.1.1 + title: Evaluation of Binary Classifiers + maintainer: Antoine Bichat + description: |- + Evaluates the performance of binary classifiers. Computes + confusion measures (TP, TN, FP, FN), derived measures (TPR, FDR, + accuracy, F1, DOR, ..), and area under the curve. Outputs are well + suited for nested dataframes. + date_publication: '2022-08-17' + bug_reports: https://github.com/abichat/evabic/issues + url: https://abichat.github.io/evabic/ + url_cran: https://CRAN.R-project.org/package=evabic + url_git: https://github.com/abichat/evabic +Evacluster: + version: 0.1.0 + title: Evaluation Clustering Methods for Disease Subtypes Diagnosis + maintainer: Fahimeh Nezhadmoghadam + description: 'Contains a set of clustering methods and evaluation metrics to select + the best number of the clusters based on clustering stability. Two references + describe the methodology: Fahimeh Nezhadmoghadam, and Jose Tamez-Pena (2021), + and Fahimeh Nezhadmoghadam, et al.(2021).' + date_publication: '2022-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Evacluster + url_git: '' +evalITR: + version: 1.0.0 + title: Evaluating Individualized Treatment Rules + maintainer: Michael Lingzhi Li + description: |- + Provides various statistical methods for evaluating + Individualized Treatment Rules under randomized data. The provided + metrics include Population Average Value (PAV), Population Average + Prescription Effect (PAPE), Area Under Prescription Effect Curve + (AUPEC). It also provides the tools to analyze Individualized + Treatment Rules under budget constraints. Detailed reference in Imai + and Li (2019) . + date_publication: '2023-08-25' + bug_reports: https://github.com/MichaelLLi/evalITR/issues + url: https://michaellli.github.io/evalITR/ + url_cran: https://CRAN.R-project.org/package=evalITR + url_git: https://github.com/MichaelLLi/evalITR +evalR: + version: 0.0.1 + title: Evaluation of Unverified Code + maintainer: Trevor Olsen + description: The purpose of this package is to generate trees and validate unverified + code. Trees are made by parsing a statement into a verification tree data structure. + This will make it easy to port the statement into another language. Safe statement + evaluations are done by executing the verification trees. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evalR + url_git: '' +evaluate: + version: 1.0.3 + title: |- + Parsing and Evaluation Tools that Provide More Details than the + Default + maintainer: Hadley Wickham + description: |- + Parsing and evaluation tools that make it easy to recreate + the command line behaviour of R. + date_publication: '2025-01-10' + bug_reports: https://github.com/r-lib/evaluate/issues + url: https://evaluate.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=evaluate + url_git: https://github.com/r-lib/evaluate +EvaluateCore: + version: 0.1.3 + title: Quality Evaluation of Core Collections + maintainer: J. Aravind + description: |- + Implements various quality evaluation statistics to assess the + value of plant germplasm core collections using qualitative and + quantitative phenotypic trait data according to Odong et al. (2015) + . + date_publication: '2022-07-03' + bug_reports: https://github.com/aravind-j/EvaluateCore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EvaluateCore + url_git: https://github.com/aravind-j/EvaluateCorehttps://CRAN.R-project.org/package=EvaluateCorehttps://aravind-j.github.io/EvaluateCore/https://doi.org/10.5281/zenodo.3875930 +EvaluationMeasures: + version: 1.1.0 + title: Collection of Model Evaluation Measure Functions + maintainer: Babak Khorsand + description: Provides Some of the most important evaluation measures for evaluating + a model. Just by giving the real and predicted class, measures such as accuracy, + sensitivity, specificity, ppv, npv, fmeasure, mcc and ... will be returned. + date_publication: '2016-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EvaluationMeasures + url_git: '' +EValue: + version: 4.1.3 + title: |- + Sensitivity Analyses for Unmeasured Confounding and Other Biases + in Observational Studies and Meta-Analyses + maintainer: Maya B. Mathur + description: Conducts sensitivity analyses for unmeasured confounding, selection + bias, and measurement error (individually or in combination; VanderWeele & Ding + (2017) ; Smith & VanderWeele (2019) ; + VanderWeele & Li (2019) ; Smith & VanderWeele (2021) ). + Also conducts sensitivity analyses for unmeasured confounding in meta-analyses + (Mathur & VanderWeele (2020a) ; Mathur & VanderWeele + (2020b) ) and for additive measures of effect + modification (Mathur et al., under review). + date_publication: '2021-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EValue + url_git: '' +evapoRe: + version: 1.0.0 + title: Evapotranspiration R Recipes + maintainer: Akbar Rahmati Ziveh + description: |- + An R-based application for exploratory data analysis of global EvapoTranspiration (ET) datasets. + 'evapoRe' enables users to download, validate, visualize, and analyze multi-source ET data across various spatio-temporal scales. + Also, the package offers calculation methods for estimating potential ET (PET), including temperature-based approaches described in : Oudin et al., (2005) . + 'evapoRe' supports hydrological modeling, climate studies, agricultural research, and other data-driven fields by facilitating access to ET data and offering powerful analysis capabilities. + Users can seamlessly integrate the package into their research applications and explore diverse ET data at different resolutions. + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evapoRe + url_git: https://github.com/AkbarR1184/evapoRe +Evapotranspiration: + version: '1.16' + title: |- + Modelling Actual, Potential and Reference Crop + Evapotranspiration + maintainer: Danlu Guo + description: Uses data and constants to calculate potential evapotranspiration (PET) + and actual evapotranspiration (AET) from 21 different formulations including Penman, + Penman-Monteith FAO 56, Priestley-Taylor and Morton formulations. + date_publication: '2022-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Evapotranspiration + url_git: '' +EVchargcost: + version: 0.1.0 + title: |- + Computes and Plot the Optimal Charging Strategy for Electric + Vehicles + maintainer: Brais Gonzalez-Rodriguez + description: The purpose of this library is to compute the optimal charging cost + function for a electric vehicle (EV). It is well known that the charging function + of a EV is a concave function that can be approximated by a piece-wise linear + function, so bigger the state of charge, slower the charging process is. Moreover, + the other important function is the one that gives the electricity price. This + function is usually step-wise, since depending on the time of the day, the price + of the electricity is different. Then, the problem of charging an EV to a certain + state of charge is not trivial. This library implements an algorithm to compute + the optimal charging cost function, that is, it plots for a given state of charge + r (between 0 and 1) the minimum cost we need to pay in order to charge the EV + to that state of charge r. The details of the algorithm are described in González-Rodríguez + et at (2023) . + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EVchargcost + url_git: '' +evclass: + version: 2.0.2 + title: Evidential Distance-Based Classification + maintainer: Thierry Denoeux + description: |- + Different evidential classifiers, which provide + outputs in the form of Dempster-Shafer mass functions. The methods are: + the evidential K-nearest neighbor rule, the evidential neural + network, radial basis function neural networks, logistic regression, + feed-forward neural networks. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evclass + url_git: '' +evclust: + version: 2.0.3 + title: Evidential Clustering + maintainer: Thierry Denoeux + description: |- + Various clustering algorithms that produce a credal partition, + i.e., a set of Dempster-Shafer mass functions representing the membership of objects + to clusters. The mass functions quantify the cluster-membership uncertainty of the + objects. The algorithms are: Evidential c-Means, Relational Evidential c-Means, + Constrained Evidential c-Means, Evidential Clustering, Constrained Evidential + Clustering, Evidential K-nearest-neighbor-based Clustering, Bootstrap Model-Based + Evidential Clustering, Belief Peak Evidential Clustering, Neural-Network-based + Evidential Clustering. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evclust + url_git: '' +EvCombR: + version: 0.1-4 + title: Evidence Combination in R + maintainer: Alexander Karlsson + description: Combine pieces of evidence in the form of uncertainty representations. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EvCombR + url_git: '' +evd: + version: 2.3-7.1 + title: Functions for Extreme Value Distributions + maintainer: Alec Stephenson + description: |- + Extends simulation, distribution, quantile and density + functions to univariate and multivariate parametric extreme + value distributions, and provides fitting functions which + calculate maximum likelihood estimates for univariate and + bivariate maxima models, and for univariate and bivariate + threshold models. + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evd + url_git: '' +evdbayes: + version: 1.1-3 + title: Bayesian Analysis in Extreme Value Theory + maintainer: Alec Stephenson + description: |- + Provides functions for the Bayesian analysis of extreme + value models, using Markov chain Monte Carlo methods. Allows + the construction of both uninformative and informed prior + distributions for common statistical models applied to extreme + event data, including the generalized extreme value distribution. + date_publication: '2023-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evdbayes + url_git: '' +evenBreak: + version: '1.0' + title: A Posteriori Probs of Suits Breaking Evenly Across Four Hands + maintainer: Barry Zeeberg + description: We quantitatively evaluated the assertion that says if one suit is + found to be evenly distributed among the 4 players, the rest of the suits are + more likely to be evenly distributed. Our mathematical analyses show that, if + one suit is found to be evenly distributed, then a second suit has a slightly + elevated probability (ranging between 10% to 15%) of being evenly distributed. + If two suits are found to be evenly distributed, then a third suit has a substantially + elevated probability (ranging between 30% to 50%) of being evenly distributed.This + package refers to methods and authentic data from Ely Culbertson , + Gregory Stoll , and details + of performing the probability calculations from Jeremy L. Martin , + Emile Borel and Andre Cheron (1954) "The Mathematical Theory of Bridge",Antonio + Vivaldi and Gianni Barracho (2001, ISBN:0 7134 8663 5) "Probabilities and Alternatives + in Bridge", Ken Monzingo (2005) "Hand and Suit Patterns" Ken + Monzingo (2005) "Hand and Suit Patterns" . + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evenBreak + url_git: '' +event: + version: 1.1.1 + title: Event History Procedures and Models + maintainer: Bruce Swihart + description: Functions for setting up and analyzing event history data. + date_publication: '2018-05-24' + bug_reports: https://github.com/swihart/event/issues + url: http://www.commanster.eu/rcode.html + url_cran: https://CRAN.R-project.org/package=event + url_git: '' +eventdataR: + version: 0.3.1 + title: Event Data Repository + maintainer: Gert Janssenswillen + description: Event dataset repository including both real-life and artificial event + logs. They can be used in combination with functionalities provided by the 'bupaR' + packages. Janssenswillen et al. (2020) . + date_publication: '2022-06-28' + bug_reports: https://github.com/bupaverse/eventdataR/ + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=eventdataR + url_git: https://github.com/bupaverse/eventdataR/ +EventDetectGUI: + version: 0.3.0 + title: Graphical User Interface for the 'EventDetectR' Package + maintainer: Sowmya Chandrasekaran + description: A graphical user interface for open source event detection. + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EventDetectGUI + url_git: '' +EventDetectR: + version: 0.3.5 + title: Event Detection Framework + maintainer: Sowmya Chandrasekaran + description: Detect events in time-series data. Combines multiple well-known R packages + like 'forecast' and 'neuralnet' to deliver an easily configurable tool for multivariate + event detection. + date_publication: '2020-10-10' + bug_reports: https://github.com/frehbach/EventDetectR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EventDetectR + url_git: https://github.com/frehbach/EventDetectR +eventglm: + version: 1.2.2 + title: Regression Models for Event History Outcomes + maintainer: Michael C Sachs + description: |- + A user friendly, easy to understand way of doing event + history regression for marginal estimands of interest, + including the cumulative incidence and the restricted mean + survival, using the pseudo observation framework for + estimation. For a review of the methodology, see Andersen and + Pohar Perme (2010) or Sachs + and Gabriel (2022) . The + interface uses the well known formulation of a generalized + linear model and allows for features including plotting of + residuals, the use of sampling weights, and corrected + variance estimation. + date_publication: '2022-04-26' + bug_reports: https://github.com/sachsmc/eventglm/issues/ + url: https://sachsmc.github.io/eventglm/ + url_cran: https://CRAN.R-project.org/package=eventglm + url_git: '' +eventInterval: + version: '1.3' + title: Sequential Event Interval Analysis + maintainer: Jim Lemon + description: Functions for analysis of rate changes in sequential events. + date_publication: '2015-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eventInterval + url_git: '' +eventPred: + version: 0.2.6 + title: Event Prediction + maintainer: Kaifeng Lu + description: Predicts enrollment and events at the design or analysis stage using + specified enrollment and time-to-event models through simulations. + date_publication: '2024-09-17' + bug_reports: https://github.com/kaifenglu/eventPred/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eventPred + url_git: https://github.com/kaifenglu/eventPred +EventPredInCure: + version: '1.0' + title: Event Prediction Including Cured Population + maintainer: Bo Wei + description: 'Predicts enrollment and events assumed enrollment and treatment-specific + time-to-event models, and calculates test statistics for time-to-event data with + cured population based on the simulation.Methods for prediction event in the existence + of cured population are as described in : Chen, Tai-Tsang(2016) .' + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EventPredInCure + url_git: '' +eventstream: + version: 0.1.1 + title: Streaming Events and their Early Classification + maintainer: Sevvandi Kandanaarachchi + description: |- + Implements event extraction and early classification of events in data streams in R. + It has the functionality to generate 2-dimensional data streams with events belonging to + 2 classes. These events can be extracted and features computed. The event features extracted + from incomplete-events can be classified using a partial-observations-classifier + (Kandanaarachchi et al. 2018) . + date_publication: '2022-05-16' + bug_reports: '' + url: https://sevvandi.github.io/eventstream/index.html + url_cran: https://CRAN.R-project.org/package=eventstream + url_git: '' +eventstudyr: + version: 1.1.3 + title: Estimation and Visualization of Linear Panel Event Studies + maintainer: Santiago Hermo + description: Estimates linear panel event study models. Plots coefficients following + the recommendations in Freyaldenhoven et al. (2021) . Includes + sup-t bands, testing for key hypotheses, least wiggly path through the Wald region. + Allows instrumental variables estimation following Freyaldenhoven et al. (2019) + . + date_publication: '2024-03-04' + bug_reports: https://github.com/JMSLab/eventstudyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eventstudyr + url_git: https://github.com/JMSLab/eventstudyr +eventTrack: + version: 1.0.4 + title: Event Prediction for Time-to-Event Endpoints + maintainer: Kaspar Rufibach + description: Implements the hybrid framework for event prediction described in Fang + & Zheng (2011, ). To estimate the survival function + the event prediction is based on, a piecewise exponential hazard function is fit + to the time-to-event data to infer the potential change points. Prior to the last + identified change point, the survival function is estimated using Kaplan-Meier, + and the tail after the change point is fit using piecewise exponential. + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eventTrack + url_git: '' +EventWinRatios: + version: 1.0.0 + title: Event-Specific Win Ratios for Terminal and Non-Terminal Events + maintainer: Daewoo Pak + description: |- + Provides several confidence interval and testing procedures using + event-specific win ratios for semi-competing risks data with non-terminal + and terminal events, as developed in Yang et al. (2021). + Compared with conventional methods for survival data, these procedures are + designed to utilize more data for improved inference procedures with + semi-competing risks data. The event-specific win ratios were introduced in + Yang and Troendle (2021). In this package, + the event-specific win ratios and confidence intervals are obtained for each + event type, and several testing procedures are developed for the global null + of no treatment effect on either terminal or non-terminal events. Furthermore, + a test of proportional hazard assumptions, under which the event-specific win + ratios converge to the hazard ratios, and a test of equal hazard ratios are + provided. For summarizing the treatment effect on all events, confidence + intervals for linear combinations of the event-specific win ratios are available + using pre-determined or data-driven weights. Asymptotic properties of these + inference procedures are discussed in Yang et al (2021). + Also, transformations are used to yield better control of the type one error + rates for moderately sized data sets. + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EventWinRatios + url_git: '' +evesim: + version: 1.0.0 + title: |- + Evolution Emulator: Species Diversification under an + Evolutionary Relatedness Dependent Scenario + maintainer: Tianjian Qin + description: Evolutionary relatedness dependent diversification simulation powered + by the 'Rcpp' back-end 'SimTable'. + date_publication: '2025-02-13' + bug_reports: '' + url: http://qtj.me/evesim/ + url_cran: https://CRAN.R-project.org/package=evesim + url_git: '' +evgam: + version: 1.0.0 + title: Generalised Additive Extreme Value Models + maintainer: Ben Youngman + description: |- + Methods for fitting various extreme value distributions with parameters of + generalised additive model (GAM) form are provided. For details of distributions + see Coles, S.G. (2001) , GAMs see Wood, S.N. (2017) + , and the fitting approach see Wood, S.N., Pya, N. & + Safken, B. (2016) . Details of how evgam works + and various examples are given in Youngman, B.D. (2022) . + date_publication: '2022-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evgam + url_git: '' +EVI: + version: 0.2.0-0 + title: Epidemic Volatility Index as an Early-Warning Tool + maintainer: Konstantinos Pateras + description: |2- + + This is an R package implementing the epidemic volatility index (EVI), as + discussed by Kostoulas et. al. (2021) and variations by Pateras et. al. (2023). EVI is a new, conceptually simple, early warning tool for oncoming epidemic waves. + EVI is based on the volatility of newly reported cases per unit of time, + ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. + date_publication: '2023-12-05' + bug_reports: '' + url: https://www.nature.com/articles/s41598-021-02622-3 + url_cran: https://CRAN.R-project.org/package=EVI + url_git: '' +evian: + version: 2.1.0 + title: Evidential Analysis of Genetic Association Data + maintainer: Jiafen Gong + description: |- + Evidential regression analysis for dichotomous and quantitative outcome data. The following references described the methods in this package: + Strug, L. J., Hodge, S. E., Chiang, T., Pal, D. K., Corey, P. N., & Rohde, C. (2010) . + Strug, L. J., & Hodge, S. E. (2006) . + Royall, R. (1997) . + date_publication: '2019-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evian + url_git: '' +evidence: + version: 0.8.10 + title: |- + Analysis of Scientific Evidence Using Bayesian and Likelihood + Methods + maintainer: Robert van Hulst + description: 'Bayesian (and some likelihoodist) functions as alternatives to hypothesis-testing + functions in R base using a user interface patterned after those of R''s hypothesis + testing functions. See McElreath (2016, ISBN: 978-1-4822-5344-3), Gelman and Hill + (2007, ISBN: 0-521-68689-X) (new edition in preparation) and Albert (2009, ISBN: + 978-0-387-71384-7) for good introductions to Bayesian analysis and Pawitan (2002, + ISBN: 0-19-850765-8) for the Likelihood approach. The functions in the package + also make extensive use of graphical displays for data exploration and model comparison.' + date_publication: '2018-05-15' + bug_reports: https://github.com/rvhulst/evidence/ + url: '' + url_cran: https://CRAN.R-project.org/package=evidence + url_git: '' +evidenceFactors: + version: '1.8' + title: |- + Reporting Tools for Sensitivity Analysis of Evidence Factors in + Observational Studies + maintainer: Bikram Karmakar + description: |- + Provides tools for integrated sensitivity analysis of evidence factors in observational + studies. When an observational study allows for multiple independent or nearly + independent inferences which, if vulnerable, are vulnerable to different biases, we have + multiple evidence factors. This package provides methods that respect type I error rate control. + Examples are provided of integrated evidence factors analysis in a longitudinal study with + continuous outcome and in a case-control study. + Karmakar, B., French, B., and Small, D. S. (2019). + date_publication: '2020-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evidenceFactors + url_git: '' +EvidenceSynthesis: + version: 0.5.0 + title: Synthesizing Causal Evidence in a Distributed Research Network + maintainer: Martijn Schuemie + description: |- + Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. + Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter. + date_publication: '2023-05-08' + bug_reports: https://github.com/OHDSI/EvidenceSynthesis/issues + url: https://ohdsi.github.io/EvidenceSynthesis/ + url_cran: https://CRAN.R-project.org/package=EvidenceSynthesis + url_git: https://github.com/OHDSI/EvidenceSynthesis +evident: + version: 1.0.4 + title: Evidence Factors in Observational Studies + maintainer: Paul R. Rosenbaum + description: Contains a collection of examples of evidence factors in observational + studies from the book Replication and Evidence Factors in Observational Studies + by Paul R. Rosenbaum (2021) . + date_publication: '2022-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evident + url_git: '' +EviewsR: + version: 0.1.6 + title: A Seamless Integration of 'EViews' and R + maintainer: Sagiru Mati + description: It allows running 'EViews' () program from R, R + Markdown and Quarto documents. 'EViews' (Econometric Views) is a statistical software + for Econometric analysis. This package integrates 'EViews' and R and also serves + as an 'EViews' Knit-Engine for 'knitr' package. Write all your 'EViews' commands + in R, R Markdown or Quarto documents. For details, please consult our peer-review + article Mati S., Civcir I. and Abba S.I (2023) . + date_publication: '2023-11-28' + bug_reports: https://github.com/sagirumati/EviewsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=EviewsR + url_git: '' +evilDice: + version: '1.0' + title: Test Dice Sets for Intransitive Properties + maintainer: Carl Witthoft + description: Checks to see whether a supplied set of dice (their face values) are + transitive, returning pair-win and group-roll win probabilities. Expected returns + (mean magnitude of win/loss) are presented as well. + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evilDice + url_git: '' +evinf: + version: 0.8.10 + title: Inference with Extreme Value Inflated Count Data + maintainer: David Randahl + description: Allows users to model and draw inferences from extreme value inflated + count data, and to evaluate these models and compare to non extreme-value inflated + counterparts. The package is built to be compatible with standard presentation + tools such as 'broom', 'tidy', and 'modelsummary'. + date_publication: '2024-05-17' + bug_reports: https://github.com/Doktorandahl/evinf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=evinf + url_git: https://github.com/Doktorandahl/evinf +evir: + version: 1.7-4 + title: Extreme Values in R + maintainer: Bernhard Pfaff + description: |- + Functions for extreme value theory, which may be + divided into the following groups; exploratory data analysis, + block maxima, peaks over thresholds (univariate and bivariate), + point processes, gev/gpd distributions. + date_publication: '2018-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evir + url_git: '' +evitaicossa: + version: 0.0-1 + title: Antiassociative Algebra + maintainer: Robin K. S. Hankin + description: |- + Methods to deal with the free antiassociative algebra + over the reals with an arbitrary number of indeterminates. + Antiassociativity means that (xy)z = -x(yz). Antiassociative + algebras are nilpotent with nilindex four (Remm, 2022, + ) and this drives the design and + philosophy of the package. Methods are defined to create and + manipulate arbitrary elements of the antiassociative algebra, + and to extract and replace coefficients. A vignette is + provided. + date_publication: '2024-06-28' + bug_reports: https://github.com/RobinHankin/evitaicossa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=evitaicossa + url_git: https://github.com/RobinHankin/evitaicossa +evmix: + version: '2.12' + title: |- + Extreme Value Mixture Modelling, Threshold Estimation and + Boundary Corrected Kernel Density Estimation + maintainer: Carl Scarrott + description: |- + The usual distribution functions, maximum likelihood inference and + model diagnostics for univariate stationary extreme value mixture models + are provided. Kernel density estimation including various boundary + corrected kernel density estimation methods and a wide choice of kernels, + with cross-validation likelihood based bandwidth estimator. + Reasonable consistency with the base functions in the 'evd' package is + provided, so that users can safely interchange most code. + date_publication: '2019-09-03' + bug_reports: '' + url: http://www.math.canterbury.ac.nz/~c.scarrott/evmix + url_cran: https://CRAN.R-project.org/package=evmix + url_git: '' +evobiR: + version: '1.1' + title: Comparative and Population Genetic Analyses + maintainer: Heath Blackmon + description: Comparative analysis of continuous traits influencing discrete states, + and utility tools to facilitate comparative analyses. Implementations of ABBA/BABA + type statistics to test for introgression in genomic data. Wright-Fisher, phylogenetic + tree, and statistical distribution Shiny interactive simulations for use in teaching. + date_publication: '2015-09-06' + bug_reports: '' + url: http://www.uta.edu/karyodb/evobiR/ + url_cran: https://CRAN.R-project.org/package=evobiR + url_git: '' +evola: + version: 1.0.4 + title: Evolutionary Algorithm + maintainer: Giovanny Covarrubias-Pazaran + description: Runs a genetic algorithm using the 'AlphaSimR' machinery + and the coalescent simulator 'MaCS' . + date_publication: '2025-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evola + url_git: '' +evolMap: + version: 1.3.8 + title: Dynamic and Interactive Maps + maintainer: Modesto Escobar + description: Dynamic and Interactive Maps with R, powered by 'leaflet' . + 'evolMap' generates a web page with interactive and dynamic maps to which you + can add geometric entities (points, lines or colored geographic areas), and/or + markers with optional links between them. The dynamic ability of these maps allows + their components to evolve over a continuous period of time or by periods. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evolMap + url_git: '' +evolqg: + version: 0.3-4 + title: Evolutionary Quantitative Genetics + maintainer: Diogo Melo + description: Provides functions for covariance matrix comparisons, estimation of + repeatabilities in measurements and matrices, and general evolutionary quantitative + genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) . + date_publication: '2023-12-05' + bug_reports: https://github.com/lem-usp/evolqg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=evolqg + url_git: '' +EvolutionaryGames: + version: 0.1.2 + title: Important Concepts of Evolutionary Game Theory + maintainer: Jochen Staudacher + description: |- + Evolutionary game theory applies game theory to evolving populations + in biology, see e.g. one of the books by Weibull (1994, ISBN:978-0262731218) + or by Sandholm (2010, ISBN:978-0262195874) for more details. A comprehensive + set of tools to illustrate the core concepts of evolutionary game theory, + such as evolutionary stability or various evolutionary dynamics, for teaching + and academic research is provided. + date_publication: '2022-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EvolutionaryGames + url_git: '' +evolvability: + version: 2.0.0 + title: Calculation of Evolvability Parameters + maintainer: Geir H. Bolstad + description: |- + Provides tools for calculating evolvability parameters from estimated G-matrices as defined + in Hansen and Houle (2008) and fits phylogenetic + comparative models that link the rate of evolution of a trait to the state of another evolving + trait (see Hansen et al. 2021 Systematic Biology ). The package was + released with Bolstad et al. (2014) , which contains some examples of use. + date_publication: '2021-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evolvability + url_git: '' +evolved: + version: 1.0.0 + title: |- + Open Software for Teaching Evolutionary Biology at Multiple + Scales Through Virtual Inquiries + maintainer: Matheus Januario + description: '"Evolutionary Virtual Education" - ''evolved'' - provides multiple + tools to help educators (especially at the graduate level or in advanced undergraduate + level courses) apply inquiry-based learning in general evolution classes. In particular, + the tools provided include functions that simulate evolutionary processes (e.g., + genetic drift, natural selection within a single locus) or concepts (e.g. Hardy-Weinberg + equilibrium, phylogenetic distribution of traits). More than only simulating, + the package also provides tools for students to analyze (e.g., measuring, testing, + visualizing) datasets with characteristics that are common to many fields related + to evolutionary biology. Importantly, the package is heavily oriented towards + providing tools for inquiry-based learning - where students follow scientific + practices to actively construct knowledge. For additional details, see package''s + vignettes.' + date_publication: '2024-11-27' + bug_reports: https://github.com/Auler-J/evolved/issues + url: '' + url_cran: https://CRAN.R-project.org/package=evolved + url_git: +Evomorph: + version: '0.9' + title: Evolutionary Morphometric Simulation + maintainer: Juan Manuel Cabrera + description: Evolutionary process simulation using geometric morphometric data. + Manipulation of landmark data files (TPS), shape plotting and distances plotting + functions. + date_publication: '2016-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Evomorph + url_git: '' +evoper: + version: 0.5.0 + title: Evolutionary Parameter Estimation for 'Repast Simphony' Models + maintainer: Antonio Prestes Garcia + description: |- + The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible + package providing optimization driven parameter estimation methods using metaheuristics and + evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization + for continuous domains, Tabu Search, Evolutionary Strategies, ...) which could be more efficient and require, + in some cases, fewer model evaluations than alternatives relying on experimental design. Currently there + are built in support for models developed with 'Repast Simphony' Agent-Based framework () + and with NetLogo () which are the most used frameworks for Agent-based modeling. + date_publication: '2018-08-30' + bug_reports: https://github.com/antonio-pgarcia/evoper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=evoper + url_git: https://github.com/antonio-pgarcia/evoper +EvoPhylo: + version: 0.3.2 + title: |- + Pre- And Postprocessing of Morphological Data from Relaxed Clock + Bayesian Phylogenetics + maintainer: Tiago Simoes + description: |- + Performs automated morphological character partitioning for + phylogenetic analyses and analyze macroevolutionary parameter + outputs from clock (time-calibrated) Bayesian inference analyses, following + concepts introduced by Simões and Pierce (2021) . + date_publication: '2022-11-03' + bug_reports: https://github.com/tiago-simoes/EvoPhylo/issues + url: https://tiago-simoes.github.io/EvoPhylo/ + url_cran: https://CRAN.R-project.org/package=EvoPhylo + url_git: https://github.com/tiago-simoes/EvoPhylo +evoTS: + version: 1.0.3 + title: Analyses of Evolutionary Time-Series + maintainer: Kjetil Lysne Voje + description: Facilitates univariate and multivariate analysis of evolutionary sequences + of phenotypic change. The package extends the modeling framework available in + the 'paleoTS' package. Please see + for information about the package and the implemented models. + date_publication: '2024-06-20' + bug_reports: https://github.com/klvoje/evoTS/issues + url: https://klvoje.github.io/evoTS/index.html + url_cran: https://CRAN.R-project.org/package=evoTS + url_git: '' +evprof: + version: 1.1.2 + title: Electric Vehicle Charging Sessions Profiling and Modelling + maintainer: Marc Cañigueral + description: |- + Tools for modelling electric vehicle charging sessions into + generic groups with similar connection patterns called "user profiles", + using Gaussian Mixture Models clustering. The clustering and profiling + methodology is described in Cañigueral and Meléndez (2021, ISBN:0142-0615) + . + date_publication: '2024-03-14' + bug_reports: https://github.com/mcanigueral/evprof/issues + url: https://mcanigueral.github.io/evprof/ + url_cran: https://CRAN.R-project.org/package=evprof + url_git: https://github.com/mcanigueral/evprof/ +evreg: + version: 1.1.1 + title: Evidential Regression + maintainer: Thierry Denoeux + description: An implementation of the 'Evidential Neural Network for Regression' + model recently introduced in Denoeux (2023) . + In this model, prediction uncertainty is quantified by Gaussian random fuzzy numbers + as introduced in Denoeux (2023) . The package contains + functions for training the network, tuning hyperparameters by cross-validation + or the hold-out method, and making predictions. It also contains utilities for + making calculations with Gaussian random fuzzy numbers (such as, e.g., computing + the degrees of belief and plausibility of an interval, or combining Gaussian random + fuzzy numbers). + date_publication: '2024-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evreg + url_git: '' +evsim: + version: 1.6.0 + title: Electric Vehicle Charging Sessions Simulation + maintainer: Marc Cañigueral + description: |- + Simulation of Electric Vehicles charging sessions using + Gaussian models, together with time-series power demand calculations. + The simulation methodology is published in + Cañigueral et al. (2023, ISBN:0957-4174) . + date_publication: '2024-10-03' + bug_reports: https://github.com/mcanigueral/evsim/issues + url: https://mcanigueral.github.io/evsim/ + url_cran: https://CRAN.R-project.org/package=evsim + url_git: https://github.com/mcanigueral/evsim/ +evt0: + version: 1.1.5 + title: |- + Mean of Order P, Peaks over Random Threshold Hill and High + Quantile Estimates + maintainer: Leo Belzile + description: |- + The R package proposes extreme value index estimators for heavy tailed models + by mean of order p , peaks over random threshold + and a bias-reduced estimator + . + The package also computes moment, generalised Hill + and mixed moment estimates for the extreme value index. + High quantiles and value at risk estimators based on these estimators are implemented. + date_publication: '2024-07-08' + bug_reports: https://github.com/lbelzile/evt0/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=evt0 + url_git: '' +evtclass: + version: '1.0' + title: |- + Extreme Value Theory for Open Set Classification - GPD and GEV + Classifiers + maintainer: Edoardo Vignotto + description: Two classifiers for open set recognition and novelty detection based + on extreme value theory. The first classifier is based on the generalized Pareto + distribution (GPD) and the second classifier is based on the generalized extreme + value (GEV) distribution. For details, see Vignotto, E., & Engelke, S. (2018) + . + date_publication: '2018-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evtclass + url_git: '' +evtree: + version: 1.0-8 + title: Evolutionary Learning of Globally Optimal Trees + maintainer: Thomas Grubinger + description: |- + Commonly used classification and regression tree methods like the CART algorithm + are recursive partitioning methods that build the model in a forward stepwise search. + Although this approach is known to be an efficient heuristic, the results of recursive + tree methods are only locally optimal, as splits are chosen to maximize homogeneity at + the next step only. An alternative way to search over the parameter space of trees is + to use global optimization methods like evolutionary algorithms. The 'evtree' package + implements an evolutionary algorithm for learning globally optimal classification and + regression trees in R. CPU and memory-intensive tasks are fully computed in C++ while + the 'partykit' package is leveraged to represent the resulting trees in R, providing + unified infrastructure for summaries, visualizations, and predictions. + date_publication: '2019-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=evtree + url_git: '' +EWGoF: + version: 2.2.2 + title: |- + Goodness-of-Fit Tests for the Exponential and Two-Parameter + Weibull Distributions + maintainer: Meryam Krit + description: 'Contains a large number of the goodness-of-fit tests for the Exponential + and Weibull distributions classified into families: the tests based on the empirical + distribution function, the tests based on the probability plot, the tests based + on the normalized spacings, the tests based on the Laplace transform and the likelihood + based tests.' + date_publication: '2019-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EWGoF + url_git: '' +ewoc: + version: 0.3.0 + title: Escalation with Overdose Control + maintainer: Marcio A. Diniz + description: An implementation of a variety of escalation with overdose control + designs introduced by Babb, Rogatko and Zacks (1998) . + It calculates the next dose as a clinical trial proceeds and performs simulations + to obtain operating characteristics. + date_publication: '2020-06-07' + bug_reports: https://github.com/dnzmarcio/ewoc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ewoc + url_git: https://github.com/dnzmarcio/ewoc/ +EWOC.Comb: + version: '1.0' + title: Escalation with Overdose Control using 2 Drug Combinations + maintainer: Yujie Cui + description: Implements Escalation With Overdose Control trial designs using two + drug combinations described by this paper (Tighiouart et + al., 2016). It calculates the recommended dose for next cohorts and perform simulations + to obtain operating characteristics. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EWOC.Comb + url_git: '' +ewp: + version: 0.1.1 + title: An Empirical Model for Underdispersed Count Data + maintainer: Philipp Boersch-Supan + description: Count regression models for underdispersed small counts (lambda < 20) + based on the three-parameter exponentially weighted Poisson distribution of Ridout + & Besbeas (2004) . + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ewp + url_git: '' +EwR: + version: '1.4' + title: Econometrics with R + maintainer: Burak Guris + description: Function and data sets in the book entitled "R ile Temel Ekonometri", + S.Guris, E.C.Akay, B. Guris(2020). The book published in Turkish. It is possible + to makes Durbin two stage method for autocorrelation, generalized differencing + method for correction autocorrelation, Hausman Test for identification and computes + LM, LR and Wald test statistics for redundant variable by using the functions + written in this package. + date_publication: '2020-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EwR + url_git: '' +EWS: + version: 0.2.0 + title: Early Warning System + maintainer: Quentin Lajaunie + description: The purpose of Early Warning Systems (EWS) is to detect accurately + the occurrence of a crisis, which is represented by a binary variable which takes + the value of one when the event occurs, and the value of zero otherwise. EWS are + a toolbox for policymakers to prevent or attenuate the impact of economic downturns. + Modern EWS are based on the econometric framework of Kauppi and Saikkonen (2008) + . Specifically, this framework includes four dichotomous + models, relying on a logit approach to model the relationship between yield spreads + and future recessions, controlling for recession risk factors. These models can + be estimated in a univariate or a balanced panel framework as in Candelon, Dumitrescu + and Hurlin (2014) . This package provides + both methods for estimating these models and a dataset covering 13 OECD countries + over a period of 45 years. In addition, this package also provides methods for + the analysis of the propagation mechanisms of an exogenous shock, as well as robust + confidence intervals for these response functions using a block-bootstrap method + as in Lajaunie (2021). This package constitutes a useful toolbox (data and functions) + for scholars as well as policymakers. + date_publication: '2021-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EWS + url_git: '' +EWSmethods: + version: 1.3.1 + title: Forecasting Tipping Points at the Community Level + maintainer: Duncan O'Brien + description: Rolling and expanding window approaches to assessing abundance based + early warning signals, non-equilibrium resilience measures, and machine learning. + See Dakos et al. (2012) , Deb et al. (2022) + , Drake and Griffen (2010) , + Ushio et al. (2018) and Weinans et al. (2021) + for methodological details. Graphical presentation of the outputs are also provided + for clear and publishable figures. Visit the 'EWSmethods' website for more information, + and tutorials. + date_publication: '2024-05-15' + bug_reports: https://github.com/duncanobrien/EWSmethods/issues + url: https://duncanobrien.github.io/EWSmethods/ + url_cran: https://CRAN.R-project.org/package=EWSmethods + url_git: https://github.com/duncanobrien/EWSmethods +Exact: + version: '3.3' + title: Unconditional Exact Test + maintainer: Peter Calhoun + description: |- + Performs unconditional exact tests and power calculations for 2x2 contingency tables. + For comparing two independent proportions, performs Barnard's test (1945) + using the original CSM test (Barnard, 1947 ), + using Fisher's p-value referred to as Boschloo's test (1970) , + or using a Z-statistic (Suissa and Shuster, 1985, ). + For comparing two binary proportions, performs unconditional exact test using McNemar's + Z-statistic (Berger and Sidik, 2003, ), + using McNemar's conditional p-value, using McNemar's Z-statistic with continuity correction, + or using CSM test. Calculates confidence intervals for the difference in proportion. + This package interacts with pre-computed data available through the ExactData R package, + which is available in a 'drat' repository. + Install the ExactData R package from GitHub at . + The ExactData R package is approximately 85 MB. + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Exact + url_git: '' +exact.n: + version: 1.1.1 + title: |- + Exact Samples Sizes and Inference for Clinical Trials with + Binary Endpoint + maintainer: Chris J. Lloyd + description: Allows the user to determine minimum sample sizes that achieve target + size and power at a specified alternative. For more information, see “Exact samples + sizes for clinical trials subject to size and power constraints” by Lloyd, C.J. + (2022) Preprint . + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exact.n + url_git: '' +exact2x2: + version: 1.6.9 + title: Exact Tests and Confidence Intervals for 2x2 Tables + maintainer: Michael P. Fay + description: Calculates conditional exact tests (Fisher's exact test, Blaker's exact + test, or exact McNemar's test) and unconditional exact tests (including score-based + tests on differences in proportions, ratios of proportions, and odds ratios, and + Boshcloo's test) with appropriate matching confidence intervals, and provides + power and sample size calculations. Gives melded confidence intervals for the + binomial case (Fay, et al, 2015, ). Gives boundary-optimized + rejection region test (Gabriel, et al, 2018, ), an unconditional + exact test for the situation where the controls are all expected to fail. Gives + confidence intervals compatible with exact McNemar's or sign tests (Fay and Lumbard, + 2021, ). For review of these kinds of exact tests see Fay + and Hunsberger (2021, ). + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exact2x2 + url_git: '' +exactamente: + version: 0.1.1 + title: Explore the Exact Bootstrap Method + maintainer: Mackson Ncube + description: |- + Researchers often use the bootstrap to understand a sample drawn + from a population with unknown distribution. The exact bootstrap method is a + practical tool for exploring the distribution of small sample size data. For + a sample of size n, the exact bootstrap method generates the entire space of + n to the power of n resamples and calculates all realizations of the selected + statistic. The 'exactamente' package includes functions for implementing two + bootstrap methods, the exact bootstrap and the regular bootstrap. The + exact_bootstrap() function applies the exact bootstrap method following + methodologies outlined in Kisielinska (2013) . + The regular_bootstrap() function offers a more traditional bootstrap approach, + where users can determine the number of resamples. The e_vs_r() function + allows users to directly compare results from these bootstrap methods. To + augment user experience, 'exactamente' includes the function exactamente_app() + which launches an interactive 'shiny' web application. This application + facilitates exploration and comparison of the bootstrap methods, providing + options for modifying various parameters and visualizing results. + date_publication: '2023-08-29' + bug_reports: https://github.com/mightymetrika/exactamente/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exactamente + url_git: https://github.com/mightymetrika/exactamente +exactci: + version: 1.4-4 + title: |- + Exact P-Values and Matching Confidence Intervals for Simple + Discrete Parametric Cases + maintainer: Michael P. Fay + description: Calculates exact tests and confidence intervals for one-sample binomial + and one- or two-sample Poisson cases (see Fay (2010) ). + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exactci + url_git: '' +ExactCIdiff: + version: '2.1' + title: |- + Inductive Confidence Intervals for the Difference Between Two + Proportions + maintainer: Guogen Shan + description: This is a package for exact Confidence Intervals for the difference + between two independent or dependent proportions. + date_publication: '2022-07-08' + bug_reports: '' + url: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.R-2Dproject.org&d=DwICaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=u5749-0kOlGR1AfizUVmaw&m=qjJHLdipM5gUyXllZWH5kL0wENGFef6KuJ57hW5lHx14eZasfdmgFN_1geUbxk5J&s=VFf9h_9FOlJBpRMIjim8tGuVnJ7GlWc5qZkrA9kmoMM&e= + url_cran: https://CRAN.R-project.org/package=ExactCIdiff + url_git: '' +ExactCIone: + version: 1.0.5 + title: |- + Admissible Exact Intervals for One-Dimensional Discrete + Distributions + maintainer: Chongxiu Yu + description: Construct the admissible exact intervals for the binomial proportion, + the Poisson mean and the total number of subjects with a certain attribute or + the total number of the subjects for the hypergeometric distribution. Both one-sided + and two-sided intervals are of interest. This package can be used to calculate + the intervals constructed methods developed by Wang (2014) + and Wang (2015) . + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExactCIone + url_git: '' +ExactCox: + version: 0.1.0 + title: Exact Test and Exact Confidence Interval for the Cox Model + maintainer: Yongwu Shao + description: |- + Performs the exact test on whether there is a difference between two survival curves. + Exact confidence interval for the hazard ratio can also be generated for the Cox model. + date_publication: '2024-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExactCox + url_git: '' +exactextractr: + version: 0.10.0 + title: Fast Extraction from Raster Datasets using Polygons + maintainer: Daniel Baston + description: Quickly and accurately summarizes raster values over polygonal areas + ("zonal statistics"). + date_publication: '2023-09-20' + bug_reports: https://github.com/isciences/exactextractr/issues + url: https://isciences.gitlab.io/exactextractr/ + url_cran: https://CRAN.R-project.org/package=exactextractr + url_git: https://github.com/isciences/exactextractr +exactLTRE: + version: 0.1.0 + title: |- + An Exact Method for Life Table Response Experiment (LTRE) + Analysis + maintainer: Christina Hernandez + description: 'Life Table Response Experiments (LTREs) are a method of comparative + demographic analysis. The purpose is to quantify how the difference or variance + in vital rates (stage-specific survival, growth, and fertility) among populations + contributes to difference or variance in the population growth rate, "lambda." + We provide functions for one-way fixed design and random design LTRE, using either + the classical methods that have been in use for several decades, or an fANOVA-based + exact method that directly calculates the impact on lambda of changes in matrix + elements, for matrix elements and their interactions. The equations and descriptions + for the classical methods of LTRE analysis can be found in "Matrix Population + Models: Construction, Analysis, and Interpretation (2nd edition)" Caswell (2001, + ISBN: 0878930965), and the fANOVA-based exact methods will be published in a forthcoming + paper. We also provide some demographic functions, including generation time from + Bienvenu and Legendre (2015) . For implementation of exactLTRE + where all possible interactions are calculated, we use an operator matrix presented + in Poelwijk, Krishna, and Ranganathan (2016) .' + date_publication: '2022-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exactLTRE + url_git: '' +ExactMed: + version: 0.3.0 + title: Exact Mediation Analysis for Binary Outcomes + maintainer: Miguel Caubet + description: |- + A tool for conducting exact parametric regression-based causal mediation analysis of binary outcomes + as described in Samoilenko, Blais and Lefebvre (2018) ; + Samoilenko, Lefebvre (2021) ; and Samoilenko, Lefebvre (2023) . + date_publication: '2023-09-22' + bug_reports: https://github.com/caubm/ExactMed/issues + url: https://caubm.github.io/ExactMed/ + url_cran: https://CRAN.R-project.org/package=ExactMed + url_git: '' +ExactMultinom: + version: 0.1.3 + title: Multinomial Goodness-of-Fit Tests + maintainer: Johannes Resin + description: Computes exact p-values for multinomial goodness-of-fit tests based + on multiple test statistics, namely, Pearson's chi-square, the log-likelihood + ratio and the probability mass statistic. Implements the algorithm detailed in + Resin (2023) . Estimates based on the classical + asymptotic chi-square approximation or Monte-Carlo simulation can also be computed. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExactMultinom + url_git: '' +exactRankTests: + version: 0.8-35 + title: Exact Distributions for Rank and Permutation Tests + maintainer: Torsten Hothorn + description: |- + Computes exact conditional p-values and quantiles using an + implementation of the Shift-Algorithm by Streitberg & Roehmel. + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exactRankTests + url_git: '' +exametrika: + version: 1.2.0 + title: Test Theory Analysis and Biclustering + maintainer: Koji Kosugi + description: |- + Implements comprehensive test data engineering methods as described in + Shojima (2022, ISBN:978-9811699856). Provides statistical techniques for + engineering and processing test data: Classical Test Theory (CTT) with + reliability coefficients for continuous ability assessment; Item Response + Theory (IRT) including Rasch, 2PL, and 3PL models with item/test information + functions; Latent Class Analysis (LCA) for nominal clustering; Latent Rank + Analysis (LRA) for ordinal clustering with automatic determination of cluster + numbers; Biclustering methods including infinite relational models for + simultaneous clustering of examinees and items without predefined cluster + numbers; and Bayesian Network Models (BNM) for visualizing inter-item + dependencies. Features local dependence analysis through LRA and biclustering, + parameter estimation, dimensionality assessment, and network structure + visualization for educational, psychological, and social science research. + date_publication: '2025-01-31' + bug_reports: '' + url: https://kosugitti.github.io/exametrika/ + url_cran: https://CRAN.R-project.org/package=exametrika + url_git: '' +ExamPAData: + version: 0.5.0 + title: Data Sets for Predictive Analytics Exam + maintainer: Guanglai Li + description: |- + Contains all data sets for Exam PA: Predictive Analytics at + . + date_publication: '2021-10-23' + bug_reports: https://github.com/sdcastillo/ExamPAData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ExamPAData + url_git: https://github.com/sdcastillo/ExamPAData +exampletestr: + version: 1.7.3 + title: Help for Writing Unit Tests Based on Function Examples + maintainer: Rory Nolan + description: |- + Take the examples written in your documentation of functions + and use them to create shells (skeletons which must be manually + completed by the user) of test files to be tested with the 'testthat' + package. Sort of like python 'doctests' for R. + date_publication: '2024-10-07' + bug_reports: https://github.com/rorynolan/exampletestr/issues + url: https://rorynolan.github.io/exampletestr/ + url_cran: https://CRAN.R-project.org/package=exampletestr + url_git: https://github.com/rorynolan/exampletestr#readme +exams: + version: 2.4-1 + title: Automatic Generation of Exams in R + maintainer: Achim Zeileis + description: |- + Automatic generation of exams based on exercises in Markdown or LaTeX format, + possibly including R code for dynamic generation of exercise elements. + Exercise types include single-choice and multiple-choice questions, arithmetic problems, + string questions, and combinations thereof (cloze). Output formats include standalone + files (PDF, HTML, Docx, ODT, ...), Moodle XML, QTI 1.2, QTI 2.1, Blackboard, Canvas, OpenOlat, ILIAS, TestVision, + Particify, ARSnova, Kahoot!, Grasple, and TCExam. In addition to fully customizable PDF exams, a standardized PDF format + (NOPS) is provided that can be printed, scanned, and automatically evaluated. + date_publication: '2024-07-10' + bug_reports: https://www.R-exams.org/contact/ + url: https://www.R-exams.org/ + url_cran: https://CRAN.R-project.org/package=exams + url_git: '' +exams.forge: + version: 1.0.10 + title: |- + Support for Compiling Examination Tasks using the 'exams' + Package + maintainer: Sigbert Klinke + description: |- + The main aim is to further facilitate the creation of exercises based on the package 'exams' + by Grün, B., and Zeileis, A. (2009) . Creating effective student exercises + involves challenges such as creating appropriate data sets and ensuring access to intermediate values + for accurate explanation of solutions. The functionality includes the generation of univariate and + bivariate data including simple time series, functions for theoretical distributions and their approximation, + statistical and mathematical calculations for tasks in basic statistics courses as well as general tasks + such as string manipulation, LaTeX/HTML formatting and the editing of XML task files for 'Moodle'. + date_publication: '2024-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exams.forge + url_git: '' +exams.forge.data: + version: 0.1.0 + title: Precomputed Dataset Collection Used in 'exams.forge' + maintainer: Sigbert Klinke + description: |- + The dataset collection supports Pearson correlation and linear regression analysis, + with datasets for n=100,200,400,800,1000, where n is the sum of squared values in x. + Each dataset has x values summing to zero, with sample sizes (observations in x) ranging + from 2 to 10. Additional data frames include variables with German names and measurement levels, + and distribution details with R function names, LaTeX names, discreteness, and package origins. + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exams.forge.data + url_git: '' +exams.mylearn: + version: '1.4' + title: Question Generation in the 'MyLearn' XML Format + maintainer: Darjus Hosszejni + description: |- + Randomized multiple-select and single-select + question generation for the 'MyLearn' teaching and learning + platform. Question templates + in the form of the R/exams package (see ) + are transformed into XML format required by 'MyLearn'. + date_publication: '2021-04-19' + bug_reports: https://github.com/hdarjus/exams.mylearn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exams.mylearn + url_git: https://github.com/hdarjus/exams.mylearn +exams2forms: + version: 0.1-0 + title: |- + Embedding 'exams' Exercises as Forms in 'rmarkdown' or 'quarto' + Documents + maintainer: Achim Zeileis + description: Automatic generation of quizzes or individual questions as (interactive) + forms within 'rmarkdown' or 'quarto' documents based on 'R/exams' exercises. + date_publication: '2024-11-06' + bug_reports: https://www.R-exams.org/contact/ + url: https://www.R-exams.org/ + url_cran: https://CRAN.R-project.org/package=exams2forms + url_git: '' +exams2learnr: + version: 0.1-0 + title: Interface for 'exams' Exercises in 'learnr' Tutorials + maintainer: Achim Zeileis + description: Automatic generation of quizzes or individual questions for 'learnr' + tutorials based on 'R/exams' exercises. + date_publication: '2022-10-21' + bug_reports: https://www.R-exams.org/contact/ + url: https://www.R-exams.org/ + url_cran: https://CRAN.R-project.org/package=exams2learnr + url_git: '' +exams2sakai: + version: '0.4' + title: Automatic Generation of Exams in R for 'Sakai' + maintainer: Jesús María Méndez Pérez + description: |- + Automatic Generation of Exams in R for 'Sakai'. + Question templates in the form of the 'exams' package (see ) + are transformed into XML format required by 'Sakai'. + date_publication: '2024-09-02' + bug_reports: https://github.com/jesusmmp/exams2sakai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exams2sakai + url_git: https://github.com/jesusmmp/exams2sakai +ExceedanceTools: + version: 1.3.6 + title: |- + Confidence/Credible Regions for Exceedance Sets and Contour + Lines + maintainer: Joshua French + description: |- + Provides methods for constructing confidence or credible regions + for exceedance sets and contour lines. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExceedanceTools + url_git: '' +excel2eprime: + version: 0.4.0 + title: Split Sentences by Factors + maintainer: Jack Will + description: Split experiment sentences by different experiment design given by + the user and the result can be used in 'E-prime' (). + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=excel2eprime + url_git: https://github.com/wujackwill/excel2eprime +exceldata: + version: 0.1.1.3 + title: Streamline Data Import, Cleaning and Recoding from 'Excel' + maintainer: Lisa Avery + description: |- + A small group of functions to read in a data dictionary and the + corresponding data table from 'Excel' and to automate the cleaning, re-coding + and creation of simple calculated variables. This package was designed to + be a companion to the macro-enabled 'Excel' template available + on the GitHub site, but works with any similarly-formatted 'Excel' data. + date_publication: '2023-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exceldata + url_git: '' +ExcelFunctionsR: + version: 0.1.4 + title: Imports Excel Functions to R + maintainer: Nika Salia + description: Implements 'Excel' functions in 'R' for your calculation simplicity.You + can use most of the aggregate functions, addressing functions,logical functions + and text functions. Helps you a ton in learning how 'R' works as some 'Excel' + users might be struggling with the program. + date_publication: '2020-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExcelFunctionsR + url_git: '' +excelR: + version: 0.4.0 + title: A Wrapper of the 'JavaScript' Library 'jExcel' + maintainer: Swechhya Bista + description: An R interface to 'jExcel' library to create web-based interactive + tables and spreadsheets compatible with 'Excel' or any other spreadsheet software. + date_publication: '2020-03-09' + bug_reports: https://github.com/Swechhya/excelR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=excelR + url_git: https://github.com/Swechhya/excelR +ExcessMass: + version: 1.0.1 + title: Excess Mass Calculation and Plots + maintainer: Marc-Daniel Mildenberger + description: |- + Implementation of a function which calculates the empirical excess mass + for given \eqn{\lambda} and given maximal number of modes (excessm()). Offering + powerful plot features to visualize empirical excess mass (exmplot()). This + includes the possibility of drawing several plots (with different maximal + number of modes / cut off values) in a single graph. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExcessMass + url_git: '' +excessmort: + version: 0.8.0 + title: Excess Mortality + maintainer: Rafael A. Irizarry + description: Implementation of method for estimating excess mortality and other + health related outcomes from weekly or daily count data described in Acosta and + Irizarry (2021) "A Flexible Statistical Framework for Estimating Excess Mortality". + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=excessmort + url_git: '' +excluder: + version: 0.5.1 + title: Checks for Exclusion Criteria in Online Data + maintainer: Jeffrey R. Stevens + description: |- + Data that are collected through online sources such as + Mechanical Turk may require excluding rows because of IP address + duplication, geolocation, or completion duration. This package + facilitates exclusion of these data for Qualtrics datasets. + date_publication: '2024-01-13' + bug_reports: https://github.com/ropensci/excluder/issues/ + url: https://docs.ropensci.org/excluder/ + url_cran: https://CRAN.R-project.org/package=excluder + url_git: https://github.com/ropensci/excluder/ +ExclusionTable: + version: 1.1.0 + title: Creating Tables of Excluded Observations + maintainer: Joshua P. Entrop + description: |- + Instead of counting observations before and after a subset() + call, the ExclusionTable() function reports the number before and after + each subset() call together with the number of observations that have been + excluded. This is especially useful in observational studies for keeping + track how many observations have been excluded for each in-/ or + exclusion criteria. You just need to provide ExclusionTable() with a + dataset and a list of logical filter statements. + date_publication: '2023-09-21' + bug_reports: https://github.com/entjos/ExclusionTable/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=ExclusionTable + url_git: https://github.com/entjos/ExclusionTable/ +exCon: + version: 0.2.5 + title: Interactive Exploration of Contour Data + maintainer: Bryan A. Hanson + description: |- + Interactive tools to explore topographic-like data + sets. Such data sets take the form of a matrix in which the rows and + columns provide location/frequency information, and the matrix elements + contain altitude/response information. Such data is found in cartography, + 2D spectroscopy and chemometrics. The functions in this package create + interactive web pages showing the contoured data, possibly with + slices from the original matrix parallel to each dimension. The interactive + behavior is created using the 'D3.js' 'JavaScript' library by Mike Bostock. + date_publication: '2017-07-26' + bug_reports: https://github.com/bryanhanson/exCon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exCon + url_git: https://github.com/bryanhanson/exCon +excursions: + version: 2.5.8 + title: Excursion Sets and Contour Credibility Regions for Random Fields + maintainer: David Bolin + description: Functions that compute probabilistic excursion sets, contour credibility + regions, contour avoiding regions, and simultaneous confidence bands for latent + Gaussian random processes and fields. The package also contains functions that + calculate these quantities for models estimated with the INLA package. The main + references for excursions are Bolin and Lindgren (2015) , + Bolin and Lindgren (2017) , and Bolin and Lindgren + (2018) . These can be generated by the citation function + in R. + date_publication: '2023-11-30' + bug_reports: https://github.com/davidbolin/excursions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=excursions + url_git: https://github.com/davidbolin/excursions +exdex: + version: 1.2.3 + title: Estimation of the Extremal Index + maintainer: Paul J. Northrop + description: |- + Performs frequentist inference for the extremal index of a + stationary time series. Two types of methodology are used. One type is + based on a model that relates the distribution of block maxima to the + marginal distribution of series and leads to the semiparametric maxima + estimators described in Northrop (2015) and + Berghaus and Bucher (2018) . Sliding block maxima + are used to increase precision of estimation. A graphical block size + diagnostic is provided. The other type of methodology uses a model for the + distribution of threshold inter-exceedance times (Ferro and Segers (2003) + ). Three versions of this type of approach are + provided: the iterated weight least squares approach of Suveges (2007) + , the K-gaps model of + Suveges and Davison (2010) and a similar approach + of Holesovsky and Fusek (2020) + that we refer to as D-gaps. For the K-gaps and D-gaps models this package + allows missing values in the data, can accommodate independent subsets of + data, such as monthly or seasonal time series from different years, and can + incorporate information from right-censored inter-exceedance times. + Graphical diagnostics for the threshold level and the respective tuning + parameters K and D are provided. + date_publication: '2023-12-02' + bug_reports: https://github.com/paulnorthrop/exdex/issues + url: https://paulnorthrop.github.io/exdex/ + url_cran: https://CRAN.R-project.org/package=exdex + url_git: https://github.com/paulnorthrop/exdex +exdqlm: + version: 0.1.3 + title: Extended Dynamic Quantile Linear Models + maintainer: Raquel Barata + description: Routines for Bayesian estimation and analysis of dynamic quantile linear + models utilizing the extended asymmetric Laplace error distribution, also known + as extended dynamic quantile linear models (exDQLM) described in Barata et al + (2020) . + date_publication: '2023-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exdqlm + url_git: '' +executablePackeR: + version: 0.0.2 + title: Make 'shiny' App to Executable Program + maintainer: Changwoo Lim + description: |- + Make your 'shiny' application as executable program. + Users do not need to install 'R' and 'shiny' on their system. + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=executablePackeR + url_git: '' +ExGaussEstim: + version: 0.1.2 + title: |- + Quantile Maximization Likelihood Estimation and Bayesian + Ex-Gaussian Estimation + maintainer: Jean DUMONCEL + description: 'Presents two methods to estimate the parameters ''mu'', ''sigma'', + and ''tau'' of an ex-Gaussian distribution. Those methods are Quantile Maximization + Likelihood Estimation (''QMLE'') and Bayesian. The ''QMLE'' method allows a choice + between three different estimation algorithms for these parameters : ''neldermead'' + (''NEMD''), ''fminsearch'' (''FMIN''), and ''nlminb'' (''NLMI''). For more details + about the methods you can refer at the following list: Brown, S., & Heathcote, + A. (2003) ; McCormack, P. D., & Wright, N. M. (1964) ; + Van Zandt, T. (2000) ; El Haj, A., Slaoui, Y., Solier, + C., & Perret, C. (2021) ; Gilks, W. R., Best, + N. G., & Tan, K. K. C. (1995) .' + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExGaussEstim + url_git: '' +exhaustiveRasch: + version: 0.3.7 + title: Item Selection and Exhaustive Search for Rasch Models + maintainer: Christian Grebe + description: Automation of the item selection processes for Rasch scales by means + of exhaustive search for suitable Rasch models (dichotomous, partial credit, rating-scale) + in a list of item-combinations. The item-combinations to test can be either all + possible combinations or item-combinations can be defined by several rules (forced + inclusion of specific items, exclusion of combinations, minimum/maximum items + of a subset of items). Tests for model fit and item fit include ordering of the + thresholds, item fit-indices, likelihood ratio test, Martin-Löf test, Wald-like + test, person-item distribution, person separation index, principal components + of Rasch residuals, empirical representation of all raw scores or Rasch trees + for detecting differential item functioning. The tests, their ordering and their + parameters can be defined by the user. For parameter estimation and model tests, + functions of the packages 'eRm', 'psychotools' or 'pairwise' can be used. + date_publication: '2024-12-17' + bug_reports: https://github.com/chrgrebe/exhaustiveRasch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exhaustiveRasch + url_git: https://github.com/chrgrebe/exhaustiveRasch +ExhaustiveSearch: + version: 1.0.1 + title: A Fast and Scalable Exhaustive Feature Selection Framework + maintainer: Rudolf Jagdhuber + description: |- + The goal of this package is to provide an easy to use, fast and + scalable exhaustive search framework. Exhaustive feature selections + typically require a very large number of models to be fitted and evaluated. + Execution speed and memory management are crucial factors here. This package + provides solutions for both. Execution speed is optimized by using a + multi-threaded C++ backend, and memory issues are solved by by only storing + the best results during execution and thus keeping memory usage constant. + date_publication: '2021-01-18' + bug_reports: https://github.com/RudolfJagdhuber/ExhaustiveSearch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ExhaustiveSearch + url_git: https://github.com/RudolfJagdhuber/ExhaustiveSearch +exif: + version: 0.1.0 + title: Read EXIF Metadata from JPEGs + maintainer: Oliver Keyes + description: |- + Extracts Exchangeable Image File Format (EXIF) metadata, such as camera make and model, ISO speed and the date-time + the picture was taken on, from JPEG images. Incorporates the 'easyexif' (https://github.com/mayanklahiri/easyexif) + library. + date_publication: '2015-12-14' + bug_reports: https://github.com/Ironholds/exif/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exif + url_git: https://github.com/Ironholds/exif +exifr: + version: 0.3.2 + title: EXIF Image Data in R + maintainer: Dewey Dunnington + description: |- + Reads EXIF data using ExifTool + and returns results as a data frame. + ExifTool is a platform-independent Perl library plus a command-line + application for reading, writing and editing meta information in a wide variety + of files. ExifTool supports many different metadata formats including EXIF, + GPS, IPTC, XMP, JFIF, GeoTIFF, ICC Profile, Photoshop IRB, FlashPix, AFCP and + ID3, as well as the maker notes of many digital cameras by Canon, Casio, FLIR, + FujiFilm, GE, HP, JVC/Victor, Kodak, Leaf, Minolta/Konica-Minolta, Motorola, Nikon, + Nintendo, Olympus/Epson, Panasonic/Leica, Pentax/Asahi, Phase One, Reconyx, Ricoh, + Samsung, Sanyo, Sigma/Foveon and Sony. + date_publication: '2021-03-20' + bug_reports: https://github.com/paleolimbot/exifr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exifr + url_git: https://github.com/paleolimbot/exifr +exiftoolr: + version: 0.2.7 + title: ExifTool Functionality from R + maintainer: Joshua O'Brien + description: |- + Reads, writes, and edits EXIF and other file metadata using + ExifTool , returning read results as a data + frame. ExifTool supports many different metadata formats including EXIF, + GPS, IPTC, XMP, JFIF, GeoTIFF, ICC Profile, Photoshop IRB, FlashPix, AFCP + and ID3, Lyrics3, as well as the maker notes of many digital cameras by + Canon, Casio, DJI, FLIR, FujiFilm, GE, GoPro, HP, JVC/Victor, Kodak, Leaf, + Minolta/Konica-Minolta, Motorola, Nikon, Nintendo, Olympus/Epson, + Panasonic/Leica, Pentax/Asahi, Phase One, Reconyx, Ricoh, Samsung, Sanyo, + Sigma/Foveon and Sony. + date_publication: '2025-01-14' + bug_reports: https://github.com/JoshOBrien/exiftoolr/issues + url: https://joshobrien.github.io/exiftoolr/ + url_cran: https://CRAN.R-project.org/package=exiftoolr + url_git: https://github.com/JoshOBrien/exiftoolr#readme +ExNRuleEnsemble: + version: 0.1.1 + title: |- + A k Nearest Neibour Ensemble Based on Extended Neighbourhood + Rule + maintainer: Amjad Ali + description: The extended neighbourhood rule for the k nearest neighbour ensemble + where the neighbours are determined in k steps. Starting from the first nearest + observation of the test point, the algorithm identifies a single observation that + is closest to the observation at the previous step. At each base learner in the + ensemble, this search is extended to k steps on a random bootstrap sample with + a random subset of features selected from the feature space. The final predicted + class of the test point is determined by using a majority vote in the predicted + classes given by all base models. Amjad Ali, Muhammad Hamraz, Naz Gul, Dost Muhammad + Khan, Saeed Aldahmani, Zardad Khan (2022) . + date_publication: '2022-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExNRuleEnsemble + url_git: '' +ExpAnalysis3d: + version: 0.1.2 + title: |- + Pacote Para Analise De Experimentos Com Graficos De Superficie + Resposta + maintainer: Alcinei Mistico Azevedo + description: |- + Pacote para a analise de experimentos havendo duas variaveis + explicativas quantitativas e uma variavel dependente quantitativa. Os + experimentos podem ser sem repeticoes ou com delineamento estatistico. + Sao ajustados 12 modelos de regressao multipla e plotados graficos de + superficie resposta (Hair JF, 2016) .(Package + for the analysis of experiments having two explanatory quantitative + variables and one quantitative dependent variable. The experiments can + be without repetitions or with a statistical design. Twelve multiple + regression models are fitted and response surface graphs are plotted + (Hair JF, 2016) ). + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExpAnalysis3d + url_git: '' +ExPanDaR: + version: 0.5.3 + title: Explore Your Data Interactively + maintainer: Joachim Gassen + description: |- + Provides a shiny-based front end (the 'ExPanD' app) and + a set of functions for exploratory data analysis. Run as a web-based + app, 'ExPanD' enables users to assess the robustness of empirical evidence + without providing them access to the underlying data. You can export a + notebook containing the analysis of 'ExPanD' and/or use the functions of the + package to support your exploratory data analysis workflow. Refer to the + vignettes of the package for more information on how to use 'ExPanD' and/or + the functions of this package. + date_publication: '2020-12-06' + bug_reports: https://github.com/joachim-gassen/ExPanDaR/issues + url: https://joachim-gassen.github.io/ExPanDaR/ + url_cran: https://CRAN.R-project.org/package=ExPanDaR + url_git: '' +expandFunctions: + version: 0.1.0 + title: Feature Matrix Builder + maintainer: Scott Miller + description: |- + Generates feature matrix outputs from R object inputs + using a variety of expansion functions. The generated + feature matrices have applications as inputs + for a variety of machine learning algorithms. + The expansion functions are based on coercing the input + to a matrix, treating the columns as features and + converting individual columns or combinations into blocks of + columns. + Currently these include expansion of columns by + efficient sparse embedding by vectors of lags, + quadratic expansion into squares and unique products, + powers by vectors of degree, + vectors of orthogonal polynomials functions, + and block random affine projection transformations (RAPTs). + The transformations are + magrittr- and cbind-friendly, and can be used in a + building block fashion. For instance, taking the cos() of + the output of the RAPT transformation generates a + stationary kernel expansion via Bochner's theorem, and this + expansion can then be cbind-ed with other features. + Additionally, there are utilities for replacing features, + removing rows with NAs, + creating matrix samples of a given distribution, + a simple wrapper for LASSO with CV, + a Freeman-Tukey transform, + generalizations of the outer function, + matrix size-preserving discrete difference by row, + plotting, etc. + date_publication: '2016-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=expandFunctions + url_git: '' +EXPAR: + version: 0.1.0 + title: Fitting of Exponential Autoregressive (EXPAR) Model + maintainer: Saikath Das + description: The amplitude-dependent exponential autoregressive (EXPAR) time series + model, initially proposed by Haggan and Ozaki (1981) has + been implemented in this package. Throughout various studies, the model has been + found to adequately capture the cyclical nature of datasets. Parameter estimation + of such family of models has been tackled by the approach of minimizing the residual + sum of squares (RSS). Model selection among various candidate orders has been + implemented using various information criteria, viz., Akaike information criteria + (AIC), corrected Akaike information criteria (AICc) and Bayesian information criteria + (BIC). An illustration utilizing data of egg price indices has also been provided. + date_publication: '2024-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EXPAR + url_git: '' +EXPARMA: + version: 0.1.0 + title: |- + Fitting of Exponential Autoregressive Moving Average (EXPARMA) + Model + maintainer: Bishal Gurung + description: The amplitude-dependent autoregressive time series model (EXPAR) proposed + by Haggan and Ozaki (1981) was improved by incorporating + the moving average (MA) framework for capturing the variability efficiently. Parameters + of the EXPARMA model can be estimated using this package. The user is provided + with the best fitted EXPARMA model for the data set under consideration. + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EXPARMA + url_git: '' +expDB: + version: 0.1.0 + title: Database for Experiment Dataset + maintainer: Bangyou Zheng + description: |- + A SQLite database is designed to store all information + of experiment-based data including metadata, experiment design, + managements, phenotypic values and climate records. The dataset can be + imported from an excel file. + date_publication: '2021-10-08' + bug_reports: https://github.com/byzheng/expdb/issues + url: https://expdb.bangyou.me/ + url_cran: https://CRAN.R-project.org/package=expDB + url_git: https://github.com/byzheng/expdb +ExpDE: + version: 0.1.4 + title: Modular Differential Evolution for Experimenting with Operators + maintainer: Felipe Campelo + description: |- + Modular implementation of the Differential Evolution algorithm for + experimenting with different types of operators. + date_publication: '2018-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExpDE + url_git: http://github.com/fcampelo/ExpDE +ExpDes: + version: 1.2.2 + title: Experimental Designs Package + maintainer: Eric Batista Ferreira + description: Package for analysis of simple experimental designs (CRD, RBD and LSD), + experiments in double factorial schemes (in CRD and RBD), experiments in a split + plot in time schemes (in CRD and RBD), experiments in double factorial schemes + with an additional treatment (in CRD and RBD), experiments in triple factorial + scheme (in CRD and RBD) and experiments in triple factorial schemes with an additional + treatment (in CRD and RBD), performing the analysis of variance and means comparison + by fitting regression models until the third power (quantitative treatments) or + by a multiple comparison test, Tukey test, test of Student-Newman-Keuls (SNK), + Scott-Knott, Duncan test, t test (LSD) and Bonferroni t test (protected LSD) - + for qualitative treatments; residual analysis (Ferreira, Cavalcanti and Nogueira, + 2014) . + date_publication: '2021-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExpDes + url_git: '' +ExpDes.pt: + version: 1.2.2 + title: Pacote Experimental Designs (Portugues) + maintainer: Eric Batista Ferreira + description: Pacote para análise de delineamentos experimentais (DIC, DBC e DQL), + experimentos em esquema fatorial duplo (em DIC e DBC), experimentos em parcelas + subdivididas (em DIC e DBC), experimentos em esquema fatorial duplo com um tratamento + adicional (em DIC e DBC), experimentos em fatorial triplo (em DIC e DBC) e experimentos + em esquema fatorial triplo com um tratamento adicional (em DIC e DBC), fazendo + analise de variancia e comparacao de multiplas medias (para tratamentos qualitativos), + ou ajustando modelos de regressao ate a terceira potencia (para tratamentos quantitativos); + analise de residuos (Ferreira, Cavalcanti and Nogueira, 2014) . + date_publication: '2021-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExpDes.pt + url_git: '' +expectreg: + version: '0.53' + title: Expectile and Quantile Regression + maintainer: Fabian Otto-Sobotka + description: |- + Expectile and quantile regression of models with nonlinear effects + e.g. spatial, random, ridge using least asymmetric weighed squares / absolutes + as well as boosting; also supplies expectiles for common distributions. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=expectreg + url_git: '' +experDesign: + version: 0.4.0 + title: Design Experiments for Batches + maintainer: Lluís Revilla Sancho + description: |- + Distributes samples in batches while making batches + homogeneous according to their description. Allows for an arbitrary + number of variables, both numeric and categorical. For quality control + it provides functions to subset a representative sample. + date_publication: '2024-05-20' + bug_reports: https://github.com/llrs/experDesign/issues + url: https://experdesign.llrs.dev + url_cran: https://CRAN.R-project.org/package=experDesign + url_git: https://github.com/llrs/experDesign/ +experiences: + version: 0.1.1 + title: Experience Research + maintainer: Joe Chelladurai + description: |- + Provides convenience functions for researching experiences + including user, customer, patient, employee, and other human experiences. + It provides a suite of tools to simplify data exploration such as + benchmarking, comparing groups, and checking for differences. The outputs + translate statistical approaches in applied experience research to + human readable output. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=experiences + url_git: '' +experiment: + version: 1.2.1 + title: R Package for Designing and Analyzing Randomized Experiments + maintainer: Kosuke Imai + description: |- + Provides various statistical methods for + designing and analyzing randomized experiments. One functionality + of the package is the implementation of randomized-block and + matched-pair designs based on possibly multivariate pre-treatment + covariates. The package also provides the tools to analyze various + randomized experiments including cluster randomized experiments, + two-stage randomized experiments, randomized experiments with + noncompliance, and randomized experiments with missing data. + date_publication: '2022-04-12' + bug_reports: https://github.com/kosukeimai/experiment/issues + url: '' + url_cran: https://CRAN.R-project.org/package=experiment + url_git: https://github.com/kosukeimai/experiment +experimentr: + version: 0.1.0 + title: |- + Datasets Used in Social Science Experiments: A Hands-on + Introduction + maintainer: Kerem Tuncer + description: 'Contains all the datasets that were used in Social Science Experiments: + A Hands-On Introduction and in its R Companion. Relevant materials can be found + at .' + date_publication: '2022-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=experimentr + url_git: '' +ExpertChoice: + version: 0.2.0 + title: Design of Discrete Choice and Conjoint Analysis + maintainer: Jed Stephens + description: Supports designing efficient discrete choice experiments (DCEs). Experimental + designs can be formed on the basis of orthogonal arrays or search methods for + optimal designs (Federov or mixed integer programs). Various methods for converting + these experimental designs into a discrete choice experiment. Many efficiency + measures! Draws from literature of Kuhfeld (2010) and Street et. al (2005) . + date_publication: '2020-04-03' + bug_reports: https://github.com/JedStephens/ExpertChoice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ExpertChoice + url_git: '' +expertsurv: + version: 1.4.0 + title: Incorporate Expert Opinion with Parametric Survival Models + maintainer: Philip Cooney + description: Enables users to incorporate expert opinion with parametric survival + analysis using a Bayesian or frequentist approach. Expert Opinion can be provided + on the survival probabilities at certain time-point(s) or for the difference in + mean survival between two treatment arms. Please reference it's use as Cooney, + P., White, A. (2023) . + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=expertsurv + url_git: '' +ExpGenetic: + version: 0.1.0 + title: Non-Additive Expression Analysis of Hybrid Offspring + maintainer: Yuqing Wu + description: Three functional modules, including genetic features, differential + expression analysis and non-additive expression analysis were integrated into + the package. And the package is suitable for RNA-seq and small RNA sequencing + data. Besides, two methods of non-additive expression analysis were provided. + One is the calculation of the additive (a) and dominant (d), the other is the + evaluation of expression level dominance by comparing the total expression of + the gene in hybrid offspring with the expression level in parents. For non-additive + expression analysis of RNA-seq data, it is only applicable to hybrid offspring + (including two sub-genomes) species for the time being. + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExpGenetic + url_git: '' +expint: + version: 0.1-8 + title: Exponential Integral and Incomplete Gamma Function + maintainer: Vincent Goulet + description: |- + The exponential integrals E_1(x), E_2(x), E_n(x) and + Ei(x), and the incomplete gamma function G(a, x) defined for + negative values of its first argument. The package also gives easy + access to the underlying C routines through an API; see the package + vignette for details. A test package included in sub-directory + example_API provides an implementation. C routines derived from the + GNU Scientific Library . + date_publication: '2022-10-28' + bug_reports: https://gitlab.com/vigou3/expint/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=expint + url_git: https://gitlab.com/vigou3/expint +expirest: + version: 0.1.7 + title: Expiry Estimation Procedures + maintainer: Pius Dahinden + description: |- + The Australian Regulatory Guidelines for Prescription + Medicines (ARGPM), guidance on "Stability testing for prescription + medicines", recommends to predict the shelf life of chemically derived + medicines from stability data by taking the worst case situation at batch + release into account. Consequently, if a change over time is observed, + a release limit needs to be specified. Finding a release limit and the + associated shelf life is supported, as well as the standard approach + that is recommended by guidance Q1E "Evaluation of stability data" + from the International Council for Harmonisation (ICH). + date_publication: '2025-02-25' + bug_reports: https://github.com/piusdahinden/expirest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=expirest + url_git: https://github.com/piusdahinden/expirest +explainer: + version: 1.0.2 + title: Machine Learning Model Explainer + maintainer: Ramtin Zargari Marandi + description: It enables detailed interpretation of complex classification and regression + models through Shapley analysis including data-driven characterization of subgroups + of individuals. Furthermore, it facilitates multi-measure model evaluation, model + fairness, and decision curve analysis. Additionally, it offers enhanced visualizations + with interactive elements. + date_publication: '2024-09-30' + bug_reports: https://github.com/PERSIMUNE/explainer/issues + url: https://persimune.github.io/explainer/ + url_cran: https://CRAN.R-project.org/package=explainer + url_git: https://github.com/PERSIMUNE/explainer +ExplainPrediction: + version: 1.3.0 + title: |- + Explanation of Predictions for Classification and Regression + Models + maintainer: Marko Robnik-Sikonja + description: |- + Generates explanations for classification and regression models and visualizes them. + Explanations are generated for individual predictions as well as for models as a whole. Two explanation methods + are included, EXPLAIN and IME. The EXPLAIN method is fast but might miss explanations expressed redundantly + in the model. The IME method is slower as it samples from all feature subsets. + For the EXPLAIN method see Robnik-Sikonja and Kononenko (2008) , + and the IME method is described in Strumbelj and Kononenko (2010, JMLR, vol. 11:1-18). + All models in package 'CORElearn' are natively supported, for other prediction models a wrapper function is provided + and illustrated for models from packages 'randomForest', 'nnet', and 'e1071'. + date_publication: '2018-01-07' + bug_reports: '' + url: http://lkm.fri.uni-lj.si/rmarko/software/ + url_cran: https://CRAN.R-project.org/package=ExplainPrediction + url_git: '' +ExplodeLayout: + version: 0.1.2 + title: |- + Calculate Exploded Coordinates Based on Original Node + Coordinates and Node Clustering Membership + maintainer: Weibin Zhang + description: 'Current layout algorithms such as Kamada Kawai do not take into consideration + disjoint clusters in a network, often resulting in a high overlap among the clusters, + resulting in a visual “hairball” that often is uninterpretable. The ExplodeLayout + algorithm takes as input (1) an edge list of a unipartite or bipartite network, + (2) node layout coordinates (x, y) generated by a layout algorithm such as Kamada + Kawai, (3) node cluster membership generated from a clustering algorithm such + as modularity maximization, and (4) a radius to enable the node clusters to be + “exploded” to reduce their overlap. The algorithm uses these inputs to generate + new layout coordinates of the nodes which “explodes” the clusters apart, such + that the edge lengths within the clusters are preserved, while the edge lengths + between clusters are recalculated. The modified network layout with nodes and + edges are displayed in two dimensions. The user can experiment with different + explode radii to generate a layout which has sufficient separation of clusters, + while reducing the overall layout size of the network. This package is a basic + version of an earlier version called [epl] + that searched for an optimal explode radius, and offered multiple ways to separate + clusters in a network (Bhavnani et al(2017) ). The example dataset + is for a bipartite network, but the algorithm can work also for unipartite networks.' + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExplodeLayout + url_git: '' +explor: + version: 0.3.10 + title: Interactive Interfaces for Results Exploration + maintainer: Julien Barnier + description: Shiny interfaces and graphical functions for multivariate analysis + results exploration. + date_publication: '2023-04-29' + bug_reports: https://github.com/juba/explor/issues + url: https://juba.github.io/explor/ + url_cran: https://CRAN.R-project.org/package=explor + url_git: '' +exploratory: + version: 0.3.31 + title: A Tool for Large-Scale Exploratory Analyses + maintainer: Jin Kim + description: |- + Conduct numerous exploratory analyses in an instant with a + point-and-click interface. With one simple command, this tool + launches a Shiny App on the local machine. Drag and drop variables + in a data set to categorize them as possible independent, + dependent, moderating, or mediating variables. Then run dozens + (or hundreds) of analyses instantly to uncover any statistically + significant relationships among variables. Any relationship + thus uncovered should be tested in follow-up studies. + This tool is designed only to facilitate exploratory + analyses and should NEVER be used for p-hacking. Many of + the functions used in this package are previous versions of functions + in the R Packages 'kim' and 'ezr'. + Selected References: + Chang et al. (2021) . + Dowle et al. (2021) . + Kim (2023) . + Kim (2021) . + Kim (2020) . + Simmons et al. (2011) + Tingley et al. (2019) . + Wickham et al. (2020) . + date_publication: '2023-10-10' + bug_reports: https://github.com/jinkim3/exploratory/issues + url: https://exploratoryonly.com + url_cran: https://CRAN.R-project.org/package=exploratory + url_git: '' +explore: + version: 1.3.3 + title: Simplifies Exploratory Data Analysis + maintainer: Roland Krasser + description: |- + Interactive data exploration with one line of code, automated + reporting or use an easy to remember set of tidy functions for low + code exploratory data analysis. + date_publication: '2024-11-12' + bug_reports: https://github.com/rolkra/explore/issues + url: https://rolkra.github.io/explore/ + url_cran: https://CRAN.R-project.org/package=explore + url_git: https://github.com/rolkra/explore +exploreR: + version: '0.1' + title: Tools for Quickly Exploring Data + maintainer: Michael Coates + description: Simplifies some complicated and labor intensive processes involved + in exploring and explaining data. Allows you to quickly and efficiently visualize + the interaction between variables and simplifies the process of discovering covariation + in your data. Also includes some convenience features designed to remove as much + redundant typing as possible. + date_publication: '2016-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exploreR + url_git: '' +expm: + version: 1.0-0 + title: Matrix Exponential, Log, 'etc' + maintainer: Martin Maechler + description: |- + Computation of the matrix exponential, logarithm, sqrt, + and related quantities, using traditional and modern methods. + date_publication: '2024-08-19' + bug_reports: https://R-forge.R-project.org/tracker/?atid=472&group_id=107 + url: '' + url_cran: https://CRAN.R-project.org/package=expm + url_git: https://R-Forge.R-project.org/projects/expm/ +export: + version: 0.3.0 + title: Streamlined Export of Graphs and Data Tables + maintainer: Tom Wenseleers + description: |- + Easily export 'R' graphs and statistical output to 'Microsoft + Office' / 'LibreOffice', 'Latex' and 'HTML' Documents, using sensible defaults + that result in publication-quality output with simple, straightforward commands. + Output to 'Microsoft Office' is in editable 'DrawingML' vector format for + graphs, and can use corporate template documents for styling. This enables + the production of standardized reports and also allows for manual tidy-up + of the layout of 'R' graphs in 'Powerpoint' before final publication. Export + of graphs is flexible, and functions enable the currently showing R graph + or the currently showing 'R' stats object to be exported, but also allow the + graphical or tabular output to be passed as objects. The package relies on package + 'officer' for export to 'Office' documents,and output files are also fully compatible + with 'LibreOffice'. Base 'R', 'ggplot2' and 'lattice' plots are supported, as + well as a wide variety of 'R' stats objects, via wrappers to xtable(), broom::tidy() + and stargazer(), including aov(), lm(), glm(), lme(), glmnet() and coxph() as + well as matrices and data frames and many more... + date_publication: '2022-12-07' + bug_reports: https://github.com/tomwenseleers/export/issues + url: '' + url_cran: https://CRAN.R-project.org/package=export + url_git: '' +ExPosition: + version: 2.8.23 + title: Exploratory Analysis with the Singular Value Decomposition + maintainer: Derek Beaton + description: |- + A variety of descriptive multivariate analyses with the singular value decomposition, + such as principal components analysis, correspondence analysis, and multidimensional scaling. + See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) . + date_publication: '2019-01-07' + bug_reports: https://github.com/derekbeaton/ExPosition-Family_OLD + url: '' + url_cran: https://CRAN.R-project.org/package=ExPosition + url_git: '' +ExposR: + version: '1.2' + title: Models Topographic Exposure to Hurricane Winds + maintainer: Emery Boose + description: |- + The EXPOS model uses a digital elevation model (DEM) to estimate + exposed and protected areas for a given hurricane wind direction and + inflection angle. The resulting topographic exposure maps can be combined + with output from the HURRECON model to estimate hurricane wind damage + across a region. For details on the original version of the EXPOS model + written in 'Borland Pascal', see: Boose, Foster, and Fluet (1994) + , Boose, Chamberlin, and Foster (2001) + , and Boose, + Serrano, and Foster (2004) . + date_publication: '2024-11-09' + bug_reports: https://github.com/expos-model/ExposR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ExposR + url_git: https://github.com/expos-model/ExposR +expowo: + version: '2.0' + title: Data Mining of Plant Diversity and Distribution + maintainer: Debora Zuanny + description: Produces diversity estimates and species lists with associated global + distribution for any vascular plant family and genus from 'Plants of the World + Online' database , by interacting with the source + code of each plant taxon page. It also creates global maps of species richness, + graphics of species discoveries and nomenclatural changes over time. + date_publication: '2024-03-01' + bug_reports: https://github.com/DBOSlab/expowo/issues + url: https://dboslab.github.io/expowo/ + url_cran: https://CRAN.R-project.org/package=expowo + url_git: https://github.com/dboslab/expowo +expperm: + version: '1.6' + title: Computing Expectations and Marginal Likelihoods for Permutations + maintainer: Ben Powell + description: A set of functions for computing expected permutation matrices given + a matrix of likelihoods for each individual assignment. It has been written to + accompany the forthcoming paper 'Computing expectations and marginal likelihoods + for permutations'. Publication details will be updated as soon as they are finalized. + date_publication: '2019-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=expperm + url_git: '' +ExpRep: + version: '1.0' + title: Experiment Repetitions + maintainer: Larisa Zamora-Matamoros + description: |- + Allows to calculate the probabilities of occurrences of an event in a + great number of repetitions of Bernoulli experiment, through the application of + the local and the integral theorem of De Moivre Laplace, and the theorem of Poisson. + Gives the possibility to show the results graphically and analytically, and to compare + the results obtained by the application of the above theorems with those calculated by + the direct application of the Binomial formula. Is basically useful for educational + purposes. + date_publication: '2017-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExpRep + url_git: '' +expSBM: + version: 1.3.5 + title: An Exponential Stochastic Block Model for Interaction Lengths + maintainer: Riccardo Rastelli + description: Given a continuous-time dynamic network, this package allows one to + fit a stochastic blockmodel where nodes belonging to the same group create interactions + and non-interactions of similar lengths. This package implements the methodology + described by R. Rastelli and M. Fop (2019) . + date_publication: '2019-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=expSBM + url_git: '' +expsmooth: + version: '2.3' + title: Data Sets from "Forecasting with Exponential Smoothing" + maintainer: Rob J Hyndman + description: |- + Data sets from the book "Forecasting with exponential smoothing: the state space approach" by + Hyndman, Koehler, Ord and Snyder (Springer, 2008). + date_publication: '2015-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=expsmooth + url_git: https://github.com/robjhyndman/expsmooth +expss: + version: 0.11.6 + title: |- + Tables, Labels and Some Useful Functions from Spreadsheets and + 'SPSS' Statistics + maintainer: Gregory Demin + description: |- + Package computes and displays tables with support for 'SPSS'-style + labels, multiple and nested banners, weights, multiple-response variables + and significance testing. There are facilities for nice output of tables + in 'knitr', 'Shiny', '*.xlsx' files, R and 'Jupyter' notebooks. Methods + for labelled variables add value labels support to base R functions and to + some functions from other packages. Additionally, the package brings + popular data transformation functions from 'SPSS' Statistics and 'Excel': + 'RECODE', 'COUNT', 'COUNTIF', 'VLOOKUP' and etc. + These functions are very useful for data processing in marketing research + surveys. Package intended to help people to move data + processing from 'Excel' and 'SPSS' to R. + date_publication: '2023-07-15' + bug_reports: https://github.com/gdemin/expss/issues + url: https://gdemin.github.io/expss/ + url_cran: https://CRAN.R-project.org/package=expss + url_git: '' +expstudy: + version: 2.0.0 + title: Tools for Actuarial Experience Studies + maintainer: Cody Buehler + description: |- + Experiences studies are an integral component of the actuarial + control cycle. Regardless of the decrement or policyholder behavior of + interest, the analyses conducted is often the same. Ultimately, this + package aims to reduce time spent writing the same code used for + different experience studies, therefore increasing the time for to uncover + new insights inherit within the relevant experience. + date_publication: '2024-02-05' + bug_reports: https://github.com/cb12991/expstudy/issues + url: https://cb12991.github.io/expstudy/ + url_cran: https://CRAN.R-project.org/package=expstudy + url_git: https://github.com/cb12991/expstudy +exreport: + version: 0.4.1 + title: Fast, Reliable and Elegant Reproducible Research + maintainer: Jacinto Arias + description: Analysis of experimental results and automatic report generation in + both interactive HTML and LaTeX. This package ships with a rich interface for + data modeling and built in functions for the rapid application of statistical + tests and generation of common plots and tables with publish-ready quality. + date_publication: '2016-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exreport + url_git: '' +EXRQ: + version: '1.0' + title: Extreme Regression of Quantiles + maintainer: Huixia Judy Wang + description: Estimation for high conditional quantiles based on quantile regression. + date_publication: '2016-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EXRQ + url_git: '' +extBatchMarking: + version: 1.1.0 + title: Extended Batch Marking Models + maintainer: Kehinde Olobatuyi + description: 'A system for batch-marking data analysis to estimate survival probabilities, + capture probabilities, and enumerate the population abundance for both marked + and unmarked individuals. The estimation of only marked individuals can be achieved + through the batchMarkOptim() function. Similarly, the combined marked and unmarked + can be achieved through the batchMarkUnmarkOptim() function. The algorithm was + also implemented for the hidden Markov model encapsulated in batchMarkUnmarkOptim() + to estimate the abundance of both marked and unmarked individuals in the population. + The package is based on the paper: "Hidden Markov Models for Extended Batch Data" + of Cowen et al. (2017) .' + date_publication: '2024-10-04' + bug_reports: https://github.com/Olobatuyi/extBatchMarking_cov/issues + url: '' + url_cran: https://CRAN.R-project.org/package=extBatchMarking + url_git: https://github.com/Olobatuyi/extBatchMarking_cov +ExtDist: + version: 0.7-2 + title: Extending the Range of Functions for Probability Distributions + maintainer: Oleksii Nikolaienko + description: |- + A consistent, unified and extensible + framework for estimation of parameters for probability distributions, including + parameter estimation procedures that allow for weighted samples; the current set of distributions included are: the standard beta, The four-parameter beta, Burr, gamma, Gumbel, Johnson SB and SU, Laplace, logistic, normal, symmetric truncated normal, truncated normal, symmetric-reflected truncated beta, standard symmetric-reflected truncated beta, triangular, uniform, and Weibull distributions; decision criteria and selections based on these decision criteria. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExtDist + url_git: '' +extendedFamily: + version: 0.2.4 + title: Additional Families for Generalized Linear Models + maintainer: Greg McMahan + description: |- + Creates family objects identical to stats + family but for new links. + date_publication: '2023-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extendedFamily + url_git: '' +exteriorMatch: + version: 1.0.0 + title: Constructs the Exterior Match from Two Matched Control Groups + maintainer: Paul R. Rosenbaum + description: If one treated group is matched to one control reservoir in two different + ways to produce two sets of treated-control matched pairs, then the two control + groups may be entwined, in the sense that some control individuals are in both + control groups. The exterior match is used to compare the two control groups. + date_publication: '2016-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exteriorMatch + url_git: '' +extlasso: + version: '0.3' + title: |- + Maximum Penalized Likelihood Estimation with Extended Lasso + Penalty + maintainer: B N Mandal + description: Estimates coefficients of extended LASSO penalized linear regression + and generalized linear models. Currently lasso and elastic net penalized linear + regression and generalized linear models are considered. This package currently + utilizes an accurate approximation of L1 penalty and then a modified Jacobi algorithm + to estimate the coefficients. There is provision for plotting of the solutions + and predictions of coefficients at given values of lambda. This package also contains + functions for cross validation to select a suitable lambda value given the data. + Also provides a function for estimation in fused lasso penalized linear regression. + For more details, see Mandal, B. N.(2014). Computational methods for L1 penalized + GLM model fitting, unpublished report submitted to Macquarie University, NSW, + Australia. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extlasso + url_git: '' +ExtMallows: + version: 0.1.0 + title: |- + An Extended Mallows Model and Its Hierarchical Version for + Ranked Data Aggregation + maintainer: Han Li + description: For multiple full/partial ranking lists, R package 'ExtMallows' can + (1) detect whether the input ranking lists are over-correlated, and (2) use the + Mallows model or extended Mallows model to integrate the ranking lists, and (3) + use hierarchical extended Mallows model for rank integration if there are groups + of over-correlated ranking lists. + date_publication: '2018-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExtMallows + url_git: '' +extractox: + version: 1.0.0 + title: Extract Tox Info from Various Databases + maintainer: Claudio Zanettini + description: |- + Extract toxicological and chemical information from databases + maintained by scientific agencies and resources, including the + Comparative Toxicogenomics Database , the + Integrated Chemical Environment , the + Integrated Risk Information System , + Provisional Peer-Reviewed Toxicity Values + , + the CompTox Chemicals Dashboard Resource Hub + , + PubChem , and others. + date_publication: '2025-01-07' + bug_reports: https://github.com/c1au6i0/extractox/issues + url: https://c1au6i0.github.io/extractox/ + url_cran: https://CRAN.R-project.org/package=extractox + url_git: https://github.com/c1au6i0/extractox +ExtractTrainData: + version: 9.1.6 + title: Extract Values from Raster + maintainer: Subhadip Datta + description: By using a multispectral image and ESRI shapefile (Point/ Line/ Polygon), + a data table will be generated for classification, regression or other processing. + The data table will be contained by band wise raster values and shapefile ids + (User Defined). + date_publication: '2023-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExtractTrainData + url_git: '' +extraDistr: + version: 1.10.0 + title: Additional Univariate and Multivariate Distributions + maintainer: Tymoteusz Wolodzko + description: |- + Density, distribution function, quantile function + and random generation for a number of univariate + and multivariate distributions. This package implements the + following distributions: Bernoulli, beta-binomial, beta-negative + binomial, beta prime, Bhattacharjee, Birnbaum-Saunders, + bivariate normal, bivariate Poisson, categorical, Dirichlet, + Dirichlet-multinomial, discrete gamma, discrete Laplace, + discrete normal, discrete uniform, discrete Weibull, Frechet, + gamma-Poisson, generalized extreme value, Gompertz, + generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t, + Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy, + Laplace, location-scale t, logarithmic, Lomax, multivariate + hypergeometric, multinomial, negative hypergeometric, + non-standard beta, normal mixture, Poisson mixture, Pareto, + power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam, + slash, triangular, truncated binomial, truncated normal, + truncated Poisson, Tukey lambda, Wald, zero-inflated binomial, + zero-inflated negative binomial, zero-inflated Poisson. + date_publication: '2023-11-30' + bug_reports: https://github.com/twolodzko/extraDistr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=extraDistr + url_git: https://github.com/twolodzko/extraDistr +extrafont: + version: '0.19' + title: Tools for Using Fonts + maintainer: Winston Chang + description: |- + Tools to using fonts other than the standard PostScript fonts. + This package makes it easy to use system TrueType fonts and with PDF or + PostScript output files, and with bitmap output files in Windows. extrafont + can also be used with fonts packaged specifically to be used with, such as + the fontcm package, which has Computer Modern PostScript fonts with math + symbols. + date_publication: '2023-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extrafont + url_git: https://github.com/wch/extrafont +extrafontdb: + version: '1.0' + title: Package for holding the database for the extrafont package + maintainer: Winston Chang + description: Package for holding the database for the extrafont package + date_publication: '2012-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extrafontdb + url_git: https://github.com/wch/extrafontdb +extrafrail: + version: '1.12' + title: |- + Estimation and Additional Tools for Alternative Shared Frailty + Models + maintainer: Diego Gallardo + description: |- + Provide estimation and data generation tools for some new multivariate frailty models. + This version includes the gamma, inverse Gaussian, weighted Lindley, Birnbaum-Saunders, + truncated normal, mixture of inverse Gaussian and mixture of Birnbaum-Saunders as the + distribution for the frailty terms. For the basal model, it is considered a parametric + approach based on the exponential, Weibull and the piecewise exponential distributions + as well as a semiparametric approach. + For details, see Gallardo and Bourguignon (2022) and + Gallardo et al. (2024) . + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extrafrail + url_git: '' +extraoperators: + version: 0.3.0 + title: Extra Binary Relational and Logical Operators + maintainer: Joshua F. Wiley + description: |- + Speed up common tasks, particularly logical or + relational comparisons and routine follow up tasks such as finding the + indices and subsetting. Inspired by mathematics, where something like: + 3 < x < 6 is a standard, elegant and clear way to assert that + x is both greater than 3 and less than 6 + (see for example ), + a chaining operator is implemented. The chaining operator, %c%, + allows multiple relational operations to be used in quotes on the right + hand side for the same object, on the left hand side. + The %e% operator allows something like set-builder notation + (see for example ) + to be used on the right hand side. + All operators have built in prefixes defined for all, subset, and which + to reduce the amount of code needed for common tasks, such as return those + values that are true. + date_publication: '2023-12-14' + bug_reports: https://github.com/JWiley/extraoperators/issues + url: https://joshuawiley.com/extraoperators/ + url_cran: https://CRAN.R-project.org/package=extraoperators + url_git: https://github.com/JWiley/extraoperators +extras: + version: 0.8.0 + title: Helper Functions for Bayesian Analyses + maintainer: Nicole Hill + description: |- + Functions to 'numericise' 'R' objects (coerce to numeric + objects), summarise 'MCMC' (Monte Carlo Markov Chain) samples and + calculate deviance residuals as well as 'R' translations of some + 'BUGS' (Bayesian Using Gibbs Sampling), 'JAGS' (Just Another Gibbs + Sampler), 'STAN' and 'TMB' (Template Model Builder) functions. + date_publication: '2025-01-13' + bug_reports: https://github.com/poissonconsulting/extras/issues + url: https://poissonconsulting.github.io/extras/ + url_cran: https://CRAN.R-project.org/package=extras + url_git: https://github.com/poissonconsulting/extras +extrasteps: + version: 0.1.0 + title: More Miscellaneous Steps for the 'recipes' Package + maintainer: Emil Hvitfeldt + description: |- + Contains additional miscellaneous steps for the 'recipes' package. + These steps are useful, but doesn't have a good home in other 'recipes' + packages or its extensions. + date_publication: '2024-10-03' + bug_reports: https://github.com/EmilHvitfeldt/extrasteps/issues + url: https://emilhvitfeldt.github.io/extrasteps/ + url_cran: https://CRAN.R-project.org/package=extrasteps + url_git: https://github.com/EmilHvitfeldt/extrasteps +extraterrestrial: + version: 0.1.0 + title: Astrobiology Equations Estimating Extraterrestrial Life + maintainer: Chester C. Deocaris + description: Finding life outside the planet Earth several is the ultimate goal + of an astrobiologist. Using known astronomical measurements and assumptions the + probability of extraterrestrial life existence could be estimated. Equations such + as the Drake equation (1961) as stated in the paper of Molina (2019) , + Seager (2013) + and Foucher et al, (2017) are included in the 'extraterrestrial' + package. + date_publication: '2020-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extraterrestrial + url_git: '' +extRatum: + version: 1.0.4 + title: Summary Statistics for Geospatial Features + maintainer: Nikos Patias + description: |- + Provides summary statistics of local geospatial features within a given geographic area. + It does so by calculating the area covered by a target geospatial feature (i.e. buildings, parks, lakes, etc.). + The geospatial features can be of any type of geospatial data, including point, polygon or line data. + date_publication: '2021-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extRatum + url_git: '' +extRC: + version: '1.2' + title: Extended RC Models for Contingency Tables + maintainer: Francesco Bartolucci + description: Maximum likelihood estimation of an extended class of row-column (RC) + association models for two-dimensional contingency tables, which are formulated + by a condition of reduced rank on a matrix of extended association parameters; + see Forcina (2019) . These parameters are defined by choosing + the logit type for the row and column variables among four different options and + a transformation derived from suitable divergence measures. + date_publication: '2020-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extRC + url_git: '' +ExtremalDep: + version: 0.0.4-4 + title: Extremal Dependence Models + maintainer: Simone Padoan + description: A set of procedures for parametric and non-parametric modelling of + the dependence structure of multivariate extreme-values is provided. The statistical + inference is performed with non-parametric estimators, likelihood-based estimators + and Bayesian techniques. It adapts the methodologies of Beranger and Padoan (2015) + , Marcon et al. (2016) , + Marcon et al. (2017) , Marcon et al. (2017) + and Beranger et al. (2021) . This package also + allows for the modelling of spatial extremes using flexible max-stable processes. + It provides simulation algorithms and fitting procedures relying on the Stephenson-Tawn + likelihood as per Beranger at al. (2021) . + date_publication: '2024-12-18' + bug_reports: https://github.com/borisberanger/ExtremalDep/issues + url: https://faculty.unibocconi.it/simonepadoan/ + url_cran: https://CRAN.R-project.org/package=ExtremalDep + url_git: '' +ExtremeBounds: + version: 0.1.7 + title: Extreme Bounds Analysis (EBA) + maintainer: Marek Hlavac + description: An implementation of Extreme Bounds Analysis (EBA), a global sensitivity + analysis that examines the robustness of determinants in regression models. The + package supports both Leamer's and Sala-i-Martin's versions of EBA, and allows + users to customize all aspects of the analysis. + date_publication: '2023-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExtremeBounds + url_git: '' +extremefit: + version: 1.0.2 + title: Estimation of Extreme Conditional Quantiles and Probabilities + maintainer: Kevin Jaunatre + description: |- + Extreme value theory, nonparametric kernel estimation, tail + conditional probabilities, extreme conditional quantile, adaptive estimation, + quantile regression, survival probabilities. + date_publication: '2019-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extremefit + url_git: '' +extremeIndex: + version: 0.0.3 + title: Forecast Verification for Extreme Events + maintainer: Maxime Taillardat + description: An index measuring the amount of information brought by forecasts for + extreme events, subject to calibration, is computed. This index is originally + designed for weather or climate forecasts, but it may be used in other forecasting + contexts. This is the implementation of the index in Taillardat et al. (2019) + . + date_publication: '2021-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extremeIndex + url_git: '' +extrememix: + version: 0.0.1 + title: Bayesian Estimation of Extreme Value Mixture Models + maintainer: Manuele Leonelli + description: 'Fits extreme value mixture models, which are models for tails not + requiring selection of a threshold, for continuous data. It includes functions + for model comparison, estimation of quantity of interest in extreme value analysis + and plotting. Reference: CN Behrens, HF Lopes, D Gamerman (2004) . + FF do Nascimento, D. Gamerman, HF Lopes .' + date_publication: '2024-10-04' + bug_reports: https://github.com/manueleleonelli/extrememix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=extrememix + url_git: https://github.com/manueleleonelli/extrememix +ExtremeRisks: + version: 0.0.4 + title: Extreme Risk Measures + maintainer: Simone Padoan + description: A set of procedures for estimating risks related to extreme events + via risk measures such as Expectile, Value-at-Risk, etc. is provided. Estimation + methods for univariate independent observations and temporal dependent observations + are available. The methodology is extended to the case of independent multidimensional + observations. The statistical inference is performed through parametric and non-parametric + estimators. Inferential procedures such as confidence intervals, confidence regions + and hypothesis testing are obtained by exploiting the asymptotic theory. Adapts + the methodologies derived in Padoan and Stupfler (2020) , Padoan + and Stupfler (2020) , Daouia et al. (2018) , + Drees (2000) , Drees (2003) , + de Haan and Ferreira (2006) , de Haan et al. (2016) + . + date_publication: '2020-08-27' + bug_reports: '' + url: mypage.unibocconi.it/simonepadoan/ + url_cran: https://CRAN.R-project.org/package=ExtremeRisks + url_git: '' +extRemes: + version: '2.2' + title: Extreme Value Analysis + maintainer: Eric Gilleland + description: 'General functions for performing extreme value analysis. In particular, + allows for inclusion of covariates into the parameters of the extreme-value distributions, + as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), + as well as Bayes. Inference methods include parametric normal approximation, + profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and + dependence checking (e.g., auto-tail dependence function plot, extremal index + estimation) is also included. For a tutorial, see Gilleland and Katz (2016) and for bootstrapping, please see Gilleland (2020) .' + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extRemes + url_git: '' +extremeStat: + version: 1.5.9 + title: Extreme Value Statistics and Quantile Estimation + maintainer: Berry Boessenkool + description: |- + Fit, plot and compare several (extreme value) distribution functions. + Compute (truncated) distribution quantile estimates and plot return periods on a linear scale. + On the fitting method, see Asquith (2011): Distributional Analysis with L-moment Statistics [...] ISBN 1463508417. + date_publication: '2024-01-13' + bug_reports: https://github.com/brry/extremeStat + url: '' + url_cran: https://CRAN.R-project.org/package=extremeStat + url_git: https://github.com/brry/extremeStat +extremevalues: + version: 2.4.1 + title: Univariate Outlier Detection + maintainer: Mark van der Loo + description: Detect outliers in one-dimensional data. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extremevalues + url_git: https://github.com/markvanderloo/extremevalues +extremis: + version: 1.2.1 + title: Statistics of Extremes + maintainer: Miguel de Carvalho + description: Conducts inference in statistical models for extreme values (de Carvalho + et al (2012), ; de Carvalho and Davison (2014), + ; Einmahl et al (2016), ). + date_publication: '2022-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extremis + url_git: '' +extremogram: + version: 1.0.2 + title: Estimation of Extreme Value Dependence for Time Series Data + maintainer: Nadezda Frolova + description: Estimation of the sample univariate, cross and return time extremograms. + The package can also adds empirical confidence bands to each of the extremogram + plots via a permutation procedure under the assumption that the data are independent. + Finally, the stationary bootstrap allows us to construct credible confidence bands + for the extremograms. + date_publication: '2016-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=extremogram + url_git: '' +ExtrPatt: + version: 0.1-4 + title: Spatial Dependencies and Indices for Extremes + maintainer: Svenja Szemkus + description: |- + An implementation of + 1) the tail pairwise dependence matrix (TPDM) as described in Jiang & Cooley (2020) + 2) the extremal pattern index (EPI) as described in Szemkus & Friederichs ('Spatial patterns and indices for heatwave and droughts over Europe using a decomposition of extremal dependency'; submitted to ASCMO 2023). + date_publication: '2023-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ExtrPatt + url_git: '' +exuber: + version: 1.0.2 + title: Econometric Analysis of Explosive Time Series + maintainer: Kostas Vasilopoulos + description: |- + Testing for and dating periods of explosive + dynamics (exuberance) in time series using the univariate and panel + recursive unit root tests proposed by Phillips et al. (2015) + and Pavlidis et al. (2016) + .The recursive least-squares + algorithm utilizes the matrix inversion lemma to avoid matrix + inversion which results in significant speed improvements. Simulation + of a variety of periodically-collapsing bubble processes. Details can be + found in Vasilopoulos et al. (2022) . + date_publication: '2023-03-22' + bug_reports: https://github.com/kvasilopoulos/exuber/issues + url: '' + url_cran: https://CRAN.R-project.org/package=exuber + url_git: https://github.com/kvasilopoulos/exuber +exvatools: + version: 0.9.0 + title: |- + Value Added in Exports and Other Input-Output Table Analysis + Tools + maintainer: Enrique Feas + description: |- + Analysis of trade in value added with international + input-output tables. Includes commands for easy data extraction, + matrix manipulation, decomposition of value added in gross exports and + calculation of value added indicators, with full geographical and + sector customization. Decomposition methods include Borin and Mancini + (2023) , Miroudot and Ye (2021) + , Wang et al. (2013) + and Koopman + et al. (2014) . + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=exvatools + url_git: '' +eye: + version: 1.2.1 + title: Analysis of Eye Data + maintainer: Tjebo Heeren + description: |- + There is no ophthalmic researcher who has not had headaches from + the handling of visual acuity entries. Different notations, untidy entries. + This shall now be a matter of the past. Eye makes it as easy as pie to work + with VA data - easy cleaning, easy conversion between + Snellen, logMAR, ETDRS letters, and qualitative visual acuity + shall never pester you again. The eye + package automates the pesky task to count number of patients and eyes, + and can help to clean data with easy re-coding for right and left eyes. + It also contains functions to help reshaping eye side specific variables + between wide and long format. Visual acuity conversion is based on + Schulze-Bonsel et al. (2006) , + Gregori et al. (2010) , + Beck et al. (2003) and + Bach (2007) . + date_publication: '2021-09-04' + bug_reports: https://github.com/tjebo/eye/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eye + url_git: https://github.com/tjebo/eye +eyedata: + version: 0.1.0 + title: Open Source Ophthalmic Data Sets Curated for R + maintainer: Tjebo Heeren + description: |- + Open source data allows for reproducible research and helps advance + our knowledge. The purpose of this package is to collate open source + ophthalmic data sets curated for direct use. This is real life data of + people with intravitreal injections with anti-vascular endothelial growth + factor (anti-VEGF), due to age-related macular degeneration or diabetic + macular edema. Associated publications of the data sets: + Fu et al. (2020) , + Moraes et al (2020) , + Fasler et al. (2019) , + Arpa et al. (2020) , + Kern et al. 2020, . + date_publication: '2020-12-09' + bug_reports: https://github.com/tjebo/eyedata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eyedata + url_git: https://github.com/tjebo/eyedata +eyelinker: + version: 0.2.1 + title: Import ASC Files from EyeLink Eye Trackers + maintainer: Austin Hurst + description: |- + Imports plain-text ASC data files from EyeLink eye trackers + into (relatively) tidy data frames for analysis and visualization. + date_publication: '2021-06-03' + bug_reports: https://github.com/a-hurst/eyelinker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eyelinker + url_git: https://github.com/a-hurst/eyelinker +eyelinkReader: + version: 1.0.3 + title: Import Gaze Data for EyeLink Eye Tracker + maintainer: Alexander Pastukhov + description: |- + Import gaze data from edf files generated by + the SR Research EyeLink eye tracker. Gaze data, + both recorded events and samples, is imported per trial. The package allows to extract + events of interest, such as saccades, blinks, etc. as well as + recorded variables and custom events (areas of interest, triggers) into separate tables. + The package requires EDF API library that can be obtained at . + date_publication: '2025-01-09' + bug_reports: https://github.com/alexander-pastukhov/eyelinkReader/issues + url: https://alexander-pastukhov.github.io/eyelinkReader/ + url_cran: https://CRAN.R-project.org/package=eyelinkReader + url_git: https://github.com/alexander-pastukhov/eyelinkReader/ +eyeRead: + version: 0.0.4 + title: Prepare/Analyse Eye Tracking Data for Reading + maintainer: San Verhavert + description: |- + Functions to prepare and analyse eye tracking data of reading + exercises. The functions allow some basic data preparations and code fixations + as first and second pass. First passes can be further devided into forward and + reading. The package further allows for aggregating fixation times per AOI or + per AOI and per type of pass (first forward, first rereading, second). These + methods are based on Hyönä, Lorch, and Rinck (2003) + and Hyönä, and Lorch (2004) . It is + also possible to convert between metric length and visual degrees. + date_publication: '2020-08-07' + bug_reports: https://github.com/SanVerhavert/eyeRead/issues + url: '' + url_cran: https://CRAN.R-project.org/package=eyeRead + url_git: https://github.com/SanVerhavert/eyeRead +eyetools: + version: 0.8.1 + title: Analyse Eye Data + maintainer: Tom Beesley + description: |- + Enables the automation of actions across the pipeline, including + initial steps of transforming binocular data and gap repair to event-based + processing such as fixations, saccades, and entry/duration in Areas of + Interest (AOIs). It also offers visualisation of eye movement and AOI + entries. These tools take relatively raw (trial, time, x, and y form) data + and can be used to return fixations, saccades, and AOI entries and time spent + in AOIs. As the tools rely on this basic data format, the functions can work + with data from any eye tracking device. Implements fixation and saccade + detection using methods proposed by Salvucci and Goldberg (2000) + . + date_publication: '2024-12-19' + bug_reports: https://github.com/tombeesley/eyetools/issues + url: https://tombeesley.github.io/eyetools/ + url_cran: https://CRAN.R-project.org/package=eyetools + url_git: '' +eyetrackingR: + version: 0.2.1 + title: Eye-Tracking Data Analysis + maintainer: Samuel Forbes + description: |- + Addresses tasks along the pipeline from raw + data to analysis and visualization for eye-tracking data. Offers several + popular types of analyses, including linear and growth curve time analyses, + onset-contingent reaction time analyses, as well as several non-parametric + bootstrapping approaches. For references to the approach see Mirman, + Dixon & Magnuson (2008) , and + Barr (2008) . + date_publication: '2023-09-15' + bug_reports: https://github.com/samhforbes/eyetrackingR/issues + url: http://samforbes.me/eyetrackingR/ + url_cran: https://CRAN.R-project.org/package=eyetrackingR + url_git: '' +eyeTrackR: + version: 1.0.1 + title: Organising and Analysing Eye-Tracking Data + maintainer: Hayward Godwin + description: |- + A set of functions for organising and analysing datasets from + experiments run using 'Eyelink' eye-trackers. Organising functions help + to clean and prepare eye-tracking datasets for analysis, and mark up + key events such as display changes and responses made by participants. + Analysing functions help to create means for a wide range of standard + measures (such as 'mean fixation durations'), which can then be fed into + the appropriate statistical analyses and graphing packages as necessary. + date_publication: '2020-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=eyeTrackR + url_git: '' +ez: + version: 4.4-0 + title: Easy Analysis and Visualization of Factorial Experiments + maintainer: Michael A. Lawrence + description: |- + Facilitates easy analysis of factorial experiments, including + purely within-Ss designs (a.k.a. "repeated measures"), purely between-Ss + designs, and mixed within-and-between-Ss designs. The functions in this package + aim to provide simple, intuitive and consistent specification of data analysis + and visualization. Visualization functions also include design visualization for + pre-analysis data auditing, and correlation matrix visualization. Finally, this + package includes functions for non-parametric analysis, including permutation + tests and bootstrap resampling. The bootstrap function obtains predictions + either by cell means or by more advanced/powerful mixed effects models, yielding + predictions and confidence intervals that may be easily visualized at any level + of the experiment's design. + date_publication: '2016-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ez + url_git: http://github.com/mike-lawrence/ez +ez.combat: + version: 1.0.0 + title: Easy ComBat Harmonization + maintainer: Timothy Koscik + description: |- + A dataframe-friendly implementation of ComBat Harmonization which uses an empirical Bayesian framework to remove batch effects. + Johnson WE & Li C (2007) "Adjusting batch effects in microarray expression data using empirical Bayes methods." + Fortin J-P, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, Adams P, Cooper C, Fava M, McGrath PJ, McInnes M, Phillips ML, Trivedi MH, Weissman MM, & Shinohara RT (2017) "Harmonization of cortical thickness measurements across scanners and sites." + Fortin J-P, Parker D, Tun B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) "Harmonization of multi-site diffusion tensor imaging data." + date_publication: '2021-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ez.combat + url_git: '' +ezcox: + version: 1.0.4 + title: Easily Process a Batch of Cox Models + maintainer: Shixiang Wang + description: |- + A tool to operate a batch of univariate or multivariate Cox + models and return tidy result. + date_publication: '2023-05-08' + bug_reports: https://github.com/ShixiangWang/ezcox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ezcox + url_git: https://github.com/ShixiangWang/ezcox +ezCutoffs: + version: 1.0.1 + title: Fit Measure Cutoffs in SEM + maintainer: Bjarne Schmalbach + description: Calculate cutoff values for model fit measures used in structural equation + modeling (SEM) by simulating and testing data sets (cf. Hu & Bentler, 1999 ) + with the same parameters (population model, number of observations, etc.) as the + model under consideration. + date_publication: '2019-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ezCutoffs + url_git: '' +ezec: + version: 1.0.1 + title: Easy Interface to Effective Concentration Calculations + maintainer: Zhian N. Kamvar + description: |- + Because fungicide resistance is an important phenotypic trait for + fungi and oomycetes, it is necessary to have a standardized method of + statistically analyzing the Effective Concentration (EC) values. This + package is designed for those who are not terribly familiar with R to be + able to analyze and plot an entire set of isolates using the 'drc' package. + date_publication: '2016-12-05' + bug_reports: https://github.com/grunwaldlab/ezec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ezec + url_git: https://github.com/grunwaldlab/ezec +ezECM: + version: 1.0.0 + title: |- + Event Categorization Matrix Classification for Nuclear + Detonations + maintainer: Scott Koermer + description: Implementation of an Event Categorization Matrix (ECM) detonation detection + model and a Bayesian variant. Functions are provided for importing and exporting + data, fitting models, and applying decision criteria for categorizing new events. + This package implements methods described in the paper "Bayesian Event Categorization + Matrix Approach for Nuclear Detonations" Koermer, Carmichael, and Williams (2024) + available on arXiv at . + date_publication: '2024-10-17' + bug_reports: https://github.com/lanl/ezECM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ezECM + url_git: https://github.com/lanl/ezECM +ezEDA: + version: 0.1.1 + title: Task Oriented Interface for Exploratory Data Analysis + maintainer: Viswa Viswanathan + description: |- + Enables users to create visualizations using functions + based on the data analysis task rather than on plotting mechanics. It hides + the details of the individual 'ggplot2' function calls and + allows the user to focus on the end goal. Useful for quick preliminary explorations. + Provides functions for common exploration patterns. Some of the ideas in this + package are motivated by Fox (2015, ISBN:1938377052). + date_publication: '2021-06-29' + bug_reports: https://github.com/kviswana/ezEDA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ezEDA + url_git: https://github.com/kviswana/ezEDA +EzGP: + version: 0.1.0 + title: |- + Easy-to-Interpret Gaussian Process Models for Computer + Experiments + maintainer: Jiayi Li + description: |- + Fit model for datasets with easy-to-interpret Gaussian process modeling, predict responses for new inputs. + The input variables of the datasets can be quantitative, qualitative/categorical or mixed. + The output variable of the datasets is a scalar (quantitative). + The optimization of the likelihood function can be chosen by the users (see the documentation of EzGP_fit()). + The modeling method is published in "EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments with Both Quantitative and Qualitative Factors" + by Qian Xiao, Abhyuday Mandal, C. Devon Lin, and Xinwei Deng (2022) . + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EzGP + url_git: '' +ezknitr: + version: 0.6.3 + title: Avoid the Typical Working Directory Pain When Using 'knitr' + maintainer: Dean Attali + description: |- + An extension of 'knitr' that adds flexibility in several + ways. One common source of frustration with 'knitr' is that it assumes + the directory where the source file lives should be the working directory, + which is often not true. 'ezknitr' addresses this problem by giving you + complete control over where all the inputs and outputs are, and adds several + other convenient features to make rendering markdown/HTML documents easier. + date_publication: '2023-08-20' + bug_reports: https://github.com/ropensci/ezknitr/issues + url: https://docs.ropensci.org/ezknitr/ + url_cran: https://CRAN.R-project.org/package=ezknitr + url_git: https://github.com/ropensci/ezknitr +ezmmek: + version: 0.2.4 + title: Easy Michaelis-Menten Enzyme Kinetics + maintainer: Christopher Cook + description: |- + Serves as a platform for published fluorometric enzyme assay + protocols. 'ezmmek' calibrates, calculates, and plots enzyme activities as they + relate to the transformation of synthetic substrates. At present, 'ezmmek' + implements two common protocols found in the literature, and is modular to accommodate + additional protocols. Here, these protocols are referred to as the In-Sample + Calibration (Hoppe, 1983; ) and In-Buffer Calibration (German et al., 2011; ). + protocols. By containing multiple protocols, 'ezmmek' aims to stimulate + discussion about how to best optimize fluorometric enzyme assays. A standardized + approach would make studies more comparable and reproducible. + date_publication: '2020-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ezmmek + url_git: '' +ezplot: + version: 0.7.13 + title: Functions for Common Chart Types + maintainer: Wojtek Kostelecki + description: |- + Wrapper for the 'ggplot2' package that creates a variety of common + charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce + typing. + date_publication: '2024-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ezplot + url_git: '' +ezr: + version: 0.1.5 + title: |- + Easy Use of R via Shiny App for Basic Analyses of Experimental + Data + maintainer: Jin Kim + description: |- + Runs a Shiny App in the local machine for basic + statistical and graphical analyses. The point-and-click interface + of Shiny App enables obtaining the same analysis outputs (e.g., plots and + tables) more quickly, as compared with typing the required code in R, + especially for users without much experience or expertise with coding. + Examples of possible analyses include tabulating descriptive + statistics for a variable, creating histograms by experimental groups, + and creating a scatter plot and calculating the correlation between + two variables. + date_publication: '2020-11-25' + bug_reports: https://github.com/jinkim3/ezr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ezr + url_git: https://github.com/jinkim3/ezr +EZtune: + version: 3.1.1 + title: |- + Tunes AdaBoost, Elastic Net, Support Vector Machines, and + Gradient Boosting Machines + maintainer: Jill Lundell + description: |- + Contains two functions that are intended to make + tuning supervised learning methods easy. The eztune function uses a + genetic algorithm or Hooke-Jeeves optimizer to find the best + set of tuning parameters. The user can choose the optimizer, the + learning method, and if optimization will be based on accuracy + obtained through validation error, cross validation, or resubstitution. + The function eztune.cv will compute a cross validated error rate. The purpose + of eztune_cv is to provide a cross validated accuracy or MSE when + resubstitution or validation data are used for optimization because + error measures from both approaches can be misleading. + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=EZtune + url_git: '' +f1dataR: + version: 2.0.0 + title: Access Formula 1 Data + maintainer: Santiago Casanova + description: Obtain Formula 1 data via the 'Jolpica API' and + the unofficial API via the 'fastf1' + 'Python' library . + date_publication: '2025-03-01' + bug_reports: https://github.com/SCasanova/f1dataR/issues + url: https://scasanova.github.io/f1dataR/ + url_cran: https://CRAN.R-project.org/package=f1dataR + url_git: https://github.com/SCasanova/f1dataR +FaaSr: + version: 1.4.3 + title: FaaS (Function as a Service) Package + maintainer: Figueiredo Renato + description: |- + Allows users to create and deploy the workflow with multiple functions + in Function-as-a-Service (FaaS) cloud computing platforms. + The 'FaaSr' package makes it simpler for R developers to use FaaS platforms by providing the following functionality: + 1) Parsing and validating a JSON-based payload compliant to 'FaaSr' schema supporting multiple FaaS platforms + 2) Invoking user functions written in R in a Docker container (derived from rocker), using a list generated from + the parser as argument + 3) Downloading/uploading of files from/to S3 buckets using simple primitives + 4) Logging to files in S3 buckets + 5) Triggering downstream actions supporting multiple FaaS platforms + 6) Generating FaaS-specific API calls to simplify the registering of a user's workflow with a FaaS platform + Supported FaaS platforms: + Apache OpenWhisk + GitHub Actions + Amazon Web Services (AWS) Lambda + Supported cloud data storage for persistent storage: + Amazon Web Services (AWS) Simple Storage Service (S3) . + date_publication: '2024-12-19' + bug_reports: https://github.com/FaaSr/FaaSr-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FaaSr + url_git: https://github.com/FaaSr/FaaSr-package +fabCI: + version: '0.2' + title: FAB Confidence Intervals + maintainer: Peter Hoff + description: |- + Frequentist assisted by Bayes (FAB) confidence interval + construction. See 'Adaptive multigroup confidence intervals with constant + coverage' by Yu and Hoff and + 'Exact adaptive confidence intervals for linear regression coefficients' + by Hoff and Yu . + date_publication: '2021-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fabCI + url_git: '' +FABInference: + version: '0.1' + title: FAB p-Values and Confidence Intervals + maintainer: Peter Hoff + description: |- + Frequentist assisted by Bayes (FAB) p-values and confidence + interval construction. See + Hoff (2019) + "Smaller p-values via indirect information", + Hoff and Yu (2019) + "Exact adaptive confidence intervals for linear regression coefficients", and + Yu and Hoff (2018) + "Adaptive multigroup confidence intervals with constant coverage". + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FABInference + url_git: '' +fabisearch: + version: 0.0.4.5 + title: Change Point Detection in High-Dimensional Time Series Networks + maintainer: Martin Ondrus + description: Implementation of the Factorized Binary Search (FaBiSearch) methodology + for the estimation of the number and the location of multiple change points in + the network (or clustering) structure of multivariate high-dimensional time series. + The method is motivated by the detection of change points in functional connectivity + networks for functional magnetic resonance imaging (fMRI) data. FaBiSearch uses + non-negative matrix factorization (NMF), an unsupervised dimension reduction technique, + and a new binary search algorithm to identify multiple change points. It requires + minimal assumptions. Lastly, we provide interactive, 3-dimensional, brain-specific + network visualization capability in a flexible, stand-alone function. This function + can be conveniently used with any node coordinate atlas, and nodes can be color + coded according to community membership, if applicable. The output is an elegantly + displayed network laid over a cortical surface, which can be rotated in the 3-dimensional + space. The main routines of the package are detect.cps(), for multiple change + point detection, est.net(), for estimating a network between stationary multivariate + time series, net.3dplot(), for plotting the estimated functional connectivity + networks, and opt.rank(), for finding the optimal rank in NMF for a given data + set. The functions have been extensively tested on simulated multivariate high-dimensional + time series data and fMRI data. For details on the FaBiSearch methodology, please + see Ondrus et al. (2021) . For a more detailed explanation and + applied examples of the fabisearch package, please see Ondrus and Cribben (2022), + preprint. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fabisearch + url_git: https://github.com/mondrus96/FaBiSearch +fable: + version: 0.4.1 + title: Forecasting Models for Tidy Time Series + maintainer: Mitchell O'Hara-Wild + description: |- + Provides a collection of commonly used univariate and multivariate + time series forecasting models including automatically selected exponential + smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. + These models work within the 'fable' framework provided by the 'fabletools' + package, which provides the tools to evaluate, visualise, and combine models + in a workflow consistent with the tidyverse. + date_publication: '2024-11-05' + bug_reports: https://github.com/tidyverts/fable/issues + url: https://fable.tidyverts.org + url_cran: https://CRAN.R-project.org/package=fable + url_git: https://github.com/tidyverts/fable +fable.ata: + version: 0.0.6 + title: '''ATAforecasting'' Modelling Interface for ''fable'' Framework' + maintainer: Ali Sabri Taylan + description: |- + Allows ATA (Automatic Time series analysis using the Ata method) models from the 'ATAforecasting' package to be used in a tidy workflow with the modeling interface of + 'fabletools'. This extends 'ATAforecasting' to provide enhanced model specification and management, performance evaluation methods, and + model combination tools. The Ata method (Yapar et al. (2019) ), an alternative to exponential smoothing (described in Yapar (2016) + , Yapar et al. (2017) ), is a new univariate time series forecasting method which provides + innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods. + Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting. + It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal). + date_publication: '2023-06-19' + bug_reports: https://github.com/alsabtay/fable.ata/issues + url: https://alsabtay.github.io/fable.ata/ + url_cran: https://CRAN.R-project.org/package=fable.ata + url_git: '' +fable.prophet: + version: 0.1.0 + title: Prophet Modelling Interface for 'fable' + maintainer: Mitchell O'Hara-Wild + description: Allows prophet models from the 'prophet' package to be used in a tidy + workflow with the modelling interface of 'fabletools'. This extends 'prophet' + to provide enhanced model specification and management, performance evaluation + methods, and model combination tools. + date_publication: '2020-08-20' + bug_reports: https://github.com/mitchelloharawild/fable.prophet/issues + url: https://pkg.mitchelloharawild.com/fable.prophet/ + url_cran: https://CRAN.R-project.org/package=fable.prophet + url_git: '' +fableCount: + version: 0.1.0 + title: |- + INGARCH and GLARMA Models for Count Time Series in Fable + Framework + maintainer: Gustavo Almeida + description: Provides a tidy R interface for count time series analysis. It includes + implementation of the INGARCH (Integer Generalized Autoregressive Conditional + Heteroskedasticity) model from the 'tscount' package and the GLARMA (Generalized + Linear Autoregressive Moving Averages) model from the 'glarma' package. Additionally, + it offers automated parameter selection algorithms based on the minimization of + a penalized likelihood. + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fableCount + url_git: '' +fabletools: + version: 0.5.0 + title: Core Tools for Packages in the 'fable' Framework + maintainer: Mitchell O'Hara-Wild + description: |- + Provides tools, helpers and data structures for + developing models and time series functions for 'fable' and extension + packages. These tools support a consistent and tidy interface for time + series modelling and analysis. + date_publication: '2024-09-17' + bug_reports: https://github.com/tidyverts/fabletools/issues + url: https://fabletools.tidyverts.org/ + url_cran: https://CRAN.R-project.org/package=fabletools + url_git: https://github.com/tidyverts/fabletools +fabMix: + version: '5.1' + title: |- + Overfitting Bayesian Mixtures of Factor Analyzers with + Parsimonious Covariance and Unknown Number of Components + maintainer: Panagiotis Papastamoulis + description: 'Model-based clustering of multivariate continuous data using Bayesian + mixtures of factor analyzers (Papastamoulis (2019) + (2018) ). The number of clusters is estimated + using overfitting mixture models (Rousseau and Mengersen (2011) ): + suitable prior assumptions ensure that asymptotically the extra components will + have zero posterior weight, therefore, the inference is based on the ``alive'''' + components. A Gibbs sampler is implemented in order to (approximately) sample + from the posterior distribution of the overfitting mixture. A prior parallel tempering + scheme is also available, which allows to run multiple parallel chains with different + prior distributions on the mixture weights. These chains run in parallel and can + swap states using a Metropolis-Hastings move. Eight different parameterizations + give rise to parsimonious representations of the covariance per cluster (following + Mc Nicholas and Murphy (2008) ). The model parameterization + and number of factors is selected according to the Bayesian Information Criterion. + Identifiability issues related to label switching are dealt by post-processing + the simulated output with the Equivalence Classes Representatives algorithm (Papastamoulis + and Iliopoulos (2010) , Papastamoulis (2016) ).' + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fabMix + url_git: https://github.com/mqbssppe/overfittingFABMix +fabPrediction: + version: 1.0.4 + title: |- + Compute FAB (Frequentist and Bayes) Conformal Prediction + Intervals + maintainer: Elizabeth Bersson + description: |- + Computes and plots prediction intervals for numerical + data or prediction sets for categorical data using prior information. + Empirical Bayes procedures to estimate the prior information from + multi-group data are included. See, e.g.,Bersson and Hoff (2022) + "Optimal Conformal Prediction for Small Areas". + date_publication: '2024-03-26' + bug_reports: https://github.com/betsybersson/fabPrediction/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fabPrediction + url_git: https://github.com/betsybersson/fabPrediction +fabR: + version: 2.1.0 + title: Wrapper Functions Collection Used in Data Pipelines + maintainer: Guillaume Fabre + description: |- + The goal of this package is to provide wrapper functions in the + data cleaning and cleansing processes. These function helps in messages and + interaction with the user, keep track of information in pipelines, help in + the wrangling, munging, assessment and visualization of data frame-like + material. + date_publication: '2024-04-19' + bug_reports: https://github.com/GuiFabre/fabR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fabR + url_git: https://github.com/GuiFabre/fabR +fabricatr: + version: 1.0.2 + title: Imagine Your Data Before You Collect It + maintainer: Graeme Blair + description: |- + Helps you imagine your data before you collect it. Hierarchical data structures + and correlated data can be easily simulated, either from random number generators or + by resampling from existing data sources. This package is faster with 'data.table' and + 'mvnfast' installed. + date_publication: '2024-01-16' + bug_reports: https://github.com/DeclareDesign/fabricatr/issues + url: https://declaredesign.org/r/fabricatr/ + url_cran: https://CRAN.R-project.org/package=fabricatr + url_git: https://github.com/DeclareDesign/fabricatr +fabricerin: + version: 0.1.2 + title: Create Easily Canvas in 'shiny' and 'RMarkdown' Documents + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to implement easily canvas elements within a 'shiny' app or an 'RMarkdown' document. + The user can create shapes, images and text elements within the canvas which can also be used as a drawing tool for taking notes. + The package relies on the 'fabricjs' 'JavaScript' library. See . + date_publication: '2020-08-14' + bug_reports: https://github.com/feddelegrand7/fabricerin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fabricerin + url_git: https://github.com/feddelegrand7/fabricerin +face: + version: 0.1-7 + title: Fast Covariance Estimation for Sparse Functional Data + maintainer: Cai Li + description: |- + We implement the Fast Covariance Estimation for + Sparse Functional Data paper published in Statistics and Computing . + date_publication: '2022-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=face + url_git: '' +facebookadsR: + version: 0.1.0 + title: Access to Facebook Ads via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: |- + Collect marketing data from facebook Ads using the 'Windsor.ai' API . + Use four spaces when indenting paragraphs within the Description. + date_publication: '2022-10-17' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=facebookadsR + url_git: '' +facebookleadsR: + version: 0.1.0 + title: Get Facebook Leads Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Facebook Leads + Ads using the 'Windsor.ai' API . + date_publication: '2022-11-23' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=facebookleadsR + url_git: '' +facebookorganicR: + version: 0.1.0 + title: Get Data from 'Facebook Organic' via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from 'Facebook Organic' + using the 'Windsor.ai' API . + date_publication: '2022-12-08' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=facebookorganicR + url_git: '' +facerec: + version: 0.1.0 + title: An Interface for Face Recognition + maintainer: Carsten Schwemmer + description: Provides an interface to the 'Kairos' Face Recognition API . + The API detects faces in images and returns estimates for demographics like gender, + ethnicity and age. + date_publication: '2018-05-14' + bug_reports: https://github.com/methodds/facerec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=facerec + url_git: https://github.com/methodds/facerec +facmodCS: + version: '1.0' + title: Cross-Section Factor Models + maintainer: Mido Shammaa + description: |- + Linear cross-section factor model fitting with least-squares + and robust fitting the 'lmrobdetMM()' function from 'RobStatTM'; related + volatility, Value at Risk and Expected Shortfall risk and performance + attribution (factor-contributed vs idiosyncratic returns); + tabular displays of risk and performance reports; + factor model Monte Carlo. The package authors would like to thank Chicago + Research on Security Prices,LLC for the cross-section of about 300 + CRSP stocks data (in the data.table object 'stocksCRSP', and S&P GLOBAL MARKET + INTELLIGENCE for contributing 14 factor scores (a.k.a "alpha factors".and + "factor exposures") fundamental data on the 300 companies in the data.table + object 'factorSPGMI'. The 'stocksCRSP' and 'factorsSPGMI' data are not covered by + the GPL-2 license, are not provided as open source of any kind, and they are + not to be redistributed in any form. + date_publication: '2023-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=facmodCS + url_git: https://github.com/robustport/facmodCS +facmodTS: + version: '1.0' + title: Time Series Factor Models for Asset Returns + maintainer: Doug Martin + description: |- + Supports teaching methods of estimating and testing time series + factor models for use in robust portfolio construction and analysis. Unique + in providing not only classical least squares, but also modern robust model + fitting methods which are not much influenced by outliers. Includes + returns and risk decompositions, with user choice of standard deviation, + value-at-risk, and expected shortfall risk measures. "Robust Statistics + Theory and Methods (with R)", R. A. Maronna, R. D. Martin, V. J. Yohai, + M. Salibian-Barrera (2019) . + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=facmodTS + url_git: https://github.com/robustport/facmodTS +FACT: + version: 0.1.1 + title: Feature Attributions for ClusTering + maintainer: Henri Funk + description: |- + We present 'FACT' (Feature Attributions for ClusTering), a + framework for unsupervised interpretation methods that can be used with an + arbitrary clustering algorithm. The package is capable of re-assigning instances to + clusters (algorithm agnostic), preserves the integrity of the data and does + not introduce additional models. 'FACT' is inspired by the principles of + model-agnostic interpretation in supervised learning. Therefore, some of the + methods presented are based on 'iml', a R Package for Interpretable Machine + Learning by Christoph Molnar, Giuseppe Casalicchio, and Bernd Bischl (2018) + . + date_publication: '2024-03-25' + bug_reports: https://github.com/henrifnk/FACT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FACT + url_git: '' +factiv: + version: 0.1.0 + title: Instrumental Variables Estimation for 2^k Factorial Experiments + maintainer: Matthew Blackwell + description: Implements instrumental variable estimators for 2^K factorial experiments + with noncompliance. + date_publication: '2021-05-21' + bug_reports: https://github.com/mattblackwell/factiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=factiv + url_git: https://github.com/mattblackwell/factiv +FACTMLE: + version: '1.1' + title: Maximum Likelihood Factor Analysis + maintainer: Koulik Khamaru + description: Perform Maximum Likelihood Factor analysis on a covariance matrix or + data matrix. + date_publication: '2015-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FACTMLE + url_git: '' +FactoClass: + version: 1.2.9 + title: Combination of Factorial Methods and Cluster Analysis + maintainer: Campo Elias Pardo + description: |- + Some functions of 'ade4' and 'stats' are combined in order to obtain + a partition of the rows of a data table, with columns representing + variables of scales: quantitative, qualitative or frequency. + First, a principal axes method is performed and then, a combination + of Ward agglomerative hierarchical classification and K-means is + performed, using some of the first coordinates obtained from the + previous principal axes method. + In order to permit different weights of the elements to be clustered, + the function 'kmeansW', programmed in C++, is included. + It is a modification of 'kmeans'. Some graphical functions include + the option: 'gg=FALSE'. When 'gg=TRUE', they use the 'ggplot2' + and 'ggrepel' packages to avoid the super-position of the labels. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FactoClass + url_git: '' +factoextra: + version: 1.0.7 + title: Extract and Visualize the Results of Multivariate Data Analyses + maintainer: Alboukadel Kassambara + description: |- + Provides some easy-to-use functions to extract and visualize the + output of multivariate data analyses, including 'PCA' (Principal Component + Analysis), 'CA' (Correspondence Analysis), 'MCA' (Multiple Correspondence + Analysis), 'FAMD' (Factor Analysis of Mixed Data), 'MFA' (Multiple Factor Analysis) and 'HMFA' (Hierarchical Multiple + Factor Analysis) functions from different R packages. It contains also functions + for simplifying some clustering analysis steps and provides 'ggplot2' - based + elegant data visualization. + date_publication: '2020-04-01' + bug_reports: https://github.com/kassambara/factoextra/issues + url: http://www.sthda.com/english/rpkgs/factoextra + url_cran: https://CRAN.R-project.org/package=factoextra + url_git: '' +FactoInvestigate: + version: '1.9' + title: Automatic Description of Factorial Analysis + maintainer: Francois Husson + description: Brings a set of tools to help and automatically realise the description + of principal component analyses (from 'FactoMineR' functions). Detection of existing + outliers, identification of the informative components, graphical views and dimensions + description are performed threw dedicated functions. The Investigate() function + performs all these functions in one, and returns the result as a report document + (Word, PDF or HTML). + date_publication: '2023-11-27' + bug_reports: '' + url: http://factominer.free.fr/reporting/ + url_cran: https://CRAN.R-project.org/package=FactoInvestigate + url_git: '' +FactoMineR: + version: '2.11' + title: Multivariate Exploratory Data Analysis and Data Mining + maintainer: Francois Husson + description: 'Exploratory data analysis methods to summarize, visualize and describe + datasets. The main principal component methods are available, those with the largest + potential in terms of applications: principal component analysis (PCA) when variables + are quantitative, correspondence analysis (CA) and multiple correspondence analysis + (MCA) when variables are categorical, Multiple Factor Analysis when variables + are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. + Le and J. Pages (2017).' + date_publication: '2024-04-20' + bug_reports: https://github.com/husson/FactoMineR + url: http://factominer.free.fr + url_cran: https://CRAN.R-project.org/package=FactoMineR + url_git: '' +factoptd: + version: 1.0.3 + title: |- + Factorial Optimal Designs for Two-Colour cDNA Microarray + Experiments + maintainer: Dibaba Bayisa Gemechu + description: Computes factorial A-, D- and E-optimal designs for two-colour cDNA + microarray experiments. + date_publication: '2018-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factoptd + url_git: '' +factor.switching: + version: '1.4' + title: Post-Processing MCMC Outputs of Bayesian Factor Analytic Models + maintainer: Panagiotis Papastamoulis + description: A well known identifiability issue in factor analytic models is the + invariance with respect to orthogonal transformations. This problem burdens the + inference under a Bayesian setup, where Markov chain Monte Carlo (MCMC) methods + are used to generate samples from the posterior distribution. The package applies + a series of rotation, sign and permutation transformations (Papastamoulis and + Ntzoufras (2022) ) into raw MCMC samples of factor + loadings, which are provided by the user. The post-processed output is identifiable + and can be used for MCMC inference on any parametric function of factor loadings. + Comparison of multiple MCMC chains is also possible. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factor.switching + url_git: '' +factor256: + version: 0.1.0 + title: Use Raw Vectors to Minimize Memory Consumption of Factors + maintainer: Hugh Parsonage + description: |- + Uses raw vectors to minimize memory consumption of categorical + variables with fewer than 256 unique values. Useful for analysis of large + datasets involving variables such as age, years, states, countries, or + education levels. + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factor256 + url_git: '' +FactorAssumptions: + version: 2.0.1 + title: Set of Assumptions for Factor and Principal Component Analysis + maintainer: Jose Storopoli + description: |- + Tests for Kaiser-Meyer-Olkin (KMO) and + communalities in a dataset. It provides a final sample by removing + variables in a iterable manner while keeping account of the variables + that were removed in each step. It follows the best practices and assumptions according to + Hair, Black, Babin & Anderson (2018, ISBN:9781473756540). + date_publication: '2022-03-08' + bug_reports: https://github.com/storopoli/FactorAssumptions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FactorAssumptions + url_git: https://github.com/storopoli/FactorAssumptions +FactorCopula: + version: 0.9.3 + title: Factor, Bi-Factor, Second-Order and Factor Tree Copula Models + maintainer: Aristidis K. Nikoloulopoulos + description: Estimation, model selection and goodness-of-fit of (1) factor copula + models for mixed continuous and discrete data in Kadhem and Nikoloulopoulos (2021) + ; (2) bi-factor and second-order copula models for item + response data in Kadhem and Nikoloulopoulos (2023) ; + (3) factor tree copula models for item response data in Kadhem and Nikoloulopoulos + (2022) . + date_publication: '2023-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FactorCopula + url_git: '' +FactorHet: + version: 1.0.0 + title: |- + Estimate Heterogeneous Effects in Factorial Experiments Using + Grouping and Sparsity + maintainer: Max Goplerud + description: |- + Estimates heterogeneous effects in factorial (and conjoint) + models. The methodology employs a Bayesian finite mixture of + regularized logistic regressions, where moderators can affect each + observation's probability of group membership and a sparsity-inducing + prior fuses together levels of each factor while respecting + ANOVA-style sum-to-zero constraints. Goplerud, Imai, and Pashley + (2024) provide further details. + date_publication: '2025-01-13' + bug_reports: https://github.com/mgoplerud/FactorHet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FactorHet + url_git: https://github.com/mgoplerud/FactorHet +factorial2x2: + version: 0.2.0 + title: Design and Analysis of a 2x2 Factorial Trial + maintainer: Eric Leifer + description: |- + Used for the design and analysis of a 2x2 factorial trial for + a time-to-event endpoint. It performs power calculations and significance + testing as well as providing estimates of the relevant hazard ratios and the + corresponding 95% confidence intervals. Important reference papers include + Slud EV. (1994) + Lin DY, Gong J, Gallo P, Bunn PH, Couper D. (2016) + Leifer ES, Troendle JF, Kolecki A, Follmann DA. (2020) + . + date_publication: '2020-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factorial2x2 + url_git: '' +factormodel: + version: '1.0' + title: Factor Model Estimation Using Proxy Variables + maintainer: Yujung Hwang + description: Functions to estimate a factor model using discrete and continuous + proxy variables. The function 'dproxyme' estimates a factor model of discrete + proxy variables using an EM algorithm (Dempster, Laird, Rubin (1977) ; + Hu (2008) ; Hu(2017) + ). The function 'cproxyme' estimates a linear factor model (Cunha, Heckman, and + Schennach (2010) ). + date_publication: '2021-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factormodel + url_git: '' +factorplot: + version: 1.2.3 + title: Presenting Pairwise Comparisons + maintainer: Dave Armstrong + description: The tools herein calculate, print, summarize and plot pairwise differences + that result from generalized linear models, general linear hypothesis tests and + multinomial logistic regression models. For more information, see Armstrong (2013) + . + date_publication: '2024-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factorplot + url_git: '' +factorstochvol: + version: 1.1.0 + title: |- + Bayesian Estimation of (Sparse) Latent Factor Stochastic + Volatility Models + maintainer: Gregor Kastner + description: Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation + of latent factor stochastic volatility models with interweaving . + Sparsity can be achieved through the usage of Normal-Gamma priors on the factor + loading matrix . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factorstochvol + url_git: '' +factory: + version: 0.1.0 + title: Build Function Factories + maintainer: Jon Harmon + description: |- + Function factories are functions that make functions. They can be + confusing to construct. Straightforward techniques can produce functions + that are fragile or hard to understand. While more robust techniques exist + to construct function factories, those techniques can be confusing. This + package is designed to make it easier to construct function factories. + date_publication: '2019-08-21' + bug_reports: https://github.com/jonthegeek/factory/issues + url: '' + url_cran: https://CRAN.R-project.org/package=factory + url_git: https://github.com/jonthegeek/factory +Factoshiny: + version: '2.7' + title: |- + Perform Factorial Analysis from 'FactoMineR' with a Shiny + Application + maintainer: Francois Husson + description: Perform factorial analysis with a menu and draw graphs interactively + thanks to 'FactoMineR' and a Shiny application. + date_publication: '2025-01-15' + bug_reports: '' + url: http://factominer.free.fr/graphs/factoshiny.html + url_cran: https://CRAN.R-project.org/package=Factoshiny + url_git: '' +factReg: + version: 1.0.0 + title: |- + Multi-Environment Genomic Prediction with Penalized Factorial + Regression + maintainer: Bart-Jan van Rossum + description: |- + Multi-environment genomic prediction for training and test + environments using penalized factorial regression. Predictions are made + using genotype-specific environmental sensitivities as in Millet et al. + (2019) . + date_publication: '2023-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=factReg + url_git: '' +factset.analyticsapi.engines: + version: 3.0.1 + title: '''FactSet'' Engines API Client' + maintainer: Akshay Sheth + description: |- + Allow clients to fetch 'analytics' through API for Portfolio + 'Analytics'('PA'), Style Performance Risk('SPAR') and 'Vault' products of + 'FactSet'. Visit + + for more information on the usage of package. Visit + for more information on products. + date_publication: '2020-02-02' + bug_reports: https://github.com/factset/analyticsapi-engines-r-sdk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=factset.analyticsapi.engines + url_git: https://github.com/factset/analyticsapi-engines-r-sdk +factset.protobuf.stach.v2: + version: 1.0.6 + title: '''FactSet'' ''STACH V2'' Library' + maintainer: Charlie Mathis + description: |- + Generates 'RProtobuf' classes for 'FactSet' 'STACH V2' tabular + format which represents complex multi-dimensional array of data. These + classes help in the 'serialization' and 'deserialization' of 'STACH V2' + formatted data. See 'GitHub' repository documentation for more + information. + date_publication: '2022-10-16' + bug_reports: https://github.com/factset/stachschema-sdks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=factset.protobuf.stach.v2 + url_git: https://github.com/factset/stachschema-sdks +factset.protobuf.stachextensions: + version: 1.0.4 + title: '''FactSet'' ''STACH'' Extensions Package' + maintainer: Veda Bhaskara Ramanth + description: |- + Allow clients to convert 'FactSet' 'STACH' formatted data to simpler + tabular formats in the form of data frames. This package also provides helper + methods to extract the meta data from 'FactSet' 'STACH' formatted + data. See documentation on the 'GitHub' repository for more information. + date_publication: '2023-10-19' + bug_reports: https://github.com/factset/stach-extensions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=factset.protobuf.stachextensions + url_git: https://github.com/factset/stach-extensions +fad: + version: 0.9-1 + title: Factor Analysis for Data + maintainer: Somak Dutta + description: |- + Compute maximum likelihood estimators of parameters in a Gaussian factor model using + the the matrix-free methodology described in Dai et al. (2020) . + In contrast to the factanal() function from 'stats' package, fad() can handle high-dimensional datasets where + number of variables exceed the sample size and is also substantially faster than the EM algorithms. + date_publication: '2022-05-01' + bug_reports: https://github.com/somakd/fad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fad + url_git: https://github.com/somakd/fad +FADA: + version: 1.3.5 + title: |- + Variable Selection for Supervised Classification in High + Dimension + maintainer: David Causeur + description: |- + The functions provided in the FADA (Factor Adjusted Discriminant Analysis) package aim at performing supervised classification of high-dimensional and correlated profiles. The procedure combines a decorrelation step based on a + factor modeling of the dependence among covariates and a classification method. The available methods are Lasso regularized logistic model + (see Friedman et al. (2010)), sparse linear discriminant analysis (see + Clemmensen et al. (2011)), shrinkage linear and diagonal discriminant + analysis (see M. Ahdesmaki et al. (2010)). More methods of classification can be used on the decorrelated data provided by the package FADA. + date_publication: '2019-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FADA + url_git: '' +FAdist: + version: '2.4' + title: Distributions that are Sometimes Used in Hydrology + maintainer: Thomas Petzoldt + description: Probability distributions that are sometimes useful in hydrology. + date_publication: '2022-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAdist + url_git: https://github.com/tpetzoldt/FAdist +FADPclust: + version: 1.1.1 + title: Functional Data Clustering Using Adaptive Density Peak Detection + maintainer: Rui Ren + description: An implementation of a clustering algorithm for functional data based + on adaptive density peak detection technique, in which the density is estimated + by functional k-nearest neighbor density estimation based on a proposed semi-metric + between functions. The proposed functional data clustering algorithm is computationally + fast since it does not need iterative process. (Alex Rodriguez and Alessandro + Laio (2014) ; Xiao-Feng Wang and Yifan Xu (2016) + ). + date_publication: '2022-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FADPclust + url_git: '' +faersquarterlydata: + version: 1.2.0 + title: |- + FDA Adverse Event Reporting System Quarterly Data Extracting + Tool + maintainer: Luis Garcez + description: An easy framework to read FDA Adverse Event Reporting System XML/ASCII + files . + date_publication: '2024-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=faersquarterlydata + url_git: '' +FAfA: + version: '0.2' + title: Factor Analysis for All + maintainer: Abdullah Faruk KILIC + description: This Shiny application offers researchers a comprehensive tool for + performing factor analysis. Users can upload datasets, validate assumptions, manage + missing and outlier data, split data for different analyses, and run exploratory + and confirmatory factor analyses ("EFA" and "CFA"). The software also offers reliability + analysis, exploratory graph analysis, and item weighting. With a user-friendly + interface, this tool simplifies the EFA and CFA processes. The main features are + data submission and simple data inspection. Data manipulation (excluding variables, + splitting data, checking for outliers), assumption checking (Tabachnik & Fidell + (2012) and Field (2009) ) for + factor analysis, exploratory factor analysis (with various factor number determination + methods (Lorenzo-Seva & Ferrando (2021) )), confirmatory + factor analysis (model definition and modification suggestions (Kline (2011) )), + reliability analysis (Cronbach's alpha, McDonald's omega, Armor's theta, structural + reliability, stratified alpha), item weighting (Kilic & Dogan (2019) ). + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAfA + url_git: '' +Fahrmeir: + version: 2016.5.31 + title: |- + Data from the Book "Multivariate Statistical Modelling Based on + Generalized Linear Models", First Edition, by Ludwig Fahrmeir + and Gerhard Tutz + maintainer: Kjetil B Halvorsen + description: |- + Data and functions for the book "Multivariate Statistical + Modelling Based on Generalized Linear Models", first edition, by + Ludwig Fahrmeir and Gerhard Tutz. Useful when using the book. + date_publication: '2016-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Fahrmeir + url_git: '' +fail: + version: '1.3' + title: File Abstraction Interface Layer (FAIL) + maintainer: Michel Lang + description: |- + More comfortable interface to work with R data or source files + in a key-value fashion. + date_publication: '2015-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fail + url_git: https://github.com/mllg/fail +fairadapt: + version: 1.0.0 + title: Fair Data Adaptation with Quantile Preservation + maintainer: Drago Plecko + description: |- + An implementation of the fair data adaptation with quantile + preservation described in Plecko & Meinshausen (JMLR 2020, 21(242), 1-44). + The adaptation procedure uses the specified causal graph to pre-process the + given training and testing data in such a way to remove the bias caused by + the protected attribute. The procedure uses tree ensembles for quantile + regression. Instructions for using the methods are further elaborated in + the corresponding JSS manuscript, see . + date_publication: '2024-09-06' + bug_reports: https://github.com/dplecko/fairadapt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fairadapt + url_git: https://github.com/dplecko/fairadapt +FAIRmaterials: + version: 0.4.2.1 + title: Ontology Tools with Data FAIRification in Development + maintainer: Roger H French + description: |- + Translates several CSV files with ontological terms and corresponding + data into RDF triples. These RDF triples are stored in OWL and JSON-LD files, + facilitating data accessibility, interoperability, and knowledge unification. + The triples are also visualized in a graph saved as an SVG. The input CSVs + must be formatted with a template from a public Google Sheet; see README or + vignette for more information. This is a tool is used by the SDLE Research + Center at Case Western Reserve University to create and visualize material + science ontologies, and it includes example ontologies to demonstrate its + capabilities. This work was supported by the U.S. Department of Energy’s + Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy + Technologies Office (SETO) Agreement Numbers E-EE0009353 and DE-EE0009347, + Department of Energy (National Nuclear Security Administration) under Award + Number DE-NA0004104 and Contract number B647887, and U.S. National Science + Foundation Award under Award Number 2133576. + date_publication: '2024-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAIRmaterials + url_git: '' +FairMclus: + version: 2.2.1 + title: Clustering for Data with Sensitive Attribute + maintainer: Carlos Santos-Mangudo + description: |- + Clustering for categorical and mixed-type of data, to preventing classification biases due to race, + gender or others sensitive attributes. + This algorithm is an extension of the methodology proposed by "Santos & Heras (2020) ". + date_publication: '2021-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FairMclus + url_git: '' +fairml: + version: '0.8' + title: Fair Models in Machine Learning + maintainer: Marco Scutari + description: |- + Fair machine learning regression models which take sensitive attributes into account in + model estimation. Currently implementing Komiyama et al. (2018) + , Zafar et al. + (2019) and my own + approach from Scutari, Panero and Proissl (2022) + + that uses ridge regression to enforce fairness. + date_publication: '2023-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fairml + url_git: '' +fairmodels: + version: 1.2.1 + title: Flexible Tool for Bias Detection, Visualization, and Mitigation + maintainer: Jakub Wiśniewski + description: Measure fairness metrics in one place for many models. Check how big + is model's bias towards different races, sex, nationalities etc. Use measures + such as Statistical Parity, Equal odds to detect the discrimination against unprivileged + groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). + There are various pre-processing and post-processing bias mitigation algorithms + implemented. Package also supports calculating fairness metrics for regression + models. Find more details in (Wiśniewski, Biecek (2021)) . + date_publication: '2022-08-23' + bug_reports: https://github.com/ModelOriented/fairmodels/issues + url: https://fairmodels.drwhy.ai/ + url_cran: https://CRAN.R-project.org/package=fairmodels + url_git: '' +fairness: + version: 1.2.2 + title: Algorithmic Fairness Metrics + maintainer: Nikita Kozodoi + description: Offers calculation, visualization and comparison of algorithmic fairness + metrics. Fair machine learning is an emerging topic with the overarching aim to + critically assess whether ML algorithms reinforce existing social biases. Unfair + algorithms can propagate such biases and produce predictions with a disparate + impact on various sensitive groups of individuals (defined by sex, gender, ethnicity, + religion, income, socioeconomic status, physical or mental disabilities). Fair + algorithms possess the underlying foundation that these groups should be treated + similarly or have similar prediction outcomes. The fairness R package offers the + calculation and comparisons of commonly and less commonly used fairness metrics + in population subgroups. These methods are described by Calders and Verwer (2010) + , Chouldechova (2017) , + Feldman et al. (2015) , Friedler et al. (2018) + and Zafar et al. (2017) . The package also offers + convenient visualizations to help understand fairness metrics. + date_publication: '2021-04-14' + bug_reports: https://github.com/kozodoi/fairness/issues + url: https://kozodoi.me/r/fairness/packages/2020/05/01/fairness-tutorial.html + url_cran: https://CRAN.R-project.org/package=fairness + url_git: '' +fairsubset: + version: '1.0' + title: Choose Representative Subsets + maintainer: Joe Delaney + description: Allows user to obtain subsets of columns of data or vectors within + a list. These subsets will match the original data in terms of average and variation, + but have a consistent length of data per column. It is intended for use on automated + data generation which may not always output the same N per replicate or sample. + date_publication: '2020-09-17' + bug_reports: '' + url: https://pubmed.ncbi.nlm.nih.gov/31583263/ + url_cran: https://CRAN.R-project.org/package=fairsubset + url_git: '' +fake: + version: 1.4.0 + title: |- + Flexible Data Simulation Using the Multivariate Normal + Distribution + maintainer: Barbara Bodinier + description: This R package can be used to generate artificial data conditionally + on pre-specified (simulated or user-defined) relationships between the variables + and/or observations. Each observation is drawn from a multivariate Normal distribution + where the mean vector and covariance matrix reflect the desired relationships. + Outputs can be used to evaluate the performances of variable selection, graphical + modelling, or clustering approaches by comparing the true and estimated structures + (B Bodinier et al (2021) ). + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fake + url_git: '' +fakemake: + version: 1.11.1 + title: Mock the Unix Make Utility + maintainer: Andreas Dominik Cullmann + description: |- + Use R as a minimal build system. This might come in + handy if you are developing R packages and can not use a proper build + system. Stay away if you can (use a proper build system). + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fakemake + url_git: https://gitlab.com/fvafrcu/fakemake +fakir: + version: 1.0.0 + title: Generate Fake Datasets for Prototyping and Teaching + maintainer: Colin Fay + description: |- + Create fake datasets that can be used for prototyping and teaching. + This package provides a set of functions to generate fake data + for a variety of data types, such as dates, addresses, + and names. It can be used for prototyping (notably in 'shiny') or as a tool + to teach data manipulation and data visualization. + date_publication: '2023-04-13' + bug_reports: https://github.com/Thinkr-open/fakir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fakir + url_git: https://github.com/Thinkr-open/fakir +fakmct: + version: 0.1.0 + title: Fuzzy Adaptive Resonance Theory K-Means Clustering Technique + maintainer: Alfi Nurrahmah + description: |- + A set of function for clustering data observation with hybrid method Fuzzy ART and K-Means + by Sengupta, Ghosh & Dan (2011) . + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fakmct + url_git: +falcon: + version: '0.2' + title: |- + Finding Allele-Specific Copy Number in Next-Generation + Sequencing Data + maintainer: Hao Chen + description: This is a method for Allele-specific DNA Copy Number Profiling using + Next-Generation Sequencing. Given the allele-specific coverage at the variant + loci, this program segments the genome into regions of homogeneous allele-specific + copy number. It requires, as input, the read counts for each variant allele in + a pair of case and control samples. For detection of somatic mutations, the case + and control samples can be the tumor and normal sample from the same individual. + date_publication: '2016-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=falcon + url_git: '' +falconx: + version: '0.2' + title: |- + Finding Allele-Specific Copy Number in Whole-Exome Sequencing + Data + maintainer: Hao Chen + description: 'This is a method for Allele-specific DNA Copy Number profiling for + whole-Exome sequencing data. Given the allele-specific coverage and site biases + at the variant loci, this program segments the genome into regions of homogeneous + allele-specific copy number. It requires, as input, the read counts for each + variant allele in a pair of case and control samples, as well as the site biases. + For detection of somatic mutations, the case and control samples can be the tumor + and normal sample from the same individual. The implemented method is based on + the paper: Chen, H., Jiang, Y., Maxwell, K., Nathanson, K. and Zhang, N. (under + review). Allele-specific copy number estimation by whole Exome sequencing.' + date_publication: '2017-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=falconx + url_git: '' +fam.recrisk: + version: '0.1' + title: Familial Recurrence Risk + maintainer: Jason Sinnwell + description: Given vectors of family sizes and number of affecteds per family, calculates + the risk of disease recurrence in an unaffected person, conditional on a family + having at least k affected members. Methods also model heterogeneity of disease + risk across families by fitting a mixture model, allowing for high and low risk + families. + date_publication: '2018-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fam.recrisk + url_git: '' +FAMetA: + version: 0.1.6 + title: Fatty Acid Metabolic Analysis + maintainer: Maribel Alcoriza-Balaguer + description: Fatty acid metabolic analysis aimed to the estimation of FA import + (I), de novo synthesis (S), fractional contribution of the 13C-tracers (D0, D1, + D2), elongation (E) and desaturation (Des) based on mass isotopologue data. + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAMetA + url_git: '' +FamEvent: + version: '3.2' + title: Family Age-at-Onset Data Simulation and Penetrance Estimation + maintainer: Yun-Hee Choi + description: |- + Simulates age-at-onset traits associated with a segregating major gene in family data + obtained from population-based, clinic-based, or multi-stage designs. Appropriate ascertainment + correction is utilized to estimate age-dependent penetrance functions either parametrically from + the fitted model or nonparametrically from the data. The Expectation and Maximization algorithm + can infer missing genotypes and carrier probabilities estimated from family's genotype and + phenotype information or from a fitted model. Plot functions include pedigrees of simulated + families and predicted penetrance curves based on specified parameter values. + For more information see Choi, Y.-H., Briollais, L., He, W. and Kopciuk, K. (2021) FamEvent: An + R Package for Generating and Modeling Time-to-Event Data in Family Designs, + Journal of Statistical Software 97 (7), 1-30. + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FamEvent + url_git: '' +familial: + version: 1.0.7 + title: Statistical Tests of Familial Hypotheses + maintainer: Ryan Thompson + description: |- + Provides functionality for testing familial hypotheses. Supports testing centers + belonging to the Huber family. Testing is carried out using the Bayesian bootstrap. One- and + two-sample tests are supported, as are directional tests. Methods for visualizing output are + provided. + date_publication: '2024-12-10' + bug_reports: https://github.com/ryan-thompson/familial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=familial + url_git: https://github.com/ryan-thompson/familial +familiar: + version: 1.5.0 + title: End-to-End Automated Machine Learning and Model Evaluation + maintainer: Alex Zwanenburg + description: |- + Single unified interface for end-to-end modelling of regression, + categorical and time-to-event (survival) outcomes. Models created using + familiar are self-containing, and their use does not require additional + information such as baseline survival, feature clustering, or feature + transformation and normalisation parameters. Model performance, + calibration, risk group stratification, (permutation) variable importance, + individual conditional expectation, partial dependence, and more, are + assessed automatically as part of the evaluation process and exported in + tabular format and plotted, and may also be computed manually using export + and plot functions. Where possible, metrics and values obtained during the + evaluation process come with confidence intervals. + date_publication: '2024-09-23' + bug_reports: https://github.com/alexzwanenburg/familiar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=familiar + url_git: https://github.com/alexzwanenburg/familiar +Familias: + version: 2.6.2 + title: Probabilities for Pedigrees Given DNA Data + maintainer: Thore Egeland + description: |- + An interface to the core 'Familias' functions which are + programmed in C++. The implementation is described in Egeland, Mostad and Olaisen + (1997) and Simonsson and Mostad + (2016) . + date_publication: '2025-01-08' + bug_reports: '' + url: https://www.familias.name/openfamilias.html + url_cran: https://CRAN.R-project.org/package=Familias + url_git: '' +Families: + version: 2.0.2 + title: Kinship Ties in (Virtual) Multi-Generation Populations + maintainer: Frans Willekens + description: Tools to study lineages, grandparenthood, loss of close relatives, + kinship networks and other topics in multi-generation populations. + date_publication: '2024-04-13' + bug_reports: https://github.com/willekens/Families/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Families + url_git: '' +FamilyRank: + version: '1.0' + title: |- + Algorithm for Ranking Predictors Using Graphical Domain + Knowledge + maintainer: Michelle Saul + description: Grows families of features by selecting features that maximize a weighted + score calculated from empirical feature scores and graphical knowledge. The final + weighted score for a feature is determined by summing a feature's family-weighted + scores across all families in which the feature appears. + date_publication: '2021-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FamilyRank + url_git: '' +FAmle: + version: 1.3.7 + title: |- + Maximum Likelihood and Bayesian Estimation of Univariate + Probability Distributions + maintainer: Thomas Petzoldt + description: |- + Estimate parameters of univariate probability distributions + with maximum likelihood and Bayesian methods. + date_publication: '2022-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAmle + url_git: https://github.com/tpetzoldt/FAmle +FAMoS: + version: 0.3.0 + title: A Flexible Algorithm for Model Selection + maintainer: Michael Gabel + description: |- + Given a set of parameters describing model dynamics and a corresponding cost function, + FAMoS performs a dynamic forward-backward model selection on a specified selection + criterion. It also applies a non-local swap search method. Works on any cost function. + For detailed information see Gabel et al. (2019) . + date_publication: '2020-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAMoS + url_git: '' +famSKATRC: + version: 1.1.0 + title: |- + Family Sequence Kernel Association Test for Rare and Common + Variants + maintainer: Khalid B. Kunji + description: |- + FamSKAT-RC is a family-based association kernel test for both + rare and common variants. This test is general and several special cases + are known as other methods: famSKAT, which only focuses on rare variants + in family-based data, SKAT, which focuses on rare variants in + population-based data (unrelated individuals), and SKAT-RC, which focuses + on both rare and common variants in population-based data. When one + applies famSKAT-RC and sets the value of phi to 1, famSKAT-RC becomes + famSKAT. When one applies famSKAT-RC and set the value of phi to 1 and the + kinship matrix to the identity matrix, famSKAT-RC becomes SKAT. When one + applies famSKAT-RC and set the kinship matrix (fullkins) to the identity + matrix (and phi is not equal to 1), famSKAT-RC becomes SKAT-RC. We also + include a small sample synthetic pedigree to demonstrate the method with. + For more details see Saad M and Wijsman EM (2014) . + date_publication: '2017-11-09' + bug_reports: '' + url: https://www.ncbi.nlm.nih.gov/pubmed/25132070 + url_cran: https://CRAN.R-project.org/package=famSKATRC + url_git: '' +FAMT: + version: '2.6' + title: |- + Factor Analysis for Multiple Testing (FAMT) : Simultaneous Tests + under Dependence in High-Dimensional Data + maintainer: David Causeur + description: The method proposed in this package takes into account the impact of + dependence on the multiple testing procedures for high-throughput data as proposed + by Friguet et al. (2009). The common information shared by all the variables is + modeled by a factor analysis structure. The number of factors considered in the + model is chosen to reduce the false discoveries variance in multiple tests. The + model parameters are estimated thanks to an EM algorithm. Adjusted tests statistics + are derived, as well as the associated p-values. The proportion of true null hypotheses + (an important parameter when controlling the false discovery rate) is also estimated + from the FAMT model. Graphics are proposed to interpret and describe the factors. + date_publication: '2022-05-09' + bug_reports: '' + url: http://famt.free.fr/ + url_cran: https://CRAN.R-project.org/package=FAMT + url_git: '' +fanc: + version: 2.3.11 + title: Penalized Likelihood Factor Analysis via Nonconvex Penalty + maintainer: Kei Hirose + description: Computes the penalized maximum likelihood estimates of factor loadings + and unique variances for various tuning parameters. The pathwise coordinate descent + along with EM algorithm is used. This package also includes a new graphical tool + which outputs path diagram, goodness-of-fit indices and model selection criteria + for each regularization parameter. The user can change the regularization parameter + by manipulating scrollbars, which is helpful to find a suitable value of regularization + parameter. + date_publication: '2024-01-14' + bug_reports: '' + url: https://doi.org/10.1007/s11222-014-9458-0 + url_cran: https://CRAN.R-project.org/package=fanc + url_git: '' +fANCOVA: + version: 0.6-1 + title: Nonparametric Analysis of Covariance + maintainer: Xiaofeng Wang + description: |- + A collection of R functions to perform nonparametric + analysis of covariance for regression curves or surfaces. + Testing the equality or parallelism of nonparametric curves + or surfaces is equivalent to analysis of variance (ANOVA) or + analysis of covariance (ANCOVA) for one-sample functional data. + Three different testing methods are available in the package, + including one based on L-2 distance, one based on an ANOVA + statistic, and one based on variance estimators. + date_publication: '2020-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fANCOVA + url_git: '' +fancycut: + version: 0.1.3 + title: A Fancy Version of 'base::cut' + maintainer: Adam Rich + description: |- + Provides the function fancycut() which is like cut() except + you can mix left open and right open intervals with point values, + intervals that are closed on both ends and intervals that are open on both ends. + date_publication: '2024-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fancycut + url_git: '' +fangs: + version: 0.2.17 + title: Feature Allocation Neighborhood Greedy Search Algorithm + maintainer: David B. Dahl + description: A neighborhood-based, greedy search algorithm is performed to estimate + a feature allocation by minimizing the expected loss based on posterior samples + from the feature allocation distribution. The method is currently under peer review + but an earlier draft is available in Dahl, Johnson, and Andros (2022+) . + date_publication: '2024-09-06' + bug_reports: https://github.com/dbdahl/fangs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fangs + url_git: https://github.com/dbdahl/fangs +fanovaGraph: + version: '1.5' + title: Building Kriging Models from FANOVA Graphs + maintainer: Sonja Kuhnt + description: Estimation and plotting of a function's FANOVA graph to identify the + interaction structure and fitting, prediction and simulation of a Kriging model + modified by the identified structure. The interactive function plotManipulate() + can only be run on the 'RStudio IDE' with 'RStudio' package 'manipulate' loaded. + 'RStudio' is freely available (), and includes package 'manipulate'. + The equivalent function plotTk() bases on CRAN Repository packages only. For further + information on the method see Fruth, J., Roustant, O., Kuhnt, S. (2014) . + date_publication: '2020-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fanovaGraph + url_git: '' +fanplot: + version: 4.0.0 + title: |- + Visualisation of Sequential Probability Distributions Using Fan + Charts + maintainer: Guy J. Abel + description: |- + Visualise sequential distributions using a range of plotting + styles. Sequential distribution data can be input as either simulations or + values corresponding to percentiles over time. Plots are added to + existing graphic devices using the fan function. Users can choose from four + different styles, including fan chart type plots, where a set of coloured + polygon, with shadings corresponding to the percentile values are layered + to represent different uncertainty levels. Full details in R Journal article; Abel (2015) . + date_publication: '2021-08-02' + bug_reports: https://github.com/guyabel/fanplot/issues/ + url: http://guyabel.github.io/fanplot/ + url_cran: https://CRAN.R-project.org/package=fanplot + url_git: '' +fansi: + version: 1.0.6 + title: ANSI Control Sequence Aware String Functions + maintainer: Brodie Gaslam + description: |- + Counterparts to R string manipulation functions that account for + the effects of ANSI text formatting control sequences. + date_publication: '2023-12-08' + bug_reports: https://github.com/brodieG/fansi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fansi + url_git: https://github.com/brodieG/fansi +fanyi: + version: 0.0.7 + title: Translate Words or Sentences via Online Translators + maintainer: Guangchuang Yu + description: |- + Useful functions to translate text for multiple languages using online translators. + For example, by translating error messages and descriptive analysis results into a language familiar + to the user, it enables a better understanding of the information, thereby reducing the barriers caused by language. + It offers several helper functions to query gene information to help interpretation of interested genes (e.g., marker genes, differential expression genes), + and provides utilities to translate 'ggplot' graphics. This package is not affiliated with any of the online translators. + The developers do not take responsibility for the invoice it incurs when using this package, especially for exceeding the free quota. + date_publication: '2024-04-14' + bug_reports: https://github.com/YuLab-SMU/fanyi/issues + url: https://www.biorxiv.org/content/10.1101/2023.12.21.572729 + url_cran: https://CRAN.R-project.org/package=fanyi + url_git: https://github.com/YuLab-SMU/fanyi +FAO56: + version: '1.0' + title: Evapotranspiration Based on FAO Penman-Monteith Equation + maintainer: Ali Ahani + description: Calculation of Evapotranspiration by FAO Penman-Monteith equation based + on Allen, R. G., Pereira, L. S., Raes, D., Smith, M. (1998, ISBN:92-5-104219-5) + "Crop evapotranspiration - Guidelines for computing crop water requirements - + FAO Irrigation and drainage paper 56". + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAO56 + url_git: '' +FAOSTAT: + version: 2.4.0 + title: Download Data from the FAOSTAT Database + maintainer: Paul Rougieux + description: |- + Download Data from the FAOSTAT Database of the Food and Agricultural Organization (FAO) of the United Nations. + A list of functions to download statistics from FAOSTAT (database of the FAO ) + and WDI (database of the World Bank ), and to perform some harmonization operations. + date_publication: '2024-05-22' + bug_reports: https://gitlab.com/paulrougieux/faostatpackage/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FAOSTAT + url_git: https://gitlab.com/paulrougieux/faostatpackage +faoutlier: + version: 0.7.6 + title: |- + Influential Case Detection Methods for Factor Analysis and + Structural Equation Models + maintainer: Phil Chalmers + description: |- + Tools for detecting and summarize influential cases that + can affect exploratory and confirmatory factor analysis models as well as + structural equation models more generally (Chalmers, 2015, ; + Flora, D. B., LaBrish, C. & Chalmers, R. P., 2012, ). + date_publication: '2021-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=faoutlier + url_git: https://github.com/philchalmers/faoutlier +faq: + version: 0.1.1 + title: Create FAQ Page + maintainer: Jiena McLellan + description: Create Frequently Asked Questions page for Shiny application. + date_publication: '2021-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=faq + url_git: '' +far: + version: 0.6-7 + title: Modelization for Functional AutoRegressive Processes + maintainer: Julien Damon + description: |- + Modelizations and previsions functions for + Functional AutoRegressive processes using + nonparametric methods: functional kernel, + estimation of the covariance operator in + a subspace, ... + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=far + url_git: https://github.com/Looping027/far +faraway: + version: 1.0.9 + title: Datasets and Functions for Books by Julian Faraway + maintainer: Julian Faraway + description: Books are "Linear Models with R" published 1st Ed. August 2004, 2nd + Ed. July 2014, 3rd Ed. February 2025 by CRC press, ISBN 9781439887332, and "Extending + the Linear Model with R" published by CRC press in 1st Ed. December 2005 and 2nd + Ed. March 2016, ISBN 9781584884248 and "Practical Regression and ANOVA in R" contributed + documentation on CRAN (now very dated). + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=faraway + url_git: https://github.com/julianfaraway/faraway +FARDEEP: + version: 1.0.1 + title: |- + Fast and Robust Deconvolution of Tumor Infiltrating Lymphocyte + from Expression Profiles using Least Trimmed Squares + maintainer: Yuying Xie + description: Using the idea of least trimmed square, it could automatically detects + and removes outliers from data before estimating the coefficients. It is a robust + machine learning tool which can be applied to gene-expression deconvolution technique. + Yuning Hao, Ming Yan, Blake R. Heath, Yu L. Lei and Yuying Xie (2019) . + date_publication: '2019-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FARDEEP + url_git: '' +farff: + version: 1.1.1 + title: A Faster 'ARFF' File Reader and Writer + maintainer: Marc Becker + description: |- + Reads and writes 'ARFF' files. 'ARFF' (Attribute-Relation + File Format) files are like 'CSV' files, with a little bit of added + meta information in a header and standardized NA values. They are + quite often used for machine learning data sets and were introduced + for the 'WEKA' machine learning 'Java' toolbox. See + + for further info on 'ARFF' and for + for more info on 'WEKA'. + 'farff' gets rid of the 'Java' dependency that 'RWeka' enforces, and + it is at least a faster reader (for bigger files). It uses 'readr' as + parser back-end for the data section of the 'ARFF' file. Consistency + with 'RWeka' is tested on 'Github' and 'Travis CI' with hundreds of + 'ARFF' files from 'OpenML'. + date_publication: '2021-05-10' + bug_reports: https://github.com/mlr-org/farff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=farff + url_git: https://github.com/mlr-org/farff +FarmSelect: + version: 1.0.2 + title: Factor Adjusted Robust Model Selection + maintainer: Koushiki Bose + description: Implements a consistent model selection strategy for high dimensional + sparse regression when the covariate dependence can be reduced through factor + models. By separating the latent factors from idiosyncratic components, the problem + is transformed from model selection with highly correlated covariates to that + with weakly correlated variables. It is appropriate for cases where we have many + variables compared to the number of samples. Moreover, it implements a robust + procedure to estimate distribution parameters wherever possible, hence being suitable + for cases when the underlying distribution deviates from Gaussianity. See the + paper on the 'FarmSelect' method, Fan et al.(2017) , for detailed + description of methods and further references. + date_publication: '2018-04-19' + bug_reports: '' + url: https://kbose28.github.io/FarmSelect/ + url_cran: https://CRAN.R-project.org/package=FarmSelect + url_git: '' +FarmTest: + version: 2.2.0 + title: Factor-Adjusted Robust Multiple Testing + maintainer: Xiaoou Pan + description: |- + Performs robust multiple testing for means in the presence of known and unknown latent factors presented in Fan et al.(2019) "FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control" . + Implements a series of adaptive Huber methods combined with fast data-drive tuning schemes proposed in Ke et al.(2019) "User-Friendly Covariance Estimation for Heavy-Tailed Distributions" to estimate model parameters and construct test statistics that are robust against heavy-tailed and/or asymmetric error distributions. + Extensions to two-sample simultaneous mean comparison problems are also included. + As by-products, this package contains functions that compute adaptive Huber mean, covariance and regression estimators that are of independent interest. + date_publication: '2020-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FarmTest + url_git: https://github.com/XiaoouPan/FarmTest +farr: + version: 0.3.0 + title: Data and Code for Financial Accounting Research + maintainer: Ian Gow + description: |- + Handy functions and data to support a course book for accounting research. + Gow, Ian and Tongqing Ding (2022) 'Accounting Research: An Introductory Course' . + date_publication: '2024-02-29' + bug_reports: https://github.com/iangow/farr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=farr + url_git: https://github.com/iangow/farr +farrell: + version: 0.2.1 + title: Interactive Interface to Data Envelopment Analysis Modeling + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to execute interactively radial data envelopment analysis models. The user has the ability to upload a data frame, + select the input/output variables, choose the technology assumption to adopt and decide whether to run an input or an output oriented model. + When the model is executed a set of results are displayed which include efficiency scores, peers' determination, scale efficiencies' evaluation + and slacks' calculation. Fore more information about the theoretical background of the package, + please refer to Bogetoft & Otto (2011) . + date_publication: '2020-09-26' + bug_reports: https://github.com/feddelegrand7/farrell/issues + url: '' + url_cran: https://CRAN.R-project.org/package=farrell + url_git: https://github.com/feddelegrand7/farrell +farver: + version: 2.1.2 + title: High Performance Colour Space Manipulation + maintainer: Thomas Lin Pedersen + description: |- + The encoding of colour can be handled in many different ways, + using different colour spaces. As different colour spaces have + different uses, efficient conversion between these representations are + important. The 'farver' package provides a set of functions that gives + access to very fast colour space conversion and comparisons + implemented in C++, and offers speed improvements over the + 'convertColor' function in the 'grDevices' package. + date_publication: '2024-05-13' + bug_reports: https://github.com/thomasp85/farver/issues + url: https://farver.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=farver + url_git: https://github.com/thomasp85/farver +FAS: + version: 1.0.0 + title: Factor-Augmented Sparse Regression Tuning-Free Testing + maintainer: Jonas Striaukas + description: The 'FAS' package implements the bootstrap method for the tuning parameter + selection and tuning-free inference on sparse regression coefficient vectors. + Currently, the test could be applied to linear and factor-augmented sparse regressions, + see Lederer & Vogt (2021, JMLR) + and Beyhum & Striaukas (2023) . + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAS + url_git: '' +fasano.franceschini.test: + version: 2.2.2 + title: |- + Fasano-Franceschini Test: A Multivariate Kolmogorov-Smirnov + Two-Sample Test + maintainer: Connor Puritz + description: |- + An implementation of the two-sample multivariate + Kolmogorov-Smirnov test described by Fasano and Franceschini (1987) + . This test evaluates the null hypothesis + that two i.i.d. random samples were drawn from the same underlying + probability distribution. The data can be of any dimension, and can be + of any type (continuous, discrete, or mixed). + date_publication: '2024-02-07' + bug_reports: https://github.com/braunlab-nu/fasano.franceschini.test/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fasano.franceschini.test + url_git: https://github.com/braunlab-nu/fasano.franceschini.test +fase: + version: 1.0.1 + title: Functional Adjacency Spectral Embedding + maintainer: Peter W. MacDonald + description: Latent process embedding for functional network data with the Functional + Adjacency Spectral Embedding. Fits smooth latent processes based on cubic spline + bases. Also generates functional network data from three models, and evaluates + a network generalized cross-validation criterion for dimension selection. For + more information, see MacDonald, Zhu and Levina (2022+) . + date_publication: '2024-04-03' + bug_reports: https://github.com/peterwmacd/fase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fase + url_git: https://github.com/peterwmacd/fase +FASeg: + version: 0.1.9 + title: Joint Segmentation of Correlated Time Series + maintainer: Emilie Lebarbier + description: It contains a function designed to the joint segmentation in the mean + of several correlated series. The method is described in the paper X. Collilieux, + E. Lebarbier and S. Robin. A factor model approach for the joint segmentation + with between-series correlation (2015) . + date_publication: '2018-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FASeg + url_git: '' +fAssets: + version: '4023.85' + title: Rmetrics - Analysing and Modelling Financial Assets + maintainer: Stefan Theussl + description: |- + A collection of functions to manage, to investigate and to analyze data sets of financial + assets from different points of view. + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fAssets + url_git: https://r-forge.r-project.org/projects/rmetrics/ +fasstr: + version: 0.5.3 + title: Analyze, Summarize, and Visualize Daily Streamflow Data + maintainer: Jon Goetz + description: |- + The Flow Analysis Summary Statistics Tool for R, 'fasstr', provides various functions to tidy and screen daily stream discharge data, calculate and visualize various summary statistics and metrics, and compute annual trending and volume frequency analyses. + It features useful function arguments for filtering of and handling dates, customizing data and metrics, and the ability to pull daily data directly from the Water Survey of Canada hydrometric database (). + date_publication: '2024-09-27' + bug_reports: https://github.com/bcgov/fasstr/issues + url: https://bcgov.github.io/fasstr/ + url_cran: https://CRAN.R-project.org/package=fasstr + url_git: https://github.com/bcgov/fasstr +FAST.R: + version: 0.2.1 + title: Analyze and Visualize FAST-Generated Data + maintainer: Francesco Neri + description: |- + R 'shiny' app to perform data analysis and visualization for the + Fully Automated Senescence Test (FAST) workflow. + date_publication: '2024-03-07' + bug_reports: https://github.com/f-neri/FAST.R/issues + url: https://f-neri.github.io/FAST.R/ + url_cran: https://CRAN.R-project.org/package=FAST.R + url_git: https://github.com/f-neri/FAST.R +fasta: + version: 0.1.0 + title: Fast Adaptive Shrinkage/Thresholding Algorithm + maintainer: Eric C. Chi + description: |- + A collection of acceleration schemes for proximal gradient methods for estimating penalized regression parameters described in + Goldstein, Studer, and Baraniuk (2016) . Schemes such as Fast Iterative Shrinkage and Thresholding Algorithm (FISTA) by Beck and Teboulle (2009) + and the adaptive stepsize rule introduced in Wright, Nowak, and Figueiredo (2009) are included. You provide the objective function and proximal mappings, and it takes care of the issues like stepsize selection, acceleration, and stopping conditions for you. + date_publication: '2018-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fasta + url_git: '' +fastadi: + version: 0.1.1 + title: Self-Tuning Data Adaptive Matrix Imputation + maintainer: Alex Hayes + description: |- + Implements the AdaptiveImpute matrix completion + algorithm of 'Intelligent Initialization and Adaptive Thresholding for + Iterative Matrix Completion', + . + AdaptiveImpute is useful for embedding sparsely observed matrices, + often out performs competing matrix completion algorithms, and + self-tunes its hyperparameter, making usage easy. + date_publication: '2022-09-07' + bug_reports: https://github.com/RoheLab/fastadi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastadi + url_git: https://github.com/RoheLab/fastadi +fastAFT: + version: '1.4' + title: Fast Regression for the Accelerated Failure Time (AFT) Model + maintainer: Yijian Huang + description: Fast censored linear regression for the accelerated failure time (AFT) + model of Huang (2013) . + date_publication: '2023-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastAFT + url_git: '' +fastai: + version: 2.2.2 + title: Interface to 'fastai' + maintainer: Turgut Abdullayev + description: |- + The 'fastai' library + simplifies training fast and accurate neural networks + using modern best practices. It is based on research + in to deep learning best practices undertaken + at 'fast.ai', including 'out of the box' support + for vision, text, tabular, audio, time series, and + collaborative filtering models. + date_publication: '2024-04-11' + bug_reports: https://github.com/EagerAI/fastai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastai + url_git: https://github.com/EagerAI/fastai +fastbackward: + version: 1.0.1 + title: Fast Backward Elimination Based on Information Criterion + maintainer: Jacob Seedorff + description: |- + Performs backward elimination with similar syntax to + the stepAIC() function from the 'MASS' package. A bounding algorithm is + used to avoid fitting unnecessary models, making it much faster. + date_publication: '2024-05-29' + bug_reports: https://github.com/JacobSeedorff21/fastbackward/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastbackward + url_git: https://github.com/JacobSeedorff21/fastbackward +FastBandChol: + version: 0.1.1 + title: |- + Fast Estimation of a Covariance Matrix by Banding the Cholesky + Factor + maintainer: Aaron Molstad + description: Fast and numerically stable estimation of a covariance matrix by banding + the Cholesky factor using a modified Gram-Schmidt algorithm implemented in RcppArmadilo. + See for details on the algorithm. + date_publication: '2015-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastBandChol + url_git: '' +fastbeta: + version: 0.3.1 + title: |- + Fast Approximation of Time-Varying Infectious Disease + Transmission Rates + maintainer: Mikael Jagan + description: |- + A fast method for approximating time-varying infectious disease + transmission rates from disease incidence time series and other + data, based on a discrete time approximation of an SEIR model, as + analyzed in Jagan et al. (2020) . + date_publication: '2024-11-22' + bug_reports: https://github.com/davidearn/fastbeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastbeta + url_git: https://github.com/davidearn/fastbeta +fastcluster: + version: 1.2.6 + title: Fast Hierarchical Clustering Routines for R and 'Python' + maintainer: Daniel Müllner + description: |- + This is a two-in-one package which provides interfaces to + both R and 'Python'. It implements fast hierarchical, agglomerative + clustering routines. Part of the functionality is designed as drop-in + replacement for existing routines: linkage() in the 'SciPy' package + 'scipy.cluster.hierarchy', hclust() in R's 'stats' package, and the + 'flashClust' package. It provides the same functionality with the + benefit of a much faster implementation. Moreover, there are + memory-saving routines for clustering of vector data, which go beyond + what the existing packages provide. For information on how to install + the 'Python' files, see the file INSTALL in the source distribution. + Based on the present package, Christoph Dalitz also wrote a pure 'C++' + interface to 'fastcluster': + . + date_publication: '2024-01-12' + bug_reports: '' + url: https://danifold.net/fastcluster.html + url_cran: https://CRAN.R-project.org/package=fastcluster + url_git: '' +fastcmh: + version: 0.2.7 + title: Significant Interval Discovery with Categorical Covariates + maintainer: Dean Bodenham + description: A method which uses the Cochran-Mantel-Haenszel test with significant + pattern mining to detect intervals in binary genotype data which are significantly + associated with a particular phenotype, while accounting for categorical covariates. + date_publication: '2016-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastcmh + url_git: '' +fastcmprsk: + version: 1.24.10 + title: Fine-Gray Regression via Forward-Backward Scan + maintainer: Eric S. Kawaguchi + description: 'In competing risks regression, the proportional subdistribution hazards + (PSH) model is popular for its direct assessment of covariate effects on the cumulative + incidence function. This package allows for both penalized and unpenalized PSH + regression in linear time using a novel forward-backward scan. Penalties include + Ridge, Lease Absolute Shrinkage and Selection Operator (LASSO), Smoothly Clipped + Absolute Deviation (SCAD), Minimax Concave Plus (MCP), and elastic net .' + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastcmprsk + url_git: '' +fastcox: + version: 1.1.3 + title: |- + Lasso and Elastic-Net Penalized Cox's Regression in High + Dimensions Models using the Cocktail Algorithm + maintainer: Yi Yang + description: 'We implement a cocktail algorithm, a good mixture of coordinate decent, + the majorization-minimization principle and the strong rule, for computing the + solution paths of the elastic net penalized Cox''s proportional hazards model. + The package is an implementation of Yang, Y. and Zou, H. (2013) DOI: .' + date_publication: '2017-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastcox + url_git: https://github.com/emeryyi/fastcox +fastcpd: + version: 0.14.6 + title: Fast Change Point Detection via Sequential Gradient Descent + maintainer: Xingchi Li + description: |- + Implements fast change point detection algorithm based on the + paper "Sequential Gradient Descent and Quasi-Newton's Method for + Change-Point Analysis" by Xianyang Zhang, Trisha Dawn + . The algorithm is + based on dynamic programming with pruning and sequential gradient + descent. It is able to detect change points a magnitude faster than + the vanilla Pruned Exact Linear Time(PELT). The package includes + examples of linear regression, logistic regression, Poisson + regression, penalized linear regression data, and whole lot more + examples with custom cost function in case the user wants to use their + own cost function. + date_publication: '2024-11-05' + bug_reports: https://github.com/doccstat/fastcpd/issues + url: https://fastcpd.xingchi.li + url_cran: https://CRAN.R-project.org/package=fastcpd + url_git: https://github.com/doccstat/fastcpd +FastCUB: + version: 0.0.3 + title: Fast Estimation of CUB Models via Louis' Identity + maintainer: Rosaria Simone + description: |- + For ordinal rating data, consider the accelerated EM algorithm to estimate and test models within the family of + CUB models (where CUB stands for Combination of a + discrete Uniform and a shifted Binomial distributions). The procedure is built upon Louis' identity for the observed information matrix. Best-subset variable selection is then implemented since it becomes more feasible from the computational point of view. + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastCUB + url_git: '' +fastdid: + version: 1.0.3 + title: Fast Staggered Difference-in-Difference Estimators + maintainer: Lin-Tung Tsai + description: A fast and flexible implementation of Callaway and Sant'Anna's (2021) + staggered Difference-in-Differences (DiD) estimators, 'fastdid' reduces the computation + time from hours to seconds, and incorporates extensions such as time-varying covariates + and multiple events. + date_publication: '2024-11-04' + bug_reports: https://github.com/TsaiLintung/fastdid/issues + url: https://tsailintung.github.io/fastdid/ + url_cran: https://CRAN.R-project.org/package=fastdid + url_git: https://github.com/TsaiLintung/fastdid +fastDummies: + version: 1.7.5 + title: |- + Fast Creation of Dummy (Binary) Columns and Rows from + Categorical Variables + maintainer: Jacob Kaplan + description: Creates dummy columns from columns that have categorical variables + (character or factor types). You can also specify which columns to make dummies + out of, or which columns to ignore. Also creates dummy rows from character, factor, + and Date columns. This package provides a significant speed increase from creating + dummy variables through model.matrix(). + date_publication: '2025-01-20' + bug_reports: https://github.com/jacobkap/fastDummies/issues + url: https://jacobkap.github.io/fastDummies/ + url_cran: https://CRAN.R-project.org/package=fastDummies + url_git: https://github.com/jacobkap/fastDummies +fasterElasticNet: + version: 1.1.2 + title: An Amazing Fast Way to Fit Elastic Net + maintainer: Linyu Zuo + description: Fit Elastic Net, Lasso, and Ridge regression and do cross-validation + in a fast way. We build the algorithm based on Least Angle Regression by Bradley + Efron, Trevor Hastie, Iain Johnstone, etc. (2004)() and some algorithms like Givens rotation and Forward/Back Substitution. In + this way, many matrices to be computed are retained as triangular matrices which + can eventually speed up the computation. The fitting algorithm for Elastic Net + is written in C++ using Armadillo linear algebra library. + date_publication: '2018-08-11' + bug_reports: https://github.com/CUFESAM/Elastic-Net/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fasterElasticNet + url_git: https://github.com/CUFESAM/Elastic-Net +fasterize: + version: 1.1.0 + title: Fast Polygon to Raster Conversion + maintainer: Michael Sumner + description: |- + Provides a drop-in replacement for rasterize() from the 'raster' + package that takes polygon vector or data frame objects, and is much faster. + There is support for the main options provided by the rasterize() function, + including setting the field used and background value, and options for + aggregating multi-layer rasters. Uses the scan line algorithm attributed to + Wylie et al. (1967) . + date_publication: '2024-10-01' + bug_reports: https://github.com/ecohealthalliance/fasterize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fasterize + url_git: https://github.com/ecohealthalliance/fasterize +fasterRaster: + version: 8.4.0.5 + title: Faster Raster and Spatial Vector Processing Using 'GRASS GIS' + maintainer: Adam B. Smith + description: "Processing of large-in-memory/large-on disk rasters and spatial\nvectors + using 'GRASS GIS' . Most functions in\nthe 'terra' package + are\trecreated. Processing of medium-sized and smaller\nspatial objects will nearly + always be faster using 'terra' or 'sf', but\nfor large-in-memory/large-on-disk + objects, 'fasterRaster' may be faster.\nTo use most of the functions, you must + have the stand-alone version (not\nthe 'OSGeoW4' installer version) of 'GRASS + GIS' 8.0 or higher." + date_publication: '2025-02-25' + bug_reports: https://github.com/adamlilith/fasterRaster/issues + url: https://adamlilith.github.io/fasterRaster/ + url_cran: https://CRAN.R-project.org/package=fasterRaster + url_git: https://github.com/adamlilith/fasterRaster +fastFMM: + version: 0.3.0 + title: Fast Functional Mixed Models using Fast Univariate Inference + maintainer: Erjia Cui + description: Implementation of the fast univariate inference approach (Cui et al. + (2022) , Loewinger et al. (2023) ) + for fitting functional mixed models. + date_publication: '2024-09-29' + bug_reports: https://github.com/gloewing/fastFMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastFMM + url_git: https://github.com/gloewing/fastFMM +FastGaSP: + version: 0.6.0 + title: Fast and Exact Computation of Gaussian Stochastic Process + maintainer: Mengyang Gu + description: 'Implements fast and exact computation of Gaussian stochastic process + with the Matern kernel using forward filtering and backward smoothing algorithm. + It includes efficient implementations of the inverse Kalman filter, with applications + such as estimating particle interaction functions. These tools support models + with or without noise. Additionally, the package offers algorithms for fast parameter + estimation in latent factor models, where the factor loading matrix is orthogonal, + and latent processes are modeled by Gaussian processes. See the references: 1) + Mengyang Gu and Yanxun Xu (2020), Journal of Computational and Graphical Statistics; + 2) Xinyi Fang and Mengyang Gu (2024), ; 3) Mengyang + Gu and Weining Shen (2020), Journal of Machine Learning Research; 4) Yizi Lin, + Xubo Liu, Paul Segall and Mengyang Gu (2025), .' + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastGaSP + url_git: '' +fastGHQuad: + version: 1.0.1 + title: Fast 'Rcpp' Implementation of Gauss-Hermite Quadrature + maintainer: Alexander W Blocker + description: |- + Fast, numerically-stable Gauss-Hermite quadrature rules and + utility functions for adaptive GH quadrature. See Liu, Q. and Pierce, D. A. + (1994) for a reference on these methods. + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastGHQuad + url_git: https://github.com/awblocker/fastGHQuad +fastGLCM: + version: 1.0.2 + title: '''GLCM'' Texture Features' + maintainer: Lampros Mouselimis + description: 'Two ''Gray Level Co-occurrence Matrix'' (''GLCM'') implementations + are included: The first is a fast ''GLCM'' feature texture computation based on + ''Python'' ''Numpy'' arrays (''Github'' Repository, ). + The second is a fast ''GLCM'' ''RcppArmadillo'' implementation which is parallelized + (using ''OpenMP'') with the option to return all ''GLCM'' features at once. For + more information, see "Artifact-Free Thin Cloud Removal Using Gans" by Toizumi + Takahiro, Zini Simone, Sagi Kazutoshi, Kaneko Eiji, Tsukada Masato, Schettini + Raimondo (2019), IEEE International Conference on Image Processing (ICIP), pp. + 3596-3600, .' + date_publication: '2022-09-25' + bug_reports: https://github.com/mlampros/fastGLCM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastGLCM + url_git: https://github.com/mlampros/fastGLCM +fastglm: + version: 0.0.3 + title: |- + Fast and Stable Fitting of Generalized Linear Models using + 'RcppEigen' + maintainer: Jared Huling + description: |- + Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares + implementation utilizes the step-halving approach of Marschner (2011) to help safeguard + against convergence issues. + date_publication: '2022-05-23' + bug_reports: https://github.com/jaredhuling/fastglm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastglm + url_git: '' +fastglmpca: + version: 0.1-103 + title: Fast Algorithms for Generalized Principal Component Analysis + maintainer: Eric Weine + description: |- + Implements fast, scalable optimization algorithms for + fitting generalized principal components analysis (GLM-PCA) models, + as described in "A Generalization of Principal Components + Analysis to the Exponential Family" Collins M, Dasgupta S, Schapire RE + (2002, ISBN:9780262271738), and subsequently "Feature Selection + and Dimension Reduction for Single-Cell RNA-Seq Based on a Multinomial + Model" Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) + . + date_publication: '2024-01-31' + bug_reports: https://github.com/stephenslab/fastglmpca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastglmpca + url_git: https://github.com/stephenslab/fastglmpca +FastGP: + version: '1.2' + title: Efficiently Using Gaussian Processes with Rcpp and RcppEigen + maintainer: Giri Gopalan + description: Contains Rcpp and RcppEigen implementations of matrix operations useful + for Gaussian process models, such as the inversion of a symmetric Toeplitz matrix, + sampling from multivariate normal distributions, evaluation of the log-density + of a multivariate normal vector, and Bayesian inference for latent variable Gaussian + process models with elliptical slice sampling (Murray, Adams, and MacKay 2010). + date_publication: '2016-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastGP + url_git: '' +fastGraph: + version: '2.1' + title: Fast Drawing and Shading of Graphs of Statistical Distributions + maintainer: Steven T. Garren + description: Provides functionality to produce graphs of probability density functions + and cumulative distribution functions with few keystrokes, allows shading under + the curve of the probability density function to illustrate concepts such as p-values + and critical values, and fits a simple linear regression line on a scatter plot + with the equation as the main title. + date_publication: '2019-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastGraph + url_git: '' +fastICA: + version: 1.2-7 + title: FastICA Algorithms to Perform ICA and Projection Pursuit + maintainer: Brian Ripley + description: |- + Implementation of FastICA algorithm to perform Independent + Component Analysis (ICA) and Projection Pursuit. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastICA + url_git: '' +FastImputation: + version: 2.2.1 + title: Learn from Training Data then Quickly Fill in Missing Data + maintainer: Stephen R. Haptonstahl + description: |- + TrainFastImputation() uses training data to describe a + multivariate normal distribution that the data approximates or + can be transformed into approximating and stores this information + as an object of class 'FastImputationPatterns'. FastImputation() + function uses this 'FastImputationPatterns' object to impute (make + a good guess at) missing data in a single line or a whole data frame + of data. This approximates the process used by 'Amelia' + but is much faster when + filling in values for a single line of data. + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastImputation + url_git: '' +FastJM: + version: 1.4.2 + title: Semi-Parametric Joint Modeling of Longitudinal and Survival Data + maintainer: Shanpeng Li + description: |- + Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and longitudinal data applying customized linear scan algorithms, proposed by Li and colleagues (2022) . + The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates. The longitudinal + outcome is modelled using a linear mixed effects model. The association is captured by shared random effects. The model + is estimated using an Expectation Maximization algorithm. + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastJM + url_git: '' +fastJT: + version: 1.0.6 + title: Efficient Jonckheere-Terpstra Test Statistics + maintainer: Alexander Sibley + description: This 'Rcpp'-based package implements highly efficient functions for + the calculation of the Jonckheere-Terpstra statistic. It can be used for a variety + of applications, including feature selection in machine learning problems, or + to conduct genome-wide association studies (GWAS) with multiple quantitative phenotypes. + The code leverages 'OpenMP' directives for multi-core computing to reduce overall + processing time. + date_publication: '2020-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastJT + url_git: '' +FastKM: + version: '1.1' + title: A Fast Multiple-Kernel Method Based on a Low-Rank Approximation + maintainer: Shannon T. Holloway + description: |- + A computationally efficient and statistically rigorous fast + Kernel Machine method for multi-kernel analysis. The approach is based on + a low-rank approximation to the nuisance effect kernel matrices. The + algorithm is applicable to continuous, binary, and survival traits and + is implemented using the existing single-kernel analysis software 'SKAT' + and 'coxKM'. 'coxKM' can be obtained from + . + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastKM + url_git: '' +fastkmedoids: + version: '1.2' + title: |- + Faster K-Medoids Clustering Algorithms: FastPAM, FastCLARA, + FastCLARANS + maintainer: Xun Li + description: R wrappers of C++ implementation of Faster K-Medoids clustering algorithms + (FastPAM, FastCLARA and FastCLARANS) proposed in Erich Schubert, Peter J. Rousseeuw + 2019 . + date_publication: '2021-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastkmedoids + url_git: '' +FastKNN: + version: 0.0.1 + title: Fast k-Nearest Neighbors + maintainer: Gaston Besanson + description: Compute labels for a test set according to the k-Nearest Neighbors + classification. This is a fast way to do k-Nearest Neighbors classification because + the distance matrix -between the features of the observations- is an input to + the function rather than being calculated in the function itself every time. + date_publication: '2015-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastKNN + url_git: '' +fastkqr: + version: 1.0.0 + title: A Fast Algorithm for Kernel Quantile Regression + maintainer: Qian Tang + description: An efficient algorithm to fit and tune kernel quantile regression models + based on the majorization-minimization (MM) method. It can also fit multiple quantile + curves simultaneously without crossing. + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastkqr + url_git: '' +fastLink: + version: 0.6.1 + title: Fast Probabilistic Record Linkage with Missing Data + maintainer: Ted Enamorado + description: |- + Implements a Fellegi-Sunter probabilistic record linkage model that allows for missing data + and the inclusion of auxiliary information. This includes functionalities to conduct a merge of two + datasets under the Fellegi-Sunter model using the Expectation-Maximization algorithm. In addition, + tools for preparing, adjusting, and summarizing data merges are included. The package implements methods + described in Enamorado, Fifield, and Imai (2019) ''Using a Probabilistic Model to Assist Merging of + Large-scale Administrative Records'' and is available + at . + date_publication: '2023-11-17' + bug_reports: https://github.com/kosukeimai/fastLink/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastLink + url_git: '' +fastliu: + version: '1.0' + title: |- + Fast Functions for Liu Regression with Regularization Parameter + and Statistics + maintainer: Murat Genç + description: |- + Efficient computation of the Liu regression coefficient paths, Liu-related statistics and + information criteria for a grid of the regularization parameter. + The computations are based on the 'C++' library 'Armadillo' through the 'R' package 'Rcpp'. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastliu + url_git: '' +fastLogisticRegressionWrap: + version: 1.2.0 + title: Fast Logistic Regression Wrapper + maintainer: Adam Kapelner + description: Provides very fast logistic regression with coefficient inferences + plus other useful methods such as a forward stepwise model generator (see the + benchmarks by visiting the github page at the URL below). The inputs are flexible + enough to accomodate GPU computations. The coefficient estimation employs the + fastLR() method in the 'RcppNumerical' package by Yixuan Qiu et al. This package + allows their work to be more useful to a wider community that consumes inference. + date_publication: '2023-08-08' + bug_reports: https://github.com/kapelner/fastLogisticRegressionWrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastLogisticRegressionWrap + url_git: https://github.com/kapelner/fastLogisticRegressionWrap +fastlogitME: + version: 0.1.0 + title: Basic Marginal Effects for Logit Models + maintainer: Mathieu Steijn + description: Calculates marginal effects based on logistic model objects such as + 'glm' or 'speedglm' at the average (default) or at given values using finite differences. + It also returns confidence intervals for said marginal effects and the p-values, + which can easily be used as input in stargazer. The function only returns the + essentials and is therefore much faster but not as detailed as other functions + available to calculate marginal effects. As a result, it is highly suitable for + large datasets for which other packages may require too much time or calculating + power. + date_publication: '2020-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastlogitME + url_git: '' +fastM: + version: 0.0-4 + title: Fast Computation of Multivariate M-Estimators + maintainer: Klaus Nordhausen + description: Implements the new algorithm for fast computation of M-scatter matrices + using a partial Newton-Raphson procedure for several estimators. The algorithm + is described in Duembgen, Nordhausen and Schuhmacher (2016) . + date_publication: '2018-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastM + url_git: '' +fastmap: + version: 1.2.0 + title: Fast Data Structures + maintainer: Winston Chang + description: |- + Fast implementation of data structures, including a key-value + store, stack, and queue. Environments are commonly used as key-value stores + in R, but every time a new key is used, it is added to R's global symbol + table, causing a small amount of memory leakage. This can be problematic in + cases where many different keys are used. Fastmap avoids this memory leak + issue by implementing the map using data structures in C++. + date_publication: '2024-05-15' + bug_reports: https://github.com/r-lib/fastmap/issues + url: https://r-lib.github.io/fastmap/ + url_cran: https://CRAN.R-project.org/package=fastmap + url_git: https://github.com/r-lib/fastmap +fastmatch: + version: 1.1-6 + title: Fast 'match()' Function + maintainer: Simon Urbanek + description: |- + Package providing a fast match() replacement for cases + that require repeated look-ups. It is slightly faster that R's + built-in match() function on first match against a table, but + extremely fast on any subsequent lookup as it keeps the hash + table in memory. + date_publication: '2024-12-23' + bug_reports: '' + url: http://www.rforge.net/fastmatch + url_cran: https://CRAN.R-project.org/package=fastmatch + url_git: '' +fastmatrix: + version: 0.5-7721 + title: Fast Computation of some Matrices Useful in Statistics + maintainer: Felipe Osorio + description: |- + Small set of functions to fast computation of some matrices and operations + useful in statistics and econometrics. Currently, there are functions for efficient + computation of duplication, commutation and symmetrizer matrices with minimal storage + requirements. Some commonly used matrix decompositions (LU and LDL), basic matrix + operations (for instance, Hadamard, Kronecker products and the Sherman-Morrison formula) + and iterative solvers for linear systems are also available. In addition, the package + includes a number of common statistical procedures such as the sweep operator, weighted + mean and covariance matrix using an online algorithm, linear regression (using Cholesky, + QR, SVD, sweep operator and conjugate gradients methods), ridge regression (with optimal + selection of the ridge parameter considering several procedures), omnibus tests for + univariate normality, functions to compute the multivariate skewness, kurtosis, the + Mahalanobis distance (checking the positive defineteness), and the Wilson-Hilferty + transformation of gamma variables. Furthermore, the package provides interfaces + to C code callable by another C code from other R packages. + date_publication: '2024-09-06' + bug_reports: '' + url: https://faosorios.github.io/fastmatrix/ + url_cran: https://CRAN.R-project.org/package=fastmatrix + url_git: '' +fastmit: + version: 0.1.1 + title: Fast Mutual Information Based Independence Test + maintainer: Shiyun Lin + description: A mutual information estimator based on k-nearest neighbor method proposed + by A. Kraskov, et al. (2004) to measure general + dependence and the time complexity for our estimator is only squared to the sample + size, which is faster than other statistics. Besides, an implementation of mutual + information based independence test is provided for analyzing multivariate data + in Euclidean space (T B. Berrett, et al. (2019) ); + furthermore, we extend it to tackle datasets in metric spaces. + date_publication: '2019-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastmit + url_git: '' +fastml: + version: 0.4.0 + title: Fast Machine Learning Model Training and Evaluation + maintainer: Selcuk Korkmaz + description: |- + Streamlines the training, evaluation, and comparison of multiple machine learning models with minimal code by providing + comprehensive data preprocessing and support for a wide range of algorithms with hyperparameter tuning. + It offers performance metrics and visualization tools to facilitate efficient and effective machine learning workflows. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastml + url_git: '' +fastNaiveBayes: + version: 2.2.1 + title: Extremely Fast Implementation of a Naive Bayes Classifier + maintainer: Martin Skogholt + description: |- + This is an extremely fast implementation of a Naive Bayes classifier. This + package is currently the only package that supports a Bernoulli distribution, a Multinomial + distribution, and a Gaussian distribution, making it suitable for both binary features, + frequency counts, and numerical features. Another feature is the support of a mix of + different event models. Only numerical variables are allowed, however, categorical variables + can be transformed into dummies and used with the Bernoulli distribution. + The implementation is largely based on the paper + "A comparison of event models for Naive Bayes anti-spam e-mail filtering" + written by K.M. Schneider (2003) . Any issues can be + submitted to: . + date_publication: '2020-05-04' + bug_reports: https://github.com/mskogholt/fastNaiveBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastNaiveBayes + url_git: https://github.com/mskogholt/fastNaiveBayes +fastnet: + version: 1.0.0 + title: Large-Scale Social Network Analysis + maintainer: Nazrul Shaikh + description: |- + We present an implementation of the algorithms required to simulate + large-scale social networks and retrieve their most relevant metrics. Details + can be found in the accompanying scientific paper on the Journal + of Statistical Software, . + date_publication: '2020-12-01' + bug_reports: https://github.com/networkgroupR/fastnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastnet + url_git: '' +fastOnlineCpt: + version: '1.0' + title: Online Multivariate Changepoint Detection + maintainer: Georg Hahn + description: Implementation of a simple algorithm designed for online multivariate + changepoint detection of a mean in sparse changepoint settings. The algorithm + is based on a modified cusum statistic and guarantees control of the type I error + on any false discoveries, while featuring O(1) time and O(1) memory updates per + series as well as a proven detection delay. + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastOnlineCpt + url_git: '' +FastPCS: + version: 0.1.4 + title: FastPCS Robust Fit of Multivariate Location and Scatter + maintainer: Kaveh Vakili + description: The FastPCS algorithm of Vakili and Schmitt (2014) + for robust estimation of multivariate location and scatter and multivariate outliers + detection. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastPCS + url_git: '' +fastPLS: + version: '0.2' + title: A Fast Implementation of Partial Least Square + maintainer: Stefano Cacciatore + description: An implementation in 'Rcpp' / 'RcppArmadillo' of Partial Least Square + algorithms. This package includes other functions to perform the double cross-validation + and a fast correlation. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastPLS + url_git: '' +fastplyr: + version: 0.5.1 + title: Fast Alternatives to 'tidyverse' Functions + maintainer: Nick Christofides + description: |- + A full set of fast data manipulation tools with a tidy + front-end and a fast back-end using 'collapse' and 'cheapr'. + date_publication: '2025-02-21' + bug_reports: https://github.com/NicChr/fastplyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastplyr + url_git: '' +fastpng: + version: 0.1.7 + title: |- + Read and Write PNG Files with Configurable Decoder/Encoder + Options + maintainer: Mike Cheng + description: |- + Read and write PNG images with arrays, rasters, native + rasters, numeric arrays, integer arrays, raw vectors and indexed + values. This PNG encoder exposes configurable internal options + enabling the user to select a speed-size tradeoff. For example, + disabling compression can speed up writing PNG by a factor of 50. + Multiple image formats are supported including raster, native rasters, + and integer and numeric arrays at color depths of 1, 2, 3 or 4. 16-bit + images are also supported. This implementation uses the 'libspng' 'C' + library which is available from + . + date_publication: '2025-01-14' + bug_reports: https://github.com/coolbutuseless/fastpng/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastpng + url_git: https://github.com/coolbutuseless/fastpng +fastpos: + version: 0.5.1 + title: |- + Finds the Critical Sequential Point of Stability for a Pearson + Correlation + maintainer: Johannes Titz + description: |- + Finds the critical sample size ("critical point of stability") for a + correlation to stabilize in Schoenbrodt and Perugini's definition of + sequential stability (see ). + date_publication: '2022-08-15' + bug_reports: https://github.com/johannes-titz/fastpos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastpos + url_git: https://github.com/johannes-titz/fastpos +fastqcr: + version: 0.1.3 + title: Quality Control of Sequencing Data + maintainer: Alboukadel Kassambara + description: |- + 'FASTQC' is the most widely used tool for evaluating the quality of high throughput sequencing data. + It produces, for each sample, an html report and a compressed file containing the raw data. + If you have hundreds of samples, you are not going to open up each 'HTML' page. + You need some way of looking at these data in aggregate. + 'fastqcr' Provides helper functions to easily parse, aggregate and analyze + 'FastQC' reports for large numbers of samples. It provides a convenient solution for building + a 'Multi-QC' report, as well as, a 'one-sample' report with result interpretations. + date_publication: '2023-02-18' + bug_reports: https://github.com/kassambara/fastqcr/issues + url: https://rpkgs.datanovia.com/fastqcr/index.html + url_cran: https://CRAN.R-project.org/package=fastqcr + url_git: '' +fastqq: + version: 0.1.3 + title: Faster Generation of Quantile Quantile Plots with Large Samples + maintainer: Gudmundur Einarsson + description: |- + New and faster implementations for quantile quantile plots. + The package also includes a function to prune data for quantile quantile + plots. This can drastically reduce the running time for large samples, + for 100 million samples, you can expect a factor 80X speedup. + date_publication: '2022-10-25' + bug_reports: https://github.com/gumeo/fastqq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastqq + url_git: https://github.com/gumeo/fastqq +fastR2: + version: 1.2.4 + title: Foundations and Applications of Statistics Using R (2nd Edition) + maintainer: Randall Pruim + description: |- + Data sets and utilities to accompany the second edition of + "Foundations and Applications of Statistics: an Introduction + using R" (R Pruim, published by AMS, 2017), a text covering + topics from probability and mathematical statistics at an advanced + undergraduate level. R is integrated throughout, and access to all + the R code in the book is provided via the snippet() function. + date_publication: '2023-11-09' + bug_reports: https://github.com/rpruim/fastR2/issues + url: http://rpruim.github.io/fastR2/ + url_cran: https://CRAN.R-project.org/package=fastR2 + url_git: https://github.com/rpruim/fastR2 +FastRCS: + version: 0.0.9 + title: Fits the FastRCS Robust Multivariable Linear Regression Model + maintainer: Kaveh Vakili + description: The FastRCS algorithm of Vakili and Schmitt (2014) for robust fit of + the multivariable linear regression model and outliers detection. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastRCS + url_git: '' +fastrep: + version: '0.7' + title: Time-Saving Package for Creating Reports + maintainer: Alisson Rosa + description: |- + Provides templates for reports in 'rmarkdown' and + functions to create tables and summaries of data. + date_publication: '2022-09-12' + bug_reports: https://github.com/AlissonRP/fastrep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastrep + url_git: '' +fastrerandomize: + version: '0.2' + title: Hardware-Accelerated Rerandomization for Improved Balance + maintainer: Connor Jerzak + description: |- + Provides hardware-accelerated tools for performing rerandomization + and randomization testing in experimental research. Using a 'JAX' backend, the + package enables exact rerandomization inference even for large experiments + with hundreds of billions of possible randomizations. Key functionalities + include generating pools of acceptable rerandomizations based on covariate + balance, conducting exact randomization tests, and performing pre-analysis + evaluations to determine optimal rerandomization acceptance thresholds. The + package supports various hardware acceleration frameworks including 'CPU', + 'CUDA', and 'METAL', making it versatile across accelerated computing environments. This + allows researchers to efficiently implement stringent rerandomization designs and + conduct valid inference even with large sample sizes. The package is partly based on Jerzak and Goldstein (2023) . + date_publication: '2025-01-14' + bug_reports: https://github.com/cjerzak/fastrerandomize-software/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastrerandomize + url_git: https://github.com/cjerzak/fastrerandomize-software +FastRet: + version: 1.1.4 + title: Retention Time Prediction in Liquid Chromatography + maintainer: Tobias Schmidt + description: |- + A framework for predicting retention times in liquid + chromatography. Users can train custom models for specific + chromatography columns, predict retention times using existing models, + or adjust existing models to account for altered experimental + conditions. The provided functionalities can be accessed either via + the R console or via a graphical user interface. Related work: Bonini + et al. (2020) . + date_publication: '2025-02-10' + bug_reports: https://github.com/spang-lab/FastRet/issues + url: https://spang-lab.github.io/FastRet/ + url_cran: https://CRAN.R-project.org/package=FastRet + url_git: https://github.com/spang-lab/FastRet/ +fastRG: + version: 0.3.2 + title: Sample Generalized Random Dot Product Graphs in Linear Time + maintainer: Alex Hayes + description: |- + Samples generalized random product graphs, a generalization of + a broad class of network models. Given matrices X, S, and Y with with + non-negative entries, samples a matrix with expectation X S Y^T and + independent Poisson or Bernoulli entries using the fastRG algorithm of + Rohe et al. (2017) . The + algorithm first samples the number of edges and then puts them down + one-by-one. As a result it is O(m) where m is the number of edges, a + dramatic improvement over element-wise algorithms that which require + O(n^2) operations to sample a random graph, where n is the number of + nodes. + date_publication: '2023-08-21' + bug_reports: https://github.com/RoheLab/fastRG/issues + url: https://rohelab.github.io/fastRG/ + url_cran: https://CRAN.R-project.org/package=fastRG + url_git: https://github.com/RoheLab/fastRG +fastRhockey: + version: 0.4.0 + title: |- + Functions to Access Premier Hockey Federation and National + Hockey League Play by Play Data + maintainer: Saiem Gilani + description: |- + A utility to scrape and load play-by-play data + and statistics from the Premier Hockey Federation (PHF) , formerly + known as the National Women's Hockey League (NWHL). Additionally, allows access to the National Hockey League's + stats API . + date_publication: '2022-10-25' + bug_reports: https://github.com/sportsdataverse/fastRhockey/issues + url: https://fastRhockey.sportsdataverse.org/ + url_cran: https://CRAN.R-project.org/package=fastRhockey + url_git: https://github.com/sportsdataverse/fastRhockey +fastrmodels: + version: 1.0.2 + title: Models for the 'nflfastR' Package + maintainer: Sebastian Carl + description: |- + A data package that hosts all models for the + 'nflfastR' package. + date_publication: '2021-02-20' + bug_reports: https://github.com/mrcaseb/fastrmodels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastrmodels + url_git: https://github.com/mrcaseb/fastrmodels +FastRWeb: + version: 1.2-1 + title: Fast Interactive Framework for Web Scripting Using R + maintainer: Simon Urbanek + description: Infrastrcture for creating rich, dynamic web content using R scripts + while maintaining very fast response time. + date_publication: '2023-11-28' + bug_reports: '' + url: http://www.rforge.net/FastRWeb/ + url_cran: https://CRAN.R-project.org/package=FastRWeb + url_git: '' +FastSF: + version: 0.1.1 + title: Fast Structural Filtering + maintainer: Canhong Wen + description: An implementation of the fast structural filtering with L0 penalty. + It includes an adaptive polynomial estimator by minimizing the least squares error + with constraints on the number of breaks in their (k + 1)-st discrete derivative, + for a chosen integer k >= 0. It also includes generalized structure sparsity constraint, + i.e., graph trend filtering. This package is implemented via the primal dual active + set algorithm, which formulates estimates and residuals as primal and dual variables, + and utilizes efficient active set selection strategies based on the properties + of the primal and dual variables. + date_publication: '2017-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastSF + url_git: '' +fastshap: + version: 0.1.1 + title: Fast Approximate Shapley Values + maintainer: Brandon Greenwell + description: |- + Computes fast (relative to other implementations) approximate + Shapley values for any supervised learning model. Shapley values help to + explain the predictions from any black box model using ideas from game + theory; see Strumbel and Kononenko (2014) + for details. + date_publication: '2024-02-22' + bug_reports: https://github.com/bgreenwell/fastshap/issues + url: https://bgreenwell.github.io/fastshap/ + url_cran: https://CRAN.R-project.org/package=fastshap + url_git: https://github.com/bgreenwell/fastshap +fastSOM: + version: 1.0.1 + title: Fast Calculation of Spillover Measures + maintainer: Stefan Kloessner + description: |- + Functions for computing spillover measures, especially spillover + tables and spillover indices, as well as their average, minimal, and maximal + values. + date_publication: '2019-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fastSOM + url_git: '' +FastStepGraph: + version: 0.1.1 + title: A Fast Algorithm for Sparse Precision Matrix Estimation + maintainer: Juan G. Colonna + description: |- + It implements an improved and computationally faster version + of the original Stepwise Gaussian Graphical Algorithm for estimating + the Omega precision matrix from high-dimensional data. + Zamar, R., Ruiz, M., Lafit, G. and Nogales, J. (2021) + . + date_publication: '2023-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FastStepGraph + url_git: https://github.com/juancolonna/FastStepGraph +fastText: + version: 1.0.4 + title: |- + Efficient Learning of Word Representations and Sentence + Classification + maintainer: Lampros Mouselimis + description: 'An interface to the ''fastText'' + library for efficient learning of word representations and sentence classification. + The ''fastText'' algorithm is explained in detail in (i) "Enriching Word Vectors + with subword Information", Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas + Mikolov, 2017, ; (ii) "Bag of Tricks for Efficient Text + Classification", Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov, + 2017, ; (iii) "FastText.zip: Compressing text classification + models", Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Herve + Jegou, Tomas Mikolov, 2016, .' + date_publication: '2024-02-17' + bug_reports: https://github.com/mlampros/fastText/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastText + url_git: https://github.com/mlampros/fastText +fastTextR: + version: 2.1.0 + title: An Interface to the 'fastText' Library + maintainer: Emil Hvitfeldt + description: |- + An interface to the 'fastText' library + . The package + can be used for text classification and to learn word vectors. + An example how to use 'fastTextR' can be found in the 'README' file. + date_publication: '2023-12-09' + bug_reports: https://github.com/EmilHvitfeldt/fastTextR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastTextR + url_git: https://github.com/EmilHvitfeldt/fastTextR +fasttime: + version: 1.1-0 + title: Fast Utility Function for Time Parsing and Conversion + maintainer: Simon Urbanek + description: |- + Fast functions for timestamp + manipulation that avoid system calls and take shortcuts + to facilitate operations on very large data. + date_publication: '2022-03-16' + bug_reports: '' + url: http://www.rforge.net/fasttime + url_cran: https://CRAN.R-project.org/package=fasttime + url_git: '' +fastTopics: + version: 0.6-192 + title: |- + Fast Algorithms for Fitting Topic Models and Non-Negative Matrix + Factorizations to Count Data + maintainer: Peter Carbonetto + description: |- + Implements fast, scalable optimization algorithms for + fitting topic models ("grade of membership" models) and + non-negative matrix factorizations to count data. The methods + exploit the special relationship between the multinomial topic + model (also, "probabilistic latent semantic indexing") and Poisson + non-negative matrix factorization. The package provides tools to + compare, annotate and visualize model fits, including functions to + efficiently create "structure plots" and identify key features in + topics. The 'fastTopics' package is a successor to the + 'CountClust' package. For more information, see + and + . Please also see the GitHub + repository for additional vignettes not included in the package on + CRAN. + date_publication: '2024-07-09' + bug_reports: https://github.com/stephenslab/fastTopics/issues + url: https://stephenslab.github.io/fastTopics/ + url_cran: https://CRAN.R-project.org/package=fastTopics + url_git: https://github.com/stephenslab/fastTopics +fastTS: + version: 1.0.2 + title: |- + Fast Time Series Modeling for Seasonal Series with Exogenous + Variables + maintainer: Ryan Andrew Peterson + description: |- + An implementation of sparsity-ranked lasso and related methods + for time series data. This methodology is especially useful for + large time series with exogenous features and/or complex + seasonality. Originally described in Peterson and Cavanaugh + (2022) in the context of variable + selection with interactions and/or polynomials, ranked sparsity is + a philosophy with methods useful for variable selection in the + presence of prior informational asymmetry. This situation exists for time + series data with complex seasonality, as shown in Peterson and Cavanaugh + (2024) , which also describes this package + in greater detail. The sparsity-ranked penalization methods for time series + implemented in 'fastTS' can fit large/complex/high-frequency time series + quickly, even with a high-dimensional exogenous feature set. The method is + considerably faster than its competitors, while often producing more + accurate predictions. Also included is a long hourly series of arrivals + into the University of Iowa Emergency Department with concurrent local + temperature. + date_publication: '2024-12-01' + bug_reports: https://github.com/petersonR/fastTS/issues + url: https://petersonr.github.io/fastTS/ + url_cran: https://CRAN.R-project.org/package=fastTS + url_git: https://github.com/petersonR/fastTS/ +FastUtils: + version: 0.2.1 + title: Fast, Readable Utility Functions + maintainer: Qile Yang + description: A wide variety of tools for general data analysis, wrangling, spelling, + statistics, visualizations, package development, and more. All functions have + vectorized implementations whenever possible. Exported names are designed to be + readable, with longer names possessing short aliases. + date_publication: '2024-08-17' + bug_reports: https://github.com/Qile0317/FastUtils/issues/ + url: https://qile0317.github.io/FastUtils/ + url_cran: https://CRAN.R-project.org/package=FastUtils + url_git: https://github.com/Qile0317/FastUtils +fastverse: + version: 0.3.4 + title: |- + A Suite of High-Performance Packages for Statistics and Data + Manipulation + maintainer: Sebastian Krantz + description: |- + Easy installation, loading and management, of high-performance packages + for statistical computing and data manipulation in R. + The core 'fastverse' consists of 4 packages: 'data.table', 'collapse', + 'kit' and 'magrittr', that jointly only depend on 'Rcpp'. + The 'fastverse' can be freely and permanently extended with + additional packages, both globally or for individual projects. + Separate package verses can also be created. Fast packages + for many common tasks such as time series, dates and times, strings, + spatial data, statistics, data serialization, larger-than-memory + processing, and compilation of R code are listed in the README file: + . + date_publication: '2024-10-08' + bug_reports: https://github.com/fastverse/fastverse/issues + url: https://fastverse.github.io/fastverse/ + url_cran: https://CRAN.R-project.org/package=fastverse + url_git: https://github.com/fastverse +fastVoteR: + version: 0.0.1 + title: Efficient Voting Methods for Committee Selection + maintainer: John Zobolas + description: |- + A fast 'Rcpp'-based implementation of polynomially-computable + voting theory methods for committee ranking and scoring. The package + includes methods such as Approval Voting (AV), Satisfaction Approval + Voting (SAV), sequential Proportional Approval Voting (PAV), and + sequential Phragmen's Rule. Weighted variants of these methods are + also provided, allowing for differential voter influence. + date_publication: '2024-11-27' + bug_reports: '' + url: https://bblodfon.github.io/fastVoteR/ + url_cran: https://CRAN.R-project.org/package=fastVoteR + url_git: '' +fastWavelets: + version: 1.0.1 + title: |- + Compute Maximal Overlap Discrete Wavelet Transform (MODWT) and À + Trous Discrete Wavelet Transform + maintainer: John You + description: |- + A lightweight package to compute Maximal Overlap Discrete Wavelet + Transform (MODWT) and À Trous Discrete Wavelet Transform by leveraging the + power of 'Rcpp' to make these operations fast. This package was designed for use in forecasting, and + allows users avoid the inclusion of future data when performing wavelet decomposition of time series. + See Quilty and Adamowski (2018) . + date_publication: '2022-11-18' + bug_reports: https://github.com/johnswyou/fastWavelets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fastWavelets + url_git: https://github.com/johnswyou/fastWavelets +fat2Lpoly: + version: 1.2.5 + title: Two-Locus Family-Based Association Test with Polytomous Outcome + maintainer: Alexandre BUREAU + description: |- + Performs family-based association tests with a polytomous outcome under 2-locus and 1-locus models + defined by some design matrix. + date_publication: '2022-01-04' + bug_reports: '' + url: https://www.cervo.ulaval.ca/pages_perso_chercheurs/bureau_a/ + url_cran: https://CRAN.R-project.org/package=fat2Lpoly + url_git: '' +FateID: + version: 0.2.2 + title: Quantification of Fate Bias in Multipotent Progenitors + maintainer: Dominic Grün + description: Application of 'FateID' allows computation and visualization of cell + fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, + Grün D. (2018) . + date_publication: '2022-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FateID + url_git: '' +FatTailsR: + version: 1.8-5 + title: Kiener Distributions and Fat Tails in Finance + maintainer: Patrice Kiener + description: |- + Kiener distributions K1, K2, K3, K4 and K7 to characterize + distributions with left and right, symmetric or asymmetric fat tails in market + finance, neuroscience and other disciplines. Two algorithms to estimate with + a high accuracy distribution parameters, quantiles, value-at-risk and expected + shortfall. Include power hyperbolas and power hyperbolic functions. + date_publication: '2024-03-03' + bug_reports: '' + url: https://www.inmodelia.com/fattailsr-en.html + url_cran: https://CRAN.R-project.org/package=FatTailsR + url_git: '' +FaultTree: + version: 1.0.1 + title: Fault Trees for Risk and Reliability Analysis + maintainer: Jacob Ormerod + description: 'Construction, calculation and display of fault trees. Methods derived + from Clifton A. Ericson II (2005, ISBN: 9780471739425) , + Antoine Rauzy (1993) , Tim Bedford and Roger + Cooke (2012, ISBN: 9780511813597) , Nikolaos Limnios, (2007, + ISBN: 9780470612484) .' + date_publication: '2023-08-26' + bug_reports: '' + url: http://www.openreliability.org/fault-tree-analysis-on-r/ + url_cran: https://CRAN.R-project.org/package=FaultTree + url_git: '' +faux: + version: 1.2.2 + title: Simulation for Factorial Designs + maintainer: Lisa DeBruine + description: Create datasets with factorial structure through simulation by specifying + variable parameters. Extended documentation at . + Described in DeBruine (2020) . + date_publication: '2025-01-15' + bug_reports: https://github.com/debruine/faux/issues + url: https://debruine.github.io/faux/ + url_cran: https://CRAN.R-project.org/package=faux + url_git: https://github.com/debruine/faux +fauxnaif: + version: 0.7.1 + title: Convert Values to NA + maintainer: Alexander Rossell Hayes + description: |- + Provides a replacement for dplyr::na_if(). Allows you to + specify multiple values to be replaced with NA using a single + function. + date_publication: '2022-08-12' + bug_reports: https://github.com/rossellhayes/fauxnaif/issues + url: https://fauxnaif.rossellhayes.com/ + url_cran: https://CRAN.R-project.org/package=fauxnaif + url_git: https://github.com/rossellhayes/fauxnaif +fauxpas: + version: 0.5.2 + title: HTTP Error Helpers + maintainer: Scott Chamberlain + description: |- + HTTP error helpers. Methods included for general purpose HTTP + error handling, as well as individual methods for every HTTP status + code, both via status code numbers as well as their descriptive names. + Supports ability to adjust behavior to stop, message or warning. + Includes ability to use custom whisker template to have any configuration + of status code, short description, and verbose message. Currently + supports integration with 'crul', 'curl', and 'httr'. + date_publication: '2023-05-03' + bug_reports: https://github.com/sckott/fauxpas/issues + url: https://sckott.github.io/fauxpas/ + url_cran: https://CRAN.R-project.org/package=fauxpas + url_git: https://github.com/sckott/fauxpas +FAVA: + version: 1.0.7 + title: |- + Quantify Compositional Variability Across Relative Abundance + Vectors + maintainer: Maike Morrison + description: |- + Implements the statistic FAVA, an Fst-based Assessment of Variability across + vectors of relative Abundances, as well as a suite of helper functions which enable the + visualization and statistical analysis of relative abundance data. The 'FAVA' R package + accompanies the paper, “Quantifying compositional variability in microbial communities + with FAVA” by Morrison, Xue, and Rosenberg (2024) . + date_publication: '2024-12-10' + bug_reports: https://github.com/MaikeMorrison/FAVA/issues + url: https://maikemorrison.github.io/FAVA/ + url_cran: https://CRAN.R-project.org/package=FAVA + url_git: '' +FAVAR: + version: 0.1.3 + title: Bayesian Analysis of a FAVAR Model + maintainer: Pu Chen + description: Estimate a FAVAR model by a Bayesian method, based on Bernanke et al. + (2005) . + date_publication: '2022-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAVAR + url_git: '' +favawesome: + version: 0.1.1 + title: '''Font Awesome'' Icons as ''shiny'' ''favicons''' + maintainer: Jon Harmon + description: |- + Easily use 'Font Awesome' icons as 'shiny' 'favicons' (the + icons that appear on browser tabs). 'Font Awesome' + () is a popular set of icons that can be used in + web pages. 'favawesome' provides a simple way to use these icons as + 'favicons' in 'shiny' applications and other HTML pages. + date_publication: '2024-11-01' + bug_reports: https://github.com/shinyworks/favawesome/issues + url: https://favawesome.shinyworks.org + url_cran: https://CRAN.R-project.org/package=favawesome + url_git: https://github.com/shinyworks/favawesome +faviconPlease: + version: 0.1.3 + title: Find the URL to the 'Favicon' for a Website + maintainer: John Blischak + description: |- + Finds the URL to the 'favicon' for a website. This is useful if you + want to display the 'favicon' in an HTML document or web application, + especially if the website is behind a firewall. + date_publication: '2023-08-10' + bug_reports: https://github.com/jdblischak/faviconPlease/issues + url: '' + url_cran: https://CRAN.R-project.org/package=faviconPlease + url_git: https://github.com/jdblischak/faviconPlease +favnums: + version: 1.0.0 + title: A Dataset of Favourite Numbers + maintainer: Oliver Keyes + description: |- + A dataset of favourite numbers, selected from an online poll of over 30,000 people by Alex Bellos + (http://pages.bloomsbury.com/favouritenumber). + date_publication: '2015-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=favnums + url_git: '' +FAwR: + version: 1.1.2 + title: Functions and Datasets for "Forest Analytics with R" + maintainer: Andrew Robinson + description: Provides functions and datasets from the book "Forest Analytics with + R". + date_publication: '2020-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FAwR + url_git: '' +fbar: + version: 0.6.0 + title: An Extensible Approach to Flux Balance Analysis + maintainer: Max Conway + description: |- + A toolkit for Flux Balance Analysis and related + metabolic modeling techniques. Functions are provided for: parsing + models in tabular format, converting parsed metabolic models to input + formats for common linear programming solvers, and + evaluating and applying gene-protein-reaction mappings. In addition, there + are wrappers to parse a model, select a solver, find the metabolic fluxes, + and return the results applied to the original model. Compared to other + packages in this field, this package puts a much heavier focus on + providing reusable components that can be used in the design of new + implementation of new techniques, in particular those that involve large + parameter sweeps. For a background on the theory, see What is Flux Balance + Analysis . + date_publication: '2020-09-02' + bug_reports: https://github.com/maxconway/fbar/issues + url: http://maxconway.github.io/fbar/ + url_cran: https://CRAN.R-project.org/package=fbar + url_git: https://github.com/maxconway/fbar +fBasics: + version: '4041.97' + title: Rmetrics - Markets and Basic Statistics + maintainer: Georgi N. Boshnakov + description: |- + Provides a collection of functions to + explore and to investigate basic properties of financial returns + and related quantities. + The covered fields include techniques of explorative data analysis + and the investigation of distributional properties, including + parameter estimation and hypothesis testing. Even more there are + several utility functions for data handling and management. + date_publication: '2024-08-19' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://geobosh.github.io/fBasicsDoc/(doc) + url_cran: https://CRAN.R-project.org/package=fBasics + url_git: https://r-forge.r-project.org/scm/viewvc.php/pkg/fBasics/?root=rmetrics(devel) +fbati: + version: 1.0-11 + title: |- + Gene by Environment Interaction and Conditional Gene Tests for + Nuclear Families + maintainer: Thomas Hoffmann + description: Does family-based gene by environment interaction tests, joint gene, + gene-environment interaction test, and a test of a set of genes conditional on + another set of genes. + date_publication: '2025-02-01' + bug_reports: '' + url: https://doi.org/10.1111/j.1541-0420.2011.01581.x + url_cran: https://CRAN.R-project.org/package=fbati + url_git: '' +FBCRM: + version: '1.1' + title: |- + Phase I Optimal Dose Assignment using the FBCRM and MFBCRM + Methods + maintainer: Andrew G Chapple + description: Performs dose assignment and trial simulation for the FBCRM (Fully + Bayesian Continual Reassessment Method) and MFBCRM (Mixture Fully Bayesian Continual + Reassessment Method) phase I clinical trial designs. These trial designs extend + the Continual Reassessment Method (CRM) and Bayesian Model Averaging Continual + Reassessment Method (BMA-CRM) by allowing the prior toxicity skeleton itself to + be random, with posterior distributions obtained from Markov Chain Monte Carlo. + On average, the FBCRM and MFBCRM methods outperformed the CRM and BMA-CRM methods + in terms of selecting an optimal dose level across thousands of randomly generated + simulation scenarios. Details on the methods and results of this simulation study + are available on request, and the manuscript is currently under review. + date_publication: '2022-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FBCRM + url_git: '' +FBFsearch: + version: '1.2' + title: |- + Algorithm for Searching the Space of Gaussian Directed Acyclic + Graph Models Through Moment Fractional Bayes Factors + maintainer: Davide Altomare + description: 'We propose an objective Bayesian algorithm for searching the space + of Gaussian directed acyclic graph (DAG) models. The algorithm proposed makes + use of moment fractional Bayes factors (MFBF) and thus it is suitable for learning + sparse graph. The algorithm is implemented by using Armadillo: an open-source + C++ linear algebra library.' + date_publication: '2022-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FBFsearch + url_git: '' +fbglm: + version: 1.5.0 + title: Fractional Binomial Regression Model + maintainer: Jeonghwa Lee + description: |- + Fit a fractional binomial regression model and + extended zero-inflated negative binomial regression + model to count data with excess zeros using maximum + likelihood estimation. + Compare zero-inflated regression models via Vuong + closeness test. + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fbglm + url_git: '' +FBMS: + version: '1.1' + title: Flexible Bayesian Model Selection and Model Averaging + maintainer: Jon Lachmann + description: Implements the Mode Jumping Markov Chain Monte Carlo algorithm described + in and its Genetically Modified counterpart described + in as well as the sub-sampling versions described in + for flexible Bayesian model selection and model + averaging. + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FBMS + url_git: '' +FBN: + version: 1.5.2 + title: |- + FISH Based Normalization and Copy Number Inference of SNP + Microarray Data + maintainer: Luca Agnelli + description: Normalizes the data from a file containing the raw values of the SNP + probes of microarray data by using the FISH probes and their corresponding copy + number. + date_publication: '2023-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FBN + url_git: '' +fbnet: + version: 1.0.4 + title: Forensic Bayesian Networks + maintainer: Franco Marsico + description: Open-source package for computing likelihood ratios in kinship testing + and human identification cases. It has the core function of the software GENis, + developed by Fundación Sadosky. It relies on a Bayesian Networks framework and + is particularly well suited to efficiently perform large-size queries against + databases of missing individuals. + date_publication: '2025-02-04' + bug_reports: https://github.com/MarsicoFL/fbnet/issues + url: https://marsicofl.github.io/fbnet/ + url_cran: https://CRAN.R-project.org/package=fbnet + url_git: https://github.com/MarsicoFL/fbnet +fBonds: + version: '3042.78' + title: Rmetrics - Pricing and Evaluating Bonds + maintainer: Tobias Setz + description: |- + It implements the Nelson-Siegel and the Nelson-Siegel-Svensson + term structures. + date_publication: '2017-11-15' + bug_reports: '' + url: http://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fBonds + url_git: '' +fbRads: + version: 17.0.0 + title: Analyzing and Managing Facebook Ads from R + maintainer: Gergely Daroczi + description: |- + Wrapper functions around the Facebook Marketing 'API' to create, + read, update and delete custom audiences, images, campaigns, ad sets, ads and + related content. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fbRads + url_git: https://github.com/daroczig/fbRads +fbroc: + version: 0.4.1 + title: |- + Fast Algorithms to Bootstrap Receiver Operating Characteristics + Curves + maintainer: Erik Peter + description: |- + Implements a very fast C++ algorithm to quickly bootstrap receiver + operating characteristics (ROC) curves and derived performance metrics, + including the area under the curve (AUC) and the partial area under the curve as well as + the true and false positive rate. The analysis of paired receiver operating curves is supported as well, + so that a comparison of two predictors is possible. You can also plot the + results and calculate confidence intervals. On a typical desktop computer the time needed for + the calculation of 100000 bootstrap replicates given 500 observations requires time on the + order of magnitude of one second. + date_publication: '2019-03-24' + bug_reports: http://github.com/erikpeter/fbroc/issues + url: http://www.epeter-stats.de/roc-curve-analysis-with-fbroc/ + url_cran: https://CRAN.R-project.org/package=fbroc + url_git: '' +fbst: + version: '2.2' + title: |- + The Full Bayesian Evidence Test, Full Bayesian Significance Test + and the e-Value + maintainer: Riko Kelter + description: Provides access to a range of functions for computing and visualizing + the Full Bayesian Significance Test (FBST) and the e-value for testing a sharp + hypothesis against its alternative, and the Full Bayesian Evidence Test (FBET) + and the (generalized) Bayesian evidence value for testing a composite (or interval) + hypothesis against its alternative. The methods are widely applicable as long + as a posterior MCMC sample is available. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fbst + url_git: '' +fc: + version: 0.1.0 + title: Standard Evaluation-Based Multivariate Function Composition + maintainer: Xiaofei (Susan) Wang + description: Provides a streamlined, standard evaluation-based approach to multivariate + function composition. Allows for chaining commands via a forward-pipe operator, + %>%. + date_publication: '2018-08-14' + bug_reports: https://github.com/swang87/fc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fc + url_git: https://github.com/swang87/fc +fca: + version: 0.1.0 + title: |- + Floating Catchment Area (FCA) Methods to Calculate Spatial + Accessibility + maintainer: Etienne Grueebler + description: |- + Perform various floating catchment area methods to calculate a + spatial accessibility index (SPAI) for demand point data. The distance + matrix used for weighting is normalized in a preprocessing step using + common functions (gaussian, gravity, exponential or logistic). + date_publication: '2021-12-06' + bug_reports: https://github.com/egrueebler/fca/issues/ + url: https://egrueebler.github.io/fca/ + url_cran: https://CRAN.R-project.org/package=fca + url_git: https://github.com/egrueebler/fca/ +fcaR: + version: 1.2.2 + title: Formal Concept Analysis + maintainer: Domingo Lopez Rodriguez + description: |- + Provides tools to perform fuzzy formal concept + analysis, presented in Wille (1982) + and in Ganter and Obiedkov (2016) . It + provides functions to load and save a formal context, extract its + concept lattice and implications. In addition, one can use the + implications to compute semantic closures of fuzzy sets and, thus, + build recommendation systems. + date_publication: '2023-11-30' + bug_reports: https://github.com/Malaga-FCA-group/fcaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fcaR + url_git: https://github.com/Malaga-FCA-group/fcaR +fcci: + version: 1.0.1 + title: Feldman-Cousins Confidence Intervals + maintainer: Valerio Gherardi + description: |2- + + Provides support for building Feldman-Cousins confidence intervals + [G. J. Feldman and R. D. Cousins (1998) ]. + date_publication: '2022-01-07' + bug_reports: https://github.com/vgherard/fcci/issues + url: https://vgherard.github.io/fcci/ + url_cran: https://CRAN.R-project.org/package=fcci + url_git: https://github.com/vgherard/fcci +fcfdr: + version: 1.0.0 + title: Flexible cFDR + maintainer: Anna Hutchinson + description: Provides functions to implement the Flexible cFDR (Hutchinson et al. + (2021) ) and Binary cFDR (Hutchinson et al. + (2021) ) methodologies to leverage auxiliary data + from arbitrary distributions, for example functional genomic data, with GWAS p-values + to generate re-weighted p-values. + date_publication: '2022-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fcfdr + url_git: '' +fcirt: + version: 0.1.0 + title: Forced Choice in Item Response Theory + maintainer: Naidan Tu + description: Bayesian estimation of forced choice models in Item Response Theory + using 'rstan' (See Stan Development Team (2020) ). + date_publication: '2022-02-01' + bug_reports: https://github.com/Naidantu/fcirt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fcirt + url_git: https://github.com/Naidantu/fcirt +fcl: + version: 0.1.3 + title: A Financial Calculator + maintainer: Xianying Tan + description: |- + A financial calculator that provides very fast implementations + of common financial indicators using 'Rust' code. It includes functions for + bond-related indicators, such as yield to maturity ('YTM'), modified duration, + and Macaulay duration, as well as functions for calculating time-weighted + and money-weighted rates of return (using 'Modified Dietz' method) for multiple portfolios, + given their market values and profit and loss ('PnL') data. 'fcl' is designed + to be efficient and accurate for financial analysis and computation. The methods + used in this package are based on the following references: + , + . + date_publication: '2024-11-26' + bug_reports: https://github.com/shrektan/fcl/issues + url: https://shrektan.github.io/fcl/ + url_cran: https://CRAN.R-project.org/package=fcl + url_git: https://github.com/shrektan/fcl +fclust: + version: 2.1.1.1 + title: Fuzzy Clustering + maintainer: Paolo Giordani + description: Algorithms for fuzzy clustering, cluster validity indices and plots + for cluster validity and visualizing fuzzy clustering results. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fclust + url_git: '' +fcm: + version: 0.1.3 + title: Inference of Fuzzy Cognitive Maps (FCMs) + maintainer: Zoumpoulia Dikopoulou + description: Provides a selection of 3 different inference rules (including additionally + the clamped types of the referred inference rules) and 4 threshold functions in + order to obtain the inference of the FCM (Fuzzy Cognitive Map). Moreover, the + 'fcm' package returns a data frame of the concepts' values of each state after + the inference procedure. Fuzzy cognitive maps were introduced by Kosko (1986) + providing ideal causal cognition tools for modeling + and simulating dynamic systems. + date_publication: '2017-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fcm + url_git: '' +FCMapper: + version: '1.1' + title: Fuzzy Cognitive Mapping + maintainer: Shaun Turney + description: |- + Provides several functions to create and manipulate fuzzy + cognitive maps. It is based on 'FCMapper' for Excel, distributed at , developed by Michael Bachhofer and Martin Wildenberg. + Maps are inputted as adjacency matrices. Attributes of the maps and the + equilibrium values of the concepts (including with user-defined constrained + values) can be calculated. The maps can be graphed with a function that calls + 'igraph'. Multiple maps with shared concepts can be aggregated. + date_publication: '2016-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FCMapper + url_git: '' +FCO: + version: 0.8.0 + title: |- + Flexible Cutoffs for Model Fit Evaluation in Covariance-Based + Structural Models + maintainer: Thomas Niemand + description: A toolbox to derive flexible cutoffs for fit indices in 'Covariance-based + Structural Equation Modeling' based on the paper by 'Niemand & Mai (2018)' . + Flexible cutoffs are an alternative to fixed cutoffs - rules-of-thumb - regarding + an appropriate cutoff for fit indices such as 'CFI' or 'SRMR'. It has been demonstrated + that these flexible cutoffs perform better than fixed cutoffs in grey areas where + misspecification is not easy to detect. The package provides an alternative to + the tool at as it allows to tailor flexible cutoffs + to a given dataset and model, which is so far not available in the tool. The package + simulates fit indices based on a given dataset and model and then estimates the + flexible cutoffs. Some useful functions, e.g., to determine the 'GoF-' or 'BoF-nature' + of a fit index, are provided. So far, additional options for a relative use (is + a model better than another?) are provided in an exploratory manner. + date_publication: '2023-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FCO + url_git: '' +fCopulae: + version: '4022.85' + title: Rmetrics - Bivariate Dependence Structures with Copulae + maintainer: Paul Smith + description: |- + Provides a collection of functions to + manage, to investigate and to analyze bivariate financial returns by + Copulae. Included are the families of Archemedean, Elliptical, + Extreme Value, and Empirical Copulae. + date_publication: '2023-01-07' + bug_reports: '' + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fCopulae + url_git: '' +fcp: + version: 0.1.0 + title: Function Composition + maintainer: Xiaoran Tong + description: A function composition operator to chain a series of calls into a single + function, mimicking the math notion of (f o g o h)(x) = h(g(f(x))). Inspired by + 'pipeOp' ('|>') since R4.1 and 'magrittr pipe' ('%>%'), the operator build a pipe + without putting data through, which is best for anonymous function accepted by + utilities such as apply() and lapply(). + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fcp + url_git: https://github.com/xiaoran831213/R_fun_comp +FCPS: + version: 1.3.4 + title: Fundamental Clustering Problems Suite + maintainer: Michael Thrun + description: 'Over sixty clustering algorithms are provided in this package with + consistent input and output, which enables the user to try out algorithms swiftly. + Additionally, 26 statistical approaches for the estimation of the number of clusters + as well as the mirrored density plot (MD-plot) of clusterability are implemented. + The packages is published in Thrun, M.C., Stier Q.: "Fundamental Clustering Algorithms + Suite" (2021), SoftwareX, . Moreover, the fundamental + clustering problems suite (FCPS) offers a variety of clustering challenges any + algorithm should handle when facing real world data, see Thrun, M.C., Ultsch A.: + "Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems" + (2020), Data in Brief, .' + date_publication: '2023-10-19' + bug_reports: https://github.com/Mthrun/FCPS/issues + url: https://www.deepbionics.org/ + url_cran: https://CRAN.R-project.org/package=FCPS + url_git: '' +fcr: + version: '1.0' + title: Functional Concurrent Regression for Sparse Data + maintainer: Andrew Leroux + description: Dynamic prediction in functional concurrent regression with an application + to child growth. Extends the pffr() function from the 'refund' package to handle + the scenario where the functional response and concurrently measured functional + predictor are irregularly measured. Leroux et al. (2017), Statistics in Medicine, + . + date_publication: '2018-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fcr + url_git: '' +fcros: + version: 1.6.1 + title: |- + A Method to Search for Differentially Expressed Genes and to + Detect Recurrent Chromosomal Copy Number Aberrations + maintainer: Doulaye Dembele + description: |- + A fold change rank based method is presented to search for genes with changing + expression and to detect recurrent chromosomal copy number aberrations. This + method may be useful for high-throughput biological data (micro-array, sequencing, ...). + Probabilities are associated with genes or probes in the data set and there is no + problem of multiple tests when using this method. For array-based comparative genomic + hybridization data, segmentation results are obtained by merging the significant + probes detected. + date_publication: '2019-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fcros + url_git: '' +fctbases: + version: 1.1.1 + title: Functional Bases + maintainer: Niels Olsen + description: |- + Easy-to-use, very fast implementation of various functional bases. Easily used together with other packages. + A functional basis is a collection of basis functions [\phi_1, ..., \phi_n] that can represent a smooth function, i.e. $f(t) = \sum c_k \phi_k(t)$. + First- and second-order derivatives are also included. These are the mathematically correct ones, no approximations applied. + As of version 1.1, this package includes B-splines, Fourier bases and polynomials. + date_publication: '2022-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fctbases + url_git: https://github.com/naolsen/fctbases +fctutils: + version: 0.0.7 + title: Advanced Factor Manipulation Utilities + maintainer: Kai Guo + description: Provides a collection of utility functions for manipulating and analyzing + factor vectors in R. It offers tools for filtering, splitting, combining, and + reordering factor levels based on various criteria. The package is designed to + simplify common tasks in categorical data analysis, making it easier to work with + factors in a flexible and efficient manner. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fctutils + url_git: '' +fcuk: + version: 0.1.21 + title: The Ultimate Helper for Clumsy Fingers + maintainer: Vincent Guyader + description: Automatically suggests a correction when a typo occurs. + date_publication: '2017-07-08' + bug_reports: https://github.com/ThinkRstat/fcuk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fcuk + url_git: https://github.com/ThinkRstat/fcuk +FCVAR: + version: 0.1.4 + title: Estimation and Inference for the Fractionally Cointegrated VAR + maintainer: Lealand Morin + description: |- + Estimation and inference using the Fractionally Cointegrated + Vector Autoregressive (VAR) model. It includes functions for model specification, + including lag selection and cointegration rank selection, as well as a comprehensive + set of options for hypothesis testing, including tests of hypotheses on the + cointegrating relations, the adjustment coefficients and the fractional + differencing parameters. + An article describing the FCVAR model with examples is available on the Webpage + . + date_publication: '2022-05-05' + bug_reports: https://github.com/LeeMorinUCF/FCVAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FCVAR + url_git: https://github.com/LeeMorinUCF/FCVAR +FD: + version: 1.0-12.3 + title: |- + Measuring Functional Diversity (FD) from Multiple Traits, and + Other Tools for Functional Ecology + maintainer: Etienne Laliberté + description: Computes different multidimensional FD indices. Implements a distance-based + framework to measure FD that allows any number and type of functional traits, + and can also consider species relative abundances. Also contains other useful + tools for functional ecology. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FD + url_git: '' +fda: + version: 6.2.0 + title: Functional Data Analysis + maintainer: James Ramsay + description: |- + These functions were developed to support functional data + analysis as described in Ramsay, J. O. and Silverman, B. W. + (2005) Functional Data Analysis. New York: Springer and in + Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). + Functional Data Analysis with R and Matlab (Springer). + The package includes data sets and script files working many examples + including all but one of the 76 figures in this latter book. Matlab versions + are available by ftp from + . + date_publication: '2024-09-17' + bug_reports: '' + url: http://www.functionaldata.org + url_cran: https://CRAN.R-project.org/package=fda + url_git: '' +fda.usc: + version: 2.2.0 + title: Functional Data Analysis and Utilities for Statistical Computing + maintainer: Manuel Oviedo de la Fuente + description: Routines for exploratory and descriptive analysis of functional data + such as depth measurements, atypical curves detection, regression models, supervised + classification, unsupervised classification and functional analysis of variance. + date_publication: '2024-11-09' + bug_reports: https://github.com/moviedo5/fda.usc/issues + url: https://moviedo5.github.io/fda.usc/ + url_cran: https://CRAN.R-project.org/package=fda.usc + url_git: https://github.com/moviedo5/fda.usc +fdaACF: + version: 1.0.0 + title: Autocorrelation Function for Functional Time Series + maintainer: Guillermo Mestre Marcos + description: |- + Quantify the serial correlation across lags of a given functional + time series using the autocorrelation function and a partial autocorrelation + function for functional time series proposed in + Mestre et al. (2021) . + The autocorrelation functions are based on the L2 norm of the lagged covariance + operators of the series. Functions are available for estimating the + distribution of the autocorrelation functions under the assumption + of strong functional white noise. + date_publication: '2020-10-20' + bug_reports: https://github.com/GMestreM/fdaACF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdaACF + url_git: https://github.com/GMestreM/fdaACF +fdacluster: + version: 0.4.1 + title: Joint Clustering and Alignment of Functional Data + maintainer: Aymeric Stamm + description: |- + Implementations of the k-means, hierarchical agglomerative and + DBSCAN clustering methods for functional data which allows for jointly + aligning and clustering curves. It supports functional data defined on + one-dimensional domains but possibly evaluating in multivariate codomains. + It supports functional data defined in arrays but also via the 'fd' and + 'funData' classes for functional data defined in the 'fda' and 'funData' + packages respectively. It currently supports shift, dilation and affine + warping functions for functional data defined on the real line and uses the + SRVF framework to handle boundary-preserving warping for functional data + defined on a specific interval. Main reference for the k-means algorithm: + Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment + for curve clustering" . Main reference for + the SRVF framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013) + "Generative models for functional data using phase and amplitude separation" + . + date_publication: '2025-01-14' + bug_reports: '' + url: https://astamm.github.io/fdacluster/ + url_cran: https://CRAN.R-project.org/package=fdacluster + url_git: https://github.com/astamm/fdacluster +fdaconcur: + version: 0.1.3 + title: |- + Concurrent Regression and History Index Models for Functional + Data + maintainer: Su I Iao + description: |- + Provides an implementation of concurrent or varying coefficient regression methods for + functional data. The implementations are done for both dense and sparsely observed functional + data. Pointwise confidence bands can be constructed for each case. Further, the influence of + past predictor values are modeled by a smooth history index function, + while the effects on the response are described by smooth varying coefficient functions, + which are very useful in analyzing real data such as COVID data. + References: Yao, F., Müller, H.G., Wang, J.L. (2005) . + Sentürk, D., Müller, H.G. (2010) . + date_publication: '2024-07-20' + bug_reports: https://github.com/functionaldata/tFDAconcur/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdaconcur + url_git: https://github.com/functionaldata/tFDAconcur +fdadensity: + version: 0.1.2 + title: |- + Functional Data Analysis for Density Functions by Transformation + to a Hilbert Space + maintainer: Alexander Petersen + description: |- + An implementation of the methodology described in + Petersen and Mueller (2016) for the functional + data analysis of samples of density functions. Densities are first + transformed to their corresponding log quantile densities, followed by + ordinary Functional Principal Components Analysis (FPCA). Transformation + modes of variation yield improved interpretation of the variability in the + data as compared to FPCA on the densities themselves. The standard + fraction of variance explained (FVE) criterion commonly used for functional + data is adapted to the transformation setting, also allowing for an + alternative quantification of variability for density data through the + Wasserstein metric of optimal transport. + date_publication: '2019-12-05' + bug_reports: https://github.com/functionaldata/tDENS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdadensity + url_git: https://github.com/functionaldata/tDENS +fdaMixed: + version: 0.6.1 + title: Functional Data Analysis in a Mixed Model Framework + maintainer: Bo Markussen + description: |- + Likelihood based analysis of 1-dimension functional data + in a mixed-effects model framework. Matrix computation are + approximated by semi-explicit operator equivalents with linear + computational complexity. Markussen (2013) . + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdaMixed + url_git: '' +fdaMocca: + version: 0.1-1 + title: Model-Based Clustering for Functional Data with Covariates + maintainer: Natalya Pya Arnqvist + description: Routines for model-based functional cluster analysis for functional + data with optional covariates. The idea is to cluster functional subjects (often + called functional objects) into homogenous groups by using spline smoothers (for + functional data) together with scalar covariates. The spline coefficients and + the covariates are modelled as a multivariate Gaussian mixture model, where the + number of mixtures corresponds to the number of clusters. The parameters of the + model are estimated by maximizing the observed mixture likelihood via an EM algorithm + (Arnqvist and Sjöstedt de Luna, 2019) . The clustering method + is used to analyze annual lake sediment from lake Kassjön (Northern Sweden) which + cover more than 6400 years and can be seen as historical records of weather and + climate. + date_publication: '2022-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdaMocca + url_git: '' +fdANOVA: + version: 0.1.2 + title: |- + Analysis of Variance for Univariate and Multivariate Functional + Data + maintainer: Lukasz Smaga + description: Performs analysis of variance testing procedures for univariate and + multivariate functional data (Cuesta-Albertos and Febrero-Bande (2010) , + Gorecki and Smaga (2015) , Gorecki and Smaga (2017) + , Zhang et al. (2018) ). + date_publication: '2018-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdANOVA + url_git: '' +fdaoutlier: + version: 0.2.1 + title: Outlier Detection Tools for Functional Data Analysis + maintainer: Oluwasegun Taiwo Ojo + description: |- + A collection of functions for outlier detection in functional data analysis. + Methods implemented include directional outlyingness by + Dai and Genton (2019) , + MS-plot by Dai and Genton (2018) , + total variation depth and modified shape similarity index by + Huang and Sun (2019) , and sequential transformations by + Dai et al. (2020) ; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) . + date_publication: '2024-07-03' + bug_reports: https://github.com/functionaldata/tPACE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdapace + url_git: https://github.com/functionaldata/tPACE +fdapaceShiny: + version: 1.0.5 + title: A Shiny App for the 'fdapace' Package + maintainer: Camden Possinger + description: Shiny app for the 'fdapace' package. + date_publication: '2021-11-11' + bug_reports: https://github.com/cpossinger/fdapaceShiny/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdapaceShiny + url_git: https://github.com/cpossinger/fdapaceShiny +fdaPDE: + version: 1.1-21 + title: Physics-Informed Spatial and Functional Data Analysis + maintainer: Eleonora Arnone + description: An implementation of regression models with partial differential regularizations, + making use of the Finite Element Method. The models efficiently handle data distributed + over irregularly shaped domains and can comply with various conditions at the + boundaries of the domain. A priori information about the spatial structure of + the phenomenon under study can be incorporated in the model via the differential + regularization. See Sangalli, L. M. (2021) "Spatial Regression + With Partial Differential Equation Regularisation" for an overview. The release + 1.1-9 requires R (>= 4.2.0) to be installed on windows machines. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdaPDE + url_git: '' +fdaPOIFD: + version: 1.0.3 + title: Partially Observed Integrated Functional Depth + maintainer: Antonio Elías + description: Applications to visualization, outlier detection and classification. + Software companion for Elías, Antonio, Jiménez, Raúl, Paganoni, Anna M. and Sangalli, + Laura M., (2022), "Integrated Depth for Partially Observed Functional Data". Journal + of Computational and Graphical Statistics. . + date_publication: '2022-05-16' + bug_reports: https://github.com/aefdz/fdaPOIFD + url: '' + url_cran: https://CRAN.R-project.org/package=fdaPOIFD + url_git: https://github.com/aefdz/fdaPOIFD +fdarep: + version: 0.1.1 + title: |- + Two-Dimensional FPCA, Marginal FPCA, and Product FPCA for + Repeated Functional Data + maintainer: Poorbita Kundu + description: |- + Provides an implementation of two-dimensional functional principal component analysis (FPCA), Marginal FPCA, and Product FPCA for repeated functional data. Marginal and Product FPCA implementations are done for both dense and sparsely observed functional data. + References: Chen, K., Delicado, P., & Müller, H. G. (2017) . + Chen, K., & Müller, H. G. (2012) . + Hall, P., Müller, H.G. and Wang, J.L. (2006) . + Yao, F., Müller, H. G., & Wang, J. L. (2005) . + date_publication: '2024-03-06' + bug_reports: https://github.com/functionaldata/tFDArep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdarep + url_git: https://github.com/functionaldata/tFDArep +fdaSP: + version: 1.1.1 + title: Sparse Functional Data Analysis Methods + maintainer: Mauro Bernardi + description: |- + Provides algorithms to fit linear regression models under several popular penalization techniques and functional linear regression models based on Majorizing-Minimizing (MM) and Alternating Direction Method of Multipliers (ADMM) techniques. + See Boyd et al (2010) for complete introduction to the method. + date_publication: '2023-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdaSP + url_git: '' +fdasrvf: + version: 2.3.6 + title: Elastic Functional Data Analysis + maintainer: J. Derek Tucker + description: |- + Performs alignment, PCA, and modeling of multidimensional and + unidimensional functions using the square-root velocity framework + (Srivastava et al., 2011 and Tucker et al., 2014 + ). This framework allows for elastic + analysis of functional data through phase and amplitude separation. + date_publication: '2025-02-17' + bug_reports: https://github.com/jdtuck/fdasrvf_R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fdasrvf + url_git: https://github.com/jdtuck/fdasrvf_R +fdatest: + version: 2.1.1 + title: Interval Testing Procedure for Functional Data + maintainer: Alessia Pini + description: 'Implementation of the Interval Testing Procedure for functional data + in different frameworks (i.e., one or two-population frameworks, functional linear + models) by means of different basis expansions (i.e., B-spline, Fourier, and phase-amplitude + Fourier). The current version of the package requires functional data evaluated + on a uniform grid; it automatically projects each function on a chosen functional + basis; it performs the entire family of multivariate tests; and, finally, it provides + the matrix of the p-values of the previous tests and the vector of the corrected + p-values. The functional basis, the coupled or uncoupled scenario, and the kind + of test can be chosen by the user. The package provides also a plotting function + creating a graphical output of the procedure: the p-value heat-map, the plot of + the corrected p-values, and the plot of the functional data.' + date_publication: '2022-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdatest + url_git: '' +FDboost: + version: 1.1-2 + title: Boosting Functional Regression Models + maintainer: David Ruegamer + description: |- + Regression models for functional data, i.e., scalar-on-function, + function-on-scalar and function-on-function regression models, are fitted + by a component-wise gradient boosting algorithm. + For a manual on how to use 'FDboost', see Brockhaus, Ruegamer, Greven (2017) . + date_publication: '2023-08-12' + bug_reports: https://github.com/boost-R/FDboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FDboost + url_git: https://github.com/boost-R/FDboost +fddm: + version: 1.0-2 + title: Fast Implementation of the Diffusion Decision Model + maintainer: Henrik Singmann + description: |- + Provides the probability density function (PDF), cumulative + distribution function (CDF), the first-order and second-order partial + derivatives of the PDF, and a fitting function for the diffusion decision + model (DDM; e.g., + Ratcliff & McKoon, 2008, ) with across-trial + variability in the drift rate. Because the PDF, its partial derivatives, and + the CDF of the DDM both contain an infinite sum, they need to be approximated. + 'fddm' implements all published approximations + (Navarro & Fuss, 2009, ; + Gondan, Blurton, & Kesselmeier, 2014, ; + Blurton, Kesselmeier, & Gondan, 2017, ; + Hartmann & Klauer, 2021, ) plus + new approximations. All approximations are implemented purely in 'C++' + providing faster speed than existing packages. + date_publication: '2024-07-02' + bug_reports: https://github.com/rtdists/fddm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fddm + url_git: https://github.com/rtdists/fddm +fdesigns: + version: '1.0' + title: Optimal Experimental Designs for Functional/Dynamic Models + maintainer: Damianos Michaelides + description: Optimal experimental designs for functional linear and functional generalised + linear models, for scalar responses and profile/dynamic factors. The designs are + optimised using the coordinate exchange algorithm. The methods are discussed by + Michaelides (2023) . + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdesigns + url_git: '' +fdicdata: + version: 0.1.1 + title: Accessing FDIC Bank Data + maintainer: Ugur Dar + description: |- + Retrieves financial data from Federal Deposit Insurance Corporation + (FDIC)-insured institutions and provides access to the FDIC data taxonomy. + date_publication: '2024-09-12' + bug_reports: https://github.com/visbanking/fdicdata/issues + url: https://visbanking.com/opensource/ + url_cran: https://CRAN.R-project.org/package=fdicdata + url_git: https://github.com/visbanking/fdicdata +fdm2id: + version: 0.9.9 + title: Data Mining and R Programming for Beginners + maintainer: Alexandre Blansché + description: 'Contains functions to simplify the use of data mining methods (classification, + regression, clustering, etc.), for students and beginners in R programming. Various + R packages are used and wrappers are built around the main functions, to standardize + the use of data mining methods (input/output): it brings a certain loss of flexibility, + but also a gain of simplicity. The package name came from the French "Fouille + de Données en Master 2 Informatique Décisionnelle".' + date_publication: '2023-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdm2id + url_git: '' +fDMA: + version: 2.2.8 + title: |- + Dynamic Model Averaging and Dynamic Model Selection for + Continuous Outcomes + maintainer: Krzysztof Drachal + description: 'Allows to estimate dynamic model averaging, dynamic model selection + and median probability model. The original methods are implemented, as well as, + selected further modifications of these methods. In particular the user might + choose between recursive moment estimation and exponentially moving average for + variance updating. Inclusion probabilities might be modified in a way using ''Google + Trends''. The code is written in a way which minimises the computational burden + (which is quite an obstacle for dynamic model averaging if many variables are + used). For example, this package allows for parallel computations and Occam''s + window approach. The package is designed in a way that is hoped to be especially + useful in economics and finance. Main reference: Raftery, A.E., Karny, M., Ettler, + P. (2010) .' + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fDMA + url_git: '' +fdq: + version: '0.12' + title: Forest Data Quality + maintainer: Caíque de Oliveira de Souza + description: |2- + + Forest data quality is a package containing nine methods of analysis for forest databases, + from databases containing inventory data and growth models, the focus of the analyzes is related to the + quality of the data present in the database with a focus on consistency , punctuality and completeness of data. + date_publication: '2021-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdq + url_git: '' +fdrci: + version: '2.4' + title: Permutation-Based FDR Point and Confidence Interval Estimation + maintainer: Joshua Millstein + description: |- + FDR functions for permutation-based estimators, including pi0 as well as FDR + confidence intervals. The confidence intervals account for dependencies between + tests by the incorporation of an overdispersion parameter, which is estimated + from the permuted data. Also included are options for an analog parametric approach. + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdrci + url_git: '' +fdrDiscreteNull: + version: '1.4' + title: |- + False Discovery Rate Procedures Under Discrete and Heterogeneous + Null Distributions + maintainer: Xiongzhi Chen + description: 'It is known that current false discovery rate (FDR) procedures can + be very conservative when applied to multiple testing in the discrete paradigm + where p-values (and test statistics) have discrete and heterogeneous null distributions. + This package implements more powerful weighted or adaptive FDR procedures for + FDR control and estimation in the discrete paradigm. The package takes in the + original data set rather than just the p-values in order to carry out the adjustments + for discreteness and heterogeneity of p-value distributions. The package implements + methods for two types of test statistics and their p-values: (a) binomial test + on if two independent Poisson distributions have the same means, (b) Fisher''s + exact test on if the conditional distribution is the same as the marginal distribution + for two binomial distributions, or on if two independent binomial distributions + have the same probabilities of success.' + date_publication: '2020-04-25' + bug_reports: '' + url: http://math.wsu.edu/faculty/xchen/welcome.php + url_cran: https://CRAN.R-project.org/package=fdrDiscreteNull + url_git: '' +FDRestimation: + version: 1.0.1 + title: Estimate, Plot, and Summarize False Discovery Rates + maintainer: Megan Murray + description: The user can directly compute and display false discovery rates from + inputted p-values or z-scores under a variety of assumptions. p.fdr() computes + FDRs, adjusted p-values and decision reject vectors from inputted p-values or + z-values. get.pi0() estimates the proportion of data that are truly null. plot.p.fdr() + plots the FDRs, adjusted p-values, and the raw p-values points against their rejection + threshold lines. + date_publication: '2022-04-01' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=FDRestimation + url_git: '' +FDRsamplesize2: + version: 0.2.0 + title: |- + Computing Power and Sample Size for the False Discovery Rate in + Multiple Applications + maintainer: Yonghui Ni + description: Defines a collection of functions to compute average power and sample + size for studies that use the false discovery rate as the final measure of statistical + significance. A three-rectangle approximation method of a p-value histogram is + proposed to derive a formula to compute the statistical power for analyses that + involve the FDR. The methodology paper of this package is under review. + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FDRsamplesize2 + url_git: '' +FDRsampsize: + version: '1.0' + title: |- + Compute Sample Size that Meets Requirements for Average Power + and FDR + maintainer: Stan Pounds + description: Defines a collection of functions to compute average power and sample + size for studies that use the false discovery rate as the final measure of statistical + significance. + date_publication: '2016-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FDRsampsize + url_git: '' +fdrtool: + version: 1.2.18 + title: Estimation of (Local) False Discovery Rates and Higher Criticism + maintainer: Korbinian Strimmer + description: |- + Estimates both tail area-based false + discovery rates (Fdr) as well as local false discovery rates (fdr) for a + variety of null models (p-values, z-scores, correlation coefficients, + t-scores). The proportion of null values and the parameters of the null + distribution are adaptively estimated from the data. In addition, the package + contains functions for non-parametric density estimation (Grenander estimator), + for monotone regression (isotonic regression and antitonic regression with weights), + for computing the greatest convex minorant (GCM) and the least concave majorant (LCM), + for the half-normal and correlation distributions, and for computing + empirical higher criticism (HC) scores and the corresponding decision threshold. + date_publication: '2024-08-20' + bug_reports: '' + url: https://strimmerlab.github.io/software/fdrtool/ + url_cran: https://CRAN.R-project.org/package=fdrtool + url_git: '' +fds: + version: '1.8' + title: Functional Data Sets + maintainer: Han Lin Shang + description: Functional data sets. + date_publication: '2018-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fds + url_git: '' +fdth: + version: 1.3-0 + title: Frequency Distribution Tables, Histograms and Polygons + maintainer: J. C. Faria + description: |- + Perform frequency distribution tables, associated histograms + and polygons from vector, data.frame and matrix objects for + numerical and categorical variables. + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdth + url_git: https://github.com/jcfaria/fdth +fdWasserstein: + version: '1.0' + title: Application of Optimal Transport to Functional Data Analysis + maintainer: Valentina Masarotto + description: |- + These functions were developed to support statistical analysis on functional covariance operators. + The package contains functions to: + - compute 2-Wasserstein distances between Gaussian Processes as in + Masarotto, Panaretos & Zemel (2019) ; + - compute the Wasserstein barycenter (Frechet mean) as in Masarotto, + Panaretos & Zemel (2019) ; + - perform analysis of variance testing procedures for functional + covariances and tangent space principal component analysis of + covariance operators as in Masarotto, Panaretos & Zemel (2022) + . + - perform a soft-clustering based on the Wasserstein distance where + functional data are classified based on their covariance structure + as in Masarotto & Masarotto (2023) . + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fdWasserstein + url_git: '' +FDX: + version: 2.0.2 + title: |- + False Discovery Exceedance Controlling Multiple Testing + Procedures + maintainer: Florian Junge + description: |- + Multiple testing procedures for heterogeneous and discrete tests as + described in Döhler and Roquain (2020) . The main + algorithms of the paper are available as continuous, discrete and weighted + versions. They take as input the results of a test procedure from package + 'DiscreteTests', or a set of observed p-values and their discrete support + under their nulls. A shortcut function to obtain such p-values and supports + is also provided, along with wrappers allowing to apply discrete procedures + directly to data. + date_publication: '2024-11-11' + bug_reports: https://github.com/DISOhda/FDX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FDX + url_git: https://github.com/DISOhda/FDX +FEA: + version: 0.0.2 + title: Finite Element Modeling for R + maintainer: Henna D. Bhramdat + description: 'Finite element modeling of beam structures and 2D geometries using + constant strain triangles. Applies material properties and boundary conditions + (load and constraint) to generate a finite element model. The model produces stress, + strain, and nodal displacements; a heat map is available to demonstrate regions + where output variables are high or low. Also provides options for creating a + triangular mesh of 2D geometries. Package developed with reference to: Bathe, + K. J. (1996). Finite Element Procedures.[ISBN 978-0-9790049-5-7] -- Seshu, P. + (2012). Textbook of Finite Element Analysis. [ISBN-978-81-203-2315-5] -- Mustapha, + K. B. (2018). Finite Element Computations in Mechanics with R. [ISBN 9781315144474].' + date_publication: '2023-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FEA + url_git: '' +FeaLect: + version: '1.20' + title: Scores Features for Feature Selection + maintainer: Habil Zare + description: |- + For each feature, a score is computed that can be useful + for feature selection. Several random subsets are sampled from + the input data and for each random subset, various linear + models are fitted using lars method. A score is assigned to + each feature based on the tendency of LASSO in including that + feature in the models.Finally, the average score and the models + are returned as the output. The features with relatively low + scores are recommended to be ignored because they can lead to + overfitting of the model to the training data. Moreover, for + each random subset, the best set of features in terms of global + error is returned. They are useful for applying Bolasso, the + alternative feature selection method that recommends the + intersection of features subsets. + date_publication: '2020-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FeaLect + url_git: '' +feasts: + version: 0.4.1 + title: Feature Extraction and Statistics for Time Series + maintainer: Mitchell O'Hara-Wild + description: |- + Provides a collection of features, decomposition methods, + statistical summaries and graphics functions for the analysing tidy time + series data. The package name 'feasts' is an acronym comprising of its key + features: Feature Extraction And Statistics for Time Series. + date_publication: '2024-09-25' + bug_reports: https://github.com/tidyverts/feasts/issues + url: http://feasts.tidyverts.org/ + url_cran: https://CRAN.R-project.org/package=feasts + url_git: https://github.com/tidyverts/feasts/ +feather: + version: 0.3.5 + title: R Bindings to the Feather 'API' + maintainer: Hadley Wickham + description: |- + Read and write feather files, a lightweight binary columnar + data store designed for maximum speed. + date_publication: '2019-09-15' + bug_reports: https://github.com/wesm/feather/issues + url: '' + url_cran: https://CRAN.R-project.org/package=feather + url_git: https://github.com/wesm/feather +feature: + version: 1.2.15 + title: |- + Local Inferential Feature Significance for Multivariate Kernel + Density Estimation + maintainer: Tarn Duong + description: Local inferential feature significance for multivariate kernel density + estimation. + date_publication: '2021-02-10' + bug_reports: '' + url: https://www.mvstat.net/tduong/ + url_cran: https://CRAN.R-project.org/package=feature + url_git: '' +featureCorMatrix: + version: 0.4.0 + title: Measurement Level Independent Feature Correlation Matrix + maintainer: Guido Moeser + description: |- + Uses three different correlation coefficients to + calculate measurement-level adequate correlations in a feature matrix: + Pearson product-moment correlation coefficient, + Intraclass correlation and Cramer's V. + date_publication: '2020-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=featureCorMatrix + url_git: '' +FeatureExtraction: + version: 3.7.2 + title: Generating Features for a Cohort + maintainer: Ger Inberg + description: An R interface for generating features for a cohort using data in the + Common Data Model. Features can be constructed using default or custom made feature + definitions. Furthermore it's possible to aggregate features and get the summary + statistics. + date_publication: '2024-10-18' + bug_reports: https://github.com/OHDSI/FeatureExtraction/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FeatureExtraction + url_git: https://github.com/OHDSI/FeatureExtraction +featurefinder: + version: '1.2' + title: Feature Finder + maintainer: Richard Davis + description: Finds features through a detailed analysis of model residuals using + rpart classification and regression trees. Scans the residuals of a model across + subsets of the data to identify areas where the model differs from the actual + data. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=featurefinder + url_git: '' +featureflag: + version: 0.1.0 + title: Turn Features On and Off using Feature Flags + maintainer: Ryszard Szymański + description: |- + Feature flags allow developers to turn features of their + software on and off in form of configuration. This package provides + functions for creating feature flags in code. It exposes an interface + for defining own feature flags which are enabled based on custom criteria. + date_publication: '2021-02-18' + bug_reports: https://github.com/szymanskir/featureflag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=featureflag + url_git: https://github.com/szymanskir/featureflag +FeatureImpCluster: + version: 0.1.5 + title: Feature Importance for Partitional Clustering + maintainer: Oliver Pfaffel + description: 'Implements a novel approach for measuring feature importance in k-means + clustering. Importance of a feature is measured by the misclassification rate + relative to the baseline cluster assignment due to a random permutation of feature + values. An explanation of permutation feature importance in general can be found + here: .' + date_publication: '2021-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FeatureImpCluster + url_git: '' +features: + version: 2015.12-1 + title: Feature Extraction for Discretely-Sampled Functional Data + maintainer: Ravi Varadhan + description: |- + Discretely-sampled function is first smoothed. Features + of the smoothed function are then extracted. Some of the key + features include mean value, first and second derivatives, + critical points (i.e. local maxima and minima), curvature of + cunction at critical points, wiggliness of the function, noise + in data, and outliers in data. + date_publication: '2015-12-02' + bug_reports: '' + url: http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.html + url_cran: https://CRAN.R-project.org/package=features + url_git: '' +FeatureTerminatoR: + version: 1.0.0 + title: |- + Feature Selection Engine to Remove Features with Minimal + Predictive Power + maintainer: Gary Hutson + description: |- + The aim is to take in data.frame inputs and utilises methods, such as recursive feature engineering, to enable the features to be removed. + What this does differently from the other packages, is that it gives you the choice to remove the variables manually, or it automated this process. + Feature selection is a concept in machine learning, and statistical pipelines, whereby unimportant, or less predictive variables are eliminated from the analysis, see Boughaci (2018) . + date_publication: '2021-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FeatureTerminatoR + url_git: '' +featurizer: + version: '0.2' + title: Some Helper Functions that Help Create Features from Data + maintainer: Chhavi Choudhury + description: A collection of functions that would help one to build features based + on external data. Very useful for Data Scientists in data to day work. Many functions + create features using parallel computation. Since the nitty gritty of parallel + computation is hidden under the hood, the user need not worry about creating clusters + and shutting them down. + date_publication: '2017-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=featurizer + url_git: '' +fec16: + version: 0.1.4 + title: Data Package for the 2016 United States Federal Elections + maintainer: Marium Tapal + description: |- + Easily analyze relational data from the United States 2016 federal + election cycle as reported by the Federal Election Commission. + This package contains data about candidates, committees, and a + variety of different financial expenditures. Data is from . + date_publication: '2023-08-09' + bug_reports: https://github.com/baumer-lab/fec16/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fec16 + url_git: https://github.com/baumer-lab/fec16 +fechner: + version: 1.0-3 + title: Fechnerian Scaling of Discrete Object Sets + maintainer: Ali Uenlue + description: |- + Functions and example datasets for Fechnerian scaling of discrete + object sets. User can compute Fechnerian distances among objects representing + subjective dissimilarities, and other related information. See + package?fechner for an overview. + date_publication: '2016-06-06' + bug_reports: '' + url: http://www.meb.edu.tum.de + url_cran: https://CRAN.R-project.org/package=fechner + url_git: '' +fect: + version: 1.0.0 + title: Fixed Effects Counterfactuals + maintainer: Ziyi Liu + description: Estimates causal effects with panel data using the counterfactual methods. + It is suitable for panel or time-series cross-sectional analysis with binary treatments + under (hypothetically) baseline randomization.It allows a treatment to switch + on and off and limited carryover effects. It supports linear factor models, a + generalization of gsynth and the matrix completion method. Implementation details + can be found in Liu, Wang and Xu (2022) . + date_publication: '2022-10-14' + bug_reports: '' + url: https://yiqingxu.org/packages/fect/articles/tutorial.html + url_cran: https://CRAN.R-project.org/package=fect + url_git: '' +FedData: + version: 4.2.0 + title: |- + Download Geospatial Data Available from Several Federated Data + Sources + maintainer: R. Kyle Bocinsky + description: |- + Download geospatial data available + from several federated data sources (mainly sources maintained by the + US Federal government). Currently, the package enables extraction from + nine datasets: The National Elevation Dataset digital elevation + models ( 1 and 1/3 arc-second; + USGS); The National Hydrography Dataset + (; + USGS); The Soil Survey Geographic (SSURGO) database from the National + Cooperative Soil Survey (; NCSS), + which is led by the Natural Resources + Conservation Service (NRCS) under the USDA; + the Global Historical Climatology Network (; GHCN), coordinated by National Climatic Data + Center at NOAA; the Daymet gridded estimates of daily weather + parameters for North America, version 4, available from the Oak Ridge + National Laboratory's Distributed Active Archive Center + (; DAAC); the + International Tree Ring Data Bank; the National Land Cover + Database (; NLCD); the Cropland Data Layer from the National Agricultural + Statistics Service (; NASS); + and the PAD-US dataset of protected area boundaries (; USGS). + date_publication: '2024-12-10' + bug_reports: https://github.com/ropensci/FedData/issues + url: https://docs.ropensci.org/FedData/ + url_cran: https://CRAN.R-project.org/package=FedData + url_git: https://github.com/ropensci/FedData +federalregister: + version: 0.2.0 + title: Client Package for the U.S. Federal Register API + maintainer: Thomas J. Leeper + description: Access data from the Federal Register API . + date_publication: '2015-12-22' + bug_reports: https://github.com/rOpenGov/federalregister/issues + url: '' + url_cran: https://CRAN.R-project.org/package=federalregister + url_git: https://github.com/rOpenGov/federalregister +FedIRT: + version: 1.1.0 + title: Federated Item Response Theory Models + maintainer: Biying Zhou + description: Integrate Item Response Theory (IRT) and Federated Learning to estimate + traditional IRT models, including the 2-Parameter Logistic (2PL) and the Graded + Response Models, with enhanced privacy. It allows for the estimation in a distributed + manner without compromising accuracy. A user-friendly 'shiny' application is included. + date_publication: '2024-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FedIRT + url_git: '' +fedmatch: + version: 2.1.0 + title: Fast, Flexible, and User-Friendly Record Linkage Methods + maintainer: Chris Webster + description: |- + Provides a flexible set of tools for matching two un-linked data sets. + 'fedmatch' allows for three ways to match data: exact matches, fuzzy matches, and multi-variable matches. + It also allows an easy combination of these three matches via the tier matching function. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fedmatch + url_git: '' +fedstatAPIr: + version: 1.0.3 + title: |- + Unofficial API for Fedstat (Rosstat EMISS System) for Automatic + and Efficient Data Queries + maintainer: Denis Krylov + description: An API for automatic data queries to the fedstat , + using a small set of functions with a common interface. + date_publication: '2023-03-30' + bug_reports: https://github.com/DenchPokepon/fedstatAPIr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fedstatAPIr + url_git: https://github.com/DenchPokepon/fedstatAPIr +fedz1: + version: 0.1.0 + title: An Easier Access to Financial Accounts of the United States(Z.1) + maintainer: Hamid Shafiezadeh + description: |- + Flow of funds are financial accounts that are provided by Federal Reserve quarterly. The package contains all + datasets , tables + and descriptions with functions to understand series and explore them. + date_publication: '2023-01-30' + bug_reports: https://github.com/shaf1430/fedz1/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fedz1 + url_git: https://github.com/shaf1430/fedz1 +FeedbackTS: + version: '1.5' + title: Analysis of Feedback in Time Series + maintainer: Samuel Soubeyrand + description: Analysis of fragmented time directionality to investigate feedback + in time series. Tools provided by the package allow the analysis of feedback for + a single time series and the analysis of feedback for a set of time series collected + across a spatial domain. + date_publication: '2020-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FeedbackTS + url_git: '' +feisr: + version: 1.3.0 + title: Estimating Fixed Effects Individual Slope Models + maintainer: Tobias Ruettenauer + description: |- + Provides the function feis() to estimate fixed effects individual + slope (FEIS) models. The FEIS model constitutes a more general version of + the often-used fixed effects (FE) panel model, as implemented in the + package 'plm' by Croissant and Millo (2008) . + In FEIS models, data are not only person demeaned like in conventional + FE models, but detrended by the predicted individual slope of each + person or group. Estimation is performed by applying least squares lm() + to the transformed data. For more details on FEIS models see Bruederl and + Ludwig (2015, ISBN:1446252442); Frees (2001) ; + Polachek and Kim (1994) ; + Ruettenauer and Ludwig (2020) ; + Wooldridge (2010, ISBN:0262294354). To test consistency of conventional FE + and random effects estimators against heterogeneous slopes, the package + also provides the functions feistest() for an artificial regression test + and bsfeistest() for a bootstrapped version of the Hausman test. + date_publication: '2022-04-01' + bug_reports: https://github.com/ruettenauer/feisr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=feisr + url_git: https://github.com/ruettenauer/feisr +felp: + version: 0.6.0 + title: Functional Help for Functions, Objects, and Packages + maintainer: Atsushi Yasumoto + description: |- + Enhance R help system by fuzzy search and preview interface, pseudo-postfix operators, and more. + The `?.` pseudo-postfix operator and the `?` prefix operator displays documents and contents (source or structure) of objects simultaneously to help understanding the objects. + The `?p` pseudo-postfix operator displays package documents, and is shorter than help(package = foo). + date_publication: '2024-09-25' + bug_reports: https://github.com/atusy/felp/issues + url: https://felp.atusy.net/ + url_cran: https://CRAN.R-project.org/package=felp + url_git: https://github.com/atusy/felp +feltr: + version: 0.0.4 + title: Access the Felt API + maintainer: Christopher T. Kenny + description: |- + Upload, download, and edit internet maps with the Felt API + (). + Allows users to create new maps, edit existing maps, and extract data. + Provides tools for working with layers, which represent geographic data, and elements, + which are interactive annotations. Spatial data accessed from the API is + transformed to work with 'sf'. + date_publication: '2023-11-05' + bug_reports: '' + url: https://christophertkenny.com/feltr/ + url_cran: https://CRAN.R-project.org/package=feltr + url_git: https://github.com/christopherkenny/feltr +fence: + version: '1.0' + title: Using Fence Methods for Model Selection + maintainer: Thuan Nguyen + description: |- + This method is a new class of model selection strategies, + for mixed model selection, which includes linear and generalized linear + mixed models. The idea involves a procedure to isolate a subgroup of what + are known as correct models (of which the optimal model is a member). This is + accomplished by constructing a statistical fence, or barrier, to carefully + eliminate incorrect models. Once the fence is constructed, the optimal model is + selected from among those within the fence according to a criterion which can + be made flexible. + References: + 1. Jiang J., Rao J.S., Gu Z., Nguyen T. (2008), Fence Methods for Mixed Model Selection. + The Annals of Statistics, 36(4): 1669-1692. + . + 2. Jiang J., Nguyen T., Rao J.S. (2009), A Simplified Adaptive Fence Procedure. + Statistics and Probability Letters, 79, 625-629. + + 3. Jiang J., Nguyen T., Rao J.S. (2010), Fence Method for Nonparametric Small Area Estimation. + Survey Methodology, 36(1), 3-11. + . + 4. Jiming Jiang, Thuan Nguyen and J. Sunil Rao (2011), Invisible fence methods and the identification of differentially expressed gene sets. + Statistics and Its Interface, Volume 4, 403-415. + . + 5. Thuan Nguyen & Jiming Jiang (2012), Restricted fence method for covariate selection in longitudinal data analysis. + Biostatistics, 13(2), 303-314. + . + 6. Thuan Nguyen, Jie Peng, Jiming Jiang (2014), Fence Methods for Backcross Experiments. + Statistical Computation and Simulation, 84(3), 644-662. + . + 7. Jiang, J. (2014), The fence methods, in Advances in Statistics, Hindawi Publishing Corp., Cairo. + . + 8. Jiming Jiang and Thuan Nguyen (2015), The Fence Methods, World Scientific, Singapore. + . + date_publication: '2017-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fence + url_git: '' +FENmlm: + version: 2.4.4 + title: Fixed Effects Nonlinear Maximum Likelihood Models + maintainer: Laurent Berge + description: Efficient estimation of maximum likelihood models with multiple fixed-effects. + Standard-errors can easily and flexibly be clustered and estimations exported. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FENmlm + url_git: '' +FEprovideR: + version: '1.1' + title: Fixed Effects Logistic Model with High-Dimensional Parameters + maintainer: Michael Kleinsasser + description: A structured profile likelihood algorithm for the logistic fixed effects + model and an approximate expectation maximization (EM) algorithm for the logistic + mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) + . + date_publication: '2019-07-30' + bug_reports: https://github.com/umich-biostatistics/FEprovideR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FEprovideR + url_git: '' +FER: + version: '0.94' + title: Financial Engineering in R + maintainer: Jaehyuk Choi + description: |- + R implementations of standard financial engineering codes; + vanilla option pricing models such as Black-Scholes, Bachelier, CEV, and + SABR. + date_publication: '2021-03-05' + bug_reports: https://github.com/PyFE/FE-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FER + url_git: https://github.com/PyFE/FE-R +fergm: + version: 1.1.4 + title: |- + Estimation and Fit Assessment of Frailty Exponential Random + Graph Models + maintainer: Benjamin W. Campbell + description: |- + Frailty Exponential Random Graph Models estimated through pseudo likelihood with frailty terms estimated using 'Stan' as per Box-Steffensmeier et. al (2017) . + Goodness of fit for Frailty Exponential Random Graph Models is also available, with easy visualizations for comparison to fit Exponential Random Graph Models. + date_publication: '2018-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fergm + url_git: http://github.com/benjamin-w-campbell/fergm +fermicatsR: + version: '1.4' + title: Fermi Large Area Telescope Catalogs + maintainer: Pablo Saz Parkinson + description: |- + Data from various catalogs of astrophysical gamma-ray sources + detected by NASA's Large Area Telescope (The Astrophysical Journal, 697, 1071, + 2009 June 1), on board the Fermi gamma-ray satellite. More information on + Fermi and its data products is available from the Fermi Science Support Center + (http://fermi.gsfc.nasa.gov/ssc/). + date_publication: '2016-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fermicatsR + url_git: https://github.com/sazpark/fermicatsR.git +ferrn: + version: 0.1.0 + title: Facilitate Exploration of touRR optimisatioN + maintainer: H. Sherry Zhang + description: |- + Diagnostic plots for optimisation, with a focus on projection pursuit. These show paths the optimiser + takes in the high-dimensional space in multiple ways: by reducing the dimension using principal component analysis, and + also using the tour to show the path on the high-dimensional space. Several botanical colour palettes are included, reflecting the + name of the package. A paper describing the methodology can be found at . + date_publication: '2024-06-23' + bug_reports: https://github.com/huizezhang-sherry/ferrn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ferrn + url_git: https://github.com/huizezhang-sherry/ferrn/ +FertBoot: + version: 0.5.0 + title: Fertilizer Response Curve Analysis by Bootstrapping Residuals + maintainer: Ting Fung (Ralph) Ma + description: Quantify variability (such as confidence interval) of fertilizer response + curves and optimum fertilizer rates using bootstrapping residuals with several + popular non-linear and linear models. + date_publication: '2021-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FertBoot + url_git: '' +fertilmodel: + version: '1.4' + title: Fertility Models + maintainer: Michail Tsagris + description: 'Four fertility models are fitted using non-linear least squares. These + are the Hadwiger, the Gamma, the Model1 and Model2, following the terminology + of the following paper: Peristera P. and Kostaki A. (2007). "Modeling fertility + in modern populations". Demographic Research, 16(6): 141--194. . + Model based averaging is also supported.' + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fertilmodel + url_git: '' +FertNet: + version: 0.1.2 + title: Process Data from the Social Networks and Fertility Survey + maintainer: Gert Stulp + description: |- + Processes data from The Social Networks and Fertility Survey, + downloaded from , including correcting + respondent errors and transforming network data into network objects to + facilitate analyses and visualisation. + date_publication: '2024-02-05' + bug_reports: https://github.com/gertstulp/FertNet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FertNet + url_git: https://github.com/gertstulp/FertNet +FESta: + version: 1.0.0 + title: Fishing Effort Standardisation + maintainer: Eldho Varghese + description: Original idea was presented in the reference paper. Varghese et al. + (2020, 74(1):35-42) "Bayesian State-space Implementation of Schaefer Production + Model for Assessment of Stock Status for Multi-gear Fishery". Marine fisheries + governance and management practices are very essential to ensure the sustainability + of the marine resources. A widely accepted resource management strategy towards + this is to derive sustainable fish harvest levels based on the status of marine + fish stock. Various fish stock assessment models that describe the biomass dynamics + using time series data on fish catch and fishing effort are generally used for + this purpose. In the scenario of complex multi-species marine fishery in which + different species are caught by a number of fishing gears and each gear harvests + a number of species make it difficult to obtain the fishing effort corresponding + to each fish species. Since the capacity of the gears varies, the effort made + to catch a resource cannot be considered as the sum of efforts expended by different + fishing gears. This necessitates standardisation of fishing effort in unit base. + date_publication: '2020-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FESta + url_git: '' +fetch: + version: 0.1.5 + title: Fetch Data from Various Data Sources + maintainer: David Bosak + description: |- + Contains functions to fetch data from various data sources. + The user first creates a catalog of objects from a data source, + then fetches data from the catalog. The package provides an easy + way to access data from many different types of sources. + date_publication: '2024-02-11' + bug_reports: https://github.com/dbosak01/fetch/issues + url: https://fetch.r-sassy.org + url_cran: https://CRAN.R-project.org/package=fetch + url_git: '' +fetchGoogleAnalyticsR: + version: 0.1.0 + title: Get Data from Google Analytics via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Google Analytics + using the 'Windsor.ai' API . + date_publication: '2022-11-22' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=fetchGoogleAnalyticsR + url_git: '' +fetchSalesforceR: + version: 0.1.0 + title: Get Data from Salesforce via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Salesforce using + the 'Windsor.ai' API . + date_publication: '2022-11-14' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=fetchSalesforceR + url_git: '' +fetwfe: + version: 0.4.4 + title: Fused Extended Two-Way Fixed Effects + maintainer: Gregory Faletto + description: Calculates the fused extended two-way fixed effects (FETWFE) estimator + for unbiased and efficient estimation of difference-in-differences in panel data + with staggered treatment adoption. This estimator eliminates bias inherent in + conventional two-way fixed effects estimators, while also employing a novel bridge + regression regularization approach to improve efficiency and yield valid standard + errors. Provides flexible tuning parameters (including user-specified or data-driven + choices for penalty parameters), detailed output including overall and cohort-specific + treatment effects with confidence intervals, and extensive diagnostic tools. See + details in Faletto (2024) (). + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fetwfe + url_git: '' +fExtremes: + version: '4032.84' + title: Rmetrics - Modelling Extreme Events in Finance + maintainer: Paul J. Northrop + description: |- + Provides functions for analysing + and modelling extreme events in financial time Series. The + topics include: (i) data pre-processing, (ii) explorative + data analysis, (iii) peak over threshold modelling, (iv) block + maxima modelling, (v) estimation of VaR and CVaR, and (vi) the + computation of the extreme index. + date_publication: '2023-12-21' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fExtremes + url_git: '' +ff: + version: 4.5.2 + title: |- + Memory-Efficient Storage of Large Data on Disk and Fast Access + Functions + maintainer: Jens Oehlschlägel + description: |- + The ff package provides data structures that are stored on + disk but behave (almost) as if they were in RAM by transparently + mapping only a section (pagesize) in main memory - the effective + virtual memory consumption per ff object. ff supports R's standard + atomic data types 'double', 'logical', 'raw' and 'integer' and + non-standard atomic types boolean (1 bit), quad (2 bit unsigned), + nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte + unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned), + single (4 byte float with NAs). For example 'quad' allows efficient + storage of genomic data as an 'A','T','G','C' factor. The unsigned + types support 'circular' arithmetic. There is also support for + close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and + custom close-to-atomic types. + ff not only has native C-support for vectors, matrices and arrays + with flexible dimorder (major column-order, major row-order and + generalizations for arrays). There is also a ffdf class not unlike + data.frames and import/export filters for csv files. + ff objects store raw data in binary flat files in native encoding, + and complement this with metadata stored in R as physical and virtual + attributes. ff objects have well-defined hybrid copying semantics, + which gives rise to certain performance improvements through + virtualization. ff objects can be stored and reopened across R + sessions. ff files can be shared by multiple ff R objects + (using different data en/de-coding schemes) in the same process + or from multiple R processes to exploit parallelism. A wide choice of + finalizer options allows to work with 'permanent' files as well as + creating/removing 'temporary' ff files completely transparent to the + user. On certain OS/Filesystem combinations, creating the ff files + works without notable delay thanks to using sparse file allocation. + Several access optimization techniques such as Hybrid Index + Preprocessing and Virtualization are implemented to achieve good + performance even with large datasets, for example virtual matrix + transpose without touching a single byte on disk. Further, to reduce + disk I/O, 'logicals' and non-standard data types get stored native and + compact on binary flat files i.e. logicals take up exactly 2 bits to + represent TRUE, FALSE and NA. + Beyond basic access functions, the ff package also provides + compatibility functions that facilitate writing code for ff and ram + objects and support for batch processing on ff objects (e.g. as.ram, + as.ff, ffapply). ff interfaces closely with functionality from package + 'bit': chunked looping, fast bit operations and coercions between + different objects that can store subscript information ('bit', + 'bitwhich', ff 'boolean', ri range index, hi hybrid index). This allows + to work interactively with selections of large datasets and quickly + modify selection criteria. + Further high-performance enhancements can be made available upon request. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ff + url_git: https://github.com/truecluster/ff +FFD: + version: 1.0-9 + title: Freedom from Disease + maintainer: Ian Kopacka + description: Functions, S4 classes/methods and a graphical user interface (GUI) + to design surveys to substantiate freedom from disease using a modified hypergeometric + function (see Cameron and Baldock, 1997, ). + Herd sensitivities are computed according to sampling strategies "individual sampling" + or "limited sampling" (see M. Ziller, T. Selhorst, J. Teuffert, M. Kramer and + H. Schlueter, 2002, ). Methods to compute the + a-posteriori alpha-error are implemented. Risk-based targeted sampling is supported. + date_publication: '2022-11-08' + bug_reports: '' + url: https://www.ages.at/ + url_cran: https://CRAN.R-project.org/package=FFD + url_git: http://ffd.r-forge.r-project.org +FFdownload: + version: 1.1.1 + title: Download Data from Kenneth French's Website + maintainer: Sebastian Stoeckl + description: Downloads all the datasets (you can exclude the daily ones or specify + a list of those you are targeting specifically) from Kenneth French's Website + at , + process them and convert them to list of 'xts' (time series). + date_publication: '2023-10-12' + bug_reports: https://github.com/sstoeckl/ffdownload/issues + url: https://sstoeckl.github.io/ffdownload/ + url_cran: https://CRAN.R-project.org/package=FFdownload + url_git: https://github.com/sstoeckl/ffdownload +ffmanova: + version: 1.1.2 + title: Fifty-Fifty MANOVA + maintainer: Øyvind Langsrud + description: General linear modeling with multiple responses (MANCOVA). An overall + p-value for each model term is calculated by the 50-50 MANOVA method by Langsrud + (2002) , which handles collinear responses. Rotation + testing, described by Langsrud (2005) , is used + to compute adjusted single response p-values according to familywise error rates + and false discovery rates (FDR). The approach to FDR is described in the appendix + of Moen et al. (2005) . Unbalanced designs + are handled by Type II sums of squares as argued in Langsrud (2003) . + Furthermore, the Type II philosophy is extended to continuous design variables + as described in Langsrud et al. (2007) . This means + that the method is invariant to scale changes and that common pitfalls are avoided. + date_publication: '2023-10-18' + bug_reports: https://github.com/olangsrud/ffmanova/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ffmanova + url_git: https://github.com/olangsrud/ffmanova +ffp: + version: 0.2.2 + title: |- + Fully Flexible Probabilities for Stress Testing and Portfolio + Construction + maintainer: Bernardo Reckziegel + description: |- + Implements numerical entropy-pooling for portfolio construction and + scenario analysis as described in Meucci, Attilio (2008) and Meucci, Attilio (2010) + . + date_publication: '2022-09-29' + bug_reports: https://github.com/Reckziegel/FFP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ffp + url_git: https://github.com/Reckziegel/FFP +ffscrapr: + version: 1.4.8 + title: API Client for Fantasy Football League Platforms + maintainer: Tan Ho + description: |- + Helps access various Fantasy Football APIs by handling + authentication and rate-limiting, forming appropriate calls, and + returning tidy dataframes which can be easily connected to other data + sources. + date_publication: '2023-02-12' + bug_reports: https://github.com/ffverse/ffscrapr/issues + url: https://ffscrapr.ffverse.com + url_cran: https://CRAN.R-project.org/package=ffscrapr + url_git: https://github.com/ffverse/ffscrapr +fftab: + version: 0.1.0 + title: Tidy Manipulation of Fourier Transformed Data + maintainer: Timothy Keitt + description: |- + The 'fftab' package stores Fourier coefficients in a tibble and + allows their manipulation in various ways. Functions are available for converting + between complex, rectangular ('re', 'im'), and polar ('mod', 'arg') representations, + as well as for extracting components as vectors or matrices. Inputs can include + vectors, time series, and arrays of arbitrary dimensions, which are restored + to their original form when inverting the transform. Since 'fftab' stores Fourier + frequencies as columns in the tibble, many standard operations on spectral data + can be easily performed using tidy packages like 'dplyr'. + date_publication: '2025-01-15' + bug_reports: https://github.com/thk686/fftab/issues + url: https://thk686.github.io/fftab/ + url_cran: https://CRAN.R-project.org/package=fftab + url_git: https://github.com/thk686/fftab +FFTrees: + version: 2.0.0 + title: Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees + maintainer: Hansjoerg Neth + description: |- + Create, visualize, and test fast-and-frugal decision trees (FFTs) using the algorithms and methods described by Phillips, Neth, Woike & Gaissmaier (2017), . + FFTs are simple and transparent decision trees for solving binary classification problems. + FFTs can be preferable to more complex algorithms because they require very little information, are easy to understand and communicate, and are robust against overfitting. + date_publication: '2023-06-05' + bug_reports: https://github.com/ndphillips/FFTrees/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FFTrees + url_git: https://github.com/ndphillips/FFTrees/ +fftw: + version: 1.0-9 + title: Fast FFT and DCT Based on the FFTW Library + maintainer: Uwe Ligges + description: |- + Provides a simple and efficient wrapper around the fastest + Fourier transform in the west (FFTW) library . + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fftw + url_git: '' +fftwtools: + version: 0.9-11 + title: |- + Wrapper for 'FFTW3' Includes: One-Dimensional, Two-Dimensional, + Three-Dimensional, and Multivariate Transforms + maintainer: Karim Rahim + description: Provides a wrapper for several 'FFTW' functions. This package provides + access to the two-dimensional 'FFT', the multivariate 'FFT', and the one-dimensional + real to complex 'FFT' using the 'FFTW3' library. The package includes the functions + fftw() and mvfftw() which are designed to mimic the functionality of the R functions + fft() and mvfft(). The 'FFT' functions have a parameter that allows them to not + return the redundant complex conjugate when the input is real data. + date_publication: '2021-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fftwtools + url_git: https://github.com/krahim/fftwtools +FGalgorithm: + version: '1.0' + title: Flury and Gautschi algorithms + maintainer: Dariush Najarzadeh + description: This is a package for implementation of Flury-Gautschialgorithms. + date_publication: '2013-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FGalgorithm + url_git: '' +fGarch: + version: '4033.92' + title: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling + maintainer: Georgi N. Boshnakov + description: Analyze and model heteroskedastic behavior in financial time series. + date_publication: '2024-03-26' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://geobosh.github.io/fGarchDoc/(doc) + url_cran: https://CRAN.R-project.org/package=fGarch + url_git: '' +fgdr: + version: 1.1.1 + title: Utilities for Fundamental Geo-Spatial Data + maintainer: Shinya Uryu + description: |- + Read and Parse for Fundamental Geo-Spatial Data (FGD) which downloads XML file + from providing site (). The JPGIS format file + provided by FGD so that it can be handled as an R spatial object such as 'sf' and + 'raster', 'terra' or 'stars'. + Supports the FGD version 4.1, and accepts fundamental items and digital elevation models. + date_publication: '2022-02-22' + bug_reports: https://github.com/uribo/fgdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fgdr + url_git: https://github.com/uribo/fgdr +fgeo: + version: 1.1.4 + title: Analyze Forest Diversity and Dynamics + maintainer: Mauro Lepore + description: |- + To help you access, transform, analyze, and + visualize ForestGEO data, we developed a collection of R packages + (). This package, in particular, + helps you to install and load the entire package-collection with a + single R command, and provides convenient ways to find relevant + documentation. Most commonly, you should not worry about the + individual packages that make up the package-collection as you can + access all features via this package. To learn more about ForestGEO + visit . + date_publication: '2019-06-19' + bug_reports: https://github.com/forestgeo/fgeo/issues + url: http://forestgeo.github.io/fgeo + url_cran: https://CRAN.R-project.org/package=fgeo + url_git: https://github.com/forestgeo/fgeo +fgeo.analyze: + version: 1.1.14 + title: Analyze ForestGEO Data + maintainer: Mauro Lepore + description: |- + To help you access, transform, analyze, and + visualize ForestGEO data, we developed a collection of R packages + (). This package, in particular, + helps you to implement analyses of plot species distributions, + topography, demography, and biomass. It also includes a torus + translation test to determine habitat associations of tree species as + described by Zuleta et al. (2018) . To + learn more about ForestGEO visit . + date_publication: '2020-12-05' + bug_reports: https://github.com/forestgeo/fgeo.analyze/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fgeo.analyze + url_git: https://github.com/forestgeo/fgeo.analyze +fgeo.plot: + version: 1.1.11 + title: Plot ForestGEO Data + maintainer: Mauro Lepore + description: |- + To help you access, transform, analyze, and visualize + ForestGEO data, we developed a collection of R packages + (). This package, in particular, + helps you to plot ForestGEO data. To learn more about ForestGEO visit + . + date_publication: '2022-09-03' + bug_reports: https://github.com/forestgeo/fgeo.plot/issues + url: https://forestgeo.github.io/fgeo.plot/ + url_cran: https://CRAN.R-project.org/package=fgeo.plot + url_git: https://github.com/forestgeo/fgeo.plot +fgeo.tool: + version: 1.2.9 + title: Import and Manipulate 'ForestGEO' Data + maintainer: Mauro Lepore + description: |- + To help you access, transform, analyze, and visualize + 'ForestGEO' data, we developed a collection of R packages + (). This package, in particular, + helps you to easily import, filter, and modify 'ForestGEO' data. To + learn more about 'ForestGEO' visit . + date_publication: '2024-01-27' + bug_reports: https://github.com/forestgeo/fgeo.tool/issues + url: https://forestgeo.github.io/fgeo.tool/ + url_cran: https://CRAN.R-project.org/package=fgeo.tool + url_git: https://github.com/forestgeo/fgeo.tool +fgeo.x: + version: 1.1.4 + title: Access Small ForestGEO Datasets For Examples + maintainer: Mauro Lepore + description: |- + Access small example datasets from Luquillo, a + ForestGEO site in Puerto Rico + (). + date_publication: '2019-06-07' + bug_reports: https://github.com/forestgeo/fgeo.x/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fgeo.x + url_git: https://github.com/forestgeo/fgeo.x +fgitR: + version: 0.2.0 + title: Using 'FastGit' to Accelerate the Access to 'GitHub' + maintainer: Han Chen + description: '''FastGit'' works like a mirror of ''GitHub'' + to make significant acceleration. ''fgitR'' is a package to do git operation with + ''FastGit'' automatically.' + date_publication: '2022-02-28' + bug_reports: https://github.com/FastGitORG/fgitR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fgitR + url_git: '' +FGLMtrunc: + version: 0.1.0 + title: Truncated Functional Generalized Linear Models + maintainer: Chau Tran + description: |- + An implementation of the methodologies described in Xi Liu, Afshin A. Divani, and Alexander Petersen (2022) , including + truncated functional linear and truncated functional logistic regression models. + date_publication: '2022-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FGLMtrunc + url_git: '' +fglsnet: + version: '1.1' + title: |- + A Feasible Generalized Least Squares Estimator for Regression + Analysis of Outcomes with Network Dependence + maintainer: Weihua An + description: The function estimates a multivariate regression model for outcomes + with network dependence. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fglsnet + url_git: '' +fgm: + version: '1.0' + title: Partial Separability and Functional Gaussian Graphical Models + maintainer: Javier Zapata + description: Estimates a functional graphical model and a partially separable Karhunen-Loève + decomposition for a multivariate Gaussian process. See Zapata J., Oh S. and Petersen + A. (2019) . + date_publication: '2019-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fgm + url_git: '' +Fgmutils: + version: 0.9.5 + title: Forest Growth Model Utilities + maintainer: Clayton Vieira Fraga Filho + description: |- + Growth models and forest production require existing data + manipulation and the creation of new data, structured from basic forest + inventory data. The purpose of this package is provide functions to support + these activities. + date_publication: '2018-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Fgmutils + url_git: '' +FGRepo: + version: 1.3.2.0 + title: Functional Genomics Repository for POST-GWAS Analysis + maintainer: Alireza Ani + description: A collection of datasets essential for functional genomic analysis. + Gene names, gene positions, cytoband information, sourced from Ensembl and phenotypes + association graph prepared from GWAScatalog are included. Data is available in + both GRCh37 and 38 builds. These datasets facilitate a wide range of genomic studies, + including the identification of genetic variants, exploration of genomic features, + and post-GWAS functional analysis. + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FGRepo + url_git: '' +fgui: + version: 1.0-8 + title: Function GUI + maintainer: Thomas Hoffmann + description: Rapidly create a GUI interface for a function you created by automatically + creating widgets for arguments of the function. Automatically parses help routines + for context-sensitive help to these arguments. The interface essentially a wrapper + to some Tcl/Tk routines to both simplify and facilitate GUI creation. More advanced + Tcl/Tk routines/GUI objects can be incorporated into the interface for greater + customization for the more experienced. + date_publication: '2018-04-21' + bug_reports: '' + url: https://sites.google.com/site/thomashoffmannproject/software/fgui + url_cran: https://CRAN.R-project.org/package=fgui + url_git: '' +FHDI: + version: 1.4.1 + title: Fractional Hot Deck and Fully Efficient Fractional Imputation + maintainer: Inho Cho + description: Impute general multivariate missing data with the fractional hot deck + imputation based on Jaekwang Kim (2011) . + date_publication: '2020-09-22' + bug_reports: https://sites.google.com/site/ichoddcse2017/home/type-of-trainings/r-package-fhdi + url: https://sites.google.com/view/jaekwangkim/software + url_cran: https://CRAN.R-project.org/package=FHDI + url_git: '' +fhircrackr: + version: 2.2.0 + title: Handling HL7 FHIR® Resources in R + maintainer: Julia Palm + description: |- + Useful tools for conveniently downloading FHIR resources in xml format + and converting them to R data.frames. The package uses FHIR-search to download bundles + from a FHIR server, provides functions to save and read xml-files containing such bundles + and allows flattening the bundles to data.frames using XPath expressions. FHIR® is the registered trademark + of HL7 and is used with the permission of HL7. Use of the FHIR trademark does not constitute endorsement of this product by HL7. + date_publication: '2024-03-21' + bug_reports: https://github.com/POLAR-fhiR/fhircrackr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fhircrackr + url_git: '' +fHMM: + version: 1.4.1 + title: Fitting Hidden Markov Models to Financial Data + maintainer: Lennart Oelschläger + description: |- + Fitting (hierarchical) hidden Markov models to financial data + via maximum likelihood estimation. See Oelschläger, L. and Adam, T. + "Detecting Bearish and Bullish Markets in Financial Time Series Using + Hierarchical Hidden Markov Models" (2021, Statistical Modelling) + for a reference on the method. A user guide + is provided by the accompanying software paper "fHMM: Hidden Markov Models + for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R. + (2024, Journal of Statistical Software) . + date_publication: '2024-09-16' + bug_reports: https://github.com/loelschlaeger/fHMM/issues + url: https://loelschlaeger.de/fHMM/ + url_cran: https://CRAN.R-project.org/package=fHMM + url_git: '' +FHtest: + version: 1.5.1 + title: |- + Tests for Right and Interval-Censored Survival Data Based on the + Fleming-Harrington Class + maintainer: Ramon Oller + description: |- + Functions to compare two or more survival curves with: + a) The Fleming-Harrington test for right-censored data based on permutations and on counting processes. + b) An extension of the Fleming-Harrington test for interval-censored data based on a permutation distribution and on a score vector distribution. + date_publication: '2023-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FHtest + url_git: '' +FI: + version: '1.0' + title: Provide functions for forest inventory calculations + maintainer: David V. Dias + description: Provide functions for forest inventory calculations.Common + volumetric equations (Smalian, Newton and Huber) as wellstacking factor + and form + date_publication: '2013-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FI + url_git: '' +fiberLD: + version: 0.1-8 + title: Fiber Length Determination + maintainer: Natalya Pya Arnqvist + description: |- + Routines for estimating tree fiber (tracheid) length distributions in the standing tree + based on increment core samples. Two types of data can be used with the package, increment + core data measured by means of an optical fiber analyzer (OFA), e.g. such as the Kajaani + Fiber Lab, or measured by microscopy. Increment core data analyzed by OFAs consist of the cell + lengths of both cut and uncut fibres (tracheids) and fines (such as ray parenchyma cells) + without being able to identify which cells are cut or if they are fines or fibres. The + microscopy measured data consist of the observed lengths of the uncut fibres in the increment + core. A censored version of a mixture of the fine and fiber length distributions is proposed to + fit the OFA data, under distributional assumptions (Svensson et al., 2006) . The package offers two choices for the + assumptions of the underlying density functions of the true fiber (fine) lenghts of those fibers + (fines) that at least partially appear in the increment core, being the generalized gamma and + the log normal densities. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fiberLD + url_git: '' +fic: + version: 1.0.0 + title: Focused Information Criteria for Model Comparison + maintainer: Christopher Jackson + description: Compares how well different models estimate a quantity of interest + (the "focus") so that different models may be preferred for different purposes. Comparisons + within any class of models fitted by maximum likelihood are supported, with shortcuts + for commonly-used classes such as generalised linear models and parametric survival + models. The methods originate from Claeskens and Hjort (2003) + and Claeskens and Hjort (2008, ISBN:9780521852258). + date_publication: '2019-04-13' + bug_reports: https://github.com/chjackson/fic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fic + url_git: https://github.com/chjackson/fic +fICA: + version: 1.1-2 + title: Classical, Reloaded and Adaptive FastICA Algorithms + maintainer: Klaus Nordhausen + description: Algorithms for classical symmetric and deflation-based FastICA, reloaded + deflation-based FastICA algorithm and an algorithm for adaptive deflation-based + FastICA using multiple nonlinearities. For details, see Miettinen et al. (2014) + and Miettinen et al. (2017) . + The package is described in Miettinen, Nordhausen and Taskinen (2018) . + date_publication: '2021-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fICA + url_git: '' +fidelius: + version: 0.0.2 + title: Browser-Side Password-Protected HTML Documents + maintainer: Matthew T. Warkentin + description: |- + Create secure, encrypted, and password-protected static HTML + documents that include the machinery for secure in-browser authentication + and decryption. + date_publication: '2021-11-16' + bug_reports: https://github.com/mattwarkentin/fidelius/issues + url: https://mattwarkentin.github.io/fidelius/ + url_cran: https://CRAN.R-project.org/package=fidelius + url_git: https://github.com/mattwarkentin/fidelius +fido: + version: 1.1.2 + title: Bayesian Multinomial Logistic Normal Regression + maintainer: Justin Silverman + description: Provides methods for fitting and inspection of Bayesian Multinomial + Logistic Normal Models using MAP estimation and Laplace Approximation as developed + in Silverman et. Al. (2022) . Key + functionality is implemented in C++ for scalability. 'fido' replaces the previous + package 'stray'. + date_publication: '2025-02-27' + bug_reports: https://github.com/jsilve24/fido/issues + url: https://jsilve24.github.io/fido/ + url_cran: https://CRAN.R-project.org/package=fido + url_git: '' +FielDHub: + version: 1.4.2 + title: A Shiny App for Design of Experiments in Life Sciences + maintainer: Didier Murillo + description: |- + A shiny design of experiments (DOE) app that aids in the creation of traditional, + un-replicated, augmented and partially-replicated designs applied to agriculture, + plant breeding, forestry, animal and biological sciences. + date_publication: '2024-07-26' + bug_reports: https://github.com/DidierMurilloF/FielDHub/issues + url: https://didiermurillof.github.io/FielDHub/ + url_cran: https://CRAN.R-project.org/package=FielDHub + url_git: https://github.com/DidierMurilloF/FielDHub +fields: + version: '16.3' + title: Tools for Spatial Data + maintainer: Douglas Nychka + description: |- + For curve, surface and function fitting with an emphasis + on splines, spatial data, geostatistics, and spatial statistics. The major methods + include cubic, and thin plate splines, Kriging, and compactly supported + covariance functions for large data sets. The splines and Kriging methods are + supported by functions that can determine the smoothing parameter + (nugget and sill variance) and other covariance function parameters by cross + validation and also by restricted maximum likelihood. For Kriging + there is an easy to use function that also estimates the correlation + scale (range parameter). A major feature is that any covariance function + implemented in R and following a simple format can be used for + spatial prediction. There are also many useful functions for plotting + and working with spatial data as images. This package also contains + an implementation of sparse matrix methods for large spatial data + sets and currently requires the sparse matrix (spam) package. Use + help(fields) to get started and for an overview. The fields source + code is deliberately commented and provides useful explanations of + numerical details as a companion to the manual pages. The commented + source code can be viewed by expanding the source code version + and looking in the R subdirectory. The reference for fields can be generated + by the citation function in R and has DOI . Development + of this package was supported in part by the National Science Foundation Grant + 1417857, the National Center for Atmospheric Research, and Colorado School of Mines. + See the Fields URL + for a vignette on using this package and some background on spatial statistics. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fields + url_git: https://github.com/dnychka/fieldsRPackage +FieldSimR: + version: 1.4.0 + title: |- + Simulation of Plot Errors and Phenotypes in Plant Breeding Field + Trials + maintainer: Christian Werner + description: |- + Simulates plot data in multi-environment field trials with one or more traits. + Its core function generates plot errors that capture spatial trend, random error (noise), + and extraneous variation, which are combined at a user-defined ratio. + Phenotypes can be generated by combining the plot errors with simulated genetic values that capture + genotype-by-environment (GxE) interaction using wrapper functions for the R package `AlphaSimR`. + date_publication: '2024-08-30' + bug_reports: https://github.com/crWerner/fieldsimr/issues + url: https://crwerner.github.io/fieldsimr/ + url_cran: https://CRAN.R-project.org/package=FieldSimR + url_git: https://github.com/crWerner/fieldsimr +fiery: + version: 1.2.1 + title: A Lightweight and Flexible Web Framework + maintainer: Thomas Lin Pedersen + description: |- + A very flexible framework for building server side logic in + R. The framework is unopinionated when it comes to how HTTP requests + and WebSocket messages are handled and supports all levels of app + complexity; from serving static content to full-blown dynamic + web-apps. Fiery does not hold your hand as much as e.g. the shiny + package does, but instead sets you free to create your web app the way + you want. + date_publication: '2024-02-05' + bug_reports: https://github.com/thomasp85/fiery/issues + url: https://fiery.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=fiery + url_git: https://github.com/thomasp85/fiery +FIESTA: + version: 3.7.0 + title: Forest Inventory Estimation and Analysis + maintainer: Grayson White + description: |- + A research estimation tool for analysts that work with sample-based + inventory data from the U.S. Department of Agriculture, Forest Service, + Forest Inventory and Analysis (FIA) Program. + date_publication: '2025-02-04' + bug_reports: https://github.com/USDAForestService/FIESTA/issues + url: https://usdaforestservice.github.io/FIESTA/ + url_cran: https://CRAN.R-project.org/package=FIESTA + url_git: https://github.com/USDAForestService/FIESTA +FIESTAutils: + version: 1.3.0 + title: Utility Functions for Forest Inventory Estimation and Analysis + maintainer: Grayson White + description: |- + A set of tools for data wrangling, spatial data analysis, + statistical modeling (including direct, model-assisted, photo-based, and + small area tools), and USDA Forest Service data base tools. These tools are + aimed to help Foresters, Analysts, and Scientists extract and perform + analyses on USDA Forest Service data. + date_publication: '2025-01-29' + bug_reports: https://github.com/USDAForestService/FIESTAutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FIESTAutils + url_git: https://github.com/USDAForestService/FIESTAutils +fig: + version: 1.0.0 + title: A Config Package with No "Con" + maintainer: Tymoteusz Makowski + description: |- + Work with configs with a source precedence. Either create own R6 + instance or work with convenient functions at a package level. + date_publication: '2022-03-31' + bug_reports: https://github.com/TymekDev/fig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fig + url_git: https://github.com/TymekDev/fig +figir: + version: 0.1.7.0 + title: Check Validity of FIGI, CUSIP, ISIN, SEDOL + maintainer: Panagiotis Cheilaris + description: |- + With the functions in this package you can check the + validity of the following financial instrument identifiers: + FIGI (Financial Instrument Global Identifier + ), + CUSIP (Committee on Uniform Security Identification Procedures + ), + ISIN (International Securities Identification Number + ), + SEDOL (Stock Exchange Daily Official List + ). + You can also calculate the FIGI checksum of 11-character strings, + which can be useful if you want to create your own FIGI identifiers. + date_publication: '2023-08-19' + bug_reports: https://github.com/philaris/figir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=figir + url_git: https://github.com/philaris/figir +figma: + version: 0.2.0 + title: Web Client/Wrapper to the 'Figma API' + maintainer: Pedro Faria + description: |- + An easy-to-use web client/wrapper for the 'Figma API' . + It allows you to bring all data from a 'Figma' file to your 'R' session. This includes the data of all objects + that you have drawn in this file, and their respective canvas/page metadata. + date_publication: '2023-01-06' + bug_reports: https://github.com/pedropark99/figma/issues + url: https://pedropark99.github.io/figma/ + url_cran: https://CRAN.R-project.org/package=figma + url_git: https://github.com/pedropark99/figma +figuRes2: + version: 1.0.0 + title: Support for a Variety of Figure Production Tasks + maintainer: Greg Cicconetti + description: |- + We view a figure as a collection of graphs/tables assembled on a page and optionally annotated with metadata + (titles, headers and footers). Functions and supporting documentation are offered to streamline a variety of figure production task. + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=figuRes2 + url_git: https://github.com/gcicc/figures2 +file2meco: + version: 0.9.1 + title: Transform Files to 'microtable' Object with 'microeco' Package + maintainer: Chi Liu + description: Transform output files of some tools to the 'microtable' object of + 'microtable' class in 'microeco' package. The 'microtable' class is the basic + class in 'microeco' package and is necessary for the downstream microbial community + data analysis. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=file2meco + url_git: https://github.com/ChiLiubio/file2meco +filearray: + version: 0.1.9 + title: File-Backed Array for Out-of-Memory Computation + maintainer: Zhengjia Wang + description: |- + Stores large arrays in files to avoid occupying large + memories. Implemented with super fast gigabyte-level multi-threaded + reading/writing via 'OpenMP'. Supports multiple non-character data + types (double, float, complex, integer, logical, and raw). + date_publication: '2024-11-08' + bug_reports: https://github.com/dipterix/filearray/issues + url: https://dipterix.org/filearray/ + url_cran: https://CRAN.R-project.org/package=filearray + url_git: https://github.com/dipterix/filearray +filebin: + version: 0.0.6 + title: Wrapper for the Filebin File Sharing API + maintainer: Andrew B. Collier + description: |- + A wrapper for the Filebin API. Filebin implements convenient file + sharing on the web. + date_publication: '2023-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=filebin + url_git: '' +filecacher: + version: 0.2.9 + title: File Cacher + maintainer: Or Gadish + description: |2- + + The main functions in this package are with_cache() and cached_read(). + The former is a simple way to cache an R object into a file on disk, + using 'cachem'. The latter is a wrapper around any standard read function, + but caches both the output and the file list info. If the input file list + info hasn't changed, the cache is used; otherwise, the original files are + re-read. This can save time if the original operation requires reading from + many files, and/or involves lots of processing. + date_publication: '2024-01-19' + bug_reports: https://github.com/orgadish/filecacher/issues + url: '' + url_cran: https://CRAN.R-project.org/package=filecacher + url_git: https://github.com/orgadish/filecacher +filehash: + version: 2.4-6 + title: Simple Key-Value Database + maintainer: Roger D. Peng + description: |- + Implements a simple key-value style database where character string keys + are associated with data values that are stored on the disk. A simple interface is provided for inserting, + retrieving, and deleting data from the database. Utilities are provided that allow 'filehash' databases to be + treated much like environments and lists are already used in R. These utilities are provided to encourage + interactive and exploratory analysis on large datasets. Three different file formats for representing the + database are currently available and new formats can easily be incorporated by third parties for use in the + 'filehash' framework. + date_publication: '2024-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=filehash + url_git: https://github.com/rdpeng/filehash +filehashSQLite: + version: 0.2-7 + title: Simple Key-Value Database using SQLite + maintainer: Roger D. Peng + description: Simple key-value database using SQLite as the backend. + date_publication: '2024-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=filehashSQLite + url_git: https://github.com/rdpeng/filehashsqlite +filelock: + version: 1.0.3 + title: Portable File Locking + maintainer: Gábor Csárdi + description: |- + Place an exclusive or shared lock on a file. It uses + 'LockFile' on Windows and 'fcntl' locks on Unix-like systems. + date_publication: '2023-12-11' + bug_reports: https://github.com/r-lib/filelock/issues + url: https://r-lib.github.io/filelock/ + url_cran: https://CRAN.R-project.org/package=filelock + url_git: https://github.com/r-lib/filelock +filematrix: + version: '1.3' + title: File-Backed Matrix Class with Convenient Read and Write Access + maintainer: Andrey A Shabalin + description: |- + Interface for working with large matrices stored in files, + not in computer memory. Supports multiple non-character + data types (double, integer, logical and raw) of + various sizes (e.g. 8 and 4 byte real values). + Access to parts of the matrix is done by indexing, + exactly as with usual R matrices. + Supports very large matrices. + Tested on multi-terabyte matrices. + Allows for more than 2^32 rows or columns. + Allows for quick addition of extra columns to a filematrix. + Cross-platform as the package has R code only. + date_publication: '2018-02-27' + bug_reports: https://github.com/andreyshabalin/filematrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=filematrix + url_git: https://github.com/andreyshabalin/filematrix +filenamer: + version: 0.2.4 + title: Easy Management of File Names + maintainer: David J. H. Shih + description: |- + Create descriptive file names with ease. New file names are + automatically (but optionally) time stamped and placed in date stamped + directories. Streamline your analysis pipeline with input and output file + names that have informative tags and proper file extensions. + date_publication: '2024-04-04' + bug_reports: https://bitbucket.org/djhshih/filenamer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=filenamer + url_git: https://bitbucket.org/djhshih/filenamer +files: + version: 0.0.1 + title: Effective File Navigation from the R Console + maintainer: Ronald E. Robertson + description: |- + Functions for printing the contents of a folder as columns in a ragged-bottom data.frame and for + viewing the details (size, time created, time modified, etc.) of a folder's top level contents. + date_publication: '2016-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=files + url_git: '' +filesstrings: + version: 3.4.0 + title: Handy File and String Manipulation + maintainer: Rory Nolan + description: |- + This started out as a package for file and string + manipulation. Since then, the 'fs' and 'strex' packages emerged, + offering functionality previously given by this package (but it's done + better in these new ones). Those packages have hence almost pushed + 'filesstrings' into extinction. However, it still has a small number + of unique, handy file manipulation functions which can be seen in the + vignette. One example is a function to remove spaces from all file + names in a directory. + date_publication: '2024-02-11' + bug_reports: https://github.com/rorynolan/filesstrings/issues + url: https://rorynolan.github.io/filesstrings/ + url_cran: https://CRAN.R-project.org/package=filesstrings + url_git: https://github.com/rorynolan/filesstrings +FILEST: + version: 1.1.2 + title: Fine-Level Structure Simulator + maintainer: Kridsadakorn Chaichoompu + description: A population genetic simulator, which is able to generate synthetic + datasets for single-nucleotide polymorphisms (SNP) for multiple populations. The + genetic distances among populations can be set according to the Fixation Index + (Fst) as explained in Balding and Nichols (1995) . This + tool is able to simulate outlying individuals and missing SNPs can be specified. + For Genome-wide association study (GWAS), disease status can be set in desired + level according risk ratio. + date_publication: '2021-01-25' + bug_reports: https://gitlab.com/kris.ccp/filest/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FILEST + url_git: https://gitlab.com/kris.ccp/filest +filling: + version: 0.2.3 + title: Matrix Completion, Imputation, and Inpainting Methods + maintainer: Kisung You + description: Filling in the missing entries of a partially observed data is one + of fundamental problems in various disciplines of mathematical science. For many + cases, data at our interests have canonical form of matrix in that the problem + is posed upon a matrix with missing values to fill in the entries under preset + assumptions and models. We provide a collection of methods from multiple disciplines + under Matrix Completion, Imputation, and Inpainting. See Davenport and Romberg + (2016) for an overview of the topic. + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=filling + url_git: '' +fillpattern: + version: 1.0.2 + title: Patterned Fills for 'ggplot2' and 'grid' Graphics + maintainer: Daniel P. Smith + description: |- + Adds distinctive yet unobtrusive geometric patterns where solid + color fills are normally used. Patterned figures look just as + professional when viewed by colorblind readers or when printed in black + and white. The dozen included patterns can be customized in terms of scale, + rotation, color, fill, line type, and line width. Compatible with the + 'ggplot2' package as well as 'grid' graphics. + date_publication: '2024-06-24' + bug_reports: https://github.com/cmmr/fillpattern/issues + url: https://cmmr.github.io/fillpattern/ + url_cran: https://CRAN.R-project.org/package=fillpattern + url_git: https://github.com/cmmr/fillpattern +fillr: + version: 1.0.0 + title: Fill Missing Values in Vectors + maintainer: Jelger van Zaane + description: Edit vectors to fill missing values, based on the vector itself. + date_publication: '2020-01-28' + bug_reports: https://github.com/jelger12/fillr/issues + url: https://jelger12.github.io/fillr/ + url_cran: https://CRAN.R-project.org/package=fillr + url_git: '' +FilmsGmooG: + version: 0.1.0 + title: IMDb Film Ratings from the Summer of 2022 + maintainer: Antony Unwin + description: Average rating and number of votes reported by IMDb for films and shorts + with over 100 votes in 2022. The data are analysed in Chapter 3 of the Book 'Getting + (more out of) Graphics' (Antony Unwin, CRC Press 2024). + date_publication: '2024-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FilmsGmooG + url_git: '' +filterNHP: + version: 0.1.2 + title: Non-Human Primate Search Filters + maintainer: Alan V. Rincon + description: |- + Generate search filters to query scientific bibliographic sources, + such as PubMed and Web of Science, for non-human primate related + publications. + date_publication: '2021-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=filterNHP + url_git: '' +filters: + version: 0.3.1 + title: A "Snake_case" Filter System for R + maintainer: Joe Zhu + description: |- + Enables filtering datasets by a prior specified identifiers + which correspond to saved filter expressions. + date_publication: '2024-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=filters + url_git: '' +fImport: + version: '4041.88' + title: Rmetrics - Importing Economic and Financial Data + maintainer: Georgi N. Boshnakov + description: |- + Provides a collection of utility functions + to download and manage data sets from the Internet or from other + sources. + date_publication: '2024-09-20' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fImport + url_git: https://r-forge.r-project.org/scm/viewvc.php/pkg/fImport/?root=rmetrics(devel) +finalfit: + version: 1.0.8 + title: |- + Quickly Create Elegant Regression Results Tables and Plots when + Modelling + maintainer: Ewen Harrison + description: |- + Generate regression results tables and plots in final + format for publication. Explore models and export directly to PDF + and 'Word' using 'RMarkdown'. + date_publication: '2024-07-24' + bug_reports: https://github.com/ewenharrison/finalfit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=finalfit + url_git: https://github.com/ewenharrison/finalfit +finalsize: + version: 0.2.1 + title: Calculate the Final Size of an Epidemic + maintainer: Pratik Gupte + description: |- + Calculate the final size of a + susceptible-infectious-recovered epidemic in a population with + demographic variation in contact patterns and susceptibility to + disease, as discussed in Miller (2012) + . + date_publication: '2024-04-09' + bug_reports: https://github.com/epiverse-trace/finalsize/issues + url: https://epiverse-trace.github.io/finalsize/ + url_cran: https://CRAN.R-project.org/package=finalsize + url_git: https://github.com/epiverse-trace/finalsize +FinAna: + version: 0.1.2 + title: Financial Analysis and Regression Diagnostic Analysis + maintainer: Xuanhua(Peter) Yin + description: |- + Functions for financial analysis and financial modeling, + including batch graphs generation, beta calculation, + descriptive statistics, annuity calculation, bond pricing + and financial data download. + date_publication: '2017-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FinAna + url_git: '' +FinancialInstrument: + version: 1.3.1 + title: Financial Instrument Model Infrastructure and Meta-Data + maintainer: Ross Bennett + description: |- + Infrastructure for defining meta-data and + relationships for financial instruments. + date_publication: '2018-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FinancialInstrument + url_git: https://github.com/braverock/FinancialInstrument +FinancialMath: + version: 0.1.1 + title: Financial Mathematics for Actuaries + maintainer: Kameron Penn + description: Contains financial math functions and introductory derivative functions + included in the Society of Actuaries and Casualty Actuarial Society 'Financial + Mathematics' exam, and some topics in the 'Models for Financial Economics' exam. + date_publication: '2016-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FinancialMath + url_git: '' +finbif: + version: 0.9.9 + title: |- + Interface for the 'Finnish Biodiversity Information Facility' + API + maintainer: William K. Morris + description: |- + A programmatic interface to the 'Finnish Biodiversity Information + Facility' ('FinBIF') API (). 'FinBIF' aggregates + Finnish biodiversity data from multiple sources in a single open access + portal for researchers, citizen scientists, industry and government. + 'FinBIF' allows users of biodiversity information to find, access, combine + and visualise data on Finnish plants, animals and microorganisms. The + 'finbif' package makes the publicly available data in 'FinBIF' easily + accessible to programmers. Biodiversity information is available on taxonomy + and taxon occurrence. Occurrence data can be filtered by taxon, time, + location and other variables. The data accessed are conveniently + preformatted for subsequent analyses. + date_publication: '2024-11-05' + bug_reports: https://github.com/luomus/finbif/issues + url: https://luomus.github.io/finbif/ + url_cran: https://CRAN.R-project.org/package=finbif + url_git: https://github.com/luomus/finbif +FinCal: + version: 0.6.3 + title: |- + Time Value of Money, Time Series Analysis and Computational + Finance + maintainer: Felix Yanhui Fan + description: Package for time value of money calculation, time series analysis and + computational finance. + date_publication: '2016-07-29' + bug_reports: '' + url: http://felixfan.github.io/FinCal/ + url_cran: https://CRAN.R-project.org/package=FinCal + url_git: '' +finch: + version: 0.4.0 + title: Parse Darwin Core Files + maintainer: Scott Chamberlain + description: |- + Parse and create Darwin Core () Simple + and Archives. Functionality includes reading and parsing all the + files in a Darwin Core Archive, including the datasets and metadata; + read and parse simple Darwin Core files; and validation of Darwin + Core Archives. + date_publication: '2020-08-11' + bug_reports: https://github.com/ropensci/finch/issues + url: https://docs.ropensci.org/finch/ + url_cran: https://CRAN.R-project.org/package=finch + url_git: https://github.com/ropensci/finch +FinCovRegularization: + version: 1.1.0 + title: Covariance Matrix Estimation and Regularization for Finance + maintainer: YaChen Yan + description: |- + Estimation and regularization for covariance matrix of asset + returns. For covariance matrix estimation, three major types of factor + models are included: macroeconomic factor model, fundamental factor model and + statistical factor model. For covariance matrix regularization, four regularized + estimators are included: banding, tapering, hard-thresholding and soft- + thresholding. The tuning parameters of these regularized estimators are selected + via cross-validation. + date_publication: '2016-04-25' + bug_reports: http://github.com/yanyachen/FinCovRegularization/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FinCovRegularization + url_git: http://github.com/yanyachen/FinCovRegularization +findGSEP: + version: 1.2.0 + title: |- + Estimate Genome Size of Polyploid Species Using k-Mer + Frequencies + maintainer: Laiyi Fu + description: Provides tools to estimate the genome size of polyploid species using + k-mer frequencies. This package includes functions to process k-mer frequency + data and perform genome size estimation by fitting k-mer frequencies with a normal + distribution model. It supports handling of complex polyploid genomes and offers + various options for customizing the estimation process. The basic method 'findGSE' + is detailed in Sun, Hequan, et al. (2018) . + date_publication: '2024-05-26' + bug_reports: https://github.com/sperfu/findGSEP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=findGSEP + url_git: https://github.com/sperfu/findGSEP +findInFiles: + version: 0.5.0 + title: Find Pattern in Files + maintainer: Stéphane Laurent + description: |- + Creates a HTML widget which displays the results of searching + for a pattern in files in a given folder. The results can be viewed in + the 'RStudio' viewer pane, included in a 'R Markdown' document or in a + 'Shiny' application. Also provides a 'Shiny' application allowing to run + this widget and to navigate in the files found by the search. Instead of + creating a HTML widget, it is also possible to get the results of the + search in a 'tibble'. The search is performed by the 'grep' command-line + utility. + date_publication: '2024-04-28' + bug_reports: https://github.com/stla/findInFiles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=findInFiles + url_git: https://github.com/stla/findInFiles +findInGit: + version: 0.1.1 + title: Find Pattern in Files of All Branches of a 'git' Repository + maintainer: Stéphane Laurent + description: Creates a HTML widget which displays the results of searching for a + pattern in files in a given 'git' repository, including all its branches. The + results can also be returned in a dataframe. + date_publication: '2021-07-28' + bug_reports: https://github.com/stla/findInGit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=findInGit + url_git: https://github.com/stla/findInGit +FindIt: + version: 1.2.0 + title: Finding Heterogeneous Treatment Effects + maintainer: Naoki Egami + description: |- + The heterogeneous treatment effect estimation procedure + proposed by Imai and Ratkovic (2013). + The proposed method is applicable, for + example, when selecting a small number of most (or least) + efficacious treatments from a large number of alternative + treatments as well as when identifying subsets of the + population who benefit (or are harmed by) a treatment of + interest. The method adapts the Support Vector Machine + classifier by placing separate LASSO constraints over the + pre-treatment parameters and causal heterogeneity parameters of + interest. This allows for the qualitative distinction between + causal and other parameters, thereby making the variable + selection suitable for the exploration of causal heterogeneity. + The package also contains a class of functions, CausalANOVA, + which estimates the average marginal interaction effects (AMIEs) + by a regularized ANOVA as proposed by Egami and Imai (2019). + It contains a variety of regularization techniques to facilitate + analysis of large factorial experiments. + date_publication: '2019-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FindIt + url_git: '' +findPackage: + version: 0.2.0 + title: Find 'CRAN' Package by Topic + maintainer: Amarnath Bose + description: Finds 'CRAN' packages by the topic requested. The topic can be given + as a character string or as a regular expression and will help users to locate + 'CRAN' packages matching their specified requirement. findPackage() returns + a data frame of packages with description containing the input string. + date_publication: '2023-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=findPackage + url_git: '' +findpython: + version: 1.0.9 + title: Functions to Find an Acceptable Python Binary + maintainer: Trevor L. Davis + description: Package designed to find an acceptable python binary. + date_publication: '2024-11-19' + bug_reports: https://github.com/trevorld/findpython/issues + url: https://trevorldavis.com/R/findpython/ + url_cran: https://CRAN.R-project.org/package=findpython + url_git: https://github.com/trevorld/findpython +findR: + version: 0.2.1 + title: |- + Find Code Snippets, R Scripts, R Markdown, PDF and Text Files + with Pattern Matching + maintainer: David Zumbach + description: |- + Scans all directories and subdirectories of a path for code snippets, R scripts, + R Markdown, PDF or text files containing a specific pattern. Files found can be copied to a new folder. + date_publication: '2018-03-13' + bug_reports: https://github.com/zumbov2/findR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=findR + url_git: '' +findSVI: + version: 0.2.0 + title: Calculate Social Vulnerability Index for Communities + maintainer: Heli Xu + description: |- + Developed by CDC/ATSDR (Centers for Disease Control and Prevention/ + Agency for Toxic Substances and Disease Registry), + Social Vulnerability Index (SVI) serves as a tool to assess the resilience + of communities by taking into account socioeconomic and demographic factors. + Provided with year(s), region(s) and a geographic level of interest, + 'findSVI' retrieves required variables from US census data and calculates SVI + for communities in the specified area based on CDC/ATSDR SVI documentation. + Reference for the calculation methods: Flanagan BE, Gregory EW, Hallisey EJ, + Heitgerd JL, Lewis B (2011) . + date_publication: '2025-02-08' + bug_reports: https://github.com/heli-xu/findSVI/issues + url: https://heli-xu.github.io/findSVI/ + url_cran: https://CRAN.R-project.org/package=findSVI + url_git: https://github.com/heli-xu/findSVI +findviews: + version: 0.1.3 + title: A View Generator for Multidimensional Data + maintainer: Thibault Sellam + description: |- + A tool to explore wide data sets, by detecting, ranking + and plotting groups of statistically dependent columns. + date_publication: '2016-12-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=findviews + url_git: https://github.com/tsellam/findviews +FinePop: + version: 1.5.2 + title: Fine-Scale Population Analysis + maintainer: Reiichiro Nakamichi + description: 'Statistical tool set for population genetics. The package provides + following functions: 1) empirical Bayes estimator of Fst and other measures of + genetic differentiation, 2) regression analysis of environmental effects on genetic + differentiation using bootstrap method, 3) interfaces to read and manipulate ''GENEPOP'' + format data files and allele/haplotype frequency format files.' + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FinePop + url_git: '' +FinePop2: + version: '0.4' + title: |- + Fine-Scale Population Analysis (Rewrite for + Gene-Trait-Environment Interaction Analysis) + maintainer: Reiichiro Nakamichi + description: 'Statistical tool set for population genetics. The package provides + following functions: 1) estimators of genetic differentiation (FST), 2) regression + analysis of environmental effects on genetic differentiation using generalized + least squares (GLS) method, 3) interfaces to read and manipulate ''GENEPOP'' format + data files). For more information, see Kitada, Nakamichi and Kishino (2020) .' + date_publication: '2020-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FinePop2 + url_git: '' +finetune: + version: 1.2.0 + title: Additional Functions for Model Tuning + maintainer: Max Kuhn + description: |- + The ability to tune models is important. 'finetune' enhances + the 'tune' package by providing more specialized methods for finding + reasonable values of model tuning parameters. Two racing methods + described by Kuhn (2014) are included. An iterative + search method using generalized simulated annealing (Bohachevsky, + Johnson and Stein, 1986) is also + included. + date_publication: '2024-03-21' + bug_reports: https://github.com/tidymodels/finetune/issues + url: https://finetune.tidymodels.org + url_cran: https://CRAN.R-project.org/package=finetune + url_git: https://github.com/tidymodels/finetune +fingerprint: + version: 3.5.7 + title: Functions to Operate on Binary Fingerprint Data + maintainer: Rajarshi Guha + description: |- + Functions to manipulate binary fingerprints + of arbitrary length. A fingerprint is represented by an object of S4 class 'fingerprint' + which is internally represented a vector of integers, such + that each element represents the position in the fingerprint that is set to 1. + The bitwise logical functions in R are overridden so that they can be used directly + with 'fingerprint' objects. A number of distance metrics are also + available (many contributed by Michael Fadock). Fingerprints + can be converted to Euclidean vectors (i.e., points on the unit hypersphere) and + can also be folded using OR. Arbitrary fingerprint formats can be handled via line + handlers. Currently handlers are provided for CDK, MOE and BCI fingerprint data. + date_publication: '2018-01-07' + bug_reports: https://github.com/rajarshi/cdkr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fingerprint + url_git: '' +fingerPro: + version: '1.1' + title: Sediment Source Fingerprinting + maintainer: Ivan Lizaga + description: Quantifies the provenance of the sediments in a catchment or study + area. Based on a comprehensive characterization of the sediment sources and the + end sediment mixtures a mixing model algorithm is applied to the sediment mixtures + in order to estimate the relative contribution of each potential source. The package + includes several statistical methods such as Kruskal-Wallis test, discriminant + function analysis ('DFA'), principal component plot ('PCA') to select the optimal + subset of tracer properties. The variability within each sediment source is also + considered to estimate the statistical distribution of the sources contribution. + date_publication: '2018-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fingerPro + url_git: https://github.com/eead-csic-eesa +finiteruinprob: + version: '0.6' + title: |- + Computation of the Probability of Ruin Within a Finite Time + Horizon + maintainer: Benjamin Baumgartner + description: |- + In the Cramér–Lundberg risk process perturbed by a Wiener + process, this packages provides approximations to the probability of + ruin within a finite time horizon. Currently, there are three methods + implemented: The first one uses saddlepoint approximation (two + variants are provided), the second one uses importance sampling and + the third one is based on the simulation of a dual process. This last + method is not very accurate and only given here for completeness. + date_publication: '2016-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=finiteruinprob + url_git: '' +finity: + version: 0.1.5 + title: Test for Finiteness of Moments in a Distribution + maintainer: Torsten Heinrich + description: |- + The purpose of this package is to tests whether a given + moment of the distribution of a given sample is finite or not. For + heavy-tailed distributions with tail exponent b, only moments of + order smaller than b are finite. Tail exponent and heavy- + tailedness are notoriously difficult to ascertain. But the + finiteness of moments (including fractional moments) can be tested + directly. This package does that following the test suggested by + Trapani (2016) . + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=finity + url_git: '' +finna: + version: 0.1.1 + title: Access the 'Finna' API + maintainer: Akewak Jeba + description: Provides functions to access and retrieve metadata from the 'Finna' + API , which aggregates content from Finnish archives, libraries, + and museums. + date_publication: '2025-01-22' + bug_reports: https://github.com/rOpenGov/finna/issues + url: https://ropengov.github.io/finna/ + url_cran: https://CRAN.R-project.org/package=finna + url_git: '' +FinNet: + version: 0.2.1 + title: Quickly Build and Manipulate Financial Networks + maintainer: Fabio Ashtar Telarico + description: |- + Providing classes, methods, and functions to deal with financial networks. + Users can easily store information about both physical and legal persons by using pre-made classes that are studied for integration with scraping packages such as 'rvest' and 'RSelenium'. + Moreover, the package assists in creating various types of financial networks depending on the type of relation between its units depending on the relation under scrutiny (ownership, board interlocks, etc.), the desired tie type (valued or binary), and renders them in the most common formats (adjacency matrix, incidence matrix, edge list, 'igraph', 'network'). + There are also ad-hoc functions for the Fiedler value, global network efficiency, and cascade-failure analysis. + date_publication: '2024-10-31' + bug_reports: https://github.com/FATelarico/FinNet/issues + url: https://fatelarico.github.io/FinNet.html + url_cran: https://CRAN.R-project.org/package=FinNet + url_git: '' +finnishgrid: + version: 0.2.0 + title: '''Fingrid Open Data API'' R Client' + maintainer: Markus Virtanen + description: |- + R API client package for 'Fingrid Open Data' + on the electricity market and the power system. + get_data() function holds the main application logic to retrieve + time-series data. API calls require free user account registration. + Data is made available by Fingrid Oyj and distributed under + Creative Commons 4.0 . + date_publication: '2024-06-05' + bug_reports: https://github.com/virmar/finnishgrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=finnishgrid + url_git: https://github.com/virmar/finnishgrid +finnsurveytext: + version: 2.1.0 + title: Analyse Open-Ended Survey Responses in Finnish + maintainer: Adeline Clarke + description: Annotates Finnish textual survey responses into CoNLL-U format using + Finnish treebanks from using UDPipe + as described in Straka and Straková (2017) . Formatted + data is then analysed using single or comparison n-gram plots, wordclouds, summary + tables and Concept Network plots. The Concept Network plots use the TextRank algorithm + as outlined in Mihalcea, Rada & Tarau, Paul (2004) . + date_publication: '2024-11-08' + bug_reports: https://github.com/DARIAH-FI-Survey-Concept-Network/finnsurveytext/issues + url: https://dariah-fi-survey-concept-network.github.io/finnsurveytext/ + url_cran: https://CRAN.R-project.org/package=finnsurveytext + url_git: https://github.com/DARIAH-FI-Survey-Concept-Network/finnsurveytext +finnts: + version: 0.5.0 + title: Microsoft Finance Time Series Forecasting Framework + maintainer: Mike Tokic + description: |- + Automated time series forecasting developed by Microsoft Finance. The Microsoft Finance Time + Series Forecasting Framework, aka Finn, can be used to forecast any component of the income + statement, balance sheet, or any other area of interest by finance. Any numerical quantity over time, + Finn can be used to forecast it. While it can be applied outside of the finance domain, Finn was built + to meet the needs of financial analysts to better forecast their businesses within a company, and has + a lot of built in features that are specific to the needs of financial forecasters. Happy forecasting! + date_publication: '2024-10-25' + bug_reports: https://github.com/microsoft/finnts/issues + url: https://microsoft.github.io/finnts/ + url_cran: https://CRAN.R-project.org/package=finnts + url_git: https://github.com/microsoft/finnts +finreportr: + version: 1.0.4 + title: Financial Data from U.S. Securities and Exchange Commission + maintainer: Seward Lee + description: |- + Download and display company financial data from the U.S. Securities + and Exchange Commission's EDGAR database. It contains a suite of functions with + web scraping and XBRL parsing capabilities that allows users to extract data from EDGAR + in an automated and scalable manner. See + for more information. + date_publication: '2022-01-17' + bug_reports: https://github.com/sewardlee337/finreportr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=finreportr + url_git: https://github.com/sewardlee337/finreportr +FinTS: + version: 0.4-9 + title: Companion to Tsay (2005) Analysis of Financial Time Series + maintainer: Georgi N. Boshnakov + description: |- + R companion to Tsay (2005) Analysis of Financial Time + Series, second edition (Wiley). Includes data sets, functions and + script files required to work some of the examples. Version 0.3-x + includes R objects for all data files used in the text and script + files to recreate most of the analyses in chapters 1-3 and 9 plus + parts of chapters 4 and 11. + date_publication: '2024-01-26' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=84&atid=380 + url: https://geobosh.github.io/FinTSDoc/(doc) + url_cran: https://CRAN.R-project.org/package=FinTS + url_git: https://r-forge.r-project.org/projects/fints/(devel) +fio: + version: 0.1.2 + title: Friendly Input-Output Analysis + maintainer: Alberson da Silva Miranda + description: |- + Simplifies the process of importing and managing input-output + matrices from 'Microsoft Excel' into R, and provides a suite of functions for + analysis. It leverages the 'R6' class for clean, memory-efficient + object-oriented programming. Furthermore, all linear algebra computations are + implemented in 'Rust' to achieve highly optimized performance. + date_publication: '2024-08-27' + bug_reports: https://github.com/albersonmiranda/fio/issues + url: https://albersonmiranda.github.io/fio/ + url_cran: https://CRAN.R-project.org/package=fio + url_git: https://github.com/albersonmiranda/fio +fipio: + version: 1.1.2 + title: |- + Lightweight Federal Information Processing System (FIPS) Code + Information Retrieval + maintainer: Justin Singh-Mohudpur + description: |- + Provides a lightweight suite + of functions for retrieving information + about 5-digit or 2-digit US FIPS codes. + date_publication: '2024-01-22' + bug_reports: https://github.com/program--/fipio/issues + url: https://fipio.justinsingh.me + url_cran: https://CRAN.R-project.org/package=fipio + url_git: https://github.com/program--/fipio +fipp: + version: 1.0.0 + title: Induced Priors in Bayesian Mixture Models + maintainer: Jan Greve + description: |- + Computes implicitly induced quantities from prior/hyperparameter + specifications of three Mixtures of Finite Mixtures models: Dirichlet + Process Mixtures (DPMs; Escobar and West (1995) + ), Static Mixtures of Finite Mixtures + (Static MFMs; Miller and Harrison (2018) + ), and Dynamic Mixtures of Finite + Mixtures (Dynamic MFMs; Frühwirth-Schnatter, Malsiner-Walli and Grün (2020) + ). For methodological details, please refer to + Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2020) + ) as well as the package vignette. + date_publication: '2021-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fipp + url_git: '' +FiRE: + version: 1.0.1 + title: Finder of Rare Entities (FiRE) + maintainer: Prashant Gupta + description: |- + The algorithm assigns rareness/ outlierness score to every sample in voluminous datasets. + The algorithm makes multiple estimations of the proximity between a pair of samples, in low-dimensional spaces. To compute proximity, FiRE uses Sketching, a variant of locality sensitive hashing. For more details: Jindal, A., Gupta, P., Jayadeva and Sengupta, D., 2018. Discovery of rare cells from voluminous single cell expression data. Nature Communications, 9(1), p.4719. . + date_publication: '2021-09-06' + bug_reports: https://github.com/princethewinner/FiRE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FiRE + url_git: https://github.com/princethewinner/FiRE +firebase: + version: 1.0.2 + title: |- + Integrates 'Google Firebase' Authentication Storage, and + 'Analytics' with 'Shiny' + maintainer: David Munoz Tord + description: |- + Authenticate users in 'Shiny' applications using 'Google Firebase' + with any of the many methods provided; email and password, email link, or + using a third-party provider such as 'Github', 'Twitter', or 'Google'. + Use 'Firebase Storage' to store files securely, and leverage 'Firebase Analytics' + to easily log events and better understand your audience. + date_publication: '2023-07-07' + bug_reports: https://github.com/JohnCoene/firebase/issues + url: https://firebase.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=firebase + url_git: https://github.com/JohnCoene/firebase +firebehavioR: + version: 0.1.2 + title: Prediction of Wildland Fire Behavior and Hazard + maintainer: Justin Ziegler + description: Fire behavior prediction models, including the Scott & Reinhardt's + (2001) Rothermel Wildland Fire Modelling System and Alexander + et al.'s (2006) Crown Fire Initiation & Spread model . + Also contains sample datasets, estimation of fire behavior prediction model inputs + (e.g., fuel moisture, canopy characteristics, wind adjustment factor), results + visualization, and methods to estimate fire weather hazard. + date_publication: '2019-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=firebehavioR + url_git: '' +first: + version: '1.1' + title: Factor Importance Ranking and Selection using Total Indices + maintainer: Chaofan Huang + description: A model-independent factor importance ranking and selection procedure + that is based on total Sobol' indices. Please see Huang and Joseph (2024) . + This research is supported by U.S. National Science Foundation grants DMS-2310637 + and DMREF-1921873. + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=first + url_git: '' +FiSh: + version: '1.1' + title: Fisher-Shannon Method + maintainer: Mohamed Laib + description: |- + Proposes non-parametric estimates of the Fisher information measure and the + Shannon entropy power. More theoretical and implementation details can be found + in Guignard et al. . A 'python' version of this + work is available on 'github' and 'PyPi' ('FiShPy'). + date_publication: '2021-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FiSh + url_git: '' +fishbc: + version: 0.2.1 + title: Fishes of British Columbia + maintainer: Evan Amies-Galonski + description: |- + Provides raw and curated data on the codes, + classification and conservation status of freshwater fishes in British + Columbia. Marine fishes will be added in a future release. + date_publication: '2021-05-12' + bug_reports: https://github.com/poissonconsulting/fishbc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fishbc + url_git: https://github.com/poissonconsulting/fishbc +fishdata: + version: 1.0.1 + title: A Small Collection of Fish Population Datasets + maintainer: Conor Neilson + description: |- + A collection of four datasets + based around the population dynamics of migratory fish. Datasets + contain both basic size information on a per fish basis, as well as + otolith data that contains a per day record of fish growth history. + All data in this package was collected by the author, from + 2015-2016, in the Wellington region of New Zealand. + date_publication: '2021-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fishdata + url_git: '' +FisherEM: + version: '1.6' + title: |- + The FisherEM Algorithm to Simultaneously Cluster and Visualize + High-Dimensional Data + maintainer: Charles Bouveyron + description: |- + The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) , + is an efficient method for the clustering of high-dimensional data. FisherEM models and + clusters the data in a discriminative and low-dimensional latent subspace. It also provides + a low-dimensional representation of the clustered data. A sparse version of Fisher-EM + algorithm is also provided. + date_publication: '2020-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FisherEM + url_git: '' +fisheye: + version: 0.2.0 + title: Transform Base Maps Using Log-Azimuthal Projection + maintainer: Timothée Giraud + description: |- + Base maps are transformed to focus on a specific location using an + azimuthal logarithmic distance transformation. + date_publication: '2023-12-12' + bug_reports: https://github.com/riatelab/fisheye/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fisheye + url_git: https://github.com/riatelab/fisheye +fishgrowth: + version: 1.0.1 + title: Fit Growth Curves to Fish Data + maintainer: Arni Magnusson + description: |- + Fit growth models to otoliths and/or tagging data, using the 'RTMB' + package and maximum likelihood. The otoliths (or similar measurements of age) + provide direct observed coordinates of age and length. The tagging data + provide information about the observed length at release and length at + recapture at a later time, where the age at release is unknown and estimated + as a vector of parameters. The growth models provided by this package can be + fitted to otoliths only, tagging data only, or a combination of the two. + Growth variability can be modelled as constant or increasing with length. + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fishgrowth + url_git: https://github.com/arni-magnusson/fishgrowth +fishkirkko2015: + version: 1.0.0 + title: |- + Dataset of Measurements of Fish Species at Kirkkojarvi Lake, + Finland + maintainer: Jose Gama + description: |- + Dataset of 302 measurements of 11 fish species to accompany the + manuscript "Length-weight relationships of six freshwater fish species + from lake Kirkkojarvi, Finland". + date_publication: '2016-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fishkirkko2015 + url_git: '' +fishmethods: + version: 1.13-1 + title: Fishery Science Methods and Models + maintainer: Gary A. Nelson + description: Functions for applying a wide range of fisheries stock assessment methods. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fishmethods + url_git: '' +fishMod: + version: 0.29.2 + title: |- + Fits Poisson-Sum-of-Gammas GLMs, Tweedie GLMs, and Delta + Log-Normal Models + maintainer: Scott D. Foster + description: Fits models to catch and effort data. Single-species models are 1) + delta log-normal, 2) Tweedie, or 3) Poisson-gamma (G)LMs. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fishMod + url_git: '' +FishPhyloMaker: + version: 0.2.0 + title: Phylogenies for a List of Finned-Ray Fishes + maintainer: Gabriel Nakamura + description: |- + Provides an alternative to facilitate the construction of a phylogeny for fish species from a list of species + or a community matrix using as a backbone the phylogenetic tree proposed by Rabosky et al. (2018) . + date_publication: '2021-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FishPhyloMaker + url_git: '' +FishProxCompAnalyzer: + version: 0.1.0 + title: Proximate Composition Analysis of Fish and Feed Ingredients + maintainer: Tanuj Misra + description: The proximate composition analysis is the quantification of main components + that constitutes nutritional profile of any food and food products including fish, + shellfish, fish feed and their ingredients. Understanding this composition is + essential for evaluating their nutritional value and for making informed dietary + choices. The primary components typically analyzed include; moisture/ water in + foods, crude protein, crude fat/ lipid, total ash, fiber and carbohydrates AOAC(2005,ISBN:0-935584-77-3). + In case of fish, shellfish and its products, the proximate composition consists + of four primary constituents - water, protein, fat, and ash (mostly minerals). + Fish exhibit significant variation in their chemical makeup based on age, sex, + environment, and season, both within the same species and between individual fish. + There is minimal fluctuation in the content of ash and protein. The lipid concentration + varies remarkably and is inversely correlated with the water content. In case + of fish, carbohydrates are present in minor quantity so that are quantified by + subtracting total of other components from 100 to get percentage of carbohydrates. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FishProxCompAnalyzer + url_git: '' +FishResp: + version: 1.1.2 + title: Analytical Tool for Aquatic Respirometry + maintainer: Sergey Morozov + description: |- + Calculates metabolic rate of fish and other aquatic organisms measured using + an intermittent-flow respirometry approach. The tool is used to run a set of graphical + QC tests of raw respirometry data, correct it for background respiration and chamber + effect, filter and extract target values of absolute and mass-specific metabolic rate. + Experimental design should include background respiration tests and measuring of one + or more metabolic rate traits. The R package is ideally integrated with the pump + controller 'PumpResp' and the DO meter 'SensResp' (open-source hardware by FishResp). + Raw respirometry data can be also imported from 'AquaResp' (free software), 'AutoResp' + ('LoligoSystems'), 'OxyView' ('PreSens'), 'Pyro Oxygen Logger' ('PyroScience') and + 'Q-box Aqua' ('QubitSystems'). More information about the R package 'FishResp'is + available in the publication by Morozov et al. (2019) . + date_publication: '2024-11-12' + bug_reports: '' + url: https://fishresp.org + url_cran: https://CRAN.R-project.org/package=FishResp + url_git: '' +fishRman: + version: 1.2.3 + title: The Fisheries Scientist's Toolbox + maintainer: Pasquale Buonomo + description: A bundle of analytics tools for fisheries scientists. A 'shiny' R App + is included for a 'no-code' solution for retrieval, analysis, and visualization. + date_publication: '2024-03-26' + bug_reports: https://github.com/Shyentist/fish-r-man/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fishRman + url_git: https://github.com/Shyentist/fish-r-man +fishstat: + version: 2024.1.0.1 + title: Global Fishery and Aquaculture Statistics + maintainer: Arni Magnusson + description: |- + The Food and Agriculture Organization of the United Nations (FAO) + FishStat database is the leading source of global fishery and aquaculture + statistics and provides unique information for sector analysis and monitoring. + This package provides the global production data from all fisheries and + aquaculture in R format, ready for analysis. + date_publication: '2025-02-17' + bug_reports: '' + url: https://www.fao.org/fishery/en/fishstat + url_cran: https://CRAN.R-project.org/package=fishstat + url_git: https://github.com/sofia-taf/fishstat +fishtree: + version: 0.3.4 + title: Interface to the Fish Tree of Life API + maintainer: Jonathan Chang + description: |- + An interface to the Fish Tree of Life API to download taxonomies, + phylogenies, fossil calibrations, and diversification rate information for + ray-finned fishes. + date_publication: '2021-01-31' + bug_reports: https://github.com/jonchang/fishtree/issues + url: https://fishtreeoflife.org/ + url_cran: https://CRAN.R-project.org/package=fishtree + url_git: https://github.com/jonchang/fishtree +fishualize: + version: 0.2.3 + title: Color Palettes Based on Fish Species + maintainer: Nina M. D. Schiettekatte + description: Implementation of color palettes based on fish species. + date_publication: '2022-03-08' + bug_reports: https://github.com/nschiett/fishualize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fishualize + url_git: https://github.com/nschiett/fishualize +FisPro: + version: 1.1.4 + title: Fuzzy Inference System Design and Optimization + maintainer: Jean-Luc Lablée + description: |- + Fuzzy inference systems are based on fuzzy rules, which have a good capability for managing progressive phenomenons. + This package is a basic implementation of the main functions to use a Fuzzy Inference System (FIS) provided by the open source software 'FisPro' . + 'FisPro' allows to create fuzzy inference systems and to use them for reasoning purposes, especially for simulating a physical or biological system. + date_publication: '2023-03-16' + bug_reports: '' + url: https://www.fispro.org + url_cran: https://CRAN.R-project.org/package=FisPro + url_git: '' +FIT: + version: 0.0.6 + title: Transcriptomic Dynamics Models in Field Conditions + maintainer: Koji Iwayama + description: |- + Provides functionality for constructing + statistical models of transcriptomic dynamics in field conditions. + It further offers the function to predict expression of a gene given + the attributes of samples and meteorological data. Nagano, A. J., Sato, + Y., Mihara, M., Antonio, B. A., Motoyama, R., Itoh, H., Naganuma, Y., and + Izawa, T. (2012). . Iwayama, K., Aisaka, Y., + Kutsuna, N., and Nagano, A. J. (2017). . + date_publication: '2019-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FIT + url_git: '' +fit.models: + version: '0.64' + title: Compare Fitted Models + maintainer: Kjell Konis + description: |- + The fit.models function and its associated methods (coefficients, print, + summary, plot, etc.) were originally provided in the robust package to compare robustly + and classically fitted model objects. See chapters 2, 3, and 5 in Insightful (2002) + 'Robust Library User's Guide' ). The aim + of the fit.models package is to separate this fitted model object comparison functionality + from the robust package and to extend it to support fitting methods (e.g., classical, + robust, Bayesian, regularized, etc.) more generally. + date_publication: '2020-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fit.models + url_git: '' +fitbitr: + version: 0.3.0 + title: Interface with the 'Fitbit' API + maintainer: Matt Kaye + description: |- + Many 'Fitbit' users, and R-friendly 'Fitbit' users + especially, have found themselves curious about their 'Fitbit' data. + 'Fitbit' aggregates a large amount of personal data, much of which is + interesting for personal research and to satisfy curiosity, and is + even potentially useful in medical settings. The goal of 'fitbitr' is + to make interfacing with the 'Fitbit' API as streamlined as possible, + to make it simple for R users of all backgrounds and comfort levels to + analyze their 'Fitbit' data and do whatever they want with it! + Currently, 'fitbitr' includes methods for pulling data on activity, + sleep, and heart rate, but this list is likely to grow in the future + as the package gains more traction and more requests for new methods + to be implemented come in. You can find details on the 'Fitbit' API + at . + date_publication: '2023-03-25' + bug_reports: https://github.com/mrkaye97/fitbitr/issues + url: https://matthewrkaye.com/fitbitr/ + url_cran: https://CRAN.R-project.org/package=fitbitr + url_git: https://github.com/mrkaye97/fitbitr +fitbitScraper: + version: 0.1.8 + title: Scrapes Data from Fitbit + maintainer: Cory Nissen + description: |- + Scrapes data from Fitbit . This does not use the official + API, but instead uses the API that the web dashboard uses to generate the graphs + displayed on the dashboard after login at . + date_publication: '2017-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitbitScraper + url_git: https://github.com/corynissen/fitbitScraper +fitbitViz: + version: 1.0.6 + title: '''Fitbit'' Visualizations' + maintainer: Lampros Mouselimis + description: Connection to the 'Fitbit' Web API + by including 'ggplot2' Visualizations, 'Leaflet' and 3-dimensional 'Rayshader' + Maps. The 3-dimensional 'Rayshader' Map requires the installation of the 'CopernicusDEM' + R package which includes the 30- and 90-meter elevation data. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitbitViz + url_git: https://github.com/mlampros/fitbitViz +fitConic: + version: 1.2.1 + title: Fit Data to Any Conic Section + maintainer: Carl Witthoft + description: Fit data to an ellipse, hyperbola, or parabola. Bootstrapping is available + when needed. The conic curve can be rotated through an arbitrary angle and the + fit will still succeed. Helper functions are provided to convert generator coefficients + from one style to another, generate test data sets, rotate conic section parameters, + and so on. References include Nikolai Chernov (2014) "Fitting ellipses, circles, + and lines by least squares" ; A. W. Fitzgibbon, + M. Pilu, R. B. Fisher (1999) "Direct Least Squares Fitting of Ellipses" IEEE Trans. + PAMI, Vol. 21, pages 476-48; N. Chernov, Q. Huang, and H. Ma (2014) "Fitting + quadratic curves to data points", British Journal of Mathematics & Computer Science, + 4, 33-60; N. Chernov and H. Ma (2011) "Least squares fitting of quadratic curves + and surfaces", Computer Vision, Editor S. R. Yoshida, Nova Science Publishers, + pp. 285-302. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitConic + url_git: '' +fitdistrplus: + version: 1.2-2 + title: |- + Help to Fit of a Parametric Distribution to Non-Censored or + Censored Data + maintainer: Aurélie Siberchicot + description: |- + Extends the fitdistr() function (of the MASS package) with several functions + to help the fit of a parametric distribution to non-censored or censored data. + Censored data may contain left censored, right censored and interval censored values, + with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), + the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit + estimation (MGE) and maximum spacing estimation (MSE) methods (available only for + non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. + Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction + to parametric estimation. + date_publication: '2025-01-07' + bug_reports: https://github.com/lbbe-software/fitdistrplus/issues + url: https://lbbe-software.github.io/fitdistrplus/ + url_cran: https://CRAN.R-project.org/package=fitdistrplus + url_git: https://github.com/lbbe-software/fitdistrplus +FitDynMix: + version: 1.0.0 + title: Estimation of Dynamic Mixtures + maintainer: Marco Bee + description: Estimation of a dynamic lognormal - Generalized Pareto mixture via + the Approximate Maximum Likelihood and the Cross-Entropy methods. See Bee, M. + (2023) . + date_publication: '2024-01-11' + bug_reports: https://github.com/marco-bee/FitDynMix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FitDynMix + url_git: https://github.com/marco-bee/FitDynMix +fitHeavyTail: + version: 0.2.0 + title: Mean and Covariance Matrix Estimation under Heavy Tails + maintainer: Daniel P. Palomar + description: |- + Robust estimation methods for the mean vector, scatter matrix, + and covariance matrix (if it exists) from data (possibly containing NAs) + under multivariate heavy-tailed distributions such as angular Gaussian + (via Tyler's method), Cauchy, and Student's t distributions. Additionally, + a factor model structure can be specified for the covariance matrix. The + latest revision also includes the multivariate skewed t distribution. + The package is based on the papers: Sun, Babu, and Palomar (2014); + Sun, Babu, and Palomar (2015); Liu and Rubin (1995); + Zhou, Liu, Kumar, and Palomar (2019); Pascal, Ollila, and Palomar (2021). + date_publication: '2023-05-01' + bug_reports: https://github.com/convexfi/fitHeavyTail/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=fitHeavyTail + url_git: https://github.com/convexfi/fitHeavyTail +fitlandr: + version: 0.1.0 + title: |- + Fit Vector Fields and Potential Landscapes from Intensive + Longitudinal Data + maintainer: Jingmeng Cui + description: |- + A toolbox for estimating vector fields from intensive + longitudinal data, and construct potential landscapes thereafter. The + vector fields can be estimated with two nonparametric methods: the + Multivariate Vector Field Kernel Estimator (MVKE) by Bandi & Moloche + (2018) and the Sparse Vector Field + Consensus (SparseVFC) algorithm by Ma et al. (2013) + . The potential landscapes can be + constructed with a simulation-based approach with the 'simlandr' + package (Cui et al., 2021) , or the + Bhattacharya et al. (2011) method for path integration + . + date_publication: '2023-02-10' + bug_reports: https://github.com/Sciurus365/fitlandr/issues + url: https://sciurus365.github.io/fitlandr/ + url_cran: https://CRAN.R-project.org/package=fitlandr + url_git: https://github.com/Sciurus365/fitlandr +fitmix: + version: 0.1.0 + title: Finite Mixture Model Fitting of Lifespan Datasets + maintainer: Emine Guven + description: |- + Fits the lifespan datasets of biological systems such as yeast, fruit flies, and other similar biological units with well-known finite mixture models introduced by Farewell V. (1982) and Al-Hussaini et al. (2000) . Estimates parameter space fitting of a lifespan dataset with finite mixtures of parametric distributions. Computes the following tasks; 1) Estimates parameter space of the finite mixture model + by implementing the expectation maximization (EM) algorithm. 2) Finds a sequence of four goodness-of-fit measures consist of Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Kolmogorov-Smirnov (KS), and log-likelihood (log-likelihood) statistics. 3)The initial values is determined by k-means clustering. + date_publication: '2021-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitmix + url_git: https://github.com/guven-code/fitmix/ +fitODBOD: + version: 1.5.4 + title: Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD + maintainer: Amalan Mahendran + description: |- + Contains Probability Mass Functions, Cumulative Mass + Functions, Negative Log Likelihood value, parameter estimation and + modeling data using Binomial Mixture Distributions (BMD) (Manoj et al + (2013) ) and Alternate Binomial + Distributions (ABD) (Paul (1985) ), + also Journal article to use the package(). + date_publication: '2024-11-20' + bug_reports: https://github.com/Amalan-ConStat/fitODBOD/issues + url: https://amalan-constat.github.io/fitODBOD/index.html + url_cran: https://CRAN.R-project.org/package=fitODBOD + url_git: https://github.com/Amalan-ConStat/fitODBOD +fitODBODRshiny: + version: 1.0.2 + title: '''Shiny'' Application for R Package ''fitODBOD''' + maintainer: Amalan Mahendran + description: |- + For binomial outcome data Alternate Binomial Distributions + and Binomial Mixture Distributions are fitted when overdispersion is + available. + date_publication: '2024-03-08' + bug_reports: https://github.com/Amalan-ConStat/fitODBODRshiny/issues + url: https://amalan-con-stat.shinyapps.io/fitODBODRshiny/ + url_cran: https://CRAN.R-project.org/package=fitODBODRshiny + url_git: https://github.com/Amalan-ConStat/fitODBODRshiny +fitode: + version: 0.1.1 + title: Tools for Ordinary Differential Equations Model Fitting + maintainer: Sang Woo Park + description: Methods and functions for fitting ordinary differential equations (ODE) + model in 'R'. Sensitivity equations are used to compute the gradients of ODE trajectories + with respect to underlying parameters, which in turn allows for more stable fitting. + Other fitting methods, such as MCMC (Markov chain Monte Carlo), are also available. + date_publication: '2022-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitode + url_git: '' +fitplc: + version: 1.2-3 + title: Fit Hydraulic Vulnerability Curves + maintainer: Remko Duursma + description: Fits Weibull or sigmoidal models to percent loss conductivity (plc) + curves as a function of plant water potential, computes confidence intervals of + parameter estimates and predictions with bootstrap or parametric methods, and + provides convenient plotting methods. + date_publication: '2018-11-29' + bug_reports: https://www.bitbucket.org/remkoduursma/fitplc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fitplc + url_git: https://www.bitbucket.org/remkoduursma/fitplc +fitPoly: + version: 4.0.0 + title: Genotype Calling for Bi-Allelic Marker Assays + maintainer: Giorgio Tumino + description: |- + Genotyping assays for bi-allelic markers (e.g. SNPs) produce + signal intensities for the two alleles. 'fitPoly' assigns genotypes + (allele dosages) to a collection of polyploid samples based on these + signal intensities. 'fitPoly' replaces the older package 'fitTetra' that was + limited (a.o.) to only tetraploid populations whereas 'fitPoly' accepts any + ploidy level. Reference: Voorrips RE, Gort G, Vosman B (2011) + . + New functions added on conversion of data from SNP array software formats, + drawing of XY-scatterplots with or without genotype colors, + checking against expected F1 segregation patterns, + comparing results from two different assays (probes) for the same SNP, + recovery from a saveMarkerModels() crash. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitPoly + url_git: '' +fitPS: + version: 1.0.1 + title: Fit Zeta Distributions to Forensic Data + maintainer: James Curran + description: |- + Fits Zeta distributions (discrete power laws) to data that arises + from forensic surveys of clothing on the presence of glass and paint in + various populations. The general method is described to some extent in + Coulson, S.A., Buckleton, J.S., Gummer, A.B., and Triggs, C.M. (2001) + , although the implementation differs. + date_publication: '2024-03-20' + bug_reports: https://github.com/jmcurran/fitPS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fitPS + url_git: https://github.com/jmcurran/fitPS +fitscape: + version: 0.1.0 + title: Classes for Fitness Landscapes and Seascapes + maintainer: Raoul Wadhwa + description: |- + Convenient classes to model fitness landscapes and fitness + seascapes. A low-level package with which most users will not interact but + upon which other packages modeling fitness landscapes and fitness seascapes + will depend. + date_publication: '2022-03-01' + bug_reports: https://github.com/rrrlw/fitscape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fitscape + url_git: https://github.com/rrrlw/fitscape +FITSio: + version: 2.1-6 + title: FITS (Flexible Image Transport System) Utilities + maintainer: Andrew Harris + description: |- + Utilities to read and write files in the FITS (Flexible + Image Transport System) format, a standard format in astronomy (see + e.g. for more information). + Present low-level routines allow: reading, parsing, and modifying + FITS headers; reading FITS images (multi-dimensional arrays); + reading FITS binary and ASCII tables; and writing FITS images + (multi-dimensional arrays). Higher-level functions allow: reading + files composed of one or more headers and a single (perhaps + multidimensional) image or single table; reading tables into + data frames; generating vectors for image array axes; scaling and + writing images as 16-bit integers. Known incompletenesses are + reading random group extensions, as well as + complex and array descriptor data types in binary tables. + date_publication: '2021-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FITSio + url_git: '' +fitteR: + version: 0.2.0 + title: Fit Hundreds of Theoretical Distributions to Empirical Data + maintainer: Markus Boenn + description: 'Systematic fit of hundreds of theoretical univariate distributions + to empirical data via maximum likelihood estimation. Fits are reported and summarized + by a data.frame, a csv file or a ''shiny'' app (here with additional features + like visual representation of fits). All output formats provide assessment of + goodness-of-fit by the following methods: Kolmogorov-Smirnov test, Shapiro-Wilks + test, Anderson-Darling test.' + date_publication: '2022-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fitteR + url_git: '' +FitUltD: + version: 3.1.0 + title: Fit Univariate Mixed and Usual Distributions + maintainer: José Carlos Del Valle + description: Extends the fitdist() (from 'fitdistrplus') adding the Anderson-Darling + ad.test() (from 'ADGofTest') and Kolmogorov Smirnov Test ks.test() inside, trying + the distributions from 'stats' package by default and offering a second function + which uses mixed distributions to fit, this distributions are split with unsupervised + learning, with Mclust() function (from 'mclust'). + date_publication: '2019-09-11' + bug_reports: https://github.com/jcval94/FitUltD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FitUltD + url_git: https://github.com/jcval94/FitUltD +fitur: + version: 0.6.2 + title: Fit Univariate Distributions + maintainer: Thomas Roh + description: Wrapper for computing parameters for univariate distributions using + MLE. It creates an object that stores d, p, q, r functions as well as parameters + and statistics for diagnostics. Currently supports automated fitting from base + and actuar packages. A manually fitting distribution fitting function is included + to support directly specifying parameters for any distribution from ancillary + packages. + date_publication: '2021-10-06' + bug_reports: https://github.com/tomroh/fitur/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fitur + url_git: https://github.com/tomroh/fitur +fitzRoy: + version: 1.6.0 + title: Easily Scrape and Process AFL Data + maintainer: James Day + description: |- + An easy package for scraping and processing Australia Rules Football (AFL) + data. 'fitzRoy' provides a range of functions for accessing publicly available data + from 'AFL Tables' , 'Footy Wire' and + 'The Squiggle' . Further functions allow for easy processing, + cleaning and transformation of this data into formats that can be used for analysis. + date_publication: '2024-12-10' + bug_reports: https://github.com/jimmyday12/fitzRoy/issues + url: https://jimmyday12.github.io/fitzRoy/ + url_cran: https://CRAN.R-project.org/package=fitzRoy + url_git: https://github.com/jimmyday12/fitzRoy +fivethirtyeight: + version: 0.6.2 + title: |- + Data and Code Behind the Stories and Interactives at + 'FiveThirtyEight' + maintainer: Albert Y. Kim + description: |- + Datasets and code published by the data journalism website + 'FiveThirtyEight' available at . + Note that while we received guidance from editors at 'FiveThirtyEight', this + package is not officially published by 'FiveThirtyEight'. + date_publication: '2021-10-07' + bug_reports: https://github.com/rudeboybert/fivethirtyeight/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fivethirtyeight + url_git: https://github.com/rudeboybert/fivethirtyeight +FixedPoint: + version: 0.6.3 + title: Algorithms for Finding Fixed Point Vectors of Functions + maintainer: Stuart Baumann + description: For functions that take and return vectors (or scalars), this package + provides 8 algorithms for finding fixed point vectors (vectors for which the inputs + and outputs to the function are the same vector). These algorithms include Anderson + (1965) acceleration , epsilon extrapolation methods + (Wynn 1962 ) and minimal polynomial methods (Cabay and Jackson + 1976 ). + date_publication: '2022-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FixedPoint + url_git: '' +fixedpointproperty: + version: '1.0' + title: |- + Determine and Test the Fixed-Point Property in Binary Mixture + Data + maintainer: Leendert Van Maanen + description: |- + Determine and test the fixed-point property in binary mixture data. + This package was originally developed in the context of detecting mixture of + cognitive processing strategies, based on observed response time distributions. + The method is explain in more detail by Van Maanen, De Jong, Van Rijn (2014) + and Van Maanen, Couto, Lebreton, (2016) + . + date_publication: '2023-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fixedpointproperty + url_git: '' +fixedTimeEvents: + version: 1.0.1 + title: |- + The Distribution of Distances Between Discrete Events in Fixed + Time + maintainer: Kristian Hovde Liland + description: |- + Distribution functions and test for over-representation of short + distances in the Liland distribution. Simulation functions are included for + comparison. + date_publication: '2022-01-04' + bug_reports: https://github.com/khliland/fixedTimeEvents/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=fixedTimeEvents + url_git: https://github.com/khliland/fixedTimeEvents/ +fixerapi: + version: 0.1.6 + title: An R Client for the "Fixer.io" Currency API + maintainer: Evan Odell + description: |- + An R client for the "fixer.io" currency conversion and exchange + rate API. The API requires registration and some features are only available + on paid accounts. The full API documentation is available at + . + date_publication: '2018-08-23' + bug_reports: https://github.com/evanodell/fixerapi/issues + url: https://docs.evanodell.com/fixerapi + url_cran: https://CRAN.R-project.org/package=fixerapi + url_git: '' +fixest: + version: 0.12.1 + title: Fast Fixed-Effects Estimations + maintainer: Laurent Berge + description: |- + Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. + The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) . + Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors. + date_publication: '2024-06-13' + bug_reports: https://github.com/lrberge/fixest/issues + url: https://lrberge.github.io/fixest/ + url_cran: https://CRAN.R-project.org/package=fixest + url_git: https://github.com/lrberge/fixest +fixr: + version: 0.2.0 + title: Fixing Data Made Easy for Statistical Analysis + maintainer: Ambu Vijayan + description: A set of functions that facilitate basic data manipulation and cleaning + for statistical analysis including functions for finding and fixing duplicate + rows and columns, missing values, outliers, and special characters in column and + row names and functions for checking data consistency, distribution, quality, + reliability, and structure. + date_publication: '2025-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fixr + url_git: https://github.com/ambuvjyn/fixr +FixSeqMTP: + version: 0.1.2 + title: Fixed Sequence Multiple Testing Procedures + maintainer: Yalin Zhu + description: |- + Several generalized / directional Fixed Sequence Multiple Testing + Procedures (FSMTPs) are developed for testing a sequence of pre-ordered + hypotheses while controlling the FWER, FDR and Directional Error (mdFWER). + All three FWER controlling generalized FSMTPs are designed under arbitrary + dependence, which allow any number of acceptances. Two FDR controlling + generalized FSMTPs are respectively designed under arbitrary dependence and + independence, which allow more but a given number of acceptances. Two mdFWER + controlling directional FSMTPs are respectively designed under arbitrary + dependence and independence, which can also make directional decisions based + on the signs of the test statistics. The main functions for each proposed + generalized / directional FSMTPs are designed to calculate adjusted p-values + and critical values, respectively. For users' convenience, the functions also + provide the output option for printing decision rules. + date_publication: '2017-01-05' + bug_reports: https://github.com/allenzhuaz/FixSeqMTP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FixSeqMTP + url_git: '' +fixtuRes: + version: 0.1.3 + title: Mock Data Generator + maintainer: Jakub Nowicki + description: Generate mock data in R using YAML configuration. + date_publication: '2022-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fixtuRes + url_git: https://github.com/jakubnowicki/fixtuRes +fizzbuzzR: + version: 0.1.1 + title: Fizz Buzz Implementation + maintainer: Ansgar Wenzel + description: |- + An implementation of the Fizz Buzz algorithm, as defined e.g. in . + It provides the standard algorithm with 3 replaced by Fizz and 5 replaced by Buzz, with the option of specifying start + and end numbers, step size and the numbers being replaced by fizz and buzz, respectively. This package gives + interviewers the optional answer of "I use fizzbuzzR::fizzbuzz()" when interviewing rather than having to write an algorithm + themselves. + date_publication: '2016-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fizzbuzzR + url_git: '' +FjordLight: + version: 1.0.1 + title: |- + Available Light Within the Water Column and on the Seafloor of + Arctic Fjords + maintainer: Robert W. Schlegel + description: |- + Satellite data collected between 2003 and 2022, + in conjunction with gridded bathymetric data (50-150 m resolution), + are used to estimate the irradiance reaching the bottom of a series of representative EU Arctic fjords. + An Earth System Science Data (ESSD) manuscript, Schlegel et al. (2024), + provides a detailed explanation of the methodology. + date_publication: '2024-08-19' + bug_reports: '' + url: https://face-it-project.github.io/FjordLight/index.html + url_cran: https://CRAN.R-project.org/package=FjordLight + url_git: '' +fkbma: + version: 0.1.0 + title: Free Knot-Bayesian Model Averaging + maintainer: Lara Maleyeff + description: Analysis of Bayesian adaptive enrichment clinical trial using Free-Knot + Bayesian Model Averaging (FK-BMA) method of Maleyeff et al. (2024) for Gaussian + data. Maleyeff, L., Golchi, S., Moodie, E. E. M., & Hudson, M. (2024) "An adaptive + enrichment design using Bayesian model averaging for selection and threshold-identification + of predictive variables" . + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fkbma + url_git: '' +FKF: + version: 0.2.6 + title: Fast Kalman Filter + maintainer: Paul Smith + description: |- + This is a fast and flexible implementation of the Kalman + filter and smoother, which can deal with NAs. It is entirely written in C and relies fully on linear algebra subroutines contained in + BLAS and LAPACK. Due to the speed of the filter, the fitting of + high-dimensional linear state space models to large datasets + becomes possible. This package also contains a plot function + for the visualization of the state vector and graphical + diagnostics of the residuals. + date_publication: '2024-09-08' + bug_reports: https://github.com/waternumbers/FKF/issues + url: https://waternumbers.github.io/FKF/ + url_cran: https://CRAN.R-project.org/package=FKF + url_git: https://github.com/waternumbers/FKF +FKF.SP: + version: 0.3.3 + title: Fast Kalman Filtering Through Sequential Processing + maintainer: Thomas Aspinall + description: Fast and flexible Kalman filtering and smoothing implementation utilizing + sequential processing, designed for efficient parameter estimation through maximum + likelihood estimation. Sequential processing is a univariate treatment of a multivariate + series of observations and can benefit from computational efficiency over traditional + Kalman filtering when independence is assumed in the variance of the disturbances + of the measurement equation. Sequential processing is described in the textbook + of Durbin and Koopman (2001, ISBN:978-0-19-964117-8). 'FKF.SP' was built upon + the existing 'FKF' package and is, in general, a faster Kalman filter/smoother. + date_publication: '2024-10-30' + bug_reports: https://github.com/TomAspinall/FKF.SP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FKF.SP + url_git: https://github.com/TomAspinall/FKF.SP +FKSUM: + version: 1.0.1 + title: Fast Kernel Sums + maintainer: David P. Hofmeyr + description: |- + Implements the method of Hofmeyr, D.P. (2021) for fast evaluation of univariate kernel smoothers based on recursive computations. + Applications to the basic problems of density and regression function estimation are provided, as well as some projection pursuit methods + for which the objective is based on non-parametric functionals of the projected density, or conditional density of a response given projected + covariates. + The package is accompanied by an instructive paper in the Journal of Statistical Software . + date_publication: '2023-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FKSUM + url_git: '' +flacco: + version: '1.8' + title: |- + Feature-Based Landscape Analysis of Continuous and Constrained + Optimization Problems + maintainer: Pascal Kerschke + description: |- + Tools and features for "Exploratory Landscape Analysis (ELA)" of + single-objective continuous optimization problems. + Those features are able to quantify rather complex properties, such as the + global structure, separability, etc., of the optimization problems. + date_publication: '2020-03-31' + bug_reports: https://github.com/kerschke/flacco/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flacco + url_git: https://github.com/kerschke/flacco +flagr: + version: 0.3.2 + title: Implementation of Flag Aggregation + maintainer: Mátyás Mészáros + description: |- + Three methods are implemented in R to facilitate the aggregations of flags in official statistics. + From the underlying flags the highest in the hierarchy, the most frequent, or with the highest total weight + is propagated to the flag(s) for EU or other aggregates. Below there are some reference documents for the topic: + , + , + , + , + . + date_publication: '2019-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flagr + url_git: '' +flam: + version: '3.2' + title: Fits Piecewise Constant Models with Data-Adaptive Knots + maintainer: Ashley Petersen + description: 'Implements the fused lasso additive model as proposed in Petersen, + A., Witten, D., and Simon, N. (2016). Fused Lasso Additive Model. Journal of Computational + and Graphical Statistics, 25(4): 1005-1025.' + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flam + url_git: '' +FLAME: + version: 2.1.1 + title: Interpretable Matching for Causal Inference + maintainer: Vittorio Orlandi + description: |- + Efficient implementations of the algorithms in the + Almost-Matching-Exactly framework for interpretable matching in causal + inference. These algorithms match units via a learned, weighted Hamming + distance that determines which covariates are more important to match on. + For more information and examples, see the Almost-Matching-Exactly website. + date_publication: '2021-12-07' + bug_reports: https://github.com/vittorioorlandi/FLAME/issues + url: https://almost-matching-exactly.github.io + url_cran: https://CRAN.R-project.org/package=FLAME + url_git: '' +flametree: + version: 0.1.3 + title: Generate Random Tree-Like Images + maintainer: Danielle Navarro + description: |- + A generative art system for producing tree-like + images using an L-system to create the structures. The package + includes tools for generating the data structures and visualise + them in a variety of styles. + date_publication: '2021-11-29' + bug_reports: https://github.com/djnavarro/flametree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flametree + url_git: https://github.com/djnavarro/flametree +flamingos: + version: 0.1.0 + title: |- + Functional Latent Data Models for Clustering Heterogeneous + Curves ('FLaMingos') + maintainer: Florian Lecocq + description: |- + Provides a variety of original and flexible user-friendly + statistical latent variable models for the simultaneous clustering and + segmentation of heterogeneous functional data (i.e time series, or more + generally longitudinal data, fitted by unsupervised algorithms, including + EM algorithms. Functional Latent Data Models for Clustering heterogeneous + curves ('FLaMingos') are originally introduced and written in 'Matlab' by + Faicel Chamroukhi + . + The references are mainly the following ones. + Chamroukhi F. (2010) . + Chamroukhi F., Same A., Govaert, G. and Aknin P. (2010) . + Chamroukhi F., Same A., Aknin P. and Govaert G. (2011). . + Same A., Chamroukhi F., Govaert G. and Aknin, P. (2011) . + Chamroukhi F., and Glotin H. (2012) . + Chamroukhi F., Glotin H. and Same A. (2013) . + Chamroukhi F. (2015) . + Chamroukhi F. and Nguyen H-D. (2019) . + date_publication: '2019-08-06' + bug_reports: https://github.com/fchamroukhi/FLaMingos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flamingos + url_git: https://github.com/fchamroukhi/FLaMingos +flan: + version: '1.0' + title: FLuctuation ANalysis on Mutation Models + maintainer: Adrien Mazoyer + description: Tools for fluctuations analysis of mutant cells counts. Main reference + is A. Mazoyer, R. Drouilhet, S. Despreaux and B. Ycart (2017) . + date_publication: '2024-08-22' + bug_reports: https://github.com/AdriMaz/flan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flan + url_git: https://github.com/AdriMaz/flan +flap: + version: 0.2.0 + title: Forecast Linear Augmented Projection + maintainer: Yangzhuoran Fin Yang + description: |- + The Forecast Linear Augmented Projection (flap) method reduces + forecast variance by adjusting the forecasts of multivariate time series to + be consistent with the forecasts of linear combinations (components) of the + series by projecting all forecasts onto the space where the linear + constraints are satisfied. The forecast variance can be reduced + monotonically by including more components. For a given number of + components, the flap method achieves maximum forecast variance reduction + among linear projections. + date_publication: '2024-06-19' + bug_reports: https://github.com/FinYang/flap/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=flap + url_git: https://github.com/FinYang/flap +flare: + version: 1.7.0.2 + title: Family of Lasso Regression + maintainer: Xingguo Li + description: Provide the implementation of a family of Lasso variants including + Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional + sparse linear model. We adopt the alternating direction method of multipliers + and convert the original optimization problem into a sequential L1 penalized least + square minimization problem, which can be efficiently solved by linearization + algorithm. A multi-stage screening approach is adopted for further acceleration. + Besides the sparse linear model estimation, we also provide the extension of these + Lasso variants to sparse Gaussian graphical model estimation including TIGER and + CLIME using either L1 or adaptive penalty. Missing values can be tolerated for + Dantzig selector and CLIME. The computation is memory-optimized using the sparse + matrix output. For more information, please refer to . + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flare + url_git: '' +flashCard: + version: 0.1.0 + title: Create a Flash Card + maintainer: Jiena McLellan + description: Create a flip over style Flash Card with desired data frame for Shiny + application. + date_publication: '2020-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flashCard + url_git: '' +flashClust: + version: 1.01-2 + title: Implementation of optimal hierarchical clustering + maintainer: Peter Langfelder + description: Fast implementation of hierarchical clustering + date_publication: '2012-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flashClust + url_git: '' +flashier: + version: 1.0.7 + title: Empirical Bayes Matrix Factorization + maintainer: Jason Willwerscheid + description: |- + Methods for matrix factorization based on Wang and Stephens (2021) + . + date_publication: '2023-10-17' + bug_reports: https://github.com/willwerscheid/flashier/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flashier + url_git: https://github.com/willwerscheid/flashier +flashlight: + version: 0.9.0 + title: Shed Light on Black Box Machine Learning Models + maintainer: Michael Mayer + description: |- + Shed light on black box machine learning models by the help + of model performance, variable importance, global surrogate models, + ICE profiles, partial dependence (Friedman J. H. (2001) + ), accumulated local effects (Apley D. W. + (2016) ), further effects plots, interaction + strength, and variable contribution breakdown (Gosiewska and Biecek + (2019) ). All tools are implemented to work with + case weights and allow for stratified analysis. Furthermore, multiple + flashlights can be combined and analyzed together. + date_publication: '2023-05-10' + bug_reports: https://github.com/mayer79/flashlight/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flashlight + url_git: https://github.com/mayer79/flashlight +FLASHMM: + version: 1.0.0 + title: |- + Fast and Scalable Single Cell Differential Expression Analysis + using Mixed-Effects Models + maintainer: Changjiang Xu + description: |- + A fast and scalable linear mixed-effects model (LMM) estimation algorithm + for analysis of single-cell differential expression. The algorithm uses + summary-level statistics and requires less computer memory to fit the LMM. + date_publication: '2025-01-14' + bug_reports: https://github.com/BaderLab/FLASHMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FLASHMM + url_git: https://github.com/BaderLab/FLASHMM +flashr: + version: 0.2.0 + title: Create Flashcards of Terms and Definitions + maintainer: Jeffrey R. Stevens + description: |- + Provides functions for creating flashcard decks of terms and + definitions. This package creates HTML slides using 'revealjs' that can be + viewed in the 'RStudio' viewer or a web browser. Users can create + flashcards from either existing built-in decks or create their own from CSV + files or vectors of function names. + date_publication: '2024-12-09' + bug_reports: https://github.com/JeffreyRStevens/flashr/issues + url: https://jeffreyrstevens.github.io/flashr/ + url_cran: https://CRAN.R-project.org/package=flashr + url_git: https://github.com/JeffreyRStevens/flashr +flatr: + version: 0.1.1 + title: Transforms Contingency Tables to Data Frames, and Analyses Them + maintainer: Scott D. Graham + description: |- + Contingency Tables are a pain to work with when you want to run regressions. + This package takes them, flattens them into a long data frame, so you can more easily analyse them! + As well, you can calculate other related statistics. All of this is done so in a 'tidy' manner, + so it should tie in nicely with 'tidyverse' series of packages. + date_publication: '2017-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flatr + url_git: '' +flattabler: + version: 2.1.2 + title: Obtaining a Flat Table from Pivot Tables + maintainer: Jose Samos + description: |- + Transformations that allow obtaining a flat table from + reports in text or Excel format that contain data in the form of pivot + tables. They can be defined for a single report and applied to a set + of reports. + date_publication: '2024-05-01' + bug_reports: https://github.com/josesamos/flattabler/issues + url: https://josesamos.github.io/flattabler/ + url_cran: https://CRAN.R-project.org/package=flattabler + url_git: https://github.com/josesamos/flattabler +flatxml: + version: 0.1.1 + title: Tools for Working with XML Files as R Dataframes + maintainer: Joachim Zuckarelli + description: On import, the XML information is converted to a dataframe that reflects + the hierarchical XML structure. Intuitive functions allow to navigate within this + transparent XML data structure (without any knowledge of 'XPath'). 'flatXML' also + provides tools to extract data from the XML into a flat dataframe that can be + used to perform statistical operations. It also supports converting dataframes + to XML. + date_publication: '2020-12-01' + bug_reports: https://github.com/jsugarelli/flatxml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flatxml + url_git: https://github.com/jsugarelli/flatxml/ +fledge: + version: 0.1.2 + title: Smoother Change Tracking and Versioning for R Packages + maintainer: Kirill Müller + description: |- + Streamlines the process of updating changelogs (NEWS.md) + and versioning R packages developed in git repositories. + date_publication: '2024-02-18' + bug_reports: https://github.com/cynkra/fledge/issues + url: https://fledge.cynkra.com/ + url_cran: https://CRAN.R-project.org/package=fledge + url_git: https://github.com/cynkra/fledge +flevr: + version: 0.0.4 + title: |- + Flexible, Ensemble-Based Variable Selection with Potentially + Missing Data + maintainer: Brian D. Williamson + description: |- + Perform variable selection in settings with possibly missing data + based on extrinsic (algorithm-specific) and intrinsic (population-level) + variable importance. Uses a Super Learner ensemble to estimate the + underlying prediction functions that give rise to estimates of variable importance. For more information about the methods, please see Williamson and Huang (2023+) . + date_publication: '2023-11-30' + bug_reports: https://github.com/bdwilliamson/flevr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flevr + url_git: https://github.com/bdwilliamson/flevr +flexclust: + version: 1.5.0 + title: Flexible Cluster Algorithms + maintainer: Bettina Grün + description: |- + The main function kcca implements a general framework for + k-centroids cluster analysis supporting arbitrary distance measures + and centroid computation. Further cluster methods include hard + competitive learning, neural gas, and QT clustering. There are + numerous visualization methods for cluster results (neighborhood + graphs, convex cluster hulls, barcharts of centroids, ...), and + bootstrap methods for the analysis of cluster stability. + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexclust + url_git: '' +flexCWM: + version: '1.92' + title: Flexible Cluster-Weighted Modeling + maintainer: Angelo Mazza + description: |- + Allows maximum likelihood fitting of cluster-weighted models, a class of mixtures of regression models with random covariates. + Methods are described in Angelo Mazza, Antonio Punzo, Salvatore Ingrassia (2018) . + date_publication: '2020-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexCWM + url_git: '' +flexdashboard: + version: 0.6.2 + title: R Markdown Format for Flexible Dashboards + maintainer: Garrick Aden-Buie + description: |- + Format for converting an R Markdown document to a grid + oriented dashboard. The dashboard flexibly adapts the size of it's + components to the containing web page. + date_publication: '2023-08-11' + bug_reports: https://github.com/rstudio/flexdashboard/issues + url: https://pkgs.rstudio.com/flexdashboard/ + url_cran: https://CRAN.R-project.org/package=flexdashboard + url_git: https://github.com/rstudio/flexdashboard/ +FlexDir: + version: '1.0' + title: Tools to Work with the Flexible Dirichlet Distribution + maintainer: Agnese Maria Di Brisco + description: |- + Provides tools to work with the Flexible Dirichlet + distribution. The main features are an E-M algorithm for computing the maximum + likelihood estimate of the parameter vector and a function based on conditional + bootstrap to estimate its asymptotic variance-covariance matrix. It contains + also functions to plot graphs, to generate random observations and to handle + compositional data. + date_publication: '2017-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlexDir + url_git: '' +flexFitR: + version: 1.1.0 + title: Flexible Non-Linear Least Square Model Fitting + maintainer: Johan Aparicio + description: Provides tools for flexible non-linear least squares model fitting + using general-purpose optimization techniques. The package supports a variety + of optimization algorithms, including those provided by the 'optimx' package, + making it suitable for handling complex non-linear models. Features include parallel + processing support via the 'future' and 'foreach' packages, comprehensive model + diagnostics, and visualization capabilities. Implements methods described in Nash + and Varadhan (2011, ). + date_publication: '2025-02-21' + bug_reports: https://github.com/AparicioJohan/flexFitR/issues + url: https://apariciojohan.github.io/flexFitR/ + url_cran: https://CRAN.R-project.org/package=flexFitR + url_git: https://github.com/AparicioJohan/flexFitR +FlexGAM: + version: 0.7.2 + title: Generalized Additive Models with Flexible Response Functions + maintainer: Elmar Spiegel + description: |- + Standard generalized additive models assume a response function, + which induces an assumption on the shape of the distribution of the + response. However, miss-specifying the response function results in biased + estimates. Therefore in Spiegel et al. (2017) + we propose to estimate the response function + jointly with the covariate effects. This package provides the underlying + functions to estimate these generalized additive models with flexible + response functions. The estimation is based on an iterative algorithm. In + the outer loop the response function is estimated, while in the inner loop + the covariate effects are determined. For the response function a strictly + monotone P-spline is used while the covariate effects are estimated based on + a modified Fisher-Scoring algorithm. Overall the estimation relies on the + 'mgcv'-package. + date_publication: '2020-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlexGAM + url_git: '' +flexiblas: + version: 3.4.0 + title: '''FlexiBLAS'' API Interface' + maintainer: Iñaki Ucar + description: |- + Provides functions to switch the 'BLAS'/'LAPACK' optimized backend + and change the number of threads without leaving the R session, which needs + to be linked against the 'FlexiBLAS' wrapper library + . + date_publication: '2024-01-11' + bug_reports: https://github.com/Enchufa2/r-flexiblas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flexiblas + url_git: https://github.com/Enchufa2/r-flexiblas +flexlsx: + version: 0.3.4 + title: Exporting 'flextable' to 'xlsx' Files + maintainer: Tobias Heidler + description: |- + Exports 'flextable' objects to 'xlsx' files, + utilizing functionalities provided by 'flextable' and 'openxlsx2'. + date_publication: '2025-02-26' + bug_reports: https://github.com/pteridin/flexlsx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flexlsx + url_git: https://github.com/pteridin/flexlsx +flexmet: + version: '1.1' + title: |- + Flexible Latent Trait Metrics using the Filtered Monotonic + Polynomial Item Response Model + maintainer: Leah Feuerstahler + description: |- + Application of the filtered monotonic polynomial (FMP) item response + model to flexibly fit item response models. The package includes tools that + allow the item response model to be build on any monotonic transformation of + the latent trait metric, as described by Feuerstahler (2019) . + date_publication: '2021-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexmet + url_git: '' +flexmix: + version: 2.3-20 + title: Flexible Mixture Modeling + maintainer: Bettina Gruen + description: |- + A general framework for finite mixtures of regression + models using the EM algorithm is implemented. The E-step and all + data handling are provided, while the M-step can be supplied by the + user to easily define new models. Existing drivers implement + mixtures of standard linear models, generalized linear models and + model-based clustering. + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexmix + url_git: '' +flexmixNL: + version: 0.0.1 + title: Finite Mixture Modeling of Generalized Nonlinear Models + maintainer: Sanela Omerovic + description: The fitting of mixtures of generalized nonlinear models is implemented + as an extension of the existing package 'flexmix'. + date_publication: '2019-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexmixNL + url_git: '' +flexmsm: + version: 0.1.2 + title: A General Framework for Flexible Multi-State Survival Modelling + maintainer: Alessia Eletti + description: |- + A general estimation framework for multi-state Markov processes with flexible specification of the transition intensities. + The log-transition intensities can be specified through Generalised Additive Models which allow for virtually any type of covariate + effect. Elementary specifications such as time-homogeneous processes and simple parametric forms are also supported. There are + no limitations on the type of process one can assume, with both forward and backward transitions allowed and virtually any number + of states. + date_publication: '2024-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexmsm + url_git: '' +flexOR: + version: 1.0.0 + title: Flexible Odds Ratio Curves + maintainer: Marta Azevedo + description: Provides flexible odds ratio curves that enable modeling non-linear + relationships between continuous predictors and binary outcomes. This package + facilitates a deeper understanding of the impact of each continuous predictor + on the outcome by presenting results in terms of odds ratio (OR) curves based + on splines. These curves allow for comparison against a specified reference value, + aiding in the interpretation of the predictor's effect. + date_publication: '2024-04-16' + bug_reports: https://github.com/martaaaa/flexOR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flexOR + url_git: https://github.com/martaaaa/flexOR +FlexParamCurve: + version: 1.5-6 + title: Tools to Fit Flexible Parametric Curves + maintainer: Stephen Oswald + description: Model selection tools and 'selfStart' functions to fit parametric curves + in 'nls', 'nlsList' and 'nlme' frameworks. + date_publication: '2023-12-11' + bug_reports: '' + url: https://pennstate.academia.edu:443/SteveOswald + url_cran: https://CRAN.R-project.org/package=FlexParamCurve + url_git: '' +flexpolyline: + version: 0.3.0 + title: Flexible Polyline Encoding + maintainer: Merlin Unterfinger + description: |- + Binding to the C++ implementation of the flexible polyline + encoding by HERE . The + flexible polyline encoding is a lossy compressed representation of a list of + coordinate pairs or coordinate triples. The encoding is achieved by: + (1) Reducing the decimal digits of each value; + (2) encoding only the offset from the previous point; + (3) using variable length for each coordinate delta; and + (4) using 64 URL-safe characters to display the result. + date_publication: '2023-02-12' + bug_reports: https://github.com/munterfi/flexpolyline/issues/ + url: https://munterfi.github.io/flexpolyline/ + url_cran: https://CRAN.R-project.org/package=flexpolyline + url_git: https://github.com/munterfi/flexpolyline/ +FlexReg: + version: 1.3.0 + title: Regression Models for Bounded Continuous and Discrete Responses + maintainer: Roberto Ascari + description: Functions to fit regression models for bounded continuous and discrete + responses. In case of bounded continuous responses (e.g., proportions and rates), + available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, + A. (2018) ), the variance-inflated beta (Di Brisco, A. + M., Migliorati, S., Ongaro, A. (2020) ), the beta + (Ferrari, S.L.P., Cribari-Neto, F. (2004) ), + and their augmented versions to handle the presence of zero/one values (Di Brisco, + A. M., Migliorati, S. (2020) ) are implemented. In case + of bounded discrete responses (e.g., bounded counts, such as the number of successes + in n trials), available models are the flexible beta-binomial (Ascari, R., Migliorati, + S. (2021) ), the beta-binomial, and the binomial are implemented. + Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo + (HMC) algorithm (Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2014) + ). Besides, functions to compute residuals, posterior predictives, + goodness of fit measures, convergence diagnostics, and graphical representations + are provided. + date_publication: '2023-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlexReg + url_git: '' +FlexRL: + version: 0.1.0 + title: A Flexible Model for Record Linkage + maintainer: Kayané ROBACH + description: Implementation of the Stochastic Expectation Maximisation (StEM) approach + to Record Linkage described in the paper by K. Robach, S. L. van der Pas, M. A. + van de Wiel and M. H. Hof (2024, ); see 'citation("FlexRL")' + for details. This is a record linkage method, for finding the common set of records + among 2 data sources based on Partially Identifying Variables (PIVs) available + in both sources. It includes modelling of dynamic Partially Identifying Variables + (e.g. postal code) that may evolve over time and registration errors (missing + values and mistakes in the registration). Low memory footprint. + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlexRL + url_git: '' +flexrsurv: + version: 2.0.18 + title: Flexible Relative Survival Analysis + maintainer: Michel Grzebyk + description: |- + Package for parametric relative survival analyses. It allows to model non-linear and + non-proportional effects and both non proportional and non linear effects, using splines (B-spline and truncated power basis), Weighted Cumulative Index of Exposure effect, with correction model for + the life table. Both non proportional and non linear effects are described in + Remontet, L. et al. (2007) and + Mahboubi, A. et al. (2011) . + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flexrsurv + url_git: '' +FlexScan: + version: 0.2.2 + title: Flexible Scan Statistics + maintainer: Zhicheng Du + description: |- + An easy way to conduct flexible scan. + Monte-Carlo method is used to test the spatial clusters given the cases, population, and shapefile. + A table with formal style and a map with clusters are included in the result report. + The method can be referenced at: Toshiro Tango and Kunihiko Takahashi (2005) . + date_publication: '2022-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlexScan + url_git: '' +flexsiteboard: + version: 0.0.7 + title: |- + Breaks Single Page Applications from 'flexdashboard' in Multiple + Files + maintainer: Stephan Struckmann + description: |- + A drop-in replacement for 'flexdashboard' 'Rmd' documents, which + implements an after-knit-hook to split the generated single page application + in one document per main section to reduce rendering load in the web browser + displaying the document. Put all 'JavaScript' stuff needed in all sections + before the first headline featuring navigation menu attributes. This package + is experimental and maybe replaced by a solution inside 'flexdashboard'. + date_publication: '2022-11-15' + bug_reports: https://gitlab.com/libreumg/flexsiteboard/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flexsiteboard + url_git: https://gitlab.com/libreumg/flexsiteboard/ +flexsurv: + version: 2.3.2 + title: Flexible Parametric Survival and Multi-State Models + maintainer: Christopher Jackson + description: |- + Flexible parametric models for time-to-event data, + including the Royston-Parmar spline model, generalized gamma and + generalized F distributions. Any user-defined parametric + distribution can be fitted, given at least an R function defining + the probability density or hazard. There are also tools for + fitting and predicting from fully parametric multi-state models, + based on either cause-specific hazards or mixture models. + date_publication: '2024-08-17' + bug_reports: https://github.com/chjackson/flexsurv/issues + url: http://chjackson.github.io/flexsurv/ + url_cran: https://CRAN.R-project.org/package=flexsurv + url_git: https://github.com/chjackson/flexsurv +flexsurvcure: + version: 1.3.3 + title: Flexible Parametric Cure Models + maintainer: Jordan Amdahl + description: Flexible parametric mixture and non-mixture cure models for time-to-event + data. + date_publication: '2025-02-15' + bug_reports: https://github.com/jrdnmdhl/flexsurvcure/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flexsurvcure + url_git: https://github.com/jrdnmdhl/flexsurvcure +flextable: + version: 0.9.7 + title: Functions for Tabular Reporting + maintainer: David Gohel + description: |- + Use a grammar for creating and customizing pretty tables. + The following formats are supported: 'HTML', 'PDF', 'RTF', 'Microsoft + Word', 'Microsoft PowerPoint' and R 'Grid Graphics'. 'R Markdown', + 'Quarto' and the package 'officer' can be used to produce the result + files. The syntax is the same for the user regardless of the type of + output to be produced. A set of functions allows the creation, + definition of cell arrangement, addition of headers or footers, + formatting and definition of cell content with text and or images. The + package also offers a set of high-level functions that allow tabular + reporting of statistical models and the creation of complex cross + tabulations. + date_publication: '2024-10-27' + bug_reports: https://github.com/davidgohel/flextable/issues + url: https://ardata-fr.github.io/flextable-book/ + url_cran: https://CRAN.R-project.org/package=flextable + url_git: '' +FlexVarJM: + version: 0.1.0 + title: Estimate Joint Models with Subject-Specific Variance + maintainer: Léonie Courcoul + description: Estimation of mixed models including a subject-specific variance which + can be time and covariate dependent. In the joint model framework, the package + handles left truncation and allows a flexible dependence structure between the + competing events and the longitudinal marker. The estimation is performed under + the frequentist framework, using the Marquardt-Levenberg algorithm. (Courcoul, + Tzourio, Woodward, Barbieri, Jacqmin-Gadda (2023) ). + date_publication: '2023-11-20' + bug_reports: https://github.com/LeonieCourcoul/FlexVarJM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FlexVarJM + url_git: https://github.com/LeonieCourcoul/FlexVarJM +FlickrAPI: + version: 0.1.0.1 + title: Access to Flickr API + maintainer: Koki Ando + description: |- + Provides an interface to the Flickr API + and allows R users to download data on Flickr. + date_publication: '2022-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlickrAPI + url_git: '' +flifo: + version: 0.1.5 + title: Don't Get Stuck with Stacks in R + maintainer: Paul Poncet + description: |- + Functions to create and manipulate + FIFO (First In First Out), LIFO (Last In First Out), and NINO (Not In or Never Out) + stacks in R. + date_publication: '2018-07-31' + bug_reports: https://github.com/paulponcet/flifo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flifo + url_git: https://github.com/paulponcet/flifo +flightplot: + version: 0.1.0 + title: Plotting Flight Paths on Maps + maintainer: Mingchu Xu + description: Provides functionality to plot airplane flight paths on maps. The plotted + flight paths follow the great circle of the Earth. + date_publication: '2020-06-29' + bug_reports: https://github.com/xmc811/flightplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flightplot + url_git: https://github.com/xmc811/flightplot +FLightR: + version: 0.5.5 + title: Reconstruct Animal Paths from Solar Geolocation Loggers Data + maintainer: Eldar Rakhimberdiev + description: |- + Spatio-temporal locations of an animal are computed + from annotated data with a hidden Markov model via particle + filter algorithm. The package is relatively robust to varying + degrees of shading. + The hidden Markov model is described in Movement Ecology - Rakhimberdiev et al. (2015) , + general package description is in the Methods in Ecology and Evolution - Rakhimberdiev et al. (2017) + and package accuracy assessed in the Journal of Avian Biology - Rakhimberdiev et al. (2016) . + date_publication: '2024-07-04' + bug_reports: https://github.com/eldarrak/FLightR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FLightR + url_git: '' +flightsbr: + version: 1.0.0 + title: Download Flight and Airport Data from Brazil + maintainer: Rafael H. M. Pereira + description: |- + Download flight and airport data from Brazil’s Civil Aviation Agency + (ANAC) . The data covers detailed + information on aircraft, airports, and airport operations registered + with ANAC. It also includes data on airfares, all international + flights to and from Brazil, and domestic flights within the country. + date_publication: '2024-10-22' + bug_reports: https://github.com/ipeaGIT/flightsbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flightsbr + url_git: https://github.com/ipeaGIT/flightsbr +flimo: + version: 0.1.5 + title: Fixed Landscape Inference Method + maintainer: Sylvain Moinard + description: |- + Likelihood-free inference method for stochastic models. + Uses a deterministic optimizer on simple simulations of the model + that are performed with a prior drawn randomness by applying the inverse transform method. + Is designed to work on its own and also by using the Julia package 'Jflimo' + available on the git page of the project: . + date_publication: '2023-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flimo + url_git: '' +flint: + version: 0.0.3 + title: Fast Library for Number Theory + maintainer: Mikael Jagan + description: |- + An R interface to 'FLINT' , a C library for + number theory. 'FLINT' extends GNU 'MPFR' + and GNU 'MP' with support for arithmetic in + standard rings (the integers, the integers modulo n, the rational, + p-adic, real, and complex numbers) as well as vectors, matrices, + polynomials, and power series over rings. 'FLINT' implements + midpoint-radius interval arithmetic, also known as ball arithmetic, + in the real and complex numbers, enabling computation in arbitrary + precision with rigorous propagation of errors; see Johansson (2017) + . Finally, 'FLINT' provides ball + arithmetic implementations of many special mathematical functions, + with high coverage of reference works such as the NIST Digital + Library of Mathematical Functions . The R + interface defines S4 classes, generic functions, and methods for + representation and basic operations as well as plain R functions + mirroring and vectorizing entry points in the C library. + date_publication: '2025-02-23' + bug_reports: https://github.com/jaganmn/flint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flint + url_git: https://github.com/jaganmn/flint +flintyR: + version: 0.1.0 + title: Simple and Flexible Tests of Sample Exchangeability + maintainer: Alan Aw + description: |- + Given a multivariate dataset and some knowledge about the dependencies + between its features, it is customary to fit a statistical model to the features + to infer parameters of interest. Such a procedure implicitly assumes that the + sample is exchangeable. This package provides a flexible non-parametric test + of this exchangeability assumption, allowing the user to specify the feature + dependencies by hand as long as features can be grouped into disjoint independent sets. + This package also allows users to test a dual hypothesis, which is, given that the + sample is exchangeable, does a proposed grouping of the features into disjoint sets + also produce statistically independent sets of features? See Aw, Spence and Song (2023) + for the accompanying paper. + date_publication: '2023-03-23' + bug_reports: https://github.com/alanaw1/flintyR/issues + url: https://alanaw1.github.io/flintyR/ + url_cran: https://CRAN.R-project.org/package=flintyR + url_git: '' +flip: + version: 2.5.0 + title: Multivariate Permutation Tests + maintainer: Livio Finos + description: |- + It implements many univariate and multivariate permutation (and + rotation) tests. Allowed tests: the t one and two samples, ANOVA, linear + models, Chi Squared test, rank tests (i.e. Wilcoxon, Mann-Whitney, + Kruskal-Wallis), Sign test and Mc Nemar. Test on Linear Models are + performed also in presence of covariates (i.e. nuisance parameters). + The permutation and the rotation methods to get the null distribution of + the test statistics are available. It also implements methods for + multiplicity control such as Westfall & Young minP procedure and Closed + Testing (Marcus, 1976) and k-FWER. Moreover, it allows to test for fixed + effects in mixed effects models. + date_publication: '2018-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flip + url_git: '' +flipbookr: + version: 0.1.0 + title: Parses Code, Creates Partial Code Builds, Delivers Code Movie + maintainer: Evangeline Reynolds + description: Flipbooks present code step-by-step and side-by-side with its output. 'flipbookr' + helps creators build flipbooks efficiently because code pipelines are automatically + parsed and prepped for presentation as flipbooks. + date_publication: '2021-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flipbookr + url_git: '' +flipdownr: + version: 0.1.1 + title: |- + Implement a Countdown in 'RMarkdown' Documents and 'shiny' + Applications + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to create a countdown in 'RMarkdown' documents and 'shiny' applications. + The package is a wrapper of the 'JavaScript' library 'flipdown.js'. See for more info. + date_publication: '2020-11-29' + bug_reports: https://github.com/feddelegrand7/flipdownr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flipdownr + url_git: https://github.com/feddelegrand7/flipdownr +flipdownWidgets: + version: 0.1.0 + title: A Wrapper of JavaScript Library 'flipdown.js' + maintainer: Yongchao Fang + description: Include a countdown in all R + contexts with the convenience of 'htmlwidgets'. + date_publication: '2021-06-30' + bug_reports: https://github.com/fanggong/flipdownWidgets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flipdownWidgets + url_git: https://github.com/fanggong/flipdownWidgets +flippant: + version: 1.5.5 + title: Dithionite Scramblase Assay Analysis + maintainer: Johannes Graumann + description: |- + The lipid scrambling activity of protein extracts and purified + scramblases is often determined using a fluorescence-based assay involving + many manual steps. flippant offers an integrated solution for the analysis + and publication-grade graphical presentation of dithionite scramblase + assays, as well as a platform for review, dissemination and extension of the + strategies it employs. The package's name derives from a play on the fact + that lipid scrambling is also sometimes referred to as 'flipping'. + The package is originally published as Cotton, R.J., Ploier, B., Goren, + M.A., Menon, A.K., and Graumann, J. (2017). "flippant–An R package for the + automated analysis of fluorescence-based scramblase assays." BMC + Bioinformatics 18, 146. . + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flippant + url_git: '' +flipr: + version: 0.3.3 + title: Flexible Inference via Permutations in R + maintainer: Aymeric Stamm + description: |- + A flexible permutation framework for making + inference such as point estimation, confidence + intervals or hypothesis testing, on any kind of data, + be it univariate, multivariate, or more complex such + as network-valued data, topological data, functional + data or density-valued data. + date_publication: '2023-08-23' + bug_reports: https://github.com/LMJL-Alea/flipr/issues/ + url: https://LMJL-Alea.github.io/flipr/ + url_cran: https://CRAN.R-project.org/package=flipr + url_git: https://github.com/LMJL-Alea/flipr/ +flipscores: + version: 1.3.2 + title: Robust Score Testing in GLMs, by Sign-Flip Contributions + maintainer: Livio Finos + description: Provides robust tests for testing in GLMs, by sign-flipping score contributions. + The tests are robust against overdispersion, heteroscedasticity and, in some cases, + ignored nuisance variables. See Hemerik, Goeman and Finos (2020) . + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flipscores + url_git: '' +float: + version: 0.3-2 + title: 32-Bit Floats + maintainer: Drew Schmidt + description: |- + R comes with a suite of utilities for linear algebra with "numeric" + (double precision) vectors/matrices. However, sometimes single precision (or + less!) is more than enough for a particular task. This package extends R's + linear algebra facilities to include 32-bit float (single precision) data. + Float vectors/matrices have half the precision of their "numeric"-type + counterparts but are generally faster to numerically operate on, for a + performance vs accuracy trade-off. The internal representation is an S4 + class, which allows us to keep the syntax identical to that of base R's. + Interaction between floats and base types for binary operators is generally + possible; in these cases, type promotion always defaults to the higher + precision. The package ships with copies of the single precision 'BLAS' and + 'LAPACK', which are automatically built in the event they are not available + on the system. + date_publication: '2023-12-10' + bug_reports: https://github.com/wrathematics/float/issues + url: '' + url_cran: https://CRAN.R-project.org/package=float + url_git: https://github.com/wrathematics/float +flobr: + version: 0.2.3 + title: Convert Files to and from Binary Objects (BLOBs) + maintainer: Joe Thorley + description: |- + Converts files to and from flobs. A flob is a file that was + read into binary in integer-mode as little endian, saved as the single + element of a named list (where the name is the name of the original + file) and then serialized before being coerced into a blob. Flobs are + useful for writing and reading files to and from databases. + date_publication: '2022-08-25' + bug_reports: https://github.com/poissonconsulting/flobr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flobr + url_git: https://github.com/poissonconsulting/flobr +flock: + version: '0.7' + title: Process Synchronization Using File Locks + maintainer: Ivan Popivanov + description: Implements synchronization between R processes (spawned by using the + "parallel" package for instance) using file locks. Supports both exclusive and + shared locking. + date_publication: '2016-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flock + url_git: '' +flocker: + version: 1.0-0 + title: Flexible Occupancy Estimation with Stan + maintainer: Jacob B. Socolar + description: |- + Fit occupancy models in 'Stan' via 'brms'. The full variety + of 'brms' formula-based effects structures are available to use in + multiple classes of occupancy model, including single-season + models, models with data augmentation for never-observed species, + dynamic (multiseason) models with explicit colonization and extinction + processes, and dynamic models with autologistic occupancy dynamics. + Formulas can be specified for all relevant distributional terms, + including detection and one or more of occupancy, colonization, + extinction, and autologistic depending on the model type. Several + important forms of model post-processing are provided. References: + Bürkner (2017) ; Carpenter et al. (2017) + ; Socolar & Mills (2023) + . + date_publication: '2024-02-05' + bug_reports: https://github.com/jsocolar/flocker/issues + url: https://jsocolar.github.io/flocker/ + url_cran: https://CRAN.R-project.org/package=flocker + url_git: https://github.com/jsocolar/flocker +flood: + version: 0.1.1 + title: |- + Statistical Methods for the (Regional) Analysis of Flood + Frequency + maintainer: Friederike Deiters + description: |- + Includes several statistical methods for the estimation of parameters and high quantiles of river flow distributions. The focus is on regional estimation based on homogeneity assumptions and computed from multivariate observations (multiple measurement stations). + For details see Kinsvater et al. (2017) . + date_publication: '2017-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flood + url_git: '' +FloodFreqPlot: + version: 0.1.0 + title: Flood Probability Plotting and Graphical Frequency Analysis + maintainer: Ali Ahani + description: |- + Plotting flood quantiles and their corresponding probabilities (return periods) on the probability papers. + The details of relevant methods are available in Chow et al (1988, ISBN: 007070242X, 9780070702424), and + Bobee and Ashkar (1991, ISBN: 0918334683, 9780918334688). + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FloodFreqPlot + url_git: '' +FLOPART: + version: 2024.6.19 + title: Functional Labeled Optimal Partitioning + maintainer: Toby Dylan Hocking + description: |- + Provides an efficient 'C++' code for computing an + optimal segmentation model + with Poisson loss, + up-down constraints, + and label constraints, + as described by Kaufman et al. (2024) . + date_publication: '2024-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FLOPART + url_git: '' +flora: + version: 0.3.4 + title: Tools for Interacting with the Brazilian Flora 2020 + maintainer: Gustavo Carvalho + description: |- + Tools to quickly compile taxonomic and distribution data from + the Brazilian Flora 2020. + date_publication: '2020-04-28' + bug_reports: http://www.github.com/gustavobio/flora/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flora + url_git: http://www.github.com/gustavobio/flora +florabr: + version: 1.3.0 + title: Explore Flora e Funga do Brasil Database + maintainer: Weverton Trindade + description: A collection of functions designed to retrieve, filter and spatialize + data from the Flora e Funga do Brasil dataset. For more information about the + dataset, please visit . + date_publication: '2024-09-09' + bug_reports: https://github.com/wevertonbio/florabr/issues + url: https://wevertonbio.github.io/florabr/ + url_cran: https://CRAN.R-project.org/package=florabr + url_git: '' +FLORAL: + version: 0.4.0 + title: Fit Log-Ratio Lasso Regression for Compositional Data + maintainer: Teng Fei + description: Log-ratio Lasso regression for continuous, binary, and survival outcomes + with (longitudinal) compositional features. See Fei and others (2024) . + date_publication: '2025-02-17' + bug_reports: https://github.com/vdblab/FLORAL/issues + url: https://vdblab.github.io/FLORAL/ + url_cran: https://CRAN.R-project.org/package=FLORAL + url_git: '' +flourishcharts: + version: 1.0.0.3 + title: '''Flourish'' for ''R'' and ''Python''' + maintainer: Zoe Meers + description: |- + Interactive data visualization for data practitioners. 'flourishcharts' allows users to visualize their data + using 'Flourish' graphs that are grounded in data storytelling principles. Users can create racing bar & line + charts, as well as other interactive elements commonly found in 'D3' graphics, easily in 'R' and 'Python'. + The package relies on an enterprise API provided by 'Flourish', a data visualization platform . + date_publication: '2024-10-22' + bug_reports: https://github.com/canva-public/flourishcharts/issues + url: https://www.canva.dev/opensource/flourish-charts/ + url_cran: https://CRAN.R-project.org/package=flourishcharts + url_git: https://github.com/canva-public/flourishcharts +flow: + version: 0.2.0 + title: View and Browse Code Using Flow Diagrams + maintainer: Antoine Fabri + description: |- + Visualize as flow diagrams the logic of functions, expressions or + scripts in a static way or when running a call, visualize the dependencies between + functions or between modules in a shiny app, and more. + date_publication: '2023-06-06' + bug_reports: https://github.com/moodymudskipper/flow/issues + url: https://moodymudskipper.github.io/flow/ + url_cran: https://CRAN.R-project.org/package=flow + url_git: https://github.com/moodymudskipper/flow +flowchart: + version: 0.7.0 + title: Tidy Flowchart Generator + maintainer: Pau Satorra + description: Creates participant flow diagrams directly from a dataframe. Representing + the flow of participants through each stage of a study, especially in clinical + trials, is essential to assess the generalisability and validity of the results. + This package provides a set of functions that can be combined with a pipe operator + to create all kinds of flowcharts from a data frame in an easy way. + date_publication: '2025-01-20' + bug_reports: https://github.com/bruigtp/flowchart/issues + url: https://bruigtp.github.io/flowchart/ + url_cran: https://CRAN.R-project.org/package=flowchart + url_git: '' +FlowerMate: + version: '1.0' + title: Reciprocity Indices for Style-Polymorphic Plants + maintainer: A. J. Muñoz-Pajares Developer + description: 'Computes unidimensional and multidimensional Reciprocity and Inaccuracy + indices. These indices are applicable to common heterostylous populations and + to any other type of stylar dimorphic and trimorphic populations, such as in enantiostylous + and three-dimensional heterostylous plants. Simón-Porcar, V., A. J. Muñoz-Pajares, + J. Arroyo, and S. D. Johnson. (in press) "FlowerMate: multidimensional reciprocity + and inaccuracy indices for style-polymorphic plant populations."' + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlowerMate + url_git: '' +flowmapblue: + version: 0.0.2 + title: Flow Map Rendering + maintainer: Egor Kotov + description: |- + Create interactive flow maps using 'FlowmapBlue' 'TypeScript' + library , which is a free + tool for representing aggregated numbers of movements between + geographic locations as flow maps. It is used to visualize urban + mobility, commuting behavior, bus, subway and air travels, bicycle + sharing, human and bird migration, refugee flows, freight + transportation, trade, supply chains, scientific collaboration, + epidemiological and historical data and many other topics. The package + allows to either create standalone flow maps in form of 'htmlwidgets' + and save them in 'HTML' files, or integrate flow maps into 'Shiny' + applications. + date_publication: '2024-09-05' + bug_reports: https://github.com/FlowmapBlue/flowmapblue.R/issues + url: https://flowmapblue.github.io/flowmapblue.R/ + url_cran: https://CRAN.R-project.org/package=flowmapblue + url_git: https://github.com/FlowmapBlue/flowmapblue.R +flowmapper: + version: 0.1.3 + title: |- + Draw Flows (Migration, Goods, Money, Information) on 'ggplot2' + Plots + maintainer: Johannes Mast + description: Adds flow maps to 'ggplot2' plots. The flow maps consist of 'ggplot2' + layers which visualize the nodes as circles and the bilateral flows between the + nodes as bidirectional half-arrows. + date_publication: '2024-11-15' + bug_reports: https://github.com/JohMast/flowmapper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flowmapper + url_git: https://github.com/JohMast/flowmapper +flowml: + version: 0.1.3 + title: |- + A Backend for a 'nextflow' Pipeline that Performs + Machine-Learning-Based Modeling of Biomedical Data + maintainer: Sebastian Malkusch + description: |- + Provides functionality to perform machine-learning-based modeling in a computation pipeline. + Its functions contain the basic steps of machine-learning-based knowledge discovery workflows, + including model training and optimization, model evaluation, and model testing. + To perform these tasks, the package builds heavily on existing machine-learning packages, + such as 'caret' and associated packages. + The package can train multiple models, optimize model hyperparameters by performing a grid search + or a random search, and evaluates model performance by different metrics. + Models can be validated either on a test data set, or in case of a small sample size + by k-fold cross validation or repeated bootstrapping. + It also allows for 0-Hypotheses generation by performing permutation experiments. + Additionally, it offers methods of model interpretation and item categorization + to identify the most informative features from a high dimensional data space. + The functions of this package can easily be integrated into computation pipelines + (e.g. 'nextflow' ) and hereby improve scalability, + standardization, and re-producibility in the context of machine-learning. + date_publication: '2024-02-16' + bug_reports: https://github.com/Boehringer-Ingelheim/flowml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=flowml + url_git: https://github.com/Boehringer-Ingelheim/flowml +FlowRegEnvCost: + version: 0.1.1 + title: The Environmental Costs of Flow Regulation + maintainer: Javier Martinez-Lopez + description: An application to calculate the daily environmental costs of river + flow regulation by dams based on García de Jalon et al. 2017 . + date_publication: '2017-10-18' + bug_reports: https://github.com/garciadejalon/FlowRegEnvCost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FlowRegEnvCost + url_git: https://github.com/garciadejalon/FlowRegEnvCost +FlowScreen: + version: 1.2.6 + title: Daily Streamflow Trend and Change Point Screening + maintainer: Jennifer Dierauer + description: |- + Screens daily streamflow time series for temporal trends and + change-points. This package has been primarily developed for assessing the + quality of daily streamflow time series. It also contains tools for plotting + and calculating many different streamflow metrics. The package can be used to + produce summary screening plots showing change-points and significant temporal + trends for high flow, low flow, and/or baseflow statistics, or it can be used + to perform more detailed hydrological time series analyses. The package was + designed for screening daily streamflow time series from Water Survey Canada + and the United States Geological Survey but will also work with streamflow time + series from many other agencies. + date_publication: '2019-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FlowScreen + url_git: '' +flowTraceR: + version: 0.1.0 + title: |- + Tracing Information Flow for Inter-Software Comparisons in Mass + Spectrometry-Based Bottom-Up Proteomics + maintainer: Oliver Kardell + description: Useful functions to standardize software outputs from ProteomeDiscoverer, + Spectronaut, DIA-NN and MaxQuant on precursor, modified peptide and proteingroup + level and to trace software differences for identifications such as varying proteingroup + denotations for common precursor. + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flowTraceR + url_git: https://github.com/OKdll/flowTraceR +flps: + version: 1.1.0 + title: Fully-Latent Principal Stratification + maintainer: Sooyong Lee + description: Simulation and analysis of Fully-Latent Principal Stratification (FLPS) + with measurement models. Lee, Adam, Kang, & Whittaker (2023). . + This package is supported by the Institute of Education Sciences, U.S. Department + of Education, through Grant R305D210036. + date_publication: '2024-04-21' + bug_reports: '' + url: https://sooyongl.github.io/flps/ + url_cran: https://CRAN.R-project.org/package=flps + url_git: '' +FLR: + version: '1.0' + title: Fuzzy Logic Rule Classifier + maintainer: Constantinos Mavridis + description: FLR algorithm for classification + date_publication: '2014-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FLR + url_git: '' +flsa: + version: 1.5.5 + title: Path Algorithm for the General Fused Lasso Signal Approximator + maintainer: Holger Hoefling + description: |- + Implements a path algorithm for the Fused Lasso Signal Approximator. + For more details see the help files or the article by Hoefling (2009) . + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flsa + url_git: '' +Fluidigm: + version: '0.2' + title: Handling Fluidigm Data + maintainer: Daniel Fischer + description: Designed to streamline the process of analyzing genotyping data from + Fluidigm machines, this package offers a suite of tools for data handling and + analysis. It includes functions for converting Fluidigm data to format used by + 'PLINK', estimating errors, calculating pairwise similarities, determining pairwise + similarity loci, and generating a similarity matrix. + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Fluidigm + url_git: '' +fluidsynth: + version: 1.0.2 + title: Read and Play Digital Music (MIDI) + maintainer: Jeroen Ooms + description: |- + Bindings to 'libfluidsynth' to parse and synthesize MIDI files. It can + read MIDI into a data frame, play it on the local audio device, or convert into + an audio file. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/fluidsynth/issues + url: https://docs.ropensci.org/fluidsynth/https://ropensci.r-universe.dev/fluidsynth + url_cran: https://CRAN.R-project.org/package=fluidsynth + url_git: '' +FluMoDL: + version: 0.0.3 + title: Influenza-Attributable Mortality with Distributed-Lag Models + maintainer: Theodore Lytras + description: |- + Functions to estimate the mortality attributable to + influenza and temperature, using distributed-lag nonlinear models + (DLNMs), as first implemented in + Lytras et al. (2019) . + Full descriptions of underlying DLNM methodology in Gasparrini et al. + (DLNMs), + (attributable risk from DLNMs) and + (multivariate meta-analysis). + date_publication: '2019-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FluMoDL + url_git: '' +fluoSurv: + version: 1.0.0 + title: Estimate Insect Survival from Fluorescence Data + maintainer: Jean-Baptiste Ferdy + description: |- + Use spectrophotometry measurements performed on insects as a way to infer pathogens + virulence. Insect movements cause fluctuations in fluorescence signal, and functions are + provided to estimate when the insect has died as the moment when variance in autofluorescence + signal drops to zero. The package provides functions to obtain this estimate together with + functions to import spectrophotometry data from a Biotek microplate reader. Details of the method + are given in Parthuisot et al. (2018) . + date_publication: '2018-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fluoSurv + url_git: '' +fluspect: + version: 1.0.0 + title: Fluspect-B + maintainer: Alberto Hornero + description: |- + A model for leaf fluorescence, reflectance and transmittance spectra. It implements + the model introduced by Vilfan et al. (2016) . Fluspect-B + calculates the emission of ChlF on both the illuminated and shaded side of the leaf. + Other input parameters are chlorophyll and carotenoid concentrations, leaf water, dry matter + and senescent material (brown pigments) content, leaf mesophyll structure parameter and ChlF + quantum efficiency for the two photosystems, PS-I and PS-II. + date_publication: '2018-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fluspect + url_git: '' +flux: + version: 0.3-0.1 + title: Flux Rate Calculation from Dynamic Closed Chamber Measurements + maintainer: Gerald Jurasinski + description: |- + Functions for the calculation of greenhouse gas flux rates + from closed chamber concentration measurements. The package follows + a modular concept: Fluxes can be calculated in just two simple steps + or in several steps if more control in details is wanted. Additionally + plot and preparation functions as well as functions for modelling + gpp and reco are provided. + date_publication: '2022-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flux + url_git: '' +fluxible: + version: 1.0.0 + title: Ecosystem Gas Fluxes Calculations for Closed Loop Chamber Setup + maintainer: Joseph Gaudard + description: |- + Processes the raw data from closed loop flux chamber (or tent) + setups into ecosystem gas fluxes usable for analysis. It goes from a + data frame of gas concentration over time (which can contain several + measurements) and a meta data file indicating which measurement was done + when, to a data frame of ecosystem gas fluxes including quality diagnostics. + Functions provided include different models (exponential as described in + Zhao et al (2018) , quadratic and + linear) to estimate the fluxes from the raw data, quality assessment, + plotting for visual check and calculation of fluxes based on the setup + specific parameters (chamber size, plot area, ...). + date_publication: '2025-02-13' + bug_reports: https://github.com/Plant-Functional-Trait-Course/fluxible/issues + url: https://plant-functional-trait-course.github.io/fluxible/ + url_cran: https://CRAN.R-project.org/package=fluxible + url_git: https://github.com/Plant-Functional-Trait-Course/fluxible +fluxweb: + version: 0.2.0 + title: Estimate Energy Fluxes in Food Webs + maintainer: Benoit Gauzens + description: Compute energy fluxes in trophic networks, from resources to their + consumers, and can be applied to systems ranging from simple two-species interactions + to highly complex food webs. It implements the approach described in Gauzens et + al. (2017) to calculate energy fluxes, which are also used + to calculate equilibrium stability. + date_publication: '2018-09-27' + bug_reports: '' + url: https://www.biorxiv.org/content/early/2017/12/06/229450 + url_cran: https://CRAN.R-project.org/package=fluxweb + url_git: '' +flying: + version: 0.1.3 + title: Simulation of Bird Flight Range + maintainer: Brian Masinde + description: |- + Functions for range estimation in birds based on Pennycuick (2008) + and Pennycuick (1975), 'Flight' program which compliments Pennycuick (2008) + requires manual entry of birds which can be tedious when there are thousands + of birds to estimate. Implemented are two ODE methods discussed in Pennycuick (1975) + and time-marching computation method "constant muscle mass" as in Pennycuick (1998). + See Pennycuick (1975, ISBN:978-0-12-249405-5), Pennycuick (1998) , + and Pennycuick (2008, ISBN:9780080557816). + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=flying + url_git: '' +FlyingR: + version: 0.2.2 + title: Simulation of Bird Flight Range + maintainer: Brian Masinde + description: |- + Functions for range estimation in birds based on Pennycuick (2008) + and Pennycuick (1975), 'Flight' program which compliments Pennycuick (2008) + requires manual entry of birds which can be tedious when there are hundreds + of birds to estimate. Implemented are two ODE methods discussed in Pennycuick (1975) + and time-marching computation methods as in Pennycuick (1998) and Pennycuick (2008). + See Pennycuick (1975, ISBN:978-0-12-249405-5), Pennycuick (1998) , + and Pennycuick (2008, ISBN:9780080557816). + date_publication: '2022-06-27' + bug_reports: https://github.com/BMasinde/FlyingR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FlyingR + url_git: https://github.com/BMasinde/FlyingR +fma: + version: '2.5' + title: |- + Data Sets from "Forecasting: Methods and Applications" by + Makridakis, Wheelwright & Hyndman (1998) + maintainer: Rob Hyndman + description: 'All data sets from "Forecasting: methods and applications" by Makridakis, + Wheelwright & Hyndman (Wiley, 3rd ed., 1998) .' + date_publication: '2023-02-15' + bug_reports: https://github.com/robjhyndman/fma/issues + url: https://pkg.robjhyndman.com/fma/ + url_cran: https://CRAN.R-project.org/package=fma + url_git: https://github.com/robjhyndman/fma +FMAdist: + version: 0.1.2 + title: Frequentist Model Averaging Distribution + maintainer: Xi Jiang + description: Creation of an input model (fitted distribution) via the frequentist + model averaging (FMA) approach and generate random-variates from the distribution + specified by "myfit" which is the fitted input model via the FMA approach. See + W. X. Jiang and B. L. Nelson (2018), "Better Input Modeling via Model Averaging," + Proceedings of the 2018 Winter Simulation Conference, IEEE Press, 1575-1586. + date_publication: '2022-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMAdist + url_git: '' +FMAT: + version: '2024.7' + title: The Fill-Mask Association Test + maintainer: Han-Wu-Shuang Bao + description: |- + The Fill-Mask Association Test ('FMAT') + + is an integrative and probability-based method using + Masked Language Models to measure conceptual associations + (e.g., attitudes, biases, stereotypes, social norms, cultural values) + as propositions in natural language. + Supported language models include 'BERT' + and its variants available at 'Hugging Face' + . + Methodological references and installation guidance are provided at + . + date_publication: '2024-07-29' + bug_reports: https://github.com/psychbruce/FMAT/issues + url: https://psychbruce.github.io/FMAT/ + url_cran: https://CRAN.R-project.org/package=FMAT + url_git: '' +FMC: + version: 1.0.1 + title: Factorial Experiments with Minimum Level Changes + maintainer: Shwetank Lall + description: |- + Generate cost effective minimally changed run sequences + for symmetrical as well as asymmetrical factorial + designs. + date_publication: '2022-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMC + url_git: '' +FMCCSD: + version: '1.0' + title: Efficient Estimation of Clustered Current Status Data + maintainer: Tong Wang + description: |- + Current status data abounds + in the field of epidemiology and public health, where the only observable data for a subject is + the random inspection time and the event status at inspection. Motivated by such a current status + data from a periodontal study where data are inherently clustered, + we propose a unified methodology to analyze such complex data. + date_publication: '2020-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMCCSD + url_git: '' +fmcmc: + version: 0.5-2 + title: A friendly MCMC framework + maintainer: George Vega Yon + description: |- + Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) + framework for implementing Metropolis-Hastings algorithm in a modular way + allowing users to specify automatic convergence checker, personalized + transition kernels, and out-of-the-box multiple MCMC chains using + parallel computing. Most of the methods implemented in this package can + be found in Brooks et al. (2011, ISBN 9781420079425). Among the methods + included, we have: Haario (2001) + Adaptive Metropolis, Vihola (2012) + Robust Adaptive Metropolis, and Thawornwattana et + al. (2018) Mirror transition kernels. + date_publication: '2023-08-29' + bug_reports: https://github.com/USCbiostats/fmcmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fmcmc + url_git: https://github.com/USCbiostats/fmcmc +fmdu: + version: 0.2.1 + title: (Restricted) [external] Multidimensional Unfolding + maintainer: Frank Busing + description: |- + Functions for performing (external) multidimensional unfolding. + Restrictions (fixed coordinates or model restrictions) are available for both row and column coordinates in all combinations. + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fmdu + url_git: '' +FME: + version: 1.3.6.3 + title: |- + A Flexible Modelling Environment for Inverse Modelling, + Sensitivity, Identifiability and Monte Carlo Analysis + maintainer: Karline Soetaert + description: |- + Provides functions to help in fitting models to data, to + perform Monte Carlo, sensitivity and identifiability analysis. It is + intended to work with models be written as a set of differential + equations that are solved either by an integration routine from + package 'deSolve', or a steady-state solver from package + 'rootSolve'. However, the methods can also be used with other types of + functions. + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FME + url_git: http://fme.r-forge.r-project.org/ +fmeffects: + version: 0.1.4 + title: Model-Agnostic Interpretations with Forward Marginal Effects + maintainer: Holger Löwe + description: 'Create local, regional, and global explanations for any machine learning + model with forward marginal effects. You provide a model and data, and ''fmeffects'' + computes feature effects. The package is based on the theory in: C. A. Scholbeck, + G. Casalicchio, C. Molnar, B. Bischl, and C. Heumann (2022) .' + date_publication: '2024-11-05' + bug_reports: https://github.com/holgstr/fmeffects/issues + url: https://holgstr.github.io/fmeffects/ + url_cran: https://CRAN.R-project.org/package=fmeffects + url_git: https://github.com/holgstr/fmeffects +fmerPack: + version: 0.0-1 + title: Tools of Heterogeneity Pursuit via Finite Mixture Effects Model + maintainer: Yan Li + description: Heterogeneity pursuit methodologies for regularized finite mixture + regression by effects-model formulation proposed by Li et al. (2021) . + date_publication: '2021-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fmerPack + url_git: '' +fmesher: + version: 0.2.0 + title: Triangle Meshes and Related Geometry Tools + maintainer: Finn Lindgren + description: |- + Generate planar and spherical triangle meshes, + compute finite element calculations for 1- and 2-dimensional flat and curved + manifolds with associated basis function spaces, methods for lines and + polygons, and transparent handling of coordinate reference systems and + coordinate transformation, including 'sf' and 'sp' geometries. The core + 'fmesher' library code was originally part of the 'INLA' package, and + implements parts of "Triangulations and Applications" by + Hjelle and Daehlen (2006) . + date_publication: '2024-11-06' + bug_reports: https://github.com/inlabru-org/fmesher/issues + url: https://inlabru-org.github.io/fmesher/ + url_cran: https://CRAN.R-project.org/package=fmesher + url_git: https://github.com/inlabru-org/fmesher +fmf: + version: 1.1.1 + title: Fast Class Noise Detector with Multi-Factor-Based Learning + maintainer: Wanwan Zheng + description: A fast class noise detector which provides noise score for each observations. + The package takes advantage of 'RcppArmadillo' to speed up the calculation of + distances between observations. + date_publication: '2020-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fmf + url_git: '' +FMM: + version: 0.3.1 + title: Rhythmic Patterns Modeling by FMM Models + maintainer: Itziar Fernandez + description: Provides a collection of functions to fit and explore single, multi-component + and restricted Frequency Modulated Moebius (FMM) models. 'FMM' is a nonlinear + parametric regression model capable of fitting non-sinusoidal shapes in rhythmic + patterns. Details about the mathematical formulation of 'FMM' models can be found + in Rueda et al. (2019) . + date_publication: '2021-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMM + url_git: https://github.com/alexARC26/FMM +FMP: + version: '1.4' + title: Filtered Monotonic Polynomial IRT Models + maintainer: Niels G. Waller + description: Estimates Filtered Monotonic Polynomial IRT Models as described by + Liang and Browne (2015) . + date_publication: '2016-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMP + url_git: '' +fmpapi: + version: 0.2.0 + title: Flexible Client for the 'Financial Modeling Prep' API + maintainer: Christoph Scheuch + description: |- + Provides a flexible interface to the 'Financial Modeling Prep' API + . The package + supports all available endpoints and parameters, enabling R users + to interact with a wide range of financial data. + date_publication: '2024-12-19' + bug_reports: https://github.com/tidy-finance/r-fmpapi/issues + url: https://tidy-finance.github.io/r-fmpapi/ + url_cran: https://CRAN.R-project.org/package=fmpapi + url_git: https://github.com/tidy-finance/r-fmpapi +fmpcloudr: + version: 0.1.5 + title: R Access to the 'FMP Cloud' and 'Financial Modeling Prep' API + maintainer: Anthony Balentine + description: |- + Use R to access to the 'FMP Cloud' API and + 'Financial Modeling Prep' API . + Data available includes stock prices, market indexes, company fundamentals, + 13F holdings data, and much more. A valid API token must be set to enable + functions. + date_publication: '2021-03-01' + bug_reports: https://github.com/exploringfinance/fmpcloudr/issues + url: https://exploringfinance.github.io/fmpcloudr/ + url_cran: https://CRAN.R-project.org/package=fmpcloudr + url_git: '' +FMradio: + version: 1.1.1 + title: Factor Modeling for Radiomics Data + maintainer: Carel F.W. Peeters + description: Functions that support stable prediction and classification with radiomics + data through factor-analytic modeling. For details, see Peeters et al. (2019) + . + date_publication: '2019-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMradio + url_git: https://github.com/CFWP/FMradio +fmri: + version: 1.9.12.1 + title: Analysis of fMRI Experiments + maintainer: Karsten Tabelow + description: |- + Contains R-functions to perform an fMRI analysis as described in + Polzehl and Tabelow (2019) , + Tabelow et al. (2006) , + Polzehl et al. (2010) , + Tabelow and Polzehl (2011) . + date_publication: '2024-07-24' + bug_reports: '' + url: https://www.wias-berlin.de/software/imaging/ + url_cran: https://CRAN.R-project.org/package=fmri + url_git: '' +fmriqa: + version: 0.3.0 + title: Functional MRI Quality Assurance Routines + maintainer: Martin Wilson + description: |- + Methods for performing fMRI quality assurance (QA) measurements of + test objects. Heavily based on the fBIRN procedures detailed by Friedman and + Glover (2006) . + date_publication: '2018-02-19' + bug_reports: https://github.com/martin3141/fmriqa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fmriqa + url_git: '' +fMRIscrub: + version: 0.14.5 + title: Scrubbing and Other Data Cleaning Routines for fMRI + maintainer: Amanda Mejia + description: |- + Data-driven fMRI denoising with projection scrubbing (Pham et al + (2022) ). Also includes routines for + DVARS (Derivatives VARianceS) (Afyouni and Nichols (2018) + ), motion scrubbing (Power et al + (2012) ), aCompCor (anatomical + Components Correction) (Muschelli et al (2014) + ), detrending, and nuisance + regression. Projection scrubbing is also applicable to other + outlier detection tasks involving high-dimensional data. + date_publication: '2023-10-25' + bug_reports: https://github.com/mandymejia/fMRIscrub/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fMRIscrub + url_git: https://github.com/mandymejia/fMRIscrub +fMRItools: + version: 0.4.7 + title: Routines for Common fMRI Processing Tasks + maintainer: Amanda Mejia + description: |- + Supports fMRI (functional magnetic resonance imaging) + analysis tasks including reading in 'CIFTI', 'GIFTI' and + 'NIFTI' data, temporal filtering, nuisance regression, and + aCompCor (anatomical Components Correction) (Muschelli et al. + (2014) ). + date_publication: '2024-05-30' + bug_reports: https://github.com/mandymejia/fMRItools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fMRItools + url_git: https://github.com/mandymejia/fMRItools +fmsb: + version: 0.7.6 + title: Functions for Medical Statistics Book with some Demographic Data + maintainer: Minato Nakazawa + description: |- + Several utility functions for the book entitled + "Practices of Medical and Health Data Analysis using R" + (Pearson Education Japan, 2007) with Japanese demographic + data and some demographic analysis related functions. + date_publication: '2024-01-19' + bug_reports: '' + url: https://minato.sip21c.org/msb/ + url_cran: https://CRAN.R-project.org/package=fmsb + url_git: '' +FMsmsnReg: + version: '1.0' + title: |- + Regression Models with Finite Mixtures of Skew Heavy-Tailed + Errors + maintainer: Luis Benites Sanchez + description: Fit linear regression models where the random errors follow a finite + mixture of of Skew Heavy-Tailed Errors. + date_publication: '2016-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMsmsnReg + url_git: '' +FMStable: + version: 0.1-4 + title: Finite Moment Stable Distributions + maintainer: Daniel Wilson + description: |- + Some basic procedures for dealing + with log maximally skew stable distributions, which are also + called finite moment log stable distributions. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FMStable + url_git: '' +fmt: + version: '2.0' + title: Variance Estimation of FMT Method (Fully Moderated T-Statistic) + maintainer: Lianbo Yu + description: |- + The FMT method computes posterior residual variances to be used in + the denominator of a moderated t-statistic from a linear model analysis of + gene expression data. It is an extension of the moderated t-statistic + originally proposed by Smyth (2004) . + LOESS local regression and empirical Bayesian method are used to estimate + gene specific prior degrees of freedom and prior variance based on average + gene intensity levels. The posterior residual variance in the denominator is + a weighted average of prior and residual variance and the weights are prior + degrees of freedom and residual variance degrees of freedom. The degrees of + freedom of the moderated t-statistic is simply the sum of prior and residual + variance degrees of freedom. + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fmt + url_git: '' +fmtr: + version: 1.6.8 + title: Easily Apply Formats to Data + maintainer: David Bosak + description: |- + Contains a set of functions that can be used to apply + formats to data frames or vectors. The package aims to provide + functionality similar to that of SAS® formats. Formats are assigned to + the format attribute on data frame columns. Then when the fdata() + function is called, a new data frame is created with the column data + formatted as specified. The package also contains a value() function + to create a user-defined format, similar to a SAS® user-defined format. + date_publication: '2025-01-28' + bug_reports: https://github.com/dbosak01/fmtr/issues + url: https://fmtr.r-sassy.org + url_cran: https://CRAN.R-project.org/package=fmtr + url_git: https://github.com/dbosak01/fmtr +fMultivar: + version: '4031.84' + title: |- + Rmetrics - Modeling of Multivariate Financial Return + Distributions + maintainer: Stefan Theussl + description: |- + A collection of functions inspired by Venables and Ripley (2002) + and Azzalini and Capitanio (1999) to manage, investigate and analyze + bivariate and multivariate data sets of financial returns. + date_publication: '2023-07-11' + bug_reports: '' + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fMultivar + url_git: '' +fmx: + version: 0.1.2 + title: Finite Mixture Parametrization + maintainer: Tingting Zhan + description: |- + A parametrization framework for finite mixture + distribution using S4 objects. Density, cumulative + density, quantile and simulation functions are defined. + Currently normal, Tukey g-&-h, skew-normal and skew-t + distributions are well tested. The gamma, negative + binomial distributions are being tested. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fmx + url_git: '' +fnets: + version: 0.1.6 + title: |- + Factor-Adjusted Network Estimation and Forecasting for + High-Dimensional Time Series + maintainer: Haeran Cho + description: |- + Implements methods for network estimation and forecasting of high-dimensional time series + exhibiting strong serial and cross-sectional correlations under a factor-adjusted vector autoregressive model. + See Barigozzi, Cho and Owens (2024+) for further descriptions of FNETS methodology and + Owens, Cho and Barigozzi (2024+) accompanying the R package. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fnets + url_git: '' +FNN: + version: 1.1.4.1 + title: Fast Nearest Neighbor Search Algorithms and Applications + maintainer: Shengqiao Li + description: |- + Cover-tree and kd-tree fast k-nearest neighbor search algorithms and related applications + including KNN classification, regression and information measures are implemented. + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FNN + url_git: '' +fNonlinear: + version: '4041.82' + title: Rmetrics - Nonlinear and Chaotic Time Series Modelling + maintainer: Paul Smith + description: |- + Provides a collection of functions for testing various aspects of + univariate time series including independence and neglected + nonlinearities. Further provides functions to investigate the chaotic + behavior of time series processes and to simulate different types of chaotic + time series maps. + date_publication: '2024-09-08' + bug_reports: '' + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fNonlinear + url_git: '' +FnR: + version: 1.1.0 + title: Inbreeding and Numerator Relationship Coefficients + maintainer: Mohammad Ali Nilforooshan + description: Compute inbreeding coefficients using the method of Meuwissen and Luo + (1992) , and numerator relationship coefficients + between individuals using the method of Van Vleck (2007) . + date_publication: '2024-05-05' + bug_reports: https://github.com/nilforooshan/FnR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FnR + url_git: https://github.com/nilforooshan/FnR +fntl: + version: 0.1.2 + title: Numerical Tools for 'Rcpp' and Lambda Functions + maintainer: Andrew M. Raim + description: |- + Provides a 'C++' API for routinely used numerical tools such as integration, + root-finding, and optimization, where function arguments are given as + lambdas. This facilitates 'Rcpp' programming, enabling the development of + 'R'-like code in 'C++' where functions can be defined on the fly and use + variables in the surrounding environment. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fntl + url_git: https://github.com/andrewraim/fntl +FOCI: + version: 0.1.3 + title: Feature Ordering by Conditional Independence + maintainer: Mona Azadkia + description: |- + Feature Ordering by Conditional Independence (FOCI) is a variable selection algorithm based on the measure of conditional dependence. + For more information, see the paper: Azadkia and Chatterjee (2019),"A simple measure of conditional dependence" . + date_publication: '2021-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FOCI + url_git: '' +focusedMDS: + version: 1.3.3 + title: Focused, Interactive Multidimensional Scaling + maintainer: Lea Urpa + description: |- + Takes a distance matrix and plots it as an + interactive graph. One point is focused at the center of the graph, + around which all other points are plotted in their exact distances as + given in the distance matrix. All other non-focus points are plotted + as best as possible in relation to one another. Double click on any + point to choose a new focus point, and hover over points to see their + ID labels. If color label categories are given, hover over colors in + the legend to highlight only those points and click on colors to + highlight multiple groups. For more information on the rationale + and mathematical background, as well as an interactive introduction, + see . + date_publication: '2017-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=focusedMDS + url_git: '' +foghorn: + version: 1.6.0 + title: Summarize CRAN Check Results in the Terminal + maintainer: Francois Michonneau + description: |- + The CRAN check results and where your package stands in the + CRAN submission queue in your R terminal. + date_publication: '2024-07-02' + bug_reports: https://github.com/fmichonneau/foghorn/issues + url: https://fmichonneau.github.io/foghorn/ + url_cran: https://CRAN.R-project.org/package=foghorn + url_git: https://github.com/fmichonneau/foghorn +folda: + version: 0.2.0 + title: Forward Stepwise Discriminant Analysis with Pillai's Trace + maintainer: Siyu Wang + description: |- + A novel forward stepwise discriminant analysis framework + that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA), + providing an improvement over traditional stepwise LDA methods that rely on Wilks' Lambda. + A stand-alone ULDA implementation is also provided, offering a more general solution + than the one available in the 'MASS' package. It automatically handles missing values and + provides visualization tools. For more details, see Wang (2024) . + date_publication: '2024-10-29' + bug_reports: https://github.com/Moran79/folda/issues + url: http://iamwangsiyu.com/folda/ + url_cran: https://CRAN.R-project.org/package=folda + url_git: https://github.com/Moran79/folda +folders: + version: 0.1.0 + title: Standardized Folder Names + maintainer: Brian High + description: Supports the use of standardized folder names. + date_publication: '2024-03-15' + bug_reports: https://github.com/deohs/folders/issues + url: '' + url_cran: https://CRAN.R-project.org/package=folders + url_git: https://github.com/deohs/folders +folio: + version: 1.5.0 + title: Datasets for Teaching Archaeology and Paleontology + maintainer: Nicolas Frerebeau + description: |- + Datasets for teaching quantitative approaches and modeling in + archaeology and paleontology. This package provides several types of + data related to broad topics (cultural evolution, radiocarbon dating, + paleoenvironments, etc.), which can be used to illustrate statistical + methods in the classroom (multivariate data analysis, compositional + data analysis, diversity measurement, etc.). + date_publication: '2024-09-03' + bug_reports: https://github.com/tesselle/folio/issues + url: https://packages.tesselle.org/folio/ + url_cran: https://CRAN.R-project.org/package=folio + url_git: https://github.com/tesselle/folio +fomantic.plus: + version: 0.1.0 + title: Add Extra 'Fomantic UI' Components to 'shiny.semantic' + maintainer: Ashley Baldry + description: |- + Extend 'shiny.semantic' with extra 'Fomantic UI' components. + Create pages in a format similar to 'shiny', form validation and more. + date_publication: '2022-01-24' + bug_reports: https://github.com/ashbaldry/fomantic.plus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fomantic.plus + url_git: https://github.com/ashbaldry/fomantic.plus +fontawesome: + version: 0.5.3 + title: Easily Work with 'Font Awesome' Icons + maintainer: Richard Iannone + description: |- + Easily and flexibly insert 'Font Awesome' icons into 'R Markdown' + documents and 'Shiny' apps. These icons can be inserted into HTML content + through inline 'SVG' tags or 'i' tags. There is also a utility function for + exporting 'Font Awesome' icons as 'PNG' images for those situations where + raster graphics are needed. + date_publication: '2024-11-16' + bug_reports: https://github.com/rstudio/fontawesome/issues + url: https://rstudio.github.io/fontawesome/ + url_cran: https://CRAN.R-project.org/package=fontawesome + url_git: https://github.com/rstudio/fontawesome +fontBitstreamVera: + version: 0.1.1 + title: Fonts with 'Bitstream Vera Fonts' License + maintainer: Lionel Henry + description: |- + Provides fonts licensed under the 'Bitstream Vera Fonts' + license for the 'fontquiver' package. + date_publication: '2017-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fontBitstreamVera + url_git: '' +fontcm: + version: '1.1' + title: Computer Modern font for use with extrafont package + maintainer: Winston Chang + description: Computer Modern font for use with extrafont package + date_publication: '2014-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fontcm + url_git: https://github.com/wch/fontcm +fontLiberation: + version: 0.1.0 + title: Liberation Fonts + maintainer: Lionel Henry + description: |- + A placeholder for the Liberation fontset intended for the + `fontquiver` package. This fontset covers the 12 combinations of + families (sans, serif, mono) and faces (plain, bold, italic, bold + italic) supported in R graphics devices. + date_publication: '2016-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fontLiberation + url_git: '' +fontquiver: + version: 0.2.1 + title: Set of Installed Fonts + maintainer: Lionel Henry + description: |- + Provides a set of fonts with permissive licences. This is + useful when you want to avoid system fonts to make sure your + outputs are reproducible. + date_publication: '2017-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fontquiver + url_git: '' +foodingraph: + version: 0.1.0 + title: Food Network Inference and Visualization + maintainer: Victor Gasque + description: |- + Displays a weighted undirected food graph from an adjacency matrix. + Can perform confidence-interval bootstrap inference with mutual information + or maximal information coefficient. + Based on my Master 1 internship at the Bordeaux Population Health center. + References : Reshef et al. (2011) , + Meyer et al. (2008) , + Liu et al. (2016) . + date_publication: '2019-10-06' + bug_reports: https://github.com/vgasque/foodingraph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=foodingraph + url_git: https://github.com/vgasque/foodingraph/ +foodquotient: + version: 0.1.1 + title: Food Quotient and Nutrient Analysis for HSFFQ + maintainer: Kate Pogue + description: |- + Aids in analysing data from a food frequency questionnaire known as + the Harvard Service Food Frequency Questionnaire (HSFFQ). + Functions from this package use answers from the HSFFQ to generate + estimates of daily consumed micronutrients, calories, macronutrients on + an individual level. + The package also calculates food quotients on individual and group levels. + Foodquotient calculation is an often tedious step in the calculation of + total human energy expenditure (TEE) using the doubly labeled water method, + which is the gold standard for measuring TEE. + date_publication: '2023-08-22' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=foodquotient + url_git: '' +foodwebWrapper: + version: 1.1.0 + title: Enhanced Wrapper to Show Which Functions Call What + maintainer: Barry Zeeberg + description: Enhances the functionality of the mvbutils::foodweb() program. The + matrix-format output of the original program contains identical row names and + column names, each name representing a retrieved function. This format is enhanced + by using the find_funs() program [see Sebastian (2017) ] + to concatenate the package name to the function name. Each package is assigned + a unique color, that is used to color code the text naming the packages and the + functions. This color coding is extended to the entries of value "1" within the + matrix, indicating the pattern of ancestor and descendent functions. + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=foodwebWrapper + url_git: '' +footballpenaltiesBL: + version: 1.0.0 + title: Penalties in the German Men's Football Bundesliga + maintainer: Leo N. Geppert + description: |- + Basic analysis of all penalties taken in the German men's Bundesliga + between the start of its inaugural season and May 2017. The main functions are + suitable printing and plotting functions. Flexible selection of a player is + supported via grep. Missed penalties can easily be included or excluded, depending + on the user's wishes. + date_publication: '2021-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=footballpenaltiesBL + url_git: '' +footBayes: + version: 1.0.0 + title: Fitting Bayesian and MLE Football Models + maintainer: Leonardo Egidi + description: |- + This is the first package allowing for the estimation, + visualization and prediction of the most well-known + football models: double Poisson, bivariate Poisson, + Skellam, student_t, diagonal-inflated bivariate Poisson, and + zero-inflated Skellam. The package allows Hamiltonian + Monte Carlo (HMC) estimation through the underlying Stan + environment and Maximum Likelihood estimation (MLE, for + 'static' models only). The model construction relies on + the most well-known football references, such as + Dixon and Coles (1997) , + Karlis and Ntzoufras (2003) and + Egidi, Pauli and Torelli (2018) . + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=footBayes + url_git: https://github.com/leoegidi/footbayes +footprint: + version: '0.2' + title: Calculate Air Travel Emissions + maintainer: Anthony Schmidt + description: |- + A handy tool to calculate carbon footprints from + air travel based on three-letter International Air Transport Association (IATA) airport codes or latitude and longitude. + footprint first calculates the great-circle distance between departure and arrival + destinations. It then uses the Department of Environment, Food & Rural Affairs (DEFRA) + greenhouse gas conversion factors for business air travel to estimate the carbon footprint. + These conversion factors consider trip length, flight class (e.g. economy, business), and emissions + metric (e.g. carbon dioxide equivalent, methane). + date_publication: '2024-08-27' + bug_reports: https://github.com/acircleda/footprint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=footprint + url_git: https://github.com/acircleda/footprint +foqat: + version: 2.0.8.2 + title: Field Observation Quick Analysis Toolkit + maintainer: Tianshu Chen + description: |- + Tools for quickly processing and analyzing + field observation data and air quality data. This + tools contain functions that facilitate analysis + in atmospheric chemistry (especially in ozone + pollution). Some functions of time series are also + applicable to other fields. For detail please view + homepage. + Scientific Reference: + 1. The Hydroxyl Radical (OH) Reactivity: Roger Atkinson and Janet Arey (2003) . + 2. Ozone Formation Potential (OFP): , Zhang et al.(2021) . + 3. Aerosol Formation Potential (AFP): Wenjing Wu et al. (2016) . + 4. TUV model: . + date_publication: '2023-09-30' + bug_reports: https://github.com/tianshu129/foqat/issues + url: https://tianshu129.github.io/foqat/ + url_cran: https://CRAN.R-project.org/package=foqat + url_git: https://github.com/tianshu129/foqat +ForagingOrg: + version: 0.1.0 + title: Organization Measures for Visual Foraging + maintainer: Marcos Bella-Fernández + description: 'Several functions to compute indicators for organization and efficiency + in visual foraging, multi-target visual search, and cancellation tasks. The current + version of this package includes the following indicators: best-r, mean Inter-target + Distance, Percentage Above Optimal (PAO) scan path, and intersections in the scan + path. For more detailed descriptions, see Mark et al. (2004) .' + date_publication: '2022-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForagingOrg + url_git: '' +forams: + version: 2.0-6 + title: Foraminifera and Community Ecology Analyses + maintainer: Rodrigo Aluizio + description: |- + SHE, FORAM Index and ABC Method analyses and custom plot + functions for community data. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forams + url_git: '' +forcats: + version: 1.0.0 + title: Tools for Working with Categorical Variables (Factors) + maintainer: Hadley Wickham + description: |- + Helpers for reordering factor levels (including moving + specified levels to front, ordering by first appearance, reversing, + and randomly shuffling), and tools for modifying factor levels + (including collapsing rare levels into other, 'anonymising', and + manually 'recoding'). + date_publication: '2023-01-29' + bug_reports: https://github.com/tidyverse/forcats/issues + url: https://forcats.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=forcats + url_git: https://github.com/tidyverse/forcats +forceplate: + version: 1.1-3 + title: Processing Force-Plate Data + maintainer: Raphae Hartmann + description: |- + Process raw force-plate data (txt-files) by segmenting them into trials and, if needed, calculating (user-defined) descriptive + statistics of variables for user-defined time bins (relative to trigger onsets) for each trial. When segmenting the data a baseline + correction, a filter, and a data imputation can be applied if needed. Experimental data can also be processed and combined with the + segmented force-plate data. This procedure is suggested by Johannsen et al. (2023) and some of the + options (e.g., choice of low-pass filter) are also suggested by Winter (2009) . + date_publication: '2024-03-12' + bug_reports: https://github.com/RaphaelHartmann/forceplate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forceplate + url_git: https://github.com/RaphaelHartmann/forceplate +forceR: + version: 1.0.20 + title: Force Measurement Analyses + maintainer: Peter T. Rühr + description: |- + For cleaning and analysis of graphs, such as animal closing force + measurements. + 'forceR' was initially written and optimized to deal with insect bite force + measurements, but can be used for any time series. Includes a full workflow + to load, plot and crop data, correct amplifier and baseline drifts, + identify individual peak shapes (bites), rescale (normalize) peak curves, + and find best polynomial fits to describe and analyze force curve shapes. + date_publication: '2023-03-01' + bug_reports: https://github.com/Peter-T-Ruehr/forceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forceR + url_git: https://github.com/Peter-T-Ruehr/forceR +foreach: + version: 1.5.2 + title: Provides Foreach Looping Construct + maintainer: Folashade Daniel + description: |- + Support for the foreach looping construct. Foreach is an + idiom that allows for iterating over elements in a collection, + without the use of an explicit loop counter. This package in + particular is intended to be used for its return value, rather + than for its side effects. In that sense, it is similar to the + standard lapply function, but doesn't require the evaluation + of a function. Using foreach without side effects also + facilitates executing the loop in parallel. + date_publication: '2022-02-02' + bug_reports: https://github.com/RevolutionAnalytics/foreach/issues + url: '' + url_cran: https://CRAN.R-project.org/package=foreach + url_git: https://github.com/RevolutionAnalytics/foreach +ForeCA: + version: 0.2.7 + title: Forecastable Component Analysis + maintainer: Georg M. Goerg + description: |- + Implementation of Forecastable Component Analysis ('ForeCA'), + including main algorithms and auxiliary function (summary, plotting, etc.) to + apply 'ForeCA' to multivariate time series data. 'ForeCA' is a novel dimension + reduction (DR) technique for temporally dependent signals. Contrary to other + popular DR methods, such as 'PCA' or 'ICA', 'ForeCA' takes time dependency + explicitly into account and searches for the most ''forecastable'' signal. + The measure of forecastability is based on the Shannon entropy of the spectral + density of the transformed signal. + date_publication: '2020-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForeCA + url_git: https://github.com/gmgeorg/ForeCA +forecast: + version: 8.23.0 + title: Forecasting Functions for Time Series and Linear Models + maintainer: Rob Hyndman + description: |- + Methods and tools for displaying and analysing + univariate time series forecasts including exponential smoothing + via state space models and automatic ARIMA modelling. + date_publication: '2024-06-20' + bug_reports: https://github.com/robjhyndman/forecast/issues + url: https://pkg.robjhyndman.com/forecast/ + url_cran: https://CRAN.R-project.org/package=forecast + url_git: https://github.com/robjhyndman/forecast +ForecastComb: + version: 1.3.1 + title: Forecast Combination Methods + maintainer: Christoph E. Weiss + description: |- + Provides geometric- and regression-based forecast + combination methods under a unified user interface for the packages 'ForecastCombinations' + and 'GeomComb'. Additionally, updated tools and convenience functions for data pre-processing are available in order to deal with + common problems in forecast combination (missingness, collinearity). For method details see Hsiao C, Wan SK (2014). , Hansen BE (2007). , + Elliott G, Gargano A, Timmermann A (2013). , + and Clemen RT (1989). . + date_publication: '2018-08-07' + bug_reports: https://github.com/ceweiss/ForecastComb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ForecastComb + url_git: https://github.com/ceweiss/ForecastComb +ForecastCombinations: + version: '1.1' + title: Forecast Combinations + maintainer: Eran Raviv + description: 'Aim: Supports the most frequently used methods to combine forecasts. + Among others: Simple average, Ordinary Least Squares, Least Absolute Deviation, + Constrained Least Squares, Variance-based, Best Individual model, Complete subset + regressions and Information-theoretic (information criteria based).' + date_publication: '2015-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForecastCombinations + url_git: '' +forecasteR: + version: 3.0.2 + title: Time Series Forecast System + maintainer: Oldemar Rodriguez + description: A web application for displaying, analysing and forecasting univariate + time series. Includes basic methods such as mean, naïve, seasonal naïve and drift, + as well as more complex methods such as Holt-Winters Box,G and Jenkins, G (1976) + and ARIMA Brockwell, P.J. and R.A.Davis (1991) . + date_publication: '2024-11-26' + bug_reports: https://github.com/PROMiDAT/forecasteR/issues + url: https://promidat.website + url_cran: https://CRAN.R-project.org/package=forecasteR + url_git: https://github.com/PROMiDAT/forecasteR +forecastHybrid: + version: 5.0.19 + title: Convenient Functions for Ensemble Time Series Forecasts + maintainer: David Shaub + description: |- + Convenient functions for ensemble forecasts in R combining + approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), + thetaf(), nnetar(), stlm(), tbats(), and snaive() can be combined with equal weights, weights + based on in-sample errors (introduced by Bates & Granger (1969) ), + or cross-validated weights. Cross validation for time series data with user-supplied models + and forecasting functions is also supported to evaluate model accuracy. + date_publication: '2020-08-28' + bug_reports: https://github.com/ellisp/forecastHybrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forecastHybrid + url_git: https://gitlab.com/dashaub/forecastHybrid +forecastLSW: + version: '1.0' + title: Forecasting Routines for Locally Stationary Wavelet Processes + maintainer: Rebecca Killick + description: Implementation to perform forecasting of locally stationary wavelet + processes by examining the local second order structure of the time series. + date_publication: '2023-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forecastLSW + url_git: '' +forecastML: + version: 0.9.0 + title: Time Series Forecasting with Machine Learning Methods + maintainer: Nickalus Redell + description: The purpose of 'forecastML' is to simplify the process of multi-step-ahead + forecasting with standard machine learning algorithms. 'forecastML' supports lagged, + dynamic, static, and grouping features for modeling single and grouped numeric + or factor/sequence time series. In addition, simple wrapper functions are used + to support model-building with most R packages. This approach to forecasting is + inspired by Bergmeir, Hyndman, and Koo's (2018) paper "A note on the validity + of cross-validation for evaluating autoregressive time series prediction" . + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forecastML + url_git: https://github.com/nredell/forecastML/ +forecastSNSTS: + version: 1.3-0 + title: Forecasting for Stationary and Non-Stationary Time Series + maintainer: Tobias Kley + description: |- + Methods to compute linear h-step ahead prediction coefficients based + on localised and iterated Yule-Walker estimates and empirical mean squared + and absolute prediction errors for the resulting predictors. Also, functions + to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time + series, and to verify an assumption from Kley et al. (2019), Electronic of Statistics, + forthcoming. Preprint . + date_publication: '2019-09-02' + bug_reports: http://github.com/tobiaskley/forecastSNSTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forecastSNSTS + url_git: http://github.com/tobiaskley/forecastSNSTS +ForecastTB: + version: 1.0.1 + title: Test Bench for the Comparison of Forecast Methods + maintainer: Neeraj Dhanraj Bokde + description: |- + Provides a test bench for the comparison of forecasting + methods in uni-variate time series. Forecasting methods are compared using + different error metrics. Proposed forecasting methods and alternative error + metrics can be used. Detailed discussion is provided in the vignette. + date_publication: '2020-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForecastTB + url_git: '' +FoReco: + version: 1.0.0 + title: Forecast Reconciliation + maintainer: Daniele Girolimetto + description: |- + Classical (bottom-up and top-down), optimal combination and heuristic + point (Di Fonzo and Girolimetto, 2023 ) and + probabilistic (Girolimetto et al. 2023 ) + forecast reconciliation procedures for linearly constrained time series + (e.g., hierarchical or grouped time series) in cross-sectional, temporal, + or cross-temporal frameworks. + date_publication: '2024-08-20' + bug_reports: https://github.com/daniGiro/FoReco/issues + url: https://danigiro.github.io/FoReco/ + url_cran: https://CRAN.R-project.org/package=FoReco + url_git: https://github.com/daniGiro/FoReco +ForeComp: + version: 0.9.0 + title: |- + Size-Power Tradeoff Visualization for Equal Predictive Ability + of Two Forecasts + maintainer: Minchul Shin + description: Offers a set of tools for visualizing and analyzing size and power + properties of the test for equal predictive accuracy, the Diebold-Mariano test + that is based on heteroskedasticity and autocorrelation-robust (HAR) inference. + A typical HAR inference is involved with non-parametric estimation of the long-run + variance, and one of its tuning parameters, the truncation parameter, trades off + a size and power. Lazarus, Lewis, and Stock (2021) theoretically + characterize the size-power frontier for the Gaussian multivariate location model. + 'ForeComp' computes and visualizes the finite-sample size-power frontier of the + Diebold-Mariano test based on fixed-b asymptotics together with the Bartlett kernel. + To compute the finite-sample size and power, it works with the best approximating + ARMA process to the given dataset. It informs the user how their choice of the + truncation parameter performs and how robust the testing outcomes are. + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForeComp + url_git: https://github.com/mcmcs/ForeComp +forecTheta: + version: 2.6.2 + title: Forecasting Time Series by Theta Models + maintainer: Jose Augusto Fiorucci + description: Routines for forecasting univariate time series using Theta Models. + date_publication: '2022-11-11' + bug_reports: https://github.com/jafiorucci/forecTheta/issues + url: https://www.sciencedirect.com/science/article/pii/S0169207016300243 + url_cran: https://CRAN.R-project.org/package=forecTheta + url_git: '' +foreign: + version: 0.8-88 + title: |- + Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', + 'Systat', 'Weka', 'dBase', ... + maintainer: R Core Team + description: |- + Reading and writing data stored by some versions of + 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', + and for reading and writing some 'dBase' files. + date_publication: '2025-01-12' + bug_reports: https://bugs.r-project.org + url: '' + url_cran: https://CRAN.R-project.org/package=foreign + url_git: '' +forensicolors: + version: 1.0.0 + title: Forensic Colors + maintainer: Franco Marsico + description: Computes likelihood ratios based on pigmentation traits. Also, it allows + computing conditional probabilities for unidentified individuals based on missing + person characteristics. A set of tailored plots are incorporated to analyze likelihood + ratio distributions. + date_publication: '2024-05-01' + bug_reports: https://github.com/MarsicoFL/forensicolors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forensicolors + url_git: https://github.com/MarsicoFL/forensicolors +forensIT: + version: 1.1.1 + title: Information Theory Tools for Forensic Analysis + maintainer: Franco Marsico + description: The 'forensIT' package is a comprehensive statistical toolkit tailored + for handling missing person cases. By leveraging information theory metrics, it + enables accurate assessment of kinship, particularly when limited genetic evidence + is available. With a focus on optimizing statistical power, 'forensIT' empowers + investigators to effectively prioritize family members, enhancing the reliability + and efficiency of missing person investigations. + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forensIT + url_git: '' +foreSIGHT: + version: 1.2.0 + title: Systems Insights from Generation of Hydroclimatic Timeseries + maintainer: David McInerney + description: A tool to create hydroclimate scenarios, stress test systems and visualize + system performance in scenario-neutral climate change impact assessments. Scenario-neutral + approaches 'stress-test' the performance of a modelled system by applying a wide + range of plausible hydroclimate conditions (see Brown & Wilby (2012) + and Prudhomme et al. (2010) ). These approaches + allow the identification of hydroclimatic variables that affect the vulnerability + of a system to hydroclimate variation and change. This tool enables the generation + of perturbed time series using a range of approaches including simple scaling + of observed time series (e.g. Culley et al. (2016) ) + and stochastic simulation of perturbed time series via an inverse approach (see + Guo et al. (2018) ). It incorporates 'Richardson-type' + weather generator model configurations documented in Richardson (1981) , + Richardson and Wright (1984), as well as latent variable type model configurations + documented in Bennett et al. (2018) , Rasmussen + (2013) , Bennett et al. (2019) + to generate hydroclimate variables on a daily basis (e.g. precipitation, temperature, + potential evapotranspiration) and allows a variety of different hydroclimate variable + properties, herein called attributes, to be perturbed. Options are included for + the easy integration of existing system models both internally in R and externally + for seamless 'stress-testing'. A suite of visualization options for the results + of a scenario-neutral analysis (e.g. plotting performance spaces and overlaying + climate projection information) are also included. Version 1.0 of this package + is described in Bennett et al. (2021) . As + further developments in scenario-neutral approaches occur the tool will be updated + to incorporate these advances. + date_publication: '2023-10-19' + bug_reports: https://github.com/ClimateAnalytics/foreSIGHT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=foreSIGHT + url_git: '' +forestat: + version: 1.1.0 + title: |- + Forest Carbon Sequestration and Potential Productivity + Calculation + maintainer: Yuanyuan Han + description: 'Include assessing site classes based on the stand height growth and + establishing a nonlinear mixed-effect biomass model under different site classes + based on the whole stand model to achieve more accurate estimation of carbon sequestration. + In particular, a carbon sequestration potential productivity calculation method + based on the potential mean annual increment is proposed. This package is applicable + to both natural forests and plantations. It can quantitatively assess stand’s + potential productivity, realized productivity, and possible improvement under + certain site, and can be used in many aspects such as site quality assessment, + tree species suitability evaluation, and forest degradation evaluation. Reference: + Lei X, Fu L, Li H, et al (2018) . Fu L, Sharma + R P, Zhu G, et al (2017) .' + date_publication: '2023-10-10' + bug_reports: https://github.com/caf-ifrit/forestat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forestat + url_git: https://github.com/caf-ifrit/forestat +forestControl: + version: 0.2.2 + title: |- + Approximate False Positive Rate Control in Selection Frequency + for Random Forest + maintainer: Tom Wilson + description: |- + Approximate false positive rate control in selection frequency for + random forest using the methods described by Ender Konukoglu and Melanie Ganz (2014) . + Methods for calculating the selection frequency threshold at false positive rates + and selection frequency false positive rate feature selection. + date_publication: '2022-02-09' + bug_reports: https://github.com/aberHRML/forestControl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forestControl + url_git: https://github.com/aberHRML/forestControl +ForestDisc: + version: 0.1.0 + title: Forest Discretization + maintainer: Haddouchi Maïssae + description: 'Supervised, multivariate, and non-parametric discretization algorithm + based on tree ensembles learning and moment matching optimization. This version + of the algorithm relies on random forest algorithm to learn a large set of split + points that conserves the relationship between attributes and the target class, + and on moment matching optimization to transform this set into a reduced number + of cut points matching as well as possible statistical properties of the initial + set of split points. For each attribute to be discretized, the set S of its related + split points extracted through random forest is mapped to a reduced set C of cut + points of size k. This mapping relies on minimizing, for each continuous attribute + to be discretized, the distance between the four first moments of S and the four + first moments of C subject to some constraints. This non-linear optimization problem + is performed using k values ranging from 2 to ''max_splits'', and the best solution + returned correspond to the value k which optimum solution is the lowest one over + the different realizations. ForestDisc is a generalization of RFDisc discretization + method initially proposed by Berrado and Runger (2009) , + and improved by Berrado et al. in 2012 by adopting the idea of moment matching + optimization related by Hoyland and Wallace (2001) .' + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForestDisc + url_git: '' +forestecology: + version: 0.2.0 + title: |- + Fitting and Assessing Neighborhood Models of the Effect of + Interspecific Competition on the Growth of Trees + maintainer: Albert Y. Kim + description: |- + Code for fitting and assessing models for the growth of trees. In + particular for the Bayesian neighborhood competition linear regression model + of Allen (2020): methods for model fitting and generating fitted/predicted + values, evaluating the effect of competitor species identity using + permutation tests, and evaluating model performance using spatial + cross-validation. + date_publication: '2021-10-02' + bug_reports: https://github.com/rudeboybert/forestecology/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forestecology + url_git: https://github.com/rudeboybert/forestecology +forested: + version: 0.1.0 + title: Forest Attributes in Washington State + maintainer: Simon Couch + description: |- + A small subset of plots in Washington State are sampled and + assessed "on-the-ground" as forested or non-forested by the U.S. + Department of Agriculture, Forest Service, Forest Inventory and Analysis + (FIA) Program, but the FIA also has access to remotely sensed data for + all land in the state. The 'forested' package contains a data frame by the + same name intended for use in predictive modeling applications + where the more easily-accessible remotely sensed data can be used to + predict whether a plot is forested or non-forested. + date_publication: '2024-07-31' + bug_reports: https://github.com/simonpcouch/forested/issues + url: https://simonpcouch.github.io/forested/ + url_cran: https://CRAN.R-project.org/package=forested + url_git: https://github.com/simonpcouch/forested +ForestElementsR: + version: 2.1.0 + title: Data Structures and Functions for Working with Forest Data + maintainer: Peter Biber + description: |- + Provides generic data structures and algorithms for use with forest + mensuration data in a consistent framework. The functions and objects + included are a collection of broadly applicable tools. More specialized + applications should be implemented in separate packages that build on this + foundation. Documentation about 'ForestElementsR' is provided by three + vignettes included in this package. For an introduction to the field of + forest mensuration, refer to the textbooks by Kershaw et al. (2017) + , and van Laar and Akca (2007) + . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForestElementsR + url_git: '' +forestError: + version: 1.1.0 + title: |- + A Unified Framework for Random Forest Prediction Error + Estimation + maintainer: Benjamin Lu + description: |- + Estimates the conditional error distributions of random forest + predictions and common parameters of those distributions, including + conditional misclassification rates, conditional mean squared prediction + errors, conditional biases, and conditional quantiles, by out-of-bag + weighting of out-of-bag prediction errors as proposed by Lu and Hardin + (2021). This package is compatible with several existing packages that + implement random forests in R. + date_publication: '2021-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestError + url_git: '' +ForestFit: + version: 2.4.3 + title: Statistical Modelling for Plant Size Distributions + maintainer: Mahdi Teimouri + description: |- + Developed for the following tasks. 1 ) Computing the probability density function, + cumulative distribution function, random generation, and estimating the parameters + of the eleven mixture models. 2 ) Point estimation of the parameters of two - + parameter Weibull distribution using twelve methods and three - parameter Weibull + distribution using nine methods. 3 ) The Bayesian inference for the three - + parameter Weibull distribution. 4 ) Estimating parameters of the three - parameter + Birnbaum - Saunders, generalized exponential, and Weibull distributions fitted to + grouped data using three methods including approximated maximum likelihood, + expectation maximization, and maximum likelihood. 5 ) Estimating the parameters + of the gamma, log-normal, and Weibull mixture models fitted to the grouped data + through the EM algorithm, 6 ) Estimating parameters of the nonlinear height curve + fitted to the height - diameter observation, 7 ) Estimating parameters, computing + probability density function, cumulative distribution function, and generating + realizations from gamma shape mixture model introduced by Venturini et al. (2008) + , 8 ) The Bayesian inference, computing probability + density function, cumulative distribution function, and generating realizations + from univariate and bivariate Johnson SB distribution, 9 ) Robust multiple linear + regression analysis when error term follows skewed t distribution, 10 ) Estimating + parameters of a given distribution fitted to grouped data using method of maximum + likelihood, and 11 ) Estimating parameters of the Johnson SB distribution through + the Bayesian, method of moment, conditional maximum likelihood, and two - percentile + method. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForestFit + url_git: '' +ForestGapR: + version: 0.1.7 + title: Tropical Forest Canopy Gaps Analysis + maintainer: Carlos Alberto Silva + description: Set of tools for detecting and analyzing Airborne Laser Scanning-derived + Tropical Forest Canopy Gaps. Details were published in Silva and others (2019) + . + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForestGapR + url_git: '' +forestGYM: + version: 1.0.0 + title: Forest Growth and Yield Model Based on Clutter Model + maintainer: Zongzheng Chai + description: 'The Clutter model is a significant forest growth simulation tool. + Grounded on individual trees and comprehensively considering factors such as competition + among trees and the impact of environmental elements on growth, it can accurately + reflect the growth process of forest stands. It can be applied in areas like forest + resource management, harvesting planning, and ecological research. With the help + of the Clutter model, people can better understand the dynamic changes of forests + and provide a scientific basis for rational forest management and protecting the + ecological environment. This R package can effectively realize the construction + of forest growth and harvest models based on the Clutter model and achieve optimized + forest management.References: Farias A, Soares C, Leite H et al(2021). + Guera O, Silva J, Ferreira R, et al(2019).' + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestGYM + url_git: '' +forestHES: + version: 2.0.1 + title: Forest Health Evaluation System at the Forest Stand Level + maintainer: Zongzheng Chai + description: Assessing forest ecosystem health is an effective way for forest resource + management.The national forest health evaluation system at the forest stand level + using analytic hierarchy process, has a high application value and practical significance. + The package can effectively and easily realize the total assessment process, and + help foresters to further assess and management forest resources. + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestHES + url_git: '' +forestinventory: + version: 1.0.0 + title: |- + Design-Based Global and Small-Area Estimations for Multiphase + Forest Inventories + maintainer: Andreas Hill + description: |- + Extensive global and small-area estimation procedures for multiphase + forest inventories under the design-based Monte-Carlo approach are provided. + The implementation has been published in the Journal of Statistical Software () + and includes estimators for simple and cluster sampling + published by Daniel Mandallaz in 2007 (), + 2013 (, , + , ) + and 2016 (). It provides point estimates, + their external- and design-based variances and confidence intervals, as well as a + set of functions to analyze and visualize the produced estimates. + The procedures have also been optimized for the use of remote sensing data + as auxiliary information, as demonstrated in 2018 by Hill et al. (). + date_publication: '2021-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestinventory + url_git: '' +forestly: + version: 0.1.2 + title: Interactive Forest Plot + maintainer: Benjamin Wang + description: |- + Interactive forest plot for clinical trial safety analysis + using 'metalite', 'reactable', 'plotly', and Analysis Data Model (ADaM) + datasets. Includes functionality for adverse event filtering, + incidence-based group filtering, hover-over reveals, and search and sort + operations. The workflow allows for metadata construction, data preparation, + output formatting, and interactive plot generation. + date_publication: '2025-01-10' + bug_reports: https://github.com/Merck/forestly/issues + url: https://merck.github.io/forestly/ + url_cran: https://CRAN.R-project.org/package=forestly + url_git: https://github.com/Merck/forestly +forestmangr: + version: 0.9.8 + title: Forest Mensuration and Management + maintainer: Sollano Rabelo Braga + description: 'Processing forest inventory data with methods such as simple random + sampling, stratified random sampling and systematic sampling. There are also functions + for yield and growth predictions and model fitting, linear and nonlinear grouped + data fitting, and statistical tests. References: Kershaw Jr., Ducey, Beers and + Husch (2016). .' + date_publication: '2024-12-01' + bug_reports: https://github.com/sollano/forestmangr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forestmangr + url_git: https://github.com/sollano/forestmangr#readme +forestmodel: + version: 0.6.2 + title: Forest Plots from Regression Models + maintainer: Nick Kennedy + description: |- + Produces forest plots using 'ggplot2' from models produced by functions + such as stats::lm(), stats::glm() and survival::coxph(). + date_publication: '2020-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestmodel + url_git: '' +forestplot: + version: 3.1.6 + title: Advanced Forest Plot Using 'grid' Graphics + maintainer: Max Gordon + description: |- + Allows the creation of forest plots with advanced features, such as + multiple confidence intervals per row, customizable fonts for individual text + elements, and flexible confidence interval drawing. It also supports mixing + text with mathematical expressions. The package extends the application of + forest plots beyond traditional meta-analyses, offering a more general version + of the original 'rmeta' package’s forestplot() function. It relies heavily on + the 'grid' package for rendering the plots. + date_publication: '2024-11-19' + bug_reports: https://github.com/gforge/forestplot/issues + url: https://gforge.se/packages/ + url_cran: https://CRAN.R-project.org/package=forestplot + url_git: '' +forestploter: + version: 1.1.2 + title: Create a Flexible Forest Plot + maintainer: Alimu Dayimu + description: Create a forest plot based on the layout of the data. Confidence intervals + in multiple columns by groups can be done easily. Editing the plot, inserting/adding + text, applying a theme to the plot, and much more. + date_publication: '2024-04-13' + bug_reports: https://github.com/adayim/forestploter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forestploter + url_git: https://github.com/adayim/forestploter +forestPSD: + version: 1.0.0 + title: Forest Population Structure and Numeric Dynamics + maintainer: Zongzheng Chai + description: 'Analysis of forest population structure and quantitative dynamics + is the research and evaluation of the composition, distribution, age structure + and changes in quantity over time of various populations in the forest. By deeply + understanding these characteristics of forest populations, scientific basis can + be provided for the management, protection and sustainable utilization of forest + resources. This R package conducts a systematic analysis of forest population + structure and quantitative dynamics through analyzing age structure, compiling + life tables, population quantitative dynamic change indices and time series models, + in order to provide support for forest population protection and sustainable management. + References: Zhang Y, Wang J, Wang X, et al(2024). + Yuan G, Guo Q, Xie N, et al(2023).' + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestPSD + url_git: '' +forestr: + version: 2.0.2 + title: Ecosystem and Canopy Structural Complexity Metrics from LiDAR + maintainer: Jeff Atkins + description: |- + Provides a toolkit for calculating forest and canopy structural complexity metrics from + terrestrial LiDAR (light detection and ranging). References: Atkins et al. 2018 ; Hardiman et al. 2013 ; + Parker et al. 2004 . + date_publication: '2020-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestr + url_git: https://github.com/atkinsjeff/forestr +forestRK: + version: 0.0-5 + title: Implements the Forest-R.K. Algorithm for Classification Problems + maintainer: Hyunjin Cho + description: |- + Provides functions that calculates common types of splitting + criteria used in random forests for classification problems, as well as + functions that make predictions based on a single tree or a Forest-R.K. model; + the package also provides functions to generate importance plot for a + Forest-R.K. model, as well as the 2D multidimensional-scaling plot of + data points that are colour coded by their predicted class types by the + Forest-R.K. model. This package is based on: + Bernard, S., Heutte, L., Adam, S., (2008, ISBN:978-3-540-85983-3) + "Forest-R.K.: A New Random Forest Induction Method", + Fourth International Conference on Intelligent Computing, + September 2008, Shanghai, China, pp.430-437. + date_publication: '2019-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestRK + url_git: '' +forestry: + version: 0.1.1 + title: Reshape Data Tree + maintainer: Jiena McLellan + description: |- + A series of utility functions to help with + reshaping hierarchy of data tree, and reform the structure of data tree. + date_publication: '2023-11-20' + bug_reports: https://github.com/jienagu/forestry/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forestry + url_git: '' +forestSAS: + version: 2.0.4 + title: Forest Spatial Structure Analysis Systems + maintainer: Zongzheng Chai + description: 'Recent years have seen significant interest in neighborhood-based + structural parameters that effectively represent the spatial characteristics of + tree populations and forest communities, and possess strong applicability for + guiding forestry practices. This package provides valuable information that enhances + our understanding and analysis of the fine-scale spatial structure of tree populations + and forest stands. Reference: Yan L, Tan W, Chai Z, et al (2019) .' + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forestSAS + url_git: '' +ForestTools: + version: 1.0.3 + title: Tools for Analyzing Remote Sensing Forest Data + maintainer: Andrew Plowright + description: Tools for analyzing remote sensing forest data, including functions + for detecting treetops from canopy models, outlining tree crowns, and calculating + textural metrics. + date_publication: '2025-02-04' + bug_reports: https://github.com/andrew-plowright/ForestTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ForestTools + url_git: https://github.com/andrew-plowright/ForestTools +foretell: + version: 0.2.0 + title: |- + Projecting Customer Retention Based on Fader and Hardie + Probability Models + maintainer: Srihari Jaganathan + description: |- + Project Customer Retention based on Beta Geometric, Beta Discrete Weibull and Latent Class + Discrete Weibull Models.This package is based on Fader and Hardie (2007) + and Fader and Hardie et al. (2018) . + date_publication: '2019-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=foretell + url_git: '' +forge: + version: 0.2.0 + title: Casting Values into Shape + maintainer: Kevin Kuo + description: |- + Helper functions with a consistent interface to coerce and verify + the types and shapes of values for input checking. + date_publication: '2019-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forge + url_git: '' +forgts: + version: 0.0.1 + title: |- + Convert Formatted Spreadsheets to Presentation-Ready Display + Tables + maintainer: Luis D. Verde Arregoitia + description: Reads cell contents plus formatting from a spreadsheet file and creates + an editable 'gt' object with the same data and formatting. Supports the most commonly-used + cell and text styles including colors, fills, font weights and decorations, and + borders. + date_publication: '2025-01-31' + bug_reports: https://github.com/luisDVA/forgts/issues + url: https://luisdva.github.io/forgts/ + url_cran: https://CRAN.R-project.org/package=forgts + url_git: https://github.com/luisDVA/forgts +forImage: + version: 0.1.0 + title: Foraminiferal Image Analysis and Test Measurement + maintainer: Thaise R Freitas + description: |2- + + The goal of this collection of functions is to provide an easy to use tool for the measurement of foraminifera and other unicellulars organisms size. With functions developed to guide foraminiferal test biovolume calculations and cell biomass estimations. The volume function includes several microalgae models geometric adaptations based on Hillebrand et al. (1999) , Sun and Liu (2003) and Vadrucci, Cabrini and Basset (2007) . + date_publication: '2021-03-02' + bug_reports: https://github.com/ThaiseRF/forImage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forImage + url_git: https://github.com/ThaiseRF/forImage +ForIT: + version: 2.4.0 + title: |- + Functions to Estimate Tree Volume and Phytomass in the Italian + Forest Inventory 2005 + maintainer: Nicola Puletti + description: |- + Tabacchi et al. (2011) published a very detailed study producing a uniform system of functions to estimate tree volume and + phytomass components (stem, branches, stool). The estimates of the 2005 Italian forest inventory () + are based on these functions. The study documents the domain of applicability of each function and the equations to quantify estimates + accuracies for individual estimates as well as for aggregated estimates. This package makes the functions available in the R environment. + Version 2 exposes two distinct functions for individual and summary estimates. To facilitate access to the functions, tree species + identification is now based on EPPO species codes (). + date_publication: '2023-09-26' + bug_reports: '' + url: DOI:10.5281/zenodo.5790157 + url_cran: https://CRAN.R-project.org/package=ForIT + url_git: https://gitlab.com/NuoroForestrySchool/ForIT.git +ForLion: + version: 0.1.0 + title: '''ForLion'' Algorithm to Find D-Optimal Designs for Experiments' + maintainer: Siting Lin + description: 'Designing experimental plans that involve both discrete and continuous + factors with general parametric statistical models using the ''ForLion'' algorithm + and ''EW ForLion'' algorithm. The algorithms will search for locally optimal designs + and EW optimal designs under the D-criterion. Reference: Huang, Y., Li, K., Mandal, + A., & Yang, J., (2024).' + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ForLion + url_git: '' +formatBibtex: + version: 0.1.0 + title: Format BibTeX Entries and Files + maintainer: Wenjie Wang + description: Format BibTeX entries and files in an opinionated way. + date_publication: '2023-02-03' + bug_reports: https://github.com/wenjie2wang/formatBibtex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=formatBibtex + url_git: https://github.com/wenjie2wang/formatBibtex +formatdown: + version: 0.1.4 + title: Formatting Numbers in 'rmarkdown' Documents + maintainer: Richard Layton + description: |- + Provides a small set of tools for formatting numbers in R-markdown + documents. Convert a numerical vector to character strings in power-of-ten + form, decimal form, or measurement-units form; all are math-delimited for + rendering as inline equations. Can also convert text into math-delimited + text to match the font face and size of math-delimited numbers. Useful for + rendering single numbers in inline R code chunks and for rendering columns + in tables. + date_publication: '2024-05-07' + bug_reports: https://github.com/graphdr/formatdown/issues + url: https://graphdr.github.io/formatdown/ + url_cran: https://CRAN.R-project.org/package=formatdown + url_git: https://github.com/graphdr/formatdown/ +formatR: + version: '1.14' + title: Format R Code Automatically + maintainer: Yihui Xie + description: |- + Provides a function tidy_source() to format R source code. Spaces + and indent will be added to the code automatically, and comments will be + preserved under certain conditions, so that R code will be more + human-readable and tidy. There is also a Shiny app as a user interface in + this package (see tidy_app()). + date_publication: '2023-01-17' + bug_reports: https://github.com/yihui/formatR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=formatR + url_git: https://github.com/yihui/formatR +formattable: + version: 0.2.1 + title: Create 'Formattable' Data Structures + maintainer: Kun Ren + description: |- + Provides functions to create formattable vectors and data frames. + 'Formattable' vectors are printed with text formatting, and formattable + data frames are printed with multiple types of formatting in HTML + to improve the readability of data presented in tabular form rendered in + web pages. + date_publication: '2021-01-07' + bug_reports: https://github.com/renkun-ken/formattable/issues + url: https://renkun-ken.github.io/formattable/ + url_cran: https://CRAN.R-project.org/package=formattable + url_git: https://github.com/renkun-ken/formattable +formatters: + version: 0.5.10 + title: ASCII Formatting for Values and Tables + maintainer: Joe Zhu + description: |- + We provide a framework for rendering complex tables to ASCII, + and a set of formatters for transforming values or sets of values into + ASCII-ready display strings. + date_publication: '2025-01-09' + bug_reports: https://github.com/insightsengineering/formatters/issues + url: https://insightsengineering.github.io/formatters/ + url_cran: https://CRAN.R-project.org/package=formatters + url_git: https://github.com/insightsengineering/formatters/ +formods: + version: 0.2.0 + title: '''Shiny'' Modules for General Tasks' + maintainer: John Harrold + description: '''Shiny'' apps can often make use of the same key elements, this package + provides modules for common tasks (data upload, wrangling data, figure generation + and saving the app state), and also a framework for developing. These modules + can react and interact as well as generate code to create reproducible analyses.' + date_publication: '2025-01-07' + bug_reports: https://github.com/john-harrold/formods/issues + url: https://formods.ubiquity.tools/ + url_cran: https://CRAN.R-project.org/package=formods + url_git: '' +FormShare: + version: 1.0.1 + title: |- + A Simple Connection Between the 'FormShare App' and 'R' for + Advanced Analytics + maintainer: Carlos Quiros + description: |- + Provides analytics directly from 'R'. It requires: + 'FormShare App': = 2.22.0> . + Analytics plugin: . + Remote SQL plugin: . + date_publication: '2023-01-28' + bug_reports: https://github.com/qlands/formshare-R-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FormShare + url_git: https://github.com/qlands/formshare-R-package +Formula: + version: 1.2-5 + title: Extended Model Formulas + maintainer: Achim Zeileis + description: |- + Infrastructure for extended formulas with multiple parts on the + right-hand side and/or multiple responses on the left-hand side + (see ). + date_publication: '2023-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Formula + url_git: '' +formula.tools: + version: 1.7.1 + title: |- + Programmatic Utilities for Manipulating Formulas, Expressions, + Calls, Assignments and Other R Objects + maintainer: Christopher Brown + description: |- + These utilities facilitate the programmatic manipulations of + formulas, expressions, calls, assignments and other R language objects. + These objects all share the same structure: a left-hand side, operator and + right-hand side. This packages provides methods for accessing and + modifying this structures as well as extracting and replacing names and + symbols from these objects. + date_publication: '2018-03-01' + bug_reports: https://github.com/decisionpatterns/formula.tools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=formula.tools + url_git: https://github.com/decisionpatterns/formula.tools +formulaic: + version: 0.0.8 + title: Dynamic Generation and Quality Checks of Formula Objects + maintainer: Anderson Nelson + description: Many statistical models and analyses in R are implemented through formula + objects. The formulaic package creates a unified approach for programmatically + and dynamically generating formula objects. Users may specify the outcome and + inputs of a model directly, search for variables to include based upon naming + patterns, incorporate interactions, and identify variables to exclude. A wide + range of quality checks are implemented to identify issues such as misspecified + variables, duplication, a lack of contrast in the inputs, and a large number of + levels in categorical data. Variables that do not meet these quality checks can + be automatically excluded from the model. These issues are documented and reported + in a manner that provides greater accountability and useful information to guide + an investigation of the data. + date_publication: '2021-02-15' + bug_reports: https://github.com/dachosen1/formulaic/issues + url: https://dachosen1.github.io/formulaic/index.html + url_cran: https://CRAN.R-project.org/package=formulaic + url_git: '' +formulops: + version: 0.5.1 + title: Mathematical Operations on R Formula + maintainer: Bill Denney + description: Perform mathematical operations on R formula (add, subtract, multiply, + etc.) and substitute parts of formula. + date_publication: '2025-01-22' + bug_reports: https://github.com/humanpred/formulops/issues + url: '' + url_cran: https://CRAN.R-project.org/package=formulops + url_git: https://github.com/humanpred/formulops +FormulR: + version: 1.0.0 + title: |- + Comprehensive Tools for Drug Formulation Analysis and + Visualization + maintainer: Oche Ambrose George + description: This presents a comprehensive set of tools for the analysis and visualization + of drug formulation data. It includes functions for statistical analysis, regression + modeling, hypothesis testing, and comparative analysis to assess the impact of + formulation parameters on drug release and other critical attributes. Additionally, + the package offers a variety of data visualization functions, such as scatterplots, + histograms, and boxplots, to facilitate the interpretation of formulation data. + With its focus on usability and efficiency, this package aims to streamline the + drug formulation process and aid researchers in making informed decisions during + formulation design and optimization. + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FormulR + url_git: '' +forplo: + version: 0.2.5 + title: Flexible Forest Plots + maintainer: '"Vincent ten Cate, PhD"' + description: Simplifies the creation and customization of forest plots (alternatively + called dot-and-whisker plots). Input classes accepted by 'forplo' are data.frame, + matrix, lm, glm, and coxph. 'forplo' was written in base R and does not depend + on other packages. + date_publication: '2023-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forplo + url_git: '' +forrel: + version: 1.7.1 + title: Forensic Pedigree Analysis and Relatedness Inference + maintainer: Magnus Dehli Vigeland + description: |- + Forensic applications of pedigree analysis, including + likelihood ratios for relationship testing, general relatedness + inference, marker simulation, and power analysis. 'forrel' is part of + the 'pedsuite', a collection of packages for pedigree analysis, + further described in the book 'Pedigree Analysis in R' (Vigeland, + 2021, ISBN:9780128244302). Several functions deal specifically with + power analysis in missing person cases, implementing methods described + in Vigeland et al. (2020) . Data + import from the 'Familias' software (Egeland et al. (2000) + ) is supported through the + 'pedFamilias' package. + date_publication: '2025-02-11' + bug_reports: https://github.com/magnusdv/forrel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forrel + url_git: https://github.com/magnusdv/forrel +forsearch: + version: 6.4.0 + title: |- + Diagnostic Analysis Using Forward Search Procedure for Various + Models + maintainer: William Fairweather + description: |- + Identifies potential data outliers and their impact on estimates and + analyses. Tool for evaluation of study credibility. Uses the forward + search approach of Atkinson and Riani, "Robust Diagnostic Regression + Analysis", 2000, to prepare descriptive statistics + of a dataset that is to be analyzed by functions lm {stats}, glm {stats}, + nls {stats}, lme {nlme}, or coxph {survival}, or their equivalent in + another language. Includes graphics functions to display the + descriptive statistics. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forsearch + url_git: '' +forstringr: + version: 1.0.0 + title: |- + String Manipulation Package for Those Familiar with 'Microsoft + Excel' + maintainer: Ezekiel Ogundepo + description: |- + The goal of 'forstringr' is to enable complex string + manipulation in R especially to those more familiar with LEFT(), + RIGHT(), and MID() functions in Microsoft Excel. The package combines + the power of 'stringr' with other manipulation packages such as + 'dplyr' and 'tidyr'. + date_publication: '2023-08-07' + bug_reports: https://github.com/gbganalyst/forstringr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forstringr + url_git: https://github.com/gbganalyst/forstringr +FORTLS: + version: 1.4.0 + title: |- + Automatic Processing of Terrestrial-Based Technologies Point + Cloud Data for Forestry Purposes + maintainer: Juan Alberto Molina-Valero + description: Process automation of point cloud data derived from terrestrial-based + technologies such as Terrestrial Laser Scanner (TLS) or Mobile Laser Scanner. + 'FORTLS' enables (i) detection of trees and estimation of tree-level attributes + (e.g. diameters and heights), (ii) estimation of stand-level variables (e.g. density, + basal area, mean and dominant height), (iii) computation of metrics related to + important forest attributes estimated in Forest Inventories at stand-level, and + (iv) optimization of plot design for combining TLS data and field measured data. + Documentation about 'FORTLS' is described in Molina-Valero et al. (2022, ). + date_publication: '2024-01-21' + bug_reports: https://github.com/Molina-Valero/FORTLS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FORTLS + url_git: https://github.com/Molina-Valero/FORTLS +fortunes: + version: 1.5-4 + title: R Fortunes + maintainer: Achim Zeileis + description: A collection of fortunes from the R community. + date_publication: '2016-12-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fortunes + url_git: '' +forward: + version: 1.0.7 + title: Robust Analysis using Forward Search + maintainer: Ken Beath + description: 'Robust analysis using forward search in linear and generalized linear + regression models, as described in Atkinson, A.C. and Riani, M. (2000), Robust + Diagnostic Regression Analysis, First Edition. New York: Springer.' + date_publication: '2024-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=forward + url_git: '' +forwards: + version: 0.1.3 + title: Data from Surveys Conducted by Forwards + maintainer: Heather Turner + description: Anonymized data from surveys conducted by Forwards , + the R Foundation task force on women and other under-represented groups. Currently, + a single data set of responses to a survey of attendees at useR! 2016 , + the R user conference held at Stanford University, Stanford, California, USA, + June 27 - June 30 2016. + date_publication: '2019-07-30' + bug_reports: https://github.com/forwards/forwards/issues + url: '' + url_cran: https://CRAN.R-project.org/package=forwards + url_git: https://github.com/forwards/forwards +fossil: + version: 0.4.0 + title: Palaeoecological and Palaeogeographical Analysis Tools + maintainer: Matthew J. Vavrek + description: A set of analytical tools useful in analysing ecological and geographical + data sets, both ancient and modern. The package includes functions for estimating + species richness (Chao 1 and 2, ACE, ICE, Jacknife), shared species/beta diversity, + species area curves and geographic distances and areas. + date_publication: '2020-03-23' + bug_reports: '' + url: http://matthewvavrek.com/programs-and-code/fossil/ + url_cran: https://CRAN.R-project.org/package=fossil + url_git: '' +fossilbrush: + version: 1.0.5 + title: Automated Cleaning of Fossil Occurrence Data + maintainer: Joe Flannery-Sutherland + description: Functions to automate the detection and resolution of taxonomic and + stratigraphic errors in fossil occurrence datasets. Functions were developed using + data from the Paleobiology Database. + date_publication: '2024-07-09' + bug_reports: https://cran.r-project.org/package=fossilbrush + url: '' + url_cran: https://CRAN.R-project.org/package=fossilbrush + url_git: '' +FossilSim: + version: 2.4.1 + title: Simulation and Plots for Fossil and Taxonomy Data + maintainer: Joelle Barido-Sottani + description: |- + Simulating and plotting taxonomy and fossil data on phylogenetic trees under mechanistic + models of speciation, preservation and sampling. + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FossilSim + url_git: '' +FossilSimShiny: + version: 1.1.2 + title: Shiny Application for 'FossilSim' + maintainer: Joelle Barido-Sottani + description: |- + A shiny application based on 'FossilSim'. Used for simulating + tree, taxonomic and fossil data under mechanistic models of speciation, + preservation and sampling. + date_publication: '2024-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FossilSimShiny + url_git: '' +foto: + version: '1.1' + title: Fourier Transform Textural Ordination + maintainer: Koen Hufkens + description: |- + A tool to use a principal component analysis on radially averaged + two dimensional Fourier spectra to characterize image texture. The method + within the context of ecology was first described by Couteron et al. (2005) + and expanded upon by + Solorzano et al. (2018) + using a moving window approach. + date_publication: '2023-10-03' + bug_reports: https://github.com/bluegreen-labs/foto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=foto + url_git: https://github.com/bluegreen-labs/foto +foundry: + version: 0.13.0 + title: '''Palantir Foundry'' Software Development Kit' + maintainer: Alexandre Guinaudeau + description: |- + Interface to 'Palantir Foundry', including + reading and writing structured or unstructured datasets, and more + . + date_publication: '2023-05-19' + bug_reports: https://github.com/palantir/palantir-r-sdk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=foundry + url_git: https://github.com/palantir/palantir-r-sdk +FourgameteP: + version: 0.1.0 + title: FourGamete Test + maintainer: Milton T Drott + description: The four-gamete test is based on the infinite-sites model which assumes + that the probability of the same mutation occurring twice (recurrent or parallel + mutations) and the probability of a mutation back to the original state (reverse + mutations) are close to zero. Without these types of mutations, the only explanation + for observing the four dilocus genotypes (example below) is recombination (Hudson + and Kaplan 1985, Genetics 111:147-164). Thus, the presence of all four gametes + is also called phylogenetic incompatibility. + date_publication: '2018-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FourgameteP + url_git: '' +fourierin: + version: 0.2.5 + title: Computes Numeric Fourier Integrals + maintainer: Guillermo Basulto-Elias + description: Computes Fourier integrals of functions of one and two variables using + the Fast Fourier transform. The Fourier transforms must be evaluated on a regular + grid for fast evaluation. + date_publication: '2023-12-08' + bug_reports: https://github.com/gbasulto/fourierin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fourierin + url_git: https://github.com/gbasulto/fourierin +fourPNO: + version: 1.1.0 + title: Bayesian 4 Parameter Item Response Model + maintainer: Steven Andrew Culpepper + description: |- + Estimate Barton & Lord's (1981) + four parameter IRT model with lower and upper asymptotes using Bayesian + formulation described by Culpepper (2016) . + date_publication: '2019-09-24' + bug_reports: https://github.com/tmsalab/fourPNO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fourPNO + url_git: https://github.com/tmsalab/fourPNO +FourScores: + version: 1.5.1 + title: A Game for Human vs. Human or Human vs. AI + maintainer: Matthias Speidel + description: 'A game for two players: Who gets first four in a row (horizontal, + vertical or diagonal) wins. As board game published by Milton Bradley, designed + by Howard Wexler and Ned Strongin.' + date_publication: '2018-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FourScores + url_git: '' +FourWayHMM: + version: 1.0.0 + title: Parsimonious Hidden Markov Models for Four-Way Data + maintainer: Salvatore D. Tomarchio + description: |- + Implements parsimonious hidden Markov models for four-way data via expectation- + conditional maximization algorithm, as described in Tomarchio et al. (2020) . + The matrix-variate normal distribution is used as emission distribution. For each hidden + state, parsimony is reached via the eigen-decomposition of the covariance matrices of the + emission distribution. This produces a family of 98 parsimonious hidden Markov models. + date_publication: '2021-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FourWayHMM + url_git: '' +fpa: + version: '1.0' + title: Spatio-Temporal Fixation Pattern Analysis + maintainer: Jinlu Cao + description: |- + Spatio-temporal Fixation Pattern Analysis (FPA) is a new method of analyzing eye + movement data, developed by Mr. Jinlu Cao under the supervision of Prof. Chen Hsuan-Chih at + The Chinese University of Hong Kong, and Prof. Wang Suiping at the South China Normal + Univeristy. The package "fpa" is a R implementation which makes FPA analysis much easier. + There are four major functions in the package: ft2fp(), get_pattern(), plot_pattern(), and + lineplot(). The function ft2fp() is the core function, which can complete all the preprocessing + within moments. The other three functions are supportive functions which visualize the eye + fixation patterns. + date_publication: '2016-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fpa + url_git: '' +fPASS: + version: 1.0.0 + title: |- + Power and Sample Size for Projection Test under Repeated + Measures + maintainer: Salil Koner + description: |- + Computes the power and sample size (PASS) required to test for the + difference in the mean function between two groups under a repeatedly measured longitudinal + or sparse functional design. See the manuscript by Koner and Luo (2023) + for details of the PASS formula and computational details. The details of the testing + procedure for univariate and multivariate response are presented in + Wang (2021) and Koner and Luo (2023) + respectively. + date_publication: '2023-07-19' + bug_reports: https://github.com/SalilKoner/fPASS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fPASS + url_git: https://github.com/SalilKoner/fPASS +fpc: + version: 2.2-13 + title: Flexible Procedures for Clustering + maintainer: Christian Hennig + description: |- + Various methods for clustering and cluster validation. + Fixed point clustering. Linear regression clustering. Clustering by + merging Gaussian mixture components. Symmetric + and asymmetric discriminant projections for visualisation of the + separation of groupings. Cluster validation statistics + for distance based clustering including corrected Rand index. + Standardisation of cluster validation statistics by random clusterings and + comparison between many clustering methods and numbers of clusters based on + this. + Cluster-wise cluster stability assessment. Methods for estimation of + the number of clusters: Calinski-Harabasz, Tibshirani and Walther's + prediction strength, Fang and Wang's bootstrap stability. + Gaussian/multinomial mixture fitting for mixed + continuous/categorical variables. Variable-wise statistics for cluster + interpretation. DBSCAN clustering. Interface functions for many + clustering methods implemented in R, including estimating the number of + clusters with kmeans, pam and clara. Modality diagnosis for Gaussian + mixtures. For an overview see package?fpc. + date_publication: '2024-09-24' + bug_reports: '' + url: https://www.unibo.it/sitoweb/christian.hennig/en/ + url_cran: https://CRAN.R-project.org/package=fpc + url_git: '' +FPCA3D: + version: '1.0' + title: Three Dimensional Functional Component Analysis + maintainer: Nan Lin + description: Run three dimensional functional principal component analysis and return + the three dimensional functional principal component scores. The details of the + method are explained in Lin et al.(2015) . + date_publication: '2018-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FPCA3D + url_git: '' +fpcb: + version: 0.1.0 + title: |- + Predictive Confidence Bands for Functional Time Series + Forecasting + maintainer: Nicolás Hernández + description: |- + Functions to represent functional objects under a Reproducing Kernel Hilbert Space (RKHS) framework as described + in Muñoz & González (2010). Autoregressive Hilbertian Model for functional time series using RKHS and predictive confidence bands construction + as proposed in Hernández et al (2021). + date_publication: '2021-06-07' + bug_reports: https://github.com/nicolashernandezb/fpcb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fpcb + url_git: '' +FPCdpca: + version: 0.1.0 + title: |- + The FPCdpca Criterion on Distributed Principal Component + Analysis + maintainer: Guangbao Guo + description: We consider optimal subset selection in the setting that one needs + to use only one data subset to represent the whole data set with minimum information + loss, and devise a novel intersection-based criterion on selecting optimal subset, + called as the FPC criterion, to handle with the optimal sub-estimator in distributed + principal component analysis; That is, the FPCdpca. The philosophy of the package + is described in Guo G. (2020) . + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FPCdpca + url_git: '' +fpCompare: + version: 0.2.4 + title: Reliable Comparison of Floating Point Numbers + maintainer: Alex M Chubaty + description: |- + Comparisons of floating point numbers are problematic due to errors + associated with the binary representation of decimal numbers. + Despite being aware of these problems, people still use numerical methods + that fail to account for these and other rounding errors (this pitfall is + the first to be highlighted in Circle 1 of Burns (2012) + 'The R Inferno' ). + This package provides new relational operators useful for performing + floating point number comparisons with a set tolerance. + date_publication: '2022-08-15' + bug_reports: https://github.com/PredictiveEcology/fpCompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fpCompare + url_git: https://github.com/PredictiveEcology/fpCompare +FPDclustering: + version: 2.3.4 + title: PD-Clustering and Related Methods + maintainer: Cristina Tortora + description: Probabilistic distance clustering (PD-clustering) is an iterative, + distribution-free, probabilistic clustering method. PD-clustering assigns units + to a cluster according to their probability of membership under the constraint + that the product of the probability and the distance of each point to any cluster + center is a constant. PD-clustering is a flexible method that can be used with + elliptical clusters, outliers, or noisy data. PDQ is an extension of the algorithm + for clusters of different sizes. GPDC and TPDC use a dissimilarity measure based + on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves + a linear transformation of variables and a cluster optimizing the PD-clustering + criterion. It works on high-dimensional data sets. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FPDclustering + url_git: '' +fpeek: + version: 0.1.2 + title: Check Text Files Content at a Glance + maintainer: David Gohel + description: |- + Tools to help text files importation. It can return + the number of lines; print the first and last lines; convert + encoding. Operations are made without reading the entire file + before starting, resulting in good performances with large files. + This package provides an alternative to a simple use of the + 'head', 'tail', 'wc' and 'iconv' programs that are not always + available on machine where R is installed. + date_publication: '2021-03-31' + bug_reports: https://github.com/davidgohel/fpeek/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fpeek + url_git: https://github.com/davidgohel/fpeek +fpest: + version: 0.1.1 + title: Estimating Finite Population Total + maintainer: S.Sampath + description: |- + Given the values of sampled units and selection probabilities + the desraj function in the package computes the estimated value of the total + as well as estimated variance. + date_publication: '2017-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fpest + url_git: '' +FPLdata: + version: 0.1.0 + title: Read in Fantasy Premier League Data + maintainer: Andrew Little + description: |- + This data contains a large variety of information on players and their + current attributes on Fantasy Premier League + . In particular, it contains a + `next_gw_points` (next gameweek points) value for each player + given their attributes in the current week. Rows represent player-gameweeks, + i.e. for each player there is a row for each gameweek. This + makes the data suitable for modelling a player's next gameweek points, given + attributes such as form, total points, and cost at the current gameweek. + This data can therefore be used to create Fantasy Premier League bots that + may use a machine learning algorithm and a linear programming solver + (for example) to return the best possible transfers and team to pick for + each gameweek, thereby fully automating the decision making process in + Fantasy Premier League. This function simply supplies the required data + for such a task. + date_publication: '2021-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FPLdata + url_git: '' +fplot: + version: 1.1.0 + title: Automatic Distribution Graphs Using Formulas + maintainer: Laurent Berge + description: 'Easy way to plot regular/weighted/conditional distributions by using + formulas. The core of the package concerns distribution plots which are automatic: + the many options are tailored to the data at hand to offer the nicest and most + meaningful graphs possible -- with no/minimum user input. Further provide functions + to plot conditional trends and box plots. See + for more information.' + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fplot + url_git: '' +fplyr: + version: 1.3.0 + title: Apply Functions to Blocks of Files + maintainer: Federico Marotta + description: |- + Read and process a large delimited file block by + block. A block consists of all the contiguous rows that have the same value + in the first field. The result can be returned as a list or a data.table, + or even directly printed to an output file. + date_publication: '2023-08-23' + bug_reports: https://github.com/fmarotta/fplyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fplyr + url_git: https://github.com/fmarotta/fplyr +fpop: + version: 2019.08.26 + title: Segmentation using Optimal Partitioning and Function Pruning + maintainer: Guillem Rigaill + description: |- + A dynamic programming algorithm for the fast segmentation of univariate signals into piecewise constant profiles. + The 'fpop' package is a wrapper to a C++ implementation of the fpop (Functional Pruning Optimal Partioning) algorithm described in Maidstone et al. 2017 + . The problem of detecting changepoints in an univariate sequence is formulated + in terms of minimising the mean squared error over segmentations. The fpop algorithm exactly minimizes the mean squared error + for a penalty linear in the number of changepoints. + date_publication: '2019-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fpop + url_git: '' +fpopw: + version: '1.1' + title: |- + Weighted Segmentation using Functional Pruning and Optimal + Partioning + maintainer: Guillem Rigaill + description: Weighted-L2 FPOP Maidstone et al. (2017) + and pDPA/FPSN Rigaill (2010) algorithm for detecting multiple + changepoints in the mean of a vector. Also includes a few model selection functions + using Lebarbier (2005) and the 'capsushe' package. + date_publication: '2022-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fpopw + url_git: '' +fPortfolio: + version: '4023.84' + title: Rmetrics - Portfolio Selection and Optimization + maintainer: Stefan Theussl + description: A collection of functions to optimize portfolios and to analyze them + from different points of view. + date_publication: '2023-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fPortfolio + url_git: https://r-forge.r-project.org/projects/rmetrics/ +fpow: + version: 0.0-2 + title: |- + Computing the noncentrality parameter of the noncentral F + distribution + maintainer: Ali Baharev + description: |- + Returns the noncentrality parameter of the noncentral F + distribution if probability of type I and type II error, + degrees of freedom of the numerator and the denominator are + given. It may be useful for computing minimal detectable + differences for general ANOVA models. This program is + documented in the paper of A. Baharev, S. Kemeny, On the + computation of the noncentral F and noncentral beta + distribution; Statistics and Computing, 2008, 18 (3), 333-340. + date_publication: '2012-11-01' + bug_reports: '' + url: http://dx.doi.org/10.1007/s11222-008-9061-3 + url_cran: https://CRAN.R-project.org/package=fpow + url_git: '' +fpp: + version: '0.5' + title: 'Data for "Forecasting: principles and practice"' + maintainer: Rob J Hyndman + description: 'All data sets required for the examples and exercises inthe + book "Forecasting: principles and practice" by Rob JHyndman and George + Athanasopoulos. All packages required to runthe examples are also loaded.' + date_publication: '2013-03-14' + bug_reports: '' + url: http://otexts.com/fpp/ + url_cran: https://CRAN.R-project.org/package=fpp + url_git: '' +fpp2: + version: '2.5' + title: 'Data for "Forecasting: Principles and Practice" (2nd Edition)' + maintainer: Rob Hyndman + description: |- + All data sets required for the examples and exercises + in the book "Forecasting: principles and practice" (2nd ed, 2018) + by Rob J Hyndman and George Athanasopoulos . + All packages required to run the examples are also loaded. + date_publication: '2023-02-19' + bug_reports: https://github.com/robjhyndman/fpp2-package/issues + url: https://pkg.robjhyndman.com/fpp2-package/ + url_cran: https://CRAN.R-project.org/package=fpp2 + url_git: https://github.com/robjhyndman/fpp2-package +fpp3: + version: 1.0.1 + title: 'Data for "Forecasting: Principles and Practice" (3rd Edition)' + maintainer: Rob Hyndman + description: |- + All data sets required for the examples and exercises in the book + "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos + . All packages required to run the examples are also + loaded. Additional data sets not used in the book are also included. + date_publication: '2024-09-18' + bug_reports: https://github.com/robjhyndman/fpp3/issues + url: https://pkg.robjhyndman.com/fpp3/ + url_cran: https://CRAN.R-project.org/package=fpp3 + url_git: https://github.com/robjhyndman/fpp3 +fptdApprox: + version: '2.5' + title: |- + Approximation of First-Passage-Time Densities for Diffusion + Processes + maintainer: Juan J. Serrano-Perez + description: Efficient approximation of first passage time densities for diffusion + processes based on the First Passage Time Location (FPTL) function. + date_publication: '2023-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fptdApprox + url_git: '' +FPV: + version: '0.5' + title: Testing Hypotheses via Fuzzy P-Value in Fuzzy Environment + maintainer: Abbas Parchami + description: 'The main goal of this package is drawing the membership function of + the fuzzy p-value which is defined as a fuzzy set on the unit interval for three + following problems: (1) testing crisp hypotheses based on fuzzy data, see Filzmoser + and Viertl (2004) , (2) testing fuzzy hypotheses based + on crisp data, see Parchami et al. (2010) , and + (3) testing fuzzy hypotheses based on fuzzy data, see Parchami et al. (2012) . + In all cases, the fuzziness of data or / and the fuzziness of the boundary of + null fuzzy hypothesis transported via the p-value function and causes to produce + the fuzzy p-value. If the p-value is fuzzy, it is more appropriate to consider + a fuzzy significance level for the problem. Therefore, the comparison of the fuzzy + p-value and the fuzzy significance level is evaluated by a fuzzy ranking method + in this package.' + date_publication: '2017-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FPV + url_git: '' +fqacalc: + version: 1.1.0 + title: Calculate Floristic Quality Assessment Metrics + maintainer: Iris Foxfoot + description: |- + A collection of functions for calculating Floristic Quality + Assessment (FQA) metrics using regional FQA databases that have been + approved or approved with reservations as ecological planning models + by the U.S. Army Corps of Engineers (USACE). For information on FQA + see Spyreas (2019) . These databases are stored + in a sister R package, 'fqadata'. Both packages were developed for the + USACE by the U.S. Army Engineer Research and Development Center’s + Environmental Laboratory. + date_publication: '2023-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fqacalc + url_git: '' +fqadata: + version: 1.1.0 + title: Contains Regional Floristic Quality Assessment Databases + maintainer: Iris Foxfoot + description: |- + Contains regional Floristic Quality Assessment databases that + have been approved or approved with reservations by the U.S. Army + Corps of Engineers (USACE). Paired with the 'fqacalc' R package, these + data sets allow for Floristic Quality Assessment metrics to be + calculated. For information on FQA see Spyreas (2019) + . Both packages were developed for the USACE by + the U.S. Army Engineer Research and Development Center's + Environmental Laboratory. + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fqadata + url_git: '' +fqar: + version: 0.5.4 + title: Floristic Quality Assessment Tools for R + maintainer: Andrew Gard + description: |- + Tools for downloading and analyzing floristic quality assessment data. + See Freyman et al. (2015) for more information + about floristic quality assessment and the associated database. + date_publication: '2024-10-06' + bug_reports: https://github.com/equitable-equations/fqar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fqar + url_git: https://github.com/equitable-equations/fqar/ +fr: + version: 0.5.2 + title: Frictionless Standards + maintainer: Cole Brokamp + description: A "tabular-data-resource" () + is a simple format to describe a singular tabular data resource such as a CSV + file. It includes support both for metadata such as author and title and a schema + to describe the data, for example the types of the fields/columns in the data. + Create a tabular-data-resource by providing a data.frame and specifying metadata. + Write and read tabular-data-resources to and from disk. + date_publication: '2024-11-07' + bug_reports: https://github.com/cole-brokamp/fr/issues + url: https://cole-brokamp.github.io/fr/ + url_cran: https://CRAN.R-project.org/package=fr + url_git: https://github.com/cole-brokamp/fr +frab: + version: 0.0-6 + title: How to Add Two R Tables + maintainer: Robin K. S. Hankin + description: |- + Methods to "add" two R tables; also an alternative + interpretation of named vectors as generalized R tables, so that + c(a=1,b=2,c=3) + c(b=3,a=-1) will return c(b=5,c=3). Uses + 'disordR' discipline (Hankin, 2022, + ). Extraction and replacement + methods are provided. The underlying mathematical structure is + the Free Abelian group, hence the name. To cite in publications + please use Hankin (2023) . + date_publication: '2024-07-24' + bug_reports: https://github.com/RobinHankin/frab + url: '' + url_cran: https://CRAN.R-project.org/package=frab + url_git: https://github.com/RobinHankin/frab +fracARMA: + version: 0.1.0 + title: Fractionally Integrated ARMA Model + maintainer: Muhammed Irshad M + description: "Implements fractional differencing with Autoregressive Moving Average + models to analyse long-memory \ttime series data. Traditional ARIMA models typically + use integer values for differencing, which are \tsuitable for time series with + short memory or anti-persistent behaviour. In contrast, the Fractional ARIMA \tmodel + allows fractional differencing, enabling it to effectively capture long memory + characteristics in \ttime series data. The ‘fracARMA’ package is user-friendly + and allows users to manually input the \tfractional differencing parameter, which + can be obtained using various estimators such as the GPH \testimator, Sperio method, + or Wavelet method and many. Additionally, the package enables users to directly + \tfeed the time series data, AR order, MA order, fractional differencing parameter, + and the proportion of \ttraining data as a split ratio, all in a single command. + The package is based on the reference from the \tpaper of Irshad and others (2024, + )." + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fracARMA + url_git: '' +fracdiff: + version: 1.5-3 + title: Fractionally Differenced ARIMA aka ARFIMA(P,d,q) Models + maintainer: Martin Maechler + description: |- + Maximum likelihood estimation of the parameters of a fractionally + differenced ARIMA(p,d,q) model (Haslett and Raftery, Appl.Statistics, 1989); + including inference and basic methods. Some alternative algorithms to estimate "H". + date_publication: '2024-02-01' + bug_reports: https://github.com/mmaechler/fracdiff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fracdiff + url_git: https://github.com/mmaechler/fracdiff +fracdist: + version: 0.1.1 + title: Numerical CDFs for Fractional Unit Root and Cointegration Tests + maintainer: Lealand Morin + description: |- + Calculate numerical asymptotic distribution functions of likelihood ratio + statistics for fractional unit root tests and tests of cointegration rank. + For these distributions, the included functions calculate critical values + and P-values used in unit root tests, cointegration tests, and rank tests + in the Fractionally Cointegrated Vector Autoregression (FCVAR) model. + The functions implement procedures for tests described in the following articles: + Johansen, S. and M. Ø. Nielsen (2012) , + MacKinnon, J. G. and M. Ø. Nielsen (2014) . + date_publication: '2021-05-25' + bug_reports: https://github.com/LeeMorinUCF/fracdist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fracdist + url_git: https://github.com/LeeMorinUCF/fracdist +FracKrigingR: + version: 1.0.0 + title: Spatial Multivariate Data Modeling + maintainer: Neringa Urbonaite + description: Aim is to provide fractional Brownian vector field generation algorithm, + Hurst parameter estimation method and fractional kriging model for multivariate + data modeling. + date_publication: '2021-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FracKrigingR + url_git: https://github.com/NidaGreen/FracKriging +fracprolif: + version: 1.0.7 + title: Fraction Proliferation via a Quiescent Growth Model + maintainer: Shawn Garbett + description: |- + Functions for fitting data to a quiescent growth model, + i.e. a growth process that involves members of the population + who stop dividing or propagating. + date_publication: '2018-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fracprolif + url_git: '' +fractaldim: + version: 0.8-5 + title: Estimation of Fractal Dimensions + maintainer: Hana Sevcikova + description: Implements various methods for estimating fractal dimension of time + series and 2-dimensional data . + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fractaldim + url_git: '' +FractalParameterEstimation: + version: 1.1.2 + title: |- + Simulation and Parameter Estimation of Randomized Sierpinski + Carpets using the p-p-p-q-Model + maintainer: Philipp Hermann + description: The parameters p and q are estimated with the aid of a randomized Sierpinski + Carpet which is built on a [p-p-p-q]-model. Thereby, for three times a simulation + with a p-value and once with a q-value is assumed. Hence, these parameters are + estimated and displayed. Moreover, functions for simulating random Sierpinski-Carpets + with constant and variable probabilities are included. For more details on the + method please see Hermann et al. (2015) . + date_publication: '2019-07-10' + bug_reports: https://github.com/PhHermann/FractalParameterEstimation + url: '' + url_cran: https://CRAN.R-project.org/package=FractalParameterEstimation + url_git: '' +fractD: + version: 0.1.0 + title: |- + Estimation of Fractal Dimension of a Black Area in 2D and 3D + (Slices) Images + maintainer: Francesco Paolo Mancuso + description: Estimate the of fractal dimension of a black area in 2D and 3D (slices) + images using the box-counting method. See Klinkenberg B. (1994) . + date_publication: '2021-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fractD + url_git: '' +FRACTION: + version: 1.1.1 + title: Numeric Number into Fraction + maintainer: OuYang Ming + description: Turn numeric,data.frame,matrix into fraction form. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRACTION + url_git: '' +fractional: + version: 0.1.3 + title: Vulgar Fractions in R + maintainer: Bill Venables + description: |- + The main function of this package allows numerical vector objects to + be displayed with their values in vulgar fractional form. This is convenient if + patterns can then be more easily detected. In some cases replacing the components + of a numeric vector by a rational approximation can also be expected to remove + some component of round-off error. The main functions form a re-implementation + of the functions 'fractions' and 'rational' of the MASS package, but using a + radically improved programming strategy. + date_publication: '2016-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fractional + url_git: '' +fracture: + version: 0.2.1 + title: Convert Decimals to Fractions + maintainer: Alexander Rossell Hayes + description: |- + Provides functions for converting decimals to a + matrix of numerators and denominators or a character vector of + fractions. Supports mixed or improper fractions, finding common + denominators for vectors of fractions, limiting denominators to powers + of ten, and limiting denominators to a maximum value. Also includes + helper functions for finding the least common multiple and greatest + common divisor for a vector of integers. Implemented using C++ for + maximum speed. + date_publication: '2022-05-21' + bug_reports: https://github.com/rossellhayes/fracture/issues + url: https://fracture.rossellhayes.com/ + url_cran: https://CRAN.R-project.org/package=fracture + url_git: https://github.com/rossellhayes/fracture +fragility: + version: 1.6.1 + title: |- + Assessing and Visualizing Fragility of Clinical Results with + Binary Outcomes + maintainer: Lifeng Lin + description: 'A collection of user-friendly functions for assessing and visualizing + fragility of individual studies (Walsh et al., 2014 ; + Lin, 2021 ), conventional pairwise meta-analyses (Atal + et al., 2019 ), and network meta-analyses + of multiple treatments with binary outcomes (Xing et al., 2020 ). + The included functions are designed to: 1) calculate the fragility index (i.e., + the minimal event status modifications that can alter the significance or non-significance + of the original result) and fragility quotient (i.e., fragility index divided + by sample size) at a specific significance level; 2) give the cases of event status + modifications for altering the result''s significance or non-significance and + visualize these cases; 3) visualize the trend of statistical significance as event + status is modified; 4) efficiently derive fragility indexes and fragility quotients + at multiple significance levels, and visualize the relationship between these + fragility measures against the significance levels; and 5) calculate fragility + indexes and fragility quotients of multiple datasets (e.g., a collection of clinical + trials or meta-analyses) and produce plots of their overall distributions. The + outputs from these functions may inform the robustness of clinical results in + terms of statistical significance and aid the interpretation of fragility measures. + The usage of this package is illustrated in Lin et al. (2023 ) + and detailed in Lin and Chu (2022 ).' + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fragility + url_git: '' +Fragman: + version: 1.0.9 + title: Fragment Analysis in R + maintainer: Giovanny Covarrubias-Pazaran + description: Performs fragment analysis using genetic data coming from capillary + electrophoresis machines. These are files with FSA extension which stands for + FASTA-type file, and .txt files from Beckman CEQ 8000 system, both contain DNA + fragment intensities read by machinery. In addition to visualization, it performs + automatic scoring of SSRs (Sample Sequence Repeats; a type of genetic marker very + common across the genome) and other type of PCR markers (standing for Polymerase + Chain Reaction) in biparental populations such as F1, F2, BC (backcross), and + diversity panels (collection of genetic diversity). + date_publication: '2018-01-14' + bug_reports: '' + url: http://www.wisc.edu + url_cran: https://CRAN.R-project.org/package=Fragman + url_git: '' +frailtyEM: + version: 1.0.1 + title: Fitting Frailty Models with the EM Algorithm + maintainer: Theodor Adrian Balan + description: |- + Contains functions for fitting shared frailty models with a semi-parametric + baseline hazard with the Expectation-Maximization algorithm. Supported data formats + include clustered failures with left truncation and recurrent events in gap-time + or Andersen-Gill format. Several frailty distributions, such as the the gamma, positive stable + and the Power Variance Family are supported. + date_publication: '2019-09-22' + bug_reports: https://github.com/tbalan/frailtyEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frailtyEM + url_git: https://github.com/tbalan/frailtyEM +frailtyHL: + version: '2.3' + title: Frailty Models via Hierarchical Likelihood + maintainer: Maengseok Noh + description: Implements the h-likelihood estimation procedures for general frailty + models including competing-risk models and joint models. + date_publication: '2019-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frailtyHL + url_git: '' +frailtyMMpen: + version: 1.2.1 + title: Efficient Algorithm for High-Dimensional Frailty Model + maintainer: Yunpeng Zhou + description: |- + The penalized and non-penalized Minorize-Maximization (MM) method for frailty models to fit the clustered data, multi-event data and recurrent data. Least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalized functions are implemented. All the methods are computationally efficient. These general methods are proposed based on the following papers, + Huang, Xu and Zhou (2022) , + Huang, Xu and Zhou (2023) . + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frailtyMMpen + url_git: '' +frailtypack: + version: 3.6.5 + title: Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints + maintainer: Virginie Rondeau + description: |- + The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: + 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. + 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). + 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. + 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. + 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. + 6) Joint Nested frailty models in the context of the joint modelling for recurrent events with terminal event, for hierarchically clustered data (with two levels of clustering) by including two iid gamma random effects. + 7) Multivariate joint frailty models for two types of recurrent events and a terminal event. + 8) Joint models for longitudinal data and a terminal event. + 9) Trivariate joint models for longitudinal data, recurrent events and a terminal event. + 10) Joint frailty models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time and/or longitudinal endpoints + with the possibility to use a mediation analysis model. + 11) Conditional and Marginal two-part joint models for longitudinal semicontinuous data and a terminal event. + 12) Joint frailty-copula models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time endpoints. + 13) Generalized shared and joint frailty models for recurrent and terminal events. Proportional hazards (PH), additive hazard (AH), proportional odds (PO) and probit models are available in a fully parametric framework. For PH and AH models, it is possible to consider type-varying coefficients and flexible semiparametric hazard function. + Prediction values are available (for a terminal event or for a new recurrent event). Left-truncated (not for Joint model), right-censored data, interval-censored data (only for Cox proportional hazard and shared frailty model) and strata are allowed. In each model, the random effects have the gamma or normal distribution. Now, you can also consider time-varying covariates effects in Cox, shared and joint frailty models (1-5). The package includes concordance measures for Cox proportional hazards models and for shared frailty models. + 14) Competing Joint Frailty Model: A single type of recurrent event and two terminal events. + Moreover, the package can be used with its shiny application, in a local mode or by following the link below. + date_publication: '2024-12-14' + bug_reports: '' + url: https://virginie1rondeau.wixsite.com/virginierondeau/software-frailtypackhttps://frailtypack-pkg.shinyapps.io/shiny_frailtypack/ + url_cran: https://CRAN.R-project.org/package=frailtypack + url_git: '' +frailtySurv: + version: 1.3.8 + title: General Semiparametric Shared Frailty Model + maintainer: Vinnie Monaco + description: |- + Simulates and fits semiparametric shared frailty models under a + wide range of frailty distributions using a consistent and + asymptotically-normal estimator. Currently supports: gamma, power variance + function, log-normal, and inverse Gaussian frailty models. + date_publication: '2023-08-13' + bug_reports: https://github.com/vmonaco/frailtySurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frailtySurv + url_git: https://github.com/vmonaco/frailtySurv/ +frair: + version: 0.5.100 + title: Tools for Functional Response Analysis + maintainer: Daniel Pritchard + description: Tools to support sensible statistics for functional response analysis. + date_publication: '2017-03-26' + bug_reports: https://github.com/dpritchard/frair/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frair + url_git: https://github.com/dpritchard/frair +framecleaner: + version: 0.2.1 + title: Clean Data Frames + maintainer: Harrison Tietze + description: Provides a friendly interface for modifying data frames with a sequence + of piped commands built upon the 'tidyverse' Wickham et al., (2019) + . The majority of commands wrap 'dplyr' mutate statements in a convenient way + to concisely solve common issues that arise when tidying small to medium data + sets. Includes smart defaults and allows flexible selection of columns via 'tidyselect'. + date_publication: '2024-03-15' + bug_reports: https://github.com/Harrison4192/framecleaner/issues + url: https://harrison4192.github.io/framecleaner/ + url_cran: https://CRAN.R-project.org/package=framecleaner + url_git: https://github.com/Harrison4192/framecleaner +Frames2: + version: 0.2.1 + title: Estimation in Dual Frame Surveys + maintainer: David Molina + description: |- + Point and interval estimation in dual frame surveys. In contrast + to classic sampling theory, where only one sampling frame is considered, + dual frame methodology assumes that there are two frames available for + sampling and that, overall, they cover the entire target population. Then, + two probability samples (one from each frame) are drawn and information + collected is suitably combined to get estimators of the parameter of + interest. + date_publication: '2015-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Frames2 + url_git: '' +franc: + version: 1.1.4 + title: Detect the Language of Text + maintainer: Gábor Csárdi + description: |- + With no external dependencies and + support for 335 languages; all languages spoken by + more than one million speakers. 'Franc' is a port + of the 'JavaScript' project of the same name, + see . + date_publication: '2021-10-18' + bug_reports: https://github.com/gaborcsardi/franc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=franc + url_git: https://github.com/gaborcsardi/franc#readme +FRAPO: + version: 0.4-1 + title: Financial Risk Modelling and Portfolio Optimisation with R + maintainer: Bernhard Pfaff + description: |- + Accompanying package of the book 'Financial Risk Modelling + and Portfolio Optimisation with R', second edition. The data sets used in the book are contained in this package. + date_publication: '2016-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRAPO + url_git: '' +FRApp: + version: 1.0.0 + title: |- + FRAP Data Analysis Using Nonlinear Mixed Effect Models with + 'shiny' + maintainer: Gioia Di Credico + description: |- + Analysis of Fluorescence Recovery After Photobleaching (FRAP) experiments using nonlinear mixed-effects regression models and analysis of the results. 'FRApp' is not limited to the analysis of FRAP experiments only. Any nonlinear mixed-effects models with an asymptotic exponential functional relationship to hierarchical data in various domains can be fitted. + The analysis of data available in the package is presented in Di Credico, G., Pelucchi, S., Pauli, F. et al. (2025) . + date_publication: '2025-02-24' + bug_reports: https://github.com/gioiadc/FRApp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FRApp + url_git: https://github.com/gioiadc/FRApp +frapplot: + version: 0.1.3 + title: Automatic Data Processing and Visualization for FRAP + maintainer: Guanqiao Ding + description: 'Automatically process Fluorescence Recovery After Photobleaching (FRAP) + data and generate consistent, publishable figures. Note: this package does not + replace ''ImageJ'' (or its equivalence) in raw image quantification. Some references + about the methods: Sprague, Brian L. (2004) ; + Day, Charles A. (2012) .' + date_publication: '2019-01-08' + bug_reports: https://github.com/GuanqiaoDing/frapplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frapplot + url_git: https://github.com/GuanqiaoDing/frapplot +FRB: + version: 2.0-1 + title: Fast and Robust Bootstrap + maintainer: Valentin Todorov + description: |- + Perform robust inference based on applying Fast and Robust Bootstrap + on robust estimators (Van Aelst and Willems (2013) ). + This method constitutes an alternative to ordinary bootstrap or asymptotic inference. + procedures when using robust estimators such as S-, MM- or GS-estimators. + The available methods are multivariate regression, principal component analysis + and one-sample and two-sample Hotelling tests. It provides both the robust point + estimates and uncertainty measures based on the fast and robust bootstrap. + date_publication: '2024-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRB + url_git: '' +frbinom: + version: 1.0.0 + title: Fractional Binomial Distributions + maintainer: Jeonghwa Lee + description: Generating fractional binomial random variables and computing density, + cumulative distribution, and quantiles of fractional binomial distributions. (Lee, + J. (2023) .) + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frbinom + url_git: '' +frbs: + version: 3.2-0 + title: Fuzzy Rule-Based Systems for Classification and Regression Tasks + maintainer: Christoph Bergmeir + description: |- + An implementation of various learning algorithms based on fuzzy rule-based systems (FRBSs) for dealing with classification and regression tasks. Moreover, it allows to construct an FRBS model defined by human experts. + FRBSs are based on the concept of fuzzy sets, proposed by Zadeh in 1965, which aims at + representing the reasoning of human experts in a set of IF-THEN rules, to + handle real-life problems in, e.g., control, prediction and inference, data + mining, bioinformatics data processing, and robotics. FRBSs are also known + as fuzzy inference systems and fuzzy models. During the modeling of an + FRBS, there are two important steps that need to be conducted: structure + identification and parameter estimation. Nowadays, there exists a wide + variety of algorithms to generate fuzzy IF-THEN rules automatically from + numerical data, covering both steps. Approaches that have been used in the + past are, e.g., heuristic procedures, neuro-fuzzy techniques, clustering + methods, genetic algorithms, squares methods, etc. Furthermore, in this + version we provide a universal framework named 'frbsPMML', which is adopted + from the Predictive Model Markup Language (PMML), for representing FRBS + models. PMML is an XML-based language to provide a standard for describing + models produced by data mining and machine learning algorithms. Therefore, + we are allowed to export and import an FRBS model to/from 'frbsPMML'. + Finally, this package aims to implement the most widely used standard + procedures, thus offering a standard package for FRBS modeling to the R + community. + date_publication: '2019-12-15' + bug_reports: '' + url: http://sci2s.ugr.es/dicits/software/FRBS + url_cran: https://CRAN.R-project.org/package=frbs + url_git: '' +FRCC: + version: 1.1.0 + title: Fast Regularized Canonical Correlation Analysis + maintainer: Raul Cruz-Cano + description: |- + Contains the core functions associated with Fast + Regularized Canonical Correlation Analysis. Please see the following for + details: Raul Cruz-Cano, Mei-Ling Ting Lee, + Fast regularized canonical correlation analysis, + Computational Statistics & Data Analysis, + Volume 70, 2014, Pages 88-100, + ISSN 0167-9473 . + date_publication: '2022-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRCC + url_git: '' +frechet: + version: 0.3.0 + title: Statistical Analysis for Random Objects and Non-Euclidean Data + maintainer: Yaqing Chen + description: |- + Provides implementation of statistical methods for random objects + lying in various metric spaces, which are not necessarily linear spaces. + The core of this package is Fréchet regression for random objects with + Euclidean predictors, which allows one to perform regression analysis + for non-Euclidean responses under some mild conditions. + Examples include distributions in 2-Wasserstein space, + covariance matrices endowed with power metric (with Frobenius metric + as a special case), Cholesky and log-Cholesky metrics, spherical data. + References: Petersen, A., & Müller, H.-G. (2019) . + date_publication: '2023-12-09' + bug_reports: https://github.com/functionaldata/tFrechet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frechet + url_git: https://github.com/functionaldata/tFrechet +fredr: + version: 2.1.0 + title: An R Client for the 'FRED' API + maintainer: Sam Boysel + description: |- + An R client for the 'Federal Reserve Economic Data' + ('FRED') API . Functions + to retrieve economic time series and other data from 'FRED'. + date_publication: '2021-01-29' + bug_reports: https://github.com/sboysel/fredr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fredr + url_git: https://github.com/sboysel/fredr +free: + version: 1.0.2 + title: Flexible Regularized Estimating Equations + maintainer: Yi Lian + description: 'Unified regularized estimating equation solver. Currently the package + includes one solver with the l1 penalty only. More solvers and penalties are under + development. Reference: Yi Yang, Yuwen Gu, Yue Zhao, Jun Fan (2021) .' + date_publication: '2024-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=free + url_git: '' +freealg: + version: 1.1-8 + title: The Free Algebra + maintainer: Robin K. S. Hankin + description: |- + The free algebra in R with non-commuting indeterminates. + Uses 'disordR' discipline + (Hankin, 2022, ). To cite the + package in publications please use Hankin (2022) + . + date_publication: '2024-08-26' + bug_reports: https://github.com/RobinHankin/freealg/issues + url: https://robinhankin.github.io/freealg/ + url_cran: https://CRAN.R-project.org/package=freealg + url_git: https://github.com/RobinHankin/freealg +freebird: + version: '1.0' + title: |- + Estimation and Inference for High Dimensional Mediation and + Surrogate Analysis + maintainer: Layla Parast + description: |- + Estimates and provides inference for quantities that assess high dimensional mediation and potential surrogate markers including the direct effect of treatment, indirect effect of treatment, and the proportion of treatment effect explained by a surrogate/mediator; details are described in Zhou et al (2022) and Zhou et al (2020) + . This package relies on the optimization software 'MOSEK', + . + date_publication: '2022-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freebird + url_git: '' +freecurrencyapi: + version: 0.1.0 + title: Client for the 'freecurrencyapi.com' Currency Conversion API + maintainer: Dominik Kukacka + description: An R client for the 'freecurrencyapi.com' currency conversion API. + The API requires registration of an API key. You can find the full API documentation + at . + date_publication: '2023-05-10' + bug_reports: '' + url: https://freecurrencyapi.com + url_cran: https://CRAN.R-project.org/package=freecurrencyapi + url_git: '' +freedom: + version: 1.0.1 + title: Demonstration of Disease Freedom (DDF) + maintainer: Thomas Rosendal + description: |- + Implements the formulae required to calculate freedom + from disease according to Cameron and Baldock (1998) + . These are the + methods used at the Swedish national veterinary institute (SVA) to + evaluate the performance of our nation animal disease + surveillance programmes. + date_publication: '2020-09-08' + bug_reports: https://github.com/SVA-SE/freedom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=freedom + url_git: https://github.com/SVA-SE/freedom +freegroup: + version: 1.1-9 + title: The Free Group + maintainer: Robin K. S. Hankin + description: |- + The free group in R; juxtaposition is represented by a + plus. Includes inversion, multiplication by a scalar, + group-theoretic power operation, and Tietze forms. To cite the + package in publications please use Hankin (2022) + . + date_publication: '2025-01-30' + bug_reports: https://github.com/RobinHankin/freegroup/issues + url: https://robinhankin.github.io/freegroup/ + url_cran: https://CRAN.R-project.org/package=freegroup + url_git: https://github.com/RobinHankin/freegroup +FreeSortR: + version: '1.3' + title: Free Sorting Data Analysis + maintainer: Philippe Courcoux + description: Provides tools for describing and analysing free sorting data. Main + methods are computation of consensus partition and factorial analysis of the dissimilarity + matrix between stimuli (using multidimensional scaling approach). + date_publication: '2017-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FreeSortR + url_git: '' +freesurfer: + version: 1.6.10 + title: Wrapper Functions for 'Freesurfer' + maintainer: John Muschelli + description: |- + Wrapper functions that interface with 'Freesurfer' + , a powerful and + commonly-used 'neuroimaging' + software, using system commands. The goal is to be able to interface with + 'Freesurfer' completely in R, where you pass R objects of class 'nifti', + implemented by package 'oro.nifti', and the function executes an 'Freesurfer' + command and returns an R object of class 'nifti' or necessary output. + date_publication: '2024-05-14' + bug_reports: https://github.com/muschellij2/freesurfer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=freesurfer + url_git: '' +freesurferformats: + version: 0.1.18 + title: Read and Write 'FreeSurfer' Neuroimaging File Formats + maintainer: Tim Schäfer + description: 'Provides functions to read and write neuroimaging data in various + file formats, with a focus on ''FreeSurfer'' formats. + This includes, but is not limited to, the following file formats: 1) MGH/MGZ format + files, which can contain multi-dimensional images or other data. Typically they + contain time-series of three-dimensional brain scans acquired by magnetic resonance + imaging (MRI). They can also contain vertex-wise measures of surface morphometry + data. The MGH format is named after the Massachusetts General Hospital, and the + MGZ format is a compressed version of the same format. 2) ''FreeSurfer'' morphometry + data files in binary ''curv'' format. These contain vertex-wise surface measures, + i.e., one scalar value for each vertex of a brain surface mesh. These are typically + values like the cortical thickness or brain surface area at each vertex. 3) Annotation + file format. This contains a brain surface parcellation derived from a cortical + atlas. 4) Surface file format. Contains a brain surface mesh, given by a list + of vertices and a list of faces.' + date_publication: '2024-02-02' + bug_reports: https://github.com/dfsp-spirit/freesurferformats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=freesurferformats + url_git: https://github.com/dfsp-spirit/freesurferformats +FREEtree: + version: 0.1.0 + title: Tree Method for High Dimensional Longitudinal Data + maintainer: Athanasse Zafirov + description: |- + This tree-based method deals with high dimensional longitudinal + data with correlated features through the use of a piecewise random effect + model. FREE tree also exploits the network structure of the features, by + first clustering them using Weighted Gene Co-expression Network Analysis + ('WGCNA'). It then conducts a screening step within each cluster of features + and a selecting step among the surviving features, which provides a relatively + unbiased way to do feature selection. By using dominant principle components + as regression variables at each leaf and the original features as splitting + variables at splitting nodes, FREE tree delivers easily interpretable results + while improving computational efficiency. + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FREEtree + url_git: '' +freewall: + version: 1.0.0 + title: A Wrapper of the JavaScript Library 'Freewall' + maintainer: Stéphane Laurent + description: |- + Creates dynamic grid layouts of images that can be included in + 'Shiny' applications and R markdown documents. + date_publication: '2024-04-30' + bug_reports: https://github.com/stla/freewall/issues + url: '' + url_cran: https://CRAN.R-project.org/package=freewall + url_git: https://github.com/stla/freewall +fRegression: + version: '4021.83' + title: Rmetrics - Regression Based Decision and Prediction + maintainer: Paul J. Northrop + description: |- + A collection of functions for linear and non-linear regression + modelling. It implements a wrapper for several regression models available + in the base and contributed packages of R. + date_publication: '2022-08-11' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fRegression + url_git: '' +frenchCurve: + version: 0.2.0 + title: Generate Open or Closed Interpolating Curves + maintainer: Bill Venables + description: |- + Functions for finding smooth interpolating curves connecting + a series of points in the plane. Curves may be open or closed, + that is, with the first and last point of the curve at the initial point. + date_publication: '2022-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frenchCurve + url_git: '' +frenchdata: + version: 0.2.0 + title: |- + Download Data Sets from Kenneth's French Finance Data Library + Site + maintainer: Nelson Areal + description: |- + Download data sets from Kenneth's French finance data library site , reads all the data subsets from the file. Allows R users to collect the data as + 'tidyverse'-ready data frames. + date_publication: '2021-09-10' + bug_reports: https://github.com/nareal/frenchdata/issues + url: https://nareal.github.io/frenchdata/ + url_cran: https://CRAN.R-project.org/package=frenchdata + url_git: https://github.com/nareal/frenchdata +FREQ: + version: '1.0' + title: 'FREQ: Estimate population size from capture frequencies' + maintainer: Annegret Grimm + description: Real capture frequencies will be fitted to various distributions which + provide the basis of estimating population sizes, their standard error, and symmetric + as well as asymmetric confidence intervalls. + date_publication: '2013-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FREQ + url_git: '' +freqdist: + version: '0.1' + title: Frequency Distribution + maintainer: Kenneth W. Moffett + description: |- + Generates a frequency distribution. The frequency + distribution includes raw frequencies, percentages in each category, and + cumulative frequencies. The frequency distribution can be stored as a data + frame. + date_publication: '2016-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freqdist + url_git: '' +freqdistributionNogives: + version: 0.1.1 + title: Automated Cumulative Frequency Plots for Grouped Distribution + maintainer: Harshit Budakoti + description: Input has to be in the form of vectors of lower class limits and upper + class limits and frequencies; the output will give a cumulative frequency distribution + table with cumulative frequency plot. + date_publication: '2022-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freqdistributionNogives + url_git: https://github.com/Harshit-Budakoti/freqdistributionNogives +freqdom: + version: 2.0.5 + title: 'Frequency Domain Based Analysis: Dynamic PCA' + maintainer: Kidzinski L. + description: |- + Implementation of dynamic principal component + analysis (DPCA), simulation of VAR and VMA processes and frequency domain tools. + These frequency domain methods for dimensionality reduction of multivariate time series + were introduced by David Brillinger in his book Time Series (1974). We follow implementation + guidelines as described in Hormann, Kidzinski and Hallin (2016), + Dynamic Functional Principal Component . + date_publication: '2024-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freqdom + url_git: '' +freqdom.fda: + version: 1.0.1 + title: 'Functional Time Series: Dynamic Functional Principal Components' + maintainer: Kidzinski L. + description: |- + Implementations of functional dynamic principle components analysis. Related graphic tools and frequency domain methods. + These methods directly use multivariate dynamic principal components implementation, + following the guidelines from Hormann, Kidzinski and Hallin (2016), Dynamic Functional Principal Component . + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freqdom.fda + url_git: '' +freqparcoord: + version: 1.0.1 + title: Novel Methods for Parallel Coordinates + maintainer: Norm Matloff + description: |- + New approaches to parallel coordinates plots for + multivariate data visualization, including applications to clustering, + outlier hunting and regression diagnostics. Includes general functions + for multivariate nonparametric density and regression estimation, + using parallel computation. + date_publication: '2016-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freqparcoord + url_git: '' +freqpcr: + version: 0.4.0 + title: |- + Estimates Allele Frequency on qPCR DeltaDeltaCq from Bulk + Samples + maintainer: Masaaki Sudo + description: Interval estimation of the population allele frequency from qPCR analysis + based on the restriction enzyme digestion (RED)-DeltaDeltaCq method (Osakabe et + al. 2017, ), as well as general DeltaDeltaCq + analysis. Compatible with the Cq measurement of DNA extracted from multiple individuals + at once, so called "group-testing", this model assumes that the quantity of DNA + extracted from an individual organism follows a gamma distribution. Therefore, + the point estimate is robust regarding the uncertainty of the DNA yield. + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=freqpcr + url_git: https://github.com/sudoms/freqpcr +FreqProf: + version: 0.0.1 + title: Frequency Profiles Computing and Plotting + maintainer: Ronald E. Robertson + description: |- + Tools for generating an informative type of line graph, the frequency profile, + which allows single behaviors, multiple behaviors, or the specific behavioral patterns + of individual subjects to be graphed from occurrence/nonoccurrence behavioral data. + date_publication: '2016-01-21' + bug_reports: https://github.com/AIBRT/FreqProf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FreqProf + url_git: https://github.com/AIBRT/FreqProf +freqtables: + version: 0.1.1 + title: Make Quick Descriptive Tables for Categorical Variables + maintainer: Brad Cannell + description: |- + Quickly make tables of descriptive statistics (i.e., counts, + percentages, confidence intervals) for categorical variables. This + package is designed to work in a Tidyverse pipeline, and consideration + has been given to get results from R to Microsoft Word ® with minimal pain. + date_publication: '2022-04-03' + bug_reports: https://github.com/brad-cannell/freqtables/issues + url: '' + url_cran: https://CRAN.R-project.org/package=freqtables + url_git: https://github.com/brad-cannell/freqtables +frequency: + version: 0.4.1 + title: Easy Frequency Tables + maintainer: Alistair Wilcox + description: |- + Generate 'SPSS'/'SAS' styled frequency tables. Frequency tables are + generated with variable and value label attributes where applicable with optional + html output to quickly examine datasets. + date_publication: '2021-01-11' + bug_reports: https://github.com/wilcoxa/frequency/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frequency + url_git: https://github.com/wilcoxa/frequency +frequencyConnectedness: + version: 0.2.4 + title: Spectral Decomposition of Connectedness Measures + maintainer: Tomas Krehlik + description: Accompanies a paper (Barunik, Krehlik (2018) ) + dedicated to spectral decomposition of connectedness measures and their interpretation. + We implement all the developed estimators as well as the historical counterparts. + For more information, see the help or GitHub page () + for relevant information. + date_publication: '2023-02-24' + bug_reports: https://github.com/tomaskrehlik/frequencyConnectedness/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frequencyConnectedness + url_git: https://github.com/tomaskrehlik/frequencyConnectedness +frequentdirections: + version: 0.1.0 + title: |- + Implementation of Frequent-Directions Algorithm for Efficient + Matrix Sketching + maintainer: Shinichi Takayanagi + description: |- + Implement frequent-directions algorithm for efficient matrix sketching. + (Edo Liberty (2013) ). + date_publication: '2019-04-16' + bug_reports: https://github.com/shinichi-takayanagi/frequentdirections/issues + url: '' + url_cran: https://CRAN.R-project.org/package=frequentdirections + url_git: https://github.com/shinichi-takayanagi/frequentdirections +frequentistSSD: + version: 0.1.1 + title: Screened Selection Design with Survival Endpoints + maintainer: Chia-Wei Hsu + description: A study based on the screened selection design (SSD) is an exploratory + phase II randomized trial with two or more arms but without concurrent control. + The primary aim of the SSD trial is to pick a desirable treatment arm (e.g., in + terms of the median survival time) to recommend to the subsequent randomized phase + IIb (with the concurrent control) or phase III. Though The survival endpoint is + often encountered in phase II trials, the existing SSD methods cannot deal with + the survival endpoint. Furthermore, the existing SSD won’t control the type I + error rate. The proposed designs can “partially” control or provide the empirical + type I error/false positive rate by an optimal algorithm (implemented by the optimal() + function) for each arm. All the design needed components (sample size, operating + characteristics) are supported. + date_publication: '2022-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frequentistSSD + url_git: '' +frequentistSSDBinary: + version: 0.1.0 + title: Screened Selection Design with Binary Endpoints + maintainer: Chia-Wei Hsu + description: A study based on the screened selection design (SSD) is an exploratory + phase II randomized trial with two or more arms but without concurrent control. + The primary aim of the SSD trial is to pick a desirable treatment arm (e.g., in + terms of the response rate) to recommend to the subsequent randomized phase IIb + (with the concurrent control) or phase III. The proposed designs can “partially” + control or provide the empirical type I error/false positive rate by an optimal + algorithm (implemented by the optimal_2arm_binary() or optimal_3arm_binary() function) + for each arm. All the design needed components (sample size, operating characteristics) + are supported. + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frequentistSSDBinary + url_git: '' +FRESA.CAD: + version: 3.4.8 + title: Feature Selection Algorithms for Computer Aided Diagnosis + maintainer: Jose Gerardo Tamez-Pena + description: Contains a set of utilities for building and testing statistical models + (linear, logistic,ordinal or COX) for Computer Aided Diagnosis/Prognosis applications. + Utilities include data adjustment, univariate analysis, model building, model-validation, + longitudinal analysis, reporting and visualization. + date_publication: '2024-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRESA.CAD + url_git: '' +fresh: + version: 0.2.1 + title: Create Custom 'Bootstrap' Themes to Use in 'Shiny' + maintainer: Victor Perrier + description: |- + Customize 'Bootstrap' and 'Bootswatch' themes, like colors, fonts, grid layout, + to use in 'Shiny' applications, 'rmarkdown' documents and 'flexdashboard'. + date_publication: '2024-06-26' + bug_reports: https://github.com/dreamRs/fresh/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fresh + url_git: https://github.com/dreamRs/fresh +FRESHD: + version: '1.0' + title: Fast Robust Estimation of Signals in Heterogeneous Data + maintainer: Adam Lund + description: Procedure for solving the maximin problem for identical design across + heterogeneous data groups. Particularly efficient when the design matrix is either + orthogonal or has tensor structure. Orthogonal wavelets can be specified for 1d, + 2d or 3d data simply by name. For tensor structured design the tensor components + (two or three) may be supplied. The package also provides an efficient implementation + of the generic magging estimator. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRESHD + url_git: '' +freshr: + version: 1.0.2 + title: Make R Environment Fresh Again + maintainer: Shawn Lin + description: |- + A simple way to unload none-base packages and remove all global + variables. + date_publication: '2022-10-03' + bug_reports: https://github.com/shawnlinxl/freshr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=freshr + url_git: https://github.com/shawnlinxl/freshr +FrF2: + version: 2.3-3 + title: Fractional Factorial Designs with 2-Level Factors + maintainer: Ulrike Groemping + description: |- + Regular and non-regular Fractional Factorial 2-level designs + can be created. Furthermore, analysis tools for Fractional + Factorial designs with 2-level factors are offered (main + effects and interaction plots for all factors simultaneously, + cube plot for looking at the simultaneous effects of three + factors, full or half normal plot, alias structure in a more + readable format than with the built-in function alias). + date_publication: '2023-09-20' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/DoE/ + url_cran: https://CRAN.R-project.org/package=FrF2 + url_git: '' +FrF2.catlg128: + version: 1.2-3 + title: |- + Catalogues of Resolution IV 128 Run 2-Level Fractional + Factorials Up to 33 Factors that Do Have 5-Letter Words + maintainer: Ulrike Groemping + description: |- + Catalogues of resolution IV regular + fractional factorial designs in 128 runs are provided + for up to 33 2-level factors. The catalogues are complete, + excluding resolution IV designs without 5-letter words, + because these do not add value for a search for unblocked + clear designs. The previous package version + 1.0 with complete catalogues up to 24 runs (24 runs and a + namespace added later) can be downloaded from the authors + website. + date_publication: '2023-10-07' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/DoE/ + url_cran: https://CRAN.R-project.org/package=FrF2.catlg128 + url_git: '' +FRI: + version: '1.0' + title: Relative Importance of Main and Interaction Effects + maintainer: Omar Maghawry Ibrahim + description: Computes relative importance of main and interaction effects. Also, + sum of the modified generalized weights is computed. Ibrahim et al. (2022) . + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FRI + url_git: '' +frictionless: + version: 1.2.0 + title: Read and Write Frictionless Data Packages + maintainer: Peter Desmet + description: |- + Read and write Frictionless Data Packages. A 'Data Package' + () is a simple + container format and standard to describe and package a collection of + (tabular) data. It is typically used to publish FAIR + () and open datasets. + date_publication: '2024-08-28' + bug_reports: https://github.com/frictionlessdata/frictionless-r/issues + url: https://docs.ropensci.org/frictionless/ + url_cran: https://CRAN.R-project.org/package=frictionless + url_git: https://github.com/frictionlessdata/frictionless-r +friends: + version: 0.1.0 + title: The Entire Transcript from Friends in Tidy Format + maintainer: Emil Hvitfeldt + description: |- + The complete scripts from the American sitcom Friends in tibble + format. Use this package to practice data wrangling, text analysis and + network analysis. + date_publication: '2020-09-03' + bug_reports: https://github.com/EmilHvitfeldt/friends/issues + url: '' + url_cran: https://CRAN.R-project.org/package=friends + url_git: https://github.com/EmilHvitfeldt/friends +fritools: + version: 4.4.0 + title: |- + Utilities for the Forest Research Institute of the State + Baden-Wuerttemberg + maintainer: Andreas Dominik Cullmann + description: |- + Miscellaneous utilities, tools and helper + functions for finding and searching files on disk, searching for and + removing R objects from the workspace. + Does not import or depend on any third party package, but on core R + only (i.e. it may depend on packages with priority 'base'). + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fritools + url_git: https://gitlab.com/fvafrcu/fritools +fritools2: + version: 4.1.0 + title: |- + Utilities for the Forest Research Institute of the State + Baden-Wuerttemberg + maintainer: Andreas Dominik Cullmann + description: |- + Miscellaneous utilities, tools and helper + functions for finding and searching files on disk, searching for and + removing R objects from the workspace. + Does not import or depend on any third party package, but on core R + only (i.e. it may depend on packages with priority 'base'). + date_publication: '2023-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fritools2 + url_git: https://gitlab.com/fvafrcu/fritools +FRK: + version: 2.3.1 + title: Fixed Rank Kriging + maintainer: Andrew Zammit-Mangion + description: A tool for spatial/spatio-temporal modelling and prediction with large + datasets. The approach models the field, and hence the covariance function, using + a set of basis functions. This fixed-rank basis-function representation facilitates + the modelling of big data, and the method naturally allows for non-stationary, + anisotropic covariance functions. Discretisation of the spatial domain into so-called + basic areal units (BAUs) facilitates the use of observations with varying support + (i.e., both point-referenced and areal supports, potentially simultaneously), + and prediction over arbitrary user-specified regions. `FRK` also supports inference + over various manifolds, including the 2D plane and 3D sphere, and it provides + helper functions to model, fit, predict, and plot with relative ease. Version + 2.0.0 and above also supports the modelling of non-Gaussian data (e.g., Poisson, + binomial, negative-binomial, gamma, and inverse-Gaussian) by employing a generalised + linear mixed model (GLMM) framework. Zammit-Mangion and Cressie + describe `FRK` in a Gaussian setting, and detail its use of basis functions and + BAUs, while Sainsbury-Dale, Zammit-Mangion, and Cressie + describe `FRK` in a non-Gaussian setting; two vignettes are available that summarise + these papers and provide additional examples. + date_publication: '2024-07-16' + bug_reports: https://github.com/andrewzm/FRK/issues/ + url: https://andrewzm.github.io/FRK/ + url_cran: https://CRAN.R-project.org/package=FRK + url_git: https://github.com/andrewzm/FRK/ +fRLR: + version: 1.3.0 + title: Fit Repeated Linear Regressions + maintainer: Lijun Wang + description: When fitting a set of linear regressions which have some same variables, + we can separate the matrix and reduce the computation cost. This package aims + to fit a set of repeated linear regressions faster. More details can be found + in this blog Lijun Wang (2017) . + date_publication: '2023-10-12' + bug_reports: '' + url: https://stats.hohoweiya.xyz/regression/2017/09/26/An-R-Package-Fit-Repeated-Linear-Regressions/ + url_cran: https://CRAN.R-project.org/package=fRLR + url_git: https://github.com/szcf-weiya/fRLR +froggeR: + version: 0.3.0 + title: Enhance 'Quarto' Project Workflows and Standards + maintainer: Kyle Grealis + description: 'Streamlines ''Quarto'' workflows by providing tools for consistent + project setup and documentation. Enables portability through reusable metadata, + automated project structure creation, and standardized templates. Features include + enhanced project initialization, pre-formatted ''Quarto'' documents, comprehensive + data protection settings, custom styling, and structured documentation generation. + Designed to improve efficiency and collaboration in R data science projects by + reducing repetitive setup tasks while maintaining consistent formatting across + multiple documents. There are many valuable resources providing in-depth explanations + of customizing ''Quarto'' templates and theme styling by the Posit team: + & , and at the Bootstrap + community''s GitHub at .' + date_publication: '2025-01-15' + bug_reports: https://github.com/kyleGrealis/froggeR/issues + url: https://kylegrealis.github.io/froggeR/ + url_cran: https://CRAN.R-project.org/package=froggeR + url_git: '' +fromhere: + version: 0.1.0 + title: File Paths Relative to Project Roots + maintainer: Mitchell O'Hara-Wild + description: |- + Provides a set of helper functions for constructing file paths + relative to the root of various types of projects, such as R packages, Git + repositories, and more. File paths are specified with function arguments, + or `$` to navigate into folders to specific files supported by + auto-completion. + date_publication: '2025-01-15' + bug_reports: https://github.com/mitchelloharawild/fromhere/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fromhere + url_git: https://github.com/mitchelloharawild/fromhere +fromo: + version: 0.2.4 + title: Fast Robust Moments + maintainer: Steven E. Pav + description: |- + Fast, numerically robust computation of weighted moments via 'Rcpp'. + Supports computation on vectors and matrices, and Monoidal append of moments. + Moments and cumulants over running fixed length windows can be computed, + as well as over time-based windows. + Moment computations are via a generalization of Welford's method, as described + by Bennett et. (2009) . + date_publication: '2024-11-30' + bug_reports: https://github.com/shabbychef/fromo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fromo + url_git: https://github.com/shabbychef/fromo +frontier: + version: 1.1-8 + title: Stochastic Frontier Analysis + maintainer: Arne Henningsen + description: |- + Maximum Likelihood Estimation of + Stochastic Frontier Production and Cost Functions. + Two specifications are available: + the error components specification with time-varying efficiencies + (Battese and Coelli, 1992, ) + and a model specification in which the firm effects are directly + influenced by a number of variables (Battese and Coelli, 1995, + ). + date_publication: '2020-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frontier + url_git: http://frontier.r-forge.r-project.org/ +frontiles: + version: 1.3.1 + title: Partial Frontier Efficiency Analysis + maintainer: Thibault Laurent + description: It calculates the alpha-quantile proposed by Daouia and Simar (2007) + and order-m efficiency score in multi-dimension + proposed by Daouia and Gijbels (2011) and + computes several summaries and representation of the associated frontiers in 2d + and 3d. + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frontiles + url_git: '' +frostr: + version: 0.2.0 + title: R API to MET Norway's 'Frost' API + maintainer: Iman Ghayoornia + description: |- + An R API to MET Norway's 'Frost' API + to retrieve data as data frames. The 'Frost' API, and the underlying data, is + made available by the Norwegian Meteorological Institute (MET Norway). The data + and products are distributed under the + Norwegian License for Open Data 2.0 (NLOD) + and Creative Commons 4.0 . + date_publication: '2020-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frostr + url_git: '' +froth: + version: 1.1.0 + title: Emulate a 'Forth' Programming Environment + maintainer: Aidan Lakshman + description: |- + Emulates a 'Forth' programming environment with added features to + interface between R and 'Forth'. Implements most of the functionality described + in the original "Starting Forth" textbook . + date_publication: '2024-03-04' + bug_reports: https://github.com/ahl27/froth/issues/new/choose + url: https://www.ahl27.com/froth/ + url_cran: https://CRAN.R-project.org/package=froth + url_git: '' +frscore: + version: 0.4.1 + title: Functions for Calculating Fit-Robustness of CNA-Solutions + maintainer: Veli-Pekka Parkkinen + description: |- + Functions for automatically performing + a reanalysis series + on a data set using CNA, and for calculating the fit-robustness + of the resulting models, as described in + Parkkinen and Baumgartner (2021) . + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=frscore + url_git: '' +fruclimadapt: + version: 0.4.5 + title: |- + Evaluation Tools for Assessing Climate Adaptation of Fruit Tree + Species + maintainer: Carlos Miranda + description: |- + Climate is a critical component limiting growing range of plant species, which + also determines cultivar adaptation to a region. The evaluation of climate influence on + fruit production is critical for decision-making in the design stage of orchards and + vineyards and in the evaluation of the potential consequences of future climate. Bio- + climatic indices and plant phenology are commonly used to describe the suitability of + climate for growing quality fruit and to provide temporal and spatial information about + regarding ongoing and future changes. 'fruclimadapt' streamlines the assessment of + climate adaptation and the identification of potential risks for grapevines and fruit + trees. Procedures in the package allow to i) downscale daily meteorological variables + to hourly values (Forster et al (2016) ), + ii) estimate chilling and forcing heat accumulation (Miranda et al (2019) + ), + iii) estimate plant phenology (Schwartz (2012) ), iv) + calculate bioclimatic indices to evaluate fruit tree and grapevine adaptation (e.g. Badr + et al (2017) ), v) estimate the incidence of weather-related disorders + in fruits (e.g. Snyder and de Melo-Abreu (2005, ISBN:92-5-105328-6) and vi) + estimate plant water requirements (Allen et al (1998, ISBN:92-5-104219-5)). + date_publication: '2023-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fruclimadapt + url_git: '' +fs: + version: 1.6.5 + title: Cross-Platform File System Operations Based on 'libuv' + maintainer: Gábor Csárdi + description: |- + A cross-platform interface to file system operations, built + on top of the 'libuv' C library. + date_publication: '2024-10-30' + bug_reports: https://github.com/r-lib/fs/issues + url: https://fs.r-lib.org + url_cran: https://CRAN.R-project.org/package=fs + url_git: https://github.com/r-lib/fs +FSA: + version: 0.9.6 + title: Simple Fisheries Stock Assessment Methods + maintainer: Derek H. Ogle + description: A variety of simple fish stock assessment methods. + date_publication: '2025-01-07' + bug_reports: https://github.com/fishR-Core-Team/FSA/issues + url: https://fishr-core-team.github.io/FSA/ + url_cran: https://CRAN.R-project.org/package=FSA + url_git: '' +FSAdata: + version: 0.4.1 + title: Data to Support Fish Stock Assessment ('FSA') Package + maintainer: Derek Ogle + description: The datasets to support the Fish Stock Assessment ('FSA') package. + date_publication: '2023-08-24' + bug_reports: https://github.com/fishR-Core-Team/FSAdata/issues + url: https://fishr-core-team.github.io/FSAdata/ + url_cran: https://CRAN.R-project.org/package=FSAdata + url_git: '' +fsbrain: + version: 0.5.5 + title: Managing and Visualizing Brain Surface Data + maintainer: Tim Schäfer + description: Provides high-level access to neuroimaging data from standard software + packages like 'FreeSurfer' on the level of subjects and + groups. Load morphometry data, surfaces and brain parcellations based on atlases. + Mask data using labels, load data for specific atlas regions only, and visualize + data and statistical results directly in 'R'. + date_publication: '2024-02-03' + bug_reports: https://github.com/dfsp-spirit/fsbrain/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fsbrain + url_git: https://github.com/dfsp-spirit/fsbrain +fscache: + version: 1.0.5 + title: File System Cache + maintainer: Pierrick Roger + description: 'Manages a file system cache. Regular files can be moved or copied + to the cache folder. Sub-folders can be created in order to organize the files. + Files can be located inside the cache using a glob function. Text contents can + be easily stored in and retrieved from the cache using dedicated functions. It + can be used for an application or a package, as a global cache, or as a per-user + cache, in which case the standard OS user cache folder will be used (e.g.: on + Linux $HOME/.cache/R/my_app_or_pkg_cache_folder).' + date_publication: '2024-06-02' + bug_reports: https://gitlab.com/cnrgh/databases/r-fscache/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fscache + url_git: https://gitlab.com/cnrgh/databases/r-fscache +fscaret: + version: 0.9.4.4 + title: Automated Feature Selection from 'caret' + maintainer: Jakub Szlek + description: |- + Automated feature selection using variety of models + provided by 'caret' package. + This work was funded by Poland-Singapore bilateral cooperation + project no 2/3/POL-SIN/2012. + date_publication: '2018-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fscaret + url_git: '' +FSDAM: + version: 2024.7-30 + title: Forward Stepwise Deep Autoencoder-Based Monotone NLDR + maintainer: Youyi Fong + description: FS-DAM performs feature extraction through latent variables identification. + Implementation is based on autoencoders with monotonicity and orthogonality constraints. + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FSDAM + url_git: '' +fsdaR: + version: 0.9-0 + title: |- + Robust Data Analysis Through Monitoring and Dynamic + Visualization + maintainer: Valentin Todorov + description: |- + Provides interface to the 'MATLAB' toolbox 'Flexible Statistical Data Analysis + (FSDA)' which is comprehensive and computationally efficient + software package for robust statistics in regression, multivariate + and categorical data analysis. The current R version implements tools + for regression: (forward search, S- and MM-estimation, least trimmed + squares (LTS) and least median of squares (LMS)), for multivariate analysis + (forward search, S- and MM-estimation), for cluster analysis and cluster-wise regression. + The distinctive feature of our package is the possibility of + monitoring the statistics of interest as a function of breakdown point, + efficiency or subset size, depending on the estimator. This is + accompanied by a rich set of graphical features, such as dynamic + brushing, linking, particularly useful for exploratory data analysis. + date_publication: '2023-12-06' + bug_reports: https://github.com/UniprJRC/fsdaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fsdaR + url_git: https://github.com/UniprJRC/fsdaR +FSelector: + version: '0.34' + title: Selecting Attributes + maintainer: Lars Kotthoff + description: |- + Functions for selecting attributes from a given + dataset. Attribute subset selection is the process of identifying and + removing as much of the irrelevant and redundant information as + possible. + date_publication: '2023-08-22' + bug_reports: https://github.com/larskotthoff/fselector/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FSelector + url_git: https://github.com/larskotthoff/fselector +FSelectorRcpp: + version: 0.3.13 + title: |- + 'Rcpp' Implementation of 'FSelector' Entropy-Based Feature + Selection Algorithms with a Sparse Matrix Support + maintainer: Zygmunt Zawadzki + description: |- + 'Rcpp' (free of 'Java'/'Weka') implementation of 'FSelector' entropy-based feature selection + algorithms based on an MDL discretization (Fayyad U. M., Irani K. B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. + In 13'th International Joint Conference on Uncertainly in Artificial Intelligence (IJCAI93), pages 1022-1029, Chambery, France, 1993.) + with a sparse matrix support. + date_publication: '2024-10-02' + bug_reports: https://github.com/mi2-warsaw/FSelectorRcpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FSelectorRcpp + url_git: https://github.com/mi2-warsaw/FSelectorRcpp +fsemipar: + version: 1.1.1 + title: |- + Estimation, Variable Selection and Prediction for Functional + Semiparametric Models + maintainer: Silvia Novo + description: Routines for the estimation or simultaneous estimation and variable + selection in several functional semiparametric models with scalar responses are + provided. These models include the functional single-index model, the semi-functional + partial linear model, and the semi-functional partial linear single-index model. + Additionally, the package offers algorithms for handling scalar covariates with + linear effects that originate from the discretization of a curve. This functionality + is applicable in the context of the linear model, the multi-functional partial + linear model, and the multi-functional partial linear single-index model. + date_publication: '2024-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fsemipar + url_git: '' +fsia: + version: 1.1.1 + title: Import and Analysis of OMR Data from FormScanner + maintainer: Michela Battauz + description: Import data of tests and questionnaires from FormScanner. FormScanner + is an open source software that converts scanned images to data using optical + mark recognition (OMR) and it can be downloaded from . + The spreadsheet file created by FormScanner is imported in a convenient format + to perform the analyses provided by the package. These analyses include the conversion + of multiple responses to binary (correct/incorrect) data, the computation of the + number of corrected responses for each subject or item, scoring using weights,the + computation and the graphical representation of the frequencies of the responses + to each item and the report of the responses of a few subjects. + date_publication: '2017-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fsia + url_git: '' +FSInteract: + version: 0.1.2 + title: Fast Searches for Interactions + maintainer: Rajen D. Shah + description: |- + Performs fast detection of interactions in large-scale data using the + method of random intersection trees introduced in + Shah, R. D. and Meinshausen, N. (2014) . + The algorithm finds potentially high-order interactions in high-dimensional binary + two-class classification data, without requiring lower order interactions + to be informative. The search is particularly fast when the matrices of + predictors are sparse. It can also be used to perform market basket analysis + when supplied with a single binary data matrix. Here it will find collections + of columns which for many rows contain all 1's. + date_publication: '2017-04-03' + bug_reports: '' + url: http://www.jmlr.org/papers/v15/shah14a.html + url_cran: https://CRAN.R-project.org/package=FSInteract + url_git: '' +FSK2R: + version: 0.1.3 + title: An Interface Between the 'FSKX' Standard and 'R' + maintainer: Alberto Garre + description: |- + Functions for importing, creating, editing and + exporting 'FSK' files + using the 'R' programming environment. Furthermore, it enables users + to run simulations contained in the 'FSK' files and visualize the results. + date_publication: '2022-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FSK2R + url_git: '' +fslr: + version: 2.25.3 + title: |- + Wrapper Functions for 'FSL' ('FMRIB' Software Library) from + Functional MRI of the Brain ('FMRIB') + maintainer: John Muschelli + description: |- + Wrapper functions that interface with 'FSL' + , a powerful and commonly-used 'neuroimaging' + software, using system commands. The goal is to be able to interface with 'FSL' + completely in R, where you pass R objects of class 'nifti', implemented by + package 'oro.nifti', and the function executes an 'FSL' command and returns an R + object of class 'nifti' if desired. + date_publication: '2024-05-10' + bug_reports: https://github.com/muschellij2/fslr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fslr + url_git: '' +FSM: + version: 1.0.0 + title: Finite Selection Model + maintainer: Ambarish Chattopadhyay + description: Randomized and balanced allocation of units to treatment groups using + the Finite Selection Model (FSM). The FSM was originally proposed and developed + at the RAND corporation by Carl Morris to enhance the experimental design for + the now famous Health Insurance Experiment. See Morris (1979) + for details on the original version of the FSM. + date_publication: '2021-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FSM + url_git: '' +fsn: + version: '0.4' + title: Rosenthal's Fail Safe Number and Related Functions + maintainer: Michail Tsagris + description: 'Estimation of Rosenthal''s fail safe number including confidence intervals. + The relevant papers are the following. Konstantinos C. Fragkos, Michail Tsagris + and Christos C. Frangos (2014). "Publication Bias in Meta-Analysis: Confidence + Intervals for Rosenthal''s Fail-Safe Number". International Scholarly Research + Notices, Volume 2014. . Konstantinos C. Fragkos, Michail + Tsagris and Christos C. Frangos (2017). "Exploring the distribution for the estimator + of Rosenthal''s fail-safe number of unpublished studies in meta-analysis". Communications + in Statistics-Theory and Methods, 46(11):5672--5684. .' + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fsn + url_git: '' +fso: + version: 2.1-2 + title: Fuzzy Set Ordination + maintainer: David W. Roberts + description: |- + Fuzzy set ordination is a multivariate analysis used in ecology to + relate the composition of samples to possible explanatory variables. While + differing in theory and method, in practice, the use is similar to 'constrained + ordination.' The package contains plotting and summary functions as well as + the analyses. + date_publication: '2022-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fso + url_git: '' +fspe: + version: 0.1.2 + title: |- + Estimating the Number of Factors in EFA with Out-of-Sample + Prediction Errors + maintainer: Jonas Haslbeck + description: Estimating the number of factors in Exploratory Factor Analysis (EFA) + with out-of-sample prediction errors using a cross-validation scheme. Haslbeck + & van Bork (Preprint) . + date_publication: '2023-03-28' + bug_reports: https://github.com/jmbh/fspe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fspe + url_git: '' +fsr: + version: 2.0.1 + title: Handling Fuzzy Spatial Data + maintainer: Anderson Carniel + description: |- + Support for fuzzy spatial objects, their operations, and fuzzy spatial inference models based on Spatial Plateau Algebra. + It employs fuzzy set theory and fuzzy logic as foundation to deal with spatial fuzziness. + It mainly implements underlying concepts defined in the following research papers: + (i) "Spatial Plateau Algebra: An Executable Type System for Fuzzy Spatial Data Types" ; + (ii) "A Systematic Approach to Creating Fuzzy Region Objects from Real Spatial Data Sets" ; + (iii) "Spatial Data Types for Heterogeneously Structured Fuzzy Spatial Collections and Compositions" ; + (iv) "Fuzzy Inference on Fuzzy Spatial Objects (FIFUS) for Spatial Decision Support Systems" ; + (v) "Evaluating Region Inference Methods by Using Fuzzy Spatial Inference Models" . + date_publication: '2024-01-10' + bug_reports: https://github.com/accarniel/fsr/issues + url: https://accarniel.github.io/fsr/ + url_cran: https://CRAN.R-project.org/package=fsr + url_git: https://github.com/accarniel/fsr +fSRM: + version: 0.6.5 + title: Social Relations Analyses with Roles ("Family SRM") + maintainer: Felix Schönbrodt + description: |- + Social Relations Analysis with roles ("Family SRM") are computed, + using a structural equation modeling approach. Groups ranging from three members + up to an unlimited number of members are supported and the mean structure can + be computed. Means and variances can be compared between different groups of + families and between roles. + date_publication: '2021-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fSRM + url_git: '' +fssemR: + version: 0.1.8 + title: |- + Fused Sparse Structural Equation Models to Jointly Infer Gene + Regulatory Network + maintainer: Xin Zhou + description: |- + An optimizer of Fused-Sparse Structural Equation Models, which is + the state of the art jointly fused sparse maximum likelihood function + for structural equation models proposed by Xin Zhou and Xiaodong Cai (2018 + ). + date_publication: '2022-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fssemR + url_git: https://github.com/Ivis4ml/fssemR +FSSF: + version: 0.1.1 + title: |- + Generate Fully-Sequential Space-Filling Designs Inside a Unit + Hypercube + maintainer: Boyang Shang + description: Provides three methods proposed by Shang and Apley (2019) + to generate fully-sequential space-filling designs inside a unit hypercube. A + 'fully-sequential space-filling design' means a sequence of nested designs (as + the design size varies from one point up to some maximum number of points) with + the design points added one at a time and such that the design at each size has + good space-filling properties. Two methods target the minimum pairwise distance + criterion and generate maximin designs, among which one method is more efficient + when design size is large. One method targets the maximum hole size criterion + and uses a heuristic to generate what is closer to a minimax design. + date_publication: '2020-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FSSF + url_git: '' +fst: + version: 0.9.8 + title: Lightning Fast Serialization of Data Frames + maintainer: Mark Klik + description: |- + Multithreaded serialization of compressed data frames using the 'fst' format. The + 'fst' format allows for full random access of stored data and a wide range of compression + settings using the LZ4 and ZSTD compressors. + date_publication: '2022-02-08' + bug_reports: https://github.com/fstpackage/fst/issues + url: http://www.fstpackage.org + url_cran: https://CRAN.R-project.org/package=fst + url_git: '' +fst4pg: + version: 1.0.0 + title: Genetic Distance Segmentation for Population Genetics + maintainer: Tristan Mary-Huard + description: |- + Provides efficient methods to compute local and genome wide + genetic distances (corresponding to the so called Hudson Fst + parameters) through moment method, perform chromosome segmentation + into homogeneous Fst genomic regions, and selection sweep detection + for multi-population comparison. When multiple profile segmentation is + required, the procedure can be parallelized using the future package. + date_publication: '2022-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fst4pg + url_git: '' +Fstability: + version: 0.1.2 + title: Calculate Feature Stability + maintainer: Nicolas Ewen + description: |- + Has two functions to help with calculating feature selection stability. 'Lump' is a function that groups subset vectors into a dataframe, and adds NA to shorter vectors so they all have the same length. + 'ASM' is a function that takes a dataframe of subset vectors and the original vector of features as inputs, and calculates the Stability of the feature selection. + The calculation for 'asm' uses the Adjusted Stability Measure proposed in: 'Lustgarten', 'Gopalakrishnan', & 'Visweswaran' (2009). + date_publication: '2018-12-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Fstability + url_git: '' +fstcore: + version: 0.10.0 + title: R Bindings to the 'Fstlib' Library + maintainer: Mark Klik + description: |- + The 'fstlib' library provides multithreaded serialization of compressed data frames using the + 'fst' format. The 'fst' format allows for random access of stored data and compression with the 'LZ4' and 'ZSTD' + compressors. + date_publication: '2025-02-10' + bug_reports: https://github.com/fstpackage/fst/issues + url: https://www.fstpackage.org/fstcore/ + url_cran: https://CRAN.R-project.org/package=fstcore + url_git: '' +fsthet: + version: 1.0.1 + title: Fst-Heterozygosity Smoothed Quantiles + maintainer: Sarah P. Flanagan + description: A program to generate smoothed quantiles for the Fst-heterozygosity + distribution. Designed for use with large numbers of loci (e.g., genome-wide SNPs). + The best case for analyzing the Fst-heterozygosity distribution is when many populations + (>10) have been sampled. See Flanagan & Jones (2017) . + date_publication: '2018-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fsthet + url_git: '' +FSTpackage: + version: '0.1' + title: |- + Unified Sequence-Based Association Tests Allowing for Multiple + Functional Annotation Scores + maintainer: Zihuai He + description: Functions for sequencing studies allowing for multiple functional annotation + scores. Score type tests and an efficient perturbation method are used for individual + gene/large gene-set/genome wide analysis. Only summary statistics are needed. + date_publication: '2017-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FSTpackage + url_git: '' +ftaproxim: + version: 0.0.1 + title: Fault Tree Analysis Based on Proxel Simulation + maintainer: Hossein Haghbin + description: 'Calculation and plotting of instantaneous unavailabilities of basic + events along with the top event of fault trees are issues important in reliability + analysis of complex systems. Here, a fault tree is provided in terms of its minimal + cut sets, along with reliability and maintainability distribution functions of + the basic events. All the methods are derived from Horton (2002, ISBN: 3-936150-21-4), + Niloofar and Lazarova-Molnar (2022).' + date_publication: '2022-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ftaproxim + url_git: '' +ftDK: + version: '1.0' + title: A Wrapper for the API of the Danish Parliament + maintainer: Mikkel Freltoft Krogsholm + description: |- + A wrapper for the API of the Danish Parliament. It makes it + possible to get data from the API easily into a data frame. Learn more at + . + date_publication: '2017-06-21' + bug_reports: https://github.com/mikkelkrogsholm/ftDK/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ftDK + url_git: https://github.com/mikkelkrogsholm/ftDK +ftExtra: + version: 0.6.4 + title: Extensions for 'Flextable' + maintainer: Atsushi Yasumoto + description: |- + Build display tables easily by extending the functionality of the + 'flextable' package. Features include spanning header, grouping rows, + parsing markdown and so on. + date_publication: '2024-05-10' + bug_reports: https://github.com/atusy/ftExtra/issues + url: https://ftextra.atusy.net + url_cran: https://CRAN.R-project.org/package=ftExtra + url_git: https://github.com/atusy/ftExtra +fTrading: + version: '3042.79' + title: Rmetrics - Trading and Rebalancing Financial Instruments + maintainer: Tobias Setz + description: |- + A collection of functions for trading and rebalancing financial + instruments. It implements various technical indicators to analyse time series such + as moving averages or stochastic oscillators. + date_publication: '2017-11-15' + bug_reports: '' + url: http://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fTrading + url_git: '' +ftrCOOL: + version: 2.0.0 + title: Feature Extraction from Biological Sequences + maintainer: Sare Amerifar + description: 'Extracts features from biological sequences. It contains most features + which are presented in related work and also includes features which have never + been introduced before. It extracts numerous features from nucleotide and peptide + sequences. Each feature converts the input sequences to discrete numbers in order + to use them as predictors in machine learning models. There are many features + and information which are hidden inside a sequence. Utilizing the package, users + can convert biological sequences to discrete models based on chosen properties. + References: ''iLearn'' ''Z. Chen et al.'' (2019) . ''iFeature'' + ''Z. Chen et al.'' (2018) . . + ''PseKRAAC'' ''Y. Zuo et al.'' ''PseKRAAC: a flexible web server for generating + pseudo K-tuple reduced amino acids composition'' (2017) . + ''iDNA6mA-PseKNC'' ''P. Feng et al.'' ''iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine + sites by incorporating nucleotide physicochemical properties into PseKNC'' (2019) + . ''I. Dubchak et al.'' ''Prediction of protein + folding class using global description of amino acid sequence'' (1995) . + ''W. Chen et al.'' ''Identification and analysis of the N6-methyladenosine in + the Saccharomyces cerevisiae transcriptome'' (2015) .' + date_publication: '2021-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ftrCOOL + url_git: '' +ftsa: + version: '6.6' + title: Functional Time Series Analysis + maintainer: Han Lin Shang + description: Functions for visualizing, modeling, forecasting and hypothesis testing + of functional time series. + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ftsa + url_git: '' +FTSgof: + version: 1.0.0 + title: White Noise and Goodness-of-Fit Tests for Functional Time Series + maintainer: Mihyun Kim + description: |- + It offers comprehensive tools for the analysis of functional + time series data, focusing on white noise hypothesis testing and + goodness-of-fit evaluations, alongside functions for + simulating data and advanced visualization techniques, such as 3D + rainbow plots. These methods are described in Kokoszka, Rice, and Shang (2017) , + Yeh, Rice, and Dubin (2023) , Kim, Kokoszka, and Rice (2023) , and + Rice, Wirjanto, and Zhao (2020) . + date_publication: '2024-10-03' + bug_reports: https://github.com/veritasmih/FTSgof/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FTSgof + url_git: https://github.com/veritasmih/FTSgof +ftsspec: + version: 1.0.0 + title: |- + Spectral Density Estimation and Comparison for Functional Time + Series + maintainer: Shahin Tavakoli + description: |- + Functions for estimating spectral density operator of functional + time series (FTS) and comparing the spectral density operator of two + functional time series, in a way that allows detection of differences of + the spectral density operator in frequencies and along the curve length. + date_publication: '2015-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ftsspec + url_git: '' +fucom: + version: 0.0.3 + title: Full Consistency Method (FUCOM) + maintainer: Mateus Vanzetta + description: Full Consistency Method (FUCOM) for multi-criteria decision-making + (MCDM), developed by Dragam Pamucar in 2018 (). The goal + of the method is to determine the weights of criteria such that the deviation + from full consistency is minimized. Users provide a character vector specifying + the ranking of each criterion according to its significance, starting from the + criterion expected to have the highest weight to the least significant one. Additionally, + users provide a numeric vector specifying the priority values for each criterion. + The comparison is made with respect to the first-ranked (most significant) criterion. + The function returns the optimized weights for each criterion (summing to 1), + the comparative priority (Phi) values, the mathematical transitivity condition + (w) value, and the minimum deviation from full consistency (DFC). + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fucom + url_git: '' +fude: + version: 0.3.7 + title: Utilities for Fude Polygon + maintainer: Takeshi Nishimura + description: |- + Provides utilities to facilitate handling of Fude Polygon data + downloadable from the Ministry of Agriculture, Forestry and Fisheries + website . + date_publication: '2024-12-22' + bug_reports: https://github.com/takeshinishimura/fude/issues + url: https://takeshinishimura.github.io/fude/ + url_cran: https://CRAN.R-project.org/package=fude + url_git: https://github.com/takeshinishimura/fude +fuel: + version: 1.2.0 + title: Framework for Unified Estimation in Lognormal Models + maintainer: Jiangtao Gou + description: Lognormal models have broad applications in various research areas + such as economics, actuarial science, biology, environmental science and psychology. + The estimation problem in lognormal models has been extensively studied. This + R package 'fuel' implements thirty-nine existing and newly proposed estimators. + See Zhang, F., and Gou, J. (2020), A unified framework for estimation in lognormal + models, Technical report. + date_publication: '2020-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fuel + url_git: '' +fueleconomy: + version: 1.0.0 + title: EPA Fuel Economy Data + maintainer: Hadley Wickham + description: |- + Fuel economy data from the EPA, 1985-2015, + conveniently packaged for consumption by R users. + date_publication: '2020-03-23' + bug_reports: https://github.com/hadley/fueleconomy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fueleconomy + url_git: https://github.com/hadley/fueleconomy +fugue: + version: 0.1.7 + title: Sensitivity Analysis Optimized for Matched Sets of Varied Sizes + maintainer: Paul R. Rosenbaum + description: As in music, a fugue statistic repeats a theme in small variations. Here, + the psi-function that defines an m-statistic is slightly altered to maintain the + same design sensitivity in matched sets of different sizes. The main functions + in the package are sen() and senCI(). For sensitivity analyses for m-statistics, + see Rosenbaum (2007) Biometrics 63 456-464 . + date_publication: '2019-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fugue + url_git: '' +fuj: + version: 0.2.1 + title: Functions and Utilities for Jordan + maintainer: Jordan Mark Barbone + description: |- + Provides core functions and utilities for packages and other code + developed by Jordan Mark Barbone. + date_publication: '2024-05-20' + bug_reports: https://github.com/jmbarbone/fuj/issues + url: https://jmbarbone.github.io/fuj/ + url_cran: https://CRAN.R-project.org/package=fuj + url_git: https://github.com/jmbarbone/fuj +fullfact: + version: 1.5.2 + title: Full Factorial Breeding Analysis + maintainer: Aimee Lee Houde + description: We facilitate the analysis of full factorial mating designs with mixed-effects + models. The package contains six vignettes containing detailed examples. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fullfact + url_git: '' +fullRankMatrix: + version: 0.1.0 + title: Generation of Full Rank Design Matrix + maintainer: Paula Weidemueller + description: |- + Creates a full rank matrix out of a given matrix. + The intended use is for one-hot encoded design matrices that should be used in linear models to ensure that significant associations can be correctly interpreted. However, 'fullRankMatrix' can be applied to any matrix to make it full rank. + It removes columns with only 0's, merges duplicated columns and discovers linearly dependent columns and replaces them with linearly independent columns that span the space of the original columns. Columns are renamed to reflect those modifications. + This results in a full rank matrix that can be used as a design matrix in linear models. The algorithm and some functions are inspired by Kuhn, M. (2008) . + date_publication: '2024-06-28' + bug_reports: https://github.com/Pweidemueller/fullRankMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fullRankMatrix + url_git: https://github.com/Pweidemueller/fullRankMatrix +fullROC: + version: 0.1.0 + title: Plot Full ROC Curves using Eyewitness Lineup Data + maintainer: Yueran Yang + description: |- + Enable researchers to adjust identification rates using the 1/(lineup size) method, generate the full receiver operating characteristic (ROC) curves, and statistically compare the area under the curves (AUC). + References: Yueran Yang & Andrew Smith. (2020). "fullROC: An R package for generating and analyzing eyewitness-lineup ROC curves". , + Andrew Smith, Yueran Yang, & Gary Wells. (2020). "Distinguishing between investigator discriminability and eyewitness discriminability: A method for creating full receiver operating characteristic curves of lineup identification performance". Perspectives on Psychological Science, 15(3), 589-607. . + date_publication: '2021-01-13' + bug_reports: https://github.com/yuerany/fullROC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fullROC + url_git: '' +fun: + version: '0.3' + title: Use R for Fun + maintainer: Yihui Xie + description: |- + This is a collection of R games and other funny stuff, such as the + classic Mine sweeper and sliding puzzles. + date_publication: '2020-10-23' + bug_reports: https://github.com/yihui/fun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fun + url_git: https://github.com/yihui/fun +func2vis: + version: 1.0-3 + title: |- + Clean and Visualize Over Expression Results from + 'ConsensusPathDB' + maintainer: Raghvendra Mall + description: |- + Provides functions to have visualization and clean-up of enriched gene ontologies (GO) terms, + protein complexes and pathways (obtained from multiple databases) using 'ConsensusPathDB' + from gene set over-expression analysis. Performs clustering of pathway based on similarity + of over-expressed gene sets and visualizations similar to Ingenuity Pathway Analysis (IPA) + when up and down regulated genes are known. The methods are described in a paper currently + submitted by Orecchioni et al, 2020 in Nanoscale. + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=func2vis + url_git: '' +FunCC: + version: '1.0' + title: Functional Cheng and Church Bi-Clustering + maintainer: Agostino Torti + description: The FunCC algorithm allows to apply the FunCC algorithm to simultaneously + cluster the rows and the columns of a data matrix whose inputs are functions. + date_publication: '2020-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FunCC + url_git: '' +FuncDiv: + version: 1.0.0 + title: Compute Contributional Diversity Metrics + maintainer: Gavin Douglas + description: |- + Compute alpha and beta contributional diversity metrics, + which is intended for linking taxonomic and functional microbiome + data. See 'GitHub' repository for the tutorial: + . Citation: Gavin M. + Douglas, Sunu Kim, Morgan G. I. Langille, B. Jesse Shapiro (2023) + . + date_publication: '2023-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuncDiv + url_git: '' +funcharts: + version: 1.6.0 + title: Functional Control Charts + maintainer: Christian Capezza + description: |- + Provides functional control charts + for statistical process monitoring of functional data, + using the methods of Capezza et al. (2020) , + Centofanti et al. (2021) , + Capezza et al. (2024) , + Capezza et al. (2024) , + Centofanti et al. (2022) . + The package is thoroughly illustrated in the paper of + Capezza et al (2023) . + date_publication: '2024-12-11' + bug_reports: https://github.com/unina-sfere/funcharts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=funcharts + url_git: https://github.com/unina-sfere/funcharts +funchir: + version: 0.3.0-1 + title: Convenience Functions by Michael Chirico + maintainer: Michael Chirico + description: YACFP (Yet Another Convenience Function Package). get_age() is a fast + & accurate tool for measuring fractional years between two dates. stale_package_check() + tries to identify any library() calls to unused packages. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funchir + url_git: https://github.com/MichaelChirico/funchir +FunChisq: + version: 2.5.4 + title: Model-Free Functional Chi-Squared and Exact Tests + maintainer: Joe Song + description: |- + Statistical hypothesis testing methods for + inferring model-free functional dependency using asymptotic + chi-squared or exact distributions. Functional test + statistics are asymmetric and functionally optimal, unique + from other related statistics. Tests in this package reveal + evidence for causality based on the causality-by- + functionality principle. They include asymptotic functional + chi-squared tests (Zhang & Song 2013) , + an adapted functional chi-squared test (Kumar & Song 2022) + , + and an exact functional test (Zhong & Song 2019) + (Nguyen et al. 2020) + . The normalized functional + chi-squared test was used by Best Performer 'NMSUSongLab' + in HPN-DREAM (DREAM8) Breast Cancer Network Inference + Challenges (Hill et al. 2016) . A + function index (Zhong & Song 2019) + (Kumar et al. 2018) + derived from the + functional test statistic offers a new effect size measure + for the strength of functional dependency, a better + alternative to conditional entropy in many aspects. For + continuous data, these tests offer an advantage over + regression analysis when a parametric functional form + cannot be assumed; for categorical data, they provide a + novel means to assess directional dependency not possible + with symmetrical Pearson's chi-squared or Fisher's exact + tests. + date_publication: '2024-05-10' + bug_reports: '' + url: https://www.cs.nmsu.edu/~joemsong/publications/ + url_cran: https://CRAN.R-project.org/package=FunChisq + url_git: '' +FuncMap: + version: 1.0.10 + title: Hive Plots of R Package Function Calls + maintainer: Bryan A. Hanson + description: 'Analyzes the function calls in an R package and creates a hive plot + of the calls, dividing them among functions that only make outgoing calls (sources), + functions that have only incoming calls (sinks), and those that have both incoming + calls and make outgoing calls (managers). Function calls can be mapped by their + absolute numbers, their normalized absolute numbers, or their rank. FuncMap should + be useful for comparing packages at a high level for their overall design. Plus, + it''s just plain fun. The hive plot concept was developed by Martin Krzywinski + (www.hiveplot.com) and inspired this package. Note: this package is maintained + for historical reasons. HiveR is a full package for creating hive plots.' + date_publication: '2018-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuncMap + url_git: '' +FuncNN: + version: '1.0' + title: Functional Neural Networks + maintainer: Barinder Thind + description: |- + A collection of functions which fit functional neural network models. In + other words, this package will allow users to build deep learning models + that have either functional or scalar responses paired with functional and + scalar covariates. We implement the theoretical discussion found + in Thind, Multani and Cao (2020) through the help of a main fitting and + prediction function as well as a number of helper functions to assist with + cross-validation, tuning, and the display of estimated functional weights. + date_publication: '2020-09-15' + bug_reports: '' + url: https://arxiv.org/abs/2006.09590 + url_cran: https://CRAN.R-project.org/package=FuncNN + url_git: https://github.com/b-thi/FuncNN +FunctanSNP: + version: 0.1.0 + title: Functional Analysis (with Interactions) for Dense SNP Data + maintainer: Rui Ren + description: An implementation of revised functional regression models for multiple + genetic variation data, such as single nucleotide polymorphism (SNP) data, which + provides revised functional linear regression models, partially functional interaction + regression analysis with penalty-based techniques and corresponding drawing functions, + etc.(Ruzong Fan, Yifan Wang, James L. Mills, Alexander F. Wilson, Joan E. Bailey-Wilson, + and Momiao Xiong (2013) ). + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FunctanSNP + url_git: '' +functional: + version: '0.6' + title: Curry, Compose, and other higher-order functions + maintainer: Peter Danenberg + description: Curry, Compose, and other higher-order functions + date_publication: '2014-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=functional + url_git: '' +functiondepends: + version: 0.2.3 + title: Find Functions and their Dependencies + maintainer: Jakub Sobolewski + description: |- + Find functions in an unstructured directory and explore their dependencies. + Sourcing of R source files is performed without side-effects: from R scripts that have + executable code and function definitions only functions are sourced. + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=functiondepends + url_git: '' +funData: + version: 1.3-9 + title: An S4 Class for Functional Data + maintainer: Clara Happ-Kurz + description: |- + S4 classes for univariate and multivariate functional data with + utility functions. See for a detailed description + of the package functionalities and its interplay with the MFPCA package for + multivariate functional principal component analysis + . + date_publication: '2024-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funData + url_git: https://github.com/ClaraHapp/funData +fundiversity: + version: 1.1.1 + title: Easy Computation of Functional Diversity Indices + maintainer: Matthias Grenié + description: |- + Computes six functional diversity indices. These are namely, + Functional Divergence (FDiv), Function Evenness (FEve), Functional Richness + (FRic), Functional Richness intersections (FRic_intersect), Functional + Dispersion (FDis), and Rao's entropy (Q) (reviewed in Villéger et al. 2008 + ). Provides efficient, modular, and parallel functions + to compute functional diversity indices + (preprint: ). + date_publication: '2022-11-21' + bug_reports: https://github.com/funecology/fundiversity/issues + url: https://funecology.github.io/fundiversity/ + url_cran: https://CRAN.R-project.org/package=fundiversity + url_git: https://github.com/funecology/fundiversity +funFEM: + version: '1.2' + title: Clustering in the Discriminative Functional Subspace + maintainer: Charles Bouveyron + description: The funFEM algorithm (Bouveyron et al., 2014) allows to cluster functional + data by modeling the curves within a common and discriminative functional subspace. + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funFEM + url_git: '' +fungible: + version: 2.4.4 + title: Psychometric Functions from the Waller Lab + maintainer: Niels Waller + description: |- + Computes fungible coefficients and Monte Carlo data. Underlying theory for these functions is described in the following publications: + Waller, N. (2008). Fungible Weights in Multiple Regression. Psychometrika, 73(4), 691-703, . + Waller, N. & Jones, J. (2009). Locating the Extrema of Fungible Regression Weights. + Psychometrika, 74(4), 589-602, . + Waller, N. G. (2016). Fungible Correlation Matrices: + A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for + Monte Carlo Research. Multivariate Behavioral Research, 51(4), 554-568. + Jones, J. A. & Waller, N. G. (2015). The normal-theory and asymptotic distribution-free (ADF) + covariance matrix of standardized regression coefficients: theoretical extensions + and finite sample behavior. Psychometrika, 80, 365-378, . + Waller, N. G. (2018). Direct Schmid-Leiman transformations and rank-deficient loadings matrices. Psychometrika, 83, 858-870. . + date_publication: '2024-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fungible + url_git: '' +funGp: + version: 1.0.0 + title: Gaussian Process Models for Scalar and Functional Inputs + maintainer: Jose Betancourt + description: |- + Construction and smart selection of Gaussian process models + for analysis of computer experiments + with emphasis on treatment of functional inputs that are regularly sampled. This package + offers: (i) flexible modeling of functional-input regression + problems through the fairly general Gaussian process model; (ii) + built-in dimension reduction for functional inputs; (iii) + heuristic optimization of the structural parameters of the model + (e.g., active inputs, kernel function, type of distance). + An in-depth tutorial in the use of funGp is provided in + Betancourt et al. (2024) and + Metamodeling background is provided in + Betancourt et al. (2020) . + The algorithm for structural parameter optimization is described + in . + date_publication: '2024-05-10' + bug_reports: https://github.com/djbetancourt-gh/funGp/issues + url: https://djbetancourt-gh.github.io/funGp/ + url_cran: https://CRAN.R-project.org/package=funGp + url_git: https://github.com/djbetancourt-gh/funGp +funique: + version: 0.0.1 + title: A Faster Unique Function + maintainer: Michael Wayne Kearney + description: |- + Similar to base's unique function, only optimized for working with + data frames, especially those that contain date-time columns. + date_publication: '2018-08-26' + bug_reports: https://github.com/mkearney/funique/issues + url: '' + url_cran: https://CRAN.R-project.org/package=funique + url_git: https://github.com/mkearney/funique +fUnitRoots: + version: '4040.81' + title: Rmetrics - Modelling Trends and Unit Roots + maintainer: Georgi N. Boshnakov + description: |- + Provides four addons for analyzing trends and + unit roots in financial time series: (i) functions for the density + and probability of the augmented Dickey-Fuller Test, (ii) functions + for the density and probability of MacKinnon's unit root test + statistics, (iii) reimplementations for the ADF and MacKinnon + Test, and (iv) an 'urca' Unit Root Test Interface for Pfaff's + unit root test suite. + date_publication: '2024-05-15' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://www.rmetrics.org + url_cran: https://CRAN.R-project.org/package=fUnitRoots + url_git: https://r-forge.r-project.org/scm/viewvc.php/pkg/fUnitRoots/?root=rmetrics(devel) +funkycells: + version: 1.1.1 + title: Functional Data Analysis for Multiplexed Cell Images + maintainer: Jeremy VanderDoes + description: |- + Compare variables of interest between (potentially large + numbers of) spatial interactions and meta-variables. Spatial variables + are summarized using K, or other, functions, and projected for use in + a modified random forest model. The model allows comparison of + functional and non-functional variables to each other and to noise, + giving statistical significance to the results. Included are + preparation, modeling, and interpreting tools along with example + datasets, as described in VanderDoes et al., (2023) + . + date_publication: '2023-08-09' + bug_reports: https://github.com/jrvanderdoes/funkycells/issues + url: https://jrvanderdoes.github.io/funkycells/ + url_cran: https://CRAN.R-project.org/package=funkycells + url_git: https://github.com/jrvanderdoes/funkycells +funkyheatmap: + version: 0.5.1 + title: Generating Funky Heatmaps for Data Frames + maintainer: Robrecht Cannoodt + description: |- + Allows generating heatmap-like visualisations for data + frames. Funky heatmaps can be fine-tuned by providing annotations of the + columns and rows, which allows assigning multiple palettes or geometries + or grouping rows and columns together in categories. + Saelens et al. (2019) . + date_publication: '2025-01-15' + bug_reports: https://github.com/funkyheatmap/funkyheatmap/issues + url: https://funkyheatmap.github.io/funkyheatmap/ + url_cran: https://CRAN.R-project.org/package=funkyheatmap + url_git: https://github.com/funkyheatmap/funkyheatmap +funLBM: + version: '2.3' + title: Model-Based Co-Clustering of Functional Data + maintainer: Charles Bouveyron + description: The funLBM algorithm allows to simultaneously cluster the rows and + the columns of a data matrix where each entry of the matrix is a function or a + time series. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funLBM + url_git: '' +funmediation: + version: 1.0.2 + title: Functional Mediation for a Distal Outcome + maintainer: John J. Dziak + description: Fits a functional mediation model with a scalar distal outcome. The + method is described in detail by Coffman, Dziak, Litson, Chakraborti, Piper & + Li (2021) . The model is similar to that of Lindquist (2012) + although allowing a binary outcome as an alternative + to a numerical outcome. The current version is a minor bug fix in the vignette. + The development of this package was part of a research project supported by National + Institutes of Health grants P50 DA039838 from the National Institute of Drug Abuse + and 1R01 CA229542-01 from the National Cancer Institute and the NIH Office of + Behavioral and Social Science Research. Content is solely the responsibility of + the authors and does not necessarily represent the official views of the funding + institutions mentioned above. This software is distributed in the hope that it + will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public + License for more details. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funmediation + url_git: '' +funModeling: + version: 1.9.5 + title: Exploratory Data Analysis and Data Preparation Tool-Box + maintainer: Pablo Casas + description: 'Around 10% of almost any predictive modeling project is spent in predictive + modeling, ''funModeling'' and the book Data Science Live Book () + are intended to cover remaining 90%: data preparation, profiling, selecting best + variables ''dataViz'', assessing model performance and other functions.' + date_publication: '2024-04-01' + bug_reports: https://github.com/pablo14/funModeling/issues + url: https://livebook.datascienceheroes.com + url_cran: https://CRAN.R-project.org/package=funModeling + url_git: '' +funneljoin: + version: 0.2.0 + title: Time-Based Joins to Analyze Sequences of Events + maintainer: Emily Robinson + description: |- + Time-based joins to analyze sequence of events, + both in memory and out of memory. after_join() joins two + tables of events, while funnel_start() and funnel_step() + join events in the same table. With the type argument, you + can switch between different funnel types, like first-first + and last-firstafter. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funneljoin + url_git: '' +FunnelPlotR: + version: 0.5.0 + title: Funnel Plots for Comparing Institutional Performance + maintainer: Chris Mainey + description: An implementation of methods presented by Spiegelhalter (2005) + Funnel plots for comparing institutional performance, for standardised ratios, + ratios of counts and proportions with additive overdispersion adjustment. + date_publication: '2024-04-12' + bug_reports: https://github.com/nhs-r-community/FunnelPlotR/issues + url: https://nhs-r-community.github.io/FunnelPlotR/ + url_cran: https://CRAN.R-project.org/package=FunnelPlotR + url_git: https://github.com/nhs-r-community/FunnelPlotR +funnelR: + version: 0.1.0 + title: Funnel Plots for Proportion Data + maintainer: Matthew Kumar + description: A set of simplified functions for creating funnel plots for proportion + data. This package supports user defined benchmarks, confidence limits and estimation + methods (i.e. exact or approximate) based on Spiegelhalter (2005) . + Additional routines for returning scored unit level data according to a set of + specifications is also implemented for convenience. Specifically, both a categorical + and a continuous score variable is returned to the sample data frame, which identifies + which observations are deemed extreme or in control. Typically, such variables + are useful as stratifications or covariates in further exploratory analyses. Lastly, + the plotting routine returns a base funnel plot ('ggplot2'), which can also be + tailored. + date_publication: '2018-03-14' + bug_reports: '' + url: https://matt-kumar.shinyapps.io/funnel/ + url_cran: https://CRAN.R-project.org/package=funnelR + url_git: '' +funpca: + version: '9.0' + title: Functional Principal Component Analysis + maintainer: Francisco Rosales + description: 'Functional principal component analysis under the Linear Mixed Models + representation of smoothing splines. The method utilizes the Demmler-Reinsch basis + and assumes error independence. For more details see: F. Rosales (2016) .' + date_publication: '2023-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funpca + url_git: '' +funprog: + version: 0.3.0 + title: Functional Programming + maintainer: Pierre-Yves Berrard + description: |2- + + High-order functions for data manipulation : sort or group data, given one + or more auxiliary functions. Functions are inspired by other pure + functional programming languages ('Haskell' mainly). The package also + provides built-in function operators for creating compact anonymous + functions, as well as the possibility to use the 'purrr' package syntax. + date_publication: '2020-11-07' + bug_reports: https://gitlab.com/py_b/funprog/-/issues + url: https://py_b.gitlab.io/funprog + url_cran: https://CRAN.R-project.org/package=funprog + url_git: https://gitlab.com/py_b/funprog +funr: + version: 0.3.2 + title: Simple Utility Providing Terminal Access to all R Functions + maintainer: Sahil Seth + description: |- + A small utility which wraps Rscript and provides access to all R + functions from the shell. + date_publication: '2016-04-19' + bug_reports: https://github.com/sahilseth/funr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=funr + url_git: https://github.com/sahilseth/funr +funrar: + version: 1.5.0 + title: Functional Rarity Indices Computation + maintainer: Matthias Grenié + description: |- + Computes functional rarity indices as proposed by Violle et al. + (2017) . Various indices can be computed + using both regional and local information. Functional Rarity combines both + the functional aspect of rarity as well as the extent aspect of rarity. + 'funrar' is presented in Grenié et al. (2017) . + date_publication: '2022-09-23' + bug_reports: https://github.com/Rekyt/funrar/issues + url: https://rekyt.github.io/funrar/ + url_cran: https://CRAN.R-project.org/package=funrar + url_git: https://github.com/Rekyt/funrar +funreg: + version: 1.2.2 + title: Functional Regression for Irregularly Timed Data + maintainer: John Dziak + description: |- + Performs functional regression, and some related + approaches, for intensive longitudinal data (see the book by Walls & Schafer, + 2006, Models for Intensive Longitudinal Data, Oxford) when such data is not + necessarily observed on an equally spaced grid of times. The + approach generally follows the ideas of Goldsmith, Bobb, Crainiceanu, + Caffo, and Reich (2011) and the approach taken in their sample code, but + with some modifications to make it more feasible to use with long rather + than wide, non-rectangular longitudinal datasets with unequal and + potentially random measurement times. It also allows easy plotting of the + correlation between the smoothed covariate and the outcome as a function of + time, which can add additional insights on how to interpret a functional + regression. Additionally, it also provides several permutation tests for + the significance of the functional predictor. The heuristic interpretation + of ``time'' is used to describe the index of the functional predictor, but + the same methods can equally be used for another unidimensional continuous + index, such as space along a north-south axis. Note that most of the functionality + of this package has been superseded by added features after 2016 in the 'pfr' function by + Jonathan Gellar, Mathew W. McLean, Jeff Goldsmith, and Fabian Scheipl, in the + 'refund' package built by Jeff Goldsmith and co-authors and maintained by Julia Wrobel. + The development of the funreg package in 2015 and 2016 was part of a research + project supported by Award R03 CA171809-01 from the National Cancer Institute and Award P50 + DA010075 from the National Institute on Drug Abuse. The content is solely the responsibility of the + authors and does not necessarily represent the official views of the + National Institute on Drug Abuse, the National Cancer Institute, or the + National Institutes of Health. + date_publication: '2021-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funreg + url_git: '' +funspace: + version: 0.2.2 + title: Creating and Representing Functional Trait Spaces + maintainer: Carlos P. Carmona + description: |- + Estimation of functional spaces based on traits of organisms. + The package includes functions to impute missing trait values (with or + without considering phylogenetic information), and to create, + represent and analyse two dimensional functional spaces based on + principal components analysis, other ordination methods, or raw + traits. It also allows for mapping a third variable onto the + functional space. See 'Carmona et al. (2021)' + , 'Puglielli et al. (2021)' + , 'Carmona et al. (2021)' + , 'Carmona et al. (2019)' + for more information. + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funspace + url_git: '' +funspotr: + version: 0.0.4 + title: Spot R Functions & Packages + maintainer: Bryan Shalloway + description: |- + Helpers for parsing out the R functions + and packages used in R scripts and notebooks. + date_publication: '2023-11-22' + bug_reports: https://github.com/brshallo/funspotr/issues + url: https://brshallo.github.io/funspotr/ + url_cran: https://CRAN.R-project.org/package=funspotr + url_git: '' +funStatTest: + version: 1.0.3 + title: Statistical Testing for Functional Data + maintainer: Ghislain Durif + description: |- + Implementation of two sample comparison procedures based on + median-based statistical tests for functional data, introduced in + Smida et al (2022) . Other + competitive state-of-the-art approaches proposed by Chakraborty and + Chaudhuri (2015) , Horvath et al (2013) + or Cuevas et al (2004) + are also included in the package, as + well as procedures to run test result comparisons and power analysis + using simulations. + date_publication: '2024-05-23' + bug_reports: '' + url: https://plmlab.math.cnrs.fr/gdurif/funStatTest/ + url_cran: https://CRAN.R-project.org/package=funStatTest + url_git: '' +FUNTA: + version: 0.1.0 + title: Functional Tangential Angle Pseudo-Depth + maintainer: Andre Rehage + description: 'Computes the functional tangential angle pseudo-depth and its robustified + version from the paper by Kuhnt and Rehage (2016). See Kuhnt, S.; Rehage, A. (2016): + An angle-based multivariate functional pseudo-depth for shape outlier detection, + JMVA 146, 325-340, for details.' + date_publication: '2016-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FUNTA + url_git: '' +funtimes: + version: '9.1' + title: Functions for Time Series Analysis + maintainer: Vyacheslav Lyubchich + description: Nonparametric estimators and tests for time series analysis. The functions + use bootstrap techniques and robust nonparametric difference-based estimators + to test for the presence of possibly non-monotonic trends and for synchronicity + of trends in multiple time series. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=funtimes + url_git: '' +FunWithNumbers: + version: '1.2' + title: Fun with Fractions and Number Sequences + maintainer: Carl Witthoft + description: A collection of toys to do things like generate Collatz and other interesting + sequences, calculate a fraction which is a close approximation to some value (e.g., + 22/7 or 355/113 for pi), and so on. + date_publication: '2024-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FunWithNumbers + url_git: '' +furniture: + version: 1.9.14 + title: Furniture for Quantitative Scientists + maintainer: Tyson S. Barrett + description: |- + Contains four main functions (i.e., four pieces of furniture): + table1() which produces a well-formatted table of descriptive statistics common as Table 1 + in research articles, tableC() which produces a well-formatted table of correlations, + tableF() which provides frequency counts, and washer() which + is helpful in cleaning up the data. These furniture-themed functions are designed + to simplify common tasks in quantitative analysis. Other data summary and cleaning tools + are also available. + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=furniture + url_git: '' +furrr: + version: 0.3.1 + title: Apply Mapping Functions in Parallel using Futures + maintainer: Davis Vaughan + description: |- + Implementations of the family of map() functions from 'purrr' + that can be resolved using any 'future'-supported backend, e.g. + parallel on the local machine or distributed on a compute cluster. + date_publication: '2022-08-15' + bug_reports: https://github.com/DavisVaughan/furrr/issues + url: https://furrr.futureverse.org/ + url_cran: https://CRAN.R-project.org/package=furrr + url_git: https://github.com/DavisVaughan/furrr +fusedMGM: + version: 0.1.2 + title: Implementation of Fused MGM to Infer 2-Class Networks + maintainer: Jaehyun Park + description: Implementation of fused Markov graphical model (FMGM; Park and Won, + 2022). The functions include building mixed graphical model (MGM) objects from + data, inference of networks using FMGM, stable edge-specific penalty selection + (StEPS) for the determination of penalization parameters, and the visualization. + For details, please refer to Park and Won (2022) . + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fusedMGM + url_git: '' +fuseMLR: + version: 0.0.1 + title: Fusing Machine Learning in R + maintainer: Cesaire J. K. Fouodo + description: |- + Recent technological advances have enable the simultaneous collection + of multi-omics data i.e., different types or modalities of molecular data, + presenting challenges for integrative prediction modeling due to the heterogeneous, + high-dimensional nature and possible missing modalities of some individuals. + We introduce this package for late integrative prediction modeling, enabling + modality-specific variable selection and prediction modeling, followed by the + aggregation of the modality-specific predictions to train a final meta-model. + This package facilitates conducting late integration predictive modeling in a + systematic, structured, and reproducible way. + date_publication: '2024-12-17' + bug_reports: https://github.com/imbs-hl/fuseMLR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fuseMLR + url_git: '' +fusen: + version: 0.7.1 + title: Build a Package from Rmarkdown Files + maintainer: Vincent Guyader + description: |- + Use Rmarkdown First method to build your package. Start your + package with documentation, functions, examples and tests in the same + unique file. Everything can be set from the Rmarkdown template file + provided in your project, then inflated as a package. Inflating the + template copies the relevant chunks and sections in the appropriate + files required for package development. + date_publication: '2025-01-26' + bug_reports: '' + url: https://thinkr-open.github.io/fusen/ + url_cran: https://CRAN.R-project.org/package=fusen + url_git: https://github.com/Thinkr-open/fusen +fuser: + version: 1.0.1 + title: Fused Lasso for High-Dimensional Regression over Groups + maintainer: Frank Dondelinger + description: |- + Enables high-dimensional penalized regression across heterogeneous + subgroups. Fusion penalties are used to share information about the linear + parameters across subgroups. The underlying model is described + in detail in Dondelinger and Mukherjee (2017) . + date_publication: '2018-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fuser + url_git: '' +fusionchartsR: + version: 1.1.0 + title: Embedding FusionCharts in R + maintainer: Alex Yahiaoui Martinez + description: FusionCharts provides awesome and minimalist functions to make beautiful + interactive charts . + date_publication: '2024-12-19' + bug_reports: https://github.com/alexym1/fusionchartsR/issues + url: https://alexym1.github.io/fusionchartsR/ + url_cran: https://CRAN.R-project.org/package=fusionchartsR + url_git: https://github.com/alexym1/fusionchartsR +fusionclust: + version: 1.0.0 + title: Clustering and Feature Screening using L1 Fusion Penalty + maintainer: Trambak Banerjee + description: |- + Provides the Big Merge Tracker and COSCI algorithms for convex clustering and + feature screening using L1 fusion penalty. See Radchenko, P. and Mukherjee, G. (2017) and + T.Banerjee et al. (2017) for more details. + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fusionclust + url_git: https://github.com/trambakbanerjee/fusionclust +FusionLearn: + version: 0.2.1 + title: Fusion Learning + maintainer: Yuan Zhong + description: The fusion learning method uses a model selection algorithm to learn + from multiple data sets across different experimental platforms through group + penalization. The responses of interest may include a mix of discrete and continuous + variables. The responses may share the same set of predictors, however, the models + and parameters differ across different platforms. Integrating information from + different data sets can enhance the power of model selection. Package is based + on Xin Gao, Raymond J. Carroll (2017) . + date_publication: '2022-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FusionLearn + url_git: '' +futile.logger: + version: 1.4.3 + title: A Logging Utility for R + maintainer: Brian Lee Yung Rowe + description: |- + Provides a simple yet powerful logging utility. Based loosely on + log4j, futile.logger takes advantage of R idioms to make logging a + convenient and easy to use replacement for cat and print statements. + date_publication: '2016-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=futile.logger + url_git: '' +futile.options: + version: 1.0.1 + title: Futile Options Management + maintainer: Brian Lee Yung Rowe + description: A scoped options management framework. Used in other packages. + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=futile.options + url_git: '' +futility: + version: '0.4' + title: |- + Interim Analysis of Operational Futility in Randomized Trials + with Time-to-Event Endpoints and Fixed Follow-Up + maintainer: Michal Juraska + description: Randomized clinical trials commonly follow participants for a time-to-event + efficacy endpoint for a fixed period of time. Consequently, at the time when the + last enrolled participant completes their follow-up, the number of observed endpoints + is a random variable. Assuming data collected through an interim timepoint, simulation-based + estimation and inferential procedures in the standard right-censored failure time + analysis framework are conducted for the distribution of the number of endpoints--in + total as well as by treatment arm--at the end of the follow-up period. The future + (i.e., yet unobserved) enrollment, endpoint, and dropout times are generated according + to mechanisms specified in the simTrial() function in the 'seqDesign' package. + A Bayesian model for the endpoint rate, offering the option to specify a robust + mixture prior distribution, is used for generating future data (see the vignette + for details). Inference can be restricted to participants who received treatment + according to the protocol and are observed to be at risk for the endpoint at a + specified timepoint. Plotting functions are provided for graphical display of + results. + date_publication: '2019-04-11' + bug_reports: https://github.com/mjuraska/futility/issues + url: '' + url_cran: https://CRAN.R-project.org/package=futility + url_git: https://github.com/mjuraska/futility +future: + version: 1.34.0 + title: Unified Parallel and Distributed Processing in R for Everyone + maintainer: Henrik Bengtsson + description: |- + The purpose of this package is to provide a lightweight and + unified Future API for sequential and parallel processing of R + expression via futures. The simplest way to evaluate an expression + in parallel is to use `x %<-% { expression }` with `plan(multisession)`. + This package implements sequential, multicore, multisession, and + cluster futures. With these, R expressions can be evaluated on the + local machine, in parallel a set of local machines, or distributed + on a mix of local and remote machines. + Extensions to this package implement additional backends for + processing futures via compute cluster schedulers, etc. + Because of its unified API, there is no need to modify any code in order + switch from sequential on the local machine to, say, distributed + processing on a remote compute cluster. + Another strength of this package is that global variables and functions + are automatically identified and exported as needed, making it + straightforward to tweak existing code to make use of futures. + date_publication: '2024-07-29' + bug_reports: https://github.com/HenrikBengtsson/future/issues + url: https://future.futureverse.org + url_cran: https://CRAN.R-project.org/package=future + url_git: https://github.com/HenrikBengtsson/future +future.apply: + version: 1.11.3 + title: Apply Function to Elements in Parallel using Futures + maintainer: Henrik Bengtsson + description: Implementations of apply(), by(), eapply(), lapply(), Map(), .mapply(), + mapply(), replicate(), sapply(), tapply(), and vapply() that can be resolved using + any future-supported backend, e.g. parallel on the local machine or distributed + on a compute cluster. These future_*apply() functions come with the same pros + and cons as the corresponding base-R *apply() functions but with the additional + feature of being able to be processed via the future framework . + date_publication: '2024-10-27' + bug_reports: https://github.com/futureverse/future.apply/issues + url: https://future.apply.futureverse.org + url_cran: https://CRAN.R-project.org/package=future.apply + url_git: https://github.com/futureverse/future.apply +future.batchtools: + version: 0.12.1 + title: |- + A Future API for Parallel and Distributed Processing using + 'batchtools' + maintainer: Henrik Bengtsson + description: |- + Implementation of the Future API on top of the 'batchtools' package. + This allows you to process futures, as defined by the 'future' package, + in parallel out of the box, not only on your local machine or ad-hoc + cluster of machines, but also via high-performance compute ('HPC') job + schedulers such as 'LSF', 'OpenLava', 'Slurm', 'SGE', and 'TORQUE' / 'PBS', + e.g. 'y <- future.apply::future_lapply(files, FUN = process)'. + date_publication: '2023-12-20' + bug_reports: https://github.com/HenrikBengtsson/future.batchtools/issues + url: https://future.batchtools.futureverse.org + url_cran: https://CRAN.R-project.org/package=future.batchtools + url_git: https://github.com/HenrikBengtsson/future.batchtools +future.callr: + version: 0.8.2 + title: A Future API for Parallel Processing using 'callr' + maintainer: Henrik Bengtsson + description: Implementation of the Future API on top of the 'callr' package. This + allows you to process futures, as defined by the 'future' package, in parallel + out of the box, on your local (Linux, macOS, Windows, ...) machine. Contrary + to backends relying on the 'parallel' package (e.g. 'future::multisession') and + socket connections, the 'callr' backend provided here can run more than 125 parallel + R processes. + date_publication: '2023-08-09' + bug_reports: https://github.com/HenrikBengtsson/future.callr/issues + url: https://future.callr.futureverse.org + url_cran: https://CRAN.R-project.org/package=future.callr + url_git: https://github.com/HenrikBengtsson/future.callr +future.mirai: + version: 0.2.2 + title: A 'Future' API for Parallel Processing using 'mirai' + maintainer: Henrik Bengtsson + description: Implementation of the 'Future' API on top + of the 'mirai' package . This allows you to process + futures, as defined by the 'future' package, in parallel out of the box, on your + local machine or across remote machines. Contrary to back-ends relying on the + 'parallel' package (e.g. 'multisession') and socket connections, 'mirai_cluster' + and 'mirai_multisession', provided here, can run more than 125 parallel R processes. + date_publication: '2024-07-03' + bug_reports: https://github.com/futureverse/future.mirai/issues + url: https://future.mirai.futureverse.org + url_cran: https://CRAN.R-project.org/package=future.mirai + url_git: https://github.com/futureverse/future.mirai +future.tests: + version: 0.7.0 + title: Test Suite for 'Future API' Backends + maintainer: Henrik Bengtsson + description: Backends implementing the 'Future' API, as defined by the 'future' + package, should use the tests provided by this package to validate that they meet + the minimal requirements of the 'Future' API. The tests can be performed easily + from within R or from outside of R from the command line making it straightforward + to include them in package tests and in Continuous Integration (CI) pipelines. + date_publication: '2023-05-22' + bug_reports: https://github.com/HenrikBengtsson/future.tests/issues + url: https://future.tests.futureverse.org + url_cran: https://CRAN.R-project.org/package=future.tests + url_git: https://github.com/HenrikBengtsson/future.tests +futureverse: + version: 0.1.0 + title: Easily Install and Load the 'Futureverse' + maintainer: Henrik Bengtsson + description: The 'Futureverse' is a set of packages for parallel and distributed + process with the 'future' package at its core, cf. Bengtsson (2021) . + This package is designed to make it easy to install and load multiple 'Futureverse' + packages in a single step. This package is intended for end-users, interactive + use, and R scripts. Packages must not list it as a dependency - instead, explicitly + declare each 'Futureverse' package as a dependency as needed. + date_publication: '2024-06-07' + bug_reports: '' + url: https://www.futureverse.org + url_cran: https://CRAN.R-project.org/package=futureverse + url_git: '' +fuzzr: + version: 0.2.2 + title: Fuzz-Test R Functions + maintainer: Matthew Lincoln + description: |- + Test function arguments with a wide array of inputs, and produce + reports summarizing messages, warnings, errors, and returned values. + date_publication: '2018-05-08' + bug_reports: https://github.com/mdlincoln/fuzzr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fuzzr + url_git: https://github.com/mdlincoln/fuzzr +Fuzzy.p.value: + version: '1.1' + title: Computing Fuzzy p-Value + maintainer: Abbas Parchami + description: 'The main goal of this package is drawing the membership function of + the fuzzy p-value which is defined as a fuzzy set on the unit interval for three + following problems: (1) testing crisp hypotheses based on fuzzy data, (2) testing + fuzzy hypotheses based on crisp data, and (3) testing fuzzy hypotheses based on + fuzzy data. In all cases, the fuzziness of data or/and the fuzziness of the boundary + of null fuzzy hypothesis transported via the p-value function and causes to produce + the fuzzy p-value. If the p-value is fuzzy, it is more appropriate to consider + a fuzzy significance level for the problem. Therefore, the comparison of the fuzzy + p-value and the fuzzy significance level is evaluated by a fuzzy ranking method + in this package.' + date_publication: '2017-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Fuzzy.p.value + url_git: '' +FuzzyAHP: + version: 0.9.5 + title: (Fuzzy) AHP Calculation + maintainer: Jan Caha + description: |- + Calculation of AHP (Analytic Hierarchy Process - + ) + with classic and fuzzy weights based on Saaty's pairwise + comparison method for determination of weights. + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyAHP + url_git: http://github.com/JanCaha/FuzzyAHP/ +FuzzyClass: + version: 0.1.6 + title: Fuzzy and Non-Fuzzy Classifiers + maintainer: Jodavid Ferreira + description: It provides classifiers which can be used for discrete variables and + for continuous variables based on the Naive Bayes and Fuzzy Naive Bayes hypothesis. + Those methods were developed by researchers belong to the 'Laboratory of Technologies + for Virtual Teaching and Statistics (LabTEVE)' and 'Laboratory of Applied Statistics + to Image Processing and Geoprocessing (LEAPIG)' at 'Federal University of Paraiba, + Brazil'. They considered some statistical distributions and their papers were + published in the scientific literature, as for instance, the Gaussian classifier + using fuzzy parameters, proposed by 'Moraes, Ferreira and Machado' (2021) . + date_publication: '2024-02-14' + bug_reports: https://github.com/leapigufpb/FuzzyClass/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyClass + url_git: https://github.com/leapigufpb/FuzzyClass +FuzzyDBScan: + version: 0.0.3 + title: Run and Predict a Fuzzy DBScan + maintainer: Henri Funk + description: |- + An interface for training Fuzzy DBScan with both Fuzzy Core and Fuzzy Border. + Therefore, the package provides a method to initialize and run the algorithm and a + function to predict new data w.t.h. of 'R6'. + The package is build upon the paper "Fuzzy Extensions of the DBScan algorithm" + from Ienco and Bordogna (2018) . + A predict function assigns new data according to the same criteria as the algorithm itself. + However, the prediction function freezes the algorithm to preserve the trained + cluster structure and treats each new prediction object individually. + date_publication: '2023-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyDBScan + url_git: '' +fuzzyforest: + version: 1.0.8 + title: Fuzzy Forests + maintainer: Daniel Conn + description: |- + Fuzzy forests, a new algorithm based on random forests, + is designed to reduce the bias seen in random forest feature selection + caused by the presence of correlated features. Fuzzy forests uses + recursive feature elimination random forests to select + features from separate blocks of correlated features where the + correlation within each block of features is high + and the correlation between blocks of features is low. + One final random forest is fit using the surviving features. + This package fits random forests using the 'randomForest' package and + allows for easy use of 'WGCNA' to split features into distinct blocks. + See D. Conn, Ngun, T., C. Ramirez, and G. Li (2019) + for further details. + date_publication: '2020-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fuzzyforest + url_git: '' +FuzzyImputationTest: + version: 0.4.0 + title: Imputation Procedures and Quality Tests for Fuzzy Data + maintainer: Maciej Romaniuk + description: Special procedures for the imputation of missing fuzzy numbers are + still underdeveloped. The goal of the package is to provide the new d-imputation + method (DIMP for short, Romaniuk, M. and Grzegorzewski, P. (2023) "Fuzzy Data + Imputation with DIMP and FGAIN" RB/23/2023) and covert some classical ones applied + in R packages ('missForest','miceRanger','knn') for use with fuzzy datasets. Additionally, + specially tailored benchmarking tests are provided to check and compare these + imputation procedures with fuzzy datasets. + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyImputationTest + url_git: '' +fuzzyjoin: + version: 0.1.6 + title: Join Tables Together on Inexact Matching + maintainer: David Robinson + description: |- + Join tables together based not on whether columns + match exactly, but whether they are similar by some comparison. + Implementations include string distance and regular expression + matching. + date_publication: '2020-05-15' + bug_reports: https://github.com/dgrtwo/fuzzyjoin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fuzzyjoin + url_git: https://github.com/dgrtwo/fuzzyjoin +FuzzyLP: + version: 0.1-7 + title: Fuzzy Linear Programming + maintainer: Pablo J. Villacorta + description: |- + Provides methods to solve Fuzzy Linear Programming Problems with + fuzzy constraints (following different approaches proposed by + Verdegay, Zimmermann, Werners and Tanaka), fuzzy costs, and fuzzy + technological matrix. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyLP + url_git: https://github.com/olbapjose/FuzzyLP +FuzzyM: + version: 0.1.0 + title: Fuzzy Cognitive Maps Operations + maintainer: Alina Petukhova + description: Contains functions for operations with fuzzy cognitive maps using t-norm + and s-norm operators. T-norms and S-norms are described by Dov M. Gabbay and George + Metcalfe (2007) . System indicators are described + by Cox, Earl D. (1995) . Executable examples are provided in + the "inst/examples" folder. + date_publication: '2022-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyM + url_git: '' +FuzzyNumbers: + version: 0.4-7 + title: Tools to Deal with Fuzzy Numbers + maintainer: Marek Gagolewski + description: |- + S4 classes and methods + to deal with fuzzy numbers. They allow for computing any arithmetic + operations (e.g., by using the Zadeh extension principle), + performing approximation of arbitrary fuzzy numbers by trapezoidal + and piecewise linear ones, preparing plots for publications, computing + possibility and necessity values for comparisons, etc. + date_publication: '2021-11-15' + bug_reports: https://github.com/gagolews/FuzzyNumbers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyNumbers + url_git: https://github.com/gagolews/FuzzyNumbers/ +FuzzyNumbers.Ext.2: + version: '3.2' + title: Apply Two Fuzzy Numbers on a Monotone Function + maintainer: Abbas Parchami + description: One can easily draw the membership function of f(x,y) by package 'FuzzyNumbers.Ext.2' + in which f(.,.) is supposed monotone and x and y are two fuzzy numbers. This work + is possible using function f2apply() which is an extension of function fapply() + from Package 'FuzzyNumbers' for two-variable monotone functions. Moreover, this + package has the ability of computing the core, support and alpha-cuts of the fuzzy-valued + final result. + date_publication: '2017-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyNumbers.Ext.2 + url_git: '' +FuzzyPovertyR: + version: 3.0.2 + title: Estimation of Fuzzy Poverty Measures + maintainer: Federico Crescenzi + description: Estimates fuzzy measures of poverty and deprivation. It also estimates + the sampling variance of these measures using bootstrap or jackknife repeated + replications. + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyPovertyR + url_git: '' +FuzzyQ: + version: 0.1.0 + title: Fuzzy Quantification of Common and Rare Species + maintainer: Juan A. Balbuena + description: |- + Fuzzy clustering of species in an ecological community as common or + rare based on their abundance and occupancy. It also includes functions to + compute confidence intervals of classification metrics and plot results. See + Balbuena et al. (2020, ). + date_publication: '2021-01-05' + bug_reports: '' + url: https://ligophorus.github.io/FuzzyQ/ + url_cran: https://CRAN.R-project.org/package=FuzzyQ + url_git: '' +FuzzyR: + version: 2.3.2 + title: Fuzzy Logic Toolkit for R + maintainer: Chao Chen + description: |- + Design and simulate fuzzy logic systems using Type-1 and Interval Type-2 Fuzzy Logic. + This toolkit includes with graphical user interface (GUI) and an adaptive neuro- + fuzzy inference system (ANFIS). This toolkit is a continuation from the previous + package ('FuzzyToolkitUoN'). Produced by the Intelligent Modelling & Analysis Group (IMA) + and Lab for UnCertainty In Data and decision making (LUCID), University of Nottingham. + A big thank you to the many people who have contributed to the development/evaluation of the toolbox. + Please cite the toolbox and the corresponding paper when using it. + More related papers can be found in the NEWS. + date_publication: '2021-05-19' + bug_reports: '' + url: https://www.lucidresearch.org/ + url_cran: https://CRAN.R-project.org/package=FuzzyR + url_git: '' +fuzzyRankTests: + version: '0.4' + title: Fuzzy Rank Tests and Confidence Intervals + maintainer: Charles J. Geyer + description: |- + Does fuzzy tests and confidence intervals (following Geyer + and Meeden, Statistical Science, 2005, ) + for sign test and Wilcoxon signed rank and rank sum tests. + date_publication: '2021-08-14' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/fuzz/ + url_cran: https://CRAN.R-project.org/package=fuzzyRankTests + url_git: '' +fuzzyreg: + version: 0.6.2 + title: Fuzzy Linear Regression + maintainer: Natalia Martinkova + description: |- + Estimators for fuzzy linear regression. The functions estimate parameters of + fuzzy linear regression models with crisp or fuzzy independent variables (triangular + fuzzy numbers are supported). Implements multiple methods for parameter estimation and + algebraic operations with triangular fuzzy numbers. Includes functions for + summarising, printing and plotting the model fit. Calculates predictions from the + model and total error of fit. Individual methods are described in + Diamond (1988) , + Hung & Yang (2006) , + Lee & Tanaka (1999) , + Nasrabadi, Nasrabadi & Nasrabady (2005) , + Skrabanek, Marek & Pozdilkova (2021) , + Tanaka, Hayashi & Watada (1989) , + Zeng, Feng & Li (2017) . + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fuzzyreg + url_git: '' +FuzzyResampling: + version: 0.6.4 + title: Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers + maintainer: Maciej Romaniuk + description: |- + The classical (i.e. Efron's, see Efron and Tibshirani (1994, ISBN:978-0412042317) "An Introduction to the Bootstrap") bootstrap is widely used for both the real (i.e. "crisp") and fuzzy data. + The main aim of the algorithms implemented in this package is to overcome a problem with repetition of a few distinct values and to create fuzzy numbers, which are "similar" (but not the same) to values from the initial sample. + To do this, different characteristics of triangular/trapezoidal numbers are kept (like the value, the ambiguity, etc., see Grzegorzewski et al. , Grzegorzewski et al. (2020) , Grzegorzewski et al. (2020) , Grzegorzewski and Romaniuk (2022) , Romaniuk and Hryniewicz (2019) ). + Some additional procedures related to these resampling methods are also provided, + like calculation of the Bertoluzza et al.'s distance (aka the mid/spread distance, see Bertoluzza et al. (1995) "On a new class of distances between fuzzy numbers") + and estimation of the p-value of the one- and two- sample bootstrapped test for the mean (see Lubiano et al. (2016, )). + Additionally, there are procedures which randomly generate trapezoidal fuzzy numbers using some well-known statistical distributions. + date_publication: '2024-10-04' + bug_reports: https://github.com/mroman-ibs/FuzzyResampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyResampling + url_git: https://github.com/mroman-ibs/FuzzyResampling +fuzzySim: + version: '4.29' + title: Fuzzy Similarity in Species Distributions + maintainer: A. Marcia Barbosa + description: Functions to compute fuzzy versions of species occurrence patterns + based on presence-absence data (including inverse distance interpolation, trend + surface analysis, and prevalence-independent favourability obtained from probability + of presence), as well as pair-wise fuzzy similarity (based on fuzzy logic versions + of commonly used similarity indices) among those occurrence patterns. Includes + also functions for model consensus and comparison (overlap and fuzzy similarity, + fuzzy loss, fuzzy gain), and for data preparation, such as obtaining unique abbreviations + of species names, defining the background region, cleaning and gridding (thinning) + point occurrence data onto raster maps, selecting among (pseudo)absences to address + survey bias, converting species lists (long format) to presence-absence tables + (wide format), transposing part of a data frame, selecting relevant variables + for models, assessing the false discovery rate, or analysing and dealing with + multicollinearity. Initially described in Barbosa (2015) . + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fuzzySim + url_git: http://fuzzysim.r-forge.r-project.org/ +FuzzySimRes: + version: 0.4.3 + title: Simulation and Resampling Methods for Epistemic Fuzzy Data + maintainer: Maciej Romaniuk + description: |- + Random simulations of fuzzy numbers are still a challenging problem. The aim of this package is to provide the respective + procedures to simulate fuzzy random variables, especially in the case of the piecewise linear fuzzy numbers (PLFNs, + see Coroianua et al. (2013) for the further details). + Additionally, the special resampling algorithms known as the epistemic bootstrap are provided (see Grzegorzewski and Romaniuk + (2022) , Grzegorzewski and Romaniuk (2022) ) + together with the functions to apply statistical tests and estimate various characteristics based on the epistemic bootstrap. + The package also includes a real-life data set of epistemic fuzzy triangular numbers. + The fuzzy numbers used in this package are consistent with the 'FuzzyNumbers' package. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzySimRes + url_git: '' +FuzzyStatProb: + version: 2.0.4 + title: |- + Fuzzy Stationary Probabilities from a Sequence of Observations + of an Unknown Markov Chain + maintainer: Pablo J. Villacorta + description: |- + An implementation of a method for computing fuzzy numbers representing stationary probabilities of an unknown Markov chain, + from which a sequence of observations along time has been obtained. The algorithm is based on the proposal presented by James Buckley + in his book on Fuzzy probabilities (Springer, 2005), chapter 6. Package 'FuzzyNumbers' is used to represent the output probabilities. + date_publication: '2019-02-09' + bug_reports: '' + url: http://decsai.ugr.es/~pjvi/r-packages.html + url_cran: https://CRAN.R-project.org/package=FuzzyStatProb + url_git: '' +FuzzyStatTra: + version: '1.0' + title: Statistical Methods for Trapezoidal Fuzzy Numbers + maintainer: Asun Lubiano + description: |- + The aim of the package is to provide some basic functions + for doing statistics with trapezoidal fuzzy numbers. In particular, + the package contains several functions for simulating trapezoidal + fuzzy numbers, as well as for calculating some central tendency + measures (mean and two types of median), some scale measures + (variance, ADD, MDD, Sn, Qn, Tn and some M-estimators) and + one diversity index and one inequality index. Moreover, + functions for calculating the 1-norm distance, the mid/spr + distance and the (phi,theta)-wabl/ldev/rdev distance between + fuzzy numbers are included, and a function to calculate the + value phi-wabl given a sample of trapezoidal fuzzy numbers. + date_publication: '2017-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzyStatTra + url_git: '' +FuzzySTs: + version: '0.3' + title: Fuzzy Statistical Tools + maintainer: Redina Berkachy + description: 'The main goal of this package is to present various fuzzy statistical + tools. It intends to provide an implementation of the theoretical and empirical + approaches presented in the book entitled "The signed distance measure in fuzzy + statistical analysis. Some theoretical, empirical and programming advances" . For the theoretical approaches, see Berkachy R. and + Donze L. (2019) . For the empirical approaches, + see Berkachy R. and Donze L. (2016) ). Important (non-exhaustive) + implementation highlights of this package are as follows: (1) a numerical procedure + to estimate the fuzzy difference and the fuzzy square. (2) two numerical methods + of fuzzification. (3) a function performing different possibilities of distances, + including the signed distance and the generalized signed distance for instance + with all its properties. (4) numerical estimations of fuzzy statistical measures + such as the variance, the moment, etc. (5) two methods of estimation of the bootstrap + distribution of the likelihood ratio in the fuzzy context. (6) an estimation of + a fuzzy confidence interval by the likelihood ratio method. (7) testing fuzzy + hypotheses and/or fuzzy data by fuzzy confidence intervals in the Kwakernaak - + Kruse and Meyer sense. (8) a general method to estimate the fuzzy p-value with + fuzzy hypotheses and/or fuzzy data. (9) a method of estimation of global and individual + evaluations of linguistic questionnaires. (10) numerical estimations of multi-ways + analysis of variance models in the fuzzy context. The unbalance in the considered + designs are also foreseen.' + date_publication: '2024-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FuzzySTs + url_git: '' +fuzzywuzzyR: + version: 1.0.5 + title: Fuzzy String Matching + maintainer: Lampros Mouselimis + description: Fuzzy string matching implementation of the 'fuzzywuzzy' + 'python' package. It uses the Levenshtein Distance + to calculate the differences between sequences. + date_publication: '2021-09-11' + bug_reports: https://github.com/mlampros/fuzzywuzzyR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=fuzzywuzzyR + url_git: https://github.com/mlampros/fuzzywuzzyR +FVDDPpkg: + version: 0.1.2 + title: Implement Fleming-Viot-Dependent Dirichlet Processes + maintainer: Stefano Damato + description: |- + A Bayesian Nonparametric model for the study of time-evolving frequencies, which has become renowned in the study of population genetics. + The model consists of a Hidden Markov Model (HMM) in which the latent signal is a distribution-valued stochastic process that takes the form of a finite mixture of Dirichlet Processes, indexed by vectors that count how many times each value is observed in the population. + The package implements methodologies presented in Ascolani, Lijoi and Ruggiero (2021) and Ascolani, Lijoi and Ruggiero (2023) that make it possible to study the process at the time of data collection or to predict its evolution in future or in the past. + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FVDDPpkg + url_git: '' +fwb: + version: 0.2.0 + title: Fractional Weighted Bootstrap + maintainer: Noah Greifer + description: |- + An implementation of the fractional weighted bootstrap to be used as a drop-in for functions in + the 'boot' package. The fractional weighted bootstrap (also known as the Bayesian bootstrap) involves drawing + weights randomly that are applied to the data rather than resampling units from the data. See Xu et al. (2020) + for details. + date_publication: '2023-12-07' + bug_reports: https://github.com/ngreifer/fwb/issues + url: https://ngreifer.github.io/fwb/ + url_cran: https://CRAN.R-project.org/package=fwb + url_git: https://github.com/ngreifer/fwb +FWDselect: + version: 2.1.0 + title: Selecting Variables in Regression Models + maintainer: Marta Sestelo + description: |- + A simple method + to select the best model or best subset of variables using + different types of data (binary, Gaussian or Poisson) and + applying it in different contexts (parametric or non-parametric). + date_publication: '2015-12-19' + bug_reports: http://github.com/sestelo/fwdselect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=FWDselect + url_git: '' +fwlplot: + version: 0.3.0 + title: Scatter Plot After Residualizing Using 'fixest' Package + maintainer: Kyle Butts + description: Creates a scatter plot after residualizing using a set of covariates. + The residuals are calculated using the 'fixest' package which allows very fast + estimation that scales. Details of the (Yule-)Frisch-Waugh-Lovell theorem is given + in Basu (2023) . + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fwlplot + url_git: '' +FWRGB: + version: 0.1.0 + title: Fresh Weight Determination from Visual Image of the Plant + maintainer: Tanuj Misra + description: Fresh biomass determination is the key to evaluating crop genotypes' + response to diverse input and stress conditions and forms the basis for calculating + net primary production. However, as conventional phenotyping approaches for measuring + fresh biomass is time-consuming, laborious and destructive, image-based phenotyping + methods are being widely used now. In the image-based approach, the fresh weight + of the above-ground part of the plant depends on the projected area. For determining + the projected area, the visual image of the plant is converted into the grayscale + image by simply averaging the Red(R), Green (G) and Blue (B) pixel values. Grayscale + image is then converted into a binary image using Otsu’s thresholding method Otsu, + N. (1979) to separate plant area from the background + (image segmentation). The segmentation process was accomplished by selecting the + pixels with values over the threshold value belonging to the plant region and + other pixels to the background region. The resulting binary image consists of + white and black pixels representing the plant and background regions. Finally, + the number of pixels inside the plant region was counted and converted to square + centimetres (cm2) using the reference object (any object whose actual area is + known previously) to get the projected area. After that, the projected area is + used as input to the machine learning model (Linear Model, Artificial Neural Network, + and Support Vector Regression) to determine the plant's fresh weight. + date_publication: '2021-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=FWRGB + url_git: '' +fwsim: + version: 0.3.4 + title: Fisher-Wright Population Simulation + maintainer: Mikkel Meyer Andersen + description: Simulates a population under the Fisher-Wright model (fixed or stochastic + population size) with a one-step neutral mutation process (stepwise mutation model, + logistic mutation model and exponential mutation model supported). The stochastic + population sizes are random Poisson distributed and different kinds of population + growth are supported. For the stepwise mutation model, it is possible to specify + locus and direction specific mutation rate (in terms of upwards and downwards + mutation rate). Intermediate generations can be saved in order to study e.g. drift. + date_publication: '2018-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fwsim + url_git: '' +fxl: + version: 1.7.2 + title: '''fxl'' Single Case Design Charting Package' + maintainer: Shawn Gilroy + description: The 'fxl' Charting package is used to prepare and design single case + design figures that are typically prepared in spreadsheet software. With 'fxl', + there is no need to leave the R environment to prepare these works and many of + the more unique conventions in single case experimental designs can be performed + without the need for physically constructing features of plots (e.g., drawing + annotations across plots). Support is provided for various different plotting + arrangements (e.g., multiple baseline), annotations (e.g., brackets, arrows), + and output formats (e.g., svg, rasters). + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fxl + url_git: '' +fxregime: + version: 1.0-4 + title: Exchange Rate Regime Analysis + maintainer: Achim Zeileis + description: |- + Exchange rate regression and structural change tools + for estimating, testing, dating, and monitoring + (de facto) exchange rate regimes. + date_publication: '2020-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fxregime + url_git: '' +fxTWAPLS: + version: 0.1.3 + title: An Improved Version of WA-PLS + maintainer: Roberto Villegas-Diaz + description: |- + The goal of this package is to provide an improved version of + WA-PLS (Weighted Averaging Partial Least Squares) by including the + tolerances of taxa and the frequency of the sampled climate variable. + This package also provides a way of leave-out cross-validation that + removes both the test site and sites that are both geographically + close and climatically close for each cycle, to avoid the risk of + pseudo-replication. + date_publication: '2024-06-25' + bug_reports: https://github.com/special-uor/fxTWAPLS/issues/ + url: https://special-uor.github.io/fxTWAPLS/ + url_cran: https://CRAN.R-project.org/package=fxTWAPLS + url_git: https://github.com/special-uor/fxTWAPLS/ +fy: + version: 0.4.2 + title: Utilities for Financial Years + maintainer: Hugh Parsonage + description: |- + In Australia, a financial year (or fiscal year) is the period from 1 July to 30 June + of the following calendar year. As such, many databases need to represent and + validate financial years efficiently. While the use of integer years with a convention that + they represent the year ending is common, it may lead to ambiguity with calendar years. + On the other hand, string representations may be too inefficient and do not easily admit + arithmetic operations. This package tries to make validation of financial years quicker while + retaining clarity. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=fy + url_git: '' +g.data: + version: 2.4.1 + title: Delayed-Data Packages + maintainer: David Brahm + description: |- + Create and maintain delayed-data packages (ddp's). Data stored in + a ddp are available on demand, but do not take up memory until requested. + You attach a ddp with g.data.attach(), then read from it and assign to it in + a manner similar to S-PLUS, except that you must run g.data.save() to + actually commit to disk. + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=g.data + url_git: '' +g.ridge: + version: '1.0' + title: Generalized Ridge Regression for Linear Models + maintainer: Takeshi Emura + description: |- + Ridge regression due to Hoerl and Kennard (1970) and generalized ridge regression due to Yang and Emura (2017) with optimized tuning parameters. + These ridge regression estimators (the HK estimator and the YE estimator) are computed by minimizing the cross-validated mean squared errors. + Both the ridge and generalized ridge estimators are applicable for high-dimensional regressors (p>n), where p is the number of regressors, and n is the sample size. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=g.ridge + url_git: '' +G2Sd: + version: 2.1.5 + title: Grain-Size Statistics and Description of Sediment + maintainer: Regis K. Gallon + description: |- + Full descriptive statistics, physical description of sediment, + metric or phi sieves. + date_publication: '2015-12-07' + bug_reports: '' + url: http://regisgallon.wordpress.com/r-software/ + url_cran: https://CRAN.R-project.org/package=G2Sd + url_git: '' +g3viz: + version: 1.2.0 + title: |- + Interactively Visualize Genetic Mutation Data using a + Lollipop-Diagram + maintainer: Xin Guo + description: |- + Interface for 'g3-lollipop' 'JavaScript' library. + Visualize genetic mutation data using an interactive lollipop diagram in 'RStudio' or your web browser. + date_publication: '2024-09-04' + bug_reports: https://github.com/G3viz/g3viz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=g3viz + url_git: https://github.com/G3viz/g3viz +GA: + version: 3.2.4 + title: Genetic Algorithms + maintainer: Luca Scrucca + description: |- + Flexible general-purpose toolbox implementing genetic + algorithms (GAs) for stochastic optimisation. Binary, real-valued, and + permutation representations are available to optimize a fitness + function, i.e. a function provided by users depending on their + objective function. Several genetic operators are available and can be + combined to explore the best settings for the current task. + Furthermore, users can define new genetic operators and easily + evaluate their performances. Local search using general-purpose + optimisation algorithms can be applied stochastically to exploit + interesting regions. GAs can be run sequentially or in parallel, using + an explicit master-slave parallelisation or a coarse-grain islands + approach. For more details see Scrucca (2013) + and Scrucca (2017) + . + date_publication: '2024-01-28' + bug_reports: https://github.com/luca-scr/GA/issues + url: https://luca-scr.github.io/GA/ + url_cran: https://CRAN.R-project.org/package=GA + url_git: '' +gaawr2: + version: 0.0.2 + title: Genetic Association Analysis + maintainer: Jing Hua Zhao + description: |- + It gathers information, meta-data and scripts in a two-part Henry-Stewart talk by + Zhao (2009, ), which showcases analysis in aspects such as testing of polymorphic + variant(s) for Hardy-Weinberg equilibrium, association with trait using genetic and statistical models + as well as Bayesian implementation, power calculation in study design and genetic annotation. It also + covers R integration with the Linux environment, GitHub, package creation and web applications. + date_publication: '2025-02-21' + bug_reports: https://github.com/jinghuazhao/gaawr2/issues + url: https://jinghuazhao.github.io/gaawr2/ + url_cran: https://CRAN.R-project.org/package=gaawr2 + url_git: https://github.com/jinghuazhao/gaawr2 +GABB: + version: 0.3.8 + title: |- + Facilitation of Data Preparation and Plotting Procedures for RDA + and PCA Analyses + maintainer: Gregoire Bianchetti + description: |- + Help to the occasional R user for synthesis and enhanced graphical visualization of redundancy analysis (RDA) and principal component analysis (PCA) methods and objects. + Inputs are : data frame, RDA (package 'vegan') and PCA (package 'FactoMineR') objects. + Outputs are : synthesized results of RDA, displayed in console and saved in tables ; displayed and saved objects of PCA graphic visualization of individuals and variables projections with multiple graphic parameters. + date_publication: '2024-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GABB + url_git: '' +GACFF: + version: '1.0' + title: Genetic Similarity in User-Based Collaborative Filtering + maintainer: Farimah Houshmand Nanehkaran + description: |- + The genetic algorithm can be used directly to find the similarity of users and more effectively to increase the efficiency of the collaborative filtering method. + By identifying the nearest neighbors to the active user, before the genetic algorithm, and by identifying suitable starting points, an effective method for user-based collaborative filtering method has been developed. + This package uses an optimization algorithm (continuous genetic algorithm) to directly find the optimal similarities between active users (users for whom current recommendations are made) and others. + First, by determining the nearest neighbor and their number, the number of genes in a chromosome is determined. Each gene represents the neighbor's similarity to the active user. + By estimating the starting points of the genetic algorithm, it quickly converges to the optimal solutions. + The positive point is the independence of the genetic algorithm on the number of data that for big data is an effective help in solving the problem. + date_publication: '2019-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GACFF + url_git: '' +GAD: + version: '2.0' + title: Analysis of Variance from General Principles + maintainer: Leonardo Sandrini-Neto + description: 'Analysis of complex ANOVA models with any combination of orthogonal/nested + and fixed/random factors, as described by Underwood (1997). There are two restrictions: + (i) data must be balanced; (ii) fixed nested factors are not allowed. Homogeneity + of variances is checked using Cochran''s C test and ''a posteriori'' comparisons + of means are done using Student-Newman-Keuls (SNK) procedure. For those terms + with no denominator in the F-ratio calculation, pooled mean squares and quasi + F-ratios are provided. Magnitute of effects are assessed by components of variation.' + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GAD + url_git: '' +GADAG: + version: 0.99.0 + title: A Genetic Algorithm for Learning Directed Acyclic Graphs + maintainer: Magali Champion + description: Sparse large Directed Acyclic Graphs learning with a combination of + a convex program and a tailored genetic algorithm (see Champion et al. (2017) + ). + date_publication: '2017-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GADAG + url_git: '' +gadget2: + version: 2.3.11 + title: |- + Gadget is the Globally-Applicable Area Disaggregated General + Ecosystem Toolbox + maintainer: Bjarki Thor Elvarsson + description: |- + A statistical ecosystem modelling package, taking many features of + the ecosystem into account. Gadget works by running an internal + model based on many parameters, and then comparing the data from + the output of this model to real data to get a goodness-of-fit + likelihood score. These parameters can then be adjusted, and the + model re-run, until an optimum is found, which corresponds to the + model with the lowest likelihood score. Gadget allows the user to + include a number of features into an ecosystem model: One or more + species, each of which may be split into multiple stocks; multiple + areas with migration between areas; predation between and within + species; maturation; reproduction and recruitment; multiple + commercial and survey fleets taking catches from the populations. + For more details see . + This is the C++ Gadget2 runtime, making it available for R. + date_publication: '2023-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gadget2 + url_git: '' +gadget3: + version: 0.12-1 + title: |- + Globally-Applicable Area Disaggregated General Ecosystem Toolbox + V3 + maintainer: Jamie Lentin + description: |- + A framework to assist creation of marine ecosystem models, + generating either 'R' or 'C++' code which can then be optimised using + the 'TMB' package and standard 'R' tools. Principally designed to + reproduce gadget2 models in 'TMB', but can be extended beyond + gadget2's capabilities. + Kasper Kristensen, Anders Nielsen, Casper W. Berg, Hans Skaug, Bradley M. Bell (2016) "TMB: Automatic Differentiation and Laplace Approximation.". + Begley, J., & Howell, D. (2004) "An overview of Gadget, the globally applicable area-disaggregated general ecosystem toolbox. ICES.". + date_publication: '2024-07-03' + bug_reports: '' + url: https://gadget-framework.github.io/gadget3/ + url_cran: https://CRAN.R-project.org/package=gadget3 + url_git: https://github.com/gadget-framework/gadget3/ +gafit: + version: 0.5.1 + title: Genetic Algorithm for Curve Fitting + maintainer: Telford Tendys + description: |- + A group of sample points are evaluated against a + user-defined expression, the sample points are lists of + parameters with values that may be substituted into that + expression. The genetic algorithm attempts to make the result + of the expression as low as possible (usually this would be the + sum of residuals squared). + date_publication: '2016-12-05' + bug_reports: '' + url: http://lnx-bsp.net/ + url_cran: https://CRAN.R-project.org/package=gafit + url_git: '' +GAGAs: + version: 0.6.2 + title: |- + Global Adaptive Generative Adjustment Algorithm for Generalized + Linear Models + maintainer: Bin Wang + description: |- + Fits linear regression, logistic and multinomial regression models, Poisson regression, Cox model via Global Adaptive Generative Adjustment Algorithm. + For more detailed information, see Bin Wang, Xiaofei Wang and Jianhua Guo (2022) . + This paper provides the theoretical properties of Gaga linear model when the load matrix is orthogonal. + Further study is going on for the nonorthogonal cases and generalized linear models. + These works are in part supported by the National Natural Foundation of China (No.12171076). + date_publication: '2024-01-23' + bug_reports: '' + url: https://arxiv.org/abs/1911.00658 + url_cran: https://CRAN.R-project.org/package=GAGAs + url_git: '' +GAGBLUP: + version: '1.0' + title: |- + Genetic Algorithm Assisted Genomic Best Liner Unbiased + Prediction + maintainer: Yuxiang Zhang + description: |- + Performs genetic algorithm (Scrucca, L (2013) ) + assisted genomic best liner unbiased prediction for genomic selection. + It also provides a binning method in natural population for genomic selection + under the principle of linkage disequilibrium for dimensional reduction. + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GAGBLUP + url_git: '' +gaiah: + version: 0.0.5 + title: |- + Genetic and Isotopic Assignment Accounting for Habitat + Suitability + maintainer: Eric C. Anderson + description: |- + Tools for using genetic markers, stable isotope data, and habitat + suitability data to calculate posterior probabilities of breeding origin of + migrating birds. + date_publication: '2023-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gaiah + url_git: '' +gainML: + version: 0.1.0 + title: |- + Machine Learning-Based Analysis of Potential Power Gain from + Passive Device Installation on Wind Turbine Generators + maintainer: Hoon Hwangbo + description: |- + Provides an effective machine learning-based tool that quantifies the gain of passive device installation on wind turbine generators. + H. Hwangbo, Y. Ding, and D. Cabezon (2019) . + date_publication: '2019-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gainML + url_git: '' +gains: + version: '1.2' + title: Lift (Gains) Tables and Charts + maintainer: Craig A. Rolling + description: Constructs gains tables and lift charts for prediction algorithms. + Gains tables and lift charts are commonly used in direct marketing applications. The + method is described in Drozdenko and Drake (2002), "Optimal Database Marketing", + Chapter 11. + date_publication: '2017-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gains + url_git: '' +GAIPE: + version: '1.1' + title: |- + Graphical Extension with Accuracy in Parameter Estimation + (GAIPE) + maintainer: Yao Lin + description: 'Implements graphical extension with accuracy in parameter estimation + (AIPE) on RMSEA for sample size planning in structural equation modeling based + on Lin, T.-Z. & Weng, L.-J. (2014) . And, it + can also implement AIPE on RMSEA and power analysis on RMSEA.' + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GAIPE + url_git: '' +galah: + version: 2.1.1 + title: Biodiversity Data from the GBIF Node Network + maintainer: Martin Westgate + description: |- + The Global Biodiversity Information Facility + ('GBIF', ) sources data from an international network + of data providers, known as 'nodes'. Several of these nodes - the "living + atlases" () - maintain their own web + services using software originally developed by the Atlas of Living + Australia ('ALA', ). 'galah' enables the R community + to directly access data and resources hosted by 'GBIF' and its partner nodes. + date_publication: '2025-02-07' + bug_reports: https://github.com/AtlasOfLivingAustralia/galah-R/issues + url: https://galah.ala.org.au/R/ + url_cran: https://CRAN.R-project.org/package=galah + url_git: '' +galamm: + version: 0.2.1 + title: Generalized Additive Latent and Mixed Models + maintainer: Øystein Sørensen + description: |- + Estimates generalized additive latent and + mixed models using maximum marginal likelihood, + as defined in Sorensen et al. (2023) + , which is an extension of Rabe-Hesketh and + Skrondal (2004)'s unifying framework for multilevel latent variable + modeling . Efficient computation is done using sparse + matrix methods, Laplace approximation, and automatic differentiation. The + framework includes generalized multilevel models with heteroscedastic + residuals, mixed response types, factor loadings, smoothing splines, + crossed random effects, and combinations thereof. Syntax for model + formulation is close to 'lme4' (Bates et al. (2015) + ) and 'PLmixed' (Rockwood and Jeon (2019) + ). + date_publication: '2024-08-18' + bug_reports: https://github.com/LCBC-UiO/galamm/issues + url: https://lcbc-uio.github.io/galamm/ + url_cran: https://CRAN.R-project.org/package=galamm + url_git: https://github.com/LCBC-UiO/galamm +galigor: + version: 0.2.5 + title: Collection of Packages for Internet Marketing + maintainer: Alexey Seleznev + description: |- + Collection of packages for work with API 'Google Ads' , + 'Yandex Direct' , 'Yandex Metrica' , + 'MyTarget' , 'Vkontakte' , + 'Facebook' and 'AppsFlyer' . + This packages allows you loading data from ads account and manage your ads materials. + date_publication: '2021-09-06' + bug_reports: '' + url: https://selesnow.github.io + url_cran: https://CRAN.R-project.org/package=galigor + url_git: '' +gallery: + version: 1.0.0 + title: Generate Test Matrices for Numerical Experiments + maintainer: Thomas Hsiao + description: Generates a variety of structured test matrices commonly used in numerical + linear algebra and computational experiments. Includes well-known matrices for + benchmarking and testing the performance, stability, and accuracy of linear algebra + algorithms. Inspired by 'MATLAB' 'gallery' functions. + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gallery + url_git: '' +GALLO: + version: '1.5' + title: Genomic Annotation in Livestock for Positional Candidate LOci + maintainer: Pablo Fonseca + description: The accurate annotation of genes and Quantitative Trait Loci (QTLs) + located within candidate markers and/or regions (haplotypes, windows, CNVs, etc) + is a crucial step the most common genomic analyses performed in livestock, such + as Genome-Wide Association Studies or transcriptomics. The Genomic Annotation + in Livestock for positional candidate LOci (GALLO) is an R package designed to + provide an intuitive and straightforward environment to annotate positional candidate + genes and QTLs from high-throughput genetic studies in livestock. Moreover, GALLO + allows the graphical visualization of gene and QTL annotation results, data comparison + among different grouping factors (e.g., methods, breeds, tissues, statistical + models, studies, etc.), and QTL enrichment in different livestock species including + cattle, pigs, sheep, and chicken, among others. + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GALLO + url_git: +galts: + version: 1.3.2 + title: |- + Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares) + Estimation + maintainer: Mehmet Hakan Satman + description: |- + Includes the ga.lts() function that estimates + LTS (Least Trimmed Squares) parameters using genetic algorithms + and C-steps. ga.lts() constructs a genetic algorithm to form a + basic subset and iterates C-steps as defined in Rousseeuw and + van-Driessen (2006) to calculate the cost value of the LTS + criterion. OLS (Ordinary Least Squares) regression is known to + be sensitive to outliers. A single outlying observation can + change the values of estimated parameters. LTS is a resistant + estimator even the number of outliers is up to half of the + data. This package is for estimating the LTS parameters with + lower bias and variance in a reasonable time. Version >=1.3 + includes the function medmad for fast outlier detection in + linear regression. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=galts + url_git: '' +galvanizer: + version: 0.5.3 + title: Interface to Galvanize 'Highbond' Internal Audit Software + maintainer: Jonathan Lin + description: An R interface to the Galvanize 'Highbond' API . + date_publication: '2021-05-28' + bug_reports: https://github.com/jonlinca/galvanizer/issues + url: https://jonlinca.github.io/galvanizer/ + url_cran: https://CRAN.R-project.org/package=galvanizer + url_git: https://github.com/jonlinca/galvanizer +gam: + version: 1.22-5 + title: Generalized Additive Models + maintainer: Trevor Hastie + description: "Functions for fitting and working with generalized\tadditive models, + as described in chapter 7 of \"Statistical Models in S\" (Chambers and Hastie + (eds), 1991), and \"Generalized Additive Models\" (Hastie and Tibshirani, 1990)." + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gam + url_git: '' +gam.hp: + version: 0.0-3 + title: |- + Hierarchical Partitioning of Adjusted R2 and Explained Deviance + for Generalized Additive Models + maintainer: Jiangshan Lai + description: 'Conducts hierarchical partitioning to calculate individual contributions + of each predictor towards adjusted R2 and explained deviance for generalized additive + models based on output of gam()in ''mgcv'' package, applying the algorithm in + this paper: Lai(2024) .' + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gam.hp + url_git: https://github.com/laijiangshan/gam.hp +gamair: + version: 1.0-2 + title: 'Data for ''GAMs: An Introduction with R''' + maintainer: Simon Wood + description: |- + Data sets and scripts used in the book 'Generalized Additive + Models: An Introduction with R', Wood (2006,2017) CRC. + date_publication: '2019-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamair + url_git: '' +gambin: + version: 2.5.0 + title: Fit the Gambin Model to Species Abundance Distributions + maintainer: Thomas Matthews + description: |- + Fits unimodal and multimodal gambin distributions to species-abundance distributions + from ecological data, as in in Matthews et al. (2014) . + 'gambin' is short for 'gamma-binomial'. The main function is fit_abundances(), which estimates + the 'alpha' parameter(s) of the gambin distribution using maximum likelihood. Functions are + also provided to generate the gambin distribution and for calculating likelihood statistics. + date_publication: '2021-04-16' + bug_reports: https://github.com/txm676/gambin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gambin + url_git: https://github.com/txm676/gambin/ +gamblers.ruin.gameplay: + version: 4.0.5 + title: |- + One-Dimensional Random Walks Through Simulation of the Gambler's + Ruin Problem + maintainer: Somjit Roy + description: Simulates a gambling game under the gambler's ruin setup, after asking + for the money you have and the money you want to win, along with your win probability + in each round of the game. + date_publication: '2021-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamblers.ruin.gameplay + url_git: '' +gamboostLSS: + version: 2.1-0 + title: Boosting Methods for 'GAMLSS' + maintainer: Benjamin Hofner + description: |- + Boosting models for fitting generalized additive models for + location, shape and scale ('GAMLSS') to potentially high dimensional + data. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamboostLSS + url_git: https://github.com/boost-R/gamboostLSS +gamboostMSM: + version: 1.1.88 + title: Boosting Multistate Models + maintainer: Holger Reulen + description: Contains infrastructure for using mboost::gamboost() in order to estimate + multistate models. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamboostMSM + url_git: '' +gamclass: + version: 0.62.5 + title: |- + Functions and Data for a Course on Modern Regression and + Classification + maintainer: John Maindonald + description: |- + Functions and data are provided that support a course + that emphasizes statistical issues of inference and generalizability. + The functions are designed to make it straightforward to illustrate + the use of cross-validation, the training/test approach, simulation, + and model-based estimates of accuracy. Methods considered are + Generalized Additive Modeling, Linear and Quadratic Discriminant + Analysis, Tree-based methods, and Random Forests. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamclass + url_git: '' +gamCopula: + version: 0.0-7 + title: |- + Generalized Additive Models for Bivariate Conditional Dependence + Structures and Vine Copulas + maintainer: Thibault Vatter + description: |- + Implementation of various inference and simulation tools to + apply generalized additive models to bivariate dependence structures and + non-simplified vine copulas. + date_publication: '2020-02-05' + bug_reports: https://github.com/tvatter/gamCopula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gamCopula + url_git: https://github.com/tvatter/gamCopula +GAMens: + version: 1.2.1 + title: |- + Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for + Binary Classification + maintainer: Koen W. De Bock + description: |- + Implements the GAMbag, GAMrsm and GAMens ensemble + classifiers for binary classification (De Bock et al., 2010) . The ensembles + implement Bagging (Breiman, 1996) , the Random Subspace Method (Ho, 1998) + , or both, and use Hastie and Tibshirani's (1990, ISBN:978-0412343902) generalized additive models (GAMs) + as base classifiers. Once an ensemble classifier has been trained, it can + be used for predictions on new data. A function for cross validation is also + included. + date_publication: '2018-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GAMens + url_git: '' +gameR: + version: 0.0.7 + title: Color Palettes Inspired by Video Games + maintainer: Nathan Constantine-Cooke + description: Palettes based on video games. + date_publication: '2024-11-26' + bug_reports: https://github.com/nathansam/gameR/issues + url: https://www.constantine-cooke.com/gameR/ + url_cran: https://CRAN.R-project.org/package=gameR + url_git: https://github.com/nathansam/gameR/ +gamesGA: + version: 1.1.3.7 + title: Genetic Algorithm for Sequential Symmetric Games + maintainer: A. Bradley Duthie + description: |- + Finds adaptive strategies for sequential symmetric + games using a genetic algorithm. Currently, any symmetric two by two matrix + is allowed, and strategies can remember the history of an opponent's play + from the previous three rounds of moves in iterated interactions between + players. The genetic algorithm returns a list of adaptive strategies given + payoffs, and the mean fitness of strategies in each generation. + date_publication: '2020-03-01' + bug_reports: https://github.com/bradduthie/gamesGA/issues + url: https://bradduthie.github.io/gamesGA/ + url_cran: https://CRAN.R-project.org/package=gamesGA + url_git: '' +GameTheory: + version: 2.7.1 + title: Cooperative Game Theory + maintainer: Sebastian Cano-Berlanga + description: Implementation of a common set of punctual solutions for Cooperative + Game Theory. + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GameTheory + url_git: '' +GameTheoryAllocation: + version: '1.0' + title: Tools for Calculating Allocations in Game Theory + maintainer: Alejandro Saavedra-Nieves + description: 'Many situations can be modeled as game theoretic situations. Some + procedures are included in this package to calculate the most important allocations + rules in Game Theory: Shapley value, Owen value or nucleolus, among other. First, + we must define as an argument the value of the unions of the envolved agents with + the characteristic function.' + date_publication: '2016-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GameTheoryAllocation + url_git: '' +gamlr: + version: 1.13-8 + title: Gamma Lasso Regression + maintainer: Matt Taddy + description: 'The gamma lasso algorithm provides regularization paths corresponding + to a range of non-convex cost functions between L0 and L1 norms. As much as possible, + usage for this package is analogous to that for the glmnet package (which does + the same thing for penalization between L1 and L2 norms). For details see: Taddy + (2017 JCGS), ''One-Step Estimator Paths for Concave Regularization'', .' + date_publication: '2023-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamlr + url_git: https://github.com/TaddyLab/gamlr +gamlss: + version: 5.4-22 + title: Generalized Additive Models for Location Scale and Shape + maintainer: Mikis Stasinopoulos + description: Functions for fitting the Generalized Additive Models for Location + Scale and Shape introduced by Rigby and Stasinopoulos (2005), . + The models use a distributional regression approach where all the parameters of + the conditional distribution of the response variable are modelled using explanatory + variables. + date_publication: '2024-03-20' + bug_reports: https://github.com/gamlss-dev/gamlss/issues + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss + url_git: '' +gamlss.add: + version: 5.1-13 + title: |- + Extra Additive Terms for Generalized Additive Models for + Location Scale and Shape + maintainer: Mikis Stasinopoulos + description: |- + Interface for extra smooth functions including tensor products, + neural networks and decision trees. + date_publication: '2024-03-28' + bug_reports: https://github.com/gamlss-dev/gamlss.add/issues + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.add + url_git: '' +gamlss.cens: + version: 5.0-7 + title: |- + Fitting an Interval Response Variable Using `gamlss.family' + Distributions + maintainer: Mikis Stasinopoulos + description: |- + This is an add-on package to GAMLSS. The purpose of this + package is to allow users to fit interval response variables in + GAMLSS models. The main function gen.cens() generates a + censored version of an existing GAMLSS family distribution. + date_publication: '2023-10-07' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.cens + url_git: '' +gamlss.countKinf: + version: 3.5.1 + title: |- + Generating and Fitting K-Inflated 'discrete gamlss.family' + Distributions + maintainer: Saeed Mohammadpour + description: This is an add on package to 'GAMLSS'. The main purpose of this package + is generating and fitting inflated distributions at any desired point (0, 1, 2, + ...). The function gen.Kinf() generates K-inflated version of an existing discrete + 'GAMLSS' family distribution. + date_publication: '2018-11-14' + bug_reports: '' + url: http://www.gamlss.org/ + url_cran: https://CRAN.R-project.org/package=gamlss.countKinf + url_git: '' +gamlss.data: + version: 6.0-6 + title: |- + Data for Generalised Additive Models for Location Scale and + Shape + maintainer: Mikis Stasinopoulos + description: Data used as examples in the current two books on Generalised Additive + Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), + . + date_publication: '2024-03-14' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.data + url_git: '' +gamlss.demo: + version: 4.3-3 + title: Demos for GAMLSS + maintainer: Mikis Stasinopoulos + description: Demos for smoothing and gamlss.family distributions. + date_publication: '2015-07-17' + bug_reports: '' + url: http://www.gamlss.org/ + url_cran: https://CRAN.R-project.org/package=gamlss.demo + url_git: '' +gamlss.dist: + version: 6.1-1 + title: |- + Distributions for Generalized Additive Models for Location Scale + and Shape + maintainer: Mikis Stasinopoulos + description: A set of distributions which can be used for modelling the response + variables in Generalized Additive Models for Location Scale and Shape, Rigby and + Stasinopoulos (2005), . The distributions + can be continuous, discrete or mixed distributions. Extra distributions can be + created, by transforming, any continuous distribution defined on the real line, + to a distribution defined on ranges 0 to infinity or 0 to 1, by using a 'log' + or a 'logit' transformation respectively. + date_publication: '2023-08-23' + bug_reports: https://github.com/mstasinopoulos/GAMLSS-Distibutions/issues + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.dist + url_git: '' +gamlss.foreach: + version: 1.1-6 + title: Parallel Computations for Distributional Regression + maintainer: Mikis Stasinopoulos + description: Computational intensive calculations for Generalized Additive Models + for Location Scale and Shape, . + date_publication: '2022-08-28' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.foreach + url_git: '' +gamlss.ggplots: + version: 2.1-12 + title: |- + Plotting Functions for Generalized Additive Model for Location + Scale and Shape + maintainer: Mikis Stasinopoulos + description: Functions for plotting Generalized Additive Models for Location Scale + and Shape from the 'gamlss' package, Stasinopoulos and Rigby (2007) , + using the graphical methods from 'ggplot2'. + date_publication: '2024-03-25' + bug_reports: https://github.com/gamlss-dev/gamlss.ggplots/issues + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.ggplots + url_git: '' +gamlss.inf: + version: 1.0-1 + title: Fitting Mixed (Inflated and Adjusted) Distributions + maintainer: Marco Enea + description: This is an add-on package to 'gamlss'. The purpose of this package + is to allow users to fit GAMLSS (Generalised Additive Models for Location Scale + and Shape) models when the response variable is defined either in the intervals + [0,1), (0,1] and [0,1] (inflated at zero and/or one distributions), or in the + positive real line including zero (zero-adjusted distributions). The mass points + at zero and/or one are treated as extra parameters with the possibility to include + a linear predictor for both. The package also allows transformed or truncated + distributions from the GAMLSS family to be used for the continuous part of the + distribution. Standard methods and GAMLSS diagnostics can be used with the resulting + fitted object. + date_publication: '2019-03-12' + bug_reports: '' + url: http://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.inf + url_git: '' +gamlss.lasso: + version: 1.0-1 + title: Extra Lasso-Type Additive Terms for GAMLSS + maintainer: Florian Ziel + description: Interface for extra high-dimensional smooth functions for Generalized + Additive Models for Location Scale and Shape (GAMLSS) including (adaptive) lasso, + ridge, elastic net and least angle regression. + date_publication: '2021-05-21' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.lasso + url_git: '' +gamlss.mx: + version: 6.0-1 + title: Fitting Mixture Distributions with GAMLSS + maintainer: Mikis Stasinopoulos + description: |- + The main purpose of this package is to allow fitting of + mixture distributions with generalised additive models for location + scale and shape models see Chapter 7 of Stasinopoulos et al. (2017) . + date_publication: '2024-01-30' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.mx + url_git: '' +gamlss.spatial: + version: 3.0-2 + title: |- + Spatial Terms in Generalized Additive Models for Location Scale + and Shape Models + maintainer: Fernanda De Bastiani + description: |- + It allows us to fit Gaussian Markov Random Field within the + Generalized Additive Models for Location Scale and Shape algorithms. + date_publication: '2023-10-15' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.spatial + url_git: '' +gamlss.tr: + version: 5.1-9 + title: Generating and Fitting Truncated `gamlss.family' Distributions + maintainer: Mikis Stasinopoulos + description: |- + This is an add on package to GAMLSS. The purpose of this + package is to allow users to defined truncated distributions in + GAMLSS models. The main function gen.trun() generates truncated + version of an existing GAMLSS family distribution. + date_publication: '2024-01-30' + bug_reports: '' + url: https://www.gamlss.com/ + url_cran: https://CRAN.R-project.org/package=gamlss.tr + url_git: '' +gamlssbssn: + version: 0.1.0 + title: Bimodal Skew Symmetric Normal Distribution + maintainer: Abu Hossain + description: Density, distribution function, quantile function and random generation + for the bimodal skew symmetric normal distribution of Hassan and El-Bassiouni + (2016) . + date_publication: '2017-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamlssbssn + url_git: '' +gamlssx: + version: 1.0.2 + title: |- + Generalized Additive Extreme Value Models for Location, Scale + and Shape + maintainer: Paul J. Northrop + description: |- + Fits generalized additive models for the location, scale and shape + parameters of a generalized extreme value response distribution. The + methodology is based on Rigby, R.A. and Stasinopoulos, D.M. (2005), + and implemented using functions from + the 'gamlss' package . + date_publication: '2025-02-28' + bug_reports: https://github.com/paulnorthrop/gamlssx/issues + url: https://paulnorthrop.github.io/gamlssx/ + url_cran: https://CRAN.R-project.org/package=gamlssx + url_git: https://github.com/paulnorthrop/gamlssx +gamm4: + version: 0.2-6 + title: Generalized Additive Mixed Models using 'mgcv' and 'lme4' + maintainer: Simon Wood + description: |- + Estimate generalized additive mixed models via a version of + function gamm() from 'mgcv', using 'lme4' for estimation. + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamm4 + url_git: '' +gamma: + version: 1.1.0 + title: |- + Dose Rate Estimation from in-Situ Gamma-Ray Spectrometry + Measurements + maintainer: Archéosciences Bordeaux + description: |- + Process in-situ Gamma-Ray Spectrometry for Luminescence + Dating. This package allows to import, inspect and correct the energy + shifts of gamma-ray spectra. It provides methods for estimating the + gamma dose rate by the use of a calibration curve as described in + Mercier and Falguères (2007). The package only supports Canberra CNF + and TKA and Kromek SPE files. + date_publication: '2024-09-23' + bug_reports: https://github.com/crp2a/gamma/issues + url: https://crp2a.github.io/gamma/ + url_cran: https://CRAN.R-project.org/package=gamma + url_git: https://github.com/crp2a/gamma +Gammareg: + version: 3.0.1 + title: |- + Classic Gamma Regression: Joint Modeling of Mean and Shape + Parameters + maintainer: Martha Corrales + description: Performs Gamma regression, where both mean and shape parameters follows + lineal regression structures. + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Gammareg + url_git: '' +gammi: + version: '0.2' + title: Generalized Additive Mixed Model Interface + maintainer: Nathaniel E. Helwig + description: An interface for fitting generalized additive models (GAMs) and generalized + additive mixed models (GAMMs) using the 'lme4' package as the computational engine, + as described in Helwig (2024) . Supports default and + formula methods for model specification, additive and tensor product splines for + capturing nonlinear effects, and automatic determination of spline type based + on the class of each predictor. Includes an S3 plot method for visualizing the + (nonlinear) model terms, an S3 predict method for forming predictions from a fit + model, and an S3 summary method for conducting significance testing using the + Bayesian interpretation of a smoothing spline. + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gammi + url_git: '' +gammSlice: + version: 2.0-2 + title: Generalized Additive Mixed Model Analysis via Slice Sampling + maintainer: Matt P. Wand + description: |- + Uses a slice sampling-based Markov chain Monte Carlo to + conduct Bayesian fitting and inference for generalized additive + mixed models. Generalized linear mixed models and generalized + additive models are also handled as special cases of generalized + additive mixed models. The methodology and software is described + in Pham, T.H. and Wand, M.P. (2018). Australian and New Zealand + Journal of Statistics, 60, 279-330 . + date_publication: '2019-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gammSlice + url_git: '' +gamreg: + version: '0.3' + title: Robust and Sparse Regression via Gamma-Divergence + maintainer: Takayuki Kawashima + description: Robust regression via gamma-divergence with L1, elastic net and ridge. + date_publication: '2017-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamreg + url_git: '' +gamRR: + version: 0.7.0 + title: Calculate the RR for the GAM + maintainer: Zhicheng Du + description: To calculate the relative risk (RR) for the generalized additive model. + date_publication: '2019-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamRR + url_git: '' +gamsel: + version: 1.8-5 + title: Fit Regularization Path for Generalized Additive Models + maintainer: Trevor Hastie + description: Using overlap grouped-lasso penalties, 'gamsel' selects whether a term + in a 'gam' is nonzero, linear, or a non-linear spline (up to a specified max df + per variable). It fits the entire regularization path on a grid of values for + the overall penalty lambda, both for gaussian and binomial families. See + for more details. + date_publication: '2024-09-24' + bug_reports: '' + url: https://arxiv.org/abs/1506.03850 + url_cran: https://CRAN.R-project.org/package=gamsel + url_git: '' +gamselBayes: + version: 2.0-2 + title: Bayesian Generalized Additive Model Selection + maintainer: Matt P. Wand + description: 'Generalized additive model selection via approximate Bayesian inference + is provided. Bayesian mixed model-based penalized splines with spike-and-slab-type + coefficient prior distributions are used to facilitate fitting and selection. + The approximate Bayesian inference engine options are: (1) Markov chain Monte + Carlo and (2) mean field variational Bayes. Markov chain Monte Carlo has better + Bayesian inferential accuracy, but requires a longer run-time. Mean field variational + Bayes is faster, but less accurate. The methodology is described in He and Wand + (2024) .' + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gamselBayes + url_git: '' +gamstransfer: + version: 3.0.4 + title: A Data Interface Between 'GAMS' and R + maintainer: Atharv Bhosekar + description: |- + Read, analyze, modify, and write 'GAMS' (General Algebraic + Modeling System) data. The main focus of 'gamstransfer' is the + highly efficient transfer of data with 'GAMS' , + while keeping these operations as simple as possible for the user. The + transfer of data usually takes place via an intermediate GDX (GAMS Data + Exchange) file. Additionally, 'gamstransfer' provides utility + functions to get an overview of 'GAMS' data and to check its validity. + date_publication: '2024-09-24' + bug_reports: https://github.com/GAMS-dev/transfer-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gamstransfer + url_git: https://github.com/GAMS-dev/transfer-r/tree/main/gamstransfer +ganDataModel: + version: 1.1.7 + title: Build a Metric Subspaces Data Model for a Data Source + maintainer: Werner Mueller + description: Neural networks are applied to create a density value function which + approximates density values for a data source. The trained neural network is analyzed + for different levels. For each level metric subspaces with density values above + a level are determined. The obtained set of metric subspaces and the trained neural + network are assembled into a data model. A prerequisite is the definition of a + data source, the generation of generative data and the calculation of density + values. These tasks are executed using package 'ganGenerativeData' . + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ganDataModel + url_git: '' +gander: + version: 0.1.0 + title: High Performance, Low Friction Large Language Model Chat + maintainer: Simon Couch + description: |- + Introduces a 'Copilot'-like completion experience, but it knows how + to talk to the objects in your R environment. 'ellmer' chats are integrated + directly into your 'RStudio' and 'Positron' sessions, automatically + incorporating relevant context from surrounding lines of code and your + global environment (like data frame columns and types). Open the package + dialog box with a keyboard shortcut, type your request, and the assistant + will stream its response directly into your documents. + date_publication: '2025-02-19' + bug_reports: https://github.com/simonpcouch/gander/issues + url: https://simonpcouch.github.io/gander/ + url_cran: https://CRAN.R-project.org/package=gander + url_git: https://github.com/simonpcouch/gander +ganGenerativeData: + version: 2.1.4 + title: Generate Generative Data for a Data Source + maintainer: Werner Mueller + description: 'Generative Adversarial Networks are applied to generate generative + data for a data source. A generative model consisting of a generator and a discriminator + network is trained. During iterative training the distribution of generated data + is converging to that of the data source. Direct applications of generative data + are the created functions for data evaluation, missing data completion and data + classification. A software service for accelerated training of generative models + on graphics processing units is available. Reference: Goodfellow et al. (2014) + .' + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ganGenerativeData + url_git: '' +GANPA: + version: '1.2' + title: Gene Association Network-Based Pathway Analysis (GANPA) + maintainer: Zhaoyuan Fang + description: A network-based gene weighting algorithm for pathway enrichment analysis, + using either RNA-seq or microarray data. Zhaoyuan Fang, Weidong Tian and Hongbin + Ji (2012) . + date_publication: '2024-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GANPA + url_git: '' +GANPAdata: + version: '1.0' + title: The GANPA Datasets Package + maintainer: Zhaoyuan Fang + description: This is a dataset package for GANPA, which implements anetwork-based + gene weighting approach to pathway analysis. Thispackage includes data + useful for GANPA, such as a functionalassociation network, pathways, an + expression dataset andmulti-subunit proteins. + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GANPAdata + url_git: '' +gap: + version: '1.6' + title: Genetic Analysis Package + maintainer: Jing Hua Zhao + description: |- + As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. + ], it is designed as an integrated package for genetic data + analysis of both population and family data. Currently, it contains functions for + sample size calculations of both population-based and family-based designs, probability + of familial disease aggregation, kinship calculation, statistics in linkage analysis, + and association analysis involving genetic markers including haplotype analysis with or + without environmental covariates. Over years, the package has been developed in-between + many projects hence also in line with the name (gap). + date_publication: '2024-08-27' + bug_reports: https://github.com/jinghuazhao/R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gap + url_git: https://github.com/jinghuazhao/R +gap.datasets: + version: 0.0.6 + title: Datasets for 'gap' + maintainer: Jing Hua Zhao + description: |- + Datasets associated with the 'gap' package. Currently, + it includes an example data for regional association + plot (CDKN), an example data for a genomewide association + meta-analysis (OPG), data in studies of Parkinson's diease (PD), + ALHD2 markers and alcoholism (aldh2), APOE/APOC1 markers + and Schizophrenia (apoeapoc), cystic fibrosis (cf), a + Olink/INF panel (inf1), Manhattan plots with (hr1420, mhtdata) + and without (w4) gene annotations. + date_publication: '2023-08-25' + bug_reports: '' + url: https://jinghuazhao.github.io/R/ + url_cran: https://CRAN.R-project.org/package=gap.datasets + url_git: '' +GAparsimony: + version: 0.9.5 + title: Searching Parsimony Models with Genetic Algorithms + maintainer: F.J. Martinez-de-Pison + description: Methodology that combines feature selection, model tuning, and parsimonious + model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) + . To this objective, a novel GA selection procedure + is introduced based on separate cost and complexity evaluations. + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GAparsimony + url_git: https://github.com/jpison/GAparsimony +gapclosing: + version: 1.0.2 + title: Estimate Gaps Under an Intervention + maintainer: Ian Lundberg + description: Provides functions to estimate the disparities across categories (e.g. + Black and white) that persists if a treatment variable (e.g. college) is equalized. + Makes estimates by treatment modeling, outcome modeling, and doubly-robust augmented + inverse probability weighting estimation, with standard errors calculated by a + nonparametric bootstrap. Cross-fitting is supported. Survey weights are supported + for point estimation but not for standard error estimation; those applying this + package with complex survey samples should consult the data distributor to select + an appropriate approach for standard error construction, which may involve calling + the functions repeatedly for many sets of replicate weights provided by the data + distributor. The methods in this package are described in Lundberg (2021) . + date_publication: '2021-10-11' + bug_reports: https://github.com/ilundberg/gapclosing/issues + url: https://ilundberg.github.io/gapclosing/ + url_cran: https://CRAN.R-project.org/package=gapclosing + url_git: '' +gapfill: + version: 0.9.6-1 + title: Fill Missing Values in Satellite Data + maintainer: Florian Gerber + description: |- + Tools to fill missing values in satellite data and to develop new + gap-fill algorithms. The methods are tailored to data (images) observed + at equally-spaced points in time. The package is illustrated with MODIS + NDVI data. + date_publication: '2021-02-12' + bug_reports: https://github.com/florafauna/gapfill/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gapfill + url_git: https://github.com/florafauna/gapfill +gapmap: + version: 1.0.0 + title: Drawing Gapped Cluster Heatmaps with 'ggplot2' + maintainer: Evan Biederstedt + description: |- + The gap encodes the distance between clusters and improves + interpretation of cluster heatmaps. The gaps can be of the same + distance based on a height threshold to cut the dendrogram. Another + option is to vary the size of gaps based on the distance between + clusters. + date_publication: '2024-01-22' + bug_reports: https://github.com/evanbiederstedt/gapmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gapmap + url_git: https://github.com/evanbiederstedt/gapmap +gapminder: + version: 1.0.0 + title: Data from Gapminder + maintainer: Jennifer Bryan + description: |- + An excerpt of the data available at Gapminder.org. For each + of 142 countries, the package provides values for life expectancy, GDP + per capita, and population, every five years, from 1952 to 2007. + date_publication: '2023-03-10' + bug_reports: https://github.com/jennybc/gapminder/issues + url: https://www.gapminder.org/data/ + url_cran: https://CRAN.R-project.org/package=gapminder + url_git: https://github.com/jennybc/gapminder +GARCHIto: + version: 0.1.0 + title: Class of GARCH-Ito Models + maintainer: Xinyu Song + description: Provides functions to estimate model parameters and forecast future + volatilities using the Unified GARCH-Ito [Kim and Wang (2016) ] + and Realized GARCH-Ito [Song et. al. (2020) ] + models. Optimization is done using augmented Lagrange multiplier method. + date_publication: '2020-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GARCHIto + url_git: '' +GARCHSK: + version: 0.1.0 + title: Estimating a GARCHSK Model and GJRSK Model + maintainer: Kei Nakagawa + description: Functions for estimating a GARCHSK model and GJRSK model based on a + publication by Leon et,al (2005) and Nakagawa + and Uchiyama (2020). These are a GARCH-type model allowing + for time-varying volatility, skewness and kurtosis. + date_publication: '2021-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GARCHSK + url_git: '' +garchx: + version: '1.5' + title: Flexible and Robust GARCH-X Modelling + maintainer: Genaro Sucarrat + description: Flexible and robust estimation and inference of generalised autoregressive + conditional heteroscedasticity (GARCH) models with covariates ('X') based on the + results by Francq and Thieu (2018) . Coefficients + can straightforwardly be set to zero by omission, and quasi maximum likelihood + methods ensure estimates are generally consistent and inference valid, even when + the standardised innovations are non-normal and/or dependent over time, see + for an overview of the package. + date_publication: '2022-09-13' + bug_reports: https://github.com/gsucarrat/garchx/issues + url: https://www.sucarrat.net/ + url_cran: https://CRAN.R-project.org/package=garchx + url_git: '' +GARCOM: + version: 1.2.2 + title: Gene and Region Counting of Mutations ("GARCOM") + maintainer: Sanjeev Sariya + description: Gene and Region Counting of Mutations (GARCOM) package computes mutation + (or alleles) counts per gene per individuals based on gene annotation or genomic + base pair boundaries. It comes with features to accept data formats in plink(.raw) + and VCF. It provides users flexibility to extract and filter individuals, mutations + and genes of interest. + date_publication: '2022-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GARCOM + url_git: '' +gargle: + version: 1.5.2 + title: Utilities for Working with Google APIs + maintainer: Jennifer Bryan + description: |- + Provides utilities for working with Google APIs + . This includes + functions and classes for handling common credential types and for + preparing, executing, and processing HTTP requests. + date_publication: '2023-07-20' + bug_reports: https://github.com/r-lib/gargle/issues + url: https://gargle.r-lib.org + url_cran: https://CRAN.R-project.org/package=gargle + url_git: https://github.com/r-lib/gargle +gargoyle: + version: 0.0.1 + title: An Event-Based Mechanism for 'Shiny' + maintainer: Colin Fay + description: |- + An event-Based framework for building 'Shiny' apps. + Instead of relying on standard 'Shiny' reactive objects, this + package allow to relying on a lighter set of triggers, so that + reactive contexts can be invalidated with more control. + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gargoyle + url_git: '' +garma: + version: 0.9.23 + title: Fitting and Forecasting Gegenbauer ARMA Time Series Models + maintainer: Richard Hunt + description: |- + Methods for estimating univariate long memory-seasonal/cyclical + Gegenbauer time series processes. See for example (2022) . + Refer to the vignette for details of fitting these processes. + date_publication: '2024-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=garma + url_git: https://github.com/rlph50/garma +garray: + version: 1.1.2 + title: |- + Generalized Array Arithmetic for Ragged Arrays with Named + Margins + maintainer: Qingsheng Huang + description: |- + Organize a so-called ragged array as generalized arrays, which + is simply an array with sub-dimensions denoting the subdivision of + dimensions (grouping of members within dimensions). + By the margins (names of dimensions and sub-dimensions) in generalized + arrays, operators and utility functions provided in this package + automatically match the margins, + doing map-reduce style parallel computation + along margins. Generalized arrays are also cooperative to R's native + functions that work on simple arrays. + date_publication: '2018-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=garray + url_git: '' +GAS: + version: 0.3.4.1 + title: Generalized Autoregressive Score Models + maintainer: Leopoldo Catania + description: |- + Simulate, estimate and forecast using univariate and multivariate GAS models + as described in Ardia et al. (2019) . + date_publication: '2024-08-19' + bug_reports: https://github.com/LeopoldoCatania/GAS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GAS + url_git: https://github.com/LeopoldoCatania/GAS +gasanalyzer: + version: 0.4.3 + title: Import, Recompute and Analyze Data from Portable Gas Analyzers + maintainer: Danny Tholen + description: |- + The gasanalyzer R package offers methods for importing, preprocessing, + and analyzing data related to photosynthetic characteristics (gas exchange, + chlorophyll fluorescence and isotope ratios). It translates variable names + into a standard format, and can recalculate derived, physiological + quantities using imported or predefined equations. The package also allows + users to assess the sensitivity of their results to different assumptions + used in the calculations. + See also Tholen (2024) . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gasanalyzer + url_git: https://gitlab.com/plantphys/gasanalyzer +gaselect: + version: 1.0.22 + title: |- + Genetic Algorithm (GA) for Variable Selection from + High-Dimensional Data + maintainer: David Kepplinger + description: |- + Provides a genetic algorithm for finding variable + subsets in high dimensional data with high prediction performance. The + genetic algorithm can use ordinary least squares (OLS) regression models or + partial least squares (PLS) regression models to evaluate the prediction + power of variable subsets. By supporting different cross-validation + schemes, the user can fine-tune the tradeoff between speed and quality of + the solution. + date_publication: '2023-12-11' + bug_reports: https://github.com/dakep/gaselect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gaselect + url_git: https://github.com/dakep/gaselect +gasfluxes: + version: '0.7' + title: Greenhouse Gas Flux Calculation from Chamber Measurements + maintainer: Roland Fuss + description: |- + Functions for greenhouse gas flux calculation from chamber + measurements. + date_publication: '2024-08-16' + bug_reports: '' + url: https://git-dmz.thuenen.de/fuss/gasfluxes + url_cran: https://CRAN.R-project.org/package=gasfluxes + url_git: '' +gasmodel: + version: 0.6.0 + title: Generalized Autoregressive Score Models + maintainer: Vladimír Holý + description: |- + Estimation, forecasting, and simulation of generalized + autoregressive score (GAS) models of Creal, Koopman, and Lucas (2013) + and Harvey (2013) . + Model specification allows for various data types and distributions, + different parametrizations, exogenous variables, joint and separate modeling + of exogenous variables and dynamics, higher score and autoregressive orders, + custom and unconditional initial values of time-varying parameters, fixed + and bounded values of coefficients, and missing values. Model estimation is + performed by the maximum likelihood method. + date_publication: '2024-02-02' + bug_reports: https://github.com/vladimirholy/gasmodel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gasmodel + url_git: https://github.com/vladimirholy/gasmodel +GaSP: + version: 1.0.6 + title: Train and Apply a Gaussian Stochastic Process Model + maintainer: William J. Welch + description: Train a Gaussian stochastic process model of an unknown function, possibly + observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, + run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., + Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", + Statistical Science, . Perform sensitivity analysis + and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), + "Screening the Input Variables to a Computer Model Via Analysis of Variance and + Visualization", . + date_publication: '2024-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GaSP + url_git: '' +gasper: + version: 1.1.6 + title: Graph Signal Processing + maintainer: Fabien Navarro + description: |- + Provides the standard operations for signal processing on graphs: + graph Fourier transform, spectral graph wavelet transform, + visualization tools. It also implements a data driven method + for graph signal denoising/regression, for details see + De Loynes, Navarro, Olivier (2019) . + The package also provides an interface to the SuiteSparse Matrix Collection, + , a large and widely used set of sparse matrix + benchmarks collected from a wide range of applications. + date_publication: '2024-02-28' + bug_reports: https://github.com/fabnavarro/gasper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gasper + url_git: https://github.com/fabnavarro/gasper +gastempt: + version: 0.7.0 + title: Analyzing Gastric Emptying from MRI or Scintigraphy + maintainer: Dieter Menne + description: |- + Fits gastric emptying time series from MRI or 'scintigraphic' measurements + using nonlinear mixed-model population fits with 'nlme' and Bayesian methods with + Stan; computes derived parameters such as t50 and AUC. + date_publication: '2024-12-20' + bug_reports: https://github.com/dmenne/gastempt/issues + url: http://dmenne.github.io/gastempt/ + url_cran: https://CRAN.R-project.org/package=gastempt + url_git: https://github.com/dmenne/gastempt +gaston: + version: '1.6' + title: Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models + maintainer: Hervé Perdry + description: Manipulation of genetic data (SNPs). Computation of GRM and dominance + matrix, LD, heritability with efficient algorithms for linear mixed model (AIREML). + Dandine et al . + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gaston + url_git: '' +gatepoints: + version: 0.1.5 + title: Easily Gate or Select Points on a Scatter Plot + maintainer: Wajid Jawaid + description: |- + Allows user to choose/gate a region on the plot and returns points + within it. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gatepoints + url_git: https://github.com/wjawaid/gatepoints +gateR: + version: 0.1.15 + title: Flow/Mass Cytometry Gating via Spatial Kernel Density Estimation + maintainer: Ian D. Buller + description: |- + Estimates statistically significant marker combination values within + which one immunologically distinctive group (i.e., disease case) is more associated than + another group (i.e., healthy control), successively, using various combinations (i.e., + "gates") of markers to examine features of cells that may be different between + groups. For a two-group comparison, the 'gateR' package uses the spatial relative risk + function estimated using the 'sparr' package. Details about the 'sparr' package + methods can be found in the tutorial: Davies et al. (2018) . Details + about kernel density estimation can be found in J. F. Bithell (1990) . + More information about relative risk functions using kernel density estimation can be + found in J. F. Bithell (1991) . + date_publication: '2024-01-23' + bug_reports: https://github.com/lance-waller-lab/gateR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gateR + url_git: https://github.com/lance-waller-lab/gateR +gatoRs: + version: 1.0.2 + title: Geographic and Taxonomic Occurrence R-Based Scrubbing + maintainer: Natalie N. Patten + description: Streamlines downloading and cleaning biodiversity data from Integrated + Digitized Biocollections (iDigBio) and the Global Biodiversity Information Facility + (GBIF). + date_publication: '2024-05-17' + bug_reports: https://github.com/nataliepatten/gatoRs/issues + url: https://nataliepatten.github.io/gatoRs/ + url_cran: https://CRAN.R-project.org/package=gatoRs + url_git: https://github.com/nataliepatten/gatoRs +GauPro: + version: 0.2.13 + title: Gaussian Process Fitting + maintainer: Collin Erickson + description: |- + Fits a Gaussian process model to data. Gaussian processes + are commonly used in computer experiments to fit an interpolating model. + The model is stored as an 'R6' object and can be easily updated with new + data. There are options to run in parallel, and 'Rcpp' + has been used to speed up calculations. + For more info about Gaussian process software, see Erickson et al. (2018) + . + date_publication: '2024-09-26' + bug_reports: https://github.com/CollinErickson/GauPro/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GauPro + url_git: https://github.com/CollinErickson/GauPro +gauseR: + version: '1.2' + title: Lotka-Volterra Models for Gause's 'Struggle for Existence' + maintainer: Adam Clark + description: 'A collection of tools and data for analyzing the Gause microcosm experiments, + and for fitting Lotka-Volterra models to time series data. Includes methods for + fitting single-species logistic growth, and multi-species interaction models, + e.g. of competition, predator/prey relationships, or mutualism. See documentation + for individual functions for examples. In general, see the lv_optim() function + for examples of how to fit parameter values in multi-species systems. Note that + the general methods applied here, as well as the form of the differential equations + that we use, are described in detail in the Quantitative Ecology textbook by Lehman + et al., available at , and in Lina K. Mühlbauer, + Maximilienne Schulze, W. Stanley Harpole, and Adam T. Clark. ''gauseR'': Simple + methods for fitting Lotka-Volterra models describing Gause''s ''Struggle for Existence'' + in the journal Ecology and Evolution.' + date_publication: '2023-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gauseR + url_git: '' +gausscov: + version: 1.1.5 + title: The Gaussian Covariate Method for Variable Selection + maintainer: Laurie Davies + description: 'The standard linear regression theory whether frequentist or Bayesian + is based on an ''assumed (revealed?) truth'' (John Tukey) attitude to models. This + is reflected in the language of statistical inference which involves a concept + of truth, for example confidence intervals, hypothesis testing and consistency. + The motivation behind this package was to remove the word true from the theory + and practice of linear regression and to replace it by approximation. The approximations + considered are the least squares approximations. An approximation is called valid + if it contains no irrelevant covariates. This is operationalized using the concept + of a Gaussian P-value which is the probability that pure Gaussian noise is better + in term of least squares than the covariate. The precise definition given in the + paper, it is intuitive and requires only four simple equations. Its overwhelming + advantage compared with a standard F P-value is that is is exact and valid whatever + the data. In contrast F P-values are only valid for specially designed simulations. + Given this a valid approximation is one where all the Gaussian P-values are less + than a threshold p0 specified by the statistician, in this package with the default + value 0.01. This approximations approach is not only much simpler it is overwhelmingly + better than the standard model based approach. The will be demonstrated using + six real data sets, four from high dimensional regression and two from vector + autoregression. The simplicity and superiority of Gaussian P-values derive from + their universal exactness and validity. This is in complete contrast to standard + F P-values which are valid only for carefully designed simulations. The function + f1st is the most important function. It is a greedy forward selection procedure + which results in either just one or no approximations which may however not be + valid. If the size is less than than a threshold with default value 21 then an + all subset procedure is called which returns the best valid subset. A good default + start is f1st(y,x,kmn=15) The best function for returning multiple approximations + is f3st which repeatedly calls f1st. For more information see the web site below + and the accompanying papers: L. Davies and L. Duembgen, "Covariate Selection Based + on a Model-free Approach to Linear Regression with Exact Probabilities", , + L. Davies, "An Approximation Based Theory of Linear Regression", 2024, .' + date_publication: '2025-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gausscov + url_git: '' +gaussDiff: + version: '1.1' + title: |- + Difference measures for multivariate Gaussian probability + density functions + maintainer: Henning Rust + description: |- + A collection difference measures for multivariate Gaussian + probability density functions, such as the Euclidea mean, the + Mahalanobis distance, the Kullback-Leibler divergence, the + J-Coefficient, the Minkowski L2-distance, the Chi-square + divergence and the Hellinger Coefficient. + date_publication: '2012-08-23' + bug_reports: '' + url: www.geo.fu-berlin.de/met/ag/clidia/Mitarbeiter/HenningRust/ + url_cran: https://CRAN.R-project.org/package=gaussDiff + url_git: '' +gaussfacts: + version: 0.0.2 + title: The Greatest Mathematician Since Antiquity + maintainer: Dirk Eddelbuettel + description: |- + Display a random fact about Carl Friedrich Gauss + based the on collection curated by Mike Cavers via the + site. + date_publication: '2016-08-03' + bug_reports: https://github.com/eddelbuettel/gaussfacts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gaussfacts + url_git: '' +GaussianHMM1d: + version: 1.1.2 + title: |- + Inference, Goodness-of-Fit and Forecast for Univariate Gaussian + Hidden Markov Models + maintainer: Bouchra R. Nasri + description: Inference, goodness-of-fit test, and prediction densities and intervals + for univariate Gaussian Hidden Markov Models (HMM). The goodness-of-fit is based + on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the + p-value. The description of the methodology is taken from Chapter 10.2 of Remillard + (2013) . + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GaussianHMM1d + url_git: '' +gaussplotR: + version: 0.2.5 + title: Fit, Predict and Plot 2D Gaussians + maintainer: Vikram B. Baliga + description: |2- + + Functions to fit two-dimensional Gaussian functions, predict values from + fits, and produce plots of predicted data via either 'ggplot2' or base R + plotting. + date_publication: '2021-05-02' + bug_reports: https://github.com/vbaliga/gaussplotR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gaussplotR + url_git: https://github.com/vbaliga/gaussplotR +gaussquad: + version: 1.0-3 + title: Collection of Functions for Gaussian Quadrature + maintainer: Frederick Novomestky + description: |- + A collection of functions to perform Gaussian quadrature + with different weight functions corresponding to the orthogonal + polynomials in package orthopolynom. Examples verify the + orthogonality and inner products of the polynomials. + date_publication: '2022-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gaussquad + url_git: '' +gaussratiovegind: + version: 1.0.1 + title: Distribution of Gaussian Ratios + maintainer: Pierre Santagostini + description: |- + It is well known that the distribution of a Gaussian ratio + does not follow a Gaussian distribution. + The lack of awareness among users of vegetation indices about this + non-Gaussian nature could lead to incorrect statistical modeling + and interpretation. + This package provides tools to accurately handle and analyse such + ratios: density function, parameter estimation, simulation. + An example on the study of chlorophyll fluorescence can be found in + A. El Ghaziri et al. (2023) . + date_publication: '2025-02-11' + bug_reports: https://forgemia.inra.fr/imhorphen/gaussratiovegind/-/issues + url: https://forgemia.inra.fr/imhorphen/gaussratiovegind + url_cran: https://CRAN.R-project.org/package=gaussratiovegind + url_git: '' +GaussSuppression: + version: 0.9.5 + title: Tabular Data Suppression using Gaussian Elimination + maintainer: Øyvind Langsrud + description: |- + A statistical disclosure control tool to protect tables by suppression + using the Gaussian elimination secondary suppression algorithm + (Langsrud, 2024) . A suggestion is + to start by working with functions SuppressSmallCounts() and + SuppressDominantCells(). These functions use primary suppression functions for + the minimum frequency rule and the dominance rule, respectively. Novel + functionality for suppression of disclosive cells is also included. General + primary suppression functions can be supplied as input to the general working + horse function, GaussSuppressionFromData(). Suppressed frequencies can be + replaced by synthetic decimal numbers as described in + Langsrud (2019) . + date_publication: '2025-02-07' + bug_reports: https://github.com/statisticsnorway/ssb-gausssuppression/issues + url: https://statisticsnorway.github.io/ssb-gausssuppression/ + url_cran: https://CRAN.R-project.org/package=GaussSuppression + url_git: https://github.com/statisticsnorway/ssb-gausssuppression +gawdis: + version: 0.1.5 + title: Multi-Trait Dissimilarity with more Uniform Contributions + maintainer: Pavel Fibich + description: R function gawdis() produces multi-trait dissimilarity with more uniform + contributions of different traits. de Bello et al. (2021) + presented the approach based on minimizing the differences in the correlation + between the dissimilarity of each trait, or groups of traits, and the multi-trait + dissimilarity. This is done using either an analytic or a numerical solution, + both available in the function. + date_publication: '2023-05-03' + bug_reports: https://github.com/pavel-fibich/gawdis/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=gawdis + url_git: https://github.com/pavel-fibich/gawdis/ +gb: + version: 2.3.3 + title: Generalize Lambda Distribution and Generalized Bootstrapping + maintainer: Bin Wang + description: |- + A collection of algorithms and functions + for fitting data to a generalized lambda distribution + via moment matching methods, and generalized + bootstrapping. + date_publication: '2018-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gb + url_git: '' +GB2: + version: 2.1.1 + title: |- + Generalized Beta Distribution of the Second Kind: Properties, + Likelihood, Estimation + maintainer: Desislava Nedyalkova + description: Package GB2 explores the Generalized Beta distribution of the second + kind. Density, cumulative distribution function, quantiles and moments of the + distributions are given. Functions for the full log-likelihood, the profile log-likelihood + and the scores are provided. Formulas for various indicators of inequality and + poverty under the GB2 are implemented. The GB2 is fitted by the methods of maximum + pseudo-likelihood estimation using the full and profile log-likelihood, and non-linear + least squares estimation of the model parameters. Various plots for the visualization + and analysis of the results are provided. Variance estimation of the parameters + is provided for the method of maximum pseudo-likelihood estimation. A mixture + distribution based on the compounding property of the GB2 is presented (denoted + as "compound" in the documentation). This mixture distribution is based on the + discretization of the distribution of the underlying random scale parameter. The + discretization can be left or right tail. Density, cumulative distribution function, + moments and quantiles for the mixture distribution are provided. The compound + mixture distribution is fitted using the method of maximum pseudo-likelihood estimation. + The fit can also incorporate the use of auxiliary information. In this new version + of the package, the mixture case is complemented with new functions for variance + estimation by linearization and comparative density plots. + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GB2 + url_git: '' +GB2group: + version: 0.3.0 + title: |- + Estimation of the Generalised Beta Distribution of the Second + Kind from Grouped Data + maintainer: Vanesa Jorda + description: |- + Estimation of the generalized beta distribution of the second + kind (GB2) and related models using grouped data in form of income shares. + The GB2 family is a general class of distributions that provides an accurate + fit to income data. 'GB2group' includes functions to estimate the GB2, the + Singh-Maddala, the Dagum, the Beta 2, the Lognormal and the Fisk distributions. + 'GB2group' deploys two different econometric strategies to estimate these + parametric distributions, the equally weighted minimum distance (EWMD) estimator and the + optimally weighted minimum distance (OMD) estimator. Asymptotic standard errors are reported for the + OMD estimates. Standard errors of the EWMD estimates are obtained by Monte + Carlo simulation. See Jorda et al. (2018) for a detailed + description of the estimation procedure. + date_publication: '2021-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GB2group + url_git: '' +GB5mcPred: + version: 0.1.0 + title: Gradient Boosting Algorithm for Predicting Methylation States + maintainer: Dipro Sinha + description: DNA methylation of 5-methylcytosine (5mC) is the result of a multi-step, + enzyme-dependent process. Predicting these sites in-vitro is laborious, time consuming + as well as costly. This ' Gb5mC-Pred ' package is an in-silico pipeline for predicting + DNA sequences containing the 5mC sites. It uses a machine learning approach which + uses Stochastic Gradient Boosting approach for prediction of the sequences with + 5mC sites. This package has been developed by using the concept of Navarez and + Roxas (2022) . + date_publication: '2023-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GB5mcPred + url_git: '' +gbeta: + version: 0.1.0 + title: Generalized Beta and Beta Prime Distributions + maintainer: Stéphane Laurent + description: 'Density, distribution function, quantile function, and random generation + for the generalized Beta and Beta prime distributions. The family of generalized + Beta distributions is conjugate for the Bayesian binomial model, and the generalized + Beta prime distribution is the posterior distribution of the relative risk in + the Bayesian ''two Poisson samples'' model when a Gamma prior is assigned to the + Poisson rate of the reference group and a Beta prime prior is assigned to the + relative risk. References: Laurent (2012) , Hamza & Vallois + (2016) , Chen & Novick (1984) .' + date_publication: '2020-11-19' + bug_reports: https://github.com/stla/gbeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gbeta + url_git: https://github.com/stla/gbeta +gbfs: + version: 1.3.10 + title: Interface with Live Bikeshare Data + maintainer: Simon P. Couch + description: |- + Supplies a set of functions to interface with bikeshare data + following the General Bikeshare Feed Specification, allowing users to query + and accumulate tidy datasets for specified cities/bikeshare programs. + date_publication: '2025-01-13' + bug_reports: https://github.com/simonpcouch/gbfs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gbfs + url_git: https://github.com/simonpcouch/gbfs +gbifdb: + version: 1.0.0 + title: High Performance Interface to 'GBIF' + maintainer: Carl Boettiger + description: |- + A high performance interface to the Global Biodiversity + Information Facility, 'GBIF'. In contrast to 'rgbif', which can + access small subsets of 'GBIF' data through web-based queries to + a central server, 'gbifdb' provides enhanced performance for R users + performing large-scale analyses on servers and cloud computing + providers, providing full support for arbitrary 'SQL' or 'dplyr' + operations on the complete 'GBIF' data tables (now over 1 billion + records, and over a terabyte in size). 'gbifdb' accesses a copy + of the 'GBIF' data in 'parquet' format, which is already readily + available in commercial computing clouds such as the Amazon Open + Data portal and the Microsoft Planetary Computer, or can be + accessed directly without downloading, or downloaded + to any server with suitable bandwidth and storage space. + The high-performance techniques for local and remote access + are described in + and respectively. + date_publication: '2023-10-19' + bug_reports: https://github.com/ropensci/gbifdb + url: https://docs.ropensci.org/gbifdb/ + url_cran: https://CRAN.R-project.org/package=gbifdb + url_git: https://github.com/ropensci/gbifdb +GBJ: + version: 0.5.4 + title: |- + Generalized Berk-Jones Test for Set-Based Inference in Genetic + Association Studies + maintainer: Ryan Sun + description: |- + Offers the Generalized Berk-Jones (GBJ) test for set-based inference in genetic + association studies. The GBJ is designed as an alternative to tests such as Berk-Jones (BJ), + Higher Criticism (HC), Generalized Higher Criticism (GHC), Minimum p-value (minP), and Sequence + Kernel Association Test (SKAT). All of these other methods (except for SKAT) are also implemented + in this package, and we additionally provide an omnibus test (OMNI) which integrates information from each of the tests. + The GBJ has been shown to outperform other tests in genetic association studies when signals + are correlated and moderately sparse. Please see the vignette for a quickstart guide or Sun and Lin + (2017) for more details. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GBJ + url_git: '' +gbm: + version: 2.2.2 + title: Generalized Boosted Regression Models + maintainer: Greg Ridgeway + description: |- + An implementation of extensions to Freund and Schapire's AdaBoost + algorithm and Friedman's gradient boosting machine. Includes regression + methods for least squares, absolute loss, t-distribution loss, quantile + regression, logistic, multinomial logistic, Poisson, Cox proportional hazards + partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and + Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway. + Newer version available at github.com/gbm-developers/gbm3. + date_publication: '2024-06-28' + bug_reports: https://github.com/gbm-developers/gbm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gbm + url_git: https://github.com/gbm-developers/gbm +gbm.auto: + version: 2024.10.01 + title: Automated Boosted Regression Tree Modelling and Mapping Suite + maintainer: Simon Dedman + description: |- + Automates delta log-normal boosted regression tree abundance + prediction. Loops through parameters provided (LR (learning rate), TC + (tree complexity), BF (bag fraction)), chooses best, simplifies, & + generates line, dot & bar plots, & outputs these & predictions & a + report, makes predicted abundance maps, and Unrepresentativeness + surfaces. Package core built around 'gbm' (gradient boosting machine) + functions in 'dismo' (Hijmans, Phillips, Leathwick & Jane Elith, 2020 + & ongoing), itself built around 'gbm' (Greenwell, Boehmke, Cunningham + & Metcalfe, 2020 & ongoing, originally by Ridgeway). Indebted to + Elith/Leathwick/Hastie 2008 'Working Guide' + ; workflow follows Appendix S3. + See for published guides and papers + using this package. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gbm.auto + url_git: '' +gbm2sas: + version: '3.0' + title: Convert GBM Object Trees to SAS Code + maintainer: John R. Dixon + description: Writes SAS code to get predicted values from every tree of a gbm.object. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gbm2sas + url_git: '' +gbmt: + version: 0.1.4 + title: Group-Based Multivariate Trajectory Modeling + maintainer: Alessandro Magrini + description: Estimation and analysis of group-based multivariate trajectory models + (Nagin, 2018 ; Magrini, 2022 ). + The package implements an Expectation-Maximization (EM) algorithm allowing unbalanced + panel and missing values, and provides several functionalities for prediction + and graphical representation. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gbmt + url_git: '' +gbp: + version: 0.1.0.4 + title: A Bin Packing Problem Solver + maintainer: Guang Yang + description: |- + Basic infrastructure and several algorithms for 1d-4d bin packing + problem. This package provides a set of c-level classes and solvers for + 1d-4d bin packing problem, and an r-level solver for 4d bin packing problem, + which is a wrapper over the c-level 4d bin packing problem solver. + The 4d bin packing problem solver aims to solve bin packing problem, a.k.a + container loading problem, with an additional constraint on weight. + Given a set of rectangular-shaped items, and a set of rectangular-shaped bins + with weight limit, the solver looks for an orthogonal packing solution + such that minimizes the number of bins and maximize volume utilization. + Each rectangular-shaped item i = 1, .. , n is characterized by length l_i, + depth d_i, height h_i, and weight w_i, and each rectangular-shaped bin + j = 1, .. , m is specified similarly by length l_j, depth d_j, height h_j, + and weight limit w_j. + The item can be rotated into any orthogonal direction, and no further + restrictions implied. + date_publication: '2017-01-28' + bug_reports: https://github.com/gyang274/gbp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gbp + url_git: https://github.com/gyang274/gbp +gbRd: + version: 0.4.12 + title: Utilities for Processing Rd Objects and Files + maintainer: Georgi N. Boshnakov + description: |- + Provides utilities for processing Rd objects and files. + Extract argument descriptions and other parts of the help pages of + functions. + date_publication: '2024-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gbRd + url_git: '' +gbs2ploidy: + version: '1.0' + title: Inference of Ploidy from (Genotyping-by-Sequencing) GBS Data + maintainer: Zachariah Gompert + description: Functions for inference of ploidy from (Genotyping-by-sequencing) GBS + data, including a function to infer allelic ratios and allelic proportions in + a Bayesian framework. + date_publication: '2016-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gbs2ploidy + url_git: '' +gbts: + version: 1.2.0 + title: Hyperparameter Search for Gradient Boosted Trees + maintainer: Waley W. J. Liang + description: |- + An implementation of hyperparameter optimization for Gradient + Boosted Trees on binary classification and regression problems. The current + version provides two optimization methods: Bayesian optimization and random + search. Instead of giving the single best model, the final output is an + ensemble of Gradient Boosted Trees constructed via the method of ensemble + selection. + date_publication: '2017-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gbts + url_git: '' +gbutils: + version: '0.5' + title: |- + Utilities for Simulation, Plots, Quantile Functions and + Programming + maintainer: Georgi N. Boshnakov + description: |- + Plot density and distribution functions with automatic selection of + suitable regions. Numerically invert (compute quantiles) distribution + functions. Simulate real and complex numbers from distributions of their + magnitude and arguments. Optionally, the magnitudes and/or arguments may + be fixed in almost arbitrary ways. Create polynomials from roots given in + Cartesian or polar form. Small programming utilities: check if an object + is identical to NA, count positional arguments in a call, set + intersection of more than two sets, check if an argument is unnamed, + compute the graph of S4 classes in packages. + date_publication: '2022-05-27' + bug_reports: https://github.com/GeoBosh/gbutils/issues + url: https://geobosh.github.io/gbutils/(website) + url_cran: https://CRAN.R-project.org/package=gbutils + url_git: https://github.com/GeoBosh/gbutils(devel) +GCalcium: + version: 1.0.0 + title: |- + A Data Manipulation and Analysis Package for Calcium Indicator + Data + maintainer: Andrew Tamalunas + description: Provides shortcuts in extracting useful data points and summarizing + waveform data. It is optimized for speed to work efficiently with large data sets + so you can get to the analysis phase more quickly. It also utilizes a user-friendly + format for use by both beginners and seasoned R users. + date_publication: '2019-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GCalcium + url_git: '' +GCalignR: + version: 1.0.7 + title: Simple Peak Alignment for Gas-Chromatography Data + maintainer: Meinolf Ottensmann + description: |- + Aligns peak based on peak retention times and matches homologous peaks + across samples. The underlying alignment procedure comprises three sequential steps. + (1) Full alignment of samples by linear transformation of retention times to + maximise similarity among homologous peaks (2) Partial alignment of peaks within + a user-defined retention time window to cluster homologous peaks (3) Merging rows + that are likely representing homologous substances (i.e. no sample shows peaks in + both rows and the rows have similar retention time means). The algorithm is described in detail + in Ottensmann et al., 2018 . + date_publication: '2024-07-03' + bug_reports: https://github.com/mottensmann/GCalignR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GCalignR + url_git: https://github.com/mottensmann/GCalignR +gCat: + version: '0.2' + title: Graph-Based Two-Sample Tests for Categorical Data + maintainer: Hao Chen + description: These are two-sample tests for categorical data utilizing similarity + information among the categories. They are useful when there is underlying structure + on the categories. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gCat + url_git: '' +gcbd: + version: 0.2.7 + title: '''GPU''/CPU Benchmarking in Debian-Based Systems' + maintainer: Dirk Eddelbuettel + description: |- + 'GPU'/CPU Benchmarking on Debian-package based systems + This package benchmarks performance of a few standard linear algebra + operations (such as a matrix product and QR, SVD and LU decompositions) + across a number of different 'BLAS' libraries as well as a 'GPU' implementation. + To do so, it takes advantage of the ability to 'plug and play' different + 'BLAS' implementations easily on a Debian and/or Ubuntu system. The current + version supports + - 'Reference BLAS' ('refblas') which are un-accelerated as a baseline + - Atlas which are tuned but typically configure single-threaded + - Atlas39 which are tuned and configured for multi-threaded mode + - 'Goto Blas' which are accelerated and multi-threaded + - 'Intel MKL' which is a commercial accelerated and multithreaded version. + As for 'GPU' computing, we use the CRAN package + - 'gputools' + For 'Goto Blas', the 'gotoblas2-helper' script from the ISM in Tokyo can be + used. For 'Intel MKL' we use the Revolution R packages from Ubuntu 9.10. + date_publication: '2024-10-29' + bug_reports: https://github.com/eddelbuettel/gcbd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gcbd + url_git: https://github.com/eddelbuettel/gcbd +GCCfactor: + version: 1.0.1 + title: GCC Estimation of the Multilevel Factor Model + maintainer: Rui Lin + description: |- + Provides methods for model selection, estimation, bootstrap inference, and simulation for the + multilevel factor model, based on the principal component estimation and generalised + canonical correlation approach. Details can be found in "Generalised Canonical Correlation + Estimation of the Multilevel Factor Model." Lin and Shin (2023) . + date_publication: '2023-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GCCfactor + url_git: '' +GCD: + version: 4.0.7 + title: Global Charcoal Database + maintainer: Olivier Blarquez + description: |- + Contains the Global Charcoal database data. Data include charcoal + series (age, depth, charcoal quantity, associated units and methods) and + information on sedimentary sites (localisation, depositional environment, biome, + etc.) as well as publications informations. Since 4.0.0 the GCD mirrors the online SQL database at . + date_publication: '2020-10-26' + bug_reports: '' + url: http://paleofire.org + url_cran: https://CRAN.R-project.org/package=GCD + url_git: '' +gcdnet: + version: 1.0.6 + title: |- + The (Adaptive) LASSO and Elastic Net Penalized Least Squares, + Logistic Regression, Hybrid Huberized Support Vector Machines, + Squared Hinge Loss Support Vector Machines and Expectile + Regression using a Fast Generalized Coordinate Descent + Algorithm + maintainer: Yi Yang + description: |- + Implements a generalized coordinate descent (GCD) algorithm + for computing the solution paths of the hybrid Huberized support vector + machine (HHSVM) and its generalizations. Supported models include the + (adaptive) LASSO and elastic net penalized least squares, logistic + regression, HHSVM, squared hinge loss SVM and expectile regression. + date_publication: '2022-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcdnet + url_git: https://github.com/emeryyi/gcdnet +gcerisk: + version: 19.05.24 + title: Generalized Competing Event Model + maintainer: Hanjie Shen + description: |- + Generalized competing event model based on Cox PH model and Fine-Gray model. + This function is designed to develop optimized risk-stratification methods for competing + risks data, such as described in: + 1. Carmona R, Gulaya S, Murphy JD, Rose BS, Wu J, Noticewala S,McHale MT, Yashar CM, Vaida F, + and Mell LK (2014) . + 2. Carmona R, Zakeri K, Green G, Hwang L, Gulaya S, Xu B, Verma R, Williamson CW, Triplett DP, Rose + BS, Shen H, Vaida F, Murphy JD, and Mell LK (2016) . + 3. Lunn, Mary, and Don McNeil (1995) . + date_publication: '2019-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcerisk + url_git: '' +gcite: + version: 0.10.1 + title: Google Citation Parser + maintainer: John Muschelli + description: |- + Scrapes Google Citation pages and creates data frames of + citations over time. + date_publication: '2019-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcite + url_git: '' +gcKrig: + version: 1.1.8 + title: Analysis of Geostatistical Count Data using Gaussian Copulas + maintainer: Zifei Han + description: |- + Provides a variety of functions to analyze and model + geostatistical count data with Gaussian copulas, including + 1) data simulation and visualization; + 2) correlation structure assessment (here also known as the Normal To Anything); + 3) calculate multivariate normal rectangle probabilities; + 4) likelihood inference and parallel prediction at predictive locations. + Description of the method is available from: Han and DeOliveira (2018) . + date_publication: '2022-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcKrig + url_git: '' +gclm: + version: 0.0.1 + title: Graphical Continuous Lyapunov Models + maintainer: Gherardo Varando + description: |- + Estimation of covariance matrices as solutions of + continuous time Lyapunov equations. + Sparse coefficient matrix and diagonal noise are estimated + with a proximal gradient + method for an l1-penalized loss minimization problem. + Varando G, Hansen NR (2020) . + date_publication: '2020-06-04' + bug_reports: https://github.com/gherardovarando/gclm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gclm + url_git: https://github.com/gherardovarando/gclm +gclus: + version: 1.3.2 + title: Clustering Graphics + maintainer: Catherine Hurley + description: |- + Orders panels in scatterplot matrices and parallel coordinate + displays by some merit index. Package contains various indices of merit, + ordering functions, and enhanced versions of pairs and parcoord which + color panels according to their merit level. + date_publication: '2019-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gclus + url_git: '' +gcmr: + version: 1.0.3 + title: Gaussian Copula Marginal Regression + maintainer: Cristiano Varin + description: |- + Likelihood inference in Gaussian copula marginal + regression models. + date_publication: '2022-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcmr + url_git: '' +gconsensus: + version: 0.3.2 + title: Consensus Value Constructor + maintainer: Hugo Gasca-Aragon + description: An implementation of the International Bureau of Weights and Measures + (BIPM) generalized consensus estimators used to assign the reference value in + a key comparison exercise. This can also be applied to any interlaboratory study. + Given a set of different sources, primary laboratories or measurement methods + this package provides an evaluation of the variance components according to the + selected statistical method for consensus building. It also implements the comparison + among different consensus builders and evaluates the participating method or sources + against the consensus reference value. Based on a diverse set of references, DerSimonian-Laird + (1986) , for a complete list of references look + at the reference section in the package documentation. + date_publication: '2022-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gconsensus + url_git: '' +gcookbook: + version: '2.0' + title: Data for "R Graphics Cookbook" + maintainer: Winston Chang + description: |- + Data sets used in the book "R Graphics Cookbook" by Winston + Chang, published by O'Reilly Media. + date_publication: '2018-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcookbook + url_git: '' +GCPBayes: + version: 4.2.0 + title: |- + Bayesian Meta-Analysis of Pleiotropic Effects Using Group + Structure + maintainer: Yazdan Asgari + description: 'Run a Gibbs sampler for a multivariate Bayesian sparse group selection + model with Dirac, continuous and hierarchical spike prior for detecting pleiotropy + on the traits. This package is designed for summary statistics containing estimated + regression coefficients and its estimated covariance matrix. The methodology is + available from: Baghfalaki, T., Sugier, P. E., Truong, T., Pettitt, A. N., Mengersen, + K., & Liquet, B. (2021) .' + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GCPBayes + url_git: https://github.com/tbaghfalaki/GCPBayes +gcplyr: + version: 1.11.0 + title: Wrangle and Analyze Growth Curve Data + maintainer: Mike Blazanin + description: |- + Easy wrangling and model-free analysis of + microbial growth curve data, as commonly output by plate readers. + Tools for reshaping common plate reader outputs into 'tidy' formats and + merging them with design information, making data easy to work with using + 'gcplyr' and other packages. Also streamlines common growth curve + processing steps, like smoothing and calculating derivatives, and + facilitates model-free characterization and analysis of growth data. + See methods at . + date_publication: '2025-01-17' + bug_reports: '' + url: https://mikeblazanin.github.io/gcplyr/ + url_cran: https://CRAN.R-project.org/package=gcplyr + url_git: https://github.com/mikeblazanin/gcplyr/ +GCPM: + version: 1.2.2 + title: Generalized Credit Portfolio Model + maintainer: Kevin Jakob + description: |- + Analyze the default risk of credit portfolios. Commonly known models, + like CreditRisk+ or the CreditMetrics model are implemented in their very basic settings. + The portfolio loss distribution can be achieved either by simulation or analytically + in case of the classic CreditRisk+ model. Models are only implemented to respect losses + caused by defaults, i.e. migration risk is not included. The package structure is kept + flexible especially with respect to distributional assumptions in order to quantify the + sensitivity of risk figures with respect to several assumptions. Therefore the package + can be used to determine the credit risk of a given portfolio as well as to quantify + model sensitivities. + date_publication: '2016-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GCPM + url_git: '' +GCSM: + version: 0.1.1 + title: Implements Generic Composite Similarity Measure + maintainer: Yadong Liu + description: |- + Provides implementation of the generic composite similarity measure + (GCSM) described in Liu et al. (2020) . The + implementation is in C++ and uses 'RcppArmadillo'. Additionally, implementations + of the structural similarity (SSIM) and the composite similarity measure based + on means, standard deviations, and correlation coefficient (CMSC), are included. + date_publication: '2021-03-27' + bug_reports: https://github.com/liuyadong/GCSM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GCSM + url_git: https://github.com/liuyadong/GCSM +gcTensor: + version: 1.0.0 + title: Generalized Coupled Tensor Factorization + maintainer: Koki Tsuyuzaki + description: Multiple matrices/tensors can be specified and decomposed simultaneously + by Probabilistic Latent Tensor Factorisation (PLTF). See the reference section + of GitHub README.md , for details of the + method. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcTensor + url_git: https://github.com/rikenbit/gcTensor +gcxgclab: + version: 1.0.1 + title: GCxGC Preprocessing and Analysis + maintainer: Stephanie Gamble + description: Provides complete detailed preprocessing of two-dimensional gas chromatogram + (GCxGC) samples. Baseline correction, smoothing, peak detection, and peak alignment. + Also provided are some analysis functions, such as finding extracted ion chromatograms, + finding mass spectral data, targeted analysis, and nontargeted analysis with either + the 'National Institute of Standards and Technology Mass Spectral Library' or + with the mass data. There are also several visualization methods provided for + each step of the preprocessing and analysis. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gcxgclab + url_git: '' +GD: + version: '10.8' + title: Geographical Detectors for Assessing Spatial Factors + maintainer: Wenbo Lv + description: |- + Geographical detectors for measuring spatial stratified heterogeneity, + as described in Jinfeng Wang (2010) and + Jinfeng Wang (2016) . Includes the + optimal discretization of continuous data, four primary functions of + geographical detectors, comparison of size effects of spatial unit and + the visualizations of results. To use the package and to refer the + descriptions of the package, methods and case datasets, please cite + Yongze Song (2020) . The model has + been applied in factor exploration of road performance and multi-scale + spatial segmentation for network data, as described in + Yongze Song (2018) and + Yongze Song (2020) , respectively. + date_publication: '2024-11-20' + bug_reports: https://github.com/ausgis/GD/issues + url: https://ausgis.github.io/GD/ + url_cran: https://CRAN.R-project.org/package=GD + url_git: https://github.com/ausgis/GD +GDAdata: + version: '0.93' + title: Datasets for the Book Graphical Data Analysis with R + maintainer: Antony Unwin + description: Datasets used in the book 'Graphical Data Analysis with R' (Antony + Unwin, CRC Press 2015). + date_publication: '2015-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GDAdata + url_git: '' +gdalcubes: + version: 0.7.0 + title: Earth Observation Data Cubes from Satellite Image Collections + maintainer: Marius Appel + description: |- + Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users + define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and + resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, + applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, + exporting data cubes as 'netCDF' or 'GeoTIFF' files, plotting, and extraction from spatial and or spatiotemporal features. + All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. + See Appel and Pebesma (2019) for further details. + date_publication: '2024-03-07' + bug_reports: https://github.com/appelmar/gdalcubes/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=gdalcubes + url_git: https://github.com/appelmar/gdalcubes +gdalraster: + version: 1.12.0 + title: Bindings to the 'Geospatial Data Abstraction Library' Raster API + maintainer: Chris Toney + description: |- + Interface to the Raster API of the 'Geospatial Data Abstraction + Library' ('GDAL', ). Bindings are implemented in an + exposed C++ class encapsulating a 'GDALDataset' and its raster band + objects, along with several stand-alone functions. These support manual + creation of uninitialized datasets, creation from existing raster as + template, read/set dataset parameters, low level I/O, color tables, raster + attribute tables, virtual raster (VRT), and 'gdalwarp' wrapper for + reprojection and mosaicing. Includes 'GDAL' algorithms ('dem_proc()', + 'polygonize()', 'rasterize()', etc.), and functions for coordinate + transformation and spatial reference systems. Calling signatures resemble + the native C, C++ and Python APIs provided by the 'GDAL' project. Includes + raster 'calc()' to evaluate a given R expression on a layer or stack of + layers, with pixel x/y available as variables in the expression; and raster + 'combine()' to identify and count unique pixel combinations across multiple + input layers, with optional output of the pixel-level combination IDs. + Provides raster display using base 'graphics'. Bindings to a subset of the + 'OGR' API are also included for managing vector data sources. Bindings to a + subset of the Virtual Systems Interface ('VSI') are also included to support + operations on 'GDAL' virtual file systems. These are general utility + functions that abstract file system operations on URLs, cloud storage + services, 'Zip'/'GZip'/'7z'/'RAR' archives, and in-memory files. + 'gdalraster' may be useful in applications that need scalable, low-level + I/O, or prefer a direct 'GDAL' API. + date_publication: '2025-01-19' + bug_reports: https://github.com/USDAForestService/gdalraster/issues + url: https://usdaforestservice.github.io/gdalraster/ + url_cran: https://CRAN.R-project.org/package=gdalraster + url_git: https://github.com/USDAForestService/gdalraster +gdalUtilities: + version: 1.2.5 + title: Wrappers for 'GDAL' Utilities Executables + maintainer: Joshua O'Brien + description: |- + R's 'sf' package ships with self-contained 'GDAL' + executables, including a bare bones interface to several + 'GDAL'-related utility programs collectively known as the 'GDAL + utilities'. For each of those utilities, this package provides an + R wrapper whose formal arguments closely mirror those of the + 'GDAL' command line interface. The utilities operate on data + stored in files and typically write their output to other + files. Therefore, to process data stored in any of R's more common + spatial formats (i.e. those supported by the 'sf' and 'terra' + packages), first write them to disk, then process them with the + package's wrapper functions before reading the outputted results + back into R. GDAL function arguments introduced in GDAL version + 3.5.2 or earlier are supported. + date_publication: '2023-08-10' + bug_reports: https://github.com/JoshOBrien/gdalUtilities/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=gdalUtilities + url_git: https://github.com/JoshOBrien/gdalUtilities/ +gdata: + version: 3.0.1 + title: Various R Programming Tools for Data Manipulation + maintainer: Arni Magnusson + description: |- + Various R programming tools for data manipulation, including + medical unit conversions, combining objects, character vector operations, + factor manipulation, obtaining information about R objects, generating + fixed-width format files, extracting components of date & time objects, + operations on columns of data frames, matrix operations, operations on + vectors, operations on data frames, value of last evaluated expression, and a + resample() wrapper for sample() that ensures consistent behavior for both + scalar and vector arguments. + date_publication: '2024-10-22' + bug_reports: https://github.com/r-gregmisc/gdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gdata + url_git: https://github.com/r-gregmisc/gdata +GDAtools: + version: '2.1' + title: Geometric Data Analysis + maintainer: Nicolas Robette + description: Many tools for Geometric Data Analysis (Le Roux & Rouanet (2005) ), + such as MCA variants (Specific Multiple Correspondence Analysis, Class Specific + Analysis), many graphical and statistical aids to interpretation (structuring + factors, concentration ellipses, inductive tests, bootstrap validation, etc.) + and multiple-table analysis (Multiple Factor Analysis, between- and inter-class + analysis, Principal Component Analysis and Correspondence Analysis with Instrumental + Variables, etc.). + date_publication: '2024-03-07' + bug_reports: https://github.com/nicolas-robette/GDAtools/issues + url: https://nicolas-robette.github.io/GDAtools/ + url_cran: https://CRAN.R-project.org/package=GDAtools + url_git: https://github.com/nicolas-robette/GDAtools +gde: + version: 0.2.1 + title: GBIF Dataset Explorer + maintainer: Luis J Villanueva + description: Functions to explore datasets from the Global Biodiversity Information + Facility (GBIF - ) using a Shiny interface. + date_publication: '2023-03-20' + bug_reports: https://github.com/Smithsonian/GBIF-Dataset-Explorer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gde + url_git: https://github.com/Smithsonian/GBIF-Dataset-Explorer +GDELTtools: + version: '1.7' + title: |- + Download, Slice, and Normalize GDELT V1 Event and Sentiment API + Data + maintainer: Stephen R. Haptonstahl + description: |- + The GDELT V1 Event data set is over 41 GB now and growing 250 MB + a month. The number of source articles has increased over time and unevenly + across countries. This package makes it easy to download a subset of that + data, then normalize that data to facilitate valid time series analysis. + date_publication: '2023-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GDELTtools + url_git: '' +gdi: + version: 1.6.0 + title: Volumetric Analysis using Graphic Double Integration + maintainer: Darius Nau + description: Tools implementing an automated version of the graphic double integration + technique (GDI) for volume implementation, and some other related utilities for + paleontological image-analysis. GDI was first employed by Jerison (1973) + and Hurlburt (1999) and is primarily used + for volume or mass estimation of (extinct) animals. The package 'gdi' aims to + make this technique as convenient and versatile as possible. The core functions + of 'gdi' provide utilities for automatically measuring diameters from digital + silhouettes provided as image files and calculating volume via graphic double + integration with simple elliptical, superelliptical (following Motani 2001 ) + or complex cross-sectional models. Additionally, the package provides functions + for estimating the center of mass position (COM), the moment of inertia (I) for + 3D shapes and the second moment of area (Ix, Iy, Iz) of 2D cross-sections, as + well as for visualization of results. + date_publication: '2024-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gdi + url_git: '' +gdiff: + version: 0.2-5 + title: Graphical Difference Testing + maintainer: Paul Murrell + description: |- + Functions for performing graphical difference testing. + Differences are generated between raster images. + Comparisons can be performed between different package + versions and between different R versions. + date_publication: '2023-03-08' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2020/01/06/2020-01-visual-testing-for-graphics-in-r/ + url_cran: https://CRAN.R-project.org/package=gdiff + url_git: https://github.com/pmur002/ +GDILM.ME: + version: 1.2.1 + title: Spatial Modeling of Infectious Diseases with Co-Variate Error + maintainer: Ruwani Herath + description: Provides tools for simulating from spatial modeling of individual level of + infectious disease transmission when co-variates measured with error, and carrying + out infectious disease data analyses with the same models. The epidemic models + considered are distance-based model within Susceptible-Infectious-Removed (SIR) + compartmental frameworks. + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GDILM.ME + url_git: '' +GDILM.SEIRS: + version: 0.0.3 + title: Spatial Modeling of Infectious Disease with Reinfection + maintainer: Amin Abed + description: Geographically Dependent Individual Level Models (GDILMs) within the + Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) framework are applied + to model infectious disease transmission, incorporating reinfection dynamics. + This package employs a likelihood based Monte Carlo Expectation Conditional Maximization + (MCECM) algorithm for estimating model parameters. It also provides tools for + GDILM fitting, parameter estimation, AIC calculation on real pandemic data, and + simulation studies customized to user-defined model settings. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GDILM.SEIRS + url_git: '' +GDILM.SIR: + version: 1.2.1 + title: Inference for Infectious Disease Transmission in SIR Framework + maintainer: Ruwani Herath + description: |- + Model and estimate the model parameters + for the spatial model of individual-level infectious disease + transmission in Susceptible-Infected-Recovered (SIR) framework. + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GDILM.SIR + url_git: '' +gdim: + version: 0.1.0 + title: Estimate Graph Dimension using Cross-Validated Eigenvalues + maintainer: Alex Hayes + description: |- + Cross-validated eigenvalues are estimated by + splitting a graph into two parts, the training and the test graph. + The training graph is used to estimate eigenvectors, and + the test graph is used to evaluate the correlation between the training + eigenvectors and the eigenvectors of the test graph. + The correlations follow a simple central limit theorem that can + be used to estimate graph dimension via hypothesis testing, see + Chen et al. (2021) for details. + date_publication: '2023-09-05' + bug_reports: https://github.com/RoheLab/gdim/issues + url: https://rohelab.github.io/gdim/ + url_cran: https://CRAN.R-project.org/package=gdim + url_git: https://github.com/RoheLab/gdim +GDINA: + version: 2.9.4 + title: The Generalized DINA Model Framework + maintainer: Wenchao Ma + description: A set of psychometric tools for cognitive diagnosis modeling based + on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la + Torre (2011) and its extensions, including the + sequential G-DINA model by Ma and de la Torre (2016) + for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre + for polytomous attributes. Joint attribute distribution + can be independent, saturated, higher-order, loglinear smoothed or structured. + Q-matrix validation, item and model fit statistics, model comparison at test and + item level and differential item functioning can also be conducted. A graphical + user interface is also provided. For tutorials, please check Ma and de la Torre + (2020) , Ma and de la Torre (2019) , + Ma (2019) and de la Torre and Akbay (2019). + date_publication: '2023-07-01' + bug_reports: https://github.com/Wenchao-Ma/GDINA/issues + url: https://wenchao-ma.github.io/GDINA/ + url_cran: https://CRAN.R-project.org/package=GDINA + url_git: https://github.com/Wenchao-Ma/GDINA +gdistance: + version: 1.6.4 + title: Distances and Routes on Geographical Grids + maintainer: Andrew Marx + description: |- + Provides classes and functions to calculate various + distance measures and routes in heterogeneous geographic + spaces represented as grids. The package implements measures + to model dispersal histories first presented by van Etten and + Hijmans (2010) . Least-cost + distances as well as more complex distances based on (constrained) + random walks can be calculated. The distances implemented in + the package are used in geographical genetics, accessibility + indicators, and may also have applications in other fields of + geospatial analysis. + date_publication: '2023-06-19' + bug_reports: https://github.com/AgrDataSci/gdistance/issues + url: https://AgrDataSci.github.io/gdistance/ + url_cran: https://CRAN.R-project.org/package=gdistance + url_git: '' +gdldata: + version: '0.1' + title: '''Global Data Lab'' R API' + maintainer: Aaron van Geffen + description: |- + Retrieve datasets from the 'Global Data Lab' website + directly into R data frames. Functions are provided to reference available options + (indicators, levels, countries, regions) as well. + date_publication: '2023-09-20' + bug_reports: https://github.com/GlobalDataLab/R-data-api/issues + url: https://docs.globaldatalab.org/gdldata/ + url_cran: https://CRAN.R-project.org/package=gdldata + url_git: https://github.com/GlobalDataLab/R-data-api +gdm: + version: 1.6.0-6 + title: Generalized Dissimilarity Modeling + maintainer: Matt Fitzpatrick + description: A toolkit with functions to fit, plot, summarize, and apply Generalized + Dissimilarity Models. Mokany K, Ware C, Woolley SNC, Ferrier S, Fitzpatrick MC + (2022) Ferrier S, Manion G, Elith J, Richardson K (2007) + . + date_publication: '2025-01-31' + bug_reports: https://github.com/fitzLab-AL/gdm/issues/ + url: https://mfitzpatrick.al.umces.edu/gdm/ + url_cran: https://CRAN.R-project.org/package=gdm + url_git: https://github.com/fitzLab-AL/gdm/ +gdpc: + version: 1.1.4 + title: Generalized Dynamic Principal Components + maintainer: Ezequiel Smucler + description: |- + Functions to compute the Generalized Dynamic Principal Components + introduced in Peña and Yohai (2016) . The implementation + includes an automatic procedure proposed in Peña, Smucler and Yohai (2020) + for the identification of both the number of lags to be used + in the generalized dynamic principal components as well as the number of components required + for a given reconstruction accuracy. + date_publication: '2023-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gdpc + url_git: '' +GDPuc: + version: 1.0.4 + title: Easily Convert GDP Data + maintainer: Johannes Koch + description: |- + Convert GDP time series data from one unit to + another. All common GDP units are included, i.e. current and constant + local currency units, US$ via market exchange rates and international + dollars via purchasing power parities. + date_publication: '2024-09-04' + bug_reports: https://github.com/pik-piam/GDPuc/issues + url: https://pik-piam.github.io/GDPuc/ + url_cran: https://CRAN.R-project.org/package=GDPuc + url_git: https://github.com/pik-piam/GDPuc +gds: + version: 0.1.1 + title: Descriptive Statistics of Grouped Data + maintainer: Partha Sarathi Bishnu + description: |- + Contains a function called gds() which accepts three input + parameters like lower limits, upper limits and the frequencies of the + corresponding classes. The gds() function calculate and return the values + of mean ('gmean'), median ('gmedian'), mode ('gmode'), variance ('gvar'), standard + deviation ('gstdev'), coefficient of variance ('gcv'), quartiles ('gq1', 'gq2', 'gq3'), + inter-quartile range ('gIQR'), skewness ('g1'), and kurtosis ('g2') which facilitate + effective data analysis. For skewness and kurtosis calculations we use moments. + date_publication: '2021-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gds + url_git: '' +GDSARM: + version: 0.1.1 + title: 'Gauss - Dantzig Selector: Aggregation over Random Models' + maintainer: Rakhi Singh + description: The method aims to identify important factors in screening experiments + by aggregation over random models as studied in Singh and Stufken (2022) . + This package provides functions to run the Gauss-Dantzig selector on screening + experiments when interactions may be affecting the response. Currently, all functions + require each factor to be at two levels coded as +1 and -1. + date_publication: '2022-07-13' + bug_reports: https://github.com/agrakhi/GDSARM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GDSARM + url_git: https://github.com/agrakhi/GDSARM +gdtools: + version: 0.4.1 + title: Utilities for Graphical Rendering and Fonts Management + maintainer: David Gohel + description: |- + Tools are provided to compute metrics of formatted strings + and to check the availability of a font. Another set of functions is + provided to support the collection of fonts from 'Google Fonts' in a + cache. Their use is simple within 'R Markdown' documents and 'shiny' + applications but also with graphic productions generated with the + 'ggiraph', 'ragg' and 'svglite' packages or with tabular productions + from the 'flextable' package. + date_publication: '2024-11-04' + bug_reports: https://github.com/davidgohel/gdtools/issues + url: https://davidgohel.github.io/gdtools/ + url_cran: https://CRAN.R-project.org/package=gdtools + url_git: '' +gdverse: + version: 1.3-2 + title: Analysis of Spatial Stratified Heterogeneity + maintainer: Wenbo Lv + description: Analyzing spatial factors and exploring spatial associations based + on the concept of spatial stratified heterogeneity, while also taking into account + local spatial dependencies, spatial interpretability, complex spatial interactions, + and robust spatial stratification. Additionally, it supports the spatial stratified + heterogeneity family established in academic literature. + date_publication: '2025-02-17' + bug_reports: https://github.com/stscl/gdverse/issues + url: https://stscl.github.io/gdverse/ + url_cran: https://CRAN.R-project.org/package=gdverse + url_git: https://github.com/stscl/gdverse +gdxdt: + version: 0.1.0 + title: IO for GAMS GDX Files using 'data.table' + maintainer: Alois Dirnaichner + description: 'Interfaces GAMS data (*.gdx) files with ''data.table''s using the + GAMS R package ''gdxrrw''. The ''gdxrrw'' package is available on the GAMS wiki: + .' + date_publication: '2019-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gdxdt + url_git: '' +GE: + version: 0.4.8 + title: General Equilibrium Modeling + maintainer: Wu LI + description: 'Some tools for developing general equilibrium models and some general + equilibrium models. These models can be used for teaching economic theory and + are built by the methods of new structural economics (see LI Wu, 2019, ISBN: 9787521804225, + General Equilibrium and Structural Dynamics: Perspectives of New Structural Economics. + Beijing: Economic Science Press). The model form and mathematical methods can + be traced back to J. von Neumann (1945, A Model of General Economic Equilibrium. + The Review of Economic Studies, 13. pp. 1-9), J. G. Kemeny, O. Morgenstern and + G. L. Thompson (1956, A Generalization of the von Neumann Model of an Expanding + Economy, Econometrica, 24, pp. 115-135) et al. By the way, J. G. Kemeny is a co-inventor + of the computer language BASIC.' + date_publication: '2025-01-08' + bug_reports: https://x.com/LiwuShu + url: '' + url_cran: https://CRAN.R-project.org/package=GE + url_git: '' +gear: + version: 0.3.4 + title: Geostatistical Analysis in R + maintainer: Joshua French + description: Implements common geostatistical methods in a clean, straightforward, + efficient manner. The methods are discussed in Schabenberger and Gotway (2004, + ) and Waller and Gotway (2004, ). + date_publication: '2020-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gear + url_git: '' +geboes.score: + version: 1.0.0 + title: Evaluate the Geboes Score for Histology in Ulcerative Colitis + maintainer: Bill Denney + description: |- + Evaluate and validate the Geboes score for histological assessment + of inflammation in ulcerative colitis. The original Geboes score from Geboes, + et al. (2000) , binary version from Li, et al. + (2019) , and continuous version from Magro, et + al. (2020) are all described and implemented. + date_publication: '2024-02-02' + bug_reports: '' + url: https://billdenney.github.io/geboes.score/ + url_cran: https://CRAN.R-project.org/package=geboes.score + url_git: '' +GEC: + version: 0.1.0 + title: Generalized Exponentiated Composite Distributions + maintainer: Bowen Liu + description: Contains the framework of the estimation, sampling, and hypotheses + testing for two special distributions (Exponentiated Exponential-Pareto and Exponentiated + Inverse Gamma-Pareto) within the family of Generalized Exponentiated Composite + distributions. The detailed explanation and the applications of these two distributions + were introduced in Bowen Liu, Malwane M.A. Ananda (2022) , + Bowen Liu, Malwane M.A. Ananda (2022) , and Bowen Liu, + Malwane M.A. Ananda (2022) . + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEC + url_git: '' +GECal: + version: 0.1.5 + title: Generalized Entropy Calibration + maintainer: Yonghyun Kwon + description: |- + Generalized Entropy Calibration produces calibration weights + using generalized entropy as the objective function for optimization. + This approach, as implemented in the 'GECal' package, is based on + Kwon, Kim, and Qiu (2024) . Unlike + traditional methods, 'GECal' incorporates design weights into the + constraints to maintain design consistency, rather than including + them in the objective function itself. + date_publication: '2024-09-25' + bug_reports: https://github.com/yonghyun-K/GECal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GECal + url_git: https://github.com/yonghyun-K/GECal +gecko: + version: 1.0.1 + title: Geographical Ecology and Conservation Knowledge Online + maintainer: Vasco V. Branco + description: Includes a collection of geographical analysis functions aimed primarily + at ecology and conservation science studies, allowing processing of both point + and raster data. Now integrates SPECTRE (), + a dataset of global geospatial threat data, developed by the authors. + date_publication: '2024-12-17' + bug_reports: https://github.com/VascoBranco/gecko/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gecko + url_git: https://github.com/VascoBranco/gecko +GeDS: + version: 0.2.6 + title: Geometrically Designed Spline Regression + maintainer: Emilio L. Sáenz Guillén + description: |- + Spline Regression, Generalized Additive Models, and Component-wise Gradient + Boosting, utilizing Geometrically Designed (GeD) Splines. GeDS regression is a + non-parametric method inspired by geometric principles, for fitting spline regression + models with variable knots in one or two independent variables. It efficiently estimates + the number of knots and their positions, as well as the spline order, assuming the + response variable follows a distribution from the exponential family. GeDS models + integrate the broader category of Generalized (Non-)Linear Models, offering a flexible + approach to modeling complex relationships. A description of the method can be found in + Kaishev et al. (2016) and Dimitrova et al. (2023) + . Further extending its capabilities, GeDS's implementation + includes Generalized Additive Models (GAM) and Functional Gradient Boosting (FGB), + enabling versatile multivariate predictor modeling, as discussed in the forthcoming work of + Dimitrova et al. (2024). + date_publication: '2025-02-10' + bug_reports: https://github.com/emilioluissaenzguillen/GeDS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeDS + url_git: https://github.com/emilioluissaenzguillen/GeDS +gee: + version: 4.13-29 + title: Generalized Estimation Equation Solver + maintainer: Brian Ripley + description: Generalized Estimation Equation solver. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gee + url_git: '' +GEEaSPU: + version: 1.0.2 + title: |- + Adaptive Association Tests for Multiple Phenotypes using + Generalized Estimating Equations (GEE) + maintainer: Junghi Kim + description: Provides adaptive association tests for SNP level, gene level and pathway + level analyses. + date_publication: '2016-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEEaSPU + url_git: '' +geeasy: + version: 0.1.2 + title: Solve Generalized Estimating Equations for Clustered Data + maintainer: Søren Højsgaard + description: |- + Estimation of generalized linear models with + correlated/clustered observations by use of generalized estimating + equations (GEE). See e.g. Halekoh and Højsgaard, (2005, + ), for details. Several types of + clustering are supported, including exchangeable variance + structures, AR1 structures, M-dependent, user-specified variance + structures and more. The model fitting computations are performed + using modified code from the 'geeM' package, while the interface + and output objects have been written to resemble the 'geepack' + package. The package also contains additional tools for working + with and inspecting results from the 'geepack' package, e.g. a + 'confint' method for 'geeglm' objects from 'geepack'. + date_publication: '2024-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geeasy + url_git: '' +geeCRT: + version: 1.1.3 + title: Bias-Corrected GEE for Cluster Randomized Trials + maintainer: Hengshi Yu + description: |- + Population-averaged models have been increasingly used in the design and analysis of + cluster randomized trials (CRTs). To facilitate the applications of population-averaged + models in CRTs, the package implements the generalized estimating equations (GEE) and + matrix-adjusted estimating equations (MAEE) approaches to jointly estimate the marginal + mean models correlation models both for general CRTs and stepped wedge CRTs. Despite the + general GEE/MAEE approach, the package also implements a fast cluster-period GEE method by + Li et al. (2022) + specifically for stepped wedge CRTs with large and variable cluster-period sizes and gives + a simple and efficient estimating equations approach based on the cluster-period means to + estimate the intervention effects as well as correlation parameters. In addition, the package + also provides functions for generating correlated binary data with specific mean vector and + correlation matrix based on the multivariate probit method in Emrich and Piedmonte (1991) or + the conditional linear family method in Qaqish (2003) . + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geeCRT + url_git: '' +geecure: + version: 1.0-6 + title: |- + Marginal Proportional Hazards Mixture Cure Models with + Generalized Estimating Equations + maintainer: Yi Niu + description: Features the marginal parametric and semi-parametric proportional hazards + mixture cure models for analyzing clustered survival data with a possible cure + fraction. A reference is Yi Niu and Yingwei Peng (2014) . + date_publication: '2018-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geecure + url_git: '' +geeM: + version: 0.10.1 + title: Solve Generalized Estimating Equations + maintainer: Lee McDaniel + description: |- + GEE estimation of the parameters in mean structures with possible + correlation between the outcomes. User-specified mean link and variance + functions are allowed, along with observation weighting. The 'M' in the name + 'geeM' is meant to emphasize the use of the Matrix package, which allows for an + implementation based fully in R. + date_publication: '2018-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geeM + url_git: '' +GEEmediate: + version: 1.1.4 + title: |- + Mediation Analysis for Generalized Linear Models Using the + Difference Method + maintainer: Daniel Nevo + description: |- + Causal mediation analysis for a single exposure/treatment and a + single mediator, both allowed to be either continuous or binary. The package + implements the difference method and provides point and interval estimates as + well as testing for the natural direct and indirect effects and the mediation + proportion. Nevo, Xiao and Spiegelman (2017) . + date_publication: '2023-01-16' + bug_reports: https://github.com/daniel258/GEEMediate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GEEmediate + url_git: '' +geepack: + version: 1.3.12 + title: Generalized Estimating Equation Package + maintainer: Søren Højsgaard + description: |- + Generalized estimating equations solver for parameters in + mean, scale, and correlation structures, through mean link, + scale link, and correlation link. Can also handle clustered + categorical responses. See e.g. Halekoh and Højsgaard, (2005, + ), for details. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geepack + url_git: '' +geesmv: + version: '1.3' + title: |- + Modified Variance Estimators for Generalized Estimating + Equations + maintainer: Zheng Li + description: Generalized estimating equations with the original sandwich variance + estimator proposed by Liang and Zeger (1986), and eight types of more recent modified + variance estimators for improving the finite small-sample performance. + date_publication: '2015-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geesmv + url_git: '' +geessbin: + version: 1.0.0 + title: Modified Generalized Estimating Equations for Binary Outcome + maintainer: Ryota Ishii + description: |- + Analyze small-sample clustered or longitudinal data with binary + outcome using modified generalized estimating equations (GEE) with + bias-adjusted covariance estimator. The package provides any combination of + three GEE methods and 12 covariance estimators. + date_publication: '2024-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geessbin + url_git: https://github.com/rtishii/geessbin +geeVerse: + version: 0.2.2 + title: A Comprehensive Analysis of High Dimensional Longitudinal Data + maintainer: Tianhai Zu + description: |- + To provide a comprehensive analysis of high dimensional longitudinal + data,this package provides analysis for any combination of 1) simultaneous + variable selection and estimation, 2) mean regression or quantile regression + for heterogeneous data, 3) cross-sectional or longitudinal data, 4) balanced + or imbalanced data, 5) moderate, high or even ultra-high dimensional data, + via computationally efficient implementations of penalized generalized + estimating equations. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geeVerse + url_git: '' +geex: + version: 1.1.1 + title: An API for M-Estimation + maintainer: Bradley Saul + description: |- + Provides a general, flexible framework for estimating parameters + and empirical sandwich variance estimator from a set of unbiased estimating + equations (i.e., M-estimation in the vein of Stefanski & Boos (2002) + ). All examples from Stefanski & Boos (2002) + are published in the corresponding Journal of Statistical Software paper + "The Calculus of M-Estimation in R with geex" by Saul & Hudgens (2020) + . Also provides an API to compute finite-sample + variance corrections. + date_publication: '2022-08-08' + bug_reports: https://github.com/bsaul/geex/issues + url: https://bsaul.github.io/geex/ + url_cran: https://CRAN.R-project.org/package=geex + url_git: https://github.com/bsaul/geex +geigen: + version: '2.3' + title: |- + Calculate Generalized Eigenvalues, the Generalized Schur + Decomposition and the Generalized Singular Value Decomposition + of a Matrix Pair with Lapack + maintainer: Berend Hasselman + description: |- + Functions to compute generalized eigenvalues and eigenvectors, + the generalized Schur decomposition and + the generalized Singular Value Decomposition of a matrix pair, + using Lapack routines. + date_publication: '2019-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geigen + url_git: '' +geiger: + version: 2.0.11 + title: Analysis of Evolutionary Diversification + maintainer: Luke Harmon + description: |- + Methods for fitting macroevolutionary models to phylogenetic trees + Pennell (2014) . + date_publication: '2023-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geiger + url_git: '' +GEInfo: + version: '1.0' + title: |- + Gene-Environment Interaction Analysis Incorporating Prior + Information + maintainer: Xiaoyan Wang + description: Realize three approaches for Gene-Environment interaction analysis. + All of them adopt Sparse Group Minimax Concave Penalty to identify important G + variables and G-E interactions, and simultaneously respect the hierarchy between + main G and G-E interaction effects. All the three approaches are available for + Linear, Logistic, and Poisson regression. Also realize to mine and construct prior + information for G variables and G-E interactions. + date_publication: '2022-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEInfo + url_git: '' +GEInter: + version: 0.3.2 + title: Robust Gene-Environment Interaction Analysis + maintainer: Xing Qin + description: 'Description: For the risk, progression, and response to treatment + of many complex diseases, it has been increasingly recognized that gene-environment + interactions play important roles beyond the main genetic and environmental effects. + In practical interaction analyses, outliers in response variables and covariates + are not uncommon. In addition, missingness in environmental factors is routinely + encountered in epidemiological studies. The developed package consists of five + robust approaches to address the outliers problems, among which two approaches + can also accommodate missingness in environmental factors. Both continuous and + right censored responses are considered. The proposed approaches are based on + penalization and sparse boosting techniques for identifying important interactions, + which are realized using efficient algorithms. Beyond the gene-environment analysis, + the developed package can also be adopted to conduct analysis on interactions + between other types of low-dimensional and high-dimensional data. (Mengyun Wu + et al (2017), ; Mengyun Wu et al (2017), ; + Yaqing Xu et al (2018), ; Yaqing Xu et al (2019), + ; Mengyun Wu et al (2021), ).' + date_publication: '2022-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEInter + url_git: '' +gellipsoid: + version: 0.7.3 + title: Generalized Ellipsoids + maintainer: Michael Friendly + description: |- + Represents generalized geometric ellipsoids with the "(U,D)" representation. It allows degenerate + and/or unbounded ellipsoids, together with methods for linear and duality transformations, and for plotting. + Thus ellipsoids are naturally extended to include lines, hyperplanes, points, cylinders, etc. + This permits exploration of a variety to statistical issues that can be visualized using ellipsoids + as discussed by Friendly, Fox & Monette (2013), Elliptical Insights: Understanding Statistical Methods + Through Elliptical Geometry . + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gellipsoid + url_git: https://github.com/friendly/gellipsoid +gelnet: + version: 1.2.1 + title: Generalized Elastic Nets + maintainer: Artem Sokolov + description: |- + Implements several extensions of the elastic net regularization + scheme. These extensions include individual feature penalties for the L1 term, + feature-feature penalties for the L2 term, as well as translation coefficients + for the latter. + date_publication: '2016-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gelnet + url_git: '' +GEmetrics: + version: 1.0.0 + title: |- + Best Linear Unbiased Prediction of Genotype-by-Environment + Metrics + maintainer: Simon Rio + description: 'Provides functions to calculate the best linear unbiased prediction + of genotype-by-environment metrics: ecovalence, environmental variance, Finlay + and Wilkinson regression and Lin and Binns superiority measure, based on a multi-environment + genomic prediction model.' + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEmetrics + url_git: '' +gemini.R: + version: 0.8.0 + title: Interface for 'Google Gemini' API + maintainer: Jinhwan Kim + description: |- + Provides a comprehensive interface for Google Gemini API, + enabling users to access and utilize Gemini Large Language Model (LLM) functionalities directly from R. + This package facilitates seamless integration with Google Gemini, allowing for advanced language processing, + text generation, and other AI-driven capabilities within the R environment. + For more information, please visit . + date_publication: '2025-02-06' + bug_reports: https://github.com/jhk0530/gemini.R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gemini.R + url_git: https://github.com/jhk0530/gemini.R +gemma2: + version: 0.1.3 + title: GEMMA Multivariate Linear Mixed Model + maintainer: Frederick Boehm + description: Fits a multivariate linear mixed effects model that uses a polygenic + term, after Zhou & Stephens (2014) (). + Of particular interest is the estimation of variance components with restricted + maximum likelihood (REML) methods. Genome-wide efficient mixed-model association + (GEMMA), as implemented in the package 'gemma2', uses an expectation-maximization + algorithm for variance components inference for use in quantitative trait locus + studies. + date_publication: '2020-10-24' + bug_reports: https://github.com/fboehm/gemma2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gemma2 + url_git: https://github.com/fboehm/gemma2 +gems: + version: 1.1.1 + title: Generalized Multistate Simulation Model + maintainer: Luisa Salazar Vizcaya + description: |- + Simulate and analyze multistate models with general hazard + functions. gems provides functionality for the preparation of hazard functions + and parameters, simulation from a general multistate model and predicting future + events. The multistate model is not required to be a Markov model and may take + the history of previous events into account. In the basic version, it allows + to simulate from transition-specific hazard function, whose parameters are + multivariable normally distributed. + date_publication: '2017-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gems + url_git: '' +gemtc: + version: 1.0-2 + title: Network Meta-Analysis Using Bayesian Methods + maintainer: Gert van Valkenhoef + description: |- + Network meta-analyses (mixed treatment comparisons) in the Bayesian + framework using JAGS. Includes methods to assess heterogeneity and + inconsistency, and a number of standard visualizations. + van Valkenhoef et al. (2012) ; + van Valkenhoef et al. (2015) . + date_publication: '2023-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gemtc + url_git: https://github.com/gertvv/gemtc +gen2stage: + version: '1.0' + title: Generalized Two-Stage Designs for Phase II Single-Arm Studies + maintainer: Seongho Kim + description: |- + One can find single-stage and two-stage designs for a phase II + single-arm study with either efficacy or safety/toxicity endpoints as described in Kim and Wong (2019) . + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gen2stage + url_git: '' +gen3sis: + version: 1.5.11 + title: General Engine for Eco-Evolutionary Simulations + maintainer: Oskar Hagen + description: 'Contains an engine for spatially-explicit eco-evolutionary mechanistic + models with a modular implementation and several support functions. It allows + exploring the consequences of ecological and macroevolutionary processes across + realistic or theoretical spatio-temporal landscapes on biodiversity patterns as + a general term. Reference: Oskar Hagen, Benjamin Flueck, Fabian Fopp, Juliano + S. Cabral, Florian Hartig, Mikael Pontarp, Thiago F. Rangel, Loic Pellissier (2021) + "gen3sis: A general engine for eco-evolutionary simulations of the processes that + shape Earth''s biodiversity" .' + date_publication: '2023-11-22' + bug_reports: https://github.com/project-Gen3sis/R-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gen3sis + url_git: https://github.com/project-Gen3sis/R-package +gen5helper: + version: 1.0.1 + title: Processing 'Gen5' 2.06 Exported Data + maintainer: Yanxian Lin + description: |- + A collection of functions for processing 'Gen5' 2.06 exported data. + 'Gen5' is an essential data analysis software for BioTek plate readers . This package contains functions for data cleaning, + modeling and plotting using exported data from 'Gen5' version 2.06. It exports + technically correct data defined in (Edwin de Jonge and Mark van der Loo + (2013) ) for customized analysis. It + contains Boltzmann fitting for general kinetic analysis. + See for more information, + documentation and examples. + date_publication: '2019-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gen5helper + url_git: '' +gena: + version: 1.0.0 + title: Genetic Algorithm and Particle Swarm Optimization + maintainer: Bogdan Potanin + description: Implements genetic algorithm and particle swarm algorithm for real-valued + functions. Various modifications (including hybridization and elitism) of these + algorithms are provided. Implemented functions are based on ideas described in + S. Katoch, S. Chauhan, V. Kumar (2020) and M. + Clerc (2012) . + date_publication: '2022-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gena + url_git: '' +GenAI: + version: 0.2.0 + title: Generative Artificial Intelligence + maintainer: Li Yuan + description: Utilizing Generative Artificial Intelligence models like 'GPT-4' and + 'Gemini Pro' as coding and writing assistants for 'R' users. Through these models, + 'GenAI' offers a variety of functions, encompassing text generation, code optimization, + natural language processing, chat, and image interpretation. The goal is to aid + 'R' users in streamlining laborious coding and language processing tasks. + date_publication: '2024-02-15' + bug_reports: https://github.com/GitData-GA/GenAI/issues + url: https://genai.gd.edu.kg/ + url_cran: https://CRAN.R-project.org/package=GenAI + url_git: '' +genalg: + version: 0.2.1 + title: R Based Genetic Algorithm + maintainer: Michel Ballings + description: |- + R based genetic algorithm for binary and floating point + chromosomes. + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genalg + url_git: '' +GenAlgo: + version: 2.2.0 + title: |- + Classes and Methods to Use Genetic Algorithms for Feature + Selection + maintainer: Kevin R. Coombes + description: |- + Defines classes and methods that can be used + to implement genetic algorithms for feature selection. The idea is + that we want to select a fixed number of features to combine into a + linear classifier that can predict a binary outcome, and can use a + genetic algorithm heuristically to select an optimal set of features. + date_publication: '2020-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenAlgo + url_git: http://oompa.r-forge.r-project.org/ +genBaRcode: + version: 1.2.7 + title: Analysis and Visualization Tools for Genetic Barcode Data + maintainer: Lars Thielecke + description: Provides the necessary functions to identify and extract a selection + of already available barcode constructs (Cornils, K. et al. (2014) ) + and freely choosable barcode designs from next generation sequence (NGS) data. + Furthermore, it offers the possibility to account for sequence errors, the calculation + of barcode similarities and provides a variety of visualisation tools (Thielecke, + L. et al. (2017) ). + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genBaRcode + url_git: '' +GenBinomApps: + version: 1.2.1 + title: |- + Clopper-Pearson Confidence Interval and Generalized Binomial + Distribution + maintainer: Horst Lewitschnig + description: Density, distribution function, quantile function and random generation + for the Generalized Binomial Distribution. Functions to compute the Clopper-Pearson + Confidence Interval and the required sample size. Enhanced model for burn-in studies, + where failures are tackled by countermeasures. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenBinomApps + url_git: '' +gencor: + version: 1.0.2 + title: Generate Customized Correlation Matrices + maintainer: Helgem de Souza Ribeiro Martins + description: Provides a function that generates a customized correlation matrix + based on limit values and proportions for intervals composed by its limits. It + can also generate random matrices with low, medium, and high correlations, in + which low, medium, and high thresholds are user-defined. + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gencor + url_git: '' +genCountR: + version: 1.0.0 + title: |- + Interacting with Roberts and Utych's (2019) Gendered Language + Dictionary + maintainer: Damon Roberts + description: Allows users to generate a gendered language score according to the + gendered language dictionary in Roberts and Utych (2019) . + date_publication: '2023-12-05' + bug_reports: '' + url: https://gencounter.app.damoncroberts.com + url_cran: https://CRAN.R-project.org/package=genCountR + url_git: '' +gendata: + version: 1.2.0 + title: Generate and Modify Synthetic Datasets + maintainer: Francis Huang + description: Set of functions to create datasets using a correlation matrix. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gendata + url_git: '' +gender: + version: 0.6.0 + title: Predict Gender from Names Using Historical Data + maintainer: Lincoln Mullen + description: |- + Infers state-recorded gender categories from first names and dates of birth using historical + datasets. By using these datasets instead of lists of male and female names, + this package is able to more accurately infer the gender of a name, and it + is able to report the probability that a name was male or female. GUIDELINES: + This method must be used cautiously and responsibly. Please be sure to see the + guidelines and warnings about usage in the 'README' or the package documentation. + See Blevins and Mullen (2015) . + date_publication: '2021-10-13' + bug_reports: https://github.com/lmullen/gender/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gender + url_git: https://github.com/lmullen/gender +genderBR: + version: 1.1.2 + title: Predict Gender from Brazilian First Names + maintainer: Fernando Meireles + description: |- + A method to predict and report gender from Brazilian first names + using the Brazilian Institute of Geography and Statistics' Census data (). + date_publication: '2021-05-02' + bug_reports: https://github.com/meirelesff/genderBR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=genderBR + url_git: https://github.com/meirelesff/genderBR +GenderInfer: + version: 0.1.0 + title: This is a Collection of Functions to Analyse Gender Differences + maintainer: Rita Giordano + description: |- + Implementation of functions, which combines binomial calculation + and data visualisation, to analyse the differences in publishing authorship + by gender described in Day et al. (2020) . + It should only be used when self-reported gender is unavailable. + date_publication: '2021-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenderInfer + url_git: '' +genderstat: + version: 0.1.5 + title: Quantitative Analysis Tools for Gender Studies + maintainer: S M Mashrur Arafin Ayon + description: 'Provides tools for quantitative analysis in gender studies, including + functions to calculate various gender inequality metrics such as the Gender Pay + Gap, Gender Inequality Index (GII), Gender Development Index (GDI), and Gender + Empowerment Measure (GEM). Also includes extracted secondary example datasets + for practice and learning purposes, which were obtained from the UNDP Human Development + Reports Data Center and the World Bank Gender Data Portal by the author the dataset + is available on . References: Miller, Kevin; + Vagins, Deborah J. (2021) . Jacques Charmes + & Saskia Wieringa (2003) . Gaëlle Ferrant (2010) + .' + date_publication: '2024-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genderstat + url_git: '' +gendist: + version: '2.0' + title: Generated Probability Distribution Models + maintainer: Shaiful Anuar Abu Bakar + description: 'Computes the probability density function (pdf), cumulative distribution + function (cdf), quantile function (qf) and generates random values (rg) for the + following general models : mixture models, composite models, folded models, skewed + symmetric models and arc tan models.' + date_publication: '2019-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gendist + url_git: '' +GENEAclassify: + version: 1.5.5 + title: Segmentation and Classification of Accelerometer Data + maintainer: Jia Ying Chua + description: |- + Segmentation and classification procedures for data from the 'Activinsights GENEActiv' accelerometer that provides the user with a model to guess behaviour from test data where behaviour is missing. + Includes a step counting algorithm, a function to create segmented data with custom features and a function to use recursive partitioning provided in the function rpart() of the 'rpart' package to create classification models. + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GENEAclassify + url_git: '' +GENEAread: + version: 2.0.10 + title: Package for Reading Binary Files + maintainer: Jia Ying Chua + description: |- + Functions and analytics for GENEA-compatible accelerometer data into R objects. + See topic 'GENEAread' for an introduction to the package. + See for more details on the GENEActiv device. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GENEAread + url_git: '' +GeneCycle: + version: 1.1.5 + title: Identification of Periodically Expressed Genes + maintainer: Miika Ahdesmaki + description: |- + The GeneCycle package implements the approaches of Wichert + et al. (2004) , Ahdesmaki + et al. (2005) and Ahdesmaki et al. + (2007) for detecting periodically + expressed genes from gene expression time series data. + date_publication: '2021-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneCycle + url_git: '' +geneExpressionFromGEO: + version: '0.9' + title: |- + Easily Downloads a Gene Expression Dataset from a GEO Code and + Retrieves the Gene Symbols of Its Probesets + maintainer: Davide Chicco + description: 'A function that reads in the GEO code of a gene expression dataset, + retrieves its data from GEO, (optionally) retrieves the gene symbols of the dataset, + and returns a simple dataframe table containing all the data. Platforms available: + GPL11532, GPL23126, GPL6244, GPL8300, GPL80, GPL96, GPL570, GPL571, GPL20115, + GPL1293, GPL6102, GPL6104, GPL6883, GPL6884, GPL13497, GPL14550, GPL17077, GPL6480. + GEO: Gene Expression Omnibus. ID: identifier code. The GEO datasets are downloaded + from the URL . More information can + be found in the following manuscript: Davide Chicco, "geneExpressionFromGEO: an + R package to facilitate data reading from Gene Expression Omnibus (GEO)". Microarray + Data Analysis, Methods in Molecular Biology, volume 2401, chapter 12, pages 187-194, + Springer Protocols, 2021, .' + date_publication: '2021-12-16' + bug_reports: https://github.com/davidechicco/geneExpressionFromGEO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geneExpressionFromGEO + url_git: https://github.com/davidechicco/geneExpressionFromGEO +GeneF: + version: 1.0.1 + title: Package for Generalized F-Statistics + maintainer: Yinglei Lai + description: |- + Implementation of several generalized F-statistics. The + current version includes a generalized F-statistic based on the + flexible isotonic/monotonic regression or order restricted hypothesis + testing. Based on: Y. Lai (2011) . + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneF + url_git: '' +geneHapR: + version: 1.2.4 + title: |- + Gene Haplotype Statistics, Phenotype Association and + Visualization + maintainer: Zhang Renliang + description: |- + Import genome variants data and perform gene haplotype Statistics, + visualization and phenotype association with 'R'. + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geneHapR + url_git: '' +geneHummus: + version: 1.0.11 + title: A Pipeline to Define Gene Families in Legumes and Beyond + maintainer: Jose V. Die + description: |- + A pipeline with high specificity and sensitivity in extracting + proteins from the RefSeq database (National Center for Biotechnology + Information). Manual identification of gene families is highly + time-consuming and laborious, requiring an iterative process of manual and + computational analysis to identify members of a given family. The pipelines + implements an automatic approach for the identification of gene families + based on the conserved domains that specifically define that family. See + Die et al. (2018) for more information and examples. + date_publication: '2019-04-04' + bug_reports: https://github.com/NCBI-Hackathons/GeneHummus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geneHummus + url_git: https://github.com/NCBI-Hackathons/GeneHummus +genekitr: + version: 1.2.8 + title: Gene Analysis Toolkit + maintainer: Yunze Liu + description: Provides features for searching, converting, analyzing, plotting, and + exporting data effortlessly by inputting feature IDs. Enables easy retrieval of + feature information, conversion of ID types, gene enrichment analysis, publication-level + figures, group interaction plotting, and result export in one Excel file for seamless + sharing and communication. + date_publication: '2024-09-06' + bug_reports: https://github.com/GangLiLab/genekitr/issues + url: https://www.genekitr.fun/ + url_cran: https://CRAN.R-project.org/package=genekitr + url_git: '' +genemodel: + version: 1.1.0 + title: Gene Model Plotting in R + maintainer: J Grey Monroe + description: Using simple input, this package creates plots of gene models. Users + can create plots of alternatively spliced gene variants and the positions of mutations + and other gene features. + date_publication: '2017-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genemodel + url_git: https://github.com/greymonroe/genemodel +GeneNet: + version: 1.2.16 + title: Modeling and Inferring Gene Networks + maintainer: Korbinian Strimmer + description: |- + Analyzes gene expression + (time series) data with focus on the inference of gene networks. + In particular, GeneNet implements the methods of Schaefer and + Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) + for learning large-scale gene association networks (including + assignment of putative directions). + date_publication: '2021-11-14' + bug_reports: '' + url: https://strimmerlab.github.io/software/genenet/ + url_cran: https://CRAN.R-project.org/package=GeneNet + url_git: '' +GeneNMF: + version: 0.6.2 + title: Non-Negative Matrix Factorization for Single-Cell Omics + maintainer: Massimo Andreatta + description: A collection of methods to extract gene programs from single-cell gene + expression data using non-negative matrix factorization (NMF). 'GeneNMF' contains + functions to directly interact with the 'Seurat' toolkit and derive interpretable + gene program signatures. + date_publication: '2024-11-12' + bug_reports: https://github.com/carmonalab/GeneNMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeneNMF + url_git: https://github.com/carmonalab/GeneNMF +genepi: + version: 1.0.3 + title: Genetic Epidemiology Design and Inference + maintainer: Venkatraman E. Seshan + description: Package for Genetic Epidemiologic Methods Developed at MSKCC. It contains + functions to calculate haplotype specific odds ratio and the power of two stage + design for GWAS studies. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genepi + url_git: '' +genepop: + version: 1.2.2 + title: Population Genetic Data Analysis Using Genepop + maintainer: François Rousset + description: 'Makes the Genepop software available in R. This software implements + a mixture of traditional population genetic methods and some more focused developments: + it computes exact tests for Hardy-Weinberg equilibrium, for population differentiation + and for genotypic disequilibrium among pairs of loci; it computes estimates of + F-statistics, null allele frequencies, allele size-based statistics for microsatellites, + etc.; and it performs analyses of isolation by distance from pairwise comparisons + of individuals or population samples.' + date_publication: '2023-01-19' + bug_reports: '' + url: https://kimura.univ-montp2.fr/~rousset/Genepop.htm + url_cran: https://CRAN.R-project.org/package=genepop + url_git: '' +generalCorr: + version: 1.2.6 + title: Generalized Correlations, Causal Paths and Portfolio Selection + maintainer: H. D. Vinod + description: |- + Function gmcmtx0() computes a more reliable (general) + correlation matrix. Since causal paths from data are important for all sciences, the + package provides many sophisticated functions. causeSummBlk() and causeSum2Blk() + give easy-to-interpret causal paths. Let Z denote control variables and compare + two flipped kernel regressions: X=f(Y, Z)+e1 and Y=g(X, Z)+e2. Our criterion Cr1 + says that if |e1*Y|>|e2*X| then variation in X is more "exogenous or independent" + than in Y, and the causal path is X to Y. Criterion Cr2 requires |e2|<|e1|. These + inequalities between many absolute values are quantified by four orders of + stochastic dominance. Our third criterion Cr3, for the causal path X to Y, + requires new generalized partial correlations to satisfy |r*(x|y,z)|< |r*(y|x,z)|. + The function parcorVec() reports generalized partials between the first + variable and all others. The package provides several R functions including + get0outliers() for outlier detection, bigfp() for numerical integration by the + trapezoidal rule, stochdom2() for stochastic dominance, pillar3D() for 3D charts, + canonRho() for generalized canonical correlations, depMeas() measures nonlinear + dependence, and causeSummary(mtx) reports summary of causal paths among matrix + columns. Portfolio selection: decileVote(), momentVote(), dif4mtx(), exactSdMtx() + can rank several stocks. Functions whose names begin with 'boot' provide bootstrap + statistical inference, including a new bootGcRsq() test for "Granger-causality" + allowing nonlinear relations. A new tool for evaluation of out-of-sample + portfolio performance is outOFsamp(). Panel data implementation is now included. + See eight vignettes of the package for theory, examples, and + usage tips. See Vinod (2019) \doi{10.1080/03610918.2015.1122048}. + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=generalCorr + url_git: '' +generalhoslem: + version: 1.3.4 + title: Goodness of Fit Tests for Logistic Regression Models + maintainer: Matthew Jay + description: Functions to assess the goodness of fit of binary, multinomial and + ordinal logistic models. Included are the Hosmer-Lemeshow tests (binary, multinomial + and ordinal) and the Lipsitz and Pulkstenis-Robinson tests (ordinal). + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=generalhoslem + url_git: '' +GeneralisedCovarianceMeasure: + version: 0.2.0 + title: |- + Test for Conditional Independence Based on the Generalized + Covariance Measure (GCM) + maintainer: Jonas Peters + description: 'A statistical hypothesis test for conditional independence. It performs + nonlinear regressions on the conditioning variable and then tests for a vanishing + covariance between the resulting residuals. It can be applied to both univariate + random variables and multivariate random vectors. Details of the method can be + found in Rajen D. Shah and Jonas Peters: The Hardness of Conditional Independence + Testing and the Generalised Covariance Measure, Annals of Statistics 48(3), 1514--1538, + 2020.' + date_publication: '2022-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneralisedCovarianceMeasure + url_git: '' +GeneralizedHyperbolic: + version: 0.8-6 + title: The Generalized Hyperbolic Distribution + maintainer: David Scott + description: |- + Functions for the hyperbolic and related distributions. + Density, distribution and quantile functions and random number generation + are provided for the hyperbolic distribution, the generalized hyperbolic + distribution, the generalized inverse Gaussian distribution and + the skew-Laplace distribution. Additional functionality is + provided for the hyperbolic distribution, normal inverse + Gaussian distribution and generalized inverse Gaussian distribution, + including fitting of these distributions to data. Linear models with + hyperbolic errors may be fitted using hyperblmFit. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneralizedHyperbolic + url_git: https://r-forge.r-project.org/projects/rmetrics/ +GeneralizedUmatrix: + version: 1.3.1 + title: Credible Visualization for Two-Dimensional Projections of Data + maintainer: Michael Thrun + description: 'Projections are common dimensionality reduction methods, which represent + high-dimensional data in a two-dimensional space. However, when restricting the + output space to two dimensions, which results in a two dimensional scatter plot + (projection) of the data, low dimensional similarities do not represent high dimensional + distances coercively [Thrun, 2018] . This could + lead to a misleading interpretation of the underlying structures [Thrun, 2018]. + By means of the 3D topographic map the generalized Umatrix is able to depict errors + of these two-dimensional scatter plots. The package is derived from the book of + Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm + Intelligence" (2018) and the main algorithm called + simplified self-organizing map for dimensionality reduction methods is published + in .' + date_publication: '2025-01-29' + bug_reports: https://github.com/Mthrun/GeneralizedUmatrix/issues + url: https://www.deepbionics.org + url_cran: https://CRAN.R-project.org/package=GeneralizedUmatrix + url_git: '' +GeneralizedWendland: + version: 0.6.0 + title: Fully Parameterized Generalized Wendland Covariance Function + maintainer: Thomas C. Fischer + description: |- + A fully parameterized Generalized Wendland covariance function for use in Gaussian process models, as well as multiple methods for approximating it via covariance interpolation. The available methods are linear interpolation, polynomial interpolation, and cubic spline interpolation. + Moreno Bevilacqua and Reinhard Furrer and Tarik Faouzi and Emilio Porcu (2019) >. + Moreno Bevilacqua and Christian Caamaño-Carrillo and Emilio Porcu (2022) . + Reinhard Furrer and Roman Flury and Florian Gerber (2022) >. + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneralizedWendland + url_git: '' +GeneralOaxaca: + version: '1.0' + title: Blinder-Oaxaca Decomposition for Generalized Linear Model + maintainer: Aurelien Nicosia + description: |- + Perform the Blinder-Oaxaca decomposition for generalized linear + model with bootstrapped standard errors. The twofold and threefold + decomposition are given, even the generalized linear model output in each group. + date_publication: '2015-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneralOaxaca + url_git: '' +generalRSS: + version: 0.1.3 + title: |- + Statistical Tools for Balanced and Unbalanced Ranked Set + Sampling + maintainer: Soohyun Ahn + description: Ranked Set Sampling (RSS) is a stratified sampling method known for + its efficiency compared to Simple Random Sampling (SRS). When sample allocation + is equal across strata, it is referred to as balanced RSS (BRSS) whereas unequal + allocation is called unbalanced RSS (URSS), which is particularly effective for + asymmetric or skewed distributions. This package offers practical statistical + tools and sampling methods for both BRSS and URSS, emphasizing flexible sampling + designs and inference for population means, medians, proportions, and Area Under + the Curve (AUC). It incorporates parametric and nonparametric tests, including + empirical likelihood ratio (LR) methods. The package provides ranked set sampling + methods from a given population, including sampling with imperfect ranking using + auxiliary variables. Furthermore, it provides tools for efficient sample allocation + in URSS, ensuring greater efficiency than SRS and BRSS. For more details, refer + e.g. to Chen et al. (2003) , Ahn et al. (2022) + , and Ahn et al. (2024) . + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=generalRSS + url_git: '' +generator: + version: 0.1.0 + title: |- + Generate Data Containing Fake Personally Identifiable + Information + maintainer: Paul Hendricks + description: |- + Allows users to quickly and easily generate fake data containing + Personally Identifiable Information (PII) through convenience functions. + date_publication: '2015-08-26' + bug_reports: https://github.com/paulhendricks/generator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=generator + url_git: https://github.com/paulhendricks/generator +GenericML: + version: 0.2.2 + title: Generic Machine Learning Inference + maintainer: Max Welz + description: Generic Machine Learning Inference on heterogeneous treatment effects + in randomized experiments as proposed in Chernozhukov, Demirer, Duflo and Fernández-Val + (2020) . This package's workhorse is the 'mlr3' framework of + Lang et al. (2019) , which enables the specification + of a wide variety of machine learners. The main functionality, GenericML(), runs + Algorithm 1 in Chernozhukov, Demirer, Duflo and Fernández-Val (2020) + for a suite of user-specified machine learners. All steps in the algorithm are + customizable via setup functions. Methods for printing and plotting are available + for objects returned by GenericML(). Parallel computing is supported. + date_publication: '2022-06-18' + bug_reports: https://github.com/mwelz/GenericML/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=GenericML + url_git: https://github.com/mwelz/GenericML/ +generics: + version: 0.1.3 + title: |- + Common S3 Generics not Provided by Base R Methods Related to + Model Fitting + maintainer: Hadley Wickham + description: |- + In order to reduce potential package dependencies and + conflicts, generics provides a number of commonly used S3 generics. + date_publication: '2022-07-05' + bug_reports: https://github.com/r-lib/generics/issues + url: https://generics.r-lib.org + url_cran: https://CRAN.R-project.org/package=generics + url_git: https://github.com/r-lib/generics +genero: + version: 0.1.0 + title: Estimate Gender from Names in Spanish and Portuguese + maintainer: Juan Pablo Marin Diaz + description: |- + Estimate gender from names in Spanish and Portuguese. + Works with vectors and dataframes. The estimation works not only + for first names but also full names. The package relies on a + compilation of common names with it's most frequent associated + gender in both languages which are used as look up tables for gender + inference. + date_publication: '2020-03-09' + bug_reports: https://github.com/datasketch/genero/issues + url: '' + url_cran: https://CRAN.R-project.org/package=genero + url_git: https://github.com/datasketch/genero +GeneScape: + version: '1.0' + title: Simulation of Single Cell RNA-Seq Data with Complex Structure + maintainer: Qi Gao + description: Simulating single cell RNA-seq data with complicated structure. This + package is developed based on the Splat method (Zappia, Phipson and Oshlack (2017) + ). 'GeneScape' incorporates additional features + to simulate single cell RNA-seq data with complicated differential expression + and correlation structures, such as sub-cell-types, correlated genes (pathway + genes) and hub genes. + date_publication: '2023-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneScape + url_git: '' +GeneScoreR: + version: 0.1.1 + title: Gene Scoring from Count Tables + maintainer: Aris Syntakas + description: 'Provides two methods for automatic calculation of gene scores from + gene count tables: the z-score method, which requires a table of samples being + scored and a count table with control samples, and the geometric mean method, + which does not rely on control samples. The mathematical methods implemented are + described by Kim et al. (2018) .' + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneScoreR + url_git: '' +GeneSelectR: + version: 1.0.1 + title: |- + 'GeneSelectR' - Comprehensive Feature Selection Workflow for + Bulk RNAseq Datasets + maintainer: Damir Zhakparov + description: The workflow is a versatile R package designed for comprehensive feature + selection in bulk RNAseq datasets. Its key innovation lies in the seamless integration + of the 'Python' 'scikit-learn' () + machine learning framework with R-based bioinformatics tools. 'GeneSelectR' performs + robust Machine Learning-driven (ML) feature selection while leveraging 'Gene Ontology' + (GO) enrichment analysis as described by Thomas PD et al. (2022) , + using 'clusterProfiler' (Wu et al., 2021) and + semantic similarity analysis powered by 'simplifyEnrichment' (Gu, Huebschmann, + 2021) . This combination of methodologies optimizes + computational and biological insights for analyzing complex RNAseq datasets. + date_publication: '2024-02-03' + bug_reports: https://github.com/dzhakparov/GeneSelectR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeneSelectR + url_git: https://github.com/dzhakparov/GeneSelectR +geneset: + version: 0.2.7 + title: Get Gene Sets for Gene Enrichment Analysis + maintainer: Yunze Liu + description: |- + Gene sets are fundamental for gene enrichment analysis. The package 'geneset' enables querying + gene sets from public databases including 'GO' (Gene Ontology Consortium. (2004) ), + 'KEGG' (Minoru et al. (2000) ), + 'WikiPathway' (Marvin et al. (2020) ), + 'MsigDb' (Arthur et al. (2015) ), + 'Reactome' (David et al. (2011) ), + 'MeSH' (Ish et al. (2014) ), + 'DisGeNET' (Janet et al. (2017) ), + 'Disease Ontology' (Lynn et al. (2011) ), + 'Network of Cancer Genes' (Dimitra et al. (2019) ) and + 'COVID-19' (Maxim et al. (2020) ). + Gene sets are stored in the list object which provides data frame of 'geneset' and 'geneset_name'. + The 'geneset' has two columns of term ID and gene ID. The 'geneset_name' has two columns of + terms ID and term description. + date_publication: '2022-11-20' + bug_reports: https://github.com/GangLiLab/geneset/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geneset + url_git: https://github.com/GangLiLab/geneset +geneSLOPE: + version: 0.38.2 + title: Genome-Wide Association Study with SLOPE + maintainer: Piotr Sobczyk + description: |- + Genome-wide association study (GWAS) performed with SLOPE, + short for Sorted L-One Penalized Estimation, a + method for estimating the vector of coefficients in a linear model. + In the first step of GWAS, single nucleotide polymorphisms (SNPs) are + clumped according to their correlations and distances. + Then, SLOPE is performed on the data where each clump has + one representative. + Malgorzata Bogdan, Ewout van den Berg, Chiara Sabatti, Weijie Su + and Emmanuel Candes (2014) + "SLOPE - Adaptive Variable Selection via Convex Optimization" + . + date_publication: '2023-08-16' + bug_reports: https://github.com/psobczyk/geneSLOPE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geneSLOPE + url_git: https://github.com/psobczyk/geneSLOPE +GenEst: + version: 1.4.9 + title: Generalized Mortality Estimator + maintainer: Daniel Dalthorp + description: Command-line and 'shiny' GUI implementation of the GenEst models for + estimating bird and bat mortality at wind and solar power facilities, following + Dalthorp, et al. (2018) . + date_publication: '2023-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenEst + url_git: '' +genesysr: + version: 2.1.1 + title: Genesys PGR Client + maintainer: Matija Obreza + description: |- + Access data on plant genetic resources from genebanks around the world published on Genesys (). + Your use of data is subject to terms and conditions available at . + date_publication: '2024-02-23' + bug_reports: https://gitlab.croptrust.org/genesys-pgr/genesysr/-/issues + url: https://gitlab.croptrust.org/genesys-pgr/genesysr + url_cran: https://CRAN.R-project.org/package=genesysr + url_git: '' +genetic.algo.optimizeR: + version: 0.3.3 + title: Genetic Algorithm Optimization + maintainer: Dany Mukesha + description: |- + Genetic algorithm are a class of optimization + algorithms inspired by the process of natural selection and genetics. + This package is for learning purposes and allows users to optimize + various functions or parameters by mimicking biological evolution + processes such as selection, crossover, and mutation. Ideal for tasks + like machine learning parameter tuning, mathematical function + optimization, and solving an optimization problem that involves finding + the best solution in a discrete space. + date_publication: '2025-01-24' + bug_reports: https://github.com/danymukesha/genetic.algo.optimizeR/issues + url: https://danymukesha.github.io/genetic.algo.optimizeR/ + url_cran: https://CRAN.R-project.org/package=genetic.algo.optimizeR + url_git: https://github.com/danymukesha/genetic.algo.optimizeR +geneticae: + version: 0.4.0 + title: |- + Statistical Tools for the Analysis of Multi Environment + Agronomic Trials + maintainer: Julia Angelini + description: |- + Data from multi environment agronomic trials, which are often + carried out by plant breeders, can be analyzed with the tools offered by this + package such as the Additive Main effects and Multiplicative Interaction model + or 'AMMI' ('Gauch' 1992, ISBN:9780444892409) + and the Site Regression model or 'SREG' ('Cornelius' 1996, + ). Since these methods present a poor performance + under the presence of outliers and missing values, this package includes + robust versions of the 'AMMI' model ('Rodrigues' 2016, + ), and also imputation techniques + specifically developed for this kind of data ('Arciniegas-Alarcón' 2014, + ). + date_publication: '2022-07-20' + bug_reports: https://github.com/jangelini/geneticae/issues + url: https://jangelini.github.io/geneticae/ + url_cran: https://CRAN.R-project.org/package=geneticae + url_git: '' +genetics: + version: 1.3.8.1.3 + title: Population Genetics + maintainer: Gregory Warnes + description: |- + Classes and methods for handling genetic data. Includes + classes to represent genotypes and haplotypes at single markers + up to multiple markers on multiple chromosomes. Function + include allele frequencies, flagging homo/heterozygotes, + flagging carriers of certain alleles, estimating and testing + for Hardy-Weinberg disequilibrium, estimating and testing for + linkage disequilibrium, ... + date_publication: '2021-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genetics + url_git: '' +GeneticSubsetter: + version: '0.8' + title: Identify Favorable Subsets of Germplasm Collections + maintainer: Ryan C. Graebner + description: Finds subsets of sets of genotypes with a high Heterozygosity, and + Mean of Transformed Kinships (MTK), measures that can indicate a subset would + be beneficial for rare-trait discovery and genome-wide association scanning, respectively. + date_publication: '2016-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeneticSubsetter + url_git: '' +GeNetIt: + version: 0.1-6 + title: Spatial Graph-Theoretic Genetic Gravity Modelling + maintainer: Jeffrey S. Evans + description: |- + Implementation of spatial graph-theoretic genetic gravity models. + The model framework is applicable for other types of spatial flow questions. + Includes functions for constructing spatial graphs, sampling and summarizing + associated raster variables and building unconstrained and singly constrained + gravity models. + date_publication: '2023-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeNetIt + url_git: https://github.com/jeffreyevans/GeNetIt +geneviewer: + version: 0.1.10 + title: Gene Cluster Visualizations + maintainer: Niels van der Velden + description: |- + Provides tools for plotting gene clusters and transcripts by + importing data from GenBank, FASTA, and GFF files. It performs BLASTP and + MUMmer alignments [Altschul et al. (1990) ; + Delcher et al. (1999) ] and displays results on + gene arrow maps. Extensive customization options are available, including + legends, labels, annotations, scales, colors, tooltips, and more. + date_publication: '2025-01-10' + bug_reports: https://github.com/nvelden/geneviewer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geneviewer + url_git: https://github.com/nvelden/geneviewer +genfrn: + version: 0.1.4 + title: |- + Generating Triangular and Trapezoidal Fuzzy Random Numbers via + Uniform Distribution + maintainer: Atchanut Rattanalertnusorn + description: |- + Triangular and trapezoidal fuzzy numbers are used to study fuzzy logic, + fuzzy reasoning and approximating, fuzzy regression models, etc. + This package builds the generating function for triangular and trapezoidal fuzzy numbers based on Souliotis et al. (2022). + They proposed a method for the construction of fuzzy numbers via a cumulative distribution function based on the possibility theory. + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genfrn + url_git: '' +genie: + version: 1.0.5 + title: Fast, Robust, and Outlier Resistant Hierarchical Clustering + maintainer: Marek Gagolewski + description: |- + Includes the reference implementation of Genie - a hierarchical + clustering algorithm that links two point groups in such a way that + an inequity measure (namely, the Gini index) of the cluster sizes + does not significantly increase above a given threshold. + This method most often outperforms many other data segmentation approaches + in terms of clustering quality as tested on a wide range of benchmark + datasets. At the same time, Genie retains the high speed of the single + linkage approach, therefore it is also suitable for analysing larger data sets. + For more details see (Gagolewski et al. 2016 ). + For an even faster and more feature-rich implementation, including, + amongst others, noise point detection, see the 'genieclust' package. + date_publication: '2020-08-02' + bug_reports: http://github.com/gagolews/genie/issues + url: http://genieclust.gagolewski.com/ + url_cran: https://CRAN.R-project.org/package=genie + url_git: '' +genieBPC: + version: 2.0.1 + title: Project GENIE BioPharma Collaborative Data Processing Pipeline + maintainer: Jessica A. Lavery + description: |- + The American Association Research (AACR) Project + Genomics Evidence Neoplasia Information Exchange (GENIE) BioPharma + Collaborative represents a multi-year, multi-institution effort + to build a pan-cancer repository of linked clinico-genomic data. + The genomic and clinical data are provided in multiple releases (separate + releases for each cancer cohort with updates following data corrections), + which are stored on the data sharing platform + 'Synapse' . + The 'genieBPC' package provides a seamless way to obtain the + data corresponding to each release from 'Synapse' and to prepare + datasets for analysis. + date_publication: '2024-07-11' + bug_reports: https://github.com/GENIE-BPC/genieBPC/issues + url: https://genie-bpc.github.io/genieBPC/ + url_cran: https://CRAN.R-project.org/package=genieBPC + url_git: '' +genieclust: + version: 1.1.6 + title: |- + Fast and Robust Hierarchical Clustering with Noise Points + Detection + maintainer: Marek Gagolewski + description: |- + A retake on the Genie algorithm + (Gagolewski, 2021 ) - a robust + hierarchical clustering method + (Gagolewski, Bartoszuk, Cena, 2016 ). + Now faster and more memory efficient; determining the whole hierarchy + for datasets of 10M points in low dimensional Euclidean spaces or + 100K points in high-dimensional ones takes only 1-2 minutes. + Allows clustering with respect to mutual reachability distances + so that it can act as a noise point detector or a robustified version of + 'HDBSCAN*' (that is able to detect a predefined number of + clusters and hence it does not dependent on the somewhat + fragile 'eps' parameter). + The package also features an implementation of inequality indices + (the Gini, Bonferroni index), external cluster validity measures + (e.g., the normalised clustering accuracy and partition similarity scores + such as the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, + and the pair sets index), + and internal cluster validity indices (e.g., the Calinski-Harabasz, + Davies-Bouldin, Ball-Hall, Silhouette, and generalised Dunn indices). + See also the 'Python' version of 'genieclust' available on 'PyPI', which + supports sparse data, more metrics, and even larger datasets. + date_publication: '2024-08-22' + bug_reports: https://github.com/gagolews/genieclust/issues + url: https://genieclust.gagolewski.com/ + url_cran: https://CRAN.R-project.org/package=genieclust + url_git: https://github.com/gagolews/genieclust +genio: + version: 1.1.2 + title: Genetics Input/Output Functions + maintainer: Alejandro Ochoa + description: Implements readers and writers for file formats associated with genetics + data. Reading and writing Plink BED/BIM/FAM and GCTA binary GRM formats is fully + supported, including a lightning-fast BED reader and writer implementations. Other + functions are 'readr' wrappers that are more constrained, user-friendly, and efficient + for these particular applications; handles Plink and Eigenstrat tables (FAM, BIM, + IND, and SNP files). There are also make functions for FAM and BIM tables with + default values to go with simulated genotype data. + date_publication: '2023-01-06' + bug_reports: https://github.com/OchoaLab/genio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=genio + url_git: https://github.com/OchoaLab/genio +geniusr: + version: 1.2.1 + title: Tools for Working with the 'Genius' API + maintainer: Ewen Henderson + description: |- + Provides tools to interact nicely with the 'Genius' API + . + Search hosted content, extract associated metadata and retrieve lyrics with ease. + date_publication: '2022-09-03' + bug_reports: https://github.com/ewenme/geniusr/issues + url: https://ewenme.github.io/geniusr/ + url_cran: https://CRAN.R-project.org/package=geniusr + url_git: https://github.com/ewenme/geniusr +genlasso: + version: 1.6.1 + title: Path Algorithm for Generalized Lasso Problems + maintainer: Taylor B. Arnold + description: Computes the solution path for generalized lasso problems. Important + use cases are the fused lasso over an arbitrary graph, and trend fitting of any + given polynomial order. Specialized implementations for the latter two subproblems + are given to improve stability and speed. See Taylor Arnold and Ryan Tibshirani + (2016) . + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genlasso + url_git: https://github.com/glmgen/genlasso +GENLIB: + version: 1.1.10 + title: Genealogical Data Analysis + maintainer: Marie-Helene Roy-Gagnon + description: 'Genealogical data analysis including descriptive statistics (e.g., + kinship and inbreeding coefficients) and gene-dropping simulations. See: "GENLIB: + an R package for the analysis of genealogical data" Gauvin et al. (2015) .' + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GENLIB + url_git: '' +genlogis: + version: 1.0.2 + title: Generalized Logistic Distribution + maintainer: Eduardo Hellas + description: Provides basic distribution functions for a generalized logistic distribution + proposed by Rathie and Swamee (2006) . + It also has an interactive 'RStudio' plot for better guessing dynamically of initial + values for ease of included optimization and simulating. + date_publication: '2024-02-03' + bug_reports: '' + url: https://pinduzera.github.io/genlogis/ + url_cran: https://CRAN.R-project.org/package=genlogis + url_git: '' +GenMarkov: + version: 0.2.0 + title: Multivariate Markov Chains + maintainer: Carolina Vasconcelos + description: Provides routines to estimate the Mixture Transition Distribution Model + based on Raftery (1985) and Nicolau (2014) + specifications, for multivariate data. Additionally, + provides a function for the estimation of a new model for multivariate non-homogeneous + Markov chains. This new specification, Generalized Multivariate Markov Chains + (GMMC) was proposed by Carolina Vasconcelos and Bruno Damasio and considers (continuous + or discrete) covariates exogenous to the Markov chain. + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenMarkov + url_git: '' +genMCMCDiag: + version: 0.2.3 + title: |- + Generalized Convergence Diagnostics for Difficult MCMC + Algorithms + maintainer: Luke Duttweiler + description: Trace plots and convergence diagnostics for Markov Chain Monte Carlo + (MCMC) algorithms on highly multivariate or unordered spaces. Methods outlined + in a forthcoming paper. + date_publication: '2025-01-09' + bug_reports: https://github.com/LukeDuttweiler/genMCMCDiag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=genMCMCDiag + url_git: https://github.com/LukeDuttweiler/genMCMCDiag +GENMETA: + version: 0.2.0 + title: |- + Implements Generalized Meta-Analysis Using Iterated Reweighted + Least Squares Algorithm + maintainer: Prosenjit Kundu + description: Generalized meta-analysis is a technique for estimating parameters + associated with a multiple regression model through meta-analysis of studies which + may have information only on partial sets of the regressors. It estimates the + effects of each variable while fully adjusting for all other variables that are + measured in at least one of the studies. Using algebraic relationships between + regression parameters in different dimensions, a set of moment equations is specified + for estimating the parameters of a maximal model through information available + on sets of parameter estimates from a series of reduced models available from + the different studies. The specification of the equations requires a reference + dataset to estimate the joint distribution of the covariates. These equations + are solved using the generalized method of moments approach, with the optimal + weighting of the equations taking into account uncertainty associated with estimates + of the parameters of the reduced models. The proposed framework is implemented + using iterated reweighted least squares algorithm for fitting generalized linear + regression models. For more details about the method, please see pre-print version + of the manuscript on generalized meta-analysis by Prosenjit Kundu, Runlong Tang + and Nilanjan Chatterjee (2018) .The current version + (0.2.0) is updated to address some of the stability issues in the previous version + (0.1). + date_publication: '2022-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GENMETA + url_git: '' +geno2proteo: + version: 0.0.6 + title: |- + Finding the DNA and Protein Sequences of Any Genomic or + Proteomic Loci + maintainer: Yaoyong Li + description: |- + Using the DNA sequence and gene annotation files provided in + 'ENSEMBL' , + the functions implemented in the package try to find the DNA sequences and + protein sequences of any given genomic loci, and to find the genomic coordinates + and protein sequences of any given protein locations, which are the frequent + tasks in the analysis of genomic and proteomic data. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geno2proteo + url_git: '' +genodds: + version: 1.1.2 + title: Generalised Odds Ratios + maintainer: Hannah Johns + description: |2- + + Calculates Agresti's generalized odds ratios. + For a randomly selected pair of observations + from two groups, calculates the odds that + the second group will have a higher scoring outcome + than that of the first group. + Package provides hypothesis testing for if this odds + ratio is significantly different to 1 (equal chance). + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genodds + url_git: '' +genogeographer: + version: 0.1.19 + title: Methods for Analysing Forensic Ancestry Informative Markers + maintainer: Torben Tvedebrink + description: Evaluates likelihood ratio tests for alleged ancestry. Implements the + methods of Tvedebrink et al (2018) . + date_publication: '2019-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genogeographer + url_git: '' +GenomeAdmixR: + version: 2.1.7 + title: Simulate Admixture of Genomes + maintainer: Thijs Janzen + description: |- + Individual-based simulations forward in time, + simulating how patterns in ancestry along the genome change after + admixture. Full description can be found in Janzen (2021) + . + date_publication: '2022-03-01' + bug_reports: https://github.com/thijsjanzen/GenomeAdmixR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GenomeAdmixR + url_git: https://github.com/thijsjanzen/GenomeAdmixR +genomic.autocorr: + version: 1.0-1 + title: Models Dealing with Spatial Dependency in Genomic Data + maintainer: Chris Wallace + description: Local structure in genomic data often induces dependence between observations + taken at different genomic locations. Ignoring this dependence leads to underestimation + of the standard error of parameter estimates. This package uses block bootstrapping + to estimate asymptotically correct standard errors of parameters from any standard + generalised linear model that may be fit by the glm() function. + date_publication: '2017-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genomic.autocorr + url_git: https://github.com/chr1swallace/genomic.autocorr +genomicper: + version: '1.7' + title: |- + Circular Genomic Permutation using Genome Wide Association + p-Values + maintainer: Claudia P Cabrera + description: 'Circular genomic permutation approach uses genome wide association + studies (GWAS) results to establish the significance of pathway/gene-set associations + whilst accounting for genomic structure(Cabrera et al (2012) ). + All single nucleotide polymorphisms (SNPs) in the GWAS are placed in a ''circular + genome'' according to their location. Then the complete set of SNP association + p-values are permuted by rotation with respect to the SNPs'' genomic locations. + Two testing frameworks are available: permutations at the gene level, and permutations + at the SNP level. The permutation at the gene level uses Fisher''s combination + test to calculate a single gene p-value, followed by the hypergeometric test. + The SNP count methodology maps each SNP to pathways/gene-sets and calculates the + proportion of SNPs for the real and the permutated datasets above a pre-defined + threshold. Genomicper requires a matrix of GWAS association p-values and SNPs + annotation to genes. Pathways can be obtained from within the package or can be + provided by the user.' + date_publication: '2021-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genomicper + url_git: '' +GenomicSig: + version: 0.1.0 + title: Computation of Genomic Signatures + maintainer: Anu Sharma + description: Genomic signatures represent unique features within a species' DNA, + enabling the differentiation of species and offering broad applications across + various fields. This package provides essential tools for calculating these specific + signatures, streamlining the process for researchers and offering a comprehensive + and time-saving solution for genomic analysis.The amino acid contents are identified + based on the work published by Sandberg et al. (2003) + and Xiao et al. (2015) . The Average Mutual + Information Profiles (AMIP) values are calculated based on the work of Bauer et + al. (2008) . The Chaos Game Representation (CGR) plot + visualization was done based on the work of Deschavanne et al. (1999) + and Jeffrey et al. (1990) . The GC content is calculated + based on the work published by Nakabachi et al. (2006) + and Barbu et al. (1956) . The Oligonucleotide + Frequency Derived Error Gradient (OFDEG) values are computed based on the work + published by Saeed et al. (2009) . The Relative + Synonymous Codon Usage (RSCU) values are calculated based on the work published + by Elek (2018) . + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenomicSig + url_git: '' +GenomicTools.fileHandler: + version: 0.1.5.9 + title: File Handlers for Genomic Data Analysis + maintainer: Daniel Fischer + description: A collection of I/O tools for handling the most commonly used genomic + datafiles, like fasta/-q, bed, gff, gtf, ped/map and vcf. + date_publication: '2020-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenomicTools.fileHandler + url_git: '' +genoPlotR: + version: 0.8.11 + title: Plot Publication-Grade Gene and Genome Maps + maintainer: Lionel Guy + description: |- + Draws gene or genome maps and comparisons between these, in a + publication-grade manner. Starting from simple, common files, it will + draw postscript or PDF files that can be sent as such to journals. + date_publication: '2021-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genoPlotR + url_git: http://genoplotr.r-forge.r-project.org/ +GenoPop: + version: 1.0.0 + title: |- + Genotype Imputation and Population Genomics Efficiently from + Variant Call Formatted (VCF) Files + maintainer: Marie Gurke + description: Tools for efficient processing of large, whole genome genotype data + sets in variant call format (VCF). It includes several functions to calculate + commonly used population genomic metrics and a method for reference panel free + genotype imputation, which is described in the preprint Gurke & Mayer (2024) . + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenoPop + url_git: '' +GenOrd: + version: 1.4.0 + title: |- + Simulation of Discrete Random Variables with Given Correlation + Matrix and Marginal Distributions + maintainer: Alessandro Barbiero + description: A gaussian copula based procedure for generating samples from discrete + random variables with prescribed correlation matrix and marginal distributions. + date_publication: '2015-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenOrd + url_git: '' +GenoScan: + version: '0.1' + title: |- + A Genome-Wide Scan Statistic Framework for Whole-Genome Sequence + Data Analysis + maintainer: Zihuai He + description: Functions for whole-genome sequencing studies, including genome-wide + scan, candidate region scan and single window test. + date_publication: '2018-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenoScan + url_git: '' +GenoTriplo: + version: 1.1.2 + title: Genotyping Triploids (or Diploids) from Luminescence Data + maintainer: Julien Roche + description: |- + Genotyping of triploid individuals from luminescence data (marker probeset A and B). Works also for diploids. + Two main functions: Run_Clustering() that regroups individuals with a same genotype based on proximity and + Run_Genotyping() that assigns a genotype to each cluster. For Shiny interface use: launch_GenoShiny(). + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenoTriplo + url_git: '' +genpathmox: + version: '1.1' + title: Pathmox Approach Segmentation Tree Analysis + maintainer: Giuseppe Lamberti + description: |- + It provides an interesting solution for handling a high number + of segmentation variables in partial least squares structural equation + modeling. The package implements the "Pathmox" algorithm (Lamberti, Sanchez, + and Aluja,(2016)) including the F-coefficient + test (Lamberti, Sanchez, and Aluja,(2017)) + to detect the path coefficients responsible for the identified differences). + The package also allows running the hybrid multi-group approach (Lamberti (2021) + ). + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genpathmox + url_git: '' +genpwr: + version: 1.0.4 + title: Power Calculations Under Genetic Model Misspecification + maintainer: Camille Moore + description: |- + Power and sample size calculations for genetic association studies allowing + for misspecification of the model of genetic susceptibility. + "Hum Hered. 2019;84(6):256-271.. Epub 2020 Jul 28." + Power and/or sample size can be calculated for logistic (case/control study design) + and linear (continuous phenotype) regression models, using additive, dominant, + recessive or degree of freedom coding of the genetic covariate while assuming + a true dominant, recessive or additive genetic effect. In addition, power and + sample size calculations can be performed for gene by environment interactions. + These methods are extensions of Gauderman (2002) + and Gauderman (2002) + and are described in: + Moore CM, Jacobson S, Fingerlin TE. Power and Sample Size Calculations + for Genetic Association Studies in the Presence of Genetic Model Misspecification. + American Society of Human Genetics. + October 2018, San Diego. + date_publication: '2021-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genpwr + url_git: '' +genridge: + version: 0.8.0 + title: Generalized Ridge Trace Plots for Ridge Regression + maintainer: Michael Friendly + description: |- + The genridge package introduces generalizations of the standard univariate + ridge trace plot used in ridge regression and related methods. These graphical methods + show both bias (actually, shrinkage) and precision, by plotting the covariance ellipsoids of the estimated + coefficients, rather than just the estimates themselves. 2D and 3D plotting methods are provided, + both in the space of the predictor variables and in the transformed space of the PCA/SVD of the + predictors. + date_publication: '2024-12-02' + bug_reports: https://github.com/friendly/genridge/issues + url: https://friendly.github.io/genridge/ + url_cran: https://CRAN.R-project.org/package=genridge + url_git: https://github.com/friendly/genridge +GenSA: + version: 1.1.14.1 + title: R Functions for Generalized Simulated Annealing + maintainer: Sylvain Gubian + description: |- + Performs search for global minimum of a very complex non-linear + objective function with a very large number of optima. + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenSA + url_git: '' +genscore: + version: 1.0.2.2 + title: Generalized Score Matching Estimators + maintainer: Shiqing Yu + description: Implementation of the Generalized Score Matching estimator in Yu et + al. (2019) for non-negative graphical + models (truncated Gaussian, exponential square-root, gamma, a-b models) and univariate + truncated Gaussian distributions. Also includes the original estimator for untruncated + Gaussian graphical models from Lin et al. (2016) , with + the addition of a diagonal multiplier. + date_publication: '2023-12-16' + bug_reports: https://github.com/sqyu/genscore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=genscore + url_git: https://github.com/sqyu/genscore +genSEIR: + version: 0.1.1 + title: Predict Epidemic Curves with Generalized SEIR Modeling + maintainer: Selcuk Korkmaz + description: Performs generalized Susceptible-Exposed-Infected-Recovered (SEIR) + modeling to predict epidemic curves. The method is described in Peng et al. (2020) + . + date_publication: '2021-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genSEIR + url_git: '' +genset: + version: 0.1.0 + title: Generates Data Sets for Class Demonstrations + maintainer: Lori Murray + description: For educational purposes to demonstrate the importance of multiple + regression. The genset function generates a data set from an initial data set + to have the same summary statistics (mean, median, and standard deviation) but + opposing regression results. + date_publication: '2020-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genset + url_git: '' +gensphere: + version: '1.3' + title: Generalized Spherical Distributions + maintainer: John P Nolan + description: |- + Define and compute with generalized spherical distributions - multivariate probability + laws that are specified by a star shaped contour (directional behavior) and a radial component. + The methods are described in Nolan (2016) . + date_publication: '2021-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gensphere + url_git: '' +genstab: + version: 1.0.0 + title: Resampling Based Yield Stability Analyses + maintainer: Jixiang Wu + description: 'Several yield stability analyses are mentioned in this package: variation + and regression based yield stability analyses. Resampling techniques are integrated + with these stability analyses. The function stab.mean() provides the genotypic + means and ranks including their corresponding confidence intervals. The function + stab.var() provides the genotypic variances over environments including their + corresponding confidence intervals. The function stab.fw() is an extended method + from the Finlay-Wilkinson method (1963). This method can include several other + factors that might impact yield stability. Resampling technique is integrated + into this method. A few missing data points or unbalanced data are allowed too. + The function stab.fw.check() is an extended method from the Finlay-Wilkinson method + (1963). The yield stability is evaluated via common check line(s). Resampling + technique is integrated.' + date_publication: '2021-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genstab + url_git: '' +genSurv: + version: 1.0.4 + title: Generating Multi-State Survival Data + maintainer: Artur Araujo + description: |- + Generation of survival data with one (binary) + time-dependent covariate. Generation of survival data arising + from a progressive illness-death model. + date_publication: '2021-10-19' + bug_reports: https://github.com/arturstat/genSurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=genSurv + url_git: https://github.com/arturstat/genSurv +gensvm: + version: 0.1.7 + title: A Generalized Multiclass Support Vector Machine + maintainer: Gertjan van den Burg + description: |- + The GenSVM classifier is a generalized multiclass support vector + machine (SVM). This classifier aims to find decision boundaries that + separate the classes with as wide a margin as possible. In GenSVM, the + loss function is very flexible in the way that misclassifications are + penalized. This allows the user to tune the classifier to the dataset + at hand and potentially obtain higher classification accuracy than + alternative multiclass SVMs. Moreover, this flexibility means that + GenSVM has a number of other multiclass SVMs as special cases. One of + the other advantages of GenSVM is that it is trained in the primal + space, allowing the use of warm starts during optimization. This + means that for common tasks such as cross validation or repeated model + fitting, GenSVM can be trained very quickly. Based on: G.J.J. van den + Burg and P.J.F. Groenen (2018) . + date_publication: '2023-01-28' + bug_reports: https://github.com/GjjvdBurg/RGenSVM + url: '' + url_cran: https://CRAN.R-project.org/package=gensvm + url_git: https://github.com/GjjvdBurg/RGenSVMhttps://jmlr.org/papers/v17/14-526.html +GenTag: + version: '1.0' + title: Generate Color Tag Sequences + maintainer: Carlos Biagolini-Jr. + description: Implement a coherent and flexible protocol for animal color tagging. + 'GenTag' provides a simple computational routine with low CPU usage to create + color sequences for animal tag. First, a single-color tag sequence is created + from an algorithm selected by the user, followed by verification of the combination + uniqueness. Three methods to produce color tag sequences are provided. Users can + modify the main function core to allow a wide range of applications. + date_publication: '2019-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenTag + url_git: '' +genTS: + version: 0.1.4 + title: R Shiny App for Creating Simplified Trial Summary (TS) Domain + maintainer: Hanming Tu + description: |- + Make it easy to create simplified trial summary (TS) domain + based on FDA FDA guide + . + date_publication: '2022-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=genTS + url_git: '' +GenTwoArmsTrialSize: + version: 0.0.5 + title: Generalized Two Arms Clinical Trial Sample Size Calculation + maintainer: Chel Hee Lee + description: 'Two arms clinical trials required sample size is calculated in the + comprehensive parametric context. The calculation is based on the type of endpoints(continuous/binary/time-to-event/ordinal), + design (parallel/crossover), hypothesis tests (equality/noninferiority/superiority/equivalence), + trial arms noncompliance rates and expected loss of follow-up. Methods are described + in: Chow SC, Shao J, Wang H, Lokhnygina Y (2017) , + Wittes, J (2002) , Sato, T (2000) , + Lachin J M, Foulkes, M A (1986) , Whitehead J(1993) , + Julious SA (2023) .' + date_publication: '2024-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenTwoArmsTrialSize + url_git: '' +GenWin: + version: '1.0' + title: Spline Based Window Boundaries for Genomic Analyses + maintainer: Timothy M. Beissinger + description: |- + Defines window or bin boundaries for the analysis of genomic data. + Boundaries are based on the inflection points of a cubic smoothing spline + fitted to the raw data. Along with defining boundaries, a technique to + evaluate results obtained from unequally-sized windows is provided. + Applications are particularly pertinent for, though not limited to, genome + scans for selection based on variability between populations (e.g. using + Wright's fixations index, Fst, which measures variability in subpopulations + relative to the total population). + date_publication: '2022-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GenWin + url_git: '' +GeoAdjust: + version: 2.0.0 + title: |- + Accounting for Random Displacements of True GPS Coordinates of + Data + maintainer: Umut Altay + description: |- + The purpose is to account for the random displacements + (jittering) of true survey household cluster center coordinates in geostatistical + analyses of Demographic and Health Surveys program (DHS) data. Adjustment for + jittering can be implemented either in the spatial random effect, or in the + raster/distance based covariates, or in both. Detailed information about the methods + behind the package functionality can be found in two preprints. + Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad (2022) . + Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad (2022) . + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeoAdjust + url_git: '' +geoAr: + version: 1.0.0 + title: Argentina's Spatial Data Toolbox + maintainer: Juan Pablo Ruiz Nicolini + description: Collection of tools that facilitates data access and workflow for spatial + analysis of Argentina. Includes historical information from censuses, administrative + limits at different levels of aggregation, location of human settlements, among + others. Since it is expected that the majority of users will be Spanish-speaking, + the documentation of the package prioritizes this language, although an effort + is made to also offer annotations in English. + date_publication: '2024-03-03' + bug_reports: https://github.com/PoliticaArgentina/geoAr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geoAr + url_git: https://github.com/PoliticaArgentina/geoAr +geoarrow: + version: 0.2.1 + title: Extension Types for Spatial Data for Use with 'Arrow' + maintainer: Dewey Dunnington + description: |- + Provides extension types and conversions to between R-native + object types and 'Arrow' columnar types. This includes integration among + the 'arrow', 'nanoarrow', 'sf', and 'wk' packages such that spatial + metadata is preserved wherever possible. Extension type implementations + ensure first-class geometry data type support in the 'arrow' and 'nanoarrow' + packages. + date_publication: '2024-06-13' + bug_reports: https://github.com/geoarrow/geoarrow-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geoarrow + url_git: https://github.com/geoarrow/geoarrow-r +geoBayes: + version: 0.7.4 + title: |- + Analysis of Geostatistical Data using Bayes and Empirical Bayes + Methods + maintainer: Evangelos Evangelou + description: |- + Functions to fit geostatistical data. The data can be + continuous, binary or count data and the models implemented are + flexible. Conjugate priors are assumed on some parameters while + inference on the other parameters can be done through a full + Bayesian analysis of by empirical Bayes methods. + date_publication: '2024-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geoBayes + url_git: '' +geobr: + version: 1.9.1 + title: Download Official Spatial Data Sets of Brazil + maintainer: Rafael H. M. Pereira + description: |- + Easy access to official spatial data sets of Brazil as 'sf' objects + in R. The package includes a wide range of geospatial data available + at various geographic scales and for various years with harmonized + attributes, projection and fixed topology. + date_publication: '2024-09-06' + bug_reports: https://github.com/ipeaGIT/geobr/issues + url: https://ipeagit.github.io/geobr/ + url_cran: https://CRAN.R-project.org/package=geobr + url_git: https://github.com/ipeaGIT/geobr +geocacheR: + version: 0.1.0 + title: Tools for Geocaching + maintainer: Alun Hewinson + description: |- + Tools for solving common geocaching puzzle types, and other + Geocaching-related tasks. + date_publication: '2020-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geocacheR + url_git: '' +geocausal: + version: 0.3.4 + title: Causal Inference with Spatio-Temporal Data + maintainer: Mitsuru Mukaigawara + description: |- + Spatio-temporal causal inference based on point process data. + You provide the raw data of locations and timings of treatment and + outcome events, specify counterfactual scenarios, and the package + estimates causal effects over specified spatial and temporal windows. + See Papadogeorgou, et al. (2022) and + Mukaigawara, et al. (2024) . + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geocausal + url_git: https://github.com/mmukaigawara/geocausal +geocmeans: + version: 0.3.4 + title: |- + Implementing Methods for Spatial Fuzzy Unsupervised + Classification + maintainer: Jeremy Gelb + description: |- + Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed. + The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 and Zaho and al. 2013 ) and recently applied in geography (see Gelb and Apparicio ). + date_publication: '2023-09-12' + bug_reports: https://github.com/JeremyGelb/geocmeans/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geocmeans + url_git: https://github.com/JeremyGelb/geocmeans +geocodebr: + version: 0.1.1 + title: |- + Geolocalização De Endereços Brasileiros (Geocoding Brazilian + Addresses) + maintainer: Rafael H. M. Pereira + description: |- + Método simples e eficiente de geolocalizar dados no Brasil. O + pacote é baseado em conjuntos de dados espaciais abertos de endereços + brasileiros, utilizando principalmente o Cadastro Nacional de Endereços para + Fins Estatísticos (CNEFE). O CNEFE é publicado pelo Instituto Brasileiro de + Geografia e Estatística (IBGE), órgão oficial de estatísticas e geografia do + Brasil. (A simple and efficient method for geolocating data in Brazil. The + package is based on open spatial datasets of Brazilian addresses, primarily + using the Cadastro Nacional de Endereços para Fins Estatísticos (CNEFE), + published by the Instituto Brasileiro de Geografia e Estatística (IBGE), + Brazil's official statistics and geography agency.) + date_publication: '2025-02-17' + bug_reports: https://github.com/ipeaGIT/geocodebr/issues + url: https://ipeagit.github.io/geocodebr/ + url_cran: https://CRAN.R-project.org/package=geocodebr + url_git: https://github.com/ipeaGIT/geocodebr +geocomplexity: + version: 0.2.1 + title: Mitigating Spatial Bias Through Geographical Complexity + maintainer: Wenbo Lv + description: The geographical complexity of individual variables can be characterized + by the differences in local attribute variables, while the common geographical + complexity of multiple variables can be represented by fluctuations in the similarity + of vectors composed of multiple variables. In spatial regression tasks, the goodness + of fit can be improved by incorporating a geographical complexity representation + vector during modeling, using a geographical complexity-weighted spatial weight + matrix, or employing local geographical complexity kernel density. Similarly, + in spatial sampling tasks, samples can be selected more effectively by using a + method that weights based on geographical complexity. By optimizing performance + in spatial regression and spatial sampling tasks, the spatial bias of the model + can be effectively reduced. + date_publication: '2024-11-11' + bug_reports: https://github.com/ausgis/geocomplexity/issues + url: https://ausgis.github.io/geocomplexity/ + url_cran: https://CRAN.R-project.org/package=geocomplexity + url_git: https://github.com/ausgis/geocomplexity +geodaData: + version: 0.1.0 + title: Spatial Analysis Datasets for Teaching + maintainer: Angela Li + description: |- + Stores small spatial datasets used to teach basic spatial analysis + concepts. Datasets are based off of the 'GeoDa' software workbook and data + site developed by Luc Anselin + and team at the University of Chicago. Datasets are stored as 'sf' objects. + date_publication: '2020-05-27' + bug_reports: https://github.com/spatialanalysis/geodaData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geodaData + url_git: https://github.com/spatialanalysis/geodaData +geodata: + version: 0.6-2 + title: Download Geographic Data + maintainer: Robert J. Hijmans + description: Functions for downloading of geographic data for use in spatial analysis + and mapping. The package facilitates access to climate, crops, elevation, land + use, soil, species occurrence, accessibility, administrative boundaries and other + data. + date_publication: '2024-06-10' + bug_reports: https://github.com/rspatial/geodata/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=geodata + url_git: '' +geodetector: + version: 1.0-5 + title: |- + Stratified Heterogeneity Measure, Dominant Driving Force + Detection, Interaction Relationship Investigation + maintainer: Chengdong Xu + description: 'Spatial stratified heterogeneity (SSH), referring to the within strata + are more similar than the between strata, a model with global parameters would + be confounded if input data is SSH. Note that the "spatial" here can be either + geospatial or the space in mathematical meaning. Geographical detector is a novel + tool to investigate SSH: (1) measure and find SSH of a variable Y; (2) test the + power of determinant X of a dependent variable Y according to the consistency + between their spatial distributions; and (3) investigate the interaction between + two explanatory variables X1 and X2 to a dependent variable Y (Wang et al 2014 + , Wang, Zhang, and Fu 2016 ).' + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geodetector + url_git: '' +geodimension: + version: 2.0.0 + title: Definition of Geographic Dimensions + maintainer: Jose Samos + description: |- + The geographic dimension plays a fundamental role in + multidimensional systems. To define a geographic dimension in a star + schema, we need a table with attributes corresponding to the levels of + the dimension. Additionally, we will also need one or more geographic + layers to represent the data using this dimension. The goal of this + package is to support the definition of geographic dimensions from + layers of geographic information related to each other. It makes it + easy to define relationships between layers and obtain the necessary + data from them. + date_publication: '2024-01-09' + bug_reports: https://github.com/josesamos/geodimension/issues + url: https://josesamos.github.io/geodimension/ + url_cran: https://CRAN.R-project.org/package=geodimension + url_git: https://github.com/josesamos/geodimension +geodist: + version: 0.1.0 + title: Fast, Dependency-Free Geodesic Distance Calculations + maintainer: Mark Padgham + description: |- + Dependency-free, ultra fast calculation of geodesic + distances. Includes the reference nanometre-accuracy geodesic + distances of Karney (2013) , as used by + the 'sf' package, as well as Haversine and Vincenty distances. Default + distance measure is the "Mapbox cheap ruler" which is generally more + accurate than Haversine or Vincenty for distances out to a few hundred + kilometres, and is considerably faster. The main function accepts one + or two inputs in almost any generic rectangular form, and returns + either matrices of pairwise distances, or vectors of sequential + distances. + date_publication: '2024-05-23' + bug_reports: https://github.com/hypertidy/geodist/issues + url: https://hypertidy.github.io/geodist/ + url_cran: https://CRAN.R-project.org/package=geodist + url_git: https://github.com/hypertidy/geodist +geodiv: + version: 1.1.0 + title: Methods for Calculating Gradient Surface Metrics + maintainer: Annie C. Smith + description: |- + Methods for calculating gradient surface metrics for + continuous analysis of landscape features. + date_publication: '2023-10-05' + bug_reports: https://github.com/bioXgeo/geodiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geodiv + url_git: https://github.com/bioXgeo/geodiv +geodl: + version: 0.2.0 + title: Geospatial Semantic Segmentation with Torch and Terra + maintainer: Aaron Maxwell + description: |- + Provides tools for semantic segmentation of geospatial data using convolutional neural + network-based deep learning. Utility functions allow for creating masks, image chips, data frames listing image + chips in a directory, and DataSets for use within DataLoaders. Additional functions are provided to serve as checks + during the data preparation and training process. A UNet architecture can be defined with 4 blocks in the encoder, a + bottleneck block, and 4 blocks in the decoder. The UNet can accept a variable number of input channels, and the user + can define the number of feature maps produced in each encoder and decoder block and the bottleneck. Users can also + choose to (1) replace all rectified linear unit (ReLU) activation functions with leaky ReLU or swish, (2) implement attention gates along the + skip connections, (3) implement squeeze and excitation modules within the encoder blocks, (4) add residual connections + within all blocks, (5) replace the bottleneck with a modified atrous spatial pyramid pooling (ASPP) module, and/or + (6) implement deep supervision using predictions generated at each stage in the decoder. A unified focal loss framework is implemented after + Yeung et al. (2022) . We have also implemented + assessment metrics using the 'luz' package including F1-score, recall, and precision. Trained models can be used to predict to spatial + data without the need to generate chips from larger spatial extents. Functions are available for performing accuracy assessment. The package + relies on 'torch' for implementing deep learning, which does not require the installation of a 'Python' environment. Raster geospatial + data are handled with 'terra'. Models can be trained using a Compute Unified Device Architecture (CUDA)-enabled graphics processing unit (GPU); + however, multi-GPU training is not supported by 'torch' in 'R'. + date_publication: '2024-08-20' + bug_reports: https://github.com/maxwell-geospatial/geodl/issues + url: https://doi.org/10.31223/X53M6T + url_cran: https://CRAN.R-project.org/package=geodl + url_git: https://github.com/maxwell-geospatial/geodl +geodrawr: + version: 2.0.0 + title: Making Geospatial Objects + maintainer: Heoncheol Ha + description: |- + Draw geospatial objects by clicks on the map. + This packages can help data analyst who want to check + their own geospatial hypothesis but has no ready-made geospatial objects. + date_publication: '2020-11-08' + bug_reports: https://github.com/Curycu/geodrawr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geodrawr + url_git: https://github.com/Curycu/geodrawr +GeodRegr: + version: 0.2.0 + title: Geodesic Regression + maintainer: Ha-Young Shin + description: 'Provides a gradient descent algorithm to find a geodesic relationship + between real-valued independent variables and a manifold-valued dependent variable + (i.e. geodesic regression). Available manifolds are Euclidean space, the sphere, + hyperbolic space, and Kendall''s 2-dimensional shape space. Besides the standard + least-squares loss, the least absolute deviations, Huber, and Tukey biweight loss + functions can also be used to perform robust geodesic regression. Functions to + help choose appropriate cutoff parameters to maintain high efficiency for the + Huber and Tukey biweight estimators are included, as are functions for generating + random tangent vectors from the Riemannian normal distributions on the sphere + and hyperbolic space. The n-sphere is a n-dimensional manifold: we represent it + as a sphere of radius 1 and center 0 embedded in (n+1)-dimensional space. Using + the hyperboloid model of hyperbolic space, n-dimensional hyperbolic space is embedded + in (n+1)-dimensional Minkowski space as the upper sheet of a hyperboloid of two + sheets. Kendall''s 2D shape space with K landmarks is of real dimension 2K-4; + preshapes are represented as complex K-vectors with mean 0 and magnitude 1. Details + are described in Shin, H.-Y. and Oh, H.-S. (2020) . Also see + Fletcher, P. T. (2013) .' + date_publication: '2021-09-03' + bug_reports: https://github.com/hayoungshin1/GeodRegr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeodRegr + url_git: https://github.com/hayoungshin1/GeodRegr +geoelectrics: + version: 0.2.2 + title: 3D-Visualization of Geoelectric Resistivity Measurement Profiles + maintainer: Anja Kleebaum + description: Visualizes two-dimensional geoelectric resistivity measurement profiles + in three dimensions. + date_publication: '2023-02-01' + bug_reports: https://github.com/kleebaum/geoelectrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geoelectrics + url_git: https://github.com/kleebaum/geoelectrics +geofacet: + version: 0.2.1 + title: '''ggplot2'' Faceting Utilities for Geographical Data' + maintainer: Ryan Hafen + description: |- + Provides geographical faceting functionality for 'ggplot2'. + Geographical faceting arranges a sequence of plots of data for different + geographical entities into a grid that preserves some of the geographical + orientation. + date_publication: '2023-11-30' + bug_reports: https://github.com/hafen/geofacet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geofacet + url_git: https://github.com/hafen/geofacet +geofi: + version: 1.0.18 + title: Access Finnish Geospatial Data + maintainer: Markus Kainu + description: Designed to simplify geospatial data access from the Statistics Finland + Web Feature Service API , the geofi + package offers researchers and analysts a set of tools to obtain and harmonize + administrative spatial data for a wide range of applications, from urban planning + to environmental research. The package contains annually updated time series of + municipality key datasets that can be used for data aggregation and language translations. + date_publication: '2025-02-11' + bug_reports: https://github.com/rOpenGov/geofi/issues + url: https://ropengov.github.io/geofi/ + url_cran: https://CRAN.R-project.org/package=geofi + url_git: https://github.com/rOpenGov/geofi +GeoFIS: + version: 1.1.1 + title: Spatial Data Processing for Decision Making + maintainer: Jean-Luc Lablée + description: |- + Methods for processing spatial data for decision-making. + This package is an R implementation of methods provided by the open source software GeoFIS (Leroux et al. 2018) . + The main functionalities are the management zone delineation (Pedroso et al. 2010) and data aggregation (Mora-Herrera et al. 2020) . + date_publication: '2024-12-18' + bug_reports: '' + url: https://www.geofis.org + url_cran: https://CRAN.R-project.org/package=GeoFIS + url_git: '' +geoFKF: + version: 0.1.1 + title: Kriging Method for Spatial Functional Data + maintainer: Gilberto Sassi + description: |- + A Kriging method for functional datasets with spatial dependency. + This functional Kriging method avoids the need to estimate the + trace-variogram, and the curve is estimated by minimizing a quadratic + form. The curves in the functional dataset are smoothed using Fourier + series. The functional Kriging of this package is a modification of the + method proposed by Giraldo (2011) . + date_publication: '2022-08-12' + bug_reports: https://github.com/gilberto-sassi/geoFKF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geoFKF + url_git: https://github.com/gilberto-sassi/geoFKF +geoFourierFDA: + version: 0.1.0 + title: |- + Ordinary Functional Kriging Using Fourier Smoothing and Gaussian + Quadrature + maintainer: Gilberto Sassi + description: |- + Implementation of the ordinary functional kriging method + proposed by Giraldo (2011) . This + implements an alternative method to estimate the trace-variogram using + Fourier Smoothing and Gaussian Quadrature. + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geoFourierFDA + url_git: '' +geoGAM: + version: 0.1-3 + title: Select Sparse Geoadditive Models for Spatial Prediction + maintainer: Madlene Nussbaum + description: A model building procedure to build parsimonious geoadditive model + from a large number of covariates. Continuous, binary and ordered categorical + responses are supported. The model building is based on component wise gradient + boosting with linear effects, smoothing splines and a smooth spatial surface to + model spatial autocorrelation. The resulting covariate set after gradient boosting + is further reduced through backward elimination and aggregation of factor levels. + The package provides a model based bootstrap method to simulate prediction intervals + for point predictions. A test data set of a soil mapping case study in Berne (Switzerland) + is provided. Nussbaum, M., Walthert, L., Fraefel, M., Greiner, L., and Papritz, + A. (2017) . + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geoGAM + url_git: '' +geogenr: + version: 2.0.1 + title: Generator from American Community Survey Geodatabases + maintainer: Jose Samos + description: |- + The American Community Survey (ACS) + offers geodatabases with + geographic information and associated data of interest to researchers + in the area. The goal of this package is to generate objects that + allow us to access and consult the information available in various + formats, such as in 'GeoPackage' format or in multidimensional 'ROLAP' + (Relational On-Line Analytical Processing) star format. + date_publication: '2024-01-09' + bug_reports: https://github.com/josesamos/geogenr/issues + url: https://josesamos.github.io/geogenr/ + url_cran: https://CRAN.R-project.org/package=geogenr + url_git: https://github.com/josesamos/geogenr +geogrid: + version: 0.1.2 + title: Turn Geospatial Polygons into Regular or Hexagonal Grids + maintainer: Ryan Hafen + description: |- + Turn irregular polygons (such as geographical regions) into regular or hexagonal grids. + This package enables the generation of regular (square) and hexagonal grids through the package + 'sp' and then assigns the content of the existing polygons to the new grid using + the Hungarian algorithm, Kuhn (1955) (). + This prevents the need for manual generation of hexagonal grids or regular grids + that are supposed to reflect existing geography. + date_publication: '2023-08-19' + bug_reports: https://github.com/jbaileyh/geogrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geogrid + url_git: https://github.com/jbaileyh/geogrid +geohashTools: + version: 0.3.3 + title: Tools for Working with Geohashes + maintainer: Michael Chirico + description: Tools for working with Gustavo Niemeyer's geohash coordinate system, + including API for interacting with other common R GIS libraries. + date_publication: '2023-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geohashTools + url_git: https://github.com/MichaelChirico/geohashTools +geoheatmap: + version: 0.1.0 + title: Create Geospatial Cartogram Heatmaps + maintainer: Sanne J.W. Willems + description: |- + The functionality provided by this package is an expansion of the code + of the 'statebins' package, created by B. Rudis (2022), . It allows for the creation of square choropleths + for the entire world, provided an appropriate specified grid is supplied. + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geoheatmap + url_git: '' +geojson: + version: 0.3.5 + title: Classes for 'GeoJSON' + maintainer: Michael Sumner + description: |- + Classes for 'GeoJSON' to make working with 'GeoJSON' easier. + Includes S3 classes for 'GeoJSON' classes with brief summary output, + and a few methods such as extracting and adding bounding boxes, + properties, and coordinate reference systems; working with + newline delimited 'GeoJSON'; and serializing to/from 'Geobuf' binary 'GeoJSON' + format. + date_publication: '2023-08-08' + bug_reports: https://github.com/ropensci/geojson/issues + url: https://docs.ropensci.org/geojson/ + url_cran: https://CRAN.R-project.org/package=geojson + url_git: https://github.com/ropensci/geojson +geojsonio: + version: 0.11.3 + title: Convert Data from and to 'GeoJSON' or 'TopoJSON' + maintainer: Michael Mahoney + description: |- + Convert data to 'GeoJSON' or 'TopoJSON' from various R + classes, including vectors, lists, data frames, shape files, and + spatial classes. 'geojsonio' does not aim to replace packages like + 'sp', 'rgdal', 'rgeos', but rather aims to be a high level client to + simplify conversions of data from and to 'GeoJSON' and 'TopoJSON'. + date_publication: '2023-09-06' + bug_reports: https://github.com/ropensci/geojsonio/issues + url: https://docs.ropensci.org/geojsonio/ + url_cran: https://CRAN.R-project.org/package=geojsonio + url_git: https://github.com/ropensci/geojsonio +geojsonR: + version: 1.1.2 + title: A GeoJson Processing Toolkit + maintainer: Lampros Mouselimis + description: Includes functions for processing GeoJson objects + relying on 'RFC 7946' . The geojson + encoding is based on 'json11', a tiny JSON library for 'C++11' . + Furthermore, the source code is exported in R through the 'Rcpp' and 'RcppArmadillo' + packages. + date_publication: '2025-01-13' + bug_reports: https://github.com/mlampros/geojsonR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geojsonR + url_git: https://github.com/mlampros/geojsonR +geojsonsf: + version: 2.0.3 + title: GeoJSON to Simple Feature Converter + maintainer: David Cooley + description: Converts Between GeoJSON and simple feature objects. + date_publication: '2022-05-30' + bug_reports: https://github.com/SymbolixAU/geojsonsf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geojsonsf + url_git: https://github.com/SymbolixAU/geojsonsf +geomander: + version: 2.3.0 + title: Geographic Tools for Studying Gerrymandering + maintainer: Christopher T. Kenny + description: |- + A compilation of tools to complete common tasks for studying gerrymandering. + This focuses on the geographic tool side of common problems, such as linking + different levels of spatial units or estimating how to break up units. Functions + exist for creating redistricting-focused data for the US. + date_publication: '2024-02-15' + bug_reports: https://github.com/christopherkenny/geomander/issues + url: https://christophertkenny.com/geomander/ + url_cran: https://CRAN.R-project.org/package=geomander + url_git: https://github.com/christopherkenny/geomander +GEOmap: + version: 2.5-11 + title: Topographic and Geologic Mapping + maintainer: Jonathan M. Lees + description: Set of routines for making map projections (forward and inverse), topographic + maps, perspective plots, geological maps, geological map symbols, geological databases, + interactive plotting and selection of focus regions. + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEOmap + url_git: '' +geomapdata: + version: 2.0-2 + title: Data for Topographic and Geologic Mapping + maintainer: Jonathan M. Lees + description: Data sets included here are for use with package GEOmap. These include + world map, USA map, Coso map, Japan Map. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geomapdata + url_git: '' +GeomArchetypal: + version: 1.0.3 + title: Finds the Geometrical Archetypal Analysis of a Data Frame + maintainer: Demetris Christopoulos + description: |- + Performs Geometrical Archetypal Analysis after creating Grid Archetypes + which are the Cartesian Product of all minimum, maximum variable values. Since the archetypes + are fixed now, we have the ability to compute the convex composition coefficients for all + our available data points much faster by using the half part of Principal Convex Hull Archetypal method. + Additionally we can decide to keep as archetypes the closer to the Grid Archetypes ones. Finally + the number of archetypes is always 2 to the power of the dimension of our data points + if we consider them as a vector space. + Cutler, A., Breiman, L. (1994) . + Morup, M., Hansen, LK. (2012) . + Christopoulos, DT. (2024) . + date_publication: '2024-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeomArchetypal + url_git: '' +geomaroc: + version: 0.1.1 + title: Easily Visualize Geographic Data of Morocco + maintainer: Amine Andam + description: |- + Tools to easily visualize geographic data of Morocco. + This package interacts with data available through the + 'geomarocdata' package, which is available in a 'drat' + repository. The size of the 'geomarocdata' package is + approximately 12 MB. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geomaroc + url_git: https://github.com/AmineAndam04/R-geomaroc +GeomComb: + version: '1.0' + title: (Geometric) Forecast Combination Methods + maintainer: Christoph E. Weiss + description: |- + Provides eigenvector-based (geometric) forecast + combination methods; also includes simple approaches (simple average, + median, trimmed and winsorized mean, inverse rank method) and regression-based + combination. Tools for data pre-processing are available in order to deal with + common problems in forecast combination (missingness, collinearity). + date_publication: '2016-11-27' + bug_reports: https://github.com/ceweiss/GeomComb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeomComb + url_git: https://github.com/ceweiss/GeomComb +geomerge: + version: 0.3.4 + title: Geospatial Data Integration + maintainer: Karsten Donnay + description: Geospatial data integration framework that merges raster, spatial polygon, + and (dynamic) spatial points data into a spatial (panel) data frame at any geographical + resolution. + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geomerge + url_git: '' +geometa: + version: 0.9.1 + title: Tools for Reading and Writing ISO/OGC Geographic Metadata + maintainer: Emmanuel Blondel + description: |- + Provides facilities to read, write and validate geographic metadata + defined with ISO TC211 / OGC ISO geographic information metadata standards, and + encoded using the ISO 19139 and ISO 19115-3 (XML) standard technical specifications. + This includes ISO 19110 (Feature cataloguing), 19115 (dataset metadata), 19119 (service metadata) + and 19136 (GML). Other interoperable schemas from the OGC are progressively supported + as well, such as the Sensor Web Enablement (SWE) Common Data Model, the OGC GML + Coverage Implementation Schema (GMLCOV), or the OGC GML Referenceable Grid (GMLRGRID). + date_publication: '2025-02-21' + bug_reports: https://github.com/eblondel/geometa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geometa + url_git: https://github.com/eblondel/geometa/wiki +geometries: + version: 0.2.4 + title: Convert Between R Objects and Geometric Structures + maintainer: David Cooley + description: |- + Geometry shapes in 'R' are typically represented by matrices (points, lines), with more complex + shapes being lists of matrices (polygons). 'Geometries' will convert various 'R' objects into these shapes. + Conversion functions are available at both the 'R' level, and through 'Rcpp'. + date_publication: '2024-01-15' + bug_reports: https://github.com/dcooley/geometries/issues + url: https://dcooley.github.io/geometries/ + url_cran: https://CRAN.R-project.org/package=geometries + url_git: '' +geometry: + version: 0.5.2 + title: Mesh Generation and Surface Tessellation + maintainer: David C. Sterratt + description: |- + Makes the 'Qhull' library + available in R, in a similar manner as in Octave and MATLAB. Qhull + computes convex hulls, Delaunay triangulations, halfspace + intersections about a point, Voronoi diagrams, furthest-site + Delaunay triangulations, and furthest-site Voronoi diagrams. It + runs in 2D, 3D, 4D, and higher dimensions. It implements the + Quickhull algorithm for computing the convex hull. Qhull does not + support constrained Delaunay triangulations, or mesh generation of + non-convex objects, but the package does include some R functions + that allow for this. + date_publication: '2025-02-08' + bug_reports: https://github.com/davidcsterratt/geometry/issues + url: https://davidcsterratt.github.io/geometry/ + url_cran: https://CRAN.R-project.org/package=geometry + url_git: '' +geommc: + version: 0.1.1 + title: Geometric Markov Chain Sampling + maintainer: Vivekananda Roy + description: |- + Simulates from discrete and continuous target distributions + using geometric Metropolis-Hastings (MH) + algorithms. Users specify the target distribution + by an R function that evaluates the log un-normalized pdf or pmf. The package + also contains a function implementing a specific geometric MH algorithm for + performing high dimensional Bayesian variable selection. + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geommc + url_git: https://github.com/vroys/geommc +geomod: + version: 0.1.0 + title: A Computer Program for Geotechnical Investigations + maintainer: Festus Ngeno + description: |- + The 'geomod' does spatial prediction of the Geotechnical soil properties. + It predicts the spatial distribution of Geotechnical properties of soil e.g. shear strength, + permeability, plasticity index, Standard Penetration Test (SPT) counts, etc. The output of the prediction takes the form of a + map or a series of maps. It uses the interpolation technique where a single or statistically “best” + estimate of spatial occurrence soil property is determined. The interpolation is based on both the + sampled data and a variogram model for the spatial correlation of the sampled data. + The single estimate is produced by a Kriging technique. + date_publication: '2023-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geomod + url_git: '' +GeoModels: + version: 2.1.0 + title: |- + Procedures for Gaussian and Non Gaussian Geostatistical (Large) + Data Analysis + maintainer: Moreno Bevilacqua + description: Functions for Gaussian and Non Gaussian (bivariate) spatial and spatio-temporal + data analysis are provided for a) (fast) simulation of random fields, b) inference for + random fields using standard likelihood and a likelihood approximation method + called weighted composite likelihood based on pairs and b) prediction using (local) + best linear unbiased prediction. Weighted composite likelihood can be very efficient + for estimating massive datasets. Both regression and spatial (temporal) dependence + analysis can be jointly performed. Flexible covariance models for spatial and + spatial-temporal data on Euclidean domains and spheres are provided. There are + also many useful functions for plotting and performing diagnostic analysis. Different + non Gaussian random fields can be considered in the analysis. Among them, random + fields with marginal distributions such as Skew-Gaussian, Student-t, Tukey-h, + Sin-Arcsin, Two-piece, Weibull, Gamma, Log-Gaussian, Binomial, Negative Binomial and + Poisson. See the URL for the papers associated with this package, as for instance, + Bevilacqua and Gaetan (2015) , Bevilacqua et al. + (2016) , Vallejos et al. (2020) , + Bevilacqua et. al (2020) , Bevilacqua et. al (2021) , + Bevilacqua et al. (2022) , Morales-Navarrete et + al. (2023) , and a large class of examples + and tutorials. + date_publication: '2025-01-14' + bug_reports: https://github.com/vmoprojs/GeoModels/issues + url: https://vmoprojs.github.io/GeoModels-page/ + url_cran: https://CRAN.R-project.org/package=GeoModels + url_git: '' +GeoMongo: + version: 1.0.3 + title: Geospatial Queries Using 'PyMongo' + maintainer: Lampros Mouselimis + description: Utilizes methods of the 'PyMongo' 'Python' library to initialize, insert + and query 'GeoJson' data (see + for more information on 'PyMongo'). Furthermore, it allows the user to validate + 'GeoJson' objects and to use the console for 'MongoDB' (bulk) commands. The 'reticulate' + package provides the 'R' interface to 'Python' modules, classes and functions. + date_publication: '2021-09-11' + bug_reports: https://github.com/mlampros/GeoMongo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeoMongo + url_git: https://github.com/mlampros/GeoMongo +geomorph: + version: 4.0.10 + title: Geometric Morphometric Analyses of 2D and 3D Landmark Data + maintainer: Dean Adams + description: |- + Read, manipulate, and digitize landmark data, generate shape + variables via Procrustes analysis for points, curves and surfaces, perform + shape analyses, and provide graphical depictions of shapes and patterns of + shape variation. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geomorph + url_git: https://github.com/geomorphR/geomorph +geomtextpath: + version: 0.1.5 + title: Curved Text in 'ggplot2' + maintainer: Allan Cameron + description: |- + A 'ggplot2' extension that allows text to follow curved paths. + Curved text makes it easier to directly label paths or neatly annotate in + polar co-ordinates. + date_publication: '2025-01-14' + bug_reports: https://github.com/AllanCameron/geomtextpath/issues + url: https://allancameron.github.io/geomtextpath/ + url_cran: https://CRAN.R-project.org/package=geomtextpath + url_git: '' +geomultistar: + version: 1.2.2 + title: Multidimensional Queries Enriched with Geographic Data + maintainer: Jose Samos + description: |- + Multidimensional systems allow complex queries to be carried + out in an easy way. The geographical dimension, together with the + temporal dimension, plays a fundamental role in multidimensional + systems. Through this package, vector geographic data layers can be + associated to the attributes of geographic dimensions, so that the + results of multidimensional queries can be obtained directly as vector + layers. The multidimensional structures on which we can define the + queries can be created from a flat table or imported directly using + functions from this package. + date_publication: '2024-07-29' + bug_reports: https://github.com/josesamos/geomultistar/issues + url: https://josesamos.github.io/geomultistar/ + url_cran: https://CRAN.R-project.org/package=geomultistar + url_git: https://github.com/josesamos/geomultistar +geonames: + version: '0.999' + title: Interface to the "Geonames" Spatial Query Web Service + maintainer: Barry Rowlingson + description: |- + The web service at provides a number of spatial data queries, including + administrative area hierarchies, city locations and some country postal code queries. A (free) username + is required and rate limits exist. + date_publication: '2019-02-19' + bug_reports: https://github.com/ropensci/geonames/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geonames + url_git: '' +geonapi: + version: '0.8' + title: '''GeoNetwork'' API R Interface' + maintainer: Emmanuel Blondel + description: Provides an R interface to the 'GeoNetwork' API () + allowing to upload and publish metadata in a 'GeoNetwork' web-application and + expose it to OGC CSW. + date_publication: '2025-01-31' + bug_reports: https://github.com/eblondel/geonapi/issues + url: https://geonetwork-opensource.org + url_cran: https://CRAN.R-project.org/package=geonapi + url_git: https://github.com/eblondel/geonapi/wiki +geonetwork: + version: 0.5.0 + title: Geographic Networks + maintainer: Facundo Muñoz + description: |- + Provides classes and methods for handling networks or + graphs whose nodes are geographical (i.e. locations in the globe). + The functionality includes the creation of objects of class geonetwork + as a graph with node coordinates, the computation of network measures, + the support of spatial operations (projection to different Coordinate + Reference Systems, handling of bounding boxes, etc.) and the plotting of + the geonetwork object combined with supplementary cartography for spatial + representation. + date_publication: '2023-04-14' + bug_reports: https://forgemia.inra.fr/umr-astre/geonetwork/-/issues + url: https://umr-astre.pages.mia.inra.fr/geonetwork + url_cran: https://CRAN.R-project.org/package=geonetwork + url_git: '' +geonode4R: + version: 0.1-1 + title: Interface to 'GeoNode' REST API + maintainer: Emmanuel Blondel + description: |- + Provides an interface to the 'GeoNode' API, allowing to upload and publish metadata and data in 'GeoNode'. + For more information about the 'GeoNode' API, see . + date_publication: '2024-05-20' + bug_reports: https://github.com/eblondel/geonode4R/issues + url: https://eblondel.github.io/geonode4R/ + url_cran: https://CRAN.R-project.org/package=geonode4R + url_git: https://github.com/eblondel/geonode4R +geoperu: + version: 0.0.0.2 + title: Download Spatial Datasets of Peru + maintainer: Paul E. Santos Andrade + description: 'Provides convenient access to the official spatial datasets of Peru + as ''sf'' objects in R. This package includes a wide range of geospatial data + covering various aspects of Peruvian geography, such as: administrative divisions + (Source: INEI ), protected natural areas (Source: GEO + ANP - SERNANP ). All datasets are harmonized + in terms of attributes, projection, and topology, ensuring consistency and ease + of use for spatial analysis and visualization.' + date_publication: '2024-04-01' + bug_reports: https://github.com/PaulESantos/geoperu/issues + url: https://paulesantos.github.io/geoperu/ + url_cran: https://CRAN.R-project.org/package=geoperu + url_git: https://github.com/PaulESantos/geoperu +geoR: + version: 1.9-4 + title: Analysis of Geostatistical Data + maintainer: Paulo Justiniano Ribeiro Jr + description: Geostatistical analysis including variogram-based, likelihood-based + and Bayesian methods. Software companion for Diggle and Ribeiro (2007) . + date_publication: '2024-02-15' + bug_reports: '' + url: http://www.leg.ufpr.br/geoR/ + url_cran: https://CRAN.R-project.org/package=geoR + url_git: '' +GeoRange: + version: 0.1.0 + title: Calculating Geographic Range from Occurrence Data + maintainer: James Boyle Developer + description: Calculates and analyzes six measures of geographic range from a set + of longitudinal and latitudinal occurrence data. Measures included are minimum + convex hull area, minimum spanning tree distance, longitudinal range, latitudinal + range, maximum pairwise great circle distance, and number of X by X degree cells + occupied. + date_publication: '2017-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeoRange + url_git: '' +georefdatar: + version: 0.6.5 + title: Geosciences Reference Datasets + maintainer: Gerald Schuberth-Hlavač + description: |- + Reference datasets commonly used in the geosciences. These include + standard atomic weights of the elements, a periodic table, a list of minerals + including their abbreviations and chemistry, geochemical data of reservoirs + (primitive mantle, continental crust, mantle, basalts, etc.), decay constants + and isotopic ratios frequently used in geochronology, color codes of the + chronostratigraphic chart. In addition, the package provides functions for + basic queries of atomic weights, the list of minerals, and chronostratigraphic + chart colors. All datasets are fully referenced, and a BibTeX file containing + the references is included. + date_publication: '2024-01-15' + bug_reports: https://github.com/abuseki/georefdatar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=georefdatar + url_git: https://github.com/abuseki/georefdatar +georob: + version: 0.3-23 + title: Robust Geostatistical Analysis of Spatial Data + maintainer: Andreas Papritz + description: Provides functions for efficiently fitting linear models with spatially + correlated errors by robust (Kuensch et al. (2011) ) + and Gaussian (Harville (1977) ) (Restricted) + Maximum Likelihood and for computing robust and customary point and block external-drift + Kriging predictions (Cressie (1993) ), along with utility + functions for variogram modelling in ad hoc geostatistical analyses, model building, + model evaluation by cross-validation, (conditional) simulation of Gaussian processes + (Davies and Bryant (2013) ), unbiased back-transformation + of Kriging predictions of log-transformed data (Cressie (2006) ). + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=georob + url_git: '' +geos: + version: 0.2.4 + title: Open Source Geometry Engine ('GEOS') R API + maintainer: Dewey Dunnington + description: |- + Provides an R API to the Open Source Geometry Engine + ('GEOS') library () and a vector format + with which to efficiently store 'GEOS' geometries. High-performance functions + to extract information from, calculate relationships between, and + transform geometries are provided. Finally, facilities to import + and export geometry vectors to other spatial formats are provided. + date_publication: '2023-11-30' + bug_reports: https://github.com/paleolimbot/geos/issues + url: https://paleolimbot.github.io/geos/ + url_cran: https://CRAN.R-project.org/package=geos + url_git: https://github.com/paleolimbot/geos/ +geoSAE: + version: 0.1.0 + title: Geoadditive Small Area Model + maintainer: Ketut Karang Pradnyadika + description: 'This function is an extension of the Small Area Estimation (SAE) model. + Geoadditive Small Area Model is a combination of the geoadditive model with the + Small Area Estimation (SAE) model, by adding geospatial information to the SAE + model. This package refers to J.N.K Rao and Isabel Molina (2015, ISBN: 978-1-118-73578-7), + Bocci, C., & Petrucci, A. (2016), and Ardiansyah, + M., Djuraidah, A., & Kurnia, A. (2018).' + date_publication: '2021-06-14' + bug_reports: https://github.com/ketutdika/geoSAE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geoSAE + url_git: https://github.com/ketutdika/geoSAE +geosapi: + version: 0.7-1 + title: GeoServer REST API R Interface + maintainer: Emmanuel Blondel + description: |- + Provides an R interface to the GeoServer REST API, allowing to upload + and publish data in a GeoServer web-application and expose data to OGC Web-Services. + The package currently supports all CRUD (Create,Read,Update,Delete) operations + on GeoServer workspaces, namespaces, datastores (stores of vector data), featuretypes, + layers, styles, as well as vector data upload operations. For more information about + the GeoServer REST API, see . + date_publication: '2024-03-11' + bug_reports: https://github.com/eblondel/geosapi/issues + url: https://eblondel.github.io/geosapi/ + url_cran: https://CRAN.R-project.org/package=geosapi + url_git: https://github.com/eblondel/geosapi +geoscale: + version: 2.0.1 + title: Geological Time Scale Plotting + maintainer: Mark A. Bell + description: Functionality for adding the geological timescale to bivariate plots. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geoscale + url_git: '' +geosed: + version: 0.1.1 + title: Smallest Enclosing Disc for Latitude and Longitude Points + maintainer: Shant Sukljian + description: |2- + + Find the smallest circle that contains all longitude and latitude input points. From the generated center and radius, variable side polygons can be created, navigation based on bearing and distance can be applied, and more. Based on a modified version of Welzl's algorithm for smallest circle. Distance calculations are based on the haversine formula. Calculations for distance, midpoint, bearing and more are derived from . + date_publication: '2019-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geosed + url_git: '' +geosimilarity: + version: '3.7' + title: Geographically Optimal Similarity + maintainer: Wenbo Lv + description: |- + Understanding spatial association is essential for spatial + statistical inference, including factor exploration and spatial prediction. + Geographically optimal similarity (GOS) model is an effective method + for spatial prediction, as described in Yongze Song (2022) + . GOS was developed based on + the geographical similarity principle, as described in Axing Zhu (2018) + . GOS has advantages in + more accurate spatial prediction using fewer samples and + critically reduced prediction uncertainty. + date_publication: '2024-10-17' + bug_reports: https://github.com/ausgis/geosimilarity/issues + url: https://ausgis.github.io/geosimilarity/ + url_cran: https://CRAN.R-project.org/package=geosimilarity + url_git: https://github.com/ausgis/geosimilarity +geospark: + version: 0.3.1 + title: Bring Local Sf to Spark + maintainer: Harry Zhu + description: |- + R binds 'GeoSpark' extending 'sparklyr' + R package to make distributed 'geocomputing' easier. Sf is a + package that provides [simple features] access + for R and which is a leading 'geospatial' data processing tool. 'Geospark' R package bring + the same simple features access like sf but running on Spark distributed system. + date_publication: '2020-03-02' + bug_reports: https://github.com/harryprince/geospark/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geospark + url_git: '' +geosphere: + version: 1.5-20 + title: Spherical Trigonometry + maintainer: Robert J. Hijmans + description: Spherical trigonometry for geographic applications. That is, compute + distances and related measures for angular (longitude/latitude) locations. + date_publication: '2024-10-04' + bug_reports: https://github.com/rspatial/geosphere/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=geosphere + url_git: '' +geospt: + version: 1.0-4 + title: |- + Geostatistical Analysis and Design of Optimal Spatial Sampling + Networks + maintainer: Ali Santacruz + description: |- + Estimation of the variogram through trimmed mean, radial basis + functions (optimization, prediction and cross-validation), summary + statistics from cross-validation, pocket plot, and design of + optimal sampling networks through sequential and simultaneous + points methods. + date_publication: '2024-02-20' + bug_reports: https://github.com/amsantac/geospt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geospt + url_git: https://github.com/amsantac/geospt +geosptdb: + version: 1.0-1 + title: |- + Spatio-Temporal Radial Basis Functions with Distance-Based + Methods (Optimization, Prediction and Cross Validation) + maintainer: Carlos Melo + description: Spatio-temporal radial basis functions (optimization, prediction and + cross-validation), summary statistics from cross-validation, Adjusting distance-based + linear regression model and generation of the principal coordinates of a new individual + from Gower's distance. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geosptdb + url_git: '' +geostan: + version: 0.8.1 + title: Bayesian Spatial Analysis + maintainer: Connor Donegan + description: 'For spatial data analysis; provides exploratory spatial analysis tools, + spatial regression, spatial econometric, and disease mapping models, model diagnostics, + and special methods for inference with small area survey data (e.g., the America + Community Survey (ACS)) and censored population health monitoring data. Models + are pre-specified using the Stan programming language, a platform for Bayesian + inference using Markov chain Monte Carlo (MCMC). References: Carpenter et al. + (2017) ; Donegan (2021) ; + Donegan (2022) ; Donegan, Chun and Hughes (2020) ; + Donegan, Chun and Griffith (2021) ; Morris et al. + (2019) .' + date_publication: '2024-12-04' + bug_reports: https://github.com/ConnorDonegan/geostan/issues + url: https://connordonegan.github.io/geostan/ + url_cran: https://CRAN.R-project.org/package=geostan + url_git: '' +geostats: + version: '1.6' + title: An Introduction to Statistics for Geoscientists + maintainer: Pieter Vermeesch + description: A collection of datasets and simplified functions for an introductory + (geo)statistics module at University College London. Provides functionality for + compositional, directional and spatial data, including ternary diagrams, Wulff + and Schmidt stereonets, and ordinary kriging interpolation. Implements logistic + and (additive and centred) logratio transformations. Computes vector averages + and concentration parameters for the von-Mises distribution. Includes a collection + of natural and synthetic fractals, and a simulator for deterministic chaos using + a magnetic pendulum example. The main purpose of these functions is pedagogical. + Researchers can find more complete alternatives for these tools in other packages + such as 'compositions', 'robCompositions', 'sp', 'gstat' and 'RFOC'. All the functions + are written in plain R, with no compiled code and a minimal number of dependencies. + Theoretical background and worked examples are available at . + date_publication: '2023-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geostats + url_git: https://github.com/pvermees/geostats/ +geostatsp: + version: 2.0.8 + title: Geostatistical Modelling with Likelihood and Bayes + maintainer: Patrick Brown + description: |- + Geostatistical modelling facilities using 'SpatRaster' and 'SpatVector' + objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian + geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) . The 'RandomFields' package is available at . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geostatsp + url_git: '' +GeoThinneR: + version: 1.1.0 + title: Simple Spatial Thinning for Ecological and Spatial Analysis + maintainer: Jorge Mestre-Tomás + description: |- + Provides efficient geospatial thinning algorithms to reduce + the density of coordinate data while maintaining spatial + relationships. Implements K-D Tree and brute-force distance-based + thinning, as well as grid-based and precision-based thinning methods. + For more information on the methods, see Elseberg et al. (2012) + . + date_publication: '2024-10-03' + bug_reports: https://github.com/jmestret/GeoThinneR/issues + url: https://jmestret.github.io/GeoThinneR/ + url_cran: https://CRAN.R-project.org/package=GeoThinneR + url_git: https://github.com/jmestret/GeoThinneR +geotools: + version: '0.1' + title: Geo tools + maintainer: Antoine Lucas + description: Tools + date_publication: '2012-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geotools + url_git: '' +geotoolsR: + version: 1.2.1 + title: Tools to Improve the Use of Geostatistic + maintainer: Diogo Francisco Rossoni + description: 'The basic idea of this package is provides some tools to help the + researcher to work with geostatistics. Initially, we present a collection of functions + that allow the researchers to deal with spatial data using bootstrap procedure. + There are five methods available and two ways to display them: bootstrap confidence + interval - provides a two-sided bootstrap confidence interval; bootstrap plot + - a graphic with the original variogram and each of the B bootstrap variograms.' + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geotoolsR + url_git: '' +geotopbricks: + version: 1.5.8.2 + title: An R Plug-in for the Distributed Hydrological Model GEOtop + maintainer: Emanuele Cordano + description: |- + It analyzes raster maps and other information as input/output + files from the Hydrological Distributed Model GEOtop. It contains functions + and methods to import maps and other keywords from geotop.inpts file. Some + examples with simulation cases of GEOtop 2.x/3.x are presented in the package. + Any information about the GEOtop Distributed Hydrological Model source code + is available on www.geotop.org. Technical details about the model are + available in Endrizzi et al (2014) . + date_publication: '2024-03-04' + bug_reports: '' + url: https://zenodo.org/record/8228413 + url_cran: https://CRAN.R-project.org/package=geotopbricks + url_git: https://github.com/ecor/geotopbricks +GeoTox: + version: 0.2.0 + title: Spatiotemporal Mixture Risk Assessment + maintainer: Kyle Messier + description: |- + Connecting spatiotemporal exposure to individual and + population-level risk via source-to-outcome continuum modeling. The package, + methods, and case-studies are described in Messier, Reif, and Marvel (2024) + and Eccles et al. (2023) + . + date_publication: '2024-11-15' + bug_reports: https://github.com/NIEHS/GeoTox/issues + url: https://niehs.github.io/GeoTox/ + url_cran: https://CRAN.R-project.org/package=GeoTox + url_git: https://github.com/NIEHS/GeoTox +geoTS: + version: 0.1.8 + title: |- + Methods for Handling and Analyzing Time Series of Satellite + Images + maintainer: Inder Tecuapetla-Gómez + description: |- + Provides functions and methods for: splitting large raster objects + into smaller chunks, transferring images from a binary format into raster + layers, transferring raster layers into an 'RData' file, calculating the + maximum gap (amount of consecutive missing values) of a numeric vector, + and fitting harmonic regression models to periodic time series. The homoscedastic + harmonic regression model is based on G. Roerink, M. Menenti and W. Verhoef (2000) . + date_publication: '2022-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geoTS + url_git: '' +geouy: + version: 0.2.8 + title: Geographic Information of Uruguay + maintainer: Richard Detomasi + description: |- + The toolbox have functions to load and process geographic + information for Uruguay. And extra-function to get address + coordinates and orthophotos through the uruguayan 'IDE' API + . + date_publication: '2023-08-23' + bug_reports: https://github.com/RichDeto/geouy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geouy + url_git: '' +geovol: + version: '1.0' + title: Geopolitical Volatility (GEOVOL) Modelling + maintainer: Susana Campos-Martins + description: Simulation, estimation and inference for the geopolitical volatility + (GEOVOL) model of Engle and Campos-Martins (2020) , + where GEOVOL is modelled as a latent multiplicative volatility factor with heterogeneous + factor loadings. Estimation is carried out as a maximization-maximization procedure, + where GEOVOL and the GEOVOL loadings are estimated iteratively until convergence. + date_publication: '2021-07-09' + bug_reports: '' + url: https://sites.google.com/site/susanacamposmartins/ + url_cran: https://CRAN.R-project.org/package=geovol + url_git: '' +GeoWeightedModel: + version: 1.0.3 + title: User-Friendly Interface for Geographically-Weighted Models + maintainer: Javier De La Hoz Maestre + description: |- + Contains the development of a tool that provides a web-based + graphical user interface (GUI) to perform Techniques from a subset of + spatial statistics known as geographically weighted (GW) models. + Contains methods described by Brunsdon et al., 1996 + , Brunsdon et al., 2002 + , Harris et al., 2011 + , Brunsdon et al., 2007 + . + date_publication: '2024-02-11' + bug_reports: https://github.com/JavierDeLaHoz/GeoWeightedModel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GeoWeightedModel + url_git: '' +geozoo: + version: 0.5.1 + title: Zoo of Geometric Objects + maintainer: Barret Schloerke + description: Geometric objects defined in 'geozoo' can be simulated or displayed + in the R package 'tourr'. + date_publication: '2016-05-07' + bug_reports: https://github.com/schloerke/geozoo/issues + url: http://schloerke.github.io/geozoo/ + url_cran: https://CRAN.R-project.org/package=geozoo + url_git: https://github.com/schloerke/geozoo +gepaf: + version: 0.2.0 + title: Google Encoded Polyline Algorithm Format + maintainer: Timothée Giraud + description: |- + Encode and decode the Google Encoded Polyline Algorithm Format. + See + for more information. + date_publication: '2024-10-16' + bug_reports: https://github.com/riatelab/gepaf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gepaf + url_git: https://github.com/riatelab/gepaf +GephiForR: + version: 0.1.0 + title: '''Gephi'' Network Visualization' + maintainer: Julia Manso + description: Implements key features of 'Gephi' for network visualization, including + 'ForceAtlas2' (with LinLog mode), network scaling, and network rotations. It also + includes easy network visualization tools such as edge and node color assignment + for recreating 'Gephi'-style graphs in R. The package references layout algorithms + developed by Jacomy, M., Venturini T., Heymann S., and Bastian M. (2014) + and Noack, A. (2009) . + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GephiForR + url_git: '' +geppe: + version: '1.0' + title: |- + Generalised Exponential Poisson and Poisson Exponential + Distributions + maintainer: Michail Tsagris + description: 'Maximum likelihood estimation, random values generation, density computation + and other functions for the exponential-Poisson generalised exponential-Poisson + and Poisson-exponential distributions. References include: Rodrigues G. C., Louzada + F. and Ramos P. L. (2018). "Poisson-exponential distribution: different methods + of estimation". Journal of Applied Statistics, 45(1): 128--144. . + Louzada F., Ramos, P. L. and Ferreira, H. P. (2020). "Exponential-Poisson distribution: + estimation and applications to rainfall and aircraft data with zero occurrence". + Communications in Statistics--Simulation and Computation, 49(4): 1024--1043. . + Barreto-Souza W. and Cribari-Neto F. (2009). "A generalization of the exponential-Poisson + distribution". Statistics and Probability Letters, 79(24): 2493--2500. .' + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=geppe + url_git: '' +gerbil: + version: 0.1.9 + title: |- + Generalized Efficient Regression-Based Imputation with Latent + Processes + maintainer: Michael Robbins + description: |- + Implements a new multiple imputation method that draws + imputations from a latent joint multivariate normal model which + underpins generally structured data. This model is constructed using a + sequence of flexible conditional linear models that enables the + resulting procedure to be efficiently implemented on high dimensional + datasets in practice. See Robbins (2021) . + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gerbil + url_git: '' +gerda: + version: 0.1.0 + title: German Election Database (GERDA) + maintainer: Hanno Hilbig + description: |- + Provides tools to download comprehensive datasets of local, + state, and federal election results in Germany from 1990 to 2021. The package + facilitates access to data on turnout, vote shares for major parties, and + demographic information across different levels of government (municipal, state, + and federal). It offers access to geographically harmonized datasets + that account for changes in municipal boundaries over time and incorporate + mail-in voting districts. Users can easily retrieve, clean, and standardize + German electoral data, making it ready for analysis. Data is sourced from + . + date_publication: '2024-11-20' + bug_reports: https://github.com/hhilbig/gerda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gerda + url_git: https://github.com/hhilbig/gerda +gerefer: + version: 0.1.1 + title: |- + Preparer of Main Scientific References for Automatic Insertion + in Academic Papers + maintainer: Márcio Eustáquio + description: |- + Generates a file, containing the main scientific references, prepared to be automatically inserted into an academic paper. + The articles present in the list are chosen from the main references generated, by function principal_lister(), of the package 'bibliorefer'. + The generated file contains the list of metadata of the principal references in 'BibTex' format. + Massimo Aria, Corrado Cuccurullo. (2017) . + Caibo Zhou, Wenyan Song. (2021) . + Hamid Derviş. (2019) . + date_publication: '2024-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gerefer + url_git: '' +GerminaR: + version: 2.1.4 + title: Indices and Graphics for Assess Seed Germination Process + maintainer: Flavio Lozano-Isla + description: A collection of different indices and visualization techniques for + evaluate the seed germination process in ecophysiological studies (Lozano-Isla + et al. 2019) . + date_publication: '2022-05-18' + bug_reports: https://github.com/flavjack/germinar/issues + url: https://germinar.inkaverse.com/ + url_cran: https://CRAN.R-project.org/package=GerminaR + url_git: https://github.com/flavjack/germinar +germinationmetrics: + version: 0.1.8 + title: Seed Germination Indices and Curve Fitting + maintainer: J. Aravind + description: |- + Provides functions to compute various germination indices + such as germinability, median germination time, mean germination time, + mean germination rate, speed of germination, Timson's index, + germination value, coefficient of uniformity of germination, + uncertainty of germination process, synchrony of germination etc. from + germination count data. Includes functions for fitting cumulative seed + germination curves using four-parameter hill function and computation + of associated parameters. See the vignette for more, including full + list of citations for the methods implemented. + date_publication: '2023-08-18' + bug_reports: https://github.com/aravind-j/germinationmetrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=germinationmetrics + url_git: https://github.com/aravind-j/germinationmetrics +GeRnika: + version: 1.0.0 + title: Simulation, Visualization and Comparison of Tumor Evolution Data + maintainer: Aitor Sánchez-Ferrera + description: Simulating, visualizing and comparing tumor clonal data by using simple + commands. This aims at providing a tool to help researchers to easily simulate + tumor data and analyze the results of their approaches for studying the composition + and the evolutionary history of tumors. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GeRnika + url_git: '' +gert: + version: 2.1.4 + title: Simple Git Client for R + maintainer: Jeroen Ooms + description: |- + Simple git client for R based on 'libgit2' with + support for SSH and HTTPS remotes. All functions in 'gert' use basic R data + types (such as vectors and data-frames) for their arguments and return values. + User credentials are shared with command line 'git' through the git-credential + store and ssh keys stored on disk or ssh-agent. + date_publication: '2024-10-14' + bug_reports: https://github.com/r-lib/gert/issues + url: https://docs.ropensci.org/gert/ + url_cran: https://CRAN.R-project.org/package=gert + url_git: '' +gesca: + version: 1.0.5 + title: |- + Generalized Structured Component Analysis Structural Equation + Modeling + maintainer: Sunmee Kim + description: |- + Implementing generalized structured component analysis (GSCA) and + its basic extensions, including constrained single and multiple group + analysis, and second order latent variable modeling. For a comprehensive + overview of GSCA, see Hwang & Takane (2014, ISBN: 9780367738754). + date_publication: '2024-10-22' + bug_reports: '' + url: https://quantmm.github.io/gesca/ + url_cran: https://CRAN.R-project.org/package=gesca + url_git: '' +GESE: + version: 2.0.1 + title: Gene-Based Segregation Test + maintainer: Dandi Qiao + description: Implements the gene-based segregation test(GESE) and the weighted GESE + test for identifying genes with causal variants of large effects for family-based + sequencing data. The methods are described in Qiao, D. Lange, C., Laird, N.M., + Won, S., Hersh, C.P., et al. (2017). . Gene-based segregation + method for identifying rare variants for family-based sequencing studies. Genet + Epidemiol 41(4):309-319. More details can be found at . + date_publication: '2017-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GESE + url_git: '' +gesisdata: + version: 0.1.2 + title: Reproducible Data Retrieval from the GESIS Data Archive + maintainer: Frederick Solt + description: |- + Reproducible, programmatic retrieval of datasets from the + GESIS Data Archive. The GESIS Data Archive + makes available thousands of invaluable datasets, but researchers using + these datasets are caught in a bind. The archive's terms and conditions + bar dissemination of downloaded datasets to third parties, but to ensure + that one's work can be reproduced, assessed, and built upon by others, one + must provide access to the raw data one has employed. The 'gesisdata' + package cuts this knot by providing registered users with programmatic, + reproducible access to GESIS datasets from within 'R'. + date_publication: '2023-07-03' + bug_reports: https://github.com/fsolt/gesisdata/issues + url: https://fsolt.org/gesisdata/ + url_cran: https://CRAN.R-project.org/package=gesisdata + url_git: https://github.com/fsolt/gesisdata +geslaR: + version: 1.0-1 + title: Get and Manipulate the GESLA Dataset + maintainer: Fernando Mayer + description: |- + Promote access to the GESLA + (Global Extreme Sea Level + Analysis) dataset, a higher-frequency sea-level record data from all + over the world. It provides functions to download it entirely, or + query subsets directly into R, without the need of downloading the + full dataset. Also, it provides a built-in web-application, so that + users can apply basic filters to select the data of interest, + generating informative plots, and showing the selected sites. + date_publication: '2023-10-09' + bug_reports: https://github.com/EireExtremes/geslaR/issues + url: https://eireextremes.github.io/geslaR/ + url_cran: https://CRAN.R-project.org/package=geslaR + url_git: https://github.com/EireExtremes/geslaR +gesso: + version: 1.0.2 + title: Hierarchical GxE Interactions in a Regularized Regression Model + maintainer: Natalia Zemlianskaia + description: |- + The method focuses on a single environmental exposure and induces + a main-effect-before-interaction hierarchical structure for the joint selection of interaction terms + in a regularized regression model. For details see Zemlianskaia et al. (2021) . + date_publication: '2021-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gesso + url_git: '' +gestalt: + version: 0.2.0 + title: Tools for Making and Combining Functions + maintainer: Eugene Ha + description: |- + Provides a suite of function-building tools centered around a + (forward) composition operator, %>>>%, which extends the semantics of the + 'magrittr' %>% operator and supports 'Tidyverse' quasiquotation. It enables + you to construct composite functions that can be inspected and transformed as + list-like objects. In conjunction with %>>>%, a compact function constructor, + fn(), and a partial-application constructor, partial(), are also provided; + both support quasiquotation. + date_publication: '2022-08-22' + bug_reports: https://github.com/egnha/gestalt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gestalt + url_git: https://github.com/egnha/gestalt +gestate: + version: 1.6.0 + title: Generalised Survival Trial Assessment Tool Environment + maintainer: James Bell + description: 'Provides tools to assist planning and monitoring of time-to-event + trials under complicated censoring assumptions and/or non-proportional hazards. + There are three main components: The first is analytic calculation of predicted + time-to-event trial properties, providing estimates of expected hazard ratio, + event numbers and power under different analysis methods. The second is simulation, + allowing stochastic estimation of these same properties. Thirdly, it provides + parametric event prediction using blinded trial data, including creation of prediction + intervals. Methods are based upon numerical integration and a flexible object-orientated + structure for defining event, censoring and recruitment distributions (Curves).' + date_publication: '2023-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gestate + url_git: '' +gesttools: + version: 1.3.0 + title: |- + General Purpose G-Estimation for End of Study or Time-Varying + Outcomes + maintainer: Daniel Tompsett + description: Provides a series of general purpose tools to perform g-estimation + using the methods described in Sjolander and Vansteelandt (2016) + and Dukes and Vansteelandt . The package allows for g-estimation + in a wide variety of circumstances, including an end of study or time-varying + outcome, and an exposure that is a binary, continuous, or a categorical variable + with three or more categories. The package also supports g-estimation with time-varying + causal effects and effect modification by a confounding variable. + date_publication: '2022-01-04' + bug_reports: https://github.com/danieltompsett/gesttools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gesttools + url_git: https://github.com/danieltompsett/gesttools +GET: + version: 1.0-4 + title: Global Envelopes + maintainer: Mari Myllymäki + description: |- + Implementation of global envelopes for a set of general d-dimensional vectors T + in various applications. A 100(1-alpha)% global envelope is a band bounded by two + vectors such that the probability that T falls outside this envelope in any of the d + points is equal to alpha. Global means that the probability is controlled simultaneously + for all the d elements of the vectors. The global envelopes can be used for graphical + Monte Carlo and permutation tests where the test statistic is a multivariate vector or + function (e.g. goodness-of-fit testing for point patterns and random sets, functional + analysis of variance, functional general linear model, n-sample test of correspondence + of distribution functions), for central regions of functional or multivariate data (e.g. + outlier detection, functional boxplot) and for global confidence and prediction bands + (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See + Myllymäki and Mrkvička (2024) , + Myllymäki et al. (2017) , + Mrkvička and Myllymäki (2023) , + Mrkvička et al. (2016) , + Mrkvička et al. (2017) , + Mrkvička et al. (2020) , + Mrkvička et al. (2021) , + Myllymäki et al. (2021) , + Mrkvička et al. (2022) , + Dai et al. (2022) , + Dvořák and Mrkvička (2022) , + Mrkvička et al. (2023) , and + Konstantinou et al. (2024) . + date_publication: '2024-12-02' + bug_reports: https://github.com/myllym/GET/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GET + url_git: https://github.com/myllym/GET +getable: + version: 1.0.3 + title: |- + Fetching Tabular Data "Onload" in Compiled R Markdown HTML + Documents + maintainer: Yongfu Liao + description: |- + Dynamically retrieve data from the web to render HTML tables + on inspection in R Markdown HTML documents. + date_publication: '2020-10-02' + bug_reports: https://github.com/liao961120/getable/issues/ + url: https://yongfu.name/getable/ + url_cran: https://CRAN.R-project.org/package=getable + url_git: https://github.com/liao961120/getable/ +GetBCBData: + version: 0.7.0 + title: |- + Imports Datasets from BCB (Central Bank of Brazil) using Its + Official API + maintainer: Marcelo Perlin + description: |- + Downloads and organizes datasets using BCB's API . Offers options for caching with the 'memoise' package and + , multicore/multisession with 'furrr' and format of output data (long/wide). + date_publication: '2022-06-07' + bug_reports: https://github.com/msperlin/GetBCBData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GetBCBData + url_git: https://github.com/msperlin/GetBCBData/ +GETdesigns: + version: 1.2.0 + title: Generalized Extended Triangular Designs ('GETdesigns') + maintainer: Ashutosh Dalal + description: Since their introduction by Bose and Nair (1939) , + partially balanced incomplete block (PBIB) designs remain an important class of + incomplete block designs. The concept of association scheme was used by Bose and + Shimamoto (1952) for the classification of + these designs. The constraint of resources always motivates the experimenter to + advance towards PBIB designs, more specifically to higher associate class PBIB + designs from balanced incomplete block designs. It is interesting to note that + many times higher associate PBIB designs perform better than their counterpart + lower associate PBIB designs for the same set of parameters v, b, r, k and lambda_i + (i=1,2...m). This package contains functions named GETD() for generating m-associate + (m>=2) class PBIB designs along with parameters (v, b, r, k and lambda_i, i = + 1, 2,…,m) based on Generalized Triangular (GT) Association Scheme. It also calculates + the Information matrix, Average variance factor and canonical efficiency factor + of the generated design. These designs, besides having good efficiency, require + smaller number of replications and smallest possible concurrence of treatment + pairs. + date_publication: '2024-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GETdesigns + url_git: '' +GetDFPData: + version: '1.6' + title: |- + Reading Annual Financial Reports from Bovespa's DFP, FRE and FCA + System + maintainer: Marcelo Perlin + description: |- + Reads annual financial reports including assets, liabilities, dividends history, stockholder composition and much more from Bovespa's DFP, FRE and FCA systems . + These are web based interfaces for all financial reports of companies traded at Bovespa. The package is specially designed for large scale data importation, keeping a tabular (long) structure for easier processing. + date_publication: '2021-04-01' + bug_reports: https://github.com/msperlin/GetDFPData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GetDFPData + url_git: https://github.com/msperlin/GetDFPData/ +GetDFPData2: + version: 0.6.3 + title: Reading Annual and Quarterly Financial Reports from B3 + maintainer: Marcelo Perlin + description: |- + Reads annual and quarterly financial reports from companies traded at B3, the Brazilian exchange + . + All data is downloaded and imported from CVM's public ftp site . + date_publication: '2023-04-25' + bug_reports: https://github.com/msperlin/GetDFPData2/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=GetDFPData2 + url_git: https://github.com/msperlin/GetDFPData2/ +getDTeval: + version: 0.0.2 + title: |- + Translating Coding Statements using get() and eval() for + Improved Run-Time Coding Efficiency + maintainer: Mayur Bansal + description: |- + The getDTeval() function facilitates the translation of the original coding statement to an optimized form for improved runtime efficiency without compromising on the programmatic coding design. + The function can either provide a translation of the coding statement, directly evaluate the translation to return a coding result, or provide both of these outputs. + date_publication: '2021-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=getDTeval + url_git: '' +GetFREData: + version: 0.8.1 + title: Reading FRE Corporate Data of Public Traded Companies from B3 + maintainer: Marcelo Perlin + description: |- + Reads corporate data such as board composition and compensation for companies traded at B3, + the Brazilian exchange . All data is downloaded and imported from the ftp site . + date_publication: '2022-06-13' + bug_reports: https://github.com/msperlin/GetFREData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GetFREData + url_git: https://github.com/msperlin/GetFREData/ +getip: + version: 0.1-4 + title: '''IP'' Address ''Lookup''' + maintainer: Drew Schmidt + description: |- + A micro-package for getting your 'IP' address, either the + local/internal or the public/external one. Currently only 'IPv4' addresses + are supported. + date_publication: '2023-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=getip + url_git: '' +getLattes: + version: 0.2.0 + title: Import and Process Data from the 'Lattes' Curriculum Platform + maintainer: Roney Fraga Souza + description: 'Tool for import and process data from ''Lattes'' curriculum platform + (). The Brazilian government keeps an extensive base of + curricula for academics from all over the country, with over 5 million registrations. + The academic life of the Brazilian researcher, or related to Brazilian universities, + is documented in ''Lattes''. Some information that can be obtained: professional + formation, research area, publications, academics advisories, projects, etc. ''getLattes'' + package allows work with ''Lattes'' data exported to XML format.' + date_publication: '2021-06-11' + bug_reports: https://github.com/roneyfraga/getLattes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=getLattes + url_git: https://github.com/roneyfraga/getLattes +GetLattesData: + version: '1.5' + title: Reading Bibliometric Data from Lattes Platform + maintainer: Marcelo Perlin + description: A simple API for downloading and reading xml data directly from Lattes + . + date_publication: '2024-05-04' + bug_reports: https://github.com/msperlin/GetLattesData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GetLattesData + url_git: https://github.com/msperlin/GetLattesData/ +getmstatistic: + version: 0.2.2 + title: Quantifying Systematic Heterogeneity in Meta-Analysis + maintainer: Lerato E Magosi + description: |- + Quantifying systematic heterogeneity in meta-analysis using R. + The M statistic aggregates heterogeneity information across multiple + variants to, identify systematic heterogeneity patterns and their direction + of effect in meta-analysis. It's primary use is to identify outlier studies, + which either show "null" effects or consistently show stronger or weaker + genetic effects than average across, the panel of variants examined in a + GWAS meta-analysis. In contrast to conventional heterogeneity metrics + (Q-statistic, I-squared and tau-squared) which measure random heterogeneity + at individual variants, M measures systematic (non-random) + heterogeneity across multiple independently associated variants. Systematic + heterogeneity can arise in a meta-analysis due to differences in the study + characteristics of participating studies. Some of the differences may + include: ancestry, allele frequencies, phenotype definition, age-of-disease + onset, family-history, gender, linkage disequilibrium and quality control + thresholds. See for statistical + statistical theory, documentation and examples. + date_publication: '2021-05-09' + bug_reports: https://github.com/magosil86/getmstatistic/issues + url: https://magosil86.github.io/getmstatistic/ + url_cran: https://CRAN.R-project.org/package=getmstatistic + url_git: '' +getopt: + version: 1.20.4 + title: C-Like 'getopt' Behavior + maintainer: Trevor L Davis + description: |- + Package designed to be used with Rscript to write + '#!' shebang scripts that accept short and long flags/options. + Many users will prefer using instead the packages optparse or argparse + which add extra features like automatically generated help option and usage, + support for default values, positional argument support, etc. + date_publication: '2023-10-01' + bug_reports: https://github.com/trevorld/r-getopt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=getopt + url_git: https://github.com/trevorld/r-getopt +GetoptLong: + version: 1.0.5 + title: Parsing Command-Line Arguments and Simple Variable Interpolation + maintainer: Zuguang Gu + description: |- + This is a command-line argument parser which wraps the + powerful Perl module Getopt::Long and with some adaptations for easier use + in R. It also provides a simple way for variable interpolation in R. + date_publication: '2020-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GetoptLong + url_git: https://github.com/jokergoo/GetoptLong +getPass: + version: 0.2-4 + title: Masked User Input + maintainer: Drew Schmidt + description: |- + A micro-package for reading "passwords", i.e. reading + user input with masking, so that the input is not displayed as it + is typed. Currently we have support for 'RStudio', the command line + (every OS), and any platform where 'tcltk' is present. + date_publication: '2023-12-10' + bug_reports: https://github.com/wrathematics/getPass/issues + url: '' + url_cran: https://CRAN.R-project.org/package=getPass + url_git: https://github.com/wrathematics/getPass +getProxy: + version: '1.13' + title: Get Free Proxy IP and Port + maintainer: Alexey Seleznev + description: |- + Allows get address and port + of the free proxy server, from one of two services + or . + And it's easy to redirect your Internet connection through + a proxy server. + date_publication: '2022-01-05' + bug_reports: https://github.com/selesnow/getProxy/issues + url: https://selesnow.github.io/getProxy/ + url_cran: https://CRAN.R-project.org/package=getProxy + url_git: '' +GetQuandlData: + version: 1.0.0 + title: |- + Fast and Cached Import of Data from 'Quandl' Using the 'json + API' + maintainer: Marcelo S. Perlin + description: |- + Imports time series data from the 'Quandl' database . The package uses the 'json api' at , local caching ('memoise' package) and the tidy format by default. + Also allows queries of databases, allowing the user to see which time series are available for each database id. In short, it is an alternative to package 'Quandl', with faster data importation in the tidy/long format. + date_publication: '2023-02-15' + bug_reports: https://github.com/msperlin/GetQuandlData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GetQuandlData + url_git: https://github.com/msperlin/GetQuandlData/ +gets: + version: '0.38' + title: |- + General-to-Specific (GETS) Modelling and Indicator Saturation + Methods + maintainer: Genaro Sucarrat + description: Automated General-to-Specific (GETS) modelling of the mean and variance + of a regression, and indicator saturation methods for detecting and testing for + structural breaks in the mean, see Pretis, Reade and Sucarrat (2018) + for an overview of the package. In advanced use, the estimator and diagnostics + tests can be fully user-specified, see Sucarrat (2021) . + date_publication: '2024-07-14' + bug_reports: https://github.com/gsucarrat/gets/issues + url: http://www.sucarrat.net/R/gets/ + url_cran: https://CRAN.R-project.org/package=gets + url_git: '' +getspanel: + version: 0.2.0 + title: General-to-Specific Modelling of Panel Data + maintainer: Moritz Schwarz + description: Uses several types of indicator saturation and automated General-to-Specific + (GETS) modelling from the 'gets' package and applies it to panel data. This allows + the detection of structural breaks in panel data, operationalising a reverse causal + approach of causal inference, see Pretis and Schwarz (2022) . + date_publication: '2024-03-19' + bug_reports: https://github.com/moritzpschwarz/getspanel/issues + url: http://moritzschwarz.org/getspanel/ + url_cran: https://CRAN.R-project.org/package=getspanel + url_git: https://github.com/moritzpschwarz/getspanel +getspres: + version: 0.2.0 + title: SPRE Statistics for Exploring Heterogeneity in Meta-Analysis + maintainer: Lerato E Magosi + description: |- + An implementation of SPRE (standardised predicted random-effects) + statistics in R to explore heterogeneity in genetic association meta- + analyses, as described by Magosi et al. (2019) + . SPRE statistics are precision + weighted residuals that indicate the direction and extent with which + individual study-effects in a meta-analysis deviate from the average + genetic effect. Overly influential positive outliers have the potential + to inflate average genetic effects in a meta-analysis whilst negative + outliers might lower or change the direction of effect. See the 'getspres' + website for documentation and examples + . + date_publication: '2021-05-09' + bug_reports: https://github.com/magosil86/getspres/issues + url: https://magosil86.github.io/getspres/ + url_cran: https://CRAN.R-project.org/package=getspres + url_git: '' +GetTDData: + version: 1.5.6 + title: Get Data for Brazilian Bonds (Tesouro Direto) + maintainer: Marcelo Perlin + description: Downloads and aggregates data for Brazilian government issued bonds + directly from the website of Tesouro Direto . + date_publication: '2024-08-20' + bug_reports: https://github.com/msperlin/GetTDData/issues/ + url: https://msperlin.github.io/GetTDData/ + url_cran: https://CRAN.R-project.org/package=GetTDData + url_git: https://github.com/msperlin/GetTDData/ +gettz: + version: 0.0.5 + title: Get the Timezone Information + maintainer: Dirk Eddelbuettel + description: |- + A function to retrieve the system timezone on Unix systems + which has been found to find an answer when 'Sys.timezone()' has failed. + It is based on an answer by Duane McCully posted on 'StackOverflow', and + adapted to be callable from R. The package also builds on Windows, but + just returns NULL. + date_publication: '2022-10-29' + bug_reports: https://github.com/eddelbuettel/gettz/issues + url: https://dirk.eddelbuettel.com/code/gettz.html + url_cran: https://CRAN.R-project.org/package=gettz + url_git: https://github.com/eddelbuettel/gettz/ +getwiki: + version: 0.9.0 + title: R Wrapper for Wikipedia Data + maintainer: Corydon Baylor + description: |- + A simple wrapper for 'Wikipedia' data. Specifically, this + package looks to fill a gap in retrieving text data in a tidy format that can be used for Natural Language Processing. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=getwiki + url_git: '' +GEVACO: + version: 1.0.1 + title: Joint Test of Gene and GxE Interactions via Varying Coefficients + maintainer: Sydney Manning + description: A novel statistical model to detect the joint genetic and dynamic gene-environment + (GxE) interaction with continuous traits in genetic association studies. It uses + varying-coefficient models to account for different GxE trajectories, regardless + whether the relationship is linear or not. The package includes one function, + GxEtest(), to test a single genetic variant (e.g., a single nucleotide polymorphism + or SNP), and another function, GxEscreen(), to test for a set of genetic variants. + The method involves a likelihood ratio test described in Crainiceanu, C. M., and + Ruppert, D. (2004) . + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEVACO + url_git: '' +GEVcdn: + version: 1.1.6-2 + title: GEV Conditional Density Estimation Network + maintainer: Alex J. Cannon + description: Implements a flexible nonlinear modelling framework for nonstationary + generalized extreme value analysis in hydroclimatology following Cannon (2010) + . + date_publication: '2020-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GEVcdn + url_git: '' +gexp: + version: 1.0-21 + title: Generator of Experiments + maintainer: Ivan Bezerra Allaman + description: |- + Generates experiments - simulating structured or experimental data as: + completely randomized design, randomized block design, latin square design, + factorial and split-plot experiments (Ferreira, 2008, ISBN:8587692526; + Naes et al., 2007 ; Rencher et al., 2007, ISBN:9780471754985; + Montgomery, 2001, ISBN:0471316490). + date_publication: '2023-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gexp + url_git: https://github.com/ivanalaman/gexp +geysertimes: + version: 0.1.9 + title: Geyser Data from GeyserTimes.org + maintainer: Stephen Kaluzny + description: |- + Download geyser eruption and observation data from the GeyserTimes + site () and optionally store it locally. The vignette + shows a simple analysis of downloading, accessing, and summarizing the data. + date_publication: '2021-09-09' + bug_reports: https://github.com/geysertimes/geysertimes-r-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=geysertimes + url_git: https://github.com/geysertimes/geysertimes-r-package +GFA: + version: 1.0.5 + title: Group Factor Analysis + maintainer: Eemeli Leppäaho + description: Factor analysis implementation for multiple data sources, i.e., for + groups of variables. The whole data analysis pipeline is provided, including functions + and recommendations for data normalization and model definition, as well as missing + value prediction and model visualization. The model group factor analysis (GFA) + is inferred with Gibbs sampling, and it has been presented originally by Virtanen + et al. (2012), and extended in Klami et al. (2015) + and Bunte et al. (2016) ; for details, see + the citation info. + date_publication: '2023-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFA + url_git: '' +gfboost: + version: 0.1.1 + title: Gradient-Free Gradient Boosting + maintainer: Tino Werner + description: Implementation of routines of the author's PhD thesis on gradient-free + Gradient Boosting (Werner, Tino (2020) "Gradient-Free Gradient Boosting", URL + ''). + date_publication: '2022-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gfboost + url_git: '' +gfcanalysis: + version: 1.8.0 + title: |- + Tools for Working with Hansen et al. Global Forest Change + Dataset + maintainer: Matthew Cooper + description: |- + Supports analyses using the Global Forest Change dataset released + by Hansen et al. gfcanalysis was originally written for the Tropical Ecology + Assessment and Monitoring (TEAM) Network. For additional details on the + Global Forest Change dataset, see: Hansen, M. et al. 2013. "High-Resolution + Global Maps of 21st-Century Forest Cover Change." Science 342 (15 + November): 850-53. The forest change data and more information on the + product is available at . + date_publication: '2023-10-11' + bug_reports: https://github.com/azvoleff/gfcanalysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gfcanalysis + url_git: https://github.com/azvoleff/gfcanalysis +GFD: + version: 0.3.3 + title: Tests for General Factorial Designs + maintainer: Sarah Friedrich + description: |- + Implemented are the Wald-type statistic, + a permuted version thereof as well as the ANOVA-type statistic + for general factorial designs, even with non-normal error terms + and/or heteroscedastic variances, for crossed designs with an + arbitrary number of factors and nested designs with up to three factors. + Friedrich et al. (2017) . + date_publication: '2022-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFD + url_git: '' +GFDmcv: + version: 0.1.0 + title: |- + General Hypothesis Testing Problems for Multivariate + Coefficients of Variation + maintainer: Lukasz Smaga + description: Performs test procedures for general hypothesis testing problems for + four multivariate coefficients of variation (Ditzhaus and Smaga, 2023 ). + We can verify the global hypothesis about equality as well as the particular hypotheses + defined by contrasts, e.g., we can conduct post hoc tests. We also provide the + simultaneous confidence intervals for contrasts. + date_publication: '2023-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFDmcv + url_git: '' +GFDrmst: + version: 0.1.1 + title: Multiple RMST-Based Tests in General Factorial Designs + maintainer: Merle Munko + description: We implemented multiple tests based on the restricted mean survival + time (RMST) for general factorial designs as described in Munko et al. (2024) + . Therefore, an asymptotic test, a groupwise bootstrap + test, and a permutation test are incorporated with a Wald-type test statistic. + The asymptotic and groupwise bootstrap test take the asymptotic exact dependence + structure of the test statistics into account to gain more power. Furthermore, + confidence intervals for RMST contrasts can be calculated and plotted and a stepwise + extension that can improve the power of the multiple tests is available. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFDrmst + url_git: '' +GFDrmtl: + version: 0.1.0 + title: |- + Multiple RMTL-Based Tests for Competing Risks Data in General + Factorial Designs + maintainer: Merle Munko + description: We implemented multiple tests based on the restricted mean time lost + (RMTL) for general factorial designs as described in Munko et al. (2024) . + Therefore, an asymptotic test and a permutation test are incorporated with a Wald-type + test statistic. The asymptotic test takes the asymptotic exact dependence structure + of the test statistics into account to gain more power. Furthermore, confidence + intervals for RMTL contrasts can be calculated and plotted and a stepwise extension + that can improve the power of the multiple tests is available. + date_publication: '2024-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFDrmtl + url_git: '' +GFDsurv: + version: 0.1.1 + title: Tests for Survival Data in General Factorial Designs + maintainer: Merle Munko + description: |- + Implemented are three Wald-type statistic and respective + permuted versions for null hypotheses formulated in terms of cumulative hazard rate functions, medians and the concordance measure, respectively, in the general framework of survival factorial designs with possibly heterogeneous survival and/or censoring distributions, for crossed designs with an arbitrary number of factors and nested designs with up to three factors. + Ditzhaus, Dobler and Pauly (2020) + Ditzhaus, Janssen, Pauly (2020) + Dobler and Pauly (2019) . + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFDsurv + url_git: https://github.com/PhilippSteinhauer/GFDsurv +GFE: + version: 0.1.1 + title: Gross Flows Estimation under Complex Surveys + maintainer: Acero William + description: The philosophy in the package is described in Stasny (1988) + and Gutierrez, A., Trujillo, L. & Silva, N. (2014), to estimate + the gross flows under complex surveys using a Markov chain approach with non response. + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFE + url_git: '' +gfer: + version: 0.1.12 + title: Green Finance and Environmental Risk + maintainer: Yuanchao Xu + description: |- + Focuses on data collecting, analyzing and visualization in green finance and environmental + risk research and analysis. Main function includes environmental data collecting from + official websites such as MEP (Ministry of Environmental Protection of China, ), water + related projects identification and environmental data visualization. + date_publication: '2022-02-06' + bug_reports: https://github.com/Yuanchao-Xu/gfer/issues + url: https://yuanchao-xu.github.io/gfer/ + url_cran: https://CRAN.R-project.org/package=gfer + url_git: '' +GFGM.copula: + version: 1.0.4 + title: Generalized Farlie-Gumbel-Morgenstern Copula + maintainer: Jia-Han Shih + description: Compute bivariate dependence measures and perform bivariate competing + risks analysis under the generalized Farlie-Gumbel-Morgenstern (FGM) copula. See + Shih and Emura (2018) and Shih and Emura (2019) + for details. + date_publication: '2019-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFGM.copula + url_git: '' +gfiExtremes: + version: 1.0.1 + title: Generalized Fiducial Inference for Extremes + maintainer: Stéphane Laurent + description: 'Fiducial framework to perform inference on the quantiles for a generalized + Pareto distribution model and on the parameters of the Pareto exceedance distribution, + assuming the exceedance threshold is a known or unknown parameter. Reference: + Damian V. Wandler & Jan Hannig (2012) .' + date_publication: '2024-01-25' + bug_reports: https://github.com/stla/gfiExtremes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gfiExtremes + url_git: https://github.com/stla/gfiExtremes +GFisher: + version: 0.2.0 + title: Generalized Fisher's Combination Tests Under Dependence + maintainer: Hong Zhang + description: Accurate and computationally efficient p-value calculation methods + for a general family of Fisher type statistics (GFisher). The GFisher covers Fisher's + combination, Good's statistic, Lancaster's statistic, weighted Z-score combination, + etc. It allows a flexible weighting scheme, as well as an omnibus procedure that + automatically adapts proper weights and degrees of freedom to a given data. The + new p-value calculation methods are based on novel ideas of moment-ratio matching + and joint-distribution approximation. The technical details can be found in Hong + Zhang and Zheyang Wu (2020) . + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GFisher + url_git: '' +gfiUltra: + version: 1.0.0 + title: |- + Generalized Fiducial Inference for Ultrahigh-Dimensional + Regression + maintainer: Stéphane Laurent + description: 'Variable selection for ultrahigh-dimensional ("large p small n") linear + Gaussian models using a fiducial framework allowing to draw inference on the parameters. + Reference: Lai, Hannig & Lee (2015) .' + date_publication: '2020-12-09' + bug_reports: https://github.com/stla/gfiUltra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gfiUltra + url_git: https://github.com/stla/gfiUltra +GFM: + version: 1.2.1 + title: Generalized Factor Model + maintainer: Wei Liu + description: |- + Generalized factor model is implemented for ultra-high dimensional data with mixed-type variables. + Two algorithms, variational EM and alternate maximization, are designed to implement the generalized factor model, + respectively. The factor matrix and loading matrix together with the number of factors can be well estimated. + This model can be employed in social and behavioral sciences, economy and finance, and genomics, + to extract interpretable nonlinear factors. More details can be referred to + Wei Liu, Huazhen Lin, Shurong Zheng and Jin Liu. (2021) . + date_publication: '2023-08-11' + bug_reports: https://github.com/feiyoung/GFM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GFM + url_git: https://github.com/feiyoung/GFM +gfonts: + version: 0.2.0 + title: Offline 'Google' Fonts for 'Markdown' and 'Shiny' + maintainer: Victor Perrier + description: |- + Download 'Google' fonts and generate 'CSS' to use in 'rmarkdown' documents and + 'shiny' applications. Some popular fonts are included and ready to use. + date_publication: '2023-01-08' + bug_reports: https://github.com/dreamRs/gfonts/issues + url: https://dreamrs.github.io/gfonts/ + url_cran: https://CRAN.R-project.org/package=gfonts + url_git: https://github.com/dreamRs/gfonts +gfoRmula: + version: 1.1.0 + title: Parametric G-Formula + maintainer: Sean McGrath + description: |- + Implements the non-iterative conditional expectation (NICE) + algorithm of the g-formula algorithm (Robins (1986) + , Hernán and Robins (2024, ISBN:9781420076165)). + The g-formula can estimate an outcome's counterfactual mean or risk under + hypothetical treatment strategies (interventions) when there is sufficient + information on time-varying treatments and confounders. + This package can be used for discrete or continuous time-varying treatments + and for failure time outcomes or continuous/binary end of follow-up + outcomes. The package can handle a random measurement/visit process and a + priori knowledge of the data structure, as well as censoring (e.g., by loss + to follow-up) and two options for handling competing events for failure time + outcomes. Interventions can be flexibly specified, both as interventions on + a single treatment or as joint interventions on multiple treatments. + See McGrath et al. (2020) for a guide on + how to use the package. + date_publication: '2024-10-01' + bug_reports: https://github.com/CausalInference/gfoRmula/issues + url: https://doi.org/10.1016/j.patter.2020.100008 + url_cran: https://CRAN.R-project.org/package=gfoRmula + url_git: https://github.com/CausalInference/gfoRmula +gfoRmulaICE: + version: 0.1.0 + title: Parametric Iterative Conditional Expectation G-Formula + maintainer: Zhaoxi Cheng + description: |- + Implements iterative conditional expectation (ICE) estimators of the plug-in g-formula (Wen, Young, Robins, and Hernán (2020) ). + Both singly robust and doubly robust ICE estimators based on parametric models are available. + The package can be used to estimate survival curves under sustained treatment strategies (interventions) using longitudinal data with time-varying treatments, time-varying confounders, censoring, and competing events. + The interventions can be static or dynamic, and deterministic or stochastic (including threshold interventions). Both prespecified and user-defined interventions are available. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gfoRmulaICE + url_git: '' +gFormulaMI: + version: 1.0.0 + title: G-Formula for Causal Inference via Multiple Imputation + maintainer: Jonathan Bartlett + description: |- + Implements the G-Formula method for causal inference with time-varying treatments and + confounders using Bayesian multiple imputation methods, as described by + Bartlett, Olarte Parra and Daniel (2023) . It creates multiple synthetic imputed + datasets under treatment regimes of interest using the 'mice' package. These can then be analysed + using rules developed for analysing multiple synthetic datasets. + date_publication: '2023-05-25' + bug_reports: '' + url: https://jwb133.github.io/gFormulaMI/ + url_cran: https://CRAN.R-project.org/package=gFormulaMI + url_git: '' +gfunctions: + version: '1.0' + title: G-Functions + maintainer: Genaro Sucarrat + description: 'Modified versions of the lag() and summary() functions: glag() and + gsummary(). The prefix ''g'' is a reminder of who to blame if things do not work + as they should.' + date_publication: '2024-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gfunctions + url_git: '' +gg.gap: + version: '1.3' + title: Define Segments in y-Axis for 'ggplot2' + maintainer: Jiacheng Lou + description: It is not very easy to define segments for y-axis in a 'ggplot2' plot. + gg.gap() function in this package can carry it out. + date_publication: '2019-09-30' + bug_reports: https://github.com/ChrisLou-bioinfo/gg.gap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gg.gap + url_git: https://github.com/ChrisLou-bioinfo/gg.gap +gg1d: + version: 0.1.0 + title: Exploratory Data Analysis using Tiled One-Dimensional Graphics + maintainer: Sam El-Kamand + description: |- + Streamlines exploratory data analysis by providing a turnkey approach + to visualising n-dimensional data which graphically reveals correlative or associative relationships + between 2 or more features. Represents all dataset features as distinct, vertically + aligned bar or tile plots, with plot types auto-selected based on whether variables are categorical or numeric. + date_publication: '2024-12-09' + bug_reports: https://github.com/selkamand/gg1d/issues + url: https://selkamand.github.io/gg1d/ + url_cran: https://CRAN.R-project.org/package=gg1d + url_git: https://github.com/selkamand/gg1d +ggalign: + version: 0.1.0 + title: A 'ggplot2' Extension for Consistent Axis Alignment + maintainer: Yun Peng + description: |- + A 'ggplot2' extension offers various tools for organizing and arranging plots. + It is designed to consistently align a specific axis across multiple 'ggplot' objects, + making it especially useful for plots requiring data order manipulation. A typical use + case includes organizing combinations like a dendrogram and a heatmap. + date_publication: '2025-02-06' + bug_reports: https://github.com/Yunuuuu/ggalign/issues + url: https://yunuuuu.github.io/ggalign/ + url_cran: https://CRAN.R-project.org/package=ggalign + url_git: https://github.com/Yunuuuu/ggalign +ggaligner: + version: '0.1' + title: |- + Visualizing Sequence Alignment by Generating Publication-Ready + Plots + maintainer: Mohamed Soudy + description: Providing publication-ready graphs for Multiple sequence alignment. + Moreover, it provides a unique solution for visualizing the multiple sequence + alignment without the need to do the alignment in each run which is a big limitation + in other available packages. + date_publication: '2023-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggaligner + url_git: '' +ggalignment: + version: 1.0.2 + title: Plots 'D&D'-Style Alignment Charts + maintainer: Afton Coombs + description: |- + 'D&D' alignment charts show 9 boxes with values for good + through evil and values for chaotic through lawful. This package + easily creates these alignment charts from user-provided image paths + and alignment values. + date_publication: '2025-02-24' + bug_reports: https://github.com/aftonsteps/ggalignment/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggalignment + url_git: https://github.com/aftonsteps/ggalignment +ggallin: + version: 0.1.1 + title: Grab Bag of 'ggplot2' Functions + maintainer: Steven E. Pav + description: |- + Extra geoms and scales for 'ggplot2', including geom_cloud(), + a Normal density cloud replacement for errorbars; + transforms ssqrt_trans and pseudolog10_trans, which are loglike but + appropriate for negative data; interp_trans() and warp_trans() which + provide scale transforms based on interpolation; + and an infix compose operator for scale transforms. + date_publication: '2017-10-02' + bug_reports: https://github.com/shabbychef/ggallin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggallin + url_git: https://github.com/shabbychef/ggallin +ggalluvial: + version: 0.12.5 + title: Alluvial Plots in 'ggplot2' + maintainer: Jason Cory Brunson + description: |- + Alluvial plots use variable-width ribbons and stacked bar plots to + represent multi-dimensional or repeated-measures data with categorical or + ordinal variables; see Riehmann, Hanfler, and Froehlich (2005) + and Rosvall and Bergstrom (2010) + . + Alluvial plots are statistical graphics in the sense of Wilkinson (2006) + ; they share elements with Sankey diagrams and + parallel sets plots but are uniquely determined from the data and a small + set of parameters. This package extends Wickham's (2010) + layered grammar of graphics to generate + alluvial plots from tidy data. + date_publication: '2023-02-22' + bug_reports: https://github.com/corybrunson/ggalluvial/issues + url: http://corybrunson.github.io/ggalluvial/ + url_cran: https://CRAN.R-project.org/package=ggalluvial + url_git: '' +GGally: + version: 2.2.1 + title: Extension to 'ggplot2' + maintainer: Barret Schloerke + description: |2- + + The R package 'ggplot2' is a plotting system based on the grammar of graphics. + 'GGally' extends 'ggplot2' by adding several functions + to reduce the complexity of combining geometric objects with transformed data. + Some of these functions include a pairwise plot matrix, a two group pairwise plot + matrix, a parallel coordinates plot, a survival plot, and several functions to + plot networks. + date_publication: '2024-02-14' + bug_reports: https://github.com/ggobi/ggally/issues + url: https://ggobi.github.io/ggally/ + url_cran: https://CRAN.R-project.org/package=GGally + url_git: https://github.com/ggobi/ggally +ggalt: + version: 0.4.0 + title: |- + Extra Coordinate Systems, 'Geoms', Statistical Transformations, + Scales and Fonts for 'ggplot2' + maintainer: Bob Rudis + description: |- + A compendium of new geometries, coordinate systems, statistical + transformations, scales and fonts for 'ggplot2', including splines, 1d and 2d densities, + univariate average shifted histograms, a new map coordinate system based on the + 'PROJ.4'-library along with geom_cartogram() that mimics the original functionality of + geom_map(), formatters for "bytes", a stat_stepribbon() function, increased 'plotly' + compatibility and the 'StateFace' open source font 'ProPublica'. Further new + functionality includes lollipop charts, dumbbell charts, the ability to encircle + points and coordinate-system-based text annotations. + date_publication: '2017-02-15' + bug_reports: https://github.com/hrbrmstr/ggalt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggalt + url_git: https://github.com/hrbrmstr/ggalt +ggamma: + version: 1.0.1 + title: Generalized Gamma Probability Distribution + maintainer: Matheus H. J. Saldanha + description: Density, distribution function, quantile function and random generation + for the Generalized Gamma proposed in Stacy, E. W. (1962) . + date_publication: '2019-12-15' + bug_reports: https://github.com/matheushjs/ggamma/issues + url: https://mjsaldanha.com/posts/ggamma + url_cran: https://CRAN.R-project.org/package=ggamma + url_git: '' +gganimate: + version: 1.0.9 + title: A Grammar of Animated Graphics + maintainer: Thomas Lin Pedersen + description: |- + The grammar of graphics as implemented in the 'ggplot2' + package has been successful in providing a powerful API for creating + static visualisation. In order to extend the API for animated graphics + this package provides a completely new set of grammar, fully + compatible with 'ggplot2' for specifying transitions and animations in + a flexible and extensible way. + date_publication: '2024-02-27' + bug_reports: https://github.com/thomasp85/gganimate/issues + url: https://gganimate.com + url_cran: https://CRAN.R-project.org/package=gganimate + url_git: https://github.com/thomasp85/gganimate +ggarchery: + version: 0.4.3 + title: Flexible Segment Geoms with Arrows for 'ggplot2' + maintainer: Matthew Hall + description: Geoms for placing arrowheads at multiple points along a segment, not + just at the end; position function to shift starts and ends of arrows to avoid + exactly intersecting points. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggarchery + url_git: https://github.com/mdhall272/ggarchery +ggarrow: + version: 0.1.0 + title: Arrows for 'ggplot2' + maintainer: Teun van den Brand + description: |- + A 'ggplot2' extension that adds specialised arrow geometry layers. + It offers more arrow options than the standard 'grid' arrows that + are built-in many line-based geom layers. + date_publication: '2024-06-05' + bug_reports: https://github.com/teunbrand/ggarrow/issues + url: https://teunbrand.github.io/ggarrow/ + url_cran: https://CRAN.R-project.org/package=ggarrow + url_git: https://github.com/teunbrand/ggarrow +ggautomap: + version: 0.3.2 + title: Create Maps from a Column of Place Names + maintainer: Carl Suster + description: |- + Mapping tools that convert place names to coordinates on the fly. + These 'ggplot2' extensions make maps from a data frame where one of the + columns contains place names, without having to directly work with the + underlying geospatial data and tools. The corresponding map data must be + registered with 'cartographer' either by the user or by another package. + date_publication: '2023-05-24' + bug_reports: https://github.com/cidm-ph/ggautomap/issues + url: https://cidm-ph.github.io/ggautomap/ + url_cran: https://CRAN.R-project.org/package=ggautomap + url_git: https://github.com/cidm-ph/ggautomap +ggbeeswarm: + version: 0.7.2 + title: Categorical Scatter (Violin Point) Plots + maintainer: Erik Clarke + description: |- + Provides two methods of plotting categorical scatter plots such + that the arrangement of points within a category reflects the density of + data at that region, and avoids over-plotting. + date_publication: '2023-04-29' + bug_reports: https://github.com/eclarke/ggbeeswarm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggbeeswarm + url_git: https://github.com/eclarke/ggbeeswarm +ggbiplot: + version: 0.6.2 + title: A Grammar of Graphics Implementation of Biplots + maintainer: Michael Friendly + description: |- + A 'ggplot2' based implementation of biplots, giving a representation of a dataset in + a two dimensional space accounting for the greatest variance, together with variable vectors + showing how the data variables relate to this space. It provides a + replacement for stats::biplot(), but with many enhancements to control the analysis and + graphical display. It implements + biplot and scree plot methods which can be used with the results of prcomp(), princomp(), + FactoMineR::PCA(), ade4::dudi.pca() or MASS::lda() and can be customized using 'ggplot2' techniques. + date_publication: '2024-01-08' + bug_reports: https://github.com/friendly/ggbiplot/issues + url: https://friendly.github.io/ggbiplot/ + url_cran: https://CRAN.R-project.org/package=ggbiplot + url_git: https://github.com/friendly/ggbiplot +ggblanket: + version: 12.1.0 + title: Simplify 'ggplot2' Visualisation + maintainer: David Hodge + description: |- + Simplify 'ggplot2' visualisation with 'ggblanket' wrapper + functions. + date_publication: '2025-01-27' + bug_reports: https://github.com/davidhodge931/ggblanket/issues + url: https://davidhodge931.github.io/ggblanket/ + url_cran: https://CRAN.R-project.org/package=ggblanket + url_git: https://github.com/davidhodge931/ggblanket +ggblend: + version: 0.1.0 + title: Blending and Compositing Algebra for 'ggplot2' + maintainer: Matthew Kay + description: |- + Algebra of operations for blending, copying, adjusting, and + compositing layers in 'ggplot2'. Supports copying and adjusting the + aesthetics or parameters of an existing layer, partitioning a layer + into multiple pieces for re-composition, applying affine transformations + to layers, and combining layers (or partitions of layers) using blend modes + (including commutative blend modes, like multiply and darken). Blend + mode support is particularly useful for creating plots with overlapping + groups where the layer drawing order does not change the output; + see Kindlmann and Scheidegger (2014) . + date_publication: '2023-05-22' + bug_reports: https://github.com/mjskay/ggblend/issues/new + url: https://mjskay.github.io/ggblend/ + url_cran: https://CRAN.R-project.org/package=ggblend + url_git: https://github.com/mjskay/ggblend/ +ggborderline: + version: 0.2.0 + title: Line Plots that Pop + maintainer: Jacob Scott + description: |- + A set of geometries to make line plots a little bit nicer. Use + along with 'ggplot2' to: + - Improve the clarity of line plots with many overlapping lines + - Draw more realistic worms. + date_publication: '2022-10-25' + bug_reports: '' + url: https://wurli.github.io/ggborderline/ + url_cran: https://CRAN.R-project.org/package=ggborderline + url_git: https://github.com/wurli/ggborderline +ggbrace: + version: 0.1.1 + title: Curly Braces for 'ggplot2' + maintainer: Nicolas Huber + description: |- + Provides curly braces in 'ggplot2' plus matching text. + stat_brace() plots braces partially in the confines of data so that the brace is set apart from it. + stat_bracetext() plots corresponding text, fitting to the braces from stat_brace(). + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggbrace + url_git: '' +ggbrain: + version: 0.8.1 + title: |- + Create Images of Volumetric Brain Data in NIfTI Format Using + 'ggplot2' Syntax + maintainer: Michael Hallquist + description: |- + A 'ggplot2'-consistent approach to generating 2D displays of volumetric brain imaging data. + Display data from multiple NIfTI images using standard 'ggplot2' conventions such scales, limits, and + themes to control the appearance of displays. The resulting plots are returned as 'patchwork' objects, + inheriting from 'ggplot', allowing for any standard modifications of display aesthetics supported by 'ggplot2'. + date_publication: '2023-03-21' + bug_reports: https://github.com/michaelhallquist/ggbrain/issues + url: https://michaelhallquist.github.io/ggbrain/ + url_cran: https://CRAN.R-project.org/package=ggbrain + url_git: '' +ggbreak: + version: 0.1.4 + title: Set Axis Break for 'ggplot2' + maintainer: Guangchuang Yu + description: An implementation of scale functions for setting axis breaks of a 'gg' + plot (S Xu (2021) ). + date_publication: '2025-02-04' + bug_reports: https://github.com/YuLab-SMU/ggbreak/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggbreak + url_git: https://github.com/YuLab-SMU/ggbreak +ggbrick: + version: 0.3.0 + title: Waffle Style Chart with a Brick Layout in 'ggplot2' + maintainer: Daniel Oehm + description: |- + A new take on the bar chart. Similar to a waffle style chart but + instead of squares the layout resembles a brick wall. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggbrick + url_git: '' +ggBubbles: + version: 0.1.4 + title: Mini Bubble Plots for Comparison of Discrete Data with 'ggplot2' + maintainer: Thomas Schwarzl + description: |- + When comparing discrete data mini bubble plots allow displaying + more information than traditional bubble plots via colour, shape or labels. + Exact overlapping coordinates will be transformed so they surround the + original point circularly without overlapping. This is implemented as a + position_surround() function for 'ggplot2'. + date_publication: '2019-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggBubbles + url_git: '' +ggbuildr: + version: 0.1.0 + title: Save Incremental Builds of Plots + maintainer: Jongbin Jung + description: |- + Saves a 'ggplot' object into multiple files, each with a layer + added incrementally. Generally to be used in presentation slides. + Flexible enough to allow different file types for the final complete plot, + and intermediate builds. + date_publication: '2018-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggbuildr + url_git: '' +ggbump: + version: 0.1.0 + title: Bump Chart and Sigmoid Curves + maintainer: David Sjoberg + description: A geom for ggplot to create bump plots. Can be good to use for showing + rank over time. + date_publication: '2020-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggbump + url_git: '' +ggchangepoint: + version: 0.1.0 + title: Combines Changepoint Analysis with 'ggplot2' + maintainer: Youzhi Yu + description: |- + R provides fantastic tools for changepoint + analysis, but plots generated by the tools do + not have the 'ggplot2' style. This tool, however, + combines 'changepoint', 'changepoint.np' and 'ecp' + together, and uses 'ggplot2' to visualize changepoints. + date_publication: '2022-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggchangepoint + url_git: '' +ggcharts: + version: 0.2.1 + title: Shorten the Distance from Data Visualization Idea to Actual Plot + maintainer: Thomas Neitmann + description: |- + Streamline the creation of common charts by taking care of a lot of + data preprocessing and plot customization for the user. Provides a + high-level interface to create plots using 'ggplot2'. + date_publication: '2020-05-20' + bug_reports: https://github.com/thomas-neitmann/ggcharts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggcharts + url_git: https://github.com/thomas-neitmann/ggcharts +ggChernoff: + version: 0.3.0 + title: Chernoff Faces for 'ggplot2' + maintainer: David Selby + description: |- + Provides a Chernoff face geom for 'ggplot2'. Maps multivariate data + to human-like faces. Inspired by Chernoff (1973) . + date_publication: '2022-11-17' + bug_reports: https://github.com/Selbosh/ggChernoff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggChernoff + url_git: https://github.com/Selbosh/ggChernoff +GGClassification: + version: '0.1' + title: Gabriel Graph Based Large-Margin Classifiers + maintainer: Felipe Campos + description: Contains the implementation of a binary large margin classifier based + on Gabriel Graph. References for this method can be found in L.C.B. Torres et + al. (2015) . + date_publication: '2020-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGClassification + url_git: '' +ggcleveland: + version: 0.1.0 + title: Implementation of Plots from Cleveland's Visualizing Data Book + maintainer: Marcos Prunello + description: |- + William S. Cleveland's book 'Visualizing Data' is a classic piece + of literature on Exploratory Data Analysis. Although it was written + several decades ago, its content is still relevant as it proposes several + tools which are useful to discover patterns and relationships among the data + under study, and also to assess the goodness of fit o a model. This package + provides functions to produce the 'ggplot2' versions of the visualization tools + described in this book and is thought to be used in the context of courses on + Exploratory Data Analysis. + date_publication: '2021-08-16' + bug_reports: https://github.com/mpru/ggcleveland/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggcleveland + url_git: https://github.com/mpru/ggcleveland +ggcompare: + version: 0.0.3 + title: Mean Comparison in 'ggplot2' + maintainer: Hao Wang + description: |- + Add mean comparison annotations to a 'ggplot'. + This package provides an easy way to indicate if two or more groups are significantly different in a 'ggplot'. + Usually you do not need to specify the test method, you only need to tell stat_compare() whether you want to perform a parametric test or a nonparametric test, and stat_compare() will automatically choose the appropriate test method based on your data. + For comparisons between two groups, the p-value is calculated by t-test (parametric) or Wilcoxon rank sum test (nonparametric). For comparisons among more than two groups, the p-value is calculated by One-way ANOVA (parametric) or Kruskal-Wallis test (nonparametric). + date_publication: '2024-12-09' + bug_reports: https://github.com/HMU-WH/ggcompare/issues/ + url: https://hmu-wh.github.io/ggcompare/ + url_cran: https://CRAN.R-project.org/package=ggcompare + url_git: https://github.com/HMU-WH/ggcompare/ +ggcorrplot: + version: 0.1.4.1 + title: Visualization of a Correlation Matrix using 'ggplot2' + maintainer: Alboukadel Kassambara + description: |- + The 'ggcorrplot' package can be used to visualize easily a + correlation matrix using 'ggplot2'. It provides a solution for + reordering the correlation matrix and displays the significance level + on the plot. It also includes a function for computing a matrix of + correlation p-values. + date_publication: '2023-09-05' + bug_reports: https://github.com/kassambara/ggcorrplot/issues + url: http://www.sthda.com/english/wiki/ggcorrplot-visualization-of-a-correlation-matrix-using-ggplot2 + url_cran: https://CRAN.R-project.org/package=ggcorrplot + url_git: '' +ggcorset: + version: 0.5.0 + title: The Corset Plot + maintainer: Kyla Belisario + description: |- + Corset plots are a visualization technique used strictly to visualize repeat measures + at 2 time points (such as pre- and post- data). The distribution of measurements are visualized at + each time point, whilst the trajectories of individual change are visualized by connecting the pre- + and post- values linearly. These lines can be coloured to represent the magnitude of change, or + other user-defined value. This method of visualization is ideal for showing the heterogeneity of + data, including differences by sub-groups. The package relies on 'ggplot2' allowing for easy + integration so that users can customize their visualizations as required. Users can create corset + plots using data in either wide or long format using the functions gg_corset() or gg_corset_elongated(), respectively. + date_publication: '2024-04-07' + bug_reports: https://github.com/kbelisar/ggcorset/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggcorset + url_git: https://github.com/kbelisar/ggcorset +ggdag: + version: 0.2.13 + title: Analyze and Create Elegant Directed Acyclic Graphs + maintainer: Malcolm Barrett + description: |- + Tidy, analyze, and plot directed acyclic graphs (DAGs). + 'ggdag' is built on top of 'dagitty', an R package that uses the + 'DAGitty' web tool () for creating and analyzing + DAGs. 'ggdag' makes it easy to tidy and plot 'dagitty' objects using + 'ggplot2' and 'ggraph', as well as common analytic and graphical + functions, such as determining adjustment sets and node relationships. + date_publication: '2024-07-22' + bug_reports: https://github.com/r-causal/ggdag/issues + url: https://r-causal.github.io/ggdag/ + url_cran: https://CRAN.R-project.org/package=ggdag + url_git: https://github.com/r-causal/ggdag +ggdark: + version: 0.2.1 + title: Dark Mode for 'ggplot2' Themes + maintainer: Neal Grantham + description: |- + Activate dark mode on your favorite 'ggplot2' theme + with dark_mode() or use the dark versions of + 'ggplot2' themes, including dark_theme_gray(), + dark_theme_minimal(), and others. When a dark theme + is applied, all geom color and geom fill defaults + are changed to make them visible against a dark + background. To restore the defaults to their original + values, use invert_geom_defaults(). + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggdark + url_git: '' +ggdaynight: + version: 0.1.3 + title: Add Day/Night Patterns to 'ggplot2' Plots + maintainer: Gabriel S. Pires + description: |- + It provides a custom 'ggplot2' geom to add day/night patterns to plots. + It visually distinguishes daytime and nighttime periods. It is useful for + visualizing data that spans multiple days and for highlighting diurnal patterns. + date_publication: '2024-05-23' + bug_reports: https://github.com/GabrielSlPires/ggdaynight/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggdaynight + url_git: https://github.com/GabrielSlPires/ggdaynight +ggdemetra: + version: 0.2.8 + title: |- + 'ggplot2' Extension for Seasonal and Trading Day Adjustment with + 'RJDemetra' + maintainer: Alain Quartier-la-Tente + description: |- + Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment + made by 'RJDemetra'. 'RJDemetra' is an 'R' interface around 'JDemetra+' (), + the seasonal adjustment software officially recommended to the members of the European Statistical System and + the European System of Central Banks. + date_publication: '2024-02-04' + bug_reports: https://github.com/AQLT/ggdemetra/issues + url: https://aqlt.github.io/ggdemetra/ + url_cran: https://CRAN.R-project.org/package=ggdemetra + url_git: https://github.com/AQLT/ggdemetra +ggdendro: + version: 0.2.0 + title: Create Dendrograms and Tree Diagrams Using 'ggplot2' + maintainer: Andrie de Vries + description: |- + This is a set of tools for dendrograms and + tree plots using 'ggplot2'. The 'ggplot2' philosophy is to + clearly separate data from the presentation. + Unfortunately the plot method for dendrograms plots + directly to a plot device without exposing the data. + The 'ggdendro' package resolves this by making available + functions that extract the dendrogram plot data. The package + provides implementations for 'tree', 'rpart', as well as diana and agnes + (from 'cluster') diagrams. + date_publication: '2024-02-23' + bug_reports: https://github.com/andrie/ggdendro/issues + url: https://andrie.github.io/ggdendro/ + url_cran: https://CRAN.R-project.org/package=ggdendro + url_git: '' +ggdensity: + version: 1.0.0 + title: Interpretable Bivariate Density Visualization with 'ggplot2' + maintainer: James Otto + description: |- + The 'ggplot2' package provides simple functions for visualizing contours + of 2-d kernel density estimates. 'ggdensity' implements several additional density estimators + as well as more interpretable visualizations based on highest density regions instead of + the traditional height of the estimated density surface. + date_publication: '2023-02-09' + bug_reports: https://github.com/jamesotto852/ggdensity/issues/ + url: https://jamesotto852.github.io/ggdensity/ + url_cran: https://CRAN.R-project.org/package=ggdensity + url_git: https://github.com/jamesotto852/ggdensity/ +ggdist: + version: 3.3.2 + title: Visualizations of Distributions and Uncertainty + maintainer: Matthew Kay + description: |- + Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for + visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as + frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as + bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include + but are not limited to: points with multiple uncertainty intervals, + eye plots (Spiegelhalter D., 1999) , + density plots, gradient plots, dot plots (Wilkinson L., 1999) , + quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) , + complementary cumulative distribution function + barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) , + and fit curves with multiple uncertainty ribbons. + date_publication: '2024-03-05' + bug_reports: https://github.com/mjskay/ggdist/issues/new + url: https://mjskay.github.io/ggdist/ + url_cran: https://CRAN.R-project.org/package=ggdist + url_git: https://github.com/mjskay/ggdist/ +ggdmc: + version: 0.2.6.0 + title: Cognitive Models + maintainer: Yi-Shin Lin + description: Hierarchical Bayesian models. The package provides tools to fit two + response time models, using the population-based Markov Chain Monte Carlo. + date_publication: '2019-04-29' + bug_reports: https://github.com/yxlin/ggdmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggdmc + url_git: https://github.com/yxlin/ggdmc +ggDoE: + version: '0.8' + title: Modern Graphs for Design of Experiments with 'ggplot2' + maintainer: Jose Toledo Luna + description: |- + Generate commonly used plots in the field of design of experiments using 'ggplot2'. + 'ggDoE' currently supports the following plots: alias matrix, box cox transformation, boxplots, lambda plot, + regression diagnostic plots, half normal plots, main and interaction effect plots for factorial designs, + contour plots for response surface methodology, Pareto plot, and two dimensional projections of a latin hypercube design. + date_publication: '2024-02-10' + bug_reports: https://github.com/toledo60/ggDoE/issues + url: https://ggdoe.netlify.app + url_cran: https://CRAN.R-project.org/package=ggDoE + url_git: '' +ggDoubleHeat: + version: 0.1.2 + title: A Heatmap-Like Visualization Tool + maintainer: Youzhi Yu + description: |- + A data visualization design that provides comparison between + two (Double) data sources (usually on a par with each other) on one + reformed heatmap, while inheriting 'ggplot2' features. + date_publication: '2023-08-24' + bug_reports: https://github.com/PursuitOfDataScience/ggDoubleHeat/issues + url: https://pursuitofdatascience.github.io/ggDoubleHeat/ + url_cran: https://CRAN.R-project.org/package=ggDoubleHeat + url_git: '' +gge: + version: '1.9' + title: Genotype Plus Genotype-by-Environment Biplots + maintainer: Kevin Wright + description: |- + Create biplots for GGE (genotype plus + genotype-by-environment) and GGB (genotype plus + genotype-by-block-of-environments) models. See Laffont et al. (2013) + . + date_publication: '2024-10-28' + bug_reports: https://github.com/kwstat/gge/issues + url: https://kwstat.github.io/gge/ + url_cran: https://CRAN.R-project.org/package=gge + url_git: '' +ggeasy: + version: 0.1.5 + title: Easy Access to 'ggplot2' Commands + maintainer: Jonathan Carroll + description: |- + Provides a series of aliases to commonly used but difficult + to remember 'ggplot2' sequences. + date_publication: '2024-11-03' + bug_reports: https://github.com/jonocarroll/ggeasy/issues + url: https://jonocarroll.github.io/ggeasy/ + url_cran: https://CRAN.R-project.org/package=ggeasy + url_git: https://github.com/jonocarroll/ggeasy +GGEBiplots: + version: 0.1.3 + title: GGE Biplots with 'ggplot2' + maintainer: Sam Dumble + description: Genotype plus genotype-by-environment (GGE) biplots rendered using + 'ggplot2'. Provides a command line interface to all of the functionality contained + within the archived package 'GGEBiplotGUI'. + date_publication: '2022-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGEBiplots + url_git: '' +ggedit: + version: 0.4.1 + title: Interactive 'ggplot2' Layer and Theme Aesthetic Editor + maintainer: Jonathan Sidi + description: Interactively edit 'ggplot2' layer and theme aesthetics definitions. + date_publication: '2024-03-04' + bug_reports: https://github.com/yonicd/ggedit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggedit + url_git: https://github.com/yonicd/ggedit +ggeffects: + version: 2.2.0 + title: |- + Create Tidy Data Frames of Marginal Effects for 'ggplot' from + Model Outputs + maintainer: Daniel Lüdecke + description: |- + Compute marginal effects and adjusted predictions from statistical + models and returns the result as tidy data frames. These data frames are + ready to use with the 'ggplot2'-package. Effects and predictions can be + calculated for many different models. Interaction terms, splines and + polynomial terms are also supported. The main functions are ggpredict(), + ggemmeans() and ggeffect(). There is a generic plot()-method to plot the + results using 'ggplot2'. + date_publication: '2025-02-05' + bug_reports: https://github.com/strengejacke/ggeffects/issues/ + url: https://strengejacke.github.io/ggeffects/ + url_cran: https://CRAN.R-project.org/package=ggeffects + url_git: '' +ggenealogy: + version: 1.0.3 + title: Visualization Tools for Genealogical Data + maintainer: Lindsay Rutter + description: Methods for searching through genealogical data and displaying the + results. Plotting algorithms assist with data exploration and publication-quality + image generation. Includes interactive genealogy visualization tools. Provides + parsing and calculation methods for variables in descendant branches of interest. + Uses the Grammar of Graphics. + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggenealogy + url_git: '' +ggESDA: + version: 0.2.0 + title: Exploratory Symbolic Data Analysis with 'ggplot2' + maintainer: Bo-Syue Jiang + description: Implements an extension of 'ggplot2' and visualizes the symbolic data + with multiple plot which can be adjusted by more general and flexible input arguments. + It also provides a function to transform the classical data to symbolic data by + both clustering algorithm and customized method. + date_publication: '2022-08-19' + bug_reports: https://github.com/kiangkiangkiang/ggESDA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggESDA + url_git: https://github.com/kiangkiangkiang/ggESDA +ggetho: + version: 0.3.7 + title: |- + Visualisation of High-Throughput Behavioural (i.e. Ethomics) + Data + maintainer: Quentin Geissmann + description: |- + Extension of 'ggplot2' providing layers, scales and preprocessing functions + useful to represent behavioural variables that are recorded over multiple animals and days. + This package is part of the 'rethomics' framework . + date_publication: '2022-11-24' + bug_reports: https://github.com/rethomics/ggetho/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggetho + url_git: https://github.com/rethomics/ggetho +ggExtra: + version: 0.10.1 + title: |- + Add Marginal Histograms to 'ggplot2', and More 'ggplot2' + Enhancements + maintainer: Dean Attali + description: |- + Collection of functions and layers to enhance 'ggplot2'. The + flagship function is 'ggMarginal()', which can be used to add marginal + histograms/boxplots/density plots to 'ggplot2' scatterplots. + date_publication: '2023-08-21' + bug_reports: https://github.com/daattali/ggExtra/issues + url: https://daattali.com/shiny/ggExtra-ggMarginal-demo/ + url_cran: https://CRAN.R-project.org/package=ggExtra + url_git: https://github.com/daattali/ggExtra +ggfacto: + version: 0.3.2 + title: Graphs for Correspondence Analysis + maintainer: Brice Nocenti + description: |- + Readable, complete and pretty graphs for correspondence analysis made + with 'FactoMineR'. They can be rendered as interactive 'HTML' plots, showing useful + informations at mouse hover. The interest is not mainly visual but statistical: + it helps the reader to keep in mind the data contained in the cross-table or Burt + table while reading the correspondence analysis, thus preventing over-interpretation. + Most graphs are made with 'ggplot2', which means that you can use the + syntax to + manually add as many graphical pieces you want, or change theme elements. 3D + graphs are made with 'plotly'. + date_publication: '2024-10-02' + bug_reports: https://github.com/BriceNocenti/ggfacto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggfacto + url_git: https://github.com/BriceNocenti/ggfacto +ggfields: + version: 0.0.6 + title: Add Vector Field Layers to Ggplots + maintainer: Pepijn de Vries + description: |- + Add vector field layers to ggplots. Ideal for visualising + wind speeds, water currents, electric/magnetic fields, etc. + Accepts data.frames, simple features (sf), and spatiotemporal arrays (stars) + objects as input. Vector fields are depicted as arrows starting at specified + locations, and with specified angles and radii. + date_publication: '2024-02-26' + bug_reports: '' + url: https://pepijn-devries.github.io/ggfields/ + url_cran: https://CRAN.R-project.org/package=ggfields + url_git: https://github.com/pepijn-devries/ggfields/ +ggfigdone: + version: 0.1.2 + title: Manage & Modify 'ggplot' Figures using 'ggfigdone' + maintainer: Wenjie SUN + description: When you prepare a presentation or a report, you often need to manage + a large number of 'ggplot' figures. You need to change the figure size, modify + the title, label, themes, etc. It is inconvenient to go back to the original code + to make these changes. This package provides a simple way to manage 'ggplot' figures. + You can easily add the figure to the database and update them later using CLI + (command line interface) or GUI (graphical user interface). + date_publication: '2024-09-10' + bug_reports: https://github.com/wenjie1991/ggfigdone/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggfigdone + url_git: '' +ggFishPlots: + version: 0.3.0 + title: |- + Visualise and Calculate Life History Parameters for Fisheries + Science using 'ggplot2' + maintainer: Mikko Vihtakari + description: |- + Contains functions to create life history parameter plots from raw data. + The plots are created using 'ggplot2', and calculations done using the 'tidyverse' + collection of packages. The package contains references to FishBase + (Froese R., Pauly D., 2023) . + date_publication: '2024-06-26' + bug_reports: https://github.com/DeepWaterIMR/ggFishPlots/issues + url: https://deepwaterimr.github.io/ggFishPlots/ + url_cran: https://CRAN.R-project.org/package=ggFishPlots + url_git: '' +ggfittext: + version: 0.10.2 + title: Fit Text Inside a Box in 'ggplot2' + maintainer: David Wilkins + description: A 'ggplot2' extension to fit text into a box by growing, shrinking + or wrapping the text. + date_publication: '2024-02-01' + bug_reports: https://github.com/wilkox/ggfittext/issues/ + url: https://wilkox.org/ggfittext/ + url_cran: https://CRAN.R-project.org/package=ggfittext + url_git: '' +ggfixest: + version: 0.2.0 + title: Dedicated 'ggplot2' Methods for 'fixest' Objects + maintainer: Grant McDermott + description: |- + Provides 'ggplot2' equivalents of fixest::coefplot() and fixest::iplot(), + for producing nice coefficient plots and interaction plots. Enables some + additional functionality and convenience features, including grouped + multi-'fixest' object faceting and programmatic updates to existing plots + (e.g., themes and aesthetics). + date_publication: '2025-01-22' + bug_reports: https://github.com/grantmcdermott/ggfixest/issues + url: https://grantmcdermott.com/ggfixest/ + url_cran: https://CRAN.R-project.org/package=ggfixest + url_git: '' +ggflowchart: + version: 1.0.0 + title: Flowcharts with 'ggplot2' + maintainer: Nicola Rennie + description: |- + Flowcharts can be a useful way to visualise complex processes. This package + uses the layered grammar of graphics of 'ggplot2' to create simple flowcharts. + date_publication: '2023-05-11' + bug_reports: '' + url: https://nrennie.github.io/ggflowchart/ + url_cran: https://CRAN.R-project.org/package=ggflowchart + url_git: '' +ggfocus: + version: 1.0.0 + title: Scales that Focus Specific Levels in your ggplot() + maintainer: Victor Freguglia + description: |- + A 'ggplot2' extension that provides tools for automatically + creating scales to focus on subgroups of the data plotted + without losing other information. + date_publication: '2020-01-23' + bug_reports: https://github.com/Freguglia/ggfocus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggfocus + url_git: https://github.com/Freguglia/ggfocus +ggfootball: + version: 0.2.0 + title: Plotting Expected Goals (xG) Stats with 'Understat' Data + maintainer: Aymen Nasri + description: |- + Scrapes shots data from 'Understat' and visualizes it using interactive plots: + - A detailed shot map displaying the location, type, and xG value of shots taken by both teams. + - An xG timeline chart showing the cumulative xG for each team over time, annotated with the details of scored goals. + date_publication: '2025-01-31' + bug_reports: https://github.com/aymennasri/ggfootball/issues + url: http://aymennasri.me/ggfootball/ + url_cran: https://CRAN.R-project.org/package=ggfootball + url_git: '' +ggforce: + version: 0.4.2 + title: Accelerating 'ggplot2' + maintainer: Thomas Lin Pedersen + description: |- + The aim of 'ggplot2' is to aid in visual data investigations. This + focus has led to a lack of facilities for composing specialised plots. + 'ggforce' aims to be a collection of mainly new stats and geoms that fills + this gap. All additional functionality is aimed to come through the official + extension system so using 'ggforce' should be a stable experience. + date_publication: '2024-02-19' + bug_reports: https://github.com/thomasp85/ggforce/issues + url: https://ggforce.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=ggforce + url_git: https://github.com/thomasp85/ggforce +ggformula: + version: 0.12.0 + title: Formula Interface to the Grammar of Graphics + maintainer: Randall Pruim + description: Provides a formula interface to 'ggplot2' graphics. + date_publication: '2023-11-09' + bug_reports: https://github.com/ProjectMOSAIC/ggformula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggformula + url_git: https://github.com/ProjectMOSAIC/ggformula +ggfortify: + version: 0.4.17 + title: Data Visualization Tools for Statistical Analysis Results + maintainer: Yuan Tang + description: |- + Unified plotting tools for statistics commonly used, such as GLM, + time series, PCA families, clustering and survival analysis. The package offers + a single plotting interface for these analysis results and plots in a unified + style using 'ggplot2'. + date_publication: '2024-04-17' + bug_reports: https://github.com/sinhrks/ggfortify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggfortify + url_git: https://github.com/sinhrks/ggfortify +ggfoundry: + version: 0.3.1 + title: Shape Foundry & Geom for 'ggplot2' + maintainer: Carl Goodwin + description: |- + A 'ggplot2' extension that supports arbitrary + hand-crafted colourable & fillable shapes. New shapes may be feature + requested via a Github issue. + date_publication: '2024-07-06' + bug_reports: https://github.com/cgoo4/ggfoundry/issues + url: https://cgoo4.github.io/ggfoundry/ + url_cran: https://CRAN.R-project.org/package=ggfoundry + url_git: https://github.com/cgoo4/ggfoundry +ggfun: + version: 0.1.8 + title: Miscellaneous Functions for 'ggplot2' + maintainer: Guangchuang Yu + description: Useful functions and utilities for 'ggplot' object (e.g., geometric + layers, themes, and utilities to edit the object). + date_publication: '2024-12-03' + bug_reports: https://github.com/YuLab-SMU/ggfun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggfun + url_git: https://github.com/YuLab-SMU/ggfun +ggfx: + version: 1.0.1 + title: Pixel Filters for 'ggplot2' and 'grid' + maintainer: Thomas Lin Pedersen + description: |- + Provides a range of filters that can be applied to layers from the + 'ggplot2' package and its extensions, along with other graphic elements such + as guides and theme elements. The filters are applied at render time and + thus uses the exact pixel dimensions needed. + date_publication: '2022-08-22' + bug_reports: https://github.com/thomasp85/ggfx/issues + url: https://ggfx.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=ggfx + url_git: https://github.com/thomasp85/ggfx +gggap: + version: 1.0.1 + title: |- + Streamlined Creation of Segments on the Y-Axis of 'ggplot2' + Plots + maintainer: Carlos Morales + description: |- + The function gggap() streamlines the creation of segments on + the y-axis of 'ggplot2' plots which is otherwise not a trivial task to + accomplish. + date_publication: '2020-11-20' + bug_reports: https://github.com/cmoralesmx/gggap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gggap + url_git: https://github.com/cmoralesmx/gggap +gggenes: + version: 0.5.1 + title: Draw Gene Arrow Maps in 'ggplot2' + maintainer: David Wilkins + description: A 'ggplot2' extension for drawing gene arrow maps. + date_publication: '2023-09-05' + bug_reports: https://github.com/wilkox/gggenes/issues/ + url: https://wilkox.org/gggenes/ + url_cran: https://CRAN.R-project.org/package=gggenes + url_git: '' +gggenomes: + version: 1.0.1 + title: A Grammar of Graphics for Comparative Genomics + maintainer: Thomas Hackl + description: |- + An extension of 'ggplot2' for creating complex genomic + maps. It builds on the power of 'ggplot2' and 'tidyverse' adding new 'ggplot2'-style + geoms & positions and 'dplyr'-style verbs to manipulate the underlying data. It + implements a layout concept inspired by 'ggraph' and introduces tracks to bring + tidiness to the mess that is genomics data. + date_publication: '2024-08-30' + bug_reports: https://github.com/thackl/gggenomes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gggenomes + url_git: https://github.com/thackl/gggenomes +ggghost: + version: 0.2.1 + title: Capture the Spirit of Your 'ggplot2' Calls + maintainer: Jonathan Carroll + description: Creates a reproducible 'ggplot2' object by storing the data and calls. + date_publication: '2016-08-20' + bug_reports: https://github.com/jonocarroll/ggghost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggghost + url_git: https://github.com/jonocarroll/ggghost +gggibbous: + version: 0.1.1 + title: Moon Charts, a Pie Chart Alternative + maintainer: Michael Bramson + description: |- + Moon charts are like pie charts except that the proportions are + shown as crescent or gibbous portions of a circle, like the lit and unlit + portions of the moon. As such, they work best with only one or two groups. + 'gggibbous' extends 'ggplot2' to allow for plotting multiple moon charts in + a single panel and does not require a square coordinate system. + date_publication: '2021-01-06' + bug_reports: https://github.com/mnbram/gggibbous/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gggibbous + url_git: https://github.com/mnbram/gggibbous +gggrid: + version: 0.2-0 + title: Draw with 'grid' in 'ggplot2' + maintainer: Paul Murrell + description: |- + An extension of 'ggplot2' that makes it easy to add + raw 'grid' output, such as customised annotations, to a + 'ggplot2' plot. + date_publication: '2022-01-11' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2021/05/31/2021-01-accessing-grid-from-ggplot2/ + url_cran: https://CRAN.R-project.org/package=gggrid + url_git: https://github.com/pmur002/gggrid +ggh4x: + version: 0.3.0 + title: Hacks for 'ggplot2' + maintainer: Teun van den Brand + description: |- + A 'ggplot2' extension that does a variety of little + helpful things. The package extends 'ggplot2' facets through + customisation, by setting individual scales per panel, resizing panels + and providing nested facets. Also allows multiple colour and fill + scales per plot. Also hosts a smaller collection of stats, geoms and axis + guides. + date_publication: '2024-12-15' + bug_reports: https://github.com/teunbrand/ggh4x/issues + url: https://teunbrand.github.io/ggh4x/ + url_cran: https://CRAN.R-project.org/package=ggh4x + url_git: https://github.com/teunbrand/ggh4x +gghalfnorm: + version: 1.1.2 + title: Create a Half Normal Plot Using 'ggplot2' + maintainer: Nathan Eastwood + description: |- + Reproduce the halfnorm() function found in the 'faraway' package + using the 'ggplot2' API. + date_publication: '2017-06-06' + bug_reports: https://github.com/nathaneastwood/gghalfnorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gghalfnorm + url_git: https://github.com/nathaneastwood/gghalfnorm +gghalves: + version: 0.1.4 + title: Compose Half-Half Plots Using Your Favourite Geoms + maintainer: Frederik Tiedemann + description: A 'ggplot2' extension for easy plotting of half-half geom combinations. + Think half boxplot and half jitterplot, or half violinplot and half dotplot. + date_publication: '2022-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gghalves + url_git: https://github.com/erocoar/gghalves +gghdx: + version: 0.1.4 + title: HDX Theme, Scales, and Other Conveniences for 'ggplot2' + maintainer: Seth Caldwell + description: |- + A Humanitarian Data Exchange (HDX) theme, color palettes, and + scales for 'ggplot2' to allow users to easily follow the HDX visual design + guide, including convenience functions for for loading and using the + Source Sans 3 font. + date_publication: '2024-09-23' + bug_reports: https://github.com/OCHA-DAP/gghdx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gghdx + url_git: https://github.com/OCHA-DAP/gghdx +ggheatmap: + version: '2.2' + title: Plot Heatmap + maintainer: Baiwei Luo + description: |- + The flexibility and excellence of 'ggplot2' is unquestionable, + so many drawing tools basically need 'ggplot2' as the operating object. + In order to develop a heatmap drawing system based on ggplot2, we developed + this tool, mainly to solve the heatmap puzzle problem and the flexible + connection between the heatmap and the 'ggplot2' object. + The advantages of this tool are as follows: + 1. More flexible label settings; + 2. Realize the linkage of heatmap and 'ggplot2' drawing system, + which is helpful for operations such as puzzles; + 3. Simple and easy to operate; + 4. Optimization of clustering tree visualization. + date_publication: '2022-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggheatmap + url_git: '' +gghighlight: + version: 0.4.1 + title: Highlight Lines and Points in 'ggplot2' + maintainer: Hiroaki Yutani + description: Make it easier to explore data with highlights. + date_publication: '2023-12-16' + bug_reports: https://github.com/yutannihilation/gghighlight/issues + url: https://yutannihilation.github.io/gghighlight/ + url_cran: https://CRAN.R-project.org/package=gghighlight + url_git: https://github.com/yutannihilation/gghighlight/ +gghilbertstrings: + version: 0.3.3 + title: A Fast 'ggplot2'-Based Implementation of Hilbert Curves + maintainer: André Calero Valdez + description: |- + A set of functions that help to create plots based on Hilbert curves. + Hilbert curves are used to map one dimensional data into the 2D plane. + The package provides a function that generate a 2D coordinate from an + integer position. As a specific use case the package provides a function + that allows mapping a character column in a data frame into 2D space + using 'ggplot2'. This allows visually comparing long lists of URLs, words, + genes or other data that has a fixed order and position. + date_publication: '2021-04-07' + bug_reports: https://github.com/Sumidu/gghilbertstrings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gghilbertstrings + url_git: https://github.com/Sumidu/gghilbertstrings +gghist: + version: 0.1.0 + title: Plot the Histogram of a Numeric Vector + maintainer: Frederik Ziebell + description: Wrapper around geom_histogram() of 'ggplot2' to plot the histogram + of a numeric vector. This is especially useful, since qplot() was deprecated in + 'ggplot2' 3.4.0. + date_publication: '2023-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gghist + url_git: https://github.com/frederikziebell/gghist +ggHoriPlot: + version: 1.0.1 + title: Horizon Plots for 'ggplot2' + maintainer: Iker Rivas-González + description: |- + A user-friendly, highly customizable R package for building + horizon plots in the 'ggplot2' environment. + date_publication: '2022-10-11' + bug_reports: https://github.com/rivasiker/ggHoriPlot/issues + url: https://rivasiker.github.io/ggHoriPlot/ + url_cran: https://CRAN.R-project.org/package=ggHoriPlot + url_git: https://github.com/rivasiker/ggHoriPlot +ggimage: + version: 0.3.3 + title: Use Image in 'ggplot2' + maintainer: Guangchuang Yu + description: |- + Supports image files and graphic objects to be visualized in + 'ggplot2' graphic system. + date_publication: '2023-06-19' + bug_reports: https://github.com/GuangchuangYu/ggimage/issues + url: https://yulab-smu.top/pkgdocs/ggimage.html(vignette) + url_cran: https://CRAN.R-project.org/package=ggimage + url_git: https://github.com/GuangchuangYu/ggimage(devel) +ggimg: + version: 0.1.2 + title: Graphics Layers for Plotting Image Data with 'ggplot2' + maintainer: Taylor B. Arnold + description: |- + Provides two new layer types for displaying image data as layers + within the Grammar of Graphics framework. Displays images using either a + rectangle interface, with a fixed bounding box, or a point interface using a + central point and general size parameter. Images can be given as local + JPEG or PNG files, external resources, or as a list column containing + raster image data. + date_publication: '2022-08-17' + bug_reports: https://github.com/statsmaths/ggimg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggimg + url_git: https://github.com/statsmaths/ggimg +gginference: + version: 0.1.3 + title: Visualise the Results of Inferential Statistics using 'ggplot2' + maintainer: Kleanthis Koupidis + description: Visualise the results of F test to compare two variances, Student's + t-test, test of equal or given proportions, Pearson's chi-squared test for count + data and test for association/correlation between paired samples. + date_publication: '2020-10-31' + bug_reports: https://github.com/okgreece/gginference/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gginference + url_git: https://github.com/okgreece/gginference +gginnards: + version: 0.2.0-1 + title: Explore the Innards of 'ggplot2' Objects + maintainer: Pedro J. Aphalo + description: |- + Extensions to 'ggplot2' providing low-level debug tools: statistics + and geometries echoing their data argument. Layer manipulation: deletion, + insertion, extraction and reordering of layers. Deletion of unused variables + from the data object embedded in "ggplot" objects. + date_publication: '2024-11-14' + bug_reports: https://github.com/aphalo/gginnards/issues + url: https://docs.r4photobiology.info/gginnards/ + url_cran: https://CRAN.R-project.org/package=gginnards + url_git: https://github.com/aphalo/gginnards +ggip: + version: 0.3.2 + title: Data Visualization for IP Addresses and Networks + maintainer: David Hall + description: |- + A 'ggplot2' extension that enables visualization of IP + (Internet Protocol) addresses and networks. The address space is + mapped onto the Cartesian coordinate system using a space-filling + curve. Offers full support for both IPv4 and IPv6 (Internet Protocol + versions 4 and 6) address spaces. + date_publication: '2023-04-04' + bug_reports: https://github.com/davidchall/ggip/issues + url: https://davidchall.github.io/ggip/ + url_cran: https://CRAN.R-project.org/package=ggip + url_git: https://github.com/davidchall/ggip +GGIR: + version: 3.2-0 + title: Raw Accelerometer Data Analysis + maintainer: Vincent T van Hees + description: A tool to process and analyse data collected with wearable raw acceleration + sensors as described in Migueles and colleagues (JMPB 2019), and van Hees and + colleagues (JApplPhysiol 2014; PLoSONE 2015). The package has been developed and + tested for binary data from 'GENEActiv' , binary (.gt3x) + and .csv-export data from 'Actigraph' devices, and + binary (.cwa) and .csv-export data from 'Axivity' . These + devices are currently widely used in research on human daily physical activity. + Further, the package can handle accelerometer data file from any other sensor + brand providing that the data is stored in csv format. Also the package allows + for external function embedding. + date_publication: '2025-02-20' + bug_reports: https://github.com/wadpac/GGIR/issues + url: https://groups.google.com/forum/#!forum/RpackageGGIR + url_cran: https://CRAN.R-project.org/package=GGIR + url_git: https://github.com/wadpac/GGIR/ +ggiraph: + version: 0.8.12 + title: Make 'ggplot2' Graphics Interactive + maintainer: David Gohel + description: Create interactive 'ggplot2' graphics using 'htmlwidgets'. + date_publication: '2025-01-08' + bug_reports: https://github.com/davidgohel/ggiraph/issues + url: https://davidgohel.github.io/ggiraph/ + url_cran: https://CRAN.R-project.org/package=ggiraph + url_git: '' +ggiraphExtra: + version: 0.3.0 + title: Make Interactive 'ggplot2'. Extension to 'ggplot2' and 'ggiraph' + maintainer: Keon-Woong Moon + description: |- + Collection of functions to enhance 'ggplot2' and 'ggiraph'. Provides functions for exploratory plots. + All plot can be a 'static' plot or an 'interactive' plot using 'ggiraph'. + date_publication: '2020-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggiraphExtra + url_git: https://github.com/cardiomoon/ggiraphExtra +GGIRread: + version: 1.0.2 + title: Wearable Accelerometer Data File Readers + maintainer: Vincent T van Hees + description: 'Reads data collected from wearable acceleratometers as used in sleep + and physical activity research. Currently supports file formats: binary data from + ''GENEActiv'' , .bin-format from GENEA devices (not + for sale), and .cwa-format from ''Axivity'' . Further, it + has functions for reading text files with epoch level aggregates from ''Actical'', + ''Fitbit'', ''Actiwatch'', ''ActiGraph'', and ''PhilipsHealthBand''. Primarily + designed to complement R package GGIR .' + date_publication: '2024-10-25' + bug_reports: https://github.com/wadpac/GGIRread/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GGIRread + url_git: https://github.com/wadpac/GGIRread/ +ggisotonic: + version: 0.1.2 + title: '''ggplot2'' Friendly Isotonic or Monotonic Regression Curves' + maintainer: Komala Sheshachala Srikanth + description: Provides stat_isotonic() to add weighted univariate isotonic regression + curves. + date_publication: '2022-05-24' + bug_reports: https://github.com/talegari/ggisotonic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggisotonic + url_git: https://github.com/talegari/ggisotonic +ggjoy: + version: 0.4.1 + title: Joyplots in 'ggplot2' + maintainer: Claus O. Wilke + description: Joyplots provide a convenient way of visualizing changes in distributions + over time or space. This package enables the creation of such plots in 'ggplot2'. + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggjoy + url_git: https://github.com/clauswilke/ggjoy +gglasso: + version: 1.5.1 + title: Group Lasso Penalized Learning Using a Unified BMD Algorithm + maintainer: Yi Yang + description: 'A unified algorithm, blockwise-majorization-descent (BMD), for efficiently + computing the solution paths of the group-lasso penalized least squares, logistic + regression, Huberized SVM and squared SVM. The package is an implementation of + Yang, Y. and Zou, H. (2015) DOI: .' + date_publication: '2024-03-24' + bug_reports: https://github.com/emeryyi/gglasso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gglasso + url_git: https://github.com/emeryyi/gglasso +gglgbtq: + version: 0.2.0 + title: Show Pride on 'ggplot2' Plots + maintainer: Laura Bakala + description: Provides multiple palettes based on pride flags with tailored themes. + date_publication: '2024-06-25' + bug_reports: '' + url: https://turtletopia.github.io/gglgbtq/ + url_cran: https://CRAN.R-project.org/package=gglgbtq + url_git: https://github.com/turtletopia/gglgbtq +gglm: + version: 1.0.3 + title: Grammar of Graphics for Linear Model Diagnostic Plots + maintainer: Grayson White + description: |- + Allows for easy creation of diagnostic plots for a variety of model objects using the Grammar of Graphics. + Provides functionality for both individual diagnostic plots and an array of four standard diagnostic plots. + date_publication: '2024-01-16' + bug_reports: https://github.com/graysonwhite/gglm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gglm + url_git: https://github.com/graysonwhite/gglm +gglogger: + version: 0.1.5 + title: Track 'ggplot2' Calls + maintainer: Panwen Wang + description: |- + Provides a way to log 'ggplot' component calls, which can be + useful for debugging and understanding how 'ggplot' objects are created. + The logged calls can be printed, saved, and re-executed to reproduce the + original 'ggplot' object. + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gglogger + url_git: https://github.com/pwwang/gglogger/ +gglorenz: + version: 0.0.2 + title: Plotting Lorenz Curve with the Blessing of 'ggplot2' + maintainer: JJ Chen + description: |- + Provides statistical transformations for plotting empirical + ordinary Lorenz curve (Lorenz 1905) and + generalized Lorenz curve (Shorrocks 1983) . + date_publication: '2020-05-27' + bug_reports: https://github.com/jjchern/gglorenz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gglorenz + url_git: https://github.com/jjchern/gglorenz +ggm: + version: 2.5.1 + title: Graphical Markov Models with Mixed Graphs + maintainer: Giovanni M. Marchetti + description: |- + Provides functions for defining + mixed graphs containing three types of edges, directed, + undirected and bi-directed, with possibly multiple edges. + These graphs are useful because they capture fundamental + independence structures in multivariate distributions + and in the induced distributions after marginalization + and conditioning. + The package is especially concerned with Gaussian graphical + models for + (i) ML estimation for directed acyclic graphs, undirected and + bi-directed graphs and ancestral graph models + (ii) testing several conditional independencies + (iii) checking global identification of DAG Gaussian models + with one latent variable + (iv) testing Markov equivalences and generating Markov + equivalent graphs of specific types. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggm + url_git: https://github.com/StaThin/ggm +ggmap: + version: 4.0.0 + title: Spatial Visualization with ggplot2 + maintainer: David Kahle + description: |- + A collection of functions to visualize spatial data and models + on top of static maps from various online sources (e.g Google Maps and Stamen + Maps). It includes tools common to those tasks, including functions for + geolocation and routing. + date_publication: '2023-11-19' + bug_reports: https://github.com/dkahle/ggmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggmap + url_git: https://github.com/dkahle/ggmap +ggmapcn: + version: 0.1.2 + title: Customizable China Map Visualizations + maintainer: Liang Ren + description: |- + A 'ggplot2' extension for visualizing China’s map, offering customizable projections, boundary styles, and buffer zones for thematic maps. + Suitable for spatial data analysis and enhancing map visualization with flexible styling options. + date_publication: '2025-01-14' + bug_reports: https://github.com/Rimagination/ggmapcn/issues + url: https://rimagination.github.io/ggmapcn/ + url_cran: https://CRAN.R-project.org/package=ggmapcn + url_git: '' +ggmapinset: + version: 0.4.0 + title: Add Inset Panels to Maps + maintainer: Carl Suster + description: |- + Helper to add insets based on geom_sf() from 'ggplot2'. + This package gives you a drop-in replacement for geom_sf() that supports + adding a zoomed inset map without having to create and embed a separate plot. + date_publication: '2024-12-18' + bug_reports: https://github.com/cidm-ph/ggmapinset/issues + url: https://cidm-ph.github.io/ggmapinset/ + url_cran: https://CRAN.R-project.org/package=ggmapinset + url_git: https://github.com/cidm-ph/ggmapinset +ggmatplot: + version: 0.1.2 + title: Plot Columns of Two Matrices Against Each Other Using 'ggplot2' + maintainer: Xuan Liang + description: |- + A quick and easy way of plotting the columns of two matrices or + data frames against each other using 'ggplot2'. Although 'ggmatplot' doesn't + provide the same flexibility as 'ggplot2', it can be used as a workaround for + having to wrangle wide format data into long format for plotting with + 'ggplot2'. + date_publication: '2022-05-17' + bug_reports: https://github.com/xuan-liang/ggmatplot/issues + url: https://xuan-liang.github.io/ggmatplot/ + url_cran: https://CRAN.R-project.org/package=ggmatplot + url_git: https://github.com/xuan-liang/ggmatplot +ggmcmc: + version: 1.5.1.1 + title: Tools for Analyzing MCMC Simulations from Bayesian Inference + maintainer: Xavier Fernández i Marín + description: |- + Tools for assessing and diagnosing convergence of + Markov Chain Monte Carlo simulations, as well as for graphically display + results from full MCMC analysis. The package also facilitates the graphical + interpretation of models by providing flexible functions to plot the + results against observed variables, and functions to work with + hierarchical/multilevel batches of parameters + (Fernández-i-Marín, 2016 ). + date_publication: '2021-02-10' + bug_reports: https://github.com/xfim/ggmcmc/issues/ + url: http://xavier-fim.net/packages/ggmcmc/ + url_cran: https://CRAN.R-project.org/package=ggmcmc + url_git: https://github.com/xfim/ggmcmc/ +ggmice: + version: 0.1.0 + title: Visualizations for 'mice' with 'ggplot2' + maintainer: Hanne Oberman + description: |- + Enhance a 'mice' imputation workflow with visualizations for + incomplete and/or imputed data. The plotting functions produce + 'ggplot' objects which may be easily manipulated or extended. Use + 'ggmice' to inspect missing data, develop imputation models, evaluate + algorithmic convergence, or compare observed versus imputed data. + date_publication: '2023-08-07' + bug_reports: https://github.com/amices/ggmice + url: https://amices.org/ + url_cran: https://CRAN.R-project.org/package=ggmice + url_git: https://github.com/amices/ggmice +ggmix: + version: 0.0.2 + title: Variable Selection in Linear Mixed Models for SNP Data + maintainer: Sahir Bhatnagar + description: |- + Fit penalized multivariable linear mixed models with a single + random effect to control for population structure in genetic association + studies. The goal is to simultaneously fit many genetic variants at the + same time, in order to select markers that are independently associated + with the response. Can also handle prior annotation information, + for example, rare variants, in the form of variable weights. For more + information, see the website below and the accompanying paper: + Bhatnagar et al., "Simultaneous SNP selection and adjustment for + population structure in high dimensional prediction models", 2020, + . + date_publication: '2021-04-13' + bug_reports: https://github.com/sahirbhatnagar/ggmix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggmix + url_git: https://github.com/sahirbhatnagar/ggmix +GGMncv: + version: 2.1.1 + title: Gaussian Graphical Models with Nonconvex Regularization + maintainer: Donald Williams + description: |- + Estimate Gaussian graphical models with nonconvex penalties , + including the atan Wang and Zhu (2016) , + seamless L0 Dicker, Huang, and Lin (2013) , + exponential Wang, Fan, and Zhu , + smooth integration of counting and absolute deviation Lv and Fan (2009) , + logarithm Mazumder, Friedman, and Hastie (2011) , + Lq, smoothly clipped absolute deviation Fan and Li (2001) , + and minimax concave penalty Zhang (2010) . There are also extensions + for computing variable inclusion probabilities, multiple regression coefficients, and + statistical inference . + date_publication: '2021-12-15' + bug_reports: https://github.com/donaldRwilliams/GGMncv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GGMncv + url_git: '' +GGMnonreg: + version: 1.0.0 + title: Non-Regularized Gaussian Graphical Models + maintainer: Donald Williams + description: |- + Estimate non-regularized Gaussian graphical models, Ising models, + and mixed graphical models. The current methods consist of multiple regression, + a non-parametric bootstrap , and Fisher z + transformed partial correlations . Parameter uncertainty, + predictability, and network replicability are also implemented. + date_publication: '2021-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGMnonreg + url_git: '' +ggmosaic: + version: 0.3.3 + title: Mosaic Plots in the 'ggplot2' Framework + maintainer: Haley Jeppson + description: |- + Mosaic plots in the 'ggplot2' framework. Mosaic + plot functionality is provided in a single 'ggplot2' layer by calling + the geom 'mosaic'. + date_publication: '2021-02-23' + bug_reports: https://github.com/haleyjeppson/ggmosaic + url: '' + url_cran: https://CRAN.R-project.org/package=ggmosaic + url_git: https://github.com/haleyjeppson/ggmosaic +ggmr: + version: 0.1.1 + title: Generalized Gauss Markov Regression + maintainer: Hugo Gasca-Aragon + description: Implements the generalized Gauss Markov regression, this is useful + when both predictor and response have uncertainty attached to them and also when + covariance within the predictor, within the response and between the predictor + and the response is present. Base on the results published in guide ISO/TS 28037 + (2010) . + date_publication: '2019-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggmr + url_git: '' +GGMridge: + version: '1.4' + title: |- + Gaussian Graphical Models Using Ridge Penalty Followed by + Thresholding and Reestimation + maintainer: Shannon T. Holloway + description: |- + Estimation of partial correlation matrix using ridge penalty + followed by thresholding and reestimation. Under multivariate Gaussian + assumption, the matrix constitutes an Gaussian graphical model (GGM). + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGMridge + url_git: '' +GGMselect: + version: 0.1-12.7.1 + title: Gaussian Graphs Models Selection + maintainer: Benjamin Auder + description: |- + Graph estimation in Gaussian Graphical Models, following the method + developed by C. Giraud, S. Huet and N. Verzelen (2012) . + The main functions return the adjacency matrix of an undirected graph + estimated from a data matrix. + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGMselect + url_git: '' +ggmugs: + version: 0.6.0 + title: |- + Visualization of Multiple Genome-Wide Association Study Summary + Statistics + maintainer: Wanjun Gu + description: 'A ''grammar of graphics'' approach for visualizing summary statistics + from multiple Genome-wide Association Studies (GWAS). It offers geneticists, bioinformaticians, + and researchers a powerful yet flexible tool for illustrating complex genetic + associations using data from various GWAS datasets. The visualizations can be + extensively customized, facilitating detailed comparative analysis across different + genetic studies. Reference: Uffelmann, E. et al. (2021) .' + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggmugs + url_git: '' +ggmuller: + version: 0.5.6 + title: Create Muller Plots of Evolutionary Dynamics + maintainer: Robert Noble + description: |- + Create plots that combine a phylogeny and frequency dynamics. + Phylogenetic input can be a generic adjacency matrix or a tree of class "phylo". + Inspired by similar plots in publications of the labs of RE Lenski and JE + Barrick. Named for HJ Muller (who popularised such plots) and H Wickham (whose + code this package exploits). + date_publication: '2023-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggmuller + url_git: '' +ggmulti: + version: 1.0.7 + title: High Dimensional Data Visualization + maintainer: Zehao Xu + description: It provides materials (i.e. 'serial axes' objects, Andrew's plot, various + glyphs for scatter plot) to visualize high dimensional data. + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggmulti + url_git: '' +ggnetwork: + version: 0.5.13 + title: Geometries to Plot Networks with 'ggplot2' + maintainer: François Briatte + description: Geometries to plot network objects with 'ggplot2'. + date_publication: '2024-02-14' + bug_reports: https://github.com/briatte/ggnetwork/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggnetwork + url_git: https://github.com/briatte/ggnetwork +ggnewscale: + version: 0.5.1 + title: Multiple Fill and Colour Scales in 'ggplot2' + maintainer: Elio Campitelli + description: Use multiple fill and colour scales in 'ggplot2'. + date_publication: '2025-02-24' + bug_reports: https://github.com/eliocamp/ggnewscale/issues + url: https://eliocamp.github.io/ggnewscale/ + url_cran: https://CRAN.R-project.org/package=ggnewscale + url_git: https://github.com/eliocamp/ggnewscale +ggnormalviolin: + version: 0.1.2 + title: A 'ggplot2' Extension to Make Normal Violin Plots + maintainer: W. Joel Schneider + description: |- + Uses 'ggplot2' to create normally distributed + violin plots with specified means and standard deviations. This + function can be useful in showing hypothetically normal distributions + and confidence intervals. + date_publication: '2019-05-27' + bug_reports: https://github.com/wjschne/ggnormalviolin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggnormalviolin + url_git: https://github.com/wjschne/ggnormalviolin +ggnuplot: + version: 0.1.0 + title: Make 'ggplot2' Look Like 'gnuplot' + maintainer: Hannes Riebl + description: |- + Provides a theme, a discrete color palette, and continuous scales + to make 'ggplot2' look like 'gnuplot'. This may be helpful if you use both + 'ggplot2' and 'gnuplot' in one project. + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggnuplot + url_git: https://github.com/hriebl/ggnuplot +ggOceanMaps: + version: 2.2.0 + title: Plot Data on Oceanographic Maps using 'ggplot2' + maintainer: Mikko Vihtakari + description: |- + Allows plotting data on bathymetric maps using 'ggplot2'. Plotting + oceanographic spatial data is made as simple as feasible, but also flexible + for custom modifications. Data that contain geographic information from + anywhere around the globe can be plotted on maps generated by the basemap() + or qmap() functions using 'ggplot2' layers separated by the '+' operator. The + package uses spatial shape- ('sf') and raster ('stars') files, geospatial + packages for R to manipulate, and the 'ggplot2' package to plot these + files. The package ships with low-resolution spatial data files and + higher resolution files for detailed maps are stored in the + 'ggOceanMapsLargeData' repository on GitHub and downloaded automatically + when needed. + date_publication: '2024-01-15' + bug_reports: https://github.com/MikkoVihtakari/ggOceanMaps/issues + url: https://mikkovihtakari.github.io/ggOceanMaps/ + url_cran: https://CRAN.R-project.org/package=ggOceanMaps + url_git: '' +ggokabeito: + version: 0.1.0 + title: '''Okabe-Ito'' Scales for ''ggplot2'' and ''ggraph''' + maintainer: Malcolm Barrett + description: |- + Discrete scales for the colorblind-friendly 'Okabe-Ito' + palette, including 'color', 'fill', and 'edge_colour'. 'ggokabeito' + provides 'ggplot2' and 'ggraph' scales to easily use the 'Okabe-Ito' + palette in your data visualizations. + date_publication: '2021-10-18' + bug_reports: https://github.com/malcolmbarrett/ggokabeito/issues + url: https://malcolmbarrett.github.io/ggokabeito/ + url_cran: https://CRAN.R-project.org/package=ggokabeito + url_git: https://github.com/malcolmbarrett/ggokabeito +ggordiplots: + version: 0.4.3 + title: Make 'ggplot2' Versions of Vegan's Ordiplots + maintainer: John Quensen + description: |- + The 'vegan' package includes several functions for adding features + to ordination plots: ordiarrows(), ordiellipse(), ordihull(), + ordispider() and ordisurf(). This package adds these same features to + ordination plots made with 'ggplot2'. In addition, gg_ordibubble() sizes + points relative to the value of an environmental variable. + date_publication: '2024-01-14' + bug_reports: https://github.com/jfq3/ggordiplots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggordiplots + url_git: https://github.com/jfq3/ggordiplots +GGoutlieR: + version: 1.0.2 + title: Identify Individuals with Unusual Geo-Genetic Patterns + maintainer: Che-Wei Chang + description: Identify and visualize individuals with unusual association patterns + of genetics and geography using the approach of Chang and Schmid (2023) . + It detects potential outliers that violate the isolation-by-distance assumption + using the K-nearest neighbor approach. You can obtain a table of outliers with + statistics and visualize unusual geo-genetic patterns on a geographical map. This + is useful for landscape genomics studies to discover individuals with unusual + geography and genetics associations from a large biological sample. + date_publication: '2023-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGoutlieR + url_git: '' +ggpackets: + version: 0.2.1 + title: Package Plot Layers for Easier Portability and Modularization + maintainer: Doug Kelkhoff + description: |2- + + Create groups of 'ggplot2' layers that can be easily migrated from one plot + to another, reducing redundant code and improving the ability to format many + plots that draw from the same source 'ggpacket' layers. + date_publication: '2022-10-10' + bug_reports: https://github.com/dgkf/ggpackets/issues + url: https://dgkf.github.io/ggpackets/ + url_cran: https://CRAN.R-project.org/package=ggpackets + url_git: https://github.com/dgkf/ggpackets +ggpage: + version: 0.2.3 + title: Creates Page Layout Visualizations + maintainer: Emil Hvitfeldt + description: |- + Facilitates the creation of page layout + visualizations in which words are represented as rectangles with sizes + relating to the length of the words. Which then is divided in lines + and pages for easy overview of up to quite large texts. + date_publication: '2019-06-13' + bug_reports: https://github.com/EmilHvitfeldt/ggpage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggpage + url_git: https://github.com/EmilHvitfeldt/ggpage +ggparallel: + version: 0.4.0 + title: Variations of Parallel Coordinate Plots for Categorical Data + maintainer: Heike Hofmann + description: |- + Create hammock plots, parallel sets, and common angle plots + with 'ggplot2'. + date_publication: '2024-03-09' + bug_reports: https://github.com/heike/ggparallel/issues/ + url: https://heike.github.io/ggparallel/ + url_cran: https://CRAN.R-project.org/package=ggparallel + url_git: https://github.com/heike/ggparallel/ +ggparty: + version: 1.0.0 + title: '''ggplot'' Visualizations for the ''partykit'' Package' + maintainer: Martin Borkovec + description: Extends 'ggplot2' functionality to the 'partykit' package. 'ggparty' + provides the necessary tools to create clearly structured and highly customizable + visualizations for tree-objects of the class 'party'. + date_publication: '2019-07-18' + bug_reports: https://github.com/martin-borkovec/ggparty/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggparty + url_git: https://github.com/martin-borkovec/ggparty +ggpath: + version: 1.0.2 + title: Robust Image Rendering Support for 'ggplot2' + maintainer: Sebastian Carl + description: |- + A 'ggplot2' extension that enables robust image grobs in + panels and theme elements. + date_publication: '2024-08-20' + bug_reports: https://github.com/mrcaseb/ggpath/issues + url: https://mrcaseb.github.io/ggpath/ + url_cran: https://CRAN.R-project.org/package=ggpath + url_git: https://github.com/mrcaseb/ggpath +ggpattern: + version: 1.1.4 + title: '''ggplot2'' Pattern Geoms' + maintainer: Trevor L. Davis + description: Provides 'ggplot2' geoms filled with various patterns. Includes a + patterned version of every 'ggplot2' geom that has a region that can be filled + with a pattern. Provides a suite of 'ggplot2' aesthetics and scales for controlling + pattern appearances. Supports over a dozen builtin patterns (every pattern implemented + by 'gridpattern') as well as allowing custom user-defined patterns. + date_publication: '2025-01-29' + bug_reports: https://github.com/trevorld/ggpattern/issues + url: https://trevorldavis.com/R/ggpattern/ + url_cran: https://CRAN.R-project.org/package=ggpattern + url_git: https://github.com/trevorld/ggpattern +ggpca: + version: 0.1.3 + title: Publication-Ready PCA, t-SNE, and UMAP Plots + maintainer: Yaoxiang Li + description: Provides tools for creating publication-ready dimensionality reduction + plots, including Principal Component Analysis (PCA), t-Distributed Stochastic + Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection + (UMAP). This package helps visualize high-dimensional data with options for custom + labels, density plots, and faceting, using the 'ggplot2' framework Wickham (2016) + . + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggpca + url_git: '' +ggpcp: + version: 0.2.0 + title: Parallel Coordinate Plots in the 'ggplot2' Framework + maintainer: Heike Hofmann + description: |- + Modern Parallel Coordinate Plots have been introduced in the 1980s as + a way to visualize arbitrarily many numeric variables. This Grammar of Graphics implementation + also incorporates categorical variables into the plots in a principled manner. + By separating the data managing part from the visual rendering, we give full access + to the users while keeping the number of parameters manageably low. + date_publication: '2022-11-28' + bug_reports: https://github.com/heike/ggpcp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggpcp + url_git: https://github.com/heike/ggpcp +ggperiodic: + version: 1.0.3 + title: Easy Plotting of Periodic Data with 'ggplot2' + maintainer: Elio Campitelli + description: Implements methods to plot periodic data in any arbitrary range on + the fly. + date_publication: '2023-03-22' + bug_reports: https://github.com/eliocamp/ggperiodic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggperiodic + url_git: https://github.com/eliocamp/ggperiodic +ggpie: + version: 0.2.5 + title: Pie, Donut and Rose Pie Plots + maintainer: Yabing Song + description: Create pie, donut and rose pie plot with 'ggplot2'. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggpie + url_git: https://github.com/showteeth/ggpie +ggplate: + version: 0.1.5 + title: Create Layout Plots of Biological Culture Plates and Microplates + maintainer: Jan-Philipp Quast + description: Enables users to create simple plots of biological culture plates as + well as microplates. Both continuous and discrete values can be plotted onto the + plate layout. + date_publication: '2024-10-01' + bug_reports: https://github.com/jpquast/ggplate/issues + url: https://jpquast.github.io/ggplate/ + url_cran: https://CRAN.R-project.org/package=ggplate + url_git: https://github.com/jpquast/ggplate +ggplot.multistats: + version: 1.0.1 + title: Multiple Summary Statistics for Binned Stats/Geometries + maintainer: Philipp Angerer + description: |- + Provides the ggplot binning layer stat_summaries_hex(), + which functions similar to its singular form, + but allows the use of multiple statistics per bin. + Those statistics can be mapped to multiple bin aesthetics. + date_publication: '2024-09-25' + bug_reports: https://github.com/flying-sheep/ggplot.multistats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggplot.multistats + url_git: https://github.com/flying-sheep/ggplot.multistats +ggplot2: + version: 3.5.1 + title: Create Elegant Data Visualisations Using the Grammar of Graphics + maintainer: Thomas Lin Pedersen + description: |- + A system for 'declaratively' creating graphics, based on "The + Grammar of Graphics". You provide the data, tell 'ggplot2' how to map + variables to aesthetics, what graphical primitives to use, and it + takes care of the details. + date_publication: '2024-04-23' + bug_reports: https://github.com/tidyverse/ggplot2/issues + url: https://ggplot2.tidyverse.org + url_cran: https://CRAN.R-project.org/package=ggplot2 + url_git: https://github.com/tidyverse/ggplot2 +ggplot2.utils: + version: 0.3.2 + title: Selected Utilities Extending 'ggplot2' + maintainer: Daniel Sabanés Bové + description: |- + Selected utilities, in particular 'geoms' and 'stats' + functions, extending the 'ggplot2' package. This package imports + functions from 'EnvStats' by Millard + (2013), 'ggpp' by Aphalo et + al. (2023) and 'ggstats' by Larmarange + (2023), and then exports them. This package also contains modified + code from 'ggquickeda' + by Mouksassi et al. (2023) for Kaplan-Meier lines and ticks additions + to plots. All functions are tested to make sure that they work + reliably. + date_publication: '2024-06-25' + bug_reports: https://github.com/insightsengineering/ggplot2.utils/issues + url: https://insightsengineering.github.io/ggplot2.utils/ + url_cran: https://CRAN.R-project.org/package=ggplot2.utils + url_git: '' +ggplot2movies: + version: 0.0.1 + title: Movies Data + maintainer: Hadley Wickham + description: |- + A dataset about movies. This was previously contained in ggplot2, + but has been moved its own package to reduce the download size of ggplot2. + date_publication: '2015-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggplot2movies + url_git: '' +ggplotAssist: + version: 0.1.3 + title: '''RStudio'' Addin for Teaching and Learning ''ggplot2''' + maintainer: Keon-Woong Moon + description: |- + An 'RStudio' addin for teaching and learning making plot using the 'ggplot2' package. + You can learn each steps of making plot by clicking your mouse without coding. + You can get resultant code for the plot. + date_publication: '2017-11-12' + bug_reports: https://github.com/cardiomoon/ggplotAssist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggplotAssist + url_git: https://github.com/cardiomoon/ggplotAssist +ggplotgui: + version: 1.0.0 + title: Create Ggplots via a Graphical User Interface + maintainer: Gert Stulp + description: Easily explore data by creating ggplots through a (shiny-)GUI. R-code + to recreate graph provided. + date_publication: '2017-07-08' + bug_reports: https://github.com/gertstulp/ggplotgui/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggplotgui + url_git: https://github.com/gertstulp/ggplotgui/ +ggplotify: + version: 0.1.2 + title: Convert Plot to 'grob' or 'ggplot' Object + maintainer: Guangchuang Yu + description: Convert plot function call (using expression or formula) to 'grob' + or 'ggplot' object that compatible to the 'grid' and 'ggplot2' ecosystem. With + this package, we are able to e.g. using 'cowplot' to align plots produced by 'base' + graphics, 'ComplexHeatmap', 'eulerr', 'grid', 'lattice', 'magick', 'pheatmap', + 'vcd' etc. by converting them to 'ggplot' objects. + date_publication: '2023-08-09' + bug_reports: https://github.com/GuangchuangYu/ggplotify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggplotify + url_git: https://github.com/GuangchuangYu/ggplotify +ggplotlyExtra: + version: 0.0.1 + title: Extra Convenience Functions for 'Plotly' + maintainer: Omar I. Elashkar + description: Convenience functions for smooth conversion from 'ggplot' to 'plotly' + where the conversion using ggplotly() usually gives an unexpected labels. The + package ease the process of making a 'plotly' figures generated from 'ggplot2' + object more aesthetic in terms of labels and customizability. + date_publication: '2019-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggplotlyExtra + url_git: '' +ggpmisc: + version: 0.6.1 + title: Miscellaneous Extensions to 'ggplot2' + maintainer: Pedro J. Aphalo + description: |- + Extensions to 'ggplot2' respecting the grammar of graphics + paradigm. Statistics: locate and tag peaks and valleys; label plot with the + equation of a fitted polynomial or other types of models; labels + with P-value, R^2 or adjusted R^2 or information criteria for fitted models; + label with ANOVA table for fitted models; label with summary for fitted + models. Model fit classes for which suitable methods are provided by package + 'broom' and 'broom.mixed' are supported. Scales and stats to build volcano + and quadrant plots based on outcomes, fold changes, p-values and false + discovery rates. + date_publication: '2024-11-14' + bug_reports: https://github.com/aphalo/ggpmisc/issues + url: https://docs.r4photobiology.info/ggpmisc/ + url_cran: https://CRAN.R-project.org/package=ggpmisc + url_git: https://github.com/aphalo/ggpmisc +ggPMX: + version: 1.2.11 + title: |- + 'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME + Models + maintainer: Matthew Fidler + description: |- + At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling + activities in order to reduce the overall effort required for generating such plots. + For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox, + called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient + for publication and submissions using few lines of code. This package focuses on plots recommended by ISoP + . While not required, you can get/install the 'R' 'lixoftConnectors' + package in the 'Monolix' installation, as described at the following url + . + When 'lixoftConnectors' is available, 'R' can use 'Monolix' directly to create the required + Chart Data instead of exporting it from the 'Monolix' gui. + date_publication: '2023-11-30' + bug_reports: https://github.com/ggPMXdevelopment/ggPMX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggPMX + url_git: https://github.com/ggPMXdevelopment/ggPMX +ggpointdensity: + version: 0.1.0 + title: A Cross Between a 2D Density Plot and a Scatter Plot + maintainer: Lukas P. M. Kremer + description: |- + A cross between a 2D density plot and a scatter plot, + implemented as a 'ggplot2' geom. Points in the scatter plot are + colored by the number of neighboring points. This is useful to + visualize the 2D-distribution of points in case of overplotting. + date_publication: '2019-08-28' + bug_reports: https://github.com/LKremer/ggpointdensity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggpointdensity + url_git: https://github.com/LKremer/ggpointdensity +ggpointless: + version: 0.1.0 + title: Additional Geometries and Stats for 'ggplot2' + maintainer: Markus Döring + description: |- + An (aspirational) collection of additional geometries and + statistics for 'ggplot2'. + date_publication: '2024-02-09' + bug_reports: https://github.com/flrd/ggpointless/issues + url: https://flrd.github.io/ggpointless/ + url_cran: https://CRAN.R-project.org/package=ggpointless + url_git: https://github.com/flrd/ggpointless +ggpol: + version: 0.0.7 + title: Visualizing Social Science Data with 'ggplot2' + maintainer: Frederik Tiedemann + description: A 'ggplot2' extension for implementing parliament charts and several + other useful visualizations. + date_publication: '2020-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggpol + url_git: https://github.com/erocoar/ggpol +ggpolar: + version: 0.2.2 + title: Dots and Their Connections in Polar Coordinate System + maintainer: Shixiang Wang + description: |- + Provides basic graphing functions to fully demonstrate + point-to-point connections in a polar coordinate space. + date_publication: '2022-10-10' + bug_reports: https://github.com/ShixiangWang/polar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggpolar + url_git: https://github.com/ShixiangWang/polar +ggpolypath: + version: 0.3.0 + title: Polygons with Holes for the Grammar of Graphics + maintainer: Michael D. Sumner + description: |- + Tools for working with polygons with holes in 'ggplot2', with a + new 'geom' for drawing a 'polypath' applying the 'evenodd' or 'winding' + rules. + date_publication: '2023-09-25' + bug_reports: https://github.com/mdsumner/ggpolypath/issues/ + url: https://mdsumner.github.io/ggpolypath/ + url_cran: https://CRAN.R-project.org/package=ggpolypath + url_git: '' +ggpp: + version: 0.5.8-1 + title: Grammar Extensions to 'ggplot2' + maintainer: Pedro J. Aphalo + description: |- + Extensions to 'ggplot2' respecting the grammar of graphics + paradigm. Geometries: geom_table(), geom_plot() and geom_grob() add insets to + plots using native data coordinates, while geom_table_npc(), geom_plot_npc() + and geom_grob_npc() do the same using "npc" coordinates through new + aesthetics "npcx" and "npcy". Statistics: select observations based on 2D + density. Positions: radial nudging away from a center point and nudging away + from a line or curve; combined stacking and nudging; combined dodging and + nudging. + date_publication: '2024-07-01' + bug_reports: https://github.com/aphalo/ggpp/issues + url: https://docs.r4photobiology.info/ggpp/ + url_cran: https://CRAN.R-project.org/package=ggpp + url_git: https://github.com/aphalo/ggpp +ggprism: + version: 1.0.5 + title: A 'ggplot2' Extension Inspired by 'GraphPad Prism' + maintainer: Charlotte Dawson + description: |- + Provides various themes, palettes, and other functions + that are used to customise ggplots to look like they were made in 'GraphPad + Prism'. The 'Prism'-look is achieved with theme_prism() and + scale_fill|colour_prism(), axes can be changed with custom guides like + guide_prism_minor(), and significance indicators added with add_pvalue(). + date_publication: '2024-03-21' + bug_reports: https://github.com/csdaw/ggprism/issues + url: https://csdaw.github.io/ggprism/ + url_cran: https://CRAN.R-project.org/package=ggprism + url_git: https://github.com/csdaw/ggprism +ggpubr: + version: 0.6.0 + title: '''ggplot2'' Based Publication Ready Plots' + maintainer: Alboukadel Kassambara + description: |- + The 'ggplot2' package is excellent and flexible for elegant data + visualization in R. However the default generated plots requires some formatting + before we can send them for publication. Furthermore, to customize a 'ggplot', + the syntax is opaque and this raises the level of difficulty for researchers + with no advanced R programming skills. 'ggpubr' provides some easy-to-use + functions for creating and customizing 'ggplot2'- based publication ready plots. + date_publication: '2023-02-10' + bug_reports: https://github.com/kassambara/ggpubr/issues + url: https://rpkgs.datanovia.com/ggpubr/ + url_cran: https://CRAN.R-project.org/package=ggpubr + url_git: '' +ggpval: + version: 0.2.5 + title: Annotate Statistical Tests for 'ggplot2' + maintainer: Jun Cheng + description: |- + Automatically performs desired statistical tests (e.g. wilcox.test(), t.test()) to compare between groups, + and adds the resulting p-values to the plot with an annotation bar. + Visualizing group differences are frequently performed by boxplots, bar plots, etc. + Statistical test results are often needed to be annotated on these plots. + This package provides a convenient function that works on 'ggplot2' objects, + performs the desired statistical test between groups of interest and annotates the test results on the plot. + date_publication: '2022-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggpval + url_git: https://github.com/s6juncheng/ggpval +ggQC: + version: 0.0.31 + title: Quality Control Charts for 'ggplot' + maintainer: Kenith Grey + description: |- + Plot single and faceted type quality control charts + for 'ggplot'. + date_publication: '2018-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggQC + url_git: '' +ggQQunif: + version: 0.1.5 + title: Compare Big Datasets to the Uniform Distribution + maintainer: Robert Corty + description: |- + A quantile-quantile plot can be used to compare a sample of p-values + to the uniform distribution. But when the dataset is big (i.e. > 1e4 p-values), + plotting the quantile-quantile plot can be slow. geom_QQ uses all the data to + calculate the quantiles, but thins it out in a way that focuses on points near zero + before plotting to speed up plotting and decrease file size, when vector graphics are stored. + date_publication: '2018-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggQQunif + url_git: '' +ggquickeda: + version: 0.3.1 + title: |- + Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary + Tables + maintainer: Samer Mouksassi + description: |- + Quickly and easily perform exploratory data analysis by uploading your + data as a 'csv' file. Start generating insights using 'ggplot2' plots and + 'table1' tables with descriptive stats, all using an easy-to-use point and click + 'Shiny' interface. + date_publication: '2024-01-15' + bug_reports: https://github.com/smouksassi/ggquickeda/issues + url: https://smouksassi.github.io/ggquickeda/ + url_cran: https://CRAN.R-project.org/package=ggquickeda + url_git: https://github.com/smouksassi/ggquickeda +ggquiver: + version: 0.3.3 + title: Quiver Plots for 'ggplot2' + maintainer: Mitchell O'Hara-Wild + description: |- + An extension of 'ggplot2' to provide quiver plots to visualise vector fields. + This functionality is implemented using a geom to produce a new graphical layer, which + allows aesthetic options. This layer can be overlaid on a map to improve visualisation + of mapped data. + date_publication: '2023-11-17' + bug_reports: https://github.com/mitchelloharawild/ggquiver/issues + url: https://pkg.mitchelloharawild.com/ggquiver/ + url_cran: https://CRAN.R-project.org/package=ggquiver + url_git: https://github.com/mitchelloharawild/ggquiver +ggragged: + version: 0.2.0 + title: Ragged Grids for 'ggplot2' + maintainer: Mikko Marttila + description: |- + Extend 'ggplot2' facets to panel layouts arranged in a grid + with ragged edges. facet_ragged_rows() groups panels into rows that + can vary in length, facet_ragged_cols() does the same but for columns. + These can be useful, for example, to represent nested or partially + crossed relationships between faceting variables. + date_publication: '2024-10-09' + bug_reports: https://github.com/mikmart/ggragged/issues + url: https://mikmart.github.io/ggragged/ + url_cran: https://CRAN.R-project.org/package=ggragged + url_git: https://github.com/mikmart/ggragged +ggrain: + version: 0.0.4 + title: A Rainclouds Geom for 'ggplot2' + maintainer: Nicholas Judd + description: The 'geom_rain()' function adds different geoms together using 'ggplot2' + to create raincloud plots. + date_publication: '2024-01-23' + bug_reports: https://github.com/njudd/ggrain/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggrain + url_git: https://github.com/njudd/ggrain +ggRandomForests: + version: 2.2.1 + title: Visually Exploring Random Forests + maintainer: John Ehrlinger + description: |- + Graphic elements for exploring Random Forests using the 'randomForest' or + 'randomForestSRC' package for survival, regression and classification forests and + 'ggplot2' package plotting. + date_publication: '2022-09-01' + bug_reports: https://github.com/ehrlinger/ggRandomForests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggRandomForests + url_git: https://github.com/ehrlinger/ggRandomForests +ggraph: + version: 2.2.1 + title: An Implementation of Grammar of Graphics for Graphs and Networks + maintainer: Thomas Lin Pedersen + description: |- + The grammar of graphics as implemented in ggplot2 is a poor fit for + graph and network visualizations due to its reliance on tabular data input. + ggraph is an extension of the ggplot2 API tailored to graph visualizations + and provides the same flexible approach to building up plots layer by layer. + date_publication: '2024-03-07' + bug_reports: https://github.com/thomasp85/ggraph/issues + url: https://ggraph.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=ggraph + url_git: https://github.com/thomasp85/ggraph +ggraptR: + version: '1.3' + title: |- + Allows Interactive Visualization of Data Through a Web Browser + GUI + maintainer: Eugene Dubossarsky + description: |- + Intended for both technical and non-technical users to create + interactive data visualizations through a web browser GUI without writing any + code. + date_publication: '2020-06-24' + bug_reports: https://github.com/cargomoose/raptR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggraptR + url_git: '' +ggrasp: + version: '1.2' + title: |- + Gaussian-Based Genome Representative Selector with + Prioritization + maintainer: Thomas Clarke + description: 'Given a group of genomes and their relationship with each other, the + package clusters the genomes and selects the most representative members of each + cluster. Additional data can be provided to the prioritize certain genomes. The + results can be printed out as a list or a new phylogeny with graphs of the trees + and distance distributions also available. For detailed introduction see: Thomas + H Clarke, Lauren M Brinkac, Granger Sutton, and Derrick E Fouts (2018), GGRaSP: + a R-package for selecting representative genomes using Gaussian mixture models, + Bioinformatics, bty300, .' + date_publication: '2022-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggrasp + url_git: '' +ggrastr: + version: 1.0.2 + title: Rasterize Layers for 'ggplot2' + maintainer: Evan Biederstedt + description: Rasterize only specific layers of a 'ggplot2' plot while simultaneously + keeping all labels and text in vector format. This allows users to keep plots + within the reasonable size limit without loosing vector properties of the scale-sensitive + information. + date_publication: '2023-06-01' + bug_reports: https://github.com/VPetukhov/ggrastr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggrastr + url_git: https://github.com/VPetukhov/ggrastr +ggrcs: + version: 0.4.3 + title: Draw Histograms and Restricted Cubic Splines (RCS) + maintainer: Qiang LIU + description: |- + You can use this function to easily draw a combined histogram and restricted cubic spline. + The function draws the graph through 'ggplot2'. RCS fitting requires the use of the rcs() function of the 'rms' package. + Can fit cox regression, logistic regression. This method was described by Per Kragh (2003) . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggrcs + url_git: '' +ggredist: + version: 0.0.2 + title: |- + Scales, Geometries, and Extensions of 'ggplot2' for Election + Mapping + maintainer: Christopher T. Kenny + description: |- + Provides 'ggplot2' extensions for political map making. Implements + new geometries for groups of simple feature geometries. Adds palettes and scales + for red to blue color mapping and for discrete maps. Implements tools for easy + label generation and placement, automatic map coloring, and themes. + date_publication: '2022-11-23' + bug_reports: https://github.com/alarm-redist/ggredist/issues + url: https://alarm-redist.org/ggredist/ + url_cran: https://CRAN.R-project.org/package=ggredist + url_git: https://github.com/alarm-redist/ggredist +ggrepel: + version: 0.9.6 + title: |- + Automatically Position Non-Overlapping Text Labels with + 'ggplot2' + maintainer: Kamil Slowikowski + description: |- + Provides text and label geoms for 'ggplot2' that help to avoid + overlapping text labels. Labels repel away from each other and away from the + data points. + date_publication: '2024-09-07' + bug_reports: https://github.com/slowkow/ggrepel/issues + url: https://ggrepel.slowkow.com/ + url_cran: https://CRAN.R-project.org/package=ggrepel + url_git: https://github.com/slowkow/ggrepel +ggResidpanel: + version: 0.3.0 + title: |- + Panels and Interactive Versions of Diagnostic Plots using + 'ggplot2' + maintainer: Katherine Goode + description: |- + An R package for creating panels of diagnostic plots for residuals from a model + using ggplot2 and plotly to analyze residuals and model assumptions from a variety of + viewpoints. It also allows for the creation of interactive diagnostic plots. + date_publication: '2019-05-31' + bug_reports: '' + url: https://goodekat.github.io/ggResidpanel/ + url_cran: https://CRAN.R-project.org/package=ggResidpanel + url_git: '' +ggreveal: + version: 0.1.4 + title: Reveal a 'ggplot' Incrementally + maintainer: Weverthon Machado + description: Provides functions that make it easy to reveal 'ggplot2' graphs incrementally. + The functions take a plot produced with 'ggplot2' and return a list of plots showing + data incrementally by panels, layers, groups, the values in an axis or any arbitrary + aesthetic. + date_publication: '2024-11-10' + bug_reports: https://github.com/weverthonmachado/ggreveal/issues + url: http://www.weverthon.com/ggreveal/ + url_cran: https://CRAN.R-project.org/package=ggreveal + url_git: https://github.com/weverthonmachado/ggreveal +GGRidge: + version: 1.1.0 + title: Graphical Group Ridge + maintainer: Saeed Aldahmani + description: The Graphical Group Ridge 'GGRidge' package package classifies ridge + regression predictors in disjoint groups of conditionally correlated variables + and derives different penalties (shrinkage parameters) for these groups of predictors. + It combines the ridge regression method with the graphical model for high-dimensional + data (i.e. the number of predictors exceeds the number of cases) or ill-conditioned + data (e.g. in the presence of multicollinearity among predictors). The package + reduces the mean square errors and the extent of over-shrinking of predictors + as compared to the ridge method.Aldahmani, S. and Zoubeidi, T. (2020) . + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGRidge + url_git: '' +ggridges: + version: 0.5.6 + title: Ridgeline Plots in 'ggplot2' + maintainer: Claus O. Wilke + description: Ridgeline plots provide a convenient way of visualizing changes in + distributions over time or space. This package enables the creation of such plots + in 'ggplot2'. + date_publication: '2024-01-23' + bug_reports: https://github.com/wilkelab/ggridges/issues + url: https://wilkelab.org/ggridges/ + url_cran: https://CRAN.R-project.org/package=ggridges + url_git: '' +ggrisk: + version: '1.3' + title: Risk Score Plot for Cox Regression + maintainer: Jing Zhang + description: |- + The risk plot may be one of the most commonly used figures in + tumor genetic data analysis. We can conclude the following two points: + Comparing the prediction results of the model with the real survival situation + to see whether the survival rate of the high-risk group is lower than that of the + low-level group, and whether the survival time of the high-risk group is + shorter than that of the low-risk group. The other is to compare the heat + map and scatter plot to see the correlation between the predictors and the + outcome. + date_publication: '2021-08-09' + bug_reports: https://github.com/yikeshu0611/ggrisk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggrisk + url_git: https://github.com/yikeshu0611/ggrisk +ggrounded: + version: 0.0.3 + title: Rounded Bar Plots + maintainer: Botan Ağın + description: |- + Creates bar plots with rounded corners using 'ggplot2'. + The code in this package was adapted from a solution provided by + Stack Overflow user 'sthoch' in the following post + . + date_publication: '2023-05-11' + bug_reports: https://github.com/botan/ggrounded/issues + url: https://botan.github.io/ggrounded/ + url_cran: https://CRAN.R-project.org/package=ggrounded + url_git: https://github.com/botan/ggrounded +ggroups: + version: 2.1.2 + title: Pedigree and Genetic Groups + maintainer: Mohammad Ali Nilforooshan + description: Calculates additive and dominance genetic relationship matrices and + their inverses, in matrix and tabular-sparse formats. It includes functions for + checking and processing pedigree, calculating inbreeding coefficients (Meuwissen + & Luo, 1992 ), as well as functions to calculate + the matrix of genetic group contributions (Q), and adding those contributions + to the genetic merit of animals (Quaas (1988) ). + Calculation of Q is computationally extensive. There are computationally optimized + functions to calculate Q. + date_publication: '2022-03-27' + bug_reports: https://github.com/nilforooshan/ggroups/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggroups + url_git: https://github.com/nilforooshan/ggroups +ggRtsy: + version: 0.1.0 + title: Add Some Van Gogh Colors and Overlay Colors on Your 'ggplot()' + maintainer: Katelyn Diaz + description: |- + Works with 'ggplot2' to add a Van Gogh color palette to the user’s repertoire. + It also has a function that work alongside 'ggplot2' to create more interesting data visualizations and add contextual information to the user’s plots. + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggRtsy + url_git: '' +ggsankeyfier: + version: 0.1.8 + title: Create Sankey and Alluvial Diagrams Using 'ggplot2' + maintainer: Pepijn de Vries + description: |- + Sankey and alluvial diagrams visualise flows of quantities across + stages in stacked bars. This package makes it easy to create such + diagrams using 'ggplot2'. + date_publication: '2024-04-08' + bug_reports: https://github.com/pepijn-devries/ggsankeyfier/issues + url: https://pepijn-devries.github.io/ggsankeyfier/ + url_cran: https://CRAN.R-project.org/package=ggsankeyfier + url_git: https://github.com/pepijn-devries/ggsankeyfier/ +ggScatRidges: + version: 0.1.1 + title: Scatter Plot Combined with Ridgelines in 'ggplot2' + maintainer: Matthieu Bourgery + description: The function combines a scatter plot with ridgelines to better visualise + the distribution between sample groups. The plot is created with 'ggplot2'. + date_publication: '2024-03-25' + bug_reports: https://github.com/matbou85/ggScatRidges/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggScatRidges + url_git: https://github.com/matbou85/ggScatRidges +ggsci: + version: 3.2.0 + title: |- + Scientific Journal and Sci-Fi Themed Color Palettes for + 'ggplot2' + maintainer: Nan Xiao + description: |- + A collection of 'ggplot2' color palettes inspired by + plots in scientific journals, data visualization libraries, + science fiction movies, and TV shows. + date_publication: '2024-06-18' + bug_reports: https://github.com/nanxstats/ggsci/issues + url: https://nanx.me/ggsci/ + url_cran: https://CRAN.R-project.org/package=ggsci + url_git: https://github.com/nanxstats/ggsci +ggscidca: + version: 0.2.3 + title: Plotting Decision Curve Analysis with Coloured Bars + maintainer: Qiang Liu + description: Decision curve analysis is a method for evaluating and comparing prediction + models that incorporates clinical consequences, requires only the data set on + which the models are tested, and can be applied to models that have either continuous + or dichotomous results. The 'ggscidca' package adds coloured bars of discriminant + relevance to the traditional decision curve. Improved practicality and aesthetics. + This method was described by Balachandran VP (2015) . + date_publication: '2024-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggscidca + url_git: '' +ggseas: + version: 0.5.4 + title: '''stats'' for Seasonal Adjustment on the Fly with ''ggplot2''' + maintainer: Peter Ellis + description: |- + Provides 'ggplot2' 'stats' that estimate seasonally adjusted series + and rolling summaries such as rolling average on the fly for time series. + date_publication: '2018-06-12' + bug_reports: https://github.com/ellisp/ggseas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggseas + url_git: '' +ggsector: + version: 1.7.0 + title: Draw Sectors + maintainer: Pengdong Yan + description: Some useful functions that can use 'grid' and 'ggplot2' to plot sectors + and interact with 'Seurat' to plot gene expression percentages. Also, there are + some examples of how to draw sectors in 'ComplexHeatmap'. + date_publication: '2024-10-31' + bug_reports: https://github.com/yanpd01/ggsector/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggsector + url_git: '' +ggseg: + version: 1.6.5 + title: Plotting Tool for Brain Atlases + maintainer: Athanasia Mo Mowinckel + description: |- + Contains 'ggplot2' geom for plotting brain atlases using + simple features. The largest component of the package is the data + for the two built-in atlases. Mowinckel & Vidal-Piñeiro (2020) + . + date_publication: '2022-06-13' + bug_reports: https://github.com/ggseg/ggseg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggseg + url_git: https://github.com/ggseg/ggseg +ggseg3d: + version: 1.6.3 + title: Tri-Surface Mesh Plots for Brain Atlases + maintainer: Athanasia Mo Mowinckel + description: |- + Mainly contains a plotting function ggseg3d(), + and data of two standard brain atlases (Desikan-Killiany and aseg). + By far, the largest bit of the package is the data for each of the atlases. + The functions and data enable users to plot tri-surface mesh plots of + brain atlases, and customise these by projecting colours onto the brain + segments based on values in their own data sets. Functions are wrappers + for 'plotly'. Mowinckel & Vidal-Piñeiro (2020) + . + date_publication: '2021-06-01' + bug_reports: https://github.com/ggseg/ggseg3d/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=ggseg3d + url_git: https://github.com/ggseg/ggseg3d/ +ggsem: + version: 0.2.4 + title: Interactively Visualize Structural Equation Modeling Diagrams + maintainer: Seung Hyun Min + description: It is an R package and web-based application, allowing users to perform + interactive and reproducible visualizations of path diagrams for structural equation + modeling (SEM) and networks using the 'ggplot2' engine. Its app (built with 'shiny') + provides an interface that allows extensive customization, and creates CSV outputs, + which can then be used to recreate the figures either using the web app or script-based + workflow. + date_publication: '2025-02-02' + bug_reports: https://github.com/smin95/ggsem/issues/ + url: https://smin95.github.io/ggsem/ + url_cran: https://CRAN.R-project.org/package=ggsem + url_git: '' +ggseqlogo: + version: '0.2' + title: |- + A 'ggplot2' Extension for Drawing Publication-Ready Sequence + Logos + maintainer: Omar Wagih + description: The extensive range of functions provided by this package makes it + possible to draw highly versatile sequence logos. Features include, but not limited + to, modifying colour schemes and fonts used to draw the logo, generating multiple + logo plots, and aiding the visualisation with annotations. Sequence logos can + easily be combined with other plots 'ggplot2' plots. + date_publication: '2024-02-09' + bug_reports: https://github.com/omarwagih/ggseqlogo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggseqlogo + url_git: https://github.com/omarwagih/ggseqlogo +ggseqplot: + version: 0.8.5 + title: Render Sequence Plots using 'ggplot2' + maintainer: Marcel Raab + description: |- + A set of wrapper functions that mainly re-produces most of the + sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base + R to produce the plots this library draws on 'ggplot2'. + The plots are produced on the basis of a sequence object defined + with TraMineR::seqdef(). The package automates the reshaping and plotting + of sequence data. Resulting plots are of class 'ggplot', i.e. components + can be added and tweaked using '+' and regular 'ggplot2' functions. + date_publication: '2024-10-29' + bug_reports: https://github.com/maraab23/ggseqplot/issues + url: https://maraab23.github.io/ggseqplot/ + url_cran: https://CRAN.R-project.org/package=ggseqplot + url_git: https://github.com/maraab23/ggseqplot +ggshadow: + version: 0.0.5 + title: Shadow and Glow Geoms for 'ggplot2' + maintainer: Marc Menem + description: |- + A collection of Geoms for R's 'ggplot2' library. geom_shadowpath(), geom_shadowline(), + geom_shadowstep() and geom_shadowpoint() functions draw a shadow below lines to make busy plots more + aesthetically pleasing. geom_glowpath(), geom_glowline(), geom_glowstep() and geom_glowpoint() add a + neon glow around lines to get a steampunk style. + date_publication: '2022-11-20' + bug_reports: https://github.com/marcmenem/ggshadow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggshadow + url_git: https://github.com/marcmenem/ggshadow/ +ggside: + version: 0.3.1 + title: Side Grammar Graphics + maintainer: Justin Landis + description: |- + The grammar of graphics as shown in 'ggplot2' has provided + an expressive API for users to build plots. 'ggside' extends 'ggplot2' + by allowing users to add graphical information about one of the main panel's + axis using a familiar 'ggplot2' style API with tidy data. This package is + particularly useful for visualizing metadata on a discrete axis, or summary + graphics on a continuous axis such as a boxplot or a density distribution. + date_publication: '2024-03-01' + bug_reports: https://github.com/jtlandis/ggside/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggside + url_git: https://github.com/jtlandis/ggside +ggsignif: + version: 0.6.4 + title: Significance Brackets for 'ggplot2' + maintainer: Constantin Ahlmann-Eltze + description: |- + Enrich your 'ggplots' with group-wise comparisons. + This package provides an easy way to indicate if two groups are + significantly different. Commonly this is shown by a bracket on top + connecting the groups of interest which itself is annotated with the + level of significance (NS, *, **, ***). The package provides a single + layer (geom_signif()) that takes the groups for comparison and the + test (t.test(), wilcox.text() etc.) as arguments and adds the + annotation to the plot. + date_publication: '2022-10-13' + bug_reports: '' + url: https://const-ae.github.io/ggsignif/ + url_cran: https://CRAN.R-project.org/package=ggsignif + url_git: https://github.com/const-ae/ggsignif +ggsmc: + version: 0.1.2.0 + title: |- + Visualising Output from Sequential Monte Carlo Samplers and + Ensemble-Based Methods + maintainer: Richard G Everitt + description: Functions for plotting, and animating, the output of importance samplers, + sequential Monte Carlo samplers (SMC) and ensemble-based methods. The package + can be used to plot and animate histograms, densities, scatter plots and time + series, and to plot the genealogy of an SMC or ensemble-based algorithm. These + functions all rely on algorithm output to be supplied in tidy format. A function + is provided to transform algorithm output from matrix format (one Monte Carlo + point per row) to the tidy format required by the plotting and animating functions. + date_publication: '2024-07-27' + bug_reports: https://github.com/richardgeveritt/ggsmc/issues + url: https://richardgeveritt.github.io/ggsmc/ + url_cran: https://CRAN.R-project.org/package=ggsmc + url_git: https://github.com/richardgeveritt/ggsmc +ggsoccer: + version: 0.2.0 + title: Plot Soccer Event Data + maintainer: Ben Torvaney + description: |- + The 'ggplot2' package provides a powerful set of tools + for visualising and investigating data. The 'ggsoccer' package provides a + set of functions for elegantly displaying and exploring soccer event data + with 'ggplot2'. Providing extensible layers and themes, it is designed to + work smoothly with a variety of popular sports data providers. + date_publication: '2024-10-06' + bug_reports: https://github.com/Torvaney/ggsoccer/issues + url: https://torvaney.github.io/ggsoccer/ + url_cran: https://CRAN.R-project.org/package=ggsoccer + url_git: https://github.com/Torvaney/ggsoccer +ggsolvencyii: + version: 0.1.2 + title: 'A ''ggplot2''-Plot of Composition of Solvency II SCR: SF and IM' + maintainer: Marco van Zanden + description: |- + An implementation of 'ggplot2'-methods to present the composition of Solvency II Solvency Capital Requirement (SCR) as a series of concentric circle-parts. + Solvency II (Solvency 2) is European insurance legislation, coming in force by the delegated acts of October 10, 2014. + . + Additional files, defining the structure of the Standard Formula (SF) method of the SCR-calculation are provided. + The structure files can be adopted for localization or for insurance companies who use Internal Models (IM). + Options are available for combining smaller components, horizontal and vertical scaling, rotation, and plotting only some circle-parts. + With outlines and connectors several SCR-compositions can be compared, for example in ORSA-scenarios (Own Risk and Solvency Assessment). + date_publication: '2019-01-04' + bug_reports: https://github.com/vanzanden/ggsolvencyii/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggsolvencyii + url_git: https://github.com/vanzanden/ggsolvencyii +ggsom: + version: 0.4.0 + title: New Data Visualisations for SOMs Networks + maintainer: Felipe Carvalho + description: The aim of this package is to offer more variability of graphics based + on the self-organizing maps. + date_publication: '2020-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggsom + url_git: https://github.com/oldlipe/ggsom +ggspark: + version: 0.0.2 + title: '''ggplot2'' Functions to Create Tufte Style Sparklines' + maintainer: Marc Bosch Matas + description: Functions to help with creating sparklines in the style of Edward Tufte + + in 'ggplot2'. It computes ribbon geoms with the interquartile ranges and points + and/or labels at the beginning, end, max, and min points. + date_publication: '2024-05-13' + bug_reports: https://github.com/marcboschmatas/ggspark/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggspark + url_git: https://github.com/marcboschmatas/ggspark +ggspatial: + version: 1.1.9 + title: Spatial Data Framework for ggplot2 + maintainer: Dewey Dunnington + description: |- + Spatial data plus the power of the ggplot2 framework means easier mapping when input + data are already in the form of spatial objects. + date_publication: '2023-08-17' + bug_reports: https://github.com/paleolimbot/ggspatial/issues + url: https://paleolimbot.github.io/ggspatial/ + url_cran: https://CRAN.R-project.org/package=ggspatial + url_git: https://github.com/paleolimbot/ggspatial +ggspectra: + version: 0.3.15 + title: Extensions to 'ggplot2' for Radiation Spectra + maintainer: Pedro J. Aphalo + description: |- + Additional annotations, stats, geoms and scales for plotting + "light" spectra with 'ggplot2', together with specializations of ggplot() + and autoplot() methods for spectral data and waveband definitions + stored in objects of classes defined in package 'photobiology'. Part of the + 'r4photobiology' suite, Aphalo P. J. (2015) . + date_publication: '2025-01-08' + bug_reports: https://github.com/aphalo/ggspectra/issues/ + url: https://docs.r4photobiology.info/ggspectra/ + url_cran: https://CRAN.R-project.org/package=ggspectra + url_git: https://github.com/aphalo/ggspectra/ +ggstackplot: + version: 0.4.1 + title: Create Overlapping Stacked Plots + maintainer: Sebastian Kopf + description: |- + Easily create overlapping grammar of graphics plots for scientific data visualization. + This style of plotting is particularly common in climatology and oceanography research communities. + date_publication: '2025-01-31' + bug_reports: https://github.com/kopflab/ggstackplot/issues + url: https://ggstackplot.kopflab.org/ + url_cran: https://CRAN.R-project.org/package=ggstackplot + url_git: https://github.com/kopflab/ggstackplot +ggstance: + version: 0.3.7 + title: Horizontal 'ggplot2' Components + maintainer: Lionel Henry + description: |- + A 'ggplot2' extension that provides flipped components: + horizontal versions of 'Stats' and 'Geoms', and vertical versions + of 'Positions'. This package is now superseded by 'ggplot2' itself + which now has full native support for horizontal layouts. It + remains available for backward compatibility. + date_publication: '2024-04-05' + bug_reports: https://github.com/lionel-/ggstance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggstance + url_git: https://github.com/lionel-/ggstance +ggstar: + version: 1.0.4 + title: Multiple Geometric Shape Point Layer for 'ggplot2' + maintainer: Shuangbin Xu + description: |- + To create the multiple polygonal point layer for easily discernible shapes, + we developed the package, it is like the 'geom_point' of 'ggplot2'. + It can be used to draw the scatter plot. + date_publication: '2022-11-08' + bug_reports: https://github.com/xiangpin/ggstar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggstar + url_git: https://github.com/xiangpin/ggstar/ +ggstats: + version: 0.8.0 + title: Extension to 'ggplot2' for Plotting Stats + maintainer: Joseph Larmarange + description: |- + Provides new statistics, new geometries and new positions for + 'ggplot2' and a suite of functions to facilitate the creation of + statistical plots. + date_publication: '2025-01-07' + bug_reports: https://github.com/larmarange/ggstats/issues + url: https://larmarange.github.io/ggstats/ + url_cran: https://CRAN.R-project.org/package=ggstats + url_git: https://github.com/larmarange/ggstats +ggstatsplot: + version: 0.13.0 + title: '''ggplot2'' Based Plots with Statistical Details' + maintainer: Indrajeet Patil + description: |- + Extension of 'ggplot2', 'ggstatsplot' creates graphics with + details from statistical tests included in the plots themselves. It + provides an easier syntax to generate information-rich plots for + statistical analysis of continuous (violin plots, scatterplots, + histograms, dot plots, dot-and-whisker plots) or categorical (pie and + bar charts) data. Currently, it supports the most common types of + statistical approaches and tests: parametric, nonparametric, robust, + and Bayesian versions of t-test/ANOVA, correlation analyses, + contingency table analysis, meta-analysis, and regression analyses. + References: Patil (2021) . + date_publication: '2024-12-04' + bug_reports: https://github.com/IndrajeetPatil/ggstatsplot/issues + url: https://indrajeetpatil.github.io/ggstatsplot/ + url_cran: https://CRAN.R-project.org/package=ggstatsplot + url_git: https://github.com/IndrajeetPatil/ggstatsplot +ggstream: + version: 0.1.0 + title: Create Streamplots in 'ggplot2' + maintainer: David Sjoberg + description: Make smoothed stacked area charts in 'ggplot2'. Stream plots are useful + to show magnitude trends over time. + date_publication: '2021-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggstream + url_git: '' +ggstudent: + version: 0.1.1-1 + title: Continuous Confidence Interval Plots using t-Distribution + maintainer: Jouni Helske + description: |- + Provides an extension to 'ggplot2' (Wickham, 2016, ) for creating two + types of continuous confidence interval plots (Violin CI and Gradient CI plots), typically for the sample mean. + These plots contain multiple user-defined confidence areas with varying colours, + defined by the underlying t-distribution used to compute standard confidence intervals for + the mean of the normal distribution when the variance is unknown. + Two types of plots are available, a gradient plot with rectangular areas, and a violin plot where the + shape (horizontal width) is defined by the probability density function of the t-distribution. + date_publication: '2020-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggstudent + url_git: '' +ggsurveillance: + version: 0.1.2 + title: Tools for Outbreak Investigation/Infectious Disease Surveillance + maintainer: Alexander Bartel + description: |- + Create epicurves or epigantt charts in 'ggplot2'. Prepare + data for visualisation or other reporting for infectious disease + surveillance and outbreak investigation. Includes tidy functions to solve + date based transformations for common reporting tasks, like + (A) seasonal date alignment for respiratory disease surveillance, + (B) date-based case binning based on specified time intervals like + isoweek, epiweek, month and more, (C) automated detection and marking + of the new year based on the date/datetime axis of the 'ggplot2'. + An introduction on how to use epicurves can be found on the US CDC website + (2012, ). + date_publication: '2025-02-11' + bug_reports: https://github.com/biostats-dev/ggsurveillance/issues + url: https://ggsurveillance.biostats.dev + url_cran: https://CRAN.R-project.org/package=ggsurveillance + url_git: https://github.com/biostats-dev/ggsurveillance +ggsurvey: + version: 1.0.0 + title: Simplifying 'ggplot2' for Survey Data + maintainer: Brittany Alexander + description: Functions for survey data including svydesign objects from the 'survey' + package that call 'ggplot2' to make bar charts, histograms, boxplots, and hexplots + of survey data. + date_publication: '2022-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggsurvey + url_git: '' +ggsurvfit: + version: 1.1.0 + title: Flexible Time-to-Event Figures + maintainer: Daniel D. Sjoberg + description: |- + Ease the creation of time-to-event (i.e. survival) endpoint + figures. The modular functions create figures ready for publication. + Each of the functions that add to or modify the figure are written as + proper 'ggplot2' geoms or stat methods, allowing the functions from + this package to be combined with any function or customization from + 'ggplot2' and other 'ggplot2' extension packages. + date_publication: '2024-05-08' + bug_reports: https://github.com/pharmaverse/ggsurvfit/issues + url: https://www.danieldsjoberg.com/ggsurvfit/ + url_cran: https://CRAN.R-project.org/package=ggsurvfit + url_git: https://github.com/pharmaverse/ggsurvfit +ggswissmaps: + version: 0.1.1 + title: Offers Various Swiss Maps as Data Frames and 'ggplot2' Objects + maintainer: Sandro Petrillo Burri + description: |- + Offers various swiss maps as data frames and 'ggplot2' objects and gives the + possibility to add layers of data on the maps. Data are publicly available + from the swiss federal statistical office. + date_publication: '2016-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggswissmaps + url_git: https://github.com/gibonet/ggswissmaps +ggtangle: + version: 0.0.6 + title: Draw Network with Data + maintainer: Guangchuang Yu + description: Extends the 'ggplot2' plotting system to support network visualization. + Inspired by the 'Method 1' in 'ggtree' (G Yu (2018) ), + 'ggtangle' is designed to work with network associated data. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggtangle + url_git: '' +ggtaxplot: + version: 0.0.1 + title: Create Plots to Visualize Taxonomy + maintainer: Clement Coclet + description: Provides a comprehensive suite of functions for processing and visualizing + taxonomic data. It includes functionality to clean and transform taxonomic data, + categorize it into hierarchical ranks (such as Phylum, Class, Order, Family, and + Genus), and calculate the relative abundance of each category. The package also + generates a color palette for visual representation of the taxonomic data, allowing + users to easily identify and differentiate between various taxonomic groups. Additionally, + it features a river plot visualization to effectively display the distribution + of individuals across different taxonomic ranks, facilitating insights into taxonomic + visualization. + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggtaxplot + url_git: '' +ggtea: + version: 0.1.1 + title: Palettes and Themes for 'ggplot2' + maintainer: Pushkar Sarkar + description: A collection of palettes and themes for 'ggplot2', offering a light, + pastel aesthetic. Syntax follows the 'viridis' package. + date_publication: '2021-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggtea + url_git: '' +ggtern: + version: 3.5.0 + title: An Extension to 'ggplot2', for the Creation of Ternary Diagrams + maintainer: Nicholas Hamilton + description: |- + Extends the functionality of 'ggplot2', providing the capability + to plot ternary diagrams for (subset of) the 'ggplot2' geometries. Additionally, + 'ggtern' has implemented several NEW geometries which are unavailable to the + standard 'ggplot2' release. For further examples and documentation, please + proceed to the 'ggtern' website. + date_publication: '2024-03-24' + bug_reports: '' + url: http://www.ggtern.com + url_cran: https://CRAN.R-project.org/package=ggtern + url_git: '' +ggtext: + version: 0.1.2 + title: Improved Text Rendering Support for 'ggplot2' + maintainer: Brenton M. Wiernik + description: |- + A 'ggplot2' extension that enables the rendering of + complex formatted plot labels (titles, subtitles, facet labels, + axis labels, etc.). Text boxes with automatic word wrap are also + supported. + date_publication: '2022-09-16' + bug_reports: https://github.com/wilkelab/ggtext/issues + url: https://wilkelab.org/ggtext/ + url_cran: https://CRAN.R-project.org/package=ggtext + url_git: '' +ggThemeAssist: + version: 0.1.5 + title: Add-in to Customize 'ggplot2' Themes + maintainer: Calli Gross + description: Rstudio add-in that delivers a graphical interface for editing 'ggplot2' + theme elements. + date_publication: '2016-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggThemeAssist + url_git: https://github.com/calligross/ggthemeassist +ggthemes: + version: 5.1.0 + title: Extra Themes, Scales and Geoms for 'ggplot2' + maintainer: Jeffrey B. Arnold + description: |- + Some extra themes, geoms, and scales for 'ggplot2'. + Provides 'ggplot2' themes and scales that replicate the look of plots + by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', + 'Excel', and 'The Wall Street Journal', among others. + Provides 'geoms' for Tufte's box plot and range frame. + date_publication: '2024-02-10' + bug_reports: https://github.com/jrnold/ggthemes/issues + url: https://jrnold.github.io/ggthemes/ + url_cran: https://CRAN.R-project.org/package=ggthemes + url_git: https://github.com/jrnold/ggthemes +ggthemeUL: + version: 0.1.3 + title: A 'ggplot' Theme for University of Ljubljana + maintainer: Marjan Cugmas + description: Designed to customize 'ggplot' graphics according to the institutional + identity of the University of Ljubljana. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggthemeUL + url_git: '' +ggtibble: + version: 1.0.1 + title: Create Tibbles and Lists of 'ggplot' Figures for Reporting + maintainer: Bill Denney + description: |- + Create tibbles and lists of 'ggplot' figures that can be modified as easily as + regular 'ggplot' figures. Typical use cases are for creating reports or web + pages where many figures are needed with different data and similar + formatting. + date_publication: '2024-06-19' + bug_reports: '' + url: https://billdenney.github.io/ggtibble/ + url_cran: https://CRAN.R-project.org/package=ggtibble + url_git: '' +ggtikz: + version: 0.1.3 + title: |- + Post-Process 'ggplot2' Plots with 'TikZ' Code Using Plot + Coordinates + maintainer: Oliver Thomas + description: Annotation of 'ggplot2' plots with arbitrary 'TikZ' code, using absolute + data or relative plot coordinates. + date_publication: '2024-06-16' + bug_reports: https://github.com/osthomas/ggtikz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggtikz + url_git: https://github.com/osthomas/ggtikz +ggTimeSeries: + version: 1.0.2 + title: Time Series Visualisations Using the Grammar of Graphics + maintainer: Aditya Kothari + description: Provides additional display mediums for time series visualisations. + date_publication: '2022-01-23' + bug_reports: https://github.com/thecomeonman/ggTimeSeries/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggTimeSeries + url_git: https://github.com/thecomeonman/ggTimeSeries +ggtrace: + version: 0.2.0 + title: Trace and Highlight Groups of Data Points + maintainer: Ryan Sheridan + description: |- + Provides 'ggplot2' geoms that allow groups of data points to be + outlined or highlighted for emphasis. This is particularly useful when + working with dense datasets that are prone to overplotting. + date_publication: '2022-06-24' + bug_reports: https://github.com/rnabioco/ggtrace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggtrace + url_git: https://github.com/rnabioco/ggtrace +ggtrendline: + version: 1.0.3 + title: Add Trendline and Confidence Interval to 'ggplot' + maintainer: Weiping Mei + description: |- + Add trendline and confidence interval of linear or nonlinear regression model and + show equation to 'ggplot' as simple as possible. For a general overview of the methods used in + this package, see Ritz and Streibig (2008) and + Greenwell and Schubert Kabban (2014) . + date_publication: '2022-04-27' + bug_reports: https://github.com/PhDMeiwp/ggtrendline/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggtrendline + url_git: https://github.com/PhDMeiwp/ggtrendline +ggtricks: + version: 0.1.0 + title: Create Sector and Other Charts Easily Using Grammar of Graphics + maintainer: Abdoul ISSA BIDA + description: |- + A collection of several geoms to create graphics, using + 'ggplot2' and the Cartesian coordinate system. You use the familiar + mapping 'Grammar of Graphics' without the need to do another + transformation into polar coordinates. + date_publication: '2023-05-10' + bug_reports: https://github.com/AbdoulMa/ggtricks/issues + url: https://abdoulma.github.io/ggtricks/ + url_cran: https://CRAN.R-project.org/package=ggtricks + url_git: https://github.com/AbdoulMa/ggtricks +GGUM: + version: '0.5' + title: Generalized Graded Unfolding Model + maintainer: Jorge N. Tendeiro + description: An implementation of the generalized graded unfolding model (GGUM) + in R, see Roberts, Donoghue, and Laughlin (2000) ). + It allows to simulate data sets based on the GGUM. It fits the GGUM and the GUM, + and it retrieves item and person parameter estimates. Several plotting functions + are available (item and test information functions; item and test characteristic + curves; item category response curves). Additionally, there are some functions + that facilitate the communication between R and 'GGUM2004'. Finally, a model-fit + checking utility, MODFIT(), is also available. + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GGUM + url_git: https://github.com/jorgetendeiro/GGUM/ +ggupset: + version: 0.4.1 + title: Combination Matrix Axis for 'ggplot2' to Create 'UpSet' Plots + maintainer: Constantin Ahlmann-Eltze + description: |- + Replace the standard x-axis in 'ggplots' with a combination matrix + to visualize complex set overlaps. 'UpSet' has introduced a new way to visualize + the overlap of sets as an alternative to Venn diagrams. + This package provides a simple way to produce such plots using 'ggplot2'. + In addition it can convert any categorical axis into a combination + matrix axis. + date_publication: '2025-02-11' + bug_reports: https://github.com/const-ae/ggupset/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggupset + url_git: https://github.com/const-ae/ggupset +ggvenn: + version: 0.1.10 + title: Draw Venn Diagram by 'ggplot2' + maintainer: Linlin Yan + description: An easy-to-use way to draw pretty venn diagram by 'ggplot2'. + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggvenn + url_git: '' +ggVennDiagram: + version: 1.5.2 + title: A 'ggplot2' Implement of Venn Diagram + maintainer: Chun-Hui Gao + description: |- + Easy-to-use functions to generate 2-7 sets Venn or upset plot in publication quality. + 'ggVennDiagram' plot Venn or upset using well-defined geometry dataset and 'ggplot2'. The shapes of 2-4 sets + Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which + are developed and imported from another package 'venn', authored by Adrian Dusa. We provided internal functions to + integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections + of them, then separately plot Venn in four components, set edges/labels, and region edges/labels. + From version 1.0, it is possible to customize these components as you demand in ordinary 'ggplot2' grammar. + From version 1.4.4, it supports unlimited number of sets, as it can draw a plain upset plot automatically when + number of sets is more than 7. + date_publication: '2024-02-20' + bug_reports: '' + url: https://gaospecial.github.io/ggVennDiagram/ + url_cran: https://CRAN.R-project.org/package=ggVennDiagram + url_git: https://github.com/gaospecial/ggVennDiagram +ggversa: + version: 0.0.1 + title: Graficas Versatiles Con 'ggplot2' + maintainer: Raymond L. Tremblay + description: 'A collection of datasets for the upcoming book "Graficas versatiles + con ggplot: Analisis visuales de datos", by Raymond L. Tremblay and Julian Hernandez-Serano.' + date_publication: '2017-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggversa + url_git: '' +ggview: + version: 0.2.1 + title: '''ggplot2'' Picture Previewer' + maintainer: Iaroslav Domin + description: |- + Preview what a 'ggplot2' plot would look like if you save it to a file. + Attach picture dimensions as a canvas() element and get an instant preview. + These dimensions will then be used when you save the plot. + date_publication: '2024-10-02' + bug_reports: https://github.com/idmn/ggview/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ggview + url_git: https://github.com/idmn/ggview +ggvis: + version: 0.4.9 + title: Interactive Grammar of Graphics + maintainer: Hadley Wickham + description: |- + An implementation of an interactive grammar of graphics, + taking the best parts of 'ggplot2', combining them with the reactive + framework of 'shiny' and drawing web graphics using 'vega'. + date_publication: '2024-02-05' + bug_reports: '' + url: https://ggvis.rstudio.com/ + url_cran: https://CRAN.R-project.org/package=ggvis + url_git: '' +ggvolcano: + version: 0.1.4 + title: Publication-Ready Volcano Plots + maintainer: Yaoxiang Li + description: Provides publication-ready volcano plots for visualizing differential + expression results, commonly used in RNA-seq and similar analyses. This tool helps + create high-quality visual representations of data using the 'ggplot2' framework + Wickham (2016) . + date_publication: '2025-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggvolcano + url_git: '' +ggwordcloud: + version: 0.6.2 + title: A Word Cloud Geom for 'ggplot2' + maintainer: Erwan Le Pennec + description: |- + Provides a word cloud text geom for 'ggplot2'. Texts + are placed so that they do not overlap as in 'ggrepel'. The algorithm + used is a variation around the one of 'wordcloud2.js'. + date_publication: '2024-05-30' + bug_reports: https://github.com/lepennec/ggwordcloud/issues + url: https://lepennec.github.io/ggwordcloud/ + url_cran: https://CRAN.R-project.org/package=ggwordcloud + url_git: https://github.com/lepennec/ggwordcloud +ggx: + version: 0.1.1 + title: A Natural Language Interface to 'ggplot2' + maintainer: Andreas M. Brandmaier + description: 'The ''ggplot2'' package is the state-of-the-art toolbox for creating + and formatting graphs. However, it is easy to forget how certain formatting commands + are named and sometimes users find themselves asking: How do you rotate the x-axis + labels again? Or how do you hide the legend...? This package allows users to issue + natural language commands related to theme-related styling of plots (colors, font + size and such), which then are translated into valid ''ggplot2'' commands.' + date_publication: '2021-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ggx + url_git: '' +gh: + version: 1.4.1 + title: '''GitHub'' ''API''' + maintainer: Gábor Csárdi + description: Minimal client to access the 'GitHub' 'API'. + date_publication: '2024-03-28' + bug_reports: https://github.com/r-lib/gh/issues + url: https://gh.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=gh + url_git: https://github.com/r-lib/gh#readme +GHap: + version: 3.0.0 + title: Genome-Wide Haplotyping + maintainer: Yuri Tani Utsunomiya + description: Haplotype calling from phased marker data. Given user-defined haplotype + blocks (HapBlock), the package identifies the different haplotype alleles (HapAllele) + present in the data and scores sample haplotype allele genotypes (HapGenotype) + based on HapAllele dose (i.e. 0, 1 or 2 copies). The output is not only useful + for analyses that can handle multi-allelic markers, but is also conveniently formatted + for existing pipelines intended for bi-allelic markers. The package was first + described in Bioinformatics by Utsunomiya et al. (2016, ). + Since the v2 release, the package provides functions for unsupervised and supervised + detection of ancestry tracks. The methods implemented in these functions were + described in an article published in Methods in Ecology and Evolution by Utsunomiya + et al. (2020, ). The source code for v3 was modified + for improved performance and inclusion of new functionality, including analysis + of unphased data, runs of homozygosity, sampling methods for virtual gamete mating, + mixed model fitting and GWAS. + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GHap + url_git: '' +ghapps: + version: 1.1.1 + title: Authenticate as a 'GitHub' App + maintainer: Jeroen Ooms + description: |- + 'GitHub' apps provide a powerful way to manage fine grained + programmatic access to specific 'git' repositories, without having to + create dummy users, and which are safer than a personal access token + for automated tasks. This package extends the 'gh' package to let you + authenticate and interact with 'GitHub' + in 'R' as an app. + date_publication: '2024-10-04' + bug_reports: https://github.com/r-lib/ghapps/issues + url: https://r-lib.r-universe.dev/ghapps + url_cran: https://CRAN.R-project.org/package=ghapps + url_git: '' +Ghat: + version: 0.2.0 + title: Quantifying Evolution and Selection on Complex Traits + maintainer: Tim Beissinger + description: |- + Functions are provided for quantifying evolution and selection on complex traits. + The package implements effective handling and analysis algorithms scaled for + genome-wide data and calculates a composite statistic, denoted Ghat, which is used + to test for selection on a trait. The package provides a number of simple examples + for handling and analysing the genome data and visualising the output and results. + Beissinger et al., (2018) . + date_publication: '2022-12-14' + bug_reports: https://github.com/Medhat86/Ghat/issues + url: https://academic.oup.com/genetics/article/209/1/321/5931021 + url_cran: https://CRAN.R-project.org/package=Ghat + url_git: '' +ghclass: + version: 0.3.0 + title: Tools for Managing Classes on GitHub + maintainer: Colin Rundel + description: |- + Interface for the GitHub API that enables efficient + management of courses on GitHub. It has a functionality for + managing organizations, teams, repositories, and users on GitHub + and helps automate most of the tedious and repetitive tasks + around creating and distributing assignments. + date_publication: '2024-03-26' + bug_reports: https://github.com/rundel/ghclass/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ghclass + url_git: https://github.com/rundel/ghclass +ghcm: + version: 3.0.1 + title: Functional Conditional Independence Testing with the GHCM + maintainer: Anton Rask Lundborg + description: |- + A statistical hypothesis test for conditional independence. + Given residuals from a sufficiently powerful regression, it tests whether + the covariance of the residuals is vanishing. It can be applied to both + discretely-observed functional data and multivariate data. + Details of the method can be found in Anton Rask Lundborg, Rajen D. Shah and Jonas + Peters (2022) . + date_publication: '2023-11-02' + bug_reports: https://github.com/arlundborg/ghcm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ghcm + url_git: https://github.com/arlundborg/ghcm +GHCNr: + version: 1.4.5 + title: Download Weather Station Data from GHCNd + maintainer: Emilio Berti + description: The goal of 'GHCNr' is to provide a fast and friendly interface with + the Global Historical Climatology Network daily (GHCNd) database, which contains + daily summaries of weather station data worldwide (). + GHCNd is accessed through the web API . + 'GHCNr' main functionalities consist of downloading data from GHCNd, filter it, + and to aggregate it at monthly and annual scales. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GHCNr + url_git: '' +ghibli: + version: 0.3.4 + title: Studio Ghibli Colour Palettes + maintainer: Ewen Henderson + description: |- + Colour palettes inspired by Studio Ghibli + films, ported to R for your enjoyment. + date_publication: '2024-03-18' + bug_reports: https://github.com/ewenme/ghibli/issues + url: https://ewenme.github.io/ghibli/ + url_cran: https://CRAN.R-project.org/package=ghibli + url_git: '' +Ghost: + version: 0.1.0 + title: Missing Data Segments Imputation in Multivariate Streams + maintainer: Siyavash Shabani + description: Helper functions provide an accurate imputation algorithm for reconstructing + the missing segment in a multi-variate data streams. Inspired by single-shot learning, + it reconstructs the missing segment by identifying the first similar segment in + the stream. Nevertheless, there should be one column of data available, i.e. a + constraint column. The values of columns can be characters (A, B, C, etc.). The + result of the imputed dataset will be returned a .csv file. For more details see + Reza Rawassizadeh (2019) . + date_publication: '2020-03-25' + bug_reports: '' + url: https://www.researchgate.net/publication/332779980_Ghost_Imputation_Accurately_Reconstructing_Missing_Data_of_the_Off_Period + url_cran: https://CRAN.R-project.org/package=Ghost + url_git: '' +GhostKnockoff: + version: 0.1.0 + title: The Knockoff Inference Using Summary Statistics + maintainer: Zihuai He + description: Functions for multiple knockoff inference using summary statistics, + e.g. Z-scores. The knockoff inference is a general procedure for controlling the + false discovery rate (FDR) when performing variable selection. This package provides + a procedure which performs knockoff inference without ever constructing individual + knockoffs (GhostKnockoff). It additionally supports multiple knockoff inference + for improved stability and reproducibility. Moreover, it supports meta-analysis + of multiple overlapping studies. + date_publication: '2021-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GhostKnockoff + url_git: '' +ghql: + version: 0.1.0 + title: General Purpose 'GraphQL' Client + maintainer: Scott Chamberlain + description: |- + A 'GraphQL' client, with an R6 interface for initializing + a connection to a 'GraphQL' instance, and methods for constructing + queries, including fragments and parameterized queries. Queries + are checked with the 'libgraphqlparser' C++ parser via the + 'gaphql' package. + date_publication: '2020-03-04' + bug_reports: https://github.com/ropensci/ghql/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ghql + url_git: https://github.com/ropensci/ghql(devel)https://docs.ropensci.org/ghql(docs) +GHS: + version: '0.1' + title: |- + Graphical Horseshoe MCMC Sampler Using Data Augmented Block + Gibbs Sampler + maintainer: Ashutosh Srivastava + description: Draw posterior samples to estimate the precision matrix for multivariate + Gaussian data. Posterior means of the samples is the graphical horseshoe estimate + by Li, Bhadra and Craig(2017) . The function uses matrix decomposition + and variable change from the Bayesian graphical lasso by Wang(2012) , + and the variable augmentation for sampling under the horseshoe prior by Makalic + and Schmidt(2016) . Structure of the graphical horseshoe function + was inspired by the Bayesian graphical lasso function using blocked sampling, + authored by Wang(2012) . + date_publication: '2018-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GHS + url_git: '' +ghyp: + version: 1.6.5 + title: Generalized Hyperbolic Distribution and Its Special Cases + maintainer: Marc Weibel + description: |- + Detailed functionality for working + with the univariate and multivariate Generalized Hyperbolic + distribution and its special cases (Hyperbolic (hyp), Normal + Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t + and Gaussian distribution). Especially, it contains fitting + procedures, an AIC-based model selection routine, and functions + for the computation of density, quantile, probability, random + variates, expected shortfall and some portfolio optimization + and plotting routines as well as the likelihood ratio test. In + addition, it contains the Generalized Inverse Gaussian + distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts. + Quantitative risk management: Concepts, techniques and tools. + Princeton University Press, Princeton (2005). + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ghyp + url_git: '' +ghypernet: + version: 1.1.0 + title: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs + maintainer: Giona Casiraghi + description: |- + Provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG). + To learn how to use it, check the vignettes for a quick tutorial. + Please reference its use as Casiraghi, G., Nanumyan, V. (2019) + together with those relevant references from the one listed below. + The package is based on the research developed at the Chair of Systems Design, ETH Zurich. + Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) . + Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) . + Casiraghi, G., (2017) + Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) + Casiraghi, G. (2019) . + Casiraghi, G., Nanumyan, V. (2021) . + Casiraghi, G. (2021) . + date_publication: '2021-10-15' + bug_reports: '' + url: https://ghyper.net + url_cran: https://CRAN.R-project.org/package=ghypernet + url_git: '' +giacR: + version: 1.0.1 + title: Interface to the Computer Algebra System 'Giac' + maintainer: Stéphane Laurent + description: |- + 'Giac' + + is a general purpose symbolic algebra software. It powers the + graphical interface 'Xcas'. This package allows to execute 'Giac' + commands in 'R'. + date_publication: '2024-04-28' + bug_reports: https://github.com/stla/giacR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=giacR + url_git: https://github.com/stla/giacR +GiANT: + version: 1.3.4 + title: Gene Set Uncertainty in Enrichment Analysis + maintainer: Hans A. Kestler + description: Toolbox for various enrichment analysis methods and quantification + of uncertainty of gene sets, Schmid et al. (2016) . + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GiANT + url_git: '' +gibasa: + version: 1.1.2 + title: An Alternative 'Rcpp' Wrapper of 'MeCab' + maintainer: Akiru Kato + description: |- + A plain 'Rcpp' wrapper for 'MeCab' that can segment Chinese, + Japanese, and Korean text into tokens. The main goal of this package + is to provide an alternative to 'tidytext' using morphological + analysis. + date_publication: '2025-02-16' + bug_reports: https://github.com/paithiov909/gibasa/issues + url: https://paithiov909.github.io/gibasa/ + url_cran: https://CRAN.R-project.org/package=gibasa + url_git: '' +gibble: + version: 0.4.0 + title: Geometry Decomposition + maintainer: Michael Sumner + description: |- + Build a map of path-based geometry, this is a simple description of the number + of parts in an object and their basic structure. Translation and restructuring operations for + planar shapes and other hierarchical types require a data model with a record of the underlying + relationships between elements. The gibble() function creates a geometry map, a simple record of + the underlying structure in path-based hierarchical types. There are methods for the planar shape + types in the 'sf' and 'sp' packages and for types in the 'trip' and 'silicate' packages. + date_publication: '2020-05-09' + bug_reports: https://github.com/mdsumner/gibble/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gibble + url_git: https://github.com/mdsumner/gibble +GIC: + version: 1.0.0 + title: A General Iterative Clustering Algorithm + maintainer: Ziqiang Lin + description: An iterative algorithm that improves the proximity matrix (PM) from + a random forest (RF) and the resulting clusters as measured by the silhouette + score. + date_publication: '2021-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GIC + url_git: '' +gie: + version: 0.1.2 + title: |- + API Wrapper for the Natural Gas Transparency Platforms of Gas + Infrastructure Europe + maintainer: Yannik Buhl + description: |- + Providing access to the API for Gas Infrastructure Europe's + natural gas transparency platforms and . Lets the user + easily download metadata on companies and gas storage units covered by + the API as well as the respective data on regional, country, company + or facility level. + date_publication: '2024-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gie + url_git: '' +gif: + version: 0.1.1 + title: Graphical Independence Filtering + maintainer: Shiyun Lin + description: Provides a method of recovering the precision matrix for Gaussian graphical + models efficiently. Our approach could be divided into three categories. First + of all, we use Hard Graphical Thresholding for best subset selection problem of + Gaussian graphical model, and the core concept of this method was proposed by + Luo et al. (2014) . Secondly, a closed form solution for graphical + lasso under acyclic graph structure is implemented in our package (Fattahi and + Sojoudi (2019) ). Furthermore, we implement + block coordinate descent algorithm to efficiently solve the covariance selection + problem (Dempster (1972) ). Our package is computationally + efficient and can solve ultra-high-dimensional problems, e.g. p > 10,000, in a + few minutes. + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gif + url_git: '' +Gifi: + version: 0.4-0 + title: Multivariate Analysis with Optimal Scaling + maintainer: Patrick Mair + description: Implements categorical principal component analysis ('PRINCALS'), multiple + correspondence analysis ('HOMALS'), monotone regression analysis ('MORALS'). It + replaces the 'homals' package. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Gifi + url_git: https://r-forge.r-project.org/projects/psychor/ +gifski: + version: 1.32.0-1 + title: Highest Quality GIF Encoder + maintainer: Jeroen Ooms + description: |- + Multi-threaded GIF encoder written in Rust: . + Converts images to GIF animations using pngquant's efficient cross-frame + palettes and temporal dithering with thousands of colors per frame. + date_publication: '2024-10-13' + bug_reports: https://github.com/r-rust/gifski/issues + url: https://r-rust.r-universe.dev/gifski + url_cran: https://CRAN.R-project.org/package=gifski + url_git: '' +GIFT: + version: 1.3.3 + title: Access to the Global Inventory of Floras and Traits (GIFT) + maintainer: Pierre Denelle + description: |- + Retrieving regional plant checklists, species traits and + distributions, and environmental data from the Global Inventory of Floras and + Traits (GIFT). More information about the GIFT database can be found at + and the map of available floras can be + visualized at . The API and associated + queries can be accessed according the following scheme: + . + date_publication: '2024-12-19' + bug_reports: https://github.com/BioGeoMacro/GIFT/issues + url: https://biogeomacro.github.io/GIFT/ + url_cran: https://CRAN.R-project.org/package=GIFT + url_git: https://github.com/BioGeoMacro/GIFT +gifti: + version: 0.8.0 + title: Reads in 'Neuroimaging' 'GIFTI' Files with Geometry Information + maintainer: John Muschelli + description: |- + Functions to read in the geometry format under the + 'Neuroimaging' 'Informatics' Technology Initiative ('NIfTI'), called + 'GIFTI' . + These files contain surfaces of brain imaging data. + date_publication: '2020-11-11' + bug_reports: https://github.com/muschellij2/gifti/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gifti + url_git: '' +GIFTr: + version: 0.1.0 + title: GIFT Questions Format Generator from Dataframes + maintainer: Omar I. Elashkar + description: |- + A framework and functions to create 'MOODLE' quizzes. 'GIFTr' takes dataframe of questions of + four types: multiple choices, numerical, true or false and short answer questions, and exports a text + file formatted in 'MOODLE' GIFT format. You can prepare a spreadsheet in any software and import + it into R to generate any number of questions with 'HTML', 'markdown' and 'LaTeX' support. + date_publication: '2019-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GIFTr + url_git: https://github.com/omarelashkar/GIFTr +gigg: + version: 0.2.1 + title: |- + Group Inverse-Gamma Gamma Shrinkage for Sparse Regression with + Grouping Structure + maintainer: Michael Kleinsasser + description: |- + A Gibbs sampler corresponding to a Group + Inverse-Gamma Gamma (GIGG) regression model with adjustment covariates. + Hyperparameters in the GIGG prior specification can either be fixed by the + user or can be estimated via Marginal Maximum Likelihood Estimation. + Jonathan Boss, Jyotishka Datta, Xin Wang, Sung Kyun Park, Jian Kang, Bhramar + Mukherjee (2021) . + date_publication: '2021-03-09' + bug_reports: https://github.com/umich-cphds/gigg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gigg + url_git: https://github.com/umich-cphds/gigg +GIGrvg: + version: '0.8' + title: Random Variate Generator for the GIG Distribution + maintainer: Josef Leydold + description: |2- + + Generator and density function for the + Generalized Inverse Gaussian (GIG) distribution. + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GIGrvg + url_git: '' +GillespieSSA: + version: 0.6.2 + title: Gillespie's Stochastic Simulation Algorithm (SSA) + maintainer: Robrecht Cannoodt + description: |- + Provides a simple to use, intuitive, and + extensible interface to several stochastic simulation + algorithms for generating simulated trajectories of finite + population continuous-time model. Currently it implements + Gillespie's exact stochastic simulation algorithm (Direct + method) and several approximate methods (Explicit tau-leap, + Binomial tau-leap, and Optimized tau-leap). The package also + contains a library of template models that can be run as demo + models and can easily be customized and extended. Currently the + following models are included, 'Decaying-Dimerization' reaction + set, linear chain system, logistic growth model, 'Lotka' + predator-prey model, Rosenzweig-MacArthur predator-prey model, + 'Kermack-McKendrick' SIR model, and a 'metapopulation' SIRS model. + Pineda-Krch et al. (2008) . + date_publication: '2022-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GillespieSSA + url_git: https://github.com/rcannood/GillespieSSA +GillespieSSA2: + version: 0.3.0 + title: Gillespie's Stochastic Simulation Algorithm for Impatient People + maintainer: Robrecht Cannoodt + description: |- + A fast, scalable, and versatile framework for + simulating large systems with Gillespie's Stochastic Simulation + Algorithm ('SSA'). This package is the spiritual successor to the + 'GillespieSSA' package originally written by Mario Pineda-Krch. + Benefits of this package include major speed improvements (>100x), + easier to understand documentation, and many unit tests that try to + ensure the package works as intended. Cannoodt and Saelens et al. (2021) + . + date_publication: '2023-01-23' + bug_reports: https://github.com/rcannood/GillespieSSA2/issues + url: https://rcannood.github.io/GillespieSSA2/ + url_cran: https://CRAN.R-project.org/package=GillespieSSA2 + url_git: https://github.com/rcannood/GillespieSSA2 +gim: + version: 0.33.1 + title: Generalized Integration Model + maintainer: Han Zhang + description: Implements the generalized integration model, which integrates individual-level + data and summary statistics under a generalized linear model framework. It supports + continuous and binary outcomes to be modeled by the linear and logistic regression + models. For binary outcome, data can be sampled in prospective cohort studies + or case-control studies. Described in Zhang et al. (2020). + date_publication: '2020-06-12' + bug_reports: https://github.com/zhangh12/gim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gim + url_git: https://github.com/zhangh12/gim +gimap: + version: 1.0.2 + title: Calculate Genetic Interactions for Paired CRISPR Targets + maintainer: Candace Savonen + description: Helps find meaningful patterns in complex genetic experiments. First + gimap takes data from paired CRISPR (Clustered regularly interspaced short palindromic + repeats) screens that has been pre-processed to counts table of paired gRNA (guide + Ribonucleic Acid) reads. The input data will have cell counts for how well cells + grow (or don't grow) when different genes or pairs of genes are disabled. The + output of the 'gimap' package is genetic interaction scores which are the distance + between the observed CRISPR score and the expected CRISPR score. The expected + CRISPR scores are what we expect for the CRISPR values to be for two unrelated + genes. The further away an observed CRISPR score is from its expected score the + more we suspect genetic interaction. The work in this package is based off of + original research from the Alice Berger lab at Fred Hutchinson Cancer Center (2021) + . + date_publication: '2025-02-18' + bug_reports: https://github.com/FredHutch/gimap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gimap + url_git: https://github.com/FredHutch/gimap +gimme: + version: 0.7-18 + title: Group Iterative Multiple Model Estimation + maintainer: Kathleen M Gates + description: Data-driven approach for arriving at person-specific time series models. + The method first identifies which relations replicate across the majority of individuals + to detect signal from noise. These group-level relations are then used as a foundation + for starting the search for person-specific (or individual-level) relations. See + Gates & Molenaar (2012) . + date_publication: '2024-06-21' + bug_reports: https://github.com/GatesLab/gimme/issues + url: https://tarheels.live/gimme/tutorials/ + url_cran: https://CRAN.R-project.org/package=gimme + url_git: https://github.com/GatesLab/gimme/ +GIMMEgVAR: + version: 0.1.0 + title: Group Iterative Multiple Model Estimation with 'graphicalVAR' + maintainer: Sandra Williams Lee + description: Data-driven approach for arriving at person-specific time series models + from within a Graphical Vector Autoregression (VAR) framework. The method first + identifies which relations replicate across the majority of individuals to detect + signal from noise. These group-level relations are then used as a foundation for + starting the search for person-specific (or individual-level) relations. All estimates + are obtained uniquely for each individual in the final models. The method for + the 'graphicalVAR' approach is found in Epskamp, Waldorp, Mottus & Borsboom (2018) + . + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GIMMEgVAR + url_git: '' +GimmeMyPlot: + version: 0.1.0 + title: Graphical Utilities for Visualizing and Exploring Data + maintainer: Etienne Camenen + description: |- + Simplifies the process of creating essential visualizations + in R, offering a range of plotting functions for common chart types + like violin plots, pie charts, and histograms. With an intuitive + interface, users can effortlessly customize colors, labels, and + styles, making it an ideal tool for both beginners and experienced + data analysts. Whether exploring datasets or producing quick visual + summaries, this package provides a streamlined solution for + fundamental graphics in R. + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GimmeMyPlot + url_git: '' +gimmeTools: + version: '0.1' + title: Supplemental Tools for the 'gimme' R Package + maintainer: Stephanie Lane + description: Supplemental tools for the 'gimme' R package. It contains an interactive + graphical user interface, allowing for the flexible specification of a variety + of both basic and advanced options. It will expand to include a variety of tools + for navigating output. + date_publication: '2018-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gimmeTools + url_git: https://github.com/stlane +gimms: + version: 1.2.2 + title: Download and Process GIMMS NDVI3g Data + maintainer: Florian Detsch + description: |- + This is a set of functions to retrieve information about GIMMS + NDVI3g files currently available online; download (and re-arrange, in the + case of NDVI3g.v0) the half-monthly data sets; import downloaded files from + ENVI binary (NDVI3g.v0) or NetCDF format (NDVI3g.v1) directly into R based + on the widespread 'raster' package; conduct quality control; and generate + monthly composites (e.g., maximum values) from the half-monthly input data. + As a special gimmick, a method is included to conveniently apply the + Mann-Kendall trend test upon 'Raster*' images, optionally featuring + trend-free pre-whitening to account for lag-1 autocorrelation. + date_publication: '2023-08-09' + bug_reports: https://github.com/environmentalinformatics-marburg/gimms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gimms + url_git: https://github.com/environmentalinformatics-marburg/gimms +Gini: + version: 0.1.0 + title: Gini Coefficient + maintainer: Zhicheng Du + description: |- + Providing various equations to calculate Gini coefficients. + The methods used in this package can be referenced from Brown MC (1994) . + date_publication: '2021-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Gini + url_git: '' +giniCI: + version: 0.1.0 + title: Gini-Based Composite Indicators + maintainer: Viet Duong Nguyen + description: An implementation of Gini-based weighting approaches in constructing + composite indicators, providing functionalities for normalization, aggregation, + and ranking comparison. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=giniCI + url_git: '' +GiniDecompLY: + version: 1.0.1 + title: Gini Decomposition by Income Sources + maintainer: Abdessamad Ait Mbarek + description: Estimation of the effect of each income source on income inequalities + based on the decomposition of Lerman and Yitzhaki (1985) . + date_publication: '2024-11-26' + bug_reports: https://github.com/aambarek/GiniDecompLY/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GiniDecompLY + url_git: https://github.com/aambarek/GiniDecompLY +GiniDistance: + version: 0.1.1 + title: |- + A New Gini Correlation Between Quantitative and Qualitative + Variables + maintainer: Dao Nguyen + description: An implementation of a new Gini covariance and correlation to measure + dependence between a categorical and numerical variables. Dang, X., Nguyen, D., + Chen, Y. and Zhang, J., (2018) . + date_publication: '2022-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GiniDistance + url_git: '' +giniVarCI: + version: 0.0.1-3 + title: |- + Gini Indices, Variances and Confidence Intervals for Finite and + Infinite Populations + maintainer: Juan Francisco Muñoz + description: |- + Estimates the Gini index and computes variances and confidence intervals for finite and infinite populations, using different methods; also computes Gini index for continuous probability distributions, draws samples from continuous probability distributions with Gini indices set by the user; uses 'Rcpp'. + References: + Muñoz et al. (2023) . + Álvarez et al. (2021) . + Giorgi and Gigliarano (2017) . + Langel and Tillé (2013) . + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=giniVarCI + url_git: '' +ginormal: + version: 0.0.2 + title: Generalized Inverse Normal Distribution Density and Generation + maintainer: Santiago Montoya-Blandón + description: Density function and generation of random variables from the Generalized + Inverse Normal (GIN) distribution from Robert (1991) . + Also provides density functions and generation from the GIN distribution truncated + to positive or negative reals. Theoretical guarantees supporting the sampling + algorithms and an application to Bayesian estimation of network formation models + can be found in the working paper Ding, Estrada and Montoya-Blandón (2023) . + date_publication: '2023-08-27' + bug_reports: https://github.com/smonto2/ginormal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ginormal + url_git: https://github.com/smonto2/ginormal +GInSARCorW: + version: 1.15.8 + title: GACOS InSAR Correction Workflow + maintainer: Subhadip Datta + description: |- + A workflow for correction of Differential Interferometric Synthetic Aperture Radar (DInSAR) atmospheric delay base on Generic Atmospheric Correction Online Service for InSAR (GACOS) data and correction algorithms proposed by Chen Yu. This package calculate the Both Zenith and LOS direction (User Depend). You have to just download GACOS product on your area and preprocessed D-InSAR unwrapped images. Cite those references and this package in your work, when using this framework. + References: + Yu, C., N. T. Penna, and Z. Li (2017) . + Yu, C., Li, Z., & Penna, N. T. (2017) . + Yu, C., Penna, N. T., and Li, Z. (2017) . + date_publication: '2023-05-14' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=GInSARCorW + url_git: '' +gIPFrm: + version: '3.1' + title: Generalized Iterative Proportional Fitting for Relational Models + maintainer: Anna Klimova + description: Maximum likelihood estimation under relational models, with or without + the overall effect. + date_publication: '2017-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gIPFrm + url_git: '' +GIplot: + version: 0.1.0 + title: Gaussian Interval Plot (GIplot) + maintainer: Siddhanta Phuyal + description: |- + The Gaussian Interval Plot (GIplot) is a pictorial representation of the mean + and the standard deviation of a quantitative variable. It also flags + potential outliers (together with their frequencies) that are c standard deviations away from the mean. + date_publication: '2021-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GIplot + url_git: '' +gips: + version: 1.2.1 + title: Gaussian Model Invariant by Permutation Symmetry + maintainer: Adam Przemysław Chojecki + description: |- + Find the permutation symmetry group such that the covariance + matrix of the given data is approximately invariant under it. + Discovering such a permutation decreases the number of observations + needed to fit a Gaussian model, which is of great use when it is + smaller than the number of variables. Even if that is not the case, + the covariance matrix found with 'gips' approximates the actual + covariance with less statistical error. The methods implemented in + this package are described in Graczyk et al. (2022) + . + date_publication: '2023-08-12' + bug_reports: https://github.com/PrzeChoj/gips/issues + url: https://przechoj.github.io/gips/ + url_cran: https://CRAN.R-project.org/package=gips + url_git: https://github.com/PrzeChoj/gips +GiRaF: + version: 1.0.1 + title: Gibbs Random Fields Analysis + maintainer: Julien Stoehr + description: |- + Allows calculation on, and + sampling from Gibbs Random Fields, and more precisely general + homogeneous Potts model. The primary tool is the exact computation of + the intractable normalising constant for small rectangular lattices. + Beside the latter function, it contains method that give exact sample from the likelihood + for small enough rectangular lattices or approximate sample from the + likelihood using MCMC samplers for large lattices. + date_publication: '2020-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GiRaF + url_git: '' +giscoR: + version: 0.6.1 + title: Download Map Data from GISCO API - Eurostat + maintainer: Diego Hernangómez + description: |- + Tools to download data from the GISCO (Geographic Information + System of the Commission) Eurostat database + . Global and European map + data available. This package is in no way officially related to or + endorsed by Eurostat. + date_publication: '2025-01-27' + bug_reports: https://github.com/rOpenGov/giscoR/issues + url: https://ropengov.github.io/giscoR/ + url_cran: https://CRAN.R-project.org/package=giscoR + url_git: https://github.com/rOpenGov/giscoR +GISINTEGRATION: + version: '1.0' + title: GIS Integration + maintainer: Leila Marvian Mashhad + description: |- + Designed to facilitate the preprocessing and linking of GIS (Geographic Information System) databases + , + the R package 'GISINTEGRATION' offers a robust solution for efficiently preparing GIS data for advanced + spatial analyses. This package excels in simplifying intrica procedures like data cleaning, normalization, + and format conversion, ensuring that the data are optimally primed for precise and thorough analysis. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GISINTEGRATION + url_git: '' +GISSB: + version: '1.1' + title: Network Analysis on the Norwegian Road Network + maintainer: Sindre Mikael Haugen + description: A collection of GIS (Geographic Information System) functions in R, + created for use in Statistics Norway. The functions are primarily related to network + analysis on the Norwegian road network. + date_publication: '2023-01-10' + bug_reports: '' + url: https://statisticsnorway.github.io/GISSB/ + url_cran: https://CRAN.R-project.org/package=GISSB + url_git: '' +GISTools: + version: 1.0-2 + title: Further Capabilities in Geographic Information Science + maintainer: Binbin Lu + description: |- + Mapping and spatial data manipulation tools - in particular + drawing thematic maps with nice looking legends, and aggregation of point + data to polygons. + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GISTools + url_git: '' +gistr: + version: 0.9.0 + title: Work with 'GitHub' 'Gists' + maintainer: Scott Chamberlain + description: |- + Work with 'GitHub' 'gists' from 'R' (e.g., + , + ). A 'gist' + is simply one or more files with code/text/images/etc. This package allows + the user to create new 'gists', update 'gists' with new files, rename files, + delete files, get and delete 'gists', star and 'un-star' 'gists', fork 'gists', + open a 'gist' in your default browser, get embed code for a 'gist', list + 'gist' 'commits', and get rate limit information when 'authenticated'. Some + requests require authentication and some do not. 'Gists' website: + . + date_publication: '2020-07-29' + bug_reports: https://github.com/ropensci/gistr/issues + url: https://docs.ropensci.org/gistr(website) + url_cran: https://CRAN.R-project.org/package=gistr + url_git: https://github.com/ropensci/gistr(devel) +git2r: + version: 0.35.0 + title: Provides Access to Git Repositories + maintainer: Stefan Widgren + description: |- + Interface to the 'libgit2' library, which is a pure C + implementation of the 'Git' core methods. Provides access to 'Git' + repositories to extract data and running some basic 'Git' + commands. + date_publication: '2024-10-20' + bug_reports: https://github.com/ropensci/git2r/issues + url: https://docs.ropensci.org/git2r/ + url_cran: https://CRAN.R-project.org/package=git2r + url_git: https://github.com/ropensci/git2r +git2rdata: + version: 0.5.0 + title: Store and Retrieve Data.frames in a Git Repository + maintainer: Thierry Onkelinx + description: |- + The git2rdata package is an R package for writing and reading + dataframes as plain text files. A metadata file stores important + information. 1) Storing metadata allows to maintain the classes of + variables. By default, git2rdata optimizes the data for file storage. + The optimization is most effective on data containing factors. The + optimization makes the data less human readable. The user can turn + this off when they prefer a human readable format over smaller files. + Details on the implementation are available in vignette("plain_text", + package = "git2rdata"). 2) Storing metadata also allows smaller row + based diffs between two consecutive commits. This is a useful feature + when storing data as plain text files under version control. Details + on this part of the implementation are available in + vignette("version_control", package = "git2rdata"). Although we + envisioned git2rdata with a git workflow in mind, you can use it in + combination with other version control systems like subversion or + mercurial. 3) git2rdata is a useful tool in a reproducible and + traceable workflow. vignette("workflow", package = "git2rdata") gives + a toy example. 4) vignette("efficiency", package = "git2rdata") + provides some insight into the efficiency of file storage, git + repository size and speed for writing and reading. + date_publication: '2025-01-24' + bug_reports: https://github.com/ropensci/git2rdata/issues + url: https://ropensci.github.io/git2rdata/ + url_cran: https://CRAN.R-project.org/package=git2rdata + url_git: https://github.com/ropensci/git2rdata/ +git4r: + version: 0.1.2 + title: Interactive Git for R + maintainer: John Hobbs + description: |- + An interactive git user interface from the R command line. Intuitive + tools to make commits, branches, remotes, and diffs an integrated part + of R coding. Built on git2r, a system installation of git is not required + and has default on-premises remote option. + date_publication: '2022-03-11' + bug_reports: https://github.com/johnxhobbs/git4r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=git4r + url_git: https://github.com/johnxhobbs/git4r +GitAI: + version: 0.1.0 + title: Extracts Knowledge from 'Git' Repositories + maintainer: Kamil Wais + description: Scan multiple 'Git' repositories, pull specified files content and + process it with large language models. You can summarize the content in specific + way, extract information and data, or find answers to your questions about the + repositories. The output can be stored in vector database and used for semantic + search or as a part of a RAG (Retrieval Augmented Generation) prompt. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GitAI + url_git: '' +gitcreds: + version: 0.1.2 + title: Query 'git' Credentials from 'R' + maintainer: Gábor Csárdi + description: |- + Query, set, delete credentials from the 'git' credential + store. Manage 'GitHub' tokens and other 'git' credentials. This + package is to be used by other packages that need to authenticate to + 'GitHub' and/or other 'git' repositories. + date_publication: '2022-09-08' + bug_reports: https://github.com/r-lib/gitcreds/issues + url: https://gitcreds.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=gitcreds + url_git: https://github.com/r-lib/gitcreds +gitdown: + version: 0.1.6 + title: Turn Your Git Commit Messages into a HTML Book + maintainer: Sébastien Rochette + description: |- + Read all commit messages of your local git repository and + sort them according to tags or specific text pattern into chapters of + a HTML book using 'bookdown'. The git history book presentation helps + organisms required to testify for every changes in their source code, + in relation to features requests. + date_publication: '2022-03-05' + bug_reports: https://github.com/Thinkr-open/gitdown/issues + url: https://thinkr-open.github.io/gitdown/ + url_cran: https://CRAN.R-project.org/package=gitdown + url_git: https://github.com/Thinkr-open/gitdown +gitear: + version: 1.0.0 + title: Client to the 'gitea' API + maintainer: Frans van Dunné + description: |- + 'Gitea' is a community managed, lightweight code hosting solution + were projects and their respective git repositories can be managed + . This package gives an interface to the 'Gitea' API to + access and manage repositories, issues and organizations directly in R. + date_publication: '2020-09-18' + bug_reports: https://github.com/ixpantia/gitear/issues + url: https://ixpantia.github.io/gitear/ + url_cran: https://CRAN.R-project.org/package=gitear + url_git: '' +gitgadget: + version: 0.8.1 + title: |- + 'Rstudio' Addin for Version Control and Assignment Management + using Git + maintainer: Vincent Nijs + description: |- + An 'Rstudio' addin for version control that allows users to clone + repositories, create and delete branches, and sync forks on GitHub, GitLab, etc. + Furthermore, the addin uses the GitLab API to allow instructors to create + forks and merge requests for all students/teams with one click of a button. + date_publication: '2023-08-24' + bug_reports: https://github.com/vnijs/gitgadget/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gitgadget + url_git: URL:https://github.com/vnijs/gitgadget +gitGPT: + version: 0.1.3 + title: Automated Git Commit Messages using the 'OpenAI' 'GPT' Model + maintainer: Steve Condylios + description: |- + Automates the process of adding, + committing, and pushing changes to a 'git' repository + using commit messages generated by passing the git diff output + to the 'OpenAI' + 'GPT-3.5 Turbo' model (). + date_publication: '2023-04-04' + bug_reports: https://github.com/stevecondylios/gitGPT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gitGPT + url_git: https://github.com/stevecondylios/gitGPT +githubinstall: + version: 0.2.2 + title: A Helpful Way to Install R Packages Hosted on GitHub + maintainer: Koji Makiyama + description: Provides an helpful way to install packages hosted on GitHub. + date_publication: '2018-02-18' + bug_reports: https://github.com/hoxo-m/githubinstall/issues + url: '' + url_cran: https://CRAN.R-project.org/package=githubinstall + url_git: https://github.com/hoxo-m/githubinstall +githubr: + version: 0.9.1 + title: Easier to Use API Wrapper for 'GitHub' + maintainer: Candace Savonen + description: This is a 'GitHub' API wrapper for R. + It uses the 'gh' package but has things wrapped up for convenient use cases. + date_publication: '2023-10-20' + bug_reports: https://github.com/fhdsl/githubr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=githubr + url_git: https://github.com/fhdsl/githubr +gitignore: + version: 0.1.8 + title: Create Useful .gitignore Files for your Project + maintainer: Philippe Massicotte + description: |- + Simple interface to query gitignore.io to fetch + gitignore templates that can be included in the .gitignore file. More + than 450 templates are currently available. + date_publication: '2024-11-01' + bug_reports: https://github.com/ropensci/gitignore/issues + url: https://docs.ropensci.org/gitignore/ + url_cran: https://CRAN.R-project.org/package=gitignore + url_git: https://github.com/ropensci/gitignore +gitlabr: + version: 2.1.0 + title: Access to the 'GitLab' API + maintainer: Sébastien Rochette + description: |- + Provides R functions to access the API of the project and + repository management web application 'GitLab'. For many common tasks + (repository file access, issue assignment and status, commenting) + convenience wrappers are provided, and in addition the full API can be + used by specifying request locations. 'GitLab' is open-source software + and can be self-hosted or used on . + date_publication: '2024-05-16' + bug_reports: https://github.com/ThinkR-open/gitlabr/issues + url: https://thinkr-open.github.io/gitlabr/ + url_cran: https://CRAN.R-project.org/package=gitlabr + url_git: https://github.com/ThinkR-open/gitlabr +gitlink: + version: 0.1.3 + title: Add 'Git' Links to Your Web Based Assets + maintainer: Cole Arendt + description: |- + Provides helpers to add 'Git' links to 'shiny' + applications, 'rmarkdown' documents, and other 'HTML' based resources. + This is most commonly used for 'GitHub' ribbons. + date_publication: '2019-07-23' + bug_reports: https://github.com/colearendt/gitlink/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gitlink + url_git: https://github.com/colearendt/gitlink +gitr: + version: 0.0.1 + title: A Lightweight API for 'Git' + maintainer: Stu Field + description: |- + A light-weight, dependency-free, application programming interface + (API) to access system-level 'Git' commands from within 'R'. Contains wrappers + and defaults for common data science workflows as well as + 'Zsh' plugin aliases. A generalized API syntax is also available. + A system installation of 'Git' is required. + date_publication: '2023-02-15' + bug_reports: https://github.com/stufield/gitr/issues + url: https://stufield.github.io/gitr/ + url_cran: https://CRAN.R-project.org/package=gitr + url_git: '' +GitStats: + version: 2.2.2 + title: Standardized Git Repository Data + maintainer: Maciej Banas + description: |- + Obtain standardized data from multiple 'Git' services, including 'GitHub' and 'GitLab'. + Designed to be 'Git' service-agnostic, this package assists teams with activities spread across various + 'Git' platforms by providing a unified way to access repository data. + date_publication: '2025-02-11' + bug_reports: https://github.com/r-world-devs/GitStats/issues + url: https://r-world-devs.github.io/GitStats/ + url_cran: https://CRAN.R-project.org/package=GitStats + url_git: https://github.com/r-world-devs/GitStats +gittargets: + version: 0.0.7 + title: Data Version Control for the Targets Package + maintainer: William Michael Landau + description: |- + In computationally demanding data analysis pipelines, + the 'targets' R package (2021, ) maintains + an up-to-date set of results while skipping tasks that do not need to rerun. + This process increases speed and increases trust in the final end product. + However, it also overwrites old output with new output, and past + results disappear by default. To preserve historical output, the 'gittargets' + package captures version-controlled snapshots of the data store, + and each snapshot links to the underlying commit of the source code. + That way, when the user rolls back the code to a previous branch or commit, + 'gittargets' can recover the data contemporaneous with that commit so that + all targets remain up to date. + date_publication: '2023-12-04' + bug_reports: https://github.com/ropensci/gittargets/issues + url: https://docs.ropensci.org/gittargets/ + url_cran: https://CRAN.R-project.org/package=gittargets + url_git: https://github.com/ropensci/gittargets +givitiR: + version: '1.3' + title: The GiViTI Calibration Test and Belt + maintainer: Giovanni Nattino + description: Functions to assess the calibration of logistic regression models with + the GiViTI (Gruppo Italiano per la Valutazione degli interventi in Terapia Intensiva, + Italian Group for the Evaluation of the Interventions in Intensive Care Units + - see ) approach. The approach consists in a + graphical tool, namely the GiViTI calibration belt, and in the associated statistical + test. These tools can be used both to evaluate the internal calibration (i.e. + the goodness of fit) and to assess the validity of an externally developed model. + date_publication: '2017-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=givitiR + url_git: '' +gjam: + version: 2.6.2 + title: Generalized Joint Attribute Modeling + maintainer: James S. Clark + description: Analyzes joint attribute data (e.g., species abundance) that are combinations + of continuous and discrete data with Gibbs sampling. Full model and computation + details are described in Clark et al. (2018) . + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gjam + url_git: '' +gJLS2: + version: 0.2.0 + title: |- + A Generalized Joint Location and Scale Framework for Association + Testing + maintainer: Wei Deng + description: 'An update to the Joint Location-Scale (JLS) testing framework that + identifies associated SNPs, gene-sets and pathways with main and/or interaction + effects on quantitative traits (Soave et al., 2015; ). + The JLS method simultaneously tests the null hypothesis of equal mean and equal + variance across genotypes, by aggregating association evidence from the individual + location/mean-only and scale/variance-only tests using Fisher''s method. The generalized + joint location-scale (gJLS) framework has been developed to deal specifically + with sample correlation and group uncertainty (Soave and Sun, 2017; ). + The current release: gJLS2, include additional functionalities that enable analyses + of X-chromosome genotype data through novel methods for location (Chen et al., + 2021; ) and scale (Deng et al., 2019; ).' + date_publication: '2021-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gJLS2 + url_git: '' +GJRM: + version: 0.2-6.7 + title: Generalised Joint Regression Modelling + maintainer: Giampiero Marra + description: Routines for fitting various joint (and univariate) regression models, + with several types of covariate effects, in the presence of equations' errors + association, endogeneity, non-random sample selection or partial observability. + date_publication: '2024-10-25' + bug_reports: '' + url: https://www.ucl.ac.uk/statistics/people/giampieromarra + url_cran: https://CRAN.R-project.org/package=GJRM + url_git: '' +gk: + version: 0.6.0 + title: g-and-k and g-and-h Distribution Functions + maintainer: Dennis Prangle + description: Functions for the g-and-k and generalised g-and-h distributions. + date_publication: '2023-08-10' + bug_reports: https://github.com/dennisprangle/gk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gk + url_git: https://github.com/dennisprangle/gk +GK2011: + version: 0.1.3 + title: Gaines and Kuklinski (2011) Estimators for Hybrid Experiments + maintainer: Thomas J. Leeper + description: 'Implementations of the treatment effect estimators for hybrid (self-selection) + experiments, as developed by Brian J. Gaines and James H. Kuklinski, (2011), "Experimental + Estimation of Heterogeneous Treatment Effects Related to Self-Selection," American + Journal of Political Science 55(3): 724-736.' + date_publication: '2016-05-27' + bug_reports: https://github.com/leeper/GK2011/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GK2011 + url_git: https://github.com/leeper/GK2011 +gkgraphR: + version: 1.0.2 + title: Accessing the Official 'Google Knowledge Graph' API + maintainer: Ricardo Correia + description: |- + A simple way to interact with and extract data from + the official 'Google Knowledge Graph' API . + date_publication: '2021-03-01' + bug_reports: https://github.com/racorreia/gkgraphR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gkgraphR + url_git: https://github.com/racorreia/gkgraphR +gkmSVM: + version: 0.83.0 + title: Gapped-Kmer Support Vector Machine + maintainer: Mike Beer + description: |- + Imports the 'gkmSVM' v2.0 functionalities into R + It also uses the 'kernlab' library (separate R package by different authors) for various SVM algorithms. + Users should note that the suggested packages 'rtracklayer', 'GenomicRanges', 'BSgenome', 'BiocGenerics', + 'Biostrings', 'GenomeInfoDb', 'IRanges', and 'S4Vectors' are all BioConductor packages . + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gkmSVM + url_git: '' +gKRLS: + version: 1.0.4 + title: Generalized Kernel Regularized Least Squares + maintainer: Max Goplerud + description: |- + Kernel regularized least squares, also known as kernel ridge regression, + is a flexible machine learning method. This package implements this method by + providing a smooth term for use with 'mgcv' and uses random sketching to + facilitate scalable estimation on large datasets. It provides additional + functions for calculating marginal effects after estimation and for use with + ensembles ('SuperLearning'), double/debiased machine learning ('DoubleML'), + and robust/clustered standard errors ('sandwich'). Chang and Goplerud (2024) + provide further details. + date_publication: '2024-11-07' + bug_reports: https://github.com/mgoplerud/gKRLS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gKRLS + url_git: https://github.com/mgoplerud/gKRLS +glam: + version: 1.0.2 + title: Generalized Additive and Linear Models (GLAM) + maintainer: Andrew Cooper + description: |- + Contains methods for fitting Generalized Linear Models (GLMs) + and Generalized Additive Models (GAMs). Generalized regression models are + common methods for handling data for which assuming Gaussian-distributed + errors is not appropriate. For instance, if the response of interest is + binary, count, or proportion data, one can instead model the expectation of + the response based on an appropriate data-generating distribution. + This package provides methods for fitting GLMs and GAMs under + Beta regression, Poisson regression, Gamma regression, and Binomial regression + (currently GLM only) settings. Models are fit using local scoring algorithms + described in Hastie and Tibshirani (1990) . + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glam + url_git: '' +glamlasso: + version: 3.0.1 + title: Penalization in Large Scale Generalized Linear Array Models + maintainer: Adam Lund + description: 'Efficient design matrix free lasso penalized estimation in large + scale 2 and 3-dimensional generalized linear array model framework. The procedure + is based on the gdpg algorithm from Lund et al. (2017) . + Currently Lasso or Smoothly Clipped Absolute Deviation (SCAD) penalized estimation + is possible for the following models: The Gaussian model with identity link, the + Binomial model with logit link, the Poisson model with log link and the Gamma + model with log link. It is also possible to include a component in the model + with non-tensor design e.g an intercept. Also provided are functions, glamlassoRR() + and glamlassoS(), fitting special cases of GLAMs.' + date_publication: '2021-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glamlasso + url_git: '' +glarma: + version: 1.6-0 + title: Generalized Linear Autoregressive Moving Average Models + maintainer: '"William T.M. Dunsmuir"' + description: Functions are provided for estimation, testing, diagnostic checking + and forecasting of generalized linear autoregressive moving average (GLARMA) models + for discrete valued time series with regression variables. These are a class + of observation driven non-linear non-Gaussian state space models. The state vector + consists of a linear regression component plus an observation driven component + consisting of an autoregressive-moving average (ARMA) filter of past predictive + residuals. Currently three distributions (Poisson, negative binomial and binomial) + can be used for the response series. Three options (Pearson, score-type and unscaled) + for the residuals in the observation driven component are available. Estimation + is via maximum likelihood (conditional on initializing values for the ARMA process) + optimized using Fisher scoring or Newton Raphson iterative methods. Likelihood + ratio and Wald tests for the observation driven component allow testing for serial + dependence in generalized linear model settings. Graphical diagnostics including + model fits, autocorrelation functions and probability integral transform residuals + are included in the package. Several standard data sets are included in the package. + date_publication: '2018-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glarma + url_git: '' +Glarmadillo: + version: 1.1.1 + title: Solve the Graphical Lasso Problem with 'Armadillo' + maintainer: Alessandro Meng + description: |- + Efficiently implements the Graphical Lasso algorithm, + utilizing the 'Armadillo' 'C++' library for rapid computation. This algorithm + introduces an L1 penalty to derive sparse inverse covariance matrices from + observations of multivariate normal distributions. Features include the + generation of random and structured sparse covariance matrices, beneficial + for simulations, statistical method testing, and educational purposes in + graphical modeling. A unique function for regularization parameter selection + based on predefined sparsity levels is also offered, catering to users with + specific sparsity requirements in their models. The methodology for sparse + inverse covariance estimation implemented in this package is based on the + work of Friedman, Hastie, and Tibshirani (2008) . + date_publication: '2023-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Glarmadillo + url_git: '' +GlarmaVarSel: + version: '1.0' + title: Variable Selection in Sparse GLARMA Models + maintainer: Marina Gomtsyan + description: Performs variable selection in high-dimensional sparse GLARMA models. + For further details we refer the reader to the paper Gomtsyan et al. (2020), . + date_publication: '2021-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GlarmaVarSel + url_git: '' +glassdoor: + version: 0.8.1 + title: Interface to 'Glassdoor' API + maintainer: John Muschelli + description: |- + Interacts with the 'Glassdoor' API + . Allows the user to + search job statistics, employer statistics, and job progression, + where 'Glassdoor' provides a breakdown of other jobs a person did + after their current one. + date_publication: '2018-11-21' + bug_reports: https://github.com/muschellij2/glassdoor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glassdoor + url_git: '' +glasso: + version: '1.11' + title: 'Graphical Lasso: Estimation of Gaussian Graphical Models' + maintainer: Rob Tibshirani + description: |- + Estimation of a sparse inverse covariance matrix using a lasso (L1) + penalty. Facilities are provided for estimates along a path of values + for the regularization parameter. + date_publication: '2019-10-01' + bug_reports: '' + url: http://www-stat.stanford.edu/~tibs/glasso + url_cran: https://CRAN.R-project.org/package=glasso + url_git: '' +glassoFast: + version: 1.0.1 + title: Fast Graphical LASSO + maintainer: Julien Clavel + description: A fast and improved implementation of the graphical LASSO. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glassoFast + url_git: '' +glba: + version: 0.2.1 + title: General Linear Ballistic Accumulator Models + maintainer: Ingmar Visser + description: Analyses response times and accuracies from psychological experiments + with the linear ballistic accumulator (LBA) model from Brown and Heathcote (2008). + The LBA model is optionally fitted with explanatory variables on the parameters + such as the drift rate, the boundary and the starting point parameters. A log-link + function on the linear predictors can be used to ensure that parameters remain + positive when needed. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glba + url_git: '' +glca: + version: 1.4.2 + title: An R Package for Multiple-Group Latent Class Analysis + maintainer: Youngsun Kim + description: |- + Fits multiple-group latent class analysis (LCA) for exploring + differences between populations in the data with a multilevel structure. + There are two approaches to reflect group differences in glca: + fixed-effect LCA (Bandeen-Roche et al (1997) ; + Clogg and Goodman (1985) ) and nonparametric random-effect LCA + (Vermunt (2003) ). + date_publication: '2024-08-27' + bug_reports: https://github.com/kim0sun/glca/issues/ + url: https://kim0sun.github.io/glca/ + url_cran: https://CRAN.R-project.org/package=glca + url_git: '' +glcm: + version: 1.6.5 + title: |- + Calculate Textures from Grey-Level Co-Occurrence Matrices + (GLCMs) + maintainer: Alex Zvoleff + description: |- + Enables calculation of image textures (Haralick 1973) + from grey-level co-occurrence matrices + (GLCMs). Supports processing images that cannot fit in memory. + date_publication: '2020-02-26' + bug_reports: https://github.com/azvoleff/glcm/issues + url: http://www.azvoleff.com/glcm + url_cran: https://CRAN.R-project.org/package=glcm + url_git: '' +GLCMTextures: + version: '0.5' + title: GLCM Textures of Raster Layers + maintainer: Alexander Ilich + description: Calculates grey level co-occurrence matrix (GLCM) based texture measures + (Hall-Beyer (2017) ; + Haralick et al. (1973) ) of raster layers using + a sliding rectangular window. It also includes functions to quantize a raster + into grey levels as well as tabulate a glcm and calculate glcm texture metrics + for a matrix. + date_publication: '2025-01-15' + bug_reports: https://github.com/ailich/GLCMTextures/issues + url: https://ailich.github.io/GLCMTextures/ + url_cran: https://CRAN.R-project.org/package=GLCMTextures + url_git: https://github.com/ailich/GLCMTextures +gld: + version: 2.6.7 + title: |- + Estimation and Use of the Generalised (Tukey) Lambda + Distribution + maintainer: Robert King + description: |- + The generalised lambda distribution, or Tukey lambda distribution, + provides a wide variety of shapes with one functional form. + This package provides random numbers, quantiles, probabilities, + densities and density quantiles for four different types of the distribution, + the FKML (Freimer et al 1988), RS (Ramberg and Schmeiser 1974), GPD (van Staden + and Loots 2009) and FM5 - see documentation for details. + It provides the density function, distribution function, and Quantile-Quantile + plots. + It implements a variety of estimation methods for the distribution, + including diagnostic plots. + Estimation methods include the starship (all 4 types), + method of L-Moments for the GPD and FKML types, and a + number of methods for only the FKML type. + These include maximum likelihood, maximum product of spacings, + Titterington's method, Moments, Trimmed L-Moments and + Distributional Least Absolutes. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gld + url_git: https://github.com/newystats/gld/ +GLDEX: + version: 2.0.0.9.3 + title: Fitting Single and Mixture of Generalised Lambda Distributions + maintainer: Steve Su + description: 'The fitting algorithms considered in this package have two major objectives. + One is to provide a smoothing device to fit distributions to data using the weight + and unweighted discretised approach based on the bin width of the histogram. The + other is to provide a definitive fit to the data set using the maximum likelihood + and quantile matching estimation. Other methods such as moment matching, starship + method, L moment matching are also provided. Diagnostics on goodness of fit can + be done via qqplots, KS-resample tests and comparing mean, variance, skewness + and kurtosis of the data with the fitted distribution. References include the + following: Karvanen and Nuutinen (2008) "Characterizing the generalized lambda + distribution by L-moments" , King and MacGillivray + (1999) "A starship method for fitting the generalised lambda distributions" , + Su (2005) "A Discretized Approach to Flexibly Fit Generalized Lambda Distributions + to Data" , Su (2007) "Nmerical Maximum Log Likelihood + Estimation for Generalized Lambda Distributions" , + Su (2007) "Fitting Single and Mixture of Generalized Lambda Distributions to Data + via Discretized and Maximum Likelihood Methods: GLDEX in R" , + Su (2009) "Confidence Intervals for Quantiles Using Generalized Lambda Distributions" + , Su (2010) "Chapter 14: Fitting GLDs and Mixture + of GLDs to Data using Quantile Matching Method" , Su (2010) + "Chapter 15: Fitting GLD to data using GLDEX 1.0.4 in R" , + Su (2015) "Flexible Parametric Quantile Regression Model" , + Su (2021) "Flexible parametric accelerated failure time model".' + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLDEX + url_git: '' +GLDreg: + version: 1.1.1 + title: Fit GLD Regression/Quantile/AFT Model to Data + maintainer: Steve Su + description: 'Owing to the rich shapes of Generalised Lambda Distributions (GLDs), + GLD standard/quantile/Accelerated Failure Time (AFT) regression is a competitive + flexible model compared to standard/quantile/AFT regression. The proposed method + has some major advantages: 1) it provides a reference line which is very robust + to outliers with the attractive property of zero mean residuals and 2) it gives + a unified, elegant quantile regression model from the reference line with smooth + regression coefficients across different quantiles. For AFT model, it also eliminates + the needs to try several different AFT models, owing to the flexible shapes of + GLD. The goodness of fit of the proposed model can be assessed via QQ plots and + Kolmogorov-Smirnov tests and data driven smooth test, to ensure the appropriateness + of the statistical inference under consideration. Statistical distributions of + coefficients of the GLD regression line are obtained using simulation, and interval + estimates are obtained directly from simulated data. References include the following: + Su (2015) "Flexible Parametric Quantile Regression Model" , + Su (2021) "Flexible parametric accelerated failure time model".' + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLDreg + url_git: '' +gldrm: + version: '1.6' + title: Generalized Linear Density Ratio Models + maintainer: Michael Wurm + description: |- + Fits a generalized linear density ratio model (GLDRM). + A GLDRM is a semiparametric generalized linear model. + In contrast to a GLM, which assumes a particular exponential family distribution, + the GLDRM uses a semiparametric likelihood to estimate the reference distribution. + The reference distribution may be any discrete, continuous, or mixed exponential + family distribution. The model parameters, which include both the regression + coefficients and the cdf of the unspecified reference distribution, are estimated + by maximizing a semiparametric likelihood. Regression coefficients are estimated + with no loss of efficiency, i.e. the asymptotic variance is the same as if the + true exponential family distribution were known. + Huang (2014) . + Huang and Rathouz (2012) . + Rathouz and Gao (2008) . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gldrm + url_git: '' +glinternet: + version: 1.0.12 + title: |- + Learning Interactions via Hierarchical Group-Lasso + Regularization + maintainer: Michael Lim + description: 'Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models + that satisfy strong hierarchy: if an interaction coefficient is estimated to be + nonzero, then its two associated main effects also have nonzero estimated coefficients. + Accommodates categorical variables (factors) with arbitrary numbers of levels, + continuous variables, and combinations thereof. Implements the machinery described + in the paper "Learning interactions via hierarchical group-lasso regularization" + (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015) .' + date_publication: '2021-09-03' + bug_reports: '' + url: http://web.stanford.edu/~hastie/Papers/glinternet_jcgs.pdf + url_cran: https://CRAN.R-project.org/package=glinternet + url_git: '' +glinvci: + version: 1.2.4 + title: Phylogenetic Comparative Methods with Uncertainty Estimates + maintainer: Woodrow Kiang + description: A framework for analytically computing the asymptotic confidence intervals + and maximum-likelihood estimates of a class of continuous-time Gaussian branching + processes defined by Mitov V, Bartoszek K, Asimomitis G, Stadler T (2019) . + The class of model includes the widely used Ornstein-Uhlenbeck and Brownian motion + branching processes. The framework is designed to be flexible enough so that the + users can easily specify their own sub-models, or re-parameterizations, and obtain + the maximum-likelihood estimates and confidence intervals of their own custom + models. + date_publication: '2024-04-18' + bug_reports: '' + url: https://git.sr.ht/~hckiang/glinvci + url_cran: https://CRAN.R-project.org/package=glinvci + url_git: https://github.com/hckiang/glinvci +gllm: + version: '0.38' + title: Generalised log-Linear Model + maintainer: David Duffy + description: |- + Routines for log-linear models of incomplete contingency tables, + including some latent class models, via EM and Fisher scoring + approaches. Allows bootstrapping. See Espeland and Hui (1987) + for general approach. + date_publication: '2022-10-18' + bug_reports: '' + url: https://genepi.qimr.edu.au/Staff/davidD/#loglin + url_cran: https://CRAN.R-project.org/package=gllm + url_git: '' +gllvm: + version: '2.0' + title: Generalized Linear Latent Variable Models + maintainer: Jenni Niku + description: |- + Analysis of multivariate data using generalized linear latent variable models (gllvm). + Estimation is performed using either the Laplace method, variational approximations, or extended variational approximations, implemented via TMB (Kristensen et al. (2016), ). + date_publication: '2024-11-26' + bug_reports: https://github.com/JenniNiku/gllvm/issues + url: https://jenniniku.github.io/gllvm/ + url_cran: https://CRAN.R-project.org/package=gllvm + url_git: https://github.com/JenniNiku/gllvm +glm.deploy: + version: 1.0.4 + title: '''C'' and ''Java'' Source Code Generator for Fitted Glm Objects' + maintainer: Oscar Castro-Lopez + description: |- + Provides two functions that generate source code implementing the predict + function of fitted glm objects. In this version, code can be generated for either 'C' + or 'Java'. The idea is to provide a tool for the easy and fast deployment of glm + predictive models into production. The source code generated by this package implements + two function/methods. One of such functions implements the equivalent to + predict(type="response"), while the second implements predict(type="link"). Source code + is written to disk as a .c or .java file in the specified path. In the case of c, an .h + file is also generated. + date_publication: '2018-03-09' + bug_reports: https://github.com/oscarcastrolopez/glm.deploy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glm.deploy + url_git: https://github.com/oscarcastrolopez/glm.deploy +glm.predict: + version: 4.3-0 + title: Predicted Values and Discrete Changes for Regression Models + maintainer: Benjamin E. Schlegel + description: "Functions to calculate predicted values and the difference between\nthe + two cases with confidence interval for lm() [linear model], glm() [generalized + linear model], glm.nb() [negative binomial model],\npolr() [ordinal logistic model], + vglm() [generalized ordinal logistic model],\tmultinom() [multinomial model], + tobit() [tobit model],\nsvyglm() [survey-weighted generalised linear models] and + lmer() [linear multilevel models] using Monte Carlo simulations or bootstrap. + Reference: Bennet A. Zelner (2009) ." + date_publication: '2024-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glm.predict + url_git: https://github.com/benjaminschlegel/glm.predict/ +glm2: + version: 1.2.1 + title: Fitting Generalized Linear Models + maintainer: Mark W. Donoghoe + description: Fits generalized linear models using the same model specification as + glm in the stats package, but with a modified default fitting method that provides + greater stability for models that may fail to converge using glm. + date_publication: '2018-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glm2 + url_git: '' +GLMaSPU: + version: '1.0' + title: |- + An Adaptive Test on High Dimensional Parameters in Generalized + Linear Models + maintainer: Chong Wu + description: 'Several tests for high dimensional generalized linear models have + been proposed recently. In this package, we implemented a new test called adaptive sum + of powered score (aSPU) for high dimensional generalized linear models, which + is often more powerful than the existing methods in a wide scenarios. We also + implemented permutation based version of several existing methods for research + purpose. We recommend users use the aSPU test for their real testing problem. + You can learn more about the tests implemented in the package via the following + papers: 1. Pan, W., Kim, J., Zhang, Y., Shen, X. and Wei, P. (2014) + A powerful and adaptive association test for rare variants, Genetics, 197(4). + 2. Guo, B., and Chen, S. X. (2016) . Tests for high dimensional + generalized linear models. Journal of the Royal Statistical Society: Series B. + 3. Goeman, J. J., Van Houwelingen, H. C., and Finos, L. (2011) . + Testing against a high-dimensional alternative in the generalized linear model: + asymptotic type I error control. Biometrika, 98(2).' + date_publication: '2016-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLMaSPU + url_git: '' +glmbb: + version: 0.5-1 + title: |- + All Hierarchical or Graphical Models for Generalized Linear + Model + maintainer: Charles J. Geyer + description: |- + Find all hierarchical models of specified generalized linear + model with information criterion (AIC, BIC, or AICc) within specified + cutoff of minimum value. Alternatively, find all such graphical models. + Use branch and bound algorithm so we do not have to fit all models. + date_publication: '2020-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmbb + url_git: https://github.com/cjgeyer/glmbb +glmc: + version: 0.3-1 + title: Fitting Generalized Linear Models Subject to Constraints + maintainer: Sanjay Chaudhuri + description: Fits generalized linear models where the parameters are subject to + linear constraints. The model is specified by giving a symbolic description of + the linear predictor, a description of the error distribution, and a matrix of + constraints on the parameters. + date_publication: '2018-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmc + url_git: '' +GLMcat: + version: 0.2.7 + title: Generalized Linear Models for Categorical Responses + maintainer: Lorena León + description: In statistical modeling, there is a wide variety of regression models + for categorical dependent variables (nominal or ordinal data); yet, there is no + software embracing all these models together in a uniform and generalized format. + Following the methodology proposed by Peyhardi, Trottier, and Guédon (2015) , + we introduce 'GLMcat', an R package to estimate generalized linear models implemented + under the unified specification (r, F, Z). Where r represents the ratio of probabilities + (reference, cumulative, adjacent, or sequential), F the cumulative cdf function + for the linkage, and Z, the design matrix. + date_publication: '2024-09-20' + bug_reports: https://github.com/ylleonv/GLMcat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GLMcat + url_git: https://github.com/ylleonv/GLMcat +glme: + version: 0.1.0 + title: Generalized Linear Mixed Effects Models + maintainer: Mustafa Cavus + description: Provides Generalized Inferences based on exact distributions and exact + probability statements for mixed effect models, provided by such papers as Weerahandi + and Yu (2020) under the widely used Compound + Symmetric Covariance structure. The package returns the estimation of the coefficients + in random and fixed part of the mixed models by generalized inference. + date_publication: '2021-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glme + url_git: '' +glmertree: + version: 0.2-6 + title: Generalized Linear Mixed Model Trees + maintainer: Marjolein Fokkema + description: |- + Recursive partitioning based on (generalized) linear mixed models + (GLMMs) combining lmer()/glmer() from 'lme4' and lmtree()/glmtree() from + 'partykit'. The fitting algorithm is described in more detail in Fokkema, + Smits, Zeileis, Hothorn & Kelderman (2018; ). + For detecting and modeling subgroups in growth curves with GLMM trees see + Fokkema & Zeileis (2024; ). + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmertree + url_git: '' +glmglrt: + version: 0.2.2 + title: GLRT P-Values in Generalized Linear Models + maintainer: André GILLIBERT + description: |- + Provides functions to compute Generalized Likelihood Ratio Tests (GLRT) also known as Likelihood Ratio Tests (LRT) and Rao's score tests of simple + and complex contrasts of Generalized Linear Models (GLMs). It provides the same interface as summary.glm(), adding GLRT P-values, + less biased than Wald's P-values and consistent with profile-likelihood confidence interval generated by confint(). + See Wilks (1938) for the LRT chi-square approximation. + See Rao (1948) for Rao's score test. + See Wald (1943) for Wald's test. + date_publication: '2020-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmglrt + url_git: '' +glmlep: + version: '0.2' + title: Fit GLM with LEP-Based Penalized Maximum Likelihood + maintainer: Canhong Wen + description: |- + Efficient algorithms for fitting regularization paths for + linear or logistic regression models penalized by LEP. + date_publication: '2019-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmlep + url_git: '' +glmm: + version: 1.4.5 + title: |- + Generalized Linear Mixed Models via Monte Carlo Likelihood + Approximation + maintainer: Christina Knudson + description: Approximates the likelihood of a generalized linear mixed model using + Monte Carlo likelihood approximation. Then maximizes the likelihood approximation + to return maximum likelihood estimates, observed Fisher information, and other + model information. + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmm + url_git: '' +glmm.hp: + version: 0.1-7 + title: |- + Hierarchical Partitioning of Marginal R2 for Generalized + Mixed-Effect Models + maintainer: Jiangshan Lai + description: 'Conducts hierarchical partitioning to calculate individual contributions + of each predictor (fixed effects) towards marginal R2 for generalized linear mixed-effect + model (including lm, glm and glmm) based on output of r.squaredGLMM() in ''MuMIn'', + applying the algorithm of Lai J.,Zou Y., Zhang S.,Zhang X.,Mao L.(2022)glmm.hp: + an R package for computing individual effect of predictors in generalized linear + mixed models.Journal of Plant Ecology,15(6)1302-1307.' + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmm.hp + url_git: https://github.com/laijiangshan/glmm.hp +GLMMadaptive: + version: 0.9-1 + title: |- + Generalized Linear Mixed Models using Adaptive Gaussian + Quadrature + maintainer: Dimitris Rizopoulos + description: |- + Fits generalized linear mixed models for a single grouping factor under + maximum likelihood approximating the integrals over the random effects with an + adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) + . + date_publication: '2023-10-17' + bug_reports: https://github.com/drizopoulos/GLMMadaptive/issues + url: https://drizopoulos.github.io/GLMMadaptive/ + url_cran: https://CRAN.R-project.org/package=GLMMadaptive + url_git: https://github.com/drizopoulos/GLMMadaptive +GLMMcosinor: + version: 0.2.1 + title: Fit a Cosinor Model Using a Generalized Mixed Modeling Framework + maintainer: Rex Parsons + description: |- + Allows users to fit a cosinor model using the 'glmmTMB' framework. + This extends on existing cosinor modeling packages, including 'cosinor' + and 'circacompare', by including a wide range of available link functions + and the capability to fit mixed models. The cosinor model is described by + Cornelissen (2014) . + date_publication: '2024-11-01' + bug_reports: https://github.com/ropensci/GLMMcosinor/issues + url: https://docs.ropensci.org/GLMMcosinor/ + url_cran: https://CRAN.R-project.org/package=GLMMcosinor + url_git: https://github.com/ropensci/GLMMcosinor +glmmEP: + version: 1.0-3.1 + title: |- + Generalized Linear Mixed Model Analysis via Expectation + Propagation + maintainer: Matt P. Wand + description: Approximate frequentist inference for generalized linear mixed model + analysis with expectation propagation used to circumvent the need for multivariate + integration. In this version, the random effects can be any reasonable dimension. + However, only probit mixed models with one level of nesting are supported. The + methodology is described in Hall, Johnstone, Ormerod, Wand and Yu (2018) . + date_publication: '2019-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmmEP + url_git: '' +glmmfields: + version: 0.1.8 + title: |- + Generalized Linear Mixed Models with Robust Random Fields for + Spatiotemporal Modeling + maintainer: Sean C. Anderson + description: |- + Implements Bayesian spatial and spatiotemporal + models that optionally allow for extreme spatial deviations through + time. 'glmmfields' uses a predictive process approach with random + fields implemented through a multivariate-t distribution instead of + the usual multivariate normal. Sampling is conducted with 'Stan'. + References: Anderson and Ward (2019) . + date_publication: '2023-10-20' + bug_reports: https://github.com/seananderson/glmmfields/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glmmfields + url_git: https://github.com/seananderson/glmmfields +glmMisrep: + version: 0.1.1 + title: Generalized Linear Models Adjusting for Misrepresentation + maintainer: Patrick Rafael + description: Fit Generalized Linear Models to continuous and count outcomes, as + well as estimate the prevalence of misrepresentation of an important binary predictor. + Misrepresentation typically arises when there is an incentive for the binary factor + to be misclassified in one direction (e.g., in insurance settings where policy + holders may purposely deny a risk status in order to lower the insurance premium). + This is accomplished by treating a subset of the response variable as resulting + from a mixture distribution. Model parameters are estimated via the Expectation + Maximization algorithm and standard errors of the estimates are obtained from + closed forms of the Observed Fisher Information. For an introduction to the models + and the misrepresentation framework, see Xia et. al., (2023) . + date_publication: '2024-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmMisrep + url_git: '' +glmmLasso: + version: 1.6.3 + title: |- + Variable Selection for Generalized Linear Mixed Models by + L1-Penalized Estimation + maintainer: Andreas Groll + description: |- + A variable selection approach for generalized linear mixed models by L1-penalized estimation is provided, + see Groll and Tutz (2014) . + See also Groll and Tutz (2017) for discrete survival models including heterogeneity. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmmLasso + url_git: '' +glmmML: + version: 1.1.7 + title: Generalized Linear Models with Clustering + maintainer: Göran Broström + description: |- + Binomial and Poisson regression for clustered data, fixed + and random effects with bootstrapping. + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmmML + url_git: '' +glmmPen: + version: 1.5.4.8 + title: |- + High Dimensional Penalized Generalized Linear Mixed Models + (pGLMM) + maintainer: Hillary Heiling + description: |- + Fits high dimensional penalized generalized linear + mixed models using + the Monte Carlo Expectation Conditional Minimization (MCECM) algorithm. + The purpose of the package is to perform variable selection on both the fixed and + random effects simultaneously for generalized linear mixed models. + The package supports fitting of Binomial, Gaussian, and Poisson data with canonical links, and + supports penalization using the MCP, SCAD, or LASSO penalties. The MCECM algorithm + is described in Rashid et al. (2020) . + The techniques used in the minimization portion of the procedure (the M-step) are + derived from the procedures of the 'ncvreg' package (Breheny and Huang (2011) + ) and 'grpreg' package (Breheny and Huang (2015) + ), with + appropriate modifications to account for the estimation and penalization of + the random effects. The 'ncvreg' and 'grpreg' packages also describe the MCP, SCAD, + and LASSO penalties. + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmmPen + url_git: '' +glmmrBase: + version: 0.11.2 + title: Generalised Linear Mixed Models in R + maintainer: Sam Watson + description: |- + Specification, analysis, simulation, and fitting of generalised linear mixed models. + Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models, + non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily, + robust and bias-corrected standard error estimation, power calculation, data simulation, and more. + See for a detailed manual. + date_publication: '2024-12-12' + bug_reports: https://github.com/samuel-watson/glmmrBase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glmmrBase + url_git: https://github.com/samuel-watson/glmmrBase +glmmrOptim: + version: 0.3.6 + title: |- + Approximate Optimal Experimental Designs Using Generalised + Linear Mixed Models + maintainer: Sam Watson + description: |- + Optimal design analysis algorithms for any study design that can be represented or + modelled as a generalised linear mixed model including cluster randomised trials, + cohort studies, spatial and temporal epidemiological studies, and split-plot designs. + See for a + detailed manual on model specification. A detailed discussion of the methods in this + package can be found in Watson, Hemming, and Girling (2023) . + date_publication: '2024-12-17' + bug_reports: https://github.com/samuel-watson/glmmrOptim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glmmrOptim + url_git: https://github.com/samuel-watson/glmmrOptim +GLMMRR: + version: 0.5.0 + title: |- + Generalized Linear Mixed Model (GLMM) for Binary Randomized + Response Data + maintainer: Konrad Klotzke + description: |- + Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data. + Includes Cauchit, Compl. Log-Log, Logistic, and Probit link functions for Bernoulli Distributed RR data. + RR Designs: Warner, Forced Response, Unrelated Question, Kuk, Crosswise, and Triangular. + Reference: Fox, J-P, Veen, D. and Klotzke, K. (2018). Generalized Linear Mixed Models for Randomized Responses. Methodology. . + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLMMRR + url_git: '' +GLMMselect: + version: 1.2.0 + title: Bayesian Model Selection for Generalized Linear Mixed Models + maintainer: Shuangshuang Xu + description: |- + A Bayesian model selection approach for generalized linear mixed models. + Currently, 'GLMMselect' can be used for Poisson GLMM and Bernoulli GLMM. 'GLMMselect' can select fixed effects and random effects simultaneously. + Covariance structures for the random effects are a product of a unknown scalar and a known semi-positive definite matrix. + 'GLMMselect' can be widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics. + 'GLMMselect' is based on Xu, Ferreira, Porter, and Franck (202X), Bayesian Model Selection Method for Generalized Linear Mixed Models, Biometrics, under review. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLMMselect + url_git: '' +glmmSeq: + version: 0.5.5 + title: |- + General Linear Mixed Models for Gene-Level Differential + Expression + maintainer: Myles Lewis + description: 'Using mixed effects models to analyse longitudinal gene expression + can highlight differences between sample groups over time. The most widely used + differential gene expression tools are unable to fit linear mixed effect models, + and are less optimal for analysing longitudinal data. This package provides negative + binomial and Gaussian mixed effects models to fit gene expression and other biological + data across repeated samples. This is particularly useful for investigating changes + in RNA-Sequencing gene expression between groups of individuals over time, as + described in: Rivellese, F., Surace, A. E., Goldmann, K., Sciacca, E., Cubuk, + C., Giorli, G., ... Lewis, M. J., & Pitzalis, C. (2022) Nature medicine .' + date_publication: '2022-10-08' + bug_reports: https://github.com/myles-lewis/glmmSeq/issues + url: https://myles-lewis.github.io/glmmSeq/ + url_cran: https://CRAN.R-project.org/package=glmmSeq + url_git: https://github.com/myles-lewis/glmmSeq +glmmTMB: + version: 1.1.10 + title: Generalized Linear Mixed Models using Template Model Builder + maintainer: Mollie Brooks + description: |- + Fit linear and generalized linear mixed models with various + extensions, including zero-inflation. The models are fitted using maximum + likelihood estimation via 'TMB' (Template Model Builder). Random effects are + assumed to be Gaussian on the scale of the linear predictor and are integrated + out using the Laplace approximation. Gradients are calculated using automatic + differentiation. + date_publication: '2024-09-26' + bug_reports: https://github.com/glmmTMB/glmmTMB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glmmTMB + url_git: https://github.com/glmmTMB/glmmTMB +glmnet: + version: 4.1-8 + title: Lasso and Elastic-Net Regularized Generalized Linear Models + maintainer: Trevor Hastie + description: Extremely efficient procedures for fitting the entire lasso or elastic-net + regularization path for linear regression, logistic and multinomial regression + models, Poisson regression, Cox model, multiple-response Gaussian, and the grouped + multinomial regression; see and . + There are two new and important additions. The family argument can be a GLM family + object, which opens the door to any programmed family (). + This comes with a modest computational cost, so when the built-in families suffice, + they should be used instead. The other novelty is the relax option, which refits + each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate + descent in a path-wise fashion, as described in the papers cited. + date_publication: '2023-08-22' + bug_reports: '' + url: https://glmnet.stanford.edu + url_cran: https://CRAN.R-project.org/package=glmnet + url_git: '' +glmnetcr: + version: 1.0.6 + title: |- + Fit a Penalized Constrained Continuation Ratio Model for + Predicting an Ordinal Response + maintainer: Kellie J. Archer + description: |- + Penalized methods are useful for fitting over-parameterized models. This package includes functions for restructuring an ordinal + response dataset for fitting continuation ratio models for datasets where the number of covariates exceeds the sample size or when + there is collinearity among the covariates. The 'glmnet' fitting algorithm is used to fit the continuation ratio model after data restructuring. + date_publication: '2020-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmnetcr + url_git: '' +glmnetr: + version: 0.5-5 + title: |- + Nested Cross Validation for the Relaxed Lasso and Other Machine + Learning Models + maintainer: Walter K Kremers + description: |- + Cross validation informed Relaxed LASSO, Artificial Neural Network (ANN), gradient boosting machine ('xgboost'), Random Forest ('RandomForestSRC'), Oblique Random Forest ('aorsf'), Recursive Partitioning ('RPART') or step wise regression models are fit. Cross validation leave out samples (leading to nested cross validation) or bootstrap out-of-bag samples are used to evaluate and compare performances between these models with results presented in tabular or graphical means. Calibration plots can also be generated, again based upon (outer nested) cross validation or bootstrap leave out (out of bag) samples. + For some datasets, for example when the design matrix is not of full rank, 'glmnet' may have very long run times when fitting the relaxed lasso model, from our experience when fitting Cox models on data with many predictors and many patients, making it difficult to get solutions from either glmnet() or cv.glmnet(). This may be remedied by using the 'path=TRUE' option when calling glmnet() and cv.glmnet(). Within the glmnetr package the approach of path=TRUE is taken by default. + When fitting not a relaxed lasso model but an elastic-net model, then the R-packages 'nestedcv' , 'glmnetSE' or others may provide greater functionality when performing a nested CV. + Use of the 'glmnetr' has many similarities to the 'glmnet' package and it is recommended that the user of 'glmnetr' also become familiar with the 'glmnet' package , with the "An Introduction to 'glmnet'" and "The Relaxed Lasso" being especially useful in this regard. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmnetr + url_git: '' +glmnetSE: + version: 0.0.1 + title: |- + Add Nonparametric Bootstrap SE to 'glmnet' for Selected + Coefficients (No Shrinkage) + maintainer: Sebastian Bahr + description: |- + Builds a LASSO, Ridge, or Elastic Net model with 'glmnet' or + 'cv.glmnet' with bootstrap inference statistics (SE, CI, and p-value) + for selected coefficients with no shrinkage applied for them. Model + performance can be evaluated on test data and an automated alpha + selection is implemented for Elastic Net. Parallelized computation is + used to speed up the process. The methods are described in Friedman et + al. (2010) and Simon et al. (2011) + . + date_publication: '2021-11-05' + bug_reports: https://github.com/sebastianbahr/glmnetSE/blob/main/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glmnetSE + url_git: https://github.com/sebastianbahr/glmnetSE +glmnetUtils: + version: 1.1.9 + title: Utilities for 'Glmnet' + maintainer: Hong Ooi + description: |- + Provides a formula interface for the 'glmnet' package for + elasticnet regression, a method for cross-validating the alpha parameter, + and other quality-of-life tools. + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmnetUtils + url_git: https://github.com/hongooi73/glmnetUtils +GLMpack: + version: 0.1.0 + title: |- + Data and Code to Accompany Generalized Linear Models, 2nd + Edition + maintainer: Michelle Torres + description: |- + Contains all the data and functions used in Generalized + Linear Models, 2nd edition, by Jeff Gill and Michelle Torres. Examples to create + all models, tables, and plots are included for each data set. + date_publication: '2019-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLMpack + url_git: '' +glmpath: + version: '0.98' + title: |- + L1 Regularization Path for Generalized Linear Models and Cox + Proportional Hazards Model + maintainer: Mee Young Park + description: A path-following algorithm for L1 regularized generalized linear models + and Cox proportional hazards model. + date_publication: '2018-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmpath + url_git: '' +glmpathcr: + version: 1.0.10 + title: |- + Fit a Penalized Continuation Ratio Model for Predicting an + Ordinal Response + maintainer: Kellie J. Archer + description: Provides a function for fitting a penalized constrained continuation + ratio model using the glmpath algorithm and methods for extracting coefficient + estimates, predicted class, class probabilities, and plots as described by Archer + and Williams (2012) . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmpathcr + url_git: '' +glmpca: + version: 0.2.0 + title: Dimension Reduction of Non-Normally Distributed Data + maintainer: F. William Townes + description: |- + Implements a generalized version of principal components analysis + (GLM-PCA) for dimension reduction of non-normally distributed data such as + counts or binary matrices. + Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) . + Townes FW (2019) . + date_publication: '2020-07-18' + bug_reports: https://github.com/willtownes/glmpca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glmpca + url_git: https://github.com/willtownes/glmpca +glmpermu: + version: 0.0.1 + title: Permutation-Based Inference for Generalized Linear Models + maintainer: Xuekui Zhang + description: In practical applications, the assumptions underlying generalized linear + models frequently face violations, including incorrect specifications of the outcome + variable's distribution or omitted predictors. These deviations can render the + results of standard generalized linear models unreliable. As the sample size increases, + what might initially appear as minor issues can escalate to critical concerns. + To address these challenges, we adopt a permutation-based inference method tailored + for generalized linear models. This approach offers robust estimations that effectively + counteract the mentioned problems, and its effectiveness remains consistent regardless + of the sample size. + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmpermu + url_git: '' +GLMsData: + version: '1.4' + title: Generalized Linear Model Data Sets + maintainer: Peter K. Dunn + description: Data sets from the book Generalized Linear Models with Examples in + R by Dunn and Smyth. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLMsData + url_git: '' +GlmSimulatoR: + version: 1.0.0 + title: Creates Ideal Data for Generalized Linear Models + maintainer: Greg McMahan + description: |- + Creates ideal data for all distributions in the generalized + linear model framework. + date_publication: '2023-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GlmSimulatoR + url_git: '' +glmtlp: + version: 2.0.2 + title: Generalized Linear Models with Truncated Lasso Penalty + maintainer: Yu Yang + description: Extremely efficient procedures for fitting regularization path with + l0, l1, and truncated lasso penalty for linear regression and logistic regression + models. This version is a completely new version compared with our previous version, + which was mainly based on R. New core algorithms are developed and are now written + in C++ and highly optimized. + date_publication: '2024-10-02' + bug_reports: '' + url: https://yuyangyy.com/glmtlp/ + url_cran: https://CRAN.R-project.org/package=glmtlp + url_git: '' +glmtoolbox: + version: 0.1.12 + title: Set of Tools to Data Analysis using Generalized Linear Models + maintainer: Luis Hernando Vanegas + description: 'Set of tools for the statistical analysis of data using: (1) normal + linear models; (2) generalized linear models; (3) negative binomial regression + models as alternative to the Poisson regression models under the presence of overdispersion; + (4) beta-binomial and random-clumped binomial regression models as alternative + to the binomial regression models under the presence of overdispersion; (5) Zero-inflated + and zero-altered regression models to deal with zero-excess in count data; (6) + generalized nonlinear models; (7) generalized estimating equations for cluster + correlated data.' + date_publication: '2024-07-25' + bug_reports: https://github.com/lhvanegasp/glmtoolbox/issues + url: https://mlgs.netlify.app/ + url_cran: https://CRAN.R-project.org/package=glmtoolbox + url_git: '' +glmtrans: + version: 2.1.0 + title: Transfer Learning under Regularized Generalized Linear Models + maintainer: Ye Tian + description: We provide an efficient implementation for two-step multi-source transfer + learning algorithms in high-dimensional generalized linear models (GLMs). The + elastic-net penalized GLM with three popular families, including linear, logistic + and Poisson regression models, can be fitted. To avoid negative transfer, a transferable + source detection algorithm is proposed. We also provides visualization for the + transferable source detection results. The details of methods can be found in + "Tian, Y., & Feng, Y. (2023). Transfer learning under high-dimensional generalized + linear models. Journal of the American Statistical Association, 118(544), 2684-2697.". + date_publication: '2025-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmtrans + url_git: '' +glmtree: + version: 0.3.1 + title: Logistic Regression Trees + maintainer: Adrien Ehrhardt + description: A logistic regression tree is a decision tree with logistic regressions + at its leaves. A particular stochastic expectation maximization algorithm is used + to draw a few good trees, that are then assessed via the user's criterion of choice + among BIC / AIC / test set Gini. The formal development is given in a PhD chapter, + see Ehrhardt (2019) . + date_publication: '2024-03-06' + bug_reports: https://github.com/adimajo/glmtree/issues + url: https://adimajo.github.io + url_cran: https://CRAN.R-project.org/package=glmtree + url_git: '' +glmulti: + version: 1.0.8 + title: Model Selection and Multimodel Inference Made Easy + maintainer: Vincent Calcagno + description: |- + Automated model selection and model-averaging. Provides a + wrapper for glm and other functions, automatically generating + all possible models (under constraints set by the user) with + the specified response and explanatory variables, and finding + the best models in terms of some Information Criterion (AIC, + AICc or BIC). Can handle very large numbers of candidate + models. Features a Genetic Algorithm to find the best models + when an exhaustive screening of the candidates is not feasible. + date_publication: '2020-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmulti + url_git: '' +glmvsd: + version: '1.5' + title: |- + Variable Selection Deviation Measures and Instability Tests for + High-Dimensional Generalized Linear Models + maintainer: Yi Yang + description: Variable selection deviation (VSD) measures and instability tests for + high-dimensional model selection methods such as LASSO, SCAD and MCP, etc., to + decide whether the sparse patterns identified by those methods are reliable. + date_publication: '2022-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmvsd + url_git: https://github.com/emeryyi/glmvsd +glmx: + version: 0.2-1 + title: Generalized Linear Models Extended + maintainer: Achim Zeileis + description: |- + Extended techniques for generalized linear models (GLMs), especially for binary responses, + including parametric links and heteroscedastic latent variables. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmx + url_git: '' +glmxdiag: + version: 1.0.0 + title: |- + A Collection of Graphic Tools for GLM Diagnostics and some + Extensions + maintainer: Giuseppe Reale + description: Provides diagnostic graphic tools for GLMs, beta-binomial regression + model (estimated by 'VGAM' package), beta regression model (estimated by 'betareg' + package) and negative binomial regression model (estimated by 'MASS' package). + Since most of functions implemented in 'glmxdiag' already exist in other packages, + the aim is to provide the user unique functions that work on almost all regression + models previously specified. Details about some of the implemented functions can + be found in Brown (1992) , Dunn and Smyth (1996) , + O'Hara Hines and Carter (1993) , Wang (1985) . + date_publication: '2022-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glmxdiag + url_git: '' +globalKinhom: + version: 0.1.9 + title: |- + Inhomogeneous K- And Pair Correlation Functions Using Global + Estimators + maintainer: Thomas Shaw + description: |- + Second-order summary statistics K- and pair-correlation functions describe + interactions in point pattern data. This package provides computations to estimate those + statistics on inhomogeneous point processes, using the methods of + in T Shaw, J Møller, R Waagepetersen, 2020 . + date_publication: '2024-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=globalKinhom + url_git: '' +GlobalOptions: + version: 0.1.2 + title: Generate Functions to Get or Set Global Options + maintainer: Zuguang Gu + description: |- + It provides more configurations on the option values such as validation + and filtering on the values, making options invisible or private. + date_publication: '2020-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GlobalOptions + url_git: https://github.com/jokergoo/GlobalOptions +globalOptTests: + version: '1.1' + title: |- + Objective functions for benchmarking the performance of global + optimization algorithms + maintainer: Katharine Mullen + description: This package makes available 50 objective functions for benchmarking + the performance of global optimization algorithms + date_publication: '2014-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=globalOptTests + url_git: '' +globals: + version: 0.16.3 + title: Identify Global Objects in R Expressions + maintainer: Henrik Bengtsson + description: |- + Identifies global ("unknown" or "free") objects in R expressions + by code inspection using various strategies (ordered, liberal, or + conservative). The objective of this package is to make it as simple as + possible to identify global objects for the purpose of exporting them in + parallel, distributed compute environments. + date_publication: '2024-03-08' + bug_reports: https://github.com/HenrikBengtsson/globals/issues + url: https://globals.futureverse.org + url_cran: https://CRAN.R-project.org/package=globals + url_git: https://github.com/HenrikBengtsson/globals +globaltrends: + version: 0.0.14 + title: Download and Measure Global Trends Through Google Search Volumes + maintainer: Harald Puhr + description: |- + Google offers public access to global search volumes from its + search engine through the Google Trends portal. The package downloads + these search volumes provided by Google Trends and uses them to + measure and analyze the distribution of search scores across countries + or within countries. The package allows researchers and analysts to + use these search scores to investigate global trends based on patterns + within these scores. This offers insights such as degree of + internationalization of firms and organizations or dissemination of + political, social, or technological trends across the globe or within + single countries. An outline of the package's methodological + foundations and potential applications is available as a working + paper: . + date_publication: '2023-03-06' + bug_reports: https://github.com/ha-pu/globaltrends/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=globaltrends + url_git: https://github.com/ha-pu/globaltrends/ +globe: + version: 1.2-0 + title: Plot 2D and 3D Views of the Earth, Including Major Coastline + maintainer: Adrian Baddeley + description: Basic functions for plotting 2D and 3D views of a sphere, by default + the Earth with its major coastline, and additional lines and points. + date_publication: '2017-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=globe + url_git: '' +glober: + version: '1.0' + title: Estimating Functions with Multivariate B-Splines + maintainer: Mary E. Savino + description: Generalized LassO applied to knot selection in multivariate B-splinE + Regression (GLOBER) implements a novel approach for estimating functions in a + multivariate nonparametric regression model based on an adaptive knot selection + for B-splines using the Generalized Lasso. For further details we refer the reader + to the paper Savino, M. E. and Lévy-Leduc, C. (2023), . + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glober + url_git: '' +glogis: + version: 1.0-2 + title: Fitting and Testing Generalized Logistic Distributions + maintainer: Achim Zeileis + description: |- + Tools for the generalized logistic distribution (Type I, + also known as skew-logistic distribution), encompassing + basic distribution functions (p, q, d, r, score), maximum + likelihood estimation, and structural change methods. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glogis + url_git: '' +glossa: + version: 1.0.0 + title: |- + User-Friendly 'shiny' App for Bayesian Species Distribution + Models + maintainer: Jorge Mestre-Tomás + description: |- + A user-friendly 'shiny' application for Bayesian machine + learning analysis of marine species distributions. GLOSSA (Global + Species Spatiotemporal Analysis) uses Bayesian Additive Regression + Trees (BART; Chipman, George, and McCulloch (2010) + ) to model species distributions with + intuitive workflows for data upload, processing, model fitting, and + result visualization. It supports presence-absence and presence-only + data (with pseudo-absence generation), spatial thinning, + cross-validation, and scenario-based projections. GLOSSA is designed + to facilitate ecological research by providing easy-to-use tools for + analyzing and visualizing marine species distributions across + different spatial and temporal scales. + date_publication: '2024-10-15' + bug_reports: https://github.com/iMARES-group/glossa/issues + url: https://iMARES-group.github.io/glossa/ + url_cran: https://CRAN.R-project.org/package=glossa + url_git: https://github.com/iMARES-group/glossa +glossary: + version: 1.0.0 + title: Glossaries for Markdown and Quarto Documents + maintainer: Lisa DeBruine + description: Add glossaries to markdown and quarto documents by tagging individual + words. Definitions can be provided inline or in a separate file. + date_publication: '2023-05-30' + bug_reports: https://github.com/debruine/glossary/issues + url: https://debruine.github.io/glossary/ + url_cran: https://CRAN.R-project.org/package=glossary + url_git: https://github.com/debruine/glossary +glossr: + version: 0.8.0 + title: Use Interlinear Glosses in R Markdown + maintainer: Mariana Montes + description: |- + Read examples with interlinear glosses from files + or from text and print them in a way compatible with both + Latex and HTML outputs. + date_publication: '2024-05-19' + bug_reports: '' + url: https://montesmariana.github.io/glossr/ + url_cran: https://CRAN.R-project.org/package=glossr + url_git: https://github.com/montesmariana/glossr +glow: + version: 0.13.0 + title: Make Plots that Glow + maintainer: Travers Ching + description: Provides a framework for creating plots with glowing points. + date_publication: '2024-09-25' + bug_reports: https://github.com/traversc/glow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=glow + url_git: https://github.com/traversc/glow +glpkAPI: + version: 1.3.4 + title: R Interface to C API of GLPK + maintainer: Mihail Anton + description: R Interface to C API of GLPK, depends on GLPK Version >= 4.42. + date_publication: '2022-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glpkAPI + url_git: '' +gLRTH: + version: 0.2.0 + title: Genome-Wide Association and Linkage Analysis under Heterogeneity + maintainer: Xiaoxia Han + description: Likelihood ratio tests for genome-wide association and genome-wide + linkage analysis under heterogeneity. + date_publication: '2018-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gLRTH + url_git: '' +GLSME: + version: 1.0.5 + title: Generalized Least Squares with Measurement Error + maintainer: Krzysztof Bartoszek + description: Performs linear regression with correlated predictors, responses and + correlated measurement errors in predictors and responses, correcting for biased + caused by these. + date_publication: '2019-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GLSME + url_git: '' +glue: + version: 1.8.0 + title: Interpreted String Literals + maintainer: Jennifer Bryan + description: |- + An implementation of interpreted string literals, inspired by + Python's Literal String Interpolation + and Docstrings + and Julia's Triple-Quoted + String Literals + . + date_publication: '2024-09-30' + bug_reports: https://github.com/tidyverse/glue/issues + url: https://glue.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=glue + url_git: https://github.com/tidyverse/glue +gluedown: + version: 1.0.9 + title: Wrap Vectors in Markdown Formatting + maintainer: Kiernan Nicholls + description: |- + Ease the transition between R vectors and markdown text. With + 'gluedown' and 'rmarkdown', users can create traditional vectors in R, + glue those strings together with the markdown syntax, and print those + formatted vectors directly to the document. This package primarily + uses GitHub Flavored Markdown (GFM), an offshoot of the unambiguous + CommonMark specification by John MacFarlane (2019) + . + date_publication: '2024-03-11' + bug_reports: https://github.com/k5cents/gluedown/issues + url: https://k5cents.github.io/gluedown/ + url_cran: https://CRAN.R-project.org/package=gluedown + url_git: https://github.com/k5cents/gluedown/ +gluvarpro: + version: '7.0' + title: |- + Glucose Variability Measures from Continuous Glucose Monitoring + Data + maintainer: Sergio Contador + description: |- + Calculate different glucose variability measures, + including average measures of glycemia, measures of glycemic variability and + measures of glycemic risk, from continuous glucose monitoring data. + Boris P. Kovatchev, Erik Otto, Daniel Cox, Linda Gonder-Frederick, and William Clarke (2006) . + Jean-Pierre Le Floch, Philippe Escuyer, Eric Baudin, Dominique Baudon, and Leon Perlemuter (1990) . + C.M. McDonnell, S.M. Donath, S.I. Vidmar, G.A. Werther, and F.J. Cameron (2005) . + Everitt, Brian (1998) . + Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) . + Dougherty, R. L., Edelman, A. and Hyman, J. M. (1989) . + Tukey, J. W. (1977) . + F. John Service (2013) . + Edmond A. Ryan, Tami Shandro, Kristy Green, Breay W. Paty, Peter A. Senior, David Bigam, A.M. James Shapiro, and Marie-Christine Vantyghem (2004) . + F. John Service, George D. Molnar, John W. Rosevear, Eugene Ackerman, Leal C. Gatewood, William F. Taylor (1970) . + Sarah E. Siegelaar, Frits Holleman, Joost B. L. Hoekstra, and J. Hans DeVries (2010) . + Gabor Marics, Zsofia Lendvai, Csaba Lodi, Levente Koncz, David Zakarias, Gyorgy Schuster, Borbala Mikos, Csaba Hermann, Attila J. Szabo, and Peter Toth-Heyn (2015) . + Thomas Danne, Revital Nimri, Tadej Battelino, Richard M. Bergenstal, Kelly L. Close, J. Hans DeVries, SatishGarg, Lutz Heinemann, Irl Hirsch, Stephanie A. Amiel, Roy Beck, Emanuele Bosi, Bruce Buckingham, + ClaudioCobelli, Eyal Dassau, Francis J. Doyle, Simon Heller, Roman Hovorka, Weiping Jia, Tim Jones, Olga Kordonouri,Boris Kovatchev, Aaron Kowalski, Lori Laffel, David Maahs, Helen R. Murphy, Kirsten Nørgaard, + Christopher G.Parkin, Eric Renard, Banshi Saboo, Mauro Scharf, William V. Tamborlane, Stuart A. Weinzimer, and Moshe Phillip.International consensus on use of continuous glucose monitoring.Diabetes Care, 2017 . + date_publication: '2022-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gluvarpro + url_git: '' +glvmfit: + version: 0.1.0 + title: Methods to Assess Generalized Latent Variable Model Fit + maintainer: Tyler Matta + description: Provides residual global fit indices for generalized latent variable + models. + date_publication: '2021-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=glvmfit + url_git: '' +gm: + version: 2.0.0 + title: Create Music with Ease + maintainer: Renfei Mao + description: |- + Provides a simple and intuitive high-level language for music + representation. Generates and embeds music scores and audio files in + 'RStudio', 'R Markdown' documents, and R 'Jupyter Notebooks'. + Internally, uses 'MusicXML' to represent + music, and 'MuseScore' to convert 'MusicXML'. + date_publication: '2024-07-10' + bug_reports: '' + url: https://flujoo.github.io/gm/ + url_cran: https://CRAN.R-project.org/package=gm + url_git: https://github.com/flujoo/gm +gma: + version: '1.0' + title: Granger Mediation Analysis + maintainer: Yi Zhao + description: Performs Granger mediation analysis (GMA) for time series. This package + includes a single level GMA model and a two-level GMA model, for time series with + hierarchically nested structure. The single level GMA model for the time series + of a single participant performs the causal mediation analysis which integrates + the structural equation modeling and the Granger causality frameworks. A vector + autoregressive model of order p is employed to account for the spatiotemporal + dependencies in the data. Meanwhile, the model introduces the unmeasured confounding + effect through a nonzero correlation parameter. Under the two-level model, by + leveraging the variabilities across participants, the parameters are identifiable + and consistently estimated based on a full conditional likelihood or a two-stage + method. See Zhao, Y., & Luo, X. (2017), Granger Mediation Analysis of Multiple + Time Series with an Application to fMRI, for details. + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gma + url_git: '' +GMAC: + version: '3.1' + title: Genomic Mediation Analysis with Adaptive Confounding Adjustment + maintainer: Jiebiao Wang + description: |- + Performs genomic mediation + analysis with adaptive confounding adjustment (GMAC) proposed by Yang et al. (2017) . It implements large scale + mediation analysis and adaptively selects potential confounding variables to + adjust for each mediation test from a pool of candidate confounders. The package + is tailored for but not limited to genomic mediation analysis (e.g., cis-gene + mediating trans-gene regulation pattern where an eQTL, its cis-linking gene + transcript, and its trans-gene transcript play the roles as treatment, mediator + and the outcome, respectively), restricting to scenarios with the presence of + cis-association (i.e., treatment-mediator association) and random eQTL (i.e., + treatment). + date_publication: '2022-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMAC + url_git: '' +gmailr: + version: 2.0.0 + title: Access the 'Gmail' 'RESTful' API + maintainer: Jennifer Bryan + description: |- + An interface to the 'Gmail' 'RESTful' API. Allows access to + your 'Gmail' messages, threads, drafts and labels. + date_publication: '2023-06-30' + bug_reports: https://github.com/r-lib/gmailr/issues + url: https://gmailr.r-lib.org + url_cran: https://CRAN.R-project.org/package=gmailr + url_git: https://github.com/r-lib/gmailr +gmapsdistance: + version: 4.0.5 + title: Distance and Travel Time Between Two Points from Google Maps + maintainer: Jindra Lacko + description: |- + Get distance and travel time between two points from Google Maps. + Four possible modes of transportation (bicycling, walking, driving and + public transportation). + date_publication: '2025-01-11' + bug_reports: https://github.com/jlacko/gmapsdistance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gmapsdistance + url_git: https://github.com/jlacko/gmapsdistance +GMCM: + version: '1.4' + title: Fast Estimation of Gaussian Mixture Copula Models + maintainer: Anders Ellern Bilgrau + description: |- + Unsupervised Clustering and Meta-analysis using Gaussian Mixture + Copula Models. + date_publication: '2019-11-05' + bug_reports: https://github.com/AEBilgrau/GMCM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GMCM + url_git: https://github.com/AEBilgrau/GMCM +gMCP: + version: 0.8-17 + title: Graph Based Multiple Comparison Procedures + maintainer: Kornelius Rohmeyer + description: |- + Functions and a graphical user interface for graphical described + multiple test procedures. + date_publication: '2024-03-25' + bug_reports: https://github.com/kornl/gMCP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gMCP + url_git: https://github.com/kornl/gMCP +gMCPLite: + version: 0.1.5 + title: Lightweight Graph Based Multiple Comparison Procedures + maintainer: Nan Xiao + description: |- + A lightweight fork of 'gMCP' with functions for graphical + described multiple test procedures introduced in + Bretz et al. (2009) and + Bretz et al. (2011) . + Implements a flexible function using 'ggplot2' to create + multiplicity graph visualizations. + Contains instructions of multiplicity graph and graphical testing for + group sequential design, described in + Maurer and Bretz (2013) , + with necessary unit testing using 'testthat'. + date_publication: '2024-01-11' + bug_reports: https://github.com/Merck/gMCPLite/issues + url: https://merck.github.io/gMCPLite/ + url_cran: https://CRAN.R-project.org/package=gMCPLite + url_git: https://github.com/Merck/gMCPLite +gmDatabase: + version: 0.5.0 + title: Accessing a Geometallurgical Database with R + maintainer: K. Gerald van den Boogaart + description: |- + A template for a geometallurgical database and a fast and easy + interface for accessing it is provided in this package. + date_publication: '2016-06-16' + bug_reports: '' + url: http://www.stat.boogaart.de + url_cran: https://CRAN.R-project.org/package=gmDatabase + url_git: '' +GMDH: + version: '1.6' + title: Short Term Forecasting via GMDH-Type Neural Network Algorithms + maintainer: Osman Dag + description: Group method of data handling (GMDH) - type neural network algorithm + is the heuristic self-organization method for modelling the complex systems. In + this package, GMDH-type neural network algorithms are applied to make short term + forecasting for a univariate time series. + date_publication: '2016-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMDH + url_git: '' +GMDH2: + version: '1.8' + title: Binary Classification via GMDH-Type Neural Network Algorithms + maintainer: Osman Dag + description: Performs binary classification via Group Method of Data Handling (GMDH) + - type neural network algorithms. There exist two main algorithms available in + GMDH() and dceGMDH() functions. GMDH() performs classification via GMDH algorithm + for a binary response and returns important variables. dceGMDH() performs classification + via diverse classifiers ensemble based on GMDH (dce-GMDH) algorithm. Also, the + package produces a well-formatted table of descriptives for a binary response. + Moreover, it produces confusion matrix, its related statistics and scatter plot + (2D and 3D) with classification labels of binary classes to assess the prediction + performance. All 'GMDH2' functions are designed for a binary response (Dag et + al., 2019, ). + date_publication: '2022-10-26' + bug_reports: '' + url: http://www.softmed.hacettepe.edu.tr/GMDH2 + url_cran: https://CRAN.R-project.org/package=GMDH2 + url_git: '' +GMDHreg: + version: 0.2.3 + title: Regression using GMDH Algorithms + maintainer: Manuel Villacorta Tilve + description: |- + Regression using GMDH algorithms from Prof. Alexey G. Ivakhnenko. + Group Method of Data Handling (GMDH), or polynomial neural networks, is a family of inductive algorithms + that performs gradually complicated polynomial models and selecting the best solution by an external criterion. + In other words, inductive GMDH algorithms give possibility finding automatically interrelations in data, and + selecting an optimal structure of model or network. + The package includes GMDH Combinatorial, GMDH MIA (Multilayered Iterative Algorithm), GMDH GIA (Generalized Iterative Algorithm) and GMDH Combinatorial with Active Neurons. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMDHreg + url_git: '' +Gmedian: + version: 1.2.7 + title: Geometric Median, k-Medians Clustering and Robust Median PCA + maintainer: Herve Cardot + description: Fast algorithms for robust estimation with large samples of multivariate + observations. Estimation of the geometric median, robust k-Gmedian clustering, + and robust PCA based on the Gmedian covariation matrix. + date_publication: '2022-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Gmedian + url_git: '' +gmfamm: + version: 0.1.0 + title: Generalized Multivariate Functional Additive Models + maintainer: Alexander Volkmann + description: |- + Supply implementation to model generalized multivariate functional + data using Bayesian additive mixed models of R package 'bamlss' via a latent + Gaussian process (see Umlauf, Klein, Zeileis (2018) + ). + date_publication: '2024-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmfamm + url_git: '' +gmfd: + version: 1.0.1 + title: Inference and Clustering of Functional Data + maintainer: Andrea Martino + description: |- + Some methods for the inference and clustering of univariate and + multivariate functional data, using a generalization of Mahalanobis + distance, along with some functions useful for the analysis of functional data. + For further details, see Martino A., Ghiglietti, A., Ieva, F. and Paganoni A. M. (2017) . + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmfd + url_git: '' +gmGeostats: + version: 0.11.3 + title: Geostatistics for Compositional Analysis + maintainer: K. Gerald van den Boogaart + description: |- + Support for geostatistical analysis of multivariate data, + in particular data with restrictions, e.g. positive amounts, + compositions, distributional data, microstructural data, etc. + It includes descriptive analysis and modelling for such data, both + from a two-point Gaussian perspective and multipoint perspective. + The methods mainly follow Tolosana-Delgado, Mueller and van den + Boogaart (2018) . + date_publication: '2023-04-18' + bug_reports: '' + url: https://codebase.helmholtz.cloud/geomet/gmGeostats + url_cran: https://CRAN.R-project.org/package=gmGeostats + url_git: '' +gmgm: + version: 1.1.2 + title: Gaussian Mixture Graphical Model Learning and Inference + maintainer: Jérémy Roos + description: |- + Gaussian mixture graphical models include Bayesian networks and + dynamic Bayesian networks (their temporal extension) whose local probability + distributions are described by Gaussian mixture models. They are powerful + tools for graphically and quantitatively representing nonlinear dependencies + between continuous variables. This package provides a complete framework to + create, manipulate, learn the structure and the parameters, and perform + inference in these models. Most of the algorithms are described in the PhD + thesis of Roos (2018) . + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmgm + url_git: '' +Gmisc: + version: 3.0.3 + title: Descriptive Statistics, Transition Plots, and More + maintainer: Max Gordon + description: |- + Tools for making the descriptive "Table 1" used in medical + articles, a transition plot for showing changes between categories + (also known as a Sankey diagram), flow charts by extending the grid package, + a method for variable selection based on the SVD, Bézier lines with arrows + complementing the ones in the 'grid' package, and more. + date_publication: '2023-08-25' + bug_reports: https://github.com/gforge/Gmisc/issues + url: https://gforge.se + url_cran: https://CRAN.R-project.org/package=Gmisc + url_git: '' +GMKMcharlie: + version: 1.1.5 + title: |- + Unsupervised Gaussian Mixture and Minkowski and Spherical + K-Means with Constraints + maintainer: Charlie Wusuo Liu + description: High performance trainers for parameterizing and clustering weighted + data. The Gaussian mixture (GM) module includes the conventional EM (expectation + maximization) trainer, the component-wise EM trainer, the minimum-message-length + EM trainer by Figueiredo and Jain (2002) . These trainers + accept additional constraints on mixture weights, covariance eigen ratios and + on which mixture components are subject to update. The K-means (KM) module offers + clustering with the options of (i) deterministic and stochastic K-means++ initializations, + (ii) upper bounds on cluster weights (sizes), (iii) Minkowski distances, (iv) + cosine dissimilarity, (v) dense and sparse representation of data input. The package + improved the typical implementations of GM and KM algorithms in various aspects. + It is carefully crafted in multithreaded C++ for modeling large data for industry + use. + date_publication: '2021-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMKMcharlie + url_git: '' +gmm: + version: '1.8' + title: |- + Generalized Method of Moments and Generalized Empirical + Likelihood + maintainer: Pierre Chausse + description: It is a complete suite to estimate models based on moment conditions. + It includes the two step Generalized method of moments (Hansen 1982; ), + the iterated GMM and continuous updated estimator (Hansen, Eaton and Yaron 1996; + ) and several methods that belong to the Generalized Empirical + Likelihood family of estimators (Smith 1997; , + Kitamura 1997; , Newey and Smith 2004; , + and Anatolyev 2005 ). + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmm + url_git: '' +GMMAT: + version: 1.4.2 + title: Generalized Linear Mixed Model Association Tests + maintainer: Han Chen + description: Perform association tests using generalized linear mixed models (GLMMs) + in genome-wide association studies (GWAS) and sequencing association studies. + First, GMMAT fits a GLMM with covariate adjustment and random effects to account + for population structure and familial or cryptic relatedness. For GWAS, GMMAT + performs score tests for each genetic variant as proposed in Chen et al. (2016) + . For candidate gene studies, GMMAT can also perform + Wald tests to get the effect size estimate for each genetic variant. For rare + variant analysis from sequencing association studies, GMMAT performs the variant + Set Mixed Model Association Tests (SMMAT) as proposed in Chen et al. (2019) , + including the burden test, the sequence kernel association test (SKAT), SKAT-O + and an efficient hybrid test of the burden test and SKAT, based on user-defined + variant sets. + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMMAT + url_git: '' +GMMBoost: + version: 1.1.5 + title: Likelihood-Based Boosting for Generalized Mixed Models + maintainer: Andreas Groll + description: Likelihood-based boosting approaches for generalized mixed models are + provided. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMMBoost + url_git: '' +gmmsslm: + version: 1.1.5 + title: |- + Semi-Supervised Gaussian Mixture Model with a Missing-Data + Mechanism + maintainer: Ziyang Lyu + description: The algorithm of semi-supervised learning is based on finite Gaussian + mixture models and includes a mechanism for handling missing data. It aims to + fit a g-class Gaussian mixture model using maximum likelihood. The algorithm treats + the labels of unclassified features as missing data, building on the framework + introduced by Rubin (1976) for missing data analysis. By + taking into account the dependencies in the missing pattern, the algorithm provides + more information for determining the optimal classifier, as specified by Bayes' + rule. + date_publication: '2023-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmmsslm + url_git: '' +gmnl: + version: 1.1-3.2 + title: Multinomial Logit Models with Random Parameters + maintainer: Mauricio Sarrias + description: |- + An implementation of maximum simulated likelihood method for the + estimation of multinomial logit models with random coefficients as presented by Sarrias and Daziano (2017) . + Specifically, it allows estimating models with continuous heterogeneity + such as the mixed multinomial logit and the generalized multinomial logit. + It also allows estimating models with discrete heterogeneity such as the + latent class and the mixed-mixed multinomial logit model. + date_publication: '2020-05-27' + bug_reports: '' + url: https://msarrias.com/description.html + url_cran: https://CRAN.R-project.org/package=gmnl + url_git: '' +gmodels: + version: 2.19.1 + title: Various R Programming Tools for Model Fitting + maintainer: Gregory R. Warnes + description: Various R programming tools for model fitting. + date_publication: '2024-03-06' + bug_reports: https://github.com/r-gregmisc/gmodels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gmodels + url_git: https://github.com/r-gregmisc/gmodels +gMOIP: + version: 1.5.4 + title: |- + Tools for 2D and 3D Plots of Single and Multi-Objective + Linear/Integer Programming Models + maintainer: Lars Relund Nielsen + description: |- + Make 2D and 3D plots of linear programming (LP), + integer linear programming (ILP), or mixed integer linear programming (MILP) models + with up to three objectives. Plots of both the solution and criterion space are possible. + For instance the non-dominated (Pareto) set for bi-objective LP/ILP/MILP programming models + (see vignettes for an overview). The package also contains an function for checking if a point + is inside the convex hull. + date_publication: '2024-10-25' + bug_reports: https://github.com/relund/gMOIP/issues + url: https://relund.github.io/gMOIP/ + url_cran: https://CRAN.R-project.org/package=gMOIP + url_git: https://github.com/relund/gMOIP/ +GmooG: + version: '0.7' + title: Datasets for the Book 'Getting (more out of) Graphics' + maintainer: Antony Unwin + description: Datasets analysed in the book Antony Unwin (2024, ISBN:978-0367674007) + "Getting (more out of) Graphics". + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GmooG + url_git: '' +gmoTree: + version: 1.4.1 + title: Get and Modify 'oTree' Data + maintainer: Patricia F. Zauchner + description: |- + Efficiently manage and process data from 'oTree' experiments. + Import 'oTree' data and clean them by using functions that handle + messy data, dropouts, and other problematic cases. Create IDs, + calculate the time, transfer variables between app data frames, and + delete sensitive information. Review your experimental data prior to + running the experiment and automatically generate a detailed summary + of the variables used in your 'oTree' code. Information on 'oTree' is + found in Chen, D. L., Schonger, M., & Wickens, C. (2016) + . + date_publication: '2025-02-04' + bug_reports: https://github.com/ZauchnerP/gmoTree/issues + url: https://zauchnerp.github.io/gmoTree/ + url_cran: https://CRAN.R-project.org/package=gmoTree + url_git: https://github.com/ZauchnerP/gmoTree/ +gmp: + version: 0.7-5 + title: Multiple Precision Arithmetic + maintainer: Antoine Lucas + description: |- + Multiple Precision Arithmetic (big integers and rationals, + prime number tests, matrix computation), "arithmetic without limitations" + using the C library GMP (GNU Multiple Precision Arithmetic). + date_publication: '2024-08-23' + bug_reports: '' + url: https://forgemia.inra.fr/sylvain.jasson/gmp + url_cran: https://CRAN.R-project.org/package=gmp + url_git: '' +gmpoly: + version: 1.1.0 + title: Multivariate Polynomials with Rational Coefficients + maintainer: Stéphane Laurent + description: Symbolic calculation (addition or multiplication) and evaluation of + multivariate polynomials with rational coefficients. + date_publication: '2022-03-20' + bug_reports: https://github.com/stla/gmpoly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gmpoly + url_git: https://github.com/stla/gmpoly +GMPro: + version: 0.1.0 + title: Graph Matching with Degree Profiles + maintainer: Yaofang Hu + description: 'Functions for graph matching via nodes'' degree profiles are provided + in this package. The models we can handle include Erdos-Renyi random graphs and + stochastic block models(SBM). More details are in the reference paper: Yaofang + Hu, Wanjie Wang and Yi Yu (2020) .' + date_publication: '2020-06-25' + bug_reports: '' + url: https://arxiv.org/abs/2006.03284 + url_cran: https://CRAN.R-project.org/package=GMPro + url_git: '' +GmptzCurve: + version: 0.1.0 + title: Gompertz Curve Fitting + maintainer: Arnab Roy + description: A system for fitting Gompertz Curve in a Time Series Data. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GmptzCurve + url_git: '' +gmresls: + version: 0.2.3 + title: Solve Least Squares with GMRES(k) + maintainer: Serguei Sokol + description: 'Solves a least squares system Ax~=b (dim(A)=(m,n) with m >= n) with + a precondition matrix B: BAx=Bb (dim(B)=(n,m)). Implemented method is based on + GMRES (Saad, Youcef; Schultz, Martin H. (1986). "GMRES: A Generalized Minimal + Residual Algorithm for Solving Nonsymmetric Linear Systems" ) + with callback functions, i.e. no explicit A, B or b are required.' + date_publication: '2025-01-17' + bug_reports: https://forgemia.inra.fr/mathscell/gmresls/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gmresls + url_git: '' +gms: + version: 0.31.2 + title: '''GAMS'' Modularization Support Package' + maintainer: Jan Philipp Dietrich + description: |- + A collection of tools to create, use and maintain modularized model code written in the modeling + language 'GAMS' (). Out-of-the-box 'GAMS' does not come with support for modularized + model code. This package provides the tools necessary to convert a standard 'GAMS' model to a modularized one + by introducing a modularized code structure together with a naming convention which emulates local + environments. In addition, this package provides tools to monitor the compliance of the model code with + modular coding guidelines. + date_publication: '2024-06-29' + bug_reports: https://github.com/pik-piam/gms/issues + url: https://doi.org/10.5281/zenodo.4390032 + url_cran: https://CRAN.R-project.org/package=gms + url_git: https://github.com/pik-piam/gms +GMSE: + version: 1.0.0.2 + title: Generalised Management Strategy Evaluation Simulator + maintainer: A. Bradley Duthie + description: |- + Integrates game theory and ecological theory to construct + social-ecological models that simulate the management of populations and + stakeholder actions. These models build off of a previously developed + management strategy evaluation (MSE) framework to simulate all aspects of + management: population dynamics, manager observation of populations, manager + decision making, and stakeholder responses to management decisions. The + newly developed generalised management strategy evaluation (GMSE) + framework uses genetic algorithms to mimic the decision-making process of + managers and stakeholders under conditions of change, uncertainty, and + conflict. Simulations can be run using gmse(), gmse_apply(), and + gmse_gui() functions. + date_publication: '2022-06-16' + bug_reports: https://github.com/confoobio/gmse/issues + url: https://confoobio.github.io/gmse/ + url_cran: https://CRAN.R-project.org/package=GMSE + url_git: '' +GMSimpute: + version: 0.0.1.0 + title: Generalized Mass Spectrum Missing Peaks Abundance Imputation + maintainer: Qian Li + description: |- + Two-Step Lasso (TS-Lasso) and compound minimum methods to recover + the abundance of missing peaks in mass spectrum analysis. TS-Lasso is an + imputation method that handles various types of missing peaks simultaneously. This package + provides the procedure to generate missing peaks (or data) for simulation study, + as well as a tool to estimate and visualize the proportion of missing at random. + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GMSimpute + url_git: '' +gmt: + version: 2.0.3 + title: Interface Between GMT Map-Making Software and R + maintainer: Arni Magnusson + description: |- + Interface between the GMT map-making software and R, enabling the + user to manipulate geographic data within R and call GMT commands to draw and + annotate maps in postscript format. The gmt package is about interactive data + analysis, rapidly visualizing subsets and summaries of geographic data, while + performing statistical analysis in the R console. + date_publication: '2022-06-06' + bug_reports: '' + url: https://www.generic-mapping-tools.org + url_cran: https://CRAN.R-project.org/package=gmt + url_git: '' +gmtFD: + version: 0.1.0 + title: |- + General Multiple Tests for Univariate and Multivariate + Functional Data + maintainer: Lukasz Smaga + description: The multiple contrast tests for univariate were proposed by Munko, + Ditzhaus, Pauly, Smaga, and Zhang (2023) . Recently, + they were extended to the multivariate functional data in Munko, Ditzhaus, Pauly, + and Smaga (2024) . These procedures enable us to + evaluate the overall hypothesis regarding equality, as well as specific hypotheses + defined by contrasts. In particular, we can perform post hoc tests to examine + particular comparisons of interest. Different experimental designs are supported, + e.g., one-way and multi-way analysis of variance for functional data. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmtFD + url_git: '' +gmvarkit: + version: 2.1.4 + title: |- + Estimate Gaussian and Student's t Mixture Vector Autoregressive + Models + maintainer: Savi Virolainen + description: |- + Unconstrained and constrained maximum likelihood estimation of structural and reduced form + Gaussian mixture vector autoregressive, Student's t mixture vector autoregressive, and Gaussian and Student's t + mixture vector autoregressive models, quantile residual tests, graphical diagnostics, + simulations, forecasting, and estimation of generalized impulse response function and generalized + forecast error variance decomposition. + Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) , + Savi Virolainen (2025) , + Savi Virolainen (2022) . + date_publication: '2025-01-08' + bug_reports: https://github.com/saviviro/gmvarkit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gmvarkit + url_git: '' +gmvjoint: + version: 0.4.5 + title: Joint Models of Survival and Multivariate Longitudinal Data + maintainer: James Murray + description: |- + Fit joint models of survival and multivariate longitudinal data. The longitudinal + data is specified by generalised linear mixed models. The joint models are fit via maximum + likelihood using an approximate expectation maximisation algorithm. + Bernhardt (2015) . + date_publication: '2024-10-05' + bug_reports: https://github.com/jamesmurray7/gmvjoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gmvjoint + url_git: https://github.com/jamesmurray7/gmvjoint +gmwmx: + version: 1.0.3 + title: |- + Estimate Functional and Stochastic Parameters of Linear Models + with Correlated Residuals + maintainer: Lionel Voirol + description: |- + Implements the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) presented in Cucci, D. A., Voirol, L., Kermarrec, G., Montillet, J. P., and Guerrier, S. (2023) . + The GMWMX estimator allows to estimate functional and stochastic parameters of linear models with correlated residuals. + The 'gmwmx' package provides functions to estimate, compare and analyze models, utilities to load and work with Global Navigation Satellite System (GNSS) data as well as methods to compare results with the Maximum Likelihood Estimator (MLE) implemented in Hector. + date_publication: '2023-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gmwmx + url_git: '' +gMWT: + version: '1.4' + title: Generalized Mann-Whitney Type Tests + maintainer: Daniel Fischer + description: |- + Generalized Mann-Whitney type tests based on probabilistic + indices and new diagnostic plots, for the underlying manuscript see Fischer, Oja (2015) . + date_publication: '2023-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gMWT + url_git: '' +GNAR: + version: 1.1.4 + title: Methods for Fitting Network Time Series Models + maintainer: Matt Nunes + description: Simulation of, and fitting models for, Generalised Network Autoregressive + (GNAR) time series models which take account of network structure, potentially + with exogenous variables. Such models are described in Knight et al. (2020) + and Nason and Wei (2021) . Diagnostic tools for GNAR(X) + models can be found in Nason et al. (2023) . + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GNAR + url_git: '' +GNE: + version: 0.99-6 + title: Computation of Generalized Nash Equilibria + maintainer: Christophe Dutang + description: |- + Compute standard and generalized Nash Equilibria of non-cooperative games. + Optimization methods available are nonsmooth reformulation, fixed-point formulation, + minimization problem and constrained-equation reformulation. + See e.g. Kanzow and Facchinei (2010), . + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GNE + url_git: https://r-forge.r-project.org/projects/optimizer/ +gnFit: + version: 0.2.0 + title: Goodness of Fit Test for Continuous Distribution Functions + maintainer: Ali Saeb + description: 'Computes the test statistic and p-value of the Cramer-von Mises and + Anderson-Darling test for some continuous distribution functions proposed by Chen + and Balakrishnan (1995) . + In addition to our classic distribution functions here, we calculate the Goodness + of Fit (GoF) test to dataset which follows the extreme value distribution function, + without remembering the formula of distribution/density functions. Calculates + the Value at Risk (VaR) and Average VaR are another important risk factors which + are estimated by using well-known distribution functions. Pflug and Romisch (2007, + ISBN: 9812707409) is a good reference to study the properties of risk measures.' + date_publication: '2018-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gnFit + url_git: '' +gnlm: + version: 1.1.1 + title: Generalized Nonlinear Regression Models + maintainer: Bruce Swihart + description: |- + A variety of functions to fit linear and nonlinear + regression with a large selection of distributions. + date_publication: '2019-02-03' + bug_reports: https://github.com/swihart/gnlm/issues + url: http://www.commanster.eu/rcode.html + url_cran: https://CRAN.R-project.org/package=gnlm + url_git: '' +gnm: + version: 1.1-5 + title: Generalized Nonlinear Models + maintainer: Heather Turner + description: |- + Functions to specify and fit generalized nonlinear models, + including models with multiplicative interaction terms such as the + UNIDIFF model from sociology and the AMMI model from crop science, and + many others. Over-parameterized representations of models are used + throughout; functions are provided for inference on estimable + parameter combinations, as well as standard methods for diagnostics + etc. + date_publication: '2023-09-16' + bug_reports: https://github.com/hturner/gnm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gnm + url_git: https://github.com/hturner/gnm +gnn: + version: 0.0-4 + title: Generative Neural Networks + maintainer: Marius Hofert + description: |- + Tools to set up, train, store, load, investigate and analyze + generative neural networks. In particular, functionality for + generative moment matching networks is provided. + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gnn + url_git: '' +gnomonicM: + version: 1.0.1 + title: Estimate Natural Mortality for Different Life Stages + maintainer: Josymar Torrejon-Magallanes + description: |- + Estimate natural mortality (M) throughout the life history for organisms, mainly fish and invertebrates, based on gnomonic interval approach proposed by Caddy (1996) and Martinez-Aguilar et al. (2005) . + It includes estimation of duration of each gnomonic interval (life stage), the constant probability of death (G), and some basic plots. + date_publication: '2021-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gnomonicM + url_git: '' +gnonadd: + version: 1.0.3 + title: Various Non-Additive Models for Genetic Associations + maintainer: Audunn S. Snaebjarnarson + description: The goal of 'gnonadd' is to simplify workflows in the analysis of non-additive + effects of sequence variants. This includes variance effects (Ivarsdottir et. + al (2017) ), correlation effects, interaction effects and + dominance effects. The package also includes convenience functions for visualization. + date_publication: '2024-12-19' + bug_reports: https://github.com/DecodeGenetics/gnonadd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gnonadd + url_git: https://github.com/DecodeGenetics/gnonadd +gnorm: + version: 1.0.0 + title: Generalized Normal/Exponential Power Distribution + maintainer: Maryclare Griffin + description: Functions for obtaining generalized normal/exponential power distribution + probabilities, quantiles, densities and random deviates. The generalized normal/exponential + power distribution was introduced by Subbotin (1923) and rediscovered by Nadarajah + (2005). The parametrization given by Nadarajah (2005) + is used. + date_publication: '2018-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gnorm + url_git: http://github.com/maryclare/gnorm +gnrprod: + version: 1.1.2 + title: Estimates Gross Output Functions + maintainer: David J. Jin + description: Estimation of gross output production functions and productivity in + the presence of numerous fixed (nonflexible) and a single flexible input using + the nonparametric identification strategy specified in Gandhi, Navarro, and Rivers + (2020) . Monte Carlo evidence from the paper demonstrates + high performance in estimating production function elasticities. + date_publication: '2023-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gnrprod + url_git: '' +GNRS: + version: 0.3.4 + title: Access the 'Geographic Name Resolution Service' + maintainer: Brian Maitner + description: 'Provides tools for interacting with the ''geographic name resolution + service'' (''GNRS'') API and associated + functionality. The ''GNRS'' is a batch application for resolving & standardizing + political division names against standard name in the geonames database . + The ''GNRS'' resolves political division names at three levels: country, state/province + and county/parish. Resolution is performed in a series of steps, beginning with + direct matching to standard names, followed by direct matching to alternate names + in different languages, followed by direct matching to standard codes (such as + ISO and FIPS codes). If direct matching fails, the ''GNRS'' attempts to match + to standard and then alternate names using fuzzy matching, but does not perform + fuzzing matching of political division codes. The ''GNRS'' works down the political + division hierarchy, stopping at the current level if all matches fail. In other + words, if a country cannot be matched, the ''GNRS'' does not attempt to match + state or county.' + date_publication: '2021-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GNRS + url_git: '' +GNSSseg: + version: '6.0' + title: Homogenization of GNSS Series + maintainer: Annarosa Quarello + description: Homogenize GNSS (Global Navigation Satellite System) time-series. The + general model is a segmentation in the mean model including a periodic function + and considering monthly variances, see Quarello (2020) . + date_publication: '2020-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GNSSseg + url_git: '' +gnumeric: + version: 0.7-10 + title: Read Data from Files Readable by 'gnumeric' + maintainer: Karoly Antal + description: |- + Read data files readable by 'gnumeric' into 'R'. Can read + whole sheet or a range, from several file formats, including + the native format of 'gnumeric'. Reading is done by using + 'ssconvert' (a file converter utility included in the 'gnumeric' + distribution ) to convert + the requested part to CSV. From 'gnumeric' files (but not other + formats) can list sheet names and sheet sizes or read all + sheets. + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gnumeric + url_git: '' +go2bigq: + version: 2.0.1 + title: Convert Large Numbers to Bigq Format + maintainer: Carl Witthoft + description: This function converts mfpr, numeric, or character strings representing + numbers to bigq format without loss of precision. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=go2bigq + url_git: '' +goalp: + version: 0.3.1 + title: Weighted and Lexicographic Goal Programming Interface + maintainer: David Palma + description: |- + Solves goal programming problems of the weighted and + lexicographic type, as well as combinations of the two, as described + by Ignizio (1983) . Allows for + a simple human-readable input describing the problem as a series + of equations. Relies on the 'lpSolve' package to solve the underlying + linear optimisation problem. + date_publication: '2022-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=goalp + url_git: '' +goat: + version: 1.1.2 + title: Gene Set Analysis Using the Gene Set Ordinal Association Test + maintainer: Frank Koopmans + description: |- + Perform gene set enrichment analyses using the Gene set Ordinal + Association Test (GOAT) algorithm and visualize your + results. Koopmans, F. (2024) . + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=goat + url_git: https://github.com/ftwkoopmans/goat/ +GOCompare: + version: 1.0.2.1 + title: Comprehensive GO Terms Comparison Between Species + maintainer: Chrystian Camilo Sosa + description: Supports the assessment of functional enrichment analyses obtained + for several lists of genes and provides a workflow to analyze them between two + species via weighted graphs. Methods are described in Sosa et al. (2023) . + date_publication: '2022-12-09' + bug_reports: https://github.com/ccsosa/GOCompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GOCompare + url_git: https://github.com/ccsosa/GOCompare +godley: + version: 0.2.2 + title: Stock-Flow-Consistent Model Simulator + maintainer: Elżbieta Jowik + description: Define, simulate, and validate stock-flow consistent (SFC) macroeconomic + models. The godley R package offers tools to dynamically define model structures + by adding variables and specifying governing systems of equations. With it, users + can analyze how different macroeconomic structures affect key variables, perform + parameter sensitivity analyses, introduce policy shocks, and visualize resulting + economic scenarios. The accounting structure of SFC models follows the approach + outlined in the seminal study by Godley and Lavoie (2007, ISBN:978-1-137-08599-3), + ensuring a comprehensive integration of all economic flows and stocks. The algorithms + implemented to solve the models are based on methodologies from Kinsella and O'Shea + (2010) , Peressini and Sullivan (1988, ISBN:0-387-96614-5), + and contributions by Joao Macalos. + date_publication: '2025-02-23' + bug_reports: https://github.com/gamrot/godley/issues + url: https://gamrot.github.io/godley/ + url_cran: https://CRAN.R-project.org/package=godley + url_git: '' +goeveg: + version: 0.7.5 + title: Functions for Community Data and Ordinations + maintainer: Friedemann von Lampe + description: A collection of functions useful in (vegetation) community analyses + and ordinations. Includes automatic species selection for ordination diagrams, + NMDS stress/scree plots, species response curves, merging of taxa as well as calculation + and sorting of synoptic tables. + date_publication: '2024-05-17' + bug_reports: https://github.com/fvlampe/goeveg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=goeveg + url_git: https://github.com/fvlampe/goeveg/ +gofar: + version: '0.1' + title: Generalized Co-Sparse Factor Regression + maintainer: Aditya Mishra + description: 'Divide and conquer approach for estimating low-rank and sparse coefficient + matrix in the generalized co-sparse factor regression. Please refer the manuscript + ''Mishra, Aditya, Dipak K. Dey, Yong Chen, and Kun Chen. Generalized co-sparse + factor regression. Computational Statistics & Data Analysis 157 (2021): 107127'' + for more details.' + date_publication: '2022-03-02' + bug_reports: '' + url: https://www.sciencedirect.com/science/article/pii/S0167947320302188 + url_cran: https://CRAN.R-project.org/package=gofar + url_git: https://github.com/amishra-stats/gofar +gofcat: + version: 0.1.2 + title: Goodness-of-Fit Measures for Categorical Response Models + maintainer: Ejike R. Ugba + description: |- + A post-estimation method for categorical response models (CRM). + Inputs from objects of class serp(), clm(), polr(), multinom(), mlogit(), + vglm() and glm() are currently supported. Available tests include the + Hosmer-Lemeshow tests for the binary, multinomial and ordinal logistic + regression; the Lipsitz and the Pulkstenis-Robinson tests for the ordinal + models. The proportional odds, adjacent-category, and constrained continuation-ratio + models are particularly supported at ordinal level. Tests for the proportional + odds assumptions in ordinal models are also possible with the Brant and the + Likelihood-Ratio tests. Moreover, several summary measures of predictive strength + (Pseudo R-squared), and some useful error metrics, including, the brier + score, misclassification rate and logloss are also available for the + binary, multinomial and ordinal models. Ugba, E. R. and Gertheiss, J. (2018) + . + date_publication: '2022-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gofcat + url_git: '' +GofCens: + version: 1.2.1 + title: Goodness-of-Fit Methods for Complete and Right-Censored Data + maintainer: Klaus Langohr + description: |- + Graphical tools and goodness-of-fit tests for complete and right-censored data: + 1. Kolmogorov-Smirnov, Cramér-von Mises, and Anderson-Darling tests, + which utilize the empirical distribution function for complete data + and are extended to handle right-censored data. + 2. Generalized chi-squared-type test, which is based on the squared + differences between observed and expected counts using random + cells with right-censored data. + 3. Graphical tools, such as probability and cumulative hazard plots, + to help guide decisions about the most appropriate parametric model for the data. + date_publication: '2024-11-09' + bug_reports: '' + url: https://arnaugarciagrbio.github.io/GofCens/ + url_cran: https://CRAN.R-project.org/package=GofCens + url_git: https://github.com/ArnauGarciaGRBIO/GofCens +gofCopula: + version: 0.4-1 + title: Goodness-of-Fit Tests for Copulae + maintainer: Simon Trimborn + description: Several Goodness-of-Fit (GoF) tests for Copulae are provided. A new + hybrid test, Zhang et al. (2016) is implemented + which supports all of the individual tests in the package, e.g. Genest et al. + (2009) . Estimation methods for the margins + are provided and all the tests support parameter estimation and predefined values. + The parameters are estimated by pseudo maximum likelihood but if it fails the + estimation switches automatically to inversion of Kendall's tau. For reproducibility + of results, the functions support the definition of seeds. Also all the tests + support automatized parallelization of the bootstrapping tasks. The package provides + an interface to perform new GoF tests by submitting the test statistic. + date_publication: '2021-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gofCopula + url_git: '' +gofedf: + version: 0.1.0 + title: Goodness of Fit Tests Based on Empirical Distribution Functions + maintainer: Payman Nickchi + description: Routines that allow the user to run goodness of fit tests based on + empirical distribution functions for formal model evaluation in a general likelihood + model. In addition, functions are provided to test a sample against Normal or + Gamma distributions, validate the normality assumptions in a linear model, and + examine the appropriateness of a Gamma distribution in generalized linear models + with various link functions. Michael Arthur Stephens (1976) . + date_publication: '2023-10-01' + bug_reports: https://github.com/pnickchi/gofedf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gofedf + url_git: https://github.com/pnickchi/gofedf +goffda: + version: 0.1.2 + title: Goodness-of-Fit Tests for Functional Data + maintainer: Eduardo García-Portugués + description: |- + Implementation of several goodness-of-fit tests for functional + data. Currently, mostly related with the functional linear model with + functional/scalar response and functional/scalar predictor. The package + allows for the replication of the data applications considered in + García-Portugués, Álvarez-Liébana, Álvarez-Pérez and González-Manteiga + (2021) . + date_publication: '2023-10-14' + bug_reports: https://github.com/egarpor/goffda + url: '' + url_cran: https://CRAN.R-project.org/package=goffda + url_git: https://github.com/egarpor/goffda +gofgamma: + version: '1.0' + title: Goodness-of-Fit Tests for the Gamma Distribution + maintainer: Bruno Ebner + description: We implement various classical tests for the composite hypothesis of + testing the fit to the family of gamma distributions as the Kolmogorov-Smirnov + test, the Cramer-von Mises test, the Anderson Darling test and the Watson test. + For each test a parametric bootstrap procedure is implemented, as considered in + Henze, Meintanis & Ebner (2012) . The recent + procedures presented in Henze, Meintanis & Ebner (2012) + and Betsch & Ebner (2019) are implemented. Estimation + of parameters of the gamma law are implemented using the method of Bhattacharya + (2001) . + date_publication: '2020-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gofgamma + url_git: '' +gofIG: + version: '1.0' + title: Goodness-of-Fit Tests for the Inverse Gaussian Distribution + maintainer: Bruno Ebner + description: |- + We implement various tests for the composite hypothesis of + testing the fit to the family of inverse Gaussian distributions. + Included are methods presented by Allison, J.S., Betsch, S., Ebner, B., and Visagie, I.J.H. (2022) , + as well as two tests from Henze and Klar (2002) . + Additionally, the package implements a test proposed by Baringhaus and Gaigall (2015) . + For each test a parametric bootstrap procedure is implemented. + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gofIG + url_git: '' +gofigR: + version: 0.2.2 + title: Client for 'GoFigr.io' + maintainer: Maciej Pacula + description: |- + Integrates with your 'RMarkdown' documents to automatically publish + figures to the service. Supports both 'knitr' and interactive + execution within 'RStudio'. + date_publication: '2025-02-07' + bug_reports: https://github.com/GoFigr/gofigR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gofigR + url_git: https://github.com/GoFigr/gofigR +GoFKernel: + version: 2.1-3 + title: Testing Goodness-of-Fit with the Kernel Density Estimator + maintainer: Jose M. Pavía + description: |- + Tests of goodness-of-fit based on a kernel smoothing of the data. + References: + Pavía (2015) . + date_publication: '2024-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GoFKernel + url_git: '' +GofKmt: + version: 2.2.0 + title: Khmaladze Martingale Transformation Goodness-of-Fit Test + maintainer: Jiwoong Kim + description: 'Consider a goodness-of-fit (GOF) problem of testing whether a random + sample comes from one sample location-scale model where location and scale parameters + are unknown. It is well known that Khmaladze martingale transformation method + - which was proposed by Khmaladze (1981) - provides asymptotic + distribution free test for the GOF problem. This package contains one function: + KhmaladzeTrans(). In this version, KhmaladzeTrans() provides test statistic and + critical value of GOF test for normal, Cauchy, and logistic distributions. This + package used the main algorithm proposed by Kim (2020) + and tests for other distributions will be available at the later version.' + date_publication: '2020-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GofKmt + url_git: '' +gofreg: + version: 1.0.0 + title: Bootstrap-Based Goodness-of-Fit Tests for Parametric Regression + maintainer: Gitte Kremling + description: |- + Provides statistical methods to check if a parametric family of + conditional density functions fits to some given dataset of covariates and + response variables. Different test statistics can be used to determine the + goodness-of-fit of the assumed model, see Andrews (1997) + , Bierens & Wang (2012) , + Dikta & Scheer (2021) and Kremling & Dikta + (2024) . As proposed in these papers, the + corresponding p-values are approximated using a parametric bootstrap method. + date_publication: '2024-10-04' + bug_reports: https://github.com/gkremling/gofreg/issues + url: https://gkremling.github.io/gofreg/ + url_cran: https://CRAN.R-project.org/package=gofreg + url_git: https://github.com/gkremling/gofreg +GOFShiny: + version: 0.1.0 + title: Interactive Document for Working with Goodness of Fit Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of goodness of fit analysis using + 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GOFShiny + url_git: '' +goft: + version: 1.3.6 + title: Tests of Fit for some Probability Distributions + maintainer: Elizabeth Gonzalez-Estrada + description: Goodness-of-fit tests for skew-normal, gamma, inverse Gaussian, log-normal, + 'Weibull', 'Frechet', Gumbel, normal, multivariate normal, Cauchy, Laplace or + double exponential, exponential and generalized Pareto distributions. Parameter + estimators for gamma, inverse Gaussian and generalized Pareto distributions. + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=goft + url_git: '' +goftest: + version: 1.2-3 + title: Classical Goodness-of-Fit Tests for Univariate Distributions + maintainer: Adrian Baddeley + description: |- + Cramer-Von Mises and Anderson-Darling tests of goodness-of-fit + for continuous univariate distributions, using + efficient algorithms. + date_publication: '2021-10-07' + bug_reports: https://github.com/baddstats/goftest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=goftest + url_git: https://github.com/baddstats/goftest +gogarch: + version: 0.7-5 + title: Generalized Orthogonal GARCH (GO-GARCH) Models + maintainer: Bernhard Pfaff + description: |- + Provision of classes and methods for estimating generalized + orthogonal GARCH models. This is an alternative approach to CC-GARCH models + in the context of multivariate volatility modeling. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gogarch + url_git: '' +goldfish: + version: 1.6.10 + title: Statistical Network Models for Dynamic Network Data + maintainer: Alvaro Uzaheta + description: |- + Tools for fitting statistical network models to dynamic network data. + Can be used for fitting both dynamic network actor models ('DyNAMs') and + relational event models ('REMs'). + Stadtfeld, Hollway, and Block (2017a) , + Stadtfeld, Hollway, and Block (2017b) , + Stadtfeld and Block (2017) , + Hoffman et al. (2020) . + date_publication: '2024-09-03' + bug_reports: https://github.com/stocnet/goldfish/issues/ + url: https://stocnet.github.io/goldfish/ + url_cran: https://CRAN.R-project.org/package=goldfish + url_git: '' +goldilocks: + version: 0.4.0 + title: Goldilocks Adaptive Trial Designs for Time-to-Event Endpoints + maintainer: Graeme L. Hickey + description: |- + Implements the Goldilocks adaptive trial design for a time to event + outcome using a piecewise exponential model and conjugate Gamma prior + distributions. The method closely follows the article by Broglio and + colleagues , which allows users to explore + the operating characteristics of different trial designs. + date_publication: '2025-01-08' + bug_reports: https://github.com/graemeleehickey/goldilocks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=goldilocks + url_git: https://github.com/graemeleehickey/goldilocks +GOLDprice: + version: 0.1.0 + title: Gold Price Data + maintainer: Fadhlul Mubarak + description: A collection of gold price data in various currencies in the form of + USD, EUR, JPY, GBP, CAD, CHF, INR, CNY, TRY, SAR, IDR, AED, THB, VND, EGP, KRW, + RUB, ZAR, and AUD. This data comes from the World Gold Council. In addition, the + data is in the form of daily, weekly, monthly (average and the end of period), + quarterly (average and the end of period), and yearly (average and the end of + period). + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GOLDprice + url_git: '' +golem: + version: 0.5.1 + title: A Framework for Robust Shiny Applications + maintainer: Colin Fay + description: |- + An opinionated framework for building a production-ready + 'Shiny' application. This package contains a series of tools for + building a robust 'Shiny' application from start to finish. + date_publication: '2024-08-27' + bug_reports: https://github.com/ThinkR-open/golem/issues + url: https://thinkr-open.github.io/golem/ + url_cran: https://CRAN.R-project.org/package=golem + url_git: https://github.com/ThinkR-open/golem +gomms: + version: '1.0' + title: GLM-Based Ordination Method + maintainer: Michael B. Sohn + description: A zero-inflated quasi-Poisson factor model to display similarity between + samples visually in a low (2 or 3) dimensional space. + date_publication: '2017-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gomms + url_git: '' +GomoGomonoMi: + version: 0.1.0 + title: Animate Text using the 'Animate.css' Library + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to animate text within 'rmarkdown' documents and 'shiny' applications. + The animations are activated using the 'Animate.css' library. See for more information. + date_publication: '2020-06-16' + bug_reports: https://github.com/feddelegrand7/GomoGomonoMi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GomoGomonoMi + url_git: https://github.com/feddelegrand7/GomoGomonoMi +gomp: + version: '1.0' + title: The gamma-OMP Feature Selection Algorithm + maintainer: Michail Tsagris + description: 'The gamma-Orthogonal Matching Pursuit (gamma-OMP) is a recently suggested + modification of the OMP feature selection algorithm for a wide range of response + variables. The package offers many alternative regression models, such linear, + robust, survival, multivariate etc., including k-fold cross-validation. References: + Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2018). "Efficient + feature selection on gene expression data: Which algorithm to use?" BioRxiv. . + Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2022). "The gamma-OMP + algorithm for feature selection with application to gene expression data". IEEE/ACM + Transactions on Computational Biology and Bioinformatics 19(2): 1214--1224. .' + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gomp + url_git: '' +gompertztrunc: + version: 0.1.2 + title: |- + Conducting Maximum Likelihood Estimation with Truncated + Mortality Data + maintainer: Maria Osborne + description: |- + Estimates hazard ratios and mortality differentials for + doubly-truncated data without population denominators. This method is + described in Goldstein et al. (2023) . + date_publication: '2024-02-29' + bug_reports: https://github.com/caseybreen/gompertztrunc/issues + url: https://caseybreen.github.io/gompertztrunc/ + url_cran: https://CRAN.R-project.org/package=gompertztrunc + url_git: https://github.com/caseybreen/gompertztrunc +gontr: + version: 1.1.0 + title: Dataset for 'GOxploreR' + maintainer: Kalifa Manjang + description: |- + Contains the Gene ontology terms and skeleton for the reduced GO directed acyclic graph (DAG) for the organisms + Rat and Mouse. The methods are explicitly discussed in the following article : Manjang et al (2020) . + date_publication: '2020-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gontr + url_git: '' +GoodFibes: + version: 0.1.10 + title: |- + Detection and Reconstruction of Muscle Fibers from diceCT Image + Data + maintainer: Jessica Arbour + description: Reconstruction of muscle fibers from image stacks using textural analysis. + Includes functions for tracking, smoothing, cleaning, plotting and exporting muscle + fibers. Also calculates basic fiber properties (e.g., length and curvature). + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GoodFibes + url_git: '' +GoodFitSBM: + version: 0.0.1 + title: Monte Carlo Goodness-of-Fit Tests for Stochastic Block Models + maintainer: Soham Ghosh + description: Performing goodness-of-fit tests for stochastic block models used to + fit network data. Among the three variants discussed in Karwa et al. (2023) , + goodness-of-fit test has been performed for the Erdos-Renyi (ER) and Beta versions. + date_publication: '2024-02-23' + bug_reports: https://github.com/Roy-SR-007/GoodFitSBM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GoodFitSBM + url_git: https://github.com/Roy-SR-007/GoodFitSBM +GoodmanKruskal: + version: 0.0.3 + title: Association Analysis for Categorical Variables + maintainer: Ron Pearson + description: |- + Association analysis between categorical + variables using the Goodman and Kruskal tau measure. This asymmetric association + measure allows the detection of asymmetric relations between categorical + variables (e.g., one variable obtained by re-grouping another). + date_publication: '2020-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GoodmanKruskal + url_git: '' +goodpractice: + version: 1.0.5 + title: Advice on R Package Building + maintainer: Mark Padgham + description: |- + Give advice about good practices when building R packages. + Advice includes functions and syntax to avoid, package structure, code + complexity, code formatting, etc. + date_publication: '2024-06-04' + bug_reports: https://github.com/ropensci-review-tools/goodpractice/issues + url: https://docs.ropensci.org/goodpractice/ + url_cran: https://CRAN.R-project.org/package=goodpractice + url_git: https://github.com/ropensci-review-tools/goodpractice +Goodreader: + version: 0.1.2 + title: Scrape and Analyze 'Goodreads' Book Data + maintainer: Chao Liu + description: A comprehensive toolkit for scraping and analyzing book data from . + This package provides functions to search for books, scrape book details and reviews, + perform sentiment analysis on reviews, and conduct topic modeling. It's designed + for researchers, data analysts, and book enthusiasts who want to gain insights + from 'Goodreads' data. + date_publication: '2024-10-24' + bug_reports: https://github.com/chaoliu-cl/Goodreader/issues + url: http://liu-chao.site/Goodreader/ + url_cran: https://CRAN.R-project.org/package=Goodreader + url_git: https://github.com/chaoliu-cl/Goodreader +googleadsR: + version: 1.0.0 + title: Access to 'Google Ads' via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect marketing data from 'Google Ads' using the 'Windsor.ai' API + . + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=googleadsR + url_git: '' +googleAnalyticsR: + version: 1.2.0 + title: Google Analytics API into R + maintainer: Erik Grönroos + description: |- + Interact with the Google Analytics + APIs , including + the Core Reporting API (v3 and v4), Management API, User Activity API + GA4's Data API and Admin API and Multi-Channel Funnel API. + date_publication: '2024-08-16' + bug_reports: https://github.com/8-bit-sheep/googleAnalyticsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=googleAnalyticsR + url_git: https://github.com/8-bit-sheep/googleAnalyticsR/ +googleAuthR: + version: 2.0.2 + title: Authenticate and Create Google APIs + maintainer: Erik Grönroos + description: |- + Create R functions that interact with OAuth2 Google APIs + easily, + with auto-refresh and Shiny compatibility. + date_publication: '2024-05-22' + bug_reports: https://github.com/MarkEdmondson1234/googleAuthR/issues + url: https://code.markedmondson.me/googleAuthR/ + url_cran: https://CRAN.R-project.org/package=googleAuthR + url_git: '' +googleCloudStorageR: + version: 0.7.0 + title: Interface with Google Cloud Storage API + maintainer: Mark Edmondson + description: |- + Interact with Google Cloud Storage + API in R. Part of the 'cloudyr' project. + date_publication: '2021-12-16' + bug_reports: https://github.com/cloudyr/googleCloudStorageR/issues + url: https://code.markedmondson.me/googleCloudStorageR/ + url_cran: https://CRAN.R-project.org/package=googleCloudStorageR + url_git: '' +googleCloudVisionR: + version: 0.2.0 + title: |- + Access to the 'Google Cloud Vision' API for Image Recognition, + OCR and Labeling + maintainer: Jeno Pal + description: |- + Interact with the 'Google Cloud Vision' + API in R. Part of the 'cloudyr' project. + date_publication: '2020-02-07' + bug_reports: https://github.com/cloudyr/googleCloudVisionR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=googleCloudVisionR + url_git: '' +googleComputeEngineR: + version: 0.3.0 + title: R Interface with Google Compute Engine + maintainer: Mark Edmondson + description: |- + Interact with the 'Google Compute Engine' API in R. Lets you create, + start and stop instances in the 'Google Cloud'. Support for preconfigured instances, + with templates for common R needs. + date_publication: '2019-05-04' + bug_reports: https://github.com/cloudyr/googleComputeEngineR/issues + url: https://cloudyr.github.io/googleComputeEngineR/ + url_cran: https://CRAN.R-project.org/package=googleComputeEngineR + url_git: '' +googledrive: + version: 2.1.1 + title: An Interface to Google Drive + maintainer: Jennifer Bryan + description: Manage Google Drive files from R. + date_publication: '2023-06-11' + bug_reports: https://github.com/tidyverse/googledrive/issues + url: https://googledrive.tidyverse.org + url_cran: https://CRAN.R-project.org/package=googledrive + url_git: https://github.com/tidyverse/googledrive +googleErrorReportingR: + version: 0.0.4 + title: Send Error Reports to the Google Error Reporting Service API + maintainer: Frans van Dunné + description: Send error reports to the Google Error Reporting service + and view errors and assign error status in the Google Error Reporting user interface. + date_publication: '2022-10-27' + bug_reports: '' + url: https://ixpantia.github.io/googleErrorReportingR/ + url_cran: https://CRAN.R-project.org/package=googleErrorReportingR + url_git: https://github.com/ixpantia/googleErrorReportingR +GoogleImage2Array: + version: 0.99.2 + title: |- + Create Array Data from 2D Image Thumbnails via Google Image + Search + maintainer: Satoshi Kume + description: |- + Images are provided as an array dataset of 2D image thumbnails from Google Image Search . + This array data may be suitable for a training data of machine learning or deep learning as a first trial. + date_publication: '2021-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GoogleImage2Array + url_git: https://github.com/kumeS/GoogleImage2Array +GoogleKnowledgeGraphR: + version: 0.1.0 + title: Retrieve Information from 'Google Knowledge Graph' API + maintainer: Daniel Schmeh + description: Allows you to retrieve information from the 'Google Knowledge Graph' + API + and process it in R in various forms. The 'Knowledge Graph Search' API lets you + find entities in the 'Google Knowledge Graph'. The API uses standard 'schema.org' + types and is compliant with the 'JSON-LD' specification. + date_publication: '2018-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GoogleKnowledgeGraphR + url_git: '' +googleLanguageR: + version: 0.3.0 + title: |- + Call Google's 'Natural Language' API, 'Cloud Translation' API, + 'Cloud Speech' API and 'Cloud Text-to-Speech' API + maintainer: Mark Edmondson + description: |- + Call 'Google Cloud' machine learning APIs for text and speech tasks. + Call the 'Cloud Translation' API for detection + and translation of text, the 'Natural Language' API to + analyse text for sentiment, entities or syntax, the 'Cloud Speech' API + to transcribe sound files to text and + the 'Cloud Text-to-Speech' API to turn text + into sound files. + date_publication: '2020-04-19' + bug_reports: https://github.com/ropensci/googleLanguageR/issues + url: http://code.markedmondson.me/googleLanguageR/ + url_cran: https://CRAN.R-project.org/package=googleLanguageR + url_git: https://github.com/ropensci/googleLanguageR +googlenlp: + version: 0.2.0 + title: An Interface to Google's Cloud Natural Language API + maintainer: Brian Weinstien + description: |- + Interact with Google's Cloud Natural Language API + (v1) via R. The API has + four main features, all of which are available through this + R package: syntax analysis and part-of-speech tagging, entity + analysis, sentiment analysis, and language identification. + date_publication: '2018-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=googlenlp + url_git: https://github.com/BrianWeinstein/googlenlp +googlePolylines: + version: 0.8.5 + title: Encoding Coordinates into 'Google' Polylines + maintainer: David Cooley + description: |- + Encodes simple feature ('sf') objects and coordinates, and decodes polylines + using the 'Google' polyline encoding algorithm (). + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=googlePolylines + url_git: '' +googlePublicData: + version: 0.16.1 + title: Working with Google's 'Public Data Explorer' DSPL Metadata Files + maintainer: George Vega Yon + description: |- + Provides a collection of functions to set up 'Google Public Data Explorer' + data visualization tool with your own data, + building automatically the corresponding DataSet Publishing Language file, or + DSPL (XML), metadata file jointly with the CSV files. All zip-up and ready to + be published in 'Public Data Explorer'. + date_publication: '2017-11-06' + bug_reports: http://github.com/gvegayon/googlePublicData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=googlePublicData + url_git: http://github.com/gvegayon/googlePublicData/ +googlePubsubR: + version: 0.0.4 + title: R Interface for Google 'Cloud Pub/Sub' REST API + maintainer: Andrea Dodet + description: |- + Provides an easy to use interface to the 'Google + Pub/Sub' REST API . + date_publication: '2023-03-03' + bug_reports: https://github.com/andodet/googlePubsubR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=googlePubsubR + url_git: https://github.com/andodet/googlePubsubR +googler: + version: 0.0.1 + title: Google from the R Console + maintainer: Michael W. Kearney + description: |- + This is a wrapper for the command line tool 'googler', which can be + found at the following URL: . + date_publication: '2019-09-04' + bug_reports: https://github.com/mkearney/googler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=googler + url_git: https://github.com/mkearney/googler +googlesheets4: + version: 1.1.1 + title: Access Google Sheets using the Sheets API V4 + maintainer: Jennifer Bryan + description: |- + Interact with Google Sheets through the Sheets API v4 + . "API" is an acronym for + "application programming interface"; the Sheets API allows users to + interact with Google Sheets programmatically, instead of via a web + browser. The "v4" refers to the fact that the Sheets API is currently + at version 4. This package can read and write both the metadata and + the cell data in a Sheet. + date_publication: '2023-06-11' + bug_reports: https://github.com/tidyverse/googlesheets4/issues + url: https://googlesheets4.tidyverse.org + url_cran: https://CRAN.R-project.org/package=googlesheets4 + url_git: https://github.com/tidyverse/googlesheets4 +googleTagManageR: + version: 0.2.0 + title: Access the 'Google Tag Manager' API using R + maintainer: James Cottrill + description: Interact with the 'Google Tag Manager' API , + enabling scripted deployments and updates across multiple tags, triggers, variables + and containers. + date_publication: '2022-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=googleTagManageR + url_git: '' +googletraffic: + version: 0.1.7 + title: Google Traffic + maintainer: Robert Marty + description: Create geographically referenced traffic data from the Google Maps + JavaScript API . + date_publication: '2024-09-04' + bug_reports: https://github.com/dime-worldbank/googletraffic/issues + url: https://dime-worldbank.github.io/googletraffic/ + url_cran: https://CRAN.R-project.org/package=googletraffic + url_git: '' +googleVis: + version: 0.7.3 + title: R Interface to Google Charts + maintainer: Markus Gesmann + description: |- + R interface to Google's chart tools, allowing users + to create interactive charts based on data frames. Charts + are displayed locally via the R HTTP help server. A modern + browser with an Internet connection is required. The data + remains local and is not uploaded to Google. + date_publication: '2024-05-25' + bug_reports: https://github.com/mages/googleVis/issues + url: https://mages.github.io/googleVis/ + url_cran: https://CRAN.R-project.org/package=googleVis + url_git: '' +googleway: + version: 2.7.8 + title: Accesses Google Maps APIs to Retrieve Data and Plot Maps + maintainer: David Cooley + description: |- + Provides a mechanism to plot a 'Google Map' from 'R' and overlay + it with shapes and markers. Also provides access to 'Google Maps' APIs, + including places, directions, roads, distances, geocoding, elevation and + timezone. + date_publication: '2023-08-22' + bug_reports: https://github.com/SymbolixAU/googleway/issues + url: '' + url_cran: https://CRAN.R-project.org/package=googleway + url_git: '' +GOplot: + version: 1.0.2 + title: Visualization of Functional Analysis Data + maintainer: Wencke Walter + description: |- + Implementation of multilayered visualizations for enhanced + graphical representation of functional analysis data. It combines and integrates + omics data derived from expression and functional annotation enrichment + analyses. Its plotting functions have been developed with an hierarchical + structure in mind: starting from a general overview to identify the most + enriched categories (modified bar plot, bubble plot) to a more detailed one + displaying different types of relevant information for the molecules in a given + set of categories (circle plot, chord plot, cluster plot, Venn diagram, heatmap). + date_publication: '2016-03-30' + bug_reports: https://github.com/wencke/wencke.github.io/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GOplot + url_git: https://github.com/wencke/wencke.github.io +gor: + version: '1.0' + title: Algorithms for the Subject Graphs and Network Optimization + maintainer: Cesar Asensio + description: |- + Informal implementation of some algorithms from Graph + Theory and Combinatorial Optimization which arise in the subject + "Graphs and Network Optimization" from first course of the EUPLA + (Escuela Universitaria Politecnica de La Almunia) degree of Data + Engineering in Industrial Processes. + References used are: + Cook et al (1998, ISBN:0-471-55894-X), + Korte, Vygen (2018) , + Hromkovic (2004) , + Hartmann, Weigt (2005, ISBN:978-3-527-40473-5). + date_publication: '2023-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gor + url_git: '' +GORCure: + version: '2.0' + title: |- + Fit Generalized Odds Rate Mixture Cure Model with Interval + Censored Data + maintainer: Jie Zhou + description: Generalized Odds Rate Mixture Cure (GORMC) model is a flexible model + of fitting survival data with a cure fraction, including the Proportional Hazards + Mixture Cure (PHMC) model and the Proportional Odds Mixture Cure Model as special + cases. This package fit the GORMC model with interval censored data. + date_publication: '2017-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GORCure + url_git: '' +goric: + version: 1.1-2 + title: Generalized Order-Restricted Information Criterion + maintainer: Daniel Gerhard + description: Generalized Order-Restricted Information Criterion (GORIC) value for + a set of hypotheses in multivariate linear models and generalised linear models. + date_publication: '2021-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=goric + url_git: '' +gorica: + version: 0.1.4 + title: Evaluation of Inequality Constrained Hypotheses Using GORICA + maintainer: Caspar J. van Lissa + description: |- + Implements the generalized order-restricted information criterion + approximation (GORICA), an AIC-like information criterion that can be + utilized to evaluate informative hypotheses specifying directional + relationships between model parameters in terms of (in)equality + constraints (see Altinisik, Van Lissa, Hoijtink, Oldehinkel, & Kuiper, + 2021), . The GORICA is applicable not only to + normal linear models, but also to generalized linear models (GLMs), + generalized linear mixed models (GLMMs), structural equation models + (SEMs), and contingency tables. For contingency tables, restrictions on cell + probabilities can be non-linear. + date_publication: '2023-10-11' + bug_reports: '' + url: https://informative-hypotheses.sites.uu.nl/software/goric/ + url_cran: https://CRAN.R-project.org/package=gorica + url_git: '' +gosset: + version: '1.4' + title: Tools for Data Analysis in Experimental Agriculture + maintainer: Kauê de Sousa + description: |- + Methods to analyse experimental agriculture data, + from data synthesis to model selection and visualisation. + The package is named after W.S. Gosset aka ‘Student’, a pioneer + of modern statistics in small sample experimental design and analysis. + date_publication: '2024-12-05' + bug_reports: https://github.com/agrdatasci/gosset/issues + url: https://agrdatasci.github.io/gosset/ + url_cran: https://CRAN.R-project.org/package=gosset + url_git: '' +gotop: + version: 0.1.4 + title: Scroll Back to Top Icon in Shiny and R Markdown + maintainer: Félix Luginbuhl + description: |- + Add a scroll back to top 'Font Awesome' icon + in 'rmarkdown' documents and 'shiny' + apps thanks to 'jQuery GoTop' . + date_publication: '2024-05-26' + bug_reports: https://github.com/lgnbhl/gotop/issues/ + url: https://felixluginbuhl.com/gotop/ + url_cran: https://CRAN.R-project.org/package=gotop + url_git: https://github.com/lgnbhl/gotop/ +govdown: + version: 0.10.1 + title: GOV.UK Style Templates for R Markdown + maintainer: Duncan Garmonsway + description: |- + A suite of custom R Markdown formats and templates + for authoring web pages styled with the GOV.UK Design System. + date_publication: '2021-03-10' + bug_reports: https://github.com/ukgovdatascience/govdown/issues + url: https://ukgovdatascience.github.io/govdown/ + url_cran: https://CRAN.R-project.org/package=govdown + url_git: '' +governor: + version: 0.1.3 + title: Speed Limiter to Control Rate of Execution of Loops + maintainer: Mike Cheng + description: |- + It can be necessary to limit the rate of execution of a loop or + repeated function call e.g. to show or gather data only at particular intervals. + This package includes two methods for limiting this execution rate; speed governors + and timers. A speed governor will insert pauses during execution to meet + a user-specified loop time. Timers are alarm clocks which will indicate + whether a certain time has passed. These mechanisms are implemented in 'C' + to minimize processing overhead. + date_publication: '2024-08-25' + bug_reports: https://github.com/coolbutuseless/governor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=governor + url_git: https://github.com/coolbutuseless/governor +govinfoR: + version: 0.0.3 + title: A 'GovInfo' API Wrapper + maintainer: William Blackerby + description: Access data provided by the United States Government Publishing Office + (GPO) 'GovInfo' API (). + date_publication: '2024-02-20' + bug_reports: https://github.com/blackerby/govinfoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=govinfoR + url_git: https://github.com/blackerby/govinfoR +govStatJPN: + version: '0.1' + title: functions to get public survey data in Japan + maintainer: Yuichiro Otani + description: |- + This package purposes to deal with public survey data of + Japanese government via their Application Programming Interface + (http://statdb.nstac.go.jp/) + date_publication: '2013-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=govStatJPN + url_git: '' +gower: + version: 1.0.2 + title: Gower's Distance + maintainer: Mark van der Loo + description: |- + Compute Gower's distance (or similarity) coefficient between records. Compute + the top-n matches between records. Core algorithms are executed in parallel on systems + supporting OpenMP. + date_publication: '2024-12-17' + bug_reports: https://github.com/markvanderloo/gower/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gower + url_git: https://github.com/markvanderloo/gower +goweragreement: + version: 1.0-1 + title: Bayesian Gower Agreement for Categorical Data + maintainer: John Hughes + description: Provides tools for applying the Bayesian Gower agreement methodology + (presented in the package vignette) to nominal or ordinal data. The framework + can accommodate any number of units, any number of coders, and missingness; and + can handle both one-way and two-way random study designs. Influential units and/or + coders can be identified easily using leave-one-out statistics. + date_publication: '2024-09-10' + bug_reports: '' + url: http://www.johnhughes.org + url_cran: https://CRAN.R-project.org/package=goweragreement + url_git: '' +GOxploreR: + version: 1.2.7 + title: Structural Exploration of the Gene Ontology (GO) Knowledge Base + maintainer: Kalifa Manjang + description: |- + It provides an effective, efficient, and fast way to explore the Gene Ontology (GO). + Given a set of genes, the package contains functions to assess the GO and obtain the + terms associated with the genes and the levels of the GO terms. The package provides + functions for the three different GO ontology. We discussed the methods explicitly in + the following article . + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GOxploreR + url_git: '' +goxygen: + version: 1.0.3 + title: In-Code Documentation for 'GAMS' + maintainer: Jan Philipp Dietrich + description: |- + A collection of tools which extract a model documentation from 'GAMS' code and comments. + In order to use the package you need to install 'pandoc' and 'pandoc-citeproc' + first (). + date_publication: '2020-08-16' + bug_reports: https://github.com/pik-piam/goxygen/issues + url: https://doi.org/10.5281/zenodo.1411404 + url_cran: https://CRAN.R-project.org/package=goxygen + url_git: https://github.com/pik-piam/goxygen +gp: + version: '1.1' + title: |- + Maximum Likelihood Estimation of the Generalized Poisson + Distribution + maintainer: Michail Tsagris + description: 'Functions to estimate the parameters of the generalized Poisson distribution + with or without covariates using maximum likelihood. The references include Nikoloulopoulos + A.K. & Karlis D. (2008). "On modeling count data: a comparison of some well-known + discrete distributions". Journal of Statistical Computation and Simulation, 78(3): + 437--457, and Consul P.C. & Famoye F. (1992). + "Generalized Poisson regression model". Communications in Statistics - Theory + and Methods, 21(1): 89--109, .' + date_publication: '2023-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gp + url_git: '' +gpairs: + version: 1.3.3 + title: The Generalized Pairs Plot + maintainer: John W. Emerson + description: Offers a generalization of the scatterplot matrix based on the recognition + that most datasets include both categorical and quantitative information. Traditional + grids of scatterplots often obscure important features of the data when one or + more variables are categorical but coded as numerical. The generalized pairs plot + offers a range of displays of paired combinations of categorical and quantitative + variables. Emerson et al. (2013) . + date_publication: '2020-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gpairs + url_git: '' +GPareto: + version: 1.1.8 + title: Gaussian Processes for Pareto Front Estimation and Optimization + maintainer: Mickael Binois + description: |- + Gaussian process regression models, a.k.a. Kriging models, are + applied to global multi-objective optimization of black-box functions. + Multi-objective Expected Improvement and Step-wise Uncertainty Reduction + sequential infill criteria are available. A quantification of uncertainty + on Pareto fronts is provided using conditional simulations. + date_publication: '2024-01-26' + bug_reports: https://github.com/mbinois/GPareto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GPareto + url_git: https://github.com/mbinois/GPareto +GPArotateDF: + version: 2023.11-1 + title: Derivative Free Gradient Projection Factor Rotation + maintainer: Coen Bernaards + description: |- + Derivative Free Gradient Projection Algorithms for Factor Rotation. + For more details see ?GPArotateDF. Theory for these functions can be found in + the following publications: + Jennrich (2004) . + Bernaards and Jennrich (2005) . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPArotateDF + url_git: '' +GPArotation: + version: 2024.3-1 + title: Gradient Projection Factor Rotation + maintainer: Coen Bernaards + description: |- + Gradient Projection Algorithms for Factor Rotation. + For details see ?GPArotation. When using this package, please cite: + Bernaards and Jennrich (2005) . + "Gradient Projection Algorithms and Software + for Arbitrary Rotation Criteria in Factor Analysis". + date_publication: '2024-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPArotation + url_git: https://optimizer.r-forge.r-project.org/GPArotation_www/ +GPBayes: + version: 0.1.0-6 + title: |- + Tools for Gaussian Process Modeling in Uncertainty + Quantification + maintainer: Pulong Ma + description: 'Gaussian processes (''GPs'') have been widely used to model spatial + data, ''spatio''-temporal data, and computer experiments in diverse areas of statistics + including spatial statistics, ''spatio''-temporal statistics, uncertainty quantification, + and machine learning. This package creates basic tools for fitting and prediction + based on ''GPs'' with spatial data, ''spatio''-temporal data, and computer experiments. + Key characteristics for this GP tool include: (1) the comprehensive implementation + of various covariance functions including the ''Matérn'' family and the Confluent + ''Hypergeometric'' family with isotropic form, tensor form, and automatic relevance + determination form, where the isotropic form is widely used in spatial statistics, + the tensor form is widely used in design and analysis of computer experiments + and uncertainty quantification, and the automatic relevance determination form + is widely used in machine learning; (2) implementations via Markov chain Monte + Carlo (''MCMC'') algorithms and optimization algorithms for GP models with all + the implemented covariance functions. The methods for fitting and prediction are + mainly implemented in a Bayesian framework; (3) model evaluation via Fisher information + and predictive metrics such as predictive scores; (4) built-in functionality for + simulating ''GPs'' with all the implemented covariance functions; (5) unified + implementation to allow easy specification of various ''GPs''.' + date_publication: '2024-04-25' + bug_reports: https://github.com/pulongma/GPBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GPBayes + url_git: '' +gpboost: + version: 1.5.6 + title: |- + Combining Tree-Boosting with Gaussian Process and Mixed Effects + Models + maintainer: Fabio Sigrist + description: An R package that allows for combining tree-boosting with Gaussian + process and mixed effects models. It also allows for independently doing tree-boosting + as well as inference and prediction for Gaussian process and mixed effects models. + See for more information on the software and + Sigrist (2022, JMLR) and Sigrist + (2023, TPAMI) for more information on the methodology. + date_publication: '2025-02-19' + bug_reports: https://github.com/fabsig/GPBoost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gpboost + url_git: https://github.com/fabsig/GPBoost +gpbStat: + version: 0.4.4 + title: Comprehensive Statistical Analysis of Plant Breeding Experiments + maintainer: Nandan Patil + description: Performs statistical data analysis of various Plant Breeding experiments. + Contains functions for Line by Tester analysis as per Arunachalam, V.(1974) + and Diallel analysis as per Griffing, B. (1956) . + date_publication: '2024-10-12' + bug_reports: https://github.com/nandp1/gpbStat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gpbStat + url_git: https://github.com/nandp1/gpbStat/ +GPCERF: + version: 0.2.4 + title: |- + Gaussian Processes for Estimating Causal Exposure Response + Curves + maintainer: Boyu Ren + description: 'Provides a non-parametric Bayesian framework based on Gaussian process + priors for estimating causal effects of a continuous exposure and detecting change + points in the causal exposure response curves using observational data. Ren, B., + Wu, X., Braun, D., Pillai, N., & Dominici, F.(2021). "Bayesian modeling for exposure + response curve via gaussian processes: Causal effects of exposure to air pollution + on health outcomes." arXiv preprint .' + date_publication: '2024-04-15' + bug_reports: https://github.com/NSAPH-Software/GPCERF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GPCERF + url_git: https://github.com/NSAPH-Software/GPCERF +GPCMlasso: + version: 0.1-7 + title: |- + Differential Item Functioning in Generalized Partial Credit + Models + maintainer: Gunther Schauberger + description: Provides a framework to detect Differential Item Functioning (DIF) + in Generalized Partial Credit Models (GPCM) and special cases of the GPCM as proposed + by Schauberger and Mair (2019) . A joint model + is set up where DIF is explicitly parametrized and penalized likelihood estimation + is used for parameter selection. The big advantage of the method called GPCMlasso + is that several variables can be treated simultaneously and that both continuous + and categorical variables can be used to detect DIF. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPCMlasso + url_git: '' +gpcp: + version: 0.1.0 + title: Genomic Prediction of Cross Performance + maintainer: Christine Nyaga + description: |- + This function performs genomic prediction of cross performance using genotype and phenotype data. + It processes data in several steps including loading necessary software, converting genotype data, processing phenotype data, + fitting mixed models, and predicting cross performance based on weighted marker effects. + For more information, see Labroo et al. (2023) . + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gpcp + url_git: '' +GPCsign: + version: 0.1.1 + title: |- + Gaussian Process Classification as Described in Bachoc et al. + (2020) + maintainer: Morgane Menz + description: 'Parameter estimation and prediction of Gaussian Process Classifier + models as described in Bachoc et al. (2020) . + Important functions : gpcm(), predict.gpcm(), update.gpcm().' + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPCsign + url_git: '' +GPEMR: + version: 0.1.0 + title: Growth Parameter Estimation Method + maintainer: Ruqaiya Shaikh + description: Provides functions for simulating and estimating parameters of various + growth models, including Logistic, Exponential, Theta-logistic, Von-Bertalanffy, + and Gompertz models. The package supports both simulated and real data analysis, + including parameter estimation, visualization, and calculation of global and local + estimates. The methods are based on research described by Md Aktar Ul Karim and + Amiya Ranjan Bhowmick (2022) in (). + An interactive web application is also available at [GPEMR Web App](). + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPEMR + url_git: '' +GPFDA: + version: 3.1.3 + title: Gaussian Process for Functional Data Analysis + maintainer: Evandro Konzen + description: |- + Functionalities for modelling functional data with + multidimensional inputs, multivariate functional data, and non-separable + and/or non-stationary covariance structure of function-valued processes. + In addition, there are functionalities for functional regression models where + the mean function depends on scalar and/or functional covariates and + the covariance structure depends on functional covariates. + The development version of the package can be found on + . + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPFDA + url_git: '' +GPfit: + version: 1.0-8 + title: Gaussian Processes Modeling + maintainer: Hugh Chipman + description: A computationally stable approach of fitting a Gaussian Process (GP) + model to a deterministic simulator. + date_publication: '2019-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPfit + url_git: '' +gpg: + version: 1.3.0 + title: GNU Privacy Guard for R + maintainer: Jeroen Ooms + description: |- + Bindings to GnuPG for working with OpenGPG (RFC4880) cryptographic + methods. Includes utilities for public key encryption, creating and verifying + digital signatures, and managing your local keyring. Some functionality + depends on the version of GnuPG that is installed on the system. On Windows + this package can be used together with 'GPG4Win' which provides a GUI for + managing keys and entering passphrases. + date_publication: '2024-09-20' + bug_reports: https://github.com/jeroen/gpg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gpg + url_git: https://github.com/jeroen/gpg +GPGame: + version: 1.2.0 + title: Solving Complex Game Problems using Gaussian Processes + maintainer: Victor Picheny + description: Sequential strategies for finding a game equilibrium are proposed in + a black-box setting (expensive pay-off evaluations, no derivatives). The algorithm + handles noiseless or noisy evaluations. Two acquisition functions are available. + Graphical outputs can be generated automatically. V. Picheny, M. Binois, A. Habbal + (2018) . M. Binois, V. Picheny, P. Taillandier, + A. Habbal (2020) . + date_publication: '2022-01-23' + bug_reports: https://github.com/vpicheny/GPGame/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GPGame + url_git: https://github.com/vpicheny/GPGame +GpGp: + version: 0.5.1 + title: Fast Gaussian Process Computation Using Vecchia's Approximation + maintainer: Joseph Guinness + description: |- + Functions for fitting and doing predictions with + Gaussian process models using Vecchia's (1988) approximation. + Package also includes functions for reordering input locations, + finding ordered nearest neighbors (with help from 'FNN' package), + grouping operations, and conditional simulations. + Covariance functions for spatial and spatial-temporal data + on Euclidean domains and spheres are provided. The original + approximation is due to Vecchia (1988) + , and the reordering and + grouping methods are from Guinness (2018) + . + Model fitting employs a Fisher scoring algorithm described + in Guinness (2019) . + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GpGp + url_git: '' +gpindex: + version: 0.6.2 + title: Generalized Price and Quantity Indexes + maintainer: Steve Martin + description: |- + Tools to build and work with bilateral generalized-mean + price indexes (and by extension quantity indexes), and indexes composed of + generalized-mean indexes (e.g., superlative quadratic-mean indexes, GEKS). + Covers the core mathematical machinery for making bilateral price indexes, + computing price relatives, detecting outliers, and decomposing indexes, + with wrappers for all common (and many uncommon) index-number + formulas. Implements and extends many of the methods in + Balk (2008, ), von der Lippe (2007, + ), and the CPI manual (2020, + ). + date_publication: '2024-08-16' + bug_reports: https://github.com/marberts/gpindex/issues + url: https://marberts.github.io/gpindex/ + url_cran: https://CRAN.R-project.org/package=gpindex + url_git: https://github.com/marberts/gpindex +gpk: + version: '1.0' + title: 100 Data Sets for Statistics Education + maintainer: Prabhanjan Tattar + description: Collection of datasets as prepared by Profs. A.P. Gore, S.A. Paranjape, + and M.B. Kulkarni of Department of Statistics, Poona University, India. With their + permission, first letter of their names forms the name of this package, the package + has been built by me and made available for the benefit of R users. This collection + requires a rich class of models and can be a very useful building block for a + beginner. + date_publication: '2013-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gpk + url_git: '' +gpkg: + version: 0.0.8 + title: Utilities for the Open Geospatial Consortium 'GeoPackage' Format + maintainer: Andrew Brown + description: Build Open Geospatial Consortium 'GeoPackage' files (). + 'GDAL' utilities for reading and writing spatial data are provided by the 'terra' + package. Additional 'GeoPackage' and 'SQLite' features for attributes and tabular + data are implemented with the 'RSQLite' package. + date_publication: '2024-02-20' + bug_reports: https://github.com/brownag/gpkg/issues + url: https://humus.rocks/gpkg/ + url_cran: https://CRAN.R-project.org/package=gpkg + url_git: https://github.com/brownag/gpkg +GPL2025: + version: 1.0.1 + title: |- + Convert Chip ID of the GPL2015 into GeneBank Accession and + ENTREZID + maintainer: Xiang Li + description: |- + Convert the chip ID of GPL2025 + to GeneBank Accession and ENTREZID . + date_publication: '2020-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPL2025 + url_git: '' +gplite: + version: 0.13.0 + title: General Purpose Gaussian Process Modelling + maintainer: Juho Piironen + description: |2- + + Implements the most common Gaussian process (GP) models using Laplace and + expectation propagation (EP) approximations, maximum marginal likelihood + (or posterior) inference for the hyperparameters, and sparse approximations + for larger datasets. + date_publication: '2022-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gplite + url_git: '' +gplm: + version: 0.7-4 + title: Generalized Partial Linear Models (GPLM) + maintainer: Marlene Mueller + description: |- + Provides functions for estimating a generalized partial + linear model, a semiparametric variant of the generalized linear model + (GLM) which replaces the linear predictor by the sum of a linear + and a nonparametric function. + date_publication: '2016-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gplm + url_git: '' +gplots: + version: 3.2.0 + title: Various R Programming Tools for Plotting Data + maintainer: Tal Galili + description: |- + Various R programming tools for plotting data, including: + - calculating and plotting locally smoothed summary function as + ('bandplot', 'wapply'), + - enhanced versions of standard plots ('barplot2', 'boxplot2', + 'heatmap.2', 'smartlegend'), + - manipulating colors ('col2hex', 'colorpanel', 'redgreen', + 'greenred', 'bluered', 'redblue', 'rich.colors'), + - calculating and plotting two-dimensional data summaries ('ci2d', + 'hist2d'), + - enhanced regression diagnostic plots ('lmplot2', 'residplot'), + - formula-enabled interface to 'stats::lowess' function ('lowess'), + - displaying textual data in plots ('textplot', 'sinkplot'), + - plotting dots whose size reflects the relative magnitude of the + elements ('balloonplot', 'bubbleplot'), + - plotting "Venn" diagrams ('venn'), + - displaying Open-Office style plots ('ooplot'), + - plotting multiple data on same region, with separate axes + ('overplot'), + - plotting means and confidence intervals ('plotCI', 'plotmeans'), + - spacing points in an x-y plot so they don't overlap ('space'). + date_publication: '2024-10-05' + bug_reports: https://github.com/talgalili/gplots/issues + url: https://talgalili.github.io/gplots/ + url_cran: https://CRAN.R-project.org/package=gplots + url_git: https://github.com/talgalili/gplots +gplsim: + version: 1.0.0 + title: Spline Estimation for GPLSIM + maintainer: Tianhai Zu + description: |- + We provides functions that employ splines to estimate generalized + partially linear single index models (GPLSIM), which extend the generalized linear + models to include nonlinear effect for some predictors. Please see Y. (2017) at + and Y., and R. (2002) at for more details. + date_publication: '2023-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gplsim + url_git: '' +GPLTR: + version: '1.5' + title: Generalized Partially Linear Tree-Based Regression Model + maintainer: Cyprien Mbogning + description: |- + Combining a generalized linear model with an additional tree part + on the same scale. A four-step procedure is proposed to fit the model and test + the joint effect of the selected tree part while adjusting on confounding factors. + We also proposed an ensemble procedure based on the bagging to improve prediction + accuracy and computed several scores of importance for variable selection. + See 'Cyprien Mbogning et al.'(2014) and + 'Cyprien Mbogning et al.'(2015) + for an overview of all the methods implemented in this package. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPLTR + url_git: '' +GPM: + version: 3.0.1 + title: |- + Gaussian Process Modeling of Multi-Response and Possibly Noisy + Datasets + maintainer: Ramin Bostanabad + description: Provides a general and efficient tool for fitting a response surface + to a dataset via Gaussian processes. The dataset can have multiple responses and + be noisy (with stationary variance). The fitted GP model can predict the gradient + as well. The package is based on the work of Bostanabad, R., Kearney, T., Tao, + S. Y., Apley, D. W. & Chen, W. (2018) Leveraging the nugget parameter for efficient + Gaussian process modeling. International Journal for Numerical Methods in Engineering, + 114, 501-516. + date_publication: '2019-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPM + url_git: '' +gpmap: + version: 0.1.2 + title: Analysing and Plotting Genotype-Phenotype Maps + maintainer: Arne B. Gjuvsland + description: 'Tools for studying genotype-phenotype maps for bi-allelic loci underlying + quantitative phenotypes. The 0.1 version is released in connection with the publication + of Gjuvsland et al (2013) and implements basic line plots and the monotonicity + measures for GP maps presented in the paper. Reference: Gjuvsland AB, Wang Y, + Plahte E and Omholt SW (2013) Monotonicity is a key feature of genotype-phenotype + maps. Frontier in Genetics 4:216 .' + date_publication: '2021-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gpmap + url_git: '' +GPoM: + version: '1.4' + title: Generalized Polynomial Modelling + maintainer: Mireille Huc + description: |- + Platform dedicated to the Global Modelling technique. Its aim + is to obtain ordinary differential equations of polynomial form directly + from time series. It can be applied to single or multiple time series under + various conditions of noise, time series lengths, sampling, etc. This platform + is developped at the Centre d'Etudes Spatiales de la Biosphere (CESBIO), + UMR 5126 UPS/CNRS/CNES/IRD, 18 av. Edouard Belin, 31401 TOULOUSE, FRANCE. + The developments were funded by the French program Les Enveloppes Fluides + et l'Environnement (LEFE, MANU, projets GloMo, SpatioGloMo and MoMu). The + French program Defi InFiNiTi (CNRS) and PNTS are also acknowledged (projects + Crops'IChaos and Musc & SlowFast). The method is described in the article : + Mangiarotti S. and Huc M. (2019) . + date_publication: '2023-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPoM + url_git: '' +GPP: + version: '0.1' + title: Gaussian Process Projection + maintainer: David Carlson + description: Estimates a counterfactual using Gaussian process projection. It takes + a dataframe, creates missingness in the desired outcome variable and estimates + counterfactual values based on all information in the dataframe. The package writes + Stan code, checks it for convergence and adds artificial noise to prevent overfitting + and returns a plot of actual values and estimated counterfactual values using + r-base plot. + date_publication: '2020-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPP + url_git: '' +GPRMortality: + version: 0.1.0 + title: Gaussian Process Regression for Mortality Rates + maintainer: Ali Ghanbari + description: 'A Bayesian statistical model for estimating child (under-five age + group) and adult (15-60 age group) mortality. The main challenge is how to combine + and integrate these different time series and how to produce unified estimates + of mortality rates during a specified time span. GPR is a Bayesian statistical + model for estimating child and adult mortality rates which its data likelihood + is mortality rates from different data sources such as: Death Registration System, + Censuses or surveys. There are also various hyper-parameters for completeness + of DRS, mean, covariance functions and variances as priors. This function produces + estimations and uncertainty (95% or any desirable percentiles) based on sampling + and non-sampling errors due to variation in data sources. The GP model utilizes + Bayesian inference to update predicted mortality rates as a posterior in Bayes + rule by combining data and a prior probability distribution over parameters in + mean, covariance function, and the regression model. This package uses Markov + Chain Monte Carlo (MCMC) to sample from posterior probability distribution by + ''rstan'' package in R. Details are given in Wang H, Dwyer-Lindgren L, Lofgren + KT, et al. (2012) , Wang H, Liddell CA, Coates + MM, et al. (2014) and Mohammadi, Parsaeian, + Mehdipour et al. (2017) .' + date_publication: '2018-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPRMortality + url_git: '' +gProfileR: + version: 0.7.0 + title: Interface to the 'g:Profiler' Toolkit + maintainer: Ivan Kuzmin + description: |- + This package has been deprecated and will not be updated. + New users should use the package 'gprofiler2' () + for up-to-date data and improved functionality. + Functional enrichment analysis, gene identifier conversion and + mapping homologous genes across related organisms via the 'g:Profiler' toolkit + (). + date_publication: '2019-11-04' + bug_reports: http://biit.cs.ut.ee/gprofiler/contact.cgi + url: '' + url_cran: https://CRAN.R-project.org/package=gProfileR + url_git: '' +gprofiler2: + version: 0.2.3 + title: Interface to the 'g:Profiler' Toolset + maintainer: Liis Kolberg + description: |- + A toolset for functional enrichment analysis and visualization, gene/protein/SNP identifier conversion and mapping orthologous genes across species via 'g:Profiler' (). + The main tools are: + (1) 'g:GOSt' - functional enrichment analysis and visualization of gene lists; + (2) 'g:Convert' - gene/protein/transcript identifier conversion across various namespaces; + (3) 'g:Orth' - orthology search across species; + (4) 'g:SNPense' - mapping SNP rs identifiers to chromosome positions, genes and variant effects. + This package is an R interface corresponding to the 2019 update of 'g:Profiler' and provides access to 'g:Profiler' for versions 'e94_eg41_p11' and higher. See the package 'gProfileR' for accessing older versions from the 'g:Profiler' toolset. + date_publication: '2024-02-23' + bug_reports: https://biit.cs.ut.ee/gprofiler/page/contact + url: '' + url_cran: https://CRAN.R-project.org/package=gprofiler2 + url_git: '' +gps: + version: '1.2' + title: General P-Splines + maintainer: Zheyuan Li + description: General P-splines are non-uniform B-splines penalized by a general + difference penalty, proposed by Li and Cao (2022) . Constructible + on arbitrary knots, they extend the standard P-splines of Eilers and Marx (1996) + . They are also related to the O-splines of O'Sullivan + (1986) via a sandwich formula that links a general + difference penalty to a derivative penalty. The package includes routines for + setting up and handling difference and derivative penalties. It also fits P-splines + and O-splines to (x, y) data (optionally weighted) for a grid of smoothing parameter + values in the automatic search intervals of Li and Cao (2023) . + It aims to facilitate other packages to implement P-splines or O-splines as a + smoothing tool in their model estimation framework. + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gps + url_git: https://github.com/ZheyuanLi/gps +gps.track: + version: 1.0.0 + title: GPS Track Point Information Extractor + maintainer: Wagner Martins dos Santos + description: Focused on extracting important data from track points such as speed, + distance, elevation difference and azimuth.(PLAZA, J. et al., 2022) . + date_publication: '2023-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gps.track + url_git: '' +GPSCDF: + version: 0.1.1 + title: Generalized Propensity Score Cumulative Distribution Function + maintainer: Derek W. Brown + description: |- + Implements the generalized propensity score cumulative distribution + function proposed by Greene (2017) + . + A single scalar balancing score is calculated for any generalized propensity + score vector with three or more treatments. This balancing score is used for + propensity score matching and stratification in outcome analyses when analyzing + either ordinal or multinomial treatments. + date_publication: '2019-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPSCDF + url_git: '' +GPSeqClus: + version: 1.4.0 + title: Sequential Clustering Algorithm for Location Data + maintainer: Justin Clapp + description: |- + Applies sequential clustering algorithm to animal location data + based on user-defined parameters. Plots interactive cluster maps and + provides a summary dataframe with attributes for each cluster commonly + used as covariates in subsequent modeling efforts. Additional functions + provide individual keyhole markup language plots for quick assessment, + and export of global positioning system exchange format files for + navigation purposes. + Methods can be found at . + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPSeqClus + url_git: '' +gptoolsStan: + version: 0.2.0 + title: Gaussian Processes on Graphs and Lattices in 'Stan' + maintainer: Till Hoffmann + description: |- + Gaussian processes are flexible distributions to model functional data. Whilst + theoretically appealing, they are computationally cumbersome except for small datasets. + This package implements two methods for scaling Gaussian process inference in 'Stan'. First, a + sparse approximation of the likelihood that is generally applicable and, second, an exact method + for regularly spaced data modeled by stationary kernels using fast Fourier methods. Utility + functions are provided to compile and fit 'Stan' models using the 'cmdstanr' interface. + References: Hoffmann and Onnela (2022) . + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gptoolsStan + url_git: '' +gptr: + version: 0.6.0 + title: A Convenient R Interface with the OpenAI 'ChatGPT' API + maintainer: Wanjun Gu + description: A convenient interface with the OpenAI 'ChatGPT' API . + 'gptr' allows you to interact with 'ChatGPT', a powerful language model, for various + natural language processing tasks. The 'gptr' R package makes talking to 'ChatGPT' + in R super easy. It helps researchers and data folks by simplifying the complicated + stuff, like asking questions and getting answers. With 'gptr', you can use 'ChatGPT' + in R without any hassle, making it simpler for everyone to do cool things with + language! + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gptr + url_git: '' +GPTreeO: + version: 1.0.1 + title: Dividing Local Gaussian Processes for Online Learning Regression + maintainer: Timo Braun + description: |- + We implement and extend the Dividing Local Gaussian Process + algorithm by Lederer et al. (2020) . Its + main use case is in online learning where it is used to train a network of + local GPs (referred to as tree) by cleverly partitioning the input space. + In contrast to a single GP, 'GPTreeO' is able to deal with larger amounts of + data. The package includes methods to create the tree and set its + parameter, incorporating data points from a data stream as well as making + joint predictions based on all relevant local GPs. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPTreeO + url_git: '' +gptstudio: + version: 0.4.0 + title: |- + Use Large Language Models Directly in your Development + Environment + maintainer: James Wade + description: |- + Large language models are readily accessible via API. This + package lowers the barrier to use the API inside of your development + environment. For more on the API, see + . + date_publication: '2024-05-21' + bug_reports: https://github.com/MichelNivard/gptstudio/issues + url: https://michelnivard.github.io/gptstudio/ + url_cran: https://CRAN.R-project.org/package=gptstudio + url_git: https://github.com/MichelNivard/gptstudio +gptzeror: + version: 0.0.1 + title: Identify Text Written by Large Language Models using 'GPTZero' + maintainer: Christopher T. Kenny + description: |- + An R interface to the 'GPTZero' API (). Allows + users to classify text into human and computer written with probabilities. Formats + the data into data frames where each sentence is an observation. Paragraph-level + and document-level predictions are organized to align with the sentences. + date_publication: '2023-06-05' + bug_reports: https://github.com/christopherkenny/gptzeror/issues + url: https://christophertkenny.com/gptzeror/ + url_cran: https://CRAN.R-project.org/package=gptzeror + url_git: https://github.com/christopherkenny/gptzeror +GPUmatrix: + version: 1.0.2 + title: Basic Linear Algebra with GPU + maintainer: Cesar Lobato-Fernandez + description: 'GPUs are great resources for data analysis, especially in statistics + and linear algebra. Unfortunately, very few packages connect R to the GPU, and + none of them are transparent enough to run the computations on the GPU without + substantial changes to the code. The maintenance of these packages is cumbersome: + several of the earlier attempts have been removed from their respective repositories. + It would be desirable to have a properly maintained R package that takes advantage + of the GPU with minimal changes to the existing code. We have developed the GPUmatrix + package (available on CRAN). GPUmatrix mimics the behavior of the Matrix package + and extends R to use the GPU for computations. It includes single(FP32) and double(FP64) + precision data types, and provides support for sparse matrices. It is easy to + learn, and requires very few code changes to perform the operations on the GPU. + GPUmatrix relies on either the Torch or Tensorflow R packages to perform the GPU + operations. We have demonstrated its usefulness for several statistical applications + and machine learning applications: non-negative matrix factorization, logistic + regression and general linear models. We have also included a comparison of GPU + and CPU performance on different matrix operations.' + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPUmatrix + url_git: '' +gpuR: + version: 2.0.6 + title: GPU Functions for R Objects + maintainer: Ruoyong Xu + description: |- + Provides GPU enabled functions for 'R' objects in a simple and + approachable manner. New 'gpu*' and 'vcl*' classes have been provided to + wrap typical 'R' objects (e.g. vector, matrix), in both host and device + spaces, to mirror typical 'R' syntax without the need to know 'OpenCL'. + date_publication: '2024-05-23' + bug_reports: https://github.com/cdeterman/gpuR/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=gpuR + url_git: https://github.com/eborgnine/gpuR +GPvam: + version: 3.2-0 + title: |- + Maximum Likelihood Estimation of Multiple Membership Mixed + Models Used in Value-Added Modeling + maintainer: Andrew Karl + description: An EM algorithm, Karl et al. (2013) , + is used to estimate the generalized, variable, and complete persistence models, + Mariano et al. (2010) . These are multiple-membership + linear mixed models with teachers modeled as "G-side" effects and students modeled + with either "G-side" or "R-side" effects. + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPvam + url_git: '' +GPvecchia: + version: 0.1.7 + title: Scalable Gaussian-Process Approximations + maintainer: Marcin Jurek + description: Fast scalable Gaussian process approximations, particularly well suited + to spatial (aerial, remote-sensed) and environmental data, described in more detail + in Katzfuss and Guinness (2017) . Package also contains a fast + implementation of the incomplete Cholesky decomposition (IC0), based on Schaefer + et al. (2019) and MaxMin ordering proposed in Guinness (2018) + . + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GPvecchia + url_git: '' +gpx: + version: 1.1.0 + title: Process GPX Files into R Data Structures + maintainer: Mark Ewing + description: Process open standard GPX files into data.frames for further use and + analysis in R. + date_publication: '2021-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gpx + url_git: '' +gqlr: + version: 0.0.2 + title: '''GraphQL'' Server in R' + maintainer: Barret Schloerke + description: |- + Server implementation of 'GraphQL' , + a query language originally created by Facebook for describing data requirements on complex application + data models. Visit to learn more about 'GraphQL'. + date_publication: '2019-12-02' + bug_reports: https://github.com/schloerke/gqlr/issues + url: http://graphql.github.io/graphql-spec/ + url_cran: https://CRAN.R-project.org/package=gqlr + url_git: https://github.com/schloerke/gqlr +gquad: + version: 2.1-2 + title: Prediction of G Quadruplexes and Other Non-B DNA Motifs + maintainer: Hannah O. Ajoge + description: Genomic biology is not limited to the confines of the canonical B-forming + DNA duplex, but includes over ten different types of other secondary structures + that are collectively termed non-B DNA structures. Of these non-B DNA structures, + the G-quadruplexes are highly stable four-stranded structures that are recognized + by distinct subsets of nuclear factors. This package provide functions for predicting + intramolecular G quadruplexes. In addition, functions for predicting other intramolecular + nonB DNA structures are included. + date_publication: '2022-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gquad + url_git: '' +grabsampling: + version: 1.0.0 + title: Probability of Detection for Grab Sample Selection + maintainer: Mayooran Thevaraja + description: Functions for obtaining the probability of detection, for grab samples + selection by using two different methods such as systematic or random based on + two-state Markov chain model. For detection probability calculation, we used results + from Bhat, U. and Lal, R. (1988) . + date_publication: '2020-03-04' + bug_reports: https://github.com/Mayooran1987/grabsampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grabsampling + url_git: https://github.com/Mayooran1987/grabsampling +GrabSVG: + version: 0.0.2 + title: Granularity-Based Spatially Variable Genes Identifications + maintainer: Jinpu Li + description: Identifying spatially variable genes is critical in linking molecular + cell functions with tissue phenotypes. This package implemented a granularity-based + dimension-agnostic tool for the identification of spatially variable genes. The + detailed description of this method is available at Wang, J. and Li, J. et al. + 2023 (Wang, J. and Li, J. (2023), ). + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GrabSVG + url_git: '' +Grace: + version: 0.5.3 + title: Graph-Constrained Estimation and Hypothesis Tests + maintainer: Sen Zhao + description: Use the graph-constrained estimation (Grace) procedure (Zhao and Shojaie, + 2016 ) to estimate graph-guided linear regression coefficients + and use the Grace/GraceI/GraceR tests to perform graph-guided hypothesis tests + on the association between the response and the predictors. + date_publication: '2017-04-09' + bug_reports: '' + url: http://onlinelibrary.wiley.com/doi/10.1111/biom.12418/abstract + url_cran: https://CRAN.R-project.org/package=Grace + url_git: '' +grade: + version: 0.2-1 + title: Binary Grading functions for R. + maintainer: Leif Johnson + description: Provides functions for matching student-answers to teacher answers + for a variety of data types. + date_publication: '2013-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grade + url_git: https://github.com/ltjohnson/grade +gradeR: + version: 1.0.10 + title: Helps Grade Assignment Submissions that are R Scripts + maintainer: Taylor Brown + description: After being given the location of your students' submissions and a + test file, the function runs each .R file, and evaluates the results from all + the given tests. Results are neatly returned in a data frame that has a row for + each student, and a column for each test. + date_publication: '2021-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gradeR + url_git: '' +graDiEnt: + version: 1.0.1 + title: Stochastic Quasi-Gradient Differential Evolution Optimization + maintainer: Brendan Matthew Galdo + description: An optim-style implementation of the Stochastic Quasi-Gradient Differential + Evolution (SQG-DE) optimization algorithm first published by Sala, Baldanzini, + and Pierini (2018; ). This optimization algorithm + fuses the robustness of the population-based global optimization algorithm "Differential + Evolution" with the efficiency of gradient-based optimization. The derivative-free + algorithm uses population members to build stochastic gradient estimates, without + any additional objective function evaluations. Sala, Baldanzini, and Pierini argue + this algorithm is useful for 'difficult optimization problems under a tight function + evaluation budget.' This package can run SQG-DE in parallel and sequentially. + date_publication: '2022-05-10' + bug_reports: https://github.com/bmgaldo/graDiEnt + url: '' + url_cran: https://CRAN.R-project.org/package=graDiEnt + url_git: https://github.com/bmgaldo/graDiEnt +gradientPickerD3: + version: 0.1.0.0 + title: |- + Interactive Color Gradient Picker Using 'htmlwidgets' and the + Modified JS Script 'jquery-gradient-picker' + maintainer: Christian D. Peikert + description: 'Widget for an interactive selection and modification of a color gradient. + ''gradientPickerD3'' allows addition, removement and replacement of color ticks. + List of numeric values will automatically translate in their corresponding tick + position within the numeric range. App returns a data.frame containing tick values, + colors and the positions in percent (0.0 to 1.0) for each color tick in the gradient. + The original JS ''jquery-gradient-picker'' was implemented by Matt Crinklaw-Vogt + (nick: tantaman) . Widget and JS modifications were + done by CD. Peikert.' + date_publication: '2017-09-15' + bug_reports: https://github.com/peikert/gradientPickerD3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gradientPickerD3 + url_git: https://github.com/peikert/gradientPickerD3 +grafify: + version: 4.0.1 + title: Easy Graphs for Data Visualisation and Linear Models for ANOVA + maintainer: Avinash R Shenoy + description: 'Easily explore data by plotting graphs with a few lines of code. Use + these ggplot() wrappers to quickly draw graphs of scatter/dots with box-whiskers, + violins or SD error bars, data distributions, before-after graphs, factorial ANOVA + and more. Customise graphs in many ways, for example, by choosing from colour + blind-friendly palettes (12 discreet, 3 continuous and 2 divergent palettes). + Use the simple code for ANOVA as ordinary (lm()) or mixed-effects linear models + (lmer()), including randomised-block or repeated-measures designs, and fit non-linear + outcomes as a generalised additive model (gam) using mgcv(). Obtain estimated + marginal means and perform post-hoc comparisons on fitted models (via emmeans()). + Also includes small datasets for practising code and teaching basics before users + move on to more complex designs. See vignettes for details on usage . + Citation: .' + date_publication: '2024-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grafify + url_git: https://github.com/ashenoy-cmbi/grafify +grafzahl: + version: 0.0.11 + title: |- + Supervised Machine Learning for Textual Data Using Transformers + and 'Quanteda' + maintainer: Chung-hong Chan + description: 'Duct tape the ''quanteda'' ecosystem (Benoit et al., 2018) + to modern Transformer-based text classification models (Wolf et al., 2020) , + in order to facilitate supervised machine learning for textual data. This package + mimics the behaviors of ''quanteda.textmodels'' and provides a function to setup + the ''Python'' environment to use the pretrained models from ''Hugging Face'' + . More information: .' + date_publication: '2024-03-26' + bug_reports: https://github.com/gesistsa/grafzahl/issues + url: https://gesistsa.github.io/grafzahl/ + url_cran: https://CRAN.R-project.org/package=grafzahl + url_git: https://github.com/gesistsa/grafzahl +gRain: + version: 1.4.5 + title: Bayesian Networks + maintainer: Søren Højsgaard + description: |- + Probability propagation in Bayesian networks, also known as graphical independence networks. Documentation + of the package is provided in vignettes included in the package and in + the paper by Højsgaard (2012, ). + See 'citation("gRain")' for details. + date_publication: '2024-10-17' + bug_reports: '' + url: https://people.math.aau.dk/~sorenh/software/gR/ + url_cran: https://CRAN.R-project.org/package=gRain + url_git: '' +grainscape: + version: 0.5.0 + title: Landscape Connectivity, Habitat, and Protected Area Networks + maintainer: Alex M Chubaty + description: |- + Given a landscape resistance surface, creates minimum planar graph + (Fall et al. (2007) ) and grains of connectivity + (Galpern et al. (2012) ) models that can be + used to calculate effective distances for landscape connectivity at multiple scales. + Documentation is provided by several vignettes, and a paper + (Chubaty, Galpern & Doctolero (2020) ). + date_publication: '2025-01-15' + bug_reports: https://github.com/achubaty/grainscape/issues + url: https://www.alexchubaty.com/grainscape/ + url_cran: https://CRAN.R-project.org/package=grainscape + url_git: https://github.com/achubaty/grainscape +gramEvol: + version: 2.1-4 + title: Grammatical Evolution for R + maintainer: Farzad Noorian + description: |- + A native R implementation of grammatical evolution (GE). + GE facilitates the discovery of programs that can achieve a desired goal. + This is done by performing an evolutionary optimisation over a population + of R expressions generated via a user-defined context-free grammar (CFG) + and cost function. + date_publication: '2020-07-18' + bug_reports: https://github.com/fnoorian/gramEvol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gramEvol + url_git: https://github.com/fnoorian/gramEvol/ +GramQuad: + version: 0.1.1 + title: Gram Quadrature + maintainer: Iago Giné-Vázquez + description: Numerical integration with Gram polynomials (based on + [math.NA] 28 Jun 2021, by Irfan Muhammad [School of Computer Science, University + of Birmingham, UK]). + date_publication: '2022-07-09' + bug_reports: https://gitlab.com/iagogv/GramQuad/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GramQuad + url_git: https://gitlab.com/iagogv/GramQuad +grand: + version: 0.9.0 + title: Guidelines for Reporting About Network Data + maintainer: Zachary Neal + description: Interactively applies the Guidelines for Reporting About Network Data + (GRAND) to an 'igraph' object, and generates a uniform narrative or tabular description + of the object. + date_publication: '2023-02-10' + bug_reports: https://github.com/zpneal/grand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grand + url_git: https://github.com/zpneal/grand +grandR: + version: 0.2.6 + title: Comprehensive Analysis of Nucleotide Conversion Sequencing Data + maintainer: Florian Erhard + description: |- + Nucleotide conversion sequencing experiments have been + developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such + experiments require specialized tools for primary processing such as GRAND-SLAM, + (see 'Jürges et al' ) and specialized tools for + downstream analyses. 'grandR' provides a comprehensive toolbox for quality control, + kinetic modeling, differential gene expression analysis and visualization of such data. + date_publication: '2025-01-22' + bug_reports: https://github.com/erhard-lab/grandR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grandR + url_git: https://github.com/erhard-lab/grandR +grangers: + version: 0.1.0 + title: Inference on Granger-Causality in the Frequency Domain + maintainer: Matteo Farne' + description: Contains five functions performing the calculation of unconditional + and conditional Granger-causality spectra, bootstrap inference on both, and inference + on the difference between them via the bootstrap approach of Farne' and Montanari, + 2018 . + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grangers + url_git: https://github.com/MatFar88/grangers +granova: + version: '2.2' + title: Graphical Analysis of Variance + maintainer: Frederic Bertrand + description: |- + This small collection of functions provides what we call elemental graphics for display of analysis of variance + results, David C. Hoaglin, Frederick Mosteller and John W. Tukey (1991, ISBN:978-0-471-52735-0), Paul R. Rosenbaum (1989) + , Robert M. Pruzek and James E. Helmreich . + The term elemental derives from the fact that each function is aimed at construction of + graphical displays that afford direct visualizations of data with respect to the fundamental + questions that drive the particular analysis of variance methods. These functions can be + particularly helpful for students and non-statistician analysts. But these methods should be + quite generally helpful for work-a-day applications of all kinds, as they can help to identify + outliers, clusters or patterns, as well as highlight the role of non-linear transformations of data. + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=granova + url_git: '' +granovaGG: + version: 1.4.1 + title: Graphical Analysis of Variance Using ggplot2 + maintainer: Brian A. Danielak + description: |- + Create what we call Elemental Graphics for display of + anova results. The term elemental derives from the fact + that each function is aimed at construction of + graphical displays that afford direct visualizations of + data with respect to the fundamental questions that + drive the particular anova methods. This package + represents a modification of the original granova + package; the key change is to use 'ggplot2', Hadley + Wickham's package based on Grammar of Graphics concepts + (due to Wilkinson). The main function is granovagg.1w() + (a graphic for one way ANOVA); two other functions + (granovagg.ds() and granovagg.contr()) are to construct + graphics for dependent sample analyses and + contrast-based analyses respectively. (The function + granova.2w(), which entails dynamic displays of data, is + not currently part of 'granovaGG'.) The 'granovaGG' + functions are to display data for any number of groups, + regardless of their sizes (however, very large data + sets or numbers of groups can be problematic). For + granovagg.1w() a specialized approach is used to + construct data-based contrast vectors for which anova + data are displayed. The result is that the graphics use + a straight line to facilitate clear interpretations + while being faithful to the standard effect test in + anova. The graphic results are complementary to + standard summary tables; indeed, numerical summary + statistics are provided as side effects of the graphic + constructions. granovagg.ds() and granovagg.contr() provide + graphic displays and numerical outputs for a dependent + sample and contrast-based analyses. The graphics based + on these functions can be especially helpful for + learning how the respective methods work to answer the + basic question(s) that drive the analyses. This means + they can be particularly helpful for students and + non-statistician analysts. But these methods can be of + assistance for work-a-day applications of many kinds, + as they can help to identify outliers, clusters or + patterns, as well as highlight the role of non-linear + transformations of data. In the case of granovagg.1w() + and granovagg.ds() several arguments are provided to + facilitate flexibility in the construction of graphics + that accommodate diverse features of data, according to + their corresponding display requirements. See the help + files for individual functions. + date_publication: '2023-11-23' + bug_reports: https://github.com/briandk/granovaGG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=granovaGG + url_git: https://github.com/briandk/granovaGG +grantham: + version: 0.1.2 + title: Calculate the Grantham Distance + maintainer: Ramiro Magno + description: |- + A minimal set of routines to calculate the Grantham distance + . The Grantham distance attempts to + provide a proxy for the evolutionary distance between two amino acids + based on three key chemical properties: composition, polarity and + molecular volume. In turn, evolutionary distance is used as a proxy for + the impact of missense mutations. The higher the distance, the more + deleterious the substitution is expected to be. + date_publication: '2024-07-30' + bug_reports: https://github.com/patterninstitute/grantham/issues + url: https://www.pattern.institute/grantham/ + url_cran: https://CRAN.R-project.org/package=grantham + url_git: https://github.com/patterninstitute/grantham +GRAPE: + version: 0.1.1 + title: Gene-Ranking Analysis of Pathway Expression + maintainer: Michael Klein + description: |- + Gene-Ranking Analysis of Pathway Expression (GRAPE) is a tool for + summarizing the consensus behavior of biological pathways in the form of a + template, and for quantifying the extent to which individual samples deviate + from the template. GRAPE templates are based only on the relative rankings + of the genes within the pathway and can be used for classification of tissue + types or disease subtypes. GRAPE can be used to represent gene-expression + samples as vectors of pathway scores, where each pathway score indicates the + departure from a given collection of reference samples. The resulting pathway- + space representation can be used as the feature set for various applications, + including survival analysis and drug-response prediction. + Users of GRAPE should use the following citation: + Klein MI, Stern DF, and Zhao H. GRAPE: A pathway template method to characterize + tissue-specific functionality from gene expression profiles. + BMC Bioinformatics, 18:317 (June 2017). + date_publication: '2019-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRAPE + url_git: '' +grapes: + version: 1.0.0 + title: Make Binary Operators + maintainer: William Michael Landau + description: Turn arbitrary functions into binary operators. + date_publication: '2017-04-01' + bug_reports: https://github.com/wlandau/grapes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grapes + url_git: https://github.com/wlandau/grapes +grapesAgri1: + version: 1.1.0 + title: Collection of Shiny Apps for Agricultural Research Data Analysis + maintainer: Pratheesh P. Gopinath + description: Allows user to have graphical user interface to perform analysis of + Agricultural experimental data. On using the functions in this package a Interactive + User Interface will pop up. Apps Works by simple upload of files in CSV format. + date_publication: '2021-08-14' + bug_reports: https://github.com/pratheesh3780/grapesAgri1/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grapesAgri1 + url_git: https://github.com/pratheesh3780/grapesAgri1https://CRAN.R-project.org/package=grapesAgri1https://www.kaugrapes.com/ +graph3d: + version: 0.2.0 + title: A Wrapper of the JavaScript Library 'vis-graph3d' + maintainer: Stéphane Laurent + description: Create interactive visualization charts to draw data in three dimensional + graphs. The graphs can be included in Shiny apps and R markdown documents, or + viewed from the R console and 'RStudio' Viewer. Based on the 'vis.js' Graph3d + module and the 'htmlwidgets' R package. + date_publication: '2020-11-12' + bug_reports: https://github.com/stla/graph3d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graph3d + url_git: https://github.com/stla/graph3d +graph4lg: + version: 1.8.0 + title: Build Graphs for Landscape Genetics Analysis + maintainer: Paul Savary + description: "Build graphs for landscape genetics analysis. This set of\nfunctions + can be used to import and convert spatial and genetic data\ninitially in different + formats, import landscape graphs created with\n'GRAPHAB' software (Foltete et + al., 2012) ,\nmake diagnosis plots of isolation + by distance relationships in order to\nchoose how to build genetic graphs, create + graphs with a large range of\npruning methods, weight their links with several + genetic distances, plot\nand analyse graphs,\tcompare them with other graphs. + It uses functions from\nother packages such as 'adegenet'\n(Jombart, 2008) + and 'igraph' (Csardi\net Nepusz, 2006) . It also implements + methods\ncommonly used in landscape genetics to create graphs, described by Dyer + et\nNason (2004) and Greenbaum et\nFefferman + (2017) , and to analyse distance data\n(van Strien et al., + 2015) ." + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graph4lg + url_git: '' +graphclust: + version: '1.3' + title: Hierarchical Graph Clustering for a Collection of Networks + maintainer: Tabea Rebafka + description: |- + Graph clustering using an agglomerative algorithm to maximize the + integrated classification likelihood criterion and a mixture of stochastic + block models. The method is described in the article "Model-based clustering + of multiple networks with a hierarchical algorithm" by + T. Rebafka (2022) . + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graphclust + url_git: '' +GrapheR: + version: 1.9-86-5 + title: A Multi-Platform GUI for Drawing Customizable Graphs in R + maintainer: Maxime HERVE + description: 'A multi-platform user interface for drawing highly customizable graphs + in R. It aims to be a valuable help to quickly draw publishable graphs without + any knowledge of R commands. Six kinds of graph are available: histogram, box-and-whisker + plot, bar plot, pie chart, curve and scatter plot.' + date_publication: '2023-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GrapheR + url_git: '' +grapherator: + version: 1.0.0 + title: A Modular Multi-Step Graph Generator + maintainer: Jakob Bossek + description: Set of functions for step-wise generation of (weighted) graphs. Aimed + for research in the field of single- and multi-objective combinatorial optimization. + Graphs are generated adding nodes, edges and weights. Each step may be repeated + multiple times with different predefined and custom generators resulting in high + flexibility regarding the graph topology and structure of edge weights. + date_publication: '2017-12-21' + bug_reports: https://github.com/jakobbossek/grapherator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grapherator + url_git: https://github.com/jakobbossek/grapherator +graphframes: + version: 0.1.2 + title: Interface for 'GraphFrames' + maintainer: Kevin Kuo + description: |- + A 'sparklyr' extension that provides an R + interface for 'GraphFrames' . 'GraphFrames' is a package + for 'Apache Spark' that provides a DataFrame-based API for working with graphs. Functionality + includes motif finding and common graph algorithms, such as PageRank and Breadth-first + search. + date_publication: '2018-10-30' + bug_reports: https://github.com/rstudio/graphframes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graphframes + url_git: https://github.com/rstudio/graphframes +graphhopper: + version: 0.1.2 + title: An R Interface to the 'GraphHopper' Directions API + maintainer: Stefan Kuethe + description: |- + Provides a quick and easy access to the 'GraphHopper' Directions API. + 'GraphHopper' itself is a routing engine based on 'OpenStreetMap' data. + API responses can be converted to simple feature (sf) objects in a convenient way. + date_publication: '2021-02-06' + bug_reports: https://github.com/crazycapivara/graphhopper-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graphhopper + url_git: https://github.com/crazycapivara/graphhopper-r +graphicalEvidence: + version: '1.1' + title: Graphical Evidence + maintainer: David Rowe + description: |- + Computes marginal likelihood in Gaussian graphical models through a + novel telescoping block decomposition of the precision matrix which allows + estimation of model evidence. The top level function used to estimate marginal + likelihood is called evidence(), which expects the prior name, data, and + relevant prior specific parameters. This package also provides an MCMC prior + sampler using the same underlying approach, implemented in prior_sampling(), + which expects a prior name and prior specific parameters. Both functions also + expect the number of burn-in iterations and the number of sampling iterations + for the underlying MCMC sampler. + date_publication: '2024-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graphicalEvidence + url_git: '' +graphicalExtremes: + version: 0.3.3 + title: Statistical Methodology for Graphical Extreme Value Models + maintainer: Sebastian Engelke + description: |- + Statistical methodology for sparse multivariate extreme value models. Methods are + provided for exact simulation and statistical inference for multivariate Pareto distributions + on graphical structures as described in the paper 'Graphical Models for Extremes' by + Engelke and Hitz (2020) . + date_publication: '2024-11-14' + bug_reports: https://github.com/sebastian-engelke/graphicalExtremes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graphicalExtremes + url_git: https://github.com/sebastian-engelke/graphicalExtremes +graphicalMCP: + version: 0.2.6 + title: Graphical Multiple Comparison Procedures + maintainer: Dong Xi + description: |- + Multiple comparison procedures (MCPs) control the familywise error + rate in clinical trials. Graphical MCPs include many commonly used + procedures as special cases; see Bretz et al. (2011) + , Lu (2016) , and Xi et + al. (2017) . This package is a low-dependency + implementation of graphical MCPs which allow mixed types of tests. It also + includes power simulations and visualization of graphical MCPs. + date_publication: '2024-11-08' + bug_reports: https://github.com/openpharma/graphicalMCP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graphicalMCP + url_git: https://github.com/openpharma/graphicalMCP +graphicalVAR: + version: 0.3.4 + title: Graphical VAR for Experience Sampling Data + maintainer: Sacha Epskamp + description: Estimates within and between time point interactions in experience + sampling data, using the Graphical vector autoregression model in combination + with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) . + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graphicalVAR + url_git: '' +graphkernels: + version: 1.6.1 + title: Graph Kernels + maintainer: Mahito Sugiyama + description: A fast C++ implementation for computing various graph kernels including + (1) simple kernels between vertex and/or edge label histograms, (2) graphlet kernels, + (3) random walk kernels (popular baselines), and (4) the Weisfeiler-Lehman graph + kernel (state-of-the-art). + date_publication: '2021-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graphkernels + url_git: '' +graphlayouts: + version: 1.2.2 + title: Additional Layout Algorithms for Network Visualizations + maintainer: David Schoch + description: |- + Several new layout algorithms to visualize networks are provided which are not part of 'igraph'. + Most are based on the concept of stress majorization by Gansner et al. (2004) . + Some more specific algorithms allow the user to emphasize hidden group structures in networks or focus on specific nodes. + date_publication: '2025-01-23' + bug_reports: https://github.com/schochastics/graphlayouts/issues + url: https://schochastics.github.io/graphlayouts/ + url_cran: https://CRAN.R-project.org/package=graphlayouts + url_git: https://github.com/schochastics/graphlayouts +graphon: + version: 0.3.5 + title: A Collection of Graphon Estimation Methods + maintainer: Kisung You + description: |- + Provides a not-so-comprehensive list of methods for estimating graphon, + a symmetric measurable function, from a single or multiple of observed networks. + For a detailed introduction on graphon and popular estimation techniques, + see the paper by Orbanz, P. and Roy, D.M.(2014) . + It also contains several auxiliary functions for generating sample networks + using various network models and graphons. + date_publication: '2021-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graphon + url_git: '' +graphPAF: + version: 2.0.0 + title: Estimating and Displaying Population Attributable Fractions + maintainer: John Ferguson + description: Estimation and display of various types of population attributable + fraction and impact fractions. As well as the usual calculations of attributable + fractions and impact fractions, functions are provided for attributable fraction + nomograms and fan plots, continuous exposures, for pathway specific population + attributable fractions, and for joint, average and sequential population attributable + fractions. + date_publication: '2023-12-21' + bug_reports: https://github.com/johnfergusonNUIG/graphPAF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graphPAF + url_git: https://github.com/johnfergusonNUIG/graphPAF +graphql: + version: 1.5.2 + title: A GraphQL Query Parser + maintainer: Jeroen Ooms + description: |- + Bindings to the 'libgraphqlparser' C++ library. Parses GraphQL + syntax and exports the AST in JSON format. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/graphql/issues + url: https://docs.ropensci.org/graphql/https://ropensci.r-universe.dev/graphql + url_cran: https://CRAN.R-project.org/package=graphql + url_git: '' +graphsim: + version: 1.0.3 + title: Simulate Expression Data from 'igraph' Networks + maintainer: S. Thomas Kelly + description: Functions to develop simulated continuous data (e.g., gene expression) + from a sigma covariance matrix derived from a graph structure in 'igraph' objects. + Intended to extend 'mvtnorm' to take 'igraph' structures rather than sigma matrices + as input. This allows the use of simulated data that correctly accounts for pathway + relationships and correlations. This allows the use of simulated data that correctly + accounts for pathway relationships and correlations. Here we present a versatile + statistical framework to simulate correlated gene expression data from biological + pathways, by sampling from a multivariate normal distribution derived from a graph + structure. This package allows the simulation of biological pathways from a graph + structure based on a statistical model of gene expression. For example methods + to infer biological pathways and gene regulatory networks from gene expression + data can be tested on simulated datasets using this framework. This also allows + for pathway structures to be considered as a confounding variable when simulating + gene expression data to test the performance of genomic analyses. + date_publication: '2022-09-12' + bug_reports: https://github.com/TomKellyGenetics/graphsim/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=graphsim + url_git: https://github.com/TomKellyGenetics/graphsim/ +graphTweets: + version: 0.5.3 + title: Visualise Twitter Interactions + maintainer: John Coene + description: |- + Allows building an edge table from data frame of tweets, + also provides function to build nodes and another create a temporal graph. + date_publication: '2020-01-08' + bug_reports: https://github.com/JohnCoene/graphTweets/issues + url: http://graphTweets.john-coene.com + url_cran: https://CRAN.R-project.org/package=graphTweets + url_git: '' +graposas: + version: 1.0.0 + title: Graphical Approach Optimal Sample Size + maintainer: Jiangtao Gou + description: |- + Graphical approach provides a useful framework for multiplicity adjustment in clinical trials with multiple endpoints. This package includes statistical methods to optimize sample size over initial weight and transition probability in a graphical approach under a common setting, which is to use marginal power for each endpoint in a trial design. + See Zhang, F. and Gou, J. (2023). Sample size optimization for clinical trials using graphical approaches for multiplicity adjustment, Technical Report. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=graposas + url_git: '' +grateful: + version: 0.2.10 + title: Facilitate Citation of R Packages + maintainer: Francisco Rodriguez-Sanchez + description: |- + Facilitates the citation of R packages used in analysis + projects. Scans project for packages used, gets their citations, and + produces a document with citations in the preferred bibliography + format, ready to be pasted into reports or manuscripts. Alternatively, + 'grateful' can be used directly within an 'R Markdown' or 'Quarto' document. + date_publication: '2024-09-04' + bug_reports: https://github.com/Pakillo/grateful/issues + url: https://pakillo.github.io/grateful/ + url_cran: https://CRAN.R-project.org/package=grateful + url_git: '' +grates: + version: 1.4.1 + title: Grouped Date Classes + maintainer: Tim Taylor + description: |- + Provides a coherent interface and implementation for creating + grouped date classes. This package is part of the RECON + () toolkit for outbreak analysis. + date_publication: '2025-02-05' + bug_reports: '' + url: https://www.reconverse.org/grates/ + url_cran: https://CRAN.R-project.org/package=grates + url_git: https://github.com/reconverse/grates +gratia: + version: 0.10.0 + title: |- + Graceful 'ggplot'-Based Graphics and Other Functions for GAMs + Fitted Using 'mgcv' + maintainer: Gavin L. Simpson + description: Graceful 'ggplot'-based graphics and utility functions for working + with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides + a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well + as 'tidyverse' compatible representations of estimated smooths. + date_publication: '2024-12-19' + bug_reports: https://github.com/gavinsimpson/gratia/issues + url: https://gavinsimpson.github.io/gratia/ + url_cran: https://CRAN.R-project.org/package=gratia + url_git: '' +graticule: + version: 0.4.0 + title: Meridional and Parallel Lines for Maps + maintainer: Michael D. Sumner + description: |- + Create graticule lines and labels for maps. Control the creation + of lines or tiles by setting their placement (at particular meridians and parallels) + and extent (along parallels and meridians). Labels are created independently of + lines. + date_publication: '2023-09-25' + bug_reports: https://github.com/hypertidy/graticule/issues + url: '' + url_cran: https://CRAN.R-project.org/package=graticule + url_git: https://github.com/hypertidy/graticule +gratis: + version: 1.0.7 + title: |- + Generating Time Series with Diverse and Controllable + Characteristics + maintainer: Feng Li + description: |- + Generates synthetic time series based on various univariate + time series models including MAR and ARIMA processes. Kang, Y., + Hyndman, R.J., Li, F.(2020) . + date_publication: '2024-04-10' + bug_reports: https://github.com/ykang/gratis/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=gratis + url_git: https://github.com/ykang/gratis +grattan: + version: 2024.1.1 + title: Australian Tax Policy Analysis + maintainer: Hugh Parsonage + description: |- + Utilities to cost and evaluate Australian tax policy, including fast + projections of personal income tax collections, high-performance tax and + transfer calculators, and an interface to common indices from the Australian + Bureau of Statistics. Written to support Grattan Institute's Australian + Perspectives program, and related projects. Access to the Australian Taxation + Office's sample files of personal income tax returns is assumed. + date_publication: '2024-03-27' + bug_reports: https://github.com/HughParsonage/grattan/issues + url: https://hughparsonage.github.io/grattan/ + url_cran: https://CRAN.R-project.org/package=grattan + url_git: https://github.com/HughParsonage/grattan +grattanInflators: + version: 0.5.4 + title: Inflators for Australian Policy Analysis + maintainer: Hugh Parsonage + description: |- + Using Australian Bureau of Statistics indices, provides functions + that convert historical, nominal statistics to real, contemporary values + without worrying about date input quality, performance, or the ABS catalogue. + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grattanInflators + url_git: '' +gRaven: + version: 1.1.10 + title: 'Bayes Nets: ''RHugin'' Emulation with ''gRain''' + maintainer: Peter Green + description: |- + Wrappers for functions in the 'gRain' package to emulate some 'RHugin' + functionality, allowing the building of Bayesian networks consisting on discrete + chance nodes incrementally, through adding nodes, edges and conditional probability + tables, the setting of evidence, both 'hard' (boolean) or 'soft' (likelihoods), + querying marginal probabilities and normalizing constants, and generating sets of + high-probability configurations. Computations will typically not be so fast as they are + with 'RHugin', but this package should assist users without access to 'Hugin' to use + code written to use 'RHugin'. + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gRaven + url_git: '' +gravitas: + version: 0.1.3 + title: |- + Explore Probability Distributions for Bivariate Temporal + Granularities + maintainer: Sayani Gupta + description: |- + Provides tools for systematically exploring large quantities of + temporal data across cyclic temporal granularities + (deconstructions of time) by visualizing probability distributions. + Cyclic time granularities can be circular, quasi-circular or + aperiodic. 'gravitas' computes cyclic + single-order-up or multiple-order-up granularities, check the + feasibility of creating plots for any two cyclic granularities + and recommend probability distributions plots for exploring + periodicity in the data. + date_publication: '2020-06-25' + bug_reports: https://github.com/Sayani07/gravitas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gravitas + url_git: https://github.com/Sayani07/gravitas/ +gravity: + version: '1.1' + title: Estimation Methods for Gravity Models + maintainer: Mauricio Vargas + description: |- + A wrapper of different standard estimation methods for gravity models. + This package provides estimation methods for log-log models and multiplicative models. + date_publication: '2023-05-02' + bug_reports: https://github.com/pachadotdev/gravity/issues/ + url: https://pacha.dev/gravity/ + url_cran: https://CRAN.R-project.org/package=gravity + url_git: '' +gravmagsubs: + version: 1.0.1 + title: |- + Gravitational and Magnetic Attraction of 3-D Vertical + Rectangular Prisms + maintainer: C. Cronkite-Ratcliff + description: |- + Computes the gravitational and magnetic anomalies generated by + 3-D vertical rectangular prisms at specific observation points using the + method of Plouff (1976) . + date_publication: '2023-01-25' + bug_reports: '' + url: https://code.usgs.gov/gmegsc/gravmagsubs + url_cran: https://CRAN.R-project.org/package=gravmagsubs + url_git: '' +gRbase: + version: 2.0.3 + title: A Package for Graphical Modelling in R + maintainer: Søren Højsgaard + description: |- + The 'gRbase' package provides graphical modelling features + used by e.g. the packages 'gRain', 'gRim' and 'gRc'. 'gRbase' implements + graph algorithms including (i) maximum cardinality search (for marked + and unmarked graphs). + (ii) moralization, (iii) triangulation, (iv) creation of junction tree. + 'gRbase' facilitates array operations, + 'gRbase' implements functions for testing for conditional independence. + 'gRbase' illustrates how hierarchical log-linear models may be + implemented and describes concept of graphical meta + data. + The facilities of the package are documented in the book by Højsgaard, + Edwards and Lauritzen (2012, + ) and in the paper by + Dethlefsen and Højsgaard, (2005, ). + Please see 'citation("gRbase")' for citation details. + date_publication: '2024-10-22' + bug_reports: '' + url: https://people.math.aau.dk/~sorenh/software/gR/ + url_cran: https://CRAN.R-project.org/package=gRbase + url_git: '' +gRc: + version: 0.5.1 + title: |- + Inference in Graphical Gaussian Models with Edge and Vertex + Symmetries + maintainer: Søren Højsgaard + description: |- + Estimation, model selection and other aspects of + statistical inference in Graphical Gaussian models with edge and + vertex symmetries (Graphical Gaussian models with colours). + Documentation about 'gRc' is provided in the paper by Hojsgaard and + Lauritzen (2007, ) and the paper by + Hojsgaard and Lauritzen (2008, ). + date_publication: '2024-10-15' + bug_reports: '' + url: https://people.math.aau.dk/~sorenh/software/gR/ + url_cran: https://CRAN.R-project.org/package=gRc + url_git: '' +GRCdata: + version: '1.0' + title: |- + Parameter Inference and Optimal Designs for Grouped and/or + Right-Censored Count Data + maintainer: Xin Guo + description: |- + We implement two main functions. + The first function uses a given grouped and/or + right-censored grouping scheme and empirical data to infer parameters, + and implements chi-square goodness-of-fit tests. + The second function searches for the global optimal grouping + scheme of grouped and/or right-censored count responses in surveys. + date_publication: '2017-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRCdata + url_git: '' +GRCdesigns: + version: 1.0.0 + title: Generalized Row-Column Designs + maintainer: Ashutosh Dalal + description: When the number of treatments is large with limited experimental resources + then Row-Column(RC) designs with multiple units per cell can be used. These designs + are called Generalized Row-Column (GRC) designs and are defined as designs with + v treatments in p rows and q columns such that the intersection of each row and + column (cell) consists of k experimental units. For example (Bailey & Monod (2001)), + to conduct an experiment for comparing 4 treatments using 4 plants with leaves + at 2 different heights row-column design with two units per cell can be used. + A GRC design is said to be structurally complete if corresponding to the intersection + of each row and column, there appears at least two treatments. A GRC design is + said to be structurally incomplete if corresponding to the intersection of any + row and column, there is at least one cell which does not contain any treatment. + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRCdesigns + url_git: '' +GRCRegression: + version: '1.0' + title: Modified Poisson Regression of Grouped and Right-Censored Counts + maintainer: Xin Guo + description: |- + Implement maximum likelihood estimation for Poisson generalized + linear models with grouped and right-censored count data. Intended to be used + for analyzing grouped and right-censored data, which is widely applied in + many branches of social sciences. The algorithm implemented is described + in Fu et al., (2021) . + date_publication: '2023-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRCRegression + url_git: '' +greatR: + version: 2.0.0 + title: Gene Registration from Expression and Time-Courses in R + maintainer: Ruth Kristianingsih + description: |- + A tool for registering (aligning) gene expression profiles + between reference and query data. + date_publication: '2024-04-09' + bug_reports: https://github.com/ruthkr/greatR/issues/ + url: https://ruthkr.github.io/greatR/ + url_cran: https://CRAN.R-project.org/package=greatR + url_git: https://github.com/ruthkr/greatR/ +grec: + version: 1.6.1 + title: |- + Gradient-Based Recognition of Spatial Patterns in Environmental + Data + maintainer: Wencheng Lau-Medrano + description: Provides algorithms for detection of spatial patterns from oceanographic + data using image processing methods based on Gradient Recognition. + date_publication: '2025-01-23' + bug_reports: https://github.com/LuisLauM/grec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grec + url_git: https://github.com/LuisLauM/grec +greed: + version: 0.6.1 + title: |- + Clustering and Model Selection with the Integrated + Classification Likelihood + maintainer: Etienne Côme + description: 'An ensemble of algorithms that enable the clustering of networks and + data matrices (such as counts, categorical or continuous) with different type + of generative models. Model selection and clustering is performed in combination + by optimizing the Integrated Classification Likelihood (which is equivalent to + minimizing the description length). Several models are available such as: Stochastic + Block Model, degree corrected Stochastic Block Model, Mixtures of Multinomial, + Latent Block Model. The optimization is performed thanks to a combination of greedy + local search and a genetic algorithm (see for more details).' + date_publication: '2022-10-03' + bug_reports: https://github.com/comeetie/greed/issues + url: https://comeetie.github.io/greed/ + url_cran: https://CRAN.R-project.org/package=greed + url_git: https://github.com/comeetie/greed +GreedyEPL: + version: '1.2' + title: Greedy Expected Posterior Loss + maintainer: Riccardo Rastelli + description: Summarises a collection of partitions into a single optimal partition. + The objective function is the expected posterior loss, and the minimisation is + performed through a greedy algorithm described in Rastelli, R. and Friel, N. (2017) + "Optimal Bayesian estimators for latent variable cluster models" . + date_publication: '2021-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GreedyEPL + url_git: '' +GreedyExperimentalDesign: + version: 1.5.6.1 + title: Greedy Experimental Design Construction + maintainer: Adam Kapelner + description: |- + Computes experimental designs for a + two-arm experiment with covariates via a number of methods: + (0) complete randomization and randomization with forced-balance, + (1) Greedily optimizing a + balance objective function via pairwise switching. This optimization + provides lower variance for the treatment effect estimator (and higher + power) while preserving a design that is close to complete randomization. + We return all iterations of the designs for use in a permutation test, + (2) The second is via numerical optimization + (via 'gurobi' which must be installed, see ) + a la Bertsimas and Kallus, + (3) rerandomization, + (4) Karp's method for one covariate, + (5) exhaustive enumeration to find the + optimal solution (only for small sample sizes), + (6) Binary pair matching using the 'nbpMatching' library, + (7) Binary pair matching plus design number (1) to further optimize balance, + (8) Binary pair matching plus design number (3) to further optimize balance, + (9) Hadamard designs, + (10) Simultaneous Multiple Kernels. + In (1-9) we allow for three objective functions: + Mahalanobis distance, + Sum of absolute differences standardized and + Kernel distances via the 'kernlab' library. This package is the result of a stream of research that can be found in + Krieger, A, Azriel, D and Kapelner, A "Nearly Random Designs with Greatly Improved Balance" (2016) , + Krieger, A, Azriel, D and Kapelner, A "Better Experimental Design by Hybridizing Binary Matching with Imbalance + Optimization" (2021) . + date_publication: '2023-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GreedyExperimentalDesign + url_git: https://github.com/kapelner/GreedyExperimentalDesign +GreedyExperimentalDesignJARs: + version: '1.0' + title: GreedyExperimentalDesign JARs + maintainer: Adam Kapelner + description: 'These are GreedyExperimentalDesign Java dependency libraries. Note: + this package has no functionality of its own and should not be installed as a + standalone package without GreedyExperimentalDesign.' + date_publication: '2018-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GreedyExperimentalDesignJARs + url_git: '' +greekLetters: + version: 1.0.4 + title: |- + Routines for Writing Greek Letters and Mathematical Symbols on + the 'RStudio' and 'RGui' + maintainer: Kevin Allan Sales Rodrigues + description: 'An implementation of functions to display Greek letters on the ''RStudio'' + (include subscript and superscript indexes) and ''RGui'' (without subscripts and + only with superscript 1, 2 or 3; because ''RGui'' doesn''t support printing the + corresponding Unicode characters as a string: all subscripts ranging from 0 to + 9 and superscripts equal to 0, 4, 5, 6, 7, 8 or 9). The functions in this package + do not work properly on the R console. Characters are used via Unicode and encoded + as UTF-8 to ensure that they can be viewed on all operating systems. Other characters + related to mathematics are included, such as the infinity symbol. All this accessible + from very simple commands. This is a package that can be used for teaching purposes, + the statistical notation for hypothesis testing can be written from this package + and so it is possible to build a course from the ''swirlify'' package. Another + utility of this package is to create new summary functions that contain the functional + form of the model adjusted with the Greek letters, thus making the transition + from statistical theory to practice easier. In addition, it is a natural extension + of the ''clisymbols'' package.' + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=greekLetters + url_git: '' +greeks: + version: 1.4.3 + title: |- + Sensitivities of Prices of Financial Options and Implied + Volatilities + maintainer: Anselm Hudde + description: |- + Methods to calculate sensitivities of financial option prices for + European, geometric and arithmetic Asian, and American options, with various + payoff functions in the Black Scholes model, and in more general jump diffusion + models. A shiny app to interactively plot the results is included. Furthermore, + methods to compute implied volatilities are provided for a wide range of option + types and custom payoff functions. Classical formulas are implemented for + European options in the Black Scholes Model, as is presented in Hull, J. C. + (2017), Options, Futures, and Other Derivatives. + In the case of Asian options, Malliavin Monte Carlo Greeks are implemented, see + Hudde, A. & Rüschendorf, L. (2023). European and Asian Greeks for exponential + Lévy processes. . For American + options, the Binomial Tree Method is implemented, as is presented in Hull, + J. C. (2017). + date_publication: '2024-09-17' + bug_reports: https://github.com/ahudde/greeks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=greeks + url_git: https://github.com/ahudde/greeks +greenclust: + version: 1.1.1 + title: Combine Categories Using Greenacre's Method + maintainer: Jeff Jetton + description: |- + Implements a method of iteratively collapsing the rows of a + contingency table, two at a time, by selecting the pair of categories whose + combination yields a new table with the smallest loss of chi-squared, as + described by Greenacre, M.J. (1988) . The result is + compatible with the class of object returned by the 'stats' package's + hclust() function and can be used similarly (plotted as a dendrogram, + cut, etc.). Additional functions are provided for automatic cutting and + diagnostic plotting. + date_publication: '2023-09-20' + bug_reports: https://github.com/JeffJetton/greenclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=greenclust + url_git: https://github.com/JeffJetton/greenclust +greencrab.toolkit: + version: '0.2' + title: Run 'Stan' Models to Interpret Green Crab Monitoring Assessments + maintainer: Abigail G. Keller + description: These Bayesian models written in the 'Stan' probabilistic language + can be used to interpret green crab trapping and environmental DNA monitoring + data, either independently or jointly. Detailed model information is found in + Keller (2022) . + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=greencrab.toolkit + url_git: '' +GREENeR: + version: 1.0.0 + title: |- + Geospatial Regression Equation for European Nutrient Losses + (GREEN) + maintainer: C. Alfaro + description: |- + Tools and methods to apply the model Geospatial Regression Equation + for European Nutrient losses (GREEN); + Grizzetti et al. (2005) ; + Grizzetti et al. (2008); + Grizzetti et al. (2012) ; + Grizzetti et al. (2021) . + date_publication: '2024-02-01' + bug_reports: https://github.com/calfarog/GREENeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GREENeR + url_git: https://github.com/calfarog/GREENeR +greenfeedr: + version: 1.1.0 + title: Process and Report 'GreenFeed' Data + maintainer: Guillermo Martinez-Boggio + description: Provides tools for downloading, processing, and reporting daily and + finalized 'GreenFeed' data. + date_publication: '2025-01-29' + bug_reports: https://github.com/GMBog/greenfeedr/issues + url: https://gmbog.github.io/greenfeedr/ + url_cran: https://CRAN.R-project.org/package=greenfeedr + url_git: https://github.com/GMBog/greenfeedr +Greg: + version: 2.0.2 + title: Regression Helper Functions + maintainer: Max Gordon + description: |- + Methods for manipulating regression models and for describing these in a style adapted for medical journals. + Contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model + estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots. + In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the 'sandwich' + package, a function for adding non-linearities to a model, and a wrapper around the 'Epi' package's Lexis() functions for + time-splitting a dataset when modeling non-proportional hazards in Cox regressions. + date_publication: '2024-01-29' + bug_reports: https://github.com/gforge/Greg/issues + url: http://gforge.se + url_cran: https://CRAN.R-project.org/package=Greg + url_git: '' +GregoryQuadrature: + version: 1.0.0 + title: Gregory Weights for Function Integration + maintainer: Dylan Hettinger + description: Computes Gregory weights for a given number nodes and function order. + Anthony Ralston and Philip Rabinowitz (2001) . + date_publication: '2024-04-23' + bug_reports: https://github.com/dhetting/GregoryQuadrature/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GregoryQuadrature + url_git: https://github.com/dhetting/GregoryQuadrature +gregRy: + version: 0.1.0 + title: GREGORY Estimation + maintainer: Olek Wojcik + description: |- + Functions which make using the Generalized Regression Estimator(GREG) + J.N.K. Rao, Isabel Molina, (2015) + and the Generalized Regression Estimator Operating on Resolutions of Y (GREGORY) easier. + The functions are designed to work well within a forestry context, and estimate multiple + estimation units at once. Compared to other survey estimation packages, this function has greater flexibility when + describing the linear model. + date_publication: '2021-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gregRy + url_git: '' +GRelevance: + version: '1.0' + title: |- + Graph-Based k-Sample Comparisons and Relevance Analysis in High + Dimensions + maintainer: Xiaoping Shi + description: 'We propose two distribution-free test statistics based on between-sample + edge counts and measure the degree of relevance by standardized counts. Users + can set edge costs in the graph to compare the parameters of the distributions. + Methods for comparing distributions are as described in: Xiaoping Shi (2021) .' + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRelevance + url_git: '' +gremlin: + version: 1.1.0 + title: Mixed-Effects REML Incorporating Generalized Inverses + maintainer: Matthew Wolak + description: |- + Fit linear mixed-effects models using restricted (or residual) + maximum likelihood (REML) and with generalized inverse matrices to specify + covariance structures for random effects. In particular, the package is + suited to fit quantitative genetic mixed models, often referred to as + 'animal models'. Implements the average information algorithm as the main + tool to maximize the restricted log-likelihood, but with other algorithms + available. + date_publication: '2024-11-04' + bug_reports: https://github.com/matthewwolak/gremlin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gremlin + url_git: https://github.com/matthewwolak/gremlin +GREMLINS: + version: 0.2.1 + title: Generalized Multipartite Networks + maintainer: Sophie Donnet + description: We define generalized multipartite networks as the joint observation + of several networks implying some common pre-specified groups of individuals. + The aim is to fit an adapted version of the popular stochastic block model to + multipartite networks, as described in Bar-hen, Barbillon and Donnet (2020) . + date_publication: '2023-03-10' + bug_reports: https://github.com/GrossSBM/GREMLINS/issues + url: https://GrossSBM.github.io/GREMLINS/ + url_cran: https://CRAN.R-project.org/package=GREMLINS + url_git: '' +greport: + version: 0.7-4 + title: Graphical Reporting for Clinical Trials + maintainer: Frank E Harrell Jr + description: |- + Contains many functions useful for + monitoring and reporting the results of clinical trials and other + experiments in which treatments are compared. LaTeX is + used to typeset the resulting reports, recommended to be in the + context of 'knitr'. The 'Hmisc', 'ggplot2', and 'lattice' packages are used + by 'greport' for high-level graphics. + date_publication: '2023-09-02' + bug_reports: '' + url: http://hbiostat.org/R/greport/ + url_cran: https://CRAN.R-project.org/package=greport + url_git: https://github.com/harrelfe/greport/ +greta: + version: 0.5.0 + title: Simple and Scalable Statistical Modelling in R + maintainer: Nicholas Tierney + description: |- + Write statistical models in R and fit them by MCMC and + optimisation on CPUs and GPUs, using Google 'TensorFlow'. greta lets + you write your own model like in BUGS, JAGS and Stan, except that you + write models right in R, it scales well to massive datasets, and it’s + easy to extend and build on. See the website for more information, + including tutorials, examples, package documentation, and the greta + forum. + date_publication: '2024-11-12' + bug_reports: https://github.com/greta-dev/greta/issues + url: https://greta-stats.org + url_cran: https://CRAN.R-project.org/package=greta + url_git: https://github.com/greta-dev/greta +greta.censored: + version: 0.1.0 + title: Censored Distributions for 'greta' + maintainer: Mlen-Too Wesley + description: |- + Provides additional censored distributions for use with 'greta', + a probabilistic programming framework for Bayesian modeling. Includes + censored versions of Normal, Log-Normal, Student's T, Gamma, Exponential, + Weibull, Pareto, and Beta distributions with support for right, left, + and interval censoring. For details on 'greta', see Golding (2019) + . The methods are implemented using 'TensorFlow' + and 'TensorFlow Probability' for efficient computation. + date_publication: '2024-11-29' + bug_reports: https://github.com/mtwesley/greta.censored/issues + url: '' + url_cran: https://CRAN.R-project.org/package=greta.censored + url_git: https://github.com/mtwesley/greta.censored +greta.dynamics: + version: 0.2.2 + title: Modelling Structured Dynamical Systems in 'greta' + maintainer: Nicholas Tierney + description: |- + A 'greta' extension for analysing transition matrices and + ordinary differential equations representing dynamical systems. Provides + functions for analysing transition matrices by iteration, and solving + ordinary differential equations. This is an extension to the 'greta' + software, Golding (2019) . + date_publication: '2024-11-14' + bug_reports: https://github.com/greta-dev/greta.dynamics/issues + url: https://greta-dev.github.io/greta.dynamics/ + url_cran: https://CRAN.R-project.org/package=greta.dynamics + url_git: https://github.com/greta-dev/greta.dynamics +greta.gam: + version: 0.2.0 + title: Generalised Additive Models in 'greta' using 'mgcv' + maintainer: Nicholas Tierney + description: A 'greta' (Golding (2019) ) module that lets + you use 'mgcv' smoother functions and formula syntax to define smooth terms for + use in a 'greta' model. You can then define your own likelihood to complete the + model, and fit it by Markov Chain Monte Carlo (MCMC). + date_publication: '2024-12-17' + bug_reports: https://github.com/greta-dev/greta.gam/issues + url: https://greta-dev.github.io/greta.gam/ + url_cran: https://CRAN.R-project.org/package=greta.gam + url_git: https://github.com/greta-dev/greta.gam +greta.gp: + version: 0.2.2 + title: Gaussian Process Modelling in 'greta' + maintainer: Nicholas Tierney + description: |- + Provides a syntax to create and combine Gaussian process kernels + in 'greta'. You can then them to define either full rank or sparse Gaussian + processes. This is an extension to the 'greta' software, Golding (2019) + . + date_publication: '2024-11-13' + bug_reports: https://github.com/greta-dev/greta.gp/issues + url: https://greta-dev.github.io/greta.gp/ + url_cran: https://CRAN.R-project.org/package=greta.gp + url_git: https://github.com/greta-dev/greta.gp +gretel: + version: 0.0.1 + title: Generalized Path Analysis for Social Networks + maintainer: David Buch + description: |- + The social network literature features numerous methods for assigning + value to paths as a function of their ties. 'gretel' systemizes these approaches, + casting them as instances of a generalized path value function indexed by + a penalty parameter. The package also calculates probabilistic path value and + identifies optimal paths in either value framework. Finally, proximity + matrices can be generated in these frameworks that capture high-order connections + overlooked in primitive adjacency sociomatrices. Novel methods are described + in Buch (2019) . + More traditional methods are also implemented, as described in Yang, Knoke (2001) + . + date_publication: '2019-08-22' + bug_reports: https://github.com/davidbuch/gretel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gretel + url_git: https://github.com/davidbuch/gretel +gretlR: + version: 0.1.4 + title: A Seamless Integration of 'Gretl' and 'R' + maintainer: Sagiru Mati + description: It allows running 'gretl' () + program from R, R Markdown and Quarto. 'gretl' ('Gnu' Regression, 'Econometrics', + and Time-series Library) is a statistical software for Econometric analysis. This + package does not only integrate 'gretl' and 'R' but also serves as a 'gretl' + Knit-Engine for 'knitr' package. Write all your 'gretl' commands in 'R', R Markdown + chunk. + date_publication: '2022-05-01' + bug_reports: https://github.com/sagirumati/gretlR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gretlR + url_git: '' +grex: + version: '1.9' + title: Gene ID Mapping for Genotype-Tissue Expression (GTEx) Data + maintainer: Nan Xiao + description: |- + Convert 'Ensembl' gene identifiers from Genotype-Tissue + Expression (GTEx) data to identifiers in other annotation systems, + including 'Entrez', 'HGNC', and 'UniProt'. + date_publication: '2019-05-17' + bug_reports: https://github.com/nanxstats/grex/issues + url: https://nanx.me/grex/ + url_cran: https://CRAN.R-project.org/package=grex + url_git: https://github.com/nanxstats/grex +greybox: + version: 2.0.3 + title: Toolbox for Model Building and Forecasting + maintainer: Ivan Svetunkov + description: |- + Implements functions and instruments for regression model building and its + application to forecasting. The main scope of the package is in variables selection + and models specification for cases of time series data. This includes promotional + modelling, selection between different dynamic regressions with non-standard + distributions of errors, selection based on cross validation, solutions to the fat + regression model problem and more. Models developed in the package are tailored + specifically for forecasting purposes. So as a results there are several methods + that allow producing forecasts from these models and visualising them. + date_publication: '2024-12-09' + bug_reports: https://github.com/config-i1/greybox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=greybox + url_git: https://github.com/config-i1/greybox +GreyModel: + version: 0.1.0 + title: Fitting and Forecasting of Grey Model + maintainer: Mrinmoy Ray + description: Testing, Implementation and Forecasting of Grey Model (GM(1, 1)). For + method details see Hsu, L. and Wang, C. (2007). . + date_publication: '2021-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GreyModel + url_git: '' +Greymodels: + version: 2.0.1 + title: Shiny App for Grey Forecasting Model + maintainer: Jahajeeah Havisha + description: The 'Greymodels' Shiny app is an interactive interface for statistical + modelling and forecasting using grey-based models. It covers several state-of-the-art + univariate and multivariate grey models. A user friendly interface allows users + to easily compare the performance of different models for prediction and among + others, visualize graphical plots of predicted values within user chosen confidence + intervals. Chang, C. (2019) , Li, K., Zhang, + T. (2019) , Ou, S. (2012) , + Li, S., Zhou, M., Meng, W., Zhou, W. (2019) , + Xie, N., Liu, S. (2009) , Shao, Y., Su, H. (2012) + , Xie, N., Liu, S., Yang, Y., Yuan, C. (2013) + , Li, S., Miao, Y., Li, G., Ikram, M. (2020) , + Che, X., Luo, Y., He, Z. (2013) , + Zhu, J., Xu, Y., Leng, H., Tang, H., Gong, H., Zhang, Z. (2016) , + Luo, Y., Liao, D. (2012) , Bilgil, + H. (2020) , Li, D., Chang, C., Chen, W., Chen, C. (2011) + , Chen, C. (2008) , + Zhou, W., Pei, L. (2020) , Xiao, X., Duan, H. + (2020) , Xu, N., Dang, Y. (2015) , + Chen, P., Yu, H.(2014) , Zeng, B., Li, S., Meng, W., + Zhang, D. (2019) , Liu, L., Wu, L. (2021) , + Hu, Y. (2020) , Zhou, P., Ang, B., Poh, K. (2006) + , Cheng, M., Li, J., Liu, Y., Liu, B. (2020) + , Wang, H., Wang, P., Senel, M., Li, T. (2019) , + Ding, S., Li, R. (2020) , Zeng, B., Li, C. (2018) , + Xie, N., Liu, S. (2015) , Zeng, X., Yan, S., He, + F., Shi, Y. (2019) . + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Greymodels + url_git: https://github.com/havishaJ/Greymodels +GreyZones: + version: 0.0.5 + title: Detection of Grey Zones in Two-Way Inter-Rater Agreement Tables + maintainer: Haydar Demirhan + description: Grey zones locally occur in an agreement table due to the subjective + evaluation of raters based on various factors such as not having uniform guidelines, + the differences between the raters' level of expertise or low variability among + the level of the categorical variable. It is important to detect grey zones since + they cause a negative bias in the estimate of the agreement level. This package + provides a function for detecting the existence of grey zones in two-way inter-rater + agreement tables (Demirhan and Yilmaz (2023) ). + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GreyZones + url_git: '' +grf: + version: 2.4.0 + title: Generalized Random Forests + maintainer: Erik Sverdrup + description: |- + Forest-based statistical estimation and inference. + GRF provides non-parametric methods for heterogeneous treatment effects estimation + (optionally using right-censored outcomes, multiple treatment arms or outcomes, or instrumental variables), + as well as least-squares regression, quantile regression, and survival regression, + all with support for missing covariates. + date_publication: '2024-11-15' + bug_reports: https://github.com/grf-labs/grf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grf + url_git: https://github.com/grf-labs/grf +GrFA: + version: 0.2.1 + title: Group Factor Analysis + maintainer: Jiaqi Hu + description: Several group factor analysis algorithms are implemented, including + Canonical Correlation-based Estimation by Choi et al. (2021) + , Generalised Canonical Correlation Estimation by Lin and Shin (2023) , + Circularly Projected Estimation by Chen (2022) , + and Aggregated projection method. + date_publication: '2024-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GrFA + url_git: '' +gridBase: + version: 0.4-7 + title: Integration of base and grid graphics + maintainer: Paul Murrell + description: Integration of base and grid graphics + date_publication: '2014-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridBase + url_git: '' +gridBezier: + version: 1.1-1 + title: Bezier Curves in 'grid' + maintainer: Paul Murrell + description: |- + Functions for rendering Bezier + curves (Pomax, 2018) + in 'grid'. + There is support for both quadratic and cubic Bezier curves. + There are also functions for calculating points on curves, + tangents to curves, and normals to curves. + date_publication: '2019-05-22' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2018/11/02/2018-11-variable-width-bezier-splines-in-r/ + url_cran: https://CRAN.R-project.org/package=gridBezier + url_git: https://github.com/pmur002/gridbezier +GRIDCOPULA: + version: 1.0.1 + title: Bivariate Copula Functions Based on Regular Grid + maintainer: Rogelio Salinas Gutiérrez + description: Estimates grid type bivariate copula functions, calculates some association + measures and provides several copula graphics. + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRIDCOPULA + url_git: '' +gridDebug: + version: 0.5-1 + title: Debugging 'grid' Graphics + maintainer: Paul Murrell + description: |- + Functions for drawing scene trees representing + scenes that have been drawn using grid graphics. + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridDebug + url_git: '' +gridExtra: + version: '2.3' + title: Miscellaneous Functions for "Grid" Graphics + maintainer: Baptiste Auguie + description: |- + Provides a number of user-level functions to work with "grid" + graphics, notably to arrange multiple grid-based plots on a page, and draw + tables. + date_publication: '2017-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridExtra + url_git: '' +gridGeometry: + version: 0.4-0 + title: Polygon Geometry in 'grid' + maintainer: Paul Murrell + description: |- + Functions for performing polygon geometry with 'grid' grobs. + This allows complex shapes to be defined by combining simpler + shapes. + date_publication: '2024-08-22' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2019/03/04/2019-01-a-geometry-engine-interface-for-grid/ + url_cran: https://CRAN.R-project.org/package=gridGeometry + url_git: https://github.com/pmur002/gridgeometry +gridGraphics: + version: 0.5-1 + title: Redraw Base Graphics Using 'grid' Graphics + maintainer: Paul Murrell + description: |- + Functions to convert a page of plots drawn with the + 'graphics' package into identical output drawn with the 'grid' package. + The result looks like the original 'graphics'-based plot, but consists + of 'grid' grobs and viewports that can then be manipulated with + 'grid' functions (e.g., edit grobs and revisit viewports). + date_publication: '2020-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridGraphics + url_git: https://github.com/pmur002/gridgraphics +gridGraphviz: + version: 0.3-1 + title: Drawing Graphs with 'grid' + maintainer: Paul Murrell + description: |- + Functions for drawing node-and-edge graphs that have been + laid out by 'graphviz'. This provides an alternative + rendering to that provided by the 'Rgraphviz' package, with + two main advantages: the rendering provided by 'gridGraphviz' + should be more similar to what 'graphviz' itself would draw; + and rendering with 'grid' allows for post-hoc customisations + using the named viewports and grobs that 'gridGraphviz' + produces. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridGraphviz + url_git: https://r-forge.r-project.org/projects/gridgraph/ +GridOnClusters: + version: 0.1.0.1 + title: Cluster-Preserving Multivariate Joint Grid Discretization + maintainer: Joe Song + description: |- + Discretize multivariate continuous data using a grid + that captures the joint distribution via preserving clusters in + the original data (Wang et al. 2020) . + Joint grid discretization is applicable as a data transformation step + to prepare data for model-free inference of association, function, or + causality. + date_publication: '2024-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GridOnClusters + url_git: '' +gridOT: + version: 1.0.1 + title: Approximate Optimal Transport Between Two-Dimensional Grids + maintainer: Michel Groppe + description: 'Can be used for optimal transport between two-dimensional grids with + respect to separable cost functions of l^p form. It utilizes the Frank-Wolfe algorithm + to approximate so-called pivot measures: one-dimensional transport plans that + fully describe the full transport, see G. Auricchio (2021) . + For these, it offers methods for visualization and to extract the corresponding + transport plans and costs. Additionally, related functions for one-dimensional + optimal transport are available.' + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridOT + url_git: '' +gridpattern: + version: 1.3.1 + title: '''grid'' Pattern Grobs' + maintainer: Trevor L. Davis + description: Provides 'grid' grobs that fill in a user-defined area with various + patterns. Includes enhanced versions of the geometric and image-based patterns + originally contained in the 'ggpattern' package as well as original 'pch', 'polygon_tiling', + 'regular_polygon', 'rose', 'text', 'wave', and 'weave' patterns plus support for + custom user-defined patterns. + date_publication: '2025-01-16' + bug_reports: https://github.com/trevorld/gridpattern/issues + url: https://trevorldavis.com/R/gridpattern/ + url_cran: https://CRAN.R-project.org/package=gridpattern + url_git: https://github.com/trevorld/gridpattern +gridsampler: + version: '0.6' + title: |- + A Simulation Tool to Determine the Required Sample Size for + Repertory Grid Studies + maintainer: Mark Heckmann + description: |- + Simulation tool to facilitate determination of + required sample size to achieve category saturation + for studies using multiple repertory grids in conjunction with + content analysis. + date_publication: '2016-11-23' + bug_reports: https://github.com/markheckmann/gridsampler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gridsampler + url_git: https://github.com/markheckmann/gridsampler +gridstackeR: + version: 0.1.0 + title: Wrapper for 'gridstack.js' + maintainer: Peter Gandenberger + description: An easy way to create responsive layouts with just a few lines of code. + You can create boxes that are draggable and resizable and load predefined Layouts. + The package serves as a wrapper to allow for easy integration of the 'gridstack.js' + functionalities . + date_publication: '2022-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridstackeR + url_git: '' +gridSVG: + version: 1.7-5 + title: Export 'grid' Graphics as SVG + maintainer: Paul Murrell + description: |- + Functions to export graphics drawn with package grid to SVG + format. Additional functions provide access to SVG features that + are not available in standard R graphics, such as hyperlinks, + animation, filters, masks, clipping paths, and gradient and pattern fills. + date_publication: '2023-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gridSVG + url_git: '' +gridtext: + version: 0.1.5 + title: Improved Text Rendering Support for 'Grid' Graphics + maintainer: Brenton M. Wiernik + description: |- + Provides support for rendering of formatted text using 'grid' graphics. Text can be + formatted via a minimal subset of 'Markdown', 'HTML', and inline 'CSS' directives, and it can be + rendered both with and without word wrap. + date_publication: '2022-09-16' + bug_reports: https://github.com/wilkelab/gridtext/issues + url: https://wilkelab.org/gridtext/ + url_cran: https://CRAN.R-project.org/package=gridtext + url_git: '' +gRim: + version: 0.3.4 + title: Graphical Interaction Models + maintainer: Søren Højsgaard + description: |- + Provides the following types of models: Models for contingency + tables (i.e. log-linear models) Graphical Gaussian models for multivariate + normal data (i.e. covariance selection models) Mixed interaction models. + Documentation about 'gRim' is provided by vignettes included in this + package and the book by Højsgaard, Edwards and Lauritzen (2012, + ); see 'citation("gRim")' for details. + date_publication: '2024-10-15' + bug_reports: '' + url: https://people.math.aau.dk/~sorenh/software/gR/ + url_cran: https://CRAN.R-project.org/package=gRim + url_git: '' +grImport: + version: 0.9-7 + title: Importing Vector Graphics + maintainer: Paul Murrell + description: |- + Functions for converting, importing, and drawing PostScript + pictures in R plots. + date_publication: '2023-03-09' + bug_reports: '' + url: https://doi.org/10.18637/jss.v030.i04 + url_cran: https://CRAN.R-project.org/package=grImport + url_git: https://r-forge.r-project.org/projects/grimport/ +grImport2: + version: 0.3-3 + title: Importing 'SVG' Graphics + maintainer: Paul Murrell + description: |- + Functions for importing external vector images and + drawing them as part of 'R' plots. This package is different from the + 'grImport' package because, where that package imports 'PostScript' + format images, this package imports 'SVG' format images. Furthermore, + this package imports a specific subset of 'SVG', so external images + must be preprocessed using a package like 'rsvg' to produce 'SVG' + that this package can import. 'SVG' features that are not supported + by 'R' graphics, e.g., gradient fills, can be imported and then + exported via the 'gridSVG' package. + date_publication: '2024-07-30' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2013/09/ + url_cran: https://CRAN.R-project.org/package=grImport2 + url_git: https://r-forge.r-project.org/projects/grimport/ +GrimR: + version: '0.5' + title: Calculate Optical Parameters from Spindle Stage Measurements + maintainer: Florian Dufey + description: |- + Calculates optical parameters of crystals like the optical + axes, the axis angle 2V, and the direction of the principal axes of + the indicatrix from extinction angles measured on a spindle stage + mounted on a polarisation microscope stage. Details of the method can be found in Dufey (2017) . + date_publication: '2018-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GrimR + url_git: '' +GRIN2: + version: '1.0' + title: Genomic Random Interval (GRIN) + maintainer: Abdelrahman Elsayed + description: Improved version of 'GRIN' software that streamlines its use in practice + to analyze genomic lesion data, accelerate its computing, and expand its analysis + capabilities to answer additional scientific questions including a rigorous evaluation + of the association of genomic lesions with RNA expression. Pounds, Stan, et al. + (2013) . + date_publication: '2024-11-19' + bug_reports: https://github.com/abdel-elsayed87/GRIN2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GRIN2 + url_git: https://github.com/abdel-elsayed87/GRIN2 +gripp: + version: 0.2.20 + title: General Inverse Problem Platform + maintainer: Jader Lugon Junior + description: |- + Set of functions designed to solve inverse problems. The direct problem is used to calculate a cost function to be minimized. + Here are listed some papers using Inverse Problems solvers and sensitivity analysis: + (Jader Lugon Jr.; Antonio J. Silva Neto 2011) . + (Jader Lugon Jr.; Antonio J. Silva Neto; Pedro P.G.W. Rodrigues 2008) . + (Jader Lugon Jr.; Antonio J. Silva Neto; Cesar C. Santana 2008) . + date_publication: '2019-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gripp + url_git: '' +grizbayr: + version: 1.3.5 + title: Bayesian Inference for A|B and Bandit Marketing Tests + maintainer: Ryan Angi + description: |- + Uses simple Bayesian conjugate prior update rules to calculate + the win probability of each option, value remaining in the test, and + percent lift over the baseline for various marketing objectives. + References: + Fink, Daniel (1997) "A Compendium of Conjugate Priors" . + Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" . + date_publication: '2023-10-09' + bug_reports: https://github.com/rangi513/grizbayr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grizbayr + url_git: https://github.com/rangi513/grizbayr +grmsem: + version: 1.1.0 + title: |- + Genetic-Relationship-Matrix Structural Equation Modelling + (GRMSEM) + maintainer: Beate StPourcain + description: |- + Quantitative genetics tool supporting the modelling of multivariate + genetic variance structures in quantitative data. It allows fitting different + models through multivariate genetic-relationship-matrix (GRM) + structural equation modelling (SEM) in unrelated individuals, + using a maximum likelihood approach. Specifically, + it combines genome-wide genotyping information, as captured by GRMs, + with twin-research-based SEM techniques, + St Pourcain et al. (2017) , + Shapland et al. (2020) . + date_publication: '2021-01-29' + bug_reports: https://gitlab.gwdg.de/beate.stpourcain/grmsem/-/issues + url: https://gitlab.gwdg.de/beate.stpourcain/grmsem + url_cran: https://CRAN.R-project.org/package=grmsem + url_git: '' +grnn: + version: 0.1.0 + title: General regression neural network + maintainer: Pierre-Olivier Chasset + description: |- + The program GRNN implements the algorithm proposed by + Specht (1991). + date_publication: '2013-05-16' + bug_reports: '' + url: http://flow.chasset.net/r-grnn/ + url_cran: https://CRAN.R-project.org/package=grnn + url_git: '' +GRNNs: + version: 0.1.0 + title: General Regression Neural Networks Package + maintainer: Shufeng LI + description: |- + This General Regression Neural Networks Package uses various distance functions. + It was motivated by Specht (1991, ISBN:1045-9227), and updated from previous published paper + Li et al. (2016) . This package includes various functions, + although "euclidean" distance is used traditionally. + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRNNs + url_git: '' +GROAN: + version: 1.3.1 + title: Genomic Regression Workbench + maintainer: Nelson Nazzicari + description: |- + Workbench for testing genomic regression accuracy on + (optionally noisy) phenotypes. + date_publication: '2022-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GROAN + url_git: '' +grobblR: + version: 0.2.1 + title: Creating Flexible, Reproducible 'PDF' Reports + maintainer: Calvin Floyd + description: |- + A tool which allows users the ability to intuitively create + flexible, reproducible portable document format reports comprised of + aesthetically pleasing tables, images, plots and/or text. + date_publication: '2021-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grobblR + url_git: '' +groc: + version: 1.0.10 + title: Generalized Regression on Orthogonal Components + maintainer: Pierre Lafaye De Micheaux + description: Robust multiple or multivariate linear regression, nonparametric regression + on orthogonal components, classical or robust partial least squares models as + described in Bilodeau, Lafaye De Micheaux and Mahdi (2015) . + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=groc + url_git: '' +gromovlab: + version: 0.8-3 + title: Gromov-Hausdorff Type Distances for Labeled Metric Spaces + maintainer: Volkmar Liebscher + description: Computes Gromov-Hausdorff type l^p distances for labeled metric spaces. + These distances were introduced in V.Liebscher, Gromov meets Phylogenetics - new + Animals for the Zoo of Metrics on Tree Space for phylogenetic + trees, but may apply to a diversity of scenarios. + date_publication: '2021-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gromovlab + url_git: '' +groqR: + version: 0.0.3 + title: A Coding Assistant using the Fast AI Inference 'Groq' + maintainer: Gabriel Kaiser + description: A comprehensive suite of functions and 'RStudio' Add-ins leveraging + the capabilities of open-source Large Language Models (LLMs) to support R developers. + These functions offer a range of utilities, including text rewriting, translation, + and general query capabilities. Additionally, the programming-focused functions + provide assistance with debugging, translating, commenting, documenting, and unit + testing code, as well as suggesting variable and function names, thereby streamlining + the development process. + date_publication: '2025-02-13' + bug_reports: https://github.com/GabrielKaiserQFin/groqR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=groqR + url_git: https://github.com/GabrielKaiserQFin/groqR +groundhog: + version: 3.2.2 + title: Version-Control for CRAN, GitHub, and GitLab Packages + maintainer: Uri Simonsohn + description: |- + Make R scripts reproducible, by ensuring that + every time a given script is run, the same version of the used packages are + loaded (instead of whichever version the user running the script happens to + have installed). This is achieved by using the command + groundhog.library() instead of the base command library(), and including a + date in the call. The date is used to call on the same version of the + package every time (the most recent version available at that date). + Load packages from CRAN, GitHub, or Gitlab. + date_publication: '2025-01-19' + bug_reports: https://github.com/CredibilityLab/groundhog/issues + url: https://groundhogr.com/ + url_cran: https://CRAN.R-project.org/package=groundhog + url_git: https://github.com/CredibilityLab/groundhog +GroupBN: + version: 1.2.0 + title: |- + Inferring Group Bayesian Networks using Hierarchical Feature + Clustering + maintainer: Ann-Kristin Becker + description: 'Group Bayesian Networks: This package implements the inference of + group Bayesian networks based on hierarchical feature clustering, and the adaptive + refinement of the grouping regarding an outcome of interest, as described in Becker + et. al (2021) .' + date_publication: '2021-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GroupBN + url_git: '' +GroupComparisons: + version: 0.1.0 + title: Paired/Unpaired Parametric/Non-Parametric Group Comparisons + maintainer: Aaron England + description: 'Receives two vectors, computes appropriate function for group comparison + (i.e., t-test, Mann-Whitney; equality of variances), and reports the findings + (mean/median, standard deviation, test statistic, p-value, effect size) in APA + format (Fay, M.P., & Proschan, M.A. (2010)).' + date_publication: '2018-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GroupComparisons + url_git: '' +groupdata2: + version: 2.0.5 + title: Creating Groups from Data + maintainer: Ludvig Renbo Olsen + description: |- + Methods for dividing data into groups. + Create balanced partitions and cross-validation folds. + Perform time series windowing and general grouping and splitting of data. + Balance existing groups with up- and downsampling or collapse them to fewer groups. + date_publication: '2024-12-18' + bug_reports: https://github.com/ludvigolsen/groupdata2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=groupdata2 + url_git: https://github.com/ludvigolsen/groupdata2 +groupedSurv: + version: 1.0.5.1 + title: |- + Efficient Estimation of Grouped Survival Models Using the Exact + Likelihood Function + maintainer: Alexander Sibley + description: These 'Rcpp'-based functions compute the efficient score statistics + for grouped time-to-event data (Prentice and Gloeckler, 1978), with the optional + inclusion of baseline covariates. Functions for estimating the parameter of interest + and nuisance parameters, including baseline hazards, using maximum likelihood + are also provided. A parallel set of functions allow for the incorporation of + family structure of related individuals (e.g., trios). Note that the current implementation + of the frailty model (Ripatti and Palmgren, 2000) is sensitive to departures from + model assumptions, and should be considered experimental. For these data, the + exact proportional-hazards-model-based likelihood is computed by evaluating multiple + variable integration. The integration is accomplished using the 'Cuba' library + (Hahn, 2005), and the source files are included in this package. The maximization + process is carried out using Brent's algorithm, with the C++ code file from John + Burkardt and John Denker (Brent, 2002). + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=groupedSurv + url_git: '' +Grouphmap: + version: 1.0.0 + title: |- + 'Grouphmap' is an Automated One-Step Common Analysis of Batch + Expression Profile + maintainer: Yuchen Sun + description: 'The ''Grouphmap'' was implemented in R, an open-source programming + environment, and was released under the provided website. The difference analysis + is based on the ''limma'' package, which can cover gene and protein expression + profiles (Reference: Matthew E Ritchie , Belinda Phipson , Di Wu , Yifang Hu , + Charity W Law , Wei Shi , Gordon K Smyth (2015) ). The + GO enrichment analysis is based on the ''clusterProfiler'' package and supports + three common species: human, mouse, and yeast (Reference: Guangchuang Yu, Li-Gen + Wang, Yanyan Han, Qing-Yu He (2012) ). The results + of batch difference analysis and enrichment analysis are output in separate folders + for easy viewing and further visualization of the results during the process. + The results returned a heatmap in R and exported to 3 folders named DEG, go, and + merge.' + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Grouphmap + url_git: '' +groupICA: + version: 0.1.1 + title: Independent Component Analysis for Grouped Data + maintainer: Niklas Pfister + description: Contains an implementation of an independent component analysis (ICA) + for grouped data. The main function groupICA() performs a blind source separation, + by maximizing an independence across sources and allows to adjust for varying + confounding for user-specified groups. Additionally, the package contains the + function uwedge() which can be used to approximately jointly diagonalize a list + of matrices. For more details see the project website . + date_publication: '2018-06-19' + bug_reports: https://github.com/sweichwald/groupICA-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=groupICA + url_git: https://github.com/sweichwald/groupICA-R +groupr: + version: 0.1.2 + title: Groups with Inapplicable Values + maintainer: Nicholas Griffiths + description: |- + The 'groupr' package provides a more powerful version of grouped + tibbles from 'dplyr'. It allows groups to be marked inapplicable, + which is a simple but widely useful way to express structure in a dataset. + It also provides powerful pivoting and other group manipulation functions. + date_publication: '2023-03-23' + bug_reports: https://github.com/ngriffiths21/groupr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=groupr + url_git: https://github.com/ngriffiths21/groupr +grouprar: + version: 0.1.0 + title: Group Response Adaptive Randomization for Clinical Trials + maintainer: Guannan Zhai + description: |2- + + Implement group response-adaptive randomization procedures, which also integrates standard non-group response-adaptive randomization methods as specialized instances. It is also uniquely capable of managing complex scenarios, including those with delayed and missing responses, thereby expanding its utility in real-world applications. This package offers 16 functions for simulating a variety of response adaptive randomization procedures. These functions are essential for guiding the selection of statistical methods in clinical trials, providing a flexible and effective approach to trial design. Some of the detailed methodologies and algorithms used in this package, please refer to the following references: + LJ Wei (1979) + L. J. WEI and S. DURHAM (1978) + Durham, S. D., FlournoY, N. AND LI, W. (1998) + Ivanova, A., Rosenberger, W. F., Durham, S. D. and Flournoy, N. (2000) + Bai Z D, Hu F, Shen L. (2002) + Ivanova, A. (2003) + Hu, F., & Zhang, L. X. (2004) + Hu, F., & Rosenberger, W. F. (2006, ISBN:978-0-471-65396-7). + Zhang, L. X., Chan, W. S., Cheung, S. H., & Hu, F. (2007) + Zhang, L., & Rosenberger, W. F. (2006) + Hu, F., Zhang, L. X., Cheung, S. H., & Chan, W. S. (2008) . + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grouprar + url_git: '' +GroupSeq: + version: 1.4.3 + title: |- + Group Sequential Design Probabilities - With Graphical User + Interface + maintainer: Roman Pahl + description: |- + Computes probabilities related to group sequential designs for + normally distributed test statistics. Enables to derive critical + boundaries, power, drift, and confidence intervals of such designs. + Supports the alpha spending approach by Lan-DeMets (1994) + . + date_publication: '2024-02-03' + bug_reports: https://github.com/rpahl/GroupSeq/issues + url: https://rpahl.github.io/GroupSeq/ + url_cran: https://CRAN.R-project.org/package=GroupSeq + url_git: '' +GroupTest: + version: 1.0.1 + title: Multiple Testing Procedure for Grouped Hypotheses + maintainer: Zhigen Zhao + description: Contains functions for a two-stage multiple testing procedure for grouped + hypothesis, aiming at controlling both the total posterior false discovery rate + and within-group false discovery rate. + date_publication: '2015-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GroupTest + url_git: '' +groupTesting: + version: 1.3.0 + title: Simulating and Modeling Group (Pooled) Testing Data + maintainer: Md S. Warasi + description: Provides an expectation-maximization (EM) algorithm using the approach + introduced in Warasi (2023) . The EM algorithm + can be used to estimate the prevalence (overall proportion) of a disease and to + estimate a binary regression model from among the class of generalized linear + models based on group testing data. The estimation framework we consider offers + a flexible and general approach; i.e., its application is not limited to any specific + group testing protocol. Consequently, the EM algorithm can model data arising + from simple pooling as well as advanced pooling such as hierarchical testing, + array testing, and quality control pooling. Also, provided are functions that + can be used to conduct the Wald tests described in Buse (1982) + and to simulate the group testing data described in Kim et al. (2007) . + We offer a function to compute relative efficiency measures, which can be used + to optimize the maximum likelihood estimator of disease prevalence. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=groupTesting + url_git: '' +groupwalk: + version: 0.1.2 + title: Implement the Group Walk Algorithm + maintainer: Jack Freestone + description: A procedure that uses target-decoy competition (or knockoffs) to reject + multiple hypotheses in the presence of group structure. The procedure controls + the false discovery rate (FDR) at a user-specified threshold. + date_publication: '2022-06-18' + bug_reports: '' + url: https://www.biorxiv.org/content/10.1101/2022.01.30.478144v1 + url_cran: https://CRAN.R-project.org/package=groupwalk + url_git: https://github.com/freejstone/groupwalk +groupWQS: + version: 0.0.3 + title: Grouped Weighted Quantile Sum Regression + maintainer: Matthew Carli + description: Fits weighted quantile sum (WQS) regressions for one or more chemical + groups with continuous or binary outcomes. Wheeler D, Czarnota J.(2016) . + date_publication: '2020-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=groupWQS + url_git: '' +grove: + version: 1.1.1 + title: Wavelet Functional ANOVA Through Markov Groves + maintainer: Li Ma + description: |- + Functional denoising and functional ANOVA through wavelet-domain + Markov groves. Fore more details see: Ma L. and Soriano J. (2018) + Efficient functional ANOVA through wavelet-domain Markov groves. + . + date_publication: '2023-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grove + url_git: '' +growfunctions: + version: '0.16' + title: |- + Bayesian Non-Parametric Dependent Models for Time-Indexed + Functional Data + maintainer: Terrance Savitsky + description: |- + Estimates a collection of time-indexed functions under + either of Gaussian process (GP) or intrinsic Gaussian Markov + random field (iGMRF) prior formulations where a Dirichlet process + mixture allows sub-groupings of the functions to share the same + covariance or precision parameters. The GP and iGMRF formulations + both support any number of additive covariance or precision terms, + respectively, expressing either or both of multiple trend and + seasonality. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=growfunctions + url_git: '' +growR: + version: 1.3.0 + title: Implementation of the Vegetation Model ModVege + maintainer: Kevin Kramer + description: |- + Run grass growth simulations using a grass growth model based + on ModVege (Jouven, M., P. Carrère, and R. Baumont "Model Predicting + Dynamics of Biomass, Structure and Digestibility of Herbage in Managed + Permanent Pastures. 1. Model Description." (2006) + ). The implementation in + this package contains a few additions to the above cited version of ModVege, + such as simulations of management decisions, and influences of snow cover. + As such, the model is fit to simulate grass growth in mountainous + regions, such as the Swiss Alps. The package also contains routines for + calibrating the model and helpful tools for analysing model outputs and + performance. + date_publication: '2024-05-23' + bug_reports: https://github.com/kuadrat/growR/issues + url: https://kuadrat.github.io/growR/ + url_cran: https://CRAN.R-project.org/package=growR + url_git: https://github.com/kuadrat/growR +growth: + version: 1.1.1 + title: |- + Multivariate Normal and Elliptically-Contoured Repeated + Measurements Models + maintainer: Bruce Swihart + description: |- + Functions for fitting various normal theory (growth + curve) and elliptically-contoured repeated measurements models + with ARMA and random effects dependence. + date_publication: '2019-02-04' + bug_reports: https://github.com/swihart/growth/issues + url: http://www.commanster.eu/rcode.html + url_cran: https://CRAN.R-project.org/package=growth + url_git: '' +growthcleanr: + version: 2.2.0 + title: Data Cleaner for Anthropometric Measurements + maintainer: Carrie Daymont + description: |- + Identifies implausible anthropometric (e.g., height, + weight) measurements in irregularly spaced longitudinal datasets, such as those from electronic health records. + date_publication: '2024-02-26' + bug_reports: https://github.com/carriedaymont/growthcleanr/issues + url: https://carriedaymont.github.io/growthcleanr/index.html + url_cran: https://CRAN.R-project.org/package=growthcleanr + url_git: https://github.com/carriedaymont/growthcleanr +GrowthCurveME: + version: 0.1.0 + title: Mixed-Effects Modeling for Growth Data + maintainer: Anand Panigrahy + description: |- + Simple and user-friendly wrappers to the 'saemix' package for + performing linear and non-linear mixed-effects regression modeling for + growth data to account for clustering or longitudinal analysis via repeated + measurements. The package allows users to fit a variety of growth + models, including linear, exponential, logistic, and 'Gompertz' + functions. For non-linear models, starting values are automatically + calculated using initial least-squares estimates. The package includes + functions for summarizing models, visualizing data and results, + calculating doubling time and other key statistics, and generating model + diagnostic plots and residual summary statistics. It also provides + functions for generating publication-ready summary tables for reports. + Additionally, users can fit linear and non-linear least-squares + regression models if clustering is not applicable. The mixed-effects + modeling methods in this package are based on Comets, Lavenu, and + Lavielle (2017) as implemented in the + 'saemix' package. Please contact us at models@dfci.harvard.edu + with any questions. + date_publication: '2024-12-17' + bug_reports: https://github.com/cancermodels-org/GrowthCurveME/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GrowthCurveME + url_git: https://github.com/cancermodels-org/GrowthCurveME +growthcurver: + version: 0.3.1 + title: Simple Metrics to Summarize Growth Curves + maintainer: Kathleen Sprouffske + description: |- + Fits the logistic equation to + microbial growth curve data (e.g., repeated absorbance measurements + taken from a plate reader over time). From this fit, a variety of + metrics are provided, including the maximum growth rate, + the doubling time, the carrying capacity, the area under the logistic + curve, and the time to the inflection point. Method described in + Sprouffske and Wagner (2016) . + date_publication: '2020-10-19' + bug_reports: https://github.com/sprouffske/growthcurver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=growthcurver + url_git: https://github.com/sprouffske/growthcurver +growthmodels: + version: 1.3.1 + title: Nonlinear Growth Models + maintainer: Daniel Rodriguez + description: A compilation of nonlinear growth models. + date_publication: '2023-05-22' + bug_reports: https://github.com/drodriguezperez/growthmodels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=growthmodels + url_git: https://github.com/drodriguezperez/growthmodels +growthPheno: + version: 3.1.10 + title: |- + Functional Analysis of Phenotypic Growth Data to Smooth and + Extract Traits + maintainer: Chris Brien + description: |- + Assists in the plotting and functional smoothing of traits + measured over time and the extraction of features from these traits, + implementing the SET (Smoothing and Extraction of Traits) method + described in Brien et al. (2020) Plant Methods, 16. Smoothing of + growth trends for individual plants using natural cubic smoothing + splines or P-splines is available for removing transient effects and + segmented smoothing is available to deal with discontinuities in + growth trends. There are graphical tools for assessing the adequacy + of trait smoothing, both when using this and other packages, such as + those that fit nonlinear growth models. A range of per-unit (plant, + pot, plot) growth traits or features can be extracted from the + data, including single time points, interval growth rates and other + growth statistics, such as maximum growth or days to maximum growth. + The package also has tools adapted to inputting data from + high-throughput phenotyping facilities, such from a Lemna-Tec + Scananalyzer 3D (see + for more information). The package 'growthPheno' can also be + installed from . + date_publication: '2025-01-13' + bug_reports: https://github.com/briencj/growthPheno/issues + url: http://chris.brien.name/ + url_cran: https://CRAN.R-project.org/package=growthPheno + url_git: '' +growthrate: + version: '1.3' + title: Bayesian reconstruction of growth velocity + maintainer: Ian W. McKeague + description: |- + A nonparametric empirical Bayes method for recovering + gradients (or growth velocities) from observations of smooth + functions (e.g., growth curves) at isolated time points. + date_publication: '2014-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=growthrate + url_git: '' +growthrates: + version: 0.8.4 + title: Estimate Growth Rates from Experimental Data + maintainer: Thomas Petzoldt + description: |- + A collection of methods to determine growth rates from + experimental data, in particular from batch experiments and + plate reader trials. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=growthrates + url_git: https://github.com/tpetzoldt/growthrates +grpCox: + version: 1.0.2 + title: |- + Penalized Cox Model for High-Dimensional Data with Grouped + Predictors + maintainer: Xuan Dang + description: Fit the penalized Cox models with both non-overlapping and overlapping + grouped penalties including the group lasso, group smoothly clipped absolute deviation, + and group minimax concave penalty. The algorithms combine the MM approach and + group-wise descent with some computational tricks including the screening, active + set, and warm-start. Different tuning regularization parameter methods are provided. + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grpCox + url_git: '' +grPipe: + version: 0.1.0 + title: |- + Graphviz Pipeline Plot Based on Grids (grPipe: Graphviz + Pipeline) + maintainer: Daniel Gaspar Gonçalves + description: |- + Create a grid-based graphviz using the following functions: + 1 - Creating the data.frame where the nodes are; + 2 - Adding and editing nodes; + 3 - Plotting these nodes. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grPipe + url_git: '' +grplasso: + version: 0.4-7 + title: Fitting User-Specified Models with Group Lasso Penalty + maintainer: Lukas Meier + description: Fits user-specified (GLM-) models with group lasso penalty. + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grplasso + url_git: '' +grpnet: + version: '0.7' + title: Group Elastic Net Regularized GLMs and GAMs + maintainer: Nathaniel E. Helwig + description: Efficient algorithms for fitting generalized linear and additive models + with group elastic net penalties as described in Helwig (2024) . + Implements group LASSO, group MCP, and group SCAD with an optional group ridge + penalty. Computes the regularization path for linear regression (gaussian), multivariate + regression (multigaussian), logistic regression (binomial), multinomial logistic + regression (multinomial), log-linear count regression (poisson and negative.binomial), + and log-linear continuous regression (gamma and inverse gaussian). Supports default + and formula methods for model specification, k-fold cross-validation for tuning + the regularization parameters, and nonparametric regression via tensor product + reproducing kernel (smoothing spline) basis function expansion. + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grpnet + url_git: '' +grpreg: + version: 3.5.0 + title: |- + Regularization Paths for Regression Models with Grouped + Covariates + maintainer: Patrick Breheny + description: |- + Efficient algorithms for fitting the regularization path of linear + regression, GLM, and Cox regression models with grouped penalties. This + includes group selection methods such as group lasso, group MCP, and + group SCAD as well as bi-level selection methods such as the group + exponential lasso, the composite MCP, and the group bridge. For more + information, see Breheny and Huang (2009) , + Huang, Breheny, and Ma (2012) , Breheny and Huang + (2015) , and Breheny (2015) + , or visit the package homepage + . + date_publication: '2024-09-03' + bug_reports: https://github.com/pbreheny/grpreg/issues + url: https://pbreheny.github.io/grpreg/ + url_cran: https://CRAN.R-project.org/package=grpreg + url_git: https://github.com/pbreheny/grpreg +grpsel: + version: 1.3.2 + title: Group Subset Selection + maintainer: Ryan Thompson + description: |- + Provides tools for sparse regression modelling with grouped predictors using the group + subset selection penalty. Uses coordinate descent and local search algorithms to rapidly deliver + near optimal estimates. The group subset penalty can be combined with a group lasso or ridge + penalty for added shrinkage. Linear and logistic regression are supported, as are overlapping + groups. + date_publication: '2024-11-28' + bug_reports: https://github.com/ryan-thompson/grpsel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grpsel + url_git: https://github.com/ryan-thompson/grpsel +grpseq: + version: '1.0' + title: Group Sequential Analysis of Clinical Trials + maintainer: Lu Mao + description: |- + Design of group sequential trials, including non-binding futility analysis + at multiple time points (Gallo, Mao, and Shih, 2014, ). + date_publication: '2021-12-06' + bug_reports: '' + url: https://sites.google.com/view/lmaowisc/ + url_cran: https://CRAN.R-project.org/package=grpseq + url_git: '' +grpSLOPE: + version: 0.3.3 + title: Group Sorted L1 Penalized Estimation + maintainer: Alexej Gossmann + description: |- + Group SLOPE (Group Sorted L1 Penalized Estimation) is + a penalized linear regression method that is used for adaptive + selection of groups of significant predictors in a high-dimensional + linear model. The Group SLOPE method can control the (group) false + discovery rate at a user-specified level (i.e., control the expected + proportion of irrelevant among all selected groups of predictors). + For additional information about the implemented methods please see + Brzyski, Gossmann, Su, Bogdan (2018) . + date_publication: '2023-05-24' + bug_reports: https://github.com/agisga/grpSLOPE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grpSLOPE + url_git: https://github.com/agisga/grpSLOPE +GrpString: + version: 0.3.2 + title: |- + Patterns and Statistical Differences Between Two Groups of + Strings + maintainer: Hui (Tom) Tang + description: |- + Methods include converting series of event names to strings, finding common patterns + in a group of strings, discovering featured patterns when comparing two groups of strings as well + as the number and starting position of each pattern in each string, obtaining transition matrix, + computing transition entropy, statistically comparing the difference between two groups of strings, + and clustering string groups. Event names can be any action names or labels such as events in log + files or areas of interest (AOIs) in eye tracking research. + date_publication: '2017-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GrpString + url_git: '' +grr: + version: 0.9.5 + title: Alternative Implementations of Base R Functions + maintainer: Craig Varrichio + description: Alternative implementations of some base R functions, including sort, + order, and match. Functions are simplified but can be faster or have other advantages. + date_publication: '2016-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grr + url_git: '' +GRS.test: + version: '1.2' + title: |- + GRS Test for Portfolio Efficiency, Its Statistical Power + Analysis, and Optimal Significance Level Calculation + maintainer: Jae H. Kim + description: |- + Computational resources for test proposed by Gibbons, Ross, Shanken (1989). + It also has the functions for the power analysis and the choice of the optimal level of significance. + The optimal level is determined by minimizing the expected loss from hypothesis testing. + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRS.test + url_git: '' +GRShiny: + version: 1.0.0 + title: Graded Response Model + maintainer: Sooyong Lee + description: Simulation and analysis of graded response data with different types + of estimators. Also, an interactive shiny application is provided with graphics + for characteristic and information curves. Samejima (2018) . + date_publication: '2023-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRShiny + url_git: https://github.com/sooyongl/GRShiny +GRSxE: + version: 1.0.1 + title: |- + Testing Gene-Environment Interactions Through Genetic Risk + Scores + maintainer: Michael Lau + description: |- + Statistical testing procedures for detecting + GxE (gene-environment) interactions. The main focus lies on + GRSxE interaction tests that aim at detecting GxE interactions + through GRS (genetic risk scores). Moreover, a novel testing + procedure based on bagging and OOB (out-of-bag) predictions is + implemented for incorporating all available observations at + both GRS construction and GxE testing (Lau et al., 2023, + ). + date_publication: '2023-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRSxE + url_git: '' +grt: + version: 0.2.1 + title: General Recognition Theory + maintainer: Andy Wills + description: Functions to generate and analyze data for psychology experiments based + on the General Recognition Theory. + date_publication: '2017-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=grt + url_git: '' +GRTo: + version: '1.3' + title: |- + Tools for the Analysis of Gutenberg-Richter Distributions of + Earthquake Magnitudes + maintainer: Daniel C. Amorese + description: |- + Offers functions for the comparison of Gutenberg-Richter + b-values. Several functions in GRTo are helpful for the assessment of the + quality of seismicity catalogs. + date_publication: '2015-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GRTo + url_git: '' +grwat: + version: 0.0.4 + title: River Hydrograph Separation and Analysis + maintainer: Timofey Samsonov + description: |- + River hydrograph separation and daily runoff time series analysis. Provides + various filters to separate baseflow and quickflow. Implements advanced separation + technique by Rets et al. (2022) which involves + meteorological data to reveal genetic components of the runoff: ground, rain, thaw + and spring (seasonal thaw). High-performance C++17 computation, annually aggregated + variables, statistical testing and numerous plotting functions for high-quality + visualization. + date_publication: '2023-10-27' + bug_reports: https://github.com/tsamsonov/grwat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=grwat + url_git: https://github.com/tsamsonov/grwat +GSA: + version: 1.03.3 + title: Gene Set Analysis + maintainer: Rob Tibshirani + description: Gene Set Analysis. + date_publication: '2024-04-20' + bug_reports: '' + url: https://tibshirani.su.domains/GSA/ + url_cran: https://CRAN.R-project.org/package=GSA + url_git: '' +GSA.UN: + version: 1.0.0 + title: Global Sensitivity Analysis Tool + maintainer: Camila Garcia-Echeverri + description: |- + A tool to sensitivity analysis using SOBOL (Sobol, 1993) and AMA (Dell'Oca et al. 2017 ) indices. + It allows to identify the most sensitive parameter or parameters of a model. + date_publication: '2020-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSA.UN + url_git: '' +GSAfisherCombined: + version: '1.0' + title: Gene Set Analysis with Fisher Combined Method + maintainer: Carlos Garcia Prieto + description: Provides the p-value for a joint test of association between a phenotype + and a set of genetic variants (SNPs) by combining marginal p-values using the + Fisher method. See Fisher, R.A. (1925,ISBN:0-05-002170-2) Statistical Methods + for Research Workers. + date_publication: '2018-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSAfisherCombined + url_git: '' +gsalib: + version: 2.2.1 + title: Utility Functions for 'GATK' + maintainer: Louis Bergelson + description: Provides utility functions used by the Genome Analysis Toolkit ('GATK') + to load tables and plot data. The 'GATK' is a toolkit for variant discovery in + high-throughput sequencing data. + date_publication: '2022-10-07' + bug_reports: https://github.com/broadinstitute/gsalib/issues + url: https://gatk.broadinstitute.org/hc/en-us + url_cran: https://CRAN.R-project.org/package=gsalib + url_git: https://github.com/broadinstitute/gatk +gsaot: + version: 0.1.0 + title: |- + Compute Global Sensitivity Analysis Indices Using Optimal + Transport + maintainer: Leonardo Chiani + description: Computing Global Sensitivity Indices from given data using Optimal + Transport, as defined in Borgonovo et al (2024) . + You provide an input sample, an output sample, decide the algorithm, and compute + the indices. + date_publication: '2025-01-10' + bug_reports: https://github.com/pietrocipolla/gsaot/issues + url: https://pietrocipolla.github.io/gsaot/ + url_cran: https://CRAN.R-project.org/package=gsaot + url_git: https://github.com/pietrocipolla/gsaot +GSAQ: + version: '1.0' + title: Gene Set Analysis with QTL + maintainer: Samarendra Das + description: Computation of Quantitative Trait Loci hits in the selected gene set. + Performing gene set validation with Quantitative Trait Loci information. Performing + gene set enrichment analysis with available Quantitative Trait Loci data and computation + of statistical significance value from gene set analysis. Obtaining the list of + Quantitative Trait Loci hit genes along with their overlapped Quantitative Trait + Loci names. + date_publication: '2016-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSAQ + url_git: '' +gsarima: + version: 0.1-5 + title: Two Functions for Generalized SARIMA Time Series Simulation + maintainer: Olivier Briet + description: |- + Write SARIMA models in (finite) AR representation and simulate + generalized multiplicative seasonal autoregressive moving average (time) series + with Normal / Gaussian, Poisson or negative binomial distribution. + The methodology of this method is described in Briet OJT, Amerasinghe PH, and + Vounatsou P (2013) . + date_publication: '2020-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsarima + url_git: '' +gsbDesign: + version: 1.0-3 + title: Group Sequential Bayes Design + maintainer: Bjoern Bornkamp + description: |- + Group Sequential Operating Characteristics for Clinical, + Bayesian two-arm Trials with known Sigma and Normal Endpoints, + as described in Gerber and Gsponer (2016) . + date_publication: '2024-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsbDesign + url_git: '' +gsbm: + version: 0.2.2 + title: Estimate Parameters in the Generalized SBM + maintainer: Solenne Gaucher + description: Given an adjacency matrix drawn from a Generalized Stochastic Block + Model with missing observations, this package robustly estimates the probabilities + of connection between nodes and detects outliers nodes, as describes in Gaucher, + Klopp and Robin (2019) . + date_publication: '2022-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsbm + url_git: '' +gscaLCA: + version: 0.0.5 + title: |- + Generalized Structure Component Analysis- Latent Class Analysis + & Latent Class Regression + maintainer: Seohee Park + description: |2- + + Execute Latent Class Analysis (LCA) and Latent Class Regression (LCR) by using Generalized Structured Component Analysis (GSCA). This is explained in Ryoo, Park, and Kim (2019) . + It estimates the parameters of latent class prevalence and item response probability in LCA with a single line comment. It also provides graphs of item response probabilities. In addition, the package enables to estimate the relationship between the prevalence and covariates. + date_publication: '2020-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gscaLCA + url_git: https://github.com/hee6904/gscaLCA +gscounts: + version: 0.1-4 + title: Group Sequential Designs with Negative Binomial Outcomes + maintainer: Tobias Mütze + description: |- + Design and analysis of group sequential designs for negative + binomial outcomes, as described by T Mütze, E Glimm, H Schmidli, T Friede (2018) . + date_publication: '2021-11-02' + bug_reports: https://github.com/tobiasmuetze/gscounts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gscounts + url_git: https://github.com/tobiasmuetze/gscounts +gscramble: + version: 1.0.1 + title: Simulating Admixed Genotypes Without Replacement + maintainer: Eric C. Anderson + description: |- + A genomic simulation approach for creating biologically + informed individual genotypes from empirical data that 1) samples alleles + from populations without replacement, 2) segregates alleles based on species-specific + recombination rates. 'gscramble' is a flexible simulation approach that allows users + to create pedigrees of varying complexity in order to simulate admixed genotypes. + Furthermore, it allows users to track haplotype blocks from the source populations + through the pedigrees. + date_publication: '2024-02-28' + bug_reports: https://github.com/eriqande/gscramble/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gscramble + url_git: https://github.com/eriqande/gscramble +GSD: + version: 1.0.0 + title: Graph Signal Decomposition + maintainer: Donghoh Kim + description: Graph signals residing on the vertices of a graph have recently gained + prominence in research in various fields. Many methodologies have been proposed + to analyze graph signals by adapting classical signal processing tools. Recently, + several notable graph signal decomposition methods have been proposed, which include + graph Fourier decomposition based on graph Fourier transform, graph empirical + mode decomposition, and statistical graph empirical mode decomposition. This package + efficiently implements multiscale analysis applicable to various fields, and offers + an effective tool for visualizing and decomposing graph signals. For the detailed + methodology, see Ortega et al. (2018) , Shuman + et al. (2013) , Tremblay et al. (2014) , + and Cho et al. (2024) "Statistical graph empirical mode decomposition by graph + denoising and boundary treatment". + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSD + url_git: '' +GSDA: + version: '1.0' + title: Gene Set Distance Analysis (GSDA) + maintainer: Xueyuan Cao + description: The gene-set distance analysis of omic data is implemented by generalizing + distance correlations to evaluate the association of a gene set with categorical + and censored event-time variables. + date_publication: '2021-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSDA + url_git: '' +gsDesign: + version: 3.6.6 + title: Group Sequential Design + maintainer: Keaven Anderson + description: |- + Derives group sequential clinical trial designs and describes + their properties. Particular focus on time-to-event, binary, and + continuous outcomes. Largely based on methods described in + Jennison, Christopher and Turnbull, Bruce W., 2000, + "Group Sequential Methods with Applications to Clinical Trials" + ISBN: 0-8493-0316-8. + date_publication: '2025-02-11' + bug_reports: https://github.com/keaven/gsDesign/issues + url: https://keaven.github.io/gsDesign/ + url_cran: https://CRAN.R-project.org/package=gsDesign + url_git: https://github.com/keaven/gsDesign +gsDesign2: + version: 1.1.3 + title: Group Sequential Design with Non-Constant Effect + maintainer: Yujie Zhao + description: |- + The goal of 'gsDesign2' is to enable fixed or group sequential + design under non-proportional hazards. To enable highly flexible enrollment, + time-to-event and time-to-dropout assumptions, 'gsDesign2' offers piecewise + constant enrollment, failure rates, and dropout rates for a stratified + population. This package includes three methods for designs: + average hazard ratio, weighted logrank tests in Yung and Liu (2019) + , and MaxCombo tests. + Substantial flexibility on top of what is in the 'gsDesign' package + is intended for selecting boundaries. + date_publication: '2024-11-15' + bug_reports: https://github.com/Merck/gsDesign2/issues + url: https://merck.github.io/gsDesign2/ + url_cran: https://CRAN.R-project.org/package=gsDesign2 + url_git: https://github.com/Merck/gsDesign2 +GSE: + version: 4.2-1 + title: |- + Robust Estimation in the Presence of Cellwise and Casewise + Contamination and Missing Data + maintainer: Claudio Agostinelli + description: |- + Robust Estimation of Multivariate Location and Scatter in the + Presence of Cellwise and Casewise Contamination and Missing Data. + date_publication: '2022-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSE + url_git: '' +gsEasy: + version: '1.5' + title: Gene Set Enrichment Analysis in R + maintainer: Daniel Greene + description: 'R-interface to C++ implementation of the rank/score permutation based + GSEA test (Subramanian et al 2005 ).' + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsEasy + url_git: '' +GseaVis: + version: 0.0.5 + title: Implement for 'GSEA' Enrichment Visualization + maintainer: Jun Zhang + description: Mark your interesting genes on plot and support more parameters to + handle your own gene set enrichment analysis plot. + date_publication: '2022-12-20' + bug_reports: https://github.com/junjunlab/GseaVis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GseaVis + url_git: https://github.com/junjunlab/GseaVis +GSED: + version: '2.6' + title: Group Sequential Enrichment Design + maintainer: Marie-Karelle Riviere + description: Provides function to apply "Group sequential enrichment design incorporating + subgroup selection" (GSED) method proposed by Magnusson and Turnbull (2013) . + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSED + url_git: '' +gSeg: + version: '1.0' + title: Graph-Based Change-Point Detection (g-Segmentation) + maintainer: Hao Chen + description: Using an approach based on similarity graph to estimate change-point(s) + and the corresponding p-values. Can be applied to any type of data (high-dimensional, + non-Euclidean, etc.) as long as a reasonable similarity measure is available. + date_publication: '2020-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gSeg + url_git: '' +GSelection: + version: 0.1.0 + title: Genomic Selection + maintainer: Sayanti Guha Majumdar + description: Genomic selection is a specialized form of marker assisted selection. + The package contains functions to select important genetic markers and predict + phenotype on the basis of fitted training data using integrated model framework + (Guha Majumdar et. al. (2019) ) developed by combining + one additive (sparse additive models by Ravikumar et. al. (2009) ) + and one non-additive (hsic lasso by Yamada et. al. (2014) ) + model. + date_publication: '2019-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSelection + url_git: '' +GSEMA: + version: 0.99.3 + title: Gene Set Enrichment Meta-Analysis + maintainer: Juan Antonio Villatoro-García + description: Performing the different steps of gene set enrichment meta-analysis. + It provides different functions that allow the application of meta-analysis based + on the combination of effect sizes from different pathways in different studies + to obtain significant pathways that are common to all of them. + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSEMA + url_git: '' +gsheet: + version: 0.4.6 + title: Download Google Sheets Using Just the URL + maintainer: Max Conway + description: |- + Simple package to download Google Sheets using just the sharing + link. Spreadsheets can be downloaded as a data frame, or as plain text to parse + manually. Google Sheets is the new name for Google Docs Spreadsheets . + date_publication: '2024-12-14' + bug_reports: https://github.com/maxconway/gsheet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gsheet + url_git: https://github.com/maxconway/gsheet +gsignal: + version: 0.3-7 + title: Signal Processing + maintainer: Geert van Boxtel + description: |- + R implementation of the 'Octave' package 'signal', containing + a variety of signal processing tools, such as signal generation and + measurement, correlation and convolution, filtering, filter design, + filter analysis and conversion, power spectrum analysis, system + identification, decimation and sample rate change, and windowing. + date_publication: '2024-09-11' + bug_reports: https://github.com/gjmvanboxtel/gsignal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gsignal + url_git: https://github.com/gjmvanboxtel/gsignal +gsisdecoder: + version: 0.0.1 + title: High Efficient Functions to Decode NFL Player IDs + maintainer: Sebastian Carl + description: |- + A set of high efficient functions to decode identifiers of National + Football League players. + date_publication: '2020-10-13' + bug_reports: https://github.com/mrcaseb/gsisdecoder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gsisdecoder + url_git: https://github.com/mrcaseb/gsisdecoder +gsl: + version: 2.1-8 + title: Wrapper for the Gnu Scientific Library + maintainer: Robin K. S. Hankin + description: |2- + + An R wrapper for some of the functionality of the + Gnu Scientific Library. + date_publication: '2023-01-24' + bug_reports: https://github.com/RobinHankin/gsl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gsl + url_git: https://github.com/RobinHankin/gsl +gslnls: + version: 1.4.1 + title: GSL Multi-Start Nonlinear Least-Squares Fitting + maintainer: Joris Chau + description: An R interface to weighted nonlinear least-squares optimization with + the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). + The available trust region methods include the Levenberg-Marquardt algorithm with + and without geodesic acceleration, the Steihaug-Toint conjugate gradient algorithm + for large systems and several variants of Powell's dogleg algorithm. Multi-start + optimization based on quasi-random samples is implemented using a modified version + of the algorithm in Hickernell and Yuan (1997, OR Transactions). Robust nonlinear + regression can be performed using various robust loss functions, in which case + the optimization problem is solved by iterative reweighted least squares (IRLS). + Bindings are provided to tune a number of parameters affecting the low-level aspects + of the trust region algorithms. The interface mimics R's nls() function and returns + model objects inheriting from the same class. + date_publication: '2025-01-17' + bug_reports: https://github.com/JorisChau/gslnls/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gslnls + url_git: https://github.com/JorisChau/gslnls +gsloid: + version: 0.2.0 + title: Global Sea Level and Oxygen Isotope Data + maintainer: Ben Marwick + description: |- + Contains published data sets for global benthic d18O data for + 0-5.3 Myr and global sea levels based + on marine sediment core data for 0-800 ka . + date_publication: '2022-05-14' + bug_reports: https://github.com/benmarwick/gsloid + url: '' + url_cran: https://CRAN.R-project.org/package=gsloid + url_git: https://github.com/benmarwick/gsloid +GSM: + version: 1.3.2 + title: Gamma Shape Mixture + maintainer: Sergio Venturini + description: Implementation of a Bayesian approach for estimating a mixture of gamma + distributions in which the mixing occurs over the shape parameter. This family + provides a flexible and novel approach for modeling heavy-tailed distributions, + it is computationally efficient, and it only requires to specify a prior distribution + for a single parameter. + date_publication: '2015-07-08' + bug_reports: '' + url: http://projecteuclid.org/euclid.aoas/1215118537 + url_cran: https://CRAN.R-project.org/package=GSM + url_git: '' +gsMAMS: + version: 0.7.2 + title: Group Sequential Designs of Multi-Arm Multi-Stage Trials + maintainer: Tushar Patni + description: It provides functions to generate operating characteristics and to + calculate Sequential Conditional Probability Ratio Tests(SCPRT) efficacy and futility + boundary values along with sample/event size of Multi-Arm Multi-Stage(MAMS) trials + for different outcomes. The package is based on Jianrong Wu, Yimei Li, Liang Zhu + (2023) , Jianrong Wu, Yimei Li (2023) "Group Sequential + Multi-Arm Multi-Stage Survival Trial Design with Treatment Selection"(Manuscript + accepted for publication) and Jianrong Wu, Yimei Li, Shengping Yang (2023) "Group + Sequential Multi-Arm Multi-Stage Trial Design with Ordinal Endpoints"(In preparation). + date_publication: '2024-05-10' + bug_reports: https://github.com/Tpatni719/gsMAMS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gsMAMS + url_git: https://github.com/Tpatni719/gsMAMS +gsmoothr: + version: 0.1.7 + title: Smoothing tools + maintainer: Mark Robinson + description: Tools rewritten in C for various smoothing tasks + date_publication: '2014-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsmoothr + url_git: '' +GSMX: + version: '1.3' + title: Multivariate Genomic Selection + maintainer: Zhenyu Jia + description: Estimating trait heritability and handling overfitting. This package + includes a collection of functions for (1) estimating genetic variance-covariances + and calculate trait heritability; and (2) handling overfitting by calculating + the variance components and the heritability through cross validation. + date_publication: '2017-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSMX + url_git: '' +GSODR: + version: 4.1.3 + title: Global Surface Summary of the Day ('GSOD') Weather Data Client + maintainer: Adam H. Sparks + description: |- + Provides automated downloading, parsing, cleaning, unit + conversion and formatting of Global Surface Summary of the Day + ('GSOD') weather data from the from the USA National Centers for + Environmental Information ('NCEI'). Units are converted from from + United States Customary System ('USCS') units to International System + of Units ('SI'). Stations may be individually checked for number of + missing days defined by the user, where stations with too many missing + observations are omitted. Only stations with valid reported latitude + and longitude values are permitted in the final data. Additional + useful elements, saturation vapour pressure ('es'), actual vapour + pressure ('ea') and relative humidity ('RH') are calculated from the + original data using the improved August-Roche-Magnus approximation + (Alduchov & Eskridge 1996) and included in the final data set. The + resulting metadata include station identification information, + country, state, latitude, longitude, elevation, weather observations + and associated flags. For information on the 'GSOD' data from 'NCEI', + please see the 'GSOD' 'readme.txt' file available from, + . + date_publication: '2024-10-16' + bug_reports: https://github.com/ropensci/GSODR/issues + url: https://docs.ropensci.org/GSODR/ + url_cran: https://CRAN.R-project.org/package=GSODR + url_git: https://github.com/ropensci/GSODR +gson: + version: 0.1.0 + title: Base Class and Methods for 'gson' Format + maintainer: Guangchuang Yu + description: Proposes a new file format ('gson') for storing gene set and related + information, and provides read, write and other utilities to process this file + format. + date_publication: '2023-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gson + url_git: '' +GSparO: + version: '1.0' + title: Group Sparse Optimization + maintainer: Yaohua Hu + description: Approaches a group sparse solution of an underdetermined linear system. + It implements the proximal gradient algorithm to solve a lower regularization + model of group sparse learning. For details, please refer to the paper "Y. Hu, + C. Li, K. Meng, J. Qin and X. Yang. Group sparse optimization via l_{p,q} regularization. + Journal of Machine Learning Research, to appear, 2017". + date_publication: '2017-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSparO + url_git: '' +gspcr: + version: 0.9.5 + title: Generalized Supervised Principal Component Regression + maintainer: Edoardo Costantini + description: |- + Generalization of supervised principal component regression (SPCR; + Bair et al., 2006, ) to support continuous, + binary, and discrete variables as outcomes and predictors + (inspired by the 'superpc' R package ). + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gspcr + url_git: '' +gsrs: + version: 0.1.1 + title: A Group-Specific Recommendation System + maintainer: Yifei Zhang + description: A group-specific recommendation system to use dependency information + from users and items which share similar characteristics under the singular value + decomposition framework. Refer to paper A Group-Specific Recommender System + for the details. + date_publication: '2021-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsrs + url_git: '' +gsrsb: + version: 1.2.1 + title: Group Sequential Refined Secondary Boundary + maintainer: Jiangtao Gou + description: |- + A gate-keeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Computations related to group sequential primary and secondary boundaries. Refined secondary boundaries are calculated for a gate-keeping test on a primary and a secondary endpoint in a group sequential design with multiple interim looks. The choices include both the standard boundaries and the boundaries using error spending functions. + See Tamhane et al. (2018), "A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks", Biometrics, 74(1), 40-48. + date_publication: '2023-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gsrsb + url_git: '' +gss: + version: 2.2-8 + title: General Smoothing Splines + maintainer: Chong Gu + description: |- + A comprehensive package for structural multivariate + function estimation using smoothing splines. + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gss + url_git: '' +GSSE: + version: '0.1' + title: Genotype-Specific Survival Estimation + maintainer: Baosheng Liang + description: We propose a fully efficient sieve maximum likelihood method to estimate + genotype-specific distribution of time-to-event outcomes under a nonparametric + model. We can handle missing genotypes in pedigrees. We estimate the time-dependent + hazard ratio between two genetic mutation groups using B-splines, while applying + nonparametric maximum likelihood estimation to the reference baseline hazard function. The + estimators are calculated via an expectation-maximization algorithm. + date_publication: '2015-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSSE + url_git: '' +GSSTDA: + version: 1.0.0 + title: |- + Progression Analysis of Disease with Survival using Topological + Data Analysis + maintainer: Miriam Esteve + description: |- + Mapper-based survival analysis with transcriptomics data is designed to carry out. + Mapper-based survival analysis is a modification of Progression Analysis of Disease (PAD) + where survival data is taken into account in the filtering function. More + details in: J. Fores-Martos, B. Suay-Garcia, R. Bosch-Romeu, M.C. Sanfeliu-Alonso, + A. Falco, J. Climent, "Progression Analysis of Disease with Survival (PAD-S) by SurvMap + identifies different prognostic subgroups of breast cancer in a large combined set of transcriptomics + and methylation studies" . + date_publication: '2024-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GSSTDA + url_git: '' +gstar: + version: 0.1.0 + title: Generalized Space-Time Autoregressive Model + maintainer: Ahmad Zaenal + description: Multivariate time series analysis based on Generalized Space-Time Autoregressive + Model by Ruchjana et al.(2012) . + date_publication: '2019-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gstar + url_git: '' +gstat: + version: 2.1-3 + title: |- + Spatial and Spatio-Temporal Geostatistical Modelling, Prediction + and Simulation + maintainer: Edzer Pebesma + description: Variogram modelling; simple, ordinary and universal point or block + (co)kriging; spatio-temporal kriging; sequential Gaussian or indicator (co)simulation; + variogram and variogram map plotting utility functions; supports sf and stars. + date_publication: '2025-02-04' + bug_reports: https://github.com/r-spatial/gstat/issues/ + url: https://r-spatial.github.io/gstat/ + url_cran: https://CRAN.R-project.org/package=gstat + url_git: https://github.com/r-spatial/gstat/ +gStream: + version: 0.2.0 + title: Graph-Based Sequential Change-Point Detection for Streaming Data + maintainer: Hao Chen + description: Uses an approach based on k-nearest neighbor information to sequentially + detect change-points. Offers analytic approximations for false discovery control + given user-specified average run length. Can be applied to any type of data (high-dimensional, + non-Euclidean, etc.) as long as a reasonable similarity measure is available. See + references (1) Chen, H. (2019) Sequential change-point detection based on nearest + neighbors. The Annals of Statistics, 47(3):1381-1407. (2) Chu, L. and Chen, H. + (2018) Sequential change-point detection for high-dimensional and non-Euclidean + data . + date_publication: '2019-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gStream + url_git: '' +gstsm: + version: 1.0.0 + title: Generalized Spatial-Time Sequence Miner + maintainer: Antonio Castro + description: |- + Implementations of the algorithms present article + Generalized Spatial-Time Sequence Miner, original title + (Castro, Antonio; Borges, Heraldo ; Pacitti, Esther ; Porto, Fabio + ; Coutinho, Rafaelli ; Ogasawara, Eduardo . Generalização de Mineração de + Sequências Restritas no Espaço e no Tempo. In: XXXVI SBBD - + Simpósio Brasileiro de Banco de Dados, 2021 ). + date_publication: '2022-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gstsm + url_git: '' +gsubfn: + version: '0.7' + title: Utilities for Strings and Function Arguments + maintainer: G. Grothendieck + description: |- + The gsubfn function is like gsub but can take a replacement + function or certain other objects instead of the replacement string. + Matches and back references are input to the replacement function and + replaced by the function output. gsubfn can be used to split strings + based on content rather than delimiters and for quasi-perl-style string + interpolation. The package also has facilities for translating formulas + to functions and allowing such formulas in function calls instead of + functions. This can be used with R functions such as apply, sapply, + lapply, optim, integrate, xyplot, Filter and any other function that + expects another function as an input argument or functions like cat + or sql calls that may involve strings where substitution is desirable. + There is also a facility for returning multiple objects from functions + and a version of transform that allows the RHS to refer to LHS used in + the same transform. + date_publication: '2018-03-16' + bug_reports: https://github.com/ggrothendieck/gsubfn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gsubfn + url_git: https://github.com/ggrothendieck/gsubfn +gsw: + version: 1.2-0 + title: Gibbs Sea Water Functions + maintainer: Dan Kelley + description: Provides an interface to the Gibbs 'SeaWater' ('TEOS-10') C library, + version 3.06-16-0 (commit '657216dd4f5ea079b5f0e021a4163e2d26893371', dated 2022-10-11, + available at , which stems from 'Matlab' and + other code written by members of Working Group 127 of 'SCOR'/'IAPSO' (Scientific + Committee on Oceanic Research / International Association for the Physical Sciences + of the Oceans). + date_publication: '2024-08-19' + bug_reports: https://github.com/TEOS-10/GSW-R/issues + url: http://teos-10.github.io/GSW-R/ + url_cran: https://CRAN.R-project.org/package=gsw + url_git: '' +GsymPoint: + version: 1.1.2 + title: |- + Estimation of the Generalized Symmetry Point, an Optimal + Cutpoint in Continuous Diagnostic Tests + maintainer: Mónica López-Ratón + description: Estimation of the cutpoint defined by the Generalized Symmetry point + in a binary classification setting based on a continuous diagnostic test or marker. + Two methods have been implemented to construct confidence intervals for this optimal + cutpoint, one based on the Generalized Pivotal Quantity and the other based on + Empirical Likelihood. Numerical and graphical outputs for these two methods are + easily obtained. + date_publication: '2023-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GsymPoint + url_git: '' +gsynth: + version: 1.2.1 + title: Generalized Synthetic Control Method + maintainer: Yiqing Xu + description: Provides causal inference with interactive fixed-effect models. It + imputes counterfactuals for each treated unit using control group information + based on a linear interactive fixed effects model that incorporates unit-specific + intercepts interacted with time-varying coefficients. This method generalizes + the synthetic control method to the case of multiple treated units and variable + treatment periods, and improves efficiency and interpretability. This version + supports unbalanced panels and implements the matrix completion method. + date_publication: '2021-08-06' + bug_reports: '' + url: https://yiqingxu.org/packages/gsynth/gsynth_examples.html + url_cran: https://CRAN.R-project.org/package=gsynth + url_git: '' +gt: + version: 0.11.1 + title: Easily Create Presentation-Ready Display Tables + maintainer: Richard Iannone + description: |- + Build display tables from tabular data with an easy-to-use + set of functions. With its progressive approach, we can construct + display tables with a cohesive set of table parts. Table values can be + formatted using any of the included formatting functions. Footnotes + and cell styles can be precisely added through a location targeting + system. The way in which 'gt' handles things for you means that you + don't often have to worry about the fine details. + date_publication: '2024-10-04' + bug_reports: https://github.com/rstudio/gt/issues + url: https://gt.rstudio.com + url_cran: https://CRAN.R-project.org/package=gt + url_git: https://github.com/rstudio/gt +gt4ireval: + version: '2.0' + title: Generalizability Theory for Information Retrieval Evaluation + maintainer: Julián Urbano + description: |- + Provides tools to measure the reliability of an Information Retrieval test collection. + It allows users to estimate reliability using Generalizability Theory and map those estimates onto + well-known indicators such as Kendall tau correlation or sensitivity. + date_publication: '2017-03-06' + bug_reports: https://github.com/julian-urbano/gt4ireval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gt4ireval + url_git: https://github.com/julian-urbano/gt4ireval/ +gtable: + version: 0.3.6 + title: Arrange 'Grobs' in Tables + maintainer: Thomas Lin Pedersen + description: |- + Tools to make it easier to work with "tables" of 'grobs'. The + 'gtable' package defines a 'gtable' grob class that specifies a grid + along with a list of grobs and their placement in the grid. Further + the package makes it easy to manipulate and combine 'gtable' objects + so that complex compositions can be built up sequentially. + date_publication: '2024-10-25' + bug_reports: https://github.com/r-lib/gtable/issues + url: https://gtable.r-lib.org + url_cran: https://CRAN.R-project.org/package=gtable + url_git: https://github.com/r-lib/gtable +GTbasedIM: + version: 1.0.0 + title: Game Theory-Based Influence Measures + maintainer: Laura Davila-Pena + description: |- + Understanding how features influence a specific response variable becomes crucial in classification problems, with applications ranging from medical diagnosis to customer behavior analysis. + This packages provides tools to compute such an influence measure grounded on game theory concepts. + In particular, the influence measures presented in Davila-Pena, Saavedra-Nieves, and Casas-Méndez (2024) can be obtained. + date_publication: '2024-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GTbasedIM + url_git: '' +GTDL: + version: 1.0.0 + title: The Generalized Time-Dependent Logistic Family + maintainer: Jalmar Carrasco + description: |- + Computes the probability density, survival function, + the hazard rate functions and generates random samples from the + GTDL distribution given by Mackenzie, G. (1996) . + The likelihood estimates, the randomized quantile (Louzada, F., et al. + (2020) ) + residuals and the normally transformed randomized survival + probability (Li,L., et al. (2021) ) + residuals are obtained for the GTDL model. + date_publication: '2022-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GTDL + url_git: '' +gte: + version: 1.2-3 + title: Generalized Turnbull's Estimator + maintainer: Thierry Duchesne + description: |- + Generalized Turnbull's estimator proposed by Dehghan and Duchesne + (2011). + date_publication: '2022-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gte + url_git: '' +GTEs: + version: 1.0.0 + title: Group Technical Effects + maintainer: Yang Zhou + description: Implementation of the GTE (Group Technical Effects) model for single-cell + data. GTE is a quantitative metric to assess batch effects for individual genes + in single-cell data. For a single-cell dataset, the user can calculate the GTE + value for individual features (such as genes), and then identify the highly batch-sensitive + features. Removing these highly batch-sensitive features results in datasets with + low batch effects. + date_publication: '2025-02-27' + bug_reports: https://github.com/yzhou1999/GTEs/issues + url: https://yzhou1999.github.io/GTEs/ + url_cran: https://CRAN.R-project.org/package=GTEs + url_git: https://github.com/yzhou1999/GTEs +gTests: + version: '0.2' + title: Graph-Based Two-Sample Tests + maintainer: Hao Chen + description: Four graph-based tests are provided for testing whether two samples + are from the same distribution. It works for both continuous data and discrete + data. + date_publication: '2017-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gTests + url_git: '' +gTestsMulti: + version: 0.1.1 + title: New Graph-Based Multi-Sample Tests + maintainer: Hoseung Song + description: |- + New multi-sample tests for testing whether multiple samples are from the same distribution. They work well particularly for high-dimensional data. + Song, H. and Chen, H. (2022) + . + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gTestsMulti + url_git: '' +gtexr: + version: 0.1.0 + title: Query the GTEx Portal API + maintainer: Alasdair Warwick + description: |- + A convenient R interface to the Genotype-Tissue Expression (GTEx) + Portal API. For more information on the API, see + . + date_publication: '2024-09-19' + bug_reports: https://github.com/rmgpanw/gtexr/issues + url: https://rmgpanw.github.io/gtexr/ + url_cran: https://CRAN.R-project.org/package=gtexr + url_git: https://github.com/rmgpanw/gtexr +gtExtras: + version: 0.5.0 + title: Extending 'gt' for Beautiful HTML Tables + maintainer: Thomas Mock + description: |- + Provides additional functions for creating beautiful tables + with 'gt'. The functions are generally wrappers around boilerplate or + adding opinionated niche capabilities and helpers functions. + date_publication: '2023-09-15' + bug_reports: https://github.com/jthomasmock/gtExtras/issues + url: https://jthomasmock.github.io/gtExtras/ + url_cran: https://CRAN.R-project.org/package=gtExtras + url_git: https://github.com/jthomasmock/gtExtras +gtexture: + version: 1.0.0 + title: |- + Generalized Application of Co-Occurrence Matrices and Haralick + Texture + maintainer: Rowan Barker-Clarke + description: |- + Generalizes application of gray-level co-occurrence matrix + (GLCM) metrics to objects outside of images. The current focus is to + apply GLCM metrics to the study of biological networks and fitness + landscapes that are used in studying evolutionary medicine and + biology, particularly the evolution of cancer resistance. The package was + developed as part of the author's publication in Physics in Medicine and Biology + Barker-Clarke et al. (2023) . + A general reference to learn more about mathematical oncology can be found at + Rockne et al. (2019) . + date_publication: '2024-04-08' + bug_reports: https://github.com/rbarkerclarke/gtexture/issues + url: + url_cran: https://CRAN.R-project.org/package=gtexture + url_git: '' +gtfs2emis: + version: 0.1.1 + title: |- + Estimating Public Transport Emissions from General Transit Feed + Specification (GTFS) Data + maintainer: Joao Bazzo + description: 'A bottom up model to estimate the emission levels of public transport + systems based on General Transit Feed Specification (GTFS) data. The package requires + two main inputs: i) Public transport data in the GTFS standard format; and ii) + Some basic information on fleet characteristics such as fleet age, technology, + fuel and Euro stage. As it stands, the package estimates several pollutants at + high spatial and temporal resolutions. Pollution levels can be calculated for + specific transport routes, trips, time of the day or for the transport system + as a whole. The output with emission estimates can be extracted in different formats, + supporting analysis on how emission levels vary across space, time and by fleet + characteristics. A full description of the methods used in the ''gtfs2emis'' model + is presented in Vieira, J. P. B.; Pereira, R. H. M.; Andrade, P. R. (2022) .' + date_publication: '2024-12-02' + bug_reports: https://github.com/ipeaGIT/gtfs2emis/issues + url: https://ipeagit.github.io/gtfs2emis/ + url_cran: https://CRAN.R-project.org/package=gtfs2emis + url_git: https://github.com/ipeaGIT/gtfs2emis +gtfs2gps: + version: 2.1-2 + title: Converting Transport Data from GTFS Format to GPS-Like Records + maintainer: Pedro R. Andrade + description: Convert general transit feed specification (GTFS) data to global positioning + system (GPS) records in 'data.table' format. It also has some functions to subset + GTFS data in time and space and to convert both representations to simple feature + format. + date_publication: '2024-10-08' + bug_reports: https://github.com/ipeaGIT/gtfs2gps/issues + url: https://ipeagit.github.io/gtfs2gps/ + url_cran: https://CRAN.R-project.org/package=gtfs2gps + url_git: https://github.com/ipeaGIT/gtfs2gps +gtfsio: + version: 1.2.0 + title: Read and Write General Transit Feed Specification (GTFS) Files + maintainer: Daniel Herszenhut + description: |- + Tools for the development of packages related to General + Transit Feed Specification (GTFS) files. Establishes a standard for + representing GTFS feeds using R data types. Provides fast and flexible + functions to read and write GTFS feeds while sticking to this + standard. Defines a basic 'gtfs' class which is meant to be extended + by packages that depend on it. And offers utility functions that + support checking the structure of GTFS objects. + date_publication: '2024-10-11' + bug_reports: https://github.com/r-transit/gtfsio/issues + url: https://r-transit.github.io/gtfsio/ + url_cran: https://CRAN.R-project.org/package=gtfsio + url_git: https://github.com/r-transit/gtfsio +gtfsrouter: + version: 0.1.3 + title: Routing with 'GTFS' (General Transit Feed Specification) Data + maintainer: Mark Padgham + description: |- + Use 'GTFS' (General Transit Feed Specification) data for routing + from nominated start and end stations, for extracting 'isochrones', and + travel times from any nominated start station to all other stations. + date_publication: '2024-10-29' + bug_reports: https://github.com/UrbanAnalyst/gtfsrouter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gtfsrouter + url_git: https://github.com/UrbanAnalyst/gtfsrouter +gtfstools: + version: 1.4.0 + title: |- + General Transit Feed Specification (GTFS) Editing and Analysing + Tools + maintainer: Daniel Herszenhut + description: |- + Utility functions to read, manipulate, analyse and write + transit feeds in the General Transit Feed Specification (GTFS) data + format. + date_publication: '2025-01-09' + bug_reports: https://github.com/ipeaGIT/gtfstools/issues + url: https://ipeagit.github.io/gtfstools/ + url_cran: https://CRAN.R-project.org/package=gtfstools + url_git: https://github.com/ipeaGIT/gtfstools +GTFSwizard: + version: 1.0.0 + title: Exploring and Manipulating 'GTFS' Files + maintainer: Nelson de O. Quesado Filho + description: Exploring, analyzing, and manipulating General Transit Feed Specification + (GTFS) files, which represent public transportation schedules and geographic data. + The package allows users to filter data by routes, trips, stops, and time, generate + spatial visualizations, and perform detailed analyses of transit networks, including + headway, dwell times, and route frequencies. Designed for transit planners, researchers, + and data analysts, 'GTFSwizard' integrates functionalities from popular packages + to enable efficient GTFS data manipulation and visualization. + date_publication: '2024-11-11' + bug_reports: https://github.com/nelsonquesado/GTFSwizard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GTFSwizard + url_git: https://github.com/nelsonquesado/GTFSwizard +gtheory: + version: 0.1.2 + title: Apply Generalizability Theory with R + maintainer: Christopher T. Moore + description: |- + Estimates variance components, generalizability coefficients, + universe scores, and standard errors when observed scores contain variation from + one or more measurement facets (e.g., items and raters). + date_publication: '2016-10-30' + bug_reports: '' + url: http://EvaluationDashboard.com + url_cran: https://CRAN.R-project.org/package=gtheory + url_git: '' +gto: + version: 0.1.2 + title: Insert 'gt' Tables into Word Documents + maintainer: Ellis Hughes + description: |- + Insert tables created by the 'gt' R package into 'Microsoft Word' + documents. This gives users the ability to add to their existing word documents + the tables made in 'gt' using the familiar 'officer' package and syntax from + the 'officeverse'. + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gto + url_git: '' +gtools: + version: 3.9.5 + title: Various R Programming Tools + maintainer: Ben Bolker + description: |- + Functions to assist in R programming, including: + - assist in developing, updating, and maintaining R and R packages ('ask', 'checkRVersion', + 'getDependencies', 'keywords', 'scat'), + - calculate the logit and inverse logit transformations ('logit', 'inv.logit'), + - test if a value is missing, empty or contains only NA and NULL values ('invalid'), + - manipulate R's .Last function ('addLast'), + - define macros ('defmacro'), + - detect odd and even integers ('odd', 'even'), + - convert strings containing non-ASCII characters (like single quotes) to plain ASCII ('ASCIIfy'), + - perform a binary search ('binsearch'), + - sort strings containing both numeric and character components ('mixedsort'), + - create a factor variable from the quantiles of a continuous variable ('quantcut'), + - enumerate permutations and combinations ('combinations', 'permutation'), + - calculate and convert between fold-change and log-ratio ('foldchange', + 'logratio2foldchange', 'foldchange2logratio'), + - calculate probabilities and generate random numbers from Dirichlet distributions + ('rdirichlet', 'ddirichlet'), + - apply a function over adjacent subsets of a vector ('running'), + - modify the TCP_NODELAY ('de-Nagle') flag for socket objects, + - efficient 'rbind' of data frames, even if the column names don't match ('smartbind'), + - generate significance stars from p-values ('stars.pval'), + - convert characters to/from ASCII codes ('asc', 'chr'), + - convert character vector to ASCII representation ('ASCIIfy'), + - apply title capitalization rules to a character vector ('capwords'). + date_publication: '2023-11-20' + bug_reports: https://github.com/r-gregmisc/gtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gtools + url_git: https://github.com/r-gregmisc/gtools +gtranslate: + version: 0.0.1 + title: Translate Between Different Languages + maintainer: Mohamed El-Desouky + description: The goal of this package is to translate between different languages + without any Google API authentication which is pain and you must pay for the key, + This package is free and lightweight. + date_publication: '2023-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gtranslate + url_git: '' +gtreg: + version: 0.4.1 + title: Regulatory Tables for Clinical Research + maintainer: Shannon Pileggi + description: |- + Creates tables suitable for regulatory agency submission by + leveraging the 'gtsummary' package as the back end. Tables can be exported + to HTML, Word, PDF and more. Highly customized outputs are + available by utilizing existing styling functions from 'gtsummary' as + well as custom options designed for regulatory tables. + date_publication: '2025-02-27' + bug_reports: https://github.com/shannonpileggi/gtreg/issues + url: https://shannonpileggi.github.io/gtreg/ + url_cran: https://CRAN.R-project.org/package=gtreg + url_git: https://github.com/shannonpileggi/gtreg +gtrendsR: + version: 1.5.1 + title: Perform and Display Google Trends Queries + maintainer: Philippe Massicotte + description: |- + An interface for retrieving and displaying the information + returned online by Google Trends is provided. Trends (number of + hits) over the time as well as geographic representation of the + results can be displayed. + date_publication: '2022-05-23' + bug_reports: https://github.com/PMassicotte/gtrendsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gtrendsR + url_git: https://github.com/PMassicotte/gtrendsR +gtsummary: + version: 2.1.0 + title: Presentation-Ready Data Summary and Analytic Result Tables + maintainer: Daniel D. Sjoberg + description: |- + Creates presentation-ready tables summarizing data sets, + regression models, and more. The code to create the tables is concise + and highly customizable. Data frames can be summarized with any + function, e.g. mean(), median(), even user-written functions. + Regression models are summarized and include the reference rows for + categorical variables. Common regression models, such as logistic + regression and Cox proportional hazards regression, are automatically + identified and the tables are pre-filled with appropriate column + headers. + date_publication: '2025-02-19' + bug_reports: https://github.com/ddsjoberg/gtsummary/issues + url: https://www.danieldsjoberg.com/gtsummary/ + url_cran: https://CRAN.R-project.org/package=gtsummary + url_git: https://github.com/ddsjoberg/gtsummary +gtWAS: + version: 1.1.0 + title: Genome and Transcriptome Wide Association Study + maintainer: JunhuiLi + description: Quantitative trait loci mapping and genome wide association analysis + are used to find candidate molecular marker or region associated with phenotype + based on linkage analysis and linkage disequilibrium. Gene expression quantitative + trait loci mapping is used to find candidate molecular marker or region associated + with gene expression. In this package, we applied the method in Liu W. (2011) + and Gusev A. (2016) to genome + and transcriptome wide association study, which is aimed at revealing the association + relationship between phenotype and molecular markers, expression levels, molecular + markers nested within different related expression effect and expression effect + nested within different related molecular marker effect. F test based on full + and reduced model are performed to obtain p value or likelihood ratio statistic. + The best linear model can be obtained by stepwise regression analysis. + date_publication: '2019-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gtWAS + url_git: '' +guaguas: + version: 0.3.0 + title: Nombres Inscritos en Chile (1920 - 2021) + maintainer: Riva Quiroga + description: |- + Datos de nombres inscritos en Chile + entre 1920 y 2021, de acuerdo al Servicio de Registro Civil. + English: Chilean baby names registered from 1920 to 2021 + by the Civil Registry Service. + date_publication: '2022-03-09' + bug_reports: https://github.com/rivaquiroga/guaguas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=guaguas + url_git: https://github.com/rivaquiroga/guaguas +guardianapi: + version: 0.1.1 + title: Access 'The Guardian' Newspaper Open Data API + maintainer: Evan Odell + description: |- + Access to 'The Guardian' newspaper's open API + , containing all articles published + in 'The Guardian' from 1999 to the present, including article text, metadata, + tags and contributor information. An API key and registration is required. + date_publication: '2019-06-23' + bug_reports: https://github.com/evanodell/guardianapi/issues + url: https://docs.evanodell.com/guardianapi + url_cran: https://CRAN.R-project.org/package=guardianapi + url_git: '' +GUD: + version: 1.0.2 + title: Bayesian Modal Regression Based on the GUD Family + maintainer: Qingyang Liu + description: 'Provides probability density functions and sampling algorithms for + three key distributions from the General Unimodal Distribution (GUD) family: the + Flexible Gumbel (FG) distribution, the Double Two-Piece (DTP) Student-t distribution, + and the Two-Piece Scale (TPSC) Student-t distribution. Additionally, this package + includes a function for Bayesian linear modal regression, leveraging these three + distributions for model fitting. The details of the Bayesian modal regression + model based on the GUD family can be found at Liu, Huang, and Bai (2024) .' + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GUD + url_git: https://github.com/rh8liuqy/Bayesian_modal_regression +Guerry: + version: 1.8.3 + title: |- + Maps, Data and Methods Related to Guerry (1833) "Moral + Statistics of France" + maintainer: Michael Friendly + description: |- + Maps of France in 1830, multivariate datasets from A.-M. Guerry and others, and statistical and + graphic methods related to Guerry's "Moral Statistics of France". The goal is to facilitate the exploration and + development of statistical and graphic methods for multivariate data in a geospatial context of historical interest. + date_publication: '2023-10-24' + bug_reports: https://github.com/friendly/Guerry/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Guerry + url_git: https://github.com/friendly/Guerry +guescini: + version: 0.1.0 + title: Real-Time PCR Data Sets by Guescini et al. (2008) + maintainer: Ramiro Magno + description: |- + Real-time quantitative polymerase chain reaction (qPCR) data + by Guescini et al. (2008) in tidy format. + This package provides two data sets where the amplification efficiency has + been modulated: either by changing the amplification mix concentration, or + by increasing the concentration of IgG, a PCR inhibitor. + Original raw data files: + and + . + date_publication: '2024-04-22' + bug_reports: https://github.com/ramiromagno/guescini/issues + url: https://rmagno.eu/guescini/ + url_cran: https://CRAN.R-project.org/package=guescini + url_git: https://github.com/ramiromagno/guescini +guess: + version: '0.1' + title: Adjust Estimates of Learning for Guessing + maintainer: Gaurav Sood + description: |- + Adjust Estimates of Learning for Guessing. The package provides + standard guessing correction, and a latent class model that leverages + informative pre-post transitions. For details of the latent class model, + see . + date_publication: '2016-02-08' + bug_reports: http://github.com/soodoku/guess/issues + url: '' + url_cran: https://CRAN.R-project.org/package=guess + url_git: http://github.com/soodoku/guess +GUEST: + version: 0.2.0 + title: |- + Graphical Models in Ultrahigh-Dimensional and Error-Prone Data + via Boosting Algorithm + maintainer: Hui-Shan Tsao + description: We consider the ultrahigh-dimensional and error-prone data. Our goal + aims to estimate the precision matrix and identify the graphical structure of + the random variables with measurement error corrected. We further adopt the estimated + precision matrix to the linear discriminant function to do classification for + multi-label classes. + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GUEST + url_git: '' +guidedPLS: + version: 1.0.0 + title: Supervised Dimensional Reduction by Guided Partial Least Squares + maintainer: Koki Tsuyuzaki + description: Guided partial least squares (guided-PLS) is the combination of partial + least squares by singular value decomposition (PLS-SVD) and guided principal component + analysis (guided-PCA). For the details of the methods, see the reference section + of GitHub README.md . + date_publication: '2023-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=guidedPLS + url_git: https://github.com/rikenbit/guidedPLS +guideR: + version: 0.1.0 + title: Miscellaneous Statistical Functions Used in 'guide-R' + maintainer: Joseph Larmarange + description: |- + Companion package for the manual + 'guide-R : Guide pour l’analyse de données d’enquêtes avec R' available at + . 'guideR' implements miscellaneous + functions introduced in 'guide-R' to facilitate statistical analysis and + manipulation of survey data. + date_publication: '2025-02-14' + bug_reports: https://github.com/larmarange/guideR/issues + url: https://larmarange.github.io/guideR/ + url_cran: https://CRAN.R-project.org/package=guideR + url_git: https://github.com/larmarange/guideR +guildai: + version: 0.0.1 + title: Track Machine Learning Experiments + maintainer: Tomasz Kalinowski + description: |- + 'Guild AI' is an open-source tool for managing machine learning + experiments. It's for scientists, engineers, and researchers who want to + run scripts, compare results, measure progress, and automate machine + learning workflow. 'Guild AI' is a light weight, external tool that runs + locally. It works with any framework, doesn't require any changes to + your code, or access to any web services. Users can easily record + experiment metadata, track model changes, manage experiment artifacts, + tune hyperparameters, and share results. 'Guild AI' combines features + from 'Git', 'SQLite', and 'Make' to provide a lab notebook for machine + learning. + date_publication: '2023-03-06' + bug_reports: https://github.com/guildai/guildai-r/issues + url: https://guildai.github.io/guildai-r/ + url_cran: https://CRAN.R-project.org/package=guildai + url_git: https://github.com/guildai/guildai-r +GUILDS: + version: 1.4.6 + title: |- + Implementation of Sampling Formulas for the Unified Neutral + Model of Biodiversity and Biogeography, with or without Guild + Structure + maintainer: Thijs Janzen + description: A collection of sampling formulas for the unified neutral model of + biogeography and biodiversity. Alongside the sampling formulas, it includes methods + to perform maximum likelihood optimization of the sampling formulas, methods to + generate data given the neutral model, and methods to estimate the expected species + abundance distribution. Sampling formulas included in the GUILDS package are the + Etienne Sampling Formula (Etienne 2005), the guild sampling formula, where guilds + are assumed to differ in dispersal ability (Janzen et al. 2015), and the guilds + sampling formula conditioned on guild size (Janzen et al. 2015). + date_publication: '2023-08-21' + bug_reports: https://github.com/thijsjanzen/GUILDS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GUILDS + url_git: https://github.com/thijsjanzen/GUILDS +guiplot: + version: 0.5.0 + title: User-Friendly GUI Plotting Tools + maintainer: Fu Yongchao + description: |- + Create a user-friendly plotting GUI for 'R'. + In addition, one purpose of creating the 'R' package is to facilitate third-party software to call 'R' for drawing, for example, 'Phoenix WinNonlin' software calls 'R' to draw the drug concentration versus time curve. + date_publication: '2023-09-03' + bug_reports: '' + url: https://s0521.github.io/guiplot/about/ + url_cran: https://CRAN.R-project.org/package=guiplot + url_git: '' +GUIProfiler: + version: 2.0.1 + title: Graphical User Interface for Rprof() + maintainer: Fernando de Villar + description: Show graphically the results of profiling R functions by tracking their + execution time. + date_publication: '2015-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GUIProfiler + url_git: '' +guix.install: + version: 1.0.0 + title: Install R Packages with GNU Guix + maintainer: Ricardo Wurmus + description: |- + This 'R' package provides a single procedure guix.install(), + which allows users to install 'R' packages via 'Guix' right from within + their running 'R' session. If the requested 'R' package does not exist + in 'Guix' at this time, the package and all its missing dependencies + will be imported recursively and the generated package definitions + will be written to ~/.Rguix/packages.scm. This record of imported + packages can be used later to reproduce the environment, and to add + the packages in question to a proper 'Guix' channel (or 'Guix' itself). + guix.install() not only supports installing packages from CRAN, but + also from Bioconductor or even arbitrary 'git' or 'mercurial' + repositories, replacing the need for installation via 'devtools'. + date_publication: '2022-04-28' + bug_reports: https://github.com/BIMSBbioinfo/guix.install/issues + url: '' + url_cran: https://CRAN.R-project.org/package=guix.install + url_git: https://github.com/BIMSBbioinfo/guix.install +gumbel: + version: 1.10-3 + title: The Gumbel-Hougaard Copula + maintainer: Christophe Dutang + description: Provides probability functions (cumulative distribution and density + functions), simulation function (Gumbel copula multivariate simulation) and estimation + functions (Maximum Likelihood Estimation, Inference For Margins, Moment Based + Estimation and Canonical Maximum Likelihood). + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gumbel + url_git: '' +gumboot: + version: 1.0.1 + title: |- + Bootstrap Analyses of Sampling Uncertainty in Goodness-of-Fit + Statistics + maintainer: Kevin Shook + description: Uses jackknife and bootstrap methods to quantify the sampling uncertainty + in goodness-of-fit statistics. Full details are in Clark et al. (2021), "The abuse + of popular performance metrics in hydrologic modeling", Water Resources Research, + . + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gumboot + url_git: '' +GUniFrac: + version: '1.8' + title: |- + Generalized UniFrac Distances, Distance-Based Multivariate + Methods and Feature-Based Univariate Methods for Microbiome + Data Analysis + maintainer: Jun Chen + description: 'A suite of methods for powerful and robust microbiome data analysis + including data normalization, data simulation, community-level association testing + and differential abundance analysis. It implements generalized UniFrac distances, Geometric + Mean of Pairwise Ratios (GMPR) normalization, semiparametric data simulator, distance-based + statistical methods, and feature-based statistical methods. The distance-based + statistical methods include three extensions of PERMANOVA: (1) PERMANOVA using + the Freedman-Lane permutation scheme, (2) PERMANOVA omnibus test using multiple + matrices, and (3) analytical approach to approximating PERMANOVA p-value. Feature-based + statistical methods include linear model-based methods for differential abundance + analysis of zero-inflated high-dimensional compositional data.' + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GUniFrac + url_git: '' +gunit: + version: 1.0.2 + title: Converts Conductance Units + maintainer: Chris Muir + description: 'For plant physiologists, converts conductance (e.g. stomatal conductance) + to different units: m/s, mol/m^2/s, and umol/m^2/s/Pa.' + date_publication: '2022-10-18' + bug_reports: https://github.com/cdmuir/gunit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gunit + url_git: https://github.com/cdmuir/gunit +gunsales: + version: 0.1.2 + title: |- + Statistical Analysis of Monthly Background Checks of Gun + Purchases + maintainer: Dirk Eddelbuettel + description: |- + Statistical analysis of monthly background checks of gun purchases for the New York Times + story "What Drives Gun Sales: Terrorism, Obama and Calls for Restrictions" at + is provided. + date_publication: '2017-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gunsales + url_git: '' +gustave: + version: 1.0.0 + title: |- + A User-Oriented Statistical Toolkit for Analytical Variance + Estimation + maintainer: Khaled Larbi + description: Provides a toolkit for analytical variance estimation in survey sampling. + Apart from the implementation of standard variance estimators, its main feature + is to help the sampling expert produce easy-to-use variance estimation "wrappers", + where systematic operations (linearization, domain estimation) are handled in + a consistent and transparent way. + date_publication: '2023-11-17' + bug_reports: https://github.com/InseeFr/gustave/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gustave + url_git: https://github.com/InseeFr/gustave +gutenbergr: + version: 0.2.4 + title: Download and Process Public Domain Works from Project Gutenberg + maintainer: Myfanwy Johnston + description: |- + Download and process public domain works in the Project + Gutenberg collection . Includes metadata for + all Project Gutenberg works, so that they can be searched and retrieved. + date_publication: '2023-11-12' + bug_reports: https://github.com/ropensci/gutenbergr/issues + url: https://docs.ropensci.org/gutenbergr/ + url_cran: https://CRAN.R-project.org/package=gutenbergr + url_git: https://github.com/ropensci/gutenbergr +GUTS: + version: 1.2.5 + title: |- + Fast Calculation of the Likelihood of a Stochastic Survival + Model + maintainer: Oliver Jakoby + description: Given exposure and survival time series as well as parameter values, + GUTS allows for the fast calculation of the survival probabilities as well as + the logarithm of the corresponding likelihood (see Albert, C., Vogel, S. and Ashauer, + R. (2016) ). + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GUTS + url_git: '' +GVARX: + version: '1.4' + title: Perform Global Vector Autoregression Estimation and Inference + maintainer: Ho Tsung-wu + description: Light procedures for learning Global Vector Autoregression model (GVAR) + of Pesaran, Schuermann and Weiner (2004) and + Dees, di Mauro, Pesaran and Smith (2007) . + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GVARX + url_git: '' +gvc: + version: 6.4.0 + title: Global Value Chains Tools + maintainer: Bastiaan Quast + description: |- + Several tools for Global Value Chain ('GVC') analysis are + implemented. + date_publication: '2022-06-19' + bug_reports: https://github.com/bquast/gvc/issues + url: https://qua.st/gvc + url_cran: https://CRAN.R-project.org/package=gvc + url_git: https://github.com/bquast/gvc +gvcR: + version: 0.4.0 + title: Genotypic Variance Components + maintainer: Muhammad Yaseen + description: Functionalities to compute model based genetic components i.e. genotypic + variance, phenotypic variance and heritability for given traits of different genotypes + from replicated data using methodology explained by Burton, G. W. & Devane, E. + H. (1953) () and Allard, R.W. (2010, + ISBN:8126524154). + date_publication: '2024-10-01' + bug_reports: https://github.com/myaseen208/gvcR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gvcR + url_git: https://myaseen208.com/gvcR/https://github.com/MYaseen208/gvcR +gvlma: + version: 1.0.0.3 + title: Global Validation of Linear Models Assumptions + maintainer: Elizabeth Slate + description: 'Methods from the paper: Pena, EA and Slate, EH, "Global Validation + of Linear Model Assumptions," J. American Statistical Association, 101(473):341-354, + 2006.' + date_publication: '2019-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gvlma + url_git: '' +GVS: + version: 0.0.1 + title: '''Geocoordinate Validation Service''' + maintainer: Brian Maitner + description: The 'Geocoordinate Validation Service' (GVS) runs checks of coordinates + in latitude/longitude format. It returns annotated coordinates with additional + flags and metadata that can be used in data cleaning. Additionally, the package + has functions related to attribution and metadata information. More information + can be found at . + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GVS + url_git: '' +GWalkR: + version: 0.2.0 + title: Interactive Exploratory Data Analysis Tool + maintainer: Yue Yu + description: Simplify your R data analysis and data visualization workflow by turning + your data frame into an interactive 'Tableau'-like interface, leveraging the 'graphic-walker' + JavaScript library and the 'htmlwidgets' package. + date_publication: '2024-10-02' + bug_reports: https://github.com/Kanaries/GWalkR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GWalkR + url_git: https://github.com/Kanaries/GWalkR/ +gwaRs: + version: 0.3.0 + title: Manhattan, Q-Q, and PCA Plots using 'ggplot2' + maintainer: Lindokuhle Nkambule + description: Generate Manhattan, Q-Q, and PCA plots from GWAS and PCA results using + 'ggplot2'. + date_publication: '2021-04-19' + bug_reports: https://github.com/LindoNkambule/gwaRs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gwaRs + url_git: https://github.com/LindoNkambule/gwaRs +GWASbyCluster: + version: 0.1.7 + title: |- + Identifying Significant SNPs in Genome Wide Association Studies + (GWAS) via Clustering + maintainer: Li Xing + description: Identifying disease-associated significant SNPs using clustering approach. + This package is implementation of method proposed in Xu et al (2019) . + date_publication: '2019-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWASbyCluster + url_git: '' +GWASExactHW: + version: '1.2' + title: Exact Hardy-Weinburg Testing for Genome Wide Association Studies + maintainer: Stephanie Gogarten + description: |2- + + Exact Hardy-Weinburg testing (using Fisher's test) for SNP genotypes + as typically obtained in a Genome Wide Association Study (GWAS). + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWASExactHW + url_git: '' +gwasforest: + version: 1.0.0 + title: Make Forest Plot with GWAS Data + maintainer: Yili Xu + description: Extract and reform data from GWAS (genome-wide association study) results, + and then make a single integrated forest plot containing multiple windows of which + each shows the result of individual SNPs (or other items of interest). + date_publication: '2020-11-24' + bug_reports: https://github.com/yilixu/gwasforest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gwasforest + url_git: https://github.com/yilixu/gwasforest +GWASinlps: + version: '2.3' + title: |- + Non-Local Prior Based Iterative Variable Selection Tool for + Genome-Wide Association Studies + maintainer: Nilotpal Sanyal + description: Performs variable selection with data from Genome-wide association + studies (GWAS), or other high-dimensional data with continuous, binary or survival + outcomes, combining in an iterative framework the computational efficiency of + the structured screen-and-select variable selection strategy based on some association + learning and the parsimonious uncertainty quantification provided by the use of + non-local priors (see Sanyal et al., 2019 ). + date_publication: '2024-10-20' + bug_reports: https://github.com/nilotpalsanyal/GWASinlps/issues + url: https://nilotpalsanyal.github.io/GWASinlps/ + url_cran: https://CRAN.R-project.org/package=GWASinlps + url_git: '' +GWASinspector: + version: 1.7.1 + title: Comprehensive and Easy to Use Quality Control of GWAS Results + maintainer: Alireza Ani + description: When evaluating the results of a genome-wide association study (GWAS), + it is important to perform a quality control to ensure that the results are valid, + complete, correctly formatted, and, in case of meta-analysis, consistent with + other studies that have applied the same analysis. This package was developed + to facilitate and streamline this process and provide the user with a comprehensive + report. + date_publication: '2024-05-06' + bug_reports: '' + url: http://GWASinspector.com + url_cran: https://CRAN.R-project.org/package=GWASinspector + url_git: '' +gwasrapidd: + version: 0.99.17 + title: '''REST'' ''API'' Client for the ''NHGRI''-''EBI'' ''GWAS'' Catalog' + maintainer: Ramiro Magno + description: |- + 'GWAS' R 'API' Data Download. + This package provides easy access to the 'NHGRI'-'EBI' 'GWAS' Catalog data by + accessing the 'REST' 'API' . + date_publication: '2023-12-15' + bug_reports: https://github.com/ramiromagno/gwasrapidd/issues + url: https://rmagno.eu/gwasrapidd/ + url_cran: https://CRAN.R-project.org/package=gwasrapidd + url_git: https://github.com/ramiromagno/gwasrapidd +gwavr: + version: 0.3.2 + title: Get Water Attributes Visually in R + maintainer: Joshua Erickson + description: Provides methods to Get Water Attributes Visually in R ('gwavr'). This + allows the user to point and click on areas within the United States and get back + hydrological data, e.g. flowlines, catchments, basin boundaries, comids, etc. + date_publication: '2024-12-17' + bug_reports: https://github.com/joshualerickson/gwavr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=gwavr + url_git: https://github.com/joshualerickson/gwavr/ +gwbr: + version: 1.0.5 + title: Local and Global Beta Regression + maintainer: Roberto Marques + description: Fit a regression model for when the response variable is presented + as a ratio or proportion. This adjustment can occur globally, with the same estimate + for the entire study space, or locally, where a beta regression model is fitted + for each region, considering only influential locations for that area. Da Silva, + A. R. and Lima, A. O. (2017) . + date_publication: '2023-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gwbr + url_git: '' +GWEX: + version: 1.1.3 + title: |- + Multi-Site Stochastic Models for Daily Precipitation and + Temperature + maintainer: Guillaume Evin + description: |- + Application of multi-site models for daily precipitation and temperature data. + This package is designed for an application to 105 precipitation and 26 temperature gauges located in Switzerland. + It applies fitting procedures and provides weather generators described in the following references: + - Evin, G., A.-C. Favre, and B. Hingray. (2018) . + - Evin, G., A.-C. Favre, and B. Hingray. (2018) . + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWEX + url_git: '' +GWI: + version: 1.0.2 + title: Count and Continuous Generalized Variability Indexes + maintainer: Aboubacar Y. Touré + description: Firstly, both functions of the univariate Poisson dispersion index + (DI) for count data and the univariate exponential variation index (VI) for nonnegative + continuous data are performed. Next, other functions of univariate indexes such + the binomial dispersion index (DIb), the negative binomial dispersion index (DInb) + and the inverse Gaussian variation index (VIiG) are given. Finally, we are computed + some multivariate versions of these functions such that the generalized dispersion + index (GDI) with its marginal one (MDI) and the generalized variation index (GVI) + with its marginal one (MVI) too. + date_publication: '2021-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWI + url_git: '' +gwid: + version: 0.3.0 + title: Genome-Wide Identity-by-Descent + maintainer: Soroush Mahmoudiandehkordi + description: |- + Methods and tools for the analysis of Genome Wide + Identity-by-Descent ('gwid') mapping data, focusing on testing whether there + is a higher occurrence of Identity-By-Descent (IBD) segments around potential causal variants + in cases compared to controls, which is crucial for identifying rare + variants. To enhance its analytical power, 'gwid' incorporates a Sliding + Window Approach, allowing for the detection and analysis of signals from + multiple Single Nucleotide Polymorphisms (SNPs). + date_publication: '2024-09-03' + bug_reports: https://github.com/soroushmdg/gwid/issues + url: https://soroushmdg.github.io/gwid/ + url_cran: https://CRAN.R-project.org/package=gwid + url_git: https://github.com/soroushmdg/gwid +gWidgets2: + version: 1.0-10 + title: Rewrite of gWidgets API for Simplified GUI Construction + maintainer: John Verzani + description: |- + Re-implementation of the 'gWidgets' API. The API is defined in this + package. A second, toolkit-specific package is required to use it. At this point only 'gWidgets2tcltk' is viable. + date_publication: '2024-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gWidgets2 + url_git: https://github.com/gWidgets3/gWidgets2 +gWidgets2tcltk: + version: 1.0-8 + title: Toolkit Implementation of gWidgets2 for tcltk + maintainer: John Verzani + description: Port of the 'gWidgets2' API for the 'tcltk' package. + date_publication: '2022-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gWidgets2tcltk + url_git: https://github.com/jverzani/gWidgets2tcltk +GWlasso: + version: 1.0.1 + title: Geographically Weighted Lasso + maintainer: Matthieu Mulot + description: |- + Performs geographically weighted Lasso regressions. Find optimal bandwidth, fit a geographically weighted lasso or ridge regression, and make predictions. + These methods are specially well suited for ecological inferences. Bandwidth selection algorithm is from A. Comber and P. Harris (2018) . + date_publication: '2024-11-22' + bug_reports: https://github.com/nibortolum/GWlasso/issues + url: https://nibortolum.github.io/GWlasso/ + url_cran: https://CRAN.R-project.org/package=GWlasso + url_git: https://github.com/nibortolum/GWlasso +GWLelast: + version: 1.2.2 + title: Geographically Weighted Logistic Elastic Net Regression + maintainer: Daisuke Yoneoka + description: 'Fit a geographically weighted logistic elastic net regression. Detailed + explanations can be found in Yoneoka et al. (2016): New algorithm for constructing + area-based index with geographical heterogeneities and variable selection: An + application to gastric cancer screening .' + date_publication: '2019-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWLelast + url_git: '' +GWmodel: + version: 2.4-1 + title: Geographically-Weighted Models + maintainer: Binbin Lu + description: 'Techniques from a particular branch of spatial statistics,termed geographically-weighted + (GW) models. GW models suit situations when data are not described well by some + global model, but where there are spatial regions where a suitably localised calibration + provides a better description. ''GWmodel'' includes functions to calibrate: GW + summary statistics (Brunsdon et al., 2002), + GW principal components analysis (Harris et al., 2011), + GW discriminant analysis (Brunsdon et al., 2007) + and various forms of GW regression (Brunsdon et al., 1996); + some of which are provided in basic and robust (outlier resistant) forms.' + date_publication: '2024-09-07' + bug_reports: '' + url: http://gwr.nuim.ie/ + url_cran: https://CRAN.R-project.org/package=GWmodel + url_git: '' +GWnnegPCA: + version: 0.0.5 + title: |- + Geographically Weighted Non-Negative Principal Components + Analysis + maintainer: Narumasa Tsutsumida + description: |- + Implements a geographically weighted non-negative principal + components analysis, which consists of the fusion of geographically + weighted and sparse non-negative principal components analyses + . + date_publication: '2025-02-05' + bug_reports: https://github.com/naru-T/GWnnegPCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=GWnnegPCA + url_git: https://github.com/naru-T/GWnnegPCA +GWpcor: + version: 0.1.7 + title: Geographically Weighted Partial Correlation Coefficient + maintainer: Narumasa Tsutsumida + description: Implements a geographically weighted partial correlation which is an + extension from gwss() function in the 'GWmodel' package (Percival and Tsutsumida + (2017) ). + date_publication: '2021-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWpcor + url_git: '' +gwpcormapper: + version: 0.1.3 + title: Geographically Weighted Partial Correlation Mapper + maintainer: Joseph Emile Honour Percival + description: An interactive mapping tool for geographically weighted correlation + and partial correlation. Geographically weighted partial correlation coefficients + are calculated following (Percival and Tsutsumida, 2017) + and are described in greater detail in (Tsutsumida et al., 2019) + and (Percival et al., 2021). + date_publication: '2021-12-09' + bug_reports: https://github.com/gwpcor/gwpcormapper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gwpcormapper + url_git: https://github.com/gwpcor/gwpcormapper +gWQS: + version: 3.0.5 + title: Generalized Weighted Quantile Sum Regression + maintainer: Stefano Renzetti + description: Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) + ), a random subset implementation of WQS (Curtin + et al. (2019) ), a repeated holdout validation + WQS (Tanner et al. (2019) ) and a WQS with 2 indices + (Renzetti et al. (2023) ) for continuous, binomial, + multinomial, Poisson, quasi-Poisson and negative binomial outcomes. + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gWQS + url_git: '' +GWRLASSO: + version: 0.1.0 + title: A Hybrid Model for Spatial Prediction Through Local Regression + maintainer: Nobin Chandra Paul + description: |- + It implements a hybrid spatial model for improved spatial prediction by combining the variable selection capability of + LASSO (Least Absolute Shrinkage and Selection Operator) with the Geographically Weighted Regression (GWR) model that + captures the spatially varying relationship efficiently. For method details see, Wheeler, D.C.(2009).. + The developed hybrid model efficiently selects the relevant variables by using LASSO as the first step; these selected variables + are then incorporated into the GWR framework, allowing the estimation of spatially varying regression coefficients at unknown locations + and finally predicting the values of the response variable at unknown test locations while taking into account the spatial heterogeneity of the data. + Integrating the LASSO and GWR models enhances prediction accuracy by considering spatial heterogeneity and capturing the local relationships between + the predictors and the response variable. The developed hybrid spatial model can be useful for spatial modeling, especially in scenarios involving complex + spatial patterns and large datasets with multiple predictor variables. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWRLASSO + url_git: '' +GWRM: + version: 2.1.0.4 + title: Generalized Waring Regression Model for Count Data + maintainer: Silverio Vilchez-Lopez + description: |- + Statistical functions to fit, validate and describe a Generalized + Waring Regression Model (GWRM). + date_publication: '2021-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWRM + url_git: '' +gwrpvr: + version: '1.0' + title: Genome-Wide Regression P-Value (Gwrpv) + maintainer: Michael O'Neill + description: |- + Computes the sample probability value (p-value) + for the estimated coefficient from a standard + genome-wide univariate regression. It computes the exact + finite-sample p-value under the assumption that the measured + phenotype (the dependent variable in the regression) has + a known Bernoulli-normal mixture distribution. + Finite-sample genome-wide regression p-values (Gwrpv) with + a non-normally distributed phenotype (Gregory Connor and + Michael O'Neill, bioRxiv 204727 ). + date_publication: '2017-10-19' + bug_reports: '' + url: https://doi.org/10.1101/204727 + url_cran: https://CRAN.R-project.org/package=gwrpvr + url_git: '' +gwrr: + version: 0.2-2 + title: |- + Fits Geographically Weighted Regression Models with Diagnostic + Tools + maintainer: David Wheeler + description: Fits geographically weighted regression (GWR) models and has tools + to diagnose and remediate collinearity in the GWR models. Also fits geographically + weighted ridge regression (GWRR) and geographically weighted lasso (GWL) models. + See Wheeler (2009) and Wheeler (2007) + for more details. + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gwrr + url_git: '' +GWSDAT: + version: 3.2.1 + title: GroundWater Spatiotemporal Data Analysis Tool (GWSDAT) + maintainer: Wayne Jones + description: |- + Shiny application for the analysis of groundwater + monitoring data, designed to work with simple time-series data for + solute concentration and ground water elevation, but can also plot + non-aqueous phase liquid (NAPL) thickness if required. Also provides + the import of a site basemap in GIS shapefile format. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWSDAT + url_git: '' +GWsignif: + version: '1.2' + title: |- + Estimating Genome-Wide Significance for Whole Genome Sequencing + Studies, Either Single SNP Tests or Region-Based Tests + maintainer: ChangJiang Xu + description: The correlations and linkage disequilibrium between tests can vary + as a function of minor allele frequency thresholds used to filter variants, and + also varies with different choices of test statistic for region-based tests. Appropriate + genome-wide significance thresholds can be estimated empirically through permutation + on only a small proportion of the whole genome. + date_publication: '2016-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GWsignif + url_git: '' +gwzinbr: + version: 0.1.0 + title: |- + Geographically Weighted Zero Inflated Negative Binomial + Regression + maintainer: Jéssica Vasconcelos + description: |- + Fits a geographically weighted regression model + using zero inflated probability distributions. Has the zero + inflated negative binomial distribution (zinb) as default, + but also accepts the zero inflated Poisson (zip), negative + binomial (negbin) and Poisson distributions. Can also fit + the global versions of each regression model. + Da Silva, A. R. & De Sousa, M. D. R. (2023). "Geographically weighted zero-inflated negative binomial regression: A general case for count data", Spatial Statistics . + Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). "Geographically weighted regression: a method for exploring spatial nonstationarity", Geographical Analysis, . + Yau, K. K. W., Wang, K., & Lee, A. H. (2003). "Zero-inflated negative binomial mixed regression modeling of over-dispersed count data with extra zeros", Biometrical Journal, . + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=gwzinbr + url_git: '' +GxEprs: + version: '1.2' + title: Genotype-by-Environment Interaction in Polygenic Score Models + maintainer: Dovini Jayasinghe + description: A novel PRS model is introduced to enhance the prediction accuracy + by utilising GxE effects. This package performs Genome Wide Association Studies + (GWAS) and Genome Wide Environment Interaction Studies (GWEIS) using a discovery + dataset. The package has the ability to obtain polygenic risk scores (PRSs) for + a target sample. Finally it predicts the risk values of each individual in the + target sample. Users have the choice of using existing models (Li et al., 2015) + , (Pandis et al., 2013) , (Peyrot + et al., 2018) and (Song et al., 2022) , + as well as newly proposed models for genomic risk prediction (refer to the URL + for more details). + date_publication: '2024-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GxEprs + url_git: https://github.com/DoviniJ/GxEprs +GxEScanR: + version: 2.0.2 + title: Run GWAS/GWEIS Scans Using Binary Dosage Files + maintainer: John Morrison + description: |- + Tools to run genome-wide association study (GWAS) and + genome-wide by environment interaction study (GWEIS) scans using the genetic + data stored in a binary dosage file. The user provides a data frame with + the subject's covariate data and the information about the binary dosage + file returned by the BinaryDosage::getbdinfo() routine. + date_publication: '2020-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=GxEScanR + url_git: '' +gym: + version: 0.1.0 + title: Provides Access to the OpenAI Gym API + maintainer: Paul Hendricks + description: |- + OpenAI Gym is a open-source Python toolkit for developing and comparing + reinforcement learning algorithms. This is a wrapper for the OpenAI Gym API, + and enables access to an ever-growing variety of environments. + For more details on OpenAI Gym, please see here: . + For more details on the OpenAI Gym API specification, please see here: + . + date_publication: '2016-10-25' + bug_reports: https://github.com/paulhendricks/gym-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gym + url_git: https://github.com/paulhendricks/gym-R +gyro: + version: 1.4.0 + title: Hyperbolic Geometry + maintainer: Stéphane Laurent + description: |- + Hyperbolic geometry in the Minkowski model and the Poincaré + model. The methods are based on the gyrovector space theory developed + by A. A. Ungar that can be found in the book 'Analytic Hyperbolic + Geometry: Mathematical Foundations And Applications' + . The package provides functions to plot + three-dimensional hyperbolic polyhedra and to plot hyperbolic tilings + of the Poincaré disk. + date_publication: '2023-10-30' + bug_reports: https://github.com/stla/gyro/issues + url: '' + url_cran: https://CRAN.R-project.org/package=gyro + url_git: https://github.com/stla/gyro +h0: + version: 1.0.1 + title: |- + A Robust Bayesian Meta-Analysis for Estimating the Hubble + Constant via Time Delay Cosmography + maintainer: Hyungsuk Tak + description: We provide a toolbox to conduct a Bayesian meta-analysis for estimating + the current expansion rate of the Universe, called the Hubble constant H0, via + time delay cosmography. The input data are Fermat potential difference and time + delay estimates. For a robust inference, we assume a Student's t error for these + inputs. Given these inputs, the meta-analysis produces posterior samples of the + model parameters including the Hubble constant via Metropolis-Hastings within + Gibbs. The package provides an option to implement repelling-attracting Metropolis-Hastings + within Gibbs in a case where the parameter space has multiple modes. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=h0 + url_git: '' +h2o: + version: 3.44.0.3 + title: R Interface for the 'H2O' Scalable Machine Learning Platform + maintainer: Tomas Fryda + description: |- + R interface for 'H2O', the scalable open source machine learning + platform that offers parallelized implementations of many supervised and + unsupervised machine learning algorithms such as Generalized Linear + Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, + Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, + Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection, + Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML). + date_publication: '2024-01-11' + bug_reports: https://github.com/h2oai/h2o-3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=h2o + url_git: https://github.com/h2oai/h2o-3 +h2o4gpu: + version: 0.3.3 + title: Interface to 'H2O4GPU' + maintainer: Navdeep Gill + description: Interface to 'H2O4GPU' , a collection + of 'GPU' solvers for machine learning algorithms. + date_publication: '2021-05-17' + bug_reports: https://github.com/h2oai/h2o4gpu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=h2o4gpu + url_git: https://github.com/h2oai/h2o4gpu +h2otools: + version: '0.3' + title: Machine Learning Model Evaluation for 'h2o' Package + maintainer: E. F. Haghish + description: |- + Several functions are provided that simplify using 'h2o' + package. Currently, a function for extracting the AutoML + model parameter is provided, alongside a function for computing + F-Measure statistics at any given threshold. For more information + about 'h2o' package see . + date_publication: '2023-05-04' + bug_reports: https://github.com/haghish/h2otools/issues + url: https://www.sv.uio.no/psi/english/people/academic/haghish/ + url_cran: https://CRAN.R-project.org/package=h2otools + url_git: https://github.com/haghish/h2otools +H2x2Factorial: + version: 2.0.0 + title: Sample Size Calculation in Hierarchical 2x2 Factorial Trials + maintainer: Zizhong Tian + description: Implements the sample size methods for hierarchical 2x2 factorial trials + under two choices of effect estimands and a series of hypothesis tests proposed + in "Sample size calculation in hierarchical 2x2 factorial trials with unequal + cluster sizes" (under review), and provides the table and plot generators for + the sample size estimations. + date_publication: '2021-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=H2x2Factorial + url_git: '' +h3jsr: + version: 1.3.1 + title: Access Uber's H3 Library + maintainer: Lauren O'Brien + description: Provides access to Uber's H3 library for geospatial indexing via its + JavaScript transpile 'h3-js' and 'V8' . + date_publication: '2023-01-21' + bug_reports: '' + url: https://obrl-soil.github.io/h3jsr/ + url_cran: https://CRAN.R-project.org/package=h3jsr + url_git: '' +h3lib: + version: 0.1.4 + title: Exposes the 'Uber' 'H3' Library to R Packages + maintainer: David Cooley + description: |- + 'H3' is a hexagonal hierarchical spatial index developed by 'Uber' . + This package exposes the source code of 'H3' (written in 'C') to routines that are callable through 'R'. + date_publication: '2024-12-12' + bug_reports: https://github.com/symbolixau/h3lib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=h3lib + url_git: https://github.com/symbolixau/h3lib +h3r: + version: 0.1.2 + title: Hexagonal Hierarchical Geospatial Indexing System + maintainer: David Cooley + description: |- + Provides access to Uber's 'H3' geospatial indexing system via 'h3lib' + . 'h3r' is designed to mimic the 'H3' + Application Programming Interface (API) , + so that any function in the API is also available in 'h3r'. + date_publication: '2024-12-13' + bug_reports: https://github.com/symbolixau/h3r/issues + url: https://symbolixau.github.io/h3r/ + url_cran: https://CRAN.R-project.org/package=h3r + url_git: '' +haarfisz: + version: 4.5.4 + title: Software to Perform Haar Fisz Transforms + maintainer: Guy Nason + description: |- + A Haar-Fisz algorithm for Poisson intensity estimation. + Will denoise Poisson distributed sequences where + underlying intensity is not constant. Uses the multiscale + variance-stabilization method called the Haar-Fisz transform. + Contains functions to carry out the forward and inverse + Haar-Fisz transform and denoising on near-Gaussian sequences. + Can also carry out cycle-spinning. + Main reference: Fryzlewicz, P. and Nason, G.P. (2004) + "A Haar-Fisz algorithm for Poisson intensity estimation." + Journal of Computational and Graphical Statistics, + 13, 621-638. . + date_publication: '2023-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=haarfisz + url_git: '' +habCluster: + version: 1.0.5 + title: |- + Detecting Spatial Clustering Based on Connection Cost Between + Grids + maintainer: Qiang Dai + description: |- + Based on landscape connectivity, spatial boundaries were + identified using community detection algorithm at grid level. Methods + using raster as input and the value of each cell of the raster is the + "smoothness" to indicate how easy the cell connecting with neighbor cells. + Details about the 'habCluster' package methods can be found in Zhang et al. + . + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=habCluster + url_git: '' +hablar: + version: 0.3.2 + title: Non-Astonishing Results in R + maintainer: David Sjoberg + description: Simple tools for converting columns to new data types. Intuitive functions + for columns with missing values. + date_publication: '2023-03-12' + bug_reports: https://github.com/davidsjoberg/hablar/issues + url: https://davidsjoberg.github.io/ + url_cran: https://CRAN.R-project.org/package=hablar + url_git: '' +habtools: + version: 1.0.7 + title: Tools and Metrics for 3D Surfaces and Objects + maintainer: Nina Schiettekatte + description: |- + A collection of functions for sampling and simulating 3D surfaces and objects + and estimating metrics like rugosity, fractal dimension, convexity, sphericity, circularity, + second moments of area and volume, and more. + date_publication: '2024-11-15' + bug_reports: https://github.com/jmadinlab/habtools/issues + url: https://jmadinlab.github.io/habtools/ + url_cran: https://CRAN.R-project.org/package=habtools + url_git: '' +HAC: + version: 1.1-1 + title: |- + Estimation, Simulation and Visualization of Hierarchical + Archimedean Copulae (HAC) + maintainer: Gong Chen + description: Package provides the estimation of the structure and the parameters, + sampling methods and structural plots of Hierarchical Archimedean Copulae (HAC). + date_publication: '2024-09-16' + bug_reports: '' + url: https://tu-dresden.de/bu/verkehr/ivw/osv/die-professur/inhaber-in + url_cran: https://CRAN.R-project.org/package=HAC + url_git: '' +hackeRnews: + version: 0.1.0 + title: Wrapper for the 'Official Hacker News' API + maintainer: Ryszard Szymanski + description: |- + Use the API through R. Retrieve + posts, articles and other items in form of convenient R objects. + date_publication: '2019-12-13' + bug_reports: https://github.com/szymanskir/hackeRnews/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hackeRnews + url_git: https://github.com/szymanskir/hackeRnews +hacksaw: + version: 0.0.2 + title: Additional Tools for Splitting and Cleaning Data + maintainer: David Ranzolin + description: |- + Move between data frames and lists more efficiently with precision + splitting via 'dplyr' verbs. Easily cast variables to different data types. Keep + rows with NAs. Shift row values. + date_publication: '2020-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hacksaw + url_git: '' +hacksig: + version: 0.1.2 + title: A Tidy Framework to Hack Gene Expression Signatures + maintainer: Andrea Carenzo + description: |- + A collection of cancer transcriptomics gene signatures as well as a + simple and tidy interface to compute single sample enrichment scores either + with the original procedure or with three alternatives: + the "combined z-score" of Lee et al. (2008) , + the "single sample GSEA" of Barbie et al. (2009) and + the "singscore" of Foroutan et al. (2018) . + The 'get_sig_info()' function can be used to retrieve information about each + signature implemented. + date_publication: '2022-02-17' + bug_reports: https://github.com/Acare/hacksig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hacksig + url_git: https://github.com/Acare/hacksig +HACSim: + version: 1.0.6-1 + title: |- + Iterative Extrapolation of Species' Haplotype Accumulation + Curves for Genetic Diversity Assessment + maintainer: Jarrett D. Phillips + description: 'Performs iterative extrapolation of species'' haplotype accumulation + curves using a nonparametric stochastic (Monte Carlo) optimization method for + assessment of specimen sampling completeness based on the approach of Phillips + et al. (2015) , Phillips et al. (2019) + and Phillips et al. (2020) . ''HACSim'' outputs a number + of useful summary statistics of sampling coverage ("Measures of Sampling Closeness"), + including an estimate of the likely required sample size (along with desired level + confidence intervals) necessary to recover a given number/proportion of observed + unique species'' haplotypes. Any genomic marker can be targeted to assess likely + required specimen sample sizes for genetic diversity assessment. The method is + particularly well-suited to assess sampling sufficiency for DNA barcoding initiatives. + Users can also simulate their own DNA sequences according to various models of + nucleotide substitution. A Shiny app is also available.' + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HACSim + url_git: +HadamardR: + version: 1.0.0 + title: Hadamard Matrix Generation + maintainer: Appavoo Dhandapani + description: Generates Hadamard matrices using different construction methods. For + those who want to generate Hadamard matrix, a generic function, Hadamard_matrix() + is provided. For those who want to generate Hadamard matrix using a particular + method, separate functions are available. See Horadam (2007, ISBN:9780691119212) + Hadamard Matrices and their applications, Princeton University Press for more + information on Hadamard Matrices. + date_publication: '2020-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HadamardR + url_git: '' +HaDeX: + version: 1.2.2 + title: |- + Analysis and Visualisation of Hydrogen/Deuterium Exchange Mass + Spectrometry Data + maintainer: Weronika Puchala + description: |- + Functions for processing, analysis and visualization of Hydrogen Deuterium eXchange monitored by + Mass Spectrometry experiments (HDX-MS) (10.1093/bioinformatics/btaa587). 'HaDeX' introduces a new + standardized and reproducible workflow for the analysis of the HDX-MS data, including novel + uncertainty intervals. Additionally, it covers data exploration, quality control and generation of + publication-quality figures. All functionalities are also available in the in-built 'Shiny' app. + date_publication: '2021-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HaDeX + url_git: '' +HadIBDs: + version: 1.0.1 + title: Incomplete Block Designs using Hadamard Matrix (HadIBDs) + maintainer: Ashutosh Dalal + description: Hadamard matrix based statistical designs are of immense importance + as the resultant designs carry various desirable characterizing properties. Constructing + Partially Balanced Incomplete Block Designs (PBIBds) using Kronecker product of + incidence matrices of Balanced Incomplete Block (BIB) and Partially Balanced Incomplete + Block (PBIB) designs is much evident from literature. Here, we have constructed + Incomplete Block Designs (IBDs) based on Hadamard matrices and Kronecker product + of Hadamard matrices. + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HadIBDs + url_git: '' +hagis: + version: 3.1.12 + title: |- + Analysis of Plant Pathogen Pathotype Complexities, Distributions + and Diversity + maintainer: Adam H. Sparks + description: |- + Analysis of plant pathogen pathotype survey data. Functions + provided calculate distribution of susceptibilities, distribution of + complexities with statistics, pathotype frequency distribution, as + well as diversity indices for pathotypes. This package is meant to be + a direct replacement for Herrmann, Löwer and Schachtel's (1999) + Habgood-Gilmour Spreadsheet, + 'HaGiS', previously used for pathotype analysis. + date_publication: '2024-05-16' + bug_reports: https://github.com/openplantpathology/hagis/issues + url: https://openplantpathology.github.io/hagis/ + url_cran: https://CRAN.R-project.org/package=hagis + url_git: https://github.com/openplantpathology/hagis +hahmmr: + version: 1.0.0 + title: Haplotype-Aware Hidden Markov Model for RNA + maintainer: Teng Gao + description: Haplotype-aware Hidden Markov Model for RNA (HaHMMR) is a method for + detecting copy number variations (CNVs) from bulk RNA-seq data. Additional examples, + documentations, and details on the method are available at . + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hahmmr + url_git: '' +hakaiApi: + version: 1.0.2 + title: Authenticated HTTP Request Client for the 'Hakai' API + maintainer: Taylor Denouden + description: |- + Initializes a class that obtains API credentials and provides + a method to use those credentials to make GET requests to the 'Hakai' + API server. Usage instructions are documented at + . + date_publication: '2022-04-18' + bug_reports: https://github.com/HakaiInstitute/hakai-api-client-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hakaiApi + url_git: https://github.com/HakaiInstitute/hakai-api-client-r +hal9001: + version: 0.4.6 + title: The Scalable Highly Adaptive Lasso + maintainer: Jeremy Coyle + description: |- + A scalable implementation of the highly adaptive lasso algorithm, + including routines for constructing sparse matrices of basis functions of the + observed data, as well as a custom implementation of Lasso regression tailored + to enhance efficiency when the matrix of predictors is composed exclusively of + indicator functions. For ease of use and increased flexibility, the Lasso + fitting routines invoke code from the 'glmnet' package by default. The highly + adaptive lasso was first formulated and described by MJ van der Laan (2017) + , with practical demonstrations of its performance + given by Benkeser and van der Laan (2016) . This + implementation of the highly adaptive lasso algorithm was described by Hejazi, + Coyle, and van der Laan (2020) . + date_publication: '2023-11-14' + bug_reports: https://github.com/tlverse/hal9001/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hal9001 + url_git: https://github.com/tlverse/hal9001 +haldensify: + version: 0.2.3 + title: Highly Adaptive Lasso Conditional Density Estimation + maintainer: Nima Hejazi + description: |- + An algorithm for flexible conditional density estimation based on + application of pooled hazard regression to an artificial repeated measures + dataset constructed by discretizing the support of the outcome variable. To + facilitate non/semi-parametric estimation of the conditional density, the + highly adaptive lasso, a nonparametric regression function shown to reliably + estimate a large class of functions at a fast convergence rate, is utilized. + The pooled hazards data augmentation formulation implemented was first + described by Díaz and van der Laan (2011) . To + complement the conditional density estimation utilities, tools for efficient + nonparametric inverse probability weighted (IPW) estimation of the causal + effects of stochastic shift interventions (modified treatment policies), + directly utilizing the density estimation technique for construction of the + generalized propensity score, are provided. These IPW estimators utilize + undersmoothing (sieve estimation) of the conditional density estimators in + order to achieve the non/semi-parametric efficiency bound. + date_publication: '2022-02-09' + bug_reports: https://github.com/nhejazi/haldensify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=haldensify + url_git: https://github.com/nhejazi/haldensify +halfcircle: + version: 0.1.0 + title: Plot Halfcircle Diagram + maintainer: Sohyun Park + description: There are growing concerns on flow data in diverse fields including + trade, migration, knowledge diffusion, disease spread, and transportation. The + package is an effective visual support to learn the pattern of flow which is called + halfcircle diagram. The flow between two nodes placed on the center line of a + circle is represented using a half circle drawn from the origin to the destination + in a clockwise direction. Through changing the order of nodes, the halfcircle + diagram enables users to examine the complex relationship between bidirectional + flow and each potential determinants. Furthermore, the halfmeancenter function, + which calculates (un) weighted mean center of half circles, makes the comparison + easier. + date_publication: '2018-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=halfcircle + url_git: '' +halfmoon: + version: 0.1.0 + title: Techniques to Build Better Balance + maintainer: Malcolm Barrett + description: |- + Build better balance in causal inference models. 'halfmoon' + helps you assess propensity score models for balance between groups + using metrics like standardized mean differences and visualization + techniques like mirrored histograms. 'halfmoon' supports both + weighting and matching techniques. + date_publication: '2023-05-30' + bug_reports: https://github.com/r-causal/halfmoon/issues + url: https://r-causal.github.io/halfmoon/ + url_cran: https://CRAN.R-project.org/package=halfmoon + url_git: https://github.com/r-causal/halfmoon +halk: + version: 0.0.5 + title: |- + Methods to Create Hierarchical Age Length Keys for Age + Assignment + maintainer: Paul Frater + description: |- + Provides methods for implementing hierarchical age length keys + to estimate fish ages from lengths using data borrowing. Users can create + hierarchical age length keys and use them to assign ages given length. + date_publication: '2023-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=halk + url_git: '' +hamlet: + version: 0.9.6 + title: Hierarchical Optimal Matching and Machine Learning Toolbox + maintainer: Teemu Daniel Laajala + description: Various functions and algorithms are provided here for solving optimal + matching tasks in the context of preclinical cancer studies. Further, various + helper and plotting functions are provided for unsupervised and supervised machine + learning as well as longitudinal mixed-effects modeling of tumor growth response + patterns. + date_publication: '2018-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hamlet + url_git: '' +handcodeR: + version: 0.1.2 + title: Text Annotation App + maintainer: Lukas Isermann + description: Shiny-App that allows to annotate vectors of texts to predefined categories + by hand. + date_publication: '2023-10-24' + bug_reports: https://github.com/liserman/handcodeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=handcodeR + url_git: https://github.com/liserman/handcodeR/ +handlr: + version: 0.3.0 + title: Convert Among Citation Formats + maintainer: Scott Chamberlain + description: |- + Converts among many citation formats, including 'BibTeX', + 'Citeproc', 'Codemeta', 'RDF XML', 'RIS', 'Schema.org', and + 'Citation File Format'. A low level 'R6' class is provided, as well + as stand-alone functions for each citation format for both read + and write. + date_publication: '2020-10-15' + bug_reports: https://github.com/ropensci/handlr/issues + url: https://docs.ropensci.org/handlr/(docs) + url_cran: https://CRAN.R-project.org/package=handlr + url_git: https://github.com/ropensci/handlr(devel) +HandTill2001: + version: 1.0.1 + title: Multiple Class Area under ROC Curve + maintainer: Andreas Dominik Cullmann + description: |- + An S4 implementation of Eq. (3) and Eq. (7) by + David J. Hand and Robert J. Till (2001) . + date_publication: '2020-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HandTill2001 + url_git: https://gitlab.com/fvafrCU/HandTill2001 +handwriter: + version: 3.2.4 + title: Handwriting Analysis in R + maintainer: Stephanie Reinders + description: |- + Perform statistical writership analysis of scanned handwritten documents. + Webpage provided at: . + date_publication: '2025-01-17' + bug_reports: https://github.com/CSAFE-ISU/handwriter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=handwriter + url_git: https://github.com/CSAFE-ISU/handwriter +handwriterApp: + version: 2.0.0 + title: A 'shiny' Application for Handwriting Analysis + maintainer: Stephanie Reinders + description: Perform statistical writership analysis of scanned handwritten documents + with a 'shiny' app for 'handwriter'. + date_publication: '2024-11-13' + bug_reports: https://github.com/CSAFE-ISU/handwriterApp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=handwriterApp + url_git: https://github.com/CSAFE-ISU/handwriterApp +handwriterRF: + version: 1.1.1 + title: Handwriting Analysis with Random Forests + maintainer: Stephanie Reinders + description: Perform forensic handwriting analysis of two scanned handwritten documents. + This package implements the statistical method described by Madeline Johnson and + Danica Ommen (2021) . Similarity measures and a random + forest produce a score-based likelihood ratio that quantifies the strength of + the evidence in favor of the documents being written by the same writer or different + writers. + date_publication: '2025-01-29' + bug_reports: https://github.com/CSAFE-ISU/handwriterRF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=handwriterRF + url_git: https://github.com/CSAFE-ISU/handwriterRF +handyFunctions: + version: 0.1.0 + title: |- + Useful Functions for Handfully Manipulating and Analyzing Data + with Data.frame Format + maintainer: Hongfei Liu + description: |- + Some useful functions for simply manipulating and analyzing data with data.frame format. + It mainly includes the following sections: ReformatDataframe (reformat dataframe with the modifiers), InteractDataframe, and Post-VCF (for downstream analysis for data generated from 'vcftools' Petr et al (2011) + or 'plink' Chang et al (2015) . + date_publication: '2022-08-22' + bug_reports: https://github.com/LuffyLouis/handyFunctions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=handyFunctions + url_git: https://github.com/LuffyLouis/handyFunctions +handyplots: + version: 1.1.3 + title: Handy Plots + maintainer: Jonathan Schwartz + description: Several handy plots for quickly looking at the relationship between + two numeric vectors of equal length. Quickly visualize scatter plots, residual + plots, qq-plots, box plots, confidence intervals, and prediction intervals. + date_publication: '2019-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=handyplots + url_git: '' +hans: + version: '0.1' + title: Haversines are not Slow + maintainer: Alex Hallam + description: |- + The haversine is a function used to calculate the distance between a pair of + latitude and longitude points while accounting for the assumption that the points + are on a spherical globe. This package provides a fast, dataframe compatible, + haversine function. For the first publication on the haversine calculation see + Joseph de Mendoza y Ríos (1795) (In Spanish). + date_publication: '2019-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hans + url_git: '' +HanStat: + version: 0.90.0 + title: Package for Easy Interpretation of Statistical Methods + maintainer: Konrad Krahl + description: A simple and time saving multiple linear regression function (OLS) + with interpretation, optional bootstrapping, effect size calculation and all tested + requirements. + date_publication: '2023-02-13' + bug_reports: https://github.com/KonradKrahl/HanStat + url: '' + url_cran: https://CRAN.R-project.org/package=HanStat + url_git: https://github.com/KonradKrahl/HanStat +hapassoc: + version: 1.2-9 + title: |- + Inference of Trait Associations with SNP Haplotypes and Other + Attributes using the EM Algorithm + maintainer: K. Burkett + description: |- + The following R functions are used for inference of trait + associations with haplotypes and other covariates in + generalized linear models. The functions are developed + primarily for data collected in cohort or cross-sectional + studies. They can accommodate uncertain haplotype phase and + handle missing genotypes at some SNPs. + date_publication: '2022-05-25' + bug_reports: '' + url: https://sfustatgen.github.io/research/hapassoc.html + url_cran: https://CRAN.R-project.org/package=hapassoc + url_git: '' +Hapi: + version: 0.0.3 + title: |- + Inference of Chromosome-Length Haplotypes Using Genomic Data of + Single Gamete Cells + maintainer: Ruidong Li + description: |- + Inference of chromosome-length haplotypes using a few haploid + gametes of an individual. The gamete genotype data may be generated from various platforms + including genotyping arrays and sequencing even with low-coverage. Hapi simply takes + genotype data of known hetSNPs in single gamete cells as input and report the high-resolution + haplotypes as well as confidence of each phased hetSNPs. The package also includes a module + allowing downstream analyses and visualization of identified crossovers in the gametes. + date_publication: '2018-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Hapi + url_git: '' +Haplin: + version: 7.3.2 + title: |- + Analyzing Case-Parent Triad and/or Case-Control Data with SNP + Haplotypes + maintainer: Hakon K. Gjessing + description: 'Performs genetic association analyses of case-parent triad (trio) + data with multiple markers. It can also incorporate complete or incomplete control + triads, for instance independent control children. Estimation is based on haplotypes, + for instance SNP haplotypes, even though phase is not known from the genetic data. + ''Haplin'' estimates relative risk (RR + conf.int.) and p-value associated with + each haplotype. It uses maximum likelihood estimation to make optimal use of data + from triads with missing genotypic data, for instance if some SNPs has not been + typed for some individuals. ''Haplin'' also allows estimation of effects of maternal + haplotypes and parent-of-origin effects, particularly appropriate in perinatal + epidemiology. ''Haplin'' allows special models, like X-inactivation, to be fitted + on the X-chromosome. A GxE analysis allows testing interactions between environment + and all estimated genetic effects. The models were originally described in "Gjessing + HK and Lie RT. Case-parent triads: Estimating single- and double-dose effects + of fetal and maternal disease gene haplotypes. Annals of Human Genetics (2006) + 70, pp. 382-396".' + date_publication: '2024-08-20' + bug_reports: '' + url: https://haplin.bitbucket.io + url_cran: https://CRAN.R-project.org/package=Haplin + url_git: '' +haplo.ccs: + version: 1.3.2 + title: Estimate Haplotype Relative Risks in Case-Control Data + maintainer: Benjamin French + description: Haplotype and covariate relative risks in case-control data are estimated + by weighted logistic regression. Diplotype probabilities, which are estimated + by EM computation with progressive insertion of loci, are utilized as weights. + French et al. (2006) . + date_publication: '2022-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=haplo.ccs + url_git: https://github.com/vubiostat/haplo.ccs +haplo.stats: + version: 1.9.7 + title: |- + Statistical Analysis of Haplotypes with Traits and Covariates + when Linkage Phase is Ambiguous + maintainer: Jason P. Sinnwell + description: 'Routines for the analysis of indirectly measured haplotypes. The statistical + methods assume that all subjects are unrelated and that haplotypes are ambiguous + (due to unknown linkage phase of the genetic markers). The main functions are: + haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed + examples in the vignette.' + date_publication: '2024-09-19' + bug_reports: '' + url: https://analytictools.mayo.edu/research/haplo-stats/ + url_cran: https://CRAN.R-project.org/package=haplo.stats + url_git: '' +HaploCatcher: + version: 1.0.4 + title: A Predictive Haplotyping Package + maintainer: Zachary Winn + description: Used for predicting a genotype’s allelic state at a specific locus/QTL/gene. + This is accomplished by using both a genotype matrix and a separate file which + has categorizations about loci/QTL/genes of interest for the individuals in the + genotypic matrix. A training population can be created from a panel of individuals + who have been previously screened for specific loci/QTL/genes, and this previous + screening could be summarized into a category. Using the categorization of individuals + which have been genotyped using a genome wide marker platform, a model can be + trained to predict what category (haplotype) an individual belongs in based on + their genetic sequence in the region associated with the locus/QTL/gene. These + trained models can then be used to predict the haplotype of a locus/QTL/gene for + individuals which have been genotyped with a genome wide platform yet not genotyped + for the specific locus/QTL/gene. This package is based off work done by Winn et + al 2021. For more specific information on this method, refer to . + date_publication: '2023-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HaploCatcher + url_git: '' +haploR: + version: 4.0.7 + title: Query 'HaploReg', 'RegulomeDB' + maintainer: Ilya Y. Zhbannikov + description: |- + A set of utilities for querying + 'HaploReg' , + 'RegulomeDB' + web-based tools. The package connects to + 'HaploReg', 'RegulomeDB' searches and downloads results, without + opening web pages, directly from R environment. + Results are stored in a data frame that can be directly used in various + kinds of downstream analyses. + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=haploR + url_git: '' +HaploSim: + version: 1.8.4.2 + title: Functions to Simulate Haplotypes + maintainer: Albart Coster + description: |- + Simulate haplotypes through meioses. Allows specification + of population parameters. + date_publication: '2022-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HaploSim + url_git: '' +haplotyper: + version: '0.1' + title: Tool for Clustering Genotypes in Haplotypes + maintainer: Gaston Quero + description: |- + Function to identify haplotypes + within QTL (Quantitative Trait Loci). One haplotype is a combination of SNP + (Single Nucleotide Polymorphisms) within the QTL. This function groups + together all individuals of a population with the same haplotype. + Each group contains individual with the same allele in each SNP, + whether or not missing data. Thus, haplotyper groups individuals, + that to be imputed, have a non-zero probability of having the same alleles + in the entire sequence of SNP's. Moreover, haplotyper calculates such + probability from relative frequencies. + date_publication: '2016-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=haplotyper + url_git: '' +haplotypes: + version: 1.1.3.1 + title: |- + Manipulating DNA Sequences and Estimating Unambiguous Haplotype + Network with Statistical Parsimony + maintainer: Caner Aktas + description: Provides S4 classes and methods for reading and manipulating aligned + DNA sequences, supporting an indel coding methods (only simple indel coding method + is available in the current version), showing base substitutions and indels, calculating + absolute pairwise distances between DNA sequences, and collapses identical DNA + sequences into haplotypes or inferring haplotypes using user provided absolute + pairwise character difference matrix. This package also includes S4 classes and + methods for estimating genealogical relationships among haplotypes using statistical + parsimony and plotting parsimony networks. + date_publication: '2023-07-15' + bug_reports: '' + url: https://biolsystematics.wordpress.com/r/ + url_cran: https://CRAN.R-project.org/package=haplotypes + url_git: '' +happign: + version: 0.3.2 + title: R Interface to 'IGN' Web Services + maintainer: Paul Carteron + description: |- + Automatic open data acquisition from resources of IGN + ('Institut National de Information Geographique et forestiere') + (). Available datasets include various types of + raster and vector data, such as digital elevation models, state + borders, spatial databases, cadastral parcels, and more. There also + access to point clouds data ('LIDAR') and specifics API + (). + date_publication: '2025-01-24' + bug_reports: https://github.com/paul-carteron/happign/issues + url: https://paul-carteron.github.io/happign/ + url_cran: https://CRAN.R-project.org/package=happign + url_git: https://github.com/paul-carteron +happytime: + version: 0.1.0 + title: Two Games to Relieve the Boredom + maintainer: Xiuwen Wang + description: There are two interesting games in this package, one is 2048 games(for + windows), using up and down to control the direction until there is a 2048 figure. + And the other is 'what to eat today',preparing for people who choose difficulties, + including most of the delicious Cantonese cuisine. + date_publication: '2018-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=happytime + url_git: '' +hapsim: + version: '0.31' + title: Haplotype Data Simulation + maintainer: Apostolos Dimitromanolakis + description: |- + Package for haplotype-based genotype simulations. Haplotypes are + generated such that their allele frequencies and linkage + disequilibrium coefficients match those estimated from an input + data set. + date_publication: '2017-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hapsim + url_git: '' +harbinger: + version: 1.1.707 + title: A Unified Time Series Event Detection Framework + maintainer: Eduardo Ogasawara + description: By analyzing time series, it is possible to observe significant changes + in the behavior of observations that frequently characterize events. Events present + themselves as anomalies, change points, or motifs. In the literature, there are + several methods for detecting events. However, searching for a suitable time series + method is a complex task, especially considering that the nature of events is + often unknown. This work presents Harbinger, a framework for integrating and analyzing + event detection methods. Harbinger contains several state-of-the-art methods described + in Salles et al. (2020) . + date_publication: '2024-12-03' + bug_reports: '' + url: https://cefet-rj-dal.github.io/harbinger/ + url_cran: https://CRAN.R-project.org/package=harbinger + url_git: https://github.com/cefet-rj-dal/harbinger +hardhat: + version: 1.4.1 + title: Construct Modeling Packages + maintainer: Hannah Frick + description: |- + Building modeling packages is hard. A large amount of effort + generally goes into providing an implementation for a new method that + is efficient, fast, and correct, but often less emphasis is put on the + user interface. A good interface requires specialized knowledge about + S3 methods and formulas, which the average package developer might not + have. The goal of 'hardhat' is to reduce the burden around building + new modeling packages by providing functionality for preprocessing, + predicting, and validating input. + date_publication: '2025-01-31' + bug_reports: https://github.com/tidymodels/hardhat/issues + url: https://hardhat.tidymodels.org + url_cran: https://CRAN.R-project.org/package=hardhat + url_git: https://github.com/tidymodels/hardhat +HardyWeinberg: + version: 1.7.8 + title: Statistical Tests and Graphics for Hardy-Weinberg Equilibrium + maintainer: Jan Graffelman + description: 'Contains tools for exploring Hardy-Weinberg equilibrium (Hardy, 1908; Weinberg, + 1908) for bi and multi-allelic genetic marker data. All classical tests (chi-square, + exact, likelihood-ratio and permutation tests) with bi-allelic variants are included + in the package, as well as functions for power computation and for the simulation + of marker data under equilibrium and disequilibrium. Routines for dealing with + markers on the X-chromosome are included (Graffelman & Weir, 2016) , + including Bayesian procedures. Some exact and permutation procedures also work + with multi-allelic variants. Special test procedures that jointly address Hardy-Weinberg + equilibrium and equality of allele frequencies in both sexes are supplied, for + the bi and multi-allelic case. Functions for testing equilibrium in the presence + of missing data by using multiple imputation are also provided. Implements several + graphics for exploring the equilibrium status of a large set of bi-allelic markers: + ternary plots with acceptance regions, log-ratio plots and Q-Q plots. The functionality + of the package is explained in detail in a related JSS paper .' + date_publication: '2024-04-06' + bug_reports: '' + url: http://www-eio.upc.edu/~jan/ + url_cran: https://CRAN.R-project.org/package=HardyWeinberg + url_git: '' +harmonicmeanp: + version: 3.0.1 + title: |- + Harmonic Mean p-Values and Model Averaging by Mean Maximum + Likelihood + maintainer: Daniel Wilson + description: The harmonic mean p-value (HMP) test combines p-values and corrects + for multiple testing while controlling the strong-sense family-wise error rate. + It is more powerful than common alternatives including Bonferroni and Simes procedures + when combining large proportions of all the p-values, at the cost of slightly + lower power when combining small proportions of all the p-values. It is more stringent + than controlling the false discovery rate, and possesses theoretical robustness + to positive correlations between tests and unequal weights. It is a multi-level + test in the sense that a superset of one or more significant tests is certain + to be significant and conversely when the superset is non-significant, the constituent + tests are certain to be non-significant. It is based on MAMML (model averaging + by mean maximum likelihood), a frequentist analogue to Bayesian model averaging, + and is theoretically grounded in generalized central limit theorem. For detailed + examples type vignette("harmonicmeanp") after installation. Version 3.0 addresses + errors in versions 1.0 and 2.0 that led function p.hmp to control the familywise + error rate only in the weak sense, rather than the strong sense as intended. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=harmonicmeanp + url_git: '' +harmonizer: + version: 0.3.2 + title: Harmonizing CN8 and PC8 Product Codes + maintainer: Christoph Baumgartner + description: |- + Several functions are provided to harmonize CN8 (Combined Nomenclature + 8 digits) and PC8 (Production Communautaire 8 digits) product codes over + time and the classification systems HS6 and BEC. Harmonization of CN8 + codes are possible by default from 1995 to 2022 and of PC8 from 2001 to + 2021, respectively. + date_publication: '2023-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=harmonizer + url_git: '' +harmony: + version: 1.2.3 + title: Fast, Sensitive, and Accurate Integration of Single Cell Data + maintainer: Ilya Korsunsky + description: Implementation of the Harmony algorithm for single cell integration, + described in Korsunsky et al . Package includes + a standalone Harmony function and interfaces to external frameworks. + date_publication: '2024-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=harmony + url_git: https://github.com/immunogenomics/harmony +harmonydata: + version: 0.1.1 + title: R Library for 'Harmony' + maintainer: Omar Hassoun + description: '''Harmony'' is a tool using AI which allows you to compare items from + questionnaires and identify similar content. You can try ''Harmony'' at + and you can read our blog at or at . + Documentation at .' + date_publication: '2023-10-19' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=harmonydata + url_git: '' +harrietr: + version: 0.2.3 + title: Wrangle Phylogenetic Distance Matrices and Other Utilities + maintainer: Anders Gonçalves da Silva + description: |- + Harriet was Charles Darwin's pet tortoise (possibly). 'harrietr' + implements some function to manipulate distance matrices and phylogenetic trees + to make it easier to plot with 'ggplot2' and to manipulate using 'tidyverse' + tools. + date_publication: '2017-12-01' + bug_reports: https://github.com/andersgs/harrietr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=harrietr + url_git: https://github.com/andersgs/harrietr +harrypotter: + version: 2.1.1 + title: Palettes Generated from All "Harry Potter" Movies + maintainer: Alejandro Jimenez Rico + description: Implementation of characteristic palettes inspired in the Wizarding + World and the Harry Potter movie franchise. + date_publication: '2020-03-05' + bug_reports: https://github.com/aljrico/harrypotter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=harrypotter + url_git: https://github.com/aljrico/harrypotter +Harvest.Tree: + version: '1.1' + title: Harvest the Classification Tree + maintainer: Bingyuan Liu + description: Aimed at applying the Harvest classification tree algorithm, modified + algorithm of classic classification tree.The harvested tree has advantage of deleting + redundant rules in trees, leading to a simplify and more efficient tree model.It + was firstly used in drug discovery field, but it also performs well in other kinds + of data, especially when the region of a class is disconnected. This package also + improves the basic harvest classification tree algorithm by extending the field + of data of algorithm to both continuous and categorical variables. To learn more + about the harvest classification tree algorithm, you can go to http://www.stat.ubc.ca/Research/TechReports/techreports/220.pdf + for more information. + date_publication: '2015-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Harvest.Tree + url_git: '' +hash: + version: 2.2.6.3 + title: |- + Full Featured Implementation of Hash Tables/Associative + Arrays/Dictionaries + maintainer: John Hughes + description: Implements a data structure similar to hashes in Perl and dictionaries + in Python but with a purposefully R flavor. For objects of appreciable size, access + using hashes outperforms native named lists and vectors. + date_publication: '2023-08-19' + bug_reports: '' + url: http://www.johnhughes.org + url_cran: https://CRAN.R-project.org/package=hash + url_git: '' +hashids: + version: 0.9.0 + title: Generate Short Unique YouTube-Like IDs (Hashes) from Integers + maintainer: Alex Shum + description: 'An R port of the hashids library. hashids generates YouTube-like + hashes from integers or vector of integers. Hashes generated from integers are + relatively short, unique and non-seqential. hashids can be used to generate unique + ids for URLs and hide database row numbers from the user. By default hashids + will avoid generating common English cursewords by preventing certain letters + being next to each other. hashids are not one-way: it is easy to encode an integer + to a hashid and decode a hashid back into an integer.' + date_publication: '2015-09-11' + bug_reports: https://github.com/ALShum/hashids-r/issues + url: http://hashids.org + url_cran: https://CRAN.R-project.org/package=hashids + url_git: https://github.com/ALShum/hashids-r/ +hashr: + version: 0.1.4 + title: Hash R Objects to Integers Fast + maintainer: Mark van der Loo + description: |- + Apply an adaptation of the SuperFastHash algorithm to any R + object. Hash whole R objects or, for vectors or lists, hash R objects to obtain + a set of hash values that is stored in a structure equivalent to the input. See + for a description of the hash + algorithm. + date_publication: '2021-09-02' + bug_reports: https://github.com/markvanderloo/hashr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hashr + url_git: https://github.com/markvanderloo/hashr +Hassani.SACF: + version: '2.0' + title: Computing Lower Bound of Ljung-Box Test + maintainer: Leila Marvian Mashhad + description: |- + The Ljung-Box test is one of the most important tests for time series diagnostics and model selection. + The Hassani SACF (Sum of the Sample Autocorrelation Function) Theorem , however, indicates that the sum of sample autocorrelation function is always fix for + any stationary time series with arbitrary length. This package confirms for sensitivity of the Ljung-Box test to + the number of lags involved in the test and therefore it should be used with extra caution. + The Hassani SACF Theorem has been described in : Hassani, Yeganegi and M. R. (2019) . + date_publication: '2023-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Hassani.SACF + url_git: '' +Hassani.Silva: + version: '1.0' + title: |- + A Test for Comparing the Predictive Accuracy of Two Sets of + Forecasts + maintainer: Leila Marvian Mashhad + description: |- + A non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) + test, referred to as the KS Predictive Accuracy (KSPA) test. The KSPA test is able to serve + two distinct purposes. Initially, the test seeks to determine whether there exists a + statistically significant difference between the distribution of forecast errors, and + secondly it exploits the principles of stochastic dominance to determine whether the + forecasts with the lower error also reports a stochastically smaller error than forecasts + from a competing model, and thereby enables distinguishing between the predictive accuracy + of forecasts. KSPA test has been described in : Hassani and Silva (2015) . + date_publication: '2023-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Hassani.Silva + url_git: '' +haven: + version: 2.5.4 + title: Import and Export 'SPSS', 'Stata' and 'SAS' Files + maintainer: Hadley Wickham + description: |- + Import foreign statistical formats into R via the embedded + 'ReadStat' C library, . + date_publication: '2023-11-30' + bug_reports: https://github.com/tidyverse/haven/issues + url: https://haven.tidyverse.org + url_cran: https://CRAN.R-project.org/package=haven + url_git: https://github.com/tidyverse/haven +hawkes: + version: 0.0-4 + title: Hawkes process simulation and calibration toolkit + maintainer: Riadh Zaatour + description: The package allows to simulate Hawkes process both in univariate and + multivariate settings. It gives functions to compute different moments of the + number of jumps of the process on a given interval, such as mean, variance or + autocorrelation of process jumps on time intervals separated by a lag. + date_publication: '2014-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hawkes + url_git: '' +hawkesbow: + version: 1.0.3 + title: Estimation of Hawkes Processes from Binned Observations + maintainer: Felix Cheysson + description: 'Implements an estimation method for Hawkes processes when count data + are only observed in discrete time, using a spectral approach derived from the + Bartlett spectrum, see Cheysson and Lang (2020) . Some general + use functions for Hawkes processes are also included: simulation of (in)homogeneous + Hawkes process, maximum likelihood estimation, residual analysis, etc.' + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hawkesbow + url_git: '' +HazardDiff: + version: 0.1.0 + title: Conditional Treatment Effect for Competing Risks + maintainer: Denise Rava + description: The conditional treatment effect for competing risks data in observational + studies is estimated. While it is described as a constant difference between the + hazard functions given the covariates, we do not assume specific functional forms + for the covariates. Rava, D. and Xu, R. (2021) . + date_publication: '2021-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HazardDiff + url_git: '' +hazer: + version: 1.1.1 + title: Identifying Foggy and Cloudy Images by Quantifying Haziness + maintainer: Bijan Seyednasrollah + description: Provides a set of functions to estimate haziness of an image based + on RGB bands. It returns a haze factor, varying from 0 to 1, a metric for fogginess + and cloudiness. The package also presents additional functions to estimate brightness, + darkness and contrast rasters of the RGB image. This package can be used for several + applications such as inference of weather quality data and performing environmental + studies from interpreting digital images. + date_publication: '2018-11-01' + bug_reports: https://github.com/bnasr/hazer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hazer + url_git: https://github.com/bnasr/hazer/ +hbal: + version: 1.2.12 + title: Hierarchically Regularized Entropy Balancing + maintainer: Yiqing Xu + description: Implements hierarchically regularized entropy balancing proposed by + Xu and Yang (2022) . The method adjusts the covariate + distributions of the control group to match those of the treatment group. 'hbal' + automatically expands the covariate space to include higher order terms and uses + cross-validation to select variable penalties for the balancing conditions. + date_publication: '2024-01-10' + bug_reports: '' + url: https://yiqingxu.org/packages/hbal/ + url_cran: https://CRAN.R-project.org/package=hbal + url_git: '' +hbamr: + version: 2.4.1 + title: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan' + maintainer: Jørgen Bølstad + description: |- + Perform hierarchical Bayesian Aldrich-McKelvey scaling using Hamiltonian Monte + Carlo via 'Stan'. Aldrich-McKelvey ('AM') scaling is a method for estimating the ideological + positions of survey respondents and political actors on a common scale using positional survey + data. The hierarchical versions of the Bayesian 'AM' model included in this package outperform + other versions both in terms of yielding meaningful posterior distributions for respondent + positions and in terms of recovering true respondent positions in simulations. The package + contains functions for preparing data, fitting models, extracting estimates, plotting key + results, and comparing models using cross-validation. The original version of the default + model is described in Bølstad (2024) . + date_publication: '2025-02-13' + bug_reports: https://github.com/jbolstad/hbamr/issues + url: https://jbolstad.github.io/hbamr/ + url_cran: https://CRAN.R-project.org/package=hbamr + url_git: '' +hBayesDM: + version: 1.2.1 + title: Hierarchical Bayesian Modeling of Decision-Making Tasks + maintainer: Woo-Young Ahn + description: |2- + + Fit an array of decision-making tasks with computational models in + a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis of + various computational models with a single line of coding + (Ahn et al., 2017) . + date_publication: '2022-09-23' + bug_reports: https://github.com/CCS-Lab/hBayesDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hBayesDM + url_git: https://github.com/CCS-Lab/hBayesDM +hbbr: + version: 1.1.2 + title: |- + Hierarchical Bayesian Benefit-Risk Assessment Using Discrete + Choice Experiment + maintainer: Saurabh Mukhopadhyay + description: Implements assessment of benefit-risk balance using Bayesian Discrete + Choice Experiment. For more details see the article by Mukhopadhyay et al. (2019) + . + date_publication: '2019-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hbbr + url_git: '' +hbim: + version: 1.1.2 + title: Hill/Bliss Independence Model for Combination Vaccines + maintainer: Michael P. Fay + description: Calculate expected relative risk and proportion protected assuming + normally distributed log10 transformed antibody dose for a several component vaccine. + Uses Hill models for each component which are combined under Bliss independence. + See Saul and Fay, 2007 . + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hbim + url_git: '' +hbmem: + version: 0.3-4 + title: Hierarchical Bayesian Analysis of Recognition Memory + maintainer: Mike Pratte + description: |- + Contains functions for fitting hierarchical versions of + EVSD, UVSD, DPSD, DPSD with d' restricted to be positive, and + our gamma signal detection model to recognition memory + confidence-ratings data. + date_publication: '2023-08-22' + bug_reports: '' + url: https://pcn.psychology.msstate.edu/ + url_cran: https://CRAN.R-project.org/package=hbmem + url_git: '' +hbsae: + version: '1.2' + title: Hierarchical Bayesian Small Area Estimation + maintainer: Harm Jan Boonstra + description: |- + Functions to compute small area estimates based on a basic area or + unit-level model. The model is fit using restricted maximum likelihood, or + in a hierarchical Bayesian way. In the latter case numerical integration is + used to average over the posterior density for the between-area variance. + The output includes the model fit, small area estimates and corresponding + mean squared errors, as well as some model selection measures. Additional functions + provide means to compute aggregate estimates and mean squared errors, to minimally + adjust the small area estimates to benchmarks at a higher aggregation + level, and to graphically compare different sets of small area estimates. + date_publication: '2022-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hbsae + url_git: '' +HBSTM: + version: 1.0.2 + title: |- + Hierarchical Bayesian Space-Time Models for Gaussian Space-Time + Data + maintainer: Alberto Lopez Moreno + description: Fits Hierarchical Bayesian space-Time models for Gaussian data. Furthermore, + its functions have been implemented for analysing the fitting qualities of those + models. + date_publication: '2022-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HBSTM + url_git: '' +HBV.IANIGLA: + version: 0.2.6 + title: Modular Hydrological Model + maintainer: Ezequiel Toum + description: The HBV hydrological model (Bergström, S. and Lindström, G., (2015) + ) has been split in modules to allow the user to build + his/her own model. This version was developed by the author in IANIGLA-CONICET + (Instituto Argentino de Nivologia, Glaciologia y Ciencias Ambientales - Consejo + Nacional de Investigaciones Cientificas y Tecnicas) for hydroclimatic studies + in the Andes. HBV.IANIGLA incorporates routines for clean and debris covered glacier + melt simulations. + date_publication: '2022-11-23' + bug_reports: https://gitlab.com/ezetoum27/hbv.ianigla/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HBV.IANIGLA + url_git: https://gitlab.com/ezetoum27/hbv.ianigla +hcandersenr: + version: 0.2.0 + title: H.C. Andersens Fairy Tales + maintainer: Emil Hvitfeldt + description: |- + Texts for H.C. Andersens fairy tales, ready for + text analysis. Fairy tales in German, Danish, English, Spanish and + French. + date_publication: '2019-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hcandersenr + url_git: https://github.com/EmilHvitfeldt/hcandersenr +hcci: + version: 1.2.0 + title: Interval Estimation of Linear Models with Heteroskedasticity + maintainer: Pedro Rafael Diniz Marinho + description: 'Calculates the interval estimates for the parameters of linear models + with heteroscedastic regression using bootstrap - (Wild Bootstrap) and double + bootstrap-t (Wild Bootstrap). It is also possible to calculate confidence intervals + using the percentile bootstrap and percentile bootstrap double. The package can + calculate consistent estimates of the covariance matrix of the parameters of linear + regression models with heteroscedasticity of unknown form. The package also provides + a function to consistently calculate the covariance matrix of the parameters of + linear models with heteroscedasticity of unknown form. The bootstrap methods exported + by the package are based on the master''s thesis of the first author, available + at . + The hcci package in previous versions was cited in the book VINOD, Hrishikesh + D. Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative + Methods and R Software. 2022, p. 441, ISBN 978-981-125-617-2 (hardcover). The + simple bootstrap schemes are based on the works of Cribari-Neto F and Lima M. + G. (2009) , while the double bootstrap schemes + for the parameters that index the linear models with heteroscedasticity of unknown + form are based on the works of Beran (1987) . The use of + bootstrap for the calculation of interval estimates in regression models with + heteroscedasticity of unknown form from a weighting of the residuals was proposed + by Wu (1986) . This bootstrap scheme is known as weighted + or wild bootstrap.' + date_publication: '2025-01-21' + bug_reports: https://github.com/prdm0/hcci/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hcci + url_git: https://github.com/prdm0/hcci +HCD: + version: '1.0' + title: Hierarchical Community Detection by Recursive Partitioning + maintainer: Tianxi Li + description: Hierarchical community detection on networks by a recursive spectral + partitioning strategy, which is shown to be effective and efficient in Li, Lei, + Bhattacharyya, Sarkar, Bickel, and Levina (2018) . The package + also includes a data generating function for a binary tree stochastic block model, + a special case of stochastic block model that admits hierarchy between communities. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HCD + url_git: '' +hce: + version: 0.6.7 + title: Design and Analysis of Hierarchical Composite Endpoints + maintainer: Samvel B. Gasparyan + description: 'Simulate and analyze hierarchical composite endpoints. Win odds is + the main analysis method, but other win statistics (win ratio, net benefit) are + also implemented, provided there is no censoring. See Gasparyan SB et al (2023) + "Hierarchical Composite Endpoints in COVID-19: The DARE-19 Trial." Case Studies + in Innovative Clinical Trials, 95-148. Chapman; Hall/CRC. .' + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hce + url_git: '' +hchinamap: + version: 0.1.0 + title: Mapping China and Its Provinces + maintainer: Zhenxing Cheng + description: By binding R functions and the 'Highmaps' + chart library, 'hchinamap' package provides a simple way to map China and its + provinces. The map of China drawn by this package contains complete Chinese territory, + especially the Nine-dotted line, South Tibet, Hong Kong, Macao and Taiwan. + date_publication: '2019-08-23' + bug_reports: https://github.com/czxa/hchinamap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hchinamap + url_git: https://github.com/czxa/hchinamap +hcidata: + version: 0.1.0 + title: HCI Datasets + maintainer: Henning Pohl + description: |- + A collection of datasets of human-computer interaction (HCI) experiments. + Each dataset is from an HCI paper, with all fields described and the original publication + linked. All paper authors of included data have consented to the inclusion of their data + in this package. The datasets include data from a range of HCI studies, such as pointing + tasks, user experience ratings, and steering tasks. + Dataset sources: + Bergström et al. (2022) ; + Dalsgaard et al. (2021) ; + Larsen et al. (2019) ; + Lilija et al. (2019) ; + Pohl and Murray-Smith (2013) ; + Pohl and Mottelson (2022) . + date_publication: '2022-12-05' + bug_reports: https://github.com/henningpohl/hcidata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hcidata + url_git: https://github.com/henningpohl/hcidata +hclust1d: + version: 0.1.1 + title: Hierarchical Clustering of Univariate (1d) Data + maintainer: Szymon Nowakowski + description: Univariate agglomerative hierarchical clustering with a comprehensive + list of choices of a linkage function in O(n*log n) time. The better algorithmic + time complexity is paired with an efficient 'C++' implementation. + date_publication: '2023-08-07' + bug_reports: https://github.com/SzymonNowakowski/hclust1d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hclust1d + url_git: https://github.com/SzymonNowakowski/hclust1d +hclusteasy: + version: 0.1.0 + title: Determining Hierarchical Clustering Easily + maintainer: Henrique Andrade + description: |- + Facilitates hierarchical clustering analysis with functions + to read data in 'txt', 'xlsx', and 'xls' formats, apply normalization + techniques to the dataset, perform hierarchical clustering and + construct scatter plot from principal component analysis to evaluate + the groups obtained. + date_publication: '2024-06-21' + bug_reports: https://github.com/tsukubai/hclusteasy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hclusteasy + url_git: https://github.com/tsukubai/hclusteasy +HCmodelSets: + version: 1.1.3 + title: |- + Regression with a Large Number of Potential Explanatory + Variables + maintainer: H. Battey + description: Software for performing the reduction, exploratory and model selection + phases of the procedure proposed by Cox, D.R. and Battey, H.S. (2017) + for sparse regression when the number of potential explanatory variables far exceeds + the sample size. The software supports linear regression, likelihood-based fitting + of generalized linear regression models and the proportional hazards model fitted + by partial likelihood. + date_publication: '2023-03-15' + bug_reports: https://github.com/hhhelfer/HCmodelSets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HCmodelSets + url_git: '' +HCR: + version: 0.1.1 + title: |- + Causal Discovery from Discrete Data using Hidden Compact + Representation + maintainer: Jie Qiao + description: |- + This code provides a method to fit the hidden compact representation model as well as to identify the causal direction on discrete data. + We implement an effective solution to recover the above hidden compact representation under the likelihood framework. + Please see the Causal Discovery from Discrete Data using Hidden Compact Representation from NIPS 2018 by Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang and Zhifeng Hao (2018) for a description of some of our methods. + date_publication: '2018-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HCR + url_git: '' +HCT: + version: 0.1.3 + title: |- + Calculates Significance Criteria and Power for a Single Arm + Trial + maintainer: David A. Schoenfeld + description: |- + Given a database of previous treatment/placebo estimates, their standard errors and sample sizes, + the program calculates a significance criteria and power estimate that takes into account the among + trial variation. + date_publication: '2022-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HCT + url_git: '' +HCTDesign: + version: 0.7.2 + title: |- + Group Sequential Design for Historical Control Trial with + Survival Outcome + maintainer: Tushar Patni + description: It provides functions to design historical controlled trials with survival + outcome by group sequential method. The options for interim look boundaries are + efficacy only, efficacy & futility or futility only. It also provides the function + to monitor the trial for any unplanned look. The package is based on Jianrong + Wu, Xiaoping Xiong (2016) and Jianrong Wu, Yimei Li (2020) + . + date_publication: '2022-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HCTDesign + url_git: '' +HCTR: + version: 0.1.1 + title: Higher Criticism Tuned Regression + maintainer: Tao Jiang + description: |- + A novel searching scheme for tuning parameter in high-dimensional + penalized regression. We propose a new estimate of the regularization + parameter based on an estimated lower bound of the proportion of false + null hypotheses (Meinshausen and Rice (2006) ). + The bound is estimated by applying the empirical null distribution of the higher + criticism statistic, a second-level significance testing, which is constructed + by dependent p-values from a multi-split regression and aggregation method + (Jeng, Zhang and Tzeng (2019) ). An estimate + of tuning parameter in penalized regression is decided corresponding to the lower + bound of the proportion of false null hypotheses. Different penalized + regression methods are provided in the multi-split algorithm. + date_publication: '2019-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HCTR + url_git: '' +hctrial: + version: 0.1.0 + title: Using Historical Controls for Designing Phase II Clinical Trials + maintainer: Dominic Edelmann + description: Provides functions for designing phase II clinical trials adjusting + for the heterogeneity of the population using known subgroups or historical controls. + date_publication: '2018-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hctrial + url_git: '' +hda: + version: 0.2-14 + title: Heteroscedastic Discriminant Analysis + maintainer: Gero Szepannek + description: Functions to perform dimensionality reduction for classification if + the covariance matrices of the classes are unequal. + date_publication: '2016-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hda + url_git: '' +HDANOVA: + version: 0.8.2 + title: High-Dimensional Analysis of Variance + maintainer: Kristian Hovde Liland + description: |- + Functions and datasets to support Smilde, Marini, Westerhuis and Liland (2025, ISBN: 978-1-394-21121-0) + "Analysis of Variance for High-Dimensional Data - Applications in Life, Food and Chemical Sciences". + This implements and imports a collection of methods for HD-ANOVA data analysis with common interfaces, result- and plotting + functions, multiple real data sets and four vignettes covering a range different applications. + date_publication: '2025-01-21' + bug_reports: https://github.com/khliland/HDANOVA/issues/ + url: https://khliland.github.io/HDANOVA/ + url_cran: https://CRAN.R-project.org/package=HDANOVA + url_git: https://github.com/khliland/HDANOVA/ +hdar: + version: 1.0.4 + title: '''REST'' API Client for Accessing Data on ''WEkEO HDA V2''' + maintainer: Matteo Mattiuzzi + description: |- + Provides seamless access to the WEkEO Harmonised Data Access (HDA) API, enabling + users to query, download, and process data efficiently from the HDA platform. + With 'hdar', researchers and data scientists can integrate the extensive HDA + datasets into their R workflows, enhancing their data analysis capabilities. + Comprehensive information on the API functionality and usage is available + at . + date_publication: '2024-11-19' + bug_reports: https://github.com/eea/hdar/issues + url: https://www.wekeo.eu/ + url_cran: https://CRAN.R-project.org/package=hdar + url_git: '' +hdbayes: + version: 0.1.1 + title: |- + Bayesian Analysis of Generalized Linear Models with Historical + Data + maintainer: Ethan M. Alt + description: |- + User-friendly functions for leveraging (multiple) historical data set(s) for generalized + linear models. The package contains functions for sampling from the posterior distribution of a + generalized linear model using the prior induced by the Bayesian hierarchical model, power prior + by Ibrahim and Chen (2000) , normalized power prior by Duan et al. (2006) + , normalized asymptotic power prior by Ibrahim et al. (2015) , + commensurate prior by Hobbs et al. (2011) , robust meta-analytic-predictive + prior by Schmidli et al. (2014) , the latent exchangeability prior by Alt et al. (2023) + , and a normal (or half-normal) prior. Functions for computing the marginal + log-likelihood under each of the implemented priors are also included. The package compiles all + the 'CmdStan' models once during installation using the 'instantiate' package. + date_publication: '2024-08-22' + bug_reports: https://github.com/ethan-alt/hdbayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hdbayes + url_git: https://github.com/ethan-alt/hdbayes +hdbcp: + version: 1.0.0 + title: Bayesian Change Point Detection for High-Dimensional Data + maintainer: JaeHoon Kim + description: |- + Functions implementing change point detection methods using the maximum pairwise Bayes factor approach. + Additionally, the package includes tools for generating simulated datasets for comparing and evaluating change point detection techniques. + date_publication: '2024-11-19' + bug_reports: https://github.com/JaeHoonKim98/hdbcp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hdbcp + url_git: https://github.com/JaeHoonKim98/hdbcp +hdbinseg: + version: 1.0.2 + title: |- + Change-Point Analysis of High-Dimensional Time Series via Binary + Segmentation + maintainer: Haeran Cho + description: Binary segmentation methods for detecting and estimating multiple change-points + in the mean or second-order structure of high-dimensional time series as described + in Cho and Fryzlewicz (2014) and Cho (2016) . + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdbinseg + url_git: '' +hdbm: + version: 0.9.0 + title: High Dimensional Bayesian Mediation Analysis + maintainer: Alexander Rix + description: |- + Perform mediation analysis in the presence of high-dimensional + mediators based on the potential outcome framework. High dimensional + Bayesian mediation (HDBM), developed by Song et al (2018) + , relies on two Bayesian sparse linear mixed models to + simultaneously analyze a relatively large number of mediators for a + continuous exposure and outcome assuming a small number of mediators are + truly active. This sparsity assumption also allows the extension of + univariate mediator analysis by casting the identification of active + mediators as a variable selection problem and applying Bayesian methods + with continuous shrinkage priors on the effects. + date_publication: '2019-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdbm + url_git: '' +hdbma: + version: '1.0' + title: Bayesian Mediation Analysis with High-Dimensional Data + maintainer: Qingzhao Yu + description: Mediation analysis is used to identify and quantify intermediate effects + from factors that intervene the observed relationship between an exposure/predicting + variable and an outcome. We use a Bayesian adaptive lasso method to take care + of the hierarchical structures and high dimensional exposures or mediators. + date_publication: '2023-12-15' + bug_reports: '' + url: https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html + url_cran: https://CRAN.R-project.org/package=hdbma + url_git: '' +HDBRR: + version: 1.1.4 + title: High Dimensional Bayesian Ridge Regression without MCMC + maintainer: Blanca Monroy-Castillo Developer + description: Ridge regression provide biased estimators of the regression parameters + with lower variance. The HDBRR ("High Dimensional Bayesian Ridge Regression") + function fits Bayesian Ridge regression without MCMC, this one uses the SVD or + QR decomposition for the posterior computation. + date_publication: '2022-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDBRR + url_git: '' +hdcate: + version: 0.1.0 + title: |- + Estimation of Conditional Average Treatment Effects with + High-Dimensional Data + maintainer: Qingliang Fan + description: 'A two-step double-robust method to estimate the conditional average + treatment effects (CATE) with potentially high-dimensional covariate(s). In the + first stage, the nuisance functions necessary for identifying CATE are estimated + by machine learning methods, allowing the number of covariates to be comparable + to or larger than the sample size. The second stage consists of a low-dimensional + local linear regression, reducing CATE to a function of the covariate(s) of interest. + The CATE estimator implemented in this package not only allows for high-dimensional + data, but also has the “double robustness” property: either the model for the + propensity score or the models for the conditional means of the potential outcomes + are allowed to be misspecified (but not both). This package is based on the paper + by Fan et al., "Estimation of Conditional Average Treatment Effects With High-Dimensional + Data" (2022), Journal of Business & Economic Statistics .' + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdcate + url_git: '' +HDCD: + version: '1.1' + title: High-Dimensional Changepoint Detection + maintainer: Per August Jarval Moen + description: 'Efficient implementations of the following multiple changepoint detection + algorithms: Efficient Sparsity Adaptive Change-point estimator by Moen, Glad and + Tveten (2023) , Informative Sparse Projection + for Estimating Changepoints by Wang and Samworth (2017) , + and the method of Pilliat et al (2023) .' + date_publication: '2024-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDCD + url_git: '' +HDCI: + version: 1.0-2 + title: |- + High Dimensional Confidence Interval Based on Lasso and + Bootstrap + maintainer: Xin Xu + description: Fits regression models on high dimensional data to estimate coefficients + and use bootstrap method to obtain confidence intervals. Choices for regression + models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge. + date_publication: '2017-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDCI + url_git: '' +HDclassif: + version: 2.2.1 + title: High Dimensional Supervised Classification and Clustering + maintainer: Laurent Berge + description: |- + Discriminant analysis and data clustering methods for high + dimensional data, based on the assumption that high-dimensional data live in + different subspaces with low dimensionality proposing a new parametrization of + the Gaussian mixture model which combines the ideas of dimension reduction and + constraints on the model. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDclassif + url_git: '' +HDclust: + version: 1.0.4 + title: |- + Clustering High Dimensional Data with Hidden Markov Model on + Variable Blocks + maintainer: Jia Li + description: Clustering of high dimensional data with Hidden Markov Model on Variable + Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the + Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin + Lin and Jia Li (2017) . + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDclust + url_git: '' +HDcpDetect: + version: 0.1.0 + title: Detect Change Points in Means of High Dimensional Data + maintainer: Natasha Stewart + description: 'Objective: Implement new methods for detecting change points in high-dimensional + time series data. These new methods can be applied to non-Gaussian data, account + for spatial and temporal dependence, and detect a wide variety of change-point + configurations, including changes near the boundary and changes in close proximity. + Additionally, this package helps address the “small n, large p” problem, which + occurs in many research contexts. This problem arises when a dataset contains + changes that are visually evident but do not rise to the level of statistical + significance due to the small number of observations and large number of parameters. + The problem is overcome by treating the dimensions as a whole and scaling the + test statistics only by its standard deviation, rather than scaling each dimension + individually. Due to the computational complexity of the functions, the package + runs best on datasets with a relatively large number of attributes but no more + than a few hundred observations.' + date_publication: '2018-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDcpDetect + url_git: '' +hdcuremodels: + version: 0.0.1 + title: Penalized Mixture Cure Models for High-Dimensional Data + maintainer: Kellie J. Archer + description: Provides functions for fitting various penalized parametric and semi-parametric + mixture cure models with different penalty functions, testing for a significant + cure fraction, and testing for sufficient follow-up as described in Fu et al (2022) + and Archer et al (2024). False discovery rate + controlled variable selection is provided using model-X knock-offs. + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdcuremodels + url_git: '' +HDCurves: + version: 0.1.2 + title: Hierarchical Derivative Curve Estimation + maintainer: Garritt L. Page + description: A procedure that fits derivative curves based on a sequence of quotient + differences. In a hierarchical setting the package produces estimates of subject-specific + and group-specific derivative curves. In a non-hierarchical setting the package + produces a single derivative curve. + date_publication: '2023-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDCurves + url_git: '' +hdd: + version: 0.1.1 + title: Easy Manipulation of Out of Memory Data Sets + maintainer: Laurent Berge + description: 'Hard drive data: Class of data allowing the easy importation/manipulation + of out of memory data sets. The data sets are located on disk but look like in-memory, + the syntax for manipulation is similar to ''data.table''. Operations are performed + "chunk-wise" behind the scene.' + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdd + url_git: '' +HDDesign: + version: '1.1' + title: |- + Sample Size Calculation for High Dimensional Classification + Study + maintainer: Brisa N. Sanchez + description: Determine the sample size requirement to achieve the target probability + of correct classification (PCC) for studies employing high-dimensional features. The + package implements functions to 1) determine the asymptotic feasibility of the + classification problem; 2) compute the upper bounds of the PCC for any linear + classifier; 3) estimate the PCC of three design methods given design assumptions; + 4) determine the sample size requirement to achieve the target PCC for three design + methods. + date_publication: '2016-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDDesign + url_git: '' +hddplot: + version: 0.59-2 + title: |- + Use Known Groups in High-Dimensional Data to Derive Scores for + Plots + maintainer: John Maindonald + description: |- + Cross-validated linear discriminant calculations determine + the optimum number of features. Test and training scores from + successive cross-validation steps determine, via a principal + components calculation, a low-dimensional global space onto which test + scores are projected, in order to plot them. Further functions are + included that are intended for didactic use. The package implements, + and extends, methods described in J.H. Maindonald and C.J. Burden (2005) + . + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hddplot + url_git: https://github.com/jhmaindonald/hddplot +hdf5r: + version: 1.3.12 + title: Interface to the 'HDF5' Binary Data Format + maintainer: Holger Hoefling + description: |- + 'HDF5' is a data model, library and file format for storing + and managing large amounts of data. This package provides a nearly + feature complete, object oriented wrapper for the 'HDF5' API + using R6 classes. + Additionally, functionality is added so that 'HDF5' objects behave very + similar to their corresponding R counterparts. + date_publication: '2025-01-20' + bug_reports: https://github.com/hhoeflin/hdf5r/issues + url: https://hhoeflin.github.io/hdf5r/ + url_cran: https://CRAN.R-project.org/package=hdf5r + url_git: https://github.com/hhoeflin/hdf5r/ +hdf5r.Extra: + version: 0.1.0 + title: Extensions for 'HDF5' R Interfaces + maintainer: Yuchen Li + description: Some methods to manipulate 'HDF5' files, extending the 'hdf5r' package. + Reading and writing R objects to 'HDF5' formats follow the specification of 'AnnData' + . + date_publication: '2024-10-18' + bug_reports: https://github.com/ycli1995/hdf5r.Extra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hdf5r.Extra + url_git: https://github.com/ycli1995/hdf5r.Extra +hdflex: + version: 0.3.0 + title: High-Dimensional Aggregate Density Forecasts + maintainer: Sven Lehmann + description: |- + Provides a forecasting method that efficiently maps vast + numbers of (scalar-valued) signals into an aggregate density forecast + in a time-varying and computationally fast manner. The method proceeds + in two steps: First, it transforms a predictive signal into a density + forecast and, second, it combines the resulting candidate density + forecasts into an ultimate aggregate density forecast. For a detailed + explanation of the method, please refer to Adaemmer et al. (2023) + . + date_publication: '2024-10-10' + bug_reports: https://github.com/lehmasve/hdflex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hdflex + url_git: https://github.com/lehmasve/hdflex +hdfqlr: + version: 0.6-2 + title: Interface to 'HDFql' API + maintainer: Michael Koohafkan + description: |- + Provides an interface to 'HDFql' + and helper functions for reading data from and writing data to 'HDF5' files. 'HDFql' + provides a high-level language for managing 'HDF5' data that is platform independent. + For more information, see the reference manual + . + date_publication: '2021-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdfqlr + url_git: '' +hdftsa: + version: '1.0' + title: High-Dimensional Functional Time Series Analysis + maintainer: Han Lin Shang + description: Offers methods for visualizing, modelling, and forecasting high-dimensional + functional time series, also known as functional panel data. Documentation about + 'hdftsa' is provided via the paper by Cristian F. Jimenez-Varon, Ying Sun and + Han Lin Shang (2024, ). + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdftsa + url_git: '' +HDGLM: + version: '0.1' + title: Tests for High Dimensional Generalized Linear Models + maintainer: Bin Guo + description: Test the significance of coefficients in high dimensional generalized + linear models. + date_publication: '2015-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDGLM + url_git: '' +hdi: + version: 0.1-9 + title: High-Dimensional Inference + maintainer: Lukas Meier + description: Implementation of multiple approaches to perform inference in high-dimensional + models. + date_publication: '2021-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdi + url_git: '' +hdImpute: + version: 0.2.1 + title: A Batch Process for High Dimensional Imputation + maintainer: Philip Waggoner + description: |- + A correlation-based batch process for fast, accurate imputation for + high dimensional missing data problems via chained random forests. + See Waggoner (2023) for more on 'hdImpute', + Stekhoven and Bühlmann (2012) for more on 'missForest', + and Mayer (2022) for more on 'missRanger'. + date_publication: '2023-08-07' + bug_reports: https://github.com/pdwaggoner/hdImpute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hdImpute + url_git: https://github.com/pdwaggoner/hdImpute +HDInterval: + version: 0.2.4 + title: Highest (Posterior) Density Intervals + maintainer: Ngumbang Juat + description: A generic function and a set of methods to calculate highest density + intervals for a variety of classes of objects which can specify a probability + density distribution, including MCMC output, fitted density objects, and functions. + date_publication: '2022-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDInterval + url_git: '' +HDiR: + version: 1.1.3 + title: Directional Highest Density Regions + maintainer: Paula Saavedra-Nieves + description: We provide an R tool for computation and nonparametric plug-in estimation + of Highest Density Regions (HDRs) and general level sets in the directional setting. + Concretely, circular and spherical HDRs can be reconstructed from a data sample + following Saavedra-Nieves and Crujeiras (2021) . + This library also contains two real datasets in the circular and spherical settings. + The first one concerns a problem from animal orientation studies and the second + one is related to earthquakes occurrences. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDiR + url_git: '' +hdiVAR: + version: 1.0.2 + title: Statistical Inference for Noisy Vector Autoregression + maintainer: Xiang Lyu + description: 'The model is high-dimensional vector autoregression with measurement + error, also known as linear gaussian state-space model. Provable sparse expectation-maximization + algorithm is provided for the estimation of transition matrix and noise variances. + Global and simultaneous testings are implemented for transition matrix with false + discovery rate control. For more information, see the accompanying paper: Lyu, + X., Kang, J., & Li, L. (2023). "Statistical inference for high-dimensional vector + autoregression with measurement error", Statistica Sinica.' + date_publication: '2023-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdiVAR + url_git: '' +HDJM: + version: 0.1.0 + title: Penalized High-Dimensional Joint Model + maintainer: Jiehuan Sun + description: |- + Joint models have been widely used to study the associations between longitudinal biomarkers and a survival outcome. However, existing joint models only consider one or a few longitudinal + biomarkers and cannot deal with high-dimensional longitudinal biomarkers. This package can be used to fit our recently developed penalized joint model that can handle high-dimensional longitudinal biomarkers. + Specifically, an adaptive lasso penalty is imposed on the parameters for the effects of the longitudinal biomarkers on the survival outcome, which allows for variable selection. + Also, our algorithm is computationally efficient, which is based on the Gaussian variational approximation method. + date_publication: '2023-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDJM + url_git: '' +HDLSSkST: + version: 2.1.0 + title: |- + Distribution-Free Exact High Dimensional Low Sample Size + k-Sample Tests + maintainer: Biplab Paul + description: |- + Testing homogeneity of k multivariate distributions is a classical and challenging problem in + statistics, and this becomes even more challenging when the dimension of the data exceeds the sample size. + We construct some tests for this purpose which are exact level (size) alpha tests based on clustering. + These tests are easy to implement and distribution-free in finite sample situations. Under appropriate + regularity conditions, these tests have the consistency property in HDLSS asymptotic regime, where the + dimension of data grows to infinity while the sample size remains fixed. We also consider a multiscale + approach, where the results for different number of partitions are aggregated judiciously. Details are in + Biplab Paul, Shyamal K De and Anil K Ghosh (2021) ; Soham Sarkar and Anil K Ghosh (2019) + ; William M Rand (1971) ; + Cyrus R Mehta and Nitin R Patel (1983) ; Joseph C Dunn (1973) + ; Sture Holm (1979) ; + Yoav Benjamini and Yosef Hochberg (1995) . + date_publication: '2022-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDLSSkST + url_git: '' +hdm: + version: 0.3.2 + title: High-Dimensional Metrics + maintainer: Martin Spindler + description: |- + Implementation of selected high-dimensional statistical and + econometric methods for estimation and inference. Efficient estimators and + uniformly valid confidence intervals for various low-dimensional causal/ + structural parameters are provided which appear in high-dimensional + approximately sparse models. Including functions for fitting heteroscedastic + robust Lasso regressions with non-Gaussian errors and for instrumental variable + (IV) and treatment effect estimation in a high-dimensional setting. Moreover, + the methods enable valid post-selection inference and rely on a theoretically + grounded, data-driven choice of the penalty. + Chernozhukov, Hansen, Spindler (2016) . + date_publication: '2024-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdm + url_git: '' +HDMAADMM: + version: 0.0.1 + title: ADMM for High-Dimensional Mediation Models + maintainer: Pei-Shan Yen + description: We use the Alternating Direction Method of Multipliers (ADMM) for parameter + estimation in high-dimensional, single-modality mediation models. To improve the + sensitivity and specificity of estimated mediation effects, we offer the sure + independence screening (SIS) function for dimension reduction. The available penalty + options include Lasso, Elastic Net, Pathway Lasso, and Network-constrained Penalty. + The methods employed in the package are based on Boyd, S., Parikh, N., Chu, E., + Peleato, B., & Eckstein, J. (2011). , Fan, J., & Lv, J. + (2008) , Li, C., & Li, H. (2008) , + Tibshirani, R. (1996) , Zhao, Y., & Luo, + X. (2022) , and Zou, H., & Hastie, T. (2005) . + date_publication: '2023-11-29' + bug_reports: https://github.com/psyen0824/HDMAADMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HDMAADMM + url_git: https://github.com/psyen0824/HDMAADMM +hdme: + version: 0.6.0 + title: High-Dimensional Regression with Measurement Error + maintainer: Oystein Sorensen + description: |- + Penalized regression for generalized linear models for + measurement error problems (aka. errors-in-variables). The package + contains a version of the lasso (L1-penalization) which corrects + for measurement error (Sorensen et al. (2015) ). + It also contains an implementation of the Generalized Matrix Uncertainty + Selector, which is a version the (Generalized) Dantzig Selector for the + case of measurement error (Sorensen et al. (2018) ). + date_publication: '2023-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdme + url_git: https://github.com/osorensen/hdme +hdmed: + version: 1.0.1 + title: Methods for Mediation Analysis with High-Dimensional Mediators + maintainer: Dylan Clark-Boucher + description: |- + A suite of functions for performing mediation + analysis with high-dimensional mediators. In addition to centralizing code + from several existing packages for high-dimensional mediation analysis, we + provide organized, well-documented functions for a handle of methods + which, though programmed their original authors, have not previously been + formalized into R packages or been made presentable for public use. The + methods we include cover a broad array of approaches and objectives, and are + described in detail by both our companion manuscript---"Methods for + Mediation Analysis with High-Dimensional DNA Methylation Data: Possible + Choices and Comparison"---and the original publications that proposed them. + The specific methods offered by our package include the Bayesian sparse + linear mixed model (BSLMM) by Song et al. (2019); high-dimensional mediation + analysis (HDMA) by Gao et al. (2019); high-dimensional multivariate + mediation (HDMM) by Chén et al. (2018); high-dimensional linear mediation + analysis (HILMA) by Zhou et al. (2020); high-dimensional mediation analysis + (HIMA) by Zhang et al. (2016); latent variable mediation analysis (LVMA) by + Derkach et al. (2019); mediation by fixed-effect model (MedFix) by + Zhang (2021); pathway LASSO by Zhao & Luo (2022); principal component + mediation analysis (PCMA) by Huang & Pan (2016); and sparse principal + component mediation analysis (SPCMA) by Zhao et al. (2020). Citations for + the corresponding papers can be found in their respective functions. + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdmed + url_git: '' +HDMFA: + version: 0.1.1 + title: High-Dimensional Matrix Factor Analysis + maintainer: Ran Zhao + description: High-dimensional matrix factor models have drawn much attention in + view of the fact that observations are usually well structured to be an array + such as in macroeconomics and finance. In addition, data often exhibit heavy-tails + and thus it is also important to develop robust procedures. We aim to address + this issue by replacing the least square loss with Huber loss function. We propose + two algorithms to do robust factor analysis by considering the Huber loss. One + is based on minimizing the Huber loss of the idiosyncratic error's Frobenius norm, + which leads to a weighted iterative projection approach to compute and learn the + parameters and thereby named as Robust-Matrix-Factor-Analysis (RMFA), see the + details in He et al. (2023). The other one + is based on minimizing the element-wise Huber loss, which can be solved by an + iterative Huber regression algorithm (IHR), see the details in He et al. (2023) + . In this package, we also provide the algorithm for alpha-PCA + by Chen & Fan (2021) , the Projected estimation + (PE) method by Yu et al. (2022). In addition, + the methods for determining the pair of factor numbers are also given. + date_publication: '2024-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDMFA + url_git: '' +HDMT: + version: 1.0.5 + title: |- + A Multiple Testing Procedure for High-Dimensional Mediation + Hypotheses + maintainer: James Dai + description: A multiple-testing procedure for high-dimensional mediation hypotheses. + Mediation analysis is of rising interest in epidemiology and clinical trials. + Among existing methods for mediation analyses, the popular joint significance + (JS) test yields an overly conservative type I error rate and therefore low power. + In the R package 'HDMT' we implement a multiple-testing procedure that accurately + controls the family-wise error rate (FWER) and the false discovery rate (FDR) + when using JS for testing high-dimensional mediation hypotheses. The core of our + procedure is based on estimating the proportions of three component null hypotheses + and deriving the corresponding mixture distribution of null p-values. Results + of the data examples include better-behaved quantile-quantile plots and improved + detection of novel mediation relationships on the role of DNA methylation in genetic + regulation of gene expression. With increasing interest in mediation by molecular + intermediaries such as gene expression, the proposed method addresses an unmet + methodological challenge. Methods used in the package refer to James Y. Dai, Janet + L. Stanford & Michael LeBlanc (2020) . + date_publication: '2022-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDMT + url_git: '' +hdnom: + version: 6.0.4 + title: Benchmarking and Visualization Toolkit for Penalized Cox Models + maintainer: Nan Xiao + description: |- + Creates nomogram visualizations for penalized Cox regression + models, with the support of reproducible survival model building, + validation, calibration, and comparison for high-dimensional data. + date_publication: '2024-09-05' + bug_reports: https://github.com/nanxstats/hdnom/issues + url: https://nanx.me/hdnom/ + url_cran: https://CRAN.R-project.org/package=hdnom + url_git: https://github.com/nanxstats/hdnom +HDNRA: + version: 2.0.1 + title: |- + High-Dimensional Location Testing with Normal-Reference + Approaches + maintainer: Pengfei Wang + description: We provide a collection of various classical tests and latest normal-reference + tests for comparing high-dimensional mean vectors including two-sample and general + linear hypothesis testing (GLHT) problem. Some existing tests for two-sample problem + [see Bai, Zhidong, and Hewa Saranadasa.(1996) ; + Chen, Song Xi, and Ying-Li Qin.(2010) ; Srivastava, Muni + S., and Meng Du.(2008) ; Srivastava, Muni S., + Shota Katayama, and Yutaka Kano.(2013)]. Normal-reference + tests for two-sample problem [see Zhang, Jin-Ting, Jia Guo, Bu Zhou, and Ming-Yen + Cheng.(2020) ; Zhang, Jin-Ting, Bu Zhou, Jia + Guo, and Tianming Zhu.(2021) ; Zhang, Liang, Tianming + Zhu, and Jin-Ting Zhang.(2020) ; Zhang, Liang, + Tianming Zhu, and Jin-Ting Zhang.(2023) ; Zhang, + Jin-Ting, and Tianming Zhu.(2022) ; Zhang, + Jin-Ting, and Tianming Zhu.(2022) ; Zhu, Tianming, + Pengfei Wang, and Jin-Ting Zhang.(2023) ]. Some + existing tests for GLHT problem [see Fujikoshi, Yasunori, Tetsuto Himeno, and + Hirofumi Wakaki.(2004) ; Srivastava, Muni S., and Yasunori + Fujikoshi.(2006) ; Yamada, Takayuki, and Muni + S. Srivastava.(2012) ; Schott, James R.(2007) + ; Zhou, Bu, Jia Guo, and Jin-Ting Zhang.(2017) + ]. Normal-reference tests for GLHT problem [see + Zhang, Jin-Ting, Jia Guo, and Bu Zhou.(2017) ; + Zhang, Jin-Ting, Bu Zhou, and Jia Guo.(2022) ; + Zhu, Tianming, Liang Zhang, and Jin-Ting Zhang.(2022) ; + Zhu, Tianming, and Jin-Ting Zhang.(2022) ; Zhang, + Jin-Ting, and Tianming Zhu.(2022) ]. + date_publication: '2024-10-22' + bug_reports: https://github.com/nie23wp8738/HDNRA/issues + url: https://nie23wp8738.github.io/HDNRA/ + url_cran: https://CRAN.R-project.org/package=HDNRA + url_git: '' +HDOMDesign: + version: 1.0-1 + title: High-Dimensional Orthogonal Maximin Distance Designs + maintainer: Xu He + description: Contains functions to construct high-dimensional orthogonal maximin + distance designs in two, four, eight, and sixteen levels from rotating the Kronecker + product of sub-Hadamard matrices. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDOMDesign + url_git: '' +HDoutliers: + version: 1.0.4 + title: |- + Leland Wilkinson's Algorithm for Detecting Multidimensional + Outliers + maintainer: Chris Fraley + description: An implementation of an algorithm for outlier detection that can handle + a) data with a mixed categorical and continuous variables, b) many columns of + data, c) many rows of data, d) outliers that mask other outliers, and e) both + unidimensional and multidimensional datasets. Unlike ad hoc methods found in many + machine learning papers, HDoutliers is based on a distributional model that uses + probabilities to determine outliers. + date_publication: '2022-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDoutliers + url_git: '' +hdpca: + version: 1.1.5 + title: Principal Component Analysis in High-Dimensional Data + maintainer: Rounak Dey + description: |- + In high-dimensional settings: + Estimate the number of distant spikes based on the Generalized Spiked Population (GSP) model. + Estimate the population eigenvalues, angles between the sample and population eigenvectors, correlations between the sample and population PC scores, and the asymptotic shrinkage factors. + Adjust the shrinkage bias in the predicted PC scores. + Dey, R. and Lee, S. (2019) . + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdpca + url_git: '' +hdpGLM: + version: 1.0.3 + title: Hierarchical Dirichlet Process Generalized Linear Models + maintainer: Diogo Ferrari + description: Implementation of MCMC algorithms to estimate the Hierarchical Dirichlet + Process Generalized Linear Model (hdpGLM) presented in the paper Ferrari (2020) + Modeling Context-Dependent Latent Heterogeneity, Political Analysis + and . + date_publication: '2023-10-12' + bug_reports: https://github.com/DiogoFerrari/hdpGLM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hdpGLM + url_git: https://github.com/DiogoFerrari/hdpGLM +hdqr: + version: 1.0.1 + title: Fast Algorithm for Penalized Quantile Regression + maintainer: Qian Tang + description: Implements an efficient algorithm to fit and tune penalized quantile + regression models using the generalized coordinate descent algorithm. Designed + to handle high-dimensional datasets effectively, with emphasis on precision and + computational efficiency. This package implements the algorithms proposed in Tang, + Q., Zhang, Y., & Wang, B. (2022) . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdqr + url_git: '' +hdrcde: + version: '3.4' + title: Highest Density Regions and Conditional Density Estimation + maintainer: Rob Hyndman + description: Computation of highest density regions in one and two dimensions, kernel + estimation of univariate density functions conditional on one covariate,and multimodal + regression. + date_publication: '2021-01-18' + bug_reports: https://github.com/robjhyndman/hdrcde/issues + url: https://pkg.robjhyndman.com/hdrcde/ + url_cran: https://CRAN.R-project.org/package=hdrcde + url_git: https://github.com/robjhyndman/hdrcde +HDRFA: + version: 0.1.5 + title: High-Dimensional Robust Factor Analysis + maintainer: Dong Liu + description: Factor models have been widely applied in areas such as economics and + finance, and the well-known heavy-tailedness of macroeconomic/financial data should + be taken into account when conducting factor analysis. We propose two algorithms + to do robust factor analysis by considering the Huber loss. One is based on minimizing + the Huber loss of the idiosyncratic error's L2 norm, which turns out to do Principal + Component Analysis (PCA) on the weighted sample covariance matrix and thereby + named as Huber PCA. The other one is based on minimizing the element-wise Huber + loss, which can be solved by an iterative Huber regression algorithm. In this + package we also provide the code for traditional PCA, the Robust Two Step (RTS) + method by He et al. (2022) and the Quantile Factor Analysis (QFA) method by Chen + et al. (2021) and He et al. (2023). + date_publication: '2024-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDRFA + url_git: '' +hds: + version: 0.8.1 + title: Hazard Discrimination Summary + maintainer: C. Jason Liang + description: |- + Functions for calculating the hazard discrimination summary and its + standard errors, as described in Liang and Heagerty (2016) . + date_publication: '2016-12-31' + bug_reports: https://github.com/liangcj/hds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hds + url_git: https://github.com/liangcj/hds +HDShOP: + version: 0.1.5 + title: High-Dimensional Shrinkage Optimal Portfolios + maintainer: Dmitry Otryakhin + description: |- + Constructs shrinkage estimators of high-dimensional mean-variance portfolios and performs + high-dimensional tests on optimality of a given portfolio. The techniques developed in + Bodnar et al. (2018 , 2019 , + 2020 , 2021 ) + are central to the package. They provide simple and feasible estimators and tests for optimal + portfolio weights, which are applicable for 'large p and large n' situations where p is the + portfolio dimension (number of stocks) and n is the sample size. The package also includes tools + for constructing portfolios based on shrinkage estimators of the mean vector and covariance matrix + as well as a new Bayesian estimator for the Markowitz efficient frontier recently developed by + Bauder et al. (2021) . + date_publication: '2024-03-25' + bug_reports: https://github.com/Otryakhin-Dmitry/global-minimum-variance-portfolio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HDShOP + url_git: https://github.com/Otryakhin-Dmitry/global-minimum-variance-portfolio +HDSinRdata: + version: 0.1.3 + title: |- + Data for the 'Mastering Health Data Science Using R' Online + Textbook + maintainer: Alice Paul + description: Contains ten datasets used in the chapters and exercises of Paul, Alice + (2023) "Health Data Science in R" . + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDSinRdata + url_git: '' +HDSpatialScan: + version: 1.0.4 + title: Multivariate and Functional Spatial Scan Statistics + maintainer: Camille FREVENT + description: Allows to detect spatial clusters of abnormal values on multivariate + or functional data. Martin KULLDORFF and Lan HUANG and Kevin KONTY (2009) , + Inkyung JUNG and Ho Jin CHO (2015) , Lionel CUCALA + and Michael GENIN and Caroline LANIER and Florent OCCELLI (2017) , + Lionel CUCALA and Michael GENIN and Florent OCCELLI and Julien SOULA (2019) , + Camille FREVENT and Mohamed-Salem AHMED and Matthieu MARBAC and Michael GENIN + (2021) , Zaineb SMIDA and Lionel CUCALA and + Ali GANNOUN and Ghislain Durif (2022) , Camille + FREVENT and Mohamed-Salem AHMED and Sophie DABO-NIANG and Michael GENIN (2023) + . + date_publication: '2023-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDSpatialScan + url_git: '' +HDStIM: + version: 0.1.0 + title: High Dimensional Stimulation Immune Mapping ('HDStIM') + maintainer: Rohit Farmer + description: A method for identifying responses to experimental stimulation in mass + or flow cytometry that uses high dimensional analysis of measured parameters and + can be performed with an end-to-end unsupervised approach. In the context of in + vitro stimulation assays where high-parameter cytometry was used to monitor intracellular + response markers, using cell populations annotated either through automated clustering + or manual gating for a combined set of stimulated and unstimulated samples, 'HDStIM' + labels cells as responding or non-responding. The package also provides auxiliary + functions to rank intracellular markers based on their contribution to identifying + responses and generating diagnostic plots. + date_publication: '2022-06-24' + bug_reports: https://github.com/niaid/HDStIM/issues + url: https://niaid.github.io/HDStIM/ + url_cran: https://CRAN.R-project.org/package=HDStIM + url_git: https://github.com/niaid/HDStIM +hdsvm: + version: 1.0.1 + title: Fast Algorithm for Support Vector Machine + maintainer: Yikai Zhang + description: Implements an efficient algorithm to fit and tune penalized Support + Vector Machine models using the generalized coordinate descent algorithm. Designed + to handle high-dimensional datasets effectively, with emphasis on precision and + computational efficiency. This package implements the algorithms proposed in Tang, + Q., Zhang, Y., & Wang, B. (2022) . + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdsvm + url_git: '' +hdthreshold: + version: 1.0.0 + title: Inference on Many Jumps in Nonparametric Panel Regression Models + maintainer: Georg Keilbar + description: |- + Provides uniform testing procedures for existence and heterogeneity of threshold + effects in high-dimensional nonparametric panel regression models. The package accompanies + the paper Chen, Keilbar, Su and Wang (2023) "Inference on many jumps in nonparametric panel + regression models". arXiv preprint . + date_publication: '2024-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hdthreshold + url_git: '' +HDTSA: + version: 1.0.5-1 + title: High Dimensional Time Series Analysis Tools + maintainer: Chen Lin + description: |- + An implementation for high-dimensional time series analysis methods, including factor model for vector time series + proposed by Lam and Yao (2012) and Chang, Guo and Yao (2015) + , martingale difference test proposed by + Chang, Jiang and Shao (2023) , principal + component analysis for vector time series proposed by Chang, Guo and Yao (2018) , + cointegration analysis proposed by Zhang, Robinson and Yao (2019) + , unit root test proposed by Chang, Cheng and Yao (2022) + , white noise test proposed by Chang, Yao and Zhou (2017) + , CP-decomposition for matrix time + series proposed by Chang et al. (2023) and + Chang et al. (2024) , and statistical inference for + spectral density matrix proposed by Chang et al. (2022) + . + date_publication: '2025-01-28' + bug_reports: https://github.com/Linc2021/HDTSA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HDTSA + url_git: https://github.com/Linc2021/HDTSA +HDtweedie: + version: '1.2' + title: |- + The Lasso for Tweedie's Compound Poisson Model Using an IRLS-BMD + Algorithm + maintainer: Wei Qian + description: The Tweedie lasso model implements an iteratively reweighed least square + (IRLS) strategy that incorporates a blockwise majorization decent (BMD) method, + for efficiently computing solution paths of the (grouped) lasso and the (grouped) + elastic net methods. + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDtweedie + url_git: '' +HDXBoxeR: + version: 0.0.2 + title: Analysis of Hydrogen-Deuterium Exchange Mass-Spectrometry Data + maintainer: Maria K. Janowska + description: |- + A protocol that facilitates the processing and analysis of Hydrogen-Deuterium Exchange Mass Spectrometry data using p-value statistics and Critical Interval analysis. + It provides a pipeline for analyzing data from 'HDXExaminer' (Sierra Analytics, Trajan Scientific), + automating matching and comparison of protein states through Welch's T-test and the Critical Interval statistical framework. + Additionally, it simplifies data export, generates 'PyMol' scripts, and ensures calculations meet publication standards. + 'HDXBoxeR' assists in various aspects of hydrogen-deuterium exchange data analysis, including reprocessing data, calculating parameters, identifying significant peptides, + generating plots, and facilitating comparison between protein states. + For details check papers by Hageman and Weis (2019) + and Masson et al. (2019) . + 'HDXBoxeR' citation: Janowska et al. (2024) . + date_publication: '2024-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HDXBoxeR + url_git: '' +headliner: + version: 0.0.3 + title: Compose Sentences to Describe Comparisons + maintainer: Jake Riley + description: |- + Create dynamic, data-driven text. Given two values, a list of + talking points is generated and can be combined using string + interpolation. Based on the 'glue' package. + date_publication: '2022-12-20' + bug_reports: https://github.com/rjake/headliner/issues/ + url: https://rjake.github.io/headliner/ + url_cran: https://CRAN.R-project.org/package=headliner + url_git: https://github.com/rjake/headliner/ +healthatlas: + version: 0.1.1 + title: |- + Explore and Import 'Metopio' Health Atlas Data and Spatial + Layers + maintainer: Ryan Zomorrodi + description: |- + Allows for painless use of the 'Metopio' health atlas APIs + to explore and import data. + 'Metopio' health atlases store open public health data. See what topics + (or indicators) are available among specific populations, periods, and + geographic layers. Download relevant data along with geographic + boundaries or point datasets. Spatial datasets are returned as 'sf' + objects. + date_publication: '2024-12-18' + bug_reports: https://github.com/ryanzomorrodi/healthatlas/issues + url: https://ryanzomorrodi.github.io/healthatlas/ + url_cran: https://CRAN.R-project.org/package=healthatlas + url_git: https://github.com/ryanzomorrodi/healthatlas +HealthCal: + version: 0.1.1 + title: Health Calculator + maintainer: Pankaj Das + description: Health Calculator helps to find different parameters like basal metabolic + rate, body mass index etc. related to fitness and health of a person. + date_publication: '2023-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HealthCal + url_git: '' +healthcare.antitrust: + version: 0.1.4 + title: Healthcare Antitrust Analysis + maintainer: Matthew T Panhans + description: |- + Antitrust analysis of + healthcare markets. Contains functions to implement the + semiparametric estimation technique described in Raval, Rosenbaum, + and Tenn (2017) "A Semiparametric Discrete Choice Model: An Application + to Hospital Mergers" . + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=healthcare.antitrust + url_git: https://github.com/mpanhans/healthcare.antitrust +healthdb: + version: 0.4.0 + title: Working with Healthcare Databases + maintainer: Kevin Hu + description: |- + A system for identifying diseases or events from healthcare databases and + preparing data for epidemiological studies. It includes capabilities not + supported by 'SQL', such as matching strings by 'stringr' style regular + expressions, and can compute comorbidity scores (Quan et al. (2005) + ) directly on a database server. The + implementation is based on 'dbplyr' with full 'tidyverse' compatibility. + date_publication: '2025-02-28' + bug_reports: https://github.com/KevinHzq/healthdb/issues + url: https://kevinhzq.github.io/healthdb/ + url_cran: https://CRAN.R-project.org/package=healthdb + url_git: https://github.com/KevinHzq/healthdb +healthequal: + version: 1.0.1 + title: Compute Summary Measures of Health Inequality + maintainer: Katherine Kirkby + description: |- + Compute 21 summary measures of health inequality and its + corresponding confidence intervals for ordered and non-ordered + dimensions using disaggregated data. Measures for ordered dimensions + (e.g., Slope Index of Inequality, Absolute Concentration Index) also + accept individual and survey data. + date_publication: '2024-11-25' + bug_reports: https://github.com/WHOequity/healthequal/issues + url: https://whoequity.github.io/healthequal/ + url_cran: https://CRAN.R-project.org/package=healthequal + url_git: https://github.com/WHOequity/healthequal +healthfinance: + version: 0.1.0 + title: Financial Projections and Planning for Health Care Practices + maintainer: Raoul Wadhwa + description: |- + Provides a shiny interface for a free, open-source managerial + accounting-like system for health care practices. This package allows + health care administrators to project revenue with monthly adjustments + and procedure-specific boosts up to a 3-year period. Granular data + (patient-level) to aggregated data (department- or hospital-level) can + all be used as valid inputs provided historical volume and revenue + data is available. For more details on managerial accounting + techniques, see Brewer et al. (2015, ISBN:9780078025792). + date_publication: '2020-10-24' + bug_reports: https://github.com/rrrlw/healthfinance/issues + url: https://rrrlw.github.io/healthfinance/ + url_cran: https://CRAN.R-project.org/package=healthfinance + url_git: '' +healthyAddress: + version: 0.4.5 + title: Convert Addresses to Standard Inputs + maintainer: Hugh Parsonage + description: |- + Efficient tools for parsing and standardizing Australian + addresses from textual data. It utilizes optimized algorithms to accurately identify and + extract components of addresses, such as street names, types, and postcodes, especially + for large batched data in contexts where sending addresses to internet services may be + slow or inappropriate. The core functionality is built on fast string processing techniques + to handle variations in address formats and abbreviations commonly found in Australian + address data. Designed for data scientists, urban planners, and logistics analysts, the + package facilitates the cleaning and normalization of address information, supporting + better data integration and analysis in urban studies, geography, and related fields. + date_publication: '2025-01-09' + bug_reports: https://github.com/HughParsonage/healthyAddress/issues + url: '' + url_cran: https://CRAN.R-project.org/package=healthyAddress + url_git: https://github.com/HughParsonage/healthyAddress +healthyR: + version: 0.2.2 + title: Hospital Data Analysis Workflow Tools + maintainer: Steven Sanderson + description: |- + Hospital data analysis workflow tools, modeling, and automations. This library + provides many useful tools to review common administrative hospital data. Some + of these include average length of stay, readmission rates, average net pay + amounts by service lines just to name a few. The aim is to provide a simple + and consistent verb framework that takes the guesswork out of everything. + date_publication: '2024-07-01' + bug_reports: https://github.com/spsanderson/healthyR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=healthyR + url_git: https://github.com/spsanderson/healthyR +healthyR.ai: + version: 0.1.0 + title: The Machine Learning and AI Modeling Companion to 'healthyR' + maintainer: Steven Sanderson + description: |- + Hospital machine learning and ai data analysis workflow tools, modeling, and automations. + This library provides many useful tools to review common administrative + hospital data. Some of these include predicting length of stay, and readmits. + The aim is to provide a simple and consistent verb framework that takes the + guesswork out of everything. + date_publication: '2024-09-11' + bug_reports: https://github.com/spsanderson/healthyR.ai/issues + url: https://www.spsanderson.com/healthyR.ai/ + url_cran: https://CRAN.R-project.org/package=healthyR.ai + url_git: https://github.com/spsanderson/healthyR.ai +healthyR.data: + version: 1.2.0 + title: Data Only Package to 'healthyR' + maintainer: Steven Sanderson + description: Provides data for functions typically used in the 'healthyR' package. + date_publication: '2025-01-13' + bug_reports: https://github.com/spsanderson/healthyR.data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=healthyR.data + url_git: https://github.com/spsanderson/healthyR.data +healthyR.ts: + version: 0.3.1 + title: The Time Series Modeling Companion to 'healthyR' + maintainer: Steven Sanderson + description: |- + Hospital time series data analysis workflow tools, modeling, and automations. + This library provides many useful tools to review common administrative time + series hospital data. Some of these include average length of stay, and + readmission rates. The aim is to provide a simple and consistent verb + framework that takes the guesswork out of everything. + date_publication: '2024-10-11' + bug_reports: https://github.com/spsanderson/healthyR.ts/issues + url: https://www.spsanderson.com/healthyR.ts/ + url_cran: https://CRAN.R-project.org/package=healthyR.ts + url_git: https://github.com/spsanderson/healthyR.ts +healthyverse: + version: 1.1.0 + title: Easily Install and Load the 'healthyverse' + maintainer: Steven Sanderson + description: |- + The 'healthyverse' is a set of packages that work in + harmony because they share common data representations and 'API' + design. This package is designed to make it easy to install and load + multiple 'healthyverse' packages in a single step. + date_publication: '2024-09-18' + bug_reports: https://github.com/spsanderson/healthyverse/issues + url: https://www.spsanderson.com/healthyverse/ + url_cran: https://CRAN.R-project.org/package=healthyverse + url_git: https://github.com/spsanderson/healthyverse +heapsofpapers: + version: 0.1.0 + title: Easily Download Heaps of PDF and CSV Files + maintainer: Rohan Alexander + description: |- + Makes it easy to download a large number of files such as PDF files + and CSV files, while automatically slowing down requests, letting you know + where it is up to, and adjusting for files that have already been downloaded. + date_publication: '2021-08-23' + bug_reports: https://github.com/RohanAlexander/heapsofpapers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=heapsofpapers + url_git: https://github.com/RohanAlexander/heapsofpapers +heatex: + version: '1.0' + title: Heat exchange calculations during physical activity. + maintainer: Kerry Atkins + description: |- + The heatex package calculates heat storage in the body and + the components of heat exchange (conductive, convective, + radiative, and evaporative) between the body and the + environment during physical activity based on the principles of + partitional calorimetry. The program enables heat exchange + calculations for a range of environmental conditions when + wearing various clothing ensembles. + date_publication: '2013-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heatex + url_git: '' +heatmap3: + version: 1.1.9 + title: An Improved Heatmap Package + maintainer: Shilin Zhao + description: |- + An improved heatmap package. Completely + compatible with the original R function 'heatmap', + and provides more powerful and convenient features. + date_publication: '2021-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heatmap3 + url_git: '' +heatmapFit: + version: 2.0.4 + title: Fit Statistic for Binary Dependent Variable Models + maintainer: Justin Esarey + description: |- + Generates a fit plot for diagnosing misspecification in models of + binary dependent variables, and calculates the related heatmap fit + statistic described in Esarey and Pierce (2012) . + date_publication: '2016-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heatmapFit + url_git: '' +heatmapFlex: + version: 0.1.2 + title: Tools to Generate Flexible Heatmaps + maintainer: Vidal Fey + description: |- + A set of tools supporting more flexible heatmaps. The graphics is grid-like using + the old graphics system. The main function is heatmap.n2(), which is a wrapper around the various functions + constructing individual parts of the heatmap, like sidebars, picket plots, legends etc. The function supports zooming + and splitting, i.e., having (unlimited) small heatmaps underneath each other in one plot deriving from the same data set, + e.g., clustered and ordered by a supervised clustering method. + date_publication: '2021-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heatmapFlex + url_git: '' +heatmaply: + version: 1.5.0 + title: Interactive Cluster Heat Maps Using 'plotly' and 'ggplot2' + maintainer: Tal Galili + description: |- + Create interactive cluster 'heatmaps' that can be saved as a stand- + alone HTML file, embedded in 'R Markdown' documents or in a 'Shiny' app, and + available in the 'RStudio' viewer pane. Hover the mouse pointer over a cell to + show details or drag a rectangle to zoom. A 'heatmap' is a popular graphical + method for visualizing high-dimensional data, in which a table of numbers + are encoded as a grid of colored cells. The rows and columns of the matrix + are ordered to highlight patterns and are often accompanied by 'dendrograms'. + 'Heatmaps' are used in many fields for visualizing observations, correlations, + missing values patterns, and more. Interactive 'heatmaps' allow the inspection + of specific value by hovering the mouse over a cell, as well as zooming into + a region of the 'heatmap' by dragging a rectangle around the relevant area. + This work is based on the 'ggplot2' and 'plotly.js' engine. It produces + similar 'heatmaps' to 'heatmap.2' with the advantage of speed + ('plotly.js' is able to handle larger size matrix), the ability to zoom from + the 'dendrogram' panes, and the placing of factor variables in the sides of the + 'heatmap'. + date_publication: '2023-10-06' + bug_reports: https://github.com/talgalili/heatmaply/issues + url: https://talgalili.github.io/heatmaply/ + url_cran: https://CRAN.R-project.org/package=heatmaply + url_git: https://github.com/talgalili/heatmaply/ +heatwaveR: + version: 0.4.6 + title: Detect Heatwaves and Cold-Spells + maintainer: Robert W. Schlegel + description: |- + The different methods for defining, detecting, and categorising the extreme events + known as heatwaves or cold-spells, as first proposed in Hobday et al. (2016) + and Hobday et al. (2018) . The functions in this package work on both air + and water temperature data. These detection algorithms may be used on non-temperature data as well. + date_publication: '2021-10-27' + bug_reports: https://github.com/robwschlegel/heatwaveR/issues + url: https://robwschlegel.github.io/heatwaveR/index.html + url_cran: https://CRAN.R-project.org/package=heatwaveR + url_git: https://github.com/robwschlegel/heatwaveR +heck: + version: 0.1.3 + title: Highly Performant String Case Converter + maintainer: Dyfan Jones + description: |- + Provides a case conversion between common cases like CamelCase and + snake_case. Using the 'rust crate heck' + as the backend for a highly performant case conversion for 'R'. + date_publication: '2024-09-11' + bug_reports: '' + url: https://dyfanjones.r-universe.dev/heck + url_cran: https://CRAN.R-project.org/package=heck + url_git: https://github.com/DyfanJones/heck +HeckmanEM: + version: 0.2-1 + title: |- + Fit Normal, Student-t or Contaminated Normal Heckman Selection + Models + maintainer: Marcos Prates + description: It performs maximum likelihood estimation for the Heckman selection + model (Normal, Student-t or Contaminated normal) using an EM-algorithm . + It also performs influence diagnostic through global and local influence for four + possible perturbation schema. + date_publication: '2024-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HeckmanEM + url_git: '' +heckmanGE: + version: 1.0.0 + title: |- + Estimation and Inference for Heckman Selection Models with + Cluster-Robust Variance + maintainer: Bastos Fernando de Souza + description: |- + Tools for the estimation of Heckman selection models with robust + variance-covariance matrices. It includes functions for computing the bread + and meat matrices, as well as clustered standard errors for generalized Heckman + models, see Fernando de Souza Bastos and Wagner Barreto-Souza and Marc G. Genton + (2022, ISSN: ). The package also offers + cluster-robust inference with sandwich estimators, and tools for handling issues + related to eigenvalues in covariance matrices. + date_publication: '2024-10-07' + bug_reports: https://github.com/fsbmat-ufv/heckmanGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=heckmanGE + url_git: https://github.com/fsbmat-ufv/heckmanGE +HEDA: + version: 0.1.5 + title: '''Hydropeaking Events Detection Algorithm''' + maintainer: Tingyu Li + description: This tool identifies hydropeaking events from raw time-series flow + record, a rapid flow variation induced by the hourly-adjusted electricity market. + The novelty of 'HEDA' is to use vector angle instead of the first-order derivative + to detect change points which not only largely improves the computing efficiency + but also accounts for the rate of change of the flow variation. More details . + date_publication: '2021-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HEDA + url_git: '' +heddlr: + version: 0.6.0 + title: Dynamic R Markdown Document Generation + maintainer: Michael Mahoney + description: |- + Helper functions designed to make + dynamically generating R Markdown documents easier by providing a + simple and tidy way to create report pieces, shape them to your data, + and combine them for exporting into a single R Markdown document. + date_publication: '2020-03-24' + bug_reports: https://github.com/mikemahoney218/heddlr/issues + url: https://mikemahoney218.github.io/heddlr/ + url_cran: https://CRAN.R-project.org/package=heddlr + url_git: https://github.com/mikemahoney218/heddlr +hedgedrf: + version: 0.0.1 + title: An Implementation of the Hedged Random Forest Algorithm + maintainer: Elliot Beck + description: This algorithm is described in detail in the paper "Hedging Forecast + Combinations With an Application to the Random Forest" by Beck et al. (2023) . + The package provides a function hedgedrf() that can be used to train a Hedged + Random Forest model on a dataset, and a function predict.hedgedrf() that can be + used to make predictions with the model. + date_publication: '2024-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hedgedrf + url_git: '' +hedgehog: + version: '0.1' + title: Property-Based Testing + maintainer: Huw Campbell + description: |- + Hedgehog will eat all your bugs. + 'Hedgehog' is a property-based testing package in the spirit + of 'QuickCheck'. With 'Hedgehog', one can test properties + of their programs against randomly generated input, providing + far superior test coverage compared to unit testing. One of the + key benefits of 'Hedgehog' is integrated shrinking of + counterexamples, which allows one to quickly find the cause of + bugs, given salient examples when incorrect behaviour occurs. + date_publication: '2018-08-22' + bug_reports: https://github.com/hedgehogqa/r-hedgehog/issues + url: https://hedgehog.qa + url_cran: https://CRAN.R-project.org/package=hedgehog + url_git: '' +heemod: + version: 1.0.2 + title: Markov Models for Health Economic Evaluations + maintainer: Kevin Zarca + description: |- + An implementation of the modelling and reporting features described + in reference textbook and guidelines (Briggs, Andrew, et al. Decision + Modelling for Health Economic Evaluation. Oxford Univ. Press, 2011; + Siebert, U. et al. State-Transition Modeling. Medical Decision Making + 32, 690-700 (2012).): deterministic and probabilistic sensitivity analysis, + heterogeneity analysis, time dependency on state-time and model-time + (semi-Markov and non-homogeneous Markov models), etc. + date_publication: '2024-09-11' + bug_reports: https://github.com/aphp/heemod/issues + url: https://aphp.github.io/heemod/ + url_cran: https://CRAN.R-project.org/package=heemod + url_git: '' +heimdall: + version: 1.0.717 + title: Drift Adaptable Models + maintainer: Eduardo Ogasawara + description: By analyzing streaming datasets, it is possible to observe significant + changes in the data distribution or models' accuracy during their prediction (concept + drift). The goal of 'heimdall' is to measure when concept drift occurs. The package + makes available several state-of-the-art methods. It also tackles how to adapt + models in a nonstationary context. Some concept drifts methods are described in + Tavares (2022) . + date_publication: '2024-06-30' + bug_reports: '' + url: https://cefet-rj-dal.github.io/heimdall/ + url_cran: https://CRAN.R-project.org/package=heimdall + url_git: https://github.com/cefet-rj-dal/heimdall +heims: + version: 0.4.0 + title: |- + Decode and Validate HEIMS Data from Department of Education, + Australia + maintainer: Hugh Parsonage + description: Decode elements of the Australian Higher Education Information Management + System (HEIMS) data for clarity and performance. HEIMS is the record system of + the Department of Education, Australia to record enrolments and completions in + Australia's higher education system, as well as a range of relevant information. + For more information, including the source of the data dictionary, see . + date_publication: '2018-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heims + url_git: '' +heiscore: + version: 0.1.4 + title: Score and Plot the Healthy Eating Index from NHANES Data + maintainer: Vijetha Ramdas + description: |- + Calculate and visualize Healthy Eating Index (HEI) scores + from National Health and Nutrition Examination Survey 24-hour dietary + recall data utilizing three methods recommended by the National Cancer + Institute (2024) + . + Effortlessly analyze HEI scores across different demographic groups + and years. + date_publication: '2024-09-26' + bug_reports: https://github.com/abhrastat/heiscore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=heiscore + url_git: https://github.com/abhrastat/heiscore +heiscore.data: + version: 0.0.1 + title: Data Only Package to 'heiscore' + maintainer: Vijetha Ramdas + description: |- + Contains the National Health and Nutrition Examination Survey + 24-hour dietary recall data and Healthy Eating Index scoring standards + used by the 'heiscore' package. + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heiscore.data + url_git: '' +helixvis: + version: 1.0.1 + title: Visualize Alpha-Helical Peptide Sequences + maintainer: Raoul Wadhwa + description: |- + Create publication-quality, 2-dimensional visualizations of alpha-helical peptide + sequences. Specifically, allows the user to programmatically generate + helical wheels and wenxiang diagrams to provide a bird's eye, top-down view of + alpha-helical oligopeptides. See Wadhwa RR, et al. (2018) + for more information. + date_publication: '2018-11-13' + bug_reports: https://github.com/rrrlw/helixvis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=helixvis + url_git: https://github.com/rrrlw/helixvis +HellCor: + version: '1.3' + title: The Hellinger Correlation + maintainer: Pierre Lafaye De Micheaux + description: |- + Empirical value of the Hellinger correlation, a measure of dependence between + two continuous random variables. More details can be found in Geenens and Lafaye De Micheaux (2019) . + date_publication: '2020-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HellCor + url_git: '' +hellno: + version: 0.0.1 + title: |- + Providing 'stringsAsFactors=FALSE' Variants of 'data.frame()' + and 'as.data.frame()' + maintainer: Peter Meissner + description: |- + Base R's default setting for 'stringsAsFactors' within + 'data.frame()' and 'as.data.frame()' is supposedly the most often complained + about piece of code in the R infrastructure. The 'hellno' package provides + an explicit solution without changing R itself or having to mess around with + options. It tries to solve this problem by providing alternative + 'data.frame()' and 'as.data.frame()' functions that are in fact simple + wrappers around base R's 'data.frame()' and 'as.data.frame()' with + 'stringsAsFactors' option set to 'HELLNO' ( which in turn equals FALSE ) + by default. + date_publication: '2015-12-14' + bug_reports: https://github.com/petermeissner/hellno/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hellno + url_git: https://github.com/petermeissner/hellno +helloJavaWorld: + version: 0.0-9 + title: Hello Java World + maintainer: Tobias Verbeke + description: |- + A dummy package to demonstrate how to interface to a jar + file that resides inside an R package. + date_publication: '2014-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=helloJavaWorld + url_git: '' +hellorust: + version: 1.2.2 + title: Minimal Examples of Using Rust Code in R + maintainer: Jeroen Ooms + description: |- + Template R package with minimal setup to use Rust code in R without + hacks or frameworks. Includes basic examples of importing cargo dependencies, + spawning threads and passing numbers or strings from Rust to R. Cargo crates + are automatically 'vendored' in the R source package to support offline + installation. The GitHub repository for this package has more details and also + explains how to set up CI. This project was first presented at 'Erum2018' to + showcase R-Rust integration ; for a real + world use-case, see the 'gifski' package on 'CRAN'. + date_publication: '2024-09-22' + bug_reports: https://github.com/r-rust/hellorust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hellorust + url_git: https://github.com/r-rust/hellorust +HelpersMG: + version: '6.4' + title: |- + Tools for Environmental Analyses, Ecotoxicology and Various R + Functions + maintainer: Marc Girondot + description: Contains miscellaneous functions useful for managing 'NetCDF' files + (see ), get moon phase and time for sun + rise and fall, tide level, analyse and reconstruct periodic time series of temperature + with irregular sinusoidal pattern, show scales and wind rose in plot with change + of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot + graphs or boxplot with error bars, search files in disk by there names or their + content, read the contents of all files from a folder at one time. + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HelpersMG + url_git: '' +helsinki: + version: 1.0.6 + title: R Tools for Helsinki Open Data + maintainer: Juuso Parkkinen + description: |- + Tools for accessing various open data APIs in the Helsinki + region in Finland. Current data sources include the Service Map API, + Linked Events API, and Helsinki Region Infoshare statistics API. + date_publication: '2022-12-02' + bug_reports: https://github.com/ropengov/helsinki/issues + url: http://ropengov.github.io/helsinki/ + url_cran: https://CRAN.R-project.org/package=helsinki + url_git: https://github.com/rOpenGov/helsinki +HEMDAG: + version: 2.7.4 + title: Hierarchical Ensemble Methods for Directed Acyclic Graphs + maintainer: Marco Notaro + description: 'An implementation of several Hierarchical Ensemble Methods (HEMs) + for Directed Acyclic Graphs (DAGs). ''HEMDAG'' package: 1) reconciles flat predictions + with the topology of the ontology; 2) can enhance the predictions of virtually + any flat learning methods by taking into account the hierarchical relationships + between ontology classes; 3) provides biologically meaningful predictions that + always obey the true-path-rule, the biological and logical rule that governs the + internal coherence of biomedical ontologies; 4) is specifically designed for exploiting + the hierarchical relationships of DAG-structured taxonomies, such as the Human + Phenotype Ontology (HPO) or the Gene Ontology (GO), but can be safely applied + to tree-structured taxonomies as well (as FunCat), since trees are DAGs; 5) scales + nicely both in terms of the complexity of the taxonomy and in the cardinality + of the examples; 6) provides several utility functions to process and analyze + graphs; 7) provides several performance metrics to evaluate HEMs algorithms. (Marco + Notaro, Max Schubach, Peter N. Robinson and Giorgio Valentini (2017) ).' + date_publication: '2021-02-12' + bug_reports: https://github.com/marconotaro/hemdag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HEMDAG + url_git: https://hemdag.readthedocs.iohttps://github.com/marconotaro/hemdaghttps://anaconda.org/bioconda/r-hemdag +hemispheR: + version: 1.1.4 + title: Processing Hemispherical Canopy Images + maintainer: Francesco Chianucci + description: Import and classify canopy fish-eye images, estimate angular gap fraction + and derive canopy attributes like leaf area index and openness. Additional information + is provided in the study by Chianucci F., Macek M. (2023) . + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hemispheR + url_git: '' +heplots: + version: 1.7.3 + title: Visualizing Hypothesis Tests in Multivariate Linear Models + maintainer: Michael Friendly + description: |- + Provides HE plot and other functions for visualizing hypothesis + tests in multivariate linear models. HE plots represent sums-of-squares-and-products + matrices for linear hypotheses and for error using ellipses (in two + dimensions) and ellipsoids (in three dimensions). The related 'candisc' package + provides visualizations in a reduced-rank canonical discriminant space when + there are more than a few response variables. + date_publication: '2024-12-22' + bug_reports: https://github.com/friendly/heplots/issues + url: http://friendly.github.io/heplots/ + url_cran: https://CRAN.R-project.org/package=heplots + url_git: '' +here: + version: 1.0.1 + title: A Simpler Way to Find Your Files + maintainer: Kirill Müller + description: |- + Constructs paths to your project's files. + Declare the relative path of a file within your project with 'i_am()'. + Use the 'here()' function as a drop-in replacement for 'file.path()', + it will always locate the files relative to your project root. + date_publication: '2020-12-13' + bug_reports: https://github.com/r-lib/here/issues + url: https://here.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=here + url_git: https://github.com/r-lib/here +hereR: + version: 1.1.0 + title: '''sf''-Based Interface to the ''HERE'' REST APIs' + maintainer: Merlin Unterfinger + description: |- + Interface to the 'HERE' REST APIs : + (1) geocode and autosuggest addresses or reverse geocode POIs using the 'Geocoder' API; + (2) route directions, travel distance or time matrices and isolines using the 'Routing', 'Matrix Routing' and 'Isoline Routing' APIs; + (3) request real-time traffic flow and incident information from the 'Traffic' API; + (4) find request public transport connections and nearby stations from the 'Public Transit' API; + (5) request intermodal routes using the 'Intermodal Routing' API; + (6) get weather forecasts, reports on current weather conditions, astronomical + information and alerts at a specific location from the 'Destination Weather' API. + Locations, routes and isolines are returned as 'sf' objects. + date_publication: '2025-02-20' + bug_reports: https://github.com/munterfi/hereR/issues/ + url: https://munterfi.github.io/hereR/ + url_cran: https://CRAN.R-project.org/package=hereR + url_git: https://github.com/munterfi/hereR/ +heritability: + version: '1.4' + title: |- + Marker-Based Estimation of Heritability Using Individual Plant + or Plot Data + maintainer: Willem Kruijer + description: Implements marker-based estimation of heritability when observations + on genetically identical replicates are available. These can be either observations + on individual plants or plot-level data in a field trial. Heritability can then + be estimated using a mixed model for the individual plant or plot data. For comparison, + also mixed-model based estimation using genotypic means and estimation of repeatability + with ANOVA are implemented. For illustration the package contains several datasets + for the model species Arabidopsis thaliana. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heritability + url_git: '' +HeritSeq: + version: 1.0.2 + title: Heritability of Gene Expression for Next-Generation Sequencing + maintainer: W. Jenny Shi + description: |- + Statistical framework to analyze heritability of gene expression + based on next-generation sequencing data and simulating sequencing reads. + Variance partition coefficients (VPC) are computed using linear mixed effects + and generalized linear mixed effects models. Compound Poisson and negative + binomial models are included. Reference: Rudra, Pratyaydipta, et al. "Model based heritability scores for high-throughput sequencing data." BMC bioinformatics 18.1 (2017): 143. + date_publication: '2021-07-12' + bug_reports: https://github.com/KechrisLab/HeritSeq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HeritSeq + url_git: '' +hermite: + version: 1.1.2 + title: Generalized Hermite Distribution + maintainer: David Moriña Soler + description: Probability functions and other utilities for the generalized Hermite + distribution. + date_publication: '2018-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hermite + url_git: '' +hermiter: + version: 2.3.1 + title: |- + Efficient Sequential and Batch Estimation of Univariate and + Bivariate Probability Density Functions and Cumulative + Distribution Functions along with Quantiles (Univariate) and + Nonparametric Correlation (Bivariate) + maintainer: Michael Stephanou + description: |- + Facilitates estimation of full univariate and bivariate + probability density functions and cumulative distribution functions along with + full quantile functions (univariate) and nonparametric correlation + (bivariate) using Hermite series based estimators. These estimators are + particularly useful in the sequential setting (both stationary and + non-stationary) and one-pass batch estimation setting for large data sets. + Based on: Stephanou, Michael, Varughese, Melvin and Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 , + Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) and Stephanou, Michael and Varughese, Melvin. "Sequential estimation of Spearman rank correlation using Hermite series estimators." Journal of Multivariate Analysis (2021) . + date_publication: '2024-03-06' + bug_reports: https://github.com/MikeJaredS/hermiter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hermiter + url_git: https://github.com/MikeJaredS/hermiter +hero: + version: '0.6' + title: Spatio-Temporal (Hero) Sandwich Smoother + maintainer: Joshua French + description: 'An implementation of the sandwich smoother proposed in Fast Bivariate + Penalized Splines by Xiao et al. (2012) . A hero is + a specific type of sandwich. Dictionary.com (2018) + describes a hero as: a large sandwich, usually consisting of a small loaf of bread + or long roll cut in half lengthwise and containing a variety of ingredients, as + meat, cheese, lettuce, and tomatoes. Also implements the spatio-temporal sandwich + smoother of French and Kokoszka (2021) .' + date_publication: '2023-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hero + url_git: '' +hesim: + version: 0.5.5 + title: Health Economic Simulation Modeling and Decision Analysis + maintainer: Devin Incerti + description: |- + A modular and computationally efficient R package for + parameterizing, simulating, and analyzing health economic simulation + models. The package supports cohort discrete time state transition models + (Briggs et al. 1998) , + N-state partitioned survival models (Glasziou et al. 1990) + , and individual-level continuous + time state transition models (Siebert et al. 2012) , + encompassing both Markov (time-homogeneous and time-inhomogeneous) and + semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is + quantified with standard graphical and tabular summaries of a probabilistic + sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) , + . Use of C++ and data.table + make individual-patient simulation, probabilistic sensitivity analysis, + and incorporation of patient heterogeneity fast. + date_publication: '2024-09-18' + bug_reports: https://github.com/hesim-dev/hesim/issues + url: https://hesim-dev.github.io/hesim/ + url_cran: https://CRAN.R-project.org/package=hesim + url_git: https://github.com/hesim-dev/hesim +HEssRNA: + version: 1.0.1 + title: Heritability-Based Estimation of Sample Size for RNA-Seq Data + maintainer: Sarika Jaiswal + description: Provides tools for estimating sample sizes primarily based on heritability, + while also considering additional parameters such as statistical power and fold + change. The package normalizes heritability values according to trait-specific + heritability and classification to enhance accuracy in sample size estimation. + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HEssRNA + url_git: '' +HeterFunctionalData: + version: 0.1.0 + title: Test of No Main and/or Interaction Effects in Functional Data + maintainer: Haiyan Wang + description: |- + Distribution free heteroscedastic tests for functional data. + The following tests are included in this package: test of no main treatment or contrast + effect and no simple treatment effect given in + Wang, Higgins, and Blasi (2010) , + no main time effect, and no interaction effect based on + original observations given in Wang and Akritas (2010a) + + and tests based on ranks given in Wang and Akritas (2010b) + . + date_publication: '2020-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HeterFunctionalData + url_git: '' +heterocop: + version: 0.1.0.0 + title: Semi-Parametric Estimation with Gaussian Copula + maintainer: Ekaterina Tomilina + description: A method for generating random vectors which are linked by a Gaussian + copula. It also enables to estimate the correlation matrix of the Gaussian copula + in order to identify independencies within the data. + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heterocop + url_git: '' +heterogen: + version: 1.2.33 + title: Spatial Functions for Heterogeneity and Climate Variability + maintainer: P.Joser Atauchi + description: |- + A comprehensive suite of spatial + functions created to analyze and assess data heterogeneity and climate variability + in spatial datasets. This package is specifically designed to address the challenges associated + with characterizing and understanding complex spatial patterns in environmental and climate-related data. + date_publication: '2023-08-17' + bug_reports: https://github.com/patauchi/heterogen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=heterogen + url_git: https://github.com/patauchi/heterogen +HeteroGGM: + version: 1.0.1 + title: Gaussian Graphical Model-Based Heterogeneity Analysis + maintainer: Mingyang Ren + description: |- + The goal of this package is to user-friendly realizing Gaussian + graphical model-based heterogeneity analysis. + Recently, several Gaussian graphical model-based heterogeneity + analysis techniques have been developed. A common methodological limitation + is that the number of subgroups is assumed to be known a priori, which + is not realistic. In a very recent study (Ren et al., 2022), a novel approach + based on the penalized fusion technique is developed to fully + data-dependently determine the number and structure of subgroups in + Gaussian graphical model-based heterogeneity analysis. It opens the door for utilizing + the Gaussian graphical model technique in more practical settings. Beyond + Ren et al. (2022), more estimations and functions are added, so + that the package is self-contained and more comprehensive and can + provide ``more direct'' insights to practitioners (with the + visualization function). Reference: + Ren, M., Zhang S., Zhang Q. and Ma S. (2022). Gaussian Graphical + Model-based Heterogeneity Analysis via Penalized Fusion. + Biometrics, 78 (2), 524-535. + date_publication: '2023-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HeteroGGM + url_git: '' +heterometa: + version: '0.3' + title: Convert Various Meta-Analysis Heterogeneity Measures + maintainer: Michael Dewey + description: |- + Published meta-analyses routinely present one of the + measures of heterogeneity introduced in Higgins and Thompson + (2002) . For critiquing articles + it is often better to convert to another of + those measures. Some + conversions are provided here and confidence intervals are also + available. + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heterometa + url_git: '' +heteromixgm: + version: 2.0.2 + title: Copula Graphical Models for Heterogeneous Mixed Data + maintainer: Sjoerd Hermes + description: A multi-core R package that allows for the statistical modeling of + multi-group multivariate mixed data using Gaussian graphical models. Combining + the Gaussian copula framework with the fused graphical lasso penalty, the 'heteromixgm' + package can handle a wide variety of datasets found in various sciences. The package + also includes an option to perform model selection using the AIC, BIC and EBIC + information criteria, a function that plots partial correlation graphs based on + the selected precision matrices, as well as simulate mixed heterogeneous data + for exploratory or simulation purposes and one multi-group multivariate mixed + agricultural dataset pertaining to maize yields. The package implements the methodological + developments found in Hermes et al. (2024) . + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=heteromixgm + url_git: '' +hetGP: + version: 1.1.7 + title: |- + Heteroskedastic Gaussian Process Modeling and Design under + Replication + maintainer: Mickael Binois + description: Performs Gaussian process regression with heteroskedastic noise following + the model by Binois, M., Gramacy, R., Ludkovski, M. (2016) , + with implementation details in Binois, M. & Gramacy, R. B. (2021) . + The input dependent noise is modeled as another Gaussian process. Replicated observations + are encouraged as they yield computational savings. Sequential design procedures + based on the integrated mean square prediction error and lookahead heuristics + are provided, and notably fast update functions when adding new observations. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hetGP + url_git: '' +HEtools: + version: 1.0.0 + title: Homomorphic Encryption Polynomials + maintainer: Bastiaan Quast + description: Homomorphic encryption (Brakerski and Vaikuntanathan (2014) ) + using Ring Learning with Errors (Lyubashevsky et al. (2012) ) + is a form of Learning with Errors (Regev (2005) ) + using polynomial rings over finite fields. Functions to generate the required + polynomials (using 'polynom'), with various distributions of coefficients are + provided. Additionally, functions to generate and take coefficient modulo are + provided. + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HEtools + url_git: '' +HETOP: + version: 0.2-6 + title: |- + MLE and Bayesian Estimation of Heteroskedastic Ordered Probit + (HETOP) Model + maintainer: J.R. Lockwood + description: Provides functions for maximum likelihood and Bayesian estimation of + the Heteroskedastic Ordered Probit (HETOP) model, using methods described in Lockwood, + Castellano and Shear (2018) and Reardon, Shear, + Castellano and Ho (2017) . It also provides a general + function to compute the triple-goal estimators of Shen and Louis (1998) . + date_publication: '2019-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HETOP + url_git: '' +HetSeq: + version: 0.1.0 + title: |- + Identifying Modulators of Cellular Responses Leveraging + Intercellular Heterogeneity + maintainer: Kevin Berg + description: |- + Cellular responses to perturbations are highly heterogeneous + and depend largely on the initial state of cells. Connecting + post-perturbation cells via cellular trajectories to untreated cells + (e.g. by leveraging metabolic labeling information) enables + exploitation of intercellular heterogeneity as a combined knock-down + and overexpression screen to identify pathway modulators, termed + Heterogeneity-seq (see 'Berg et al' ). + This package contains functions to generate cellular trajectories based + on scSLAM-seq (single-cell, thiol-(SH)-linked alkylation of RNA for + metabolic labelling sequencing) time courses, functions to identify + pathway modulators and to visualize the results. + date_publication: '2025-02-03' + bug_reports: https://github.com/erhard-lab/HetSeq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HetSeq + url_git: https://github.com/erhard-lab/HetSeq +hetsurr: + version: '1.0' + title: Assessing Heterogeneity in the Utility of a Surrogate Marker + maintainer: Layla Parast + description: 'Provides a function to assess and test for heterogeneity in the utility + of a surrogate marker with respect to a baseline covariate. The main function + can be used for either a continuous or discrete baseline covariate. More details + will be available in the future in: Parast, L., Cai, T., Tian L (2021). "Testing + for Heterogeneity in the Utility of a Surrogate Marker." Biometrics, In press.' + date_publication: '2021-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hetsurr + url_git: '' +hetsurrSurv: + version: '1.0' + title: Assessing Heterogeneity in Surrogacy Using Censored Data + maintainer: Layla Parast + description: Provides functions to assess and test for heterogeneity in the utility + of a surrogate marker with respect to a baseline covariate using censored (survival + data), and to test for heterogeneity across multiple time points. More details + are available in Parast et al (2024) . + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hetsurrSurv + url_git: '' +hett: + version: 0.3-3 + title: Heteroscedastic t-Regression + maintainer: Julian Taylor + description: Functions for the fitting and summarizing of heteroscedastic t-regression. + date_publication: '2020-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hett + url_git: '' +hettest: + version: '1.0' + title: |- + Testing for a Treatment Effect Using a Heterogeneous Surrogate + Marker + maintainer: Layla Parast + description: Tests for a treatment effect using surrogate marker information accounting + for heterogeneity in the utility of the surrogate. Details are described in Parast + et al (2022) . + date_publication: '2022-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hettest + url_git: '' +hettreatreg: + version: 0.1.0 + title: Heterogeneous Treatment Effects in Regression Analysis + maintainer: Mark McAvoy + description: |- + Computes diagnostics for linear regression when treatment effects are heterogeneous. + The output of 'hettreatreg' represents ordinary least squares (OLS) + estimates of the effect of a binary treatment as a weighted average of the average treatment effect + on the treated (ATT) and the average treatment effect on the untreated (ATU). + The program estimates the OLS weights on these parameters, computes the associated model diagnostics, + and reports the implicit OLS estimate of the average treatment effect (ATE). + See Sloczynski (2019), . + date_publication: '2020-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hettreatreg + url_git: https://github.com/tslocz/hettreatreg +hettx: + version: 0.1.3 + title: |- + Fisherian and Neymanian Methods for Detecting and Measuring + Treatment Effect Variation + maintainer: Ben Fifield + description: |- + Implements methods developed by Ding, Feller, and Miratrix (2016) , + and Ding, Feller, and Miratrix (2018) + for testing whether there is unexplained variation in treatment effects across observations, and for characterizing + the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions + implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test. + date_publication: '2023-08-19' + bug_reports: https://github.com/bfifield/hettx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hettx + url_git: '' +hetu: + version: 1.1.0 + title: Structural Handling of Finnish Personal Identity Codes + maintainer: Pyry Kantanen + description: |- + Structural handling of Finnish identity codes (natural persons and + organizations); extract information, check ID validity and diagnostics. + date_publication: '2024-12-04' + bug_reports: https://github.com/ropengov/hetu/issues + url: https://ropengov.github.io/hetu/ + url_cran: https://CRAN.R-project.org/package=hetu + url_git: https://github.com/ropengov/hetu +heumilkr: + version: 0.2.0 + title: Heuristic Capacitated Vehicle Routing Problem Solver + maintainer: Lukas Schneiderbauer + description: Implements the Clarke-Wright algorithm to find a quasi-optimal solution + to the Capacitated Vehicle Routing Problem. See Clarke, G. and Wright, J.R. (1964) + for details. The implementation is accompanied by + helper functions to inspect its solution. + date_publication: '2024-04-01' + bug_reports: https://github.com/lschneiderbauer/heumilkr/issues + url: https://lschneiderbauer.github.io/heumilkr/ + url_cran: https://CRAN.R-project.org/package=heumilkr + url_git: https://github.com/lschneiderbauer/heumilkr +heuristica: + version: 1.0.3 + title: Heuristics Including Take the Best and Unit-Weight Linear + maintainer: Jean Whitmore + description: |- + Implements various heuristics like Take The Best and + unit-weight linear, which do two-alternative choice: which of + two objects will have a higher criterion? Also offers functions + to assess performance, e.g. percent correct across all row pairs + in a data set and finding row pairs where models disagree. + New models can be added by implementing a fit and predict function-- + see vignette. Take The Best was first described in: Gigerenzer, G. + & Goldstein, D. G. (1996) . All + of these heuristics were run on many data sets and analyzed in: + Gigerenzer, G., Todd, P. M., & the ABC Group (1999). + . + date_publication: '2021-09-08' + bug_reports: https://github.com/jeanimal/heuristica/issues + url: '' + url_cran: https://CRAN.R-project.org/package=heuristica + url_git: https://github.com/jeanimal/heuristica +heuristicsmineR: + version: 0.3.0 + title: Discovery of Process Models with the Heuristics Miner + maintainer: Felix Mannhardt + description: |- + Provides the heuristics miner algorithm for process discovery + as proposed by Weijters et al. (2011) . The + algorithm builds a causal net from an event log created with the 'bupaR' + package. Event logs are a set of ordered sequences of events for which + 'bupaR' provides the S3 class eventlog(). The discovered causal nets + can be visualised as 'htmlwidgets' and it is possible to annotate them with + the occurrence frequency or processing and waiting time of process + activities. + date_publication: '2023-04-04' + bug_reports: https://github.com/bupaverse/heuristicsmineR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=heuristicsmineR + url_git: https://github.com/bupaverse/heuristicsmineR +hexbin: + version: 1.28.5 + title: Hexagonal Binning Routines + maintainer: Edzer Pebesma + description: Binning and plotting functions for hexagonal bins. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hexbin + url_git: https://github.com/edzer/hexbin +hexDensity: + version: 1.4.8 + title: Fast Kernel Density Estimation with Hexagonal Grid + maintainer: Quoc Hoang Nguyen + description: |- + Kernel density estimation with hexagonal grid for bivariate data. + Hexagonal grid has many beneficial properties like equidistant neighbours + and less edge bias, making it better for spatial analyses than the more + commonly used rectangular grid. + Carr, D. B. et al. (1987) . + Diggle, P. J. (2010) . + Hill, B. (2017) . + Jones, M. C. (1993) . + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hexDensity + url_git: https://github.com/ChenLaboratory/hexDensity +hexfont: + version: 0.5.1 + title: '''GNU Unifont'' Hex Fonts' + maintainer: Trevor L. Davis + description: Contains most of the hex font files from the 'GNU Unifont Project' + compressed by 'xz'. 'GNU Unifont' is a duospaced + bitmap font that attempts to cover all the official Unicode glyphs plus several + of the artificial scripts in the '(Under-)ConScript Unicode Registry' . Provides + a convenience function for loading in several of them at the same time as a 'bittermelon' + bitmap font object for easy rendering of the glyphs in an 'R' terminal or graphics + device. + date_publication: '2024-12-12' + bug_reports: https://github.com/trevorld/hexfont/issues + url: https://trevorldavis.com/R/hexfont/ + url_cran: https://CRAN.R-project.org/package=hexfont + url_git: https://github.com/trevorld/hexfont +hexSticker: + version: 0.4.9 + title: Create Hexagon Sticker in R + maintainer: Guangchuang Yu + description: Helper functions for creating reproducible hexagon sticker purely in + R. + date_publication: '2020-12-05' + bug_reports: https://github.com/GuangchuangYu/hexSticker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hexSticker + url_git: https://github.com/GuangchuangYu/hexSticker +HextractoR: + version: '1.4' + title: Integrated Tool for Hairping Extraction of RNA Sequences + maintainer: Cristian Yones + description: Simple and integrated tool that automatically extracts and folds all + hairpin sequences from raw genome-wide data. It predicts the secondary structure + of several overlapped segments, with longer length than the mean length of sequences + of interest for the species under processing, ensuring that no one is lost nor + inappropriately cut. + date_publication: '2019-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HextractoR + url_git: '' +hextri: + version: 0.9.17 + title: Hexbin Plots with Triangles + maintainer: Thomas Lumley + description: Display hexagonally binned scatterplots for multi-class data, using + coloured triangles to show class proportions. + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hextri + url_git: '' +hexView: + version: 0.3-4 + title: Viewing Binary Files + maintainer: Paul Murrell + description: Functions to view files in raw binary form like in a hex editor. Additional + functions to specify and read arbitrary binary formats. + date_publication: '2019-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hexView + url_git: '' +hfhub: + version: 0.1.1 + title: Hugging Face Hub Interface + maintainer: Daniel Falbel + description: |- + Provides functionality to download and cache files from 'Hugging Face Hub' . + Uses the same caching structure so files can be shared between different client libraries. + date_publication: '2023-08-18' + bug_reports: '' + url: https://mlverse.github.io/hfhub/ + url_cran: https://CRAN.R-project.org/package=hfhub + url_git: '' +hflights: + version: '0.1' + title: Flights that departed Houston in 2011 + maintainer: Hadley Wickham + description: A data only package containing commercial domestic flights thatdeparted + Houston (IAH and HOU) in 2011. + date_publication: '2013-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hflights + url_git: '' +hfr: + version: 0.7.1 + title: Estimate Hierarchical Feature Regression Models + maintainer: Johann Pfitzinger + description: Provides functions for the estimation, plotting, predicting and cross-validation + of hierarchical feature regression models as described in Pfitzinger (2024). Cluster + Regularization via a Hierarchical Feature Regression. Econometrics and Statistics + (in press). . + date_publication: '2024-02-27' + bug_reports: '' + url: https://hfr.residualmetrics.com + url_cran: https://CRAN.R-project.org/package=hfr + url_git: https://github.com/jpfitzinger/hfr +HGDMr: + version: 1.0.0 + title: Hysteretic and Gatekeeping Depressions Model + maintainer: Kevin Shook + description: Implementation of the Hysteretic and Gatekeeping Depressions Model + (HGDM) which calculates variable connected/contributing areas and resulting discharge + volumes in prairie basins dominated by depressions ("slough" or "potholes"). The + small depressions are combined into a single "meta" depression which explicitly + models the hysteresis between the storage of water and the connected/contributing + areas of the depressions. The largest (greater than 5% of the total depressional + area) depression (if it exists) is represented separately to model its gatekeeping, + i.e. the blocking of upstream flows until it is filled. The methodolgy is described + in detail in Shook and Pomeroy (2025, ). + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HGDMr + url_git: https://github.com/CentreForHydrology/HGDMr +hglasso: + version: '1.3' + title: Learning Graphical Models with Hubs + maintainer: Kean Ming Tan + description: Implements the hub graphical lasso and hub covariance graph proposal + by Tan, KM., London, P., Mohan, K., Lee, S-I., Fazel, M., and Witten, D. (2014). + Learning graphical models with hubs. Journal of Machine Learning Research 15(Oct):3297-3331. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hglasso + url_git: '' +hglm: + version: 2.2-1 + title: Hierarchical Generalized Linear Models + maintainer: Xia Shen + description: 'Implemented here are procedures for fitting hierarchical generalized + linear models (HGLM). It can be used for linear mixed models and generalized linear + mixed models with random effects for a variety of links and a variety of distributions + for both the outcomes and the random effects. Fixed effects can also be fitted + in the dispersion part of the mean model. As statistical models, HGLMs were initially + developed by Lee and Nelder (1996) . + We provide an implementation (Ronnegard, Alam and Shen 2010) + following Lee, Nelder and Pawitan (2006) with algorithms + extended for spatial modeling (Alam, Ronnegard and Shen 2015) .' + date_publication: '2019-04-04' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=558 + url: '' + url_cran: https://CRAN.R-project.org/package=hglm + url_git: '' +hglm.data: + version: 1.0-1 + title: Data for the 'hglm' Package + maintainer: Xia Shen + description: This data-only package was created for distributing data used in the + examples of the 'hglm' package. + date_publication: '2019-04-04' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=558 + url: '' + url_cran: https://CRAN.R-project.org/package=hglm.data + url_git: '' +hgm: + version: '1.23' + title: Holonomic Gradient Method and Gradient Descent + maintainer: Nobuki Takayama + description: |- + The holonomic gradient method (HGM, hgm) gives a way to evaluate normalization + constants of unnormalized probability distributions by utilizing holonomic + systems of differential or difference equations. The holonomic gradient descent (HGD, hgd) gives a method + to find maximal likelihood estimates by utilizing the HGM. + date_publication: '2023-01-31' + bug_reports: '' + url: http://www.openxm.org + url_cran: https://CRAN.R-project.org/package=hgm + url_git: '' +HGMND: + version: 0.1.0 + title: Heterogeneous Graphical Model for Non-Negative Data + maintainer: Jiaqi Zhang + description: Graphical model is an informative and powerful tool to explore the + conditional dependence relationships among variables. The traditional Gaussian + graphical model and its extensions either have a Gaussian assumption on the data + distribution or assume the data are homogeneous. However, there are data with + complex distributions violating these two assumptions. For example, the air pollutant + concentration records are non-negative and, hence, non-Gaussian. Moreover, due + to climate changes, distributions of these concentration records in different + months of a year can be far different, which means it is uncertain whether datasets + from different months are homogeneous. Methods with a Gaussian or homogeneous + assumption may incorrectly model the conditional dependence relationships among + variables. Therefore, we propose a heterogeneous graphical model for non-negative + data (HGMND) to simultaneously cluster multiple datasets and estimate the conditional + dependence matrix of variables from a non-Gaussian and non-negative exponential + family in each cluster. + date_publication: '2021-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HGMND + url_git: '' +hgnc: + version: 0.1.4 + title: |- + Download and Import the HUGO Gene Nomenclature Committee + ('HGNC') Data Set into R + maintainer: Ramiro Magno + description: |- + A set of routines to quickly download and import the 'HGNC' + data set on mapping of gene symbols to gene entries in other popular + databases or resources. + date_publication: '2023-08-29' + bug_reports: https://github.com/ramiromagno/hgnc/issues + url: https://rmagno.eu/hgnc/ + url_cran: https://CRAN.R-project.org/package=hgnc + url_git: https://github.com/ramiromagno/hgnc +HGNChelper: + version: 0.8.15 + title: |- + Identify and Correct Invalid HGNC Human Gene Symbols and MGI + Mouse Gene Symbols + maintainer: Levi Waldron + description: |- + Contains functions for + identifying and correcting HGNC human gene symbols and MGI mouse gene symbols + which have been converted to date format by Excel, withdrawn, or aliased. + Also contains functions for reversibly converting between HGNC + symbols and valid R names. + date_publication: '2024-11-16' + bug_reports: https://github.com/waldronlab/HGNChelper/issues + url: https://waldronlab.io/HGNChelper/ + url_cran: https://CRAN.R-project.org/package=HGNChelper + url_git: https://github.com/waldronlab/HGNChelper +HGraph: + version: 0.1.0 + title: Use Graph Structure to Travel + maintainer: Jinan Pang + description: |- + It is used to travel graphs, by using DFS and BFS to get the path from node to each leaf node. + Depth first traversal(DFS) is a recursive algorithm for searching all the vertices of a graph or tree data structure. + Traversal means visiting all the nodes of a graph. + Breadth first traversal(BFS) algorithm is used to search a tree or graph data structure for a node that meets a set of criteria. + It starts at the tree’s root or graph and searches/visits all nodes at the current depth level before moving on to the nodes at the next depth level. + Also, it provides the matrix which is reachable between each node. + Implement reference about Baruch Awerbuch (1985) . + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HGraph + url_git: '' +HGSL: + version: 1.0.0 + title: Heterogeneous Group Square-Root Lasso + maintainer: Yongjian Kang + description: 'Estimation of high-dimensional multi-response regression with heterogeneous + noises under Heterogeneous group square-root Lasso penalty. For details see: Ren, + Z., Kang, Y., Fan, Y. and Lv, J. (2018).' + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HGSL + url_git: '' +hgutils: + version: 0.2.13 + title: Collection of Utility Functions + maintainer: H.G. van den Boorn + description: |- + A handy collection of utility functions designed to aid in + package development, plotting and scientific research. Package + development functionalities includes among others tools such as + cross-referencing package imports with the description file, analysis + of redundant package imports, editing of the description file and the + creation of package badges for GitHub. Some of the other + functionalities include automatic package installation and loading, + plotting points without overlap, creating nice breaks for plots, + overview tables and many more handy utility functions. + date_publication: '2024-11-17' + bug_reports: https://github.com/hvdboorn/hgutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hgutils + url_git: https://github.com/hvdboorn/hgutils +hgwrr: + version: 0.6-1 + title: Hierarchical and Geographically Weighted Regression + maintainer: Yigong Hu + description: |- + This model divides coefficients into three types, + i.e., local fixed effects, global fixed effects, and random effects (Hu et al., 2022). + If data have spatial hierarchical structures (especially are overlapping on some locations), + it is worth trying this model to reach better fitness. + date_publication: '2024-11-16' + bug_reports: '' + url: https://hpdell.github.io/hgwrr/ + url_cran: https://CRAN.R-project.org/package=hgwrr + url_git: https://github.com/HPDell/hgwrr/ +HH: + version: 3.1-53 + title: 'Statistical Analysis and Data Display: Heiberger and Holland' + maintainer: Richard M. Heiberger + description: Support software for Statistical Analysis and Data Display (Second + Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, + ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary + presentation of statistical methods features extensive use of graphical displays + for exploring data and for displaying the analysis. The second edition includes + redesigned graphics and additional chapters. The authors emphasize how to construct + and interpret graphs, discuss principles of graphical design, and show how accompanying + traditional tabular results are used to confirm the visual impressions derived + directly from the graphs. Many of the graphical formats are novel and appear here + for the first time in print. All chapters have exercises. All functions introduced + in the book are in the package. R code for all examples, both graphs and tables, + in the book is included in the scripts directory of the package. + date_publication: '2025-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HH + url_git: '' +hhh4contacts: + version: 0.13.4 + title: |- + Age-Structured Spatio-Temporal Models for Infectious Disease + Counts + maintainer: Sebastian Meyer + description: |- + Meyer and Held (2017) present an + age-structured spatio-temporal model for infectious disease counts. The + approach is illustrated in a case study on norovirus gastroenteritis in + Berlin, 2011-2015, by age group, city district and week, using additional + contact data from the POLYMOD survey. This package contains the data and + code to reproduce the results from the paper, see 'demo("hhh4contacts")'. + date_publication: '2024-10-07' + bug_reports: https://codeberg.org/EE-hub/hhh4contacts/issues + url: https://codeberg.org/EE-hub/hhh4contacts + url_cran: https://CRAN.R-project.org/package=hhh4contacts + url_git: '' +hhi: + version: 1.2.0 + title: Calculate and Visualize the Herfindahl-Hirschman Index + maintainer: Philip D. Waggoner + description: 'Based on the aggregated shares retained by individual firms or actors + within a market or space, the Herfindahl-Hirschman Index (HHI) measures the level + of concentration in a space. This package allows for intuitive and straightforward + computation of HHI scores, requiring placement of objects of interest directly + into the function. The package also includes a plot function for quick visual + display of an HHI time series using any measure of time (year, quarter, month, + etc.). For usage, please cite the Journal of Open Source Software paper associated + with the package: Waggoner, Philip D. (2018) .' + date_publication: '2018-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hhi + url_git: '' +hhmR: + version: 0.0.1 + title: Hierarchical Heatmaps + maintainer: Michael Mahony + description: Allows users to create high-quality heatmaps from labelled, hierarchical + data. Specifically, for data with a two-level hierarchical structure, it will + produce a heatmap where each row and column represents a category at the lower + level. These rows and columns are then grouped by the higher-level group each + category belongs to, with the names for each category and groups shown in the + margins. While other packages (e.g. 'dendextend') allow heatmap rows and columns + to be arranged by groups only, 'hhmR' also allows the labelling of the data at + both the category and group level. + date_publication: '2025-01-14' + bug_reports: https://github.com/sgmmahon/hhmR/issues + url: https://sgmmahon.github.io/hhmR/ + url_cran: https://CRAN.R-project.org/package=hhmR + url_git: https://github.com/sgmmahon/hhmR +HhP: + version: 1.0.0 + title: Hierarchical Heterogeneity Analysis via Penalization + maintainer: Mingyang Ren + description: |- + In medical research, supervised heterogeneity analysis has important implications. Assume that there are two types of features. Using both types of features, our goal is to conduct the first supervised heterogeneity analysis that satisfies a hierarchical structure. That is, the first type of features defines a rough structure, and the second type defines a nested and more refined structure. A penalization approach is developed, which has been motivated by but differs significantly from penalized fusion and sparse group penalization. + Reference: + Ren, M., Zhang, Q., Zhang, S., Zhong, T., Huang, J. & Ma, S. (2022). "Hierarchical cancer heterogeneity analysis based on histopathological imaging features". Biometrics, . + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HhP + url_git: '' +hhsmm: + version: 0.4.2 + title: Hidden Hybrid Markov/Semi-Markov Model Fitting + maintainer: Morteza Amini + description: |- + Develops algorithms for fitting, prediction, simulation + and initialization of the following models + (1)- hidden hybrid Markov/semi-Markov model, + introduced by Guedon (2005) , + (2)- nonparametric mixture of B-splines emissions (Langrock et al., 2015 + ), + (3)- regime switching regression model + (Kim et al., 2008 ) and auto-regressive + hidden hybrid Markov/semi-Markov model, + (4)- spline-based nonparametric + estimation of additive state-switching models + (Langrock et al., 2018 ) + (5)- robust emission model proposed by + Qin et al, 2024 + (6)- several emission distributions, including mixture of multivariate normal + (which can also handle missing data using EM algorithm) and multi-nomial emission + (for modeling polymer or DNA sequences) + (7)- tools for prediction of future state sequence, computing the score of a new sequence, + splitting the samples and sequences to train and test sets, computing the information measures of + the models, computing the residual useful lifetime (reliability) and many other useful tools ... + (read for more description: Amini et al., 2022 and its + arxiv version: ). + date_publication: '2024-09-04' + bug_reports: https://github.com/mortamini/hhsmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hhsmm + url_git: '' +hht: + version: 2.1.6 + title: 'The Hilbert-Huang Transform: Tools and Methods' + maintainer: Daniel C. Bowman + description: Builds on the EMD package to provide additional tools for empirical + mode decomposition (EMD) and Hilbert spectral analysis. It also implements the + ensemble empirical decomposition (EEMD) and the complete ensemble empirical mode + decomposition (CEEMD) methods to avoid mode mixing and intermittency problems + found in EMD analysis. The package comes with several plotting methods that can + be used to view intrinsic mode functions, the HHT spectrum, and the Fourier spectrum. + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hht + url_git: '' +hibayes: + version: 3.0.3 + title: |- + Individual-Level, Summary-Level and Single-Step Bayesian + Regression Model + maintainer: Lilin Yin + description: |- + A user-friendly tool to fit Bayesian regression models. It can fit 3 types of Bayesian models using individual-level, summary-level, and individual plus pedigree-level (single-step) data for both Genomic prediction/selection (GS) and Genome-Wide Association Study (GWAS), it was designed to estimate joint effects and genetic parameters for a complex trait, including: + (1) fixed effects and coefficients of covariates, + (2) environmental random effects, and its corresponding variance, + (3) genetic variance, + (4) residual variance, + (5) heritability, + (6) genomic estimated breeding values (GEBV) for both genotyped and non-genotyped individuals, + (7) SNP effect size, + (8) phenotype/genetic variance explained (PVE) for single or multiple SNPs, + (9) posterior probability of association of the genomic window (WPPA), + (10) posterior inclusive probability (PIP). + The functions are not limited, we will keep on going in enriching it with more features. + References: Meuwissen et al. (2001) ; Gustavo et al. (2013) ; Habier et al. (2011) ; Yi et al. (2008) ; Zhou et al. (2013) ; Moser et al. (2015) ; Lloyd-Jones et al. (2019) ; Henderson (1976) ; Fernando et al. (2014) . + date_publication: '2024-02-20' + bug_reports: https://github.com/YinLiLin/hibayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hibayes + url_git: https://github.com/YinLiLin/hibayes +HiClimR: + version: 2.2.1 + title: Hierarchical Climate Regionalization + maintainer: Hamada S. Badr + description: |- + A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. + It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical + clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution, + geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance + thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function + with preliminary big data support, different clustering methods, hybrid hierarchical clustering, + multivariate clustering (MVC), cluster validation, visualization of regionalization results, and + exporting region map and mean timeseries into NetCDF-4 file. + The technical details are described in Badr et al. (2015) . + date_publication: '2022-01-20' + bug_reports: https://github.com/hsbadr/HiClimR/issues + url: https://hsbadr.github.io/HiClimR/ + url_cran: https://CRAN.R-project.org/package=HiClimR + url_git: https://github.com/hsbadr/HiClimR +hicp: + version: 0.6.1 + title: Harmonised Index of Consumer Prices + maintainer: Sebastian Weinand + description: |- + The Harmonised Index of Consumer Prices (HICP) is the key economic figure to measure inflation in the euro area. + The methodology underlying the HICP is documented in the HICP Methodological Manual (). + Based on the manual, this package provides functions to access and work with HICP data from Eurostat's public database (). + date_publication: '2024-07-23' + bug_reports: https://github.com/eurostat/hicp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hicp + url_git: https://github.com/eurostat/hicp +hiddenf: + version: '2.0' + title: |- + The All-Configurations, Maximum-Interaction F-Test for Hidden + Additivity + maintainer: Jason A. Osborne + description: Computes the ACMIF test and Bonferroni-adjusted p-value of interaction + in two-factor studies. Produces corresponding interaction plot and analysis of + variance tables and p-values from several other tests of non-additivity. + date_publication: '2016-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hiddenf + url_git: '' +HiddenMarkov: + version: 1.8-14 + title: Hidden Markov Models + maintainer: David Harte + description: Contains functions for the analysis of Discrete Time Hidden Markov + Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes + functions for simulation, parameter estimation, and the Viterbi algorithm. See + the topic "HiddenMarkov" for an introduction to the package, and "Change Log" + for a list of recent changes. The algorithms are based of those of Walter Zucchini. + date_publication: '2025-01-28' + bug_reports: '' + url: https://www.statsresearch.co.nz/dsh/sslib/ + url_cran: https://CRAN.R-project.org/package=HiddenMarkov + url_git: '' +hidecan: + version: 1.1.0 + title: |- + Create HIDECAN Plots for Visualising Genome-Wide Association + Studies and Differential Expression Results + maintainer: Olivia Angelin-Bonnet + description: |- + Generates HIDECAN plots that summarise and combine + the results of genome-wide association studies (GWAS) and transcriptomics + differential expression analyses (DE), along with manually curated candidate genes of interest. The HIDECAN plot + is presented in Angelin-Bonnet et al. (2023) (currently in review). + date_publication: '2023-02-10' + bug_reports: https://github.com/PlantandFoodResearch/hidecan/issues + url: https://plantandfoodresearch.github.io/hidecan/ + url_cran: https://CRAN.R-project.org/package=hidecan + url_git: https://github.com/PlantandFoodResearch/hidecan +HiDimDA: + version: 0.2-7 + title: High Dimensional Discriminant Analysis + maintainer: Antonio Pedro Duarte Silva + description: |- + Performs linear discriminant analysis in high dimensional + problems based on reliable covariance estimators for problems + with (many) more variables than observations. Includes routines + for classifier training, prediction, cross-validation and + variable selection. + date_publication: '2024-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HiDimDA + url_git: '' +hidradenitis: + version: 1.0.1 + title: |- + Calculate Clinical Scores for Hidradenitis Suppurativa (HS), a + Dermatologic Disease + maintainer: Bill Denney + description: |- + Calculate clinical scores for hidradenitis suppurativa (HS), a + dermatologic disease. The scores are typically used for evaluation of + efficacy in clinical trials. The scores are not commonly used in clinical + practice. The specific scores implemented are Hidradenitis Suppurativa + Clinical Response (HiSCR) (Kimball, et al. (2015) ), + Hidradenitis Suppurativa Area and Severity Index Revised (HASI-R) (Goldfarb, + et al. (2020) ), hidradenitis suppurativa Physician + Global Assessment (HS PGA) (Marzano, et al. (2020) ), + and the International Hidradenitis Suppurativa Severity Score System (IHS4) + (Zouboulis, et al. (2017) ). + date_publication: '2025-01-10' + bug_reports: https://github.com/humanpred/hidradenitis/issues + url: https://humanpred.github.io/hidradenitis/ + url_cran: https://CRAN.R-project.org/package=hidradenitis + url_git: '' +hierarchicalSets: + version: 1.0.4 + title: Set Data Visualization Using Hierarchies + maintainer: Thomas Lin Pedersen + description: |- + Pure set data visualization approaches are often limited in + scalability due to the combinatorial explosion of distinct set families as + the number of sets under investigation increases. hierarchicalSets applies + a set centric hierarchical clustering of the sets under investigation and + uses this hierarchy as a basis for a range of scalable visual + representations. hierarchicalSets is especially well suited for collections + of sets that describe comparable comparable entities as it relies on the + sets to have a meaningful relational structure. + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hierarchicalSets + url_git: '' +hierBipartite: + version: 0.0.2 + title: Bipartite Graph-Based Hierarchical Clustering + maintainer: Calvin Chi + description: |2- + + Bipartite graph-based hierarchical clustering, developed for pharmacogenomic + datasets and datasets sharing the same data structure. The goal is to + construct a hierarchical clustering of groups of samples based on + association patterns between two sets of variables. In the context of + pharmacogenomic datasets, the samples are cell lines, and the two sets of + variables are typically expression levels and drug sensitivity values. + For this method, sparse canonical correlation analysis from + Lee, W., Lee, D., Lee, Y. and Pawitan, Y. (2011) + is first applied to extract association patterns for each group of samples. + Then, a nuclear norm-based dissimilarity measure is used to construct a + dissimilarity matrix between groups based on the extracted associations. + Finally, hierarchical clustering is applied. + date_publication: '2021-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hierBipartite + url_git: '' +hierfstat: + version: 0.5-11 + title: Estimation and Tests of Hierarchical F-Statistics + maintainer: Jerome Goudet + description: |- + Estimates hierarchical F-statistics from haploid or + diploid genetic data with any numbers of levels in the hierarchy, following the + algorithm of Yang (Evolution(1998), 52:950). + Tests via randomisations the significance + of each F and variance components, using the likelihood-ratio statistics G + (Goudet et al. (1996) ). + Estimates genetic diversity statistics + for haploid and diploid genetic datasets in various formats, including inbreeding and + coancestry coefficients, and population specific F-statistics following + Weir and Goudet (2017) . + date_publication: '2022-05-05' + bug_reports: https://github.com/jgx65/hierfstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hierfstat + url_git: https://github.com/jgx65/hierfstat +hierNet: + version: '1.9' + title: A Lasso for Hierarchical Interactions + maintainer: Jacob Bien + description: Fits sparse interaction models for continuous and binary responses + subject to the strong (or weak) hierarchy restriction that an interaction between + two variables only be included if both (or at least one of) the variables is included + as a main effect. For more details, see Bien, J., Taylor, J., Tibshirani, R., + (2013) "A Lasso for Hierarchical Interactions." Annals of Statistics. 41(3). 1111-1141. + date_publication: '2020-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hierNet + url_git: '' +HierPortfolios: + version: 1.0.1 + title: Hierarchical Risk Clustering Portfolio Allocation Strategies + maintainer: Carlos Trucios + description: |- + Machine learning hierarchical risk clustering portfolio allocation strategies. + The implemented methods are: + Hierarchical risk parity (De Prado, 2016) . + Hierarchical clustering-based asset allocation (Raffinot, 2017) + . + Hierarchical equal risk contribution portfolio (Raffinot, 2018) + . + A Constrained Hierarchical Risk Parity Algorithm with Cluster-based Capital Allocation (Pfitzingera and Katzke, 2019) + . + date_publication: '2024-08-18' + bug_reports: https://github.com/ctruciosm/HierPortfolios/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HierPortfolios + url_git: https://github.com/ctruciosm/HierPortfolios +hierSDR: + version: '0.1' + title: Hierarchical Sufficient Dimension Reduction + maintainer: Jared Huling + description: Provides semiparametric sufficient dimension reduction for central + mean subspaces for heterogeneous data defined by combinations of binary factors + (such as chronic conditions). Subspaces are estimated to be hierarchically nested + to respect the structure of subpopulations with overlapping characteristics. This + package is an implementation of the proposed methodology of Huling and Yu (2021) + . + date_publication: '2021-09-23' + bug_reports: https://github.com/jaredhuling/hierSDR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hierSDR + url_git: '' +HiGarrote: + version: 1.0.2 + title: |- + Nonnegative Garrote Method Incorporating Hierarchical + Relationships + maintainer: Wei-Yang Yu + description: An implementation of the nonnegative garrote method that incorporates + hierarchical relationships among variables. The core function, HiGarrote(), offers + an automated approach for analyzing experiments while respecting hierarchical + structures among effects. For methodological details, refer to Yu and Joseph (2024) + . This work is supported by U.S. National Science + Foundation grant DMS-2310637. + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HiGarrote + url_git: '' +highcharter: + version: 0.9.4 + title: A Wrapper for the 'Highcharts' Library + maintainer: Joshua Kunst + description: |- + A wrapper for the 'Highcharts' library including + shortcut functions to plot R objects. 'Highcharts' + is a charting library offering + numerous chart types with a simple configuration syntax. + date_publication: '2022-01-03' + bug_reports: https://github.com/jbkunst/highcharter/issues + url: https://jkunst.com/highcharter/ + url_cran: https://CRAN.R-project.org/package=highcharter + url_git: https://github.com/jbkunst/highcharter +highd2means: + version: '1.0' + title: High-Dimensional Tests for Two Population Mean Vectors + maintainer: Michail Tsagris + description: 'Tests for two high-dimensional population mean vectors. The user has + the option to compute the asymptotic, the permutation or the bootstrap based p-value + of the test. Some references are: Chen S.X. and Qin Y.L. (2010). , + Cai T.T., Liu W., and Xia Y. (2014) and Yu X., Li D., + Xue L. and Li, R. (2023) .' + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=highd2means + url_git: '' +highDmean: + version: 0.1.0 + title: Testing Two-Sample Mean in High Dimension + maintainer: Huaiyu Zhang + description: |- + Implements the high-dimensional two-sample test + proposed by Zhang (2019) . + It also implements the test proposed by Srivastava, Katayama, + and Kano (2013) . These tests + are particularly suitable to high dimensional data from two populations + for which the classical multivariate Hotelling's T-square test fails due + to sample sizes smaller than dimensionality. In this case, the ZWL and ZWLm + tests proposed by Zhang (2019) , + referred to as zwl_test() in this package, provide a reliable and powerful test. + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=highDmean + url_git: '' +HighestMedianRules: + version: '1.0' + title: |- + Implementation of Voting Rules Electing the Candidate with + Highest Median Grade + maintainer: Adrien Fabre + description: |- + Computes the scores and ranks candidates according to voting rules electing the highest median grade. + Based on "Tie-breaking the highest median: alternatives to the majority judgment", A. Fabre, Social Choice & Welfare (forthcoming as of 2020). The paper is available here: . + Functions to plot the voting profiles can be found on github: . + date_publication: '2020-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HighestMedianRules + url_git: '' +highfrequency: + version: 1.0.1 + title: Tools for Highfrequency Data Analysis + maintainer: Kris Boudt + description: |- + Provide functionality to manage, clean and match highfrequency + trades and quotes data, calculate various liquidity measures, estimate and + forecast volatility, detect price jumps and investigate microstructure noise and intraday + periodicity. A detailed vignette can be found in the open-access paper + "Analyzing Intraday Financial Data in R: The highfrequency Package" + by Boudt, Kleen, and Sjoerup (2022, ). + date_publication: '2023-10-04' + bug_reports: https://github.com/jonathancornelissen/highfrequency/issues + url: '' + url_cran: https://CRAN.R-project.org/package=highfrequency + url_git: https://github.com/jonathancornelissen/highfrequency +highlight: + version: 0.5.1 + title: Syntax Highlighter + maintainer: Hadley Wickham + description: |- + Syntax highlighter for R code based on the results of the R + parser. Rendering in HTML and latex markup. Custom Sweave driver + performing syntax highlighting of R code chunks. + date_publication: '2023-01-18' + bug_reports: https://github.com/hadley/highlight/issues + url: '' + url_cran: https://CRAN.R-project.org/package=highlight + url_git: https://github.com/hadley/highlight +highlighter: + version: '0.1' + title: Code Syntax Highlighting using the 'Prism.js' Library + maintainer: Federico Rivadeneira + description: |- + Code Syntax Highlighting made easy for code snippets or complete + files. Whether you're documenting your data analysis or creating interactive + 'shiny' apps. + date_publication: '2023-09-25' + bug_reports: '' + url: https://federiva.github.io/highlighter/ + url_cran: https://CRAN.R-project.org/package=highlighter + url_git: '' +highlightHTML: + version: 0.2.5 + title: Highlight HTML Text and Tables + maintainer: Brandon LeBeau + description: |- + A tool to format R markdown with CSS ids for HTML output. + The tool may be most helpful for those using markdown to create reproducible + documents. The biggest limitations in formatting is the knowledge of CSS + by the document authors. + date_publication: '2020-04-21' + bug_reports: https://github.com/lebebr01/highlightHTML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=highlightHTML + url_git: https://github.com/lebebr01/highlightHTML +highlightr: + version: 1.0.2 + title: Highlight Conserved Edits Across Versions of a Document + maintainer: Rachel Rogers + description: |- + Input multiple versions of a source document, + and receive HTML code for a highlighted version of the source document + indicating the frequency of occurrence of phrases in the different versions. + This method is described in Chapter 3 of + Rogers (2024) . + date_publication: '2024-10-17' + bug_reports: https://github.com/rachelesrogers/highlightr/issues + url: https://rachelesrogers.github.io/highlightr/ + url_cran: https://CRAN.R-project.org/package=highlightr + url_git: https://github.com/rachelesrogers/highlightr +highmean: + version: '3.0' + title: Two-Sample Tests for High-Dimensional Mean Vectors + maintainer: Lifeng Lin + description: Provides various tests for comparing high-dimensional mean vectors + in two sample populations. + date_publication: '2016-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=highmean + url_git: '' +highMLR: + version: 0.1.1 + title: Feature Selection for High Dimensional Survival Data + maintainer: Atanu Bhattacharjee + description: |- + Perform high dimensional Feature Selection in the presence of survival outcome. + Based on Feature Selection method and different survival analysis, it will obtain the best + markers with optimal threshold levels according to their effect on disease progression + and produce the most consistent level according to those threshold values. + The functions' methodology is based on by Sonabend et al (2021) and Bhattacharjee et al (2021) . + date_publication: '2022-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=highMLR + url_git: '' +highOrderPortfolios: + version: 0.1.1 + title: Design of High-Order Portfolios Including Skewness and Kurtosis + maintainer: Daniel P. Palomar + description: |- + The classical Markowitz's mean-variance portfolio formulation ignores + heavy tails and skewness. High-order portfolios use higher order moments to + better characterize the return distribution. Different formulations and fast + algorithms are proposed for high-order portfolios based on the mean, variance, + skewness, and kurtosis. + The package is based on the papers: + R. Zhou and D. P. Palomar (2021). "Solving High-Order Portfolios via + Successive Convex Approximation Algorithms." . + X. Wang, R. Zhou, J. Ying, and D. P. Palomar (2022). "Efficient and Scalable + High-Order Portfolios Design via Parametric Skew-t Distribution." . + date_publication: '2022-10-20' + bug_reports: https://github.com/dppalomar/highOrderPortfolios/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=highOrderPortfolios + url_git: https://github.com/dppalomar/highOrderPortfolios +highr: + version: '0.11' + title: Syntax Highlighting for R Source Code + maintainer: Yihui Xie + description: |- + Provides syntax highlighting for R source code. Currently it + supports LaTeX and HTML output. Source code of other languages is supported + via Andre Simon's highlight package (). + date_publication: '2024-05-26' + bug_reports: https://github.com/yihui/highr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=highr + url_git: https://github.com/yihui/highr +highriskzone: + version: 1.4.9 + title: Determining and Evaluating High-Risk Zones + maintainer: Rickmer Schulte + description: |- + Functions for determining and evaluating high-risk zones and + simulating and thinning point process data, as described in 'Determining + high risk zones using point process methodology - Realization by building + an R package' Seibold (2012) + and 'Determining high-risk zones for unexploded World War II bombs by using point + process methodology', Mahling et al. (2013) . + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=highriskzone + url_git: '' +highs: + version: 1.9.0-1 + title: '''HiGHS'' Optimization Solver' + maintainer: Florian Schwendinger + description: |- + R interface to 'HiGHS', an optimization solver for solving mixed integer + optimization problems with quadratic or linear objective and linear constraints. + date_publication: '2025-01-08' + bug_reports: https://gitlab.com/roigrp/solver/highs/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=highs + url_git: https://gitlab.com/roigrp/solver/highs +hightR: + version: 0.3.0 + title: HIGHT Algorithm + maintainer: Yongwoo Kim + description: HIGHT(HIGh security and light weigHT) algorithm is a block cipher encryption + algorithm developed to provide confidentiality in computing environments that + demand low power consumption and lightweight, such as RFID(Radio-Frequency Identification) + and USN(Ubiquitous Sensor Network), or in mobile environments that require low + power consumption and lightweight, such as smartphones and smart cards. Additionally, + it is designed with a simple structure that enables it to be used with basic arithmetic + operations, XOR, and circular shifts in 8-bit units. This algorithm was designed + to consider both safety and efficiency in a very simple structure suitable for + limited environments, compared to the former 128-bit encryption algorithm SEED. + In December 2010, it became an ISO(International Organization for Standardization) + standard. The detailed procedure is described in Hong et al. (2006) . + date_publication: '2023-05-16' + bug_reports: https://github.com/Yongwoo-Eg-Kim/hightR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hightR + url_git: https://github.com/Yongwoo-Eg-Kim/hightR +highTtest: + version: '1.3' + title: Simultaneous Critical Values for t-Tests in Very High Dimensions + maintainer: Shannon T. Holloway + description: |- + Implements the method developed by Cao and Kosorok (2011) for the + significance analysis of thousands of features in high-dimensional + biological studies. It is an asymptotically valid data-driven procedure + to find critical values for rejection regions controlling the + k-familywise error rate, false discovery rate, and the tail probability + of false discovery proportion. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=highTtest + url_git: '' +higlasso: + version: 0.9.0 + title: Hierarchical Integrative Group LASSO + maintainer: Alexander Rix + description: |2- + + Environmental health studies are increasingly measuring multiple pollutants + to characterize the joint health effects attributable to exposure mixtures. + However, the underlying dose-response relationship between toxicants and + health outcomes of interest may be highly nonlinear, with possible nonlinear + interaction effects. Hierarchical integrative group least absolute shrinkage + and selection operator (HiGLASSO), developed by Boss et al (2020) + , is a general framework to identify noteworthy nonlinear + main and interaction effects in the presence of group structures among a set + of exposures. + date_publication: '2020-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=higlasso + url_git: '' +higrad: + version: 0.1.0 + title: |- + Statistical Inference for Online Learning and Stochastic + Approximation via HiGrad + maintainer: Yuancheng Zhu + description: |- + Implements the Hierarchical Incremental GRAdient Descent (HiGrad) algorithm, + a first-order algorithm for finding the minimizer of a function in online learning just like stochastic gradient descent (SGD). + In addition, this method attaches a confidence interval to assess the uncertainty of its predictions. + See Su and Zhu (2018) for details. + date_publication: '2018-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=higrad + url_git: '' +hilbert: + version: 0.2.1 + title: Coordinate Indexing on Hilbert Curves + maintainer: Justin Singh-Mohudpur + description: |- + Provides utilities for encoding and decoding coordinates to/from Hilbert curves + based on the iterative encoding implementation described in Chen et al. (2006) . + date_publication: '2022-04-08' + bug_reports: https://github.com/program--/hilbert/issues + url: https://hilbert.justinsingh.me + url_cran: https://CRAN.R-project.org/package=hilbert + url_git: https://github.com/program--/hilbert +hilbertSimilarity: + version: 0.4.3 + title: Hilbert Similarity Index for High Dimensional Data + maintainer: Yann Abraham + description: |- + Quantifying similarity between high-dimensional single cell samples is challenging, and usually requires + some simplifying hypothesis to be made. By transforming the high dimensional space into a high dimensional grid, + the number of cells in each sub-space of the grid is characteristic of a given sample. Using a Hilbert curve + each sample can be visualized as a simple density plot, and the distance between samples can be calculated from + the distribution of cells using the Jensen-Shannon distance. Bins that correspond to significant differences + between samples can identified using a simple bootstrap procedure. + date_publication: '2019-11-11' + bug_reports: http://github.com/yannabraham/hilbertSimilarity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hilbertSimilarity + url_git: http://github.com/yannabraham/hilbertSimilarity +hildareadR: + version: 0.2.0 + title: Extract Variables from HILDA + maintainer: Sebastian Kalucza + description: Makes it easy to extract and combine variables from the HILDA (Household, + Income and Labour Dynamics in Australia) survey maintained by the Melbourne Institute + . + date_publication: '2020-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hildareadR + url_git: '' +hilldiv: + version: 1.5.1 + title: Integral Analysis of Diversity Based on Hill Numbers + maintainer: Antton Alberdi + description: |- + Tools for analysing, comparing, visualising and partitioning diversity based on Hill numbers. + 'hilldiv' is an R package that provides a set of functions to assist analysis of diversity for + diet reconstruction, microbial community profiling or more general ecosystem characterisation + analyses based on Hill numbers, using OTU/ASV tables and associated phylogenetic trees as + inputs. The package includes functions for (phylo)diversity measurement, (phylo)diversity + profile plotting, (phylo)diversity comparison between samples and groups, (phylo)diversity + partitioning and (dis)similarity measurement. All of these grounded in abundance-based and + incidence-based Hill numbers. + The statistical framework developed around Hill numbers encompasses many of the most + broadly employed diversity (e.g. richness, Shannon index, Simpson index), + phylogenetic diversity (e.g. Faith's PD, Allen's H, Rao's quadratic entropy) and + dissimilarity (e.g. Sorensen index, Unifrac distances) metrics. This enables the most + common analyses of diversity to be performed while grounded in a single statistical + framework. The methods are described in Jost et al. (2007) , + Chao et al. (2010) and Chiu et al. (2014) + ; and reviewed in the framework of molecularly characterised + biological systems in Alberdi & Gilbert (2019) . + date_publication: '2019-10-01' + bug_reports: https://github.com/anttonalberdi/hilldiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hilldiv + url_git: https://github.com/anttonalberdi/hilldiv +hillR: + version: 0.5.2 + title: Diversity Through Hill Numbers + maintainer: Daijiang Li + description: |- + Calculate taxonomic, functional and phylogenetic diversity measures + through Hill Numbers proposed by Chao, Chiu and Jost (2014) + . + date_publication: '2023-08-19' + bug_reports: https://github.com/daijiang/hillR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hillR + url_git: https://github.com/daijiang/hillR +hillshader: + version: 0.1.2 + title: Create Hillshade Relief Maps Using Ray-Tracing + maintainer: Pierre Roudier + description: |- + A set of tools to create georeferenced hillshade relief + raster maps using ray-tracing and other advanced hill-shading + techniques. It includes a wrapper function to create a georeferenced, + ray-traced hillshade map from a digital elevation model, and other + functions that can be used in a rayshader pipeline. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hillshader + url_git: '' +HIMA: + version: 2.3.1 + title: High-Dimensional Mediation Analysis + maintainer: Yinan Zheng + description: 'Allows to estimate and test high-dimensional mediation effects based + on advanced mediator screening and penalized regression techniques. Methods used + in the package refer to Zhang H, Zheng Y, Zhang Z, Gao T, Joyce B, Yoon G, Zhang + W, Schwartz J, Just A, Colicino E, Vokonas P, Zhao L, Lv J, Baccarelli A, Hou + L, Liu L. Estimating and Testing High-dimensional Mediation Effects in Epigenetic + Studies. Bioinformatics. (2016) . PMID: 27357171.' + date_publication: '2025-01-27' + bug_reports: https://github.com/YinanZheng/HIMA/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=HIMA + url_git: https://github.com/YinanZheng/HIMA/ +himach: + version: 0.3.2 + title: High Mach Finds Routes for Supersonic Aircraft + maintainer: David Marsh + description: |- + For supersonic aircraft, flying subsonic over land, + find the best route between airports. Allow for coastal buffer and + potentially closed regions. Use a minimal model of aircraft + performance: the focus is on time saved versus subsonic flight, rather + than on vertical flight profile. For modelling and forecasting, not for planning your + flight! + date_publication: '2023-09-20' + bug_reports: https://github.com/david6marsh/himach/issues + url: '' + url_cran: https://CRAN.R-project.org/package=himach + url_git: https://github.com/david6marsh/himach +hindex: + version: 0.2.0 + title: Simulating the Development of h-Index Values + maintainer: Alexander Tekles + description: |- + H-index and h-alpha are a bibliometric indicators. This package + provides functions to simulate how these indicators may develop over time for + a given set of researchers and to visualize the simulation data. + The implementation is based on the 'STATA' ado h-index and is described in + more detail in Bornmann et al. (2019) . + date_publication: '2020-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hindex + url_git: '' +hindexcalculator: + version: 1.0.0 + title: |- + H-Index Calculator using Data from a Web of Science (WoS) + Citation Report + maintainer: Sepand Alavifard + description: 'H(x) is the h-index for the past x years. Here, the h(x) of a scientist/department/etc. + can be calculated using the exported excel file from a Web of Science citation + report of a search. Also calculated is the year of first publication, total number + of publications, and sum of times cited for the specified period. Therefore, for + h-10: the date of first publication, total number of publications, and sum of + times cited in the past 10 years are calculated. Note: the excel file has to first + be saved in a .csv format.' + date_publication: '2015-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hindexcalculator + url_git: '' +hint: + version: 0.1-3 + title: |- + Tools for Hypothesis Testing Based on Hypergeometric + Intersection Distributions + maintainer: Alex T. Kalinka + description: |- + Hypergeometric Intersection distributions are a + broad group of distributions that describe the probability of picking + intersections when drawing independently from two (or more) urns + containing variable numbers of balls belonging to the same n + categories. . + date_publication: '2022-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hint + url_git: https://github.com/alextkalinka/hint +hiphop: + version: 0.0.1 + title: Parentage Assignment using Bi-Allelic Genetic Markers + maintainer: Martijn van de Pol + description: |- + Can be used for paternity and maternity assignment and outperforms + conventional methods where closely related individuals occur in the pool of + possible parents. The method compares the genotypes of offspring with any + combination of potentials parents and scores the number of mismatches of these + individuals at bi-allelic genetic markers (e.g. Single Nucleotide Polymorphisms). + It elaborates on a prior exclusion method based on the Homozygous Opposite Test + (HOT; Huisman 2017 ) by introducing the + additional exclusion criterion HIPHOP (Homozygous Identical Parents, + Heterozygous Offspring are Precluded; Cockburn et al., in revision). Potential + parents are excluded if they have more mismatches than can + be expected due to genotyping error and mutation, and thereby one can identify the + true genetic parents and detect situations where one (or both) of the true + parents is not sampled. Package 'hiphop' can deal with (a) the case where there + is contextual information about parentage of the mother (i.e. a female has been + seen to be involved in reproductive tasks such as nest building), but paternity + is unknown (e.g. due to promiscuity), (b) where both parents need to be assigned, + because there is no contextual information on which female laid eggs and which + male fertilized them (e.g. polygynandrous mating system where multiple females + and males deposit young in a common nest, or organisms with external fertilisation + that breed in aggregations). + For details: Cockburn, A., Penalba, J.V.,Jaccoud, D.,Kilian, A., Brouwer, L., + Double, M.C., Margraf, N., Osmond, H.L., van de Pol, M. and Kruuk, L.E.B. + (in revision). HIPHOP: improved paternity assignment among close relatives + using a simple exclusion method for bi-allelic markers. + Molecular Ecology Resources, DOI to be added upon acceptance. + date_publication: '2020-08-19' + bug_reports: '' + url: https://groups.google.com/d/forum/r-hiphop + url_cran: https://CRAN.R-project.org/package=hiphop + url_git: '' +hippie: + version: 0.1.0 + title: Hippie Code Completion in 'RStudio' + maintainer: Christopher Baker + description: |- + An 'RStudio' Addin for Hippie Expand (AKA Hippie Code + Completion or Cyclic Expand Word). This type of completion searches for + matching tokens within the user's current source editor file, regardless of + file type. By searching only within the current source file, 'hippie' offers a + fast way to identify and insert completions that appear around the user's + cursor. + date_publication: '2022-09-05' + bug_reports: https://github.com/crew102/hippie/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hippie + url_git: https://github.com/crew102/hippie +hipread: + version: 0.2.4 + title: Read Hierarchical Fixed Width Files + maintainer: Derek Burk + description: |- + Read hierarchical fixed width files like those commonly used by + many census data providers. Also allows for reading of data in chunks, + and reading 'gzipped' files without storing the full file in memory. + date_publication: '2023-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hipread + url_git: '' +HiResTEC: + version: 0.63.1 + title: Non-Targeted Fluxomics on High-Resolution Mass-Spectrometry Data + maintainer: Jan Lisec + description: |- + Identifying labeled compounds in a 13C-tracer experiment in + non-targeted fashion is a cumbersome process. This package facilitates + such type of analyses by providing high level quality control plots, + deconvoluting and evaluating spectra and performing a multitude of + tests in an automatic fashion. The main idea is to use changing + intensity ratios of ion pairs from peak list generated with 'xcms' as + candidates and evaluate those against base peak chromatograms and + spectra information within the raw measurement data automatically. + The functionality is described in Hoffmann et al. (2018) + . + date_publication: '2025-02-27' + bug_reports: '' + url: https://janlisec.github.io/HiResTEC/ + url_cran: https://CRAN.R-project.org/package=HiResTEC + url_git: https://github.com/janlisec/HiResTEC +hIRT: + version: 0.3.0 + title: Hierarchical Item Response Theory Models + maintainer: Xiang Zhou + description: |- + Implementation of a class of hierarchical item response + theory (IRT) models where both the mean and the variance of latent preferences + (ability parameters) may depend on observed covariates. The current + implementation includes both the two-parameter latent trait model for binary data and the + graded response model for ordinal data. Both are fitted via the Expectation-Maximization (EM) + algorithm. Asymptotic standard errors are derived from the observed information + matrix. + date_publication: '2020-03-26' + bug_reports: http://github.com/xiangzhou09/hIRT + url: '' + url_cran: https://CRAN.R-project.org/package=hIRT + url_git: http://github.com/xiangzhou09/hIRT +hisse: + version: 2.1.11 + title: Hidden State Speciation and Extinction + maintainer: Jeremy Beaulieu + description: Sets up and executes a HiSSE model (Hidden State Speciation and Extinction) + on a phylogeny and character sets to test for hidden shifts in trait dependent + rates of diversification. Beaulieu and O'Meara (2016) . + date_publication: '2023-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hisse + url_git: '' +HistDat: + version: 0.2.0 + title: Summary Statistics for Histogram/Count Data + maintainer: Michael Milton + description: |- + In some cases you will have data in a histogram format, where + you have a vector of all possible observations, and a vector of how many + times each observation appeared. You could expand this into a single 1D + vector, but this may not be advisable if the counts are extremely large. + 'HistDat' allows for the calculation of summary statistics without the need + for expanding your data. + date_publication: '2021-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HistDat + url_git: '' +HistData: + version: 0.9-1 + title: Data Sets from the History of Statistics and Data Visualization + maintainer: Michael Friendly + description: |- + The 'HistData' package provides a collection of small data sets + that are interesting and important in the history of statistics and data + visualization. The goal of the package is to make these available, both for + instructional use and for historical research. Some of these present interesting + challenges for graphics or analysis in R. + date_publication: '2023-08-09' + bug_reports: https://github.com/friendly/HistData/issues + url: https://friendly.github.io/HistData/ + url_cran: https://CRAN.R-project.org/package=HistData + url_git: '' +HistDAWass: + version: 1.0.8 + title: Histogram-Valued Data Analysis + maintainer: Antonio Irpino + description: |- + In the framework of Symbolic Data Analysis, a relatively new + approach to the statistical analysis of multi-valued data, we consider + histogram-valued data, i.e., data described by univariate histograms. The + methods and the basic statistics for histogram-valued data are mainly based + on the L2 Wasserstein metric between distributions, i.e., the Euclidean metric + between quantile functions. The package contains unsupervised classification + techniques, least square regression and tools for histogram-valued data and for + histogram time series. An introducing paper is Irpino A. Verde R. (2015) . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HistDAWass + url_git: '' +histmdl: + version: 0.7-1 + title: A Most Informative Histogram-Like Model + maintainer: Jouke Witteveen + description: |- + Using the MDL principle, it is possible to estimate + parameters for a histogram-like model. The package contains + the implementation of such an estimation method. + date_publication: '2018-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=histmdl + url_git: '' +histogram: + version: 0.0-25 + title: |- + Construction of Regular and Irregular Histograms with Different + Options for Automatic Choice of Bins + maintainer: Thoralf Mildenberger + description: Automatic construction of regular and irregular histograms as described + in Rozenholc/Mildenberger/Gather (2010). + date_publication: '2019-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=histogram + url_git: '' +historicalborrow: + version: 1.1.0 + title: Non-Longitudinal Bayesian Historical Borrowing Models + maintainer: William Michael Landau + description: |- + Historical borrowing in clinical trials can improve + precision and operating characteristics. This package supports + a hierarchical model and a mixture model to borrow historical + control data from other studies to better characterize the + control response of the current study. It also quantifies + the amount of borrowing through benchmark models (independent + and pooled). Some of the methods are discussed by + Viele et al. (2013) . + date_publication: '2024-09-10' + bug_reports: https://github.com/wlandau/historicalborrow/issues + url: https://wlandau.github.io/historicalborrow/ + url_cran: https://CRAN.R-project.org/package=historicalborrow + url_git: https://github.com/wlandau/historicalborrow +historicalborrowlong: + version: 0.1.0 + title: Longitudinal Bayesian Historical Borrowing Models + maintainer: William Michael Landau + description: |- + Historical borrowing in clinical trials can improve + precision and operating characteristics. This package supports + a longitudinal hierarchical model to borrow historical + control data from other studies to better characterize the + control response of the current study. It also quantifies + the amount of borrowing through longitudinal benchmark models (independent + and pooled). The hierarchical model approach to historical borrowing + is discussed by Viele et al. (2013) . + date_publication: '2024-09-25' + bug_reports: https://github.com/wlandau/historicalborrowlong/issues + url: https://wlandau.github.io/historicalborrowlong/ + url_cran: https://CRAN.R-project.org/package=historicalborrowlong + url_git: https://github.com/wlandau/historicalborrowlong +historydata: + version: '0.1' + title: Data Sets for Historians + maintainer: Lincoln Mullen + description: |- + These sample data sets are intended for historians + learning R. They include population, institutional, religious, + military, and prosopographical data suitable for mapping, + quantitative analysis, and network analysis. + date_publication: '2014-12-24' + bug_reports: https://github.com/ropensci/historydata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=historydata + url_git: https://github.com/ropensci/historydata +histoslider: + version: 0.1.1 + title: A Histogram Slider Input for 'Shiny' + maintainer: Carson Sievert + description: A histogram slider input binding for use in 'Shiny'. Currently supports + creating histograms from numeric, date, and 'date-time' vectors. + date_publication: '2023-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=histoslider + url_git: '' +hitandrun: + version: 0.5-6 + title: |- + "Hit and Run" and "Shake and Bake" for Sampling Uniformly from + Convex Shapes + maintainer: Gert van Valkenhoef + description: The "Hit and Run" Markov Chain Monte Carlo method for sampling uniformly + from convex shapes defined by linear constraints, and the "Shake and Bake" method + for sampling from the boundary of such shapes. Includes specialized functions + for sampling normalized weights with arbitrary linear constraints. Tervonen, T., + van Valkenhoef, G., Basturk, N., and Postmus, D. (2012) . + van Valkenhoef, G., Tervonen, T., and Postmus, D. (2014) . + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hitandrun + url_git: https://github.com/gertvv/hitandrun +hivdata: + version: 0.1.0 + title: Six-Year Chronological Data of HIV and ART Cases in Pakistan + maintainer: Muhammad Imran + description: |- + We provide the monthly number of HIV and antiretroviral therapy (ART) cases of male, female, children and transgender as well as for the whole of Pakistan reported at various treatment centers in Pakistan from January 2016 to December 2021. Related works include: + a) Imran, M., Nasir, J. A., & Riaz, S. (2018). Regional pattern of HIV cases in Pakistan. Journal of Postgraduate Medical Institute, 32(1), 9-13. + . + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hivdata + url_git: '' +hive: + version: 0.2-2 + title: Hadoop InteractiVE + maintainer: Stefan Theussl + description: |- + Hadoop InteractiVE facilitates distributed + computing via the MapReduce paradigm through R and Hadoop. An easy to use + interface to Hadoop, the Hadoop Distributed File System (HDFS), + and Hadoop Streaming is provided. + date_publication: '2020-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hive + url_git: '' +HiveR: + version: 0.4.0 + title: 2D and 3D Hive Plots for R + maintainer: Bryan A. Hanson + description: 'Creates and plots 2D and 3D hive plots. Hive plots are a unique method + of displaying networks of many types in which node properties are mapped to axes + using meaningful properties rather than being arbitrarily positioned. The hive + plot concept was invented by Martin Krzywinski at the Genome Science Center (www.hiveplot.net/). Keywords: + networks, food webs, linnet, systems biology, bioinformatics.' + date_publication: '2024-07-18' + bug_reports: https://github.com/bryanhanson/HiveR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HiveR + url_git: https://github.com/bryanhanson/HiveR +hJAM: + version: 1.0.0 + title: Hierarchical Joint Analysis of Marginal Summary Statistics + maintainer: Lai Jiang + description: 'Provides functions to implement a hierarchical approach which is designed + to perform joint analysis of summary statistics using the framework of Mendelian + Randomization or transcriptome analysis. Reference: Lai Jiang, Shujing Xu, Nicholas + Mancuso, Paul J. Newcombe, David V. Conti (2020). "A Hierarchical Approach Using + Marginal Summary Statistics for Multiple Intermediates in a Mendelian Randomization + or Transcriptome Analysis." .' + date_publication: '2020-02-20' + bug_reports: https://github.com/lailylajiang/hJAM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hJAM + url_git: https://github.com/lailylajiang/hJAM +HK80: + version: 0.0.2 + title: Conversion Tools for HK80 Geographical Coordinate System + maintainer: Jinlong Zhang + description: This is a collection of functions for converting coordinates between + WGS84UTM, WGS84GEO, HK80UTM, HK80GEO and HK1980GRID Coordinate Systems used in + Hong Kong SAR, based on the algorithms described in Explanatory Notes on Geodetic + Datums in Hong Kong by Survey and Mapping Office Lands Department, Hong Kong Government + (1995). + date_publication: '2016-07-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HK80 + url_git: https://github.com/helixcn/ +hkdatasets: + version: 1.0.0 + title: Datasets Related to Hong Kong + maintainer: Martin Chan + description: |- + Datasets related to Hong Kong, including information on the 2019 elected District Councillors ( and ) and traffic collision data from the Hong Kong Department of Transport (). All + of the data in this package is available in the public domain. + date_publication: '2021-09-04' + bug_reports: https://github.com/Hong-Kong-Districts-Info/hkdatasets/issues + url: https://hong-kong-districts-info.github.io/hkdatasets/ + url_cran: https://CRAN.R-project.org/package=hkdatasets + url_git: '' +hkevp: + version: 1.1.5 + title: |- + Spatial Extreme Value Analysis with the Hierarchical Model of + Reich and Shaby (2012) + maintainer: Leo Belzile + description: Several procedures for the hierarchical kernel extreme value process + of Reich and Shaby (2012) , including simulation, estimation + and spatial extrapolation. The spatial latent variable model + is also included. + date_publication: '2023-04-18' + bug_reports: https://github.com/lbelzile/hkevp/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=hkevp + url_git: '' +HKRbook: + version: 0.1.3 + title: Apps and Data for the Book "Introduction to Statistics" + maintainer: Sigbert Klinke + description: |- + Functions, Shiny apps and data for the book "Introduction to Statistics" by + Wolfgang Karl Härdle, Sigbert Klinke, and Bernd Rönz (2015) . + date_publication: '2022-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HKRbook + url_git: '' +hlaR: + version: 1.0.0 + title: Tools for HLA Data + maintainer: Joan Zhang + description: A streamlined tool for eplet analysis of donor and recipient HLA (human + leukocyte antigen) mismatch. Messy, low-resolution HLA typing data is cleaned, + and imputed to high-resolution using the NMDP (National Marrow Donor Program) + haplotype reference database . High resolution + data is analyzed for overall or single antigen eplet mismatch using a reference + table (currently supporting 'HLAMatchMaker' versions + 2 and 3). Data can enter or exit the workflow at different points depending on + the user's aims and initial data quality. + date_publication: '2023-01-31' + bug_reports: https://github.com/LarsenLab/hlaR/issues + url: https://pubmed.ncbi.nlm.nih.gov/35101308/ + url_cran: https://CRAN.R-project.org/package=hlaR + url_git: '' +HLAtools: + version: 1.3.0 + title: Toolkit for HLA Immunogenomics + maintainer: Steven Mack + description: A toolkit for the analysis and management of data for genes in the + so-called "Human Leukocyte Antigen" (HLA) region. Functions extract reference + data from the Anthony Nolan HLA Informatics Group/ImmunoGeneTics HLA 'GitHub' + repository (ANHIG/IMGTHLA) , validate Genotype + List (GL) Strings, convert between UNIFORMAT and GL String Code (GLSC) formats, + translate HLA alleles and GLSCs across ImmunoPolymorphism Database (IPD) IMGT/HLA + Database release versions, identify differences between pairs of alleles at a + locus, generate customized, multi-position sequence alignments, trim and convert + allele-names across nomenclature epochs, and extend existing data-analysis methods. + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HLAtools + url_git: +hlidacr: + version: 0.2.0 + title: Access Data from the 'Hlídač Státu' API + maintainer: Michael Škvrňák + description: |- + Provides access to datasets published by 'Hlídač státu' , + a Czech watchdog, via their API. + date_publication: '2021-09-16' + bug_reports: https://github.com/skvrnami/hlidacr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hlidacr + url_git: https://github.com/skvrnami/hlidacr +HLMdiag: + version: 0.5.0 + title: Diagnostic Tools for Hierarchical (Multilevel) Linear Models + maintainer: Adam Loy + description: |- + A suite of diagnostic tools for hierarchical + (multilevel) linear models. The tools include + not only leverage and traditional deletion diagnostics (Cook's + distance, covratio, covtrace, and MDFFITS) but also + convenience functions and graphics for residual analysis. Models + can be fit using either lmer in the 'lme4' package or lme in the 'nlme' package. + date_publication: '2021-05-02' + bug_reports: https://github.com/aloy/HLMdiag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HLMdiag + url_git: https://github.com/aloy/HLMdiag +hlt: + version: 1.3.1 + title: Higher-Order Item Response Theory + maintainer: Michael Kleinsasser + description: |- + Higher-order latent trait theory (item response theory). We + implement the generalized partial credit model with a second-order latent + trait structure. Latent regression can be done on the second-order latent + trait. For a pre-print of the methods, + see, "Latent Regression in Higher-Order Item Response Theory with the R + Package hlt" . + date_publication: '2022-08-22' + bug_reports: https://github.com/mkleinsa/hlt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hlt + url_git: https://github.com/mkleinsa/hlt +HMB: + version: '1.1' + title: Hierarchical Model-Based Estimation Approach + maintainer: Svetlana Saarela + description: For estimation of a variable of interest using two sources of auxiliary + information available in a nested structure. For reference see Saarela et al. + (2016) and Saarela et al. (2018) . + date_publication: '2020-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMB + url_git: '' +HMC: + version: '1.1' + title: |- + High Dimensional Mean Comparison with Projection and + Cross-Fitting + maintainer: Tianyu Zhang + description: Provides interpretable High-dimensional Mean Comparison methods (HMC). + For example, users can use them to assess the difference in gene expression between + two treatment groups. It is not a gene-by-gene comparison. Instead, we focus on + the interplay between features and are interested in those that are predictive + of the group label. The methods are valid frequentist tests and give sparse estimates + indicating which features contribute to the test results. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMC + url_git: '' +hmcdm: + version: 2.1.1 + title: Hidden Markov Cognitive Diagnosis Models for Learning + maintainer: Sunbeom Kwon + description: |- + Fitting hidden Markov models of learning under the cognitive diagnosis framework. + The estimation of the hidden Markov diagnostic classification model, + the first order hidden Markov model, the reduced-reparameterized unified learning model, + and the joint learning model for responses and response times. + date_publication: '2023-03-20' + bug_reports: https://github.com/tmsalab/hmcdm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hmcdm + url_git: https://github.com/tmsalab/hmcdm +hmclearn: + version: 0.0.5 + title: Fit Statistical Models Using Hamiltonian Monte Carlo + maintainer: Samuel Thomas + description: |- + Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:. + Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418, + Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" , + Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" , + Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955, + Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034, + Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174. + date_publication: '2020-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hmclearn + url_git: '' +HMDHFDplus: + version: 2.0.6 + title: |- + Read Human Mortality Database and Human Fertility Database Data + from the Web + maintainer: Tim Riffe + description: Utilities for reading data from the Human Mortality Database (), + Human Fertility Database (), and similar databases + from the web or locally into an R session as data.frame objects. These are the + two most widely used sources of demographic data to study basic demographic change, + trends, and develop new demographic methods. Other supported databases at this + time include the Human Fertility Collection (), + The Japanese Mortality Database (), + and the Canadian Human Mortality Database (). + Arguments and data are standardized. + date_publication: '2025-01-21' + bug_reports: https://github.com/timriffe/HMDHFDplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HMDHFDplus + url_git: https://github.com/timriffe/HMDHFDplus +hmeasure: + version: 1.0-2 + title: |- + The H-Measure and Other Scalar Classification Performance + Metrics + maintainer: Christoforos Anagnostopoulos + description: |- + Classification performance metrics that are derived from the ROC + curve of a classifier. The package includes the H-measure performance metric + as described in , + which computes the minimum total misclassification cost, integrating over any + uncertainty about the relative misclassification costs, as per a user-defined + prior. It also offers a one-stop-shop for other scalar metrics of performance, + including sensitivity, specificity and many others, and also offers plotting + tools for ROC curves and related statistics. + date_publication: '2019-02-26' + bug_reports: '' + url: http://www.hmeasure.net + url_cran: https://CRAN.R-project.org/package=hmeasure + url_git: '' +hmer: + version: 1.6.0 + title: History Matching and Emulation Package + maintainer: Andrew Iskauskas + description: |- + A set of objects and functions for Bayes Linear emulation and history matching. + Core functionality includes automated training of emulators to data, diagnostic functions + to ensure suitability, and a variety of proposal methods for generating 'waves' of points. + For details on the mathematical background, there are many papers available on the topic + (see references attached to function help files or the below references); for details of + the functions in this package, consult the manual or help files. + Iskauskas, A, et al. (2024) . + Bower, R.G., Goldstein, M., and Vernon, I. (2010) . + Craig, P.S., Goldstein, M., Seheult, A.H., and Smith, J.A. (1997) . + date_publication: '2024-05-31' + bug_reports: https://github.com/andy-iskauskas/hmer/issues + url: https://hmer-package.github.io/website/ + url_cran: https://CRAN.R-project.org/package=hmer + url_git: https://github.com/andy-iskauskas/hmer +Hmisc: + version: 5.2-2 + title: Harrell Miscellaneous + maintainer: Frank E Harrell Jr + description: |- + Contains many functions useful for data + analysis, high-level graphics, utility operations, functions for + computing sample size and power, simulation, importing and annotating datasets, + imputing missing values, advanced table making, variable clustering, + character string manipulation, conversion of R objects to LaTeX and html code, + recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis. + date_publication: '2025-01-10' + bug_reports: '' + url: https://hbiostat.org/R/Hmisc/ + url_cran: https://CRAN.R-project.org/package=Hmisc + url_git: '' +hmix: + version: 1.0.2 + title: |- + Hidden Markov Model for Predicting Time Sequences with Mixture + Sampling + maintainer: Giancarlo Vercellino + description: An algorithm for time series analysis that leverages hidden Markov + models, cluster analysis, and mixture distributions to segment data, detect patterns + and predict future sequences. + date_publication: '2024-09-10' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/hmix + url_cran: https://CRAN.R-project.org/package=hmix + url_git: '' +HMM: + version: 1.0.1 + title: Hidden Markov Models + maintainer: Lin Himmelmann + description: Easy to use library to setup, apply and make inference with discrete + time and discrete space Hidden Markov Models. + date_publication: '2022-03-23' + bug_reports: '' + url: www.linhi.de + url_cran: https://CRAN.R-project.org/package=HMM + url_git: '' +hmm.discnp: + version: 3.0-9 + title: |- + Hidden Markov Models with Discrete Non-Parametric Observation + Distributions + maintainer: Rolf Turner + description: |- + Fits hidden Markov models with discrete non-parametric + observation distributions to data sets. The observations may + be univariate or bivariate. Simulates data from such models. + Finds most probable underlying hidden states, the most + probable sequences of such states, and the log likelihood + of a collection of observations given the parameters of + the model. Auxiliary predictors are accommodated in the + univariate setting. + date_publication: '2022-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hmm.discnp + url_git: '' +HMMcopula: + version: 1.1.0 + title: |- + Markov Regime Switching Copula Models Estimation and + Goodness-of-Fit + maintainer: Bruno N Remillard + description: Estimation procedures and goodness-of-fit test for several Markov regime + switching models and mixtures of bivariate copula models. The goodness-of-fit + test is based on a Cramer-von Mises statistic and uses Rosenblatt's transform + and parametric bootstrap to estimate the p-value. The proposed methodologies are + described in Nasri, Remillard and Thioub (2020) . + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMMcopula + url_git: '' +HMMEsolver: + version: 0.1.2 + title: |- + A Fast Solver for Henderson Mixed Model Equation via Row + Operations + maintainer: Jiwoong Kim + description: Consider the linear mixed model with normal random effects. A typical + method to solve Henderson's Mixed Model Equations (HMME) is recursive estimation + of the fixed effects and random effects. We provide a fast, stable, and scalable + solver to the HMME without computing matrix inverse. See Kim (2017) + for more details. + date_publication: '2019-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMMEsolver + url_git: '' +HMMextra0s: + version: 1.1.0 + title: Hidden Markov Models with Extra Zeros + maintainer: Ting Wang + description: Contains functions for hidden Markov models with observations having + extra zeros as defined in the following two publications, Wang, T., Zhuang, J., + Obara, K. and Tsuruoka, H. (2016) ; Wang, T., Zhuang, + J., Buckby, J., Obara, K. and Tsuruoka, H. (2018) . + The observed response variable is either univariate or bivariate Gaussian conditioning + on presence of events, and extra zeros mean that the response variable takes on + the value zero if nothing is happening. Hence the response is modelled as a mixture + distribution of a Bernoulli variable and a continuous variable. That is, if the + Bernoulli variable takes on the value 1, then the response variable is Gaussian, + and if the Bernoulli variable takes on the value 0, then the response is zero + too. This package includes functions for simulation, parameter estimation, goodness-of-fit, + the Viterbi algorithm, and plotting the classified 2-D data. Some of the functions + in the package are based on those of the R package 'HiddenMarkov' by David Harte. + This updated version has included an example dataset and R code examples to show + how to transform the data into the objects needed in the main functions. We have + also made changes to increase the speed of some of the functions. + date_publication: '2021-08-03' + bug_reports: '' + url: https://www.stats.otago.ac.nz/?people=ting_wang + url_cran: https://CRAN.R-project.org/package=HMMextra0s + url_git: '' +hmmm: + version: 1.0-5 + title: Hierarchical Multinomial Marginal Models + maintainer: Roberto Colombi + description: Functions for specifying and fitting marginal models for contingency + tables proposed by Bergsma and Rudas (2002) here + called hierarchical multinomial marginal models (hmmm) and their extensions presented + by Bartolucci, Colombi and Forcina (2007) ; + multinomial Poisson homogeneous (mph) models and homogeneous linear predictor + (hlp) models for contingency tables proposed by Lang (2004) + and Lang (2005) . Inequality constraints on the + parameters are allowed and can be tested. + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hmmm + url_git: '' +HMMmlselect: + version: 0.1.6 + title: |- + Determine the Number of States in Hidden Markov Models via + Marginal Likelihood + maintainer: Chu-Lan Michael Kao + description: |- + Provide functions to make estimate the number of states for a hidden Markov + model (HMM) using marginal likelihood method proposed by the authors. + See the Manual.pdf file a detail description of all functions, and a detail tutorial. + date_publication: '2020-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMMmlselect + url_git: '' +HMMpa: + version: 1.0.2 + title: Analysing Accelerometer Data Using Hidden Markov Models + maintainer: Foraita Ronja + description: |- + Analysing time-series accelerometer data to quantify length and + intensity of physical activity using hidden Markov models. + It also contains the traditional cut-off point method. + Witowski V, Foraita R, Pitsiladis Y, Pigeot I, Wirsik N (2014). + . + date_publication: '2025-01-31' + bug_reports: https://github.com/bips-hb/HMMpa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HMMpa + url_git: https://github.com/bips-hb/HMMpa +hmmr: + version: 1.0-0 + title: |- + "Mixture and Hidden Markov Models with R" Datasets and Example + Code + maintainer: Ingmar Visser + description: Datasets and code examples that accompany our book Visser & Speekenbrink + (2021), "Mixture and Hidden Markov Models with R", . + date_publication: '2021-05-27' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=hmmr + url_git: '' +HMMRel: + version: 0.1.1 + title: Hidden Markov Models for Reliability and Maintenance + maintainer: M.L. Gamiz + description: Reliability Analysis and Maintenance Optimization using Hidden Markov + Models (HMM). The use of HMMs to model the state of a system which is not directly + observable and instead certain indicators (signals) of the true situation are + provided via a control system. A hidden model can provide key information about + the system dependability, such as the reliability of the system and related measures. + An estimation procedure is implemented based on the Baum-Welch algorithm. Classical + structures such as K-out-of-N systems and Shock models are illustrated. Finally, + the maintenance of the system is considered in the HMM context and two functions + for new preventive maintenance strategies are considered. Maintenance efficiency + is measured in terms of expected cost. Methods are described in Gamiz, Limnios, + and Segovia-Garcia (2023) . + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMMRel + url_git: '' +hmmTMB: + version: 1.0.2 + title: Fit Hidden Markov Models using Template Model Builder + maintainer: Theo Michelot + description: |- + Fitting hidden Markov models using automatic differentiation + and Laplace approximation, allowing for fast inference and flexible covariate + effects (including random effects and smoothing splines) on model parameters. + The package is described by Michelot (2022) . + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hmmTMB + url_git: https://github.com/TheoMichelot/hmmTMB +HMP: + version: 2.0.1 + title: |- + Hypothesis Testing and Power Calculations for Comparing + Metagenomic Samples from HMP + maintainer: Berkley Shands + description: Using Dirichlet-Multinomial distribution to provide several functions + for formal hypothesis testing, power and sample size calculations for human microbiome + experiments. + date_publication: '2019-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMP + url_git: '' +HMPTrees: + version: '1.4' + title: |- + Statistical Object Oriented Data Analysis of RDP-Based Taxonomic + Trees from Human Microbiome Data + maintainer: Berkley Shands + description: Tools to model, compare, and visualize populations of taxonomic tree + objects. + date_publication: '2017-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMPTrees + url_git: '' +HMR: + version: 1.0.4 + title: Flux Estimation with Static Chamber Data + maintainer: Asger R. Pedersen + description: Statistical analysis of static chamber concentration data for trace + gas flux estimation. + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMR + url_git: '' +hms: + version: 1.1.3 + title: Pretty Time of Day + maintainer: Kirill Müller + description: |- + Implements an S3 class for storing and formatting time-of-day + values, based on the 'difftime' class. + date_publication: '2023-03-21' + bug_reports: https://github.com/tidyverse/hms/issues + url: https://hms.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=hms + url_git: https://github.com/tidyverse/hms +Hmsc: + version: 3.0-13 + title: Hierarchical Model of Species Communities + maintainer: Otso Ovaskainen + description: |- + Hierarchical Modelling of Species Communities (HMSC) is + a model-based approach for analyzing community ecological data. + This package implements it in the Bayesian framework with Gibbs + Markov chain Monte Carlo (MCMC) sampling (Tikhonov et al. (2020) + ). + date_publication: '2022-08-11' + bug_reports: https://github.com/hmsc-r/HMSC/issues/ + url: https://www.helsinki.fi/en/researchgroups/statistical-ecology/software/hmsc + url_cran: https://CRAN.R-project.org/package=Hmsc + url_git: '' +hmsidwR: + version: 1.1.2 + title: Health Metrics and the Spread of Infectious Diseases + maintainer: Federica Gazzelloni + description: A collection of datasets and supporting functions accompanying Health + Metrics and the Spread of Infectious Diseases by Federica Gazzelloni (2024). This + package provides data for health metrics calculations, including Disability-Adjusted + Life Years (DALYs), Years of Life Lost (YLLs), and Years Lived with Disability + (YLDs), as well as additional tools for analyzing and visualizing health data. + Federica Gazzelloni (2024) . + date_publication: '2024-11-13' + bug_reports: https://github.com/Fgazzelloni/hmsidwR/issues + url: https://fgazzelloni.github.io/hmsidwR/ + url_cran: https://CRAN.R-project.org/package=hmsidwR + url_git: https://github.com/Fgazzelloni/hmsidwR +hmsr: + version: 1.0.1 + title: Multipopulation Evolutionary Strategy HMS + maintainer: Wojciech Achtelik + description: |2- + + The HMS (Hierarchic Memetic Strategy) is a composite global optimization + strategy consisting of a multi-population evolutionary strategy and some + auxiliary methods. The HMS makes use of a dynamically-evolving data structure + that provides an organization among the component populations. It is a tree + with a fixed maximal height and variable internal node degree. Each component + population is governed by a particular evolutionary engine. This package + provides a simple R implementation with examples of using different genetic + algorithms as the population engines. References: J. Sawicki, M. Łoś, + M. Smołka, J. Alvarez-Aramberri (2022) . + date_publication: '2023-10-25' + bug_reports: https://github.com/WojtAcht/hms/issues + url: https://wojtacht.github.io/hms/ + url_cran: https://CRAN.R-project.org/package=hmsr + url_git: '' +hmstimer: + version: 0.3.0 + title: '''hms'' Based Timer' + maintainer: Joe Thorley + description: |- + Tracks elapsed clock time using a `hms::hms()` scalar. + It was was originally developed to time Bayesian model runs. + It should not be used to estimate how long extremely fast code takes to execute + as the package code adds a small time cost. + date_publication: '2024-08-19' + bug_reports: https://github.com/poissonconsulting/hmstimer/issues + url: https://poissonconsulting.github.io/hmstimer/ + url_cran: https://CRAN.R-project.org/package=hmstimer + url_git: https://github.com/poissonconsulting/hmstimer +HMTL: + version: 0.1.0 + title: Heterogeneous Multi-Task Feature Learning + maintainer: Yuan Zhong + description: The heterogeneous multi-task feature learning is a data integration + method to conduct joint feature selection across multiple related data sets with + different distributions. The algorithm can combine different types of learning + tasks, including linear regression, Huber regression, adaptive Huber, and logistic + regression. The modified version of Bayesian Information Criterion (BIC) is produced + to measure the model performance. Package is based on Yuan Zhong, Wei Xu, and + Xin Gao (2022) . + date_publication: '2023-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HMTL + url_git: '' +hNMF: + version: '1.0' + title: Hierarchical Non-Negative Matrix Factorization + maintainer: Nicolas Sauwen + description: Hierarchical and single-level non-negative matrix factorization. Several + NMF algorithms are available. + date_publication: '2020-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hNMF + url_git: '' +hnp: + version: 1.2-6 + title: Half-Normal Plots with Simulation Envelopes + maintainer: Rafael de Andrade Moral + description: Generates (half-)normal plots with simulation envelopes using different + diagnostics from a range of different fitted models. A few example datasets are + included. + date_publication: '2018-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hnp + url_git: '' +hoardeR: + version: '0.10' + title: |- + Collect and Retrieve Annotation Data for Various Genomic Data + Using Different Webservices + maintainer: Daniel Fischer + description: Cross-species identification of novel gene candidates using the NCBI + web service is provided. Further, sets of miRNA target genes can be identified + by using the targetscan.org API. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hoardeR + url_git: '' +hoardr: + version: 0.5.5 + title: Manage Cached Files + maintainer: Tamás Stirling + description: |- + Suite of tools for managing cached files, targeting + use in other R packages. Uses 'rappdirs' for cross-platform paths. + Provides utilities to manage cache directories, including targeting + files by path or by key; cached directories can be compressed and + uncompressed easily to save disk space. + date_publication: '2025-01-18' + bug_reports: https://github.com/ropensci/hoardr/issues + url: https://docs.ropensci.org/hoardr/ + url_cran: https://CRAN.R-project.org/package=hoardr + url_git: https://github.com/ropensci/hoardr +HOasso: + version: 1.0.1 + title: Higher Order Assortativity for Complex Networks + maintainer: Alberto Arcagni + description: Allows to evaluate Higher Order Assortativity of complex networks defined + through objects of class 'igraph' from the package of the same name. The package + returns a result also for directed and weighted graphs. References, Arcagni, A., + Grassi, R., Stefani, S., & Torriero, A. (2017) + Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2021) + Arcagni, A., Cerqueti, R., & Grassi, R. (2023) . + date_publication: '2023-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HOasso + url_git: '' +hockeystick: + version: 0.8.5 + title: Download and Visualize Essential Climate Change Data + maintainer: Hernando Cortina + description: 'Provides easy access to essential climate change datasets to non-climate + experts. Users can download the latest raw data from authoritative sources and + view it via pre-defined ''ggplot2'' charts. Datasets include atmospheric CO2, + methane, emissions, instrumental and proxy temperature records, sea levels, Arctic/Antarctic + sea-ice, Hurricanes, and Paleoclimate data. Sources include: NOAA Mauna Loa Laboratory + , Global Carbon Project , + NASA GISTEMP , National Snow and Sea Ice + Data Center , CSIRO , + NOAA Laboratory for Satellite Altimetry + and HURDAT Atlantic Hurricane Database , + Vostok Paleo carbon dioxide and temperature data: .' + date_publication: '2024-11-25' + bug_reports: https://github.com/cortinah/hockeystick/issues + url: https://cortinah.github.io/hockeystick/ + url_cran: https://CRAN.R-project.org/package=hockeystick + url_git: https://github.com/cortinah/hockeystick +HodgesTools: + version: 1.0.0 + title: Common Use Tools for Genomic Analysis + maintainer: Tyler Hansen + description: Built by Hodges lab members for current and future Hodges lab members. + Other individuals are welcome to use as well. Provides useful functions that the + lab uses everyday to analyze various genomic datasets. Critically, only general + use functions are provided; functions specific to a given technique are reserved + for a separate package. As the lab grows, we expect to continue adding functions + to the package to build on previous lab members code. + date_publication: '2022-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HodgesTools + url_git: '' +holi: + version: 0.1.1 + title: Higher Order Likelihood Inference Web Applications + maintainer: Mackson Ncube + description: |- + Higher order likelihood inference is a promising approach for + analyzing small sample size data. The 'holi' package provides web applications + for higher order likelihood inference. It currently supports linear, logistic, + and Poisson generalized linear models through the rstar_glm() function, based + on Pierce and Bellio (2017) and 'likelihoodAsy'. + The package offers two main features: LA_rstar(), which launches an interactive + 'shiny' application allowing users to fit models with rstar_glm() through their + web browser, and sim_rstar_glm_pgsql(), which streamlines the process of + launching a web-based 'shiny' simulation application that saves results to a + user-created 'PostgreSQL' database. + date_publication: '2024-08-25' + bug_reports: https://github.com/mightymetrika/holi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=holi + url_git: https://github.com/mightymetrika/holi +holiglm: + version: 1.0.1 + title: Holistic Generalized Linear Models + maintainer: Benjamin Schwendinger + description: Holistic generalized linear models (HGLMs) extend generalized linear + models (GLMs) by enabling the possibility to add further constraints to the model. + The 'holiglm' package simplifies estimating HGLMs using convex optimization. Additional + information about the package can be found in the reference manual, the 'README' + and the accompanying paper . + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=holiglm + url_git: '' +holland: + version: 0.1.2-1 + title: Statistics for Holland's Theory of Vocational Choice + maintainer: Joerg-Henrik Heine + description: |- + Offers a convenient way to compute parameters + in the framework of the theory of vocational choice introduced by + J.L. Holland, (1997). A comprehensive summary to this theory + of vocational choice is given in Holland, J.L. (1997). Making vocational + choices. A theory of vocational personalities and work environments. + Lutz, FL: Psychological Assessment. + date_publication: '2021-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=holland + url_git: '' +hollr: + version: 1.0.0 + title: Chat Completion and Text Annotation with Local and OpenAI Models + maintainer: Jason Timm + description: Enables chat completion and text annotation with local and 'OpenAI' + language models, supporting batch processing, multiple annotators, + and consistent output formats. + date_publication: '2024-10-15' + bug_reports: https://github.com/jaytimm/hollr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hollr + url_git: https://github.com/jaytimm/hollr +holobiont: + version: 0.1.2 + title: Microbiome Analysis Tools + maintainer: Sharon Bewick + description: We provide functions for identifying the core community phylogeny in + any microbiome, drawing phylogenetic Venn diagrams, calculating the core Faith’s + PD for a set of communities, and calculating the core UniFrac distance between + two sets of communities. All functions rely on construction of a core community + phylogeny, which is a phylogeny where branches are defined based on their presence + in multiple samples from a single type of habitat. Our package provides two options + for constructing the core community phylogeny, a tip-based approach, where the + core community phylogeny is identified based on incidence of leaf nodes and a + branch-based approach, where the core community phylogeny is identified based + on incidence of individual branches. We suggest use of the microViz package, which + can be downloaded from the website provided under Additional repositories. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=holobiont + url_git: '' +holodeck: + version: 0.2.2 + title: A Tidy Interface for Simulating Multivariate Data + maintainer: Eric Scott + description: |- + Provides pipe-friendly (%>%) wrapper functions for MASS::mvrnorm() to create simulated multivariate data sets + with groups of variables with different degrees of variance, covariance, and effect size. + date_publication: '2023-08-25' + bug_reports: https://github.com/Aariq/holodeck/issues + url: '' + url_cran: https://CRAN.R-project.org/package=holodeck + url_git: https://github.com/Aariq/holodeck +Holomics: + version: 1.1.1 + title: |- + An User-Friendly R 'shiny' Application for Multi-Omics Data + Integration and Analysis + maintainer: Katharina Munk + description: |- + A 'shiny' application, which allows you to perform single- and + multi-omics analyses using your own omics datasets. After the upload + of the omics datasets and a metadata file, single-omics is performed + for feature selection and dataset reduction. These datasets are used + for pairwise- and multi-omics analyses, where automatic tuning is + done to identify correlations between the datasets - the end goal + of the recommended 'Holomics' workflow. + Methods used in the package were implemented in the package 'mixomics' + by Florian Rohart,Benoît Gautier,Amrit Singh,Kim-Anh Lê Cao (2017) + and are described there in further detail. + date_publication: '2024-06-07' + bug_reports: https://github.com/MolinLab/Holomics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Holomics + url_git: https://github.com/MolinLab/Holomics +homals: + version: 1.0-10 + title: Gifi Methods for Optimal Scaling + maintainer: Patrick Mair + description: Performs a homogeneity analysis (multiple correspondence analysis) + and various extensions. Rank restrictions on the category quantifications can + be imposed (nonlinear PCA). The categories are transformed by means of optimal + scaling with options for nominal, ordinal, and numerical scale levels (for rank-1 + restrictions). Variables can be grouped into sets, in order to emulate regression + analysis and canonical correlation analysis. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=homals + url_git: '' +Homeric: + version: 0.1-3 + title: Doughnut Plots + maintainer: Lawrence Hudson + description: A simple implementation of doughnut plots - pie charts with a blank + center. The package is named after Homer Simpson - arguably the best-known lover + of doughnuts. + date_publication: '2016-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Homeric + url_git: '' +hommel: + version: '1.8' + title: |- + Methods for Closed Testing with Simes Inequality, in Particular + Hommel's Method + maintainer: Jelle Goeman + description: Provides methods for closed testing using Simes local tests. In particular, + calculates adjusted p-values for Hommel's multiple testing method, and provides + lower confidence bounds for true discovery proportions. A robust but more conservative + variant of the closed testing procedure that does not require the assumption of + Simes inequality is also implemented. The methods have been described in detail + in Goeman et al (Biometrika 106, 841-856, 2019). + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hommel + url_git: '' +homnormal: + version: '0.1' + title: Tests of Homogeneity of Variances + maintainer: Fikri Gökpınar + description: |- + Most common exact, asymptotic and resample based tests are provided for testing the + homogeneity of variances of k normal distributions under normality. + These tests are Barlett, Bhandary & Dai, Brown & Forsythe, Chang et al., Gokpinar & Gokpinar, Levene, Liu and Xu, Gokpinar. + Also, a data generation function from multiple normal distribution is provided using any multiple normal parameters. + Bartlett, M. S. (1937) + Bhandary, M., & Dai, H. (2008) + Brown, M. B., & Forsythe, A. B. (1974). + Chang, C. H., Pal, N., & Lin, J. J. (2017) + Gokpinar E. & Gokpinar F. (2017) + Liu, X., & Xu, X. (2010) + Levene, H. (1960) + Gökpınar, E. (2020) . + date_publication: '2023-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=homnormal + url_git: '' +homologene: + version: 1.4.68.19.3.27 + title: Quick Access to Homologene and Gene Annotation Updates + maintainer: Ogan Mancarci + description: |- + A wrapper for the homologene database by the National Center for + Biotechnology Information ('NCBI'). It allows searching for gene homologs across + species. Data in this package can be found at . + The package also includes an updated version of the homologene database where + gene identifiers and symbols are replaced with their latest (at the time of + submission) version and functions to fetch latest annotation data to keep updated. + date_publication: '2019-03-28' + bug_reports: https://github.com/oganm/homologene/issues + url: '' + url_cran: https://CRAN.R-project.org/package=homologene + url_git: https://github.com/oganm/homologene +homomorpheR: + version: 0.2-2 + title: Homomorphic Computations in R + maintainer: Balasubramanian Narasimhan + description: |- + Homomorphic computations in R for privacy-preserving applications. Currently only + the Paillier Scheme is implemented. + date_publication: '2019-01-23' + bug_reports: http://github.com/bnaras/homomorpheR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=homomorpheR + url_git: http://github.com/bnaras/homomorpheR +HomomorphicEncryption: + version: 0.9.0 + title: BFV, BGV, CKKS Schema for Fully Homomorphic Encryption + maintainer: Bastiaan Quast + description: Implements the Brakerski-Fan-Vercauteren (BFV, 2012) , + Brakerski-Gentry-Vaikuntanathan (BGV, 2014) , and Cheon-Kim-Kim-Song + (CKKS, 2016) schema for Fully Homomorphic + Encryption. The included vignettes demonstrate the encryption procedures. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HomomorphicEncryption + url_git: '' +HonestDiD: + version: 0.2.6 + title: |- + Robust Inference in Difference-in-Differences and Event Study + Designs + maintainer: Ashesh Rambachan + description: Provides functions to conduct robust inference in difference-in-differences + and event study designs by implementing the methods developed in Rambachan & Roth + (2023) , "A More Credible Approach to Parallel Trends" + [Previously titled "An Honest Approach..."]. Inference is conducted under a weaker + version of the parallel trends assumption. Uniformly valid confidence sets are + constructed based upon conditional confidence sets, fixed-length confidence sets + and hybridized confidence sets. + date_publication: '2024-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HonestDiD + url_git: '' +hoopR: + version: 2.1.0 + title: Access Men's Basketball Play by Play Data + maintainer: Saiem Gilani + description: |- + A utility to quickly obtain clean and tidy men's + basketball play by play data. Provides functions to access + live play by play and box score data from ESPN with shot locations + when available. It is also a full NBA Stats API wrapper. + It is also a scraping and aggregating interface for Ken Pomeroy's + men's college basketball statistics website. It provides users with an + active subscription the capability to scrape the website tables and + analyze the data for themselves. + date_publication: '2023-11-25' + bug_reports: https://github.com/sportsdataverse/hoopR/issues + url: http://hoopr.sportsdataverse.org/ + url_cran: https://CRAN.R-project.org/package=hoopR + url_git: https://github.com/sportsdataverse/hoopR +hopbyhop: + version: '3.41' + title: Transmissions and Receptions in a Hop by Hop Network + maintainer: Christian E. Galarza + description: Computes the expectation of the number of transmissions and receptions + considering a Hop-by-Hop transport model with limited number of retransmissions + per packet. It provides the theoretical results shown in Palma et. al.(2016) + and also estimated values based on Monte Carlo simulations. It is also possible + to consider random data and ACK probabilities. + date_publication: '2019-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hopbyhop + url_git: '' +hopit: + version: 0.11.6 + title: |- + Hierarchical Ordered Probit Models with Application to Reporting + Heterogeneity + maintainer: Maciej J. Danko + description: Self-reported health, happiness, attitudes, and other statuses or perceptions + are often the subject of biases that may come from different sources. For example, + the evaluation of an individual’s own health may depend on previous medical diagnoses, + functional status, and symptoms and signs of illness; as on well as life-style + behaviors, including contextual social, gender, age-specific, linguistic and other + cultural factors (Jylha 2009 ; Oksuzyan et + al. 2019 ). The hopit package offers versatile + functions for analyzing different self-reported ordinal variables, and for helping + to estimate their biases. Specifically, the package provides the function to fit + a generalized ordered probit model that regresses original self-reported status + measures on two sets of independent variables (King et al. 2004 ; + Jurges 2007 ; Oksuzyan et al. 2019 ). + The first set of variables (e.g., health variables) included in the regression + are individual statuses and characteristics that are directly related to the self-reported + variable. In the case of self-reported health, these could be chronic conditions, + mobility level, difficulties with daily activities, performance on grip strength + tests, anthropometric measures, and lifestyle behaviors. The second set of independent + variables (threshold variables) is used to model cut-points between adjacent self-reported + response categories as functions of individual characteristics, such as gender, + age group, education, and country (Oksuzyan et al. 2019 ). + The model helps to adjust for specific socio-demographic and cultural differences + in how the continuous latent health is projected onto the ordinal self-rated measure. + The fitted model can be used to calculate an individual predicted latent status + variable, a latent index, and standardized latent coefficients; and makes it possible + to reclassify a categorical status measure that has been adjusted for inter-individual + differences in reporting behavior. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hopit + url_git: '' +hopkins: + version: '1.1' + title: Calculate Hopkins Statistic for Clustering + maintainer: Kevin Wright + description: Calculate Hopkins statistic to assess the clusterability of data. See + Wright (2023) . + date_publication: '2023-08-20' + bug_reports: https://github.com/kwstat/hopkins/ + url: https://kwstat.github.io/hopkins/ + url_cran: https://CRAN.R-project.org/package=hopkins + url_git: '' +HoRM: + version: 0.1.3 + title: |- + Supplemental Functions and Datasets for "Handbook of Regression + Methods" + maintainer: Derek S. Young + description: Supplement for the book "Handbook of Regression Methods" by D. S. Young. Some + datasets used in the book are included and documented. Wrapper functions are + included that simplify the examples in the textbook, such as code for constructing + a regressogram and expanding ANOVA tables to reflect the total sum of squares. + date_publication: '2021-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HoRM + url_git: https://github.com/dsy109/HoRM +hornpa: + version: 1.1.0 + title: Horn's (1965) Test to Determine the Number of Components/Factors + maintainer: Francis Huang + description: A stand-alone function that generates a user specified number of random + datasets and computes eigenvalues using the random datasets (i.e., implements + Horn's [1965, Psychometrika] parallel analysis ). + Users then compare the resulting eigenvalues (the mean or the specified percentile) + from the random datasets (i.e., eigenvalues resulting from noise) to the eigenvalues + generated with the user's data. Can be used for both principal components analysis + (PCA) and common/exploratory factor analysis (EFA). The output table shows how + large eigenvalues can be as a result of merely using randomly generated datasets. + If the user's own dataset has actual eigenvalues greater than the corresponding + eigenvalues, that lends support to retain that factor/component. In other words, + if the i(th) eigenvalue from the actual data was larger than the percentile of + the (i)th eigenvalue generated using randomly generated data, empirical support + is provided to retain that factor/component. Horn, J. (1965). A rationale and + test for the number of factors in factor analysis. Psychometrika, 32, 179-185. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hornpa + url_git: '' +Horsekicks: + version: 1.0.2 + title: Provide Extensions to the Prussian Army Death by Horsekick Data + maintainer: Bill Venables + description: |- + We provide extensions to the classical dataset "Example 4: + Death by the kick of a horse in the Prussian Army" first + used by Ladislaus von Bortkeiwicz in his treatise on + the Poisson distribution "Das Gesetz der kleinen Zahlen", + . As well as an + extended time series for the horse-kick death data, we also + provide, in parallel, deaths by falling from a horse and by + drowning. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Horsekicks + url_git: '' +horseshoe: + version: 0.2.0 + title: Implementation of the Horseshoe Prior + maintainer: Stephanie van der Pas + description: |- + Contains functions for applying the horseshoe prior to high- + dimensional linear regression, yielding the posterior mean and credible + intervals, amongst other things. The key parameter tau can be equipped with + a prior or estimated via maximum marginal likelihood estimation (MMLE). + The main function, horseshoe, is for linear regression. In addition, there + are functions specifically for the sparse normal means problem, allowing + for faster computation of for example the posterior mean and posterior + variance. Finally, there is a function available to perform variable + selection, using either a form of thresholding, or credible intervals. + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=horseshoe + url_git: '' +horseshoenlm: + version: 0.0.6 + title: Nonlinear Regression using Horseshoe Prior + maintainer: Arnab Kumar Maity + description: |- + Provides the posterior estimates of the regression coefficients when horseshoe prior is specified. + The regression models considered here are logistic model for binary response and + log normal accelerated failure time model for right censored survival response. + The linear model analysis is also available for completeness. + All models provide deviance information criterion and widely applicable information criterion. + See Maity et. al. (2019) Maity et. al. (2020). + date_publication: '2020-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=horseshoenlm + url_git: '' +hosm: + version: 0.1.0 + title: High Order Spatial Matrix + maintainer: Fadhlul Mubarak + description: Automatically displays the order and spatial weighting matrix of the + distance between locations. This concept was derived from the research of Mubarak, + Aslanargun, and Siklar (2021) and Mubarak, Aslanargun, + and Siklar (2022) . Distance data between locations + can be imported from 'Ms. Excel', 'maps' package or created in 'R' programming + directly. This package also provides 5 simulations of distances between locations + derived from fictitious data, the 'maps' package, and from research by Mubarak, + Aslanargun, and Siklar (2022) . + date_publication: '2023-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hosm + url_git: https://github.com/mubarakfadhlul/hosm +HospitalNetwork: + version: 0.9.4 + title: Building Networks of Hospitals Through Patients Transfers + maintainer: Pascal Crépey + description: |- + Set of tools to help interested researchers to build hospital networks + from data on hospitalized patients transferred between hospitals. Methods provided + have been used in Donker T, Wallinga J, Grundmann H. (2010) , + and Nekkab N, Crépey P, Astagneau P, Opatowski L, Temime L. (2020) . + date_publication: '2024-12-22' + bug_reports: https://github.com/PascalCrepey/HospitalNetwork/issues + url: https://pascalcrepey.github.io/HospitalNetwork/ + url_cran: https://CRAN.R-project.org/package=HospitalNetwork + url_git: '' +hospitals: + version: 0.1.0 + title: Portuguese 'NHS' Hospitals + maintainer: Ramiro Magno + description: A data set of the Portuguese 'NHS' hospitals. + date_publication: '2021-11-26' + bug_reports: https://github.com/nhs-pt/hospitals/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hospitals + url_git: https://github.com/nhs-pt/hospitals +hot.deck: + version: '1.2' + title: Multiple Hot Deck Imputation + maintainer: Jeff Gill + description: Performs multiple hot-deck imputation of categorical and continuous + variables in a data frame. + date_publication: '2021-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hot.deck + url_git: '' +Hotelling: + version: 1.0-8 + title: Hotelling's T^2 Test and Variants + maintainer: James Curran + description: A set of R functions which implements Hotelling's T^2 test and some + variants of it. Functions are also included for Aitchison's additive log ratio + and centred log ratio transformations. + date_publication: '2021-09-09' + bug_reports: https://github.com/jmcurran/Hotelling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Hotelling + url_git: https://github.com/jmcurran/Hotelling +HotellingEllipse: + version: 1.2.0 + title: Hotelling’s T-Squared Statistic and Ellipse + maintainer: Christian L. Goueguel + description: Functions to calculate the Hotelling’s T-squared statistic and corresponding + confidence ellipses. Provides the semi-axes of the Hotelling’s T-squared ellipses + at 95% and 99% confidence levels. Enables users to obtain the coordinates in two + or three dimensions at user-defined confidence levels, allowing for the construction + of 2D or 3D ellipses with customized confidence levels. Bro and Smilde (2014) + . Brereton (2016) . + date_publication: '2024-07-04' + bug_reports: https://github.com/ChristianGoueguel/HotellingEllipse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HotellingEllipse + url_git: https://github.com/ChristianGoueguel/HotellingEllipse +hotspot: + version: '1.0' + title: Software Hotspot Analysis + maintainer: Csaba Farago + description: Contains data for software hotspot analysis, along with a function + performing the analysis itself. + date_publication: '2015-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hotspot + url_git: '' +hotspots: + version: 1.0.3 + title: Hot Spots + maintainer: Anthony Darrouzet-Nardi + description: The hotspots package is designed to look within a set of measured values + of a variable and identify values that are disproportionately high based on both + the deviance of any given value from a statistical distribution and its similarity + to other values. Because this relative magnitude of each value is taken into account, + a value that is a statistical outlier may not always be a hot spot if other values + are similarly large. + date_publication: '2018-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hotspots + url_git: '' +housingData: + version: 0.3.0 + title: U.S. Housing Data from 2008 to 2016 + maintainer: Ryan Hafen + description: Monthly median home listing, sale price per square foot, and number + of units sold for 2984 counties in the contiguous United States From 2008 to January + 2016. Additional data sets containing geographical information and links to Wikipedia + are also included. + date_publication: '2016-03-17' + bug_reports: https://github.com/hafen/housingData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=housingData + url_git: http://github.com/hafen/housingData +hover: + version: 0.1.1 + title: CSS Animations for 'shiny' Button Elements + maintainer: Tyler Littlefield + description: |- + A wrapper around a CSS library called 'Hover.css', intended for use + in 'shiny' applications. + date_publication: '2021-03-20' + bug_reports: https://github.com/r4fun/hover/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hover + url_git: https://github.com/r4fun/hover +howler: + version: 0.3.0 + title: '''Shiny'' Extension of ''howler.js''' + maintainer: Ashley Baldry + description: |- + Audio interactivity within 'shiny' applications using 'howler.js'. Enables the + status of the audio player to be sent from the UI to the server, and events such as + playing and pausing the audio can be triggered from the server. + date_publication: '2024-06-04' + bug_reports: https://github.com/ashbaldry/howler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=howler + url_git: https://github.com/ashbaldry/howler +howManyImputations: + version: 0.2.5 + title: |- + Calculate How many Imputations are Needed for Multiple + Imputation + maintainer: Josh Errickson + description: |- + When performing multiple imputations, while 5-10 imputations are + sufficient for obtaining point estimates, a larger number of + imputations are needed for proper standard error estimates. + This package allows you to calculate how many imputations are + needed, following the work of von Hippel (2020) + . + date_publication: '2024-03-15' + bug_reports: https://github.com/josherrickson/howManyImputations/issues/ + url: https://errickson.net/howManyImputations/ + url_cran: https://CRAN.R-project.org/package=howManyImputations + url_git: '' +howzatR: + version: 1.0.1 + title: Useful Functions for Cricket Analysis + maintainer: Luke Lockley + description: Helping to calculate cricket specific problems in a tidy & simple manner. + date_publication: '2022-09-09' + bug_reports: https://github.com/lukelockley/howzatR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=howzatR + url_git: https://github.com/lukelockley/howzatR +hpa: + version: 1.3.3 + title: Distributions Hermite Polynomial Approximation + maintainer: Potanin Bogdan + description: Multivariate conditional and marginal densities, moments, cumulative + distribution functions as well as binary choice and sample selection models based + on Hermite polynomial approximation which was proposed and described by A. Gallant + and D. W. Nychka (1987) . + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hpa + url_git: '' +hpackedbubble: + version: 0.1.0 + title: Create Split Packed Bubble Charts + maintainer: Zhenxing Cheng + description: By binding R functions and the 'Highcharts' + charting library, 'hpackedbubble' package provides a simple way to draw split + packed bubble charts. + date_publication: '2019-08-19' + bug_reports: https://github.com/czxa/hpackedbubble/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hpackedbubble + url_git: https://github.com/czxa/hpackedbubble +hpcwld: + version: 0.6-5 + title: |- + High Performance Cluster Models Based on Kiefer-Wolfowitz + Recursion + maintainer: Alexander Rumyantsev + description: |- + Probabilistic models describing the behavior + of workload and queue on a High Performance Cluster and computing GRID + under FIFO service discipline basing on modified Kiefer-Wolfowitz + recursion. Also sample data for inter-arrival times, service times, + number of cores per task and waiting times of HPC of Karelian + Research Centre are included, measurements took place from 06/03/2009 to 02/30/2011. + Functions provided to import/export workload traces in Standard Workload Format (swf). + Stability condition of the model may be verified either exactly, or approximately. + Stability analysis: see Rumyantsev and Morozov (2017) , + workload recursion: see Rumyantsev (2014) . + date_publication: '2022-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hpcwld + url_git: '' +hpfilter: + version: 1.0.2 + title: The One- And Two-Sided Hodrick-Prescott Filter + maintainer: Alexandru Monahov + description: |- + Provides two functions that implement the one-sided and + two-sided versions of the Hodrick-Prescott filter. The one-sided + version is a Kalman filter-based implementation, whereas the two- + sided version uses sparse matrices for improved efficiency. + References: + Hodrick, R. J., and Prescott, E. C. (1997) + Mcelroy, T. (2008) + Meyer-Gohde, A. (2010) + For more references, see the vignette. + date_publication: '2023-05-28' + bug_reports: '' + url: https://www.alexandrumonahov.eu.org/projects + url_cran: https://CRAN.R-project.org/package=hpfilter + url_git: '' +hpiR: + version: 0.3.2 + title: House Price Indexes + maintainer: Andy Krause + description: |- + Compute house price indexes and series using a variety of different methods and + models common through the real estate literature. Evaluate index 'goodness' based + on accuracy, volatility and revision statistics. Background on basic model construction + for repeat sales models can be found at: Case and Quigley (1991) + and for hedonic pricing models at: + Bourassa et al (2006) . The package author's working paper on the + random forest approach to house price indexes can be found at: . + date_publication: '2020-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hpiR + url_git: https://www.github.com/andykrause/hpiR +HPLB: + version: 1.0.0 + title: High-Probability Lower Bounds for the Total Variance Distance + maintainer: Loris Michel + description: |- + An implementation of high-probability lower bounds for the total variance distance + as introduced in Michel & Naef & Meinshausen (2020) . An estimated + lower-bound (with high-probability) on the total variation distance between two probability distributions from which + samples are observed can be obtained with the function HPLB. + date_publication: '2020-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HPLB + url_git: '' +HQM: + version: '1.0' + title: |- + Superefficient Estimation of Future Conditional Hazards Based on + Marker Information + maintainer: Dimitrios Bagkavos + description: Provides a nonparametric smoothed kernel estimator for the future conditional + hazard rate function when time-dependent covariates are present, a bandwidth selector + for the estimator's implementation and pointwise and uniform confidence bands. + Methods used in the package refer to Bagkavos, Isakson, Mammen, Nielsen and Proust-Lima + (2025) . + date_publication: '2025-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HQM + url_git: '' +hqmisc: + version: 0.2-1 + title: Miscellaneous Convenience Functions and Dataset + maintainer: Hugo Quene + description: |- + Miscellaneous convenience functions and wrapper functions + to convert frequencies between Hz, semitones, mel and Bark, + to create a matrix of dummy columns from a factor, + to determine whether x lies in range [a,b], + and to add a bracketed line to an existing plot. + This package also contains an example data set of a stratified sample + of 80 talkers of Dutch. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hqmisc + url_git: '' +hqreg: + version: 1.4-1 + title: |- + Regularization Paths for Lasso or Elastic-Net Penalized Huber + Loss Regression and Quantile Regression + maintainer: Congrui Yi + description: 'Offers efficient algorithms for fitting regularization paths for lasso + or elastic-net penalized regression models with Huber loss, quantile loss or squared + loss. Reference: Congrui Yi and Jian Huang (2017) .' + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hqreg + url_git: https://github.com/CY-dev/hqreg +hR: + version: 0.2.50 + title: Toolkit for Data Analytics in Human Resources + maintainer: Dale Kube + description: Transform and analyze workforce data in meaningful ways for human resources + (HR) analytics. Get started with workforce planning using a simple Shiny app. + date_publication: '2021-01-14' + bug_reports: https://github.com/dalekube/hR + url: '' + url_cran: https://CRAN.R-project.org/package=hR + url_git: '' +hrbrthemes: + version: 0.8.7 + title: Additional Themes, Theme Components and Utilities for 'ggplot2' + maintainer: Bob Rudis + description: |- + A compilation of extra 'ggplot2' themes, scales and utilities, including a + spell check function for plot label fields and an overall emphasis on typography. + A copy of the 'Google' font 'Roboto Condensed' is also included. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hrbrthemes + url_git: '' +hrcomprisk: + version: 0.1.1 + title: Nonparametric Assessment Between Competing Risks Hazard Ratios + maintainer: Daniel Antiporta + description: Nonparametric cumulative-incidence based estimation of the ratios of + sub-hazard ratios to cause-specific hazard ratios using the approach from Ng et + al. (2020). + date_publication: '2020-01-21' + bug_reports: https://github.com/AntiportaD/hrcomprisk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hrcomprisk + url_git: https://github.com/AntiportaD/hrcomprisk +hrf: + version: 0.1.3 + title: Hemodynamic Response Function + maintainer: Amanda Mejia + description: |- + Computes the hemodynamic response function (HRF) for task + functional magnetic resonance imaging (fMRI) data. Also includes functions + for constructing a design matrix from task fMRI event timings, and for + comparing multiple design matrices in a general linear model (GLM). A + wrapper function is provided for GLM analysis of CIFTI-format data. Lastly, + there are supporting functions which provide visual summaries of the + HRFs and design matrices. + date_publication: '2025-01-30' + bug_reports: https://github.com/mandymejia/hrf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hrf + url_git: https://github.com/mandymejia/hrf +hrqglas: + version: 1.1.0 + title: Group Variable Selection for Quantile and Robust Mean Regression + maintainer: Shaobo Li + description: |- + A program that conducts group variable selection for quantile and robust mean + regression (Sherwood and Li, 2022). The group lasso penalty (Yuan and Lin, 2006) is used for + group-wise variable selection. Both of the quantile and mean regression models are based on the Huber loss. + Specifically, with the tuning parameter in the Huber loss approaching to 0, the quantile check + function can be approximated by the Huber loss for the median and the tilted version of + Huber loss at other quantiles. Such approximation provides computational efficiency and stability, and + has also been shown to be statistical consistent. + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hrqglas + url_git: GitHub:https://github.com/shaobo-li/hrqglas +hrt: + version: 1.0.1 + title: Heteroskedasticity Robust Testing + maintainer: David Preinerstorfer + description: 'Functions for testing affine hypotheses on the regression coefficient + vector in regression models with heteroskedastic errors: (i) a function for computing + various test statistics (in particular using HC0-HC4 covariance estimators based + on unrestricted or restricted residuals); (ii) a function for numerically approximating + the size of a test based on such test statistics and a user-supplied critical + value; and, most importantly, (iii) a function for determining size-controlling + critical values for such test statistics and a user-supplied significance level + (also incorporating a check of conditions under which such a size-controlling + critical value exists). The three functions are based on results in Poetscher + and Preinerstorfer (2021) "Valid Heteroskedasticity Robust Testing" .' + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hrt + url_git: '' +hrtlFMC: + version: 0.1.0 + title: |- + Half Replicate of Two Level Factorial Run Order with Minimum + Level Changes + maintainer: Bijoy Chanda + description: It is used to construct run sequences with minimum changes for half + replicate of two level factorial run order. Experimenter can save time and resources + by minimizing the number of changes in levels of individual factor and therefore + the total number of changes. It consists of the function minimal_hrtlf(). This + technique can be employed to any half replicate of two level factorial run order + where the number of factors are greater than two. In Design of Experiments (DOE) + theory, two level of a factor can be represented as integers e.g. - 1 for low + and 1 for high. User is expected to enter total number of factors to be considered + in the experiment. minimal_hrtlf() provides the required run sequences for the + input number of factors. The output also gives the number of changes of each + factor along with total number of changes in the run sequence. Due to restricted + randomization the minimally changed run sequences of half replicate of two level + factorial run order will be affected by trend effect. The output also provides + the Trend Factor value of the run order. Trend factor value will lies between + 0 to 1. Higher the values, lesser the influence of trend effects on the run order. + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hrtlFMC + url_git: '' +HRTnomaly: + version: 25.2.25 + title: Historical, Relational, and Tail Anomaly-Detection Algorithms + maintainer: Luca Sartore + description: |- + The presence of outliers in a dataset can substantially bias the + results of statistical analyses. To correct for outliers, micro edits are + manually performed on all records. A set of constraints and decision rules + is typically used to aid the editing process. However, straightforward + decision rules might overlook anomalies arising from disruption of linear + relationships. Computationally efficient methods are provided to + identify historical, tail, and relational anomalies at the data-entry + level (Sartore et al., 2024; ). A score statistic + is developed for each anomaly type, using a distribution-free approach + motivated by the Bienaymé-Chebyshev's inequality, and fuzzy logic is used + to detect cellwise outliers resulting from different types of anomalies. + Each data entry is individually scored and individual scores are combined + into a final score to determine anomalous entries. In contrast to fuzzy + logic, Bayesian bootstrap and a Bayesian test based on empirical + likelihoods are also provided as studied by Sartore et + al. (2024; ). These algorithms allow for a more + nuanced approach to outlier detection, as it can identify outliers at + data-entry level which are not obviously distinct from the rest of the + data. + --- + This research was supported in part by the U.S. Department of Agriculture, + National Agriculture Statistics Service. The findings and conclusions in + this publication are those of the authors and should not be construed to + represent any official USDA, or US Government determination or policy. + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HRTnomaly + url_git: '' +HRW: + version: 1.0-5 + title: |- + Datasets, Functions and Scripts for Semiparametric Regression + Supporting Harezlak, Ruppert & Wand (2018) + maintainer: Matt P. Wand + description: 'The book "Semiparametric Regression with R" by J. Harezlak, D. Ruppert + & M.P. Wand (2018, Springer; ISBN: 978-1-4939-8851-8) makes use of datasets and + scripts to explain semiparametric regression concepts. Each of the book''s scripts + are contained in this package as well as datasets that are not within other R + packages. Functions that aid semiparametric regression analysis are also included.' + date_publication: '2021-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HRW + url_git: '' +HSAR: + version: 0.6.0 + title: Hierarchical Spatial Autoregressive Model + maintainer: Wenbo Lv + description: 'A Hierarchical Spatial Autoregressive Model (HSAR), based on a Bayesian + Markov Chain Monte Carlo (MCMC) algorithm (Dong and Harris (2014) ). + The creation of this package was supported by the Economic and Social Research + Council (ESRC) through the Applied Quantitative Methods Network: Phase II, grant + number ES/K006460/1.' + date_publication: '2024-12-23' + bug_reports: https://github.com/spatlyu/HSAR/issues + url: https://spatlyu.github.io/HSAR/ + url_cran: https://CRAN.R-project.org/package=HSAR + url_git: https://github.com/spatlyu/HSAR +HSAUR: + version: 1.3-10 + title: A Handbook of Statistical Analyses Using R (1st Edition) + maintainer: Torsten Hothorn + description: |- + Functions, data sets, analyses and examples from the book + ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten + Hothorn, Chapman & Hall/CRC, 2006). The first chapter + of the book, which is entitled ''An Introduction to R'', + is completely included in this package, for all other chapters, + a vignette containing all data analyses is available. + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HSAUR + url_git: '' +HSAUR2: + version: 1.1-20 + title: A Handbook of Statistical Analyses Using R (2nd Edition) + maintainer: Torsten Hothorn + description: |- + Functions, data sets, analyses and examples from the + second edition of the book + ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten + Hothorn, Chapman & Hall/CRC, 2008). The first chapter + of the book, which is entitled ''An Introduction to R'', + is completely included in this package, for all other chapters, + a vignette containing all data analyses is available. In addition, + the package contains Sweave code for producing slides for selected + chapters (see HSAUR2/inst/slides). + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HSAUR2 + url_git: '' +HSAUR3: + version: 1.0-15 + title: A Handbook of Statistical Analyses Using R (3rd Edition) + maintainer: Torsten Hothorn + description: |- + Functions, data sets, analyses and examples from the + third edition of the book + ''A Handbook of Statistical Analyses Using R'' (Torsten Hothorn and Brian S. + Everitt, Chapman & Hall/CRC, 2014). The first chapter + of the book, which is entitled ''An Introduction to R'', + is completely included in this package, for all other chapters, + a vignette containing all data analyses is available. In addition, + Sweave source code for slides of selected chapters is included in + this package (see HSAUR3/inst/slides). The publishers web page is + ''. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HSAUR3 + url_git: '' +hscovar: + version: 0.4.2 + title: Calculation of Covariance Between Markers for Half-Sib Families + maintainer: Dörte Wittenburg + description: |- + The theoretical covariance between pairs of markers is calculated + from either paternal haplotypes and maternal linkage disequilibrium (LD) or + vise versa. A genetic map is required. Grouping of markers is based on the + correlation matrix and a representative marker is suggested for each group. + Employing the correlation matrix, optimal sample size can be derived for + association studies based on a SNP-BLUP approach. + The implementation relies on paternal half-sib families and biallelic + markers. If maternal half-sib families are used, the roles of sire/dam are + swapped. Multiple families can be considered. + Wittenburg, Bonk, Doschoris, Reyer (2020) "Design of Experiments for + Fine-Mapping Quantitative Trait Loci in Livestock Populations" + . + Carlson, Eberle, Rieder, Yi, Kruglyak, Nickerson (2004) "Selecting a + maximally informative set of single-nucleotide polymorphisms for association + analyses using linkage disequilibrium" . + date_publication: '2021-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hscovar + url_git: '' +HSDiC: + version: '0.1' + title: |- + Homogeneity and Sparsity Detection Incorporating Prior + Constraint Information + maintainer: Yaguang Li + description: We explore sparsity and homogeneity of regression coefficients incorporating + prior constraint information. A general pairwise fusion approach is proposed to + deal with the sparsity and homogeneity detection when combining prior convex constraints. + We develop an modified alternating direction method of multipliers algorithm (ADMM) + to obtain the estimators. + date_publication: '2018-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HSDiC + url_git: '' +hSDM: + version: 1.4.4 + title: Hierarchical Bayesian Species Distribution Models + maintainer: Ghislain Vieilledent + description: User-friendly and fast set of functions for estimating parameters of + hierarchical Bayesian species distribution models (Latimer and others 2006 ). + Such models allow interpreting the observations (occurrence and abundance of a + species) as a result of several hierarchical processes including ecological processes + (habitat suitability, spatial dependence and anthropogenic disturbance) and observation + processes (species detectability). Hierarchical species distribution models are + essential for accurately characterizing the environmental response of species, + predicting their probability of occurrence, and assessing uncertainty in the model + results. + date_publication: '2023-09-06' + bug_reports: https://github.com/ghislainv/hSDM/issues/ + url: https://ecology.ghislainv.fr/hSDM/ + url_cran: https://CRAN.R-project.org/package=hSDM + url_git: https://github.com/ghislainv/hSDM/ +hse: + version: 0.0-28 + title: The hse Distribution + maintainer: Rolf Turner + description: Deprecated. + date_publication: '2021-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hse + url_git: '' +hsem: + version: '1.0' + title: Hierarchical Structural Equation Model + maintainer: Rezzy Eko Caraka + description: We present this package for fitting structural equation models using + the hierarchical likelihood method. This package allows extended structural equation + model, including dynamic structural equation model. We illustrate the use of our + packages with well-known data sets. Therefore, this package are able to handle + two serious problems inadmissible solution and factor indeterminacy . + date_publication: '2021-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hsem + url_git: '' +hset: + version: 0.1.1 + title: Sets of Numbers Implemented with Hash Tables + maintainer: Giacomo Ceoldo + description: |- + Implementation of S4 class of sets and multisets of numbers. + The implementation is based on the hash table from the package 'hash'. + Quick operations are allowed when the set is a dynamic object. + The implementation is discussed in detail in Ceoldo and Wit (2023) . + date_publication: '2023-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hset + url_git: '' +HSEtest: + version: 0.1.0 + title: Homogeneity of Stratum Effects Test + maintainer: Zhicheng Du + description: To test the homogeneity of stratum effects in stratified paired binary + data. + date_publication: '2021-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HSEtest + url_git: '' +hsphase: + version: 2.0.3 + title: |- + Phasing, Pedigree Reconstruction, Sire Imputation and + Recombination Events Identification of Half-sib Families Using + SNP Data + maintainer: Mohammad Ferdosi + description: Identification of recombination events, haplotype reconstruction, sire + imputation and pedigree reconstruction using half-sib family SNP data. + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hsphase + url_git: '' +hspm: + version: '1.1' + title: Heterogeneous Spatial Models + maintainer: Gianfranco Piras + description: Spatial heterogeneity can be specified in various ways. 'hspm' is an + ambitious project that aims at implementing various methodologies to control for + heterogeneity in spatial models. The current version of 'hspm' deals with spatial + and (non-spatial) regimes models. In particular, the package allows to estimate + a general spatial regimes model with additional endogenous variables, specified + in terms of a spatial lag of the dependent variable, the spatially lagged regressors, + and, potentially, a spatially autocorrelated error term. Spatial regime models + are estimated by instrumental variables and generalized methods of moments (see + Arraiz et al., (2010) , Bivand and Piras, + (2015) , Drukker et al., (2013) , + Kelejian and Prucha, (2010) ). + date_publication: '2023-03-08' + bug_reports: https://github.com/gpiras/hspm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hspm + url_git: https://github.com/gpiras/hspm +HSPOR: + version: 1.1.9 + title: Hidden Smooth Polynomial Regression for Rupture Detection + maintainer: Florine Greciet + description: Several functions that allow by different methods to infer a piecewise + polynomial regression model under regularity constraints, namely continuity or + differentiability of the link function. The implemented functions are either specific + to data with two regimes, or generic for any number of regimes, which can be given + by the user or learned by the algorithm. A paper describing all these methods + will be submitted soon. The reference will be added to this file as soon as available. + date_publication: '2019-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HSPOR + url_git: '' +hsrecombi: + version: 1.0.1 + title: Estimation of Recombination Rate and Maternal LD in Half-Sibs + maintainer: Dörte Wittenburg + description: |- + Paternal recombination rate and maternal linkage disequilibrium + (LD) are estimated for pairs of biallelic markers such as single nucleotide + polymorphisms (SNPs) from progeny genotypes and sire haplotypes. The + implementation relies on paternal half-sib families. If maternal half-sib + families are used, the roles of sire/dam are swapped. Multiple families can + be considered. For parameter estimation, at least one sire has to be double + heterozygous at the investigated pairs of SNPs. + Based on recombination rates, genetic distances between markers can be + estimated. Markers with unusually large recombination rate to markers in + close proximity (i.e. putatively misplaced markers) shall be discarded in + this derivation. + A workflow description is attached as vignette. + *A pipeline is available at GitHub* + + Hampel, Teuscher, Gomez-Raya, Doschoris, Wittenburg (2018) "Estimation of + recombination rate and maternal linkage disequilibrium in half-sibs" + . + Gomez-Raya (2012) "Maximum likelihood estimation of linkage disequilibrium + in half-sib families" . + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hsrecombi + url_git: '' +hsstan: + version: 0.8.2 + title: Hierarchical Shrinkage Stan Models for Biomarker Selection + maintainer: Marco Colombo + description: |- + Linear and logistic regression models penalized with hierarchical + shrinkage priors for selection of biomarkers (or more general variable + selection), which can be fitted using Stan (Carpenter et al. (2017) + ). It implements the horseshoe and regularized + horseshoe priors (Piironen and Vehtari (2017) ), + as well as the projection predictive selection approach to recover a sparse + set of predictive biomarkers (Piironen, Paasiniemi and Vehtari (2020) + ). + date_publication: '2024-01-13' + bug_reports: https://github.com/mcol/hsstan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hsstan + url_git: https://github.com/mcol/hsstan +hstats: + version: 1.2.1 + title: Interaction Statistics + maintainer: Michael Mayer + description: |- + Fast, model-agnostic implementation of different H-statistics + introduced by Jerome H. Friedman and Bogdan E. Popescu (2008) + . These statistics quantify interaction + strength per feature, feature pair, and feature triple. The package + supports multi-output predictions and can account for case weights. + In addition, several variants of the original statistics are provided. + The shape of the interactions can be explored through partial + dependence plots or individual conditional expectation plots. 'DALEX' + explainers, meta learners ('mlr3', 'tidymodels', 'caret') and most + other models work out-of-the-box. + date_publication: '2024-08-17' + bug_reports: https://github.com/ModelOriented/hstats/issues/ + url: https://modeloriented.github.io/hstats/ + url_cran: https://CRAN.R-project.org/package=hstats + url_git: https://github.com/ModelOriented/hstats/ +htestClust: + version: 0.2.2 + title: Reweighted Marginal Hypothesis Tests for Clustered Data + maintainer: Mary Gregg + description: |- + A collection of reweighted marginal hypothesis tests for clustered data, based + on reweighting methods of Williamson, J., Datta, S., and Satten, G. (2003) . + The tests in this collection are clustered analogs to well-known hypothesis tests + in the classical setting, and are appropriate for data with cluster- and/or group-size + informativeness. The syntax and output of functions are modeled after common, + recognizable functions native to R. Methods used in the package refer to + Gregg, M., Datta, S., and Lorenz, D. (2020) , + Nevalainen, J., Oja, H., and Datta, S. (2017) + Dutta, S. and Datta, S. (2015) , + Lorenz, D., Datta, S., and Harkema, S. (2011) , + Datta, S. and Satten, G. (2008) , + Datta, S. and Satten, G. (2005) . + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=htestClust + url_git: '' +htetree: + version: 0.1.20 + title: Causal Inference with Tree-Based Machine Learning Algorithms + maintainer: Jiahui Xu + description: |- + Estimating heterogeneous treatment effects with tree-based machine + learning algorithms and visualizing estimated results in flexible and + presentation-ready ways. For more information, see Brand, Xu, Koch, + and Geraldo (2021) . Our current package + first started as a fork of the 'causalTree' package on 'GitHub' and we + greatly appreciate the authors for their extremely useful and free package. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=htetree + url_git: '' +HTLR: + version: 0.4-4 + title: Bayesian Logistic Regression with Heavy-Tailed Priors + maintainer: Longhai Li + description: |- + Efficient Bayesian multinomial logistic regression based on heavy-tailed + (hyper-LASSO, non-convex) priors. The posterior of coefficients and hyper-parameters + is sampled with restricted Gibbs sampling for leveraging the high-dimensionality and + Hamiltonian Monte Carlo for handling the high-correlation among coefficients. A detailed + description of the method: Li and Yao (2018), + Journal of Statistical Computation and Simulation, 88:14, 2827-2851, . + date_publication: '2022-10-22' + bug_reports: https://github.com/longhaiSK/HTLR/issues + url: https://longhaisk.github.io/HTLR/ + url_cran: https://CRAN.R-project.org/package=HTLR + url_git: '' +htm2txt: + version: 2.2.2 + title: Convert Html into Text + maintainer: Sangchul Park + description: Convert a html document to plain texts by stripping off all html tags. + date_publication: '2022-06-12' + bug_reports: https://github.com/replicable/htm2txt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=htm2txt + url_git: https://github.com/replicable/htm2txt +html2R: + version: 0.1.0 + title: Convert 'HTML' to 'R' with a 'Shiny' App + maintainer: Stéphane Laurent + description: Provides a 'Shiny' app allowing to convert 'HTML' code to 'R' code + (e.g. 'Hello' to 'tags$span("Hello")'), for usage in a 'Shiny' UI. + date_publication: '2020-09-15' + bug_reports: https://github.com/stla/html2R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=html2R + url_git: https://github.com/stla/html2R +html5: + version: 1.0.2 + title: Creates Valid HTML5 Strings + maintainer: Timothy Conwell + description: |- + Generates valid HTML tag strings for HTML5 elements documented by Mozilla. + Attributes are passed as named lists, with names being the attribute name and values being the attribute value. + Attribute values are automatically double-quoted. To declare a DOCTYPE, wrap html() with function doctype(). + Mozilla's documentation for HTML5 is available here: . + Elements marked as obsolete are not included. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=html5 + url_git: '' +htmlreportR: + version: 1.0.0 + title: '''HTML'' Reporting Made Simple(R)' + maintainer: Álvaro Esteban Martos + description: |- + Create compressed, interactive 'HTML' (Hypertext Markup Language) reports with embedded 'Python' code, custom 'JS' ('JavaScript') and 'CSS' (Cascading Style Sheets), and wrappers for + 'CanvasXpress' plots, networks and more. Based on , its sister project. + date_publication: '2024-08-19' + bug_reports: https://github.com/AEstebanMar/htmlreportR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=htmlreportR + url_git: https://github.com/AEstebanMar/htmlreportR +htmlTable: + version: 2.4.3 + title: Advanced Tables for Markdown/HTML + maintainer: Max Gordon + description: |- + Tables with state-of-the-art layout elements such as row spanners, + column spanners, table spanners, zebra striping, and more. While allowing + advanced layout, the underlying css-structure is simple in order to maximize + compatibility with common word processors. The package also contains a few + text formatting functions that help outputting text compatible with HTML/LaTeX. + date_publication: '2024-07-21' + bug_reports: https://github.com/gforge/htmlTable/issues + url: https://gforge.se/packages/ + url_cran: https://CRAN.R-project.org/package=htmlTable + url_git: '' +htmltools: + version: 0.5.8.1 + title: Tools for HTML + maintainer: Carson Sievert + description: Tools for HTML generation and output. + date_publication: '2024-04-04' + bug_reports: https://github.com/rstudio/htmltools/issues + url: https://rstudio.github.io/htmltools/ + url_cran: https://CRAN.R-project.org/package=htmltools + url_git: https://github.com/rstudio/htmltools +HTMLUtils: + version: 0.1.9 + title: Facilitates Automated HTML Report Creation + maintainer: '"Markus Loecher, Berlin School of Economics and Law (BSEL)"' + description: |- + Facilitates automated HTML report creation, in particular + framed HTML pages and dynamically sortable tables. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HTMLUtils + url_git: '' +htmlwidgets: + version: 1.6.4 + title: HTML Widgets for R + maintainer: Carson Sievert + description: |- + A framework for creating HTML widgets that render in various + contexts including the R console, 'R Markdown' documents, and 'Shiny' + web applications. + date_publication: '2023-12-06' + bug_reports: https://github.com/ramnathv/htmlwidgets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=htmlwidgets + url_git: https://github.com/ramnathv/htmlwidgets +htrSPRanalysis: + version: 0.1.0 + title: Analysis of Surface Plasmon Resonance Data + maintainer: Janice McCarthy Developer + description: 'Analysis of Surface Plasmon Resonance (SPR) and Biolayer Interferometry + data, with automations for high-throughput SPR. This version of the package fits + the 1: 1 binding model, with and without bulkshift. It offers optional local or + global Rmax fitting. The user must provide a sample sheet and a Carterra output + file in Carterra''s current format. There is a utility function to convert from + Carterra''s old output format. The user may run a custom pipeline or use the provided + ''Runscript'', which will produce a pdf file containing fitted Rmax, ka, kd and + standard errors, a plot of the sensorgram and fits, and a plot of residuals. The + script will also produce a .csv file with all of the relevant parameters for each + spot on the SPR chip.' + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=htrSPRanalysis + url_git: '' +HTRX: + version: 1.2.4 + title: Haplotype Trend Regression with eXtra Flexibility (HTRX) + maintainer: Yaoling Yang + description: Detection of haplotype patterns that include single nucleotide polymorphisms + (SNPs) and non-contiguous haplotypes that are associated with a phenotype. Methods + for implementing HTRX are described in Yang Y, Lawson DJ (2023) + and Barrie W, Yang Y, Irving-Pease E.K, et al (2024) . + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HTRX + url_git: '' +hts: + version: 6.0.3 + title: Hierarchical and Grouped Time Series + maintainer: Earo Wang + description: |- + Provides methods for analysing and forecasting hierarchical and + grouped time series. The available forecast methods include bottom-up, + top-down, optimal combination reconciliation (Hyndman et al. 2011) + , and trace minimization reconciliation + (Wickramasuriya et al. 2018) . + date_publication: '2024-07-30' + bug_reports: https://github.com/earowang/hts/issues + url: https://pkg.earo.me/hts/ + url_cran: https://CRAN.R-project.org/package=hts + url_git: '' +HTSCluster: + version: 2.0.11 + title: Clustering High-Throughput Transcriptome Sequencing (HTS) Data + maintainer: Andrea Rau + description: |- + A Poisson mixture model is implemented to cluster genes from high- + throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is + performed using either the EM or CEM algorithm, and the slope heuristics are + used for model selection (i.e., to choose the number of clusters). + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HTSCluster + url_git: '' +htsDegenerateR: + version: 0.1.0 + title: Degenerate Hierarchical Time Series Reconciliation + maintainer: Louis Steinmeister + description: Takes the MinT implementation of the 'hts' + package and adapts it to allow degenerate hierarchical structures. Instead of + the "nodes" argument, this function takes an S matrix which is more versatile + in the structures it allows. For a demo, see Steinmeister and Pauly (2024). + The MinT algorithm is based on Wickramasuriya et al. (2019). + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=htsDegenerateR + url_git: '' +HTSeed: + version: 0.1.0 + title: Fitting of Hydrotime Model for Seed Germination Time Course + maintainer: Dr. Himadri Ghosh + description: The seed germination process starts with water uptake by the seed and + ends with the protrusion of radicle and plumule under varying temperatures and + soil water potential. Hydrotime is a way to describe the relationship between + water potential and seed germination rates at germination percentages. One important + quantity before applying hydrotime modeling of germination percentages is to consider + the proportion of viable seeds that could germinate under saturated conditions. + This package can be used to apply correction factors at various water potentials + before estimating parameters like stress tolerance, and uniformity of the hydrotime + model. Three different distributions namely, Gaussian, Logistic, and Extreme value + distributions have been considered to fit the model to the seed germination time + course. Details can be found in Bradford (2002) , + and Bradford and Still(2004) . + date_publication: '2024-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HTSeed + url_git: '' +HTSeedGLM: + version: 0.1.0 + title: |- + Hydro Thermal Time Analysis of Seed Germination Using + Generalised Linear Model + maintainer: Dr. Himadri Ghosh + description: Seed germinates through the physical process of water uptake by dry + seed driven by the difference in water potential between the seed and the water. + There exists seed-to-seed variability in the base seed water potential. Hence, + there is a need for a distribution such that a viable seed with its base seed + water potential germinates if and only if the soil water potential is more than + the base seed water potential. This package estimates the stress tolerance and + uniformity parameters of the seed lot for germination under various temperatures + by using the hydro-time model of counts of germinated seeds under various water + potentials. The distribution of base seed water potential has been considered + to follow Normal, Logistic and Extreme value distribution. The estimated proportion + of germinated seeds along with the estimates of stress and uniformity parameters + are obtained using a generalised linear model. The significance test of the above + parameters for within and between temperatures is also performed in the analysis. + Details can be found in Kebreab and Murdoch (1999) + and Bradford (2002) . + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HTSeedGLM + url_git: '' +htsr: + version: 2.1.6 + title: Hydro-Meteorology Time-Series + maintainer: Pierre Chevallier + description: |- + Functions for the management and treatment of hydrology and + meteorology time-series stored in a 'Sqlite' data base. + date_publication: '2024-08-17' + bug_reports: https://github.com/p-chevallier/htsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=htsr + url_git: https://github.com/p-chevallier/htsr +HTT: + version: 0.1.2 + title: Hypothesis Testing Tree + maintainer: Jiaqi Hu + description: A novel decision tree algorithm in the hypothesis testing framework. + The algorithm examines the distribution difference between two child nodes over + all possible binary partitions. The test statistic of the hypothesis testing is + equivalent to the generalized energy distance, which enables the algorithm to + be more powerful in detecting the complex structure, not only the mean difference. + It is applicable for numeric, nominal, ordinal explanatory variables and the response + in general metric space of strong negative type. The algorithm has superior performance + compared to other tree models in type I error, power, prediction accuracy, and + complexity. + date_publication: '2023-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HTT + url_git: '' +httk: + version: 2.5.0 + title: High-Throughput Toxicokinetics + maintainer: John Wambaugh + description: |- + Pre-made models that can be rapidly tailored to various chemicals + and species using chemical-specific in vitro data and physiological + information. These tools allow incorporation of chemical + toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") + into bioinformatics, as described by Pearce et al. (2017) + (). Chemical-specific + in vitro data characterizing toxicokinetics have been obtained + from relatively high-throughput experiments. The + chemical-independent ("generic") physiologically-based ("PBTK") and empirical + (for example, one compartment) "TK" models included here can be + parameterized with in vitro data or in silico predictions which are + provided for thousands of chemicals, multiple exposure routes, + and various species. High throughput toxicokinetics ("HTTK") is the + combination of in vitro data and generic models. We establish the + expected accuracy of HTTK for chemicals without in vivo data + through statistical evaluation of HTTK predictions for chemicals + where in vivo data do exist. The models are systems of ordinary + differential equations that are developed in MCSim and solved + using compiled (C-based) code for speed. A Monte Carlo sampler is + included for simulating human biological variability + (Ring et al., 2017 ) + and propagating parameter uncertainty + (Wambaugh et al., 2019 ). + Empirically calibrated methods are included for predicting + tissue:plasma partition coefficients and volume of distribution + (Pearce et al., 2017 ). + These functions and data provide a set of tools for using IVIVE to + convert concentrations from high-throughput screening experiments + (for example, Tox21, ToxCast) to real-world exposures via reverse + dosimetry (also known as "RTK") + (Wetmore et al., 2015 ). + date_publication: '2025-01-14' + bug_reports: https://github.com/USEPA/CompTox-ExpoCast-httk/issues + url: https://www.epa.gov/chemical-research/rapid-chemical-exposure-and-dose-research + url_cran: https://CRAN.R-project.org/package=httk + url_git: '' +httpcache: + version: 1.2.0 + title: Query Cache for HTTP Clients + maintainer: Neal Richardson + description: |- + In order to improve performance for HTTP API clients, 'httpcache' + provides simple tools for caching and invalidating cache. It includes the + HTTP verb functions GET, PUT, PATCH, POST, and DELETE, which are drop-in + replacements for those in the 'httr' package. These functions are cache-aware + and provide default settings for cache invalidation suitable for RESTful + APIs; the package also enables custom cache-management strategies. + Finally, 'httpcache' includes a basic logging framework to facilitate the + measurement of HTTP request time and cache performance. + date_publication: '2021-01-10' + bug_reports: https://github.com/nealrichardson/httpcache/issues + url: https://enpiar.com/r/httpcache/ + url_cran: https://CRAN.R-project.org/package=httpcache + url_git: https://github.com/nealrichardson/httpcache/ +httpcode: + version: 0.3.0 + title: '''HTTP'' Status Code Helper' + maintainer: Scott Chamberlain + description: |- + Find and explain the meaning of 'HTTP' status codes. + Functions included for searching for codes by full or partial number, + by message, and get appropriate dog and cat images for many + status codes. + date_publication: '2020-04-10' + bug_reports: https://github.com/sckott/httpcode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=httpcode + url_git: https://github.com/sckott/httpcode +httpgd: + version: 2.0.3 + title: A 'HTTP' Server Graphics Device + maintainer: Florian Rupprecht + description: |- + A graphics device for R that is accessible via network protocols. + This package was created to make it easier to embed live R graphics in + integrated development environments and other applications. + The included 'HTML/JavaScript' client (plot viewer) aims to provide a better overall user experience when dealing with R graphics. + The device asynchronously serves graphics via 'HTTP' and 'WebSockets'. + date_publication: '2025-02-28' + bug_reports: https://github.com/nx10/httpgd/issues + url: https://nx10.github.io/httpgd/ + url_cran: https://CRAN.R-project.org/package=httpgd + url_git: https://github.com/nx10/httpgd +httping: + version: 0.2.0 + title: '''Ping'' ''URLs'' to Time ''Requests''' + maintainer: Scott Chamberlain + description: |- + A suite of functions to ping 'URLs' and to time + 'HTTP' 'requests'. Designed to work with 'httr'. + date_publication: '2018-01-03' + bug_reports: https://github.com/sckott/httping/issues + url: '' + url_cran: https://CRAN.R-project.org/package=httping + url_git: https://github.com/sckott/httping +httpproblems: + version: 1.0.1 + title: |- + Report Errors in Web Applications with 'Problem Details' (RFC + 7807) + maintainer: Aaron Jacobs + description: |- + Tools for emitting the 'Problem Details' structure defined in + 'RFC' 7807 for reporting errors from + 'HTTP' servers in a standard way. + date_publication: '2021-06-16' + bug_reports: https://github.com/atheriel/httpproblems/issues + url: '' + url_cran: https://CRAN.R-project.org/package=httpproblems + url_git: https://github.com/atheriel/httpproblems +httpRequest: + version: 0.0.11 + title: Basic HTTP Request + maintainer: Andreas Westfeld + description: HTTP Request protocols. Implements the GET, POST and multipart POST + request. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=httpRequest + url_git: '' +httptest: + version: 4.2.2 + title: A Test Environment for HTTP Requests + maintainer: Neal Richardson + description: |- + Testing and documenting code that communicates with remote servers + can be painful. Dealing with authentication, server state, + and other complications can make testing seem too costly to + bother with. But it doesn't need to be that hard. This package enables one + to test all of the logic on the R sides of the API in your package without + requiring access to the remote service. Importantly, it provides three + contexts that mock the network connection in different ways, as well as + testing functions to assert that HTTP requests were---or were + not---made. It also allows one to safely record real API responses to use as + test fixtures. The ability to save responses and load them offline also + enables one to write vignettes and other dynamic documents that can be + distributed without access to a live server. + date_publication: '2024-01-23' + bug_reports: https://github.com/nealrichardson/httptest/issues + url: https://enpiar.com/r/httptest/ + url_cran: https://CRAN.R-project.org/package=httptest + url_git: https://github.com/nealrichardson/httptest +httptest2: + version: 1.1.0 + title: Test Helpers for 'httr2' + maintainer: Neal Richardson + description: |- + Testing and documenting code that communicates with remote servers + can be painful. This package helps with writing tests for packages that + use 'httr2'. It enables testing all of the logic + on the R sides of the API without requiring access to the + remote service, and it also allows recording real API responses to use as + test fixtures. The ability to save responses and load them offline also + enables writing vignettes and other dynamic documents that can be + distributed without access to a live server. + date_publication: '2024-04-26' + bug_reports: https://github.com/nealrichardson/httptest2/issues + url: https://enpiar.com/httptest2/ + url_cran: https://CRAN.R-project.org/package=httptest2 + url_git: https://github.com/nealrichardson/httptest2 +httpuv: + version: 1.6.15 + title: HTTP and WebSocket Server Library + maintainer: Winston Chang + description: |- + Provides low-level socket and protocol support for handling + HTTP and WebSocket requests directly from within R. It is primarily + intended as a building block for other packages, rather than making it + particularly easy to create complete web applications using httpuv + alone. httpuv is built on top of the libuv and http-parser C + libraries, both of which were developed by Joyent, Inc. (See LICENSE + file for libuv and http-parser license information.) + date_publication: '2024-03-26' + bug_reports: https://github.com/rstudio/httpuv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=httpuv + url_git: https://github.com/rstudio/httpuv +httr: + version: 1.4.7 + title: Tools for Working with URLs and HTTP + maintainer: Hadley Wickham + description: |- + Useful tools for working with HTTP organised by HTTP verbs + (GET(), POST(), etc). Configuration functions make it easy to control + additional request components (authenticate(), add_headers() and so + on). + date_publication: '2023-08-15' + bug_reports: https://github.com/r-lib/httr/issues + url: https://httr.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=httr + url_git: https://github.com/r-lib/httr +httr2: + version: 1.1.0 + title: Perform HTTP Requests and Process the Responses + maintainer: Hadley Wickham + description: |- + Tools for creating and modifying HTTP requests, then + performing them and processing the results. 'httr2' is a modern + re-imagining of 'httr' that uses a pipe-based interface and solves + more of the problems that API wrapping packages face. + date_publication: '2025-01-18' + bug_reports: https://github.com/r-lib/httr2/issues + url: https://httr2.r-lib.org + url_cran: https://CRAN.R-project.org/package=httr2 + url_git: https://github.com/r-lib/httr2 +hubeau: + version: 0.5.1 + title: Get Data from the French National Database on Water 'Hub'Eau' + maintainer: David Dorchies + description: |- + Collection of functions to help retrieving data from + 'Hub'Eau' the free and public French National APIs on water + . + date_publication: '2025-01-13' + bug_reports: https://github.com/inrae/hubeau/issues + url: https://inrae.github.io/hubeau/ + url_cran: https://CRAN.R-project.org/package=hubeau + url_git: https://github.com/inrae/hubeau#readme +hubEnsembles: + version: 0.1.9 + title: Ensemble Methods for Combining Hub Model Outputs + maintainer: Li Shandross + description: |- + Functions for combining model outputs (e.g. predictions or + estimates) from multiple models into an aggregated ensemble model + output. + date_publication: '2024-10-02' + bug_reports: https://github.com/hubverse-org/hubEnsembles/issues + url: https://hubverse-org.github.io/hubEnsembles/ + url_cran: https://CRAN.R-project.org/package=hubEnsembles + url_git: https://github.com/hubverse-org/hubEnsembles +hubUtils: + version: 0.1.7 + title: Core 'hubverse' Utilities + maintainer: Anna Krystalli + description: |- + Core set of low-level utilities common across the + 'hubverse'. Used to interact with 'hubverse' schema, Hub configuration files + and model outputs and designed to be primarily used internally by other + 'hubverse' packages. See Reich et al. (2022) + for an overview of Collaborative Hubs. + date_publication: '2024-09-18' + bug_reports: https://github.com/hubverse-org/hubUtils/issues + url: https://hubverse-org.github.io/hubUtils/ + url_cran: https://CRAN.R-project.org/package=hubUtils + url_git: https://github.com/hubverse-org/hubUtils +hudr: + version: 1.2.0 + title: |- + Providing Data from the US Department of Housing and Urban + Development + maintainer: Paul Richardson + description: Provides functions to access data from the US Department of Housing + and Urban Development . + date_publication: '2022-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hudr + url_git: '' +hues: + version: 0.2.0 + title: Distinct Colour Palettes Based on 'iwanthue' + maintainer: John Baumgartner + description: |- + Creating effective colour palettes for figures is + challenging. This package generates and plot palettes of optimally + distinct colours in perceptually uniform colour space, based on + 'iwanthue' . + This is done through k-means clustering of CIE Lab colour space, + according to user-selected constraints on hue, chroma, and + lightness. + date_publication: '2019-12-01' + bug_reports: https://github.com/johnbaums/hues/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hues + url_git: https://github.com/johnbaums/hues +huge: + version: 1.3.5 + title: High-Dimensional Undirected Graph Estimation + maintainer: Haoming Jiang + description: |- + Provides a general framework for + high-dimensional undirected graph estimation. It integrates + data preprocessing, neighborhood screening, graph estimation, + and model selection techniques into a pipeline. In + preprocessing stage, the nonparanormal(npn) transformation is + applied to help relax the normality assumption. In the graph + estimation stage, the graph structure is estimated by + Meinshausen-Buhlmann graph estimation or the graphical lasso, + and both methods can be further accelerated by the lossy + screening rule preselecting the neighborhood of each variable + by correlation thresholding. We target on high-dimensional data + analysis usually d >> n, and the computation is + memory-optimized using the sparse matrix output. We also + provide a computationally efficient approach, correlation + thresholding graph estimation. Three + regularization/thresholding parameter selection methods are + included in this package: (1)stability approach for + regularization selection (2) rotation information criterion (3) + extended Bayesian information criterion which is only available + for the graphical lasso. + date_publication: '2021-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=huge + url_git: '' +huito: + version: 0.2.5 + title: Reproducible and Flexible Label Design + maintainer: Flavio Lozano-Isla + description: |- + An open-source R package to deploys reproducible and flexible labels using layers. + The 'huito' package is part of the 'inkaverse' project for developing different procedures and + tools used in plant science and experimental designs. + Learn more about the 'inkaverse' project at . + date_publication: '2024-09-05' + bug_reports: https://github.com/flavjack/huito/issues/ + url: https://huito.inkaverse.com/ + url_cran: https://CRAN.R-project.org/package=huito + url_git: https://github.com/flavjack/huito +HUM: + version: '2.0' + title: Compute HUM Value and Visualize ROC Curves + maintainer: Natalia Novoselova + description: |- + Tools for computing HUM (Hypervolume Under the Manifold) value to estimate features ability + to discriminate the class labels, visualizing the ROC curve for two or three class labels + (Natalia Novoselova, Cristina Della Beffa, Junxi Wang, Jialiang Li, Frank Pessler, Frank Klawonn + (2014) ). + date_publication: '2022-06-21' + bug_reports: '' + url: https://public.ostfalia.de/~klawonn/HUM.htm + url_cran: https://CRAN.R-project.org/package=HUM + url_git: '' +humanFormat: + version: '1.2' + title: Human-Friendly Formatting Functions + maintainer: Dustin Sallings + description: Format quantities of time or bytes into human-friendly strings. + date_publication: '2022-08-07' + bug_reports: https://github.com/dustin/humanFormat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=humanFormat + url_git: https://github.com/dustin/humanFormat +humaniformat: + version: 0.6.0 + title: A Parser for Human Names + maintainer: Oliver Keyes + description: |- + Human names are complicated and nonstandard things. Humaniformat, + which is based on Anthony Ettinger's 'humanparser' project (https://github.com/ + chovy/humanparser) provides functions for parsing human names, making a best- + guess attempt to distinguish sub-components such as prefixes, suffixes, middle + names and salutations. + date_publication: '2016-04-24' + bug_reports: https://github.com/ironholds/humaniformat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=humaniformat + url_git: https://github.com/ironholds/humaniformat/ +humanize: + version: 0.2.0 + title: Create Values for Human Consumption + maintainer: Gerry Manoim + description: |- + An almost direct port of the 'python' 'humanize' package . + This package contains utilities to convert values into human readable forms. + date_publication: '2018-04-04' + bug_reports: https://github.com/newtux/humanize/issues + url: https://newtux.github.io/humanize/index.html + url_cran: https://CRAN.R-project.org/package=humanize + url_git: https://github.com/newtux/humanize +humanleague: + version: 2.3.2 + title: Synthetic Population Generator + maintainer: Andrew Smith + description: |- + Generates high-entropy integer synthetic populations from marginal and (optionally) seed data using quasirandom sampling, + in arbitrary dimensionality (Smith, Lovelace and Birkin (2017) ). + The package also provides an implementation of the Iterative Proportional Fitting (IPF) algorithm (Zaloznik (2011) ). + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=humanleague + url_git: '' +humidity: + version: 0.1.5 + title: Calculate Water Vapor Measures from Temperature and Dew Point + maintainer: Jun Cai + description: Vapor pressure, relative humidity, absolute humidity, specific humidity, + and mixing ratio are commonly used water vapor measures in meteorology. This R + package provides functions for calculating saturation vapor pressure (hPa), partial + water vapor pressure (Pa), relative humidity (%), absolute humidity (kg/m^3), + specific humidity (kg/kg), and mixing ratio (kg/kg) from temperature (K) and dew + point (K). Conversion functions between humidity measures are also provided. + date_publication: '2019-11-10' + bug_reports: https://github.com/caijun/humidity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=humidity + url_git: https://github.com/caijun/humidity +hunspell: + version: 3.0.5 + title: High-Performance Stemmer, Tokenizer, and Spell Checker + maintainer: Jeroen Ooms + description: |- + Low level spell checker and morphological analyzer based on the + famous 'hunspell' library . The package can analyze + or check individual words as well as parse text, latex, html or xml documents. + For a more user-friendly interface use the 'spelling' package which builds on + this package to automate checking of files, documentation and vignettes in all + common formats. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/hunspell/issues + url: https://docs.ropensci.org/hunspell/https://ropensci.r-universe.dev/hunspell + url_cran: https://CRAN.R-project.org/package=hunspell + url_git: '' +HuraultMisc: + version: 1.1.1 + title: Guillem Hurault Functions' Library + maintainer: Guillem Hurault + description: Contains various functions for data analysis, notably helpers and diagnostics + for Bayesian modelling using Stan. + date_publication: '2021-09-06' + bug_reports: https://github.com/ghurault/HuraultMisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HuraultMisc + url_git: https://github.com/ghurault/HuraultMisc +hurdlr: + version: '0.1' + title: Zero-Inflated and Hurdle Modelling Using Bayesian Inference + maintainer: Earvin Balderama + description: When considering count data, it is often the case that many more zero + counts than would be expected of some given distribution are observed. It is well + established that data such as this can be reliably modelled using zero-inflated + or hurdle distributions, both of which may be applied using the functions in this + package. Bayesian analysis methods are used to best model problematic count data + that cannot be fit to any typical distribution. The package functions are flexible + and versatile, and can be applied to varying count distributions, parameter estimation + with or without explanatory variable information, and are able to allow for multiple + hurdles as it is also not uncommon that count data have an abundance of large-number + observations which would be considered outliers of the typical distribution. In + lieu of throwing out data or misspecifying the typical distribution, these extreme + observations can be applied to a second, extreme distribution. With the given + functions of this package, such a two-hurdle model may be easily specified in + order to best manage data that is both zero-inflated and over-dispersed. + date_publication: '2017-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hurdlr + url_git: '' +HurreconR: + version: '1.1' + title: Models Hurricane Wind Speed, Wind Direction, and Wind Damage + maintainer: Emery Boose + description: |- + The HURRECON model estimates wind speed, wind direction, enhanced + Fujita scale wind damage, and duration of EF0 to EF5 winds as a function + of hurricane location and maximum sustained wind speed. Results may be + generated for a single site or an entire region. Hurricane track and + intensity data may be imported directly from the US National Hurricane + Center's HURDAT2 database. For details on the original version of the + model written in Borland Pascal, see: Boose, Chamberlin, and Foster (2001) + and Boose, Serrano, + and Foster (2004) . + date_publication: '2023-06-13' + bug_reports: https://github.com/hurrecon-model/hurreconR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HurreconR + url_git: https://github.com/hurrecon-model/HurreconR +hurricaneexposure: + version: 0.1.1 + title: |- + Explore and Map County-Level Hurricane Exposure in the United + States + maintainer: Brooke Anderson + description: |- + Allows users to create time series of tropical storm + exposure histories for chosen counties for a number of hazard metrics + (wind, rain, distance from the storm, etc.). This package interacts + with data available through the 'hurricaneexposuredata' package, which + is available in a 'drat' repository. To access this data package, see the + instructions at . + The size of the 'hurricaneexposuredata' package is + approximately 20 MB. This work was supported in part by grants from the National + Institute of Environmental Health Sciences (R00ES022631), the National Science + Foundation (1331399), and a NASA Applied Sciences Program/Public Health Program + Grant (NNX09AV81G). + date_publication: '2020-02-13' + bug_reports: https://github.com/geanders/hurricaneexposure/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hurricaneexposure + url_git: https://github.com/geanders/hurricaneexposure +hutils: + version: 1.8.1 + title: Miscellaneous R Functions and Aliases + maintainer: Hugh Parsonage + description: Provides utility functions for, and drawing on, the 'data.table' package. + The package also collates useful miscellaneous functions extending base R not + available elsewhere. The name is a portmanteau of 'utils' and the author. + date_publication: '2022-04-13' + bug_reports: https://github.com/hughparsonage/hutils/issues + url: https://hughparsonage.github.io/hutils/ + url_cran: https://CRAN.R-project.org/package=hutils + url_git: https://github.com/hughparsonage/hutils +hutilscpp: + version: 0.10.7 + title: Miscellaneous Functions in C++ + maintainer: Hugh Parsonage + description: |- + Provides utility functions that are simply, frequently used, + but may require higher performance that what can be obtained from base R. + Incidentally provides support for 'reverse geocoding', such as matching a point + with its nearest neighbour in another array. Used as a complement to package + 'hutils' by sacrificing compilation or installation time for higher running + speeds. The name is a portmanteau of the author and 'Rcpp'. + date_publication: '2025-01-08' + bug_reports: https://github.com/hughparsonage/hutilscpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hutilscpp + url_git: https://github.com/hughparsonage/hutilscpp +huxtable: + version: 5.5.7 + title: Easily Create and Style Tables for LaTeX, HTML and Other Formats + maintainer: David Hugh-Jones + description: |- + Creates styled tables for data presentation. Export to HTML, LaTeX, + RTF, 'Word', 'Excel', and 'PowerPoint'. Simple, modern interface to manipulate + borders, size, position, captions, colours, text styles and number formatting. + Table cells can span multiple rows and/or columns. + Includes a 'huxreg' function for creation of regression tables, and 'quick_*' + one-liners to print data to a new document. + date_publication: '2024-10-01' + bug_reports: https://github.com/hughjonesd/huxtable/issues + url: https://hughjonesd.github.io/huxtable/ + url_cran: https://CRAN.R-project.org/package=huxtable + url_git: '' +HVT: + version: 25.2.2 + title: |- + Constructing Hierarchical Voronoi Tessellations and Overlay + Heatmaps for Data Analysis + maintainer: '"Mu Sigma, Inc."' + description: Facilitates building topology preserving maps for data analysis. + date_publication: '2025-02-05' + bug_reports: https://github.com/Mu-Sigma/HVT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HVT + url_git: https://github.com/Mu-Sigma/HVT +hwde: + version: 0.67-3 + title: |- + Models and Tests for Departure from Hardy-Weinberg Equilibrium + and Independence Between Loci + maintainer: John Maindonald + description: |- + Fits models for genotypic disequilibria, as described in + Huttley and Wilson (2000) , Weir (1996) and Weir and Wilson (1986). + Contrast terms are available that account for first order interactions + between loci. Also implements, for a single locus in a single + population, a conditional exact test for Hardy-Weinberg equilibrium. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hwde + url_git: https://github.com/jhmaindonald/hwde +HWEintrinsic: + version: 1.2.3 + title: |- + Objective Bayesian Testing for the Hardy-Weinberg Equilibrium + Problem + maintainer: Sergio Venturini + description: General (multi-allelic) Hardy-Weinberg equilibrium problem from an + objective Bayesian testing standpoint. This aim is achieved through the identification + of a class of priors specifically designed for this testing problem. A class of + intrinsic priors under the full model is considered. This class is indexed by + a tuning quantity, the training sample size, as discussed in Consonni, Moreno + and Venturini (2010). These priors are objective, satisfy Savage's continuity + condition and have proved to behave extremely well for many statistical testing + problems. + date_publication: '2023-09-06' + bug_reports: '' + url: https://onlinelibrary.wiley.com/doi/10.1002/sim.4084/abstract + url_cran: https://CRAN.R-project.org/package=HWEintrinsic + url_git: '' +hwep: + version: 2.0.2 + title: Hardy-Weinberg Equilibrium in Polyploids + maintainer: David Gerard + description: |- + Inference concerning equilibrium and random mating in + autopolyploids. Methods are available to test for equilibrium + and random mating at any even ploidy level (>2) in the presence + of double reduction at biallelic loci. For autopolyploid populations + in equilibrium, methods are available to estimate the degree of + double reduction. We also provide functions to calculate genotype + frequencies at equilibrium, or after one or several rounds of + random mating, given rates of double reduction. The main function is + hwefit(). This material is based upon work supported by the + National Science Foundation under Grant No. 2132247. The opinions, + findings, and conclusions or recommendations expressed are those of + the author and do not necessarily reflect the views of the National + Science Foundation. For details of these methods, see + Gerard (2022a) and + Gerard (2022b) . + date_publication: '2023-05-16' + bug_reports: https://github.com/dcgerard/hwep/issues + url: https://dcgerard.github.io/hwep/ + url_cran: https://CRAN.R-project.org/package=hwep + url_git: '' +hwig: + version: 0.0.2 + title: Half-Weight Index Gregariousness + maintainer: Alec L. Robitaille + description: |- + The half-weight index gregariousness (HWIG) is an association + index used in social network analyses. It extends the half-weight + association index (HWI), correcting for level of gregariousness + in individuals. It is calculated using group by individual + data according to methods described in Godde et al. (2013) + . + date_publication: '2021-09-30' + bug_reports: https://github.com/robitalec/hwig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hwig + url_git: https://gitlab.com/robit.a/hwig +hwordcloud: + version: 0.1.0 + title: Rendering Word Clouds + maintainer: Zhenxing Cheng + description: Provides a way to display word clouds in R. The word cloud is a html + widget, so you can use it in interactive documents and 'shiny' applications. + date_publication: '2019-08-07' + bug_reports: https://github.com/czxa/hwordcloud/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hwordcloud + url_git: https://github.com/czxa/hwordcloud +hwriter: + version: 1.3.2.1 + title: HTML Writer - Outputs R Objects in HTML Format + maintainer: Gregoire Pau + description: |- + Easy-to-use and versatile functions to output R objects in + HTML format. + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hwriter + url_git: '' +hwsdr: + version: '1.1' + title: Interface to the 'HWSD' Web Services + maintainer: Koen Hufkens + description: |- + Programmatic interface to the Harmonized World Soil Database + 'HWSD' web services (). + Allows for easy downloads of 'HWSD' soil data directly to your R workspace + or your computer. Routines for both single pixel data downloads and + gridded data are provided. + date_publication: '2023-09-16' + bug_reports: https://github.com/bluegreen-labs/hwsdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hwsdr + url_git: https://github.com/bluegreen-labs/hwsdr +hwwntest: + version: 1.3.2 + title: Tests of White Noise using Wavelets + maintainer: Guy Nason + description: |- + Provides methods to test whether time series is consistent + with white noise. Two new tests based on Haar wavelets and general + wavelets described by Nason and Savchev (2014) + are provided and, for comparison purposes + this package also implements the + B test of Bartlett (1967) . Functionality + is provided to compute an approximation to the theoretical + power of the general wavelet test in the case of general + ARMA alternatives. + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hwwntest + url_git: '' +HybridDesign: + version: '1.0' + title: Hybrid Design for Phase I Dose-Finding Studies + maintainer: Heng Zhou + description: |- + The Hybrid design is a combination of model-assisted design (e.g., the modified + Toxicity Probability Interval design) with dose-toxicity model-based design for + phase I dose-finding studies. The hybrid design controls the overdosing + toxicity well and leads to a recommended dose closer to the true maximum tolerated + dose (MTD) due to its ability to calibrate for an intermediate dose. More details + can be found in Liao et al. 2022 . + date_publication: '2022-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HybridDesign + url_git: '' +HybridMicrobiomes: + version: 0.1.1 + title: Analysis of Host-Associated Microbiomes from Hybrid Organisms + maintainer: Sharon Bewick + description: 'A set of tools to analyze and visualize the relationships between + host-associated microbiomes of hybrid organisms and those of their progenitor + species. Though not necessary, installing the microViz package is recommended + as a check for phyloseq objects. To install microViz from R Universe use the following + command: install.packages("microViz", repos = c(davidbarnett = "https://david-barnett.r-universe.dev", + getOption("repos"))). To install microViz from GitHub use the following commands: + install.packages("devtools") followed by devtools::install_github("david-barnett/microViz").' + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HybridMicrobiomes + url_git: '' +hybridModels: + version: 0.3.7 + title: |- + An R Package for the Stochastic Simulation of Disease Spreading + in Dynamic Networks + maintainer: Fernando S. Marques + description: |- + Simulates stochastic hybrid models for transmission of infectious + diseases in dynamic networks. It is a metapopulation model in which each + node in the network is a sub-population and disease spreads within nodes + and among them, combining two approaches: stochastic simulation algorithm + () and individual-based + approach, respectively. Equations that models spread within nodes are + customizable and there are two link types among nodes: migration and + influence (commuting). More information in Fernando S. Marques, + Jose H. H. Grisi-Filho, Marcos Amaku et al. (2020) . + date_publication: '2020-06-26' + bug_reports: https://github.com/fernandosm/hybridModels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hybridModels + url_git: https://github.com/fernandosm/hybridModels +hybridogram: + version: 0.3.2 + title: Function that Creates a Heat Map from Hybridization Data + maintainer: Matthew Cserhati + description: |- + Using hybrid data, this package created a vividly colored hybrid heat map. + The input is two files which are auto-selected. + The first file has three columns, the first two for pairs of species, + with the third column for the hybrid experiment code (an integer). + The second file is a list of code and their descriptions in two + columns. The output is a figure showing the hybrid heat map with a color legend. + date_publication: '2021-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hybridogram + url_git: '' +hybridts: + version: 0.1.0 + title: Hybrid Time Series Forecasting Using Error Remodeling Approach + maintainer: Tanujit Chakraborty + description: |- + Method and tool for generating hybrid time series forecasts using + an error remodeling approach. These forecasting approaches utilize a recursive + technique for modeling the linearity of the series using a linear method + (e.g., ARIMA, Theta, etc.) and then models (forecasts) the residuals of the linear forecaster + using non-linear neural networks (e.g., ANN, ARNN, etc.). The hybrid architectures comprise three steps: + firstly, the linear patterns of the series are forecasted which are followed by an error re-modeling step, + and finally, the forecasts from both the steps are combined to produce the final output. This method additionally + provides the confidence intervals as needed. Ten different models can be implemented using this package. + This package generates different types of hybrid error correction models for time series forecasting + based on the algorithms by Zhang. (2003), Chakraborty et al. (2019), Chakraborty et al. (2020), + Bhattacharyya et al. (2021), Chakraborty et al. (2022), and Bhattacharyya et al. (2022) + + + . + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hybridts + url_git: '' +hyd1d: + version: 0.5.3 + title: 1d Water Level Interpolation along the Rivers Elbe and Rhine + maintainer: Arnd Weber + description: |- + An S4 class and several functions which utilize internally stored + datasets and gauging data enable 1d water level interpolation. The S4 class + (WaterLevelDataFrame) structures the computation and visualisation + of 1d water level information along the German federal waterways Elbe and + Rhine. 'hyd1d' delivers 1d water level data - extracted from the 'FLYS' + database - and validated gauging data - extracted from the hydrological + database 'WISKI7' - package-internally. For computations near real time + gauging data are queried externally from the 'PEGELONLINE REST API' + . + date_publication: '2025-02-26' + bug_reports: https://github.com/bafg-bund/hyd1d/issues/ + url: https://hyd1d.bafg.de + url_cran: https://CRAN.R-project.org/package=hyd1d + url_git: https://github.com/bafg-bund/hyd1d +hydflood: + version: 0.5.10 + title: Flood Extents and Duration along the Rivers Elbe and Rhine + maintainer: Arnd Weber + description: |- + Raster based flood modelling internally using 'hyd1d', an R package + to interpolate 1d water level and gauging data. The package computes flood + extent and duration through strategies originally developed for 'INFORM', + an 'ArcGIS'-based hydro-ecological modelling framework. It does not provide + a full, physical hydraulic modelling algorithm, but a simplified, near real + time 'GIS' approach for flood extent and duration modelling. Computationally + demanding annual flood durations have been computed already and data + products were published by Weber (2022) . + date_publication: '2025-02-27' + bug_reports: https://github.com/bafg-bund/hydflood/issues/ + url: https://hydflood.bafg.de + url_cran: https://CRAN.R-project.org/package=hydflood + url_git: https://github.com/bafg-bund/hydflood +hydra: + version: 0.1.0 + title: Hyperbolic Embedding + maintainer: Martin Keller-Ressel + description: Calculate an optimal embedding of a set of data points into low-dimensional + hyperbolic space. This uses the strain-minimizing hyperbolic embedding of Keller-Ressel + and Nargang (2019), see . + date_publication: '2019-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydra + url_git: '' +hydraulics: + version: 0.7.1 + title: Basic Pipe and Open Channel Hydraulics + maintainer: Ed Maurer + description: |- + Functions for basic hydraulic calculations related to + water flow in circular pipes both flowing full (under pressure), and + partially full (gravity flow), and trapezoidal open channels. For + pressure flow this includes friction loss calculations by solving + the Darcy-Weisbach equation for head loss, flow or diameter, + plotting a Moody diagram, matching a pump characteristic curve to a system + curve, and solving for flows in a pipe network using the Hardy-Cross method. + The Darcy-Weisbach friction factor is calculated using the Colebrook + (or Colebrook-White equation), the basis of the Moody diagram, the original + citation being Colebrook (1939) . For gravity + flow, the Manning equation is used, again solving for missing parameters. + The derivation of and solutions using the Darcy-Weisbach equation and the + Manning equation are outlined in many fluid mechanics texts such as + Finnemore and Maurer (2024, ISBN:978-1-264-78729-6). Some gradually- and + rapidly-varied flow functions are included. For the Manning equation + solutions, this package uses modifications of original code from the 'iemisc' + package by Irucka Embry. + date_publication: '2024-11-18' + bug_reports: '' + url: https://edm44.github.io/hydraulics/ + url_cran: https://CRAN.R-project.org/package=hydraulics + url_git: https://github.com/EdM44/hydraulics +hydReng: + version: 0.1.0 + title: Hydraulic Engineering Tools + maintainer: Galatioto Niccolo + description: The 'hydReng' package provides a set of functions for hydraulic engineering + tasks and natural hazard assessments. It includes basic hydraulics (wetted area, + wetted perimeter, flow, flow velocity, flow depth, and maximum flow) for open + channels with arbitrary geometry under uniform flow conditions. For structures + such as circular pipes, weirs, and gates, the package includes calculations for + pressure flow, backwater depth, and overflow over a weir crest. Additionally, + it provides formulas for calculating bedload transport. The formulas used can + be found in standard literature on hydraulics, such as Bollrich (2019, ISBN:978-3-410-29169-5) + or Hager (2011, ISBN:978-3-642-77430-0). + date_publication: '2025-01-09' + bug_reports: https://github.com/NiccoloGalatioto/hydReng/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hydReng + url_git: https://github.com/NiccoloGalatioto/hydReng +HYDROCAL: + version: 1.0.0 + title: Hydraulic Roughness Calculator + maintainer: Colton Shaw + description: |- + Estimates frictional constants for hydraulic analysis + of rivers. This HYDRaulic ROughness CALculator (HYDROCAL) was previously + developed as a spreadsheet tool and accompanying documentation by McKay and + Fischenich (2011, ). + date_publication: '2023-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HYDROCAL + url_git: GitHub() +HydroCode: + version: 1.0.3 + title: Hydrological Codes + maintainer: Thorsten Pohlert + description: |- + Pfafstetter Hydrological Codes + as cited in Verdin and Verdin (1999) + are decoded for upstream or downstream queries. + date_publication: '2023-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HydroCode + url_git: '' +hydroDCindex: + version: 1.0.0 + title: Duration Curve Hydrological Model Indexes + maintainer: Alonso Arriagada + description: 'Compute duration curves of daily flow series, both real and modeled, + to be compared through indexes of flow duration curves. The package functions + include comparative plots and goodness of fit tests. Flow duration curve indexes + are based on: Yilmaz et al., (2008) .' + date_publication: '2024-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydroDCindex + url_git: '' +hydroEvents: + version: 0.12.0 + title: Extract Event Statistics in Hydrologic Time Series + maintainer: Conrad Wasko + description: |- + Events from individual hydrologic time series are extracted, and events from multiple time series can be matched to each other. + Tang, W. & Carey, S. K. (2017) . + Kaur, S., Horne, A., Stewardson, M.J., Nathan, R., Costa, A.M., Szemis, J.M., & Webb, J.A. (2017) . + Ladson, A., Brown, R., Neal, B., & Nathan, R. J. (2013) . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydroEvents + url_git: https://github.com/conradwasko/hydroEvents +hydrogeo: + version: 0.6-1 + title: Groundwater Data Presentation and Interpretation + maintainer: Myles English + description: |- + Contains one function for drawing Piper diagrams (also + called Piper-Hill diagrams) of water analyses for major ions. + date_publication: '2017-03-12' + bug_reports: '' + url: http://rockhead.biz + url_cran: https://CRAN.R-project.org/package=hydrogeo + url_git: '' +hydroGOF: + version: 0.6-0.1 + title: |- + Goodness-of-Fit Functions for Comparison of Simulated and + Observed Hydrological Time Series + maintainer: Mauricio Zambrano-Bigiarini + description: S3 functions implementing both statistical and graphical goodness-of-fit + measures between observed and simulated values, mainly oriented to be used during + the calibration, validation, and application of hydrological models. Missing values + in observed and/or simulated values can be removed before computations. Comments + / questions / collaboration of any kind are very welcomed. + date_publication: '2024-11-04' + bug_reports: https://github.com/hzambran/hydroGOF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hydroGOF + url_git: https://github.com/hzambran/hydroGOF +hydroloom: + version: 1.1.0 + title: Utilities to Weave Hydrologic Fabrics + maintainer: David Blodgett + description: A collection of utilities that support creation of network attributes + for hydrologic networks. Methods and algorithms implemented are documented in + Moore et al. (2019) ), Cormen and Leiserson (2022) + and Verdin and Verdin (1999) . + date_publication: '2024-08-26' + bug_reports: '' + url: https://doi-usgs.github.io/hydroloom/ + url_cran: https://CRAN.R-project.org/package=hydroloom + url_git: https://github.com/DOI-USGS/hydroloom +HydroMe: + version: 2.1.1 + title: |- + Estimating Water Retention and Infiltration Model Parameters + using Experimental Data + maintainer: Christian Thine Omuto + description: Contains functions for estimating the parameters of infiltration and + water retention models using the curve-fitting methods as discussed in Omuto and + Gumbe (2009) ("Estimating water infiltration and retention characteristics using + a computer program in R"). The models considered + are those that are commonly used in soil science. Version 2 of the package has + new models for water retention characteristic curves. + date_publication: '2024-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HydroMe + url_git: '' +hydropeak: + version: 0.1.2 + title: Detect and Characterize Sub-Daily Flow Fluctuations + maintainer: Bettina Grün + description: |- + An important environmental impact on running water ecosystems + is caused by hydropeaking - the discontinuous release of turbine water + because of peaks of energy demand. An event-based algorithm is implemented + to detect flow fluctuations referring to increase events (IC) and decrease + events (DC). For each event, a set of parameters related to the fluctuation + intensity is calculated. The framework is introduced in Greimel et al. (2016) + "A method to detect and characterize sub-daily flow fluctuations" + and can be used to identify different fluctuation + types according to the potential source: e.g., sub-daily flow fluctuations + caused by hydropeaking, rainfall, or snow and glacier melt. + This is a companion to the package 'hydroroute', which is used to detect and + follow hydropower plant-specific hydropeaking waves at the sub-catchment + scale and to describe how hydropeaking flow parameters change along the + longitudinal flow path as proposed and validated in Greimel et al. (2022). + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydropeak + url_git: '' +HydroPortailStats: + version: 1.1.0 + title: '''HydroPortail'' Statistical Functions' + maintainer: Benjamin Renard + description: |- + Statistical functions used in the French 'HydroPortail' . + This includes functions to estimate distributions, quantile curves and uncertainties, along with various other utilities. + Technical details are available (in French) in Renard (2016) . + date_publication: '2024-08-19' + bug_reports: https://github.com/benRenard/HydroPortailStats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HydroPortailStats + url_git: https://github.com/benRenard/HydroPortailStats +hydroroute: + version: 0.1.2 + title: Trace Longitudinal Hydropeaking Waves + maintainer: Bettina Grün + description: Implements an empirical approach referred to as PeakTrace which uses + multiple hydrographs to detect and follow hydropower plant-specific hydropeaking + waves at the sub-catchment scale and to describe how hydropeaking flow parameters + change along the longitudinal flow path. The method is based on the identification + of associated events and uses (linear) regression models to describe translation + and retention processes between neighboring hydrographs. Several regression model + results are combined to arrive at a power plant-specific model. The approach is + proposed and validated in Greimel et al. (2022) . The identification + of associated events is based on the event detection implemented in 'hydropeak'. + date_publication: '2023-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydroroute + url_git: '' +hydrostats: + version: 0.2.9 + title: Hydrologic Indices for Daily Time Series Data + maintainer: Nick Bond + description: Calculates a suite of hydrologic indices for daily time series data + that are widely used in hydrology and stream ecology. + date_publication: '2022-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydrostats + url_git: https://github.com/nickbond/hydrostats +hydrotoolbox: + version: 1.1.2 + title: |- + Hydrological Tools for Handling Hydro-Meteorological Data + Records + maintainer: Ezequiel Toum + description: Read, plot, manipulate and process hydro-meteorological data records + (with special features for Argentina and Chile data-sets). + date_publication: '2023-04-12' + bug_reports: https://gitlab.com/ezetoum27/hydrotoolbox/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hydrotoolbox + url_git: https://gitlab.com/ezetoum27/hydrotoolbox +hydroToolkit: + version: 0.1.0 + title: |- + Hydrological Tools for Handling Hydro-Meteorological Data from + Argentina and Chile + maintainer: Ezequiel Toum + description: Read, plot, manipulate and process hydro-meteorological data from Argentina + and Chile. + date_publication: '2020-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hydroToolkit + url_git: '' +hydroTSM: + version: 0.7-0.1 + title: Time Series Management and Analysis for Hydrological Modelling + maintainer: Mauricio Zambrano-Bigiarini + description: S3 functions for management, analysis, interpolation and plotting of + time series used in hydrology and related environmental sciences. In particular, + this package is highly oriented to hydrological modelling tasks. The focus of + this package has been put in providing a collection of tools useful for the daily + work of hydrologists (although an effort was made to optimise each function as + much as possible, functionality has had priority over speed). Bugs / comments + / questions / collaboration of any kind are very welcomed, and in particular, + datasets that can be included in this package for academic purposes. + date_publication: '2024-11-04' + bug_reports: https://github.com/hzambran/hydroTSM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hydroTSM + url_git: https://github.com/hzambran/hydroTSM +hyfo: + version: 1.4.6 + title: Hydrology and Climate Forecasting + maintainer: Yuanchao Xu + description: |- + Focuses on data processing and visualization in hydrology and + climate forecasting. Main function includes data extraction, data downscaling, + data resampling, gap filler of precipitation, bias correction of forecasting + data, flexible time series plot, and spatial map generation. It is a good pre- + processing and post-processing tool for hydrological and hydraulic modellers. + date_publication: '2023-08-16' + bug_reports: https://github.com/Yuanchao-Xu/hyfo/issues + url: https://yuanchao-xu.github.io/hyfo/ + url_cran: https://CRAN.R-project.org/package=hyfo + url_git: '' +HyMETT: + version: 1.1.3 + title: Hydrologic Model Evaluation and Time-Series Tools + maintainer: Colin Penn + description: |- + Facilitates the analysis and evaluation of hydrologic model output and + time-series data with functions focused on comparison of modeled (simulated) and observed data, + period-of-record statistics, and trends. + date_publication: '2024-08-28' + bug_reports: https://code.usgs.gov/hymett/hymett/-/issues + url: https://code.usgs.gov/hymett/hymett + url_cran: https://CRAN.R-project.org/package=HyMETT + url_git: '' +hyper.fit: + version: 1.2.1 + title: N-Dimensional Hyperplane Fitting with Errors + maintainer: Aaron Robotham + description: High level functions for hyperplane fitting (hyper.fit()) and visualising + (hyper.plot2d() / hyper.plot3d()). In simple terms this allows the user to produce + robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D + x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane + model being fit to a N dimension dataset. All fits include intrinsic scatter in + the generative model orthogonal to the hyperplane. + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hyper.fit + url_git: '' +hyper2: + version: 3.1-0 + title: The Hyperdirichlet Distribution, Mark 2 + maintainer: Robin K. S. Hankin + description: |- + A suite of routines for the hyperdirichlet distribution + and reified Bradley-Terry; supersedes the 'hyperdirichlet' package; + uses 'disordR' discipline . To cite + in publications please use Hankin 2017 , + and for Generalized Plackett-Luce likelihoods use Hankin 2024 + . + date_publication: '2024-05-31' + bug_reports: https://github.com/RobinHankin/hyper2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hyper2 + url_git: https://github.com/RobinHankin/hyper2 +hyperbolicDEA: + version: 1.0.2 + title: Hyperbolic DEA Estimation + maintainer: Alexander Öttl + description: Implements Data Envelopment Analysis (DEA) with a hyperbolic orientation + using a non-linear programming solver. It enables flexible estimations with weight + restrictions, non-discretionary variables, and a generalized distance function. + Additionally, it allows for the calculation of slacks and super-efficiency scores. + The methods are detailed in Öttl et al. (2023), . + Furthermore, the package provides a non-linear profitability estimation built + upon the DEA framework. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hyperbolicDEA + url_git: '' +HyperbolicDist: + version: 0.6-5 + title: The Hyperbolic Distribution + maintainer: David Scott + description: |- + Maintenance has been discontinued for this package. It has been + superseded by 'GeneralizedHyperbolic'. 'GeneralizedHyperbolic' + includes all the functionality of 'HyperbolicDist' and more + and is based on a more rational design. 'HyperbolicDist' + provides functions for the hyperbolic and related + distributions. Density, distribution and quantile functions + and random number generation are provided for the hyperbolic + distribution, the generalized hyperbolic distribution, + the generalized inverse Gaussian distribution and the + skew-Laplace distribution. Additional functionality is + provided for the hyperbolic distribution, including + fitting of the hyperbolic to data. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HyperbolicDist + url_git: '' +hypercube: + version: 0.2.1 + title: Organizing Data in Hypercubes + maintainer: Michael Scholz + description: |- + Provides functions and methods for organizing data in hypercubes + (i.e., a multi-dimensional cube). Cubes are generated from molten data frames. + Each cube can be manipulated with five operations: rotation (change.dimensionOrder()), + dicing and slicing (add.selection(), remove.selection()), drilling down (add.aggregation()), + and rolling up (remove.aggregation()). + date_publication: '2020-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hypercube + url_git: '' +HyperG: + version: 1.0.0 + title: Hypergraphs in R + maintainer: David J. Marchette + description: |- + Implements various tools for storing and analyzing hypergraphs. + Handles basic undirected, unweighted hypergraphs, and various ways of + creating hypergraphs from a number of representations, and + converting between graphs and hypergraphs. + date_publication: '2021-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HyperG + url_git: '' +hypergate: + version: 0.8.5 + title: |- + Machine Learning of Hyperrectangular Gating Strategies for + High-Dimensional Cytometry + maintainer: Etienne Becht + description: Given a high-dimensional dataset that typically represents a cytometry + dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle + so that datapoints within the hyperrectangle best correspond to the specified + subset. In essence, this allows the conversion of clustering algorithms' outputs + to gating strategies outputs. + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hypergate + url_git: '' +hypergeo: + version: 1.2-13 + title: The Gauss Hypergeometric Function + maintainer: Robin K. S. Hankin + description: The Gaussian hypergeometric function for complex numbers. + date_publication: '2016-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hypergeo + url_git: '' +hypergeo2: + version: 0.2.0 + title: Generalized Hypergeometric Function with Tunable High Precision + maintainer: Xiurui Zhu + description: Computation of generalized hypergeometric function with tunable high + precision in a vectorized manner, with the floating-point datatypes from 'mpfr' + or 'gmp' library. The computation is limited to real numbers. + date_publication: '2024-10-14' + bug_reports: https://github.com/zhuxr11/hypergeo2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hypergeo2 + url_git: https://github.com/zhuxr11/hypergeo2 +HypergeoMat: + version: 4.0.3 + title: Hypergeometric Function of a Matrix Argument + maintainer: Stéphane Laurent + description: |- + Evaluates the hypergeometric functions of a matrix argument, + which appear in random matrix theory. This is an implementation of + Koev & Edelman's algorithm (2006) . + date_publication: '2024-07-28' + bug_reports: https://github.com/stla/HypergeoMat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=HypergeoMat + url_git: https://github.com/stla/HypergeoMat +hyperoverlap: + version: 1.1.1 + title: Overlap Detection in n-Dimensional Space + maintainer: Matilda Brown + description: 'Uses support vector machines to identify a perfectly separating hyperplane + (linear or curvilinear) between two entities in high-dimensional space. If this + plane exists, the entities do not overlap. Applications include overlap detection + in morphological, resource or environmental dimensions. More details can be found + in: Brown et al. (2020) .' + date_publication: '2021-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hyperoverlap + url_git: '' +hyperSpec: + version: 0.100.2 + title: |- + Work with Hyperspectral Data, i.e. Spectra + Meta Information + (Spatial, Time, Concentration, ...) + maintainer: Claudia Beleites + description: |- + Comfortable ways to work with hyperspectral data sets. + I.e. spatially or time-resolved spectra, or spectra with any other kind + of information associated with each of the spectra. The spectra can be data + as obtained in XRF, UV/VIS, Fluorescence, AES, NIR, IR, Raman, NMR, MS, + etc. More generally, any data that is recorded over a discretized variable, + e.g. absorbance = f(wavelength), stored as a vector of absorbance values + for discrete wavelengths is suitable. + date_publication: '2024-05-01' + bug_reports: https://github.com/r-hyperspec/hyperSpec/issues + url: https://r-hyperspec.github.io/hyperSpec/(documentation) + url_cran: https://CRAN.R-project.org/package=hyperSpec + url_git: https://github.com/r-hyperspec/hyperSpec(code) +hypervolume: + version: 3.1.5 + title: |- + High Dimensional Geometry, Set Operations, Projection, and + Inference Using Kernel Density Estimation, Support Vector + Machines, and Convex Hulls + maintainer: Benjamin Blonder + description: 'Estimates the shape and volume of high-dimensional datasets and performs + set operations: intersection / overlap, union, unique components, inclusion test, + and hole detection. Uses stochastic geometry approach to high-dimensional kernel + density estimation, support vector machine delineation, and convex hull generation. + Applications include modeling trait and niche hypervolumes and species distribution + modeling.' + date_publication: '2025-01-17' + bug_reports: https://github.com/bblonder/hypervolume/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hypervolume + url_git: https://github.com/bblonder/hypervolume +HYPEtools: + version: 1.6.4 + title: |- + Tools for Processing and Analyzing Files from the Hydrological + Catchment Model HYPE + maintainer: Rene Capell + description: |- + Work with model files (setup, input, output) from + the hydrological catchment model HYPE: Streamlined file import and export, standard + evaluation plot routines, diverse post-processing and aggregation routines + for hydrological model analysis. The HYPEtools package is also archived at + and can be cited in publications with Brendel et al. (2024) . + date_publication: '2024-11-27' + bug_reports: https://github.com/rcapell/HYPEtools/issues + url: https://hypeweb.smhi.se/ + url_cran: https://CRAN.R-project.org/package=HYPEtools + url_git: https://github.com/rcapell/HYPEtools +hypoRF: + version: 1.0.1 + title: Random Forest Two-Sample Tests + maintainer: Simon Hediger + description: An implementation of Random Forest-based two-sample tests as introduced + in Hediger & Michel & Naef (2022). + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hypoRF + url_git: '' +hypothesis: + version: 1.1.0 + title: Wrapper for 'hypothes.is' + maintainer: Krystian Igras + description: Add, share and manage annotations for 'Shiny' applications and R Markdown + documents via 'hypothes.is'. + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hypothesis + url_git: '' +hypothesisr: + version: 0.1.1 + title: Wrapper for the 'Hypothes.is' Web Annotation Service + maintainer: Matthew Lincoln + description: |- + Interact with the application programming interface for the web + annotation service 'Hypothes.is' (See for more + information.) Allows users to download data about public annotations, and + create, retrieve, update, and delete their own annotations. + date_publication: '2016-07-01' + bug_reports: https://github.com/mdlincoln/hypothesisr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hypothesisr + url_git: https://github.com/mdlincoln/hypothesisr +hypr: + version: 0.2.8 + title: Hypothesis Matrix Translation + maintainer: Maximilian M. Rabe + description: Translation between experimental null hypotheses, hypothesis matrices, + and contrast matrices as used in linear regression models. The package is based + on the method described in Schad et al. (2019) + and Rabe et al. (2020) . + date_publication: '2023-11-09' + bug_reports: https://github.com/mmrabe/hypr/issues + url: https://maxrabe.com/hypr + url_cran: https://CRAN.R-project.org/package=hypr + url_git: '' +hypsoLoop: + version: 0.2.0 + title: A Tool Used to Conduct Hypsometric Analysis of a Watershed + maintainer: Faustin GASHAKAMBA + description: |- + Functions for generating tables required for drawing and calculating hypsometric curves and hypsometric integrals. + These functions accept as input the DEM of the region of interest (your watershed) and a spatial data frame file specifying delineation of sub-catchments within the watershed. + They then generate output in the form of PNG images and HTML files contained in a folder named "HYPSO_OUTPUT" created in the current directory. + S. K. Sharma, S. Gajbhiye, et al. (2018) . + Omvir Singh, A. Sarangi, and Milap C. Sharma (2006) . + James A. Vanderwaal and Herbert Ssegane (2013) . + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hypsoLoop + url_git: '' +HyRiM: + version: 2.0.2 + title: |- + Multicriteria Risk Management using Zero-Sum Games with + Vector-Valued Payoffs that are Probability Distributions + maintainer: '"Stefan Rass, on behalf of the Austrian Institute of Technology"' + description: 'Construction and analysis of multivalued zero-sum matrix games over + the abstract space of probability distributions, which describe the losses in + each scenario of defense vs. attack action. The distributions can be compiled + directly from expert opinions or other empirical data (insofar available). The + package implements the methods put forth in the EU project HyRiM (Hybrid Risk + Management for Utility Networks), FP7 EU Project Number 608090. The method has + been published in Rass, S., König, S., Schauer, S., 2016. Decisions with Uncertain + Consequences-A Total Ordering on Loss-Distributions. PLoS ONE 11, e0168583. , + and applied for advanced persistent thread modeling in Rass, S., König, S., Schauer, + S., 2017. Defending Against Advanced Persistent Threats Using Game-Theory. PLoS + ONE 12, e0168675. . A volume covering the wider + range of aspects of risk management, partially based on the theory implemented + in the package is the book edited by S. Rass and S. Schauer, 2018. Game Theory + for Security and Risk Management: From Theory to Practice. Springer, , + ISBN 978-3-319-75267-9.' + date_publication: '2022-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=HyRiM + url_git: '' +hySAINT: + version: 1.2.1 + title: |- + Hybrid Genetic and Simulated Annealing Algorithm for High + Dimensional Linear Models with Interaction Effects + maintainer: Leiyue Li + description: 'We provide a stage-wise selection method using genetic algorithms, + designed to efficiently identify main and two-way interactions within high-dimensional + linear regression models. Additionally, it implements simulated annealing algorithm + during the mutation process. The relevant paper can be found at: Ye, C.,and Yang,Y. + (2019) .' + date_publication: '2024-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hySAINT + url_git: '' +hySpc.testthat: + version: 0.2.1 + title: '''testthat'' Unit Test Enhancements' + maintainer: Claudia Beleites + description: |- + Enhance package 'testthat' by allowing tests to be attached to the function/object they test. + This allows to keep functional and unit test code together. + date_publication: '2020-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hySpc.testthat + url_git: '' +hystar: + version: 1.0.0 + title: Fit the Hysteretic Threshold Autoregressive Model + maintainer: Daan de Jong + description: |- + Estimate parameters of the hysteretic threshold autoregressive + (HysTAR) model, using conditional least squares. + In addition, you can generate time series data from the HysTAR model. + For details, see Li, Guan, Li and Yu (2015) . + date_publication: '2023-07-05' + bug_reports: https://github.com/daandejongen/hystar/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=hystar + url_git: https://github.com/daandejongen/hystar/ +hysteresis: + version: 2.7.2 + title: |- + Tools for Modeling Rate-Dependent Hysteretic Processes and + Ellipses + maintainer: Spencer Maynes + description: |- + Fit, summarize and plot sinusoidal hysteretic processes using: + two-step simple harmonic least squares, ellipse-specific non-linear least + squares, the direct method, geometric least squares or linear least squares. See + Yang, F and A. Parkhurst, "Efficient Estimation of Elliptical Hysteresis with + Application to the Characterization of Heat Stress" . + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hysteresis + url_git: '' +hystReet: + version: 0.0.3 + title: Get Pedestrian Frequency Data from the 'Hystreet' Project + maintainer: Johannes Friedrich + description: An R API wrapper for the 'Hystreet' project . + 'Hystreet' provides pedestrian counts in different cities in Germany. + date_publication: '2022-11-27' + bug_reports: https://github.com/JohannesFriedrich/hystReet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=hystReet + url_git: https://github.com/JohannesFriedrich/hystReet +hytest: + version: 0.1.1 + title: |- + Hypothesis Testing Based on Neyman-Pearson Lemma and Likelihood + Ratio Test + maintainer: Carlos Alberto Cardozo Delgado + description: |- + Error type I and Optimal critical values to test statistical hypothesis based on Neyman-Pearson Lemma and Likelihood ratio test + based on random samples from several distributions. The families of distributions are Bernoulli, Exponential, Geometric, Inverse Normal, + Normal, Gamma, Gumbel, Lognormal, Poisson, and Weibull. + This package is an ideal resource to help with the teaching of Statistics. + The main references for this package are Casella G. and Berger R. (2003,ISBN:0-534-24312-6 , "Statistical Inference. Second Edition", Duxbury Press) and + Hogg, R., McKean, J., and Craig, A. (2019,ISBN:013468699, "Introduction to Mathematical Statistic. Eighth edition", Pearson). + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=hytest + url_git: '' +i18n: + version: 0.2.0 + title: |- + Internationalization Data from the 'Unicode CLDR' in Tabular + Form + maintainer: Richard Iannone + description: |- + Up-to-date data from the 'Unicode CLDR Project' (where 'CLDR' + stands for 'Common Locale Data Repository') are available here as a series + of easy-to-parse datasets. Several functions are provided for extracting + key elements from the tabular datasets. + date_publication: '2022-09-07' + bug_reports: https://github.com/rich-iannone/i18n/issues + url: '' + url_cran: https://CRAN.R-project.org/package=i18n + url_git: https://github.com/rich-iannone/i18n +i2extras: + version: 0.2.1 + title: Functions to Work with 'incidence2' Objects + maintainer: Tim Taylor + description: |- + Provides functions to work with 'incidence2' objects, including a + simplified interface for trend fitting and peak estimation. This package is + part of the RECON () toolkit for + outbreak analysis (. A physical copy will be published by CRC Press. + date_publication: '2020-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IAcsSPCR + url_git: '' +iAdapt: + version: 2.0.1 + title: Two-Stage Adaptive Dose-Finding Clinical Trial Design + maintainer: Alyssa Vanderbeek + description: Simulate and implement early phase two-stage adaptive dose-finding + design for binary and quasi-continuous toxicity endpoints. See Chiuzan et al. + (2018) for further reading . + date_publication: '2021-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iAdapt + url_git: '' +iadf: + version: 0.1.3 + title: Analysis of Intra Annual Density Fluctuations + maintainer: Konrad Mayer + description: |- + Calculate false ring proportions from data frames of intra annual + density fluctuations. + date_publication: '2025-01-31' + bug_reports: https://github.com/konradmayer/iadf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iadf + url_git: https://github.com/konradmayer/iadf +IADT: + version: 1.2.1 + title: Interaction Difference Test for Prediction Models + maintainer: Thomas Welchowski + description: Provides functions to conduct a model-agnostic asymptotic hypothesis + test for the identification of interaction effects in black-box machine learning + models. The null hypothesis assumes that a given set of covariates does not contribute + to interaction effects in the prediction model. The test statistic is based on + the difference of variances of partial dependence functions (Friedman (2008) + and Welchowski (2022) ) with respect to the original + black-box predictions and the predictions under the null hypothesis. The hypothesis + test can be applied to any black-box prediction model, and the null hypothesis + of the test can be flexibly specified according to the research question of interest. + Furthermore, the test is computationally fast to apply as the null distribution + does not require resampling or refitting black-box prediction models. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IADT + url_git: '' +iai: + version: 1.10.2 + title: Interface to 'Interpretable AI' Modules + maintainer: Jack Dunn + description: |- + An interface to the algorithms of 'Interpretable AI' + from the R programming language. + 'Interpretable AI' provides various modules, including 'Optimal Trees' for + classification, regression, prescription and survival analysis, 'Optimal + Imputation' for missing data imputation and outlier detection, and 'Optimal + Feature Selection' for exact sparse regression. The 'iai' package is an + open-source project. The 'Interpretable AI' software modules are proprietary + products, but free academic and evaluation licenses are available. + date_publication: '2024-10-18' + bug_reports: '' + url: https://www.interpretable.ai + url_cran: https://CRAN.R-project.org/package=iai + url_git: '' +ialiquor: + version: 0.1.0 + title: Monthly Iowa Liquor Sales Summary + maintainer: Nikhil Agarwal + description: |- + Provides a monthly summary of Iowa liquor (class E) sales from January 2015 + to October 2020. See the package website for more information, + documentation and examples. Data source: + Iowa Data portal . + date_publication: '2020-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ialiquor + url_git: '' +IALS: + version: 0.1.3 + title: |- + Iterative Alternating Least Square Estimation for + Large-Dimensional Matrix Factor Model + maintainer: Ran Zhao + description: The matrix factor model has drawn growing attention for its advantage + in achieving two-directional dimension reduction simultaneously for matrix-structured + observations. In contrast to the Principal Component Analysis (PCA)-based methods, + we propose a simple Iterative Alternating Least Squares (IALS) algorithm for matrix + factor model, see the details in He et al. (2023) . + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IALS + url_git: '' +iapws: + version: '1.1' + title: |- + Formulations of the International Association for the Properties + of Water and Steam + maintainer: Jonathan Debove + description: |- + Implementation of some of the formulations for the thermodynamic + and transport properties released by the International Association for + the Properties of Water and Steam (IAPWS). More specifically, the + releases R1-76(2014), R5-85(1994), R6-95(2018), R7-97(2012), R8-97, + R9-97, R10-06(2009), R11-07(2019), R12-08, R15-11, R16-17(2018), + R17-20 and R18-21 at . + date_publication: '2022-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iapws + url_git: '' +IAPWS95: + version: 1.2.4 + title: Thermophysical Properties of Water and Steam + maintainer: Shawn Way + description: |- + An implementation of the International Association for the + Properties of Water (IAPWS) Formulation 1995 for the Thermodynamic Properties of Ordinary + Water Substance for General and Scientific Use and on the releases for viscosity, + conductivity, surface tension and melting pressure. + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IAPWS95 + url_git: '' +iAR: + version: 1.2.0 + title: Irregularly Observed Autoregressive Models + maintainer: Elorrieta Felipe + description: Data sets, functions and scripts with examples to implement autoregressive + models for irregularly observed time series. The models available in this package + are the irregular autoregressive model (Eyheramendy et al.(2018) ), + the complex irregular autoregressive model (Elorrieta et al.(2019) ) + and the bivariate irregular autoregressive model (Elorrieta et al.(2021) ). + date_publication: '2022-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iAR + url_git: https://github.com/felipeelorrieta +iarm: + version: 0.4.3 + title: Item Analysis in Rasch Models + maintainer: Marianne Mueller + description: Tools to assess model fit and identify misfitting items for Rasch models + (RM) and partial credit models (PCM). Included are item fit statistics, item characteristic + curves, item-restscore association, conditional likelihood ratio tests, assessment + of measurement error, estimates of the reliability and test targeting as described + in Christensen et al. (Eds.) (2013, ISBN:978-1-84821-222-0). + date_publication: '2022-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iarm + url_git: '' +IASD: + version: 1.1.1 + title: Model Selection for Index of Asymmetry Distribution + maintainer: Satoshi Takahashi + description: Calculate AIC's and AICc's of unimodal model (one normal distribution) + and bimodal model(a mixture of two normal distributions) which fit the distribution + of indices of asymmetry (IAS), and plot their density, to help determine IAS distribution + is unimodal or bimodal. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IASD + url_git: '' +IAT: + version: '0.3' + title: Cleaning and Visualizing Implicit Association Test (IAT) Data + maintainer: Dan Martin + description: |- + Implements the standard D-Scoring algorithm + (Greenwald, Banaji, & Nosek, 2003) for Implicit Association Test (IAT) + data and includes plotting capabilities for exploring raw IAT data. + date_publication: '2016-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IAT + url_git: '' +IATanalytics: + version: 0.2.0 + title: |- + Compute Effect Sizes and Reliability for Implicit Association + Test (IAT) Data + maintainer: Daniel Storage + description: 'Quickly score raw data outputted from an Implicit Association Test + (IAT; Greenwald, McGhee, & Schwartz, 1998) . + IAT scores are calculated as specified by Greenwald, Nosek, and Banaji (2003) + . The output of this function is a data frame + that consists of four rows containing the following information: (1) the overall + IAT effect size for the participant''s dataset, (2) the effect size calculated + for odd trials only, (3) the effect size calculated for even trials only, and + (4) the proportion of trials with reaction times under 300ms (which is important + for exclusion purposes). Items (2) and (3) allow for a measure of the internal + consistency of the IAT. Specifically, you can use the subsetted IAT effect sizes + for odd and even trials to calculate Cronbach''s alpha across participants in + the sample. The input function consists of three arguments. First, indicate + the name of the dataset to be analyzed. This is the only required input. Second, + indicate the number of trials in your entire IAT (the default is set to 220, which + is typical for most IATs). Last, indicate whether congruent trials (e.g., flowers + and pleasant) or incongruent trials (e.g., guns and pleasant) were presented first + for this participant (the default is set to congruent). Data files should consist + of six columns organized in order as follows: Block (0-6), trial (0-19 for training + blocks, 0-39 for test blocks), category (dependent on your IAT), the type of item + within that category (dependent on your IAT), a dummy variable indicating whether + the participant was correct or incorrect on that trial (0=correct, 1=incorrect), + and the participant’s reaction time (in milliseconds). A sample dataset (titled + ''sampledata'') is included in this package to practice with.' + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IATanalytics + url_git: '' +IATScore: + version: 0.2.0 + title: Scoring Algorithm for the Implicit Association Test (IAT) + maintainer: Daniel Storage + description: 'This minimalist package is designed to quickly score raw data outputted + from an Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) . + IAT scores are calculated as specified by Greenwald, Nosek, and Banaji (2003) + . Outputted values can be interpreted as effect + sizes. The input function consists of three arguments. First, indicate the name + of the dataset to be analyzed. This is the only required input. Second, indicate + the number of trials in your entire IAT (the default is set to 219, which is typical + for most IATs). Last, indicate whether congruent trials (e.g., flowers and pleasant) + or incongruent trials (e.g., guns and pleasant) were presented first for this + participant (the default is set to congruent). The script will tell you how long + it took to run the code, the effect size for the participant, and whether that + participant should be excluded based on the criteria outlined by Greenwald et + al. (2003). Data files should consist of six columns organized in order as follows: + Block (0-6), trial (0-19 for training blocks, 0-39 for test blocks), category + (dependent on your IAT), the type of item within that category (dependent on your + IAT), a dummy variable indicating whether the participant was correct or incorrect + on that trial (0=correct, 1=incorrect), and the participant’s reaction time (in + milliseconds). Three sample datasets are included in this package (labeled ''IAT'', + ''TooFastIAT'', and ''BriefIAT'') to practice with.' + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IATScore + url_git: '' +IATscores: + version: 0.2.7 + title: Implicit Association Test Scores Using Robust Statistics + maintainer: Giulio Costantini + description: Compute several variations of the Implicit Association Test (IAT) scores, + including the D scores (Greenwald, Nosek, Banaji, 2003, ) + and the new scores that were developed using robust statistics (Richetin, Costantini, + Perugini, and Schonbrodt, 2015, ). + date_publication: '2020-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IATscores + url_git: '' +ib: + version: 0.2.0 + title: Bias Correction via Iterative Bootstrap + maintainer: Samuel Orso + description: |- + An implementation of the iterative bootstrap procedure of + Kuk (1995) to correct the estimation bias of a fitted model object. This + procedure has better bias correction properties than the + bootstrap bias correction technique. + date_publication: '2022-04-04' + bug_reports: https://github.com/SMAC-Group/ib/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=ib + url_git: https://github.com/SMAC-Group/ib/ +iBART: + version: 1.0.0 + title: |- + Iterative Bayesian Additive Regression Trees Descriptor + Selection Method + maintainer: Shengbin Ye + description: |- + A statistical method based on Bayesian Additive Regression Trees with Global + Standard Error Permutation Test (BART-G.SE) for descriptor selection + and symbolic regression. It finds the symbolic formula of the regression function + y=f(x) as described in Ye, Senftle, and Li (2023) . + date_publication: '2023-11-14' + bug_reports: https://github.com/mattsheng/iBART/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iBART + url_git: https://github.com/mattsheng/iBART +ibawds: + version: 1.0.0 + title: Functions and Datasets for the Data Science Course at IBAW + maintainer: Stefan Lanz + description: |- + A collection of useful functions and datasets for the Data Science + Course at IBAW. + date_publication: '2024-09-30' + bug_reports: https://github.com/stibu81/ibawds/issues + url: https://stibu81.github.io/ibawds/ + url_cran: https://CRAN.R-project.org/package=ibawds + url_git: '' +ibb: + version: 0.0.2 + title: R Wrapper for Istanbul Municipality Open Data Portal + maintainer: Berk Orbay + description: |- + Call wrappers for Istanbul Metropolitan + Municipality's Open Data Portal (Turkish: İstanbul Büyükşehir + Belediyesi Açık Veri Portalı) at . + date_publication: '2021-02-17' + bug_reports: https://github.com/berkorbay/ibb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ibb + url_git: https://github.com/berkorbay/ibb +IBCF.MTME: + version: 1.6-0 + title: |- + Item Based Collaborative Filtering for Multi-Trait and + Multi-Environment Data + maintainer: Francisco Javier Luna-Vazquez + description: Implements the item based collaborative filtering (IBCF) method for + continues phenotypes in the context of plant breeding where data are collected + for various traits that were studied in various environments proposed by Montesinos-López + et al. (2017) . + date_publication: '2019-03-23' + bug_reports: https://github.com/frahik/IBCF.MTME/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=IBCF.MTME + url_git: https://github.com/frahik/IBCF.MTME +ibd: + version: '1.6' + title: Incomplete Block Designs + maintainer: B N Mandal + description: A collection of several utility functions related to binary incomplete + block designs. Contains function to generate A- and D-efficient binary incomplete + block designs with given numbers of treatments, number of blocks and block size. + Contains function to generate an incomplete block design with specified concurrence + matrix. There are functions to generate balanced treatment incomplete block designs + and incomplete block designs for test versus control treatments comparisons with + specified concurrence matrix. Allows performing analysis of variance of data and + computing estimated marginal means of factors from experiments using a connected + incomplete block design. Tests of hypothesis of treatment contrasts in incomplete + block design set up is supported. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibd + url_git: '' +IBDsim: + version: 0.9-8 + title: Simulation of Chromosomal Regions Shared by Family Members + maintainer: Magnus Dehli Vigeland + description: |- + Simulation of segments shared identical-by-descent (IBD) by + pedigree members. Using sex specific recombination rates along the human + genome (Kong et. al (2010) ), phased chromosomes + are simulated for all pedigree members, either by unconditional gene + dropping or conditional on a specified IBD pattern. Additional functions + provide summaries and further analysis of the simulated genomes. + date_publication: '2019-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IBDsim + url_git: '' +ibdsim2: + version: 2.1.1 + title: Simulation of Chromosomal Regions Shared by Family Members + maintainer: Magnus Dehli Vigeland + description: |- + Simulation of segments shared identical-by-descent (IBD) by + pedigree members. Using sex specific recombination rates along the + human genome (Halldorsson et al. (2019) + ), phased chromosomes are simulated for + all pedigree members. Applications include calculation of realised + relatedness coefficients and IBD segment distributions. 'ibdsim2' is + part of the 'pedsuite' collection of packages for pedigree analysis. + A detailed presentation of the 'ped suite', including a separate + chapter on 'ibdsim2', is available in the book 'Pedigree analysis in + R' (Vigeland, 2021, ISBN:9780128244302). A 'Shiny' app for visualising + and comparing IBD distributions is available at + . + date_publication: '2024-09-08' + bug_reports: '' + url: https://magnusdv.github.io/pedsuite/ + url_cran: https://CRAN.R-project.org/package=ibdsim2 + url_git: https://github.com/magnusdv/ibdsim2 +ibelief: + version: 1.3.1 + title: Belief Function Implementation + maintainer: Kuang Zhou + description: |- + Some basic functions to implement belief functions including: + transformation between belief functions using the method introduced by + Philippe Smets , evidence combination, evidence + discounting, decision-making, and constructing masses. Currently, thirteen + combination rules and six decision rules are supported. It can also be + used to generate different types of random masses when working on belief + combination and conflict management. + date_publication: '2021-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibelief + url_git: '' +IBFS: + version: 1.0.0 + title: Initial Basic Feasible Solution for Transportation Problem + maintainer: Royson Almeida + description: |- + The initial basic feasible solution (IBFS) is a significant step to achieve the minimal total cost (optimal solution) of the transportation problem. However, the existing methods of IBFS do not always provide a good feasible solution which can reduce the number of iterations to find the optimal solution. This initial basic feasible solution can be obtained by using any of the following methods. + a) North West Corner Method. + b) Least Cost Method. + c) Row Minimum Method. + d) Column Minimum Method. + e) Vogel's Approximation Method. + etc. + For more technical details about the algorithms please refer below URLs. + . + . + . + . + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IBFS + url_git: '' +ibm: + version: 0.3.0 + title: Individual Based Models in R + maintainer: Ricardo Oliveros-Ramos + description: |- + Implementation of some Individual Based Models (IBMs, sensu Grimm and Railsback 2005) + and methods to create new ones, particularly for population dynamics models (reproduction, + mortality and movement). The basic operations for the simulations are implemented in Rcpp for speed. + date_publication: '2024-02-14' + bug_reports: https://github.com/roliveros-ramos/ibm/issues + url: https://roliveros-ramos.github.io/ibm/ + url_cran: https://CRAN.R-project.org/package=ibm + url_git: '' +ibmAcousticR: + version: 0.2.1 + title: Connect to Your 'IBM Acoustic' Data + maintainer: Chris Umphlett + description: |- + Authentication can be the most difficult part about + working with a new API. 'ibmAcousticR' facilitates making a + connection to the 'IBM Acoustic' email campaign management API + and executing various queries. The 'IBM Acoustic' API + documentation is available at + . This + package is not supported by 'IBM'. + date_publication: '2020-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibmAcousticR + url_git: '' +ibmcraftr: + version: 1.0.0 + title: |- + Toolkits to Develop Individual-Based Models in Infectious + Disease + maintainer: Sai Thein Than Tun + description: |- + It provides a generic set of tools for initializing a synthetic + population with each individual in specific disease states, and + making transitions between those disease states according to the rates + calculated on each timestep. The new version 1.0.0 has C++ code + integration to make the functions run faster. It has also a higher level + function to actually run the transitions for the number of timesteps + that users specify. Additional functions will follow for changing + attributes on demographic, health belief and movement. + date_publication: '2016-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibmcraftr + url_git: '' +ibmdbR: + version: 1.51.0 + title: IBM in-Database Analytics for R + maintainer: Shaikh Quader + description: |2- + + Functionality required to efficiently use R with IBM(R) Db2(R) + Warehouse offerings (formerly IBM dashDB(R)) and IBM Db2 for z/OS(R) in + conjunction with IBM Db2 Analytics Accelerator for z/OS. + Many basic and complex R operations are pushed down into the database, + which removes the main memory boundary of R and allows to make full + use of parallel processing in the underlying database. + For executing R-functions in a multi-node environment in parallel the idaTApply() function + requires the 'SparkR' package (). + The optional 'ggplot2' package is needed for the plot.idaLm() function only. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibmdbR + url_git: '' +IBMPopSim: + version: 1.1.0 + title: Individual Based Model Population Simulation + maintainer: Daphné Giorgi + description: |- + Simulation of the random evolution of heterogeneous populations using stochastic Individual-Based Models (IBMs) . + The package enables users to simulate population evolution, in which individuals are characterized by their age and some characteristics, and the population is modified by different types of events, including births/arrivals, death/exit events, or changes of characteristics. The frequency at which an event can occur to an individual can depend on their age and characteristics, but also on the characteristics of other individuals (interactions). + Such models have a wide range of applications. For instance, IBMs can be used for simulating the evolution of a heterogeneous insurance portfolio with selection or for validating mortality forecasts. + This package overcomes the limitations of time-consuming IBMs simulations by implementing new efficient algorithms based on thinning methods, which are compiled using the 'Rcpp' package while providing a user-friendly interface. + date_publication: '2024-10-15' + bug_reports: https://github.com/DaphneGiorgi/IBMPopSim/issues + url: https://DaphneGiorgi.github.io/IBMPopSim/ + url_cran: https://CRAN.R-project.org/package=IBMPopSim + url_git: https://github.com/DaphneGiorgi/IBMPopSim +ibmsunburst: + version: 0.1.4 + title: Generate Personality Insights Sunburst Diagrams + maintainer: Colin Gillespie + description: |- + Generates Personality Insights sunburst diagrams based on + 'IBM Watson' Personality Insights service output. + date_publication: '2024-02-28' + bug_reports: https://github.com/jumpingrivers/ibmsunburst/issues + url: https://jumpingrivers.github.io/ibmsunburst/ + url_cran: https://CRAN.R-project.org/package=ibmsunburst + url_git: https://github.com/jumpingrivers/ibmsunburst +ibr: + version: 2.0-4 + title: Iterative Bias Reduction + maintainer: '"Pierre-Andre Cornillon"' + description: Multivariate smoothing using iterative bias reduction with kernel, + thin plate splines, Duchon splines or low rank splines. + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibr + url_git: '' +iBreakDown: + version: 2.1.2 + title: Model Agnostic Instance Level Variable Attributions + maintainer: Przemyslaw Biecek + description: |- + Model agnostic tool for decomposition of predictions from black boxes. + Supports additive attributions and attributions with interactions. + The Break Down Table shows contributions of every variable to a final prediction. + The Break Down Plot presents variable contributions in a concise graphical way. + This package works for classification and regression models. + It is an extension of the 'breakDown' package (Staniak and Biecek 2018) , + with new and faster strategies for orderings. + It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). + The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) + This package is a part of the 'DrWhy.AI' universe (Biecek 2018) . + date_publication: '2023-12-01' + bug_reports: https://github.com/ModelOriented/iBreakDown/issues + url: https://ModelOriented.github.io/iBreakDown/ + url_cran: https://CRAN.R-project.org/package=iBreakDown + url_git: https://github.com/ModelOriented/iBreakDown +IBrokers: + version: 0.10-2 + title: R API to Interactive Brokers Trader Workstation + maintainer: Joshua M. Ulrich + description: Provides native R access to Interactive Brokers Trader Workstation + API. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IBrokers + url_git: '' +IBRtools: + version: 0.1.3 + title: Integrating Biomarker-Based Assessments and Radarchart Creation + maintainer: Anna Carolina Resende + description: Several functions to calculate two important indexes (IBR (Integrated + Biomarker Response) and IBRv2 (Integrated Biological Response version 2)), it + also calculates the standardized values for enzyme activity for each index, and + it has a graphing function to perform radarplots that make great data visualization + for this type of data. Beliaeff, B., & Burgeot, T. (2002). . + Sanchez, W., Burgeot, T., & Porcher, J.-M. (2013).. + Devin, S., Burgeot, T., Giambérini, L., Minguez, L., & Pain-Devin, S. (2014). + . Minato N. (2022). . + date_publication: '2023-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IBRtools + url_git: '' +ibs: + version: '1.4' + title: Integral of B-Spline Functions + maintainer: Feng Chen + description: Calculate B-spline basis functions with a given set of knots and order, + or a B-spline function with a given set of knots and order and set of de Boor + points (coefficients), or the integral of a B-spline function. + date_publication: '2018-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ibs + url_git: '' +iBST: + version: '1.2' + title: Improper Bagging Survival Tree + maintainer: Cyprien Mbogning + description: |- + Fit a full or subsampling bagging survival tree on a mixture of population (susceptible and nonsusceptible) + using either a pseudo R2 criterion or an adjusted Logrank criterion. The predictor is + evaluated using the Out Of Bag Integrated Brier Score (IBS) and several scores of importance + are computed for variable selection. The thresholds values for variable selection are + computed using a nonparametric permutation test. + See 'Cyprien Mbogning' and 'Philippe Broet' (2016) for + an overview about the methods implemented in this package. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iBST + url_git: '' +ic.infer: + version: 1.1-7 + title: Inequality Constrained Inference in Linear Normal Situations + maintainer: Ulrike Groemping + description: Implements inequality constrained inference. This includes parameter + estimation in normal (linear) models under linear equality and inequality constraints, + as well as normal likelihood ratio tests involving inequality-constrained hypotheses. + For inequality-constrained linear models, averaging over R-squared for different + orderings of regressors is also included. + date_publication: '2023-10-04' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/ + url_cran: https://CRAN.R-project.org/package=ic.infer + url_git: '' +iC10: + version: 2.0.2 + title: A Copy Number and Expression-Based Classifier for Breast Tumours + maintainer: Oscar M Rueda + description: Implementation of the classifier described in the paper Ali HR et al + (2014) . It uses copy number and/or expression + form breast cancer data, trains a Tibshirani's 'pamr' classifier with the features + available and predicts the iC10 group. + date_publication: '2024-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iC10 + url_git: '' +iC10TrainingData: + version: 2.0.1 + title: Training Datasets for iC10 Package + maintainer: Oscar M. Rueda + description: Training datasets for iC10; which implements the classifier described + in the paper 'Genome-driven integrated classification of breast cancer validated + in over 7,500 samples' (Ali HR et al., Genome Biology 2014). It uses copy number + and/or expression form breast cancer data, trains a pamr classifier (Tibshirani + et al.) with the features available and predicts the iC10 group. Genomic annotation + for the training dataset has been obtained from Mark Dunning's lluminaHumanv3.db + package. + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iC10TrainingData + url_git: '' +ica: + version: 1.0-3 + title: Independent Component Analysis + maintainer: Nathaniel E. Helwig + description: 'Independent Component Analysis (ICA) using various algorithms: FastICA, + Information-Maximization (Infomax), and Joint Approximate Diagonalization of Eigenmatrices + (JADE).' + date_publication: '2022-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ica + url_git: '' +ical: + version: 0.1.6 + title: '''iCalendar'' Parsing' + maintainer: Peter Meissner + description: |- + A simple wrapper around the 'ical.js' library executing + 'Javascript' code via 'V8' (the 'Javascript' engine driving the 'Chrome' + browser and 'Node.js' and accessible via the 'V8' R package). + This package enables users to parse 'iCalendar' files ('.ics', '.ifb', + '.iCal', '.iFBf') into lists and 'data.frames' to ultimately do statistics + on events, meetings, schedules, birthdays, and the like. + date_publication: '2019-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ical + url_git: '' +iCAMP: + version: 1.5.12 + title: |- + Infer Community Assembly Mechanisms by Phylogenetic-Bin-Based + Null Model Analysis + maintainer: Daliang Ning + description: To implement a general framework to quantitatively infer Community + Assembly Mechanisms by Phylogenetic-bin-based null model analysis, abbreviated + as 'iCAMP' (Ning et al 2020) . It can quantitatively + assess the relative importance of different community assembly processes, such + as selection, dispersal, and drift, for both communities and each phylogenetic + group ('bin'). Each bin usually consists of different taxa from a family or an + order. The package also provides functions to implement some other published methods, + including neutral taxa percentage (Burns et al 2016) + based on neutral theory model and quantifying assembly processes based on entire-community + null models ('QPEN', Stegen et al 2013) . It also includes + some handy functions, particularly for big datasets, such as phylogenetic and + taxonomic null model analysis at both community and bin levels, between-taxa niche + difference and phylogenetic distance calculation, phylogenetic signal test within + phylogenetic groups, midpoint root of big trees, etc. Version 1.3.x mainly improved + the function for 'QPEN' and added function 'icamp.cate()' to summarize 'iCAMP' + results for different categories of taxa (e.g. core versus rare taxa). + date_publication: '2022-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iCAMP + url_git: https://github.com/DaliangNing/iCAMP1 +ICAMS: + version: 2.3.12 + title: |- + In-Depth Characterization and Analysis of Mutational Signatures + ('ICAMS') + maintainer: Steve Rozen + description: |- + Analysis and visualization of experimentally elucidated mutational + signatures -- the kind of analysis and visualization in Boot et al., + "In-depth characterization of the cisplatin mutational signature in + human cell lines and in esophageal and liver tumors", Genome Research 2018, + and + "Characterization of colibactin-associated mutational signature in an + Asian oral squamous cell carcinoma and in other mucosal tumor types", + Genome Research 2020 . + 'ICAMS' stands for In-depth Characterization + and Analysis of Mutational Signatures. 'ICAMS' has functions to read in + variant call files (VCFs) and to collate the corresponding catalogs of + mutational spectra and to analyze and plot catalogs of mutational spectra + and signatures. Handles both "counts-based" and "density-based" (i.e. + representation as mutations per megabase) mutational spectra or signatures. + date_publication: '2024-02-09' + bug_reports: https://github.com/steverozen/ICAMS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ICAMS + url_git: https://github.com/steverozen/ICAMS +ICAOD: + version: 1.0.1 + title: |- + Optimal Designs for Nonlinear Statistical Models by Imperialist + Competitive Algorithm (ICA) + maintainer: Ehsan Masoudi + description: Finds optimal designs for nonlinear models using a metaheuristic algorithm + called Imperialist Competitive Algorithm (ICA). See, for details, Masoudi et al. + (2017) and Masoudi et al. (2019) . + date_publication: '2020-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICAOD + url_git: '' +icardaFIGSr: + version: 1.0.2 + title: |- + Subsetting using Focused Identification of the Germplasm + Strategy (FIGS) + maintainer: Zakaria Kehel + description: Running Focused Identification of the Germplasm Strategy (FIGS) to + make best subsets from Genebank Collection. + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icardaFIGSr + url_git: '' +iCARH: + version: 2.0.2.1 + title: Integrative Conditional Autoregressive Horseshoe Model + maintainer: Takoua Jendoubi + description: |- + Implements the integrative conditional autoregressive horseshoe model + discussed in Jendoubi, T., Ebbels, T.M. Integrative analysis of time course metabolic data and biomarker discovery. + BMC Bioinformatics 21, 11 (2020) . + The model consists in three levels: Metabolic pathways level modeling interdependencies between + variables via a conditional auto-regressive (CAR) component, integrative analysis level to identify + potential associations between heterogeneous omic variables via a Horseshoe prior and experimental + design level to capture experimental design conditions through a mixed-effects model. + The package also provides functions to simulate data from the model, construct pathway matrices, + post process and plot model parameters. + date_publication: '2020-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iCARH + url_git: '' +icarus: + version: 0.3.2 + title: Calibrates and Reweights Units in Samples + maintainer: Antoine Rebecq + description: |- + Provides user-friendly tools for calibration in survey sampling. + The package is production-oriented, and its interface is inspired by the famous + popular macro 'Calmar' for SAS, so that 'Calmar' users can quickly get used to + 'icarus'. In addition to calibration (with linear, raking and logit methods), + 'icarus' features functions for calibration on tight bounds and penalized + calibration. + date_publication: '2023-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icarus + url_git: '' +ICBioMark: + version: 0.1.4 + title: |- + Data-Driven Design of Targeted Gene Panels for Estimating + Immunotherapy Biomarkers + maintainer: Jacob R. Bradley + description: Implementation of the methodology proposed in 'Data-driven design of + targeted gene panels for estimating immunotherapy biomarkers', Bradley and Cannings + (2021) . This package allows the user to fit generative models + of mutation from an annotated mutation dataset, and then further to produce tunable + linear estimators of exome-wide biomarkers. It also contains functions to simulate + mutation annotated format (MAF) data, as well as to analyse the output and performance + of models. + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICBioMark + url_git: '' +ICC: + version: 2.4.0 + title: |- + Facilitating Estimation of the Intraclass Correlation + Coefficient + maintainer: Matthew Wolak + description: |- + Assist in the estimation of the Intraclass Correlation Coefficient + (ICC) from variance components of a one-way analysis of variance and also + estimate the number of individuals or groups necessary to obtain an ICC + estimate with a desired confidence interval width. + date_publication: '2022-05-20' + bug_reports: https://github.com/matthewwolak/ICC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ICC + url_git: https://github.com/matthewwolak/ICC +ICC.Sample.Size: + version: '1.0' + title: Calculation of Sample Size and Power for ICC + maintainer: Alasdair Rathbone + description: |- + Provides functions to calculate the requisite sample size for studies where ICC is + the primary outcome. Can also be used for calculation of power. In both cases it + allows the user to test the impact of changing input variables by calculating the outcome + for several different values of input variables. Based off the work of Zou. + Zou, G. Y. (2012). Sample size formulas for estimating intraclass correlation coefficients with + precision and assurance. Statistics in medicine, 31(29), 3972-3981. + date_publication: '2015-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICC.Sample.Size + url_git: '' +ICcalib: + version: 1.0.8 + title: Cox Model with Interval-Censored Starting Time of a Covariate + maintainer: Daniel Nevo + description: Calibration and risk-set calibration methods for fitting Cox proportional + hazard model when a binary covariate is measured intermittently. Methods include + functions to fit calibration models from interval-censored data and modified partial + likelihood for the proportional hazard model, Nevo et al. (2018+) . + date_publication: '2018-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICcalib + url_git: '' +iccbeta: + version: 1.2.0 + title: Multilevel Model Intraclass Correlation for Slope Heterogeneity + maintainer: Steven Andrew Culpepper + description: |- + A function and vignettes for computing an intraclass correlation + described in Aguinis & Culpepper (2015) . + This package quantifies the share of variance in a dependent variable that + is attributed to group heterogeneity in slopes. + date_publication: '2019-01-28' + bug_reports: https://github.com/tmsalab/iccbeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iccbeta + url_git: https://github.com/tmsalab/iccbeta +ICCbin: + version: 1.1.1 + title: |- + Facilitates Clustered Binary Data Generation, and Estimation of + Intracluster Correlation Coefficient (ICC) for Binary Data + maintainer: Akhtar Hossain + description: Assists in generating binary clustered data, estimates of Intracluster + Correlation coefficient (ICC) for binary response in 16 different methods, and + 5 different types of confidence intervals. + date_publication: '2017-11-14' + bug_reports: https://github.com/akhtarh/ICCbin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ICCbin + url_git: '' +iccCounts: + version: 1.1.2 + title: Intraclass Correlation Coefficient for Count Data + maintainer: Josep L. Carrasco + description: 'Estimates the intraclass correlation coefficient (ICC) for count data + to assess repeatability (intra-methods concordance) and concordance (between-method + concordance). In the concordance setting, the ICC is equivalent to the concordance + correlation coefficient estimated by variance components. The ICC is estimated + using the estimates from generalized linear mixed models. The within-subjects + distributions considered are: Poisson; Negative Binomial with additive and proportional + extradispersion; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial with + additive and proportional extradispersion. The statistical methodology used to + estimate the ICC with count data can be found in Carrasco (2010) .' + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iccCounts + url_git: '' +iccde: + version: 0.3.6 + title: Computation of the Double-Entry Intraclass Correlation + maintainer: Christian Blötner + description: The functions compute the double-entry intraclass correlation, which + is an index of profile similarity (Furr, 2010; McCrae, 2008). The double-entry + intraclass correlation is a more precise index of the agreement of two empirically + observed profiles than the often-used intraclass correlation (McCrae, 2008). Profiles + comprising correlations are automatically transformed according to the Fisher + z-transformation before the double-entry intraclass correlation is calculated. + If the profiles comprise scores such as sum scores from various personality scales, + it is recommended to standardize each individual score prior to computation of + the double-entry intraclass correlation (McCrae, 2008). See Furr (2010) + or McCrae (2008) for details. + date_publication: '2024-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iccde + url_git: '' +ICcforest: + version: 0.5.1 + title: An Ensemble Method for Interval-Censored Survival Data + maintainer: Weichi Yao + description: |- + Implements the conditional inference forest approach + to modeling interval-censored survival data. It also provides + functions to tune the parameters and evaluate the model fit. See + Yao et al. (2019) . + date_publication: '2020-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICcforest + url_git: '' +iccmult: + version: 1.0.1 + title: |- + Intracluster Correlation Coefficient (ICC) in Clustered + Categorical Data + maintainer: Nicole Solomon + description: Assists in generating categorical clustered outcome data, estimating + the Intracluster Correlation Coefficient (ICC) for nominal or ordinal data with + 2+ categories under the resampling and method of moments (MoM) methods, with confidence + intervals. + date_publication: '2024-11-02' + bug_reports: https://github.com/ncs14/iccmult/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iccmult + url_git: https://github.com/ncs14/iccmult +iccTraj: + version: 1.0.4 + title: |- + Estimates the Intraclass Correlation Coefficient for Trajectory + Data + maintainer: Josep L. Carrasco + description: Estimates the intraclass correlation coefficient for trajectory data + using a matrix of distances between trajectories. The distances implemented are + the extended Hausdorff distances (Min et al. 2007) + and the discrete Fréchet distance (Magdy et al. 2015) . + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iccTraj + url_git: '' +icd.data: + version: '1.0' + title: International Classifcation of Diseases (ICD) Data + maintainer: Jack O. Wasey + description: |- + Data from the United States Center for Medicare and Medicaid + Services (CMS) is included in this package. There are ICD-9 and ICD-10 + diagnostic and procedure codes, and lists of the chapter and sub-chapter + headings and the ranges of ICD codes they encompass. There are also two + sample datasets. These data are used by the 'icd' package for finding + comorbidities. + date_publication: '2018-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icd.data + url_git: '' +ICD10gm: + version: 1.2.5 + title: |- + Metadata Processing for the German Modification of the ICD-10 + Coding System + maintainer: Ewan Donnachie + description: Provides convenient access to the German modification of the International + Classification of Diagnoses, 10th revision (ICD-10-GM). It provides functionality + to aid in the identification, specification and historisation of ICD-10 codes. + Its intended use is the analysis of routinely collected data in the context of + epidemiology, medical research and health services research. The underlying metadata + are released by the German Institute for Medical Documentation and Information + , and are redistributed in accordance with their license. + date_publication: '2023-02-26' + bug_reports: https://github.com/edonnachie/ICD10gm/issues/ + url: https://edonnachie.github.io/ICD10gm/ + url_cran: https://CRAN.R-project.org/package=ICD10gm + url_git: '' +icdcomorbid: + version: 1.0.0 + title: Mapping ICD Codes to Comorbidity + maintainer: April Nguyen + description: |- + Provides tools for mapping International Classification of Diseases codes to comorbidity, + enabling the identification and analysis of various medical conditions within healthcare data. + date_publication: '2024-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icdcomorbid + url_git: '' +icdGLM: + version: 1.0.0 + title: |- + EM by the Method of Weights for Incomplete Categorical Data in + Generlized Linear Models + maintainer: Stephan Dlugosz + description: |- + Provides an estimator for generalized linear models with incomplete + data for discrete covariates. The estimation is based on the EM algorithm by the + method of weights by Ibrahim (1990) . + date_publication: '2016-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icdGLM + url_git: '' +icdpicr: + version: 1.0.1 + title: '''ICD'' Programs for Injury Categorization in R' + maintainer: Adam Black + description: |- + Categorization and scoring of injury severity typically involves + trained personnel with access to injured persons or their medical records. 'icdpicr' contains a function + that provides automated calculation of Abbreviated Injury Scale ('AIS') and Injury Severity Score ('ISS') + from International Classification of Diseases ('ICD') codes and may be a useful substitute to manual injury + severity scoring. 'ICDPIC' was originally developed in 'Stata', and 'icdpicr' is an open-access update + that accepts both 'ICD-9' and 'ICD-10' codes. + date_publication: '2022-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icdpicr + url_git: '' +ICDS: + version: 0.1.3 + title: |- + Identification of Cancer Dysfunctional Subpathway with Omics + Data + maintainer: Junwei Han + description: 'Identify Cancer Dysfunctional Sub-pathway by integrating gene expression, + DNA methylation and copy number variation, and pathway topological information. + 1)We firstly calculate the gene risk scores by integrating three kinds of data: + DNA methylation, copy number variation, and gene expression. 2)Secondly, we perform + a greedy search algorithm to identify the key dysfunctional sub-pathways within + the pathways for which the discriminative scores were locally maximal. 3)Finally, + the permutation test was used to calculate statistical significance level for + these key dysfunctional sub-pathways.' + date_publication: '2024-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICDS + url_git: '' +ICEbox: + version: 1.1.5 + title: Individual Conditional Expectation Plot Toolbox + maintainer: Adam Kapelner + description: Implements Individual Conditional Expectation (ICE) plots, a tool for + visualizing the model estimated by any supervised learning algorithm. ICE plots + refine Friedman's partial dependence plot by graphing the functional relationship + between the predicted response and a covariate of interest for individual observations. + Specifically, ICE plots highlight the variation in the fitted values across the + range of a covariate of interest, suggesting where and to what extent they may + exist. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICEbox + url_git: '' +icecream: + version: 0.2.2 + title: Print Debugging Made Sweeter + maintainer: Lewin Appleton-Fox + description: |- + Provides user-friendly and configurable print debugging via a + single function, ic(). Wrap an expression in ic() to print the + expression, its value and (where available) its source location. + Debugging output can be toggled globally without modifying code. + date_publication: '2024-02-18' + bug_reports: https://github.com/lewinfox/icecream/issues + url: https://www.lewinfox.com/icecream/ + url_cran: https://CRAN.R-project.org/package=icecream + url_git: https://github.com/lewinfox/icecream +ICED: + version: 0.0.1 + title: IntraClass Effect Decomposition + maintainer: Sam Parsons + description: |- + Estimate test-retest reliability for complex sampling strategies + and extract variances using IntraClass Effect Decomposition. Developed by + Brandmaier et al. (2018) "Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED)" + Also includes functions to simulate data based on sampling strategy. + Unofficial version release name: "Good work squirrels". + date_publication: '2022-08-18' + bug_reports: https://github.com/sdparsons/ICED + url: '' + url_cran: https://CRAN.R-project.org/package=ICED + url_git: https://github.com/sdparsons/ICED +ICEinfer: + version: '1.3' + title: |- + Incremental Cost-Effectiveness Inference using Two Unbiased + Samples + maintainer: Bob Obenchain + description: |- + Given two unbiased samples of patient level data on cost and effectiveness + for a pair of treatments, make head-to-head treatment comparisons by (i) generating the + bivariate bootstrap resampling distribution of ICE uncertainty for a specified value of + the shadow price of health, lambda, (ii) form the wedge-shaped ICE confidence region with + specified confidence fraction within [0.50, 0.99] that is equivariant with respect to + changes in lambda, (iii) color the bootstrap outcomes within the above confidence wedge + with economic preferences from an ICE map with specified values of lambda, beta and gamma + parameters, (iv) display VAGR and ALICE acceptability curves, and (v) illustrate variation + in ICE preferences by displaying potentially non-linear indifference(iso-preference) curves + from an ICE map with specified values of lambda, beta and either gamma or eta parameters. + date_publication: '2020-10-12' + bug_reports: '' + url: http://localcontrolstatistics.org + url_cran: https://CRAN.R-project.org/package=ICEinfer + url_git: '' +iCellR: + version: 1.6.7 + title: Analyzing High-Throughput Single Cell Sequencing Data + maintainer: Alireza Khodadadi-Jamayran + description: A toolkit that allows scientists to work with data from single cell + sequencing technologies such as scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and + Spatial Transcriptomics (ST). Single (i) Cell R package ('iCellR') provides unprecedented + flexibility at every step of the analysis pipeline, including normalization, clustering, + dimensionality reduction, imputation, visualization, and so on. Users can design + both unsupervised and supervised models to best suit their research. In addition, + the toolkit provides 2D and 3D interactive visualizations, differential expression + analysis, filters based on cells, genes and clusters, data merging, normalizing + for dropouts, data imputation methods, correcting for batch differences, pathway + analysis, tools to find marker genes for clusters and conditions, predict cell + types and pseudotime analysis. See Khodadadi-Jamayran, et al (2020) and + Khodadadi-Jamayran, et al (2020) for more details. + date_publication: '2024-01-29' + bug_reports: https://github.com/rezakj/iCellR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iCellR + url_git: https://github.com/rezakj/iCellR +icenReg: + version: 2.0.16 + title: Regression Models for Interval Censored Data + maintainer: Clifford Anderson-Bergman + description: |- + Regression models for interval censored data. Currently supports + Cox-PH, proportional odds, and accelerated failure time models. Allows for + semi and fully parametric models (parametric only for accelerated failure + time models) and Bayesian parametric models. Includes functions for easy visual + diagnostics of model fits and imputation of censored data. + date_publication: '2024-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icenReg + url_git: '' +icensBKL: + version: '1.5' + title: |- + Accompanion to the Book on Interval Censoring by Bogaerts, + Komarek, and Lesaffre + maintainer: Arnošt Komárek + description: 'Contains datasets and several smaller functions suitable for analysis + of interval-censored data. The package complements the book Bogaerts, Komárek + and Lesaffre (2017, ISBN: 978-1-4200-7747-6) "Survival Analysis with Interval-Censored + Data: A Practical Approach" . + Full R code related to the examples presented in the book can be found at . + Packages mentioned in the "Suggests" section are used in those examples.' + date_publication: '2023-12-20' + bug_reports: '' + url: https://ibiostat.be/online-resources/icbook/supplemental/ + url_cran: https://CRAN.R-project.org/package=icensBKL + url_git: '' +icensmis: + version: 1.5.0 + title: |- + Study Design and Data Analysis in the Presence of Error-Prone + Diagnostic Tests and Self-Reported Outcomes + maintainer: Xiangdong Gu + description: |- + We consider studies in which information from error-prone + diagnostic tests or self-reports are gathered sequentially to determine the + occurrence of a silent event. Using a likelihood-based approach + incorporating the proportional hazards assumption, we provide functions to + estimate the survival distribution and covariate effects. We also provide + functions for power and sample size calculations for this setting. + Please refer to Xiangdong Gu, Yunsheng Ma, and Raji Balasubramanian (2015) + , Xiangdong Gu and Raji Balasubramanian (2016) + , Xiangdong Gu, Mahlet G Tadesse, Andrea S Foulkes, + Yunsheng Ma, and Raji Balasubramanian (2020) . + date_publication: '2021-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icensmis + url_git: '' +icertool: + version: 0.0.3 + title: Calculate and Plot ICER + maintainer: Daniel Perez-Troncoso + description: |- + The app will calculate the ICER (incremental cost-effectiveness + ratio) Rawlins (2012) from the mean + costs and quality-adjusted life years (QALY) Torrance and Feeny (2009) + for a set of treatment options, and draw the efficiency frontier + in the costs-effectiveness plane. The app automatically identifies + and excludes dominated and extended-dominated options from the ICER + calculation. + date_publication: '2022-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icertool + url_git: '' +icesAdvice: + version: 2.1.1 + title: Functions Related to ICES Advice + maintainer: Colin Millar + description: |- + A collection of functions that facilitate computational steps + related to advice for fisheries management, according to ICES guidelines. + These include methods for calculating reference points and model diagnostics. + date_publication: '2022-02-18' + bug_reports: https://github.com/ices-tools-prod/icesAdvice/issues + url: https://ices.dk/advice + url_cran: https://CRAN.R-project.org/package=icesAdvice + url_git: https://github.com/ices-tools-prod/icesAdvice +IceSat2R: + version: 1.0.7 + title: ICESat-2 Altimeter Data using R + maintainer: Lampros Mouselimis + description: Programmatic connection to the 'OpenAltimetry API' + to download and process 'ATL03' (Global Geolocated Photon Data), 'ATL06' (Land + Ice Height), 'ATL07' (Sea Ice Height), 'ATL08' (Land and Vegetation Height), 'ATL10' + (Sea Ice Freeboard), 'ATL12' (Ocean Surface Height) and 'ATL13' (Inland Water + Surface Height) 'ICESat-2' Altimeter Data. The user has the option to download + the data by selecting a bounding box from a 1- or 5-degree grid globally utilizing + a shiny application. The 'ICESat-2' mission collects altimetry data of the Earth's + surface. The sole instrument on 'ICESat-2' is the Advanced Topographic Laser Altimeter + System (ATLAS) instrument that measures ice sheet elevation change and sea ice + thickness, while also generating an estimate of global vegetation biomass. 'ICESat-2' + continues the important observations of ice-sheet elevation change, sea-ice freeboard, + and vegetation canopy height begun by 'ICESat' in 2003. + date_publication: '2025-02-15' + bug_reports: https://github.com/mlampros/IceSat2R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IceSat2R + url_git: https://github.com/mlampros/IceSat2R +icesConnect: + version: 1.0.0 + title: Provides User Tokens for Access to ICES Web Services + maintainer: Colin Millar + description: |- + Provides user tokens for ICES web services that require + authentication and authorization. Web services covered by this + package are ICES VMS database, the ICES DATSU web services, and the + ICES SharePoint site. + date_publication: '2022-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icesConnect + url_git: '' +icesDatras: + version: 1.4.1 + title: DATRAS Trawl Survey Database Web Services + maintainer: Colin Millar + description: |- + R interface to access the web services of the ICES (International + Council for the Exploration of the Sea) DATRAS trawl survey + database . + date_publication: '2023-05-08' + bug_reports: https://github.com/ices-tools-prod/icesDatras/issues + url: https://datras.ices.dk/WebServices/Webservices.aspx + url_cran: https://CRAN.R-project.org/package=icesDatras + url_git: https://github.com/ices-tools-prod/icesDatras +icesDatsu: + version: 1.2.0 + title: |- + Functions to Interact with the ICES Data Submission Utility + (DATSU) + maintainer: Colin Millar + description: |- + Functions to Interact with the ICES Data Submission Utility (DATSU) + . + date_publication: '2024-10-24' + bug_reports: https://github.com/ices-tools-prod/icesDatsu/issues + url: https://datsu.ices.dk/web/index.aspx + url_cran: https://CRAN.R-project.org/package=icesDatsu + url_git: https://github.com/ices-tools-prod/icesDatsu +icesDatsuQC: + version: 1.2.0 + title: Run Quality Checks on Data Prior to Submission to ICES + maintainer: Colin Millar + description: |- + Run quality checks on data sets using the same checks that are conducted + on the ICES Data Submission Utility (DATSU) . + date_publication: '2024-10-25' + bug_reports: https://github.com/ices-tools-prod/icesDatsuQC/issues + url: https://datsu.ices.dk + url_cran: https://CRAN.R-project.org/package=icesDatsuQC + url_git: https://github.com/ices-tools-prod/icesDatsuQC +icesSAG: + version: 1.5.0 + title: Stock Assessment Graphs Database Web Services + maintainer: Colin Millar + description: |- + R interface to access the web services of the ICES Stock Assessment + Graphs database . + date_publication: '2024-10-24' + bug_reports: https://github.com/ices-tools-prod/icesSAG/issues + url: https://sg.ices.dk + url_cran: https://CRAN.R-project.org/package=icesSAG + url_git: https://github.com/ices-tools-prod/icesSAG +icesSD: + version: 2.1.0 + title: Stock Database Web Services + maintainer: Colin Millar + description: R interface to access the web services of the ICES Stock Database . + date_publication: '2024-10-24' + bug_reports: https://github.com/ices-tools-prod/icesSD/issues + url: https://sd.ices.dk + url_cran: https://CRAN.R-project.org/package=icesSD + url_git: https://github.com/ices-tools-prod/icesSD +icesTAF: + version: 4.2.0 + title: Functions to Support the ICES Transparent Assessment Framework + maintainer: Colin Millar + description: |- + Functions to support the ICES Transparent Assessment Framework + to organize data, methods, and results used in ICES + assessments. ICES is an organization facilitating international collaboration + in marine science. + date_publication: '2023-03-21' + bug_reports: '' + url: https://taf.ices.dk + url_cran: https://CRAN.R-project.org/package=icesTAF + url_git: https://github.com/ices-tools-prod/icesTAF +icesVocab: + version: 1.2.0 + title: ICES Vocabularies Database Web Services + maintainer: Colin Millar + description: |- + R interface to access the RECO POX web services of the ICES + (International Council for the Exploration of the Sea) Vocabularies database + . + date_publication: '2022-02-10' + bug_reports: https://github.com/ices-tools-prod/icesVocab/issues + url: https://vocab.ices.dk/services/POX.aspx + url_cran: https://CRAN.R-project.org/package=icesVocab + url_git: '' +ICGE: + version: 0.4.2 + title: |- + Estimation of Number of Clusters and Identification of Atypical + Units + maintainer: Itziar Irigoien + description: It is a package that helps to estimate the number of real clusters + in data as well as to identify atypical units. The underlying methods are based + on distances rather than on unit x variables. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICGE + url_git: '' +ICglm: + version: 0.1.0 + title: Information Criteria for Generalized Linear Regression + maintainer: Fatih Saglam + description: Calculate various information criteria in literature for "lm" and "glm" + objects. + date_publication: '2021-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICglm + url_git: '' +ICGOR: + version: '2.0' + title: |- + Fit Generalized Odds Rate Hazards Model with Interval Censored + Data + maintainer: Jie Zhou + description: Generalized Odds Rate Hazards (GORH) model is a flexible model of fitting + survival data, including the Proportional Hazards (PH) model and the Proportional + Odds (PO) Model as special cases. This package fit the GORH model with interval + censored data. + date_publication: '2017-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICGOR + url_git: '' +ichimoku: + version: 1.5.5 + title: Visualization and Tools for Ichimoku Kinko Hyo Strategies + maintainer: Charlie Gao + description: |- + An implementation of 'Ichimoku Kinko Hyo', also commonly known as + 'cloud charts'. Static and interactive visualizations with tools for + creating, backtesting and development of quantitative 'ichimoku' strategies. + As described in Sasaki (1996, ISBN:4925152009), the technique is a refinement + on candlestick charting, originating from Japan and now in widespread use in + technical analysis worldwide. Translating as 'one-glance equilibrium chart', + it allows the price action and market structure of financial securities to + be determined 'at-a-glance'. Incorporates an interface with the OANDA + fxTrade API for retrieving historical and + live streaming price data for major currencies, metals, commodities, + government bonds and stock indices. + date_publication: '2024-09-12' + bug_reports: https://github.com/shikokuchuo/ichimoku/issues + url: https://shikokuchuo.net/ichimoku/ + url_cran: https://CRAN.R-project.org/package=ichimoku + url_git: https://github.com/shikokuchuo/ichimoku/ +iClick: + version: '1.5' + title: A Button-Based GUI for Financial and Economic Data Analysis + maintainer: Ho Tsung-wu + description: |- + A GUI designed to support the analysis of financial-economic time + series data. + date_publication: '2018-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iClick + url_git: '' +iclogcondist: + version: 1.0.1 + title: Log-Concave Distribution Estimation with Interval-Censored Data + maintainer: Chaoyu Yuan + description: We consider the non-parametric maximum likelihood estimation of the + underlying distribution function, assuming log-concavity, based on mixed-case + interval-censored data. The algorithm implemented is base on Chi Wing Chu, Hok + Kan Ling and Chaoyu Yuan (2024, ). + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iclogcondist + url_git: '' +iClusterVB: + version: 0.1.4 + title: |- + Fast Integrative Clustering and Feature Selection for High + Dimensional Data + maintainer: Abdalkarim Alnajjar + description: |- + A variational Bayesian approach for fast integrative + clustering and feature selection, facilitating the analysis of + multi-view, mixed type, high-dimensional datasets with applications in + fields like cancer research, genomics, and more. + date_publication: '2024-12-09' + bug_reports: https://github.com/AbdalkarimA/iClusterVB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iClusterVB + url_git: https://github.com/AbdalkarimA/iClusterVB +icmm: + version: '1.2' + title: Empirical Bayes Variable Selection via ICM/M Algorithm + maintainer: Vitara Pungpapong + description: Empirical Bayes variable selection via ICM/M algorithm for normal, + binary logistic, and Cox's regression. The basic problem is to fit high-dimensional + regression which sparse coefficients. This package allows incorporating the Ising + prior to capture structure of predictors in the modeling process. More information + can be found in the papers listed in the URL below. + date_publication: '2021-05-26' + bug_reports: '' + url: https://www.researchgate.net/publication/279279744_Selecting_massive_variables_using_an_iterated_conditional_modesmedians_algorithm + url_cran: https://CRAN.R-project.org/package=icmm + url_git: '' +icmstate: + version: 0.1.1 + title: Interval Censored Multi-State Models + maintainer: Daniel Gomon + description: |- + Allows for the non-parametric estimation of transition intensities in interval-censored + multi-state models using the approach of Gomon and Putter (2024) or + Gu et al. (2023) . + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icmstate + url_git: '' +ICODS: + version: '1.1' + title: |- + Data Analysis for ODS and Case-Cohort Designs with + Interval-Censoring + maintainer: Shannon T. Holloway + description: |- + Sieve semiparametric likelihood methods for analyzing + interval-censored failure time data from an outcome-dependent sampling (ODS) + design and from a case-cohort design. + Zhou, Q., Cai, J., and Zhou, H. (2018) ; + Zhou, Q., Zhou, H., and Cai, J. (2017) . + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICODS + url_git: '' +ICompELM: + version: 0.1.0 + title: Independent Component Analysis Based Extreme Learning Machine + maintainer: Saikath Das + description: Single Layer Feed-forward Neural networks (SLFNs) have many applications + in various fields of statistical modelling, especially for time-series forecasting. + However, there are some major disadvantages of training such networks via the + widely accepted 'gradient-based backpropagation' algorithm, such as convergence + to local minima, dependencies on learning rate and large training time. These + concerns were addressed by Huang et al. (2006) , + wherein they introduced the Extreme Learning Machine (ELM), an extremely fast + learning algorithm for SLFNs which randomly chooses the weights connecting input + and hidden nodes and analytically determines the output weights of SLFNs. It shows + good generalized performance, but is still subject to a high degree of randomness. + To mitigate this issue, this package uses a dimensionality reduction technique + given in Hyvarinen (1999) , namely, the Independent Component + Analysis (ICA) to determine the input-hidden connections and thus, remove any + sort of randomness from the algorithm. This leads to a robust, fast and stable + ELM model. Using functions within this package, the proposed model can also be + compared with an existing alternative based on the Principal Component Analysis + (PCA) algorithm given by Pearson (1901) , i.e., + the PCA based ELM model given by Castano et al. (2013) , + from which the implemented ICA based algorithm is greatly inspired. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICompELM + url_git: '' +icosa: + version: 0.11.1 + title: |- + Global Triangular and Penta-Hexagonal Grids Based on Tessellated + Icosahedra + maintainer: Adam T. Kocsis + description: Implementation of icosahedral grids in three dimensions. The spherical-triangular + tessellation can be set to create grids with custom resolutions. Both the primary + triangular and their inverted penta-hexagonal grids can be calculated. Additional + functions are provided that allow plotting of the grids and associated data, the + interaction of the grids with other raster and vector objects, and treating the + grids as a graphs. + date_publication: '2024-08-16' + bug_reports: https://github.com/icosa-grid/R-icosa/issues + url: https://icosa-grid.github.io/R-icosa/ + url_cran: https://CRAN.R-project.org/package=icosa + url_git: '' +icpack: + version: 0.1.0 + title: Survival Analysis of Interval-Censored Data + maintainer: Hein Putter + description: Survival analysis of interval-censored data with proportional hazards, + and an explicit smooth estimate of the baseline log-hazard with P-splines. + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icpack + url_git: '' +icpsrdata: + version: 0.6.1 + title: Reproducible Data Retrieval from the ICPSR Archive + maintainer: Frederick Solt + description: |- + Reproducible, programmatic retrieval of datasets from the + Inter-university Consortium for Political and Social Research archive. + date_publication: '2023-07-04' + bug_reports: https://github.com/fsolt/icpsrdata/issues + url: https://fsolt.org/icpsrdata/ + url_cran: https://CRAN.R-project.org/package=icpsrdata + url_git: https://github.com/fsolt/icpsrdata +icr: + version: 0.6.6 + title: Compute Krippendorff's Alpha + maintainer: Alexander Staudt + description: |- + Provides functions to compute and plot Krippendorff's inter-coder + reliability coefficient alpha and bootstrapped uncertainty estimates + (Krippendorff 2004, ISBN:0761915443). The bootstrap routines are set up to + make use of parallel threads where supported. + date_publication: '2024-10-31' + bug_reports: https://github.com/staudtlex/icr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=icr + url_git: https://github.com/staudtlex/icr +ICRanks: + version: '3.1' + title: Simultaneous Confidence Intervals for Ranks + maintainer: Diaa Al Mohamad + description: Algorithms to construct simultaneous confidence intervals for the ranks + of means mu_1,...,mu_n based on an independent Gaussian sample using multiple + testing techniques. + date_publication: '2019-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICRanks + url_git: '' +icRSF: + version: '1.2' + title: A Modified Random Survival Forest Algorithm + maintainer: Hui Xu + description: Implements a modification to the Random Survival Forests algorithm + for obtaining variable importance in high dimensional datasets. The proposed algorithm + is appropriate for settings in which a silent event is observed through sequentially + administered, error-prone self-reports or laboratory based diagnostic tests. The + modified algorithm incorporates a formal likelihood framework that accommodates + sequentially administered, error-prone self-reports or laboratory based diagnostic + tests. The original Random Survival Forests algorithm is modified by the introduction + of a new splitting criterion based on a likelihood ratio test statistic. + date_publication: '2018-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=icRSF + url_git: '' +ICS: + version: 1.4-1 + title: Tools for Exploring Multivariate Data via ICS/ICA + maintainer: Klaus Nordhausen + description: |- + Implementation of Tyler, Critchley, Duembgen and Oja's (JRSS B, 2009, + ) and Oja, Sirkia and Eriksson's + (AJS, 2006, ) method of two different + scatter matrices to obtain an invariant coordinate system or independent + components, depending on the underlying assumptions. + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICS + url_git: '' +ICSClust: + version: 0.1.0 + title: Tandem Clustering with Invariant Coordinate Selection + maintainer: Aurore Archimbaud + description: |- + Implementation of tandem clustering with invariant coordinate + selection with different scatter matrices and several choices for the + selection of components as described in Alfons, A., Archimbaud, A., Nordhausen, K.and Ruiz-Gazen, A. (2022) . + date_publication: '2023-09-21' + bug_reports: https://github.com/AuroreAA/ICSClust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ICSClust + url_git: https://github.com/AuroreAA/ICSClust +ICSKAT: + version: 0.2.0 + title: Interval-Censored Sequence Kernel Association Test + maintainer: Ryan Sun + description: Implements the Interval-Censored Sequence Kernel Association (ICSKAT) + test for testing the association between interval-censored time-to-event outcomes + and groups of single nucleotide polymorphisms (SNPs). Interval-censored time-to-event + data occur when the event time is not known exactly but can be deduced to fall + within a given interval. For example, some medical conditions like bone mineral + density deficiency are generally only diagnosed at clinical visits. If a patient + goes for clinical checkups yearly and is diagnosed at, say, age 30, then the onset + of the deficiency is only known to fall between the date of their age 29 checkup + and the date of the age 30 checkup. Interval-censored data include right- and + left-censored data as special cases. This package also implements the interval-censored + Burden test and the ICSKATO test, which is the optimal combination of the ICSKAT + and Burden tests. Please see the vignette for a quickstart guide. + date_publication: '2021-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICSKAT + url_git: '' +ICSNP: + version: 1.1-2 + title: Tools for Multivariate Nonparametrics + maintainer: Klaus Nordhausen + description: Tools for multivariate nonparametrics, as location tests based on marginal + ranks, spatial median and spatial signs computation, Hotelling's T-test, estimates + of shape are implemented. + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICSNP + url_git: '' +ICSOutlier: + version: 0.4-0 + title: Outlier Detection Using Invariant Coordinate Selection + maintainer: Klaus Nordhausen + description: Multivariate outlier detection is performed using invariant coordinates + where the package offers different methods to choose the appropriate components. + ICS is a general multivariate technique with many applications in multivariate + analysis. ICSOutlier offers a selection of functions for automated detection of + outliers in the data based on a fitted ICS object or by specifying the dataset + and the scatters of interest. The current implementation targets data sets with + only a small percentage of outliers. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICSOutlier + url_git: '' +ICSS: + version: '1.1' + title: ICSS Algorithm by Inclan/Tiao (1994) + maintainer: Siegfried Köstlmeier + description: The Iterative Cumulative Sum of Squares (ICSS) algorithm by Inclan/Tiao + (1994) detects multiple change points, + i.e. structural break points, in the variance of a sequence of independent observations. + For series of moderate size (i.e. 200 observations and beyond), the ICSS algorithm + offers results comparable to those obtained by a Bayesian approach or by likelihood + ration tests, without the heavy computational burden required by these approaches. + date_publication: '2021-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICSS + url_git: '' +ICSShiny: + version: '0.5' + title: ICS via a Shiny Application + maintainer: Klaus Nordhausen + description: Performs Invariant Coordinate Selection (ICS) (Tyler, Critchley, Duembgen + and Oja (2009) ) and especially ICS for + multivariate outlier detection with application to quality control (Archimbaud, + Nordhausen, Ruiz-Gazen (2016) ) using a shiny app. + date_publication: '2018-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICSShiny + url_git: '' +ICSsmoothing: + version: 1.2.8 + title: Data Smoothing by Interpolating Cubic Splines + maintainer: Lubomir Antoni + description: We construct the explicit form of clamped cubic interpolating spline + (both uniform - knots are equidistant and non-uniform - knots are arbitrary). + Using this form, we propose a linear regression model suitable for real data smoothing. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICSsmoothing + url_git: '' +ICsurv: + version: 1.0.1 + title: Semiparametric Regression Analysis of Interval-Censored Data + maintainer: Lianming Wang + description: Currently using the proportional hazards (PH) model. More methods under + other semiparametric regression models will be included in later versions. + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICsurv + url_git: '' +ICtest: + version: 0.3-5 + title: |- + Estimating and Testing the Number of Interesting Components in + Linear Dimension Reduction + maintainer: Klaus Nordhausen + description: For different linear dimension reduction methods like principal components + analysis (PCA), independent components analysis (ICA) and supervised linear dimension + reduction tests and estimates for the number of interesting components (ICs) are + provided. + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICtest + url_git: '' +ICV: + version: '1.0' + title: Indirect Cross-Validation (ICV) for Kernel Density Estimation + maintainer: Olga Savchuk + description: Functions for computing the global and local Gaussian density estimates + based on the ICV bandwidth. See the article of Savchuk, O.Y., Hart, J.D., Sheather, + S.J. (2010). Indirect cross-validation for density estimation. Journal of the + American Statistical Association, 105(489), 415-423 . + date_publication: '2017-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ICV + url_git: '' +ICvectorfields: + version: 0.1.2 + title: Vector Fields from Spatial Time Series of Population Abundance + maintainer: Devin Goodsman + description: |- + Functions for converting time series of spatial abundance or density + data in raster format to vector fields of population movement using the digital + image correlation technique. More specifically, the functions in the package + compute cross-covariance using discrete fast Fourier transforms for computational + efficiency. Vectors in vector fields point in the direction of highest two + dimensional cross-covariance. The package has a novel implementation of the + digital image correlation algorithm that is designed to detect persistent + directional movement when image time series extend beyond a sequence of + two raster images. + date_publication: '2022-02-26' + bug_reports: https://github.com/goodsman/ICvectorfields/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ICvectorfields + url_git: '' +idar: + version: '1.5' + title: Individual Diversity-Area Relationships + maintainer: Marcelino de la Cruz + description: Computes and tests individual (species, phylogenetic and functional) + diversity-area relationships, i.e., how species-, phylogenetic- and functional-diversity + varies with spatial scale around the individuals of some species in a community. + See applications of these methods in Wiegand et al. (2007) + or Chacon-Labella et al. (2016) . + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idar + url_git: '' +idarps: + version: 0.0.4 + title: |- + Datasets and Functions for the Class "Modelling and Data + Analysis for Pharmaceutical Sciences" + maintainer: Lionel Voirol + description: |- + Provides datasets and functions for the class "Modelling and Data Analysis for Pharmaceutical Sciences". + The datasets can be used to present various methods of data analysis and statistical modeling. + Functions for data visualization are also implemented. + date_publication: '2024-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idarps + url_git: '' +idbr: + version: '1.2' + title: R Interface to the US Census Bureau International Data Base API + maintainer: Kyle Walker + description: |- + Use R to make requests to the US Census Bureau's International Data Base API. + Results are returned as R data frames. For more information about the IDB API, visit + . + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idbr + url_git: '' +IDCard: + version: 0.3.0 + title: Update Chinese ID Card Number to Eighteen Digits + maintainer: Zhicheng Du + description: The digits of the old version (before 2000 year) of 'Chinese ID Card + Number' is 15, this package aims to update to the current version of 18 digits. + Besides, this package can help check whether the given 'ID' is right or not. + date_publication: '2017-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDCard + url_git: '' +idcnrba: + version: 1.1.0 + title: |- + Interactive Application for Analyzing Representativeness and + Nonresponse Bias + maintainer: Ben Schneider + description: |- + Provides access to the + Idea Data Center (IDC) application for conducting + nonresponse bias analysis (NRBA). The IDC NRBA app is an + interactive, browser-based Shiny application that can be used to + analyze survey data with respect to response rates, + representativeness, and nonresponse bias. This app provides a user-friendly + interface to statistical methods implemented by the 'nrba' package. + Krenzke, Van de Kerckhove, and Mohadjer (2005) + + and Lohr and Riddles (2016) + + provide an overview of the statistical methods implemented in the application. + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idcnrba + url_git: '' +IDE: + version: 0.3.1 + title: Integro-Difference Equation Spatio-Temporal Models + maintainer: Andrew Zammit-Mangion + description: |- + The Integro-Difference Equation model is a linear, dynamical model used to model + phenomena that evolve in space and in time; see, for example, Cressie and Wikle (2011, + ISBN:978-0-471-69274-4) or Dewar et al. (2009) . At the + heart of the model is the kernel, which dictates how the process evolves from one time + point to the next. Both process and parameter reduction are used to facilitate computation, + and spatially-varying kernels are allowed. Data used to estimate the parameters are assumed + to be readings of the process corrupted by Gaussian measurement error. Parameters are fitted + by maximum likelihood, and estimation is carried out using an evolution algorithm. + date_publication: '2022-05-30' + bug_reports: https://github.com/andrewzm/IDE/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=IDE + url_git: '' +IDEAFilter: + version: 0.2.0 + title: Agnostic, Idiomatic Data Filter Module for Shiny + maintainer: Aaron Clark + description: |- + When added to an existing shiny app, users may subset any + developer-chosen R data.frame on the fly. That is, users are empowered to + slice & dice data by applying multiple (order specific) filters using the + AND (&) operator between each, and getting real-time updates on the number + of rows effected/available along the way. Thus, any downstream processes + that leverage this data source (like tables, plots, or statistical procedures) + will re-render after new filters are applied. The shiny module’s user interface has + a 'minimalist' aesthetic so that the focus can be on the data & + other visuals. In addition to returning a reactive (filtered) data.frame, + 'IDEAFilter' as also returns 'dplyr' filter statements used to actually slice + the data. + date_publication: '2024-04-15' + bug_reports: https://github.com/Biogen-Inc/IDEAFilter/issues + url: https://biogen-inc.github.io/IDEAFilter/ + url_cran: https://CRAN.R-project.org/package=IDEAFilter + url_git: https://github.com/Biogen-Inc/IDEAFilter +ideamdb: + version: 0.0.9 + title: Easy Manipulation of IDEAM's Climatological Data + maintainer: Luz Maria Morales + description: |- + Time series plain text conversion and data visualization. It allows + to transform IDEAM (Instituto de Hidrologia, Meteorologia y Estudios Ambientales) + daily series from plain text to CSV files or data frames in R. Additionally, + it is possible to obtain exploratory graphs from times series. IDEAM’s data + is freely delivered under formal request through the official web page + . + date_publication: '2019-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ideamdb + url_git: '' +ideanet: + version: 1.0.0 + title: Integrating Data Exchange and Analysis for Networks ('ideanet') + maintainer: Tom Wolff + description: A suite of convenient tools for social network analysis geared toward + students, entry-level users, and non-expert practitioners. ‘ideanet’ features + unique functions for the processing and measurement of sociocentric and egocentric + network data. These functions automatically generate node- and system-level measures + commonly used in the analysis of these types of networks. Outputs from these functions + maximize the ability of novice users to employ network measurements in further + analyses while making all users less prone to common data analytic errors. Additionally, + ‘ideanet’ features an R Shiny graphic user interface that allows novices to explore + network data with minimal need for coding. + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ideanet + url_git: '' +IDEATools: + version: 3.5.2 + title: |- + Individual and Group Farm Sustainability Assessments using the + IDEA4 Method + maintainer: David Carayon + description: Collection of tools to automate the processing of data collected though + the IDEA4 method (see Zahm et al. (2018) ). Starting + from the original data collecting files this packages provides functions to compute + IDEA indicators, draw modern and aesthetic plots, and produce a wide range of + reporting materials. + date_publication: '2023-12-15' + bug_reports: https://github.com/davidcarayon/IDEATools/issues + url: https://davidcarayon.github.io/IDEATools/index.html + url_cran: https://CRAN.R-project.org/package=IDEATools + url_git: https://github.com/davidcarayon/IDEATools +idefix: + version: 1.0.3 + title: Efficient Designs for Discrete Choice Experiments + maintainer: Frits Traets + description: Generates efficient designs for discrete choice experiments based on + the multinomial logit model, and individually adapted designs for the mixed multinomial + logit model. The generated designs can be presented on screen and choice data + can be gathered using a shiny application. Traets F, Sanchez G, and Vandebroek + M (2020) . + date_publication: '2022-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idefix + url_git: https://github.com/traets/idefix +idem: + version: '5.2' + title: |- + Inference in Randomized Controlled Trials with Death and + Missingness + maintainer: Chenguang Wang + description: |- + In randomized studies involving severely ill patients, functional + outcomes are often unobserved due to missed clinic visits, premature + withdrawal or death. It is well known that if these unobserved functional + outcomes are not handled properly, biased treatment comparisons can be + produced. In this package, we implement a procedure for comparing treatments + that is based on the composite endpoint of both the functional outcome and + survival. The procedure was proposed in Wang et al. (2016) + and Wang et al. (2020) . It considers missing data + imputation with different sensitivity + analysis strategies to handle the unobserved functional outcomes not due to + death. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idem + url_git: https://github.com/olssol/idem/ +idendr0: + version: 1.5.3 + title: Interactive Dendrograms + maintainer: Tomas Sieger + description: |- + Interactive dendrogram that enables the user to select and + color clusters, to zoom and pan the dendrogram, and to visualize + the clustered data not only in a built-in heat map, but also in + 'GGobi' interactive plots and user-supplied plots. + This is a backport of Qt-based 'idendro' + () to base R graphics and + Tcl/Tk GUI. + date_publication: '2017-02-22' + bug_reports: https://github.com/tsieger/idendr0/issues + url: '' + url_cran: https://CRAN.R-project.org/package=idendr0 + url_git: http://github.com/tsieger/idendr0 +ider: + version: 0.1.1 + title: Various Methods for Estimating Intrinsic Dimension + maintainer: Hideitsu Hino + description: |- + An implementation of various methods for estimating intrinsic + dimension of vector-valued dataset or distance matrix. Most methods implemented + are based on different notion of fractal dimension such as the capacity + dimension, the box-counting dimension, and the information dimension. + date_publication: '2023-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ider + url_git: '' +IDetect: + version: 0.1.0 + title: Isolate-Detect Methodology for Multiple Change-Point Detection + maintainer: Andreas Anastasiou + description: |- + Provides efficient implementation of the Isolate-Detect + methodology for the consistent estimation of the number and location of multiple + change-points in one-dimensional data sequences from the "deterministic + + noise" model. For details on the Isolate-Detect methodology, please see Anastasiou and + Fryzlewicz (2018) . + Currently implemented scenarios are: piecewise-constant signal with Gaussian + noise, piecewise-constant signal with heavy-tailed noise, continuous piecewise-linear + signal with Gaussian noise, continuous piecewise-linear signal with heavy-tailed noise. + date_publication: '2018-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDetect + url_git: '' +IDF: + version: 2.1.2 + title: Estimation and Plotting of IDF Curves + maintainer: Felix S. Fauer + description: |- + Intensity-duration-frequency (IDF) curves are a widely used analysis-tool + in hydrology to assess extreme values of precipitation + [e.g. Mailhot et al., 2007, ]. + The package 'IDF' provides functions to estimate IDF parameters for given + precipitation time series on the basis of a duration-dependent + generalized extreme value distribution + [Koutsoyiannis et al., 1998, ]. + date_publication: '2022-07-20' + bug_reports: '' + url: https://gitlab.met.fu-berlin.de/Rpackages/idf_package + url_cran: https://CRAN.R-project.org/package=IDF + url_git: '' +idiffomix: + version: 1.0.0 + title: |- + Integrated Differential Analysis of Multi Omics Data using a + Joint Mixture Model + maintainer: Koyel Majumdar + description: A joint mixture model has been developed by Majumdar et al. (2025) + that integrates information from gene expression + data and methylation data at the modelling stage to capture their inherent dependency + structure, enabling simultaneous identification of differentially methylated cytosine-guanine + dinucleotide (CpG) sites and differentially expressed genes. The model leverages + a joint likelihood function that accounts for the nested structure in the data, + with parameter estimation performed using an expectation-maximisation algorithm. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idiffomix + url_git: '' +iDINGO: + version: 1.0.4 + title: Integrative Differential Network Analysis in Genomics + maintainer: Caleb A. Class + description: Fits covariate dependent partial correlation matrices for integrative + models to identify differential networks between two groups. The methods are described + in Class et. al., (2018) and Ha et. al., (2015) + . + date_publication: '2020-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iDINGO + url_git: '' +idiogramFISH: + version: 2.0.13 + title: Shiny App. Idiograms with Marks and Karyotype Indices + maintainer: Fernando Roa + description: 'Plot idiograms of karyotypes, plasmids, circular chr. having a set + of data.frames for chromosome data and optionally mark data. Two styles of chromosomes + can be used: without or with visible chromatids. Supports micrometers, cM and + Mb or any unit. Three styles of centromeres are available: triangle, rounded and + inProtein; and six styles of marks are available: square (squareLeft), dots, cM + (cMLeft), cenStyle, upArrow (downArrow), exProtein (inProtein); its legend (label) + can be drawn inline or to the right of karyotypes. Idiograms can also be plotted + in concentric circles. It is possible to calculate chromosome indices by Levan + et al. (1964) , karyotype indices of Watanabe + et al. (1999) and Romero-Zarco (1986) + and classify chromosomes by morphology Guerra (1986) and Levan et al. (1964).' + date_publication: '2023-08-22' + bug_reports: https://gitlab.com/ferroao/idiogramFISH/-/issues + url: https://ferroao.gitlab.io/manualidiogramfish/ + url_cran: https://CRAN.R-project.org/package=idiogramFISH + url_git: '' +idiolect: + version: 1.0.1 + title: Forensic Authorship Analysis + maintainer: Andrea Nini + description: Carry out comparative authorship analysis of disputed and undisputed + texts within the Likelihood Ratio Framework for expressing evidence in forensic + science. This package contains implementations of well-known algorithms for comparative + authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta + or Koppel and Winter's (2014) Impostors Method , as well + as functions to measure their performance and to calibrate their outputs into + Log-Likelihood Ratios. + date_publication: '2024-08-28' + bug_reports: https://github.com/andreanini/idiolect/issues + url: https://andreanini.github.io/idiolect/ + url_cran: https://CRAN.R-project.org/package=idiolect + url_git: https://github.com/andreanini/idiolect +IDLFM: + version: 0.0.2 + title: Individual Dynamic Latent Factor Model + maintainer: Siyang Liu + description: A personalized dynamic latent factor model (Zhang et al. (2024) ) + for irregular multi-resolution time series data, to interpolate unsampled measurements + from low-resolution time series. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDLFM + url_git: '' +idm: + version: 1.8.3 + title: Incremental Decomposition Methods + maintainer: Angelos Markos + description: |- + Incremental Multiple Correspondence Analysis and Principal + Component Analysis. + date_publication: '2022-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idm + url_git: '' +idmact: + version: 1.0.1 + title: Interpreting Differences Between Mean ACT Scores + maintainer: Mackson Ncube + description: |- + Interpreting the differences between mean scale scores across various + forms of an assessment can be challenging. This difficulty arises from different + mappings between raw scores and scale scores, complex mathematical relationships, + adjustments based on judgmental procedures, and diverse equating functions applied + to different assessment forms. An alternative method involves running simulations + to explore the effect of incrementing raw scores on mean scale scores. The + 'idmact' package provides an implementation of this approach based on the + algorithm detailed in Schiel (1998) + which + was developed to help interpret differences between mean scale scores on the + American College Testing (ACT) assessment. The function idmact_subj() within + the package offers a framework for running simulations on subject-level scores. + In contrast, the idmact_comp() function provides a framework for conducting + simulations on composite scores. + date_publication: '2023-05-18' + bug_reports: https://github.com/mncube/idmact/issues + url: '' + url_cran: https://CRAN.R-project.org/package=idmact + url_git: https://github.com/mncube/idmact +idmc: + version: 0.3.1 + title: Load and Wrangle IDMC Displacement Data + maintainer: Seth Caldwell + description: |- + Utilities to work with data from the Internal Displacement + Monitoring Centre (IDMC) (), + with convenient functions for loading events data from the IDMC API + and transforming events data to daily displacement estimates. + date_publication: '2024-09-23' + bug_reports: https://github.com/ocha-dap/idmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=idmc + url_git: https://github.com/ocha-dap/idmc +IDmeasurer: + version: 1.0.0 + title: Assessment of Individual Identity in Animal Signals + maintainer: Pavel Linhart + description: 'Provides tools for assessment and quantification of individual identity + information in animal signals. This package accompanies a research article by + Linhart et al. (2019) : "Measuring individual identity information + in animal signals: Overview and performance of available identity metrics".' + date_publication: '2019-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDmeasurer + url_git: '' +IDmining: + version: 1.0.7 + title: Intrinsic Dimension for Data Mining + maintainer: Jean Golay + description: |- + Contains techniques for mining large and high-dimensional data + sets by using the concept of Intrinsic Dimension (ID). Here the ID is + not necessarily an integer. It is extended to fractal dimensions. And + the Morisita estimator is used for the ID estimation, but other + tools are included as well. + date_publication: '2021-05-03' + bug_reports: '' + url: https://www.sites.google.com/site/jeangolayresearch/ + url_cran: https://CRAN.R-project.org/package=IDmining + url_git: '' +IDMIR: + version: 0.1.0 + title: |- + Identification of Dysregulated MiRNAs Based on MiRNA-MiRNA + Interaction Network + maintainer: Junwei Han + description: A systematic biology tool was developed to identify dysregulated miRNAs + via a miRNA-miRNA interaction network. 'IDMIR' first constructed a weighted miRNA + interaction network through integrating miRNA-target interaction information, + molecular function data from Gene Ontology (GO) database and gene transcriptomic + data in specific-disease context, and then, it used a network propagation algorithm + on the network to identify significantly dysregulated miRNAs. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDMIR + url_git: '' +idopNetwork: + version: 0.1.2 + title: A Network Tool to Dissect Spatial Community Ecology + maintainer: Ang Dong + description: |- + Most existing approaches for network reconstruction can only infer an overall network + and, also, fail to capture a complete set of network properties. To address these issues, + a new model has been developed, which converts static data into their 'dynamic' form. + 'idopNetwork' is an 'R' interface to this model, it can inferring informative, dynamic, + omnidirectional and personalized networks. For more information on functional + clustering part, see Kim et al. (2008) , + Wang et al. (2011) . For more information on our model, + see Chen et al. (2019) , and Cao et al. (2022) + . + date_publication: '2023-04-18' + bug_reports: https://github.com/cxzdsa2332/idopNetwork/issues + url: '' + url_cran: https://CRAN.R-project.org/package=idopNetwork + url_git: https://github.com/cxzdsa2332/idopNetwork +iDOS: + version: 1.0.1 + title: Integrated Discovery of Oncogenic Signatures + maintainer: Syed Haider + description: |- + A method to integrate molecular profiles of cancer patients (gene copy number and mRNA abundance) to + identify candidate gain of function alterations. These candidate alterations can be subsequently further tested + to discover cancer driver alterations. Briefly, this method tests of genomic correlates of mRNA dysregulation and prioritise + those where DNA gains/amplifications are associated with elevated mRNA expression of the same gene. For details see, + Haider S et al. (2016) "Genomic alterations underlie a pan-cancer metabolic shift associated with tumour hypoxia", Genome Biology, . + date_publication: '2024-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iDOS + url_git: '' +iDOVE: + version: '1.5' + title: Durability of Vaccine Efficacy Against SARS-CoV-2 Infection + maintainer: Shannon T. Holloway + description: |- + Implements a nonparametric maximum likelihood method for assessing + potentially time-varying vaccine efficacy (VE) against SARS-CoV-2 infection + under staggered enrollment and time-varying community transmission, allowing + crossover of placebo volunteers to the vaccine arm. + Lin, D. Y., Gu, Y., Zeng, D., Janes, H. E., and Gilbert, P. B. (2021) + . + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iDOVE + url_git: '' +IDPmisc: + version: 1.1.21 + title: |- + 'Utilities of Institute of Data Analyses and Process Design + (www.zhaw.ch/idp)' + maintainer: Christoph Hofer + description: 'Different high-level graphics functions for displaying large datasets, + displaying circular data in a very flexible way, finding local maxima, brewing + color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently + colored margin and plot region. In addition, the package contains auxiliary functions + for data manipulation like omitting observations with irregular values or selecting + data by logical vectors, which include NAs. Other functions are especially useful + in spectroscopy and analyses of environmental data: robust baseline fitting, finding + peaks in spectra, converting humidity measures.' + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDPmisc + url_git: '' +IDPSurvival: + version: '1.2' + title: Imprecise Dirichlet Process for Survival Analysis + maintainer: Francesca Mangili + description: |- + Functions to perform robust + nonparametric survival analysis with right censored + data using a prior near-ignorant Dirichlet Process. + Mangili, F., Benavoli, A., de Campos, C.P., Zaffalon, M. (2015) . + date_publication: '2017-02-26' + bug_reports: '' + url: http://ipg.idsia.ch/software/ + url_cran: https://CRAN.R-project.org/package=IDPSurvival + url_git: '' +idr: + version: '1.3' + title: Irreproducible Discovery Rate + maintainer: Qunhua Li + description: This is a package for estimating the copula mixture model and plotting + correspondence curves. Details are in "Measuring reproducibility of high-throughput + experiments" (2011), Annals of Applied Statistics, Vol. 5, No. 3, 1752-1779, by + Li, Brown, Huang, and Bickel. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idr + url_git: '' +ids: + version: 1.0.1 + title: Generate Random Identifiers + maintainer: Rich FitzJohn + description: Generate random or human readable and pronounceable identifiers. + date_publication: '2017-05-31' + bug_reports: https://github.com/richfitz/ids/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ids + url_git: https://github.com/richfitz/ids +IDSL.CSA: + version: '1.2' + title: |- + Composite Spectra Analysis (CSA) for High-Resolution Mass + Spectrometry Analyses + maintainer: Dinesh Barupal + description: A fragmentation spectra detection pipeline for high-throughput LC/HRMS + data processing using peaklists generated by the 'IDSL.IPA' workflow . + The 'IDSL.CSA' package can deconvolute fragmentation spectra from Composite Spectra + Analysis (CSA), Data Dependent Acquisition (DDA) analysis, and various Data-Independent + Acquisition (DIA) methods such as MS^E, All-Ion Fragmentation (AIF) and SWATH-MS + analysis. The 'IDSL.CSA' package was introduced in . + date_publication: '2023-06-29' + bug_reports: https://github.com/idslme/idsl.csa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.CSA + url_git: https://github.com/idslme/idsl.csa +IDSL.FSA: + version: '1.2' + title: Fragmentation Spectra Analysis (FSA) + maintainer: Dinesh Barupal + description: The 'IDSL.FSA' package was designed to annotate standard .msp (mass + spectra format) and .mgf (Mascot generic format) files using mass spectral entropy + similarity, dot product (cosine) similarity, and normalized Euclidean mass error + (NEME) followed by intelligent pre-filtering steps for rapid spectra searches. + 'IDSL.FSA' also provides a number of modules to convert and manipulate .msp and + .mgf files. The 'IDSL.FSA' workflow was integrated in the 'IDSL.CSA' and 'IDSL.NPA' + packages introduced in . + date_publication: '2023-06-29' + bug_reports: https://github.com/idslme/idsl.fsa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.FSA + url_git: https://github.com/idslme/idsl.fsa +IDSL.IPA: + version: '2.9' + title: Intrinsic Peak Analysis (IPA) for HRMS Data + maintainer: Dinesh Barupal + description: A multi-layered untargeted pipeline for high-throughput LC/HRMS data + processing to extract signals of organic small molecules. The package performs + ion pairing, peak detection, peak table alignment, retention time correction, + aligned peak table gap filling, peak annotation and visualization of extracted + ion chromatograms (EICs) and total ion chromatograms (TICs). The 'IDSL.IPA' package + was introduced in . + date_publication: '2023-05-31' + bug_reports: https://github.com/idslme/idsl.ipa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.IPA + url_git: https://github.com/idslme/idsl.ipa +IDSL.MXP: + version: '2.0' + title: |- + Parser for mzML, mzXML, and netCDF Files (Mass Spectrometry + Data) + maintainer: Dinesh Barupal + description: A tiny parser to extract mass spectra data and metadata table of mass + spectrometry acquisition properties from mzML, mzXML and netCDF files introduced + in . + date_publication: '2023-03-24' + bug_reports: https://github.com/idslme/idsl.mxp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.MXP + url_git: https://github.com/idslme/idsl.mxphttps://colab.research.google.com/drive/1gXwwuI1zzDHykKfodLSQQt5rwTuFEMpD +IDSL.NPA: + version: '1.2' + title: Nominal Peak Analysis (NPA) + maintainer: Dinesh Barupal + description: A pipeline to process nominal mass spectrometry data to create .msp + files for untargeted analyses. + date_publication: '2023-06-29' + bug_reports: https://github.com/idslme/idsl.npa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.NPA + url_git: https://github.com/idslme/idsl.npa +IDSL.SUFA: + version: '1.3' + title: Simplified UFA + maintainer: Dinesh Barupal + description: A simplified version of the 'IDSL.UFA' package to calculate isotopic + profiles and adduct formulas from molecular formulas with no dependency on other + R packages for online tools and educational mass spectrometry courses. The 'IDSL.SUFA' + package also provides an ancillary module to process user-defined adduct formulas. + date_publication: '2023-03-23' + bug_reports: https://github.com/idslme/idsl.sufa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.SUFA + url_git: https://github.com/idslme/idsl.sufa +IDSL.UFA: + version: '2.0' + title: United Formula Annotation (UFA) for HRMS Data Processing + maintainer: Dinesh Barupal + description: A pipeline to annotate chromatography peaks from the 'IDSL.IPA' workflow + with molecular formulas of a prioritized chemical + space using an isotopic profile matching approach. The 'IDSL.UFA' workflow only + requires mass spectrometry level 1 (MS1) data for formula annotation. The 'IDSL.UFA' + methods was described in . + date_publication: '2023-05-18' + bug_reports: https://github.com/idslme/idsl.ufa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.UFA + url_git: https://github.com/idslme/idsl.ufa +IDSL.UFAx: + version: 1.9.1 + title: Exhaustive Chemical Enumeration for United Formula Annotation + maintainer: Dinesh Barupal + description: 'A pipeline to annotate a number of peaks from the ''IDSL.IPA'' peaklists + using an exhaustive chemical enumeration-based approach. This package can perform + elemental composition calculations using the following 15 elements : C, B, Br, + Cl, K, S, Si, N, H, As, F, I, Na, O, and P.' + date_publication: '2023-04-05' + bug_reports: https://github.com/idslme/idsl.ufax/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IDSL.UFAx + url_git: https://github.com/idslme/idsl.ufax +IDSpatialStats: + version: 0.4.0 + title: Estimate Global Clustering in Infectious Disease + maintainer: Justin Lessler + description: |- + Implements various novel and standard clustering statistics and + other analyses useful for understanding the spread of infectious disease. + date_publication: '2024-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IDSpatialStats + url_git: '' +idx2r: + version: 1.0.0 + title: |- + Convert Files to and from IDX Format to Vectors, Matrices and + Arrays + maintainer: Erik Doffagne + description: |- + Convert files to and from IDX format to vectors, matrices and arrays. + IDX is a very simple file format designed for storing vectors and multidimensional matrices in + binary format. The format is described on the website from Yann LeCun + . + date_publication: '2018-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=idx2r + url_git: https://github.com/edoffagne/idx2r +ie2misc: + version: 0.9.1 + title: Irucka Embry's Miscellaneous USGS Functions + maintainer: Irucka Embry + description: |- + A collection of Irucka Embry's miscellaneous USGS functions + (processing .exp and .psf files, statistical error functions, + "+" dyadic operator for use with NA, creating ADAPS and QW + spreadsheet files, calculating saturated enthalpy). Irucka created these + functions while a Cherokee Nation Technology Solutions (CNTS) United States + Geological Survey (USGS) Contractor and/or USGS employee. + date_publication: '2023-09-20' + bug_reports: https://gitlab.com/iembry/ie2misc/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ie2misc + url_git: https://gitlab.com/iembry/ie2misc +ie2miscdata: + version: 1.0.4 + title: Irucka Embry's Miscellaneous USGS Data Collection + maintainer: Irucka Embry + description: |- + A collection of Irucka Embry's miscellaneous USGS data sets (USGS + Parameter codes with fixed values, USGS global time zone codes, and US Air + Force Global Engineering Weather Data). Irucka created these data sets + while a Cherokee Nation Technology Solutions (CNTS) United States + Geological Survey (USGS) Contractor and/or USGS employee. + date_publication: '2023-08-20' + bug_reports: https://gitlab.com/iembry/ie2miscdata/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ie2miscdata + url_git: https://gitlab.com/iembry/ie2miscdata +ieeeround: + version: 0.2-2 + title: Functions to Set and Get the IEEE Rounding Mode + maintainer: Gianluca Amato + description: |- + A pair of functions for getting and setting the IEEE rounding + mode for floating point computations. + date_publication: '2024-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ieeeround + url_git: https://github.com/jandom-devel/ieeeround +ieegio: + version: 0.0.3 + title: File IO for Intracranial Electroencephalography + maintainer: Zhengjia Wang + description: |- + Integrated toolbox supporting common file formats used for intracranial + Electroencephalography (iEEG) and deep-brain stimulation (DBS) study. + date_publication: '2025-01-13' + bug_reports: https://github.com/dipterix/ieegio/issues + url: http://dipterix.org/ieegio/ + url_cran: https://CRAN.R-project.org/package=ieegio + url_git: '' +iemisctext: + version: 1.0.1 + title: Irucka Embry's Miscellaneous Text Collection + maintainer: Irucka Embry + description: |- + An eclectic collection of short stories and poetry with topics on + climate strange, connecting the geopolitical dots, the myth of us versus + them, and the idiocy of war. Please refer to the COPYRIGHTS file and the + text_citation.cff file for the reference copyright information and for the + complete citations of the reference sources, respectively. + date_publication: '2024-06-01' + bug_reports: https://gitlab.com/iembry/iemisctext/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iemisctext + url_git: https://gitlab.com/iembry/iemisctext +IETD: + version: 1.0.0 + title: Inter-Event Time Definition + maintainer: Luis F. Duque + description: |- + Computes characteristics of independent rainfall events (duration, total rainfall depth, and intensity) + extracted from a sub-daily rainfall time series based on the inter-event time definition (IETD) method. To have a + reference value of IETD, it also analyzes/computes IETD values through three methods: autocorrelation analysis, the + average annual number of events analysis, and coefficient of variation analysis. Ideal for analyzing the sensitivity + of IETD to characteristics of independent rainfall events. + Adams B, Papa F (2000) . + Joo J et al. (2014) . + Restrepo-Posada P, Eagleson P (1982) . + date_publication: '2020-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IETD + url_git: '' +ieugwasr: + version: 1.0.1 + title: Interface to the 'OpenGWAS' Database API + maintainer: Gibran Hemani + description: |- + Interface to the 'OpenGWAS' database API . Includes a wrapper + to make generic calls to the API, plus convenience functions for + specific queries. + date_publication: '2024-07-01' + bug_reports: https://github.com/MRCIEU/ieugwasr/issues + url: https://mrcieu.github.io/ieugwasr/ + url_cran: https://CRAN.R-project.org/package=ieugwasr + url_git: https://github.com/MRCIEU/ieugwasr +ifaTools: + version: '0.23' + title: Toolkit for Item Factor Analysis with 'OpenMx' + maintainer: Joshua N. Pritikin + description: |- + Tools, tutorials, and demos of Item Factor Analysis using 'OpenMx'. + This software is described in Pritikin & Falk (2020) . + date_publication: '2022-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ifaTools + url_git: https://github.com/jpritikin/ifaTools +IFC: + version: 0.2.1 + title: Tools for Imaging Flow Cytometry + maintainer: Yohann Demont + description: Contains several tools to treat imaging flow cytometry data from 'ImageStream®' + and 'FlowSight®' cytometers ('Amnis®' 'Cytek®'). Provides an easy and simple way + to read and write .fcs, .rif, .cif and .daf files. Information such as masks, + features, regions and populations set within these files can be retrieved for + each single cell. In addition, raw data such as images stored can also be accessed. + Users, may hopefully increase their productivity thanks to dedicated functions + to extract, visualize, manipulate and export 'IFC' data. Toy data example can + be installed through the 'IFCdata' package of approximately 32 MB, which is available + in a 'drat' repository . See file 'COPYRIGHTS' + and file 'AUTHORS' for a list of copyright holders and authors. + date_publication: '2023-09-13' + bug_reports: https://github.com/gitdemont/IFC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IFC + url_git: '' +ifCNVR: + version: 0.1.0 + title: Isolation-Forest Based 'CNV' Detection from 'NGS' Data + maintainer: Simon Cabello-Aguilar + description: Automatically detects Copy Number Variations (CNV) from Next Generation + Sequencing data using a machine learning algorithm, Isolation forest. More details + about the method can be found in the paper by Cabello-Aguilar (2022) . + date_publication: '2022-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ifCNVR + url_git: https://github.com/SimCab-CHU/ifCNVR +ifctools: + version: 0.3.6 + title: Italian Fiscal Code ('Codice Fiscale') Utilities + maintainer: Luca Braglia + description: |- + Provides utility functions to deal with Italian fiscal + code ('codice fiscale'). + date_publication: '2023-08-28' + bug_reports: https://github.com/lbraglia/ifctools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ifctools + url_git: https://github.com/lbraglia/ifctools +ife: + version: 0.1.12 + title: Influence Function Based Estimate Objects + maintainer: Nicholas Williams + description: |- + Implements an S7 class for estimates based on influence functions. + Standard arithmetic operations are defined for the class. + date_publication: '2025-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ife + url_git: '' +IFMCDM: + version: 0.1.17 + title: Intuitionistic Fuzzy Multi-Criteria Decision Making Methods + maintainer: Andrzej Dudek + description: 'Implementation of two multi-criteria decision making methods (MCDM): + Intuitionistic Fuzzy Synthetic Measure (IFSM) and Intuitionistic Fuzzy Technique + for Order of Preference by Similarity to Ideal Solution (IFTOPSIS) for intuitionistic + fuzzy data sets for multi-criteria decision making problems. References describing + the methods: Jefmański (2020) ; Jefmański, Roszkowska, + Kusterka-Jefmańska (2021) .' + date_publication: '2023-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IFMCDM + url_git: '' +ifo: + version: 0.2.0 + title: Client for the Ifo Institute Time Series + maintainer: Maximilian Mücke + description: |- + Download ifo business survey data and more time series from + ifo institute . + date_publication: '2024-11-28' + bug_reports: https://github.com/m-muecke/ifo/issues + url: https://m-muecke.github.io/ifo/ + url_cran: https://CRAN.R-project.org/package=ifo + url_git: https://github.com/m-muecke/ifo +iForecast: + version: 1.1.0 + title: Machine Learning Time Series Forecasting + maintainer: Ho Tsung-wu + description: Compute static, onestep and multistep time series forecasts for machine + learning models. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iForecast + url_git: '' +IFP: + version: 0.2.4 + title: Identifying Functional Polymorphisms + maintainer: Leeyoung Park + description: A suite for identifying causal models using relative concordances and + identifying causal polymorphisms in case-control genetic association data, especially + with large controls re-sequenced data. + date_publication: '2020-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IFP + url_git: '' +ifpd: + version: 0.1.0 + title: Indonesia Food Prices Data + maintainer: Fadhlul Mubarak + description: Imputation of missing values using the last observation carried forward + technique on Indonesia food prices data that is time series data. Also, this technique + applies imputation to data whose dates do not appear directly. So that the series + assumptions in the time series data are met. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ifpd + url_git: https://github.com/mubarakfadhlul/ifpd +ifs: + version: 0.1.10 + title: Iterated Function Systems + maintainer: Stefano M. Iacus + description: Iterated Function Systems Estimator as in Iacus and La Torre (2005) + . + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ifs + url_git: '' +IFTPredictor: + version: 0.1.0 + title: Predictions Using Item-Focused Tree Models + maintainer: Muditha L. Bodawatte Gedara + description: |- + This function predicts item response probabilities and item + responses using the item-focused tree model. The item-focused tree model + combines logistic regression with recursive partitioning to detect + Differential Item Functioning in dichotomous items. The model applies + partitioning rules to the data, splitting it into homogeneous subgroups, and + uses logistic regression within each subgroup to explain the data. + Differential Item Functioning detection is achieved by examining potential + group differences in item response patterns. This method is useful for + understanding how different predictors, such as demographic or psychological + factors, influence item responses across subgroups. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IFTPredictor + url_git: '' +ig.degree.betweenness: + version: 0.1.0 + title: |- + "Smith-Pittman Community Detection Algorithm for 'igraph' + Objects (2024)" + maintainer: Benjamin Smith + description: |- + Implements the "Smith-Pittman" community detection algorithm + for network analysis using 'igraph' objects. This algorithm combines node + degree and betweenness centrality measures to identify communities within + networks, with a gradient evident in social partitioning. The package + provides functions for community detection, visualization, and analysis of + the resulting community structure. Methods are based on results from Smith, + Pittman and Xu (2024) . + date_publication: '2024-11-11' + bug_reports: https://github.com/benyamindsmith/ig.degree.betweenness/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ig.degree.betweenness + url_git: https://github.com/benyamindsmith/ig.degree.betweenness +ig.vancouver.2014.topcolour: + version: 0.1.2.0 + title: Instagram 2014 Vancouver Top Colour Dataset + maintainer: Roland Tanglao + description: |- + A dataset of the top colours of photos from Instagram + taken in 2014 in the city of Vancouver, British Columbia, Canada. + It consists of: top colour and counts data. This data was + obtained using the Instagram API. Instagram is a web photo + sharing service. It can be found at: . + The Instagram API is documented at: . + date_publication: '2015-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ig.vancouver.2014.topcolour + url_git: '' +IgAScores: + version: 0.1.2 + title: Score Taxon-Level IgA Binding in IgA-Seq Experiments + maintainer: Matthew Jackson + description: |- + Functions to calculate indices used to score immunoglobulin A (IgA) binding of bacteria in IgA sequencing (IgA-Seq) experiments. + This includes the original Kau and Palm indices and more recent methods as described in Jackson et al. (2020) . + Additionally the package contains a function to simulate IgA-Seq data and an example experimental data set for method testing. + date_publication: '2020-09-01' + bug_reports: '' + url: https://doi.org/10.1101/2020.08.19.257501 + url_cran: https://CRAN.R-project.org/package=IgAScores + url_git: '' +iGasso: + version: 1.6.1 + title: Statistical Tests and Utilities for Genetic Association + maintainer: Kai Wang + description: A collection of statistical tests for genetic association studies and + summary data based Mendelian randomization. + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iGasso + url_git: '' +igate: + version: 0.3.3 + title: Guided Analytics for Testing Manufacturing Parameters + maintainer: Stefan Stein + description: |- + An implementation of the initial guided analytics for parameter testing and + controlband extraction framework. Functions are available for continuous and + categorical target variables as well as for generating standardized reports of the + conducted analysis. See for more information + on the technology. + date_publication: '2019-09-10' + bug_reports: https://github.com/stefan-stein/igate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=igate + url_git: https://github.com/stefan-stein/igate +IGC.CSM: + version: 0.2.0 + title: |- + Simulate Impact of Different Urban Policies Through a General + Equilibrium Model + maintainer: Roman Zarate + description: Develops a General Equilibrium (GE) Model, which estimates key variables + such as wages, the number of residents and workers, the prices of the floor space, + and its distribution between commercial and residential use, as in Ahlfeldt et + al., (2015) . By doing so, the model allows understanding + the economic influence of different urban policies. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IGC.CSM + url_git: '' +IGCities: + version: 0.2.0 + title: |- + Simulate Impact of Different Urban Policies Through a General + Equilibrium Model + maintainer: David Zarruk + description: Develops a General Equilibrium (GE) Model, which estimates key variables + such as wages, the number of residents and workers, the prices of the floor space, + and its distribution between commercial and residential use, as in Ahlfeldt et + al., (2015) . By doing + so, the model allows understanding the economic influence of different urban policies. + date_publication: '2022-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IGCities + url_git: '' +igcop: + version: 1.0.2 + title: Computational Tools for the IG and IGL Copula Families + maintainer: Vincenzo Coia + description: |- + Compute distributional quantities for an + Integrated Gamma (IG) or Integrated Gamma Limit (IGL) copula, such + as a cdf and density. Compute corresponding conditional quantities + such as the cdf and quantiles. Generate + data from an IG or IGL copula. See the vignette for formulas, + or for a derivation, see Coia, V (2017) "Forecasting of Nonlinear + Extreme Quantiles Using Copula Models." PhD Dissertation, + The University of British Columbia. + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=igcop + url_git: '' +iglu: + version: 4.2.2 + title: Interpreting Glucose Data from Continuous Glucose Monitors + maintainer: Irina Gaynanova + description: Implements a wide range of metrics for measuring glucose control and + glucose variability based on continuous glucose monitoring data. The list of implemented + metrics is summarized in Rodbard (2009) . Additional + visualization tools include time-series plots, lasagna plots and ambulatory glucose + profile report. + date_publication: '2025-01-14' + bug_reports: https://github.com/irinagain/iglu/issues + url: https://irinagain.github.io/iglu/ + url_cran: https://CRAN.R-project.org/package=iglu + url_git: '' +igoR: + version: 0.2.1 + title: Intergovernmental Organizations Database + maintainer: Diego Hernangómez + description: |- + Tools to extract information from the Intergovernmental + Organizations ('IGO') Database , version 3, provided by the Correlates + of War Project . See also Pevehouse, J. + C. et al. (2020). Version 3 includes information from 1815 to 2014. + date_publication: '2024-12-17' + bug_reports: https://github.com/dieghernan/igoR/issues + url: https://dieghernan.github.io/igoR/ + url_cran: https://CRAN.R-project.org/package=igoR + url_git: https://github.com/dieghernan/igoR +IgorR: + version: 0.9.0 + title: |- + Read Binary Files Saved by 'Igor Pro' (Including 'Neuromatic' + Data) + maintainer: Gregory Jefferis + description: |- + Provides function to read data from the 'Igor Pro' data analysis + program by 'Wavemetrics'. The data formats supported are 'Igor' packed + experiment format ('pxp') and 'Igor' binary wave ('ibw'). See: + for details. Also includes functions to load + special 'pxp' files produced by the 'Igor Pro' 'Neuromatic' and 'Nclamp' + packages for recording and analysing neuronal data. See + for details. + date_publication: '2024-08-28' + bug_reports: https://github.com/jefferis/IgorR/issues + url: https://jefferis.github.io/IgorR/ + url_cran: https://CRAN.R-project.org/package=IgorR + url_git: https://github.com/jefferis/IgorR +IGoRRR: + version: 0.3.4 + title: A Shiny Interface for Simple Data Management + maintainer: Jean-Luc Lipatz + description: |2- + + Launches a shiny application generating code to + view tables in several ways, + import/export tables, + modify tables, + make some basic graphics. + 'IGoR' is a graphic user interface designed to help beginners + using simple functions around table management and exploration. + Inspired by 'Rcmdr', 'IGoR' is a code generator that, with simple inputs under a Shiny application, + provides R code mainly built around the 'tidyverse' or some packages in the direct line of the Mosaic project: + the 'rio' and 'ggformula' packages. + The generated code doesn't depend on IGoR and can be manually modified by the user or copied elsewhere. + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IGoRRR + url_git: '' +igr: + version: 1.0.0 + title: Irish Grid Reference Utilities + maintainer: John Kennedy + description: |- + Convert between Irish grid references and Irish Grid coordinates. Irish grid + references can also be converted to or from an 'sf' object in any coordinate reference + system. Precisions from 1 m to 100 km including 2 km (tetrads) are supported, as are + datasets with mixed precision. Conversion to 'sf' polygons is precision-aware. + date_publication: '2025-01-07' + bug_reports: https://github.com/digitalnature-ie/igr/issues + url: https://digitalnature-ie.github.io/igr/ + url_cran: https://CRAN.R-project.org/package=igr + url_git: https://github.com/digitalnature-ie/igr +igraph: + version: 2.1.4 + title: Network Analysis and Visualization + maintainer: Kirill Müller + description: |- + Routines for simple graphs and network analysis. It can + handle large graphs very well and provides functions for generating + random and regular graphs, graph visualization, centrality methods and + much more. + date_publication: '2025-01-23' + bug_reports: https://github.com/igraph/rigraph/issues + url: https://r.igraph.org/ + url_cran: https://CRAN.R-project.org/package=igraph + url_git: '' +igraphdata: + version: 1.0.1 + title: A Collection of Network Data Sets for the 'igraph' Package + maintainer: Gabor Csardi + description: |- + A small collection of various network data sets, + to use with the 'igraph' package: the Enron email network, various food webs, + interactions in the immunoglobulin protein, the karate club network, + Koenigsberg's bridges, visuotactile brain areas of the macaque monkey, + UK faculty friendship network, domestic US flights network, etc. + date_publication: '2015-07-13' + bug_reports: https://github.com/igraph/igraphdata/issues + url: http://igraph.org + url_cran: https://CRAN.R-project.org/package=igraphdata + url_git: '' +igraphinshiny: + version: '0.1' + title: Use 'shiny' to Demo 'igraph' + maintainer: Ming-Jer Lee + description: Using 'shiny' to demo 'igraph' package makes learning graph theory + easy and fun. + date_publication: '2016-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=igraphinshiny + url_git: '' +iGraphMatch: + version: 2.0.5 + title: Tools for Graph Matching + maintainer: Daniel Sussman + description: |- + Versatile tools and data for graph matching analysis with various forms of prior information + that supports working with 'igraph' objects, matrix objects, or lists of either. + date_publication: '2024-05-17' + bug_reports: https://github.com/dpmcsuss/iGraphMatch/issues + url: https://dpmcsuss.github.io/iGraphMatch/ + url_cran: https://CRAN.R-project.org/package=iGraphMatch + url_git: https://github.com/dpmcsuss/iGraphMatch +igraphtosonia: + version: '1.0' + title: Convert iGraph graps to SoNIA .son files + maintainer: Sean J Westwood + description: |- + This program facilitates exporting igraph graphs to the + SoNIA file format + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=igraphtosonia + url_git: '' +igraphwalshdata: + version: 0.1.0 + title: '''igraph'' Datasets from Melanie Walsh' + maintainer: Benjamin Smith + description: Interesting 'igraph' datasets from Melanie Walsh's sample social network + datasets repository . + date_publication: '2024-06-10' + bug_reports: https://github.com/benyamindsmith/igraphwalshdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=igraphwalshdata + url_git: https://github.com/benyamindsmith/igraphwalshdata +igrf: + version: '1.0' + title: International Geomagnetic Reference Field + maintainer: Koen Hufkens + description: |- + The 13th generation International Geomagnetic Reference Field (IGRF). + A standard spherical harmonic representation of the Earth's main field. + date_publication: '2022-01-07' + bug_reports: https://github.com/bluegreen-labs/igrf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=igrf + url_git: https://github.com/bluegreen-labs/igrf +iGSEA: + version: '1.2' + title: Integrative Gene Set Enrichment Analysis Approaches + maintainer: Wentao Lu + description: |- + To integrate multiple GSEA studies, we propose a hybrid strategy, + iGSEA-AT, for choosing random effects (RE) versus fixed effect (FE) models, + with an attempt to achieve the potential maximum statistical efficiency as + well as stability in performance in various practical situations. In addition + to iGSEA-AT, this package also provides options to perform integrative GSEA + with testing based on a FE model (iGSEA-FE) and testing based on a RE model + (iGSEA-RE). The approaches account for different set sizes when testing a + database of gene sets. The function is easy to use, and the three approaches + can be applied to both binary and continuous phenotypes. + date_publication: '2017-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iGSEA + url_git: '' +IGST: + version: 0.1.0 + title: Informative Gene Selection Tool + maintainer: Nitesh Kumar Sharma + description: Mining informative genes with certain biological meanings are important + for clinical diagnosis of disease and discovery of disease mechanisms in plants + and animals. This process involves identification of relevant genes and removal + of redundant genes as much as possible from a whole gene set. This package selects + the informative genes related to a specific trait using gene expression dataset. + These trait specific genes are considered as informative genes. This package returns + the informative gene set from the high dimensional gene expression data using + a combination of methods SVM and MRMR (for feature selection) with bootstrapping + procedure. + date_publication: '2020-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IGST + url_git: '' +ihclust: + version: 0.1.0 + title: Iterative Hierarchical Clustering (IHC) + maintainer: Elin Cho + description: |- + Provides a set of tools to + i) identify geographic areas with significant change over time in drug utilization, and + ii) characterize common change over time patterns among the time series for multiple geographic areas. + For reference, see below: + 1. Song, J., Carey, M., Zhu, H., Miao, H., Ram´ırez, J. C., & Wu, H. (2018) + 2. Wu, S., Wu, H. (2013) + 3. Carey, M., Wu, S., Gan, G. & Wu, H. (2016) . + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ihclust + url_git: '' +iheatmapr: + version: 0.7.1 + title: Interactive, Complex Heatmaps + maintainer: Alan O'Callaghan + description: |- + Make complex, interactive heatmaps. 'iheatmapr' includes a modular + system for iteratively building up complex heatmaps, as well as the + iheatmap() function for making relatively standard heatmaps. + date_publication: '2024-01-25' + bug_reports: https://github.com/ropensci/iheatmapr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iheatmapr + url_git: https://docs.ropensci.org/iheatmapr/(website)https://github.com/ropensci/iheatmapr +iheiddown: + version: 0.9.7 + title: For Writing Geneva Graduate Institute Documents + maintainer: James Hollway + description: |- + A set of tools for writing documents + according to Geneva Graduate Institute conventions and regulations. + The most common use is for writing and compiling theses or thesis + chapters, as drafts or for examination with correct preamble formatting. + However, the package also offers users to create HTML presentation + slides with 'xaringan', complete problem sets, format posters, and, + for course instructors, prepare a syllabus. + The package includes additional functions for institutional color palettes, + an institutional 'ggplot' theme, a function for counting manuscript words, + and a bibliographical analysis toolkit. + date_publication: '2022-11-09' + bug_reports: https://github.com/jhollway/iheiddown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iheiddown + url_git: https://github.com/jhollway/iheiddown +ihpdr: + version: 1.2.1 + title: Download Data from the International House Price Database + maintainer: Kostas Vasilopoulos + description: |- + Web scraping the for + up-to-date data on international house prices and exuberance + indicators. Download data in tidy format. + date_publication: '2020-07-13' + bug_reports: https://github.com/kvasilopoulos/ihpdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ihpdr + url_git: https://github.com/kvasilopoulos/ihpdr +IHSEP: + version: 0.3.1 + title: Inhomogeneous Self-Exciting Process + maintainer: Feng Chen + description: Simulate an inhomogeneous self-exciting process (IHSEP), or Hawkes + process, with a given (possibly time-varying) baseline intensity and an excitation + function. Calculate the likelihood of an IHSEP with given baseline intensity and + excitation functions for an (increasing) sequence of event times. Calculate the + point process residuals (integral transforms of the original event times). Calculate + the mean intensity process. + date_publication: '2022-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IHSEP + url_git: '' +iimi: + version: 1.2.1 + title: Identifying Infection with Machine Intelligence + maintainer: Xuekui Zhang + description: |- + A novel machine learning method for plant viruses diagnostic using + genome sequencing data. This package includes three different machine + learning models, random forest, XGBoost, and elastic net, to train and + predict mapped genome samples. Mappability profile and unreliable regions + are introduced to the algorithm, and users can build a mappability profile + from scratch with functions included in the package. Plotting mapped sample + coverage information is provided. + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iimi + url_git: '' +iIneq: + version: 1.0.2 + title: |- + Computing Individual Components of the Gini and the Theil + Indices + maintainer: Tim Liao + description: |- + Computes individual contributions to the overall Gini and + Theil's T and Theil's L measures and their decompositions by groups + such as race, gender, national origin, with the three functions of + iGini(), iTheiT(), and iTheilL(). For details, see Tim F. Liao (2019) + . + date_publication: '2021-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iIneq + url_git: '' +IIProductionUnknown: + version: 0.0.3 + title: |- + Analyzing Data Through of Percentage of Importance Indice + (Production Unknown) and Its Derivations + maintainer: Alcinei Mistico Azevedo + description: The Importance Index (I.I.) can determine the loss and solution sources + for a system in certain knowledge areas (e.g., agronomy), when production (e.g., + fruits) is known (Demolin-Leite, 2021). Events (e.g., agricultural pest) can have + different magnitudes (numerical measurements), frequencies, and distributions + (aggregate, random, or regular) of event occurrence, and I.I. bases in this triplet + (Demolin-Leite, 2021) . + Usually, the higher the magnitude and frequency of aggregated distribution, the + greater the problem or the solution (e.g., natural enemies versus pests) for the + system (Demolin-Leite, 2021). However, the final production of the system is not + always known or is difficult to determine (e.g., degraded area recovery). A derivation + of the I.I. is the percentage of Importance Index-Production Unknown (% I.I.-PU) + that can detect the loss or solution sources, when production is unknown for the + system (Demolin-Leite, 2024) . + date_publication: '2023-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IIProductionUnknown + url_git: '' +IIS: + version: '1.1' + title: |- + Datasets to Accompany Wolfe and Schneider - Intuitive + Introductory Statistics + maintainer: Grant Schneider + description: 'These datasets and functions accompany Wolfe and Schneider (2017) + - Intuitive Introductory Statistics (ISBN: 978-3-319-56070-0) . + They are used in the examples throughout the text and in the end-of-chapter exercises. + The datasets are meant to cover a broad range of topics in order to appeal to + the diverse set of interests and backgrounds typically present in an introductory + Statistics class.' + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IIS + url_git: '' +IIVpredictor: + version: 0.1.0 + title: Modeling Within Individual Variability as Predictor + maintainer: Xiao Liu + description: Time parceling method and Bayesian variability modeling methods for + modeling within individual variability indicators as predictors.For more details, + see . + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IIVpredictor + url_git: '' +IJSE: + version: 0.1.1 + title: Infinite-Jackknife-Based Standard Errors for 'brms' Models + maintainer: Feng Ji + description: |- + Provides a function to calculate infinite-jackknife-based + standard errors for fixed effects parameters in 'brms' models, handling + both clustered and independent data. + References: Ji et al. (2024) ; Giordano et al. (2024) . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IJSE + url_git: '' +ijtiff: + version: 2.3.5 + title: Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files + maintainer: Rory Nolan + description: |- + General purpose TIFF file I/O for R users. Currently the + only such package with read and write support for TIFF files with + floating point (real-numbered) pixels, and the only package that can + correctly import TIFF files that were saved from 'ImageJ' and write + TIFF files than can be correctly read by 'ImageJ' + . Also supports text image I/O. + date_publication: '2025-01-29' + bug_reports: https://github.com/ropensci/ijtiff/issues + url: https://docs.ropensci.org/ijtiff/ + url_cran: https://CRAN.R-project.org/package=ijtiff + url_git: https://github.com/ropensci/ijtiff +ilabelled: + version: 1.0.1 + title: Simple Handling of Labelled Data + maintainer: Christof Lewerenz + description: Simple handling of survey data. Smart handling of meta-information + like e.g. variable-labels value-labels and scale-levels. Easy access and validation + of meta-information. Useage of value labels and values respectively for subsetting + and recoding data. + date_publication: '2025-01-20' + bug_reports: https://github.com/clewerenz/ilabelled/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ilabelled + url_git: https://github.com/clewerenz/ilabelled +ILRCM: + version: 0.1.0 + title: |- + Convert Irregular Longitudinal Data to Regular Intervals and + Perform Clustering + maintainer: Atanu Bhattacharjee + description: |- + Convert irregularly spaced longitudinal data into regular intervals for further analysis, + and perform clustering using advanced machine learning techniques. + The package is designed for handling complex longitudinal datasets, + optimizing them for research in healthcare, demography, and other fields + requiring temporal data modeling. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ILRCM + url_git: '' +ILS: + version: '0.3' + title: Interlaboratory Study + maintainer: Miguel Flores + description: |- + It performs interlaboratory studies (ILS) to detect those + laboratories that provide non-consistent results when comparing to others. It + permits to work simultaneously with various testing materials, from standard + univariate, and functional data analysis (FDA) perspectives. The univariate + approach based on ASTM E691-08 consist of estimating the Mandel's h and + k statistics to identify those laboratories that provide more significant + different results, testing also the presence of outliers by Cochran and Grubbs + tests, Analysis of variance (ANOVA) techniques are provided (F and Tuckey + tests) to test differences in means corresponding to different laboratories per + each material. Taking into account the functional nature of data retrieved in + analytical chemistry, applied physics and engineering (spectra, thermograms, + etc.). ILS package provides a FDA approach for finding the Mandel's k and h + statistics distribution by smoothing bootstrap resampling. + date_publication: '2023-01-15' + bug_reports: https://github.com/mflores72000/ILS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ILS + url_git: https://github.com/mflores72000/ILS/ +ILSAmerge: + version: 1.3.6 + title: |- + Merge and Download International Large-Scale Assessments (ILSA) + Data + maintainer: Andrés Christiansen + description: 'Merges and downloads ''SPSS'' data from different International Large-Scale + Assessments (ILSA), including: Trends in International Mathematics and Science + Study (TIMSS), Progress in International Reading Literacy Study (PIRLS), and others.' + date_publication: '2025-02-12' + bug_reports: '' + url: https://dopatendo.github.io/ILSAmerge/ + url_cran: https://CRAN.R-project.org/package=ILSAmerge + url_git: https://github.com/dopatendo/ILSAmerge +ILSAstats: + version: 0.3.7 + title: Statistics for International Large-Scale Assessments (ILSA) + maintainer: Andrés Christiansen + description: 'Calculates point estimates and standard errors using replicate weights + and plausible values for International Large-Scale Assessments (ILSA), including: + means, proportions, quantiles, correlations, singlelevel regressions, and multilevel + regressions.' + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ILSAstats + url_git: '' +ILSE: + version: 1.1.7 + title: Linear Regression Based on 'ILSE' for Missing Data + maintainer: Wei Liu + description: |- + Linear regression when covariates include missing values by embedding the + correlation information between covariates. Especially for block missing data, + it works well. 'ILSE' conducts imputation and regression simultaneously and iteratively. + More details can be referred to + Huazhen Lin, Wei Liu and Wei Lan. (2021) . + date_publication: '2022-01-31' + bug_reports: https://github.com/feiyoung/ILSE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ILSE + url_git: https://github.com/feiyoung/ILSE +ILSM: + version: 1.0.3.2 + title: |- + Analyze Interconnection Structure of Multilayer Interaction + Networks + maintainer: WeiCheng Sun + description: |- + In view of the analysis of the structural characteristics of the multilayer network has been complete, however, there is still a lack of a unified operation that can quickly obtain the corresponding characteristics of the multilayer network. + To solve this insufficiency, 'ILSM' was designed for supporting calculating such metrics of multilayer networks by functions of this R package. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ILSM + url_git: '' +imabc: + version: 1.0.0 + title: Incremental Mixture Approximate Bayesian Computation (IMABC) + maintainer: '"Christopher, E. Maerzluft"' + description: |- + Provides functionality to perform a likelihood-free method for estimating the parameters of complex models + that results in a simulated sample from the posterior distribution of model parameters given targets. The method begins + with a accept/reject approximate bayes computation (ABC) step applied to a sample of points from the prior distribution + of model parameters. Accepted points result in model predictions that are within the initially specified tolerance + intervals around the target points. The sample is iteratively updated by drawing additional points from a mixture of + multivariate normal distributions, accepting points within tolerance intervals. As the algorithm proceeds, the + acceptance intervals are narrowed. The algorithm returns a set of points and sampling weights that account for the + adaptive sampling scheme. For more details see Rutter, Ozik, DeYoreo, and Collier (2018) . + date_publication: '2021-04-12' + bug_reports: https://github.com/carolyner/imabc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imabc + url_git: https://github.com/carolyner/imabc +image.binarization: + version: 0.1.3 + title: Binarize Images for Enhancing Optical Character Recognition + maintainer: Jan Wijffels + description: |- + Improve optical character recognition by binarizing images. The package focuses primarily on local adaptive thresholding algorithms. + In English, this means that it has the ability to turn a color or gray scale image into a black and white image. This is particularly useful + as a preprocessing step for optical character recognition or handwritten text recognition. + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.binarization + url_git: https://github.com/DIGI-VUB/image.binarization +image.CannyEdges: + version: 0.1.1 + title: Implementation of the Canny Edge Detector for Images + maintainer: Jan Wijffels + description: An implementation of the Canny Edge Detector for detecting edges in + images. The package provides an interface to the algorithm available at . + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.CannyEdges + url_git: https://github.com/bnosac/image +image.ContourDetector: + version: 0.1.1 + title: |- + Implementation of the Unsupervised Smooth Contour Line Detection + for Images + maintainer: Jan Wijffels + description: |- + An implementation of the Unsupervised Smooth Contour Detection algorithm for digital images as described in the paper: "Unsupervised Smooth Contour Detection" by Rafael Grompone von Gioi, and Gregory Randall (2016). + The algorithm is explained at . + date_publication: '2021-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.ContourDetector + url_git: https://github.com/bnosac/image +image.CornerDetectionF9: + version: 0.1.0 + title: Find Corners in Digital Images with FAST-9 + maintainer: Jan Wijffels + description: |- + An implementation of the "FAST-9" corner detection algorithm explained in the paper 'FASTER and better: A machine learning approach to corner detection' by Rosten E., Porter R. and Drummond T. (2008), available at . + The package allows to detect corners in digital images. + date_publication: '2020-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.CornerDetectionF9 + url_git: https://github.com/bnosac/image +image.CornerDetectionHarris: + version: 0.1.2 + title: Implementation of the Harris Corner Detection for Images + maintainer: Jan Wijffels + description: |- + An implementation of the Harris Corner Detection as described in the paper "An Analysis and Implementation of the Harris Corner Detector" by Sánchez J. et al (2018) available at . + The package allows to detect relevant points in images which are characteristic to the digital image. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.CornerDetectionHarris + url_git: https://github.com/bnosac/image +image.libfacedetection: + version: '0.1' + title: Convolutional Neural Network for Face Detection + maintainer: Jan Wijffels + description: |- + An open source library for face detection in images. + Provides a pretrained convolutional neural network based on which can be used to detect faces which have size greater than 10x10 pixels. + date_publication: '2020-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.libfacedetection + url_git: https://github.com/bnosac/image +image.LineSegmentDetector: + version: 0.1.0 + title: Detect Line Segments in Images + maintainer: Jan Wijffels + description: |- + An implementation of the Line Segment Detector on digital images described in the paper: "LSD: A Fast Line Segment Detector with a False Detection Control" by Rafael Grompone von Gioi et al (2012). + The algorithm is explained at . + date_publication: '2020-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.LineSegmentDetector + url_git: https://github.com/bnosac/image +image.Otsu: + version: '0.1' + title: Otsu's Image Segmentation Method + maintainer: Jan Wijffels + description: 'An implementation of the Otsu''s Image Segmentation Method described + in the paper: "A C++ Implementation of Otsu''s Image Segmentation Method". The + algorithm is explained at .' + date_publication: '2020-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.Otsu + url_git: https://github.com/bnosac/image +image.textlinedetector: + version: 0.2.3 + title: Segment Images in Text Lines and Words + maintainer: Jan Wijffels + description: |- + Find text lines in scanned images and segment the lines into words. + Includes implementations of the paper 'Novel A* Path Planning Algorithm for Line Segmentation of Handwritten Documents' by Surinta O. et al (2014) available at , + an implementation of 'A Statistical approach to line segmentation in handwritten documents' by Arivazhagan M. et al (2007) , + and a wrapper for an image segmentation technique to detect words in text lines as described in the paper 'Scale Space Technique for Word Segmentation in Handwritten Documents' by Manmatha R. and Srimal N. (1999) paper at , wrapper for code available at . + Provides as well functionality to put cursive text in images upright using the approach defined in the paper 'A new normalization technique for cursive handwritten words' by Vinciarelli A. and Luettin J. (2001) . + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image.textlinedetector + url_git: https://github.com/DIGI-VUB/image.textlinedetector +image2data: + version: 1.0.1 + title: Turn Images into Data Sets + maintainer: P.-O. Caron + description: |- + The goal of 'image2data' is to extract images and return + them into a data set, + especially for teaching data manipulation and data visualization. + Basically, the eponymous function takes an + image file ('png', 'tiff', 'jpeg', 'bmp') and turn it into a data set, + pixels being rows (subjects) and columns (variables) being their coordinate positions (x- and y-axis) and their respective color (in hex codes). + The function can return a complete image or a range of color (i.e., contour, silhouette). + The data can then be manipulated as would any data set by either creating other related variables (to hide the image) or as a genuine toy data set. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=image2data + url_git: '' +imageData: + version: 0.1-62 + title: |- + Aids in Processing and Plotting Data from a Lemna-Tec + Scananalyzer + maintainer: Chris Brien + description: |- + Note that 'imageData' has been superseded by 'growthPheno'. + The package 'growthPheno' incorporates all the functionality of + 'imageData' and has functionality not available in 'imageData', + but some 'imageData' functions have been renamed. + The 'imageData' package is no longer maintained, but is retained + for legacy purposes. + date_publication: '2023-08-22' + bug_reports: '' + url: http://chris.brien.name + url_cran: https://CRAN.R-project.org/package=imageData + url_git: '' +imagefluency: + version: 0.2.5 + title: Image Statistics Based on Processing Fluency + maintainer: Stefan Mayer + description: |- + Get image statistics based on processing fluency theory. The + functions provide scores for several basic aesthetic principles that + facilitate fluent cognitive processing of images: contrast, + complexity / simplicity, self-similarity, symmetry, and typicality. + See Mayer & Landwehr (2018) and Mayer & Landwehr + (2018) for the theoretical background of the methods. + date_publication: '2024-02-22' + bug_reports: https://github.com/stm/imagefluency/issues/ + url: https://imagefluency.com + url_cran: https://CRAN.R-project.org/package=imagefluency + url_git: https://github.com/stm/imagefluency/ +imagefx: + version: 0.4.1 + title: Extract Features from Images + maintainer: Alex J.C. Witsil + description: Synthesize images into characteristic features for time-series analysis + or machine learning applications. The package was originally intended for monitoring + volcanic eruptions in video data by highlighting and extracting regions above + the vent associated with plume activity. However, the functions within are general + and have wide applications for image processing, analyzing, filtering, and plotting. + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imagefx + url_git: '' +imager: + version: 1.0.2 + title: Image Processing Library Based on 'CImg' + maintainer: Aaron Robotham + description: |- + Fast image processing for images in up to 4 dimensions (two spatial + dimensions, one time/depth dimension, one colour dimension). Provides most + traditional image processing tools (filtering, morphology, transformations, + etc.) as well as various functions for easily analysing image data using R. The + package wraps 'CImg', , a simple, modern C++ library for image + processing. + date_publication: '2024-05-13' + bug_reports: https://github.com/asgr/imager/issues + url: https://asgr.github.io/imager/ + url_cran: https://CRAN.R-project.org/package=imager + url_git: https://github.com/asgr/imager/ +imagerExtra: + version: 1.3.2 + title: Extra Image Processing Library Based on 'imager' + maintainer: Shota Ochi + description: Provides advanced functions for image processing based on the package + 'imager'. + date_publication: '2019-01-25' + bug_reports: https://github.com/ShotaOchi/imagerExtra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imagerExtra + url_git: https://github.com/ShotaOchi/imagerExtra +imageseg: + version: 0.5.0 + title: Deep Learning Models for Image Segmentation + maintainer: Juergen Niedballa + description: A general-purpose workflow for image segmentation using TensorFlow + models based on the U-Net architecture by Ronneberger et al. (2015) + and the U-Net++ architecture by Zhou et al. (2018) . We provide + pre-trained models for assessing canopy density and understory vegetation density + from vegetation photos. In addition, the package provides a workflow for easily + creating model input and model architectures for general-purpose image segmentation + based on grayscale or color images, both for binary and multi-class image segmentation. + date_publication: '2022-05-29' + bug_reports: https://github.com/EcoDynIZW/imageseg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imageseg + url_git: '' +imageviewer: + version: 0.1.0 + title: Simple 'htmlwidgets' Image Viewer with WebGL Brightness/Contrast + maintainer: Iakov Pustilnik + description: Display a 2D-matrix data as a interactive zoomable gray-scale image + viewer, providing tools for manual data inspection. The viewer window shows cursor + guiding lines and a corresponding data slices for both axes at the current cursor + position. A tool-bar allows adjusting image display brightness/contrast through + WebGL filters and performing basic high-pass/low-pass filtering. + date_publication: '2019-02-18' + bug_reports: https://github.com/yapus/imageviewer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imageviewer + url_git: https://github.com/yapus/imageviewer +imaginator: + version: 1.0.0 + title: Simulate General Insurance Policies and Losses + maintainer: Brian Fannin + description: |- + Simulate general insurance policies, losses and loss emergence. The functions contemplate + deterministic and stochastic policy retention and growth scenarios. Retention and growth rates are percentages relative + to the expiring portfolio. Claims are simulated for each policy. This is accomplished either be assuming a frequency + distribution per development lag or by generating random wait times until claim emergence and settlement. Loss simulation + uses standard loss distributions for claim amounts. + date_publication: '2022-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imaginator + url_git: https://github.com/casact/imaginator +imagine: + version: 2.1.2 + title: |- + IMAGing engINEs, Tools for Application of Image Filters to Data + Matrices + maintainer: Wencheng Lau-Medrano + description: |- + Provides fast application of image filters to data matrices, + using R and C++ algorithms. + date_publication: '2025-01-13' + bug_reports: https://github.com/LuisLauM/imagine/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imagine + url_git: https://github.com/LuisLauM/imagine +IMak: + version: 2.1.0 + title: Item Maker + maintainer: Diego Blum + description: This is an Automatic Item Generator for Psychological Assessment. Items + created with the 'IMak' package should not be used in applied settings as part + of the working protocol without ensuring first that the items meet the required + psychometric quality standards (see Blum & Holling, 2018) . + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IMak + url_git: '' +imanr: + version: 2.0.0 + title: Identify the Racial Complex of Native Corns from Mexico + maintainer: Rafael Nieves-Alvarez + description: |- + A model that provides researchers with a powerful tool for the classification + and study of native corn by aiding in the identification of racial complexes + which are fundamental to Mexico's agriculture and culture. This package has been + developed based on data collected by "Proyecto Global de Maíces Nativos México", + which has conducted exhaustive surveys across the country to document the + qualitative and quantitative characteristics of different types of native maize. + The trained model uses a robust and diverse dataset, enabling it to achieve an + 80% accuracy in classifying maize racial complexes. The characteristics included + in the analysis comprise geographic location, grain and cob colors, as well as + various physical measurements, such as lengths and widths. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imanr + url_git: '' +imbalance: + version: 1.0.2.1 + title: Preprocessing Algorithms for Imbalanced Datasets + maintainer: Ignacio Cordón + description: |- + Class imbalance usually damages the performance of classifiers. Thus, it is + important to treat data before applying a classifier algorithm. This package + includes recent resampling algorithms in the literature: (Barua et al. 2014) + ; (Das et al. 2015) , + (Zhang et al. 2014) ; (Gao et al. 2014) + ; (Almogahed et al. 2014) + . It also includes an useful interface to + perform oversampling. + date_publication: '2020-04-07' + bug_reports: http://github.com/ncordon/imbalance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imbalance + url_git: http://github.com/ncordon/imbalance +imbalanceDatRel: + version: 0.1.5 + title: Relocated Data Oversampling for Imbalanced Data Classification + maintainer: Fatih Saglam + description: |- + Relocates oversampled data from a specific oversampling method to + cover area determined by pure and proper class cover catch digraphs (PCCCD). + It prevents any data to be generated in class overlapping area. + date_publication: '2023-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imbalanceDatRel + url_git: '' +imbibe: + version: 0.1.1 + title: A Pipe-Friendly Image Calculator + maintainer: Jon Clayden + description: |- + Provides a set of fast, chainable image-processing operations + which are applicable to images of two, three or four dimensions, + particularly medical images. + date_publication: '2022-11-09' + bug_reports: https://github.com/jonclayden/imbibe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imbibe + url_git: https://github.com/jonclayden/imbibe +imcExperiment: + version: 0.99.0 + title: Mass Cytometry S4 Class Structure Pipeline for Images + maintainer: Anthony Colombo + description: Containerizes cytometry data and allows for S4 class structure to extend + slots related to cell morphology, spatial coordinates, phenotype network information, + and unique cellular labeling. + date_publication: '2021-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imcExperiment + url_git: '' +ImCluster: + version: 0.1.0 + title: Efficiency of Cluster Sampling for Crop Surveys + maintainer: M. Iqbal Jeelani + description: Cluster sampling is a valuable approach when constructing a comprehensive + list of individual units is challenging. It provides operational and cost advantages. + This package is designed to test the efficiency of cluster sampling in terms cluster + variance and design effect in context to crop surveys. This package has been developed + using the algorithm of Iqbal et al. (2018) . + date_publication: '2023-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImCluster + url_git: '' +IMD: + version: 1.2.2 + title: Index of Multiple Deprivation Data for the UK + maintainer: Matthew Gwynfryn Thomas + description: |- + Index of Multiple Deprivation for UK nations at various + geographical levels. In England, deprivation data is for Lower Layer Super + Output Areas, Middle Layer Super Output Areas, Wards, and Local Authorities + based on data from . + In Wales, deprivation data is for Lower Layer Super Output Areas, Middle + Layer Super Output Areas, Wards, and Local Authorities based on data from + . + In Scotland, deprivation data is for Data Zones, Intermediate Zones, and + Council Areas based on data from . In Northern Ireland, + deprivation data is for Super Output Areas and Local Government Districts + based on data from . + The 'IMD' package also provides the composite UK index developed by + . + date_publication: '2022-09-30' + bug_reports: https://github.com/humaniverse/IMD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IMD + url_git: https://github.com/humaniverse/IMD +imdbapi: + version: 0.1.0 + title: Get Movie, Television Data from the 'imdb' Database + maintainer: Yuan Li + description: |- + Provides API access to the which maintains metadata + about movies, games and television shows through a public API. + date_publication: '2018-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imdbapi + url_git: '' +IMEC: + version: 0.2.0 + title: Ising Model of Explanatory Coherence + maintainer: Maximilian Maier + description: |2- + + Theories are one of the most important tools of science. Although psychologists discussed problems of theory in their discipline for a long time, weak theories are still widespread in most subfields. + One possible reason for this is that psychologists lack the tools to systematically assess the quality of their theories. + Previously a computational model for formal theory evaluation based on the concept of explanatory coherence was developed (Thagard, 1989, ). + However, there are possible improvements to this model and it is not available in software that psychologists typically use. + Therefore, a new implementation of explanatory coherence based on the Ising model is available in this R-package. + date_publication: '2020-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IMEC + url_git: '' +iMediate: + version: 0.5.5 + title: Likelihood Methods for Mediation Analysis + maintainer: Kai Wang + description: Implements likelihood based methods for mediation analysis. + date_publication: '2019-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iMediate + url_git: '' +imf.data: + version: 0.1.7 + title: An Interface to IMF (International Monetary Fund) Data JSON API + maintainer: Pedro Baltazar + description: |- + A straightforward interface for accessing the IMF + (International Monetary Fund) data JSON API, + available at . This package offers direct access to + the primary API endpoints: Dataflow, DataStructure, and CompactData. + And, it provides an intuitive interface for exploring available + dimensions and attributes, as well as querying individual time-series datasets. + Additionally, the package implements a rate limit on API calls to reduce the + chances of exceeding service limits (limited to 10 calls every 5 seconds) + and encountering response errors. + date_publication: '2024-09-14' + bug_reports: https://github.com/pedrobtz/imf.data/issues + url: https://pedrobtz.github.io/imf.data/ + url_cran: https://CRAN.R-project.org/package=imf.data + url_git: '' +ImFoR: + version: 0.1.0 + title: Non-Linear Height Diameter Models for Forestry + maintainer: M. Iqbal Jeelani + description: Tree height is an important dendrometric variable and forms the basis + of vertical structure of a forest stand. This package will help to fit and validate + various non-linear height diameter models for assessing the underlying relationship + that exists between tree height and diameter at breast height in case of conifer + trees. This package has been implemented on Naslund, Curtis, Michailoff, Meyer, + Power, Michaelis-Menten and Wykoff non linear models using algorithm of Huang + et al. (1992) and Zeide et al. (1993) . + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImFoR + url_git: '' +imgpalr: + version: 0.4.0 + title: Create Color Palettes from Images + maintainer: Matthew Leonawicz + description: |- + Provides ability to create color palettes from image files. It + offers control over the type of color palette to derive from an image + (qualitative, sequential or divergent) and other palette properties. + Quantiles of an image color distribution can be trimmed. Near-black or + near-white colors can be trimmed in RGB color space independent of trimming + brightness or saturation distributions in HSV color space. Creating + sequential palettes also offers control over the order of HSV color + dimensions to sort by. This package differs from other related packages + like 'RImagePalette' in approaches to quantizing and extracting colors in + images to assemble color palettes and the level of user control over + palettes construction. + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/imgpalr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imgpalr + url_git: https://github.com/leonawicz/imgpalr +imgrec: + version: 0.1.4 + title: An Interface for Image Recognition + maintainer: Carsten Schwemmer + description: Provides an interface for image recognition using the 'Google Vision + API' . Converts API data for features such + as object detection and optical character recognition to data frames. The package + also includes functions for analyzing image annotations. + date_publication: '2024-06-21' + bug_reports: https://github.com/cschwem2er/imgrec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imgrec + url_git: https://github.com/cschwem2er/imgrec +imguR: + version: 1.0.3 + title: An Imgur.com API Client Package + maintainer: Thomas J. Leeper + description: A complete API client for the image hosting service Imgur.com, including + the an imgur graphics device, enabling the easy upload and sharing of plots. + date_publication: '2016-03-29' + bug_reports: https://github.com/leeper/imguR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imguR + url_git: https://github.com/leeper/imguR +ImHD: + version: 0.1.0 + title: |- + Artificial Intelligence Based Machine Learning Algorithms for + Height Diameter Relationships of Conifer Trees + maintainer: Dr. M. Iqbal Jeelani + description: Estimating height of forest plant is one of the key challenges of recent + times. This package will help to fit and validate AI (Artificial Intelligence) + based machine learning algorithms for estimation of height of conifer trees based + on diameter at breast height as explanatory variable using algorithm of Paul et + al. (2022) .. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImHD + url_git: '' +IMIFA: + version: 2.2.0 + title: |- + Infinite Mixtures of Infinite Factor Analysers and Related + Models + maintainer: Keefe Murphy + description: Provides flexible Bayesian estimation of Infinite Mixtures of Infinite + Factor Analysers and related models, for nonparametrically clustering high-dimensional + data, introduced by Murphy et al. (2020) . The IMIFA model + conducts Bayesian nonparametric model-based clustering with factor analytic covariance + structures without recourse to model selection criteria to choose the number of + clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. + Model-specific diagnostic tools are also provided, as well as many options for + plotting results, conducting posterior inference on parameters of interest, posterior + predictive checking, and quantifying uncertainty. + date_publication: '2023-12-12' + bug_reports: https://github.com/Keefe-Murphy/IMIFA + url: '' + url_cran: https://CRAN.R-project.org/package=IMIFA + url_git: '' +IMIX: + version: 1.1.5 + title: Gaussian Mixture Model for Multi-Omics Data Integration + maintainer: Ziqiao Wang + description: A multivariate Gaussian mixture model framework to integrate multiple + types of genomic data and allow modeling of inter-data-type correlations for association + analysis. 'IMIX' can be implemented to test whether a disease is associated with + genes in multiple genomic data types, such as DNA methylation, copy number variation, + gene expression, etc. It can also study the integration of multiple pathways. + 'IMIX' uses the summary statistics of association test outputs and conduct integration + analysis for two or three types of genomics data. 'IMIX' features statistically-principled + model selection, global FDR control and computational efficiency. Details are + described in Ziqiao Wang and Peng Wei (2020) . + date_publication: '2022-07-13' + bug_reports: https://github.com/ziqiaow/IMIX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IMIX + url_git: https://github.com/ziqiaow/IMIX +iml: + version: 0.11.4 + title: Interpretable Machine Learning + maintainer: Giuseppe Casalicchio + description: |- + Interpretability methods to analyze the behavior and + predictions of any machine learning model. Implemented methods are: + Feature importance described by Fisher et al. (2018) + , accumulated local effects plots described by Apley + (2018) , partial dependence plots described by + Friedman (2001) , individual conditional + expectation ('ice') plots described by Goldstein et al. (2013) + , local models (variant of 'lime') + described by Ribeiro et. al (2016) , the Shapley + Value described by Strumbelj et. al (2014) + , feature interactions described by + Friedman et. al and tree surrogate models. + date_publication: '2025-02-24' + bug_reports: https://github.com/giuseppec/iml/issues + url: https://giuseppec.github.io/iml/ + url_cran: https://CRAN.R-project.org/package=iml + url_git: https://github.com/giuseppec/iml/ +IMmailgun: + version: 0.1.2 + title: Send Emails using 'Mailgun' + maintainer: Ignacio Martinez + description: Send emails using the 'mailgun' api. To use this package you will need + an account from . + date_publication: '2018-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IMmailgun + url_git: '' +immcp: + version: 1.0.3 + title: |- + Poly-Pharmacology Toolkit for Traditional Chinese Medicine + Research + maintainer: Yuanlong Hu + description: |- + Toolkit for Poly-pharmacology Research of Traditional Chinese Medicine. Based on the + biological descriptors and drug-disease interaction networks, it can + analyze the potential poly-pharmacological mechanisms of Traditional Chinese Medicine and be + used for drug-repositioning in Traditional Chinese Medicine. + date_publication: '2022-05-12' + bug_reports: https://github.com/YuanlongHu/immcp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=immcp + url_git: https://github.com/YuanlongHu/immcp +immer: + version: 1.5-13 + title: Item Response Models for Multiple Ratings + maintainer: Alexander Robitzsch + description: |2- + + Implements some item response models for multiple + ratings, including the hierarchical rater model, + conditional maximum likelihood estimation of linear + logistic partial credit model and a wrapper function + to the commercial FACETS program. See Robitzsch and + Steinfeld (2018) for a description of the functionality + of the package. + See Wang, Su and Qiu (2014; ) + for an overview of modeling alternatives. + date_publication: '2024-03-21' + bug_reports: '' + url: https://sites.google.com/site/alexanderrobitzsch2/software + url_cran: https://CRAN.R-project.org/package=immer + url_git: https://github.com/alexanderrobitzsch/immer +Immigrate: + version: 0.2.1 + title: |- + Iterative Max-Min Entropy Margin-Maximization with Interaction + Terms for Feature Selection + maintainer: Ruzhang Zhao + description: 'Based on large margin principle, this package performs feature selection + methods: "IM4E"(Iterative Margin-Maximization under Max-Min Entropy Algorithm); + "Immigrate"(Iterative Max-Min Entropy Margin-Maximization with Interaction Terms + Algorithm); "BIM"(Boosted version of IMMIGRATE algorithm); "Simba"(Iterative Search + Margin Based Algorithm); "LFE"(Local Feature Extraction Algorithm). This package + also performs prediction for the above feature selection methods.' + date_publication: '2020-05-22' + bug_reports: '' + url: https://arxiv.org/abs/1810.02658 + url_cran: https://CRAN.R-project.org/package=Immigrate + url_git: https://github.com/RuzhangZhao/Immigrate/ +ImML: + version: 0.1.5 + title: Machine Learning Algorithms Fitting and Validation for Forestry + maintainer: Salvatore Mangiafico + description: |- + Fitting and validation of machine learning algorithms + for volume prediction of trees, currently for conifer trees based on + diameter at breast height and height as explanatory variables. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImML + url_git: '' +immunarch: + version: 0.9.1 + title: Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires + maintainer: Vadim I. Nazarov + description: |- + A comprehensive framework for bioinformatics exploratory analysis of bulk and single-cell + T-cell receptor and antibody repertoires. It provides seamless data loading, analysis and + visualisation for AIRR (Adaptive Immune Receptor Repertoire) data, both bulk immunosequencing (RepSeq) + and single-cell sequencing (scRNAseq). Immunarch implements most of the widely used AIRR analysis methods, + such as: clonality analysis, estimation of repertoire similarities in distribution of clonotypes + and gene segments, repertoire diversity analysis, annotation of clonotypes using external immune receptor + databases and clonotype tracking in vaccination and cancer studies. A successor to our + previously published 'tcR' immunoinformatics package (Nazarov 2015) . + date_publication: '2024-03-18' + bug_reports: https://github.com/immunomind/immunarch/issues + url: https://immunarch.com/ + url_cran: https://CRAN.R-project.org/package=immunarch + url_git: https://github.com/immunomind/immunarch +immunaut: + version: 1.0.1 + title: Machine Learning Immunogenicity and Vaccine Response Analysis + maintainer: Ivan Tomic + description: Used for analyzing immune responses and predicting vaccine efficacy + using machine learning and advanced data processing techniques. 'Immunaut' integrates + both unsupervised and supervised learning methods, managing outliers and capturing + immune response variability. It performs multiple rounds of predictive model testing + to identify robust immunogenicity signatures that can predict vaccine responsiveness. + The platform is designed to handle high-dimensional immune data, enabling researchers + to uncover immune predictors and refine personalized vaccination strategies across + diverse populations. + date_publication: '2024-10-25' + bug_reports: https://github.com/atomiclaboratory/immunaut/issues + url: + url_cran: https://CRAN.R-project.org/package=immunaut + url_git: https://github.com/atomiclaboratory/immunaut +immuneSIM: + version: 0.8.7 + title: Tunable Simulation of B- And T-Cell Receptor Repertoires + maintainer: Cédric R. Weber + description: |- + Simulate full B-cell and T-cell receptor repertoires using an in silico + recombination process that includes a wide variety of tunable parameters to introduce noise and biases. + Additional post-simulation modification functions allow the user to implant motifs or codon biases as + well as remodeling sequence similarity architecture. The output repertoires contain records of all + relevant repertoire dimensions and can be analyzed using provided repertoire analysis functions. + Preprint is available at bioRxiv (Weber et al., 2019 ). + date_publication: '2019-09-27' + bug_reports: https://github.com/GreiffLab/immuneSIM/issues + url: https://immuneSIM.readthedocs.io + url_cran: https://CRAN.R-project.org/package=immuneSIM + url_git: '' +Imneuron: + version: 0.1.0 + title: AI Powered Neural Network Solutions for Regression Tasks + maintainer: M Iqbal Jeelani + description: It offers a sophisticated and versatile tool for creating and evaluating + artificial intelligence based neural network models tailored for regression analysis + on datasets with continuous target variables. Leveraging the power of neural networks, + it allows users to experiment with various hidden neuron configurations across + two layers, optimizing model performance through "5 fold"" or "10 fold"" cross + validation. The package normalizes input data to ensure efficient training and + assesses model accuracy using key metrics such as R squared (R2), Root Mean Square + Error (RMSE), Mean Absolute Error (MAE), and Percentage Error (PER). By storing + and visualizing the best performing models, it provides a comprehensive solution + for precise and efficient regression modeling making it an invaluable tool for + data scientists and researchers aiming to harness AI for predictive analytics. + date_publication: '2024-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Imneuron + url_git: '' +ImNN: + version: 0.1.0 + title: Neural Networks for Predicting Volume of Forest Trees + maintainer: M. Iqbal Jeelani + description: 'Neural network has potential in forestry modelling. This package is + designed to create and assess Artificial Intelligence based Neural Networks with + varying architectures for prediction of volume of forest trees using two input + features: height and diameter at breast height, as they are the key factors in + predicting volume, therefore development and validation of efficient volume prediction + neural network model is necessary. This package has been developed using the algorithm + of Tabassum et al. (2022) .' + date_publication: '2023-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImNN + url_git: '' +imola: + version: 0.5.0 + title: CSS Layouts (Grid and Flexbox) Implementation for R/Shiny + maintainer: Pedro Silva + description: |- + Allows easy creation of CSS layouts (grid and flexbox) + directly from R without added CSS. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imola + url_git: https://github.com/pedrocoutinhosilva/imola +IMP: + version: '1.1' + title: Interactive Model Performance Evaluation + maintainer: Anup Nair + description: Contains functions for evaluating & comparing the performance of Binary + classification models. Functions can be called either statically or interactively + (as Shiny Apps). + date_publication: '2016-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IMP + url_git: https://github.com/anup50695/IMPPackage +imp4p: + version: '1.2' + title: Imputation for Proteomics + maintainer: Quentin Giai Gianetto + description: Functions to analyse missing value mechanisms and to impute data sets + in the context of bottom-up MS-based proteomics. + date_publication: '2021-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imp4p + url_git: '' +IMPACT: + version: 0.1.1 + title: The Impact of Items + maintainer: Nery Sofia Huerta-Pacheco + description: Implement a multivariate analysis of the impact of items to identify + a bias in the questionnaire validation of Likert-type scale variables. The items + requires considering a null value (category doesn't have tendency). Offering frequency, + importance and impact of the items. + date_publication: '2017-07-21' + bug_reports: '' + url: http://www.uv.mx/personal/nehuerta/impact + url_cran: https://CRAN.R-project.org/package=IMPACT + url_git: '' +ImpactEffectsize: + version: '0.7' + title: Calculation and Visualization of the Impact Effect Size Measure + maintainer: Jorn Lotsch + description: A non-parametric effect size measure capturing changes in central tendency + or shape of data distributions. The package provides the necessary functions to + calculate and plot the Impact effect size measure between two groups. + date_publication: '2024-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImpactEffectsize + url_git: '' +impactflu: + version: 0.1.0 + title: Quantification of Population-Level Impact of Vaccination + maintainer: Arseniy Khvorov + description: |2- + + Implements the compartment model from Tokars (2018) + . This enables quantification of + population-wide impact of vaccination against vaccine-preventable + diseases such as influenza. + date_publication: '2020-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=impactflu + url_git: '' +impactr: + version: 0.4.2 + title: Mechanical Loading Prediction Through Accelerometer Data + maintainer: Lucas Veras + description: |- + Functions to read, process and analyse accelerometer + data related to mechanical loading variables. This package is + developed and tested for use with raw accelerometer data from + triaxial 'ActiGraph' accelerometers. + date_publication: '2024-02-26' + bug_reports: https://github.com/verasls/impactr/issues/ + url: https://lveras.com/impactr/ + url_cran: https://CRAN.R-project.org/package=impactr + url_git: '' +impimp: + version: 0.3.1 + title: Imprecise Imputation for Statistical Matching + maintainer: Paul Fink + description: |- + Imputing blockwise missing data by imprecise imputation, + featuring a domain-based, variable-wise, and case-wise strategy. + Furthermore, the estimation of lower and upper bounds for + unconditional and conditional probabilities based on the obtained + imprecise data is implemented. + Additionally, two utility functions are supplied: one to check + whether variables in a data set contain set-valued observations; + and another to merge two already imprecisely imputed data. + The method is described in a technical report by Endres, Fink and + Augustin (2018, ). + date_publication: '2019-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=impimp + url_git: '' +implicitExpansion: + version: 0.1.0 + title: Array Operations for Arrays of Mismatching Sizes + maintainer: Manuel Hentschel + description: |- + Support for implicit expansion of arrays in operations involving + arrays of mismatching sizes. This pattern is known as "broadcasting" in + 'Python' and "implicit expansion" in 'Matlab' and is explained for example in + the article "Array programming with NumPy" by C. R. Harris et al. (2020) + . + date_publication: '2022-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=implicitExpansion + url_git: https://github.com/ManuelHentschel/implicitExpansion +implicitMeasures: + version: 0.2.1 + title: Compute Scores for Different Implicit Measures + maintainer: Ottavia M. Epifania + description: |- + A tool for computing the scores for the Implicit Association Test + (IAT; Greenwald, McGhee & Schwartz (1998) ) + and the Single Category-IAT (SC-IAT: Karpinski & Steinman + (2006) ). Functions for preparing the data + (both for the IAT and the SC-IAT), plotting the results, and obtaining a + table with the scores of implicit measures descriptive statistics are + provided. + date_publication: '2022-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=implicitMeasures + url_git: '' +implied: + version: '0.5' + title: Convert Between Bookmaker Odds and Probabilities + maintainer: Jonas Christoffer Lindstrøm + description: |- + Convert between bookmaker odds and probabilities. Eight different + algorithms are available, including basic normalization, Shin's method + (Hyun Song Shin, (1992) ), and others. + date_publication: '2023-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=implied + url_git: '' +implyr: + version: 0.5.0 + title: R Interface for Apache Impala + maintainer: Ian Cook + description: |- + 'SQL' back-end to 'dplyr' for Apache Impala, the massively + parallel processing query engine for Apache 'Hadoop'. Impala enables + low-latency 'SQL' queries on data stored in the 'Hadoop' Distributed + File System '(HDFS)', Apache 'HBase', Apache 'Kudu', Amazon Simple + Storage Service '(S3)', Microsoft Azure Data Lake Store '(ADLS)', + and Dell 'EMC' 'Isilon'. See for more + information about Impala. + date_publication: '2024-02-06' + bug_reports: https://github.com/ianmcook/implyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=implyr + url_git: https://github.com/ianmcook/implyr +import: + version: 1.3.2 + title: An Import Mechanism for R + maintainer: Magnus Thor Torfason + description: |- + Alternative mechanism for importing objects from packages + and R modules. The syntax allows for importing multiple objects with a single + command in an expressive way. The import package bridges some of the gap + between using library (or require) and direct (single-object) imports. + Furthermore the imported objects are not placed in the current environment. + date_publication: '2024-01-21' + bug_reports: https://github.com/rticulate/import/issues + url: '' + url_cran: https://CRAN.R-project.org/package=import + url_git: https://github.com/rticulate/import +ImportanceIndice: + version: 0.0.2 + title: |- + Analyzing Data Through of Percentage of Importance Indice and + Its Derivations + maintainer: Alcinei Mistico Azevedo + description: 'The Percentage of Importance Indice (Percentage_I.I.) bases in magnitudes, + frequencies, and distributions of occurrence of an event (DEMOLIN-LEITE, 2021) + . This index can + detect the key loss sources (L.S) and solution sources (S.S.), classifying them + according to their importance in terms of loss or income gain, on the productive + system. The Percentage_I.I. = [(ks1 x c1 x ds1)/SUM (ks1 x c1 x ds1) + (ks2 x + c2 x ds2) + (ksn x cn x dsn)] x 100. key source (ks) is obtained using simple + regression analysis and magnitude (abundance). Constancy (c) is SUM of occurrence + of L.S. or S.S. on the samples (absence = 0 or presence = 1), and distribution + source (ds) is obtained using chi-square test. This index has derivations: i.e., + i) Loss estimates and solutions effectiveness and ii) Attention and non-attention + levels (DEMOLIN-LEITE,2024) .' + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImportanceIndice + url_git: '' +importar: + version: 0.1.1 + title: |- + Enables Importing/Loading of Packages or Functions While + Creating an Alias for Them + maintainer: Andrea Cantieni + description: |- + Enables 'Python'-like importing/loading of packages or functions + with aliasing to prevent namespace conflicts. + date_publication: '2017-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=importar + url_git: https://github.com/andreaphsz/importar +ImportExport: + version: '1.3' + title: Import and Export Data + maintainer: Isaac Subirana + description: |- + Import and export data from the most common statistical formats by using + R functions that guarantee the least loss of the data information, giving special + attention to the date variables and the labelled ones. + date_publication: '2020-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImportExport + url_git: '' +importinegi: + version: 1.2.1 + title: Download and Manage Open Data from INEGI + maintainer: Cesar Renteria + description: Download and manage data sets of statistical projects and geographic + data created by Instituto Nacional de Estadistica y Geografia (INEGI). See . + date_publication: '2023-10-12' + bug_reports: https://github.com/crenteriam/importinegi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=importinegi + url_git: '' +imprecise101: + version: 0.2.2.4 + title: Introduction to Imprecise Probabilities + maintainer: Chel Hee Lee + description: An imprecise inference presented in the study of Walley (1996) + is one of the statistical reasoning methods when prior information is unavailable. + Functions and utils needed for illustrating this inferential paradigm are implemented + for classroom teaching and further comprehensive research. Two imprecise models + are demonstrated using multinomial data and 2x2 contingency table data. The concepts + of prior ignorance and imprecision are discussed in lower and upper probabilities. + Representation invariance principle, hypothesis testing, decision-making, and + further generalization are also illustrated. + date_publication: '2023-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imprecise101 + url_git: '' +impressionist.colors: + version: '1.0' + title: Impressionism's Color Palettes + maintainer: Federico Casale + description: Provides color palettes from Impressionism and post-Impressionism artworks. + This package allows to select colors combinations while looking at the original + paintings where colors were sampled from. + date_publication: '2020-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=impressionist.colors + url_git: '' +imprinting: + version: 0.1.1 + title: |- + Calculate Birth Year-Specific Probabilities of Immune Imprinting + to Influenza + maintainer: Alex Byrnes + description: Reconstruct birth-year specific probabilities of immune imprinting + to influenza A, using the methods of Gostic et al. (2016) . + Plot, save, or export the calculated probabilities for use in your own research. + By default, the package calculates subtype-specific imprinting probabilities, + but with user-provided frequency data, it is possible to calculate probabilities + for arbitrary kinds of primary exposure to influenza A, including primary vaccination + and exposure to specific clades, strains, etc. + date_publication: '2022-12-16' + bug_reports: https://github.com/cobeylab/imprinting/issues + url: https://cobeylab.github.io/imprinting/ + url_cran: https://CRAN.R-project.org/package=imprinting + url_git: '' +ImpShrinkage: + version: 1.0.0 + title: Improved Shrinkage Estimations for Multiple Linear Regression + maintainer: Mina Norouzirad + description: 'A variety of improved shrinkage estimators in the area of statistical + analysis: unrestricted; restricted; preliminary test; improved preliminary test; + Stein; and positive-rule Stein. More details can be found in chapter 7 of Saleh, + A. K. Md. E. (2006) .' + date_publication: '2023-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImpShrinkage + url_git: https://github.com/mnrzrad/ImpShrinkage +imptree: + version: 0.5.1 + title: Classification Trees with Imprecise Probabilities + maintainer: Paul Fink + description: |- + Creation of imprecise classification trees. They rely on + probability estimation within each node by means of either the + imprecise Dirichlet model or the nonparametric predictive + inference approach. The splitting variable is selected by the + strategy presented in Fink and Crossman (2013) + , + but also the original imprecise information gain of Abellan and + Moral (2003) is covered. + date_publication: '2018-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imptree + url_git: '' +imputeFin: + version: 0.1.2 + title: |- + Imputation of Financial Time Series with Missing Values and/or + Outliers + maintainer: Daniel P. Palomar + description: |- + Missing values often occur in financial data due to a variety + of reasons (errors in the collection process or in the processing stage, + lack of asset liquidity, lack of reporting of funds, etc.). However, + most data analysis methods expect complete data and cannot be employed + with missing values. One convenient way to deal with this issue without + having to redesign the data analysis method is to impute the missing + values. This package provides an efficient way to impute the missing + values based on modeling the time series with a random walk or an + autoregressive (AR) model, convenient to model log-prices and log-volumes + in financial data. In the current version, the imputation is + univariate-based (so no asset correlation is used). In addition, + outliers can be detected and removed. + The package is based on the paper: + J. Liu, S. Kumar, and D. P. Palomar (2019). Parameter Estimation of + Heavy-Tailed AR Model With Missing Data Via Stochastic EM. IEEE Trans. on + Signal Processing, vol. 67, no. 8, pp. 2159-2172. . + date_publication: '2021-02-20' + bug_reports: https://github.com/dppalomar/imputeFin/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=imputeFin + url_git: https://github.com/dppalomar/imputeFin +imputeGeneric: + version: 0.1.0 + title: Ease the Implementation of Imputation Methods + maintainer: Tobias Rockel + description: |- + The general workflow of most imputation methods is quite + similar. The aim of this package is to provide parts of this general + workflow to make the implementation of imputation methods easier. The + heart of an imputation method is normally the used model. These models + can be defined using the 'parsnip' package or customized + specifications. The rest of an imputation method are more technical + specification e.g. which columns and rows should be used for + imputation and in which order. These technical specifications can be + set inside the imputation functions. + date_publication: '2022-03-03' + bug_reports: https://github.com/torockel/imputeGeneric/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imputeGeneric + url_git: https://github.com/torockel/imputeGeneric +imputeLCMD: + version: '2.1' + title: |- + A Collection of Methods for Left-Censored Missing Data + Imputation + maintainer: Samuel Wieczorek + description: 'A collection of functions for left-censored missing data imputation. + Left-censoring is a special case of missing not at random (MNAR) mechanism that + generates non-responses in proteomics experiments. The package also contains functions + to artificially generate peptide/protein expression data (log-transformed) as + random draws from a multivariate Gaussian distribution as well as a function to + generate missing data (both randomly and non-randomly). For comparison reasons, + the package also contains several wrapper functions for the imputation of non-responses + that are missing at random. * New functionality has been added: a hybrid method + that allows the imputation of missing values in a more complex scenario where + the missing data are both MAR and MNAR.' + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imputeLCMD + url_git: '' +ImputeLongiCovs: + version: 0.1.0 + title: |- + Longitudinal Imputation of Categorical Variables via a Joint + Transition Model + maintainer: Pavlos Mamouris + description: Imputation of longitudinal categorical covariates. We use a methodological + framework which ensures that the plausibility of transitions is preserved, overfitting + and colinearity issues are resolved, and confounders can be utilized. See Mamouris + (2023) for an overview. + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImputeLongiCovs + url_git: '' +imputeMissings: + version: 0.0.4 + title: Impute Missing Values in a Predictive Context + maintainer: Michel Ballings + description: Compute missing values on a training data set and impute them on a + new data set. Current available options are median/mode and random forest. + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imputeMissings + url_git: '' +imputeMulti: + version: 0.8.4 + title: Imputation Methods for Multivariate Multinomial Data + maintainer: Alex Whitworth + description: |- + Implements imputation methods using EM and Data Augmentation for + multinomial data following the work of Schafer 1997 . + date_publication: '2023-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=imputeMulti + url_git: '' +imputeR: + version: '2.2' + title: A General Multivariate Imputation Framework + maintainer: Steffen Moritz + description: Multivariate Expectation-Maximization (EM) based imputation framework + that offers several different algorithms. These include regularisation methods + like Lasso and Ridge regression, tree-based models and dimensionality reduction + methods like PCA and PLS. + date_publication: '2020-01-20' + bug_reports: https://github.com/SteffenMoritz/imputeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imputeR + url_git: http://github.com/SteffenMoritz/imputeR +imputeREE: + version: 0.0.5 + title: Impute Missing Rare Earth Element Data in Zircon + maintainer: Carlos Carrasco Godoy + description: |- + Set of functions to impute missing rare earth data, calculate La + and Pr concentrations and Ce anomalies in zircons based on the + Chondrite-Onuma and Chondrite-Lattice of Carrasco-Godoy and + Campbell (2023) and the Logarithmic regression from + Zhong et al. (2019) . + date_publication: '2023-06-22' + bug_reports: https://github.com/cicarrascog/imputeREE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imputeREE + url_git: https://github.com/cicarrascog/imputeREE +ImputeRobust: + version: 1.3-1 + title: |- + Robust Multiple Imputation with Generalized Additive Models for + Location Scale and Shape + maintainer: Daniel Salfran + description: Provides new imputation methods for the 'mice' package based on generalized + additive models for location, scale, and shape (GAMLSS) as described in de Jong, + van Buuren and Spiess . + date_publication: '2018-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImputeRobust + url_git: '' +imputeTestbench: + version: 3.0.3 + title: Test Bench for the Comparison of Imputation Methods + maintainer: Marcus W. Beck + description: |- + Provides a test bench for the comparison of missing data imputation + methods in uni-variate time series. Imputation methods are compared using + different error metrics. Proposed imputation methods and alternative error + metrics can be used. + date_publication: '2019-07-05' + bug_reports: https://github.com/neerajdhanraj/imputeTestbench/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imputeTestbench + url_git: '' +imputeTS: + version: '3.3' + title: Time Series Missing Value Imputation + maintainer: Steffen Moritz + description: |- + Imputation (replacement) of missing values + in univariate time series. + Offers several imputation functions + and missing data plots. + Available imputation algorithms include: + 'Mean', 'LOCF', 'Interpolation', + 'Moving Average', 'Seasonal Decomposition', + 'Kalman Smoothing on Structural Time Series models', + 'Kalman Smoothing on ARIMA models'. Published in Moritz and Bartz-Beielstein (2017) + . + date_publication: '2022-09-09' + bug_reports: https://github.com/SteffenMoritz/imputeTS/issues + url: https://steffenmoritz.github.io/imputeTS/ + url_cran: https://CRAN.R-project.org/package=imputeTS + url_git: https://github.com/SteffenMoritz/imputeTS +iMRMC: + version: 2.1.0 + title: |- + Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and + Other Metrics) + maintainer: Brandon Gallas + description: 'This software does Multi-Reader, Multi-Case (MRMC) analyses of data + from imaging studies where clinicians (readers) evaluate patient images (cases). + What does this mean? ... Many imaging studies are designed so that every reader + reads every case in all modalities, a fully-crossed study. In this case, the data + is cross-correlated, and we consider the readers and cases to be cross-correlated + random effects. An MRMC analysis accounts for the variability and correlations + from the readers and cases when estimating variances, confidence intervals, and + p-values. The functions in this package can treat arbitrary study designs and + studies with missing data, not just fully-crossed study designs. An overview of + this software, including references presenting details on the methods, can be + found here: .' + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iMRMC + url_git: https://github.com/DIDSR/iMRMC +imsig: + version: 1.1.3 + title: |- + Immune Cell Gene Signatures for Profiling the Microenvironment + of Solid Tumours + maintainer: Ajit Johnson Nirmal + description: Estimate the relative abundance of tissue-infiltrating immune subpopulations + abundances using gene expression data. + date_publication: '2021-01-10' + bug_reports: https://github.com/ajitjohnson/imsig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imsig + url_git: https://github.com/ajitjohnson/imsig/ +imt: + version: 1.0.0 + title: Impact Measurement Toolkit + maintainer: Ignacio Martinez + description: |- + A toolkit for causal inference in experimental and observational + studies. Implements various simple Bayesian models including linear, + negative binomial, and logistic regression for impact estimation. + Provides functionality for randomization and checking baseline equivalence + in experimental designs. The package aims to simplify the process of + impact measurement for researchers and analysts across different fields. + Examples and detailed usage instructions are available at + . + date_publication: '2024-09-02' + bug_reports: https://github.com/google/imt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=imt + url_git: https://github.com/google/imt +IMTest: + version: 1.0.0 + title: Information Matrix Test for Generalized Partial Credit Models + maintainer: Daphna Harel + description: Implementation of the information matrix test for generalized partial + credit models. + date_publication: '2017-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IMTest + url_git: '' +imuf: + version: 0.6.0 + title: Estimate Orientation of an Inertial Measurement Unit + maintainer: Felix Chan + description: |- + Estimate the orientation of an inertial measurement unit + (IMU) with a 3-axis accelerometer and a 3-axis gyroscope using a + complementary filter. 'imuf' takes an IMU's accelerometer and gyroscope + readings, time duration, its initial orientation, and a gain factor as + inputs, and returns an estimate of the IMU's final orientation. + date_publication: '2025-02-12' + bug_reports: https://github.com/gitboosting/imuf/issues + url: https://gitboosting.github.io/imuf/ + url_cran: https://CRAN.R-project.org/package=imuf + url_git: https://github.com/gitboosting/imuf +ImVol: + version: 0.1.0 + title: |- + Volume Prediction of Trees Using Linear and Nonlinear Allometric + Equations + maintainer: M. Iqbal Jeelani + description: Volume prediction is one of challenging task in forestry research. + This package is a comprehensive toolset designed for the fitting and validation + of various linear and nonlinear allometric equations (Linear, Log-Linear, Inverse, + Quadratic, Cubic, Compound, Power and Exponential) used in the prediction of conifer + tree volume. This package is particularly useful for forestry professionals, researchers, + and resource managers engaged in assessing and estimating the volume of coniferous + trees. This package has been developed using the algorithm of Sharma et al. (2017) + . + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ImVol + url_git: '' +in2extRemes: + version: 1.0-3 + title: Into the extRemes Package + maintainer: Eric Gilleland + description: Graphical User Interface (GUI) to some of the functions in the package + extRemes version >= 2.0 are included. + date_publication: '2016-10-14' + bug_reports: '' + url: http://www.assessment.ucar.edu/toolkit/ + url_cran: https://CRAN.R-project.org/package=in2extRemes + url_git: '' +inaparc: + version: 1.2.0 + title: Initialization Algorithms for Partitioning Cluster Analysis + maintainer: Zeynel Cebeci + description: Partitioning clustering algorithms divide data sets into k subsets + or partitions so-called clusters. They require some initialization procedures + for starting the algorithms. Initialization of cluster prototypes is one of such + kind of procedures for most of the partitioning algorithms. Cluster prototypes + are the centers of clusters, i.e. centroids or medoids, representing the clusters + in a data set. In order to initialize cluster prototypes, the package 'inaparc' + contains a set of the functions that are the implementations of several linear + time-complexity and loglinear time-complexity methods in addition to some novel + techniques. Initialization of fuzzy membership degrees matrices is another important + task for starting the probabilistic and possibilistic partitioning algorithms. + In order to initialize membership degrees matrices required by these algorithms, + a number of functions based on some traditional and novel initialization techniques + are also available in the package 'inaparc'. + date_publication: '2022-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inaparc + url_git: '' +inbreedR: + version: 0.3.3 + title: Analysing Inbreeding Based on Genetic Markers + maintainer: Martin A. Stoffel + description: |- + A framework for analysing inbreeding and heterozygosity-fitness + correlations (HFCs) based on microsatellite and SNP markers. + date_publication: '2022-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inbreedR + url_git: '' +inca: + version: 0.0.4 + title: Integer Calibration + maintainer: Luca Sartore + description: Specific functions are provided for rounding real weights to integers + and performing an integer programming algorithm for calibration problems. They + are useful for census-weights adjustments, or for performing linear regression + with integer parameters. This research was supported in part by the U.S. Department + of Agriculture, National Agriculture Statistics Service. The findings and conclusions + in this publication are those of the authors and should not be construed to represent + any official USDA, or US Government determination or policy. + date_publication: '2019-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inca + url_git: '' +incase: + version: 0.3.2 + title: Pipe-Friendly Vector Replacement with Case Statements + maintainer: Alexander Rossell Hayes + description: |- + Offers a pipe-friendly alternative to the 'dplyr' functions + case_when() and if_else(), as well as a number of user-friendly + simplifications for common use cases. These functions accept a vector + as an optional first argument, allowing conditional statements to be + built using the 'magrittr' dot operator. The functions also coerce + all outputs to the same type, meaning you no longer have to worry + about using specific typed variants of NA or explicitly declaring + integer outputs, and evaluate outputs somewhat lazily, so you don't + waste time on long operations that won't be used. + date_publication: '2023-08-21' + bug_reports: https://github.com/rossellhayes/incase/issues + url: https://pkg.rossellhayes.com/incase/ + url_cran: https://CRAN.R-project.org/package=incase + url_git: https://github.com/rossellhayes/incase +INCATome: + version: '1.0' + title: Internal Control Analysis of Translatome Studies by Microarrays + maintainer: Thomas Sbarrato + description: Data analysis, normalisation and differential expression for Translatome + studies by microarrays (T Sbarrato et al. RNA. 2017 Aug 25; ). + date_publication: '2017-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=INCATome + url_git: '' +IncDTW: + version: 1.1.4.4 + title: Incremental Calculation of Dynamic Time Warping + maintainer: Maximilian Leodolter + description: 'The Dynamic Time Warping (DTW) distance measure for time series allows + non-linear alignments of time series to match similar patterns in time series + of different lengths and or different speeds. IncDTW is characterized by (1) the + incremental calculation of DTW (reduces runtime complexity to a linear level for + updating the DTW distance) - especially for life data streams or subsequence matching, + (2) the vector based implementation of DTW which is faster because no matrices + are allocated (reduces the space complexity from a quadratic to a linear level + in the number of observations) - for all runtime intensive DTW computations, (3) + the subsequence matching algorithm runDTW, that efficiently finds the k-NN to + a query pattern in a long time series, and (4) C++ in the heart. For details about + DTW see the original paper "Dynamic programming algorithm optimization for spoken + word recognition" by Sakoe and Chiba (1978) . + For details about this package, Dynamic Time Warping and Incremental Dynamic Time + Warping please see "IncDTW: An R Package for Incremental Calculation of Dynamic + Time Warping" by Leodolter et al. (2021) .' + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IncDTW + url_git: '' +incgraph: + version: 1.0.1 + title: Incremental Graphlet Counting for Network Optimisation + maintainer: Robrecht Cannoodt + description: |- + An efficient and incremental approach for calculating + the differences in orbit counts when performing single edge modifications + in a network. Calculating the differences in orbit counts is much more efficient than + recalculating all orbit counts from scratch for each time point. + date_publication: '2017-10-12' + bug_reports: https://github.com/rcannood/incgraph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=incgraph + url_git: http://www.github.com/rcannood/incgraph +incidence: + version: 1.7.5 + title: Compute, Handle, Plot and Model Incidence of Dated Events + maintainer: Tim Taylor + description: |- + Provides functions and classes to compute, handle and visualise + incidence from dated events for a defined time interval. Dates can be provided + in various standard formats. The class 'incidence' is used to store computed + incidence and can be easily manipulated, subsetted, and plotted. In addition, + log-linear models can be fitted to 'incidence' objects using 'fit'. This + package is part of the RECON () toolkit + for outbreak analysis. + date_publication: '2024-05-31' + bug_reports: https://github.com/reconhub/incidence/issues + url: https://www.repidemicsconsortium.org/incidence/ + url_cran: https://CRAN.R-project.org/package=incidence + url_git: '' +incidence2: + version: 2.6.0 + title: Compute, Handle and Plot Incidence of Dated Events + maintainer: Tim Taylor + description: |- + Provides functions and classes to compute, handle and visualise + incidence from dated events for a defined time interval. Dates can be + provided in various standard formats. The class 'incidence2' is used to store + computed incidence and can be easily manipulated, subsetted, and plotted. + This package is part of the RECON () + toolkit for outbreak analysis (). + date_publication: '2024-11-22' + bug_reports: https://github.com/reconverse/incidence2/issues + url: https://www.reconverse.org/incidence2/ + url_cran: https://CRAN.R-project.org/package=incidence2 + url_git: https://github.com/reconverse/incidence2 +IncidencePrevalence: + version: 1.1.0 + title: |- + Estimate Incidence and Prevalence using the OMOP Common Data + Model + maintainer: Edward Burn + description: Calculate incidence and prevalence using data mapped to the Observational + Medical Outcomes Partnership (OMOP) common data model. Incidence and prevalence + can be estimated for the total population in a database or for a stratification + cohort. + date_publication: '2025-02-20' + bug_reports: '' + url: https://darwin-eu.github.io/IncidencePrevalence/ + url_cran: https://CRAN.R-project.org/package=IncidencePrevalence + url_git: '' +incidental: + version: '0.1' + title: Implements Empirical Bayes Incidence Curves + maintainer: Lauren Hannah + description: Make empirical Bayes incidence curves from reported case data using + a specified delay distribution. + date_publication: '2020-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=incidental + url_git: '' +incidentally: + version: 1.0.2 + title: Generates Incidence Matrices and Bipartite Graphs + maintainer: Zachary Neal + description: Functions to generate incidence matrices and bipartite graphs that + have (1) a fixed fill rate, (2) given marginal sums, (3) marginal sums that follow + given distributions, or (4) represent bill sponsorships in the US Congress . + It can also generate an incidence matrix from an adjacency matrix, or bipartite + graph from a unipartite graph, via a social process mirroring team, group, or + organization formation . + date_publication: '2023-02-15' + bug_reports: https://github.com/zpneal/incidentally/issues + url: https://www.zacharyneal.com/backbone + url_cran: https://CRAN.R-project.org/package=incidentally + url_git: https://github.com/zpneal/incidentally +IncomPair: + version: 0.1.0 + title: Comparison of Means for the Incomplete Paired Data + maintainer: Desale Habtzghi + description: |- + Implements a variety of nonparametric and parametric methods that are commonly used when the data set is a mixture of paired observations and independent samples. The package also calculates and returns values of different tests with their corresponding p-values. + Bhoj, D. S. (1991) "Testing equality of means in the presence of correlation and missing data". + Dubnicka, S. R., Blair, R. C., and Hettmansperger, T. P. (2002) "Rank-based procedures for mixed paired and two-sample designs". + Einsporn, R. L. and Habtzghi, D. (2013) "Combining paired and two-sample data using a permutation test". + Ekbohm, G. (1976) "On comparing means in the paired case with incomplete data on both responses". + Lin, P. E. and Stivers, L. E. (1974) On difference of means with incomplete data". + Maritz, J. S. (1995) "A permutation paired test allowing for missing values". + date_publication: '2020-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IncomPair + url_git: '' +incR: + version: 2.1.0 + title: Analysis of Incubation Data + maintainer: Pablo Capilla-Lasheras + description: |- + Suite of functions to study animal incubation. + At the core of incR + lies an algorithm that allows for the scoring of + incubation behaviour. Additionally, several functions + extract biologically relevant metrics of incubation such as off-bout number + and off-bout duration - for a review of avian incubation studies, + see Nests, Eggs, and Incubation: New ideas about avian reproduction (2015) + edited by D. Charles Deeming and S. James Reynolds . + date_publication: '2023-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=incR + url_git: '' +inctools: + version: 1.0.15 + title: Incidence Estimation Tools + maintainer: Eduard Grebe + description: |- + Tools for estimating incidence from biomarker data in cross- + sectional surveys, and for calibrating tests for recent infection. + Implements and extends the method of Kassanjee et al. (2012) + . + date_publication: '2019-11-07' + bug_reports: https://github.com/SACEMA/inctools/issues + url: http://www.incidence-estimation.org/page/inctools + url_cran: https://CRAN.R-project.org/package=inctools + url_git: '' +incubate: + version: 1.3.0 + title: |- + Parametric Time-to-Event Analysis with Variable Incubation + Phases + maintainer: Matthias Kuhn + description: |- + Fit parametric models for time-to-event data that show an initial + 'incubation period', i.e., a variable delay phase where the hazard is zero. The + delayed Weibull distribution serves as foundational data model. The + specific method of 'MPSE' (maximum product of spacings estimation) and MLE-based methods are used for parameter + estimation. Bootstrap confidence intervals for parameters and significance + tests in a two group setting are provided. + date_publication: '2024-08-16' + bug_reports: https://gitlab.com/imb-dev/incubate/-/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=incubate + url_git: https://gitlab.com/imb-dev/incubate/ +indelmiss: + version: 1.0.10 + title: |- + Insertion Deletion Analysis While Accounting for Possible + Missing Data + maintainer: Utkarsh J. Dang + description: |- + Genome-wide gene insertion and deletion rates can be modelled in a maximum + likelihood framework with the additional flexibility of modelling potential missing + data using the models included within. These models simultaneously estimate insertion + and deletion (indel) rates of gene families and proportions of "missing" data for + (multiple) taxa of interest. The likelihood framework is utilized for parameter + estimation. A phylogenetic tree of the taxa and gene presence/absence patterns + (with data ordered by the tips of the tree) are required. See Dang et al. + (2016) for more details. + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=indelmiss + url_git: '' +independenceWeights: + version: 0.0.1 + title: |- + Estimates Weights for Confounding Control for Continuous-Valued + Exposures + maintainer: Jared Huling + description: Estimates weights to make a continuous-valued exposure statistically + independent of a vector of pre-treatment covariates using the method proposed + in Huling, Greifer, and Chen (2021) . + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=independenceWeights + url_git: '' +IndepTest: + version: 0.2.0 + title: Nonparametric Independence Tests Based on Entropy Estimation + maintainer: Daniel Grose + description: Implementations of the weighted Kozachenko-Leonenko entropy estimator + and independence tests based on this estimator, (Kozachenko and Leonenko (1987) + ). Also includes a goodness-of-fit test for a + linear model which is an independence test between covariates and errors. + date_publication: '2018-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IndepTest + url_git: '' +index0: + version: 0.0.1 + title: Zero-Based Indexing in R + maintainer: David Antony Selby + description: Extract and replace elements using indices that start from zero (rather + than one), as is common in mathematical notation and other programming languages. + date_publication: '2021-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=index0 + url_git: '' +IndexConstruction: + version: 0.1-3 + title: Index Construction for Time Series Data + maintainer: Simon Trimborn + description: Derivation of indexes for benchmarking purposes. A methodology with + flexible number of constituents is implemented. Also functions for market capitalization + and volume weighted indexes with fixed number of constituents are available. The + main function of the package, indexComp(), provides the derived index, suitable + for analysis purposes. The functions indexUpdate(), indexMemberSelection() and + indexMembersUpdate() are components of indexComp() and enable one to construct + and continuously update an index, e.g. for display on a website. The methodology + behind the functions provided gets introduced in Trimborn and Haerdle (2018) . + date_publication: '2020-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IndexConstruction + url_git: '' +IndexNumber: + version: 1.3.2 + title: Index Numbers in Social Sciences + maintainer: Alejandro Saavedra-Nieves + description: We provide an R tool for teaching in Social Sciences. It allows the + computation of index numbers. It is a measure of the evolution of a fixed magnitude + for only a product of for several products. It is very useful in Social Sciences. + Among others, we obtain simple index numbers (in chain or in serie), index numbers + for not only a product or weighted index numbers as the Laspeyres index (Laspeyres, + 1864), the Paasche index (Paasche, 1874) or the Fisher index (Lapedes, 1978). + date_publication: '2021-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IndexNumber + url_git: '' +IndexNumR: + version: 0.6.0 + title: Index Number Calculation + maintainer: Graham White + description: |- + Computes bilateral and multilateral index numbers. + It has support for many standard bilateral indexes as well as + multilateral index number methods such as GEKS, GEKS-Tornqvist + (or CCDI), Geary-Khamis and the weighted time product dummy + (for details on these methods see Diewert and Fox (2020) + ). + It also supports updating of multilateral indexes using + several splicing methods. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IndexNumR + url_git: https://github.com/grahamjwhite/IndexNumR +indexr: + version: 0.2.2 + title: A Thoughtful Saver of Results + maintainer: Logan Harris + description: |- + Helps with the thoughtful saving, reading, and management of result + files (using 'rds' files). The core functions take a list of parameters that are + used to generate a unique hash to save results under. Then, the same + parameter list can be used to read those results back in. This + is helpful to avoid clunky file naming when running a large number of + simulations. Additionally, helper functions are available for compiling a flat + file of parameters of saved results, monitoring result usage, and cleaning up + unwanted or unused results. For more information, visit the 'indexr' homepage + . + date_publication: '2025-02-17' + bug_reports: https://github.com/lharris421/indexr/issues + url: https://lharris421.github.io/indexr/ + url_cran: https://CRAN.R-project.org/package=indexr + url_git: https://github.com/lharris421/indexr +indexthis: + version: 1.0.1 + title: Quick Indexation + maintainer: Laurent Berge + description: Quick indexation of any type of vector or of any combination of those. + Indexation turns a vector into an integer vector going from 1 to the number of + unique elements. Indexes are important building blocks for many algorithms. The + method is described at . + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=indexthis + url_git: https://github.com/lrberge/indexthis +IndexWizard: + version: 0.2.1.0 + title: Constructing and Analyzing Complex Selection Indices + maintainer: Johannes Geibel + description: Allows the construction selection indices based on estimated breeding + values in animal and plant breeding and to calculate several analytic measures + around to assess its impact on genetic and phenotypic progress. The methodology + thereby allows to analyze genetic gain of traits in the breeding goal which are + not part of the actual index and automatically computes several analytic measures. + It further allows to retrospectively derive realized economic weights from observed + genetic trends. The framework is described in Simianer, H., Heise, J., Rensing, + S., Pook, T. Geibel, J. and Reimer, C. (2023) . + date_publication: '2023-06-16' + bug_reports: https://github.com/johannesgeibel/IndexWizard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IndexWizard + url_git: https://github.com/johannesgeibel/IndexWizard +IndGenErrors: + version: 0.1.6 + title: |- + Tests of Independence Between Innovations of Generalized Error + Models + maintainer: Bruno N Remillard + description: Computation of test statistics of independence between (continuous) + innovations of time series. They can be used with stochastic volatility models + and Hidden Markov Models (HMM). This improves the results in Duchesne, Ghoudi + & Remillard (2012) . + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IndGenErrors + url_git: '' +india: + version: '0.1' + title: Influence Diagnostics in Statistical Models + maintainer: Felipe Osorio + description: |- + Set of routines for influence diagnostics by using case-deletion in ordinary least + squares, ridge estimation [Walker and Birch (1988). ] and + least absolute deviations (LAD) regression [Sun and Wei (2004). ]. + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=india + url_git: '' +Indicator: + version: 0.1.3 + title: Composite 'Indicator' Construction and Imputation Data + maintainer: Gianmarco Borrata + description: 'Different functions includes constructing composite indicators, imputing + missing data, and evaluating imputation techniques. Additionally, different tools + for data normalization. Detailed methodologies of ''Indicator'' package are: + OECD/European Union/EC-JRC (2008), "Handbook on Constructing Composite Indicators: + Methodology and User Guide", OECD Publishing, Paris, , + Matteo Mazziotta & Adriano Pareto, (2018) "Measuring Well-Being Over Time: The + Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices" + and De Muro P., Mazziotta M., Pareto A. (2011), "Composite Indices of Development + and Poverty: An Application to MDGs" .' + date_publication: '2024-11-27' + bug_reports: https://github.com/GianmarcoBorrata/Indicator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Indicator + url_git: https://github.com/GianmarcoBorrata/Indicator +indicspecies: + version: 1.8.0 + title: Relationship Between Species and Groups of Sites + maintainer: Miquel De Cáceres + description: Functions to assess the strength and statistical significance of the + relationship between species occurrence/abundance and groups of sites [De Caceres + & Legendre (2009) ]. Also includes functions to measure + species niche breadth using resource categories [De Caceres et al. (2011) ]. + date_publication: '2025-02-20' + bug_reports: https://github.com/emf-creaf/indicspecies/issues + url: https://emf-creaf.github.io/indicspecies/ + url_cran: https://CRAN.R-project.org/package=indicspecies + url_git: '' +indiedown: + version: 0.1.1 + title: Individual R Markdown Templates + maintainer: Christoph Sax + description: |- + Simplifies the generation of customized R Markdown PDF templates. + A template may include an individual logo, typography, geometry or color + scheme. The package provides a skeleton with detailed instructions for + customizations. The skeleton can be modified by changing defaults in the + 'YAML' header, by adding additional 'LaTeX' commands or by applying dynamic + adjustments in R. Individual corporate design elements, such as a title page, can be added as R functions that produce 'LaTeX' code. + date_publication: '2021-03-22' + bug_reports: https://github.com/cynkra/indiedown/issues + url: https://cynkra.github.io/indiedown/ + url_cran: https://CRAN.R-project.org/package=indiedown + url_git: https://github.com/cynkra/indiedown +indirect: + version: 0.2.1 + title: |- + Elicitation of Independent Conditional Means Priors for + Generalised Linear Models + maintainer: Geoff Hosack + description: Functions are provided to facilitate prior elicitation for Bayesian + generalised linear models using independent conditional means priors. The package + supports the elicitation of multivariate normal priors for generalised linear + models. The approach can be applied to indirect elicitation for a generalised + linear model that is linear in the parameters. The package is designed such that + the facilitator executes functions within the R console during the elicitation + session to provide graphical and numerical feedback at each design point. Various + methodologies for eliciting fractiles (equivalently, percentiles or quantiles) + are supported, including versions of the approach of Hosack et al. (2017) . + For example, experts may be asked to provide central credible intervals that correspond + to a certain probability. Or experts may be allowed to vary the probability allocated + to the central credible interval for each design point. Additionally, a median + may or may not be elicited. + date_publication: '2022-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=indirect + url_git: '' +InDisc: + version: 1.1.0 + title: |- + Obtaining and Estimating Unidimensional and Multidimensional IRT + Dual Models + maintainer: David Navarro-Gonzalez + description: |- + Performs a unified approach for obtaining and estimating + unidimensional and multidimensional Item Response Theory (IRT) + Dual Models (DMs), proposed by Ferrando (2019 ). + date_publication: '2021-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InDisc + url_git: '' +IndTestPP: + version: '3.0' + title: |- + Tests of Independence and Analysis of Dependence Between Point + Processes in Time + maintainer: Ana C. Cebrian + description: It provides a general framework to analyse dependence between point + processes in time. It includes parametric and non-parametric tests to study independence, and + functions for generating and analysing different types of dependence. + date_publication: '2020-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IndTestPP + url_git: '' +industRial: + version: 0.1.0 + title: |- + Data, Functions and Support Materials from the Book "industRial + Data Science" + maintainer: Joao Ramalho + description: |- + Companion package to the book "industRial data science", + J.Ramalho (2021) . + Provides data sets and functions to complete the case studies and contains + the book original Rmd files and tutorials. + date_publication: '2021-06-11' + bug_reports: https://github.com/J-Ramalho/industRial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=industRial + url_git: https://github.com/J-Ramalho/industRial +ineAtlas: + version: 0.1.3 + title: Access to Spanish Household Income Distribution Atlas Data + maintainer: Pablo García Guzmán + description: |- + Provides access to granular socioeconomic indicators from the + Spanish Statistical Office (INE) Household Income Distribution Atlas. + The package downloads and processes data from a companion 'GitHub' + repository () which contains + processed versions of the official INE Atlas data. Functions are + provided to fetch data at multiple geographic levels (municipalities, + districts, and census tracts), including income indicators, + demographic characteristics, and inequality metrics. The data + repository is updated every year when new releases are published by + INE. + date_publication: '2024-11-30' + bug_reports: https://github.com/pablogguz/ineAtlas/issues + url: https://pablogguz.github.io/ineAtlas/ + url_cran: https://CRAN.R-project.org/package=ineAtlas + url_git: https://github.com/pablogguz/ineAtlas +inegiR: + version: 3.0.0 + title: Integrate INEGI’s (Mexican Stats Office) API with R + maintainer: Eduardo Flores + description: |- + Provides functions to download and parse information from INEGI + (Official Mexican statistics agency). To learn more about the API, see . + date_publication: '2019-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inegiR + url_git: '' +ineq: + version: 0.2-13 + title: Measuring Inequality, Concentration, and Poverty + maintainer: Achim Zeileis + description: Inequality, concentration, and poverty measures. Lorenz curves (empirical + and theoretical). + date_publication: '2014-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ineq + url_git: '' +ineq.2d: + version: 0.1.0 + title: |- + Two-Dimensional Decomposition of the Theil Index and the Squared + Coefficient of Variation + maintainer: Ivan Skliarov + description: |- + Decomposition of income inequality by groups formed of individuals + possessing similar characteristics (e.g., sex, education, age) and their + income sources at the same time. + Decomposition of the Theil index is based on Giammatteo, M. (2007) + . + Decomposition of the squared coefficient of variation is based on + Garcia-Penalosa, C., & Orgiazzi, E. (2013) . + date_publication: '2023-06-02' + bug_reports: https://github.com/sklivan/ineq.2d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ineq.2d + url_git: https://github.com/sklivan/ineq.2d +ineqJD: + version: '1.0' + title: Inequality Joint Decomposition + maintainer: Alberto Arcagni + description: 'Computes and decomposes Gini, Bonferroni and Zenga 2007 point and + synthetic concentration indexes. Decompositions are intended: by sources, by subpopulations + and by sources and subpopulations jointly. References, Zenga M. M.(2007) + Zenga M. (2015) Zenga M., Valli I. (2017) + Zenga M., Valli I. (2018) .' + date_publication: '2019-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ineqJD + url_git: '' +inet: + version: 0.1.0 + title: Performing Inference on Networks with Regularization + maintainer: Jonas Haslbeck + description: Performs inference with the lasso in Gaussian Graphical Models. The + package consists of wrappers for functions from the 'hdi' package. + date_publication: '2022-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inet + url_git: '' +iNEXT: + version: 3.0.1 + title: Interpolation and Extrapolation for Species Diversity + maintainer: T. C. Hsieh + description: |- + Provides simple functions to compute and plot two types + (sample-size- and coverage-based) rarefaction and extrapolation curves for species + diversity (Hill numbers) based on individual-based abundance data or sampling-unit- + based incidence data; see Chao and others (2014, Ecological Monographs) for pertinent + theory and methodologies, and Hsieh, Ma and Chao (2016, Methods in Ecology and Evolution) + for an introduction of the R package. + date_publication: '2024-03-24' + bug_reports: https://github.com/JohnsonHsieh/iNEXT/issues + url: http://chao.stat.nthu.edu.tw/wordpress/software_download/ + url_cran: https://CRAN.R-project.org/package=iNEXT + url_git: '' +iNEXT.3D: + version: 1.0.8 + title: |- + Interpolation and Extrapolation for Three Dimensions of + Biodiversity + maintainer: Anne Chao + description: |- + Biodiversity is a multifaceted concept covering different levels of organization from + genes to ecosystems. 'iNEXT.3D' extends 'iNEXT' to include three dimensions (3D) + of biodiversity, i.e., taxonomic diversity (TD), phylogenetic diversity (PD) and functional + diversity (FD). This package provides functions to compute standardized 3D diversity estimates + with a common sample size or sample coverage. A unified framework based on Hill numbers + and their generalizations (Hill-Chao numbers) are used to quantify 3D. All 3D estimates + are in the same units of species/lineage equivalents and can be meaningfully compared. + The package features size- and coverage-based rarefaction and extrapolation sampling + curves to facilitate rigorous comparison of 3D diversity across individual assemblages. + Asymptotic 3D diversity estimates are also provided. See Chao et al. (2021) + for more details. + date_publication: '2025-02-18' + bug_reports: https://github.com/AnneChao/iNEXT.3D/issues + url: https://sites.google.com/view/chao-lab-website/software/inext-3d + url_cran: https://CRAN.R-project.org/package=iNEXT.3D + url_git: '' +iNEXT.4steps: + version: 1.0.1 + title: Four-Step Biodiversity Analysis Based on 'iNEXT' + maintainer: Anne Chao + description: |- + Expands 'iNEXT' to include the estimation of sample completeness and evenness. The package provides simple functions to perform the following four-step biodiversity analysis: + STEP 1: Assessment of sample completeness profiles. + STEP 2a: Analysis of size-based rarefaction and extrapolation sampling curves to + determine whether the asymptotic diversity can be accurately estimated. + STEP 2b: Comparison of the observed and the estimated asymptotic diversity profiles. + STEP 3: Analysis of non-asymptotic coverage-based rarefaction and extrapolation sampling curves. + STEP 4: Assessment of evenness profiles. + The analyses in STEPs 2a, 2b and STEP 3 are mainly based on the previous 'iNEXT' package. Refer to the 'iNEXT' package for details. This package is mainly focusing on the computation for STEPs 1 and 4. See Chao et al. (2020) for statistical background. + date_publication: '2024-06-18' + bug_reports: https://github.com/KaiHsiangHu/iNEXT.4steps/issues + url: https://sites.google.com/view/chao-lab-website/software/inext-4steps/ + url_cran: https://CRAN.R-project.org/package=iNEXT.4steps + url_git: '' +iNEXT.beta3D: + version: 1.0.2 + title: |- + Interpolation and Extrapolation with Beta Diversity for Three + Dimensions of Biodiversity + maintainer: Anne Chao + description: |- + As a sequel to 'iNEXT', the 'iNEXT.beta3D' package provides functions to compute + standardized taxonomic, phylogenetic, and functional diversity (3D) estimates + with a common sample size (for alpha and gamma diversity) or sample coverage + (for alpha, beta, gamma diversity as well as dissimilarity or turnover indices). + Hill numbers and their generalizations are used to quantify 3D and to make + multiplicative decomposition (gamma = alpha x beta). The package also features + size- and coverage-based rarefaction and extrapolation sampling curves to + facilitate rigorous comparison of beta diversity across datasets. + See Chao et al. (2023) for more details. + date_publication: '2024-04-17' + bug_reports: https://github.com/AnneChao/iNEXT.beta3D/issues + url: https://sites.google.com/view/chao-lab-website/software/inext-beta3d + url_cran: https://CRAN.R-project.org/package=iNEXT.beta3D + url_git: '' +infer: + version: 1.0.7 + title: Tidy Statistical Inference + maintainer: Simon Couch + description: |- + The objective of this package is to perform inference using + an expressive statistical grammar that coheres with the tidy design + framework. + date_publication: '2024-03-25' + bug_reports: https://github.com/tidymodels/infer/issues + url: https://infer.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=infer + url_git: https://github.com/tidymodels/infer +inferCSN: + version: 1.0.8 + title: Inferring Cell-Specific Gene Regulatory Network + maintainer: Meng Xu + description: An R package for inferring cell-type specific gene regulatory network + from single-cell RNA data. + date_publication: '2024-08-24' + bug_reports: https://github.com/mengxu98/inferCSN/issues + url: https://mengxu98.github.io/inferCSN/ + url_cran: https://CRAN.R-project.org/package=inferCSN + url_git: '' +InferenceSMR: + version: 1.0.2 + title: |- + Inference About the Standardized Mortality Ratio when Evaluating + the Effect of a Screening Program on Survival + maintainer: Denis Talbot + description: |- + Functions to make inference about the + standardized mortality ratio (SMR) when evaluating the + effect of a screening program. The package is + based on methods described in Sasieni (2003) + and + Talbot et al. (2011) . + date_publication: '2023-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InferenceSMR + url_git: '' +inferference: + version: 1.0.2 + title: Methods for Causal Inference with Interference + maintainer: Bradley Saul + description: Provides methods for estimating causal effects in the presence of interference + described in B. Saul and M. Hugdens (2017) . Currently + it implements the inverse-probability weighted (IPW) estimators proposed by E.J. + Tchetgen Tchetgen and T.J. Vanderweele (2012) . + date_publication: '2021-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inferference + url_git: '' +inferr: + version: 0.3.2 + title: Inferential Statistics + maintainer: Aravind Hebbali + description: |- + Select set of parametric and non-parametric statistical tests. 'inferr' builds upon the solid set of + statistical tests provided in 'stats' package by including additional data types as inputs, expanding and + restructuring the test results. The tests included are t tests, variance tests, proportion tests, chi square tests, Levene's test, McNemar Test, Cochran's Q test and Runs test. + date_publication: '2024-11-11' + bug_reports: https://github.com/rsquaredacademy/inferr/issues + url: https://rsquaredacademy.github.io/inferr/ + url_cran: https://CRAN.R-project.org/package=inferr + url_git: https://github.com/rsquaredacademy/inferr +infiltrodiscR: + version: 0.0.5 + title: Minidisc Infiltrometer Data Management + maintainer: Sara E. Acevedo + description: |- + A set of functions for the modeling of data derived from the + Minidisc Infiltrometer device. It calculates cumulative infiltration + and square root of time. Also, it calculates the A parameter based on + soil physical properties. + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=infiltrodiscR + url_git: '' +infinitefactor: + version: '1.0' + title: Bayesian Infinite Factor Models + maintainer: Evan Poworoznek + description: Sampler and post-processing functions for semi-parametric Bayesian + infinite factor models, motivated by the Multiplicative Gamma Shrinkage Prior + of Bhattacharya and Dunson (2011) . + Contains component C++ functions for building samplers for linear and 2-way interaction + factor models using the multiplicative gamma and Dirichlet-Laplace shrinkage priors. + The package also contains post processing functions to return matrices that display + rotational ambiguity to identifiability through successive application of orthogonalization + procedures and resolution of column label and sign switching. This package was + developed with the support of the National Institute of Environmental Health Sciences + grant 1R01ES028804-01. + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=infinitefactor + url_git: '' +InfiniumPurify: + version: 1.3.1 + title: |- + Estimate and Account for Tumor Purity in Cancer Methylation Data + Analysis + maintainer: Yufang Qin + description: The proportion of cancer cells in solid tumor sample, known as the + tumor purity, has adverse impact on a variety of data analyses if not properly + accounted for. We develop 'InfiniumPurify', which is a comprehensive R package + for estimating and accounting for tumor purity based on DNA methylation Infinium + 450k array data. 'InfiniumPurify' provides functionalities for tumor purity estimation. + In addition, it can perform differential methylation detection and tumor sample + clustering with the consideration of tumor purities. + date_publication: '2017-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InfiniumPurify + url_git: '' +infix: + version: 0.1.0 + title: Basic Infix Binary Operators + maintainer: Ernest Benedito + description: Contains a number of infix binary operators that may be useful in day + to day practices. + date_publication: '2018-12-25' + bug_reports: http://github.com/ebeneditos/infix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=infix + url_git: http://github.com/ebeneditos/infix +Inflation: + version: 0.1.0 + title: Core Inflation + maintainer: Pedro Costa Ferreira + description: |- + Provides access to core inflation functions. Four different core inflation + functions are provided. The well known trimmed means, exclusion and double weighing methods, + alongside the new Triple Filter method introduced in Ferreira et al. (2016) . + date_publication: '2017-09-01' + bug_reports: https://github.com/fernote7/Inflation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Inflation + url_git: https://github.com/fernote7/Inflation +inflection: + version: 1.3.6 + title: Finds the Inflection Point of a Curve + maintainer: Demetris T. Christopoulos + description: |- + Implementation of methods Extremum Surface Estimator (ESE) and + Extremum Distance Estimator (EDE) to identify the inflection point of a curve . + Christopoulos, DT (2014) . + Christopoulos, DT (2016) . + Christopoulos, DT (2016) . + date_publication: '2022-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inflection + url_git: '' +InflectSSP: + version: '1.6' + title: Melt Curve Fitting and Melt Shift Analysis + maintainer: Amber Mosley + description: |- + Analyzes raw abundance data from a cellular thermal shift experiment and calculates melt temperatures and melt shifts for each protein in the experiment. + McCracken (2022) . + date_publication: '2023-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InflectSSP + url_git: '' +influence.ME: + version: 0.9-9 + title: Tools for Detecting Influential Data in Mixed Effects Models + maintainer: Rense Nieuwenhuis + description: |- + Provides a collection of tools for + detecting influential cases in generalized mixed effects + models. It analyses models that were estimated using 'lme4'. The + basic rationale behind identifying influential data is that + when single units are omitted from the data, models + based on these data should not produce substantially different + estimates. To standardize the assessment of how influential a + (single group of) observation(s) is, several measures of + influence are common practice, such as Cook's Distance. + In addition, we provide a measure of percentage change of the fixed point + estimates and a simple procedure to detect changing levels of significance. + date_publication: '2017-06-07' + bug_reports: '' + url: http://www.rensenieuwenhuis.nl/r-project/influenceme/ + url_cran: https://CRAN.R-project.org/package=influence.ME + url_git: '' +influence.SEM: + version: '2.3' + title: Case Influence in Structural Equation Models + maintainer: Massimiliano Pastore + description: A set of tools for evaluating several measures of case influence for + structural equation models. + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=influence.SEM + url_git: '' +influenceAUC: + version: 0.1.2 + title: Identify Influential Observations in Binary Classification + maintainer: Bo-Shiang Ke + description: Ke, B. S., Chiang, A. J., & Chang, Y. C. I. (2018) + provide two theoretical methods (influence function and local influence) based + on the area under the receiver operating characteristic curve (AUC) to quantify + the numerical impact of each observation to the overall AUC. Alternative graphical + tools, cumulative lift charts, are proposed to reveal the existences and approximate + locations of those influential observations through data visualization. + date_publication: '2020-05-30' + bug_reports: https://github.com/BoShiangKe/InfluenceAUC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=influenceAUC + url_git: '' +influenceR: + version: 0.1.5 + title: |- + Software Tools to Quantify Structural Importance of Nodes in a + Network + maintainer: Aditya Khanna + description: |- + Provides functionality to compute various node centrality measures on networks. + Included are functions to compute betweenness centrality (by utilizing Madduri and Bader's + SNAP library), implementations of constraint and effective network size by Burt (2000) ; algorithm + to identify key players by Borgatti (2006) ; and the + bridging algorithm by Valente and Fujimoto (2010) . + On Unix systems, the betweenness, Key Players, and + bridging implementations are parallelized with OpenMP, which may run + faster on systems which have OpenMP configured. + date_publication: '2023-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=influenceR + url_git: https://github.com/khanna-lab/influenceR +influential: + version: 2.2.9 + title: Identification and Classification of the Most Influential Nodes + maintainer: Adrian Salavaty + description: |- + Contains functions for the classification and ranking of top candidate features, reconstruction of networks from + adjacency matrices and data frames, analysis of the topology of the network + and calculation of centrality measures, and identification of the most + influential nodes. Also, a function is provided for running SIRIR model, which + is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment + of dependence and correlation of two network centrality measures as well as + the conditional probability of deviation from their corresponding means in opposite direction. + Fred Viole and David Nawrocki (2013, ISBN:1490523995). + Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. + Adopted algorithms and sources are referenced in function document. + date_publication: '2023-12-09' + bug_reports: https://github.com/asalavaty/influential/issues + url: https://asalavaty.github.io/influential/ + url_cran: https://CRAN.R-project.org/package=influential + url_git: https://github.com/asalavaty/influential +influxdbclient: + version: 0.1.2 + title: '''InfluxDB'' 2.x Client' + maintainer: Ales Pour + description: |2- + + 'InfluxDB' 2.x time-series database client. Supports both 'InfluxDB' OSS () and Cloud () version. + date_publication: '2022-09-01' + bug_reports: https://github.com/influxdata/influxdb-client-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=influxdbclient + url_git: https://github.com/influxdata/influxdb-client-r +influxdbr: + version: 0.14.2 + title: R Interface to InfluxDB + maintainer: Dominik Leutnant + description: An R interface to the InfluxDB time series database . + This package allows you to fetch and write time series data from/to an InfluxDB + server. Additionally, handy wrappers for the Influx Query Language (IQL) to manage + and explore a remote database are provided. + date_publication: '2018-01-10' + bug_reports: http://github.com/dleutnant/influxdbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=influxdbr + url_git: https://github.com/dleutnant/influxdbr +infoDecompuTE: + version: 0.6.2 + title: Information Decomposition of Two-Phase Experiments + maintainer: Kevin Chang + description: |- + The main purpose of this package is to generate the structure of the analysis of variance + (ANOVA) table of the two-phase experiments. The user only need to input the design and the + relationships of the random and fixed factors using the Wilkinson-Rogers' syntax, + this package can then quickly generate the structure of the ANOVA table with the + coefficients of the variance components for the expected mean squares. + Thus, the balanced incomplete block design and provides the efficiency + factors of the fixed effects can also be studied and compared much easily. + date_publication: '2020-03-28' + bug_reports: https://github.com/kcha193/infoDecompuTE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=infoDecompuTE + url_git: https://github.com/kcha193/infoDecompuTE +Information: + version: 0.0.9 + title: |- + Data Exploration with Information Theory (Weight-of-Evidence and + Information Value) + maintainer: Larsen Kim + description: |- + Performs exploratory data analysis and variable screening for + binary classification models using weight-of-evidence (WOE) and information + value (IV). In order to make the package as efficient as possible, aggregations + are done in data.table and creation of WOE vectors can be distributed across + multiple cores. The package also supports exploration for uplift models (NWOE + and NIV). + date_publication: '2016-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Information + url_git: '' +InformativeCensoring: + version: 0.3.6 + title: Multiple Imputation for Informative Censoring + maintainer: Jonathan Bartlett + description: |- + Multiple Imputation for Informative Censoring. + This package implements two methods. Gamma Imputation + described in and Risk Score Imputation + described in . + date_publication: '2023-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InformativeCensoring + url_git: https://github.com/jwb133/InformativeCensoring +informativeSCI: + version: 1.0.3 + title: Informative Simultaneous Confidence Intervals + maintainer: Liane Kluge + description: |- + Calculation of informative simultaneous confidence intervals + for graphical described multiple test procedures and given information + weights. Bretz et al. (2009) and Brannath et + al. (2024) . Furthermore, exploration of the + behavior of the informative bounds in dependence of the information + weights. Comparisons with compatible bounds are possible. + Strassburger and Bretz (2008) . + date_publication: '2024-06-21' + bug_reports: https://github.com/LianeKluge/informativeSCI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=informativeSCI + url_git: https://github.com/LianeKluge/informativeSCI +informedSen: + version: 1.0.7 + title: Sensitivity Analysis Informed by a Test for Bias + maintainer: Paul R Rosenbaum + description: 'After testing for biased treatment assignment in an observational + study using an unaffected outcome, the sensitivity analysis is constrained to + be compatible with that test. The package uses the optimization software gurobi + obtainable from , together with its associated R package, + also called gurobi; see: . The + method is a substantial computational and practical enhancement of a concept introduced + in Rosenbaum (1992) Detecting bias with confidence in observational studies Biometrika, + 79(2), 367-374 .' + date_publication: '2021-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=informedSen + url_git: '' +INFOSET: + version: '4.1' + title: Computing a New Informative Distribution Set of Asset Returns + maintainer: Gloria Polinesi + description: |- + Estimation of the most-left informative set of gross returns + (i.e., the informative set). + The procedure to compute the informative set adjusts the method + proposed by + Mariani et al. (2022a) + and + Mariani et al. (2022b) + to gross returns of financial assets. + This is accomplished through an adaptive algorithm + that identifies sub-groups of gross returns in + each iteration by approximating their distribution with a + sequence of two-component log-normal mixtures. + These sub-groups emerge when a significant change + in the distribution occurs below the median of the + financial returns, with their boundary termed as + the “change point" of the mixture. + The process concludes when no further change points are detected. + The outcome encompasses parameters of the leftmost mixture + distributions and change points of the + analyzed financial time series. + The functionalities of the INFOSET package include: (i) modelling asset distribution + detecting the parameters which describe left tail behaviour (infoset function), (ii) clustering, (iii) labeling of the financial + series for predictive and classification purposes through a Left Risk measure based on the first change point (LR_cp function) + (iv) portfolio construction (ptf_construction function). + The package also provide a specific function to construct rolling windows of different length size and overlapping time. + date_publication: '2024-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=INFOSET + url_git: '' +infotheo: + version: 1.2.0.1 + title: Information-Theoretic Measures + maintainer: Patrick E. Meyer + description: Implements various measures of information theory based on several + entropy estimators. + date_publication: '2022-04-08' + bug_reports: '' + url: http://homepage.meyerp.com/software + url_cran: https://CRAN.R-project.org/package=infotheo + url_git: '' +InfoTrad: + version: '1.2' + title: Calculates the Probability of Informed Trading (PIN) + maintainer: Murat Tinic + description: Estimates the probability of informed trading (PIN) initially introduced + by Easley et. al. (1996) . Contribution + of the package is that it uses likelihood factorizations of Easley et. al. (2010) + (EHO factorization) and Lin and Ke (2011) + (LK factorization). Moreover, the package uses different estimation algorithms. + Specifically, the grid-search algorithm proposed by Yan and Zhang (2012) + , hierarchical agglomerative clustering approach proposed by Gan et. al. (2015) + and later extended by Ersan and Alici (2016) + . + date_publication: '2017-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InfoTrad + url_git: '' +infraFDTD.assist: + version: '0.6' + title: IO Help for infraFDTD Model + maintainer: Jake Anderson + description: Facilitates the generation of input files for infraFDTD and processes + snapshot output. infraFDTD is a finite-difference model written by Keehoon Kim + for simulating infrasound that considers topography and a 1-D atmosphere (see + Kim et al., 2015 ). + date_publication: '2017-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=infraFDTD.assist + url_git: '' +Infusion: + version: 2.2.0 + title: Inference Using Simulation + maintainer: François Rousset + description: 'Implements functions for simulation-based inference. In particular, + implements functions to perform likelihood inference from data summaries whose + distributions are simulated. The package implements more advanced methods than + the ones first described in: Rousset, Gouy, Almoyna and Courtiol (2017) .' + date_publication: '2024-09-26' + bug_reports: '' + url: https://gitlab.mbb.univ-montp2.fr/francois/Infusion + url_cran: https://CRAN.R-project.org/package=Infusion + url_git: '' +ingredients: + version: 2.3.0 + title: Effects and Importances of Model Ingredients + maintainer: Przemyslaw Biecek + description: |- + Collection of tools for assessment of feature importance and feature effects. + Key functions are: + feature_importance() for assessment of global level feature importance, + ceteris_paribus() for calculation of the what-if plots, + partial_dependence() for partial dependence plots, + conditional_dependence() for conditional dependence plots, + accumulated_dependence() for accumulated local effects plots, + aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles, + generic print() and plot() for better usability of selected explainers, + generic plotD3() for interactive, D3 based explanations, and + generic describe() for explanations in natural language. + The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) . + date_publication: '2023-01-15' + bug_reports: https://github.com/ModelOriented/ingredients/issues + url: https://ModelOriented.github.io/ingredients/ + url_cran: https://CRAN.R-project.org/package=ingredients + url_git: https://github.com/ModelOriented/ingredients +ini: + version: 0.3.1 + title: Read and Write '.ini' Files + maintainer: David Valentim Dias + description: |- + Parse simple '.ini' configuration files to an structured list. Users + can manipulate this resulting list with lapply() functions. This same + structured list can be used to write back to file after modifications. + date_publication: '2018-05-20' + bug_reports: https://github.com/dvdscripter/ini/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ini + url_git: https://github.com/dvdscripter/ini +injectoR: + version: 0.2.4 + title: R Dependency Injection + maintainer: Lev Kuznetsov + description: |- + R dependency injection framework. Dependency injection allows + a program design to follow the dependency inversion principle. The user + delegates to external code (the injector) the responsibility of providing its + dependencies. This separates the responsibilities of use and construction. + date_publication: '2015-11-30' + bug_reports: https://github.com/dfci-cccb/injectoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=injectoR + url_git: https://github.com/dfci-cccb/injectoR +InjurySeverityScore: + version: 0.0.0.2 + title: Translate ICD-9 into Injury Severity Score + maintainer: Dajun Tian + description: |- + Calculate the injury severity score (ISS) + based on the dictionary in 'ICDPIC' from . The original code was written in + 'STATA 11'. The original 'STATA' code was written by David Clark, + Turner Osler and David Hahn. I implement the same logic for easier access. + Ref: David E. Clark & Turner M. Osler & David R. Hahn, 2009. + "ICDPIC: Stata module to provide methods for translating International + Classification of Diseases (Ninth Revision) diagnosis codes into standard injury + categories and/or scores," Statistical Software Components S457028, + Boston College Department of Economics, revised 29 Oct 2010. + date_publication: '2019-05-19' + bug_reports: https://github.com/dajuntian/InjurySeverityScore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=InjurySeverityScore + url_git: https://github.com/dajuntian/InjurySeverityScore +injurytools: + version: 1.0.3 + title: A Toolkit for Sports Injury Data Analysis + maintainer: Lore Zumeta Olaskoaga + description: |- + Sports Injury Data analysis aims to identify and describe the + magnitude of the injury problem, and to gain more insights (e.g. determine + potential risk factors) by statistical modelling approaches. The 'injurytools' + package provides standardized routines and utilities that simplify such + analyses. It offers functions for data preparation, informative visualizations + and descriptive and model-based analyses. + date_publication: '2023-11-14' + bug_reports: https://github.com/lzumeta/injurytools/issues + url: https://lzumeta.github.io/injurytools/ + url_cran: https://CRAN.R-project.org/package=injurytools + url_git: https://github.com/lzumeta/injurytools +INLABMA: + version: 0.1-12 + title: Bayesian Model Averaging with INLA + maintainer: Virgilio Gómez-Rubio + description: |- + Fit Spatial Econometrics models using Bayesian model averaging + on models fitted with INLA. The INLA package can be obtained from + . + date_publication: '2023-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=INLABMA + url_git: '' +inlabru: + version: 2.12.0 + title: Bayesian Latent Gaussian Modelling using INLA and Extensions + maintainer: Finn Lindgren + description: |- + Facilitates spatial and general latent Gaussian modeling using + integrated nested Laplace approximation via the INLA package (). + Additionally, extends the GAM-like model class to more general nonlinear predictor + expressions, and implements a log Gaussian Cox process likelihood for + modeling univariate and spatial point processes based on ecological survey data. + Model components are specified with general inputs and mapping methods to the + latent variables, and the predictors are specified via general R expressions, + with separate expressions for each observation likelihood model in + multi-likelihood models. A prediction method based on fast Monte Carlo sampling + allows posterior prediction of general expressions of the latent variables. + Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) + . + date_publication: '2024-11-21' + bug_reports: https://github.com/inlabru-org/inlabru/issues + url: http://www.inlabru.org + url_cran: https://CRAN.R-project.org/package=inlabru + url_git: https://github.com/inlabru-org/inlabru +INLAjoint: + version: 24.3.25 + title: |- + Multivariate Joint Modeling for Longitudinal and Time-to-Event + Outcomes with 'INLA' + maintainer: Denis Rustand + description: Estimation of joint models for multivariate longitudinal markers (with + various distributions available) and survival outcomes (possibly accounting for + competing risks) with Integrated Nested Laplace Approximations (INLA). The flexible + and user friendly function joint() facilitates the use of the fast and reliable + inference technique implemented in the 'INLA' package for joint modeling. More + details are given in the help page of the joint() function (accessible via ?joint + in the R console) and the vignette associated to the joint() function (accessible + via vignette("INLAjoint") in the R console). + date_publication: '2024-03-25' + bug_reports: https://github.com/DenisRustand/INLAjoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=INLAjoint + url_git: https://github.com/DenisRustand/INLAjoint +inlamemi: + version: 1.1.0 + title: Missing Data and Measurement Error Modelling in INLA + maintainer: Emma Skarstein + description: Facilitates fitting measurement error and missing data imputation models + using integrated nested Laplace approximations, according to the method described + in Skarstein, Martino and Muff (2023) . See Skarstein + and Muff (2024) for details on using the package. + date_publication: '2024-10-31' + bug_reports: '' + url: https://emmaskarstein.github.io/inlamemi/ + url_cran: https://CRAN.R-project.org/package=inlamemi + url_git: https://github.com/emmaSkarstein/inlamemi +INLAspacetime: + version: 0.1.11 + title: Spatial and Spatio-Temporal Models using 'INLA' + maintainer: Elias Teixeira Krainski + description: |- + Prepare objects to implement models over spatial and + spacetime domains with the 'INLA' package (). + These objects contain data to for the 'cgeneric' interface in + 'INLA', enabling fast parallel computations. + We implemented the spatial barrier model, see Bakka et. al. (2019) + , and some of the spatio-temporal + models proposed in Lindgren et. al. (2023) + . + Details are provided in the available vignettes and from the URL bellow. + date_publication: '2025-02-25' + bug_reports: https://github.com/eliaskrainski/INLAspacetime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=INLAspacetime + url_git: https://github.com/eliaskrainski/INLAspacetime +inlcolor: + version: 1.0.6 + title: |- + Color Schemes for the USGS Idaho National Laboratory Project + Office + maintainer: Jason C. Fisher + description: |- + A collection of functions for creating color schemes. + Used to support packages and scripts written + by researchers at the United States Geological Survey (USGS) + Idaho National Laboratory Project Office. + date_publication: '2024-01-30' + bug_reports: https://code.usgs.gov/inl/inlcolor/-/issues + url: https://rconnect.usgs.gov/INLPO/inlcolor-main/ + url_cran: https://CRAN.R-project.org/package=inlcolor + url_git: '' +inldata: + version: 1.2.7 + title: Collection of Datasets for the USGS-INL Monitoring Networks + maintainer: Jason C. Fisher + description: |- + A collection of analysis-ready datasets for the + U.S. Geological Survey - Idaho National Laboratory (USGS-INL) + groundwater and surface-water monitoring networks, administered by the + USGS-INL Project Office in cooperation with the U.S. Department of Energy. + The data collected from wells and surface-water stations at the + Idaho National Laboratory and surrounding areas have been used to describe + the effects of waste disposal on water contained in the + eastern Snake River Plain aquifer, located in the southeastern part of + Idaho, and the availability of water for long-term consumptive and + industrial use. The package includes long-term monitoring records dating + back to measurements from 1922. Geospatial data describing the areas from + which samples were collected or observations were made are also included in + the package. Bundling this data into a single package significantly reduces + the magnitude of data processing for researchers and provides a way to + distribute the data along with its documentation in a standard format. + Geospatial datasets are made available in a common projection and datum, and + geohydrologic data have been structured to facilitate analysis. + date_publication: '2024-09-12' + bug_reports: https://code.usgs.gov/inl/inldata/-/issues + url: https://rconnect.usgs.gov/INLPO/inldata-main/ + url_cran: https://CRAN.R-project.org/package=inldata + url_git: '' +inline: + version: 0.3.21 + title: Functions to Inline C, C++, Fortran Function Calls from R + maintainer: Dirk Eddelbuettel + description: |- + Functionality to dynamically define R functions and S4 methods + with 'inlined' C, C++ or Fortran code supporting the .C and .Call calling + conventions. + date_publication: '2025-01-09' + bug_reports: https://github.com/eddelbuettel/inline/issues + url: https://dirk.eddelbuettel.com/code/inline.html + url_cran: https://CRAN.R-project.org/package=inline + url_git: https://github.com/eddelbuettel/inline +inlinedocs: + version: 2023.9.4 + title: Convert Inline Comments to Documentation + maintainer: Toby Dylan Hocking + description: |- + Generates Rd files from R source code with comments. + The main features of the default syntax are that + (1) docs are defined in comments near the relevant code, + (2) function argument names are not repeated in comments, and + (3) examples are defined in R code, not comments. + It is also easy to define a new syntax. + date_publication: '2023-10-18' + bug_reports: https://github.com/tdhock/inlinedocs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inlinedocs + url_git: https://github.com/tdhock/inlinedocs +inlpubs: + version: 1.2.0 + title: USGS INL Project Office Publications + maintainer: Jason C. Fisher + description: |- + Contains bibliographic information for the U.S. Geological Survey + (USGS) Idaho National Laboratory (INL) Project Office. + date_publication: '2025-01-08' + bug_reports: https://code.usgs.gov/inl/inlpubs/-/issues + url: https://rconnect.usgs.gov/INLPO/inlpubs-main/ + url_cran: https://CRAN.R-project.org/package=inlpubs + url_git: '' +innsight: + version: 0.3.1 + title: Get the Insights of Your Neural Network + maintainer: Niklas Koenen + description: |- + Interpretation methods for analyzing the behavior and individual + predictions of modern neural networks in a three-step procedure: Converting + the model, running the interpretation method, and visualizing the results. + Implemented methods are, e.g., 'Connection Weights' described by Olden et al. (2004) + , layer-wise relevance + propagation ('LRP') described by Bach et al. (2015) + , deep learning important features + ('DeepLIFT') described by Shrikumar et al. (2017) + and gradient-based methods like 'SmoothGrad' described by Smilkov et + al. (2017) , 'Gradient x Input' + or 'Vanilla Gradient'. + Details can be found in the accompanying scientific paper: Koenen & Wright + (2024, Journal of Statistical Software, ). + date_publication: '2024-11-26' + bug_reports: https://github.com/bips-hb/innsight/issues/ + url: https://bips-hb.github.io/innsight/ + url_cran: https://CRAN.R-project.org/package=innsight + url_git: https://github.com/bips-hb/innsight/ +inops: + version: 0.0.1 + title: Infix Operators for Detection, Subsetting and Replacement + maintainer: Antoine Fabri + description: |- + Infix operators to detect, subset, and replace the elements matched by a given condition. + The functions have several variants of operator types, including subsets, ranges, regular expressions and others. + Implemented operators work on vectors, matrices, and lists. + date_publication: '2019-11-19' + bug_reports: https://github.com/moodymudskipper/inops/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inops + url_git: https://github.com/moodymudskipper/inops +inpdfr: + version: 0.1.12 + title: Analyse Text Documents Using Ecological Tools + maintainer: Rebaudo Francois + description: "A set of functions to analyse and compare texts, using classical\ntext + mining\tfunctions, as well as those from theoretical ecology." + date_publication: '2023-08-24' + bug_reports: https://github.com/frareb/inpdfr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inpdfr + url_git: https://github.com/frareb/inpdfr/ +inplace: + version: 0.1.2 + title: In-place Operators for R + maintainer: Florian Privé + description: |- + It provides in-place operators for R + that are equivalent to '+=', '-=', '*=', '/=' in C++. + Those can be applied on integer|double vectors|matrices. + You have also access to sweep operations (in-place). + date_publication: '2020-08-24' + bug_reports: https://github.com/privefl/inplace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inplace + url_git: https://github.com/privefl/inplace +InPosition: + version: 0.12.7.1 + title: Inference Tests for ExPosition + maintainer: Derek Beaton + description: Non-parametric resampling-based inference tests for ExPosition. + date_publication: '2019-01-31' + bug_reports: http://code.google.com/p/exposition-family/issues/list + url: '' + url_cran: https://CRAN.R-project.org/package=InPosition + url_git: '' +INQC: + version: 2.0.5 + title: Quality Control of Climatological Daily Time Series + maintainer: Enric Aguilar + description: Collection of functions for quality control (QC) of climatological + daily time series (e.g. the ECA&D station data). + date_publication: '2021-05-24' + bug_reports: https://github.com/INDECIS-Project/INQC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=INQC + url_git: https://github.com/INDECIS-Project/INQC +Inquilab: + version: 0.1.0 + title: |- + Dissipation Kinetics Analysis, Half Life Period, Rate Constant, + Plots + maintainer: Jajati Mandal + description: For environmental chemists, ecologists, researchers and agricultural + scientists to understand the dissipation kinetics, calculate the half-life periods + and rate constants of compounds, pesticides, contaminants in different matrices. + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Inquilab + url_git: '' +insane: + version: 1.0.3 + title: INsulin Secretion ANalysEr + maintainer: Mickaël Canouil + description: |- + A user-friendly interface, using Shiny, to analyse glucose-stimulated insulin secretion (GSIS) + assays in pancreatic beta cells or islets. + The package allows the user to import several sets of experiments from different spreadsheets + and to perform subsequent steps: summarise in a tidy format, visualise data quality + and compare experimental conditions without omitting to account for technical confounders + such as the date of the experiment or the technician. + Together, insane is a comprehensive method that optimises pre-processing and analyses of + GSIS experiments in a friendly-user interface. + The Shiny App was initially designed for EndoC-betaH1 cell line following method described + in Ndiaye et al., 2017 (). + date_publication: '2023-11-14' + bug_reports: https://github.com/mcanouil/insane/issues/ + url: https://m.canouil.dev/insane/ + url_cran: https://CRAN.R-project.org/package=insane + url_git: https://github.com/mcanouil/insane/ +insect: + version: 1.4.2 + title: Informatic Sequence Classification Trees + maintainer: Shaun Wilkinson + description: Provides tools for probabilistic taxon assignment with informatic sequence + classification trees. See Wilkinson et al (2018) . + date_publication: '2021-08-09' + bug_reports: https://github.com/shaunpwilkinson/insect/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=insect + url_git: https://github.com/shaunpwilkinson/insect/ +insee: + version: 1.1.7 + title: Tools to Easily Download Data from INSEE BDM Database + maintainer: Hadrien Leclerc + description: Using embedded sdmx queries, get the data of more than 150 000 insee + series from 'bdm' macroeconomic database. + date_publication: '2024-08-26' + bug_reports: https://github.com/pyr-opendatafr/R-Insee-Data/issues + url: https://pyr-opendatafr.github.io/R-Insee-Data/ + url_cran: https://CRAN.R-project.org/package=insee + url_git: '' +insight: + version: 1.0.2 + title: Easy Access to Model Information for Various Model Objects + maintainer: Daniel Lüdecke + description: |- + A tool to provide an easy, intuitive and consistent + access to information contained in various R models, like model + formulas, model terms, information about random effects, data that was + used to fit the model or data from response variables. 'insight' + mainly revolves around two types of functions: Functions that find + (the names of) information, starting with 'find_', and functions that + get the underlying data, starting with 'get_'. The package has a + consistent syntax and works with many different model objects, where + otherwise functions to access these information are missing. + date_publication: '2025-02-06' + bug_reports: https://github.com/easystats/insight/issues + url: https://easystats.github.io/insight/ + url_cran: https://CRAN.R-project.org/package=insight + url_git: '' +InSilicoVA: + version: 1.4.0 + title: Probabilistic Verbal Autopsy Coding with 'InSilicoVA' Algorithm + maintainer: Zehang Richard Li + description: Computes individual causes of death and population cause-specific mortality + fractions using the 'InSilicoVA' algorithm from McCormick et al. (2016) . + It uses data derived from verbal autopsy (VA) interviews, in a format similar + to the input of the widely used 'InterVA' method. This package provides general + model fitting and customization for 'InSilicoVA' algorithm and basic graphical + visualization of the output. + date_publication: '2022-09-29' + bug_reports: https://github.com/verbal-autopsy-software/InSilicoVA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=InSilicoVA + url_git: https://github.com/verbal-autopsy-software/InSilicoVA +InspectChangepoint: + version: '1.2' + title: High-Dimensional Changepoint Estimation via Sparse Projection + maintainer: Tengyao Wang + description: Provides a data-driven projection-based method for estimating changepoints + in high-dimensional time series. Multiple changepoints are estimated using a (wild) + binary segmentation scheme. + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InspectChangepoint + url_git: '' +inspectdf: + version: 0.0.12.1 + title: Inspection, Comparison and Visualisation of Data Frames + maintainer: Alastair Rushworth + description: A collection of utilities for columnwise summary, comparison and visualisation + of data frames. Functions report missingness, categorical levels, numeric distribution, + correlation, column types and memory usage. + date_publication: '2024-12-27' + bug_reports: https://github.com/alastairrushworth/inspectdf/issues + url: https://alastairrushworth.github.io/inspectdf/ + url_cran: https://CRAN.R-project.org/package=inspectdf + url_git: '' +InspectionPlanner: + version: '1.2' + title: Phytosanitary Inspection Sampling Planner + maintainer: Gustavo Ramirez-Valverde + description: A 'shiny' application to assist in phytosanitary inspections. It generates + a diagram of pallets in a lot, highlights the units to be sampled, and documents + them based on the selected sampling method (simple random or systematic sampling). + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InspectionPlanner + url_git: '' +inspector: + version: 1.0.3 + title: Validation of Arguments and Objects in User-Defined Functions + maintainer: Pedro Fonseca + description: |- + Utility functions that implement and automate common sets of validation tasks. + These functions are particularly useful to validate inputs, intermediate objects and output + values in user-defined functions, resulting in tidier and less verbose functions. + date_publication: '2021-06-17' + bug_reports: https://github.com/ptfonseca/inspector/issues + url: https://ptfonseca.github.io/inspector/ + url_cran: https://CRAN.R-project.org/package=inspector + url_git: https://github.com/ptfonseca/inspector +INSPECTumours: + version: 0.1.0 + title: IN-vivo reSPonsE Classification of Tumours + maintainer: Bairu Zhang + description: |- + This is a shiny app used for the statistical classifying and analysing + pre-clinical tumour responses. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=INSPECTumours + url_git: '' +INSPIRE: + version: '1.5' + title: |- + Inferring Shared Modules from Multiple Gene Expression Datasets + with Partially Overlapping Gene Sets + maintainer: Safiye Celik + description: |- + A method to infer modules of co-expressed genes and the + dependencies among the modules from multiple expression datasets that may + contain different sets of genes. Please refer to: Extracting a low-dimensional + description of multiple gene expression datasets reveals a potential driver for + tumor-associated stroma in ovarian cancer, Safiye Celik, Benjamin A. Logsdon, + Stephanie Battle, Charles W. Drescher, Mara Rendi, R. David Hawkins and Su-In + Lee (2016) . + date_publication: '2016-12-09' + bug_reports: '' + url: inspire.cs.washington.edu + url_cran: https://CRAN.R-project.org/package=INSPIRE + url_git: '' +instagramadsR: + version: 0.1.0 + title: Access to Instagram Ads via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect marketing data from Instagram Ads using the 'Windsor.ai' API + . + date_publication: '2022-10-18' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=instagramadsR + url_git: '' +install.load: + version: 1.2.5 + title: Check, Install and Load CRAN Packages + maintainer: Irucka Embry + description: |- + The function 'install_load' checks the local R library(ies) to see + if the required package(s) is/are installed or not. If the package(s) + is/are not installed, then the package(s) will be installed along with + the required dependency(ies). This function pulls source or + binary packages from the Posit/RStudio-sponsored CRAN mirror. Lastly, the + chosen package(s) is/are loaded. The function 'load_package' simply loads + the provided package(s). If this package does not fit your needs, then you + may want to consider these other R packages: 'needs', 'easypackages', + 'pacman', 'pak', 'anyLib', and/or 'librarian'. + date_publication: '2023-08-21' + bug_reports: https://gitlab.com/iembry/install.load/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=install.load + url_git: https://gitlab.com/iembry/install.load +installr: + version: 0.23.4 + title: |- + Using R to Install Stuff on Windows OS (Such As: R, 'Rtools', + 'RStudio', 'Git', and More!) + maintainer: Tal Galili + description: |- + R is great for installing software. Through the 'installr' + package you can automate the updating of R (on Windows, using updateR()) + and install new software. Software installation is initiated through a + GUI (just run installr()), or through functions such as: install.Rtools(), + install.pandoc(), install.git(), and many more. The updateR() command + performs the following: finding the latest R version, downloading it, + running the installer, deleting the installation file, copy and updating + old packages to the new R installation. + date_publication: '2022-11-12' + bug_reports: https://github.com/talgalili/installr/issues + url: https://talgalili.github.io/installr/ + url_cran: https://CRAN.R-project.org/package=installr + url_git: https://github.com/talgalili/installr/ +instantiate: + version: 0.2.3 + title: Pre-Compiled 'CmdStan' Models in R Packages + maintainer: William Michael Landau + description: |- + Similar to 'rstantools' for 'rstan', + the 'instantiate' package builds pre-compiled + 'CmdStan' models into CRAN-ready statistical modeling R packages. + The models compile once during installation, + the executables live inside the file systems of their respective packages, + and users have the full power and convenience of + 'cmdstanr' without any additional compilation after package installation. + This approach saves time and helps R package developers + migrate from 'rstan' to the more modern 'cmdstanr'. + Packages 'rstantools', 'cmdstanr', 'stannis', and + 'stanapi' are similar Stan clients with different objectives. + date_publication: '2024-10-02' + bug_reports: https://github.com/wlandau/instantiate/issues + url: https://wlandau.github.io/instantiate/ + url_cran: https://CRAN.R-project.org/package=instantiate + url_git: https://github.com/wlandau/instantiate +instaR: + version: 0.2.4 + title: Access to Instagram API via R + maintainer: Pablo Barbera + description: |- + Provides an interface to the Instagram API , which allows R users to download public pictures filtered by + hashtag, popularity, user or location, and to access public users' profile data. + date_publication: '2016-08-17' + bug_reports: https://github.com/pablobarbera/instaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=instaR + url_git: https://github.com/pablobarbera/instaR +insuranceData: + version: '1.0' + title: |- + A Collection of Insurance Datasets Useful in Risk Classification + in Non-life Insurance. + maintainer: Alicja Wolny--Dominiak + description: Insurance datasets, which are often used in claims severity and claims + frequency modelling. It helps testing new regression models in those problems, + such as GLM, GLMM, HGLM, non-linear mixed models etc. Most of the data sets are + applied in the project "Mixed models in ratemaking" supported by grant NN 111461540 + from Polish National Science Center. + date_publication: '2014-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=insuranceData + url_git: '' +insurancerating: + version: 0.7.5 + title: Analytic Insurance Rating Techniques + maintainer: Martin Haringa + description: |- + Functions to build, evaluate, and visualize insurance rating + models. It simplifies the process of modeling premiums, and allows to + analyze insurance risk factors effectively. The package employs a + data-driven strategy for constructing insurance tariff classes, drawing on + the work of Antonio and Valdez (2012) . + date_publication: '2024-10-09' + bug_reports: https://github.com/MHaringa/insurancerating/issues + url: https://mharinga.github.io/insurancerating/ + url_cran: https://CRAN.R-project.org/package=insurancerating + url_git: https://github.com/MHaringa/insurancerating +InsuSensCalc: + version: 0.0.1 + title: Insulin Sensitivity Indices Calculator + maintainer: Sufyan Suleman + description: It facilitates the calculation of 40 different insulin sensitivity + indices based on fasting, oral glucose tolerance test (OGTT), lipid (adipose), + and tracer (palmitate and glycerol rate) and dxa (fat mass) measurement values. + It enables easy and accurate assessment of insulin sensitivity, critical for understanding + and managing metabolic disorders like diabetes and obesity. Indices calculated + are described in Gastaldelli (2022). and Lorenzo (2010). + . + date_publication: '2024-04-04' + bug_reports: https://github.com/sufyansuleman/InsuSensCalc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=InsuSensCalc + url_git: https://github.com/sufyansuleman/InsuSensCalc +intamap: + version: 1.5-7 + title: Procedures for Automated Interpolation + maintainer: Jon Olav Skoien + description: Geostatistical interpolation has traditionally been done by manually + fitting a variogram and then interpolating. Here, we introduce classes and methods + that can do this interpolation automatically. Pebesma et al (2010) gives an overview + of the methods behind and possible usage . + date_publication: '2023-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intamap + url_git: '' +intamapInteractive: + version: 1.2-6 + title: Interactive Add-on Functionality for 'intamap' + maintainer: Jon Skoien + description: The methods in this package adds to the functionality of the 'intamap' + package, such as bias correction and network optimization. Pebesma et al (2010) + gives an overview of the methods behind and possible usage . + date_publication: '2023-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intamapInteractive + url_git: '' +IntCal: + version: 0.3.1 + title: Radiocarbon Calibration Curves + maintainer: Maarten Blaauw + description: The IntCal20 radiocarbon calibration curves (Reimer et al. 2020 ) + are provided here in a single data package, together with previous IntCal curves + (IntCal13, IntCal09, IntCal04, IntCal98) and postbomb curves. Also provided are + functions to copy the curves into memory, and to plot the curves and their underlying + data, as well as functions to calibrate radiocarbon dates. + date_publication: '2022-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IntCal + url_git: '' +intccr: + version: 3.0.4 + title: |- + Semiparametric Competing Risks Regression under Interval + Censoring + maintainer: Jun Park + description: Semiparametric regression models on the cumulative incidence function + for interval-censored competing risks data as described in Bakoyannis, Yu, & Yiannoutsos + (2017) /doi{10.1002/sim.7350} and the models with missing event types as described + in Park, Bakoyannis, Zhang, & Yiannoutsos (2021) \doi{10.1093/biostatistics/kxaa052}. + The proportional subdistribution hazards model (Fine-Gray model), the proportional + odds model, and other models that belong to the class of semiparametric generalized + odds rate transformation models. + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intccr + url_git: '' +intcensROC: + version: 0.1.3 + title: AUC Estimation of Interval Censored Survival Data + maintainer: Yuan Wu + description: The kernel of this 'Rcpp' based package is an efficient implementation + of the generalized gradient projection method for spline function based constrained + maximum likelihood estimator for interval censored survival data (Wu, Yuan; Zhang, + Ying. Partially monotone tensor spline estimation of the joint distribution function + with bivariate current status data. Ann. Statist. 40, 2012, 1609-1636 ). + The key function computes the density function of the joint distribution of event + time and the marker and returns the receiver operating characteristic (ROC) curve + for the interval censored survival data as well as area under the curve (AUC). + date_publication: '2021-06-15' + bug_reports: '' + url: https://gitlab.oit.duke.edu/dcibioinformatics/soft/intcensroc + url_cran: https://CRAN.R-project.org/package=intcensROC + url_git: '' +integIRTy: + version: 1.0.7 + title: |- + Integrating Multiple Modalities of High Throughput Assays Using + Item Response Theory + maintainer: Kevin R. Coombes + description: |- + Provides a systematic framework for + integrating multiple modalities of assays profiled on the same set of + samples. The goal is to identify genes that are altered in cancer + either marginally or consistently across different assays. The + heterogeneity among different platforms and different samples are + automatically adjusted so that the overall alteration magnitude can + be accurately inferred. See Tong and Coombes (2012) + . + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=integIRTy + url_git: http://oompa.r-forge.r-project.org/ +integr: + version: 1.0.0 + title: An Implementation of Interaction Graphs of Aleks Jakulin + maintainer: Petar Markovic + description: |- + Generates a 'Graphviz' graph of the most significant 3-way + interaction gains (i.e. conditional information gains) based on a provided + discrete data frame. Various output formats are supported ('Graphviz', SVG, + PNG, PDF, PS). For references, see the webpage of Aleks Jakulin + . + date_publication: '2019-05-24' + bug_reports: https://github.com/peleplay/integr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=integr + url_git: https://github.com/peleplay/integr +IntegrateBs: + version: 0.1.0 + title: Integration for B-Spline + maintainer: Yue Bai + description: Integrated B-spline function. + date_publication: '2016-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IntegrateBs + url_git: '' +IntegratedJM: + version: '1.6' + title: |- + Joint Modeling of the Gene-Expression and Bioassay Data, Taking + Care of the Effect Due to a Fingerprint Feature + maintainer: Rudradev Sengupta + description: Offers modeling the association between gene-expression and bioassay + data, taking care of the effect due to a fingerprint feature and helps with several + plots to better understand the analysis. + date_publication: '2017-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IntegratedJM + url_git: '' +IntegratedMRF: + version: 1.1.9 + title: |- + Integrated Prediction using Uni-Variate and Multivariate Random + Forests + maintainer: Raziur Rahman + description: An implementation of a framework for drug sensitivity prediction from + various genetic characterizations using ensemble approaches. Random Forests or + Multivariate Random Forest predictive models can be generated from each genetic + characterization that are then combined using a Least Square Regression approach. + It also provides options for the use of different error estimation approaches + of Leave-one-out, Bootstrap, N-fold cross validation and 0.632+Bootstrap along + with generation of prediction confidence interval using Jackknife-after-Bootstrap + approach. + date_publication: '2018-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IntegratedMRF + url_git: '' +intendo: + version: 0.1.1 + title: |- + A Group of Fun Datasets of Various Sizes and Differing Levels of + Quality + maintainer: Richard Iannone + description: |- + Four datasets are provided here from the 'Intendo' game + 'Super Jetroid'. It is data from the 2015 year of operation and it comprises + a revenue table ('all_revenue'), a daily users table ('users_daily'), a user + summary table ('user_summary'), and a table with data on all user sessions + ('all_sessions'). These core datasets come in different sizes, and, each of + them has a variant that was intentionally made faulty (totally riddled with + errors and inconsistencies). This suite of tables is useful for testing with + packages that focus on data validation and data documentation. + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intendo + url_git: '' +intensegRid: + version: 0.1.2 + title: R Wrapper for the Carbon Intensity API + maintainer: Kasia Kulma + description: |- + Electricity is not made equal and it vary in its carbon footprint (or carbon intensity) + depending on its source. This package enables to access and query data provided by the + Carbon Intensity API (). National Grid’s Carbon Intensity API + provides an indicative trend of regional carbon intensity of the electricity system in Great Britain. + date_publication: '2022-11-08' + bug_reports: https://github.com/KKulma/intensegRid/issues + url: https://kkulma.github.io/intensegRid/articles/intro-to-carbon-intensity.html + url_cran: https://CRAN.R-project.org/package=intensegRid + url_git: https://github.com/KKulma/intensegRid +intensitynet: + version: 1.4.0 + title: Intensity Analysis of Spatial Point Patterns on Complex Networks + maintainer: Pol Llagostera + description: |- + Tools to analyze point patterns in space occurring over planar network structures derived from graph-related intensity measures for undirected, directed, and mixed networks. + This package is based on the following research: Eckardt and Mateu (2018) . Eckardt and Mateu (2021) . + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intensitynet + url_git: '' +InteractionPoweR: + version: 0.2.2 + title: |- + Power Analyses for Interaction Effects in Cross-Sectional + Regressions + maintainer: David Baranger + description: |- + Power analysis for regression models which test the interaction of + two or three independent variables on a single dependent variable. Includes options + for correlated interacting variables and specifying variable reliability. + Two-way interactions can include continuous, binary, or ordinal variables. + Power analyses can be done either analytically or via simulation. Includes + tools for simulating single data sets and visualizing power analysis results. + The primary functions are power_interaction_r2() and power_interaction() for two-way + interactions, and power_interaction_3way_r2() for three-way interactions. + Please cite as: Baranger DAA, Finsaas MC, Goldstein BL, Vize CE, Lynam DR, + Olino TM (2023). "Tutorial: Power analyses for interaction effects in + cross-sectional regressions." . + date_publication: '2024-07-09' + bug_reports: https://github.com/dbaranger/InteractionPoweR/issues + url: https://dbaranger.github.io/InteractionPoweR/ + url_cran: https://CRAN.R-project.org/package=InteractionPoweR + url_git: '' +interactionR: + version: 0.1.7 + title: Full Reporting of Interaction Analyses + maintainer: Babatunde Alli + description: Produces a publication-ready table that includes all effect estimates + necessary for full reporting effect modification and interaction analysis as recommended + by Knol and Vanderweele (2012) []. It also estimates confidence + interval for the trio of additive interaction measures using the delta method + (see Hosmer and Lemeshow (1992), []), variance + recovery method (see Zou (2008), []), or percentile bootstrapping + (see Assmann et al. (1996), []). + date_publication: '2023-12-03' + bug_reports: https://github.com/tunsmart/interactionR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interactionR + url_git: https://github.com/tunsmart/interactionR +interactionRCS: + version: 0.1.1 + title: Calculate Estimates in Models with Interaction + maintainer: Giorgio Melloni + description: |- + A tool to calculate and plot estimates from models + in which an interaction between the main predictor and a continuous covariate has been specified. + Methods used in the package refer to Harrell Jr FE (2015, ISBN:9783319330396); + Durrleman S, Simon R. (1989) ; Greenland S. (1995) . + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interactionRCS + url_git: '' +interactions: + version: 1.2.0 + title: Comprehensive, User-Friendly Toolkit for Probing Interactions + maintainer: Jacob A. Long + description: |- + A suite of functions for conducting and interpreting analysis + of statistical interaction in regression models that was formerly part of the + 'jtools' package. Functionality includes visualization of two- and three-way + interactions among continuous and/or categorical variables as well as + calculation of "simple slopes" and Johnson-Neyman intervals (see e.g., + Bauer & Curran, 2005 ). These + capabilities are implemented for generalized linear models in addition to the + standard linear regression context. + date_publication: '2024-07-29' + bug_reports: https://github.com/jacob-long/interactions/issues + url: https://interactions.jacob-long.com + url_cran: https://CRAN.R-project.org/package=interactions + url_git: '' +interactionTest: + version: '1.2' + title: |- + Calculates Critical Test Statistics to Control False Discovery + Rates in Marginal Effects Plots + maintainer: Justin Esarey + description: Implements the procedures suggested in Esarey and Sumner (2017) + for controlling the false discovery rate when constructing marginal effects plots + for models with interaction terms. + date_publication: '2019-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interactionTest + url_git: '' +Interatrix: + version: 1.1.4 + title: Compute Chi-Square Measures with Corrections + maintainer: Aurélie Siberchicot + description: Chi-square tests are computed with corrections. + date_publication: '2024-01-19' + bug_reports: https://github.com/lbbe-software/Interatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Interatrix + url_git: https://github.com/lbbe-software/Interatrix +interca: + version: 0.1.2 + title: |- + Multiple Correspondence Analysis Based on Interpretive + Coordinates + maintainer: Stratos Moschidis + description: Various functions and a Shiny app to enrich the results of Multiple + Correspondence Analysis with interpretive axes and planes (see Moschidis, Markos, + and Thanopoulos, 2022; ). + date_publication: '2023-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interca + url_git: '' +InteRD: + version: 0.1.1 + title: The Integrated and Robust Deconvolution + maintainer: Chixiang Chen + description: We developed the Integrated and Robust Deconvolution algorithm to infer + cell-type proportions from target bulk RNA-seq data. This package is able to effectively + integrate deconvolution results from multiple scRNA-seq datasets and calibrates + estimates from reference-based deconvolution by taking into account extra biological + information as priors. Moreover, the proposed algorithm is robust to inaccurate + external information imposed in the deconvolution system. + date_publication: '2022-08-12' + bug_reports: https://github.com/chencxxy28/InteRD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=InteRD + url_git: https://github.com/chencxxy28/InteRD +interep: + version: 0.4.1 + title: Interaction Analysis of Repeated Measure Data + maintainer: Fei Zhou + description: Extensive penalized variable selection methods have been developed + in the past two decades for analyzing high dimensional omics data, such as gene + expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) + and others. However, lipidomics data have been rarely investigated by using high + dimensional variable selection methods. This package incorporates our recently + developed penalization procedures to conduct interaction analysis for high dimensional + lipidomics data with repeated measurements. The core module of this package is + developed in C++. The development of this software package and the associated + statistical methods have been partially supported by an Innovative Research Award + from Johnson Cancer Research Center, Kansas State University. + date_publication: '2024-01-30' + bug_reports: https://github.com/feizhoustat/interep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interep + url_git: https://github.com/feizhoustat/interep +interface: + version: 0.1.2 + title: Runtime Type System + maintainer: Dereck Mezquita + description: Provides a runtime type system, allowing users to define and implement + interfaces, enums, typed data.frame/data.table, as well as typed functions. This + package enables stricter type checking and validation, improving code structure, + robustness and reliability. + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interface + url_git: https://github.com/dereckmezquita/interface +InterfaceqPCR: + version: 1.0.1 + title: GUI to Analyse qPCR Results after PMA Treatment or not + maintainer: Olivier LE GOFF + description: Graphical User Interface allowing to determine the concentration in + the sample in CFU per mL or in number of copies per mL provided to qPCR results + after with or without PMA treatment. This package is simply to use because no + knowledge in R commands is necessary. A graphic represents the standard curve, + and a table containing the result for each sample is created. + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InterfaceqPCR + url_git: '' +interfacer: + version: 0.3.3 + title: |- + Define and Enforce Contracts for Dataframes as Function + Parameters + maintainer: Robert Challen + description: |- + A dataframe validation framework for package builders who use + dataframes as function parameters. It performs checks on column names, coerces + data-types, and checks grouping to make sure user inputs conform to a + specification provided by the package author. It provides a mechanism for + package authors to automatically document supported dataframe inputs and + selectively dispatch to functions depending on the format of a dataframe much + like S3 does for classes. It also contains some developer tools to make + working with and documenting dataframe specifications easier. It helps package + developers to improve their documentation and simplifies parameter validation + where dataframes are used as function parameters. + date_publication: '2025-02-03' + bug_reports: https://github.com/ai4ci/interfacer/issues + url: https://ai4ci.github.io/interfacer/ + url_cran: https://CRAN.R-project.org/package=interfacer + url_git: https://github.com/ai4ci/interfacer +interflex: + version: 1.2.6 + title: Multiplicative Interaction Models Diagnostics and Visualization + maintainer: Ziyi Liu + description: Performs diagnostic tests of multiplicative interaction models and + plots non-linear marginal effects of a treatment on an outcome across different + values of a moderator. + date_publication: '2021-05-18' + bug_reports: '' + url: http://yiqingxu.org/software/interaction/RGuide.html + url_cran: https://CRAN.R-project.org/package=interflex + url_git: '' +interfr: + version: 0.1.0 + title: Interference Color Charts for Polarized Light Microscopy + maintainer: Olivier Eterradossi + description: Computes interference color tables and plots customized Michel-Levy + or Raith-Sorensen charts. Automatic interpretation of polarized-light microscopy + images is still under development and will come soon. + date_publication: '2017-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interfr + url_git: '' +intergraph: + version: 2.0-4 + title: Coercion Routines for Network Data Objects + maintainer: Michał Bojanowski + description: |- + Functions implemented in this package allow to coerce (i.e. + convert) network data between classes provided by other R packages. + Currently supported classes are those defined in packages: network and + igraph. + date_publication: '2024-02-01' + bug_reports: https://github.com/mbojan/intergraph/issues + url: https://mbojan.github.io/intergraph/ + url_cran: https://CRAN.R-project.org/package=intergraph + url_git: '' +interim: + version: 0.8.0 + title: Scheduling Interim Analyses in Clinical Trials + maintainer: Bastian Becker + description: Allows the simulation of the recruitment and both the event and treatment + phase of a clinical trial. Based on these simulations, the timing of interim analyses + can be assessed. + date_publication: '2019-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interim + url_git: '' +interimApp: + version: 0.0.1 + title: App for Scheduling Interim Analyses in Clinical Trials + maintainer: Bastian Becker + description: Allows an interactive assessment of the timing of interim analyses. + The algorithm simulates both the recruitment and treatment/event phase of a clinical + trial based on the package 'interim'. + date_publication: '2019-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interimApp + url_git: '' +interleave: + version: 0.1.2 + title: Converts Tabular Data to Interleaved Vectors + maintainer: David Cooley + description: |- + Converts matrices and lists of matrices into a single vector by interleaving + their values. That is, each element of the result vector is filled from the input + matrices one row at a time. This is the same as transposing a matrix, then removing the + dimension attribute, but is designed to operate on matrices in nested list structures. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interleave + url_git: '' +interlineaR: + version: '1.0' + title: |- + Importing Interlinearized Corpora and Dictionaries as Produced + by Descriptive Linguistics Software + maintainer: Sylvain Loiseau + description: |- + Interlinearized glossed texts (IGT) are used in descriptive linguistics for + representing a morphological analysis of a text through a morpheme-by-morpheme gloss. + 'InterlineaR' provide a set of functions that targets several popular formats of IGT + ('SIL Toolbox', 'EMELD XML') and that turns an IGT into a set of data frames following + a relational model (the tables represent the different linguistic units: texts, + sentences, word, morphems). + The same pieces of software ('SIL FLEX', 'SIL Toolbox') typically produce dictionaries + of the morphemes used in the glosses. 'InterlineaR' provide a function for turning + the LIFT XML dictionary format into a set of data frames following a relational model + in order to represent the dictionary entries, the sense(s) attached to the entries, + the example(s) attached to senses, etc. + date_publication: '2018-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interlineaR + url_git: https://github.com/sylvainloiseau/interlineaR +InterNL: + version: 0.1.0 + title: Time Series Intervention Model Using Non-Linear Function + maintainer: Dr. Md Yeasin + description: 'Intervention analysis is used to investigate structural changes in + data resulting from external events. Traditional time series intervention models, + viz. Autoregressive Integrated Moving Average model with exogeneous variables + (ARIMA-X) and Artificial Neural Networks with exogeneous variables (ANN-X), rely + on linear intervention functions such as step or ramp functions, or their combinations. + In this package, the Gompertz, Logistic, Monomolecular, Richard and Hoerl function + have been used as non-linear intervention function. The equation of the above + models are represented as: Gompertz: A * exp(-B * exp(-k * t)); Logistic: K / + (1 + ((K - N0) / N0) * exp(-r * t)); Monomolecular: A * exp(-k * t); Richard: + A + (K - A) / (1 + exp(-B * (C - t)))^(1/beta) and Hoerl: a*(b^t)*(t^c).This package + introduced algorithm for time series intervention analysis employing ARIMA and + ANN models with a non-linear intervention function. This package has been developed + using algorithm of Yeasin et al. and Paul and + Yeasin .' + date_publication: '2024-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InterNL + url_git: '' +interp: + version: 1.1-6 + title: Interpolation Methods + maintainer: Albrecht Gebhardt + description: |- + Bivariate data interpolation on regular and irregular + grids, either linear or using splines are the main part of this + package. It is intended to provide FOSS replacement functions for + the ACM licensed akima::interp and tripack::tri.mesh functions. + Linear interpolation is implemented in + interp::interp(..., method="linear"), this corresponds to the call + akima::interp(..., linear=TRUE) which is the default setting and + covers most of akima::interp use cases in depending packages. + A re-implementation of Akimas irregular grid spline + interpolation (akima::interp(..., linear=FALSE)) is now also + available via interp::interp(..., method="akima"). + Estimators for partial derivatives are now also available in + interp::locpoly(), these are a prerequisite for the spline interpolation. + The basic part is a GPLed triangulation algorithm (sweep hull + algorithm by David Sinclair) providing the starting point for the + irregular grid interpolator. As side effect this algorithm is also + used to provide replacements for almost all functions of the tripack + package which also suffers from the same ACM license restrictions. + All functions are designed to be backward compatible with their + akima / tripack counterparts. + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interp + url_git: '' +interplex: + version: 0.1.2 + title: Coercion Methods for Simplicial Complex Data Structures + maintainer: Jason Cory Brunson + description: |- + Computational topology, which enables topological data analysis + (TDA), makes pervasive use of abstract mathematical objects called + simplicial complexes; see Edelsbrunner and Harer (2010) + . + Several R packages and other software libraries used through an R interface + construct and use data structures that represent simplicial complexes, + including mathematical graphs viewed as 1-dimensional complexes. + This package provides coercers (converters) between these data structures. + Currently supported structures are complete lists of simplices as used by + 'TDA'; the simplex trees of Boissonnat and Maria (2014) + as implemented in 'simplextree' and in + Python GUDHI (by way of 'reticulate'); and the graph classes of 'igraph' and + 'network', by way of the 'intergraph' package. + date_publication: '2024-02-20' + bug_reports: https://github.com/tdaverse/interplex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interplex + url_git: https://github.com/tdaverse/interplex +interplot: + version: 0.2.3 + title: Plot the Effects of Variables in Interaction Terms + maintainer: Yue Hu + description: |- + Plots the conditional coefficients ("marginal effects") of + variables included in multiplicative interaction terms. + date_publication: '2021-02-18' + bug_reports: https://github.com/sammo3182/interplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interplot + url_git: '' +interpolation: + version: 0.1.1 + title: Interpolation of Bivariate Functions + maintainer: Stéphane Laurent + description: |- + Provides two different methods, linear and nonlinear, to + interpolate a bivariate function, scalar-valued or vector-valued. + The interpolated data are not necessarily gridded. The algorithms + are performed by the 'C++' library 'CGAL' (). + date_publication: '2023-12-20' + bug_reports: https://github.com/stla/interpolation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interpolation + url_git: https://github.com/stla/interpolation +interpolators: + version: 1.0.1 + title: Some Interpolation Methods + maintainer: Stéphane Laurent + description: |- + Some interpolation methods taken from 'Boost': barycentric + rational interpolation, modified Akima interpolation, PCHIP (piecewise + cubic Hermite interpolating polynomial) interpolation, and Catmull-Rom + splines. + date_publication: '2023-11-10' + bug_reports: https://github.com/stla/interpolators/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interpolators + url_git: https://github.com/stla/interpolators +interpret: + version: 0.1.34 + title: Fit Interpretable Machine Learning Models + maintainer: Rich Caruana + description: Package for training interpretable machine learning models. Historically, + the most interpretable machine learning models were not very accurate, and the + most accurate models were not very interpretable. Microsoft Research has developed + an algorithm called the Explainable Boosting Machine (EBM) which has both high + accuracy and interpretable characteristics. EBM uses machine learning techniques + like bagging and boosting to breathe new life into traditional GAMs (Generalized + Additive Models). This makes them as accurate as random forests and gradient boosted + trees, and also enhances their intelligibility and editability. Details on the + EBM algorithm can be found in the paper by Rich Caruana, Yin Lou, Johannes Gehrke, + Paul Koch, Marc Sturm, and Noemie Elhadad (2015, ). + date_publication: '2024-11-28' + bug_reports: https://github.com/interpretml/interpret/issues + url: '' + url_cran: https://CRAN.R-project.org/package=interpret + url_git: https://github.com/interpretml/interpret +interpretCI: + version: 0.1.1 + title: Estimate the Confidence Interval and Interpret Step by Step + maintainer: Keon-Woong Moon + description: |- + Estimate confidence intervals for mean, proportion, mean difference + for unpaired and paired samples and proportion difference. Plot the confidence + intervals. Generate documents explaining the statistical result step by step. + date_publication: '2022-01-28' + bug_reports: '' + url: https://cardiomoon.github.io/interpretCI/ + url_cran: https://CRAN.R-project.org/package=interpretCI + url_git: https://github.com/cardiomoon/interpretCI +InterpretMSSpectrum: + version: 1.4.5 + title: Interpreting High Resolution Mass Spectra + maintainer: Jan Lisec + description: |- + High resolution mass spectrometry yields often large data sets of + spectra from compounds which are not present in available libraries. These + spectra need to be annotated and interpreted. + 'InterpretMSSpectrum' provides a set of functions to perform such tasks for + Electrospray-Ionization and Atmospheric-Pressure-Chemical-Ionization derived + data in positive and negative ionization mode. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InterpretMSSpectrum + url_git: https://github.com/janlisec/InterpretMSSpectrum +interpretR: + version: 0.2.5 + title: Binary Classifier and Regression Model Interpretation Functions + maintainer: Michel Ballings + description: |- + Compute permutation- based performance measures and create partial + dependence plots for (cross-validated) 'randomForest' and 'ada' models. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interpretR + url_git: '' +inters: + version: 0.2.0 + title: Flexible Tools for Estimating Interactions + maintainer: Matthew Blackwell + description: A set of functions to estimate interactions flexibly in the face of + possibly many controls. Implements the procedures described in Blackwell and Olson + (2022) . + date_publication: '2023-01-10' + bug_reports: https://github.com/mattblackwell/inters/issues + url: https://mattblackwell.github.io/inters/ + url_cran: https://CRAN.R-project.org/package=inters + url_git: '' +InterSIM: + version: 2.3.0 + title: Simulation of Inter-Related Genomic Datasets + maintainer: Prabhakar Chalise + description: 'Generates three inter-related genomic datasets: methylation, gene + expression and protein expression having user specified cluster patterns. The + simulation utilizes the realistic inter- and intra- relationships from real DNA + methylation, mRNA expression and protein expression data from the TCGA ovarian + cancer study, Chalise (2016) .' + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InterSIM + url_git: '' +InterVA4: + version: 1.7.6 + title: Replicate and Analyse 'InterVA4' + maintainer: Zehang Richard Li + description: Provides an R version of the 'InterVA4' software () + for coding cause of death from verbal autopsies. It also provides simple graphical + representation of individual and population level statistics. + date_publication: '2019-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InterVA4 + url_git: '' +InterVA5: + version: 1.1.3 + title: Replicate and Analyse 'InterVA5' + maintainer: Jason Thomas + description: Provides an R version of the 'InterVA5' software () + for coding cause of death from verbal autopsies. It also provides simple graphical + representation of individual and population level statistics. + date_publication: '2021-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InterVA5 + url_git: '' +interval: + version: 1.1-1.0 + title: Weighted Logrank Tests and NPMLE for Interval Censored Data + maintainer: Michael P. Fay + description: Functions to fit nonparametric survival curves, plot them, and perform + logrank or Wilcoxon type tests [see Fay and Shaw ]. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=interval + url_git: '' +intervalaverage: + version: 0.8.0 + title: Time-Weighted Averaging for Interval Data + maintainer: Michael Young + description: |- + Perform fast and memory efficient time-weighted averaging of values + measured over intervals into new arbitrary intervals. + This package is useful in the context of data measured or represented + as constant values over intervals on a one-dimensional discrete axis + (e.g. time-integrated averages of a curve over defined periods). + This package was written specifically to deal with air + pollution data recorded or predicted as averages over sampling periods. + Data in this format often needs to be shifted to non-aligned periods + or averaged up to periods of longer duration (e.g. averaging data measured over + sequential non-overlapping periods to calendar years). + date_publication: '2020-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intervalaverage + url_git: '' +IntervalQuestionStat: + version: 0.2.0 + title: Tools to Deal with Interval-Valued Responses in Questionnaires + maintainer: José García-García + description: |- + A user-friendly toolbox for doing the statistical analysis of + interval-valued responses in questionnaires measuring intrinsically + imprecise human attributes or features (attitudes, perceptions, opinions, + feelings, etc.). In particular, this package provides S4 classes, methods, + and functions in order to compute basic arithmetic and statistical operations + with interval-valued data; prepare customized plots; associate each + interval-valued response to its equivalent Likert-type and visual analogue + scales answers through the minimum theta-distance and the mid-point criteria; + analyze the reliability of respondents' answers from the internal consistency + point of view by means of Cronbach's alpha coefficient; and simulate + interval-valued responses in this type of questionnaires. The package also + incorporates some real-life data that can be used to illustrate its working + with several non-trivial reproducible examples. The methodology used in this + package is based in many theoretical and applied publications from + SMIRE+CoDiRE (Statistical Methods with Imprecise Random Elements and + Comparison of Distributions of Random Elements) Research Group + () + from the University of Oviedo (Spain). + date_publication: '2022-11-01' + bug_reports: https://github.com/garciagarjose/IntervalQuestionStat/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=IntervalQuestionStat + url_git: https://github.com/garciagarjose/IntervalQuestionStat/ +intervals: + version: 0.15.5 + title: Tools for Working with Points and Intervals + maintainer: Edzer Pebesma + description: Tools for working with and comparing sets of points and intervals. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intervals + url_git: https://github.com/edzer/intervals +IntervalSurgeon: + version: '1.3' + title: Operating on Integer-Bounded Intervals + maintainer: Daniel Greene + description: Manipulate integer-bounded intervals including finding overlaps, piling + and merging. + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IntervalSurgeon + url_git: '' +intervcomp: + version: 0.1.2 + title: Hypothesis Testing Using the Overlapping Interval Estimates + maintainer: Kimihiro Noguchi + description: |- + Performs hypothesis testing + using the interval estimates (e.g., confidence intervals). The + non-overlapping interval estimates indicates the statistical + significance. References to these procedures can be found at + Noguchi and Marmolejo-Ramos (2016) , + Bonett and Seier (2003) , and + Lemm (2006) . + date_publication: '2019-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intervcomp + url_git: '' +inTextSummaryTable: + version: 3.3.3 + title: Creation of in-Text Summary Table + maintainer: Laure Cougnaud + description: |- + Creation of tables of summary statistics or counts for clinical data (for 'TLFs'). + These tables can be exported as in-text table (with the 'flextable' package) for a Clinical Study Report + (Word format) or a 'topline' presentation (PowerPoint format), + or as interactive table (with the 'DT' package) to an html document for clinical data review. + date_publication: '2024-06-12' + bug_reports: https://github.com/openanalytics/inTextSummaryTable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inTextSummaryTable + url_git: https://github.com/openanalytics/inTextSummaryTable +inti: + version: 0.6.7 + title: Tools and Statistical Procedures in Plant Science + maintainer: Flavio Lozano-Isla + description: |- + The 'inti' package is part of the 'inkaverse' project for developing + different procedures and tools used in plant science and experimental designs. + The mean aim of the package is to support researchers during the planning of + experiments and data collection (tarpuy()), data analysis and graphics (yupana()) + , and technical writing. + Learn more about the 'inkaverse' project at . + date_publication: '2025-02-26' + bug_reports: https://github.com/flavjack/inti/issues/ + url: https://inkaverse.com/ + url_cran: https://CRAN.R-project.org/package=inti + url_git: https://github.com/flavjack/inti +intkrige: + version: 1.0.1 + title: A Numerical Implementation of Interval-Valued Kriging + maintainer: Brennan Bean + description: |- + An interval-valued extension of ordinary and simple kriging. + Optimization of the function is based on a generalized interval distance. + This creates a non-differentiable cost function that requires a + differentiable approximation to the absolute value function. This + differentiable approximation is optimized using a Newton-Raphson algorithm + with a penalty function to impose the constraints. Analyses in the package + are driven by the 'intsp' and 'intgrd' + classes, + which are interval-valued extensions of + 'SpatialPointsDataFrame' and 'SpatialPixelsDataFrame' respectively. + The package includes several wrappers to functions in the + 'gstat' and 'sp' packages. + date_publication: '2020-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intkrige + url_git: '' +intmap: + version: 1.0.0 + title: Ordered Containers with Integer Keys + maintainer: Stéphane Laurent + description: |- + Provides a key-value store data structure. The keys are + integers and the values can be any R object. This is like a list but + indexed by a set of integers, not necessarily contiguous and possibly + negative. The implementation uses a 'R6' class. These containers are + not faster than lists but their usage can be more convenient for + certain situations. + date_publication: '2023-04-17' + bug_reports: https://github.com/stla/intmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=intmap + url_git: https://github.com/stla/intmap +intmed: + version: 0.1.2 + title: Mediation Analysis using Interventional Effects + maintainer: Gary Chan + description: |- + Implementing the interventional effects for mediation analysis for up to 3 mediators. + The methods used are based on VanderWeele, Vansteelandt and Robins (2014) , + Vansteelandt and Daniel (2017) and Chan and Leung (2020; unpublished manuscript, available on request from the author of this package). + Linear regression, logistic regression and Poisson regression are used for continuous, binary + and count mediator/outcome variables respectively. + date_publication: '2020-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intmed + url_git: '' +IntNMF: + version: 1.3.0 + title: Integrative Clustering of Multiple Genomic Dataset + maintainer: Prabhakar Chalise + description: Carries out integrative clustering analysis using multiple types of + genomic dataset using integrative Non-negative Matrix factorization. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IntNMF + url_git: '' +intradayModel: + version: 0.0.1 + title: Modeling and Forecasting Financial Intraday Signals + maintainer: Daniel P. Palomar + description: |- + Models, analyzes, and forecasts financial intraday signals. This package + currently supports a univariate state-space model for intraday trading volume provided + by Chen (2016) . + date_publication: '2023-05-22' + bug_reports: https://github.com/convexfi/intradayModel/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=intradayModel + url_git: https://github.com/convexfi/intradayModel +inTrees: + version: '1.4' + title: Interpret Tree Ensembles + maintainer: Houtao Deng + description: 'For tree ensembles such as random forests, regularized random forests + and gradient boosted trees, this package provides functions for: extracting, measuring + and pruning rules; selecting a compact rule set; summarizing rules into a learner; + calculating frequent variable interactions; formatting rules in latex code. Reference: + Interpreting tree ensembles with inTrees (Houtao Deng, 2019, ).' + date_publication: '2024-04-23' + bug_reports: https://github.com/softwaredeng/inTrees/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inTrees + url_git: '' +intRegGOF: + version: 0.85-5 + title: Integrated Regression Goodness of Fit + maintainer: Jorge Luis Ojeda Cabrera + description: |- + Performs Goodness of Fit for regression models + using Integrated Regression method. Works for several + different fitting techniques. + date_publication: '2018-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intRegGOF + url_git: '' +INTRIGUE: + version: 0.1.0 + title: |- + Quantify and Control Reproducibility in High-Throughput + Experiments + maintainer: Michael Kleinsasser + description: |- + Estimate the proportions of the null and the reproducibility and + non-reproducibility of the signal group for the input data set. The Bayes factor + calculation and EM (Expectation Maximization) algorithm procedures are also + included. + date_publication: '2020-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=INTRIGUE + url_git: '' +intRinsic: + version: 1.1.0 + title: Likelihood-Based Intrinsic Dimension Estimators + maintainer: Francesco Denti + description: |- + Provides functions to estimate the intrinsic dimension of a dataset + via likelihood-based approaches. Specifically, the package implements the + 'TWO-NN' and 'Gride' estimators and the 'Hidalgo' Bayesian mixture model. + In addition, the first reference contains an extended vignette on the usage of + the 'TWO-NN' and 'Hidalgo' models. References: + Denti (2023, ); + Allegra et al. (2020, ); + Denti et al. (2022, ); + Facco et al. (2017, ); + Santos-Fernandez et al. (2021, ). + date_publication: '2024-09-12' + bug_reports: https://github.com/fradenti/intRinsic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=intRinsic + url_git: https://github.com/Fradenti/intRinsic +intrinsicDimension: + version: 1.2.0 + title: Intrinsic Dimension Estimation + maintainer: Kerstin Johnsson + description: A variety of methods for estimating intrinsic dimension of data sets + (i.e the manifold or Hausdorff dimension of the support of the distribution that + generated the data) as reviewed in Johnsson, K. (2016, ISBN:978-91-7623-921-6) + and Johnsson, K., Soneson, C. and Fontes, M. (2015) . + Furthermore, to evaluate the performance of these estimators, functions for generating + data sets with given intrinsic dimensions are provided. + date_publication: '2019-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intrinsicDimension + url_git: '' +intrinsicFRP: + version: 2.1.0 + title: An R Package for Factor Model Asset Pricing + maintainer: Alberto Quaini + description: |- + Functions for evaluating and testing asset pricing models, including + estimation and testing of factor risk premia, selection of "strong" risk + factors (factors having nonzero population correlation with test asset + returns), heteroskedasticity and autocorrelation robust covariance matrix + estimation and testing for model misspecification and identification. + The functions for estimating and testing factor risk + premia implement the Fama-MachBeth (1973) two-pass + approach, the misspecification-robust approaches of Kan-Robotti-Shanken (2013) + , and the approaches based on tradable factor risk + premia of Quaini-Trojani-Yuan (2023) . The + functions for selecting the "strong" risk factors are based on the Oracle + estimator of Quaini-Trojani-Yuan (2023) and the + factor screening procedure of Gospodinov-Kan-Robotti (2014) . + The functions for evaluating model misspecification implement the HJ + model misspecification distance of Kan-Robotti (2008) , + which is a modification of the prominent Hansen-Jagannathan (1997) + distance. + The functions for testing model identification + specialize the Kleibergen-Paap (2006) + and the Chen-Fang (2019) rank test + to the regression coefficient matrix of test asset returns on risk factors. + Finally, the function for heteroskedasticity and autocorrelation robust + covariance estimation implements the Newey-West (1994) + covariance estimator. + date_publication: '2024-04-15' + bug_reports: https://github.com/a91quaini/intrinsicFRP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=intrinsicFRP + url_git: https://github.com/a91quaini/intrinsicFRP +intrinsicKappa: + version: '0.1' + title: Sample Size Planning Based on Intrinsic Kappa Value + maintainer: David Schindler + description: 'Kappa statistics is one of the most used methods to evaluate the effectiveness + of inpsections based on attribute assessments in industry. However, its estimation + by available methods does not provide its "real" or "intrinstic" value. This package + provides functions for the computation of the intrinsic kappa value as it is described + in: Rafael Sanchez-Marquez, Frank Gerhorst and David Schindler (2023) "Effectiveness + of quality inspections of attributive characteristics – A novel and practical + method for estimating the “intrinsic” value of kappa based on alpha and beta statistics." + .' + date_publication: '2023-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intrinsicKappa + url_git: '' +intrval: + version: 0.1-3 + title: Relational Operators for Intervals + maintainer: Peter Solymos + description: |- + Evaluating if values + of vectors are within different open/closed intervals + (`x %[]% c(a, b)`), or if two closed + intervals overlap (`c(a1, b1) %[]o[]% c(a2, b2)`). + Operators for negation and directional relations also implemented. + date_publication: '2024-05-20' + bug_reports: https://github.com/psolymos/intrval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=intrval + url_git: https://github.com/psolymos/intrval +intRvals: + version: 1.0.1 + title: Analysis of Time-Ordered Event Data with Missed Observations + maintainer: Adriaan M. Dokter + description: Calculates event rates and compares means and variances of groups of + interval data corrected for missed arrival observations. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intRvals + url_git: '' +intSDM: + version: 2.1.1 + title: |- + Reproducible Integrated Species Distribution Models Across + Norway using 'INLA' + maintainer: Philip Mostert + description: |- + Integration of disparate datasets is needed in order to make efficient use of all available data and thereby address the issues currently threatening biodiversity. + Data integration is a powerful modeling framework which allows us to combine these datasets together into a single model, yet retain the strengths of each individual dataset. + We therefore introduce the package, 'intSDM': an R package designed to help ecologists develop a reproducible workflow of integrated species distribution models, using data both provided from the user as well as data obtained freely online. + An introduction to data integration methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) . + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=intSDM + url_git: '' +intsurv: + version: 0.2.2 + title: Integrative Survival Modeling + maintainer: Wenjie Wang + description: |- + Contains implementations of + integrative survival analysis routines, including + regular Cox cure rate model proposed by + Kuk and Chen (1992) + via an EM algorithm proposed by + Sy and Taylor (2000) , + regularized Cox cure rate model with elastic net penalty following + Masud et al. (2018) , and + Zou and Hastie (2005) , and + weighted concordance index for cure models proposed by + Asano and Hirakawa (2017) . + date_publication: '2021-01-08' + bug_reports: https://github.com/wenjie2wang/intsurv/issues + url: https://wwenjie.org/intsurv + url_cran: https://CRAN.R-project.org/package=intsurv + url_git: https://github.com/wenjie2wang/intsurv +intsvy: + version: '2.9' + title: International Assessment Data Manager + maintainer: Daniel Caro + description: |2- + + Provides tools for importing, merging, and analysing data from + international assessment studies (TIMSS, PIRLS, PISA, ICILS, and PIAAC). + date_publication: '2024-01-16' + bug_reports: https://github.com/eldafani/intsvy/issues + url: https://daniel-caro.com/r-intsvy/ + url_cran: https://CRAN.R-project.org/package=intsvy + url_git: https://github.com/eldafani/intsvy +inum: + version: 1.0-5 + title: Interval and Enum-Type Representation of Vectors + maintainer: Torsten Hothorn + description: |- + Enum-type representation of vectors and representation + of intervals, including a method of coercing variables in data frames. + date_publication: '2023-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inum + url_git: '' +invacost: + version: 1.1-6 + title: Analyse Biological Invasion Costs with the 'InvaCost' Database + maintainer: Boris Leroy + description: |- + Provides an up-to-date version of the 'InvaCost' database + () in R, and + several functions to analyse the costs of invasive alien species + (). + date_publication: '2024-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=invacost + url_git: '' +InvariantCausalPrediction: + version: '0.8' + title: Invariant Causal Prediction + maintainer: Nicolai Meinshausen + description: Confidence intervals for causal effects, using data collected in different + experimental or environmental conditions. Hidden variables can be included in + the model with a more experimental version. + date_publication: '2019-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InvariantCausalPrediction + url_git: '' +InvasionCorrection: + version: '0.1' + title: Invasion Correction + maintainer: Marcus Rosenblatt + description: The correction is achieved under the assumption that non-migrating + cells of the essay approximately form a quadratic flow profile due to frictional + effects, compare law of Hagen-Poiseuille for flow in a tube. The script fits a + conical plane to give xyz-coordinates of the cells. It outputs the number of migrated + cells and the new corrected coordinates. + date_publication: '2017-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InvasionCorrection + url_git: '' +invctr: + version: 0.2.0 + title: Infix Functions For Vector Operations + maintainer: Fred Hasselman + description: |- + Vector operations between grapes: An infix-only package! The 'invctr' functions perform common and less common operations on vectors, data frames matrices and list objects: + - Extracting a value (range), or, finding the indices of a value (range). + - Trimming, or padding a vector with a value of your choice. + - Simple polynomial regression. + - Set and membership operations. + - General check & replace function for NAs, Inf and other values. + date_publication: '2022-08-16' + bug_reports: https://github.com/FredHasselman/invctr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=invctr + url_git: https://github.com/FredHasselman/invctr +inventorize: + version: 1.1.1 + title: Inventory Analytics, Pricing and Markdowns + maintainer: Haytham Omar + description: |- + Simulate inventory policies with and without forecasting, facilitate inventory analysis calculations such as stock levels and re-order points,pricing and promotions calculations. + The package includes calculations of inventory metrics, stock-out calculations and ABC analysis calculations. + The package includes revenue management techniques such as Multi-product optimization,logit and polynomial model optimization. + The functions are referenced from : + 1-Harris, Ford W. (1913). "How many parts to make at once". Factory, The Magazine of Management. . + 2- Nahmias, S. Production and Operations Analysis. McGraw-Hill International Edition. . + 3-Silver, E.A., Pyke, D.F., Peterson, R. Inventory Management and Production Planning and Scheduling. . + 4-Ballou, R.H. Business Logistics Management. . Chapter 9. + 5-MIT Micromasters Program. + 6- Columbia University course for supply and demand analysis. + 8- Price Elasticity of Demand MATH 104,Mark Mac Lean (with assistance from Patrick Chan) 2011W + For further details or correspondence :, . + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=inventorize + url_git: '' +Inventorymodel: + version: 1.1.0.1 + title: Inventory Models + maintainer: Alejandro Saavedra Nieves + description: Determination of the optimal policy in inventory problems from a game-theoretic + perspective. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Inventorymodel + url_git: '' +inverseRegex: + version: 0.1.1 + title: Reverse Engineers Regular Expression Patterns for R Objects + maintainer: Jasper Watson + description: |- + Reverse engineer a regular expression pattern for the characters + contained in an R object. Individual characters can be categorised into + digits, letters, punctuation or spaces and encoded into run-lengths. This + can be used to summarise the structure of a dataset or identify non-standard + entries. Many non-character inputs such as numeric vectors and data frames + are supported. + date_publication: '2022-10-23' + bug_reports: https://github.com/rntq472/inverseRegex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=inverseRegex + url_git: '' +invertiforms: + version: 0.1.1 + title: Invertible Transforms for Matrices + maintainer: Alex Hayes + description: |- + Provides composable invertible transforms for + (sparse) matrices. + date_publication: '2022-11-25' + bug_reports: https://github.com/RoheLab/invertiforms/issues + url: https://rohelab.github.io/invertiforms/ + url_cran: https://CRAN.R-project.org/package=invertiforms + url_git: https://github.com/RoheLab/invertiforms +investr: + version: 1.4.2 + title: Inverse Estimation/Calibration Functions + maintainer: Brandon M. Greenwell + description: |- + Functions to facilitate inverse estimation (e.g., calibration) in + linear, generalized linear, nonlinear, and (linear) mixed-effects models. A + generic function is also provided for plotting fitted regression models with + or without confidence/prediction bands that may be of use to the general + user. For a general overview of these methods, see Greenwell and Schubert + Kabban (2014) . + date_publication: '2022-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=investr + url_git: https://github.com/bgreenwell/investr +invgamma: + version: '1.1' + title: The Inverse Gamma Distribution + maintainer: David Kahle + description: |- + Light weight implementation of the standard distribution + functions for the inverse gamma distribution, wrapping those for the gamma + distribution in the stats package. + date_publication: '2017-05-07' + bug_reports: https://github.com/dkahle/invgamma/issues + url: '' + url_cran: https://CRAN.R-project.org/package=invgamma + url_git: https://github.com/dkahle/invgamma +invgamstochvol: + version: 1.0.0 + title: |- + Obtains the Log Likelihood for an Inverse Gamma Stochastic + Volatility Model + maintainer: Blessings Majoni + description: |- + Computes the log likelihood for an inverse gamma stochastic volatility model using a closed form expression of the likelihood. The details of the computation of this closed form expression are given in Gonzalez and Majoni (2023) . + The closed form expression is obtained for a stationary inverse gamma stochastic volatility model by marginalising out the volatility. This allows the user to obtain the maximum likelihood estimator for this non linear non Gaussian state space model. In addition, the user can obtain the estimates of the smoothed volatility using the exact smoothing distributions. + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=invgamstochvol + url_git: '' +invGauss: + version: '1.2' + title: |- + Threshold Regression that Fits the (Randomized Drift) Inverse + Gaussian Distribution to Survival Data + maintainer: Hakon K. Gjessing + description: Fits the (randomized drift) inverse Gaussian distribution to survival + data. The model is described in Aalen OO, Borgan O, Gjessing HK. Survival and + Event History Analysis. A Process Point of View. Springer, 2008. It is based on + describing time to event as the barrier hitting time of a Wiener process, where + drift towards the barrier has been randomized with a Gaussian distribution. The + model allows covariates to influence starting values of the Wiener process and/or + average drift towards a barrier, with a user-defined choice of link functions. + date_publication: '2022-05-20' + bug_reports: '' + url: http://www.uib.no/smis/gjessing/projects/invgauss/ + url_cran: https://CRAN.R-project.org/package=invGauss + url_git: '' +invivoPKfit: + version: 2.0.0 + title: Fits Toxicokinetic Models to In Vivo PK Data Sets + maintainer: John Wambaugh + description: |- + Takes in vivo toxicokinetic concentration-time data and fits + parameters of 1-compartment and 2-compartment models for each + chemical. These methods are described in detail in "Informatics for Toxicokinetics" (submitted). + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=invivoPKfit + url_git: '' +InvStablePrior: + version: 0.1.1 + title: Inverse Stable Prior for Widely-Used Exponential Models + maintainer: Dexter Cahoy + description: Contains functions that allow Bayesian inference on a parameter of + some widely-used exponential models. The functions can generate independent samples + from the closed-form posterior distribution using the inverse stable prior. Inverse + stable is a non-conjugate prior for a parameter of an exponential subclass of + discrete and continuous data distributions (e.g. Poisson, exponential, inverse + gamma, double exponential (Laplace), half-normal/half-Gaussian, etc.). The prior + class provides flexibility in capturing a wide array of prior beliefs (right-skewed + and left-skewed) as modulated by a parameter that is bounded in (0,1). The generated + samples can be used to simulate the prior and posterior predictive distributions. + More details can be found in Cahoy and Sedransk (2019) . + The package can also be used as a teaching demo for introductory Bayesian courses. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=InvStablePrior + url_git: '' +iNZightMR: + version: 2.3.0 + title: Tools for Exploring Multiple Response Data + maintainer: Tom Elliott + description: |- + Interaction and analysis of multiple response data, + along with other tools for analysing these types of data including + missing value analysis and calculation of standard errors for + a range of covariance matrix results (proportions, multinomial, + independent samples, and multiple response). + date_publication: '2024-01-17' + bug_reports: https://github.com/iNZightVIT/iNZightMR/issues + url: https://inzight.nz + url_cran: https://CRAN.R-project.org/package=iNZightMR + url_git: '' +iNZightPlots: + version: 2.15.3 + title: Graphical Tools for Exploring Data with 'iNZight' + maintainer: Tom Elliott + description: Simple plotting function(s) for exploratory data analysis with flexible + options allowing for easy plot customisation. The goal is to make it easy for + beginners to start exploring a dataset through simple R function calls, as well + as provide a similar interface to summary statistics and inference information. + Includes functionality to generate interactive HTML-driven graphs. Used by 'iNZight', + a graphical user interface providing easy exploration and visualisation of data + for students of statistics, available in both desktop and online versions. + date_publication: '2023-10-14' + bug_reports: https://github.com/iNZightVIT/iNZightPlots/issues + url: https://inzight.nz + url_cran: https://CRAN.R-project.org/package=iNZightPlots + url_git: '' +iNZightRegression: + version: 1.3.4 + title: Tools for Exploring Regression Models with 'iNZight' + maintainer: Tom Elliott + description: Provides a suite of functions to use with regression models, including + summaries, residual plots, and factor comparisons. Used as part of the Model Fitting + module of 'iNZight', a graphical user interface providing easy exploration and + visualisation of data for students of statistics, available in both desktop and + online versions. + date_publication: '2024-04-05' + bug_reports: https://github.com/iNZightVIT/iNZightRegression/issues + url: https://inzight.nz + url_cran: https://CRAN.R-project.org/package=iNZightRegression + url_git: '' +iNZightTools: + version: 2.0.1 + title: Tools for 'iNZight' + maintainer: Tom Elliott + description: Provides a collection of wrapper functions for common variable and + dataset manipulation workflows primarily used by 'iNZight', a graphical user interface + providing easy exploration and visualisation of data for students of statistics, + available in both desktop and online versions. Additionally, many of the functions + return the 'tidyverse' code used to obtain the result in an effort to bridge the + gap between GUI and coding. + date_publication: '2023-10-12' + bug_reports: https://github.com/iNZightVIT/iNZightTools/issues + url: https://inzight.nz + url_cran: https://CRAN.R-project.org/package=iNZightTools + url_git: '' +iNZightTS: + version: 2.0.0 + title: Time Series for 'iNZight' + maintainer: Tom Elliott + description: 'Provides a collection of functions for working with time series data, + including functions for drawing, decomposing, and forecasting. Includes capabilities + to compare multiple series and fit both additive and multiplicative models. Used + by ''iNZight'', a graphical user interface providing easy exploration and visualisation + of data for students of statistics, available in both desktop and online versions. + Holt (1957) , Winters (1960) , + Cleveland, Cleveland, & Terpenning (1990) "STL: A Seasonal-Trend Decomposition + Procedure Based on Loess".' + date_publication: '2024-01-17' + bug_reports: https://github.com/iNZightVIT/iNZightTS/issues + url: https://inzight.nz + url_cran: https://CRAN.R-project.org/package=iNZightTS + url_git: '' +io: + version: 0.3.2 + title: A Unified Framework for Input-Output Operations in R + maintainer: David J. H. Shih + description: |- + One function to read files. One function to write files. One + function to direct plots to screen or file. Automatic file format inference + and directory structure creation. + date_publication: '2019-12-17' + bug_reports: https://bitbucket.org/djhshih/io/issues + url: '' + url_cran: https://CRAN.R-project.org/package=io + url_git: https://bitbucket.org/djhshih/io +ioanalysis: + version: 0.3.4 + title: Input Output Analysis + maintainer: John Wade + description: Calculates fundamental IO matrices (Leontief, Wassily W. (1951) ); + within period analysis via various rankings and coefficients (Sonis and Hewings + (2006) , Blair and Miller (2009) , + Antras et al (2012) , Hummels, Ishii, and Yi (2001) ); + across period analysis with impact analysis (Dietzenbacher, van der Linden, and + Steenge (2006) , Sonis, Hewings, and Guo (2006) + ); and a variety of table operators. + date_publication: '2020-09-18' + bug_reports: '' + url: http://www.real.illinois.edu + url_cran: https://CRAN.R-project.org/package=ioanalysis + url_git: '' +IOHanalyzer: + version: 0.1.8.10 + title: Data Analysis Part of 'IOHprofiler' + maintainer: Diederick Vermetten + description: |- + The data analysis module for the Iterative Optimization Heuristics + Profiler ('IOHprofiler'). This module provides statistical analysis methods for the + benchmark data generated by optimization heuristics, which can be visualized through a + web-based interface. The benchmark data is usually generated by the + experimentation module, called 'IOHexperimenter'. 'IOHanalyzer' also supports + the widely used 'COCO' (Comparing Continuous Optimisers) data format for benchmarking. + date_publication: '2024-03-01' + bug_reports: https://github.com/IOHprofiler/IOHAnalyzer/issues + url: https://iohanalyzer.liacs.nl + url_cran: https://CRAN.R-project.org/package=IOHanalyzer + url_git: https://github.com/IOHprofiler/IOHAnalyzer +IOLS: + version: 0.1.4 + title: Iterated Ordinary Least Squares Regression + maintainer: Nassim Zbalah + description: |- + Addresses the 'log of zero' by developing a new family of + estimators called iterated Ordinary Least Squares. + This family nests standard approaches such as log-linear and + Poisson regressions, offers several computational advantages, + and corresponds to the correct way to perform the popular + log(Y + 1) transformation. For more details about how to use it, + see the notebook at: . + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IOLS + url_git: '' +ioncopy: + version: 2.2.2 + title: Calling Copy Number Alterations in Amplicon Sequencing Data + maintainer: Jan Budczies + description: Method for the calculation of copy numbers and calling of copy number + alterations. The algorithm uses coverage data from amplicon sequencing of a sample + cohort as input. The method includes significance assessment, correction for multiple + testing and does not depend on normal DNA controls. Budczies (2016 Mar 15) . + date_publication: '2020-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ioncopy + url_git: '' +ionet: + version: 0.2.2 + title: Network Analysis for Input-Output Tables + maintainer: Shiying Xiao + description: Network functionalities specialized for data generated from input-output + tables. + date_publication: '2024-01-22' + bug_reports: https://github.com/Carol-seven/ionet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ionet + url_git: https://github.com/Carol-seven/ionet +ionr: + version: 0.3.0 + title: Test for Indifference of Indicator + maintainer: Uku Vainik + description: |- + Provides item exclusion procedure, which is a formal method to + test 'Indifference Of iNdicator' (ION). When a latent personality + trait-outcome association is assumed, then the association strength + should not depend on which subset of indicators (i.e. items) has been + chosen to reflect the trait. Personality traits are often measured + (reflected) by a sum-score of a certain set of indicators. + Item exclusion procedure randomly excludes items from a sum-score and + tests, whether the sum-score - outcome correlation changes. ION has been + achieved, when any item can be excluded from the sum-score without the + sum-score - outcome correlation substantially changing . For more details, + see Vainik, Mottus et. al, (2015) "Are Trait-Outcome Associations Caused + by Scales or Particular Items? Example Analysis of Personality Facets and + BMI",European Journal of Personality DOI: <10.1002/per.2009> . + date_publication: '2016-02-11' + bug_reports: '' + url: www.ut.ee/uku.vainik/ion/ + url_cran: https://CRAN.R-project.org/package=ionr + url_git: '' +iopsych: + version: 0.90.1 + title: Methods for Industrial/Organizational Psychology + maintainer: Allen Goebl + description: Collection of functions for IO Psychologists. + date_publication: '2016-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iopsych + url_git: '' +iosmooth: + version: '0.94' + title: Functions for Smoothing with Infinite Order Flat-Top Kernels + maintainer: Timothy L. McMurry + description: |- + Density, spectral density, and regression estimation using infinite + order flat-top kernels. + date_publication: '2017-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iosmooth + url_git: '' +iotables: + version: 0.9.3 + title: |- + Reproducible Input-Output Economics Analysis, Economic and + Environmental Impact Assessment with Empirical Data + maintainer: Daniel Antal + description: |- + Pre-processing and basic analytical tasks related to working + with Eurostat's symmetric input-output tables and provide basic + input-output economics calculations. The package is part of rOpenGov + to open source open government initiatives. + date_publication: '2024-01-08' + bug_reports: https://github.com/rOpenGov/iotables/issues + url: https://iotables.dataobservatory.eu/ + url_cran: https://CRAN.R-project.org/package=iotables + url_git: '' +iotarelr: + version: 0.1.5 + title: Iota Inter Coder Reliability for Content Analysis + maintainer: Berding Florian + description: |- + Routines and tools for assessing the quality of content + analysis on the basis of the Iota Reliability Concept. The concept is + inspired by item response theory and can be applied to any kind of + content analysis which uses a standardized coding scheme and discrete + categories. It is also applicable for content analysis conducted by + artificial intelligence. The package provides reliability measures + for a complete scale as well as for every single category. Analysis of + subgroup-invariance and error corrections are implemented. This + information can support the development process of a coding scheme and + allows a detailed inspection of the quality of the generated data. + Equations and formulas working in this package are part of Berding et + al. (2022) and Berding and Pargmann + (2022) . + date_publication: '2024-01-25' + bug_reports: https://github.com/FBerding/iotarelr/issues + url: https://fberding.github.io/iotarelr/ + url_cran: https://CRAN.R-project.org/package=iotarelr + url_git: '' +iotools: + version: 0.3-5 + title: I/O Tools for Streaming + maintainer: Simon Urbanek + description: Basic I/O tools for streaming and data parsing. + date_publication: '2023-12-02' + bug_reports: '' + url: https://www.rforge.net/iotools + url_cran: https://CRAN.R-project.org/package=iotools + url_git: '' +ip2location: + version: 8.1.3 + title: Lookup for IP Address Information + maintainer: Kai Wen Ooi + description: |- + Enables the user to find the country, region, district, city, coordinates, zip code, time zone, ISP, domain name, connection type, area code, weather, Mobile Country Code, Mobile Network Code, mobile brand name, elevation, usage type, address type, IAB category and Autonomous system information that any IP address or hostname originates from. Supported IPv4 and IPv6. + Please visit to learn more. You may also want to visit for free database download. + This package requires 'IP2Location Python' module. At the terminal, please run 'pip install IP2Location' to install the module. + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ip2location + url_git: https://github.com/ip2location/ip2location-r +ip2locationio: + version: 1.0.0 + title: |- + Lookup Geolocation and Proxy Information using 'IP2Location.io' + API + maintainer: IP2Location.io + description: |- + Query for enriched data such as country, region, city, latitude & longitude, ZIP code, time zone, Autonomous System, Internet Service Provider, domain, net speed, International direct dialing (IDD) code, area code, weather station data, mobile data, elevation, usage type, address type, advertisement category, and proxy data with an IP address. + This package uses the 'IP2Location.io' API to query this data. To get started with a free API key, sign up here . + date_publication: '2024-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ip2locationio + url_git: '' +ip2proxy: + version: 1.2.0 + title: Lookup for IP Address Proxy Information + maintainer: Kai Wen Ooi + description: |- + Enable user to find the IP addresses which are used as VPN anonymizer, open proxies, web proxies and Tor exits. + The package lookup the proxy IP address from IP2Proxy BIN Data file. You may visit for free database download. + date_publication: '2023-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ip2proxy + url_git: '' +ip2whois: + version: 1.0.0 + title: Lookup 'WHOIS' Information for a Particular Domain + maintainer: IP2WHOIS + description: |- + Easily implement the checking of 'WHOIS' information for a particular domain. 'IP2WHOIS' supports the query for 1113 Top-level Domains(TLDs) and 634 Country Code Top-level Domains(ccTLDs). + To get started with a free API key, you may sign up at here . + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ip2whois + url_git: '' +ipa: + version: 0.1.0 + title: Convert Between Phonetic Alphabets + maintainer: Alexander Rossell Hayes + description: |- + Converts character vectors between phonetic + representations. Supports IPA (International Phonetic Alphabet), + X-SAMPA (Extended Speech Assessment Methods Phonetic Alphabet), and + ARPABET (used by the CMU Pronouncing Dictionary). + date_publication: '2020-06-04' + bug_reports: https://github.com/rossellhayes/ipa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipa + url_git: https://github.com/rossellhayes/ipa +ipaddress: + version: 1.0.2 + title: Data Analysis for IP Addresses and Networks + maintainer: David Hall + description: |- + Classes and functions for working with IP (Internet Protocol) + addresses and networks, inspired by the Python 'ipaddress' module. + Offers full support for both IPv4 and IPv6 (Internet Protocol versions + 4 and 6) address spaces. It is specifically designed to work well with + the 'tidyverse'. + date_publication: '2023-12-01' + bug_reports: https://github.com/davidchall/ipaddress/issues + url: https://davidchall.github.io/ipaddress/ + url_cran: https://CRAN.R-project.org/package=ipaddress + url_git: https://github.com/davidchall/ipaddress +ipADMIXTURE: + version: 0.1.0 + title: Iterative Pruning Population Admixture Inference Framework + maintainer: Chainarong Amornbunchornvej + description: A data clustering package based on admixture ratios (Q matrix) of population + structure. The framework is based on iterative Pruning procedure that performs + data clustering by splitting a given population into subclusters until meeting + the condition of stopping criteria the same as ipPCA, iNJclust, and IPCAPS frameworks. + The package also provides a function to retrieve phylogeny tree that construct + a neighbor-joining tree based on a similar matrix between clusters. By given multiple + Q matrices with varying a number of ancestors (K), the framework define a similar + value between clusters i,j as a minimum number K* that makes majority of members + of two clusters are in the different clusters. This K* reflexes a minimum number + of ancestors we need to splitting cluster i,j into different clusters if we assign + K* clusters based on maximum admixture ratio of individuals. The publication of + this package is at Chainarong Amornbunchornvej, Pongsakorn Wangkumhang, and Sissades + Tongsima (2020) . + date_publication: '2020-03-26' + bug_reports: https://github.com/DarkEyes/ipADMIXTURE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipADMIXTURE + url_git: https://github.com/DarkEyes/ipADMIXTURE +ipanema: + version: 1.1.0 + title: Read Data from 'LimeSurvey' + maintainer: Maximilian Hagspiel + description: |- + Read data from 'LimeSurvey' + () + in a comfortable way. + Heavily inspired by 'limer' + (), + which lacked a few comfort features for me. + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipanema + url_git: https://gitlab.com/REDS1736/ipanema +ipbase: + version: 0.1.1 + title: Client for the 'ipbase.com' IP Geolocation API + maintainer: Dominik Kukacka + description: An R client for the 'ipbase.com' IP Geolocation API. The API requires + registration of an API key. Basic features are free, some require a paid subscription. + You can find the full API documentation at . + date_publication: '2023-05-11' + bug_reports: '' + url: https://ipbase.com + url_cran: https://CRAN.R-project.org/package=ipbase + url_git: '' +ipc: + version: 0.1.4 + title: Tools for Message Passing Between Processes + maintainer: Ian E. Fellows + description: |- + Provides tools for passing messages between R processes. + Shiny examples are provided showing how to perform useful tasks such as: + updating reactive values from within a future, progress bars for long running + async tasks, and interrupting async tasks based on user input. + date_publication: '2023-01-26' + bug_reports: https://github.com/fellstat/ipc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipc + url_git: https://github.com/fellstat/ipc +IPCAPS: + version: 1.1.8 + title: Iterative Pruning to Capture Population Structure + maintainer: Kridsadakorn Chaichoompu + description: An unsupervised clustering algorithm based on iterative pruning is + for capturing population structure. This version supports ordinal data which can + be applied directly to SNP data to identify fine-level population structure and + it is built on the iterative pruning Principal Component Analysis ('ipPCA') algorithm + as explained in Intarapanich et al. (2009) . The + 'IPCAPS' involves an iterative process using multiple splits based on multivariate + Gaussian mixture modeling of principal components and 'Expectation-Maximization' + clustering as explained in Lebret et al. (2015) . In + each iteration, rough clusters and outliers are also identified using the function + rubikclust() from the R package 'KRIS'. + date_publication: '2021-01-25' + bug_reports: https://gitlab.com/kris.ccp/ipcaps/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IPCAPS + url_git: https://gitlab.com/kris.ccp/ipcaps +IPCWK: + version: '1.0' + title: Kendall's Tau Partial Corr. for Survival Trait and Biomarkers + maintainer: Jie-Huei Wang + description: We propose the inverse probability-of-censoring weighted (IPCW) Kendall's + tau to measure the association of the survival trait with biomarkers and Kendall's + partial correlation to reflect the relationship of the survival trait with interaction + variable conditional on main effects, as described in Wang and Chen (2020) . + date_publication: '2020-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IPCWK + url_git: '' +ipcwswitch: + version: 1.0.4 + title: |- + Inverse Probability of Censoring Weights to Deal with Treatment + Switch in Randomized Clinical Trials + maintainer: Nathalie Graffeo + description: Contains functions for formatting clinical trials data and implementing + inverse probability of censoring weights to handle treatment switches when estimating + causal treatment effect in randomized clinical trials. + date_publication: '2021-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipcwswitch + url_git: '' +ipd: + version: 0.1.4 + title: Inference on Predicted Data + maintainer: Stephen Salerno + description: Performs valid statistical inference on predicted data (IPD) using + recent methods, where for a subset of the data, the outcomes have been predicted + by an algorithm. Provides a wrapper function with specified defaults for the type + of model and method to be used for estimation and inference. Further provides + methods for tidying and summarizing results. Salerno et al., (2024) . + date_publication: '2025-01-07' + bug_reports: https://github.com/ipd-tools/ipd/issues + url: https://ipd-tools.github.io/ipd/ + url_cran: https://CRAN.R-project.org/package=ipd + url_git: https://github.com/ipd-tools/ipd +IPDfromKM: + version: 0.1.10 + title: Map Digitized Survival Curves Back to Individual Patient Data + maintainer: Na Liu + description: |2- + + An implementation to reconstruct individual patient data from Kaplan-Meier (K-M) survival curves, visualize and assess the accuracy of the reconstruction, then perform secondary analysis on the reconstructed data. We involve a simple function to extract the coordinates form the published K-M curves. The function is developed based on Poisot T. ’s digitize package (2011) . For more complex and tangled together graphs, digitizing software, such as 'DigitizeIt' (for MAC or windows) or 'ScanIt'(for windows) can be used to get the coordinates. Additional information should also be involved to increase the accuracy, like numbers of patients at risk (often reported at 5-10 time points under the x-axis of the K-M graph), total number of patients, and total number of events. The package implements the modified iterative K-M estimation algorithm (modified-iKM) improved upon the approach proposed by Guyot (2012) with some modifications. + date_publication: '2020-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IPDfromKM + url_git: '' +ipdw: + version: 2.0-0 + title: Spatial Interpolation by Inverse Path Distance Weighting + maintainer: Jemma Stachelek + description: |- + Functions are provided to interpolate geo-referenced point data via + Inverse Path Distance Weighting. Useful for coastal marine applications where + barriers in the landscape preclude interpolation with Euclidean distances. + date_publication: '2023-01-05' + bug_reports: https://github.com/jsta/ipdw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipdw + url_git: https://github.com/jsta/ipdw +ipeadatar: + version: 0.1.6 + title: API Wrapper for 'Ipeadata' + maintainer: Luiz Eduardo S. Gomes + description: |- + Allows direct access to the macroeconomic, + financial and regional database maintained by + Brazilian Institute for Applied Economic Research ('Ipea'). + This R package uses the 'Ipeadata' API. For more information, + see . + date_publication: '2022-02-03' + bug_reports: https://github.com/gomesleduardo/ipeadatar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipeadatar + url_git: https://github.com/gomesleduardo/ipeadatar +ipeaplot: + version: 0.4.1 + title: Add Ipea Editorial Standards to 'ggplot2' Graphics + maintainer: Pedro Ferreira + description: |- + Convenient functions to create 'ggplot2' graphics following the + editorial guidelines of the Institute for Applied Economic + Research (Ipea). + date_publication: '2025-02-26' + bug_reports: https://github.com/ipeadata-lab/ipeaplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipeaplot + url_git: https://github.com/ipeadata-lab/ipeaplot +IPEC: + version: 1.1.0 + title: Root Mean Square Curvature Calculation + maintainer: Peijian Shi + description: Calculates the RMS intrinsic and parameter-effects curvatures of a + nonlinear regression model. The curvatures are global measures of assessing whether + a model/data set combination is close-to-linear or not. See Bates and Watts (1980) + and Ratkowsky and Reddy (2017) + for details. + date_publication: '2024-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IPEC + url_git: '' +IPEDS: + version: 0.1.0 + title: Data from the Integrated Post-Secondary Education Data System + maintainer: Aushanae Haller + description: Contains data on Post-Secondary Institution Statistics in 2020 . + The package allows easy access to a wide variety of information regarding Post-secondary + Institutions, its students, faculty, and their demographics, financial aid, educational + and recreational offerings, and completions. This package can be used by students, + college counselors, or involved parents interested in pursuing higher education, + considering their options, and securing admission into their school of choice. + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IPEDS + url_git: '' +IPEDSuploadables: + version: 2.10.0 + title: |- + Transforms Institutional Data into Text Files for IPEDS + Automated Import/Upload + maintainer: Alison Lanski + description: |- + Starting from user-supplied institutional data, these scripts + transform, aggregate, and reshape the information to produce + key-value pair data files that are able to be uploaded to IPEDS (Integrated Postsecondary Education Data System) + through their submission portal . Starting data specifications can be found in the vignettes. + Final files are saved locally to a location of the user's choice. + User-friendly readable files can also be produced for purposes of data review and validation. + date_publication: '2024-12-08' + bug_reports: https://github.com/AlisonLanski/IPEDSuploadables/issues + url: https://alisonlanski.github.io/IPEDSuploadables/ + url_cran: https://CRAN.R-project.org/package=IPEDSuploadables + url_git: https://github.com/AlisonLanski/IPEDSuploadables +iperform: + version: 0.0.3 + title: Time Series Performance + maintainer: Patrick Ilunga + description: A tool to calculate the performance of a time series in a specific + date or period. It is more intended for data analysis in the fields of finance, + banking, telecommunications or operational marketing. + date_publication: '2024-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iperform + url_git: '' +ipflasso: + version: '1.1' + title: Integrative Lasso with Penalty Factors + maintainer: Anne-Laure Boulesteix + description: The core of the package is cvr2.ipflasso(), an extension of glmnet + to be used when the (large) set of available predictors is partitioned into several + modalities which potentially differ with respect to their information content + in terms of prediction. For example, in biomedical applications patient outcome + such as survival time or response to therapy may have to be predicted based on, + say, mRNA data, miRNA data, methylation data, CNV data, clinical data, etc. The + clinical predictors are on average often much more important for outcome prediction + than the mRNA data. The ipflasso method takes this problem into account by using + different penalty parameters for predictors from different modalities. The ratio + between the different penalty parameters can be chosen from a set of optional + candidates by cross-validation or alternatively generated from the input data. + date_publication: '2019-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipflasso + url_git: '' +ipfp: + version: 1.0.2 + title: |- + Fast Implementation of the Iterative Proportional Fitting + Procedure in C + maintainer: Alexander W Blocker + description: |- + A fast (C) implementation of the iterative proportional fitting + procedure. + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipfp + url_git: https://github.com/awblocker/ipfp +ipfr: + version: 1.0.2 + title: List Balancing for Reweighting and Population Synthesis + maintainer: Kyle Ward + description: |- + Performs iterative proportional updating given a seed table and + an arbitrary number of marginal distributions. This is commonly used in + population synthesis, survey raking, matrix rebalancing, and other + applications. For example, a household survey may be weighted to match the + known distribution of households by size from the census. An origin/ + destination trip matrix might be balanced to match traffic counts. + The approach used by this package is based on a paper from + Arizona State University (Ye, Xin, et. al. (2009) + ). + Some enhancements have been made to their work including primary and + secondary target balance/importance, general marginal agreement, and weight + restriction. + date_publication: '2020-04-01' + bug_reports: https://github.com/dkyleward/ipfr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipfr + url_git: https://github.com/dkyleward/ipfr +ipft: + version: 0.7.2 + title: Indoor Positioning Fingerprinting Toolset + maintainer: Emilio Sansano + description: |- + Algorithms and utility functions for indoor positioning using fingerprinting techniques. + These functions are designed for manipulation of RSSI (Received Signal Strength Intensity) data + sets, estimation of positions,comparison of the performance of different models, and graphical + visualization of data. Machine learning algorithms and methods such as k-nearest neighbors or + probabilistic fingerprinting are implemented in this package to perform analysis + and estimations over RSSI data sets. + date_publication: '2018-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipft + url_git: '' +ipkg: + version: 1.1.2 + title: |- + Install R Packages or Download File from GitHub via the Proxy + Site + maintainer: Xinyuan Chu + description: |- + When you want to install R package or download file from GitHub, + but you can't access GitHub, this package helps you install R packages or + download file from GitHub via the proxy website + or , which is in real-time sync with GitHub. + date_publication: '2025-02-27' + bug_reports: https://gitlab.com/chuxinyuan/ipkg/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipkg + url_git: https://gitlab.com/chuxinyuan/ipkg +IPLGP: + version: 2.0.5 + title: Identification of Parental Lines via Genomic Prediction + maintainer: Ping-Yuan Chung + description: |- + Combining genomic prediction with Monte Carlo simulation, three different + strategies are implemented to select parental lines for multiple traits in plant + breeding. The selection strategies include (i) GEBV-O considers only genomic + estimated breeding values (GEBVs) of the candidate individuals; (ii) GD-O + considers only genomic diversity (GD) of the candidate individuals; and (iii) + GEBV-GD considers both GEBV and GD. The above method can be seen in Chung PY, + Liao CT (2020) . Multi-trait genomic best + linear unbiased prediction (MT-GBLUP) model is used to simultaneously estimate + GEBVs of the target traits, and then a selection index is adopted to evaluate + the composite performance of an individual. + date_publication: '2024-08-01' + bug_reports: https://github.com/py-chung/IPLGP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IPLGP + url_git: https://github.com/py-chung/IPLGP +iplookupapi: + version: 0.1.0 + title: Client for the 'iplookupapi.com' IP Lookup API + maintainer: Dominik Kukacka + description: An R client for the 'iplookupapi.com' IP Lookup API. The API requires + registration of an API key. Basic features are free, some require a paid subscription. + You can find the full API documentation at . + date_publication: '2023-05-11' + bug_reports: '' + url: https://iplookupapi.com + url_cran: https://CRAN.R-project.org/package=iplookupapi + url_git: '' +iplots: + version: 1.1-8 + title: iPlots - Interactive Graphics for R + maintainer: Simon Urbanek + description: Interactive plots for R. + date_publication: '2022-05-01' + bug_reports: https://github.com/s-u/iplots/issues + url: http://www.iPlots.org/ + url_cran: https://CRAN.R-project.org/package=iplots + url_git: '' +IPMbook: + version: 0.1.5 + title: Functions and Data for the Book 'Integrated Population Models' + maintainer: Ken Kellner + description: 'Provides functions and data sets to accompany the book ''Integrated + Population Models: Theory and Ecological Applications with R and JAGS'' by Michael + Schaub and Marc Kéry (ISBN: 9780128205648).' + date_publication: '2023-08-21' + bug_reports: https://github.com/kenkellner/IPMbook/issues + url: https://www.vogelwarte.ch/de/projekte/publikationen/ipm/ + url_cran: https://CRAN.R-project.org/package=IPMbook + url_git: '' +ipmr: + version: 0.0.7 + title: Integral Projection Models + maintainer: Sam Levin + description: |- + Flexibly implements Integral Projection Models using a + mathematical(ish) syntax. This package will not help with the vital rate + modeling process, but will help convert those regression models into an + IPM. 'ipmr' handles density dependence and environmental stochasticity, with a + couple of options for implementing the latter. In addition, provides functions + to avoid unintentional eviction of individuals from models. Additionally, + provides model diagnostic tools, plotting functionality, + stochastic/deterministic simulations, and analysis tools. + Integral projection models are described in depth by Easterling et al. (2000) + , Merow et al. (2013) + , Rees et al. (2014) , + and Metcalf et al. (2015) . + Williams et al. (2012) discuss the problem of + unintentional eviction. + date_publication: '2023-02-16' + bug_reports: https://github.com/padrinoDB/ipmr/issues + url: https://padrinoDB.github.io/ipmr/ + url_cran: https://CRAN.R-project.org/package=ipmr + url_git: https://github.com/padrinoDB/ipmr +ipolygrowth: + version: 1.0.0 + title: |- + Individual Growth Curve Parameter Calculation using Polynomial + Functions + maintainer: Jifan Wang + description: |- + Calculation of key bacterial growth curve parameters using fourth degree polynomial functions. + Six growth curve parameters are provided including peak growth rate, doubling time, lag time, maximum growth, and etc. + 'ipolygrowth' takes time series data from individual biological samples (with technical replicates) or multiple samples. + date_publication: '2024-08-29' + bug_reports: https://github.com/kivanvan/ipolygrowth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ipolygrowth + url_git: https://github.com/kivanvan/ipolygrowth +IPPP: + version: '1.1' + title: Inhomogeneous Poisson Point Processes + maintainer: Niklas Hohmann + description: Generates random numbers corresponding to the events on a Poisson point + process with changing event rates. This includes the possibility to incorporate + additional information such as the number of events occurring or the location + of an already known event. It can also generate the probability density functions + of specific events in the cases where additional information is available. Based + on Hohmann (2019) . + date_publication: '2019-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IPPP + url_git: '' +ipr: + version: 0.1.0 + title: Iterative Proportional Repartition Algorithm + maintainer: Jean-Benoit Rossel + description: Let us consider a sample of patients who can suffer from several diseases + simultaneously, in a given set of diseases. The goal of the implemented algorithm + is to estimate the individual average cost of each disease, starting from the + global health costs available for each patient. + date_publication: '2020-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipr + url_git: '' +ipred: + version: 0.9-15 + title: Improved Predictors + maintainer: Torsten Hothorn + description: |- + Improved predictive models by indirect classification and + bagging for classification, regression and survival problems + as well as resampling based estimators of prediction error. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipred + url_git: '' +iprior: + version: 0.7.4 + title: Regression Modelling using I-Priors + maintainer: Haziq Jamil + description: |- + Provides methods to perform and analyse I-prior regression models. + Estimation is done either via direct optimisation of the log-likelihood or + an EM algorithm. + date_publication: '2024-04-01' + bug_reports: https://github.com/haziqj/iprior/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iprior + url_git: https://github.com/haziqj/iprior +iPRISM: + version: 0.1.1 + title: |- + Intelligent Predicting Response to Cancer Immunotherapy Through + Systematic Modeling + maintainer: Junwei Han + description: |- + Immunotherapy has revolutionized cancer treatment, but predicting patient + response remains challenging. Here, we presented Intelligent Predicting + Response to cancer Immunotherapy through Systematic Modeling (iPRISM), a + novel network-based model that integrates multiple data types to predict + immunotherapy outcomes. It incorporates gene expression, biological + functional network, tumor microenvironment characteristics, immune-related + pathways, and clinical data to provide a comprehensive view of factors + influencing immunotherapy efficacy. By identifying key genetic and + immunological factors, it provides an insight for more personalized + treatment strategies and combination therapies to overcome resistance + mechanisms. + date_publication: '2024-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iPRISM + url_git: '' +ips: + version: 0.0.12 + title: Interfaces to Phylogenetic Software in R + maintainer: Christoph Heibl + description: |- + Functions that wrap popular phylogenetic software for sequence + alignment, masking of sequence alignments, and estimation of phylogenies and + ancestral character states. + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ips + url_git: '' +ipsecr: + version: 1.4.2 + title: Spatially Explicit Capture-Recapture by Inverse Prediction + maintainer: Murray Efford + description: |- + Estimates the density of a spatially distributed animal population + sampled with an array of passive detectors, such as traps. Models incorporating + distance-dependent detection are fitted by simulation and inverse prediction + as proposed by Efford (2004) . + date_publication: '2025-01-24' + bug_reports: '' + url: https://www.otago.ac.nz/density/ + url_cran: https://CRAN.R-project.org/package=ipsecr + url_git: https://github.com/MurrayEfford/ipsecr/ +ipsfs: + version: 1.0.0 + title: |- + Intuitionistic, Pythagorean, and Spherical Fuzzy Similarity + Measure + maintainer: Rama Ranjan Panda + description: Advanced fuzzy logic based techniques are implemented to compute the + similarity among different objects or items. Typically, application areas consist + of transforming raw data into the corresponding advanced fuzzy logic representation + and determining the similarity between two objects using advanced fuzzy similarity + techniques in various fields of research, such as text classification, pattern + recognition, software projects, decision-making, medical diagnosis, and market + prediction. Functions are designed to compute the membership, non-membership, + hesitant-membership, indeterminacy-membership, and refusal-membership for the + input matrices. Furthermore, it also includes a large number of advanced fuzzy + logic based similarity measure functions to compute the Intuitionistic fuzzy similarity + (IFS), Pythagorean fuzzy similarity (PFS), and Spherical fuzzy similarity (SFS) + between two objects or items based on their fuzzy relationships. It also includes + working examples for each function with sample data sets. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipsfs + url_git: '' +ipsRdbs: + version: 1.0.0 + title: |- + Introduction to Probability, Statistics and R for Data-Based + Sciences + maintainer: Sujit K. Sahu + description: |- + Contains data sets, programmes and illustrations + discussed in the book, "Introduction to Probability, Statistics and R: + Foundations for Data-Based Sciences." Sahu (2024, isbn:9783031378645) + describes the methods in detail. + date_publication: '2024-04-10' + bug_reports: https://github.com/sujit-sahu/ipsRdbs/issues + url: https://www.sujitsahu.com + url_cran: https://CRAN.R-project.org/package=ipsRdbs + url_git: '' +ipumsr: + version: 0.8.2 + title: An R Interface for Downloading, Reading, and Handling IPUMS Data + maintainer: Derek Burk + description: |- + An easy way to work with census, survey, and geographic data + provided by IPUMS in R. Generate and download data through the IPUMS + API and load IPUMS files into R with their associated metadata to + make analysis easier. IPUMS data describing 1.4 billion individuals + drawn from over 750 censuses and surveys is available free of charge + from the IPUMS website . + date_publication: '2025-02-24' + bug_reports: https://github.com/ipums/ipumsr/issues + url: https://tech.popdata.org/ipumsr/ + url_cran: https://CRAN.R-project.org/package=ipumsr + url_git: https://github.com/ipums/ipumsr +IPV: + version: 1.0.0 + title: Item Pool Visualization + maintainer: Nils Petras + description: |- + Generate plots based on the Item Pool Visualization concept for + latent constructs. Item Pool Visualizations are used to display the + conceptual structure of a set of items (self-report or psychometric). + Dantlgraber, Stieger, & Reips (2019) . + date_publication: '2022-09-30' + bug_reports: https://github.com/NilsPetras/IPV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IPV + url_git: https://github.com/NilsPetras/IPV +ipw: + version: 1.2.1 + title: Estimate Inverse Probability Weights + maintainer: Willem M. van der Wal + description: |- + Functions to estimate the probability to receive the observed treatment, based on + individual characteristics. The inverse of these probabilities can be used as weights when + estimating causal effects from observational data via marginal structural models. Both point + treatment situations and longitudinal studies can be analysed. The same functions can be used to + correct for informative censoring. + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipw + url_git: '' +IPWboxplot: + version: 0.1.2 + title: Adapted Boxplot to Missing Observations + maintainer: Ana Perez-Gonzalez + description: Boxplots adapted to the happenstance of missing observations where + drop-out probabilities can be given by the practitioner or modelled using auxiliary + covariates. The paper of "Zhang, Z., Chen, Z., Troendle, J. F. and Zhang, J.(2012) + ", proposes estimators of marginal quantiles + based on the Inverse Probability Weighting method. + date_publication: '2023-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IPWboxplot + url_git: '' +ipwCoxCSV: + version: '1.0' + title: |- + Inverse Probability Weighted Cox Model with Corrected Sandwich + Variance + maintainer: Di Shu + description: An implementation of corrected sandwich variance (CSV) estimation method + for making inference of marginal hazard ratios (HR) in inverse probability weighted + (IPW) Cox model without and with clustered data, proposed by Shu, Young, Toh, + and Wang (2019) in their paper under revision for Biometrics. Both conventional + inverse probability weights and stabilized weights are implemented. Logistic regression + model is assumed for propensity score model. + date_publication: '2019-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipwCoxCSV + url_git: '' +ipwErrorY: + version: '2.1' + title: |- + Inverse Probability Weighted Estimation of Average Treatment + Effect with Misclassified Binary Outcome + maintainer: Di Shu + description: An implementation of the correction methods proposed by Shu and Yi + (2017) for the inverse probability weighted (IPW) + estimation of average treatment effect (ATE) with misclassified binary outcomes. + Logistic regression model is assumed for treatment model for all implemented correction + methods, and is assumed for the outcome model for the implemented doubly robust + correction method. Misclassification probability given a true value of the outcome + is assumed to be the same for all individuals. + date_publication: '2019-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ipwErrorY + url_git: '' +iq: + version: 1.10.1 + title: Protein Quantification in Mass Spectrometry-Based Proteomics + maintainer: Thang Pham + description: |- + An implementation of the MaxLFQ algorithm by + Cox et al. (2014) in a comprehensive + pipeline for processing proteomics data in data-independent acquisition mode + (Pham et al. 2020 ). + It offers additional options for protein quantification using + the N most intense fragment ions, using all fragment ions, and + a wrapper for the median polish algorithm by Tukey (1977, ISBN:0201076160). + In general, the tool can be used to integrate multiple + proportional observations into a single quantitative value. + date_publication: '2024-12-04' + bug_reports: https://github.com/tvpham/iq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iq + url_git: https://github.com/tvpham/iq +IQCC: + version: '0.7' + title: Improved Quality Control Charts + maintainer: Flavio Barros + description: |- + Builds statistical control charts with exact limits for + univariate and multivariate cases. + date_publication: '2017-11-15' + bug_reports: https://github.com/flaviobarros/IQCC/issues + url: https://flaviobarros.github.io/IQCC + url_cran: https://CRAN.R-project.org/package=IQCC + url_git: '' +ir: + version: 0.2.1 + title: Functions to Handle and Preprocess Infrared Spectra + maintainer: Henning Teickner + description: |2- + + Functions to import and handle infrared spectra (import from '.csv' and + Thermo Galactic's '.spc', baseline correction, binning, clipping, + interpolating, smoothing, averaging, adding, subtracting, dividing, + multiplying, plotting). + date_publication: '2022-05-02' + bug_reports: '' + url: https://henningte.github.io/ir/ + url_cran: https://CRAN.R-project.org/package=ir + url_git: '' +irace: + version: 4.2.0 + title: Iterated Racing for Automatic Algorithm Configuration + maintainer: Manuel López-Ibáñez + description: |- + Iterated race is an extension of the Iterated F-race method for + the automatic configuration of optimization algorithms, that is, + (offline) tuning their parameters by finding the most appropriate + settings given a set of instances of an optimization problem. + M. López-Ibáñez, J. Dubois-Lacoste, L. Pérez Cáceres, T. Stützle, + and M. Birattari (2016) . + date_publication: '2025-02-12' + bug_reports: https://github.com/MLopez-Ibanez/irace/issues + url: https://mlopez-ibanez.github.io/irace/ + url_cran: https://CRAN.R-project.org/package=irace + url_git: https://github.com/MLopez-Ibanez/irace +iraceplot: + version: 2.1.0 + title: Plots for Visualizing the Data Produced by the 'irace' Package + maintainer: Manuel López-Ibáñez + description: Graphical visualization tools for analyzing the data produced by 'irace'. + The 'iraceplot' package enables users to analyze the performance and the parameter + space data sampled by the configuration during the search process. It provides + a set of functions that generate different plots to visualize the configurations + sampled during the execution of 'irace' and their performance. The functions just + require the log file generated by 'irace' and, in some cases, they can be used + with user-provided data. + date_publication: '2025-02-11' + bug_reports: https://github.com/auto-optimization/iraceplot/issues + url: https://auto-optimization.github.io/iraceplot/ + url_cran: https://CRAN.R-project.org/package=iraceplot + url_git: https://github.com/auto-optimization/iraceplot/ +irboost: + version: 0.2-1.0 + title: Iteratively Reweighted Boosting for Robust Analysis + maintainer: Zhu Wang + description: Fit a predictive model using iteratively reweighted boosting (IRBoost) + to minimize robust loss functions within the CC-family (concave-convex). This + constitutes an application of iteratively reweighted convex optimization (IRCO), + where convex optimization is performed using the functional descent boosting algorithm. + IRBoost assigns weights to facilitate outlier identification. Applications include + robust generalized linear models and robust accelerated failure time models. Wang + (2025) . + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irboost + url_git: '' +IRCcheck: + version: 1.0.0 + title: Irrepresentable Condition Check + maintainer: Donald Williams + description: |- + Check the irrepresentable condition (IRC) in both L1-regularized regression + and Gaussian graphical models. The IRC requires that the important and unimportant variables + are not correlated, at least not all that much, and it is necessary for consistent model + selection. Exploring the IRC as a function of the number of variables, assumed sparsity, + and effect size can provide valuable insights into the model selection + properties of L1-regularization. + date_publication: '2021-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IRCcheck + url_git: '' +ircor: + version: '1.0' + title: Correlation Coefficients for Information Retrieval + maintainer: Julián Urbano + description: |- + Provides implementation of various correlation coefficients of common use in + Information Retrieval. In particular, it includes Kendall (1970, isbn:0852641990) tau coefficient + as well as tau_a and tau_b for the treatment of ties. It also includes Yilmaz et al. (2008) + tauAP correlation coefficient, and versions tauAP_a and tauAP_b + developed by Urbano and Marrero (2017) to cope with ties. + date_publication: '2017-08-21' + bug_reports: https://github.com/julian-urbano/ircor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ircor + url_git: https://github.com/julian-urbano/ircor/ +IRdisplay: + version: '1.1' + title: '''Jupyter'' Display Machinery' + maintainer: Philipp Angerer + description: |2- + + An interface to the rich display capabilities of 'Jupyter' front-ends (e.g. 'Jupyter Notebook') . + Designed to be used from a running 'IRkernel' session . + date_publication: '2022-01-04' + bug_reports: https://github.com/IRkernel/IRdisplay/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=IRdisplay + url_git: https://github.com/IRkernel/IRdisplay +iRegression: + version: 1.2.1 + title: Regression Methods for Interval-Valued Variables + maintainer: Eufrasio de A. Lima Neto + description: Contains some important regression methods for interval-valued variables. + For each method, it is available the fitted values, residuals and some goodness-of-fit + measures. + date_publication: '2016-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iRegression + url_git: '' +iRepro: + version: '1.2' + title: Reproducibility for Interval-Censored Data + maintainer: Jelena Kovacic + description: Calculates intraclass correlation coefficient (ICC) for assessing reproducibility + of interval-censored data with two repeated measurements (Kovacic and Varnai (2014) + ). ICC is estimated by maximum likelihood from + model with one fixed and one random effect (both intercepts). Help in model checking + (normality of subjects' means and residuals) is provided. + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iRepro + url_git: '' +Irescale: + version: 2.3.0 + title: Calculate and Rectify Moran's I + maintainer: Ivan Fuentes + description: Provides a scaling method to obtain a standardized Moran's I measure. + Moran's I is a measure for the spatial autocorrelation of a data set, it gives + a measure of similarity between data and its surrounding. The range of this value + must be [-1,1], but this does not happen in practice. This package scale the Moran's + I value and map it into the theoretical range of [-1,1]. Once the Moran's I value + is rescaled, it facilitates the comparison between projects, for instance, a researcher + can calculate Moran's I in a city in China, with a sample size of n1 and area + of interest a1. Another researcher runs a similar experiment in a city in Mexico + with different sample size, n2, and an area of interest a2. Due to the differences + between the conditions, it is not possible to compare Moran's I in a straightforward + way. In this version of the package, the spatial autocorrelation Moran's I is + calculated as proposed in Chen(2013) . + date_publication: '2019-11-21' + bug_reports: '' + url: https://github.tamu.edu/jivfur/rectifiedI + url_cran: https://CRAN.R-project.org/package=Irescale + url_git: '' +IRexamples: + version: 0.0.4 + title: |- + Collection of Practical Institutional Research Examples and + Tutorials + maintainer: Vinh Nguyen + description: Provides examples of code for analyzing data or accomplishing tasks + that may be useful to institutional or educational researchers. + date_publication: '2023-10-06' + bug_reports: https://github.com/vinhdizzo/IRexamples/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IRexamples + url_git: https://github.com/vinhdizzo/IRexamples +irg: + version: 0.1.6 + title: Instantaneous Rate of Green Up + maintainer: Alec L. Robitaille + description: |- + Fits a double logistic function to NDVI time series and calculates + instantaneous rate of green (IRG) according to methods described + in Bischoff et al. (2012) . + date_publication: '2021-12-22' + bug_reports: https://github.com/robitalec/irg/issues + url: https://robitalec.github.io/irg/ + url_cran: https://CRAN.R-project.org/package=irg + url_git: https://github.com/robitalec/irg +IrishDirectorates: + version: '1.4' + title: |- + A Dynamic Bipartite Latent Space Model to Analyse Irish + Companies' Boards from 2003 to 2013 + maintainer: Riccardo Rastelli + description: Provides the dataset and an implementation of the method illustrated + in Friel, N., Rastelli, R., Wyse, J. and Raftery, A.E. (2016) . + date_publication: '2019-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IrishDirectorates + url_git: '' +IRISMustangMetrics: + version: 2.4.7 + title: Statistics and Metrics for Seismic Data + maintainer: Gillian Sharer + description: |- + Classes and functions for metrics calculation as part of the + 'EarthScope MUSTANG' project. The functionality in this package + builds upon the base classes of the 'IRISSeismic' package. + Metrics include basic statistics as well as higher level + 'health' metrics that can help identify problematic seismometers. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IRISMustangMetrics + url_git: '' +IRISSeismic: + version: 1.6.7 + title: Classes and Methods for Seismic Data Analysis + maintainer: Gillian Sharer + description: |- + Provides classes and methods for seismic data analysis. The + base classes and methods are inspired by the python code found in + the 'ObsPy' python toolbox . Additional classes and + methods support data returned by web services provided by EarthScope. + . + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IRISSeismic + url_git: '' +IRkernel: + version: 1.3.2 + title: Native R Kernel for the 'Jupyter Notebook' + maintainer: Philipp Angerer + description: |2- + + The R kernel for the 'Jupyter' environment executes R code which the front-end + ('Jupyter Notebook' or other front-ends) submits to the kernel via the network. + date_publication: '2023-01-20' + bug_reports: https://github.com/IRkernel/IRkernel/issues/ + url: https://irkernel.github.io + url_cran: https://CRAN.R-project.org/package=IRkernel + url_git: '' +irlba: + version: 2.3.5.1 + title: |- + Fast Truncated Singular Value Decomposition and Principal + Components Analysis for Large Dense and Sparse Matrices + maintainer: B. W. Lewis + description: |- + Fast and memory efficient methods for truncated singular value + decomposition and principal components analysis of large sparse and dense + matrices. + date_publication: '2022-10-03' + bug_reports: https://github.com/bwlewis/irlba/issues + url: '' + url_cran: https://CRAN.R-project.org/package=irlba + url_git: '' +iRoCoDe: + version: 1.0.1 + title: Incomplete Row-Column Designs + maintainer: Md. Ashraful Haque + description: The Row-column designs are widely recommended for experimental situations + when there are two well-identified factors that are cross-classified representing + known sources of variability. These designs are expected to result a gain in accuracy + of estimating treatment comparisons in an experiment as they eliminate the effects + of the row and column factors. However, these designs are not readily available + when the number of treatments is more than the levels of row and column blocking + factors. This package named 'iRoCoDe' generates row-column designs with incomplete + rows and columns, by amalgamating two incomplete block designs (D1 and D2). The + selection of D1 and D2 (the input designs) can be done from the available incomplete + block designs, viz., balanced incomplete block designs/ partially balanced incomplete + block designs/ t-designs. (Mcsorley, J.P., Phillips, N.C., Wallis, W.D. and Yucas, + J.L. (2005).). + date_publication: '2022-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iRoCoDe + url_git: '' +IRon: + version: 0.1.4 + title: Solving Imbalanced Regression Tasks + maintainer: Nuno Moniz + description: |- + Imbalanced domain learning has almost exclusively focused on solving + classification tasks, where the objective is to predict cases labelled with a + rare class accurately. Such a well-defined approach for regression tasks lacked + due to two main factors. First, standard regression tasks assume that each value + is equally important to the user. Second, standard evaluation metrics focus on + assessing the performance of the model on the most common cases. This package + contains methods to tackle imbalanced domain learning problems in regression + tasks, where the objective is to predict extreme (rare) values. + The methods contained in this package are: 1) an automatic and non-parametric + method to obtain such relevance functions; 2) visualisation tools; 3) suite of + evaluation measures for optimisation/validation processes; 4) the squared-error + relevance area measure, an evaluation metric tailored for imbalanced regression tasks. + More information can be found in Ribeiro and Moniz (2020) . + date_publication: '2023-01-20' + bug_reports: https://github.com/nunompmoniz/IRon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IRon + url_git: https://github.com/nunompmoniz/IRon +irr: + version: 0.84.1 + title: Various Coefficients of Interrater Reliability and Agreement + maintainer: Matthias Gamer + description: |- + Coefficients of Interrater Reliability and Agreement for + quantitative, ordinal and nominal data: ICC, Finn-Coefficient, + Robinson's A, Kendall's W, Cohen's Kappa, ... + date_publication: '2019-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irr + url_git: '' +IRR2FPR: + version: 0.1.1 + title: Computing False Positive Rate from Inter-Rater Reliability + maintainer: František Bartoš + description: |- + Implements a 'Shiny Item Analysis' module and functions for computing false positive rate + and other binary classification metrics from inter-rater reliability based on Bartoš & Martinková (2024) + . + date_publication: '2024-04-24' + bug_reports: https://github.com/FBartos/IRR2FPR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IRR2FPR + url_git: https://github.com/FBartos/IRR2FPR +irrCAC: + version: '1.0' + title: Computing Chance-Corrected Agreement Coefficients (CAC) + maintainer: Kilem L. Gwet + description: |- + Calculates various chance-corrected agreement coefficients (CAC) among 2 or more raters are provided. + Among the CAC coefficients covered are Cohen's kappa, Conger's kappa, Fleiss' kappa, Brennan-Prediger coefficient, Gwet's AC1/AC2 + coefficients, and Krippendorff's alpha. Multiple sets of weights are proposed for computing weighted analyses. All of these statistical + procedures are described in details in Gwet, K.L. (2014,ISBN:978-0970806284): "Handbook of Inter-Rater Reliability," 4th edition, + Advanced Analytics, LLC. + date_publication: '2019-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irrCAC + url_git: '' +IrregLong: + version: 0.4.0 + title: Analysis of Longitudinal Data with Irregular Observation Times + maintainer: Eleanor Pullenayegum + description: 'Functions to help with analysis of longitudinal data featuring irregular + observation times, where the observation times may be associated with the outcome + process. There are functions to quantify the degree of irregularity, fit inverse-intensity + weighted Generalized Estimating Equations (Lin H, Scharfstein DO, Rosenheck RA + (2004) ), perform multiple outputation (Pullenayegum + EM (2016) ) and fit semi-parametric joint models (Liang + Y (2009) ).' + date_publication: '2024-09-06' + bug_reports: '' + url: https://epullenayegum.github.io/IrregLong/ + url_cran: https://CRAN.R-project.org/package=IrregLong + url_git: '' +irrICC: + version: '1.0' + title: Intraclass Correlations for Quantifying Inter-Rater Reliability + maintainer: Kilem L. Gwet + description: |- + Calculates various intraclass correlation coefficients used to quantify + inter-rater and intra-rater reliability. The assumption here is that the raters produced quantitative ratings. Most of the statistical procedures implemented + in this package are described in details in Gwet, K.L. (2014, ISBN:978-0970806284): "Handbook of Inter-Rater Reliability," 4th edition, + Advanced Analytics, LLC. + date_publication: '2019-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irrICC + url_git: '' +irrNA: + version: 0.2.3 + title: |- + Coefficients of Interrater Reliability – Generalized for + Randomly Incomplete Datasets + maintainer: Markus Brueckl + description: Provides coefficients of interrater reliability that are generalized + to cope with randomly incomplete (i.e. unbalanced) datasets without any imputation + of missing values or any (row-wise or column-wise) omissions of actually available + data. Applied to complete (balanced) datasets, these generalizations yield the + same results as the common procedures, namely the Intraclass Correlation according + to McGraw & Wong (1996) \doi{10.1037/1082-989X.1.1.30} and the Coefficient of + Concordance according to Kendall & Babington Smith (1939) \doi{10.1214/aoms/1177732186}. + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irrNA + url_git: '' +irt: + version: 0.2.9 + title: Item Response Theory and Computerized Adaptive Testing Functions + maintainer: Emre Gonulates + description: |- + A collection of Item Response Theory (IRT) and Computerized + Adaptive Testing (CAT) functions that are used in psychometrics. + date_publication: '2024-02-20' + bug_reports: https://github.com/egonulates/irt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=irt + url_git: https://github.com/egonulates/irt +irtawsi: + version: 0.4.1 + title: Items Response Theory Analysis with Steps and Interpretation + maintainer: Hari Purnomo Susanto + description: Dichotomous and polytomous data analysis and their scoring using the + unidimensional Item Response Theory model (Chalmers (2012) ) + with user-friendly graphic User Interface. Suitable for beginners who are learning + item response theory. + date_publication: '2024-06-26' + bug_reports: https://github.com/SusantoHP/irtawsi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=irtawsi + url_git: https://github.com/SusantoHP/irtawsi +IRTBEMM: + version: 1.0.8 + title: Family of Bayesian EMM Algorithm for Item Response Models + maintainer: Shaoyang Guo + description: 'Applying the family of the Bayesian Expectation-Maximization-Maximization + (BEMM) algorithm to estimate: (1) Three parameter logistic (3PL) model proposed + by Birnbaum (1968, ISBN:9780201043105); (2) four parameter logistic (4PL) model + proposed by Barton & Lord (1981) ; (3) + one parameter logistic guessing (1PLG) and (4) one parameter logistic ability-based + guessing (1PLAG) models proposed by San Martín et al (2006) . + The BEMM family includes (1) the BEMM algorithm for 3PL model proposed by Guo + & Zheng (2019) ; (2) the BEMM algorithm for 1PLG + model and (3) the BEMM algorithm for 1PLAG model proposed by Guo, Wu, Zheng, & + Chen (2021) ; (4) the BEMM algorithm for 4PL model + proposed by Zheng, Guo, & Kern (2021) ; and (5) + their maximum likelihood estimation versions proposed by Zheng, Meng, Guo, & Liu + (2018) . Thus, both Bayesian modal estimates and + maximum likelihood estimates are available.' + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IRTBEMM + url_git: '' +irtDemo: + version: 0.1.4 + title: Item Response Theory Demo Collection + maintainer: Metin Bulus + description: |2- + + Includes a collection of shiny applications to demonstrate + or to explore fundamental item response theory (IRT) concepts + such as estimation, scoring, and multidimensional IRT models. + date_publication: '2018-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irtDemo + url_git: '' +IRTest: + version: 2.1.0 + title: |- + Parameter Estimation of Item Response Theory with Estimation of + Latent Distribution + maintainer: Seewoo Li + description: |- + Item response theory (IRT) parameter estimation using marginal maximum likelihood and expectation-maximization algorithm + (Bock & Aitkin, 1981 ). + Within parameter estimation algorithm, several methods for latent distribution estimation are available. + Reflecting some features of the true latent distribution, these latent distribution estimation methods can possibly enhance the estimation accuracy and free the normality assumption on the latent distribution. + date_publication: '2024-10-04' + bug_reports: https://github.com/SeewooLi/IRTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IRTest + url_git: https://github.com/SeewooLi/IRTest +irtGUI: + version: '0.2' + title: Item Response Theory Analysis with a Graphic User Interface + maintainer: Huseyin Yildiz + description: Performing Item Response Theory analysis such as parameter estimation, + ability estimation, data generation, item and model fit analyse, local independence + assumption, dimensionality assumption, wright map, characteristic and information + curves under various models with a user-friendly Graphic User Interface. + date_publication: '2021-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irtGUI + url_git: '' +irtoys: + version: 0.2.2 + title: A Collection of Functions Related to Item Response Theory (IRT) + maintainer: Ivailo Partchev + description: |- + A collection of functions useful in learning and practicing IRT, + which can be combined into larger programs. Provides basic CTT analysis, + a simple common interface to the estimation of item + parameters in IRT models for binary responses with three different programs + (ICL, BILOG-MG, and ltm), ability estimation (MLE, BME, EAP, WLE, plausible + values), item and person fit statistics, scaling methods (MM, MS, Stocking-Lord, + and the complete Hebaera method), and a rich array of parametric and + non-parametric (kernel) plots. Estimates and plots Haberman's interaction model + when all items are dichotomously scored. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irtoys + url_git: '' +irtpwr: + version: 1.0.3 + title: |- + Power Analysis for IRT Models Using the Wald, LR, Score, and + Gradient Statistics + maintainer: Felix Zimmer + description: |- + Implementation of analytical and sampling-based power analyses for + the Wald, likelihood ratio (LR), score, and gradient tests. Can be applied + to item response theory (IRT) models that are fitted using marginal maximum + likelihood estimation. The methods are described in our paper + (Zimmer et al. (2022) ). + date_publication: '2023-11-20' + bug_reports: https://github.com/flxzimmer/irtpwr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=irtpwr + url_git: https://github.com/flxzimmer/irtpwr +irtQ: + version: 0.2.1 + title: Unidimensional Item Response Theory Modeling + maintainer: Hwanggyu Lim + description: |- + Fit unidimensional item response theory (IRT) models to a mixture + of dichotomous and polytomous data, calibrate online item parameters + (i.e., pretest and operational items), estimate examinees' abilities, + and examine the IRT model-data fit on item-level in different ways + as well as provide useful functions related to IRT analyses such as + IRT model-data fit evaluation and differential item functioning analysis. + The bring.flexmirt() and write.flexmirt() functions were written by modifying + the read.flexmirt() function (Pritikin & Falk (2022) ). + The bring.bilog() and bring.parscale() functions were written by modifying the read.bilog() + and read.parscale() functions, respectively (Weeks (2010) ). + The bisection() function was written by modifying the bisection() function + (Howard (2017, ISBN:9780367657918)). The code of the inverse test characteristic curve + scoring in the est_score() function was written by modifying the irt.eq.tse() function + (González (2014) ). In est_score() function, the code of weighted + likelihood estimation method was written by referring to the Pi(), Ji(), and Ii() functions + of the catR package (Magis & Barrada (2017) ). + date_publication: '2024-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irtQ + url_git: '' +irtrees: + version: 1.0.0 + title: Estimation of Tree-Based Item Response Models + maintainer: Ivailo Partchev + description: Helper functions and example data sets to facilitate the estimation + of IRTree models from data with different shape and using different software. + date_publication: '2021-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irtrees + url_git: '' +irtreliability: + version: 0.1-1 + title: Item Response Theory Reliability + maintainer: Bjorn Andersson + description: Estimation of reliability coefficients for ability estimates and sum + scores from item response theory models as defined in Cheng, Y., Yuan, K.-H. and + Liu, C. (2012) and Kim, S. and Feldt, L. S. (2010) + . The package supports the 3-PL and generalized + partial credit models and includes estimates of the standard errors of the reliability + coefficient estimators, derived in Andersson, B. and Xin, T. (2018) . + date_publication: '2018-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=irtreliability + url_git: '' +IRTShiny: + version: '1.2' + title: Item Response Theory via Shiny + maintainer: W. Kyle Hamilton + description: |- + Interactive shiny application for running Item Response Theory + analysis. Provides graphics for characteristic and information curves. + date_publication: '2017-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IRTShiny + url_git: '' +isa2: + version: 0.3.6 + title: The Iterative Signature Algorithm + maintainer: Gabor Csardi + description: |- + The ISA is a biclustering algorithm that finds modules + in an input matrix. A module or bicluster is a block of the + reordered input matrix. + date_publication: '2023-02-21' + bug_reports: https://github.com/gaborcsardi/ISA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isa2 + url_git: https://github.com/gaborcsardi/ISA +ISAR: + version: 0.1.12 + title: Introduction to Sports Analytics using R (ISAR) Data + maintainer: Ryan Elmore + description: We provide data sets used in the forthcoming textbook "Introduction + to Sports Analytics using R" by Elmore and Urbaczweski (2024). The package currently + contains sixteen datasets and should be published in early 2024. + date_publication: '2023-07-08' + bug_reports: https://github.com/rtelmore/ISAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ISAR + url_git: https://github.com/rtelmore/ISAR +ISAT: + version: 1.0.5 + title: |- + Extract Cell Density and Nearest Distance Based on 'PerkinElmer + InForm' Software Output + maintainer: Minyu Wang + description: Reads the output of the 'PerkinElmer InForm' software . + In addition to cell-density count, it can derive statistics of intercellular spatial + distance for each cell-type. + date_publication: '2018-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISAT + url_git: '' +isatabr: + version: 1.0.1 + title: Implementation for the ISA Abstract Model + maintainer: Bart-Jan van Rossum + description: |- + ISA is a metadata framework to manage an increasingly diverse set + of life science, environmental and biomedical experiments. In isatabr + methods for reading, modifying and writing of files in the ISA-Tab format + are implemented. It also contains methods for processing assay data. + date_publication: '2022-08-19' + bug_reports: https://github.com/Biometris/isatabr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isatabr + url_git: https://github.com/Biometris/isatabr/ +ISCA: + version: 0.1.0 + title: Compare Heterogeneous Social Groups + maintainer: Lucas Drouhot + description: The Inductive Subgroup Comparison Approach ('ISCA') offers a way to + compare groups that are internally differentiated and heterogeneous. It starts + by identifying the social structure of a reference group against which a minority + or another group is to be compared, yielding empirical subgroups to which minority + members are then matched based on how similar they are. The modelling of specific + outcomes then occurs within specific subgroups in which majority and minority + members are matched. 'ISCA' is characterized by its data-driven, probabilistic, + and iterative approach and combines fuzzy clustering, Monte Carlo simulation, + and regression analysis. ISCA_random_assignments() assigns subjects probabilistically + to subgroups. ISCA_clustertable() provides summary statistics of each cluster + across iterations. ISCA_modeling() provides Ordinary Least Squares regression + results for each cluster across iterations. For further details please see Drouhot + (2021) . + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISCA + url_git: '' +ISCO08ConveRsions: + version: 0.2.0 + title: Converts ISCO-08 to Job Prestige Scores, ISCO-88 and Job Name + maintainer: Nicole Schwitter + description: Implementation of functions to assign corresponding common job prestige + scores (SIOPS, ISEI), the official job or group title and the ISCO-88 code to + given ISCO-08 codes. ISCO-08 is the latest version of the International Standard + Classification of Occupations which is used to organise information on labour + and jobs. + date_publication: '2023-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISCO08ConveRsions + url_git: '' +iscoCrosswalks: + version: 1.0.0 + title: Crosswalks Between Classifications of Occupations + maintainer: Alexandros Kouretsis + description: |- + Allows the user to perform approximate + matching between the occupational classifications using concordances provided by + the Institute for Structural Research and Faculty of Economics, University of + Warsaw, . The crosswalks offer a complete + step-by-step mapping of Standard Occupational Classification (2010) data to the + International Standard Classification of Occupations (2008). We propose a + mapping method based on the aforementioned research that converts measurements + to the smallest possible unit of the target taxonomy, and then performs an + aggregation/estimate to the requested degree Occupational Hierarchical level. + date_publication: '2022-05-17' + bug_reports: https://github.com/eworx-org/iscoCrosswalks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iscoCrosswalks + url_git: https://github.com/eworx-org/iscoCrosswalks +Iscores: + version: 1.1.0 + title: Proper Scoring Rules for Missing Value Imputation + maintainer: Loris Michel + description: Implementation of a KL-based scoring rule to assess the quality of + different missing value imputations in the broad sense as introduced in Michel + et al. (2021) . + date_publication: '2022-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Iscores + url_git: '' +isdals: + version: 3.0.1 + title: |- + Datasets for Introduction to Statistical Data Analysis for the + Life Sciences + maintainer: Claus Ekstrom + description: Provides datasets for the book "Introduction to Statistical Data Analysis + for the Life Sciences, Second edition" by Ekstrøm and Sørensen (2014). + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isdals + url_git: '' +isdparser: + version: 0.4.0 + title: Parse 'NOAA' Integrated Surface Data Files + maintainer: Scott Chamberlain + description: |- + Tools for parsing 'NOAA' Integrated Surface Data ('ISD') files, + described at . Data includes for example, + wind speed and direction, temperature, cloud data, sea level pressure, + and more. Includes data from approximately 35,000 stations worldwide, + though best coverage is in North America/Europe/Australia. Data is stored + as variable length ASCII character strings, with most fields optional. + Included are tools for parsing entire files, or individual lines of data. + date_publication: '2020-02-17' + bug_reports: https://github.com/ropensci/isdparser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isdparser + url_git: https://docs.ropensci.org/isdparser(docs)https://github.com/ropensci/isdparser(devel) +ISEtools: + version: 3.2.0 + title: Ion Selective Electrodes Analysis Methods + maintainer: Peter Dillingham + description: |- + Characterisation and calibration of single or multiple Ion Selective Electrodes (ISEs); + activity estimation of experimental samples. Implements methods described in: + Dillingham, P.W., Radu, T., Diamond, D., Radu, A. and McGraw, C.M. (2012) , + Dillingham, P.W., Alsaedi, B.S.O. and McGraw, C.M. (2017) , + Dillingham, P.W., Alsaedi, B.S.O., Radu, A., and McGraw, C.M. (2019) , and + Dillingham, P.W., Alsaedi, B.S.O., Granados-Focil, S., Radu, A., and McGraw, C.M. (2020) . + date_publication: '2022-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISEtools + url_git: '' +iSFun: + version: 1.1.0 + title: Integrative Dimension Reduction Analysis for Multi-Source Data + maintainer: Rui Ren + description: 'The implement of integrative analysis methods based on a two-part + penalization, which realizes dimension reduction analysis and mining the heterogeneity + and association of multiple studies with compatible designs. The software package + provides the integrative analysis methods including integrative sparse principal + component analysis (Fang et al., 2018), integrative sparse partial least squares + (Liang et al., 2021) and integrative sparse canonical correlation analysis, as + well as corresponding individual analysis and meta-analysis versions. References: + (1) Fang, K., Fan, X., Zhang, Q., and Ma, S. (2018). Integrative sparse principal + component analysis. Journal of Multivariate Analysis, . + (2) Liang, W., Ma, S., Zhang, Q., and Zhu, T. (2021). Integrative sparse partial + least squares. Statistics in Medicine, .' + date_publication: '2022-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iSFun + url_git: '' +IsingFit: + version: '0.4' + title: Fitting Ising Models Using the ELasso Method + maintainer: Sacha Epskamp + description: This network estimation procedure eLasso, which is based on the Ising + model, combines l1-regularized logistic regression with model selection based + on the Extended Bayesian Information Criterion (EBIC). EBIC is a fit measure that + identifies relevant relationships between variables. The resulting network consists + of variables as nodes and relevant relationships as edges. Can deal with binary + data. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IsingFit + url_git: '' +Isinglandr: + version: 0.1.1 + title: Landscape Construction and Simulation for Ising Networks + maintainer: Jingmeng Cui + description: |- + A toolbox for constructing potential landscapes for Ising + networks. The parameters of the networks can be directly supplied by + users or estimated by the 'IsingFit' package by van Borkulo and + Epskamp (2016) from + empirical data. The Ising model's Boltzmann distribution is preserved + for the potential landscape function. The landscape functions can be + used for quantifying and visualizing the stability of network states, + as well as visualizing the simulation process. + date_publication: '2023-07-13' + bug_reports: https://github.com/Sciurus365/Isinglandr/issues + url: https://sciurus365.github.io/Isinglandr/ + url_cran: https://CRAN.R-project.org/package=Isinglandr + url_git: https://github.com/Sciurus365/Isinglandr +isingLenzMC: + version: 0.2.5 + title: Monte Carlo for Classical Ising Model + maintainer: Mehmet Suzen + description: Classical Ising Model is a land mark system in statistical physics.The + model explains the physics of spin glasses and magnetic materials, and cooperative + phenomenon in general, for example phase transitions and neural networks.This + package provides utilities to simulate one dimensional Ising Model with Metropolis + and Glauber Monte Carlo with single flip dynamics in periodic boundary conditions. + Utility functions for exact solutions are provided. + date_publication: '2016-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isingLenzMC + url_git: '' +IsingSampler: + version: 0.2.3 + title: Sampling Methods and Distribution Functions for the Ising Model + maintainer: Sacha Epskamp + description: Sample states from the Ising model and compute the probability of states. + Sampling can be done for any number of nodes, but due to the intractibility of + the Ising model the distribution can only be computed up to ~10 nodes. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IsingSampler + url_git: github.com/SachaEpskamp/IsingSampler +island: + version: 0.2.10 + title: Stochastic Island Biogeography Theory Made Easy + maintainer: Vicente Jimenez + description: |- + Develops stochastic models based on the Theory of Island + Biogeography (TIB) of MacArthur and Wilson (1967) + and extensions. It implements methods to estimate colonization and + extinction rates (including environmental variables) given presence-absence + data, simulates community assembly, and performs model selection. + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=island + url_git: '' +islasso: + version: 1.5.2 + title: The Induced Smoothed Lasso + maintainer: Gianluca Sottile + description: An implementation of the induced smoothing (IS) idea to lasso regularization + models to allow estimation and inference on the model coefficients (currently + hypothesis testing only). Linear, logistic, Poisson and gamma regressions with + several link functions are implemented. The algorithm is described in the original + paper; see and discussed in a tutorial . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=islasso + url_git: '' +ISLR: + version: '1.4' + title: |- + Data for an Introduction to Statistical Learning with + Applications in R + maintainer: Trevor Hastie + description: We provide the collection of data-sets used in the book 'An Introduction + to Statistical Learning with Applications in R'. + date_publication: '2021-09-15' + bug_reports: '' + url: https://www.statlearning.com + url_cran: https://CRAN.R-project.org/package=ISLR + url_git: '' +ISLR2: + version: 1.3-2 + title: Introduction to Statistical Learning, Second Edition + maintainer: Trevor Hastie + description: We provide the collection of data-sets used in the book 'An Introduction + to Statistical Learning with Applications in R, Second Edition'. These include + many data-sets that we used in the first edition (some with minor changes), and + some new datasets. + date_publication: '2022-11-20' + bug_reports: '' + url: https://www.statlearning.com + url_cran: https://CRAN.R-project.org/package=ISLR2 + url_git: '' +ISM: + version: 0.1.0 + title: Interpretive Structural Modelling (ISM) + maintainer: Gunjan Bansal + description: |- + The development of ISM was made by Warfield in 1974. + ISM is the process of collaborating distinct or related essentials into a simplified and an organized format. Hence, ISM is a methodology that seeks the interrelationships among the various elements considered and endows with a hierarchical and multilevel structure. + To run this package user needs to provide a matrix (VAXO) converted into 0's and 1's. + Warfield,J.N. (1974) + Warfield,J.N. (1974, E-ISSN:2168-2909). + date_publication: '2017-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISM + url_git: '' +ismev: + version: '1.42' + title: An Introduction to Statistical Modeling of Extreme Values + maintainer: Eric Gilleland + description: |- + Functions to support the computations carried out in + `An Introduction to Statistical Modeling of Extreme Values' by + Stuart Coles. The functions may be divided into the following + groups; maxima/minima, order statistics, peaks over thresholds + and point processes. + date_publication: '2018-05-10' + bug_reports: '' + url: http://www.ral.ucar.edu/~ericg/softextreme.php + url_cran: https://CRAN.R-project.org/package=ismev + url_git: '' +ismtchile: + version: 2.1.5 + title: Calculating Socio Material Territorial Index + maintainer: Martín Rosas Araya + description: Paquete creado con el fin de facilitar el cálculo y distribución del + índice Socio Material Territorial (ISMT), elaborado por el Observatorio de Ciudades + UC. La metodología completa está disponible en "ISMT" () + [Observatorio de Ciudades UC (2019)]. || Package created to facilitate the calculation + and distribution of the Socio-Material Territorial Index by Observatorio de Ciudades + UC. The full methodology is available at "ISMT" () + [Observatorio de Ciudades UC (2019)]. + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ismtchile + url_git: '' +isni: + version: '1.3' + title: Index of Local Sensitivity to Nonignorability + maintainer: Hui Xie + description: "The current version provides functions to compute, print and summarize + the Index of Sensitivity to Nonignorability (ISNI) in the generalized linear model + for independent data, and in the marginal multivariate Gaussian model and the + mixed-effects models for continuous and binary longitudinal/clustered data. It + allows for arbitrary patterns of missingness in the regression outcomes caused + by dropout and/or intermittent missingness. One can compute the sensitivity index + without estimating any nonignorable models or positing specific magnitude of nonignorability. + Thus ISNI provides a simple quantitative assessment of how robust the standard + estimates assuming missing at random is with respect to the assumption of ignorability. + For a tutorial, download at .\tFor + more details, see Troxel Ma and Heitjan (2004) and Xie and Heitjan (2004) + and Ma Troxel and Heitjan (2005) and Xie (2008) + and Xie (2012) and Xie and Qian (2012) ." + date_publication: '2021-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isni + url_git: '' +isnullptr: + version: 1.0.2 + title: Check if an 'externalptr' is a Null Pointer + maintainer: Jonas Förster + description: |- + Check if an 'externalptr' is a null pointer. + R does currently not have a native function for that purpose. + This package contains a C function that returns TRUE in case of a null pointer. + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isnullptr + url_git: '' +Iso: + version: 0.0-21 + title: Functions to Perform Isotonic Regression + maintainer: Rolf Turner + description: |- + Linear order and unimodal order (univariate) + isotonic regression; bivariate isotonic regression + with linear order on both variables. + date_publication: '2023-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Iso + url_git: '' +ISO11784Tools: + version: 1.2.0 + title: ISO11784 PIT Tag ID Format Converters + maintainer: Graeme Diack + description: |- + Some tools to assist with converting International Organization for Standardization (ISO) standard 11784 (ISO11784) animal ID codes between 4 recognised formats commonly displayed on Passive Integrated Transponder (PIT) tag readers. + The most common formats are 15 digit decimal, e.g., 999123456789012, and 13 character hexadecimal 'dot' format, e.g., 3E7.1CBE991A14. These are referred + to in this package as isodecimal and isodothex. The other two formats are the raw hexadecimal representation of the ISO11784 binary + structure (see ). There are two 'flavours' of this format, a left and a right variation. Which flavour + a reader happens to output depends on if the developers decided to reverse the binary number or not before converting to hexadecimal, a decision based on + the fact that the PIT tags will transmit their binary code Least Significant Bit (LSB) first, or backwards basically. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISO11784Tools + url_git: '' +iso8601: + version: 0.1.2 + title: Working with ISO8601 Dates and Times + maintainer: Jan van der Laan + description: |- + Functions to parse strings with ISO8601 dates, times, and + date-times into R-objects. Additionally, there are functions to determine + the type of ISO8601 string and to standardise ISO8601 strings. + date_publication: '2024-12-20' + bug_reports: https://github.com/djvanderlaan/iso8601/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iso8601 + url_git: https://github.com/djvanderlaan/iso8601/tree/main/R-package +isoband: + version: 0.2.7 + title: |- + Generate Isolines and Isobands from Regularly Spaced Elevation + Grids + maintainer: Hadley Wickham + description: |- + A fast C++ implementation to generate contour lines + (isolines) and contour polygons (isobands) from regularly spaced grids + containing elevation data. + date_publication: '2022-12-20' + bug_reports: https://github.com/r-lib/isoband/issues + url: https://isoband.r-lib.org + url_cran: https://CRAN.R-project.org/package=isoband + url_git: '' +isoboost: + version: 1.0.1 + title: Isotonic Boosting Classification Rules + maintainer: David Conde + description: |- + In classification problems a monotone relation between some + predictors and the classes may be assumed. In this package 'isoboost' + we propose new boosting algorithms, based on LogitBoost, that + incorporate this isotonicity information, yielding more accurate + and easily interpretable rules. + date_publication: '2021-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isoboost + url_git: '' +isobxr: + version: 2.0.0 + title: Stable Isotope Box Modelling in R + maintainer: Theo Tacail + description: |- + A set of functions to run simple and composite box-models to describe the + dynamic or static distribution of stable isotopes in open + or closed systems. The package also allows the sweeping of many + parameters in both static and dynamic conditions. + The mathematical models used in this package are derived from Albarede, 1995, + Introduction to Geochemical Modelling, Cambridge University Press, + Cambridge . + date_publication: '2023-08-23' + bug_reports: https://github.com/ttacail/isobxr/issues + url: https://ttacail.github.io/isobxr_web/ + url_cran: https://CRAN.R-project.org/package=isobxr + url_git: https://github.com/ttacail/isobxr +isocalcR: + version: 0.1.1 + title: Isotope Calculations in R + maintainer: Justin Mathias + description: Perform common calculations based on published stable isotope theory, + such as calculating carbon isotope discrimination and intrinsic water use efficiency + from wood or leaf carbon isotope composition. See Mathias and Hudiburg (2022) + in Global Change Biology . + date_publication: '2023-03-23' + bug_reports: https://github.com/justinmathias/isocalcR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isocalcR + url_git: https://github.com/justinmathias/isocalcR +isocat: + version: 0.3.0 + title: Isotope Origin Clustering and Assignment Tools + maintainer: Caitlin Campbell + description: |- + This resource provides tools to create, compare, and post-process + spatial isotope assignment models of animal origin. It generates + probability-of-origin maps for individuals based on user-provided tissue and + environment isotope values (e.g., as generated by IsoMAP, Bowen et al. [2013] + ) using the framework established in Bowen et al. + (2010) ). The package 'isocat' can then + quantitatively compare and cluster these maps to group individuals by + similar origin. It also includes techniques for applying four approaches + (cumulative sum, odds ratio, quantile only, and quantile simulation) with + which users can summarize geographic origins and probable distance traveled + by individuals. Campbell et al. [2020] establishes several of the functions + included in this package . + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isocat + url_git: '' +IsoCheck: + version: 0.1.0 + title: |- + Isomorphism Check for Multi-Stage Factorial Designs with + Randomization Restrictions + maintainer: Pritam Ranjan + description: Contains functions to check the isomorphism of multi-stage factorial + designs with randomisation restrictions based on balanced spreads and balanced + covering stars of PG(n-1,2) as described in Spencer, Ranjan and Mendivil (2019) + . + date_publication: '2020-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IsoCheck + url_git: '' +isocir: + version: 2.0-7.1 + title: Isotonic Inference for Circular Data + maintainer: Sandra Barragan + description: A bunch of functions to deal with circular data under order restrictions. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isocir + url_git: '' +ISOcodes: + version: 2024.02.12 + title: Selected ISO Codes + maintainer: Kurt Hornik + description: |- + ISO language, territory, currency, script and character codes. + Provides ISO 639 language codes, ISO 3166 territory codes, ISO 4217 + currency codes, ISO 15924 script codes, and the ISO 8859 character codes + as well as the UN M.49 area codes. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISOcodes + url_git: '' +IsoCor: + version: 0.2.8 + title: Analyze Isotope Ratios in a 'Shiny'-App + maintainer: Jan Lisec + description: |- + Analyzing Inductively Coupled Plasma - Mass Spectrometry (ICP-MS) + measurement data to evaluate isotope ratios (IRs) is a complex process. + The 'IsoCor' package facilitates this process and renders it reproducible + by providing a function to run a 'Shiny'-App locally in any web browser. + In this App the user can upload data files of various formats, select ion + traces, apply peak detection and perform calculation of IRs and delta + values. Results are provided as figures and tables and can be exported. + The App, therefore, facilitates data processing of ICP-MS experiments to + quickly obtain optimal processing parameters compared to traditional 'Excel' + worksheet based approaches. A more detailed description can be found in the + corresponding article . The most recent version + of 'IsoCor' can be tested online at . + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IsoCor + url_git: https://github.com/janlisec/IsoCor +isocountry: + version: 0.3.0 + title: ISO 3166-1 Country Codes + maintainer: Maximilian Mücke + description: |- + ISO 3166-1 country codes and ISO 4217 currency codes provided + by the International Organization for Standardization. + date_publication: '2024-11-28' + bug_reports: https://github.com/m-muecke/isocountry/issues + url: https://m-muecke.github.io/isocountry/ + url_cran: https://CRAN.R-project.org/package=isocountry + url_git: https://github.com/m-muecke/isocountry +isodistrreg: + version: 0.1.0 + title: Isotonic Distributional Regression (IDR) + maintainer: Alexander Henzi + description: |- + Distributional regression under stochastic order restrictions for + numeric and binary response variables and partially ordered covariates. See + Henzi, Ziegel, Gneiting (2020) . + date_publication: '2021-03-22' + bug_reports: https://github.com/AlexanderHenzi/isodistrreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isodistrreg + url_git: https://github.com/AlexanderHenzi/isodistrreg +isogeochem: + version: 1.1.1 + title: Tools for Stable Isotope Geochemistry + maintainer: David Bajnai + description: |2- + + This toolbox makes working with oxygen, + carbon, and clumped isotope data reproducible and straightforward. + Use it to quickly calculate isotope fractionation factors, + and apply paleothermometry equations. + date_publication: '2023-03-15' + bug_reports: https://github.com/davidbajnai/isogeochem/issues + url: https://davidbajnai.github.io/isogeochem/ + url_cran: https://CRAN.R-project.org/package=isogeochem + url_git: '' +isokernel: + version: 0.1.0 + title: Isolation Kernel + maintainer: Ye Zhu + description: Implementation of Isolation kernel (Qin et al. (2019) ). + date_publication: '2021-10-04' + bug_reports: https://github.com/zhuye88/isokernel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isokernel + url_git: https://github.com/zhuye88/isokernel +IsoMemo: + version: 23.10.1 + title: Retrieve Data using the 'IsoMemo' API + maintainer: Jan Abel + description: 'API wrapper that contains functions to retrieve data from the ''IsoMemo'' + partnership databases. Web services for API: .' + date_publication: '2023-11-03' + bug_reports: https://github.com/Pandora-IsoMemo/isomemo-data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IsoMemo + url_git: '' +isoorbi: + version: 1.3.1 + title: Process Orbitrap Isotopocule Data + maintainer: Caj Neubauer + description: 'Read and process isotopocule data from an Orbitrap Isotope Solutions + mass spectrometer. Citation: Kantnerova et al. (Nature Protocols, 2024).' + date_publication: '2024-08-27' + bug_reports: https://github.com/isoverse/isoorbi/issues + url: https://isoorbi.isoverse.org/ + url_cran: https://CRAN.R-project.org/package=isoorbi + url_git: https://github.com/isoverse/isoorbi +isopam: + version: '3.2' + title: Clustering of Sites with Species Data + maintainer: Sebastian Schmidtlein + description: Clustering algorithm developed for use with plot inventories of species. + It groups plots by subsets of diagnostic species rather than overall species composition. + There is an unsupervised and a supervised mode, the latter accepting suggestions + for species with greater weight and cluster medoids. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isopam + url_git: '' +isopleuros: + version: 1.3.0 + title: Ternary Plots + maintainer: Nicolas Frerebeau + description: |- + Ternary plots made simple. This package allows to create + ternary plots using 'graphics'. It provides functions to display the + data in the ternary space, to add or tune graphical elements and to + display statistical summaries. It also includes common ternary + diagrams which are useful for the archaeologist (e.g. soil texture + charts, ceramic phase diagram). + date_publication: '2024-11-22' + bug_reports: https://github.com/tesselle/isopleuros/issues + url: https://packages.tesselle.org/isopleuros/ + url_cran: https://CRAN.R-project.org/package=isopleuros + url_git: https://github.com/tesselle/isopleuros +IsoplotR: + version: '6.5' + title: Statistical Toolbox for Radiometric Geochronology + maintainer: Pieter Vermeesch + description: Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. + Calculates concordia and discordia ages. Performs linear regression of measurements + with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant + Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates + (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling + (MDS) configurations and Shepard plots of multi-sample detrital datasets using + the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar + ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. + Calculates U-Th-He (single grain and central) ages, logratio plots and ternary + diagrams. Processes fission track data using the external detector method and + LA-ICP-MS, calculates central ages and plots fission track and other data on radial + (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, + Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots. + date_publication: '2025-02-13' + bug_reports: '' + url: https://isoplotr.es.ucl.ac.uk/home/index.html + url_cran: https://CRAN.R-project.org/package=IsoplotR + url_git: https://github.com/pvermees/IsoplotR/ +IsoplotRgui: + version: '6.5' + title: Web Interface to 'IsoplotR' + maintainer: Pieter Vermeesch + description: Provides a graphical user interface to the 'IsoplotR' package for radiometric + geochronology. The GUI runs in an internet browser and can either be used offline, + or hosted on a server to provide online access to the 'IsoplotR' toolbox. + date_publication: '2025-02-13' + bug_reports: '' + url: https://isoplotr.es.ucl.ac.uk/ + url_cran: https://CRAN.R-project.org/package=IsoplotRgui + url_git: https://github.com/pvermees/IsoplotRgui/ +ISOpureR: + version: 1.1.3 + title: Deconvolution of Tumour Profiles + maintainer: Paul C Boutros + description: |- + Deconvolution of mixed tumour profiles into normal and cancer for each patient, using + the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires + mixed tumour profiles and a set of unmatched "basis" normal profiles. + date_publication: '2019-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISOpureR + url_git: '' +IsoriX: + version: 0.9.3 + title: |- + Isoscape Computation and Inference of Spatial Origins using + Mixed Models + maintainer: Alexandre Courtiol + description: |- + Building isoscapes using mixed models and inferring the geographic + origin of samples based on their isotopic ratios. This package is essentially a + simplified interface to several other packages which implements a new + statistical framework based on mixed models. It uses 'spaMM' for fitting and + predicting isoscapes, and assigning an organism's origin depending on its + isotopic ratio. 'IsoriX' also relies heavily on the package 'rasterVis' for + plotting the maps produced with 'terra' using 'lattice'. + date_publication: '2024-09-08' + bug_reports: https://github.com/courtiol/IsoriX/issues + url: https://bookdown.org/content/782 + url_cran: https://CRAN.R-project.org/package=IsoriX + url_git: https://github.com/courtiol/IsoriX +IsoSpecR: + version: 2.1.3 + title: The IsoSpec Algorithm + maintainer: Matteo Lacki + description: |- + IsoSpec is a fine structure calculator used for obtaining the most + probable masses of a chemical compound given the frequencies of the composing + isotopes and their masses. It finds the smallest set of isotopologues with + a given probability. The probability is assumed to be that of the product of + multinomial distributions, each corresponding to one particular element and + parametrized by the frequencies of finding these elements in nature. These + numbers are supplied by IUPAC - the International Union of Pure and Applied + Chemistry. See: Lacki, Valkenborg, Startek (2020) + and Lacki, Startek, Valkenborg, Gambin (2017) + for the description of the algorithms used. + date_publication: '2020-10-31' + bug_reports: '' + url: http://matteolacki.github.io/IsoSpec/ + url_cran: https://CRAN.R-project.org/package=IsoSpecR + url_git: '' +isoSurv: + version: 0.3.0 + title: Isotonic Regression on Survival Analysis + maintainer: Yunro Chung + description: Nonparametric estimation on survival analysis under order-restrictions. + date_publication: '2023-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isoSurv + url_git: '' +isotone: + version: 1.1-1 + title: Active Set and Generalized PAVA for Isotone Optimization + maintainer: Patrick Mair + description: |- + Contains two main functions: one for + solving general isotone regression problems using the + pool-adjacent-violators algorithm (PAVA); another one provides + a framework for active set methods for isotone optimization + problems with arbitrary order restrictions. Various types of + loss functions are prespecified. + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isotone + url_git: https://r-forge.r-project.org/projects/psychor/ +isotonic.pen: + version: '1.0' + title: Penalized Isotonic Regression in one and two dimensions + maintainer: Mary Meyer + description: Given a response y and a one- or two-dimensional predictor, the isotonic + regression estimator is calculated with the usual orderings. + date_publication: '2014-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isotonic.pen + url_git: '' +isotracer: + version: 1.1.7 + title: Isotopic Tracer Analysis Using MCMC + maintainer: Matthieu Bruneaux + description: |- + Implements Bayesian models to analyze data from tracer addition + experiments. The implemented method was originally described in the article + "A New Method to Reconstruct Quantitative Food Webs and Nutrient Flows from + Isotope Tracer Addition Experiments" by López-Sepulcre et al. (2020) + . + date_publication: '2024-11-05' + bug_reports: https://gitlab.com/matthieu-bruneaux/isotracer/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isotracer + url_git: https://gitlab.com/matthieu-bruneaux/isotracer +isotree: + version: 0.6.1-4 + title: Isolation-Based Outlier Detection + maintainer: David Cortes + description: |- + Fast and multi-threaded implementation of + isolation forest (Liu, Ting, Zhou (2008) ), + extended isolation forest (Hariri, Kind, Brunner (2018) ), + SCiForest (Liu, Ting, Zhou (2010) ), + fair-cut forest (Cortes (2021) ), + robust random-cut forest (Guha, Mishra, Roy, Schrijvers (2016) ), + and customizable variations of them, for isolation-based outlier detection, clustered outlier detection, + distance or similarity approximation (Cortes (2019) ), + isolation kernel calculation (Ting, Zhu, Zhou (2018) ), + and imputation of missing values (Cortes (2019) ), + based on random or guided decision tree splitting, and providing different metrics for + scoring anomalies based on isolation depth or density (Cortes (2021) ). + Provides simple heuristics for fitting the model to categorical columns and handling missing data, + and offers options for varying between random and guided splits, and for using different splitting criteria. + date_publication: '2025-01-08' + bug_reports: https://github.com/david-cortes/isotree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=isotree + url_git: https://github.com/david-cortes/isotree +isoWater: + version: 1.2.0 + title: Discovery, Retrieval, and Analysis of Water Isotope Data + maintainer: Gabe Bowen + description: |- + The wiDB...() functions provide an interface to the public API + of the wiDB : + build, check and submit queries, and receive and + unpack responses. Data analysis functions support Bayesian + inference of the source and source isotope composition of water + samples that may have experienced evaporation. Algorithms + adapted from Bowen et al. (2018, ). + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isoWater + url_git: '' +ISOweek: + version: 0.6-2 + title: Week of the year and weekday according to ISO 8601 + maintainer: Uwe Block + description: |- + This is an substitute for the %V and %u formats which are + not implemented on Windows. In addition, the package offers + functions to convert from standard calender format yyyy-mm-dd + to and from ISO 8601 week format yyyy-Www-d. + date_publication: '2011-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISOweek + url_git: '' +ispd: + version: '0.2' + title: Incomplete Split-Plot Designs + maintainer: Baidya Nath Mandal + description: A collection of several functions related to construction and analysis + of incomplete split-plot designs. The package contains functions to obtain and + analyze incomplete split-plot designs for three kinds of situations namely (i) + when blocks are complete with respect to main plot treatments and main plots are + incomplete with respect to subplot treatments, (ii) when blocks are incomplete + with respect to main plot treatments and main plots are complete with respect + to subplot treatments and (iii) when blocks are incomplete with respect to main + plot treatments and main plots are incomplete with respect to subplot treatments. + date_publication: '2019-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ispd + url_git: '' +ispdata: + version: 1.1.2 + title: |- + Access Data from the Public Security Institute of the State of + Rio De Janeiro + maintainer: Igor Laltuf + description: Allows access to data from the Rio de Janeiro Public Security Institute + (ISP), such as criminal statistics, data on gun seizures and femicide. The package + also contains the spatial data of Pacifying Police Units (UPPs) and Integrated + Public Safety Regions, Areas and Circumscriptions. + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ispdata + url_git: '' +ISR: + version: 2025.01.14 + title: The Iterated Score Regression-Based Estimation + maintainer: Guangbao Guo + description: We use the ISR to handle with PCA-based missing data with high correlation, and + the DISR to handle with distributed PCA-based missing data. The philosophy of + the package is described in Guo G. (2024) . + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISR + url_git: '' +ISRaD: + version: 2.5.5 + title: Tools and Data for the International Soil Radiocarbon Database + maintainer: Jeffrey Beem-Miller + description: |- + This is the central location for data and tools for the development, + maintenance, analysis, and deployment of the International Soil Radiocarbon Database + (ISRaD). ISRaD was developed as a collaboration between the U.S. Geological Survey + Powell Center and the Max Planck Institute for Biogeochemistry. This R package provides + tools for accessing and manipulating ISRaD data, compiling local data using the ISRaD + data structure, and simple query and reporting functions for ISRaD. For more detailed + information visit the ISRaD website at: . + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISRaD + url_git: '' +ISS: + version: 1.0.0 + title: Isotonic Subgroup Selection + maintainer: Manuel M. Müller + description: Methodology for subgroup selection in the context of isotonic regression + including methods for sub-Gaussian errors, classification, homoscedastic Gaussian + errors and quantile regression. See the documentation of ISS(). Details can be + found in the paper by Müller, Reeve, Cannings and Samworth (2023) . + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISS + url_git: '' +istacr: + version: 0.2.2 + title: |- + Obtaining Open Data from Instituto Canario De Estadistica + (ISTAC) API + maintainer: Alberto Gonzalez + description: You can access to open data published in Instituto Canario De Estadistica + (ISTAC) APIs at . + date_publication: '2022-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=istacr + url_git: '' +istat: + version: '1.0' + title: Download and Manipulate Data from Istat + maintainer: Elena Gradi + description: Download data from Istat (Italian Institute of Statistics) database, + both old and new provider (respectively, and ). + Additional functions for manipulating data are provided. Moreover, a 'shiny' application + called 'shinyIstat' can be used to search, download and filter datasets in an + easier way. + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=istat + url_git: '' +iSTATS: + version: '1.7' + title: A Graphical Interface to Perform STOCSY Analyses on NMR Data + maintainer: Luiz Henrique Keng Queiroz Junior + description: Launches a 'shiny' based application for Nuclear Magnetic Resonance + (NMR)data importation and Statistical TOtal Correlation SpectroscopY (STOCSY) + analyses in a full interactive approach. The theoretical background and applications + of STOCSY method could be found at Cloarec, O., Dumas, M. E., Craig, A., Barton, + R. H., Trygg, J., Hudson, J., Blancher, C., Gauguier, D., Lindon, J. C., Holmes, + E. & Nicholson, J. (2005) . + date_publication: '2023-12-06' + bug_reports: https://github.com/vitor-mendes-iq/iSTATS + url: '' + url_cran: https://CRAN.R-project.org/package=iSTATS + url_git: '' +iSubGen: + version: 1.0.1 + title: Integrative Subtype Generation + maintainer: Paul C Boutros + description: Multi-data type subtyping, which is data type agnostic and accepts + missing data. Subtyping is performed using intermediary assessments created with + autoencoders and similarity calculations. + date_publication: '2021-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iSubGen + url_git: '' +isva: + version: '1.9' + title: Independent Surrogate Variable Analysis + maintainer: Andrew Teschendorff + description: |- + Independent Surrogate Variable Analysis is an algorithm + for feature selection in the presence of potential confounding + factors (see Teschendorff AE et al 2011, ). + date_publication: '2017-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=isva + url_git: '' +ISwR: + version: 2.0-9 + title: Introductory Statistics with R + maintainer: Peter Dalgaard + description: |- + Data sets and scripts for text examples and exercises in + P. Dalgaard (2008), `Introductory Statistics with R', 2nd ed., Springer Verlag, ISBN 978-0387790534. + date_publication: '2024-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ISwR + url_git: '' +italy: + version: 0.1.0 + title: The Italian Survey on Household and Wealth, 2008 and 2010 + maintainer: Rebecca Steorts + description: 'Provides two record linkage data sets on the Italian Survey on Household + and Wealth, 2008 and 2010, a sample survey conducted by the Bank of Italy every + two years. The 2010 survey covered 13,702 individuals, while the 2008 survey covered + 13,734 individuals. The following categorical variables are included in this data + set: year of birth, working status, employment status, branch of activity, town + size, geographical area of birth, sex, whether or not Italian national, and highest + educational level obtained. Unique identifiers are available to assess the accuracy + of one’s method. Please see Steorts (2015) to find more + details about the data set.' + date_publication: '2017-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=italy + url_git: '' +itan: + version: 3.1.1 + title: Item Analysis for Multiple Choice Tests + maintainer: Ariel Armijo + description: |- + Functions for analyzing multiple choice items. These analyses include + the convertion of student response into binaty data (correct/incorrect), + the computation of the number of corrected responses and grade for each subject, + the calculation of item difficulty and discrimination, the computation of the + frecuency and point-biserial correlation for each distractor and the graphical + analysis of each item. + date_publication: '2022-02-10' + bug_reports: https://github.com/arielarmijo/itan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=itan + url_git: https://github.com/arielarmijo/itan +itcSegment: + version: '1.0' + title: Individual Tree Crowns Segmentation + maintainer: Michele Dalponte + description: 'Three methods for Individual Tree Crowns (ITCs) delineation on remote + sensing data: one is based on LiDAR data in x,y,z format and one on imagery data + in raster format.' + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=itcSegment + url_git: '' +itdr: + version: 2.0.1 + title: Integral Transformation Methods for SDR in Regression + maintainer: Tharindu P. De Alwis + description: The itdr() routine allows for the estimation of sufficient dimension + reduction subspaces in univariate regression such as the central mean subspace + or central subspace in regression. This is achieved using Fourier transformation + methods proposed by Zhu and Zeng (2006) , convolution + transformation methods proposed by Zeng and Zhu (2010) , + and iterative Hessian transformation methods proposed by Cook and Li (2002) . + Additionally, mitdr() function provides optimal estimators for sufficient dimension + reduction subspaces in multivariate regression by optimizing a discrepancy function + using a Fourier transform approach proposed by Weng and Yin (2022) , + and selects the sufficient variables using Fourier transform sparse inverse regression + estimators proposed by Weng (2022) . + date_publication: '2024-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=itdr + url_git: '' +itemanalysis: + version: '1.1' + title: Classical Test Theory Item Analysis + maintainer: Cengiz Zopluoglu + description: Runs classical item analysis for multiple-choice test items and polytomous + items (e.g., rating scales). The statistics reported in this package can be found + in any measurement textbook such as Crocker and Algina (2006, ISBN:9780495395911). + date_publication: '2022-06-14' + bug_reports: '' + url: https://cengiz.me/ + url_cran: https://CRAN.R-project.org/package=itemanalysis + url_git: '' +iTensor: + version: 1.0.2 + title: ICA-Based Matrix/Tensor Decomposition + maintainer: Koki Tsuyuzaki + description: |- + Some functions for performing ICA, MICA, Group ICA, and Multilinear ICA are implemented. + ICA, MICA/Group ICA, and Multilinear ICA extract statistically independent components from single matrix, multiple matrices, and single tensor, respectively. + For the details of these methods, see the reference section of GitHub README.md . + date_publication: '2023-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iTensor + url_git: https://github.com/rikenbit/iTensor +IterativeHardThresholding: + version: 1.0.2 + title: Iterative Hard Thresholding Extensions to Cyclops + maintainer: Marc A. Suchard + description: |- + Fits large-scale regression models with a penalty that + restricts the maximum number of non-zero regression coefficients + to a prespecified value. While Chu et al (2020) + describe the basic algorithm, this package uses Cyclops for an efficient implementation. + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IterativeHardThresholding + url_git: '' +iteratoR: + version: 0.1.1 + title: Print Loop Iterations at Exponentially Disparate Intervals + maintainer: Steve Condylios + description: |- + Know which loop iteration the code execution is up to by including + a single, convenient function call inside the loop. + date_publication: '2022-08-30' + bug_reports: https://github.com/stevecondylios/iteratoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=iteratoR + url_git: https://github.com/stevecondylios/iteratoR +iterators: + version: 1.0.14 + title: Provides Iterator Construct + maintainer: Folashade Daniel + description: |- + Support for iterators, which allow a programmer to traverse + through all the elements of a vector, list, or other collection of data. + date_publication: '2022-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iterators + url_git: https://github.com/RevolutionAnalytics/iterators +iterLap: + version: 1.1-4 + title: |- + Approximate Probability Densities by Iterated Laplace + Approximations + maintainer: Bjoern Bornkamp + description: |- + The iterLap (iterated Laplace approximation) algorithm approximates a + general (possibly non-normalized) probability density on R^p, by repeated + Laplace approximations to the difference between current approximation + and true density (on log scale). The final approximation is a mixture of + multivariate normal distributions and might be used for example as a + proposal distribution for importance sampling (eg in Bayesian applications). + The algorithm can be seen as a computational generalization of the Laplace + approximation suitable for skew or multimodal densities. + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iterLap + url_git: '' +iterors: + version: '1.0' + title: Fast, Compact Iterators and Tools + maintainer: Peter Meilstrup + description: 'A fresh take on iterators in R. Designed to be cross-compatible with + the ''iterators'' package, but using the ''nextOr'' method will offer better performance + as well as more compact code. With batteries included: includes a collection of + iterator constructors and combinators ported and refined from the ''iterators'', + ''itertools'', and ''itertools2'' packages.' + date_publication: '2023-05-18' + bug_reports: '' + url: https://crowding.github.io/iterors/ + url_cran: https://CRAN.R-project.org/package=iterors + url_git: https://github.com/crowding/iterors +iterpc: + version: 0.4.2 + title: Efficient Iterator for Permutations and Combinations + maintainer: Randy Lai + description: |- + Iterator for generating permutations and combinations. They + can be either drawn with or without replacement, or with distinct/ non-distinct + items (multiset). The generated sequences are in lexicographical order + (dictionary order). The algorithms to generate permutations and combinations are + memory efficient. These iterative algorithms enable users to process all sequences + without putting all results in the memory at the same time. + The algorithms are written in C/C++ for faster performance. Note: 'iterpc' is no longer + being maintained. Users are recommended to switch to 'arrangements'. + date_publication: '2020-01-10' + bug_reports: '' + url: https://randy3k.github.io/iterpc + url_cran: https://CRAN.R-project.org/package=iterpc + url_git: '' +itertools: + version: 0.1-3 + title: Iterator Tools + maintainer: Steve Weston + description: Various tools for creating iterators, many patterned afterfunctions + in the Python itertools module, and others patternedafter functions in + the 'snow' package. + date_publication: '2014-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=itertools + url_git: '' +itertools2: + version: 0.1.1 + title: 'itertools2: Functions creating iterators for efficient looping' + maintainer: John A. Ramey + description: |- + A port of Python's excellent itertools module to R for efficient + looping. + date_publication: '2014-08-08' + bug_reports: '' + url: http://ramhiser.com + url_cran: https://CRAN.R-project.org/package=itertools2 + url_git: https://github.com/ramhiser/itertools2 +itmsa: + version: 0.1.0 + title: Information-Theoretic Measures for Spatial Association + maintainer: Wenbo Lv + description: Leveraging information-theoretic measures like mutual information and + v-measure to quantify spatial associations between patterns (Nowosad and Stepinski + (2018) ; Bai, H. et al. (2023) ). + date_publication: '2024-12-23' + bug_reports: https://github.com/stscl/itmsa/issues + url: https://stscl.github.io/itmsa/ + url_cran: https://CRAN.R-project.org/package=itmsa + url_git: https://github.com/stscl/itmsa +ITNr: + version: 0.7.0 + title: Analysis of the International Trade Network + maintainer: Matthew Smith + description: Functions to clean and process international trade data into an international + trade network (ITN) are provided. It then provides a set a functions to undertake + analysis and plots of the ITN (extract the backbone, centrality, blockmodels, + clustering). Examining the key players in the ITN and regional trade patterns. + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ITNr + url_git: '' +itol.toolkit: + version: 1.1.7 + title: Helper Functions for 'Interactive Tree Of Life' + maintainer: Tong Zhou + description: |2- + + The 'Interactive Tree Of Life' online server can + edit and annotate trees interactively. The 'itol.toolkit' package can + support all types of annotation templates. + date_publication: '2023-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=itol.toolkit + url_git: '' +iTOP: + version: 1.0.2 + title: Inferring the Topology of Omics Data + maintainer: Nanne Aben + description: Infers a topology of relationships between different datasets, such + as multi-omics and phenotypic data recorded on the same samples. We based this + methodology on the RV coefficient (Robert & Escoufier, 1976, ), + a measure of matrix correlation, which we have extended for partial matrix correlations + and binary data (Aben et al., 2018, ). + date_publication: '2018-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iTOP + url_git: '' +iTOS: + version: 1.0.3 + title: |- + Methods and Examples from Introduction to the Theory of + Observational Studies + maintainer: Paul R. Rosenbaum + description: Supplements for a book, "iTOS" = "Introduction to the Theory of Observational + Studies." Data sets are 'aHDL' from Rosenbaum (2023a) + and 'bingeM' from Rosenbaum (2023b) . The function makematch() + uses two-criteria matching from Zhang et al. (2023) + to create the matched data 'bingeM' from 'binge'. The makematch() function also + implements optimal matching (Rosenbaum (1989) ) and matching + with fine or near-fine balance (Rosenbaum et al. (2007) + and Yang et al (2012) ). The book makes + use of two other R packages, 'weightedRank' and 'tightenBlock'. + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iTOS + url_git: '' +itp: + version: 1.2.1 + title: The Interpolate, Truncate, Project (ITP) Root-Finding Algorithm + maintainer: Paul J. Northrop + description: |- + Implements the Interpolate, Truncate, Project (ITP) root-finding + algorithm developed by Oliveira and Takahashi (2021) . + The user provides the function, from the real numbers to the real numbers, + and an interval with the property that the values of the function at its + endpoints have different signs. If the function is continuous over this + interval then the ITP method estimates the value at which the function is + equal to zero. If the function is discontinuous then a point of + discontinuity at which the function changes sign may be found. + The function can be supplied using either an R function or an external + pointer to a C++ function. Tuning parameters of the ITP algorithm can be + set by the user. Default values are set based on arguments in Oliveira and + Takahashi (2021). + date_publication: '2023-12-02' + bug_reports: https://github.com/paulnorthrop/itp/issues + url: https://paulnorthrop.github.io/itp/ + url_cran: https://CRAN.R-project.org/package=itp + url_git: https://github.com/paulnorthrop/itp +itraxR: + version: 1.12.2 + title: Itrax Data Analysis Tools + maintainer: Thomas Bishop + description: |- + Parse, trim, join, visualise and analyse data from Itrax sediment core multi-parameter + scanners manufactured by Cox Analytical Systems, Sweden. Functions are provided for parsing + XRF-peak area files, line-scan optical images, and radiographic images, alongside accompanying metadata. + A variety of data wrangling tasks like trimming, joining and reducing XRF-peak area data are simplified. + Multivariate methods are implemented with appropriate data transformation. + date_publication: '2024-05-30' + bug_reports: https://github.com/tombishop1/itraxR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=itraxR + url_git: https://github.com/tombishop1/itraxR/ +its.analysis: + version: 1.6.0 + title: Running Interrupted Time Series Analysis + maintainer: Patrick English + description: Two functions for running and then post-estimating an Interrupted Time + Series Analysis model. This is a solution for running time series analyses on + temporally short data. See English (2019) 'The its.analysis R package - Modelling + short time series data' + for an overview of the method. + date_publication: '2021-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=its.analysis + url_git: '' +itsadug: + version: 2.4.1 + title: Interpreting Time Series and Autocorrelated Data Using GAMMs + maintainer: Jacolien van Rij + description: |- + GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) + as implemented in the R package 'mgcv' (Wood, S.N., 2006; 2011) is a nonlinear + regression analysis which is particularly useful for time course data such as + EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, + but also for behavioral data such as reaction times and response data. As time + course measures are sensitive to autocorrelation problems, GAMMs implements + methods to reduce the autocorrelation problems. This package includes functions + for the evaluation of GAMM models (e.g., model comparisons, determining regions + of significance, inspection of autocorrelational structure in residuals) + and interpreting of GAMMs (e.g., visualization of complex interactions, and + contrasts). + date_publication: '2022-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=itsadug + url_git: '' +itscalledsoccer: + version: 0.3.1 + title: American Soccer Analysis API Client + maintainer: Tyler Richardett + description: |- + Provides a wrapper around the same API + that powers the American Soccer Analysis app. + date_publication: '2025-02-07' + bug_reports: https://github.com/American-Soccer-Analysis/itscalledsoccer-r/issues + url: https://american-soccer-analysis.github.io/itscalledsoccer-r/ + url_cran: https://CRAN.R-project.org/package=itscalledsoccer + url_git: https://github.com/American-Soccer-Analysis/itscalledsoccer-r +itsdm: + version: 0.2.1 + title: |- + Isolation Forest-Based Presence-Only Species Distribution + Modeling + maintainer: Lei Song + description: |- + Collection of R functions to do purely presence-only species + distribution modeling with isolation forest (iForest) and its + variations such as Extended isolation forest and SCiForest. See the + details of these methods in references: Liu, F.T., Ting, K.M. and + Zhou, Z.H. (2008) , Hariri, S., Kind, M.C. + and Brunner, R.J. (2019) , Liu, F.T., + Ting, K.M. and Zhou, Z.H. (2010) , + Guha, S., Mishra, N., Roy, G. and Schrijvers, O. (2016) + , Cortes, D. (2021) + . Additionally, Shapley values are used to explain + model inputs and outputs. See details in references: Shapley, L.S. + (1953) , Lundberg, S.M. and Lee, S.I. + (2017) , Molnar, + C. (2020) , Štrumbelj, E. and Kononenko, I. + (2014) . itsdm also provides functions + to diagnose variable response, analyze variable importance, draw + spatial dependence of variables and examine variable contribution. As + utilities, the package includes a few functions to download + bioclimatic variables including 'WorldClim' version 2.0 (see Fick, + S.E. and Hijmans, R.J. (2017) ) and + 'CMCC-BioClimInd' (see Noce, S., Caporaso, L. and Santini, M. (2020) + . + date_publication: '2023-06-11' + bug_reports: https://github.com/LLeiSong/itsdm/issues + url: https://lleisong.github.io/itsdm/ + url_cran: https://CRAN.R-project.org/package=itsdm + url_git: https://github.com/LLeiSong/itsdm +itsmr: + version: '1.10' + title: Time Series Analysis Using the Innovations Algorithm + maintainer: George Weigt + description: Provides functions for modeling and forecasting time series data. Forecasting + is based on the innovations algorithm. A description of the innovations algorithm + can be found in the textbook "Introduction to Time Series and Forecasting" by + Peter J. Brockwell and Richard A. Davis. . + date_publication: '2022-08-06' + bug_reports: '' + url: https://georgeweigt.github.io/itsmr-refman.pdf + url_cran: https://CRAN.R-project.org/package=itsmr + url_git: '' +iucnr: + version: 0.0.0.1 + title: IUCN Red List Data + maintainer: Paul Efren Santos Andrade + description: Facilitates access to the International Union for Conservation of Nature + (IUCN) Red List of Threatened Species, a comprehensive global inventory of species + at risk of extinction. This package streamlines the process of determining conservation + status by matching species names with Red List data, providing tools to easily + query and retrieve conservation statuses. Designed to support biodiversity research + and conservation planning, this package relies on data from the 'iucnrdata' package, + available on GitHub . To install the + data package, use pak::pak('PaulESantos/iucnrdata'). + date_publication: '2024-11-06' + bug_reports: https://github.com/PaulESantos/iucnr/issues + url: https://paulesantos.github.io/iucnr/ + url_cran: https://CRAN.R-project.org/package=iucnr + url_git: https://github.com/PaulESantos/iucnr +ivaBSS: + version: 1.0.0 + title: Tools for Independent Vector Analysis + maintainer: Mika Sipilä + description: Independent vector analysis (IVA) is a blind source separation (BSS) + model where several datasets are jointly unmixed. This package provides several + methods for the unmixing together with some performance measures. For details, + see Anderson et al. (2011) and Lee et al. (2007) + . + date_publication: '2022-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivaBSS + url_git: '' +IVCor: + version: 0.1.0 + title: A Robust Integrated Variance Correlation + maintainer: Han Pan + description: |- + A integrated variance correlation is proposed to measure the dependence between a categorical or continuous random variable and a continuous random variable or vector. + This package is designed to estimate the new correlation coefficient with parametric and nonparametric approaches. + Test of independence for different problems can also be implemented via the new correlation coefficient with this package. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IVCor + url_git: '' +ivdesign: + version: 0.1.0 + title: Hypothesis Testing in Cluster-Randomized Encouragement Designs + maintainer: Bo Zhang + description: |- + An implementation of randomization-based hypothesis + testing for three different estimands in a cluster-randomized + encouragement experiment. The three estimands include (1) testing + a cluster-level constant proportional treatment effect (Fisher's + sharp null hypothesis), (2) pooled effect ratio, and (3) average + cluster effect ratio. To test the third estimand, user needs to install + 'Gurobi' (>= 9.0.1) optimizer via its R API. Please refer to + . + date_publication: '2020-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivdesign + url_git: '' +ivDiag: + version: 1.0.6 + title: |- + Estimation and Diagnostic Tools for Instrumental Variables + Designs + maintainer: Yiqing Xu + description: Estimation and diagnostic tools for instrumental variables designs, + which implements the guidelines proposed in Lal et al. (2023) , + including bootstrapped confidence intervals, effective F-statistic, Anderson-Rubin + test, valid-t ratio test, and local-to-zero tests. + date_publication: '2023-09-17' + bug_reports: '' + url: https://yiqingxu.org/packages/ivDiag/ + url_cran: https://CRAN.R-project.org/package=ivDiag + url_git: '' +ivdoctr: + version: 1.0.1 + title: Ensures Mutually Consistent Beliefs When Using IVs + maintainer: Mallick Hossain + description: |- + Uses data and researcher's beliefs on measurement error and + instrumental variable (IV) endogeneity to generate the space of consistent + beliefs across measurement error, instrument endogeneity, and instrumental + relevance for IV regressions. + Package based on DiTraglia and Garcia-Jimeno (2020) . + date_publication: '2021-12-05' + bug_reports: https://github.com/emallickhossain/ivdoctr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ivdoctr + url_git: '' +ivgets: + version: 0.1.2 + title: |- + General to Specific Modeling and Indicator Saturation in 2SLS + Models + maintainer: Kurle Jonas + description: |- + Provides facilities of general to specific model selection for + exogenous regressors in 2SLS models. Furthermore, indicator saturation + methods can be used to detect outliers and structural breaks in the sample. + date_publication: '2024-07-15' + bug_reports: https://github.com/jkurle/ivgets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ivgets + url_git: https://github.com/jkurle/ivgets +ivitr: + version: 0.1.0 + title: Estimate IV-Optimal Individualized Treatment Rules + maintainer: Bo Zhang + description: |- + A method that estimates + an IV-optimal individualized treatment rule. An individualized + treatment rule is said to be IV-optimal if it minimizes the + maximum risk with respect to the putative IV and the set of + IV identification assumptions. Please refer to + for more details on the methodology and + some theory underpinning the method. Function IV-PILE() uses + functions in the package 'locClass'. Package 'locClass' can be + accessed and installed from the 'R-Forge' repository via the following link: + . + Alternatively, one can install the package by entering the following in R: + 'install.packages("locClass", repos="")'. + date_publication: '2020-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivitr + url_git: '' +ivmodel: + version: 1.9.1 + title: |- + Statistical Inference and Sensitivity Analysis for Instrumental + Variables Model + maintainer: Hyunseung Kang + description: |- + Carries out instrumental variable + estimation of causal effects, including power analysis, sensitivity analysis, + and diagnostics. See Kang, Jiang, Zhao, and Small (2020) for details. + date_publication: '2023-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivmodel + url_git: '' +ivmte: + version: 1.4.0 + title: |- + Instrumental Variables: Extrapolation by Marginal Treatment + Effects + maintainer: Joshua Shea + description: |- + The marginal treatment effect was introduced by Heckman and + Vytlacil (2005) to provide a + choice-theoretic interpretation to instrumental variables models that + maintain the monotonicity condition of Imbens and Angrist (1994) + . This interpretation can be used to extrapolate from + the compliers to estimate treatment effects for other subpopulations. This + package provides a flexible set of methods for conducting this + extrapolation. It allows for parametric or nonparametric sieve estimation, + and allows the user to maintain shape restrictions such as monotonicity. The + package operates in the general framework developed by Mogstad, Santos and + Torgovitsky (2018) , and accommodates either point + identification or partial identification (bounds). In the partially + identified case, bounds are computed using either linear programming + or quadratically constrained quadratic programming. Support for + four solvers is provided. Gurobi and the Gurobi R API + can be obtained from . CPLEX can be obtained + from . CPLEX R APIs 'Rcplex' + and 'cplexAPI' are available from CRAN. MOSEK and the MOSEK R API can be + obtained from . The lp_solve library is freely + available from , and is included when + installing its API 'lpSolveAPI', which is available from CRAN. + date_publication: '2021-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivmte + url_git: '' +ivo.table: + version: '0.6' + title: Nicely Formatted Contingency Tables and Frequency Tables + maintainer: Måns Thulin + description: Nicely formatted frequency tables and contingency tables (1-way, 2-way, + 3-way and 4-way tables), that can easily be exported to HTML or 'Office' documents. + Designed to work with pipes. + date_publication: '2025-01-15' + bug_reports: https://github.com/mthulin/ivo.table/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ivo.table + url_git: https://github.com/mthulin/ivo.table +IVPP: + version: 1.0.0 + title: Invariance Partial Pruning Test + maintainer: Xinkai Du + description: |- + An implementation of the Invariance Partial Pruning (IVPP) approach + described in Du, X., Johnson, S. U., Epskamp, S. (in prep)to comparing idiographic + and panel network models. IVPP is a two-step method that first test for global network + structural difference with invariance test and then inspect specific edge difference with partial pruning. + date_publication: '2025-02-11' + bug_reports: https://github.com/xinkaidupsy/IVPP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=IVPP + url_git: https://github.com/xinkaidupsy/IVPP +ivreg: + version: 0.6-5 + title: |- + Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM', + with Diagnostics + maintainer: Achim Zeileis + description: Instrumental variable estimation for linear models by two-stage least-squares + (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation + (2SMM). The main ivreg() model-fitting function is designed to provide a workflow + as similar as possible to standard lm() regression. A wide range of methods is + provided for fitted ivreg model objects, including extensive functionality for + computing and graphing regression diagnostics in addition to other standard model + tools. + date_publication: '2025-01-19' + bug_reports: https://github.com/zeileis/ivreg/issues/ + url: https://zeileis.github.io/ivreg/ + url_cran: https://CRAN.R-project.org/package=ivreg + url_git: '' +ivs: + version: 0.2.0 + title: Interval Vectors + maintainer: Davis Vaughan + description: |- + Provides a library for generic interval manipulations using a + new interval vector class. Capabilities include: locating various + kinds of relationships between two interval vectors, merging overlaps + within a single interval vector, splitting an interval vector on its + overlapping endpoints, and applying set theoretical operations on + interval vectors. Many of the operations in this package were inspired + by James Allen's interval algebra, Allen (1983) + . + date_publication: '2023-03-17' + bug_reports: https://github.com/DavisVaughan/ivs/issues + url: https://davisvaughan.github.io/ivs/ + url_cran: https://CRAN.R-project.org/package=ivs + url_git: https://github.com/DavisVaughan/ivs +ivsacim: + version: 2.1.0 + title: Structural Additive Cumulative Intensity Models with IV + maintainer: Andrew Ying + description: An instrumental variable estimator under structural cumulative additive + intensity model is fitted, that leverages initial randomization as the IV. The + estimator can be used to fit an additive hazards model under time to event data + which handles treatment switching (treatment crossover) correctly. We also provide + a consistent variance estimate. + date_publication: '2022-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivsacim + url_git: '' +ivtools: + version: 2.3.0 + title: Instrumental Variables + maintainer: Arvid Sjolander + description: Contains tools for instrumental variables estimation. Currently, non-parametric + bounds, two-stage estimation and G-estimation are implemented. Balke, A. and Pearl, + J. (1997) , Vansteelandt S., Bowden J., Babanezhad M., Goetghebeur + E. (2011) . + date_publication: '2020-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ivtools + url_git: '' +ivx: + version: 1.1.0 + title: Robust Econometric Inference + maintainer: Kostas Vasilopoulos + description: |- + Drawing statistical inference on the coefficients + of a short- or long-horizon predictive regression with persistent + regressors by using the IVX method of Magdalinos and Phillips (2009) + and Kostakis, Magdalinos and + Stamatogiannis (2015) . + date_publication: '2020-11-24' + bug_reports: https://github.com/kvasilopoulos/ivx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ivx + url_git: https://github.com/kvasilopoulos/ivx +IVYplot: + version: 0.1.0 + title: |- + Produces an IVY Plot (Similar to Dot Plot) with/without + Frequencies + maintainer: Tri Ha Minh Nguyen + description: |- + For a single variable, the IVY Plot stacks tied values in the form of leaflets. Five leaflets join to form a leaf. + Leaves are stacked vertically. At most twenty leaves are shown; For high frequency, each leaflet may represent more than + one observation with multiplicity declared in the subtitle. + date_publication: '2021-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IVYplot + url_git: '' +iwaqr: + version: 1.8.4 + title: Irrigation Water Quality Assessment and Visualizations + maintainer: Wajid Ali + description: Calculates irrigation water quality ratios and has functions that could + be used to plot several popular diagrams for irrigation water quality classification. + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iwaqr + url_git: '' +iWeigReg: + version: '1.1' + title: Improved Methods for Causal Inference and Missing Data Problems + maintainer: Zhiqiang Tan + description: |- + Improved methods based on inverse probability weighting + and outcome regression for causal inference and missing data + problems. + date_publication: '2022-05-20' + bug_reports: '' + url: http://www.stat.rutgers.edu/~ztan + url_cran: https://CRAN.R-project.org/package=iWeigReg + url_git: '' +ixplorer: + version: 0.2.2 + title: Easy DataOps for R Users + maintainer: Frans van Dunne + description: Create and view tickets in 'gitea', a self-hosted git service , + using an 'RStudio' addin, and use helper functions to publish documentation and + use git. + date_publication: '2022-07-02' + bug_reports: https://github.com/ixpantia/ixplorer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ixplorer + url_git: https://github.com/ixpantia/ixplorer +IxPopDyMod: + version: 0.3.0 + title: Framework for Tick Population and Infection Modeling + maintainer: Myles Stokowski + description: |- + Code to specify, run, and then visualize and analyze the results of + Ixodidae (hard-bodied ticks) population and infection dynamics models. Such + models exist in the literature, but the source code to run them is not + always available. 'IxPopDyMod' provides an easy way for these models to be + written and shared. + date_publication: '2023-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=IxPopDyMod + url_git: https://github.com/dallenmidd/IxPopDyMod +iZID: + version: 0.0.1 + title: Identify Zero-Inflated Distributions + maintainer: Lei Wang + description: |- + Computes bootstrapped Monte Carlo estimate of p value of Kolmogorov-Smirnov (KS) test and + likelihood ratio test for zero-inflated count data, based on the work of Aldirawi et al. (2019) + . With the package, user can also find tools to simulate + random deviates from zero inflated or hurdle models and obtain maximum likelihood estimate + of unknown parameters in these models. + date_publication: '2019-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=iZID + url_git: '' +izmir: + version: 0.1.0 + title: R Wrapper for Izmir Municipality Open Data Portal + maintainer: Ozancan Ozdemir + description: Call the data wrappers for Izmir Metropolitan Municipality's Open Data + Portal. This will return all datasets formatted as Excel files (.csv or .xlsx), + as well as datasets that require an API key. + date_publication: '2023-02-28' + bug_reports: https://github.com/ozancanozdemir/izmir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=izmir + url_git: https://github.com/ozancanozdemir/izmir +jaatha: + version: 3.2.5 + title: Simulation-Based Maximum Likelihood Parameter Estimation + maintainer: Dirk Metzler + description: |- + An estimation method that can use computer simulations to + approximate maximum-likelihood estimates even when the likelihood function can not + be evaluated directly. It can be applied whenever it is feasible to conduct many + simulations, but works best when the data is approximately Poisson distributed. + It was originally designed for demographic inference in evolutionary + biology (Naduvilezhath et al., 2011 , + Mathew et al., 2013 ). + It has optional support for conducting coalescent simulation using + the 'coala' package. + date_publication: '2024-01-08' + bug_reports: https://github.com/statgenlmu/jaatha/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jaatha + url_git: https://github.com/statgenlmu/jaatha +jab.adverse.reactions: + version: 1.0.3 + title: |- + Possible Adverse Events/Reactions from the + Vaccinations/Experimental Gene Therapies + maintainer: Irucka Embry + description: |- + Provides data about the possible adverse events/reactions + resulting from being injected with a vaccine/experimental gene therapy. + Currently, this data set only includes information from six reference + sources. Refer to the CITATION.cff file for the complete citations of + the reference sources. For information about vaccination$/immunization$ + hazards, visit , + , + , + and . + date_publication: '2023-09-20' + bug_reports: https://gitlab.com/iembry/jab.adverse.reactions/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jab.adverse.reactions + url_git: https://gitlab.com/iembry/jab.adverse.reactions +jaccard: + version: 0.1.0 + title: |- + Test Similarity Between Binary Data using Jaccard/Tanimoto + Coefficients + maintainer: Neo Christopher Chung + description: |- + Calculate statistical significance of Jaccard/Tanimoto similarity + coefficients for binary data. + date_publication: '2018-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jaccard + url_git: '' +jack: + version: 6.1.0 + title: Jack, Zonal, Schur, and Other Symmetric Polynomials + maintainer: Stéphane Laurent + description: |- + Schur polynomials appear in combinatorics and zonal + polynomials appear in random matrix theory. They are particular cases + of Jack polynomials. This package allows to compute these polynomials + and other symmetric multivariate polynomials: flagged Schur + polynomials, factorial Schur polynomials, t-Schur polynomials, + Hall-Littlewood polynomials, Macdonald polynomials, and modified + Macdonald polynomials. In addition, it can compute the Kostka-Jack + numbers, the Kostka-Foulkes polynomials, the Kostka-Macdonald + polynomials, and the Hall polynomials. Mainly based on Demmel & + Koev's paper (2006) and + Macdonald's book (1995) . + date_publication: '2024-07-29' + bug_reports: https://github.com/stla/jackR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jack + url_git: https://github.com/stla/jackR +jackalope: + version: 1.1.5 + title: |- + A Swift, Versatile Phylogenomic and High-Throughput Sequencing + Simulator + maintainer: Lucas A. Nell + description: |- + Simply and efficiently + simulates (i) variants from reference genomes and (ii) reads from both Illumina + + and Pacific Biosciences (PacBio) platforms. + It can either read reference genomes from FASTA files or simulate new ones. + Genomic variants can be simulated using summary statistics, phylogenies, + Variant Call Format (VCF) files, and coalescent simulations—the latter of which + can include selection, recombination, and demographic fluctuations. + 'jackalope' can simulate single, paired-end, or mate-pair Illumina reads, + as well as PacBio reads. + These simulations include sequencing errors, mapping qualities, multiplexing, + and optical/polymerase chain reaction (PCR) duplicates. + Simulating Illumina sequencing is based on ART + by Huang et al. (2012) . + PacBio sequencing simulation is based on + SimLoRD by Stöcker et al. (2016) . + All outputs can be written to standard file formats. + date_publication: '2023-11-28' + bug_reports: https://github.com/lucasnell/jackalope/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jackalope + url_git: https://github.com/lucasnell/jackalope +jackknifeR: + version: 1.2.0 + title: Delete-d Jackknife for Point and Interval Estimation + maintainer: S. Mohanasundaram + description: |- + This function creates jackknife samples from the data by + sequentially removing d observations from the data, performs + estimation using the jackknife samples and calculates the jackknife + coefficients, bias, standard error and confidence intervals based on + the methodology discussed by Quenouille (1956) , + Tukey (1958) and Shi (1988) + . + date_publication: '2023-05-08' + bug_reports: https://github.com/MohanasundaramS/jackknifeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jackknifeR + url_git: '' +jackstrap: + version: 0.1.0 + title: Correcting Nonparametric Frontier Measurements for Outliers + maintainer: Kleber Morais de Sousa + description: |- + Provides method used to check whether data have outlier in efficiency measurement + of big samples with data envelopment analysis (DEA). In this jackstrap method, the package + provides two criteria to define outliers: heaviside and k-s test. The technique was developed + by Sousa and Stosic (2005) "Technical Efficiency of the Brazilian Municipalities: Correcting + Nonparametric Frontier Measurements for Outliers." . + date_publication: '2020-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jackstrap + url_git: '' +jackstraw: + version: 1.3.17 + title: Statistical Inference for Unsupervised Learning + maintainer: Neo Christopher Chung + description: Test for association between the observed data and their estimated + latent variables. The jackstraw package provides a resampling strategy and testing + scheme to estimate statistical significance of association between the observed + data and their latent variables. Depending on the data type and the analysis aim, + the latent variables may be estimated by principal component analysis (PCA), factor + analysis (FA), K-means clustering, and related unsupervised learning algorithms. + The jackstraw methods learn over-fitting characteristics inherent in this circular + analysis, where the observed data are used to estimate the latent variables and + used again to test against that estimated latent variables. When latent variables + are estimated by PCA, the jackstraw enables statistical testing for association + between observed variables and latent variables, as estimated by low-dimensional + principal components (PCs). This essentially leads to identifying variables that + are significantly associated with PCs. Similarly, unsupervised clustering, such + as K-means clustering, partition around medoids (PAM), and others, finds coherent + groups in high-dimensional data. The jackstraw estimates statistical significance + of cluster membership, by testing association between data and cluster centers. + Clustering membership can be improved by using the resulting jackstraw p-values + and posterior inclusion probabilities (PIPs), with an application to unsupervised + evaluation of cell identities in single cell RNA-seq (scRNA-seq). + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jackstraw + url_git: '' +jacobi: + version: 3.1.1 + title: Jacobi Theta Functions and Related Functions + maintainer: Stéphane Laurent + description: |- + Evaluation of the Jacobi theta functions and related + functions: Weierstrass elliptic function, Weierstrass sigma function, + Weierstrass zeta function, Klein j-function, Dedekind eta function, + lambda modular function, Jacobi elliptic functions, Neville theta + functions, Eisenstein series, lemniscate elliptic functions, elliptic + alpha function, Rogers-Ramanujan continued fractions, and Dixon + elliptic functions. Complex values of the variable are supported. + date_publication: '2023-11-18' + bug_reports: https://github.com/stla/jacobi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jacobi + url_git: https://github.com/stla/jacobi +JacobiEigen: + version: 0.3-4 + title: Classical Jacobi Eigenvalue Algorithm + maintainer: Bill Venables + description: |- + Implements the classical Jacobi algorithm for the + eigenvalues and eigenvectors of a real symmetric matrix, both in + pure 'R' and in 'C++' using 'Rcpp'. Mainly as a programming example + for teaching purposes. + date_publication: '2021-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JacobiEigen + url_git: '' +jacpop: + version: '0.6' + title: Jaccard Index for Population Structure Identification + maintainer: Dmitry Prokopenko + description: |- + Uses the Jaccard similarity index to account for population + structure in sequencing studies. This method was specifically + designed to detect population stratification based on rare variants, hence it + will be especially useful in rare variant analysis. + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jacpop + url_git: '' +Jacquard: + version: 1.0.2 + title: Estimation of Jacquard's Genetic Identity Coefficients + maintainer: Jan Graffelman + description: |- + Contains procedures to estimate the nine condensed Jacquard genetic identity coefficients + (Jacquard, 1974) by constrained least squares + (Graffelman et al., 2024) and by the method of moments + (Csuros, 2014) . These procedures require previous estimation of the + allele frequencies. Functions are supplied that estimate relationship parameters that derive from the Jacquard + coefficients, such as individual inbreeding coefficients and kinship coefficients. + date_publication: '2024-09-17' + bug_reports: '' + url: http://www-eio.upc.edu/~jan/ + url_cran: https://CRAN.R-project.org/package=Jacquard + url_git: '' +JADE: + version: 2.0-4 + title: |- + Blind Source Separation Methods Based on Joint Diagonalization + and Some BSS Performance Criteria + maintainer: Klaus Nordhausen + description: Cardoso's JADE algorithm as well as his functions for joint diagonalization + are ported to R. Also several other blind source separation (BSS) methods, like + AMUSE and SOBI, and some criteria for performance evaluation of BSS algorithms, + are given. The package is described in Miettinen, Nordhausen and Taskinen (2017) + . + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JADE + url_git: '' +jadeLizardOptions: + version: 1.0.1 + title: Trading Jade Lizard Option Strategies + maintainer: MaheshP Kumar + description: |- + Jade Lizard and Reverse Jade Lizard Option Strategies are presented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. + Russell A. Stultz (“The option strategy desk reference: an essential reference for option traders (First edition.)”, 2019, ISBN: 9781949443912). + date_publication: '2022-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jadeLizardOptions + url_git: '' +jage: + version: 0.1.0 + title: Estimation of Developmental Age + maintainer: Valerie Sgheiza + description: Bayesian methods for estimating developmental age from ordinal dental + data. For an explanation of the model used, see Konigsberg (2015) . + For details on the conditional correlation correction, see Sgheiza (2022) . + Dental scoring is based on Moorrees, Fanning, and Hunt (1963) . + date_publication: '2024-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jage + url_git: '' +jaggR: + version: 0.1.1 + title: |- + Supporting Files and Functions for the Book Bayesian Modelling + with 'JAGS' + maintainer: James Curran + description: |- + All the data and functions used to produce the book. We do not expect + most people to use the package for any other reason than to get simple access to the + 'JAGS' model files, the data, and perhaps run some of the simple examples. + The authors of the book are David Lucy (now sadly deceased) and James Curran. It is + anticipated that a manuscript will be provided to Taylor and Francis around February 2020, with + bibliographic details to follow at that point. Until such time, further information + can be obtained by emailing James Curran. + date_publication: '2019-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jaggR + url_git: '' +jagshelper: + version: 0.4.1 + title: Extracting and Visualizing Output from 'jagsUI' + maintainer: Matt Tyers + description: |- + Tools are provided to streamline Bayesian analyses in 'JAGS' using + the 'jagsUI' package. Included are functions for extracting output in + simpler format, functions for streamlining assessment of convergence, and + functions for producing summary plots of output. Also included is a + function that provides a simple template for running 'JAGS' from 'R'. + Referenced materials can be found at . + date_publication: '2024-11-07' + bug_reports: https://github.com/mbtyers/jagshelper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jagshelper + url_git: https://github.com/mbtyers/jagshelper +jagstargets: + version: 1.2.2 + title: Targets for JAGS Pipelines + maintainer: William Michael Landau + description: |- + Bayesian data analysis usually incurs long runtimes + and cumbersome custom code. + A pipeline toolkit tailored to Bayesian statisticians, + the 'jagstargets' R package is leverages + 'targets' and 'R2jags' to ease this burden. + 'jagstargets' makes it super easy to set up scalable + JAGS pipelines that automatically parallelize the computation + and skip expensive steps when the results are already up to date. + Minimal custom code is required, and there is no need to manually + configure branching, so usage is much easier than 'targets' alone. + For the underlying methodology, please refer + to the documentation of 'targets' and 'JAGS' + (Plummer 2003) . + date_publication: '2024-11-18' + bug_reports: https://github.com/ropensci/jagstargets/issues + url: https://docs.ropensci.org/jagstargets/ + url_cran: https://CRAN.R-project.org/package=jagstargets + url_git: https://github.com/ropensci/jagstargets +JAGStree: + version: 1.0.1 + title: |- + Automatically Write 'JAGS' Code for Hierarchical Bayesian Models + on Trees + maintainer: Mallory J Flynn + description: When relationships between sources of data can be represented by a + tree, the generation of appropriate Markov Chain Monte Carlo modeling code to + be used with 'JAGS' to run a Bayesian hierarchical model can be automatically + generated by this package. Any admissible tree-structured data can be used, under + the assumption that node counts are multinomial and branching probabilities are + Dirichlet among sibling groups. The methodological basis used to create this package + can be found in Flynn (2023) . + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JAGStree + url_git: https://github.com/malfly/JAGStree +jagsUI: + version: 1.6.2 + title: A Wrapper Around 'rjags' to Streamline 'JAGS' Analyses + maintainer: Ken Kellner + description: A set of wrappers around 'rjags' functions to run Bayesian analyses + in 'JAGS' (specifically, via 'libjags'). A single function call can control adaptive, + burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. + Posterior distributions are automatically summarized (with the ability to exclude + some monitored nodes if desired) and functions are available to generate figures + based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, + argument syntax, and output format are nearly identical to the 'R2WinBUGS'/'R2OpenBUGS' + packages to allow easy switching between MCMC samplers. + date_publication: '2024-01-30' + bug_reports: https://github.com/kenkellner/jagsUI/issues + url: https://kenkellner.com/jagsUI/ + url_cran: https://CRAN.R-project.org/package=jagsUI + url_git: '' +jalcal: + version: 0.1.0 + title: |- + Conversion Between Jalali (Persian or Solar Hijri) and Gregorian + Calendar Dates + maintainer: Abdollah Jalilian + description: |- + Jalali, also known as Persian, Solar Hijri and Hijri Shamsi calendar is + the official calendar of Iran and Afghanistan. It begins on Nowruz, the March equinox, + as determined by astronomical calculation and has years of 365 or 366 days. + Adapting the algorithms in , this package provides tools + for converting the Jalali and Gregorian dates. + date_publication: '2021-09-07' + bug_reports: https://github.com/jalilian/jalcal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jalcal + url_git: https://github.com/jalilian/jalcal +JamendoR: + version: 0.1.1 + title: Access to 'Jamendo' API + maintainer: Maximilian Greil + description: |- + Provides an interface to 'Jamendo' API . + Pull audio, features and other information for a given + 'Jamendo' user (including yourself!) or enter an artist's -, album's -, + or track's name and retrieve the available information in seconds. + date_publication: '2021-11-07' + bug_reports: https://github.com/MaxGreil/JamendoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=JamendoR + url_git: https://github.com/MaxGreil/JamendoR +JANE: + version: 0.2.1 + title: Just Another Latent Space Network Clustering Algorithm + maintainer: Alan Arakkal + description: |- + Fit and simulate latent space network cluster models using an expectation-maximization algorithm. + Enables flexible modeling of unweighted network data, supporting both directed and undirected networks, + with or without degree heterogeneity. Designed to handle large networks efficiently, it allows users to explore + network structure through latent space representations, identify clusters within network data, and simulate models + with varying clustering and connectivity patterns. + date_publication: '2024-12-19' + bug_reports: https://github.com/a1arakkal/JANE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=JANE + url_git: https://github.com/a1arakkal/JANE +janeaustenr: + version: 1.0.0 + title: Jane Austen's Complete Novels + maintainer: Julia Silge + description: |- + Full texts for Jane Austen's 6 completed novels, ready for + text analysis. These novels are "Sense and Sensibility", "Pride and + Prejudice", "Mansfield Park", "Emma", "Northanger Abbey", and + "Persuasion". + date_publication: '2022-08-26' + bug_reports: https://github.com/juliasilge/janeaustenr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=janeaustenr + url_git: https://github.com/juliasilge/janeaustenr +janitor: + version: 2.2.1 + title: Simple Tools for Examining and Cleaning Dirty Data + maintainer: Sam Firke + description: |- + The main janitor functions can: perfectly format data.frame column + names; provide quick counts of variable combinations (i.e., frequency + tables and crosstabs); and explore duplicate records. Other janitor functions + nicely format the tabulation results. These tabulate-and-report functions + approximate popular features of SPSS and Microsoft Excel. This package + follows the principles of the "tidyverse" and works well with the pipe function + %>%. janitor was built with beginning-to-intermediate R users in mind and is + optimized for user-friendliness. + date_publication: '2024-12-22' + bug_reports: https://github.com/sfirke/janitor/issues + url: https://sfirke.github.io/janitor/ + url_cran: https://CRAN.R-project.org/package=janitor + url_git: https://github.com/sfirke/janitor +janus: + version: 1.0.0 + title: Optimized Recommending System Based on 'tensorflow' + maintainer: Giancarlo Vercellino + description: Proposes a coarse-to-fine optimization of a recommending system based + on deep-neural networks using 'tensorflow'. + date_publication: '2022-12-16' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/janus + url_cran: https://CRAN.R-project.org/package=janus + url_git: '' +japanstat: + version: 0.1.0 + title: Tools for Easy Use of 'e-Stat' API + maintainer: Mizuki Uchida + description: |- + Provides tools for using the API of 'e-Stat' (), a portal site for Japanese government statistics. + Includes functions for automatic query generation, data collection and formatting. + date_publication: '2021-11-29' + bug_reports: https://github.com/UchidaMizuki/japanstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=japanstat + url_git: https://github.com/UchidaMizuki/japanstat +jarbes: + version: 2.2.3 + title: Just a Rather Bayesian Evidence Synthesis + maintainer: Pablo Emilio Verde + description: Provides a new class of Bayesian meta-analysis models that incorporates + a model for internal and external validity bias. In this way, it is possible to + combine studies of diverse quality and different types. For example, we can combine + the results of randomized control trials (RCTs) with the results of observational + studies (OS). + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jarbes + url_git: '' +JATSdecoder: + version: 1.2.0 + title: A Metadata and Text Extraction and Manipulation Tool Set + maintainer: Ingmar Böschen + description: 'Provides a function collection to extract metadata, sectioned text + and study characteristics from scientific articles in ''NISO-JATS'' format. Articles + in PDF format can be converted to ''NISO-JATS'' with the ''Content ExtRactor and + MINEr'' (''CERMINE'', ). For convenience, two + functions bundle the extraction heuristics: JATSdecoder() converts ''NISO-JATS''-tagged + XML files to a structured list with elements title, author, journal, history, + ''DOI'', abstract, sectioned text and reference list. study.character() extracts + multiple study characteristics like number of included studies, statistical methods + used, alpha error, power, statistical results, correction method for multiple + testing, software used. An estimation of the involved sample size is performed + based on reports within the abstract and the reported degrees of freedom within + statistical results. In addition, the package contains some useful functions to + process text (text2sentences(), text2num(), ngram(), strsplit2(), grep2()). See + Böschen, I. (2021) Böschen, I. (2021) + and Böschen, I (2023) .' + date_publication: '2023-10-12' + bug_reports: https://github.com/ingmarboeschen/JATSdecoder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=JATSdecoder + url_git: https://github.com/ingmarboeschen/JATSdecoder +JavaGD: + version: 0.6-5 + title: Java Graphics Device + maintainer: Simon Urbanek + description: |- + Graphics device routing all graphics commands to a Java + program. The actual functionality of the JavaGD depends + on the Java-side implementation. Simple AWT and Swing + implementations are included. + date_publication: '2022-11-30' + bug_reports: https://github.com/s-u/JavaGD/issues + url: https://www.rforge.net/JavaGD/ + url_cran: https://CRAN.R-project.org/package=JavaGD + url_git: '' +javateak: + version: '1.0' + title: Javanese Teak Above Ground Biomass Estimation + maintainer: Yudistira Adyatama + description: Simplifies the process of estimating above ground biomass components + for teak trees using a few basic inputs, based on the equations taken from the + journal "Allometric equations for estimating above ground biomass and leaf area + of planted teak (Tectona grandis) forests under agroforestry management in East + Java, Indonesia" (Purwanto & Shiba, 2006) . + This function is most reliable when applied to trees from the same region where + the equations were developed, specifically East Java, Indonesia. This function + help to estimate the stem diameter at the lowest major living branch (DB) using + the stem diameter at breast height with R^2 = 0.969. Estimate the branch dry weight + (WB) using the stem diameter at breast height and tree height (R^2 = 0.979). Estimate + the stem weight (WS) using the stem diameter at breast height and tree height + (R^2 = 0.997. Also estimate the leaf dry weight (WL) using the stem diameter at + the lowest major living branch (R^2 = 0.996). + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=javateak + url_git: '' +Jaya: + version: 1.0.3 + title: |- + Gradient-Free Optimization Algorithm for Single and + Multi-Objective Problems + maintainer: Neeraj Bokde + description: |- + An implementation of the Jaya optimization algorithm for both + single-objective and multi-objective problems. Jaya is a population-based, + gradient-free optimization algorithm capable of solving constrained and + unconstrained optimization problems without hyperparameters. This package + includes features such as multi-objective Pareto optimization, adaptive + population adjustment, and early stopping. For further details, see + R.V. Rao (2016) . + date_publication: '2024-11-18' + bug_reports: https://github.com/neerajdhanraj/Jaya/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Jaya + url_git: https://github.com/neerajdhanraj/Jaya +JBrowseR: + version: 0.10.2 + title: An R Interface to the JBrowse 2 Genome Browser + maintainer: Colin Diesh + description: |- + Provides an R interface to the JBrowse 2 genome browser. + Enables embedding a JB2 genome browser in a Shiny app or R Markdown + document. The browser can also be launched from an interactive R console. + The browser can be loaded with a variety of common genomics data types, + and can be used with a custom theme. + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JBrowseR + url_git: https://gmod.github.io/JBrowseR/https://github.com/GMOD/JBrowseR +jcalendaR: + version: 0.1.0 + title: |- + Interconversion Between the Japanese Calendar System and the + Western Calendar + maintainer: Mao Kobayashi + description: |- + This is a set of simple utility functions to perform mutual conversion between the current Japanese calendar system that Wareki, the old Japanese calendar system that the Kyureki calendar and the Julian and Gregorian calendar. + To calculate each calendar method, it converts to the Julian Day Number. + date_publication: '2024-06-24' + bug_reports: https://github.com/indenkun/jcalendaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jcalendaR + url_git: https://github.com/indenkun/jcalendaR +jcext: + version: 0.1.1 + title: Extended Classification of Weather Types + maintainer: Noelia Otero + description: |- + Provides a gridded classification of weather types by applying the Jenkinson and Collison classification. For a given region (it can be either local region or the whole map),it computes at each grid the 11 weather + types during the period considered for the analysis. See Otero et al., (2017) for more information. + date_publication: '2019-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jcext + url_git: '' +jcolors: + version: 0.0.5 + title: |- + Colors Palettes for R and 'ggplot2', Additional Themes for + 'ggplot2' + maintainer: Jared Huling + description: Contains a selection of color palettes and 'ggplot2' themes designed + by the package author. + date_publication: '2024-03-29' + bug_reports: https://github.com/jaredhuling/jcolors/issues + url: https://jaredhuling.org/jcolors/ + url_cran: https://CRAN.R-project.org/package=jcolors + url_git: '' +jcp: + version: '1.2' + title: Joint Change Point Detection + maintainer: Michael Messer + description: Procedures for joint detection of changes in both expectation and variance + in univariate sequences. Performs a statistical test of the null hypothesis of + the absence of change points. In case of rejection performs an algorithm for change + point detection. Reference - Bivariate change point detection - joint detection + of changes in expectation and variance, Scandinavian Journal of Statistics, DOI + 10.1111/sjos.12547. + date_publication: '2021-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jcp + url_git: '' +JCRImpactFactor: + version: 1.0.0 + title: |- + Journal Citation Reports ('JCR') Impact Factor by 'Clarivate' + 'Analytics' + maintainer: Shahla Faisal + description: The Impact Factor of a journal reported by Journal Citation Reports + ('JCR') of 'Clarivate' 'Analytics' is provided. The impact factor is available + for those journals only that were included Journal Citation Reports 'JCR'. + date_publication: '2021-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JCRImpactFactor + url_git: '' +Jcvrisk: + version: 0.1.0 + title: Risk Calculator for Cardiovascular Disease in Japan + maintainer: Hiroshi Okumiyama + description: A calculation tool to obtain the 10-year risk of cardiovascular disease + from various risk models (Hisayama, Suita, EPOCH Japan). + date_publication: '2024-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Jcvrisk + url_git: '' +JDCruncheR: + version: 0.3.3 + title: |- + Interface Between the 'JDemetra+' Cruncher and R, and Quality + Report Generator + maintainer: Tanguy Barthelemy + description: 'Tool for generating quality reports from cruncher outputs (and calculating + series scores). The latest version of the cruncher can be downloaded here: .' + date_publication: '2025-02-23' + bug_reports: https://github.com/InseeFr/JDCruncheR/issues + url: https://inseefr.github.io/JDCruncheR/ + url_cran: https://CRAN.R-project.org/package=JDCruncheR + url_git: https://github.com/InseeFr/JDCruncheR +jdenticon: + version: 0.1.1 + title: A Wrapper for the Node.js 'Jdenticon' Library + maintainer: Matt Roumaya + description: A Wrapper for the Node.js 'Jdenticon' Library. + Uses 'esbuild' to reduce user dependencies. + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jdenticon + url_git: '' +Jdmbs: + version: '1.4' + title: |- + Monte Carlo Option Pricing Algorithms for Jump Diffusion Models + with Correlational Companies + maintainer: Masashi Okada + description: Option is a one of the financial derivatives and its pricing is an + important problem in practice. The process of stock prices are represented as + Geometric Brownian motion [Black (1973) ] or jump diffusion + processes [Kou (2002) ]. In this package, algorithms + and visualizations are implemented by Monte Carlo method in order to calculate + European option price for three equations by Geometric Brownian motion and jump + diffusion processes and furthermore a model that presents jumps among companies + affect each other. + date_publication: '2020-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Jdmbs + url_git: '' +jds.rmd: + version: 0.3.3 + title: R Markdown Templates for Journal of Data Science + maintainer: Wenjie Wang + description: |2- + + Customized R Markdown templates for authoring articles + for Journal of Data Science. + date_publication: '2023-06-21' + bug_reports: https://github.com/wenjie2wang/jds.rmd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jds.rmd + url_git: https://github.com/wenjie2wang/jds.rmd +jeek: + version: 1.1.1 + title: |- + A Fast and Scalable Joint Estimator for Integrating Additional + Knowledge in Learning Multiple Related Sparse Gaussian + Graphical Models + maintainer: Beilun Wang + description: 'Provides a fast and scalable joint estimator for integrating additional + knowledge in learning multiple related sparse Gaussian Graphical Models (JEEK). + The JEEK algorithm can be used to fast estimate multiple related precision matrices + in a large-scale. For instance, it can identify multiple gene networks from multi-context + gene expression datasets. By performing data-driven network inference from high-dimensional + and heterogeneous data sets, this tool can help users effectively translate aggregated + data into knowledge that take the form of graphs among entities. Please run demo(jeek) + to learn the basic functions provided by this package. For further details, please + read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi "A Fast and Scalable + Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related + Sparse Gaussian Graphical Models" (ICML 2018) .' + date_publication: '2018-07-07' + bug_reports: https://github.com/QData/jeek + url: '' + url_cran: https://CRAN.R-project.org/package=jeek + url_git: https://github.com/QData/jeek +jellyfisher: + version: 1.0.4 + title: Visualize Spatiotemporal Tumor Evolution with Jellyfish Plots + maintainer: Kari Lavikka + description: |- + Generates interactive Jellyfish plots to visualize spatiotemporal tumor + evolution by integrating sample and phylogenetic trees into a unified plot. + This approach provides an intuitive way to analyze tumor heterogeneity and + evolution over time and across anatomical locations. The Jellyfish plot + visualization design was first introduced by Lahtinen, Lavikka, et al. + (2023, ). + This package also supports visualizing ClonEvol results, a tool developed + by Dang, et al. (2017, ), for analyzing clonal + evolution from multi-sample sequencing data. The 'clonevol' package is not + available on CRAN but can be installed from its GitHub + repository (). + date_publication: '2025-02-06' + bug_reports: https://github.com/HautaniemiLab/jellyfisher/issues + url: https://hautaniemilab.github.io/jellyfisher/ + url_cran: https://CRAN.R-project.org/package=jellyfisher + url_git: https://github.com/HautaniemiLab/jellyfisher +jenga: + version: 1.3.0 + title: Fast Extrapolation of Time Features using K-Nearest Neighbors + maintainer: Giancarlo Vercellino + description: Fast extrapolation of univariate and multivariate time features using + K-Nearest Neighbors. The compact set of hyper-parameters is tuned via grid or + random search. + date_publication: '2022-08-18' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/jenga + url_cran: https://CRAN.R-project.org/package=jenga + url_git: '' +jetpack: + version: 0.5.5 + title: A Friendly Package Manager + maintainer: Andrew Kane + description: Manage project dependencies from your DESCRIPTION file. Create a reproducible + virtual environment with minimal additional files in your project. Provides tools + to add, remove, and update dependencies as well as install existing dependencies + with a single function. + date_publication: '2022-10-31' + bug_reports: https://github.com/ankane/jetpack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jetpack + url_git: https://github.com/ankane/jetpack +jetset: + version: 3.4.0 + title: |- + One-to-One Gene-Probeset Mapping for Affymetrix Human + Microarrays + maintainer: Aron Eklund + description: 'On Affymetrix gene expression microarrays, a single gene may be measured + by multiple probe sets. This can present a mild conundrum when attempting to evaluate + a gene "signature" that is defined by gene names rather than by specific probe + sets. This package provides a one-to-one mapping from gene to "best" probe set + for four Affymetrix human gene expression microarrays: hgu95av2, hgu133a, hgu133plus2, + and u133x3p. This package also includes the pre-calculated probe set quality scores + that were used to define the mapping.' + date_publication: '2017-04-05' + bug_reports: '' + url: http://www.cbs.dtu.dk/biotools/jetset/ + url_cran: https://CRAN.R-project.org/package=jetset + url_git: '' +jetty: + version: 0.2.0 + title: Execute R in a 'Docker' Context + maintainer: Daniel Molitor + description: |- + The goal of 'jetty' is to execute R functions and code + snippets in an isolated R subprocess within a 'Docker' container + and return the evaluated results to the local R session. 'jetty' + can install necessary packages at runtime and seamlessly propagates + errors and outputs from the 'Docker' subprocess back to the main + session. 'jetty' is primarily designed for sandboxed testing and + quick execution of example code. + date_publication: '2025-01-24' + bug_reports: https://github.com/dmolitor/jetty/issues + url: http://www.dmolitor.com/jetty/ + url_cran: https://CRAN.R-project.org/package=jetty + url_git: https://github.com/dmolitor/jetty +jewel: + version: 2.0.2 + title: Graphical Models Estimation from Multiple Sources + maintainer: Anna Plaksienko + description: Estimates networks of conditional dependencies (Gaussian graphical + models) from multiple classes of data (similar but not exactly, i.e. measurements + on different equipment, in different locations or for various sub-types). Package + also allows to generate simulation data and evaluate the performance. Implementation + of the method described in Angelini, De Canditiis and Plaksienko (2022) . + date_publication: '2024-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jewel + url_git: https://github.com/annaplaksienko/jewel +jfa: + version: 0.7.2 + title: Statistical Methods for Auditing + maintainer: Koen Derks + description: |- + Provides statistical methods for auditing as implemented in JASP + for Audit (Derks et al., 2021 ). First, the package + makes it easy for an auditor to plan a statistical sample, select the sample + from the population, and evaluate the misstatement in the sample compliant + with international auditing standards. Second, the package provides + statistical methods for auditing data, including tests of digit + distributions and repeated values. Finally, the package includes methods for + auditing algorithms on the aspect of fairness and bias. Next to classical + statistical methodology, the package implements Bayesian equivalents of + these methods whose statistical underpinnings are described in Derks et al. + (2021) , Derks et al. (2024) + , and Derks et al. (2022) + . + date_publication: '2024-08-23' + bug_reports: https://github.com/koenderks/jfa/issues + url: https://koenderks.github.io/jfa/ + url_cran: https://CRAN.R-project.org/package=jfa + url_git: https://github.com/koenderks/jfa +JFE: + version: 2.5.8 + title: |- + Tools for Analyzing Time Series Data of Just Finance and + Econometrics + maintainer: Ho Tsung-wu + description: Offers procedures to support financial-economic time series modelling + and enhanced procedures for computing the investment performance indices of Bacon + (2004) . + date_publication: '2025-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JFE + url_git: '' +JFM: + version: '1.0' + title: Rock Mass Structural Analysis from 3D Mesh of Point Cloud + maintainer: Riccardo Campana + description: |- + Provides functions to extract joint planes from 3D triangular mesh derived + from point cloud and makes data available for structural analysis. + date_publication: '2022-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JFM + url_git: '' +JGL: + version: 2.3.2 + title: |- + Performs the Joint Graphical Lasso for Sparse Inverse Covariance + Estimation on Multiple Classes + maintainer: Patrick Danaher + description: |- + The Joint Graphical Lasso is a generalized method for + estimating Gaussian graphical models/ sparse inverse covariance + matrices/ biological networks on multiple classes of data. We + solve JGL under two penalty functions: The Fused Graphical + Lasso (FGL), which employs a fused penalty to encourage inverse + covariance matrices to be similar across classes, and the Group + Graphical Lasso (GGL), which encourages similar network + structure between classes. FGL is recommended over GGL for + most applications. Reference: Danaher P, Wang P, Witten DM. (2013) + . + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JGL + url_git: '' +JGR: + version: 1.9-2 + title: Java GUI for R + maintainer: Markus Helbig + description: Java GUI for R - cross-platform, universal and unified Graphical User + Interface for R. For full functionality on Windows and Mac OS X JGR requires a + start application which depends on your OS. + date_publication: '2023-05-20' + bug_reports: '' + url: https://rforge.net/JGR/ + url_cran: https://CRAN.R-project.org/package=JGR + url_git: '' +jgsbook: + version: 1.0.7 + title: |- + Package of the German Book "Statistik mit R und RStudio" by + Joerg grosse Schlarmann + maintainer: Jörg große Schlarmann + description: All datasets and functions used in the german book "Statistik mit R + und RStudio" by grosse Schlarmann (2010-2024) . + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jgsbook + url_git: '' +JICO: + version: '0.1' + title: Joint and Individual Regression + maintainer: Peiyao Wang + description: |- + An R package that implements the JICO algorithm [Wang, P., Wang, H., Li, Q., Shen, D., & Liu, Y. (2024). ]. + It aims at solving the multi-group regression problem. The algorithm decomposes the responses from multiple groups into shared and group-specific + components, which are driven by low-rank approximations of joint and individual structures from the covariates respectively. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JICO + url_git: '' +jiebaR: + version: '0.11' + title: Chinese Text Segmentation + maintainer: Qin Wenfeng + description: |- + Chinese text segmentation, keyword extraction and speech tagging + For R. + date_publication: '2019-12-13' + bug_reports: https://github.com/qinwf/jiebaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jiebaR + url_git: https://github.com/qinwf/jiebaR/ +jiebaRD: + version: '0.1' + title: Chinese Text Segmentation Data for jiebaR Package + maintainer: Qin Wenfeng + description: jiebaR is a package for Chinese text segmentation, keyword extractionand + speech tagging. This package provides the data files required by jiebaR. + date_publication: '2015-01-04' + bug_reports: https://github.com/qinwf/jiebaRD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jiebaRD + url_git: https://github.com/qinwf/jiebaRD/ +jinjar: + version: 0.3.1 + title: Template Engine Inspired by 'Jinja' + maintainer: David Hall + description: |- + Template engine powered by the 'inja' C++ library. Users + write a template document, using syntax inspired by the 'Jinja' Python + package, and then render the final document by passing data from R. + The template syntax supports features such as variables, loops, + conditions and inheritance. + date_publication: '2023-11-01' + bug_reports: https://github.com/davidchall/jinjar/issues + url: https://davidchall.github.io/jinjar/ + url_cran: https://CRAN.R-project.org/package=jinjar + url_git: https://github.com/davidchall/jinjar +jipApprox: + version: 0.1.5 + title: Approximate Inclusion Probabilities for Survey Sampling + maintainer: Roberto Sichera + description: Approximate joint-inclusion probabilities in Unequal Probability Sampling, + or compute Monte Carlo approximations of the first and second-order inclusion + probabilities of a general sampling design as in Fattorini (2006) . + date_publication: '2023-08-26' + bug_reports: https://github.com/rhobis/jipApprox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jipApprox + url_git: '' +jjb: + version: 0.1.1 + title: Balamuta Miscellaneous + maintainer: James Balamuta + description: |- + Set of common functions used for manipulating colors, + detecting and interacting with 'RStudio', modeling, formatting, determining + users' operating system, feature scaling, and more! + date_publication: '2020-01-08' + bug_reports: https://github.com/coatless/jjb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jjb + url_git: https://github.com/coatless/jjb +jlctree: + version: 0.0.2 + title: |- + Joint Latent Class Trees for Joint Modeling of Time-to-Event and + Longitudinal Data + maintainer: Ningshan Zhang + description: Implements the tree-based approach to joint modeling of time-to-event + and longitudinal data. This approach looks for a tree-based partitioning such + that within each estimated latent class defined by a terminal node, the time-to-event + and longitudinal responses display a lack of association. See Zhang and Simonoff + (2018) . + date_publication: '2021-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jlctree + url_git: '' +jlme: + version: 0.4.1 + title: |- + Regression Modelling with 'GLM.jl' and 'MixedModels.jl' in + 'Julia' + maintainer: June Choe + description: |- + Bindings to 'Julia' packages 'GLM.jl' + and 'MixedModels.jl' + , powered by 'JuliaConnectoR'. Fits + (generalized) linear (mixed-effects) regression models in 'Julia' + using familiar model fitting syntax from R. Offers 'broom'-style data + frame summary functionalities for 'Julia' regression models. + date_publication: '2024-11-27' + bug_reports: https://github.com/yjunechoe/jlme/issues/ + url: https://yjunechoe.github.io/jlme/ + url_cran: https://CRAN.R-project.org/package=jlme + url_git: https://github.com/yjunechoe/jlme/ +jlmerclusterperm: + version: 1.1.4 + title: Cluster-Based Permutation Analysis for Densely Sampled Time Data + maintainer: June Choe + description: |- + An implementation of fast cluster-based permutation analysis + (CPA) for densely-sampled time data developed in Maris & Oostenveld, + 2007 . Supports (generalized, + mixed-effects) regression models for the calculation of timewise + statistics. Provides both a wholesale and a piecemeal interface to the + CPA procedure with an emphasis on interpretability and diagnostics. + Integrates 'Julia' libraries 'MixedModels.jl' and 'GLM.jl' for + performance improvements, with additional functionalities for + interfacing with 'Julia' from 'R' powered by the 'JuliaConnectoR' + package. + date_publication: '2024-06-30' + bug_reports: https://github.com/yjunechoe/jlmerclusterperm/issues + url: https://yjunechoe.github.io/jlmerclusterperm/ + url_cran: https://CRAN.R-project.org/package=jlmerclusterperm + url_git: https://github.com/yjunechoe/jlmerclusterperm +JLPM: + version: 1.0.2 + title: Joint Latent Process Models + maintainer: Viviane Philipps + description: Estimation of extended joint models with shared random effects. Longitudinal + data are handled in latent process models for continuous (Gaussian or curvilinear) + and ordinal outcomes while proportional hazard models are used for the survival + part. We propose a frequentist approach using maximum likelihood estimation. See + Saulnier et al, 2022 . + date_publication: '2023-10-06' + bug_reports: https://github.com/VivianePhilipps/JLPM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=JLPM + url_git: '' +JM: + version: 1.5-2 + title: Joint Modeling of Longitudinal and Survival Data + maintainer: Dimitris Rizopoulos + description: Shared parameter models for the joint modeling of longitudinal and + time-to-event data. + date_publication: '2022-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JM + url_git: http://jmr.r-forge.r-project.org/ +jmastats: + version: 0.3.0 + title: Download Weather Data from Japan Meteorological Agency Website + maintainer: Shinya Uryu + description: |- + Provides features that allow users to download + weather data published by the Japan Meteorological Agency (JMA) website + (). The data includes information + dating back to 1976 and aligns with the categories available on the website. + Additionally, users can process the best track data of typhoons and easily + handle earthquake record files. + date_publication: '2025-01-28' + bug_reports: https://github.com/uribo/jmastats/issues + url: https://uribo.github.io/jmastats/ + url_cran: https://CRAN.R-project.org/package=jmastats + url_git: https://github.com/uribo/jmastats +jmatrix: + version: 1.5.2 + title: |- + Read from/Write to Disk Matrices with any Data Type in a Binary + Format + maintainer: Juan Domingo + description: |- + A mainly instrumental package meant to allow other packages whose core is written in 'C++' to read, write + and manipulate matrices in a binary format so that the memory used for them is no more than strictly needed. Its functionality + is already inside 'parallelpam' and 'scellpam', so if you have installed any of these, you do not need to install 'jmatrix'. + Using just the needed memory is not always true with 'R' matrices or vectors, since by default they are of double type. Trials + like the 'float' package have been done, but to use them you have to coerce a matrix already loaded in 'R' memory to a float matrix, + and then you can delete it. The problem comes when your computer has not memory enough to hold the matrix in the first place, so + you are forced to load it by chunks. This is the problem this package tries to address (with partial success, but this is a + difficult problem since 'R' is not a strictly typed language, which is anyway quite hard to get in an interpreted language). + This package allows the creation and manipulation of full, sparse and symmetric matrices of any standard data type. + date_publication: '2024-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jmatrix + url_git: '' +JMbayes: + version: 0.8-85 + title: |- + Joint Modeling of Longitudinal and Time-to-Event Data under a + Bayesian Approach + maintainer: Dimitris Rizopoulos + description: Shared parameter models for the joint modeling of longitudinal and + time-to-event data using MCMC; Dimitris Rizopoulos (2016) . + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JMbayes + url_git: https://github.com/drizopoulos/JMbayes +JMbayes2: + version: 0.5-2 + title: Extended Joint Models for Longitudinal and Time-to-Event Data + maintainer: Dimitris Rizopoulos + description: Fit joint models for longitudinal and time-to-event data under the + Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) + and multiple event times (competing risks and multi-state processes) are accommodated. + Rizopoulos (2012, ISBN:9781439872864). + date_publication: '2025-02-28' + bug_reports: https://github.com/drizopoulos/JMbayes2/issues + url: https://drizopoulos.github.io/JMbayes2/ + url_cran: https://CRAN.R-project.org/package=JMbayes2 + url_git: https://github.com/drizopoulos/JMbayes2 +jmBIG: + version: 0.1.3 + title: Joint Longitudinal and Survival Model for Big Data + maintainer: Atanu Bhattacharjee + description: |- + Provides analysis tools for big data where the sample size is very large. It offers + a suite of functions for fitting and predicting joint models, which allow for the simultaneous + analysis of longitudinal and time-to-event data. This statistical methodology is particularly + useful in medical research where there is often interest in understanding the relationship + between a longitudinal biomarker and a clinical outcome, such as survival or disease progression. + This can be particularly useful in a clinical setting where it is important to be able to predict + how a patient's health status may change over time. Overall, this package provides a + comprehensive set of tools for joint modeling of BIG data obtained as survival and + longitudinal outcomes with both Bayesian and non-Bayesian approaches. Its versatility + and flexibility make it a valuable resource for researchers in many different fields, + particularly in the medical and health sciences. + date_publication: '2025-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jmBIG + url_git: '' +jmcm: + version: 0.2.4 + title: Joint Mean-Covariance Models using 'Armadillo' and S4 + maintainer: Jianxin Pan + description: |- + Fit joint mean-covariance models for longitudinal data. The models + and their components are represented using S4 classes and methods. The core + computational algorithms are implemented using the 'Armadillo' C++ library + for numerical linear algebra and 'RcppArmadillo' glue. + date_publication: '2021-01-12' + bug_reports: https://github.com/ypan1988/jmcm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jmcm + url_git: https://github.com/ypan1988/jmcm/ +jmdem: + version: 1.0.1 + title: Fitting Joint Mean and Dispersion Effects Models + maintainer: Ka Yui Karl Wu + description: Joint mean and dispersion effects models fit the mean and dispersion + parameters of a response variable by two separate linear models, the mean and + dispersion submodels, simultaneously. It also allows the users to choose either + the deviance or the Pearson residuals as the response variable of the dispersion + submodel. Furthermore, the package provides the possibility to nest the submodels + in one another, if one of the parameters has significant explanatory power on + the other. Wu & Li (2016) . + date_publication: '2020-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jmdem + url_git: '' +JMdesign: + version: '1.5' + title: |- + Joint Modeling of Longitudinal and Survival Data - Power + Calculation + maintainer: Shannon T. Holloway + description: |- + Performs power calculations for joint modeling of longitudinal + and survival data with k-th order trajectories when the variance-covariance + matrix, Sigma_theta, is unknown. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JMdesign + url_git: '' +jmetrik: + version: '1.1' + title: Tools for Interacting with 'jMetrik' + maintainer: J. Patrick Meyer + description: 'The main purpose of this package is to make it easy for userR''s to + interact with ''jMetrik'' an open source application for psychometric analysis. + For example it allows useR''s to write data frames to file in a format that can + be used by ''jMetrik''. It also allows useR''s to read *.jmetrik files (e.g. output + from an analysis) for follow-up analysis in R. The *.jmetrik format is a flat + file that includes a multiline header and the data as comma separated values. + The header includes metadata about the file and one row per variable with the + following information in each row: variable name, data type, item scoring, special + data codes, and variable label.' + date_publication: '2018-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jmetrik + url_git: '' +JMH: + version: 1.0.3 + title: Joint Model of Heterogeneous Repeated Measures and Survival Data + maintainer: Shanpeng Li + description: |- + Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and longitudinal data in the presence of heterogeneous within-subject variability, proposed by Li and colleagues (2023) . + The proposed method models the within-subject variability of the biomarker and associates it with the risk of the competing risks event. The time-to-event data is modeled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates. + The longitudinal outcome is modeled using a mixed-effects location and scale model. The association is captured by shared random effects. The model + is estimated using an Expectation Maximization algorithm. + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JMH + url_git: '' +JMI: + version: 0.1.0 + title: Jackknife Mutual Information + maintainer: Zeng Xianli + description: Computes the Jackknife Mutual Information (JMI) between two random + vectors and provides the p-value for dependence tests. See Zeng, X., Xia, Y. and + Tong, H. (2018) . + date_publication: '2018-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JMI + url_git: '' +Jmisc: + version: 0.3.1.1 + title: Julian Miscellaneous Function + maintainer: TszKin Julian Chan + description: Some handy function in R. + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Jmisc + url_git: '' +jmotif: + version: 1.1.1 + title: |- + Time Series Analysis Toolkit Based on Symbolic Aggregate + Discretization, i.e. SAX + maintainer: Pavel Senin + description: |- + Implements time series z-normalization, SAX, HOT-SAX, VSM, SAX-VSM, RePair, and RRA + algorithms facilitating time series motif (i.e., recurrent pattern), discord (i.e., anomaly), + and characteristic pattern discovery along with interpretable time series classification. + date_publication: '2020-02-13' + bug_reports: https://github.com/jMotif/jmotif-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jmotif + url_git: https://github.com/jMotif/jmotif-R +jmuOutlier: + version: '2.2' + title: Permutation Tests for Nonparametric Statistics + maintainer: Steven T. Garren + description: Performs a permutation test on the difference between two location + parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey + test, a ratio mean deviance test. Also performs some graphing techniques, such + as for confidence intervals, vector addition, and Fourier analysis; and includes + functions related to the Laplace (double exponential) and triangular distributions. Performs + power calculations for the binomial test. + date_publication: '2019-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jmuOutlier + url_git: '' +jmv: + version: 2.5.6 + title: The 'jamovi' Analyses + maintainer: Jonathon Love + description: |- + A suite of common statistical methods such as descriptives, + t-tests, ANOVAs, regression, correlation matrices, proportion tests, + contingency tables, and factor analysis. This package is also useable from + the 'jamovi' statistical spreadsheet (see for more + information). + date_publication: '2024-06-20' + bug_reports: https://github.com/jamovi/jmv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jmv + url_git: '' +jmvconnect: + version: 2.5.7 + title: Connect to the 'jamovi' Statistical Spreadsheet + maintainer: Jonathon Love + description: |- + Methods to access data sets from the 'jamovi' statistical + spreadsheet (see for more information) from R. + date_publication: '2024-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jmvconnect + url_git: '' +jmvcore: + version: 2.6.3 + title: Dependencies for the 'jamovi' Framework + maintainer: Jonathon Love + description: |- + A framework for creating rich interactive analyses for the jamovi + platform (see for more information). + date_publication: '2024-09-07' + bug_reports: https://github.com/jamovi/jmvcore/issues + url: https://www.jamovi.org + url_cran: https://CRAN.R-project.org/package=jmvcore + url_git: '' +jmvReadWrite: + version: 0.4.10 + title: Read and Write 'jamovi' Files ('.omv') + maintainer: Sebastian Jentschke + description: |- + The free and open a statistical spreadsheet 'jamovi' + () aims to make statistical analyses easy and + intuitive. 'jamovi' produces syntax that can directly be used in R (in + connection with the R-package 'jmv'). Having import / export routines for + the data files 'jamovi' produces ('.omv') permits an easy transfer of + data and analyses between 'jamovi' and R. + date_publication: '2025-02-17' + bug_reports: https://github.com/sjentsch/jmvReadWrite/issues + url: https://sjentsch.github.io/jmvReadWrite/ + url_cran: https://CRAN.R-project.org/package=jmvReadWrite + url_git: '' +JNplots: + version: 0.1.1 + title: Visualize Outputs from the 'Johnson-Neyman' Technique + maintainer: Ken Toyama + description: Aids in the calculation and visualization of regions of non-significance + using the 'Johnson-Neyman' technique and its extensions as described by Bauer + and Curran (2005) to assess the influence of + categorical and continuous moderators. Allows correcting for phylogenetic relatedness. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JNplots + url_git: https://github.com/kenstoyama/JNplots +job: + version: 0.3.1 + title: Run Code as an RStudio Job - Free Your Console + maintainer: Jonas Kristoffer Lindeløv + description: Call job::job({}) to run R code as an RStudio job and keep + your console free in the meantime. This allows for a productive workflow while + testing (multiple) long-running chunks of code. It can also be used to organize + results using the RStudio Jobs GUI or to test code in a clean environment. Two + RStudio Addins can be used to run selected code as a job. + date_publication: '2024-05-05' + bug_reports: https://github.com/lindeloev/job/issues + url: https://lindeloev.github.io/job/ + url_cran: https://CRAN.R-project.org/package=job + url_git: '' +jobqueue: + version: 1.5.1 + title: Run Interruptible Code Asynchronously + maintainer: Daniel P. Smith + description: |- + Takes an R expression and returns a Job object with a $stop() method + which can be called to terminate the background job. Also provides timeouts + and other mechanisms for automatically terminating a background job. The + result of the expression is available synchronously via $result or + asynchronously with callbacks or through the 'promises' package framework. + date_publication: '2025-02-28' + bug_reports: https://github.com/cmmr/jobqueue/issues + url: https://cmmr.github.io/jobqueue/ + url_cran: https://CRAN.R-project.org/package=jobqueue + url_git: https://github.com/cmmr/jobqueue +jocre: + version: 0.3.3 + title: Joint Confidence Regions + maintainer: Philip Pallmann + description: Computing and plotting joint confidence regions and intervals. Regions + include classical ellipsoids, minimum-volume or minimum-length regions, and an + empirical Bayes region. Intervals include the TOST procedure with ordinary or + expanded intervals and a fixed-sequence procedure. Such regions and intervals + are useful e.g., for the assessment of multi-parameter (bio-)equivalence. Joint + confidence regions for the mean and variance of a normal distribution are available + as well. + date_publication: '2017-05-12' + bug_reports: https://github.com/PhilipPallmann/jocre/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jocre + url_git: '' +JoF: + version: 0.1.0 + title: Modelling and Simulating Judgments of Frequency + maintainer: Markus Burkhardt + description: 'In a typical experiment for the intuitive judgment of frequencies + (JoF) different stimuli with different frequencies are presented. The participants + consider these stimuli with a constant duration and give a judgment of frequency. + These judgments can be simulated by formal models: PASS 1 and PASS 2 based on + Sedlmeier (2002, ISBN:978-0198508632), MINERVA 2 baesd on Hintzman (1984) + and TODAM 2 based on Murdock, Smith & Bai (2001) . + The package provides an assessment of the frequency by determining the core aspects + of these four models (attention, decay, and presented frequency) that can be compared + to empirical results.' + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JoF + url_git: '' +joineR: + version: 1.2.8 + title: Joint Modelling of Repeated Measurements and Time-to-Event Data + maintainer: Graeme L. Hickey + description: |- + Analysis of repeated measurements and time-to-event data via random + effects joint models. Fits the joint models proposed by Henderson and colleagues + (single event time) and by Williamson and + colleagues (2008) (competing risks events time) to a + single continuous repeated measure. The time-to-event data is modelled using a + (cause-specific) Cox proportional hazards regression model with time-varying + covariates. The longitudinal outcome is modelled using a linear mixed effects + model. The association is captured by a latent Gaussian process. The model is + estimated using am Expectation Maximization algorithm. Some plotting functions + and the variogram are also included. This project is funded by the Medical + Research Council (Grant numbers G0400615 and MR/M013227/1). + date_publication: '2023-01-22' + bug_reports: https://github.com/graemeleehickey/joineR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=joineR + url_git: https://github.com/graemeleehickey/joineR/ +joineRML: + version: 0.4.7 + title: |- + Joint Modelling of Multivariate Longitudinal Data and + Time-to-Event Outcomes + maintainer: Graeme L. Hickey + description: |- + Fits the joint model proposed by Henderson and colleagues (2000) + , but extended to the case of multiple + continuous longitudinal measures. The time-to-event data is modelled using a + Cox proportional hazards regression model with time-varying covariates. The + multiple longitudinal outcomes are modelled using a multivariate version of the + Laird and Ware linear mixed model. The association is captured by a multivariate + latent Gaussian process. The model is estimated using a Monte Carlo Expectation + Maximization algorithm. This project was funded by the Medical Research Council + (Grant number MR/M013227/1). + date_publication: '2025-02-04' + bug_reports: https://github.com/graemeleehickey/joineRML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=joineRML + url_git: https://github.com/graemeleehickey/joineRML +joinet: + version: 1.0.0 + title: Penalised Multivariate Regression ('Multi-Target Learning') + maintainer: Armin Rauschenberger + description: Implements penalised multivariate regression (i.e., for multiple outcomes + and many features) by stacked generalisation (). + For positively correlated outcomes, a single multivariate regression is typically + more predictive than multiple univariate regressions. Includes functions for model + fitting, extracting coefficients, outcome prediction, and performance measurement. + For optional comparisons, install 'remMap' from GitHub (). + date_publication: '2024-09-27' + bug_reports: https://github.com/rauschenberger/joinet/issues + url: https://rauschenberger.github.io/joinet/ + url_cran: https://CRAN.R-project.org/package=joinet + url_git: https://github.com/rauschenberger/joinet +joint.Cox: + version: '3.16' + title: |- + Joint Frailty-Copula Models for Tumour Progression and Death in + Meta-Analysis + maintainer: Takeshi Emura + description: |- + Fit survival data and perform dynamic prediction under joint frailty-copula models for tumour progression and death. + Likelihood-based methods are employed for estimating model parameters, where the baseline hazard functions are modeled by the cubic M-spline or the Weibull model. + The methods are applicable for meta-analytic data containing individual-patient information from several studies. + Survival outcomes need information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression). + Methodologies were published in + Emura et al. (2017) , Emura et al. (2018) , + Emura et al. (2020) , Shinohara et al. (2020) , + Wu et al. (2020) , and Emura et al. (2021) . + See also the book of Emura et al. (2019) . + Survival data from ovarian cancer patients are also available. + date_publication: '2022-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=joint.Cox + url_git: '' +JointAI: + version: 1.0.6 + title: Joint Analysis and Imputation of Incomplete Data + maintainer: Nicole S. Erler + description: |- + Joint analysis and imputation of incomplete data in the Bayesian + framework, using (generalized) linear (mixed) models and extensions there of, + survival models, or joint models for longitudinal and survival data, as + described in Erler, Rizopoulos and Lesaffre (2021) . + Incomplete covariates, if present, are automatically imputed. + The package performs some preprocessing of the data and creates a 'JAGS' + model, which will then automatically be passed to 'JAGS' + with the help of + the package 'rjags'. + date_publication: '2024-04-02' + bug_reports: https://github.com/nerler/JointAI/issues/ + url: https://nerler.github.io/JointAI/ + url_cran: https://CRAN.R-project.org/package=JointAI + url_git: '' +jointCalib: + version: 0.1.0 + title: A Joint Calibration of Totals and Quantiles + maintainer: Maciej Beręsewicz + description: A small package containing functions to perform a joint calibration + of totals and quantiles. The calibration for totals is based on Deville and Särndal + (1992) , the calibration for quantiles is + based on Harms and Duchesne (2006) . + The package uses standard calibration via the 'survey', 'sampling' or 'laeken' + packages. In addition, entropy balancing via the 'ebal' package and empirical + likelihood based on codes from Wu (2005) + can be used. See the paper by Beręsewicz and Szymkowiak (2023) for details . + date_publication: '2023-09-07' + bug_reports: https://github.com/ncn-foreigners/jointCalib/issues + url: https://ncn-foreigners.github.io/jointCalib/ + url_cran: https://CRAN.R-project.org/package=jointCalib + url_git: https://github.com/ncn-foreigners/jointCalib +jointDiag: + version: '0.4' + title: Joint Approximate Diagonalization of a Set of Square Matrices + maintainer: Cedric Gouy-Pailler + description: |- + Different algorithms to perform approximate joint diagonalization + of a finite set of square matrices. Depending on the algorithm, + orthogonal or non-orthogonal diagonalizer is found. These algorithms + are particularly useful in the context of blind source separation. + Original publications of the algorithms can be found in + Ziehe et al. (2004), Pham and Cardoso (2001) , + Souloumiac (2009) , + Vollgraff and Obermayer . An example of + application in the context of Brain-Computer Interfaces EEG denoising + can be found in Gouy-Pailler et al (2010) . + date_publication: '2020-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jointDiag + url_git: https://github.com/gouypailler/jointDiag +jointest: + version: '1.0' + title: Multivariate Testing Through Joint Resampling-Based Tests + maintainer: Livio Finos + description: Runs resampling-based tests jointly, e.g., sign-flip score tests from + Hemerik et al., (2020) , to allow for multivariate testing, + i.e., weak and strong control of the Familywise Error Rate or True Discovery Proportion. + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jointest + url_git: '' +JointFPM: + version: 1.2.2 + title: A Parametric Model for Estimating the Mean Number of Events + maintainer: Joshua P. Entrop + description: |- + Implementation of a parametric joint model for modelling recurrent + and competing event processes using generalised survival models as described in + Entrop et al., (2005) . The joint model can + subsequently be used to predict the mean number of events in the + presence of competing risks at different time points. Comparisons of the mean + number of event functions, e.g. the differences in mean number of events + between two exposure groups, are also available. + date_publication: '2025-02-20' + bug_reports: https://github.com/entjos/JointFPM/issues + url: https://entjos.github.io/JointFPM/ + url_cran: https://CRAN.R-project.org/package=JointFPM + url_git: https://github.com/entjos/JointFPM +jointMeanCov: + version: 0.1.0 + title: Joint Mean and Covariance Estimation for Matrix-Variate Data + maintainer: Michael Hornstein + description: |- + Jointly estimates two-group means and covariances + for matrix-variate data and calculates test statistics. + This package implements the algorithms defined in + Hornstein, Fan, Shedden, and Zhou (2018) + . + date_publication: '2019-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jointMeanCov + url_git: '' +jointNmix: + version: '1.0' + title: Joint N-Mixture Models for Site-Associated Species + maintainer: Rafael de Andrade Moral + description: Fits univariate and joint N-mixture models for data on two unmarked + site-associated species. Includes functions to estimate latent abundances through + empirical Bayes methods. + date_publication: '2016-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jointNmix + url_git: '' +jointPm: + version: 2.3.2 + title: Risk Estimation Using the Joint Probability Method + maintainer: Leo Belzile + description: Estimate risk caused by two extreme and dependent forcing variables + using bivariate extreme value models as described in Zheng, Westra, and Sisson + (2013) ; Zheng, Westra and Leonard (2014) ; + Zheng, Leonard and Westra (2015) . + date_publication: '2023-04-22' + bug_reports: https://github.com/lbelzile/jointPm/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=jointPm + url_git: '' +jointseg: + version: 1.0.2 + title: Joint Segmentation of Multivariate (Copy Number) Signals + maintainer: Morgane Pierre-Jean + description: |- + Methods for fast segmentation of multivariate + signals into piecewise constant profiles and for generating realistic + copy-number profiles. A typical application is the joint segmentation of total + DNA copy numbers and allelic ratios obtained from Single Nucleotide Polymorphism + (SNP) microarrays in cancer studies. The methods are described in Pierre-Jean, + Rigaill and Neuvial (2015) . + date_publication: '2019-01-11' + bug_reports: https://github.com/mpierrejean/jointseg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jointseg + url_git: https://github.com/mpierrejean/jointseg +jointVIP: + version: 1.0.0 + title: |- + Prioritize Variables with Joint Variable Importance Plot in + Observational Study Design + maintainer: Lauren D. Liao + description: |- + In the observational study design stage, matching/weighting methods are + conducted. However, when many background variables are present, the decision as to + which variables to prioritize for matching/weighting is not trivial. Thus, the + joint treatment-outcome variable importance plots are created to guide variable + selection. The joint variable importance plots enhance variable comparisons via + unadjusted bias curves derived under the omitted variable bias framework. The + plots translate variable importance into recommended values for tuning parameters + in existing methods. Post-matching and/or weighting plots can also be used to + visualize and assess the quality of the observational study design. The method + motivation and derivation is presented in "Prioritizing Variables for Observational + Study Design using the Joint Variable Importance Plot" by Liao et al. (2024) + . See the package paper by Liao and Pimentel + (2024) for a beginner friendly user introduction. + date_publication: '2024-11-22' + bug_reports: https://github.com/ldliao/jointVIP/issues + url: https://ldliao.github.io/jointVIP/ + url_cran: https://CRAN.R-project.org/package=jointVIP + url_git: https://github.com/ldliao/jointVIP +joinXL: + version: 1.0.1 + title: Perform Joins or Minus Queries on 'Excel' Files + maintainer: Yvonne Glanville + description: |- + Performs Joins and Minus Queries on 'Excel' Files + fulljoinXL() Merges all rows of 2 'Excel' files based upon a common column in the files. + innerjoinXL() Merges all rows from base file and join file when the join condition is met. + leftjoinXL() Merges all rows from the base file, and all rows from the join file + if the join condition is met. + rightjoinXL() Merges all rows from the join file, and all rows from the base file if the join + condition is met. + minusXL() Performs 2 operations source-minus-target and target-minus-source + If the files are identical all output files will be empty. + Choose two 'Excel' files via a dialog box, and then follow prompts at the console to + choose a base or source file and columns to merge or minus on. + date_publication: '2016-09-19' + bug_reports: http://github.com/yvonneglanville/joinXL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=joinXL + url_git: http://github.com/yvonneglanville/joinXL +jomo: + version: 2.7-6 + title: Multilevel Joint Modelling Multiple Imputation + maintainer: Matteo Quartagno + description: |- + Similarly to package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) . + Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model. + date_publication: '2023-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jomo + url_git: '' +JOPS: + version: 0.1.19 + title: Practical Smoothing with P-Splines + maintainer: Paul Eilers + description: |- + Functions and data to reproduce all plots in the book "Practical Smoothing. + The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950). + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JOPS + url_git: '' +jordan: + version: 1.0-6 + title: A Suite of Routines for Working with Jordan Algebras + maintainer: Robin K. S. Hankin + description: |- + A Jordan algebra is an algebraic object originally + designed to study observables in quantum mechanics. Jordan + algebras are commutative but non-associative; they satisfy the + Jordan identity. The package follows the ideas and notation of + K. McCrimmon (2004, ISBN:0-387-95447-3) "A Taste of Jordan + Algebras". To cite the package in publications, please use + Hankin (2023) . + date_publication: '2024-07-04' + bug_reports: https://github.com/RobinHankin/jordan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jordan + url_git: https://github.com/RobinHankin/jordan +JoSAE: + version: 0.3.0 + title: Unit-Level and Area-Level Small Area Estimation + maintainer: Johannes Breidenbach + description: Implementation of some unit and area level EBLUP estimators as well + as the estimators of their MSE also under heteroscedasticity. The package further + documents the publications Breidenbach and Astrup (2012) , + Breidenbach et al. (2016) and Breidenbach et al. + (2018 in press). The vignette further explains the use of the implemented functions. + date_publication: '2018-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JoSAE + url_git: '' +josaplay: + version: 0.1.3 + title: Add Josa Based on Previous Letter in Korean + maintainer: Chanyub Park + description: |- + Josa in Korean is often determined by judging the previous word. + When writing reports using Rmd, a function that prints the + appropriate investigation for each case is helpful. + The 'josaplay' package then evaluates the previous word + to determine which josa is appropriate. + date_publication: '2019-05-16' + bug_reports: https://github.com/mrchypark/josaplay/issues + url: '' + url_cran: https://CRAN.R-project.org/package=josaplay + url_git: https://github.com/mrchypark/josaplay +jose: + version: 1.2.1 + title: JavaScript Object Signing and Encryption + maintainer: Jeroen Ooms + description: |- + Read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON + Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519) + . These standards provide + modern signing and encryption formats that are natively supported by browsers + via the JavaScript WebCryptoAPI , + and used by services like OAuth 2.0, LetsEncrypt, and Github Apps. + date_publication: '2024-10-04' + bug_reports: https://github.com/r-lib/jose/issues + url: https://r-lib.r-universe.dev/jose + url_cran: https://CRAN.R-project.org/package=jose + url_git: '' +jot: + version: 0.0.4 + title: Jot Down Values for Later + maintainer: Christopher T. Kenny + description: |- + Reproducible work requires a record of where every statistic originated. + When writing reports, some data is too big to load in the same environment and some statistics take a while to compute. + This package offers a way to keep notes on statistics, simple functions, and small objects. + Notepads can be locked to avoid accidental updates. + Notepads keep track of who added the notes and when the notes were added. + A simple text representation is used to allow for clear version histories. + date_publication: '2022-08-27' + bug_reports: https://github.com/christopherkenny/jot/issues + url: http://christophertkenny.com/jot/ + url_cran: https://CRAN.R-project.org/package=jot + url_git: https://github.com/christopherkenny/jot +journalabbr: + version: 0.4.3 + title: Journal Abbreviations for BibTeX Documents + maintainer: ShuCai Zou + description: Since the reference management software (such as 'Zotero', 'Mendeley') + exports Bib file journal abbreviation is not detailed enough, the 'journalabbr' + package only abbreviates the journal field of Bib file, and then outputs a new + Bib file for generating reference format with journal abbreviation on other software + (such as 'texstudio'). The abbreviation table is from 'JabRef'. At the same time, + 'Shiny' application is provided to generate 'thebibliography', a reference format + that can be directly used for latex paper writing based on 'Rmd' files. + date_publication: '2024-02-21' + bug_reports: https://github.com/zoushucai/journalabbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=journalabbr + url_git: https://github.com/zoushucai/journalabbr +JOUSBoost: + version: 2.1.0 + title: Implements Under/Oversampling for Probability Estimation + maintainer: Matthew Olson + description: |- + Implements under/oversampling for probability estimation. To be + used with machine learning methods such as AdaBoost, random forests, etc. + date_publication: '2017-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JOUSBoost + url_git: '' +joyn: + version: 0.2.4 + title: |- + Tool for Diagnosis of Tables Joins and Complementary Join + Features + maintainer: R.Andres Castaneda + description: |- + Tool for diagnosing table joins. It combines the speed of `collapse` + and `data.table`, the flexibility of `dplyr`, and the diagnosis and features + of the `merge` command in `Stata`. + date_publication: '2024-12-13' + bug_reports: https://github.com/randrescastaneda/joyn/issues + url: https://randrescastaneda.github.io/joyn/ + url_cran: https://CRAN.R-project.org/package=joyn + url_git: https://github.com/randrescastaneda/joyn +jpcity: + version: 0.3.0 + title: Read and Convert Japanese Municipality Codes + maintainer: Mizuki Uchida + description: |- + Read Japanese city codes () + to get city and prefecture names, or convert to city codes at different + points in time. In addition, it merges or splits wards of designated cities + and gets all city codes at a specific point in time. + date_publication: '2024-10-04' + bug_reports: https://github.com/UchidaMizuki/jpcity/issues + url: https://uchidamizuki.github.io/jpcity/ + url_cran: https://CRAN.R-project.org/package=jpcity + url_git: https://github.com/UchidaMizuki/jpcity +jpeg: + version: 0.1-10 + title: Read and write JPEG images + maintainer: Simon Urbanek + description: This package provides an easy and simple way to read, write and display + bitmap images stored in the JPEG format. It can read and write both files and + in-memory raw vectors. + date_publication: '2022-11-29' + bug_reports: https://github.com/s-u/jpeg/issues + url: https://www.rforge.net/jpeg/ + url_cran: https://CRAN.R-project.org/package=jpeg + url_git: '' +JPEN: + version: '1.0' + title: |- + Covariance and Inverse Covariance Matrix Estimation Using Joint + Penalty + maintainer: Ashwini Maurya + description: A Joint PENalty Estimation of Covariance and Inverse Covariance Matrices. + date_publication: '2015-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JPEN + url_git: '' +jpgrid: + version: 0.4.0 + title: Functions for the Grid Square Codes in Japan + maintainer: Mizuki Uchida + description: |- + Provides functions for grid square codes in Japan + (). + Generates the grid square codes from longitude/latitude, geometries, and + the grid square codes of different scales, and vice versa. + date_publication: '2024-05-26' + bug_reports: https://github.com/UchidaMizuki/jpgrid/issues + url: https://uchidamizuki.github.io/jpgrid/ + url_cran: https://CRAN.R-project.org/package=jpgrid + url_git: https://github.com/UchidaMizuki/jpgrid +jpmesh: + version: 2.1.0 + title: Utilities for Japanese Mesh Code + maintainer: Shinya Uryu + description: Helpful functions for using mesh code (80km to 100m) data in Japan. + Visualize mesh code using 'ggplot2' and 'leaflet', etc. + date_publication: '2022-01-10' + bug_reports: https://github.com/uribo/jpmesh/issues/ + url: https://uribo.github.io/jpmesh/ + url_cran: https://CRAN.R-project.org/package=jpmesh + url_git: '' +jpstat: + version: 0.4.0 + title: Tools for Easy Use of 'e-Stat', 'RESAS' API, Etc + maintainer: Mizuki Uchida + description: |- + Provides tools to use API such as 'e-Stat' (), + the portal site for Japanese government statistics, and + 'RESAS' (Regional Economy and Society Analyzing System, ). + date_publication: '2023-07-15' + bug_reports: https://github.com/UchidaMizuki/jpstat/issues + url: https://uchidamizuki.github.io/jpstat/ + url_cran: https://CRAN.R-project.org/package=jpstat + url_git: https://github.com/UchidaMizuki/jpstat +jqbr: + version: 1.0.3 + title: '''jQuery QueryBuilder'' Input for ''Shiny''' + maintainer: Harry Fisher + description: |- + A highly configurable 'jQuery' plugin offering a simple + interface to create complex queries/filters in 'Shiny'. The outputted + rules can easily be parsed into a set of 'R' and/or 'SQL' queries and + used to filter data. Custom parsing of the rules is also supported. + For more information about 'jQuery QueryBuilder' see + . + date_publication: '2023-08-15' + bug_reports: https://github.com/hfshr/jqbr/issues + url: https://hfshr.github.io/jqbr/ + url_cran: https://CRAN.R-project.org/package=jqbr + url_git: https://github.com/hfshr/jqbr +JQL: + version: 3.6.9 + title: Jump Q-Learning for Individualized Interval-Valued Dose Rule + maintainer: Hengrui Cai + description: We provide tools to estimate the individualized interval-valued dose + rule (I2DR) that maximizes the expected beneficial clinical outcome for each individual + and returns an optimal interval-valued dose, by using the jump Q-learning (JQL) + method. The jump Q-learning method directly models the conditional mean of the + response given the dose level and the baseline covariates via jump penalized least + squares regression under the framework of Q learning. We develop a searching algorithm + by dynamic programming in order to find the optimal I2DR with the time complexity + O(n2) and spatial complexity O(n). To alleviate the effects of misspecification + of the Q-function, a residual jump Q-learning is further proposed to estimate + the optimal I2DR. The outcome of interest includes the best partition of the entire + dosage of interest, the regression coefficients of each partition, and the value + function under the estimated I2DR as well as the Wald-type confidence interval + of value function constructed through the Bootstrap. + date_publication: '2019-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JQL + url_git: '' +jqr: + version: 1.4.0 + title: Client for 'jq', a 'JSON' Processor + maintainer: Jeroen Ooms + description: |- + Client for 'jq', a 'JSON' processor (), + written in C. 'jq' allows the following with 'JSON' data: index into, parse, + do calculations, cut up and filter, change key names and values, perform + conditionals and comparisons, and more. + date_publication: '2024-12-16' + bug_reports: https://github.com/ropensci/jqr/issues + url: https://docs.ropensci.org/jqr/https://ropensci.r-universe.dev/jqr + url_cran: https://CRAN.R-project.org/package=jqr + url_git: '' +jquerylib: + version: 0.1.4 + title: Obtain 'jQuery' as an HTML Dependency Object + maintainer: Carson Sievert + description: |- + Obtain any major version of 'jQuery' () and use it in any webpage generated by 'htmltools' (e.g. 'shiny', 'htmlwidgets', and 'rmarkdown'). + Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'. + date_publication: '2021-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jquerylib + url_git: '' +jrc: + version: 0.6.0 + title: Exchange Commands Between R and 'JavaScript' + maintainer: Svetlana Ovchinnikova + description: An 'httpuv' based bridge between R and 'JavaScript'. Provides an easy + way to exchange commands and data between a web page and a currently running R + session. + date_publication: '2023-08-23' + bug_reports: https://github.com/anders-biostat/jrc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jrc + url_git: https://github.com/anders-biostat/jrc +jrich: + version: 0.60-35 + title: |- + Jack-Knife Support for Evolutionary Distinctiveness Indices I + and W + maintainer: Daniel R. Miranda-Esquivel + description: |- + These functions calculate the taxonomic measures presented in Miranda-Esquivel (2016). + The package introduces Jack-knife resampling in evolutionary distinctiveness prioritization analysis, + as a way to evaluate the support of the ranking in area prioritization, and the persistence of a given area + in a conservation analysis. + The algorithm is described in: Miranda-Esquivel, D (2016) . + date_publication: '2016-03-06' + bug_reports: https://github.com/Dmirandae/jrich/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jrich + url_git: https://github.com/Dmirandae/jrich +jrSiCKLSNMF: + version: 1.2.2 + title: Multimodal Single-Cell Omics Dimensionality Reduction + maintainer: Dorothy Ellis + description: Methods to perform Joint graph Regularized Single-Cell Kullback-Leibler + Sparse Non-negative Matrix Factorization ('jrSiCKLSNMF', pronounced "junior sickles + NMF") on quality controlled single-cell multimodal omics count data. 'jrSiCKLSNMF' + specifically deals with dual-assay scRNA-seq and scATAC-seq data. This package + contains functions to extract meaningful latent factors that are shared across + omics modalities. These factors enable accurate cell-type clustering and facilitate + visualizations. Methods for pre-processing, clustering, and mini-batch updates + and other adaptations for larger datasets are also included. For further details + on the methods used in this package please see Ellis, Roy, and Datta (2023) . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jrSiCKLSNMF + url_git: '' +jrt: + version: 1.1.2 + title: Item Response Theory Modeling and Scoring for Judgment Data + maintainer: Nils Myszkowski + description: Psychometric analysis and scoring of judgment data using polytomous + Item-Response Theory (IRT) models, as described in Myszkowski and Storme (2019) + and Myszkowski (2021) . A function + is used to automatically compare and select models, as well as to present a variety + of model-based statistics. Plotting functions are used to present category curves, + as well as information, reliability and standard error functions. + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jrt + url_git: '' +jrvFinance: + version: 1.4.3 + title: Basic Finance; NPV/IRR/Annuities/Bond-Pricing; Black Scholes + maintainer: Jayanth Varma + description: |- + Implements the basic financial analysis + functions similar to (but not identical to) what + is available in most spreadsheet software. This + includes finding the IRR and NPV of regularly + spaced cash flows and annuities. Bond pricing and + YTM calculations are included. In addition, Black + Scholes option pricing and Greeks are also + provided. + date_publication: '2021-11-05' + bug_reports: https://github.com/jrvarma/jrvFinance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jrvFinance + url_git: https://github.com/jrvarma/jrvFinance +js: + version: 1.2.1 + title: Tools for Working with JavaScript in R + maintainer: Jeroen Ooms + description: |- + A set of utilities for working with JavaScript syntax in R. + Includes tools to parse, tokenize, compile, validate, reformat, optimize + and analyze JavaScript code. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/js/issues + url: https://jeroen.r-universe.dev/js + url_cran: https://CRAN.R-project.org/package=js + url_git: '' +JSconsole: + version: 0.1.0 + title: A 'RStudio' Addin to Send 'JavaScript' Code to the 'V8' Console + maintainer: Stéphane Laurent + description: Provides a 'RStudio' addin to send some 'JavaScript' code to the 'V8' + console. The user can send an entire 'JavaScript' file or only some selected lines. + This is useful to test the code. + date_publication: '2020-10-15' + bug_reports: https://github.com/stla/JSconsole/issues + url: '' + url_cran: https://CRAN.R-project.org/package=JSconsole + url_git: https://github.com/stla/JSconsole +jScore: + version: 0.1.0 + title: Calculates the j-Score Between Two Clustering Assignments + maintainer: Navid Ahmadinejad + description: |- + The jscore() function in the package calculates the J-Score metric between two clustering + assignments. The score is designed to address some problems with existing common metrics such + as problem of matching. The details of J-score is described in Ahmadinejad and Liu. (2021) . + date_publication: '2021-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jScore + url_git: https://github.com/liliulab/jscore +jSDM: + version: 0.2.6 + title: Joint Species Distribution Models + maintainer: Jeanne Clément + description: |- + Fits joint species distribution models ('jSDM') + in a hierarchical Bayesian framework (Warton and al. 2015 + ). The Gibbs sampler is written + in 'C++'. It uses 'Rcpp', 'Armadillo' and 'GSL' to maximize computation + efficiency. + date_publication: '2023-07-22' + bug_reports: https://github.com/ghislainv/jSDM/issues + url: https://ecology.ghislainv.fr/jSDM/ + url_cran: https://CRAN.R-project.org/package=jSDM + url_git: https://github.com/ghislainv/jSDM +JSDNE: + version: 4.4.4 + title: Estimating the Age using Auricular Surface by DNE + maintainer: Jisun Jang + description: 'The age is estimated by calculating the Dirichlet Normal Energy (DNE) + on the whole auricular surface and the apex of the auricular surface. It involves + three estimation methods: principal component discriminant analysis (PCQDA), principal + component regression analysis (PCR), and principal component logistic regression + analysis (PCLR) methods. The package is created with the data from the Louis Lopes + Collection in Lisbon, the 21st Century Identified Human Remains Collection in + Coimbra, and the CAL Milano Cemetery Skeletal Collection in Milan.' + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JSDNE + url_git: '' +jshintr: + version: 0.1.0 + title: Lint 'JavaScript' Files + maintainer: Stéphane Laurent + description: |- + Allow to run 'jshint' on 'JavaScript' files with a 'R' + command or a 'RStudio' addin. The report appears in the 'RStudio' + viewer pane. + date_publication: '2022-06-10' + bug_reports: https://github.com/stla/jshintr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jshintr + url_git: https://github.com/stla/jshintr +jskm: + version: 0.5.10 + title: Kaplan-Meier Plot with 'ggplot2' + maintainer: Jinseob Kim + description: The function 'jskm()' creates publication quality Kaplan-Meier plot + with at risk tables below. 'svyjskm()' provides plot for weighted Kaplan-Meier + estimator. + date_publication: '2025-02-05' + bug_reports: https://github.com/jinseob2kim/jstable/issues + url: https://jinseob2kim.github.io/jskm/ + url_cran: https://CRAN.R-project.org/package=jskm + url_git: https://github.com/jinseob2kim/jskm +JSM: + version: 1.0.1 + title: Semiparametric Joint Modeling of Survival and Longitudinal Data + maintainer: Cong Xu + description: 'Maximum likelihood estimation for the semiparametric joint modeling + of survival and longitudinal data. Refer to the Journal of Statistical Software + article: .' + date_publication: '2020-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JSM + url_git: '' +JSmediation: + version: 0.2.3 + title: Mediation Analysis Using Joint Significance + maintainer: Cédric Batailler + description: |- + A set of helper functions to conduct joint-significance tests + for mediation analysis, as recommended by Yzerbyt, Muller, Batailler, + & Judd. (2018) . + date_publication: '2025-01-26' + bug_reports: https://github.com/cedricbatailler/JSmediation/issues + url: https://jsmediation.cedricbatailler.me/ + url_cran: https://CRAN.R-project.org/package=JSmediation + url_git: https://github.com/cedricbatailler/JSmediation +jsmodule: + version: 1.6.3 + title: '''RStudio'' Addins and ''Shiny'' Modules for Medical Research' + maintainer: Jinseob Kim + description: '''RStudio'' addins and ''Shiny'' modules for descriptive statistics, + regression and survival analysis.' + date_publication: '2025-02-19' + bug_reports: https://github.com/jinseob2kim/jsmodule/issues + url: https://jinseob2kim.github.io/jsmodule/ + url_cran: https://CRAN.R-project.org/package=jsmodule + url_git: https://github.com/jinseob2kim/jsmodule +json2aRgs: + version: 0.3.0 + title: Parse Parameters Inside a Docker Container + maintainer: Alexander Dolich + description: 'The function get_parameters() is intended to be used within a docker + container to read keyword arguments from a .json file automagically. A tool.yaml + file contains specifications on these keyword arguments, which are then passed + as input to containerized R tools in the [tool-runner framework](). + A template for a containerized R tool, which can be used as a basis for developing + new tools, is available at the following URL: .' + date_publication: '2022-11-25' + bug_reports: https://github.com/VForWaTer/json2aRgs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=json2aRgs + url_git: https://github.com/VForWaTer/json2aRgs +json64: + version: 0.1.3 + title: |- + A 'Base64' Encode/Decode Package with Support for JSON + Output/Input and UTF-8 + maintainer: Mauricio Santelices + description: 'Encode/Decode ''base64'', with support for JSON format, using two + functions: j_encode() and j_decode(). ''Base64'' is a group of similar binary-to-text + encoding schemes that represent binary data in an ASCII string format by translating + it into a radix-64 representation, used when there is a need to encode binary + data that needs to be stored and transferred over media that are designed to deal + with textual data, ensuring that the data will remain intact and without modification + during transport. On + the other side, JSON (JavaScript Object Notation) is a lightweight data-interchange + format. Easy to read, write, parse and generate. It is based on a subset of the + JavaScript Programming Language. JSON is a text format that is completely language + independent but uses conventions that are familiar to programmers of the C-family + of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. + JSON structure is built around name:value pairs and ordered list of values. The + first function, j_encode(), let you transform a data.frame or list to a ''base64'' + encoded JSON (or JSON string). The j_decode() function takes a ''base64'' string + (could be an encoded JSON) and transform it to a data.frame (or list, depending + of the JSON structure).' + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=json64 + url_git: '' +jsonify: + version: 1.2.2 + title: |- + Convert Between 'R' Objects and Javascript Object Notation + (JSON) + maintainer: David Cooley + description: |- + Conversions between 'R' objects and Javascript Object Notation (JSON) using + the 'rapidjsonr' library . + date_publication: '2022-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jsonify + url_git: '' +jsonld: + version: 2.2.1 + title: JSON for Linking Data + maintainer: Jeroen Ooms + description: |- + JSON-LD is a light-weight syntax for + expressing linked data. It is primarily intended for web-based programming + environments, interoperable web services and for storing linked data in + JSON-based databases. This package provides bindings to the JavaScript + library for converting, expanding and compacting JSON-LD documents. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/jsonld/issues + url: https://docs.ropensci.org/jsonld/ + url_cran: https://CRAN.R-project.org/package=jsonld + url_git: '' +jsonlite: + version: 1.9.0 + title: A Simple and Robust JSON Parser and Generator for R + maintainer: Jeroen Ooms + description: |- + A reasonably fast JSON parser and generator, optimized for statistical + data and the web. Offers simple, flexible tools for working with JSON in R, and + is particularly powerful for building pipelines and interacting with a web API. + The implementation is based on the mapping described in the vignette (Ooms, 2014). + In addition to converting JSON data from/to R objects, 'jsonlite' contains + functions to stream, validate, and prettify JSON data. The unit tests included + with the package verify that all edge cases are encoded and decoded consistently + for use with dynamic data in systems and applications. + date_publication: '2025-02-19' + bug_reports: https://github.com/jeroen/jsonlite/issues + url: https://jeroen.r-universe.dev/jsonlitehttps://arxiv.org/abs/1403.2805 + url_cran: https://CRAN.R-project.org/package=jsonlite + url_git: '' +jsonNormalize: + version: 1.0.0 + title: Normalization of 'JSON' Strings + maintainer: Stéphane Laurent + description: |- + Provides a function allowing to normalize a 'JSON' string, + for example by adding double quotes around the keys when they are + missing. Also provides 'RStudio' addins for the same purpose. + date_publication: '2023-05-25' + bug_reports: https://github.com/stla/jsonNormalize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jsonNormalize + url_git: https://github.com/stla/jsonNormalize +jsonstat: + version: 0.0.2 + title: Interface to 'JSON-stat' + maintainer: Kim Seonghyun + description: |- + Interface to 'JSON-stat' , + a simple lightweight 'JSON' format for data dissemination. + date_publication: '2018-08-17' + bug_reports: https://github.com/zedoul/jsonstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jsonstat + url_git: https://github.com/zedoul/jsonstat +jsonStrings: + version: 2.1.1 + title: Manipulation of JSON Strings + maintainer: Stéphane Laurent + description: |- + Fast manipulation of JSON strings. Allows to extract or + delete an element in a JSON string, merge two JSON strings, and more. + date_publication: '2022-11-18' + bug_reports: https://github.com/stla/jsonStrings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jsonStrings + url_git: https://github.com/stla/jsonStrings +jsonvalidate: + version: 1.5.0 + title: Validate 'JSON' Schema + maintainer: Rich FitzJohn + description: |- + Uses the node library 'is-my-json-valid' or 'ajv' to + validate 'JSON' against a 'JSON' schema. Drafts 04, 06 and 07 of + 'JSON' schema are supported. + date_publication: '2025-02-07' + bug_reports: https://github.com/ropensci/jsonvalidate/issues + url: https://docs.ropensci.org/jsonvalidate/ + url_cran: https://CRAN.R-project.org/package=jsonvalidate + url_git: https://github.com/ropensci/jsonvalidate +JSparO: + version: 1.5.0 + title: |- + Joint Sparse Optimization via Proximal Gradient Method for Cell + Fate Conversion + maintainer: Xinlin Hu + description: Implementation of joint sparse optimization (JSparO) to infer the gene + regulatory network for cell fate conversion. The proximal gradient method is implemented + to solve different low-order regularization models for JSparO. + date_publication: '2022-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JSparO + url_git: '' +jstable: + version: 1.3.8 + title: Create Tables from Different Types of Regression + maintainer: Jinseob Kim + description: Create regression tables from generalized linear model(GLM), generalized + estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional + hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted + Cox model results for publication. + date_publication: '2024-12-11' + bug_reports: https://github.com/jinseob2kim/jstable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jstable + url_git: https://github.com/jinseob2kim/jstable +jstager: + version: 0.0.6 + title: Retrieve Information Published on J-STAGE + maintainer: Takeshi Nishimura + description: |- + Provides tools to access the J-STAGE WebAPI and retrieve + information published on J-STAGE + . + date_publication: '2024-08-22' + bug_reports: https://github.com/takeshinishimura/jstager/issues + url: https://takeshinishimura.github.io/jstager/ + url_cran: https://CRAN.R-project.org/package=jstager + url_git: https://github.com/takeshinishimura/jstager +jstor: + version: 0.3.11 + title: Read Data from JSTOR/DfR + maintainer: Thomas Klebel + description: |- + Functions and helpers to import metadata, ngrams and full-texts + delivered by Data for Research by JSTOR. + date_publication: '2023-08-16' + bug_reports: https://github.com/ropensci/jstor/issues + url: https://docs.ropensci.org/jstor/ + url_cran: https://CRAN.R-project.org/package=jstor + url_git: https://github.com/ropensci/jstor +jsTree: + version: '1.2' + title: Create Interactive Trees with the 'jQuery' 'jsTree' Plugin + maintainer: Jonathan Sidi + description: |- + Create and customize interactive trees using the + 'jQuery' 'jsTree' plugin + library and the 'htmlwidgets' package. These trees can + be used directly from the R console, from 'RStudio', in + Shiny apps and R Markdown documents. + date_publication: '2020-12-13' + bug_reports: https://github.com/yonicd/jsTree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jsTree + url_git: https://github.com/yonicd/jsTree +jsTreeR: + version: 2.6.0 + title: A Wrapper of the JavaScript Library 'jsTree' + maintainer: Stéphane Laurent + description: |- + Creates interactive trees that can be included in 'Shiny' + apps and R markdown documents. A tree allows to represent hierarchical + data (e.g. the contents of a directory). Similar to the 'shinyTree' + package but offers more features and options, such as the grid + extension, restricting the drag-and-drop behavior, and settings for + the search functionality. It is possible to attach some data to the + nodes of a tree and then to get these data in 'Shiny' when a node is + selected. Also provides a 'Shiny' gadget allowing to manipulate one or + more folders, and a 'Shiny' module allowing to navigate in the server + side file system. + date_publication: '2024-04-26' + bug_reports: https://github.com/stla/jsTreeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=jsTreeR + url_git: https://github.com/stla/jsTreeR +JSUparameters: + version: 1.0.0 + title: Estimate Parameters of the Best-Fitting JohnsonSU Distribution + maintainer: C.J. Clarke + description: 'Uses least squares optimisation to estimate the parameters of the + best-fitting JohnsonSU distribution for a given dataset, with the possibility + of the distributions corresponding to the limiting cases of the JohnsonSU distribution. + The code for the Golden Section Search used in the optimisation has been adapted + from E. Cai. This package has been created as an extension of my Master''s thesis. + E. Cai (2013, "Scripts and Functions: Using R to Implement the Golden Section + Search Method for Numerical Optimization", ).' + date_publication: '2021-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JSUparameters + url_git: '' +jtdm: + version: 0.1-3 + title: Joint Modelling of Functional Traits + maintainer: Giovanni Poggiato + description: Fitting and analyzing a Joint Trait Distribution Model. The Joint Trait + Distribution Model is implemented in the Bayesian framework using conjugate priors + and posteriors, thus guaranteeing fast inference. In particular the package computes + joint probabilities and multivariate confidence intervals, and enables the investigation + of how they depend on the environment through partial response curves. The method + implemented by the package is described in Poggiato et al. (2023) . + date_publication: '2024-09-09' + bug_reports: https://github.com/giopogg/jtdm/issues + url: https://giopogg.github.io/jtdm/ + url_cran: https://CRAN.R-project.org/package=jtdm + url_git: https://github.com/giopogg/jtdm +jti: + version: 1.0.0 + title: Junction Tree Inference + maintainer: Mads Lindskou + description: |- + Minimal and memory efficient implementation of the junction tree + algorithm using the Lauritzen-Spiegelhalter scheme; + S. L. Lauritzen and D. J. Spiegelhalter (1988) + . The jti package is + part of the paper . + date_publication: '2024-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jti + url_git: https://github.com/mlindsk/jti +jtools: + version: 2.3.0 + title: Analysis and Presentation of Social Scientific Data + maintainer: Jacob A. Long + description: |- + This is a collection of tools for more efficiently understanding + and sharing the results of (primarily) regression analyses. There are also a + number of miscellaneous functions for statistical and programming purposes. + Support for models produced by the survey and lme4 packages are points of + emphasis. + date_publication: '2024-08-25' + bug_reports: https://github.com/jacob-long/jtools/issues + url: https://jtools.jacob-long.com + url_cran: https://CRAN.R-project.org/package=jtools + url_git: '' +jubilee: + version: 0.3.3 + title: |- + Forecasting Long-Term Growth of the U.S. Stock Market and + Business Cycles + maintainer: Stephen H-T. Lihn + description: A long-term forecast model called "Jubilee-Tectonic model" is implemented + to forecast future returns of the U.S. stock market, Treasury yield, and gold + price. The five-factor model forecasts the 10-year and 20-year future equity returns + with high R-squared above 80 percent. It is based on linear growth and mean reversion + characteristics in the U.S. stock market. This model also enhances the CAPE model + by introducing the hypothesis that there are fault lines in the historical CAPE, + which can be calibrated and corrected through statistical learning. In addition, + it contains a module for business cycles, optimal interest rate, and recession + forecasts. + date_publication: '2020-01-24' + bug_reports: '' + url: https://ssrn.com/abstract=3156574https://ssrn.com/abstract=3422278https://ssrn.com/abstract=3435667 + url_cran: https://CRAN.R-project.org/package=jubilee + url_git: '' +juicedown: + version: 0.1.1 + title: |- + 'juice' + 'markdown': Convert 'R Markdown' into 'HTML' with + Inline Styles + maintainer: Kenji Sato + description: |- + A convenience tool to create 'HTML' with inline styles using + 'juicyjuice' and 'markdown' packages. It is particularly useful when working + on a content management system (CMS) whose code editor eliminates style and + link tags. The main use case of the package is the learning management system, + 'Moodle'. Additional helper functions for teaching purposes are provided. Learn + more about 'juicedown' at . + date_publication: '2023-09-05' + bug_reports: '' + url: https://kenjisato.github.io/juicedown/ + url_cran: https://CRAN.R-project.org/package=juicedown + url_git: '' +juicr: + version: '0.1' + title: |- + Automated and Manual Extraction of Numerical Data from + Scientific Images + maintainer: Marc J. Lajeunesse + description: |- + Provides a GUI interface for automating data extraction from + multiple images containing scatter and bar plots, semi-automated tools to tinker + with extraction attempts, and a fully-loaded point-and-click manual extractor + with image zoom, calibrator, and classifier. Also provides detailed and + R-independent extraction reports as fully-embedded .html records. + date_publication: '2021-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=juicr + url_git: http://lajeunesse.myweb.usf.edu/https://github.com/mjlajeunesse/https://www.youtube.com/c/LajeunesseLab/ +juicyjuice: + version: 0.1.0 + title: Inline CSS Properties into HTML Tags Using 'juice' + maintainer: Richard Iannone + description: |- + There are occasions where you need a piece of HTML with integrated + styles. A prime example of this is HTML email. This transformation + involves moving the CSS and associated formatting instructions from the + style block in the head of your document into the body of the HTML. Many + prominent email clients require integrated styles in HTML email; otherwise a + received HTML email will be displayed without any styling. This package will + quickly and precisely perform these CSS transformations when given HTML text + and it does so by using the JavaScript 'juice' library. + date_publication: '2022-11-10' + bug_reports: https://github.com/rich-iannone/juicyjuice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=juicyjuice + url_git: https://github.com/rich-iannone/juicyjuice +Julia: + version: 1.3.5 + title: Fractal Image Data Generator + maintainer: Mehmet Suzen + description: Generates image data for fractals (Julia and Mandelbrot sets) on the + complex plane in the given region and resolution. Benoit B Mandelbrot (1982). + date_publication: '2023-08-27' + bug_reports: https://github.com/msuzen/Julia/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Julia + url_git: https://github.com/msuzen/Julia +JuliaCall: + version: 0.17.6 + title: Seamless Integration Between R and 'Julia' + maintainer: Changcheng Li + description: |- + Provides an R interface to 'Julia', + which is a high-level, high-performance dynamic programming language + for numerical computing, see for more information. + It provides a high-level interface as well as a low-level interface. + Using the high level interface, you could call any 'Julia' function just like + any R function with automatic type conversion. Using the low level interface, + you could deal with C-level SEXP directly while enjoying the convenience of + using a high-level programming language like 'Julia'. + date_publication: '2024-12-07' + bug_reports: https://github.com/JuliaInterop/JuliaCall/issues + url: '' + url_cran: https://CRAN.R-project.org/package=JuliaCall + url_git: https://github.com/JuliaInterop/JuliaCall +JuliaConnectoR: + version: 1.1.4 + title: A Functionally Oriented Interface for Integrating 'Julia' with R + maintainer: Stefan Lenz + description: |- + Allows to import functions and whole packages from 'Julia' in R. + Imported 'Julia' functions can directly be called as R functions. + Data structures can be translated between 'Julia' and R. + More details can also be found in the corresponding article + . + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JuliaConnectoR + url_git: '' +JuliaFormulae: + version: 0.1.0 + title: Translate R Regression Model Formulae to 'Julia' Syntax + maintainer: June Choe + description: |- + Metaprogramming utilities for converting R regression model + formulae to equivalents in 'Julia' , via + modifications to the abstract syntax tree. Supports translations in + zero correlation random effects syntax, protection of expressions to + be evaluated as-is, interaction terms, and more. Accepts strings or R + formula objects and returns modified R formula objects where + possible (or a modified string, if not a valid formula in R). + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JuliaFormulae + url_git: '' +JUMP: + version: 1.0.1 + title: Replicability Analysis of High-Throughput Experiments + maintainer: Yan Li + description: Implementing a computationally scalable false discovery rate control + procedure for replicability analysis based on maximum of p-values. Please cite + the manuscript corresponding to this package [Lyu, P. et al., (2023), ]. + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JUMP + url_git: '' +junctions: + version: 2.1.0 + title: The Breakdown of Genomic Ancestry Blocks in Hybrid Lineages + maintainer: Thijs Janzen + description: |- + Individual based simulations of hybridizing populations, + where the accumulation of junctions is tracked. Furthermore, + mathematical equations are provided to verify simulation outcomes. + Both simulations and mathematical equations are based on Janzen + (2018, ) and Janzen (2020, + ). + date_publication: '2024-02-13' + bug_reports: https://github.com/thijsjanzen/junctions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=junctions + url_git: https//github.com/thijsjanzen/junctions +just.install: + version: 1.0.2 + title: Very Simple Function to Install Packages without Attaching + maintainer: Carlos Yanez Santibanez + description: Install packages without attaching them. If a package it is already + installed, it will be skipped. + date_publication: '2022-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=just.install + url_git: '' +justifier: + version: 0.2.6 + title: |- + Human and Machine-Readable Justifications and Justified + Decisions Based on 'YAML' + maintainer: Gjalt-Jorn Peters + description: |- + Leverages the 'yum' package to + implement a 'YAML' ('YAML Ain't Markup Language', a human + friendly standard for data serialization; see ) + standard for documenting justifications, such as for decisions + taken during the planning, execution and analysis of a study + or during the development of a behavior change intervention + as illustrated by Marques & Peters (2019) + . These justifications are both + human- and machine-readable, facilitating efficient extraction + and organisation. + date_publication: '2023-03-05' + bug_reports: https://gitlab.com/r-packages/justifier/-/issues + url: https://r-packages.gitlab.io/justifier + url_cran: https://CRAN.R-project.org/package=justifier + url_git: '' +JustifyAlpha: + version: 0.1.1 + title: Justifying Alpha Levels for Hypothesis Tests + maintainer: Maximilian Maier + description: 'Functions to justify alpha levels for statistical hypothesis tests + by avoiding Lindley''s paradox, or by minimizing or balancing error rates. For + more information about the package please read the following: Maier & Lakens (2021) + ).' + date_publication: '2021-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=JustifyAlpha + url_git: '' +jvcoords: + version: 1.0.3 + title: Principal Component Analysis (PCA) and Whitening + maintainer: Jochen Voss + description: |2- + + Provides functions to standardize and whiten data, and to perform + Principal Component Analysis (PCA). The main advantage of this + package over alternatives like prcomp() is, that jvcoords makes it + easy to convert (additional) data between the original and the + transformed coordinates. The package also provides a class coords, + which can represent affine coordinate transformations. This class + forms the basis of the transformations provided by the package, but + can also be used independently. The implementation has been + optimized to be of comparable speed (and sometimes even faster) than + existing alternatives. + date_publication: '2021-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jvcoords + url_git: https://github.com/seehuhn/jvcoords +jvnVaR: + version: '1.0' + title: Value at Risk + maintainer: Hung Vu + description: 'Many method to compute, predict and back-test VaR. For more detail, + see the report: Value at Risk .' + date_publication: '2015-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=jvnVaR + url_git: '' +JWileymisc: + version: 1.4.1 + title: Miscellaneous Utilities and Functions + maintainer: Joshua F. Wiley + description: |- + Miscellaneous tools and functions, + including: generate descriptive statistics tables, + format output, visualize relations among variables or check + distributions, and generic functions for residual and + model diagnostics. + date_publication: '2023-10-05' + bug_reports: https://github.com/JWiley/JWileymisc/issues + url: https://joshuawiley.com/JWileymisc/ + url_cran: https://CRAN.R-project.org/package=JWileymisc + url_git: https://github.com/JWiley/JWileymisc +k5: + version: 0.2.1 + title: Kiernan Nicholls Miscellaneous + maintainer: Kiernan Nicholls + description: |- + Quality of life functions for interactive programming. + Shortcuts for common combinations of functions or different default + arguments. Not to be used in production level scripts, but useful for + exploring and quickly manipulating data for easy analysis. Also + imports a variety of packages to facilitate the installation of those + imported packages on the host machine. + date_publication: '2024-03-11' + bug_reports: https://github.com/k5cents/k5/issues + url: https://k5cents.github.io/k5/ + url_cran: https://CRAN.R-project.org/package=k5 + url_git: https://github.com/k5cents/k5 +kableExtra: + version: 1.4.0 + title: Construct Complex Table with 'kable' and Pipe Syntax + maintainer: Hao Zhu + description: |- + Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' + and the piping syntax from 'magrittr'. Function 'kable()' is a light weight + table generator coming from 'knitr'. This package simplifies the way to + manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows + users to construct complex tables and customize styles using a readable + syntax. + date_publication: '2024-01-24' + bug_reports: https://github.com/haozhu233/kableExtra/issues + url: http://haozhu233.github.io/kableExtra/ + url_cran: https://CRAN.R-project.org/package=kableExtra + url_git: https://github.com/haozhu233/kableExtra +kader: + version: 0.0.8 + title: Kernel Adaptive Density Estimation and Regression + maintainer: Gerrit Eichner + description: |- + Implementation of various kernel adaptive methods in nonparametric curve + estimation like density estimation as introduced in Stute and Srihera (2011) + and Eichner and Stute (2013) + for pointwise estimation, and like regression + as described in Eichner and Stute (2012) . + date_publication: '2017-10-04' + bug_reports: http://github.com/GerritEichner/kader/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kader + url_git: http://github.com/GerritEichner/kader +kaigiroku: + version: '0.5' + title: Programmatic Access to the API for Japanese Diet Proceedings + maintainer: Akitaka Matsuo + description: Search and download data from the API for Japanese Diet Proceedings + (see the reference at ). + date_publication: '2022-06-01' + bug_reports: https://github.com/amatsuo/kaigiroku/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kaigiroku + url_git: https://github.com/amatsuo/kaigiroku +kairos: + version: 2.2.0 + title: |- + Analysis of Chronological Patterns from Archaeological Count + Data + maintainer: Nicolas Frerebeau + description: |- + A toolkit for absolute and relative dating and analysis of + chronological patterns. This package includes functions for + chronological modeling and dating of archaeological assemblages from + count data. It provides methods for matrix seriation. It also allows + to compute time point estimates and density estimates of the + occupation and duration of an archaeological site. + date_publication: '2024-12-10' + bug_reports: https://github.com/tesselle/kairos/issues + url: https://packages.tesselle.org/kairos/ + url_cran: https://CRAN.R-project.org/package=kairos + url_git: https://github.com/tesselle/kairos +kalmanfilter: + version: 2.1.1 + title: Kalman Filter + maintainer: Alex Hubbard + description: |- + 'Rcpp' implementation of the multivariate Kalman filter for state space models that can handle missing values and exogenous data in the observation and state equations. There is also a function to handle time varying parameters. + Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" . + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kalmanfilter + url_git: '' +kamila: + version: 0.1.2 + title: Methods for Clustering Mixed-Type Data + maintainer: Alexander Foss + description: |- + Implements methods for clustering mixed-type data, + specifically combinations of continuous and nominal data. Special attention + is paid to the often-overlooked problem of equitably balancing the + contribution of the continuous and categorical variables. This package + implements KAMILA clustering, a novel method for clustering + mixed-type data in the spirit of k-means clustering. It does not require + dummy coding of variables, and is efficient enough to scale to rather large + data sets. Also implemented is Modha-Spangler clustering, which uses a + brute-force strategy to maximize the cluster separation simultaneously in the + continuous and categorical variables. For more information, see Foss, Markatou, + Ray, & Heching (2016) and Foss & Markatou + (2018) . + date_publication: '2020-03-13' + bug_reports: https://github.com/ahfoss/kamila/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kamila + url_git: https://github.com/ahfoss/kamila +kangar00: + version: 1.4.2 + title: Kernel Approaches for Nonlinear Genetic Association Regression + maintainer: Juliane Manitz + description: 'Methods to extract information on pathways, genes and various single-nucleotid + polymorphisms (SNPs) from online databases. It provides functions for data preparation + and evaluation of genetic influence on a binary outcome using the logistic kernel + machine test (LKMT). Three different kernel functions are offered to analyze genotype + information in this variance component test: A linear kernel, a size-adjusted + kernel and a network-based kernel).' + date_publication: '2024-05-09' + bug_reports: https://github.com/jmanitz/kangar00/issues + url: https://kangar00.manitz.org/ + url_cran: https://CRAN.R-project.org/package=kangar00 + url_git: '' +kanjistat: + version: 0.14.1 + title: |- + A Statistical Framework for the Analysis of Japanese Kanji + Characters + maintainer: Dominic Schuhmacher + description: Various tools and data sets that support the study of kanji, including + their morphology, decomposition and concepts of distance and similarity between + them. + date_publication: '2024-06-04' + bug_reports: https://github.com/dschuhmacher/kanjistat/issues + url: https://dschuhmacher.github.io/kanjistat/ + url_cran: https://CRAN.R-project.org/package=kanjistat + url_git: '' +kantorovich: + version: 3.2.0 + title: Kantorovich Distance Between Probability Measures + maintainer: Stéphane Laurent + description: |- + Computes the Kantorovich distance between two probability + measures on a finite set. The Kantorovich distance is also known as + the Monge-Kantorovich distance or the first Wasserstein distance. + date_publication: '2024-04-23' + bug_reports: https://github.com/stla/kantorovich/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kantorovich + url_git: https://github.com/stla/kantorovich +kaos: + version: 0.1.2 + title: |- + Encoding of Sequences Based on Frequency Matrix Chaos Game + Representation + maintainer: Hannah Franziska Löchel + description: |- + Sequences encoding by using the chaos game representation. + Löchel et al. (2019) . + date_publication: '2019-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kaos + url_git: '' +kaphom: + version: '0.3' + title: Test the Homogeneity of Kappa Statistics + maintainer: Muammer Albayrak + description: Tests the homogeneity of intraclass kappa statistics obtained from + independent studies or a stratified study with binary results. It is desired to + compare the kappa statistics obtained in multi-center studies or in a single stratified + study to give a common or summary kappa using all available information. If the + homogeneity test of these kappa statistics is not rejected, then it is possible + to make inferences over a single kappa statistic that summarizes all the studies. + Muammer Albayrak, Kemal Turhan, Yasemin Yavuz, Zeliha Aydin Kasap (2019) + Jun-mo Nam (2003) Jun-mo Nam (2005) Mousumi + Banerjee, Michelle Capozzoli, Laura McSweeney,Debajyoti Sinha (1999) + Allan Donner, Michael Eliasziw, Neil Klar (1996) . + date_publication: '2019-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kaphom + url_git: '' +kappaGold: + version: 0.4.0 + title: Agreement of Nominal Scale Raters (with a Gold Standard) + maintainer: Matthias Kuhn + description: |- + Estimate agreement of a group of raters with a gold standard rating + on a nominal scale. For a single gold standard rater the average pairwise + agreement of raters with this gold standard is provided. For a group of (gold + standard) raters the approach of S. Vanbelle, A. Albert (2009) + is implemented. Bias and standard error are + estimated via delete-1 jackknife. + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kappaGold + url_git: '' +KappaGUI: + version: 2.0.2 + title: An R-Shiny Application for Calculating Cohen's and Fleiss' Kappa + maintainer: Frédéric Santos + description: Offers a graphical user interface for the evaluation of inter-rater + agreement with Cohen's and Fleiss' Kappa. The calculation of kappa statistics + is done using the R package 'irr', so that 'KappaGUI' is essentially a Shiny front-end + for 'irr'. + date_publication: '2018-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KappaGUI + url_git: '' +kappalab: + version: 0.4-12 + title: Non-Additive Measure and Integral Manipulation Functions + maintainer: Ivan Kojadinovic + description: 'S4 tool box for capacity (or non-additive measure, fuzzy measure) + and integral manipulation in a finite setting. It contains routines for handling + various types of set functions such as games or capacities. It can be used to + compute several non-additive integrals: the Choquet integral, the Sugeno integral, + and the symmetric and asymmetric Choquet integrals. An analysis of capacities + in terms of decision behavior can be performed through the computation of various + indices such as the Shapley value, the interaction index, the orness degree, etc. + The well-known Möbius transform, as well as other equivalent representations of + set functions can also be computed. Kappalab further contains seven capacity identification + routines: three least squares based approaches, a method based on linear programming, + a maximum entropy like method based on variance minimization, a minimum distance + approach and an unsupervised approach based on parametric entropies. The functions + contained in Kappalab can for instance be used in the framework of multicriteria + decision making or cooperative game theory.' + date_publication: '2023-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kappalab + url_git: '' +kappaSize: + version: '1.2' + title: |- + Sample Size Estimation Functions for Studies of Interobserver + Agreement + maintainer: Michael A Rotondi + description: Contains basic tools for sample size estimation in studies of interobserver/interrater + agreement (reliability). Includes functions for both the power-based and confidence + interval-based methods, with binary or multinomial outcomes and two through six + raters. + date_publication: '2018-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kappaSize + url_git: '' +karaoke: + version: '2.0' + title: Remove Vocals from a Song + maintainer: John R. Dixon + description: Attempts to remove vocals from a stereo '.wav' recording of a song. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=karaoke + url_git: '' +karel: + version: 0.1.1 + title: Learning programming with Karel the robot + maintainer: Marcos Prunello + description: |- + This is the R implementation of Karel the robot, a programming + language created by Dr. R. E. Pattis at Stanford University in 1981. Karel is + an useful tool to teach introductory concepts about general programming, such + as algorithmic decomposition, conditional statements, loops, etc., in an + interactive and fun way, by writing programs to make Karel the robot achieve + certain tasks in the world she lives in. Originally based on Pascal, Karel + was implemented in many languages through these decades, including 'Java', 'C++', + 'Ruby' and 'Python'. This is the first package implementing Karel in R. + date_publication: '2022-03-26' + bug_reports: https://github.com/mpru/karel/issues/ + url: https://mpru.github.io/karel/ + url_cran: https://CRAN.R-project.org/package=karel + url_git: '' +Karen: + version: '1.0' + title: Kalman Reaction Networks + maintainer: Luca Del Core + description: |- + This is a stochastic framework that combines biochemical reaction networks with extended Kalman filter and Rauch-Tung-Striebel smoothing. + This framework allows to investigate the dynamics of cell differentiation from high-dimensional clonal tracking data subject to measurement noise, false negative errors, and systematically unobserved cell types. + Our tool can provide statistical support to biologists in gene therapy clonal tracking studies for a deeper understanding of clonal reconstitution dynamics. Further details on the methods can be found in L. Del Core et al., (2022) . + date_publication: '2022-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Karen + url_git: '' +karlen: + version: 0.0.2 + title: Real-Time PCR Data Sets by Karlen et al. (2007) + maintainer: Ramiro Magno + description: |- + Real-time quantitative polymerase chain reaction (qPCR) data + sets by Karlen et al. (2007) . Provides one + single tabular tidy data set in long format, encompassing 32 + dilution series, for seven PCR targets and four biological samples. The + targeted amplicons are within the murine genes: Cav1, Ccn2, Eln, Fn1, Rpl27, + Hspg2, and Serpine1, respectively. Dilution series: scheme 1 (Cav1, Eln, + Hspg2, Serpine1): 1-fold, 10-fold, 50-fold, and 100-fold; scheme 2 (Ccn2, + Rpl27, Fn1): 1-fold, 10-fold, 50-fold, 100-fold and 1000-fold. + For each concentration there are five replicates, except for the 1000-fold + concentration, where only two replicates were performed. Each amplification + curve is 40 cycles long. Original raw data file is Additional file 2 from + "Statistical significance of quantitative PCR" by Y. Karlen, A. McNair, + S. Perseguers, C. Mazza, and N. Mermod (2007) + . + date_publication: '2024-04-30' + bug_reports: https://github.com/ramiromagno/karlen/issues + url: https://rmagno.eu/karlen/ + url_cran: https://CRAN.R-project.org/package=karlen + url_git: https://github.com/ramiromagno/karlen +KarsTS: + version: 2.4.1 + title: An Interface for Microclimate Time Series Analysis + maintainer: Marina Saez + description: An R code with a GUI for microclimate time series, with an emphasis + on underground environments. 'KarsTS' provides linear and nonlinear methods, including + recurrence analysis (Marwan et al. (2007) ) + and filling methods (Moffat et al. (2007) ), + as well as tools to manipulate easily time series and gap sets. + date_publication: '2021-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KarsTS + url_git: '' +karyotapR: + version: 1.0.1 + title: DNA Copy Number Analysis for Genome-Wide Tapestri Panels + maintainer: Joseph Mays + description: |- + Analysis of DNA copy number in single cells using + custom genome-wide targeted DNA sequencing panels for the Mission Bio + Tapestri platform. Users can easily parse, manipulate, and visualize + datasets produced from the automated 'Tapestri Pipeline', with support for + normalization, clustering, and copy number calling. Functions are also + available to deconvolute multiplexed samples by genotype and parsing + barcoded reads from exogenous lentiviral constructs. + date_publication: '2023-09-07' + bug_reports: https://github.com/joeymays/karyotapR/issues + url: http://joeymays.xyz/karyotapR/ + url_cran: https://CRAN.R-project.org/package=karyotapR + url_git: https://github.com/joeymays/karyotapR +katex: + version: 1.5.0 + title: Rendering Math to HTML, 'MathML', or R-Documentation Format + maintainer: Jeroen Ooms + description: |- + Convert latex math expressions to HTML and 'MathML' for use in + markdown documents or package manual pages. The rendering is done in + R using the V8 engine (i.e. server-side), which eliminates the need + for embedding the 'MathJax' library into your web pages. In addition + a 'math-to-rd' wrapper is provided to automatically render beautiful + math in R documentation files. + date_publication: '2024-09-29' + bug_reports: https://github.com/ropensci/katex/issues + url: https://docs.ropensci.org/katex/ + url_cran: https://CRAN.R-project.org/package=katex + url_git: https://github.com/ropensci/katexhttps://katex.org/docs/options.html(upstream) +kayadata: + version: 1.4.0 + title: Kaya Identity Data for Nations and Regions + maintainer: Jonathan Gilligan + description: |- + Provides data for Kaya identity variables (population, gross + domestic product, primary energy consumption, and energy-related + CO2 emissions) for the world and for individual nations, and + utility functions for looking up data, plotting trends of + Kaya variables, and plotting the fuel mix for a given country + or region. The Kaya identity (Yoichi Kaya and Keiichi Yokobori, + "Environment, Energy, and Economy: Strategies for Sustainability" + (United Nations University Press, 1998) and + ) expresses a nation's + or region's greenhouse gas emissions in terms of its population, + per-capita Gross Domestic Product, the energy intensity of its + economy, and the carbon-intensity of its energy supply. + date_publication: '2024-07-12' + bug_reports: https://github.com/jonathan-g/kayadata/issues + url: https://jonathan-g.github.io/kayadata/ + url_cran: https://CRAN.R-project.org/package=kayadata + url_git: https://github.com/jonathan-g/kayadata +kazaam: + version: 0.1-0 + title: Tools for Tall Distributed Matrices + maintainer: Drew Schmidt + description: |- + Many data science problems reduce to operations on very tall, + skinny matrices. However, sometimes these matrices can be so tall that they + are difficult to work with, or do not even fit into main memory. One + strategy to deal with such objects is to distribute their rows across + several processors. To this end, we offer an 'S4' class for tall, skinny, + distributed matrices, called the 'shaq'. We also provide many useful + numerical methods and statistics operations for operating on these + distributed objects. The naming is a bit "tongue-in-cheek", with the class + a play on the fact that 'Shaquille' 'ONeal' ('Shaq') is very tall, and he + starred in the film 'Kazaam'. + date_publication: '2017-06-29' + bug_reports: http://group.r-pbd.org/ + url: http://r-pbd.org/ + url_cran: https://CRAN.R-project.org/package=kazaam + url_git: '' +KbMvtSkew: + version: 1.0.2 + title: Khattree-Bahuguna's Univariate and Multivariate Skewness + maintainer: Zhixin Lun + description: 'Computes Khattree-Bahuguna''s univariate and multivariate skewness, + principal-component-based Khattree-Bahuguna''s multivariate skewness. It also + provides several measures of univariate or multivariate skewnesses including, + Pearson’s coefficient of skewness, Bowley’s univariate skewness and Mardia''s + multivariate skewness. See Khattree, R. and Bahuguna, M. (2019) .' + date_publication: '2020-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KbMvtSkew + url_git: '' +kcmeans: + version: 0.1.0 + title: |- + Conditional Expectation Function Estimation with + K-Conditional-Means + maintainer: Thomas Wiemann + description: |- + Implementation of the KCMeans regression estimator studied by + Wiemann (2023) for expectation function estimation conditional on + categorical variables. Computation leverages the unconditional KMeans + implementation in one dimension using dynamic programming algorithm of + Wang and Song (2011) , allowing for global solutions in time polynomial in + the number of observed categories. + date_publication: '2023-11-30' + bug_reports: https://github.com/thomaswiemann/kcmeans/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kcmeans + url_git: https://github.com/thomaswiemann/kcmeans +Kcop: + version: 1.0.0 + title: Smooth Test for Equality of Copulas and Clustering Multivariate + maintainer: Yves Ismael Ngounou Bakam + description: |- + Implements approaches of non-parametric smooth test to + compare simultaneously K(K>1) copulas and non-parametric clustering + of multivariate populations with arbitrary sizes. + See Yves I. Ngounou Bakam and Denys Pommeret (2022) and + Yves I. Ngounou Bakam and Denys Pommeret (2022) . + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kcop + url_git: '' +kcpRS: + version: 1.1.1 + title: Kernel Change Point Detection on the Running Statistics + maintainer: Kristof Meers + description: The running statistics of interest is first extracted using a time + window which is slid across the time series, and in each window, the running statistics + value is computed. KCP (Kernel Change Point) detection proposed by Arlot et al. + (2012) is then implemented to flag the change points on the + running statistics (Cabrieto et al., 2018, ). Change + points are located by minimizing a variance criterion based on the pairwise similarities + between running statistics which are computed via the Gaussian kernel. KCP can + locate change points for a given k number of change points. To determine the optimal + k, the KCP permutation test is first carried out by comparing the variance of + the running statistics extracted from the original data to that of permuted data. + If this test is significant, then there is sufficient evidence for at least one + change point in the data. Model selection is then used to determine the optimal + k>0. + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kcpRS + url_git: '' +KCSKNNShiny: + version: 0.1.0 + title: K-Nearest Neighbour Classifier + maintainer: Karne Chaithanya Sai + description: |- + It predicts any attribute (categorical) given a set of input numeric predictor values. Note that only numeric input predictors should be given. + The k value can be chosen according to accuracies provided. The attribute to be predicted can be selected from the dropdown provided (select categorical attribute). + This is because categorical attributes cannot be given as inputs here. A 'handsontable' is also provided to enter the input predictor values. + date_publication: '2019-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KCSKNNShiny + url_git: '' +KCSNBShiny: + version: 0.1.0 + title: Naive Bayes Classifier + maintainer: Karne Chaithanya Sai + description: |- + Predicts any variable in any categorical dataset for given values of predictor variables. + If a dataset contains 4 variables, then any variable can be predicted based on the values of the other three variables given by the user. + The user can upload their own datasets and select what variable they want to predict. + A 'handsontable' is provided to enter the predictor values and also accuracy of the prediction is also shown. + date_publication: '2019-07-01' + bug_reports: '' + url: https://karnechaithanyasai.shinyapps.io/KCSNBShiny/ + url_cran: https://CRAN.R-project.org/package=KCSNBShiny + url_git: '' +kde1d: + version: 1.1.0 + title: Univariate Kernel Density Estimation + maintainer: Thomas Nagler + description: |- + Provides an efficient implementation of univariate local polynomial + kernel density estimators that can handle bounded and discrete data. See + Geenens (2014) , + Geenens and Wang (2018) , + Nagler (2018a) , + Nagler (2018b) . + date_publication: '2025-01-08' + bug_reports: https://github.com/tnagler/kde1d/issues/ + url: https://tnagler.github.io/kde1d/ + url_cran: https://CRAN.R-project.org/package=kde1d + url_git: '' +kdecopula: + version: 0.9.2 + title: Kernel Smoothing for Bivariate Copula Densities + maintainer: Thomas Nagler + description: |- + Provides fast implementations of kernel smoothing techniques for + bivariate copula densities, in particular density estimation and resampling, + see Nagler (2018) . + date_publication: '2018-04-09' + bug_reports: https://github.com/tnagler/kdecopula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kdecopula + url_git: https://github.com/tnagler/kdecopula +kdensity: + version: 1.1.0 + title: |- + Kernel Density Estimation with Parametric Starts and Asymmetric + Kernels + maintainer: Jonas Moss + description: |- + Handles univariate non-parametric density estimation with + parametric starts and asymmetric kernels in a simple and flexible way. + Kernel density estimation with parametric starts involves fitting a + parametric density to the data before making a correction with kernel + density estimation, see Hjort & Glad (1995) . + Asymmetric kernels make kernel density estimation more efficient on bounded + intervals such as (0, 1) and the positive half-line. Supported asymmetric + kernels are the gamma kernel of Chen (2000) , + the beta kernel of Chen (1999) , and the + copula kernel of Jones & Henderson (2007) . + User-supplied kernels, parametric starts, and bandwidths are supported. + date_publication: '2020-09-30' + bug_reports: https://github.com/JonasMoss/kdensity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kdensity + url_git: https://github.com/JonasMoss/kdensity +kdevine: + version: 0.4.5 + title: Multivariate Kernel Density Estimation with Vine Copulas + maintainer: Thomas Nagler + description: |- + Implements the vine copula based kernel density estimator of + Nagler and Czado (2016) . The estimator does + not suffer from the curse of dimensionality and is therefore well suited for + high-dimensional applications. + date_publication: '2024-06-13' + bug_reports: https://github.com/tnagler/kdevine/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kdevine + url_git: https://github.com/tnagler/kdevine +kDGLM: + version: 1.2.0 + title: Bayesian Analysis of Dynamic Generalized Linear Models + maintainer: Silvaneo Vieira dos Santos Junior + description: Provide routines for filtering and smoothing, forecasting, sampling + and Bayesian analysis of Dynamic Generalized Linear Models using the methodology + described in Alves et al. (2024) and dos Santos + Jr. et al. (2024). + date_publication: '2024-05-25' + bug_reports: https://github.com/silvaneojunior/kDGLM/issues + url: https://silvaneojunior.github.io/kDGLM/ + url_cran: https://CRAN.R-project.org/package=kDGLM + url_git: '' +kdist: + version: '0.2' + title: K-Distribution and Weibull Paper + maintainer: Tim Lamont-Smith + description: |- + Density, distribution function, quantile function and random generation + for the K-distribution. A plotting function that plots data on Weibull + paper and another function to draw additional lines. See results from package in T Lamont-Smith (2018), submitted J. R. Stat. Soc. + date_publication: '2018-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kdist + url_git: '' +kdml: + version: 1.1.1 + title: Kernel Distance Metric Learning for Mixed-Type Data + maintainer: John R. J. Thompson + description: Distance metrics for mixed-type data consisting of continuous, nominal, + and ordinal variables. This methodology uses additive and product kernels to calculate + similarity functions and metrics, and selects variables relevant to the underlying + distance through bandwidth selection via maximum similarity cross-validation. + These methods can be used in any distance-based algorithm, such as distance-based + clustering. For further details, we refer the reader to Ghashti and Thompson (2024) + for dkps() methodology, and Ghashti (2024) + for dkss() methodology. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kdml + url_git: '' +kdry: + version: 0.0.2 + title: K's "Don't Repeat Yourself"-Collection + maintainer: Lorenz A. Kapsner + description: |- + A collection of personal helper functions to avoid redundancy + in the spirit of the "Don't repeat yourself" principle of software + development (). + date_publication: '2024-03-08' + bug_reports: https://github.com/kapsner/kdry/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kdry + url_git: https://github.com/kapsner/kdry +kedd: + version: 1.0.4 + title: |- + Kernel Estimator and Bandwidth Selection for Density and Its + Derivatives + maintainer: Iago Giné-Vázquez + description: Smoothing techniques and computing bandwidth selectors of the nth derivative + of a probability density for one-dimensional data (described in Arsalane Chouaib + Guidoum (2020) [stat.CO]). + date_publication: '2024-02-01' + bug_reports: https://gitlab.com/iagogv/kedd/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kedd + url_git: https://gitlab.com/iagogv/kedd +keep: + version: '1.0' + title: Arrays with Better Control over Dimension Dropping + maintainer: Paavo Jumppanen + description: Provides arrays with flexible control over dimension dropping when + subscripting. + date_publication: '2015-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=keep + url_git: '' +kehra: + version: '0.1' + title: |- + Collect, Assemble and Model Air Pollution, Weather and Health + Data + maintainer: Claudia Vitolo + description: Collection of utility functions used in the KEHRA project (see http://www.brunel.ac.uk/ife/britishcouncil). + It refers to the multidimensional analysis of air pollution, weather and health + data. + date_publication: '2016-06-10' + bug_reports: https://github.com/kehraProject/r_kehra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kehra + url_git: https://github.com/kehraProject/r_kehra +kelvin: + version: 2.0-2 + title: |- + Calculate Solutions to the Kelvin Differential Equation using + Bessel Functions + maintainer: Andrew J Barbour + description: |- + Uses Bessel functions to calculate the + fundamental and complementary analytic solutions to the + Kelvin differential equation. + date_publication: '2020-06-18' + bug_reports: https://github.com/abarbour/kelvin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kelvin + url_git: https://github.com/abarbour/kelvin +Kendall: + version: 2.2.1 + title: Kendall Rank Correlation and Mann-Kendall Trend Test + maintainer: A.I. McLeod + description: |- + Computes the Kendall rank correlation and Mann-Kendall + trend test. See documentation for use of block bootstrap when + there is autocorrelation. + date_publication: '2022-03-20' + bug_reports: '' + url: http://www.stats.uwo.ca/faculty/aim + url_cran: https://CRAN.R-project.org/package=Kendall + url_git: '' +kendallknight: + version: 0.6.0 + title: |- + Efficient Implementation of Kendall's Correlation Coefficient + Computation + maintainer: Mauricio Vargas Sepulveda + description: |- + The computational complexity of the implemented algorithm for + Kendall's correlation is O(n log(n)), which is faster than the base R + implementation with a computational complexity of O(n^2). For small vectors + (i.e., less than 100 observations), the time difference is negligible. + However, for larger vectors, the speed difference can be substantial and the + numerical difference is minimal. The references are + Knight (1966) , + Abrevaya (1999) , + Christensen (2005) and + Emara (2024) . + This implementation is described in + Vargas Sepulveda (2024) . + date_publication: '2025-02-20' + bug_reports: https://github.com/pachadotdev/kendallknight/issues + url: https://pacha.dev/kendallknight/ + url_cran: https://CRAN.R-project.org/package=kendallknight + url_git: https://github.com/pachadotdev/kendallknight +kendallRandomWalks: + version: 0.9.4 + title: |- + Simulate and Visualize Kendall Random Walks and Related + Distributions + maintainer: Mateusz Staniak + description: |- + Kendall random walks are a continuous-space Markov chains generated + by the Kendall generalized convolution. This package provides tools + for simulating these random walks and studying distributions + related to them. For more information about Kendall random walks see Jasiulis-Gołdyn (2014) . + date_publication: '2018-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kendallRandomWalks + url_git: '' +Keng: + version: 2024.12.15 + title: Knock Errors Off Nice Guesses + maintainer: Qingyao Zhang + description: |- + Miscellaneous functions and data used in psychological research and teaching. Keng + currently has a built-in dataset depress, and could (1) scale a vector; (2) compute the cut-off + values of Pearson's r with known sample size; (3) test the significance and compute the post-hoc + power for Pearson's r with known sample size; (4) conduct prior power analysis and plan the + sample size for Pearson's r; (5) compare lm()'s fitted outputs using R-squared, f_squared, + post-hoc power, and PRE (Proportional Reduction in Error, also called partial R-squared or + partial Eta-squared); (6) calculate PRE from partial correlation, Cohen's f, or f_squared; + (7) conduct prior power analysis and plan the sample size for one or a set of predictors in + regression analysis; (8) conduct post-hoc power analysis for one or a set of predictors in + regression analysis with known sample size. + date_publication: '2024-12-15' + bug_reports: https://github.com/qyaozh/Keng/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Keng + url_git: https://github.com/qyaozh/Keng +KenSyn: + version: '0.3' + title: |- + Knowledge Synthesis in Agriculture - From Experimental Network + to Meta-Analysis + maintainer: Francois Brun (ACTA) + description: |- + Demo and dataset accompaying the books : + De l'analyse des réseaux expérimentaux à la méta-analyse: Méthodes et applications avec le logiciel R pour les sciences agronomiques et environnementales (Published 2018-06-28, Quae, for french version) by David Makowski, Francois Piraux and Francois Brun - + Knowledge Synthesis in Agriculture : from Experimental Network to Meta-Analysis (in preparation for 2018-06, Springer , for English version) by David Makowski, Francois Piraux and Francois Brun + A full description of all the material is in both books. + ACKNOWLEDGMENTS : The French network "RMT modeling and data analysis for agriculture" () have contributed to the development of this R package. This project and network are lead by ACTA (French Technical Institute for Agriculture) and was funded by a grant from the Ministry of Agriculture and Fishing of France. + date_publication: '2019-04-08' + bug_reports: '' + url: http://www.modelia.org + url_cran: https://CRAN.R-project.org/package=KenSyn + url_git: '' +KEPTED: + version: 0.2.0 + title: Kernel-Embedding-of-Probability Test for Elliptical Distribution + maintainer: Yin Tang + description: Provides an implementation of a kernel-embedding of probability test + for elliptical distribution. This is an asymptotic test for elliptical distribution + under general alternatives, and the location and shape parameters are assumed + to be unknown. Some side-products are posted, including the transformation between + rectangular and polar coordinates and two product-type kernel functions. See Tang + and Li (2024) for details. + date_publication: '2024-04-13' + bug_reports: https://github.com/tyy20/KEPTED/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KEPTED + url_git: https://github.com/tyy20/KEPTED +kequate: + version: 1.6.4 + title: The Kernel Method of Test Equating + maintainer: Björn Andersson + description: Implements the kernel method of test equating as defined in von Davier, + A. A., Holland, P. W. and Thayer, D. T. (2004) and Andersson, + B. and Wiberg, M. (2017) using the CB, EG, SG, + NEAT CE/PSE and NEC designs, supporting Gaussian, logistic and uniform kernels + and unsmoothed and pre-smoothed input data. + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kequate + url_git: '' +keras: + version: 2.15.0 + title: R Interface to 'Keras' + maintainer: Tomasz Kalinowski + description: |- + Interface to 'Keras' , a high-level neural + networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, + supports both convolution based networks and recurrent networks (as well as + combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices. + date_publication: '2024-04-20' + bug_reports: https://github.com/rstudio/keras/issues + url: https://tensorflow.rstudio.com/ + url_cran: https://CRAN.R-project.org/package=keras + url_git: https://github.com/rstudio/keras/tree/r2 +keras3: + version: 1.2.0 + title: R Interface to 'Keras' + maintainer: Tomasz Kalinowski + description: |- + Interface to 'Keras' , a high-level neural + networks API. 'Keras' was developed with a focus on enabling fast experimentation, + supports both convolution based networks and recurrent networks (as well as + combinations of the two), and runs seamlessly on both CPU and GPU devices. + date_publication: '2024-09-05' + bug_reports: https://github.com/rstudio/keras3/issues + url: https://keras3.posit.co/ + url_cran: https://CRAN.R-project.org/package=keras3 + url_git: https://github.com/rstudio/keras3 +kerastuneR: + version: 0.1.0.7 + title: Interface to 'Keras Tuner' + maintainer: Turgut Abdullayev + description: |- + 'Keras Tuner' is a hypertuning framework made for humans. + It aims at making the life of AI practitioners, hypertuner + algorithm creators and model designers as simple as possible by + providing them with a clean and easy to use API for hypertuning. + 'Keras Tuner' makes moving from a base model to a hypertuned one quick and + easy by only requiring you to change a few lines of code. + date_publication: '2024-04-13' + bug_reports: https://github.com/EagerAI/kerastuneR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=kerastuneR + url_git: https://github.com/EagerAI/kerastuneR/ +kerDAA: + version: 0.1.1 + title: New Kernel-Based Test for Differential Association Analysis + maintainer: Hoseung Song + description: |- + A new practical method to evaluate whether relationships between two sets of high-dimensional variables are different or not across two conditions. + Song, H. and Wu, M.C. (2023) + . + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kerDAA + url_git: '' +KERE: + version: 1.0.0 + title: Expectile Regression in Reproducing Kernel Hilbert Space + maintainer: Yi Yang + description: An efficient algorithm inspired by majorization-minimization principle + for solving the entire solution path of a flexible nonparametric expectile regression + estimator constructed in a reproducing kernel Hilbert space. + date_publication: '2015-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KERE + url_git: '' +kergp: + version: 0.5.8 + title: Gaussian Process Laboratory + maintainer: Olivier Roustant + description: |- + Gaussian process regression with an emphasis on kernels. + Quantitative and qualitative inputs are accepted. Some pre-defined + kernels are available, such as radial or tensor-sum for + quantitative inputs, and compound symmetry, low rank, group kernel + for qualitative inputs. The user can define new kernels and + composite kernels through a formula mechanism. Useful methods + include parameter estimation by maximum likelihood, simulation, + prediction and leave-one-out validation. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kergp + url_git: '' +kerndwd: + version: 2.0.3 + title: Distance Weighted Discrimination (DWD) and Kernel Methods + maintainer: Boxiang Wang + description: 'A novel implementation that solves the linear distance weighted discrimination + and the kernel distance weighted discrimination. Reference: Wang and Zou (2018) + .' + date_publication: '2020-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kerndwd + url_git: '' +kernelboot: + version: 0.1.10 + title: Smoothed Bootstrap and Random Generation from Kernel Densities + maintainer: Tymoteusz Wolodzko + description: |- + Smoothed bootstrap and functions for random generation from + univariate and multivariate kernel densities. It does not + estimate kernel densities. + date_publication: '2023-04-14' + bug_reports: https://github.com/twolodzko/kernelboot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kernelboot + url_git: https://github.com/twolodzko/kernelboot +kernelFactory: + version: 0.3.0 + title: 'Kernel Factory: An Ensemble of Kernel Machines' + maintainer: Michel Ballings + description: 'Binary classification based on an ensemble of kernel machines ("Ballings, + M. and Van den Poel, D. (2013), Kernel Factory: An Ensemble of Kernel Machines. + Expert Systems With Applications, 40(8), 2904-2913"). Kernel factory is an ensemble + method where each base classifier (random forest) is fit on the kernel matrix + of a subset of the training data.' + date_publication: '2015-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kernelFactory + url_git: '' +Kernelheaping: + version: 2.3.0 + title: Kernel Density Estimation for Heaped and Rounded Data + maintainer: Marcus Gross + description: |- + In self-reported or anonymised data the user often encounters + heaped data, i.e. data which are rounded (to a possibly different degree + of coarseness). While this is mostly a minor problem in parametric density + estimation the bias can be very large for non-parametric methods such as kernel + density estimation. This package implements a partly Bayesian algorithm treating + the true unknown values as additional parameters and estimates the rounding + parameters to give a corrected kernel density estimate. It supports various + standard bandwidth selection methods. Varying rounding probabilities (depending + on the true value) and asymmetric rounding is estimable as well: Gross, M. and Rendtel, U. (2016) (). + Additionally, bivariate non-parametric density estimation for rounded data, Gross, M. et al. (2016) (), + as well as data aggregated on areas is supported. + date_publication: '2022-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kernelheaping + url_git: '' +KernelKnn: + version: 1.1.5 + title: Kernel k Nearest Neighbors + maintainer: Lampros Mouselimis + description: Extends the simple k-nearest neighbors algorithm by incorporating numerous + kernel functions and a variety of distance metrics. The package takes advantage + of 'RcppArmadillo' to speed up the calculation of distances between observations. + date_publication: '2023-01-06' + bug_reports: https://github.com/mlampros/KernelKnn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KernelKnn + url_git: https://github.com/mlampros/KernelKnn +kernelshap: + version: 0.7.0 + title: Kernel SHAP + maintainer: Michael Mayer + description: |- + Efficient implementation of Kernel SHAP, see Lundberg and Lee + (2017), and Covert and Lee (2021) + . Furthermore, for up to + 14 features, exact permutation SHAP values can be calculated. The + package plays well together with meta-learning packages like + 'tidymodels', 'caret' or 'mlr3'. Visualizations can be done using the + R package 'shapviz'. + date_publication: '2024-08-17' + bug_reports: https://github.com/ModelOriented/kernelshap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kernelshap + url_git: https://github.com/ModelOriented/kernelshap +kernhaz: + version: 0.1.0 + title: Kernel Estimation of Hazard Function in Survival Analysis + maintainer: Iveta Selingerova + description: |- + Producing kernel estimates of the unconditional and conditional hazard + function for right-censored data including methods of bandwidth selection. + date_publication: '2018-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kernhaz + url_git: '' +kernlab: + version: 0.9-33 + title: Kernel-Based Machine Learning Lab + maintainer: Alexandros Karatzoglou + description: |- + Kernel-based machine learning methods for classification, + regression, clustering, novelty detection, quantile regression + and dimensionality reduction. Among other methods 'kernlab' + includes Support Vector Machines, Spectral Clustering, Kernel + PCA, Gaussian Processes and a QP solver. + date_publication: '2024-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kernlab + url_git: '' +kernplus: + version: 0.1.2 + title: |- + A Kernel Regression-Based Multidimensional Wind Turbine Power + Curve + maintainer: Hoon Hwangbo + description: |- + Provides wind energy practitioners with an effective machine learning-based + tool that estimates a multivariate power curve and predicts the wind power output + for a specific environmental condition. + date_publication: '2019-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kernplus + url_git: '' +kernscr: + version: 1.0.6 + title: Kernel Machine Score Test for Semi-Competing Risks + maintainer: Boris P Hejblum + description: |- + Kernel Machine Score Test for Pathway Analysis in the Presence of + Semi-Competing Risks. Method is detailed in: Neykov, Hejblum & Sinnott (2018) + . + date_publication: '2023-04-17' + bug_reports: https://github.com/borishejblum/kernscr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kernscr + url_git: '' +KernSmooth: + version: 2.23-26 + title: Functions for Kernel Smoothing Supporting Wand & Jones (1995) + maintainer: Brian Ripley + description: |- + Functions for kernel smoothing (and density estimation) + corresponding to the book: + Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing". + date_publication: '2025-01-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KernSmooth + url_git: '' +KernSmoothIRT: + version: '6.4' + title: Nonparametric Item Response Theory + maintainer: Brian McGuire + description: Fits nonparametric item and option characteristic curves using kernel + smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation + and a variety of exploratory plotting tools. The kernel smoothing is based on + methods described in Silverman, B.W. (1986). Density Estimation for Statistics + and Data Analysis. Chapman & Hall, London. + date_publication: '2020-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KernSmoothIRT + url_git: '' +kernstadapt: + version: 0.4.0 + title: |- + Adaptive Kernel Estimators for Point Process Intensities on + Linear Networks + maintainer: Jonatan A González + description: Adaptive estimation of the first-order intensity function of a spatio-temporal + point process using kernels and variable bandwidths. The methodology used for + estimation is presented in González and Moraga (2022). . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kernstadapt + url_git: '' +kerntools: + version: 1.2.0 + title: Kernel Functions and Tools for Machine Learning Applications + maintainer: Elies Ramon + description: |- + Kernel functions for diverse types of data (including, but not + restricted to: nonnegative and real vectors, real matrices, categorical + and ordinal variables, sets, strings), plus other utilities like kernel + similarity, kernel Principal Components Analysis (PCA) and features' + importance for Support Vector Machines (SVMs), which expand other 'R' + packages like 'kernlab'. + date_publication: '2025-02-19' + bug_reports: https://github.com/elies-ramon/kerntools/issues + url: https://elies-ramon.github.io/kerntools/ + url_cran: https://CRAN.R-project.org/package=kerntools + url_git: https://github.com/elies-ramon/kerntools +kerSeg: + version: '1.1' + title: New Kernel-Based Change-Point Detection + maintainer: Hoseung Song + description: |- + New kernel-based test and fast tests for detecting change-points or changed-intervals where the distributions abruptly change. They work well particularly for high-dimensional data. + Song, H. and Chen, H. (2022) + . + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kerSeg + url_git: '' +kerTests: + version: 0.1.4 + title: Generalized Kernel Two-Sample Tests + maintainer: Hoseung Song + description: |- + New kernel-based test and fast tests for testing whether two samples are from the same distribution. They work well particularly for high-dimensional data. + Song, H. and Chen, H. (2023) + . + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kerTests + url_git: '' +kesernetwork: + version: 0.1.0 + title: Visualization of the KESER Network + maintainer: Su-Chun Cheng + description: A shiny app to visualize the knowledge networks for the code concepts. + Using co-occurrence matrices of EHR codes from Veterans Affairs (VA) and Massachusetts + General Brigham (MGB), the knowledge extraction via sparse embedding regression + (KESER) algorithm was used to construct knowledge networks for the code concepts. + Background and details about the method can be found at Chuan et al. (2021) . + date_publication: '2022-03-03' + bug_reports: https://github.com/celehs/kesernetwork/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kesernetwork + url_git: https://github.com/celehs/kesernetwork +keyATM: + version: 0.5.2 + title: Keyword Assisted Topic Models + maintainer: Shusei Eshima + description: Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. + The keyATM combines the latent dirichlet allocation (LDA) models with a small + number of keywords selected by researchers in order to improve the interpretability + and topic classification of the LDA. The keyATM can also incorporate covariates + and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki + (2024) . + date_publication: '2024-04-24' + bug_reports: https://github.com/keyATM/keyATM/issues + url: https://keyatm.github.io/keyATM/ + url_cran: https://CRAN.R-project.org/package=keyATM + url_git: '' +Keyboard: + version: 0.1.3 + title: Bayesian Designs for Early Phase Clinical Trials + maintainer: Xiaomeng Yuan + description: We developed a package 'Keyboard' for designing single-agent, drug-combination, + or phase I/II dose-finding clinical trials. The 'Keyboard' designs are novel early + phase trial designs that can be implemented simply and transparently, similar + to the 3+3 design, but yield excellent performance, comparable to those of more-complicated, + model-based designs (Yan F, Mandrekar SJ, Yuan Y (2017) , + Li DH, Whitmore JB, Guo W, Ji Y. (2017) , Liu + S, Johnson VE (2016) , Zhou Y, Lee JJ, Yuan + Y (2019) , Pan H, Lin R, Yuan Y (2020) ). + The 'Keyboard' package provides tools for designing, conducting, and analyzing + single-agent, drug-combination, and phase I/II dose-finding clinical trials. For + more details about how to use this packge, please refer to Li C, Sun H, Cheng + C, Tang L, and Pan H. (2022) "A software tool for both the maximum tolerated dose + and the optimal biological dose finding trials in early phase designs". Manuscript + submitted for publication. + date_publication: '2022-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Keyboard + url_git: '' +keyholder: + version: 0.1.7 + title: Store Data About Rows + maintainer: Evgeni Chasnovski + description: |- + Tools for keeping track of information, named + "keys", about rows of data frame like objects. This is done by + creating special attribute "keys" which is updated after every change + in rows (subsetting, ordering, etc.). This package is designed to + work tightly with 'dplyr' package. + date_publication: '2023-03-11' + bug_reports: https://github.com/echasnovski/keyholder/issues/ + url: https://echasnovski.github.io/keyholder/ + url_cran: https://CRAN.R-project.org/package=keyholder + url_git: https://github.com/echasnovski/keyholder/ +keyperm: + version: 0.1.1 + title: Keyword Analysis Using Permutation Tests + maintainer: Thoralf Mildenberger + description: Efficient implementation of permutation tests for keyword analysis + in corpus linguistics as described in Mildenberger (2023) . + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=keyperm + url_git: '' +keyplayer: + version: 1.0.4 + title: Locating Key Players in Social Networks + maintainer: Weihua An + description: Computes group centrality scores and identifies the most central group + of players in a network. + date_publication: '2023-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=keyplayer + url_git: '' +keypress: + version: 1.3.1 + title: Wait for a Key Press in a Terminal + maintainer: Gábor Csárdi + description: |- + Wait for a single key press at the 'R' prompt. + This works in terminals, but does not currently work + in the 'Windows' 'GUI', the 'OS X' 'GUI' ('R.app'), + in 'Emacs' 'ESS', in an 'Emacs' shell buffer or in + 'R Studio'. In these cases 'keypress' stops with an + error message. + date_publication: '2023-12-11' + bug_reports: https://github.com/gaborcsardi/keypress/issues + url: '' + url_cran: https://CRAN.R-project.org/package=keypress + url_git: https://github.com/gaborcsardi/keypress#readme +keyring: + version: 1.3.2 + title: Access the System Credential Store from R + maintainer: Gábor Csárdi + description: |- + Platform independent 'API' to access the operating system's + credential store. Currently supports: 'Keychain' on 'macOS', + Credential Store on 'Windows', the Secret Service 'API' on 'Linux', + and simple, platform independent stores implemented with environment + variables or encrypted files. Additional storage back-ends can be + added easily. + date_publication: '2023-12-11' + bug_reports: https://github.com/r-lib/keyring/issues + url: https://keyring.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=keyring + url_git: https://github.com/r-lib/keyring +keyringr: + version: 0.4.0 + title: |- + Decrypt Passwords from Gnome Keyring, Windows Data Protection + API and macOS Keychain + maintainer: Josh Gilfillan + description: |- + Decrypts passwords stored in the Gnome Keyring, macOS Keychain and + strings encrypted with the Windows Data Protection API. + date_publication: '2017-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=keyringr + url_git: '' +keys: + version: 0.1.1 + title: Keyboard Shortcuts for 'shiny' + maintainer: Tyler Littlefield + description: |- + Assign and listen to keyboard shortcuts in 'shiny' using the + 'Mousetrap' Javascript library. + date_publication: '2021-07-11' + bug_reports: https://github.com/r4fun/keys/issues + url: '' + url_cran: https://CRAN.R-project.org/package=keys + url_git: https://github.com/r4fun/keys +keyToEnglish: + version: 0.2.1 + title: Convert Data to Memorable Phrases + maintainer: Max Candocia + description: |- + Convert keys and other values to memorable phrases. + Includes some methods to build lists of words. + date_publication: '2021-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=keyToEnglish + url_git: https://github.com/mcandocia/keyToEnglish +kfa: + version: 0.2.2 + title: K-Fold Cross Validation for Factor Analysis + maintainer: Kyle Nickodem + description: |- + Provides functions to identify plausible and replicable factor + structures for a set of variables via k-fold cross validation. The process + combines the exploratory and confirmatory factor analytic approach to scale + development (Flora & Flake, 2017) with a cross validation + technique that maximizes the available data (Hastie, Tibshirani, & Friedman, 2009) + . Also available are functions to determine k by drawing + on power analytic techniques for covariance structures (MacCallum, Browne, & + Sugawara, 1996) , generate model syntax, and + summarize results in a report. + date_publication: '2023-07-09' + bug_reports: https://github.com/knickodem/kfa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kfa + url_git: https://github.com/knickodem/kfa +KFAS: + version: 1.5.1 + title: |- + Kalman Filter and Smoother for Exponential Family State Space + Models + maintainer: Jouni Helske + description: |- + State space modelling is an efficient and flexible framework for + statistical inference of a broad class of time series and other data. KFAS + includes computationally efficient functions for Kalman filtering, smoothing, + forecasting, and simulation of multivariate exponential family state space models, + with observations from Gaussian, Poisson, binomial, negative binomial, and gamma + distributions. See the paper by Helske (2017) for details. + date_publication: '2023-09-05' + bug_reports: https://github.com/helske/KFAS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KFAS + url_git: https://github.com/helske/KFAS +kfda: + version: 1.0.0 + title: Kernel Fisher Discriminant Analysis + maintainer: Donghwan Kim + description: |- + Kernel Fisher Discriminant Analysis (KFDA) is performed using Kernel Principal Component Analysis (KPCA) and Fisher Discriminant Analysis (FDA). + There are some similar packages. First, 'lfda' is a package that performs Local Fisher Discriminant Analysis (LFDA) and performs other functions. + In particular, 'lfda' seems to be impossible to test because it needs the label information of the data in the function argument. Also, the 'ks' package has a limited dimension, which makes it difficult to analyze properly. + This package is a simple and practical package for KFDA based on the paper of Yang, J., Jin, Z., Yang, J. Y., Zhang, D., and Frangi, A. F. (2004) . + date_publication: '2017-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kfda + url_git: https://github.com/ainsuotain/kfda +kfigr: + version: 1.2.1 + title: |- + Integrated Code Chunk Anchoring and Referencing for R Markdown + Documents + maintainer: Michael C Koohafkan + description: |- + A streamlined cross-referencing system for R Markdown documents + generated with 'knitr'. R Markdown is an authoring format for generating + dynamic content from R. 'kfigr' provides a hook for anchoring code + chunks and a function to cross-reference document elements generated from + said chunks, e.g. figures and tables. + date_publication: '2021-06-10' + bug_reports: https://github.com/mkoohafkan/kfigr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kfigr + url_git: https://github.com/mkoohafkan/kfigr +kfino: + version: 1.0.0 + title: Kalman Filter for Impulse Noised Outliers + maintainer: Isabelle Sanchez + description: |- + A method for detecting outliers with a Kalman filter on impulsed + noised outliers and prediction on cleaned data. 'kfino' is a robust + sequential algorithm allowing to filter data with a large number of outliers. + This algorithm is based on simple latent linear Gaussian processes as in the + Kalman Filter method and is devoted to detect impulse-noised outliers. These + are data points that differ significantly from other observations. 'ML' + (Maximization Likelihood) and 'EM' (Expectation-Maximization algorithm) + algorithms were implemented in 'kfino'. The method is described in full + details in the following arXiv e-Print: . + date_publication: '2022-11-03' + bug_reports: https://forgemia.inra.fr/isabelle.sanchez/kfino/-/issues + url: https://forgemia.inra.fr/isabelle.sanchez/kfino + url_cran: https://CRAN.R-project.org/package=kfino + url_git: '' +KFPCA: + version: '2.0' + title: Kendall Functional Principal Component Analysis + maintainer: Rou Zhong + description: Implementation for Kendall functional principal component analysis. + Kendall functional principal component analysis is a robust functional principal + component analysis technique for non-Gaussian functional/longitudinal data. The + crucial function of this package is KFPCA() and KFPCA_reg(). Moreover, least square + estimates of functional principal component scores are also provided. Refer to + Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) . + Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) . + date_publication: '2022-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KFPCA + url_git: '' +KFPLS: + version: '1.0' + title: Kernel Functional Partial Least Squares + maintainer: Rou Zhong + description: Implementation for kernel functional partial least squares (KFPLS) + method. KFPLS method is developed for functional nonlinear models, and the method + does not require strict constraints for the nonlinear structures. The crucial + function of this package is KFPLS(). + date_publication: '2023-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KFPLS + url_git: '' +kgc: + version: 1.0.0.2 + title: Koeppen-Geiger Climatic Zones + maintainer: Chelsey Bryant + description: |- + Aids in identifying the Koeppen-Geiger (KG) climatic zone for + a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system + to classify regions of the earth by their relative heat and humidity through the year, for + the benefit of human health, plant and agriculture and other human activity [1]. This climate + zone classification system, applicable to all of the earths surface, has continued to be + developed by scientists up to the present day. Recently one of use (FZ) has published updated, + higher accuracy KG climate zone definitions [2]. In this package we use these updated + high-resolution maps as the data source [3]. We provide functions that return the KG climate zone + for a given longitude and lattitude, or for a given United States zip code. In addition + the CZUncertainty() function will check climate zones nearby to check if the given location + is near a climate zone boundary. In addition an interactive shiny app is provided to define + the KG climate zone for a given longitude and lattitude, or United States zip code. + Digital data, as well as animated maps, showing the shift of the climate zones are provided + on the following website . + This work was supported by the DOE-EERE SunShot award DE-EE-0007140. + [1] W. Koeppen, (2011) . + [2] F. Rubel and M. Kottek, (2010) . + [3] F. Rubel, K. Brugger, K. Haslinger, and I. Auer, (2016) . + date_publication: '2017-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kgc + url_git: '' +kgen: + version: 0.3.1 + title: |- + A Tool for Calculating Stoichiometric Equilibrium Constants (Ks) + for Seawater + maintainer: Dennis Mayk + description: A unified software package simultaneously implemented in 'Python', + 'R', and 'Matlab' providing a uniform and internally-consistent way of calculating + stoichiometric equilibrium constants in modern and palaeo seawater as a function + of temperature, salinity, pressure and the concentration of magnesium, calcium, + sulphate, and fluorine. + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kgen + url_git: '' +KGode: + version: 1.0.4 + title: |- + Kernel Based Gradient Matching for Parameter Inference in + Ordinary Differential Equations + maintainer: Mu Niu + description: The kernel ridge regression and the gradient matching algorithm proposed + in Niu et al. (2016) and the warping + algorithm proposed in Niu et al. (2017) are implemented + for parameter inference in differential equations. Four schemes are provided for + improving parameter estimation in odes by using the odes regularisation and warping. + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KGode + url_git: '' +kgp: + version: 1.1.1 + title: 1000 Genomes Project Metadata + maintainer: Stephen Turner + description: Metadata about populations and data about samples from the 1000 Genomes + Project, including the 2,504 samples sequenced for the Phase 3 release and the + expanded collection of 3,202 samples with 602 additional trios. The data is described + in Auton et al. (2015) and Byrska-Bishop et al. (2022) + , and raw data is available at . + See Turner (2022) for more details. + date_publication: '2022-12-21' + bug_reports: '' + url: https://stephenturner.github.io/kgp/ + url_cran: https://CRAN.R-project.org/package=kgp + url_git: https://github.com/stephenturner/kgp +kgrams: + version: 0.2.1 + title: Classical k-gram Language Models + maintainer: Valerio Gherardi + description: |- + Training and evaluating k-gram language models in R, + supporting several probability smoothing techniques, + perplexity computations, random text generation and more. + date_publication: '2024-11-13' + bug_reports: https://github.com/vgherard/kgrams/issues + url: https://vgherard.github.io/kgrams/ + url_cran: https://CRAN.R-project.org/package=kgrams + url_git: https://github.com/vgherard/kgrams +kgraph: + version: 1.0.1 + title: Knowledge Graphs Constructions and Visualizations + maintainer: Thomas Charlon + description: 'Knowledge graphs enable to efficiently visualize and gain insights + into large-scale data analysis results, as p-values from multiple studies or embedding + data matrices. The usual workflow is a user providing a data frame of association + studies results and specifying target nodes, e.g. phenotypes, to visualize. The + knowledge graph then shows all the features which are significantly associated + with the phenotype, with the edges being proportional to the association scores. + As the user adds several target nodes and grouping information about the nodes + such as biological pathways, the construction of such graphs soon becomes complex. + The ''kgraph'' package aims to enable users to easily build such knowledge graphs, + and provides two main features: first, to enable building a knowledge graph based + on a data frame of concepts relationships, be it p-values or cosine similarities; + second, to enable determining an appropriate cut-off on cosine similarities from + a complete embedding matrix, to enable the building of a knowledge graph directly + from an embedding matrix. The ''kgraph'' package provides several display, layout + and cut-off options, and has already proven useful to researchers to enable them + to visualize large sets of p-value associations with various phenotypes, and to + quickly be able to visualize embedding results. Two example datasets are provided + to demonstrate these behaviors, and several live ''shiny'' applications are hosted + by the CELEHS laboratory and Parse Health, as the KESER Mental Health application + based on Hong C. (2021) .' + date_publication: '2025-02-01' + bug_reports: https://gitlab.com/thomaschln/kgraph/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kgraph + url_git: https://gitlab.com/thomaschln/kgraph +kgschart: + version: 1.3.5 + title: KGS Rank Graph Parser + maintainer: Kota Mori + description: |- + Restore underlining numeric data from rating history graph of + KGS (an online platform of the game of go, ). + A shiny application is also provided. + date_publication: '2017-07-02' + bug_reports: https://github.com/kota7/kgschart/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kgschart + url_git: https://github.com/kota7/kgschart +khisr: + version: 1.0.6 + title: An R Client to Retrieve Data from DHIS2 + maintainer: David Kariuki + description: |- + Provides a user-friendly interface for interacting with the District Health + Information Software 2 (DHIS2) instance. It streamlines data retrieval, + empowering researchers, analysts, and healthcare professionals to obtain and + utilize data efficiently. + date_publication: '2024-10-06' + bug_reports: https://github.com/damurka/khisr/issues + url: https://khisr.damurka.com + url_cran: https://CRAN.R-project.org/package=khisr + url_git: https://github.com/damurka/khisr +KHQ: + version: 0.2.0 + title: |- + Methods for Calculating 'KHQ' Scores and 'KHQ5D' Utility Index + Scores + maintainer: Luiz Augusto Brusaca + description: |- + The King's Health Questionnaire (KHQ) is a disease-specific, + self-administered questionnaire designed specific to assess the impact of + Urinary Incontinence (UI) on Quality of Life. The questionnaire was developed + by Kelleher and collaborators (1997) . + It is a simple, acceptable and reliable measure to use in the clinical setting + and a research tool that is useful in evaluating UI treatment outcomes. + The KHQ five dimensions (KHQ5D) is a condition-specific preference-based + measure developed by Brazier and collaborators (2008) . + Although not as popular as the SF6D and + EQ-5D , the KHQ5D measures health-related quality of + life (HRQoL) specifically for UI, not general conditions like the others + two instruments mentioned. The KHQ5D ca be used in the clinical and economic + evaluation of health care. The subject self-rates their health in terms of + five dimensions: Role Limitation (RL), Physical Limitations (PL), Social + Limitations (SL), Emotions (E), and Sleep (S). Frequently the states on these + five dimensions are converted to a single utility index using country specific + value sets, which can be used in the clinical and economic evaluation of + health care as well as in population health surveys. This package provides + methods to calculate scores for each dimension of the KHQ; converts KHQ item + scores to KHQ5D scores; and also calculates the utility index of the KHQ5D. + date_publication: '2021-08-06' + bug_reports: https://github.com/augustobrusaca/KHQ/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KHQ + url_git: https://github.com/augustobrusaca/KHQ +khroma: + version: 1.16.0 + title: Colour Schemes for Scientific Data Visualization + maintainer: Nicolas Frerebeau + description: |- + Color schemes ready for each type of data (qualitative, + diverging or sequential), with colors that are distinct for all + people, including color-blind readers. This package provides an + implementation of Paul Tol (2018) and Fabio Crameri (2018) + color schemes for use with 'graphics' + or 'ggplot2'. It provides tools to simulate color-blindness and to + test how well the colors of any palette are identifiable. Several + scientific thematic schemes (geologic timescale, land cover, FAO + soils, etc.) are also implemented. + date_publication: '2025-02-25' + bug_reports: https://codeberg.org/tesselle/khroma/issues + url: https://codeberg.org/tesselle/khroma + url_cran: https://CRAN.R-project.org/package=khroma + url_git: '' +kibior: + version: 0.1.1 + title: A Simple Data Management and Sharing Tool + maintainer: Régis Ongaro-Carcy + description: An interface to store, retrieve, search, join and share datasets, based + on Elasticsearch (ES) API. As a decentralized, FAIR and collaborative search engine + and database effort, it proposes a simple push/pull/search mechanism only based + on ES, a tool which can be deployed on nearly any hardware. It is a high-level + R-ES binding to ease data usage using 'elastic' package (S. Chamberlain (2020)) + , extends joins from 'dplyr' package (H. Wickham + et al. (2020)) and integrates specific biological + format importation with Bioconductor packages such as 'rtracklayer' (M. Lawrence + and al. (2009) ) , + 'Biostrings' (H. Pagès and al. (2020) ) , + and 'Rsamtools' (M. Morgan and al. (2020) ) , + but also a long list of more common ones with 'rio' (C-h. Chan and al. (2018)) + . + date_publication: '2021-01-28' + bug_reports: https://github.com/regisoc/kibior/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kibior + url_git: https://github.com/regisoc/kibior +kidney.epi: + version: 1.2.0 + title: 'Kidney Functions: Clinical and Epidemiological' + maintainer: Boris Bikbov + description: |- + Contains kidney care oriented functions. + Current version contains functions for calculation of: + - Kidney Donor Risk Index and Kidney Donor Profile Index for kidney transplant donors by Rao et al. (2009) . + - Estimated glomerular filtration rate by CKD-EPI, MDRD and other equations. + Citation: Bikbov B. R open source programming code for calculation of the Kidney Donor Profile Index and Kidney Donor Risk Index. Kidney Diseases (2018) 4:269–272 (the only citation for the whole package). + date_publication: '2020-03-04' + bug_reports: '' + url: http://kidneyepidemiology.org/r/ + url_cran: https://CRAN.R-project.org/package=kidney.epi + url_git: '' +kidsides: + version: 0.5.0 + title: Download, Cache, and Connect to KidSIDES + maintainer: Nicholas Giangreco + description: |- + Caches and then connects to a 'sqlite' database containing half a million pediatric drug safety signals. + The database is part of a family of resources catalogued at . The database + contains 17 tables where the description table provides a map between the fields the field's details. + The database was created by Nicholas Giangreco during his PhD thesis which you can read in Giangreco (2022) . + The observations are from the Food and Drug Administration's Adverse Event Reporting System. Generalized additive models estimated + drug effects across child development stages for the occurrence of an adverse event when exposed to a drug compared to other drugs. + Read more at the methods detailed in Giangreco (2022) . + date_publication: '2023-05-21' + bug_reports: '' + url: https://ngiangre.github.io/kidsides/ + url_cran: https://CRAN.R-project.org/package=kidsides + url_git: https://github.com/ngiangre/kidsides +Kifidi: + version: 0.1.0 + title: Summary Table and Means Plots + maintainer: Oswald Omuron + description: |- + Optimized for handling complex datasets in environmental and ecological + research, this package offers functionality that is not fully met by + general-purpose packages. It provides two key functions, 'summarize_data()', + which summarizes datasets, and 'plot_means()', which creates plots with + error bars. The 'plot_means()' function incorporates error bars by default, + allowing quick visualization of uncertainties, crucial in ecological + studies. It also streamlines workflows for grouped datasets (e.g., + by species or treatment), making it particularly user-friendly and reducing + the complexity and time required for data summarization and visualization. + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kifidi + url_git: '' +kim: + version: 0.6.1 + title: A Toolkit for Behavioral Scientists + maintainer: Jin Kim + description: |- + A collection of functions for analyzing data typically collected + or used by behavioral scientists. Examples of the functions include + a function that compares groups in a factorial experimental design, + a function that conducts two-way analysis of variance (ANOVA), + and a function that cleans a data set generated by Qualtrics surveys. + Some of the functions will require installing additional package(s). + Such packages and other references are cited within the section + describing the relevant functions. Many functions in this package + rely heavily on these two popular R packages: + Dowle et al. (2021) . + Wickham et al. (2021) . + date_publication: '2025-02-26' + bug_reports: https://github.com/jinkim3/kim/issues + url: https://jinkim.science + url_cran: https://CRAN.R-project.org/package=kim + url_git: https://github.com/jinkim3/kim +kimfilter: + version: 1.0.3 + title: Kim Filter + maintainer: Alex Hubbard + description: |- + 'Rcpp' implementation of the multivariate Kim filter, which combines the Kalman and Hamilton filters for state probability inference. + The filter is designed for state space models and can handle missing values and exogenous data in the observation and state equations. + Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" . + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kimfilter + url_git: '' +kimisc: + version: 1.0.0 + title: Kirill's Miscellaneous Functions + maintainer: Kirill Müller + description: |- + A collection of useful functions not found anywhere else, + mainly for programming: Pretty intervals, generalized lagged + differences, checking containment in an interval, and an alternative + interface to assign(). + date_publication: '2024-12-02' + bug_reports: https://github.com/krlmlr/kimisc/issues + url: https://krlmlr.github.io/kimisc/ + url_cran: https://CRAN.R-project.org/package=kimisc + url_git: https://github.com/krlmlr/kimisc +kin.cohort: + version: '0.7' + title: Analysis of Kin-Cohort Studies + maintainer: Victor Moreno + description: |- + Analysis of kin-cohort studies. kin.cohort provides estimates of age-specific + cumulative risk of a disease for carriers and noncarriers of a mutation. The cohorts are + retrospectively built from relatives of probands for whom the genotype is known. Currently + the method of moments and marginal maximum likelihood are implemented. Confidence intervals + are calculated from bootstrap samples. + Most of the code is a translation from previous 'MATLAB' code by N. Chatterjee. + date_publication: '2015-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kin.cohort + url_git: '' +kindisperse: + version: 0.10.2 + title: Simulate and Estimate Close-Kin Dispersal Kernels + maintainer: Moshe-Elijah Jasper + description: |- + Functions for simulating and estimating kinship-related dispersal. Based + on the methods described in M. Jasper, T.L. Schmidt., N.W. Ahmad, S.P. Sinkins & A.A. + Hoffmann (2019) "A genomic approach to inferring kinship + reveals limited intergenerational dispersal in the yellow fever mosquito". + Assumes an additive variance model of dispersal in two dimensions, compatible with + Wright's neighbourhood area. Simple and composite dispersal simulations are supplied, + as well as the functions needed to estimate parent-offspring dispersal for simulated or + empirical data, and to undertake sampling design for future field studies of dispersal. + For ease of use an integrated Shiny app is also included. + date_publication: '2021-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kindisperse + url_git: https://github.com/moshejasper/kindisperse +kinematics: + version: 1.0.0 + title: Studying Sampled Trajectories + maintainer: Pablo Rodriguez-Sanchez + description: |- + Allows analyzing time series representing two-dimensional movements. + It accepts a data frame with a time (t), horizontal (x) and vertical (y) coordinate as columns, + and returns several dynamical properties such as speed, acceleration or curvature. + date_publication: '2021-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kinematics + url_git: '' +KingCountyHouses: + version: 0.1.0 + title: Data on House Sales in King County WA + maintainer: Max Kuhn + description: |- + Data on houses in and around Seattle WA are included. Basic + characteristics are given along with sale prices. + date_publication: '2021-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KingCountyHouses + url_git: '' +KinMixLite: + version: 2.1.1 + title: Inference About Relationships from DNA Mixtures + maintainer: Peter Green + description: |- + Methods for inference about relationships between contributors to a DNA mixture and + other individuals of known genotype: a basic example would be testing whether a contributor to + a mixture is the father of a child of known genotype. This provides most of the functionality + of the 'KinMix' package, but with some loss of efficiency and restriction on problem size, + as the latter uses 'RHugin' as the Bayes net engine, while this package uses 'gRain'. + The package implements the methods introduced in + Green, P. J. and Mortera, J. (2017) and + Green, P. J. and Mortera, J. (2021) . + date_publication: '2024-10-09' + bug_reports: '' + url: https://petergreenweb.wordpress.com/kinmix/ + url_cran: https://CRAN.R-project.org/package=KinMixLite + url_git: '' +kinship2: + version: 1.9.6.1 + title: Pedigree Functions + maintainer: Jason Sinnwell + description: |- + Routines to handle family data with a pedigree object. The initial purpose + was to create correlation structures that describe family relationships such + as kinship and identity-by-descent, which can be used to model family data + in mixed effects models, such as in the coxme function. Also includes a tool + for pedigree drawing which is focused on producing compact layouts without + intervention. Recent additions include utilities to trim the pedigree object + with various criteria, and kinship for the X chromosome. + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kinship2 + url_git: '' +KINSIMU: + version: 0.1.2-2 + title: Panel Evaluation in Forensic Kinship Analysis + maintainer: Guanju Ma + description: 'Evaluate specific panels in different aspects: i) Simulation tools + related to pedigree researches; ii) calculation for systemic effectiveness indicators, + such as probability of exclusion (PE).' + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KINSIMU + url_git: '' +Kira: + version: 1.0.6 + title: Machine Learning + maintainer: Paulo Cesar Ossani + description: Machine learning, containing several algorithms for supervised and + unsupervised classification, in addition to a function that plots the Receiver + Operating Characteristic (ROC) and Precision-Recall (PRC) curve graphs, and also + a function that returns several metrics used for model evaluation, the latter + can be used in ranking results from other packs. + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kira + url_git: '' +kirby21.base: + version: 1.7.3 + title: Example Data from the Multi-Modal MRI 'Reproducibility' Resource + maintainer: John Muschelli + description: |- + Multi-modal magnetic resonance imaging ('MRI') + data from the 'Kirby21' 'reproducibility' study + , including functional + and structural imaging. + date_publication: '2020-07-02' + bug_reports: '' + url: https://www.nitrc.org/projects/multimodal/ + url_cran: https://CRAN.R-project.org/package=kirby21.base + url_git: '' +kirby21.fmri: + version: 1.7.0 + title: |- + Example Functional Imaging Data from the Multi-Modal MRI + 'Reproducibility' Resource + maintainer: John Muschelli + description: |- + Functional magnetic resonance imaging ('fMRI') + data from the 'Kirby21' 'reproducibility' study + . + date_publication: '2018-08-13' + bug_reports: '' + url: https://www.nitrc.org/projects/multimodal/ + url_cran: https://CRAN.R-project.org/package=kirby21.fmri + url_git: '' +kirby21.t1: + version: 1.7.0 + title: |- + Example T1 Structural Data from the Multi-Modal MRI + 'Reproducibility' Resource + maintainer: John Muschelli + description: |- + Structural T1 magnetic resonance imaging ('MRI') + data from the 'Kirby21' 'reproducibility' study + . + date_publication: '2018-08-13' + bug_reports: '' + url: https://www.nitrc.org/projects/multimodal/ + url_cran: https://CRAN.R-project.org/package=kirby21.t1 + url_git: '' +kisopenapi: + version: 0.0.2 + title: Korea Investment & Securities (KIS) Open Trading API + maintainer: Seokhoon Joo + description: |- + API Wrapper to use Korea Investment & Securities (KIS) trading + system that provides various financial services like stock price + check, orders and balance check + . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kisopenapi + url_git: '' +kissmig: + version: 1.0-5 + title: a Keep It Simple Species Migration Model + maintainer: Michael P. Nobis + description: Simulating species migration and range dynamics under stable or changing + environmental conditions based on a simple, raster-based, deterministic or stochastic + migration model. Kissmig runs on binary or quantitative suitability maps, which + are pre-calculated with niche-based habitat suitability models (also called ecological + niche models (ENMs) or species distribution models (SDMs)). Nobis & Normand (2014), + . + date_publication: '2024-07-26' + bug_reports: '' + url: https://purl.oclc.org/wsl/kissmig + url_cran: https://CRAN.R-project.org/package=kissmig + url_git: '' +kit: + version: 0.0.19 + title: Data Manipulation Functions Implemented in C + maintainer: Morgan Jacob + description: Basic functions, implemented in C, for large data manipulation. Fast + vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent + to pmin()/pmax() plus others which are missing from base R. Most of these functions + are callable at C level. + date_publication: '2024-09-07' + bug_reports: https://github.com/2005m/kit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kit + url_git: '' +kitagawa: + version: 3.1.2 + title: |- + Spectral Response of Water Wells to Harmonic Strain and Pressure + Signals + maintainer: Andrew J. Barbour + description: |- + Provides tools to calculate the theoretical hydrodynamic response + of an aquifer undergoing harmonic straining or pressurization, or analyze + measured responses. There are + two classes of models here, designed for use with confined + aquifers: (1) for sealed wells, based on the model of + Kitagawa et al (2011, ), + and (2) for open wells, based on the models of + Cooper et al (1965, ), + Hsieh et al (1987, ), + Rojstaczer (1988, ), + Liu et al (1989, ), and + Wang et al (2018, ). Wang's + solution is a special exception which + allows for leakage out of the aquifer + (semi-confined); it is equivalent to Hsieh's model + when there is no leakage (the confined case). + These models treat strain (or aquifer head) as an input to the + physical system, and fluid-pressure (or water height) as the output. The + applicable frequency band of these models is characteristic of seismic + waves, atmospheric pressure fluctuations, and solid earth tides. + date_publication: '2024-01-29' + bug_reports: https://github.com/abarbour/kitagawa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kitagawa + url_git: https://github.com/abarbour/kitagawa +kiwisR: + version: 0.2.4 + title: |- + A Wrapper for Querying KISTERS 'WISKI' Databases via the 'KiWIS' + API + maintainer: Ryan Whaley + description: |- + A wrapper for querying 'WISKI' databases via the 'KiWIS' 'REST' API. 'WISKI' is an 'SQL' relational database + used for the collection and storage of water data developed by KISTERS and 'KiWIS' is a 'REST' service that provides + access to 'WISKI' databases via HTTP requests (). + Contains a list of default databases (called 'hubs') and also allows users to provide their own 'KiWIS' URL. + Supports the entire query process- from metadata to specific time series values. All data is returned as tidy tibbles. + date_publication: '2024-10-11' + bug_reports: https://github.com/rywhale/kiwisR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kiwisR + url_git: https://github.com/rywhale/kiwisR +kknn: + version: 1.3.1 + title: Weighted k-Nearest Neighbors + maintainer: Klaus Schliep + description: Weighted k-Nearest Neighbors for Classification, Regression and Clustering. + date_publication: '2016-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kknn + url_git: https://github.com/KlausVigo/kknn +kko: + version: 1.0.1 + title: Kernel Knockoffs Selection for Nonparametric Additive Models + maintainer: Xiang Lyu + description: 'A variable selection procedure, dubbed KKO, for nonparametric additive + model with finite-sample false discovery rate control guarantee. The method integrates + three key components: knockoffs, subsampling for stability, and random feature + mapping for nonparametric function approximation. For more information, see the + accompanying paper: Dai, X., Lyu, X., & Li, L. (2021). “Kernel Knockoffs Selection + for Nonparametric Additive Models”. arXiv preprint .' + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kko + url_git: '' +klaR: + version: 1.7-3 + title: Classification and Visualization + maintainer: Uwe Ligges + description: |- + Miscellaneous functions for classification and visualization, + e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, + an interface to 'svmlight' and stepclass() wrapper variable selection + for supervised classification, partimat() visualization of classification rules + and shardsplot() of cluster results as well as kmodes() clustering for categorical data, + corclust() variable clustering, variable extraction from different variable clustering models + and weight of evidence preprocessing. + date_publication: '2023-12-13' + bug_reports: '' + url: https://statistik.tu-dortmund.de + url_cran: https://CRAN.R-project.org/package=klaR + url_git: '' +klassR: + version: 1.0.2 + title: Classifications and Codelists for Statistics Norway + maintainer: Susie Jentoft + description: |- + Functions to search, retrieve, apply and update classifications + and codelists using Statistics Norway's API + from the system 'KLASS'. Retrieves classifications by date with options + to choose language, hierarchical level and formatting. + date_publication: '2025-02-07' + bug_reports: https://github.com/statisticsnorway/ssb-klassr/issues + url: https://statisticsnorway.github.io/ssb-klassr/ + url_cran: https://CRAN.R-project.org/package=klassR + url_git: '' +klausuR: + version: 0.12-14 + title: Multiple Choice Test Evaluation + maintainer: m.eik michalke + description: |- + A set of functions designed to quickly generate results of a multiple choice + test. Generates detailed global results, lists for anonymous feedback and + personalised result feedback (in LaTeX and/or PDF format), as well as item + statistics like Cronbach's alpha or disciminatory power. 'klausuR' also + includes a plugin for the R GUI and IDE RKWard, providing graphical dialogs for + its basic features. The respective R package 'rkward' cannot be installed + directly from a repository, as it is a part of RKWard. To make full use of this + feature, please install RKWard from (plugins are + detected automatically). Due to some restrictions on CRAN, the full package + sources are only available from the project homepage. + date_publication: '2022-04-04' + bug_reports: https://github.com/unDocUMeantIt/klausuR/issues + url: https://reaktanz.de/?c=hacking&s=klausuR + url_cran: https://CRAN.R-project.org/package=klausuR + url_git: '' +kldest: + version: 1.0.0 + title: Sample-Based Estimation of Kullback-Leibler Divergence + maintainer: Niklas Hartung + description: |- + Estimation algorithms for Kullback-Leibler divergence between two probability + distributions, based on one or two samples, and including uncertainty quantification. + Distributions can be uni- or multivariate and continuous, discrete or mixed. + date_publication: '2024-04-09' + bug_reports: https://github.com/niklhart/kldest/issues + url: https://niklhart.github.io/kldest/ + url_cran: https://CRAN.R-project.org/package=kldest + url_git: '' +kldtools: + version: '1.2' + title: |- + Kullback-Leibler Divergence and Other Tools to Analyze + Frequencies + maintainer: Alexey Shipunov + description: |- + Most importantly, calculates Kullback-Leibler Divergence (KLD), Turing's perspective estimator + and their confidence intervals. + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kldtools + url_git: '' +KLexp: + version: 1.0.0 + title: Kernel_lasso Expansion + maintainer: Zongrui Dai + description: Provides the function to calculate the kernel-lasso expansion, Z-score, + and max-min-scale standardization.It can increase the dimension of existed dataset + and remove abundant features by lasso. Z Dai, L Jiayi, T Gong, C Wang (2021) . + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KLexp + url_git: https://github.com/Zongrui-Dai/Kernel-lasso-feature-expansion +klic: + version: 1.0.4 + title: Kernel Learning Integrative Clustering + maintainer: Alessandra Cabassi + description: 'Kernel Learning Integrative Clustering (KLIC) is an algorithm that + allows to combine multiple kernels, each representing a different measure of the + similarity between a set of observations. The contribution of each kernel on the + final clustering is weighted according to the amount of information carried by + it. As well as providing the functions required to perform the kernel-based clustering, + this package also allows the user to simply give the data as input: the kernels + are then built using consensus clustering. Different strategies to choose the + best number of clusters are also available. For further details please see Cabassi + and Kirk (2020) .' + date_publication: '2020-07-06' + bug_reports: http://github.com/acabassi/klic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=klic + url_git: http://github.com/acabassi/klic +KLINK: + version: 1.0.2 + title: Kinship Analysis with Linked Markers + maintainer: Magnus Dehli Vigeland + description: |- + A 'shiny' application for forensic kinship testing, based on + the 'pedsuite' R packages. 'KLINK' is closely aligned with the (non-R) + software 'Familias' and 'FamLink', but offers several unique features, + including visualisations and automated report generation. The + calculation of likelihood ratios supports pairs of linked markers, and + all common mutation models. + date_publication: '2024-09-03' + bug_reports: https://github.com/magnusdv/KLINK/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KLINK + url_git: https://github.com/magnusdv/KLINK +klovan: + version: 0.1.0 + title: Geostatistics Methods and Klovan Data + maintainer: Roger H French + description: |- + A comprehensive set of geostatistical, visual, + and analytical methods, in conjunction with the expanded version of the + acclaimed J.E. Klovan's mining dataset, are included in 'klovan'. This makes the + package an excellent learning resource for Principal Component Analysis (PCA), + Factor Analysis (FA), kriging, and other geostatistical techniques. Originally + published in the 1976 book 'Geological Factor Analysis', the included mining + dataset was assembled by Professor J. E. Klovan of the University of Calgary. + Being one of the first applications of FA in the geosciences, this dataset has + significant historical importance. As a well-regarded and published dataset, it + is an excellent resource for demonstrating the capabilities of PCA, FA, kriging, + and other geostatistical techniques in geosciences. For those interested in + these methods, the 'klovan' datasets provide a valuable and illustrative resource. + Note that some methods require the 'RGeostats' package. Please refer to the + README or Additional_repositories for installation instructions. This material is + based upon research in the Materials Data Science for Stockpile Stewardship Center + of Excellence (MDS3-COE), and supported by the Department of Energy's National + Nuclear Security Administration under Award Number DE-NA0004104. + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=klovan + url_git: '' +klsh: + version: 0.1.0 + title: Blocking for Record Linkage + maintainer: Rebecca Steorts + description: An implementation of the blocking algorithm KLSH in Steorts, Ventura, + Sadinle, Fienberg (2014) , which is a k-means + variant of locality sensitive hashing. The method is illustrated with examples + and a vignette. + date_publication: '2020-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=klsh + url_git: '' +klustR: + version: 0.1.0 + title: D3 Dynamic Cluster Visualizations + maintainer: McKay Davis + description: |- + Used to create dynamic, interactive 'D3.js' + based parallel coordinates and principal component plots in 'R'. + The plots make visualizing k-means or other clusters simple and informative. + date_publication: '2019-06-19' + bug_reports: https://github.com/McKayMDavis/klustR/issues + url: https://mckaymdavis.github.io/klustR/ + url_cran: https://CRAN.R-project.org/package=klustR + url_git: https://github.com/McKayMDavis/klustR +km.ci: + version: 0.5-6 + title: Confidence Intervals for the Kaplan-Meier Estimator + maintainer: Tobias Verbeke + description: |- + Computes various confidence intervals for the Kaplan-Meier + estimator, namely: Peto's CI, Rothman CI, CI's based on + Greenwood's variance, Thomas and Grunkemeier CI and the + simultaneous confidence bands by Nair and Hall and Wellner. + date_publication: '2022-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=km.ci + url_git: '' +kmBlock: + version: 0.1.2 + title: k-Means Like Blockmodeling of One-Mode and Linked Networks + maintainer: Aleš Žiberna + description: Implements k-means like blockmodeling of one-mode and linked networks + as presented in Žiberna (2020) . The development + of this package is financially supported by the Slovenian Research Agency () + within the research programs P5-0168 and the research projects J7-8279 (Blockmodeling + multilevel and temporal networks) and J5-2557 (Comparison and evaluation of different + approaches to blockmodeling dynamic networks by simulations with application to + Slovenian co-authorship networks). + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kmBlock + url_git: '' +kmc: + version: 0.4-2 + title: |- + Kaplan-Meier Estimator with Constraints for Right Censored Data + -- a Recursive Computational Algorithm + maintainer: Yifan Yang + description: 'Given constraints for right censored data, we use a recursive computational + algorithm to calculate the the "constrained" Kaplan-Meier estimator. The constraint + is assumed given in linear estimating equations or mean functions. We also illustrate + how this leads to the empirical likelihood ratio test with right censored data + and accelerated failure time model with given coefficients. EM algorithm from + emplik package is used to get the initial value. The properties and performance + of the EM algorithm is discussed in Mai Zhou and Yifan Yang (2015) + and Mai Zhou and Yifan Yang (2017) . More applications + could be found in Mai Zhou (2015) .' + date_publication: '2022-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kmc + url_git: https://github.com/yfyang86/kmc/ +KMD: + version: 0.1.0 + title: Kernel Measure of Multi-Sample Dissimilarity + maintainer: Zhen Huang + description: |- + Implementations of the kernel measure of multi-sample dissimilarity (KMD) between + several samples using K-nearest neighbor graphs and minimum spanning trees. The KMD + measures the dissimilarity between multiple samples, based on the observations from them. + It converges to the population quantity (depending on the kernel) which is between 0 and 1. + A small value indicates the multiple samples are from the same distribution, and a large value + indicates the corresponding distributions are different. The population quantity is 0 if and only + if all distributions are the same, and 1 if and only if all distributions are mutually singular. + The package also implements the tests based on KMD for H0: the M distributions are equal + against H1: not all the distributions are equal. Both permutation test and asymptotic test are + available. These tests are consistent against all alternatives where at least two samples have + different distributions. For more details on KMD and the associated tests, see Huang, Z. and + B. Sen (2022) . + date_publication: '2022-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KMD + url_git: '' +KMEANS.KNN: + version: 0.1.0 + title: KMeans and KNN Clustering Package + maintainer: LALLOGO Lassané + description: 'Implementation of Kmeans clustering algorithm and a supervised KNN + (K Nearest Neighbors) learning method. It allows users to perform unsupervised + clustering and supervised classification on their datasets. Additional features + include data normalization, imputation of missing values, and the choice of distance + metric. The package also provides functions to determine the optimal number of + clusters for Kmeans and the best k-value for KNN: knn_Function(), find_Knn_best_k(), + KMEANS_FUNCTION(), and find_Kmeans_best_k().' + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KMEANS.KNN + url_git: '' +kmed: + version: 0.4.2 + title: Distance-Based k-Medoids + maintainer: Weksi Budiaji + description: |- + Algorithms of distance-based k-medoids clustering: simple and fast + k-medoids, ranked k-medoids, and increasing number of clusters in k-medoids. + Calculate distances for mixed variable data such as Gower, Podani, Wishart, + Huang, Harikumar-PV, and Ahmad-Dey. Cluster validation applies internal and + relative criteria. The internal criteria includes silhouette index and shadow + values. The relative criterium applies bootstrap procedure producing a heatmap + with a flexible reordering matrix algorithm such as complete, ward, or average + linkages. The cluster result can be plotted in a marked barplot or pca biplot. + date_publication: '2022-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kmed + url_git: '' +Kmedians: + version: 2.2.0 + title: K-Medians + maintainer: Antoine Godichon-Baggioni + description: |- + Online, Semi-online, and Offline K-medians algorithms are + given. For both methods, the algorithms can be initialized + randomly or with the help of a robust hierarchical + clustering. The number of clusters can be selected with the + help of a penalized criterion. We provide functions to provide + robust clustering. Function gen_K() enables to generate a sample + of data following a contaminated Gaussian mixture. + Functions Kmedians() and Kmeans() consists in a K-median and a + K-means algorithms while Kplot() enables to produce graph for both + methods. + Cardot, H., Cenac, P. and Zitt, P-A. (2013). "Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm". Bernoulli, 19, 18-43. . + Cardot, H. and Godichon-Baggioni, A. (2017). "Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis". Test, 26(3), 461-480 . + Godichon-Baggioni, A. and Surendran, S. "A penalized criterion for selecting the number of clusters for K-medians" + Vardi, Y. and Zhang, C.-H. (2000). "The multivariate L1-median and associated data depth". Proc. Natl. Acad. Sci. USA, 97(4):1423-1426. . + date_publication: '2023-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kmedians + url_git: '' +kmer: + version: 1.1.2 + title: |- + Fast K-Mer Counting and Clustering for Biological Sequence + Analysis + maintainer: Shaun Wilkinson + description: |- + Contains tools for rapidly computing distance matrices + and clustering large sequence datasets using fast alignment-free + k-mer counting and recursive k-means partitioning. + See Vinga and Almeida (2003) + for a review of k-mer counting methods and applications for + biological sequence analysis. + date_publication: '2019-05-20' + bug_reports: http://github.com/shaunpwilkinson/kmer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kmer + url_git: http://github.com/shaunpwilkinson/kmer +kmeRs: + version: 2.1.0 + title: K-Mers Similarity Score Matrix and HeatMap + maintainer: Rafal Urniaz + description: Similarity Score Matrix and HeatMap for nucleic and amino acid k-mers. + Similarity score is evaluated by Point Accepted Mutation (PAM) and BLOcks SUbstitution + Matrix (BLOSUM). The 30, 40, 70, 120, 250 and 62, 45, 50, 62, 80, 100 matrix versions + are available for PAM and BLOSUM, respectively. Alignment is evaluated by local + and global alignment. + date_publication: '2024-07-17' + bug_reports: https://github.com/urniaz/kmeRs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kmeRs + url_git: https://github.com/urniaz/kmeRs +kmeRtone: + version: '1.0' + title: Multi-Purpose and Flexible k-Meric Enrichment Analysis Software + maintainer: Aleksandr Sahakyan + description: |- + A multi-purpose and flexible k-meric enrichment analysis software. + 'kmeRtone' measures the enrichment of k-mers by comparing the population of + k-mers in the case loci with a carefully devised internal negative control + group, consisting of k-mers from regions close to, yet sufficiently distant + from, the case loci to mitigate any potential sequencing bias. This method + effectively captures both the local sequencing variations and broader + sequence influences, while also correcting for potential biases, thereby + ensuring more accurate analysis. The core functionality of 'kmeRtone' is + the SCORE() function, which calculates the susceptibility scores for k-mers in + case and control regions. Case regions are defined by the genomic coordinates + provided in a file by the user and the control regions can be constructed + relative to the case regions or provided directly. The k-meric susceptibility + scores are calculated by using a one-proportion z-statistic. 'kmeRtone' is + highly flexible by allowing users to also specify their target k-mer patterns + and quantify the corresponding k-mer enrichment scores in the context of + these patterns, allowing for a more comprehensive approach to understanding + the functional implications of specific DNA sequences on a genomic scale + (e.g., CT motifs upon UV radiation damage). + Adib A. Abdullah, Patrick Pflughaupt, Claudia Feng, Aleksandr B. Sahakyan (2024) Bioinformatics (submitted). + date_publication: '2024-08-30' + bug_reports: https://github.com/SahakyanLab/kmeRtone/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kmeRtone + url_git: https://github.com/SahakyanLab/kmeRtone +kmi: + version: 0.5.5 + title: |- + Kaplan-Meier Multiple Imputation for the Analysis of Cumulative + Incidence Functions in the Competing Risks Setting + maintainer: Arthur Allignol + description: Performs a Kaplan-Meier multiple imputation to recover the missing + potential censoring information from competing risks events, so that standard + right-censored methods could be applied to the imputed data sets to perform analyses + of the cumulative incidence functions (Allignol and Beyersmann, 2010 ). + date_publication: '2019-05-27' + bug_reports: https://github.com/aallignol/kmi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kmi + url_git: https://github.com/aallignol/kmi +kml: + version: 2.5.0 + title: K-Means for Longitudinal Data + maintainer: Christophe Genolini + description: |- + An implementation of k-means specifically design + to cluster longitudinal data. It provides facilities to deal with missing + value, compute several quality criterion (Calinski and Harabatz, + Ray and Turie, Davies and Bouldin, BIC, ...) and propose a graphical + interface for choosing the 'best' number of clusters. + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kml + url_git: '' +kml3d: + version: 2.5.0 + title: K-Means for Joint Longitudinal Data + maintainer: Christophe Genolini + description: |- + An implementation of k-means specifically design + to cluster joint trajectories (longitudinal data on + several variable-trajectories). + Like 'kml', it provides facilities to deal with missing + value, compute several quality criterion (Calinski and Harabatz, + Ray and Turie, Davies and Bouldin, BIC,...) and propose a graphical + interface for choosing the 'best' number of clusters. In addition, the 3D graph + representing the mean joint-trajectories of each cluster can be exported through + LaTeX in a 3D dynamic rotating PDF graph. + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kml3d + url_git: '' +KMLtoSHAPE: + version: 0.1.0 + title: 'Preserving Attribute Values: Converting KML to Shapefile' + maintainer: Nobin Chandra Paul + description: |- + The developed function is designed to facilitate the seamless conversion of KML (Keyhole Markup Language) + files to Shapefiles while preserving attribute values. It provides a straightforward interface for users + to effortlessly import KML data, extract relevant attributes, and export them into the widely compatible + Shapefile format. The package ensures accurate representation of spatial data while maintaining the integrity + of associated attribute information. For details see, Flores, G. (2021). . + Whether for spatial analysis, visualization, or data interoperability, it simplifies the conversion process and + empowers users to seamlessly work with geospatial datasets. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KMLtoSHAPE + url_git: '' +kmodR: + version: 0.2.0 + title: K-Means with Simultaneous Outlier Detection + maintainer: David Charles Howe + description: |- + An implementation of the 'k-means--' algorithm proposed + by Chawla and Gionis, 2013 in their paper, + "k-means-- : A unified approach to clustering and outlier detection. + SIAM International Conference on Data Mining (SDM13)", + + and using 'ordering' described by Howe, 2013 in the thesis, + Clustering and anomaly detection in tropical cyclones". + Useful for creating (potentially) tighter clusters than + standard k-means and simultaneously finding outliers inexpensively + in multidimensional space. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kmodR + url_git: '' +KMsurv: + version: 0.1-5 + title: Data sets from Klein and Moeschberger (1997), Survival Analysis + maintainer: Jun Yan + description: Data sets and functions for Klein and Moeschberger (1997),"Survival + Analysis, Techniques for Censored and TruncatedData", Springer. + date_publication: '2012-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KMsurv + url_git: '' +KMunicate: + version: 0.2.5 + title: KMunicate-Style Kaplan–Meier Plots + maintainer: Alessandro Gasparini + description: |- + Produce Kaplan–Meier plots in the style recommended + following the KMunicate study by Morris et al. (2019) + . The KMunicate style consists of + Kaplan-Meier curves with confidence intervals to quantify uncertainty + and an extended risk table (per treatment arm) depicting the number of + study subjects at risk, events, and censored observations over time. + The resulting plots are built using 'ggplot2' and can be further + customised to a certain extent, including themes, fonts, and colour + scales. + date_publication: '2024-05-16' + bug_reports: https://github.com/ellessenne/KMunicate-package/issues + url: https://ellessenne.github.io/KMunicate-package/ + url_cran: https://CRAN.R-project.org/package=KMunicate + url_git: https://github.com/ellessenne/KMunicate-package +KnapsackSampling: + version: 0.1.1 + title: Generate Feasible Samples of a Knapsack Problem + maintainer: Chin Soon Lim + description: The sampl.mcmc function creates samples of the feasible region of a + knapsack problem with both equalities and inequalities constraints. + date_publication: '2024-01-31' + bug_reports: https://github.com/chinsoon12/KnapsackSampling + url: '' + url_cran: https://CRAN.R-project.org/package=KnapsackSampling + url_git: https://github.com/chinsoon12/KnapsackSampling +KneeArrower: + version: 1.0.0 + title: Finds Cutoff Points on Knee Curves + maintainer: Alan Tseng + description: |- + Given a set of points around a knee curve, + analyzes first and second derivatives to find knee points. + date_publication: '2020-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KneeArrower + url_git: '' +knfi: + version: 1.0.1.9 + title: Analysis of Korean National Forest Inventory Database + maintainer: Sinyoung Park + description: |- + Understanding the current status of forest resources is essential for monitoring changes + in forest ecosystems and generating related statistics. In South Korea, the National Forest + Inventory (NFI) surveys over 4,500 sample plots nationwide every five years and records 70 items, + including forest stand, forest resource, and forest vegetation surveys. Many researchers use NFI + as the primary data for research, such as biomass estimation or analyzing the importance value of + each species over time and space, depending on the research purpose. However, the large volume + of accumulated forest survey data from across the country can make it challenging to manage and + utilize such a vast dataset. To address this issue, we developed an R package that efficiently + handles large-scale NFI data across time and space. The package offers a comprehensive + workflow for NFI data analysis. It starts with data processing, where read_nfi() function + reconstructs NFI data according to the researcher's needs while performing basic integrity checks + for data quality.Following this, the package provides analytical tools that operate on the verified + data. These include functions like summary_nfi() for summary statistics, diversity_nfi() for + biodiversity analysis, iv_nfi() for calculating species importance value, and biomass_nfi() and + cwd_biomass_nfi() for biomass estimation. Finally, for visualization, the tsvis_nfi() function + generates graphs and maps, allowing users to visualize forest ecosystem changes across various + spatial and temporal scales. This integrated approach and its specialized functions can enhance + the efficiency of processing and analyzing NFI data, providing researchers with insights into + forest ecosystems. The NFI Excel files (.xlsx) are not included in the R package and must be + downloaded separately. Users can access these NFI Excel files by visiting + the Korea Forest Service Forestry Statistics Platform + to download the annual NFI Excel files, which are bundled in .zip archives. Please note that this + website is only available in Korean, and direct download links can be found in the notes section + of the read_nfi() function. + date_publication: '2024-12-03' + bug_reports: https://github.com/SYOUNG9836/knfi/issues + url: https://syoung9836.github.io/knfi/ + url_cran: https://CRAN.R-project.org/package=knfi + url_git: https://github.com/SYOUNG9836/knfi +knitcitations: + version: 1.0.12 + title: Citations for 'Knitr' Markdown Files + maintainer: Carl Boettiger + description: |- + Provides the ability to create dynamic citations + in which the bibliographic information is pulled from the web rather + than having to be entered into a local database such as 'bibtex' ahead of + time. The package is primarily aimed at authoring in the R 'markdown' + format, and can provide outputs for web-based authoring such as linked + text for inline citations. Cite using a 'DOI', URL, or + 'bibtex' file key. See the package URL for details. + date_publication: '2021-01-10' + bug_reports: https://github.com/cboettig/knitcitations/issues + url: '' + url_cran: https://CRAN.R-project.org/package=knitcitations + url_git: https://github.com/cboettig/knitcitations +knitLatex: + version: 0.9.0 + title: '''Knitr'' Helpers - Mostly Tables' + maintainer: John Shea + description: |- + Provides several helper functions for working with 'knitr' and 'LaTeX'. + It includes 'xTab' for creating traditional 'LaTeX' tables, 'lTab' for generating + 'longtable' environments, and 'sTab' for generating a 'supertabular' environment. + Additionally, this package contains a knitr_setup() function which fixes a + well-known bug in 'knitr', which distorts the 'results="asis"' command when used + in conjunction with user-defined commands; and a com command (<>=) + which renders the output from 'knitr' as a 'LaTeX' command. + date_publication: '2015-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=knitLatex + url_git: '' +knitr: + version: '1.49' + title: A General-Purpose Package for Dynamic Report Generation in R + maintainer: Yihui Xie + description: |- + Provides a general-purpose tool for dynamic report generation in R + using Literate Programming techniques. + date_publication: '2024-11-08' + bug_reports: https://github.com/yihui/knitr/issues + url: https://yihui.org/knitr/ + url_cran: https://CRAN.R-project.org/package=knitr + url_git: '' +knitrBootstrap: + version: 1.0.3 + title: '''knitr'' Bootstrap Framework' + maintainer: Jim Hester + description: |- + A framework to create Bootstrap HTML reports from 'knitr' + 'rmarkdown'. + date_publication: '2024-02-06' + bug_reports: https://github.com/jimhester/knitrBootstrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=knitrBootstrap + url_git: https://github.com/jimhester/knitrBootstrap#readme +knitrdata: + version: 0.6.1 + title: Data Language Engine for 'knitr' / 'rmarkdown' + maintainer: David M. Kaplan + description: |- + Implements a data language engine for incorporating data directly in + 'rmarkdown' documents so that they can be made completely standalone. + date_publication: '2020-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=knitrdata + url_git: https://github.com/dmkaplan2000/knitrdata +knitrProgressBar: + version: 1.1.1 + title: Provides Progress Bars in 'knitr' + maintainer: Robert M Flight + description: |- + Provides a progress bar similar to 'dplyr' that can write progress out to a + variety of locations, including stdout(), stderr(), or from file(). Useful when using 'knitr' or 'rmarkdown', + and you still want to see progress of calculations in the terminal. + date_publication: '2024-07-23' + bug_reports: https://github.com/rmflight/knitrProgressBar/issues + url: https://rmflight.github.io/knitrProgressBar/ + url_cran: https://CRAN.R-project.org/package=knitrProgressBar + url_git: '' +knitxl: + version: 0.1.0 + title: Generates a Spreadsheet Report from an 'rmarkdown' File + maintainer: Denis Dreano + description: |- + Convert an R Markdown documents into an '.xlsx' spreadsheet reports + with the knitxl() function, which works similarly to knit() from the + 'knitr' package. The generated report can be opened in 'Excel' or similar + software for further analysis and presentation. + date_publication: '2023-04-18' + bug_reports: https://github.com/dreanod/knitxl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=knitxl + url_git: https://github.com/dreanod/knitxl +knn.covertree: + version: '1.0' + title: An Accurate kNN Implementation with Multiple Distance Measures + maintainer: Philipp Angerer + description: |2- + + Similarly to the 'FNN' package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. + The implementation is based on cover trees introduced by + Alina Beygelzimer, Sham Kakade, and John Langford (2006) . + date_publication: '2019-10-28' + bug_reports: https://github.com/flying-sheep/knn.covertree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=knn.covertree + url_git: https://github.com/flying-sheep/knn.covertree +knnmi: + version: '1.0' + title: k-Nearest Neighbor Mutual Information Estimator + maintainer: Brian Gregor + description: |- + This is a 'C++' mutual information (MI) library based on the k-nearest + neighbor (KNN) algorithm. There are three functions provided for computing MI + for continuous values, mixed continuous and discrete values, and conditional MI + for continuous values. They are based on algorithms by A. Kraskov, et. al. (2004) , + BC Ross (2014), + and A. Tsimpiris (2012) , respectively. + date_publication: '2024-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=knnmi + url_git: '' +knnp: + version: 2.0.0 + title: |- + Time Series Prediction using K-Nearest Neighbors Algorithm + (Parallel) + maintainer: Daniel Bastarrica Lacalle + description: |- + Two main functionalities are provided. One of them is predicting values with + k-nearest neighbors algorithm and the other is optimizing the parameters k and d of the algorithm. + These are carried out in parallel using multiple threads. + date_publication: '2020-01-10' + bug_reports: https://github.com/Grasia/knnp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=knnp + url_git: https://github.com/Grasia/knnp +KNNShiny: + version: 0.1.0 + title: Interactive Document for Working with KNN Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of K-nearest neighbour (KNN) + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KNNShiny + url_git: '' +kNNvs: + version: 0.1.0 + title: k Nearest Neighbors with Grid Search Variable Selection + maintainer: Eddie Pei + description: k Nearest Neighbors with variable selection, combine grid search and + forward selection to achieve variable selection in order to improve k Nearest + Neighbors predictive performance. + date_publication: '2021-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kNNvs + url_git: '' +knnwtsim: + version: 1.0.0 + title: K Nearest Neighbor Forecasting with a Tailored Similarity Metric + maintainer: Matthew Trupiano + description: Functions to implement K Nearest Neighbor forecasting using a weighted + similarity metric tailored to the problem of forecasting univariate time series + where recent observations, seasonal patterns, and exogenous predictors are all + relevant in predicting future observations of the series in question. For more + information on the formulation of this similarity metric please see Trupiano (2021) + . + date_publication: '2022-03-05' + bug_reports: https://github.com/mtrupiano1/knnwtsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=knnwtsim + url_git: https://github.com/mtrupiano1/knnwtsim +knockoff: + version: 0.3.6 + title: The Knockoff Filter for Controlled Variable Selection + maintainer: Matteo Sesia + description: |- + The knockoff filter is a general procedure for controlling the false discovery rate (FDR) + when performing variable selection. + For more information, see the website below and the accompanying paper: Candes et al., + "Panning for gold: model-X knockoffs for high-dimensional controlled variable selection", + J. R. Statist. Soc. B (2018) 80, 3, pp. 551-577. + date_publication: '2022-08-15' + bug_reports: '' + url: https://web.stanford.edu/group/candes/knockoffs/index.html + url_cran: https://CRAN.R-project.org/package=knockoff + url_git: '' +KnockoffHybrid: + version: 1.0.1 + title: |- + Hybrid Analysis of Population and Trio Data with Knockoff + Statistics for FDR Control + maintainer: Yi Yang + description: 'Identification of putative causal variants in genome-wide association + studies using hybrid analysis of both the trio and population designs. The package + implements the method in the paper: Yang, Y., Wang, Q., Wang, C., Buxbaum, J., + & Ionita-Laza, I. (2024). KnockoffHybrid: A knockoff framework for hybrid analysis + of trio and population designs in genome-wide association studies. The American + Journal of Human Genetics, in press.' + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KnockoffHybrid + url_git: '' +KnockoffScreen: + version: 0.3.0 + title: Whole-Genome Sequencing Data Analysis via Knockoff Statistics + maintainer: Zihuai He + description: Functions for identification of putative causal loci in whole-genome + sequencing data. The functions allow genome-wide association scan. It also includes + an efficient knockoff generator for genetic data. + date_publication: '2021-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KnockoffScreen + url_git: '' +KnockoffTrio: + version: 1.1.0 + title: |- + GWAS with Trio and Duo Data using Knockoff Statistics for FDR + Control + maintainer: Yi Yang + description: 'Identification of putative causal variants in genome-wide association + studies with trio and duo families. The package calculates the W feature statistics + from KnockoffTrio and p-values from the family-based association test (FBAT) using + trio and/or duo data. Compared to previous versions, a significant improvement + has been made in Version 1.1.0 to allow the package to be applied not only to + trio families but also to duo families. The package implements the methods in + the paper: "Yang, Y., Wang, C., Liu, L., Buxbaum, J., He, Z., & Ionita-Laza, I. + (2022). KnockoffTrio: A knockoff framework for the identification of putative + causal variants in genome-wide association studies with trio design. The American + Journal of Human Genetics, 109(10), 1761-1776."' + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KnockoffTrio + url_git: '' +knotR: + version: 1.0-4 + title: Knot Diagrams using Bezier Curves + maintainer: Robin K. S. Hankin + description: Makes visually pleasing diagrams of knot projections using optimized + Bezier curves. + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=knotR + url_git: '' +KnowBR: + version: '2.2' + title: |- + Discriminating Well Surveyed Spatial Units from Exhaustive + Biodiversity Databases + maintainer: Castor Guisande Gonzalez + description: It uses species accumulation curves and diverse estimators to assess, + at the same time, the levels of survey coverage in multiple geographic cells of + a size defined by the user or polygons. It also enables the geographical depiction + of observed species richness, survey effort and completeness values including + a background with administrative areas. + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KnowBR + url_git: '' +kntnr: + version: 0.4.4 + title: R Client for 'kintone' API + maintainer: Hiroaki Yutani + description: |- + Retrieve data from 'kintone' () via its API. + 'kintone' is an enterprise application platform. + date_publication: '2020-04-08' + bug_reports: https://github.com/yutannihilation/kntnr/issues + url: https://yutannihilation.github.io/kntnr/ + url_cran: https://CRAN.R-project.org/package=kntnr + url_git: '' +KoboconnectR: + version: 2.0.0 + title: Download Data from Kobotoolbox to R + maintainer: Asitav Sen + description: Wrapper for 'Kobotoolbox' APIs ver 2 mentioned at , + to download data from 'Kobotoolbox' to R. Small and simple package that adds immense + convenience for the data professionals using 'Kobotoolbox'. + date_publication: '2024-08-21' + bug_reports: https://github.com/asitav-sen/koboconnectR/issues + url: https://asitav-sen.github.io/KoboconnectR/ + url_cran: https://CRAN.R-project.org/package=KoboconnectR + url_git: https://github.com/asitav-sen/KoboconnectR +KODAMA: + version: 2.4.1 + title: Knowledge Discovery by Accuracy Maximization + maintainer: Stefano Cacciatore + description: |- + An unsupervised and semi-supervised learning algorithm that performs feature extraction + from noisy and high-dimensional data. It facilitates identification of patterns representing underlying + groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. + (2017) Bioinformatics and Cacciatore S, Luchinat C, Tenori L. (2014) + Proc Natl Acad Sci USA . + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KODAMA + url_git: '' +kofdata: + version: 0.2.1 + title: Get Data from the 'KOF Datenservice' API + maintainer: Matthias Bannert + description: Read Swiss time series data from the 'KOF Data' API, . + The API provides macro economic time series data mostly about Switzerland. The + package itself is a set of wrappers around the 'KOF Datenservice' API. The 'kofdata' + package is able to consume public information as well as data that requires an + API token. + date_publication: '2024-02-03' + bug_reports: https://github.com/KOF-ch/kofdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kofdata + url_git: https://github.com/KOF-ch/kofdata +KOFM: + version: 0.1.1 + title: Test the Kronecker Product Structure in Tensor Factor Models + maintainer: Zetai Cen + description: To test if a tensor time series following a Tucker-decomposition factor + model has a Kronecker product structure. Supplementary functions for tensor reshape + and its reversal are also included. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KOFM + url_git: '' +kofnGA: + version: '1.3' + title: A Genetic Algorithm for Fixed-Size Subset Selection + maintainer: Mark A. Wolters + description: |- + Provides a function that uses a genetic algorithm to search for a subset + of size k from the integers 1:n, such that a user-supplied objective function + is minimized at that subset. The selection step is done by tournament selection + based on ranks, and elitism may be used to retain a portion of the best solutions + from one generation to the next. Population objective function values may + optionally be evaluated in parallel. + date_publication: '2018-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kofnGA + url_git: '' +KOGMWU: + version: '1.2' + title: Functional Summary and Meta-Analysis of Gene Expression Data + maintainer: Mikhail V. Matz + description: Rank-based tests for enrichment of KOG (euKaryotic Orthologous Groups) + classes with up- or down-regulated genes based on a continuous measure. The meta-analysis + is based on correlation of KOG delta-ranks across datasets (delta-rank is the + difference between mean rank of genes belonging to a KOG class and mean rank of + all other genes). With binary measure (1 or 0 to indicate significant and non-significant + genes), one-tailed Fisher's exact test for over-representation of each KOG class + among significant genes will be performed. + date_publication: '2019-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KOGMWU + url_git: '' +kohonen: + version: 3.0.12 + title: Supervised and Unsupervised Self-Organising Maps + maintainer: Ron Wehrens + description: Functions to train self-organising maps (SOMs). Also interrogation + of the maps and prediction using trained maps are supported. The name of the package + refers to Teuvo Kohonen, the inventor of the SOM. + date_publication: '2023-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kohonen + url_git: '' +kokudosuuchi: + version: 1.0.0 + title: Utilities for 'Kokudo Suuchi' + maintainer: Hiroaki Yutani + description: |- + Provides utilities for 'Kokudo Suuchi', the GIS data service of the Japanese government. + See for more information. + date_publication: '2021-02-23' + bug_reports: https://github.com/yutannihilation/kokudosuuchi/issues + url: https://yutannihilation.github.io/kokudosuuchi/ + url_cran: https://CRAN.R-project.org/package=kokudosuuchi + url_git: https://github.com/yutannihilation/kokudosuuchi +kollaR: + version: 1.0.4 + title: Filtering, Visualization and Analysis of Eye Tracking Data + maintainer: Johan Lundin Kleberg + description: |- + Functions for analysing eye tracking data, including event detection (I-VT, I-DT and two means clustering), + visualizations and area of interest (AOI) based analyses. See separate documentation for each function. The principles underlying I-VT and I-DT filters are described in + Salvucci & Goldberg (2000,\doi{10.1145/355017.355028}). Two-means clustering is described in Hessels et al. (2017, \doi{10.3758/s13428-016-0822-1}). + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kollaR + url_git: '' +komaletter: + version: 0.5.0 + title: Simply Beautiful PDF Letters from Markdown + maintainer: Robert Nuske + description: |- + Write beautiful yet customizable letters in R Markdown and + directly obtain the finished PDF. Smooth generation of PDFs is realized by + 'rmarkdown', the 'pandoc-letter' template and the 'KOMA-Script' letter class. + 'KOMA-Script' provides enhanced replacements for the standard 'LaTeX' classes + with emphasis on typography and versatility. 'KOMA-Script' is particularly + useful for international writers as it handles various paper formats well, + provides layouts for many common window envelope types (e.g. German, US, + French, Japanese) and lets you define your own layouts. The package comes + with a default letter layout based on 'DIN 5008B'. + date_publication: '2023-02-27' + bug_reports: https://github.com/rnuske/komaletter/issues + url: https://rnuske.github.io/komaletter/ + url_cran: https://CRAN.R-project.org/package=komaletter + url_git: https://github.com/rnuske/komaletter +konfound: + version: 1.0.2 + title: Quantify the Robustness of Causal Inferences + maintainer: Joshua M Rosenberg + description: |- + Statistical methods that quantify the conditions necessary to + alter inferences, also known as sensitivity analysis, are becoming + increasingly important to a variety of quantitative sciences. A series + of recent works, including Frank (2000) + and Frank et al. (2013) + extend previous sensitivity analyses by + considering the characteristics of omitted variables or unobserved + cases that would change an inference if such variables or cases were + observed. These analyses generate statements such as "an omitted + variable would have to be correlated at xx with the predictor of + interest (e.g., the treatment) and outcome to invalidate an inference of a + treatment effect". Or "one would have to replace pp percent of the + observed data with nor which the treatment had no effect to invalidate the + inference". + We implement these recent developments of sensitivity analysis and + provide modules to calculate these two robustness indices and generate + such statements in R. In particular, the functions konfound(), + pkonfound() and mkonfound() allow users to calculate the robustness of + inferences for a user's own model, a single published study and + multiple studies respectively. + date_publication: '2024-10-17' + bug_reports: https://github.com/konfound-project/konfound/issues + url: https://konfound-it.org/konfound/ + url_cran: https://CRAN.R-project.org/package=konfound + url_git: https://github.com/konfound-project/konfound +KONPsurv: + version: 1.0.4 + title: 'KONP Tests: Powerful K-Sample Tests for Right-Censored Data' + maintainer: Matan Schlesinger + description: The K-sample omnibus non-proportional hazards (KONP) tests are powerful + non-parametric tests for comparing K (>=2) hazard functions based on right-censored + data (Gorfine, Schlesinger and Hsu, 2020, ). These + tests are consistent against any differences between the hazard functions of the + groups. The KONP tests are often more powerful than other existing tests, especially + under non-proportional hazard functions. + date_publication: '2022-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KONPsurv + url_git: '' +KOR.addrlink: + version: 1.0.1 + title: Matching Address Data to Reference Index + maintainer: Daniel Schürmann + description: |- + Matches a data set with semi-structured address data, + e.g., street and house number as a concatenated string, + wrongly spelled street names or non-existing house numbers to a + reference index. The methods are specifically designed for German + municipalities ('KOR'-community) and German address schemes. + date_publication: '2024-03-05' + bug_reports: https://git-kor.stadtdo.de/stadt-dortmund/adressdaten/-/issues + url: https://git-kor.stadtdo.de + url_cran: https://CRAN.R-project.org/package=KOR.addrlink + url_git: '' +koRpus: + version: 0.13-8 + title: |- + Text Analysis with Emphasis on POS Tagging, Readability, and + Lexical Diversity + maintainer: Meik Michalke + description: |- + A set of tools to analyze texts. Includes, amongst others, functions for + automatic language detection, hyphenation, several indices of lexical diversity + (e.g., type token ratio, HD-D/vocd-D, MTLD) and readability (e.g., Flesch, + SMOG, LIX, Dale-Chall). Basic import functions for language corpora are also + provided, to enable frequency analyses (supports Celex and Leipzig Corpora + Collection file formats) and measures like tf-idf. Note: For full functionality + a local installation of TreeTagger is recommended. It is also recommended to + not load this package directly, but by loading one of the available language + support packages from the 'l10n' repository + . 'koRpus' also includes a plugin + for the R GUI and IDE RKWard, providing graphical dialogs for its basic + features. The respective R package 'rkward' cannot be installed directly from a + repository, as it is a part of RKWard. To make full use of this feature, please + install RKWard from (plugins are detected + automatically). Due to some restrictions on CRAN, the full package sources are + only available from the project homepage. To ask for help, report bugs, request + features, or discuss the development of the package, please subscribe to the + koRpus-dev mailing list (). + date_publication: '2021-05-17' + bug_reports: https://github.com/unDocUMeantIt/koRpus/issues + url: https://reaktanz.de/?c=hacking&s=koRpus + url_cran: https://CRAN.R-project.org/package=koRpus + url_git: '' +koRpus.lang.en: + version: 0.1-4 + title: 'Language Support for ''koRpus'' Package: English' + maintainer: Meik Michalke + description: |- + Adds support for the English language to the 'koRpus' package. To ask for help, report bugs, suggest feature improvements, or discuss the global development of the + package, please consider subscribing to the koRpus-dev mailing list (). + date_publication: '2020-10-24' + bug_reports: https://github.com/unDocUMeantIt/koRpus.lang.en/issues + url: https://reaktanz.de/?c=hacking&s=koRpus + url_cran: https://CRAN.R-project.org/package=koRpus.lang.en + url_git: '' +kosel: + version: 0.0.1 + title: Variable Selection by Revisited Knockoffs Procedures + maintainer: Clemence Karmann + description: 'Performs variable selection for many types of L1-regularised regressions + using the revisited knockoffs procedure. This procedure uses a matrix of knockoffs + of the covariates independent from the response variable Y. The idea is to determine + if a covariate belongs to the model depending on whether it enters the model before + or after its knockoff. The procedure suits for a wide range of regressions with + various types of response variables. Regression models available are exported + from the R packages ''glmnet'' and ''ordinalNet''. Based on the paper linked to + via the URL below: Gegout A., Gueudin A., Karmann C. (2019) .' + date_publication: '2019-07-18' + bug_reports: '' + url: https://arxiv.org/pdf/1907.03153.pdf + url_cran: https://CRAN.R-project.org/package=kosel + url_git: '' +kosis: + version: 0.0.1 + title: Korean Statistical Information Service (KOSIS) + maintainer: Seokhoon Joo + description: |- + API wrapper to download statistical information from the + Korean Statistical Information Service (KOSIS) + . + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kosis + url_git: '' +KoulMde: + version: 3.2.1 + title: |- + Koul's Minimum Distance Estimation in Regression and Image + Segmentation Problems + maintainer: Jiwoong Kim + description: |- + Many methods are developed to deal with two major statistical problems: image segmentation + and nonparametric estimation in various regression models. Image segmentation is nowadays + gaining a lot of attention from various scientific subfields. Especially, image segmentation + has been popular in medical research such as magnetic resonance imaging (MRI) analysis. When + a patient suffers from some brain diseases such as dementia and Parkinson's disease, + those diseases can be easily diagnosed in brain MRI: the area affected by those diseases is + brightly expressed in MRI, which is called a white lesion. For the purpose of medical research, + locating and segment those white lesions in MRI is a critical issue; it can be done + manually. However, manual segmentation is very expensive in that it is error-prone and demands a huge + amount of time. Therefore, supervised machine learning has emerged as an alternative solution. + Despite its powerful performance in a classification problem such as hand-written digits, supervised + machine learning has not shown the same satisfactory result in MRI analysis. Setting aside all issues + of the supervised machine learning, it exposed a critical problem when employed for MRI analysis: it + requires time-consuming data labeling. Thus, there is a strong demand for an unsupervised approach, + and this package - based on Hira L. Koul (1986) - proposes an efficient + method for simple image segmentation - here, "simple" means that an image is black-and-white - which + can easily be applied to MRI analysis. This package includes a function GetSegImage(): when a black-and-white + image is given as an input, GetSegImage() separates an area of white pixels - which corresponds to + a white lesion in MRI - from the given image. For the second problem, consider linear regression model and autoregressive model of + order q where errors in the linear regression model and innovations in the + autoregression model are independent and symmetrically distributed. Hira L. Koul + (1986) proposed a nonparametric minimum distance + estimation method by minimizing L2-type distance between certain weighted + residual empirical processes. He also proposed a simpler version of the loss + function by using symmetry of the integrating measure in the distance. Kim + (2018) proposed a fast computational method + which enables practitioners to compute the minimum distance estimator of the vector + of general multiple regression parameters for several integrating measures. This + package contains three functions: KoulLrMde(), KoulArMde(), and Koul2StageMde(). + The former two provide minimum distance estimators for linear regression model + and autoregression model, respectively, where both are based on Koul's method. + These two functions take much less time for the computation than those based + on parametric minimum distance estimation methods. Koul2StageMde() provides + estimators for regression and autoregressive coefficients of linear regression + model with autoregressive errors through minimum distant method of two stages. + The new version is written in Rcpp and dramatically reduces computational time. + date_publication: '2020-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KoulMde + url_git: '' +Kpart: + version: 1.2.2 + title: Cubic Spline Fitting with Knot Selection + maintainer: Eric Golinko + description: Cubic spline fitting along with knot selection, includes support for + additional variables. + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kpart + url_git: '' +KPC: + version: 0.1.2 + title: Kernel Partial Correlation Coefficient + maintainer: Zhen Huang + description: |- + Implementations of two empirical versions the kernel partial correlation (KPC) coefficient + and the associated variable selection algorithms. KPC is a measure of the strength of conditional + association between Y and Z given X, with X, Y, Z being random variables taking values in + general topological spaces. As the name suggests, KPC is defined in terms of kernels on + reproducing kernel Hilbert spaces (RKHSs). The population KPC is a deterministic number + between 0 and 1; it is 0 if and only if Y is conditionally independent of Z given X, and it is 1 if + and only if Y is a measurable function of Z and X. One empirical KPC estimator is based on + geometric graphs, such as K-nearest neighbor graphs and minimum spanning trees, and is + consistent under very weak conditions. The other empirical estimator, defined using conditional + mean embeddings (CMEs) as used in the RKHS literature, is also consistent under suitable + conditions. Using KPC, a stepwise forward variable selection algorithm KFOCI (using the graph + based estimator of KPC) is provided, as well as a similar stepwise forward selection algorithm + based on the RKHS based estimator. For more details on KPC, its empirical estimators and its + application on variable selection, see Huang, Z., N. Deb, and B. Sen (2022). “Kernel partial + correlation coefficient – a measure of conditional dependence” (URL listed below). When X is + empty, KPC measures the unconditional dependence between Y and Z, which has been described + in Deb, N., P. Ghosal, and B. Sen (2020), “Measuring association on topological spaces using + kernels and geometric graphs” , and it is implemented in the functions + KMAc() and Klin() in this package. The latter can be computed in near linear time. + date_publication: '2022-10-05' + bug_reports: '' + url: https://www.jmlr.org/papers/v23/21-493.html + url_cran: https://CRAN.R-project.org/package=KPC + url_git: '' +kpcaIG: + version: '1.0' + title: Variables Interpretability with Kernel PCA + maintainer: Mitja Briscik + description: The kernelized version of principal component analysis (KPCA) has proven + to be a valid nonlinear alternative for tackling the nonlinearity of biological + sample spaces. However, it poses new challenges in terms of the interpretability + of the original variables. 'kpcaIG' aims to provide a tool to select the most + relevant variables based on the kernel PCA representation of the data as in Briscik + et al. (2023) . It also includes functions for + 2D and 3D visualization of the original variables (as arrows) into the kernel + principal components axes, highlighting the contribution of the most important + ones. + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kpcaIG + url_git: '' +kpcalg: + version: 1.0.1 + title: Kernel PC Algorithm for Causal Structure Detection + maintainer: Petras Verbyla + description: Kernel PC (kPC) algorithm for causal structure learning and causal + inference using graphical models. kPC is a version of PC algorithm that uses kernel + based independence criteria in order to be able to deal with non-linear relationships + and non-Gaussian noise. + date_publication: '2017-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kpcalg + url_git: '' +kpeaks: + version: 1.1.0 + title: Determination of K Using Peak Counts of Features for Clustering + maintainer: Zeynel Cebeci + description: The number of clusters (k) is needed to start all the partitioning + clustering algorithms. An optimal value of this input argument is widely determined + by using some internal validity indices. Since most of the existing internal indices + suggest a k value which is computed from the clustering results after several + runs of a clustering algorithm they are computationally expensive. On the contrary, the + package 'kpeaks' enables to estimate k before running any clustering algorithm. + It is based on a simple novel technique using the descriptive statistics of peak + counts of the features in a data set. + date_publication: '2020-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kpeaks + url_git: '' +kpiwidget: + version: 0.1.1 + title: KPI Widgets for Quarto Dashboards with Crosstalk + maintainer: Arnold Kakas + description: Provides an easy way to create interactive KPI (key performance indicator) + widgets for 'Quarto' dashboards using 'Crosstalk'. The package enables visualization + of key metrics in a structured format, supporting interactive filtering and linking + with other 'Crosstalk'-enabled components. Designed for use in 'Quarto' Dashboards. + date_publication: '2025-02-09' + bug_reports: https://github.com/Arnold-Kakas/kpiwidget/issues + url: https://arnold-kakas.github.io/kpiwidget/ + url_cran: https://CRAN.R-project.org/package=kpiwidget + url_git: https://github.com/Arnold-Kakas/kpiwidget +kpmt: + version: 0.1.0 + title: Known Population Median Test + maintainer: Matthew M Parks + description: Functions that implement the known population median test. + date_publication: '2017-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kpmt + url_git: '' +kpodclustr: + version: '1.1' + title: Method for Clustering Partially Observed Data + maintainer: Jocelyn T. Chi + description: |- + Software for k-means clustering of partially + observed data from Chi, Chi, and Baraniuk (2016) . + date_publication: '2020-06-24' + bug_reports: '' + url: http://jocelynchi.com/kpodclustr + url_cran: https://CRAN.R-project.org/package=kpodclustr + url_git: '' +KrakenR: + version: 1.0.0 + title: |- + Comprehensive R Interface for Accessing Kraken Cryptocurrency + Exchange REST API + maintainer: Nathanaël Dürst + description: |- + A comprehensive R interface to access data from the Kraken cryptocurrency exchange REST API . + It allows users to retrieve various market data, such as asset information, trading pairs, and price data. + The package is designed to facilitate efficient data access for analysis, strategy development, and monitoring of cryptocurrency market trends. + date_publication: '2024-10-22' + bug_reports: https://github.com/nathanael-g-durst/KrakenR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KrakenR + url_git: https://github.com/nathanael-g-durst/KrakenR +KraljicMatrix: + version: 0.2.1 + title: A Quantified Implementation of the Kraljic Matrix + maintainer: Bradley Boehmke + description: |- + Implements a quantified approach to the Kraljic Matrix (Kraljic, 1983, ) + for strategically analyzing a firm’s purchasing portfolio. It combines multi-objective decision analysis to measure purchasing characteristics and + uses this information to place products and services within the Kraljic Matrix. + date_publication: '2018-03-06' + bug_reports: https://github.com/koalaverse/KraljicMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KraljicMatrix + url_git: https://github.com/koalaverse/KraljicMatrix +kriens: + version: '0.1' + title: Continuation Passing Style Development + maintainer: Matteo Provenzano + description: Provides basic functions for Continuation-Passing Style development. + date_publication: '2015-12-02' + bug_reports: '' + url: http://www.alephdue.com + url_cran: https://CRAN.R-project.org/package=kriens + url_git: '' +krige: + version: 0.6.2 + title: Geospatial Kriging with Metropolis Sampling + maintainer: Jason S. Byers + description: Estimates kriging models for geographical point-referenced data. Method + is described in Gill (2020) . + date_publication: '2022-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=krige + url_git: '' +kriging: + version: '1.2' + title: Ordinary Kriging + maintainer: Omar E. Olmedo + description: An implementation of a simple and highly optimized ordinary kriging + algorithm to plot geographical data. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kriging + url_git: '' +KrigInv: + version: 1.4.2 + title: |- + Kriging-Based Inversion for Deterministic and Noisy Computer + Experiments + maintainer: Dario Azzimonti + description: Criteria and algorithms for sequentially estimating level sets of a + multivariate numerical function, possibly observed with noise. + date_publication: '2022-09-09' + bug_reports: '' + url: https://doi.org/10.1016/j.csda.2013.03.008 + url_cran: https://CRAN.R-project.org/package=KrigInv + url_git: '' +krippendorffsalpha: + version: '2.0' + title: Measuring Agreement Using Krippendorff's Alpha Coefficient + maintainer: John Hughes + description: Provides tools for applying Krippendorff's Alpha methodology . + Both the customary methodology and Hughes' methodology + are supported, the former being preferred for larger datasets, the latter for + smaller datasets. The framework supports common and user-defined distance functions, + and can accommodate any number of units, any number of coders, and missingness. + Interval estimation can be done in parallel for either methodology. + date_publication: '2022-10-25' + bug_reports: '' + url: http://www.johnhughes.org + url_cran: https://CRAN.R-project.org/package=krippendorffsalpha + url_git: '' +KRIS: + version: 1.1.6 + title: |- + Keen and Reliable Interface Subroutines for Bioinformatic + Analysis + maintainer: Kridsadakorn Chaichoompu + description: Provides useful functions which are needed for bioinformatic analysis + such as calculating linear principal components from numeric data and Single-nucleotide + polymorphism (SNP) dataset, calculating fixation index (Fst) using Hudson method, + creating scatter plots in 3 views, handling with PLINK binary file format, detecting + rough structures and outliers using unsupervised clustering, and calculating matrix + multiplication in the faster way for big data. + date_publication: '2021-01-21' + bug_reports: https://gitlab.com/kris.ccp/kris/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KRIS + url_git: https://gitlab.com/kris.ccp/kris +KRLS: + version: 1.0-0 + title: Kernel-Based Regularized Least Squares + maintainer: Jens Hainmueller + description: Package implements Kernel-based Regularized Least Squares (KRLS), a + machine learning method to fit multidimensional functions y=f(x) for regression + and classification problems without relying on linearity or additivity assumptions. + KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov + regularization problem, using Gaussian kernels as radial basis functions. For + further details see Hainmueller and Hazlett (2014). + date_publication: '2017-07-10' + bug_reports: '' + url: https://www.stanford.edu/~jhain/ + url_cran: https://CRAN.R-project.org/package=KRLS + url_git: '' +krm: + version: 2022.10-17 + title: Kernel Based Regression Models + maintainer: Youyi Fong + description: Implements several methods for testing the variance component parameter + in regression models that contain kernel-based random effects, including a maximum + of adjusted scores test. Several kernels are supported, including a profile hidden + Markov model mutual information kernel for protein sequence. This package is described + in Fong et al. (2015) . + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=krm + url_git: '' +KRMM: + version: '1.0' + title: Kernel Ridge Mixed Model + maintainer: Laval Jacquin + description: Solves kernel ridge regression, within the the mixed model framework, + for the linear, polynomial, Gaussian, Laplacian and ANOVA kernels. The model components + (i.e. fixed and random effects) and variance parameters are estimated using the + expectation-maximization (EM) algorithm. All the estimated components and parameters, + e.g. BLUP of dual variables and BLUP of random predictor effects for the linear + kernel (also known as RR-BLUP), are available. The kernel ridge mixed model (KRMM) + is described in Jacquin L, Cao T-V and Ahmadi N (2016) A Unified and Comprehensible + View of Parametric and Kernel Methods for Genomic Prediction with Application + to Rice. Front. Genet. 7:145. . + date_publication: '2017-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KRMM + url_git: '' +kronos: + version: 1.0.0 + title: Microbiome Oriented Circadian Rhythm Analysis Toolkit + maintainer: Thomaz Bastiaanssen + description: The goal of 'kronos' is to provide an easy-to-use framework to analyse + circadian or otherwise rhythmic data using the familiar R linear modelling syntax, + while taking care of the trigonometry under the hood. + date_publication: '2023-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kronos + url_git: https://github.com/thomazbastiaanssen/kronos +ks: + version: 1.14.3 + title: Kernel Smoothing + maintainer: Tarn Duong + description: Kernel smoothers for univariate and multivariate data, with comprehensive + visualisation and bandwidth selection capabilities, including for densities, density + derivatives, cumulative distributions, clustering, classification, density ridges, + significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) + . + date_publication: '2024-09-20' + bug_reports: '' + url: https://www.mvstat.net/mvksa/ + url_cran: https://CRAN.R-project.org/package=ks + url_git: '' +KSA: + version: 0.1.0 + title: Retained Component Criterion for Principal Component Analysis + maintainer: Dr. Fayed Alshammri + description: The Retained Component Criterion for Principal Component Analysis (RCC_PCA) + is a tool to determine the optimal number of components to retain in PCA. + date_publication: '2022-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KSA + url_git: '' +kSamples: + version: 1.2-10 + title: K-Sample Rank Tests and their Combinations + maintainer: Fritz Scholz + description: |- + Compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests + with different rank score criteria, Steel's multiple comparison test, and the + Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact + P-values, all valid under randomization, with or without ties, or conditionally + under random sampling from populations, given the observed tie pattern. Except for + Steel's test and the JT test it also combines these tests across several blocks of + samples. Also analyzed are 2 x t contingency tables and their blocked combinations + using the Kruskal-Wallis criterion. Steel's test is inverted to provide simultaneous + confidence bounds for shift parameters. A plotting function compares tail probabilities + obtained under asymptotic approximation with those obtained via simulation or exact + calculations. + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kSamples + url_git: '' +KScorrect: + version: 1.4.0 + title: Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests + maintainer: Phil Novack-Gottshall + description: |- + Implements the Lilliefors-corrected Kolmogorov-Smirnov test for use + in goodness-of-fit tests, suitable when population parameters are unknown and + must be estimated by sample statistics. P-values are estimated by simulation. + Can be used with a variety of continuous distributions, including normal, + lognormal, univariate mixtures of normals, uniform, loguniform, exponential, + gamma, and Weibull distributions. Functions to generate random numbers and + calculate density, distribution, and quantile functions are provided for use + with the log uniform and mixture distributions. + date_publication: '2019-07-03' + bug_reports: https://github.com/pnovack-gottshall/KScorrect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=KScorrect + url_git: https://github.com/pnovack-gottshall/KScorrect +KSD: + version: 1.0.1 + title: Goodness-of-Fit Tests using Kernelized Stein Discrepancy + maintainer: Min Hyung Kang + description: An adaptation of Kernelized Stein Discrepancy, this package provides + a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given + distribution. It works for any distribution once its score function (the derivative + of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy + for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available + at . + date_publication: '2021-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KSD + url_git: '' +KSEAapp: + version: 0.99.0 + title: Kinase-Substrate Enrichment Analysis + maintainer: Danica D. Wiredja + description: |- + Infers relative kinase activity from phosphoproteomics data + using the method described by Casado et al. (2013) . + date_publication: '2017-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KSEAapp + url_git: '' +kselection: + version: 0.2.1 + title: Selection of K in K-Means Clustering + maintainer: Daniel Rodriguez + description: |- + Selection of k in k-means clustering based on Pham et al. paper + ``Selection of k in k-means clustering''. + date_publication: '2022-05-16' + bug_reports: https://github.com/drodriguezperez/kselection/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kselection + url_git: https://github.com/drodriguezperez/kselection +KSgeneral: + version: 2.0.2 + title: |- + Computing P-Values of the One-Sample K-S Test and the Two-Sample + K-S and Kuiper Tests for (Dis)Continuous Null Distribution + maintainer: Dimitrina S. Dimitrova + description: 'Contains functions to compute p-values for the one-sample and two-sample + Kolmogorov-Smirnov (KS) tests and the two-sample Kuiper test for any fixed critical + level and arbitrary (possibly very large) sample sizes. For the one-sample KS + test, this package implements a novel, accurate and efficient method named Exact-KS-FFT, + which allows the pre-specified cumulative distribution function under the null + hypothesis to be continuous, purely discrete or mixed. In the two-sample case, + it is assumed that both samples come from an unspecified (unknown) continuous, + purely discrete or mixed distribution, i.e. ties (repeated observations) are allowed, + and exact p-values of the KS and the Kuiper tests are computed. Note, the two-sample + Kuiper test is often used when data samples are on the line or on the circle (circular + data). To cite this package in publication: (for the use of the one-sample KS + test) Dimitrina S. Dimitrova, Vladimir K. Kaishev, and Senren Tan. Computing the + Kolmogorov-Smirnov Distribution When the Underlying CDF is Purely Discrete, Mixed, + or Continuous. Journal of Statistical Software. 2020; 95(10): 1--42. . + (for the use of the two-sample KS and Kuiper tests) Dimitrina S. Dimitrova, Yun + Jia and Vladimir K. Kaishev (2024). The R functions KS2sample and Kuiper2sample: + Efficient Exact Calculation of P-values of the Two-sample Kolmogorov-Smirnov and + Kuiper Tests. submitted.' + date_publication: '2024-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KSgeneral + url_git: https://github.com/d-dimitrova/KSgeneral +ksharp: + version: 0.1.0.1 + title: Cluster Sharpening + maintainer: Tomasz Konopka + description: Clustering typically assigns data points into discrete groups, but + the clusters can sometimes be indistinct. Cluster sharpening adjusts an existing + clustering to create contrast between groups. This package provides a general + interface for cluster sharpening along with several implementations based on different + excision criteria. + date_publication: '2020-01-26' + bug_reports: https://github.com/tkonopka/ksharp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ksharp + url_git: https://github.com/tkonopka/ksharp +ksNN: + version: 0.1.2 + title: K* Nearest Neighbors Algorithm + maintainer: Kei Nakagawa + description: |- + Prediction with k* nearest neighbor algorithm + based on a publication by Anava and Levy (2016) . + date_publication: '2019-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ksNN + url_git: '' +KSPM: + version: 0.2.1 + title: Kernel Semi-Parametric Models + maintainer: Catherine Schramm + description: To fit the kernel semi-parametric model and its extensions. It allows + multiple kernels and unlimited interactions in the same model. Coefficients are + estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters + are estimated by minimizing leave-one-out error. It includes predictions with + confidence/prediction intervals, statistical tests for the significance of each + kernel, a procedure for variable selection and graphical tools for diagnostics + and interpretation of covariate effects. Currently it is implemented for continuous + dependent variables. The package is based on the paper of Liu et al. (2007), . + date_publication: '2020-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KSPM + url_git: '' +ksrlive: + version: '1.0' + title: Identify Kinase Substrate Relationships Using Dynamic Data + maintainer: Westa Domanova + description: Using this package you can combine known kinase substrate relationships + with experimental data and determine active kinases and their substrates. + date_publication: '2015-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ksrlive + url_git: '' +kssa: + version: 0.0.1 + title: Known Sub-Sequence Algorithm + maintainer: Iván Felipe Benavides + description: Implements the Known Sub-Sequence Algorithm , + which helps to automatically identify and validate the best method for missing + data imputation in a time series. Supports the comparison of multiple state-of-the-art + algorithms. + date_publication: '2022-06-21' + bug_reports: https://github.com/pipeben/kssa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=kssa + url_git: https://github.com/pipeben/kssa +kst: + version: 0.5-4 + title: Knowledge Space Theory + maintainer: Cord Hockemeyer + description: |- + Knowledge space theory by Doignon and Falmagne (1999) + is a set- and order-theoretical + framework, which proposes mathematical formalisms to operationalize + knowledge structures in a particular domain. The 'kst' package provides + basic functionalities to generate, handle, and manipulate knowledge + structures and knowledge spaces. + date_publication: '2022-10-24' + bug_reports: '' + url: https://homepage.uni-graz.at/en/cord.hockemeyer/ + url_cran: https://CRAN.R-project.org/package=kst + url_git: '' +kStatistics: + version: 2.1.1 + title: |- + Unbiased Estimators for Cumulant Products and Faa Di Bruno's + Formula + maintainer: Giuseppe Guarino + description: Tools for estimate (joint) cumulants and (joint) products of cumulants + of a random sample using (multivariate) k-statistics and (multivariate) polykays, + unbiased estimators with minimum variance. Tools for generating univariate and + multivariate Faa di Bruno's formula and related polynomials, such as Bell polynomials, + generalized complete Bell polynomials, partition polynomials and generalized partition + polynomials. For more details see Di Nardo E., Guarino G., Senato D. (2009) , + . + date_publication: '2022-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kStatistics + url_git: '' +kstIO: + version: 0.4-1 + title: Knowledge Space Theory Input/Output + maintainer: Cord Hockemeyer + description: |- + Knowledge space theory by Doignon and Falmagne (1999) + is a set- and order-theoretical + framework which proposes mathematical formalisms to operationalize + knowledge structures in a particular domain. The 'kstIO' package + provides basic functionalities to read and write KST data from/to + files to be used together with the 'kst', 'kstMatrix', 'CDSS', 'pks', or + 'DAKS' packages. + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kstIO + url_git: '' +kstMatrix: + version: 1.1-0 + title: |- + Basic Functions in Knowledge Space Theory Using Matrix + Representation + maintainer: Cord Hockemeyer + description: |- + Knowledge space theory by Doignon and Falmagne (1999) + is a set- and order-theoretical + framework, which proposes mathematical formalisms to operationalize + knowledge structures in a particular domain. The 'kstMatrix' package + provides basic functionalities to generate, handle, and manipulate + knowledge structures and knowledge spaces. Opposed to the 'kst' + package, 'kstMatrix' uses matrix representations for knowledge + structures. Furthermore, 'kstMatrix' contains several knowledge spaces + developed by the research group around Cornelia Dowling through + querying experts. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kstMatrix + url_git: '' +ktaucenters: + version: 1.0.0 + title: Robust Clustering Procedures + maintainer: Juan Domingo Gonzalez + description: |- + A clustering algorithm similar to K-Means is implemented, it has two main advantages, + namely (a) The estimator is resistant to outliers, that means that results of estimator are still correct when + there are atypical values in the sample and (b) The estimator is efficient, roughly speaking, + if there are no outliers in the sample, results will be similar to those obtained by a classic algorithm (K-Means). + Clustering procedure is carried out by minimizing the overall robust scale so-called tau scale. + (see Gonzalez, Yohai and Zamar (2019) ). + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ktaucenters + url_git: '' +KTensorGraphs: + version: '1.1' + title: Co-Tucker3 Analysis of Two Sequences of Matrices + maintainer: Miguel Rodriguez-Rosa + description: |- + Provides a function called COTUCKER3() (Co-Inertia Analysis + + Tucker3 method) which performs a Co-Tucker3 analysis of two sequences of + matrices, as well as other functions called PCA() (Principal Component Analysis) + and BGA() (Between-Groups Analysis), which perform analysis of one matrix, + COIA() (Co-Inertia Analysis), which performs analysis of two matrices, PTA() + (Partial Triadic Analysis), STATIS(), STATISDUAL() and TUCKER3(), which perform analysis of a sequence + of matrices, and BGCOIA() (Between-Groups Co-Inertia Analysis), STATICO() + (STATIS method + Co-Inertia Analysis), COSTATIS() (Co-Inertia Analysis + STATIS + method), which also perform analysis of two sequences of matrices. + date_publication: '2020-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=KTensorGraphs + url_git: '' +ktsolve: + version: 1.3.1 + title: |- + Configurable Function for Solving Families of Nonlinear + Equations + maintainer: Carl Witthoft + description: |- + This is designed for use with an arbitrary set of equations with + an arbitrary set of unknowns. + The user selects "fixed" values for enough unknowns to leave as many variables as + there are equations, which in most cases means the system is properly + defined and a unique solution exists. The function, the fixed values + and initial values for the remaining unknowns are fed to a nonlinear backsolver. + The original version of "TK!Solver" , now a product of Universal Technical Systems () was the inspiration for this function. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ktsolve + url_git: '' +ktweedie: + version: 1.0.3 + title: |- + 'Tweedie' Compound Poisson Model in the Reproducing Kernel + Hilbert Space + maintainer: Yi Lian + description: Kernel-based 'Tweedie' compound Poisson gamma model using high-dimensional + predictors for the analyses of zero-inflated response variables. The package features + built-in estimation, prediction and cross-validation tools and supports choice + of different kernel functions. For more details, please see Yi Lian, Archer Yi + Yang, Boxiang Wang, Peng Shi & Robert William Platt (2023) . + date_publication: '2023-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ktweedie + url_git: '' +kuiper.2samp: + version: '1.0' + title: Two-Sample Kuiper Test + maintainer: Ying Ruan + description: This function performs the two-sample Kuiper test to assess the anomaly + of continuous, one-dimensional probability distributions. References used for + this method are (1). Kuiper, N. H. (1960). + and (2). Paltani, S. (2004). . + date_publication: '2018-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kuiper.2samp + url_git: '' +Kurt: + version: '1.1' + title: Performs Kurtosis-Based Statistical Analyses + maintainer: Cinzia Franceschini + description: |- + Computes measures of multivariate kurtosis, matrices of fourth-order moments and cumulants, kurtosis-based projection pursuit. + Franceschini, C. and Loperfido, N. (2018, ISBN:978-3-319-73905-2). "An Algorithm for Finding Projections with Extreme Kurtosis". + Loperfido, N. (2017,ISSN:0024-3795). "A New Kurtosis Matrix, with Statistical Applications". + date_publication: '2021-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Kurt + url_git: '' +kutils: + version: '1.73' + title: Project Management Tools + maintainer: Paul Johnson + description: |- + Tools for data importation, recoding, and inspection. + There are functions to create new project + folders, R code templates, create uniquely named output + directories, and to quickly obtain a visual summary for each + variable in a data frame. The main feature here is the systematic + implementation of the "variable key" framework for data + importation and recoding. We are eager to have community feedback + about the variable key and the vignette about it. In version 1.7, + the function 'semTable' is removed. It was deprecated since 1.67. + That is provided in a separate package, 'semTable'. + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kutils + url_git: '' +kvh: + version: 1.4.2 + title: Read/Write Files in Key-Value-Hierarchy Format + maintainer: Serguei Sokol + description: |- + The format KVH is a lightweight format that can be read/written both by humans and machines. + It can be useful in situations where XML or alike formats seem to be an overkill. + We provide an ability to parse KVH files in R pretty fast due to 'Rcpp' use. + date_publication: '2022-01-26' + bug_reports: https://github.com/sgsokol/kvh/issues + url: http://serguei.sokol.free.fr/kvh-format/ + url_cran: https://CRAN.R-project.org/package=kvh + url_git: '' +kyotil: + version: 2024.11-01 + title: |- + Utility Functions for Statistical Analysis Report Generation and + Monte Carlo Studies + maintainer: Youyi Fong + description: Helper functions for creating formatted summary of regression models, + writing publication-ready tables to latex files, and running Monte Carlo experiments. + date_publication: '2024-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kyotil + url_git: '' +kza: + version: 4.1.0.1 + title: Kolmogorov-Zurbenko Adaptive Filters + maintainer: Brian Close + description: Time Series Analysis including break detection, spectral analysis, + KZ Fourier Transforms. + date_publication: '2020-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kza + url_git: '' +kzs: + version: '1.4' + title: Kolmogorov-Zurbenko Spatial Smoothing and Applications + maintainer: Derek Cyr + description: A spatial smoothing algorithm based on convolutions of finite rectangular + kernels that provides sharp resolution in the presence of high levels of noise. + date_publication: '' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=kzs + url_git: '' +l0ara: + version: 0.1.6 + title: |- + Sparse Generalized Linear Model with L0 Approximation for + Feature Selection + maintainer: Wenchuan Guo + description: An efficient procedure for feature selection for generalized linear + models with L0 penalty, including linear, logistic, Poisson, gamma, inverse Gaussian + regression. Adaptive ridge algorithms are used to fit the models. + date_publication: '2020-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=l0ara + url_git: '' +L0Learn: + version: 2.1.0 + title: Fast Algorithms for Best Subset Selection + maintainer: Hussein Hazimeh + description: |- + Highly optimized toolkit for approximately solving L0-regularized learning problems (a.k.a. best subset selection). + The algorithms are based on coordinate descent and local combinatorial search. + For more details, check the paper by Hazimeh and Mazumder (2020) . + date_publication: '2023-03-07' + bug_reports: https://github.com/hazimehh/L0Learn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=L0Learn + url_git: https://github.com/hazimehh/L0Learnhttps://pubsonline.informs.org/doi/10.1287/opre.2019.1919 +l1ball: + version: 0.1.0 + title: L1-Ball Prior for Sparse Regression + maintainer: Maoran Xu + description: Provides function for the l1-ball prior on high-dimensional regression. + The main function, l1ball(), yields posterior samples for linear regression, as + introduced by Xu and Duan (2020) . + date_publication: '2020-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=l1ball + url_git: '' +L1centrality: + version: 0.3.1 + title: Graph/Network Analysis Based on L1 Centrality + maintainer: Seungwoo Kang + description: Analyze graph/network data using L1 centrality and prestige. Functions + for deriving global, local, and group L1 centrality/prestige are provided. Routines + for visual inspection of a graph/network are also provided. Details are in Kang + and Oh (2024a) and Kang and Oh (2024b) . + date_publication: '2025-01-08' + bug_reports: https://github.com/seungwoo-stat/L1centrality/issues + url: '' + url_cran: https://CRAN.R-project.org/package=L1centrality + url_git: https://github.com/seungwoo-stat/L1centrality +l1kdeconv: + version: 1.2.0 + title: Deconvolution for LINCS L1000 Data + maintainer: Zhao Li + description: LINCS L1000 is a high-throughput technology that allows the gene expression + measurement in a large number of assays. However, to fit the measurements of ~1000 + genes in the ~500 color channels of LINCS L1000, every two landmark genes are + designed to share a single channel. Thus, a deconvolution step is required to + infer the expression values of each gene. Any errors in this step can be propagated + adversely to the downstream analyses. We present a LINCS L1000 data peak calling + R package l1kdeconv based on a new outlier detection method and an aggregate Gaussian + mixture model. Upon the remove of outliers and the borrowing information among + similar samples, l1kdeconv shows more stable and better performance than methods + commonly used in LINCS L1000 data deconvolution. + date_publication: '2017-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=l1kdeconv + url_git: '' +L1pack: + version: '0.50' + title: Routines for L1 Estimation + maintainer: Felipe Osorio + description: |- + L1 estimation for linear regression using Barrodale and Roberts' method + and the EM algorithm . + Estimation of mean and covariance matrix using the multivariate Laplace distribution, + density, distribution function, quantile function and random number generation + for univariate and multivariate Laplace distribution . + Implementation of Naik and Plungpongpun for the + Generalized spatial median estimator is included. + date_publication: '2024-09-08' + bug_reports: '' + url: http://l1pack.mat.utfsm.cl/ + url_cran: https://CRAN.R-project.org/package=L1pack + url_git: '' +l1spectral: + version: 0.99.6 + title: An L1-Version of the Spectral Clustering + maintainer: Magali Champion + description: 'Provides an l1-version of the spectral clustering algorithm devoted + to robustly clustering highly perturbed graphs using l1-penalty. This algorithm + is described with more details in the preprint C. Champion, M. Champion, M. Blazère, + R. Burcelin and J.M. Loubes, "l1-spectral clustering algorithm: a spectral clustering + method using l1-regularization" (2022).' + date_publication: '2022-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=l1spectral + url_git: '' +l2boost: + version: 1.0.3 + title: |- + Exploring Friedman's Boosting Algorithm for Regularized Linear + Regression + maintainer: John Ehrlinger + description: |- + Efficient implementation of Friedman's boosting algorithm with + l2-loss function and coordinate direction (design matrix columns) basis + functions. + date_publication: '2022-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=l2boost + url_git: '' +L2DensityGoFtest: + version: 0.6.0 + title: Density Goodness-of-Fit Test + maintainer: Dimitrios Bagkavos + description: Provides functions for the implementation of a density goodness-of-fit + test, based on piecewise approximation of the L2 distance. + date_publication: '2023-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=L2DensityGoFtest + url_git: '' +L2E: + version: '2.0' + title: Robust Structured Regression via the L2 Criterion + maintainer: Jocelyn Chi + description: |- + An implementation of a computational framework for performing robust structured regression with the L2 criterion + from Chi and Chi (2021+). Improvements using the majorization-minimization (MM) principle from Liu, Chi, and + Lange (2022+) added in Version 2.0. + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=L2E + url_git: '' +L2hdchange: + version: '1.0' + title: L2 Inference for Change Points in High-Dimensional Time Series + maintainer: Rui Lin + description: |- + Provides a method for detecting multiple change points in high-dimensional time + series, targeting dense or spatially clustered signals. See Li et al. (2023) + "L2 Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM". + arXiv preprint . + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=L2hdchange + url_git: '' +LA: + version: '2.3' + title: Lioness Algorithm (LA) + maintainer: Hongzhi Wang + description: Contains Lioness Algorithm (LA) for finding optimal designs over continuous + design space, optimal Latin hypercube designs, and optimal order-of-addition designs. + LA is a brand new nature-inspired meta-heuristic optimization algorithm. Detailed + methodologies of LA and its implementation on numerical simulations can be found + at Hongzhi Wang, Qian Xiao and Abhyuday Mandal (2021) . + date_publication: '2024-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LA + url_git: '' +lab2clean: + version: 1.0.0 + title: Automation and Standardization of Cleaning Clinical Lab Data + maintainer: Ahmed Zayed + description: Navigating the shift of clinical laboratory data from primary everyday + clinical use to secondary research purposes presents a significant challenge. + Given the substantial time and expertise required for lab data pre-processing + and cleaning and the lack of all-in-one tools tailored for this need, we developed + our algorithm 'lab2clean' as an open-source R-package. 'lab2clean' package is + set to automate and standardize the intricate process of cleaning clinical laboratory + results. With a keen focus on improving the data quality of laboratory result + values, our goal is to equip researchers with a straightforward, plug-and-play + tool, making it smoother for them to unlock the true potential of clinical laboratory + data in clinical research and clinical machine learning (ML) model development. + Version 1.0 of the algorithm is described in detail in 'Zayed et al. (2024)' . + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lab2clean + url_git: '' +LabApplStat: + version: 1.4.4 + title: Miscellaneous Scripts from the Data Science Laboratory (UCPH) + maintainer: Bo Markussen + description: Miscellaneous scripts, e.g. functionality to make and plot factor diagrams + for the statistical design. + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LabApplStat + url_git: '' +labdsv: + version: 2.1-0 + title: Ordination and Multivariate Analysis for Ecology + maintainer: David W. Roberts + description: |- + A variety of ordination and community analyses + useful in analysis of data sets in community ecology. + Includes many of the common ordination methods, with + graphical routines to facilitate their interpretation, + as well as several novel analyses. + date_publication: '2023-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labdsv + url_git: '' +label.switching: + version: '1.8' + title: Relabelling MCMC Outputs of Mixture Models + maintainer: Panagiotis Papastamoulis + description: The Bayesian estimation of mixture models (and more general hidden + Markov models) suffers from the label switching phenomenon, making the MCMC output + non-identifiable. This package can be used in order to deal with this problem + using various relabelling algorithms. + date_publication: '2019-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=label.switching + url_git: '' +labeleR: + version: 0.4.0 + title: |- + Automate the Production of Custom Labels, Badges, Certificates, + and Other Documents + maintainer: Ignacio Ramos-Gutierrez + description: |- + Create custom labels, badges, certificates + and other documents. Automate the production of potentially large + numbers of herbarium and collection labels, accreditation badges, + attendance and participation certificates, etc, and deliver them automatically. + Documents are generated in PDF format, which requires a working + installation of 'LaTeX', such as 'TinyTeX'. + date_publication: '2025-02-09' + bug_reports: https://github.com/EcologyR/labeleR/issues/ + url: https://ecologyr.github.io/labeleR/ + url_cran: https://CRAN.R-project.org/package=labeleR + url_git: https://github.com/EcologyR/labeleR/ +labeling: + version: 0.4.3 + title: Axis Labeling + maintainer: Nuno Sempere + description: Functions which provide a range of axis labeling algorithms. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labeling + url_git: '' +labelled: + version: 2.14.0 + title: Manipulating Labelled Data + maintainer: Joseph Larmarange + description: |- + Work with labelled data imported from 'SPSS' + or 'Stata' with 'haven' or 'foreign'. This package + provides useful functions to deal with "haven_labelled" and + "haven_labelled_spss" classes introduced by 'haven' package. + date_publication: '2025-01-08' + bug_reports: https://github.com/larmarange/labelled/issues + url: https://larmarange.github.io/labelled/ + url_cran: https://CRAN.R-project.org/package=labelled + url_git: https://github.com/larmarange/labelled +labelmachine: + version: 1.0.0 + title: Make Labeling of R Data Sets Easy + maintainer: Adrian Maldet + description: |- + Assign meaningful labels to data frame columns. + 'labelmachine' manages your label assignment rules in 'yaml' files + and makes it easy to use the same labels in multiple projects. + date_publication: '2019-10-11' + bug_reports: https://github.com/a-maldet/labelmachine/issues + url: https://a-maldet.github.io/labelmachine + url_cran: https://CRAN.R-project.org/package=labelmachine + url_git: https://github.com/a-maldet/labelmachine +labelr: + version: 0.1.9 + title: Label Data Frames, Variables, and Values + maintainer: Robert Hartman + description: Create and use data frame labels for data frame objects (frame labels), + their columns (name labels), and individual values of a column (value labels). + Value labels include one-to-one and many-to-one labels for nominal and ordinal + variables, as well as numerical range-based value labels for continuous variables. + Convert value-labeled variables so each value is replaced by its corresponding + value label. Add values-converted-to-labels columns to a value-labeled data frame + while preserving parent columns. Filter and subset a value-labeled data frame + using labels, while returning results in terms of values. Overlay labels in place + of values in common R commands to increase interpretability. Generate tables of + value frequencies, with categories expressed as raw values or as labels. Access + data frames that show value-to-label mappings for easy reference. + date_publication: '2024-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labelr + url_git: https://github.com/rhartmano/labelr +labelVector: + version: 0.1.2 + title: Label Attributes for Atomic Vectors + maintainer: Benjamin Nutter + description: |- + Labels are a common construct in statistical software providing a + human readable description of a variable. While variable names are succinct, + quick to type, and follow a language's naming conventions, labels may + be more illustrative and may use plain text and spaces. R does not provide + native support for labels. Some packages, however, have made this feature + available. Most notably, the 'Hmisc' package provides labelling methods + for a number of different object. Due to design decisions, these methods + are not all exported, and so are unavailable for use in package development. + The 'labelVector' package supports labels for atomic vectors in a light-weight + design that is suitable for use in other packages. + date_publication: '2021-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labelVector + url_git: '' +lablaster: + version: 1.0.1 + title: Laser Ablation Blast Through Endpoint Detection + maintainer: Alex Searle-Barnes + description: Imports a data frame containing a single time resolved laser ablation + mass spectrometry analysis of a foraminifera (or other carbonate shell), then + detects when the laser has burnt through the foraminifera test as a function of + change in signal over time. + date_publication: '2023-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lablaster + url_git: https://github.com/alexsb1/lablaster +labNorm: + version: 1.0.1 + title: Normalize Laboratory Measurements by Age and Sex + maintainer: Aviezer Lifshitz + description: Provides functions for normalizing standard laboratory measurements + (e.g. hemoglobin, cholesterol levels) according to age and sex, based on the algorithms + described in "Personalized lab test models to quantify disease potentials in healthy + individuals" (Netta Mendelson Cohen, Omer Schwartzman, Ram Jaschek, Aviezer Lifshitz, + Michael Hoichman, Ran Balicer, Liran I. Shlush, Gabi Barbash & Amos Tanay, ). + Allows users to easily obtain normalized values for standard lab results, and + to visualize their distributions. See more at . + date_publication: '2023-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labNorm + url_git: '' +LabourMarketAreas: + version: '3.4' + title: |- + Identification, Tuning, Visualisation and Analysis of Labour + Market Areas + maintainer: Luisa Franconi + description: Produces Labour Market Areas from commuting flows available at elementary + territorial units. It provides tools for automatic tuning based on spatial contiguity. + It also allows for statistical analyses and visualisation of the new functional + geography. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LabourMarketAreas + url_git: '' +labourR: + version: 1.0.0 + title: |- + Classify Multilingual Labour Market Free-Text to Standardized + Hierarchical Occupations + maintainer: Alexandros Kouretsis + description: |- + Allows the user to map multilingual free-text of occupations to a broad range + of standardized classifications. The package facilitates automatic occupation coding + (see, e.g., Gweon et al. (2017) and Turrell et al. (2019) + ), where the ISCO to ESCO mapping is exploited to extend the + occupations hierarchy, Le Vrang et al. (2014) . Document + vectorization is performed using the multilingual ESCO corpus. A method based on the + nearest neighbor search is used to suggest the closest ISCO occupation. + date_publication: '2020-07-18' + bug_reports: https://github.com/AleKoure/labourR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=labourR + url_git: https://github.com/AleKoure/labourR +LabRS: + version: 0.1.0 + title: Laboratorio di "Ricerca Sociale con R" + maintainer: Agnese Vardanega + description: Dati, scripts e funzioni per il libro "Ricerca sociale con R. Concetti + e funzioni base per la ricerca sociale" (Datasets, scripts and functions to support + the book "Ricerca sociale con R. Concetti e funzioni base per la ricerca sociale"). + date_publication: '2018-12-18' + bug_reports: '' + url: https://www.agnesevardanega.eu/ + url_cran: https://CRAN.R-project.org/package=LabRS + url_git: '' +labsimplex: + version: 0.1.2 + title: |- + Simplex Optimization Algorithms for Laboratory and Manufacturing + Processes + maintainer: Cristhian Paredes + description: |- + Simplex optimization algorithms as firstly proposed by Spendley + et al. (1962) and later modified by + Nelder and Mead (1965) for laboratory and + manufacturing processes. The package also provides tools for graphical + representation of the simplexes and some example response surfaces that + are useful in illustrating the optimization process. + date_publication: '2020-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labsimplex + url_git: '' +labstatR: + version: 1.0.13 + title: Libreria Del Laboratorio Di Statistica Con R + maintainer: Stefano M. Iacus + description: |- + Insieme di funzioni di supporto al volume "Laboratorio di + Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. + This package contains sets of functions defined in "Laboratorio + di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, + 2006. Function names and docs are in italian as well. + date_publication: '2022-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=labstatR + url_git: '' +labstats: + version: 1.0.1 + title: |- + Data Sets for the Book "Experimental Design for Laboratory + Biologists" + maintainer: Stanley E. Lazic + description: |- + Contains data sets to accompany the book: Lazic SE + (2016). "Experimental Design for Laboratory Biologists: Maximising Information + and Improving Reproducibility". Cambridge University Press. + date_publication: '2016-12-05' + bug_reports: https://github.com/stanlazic/labstats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=labstats + url_git: https://github.com/stanlazic/labstats +lacm: + version: 0.1.1 + title: Latent Autoregressive Count Models + maintainer: Cristiano Varin + description: Perform pairwise likelihood inference in latent autoregressive count + models. See Pedeli and Varin (2020) for details. + date_publication: '2020-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lacm + url_git: '' +lacrmr: + version: 1.0.5 + title: Connect to the 'Less Annoying CRM' API + maintainer: Frans van Dunné + description: Connect to the 'Less Annoying CRM' API with ease to get your crm data + in a clean and tidy format. 'Less Annoying CRM' is a simple CRM built for small + businesses, more information is available on their website . + date_publication: '2022-05-25' + bug_reports: https://github.com/ixpantia/lacrmr/issues + url: https://ixpantia.github.io/lacrmr/ + url_cran: https://CRAN.R-project.org/package=lacrmr + url_git: '' +lactater: + version: 0.2.0 + title: Tools for Analyzing Lactate Thresholds + maintainer: Felipe Mattioni Maturana + description: |- + Set of tools for analyzing lactate thresholds from a step incremental test to exhaustion. Easily analyze + the methods Log-log, Onset of Blood Lactate Accumulation (OBLA), Baseline plus (Bsln+), Dmax, Lactate Turning Point (LTP), + and Lactate / Intensity ratio (LTratio) in cycling, running, or swimming. + Beaver WL, Wasserman K, Whipp BJ (1985) . + Heck H, Mader A, Hess G, Mücke S, Müller R, Hollmann W (1985) . + Kindermann W, Simon G, Keul J (1979) . + Skinner JS, Mclellan TH (1980) . + Berg A, Jakob E, Lehmann M, Dickhuth HH, Huber G, Keul J (1990) PMID 2408033. + Zoladz JA, Rademaker AC, Sargeant AJ (1995) . + Cheng B, Kuipers H, Snyder A, Keizer H, Jeukendrup A, Hesselink M (1992) . + Bishop D, Jenkins DG, Mackinnon LT (1998) . + Hughson RL, Weisiger KH, Swanson GD (1987) . + Jamnick NA, Botella J, Pyne DB, Bishop DJ (2018) . + Hofmann P, Tschakert G (2017) . + Hofmann P, Pokan R, von Duvillard SP, Seibert FJ, Zweiker R, Schmid P (1997) . + Pokan R, Hofmann P, Von Duvillard SP, et al. (1997) . + Dickhuth H-H, Yin L, Niess A, et al. (1999) . + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lactater + url_git: '' +lactcurves: + version: 1.1.0 + title: Lactation Curve Parameter Estimation + maintainer: Eva M. Strucken + description: |- + AllCurves() runs multiple lactation curve models and extracts selection criteria for each model. + This package summarises the most common lactation curve models from the last century and provides a tool + for researchers to quickly decide on which model fits their data best to proceed with their analysis. + Start parameters were optimized based on a dataset with 1.7 million Holstein-Friesian cows. If convergence fails, + the start parameters need to be manually adjusted. + The models included in the package are taken from: + (1) Michaelis-Menten: Michaelis, L. and M.L. Menten (1913). + + (1a) Michaelis-Menten (Rook): Rook, A.J., J. France, and M.S. Dhanoa (1993). + + (1b) Michaelis-Menten + exponential (Rook): Rook, A.J., J. France, and M.S. Dhanoa (1993). + + (2) Brody (1923): Brody, S., A.C. Ragsdale, and C.W. Turner (1923). + + (3) Brody (1924): Brody, S., C.W. Tuner, and A.C. Ragsdale (1924). + + (4) Schumacher: Schumacher, F.X. (1939) in Thornley, J.H.M. and J. France (2007). + + (4a) Schumacher (Lopez et al. 2015): Lopez, S. J. France, N.E. Odongo, R.A. McBride, E. Kebreab, O. AlZahal, B.W. McBride, and J. Dijkstra (2015). + + (5) Parabolic exponential (Adediran): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). + + (6) Wood: Wood, P.D.P. (1967). + + (6a) Wood reparameterized (Dhanoa): Dhanoa, M.S. (1981). + + (6b) Wood non-linear (Cappio-Borlino): Cappio-Borlino, A., G. Pulina, and G. Rossi (1995). + + (7) Quadratic Polynomial (Dave): Dave, B.K. (1971) in Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). + + (8) Cobby and Le Du (Vargas): Vargas, B., W.J. Koops, M. Herrero, and J.A.M Van Arendonk (2000). + + (9) Papajcsik and Bodero 1: Papajcsik, I.A. and J. Bodero (1988). + + (10) Papajcsik and Bodero 2: Papajcsik, I.A. and J. Bodero (1988). + + (11) Papajcsik and Bodero 3: Papajcsik, I.A. and J. Bodero (1988). + + (12) Papajcsik and Bodero 4: Papajcsik, I.A. and J. Bodero (1988). + + (13) Papajcsik and Bodero 6: Papajcsik, I.A. and J. Bodero (1988). + + (14) Mixed log model 1 (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). + + (15) Mixed log model 3 (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). + + (16) Log-quadratic (Adediran et al. 2012): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). + + (17) Wilmink: J.B.M. Wilmink (1987). + + (17a) modified Wilmink (Jakobsen): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). + + (17b) modified Wilmink (Laurenson & Strucken): Strucken E.M., Brockmann G.A., and Y.C.S.M. Laurenson (2019). + + (18) Bicompartemental (Ferguson and Boston 1993): Ferguson, J.D., and R. Boston (1993) in Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). + + (19) Dijkstra: Dijkstra, J., J. France, M.S. Dhanoa, J.A. Maas, M.D. Hanigan, A.J. Rook, and D.E. Beever (1997). + + (20) Morant and Gnanasakthy (Pollott et al 2000): Pollott, G.E. and E. Gootwine (2000). + + (21) Morant and Gnanasakthy (Vargas et al 2000): Vargas, B., W.J. Koops, M. Herrero, and J.A.M Van Arendonk (2000). + + (22) Morant and Gnanasakthy (Adediran et al. 2012): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). + + (23) Khandekar (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). + + (24) Ali and Schaeffer: Ali, T.E. and L.R. Schaeffer (1987). + + (25) Fractional Polynomial (Elvira et al. 2013): Elvira, L., F. Hernandez, P. Cuesta, S. Cano, J.-V. Gonzalez-Martin, and S. Astiz (2012). + + (26) Pollott multiplicative (Elvira): Elvira, L., F. Hernandez, P. Cuesta, S. Cano, J.-V. Gonzalez-Martin, and S. Astiz (2012). + + (27) Pollott modified: Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). + + (28) Monophasic Grossman: Grossman, M. and W.J. Koops (1988). + + (29) Monophasic Power Transformed (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). + + (30) Diphasic (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). + + (31) Diphasic Power Transformed (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). + + (32) Legendre Polynomial (3th order): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). + + (33) Legendre Polynomial (4th order): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). + + (34) Legendre + Wilmink (Lidauer): Lidauer, M. and E.A. Mantysaari (1999). + + (35) Natural Cubic Spline (3 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999). + + (36) Natural Cubic Spline (4 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999). + + (37) Natural Cubic Spline (5 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999) + + (38) Natural Cubic Spline (defined knots according to Harrell 2001): Jr. Harrell, F.E. (2001). + + The selection criteria measure the goodness of fit of the model and include: + Residual standard error (RSE), + R-square (R2), + log likelihood, + Akaike information criterion (AIC), + Akaike information criterion corrected (AICC), + Bayesian Information Criterion (BIC), + Durbin Watson coefficient (DW). + The following model parameters are included: + Residual sum of squares (RSS), + Residual standard deviation (RSD), + F-value (F) based on F-ratio test. + date_publication: '2021-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lactcurves + url_git: '' +lacunaritycovariance: + version: 1.1-7 + title: |- + Gliding Box Lacunarity and Other Metrics for 2D Random Closed + Sets + maintainer: Kassel Liam Hingee + description: |- + Functions for estimating the gliding box lacunarity (GBL), + covariance, and pair-correlation of a random closed set (RACS) in 2D + from a binary coverage map (e.g. presence-absence land cover maps). + Contains a number of newly-developed covariance-based estimators of + GBL (Hingee et al., 2019) and + balanced estimators, proposed by Picka (2000) + , for covariance, centred + covariance, and pair-correlation. Also contains methods for + estimating contagion-like properties of RACS and simulating 2D Boolean + models. Binary coverage maps are usually represented as raster images + with pixel values of TRUE, FALSE or NA, with NA representing + unobserved pixels. A demo for extracting such a binary map from a + geospatial data format is provided. Binary maps may also be + represented using polygonal sets as the foreground, however for most + computations such maps are converted into raster images. The package + is based on research conducted during the author's PhD studies. + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lacunaritycovariance + url_git: https://github.com/kasselhingee/lacunaritycovariance +lacunr: + version: 1.0.1 + title: Fast 3D Lacunarity for Voxel Data + maintainer: Elliott Smeds + description: |- + Calculates 3D lacunarity from voxel data. It is designed for use + with point clouds generated from Light Detection And Ranging (LiDAR) scans + in order to measure the spatial heterogeneity of 3-dimensional structures + such as forest stands. It provides fast 'C++' functions to efficiently bin + point cloud data into voxels and calculate lacunarity using different + variants of the gliding-box algorithm originated by Allain & Cloitre (1991) + . + date_publication: '2024-06-04' + bug_reports: https://github.com/ElliottSmeds/lacunr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lacunr + url_git: https://github.com/ElliottSmeds/lacunr +LAD: + version: 0.1.0 + title: |- + Derive Leaf Angle Distribution (LAD) from Measured Leaf + Inclination Angles + maintainer: Francesco Chianucci + description: Calculate mean statistics and leaf angle distribution type from measured + leaf inclination angles. LAD distribution is fitted using a two-parameters (mu, + nu) Beta distribution and compared with six theoretical LAD distributions. Additional + information is provided in Chianucci and Cesaretti (2022) . + date_publication: '2023-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LAD + url_git: '' +LadderFuelsR: + version: 0.0.7 + title: |- + Automated Tool for Vertical Fuel Continuity Analysis using + Airborne Laser Scanning Data + maintainer: Olga Viedma + description: 'Set of tools for analyzing vertical fuel continuity at the tree level + using Airborne Laser Scanning data. The workflow consisted of: 1) calculating + the vertical height profiles of each segmented tree; 2) identifying gaps and fuel + layers; 3) estimating the distance between fuel layers; and 4) retrieving the + fuel layers base height and depth. Additionally, other functions recalculate previous + metrics after considering distances greater than certain threshold. Moreover, + the package calculates: i) the percentage of Leaf Area Density comprised in each + fuel layer, ii) remove fuel layers with Leaf Area Density (LAD) percentage less + than 10, and iii) recalculate the distances among the reminder ones. On the other + hand, it identifies the crown base height (CBH) based on different criteria: the + fuel layer with the highest LAD percentage and the fuel layers located at the + largest- and at the last-distance. When there is only one fuel layer, it also + identifies the CBH performing a segmented linear regression (breaking points) + on the cumulative sum of LAD as a function of height. Finally, a collection of + plotting functions is developed to represent: i) the initial gaps and fuel layers; + ii) the fuels base height, depths and gaps with distances greater than certain + threshold and, iii) the CBH based on different criteria. The methods implemented + in this package are original and have not been published elsewhere.' + date_publication: '2024-11-02' + bug_reports: https://github.com/olgaviedma/LadderFuelsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LadderFuelsR + url_git: https://github.com/olgaviedma/LadderFuelsR +laeken: + version: 0.5.3 + title: Estimation of Indicators on Social Exclusion and Poverty + maintainer: Andreas Alfons + description: |- + Estimation of indicators on social exclusion and poverty, as well + as Pareto tail modeling for empirical income distributions. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=laeken + url_git: '' +LaF: + version: 0.8.6 + title: Fast Access to Large ASCII Files + maintainer: Jan van der Laan + description: |- + Methods for fast access to large ASCII files. Currently the + following file formats are supported: comma separated format (CSV) and fixed + width format. It is assumed that the files are too large to fit into memory, + although the package can also be used to efficiently access files that do + fit into memory. Methods are provided to access and process files blockwise. + Furthermore, an opened file can be accessed as one would an ordinary + data.frame. The LaF vignette gives an overview of the functionality + provided. + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LaF + url_git: https://github.com/djvanderlaan/LaF +lagged: + version: 0.3.2 + title: Classes and Methods for Lagged Objects + maintainer: Georgi N. Boshnakov + description: |- + Provides classes and methods for objects, whose indexing + naturally starts from zero. Subsetting, indexing and mathematical + operations are defined naturally between lagged objects and lagged + and base R objects. Recycling is not used, except for singletons. + The single bracket operator doesn't drop dimensions by default. + date_publication: '2022-08-07' + bug_reports: https://github.com/GeoBosh/lagged/issues + url: https://geobosh.github.io/lagged/(doc) + url_cran: https://CRAN.R-project.org/package=lagged + url_git: https://github.com/GeoBosh/lagged(devel) +LAGOSNE: + version: 2.0.3 + title: |- + Interface to the Lake Multi-Scaled Geospatial and Temporal + Database + maintainer: Jemma Stachelek + description: |- + Client for programmatic access to the Lake + Multi-scaled Geospatial and Temporal database , with functions + for accessing lake water quality and ecological context data for the US. + date_publication: '2023-06-16' + bug_reports: https://github.com/cont-limno/LAGOSNE/issues + url: https://cont-limno.github.io/LAGOSNE/ + url_cran: https://CRAN.R-project.org/package=LAGOSNE + url_git: https://github.com/cont-limno/LAGOSNE +laGP: + version: 1.5-9 + title: Local Approximate Gaussian Process Regression + maintainer: Robert B. Gramacy + description: Performs approximate GP regression for large computer experiments and + spatial datasets. The approximation is based on finding small local designs for + prediction (independently) at particular inputs. OpenMP and SNOW parallelization + are supported for prediction over a vast out-of-sample testing set; GPU acceleration + is also supported for an important subroutine. OpenMP and GPU features may require + special compilation. An interface to lower-level (full) GP inference and prediction + is provided. Wrapper routines for blackbox optimization under mixed equality and + inequality constraints via an augmented Lagrangian scheme, and for large scale + computer model calibration, are also provided. For details and tutorial, see + Gramacy (2016 . + date_publication: '2023-03-14' + bug_reports: '' + url: https://bobby.gramacy.com/r_packages/laGP/ + url_cran: https://CRAN.R-project.org/package=laGP + url_git: '' +lagsarlmtree: + version: 1.0-1 + title: Spatial Lag Model Trees + maintainer: Achim Zeileis + description: |- + Model-based linear model trees adjusting for spatial correlation using a + simultaneous autoregressive spatial lag, Wagner and Zeileis (2019) + . + date_publication: '2019-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lagsarlmtree + url_git: '' +LagSequential: + version: 0.1.1 + title: Lag-Sequential Categorical Data Analysis + maintainer: Brian P. O'Connor + description: |- + Lag-sequential analysis is a method of assessing of patterns (what tends to + follow what?) in sequences of codes. The codes are typically for discrete + behaviors or states. The functions in this package read a stream of codes, + or a frequency transition matrix, and produce a variety of lag sequential + statistics, including transitional frequencies, expected transitional frequencies, + transitional probabilities, z values, adjusted residuals, Yule's Q values, + likelihood ratio tests of stationarity across time and homogeneity across groups + or segments, transformed kappas for unidirectional dependence, bidirectional + dependence, parallel and nonparallel dominance, and significance levels based on + both parametric and randomization tests. The methods are described in + Bakeman & Quera (2011) , + O'Connor (1999) , + Wampold & Margolin (1982) , and + Wampold (1995, ISBN:0-89391-919-5). + date_publication: '2019-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LagSequential + url_git: '' +Lahman: + version: 12.0-0 + title: Sean 'Lahman' Baseball Database + maintainer: Chris Dalzell + description: |- + Provides the tables from the 'Sean Lahman Baseball Database' as + a set of R data.frames. It uses the data on pitching, hitting and fielding + performance and other tables from 1871 through 2023, as recorded in the 2024 + version of the database. Documentation examples show how many baseball + questions can be investigated. + date_publication: '2024-09-26' + bug_reports: https://github.com/cdalzell/Lahman/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Lahman + url_git: '' +LAIr: + version: 0.3.0 + title: Converting NDVI to LAI of Field, Proximal and Satellite Data + maintainer: Francesco Chianucci + description: |- + Convert Leaf Area Index (LAI) from the Normalized Difference Vegetation Index (NDVI) using available equations from literature. + Detailed description of conversion equations in Bajocco et al. 2022 . + date_publication: '2024-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LAIr + url_git: '' +LakeMetabolizer: + version: 1.5.5 + title: Tools for the Analysis of Ecosystem Metabolism + maintainer: Jake Zwart + description: |- + A collection of tools for the calculation of freewater metabolism + from in situ time series of dissolved oxygen, water temperature, and, + optionally, additional environmental variables. LakeMetabolizer implements + 5 different metabolism models with diverse statistical underpinnings: + bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, + and Bayesian. Each of these 5 metabolism models can be combined with + 1 of 7 models for computing the coefficient of gas exchange across the + air–water interface (k). LakeMetabolizer also features a variety of + supporting functions that compute conversions and implement calculations + commonly applied to raw data prior to estimating metabolism (e.g., oxygen + saturation and optical conversion models). + date_publication: '2022-11-15' + bug_reports: https://github.com/GLEON/LakeMetabolizer/issues + url: https://www.tandfonline.com/doi/abs/10.1080/IW-6.4.883 + url_cran: https://CRAN.R-project.org/package=LakeMetabolizer + url_git: '' +lakemorpho: + version: 1.3.2 + title: Lake Morphometry Metrics + maintainer: Jeffrey W. Hollister + description: |- + Lake morphometry metrics are used by limnologists to understand, + among other things, the ecological processes in a lake. Traditionally, these + metrics are calculated by hand, with planimeters, and increasingly with + commercial GIS products. All of these methods work; however, they are either + outdated, difficult to reproduce, or require expensive licenses to use. The + 'lakemorpho' package provides the tools to calculate a typical suite + of these metrics from an input elevation model and lake polygon. The metrics + currently supported are: fetch, major axis, minor axis, major/minor axis + ratio, maximum length, maximum width, mean width, maximum depth, mean depth, + shoreline development, shoreline length, surface area, and volume. + date_publication: '2023-09-22' + bug_reports: https://github.com/jhollist/lakemorpho/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=lakemorpho + url_git: https://github.com/jhollist/lakemorpho/ +laketemps: + version: 0.5.1 + title: |- + Lake Temperatures Collected by Situ and Satellite Methods from + 1985-2009 + maintainer: Jordan S Read + description: Lake temperature records, metadata, and climate drivers for 291 global + lakes during the time period 1985-2009. Temperature observations were collected + using satellite and in situ methods. Climatic drivers and geomorphometric characteristics + were also compiled and are included for each lake. Data are part of the associated + publication from the Global Lake Temperature Collaboration project (http://www.laketemperature.org). + See citation('laketemps') for dataset attribution. + date_publication: '2015-02-28' + bug_reports: https://github.com/USGS-R/laketemps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=laketemps + url_git: '' +lakhesis: + version: 0.0.1 + title: Consensus Seriation for Binary Data + maintainer: Stephen A. Collins-Elliott + description: Determining consensus seriations for binary incidence matrices, using + a two-step process of Procrustes-fit correspondence analysis for heuristic selection + of partial seriations and iterative regression to establish a single consensus. + Contains the Lakhesis Calculator, a graphical platform for identifying seriated + sequences. Collins-Elliott (2024) . + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lakhesis + url_git: '' +LAM: + version: 0.7-22 + title: Some Latent Variable Models + maintainer: Alexander Robitzsch + description: |- + Includes some procedures for latent variable modeling with a + particular focus on multilevel data. + The 'LAM' package contains mean and covariance structure modelling + for multivariate normally distributed data (mlnormal(); Longford, 1987; + ), a general Metropolis-Hastings algorithm + (amh(); Roberts & Rosenthal, 2001, ) and + penalized maximum likelihood estimation (pmle(); Cole, Chu & Greenland, + 2014; ). + date_publication: '2024-07-15' + bug_reports: '' + url: https://sites.google.com/site/alexanderrobitzsch2/software + url_cran: https://CRAN.R-project.org/package=LAM + url_git: https://github.com/alexanderrobitzsch/LAM +LaMa: + version: 2.0.3 + title: |- + Fast Numerical Maximum Likelihood Estimation for Latent Markov + Models + maintainer: Jan-Ole Koslik + description: |- + A variety of latent Markov models, including hidden Markov models, hidden semi-Markov models, + state-space models and continuous-time variants can be formulated and estimated within the same framework via directly maximising the likelihood function using the so-called forward algorithm. + Applied researchers often need custom models that standard software does not easily support. + Writing tailored 'R' code offers flexibility but suffers from slow estimation speeds. + We address these issues by providing easy-to-use functions (written in 'C++' for speed) for common tasks like the forward algorithm. + These functions can be combined into custom models in a Lego-type approach, offering up to 10-20 times faster estimation via standard numerical optimisers. + To aid in building fully custom likelihood functions, several vignettes are included that show how to simulate data from and estimate all the above model classes. + date_publication: '2025-01-29' + bug_reports: '' + url: https://janoleko.github.io/LaMa/ + url_cran: https://CRAN.R-project.org/package=LaMa + url_git: '' +lambda.r: + version: 1.2.4 + title: Modeling Data with Functional Programming + maintainer: Brian Lee Yung Rowe + description: A language extension to efficiently write functional programs in R. + Syntax extensions include multi-part function definitions, pattern matching, guard + statements, built-in (optional) type safety. + date_publication: '2019-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lambda.r + url_git: '' +lambdaTS: + version: '1.1' + title: |- + Variational Seq2Seq Model with Lambda Transformer for Time + Series Analysis + maintainer: Giancarlo Vercellino + description: Time series analysis based on lambda transformer and variational seq2seq, + built on 'Torch'. + date_publication: '2022-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lambdaTS + url_git: '' +lambdr: + version: 1.2.5 + title: |- + Create a Runtime for Serving Containerised R Functions on 'AWS + Lambda' + maintainer: David Neuzerling + description: |- + Runtime for serving containers that can execute R code on the + 'AWS Lambda' serverless compute service . + Provides the necessary functionality for handling the various endpoints + required for accepting new input and sending responses. + date_publication: '2023-11-25' + bug_reports: https://github.com/mdneuzerling/lambdr/issues + url: https://lambdr.mdneuzerling.com/ + url_cran: https://CRAN.R-project.org/package=lambdr + url_git: https://github.com/mdneuzerling/lambdr +LambertW: + version: 0.6.9-1 + title: |- + Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, + Skewed Data + maintainer: Georg M. Goerg + description: |- + Lambert W x F distributions are a generalized framework to analyze + skewed, heavy-tailed data. It is based on an input/output system, where the + output random variable (RV) Y is a non-linearly transformed version of an input + RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). + The transformed RV Y has a Lambert W x F distribution. This package contains + functions to model and analyze skewed, heavy-tailed data the Lambert Way: + simulate random samples, estimate parameters, compute quantiles, and plot/ + print results nicely. The most useful function is 'Gaussianize', + which works similarly to 'scale', but actually makes the data Gaussian. + A do-it-yourself toolkit allows users to define their own Lambert W x + 'MyFavoriteDistribution' and use it in their analysis right away. + date_publication: '2023-11-30' + bug_reports: https://github.com/gmgeorg/LambertW/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LambertW + url_git: https://github.com/gmgeorg/LambertWhttps://arxiv.org/abs/0912.4554https://arxiv.org/abs/1010.2265https://arxiv.org/abs/1602.02200 +laminr: + version: 0.4.1 + title: Client for 'LaminDB' + maintainer: Robrecht Cannoodt + description: |- + Interact with 'LaminDB'. 'LaminDB' is an open-source data + framework for biology. This package allows you to query and download + data from 'LaminDB' instances. + date_publication: '2025-01-27' + bug_reports: https://github.com/laminlabs/laminr/issues + url: https://laminr.lamin.ai + url_cran: https://CRAN.R-project.org/package=laminr + url_git: https://github.com/laminlabs/laminr +lamle: + version: 0.3.1 + title: Maximum Likelihood Estimation of Latent Variable Models + maintainer: Björn Andersson + description: "Approximate marginal maximum likelihood estimation of multidimensional\nlatent + variable models via adaptive quadrature or Laplace approximations to the\nintegrals + in the likelihood function, as presented for confirmatory factor\nanalysis models + in Jin, S., Noh, M., and Lee, Y. (2018)\n, + for item response theory models in\nAndersson, B., and Xin, T. (2021) , + and for\ngeneralized linear latent variable models in Andersson, B., Jin, S., + and\nZhang, M. (2023) . Models implemented include\nthe + generalized\tpartial credit model, the graded response model, and generalized\nlinear + latent variable models for Poisson, negative-binomial and normal\ndistributions. + Supports a combination of binary, ordinal, count and continuous\nobserved variables + and multiple\tgroup models." + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lamle + url_git: '' +lamme: + version: 0.0.1 + title: Log-Analytic Methods for Multiplicative Effects + maintainer: Qimin Liu + description: Log-analytic methods intended for testing multiplicative effects. + date_publication: '2018-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lamme + url_git: '' +lamW: + version: 2.2.4 + title: Lambert-W Function + maintainer: Avraham Adler + description: |- + Implements both real-valued branches of the Lambert-W function + (Corless et al, 1996) without the need for + installing the entire GSL. + date_publication: '2024-06-17' + bug_reports: https://github.com/aadler/lamW/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lamW + url_git: https://github.com/aadler/lamW +lancor: + version: 0.1.2 + title: Statistical Inference via Lancaster Correlation + maintainer: Bernhard Klar + description: |- + Implementation of the methods described in Holzmann, Klar (2024) + . Lancaster correlation is a correlation coefficient + which equals the absolute value of the Pearson correlation for the bivariate + normal distribution, and is equal to or slightly less than the maximum + correlation coefficient for a variety of bivariate distributions. Rank and + moment-based estimators and corresponding confidence intervals are + implemented, as well as independence tests based on these statistics. + date_publication: '2024-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lancor + url_git: '' +LandComp: + version: 0.0.5 + title: Analysing Landscape Composition and Structure at Multiple Scales + maintainer: Krisztina Dóra Konrád + description: |- + Changes of landscape diversity and structure can be detected + soon if relying on landscape class combinations and analysing patterns + at multiple scales. 'LandComp' provides such an opportunity, based on + Juhász-Nagy's functions (Juhász-Nagy P, Podani J 1983 + ). Functions can handle multilayered data. + Requirements of the input: binary data contained by a regular square + or hexagonal grid, and the grid should have projected coordinates. + date_publication: '2024-02-06' + bug_reports: https://github.com/ladylavender/LandComp/issues + url: https://ladylavender.github.io/LandComp/ + url_cran: https://CRAN.R-project.org/package=LandComp + url_git: https://github.com/ladylavender/LandComp +landest: + version: '1.2' + title: Landmark Estimation of Survival and Treatment Effect + maintainer: Layla Parast + description: Provides functions to estimate survival and a treatment effect using + a landmark estimation approach. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=landest + url_git: '' +landform: + version: '0.2' + title: Topographic Position Index-Based Landform Classification + maintainer: Gianmarco Alberti + description: 'Provides a function for classifying a landscape into different categories + based on the Topographic Position Index (TPI) and slope. It offers two types of + classifications: Slope Position Classification, and Landform Classification. The + function internally calculates the TPI for the given landscape and then uses it + along with the slope to perform the classification. Optionally, descriptive statistics + for every class are calculated and plotted. The classifications are useful for + identifying the position of a location on a slope and for identifying broader + landform types.' + date_publication: '2023-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=landform + url_git: '' +Landmarking: + version: 1.0.0 + title: Analysis using Landmark Models + maintainer: Isobel Barrott + description: |- + The landmark approach allows survival predictions to be + updated dynamically as new measurements from an individual are recorded. + The idea is to set predefined time points, known as "landmark times", + and form a model at each landmark time using only the individuals in the + risk set. This package allows the longitudinal data to be modelled + either using the last observation carried forward or linear mixed + effects modelling. There is also the option to model competing risks, + either through cause-specific Cox regression or Fine-Gray regression. + To find out more about the methods in this package, please see + . + date_publication: '2022-02-15' + bug_reports: https://github.com/isobelbarrott/Landmarking/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Landmarking + url_git: https://github.com/isobelbarrott/Landmarking/ +landmix: + version: '1.0' + title: Landmark Prediction for Mixture Data + maintainer: Layla Parast + description: Non-parametric prediction of survival outcomes for mixture data that + incorporates covariates and a landmark time. Details are described in Garcia (2021) + . + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=landmix + url_git: '' +landmulti: + version: 0.5.0 + title: Landmark Prediction with Multiple Short-Term Events + maintainer: Wen Li + description: 'Contains functions for a flexible varying-coefficient landmark model + by incorporating multiple short-term events into the prediction of long-term survival + probability. For more information about landmark prediction please see Li, W., + Ning, J., Zhang, J., Li, Z., Savitz, S.I., Tahanan, A., Rahbar.M.H., (2023+). + "Enhancing Long-term Survival Prediction with Multiple Short-term Events: Landmarking + with A Flexible Varying Coefficient Model".' + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=landmulti + url_git: '' +landpred: + version: '1.2' + title: Landmark Prediction of a Survival Outcome + maintainer: Layla Parast + description: 'Provides functions for landmark prediction of a survival outcome incorporating + covariate and short-term event information. For more information about landmark + prediction please see: Parast, Layla, Su-Chun Cheng, and Tianxi Cai. Incorporating + short-term outcome information to predict long-term survival with discrete markers. + Biometrical Journal 53.2 (2011): 294-307, .' + date_publication: '2023-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=landpred + url_git: '' +landsat: + version: 1.1.2 + title: Radiometric and Topographic Correction of Satellite Imagery + maintainer: Sarah Goslee + description: Processing of Landsat or other multispectral satellite imagery. Includes + relative normalization, image-based radiometric correction, and topographic correction + options. The original package description was published as Goslee (2011) , + and details of the topographic corrections in Goslee (2012) . + date_publication: '2023-08-24' + bug_reports: https://github.com/phiala/landsat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=landsat + url_git: '' +landscapemetrics: + version: 2.2.1 + title: Landscape Metrics for Categorical Map Patterns + maintainer: Maximilian H.K. Hesselbarth + description: |- + Calculates landscape metrics for categorical landscape patterns in + a tidy workflow. 'landscapemetrics' reimplements the most common metrics from + 'FRAGSTATS' () and new ones from the current + literature on landscape metrics. This package supports 'terra' SpatRaster objects + as input arguments. It further provides utility functions to visualize patches, + select metrics and building blocks to develop new metrics. + date_publication: '2025-02-10' + bug_reports: https://github.com/r-spatialecology/landscapemetrics/issues + url: https://r-spatialecology.github.io/landscapemetrics/ + url_cran: https://CRAN.R-project.org/package=landscapemetrics + url_git: '' +landscapeR: + version: 1.3.1 + title: Categorical Landscape Simulation Facility + maintainer: Dario Masante + description: Simulates categorical maps on actual geographical realms, starting + from either empty landscapes or landscapes provided by the user (e.g. land use + maps). Allows to tweak or create landscapes while retaining a high degree of control + on its features, without the hassle of specifying each location attribute. In + this it differs from other tools which generate null or neutral landscapes in + a theoretical space. The basic algorithm currently implemented uses a simple agent + style/cellular automata growth model, with no rules (apart from areas of exclusion) + and von Neumann neighbourhood (four cells, aka Rook case). Outputs are raster + dataset exportable to any common GIS format. + date_publication: '2024-12-07' + bug_reports: https://github.com/dariomasante/landscapeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=landscapeR + url_git: https://github.com/dariomasante/landscapeR +landsepi: + version: 1.5.1 + title: Landscape Epidemiology and Evolution + maintainer: Jean-François Rey + description: |- + A stochastic, spatially-explicit, demo-genetic model simulating the spread and evolution + of a plant pathogen in a heterogeneous landscape to assess resistance deployment strategies. + It is based on a spatial geometry for describing the landscape and allocation of different cultivars, + a dispersal kernel for the dissemination of the pathogen, and a SEIR + ('Susceptible-Exposed-Infectious-Removed’) structure with a discrete time step. + It provides a useful tool to assess the performance of a wide range of deployment options with + respect to their epidemiological, evolutionary and economic outcomes. + Loup Rimbaud, Julien Papaïx, Jean-François Rey, Luke G Barrett, + Peter H Thrall (2018) . + date_publication: '2024-09-23' + bug_reports: https://gitlab.paca.inrae.fr/CSIRO-INRA/landsepi/-/issues + url: https://csiro-inra.pages.biosp.inrae.fr/landsepi/ + url_cran: https://CRAN.R-project.org/package=landsepi + url_git: '' +Langevin: + version: 1.3.2 + title: Langevin Analysis in One and Two Dimensions + maintainer: Philip Rinn + description: |- + Estimate drift and diffusion functions from time series and + generate synthetic time series from given drift and diffusion coefficients. + date_publication: '2024-07-01' + bug_reports: '' + url: https://gitlab.uni-oldenburg.de/TWiSt/Langevin + url_cran: https://CRAN.R-project.org/package=Langevin + url_git: '' +langevitour: + version: '0.7' + title: Langevin Tour + maintainer: Paul Harrison + description: |2- + + An HTML widget that randomly tours 2D projections of numerical data. A random walk through projections of the data is shown. The user can manipulate the plot to use specified axes, or turn on Guided Tour mode to find an informative projection of the data. Groups within the data can be hidden or shown, as can particular axes. Points can be brushed, and the selection can be linked to other widgets using crosstalk. The underlying method to produce the random walk and projection pursuit uses Langevin dynamics. The widget can be used from within R, or included in a self-contained R Markdown or Quarto document or presentation, or used in a Shiny app. + date_publication: '2024-02-24' + bug_reports: https://github.com/pfh/langevitour/issues/ + url: https://logarithmic.net/langevitour/ + url_cran: https://CRAN.R-project.org/package=langevitour + url_git: '' +languagelayeR: + version: 1.2.4 + title: Access the 'languagelayer' API + maintainer: Colin FAY + description: |- + Improve your text analysis with languagelayer + , a powerful language detection + API. + date_publication: '2019-02-12' + bug_reports: https://github.com/ColinFay/languagelayer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=languagelayeR + url_git: https://github.com/ColinFay/languagelayer +languageR: + version: 1.5.0 + title: |- + Analyzing Linguistic Data: A Practical Introduction to + Statistics + maintainer: R. H. Baayen + description: |- + Data sets exemplifying statistical methods, and some + facilitatory utility functions used in ``Analyzing Linguistic + Data: A practical introduction to statistics using R'', + Cambridge University Press, 2008. + date_publication: '2019-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=languageR + url_git: '' +languageserver: + version: 0.3.16 + title: Language Server Protocol + maintainer: Randy Lai + description: |- + An implementation of the Language Server Protocol + for R. The Language Server protocol is used by an editor client to + integrate features like auto completion. See + for details. + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=languageserver + url_git: https://github.com/REditorSupport/languageserver/ +languageserversetup: + version: 0.1.2 + title: Automated Setup and Auto Run for R Language Server + maintainer: Jozef Hajnala + description: |- + Allows to install the R 'languageserver' with all dependencies + into a separate library and use that independent installation + automatically when R is instantiated as a language server process. + Useful for making language server seamless to use without + running into package version conflicts. + date_publication: '2020-04-10' + bug_reports: https://github.com/jozefhajnala/languageserversetup/issues + url: '' + url_cran: https://CRAN.R-project.org/package=languageserversetup + url_git: https://github.com/jozefhajnala/languageserversetup +lans2r: + version: 1.2.0 + title: Work with Look at NanoSIMS Data in R + maintainer: Sebastian Kopf + description: |- + R interface for working with nanometer scale secondary ion mass + spectrometry (NanoSIMS) data exported from Look at NanoSIMS. + date_publication: '2023-02-19' + bug_reports: https://github.com/KopfLab/lans2r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lans2r + url_git: https://github.com/KopfLab/lans2r +LaplacesDemon: + version: 16.1.6 + title: Complete Environment for Bayesian Inference + maintainer: Henrik Singmann + description: Provides a complete environment for Bayesian inference using a variety + of different samplers (see ?LaplacesDemon for an overview). + date_publication: '2021-07-09' + bug_reports: https://github.com/LaplacesDemonR/LaplacesDemon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LaplacesDemon + url_git: https://github.com/LaplacesDemonR/LaplacesDemon +lar: + version: 0.1-2 + title: History of labour relations package + maintainer: Richard Zijdeman + description: This package is intended for researchers studying historical labour + relations (see http://www.historyoflabourrelations.org). The package allows for + easy access of excel files in the standard defined by the Global Collaboratory + on the History of Labour Relations. The package also allows for visualisation + of labour relations according to the Collaboratory's format. + date_publication: '2014-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lar + url_git: '' +lares: + version: 5.2.13 + title: Analytics & Machine Learning Sidekick + maintainer: Bernardo Lares + description: |- + Auxiliary package for better/faster analytics, visualization, data mining, and machine + learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, + Marketing Mix Modeling (Robyn), Exploratory, API, and Scrapper, it helps the analyst or + data scientist to get quick and robust results, without the need of repetitive coding or + advanced R programming skills. + date_publication: '2025-02-19' + bug_reports: https://github.com/laresbernardo/lares/issues + url: https://laresbernardo.github.io/lares/ + url_cran: https://CRAN.R-project.org/package=lares + url_git: https://github.com/laresbernardo/lares +lareshiny: + version: 0.0.3 + title: Lares 'shiny' Modules + maintainer: Bernardo Lares + description: Useful 'shiny' production-ready modules and helpers such as login window + and visualization tools. + date_publication: '2023-07-06' + bug_reports: https://github.com/laresbernardo/lareshiny/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lareshiny + url_git: https://github.com/laresbernardo/lareshiny +LARF: + version: '1.4' + title: |- + Local Average Response Functions for Instrumental Variable + Estimation of Treatment Effects + maintainer: Weihua An + description: Provides instrumental variable estimation of treatment effects when + both the endogenous treatment and its instrument are binary. Applicable to both + binary and continuous outcomes. + date_publication: '2016-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LARF + url_git: '' +Largevars: + version: 1.0.2 + title: Testing Large VARs for the Presence of Cointegration + maintainer: Eszter Kiss + description: Conducts a cointegration test for high-dimensional vector autoregressions + (VARs) of order k based on the large N,T asymptotics of Bykhovskaya and Gorin, + 2022 (). The implemented test is a modification + of the Johansen likelihood ratio test. In the absence of cointegration the test + converges to the partial sum of the Airy-1 point process. This package contains + simulated quantiles of the first ten partial sums of the Airy-1 point process + that are precise up to the first three digits. + date_publication: '2024-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Largevars + url_git: https://github.com/eszter-kiss/Largevars +LARisk: + version: 1.0.0 + title: |- + Estimation of Lifetime Attributable Risk of Cancer from + Radiation Exposure + maintainer: Juhee Lee + description: |- + Compute lifetime attributable risk of + radiation-induced cancer reveals that it can be helpful with + enhancement of the flexibility in research with fast calculation + and various options. Important reference papers include + Berrington de Gonzalez et al. (2012) , + National Research Council (2006, ISBN:978-0-309-09156-5). + date_publication: '2022-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LARisk + url_git: '' +lars: + version: '1.3' + title: Least Angle Regression, Lasso and Forward Stagewise + maintainer: Trevor Hastie + description: |- + Efficient procedures for fitting an entire lasso + sequence with the cost of a single least squares + fit. Least angle regression and infinitesimal forward + stagewise regression are related to the lasso, as + described in the paper below. + date_publication: '2022-04-13' + bug_reports: '' + url: https://doi.org/10.1214/009053604000000067 + url_cran: https://CRAN.R-project.org/package=lars + url_git: '' +LassoBacktracking: + version: '1.1' + title: |- + Modelling Interactions in High-Dimensional Data with + Backtracking + maintainer: Rajen Shah + description: |- + Implementation of the algorithm introduced in Shah, R. D. + (2016) . + Data with thousands of predictors can be handled. The algorithm + performs sequential Lasso fits on design matrices containing + increasing sets of candidate interactions. Previous fits are used to greatly + speed up subsequent fits, so the algorithm is very efficient. + date_publication: '2022-12-08' + bug_reports: '' + url: https://www.jmlr.org/papers/volume17/13-515/13-515.pdf + url_cran: https://CRAN.R-project.org/package=LassoBacktracking + url_git: '' +LassoGEE: + version: '1.0' + title: High-Dimensional Lasso Generalized Estimating Equations + maintainer: Yaguang Li + description: Fits generalized estimating equations with L1 regularization to longitudinal + data with high dimensional covariates. Use a efficient iterative composite gradient + descent algorithm. + date_publication: '2020-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LassoGEE + url_git: +LassoNet: + version: 0.8.3 + title: 3CoSE Algorithm + maintainer: Jonas Striaukas + description: Contains functions to estimate a penalized regression model using 3CoSE + algorithm, see Weber, Striaukas, Schumacher Binder (2018) . + date_publication: '2020-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LassoNet + url_git: '' +lassopv: + version: 0.2.0 + title: Nonparametric P-Value Estimation for Predictors in Lasso + maintainer: Lingfei Wang + description: 'Estimate the p-values for predictors x against target variable y in + lasso regression, using the regularization strength when each predictor enters + the active set of regularization path for the first time as the statistic. This + is based on the assumption that predictors (of the same variance) that (first) + become active earlier tend to be more significant. Three null distributions are + supported: normal and spherical, which are computed separately for each predictor + and analytically under approximation, which aims at efficiency and accuracy for + small p-values.' + date_publication: '2018-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lassopv + url_git: https://github.com/lingfeiwang/lassopv +LassoSIR: + version: 0.1.1 + title: Sparsed Sliced Inverse Regression via Lasso + maintainer: Zhigen Zhao + description: Estimate the sufficient dimension reduction space using sparsed sliced + inverse regression via Lasso (Lasso-SIR) introduced in Lin, Zhao, and Liu (2017) + . The Lasso-SIR is consistent and achieve the optimal convergence + rate under certain sparsity conditions for the multiple index models. + date_publication: '2017-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LassoSIR + url_git: '' +latcontrol: + version: 0.1.1 + title: |- + Evaluation of the Role of Control Variables in Structural + Equation Models + maintainer: Christian Blötner + description: Various opportunities to evaluate the effects of including one or more + control variable(s) in structural equation models onto model-implied variances, + covariances, and parameter estimates. The derivation of the methodology employed + in this package can be obtained from Blötner (2023) . + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latcontrol + url_git: '' +latdiag: + version: '0.3' + title: Draws Diagrams Useful for Checking Latent Scales + maintainer: Michael Dewey + description: |- + A graph + proposed by Rosenbaum is useful + for checking some properties of various + sorts of latent scale, this program generates commands + to obtain the graph using 'dot' from 'graphviz'. + date_publication: '2020-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latdiag + url_git: '' +latenetwork: + version: 1.0.1 + title: Inference on LATEs under Network Interference of Unknown Form + maintainer: Takahide Yanagi + description: |- + Estimating causal parameters in the presence of treatment spillover is of great interest in statistics. + This package provides tools for instrumental variables estimation of average causal effects under network interference of unknown form. + The target parameters are the local average direct effect, the local average indirect effect, the local average overall effect, and the local average spillover effect. + The methods are developed by Hoshino and Yanagi (2023) . + date_publication: '2023-08-08' + bug_reports: '' + url: https://tkhdyanagi.github.io/latenetwork/ + url_cran: https://CRAN.R-project.org/package=latenetwork + url_git: '' +latent2likert: + version: 1.2.1 + title: Converting Latent Variables into Likert Scale Responses + maintainer: Marko Lalovic + description: |- + Effectively simulates the discretization process inherent to + Likert scales while minimizing distortion. It converts continuous + latent variables into ordinal categories to generate Likert scale item + responses. Particularly useful for accurately modeling and analyzing + survey data that use Likert scales, especially when applying + statistical techniques that require metric data. + date_publication: '2024-06-24' + bug_reports: https://github.com/markolalovic/latent2likert/issues/ + url: https://lalovic.io/latent2likert/ + url_cran: https://CRAN.R-project.org/package=latent2likert + url_git: '' +LatentBMA: + version: 0.1.1 + title: |- + Bayesian Model Averaging for Univariate Link Latent Gaussian + Models + maintainer: Gregor Zens + description: Bayesian model averaging (BMA) algorithms for univariate link latent + Gaussian models (ULLGMs). For detailed information, refer to Steel M.F.J. & Zens + G. (2024) "Model Uncertainty in Latent Gaussian Models with Univariate Link Function" + . The package supports various g-priors and a beta-binomial + prior on the model space. It also includes auxiliary functions for visualizing + and tabulating BMA results. Currently, it offers an out-of-the-box solution for + model averaging of Poisson log-normal (PLN) and binomial logistic-normal (BiL) + models. The codebase is designed to be easily extendable to other likelihoods, + priors, and link functions. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LatentBMA + url_git: '' +latentcor: + version: 2.0.1 + title: Fast Computation of Latent Correlations for Mixed Data + maintainer: Mingze Huang + description: |- + The first stand-alone R package for computation of latent correlation that takes into account all variable types (continuous/binary/ordinal/zero-inflated), + comes with an optimized memory footprint, and is computationally efficient, essentially making latent correlation estimation almost as fast as rank-based correlation estimation. + The estimation is based on latent copula Gaussian models. + For continuous/binary types, see Fan, J., Liu, H., Ning, Y., and Zou, H. (2017). + For ternary type, see Quan X., Booth J.G. and Wells M.T. (2018) . + For truncated type or zero-inflated type, see Yoon G., Carroll R.J. and Gaynanova I. (2020) . + For approximation method of computation, see Yoon G., Müller C.L. and Gaynanova I. (2021) . The latter method uses multi-linear interpolation originally implemented in the R package . + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latentcor + url_git: '' +latentFactoR: + version: 0.0.6 + title: Data Simulation Based on Latent Factors + maintainer: Alexander Christensen + description: Generates data based on latent factor models. Data can be continuous, + polytomous, dichotomous, or mixed. Skews, cross-loadings, wording effects, population + errors, and local dependencies can be added. All parameters can be manipulated. + Data categorization is based on Garrido, Abad, and Ponsoda (2011) . + date_publication: '2024-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latentFactoR + url_git: '' +latentgraph: + version: '1.1' + title: Graphical Models with Latent Variables + maintainer: Yanxin Jin + description: 'Three methods are provided to estimate graphical models with latent + variables: (1) Jin, Y., Ning, Y., and Tan, K. M. (2020) (preprint available); + (2) Chandrasekaran, V., Parrilo, P. A. & Willsky, A. S. (2012) ; + (3) Tan, K. M., Ning, Y., Witten, D. M. & Liu, H. (2016) .' + date_publication: '2020-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latentgraph + url_git: '' +latentnet: + version: 2.11.0 + title: Latent Position and Cluster Models for Statistical Networks + maintainer: Pavel N. Krivitsky + description: Fit and simulate latent position and cluster models for statistical + networks. See Krivitsky and Handcock (2008) and Krivitsky, + Handcock, Raftery, and Hoff (2009) . + date_publication: '2024-02-19' + bug_reports: https://github.com/statnet/latentnet/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=latentnet + url_git: '' +later: + version: 1.4.1 + title: |- + Utilities for Scheduling Functions to Execute Later with Event + Loops + maintainer: Winston Chang + description: |- + Executes arbitrary R or C functions some time after the current + time, after the R execution stack has emptied. The functions are scheduled + in an event loop. + date_publication: '2024-11-27' + bug_reports: https://github.com/r-lib/later/issues + url: https://r-lib.github.io/later/ + url_cran: https://CRAN.R-project.org/package=later + url_git: https://github.com/r-lib/later +Laterality: + version: 0.9.5 + title: |- + Functions to Calculate Common Laterality Statistics in + Primatology + maintainer: Antony Borel + description: Calculates and plots Handedness index (HI), absolute HI, mean HI and + z-score which are commonly used indexes for the study of hand preference (laterality) + in non-human primates. + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Laterality + url_git: '' +LATERmodel: + version: 0.2.0 + title: |- + Linear Approach to Threshold with Ergodic Rate for Reaction + Times + maintainer: Maria del Mar Quiroga + description: |- + Implements the Linear Approach to Threshold with Ergodic Rate + (LATER) model, which predicts distributions of reaction times and + summarises them with as little as two free parameters. Allows for easy + visualisation and comparison of datasets, along with fitting of datasets + using the LATER model. + date_publication: '2024-05-03' + bug_reports: https://github.com/unimelbmdap/LATERmodel/issues + url: https://unimelbmdap.github.io/LATERmodel/ + url_cran: https://CRAN.R-project.org/package=LATERmodel + url_git: https://github.com/unimelbmdap/LATERmodel +latex2exp: + version: 0.9.6 + title: Use LaTeX Expressions in Plots + maintainer: Stefano Meschiari + description: |- + Parses and converts LaTeX math formulas to R's plotmath + expressions, used to enter mathematical formulas and symbols to be rendered as + text, axis labels, etc. throughout R's plotting system. + date_publication: '2022-11-28' + bug_reports: https://github.com/stefano-meschiari/latex2exp/issues + url: https://www.stefanom.io/latex2exp/ + url_cran: https://CRAN.R-project.org/package=latex2exp + url_git: https://github.com/stefano-meschiari/latex2exp +latexdiffr: + version: 0.2.0 + title: |- + Diff TeX, 'rmarkdown' or 'quarto' Files Using the 'latexdiff' + Utility + maintainer: David Hugh-Jones + description: |- + Produces a PDF diff of two 'rmarkdown', 'quarto', Sweave or TeX + files, using the external 'latexdiff' utility. + date_publication: '2024-02-16' + bug_reports: https://github.com/hughjonesd/latexdiffr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=latexdiffr + url_git: https://github.com/hughjonesd/latexdiffr +latexpdf: + version: 0.1.8 + title: Convert Tables to PDF or PNG + maintainer: Tim Bergsma + description: |- + Converts table-like objects to stand-alone PDF or PNG. + Can be used to embed tables and arbitrary content in PDF or Word + documents. Provides a low-level R interface for creating 'LaTeX' + code, e.g. command() and a high-level interface for creating PDF + documents, e.g. as.pdf.data.frame(). Extensive customization is + available via mid-level functions, e.g. as.tabular(). See also + 'package?latexpdf'. Support for PNG is experimental; see + 'as.png.data.frame'. Adapted from 'metrumrg' + . + Requires a compatible installation of 'pdflatex', + e.g. . + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latexpdf + url_git: '' +latexSymb: + version: 0.4.2 + title: Write Equations in a Way that You Can Read + maintainer: Nicolas Escobar + description: Utilities to help you write 'LaTeX' in a more readable way. Instead + of using plain code or a series of 'newcommand' statements, use 'R' functions. + You will be able to write what you mean and make fewer mistakes. + date_publication: '2024-09-20' + bug_reports: https://github.com/nicoesve/latexSymb/issues + url: https://nicoesve.github.io/latexSymb/ + url_cran: https://CRAN.R-project.org/package=latexSymb + url_git: '' +latrend: + version: 1.6.1 + title: A Framework for Clustering Longitudinal Data + maintainer: Niek Den Teuling + description: |- + A framework for clustering longitudinal datasets in a standardized way. + The package provides an interface to existing R packages for clustering longitudinal univariate trajectories, facilitating reproducible and transparent analyses. + Additionally, standard tools are provided to support cluster analyses, including repeated estimation, model validation, and model assessment. + The interface enables users to compare results between methods, and to implement and evaluate new methods with ease. + The 'akmedoids' package is available from . + date_publication: '2024-05-15' + bug_reports: https://github.com/philips-software/latrend/issues + url: https://philips-software.github.io/latrend/ + url_cran: https://CRAN.R-project.org/package=latrend + url_git: https://github.com/philips-software/latrend +latte: + version: 0.2.1 + title: Interface to 'LattE' and '4ti2' + maintainer: David Kahle + description: |- + Back-end connections to 'LattE' () + for counting lattice points and integration inside convex polytopes and + '4ti2' () for algebraic, geometric, and combinatorial + problems on linear spaces and front-end tools facilitating their use in the + 'R' ecosystem. + date_publication: '2019-03-25' + bug_reports: https://github.com/dkahle/latte/issues + url: '' + url_cran: https://CRAN.R-project.org/package=latte + url_git: https://github.com/dkahle/latte +lattice: + version: 0.22-6 + title: Trellis Graphics for R + maintainer: Deepayan Sarkar + description: |- + A powerful and elegant high-level data visualization + system inspired by Trellis graphics, with an emphasis on + multivariate data. Lattice is sufficient for typical graphics needs, + and is also flexible enough to handle most nonstandard requirements. + See ?Lattice for an introduction. + date_publication: '2024-03-20' + bug_reports: https://github.com/deepayan/lattice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lattice + url_git: https://lattice.r-forge.r-project.org/ +LatticeDesign: + version: 3.0-1 + title: Lattice-Based Space-Filling Designs + maintainer: Xu He + description: |- + Lattice-based space-filling designs with fill or separation distance properties including + interleaved lattice-based minimax distance designs proposed in Xu He (2017) + , interleaved lattice-based maximin distance designs proposed in + Xu He (2018) , interleaved lattice-based designs with low fill and + high separation distance properties proposed in Xu He (2024) , + rotated sphere packing designs proposed in Xu He (2017) + , sliced rotated sphere packing designs proposed in + Xu He (2019) , + and densest packing-based maximum projections designs proposed in Xu He (2021) + and Xu He (2018) . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LatticeDesign + url_git: '' +latticeExtra: + version: 0.6-30 + title: Extra Graphical Utilities Based on Lattice + maintainer: Deepayan Sarkar + description: |- + Building on the infrastructure provided by the lattice + package, this package provides several new high-level + functions and methods, as well as additional utilities + such as panel and axis annotation functions. + date_publication: '2022-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=latticeExtra + url_git: http://latticeextra.r-forge.r-project.org/ +LatticeKrig: + version: 9.3.0 + title: Multi-Resolution Kriging Based on Markov Random Fields + maintainer: Douglas Nychka + description: |- + Methods for the interpolation of large spatial + datasets. This package uses a basis function approach that + provides a surface fitting method + that can approximate standard spatial data models. + Using a large number of basis functions allows for estimates that + can come close to interpolating the observations (a spatial model + with a small nugget variance.) Moreover, the covariance model for + this method can approximate the Matern covariance family but also + allows for a multi-resolution model and supports efficient + computation of the profile likelihood for estimating covariance + parameters. This is accomplished through compactly supported basis + functions and a Markov random field model for the basis + coefficients. These features lead to sparse matrices for the + computations and this package makes of the R spam package for sparse + linear algebra. + An extension of this version over previous ones ( < 5.4 ) is the + support for different geometries besides a rectangular domain. The + Markov random field approach combined with a basis function + representation makes the implementation of different geometries + simple where only a few specific R functions need to be added with + most of the computation and evaluation done by generic routines that + have been tuned to be efficient. One benefit of this package's + model/approach is the facility to do unconditional and conditional + simulation of the field for large numbers of arbitrary points. There + is also the flexibility for estimating non-stationary covariances + and also the case when the observations are a linear combination + (e.g. an integral) of the spatial process. Included are generic + methods for prediction, standard errors for prediction, plotting of + the estimated surface and conditional and unconditional simulation. + See the 'LatticeKrigRPackage' GitHub repository for a vignette of this + package. + Development of this package was supported in part by the National + Science Foundation Grant 1417857 and the National Center for + Atmospheric Research. + date_publication: '2024-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LatticeKrig + url_git: '' +lava: + version: 1.8.1 + title: Latent Variable Models + maintainer: Klaus K. Holst + description: |- + A general implementation of Structural Equation Models + with latent variables (MLE, 2SLS, and composite likelihood + estimators) with both continuous, censored, and ordinal + outcomes (Holst and Budtz-Joergensen (2013) ). + Mixture latent variable models and non-linear latent variable models + (Holst and Budtz-Joergensen (2020) ). + The package also provides methods for graph exploration (d-separation, + back-door criterion), simulation of general non-linear latent variable + models, and estimation of influence functions for a broad range of + statistical models. + date_publication: '2025-01-12' + bug_reports: https://github.com/kkholst/lava/issues + url: https://kkholst.github.io/lava/ + url_cran: https://CRAN.R-project.org/package=lava + url_git: '' +lavaan: + version: 0.6-19 + title: Latent Variable Analysis + maintainer: Yves Rosseel + description: |- + Fit a variety of latent variable models, including confirmatory + factor analysis, structural equation modeling and latent growth curve models. + date_publication: '2024-09-26' + bug_reports: https://github.com/yrosseel/lavaan/issues + url: https://lavaan.ugent.be + url_cran: https://CRAN.R-project.org/package=lavaan + url_git: '' +lavaan.printer: + version: 0.1.0 + title: Helper Functions for Printing 'lavaan' Outputs + maintainer: Shu Fai Cheung + description: |- + Helpers for customizing selected outputs from + 'lavaan' by Rosseel (2012) + and print them. The functions are intended to be used + by package developers in their packages and so are not + designed to be user-friendly. They are designed to be + let developers customize the tables by other + functions. Currently the parameter estimates tables of a + fitted object are supported. + date_publication: '2024-09-15' + bug_reports: '' + url: https://sfcheung.github.io/lavaan.printer/ + url_cran: https://CRAN.R-project.org/package=lavaan.printer + url_git: '' +lavaan.shiny: + version: '1.2' + title: Latent Variable Analysis with Shiny + maintainer: W. Kyle Hamilton + description: |- + Interactive shiny application for working with different kinds of + latent variable analysis, with the 'lavaan' package. Graphical output for models + are provided and different estimators are supported. + date_publication: '2017-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lavaan.shiny + url_git: https://github.com/kylehamilton/lavaan.shiny +lavaanExtra: + version: 0.2.1 + title: Convenience Functions for Package 'lavaan' + maintainer: Rémi Thériault + description: |- + Affords an alternative, vector-based syntax to 'lavaan', as well as other + convenience functions such as naming paths and defining indirect + links automatically, in addition to convenience formatting optimized + for a publication and script sharing workflow. + date_publication: '2024-07-01' + bug_reports: https://github.com/rempsyc/lavaanExtra/issues + url: https://lavaanExtra.remi-theriault.com + url_cran: https://CRAN.R-project.org/package=lavaanExtra + url_git: '' +lavaangui: + version: 0.2.4 + title: |- + Graphical User Interface with Integrated 'Diagrammer' for + 'Lavaan' + maintainer: Julian D. Karch + description: |- + Provides a graphical user interface with an + integrated diagrammer for latent variables from the 'lavaan' package. + It offers two core functions: first, lavaangui() launches a web application + that allows users to specify models by drawing path diagrams, fitting them, + assessing model fit, and more; second, plot_lavaan() creates + interactive path diagrams from models specified in 'lavaan'. + Karch (2024) contains a tutorial. + date_publication: '2025-02-20' + bug_reports: https://github.com/karchjd/lavaangui/issues + url: https://lavaangui.org/ + url_cran: https://CRAN.R-project.org/package=lavaangui + url_git: https://github.com/karchjd/lavaangui +lavaanPlot: + version: 0.8.1 + title: Path Diagrams for 'Lavaan' Models via 'DiagrammeR' + maintainer: Alex Lishinski + description: |- + Plots path diagrams from models in 'lavaan' using the plotting + functionality from the 'DiagrammeR' package. 'DiagrammeR' provides nice path diagrams + via 'Graphviz', and these functions make it easy to generate these diagrams from a + 'lavaan' path model without having to write the DOT language graph specification. + date_publication: '2024-01-29' + bug_reports: '' + url: https://lavaanplot.alexlishinski.com/ + url_cran: https://CRAN.R-project.org/package=lavaanPlot + url_git: https://github.com/alishinski/lavaanPlot +lavacreg: + version: 0.2-2 + title: Latent Variable Count Regression Models + maintainer: Christoph Kiefer + description: |- + Estimation of a multi-group count regression models (i.e., Poisson, + negative binomial) with latent covariates. This packages provides two extensions + compared to ordinary count regression models based on a generalized linear model: + First, measurement models for the predictors can be specified allowing to account + for measurement error. Second, the count regression can be simultaneously estimated + in multiple groups with stochastic group weights. The marginal maximum likelihood + estimation is described in Kiefer & Mayer (2020) . + date_publication: '2024-06-13' + bug_reports: https://github.com/chkiefer/lavacreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lavacreg + url_git: https://github.com/chkiefer/lavacreg +LavaCvxr: + version: 1.0.2 + title: |- + Lava Estimation for the Sum of Sparse and Dense Signals(3 + Methods) + maintainer: Yang Liu + description: The lava estimation is used to recover signals that is the sum of a + sparse signal and a dense signal. The post-lava method corrects the shrinkage + bias of lava. For more information on the lava estimation, see Chernozhukov, Hansen, + and Liao (2017) . + date_publication: '2021-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LavaCvxr + url_git: '' +lavaSearch2: + version: 2.0.3 + title: Tools for Model Specification in the Latent Variable Framework + maintainer: Brice Ozenne + description: |- + Tools for model specification in the latent variable framework + (add-on to the 'lava' package). The package contains three main functionalities: + Wald tests/F-tests with improved control of the type 1 error in small samples, + adjustment for multiple comparisons when searching for local dependencies, + and adjustment for multiple comparisons when doing inference for multiple latent variable models. + date_publication: '2024-02-23' + bug_reports: https://github.com/bozenne/lavaSearch2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lavaSearch2 + url_git: https://github.com/bozenne/lavaSearch2 +Lavash: + version: '1.0' + title: Lava Estimation for the Sum of Sparse and Dense Signals + maintainer: Jaeheon Jung + description: The lava estimation is a new technique to recover signals that is the + sum of a sparse and dense signals. The post-lava method corrects the shrinkage + bias of lava. For more information on the lava estimation, see Chernozhukov, Hansen, + and Liao (2017) . + date_publication: '2018-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Lavash + url_git: '' +LAWBL: + version: 1.5.0 + title: Latent (Variable) Analysis with Bayesian Learning + maintainer: Jinsong Chen + description: 'A variety of models to analyze latent variables based on Bayesian + learning: the partially CFA (Chen, Guo, Zhang, & Pan, 2020) ; + generalized PCFA; partially confirmatory IRM (Chen, 2020) ; + Bayesian regularized EFA ; Fully and partially + EFA.' + date_publication: '2022-05-16' + bug_reports: https://github.com/Jinsong-Chen/LAWBL/issues + url: https://jinsong-chen.github.io/LAWBL/ + url_cran: https://CRAN.R-project.org/package=LAWBL + url_git: https://github.com/Jinsong-Chen/LAWBL +lawstat: + version: '3.6' + title: Tools for Biostatistics, Public Policy, and Law + maintainer: Yulia R. Gel + description: Statistical tests widely utilized in biostatistics, public policy, + and law. Along with the well-known tests for equality of means and variances, + randomness, and measures of relative variability, the package contains new robust + tests of symmetry, omnibus and directional tests of normality, and their graphical + counterparts such as robust QQ plot, robust trend tests for variances, etc. All + implemented tests and methods are illustrated by simulations and real-life examples + from legal statistics, economics, and biostatistics. + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lawstat + url_git: '' +lax: + version: 1.2.3 + title: Loglikelihood Adjustment for Extreme Value Models + maintainer: Paul J. Northrop + description: |- + Performs adjusted inferences based on model objects fitted, using + maximum likelihood estimation, by the extreme value analysis packages + 'eva' , + 'evd' , + 'evir' , + 'extRemes' , + 'fExtremes' , + 'ismev' , + 'mev' , + 'POT' and + 'texmex' . + Adjusted standard errors and an adjusted loglikelihood are provided, using + the 'chandwich' package + and the object-oriented features of the 'sandwich' package + . The adjustment is based on a + robust sandwich estimator of the parameter covariance matrix, based on the + methodology in Chandler and Bate (2007) . This + can be used for cluster correlated data when interest lies in the + parameters of the marginal distributions, or for performing inferences that + are robust to certain types of model misspecification. Univariate extreme + value models, including regression models, are supported. + date_publication: '2024-02-25' + bug_reports: https://github.com/paulnorthrop/lax/issues + url: https://paulnorthrop.github.io/lax/ + url_cran: https://CRAN.R-project.org/package=lax + url_git: https://github.com/paulnorthrop/lax +lay: + version: 0.1.3 + title: Simple but Efficient Rowwise Jobs + maintainer: Alexandre Courtiol + description: Creating efficiently new column(s) in a data frame (including tibble) + by applying a function one row at a time. + date_publication: '2023-10-30' + bug_reports: https://github.com/courtiol/lay/issues/ + url: https://courtiol.github.io/lay/ + url_cran: https://CRAN.R-project.org/package=lay + url_git: https://github.com/courtiol/lay/ +layer: + version: 0.0.3 + title: Tilt your Maps and Turn Them into 'ggplot' Plots + maintainer: Egor Kotov + description: |- + Simplifies the whole process of creating stacked tilted maps, + that are often used in scientific publications to show different + environmental layers for a geographical region. Tilting maps and + layering them allows to easily draw visual correlations between these + environmental layers. + date_publication: '2025-01-29' + bug_reports: https://github.com/marcosci/layer/issues + url: https://marcosci.github.io/layer/ + url_cran: https://CRAN.R-project.org/package=layer + url_git: https://github.com/marcosci/layer +lazy: + version: 1.2-18 + title: Lazy Learning for Local Regression + maintainer: Theo Verhelst + description: |- + By combining constant, linear, and quadratic local models, + lazy estimates the value of an unknown multivariate function on + the basis of a set of possibly noisy samples of the function + itself. This implementation of lazy learning automatically + adjusts the bandwidth on a query-by-query basis through a + leave-one-out cross-validation. + date_publication: '2022-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lazy + url_git: '' +lazyarray: + version: 1.1.0 + title: Persistent Large Data Array with Lazy-Loading on Demand + maintainer: Zhengjia Wang + description: |- + Multi-threaded serialization of compressed array that + fully utilizes modern solid state drives. It allows + to store and load extremely large data on demand within seconds + without occupying too much memories. With data stored on hard drive, + a lazy-array data can be loaded, shared across multiple R sessions. + For arrays with partition mode on, multiple R sessions can write to + a same array simultaneously along the last dimension (partition). + The internal storage format is provided by 'fstcore' package geared by + 'LZ4' and 'ZSTD' compressors. + date_publication: '2020-07-18' + bug_reports: https://github.com/dipterix/lazyarray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lazyarray + url_git: https://github.com/dipterix/lazyarray +lazybar: + version: 0.1.0 + title: Progress Bar with Remaining Time Forecast Method + maintainer: Yangzhuoran Yang + description: |- + A simple progress bar showing estimated remaining time. + Multiple forecast methods and user defined forecast method for + the remaining time are supported. + date_publication: '2020-04-28' + bug_reports: https://github.com/FinYang/lazybar/issues/ + url: https://pkg.yangzhuoranyang.com/lazybar/ + url_cran: https://CRAN.R-project.org/package=lazybar + url_git: https://github.com/FinYang/lazybar/ +lazyData: + version: 1.1.0 + title: A LazyData Facility + maintainer: Bill Venables + description: |- + Supplies a LazyData facility for packages which have data + sets but do not provide LazyData: true. A single function is + is included, requireData, which is a drop-in replacement for + base::require, but carrying the additional + functionality. By default, it suppresses package + startup messages as well. See argument 'reallyQuitely'. + date_publication: '2016-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lazyData + url_git: '' +lazyeval: + version: 0.2.2 + title: Lazy (Non-Standard) Evaluation + maintainer: Hadley Wickham + description: |- + An alternative approach to non-standard evaluation using + formulas. Provides a full implementation of LISP style 'quasiquotation', + making it easier to generate code with other code. + date_publication: '2019-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lazyeval + url_git: '' +lazysf: + version: 0.1.0 + title: Delayed Read for 'GDAL' Vector Data Sources + maintainer: Michael Sumner + description: |- + Lazy read for drawings. A 'dplyr' back end for data sources supported by + 'GDAL' vector drivers, that allows working with local or remote sources as if they + are in-memory data frames. Basic features works with any drawing format ('GDAL vector + data source') supported by the 'sf' package. + date_publication: '2020-11-14' + bug_reports: https://github.com/mdsumner/lazysf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lazysf + url_git: https://github.com/mdsumner/lazysf +lazysql: + version: 0.1.3 + title: Lazy SQL Programming + maintainer: Uwe Block + description: |2- + + Helper functions to build SQL statements + for dbGetQuery or dbSendQuery under program control. + They are intended to increase speed of coding and + to reduce coding errors. Arguments are carefully checked, + in particular SQL identifiers such as names of tables or columns. + More patterns will be added as required. + date_publication: '2016-03-12' + bug_reports: https://github.com/UweBlock/lazysql/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lazysql + url_git: https://github.com/UweBlock/lazysql +lazytrade: + version: 0.5.4 + title: Learn Computer and Data Science using Algorithmic Trading + maintainer: Vladimir Zhbanko + description: |- + Provide sets of functions and methods to learn and practice data science using idea of algorithmic trading. + Main goal is to process information within "Decision Support System" to come up with analysis or predictions. + There are several utilities such as dynamic and adaptive risk management using reinforcement learning + and even functions to generate predictions of price changes using pattern recognition deep regression learning. + Summary of Methods used: Awesome H2O tutorials: , + Market Type research of Van Tharp Institute: , + Reinforcement Learning R package: . + date_publication: '2024-07-16' + bug_reports: https://github.com/vzhomeexperiments/lazytrade/issues + url: https://vladdsm.github.io/myblog_attempt/topics/lazy%20trading/ + url_cran: https://CRAN.R-project.org/package=lazytrade + url_git: https://github.com/vzhomeexperiments/lazytrade +lazyWeave: + version: 3.0.2 + title: LaTeX Wrappers for R Users + maintainer: Benjamin Nutter + description: |- + Provides the functionality to write LaTeX code from within R + without having to learn LaTeX. Functionality also exists to create HTML + and Markdown code. While the functionality still exists to write + complete documents with lazyWeave, it is generally easier to do so with + with markdown and knitr. lazyWeave's main strength now is the ability + to design custom and complex tables for reporting results. + date_publication: '2018-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lazyWeave + url_git: '' +lba: + version: 2.4.52 + title: Latent Budget Analysis for Compositional Data + maintainer: Ivan Bezerra Allaman + description: |- + Latent budget analysis is a method for the analysis of a two-way + contingency table with an exploratory variable and a response variable. It is + specially designed for compositional data. + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lba + url_git: https://github.com/ivanalaman/lba +lbfgs: + version: 1.2.1.2 + title: Limited-memory BFGS Optimization + maintainer: Antonio Coppola + description: A wrapper built around the libLBFGS optimization library by Naoaki + Okazaki. The lbfgs package implements both the Limited-memory Broyden-Fletcher-Goldfarb-Shanno + (L-BFGS) and the Orthant-Wise Quasi-Newton Limited-Memory (OWL-QN) optimization + algorithms. The L-BFGS algorithm solves the problem of minimizing an objective, + given its gradient, by iteratively computing approximations of the inverse Hessian + matrix. The OWL-QN algorithm finds the optimum of an objective plus the L1-norm + of the problem's parameters. The package offers a fast and memory-efficient implementation + of these optimization routines, which is particularly suited for high-dimensional + problems. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lbfgs + url_git: '' +lbfgsb3c: + version: 2024-3.5 + title: |- + Limited Memory BFGS Minimizer with Bounds on Parameters with + optim() 'C' Interface + maintainer: Matthew L Fidler + description: |- + Interfacing to Nocedal et al. L-BFGS-B.3.0 + (See ) + limited memory BFGS minimizer with bounds on parameters. + This is a fork of 'lbfgsb3'. + This registers a 'R' compatible 'C' interface to L-BFGS-B.3.0 that uses the same + function types and optimization as the optim() function (see writing 'R' extensions + and source for details). This package also adds more stopping criteria as well + as allowing the adjustment of more tolerances. + date_publication: '2024-09-17' + bug_reports: https://github.com/nlmixr2/lbfgsb3c/issues + url: https://nlmixr2.github.io/lbfgsb3c/ + url_cran: https://CRAN.R-project.org/package=lbfgsb3c + url_git: https://github.com/nlmixr2/lbfgsb3c +LBI: + version: 0.2.2 + title: Likelihood Based Inference + maintainer: Kyun-Seop Bae + description: |- + Maximum likelihood estimation and likelihood ratio test are essential for modern statistics. This package supports in calculating likelihood based inference. + Reference: Pawitan Y. (2001, ISBN:0-19-850765-8). + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LBI + url_git: '' +lbm: + version: 0.9.0.2 + title: Log Binomial Regression Model in Exact Method + maintainer: Chao Zhu + description: |- + Fit the log binomial regression model (LBM) by Exact method. Limited parameter space of + LBM causes trouble to find admissible estimates and fail to converge when MLE is close to or on + the boundary of space. Exact method utilizes the property of boundary vectors to re-parametrize + the model without losing any information, and fits the model on the standard fitting algorithm + with no convergence issues. + date_publication: '2021-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lbm + url_git: '' +lboxcox: + version: '1.2' + title: Implementation of Logistic Box-Cox Regression + maintainer: Li Xing + description: Implements a logistic box-cox model. This model is fully described + in Xing, L. et al. (2021) . + date_publication: '2023-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lboxcox + url_git: '' +LBPG: + version: 0.1.2 + title: The Length-Biased Power Garima Distribution + maintainer: Kittipong Klinjan + description: |- + The Length-Biased Power Garima distribution for computes the probability density, + the cumulative density distribution and the quantile function of the distribution, + and generates sample values with random variables based on Kittipong and Sirinapa(2021). + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LBPG + url_git: '' +lbreg: + version: '1.3' + title: Log-Binomial Regression with Constrained Optimization + maintainer: Bernardo Andrade + description: Maximum likelihood estimation of log-binomial regression with special + functionality when the MLE is on the boundary of the parameter space. + date_publication: '2019-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lbreg + url_git: '' +LBSPR: + version: 0.1.6 + title: Length-Based Spawning Potential Ratio + maintainer: Adrian Hordyk + description: |- + Simulate expected equilibrium length composition, yield-per-recruit, and + the spawning potential ratio (SPR) using the length-based SPR (LBSPR) model. Fit the LBSPR + model to length data to estimate selectivity, relative apical fishing mortality, and + the spawning potential ratio for data-limited fisheries. + See Hordyk et al (2016) for more information about the + LBSPR assessment method. + date_publication: '2021-10-06' + bug_reports: https://github.com/AdrianHordyk/LBSPR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LBSPR + url_git: https://github.com/AdrianHordyk/LBSPR +LCA: + version: 0.1.1 + title: Localised Co-Dependency Analysis + maintainer: Ed Curry + description: Performs model fitting and significance estimation for Localised Co-Dependency + between pairs of features of a numeric dataset. + date_publication: '2019-04-22' + bug_reports: '' + url: https://www.imperial.ac.uk/people/e.curry + url_cran: https://CRAN.R-project.org/package=LCA + url_git: '' +LCAextend: + version: '1.3' + title: |- + Latent Class Analysis (LCA) with Familial Dependence in Extended + Pedigrees + maintainer: Alexandre BUREAU + description: |- + Latent Class Analysis of + phenotypic measurements in pedigrees and model selection + based on one of two methods: likelihood-based cross-validation + and Bayesian Information Criterion. Computation of individual + and triplet child-parents weights in a pedigree is performed using an + upward-downward algorithm. The model takes into account the familial + dependence defined by the pedigree structure by considering + that a class of a child depends on his parents classes via + triplet-transition probabilities of the classes. The package + handles the case where measurements are available on all + subjects and the case where measurements are available only on + symptomatic (i.e. affected) subjects. Distributions for + discrete (or ordinal) and continuous data are currently + implemented. The package can deal with missing data. + date_publication: '2018-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LCAextend + url_git: '' +lcars: + version: 0.4.0 + title: LCARS Aesthetic for Shiny + maintainer: Matthew Leonawicz + description: |- + Provides Shiny widgets and theme that support a 'Library Computer Access/Retrieval System' (LCARS) aesthetic for Shiny apps. + The package also includes functions for adding a minimal LCARS theme to static 'ggplot2' graphs. + More details about LCARS can be found at . + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/lcars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lcars + url_git: https://github.com/leonawicz/lcars +LCAvarsel: + version: '1.1' + title: Variable Selection for Latent Class Analysis + maintainer: Michael Fop + description: 'Variable selection for latent class analysis for model-based clustering + of multivariate categorical data. The package implements a general framework for + selecting the subset of variables with relevant clustering information and discard + those that are redundant and/or not informative. The variable selection method + is based on the approach of Fop et al. (2017) and Dean + and Raftery (2010) . Different algorithms are available + to perform the selection: stepwise, swap-stepwise and evolutionary stochastic + search. Concomitant covariates used to predict the class membership probabilities + can also be included in the latent class analysis model. The selection procedure + can be run in parallel on multiple cores machines.' + date_publication: '2018-01-04' + bug_reports: '' + url: https://michaelfop.github.io/ + url_cran: https://CRAN.R-project.org/package=LCAvarsel + url_git: '' +lcc: + version: 1.1.4 + title: Longitudinal Concordance Correlation + maintainer: Thiago de Paula Oliveira + description: Estimates the longitudinal concordance correlation to access the longitudinal + agreement profile. The estimation approach implemented is variance components + approach based on polynomial mixed effects regression model, as proposed by Oliveira, + Hinde and Zocchi (2018) . In addition, non-parametric + confidence intervals were implemented using percentile method or normal-approximation + based on Fisher Z-transformation. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lcc + url_git: '' +LCCR: + version: '2.0' + title: Latent Class Capture-Recapture Models + maintainer: Francesco Bartolucci + description: Estimation of latent class models with individual covariates for capture-recapture + data. See Bartolucci, F. and Forcina, A. (2022), Estimating the size of a closed + population by modeling latent and observed heterogeneity, Biometrics, 80(2), ujae017. + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LCCR + url_git: '' +lcda: + version: 0.3.2 + title: Latent Class Discriminant Analysis + maintainer: Michael Buecker + description: Providing a method for Local Discrimination via Latent Class Models. + The approach is described in . + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lcda + url_git: '' +LCF: + version: 1.7.0 + title: Linear Combination Fitting + maintainer: Florian Werner + description: |- + Baseline correction, normalization and linear combination fitting (LCF) + of X-ray absorption near edge structure (XANES) spectra. + The package includes data loading of .xmu files exported from 'ATHENA' (Ravel and Newville, 2005) . + Loaded spectra can be background corrected and all standards can be fitted at once. + Two linear combination fitting functions can be used: + (1) fit_athena(): Simply fitting combinations of standards as in ATHENA, + (2) fit_float(): Fitting all standards with changing baseline correction and edge-step normalization parameters. + date_publication: '2017-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LCF + url_git: '' +LCFdata: + version: '2.0' + title: Data sets for package ``LMERConvenienceFunctions'' + maintainer: Antoine Tremblay + description: This package contains (1) event-related brain potential data recorded + from 10 participants at electrodes Fz, Cz, Pz, and Oz (0--300 ms) in the context + of Antoine Tremblay's PhD thesis (Tremblay, 2009); (2) ERP amplitudes at electrode + Fz restricted to the 100 to 175 millisecond time window; and (3) plotting data + generated from a linear mixed-effects model. + date_publication: '2013-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LCFdata + url_git: '' +lchemix: + version: 0.1.0 + title: A Bayesian Multi-Dimensional Couple-Based Latent Risk Model + maintainer: Weimin Zhang + description: 'A joint latent class model where a hierarchical structure exists, + with an interaction between female and male partners of a couple. A Bayesian perspective + to inference and Markov chain Monte Carlo algorithms to obtain posterior estimates + of model parameters. The reference paper is: Beom Seuk Hwang, Zhen Chen, Germaine + M.Buck Louis, Paul S. Albert, (2018) "A Bayesian multi-dimensional couple-based + latent risk model with an application to infertility". Biometrics, 75, 315-325. + .' + date_publication: '2020-02-28' + bug_reports: http://github.com/wzhang17/lchemix/issues + url: https://doi.org/10.1111/biom.12972 + url_cran: https://CRAN.R-project.org/package=lchemix + url_git: http://github.com/wzhang17/lchemix.git +LCMCR: + version: 0.4.14 + title: Bayesian Non-Parametric Latent-Class Capture-Recapture + maintainer: Daniel Manrique-Vallier + description: Bayesian population size estimation using non parametric latent-class + models. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LCMCR + url_git: '' +lcmm: + version: 2.2.1 + title: Extended Mixed Models Using Latent Classes and Latent Processes + maintainer: Cecile Proust-Lima + description: Estimation of various extensions of the mixed models including latent + class mixed models, joint latent class mixed models, mixed models for curvilinear + outcomes, mixed models for multivariate longitudinal outcomes using a maximum + likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) ). + date_publication: '2025-02-12' + bug_reports: https://github.com/CecileProust-Lima/lcmm/issues + url: https://cecileproust-lima.github.io/lcmm/ + url_cran: https://CRAN.R-project.org/package=lcmm + url_git: '' +LCMSQA: + version: 1.0.2 + title: |- + Liquid Chromatography/Mass Spectrometry (LC/MS) Quality + Assessment + maintainer: Jaehyun Joo + description: |- + The goal of 'LCMSQA' is to make it easy to check the quality of + liquid chromatograph/mass spectrometry (LC/MS) experiments using a + 'shiny' application. This package provides interactive data + visualizations for quality control (QC) samples, including total + ion current chromatogram (TIC), base peak chromatogram (BPC), mass + spectrum, extracted ion chromatogram (XIC), and feature detection + results from internal standards or known metabolites. + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LCMSQA + url_git: '' +lconnect: + version: 0.1.2 + title: Simple Tools to Compute Landscape Connectivity Metrics + maintainer: Frederico Mestre + description: |- + Provides functions to upload vectorial data and derive landscape + connectivity metrics in habitat or matrix systems. Additionally, includes an + approach to assess individual patch contribution to the overall landscape + connectivity, enabling the prioritization of habitat patches. The computation + of landscape connectivity and patch importance are very useful in Landscape + Ecology research. The metrics available are: number of components, number of + links, size of the largest component, mean size of components, class coincidence + probability, landscape coincidence probability, characteristic path length, + expected cluster size, area-weighted flux and integral index of connectivity. + Pascual-Hortal, L., and Saura, S. (2006) + Urban, D., and Keitt, T. (2001) + Laita, A., Kotiaho, J., Monkkonen, M. (2011) . + date_publication: '2024-03-09' + bug_reports: https://github.com/FMestre1/lconnect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lconnect + url_git: '' +lcopula: + version: 1.0.7 + title: Liouville Copulas + maintainer: Leo Belzile + description: |- + Collections of functions allowing random number generations and + estimation of 'Liouville' copulas, as described in Belzile and Neslehova (2017) . + date_publication: '2023-12-05' + bug_reports: https://github.com/lbelzile/lcopula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lcopula + url_git: '' +lcpm: + version: 0.1.1 + title: 'Ordinal Outcomes: Generalized Linear Models with the Log Link' + maintainer: Gurbakhshash Singh + description: |- + An implementation of the Log Cumulative Probability Model (LCPM) + and Proportional Probability Model (PPM) for which the Maximum Likelihood Estimates are determined using constrained optimization. + This implementation accounts for the implicit constraints on the parameter space. Other + features such as standard errors, z tests and p-values use standard methods adapted from the results based on constrained optimization. + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lcpm + url_git: '' +lcra: + version: 1.1.5 + title: Bayesian Joint Latent Class and Regression Models + maintainer: Michael Kleinsasser + description: |- + For fitting Bayesian joint latent class and regression models using + Gibbs sampling. See the documentation for the model. + The technical details of the model implemented here are described in Elliott, + Michael R., Zhao, Zhangchen, Mukherjee, Bhramar, Kanaya, Alka, Needham, + Belinda L., "Methods to account for uncertainty in latent class assignments when + using latent classes as predictors in regression models, with application to + acculturation strategy measures" (2020) In press at Epidemiology + . + date_publication: '2024-03-08' + bug_reports: https://github.com/umich-biostatistics/lcra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lcra + url_git: https://github.com/umich-biostatistics/lcra +lcsm: + version: 0.3.2 + title: Univariate and Bivariate Latent Change Score Modelling + maintainer: Milan Wiedemann + description: |- + Helper functions to implement univariate and bivariate latent change score models in R using the 'lavaan' package. + For details about Latent Change Score Modeling (LCSM) see McArdle (2009) and Grimm, An, McArdle, Zonderman and Resnick (2012) . + The package automatically generates 'lavaan' syntax for different model specifications and varying timepoints. + The 'lavaan' syntax generated by this package can be returned and further specifications can be added manually. + Longitudinal plots as well as simplified path diagrams can be created to visualise data and model specifications. + Estimated model parameters and fit statistics can be extracted as data frames. + Data for different univariate and bivariate LCSM can be simulated by specifying estimates for model parameters to explore their effects. + This package combines the strengths of other R packages like 'lavaan', 'broom', and 'semPlot' by generating 'lavaan' syntax that helps these packages work together. + date_publication: '2023-02-25' + bug_reports: https://github.com/milanwiedemann/lcsm/issues + url: https://milanwiedemann.github.io/lcsm/ + url_cran: https://CRAN.R-project.org/package=lcsm + url_git: '' +lctools: + version: 0.2-10 + title: |- + Local Correlation, Spatial Inequalities, Geographically Weighted + Regression and Other Tools + maintainer: Stamatis Kalogirou + description: |- + Provides researchers and educators with easy-to-learn user friendly tools for calculating + key spatial statistics and to apply simple as well as advanced methods of spatial analysis in real data. + These include: Local Pearson and Geographically Weighted Pearson Correlation Coefficients, + Spatial Inequality Measures (Gini, Spatial Gini, LQ, Focal LQ), Spatial Autocorrelation + (Global and Local Moran's I), several Geographically Weighted Regression techniques and other + Spatial Analysis tools (other geographically weighted statistics). This package also contains functions for + measuring the significance of each statistic calculated, mainly based on Monte Carlo simulations. + date_publication: '2024-04-01' + bug_reports: '' + url: https://stamatisgeoai.eu + url_cran: https://CRAN.R-project.org/package=lctools + url_git: '' +lcyanalysis: + version: 1.0.4 + title: Stock Data Analysis Functions + maintainer: Chun-Yu Liu + description: Analysis of stock data ups and downs trend, the stock technical analysis + indicators function have trend line, reversal pattern and market trend. + date_publication: '2020-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lcyanalysis + url_git: '' +lda: + version: 1.5.2 + title: Collapsed Gibbs Sampling Methods for Topic Models + maintainer: Santiago Olivella + description: |- + Implements latent Dirichlet allocation (LDA) + and related models. This includes (but is not limited + to) sLDA, corrLDA, and the mixed-membership stochastic + blockmodel. Inference for all of these models is + implemented via a fast collapsed Gibbs sampler written + in C. Utility functions for reading/writing data + typically used in topic models, as well as tools for + examining posterior distributions are also included. + date_publication: '2024-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lda + url_git: '' +LDAandLDAS: + version: 1.1.3 + title: Linkage Disequilibrium of Ancestry (LDA) and LDA Score (LDAS) + maintainer: Yaoling Yang + description: Computation of linkage disequilibrium of ancestry (LDA) and linkage + disequilibrium of ancestry score (LDAS). LDA calculates the pairwise linkage disequilibrium + of ancestry between single nucleotide polymorphisms (SNPs). LDAS calculates the + LDA score of SNPs. The methods are described in Barrie W, Yang Y, Irving-Pease + E.K, et al (2024) . + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LDAandLDAS + url_git: '' +LDABiplots: + version: 0.1.2 + title: Biplot Graphical Interface for LDA Models + maintainer: Luis Pilacuan-Bonete + description: |- + Contains the development of a tool that provides a web-based graphical + user interface (GUI) to perform Biplots representations from a scraping of + news from digital newspapers under the Bayesian approach of Latent Dirichlet + Assignment (LDA) and machine learning algorithms. Contains LDA methods + described by Blei , David M., Andrew Y. Ng and Michael I. Jordan (2003) + , + and Biplot methods described by Gabriel K.R(1971) + and Galindo-Villardon P(1986) . + date_publication: '2022-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LDABiplots + url_git: '' +LDAcoop: + version: 0.1.2 + title: |- + Analysis of Data from Limiting Dilution Assay (LDA) with or + without Cellular Cooperation + maintainer: Daniel Samaga + description: |- + Cellular cooperation compromises the established method of + calculating clonogenic activity from limiting dilution assay (LDA) data. + This tool provides functions that enable robust analysis in presence or + absence of cellular cooperation. The implemented method incorporates the + same cooperativity module to model the non-linearity associated with + cellular cooperation as known from the colony formation assay (Brix et al. + (2021) : "Analysis of clonogenic growth in + vitro." Nature protocols). + date_publication: '2024-07-17' + bug_reports: https://github.com/ZytoHMGU/LDAcoop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LDAcoop + url_git: https://github.com/ZytoHMGU/LDAcoop +ldamatch: + version: 1.0.3 + title: Selection of Statistically Similar Research Groups + maintainer: Kyle Gorman + description: Select statistically similar research groups by backward selection + using various robust algorithms, including a heuristic based on linear discriminant + analysis, multiple heuristics based on the test statistic, and parallelized exhaustive + search. + date_publication: '2024-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ldamatch + url_git: '' +ldaPrototype: + version: 0.3.1 + title: Prototype of Multiple Latent Dirichlet Allocation Runs + maintainer: Jonas Rieger + description: 'Determine a Prototype from a number of runs of Latent Dirichlet Allocation + (LDA) measuring its similarities with S-CLOP: A procedure to select the LDA run + with highest mean pairwise similarity, which is measured by S-CLOP (Similarity + of multiple sets by Clustering with Local Pruning), to all other runs. LDA runs + are specified by its assignments leading to estimators for distribution parameters. + Repeated runs lead to different results, which we encounter by choosing the most + representative LDA run as prototype.' + date_publication: '2021-09-02' + bug_reports: https://github.com/JonasRieger/ldaPrototype/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ldaPrototype + url_git: https://github.com/JonasRieger/ldaPrototype +LDAShiny: + version: 0.9.3 + title: User-Friendly Interface for Review of Scientific Literature + maintainer: Javier De La Hoz Maestre + description: |- + Contains the development of a tool that provides a + web-based graphical user interface (GUI) to perform a review of the + scientific literature under the Bayesian approach of Latent Dirichlet + Allocation (LDA)and machine learning algorithms. The application + methodology is framed by the well known procedures in topic modelling + on how to clean and process data. Contains methods described by + Blei, David M., Andrew Y. Ng, and Michael I. Jordan (2003) + + Allocation"; Thomas L. Griffiths and Mark Steyvers (2004) + ; Xiong Hui, et al (2019) + . + date_publication: '2021-03-29' + bug_reports: https://github.com/JavierDeLaHoz/LDAShiny/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LDAShiny + url_git: '' +LDATree: + version: 0.2.0 + title: |- + Oblique Classification Trees with Uncorrelated Linear + Discriminant Analysis Splits + maintainer: Siyu Wang + description: A classification tree method that uses Uncorrelated Linear Discriminant + Analysis (ULDA) for variable selection, split determination, and model fitting + in terminal nodes. It automatically handles missing values and offers visualization + tools. For more details, see Wang (2024) . + date_publication: '2024-10-31' + bug_reports: https://github.com/Moran79/LDATree/issues + url: http://iamwangsiyu.com/LDATree/ + url_cran: https://CRAN.R-project.org/package=LDATree + url_git: https://github.com/Moran79/LDATree +LDATS: + version: 0.3.0 + title: Latent Dirichlet Allocation Coupled with Time Series Analyses + maintainer: Juniper L. Simonis + description: Combines Latent Dirichlet Allocation (LDA) and Bayesian multinomial + time series methods in a two-stage analysis to quantify dynamics in high-dimensional + temporal data. LDA decomposes multivariate data into lower-dimension latent groupings, + whose relative proportions are modeled using generalized Bayesian time series + models that include abrupt changepoints and smooth dynamics. The methods are described + in Blei et al. (2003) , Western and Kleykamp + (2004) , Venables and Ripley (2002, ISBN-13:978-0387954578), + and Christensen et al. (2018) . + date_publication: '2023-09-19' + bug_reports: https://github.com/weecology/LDATS/issues + url: https://weecology.github.io/LDATS/ + url_cran: https://CRAN.R-project.org/package=LDATS + url_git: https://github.com/weecology/LDATS +ldatuning: + version: 1.0.2 + title: Tuning of the Latent Dirichlet Allocation Models Parameters + maintainer: Nathan Chaney + description: |- + For this first version only metrics to estimate the best fitting + number of topics are implemented. + date_publication: '2020-04-21' + bug_reports: https://github.com/nikita-moor/ldatuning/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ldatuning + url_git: https://github.com/nikita-moor/ldatuning +LDAvis: + version: 0.3.2 + title: Interactive Visualization of Topic Models + maintainer: Carson Sievert + description: |- + Tools to create an interactive web-based visualization of a + topic model that has been fit to a corpus of text data using + Latent Dirichlet Allocation (LDA). Given the estimated parameters of + the topic model, it computes various summary statistics as input to + an interactive visualization built with D3.js that is accessed via + a browser. The goal is to help users interpret the topics in their + LDA topic model. + date_publication: '2015-10-24' + bug_reports: https://github.com/cpsievert/LDAvis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LDAvis + url_git: https://github.com/cpsievert/LDAvis +ldbod: + version: 0.1.2 + title: Local Density-Based Outlier Detection + maintainer: Kristopher Williams + description: |- + Flexible procedures to compute local density-based outlier scores for ranking outliers. + Both exact and approximate nearest neighbor search can be implemented, while also accommodating + multiple neighborhood sizes and four different local density-based methods. It allows for + referencing a random subsample of the input data or a user specified reference data set + to compute outlier scores against, so both unsupervised and semi-supervised outlier + detection can be implemented. + date_publication: '2017-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ldbod + url_git: https://github.com/kwilliams83/ldbod +ldbounds: + version: 2.0.2 + title: Lan-DeMets Method for Group Sequential Boundaries + maintainer: Charlie Casper + description: |- + Computations related to group sequential boundaries. + Includes calculation of bounds using the Lan-DeMets + alpha spending function approach. Based on FORTRAN + program ld98 implemented by Reboussin, et al. (2000) . + date_publication: '2023-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ldbounds + url_git: '' +LDcorSV: + version: 1.3.3 + title: |- + Linkage Disequilibrium Corrected by the Structure and the + Relatedness + maintainer: Aurélie Siberchicot + description: |- + Four measures of linkage disequilibrium are provided: the usual r^2 + measure, the r^2_S measure (r^2 corrected by the structure + sample), the r^2_V (r^2 corrected by the relatedness of + genotyped individuals), the r^2_VS measure (r^2 corrected by + both the relatedness of genotyped individuals and the structure + of the sample). + date_publication: '2020-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LDcorSV + url_git: '' +lddmm: + version: 0.4.2 + title: Longitudinal Drift-Diffusion Mixed Models (LDDMM) + maintainer: Giorgio Paulon + description: Implementation of the drift-diffusion mixed model for category learning + as described in Paulon et al. (2021) . + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lddmm + url_git: '' +ldhmm: + version: 0.6.1 + title: |- + Hidden Markov Model for Financial Time-Series Based on Lambda + Distribution + maintainer: Stephen H-T. Lihn + description: |- + Hidden Markov Model (HMM) based on symmetric lambda distribution + framework is implemented for the study of return time-series in the financial + market. Major features in the S&P500 index, such as regime identification, + volatility clustering, and anti-correlation between return and volatility, + can be extracted from HMM cleanly. Univariate symmetric lambda distribution + is essentially a location-scale family of exponential power distribution. + Such distribution is suitable for describing highly leptokurtic time series + obtained from the financial market. It provides a theoretically solid foundation + to explore such data where the normal distribution is not adequate. The HMM + implementation follows closely the book: "Hidden Markov Models for Time Series", + by Zucchini, MacDonald, Langrock (2016). + date_publication: '2023-12-11' + bug_reports: '' + url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2979516https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3435667 + url_cran: https://CRAN.R-project.org/package=ldhmm + url_git: '' +LDlinkR: + version: 1.4.0 + title: |- + Calculating Linkage Disequilibrium (LD) in Human Population + Groups of Interest + maintainer: Timothy A. Myers + description: |- + Provides access to the 'LDlink' API () + using the R console. This programmatic access facilitates researchers who are + interested in performing batch queries in 1000 Genomes Project (2015) + data using 'LDlink'. 'LDlink' is an interactive and powerful suite of web-based tools for querying + germline variants in human population groups of interest. For more details, please see + Machiela et al. (2015) . + date_publication: '2024-04-10' + bug_reports: https://github.com/CBIIT/LDlinkR/issues + url: https://ldlink.nih.gov + url_cran: https://CRAN.R-project.org/package=LDlinkR + url_git: '' +LDM: + version: 6.0.1 + title: |- + Testing Hypotheses About the Microbiome using the Linear + Decomposition Model + maintainer: Yi-Juan Hu + description: A single analysis path that includes distance-based ordination, global + tests of any effect of the microbiome, and tests of the effects of individual + taxa with false-discovery-rate (FDR) control. It accommodates both continuous + and discrete covariates as well as interaction terms to be tested either singly + or in combination, allows for adjustment of confounding covariates, and uses permutation-based + p-values that can control for sample correlations. It can be applied to transformed + data, and an omnibus test can combine results from analyses conducted on different + transformation scales. It can also be used for testing presence-absence associations + based on infinite number of rarefaction replicates, testing mediation effects + of the microbiome, analyzing censored time-to-event outcomes, and for compositional + analysis by fitting linear models to centered-log-ratio taxa count data. + date_publication: '2023-09-07' + bug_reports: https://github.com/yijuanhu/LDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LDM + url_git: https://github.com/yijuanhu/LDM +ldmppr: + version: 1.0.4 + title: |- + Estimate and Simulate from Location Dependent Marked Point + Processes + maintainer: Lane Drew + description: |- + A suite of tools for estimating, assessing model fit, simulating from, and visualizing location dependent marked point processes characterized by regularity in the pattern. + You provide a reference marked point process, a set of raster images containing location specific covariates, and select the estimation algorithm and type of mark model. + 'ldmppr' estimates the process and mark models and allows you to check the appropriateness of the model using a variety of diagnostic tools. + Once a satisfactory model fit is obtained, you can simulate from the model and visualize the results. + Documentation for the package 'ldmppr' is available in the form of a vignette. + date_publication: '2025-02-24' + bug_reports: https://github.com/lanedrew/ldmppr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ldmppr + url_git: https://github.com/lanedrew/ldmppr +LDNN: + version: '1.10' + title: Longitudinal Data Neural Network + maintainer: Vasileios Karapoulios + description: This is a Neural Network regression model implementation using 'Keras', + consisting of 10 Long Short-Term Memory layers that are fully connected along + with the rest of the inputs. + date_publication: '2020-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LDNN + url_git: '' +LDRTools: + version: 0.2-2 + title: Tools for Linear Dimension Reduction + maintainer: Klaus Nordhausen + description: Linear dimension reduction subspaces can be uniquely defined using + orthogonal projection matrices. This package provides tools to compute distances + between such subspaces and to compute the average subspace. For details see Liski, + E.Nordhausen K., Oja H., Ruiz-Gazen A. (2016) Combining Linear Dimension Reduction + Subspaces . + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LDRTools + url_git: '' +ldsep: + version: 2.1.5 + title: Linkage Disequilibrium Shrinkage Estimation for Polyploids + maintainer: David Gerard + description: |- + Estimate haplotypic or composite pairwise linkage disequilibrium + (LD) in polyploids, using either genotypes or genotype likelihoods. + Support is provided to estimate the popular measures of LD: the LD + coefficient D, the standardized LD coefficient D', and the Pearson + correlation coefficient r. All estimates are returned with corresponding + standard errors. These estimates and standard errors can then be used + for shrinkage estimation. The main functions are ldfast(), ldest(), mldest(), + sldest(), plot.lddf(), format_lddf(), and ldshrink(). Details of the methods + are available in Gerard (2021a) + and Gerard (2021b) . + date_publication: '2022-10-18' + bug_reports: https://github.com/dcgerard/ldsep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ldsep + url_git: '' +ldsr: + version: 0.0.2 + title: Linear Dynamical System Reconstruction + maintainer: Hung Nguyen + description: |- + Streamflow (and climate) reconstruction using Linear Dynamical Systems. + The advantage of this method is the additional state trajectory which can reveal more information + about the catchment or climate system. For details of the method please refer to Nguyen and Galelli + (2018) . + date_publication: '2020-05-04' + bug_reports: https://github.com/ntthung/ldsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ldsr + url_git: https://github.com/ntthung/ldsr +ldt: + version: 0.5.3 + title: Automated Uncertainty Analysis + maintainer: Ramin Mojab + description: |- + Methods and tools for model selection and multi-model inference (Burnham and Anderson (2002) , among others). + 'SUR' (for parameter estimation), 'logit'/'probit' (for binary classification), and 'VARMA' (for time-series forecasting) are implemented. + Evaluations are both in-sample and out-of-sample. + It is designed to be efficient in terms of CPU usage and memory consumption. + date_publication: '2024-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ldt + url_git: https://github.com/rmojab63/LDT +leabRa: + version: 0.1.0 + title: The Artificial Neural Networks Algorithm Leabra + maintainer: Johannes Titz + description: |- + The algorithm Leabra (local error driven and associative + biologically realistic algorithm) allows for the construction of artificial + neural networks that are biologically realistic and balance supervised and + unsupervised learning within a single framework. This package is based on + the 'MATLAB' version by Sergio Verduzco-Flores, which in turn was based on + the description of the algorithm by Randall O'Reilly (1996) + . For + more general (not 'R' specific) information on the algorithm Leabra see + . + date_publication: '2017-09-22' + bug_reports: https://github.com/johannes-titz/leabRa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leabRa + url_git: https://github.com/johannes-titz/leabRa +leaderCluster: + version: '1.5' + title: Leader Clustering Algorithm + maintainer: Taylor B. Arnold + description: |- + The leader clustering algorithm provides + a means for clustering a set of data points. Unlike many other clustering + algorithms it does not require the user to specify the number of clusters, + but instead requires the approximate radius of a cluster as its primary + tuning parameter. The package provides a fast implementation of this + algorithm in n-dimensions using Lp-distances (with special cases for p=1,2, + and infinity) as well as for spatial data using the Haversine + formula, which takes latitude/longitude pairs as inputs and clusters + based on great circle distances. + date_publication: '2023-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leaderCluster + url_git: '' +LeadSense: + version: 0.0.1.0000 + title: Medtronic Brain Sense Local Field Potencial Analysis + maintainer: Paulo Bastos + description: Extracts and creates an analysis pipeline for the JSON data files from + Brain Sense sessions using Medtronic's Deep Brain Stimulation surgery electrode + implants. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LeadSense + url_git: '' +LeafArea: + version: 0.1.8 + title: Rapid Digital Image Analysis of Leaf Area + maintainer: Masatoshi Katabuchi + description: |- + An interface for the image processing program 'ImageJ', which + allows a rapid digital image analysis for particle sizes. This package includes + function to write an 'ImageJ' macro which is optimized for a leaf area analysis by + default. + date_publication: '2019-07-03' + bug_reports: https://github.com/mattocci27/LeafArea/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LeafArea + url_git: https://github.com/mattocci27/LeafArea +leafdown: + version: 1.2.0 + title: Provides Drill Down Functionality for 'leaflet' Choropleths + maintainer: Andreas Hofheinz + description: Provides drill down functionality for 'leaflet' choropleths in 'shiny' + apps. + date_publication: '2022-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leafdown + url_git: '' +leafem: + version: 0.2.3 + title: '''leaflet'' Extensions for ''mapview''' + maintainer: Tim Appelhans + description: |- + Provides extensions for packages 'leaflet' & 'mapdeck', + many of which are used by package 'mapview'. + Focus is on functionality readily available in + Geographic Information Systems such as 'Quantum GIS'. Includes functions + to display coordinates of mouse pointer position, query image values via + mouse pointer and zoom-to-layer buttons. Additionally, provides a feature + type agnostic function to add points, lines, polygons to a map. + date_publication: '2023-09-17' + bug_reports: https://github.com/r-spatial/leafem/issues + url: https://r-spatial.github.io/leafem/ + url_cran: https://CRAN.R-project.org/package=leafem + url_git: https://github.com/r-spatial/leafem +leafgl: + version: 0.2.2 + title: High-Performance 'WebGl' Rendering for Package 'leaflet' + maintainer: Tim Appelhans + description: Provides bindings to the 'Leaflet.glify' JavaScript library which extends + the 'leaflet' JavaScript library to render large data in the browser using 'WebGl'. + date_publication: '2024-11-13' + bug_reports: https://github.com/r-spatial/leafgl/issues + url: https://r-spatial.github.io/leafgl/ + url_cran: https://CRAN.R-project.org/package=leafgl + url_git: https://github.com/r-spatial/leafgl +leaflegend: + version: 1.2.1 + title: Add Custom Legends to 'leaflet' Maps + maintainer: Thomas Roh + description: |- + Provides extensions to the 'leaflet' package to + customize legends with images, text styling, orientation, sizing, + and symbology and functions to create symbols to plot on maps. + date_publication: '2024-05-09' + bug_reports: https://github.com/tomroh/leaflegend/issues + url: https://leaflegend.delveds.com + url_cran: https://CRAN.R-project.org/package=leaflegend + url_git: https://github.com/tomroh/leaflegend +leaflet: + version: 2.2.2 + title: |- + Create Interactive Web Maps with the JavaScript 'Leaflet' + Library + maintainer: Joe Cheng + description: |- + Create and customize interactive maps using the 'Leaflet' + JavaScript library and the 'htmlwidgets' package. These maps can be + used directly from the R console, from 'RStudio', in Shiny + applications and R Markdown documents. + date_publication: '2024-03-26' + bug_reports: https://github.com/rstudio/leaflet/issues + url: https://rstudio.github.io/leaflet/ + url_cran: https://CRAN.R-project.org/package=leaflet + url_git: https://github.com/rstudio/leaflet +leaflet.esri: + version: 1.0.0 + title: '''ESRI'' Bindings for the ''leaflet'' Package' + maintainer: Bhaskar Karambelkar + description: An add-on package to the 'leaflet' package, which provides bindings + for 'ESRI' services. This package allows a user to add 'ESRI' provided services + such as 'MapService', 'ImageMapService', 'TiledMapService' etc. to a 'leaflet' + map. + date_publication: '2018-04-23' + bug_reports: https://github.com/bhaskarvk/leaflet.esri/issues + url: https://bhaskarvk.github.io/leaflet.esri/ + url_cran: https://CRAN.R-project.org/package=leaflet.esri + url_git: https://github.com/bhaskarvk/leaflet.esri +leaflet.extras: + version: 2.0.1 + title: Extra Functionality for 'leaflet' Package + maintainer: Sebastian Gatscha + description: |- + The 'leaflet' JavaScript library provides many plugins some of which + are available in the core 'leaflet' package, but there are many more. It is not + possible to support them all in the core 'leaflet' package. This package serves + as an add-on to the 'leaflet' package by providing extra functionality via 'leaflet' + plugins. + date_publication: '2024-08-19' + bug_reports: https://github.com/trafficonese/leaflet.extras/issues + url: https://trafficonese.github.io/leaflet.extras/ + url_cran: https://CRAN.R-project.org/package=leaflet.extras + url_git: https://github.com/trafficonese/leaflet.extras +leaflet.extras2: + version: 1.3.0 + title: Extra Functionality for 'leaflet' Package + maintainer: Gatscha Sebastian + description: Several 'leaflet' plugins are integrated, which are available as extension + to the 'leaflet' package. + date_publication: '2025-01-12' + bug_reports: https://github.com/trafficonese/leaflet.extras2/issues + url: https://trafficonese.github.io/leaflet.extras2/ + url_cran: https://CRAN.R-project.org/package=leaflet.extras2 + url_git: https://github.com/trafficonese/leaflet.extras2 +leaflet.minicharts: + version: 0.6.2 + title: Mini Charts for Interactive Maps + maintainer: Veronique Bachelier + description: |- + Add and modify small charts on an interactive map created with + package 'leaflet'. These charts can be used to represent at same time multiple + variables on a single map. + date_publication: '2021-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leaflet.minicharts + url_git: '' +leaflet.providers: + version: 2.0.0 + title: Leaflet Providers + maintainer: Barret Schloerke + description: |- + Contains third-party map tile provider information from + 'Leaflet.js', , + to be used with the 'leaflet' R package. Additionally, + 'leaflet.providers' enables users to retrieve up-to-date provider + information between package updates. + date_publication: '2023-10-17' + bug_reports: https://github.com/rstudio/leaflet.providers/issues + url: https://rstudio.github.io/leaflet.providers/ + url_cran: https://CRAN.R-project.org/package=leaflet.providers + url_git: https://github.com/rstudio/leaflet.providers +leafletZH: + version: 0.1.1 + title: Chinese Leaflet Map Relate Operation + maintainer: Damonsoul + description: |- + Provides 'sf' data for Chinese provinces and cities, + methods for plotting shape maps of Chinese provinces and cities, + Convert Coordinates Between Different Systems, + and a layer for 'leaflet' with Gaode tiles. + It is designed to facilitate geographical data visualization in China. + date_publication: '2024-11-10' + bug_reports: '' + url: https://damonsoul.github.io/leafletZH/ + url_cran: https://CRAN.R-project.org/package=leafletZH + url_git: '' +leafpm: + version: 0.1.0 + title: Leaflet Map Plugin for Drawing and Editing + maintainer: Kenton Russell + description: |- + A collection of tools for interactive manipulation of (spatial) data + layers on leaflet web maps. Tools include editing of existing layers, creation + of new layers through drawing of shapes (points, lines, polygons), deletion + of shapes as well as cutting holes into existing shapes. Provides control over + options to e.g. prevent self-intersection of polygons and lines or to enable/disable + snapping to align shapes. + date_publication: '2019-03-13' + bug_reports: https://github.com/r-spatial/leafpm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leafpm + url_git: https://github.com/r-spatial/leafpm +leafpop: + version: 0.1.0 + title: Include Tables, Images and Graphs in Leaflet Pop-Ups + maintainer: Tim Appelhans + description: |- + Creates 'HTML' strings to embed tables, images or graphs in pop-ups + of interactive maps created with packages like 'leaflet' or 'mapview'. Handles + local images located on the file system or via remote URL. Handles graphs created + with 'lattice' or 'ggplot2' as well as interactive plots created with 'htmlwidgets'. + date_publication: '2021-05-22' + bug_reports: https://github.com/r-spatial/leafpop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leafpop + url_git: https://github.com/r-spatial/leafpop +leafR: + version: 0.3.5 + title: Calculates the Leaf Area Index (LAD) and Other Related Functions + maintainer: Danilo Roberti Alves de Almeida + description: |- + A set of functions for analyzing the structure + of forests based on the leaf area density (LAD) and leaf area index (LAI) measures + calculated from Airborne Laser Scanning (ALS), i.e., scanning lidar (Light Detection + and Ranging) data. The methodology is discussed and described in + Almeida et al. (2019) and + Stark et al. (2012) . + date_publication: '2021-07-04' + bug_reports: https://github.com/DRAAlmeida/leafR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leafR + url_git: https://github.com/DRAAlmeida/leafR +leafSTAR: + version: '1.0' + title: Silhouette to Area Ratio of Tilted Surfaces + maintainer: Agustina Ventre Lespiaucq + description: Implementation of trigonometric functions to calculate the exposure + of flat, tilted surfaces, such as leaves and slopes, to direct solar radiation. + It implements the equations in A.G. Escribano-Rocafort, A. Ventre-Lespiaucq, C. + Granado-Yela, et al. (2014) in a few user-friendly + R functions. All functions handle data obtained with 'Ahmes' 1.0 for Android, + as well as more traditional data sources (compass, protractor, inclinometer). + The main function (star()) calculates the potential exposure of flat, tilted surfaces + to direct solar radiation (silhouette to area ratio, STAR). It is equivalent to + the ratio of the leaf projected area to total leaf area, but instead of using + area data it uses spatial position angles, such as pitch, roll and course, and + information on the geographical coordinates, hour, and date. The package includes + additional functions to recalculate STAR with custom settings of location and + time, to calculate the tilt angle of a surface, and the minimum angle between + two non-orthogonal planes. + date_publication: '2017-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leafSTAR + url_git: '' +leafsync: + version: 0.1.0 + title: Small Multiples for Leaflet Web Maps + maintainer: Tim Appelhans + description: |- + Create small multiples of several leaflet web maps with (optional) + synchronised panning and zooming control. When syncing is enabled all maps + respond to mouse actions on one map. This allows side-by-side comparisons + of different attributes of the same geometries. Syncing can be adjusted + so that any combination of maps can be synchronised. + date_publication: '2019-03-05' + bug_reports: https://github.com/r-spatial/leafsync/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leafsync + url_git: https://github.com/r-spatial/leafsync +leaftime: + version: 0.2.0 + title: '''Leaflet-timeline'' Plugin for Leaflet' + maintainer: Kent Russell + description: |- + Use the 'leaflet-timeline' plugin with a leaflet widget to add an + interactive slider with play, pause, and step buttons to explore temporal + geographic spatial data changes. + date_publication: '2020-01-26' + bug_reports: https://github.com/timelyportfolio/leaftime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leaftime + url_git: https://github.com/timelyportfolio/leaftime +leakyIV: + version: 0.0.1 + title: Leaky Instrumental Variables + maintainer: David S. Watson + description: |- + Instrumental variables (IVs) are a popular and powerful tool for + estimating causal effects in the presence of unobserved confounding. However, + classical methods rely on strong assumptions such as the exclusion criterion, + which states that instrumental effects must be entirely mediated by + treatments. In the so-called "leaky" IV setting, candidate instruments are + allowed to have some direct influence on outcomes, rendering the average + treatment effect (ATE) unidentifiable. But with limits on the amount of + information leakage, we may still recover sharp bounds on the ATE, providing + partial identification. This package implements methods for ATE bounding in + the leaky IV setting with linear structural equations. For details, see Watson + et al. (2024) . + date_publication: '2024-04-09' + bug_reports: https://github.com/dswatson/leakyIV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leakyIV + url_git: https://github.com/dswatson/leakyIV +leanpubr: + version: 0.3.1 + title: '''Leanpub'' API Interface' + maintainer: John Muschelli + description: |- + Provides access to the 'Leanpub' API + for gathering information about + publications and submissions to the 'Leanpub' platform. + date_publication: '2018-08-16' + bug_reports: https://github.com/muschellij2/leanpubr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leanpubr + url_git: https://github.com/muschellij2/leanpubr +leapgp: + version: 1.0.0 + title: Localized Ensemble of Approximate Gaussian Processes + maintainer: Kellin Rumsey + description: An emulator designed for rapid sequential emulation (e.g., Markov chain + Monte Carlo applications). Works via extension of the 'laGP' approach by Gramacy + and Apley (2015 ). Details are given in Rumsey + et al. (2023 ). + date_publication: '2024-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leapgp + url_git: '' +leapp: + version: '1.3' + title: Latent Effect Adjustment After Primary Projection + maintainer: Yunting Sun + description: |- + These functions take a gene expression value matrix, a + primary covariate vector, an additional known covariates + matrix. A two stage analysis is applied to counter the effects + of latent variables on the rankings of hypotheses. The + estimation and adjustment of latent effects are proposed by + Sun, Zhang and Owen (2011). "leapp" is developed in the + context of microarray experiments, but may be used as a general + tool for high throughput data sets where dependence may be + involved. + date_publication: '2022-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leapp + url_git: '' +leaps: + version: '3.2' + title: Regression Subset Selection + maintainer: Thomas Lumley + description: Regression subset selection, including exhaustive search. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leaps + url_git: '' +LeArEst: + version: 1.0.0 + title: Border and Area Estimation of Data Measured with Additive Error + maintainer: Petar Taler + description: |- + Provides methods for estimating borders of uniform distribution on + the interval (one-dimensional) and on the elliptical domain (two-dimensional) + under measurement errors. For one-dimensional case, it also estimates the + length of underlying uniform domain and tests the hypothesized length against + two-sided or one-sided alternatives. For two-dimensional case, it estimates + the area of underlying uniform domain. It works with numerical inputs as well + as with pictures in JPG format. + date_publication: '2019-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LeArEst + url_git: '' +LearnBayes: + version: 2.15.1 + title: Functions for Learning Bayesian Inference + maintainer: Jim Albert + description: A collection of functions helpful in learning the basic tenets of Bayesian + statistical inference. It contains functions for summarizing basic one and two + parameter posterior distributions and predictive distributions. It contains MCMC + algorithms for summarizing posterior distributions defined by the user. It also + contains functions for regression models, hierarchical models, Bayesian tests, + and illustrations of Gibbs sampling. + date_publication: '2018-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LearnBayes + url_git: '' +LearnClust: + version: '1.1' + title: Learning Hierarchical Clustering Algorithms + maintainer: Roberto Alcantara + description: |- + Classical hierarchical clustering algorithms, agglomerative and divisive clustering. Algorithms are implemented as a theoretical way, step by step. + It includes some detailed functions that explain each step. Every function allows options to get different results using different techniques. + The package explains non expert users how hierarchical clustering algorithms work. + date_publication: '2020-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LearnClust + url_git: '' +learner: + version: 0.1.0 + title: Latent Space-Based Transfer Learning + maintainer: Sean McGrath + description: |- + Implements transfer learning methods for low-rank matrix + estimation. These methods leverage similarity in the latent row and column + spaces between the source and target populations to improve estimation in + the target population. The methods include the LatEnt spAce-based tRaNsfer + lEaRning (LEARNER) method and the direct projection LEARNER (D-LEARNER) + method described by McGrath et al. (2024) . + date_publication: '2025-01-08' + bug_reports: https://github.com/stmcg/learner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=learner + url_git: https://github.com/stmcg/learner +LearnGeom: + version: '1.5' + title: Learning Plane Geometry + maintainer: Alvaro Briz-Redon + description: Contains some functions to learn and teach basic plane Geometry at + undergraduate level with the aim of being helpful to young students with little + programming skills. + date_publication: '2020-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LearnGeom + url_git: '' +learningr: + version: 0.29.1 + title: Data and Functions to Accompany the Book "Learning R" + maintainer: Richie Cotton + description: |- + Crabs in the English channel, deer skulls, English + monarchs, half-caste Manga characters, Jamaican cities, + Shakespeare's The Tempest, drugged up cyclists and sexually + transmitted diseases. + date_publication: '2019-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=learningr + url_git: '' +LearningRlab: + version: '2.4' + title: Statistical Learning Functions + maintainer: Carlos Javier Hellin Asensio + description: Aids in learning statistical functions incorporating the result of + calculus done with each function and how they are obtained, that is, which equation + and variables are used. Also for all these equations and their related variables + detailed explanations and interactive exercises are also included. All these characteristics + allow to the package user to improve the learning of statistics basics by means + of their use. + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LearningRlab + url_git: '' +LearningStats: + version: 0.1.0 + title: Elemental Descriptive and Inferential Statistics + maintainer: María Isabel Borrajo-García + description: Provides tools to teach students elemental statistics. The main topics + covered are descriptive statistics, probability models (discrete and continuous + variables) and statistical inference (confidence intervals and hypothesis tests). + One of the main advantages of this package is that allows the user to read quite + a variety of types of data files with one unique command. Moreover it includes + shortcuts to simple but up-to-now not in R descriptive features such a complete + frequency table or an histogram with the optimal number of intervals. Related + to model distributions (both discrete and continuous), the package allows the + student to easy plot the mass/density function, distribution function and quantile + function just detailing as input arguments the known population parameters. The + inference related tools are basically confidence interval and hypothesis testing. + Having defined independent commands for these two tools makes it easier for the + student to understand what the software is performing, and it also helps the student + to have a better knowledge on which specific tool they need to use in each situation. + Moreover, the hypothesis testing commands provide not only the numeric result + on the screen but also a very intuitive graph (which includes the statistic distribution, + the observed value of the statistic, the rejection area and the p-value) that + is very useful for the student to visualise the process. The regression section + includes up to now, a simple linear model, with one single command the student + can obtain the numeric summary as well as the corresponding diagram with the adjusted + regression model and a legend with basic information (formula of the adjusted + model and R-squared). + date_publication: '2021-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LearningStats + url_git: '' +learningtower: + version: 1.1.0 + title: OECD PISA Datasets from 2000-2022 in an Easy-to-Use Format + maintainer: Kevin Wang + description: The Programme for International Student Assessment (PISA) is a global + study conducted by the Organization for Economic Cooperation and Development (OECD) + in member and non-member countries to assess educational systems by assessing + 15-year-old school students academic performance in mathematics, science, and + reading. This datasets contains information on their scores and other socioeconomic + characteristics, information about their school and its infrastructure, as well + as the countries that are taking part in the program. + date_publication: '2024-12-21' + bug_reports: https://github.com/kevinwang09/learningtower/issues + url: https://kevinwang09.github.io/learningtower/ + url_cran: https://CRAN.R-project.org/package=learningtower + url_git: https://github.com/kevinwang09/learningtower +LearnNonparam: + version: 1.2.7 + title: '''R6''-Based Flexible Framework for Permutation Tests' + maintainer: Yan Du + description: Implements non-parametric tests from Higgins (2004, ISBN:0534387756), + including tests for one sample, two samples, k samples, paired comparisons, blocked + designs, trends and association. Built with 'Rcpp' for efficiency and 'R6' for + flexible, object-oriented design, the package provides a unified framework for + performing or creating custom permutation tests. + date_publication: '2025-01-30' + bug_reports: https://github.com/qddyy/LearnNonparam/issues + url: https://qddyy.github.io/LearnNonparam/ + url_cran: https://CRAN.R-project.org/package=LearnNonparam + url_git: https://github.com/qddyy/LearnNonparam +LearnPCA: + version: 0.3.4 + title: |- + Functions, Data Sets and Vignettes to Aid in Learning Principal + Components Analysis (PCA) + maintainer: Bryan A. Hanson + description: Principal component analysis (PCA) is one of the most widely used data + analysis techniques. This package provides a series of vignettes explaining PCA + starting from basic concepts. The primary purpose is to serve as a self-study + resource for anyone wishing to understand PCA better. A few convenience functions + are provided as well. + date_publication: '2024-04-26' + bug_reports: https://github.com/bryanhanson/LearnPCA/issues + url: https://bryanhanson.github.io/LearnPCA/ + url_cran: https://CRAN.R-project.org/package=LearnPCA + url_git: '' +learnPopGen: + version: 1.0.4 + title: Population Genetic Simulations & Numerical Analysis + maintainer: Liam J. Revell + description: Conducts various numerical analyses and simulations in population genetics + and evolutionary theory, primarily for the purpose of teaching (and learning about) + key concepts in population & quantitative genetics, and evolutionary theory. + date_publication: '2019-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=learnPopGen + url_git: http://github.com/liamrevell/learnPopGen +learnr: + version: 0.11.5 + title: Interactive Tutorials for R + maintainer: Garrick Aden-Buie + description: |- + Create interactive tutorials using R Markdown. Use a + combination of narrative, figures, videos, exercises, and quizzes to + create self-paced tutorials for learning about R and R packages. + date_publication: '2023-09-28' + bug_reports: https://github.com/rstudio/learnr/issues + url: https://rstudio.github.io/learnr/ + url_cran: https://CRAN.R-project.org/package=learnr + url_git: https://github.com/rstudio/learnr +learnrbook: + version: 2.0.1 + title: Datasets and Code Examples from P. J. Aphalo's "Learn R" Book + maintainer: Pedro J. Aphalo + description: |- + Data, scripts and code from chunks used as examples in the book + "Learn R: As a Language" 1ed and 2ed by Pedro J. Aphalo. + ISBN 9780367182533 (pbk 1ed); ISBN 9780367182557 (hbk 1ed); ISBN 9780429060342 (ebk 1ed). + date_publication: '2024-04-28' + bug_reports: https://github.com/aphalo/learnrbook-pkg/issues + url: https://docs.r4photobiology.info/learnrbook/ + url_cran: https://CRAN.R-project.org/package=learnrbook + url_git: https://github.com/aphalo/learnrbook-pkg/ +LearnSL: + version: 1.0.0 + title: |- + Learn Supervised Classification Methods Through Examples and + Code + maintainer: Víctor Amador Padilla + description: |- + Supervised classification methods, which (if asked) can provide + step-by-step explanations of the algorithms used, as described in + PK Josephine et. al., (2021) ; and datasets to + test them on, which highlight the strengths and weaknesses of each technique. + date_publication: '2023-09-19' + bug_reports: https://github.com/ComiSeng/LearnSL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LearnSL + url_git: https://github.com/ComiSeng/LearnSL +LearnVizLMM: + version: 1.0.0 + title: Learning and Communicating Linear Mixed Models Without Data + maintainer: Katherine Zavez + description: |- + Summarizes characteristics of linear mixed effects models without + data or a fitted model by converting code for fitting lmer() from 'lme4' + and lme() from 'nlme' into tables, equations, and visuals. Outputs can be + used to learn how to fit linear mixed effects models in 'R' and to + communicate about these models in presentations, manuscripts, and analysis + plans. + date_publication: '2024-09-25' + bug_reports: https://github.com/kzavez/LearnVizLMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LearnVizLMM + url_git: https://github.com/kzavez/LearnVizLMM +leastcostpath: + version: 2.0.12 + title: Modelling Pathways and Movement Potential Within a Landscape + maintainer: Joseph Lewis + description: Calculates cost surfaces based on slope to be used when modelling pathways + and movement potential within a landscape (Lewis, 2021) . + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leastcostpath + url_git: '' +ledger: + version: 2.0.11 + title: Utilities for Importing Data from Plain Text Accounting Files + maintainer: Trevor L. Davis + description: Utilities for querying plain text accounting files from 'Ledger', 'HLedger', + and 'Beancount'. + date_publication: '2024-05-20' + bug_reports: https://github.com/trevorld/r-ledger/issues + url: https://trevorldavis.com/R/ledger/ + url_cran: https://CRAN.R-project.org/package=ledger + url_git: https://github.com/trevorld/r-ledger +leem: + version: 0.1.0 + title: Laboratory of Teaching to Statistics and Mathematics + maintainer: Ben Deivide + description: |- + Educational tool for teaching of statistics + and mathematics in primary and higher education. The objective is + to assist in teaching/learning for both student study planning + and teacher teaching strategies. The 'leem' package will try to bring, + in a simple and at the same time in-depth, + knowledge of statistics and mathematics to everyone + who wants to study these areas of knowledge. The main function of the + package is 'leem()' function. + date_publication: '2022-03-02' + bug_reports: https://github.com/bendeivide/leem/issues + url: https://bendeivide.github.io/project/leem/ + url_cran: https://CRAN.R-project.org/package=leem + url_git: https://github.com/bendeivide/leem +lefko3: + version: 6.3.2 + title: Historical and Ahistorical Population Projection Matrix Analysis + maintainer: Richard P. Shefferson + description: |- + Complete analytical environment for the construction and analysis + of matrix population models and integral projection models. + Includes the ability to construct historical matrices, which are + 2d matrices comprising 3 consecutive times of demographic + information. Estimates both raw and function-based forms of + historical and standard ahistorical matrices. It also estimates + function-based age-by-stage matrices and raw and function-based + Leslie matrices. + date_publication: '2025-01-07' + bug_reports: '' + url: http://www.sheffersonlab.com/projects.html + url_cran: https://CRAN.R-project.org/package=lefko3 + url_git: '' +legendry: + version: 0.2.0 + title: Extended Legends and Axes for 'ggplot2' + maintainer: Teun van den Brand + description: |- + A 'ggplot2' extension that focusses on expanding the + plotter's arsenal of guides. Guides in 'ggplot2' include axes and + legends. 'legendry' offers new axes and annotation options, as well as + new legends and colour displays. + date_publication: '2024-12-14' + bug_reports: https://github.com/teunbrand/legendry/issues + url: https://teunbrand.github.io/legendry/ + url_cran: https://CRAN.R-project.org/package=legendry + url_git: https://github.com/teunbrand/legendry +legion: + version: 0.2.1 + title: Forecasting Using Multivariate Models + maintainer: Ivan Svetunkov + description: |- + Functions implementing multivariate state space models for purposes of time series analysis and forecasting. + The focus of the package is on multivariate models, such as Vector Exponential Smoothing, + Vector ETS (Error-Trend-Seasonal model) etc. It currently includes Vector Exponential + Smoothing (VES, de Silva et al., 2010, ), Vector ETS (Svetunkov et al., 2023, + ) and simulation function for VES. + date_publication: '2025-02-03' + bug_reports: https://github.com/config-i1/legion/issues + url: '' + url_cran: https://CRAN.R-project.org/package=legion + url_git: https://github.com/config-i1/legion +legislatoR: + version: 1.1.0 + title: Interface to the Comparative Legislators Database + maintainer: Sascha Goebel + description: Facilitates access to the Comparative Legislators Database (CLD). The + CLD includes political, sociodemographic, career, online presence, public attention, + and visual information for over 67,000 contemporary and historical politicians + from 16 countries. + date_publication: '2023-03-31' + bug_reports: https://github.com/saschagobel/legislatoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=legislatoR + url_git: https://github.com/saschagobel/legislatoR +LEGIT: + version: 1.4.1 + title: Latent Environmental & Genetic InTeraction (LEGIT) Model + maintainer: Alexia Jolicoeur-Martineau + description: |- + Constructs genotype x environment interaction (GxE) models where + G is a weighted sum of genetic variants (genetic score) and E is a weighted + sum of environments (environmental score) using the alternating optimization algorithm + by Jolicoeur-Martineau et al. (2017) . This approach has greatly + enhanced predictive power over traditional GxE models which include only a single + genetic variant and a single environmental exposure. Although this approach was + originally made for GxE modelling, it is flexible and does not require the use of + genetic and environmental variables. It can also handle more than 2 latent variables + (rather than just G and E) and 3-way interactions or more. The LEGIT model produces + highly interpretable results and is very parameter-efficient thus it can even be + used with small sample sizes (n < 250). Tools to determine the type of interaction + (vantage sensitivity, diathesis-stress or differential susceptibility), with any + number of genetic variants or environments, are available . The + software can now produce mixed-effects LEGIT models through the lme4 package. + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LEGIT + url_git: '' +legocolors: + version: 0.4.0 + title: Official Lego Color Palettes + maintainer: Matthew Leonawicz + description: |- + Provides a dataset containing several color naming conventions established by multiple sources, along with associated color metadata. + The package also provides related helper functions for mapping among the different Lego color naming conventions and between Lego colors, hex colors, and 'R' color names, + making it easy to convert any color palette to one based on existing Lego colors while keeping as close to the original color palette as possible. + The functions use nearest color matching based on Euclidean distance in RGB space. + Naming conventions for color mapping include those from 'BrickLink' (), 'The Lego Group' (), 'LDraw' (), and 'Peeron' (). + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/legocolors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=legocolors + url_git: https://github.com/leonawicz/legocolors +lehdr: + version: 1.1.4 + title: Grab Longitudinal Employer-Household Dynamics (LEHD) Flat Files + maintainer: Jamaal Green + description: |- + Designed to query Longitudinal Employer-Household Dynamics (LEHD) + workplace/residential association and origin-destination flat files and + optionally aggregate Census block-level data to block group, tract, county, + or state. Data comes from the LODES FTP server . + date_publication: '2024-11-21' + bug_reports: https://github.com/jamgreen/lehdr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=lehdr + url_git: https://github.com/jamgreen/lehdr/ +lehuynh: + version: 0.1.1 + title: Le-Huynh Truc-Ly's R Code and Templates + maintainer: Truc-Ly Le-Huynh + description: |- + Miscellaneous R functions (for graphics, data import, + data transformation, and general utilities) and templates (for exploratory + analysis, Bayesian modeling, and crafting scientific manuscripts). + date_publication: '2024-06-05' + bug_reports: https://github.com/le-huynh/lehuynh/issues + url: https://le-huynh.github.io/lehuynh/ + url_cran: https://CRAN.R-project.org/package=lehuynh + url_git: https://github.com/le-huynh/lehuynh +leiden: + version: 0.4.3.1 + title: R Implementation of Leiden Clustering Algorithm + maintainer: S. Thomas Kelly + description: |- + Implements the 'Python leidenalg' module to be called in R. + Enables clustering using the leiden algorithm for partition a graph into communities. + See the 'Python' repository for more details: + Traag et al (2018) From Louvain to Leiden: guaranteeing well-connected communities. . + date_publication: '2023-11-17' + bug_reports: https://github.com/TomKellyGenetics/leiden/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leiden + url_git: https://github.com/TomKellyGenetics/leiden +leidenAlg: + version: 1.1.4 + title: Implements the Leiden Algorithm via an R Interface + maintainer: Evan Biederstedt + description: 'An R interface to the Leiden algorithm, an iterative community detection + algorithm on networks. The algorithm is designed to converge to a partition in + which all subsets of all communities are locally optimally assigned, yielding + communities guaranteed to be connected. The implementation proves to be fast, + scales well, and can be run on graphs of millions of nodes (as long as they can + fit in memory). The original implementation was constructed as a python interface + "leidenalg" found here: . The algorithm was + originally described in Traag, V.A., Waltman, L. & van Eck, N.J. "From Louvain + to Leiden: guaranteeing well-connected communities". Sci Rep 9, 5233 (2019) .' + date_publication: '2024-10-17' + bug_reports: https://github.com/kharchenkolab/leidenAlg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leidenAlg + url_git: https://github.com/kharchenkolab/leidenAlg +leidenbase: + version: 0.1.32 + title: R and C/C++ Wrappers to Run the Leiden find_partition() Function + maintainer: Brent Ewing + description: |- + An R to C/C++ interface that runs the Leiden community + detection algorithm to find a basic partition (). It runs the + equivalent of the 'leidenalg' find_partition() function, which is + given in the 'leidenalg' distribution file + 'leiden/src/functions.py'. This package includes the + required source code files from the official 'leidenalg' + distribution and functions from the R 'igraph' + package. The 'leidenalg' distribution is available from + + and the R 'igraph' package is available from + . + The Leiden algorithm is described in the article by + Traag et al. (2019) . + Leidenbase includes code from the packages: + igraph version 0.9.8 with license GPL (>= 2), + leidenalg version 0.8.10 with license GPL 3. + date_publication: '2025-02-06' + bug_reports: https://github.com/cole-trapnell-lab/leidenbase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leidenbase + url_git: https://github.com/cole-trapnell-lab/leidenbase +leiv: + version: 2.0-7 + title: Bivariate Linear Errors-In-Variables Estimation + maintainer: David Leonard + description: |- + Estimate the slope and intercept of a bivariate + linear relationship by calculating a posterior density + that is invariant to interchange and scaling of the + coordinates. + date_publication: '2015-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leiv + url_git: '' +LeMaRns: + version: 0.1.2 + title: Length-Based Multispecies Analysis by Numerical Simulation + maintainer: Michael A. Spence + description: Set up, run and explore the outputs of the Length-based Multi-species + model (LeMans; Hall et al. 2006 ), focused on the marine + environment. + date_publication: '2019-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LeMaRns + url_git: '' +lemna: + version: 1.0.1 + title: Lemna Ecotox Effect Model + maintainer: Nils Kehrein + description: |- + The reference implementation of model equations and default + parameters for the toxicokinetic-toxicodynamic (TKTD) model of the Lemna + (duckweed) aquatic plant. Lemna is a standard test macrophyte used in ecotox + effect studies. The model was described and published by the SETAC Europe + Interest Group Effect Modeling. It is a refined description of the Lemna + TKTD model published by Schmitt et al. (2013) + . + date_publication: '2023-04-22' + bug_reports: https://github.com/nkehrein/lemna/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lemna + url_git: https://github.com/nkehrein/lemna +lemon: + version: 0.5.0 + title: Freshing Up your 'ggplot2' Plots + maintainer: Stefan McKinnon Edwards + description: |- + Functions for working with legends and axis lines of 'ggplot2', + facets that repeat axis lines on all panels, and some 'knitr' extensions. + date_publication: '2024-11-10' + bug_reports: https://github.com/stefanedwards/lemon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lemon + url_git: https://github.com/stefanedwards/lemon +lenght: + version: 0.1.0 + title: Allow Misspellings of Length Function + maintainer: Jacob Bradley + description: Convenient aliases for common ways of misspelling the base R function + length(). These include every permutation of the final three letters. + date_publication: '2023-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lenght + url_git: '' +lenses: + version: 0.0.3 + title: Elegant Data Manipulation with Lenses + maintainer: Chris Hammill + description: Provides tools for creating and using lenses to simplify data manipulation. + Lenses are composable getter/setter pairs for working with data in a purely functional + way. Inspired by the 'Haskell' library 'lens' (Kmett, 2012) . + For a fairly comprehensive (and highly technical) history of lenses please see + the 'lens' wiki . + date_publication: '2019-03-06' + bug_reports: https://github.com/cfhammill/lenses/issues + url: http://cfhammill.github.io/lenses + url_cran: https://CRAN.R-project.org/package=lenses + url_git: https://github.com/cfhammill/lenses +leontief: + version: '0.3' + title: Input-Output Analysis + maintainer: Mauricio Vargas Sepulveda + description: |- + An implementation of the Input-Output model developed by + Wassily Leontief that represents the interdependencies between different + sectors of a national economy or different regional economies. + date_publication: '2024-06-11' + bug_reports: https://github.com/pachadotdev/leontief/issues + url: '' + url_cran: https://CRAN.R-project.org/package=leontief + url_git: https://github.com/pachadotdev/leontief +leprechaun: + version: 1.0.0 + title: Create Simple 'Shiny' Applications as Packages + maintainer: John Coene + description: |- + Code generator for robust dependency-free 'Shiny' + applications in the form of packages. It includes numerous + convenience functions to create modules, include utility + functions to create common 'Bootstrap' elements, setup a + project from the ground-up, and much more. + date_publication: '2022-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leprechaun + url_git: '' +leptokurticMixture: + version: '1.1' + title: |- + Implements Parsimonious Finite Mixtures of Multivariate + Elliptical Leptokurtic-Normals + maintainer: Ryan Browne + description: A way to fit Parsimonious Finite Mixtures of Multivariate Elliptical + Leptokurtic-Normals. Two methods of estimation are implemented. + date_publication: '2023-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=leptokurticMixture + url_git: '' +lero.lero: + version: '0.2' + title: Generate 'Lero Lero' Quotes + maintainer: Lucas Processi + description: Generates quotes from 'Lero Lero', a database for meaningless sentences + filled with corporate buzzwords, intended to be used as corporate lorem ipsum + (see for more information). Unfortunately, quotes are + currently portuguese-only. + date_publication: '2018-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lero.lero + url_git: '' +less: + version: 0.1.0 + title: Learning with Subset Stacking + maintainer: Burhan Ozer Cavdar + description: '"Learning with Subset Stacking" is a supervised learning algorithm + that is based on training many local estimators on subsets of a given dataset, + and then passing their predictions to a global estimator. You can find the details + about LESS in our manuscript at .' + date_publication: '2022-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=less + url_git: '' +lessR: + version: 4.4.1 + title: Less Code, More Results + maintainer: David W. Gerbing + description: Each function replaces multiple standard R functions. For example, + two function calls, Read() and CountAll(), generate summary statistics for all + variables in the data frame, plus histograms and bar charts as appropriate. Other + functions provide for summary statistics via pivot tables, a comprehensive regression + analysis, ANOVA and t-test, visualizations including the Violin/Box/Scatter plot + for a numerical variable, bar chart, histogram, box plot, density curves, calibrated + power curve, reading multiple data formats with the same function call, variable + labels, time series with aggregation and forecasting, color themes, and Trellis + (facet) graphics. Also includes a confirmatory factor analysis of multiple indicator + measurement models, pedagogical routines for data simulation such as for the Central + Limit Theorem, generation and rendering of regression instructions for interpretative + output, and interactive visualizations. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lessR + url_git: '' +lessSEM: + version: 1.5.5 + title: Non-Smooth Regularization for Structural Equation Models + maintainer: Jannik H. Orzek + description: |- + Provides regularized structural equation modeling + (regularized SEM) with non-smooth penalty functions (e.g., lasso) building + on 'lavaan'. The package is heavily inspired by the + ['regsem']() and + ['lslx']() packages. + date_publication: '2024-01-22' + bug_reports: https://github.com/jhorzek/lessSEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lessSEM + url_git: https://github.com/jhorzek/lessSEM +lest: + version: 1.1.0 + title: |- + Vectorised Nested if-else Statements Similar to CASE WHEN in + 'SQL' + maintainer: Stefan Fleck + description: |- + Functions for vectorised conditional recoding of + variables. case_when() enables you to vectorise multiple if and else + statements (like 'CASE WHEN' in 'SQL'). if_else() is a stricter and + more predictable version of ifelse() in 'base' that preserves + attributes. These functions are forked from 'dplyr' with all package + dependencies removed and behave identically to the originals. + date_publication: '2019-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lest + url_git: '' +lestat: + version: '1.9' + title: A Package for Learning Statistics + maintainer: Petter Mostad + description: |- + Some simple objects and functions to do + statistics using linear models and a Bayesian framework. + date_publication: '2018-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lestat + url_git: '' +letsR: + version: '5.0' + title: Data Handling and Analysis in Macroecology + maintainer: Bruno Vilela + description: |- + Handling, processing, and analyzing geographic + data on species' distributions and environmental variables. + Read Vilela & Villalobos (2015) for details. + date_publication: '2023-11-23' + bug_reports: https://github.com/macroecology/letsR/issues + url: https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12401 + url_cran: https://CRAN.R-project.org/package=letsR + url_git: https://github.com/macroecology/letsR +lettervalue: + version: 0.2.1 + title: Computing Letter Values + maintainer: Gilberto Sassi + description: 'Letter Values for the course Exploratory Data Analysis at Federal + University of Bahia (Brazil). The approach implemented in the package is presented + in the textbook of Tukey (1977) .' + date_publication: '2023-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lettervalue + url_git: '' +levitate: + version: 0.2.0 + title: Fuzzy String Comparison + maintainer: Lewin Appleton-Fox + description: |- + Provides string similarity calculations inspired by the + Python 'thefuzz' package. Compare strings by edit distance, similarity + ratio, best matching substring, ordered token matching and set-based + token matching. A range of edit distance measures are available thanks + to the 'stringdist' package. + date_publication: '2023-10-01' + bug_reports: https://github.com/lewinfox/levitate/issues + url: https://www.lewinfox.com/levitate/ + url_cran: https://CRAN.R-project.org/package=levitate + url_git: https://github.com/lewinfox/levitate/ +LexFindR: + version: 1.1.0 + title: Find Related Items and Lexical Dimensions in a Lexicon + maintainer: ZhaoBin Li + description: |- + Implements code to identify lexical competitors in a given list + of words. We include many of the standard competitor types used in spoken word + recognition research, such as functions to find cohorts, neighbors, and + rhymes, amongst many others. The package includes documentation for using a + variety of lexicon files, including those with form codes made up of multiple + letters (i.e., phoneme codes) and also basic orthographies. Importantly, the + code makes use of multiple CPU cores and vectorization when possible, making + it extremely fast and able to handle large lexicons. Additionally, the package + contains documentation for users to easily write new functions, allowing + researchers to examine other relationships within a lexicon. + Preprint: . Open access: . + Citation: Li, Z., Crinnion, A.M. & Magnuson, J.S. (2021). + . + date_publication: '2024-06-16' + bug_reports: https://github.com/maglab-uconn/LexFindR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LexFindR + url_git: https://github.com/maglab-uconn/LexFindR +lexicon: + version: 1.2.1 + title: Lexicons for Text Analysis + maintainer: Tyler Rinker + description: A collection of lexical hash tables, dictionaries, and word lists. + date_publication: '2019-03-21' + bug_reports: https://github.com/trinker/lexicon/issues?state=open + url: '' + url_cran: https://CRAN.R-project.org/package=lexicon + url_git: https://github.com/trinker/lexicon +lexiconPT: + version: 0.1.0 + title: Lexicons for Portuguese Text Analysis + maintainer: Sillas Gonzaga + description: |- + Provides easy access for sentiment lexicons for those who want to do text analysis in Portuguese texts. + As of now, two Portuguese lexicons are available: 'SentiLex-PT02' and 'OpLexicon' (v2.1 and v3.0). + date_publication: '2017-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lexiconPT + url_git: '' +LexisNexisTools: + version: 1.0.0 + title: Working with Files from 'LexisNexis' + maintainer: Johannes B. Gruber + description: |- + My PhD supervisor once told me that everyone doing newspaper + analysis starts by writing code to read in files from the 'LexisNexis' newspaper + archive (retrieved e.g., from or any of the partner + sites). However, while this is a nice exercise I do recommend, not everyone has + the time. This package takes files downloaded from the newspaper archive of + 'LexisNexis', reads them into R and offers functions for further processing. + date_publication: '2024-04-18' + bug_reports: https://github.com/JBGruber/LexisNexisTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LexisNexisTools + url_git: https://github.com/JBGruber/LexisNexisTools +LexisPlotR: + version: 0.4.0 + title: Plot Lexis Diagrams for Demographic Purposes + maintainer: Philipp Ottolinger + description: Plots empty Lexis grids, adds lifelines and highlights certain areas + of the grid, like cohorts and age groups. + date_publication: '2020-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LexisPlotR + url_git: https://github.com/ottlngr/LexisPlotR +lexRankr: + version: 0.5.2 + title: Extractive Summarization of Text with the LexRank Algorithm + maintainer: Adam Spannbauer + description: An R implementation of the LexRank algorithm described by G. Erkan + and D. R. Radev (2004) . + date_publication: '2019-03-17' + bug_reports: https://github.com/AdamSpannbauer/lexRankr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=lexRankr + url_git: https://github.com/AdamSpannbauer/lexRankr/ +lfactors: + version: 1.0.4 + title: Factors with Levels + maintainer: Paul Bailey + description: |- + Provides an extension to factors called 'lfactor' that are similar + to factors but allows users to refer to 'lfactor' levels by either the level or + the label. + date_publication: '2018-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lfactors + url_git: '' +LFApp: + version: 1.4.1 + title: Shiny Apps for Lateral Flow Assays + maintainer: Filip Paskali + description: Shiny apps for the quantitative analysis of images from lateral flow + assays (LFAs). The images are segmented and background corrected and color intensities + are extracted. The apps can be used to import and export intensity data and to + calibrate LFAs by means of linear, loess, or gam models. The calibration models + can further be saved and applied to intensity data from new images for determining + concentrations. + date_publication: '2024-05-27' + bug_reports: https://github.com/fpaskali/LFApp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LFApp + url_git: https://github.com/fpaskali/LFApp +lfc: + version: 0.2.3 + title: |- + Log Fold Change Distribution Tools for Working with Ratios of + Counts + maintainer: Florian Erhard + description: |- + Ratios of count data such as obtained from RNA-seq are modelled + using Bayesian statistics to derive posteriors for effects sizes. This + approach is described in Erhard & Zimmer (2015) + and Erhard (2018) . + date_publication: '2023-04-19' + bug_reports: https://github.com/erhard-lab/lfc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lfc + url_git: https://github.com/erhard-lab/lfc +lfda: + version: 1.1.3 + title: Local Fisher Discriminant Analysis + maintainer: Yuan Tang + description: |- + Functions for performing and visualizing Local Fisher Discriminant + Analysis(LFDA), Kernel Fisher Discriminant Analysis(KLFDA), and Semi-supervised + Local Fisher Discriminant Analysis(SELF). + date_publication: '2019-07-31' + bug_reports: https://github.com/terrytangyuan/lfda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lfda + url_git: https://github.com/terrytangyuan/lfda +LFDR.MLE: + version: 1.0.1 + title: |- + Estimation of the Local False Discovery Rates by Type II Maximum + Likelihood Estimation + maintainer: M. Padilla + description: Suite of R functions for the estimation of the local false discovery + rate (LFDR) using Type II maximum likelihood estimation (MLE). + date_publication: '2019-10-02' + bug_reports: '' + url: http://www.statomics.com + url_cran: https://CRAN.R-project.org/package=LFDR.MLE + url_git: '' +LFDR.MME: + version: '1.0' + title: |- + Estimating Local False Discovery Rates Using the Method of + Moments + maintainer: Ali Karimnezhad + description: Estimation of the local false discovery rate using the method of moments. + date_publication: '2020-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LFDR.MME + url_git: '' +LFDREmpiricalBayes: + version: '1.0' + title: |- + Estimating Local False Discovery Rates Using Empirical Bayes + Methods + maintainer: Ali Karimnezhad + description: New empirical Bayes methods aiming at analyzing the association of + single nucleotide polymorphisms (SNPs) to some particular disease are implemented + in this package. The package uses local false discovery rate (LFDR) estimates + of SNPs within a sample population defined as a "reference class" and discovers + if SNPs are associated with the corresponding disease. Although SNPs are used + throughout this document, other biological data such as protein data and other + gene data can be used. Karimnezhad, Ali and Bickel, D. R. (2016) . + date_publication: '2017-09-27' + bug_reports: '' + url: https://davidbickel.com + url_cran: https://CRAN.R-project.org/package=LFDREmpiricalBayes + url_git: '' +lfe: + version: 3.1.1 + title: Linear Group Fixed Effects + maintainer: Mauricio Vargas Sepulveda + description: |- + Transforms away factors with many levels prior to doing an OLS. + Useful for estimating linear models with multiple group fixed effects, and for + estimating linear models which uses factors with many levels as pure control variables. See Gaure (2013) + Includes support for instrumental variables, conditional F statistics for weak instruments, + robust and multi-way clustered standard errors, as well as limited mobility bias correction (Gaure 2014 ). + Since version 3.0, it provides dedicated functions to estimate Poisson models. + date_publication: '2025-02-11' + bug_reports: https://github.com/r-econometrics/lfe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lfe + url_git: https://github.com/r-econometrics/lfe +lfl: + version: 2.2.1 + title: Linguistic Fuzzy Logic + maintainer: Michal Burda + description: |- + Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association + rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), + and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic + fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar, + Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lfl + url_git: '' +LFM: + version: 0.2.0 + title: Laplace Factor Model Analysis and Evaluation + maintainer: Guangbao Guo + description: Enables the generation of Laplace factor models across diverse Laplace + distributions and facilitates the application of Sparse Online Principal Component + (SOPC), Incremental Principal Component (IPC), Projected Principal Component (PPC), + Perturbation Principal Component (PPC), Stochastic Approximation Principal Component + (SAPC), Sparse Principal Component (SPC) and other PC methods and Farm Test methods + to these models. Evaluates the efficacy of these methods within the context of + Laplace factor models by scrutinizing parameter estimation accuracy, mean square + error, and the degree of sparsity. + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LFM + url_git: '' +lfmm: + version: '1.1' + title: Latent Factor Mixed Models + maintainer: Basile Jumentier + description: |- + Fast and accurate inference of + gene-environment associations (GEA) in genome-wide studies + (Caye et al., 2019, ). + We developed a least-squares estimation approach for confounder and effect sizes + estimation that provides a unique framework for several categories of genomic data, + not restricted to genotypes. + The speed of the new algorithm is several times faster than the existing GEA approaches, + then our previous version of the 'LFMM' program present in the 'LEA' package + (Frichot and Francois, 2015, ). + date_publication: '2021-06-30' + bug_reports: https://github.com/bcm-uga/lfmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lfmm + url_git: '' +lfproQC: + version: 1.4.0 + title: Quality Control for Label-Free Proteomics Expression Data + maintainer: Kabilan S + description: "Label-free bottom-up proteomics expression data is often affected + by data heterogeneity and missing values. Normalization and missing value imputation + are commonly used techniques to address these issues and make the dataset suitable + for further downstream analysis. This package provides an optimal combination + of normalization and imputation methods for the dataset. The package utilizes + three normalization methods and three imputation methods.The statistical evaluation + measures named pooled co-efficient of variance, pooled estimate of variance and + pooled median absolute deviation are used for selecting the best combination of + normalization and imputation method for the given dataset. The user can also visualize + the results by using various plots available in this package. The user can also + perform the differential expression analysis between two sample groups with the + function included in this package. The chosen three normalization methods, three + imputation methods and three evaluation measures were chosen for this study based + on the research papers published by\tVälikangas et al. (2016) , + Jin et al. (2021) and Srivastava et al. (2023) + ." + date_publication: '2024-10-10' + bug_reports: https://github.com/kabilansbio/lfproQC/issues + url: https://dabiniasri.shinyapps.io/lfproQC + url_cran: https://CRAN.R-project.org/package=lfproQC + url_git: https://github.com/kabilansbio/lfproQC +lfstat: + version: 0.9.12 + title: Calculation of Low Flow Statistics for Daily Stream Flow Data + maintainer: Tobias Gauster + description: The "Manual on Low-flow Estimation and Prediction" (Gustard & Demuth + (2009, ISBN:978-92-63-11029-9)), published by the World Meteorological Organisation, + gives a comprehensive summary on how to analyse stream flow data focusing on low-flows. + This packages provides functions to compute the described statistics and produces + plots similar to the ones in the manual. + date_publication: '2022-11-08' + bug_reports: https://github.com/mundl/lfstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lfstat + url_git: '' +lg: + version: 0.4.1 + title: 'Locally Gaussian Distributions: Estimation and Methods' + maintainer: Håkon Otneim + description: |- + An implementation of locally Gaussian distributions. It provides methods for + implementing locally Gaussian multivariate density estimation, conditional density + estimation, various independence tests for iid and time series data, a test for conditional + independence and a test for financial contagion. + date_publication: '2019-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lg + url_git: '' +lgarch: + version: 0.6-2 + title: Simulation and Estimation of Log-GARCH Models + maintainer: Genaro Sucarrat + description: 'Simulation and estimation of univariate and multivariate log-GARCH + models. The main functions of the package are: lgarchSim(), mlgarchSim(), lgarch() + and mlgarch(). The first two functions simulate from a univariate and a multivariate + log-GARCH model, respectively, whereas the latter two estimate a univariate and + multivariate log-GARCH model, respectively.' + date_publication: '2015-09-15' + bug_reports: '' + url: http://www.sucarrat.net/ + url_cran: https://CRAN.R-project.org/package=lgarch + url_git: '' +lgcp: + version: '2.0' + title: Log-Gaussian Cox Process + maintainer: Benjamin M. Taylor + description: |- + Spatial and spatio-temporal modelling of point patterns using the + log-Gaussian Cox process. Bayesian inference for spatial, spatiotemporal, + multivariate and aggregated point processes using Markov chain Monte Carlo. See Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J. Diggle (2015) . + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lgcp + url_git: '' +LGDtoolkit: + version: 0.2.0 + title: Collection of Tools for LGD Rating Model Development + maintainer: Andrija Djurovic + description: |- + The goal of this package is to cover the most common steps in Loss Given Default (LGD) rating model development. + The main procedures available are those that refer to bivariate and multivariate analysis. In particular two statistical methods for + multivariate analysis are currently implemented – OLS regression and fractional logistic regression. + Both methods are also available within different blockwise model designs and both have customized stepwise algorithms. + Descriptions of these customized designs are available in Siddiqi (2016) and + Anderson, R.A. (2021) . + Although they are explained for PD model, the same designs are applicable for LGD model with different underlying regression methods + (OLS and fractional logistic regression). To cover other important steps for LGD model development, it is recommended to use + 'LGDtoolkit' package along with 'PDtoolkit', and 'monobin' (or 'monobinShiny') packages. + Additionally, 'LGDtoolkit' provides set of procedures handy for initial and periodical model validation. + date_publication: '2023-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LGDtoolkit + url_git: https://github.com/andrija-djurovic/LGDtoolkit +LGEWIS: + version: '1.1' + title: |- + Tests for Genetic Association/Gene-Environment Interaction in + Longitudinal Studies + maintainer: Zihuai He + description: Functions for genome-wide association studies (GWAS)/gene-environment-wide + interaction studies (GEWIS) with longitudinal outcomes and exposures. He et al. + (2017) "Set-Based Tests for Gene-Environment Interaction in Longitudinal Studies" + and He et al. (2017) "Rare-variant association tests in longitudinal studies, + with an application to the Multi-Ethnic Study of Atherosclerosis (MESA)". + date_publication: '2017-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LGEWIS + url_git: '' +lglasso: + version: 0.1.0 + title: Longitudinal Graphical Lasso + maintainer: Jie Zhou + description: |- + For high-dimensional correlated observations, this package carries out the L_1 penalized maximum likelihood + estimation of the precision matrix (network) and the correlation parameters. The correlated data can be + longitudinal data (may be irregularly spaced) with dampening correlation or clustered data with uniform correlation. + For the details of the algorithms, please see the paper Jie Zhou et al. Identifying Microbial Interaction Networks Based on Irregularly Spaced + Longitudinal 16S rRNA sequence data . + date_publication: '2022-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lglasso + url_git: https://github.com/jiezhou-2/lglasso +lgpr: + version: 1.2.4 + title: Longitudinal Gaussian Process Regression + maintainer: Juho Timonen + description: |- + Interpretable nonparametric modeling of longitudinal data + using additive Gaussian process regression. Contains functionality + for inferring covariate effects and assessing covariate relevances. + Models are specified using a convenient formula syntax, and can include + shared, group-specific, non-stationary, heterogeneous and temporally + uncertain effects. Bayesian inference for model parameters is performed + using 'Stan'. The modeling approach and methods are described in detail in + Timonen et al. (2021) . + date_publication: '2023-09-24' + bug_reports: https://github.com/jtimonen/lgpr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lgpr + url_git: https://github.com/jtimonen/lgpr +lgr: + version: 0.4.4 + title: A Fully Featured Logging Framework + maintainer: Stefan Fleck + description: |- + A flexible, feature-rich yet light-weight logging + framework based on 'R6' classes. It supports hierarchical loggers, + custom log levels, arbitrary data fields in log events, logging to + plaintext, 'JSON', (rotating) files, memory buffers. For extra + appenders that support logging to databases, email and push + notifications see the the package lgr.app. + date_publication: '2022-09-05' + bug_reports: https://github.com/s-fleck/lgr/issues/ + url: https://s-fleck.github.io/lgr/ + url_cran: https://CRAN.R-project.org/package=lgr + url_git: '' +lgrdata: + version: 0.1.1 + title: Example Datasets for a Learning Guide to R + maintainer: Remko Duursma + description: |- + A largish collection of example datasets, including several classics. Many of + these datasets are well suited for regression, classification, and visualization. + date_publication: '2019-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lgrdata + url_git: '' +lgrExtra: + version: 0.0.9 + title: Extra Appenders for 'lgr' + maintainer: Stefan Fleck + description: |- + Additional appenders for the logging package 'lgr' that + support logging to databases, email and push notifications. + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lgrExtra + url_git: '' +LGRF: + version: '1.0' + title: Set-Based Tests for Genetic Association in Longitudinal Studies + maintainer: Zihuai He + description: Functions for the longitudinal genetic random field method (He et al., + 2015, ) to test the association between a longitudinally + measured quantitative outcome and a set of genetic variants in a gene/region. + date_publication: '2015-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LGRF + url_git: '' +lgtdl: + version: 1.1.5 + title: A Set of Methods for Longitudinal Data Objects + maintainer: Arthur Allignol + description: |- + A very simple implementation of a class for + longitudinal data. + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lgtdl + url_git: '' +LHD: + version: 1.4.1 + title: Latin Hypercube Designs (LHDs) + maintainer: Hongzhi Wang + description: Contains different algorithms and construction methods for optimal + Latin hypercube designs (LHDs) with flexible sizes. Our package is comprehensive + since it is capable of generating maximin distance LHDs, maximum projection LHDs, + and orthogonal and nearly orthogonal LHDs. Detailed comparisons and summary of + all the algorithms and construction methods in this package can be found at Hongzhi + Wang, Qian Xiao and Abhyuday Mandal (2021) . This + package is particularly useful in the area of Design and Analysis of Experiments + (DAE). More specifically, design of computer experiments. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LHD + url_git: '' +lhmixr: + version: 0.1.0 + title: |- + Fit Sex-Specific Life History Models with Missing + Classifications + maintainer: Coilin Minto + description: Fits sex-specific life-history models for fish and other taxa where + some of the individuals have unknown sex. + date_publication: '2017-05-11' + bug_reports: https://github.com/mintoc/lhmixr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lhmixr + url_git: https://github.com/mintoc/lhmixr +lhs: + version: 1.2.0 + title: Latin Hypercube Samples + maintainer: Rob Carnell + description: Provides a number of methods for creating and augmenting Latin Hypercube + Samples and Orthogonal Array Latin Hypercube Samples. + date_publication: '2024-06-30' + bug_reports: https://github.com/bertcarnell/lhs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lhs + url_git: https://github.com/bertcarnell/lhs +libbib: + version: 1.6.4 + title: Various Utilities for Library Science/Assessment and Cataloging + maintainer: Tony Fischetti + description: |- + Provides functions for validating and normalizing bibliographic + codes such as ISBN, ISSN, and LCCN. Also includes functions to communicate + with the WorldCat API, translate Call numbers (Library of Congress and + Dewey Decimal) to their subject classifications or subclassifications, + and provides various loadable data files such call number / subject + crosswalks and code tables. + date_publication: '2022-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=libbib + url_git: '' +libcoin: + version: 1.0-10 + title: Linear Test Statistics for Permutation Inference + maintainer: Torsten Hothorn + description: |- + Basic infrastructure for linear test statistics and permutation + inference in the framework of Strasser and Weber (1999) . + This package must not be used by end-users. CRAN package 'coin' implements all + user interfaces and is ready to be used by anyone. + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=libcoin + url_git: '' +libgeos: + version: 3.11.1-2 + title: Open Source Geometry Engine ('GEOS') C API + maintainer: Dewey Dunnington + description: |- + Provides the Open Source Geometry Engine ('GEOS') as a + C API that can be used to write high-performance C and C++ + geometry operations using R as an interface. Headers are provided + to make linking to and using these functions from C++ code as + easy and as safe as possible. This package contains an internal + copy of the 'GEOS' library to guarantee the best possible + consistency on multiple platforms. + date_publication: '2023-11-29' + bug_reports: https://github.com/paleolimbot/libgeos/issues + url: https://paleolimbot.github.io/libgeos/ + url_cran: https://CRAN.R-project.org/package=libgeos + url_git: https://github.com/paleolimbot/libgeos +LiblineaR: + version: 2.10-24 + title: Linear Predictive Models Based on the LIBLINEAR C/C++ Library + maintainer: Thibault Helleputte + description: |- + A wrapper around the LIBLINEAR C/C++ library for machine + learning (available at + ). LIBLINEAR is + a simple library for solving large-scale regularized linear + classification and regression. It currently supports + L2-regularized classification (such as logistic regression, + L2-loss linear SVM and L1-loss linear SVM) as well as + L1-regularized classification (such as L2-loss linear SVM and + logistic regression) and L2-regularized support vector + regression (with L1- or L2-loss). The main features of + LiblineaR include multi-class classification (one-vs-the rest, + and Crammer & Singer method), cross validation for model + selection, probability estimates (logistic regression only) or + weights for unbalanced data. The estimation of the models is + particularly fast as compared to other libraries. + date_publication: '2024-09-13' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=LiblineaR + url_git: '' +LibOPF: + version: 2.6.2 + title: Design of Optimum-Path Forest Classifiers + maintainer: Rafael Junqueira Martarelli + description: The 'LibOPF' is a framework to develop pattern recognition techniques + based on optimum-path forests (OPF), João P. Papa and Alexandre X. Falcão (2008) + , with methods for supervised learning and data + clustering. + date_publication: '2023-02-07' + bug_reports: https://github.com/RafaelJM/LibOPF-in-R/issues + url: https://www.ic.unicamp.br/~afalcao/libopf/ + url_cran: https://CRAN.R-project.org/package=LibOPF + url_git: https://github.com/RafaelJM/LibOPF-in-R +libr: + version: 1.3.9 + title: Libraries, Data Dictionaries, and a Data Step for R + maintainer: David Bosak + description: |- + Contains a set of functions to create data libraries, + generate data dictionaries, and simulate a data step. + The libname() function will load a directory of data into + a library in one line of code. The dictionary() function + will generate data dictionaries for individual + data frames or an entire library. And the datestep() function + will perform row-by-row data processing. + date_publication: '2025-01-12' + bug_reports: https://github.com/dbosak01/libr/issues + url: https://libr.r-sassy.org + url_cran: https://CRAN.R-project.org/package=libr + url_git: https://github.com/dbosak01/libr +Libra: + version: '1.7' + title: Linearized Bregman Algorithms for Generalized Linear Models + maintainer: Jiechao Xiong + description: |- + Efficient procedures for fitting the regularization path + for linear, binomial, multinomial, Ising and Potts models with lasso, + group lasso or column lasso(only for multinomial) penalty. + The package uses Linearized Bregman Algorithm to solve the + regularization path through iterations. Bregman Inverse Scale Space Differential + Inclusion solver is also provided for linear model with lasso penalty. + date_publication: '2022-04-11' + bug_reports: '' + url: https://arxiv.org/abs/1406.7728 + url_cran: https://CRAN.R-project.org/package=Libra + url_git: '' +librarian: + version: 1.8.1 + title: |- + Install, Update, Load Packages from CRAN, 'GitHub', and + 'Bioconductor' in One Step + maintainer: Desi Quintans + description: |- + Automatically install, update, and load 'CRAN', 'GitHub', and 'Bioconductor' + packages in a single function call. By accepting bare unquoted names for packages, + it's easy to add or remove packages from the list. + date_publication: '2021-07-12' + bug_reports: https://github.com/DesiQuintans/librarian/issues + url: '' + url_cran: https://CRAN.R-project.org/package=librarian + url_git: https://github.com/DesiQuintans/librarian +librarysnapshot: + version: 0.1.2 + title: |- + Library Snapshot for Packages and Dependencies in Use by Current + Session + maintainer: Peter Meissner + description: |- + Generate a local library copy with relevant packages. + All packages currently found within the search path - except base packages - + will be copied to the directory provided and can be used later on with the + .libPaths() function. + date_publication: '2018-02-13' + bug_reports: https://github.com/petermeissner/librarysnapshot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=librarysnapshot + url_git: https://github.com/petermeissner/librarysnapshot +libstable4u: + version: 1.0.4 + title: Stable Distribution Functions...For You + maintainer: Bruce Swihart + description: |- + Tools for fast and accurate evaluation of skew stable distributions + (CDF, PDF and quantile functions), random number generation, and parameter + estimation. This is 'libstableR' as per Royuela del Val, Simmross-Wattenberg, + and Alberola López (2017) under a new maintainer. + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=libstable4u + url_git: '' +LIC: + version: 0.0.2 + title: The LIC Criterion for Optimal Subset Selection + maintainer: Guangbao Guo + description: The LIC criterion is to determine the most informative subsets so that + the subset can retain most of the information contained in the complete data. + The philosophy of the package is described in Guo G. (2022) . + date_publication: '2022-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LIC + url_git: '' +lidaRtRee: + version: 4.0.8 + title: Forest Analysis with Airborne Laser Scanning (LiDAR) Data + maintainer: Jean-Matthieu Monnet + description: |- + Provides functions for forest objects detection, structure metrics + computation, model calibration and mapping with airborne laser scanning: + co-registration of field plots (Monnet and Mermin (2014) + ); tree detection (method 1 in Eysn et al. (2015) + ) and segmentation; forest parameters estimation with + the area-based approach: model calibration with ground reference, and maps + export (Aussenac et al. (2023) ); + extraction of both physical (gaps, edges, trees) and statistical + features useful for e.g. habitat suitability modeling (Glad et al. (2020) + ) and forest maturity mapping (Fuhr et al. (2022) + ). + date_publication: '2025-01-23' + bug_reports: https://forgemia.inra.fr/lidar/lidaRtRee/-/issues + url: https://lidar.pages.mia.inra.fr/lidaRtRee/ + url_cran: https://CRAN.R-project.org/package=lidaRtRee + url_git: '' +lidR: + version: 4.1.2 + title: |- + Airborne LiDAR Data Manipulation and Visualization for Forestry + Applications + maintainer: Jean-Romain Roussel + description: |- + Airborne LiDAR (Light Detection and Ranging) interface for data + manipulation and visualization. Read/write 'las' and 'laz' files, computation + of metrics in area based approach, point filtering, artificial point reduction, + classification from geographic data, normalization, individual tree segmentation + and other manipulations. + date_publication: '2024-07-09' + bug_reports: https://github.com/r-lidar/lidR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lidR + url_git: https://github.com/r-lidar/lidR +lievens: + version: 0.0.1 + title: Real-Time PCR Data Sets by Lievens et al. (2012) + maintainer: Ramiro Magno + description: |- + Real-time quantitative polymerase chain reaction (qPCR) data + sets by Lievens et al. (2012) . Provides one + single tabular tidy data set in long format, encompassing three + dilution series, targeted against the soybean Lectin endogene. Each dilution + series was assayed in one of the following PCR-efficiency-modifying + conditions: no PCR inhibition, inhibition by isopropanol and inhibition by + tannic acid. The inhibitors were co-diluted along with the dilution series. + The co-dilution series consists of a five-point, five-fold serial dilution. + For each concentration there are 18 replicates. Each amplification + curve is 60 cycles long. Original raw data file is available at the + Supplementary Data section at Nucleic Acids Research Online . + date_publication: '2024-05-03' + bug_reports: https://github.com/ramiromagno/lievens/issues + url: https://rmagno.eu/lievens/ + url_cran: https://CRAN.R-project.org/package=lievens + url_git: https://github.com/ramiromagno/lievens +lifecontingencies: + version: 1.3.12 + title: Financial and Actuarial Mathematics for Life Contingencies + maintainer: Giorgio Alfredo Spedicato + description: "Classes and methods that allow the user to manage life table,\nactuarial + tables (also multiple decrements tables). Moreover, functions to easily\nperform + demographic, financial and actuarial mathematics on life contingencies\ninsurances + calculations are contained therein. See Spedicato (2013)\t." + date_publication: '2024-09-29' + bug_reports: https://github.com/spedygiorgio/lifecontingencies/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lifecontingencies + url_git: https://github.com/spedygiorgio/lifecontingencies +lifecourse: + version: '2.0' + title: Quantification of Lifecourse Fluidity + maintainer: Glenna Nightingale + description: |- + Provides in built datasets and three functions. + These functions are mobility_index, nonStanTest and linkedLives. The mobility_index + function facilitates the calculation of lifecourse fluidity, whilst the nonStanTest and the + linkedLives functions allow the user to determine the probability that the observed sequence data + was due to chance. The linkedLives function acknowledges the fact that some individuals may + have identical sequences. + The datasets available provide sequence data on marital status(maritalData) + and mobility (mydata) for a selected group of individuals from the British Household Panel Study + (BHPS). In addition, personal and house ID's for 100 individuals are provided in a + third dataset (myHouseID) from the BHPS. + date_publication: '2016-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lifecourse + url_git: '' +lifecycle: + version: 1.0.4 + title: Manage the Life Cycle of your Package Functions + maintainer: Lionel Henry + description: |- + Manage the life cycle of your exported functions with shared + conventions, documentation badges, and user-friendly deprecation + warnings. + date_publication: '2023-11-07' + bug_reports: https://github.com/r-lib/lifecycle/issues + url: https://lifecycle.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=lifecycle + url_git: https://github.com/r-lib/lifecycle +LifeHist: + version: 1.0-1 + title: Life History Models of Individuals + maintainer: Ruben H. Roa-Ureta + description: Likelihood-based estimation of individual growth and sexual maturity + models for organisms, usually fish and invertebrates. It includes methods for + data organization, plotting standard exploratory and analytical plots, predictions. + date_publication: '2015-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LifeHist + url_git: '' +LifeInsuranceContracts: + version: 0.0.6 + title: Framework for Traditional Life Insurance Contracts + maintainer: Reinhold Kainhofer + description: Use of this package is deprecated. It has been renamed to 'LifeInsureR'. + date_publication: '2023-11-07' + bug_reports: https://gitlab.open-tools.net/R/LifeInsureR/-/issues + url: https://gitlab.open-tools.net/R/LifeInsureR + url_cran: https://CRAN.R-project.org/package=LifeInsuranceContracts + url_git: '' +LifeInsureR: + version: 1.0.0 + title: Modelling Traditional Life Insurance Contracts + maintainer: Reinhold Kainhofer + description: |- + R6 classes to model traditional life insurance + contracts like annuities, whole life insurances or endowments. Such life + insurance contracts provide a guaranteed interest and are not directly linked + to the performance of a particular investment vehicle, but they typically + provide (discretionary) profit participation. This package provides a framework + to model such contracts in a very generic (cash-flow-based) way and includes + modelling profit participation schemes, dynamic increases or more general + contract layers, as well as contract changes (like sum increases or premium + waivers). All relevant quantities like premium decomposition, reserves and + benefits over the whole contract period are calculated and potentially + exported to 'Excel'. Mortality rates are given using the 'MortalityTables' package. + date_publication: '2023-11-06' + bug_reports: https://gitlab.open-tools.net/R/LifeInsureR/-/issues + url: https://gitlab.open-tools.net/R/LifeInsureR + url_cran: https://CRAN.R-project.org/package=LifeInsureR + url_git: https://github.com/kainhofer/LifeInsureR +lifelogr: + version: 0.1.0 + title: Life Logging + maintainer: Lisa Ann Yu + description: Provides a framework for combining self-data (exercise, sleep, etc.) + from multiple sources (fitbit, Apple Health), creating visualizations, and experimenting + on onself. + date_publication: '2017-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lifelogr + url_git: '' +LifemapR: + version: 1.1.4 + title: Data Visualisation on 'Lifemap' Tree + maintainer: Aurélie Siberchicot + description: Allow to visualise data on the NCBI phylogenetic tree as presented + in Lifemap . It takes as input a dataframe with + at least a "taxid" column containing NCBI format TaxIds and allows to draw multiple + layers with different visualisation tools. + date_publication: '2024-07-31' + bug_reports: https://github.com/Lifemap-ToL/LifemapR/issues + url: https://lifemap-tol.github.io/LifemapR/ + url_cran: https://CRAN.R-project.org/package=LifemapR + url_git: https://github.com/Lifemap-ToL/LifemapR +lifepack: + version: 0.1.0 + title: Insurance Reserve Calculations + maintainer: Oskar Allerslev + description: Calculates insurance reserves and equivalence premiums using advanced + numerical methods, including the Runge-Kutta algorithm and product integrals for + transition probabilities. This package is useful for actuarial analyses and life + insurance modeling, facilitating accurate financial projections. + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lifepack + url_git: '' +lifeR: + version: 1.0.3 + title: Identify Sites for Your Bird List + maintainer: Jeffrey Oliver + description: |- + A suite of tools to use the 'eBird' database + () and APIs to compare users' species lists to + recent observations and create a report of the top sites to visit to see + new species. + date_publication: '2025-02-10' + bug_reports: '' + url: https://jcoliver.github.io/lifeR/ + url_cran: https://CRAN.R-project.org/package=lifeR + url_git: https://github.com/jcoliver/lifeR/ +Lifertable: + version: 0.1.0 + title: Life and Fertility Tables Specially for Insects + maintainer: Carlos Abimael Sarmiento Sanchez + description: |- + Life and Fertility Tables are appropriate to study the dynamics of + arthropods populations. This package provides utilities for constructing + Life Tables and Fertility Tables, related demographic parameters, and some + simple graphs of interest. It also offers functions to transform the + obtained data into a known format for better manipulation. This document is + based on the article by Maia, Luiz, and Campanhola "Statistical Inference on + Associated Fertility Life Table Parameters Using Jackknife Technique + Computational Aspects" (April 2000, Journal of Economic Entomology, Volume + 93, Issue 2) . + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Lifertable + url_git: '' +LifeTables: + version: '1.0' + title: Two-Parameter HMD Model Life Table System + maintainer: David J. Sharrow + description: |- + Functions supplied in this package will implement + discriminant analysis to select an appropriate life table + family, select an appropriate alpha level based on a desired + life expectancy at birth, produce a model mortality pattern + based on family and level as well as plot the results. + date_publication: '2015-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LifeTables + url_git: '' +liftLRD: + version: 1.0-9 + title: |- + Wavelet Lifting Estimators of the Hurst Exponent for Regularly + and Irregularly Sampled Time Series + maintainer: Matt Nunes + description: Implementations of Hurst exponent estimators based on the relationship + between wavelet lifting scales and wavelet energy of Knight et al (2017) . + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=liftLRD + url_git: '' +liftr: + version: 0.9.2 + title: Containerize R Markdown Documents for Continuous Reproducibility + maintainer: Nan Xiao + description: Persistent reproducible reporting by containerization of R Markdown + documents. + date_publication: '2019-06-19' + bug_reports: https://github.com/nanxstats/liftr/issues + url: https://nanx.me/liftr/ + url_cran: https://CRAN.R-project.org/package=liftr + url_git: https://github.com/nanxstats/liftr +LiftTest: + version: 0.2.0 + title: A Bootstrap Proportion Test for Brand Lift Testing + maintainer: Wanjun Liu + description: |- + A bootstrap proportion test for Brand Lift Testing to quantify the effectiveness of online advertising. Methods of the bootstrap proportion test are presented in + Liu, Yu, Mao, Wu, Dyer (2023) . + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LiftTest + url_git: '' +lifx: + version: 0.2.0 + title: Control 'LIFX' Smart Light Bulbs + maintainer: Martin Barner + description: |- + Allows you to read and change the state of 'LIFX' smart light bulbs via the 'LIFX' developer api . + Covers most 'LIFX' api endpoints, including changing light color and brightness, selecting lights by id, group or location as well as activating effects. + date_publication: '2020-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lifx + url_git: '' +lightAUC: + version: 0.1.2 + title: Fast AUC Computation + maintainer: Christos Adam + description: |- + Fast calculation of Area Under Curve (AUC) metric of a + Receiver Operating Characteristic (ROC) curve, using the algorithm + of Fawcett (2006) . Therefore it + is appropriate for large-scale AUC metric calculations. + date_publication: '2025-02-11' + bug_reports: https://github.com/cadam00/lightAUC/issues + url: https://cadam00.github.io/lightAUC/ + url_cran: https://CRAN.R-project.org/package=lightAUC + url_git: https://github.com/cadam00/lightAUC +lightgbm: + version: 4.6.0 + title: Light Gradient Boosting Machine + maintainer: James Lamb + description: |- + Tree based algorithms can be improved by introducing boosting frameworks. + 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) . + This package offers an R interface to work with it. + It is designed to be distributed and efficient with the following advantages: + 1. Faster training speed and higher efficiency. + 2. Lower memory usage. + 3. Better accuracy. + 4. Parallel learning supported. + 5. Capable of handling large-scale data. + In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. + Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines. + date_publication: '2025-02-13' + bug_reports: https://github.com/Microsoft/LightGBM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lightgbm + url_git: https://github.com/Microsoft/LightGBM +LightLogR: + version: 0.5.3 + title: |- + Process Data from Wearable Light Loggers and Optical Radiation + Dosimeters + maintainer: Johannes Zauner + description: Import, processing, validation, and visualization of personal light + exposure measurement data from wearable devices. The package implements features + such as the import of data and metadata files, conversion of common file formats, + validation of light logging data, verification of crucial metadata, calculation + of common parameters, and semi-automated analysis and visualization. + date_publication: '2025-02-24' + bug_reports: https://github.com/tscnlab/LightLogR/issues + url: https://tscnlab.github.io/LightLogR/ + url_cran: https://CRAN.R-project.org/package=LightLogR + url_git: https://github.com/tscnlab/LightLogR +LightningR: + version: 1.0.2 + title: Tools for Communication with Lightning-Viz Server + maintainer: Kolodziejski Kamil + description: |- + The purpose of this package is to enable usage of lightningviz server to be accessible from R. The + server itself can be found at http://lightning-viz.org/ and is required to work with this package. Package + by itself cannot and will not create any visualizations. + date_publication: '2015-12-14' + bug_reports: https://github.com/Ermlab/lightining-rstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LightningR + url_git: https://github.com/Ermlab/lightining-rstat/ +lightparser: + version: 0.1.0 + title: From 'Rmarkdown' and 'Quarto' Files to Tibble and Back + maintainer: Sebastien Rochette + description: |- + Split your 'rmarkdown' or 'quarto' files by sections into a + tibble: titles, text, chunks. Rebuild the file from the tibble. + date_publication: '2024-01-24' + bug_reports: https://github.com/ThinkR-open/lightparser/issues + url: https://thinkr-open.github.io/lightparser/ + url_cran: https://CRAN.R-project.org/package=lightparser + url_git: https://github.com/ThinkR-open/lightparser +lightr: + version: 1.8.0 + title: Read Spectrometric Data and Metadata + maintainer: Hugo Gruson + description: |- + Parse various reflectance/transmittance/absorbance spectra file + formats to extract spectral data and metadata, as described in Gruson, White + & Maia (2019) . Among other formats, it can import + files from 'Avantes' , 'CRAIC' + , and 'OceanOptics'/'OceanInsight' + brands. + date_publication: '2024-12-01' + bug_reports: https://github.com/ropensci/lightr/issues + url: https://docs.ropensci.org/lightr/ + url_cran: https://CRAN.R-project.org/package=lightr + url_git: https://github.com/ropensci/lightr +lightsout: + version: 0.3.2 + title: Implementation of the 'Lights Out' Puzzle Game + maintainer: Dean Attali + description: |- + Lights Out is a puzzle game consisting of a grid of lights + that are either on or off. Pressing any light will toggle it and its + adjacent lights. The goal of the game is to switch all the lights off. This + package provides an interface to play the game on different board sizes, + both through the command line or with a visual application. Puzzles can + also be solved using the automatic solver included. View a demo + online at . + date_publication: '2023-08-21' + bug_reports: https://github.com/daattali/lightsout/issues + url: https://daattali.com/shiny/lightsout/ + url_cran: https://CRAN.R-project.org/package=lightsout + url_git: https://github.com/daattali/lightsout +likelihood: + version: '1.9' + title: Methods for Maximum Likelihood Estimation + maintainer: Lora Murphy + description: |- + Tools for maximum likelihood estimation of parameters + of scientific models. Based on Goffe et al (1994) . + date_publication: '2023-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=likelihood + url_git: '' +likelihoodAsy: + version: '0.51' + title: Functions for Likelihood Asymptotics + maintainer: Ruggero Bellio + description: Functions for computing the r and r* statistics for inference on an + arbitrary scalar function of model parameters, plus some code for the (modified) + profile likelihood. + date_publication: '2020-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=likelihoodAsy + url_git: '' +likelihoodExplore: + version: 0.1.0 + title: Likelihood Exploration + maintainer: Ben Barnard + description: |- + Provides likelihood functions as defined by Fisher (1922) + and a function that creates likelihood + functions from density functions. The functions are meant to aid in + education of likelihood based methods. + date_publication: '2017-11-14' + bug_reports: '' + url: https://likelihoodExplore.bearstatistics.com + url_cran: https://CRAN.R-project.org/package=likelihoodExplore + url_git: '' +likelihoodR: + version: 1.1.5 + title: Likelihood Analyses for Common Statistical Tests + maintainer: Peter Cahusac + description: |- + A collection of functions that calculate the log likelihood + (support) for a range of statistical tests. Where possible the likelihood + function and likelihood interval for the observed data are displayed. The + evidential approach used here is based on the book "Likelihood" by A.W.F. + Edwards (1992, ISBN-13 : 978-0801844430), "Statistical Evidence" by R. + Royall (1997, ISBN-13 : 978-0412044113), S.N. Goodman & R. Royall + (2011) , "Understanding + Psychology as a Science" by Z. Dienes (2008, ISBN-13 : 978-0230542310), + S. Glover & P. Dixon + and others. This package accompanies "Evidence-Based Statistics" by + P. Cahusac (2020, ISBN-13 : 978-1119549802) + . + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=likelihoodR + url_git: '' +likert: + version: 1.3.5 + title: Analysis and Visualization Likert Items + maintainer: Jason Bryer + description: |- + An approach to analyzing Likert response items, with an emphasis on visualizations. + The stacked bar plot is the preferred method for presenting Likert results. Tabular results + are also implemented along with density plots to assist researchers in determining whether + Likert responses can be used quantitatively instead of qualitatively. See the likert(), + summary.likert(), and plot.likert() functions to get started. + date_publication: '2016-12-31' + bug_reports: https://github.com/jbryer/likert/issues + url: http://jason.bryer.org/likert + url_cran: https://CRAN.R-project.org/package=likert + url_git: http://github.com/jbryer/likert +LikertMakeR: + version: 0.4.0 + title: |- + Synthesise and Correlate Likert Scale and Related Rating-Scale + Data + maintainer: Hume Winzar + description: |- + Synthesise Likert scale and related rating-scale data with + predefined first and second moments (mean and standard deviation), + and, optionally, correlate multiple vectors using a predefined + correlation matrix. Additionally, generate synthetic rating-scale + items with a predefined Cronbach's Alpha, or create rating-scale items + based on a predefined summated scale. + date_publication: '2024-11-19' + bug_reports: https://github.com/WinzarH/LikertMakeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LikertMakeR + url_git: https://github.com/WinzarH/LikertMakeR +lilikoi: + version: 2.1.1 + title: Metabolomics Personalized Pathway Analysis Tool + maintainer: Lana Garmire + description: 'A comprehensive analysis tool for metabolomics data. It consists + a variety of functional modules, including several new modules: a pre-processing + module for normalization and imputation, an exploratory data analysis module for + dimension reduction and source of variation analysis, a classification module + with the new deep-learning method and other machine-learning methods, a prognosis + module with cox-PH and neural-network based Cox-nnet methods, and pathway analysis + module to visualize the pathway and interpret metabolite-pathway relationships. + References: H. Paul Benton + Jeff Xia + Travers Ching, Xun Zhu, Lana X. Garmire (2018) .' + date_publication: '2022-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lilikoi + url_git: '' +lillies: + version: 0.2.12 + title: Estimation of Life Years Lost + maintainer: Oleguer Plana-Ripoll + description: |- + Estimation of life expectancy and + Life Years Lost (LYL, or lillies for short) for a given population, for + example those with a given disease or condition. In addition, the package + can be used to compare estimates from different populations, or to estimate + confidence intervals. Technical details of the method are available in + Plana-Ripoll et al. (2020) and Andersen + (2017) . + date_publication: '2023-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lillies + url_git: '' +LilRhino: + version: 1.2.2 + title: |- + For Implementation of Feed Reduction, Learning Examples, NLP and + Code Management + maintainer: Travis Barton + description: This is for code management functions, NLP tools, a Monty Hall simulator, + and for implementing my own variable reduction technique called Feed Reduction. + The Feed Reduction technique is not yet published, but is merely a tool for implementing + a series of binary neural networks meant for reducing data into N dimensions, + where N is the number of possible values of the response variable. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LilRhino + url_git: '' +LIM: + version: 1.4.7.1 + title: Linear Inverse Model Examples and Solution Methods + maintainer: Karline Soetaert + description: |- + Functions that read and solve linear inverse problems (food web problems, linear programming problems). + These problems find solutions to linear or quadratic functions: + min or max (f(x)), where f(x) = ||Ax-b||^2 or f(x) = sum(ai*xi) + subject to equality constraints Ex=f and inequality constraints Gx>=h. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LIM + url_git: '' +lime: + version: 0.5.3 + title: Local Interpretable Model-Agnostic Explanations + maintainer: Emil Hvitfeldt + description: |- + When building complex models, it is often difficult to explain why + the model should be trusted. While global measures such as accuracy are + useful, they cannot be used for explaining why a model made a specific + prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for + explaining the outcome of black box models by fitting a local model around + the point in question an perturbations of this point. The approach is + described in more detail in the article by Ribeiro et al. (2016) + . + date_publication: '2022-08-19' + bug_reports: https://github.com/thomasp85/lime/issues + url: https://lime.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=lime + url_git: https://github.com/thomasp85/lime +limexhub: + version: 0.1.5 + title: Quantitative Trade Signals + maintainer: Vyacheslav Arbuzov + description: Provides an interface to the financial data platform ., + enabling users to retrieve real-time and historical financial data. Functions + within the package allow access to instruments, candlestick charts, fundamentals, + news, events, models, and trading signals. Authentication is managed through user-specific + API tokens, which are securely handled via environment variables. + date_publication: '2024-05-06' + bug_reports: https://github.com/Limex-com/limexhub-r/issues + url: https://datahub.limex.com + url_cran: https://CRAN.R-project.org/package=limexhub + url_git: '' +liminal: + version: 0.1.2 + title: Multivariate Data Visualization with Tours and Embeddings + maintainer: Stuart Lee + description: |- + Compose interactive visualisations designed for exploratory + high-dimensional data analysis. With 'liminal' you can create linked + interactive graphics to diagnose the quality of a dimension reduction + technique and explore the global structure of a dataset with a tour. A + complete description of the method is discussed in + ['Lee' & 'Laa' & 'Cook' (2020) ]. + date_publication: '2021-05-28' + bug_reports: https://github.com/sa-lee/liminal/issues/ + url: https://sa-lee.github.io/liminal/ + url_cran: https://CRAN.R-project.org/package=liminal + url_git: https://github.com/sa-lee/liminal/ +LimnoPalettes: + version: 0.1.0 + title: A Limnology Themed Palette Generator + maintainer: Paul Julian + description: Palettes generated from limnology based field and laboratory photos. + Palettes can be used to generate color values to be used in any functions that + calls for a color (i.e. ggplot(), plot(), flextable(), etc.). + date_publication: '2020-10-19' + bug_reports: https://github.com/SwampThingPaul/LimnoPalettes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LimnoPalettes + url_git: https://github.com/SwampThingPaul/LimnoPalettes +limonaid: + version: 0.1.5 + title: Working with 'LimeSurvey' Surveys and Responses + maintainer: Gjalt-Jorn Peters + description: |- + 'LimeSurvey' is Free/Libre Open Source Software for + the development and administrations of online studies, using + sophisticated tailoring capabilities to support multiple study + designs (see ). This package supports + programmatic creation of surveys that can then be imported into + 'LimeSurvey', as well as user friendly import of responses from + 'LimeSurvey' studies. + date_publication: '2022-06-13' + bug_reports: https://gitlab.com/r-packages/limonaid/-/issues + url: https://r-packages.gitlab.io/limonaid + url_cran: https://CRAN.R-project.org/package=limonaid + url_git: '' +limorhyde: + version: 1.0.1 + title: Differential Analysis of Rhythmic Transcriptome Data + maintainer: Jake Hughey + description: |- + A flexible approach, inspired by cosinor regression, for + differential analysis of rhythmic transcriptome data. See Singer and Hughey + (2018) . + date_publication: '2022-02-18' + bug_reports: https://github.com/hugheylab/limorhyde/issues + url: https://limorhyde.hugheylab.org + url_cran: https://CRAN.R-project.org/package=limorhyde + url_git: https://github.com/hugheylab/limorhyde +limorhyde2: + version: 0.1.0 + title: |- + Quantify Rhythmicity and Differential Rhythmicity in Genomic + Data + maintainer: Jake Hughey + description: |- + Fit linear models based on periodic splines, moderate model + coefficients using multivariate adaptive shrinkage, then compute properties of + the moderated curves. + date_publication: '2023-01-26' + bug_reports: '' + url: https://limorhyde2.hugheylab.org + url_cran: https://CRAN.R-project.org/package=limorhyde2 + url_git: https://github.com/hugheylab/limorhyde2 +limSolve: + version: 1.5.7.1 + title: Solving Linear Inverse Models + maintainer: Karline Soetaert + description: |- + Functions that (1) find the minimum/maximum of a linear or quadratic function: + min or max (f(x)), where f(x) = ||Ax-b||^2 or f(x) = sum(a_i*x_i) + subject to equality constraints Ex=f and/or inequality constraints Gx>=h, + (2) sample an underdetermined- or overdetermined system Ex=f subject to Gx>=h, and if applicable Ax~=b, + (3) solve a linear system Ax=B for the unknown x. It includes banded and tridiagonal linear systems. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=limSolve + url_git: '' +lin.eval: + version: 0.1.2 + title: Perform Polynomial Evaluation of Linearity + maintainer: Vishesh Shrivastav + description: Evaluates whether the relationship between two vectors is linear or + nonlinear. Performs a test to determine how well a linear model fits the data + compared to higher order polynomial models. Jhang et al. (2004) . + date_publication: '2019-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lin.eval + url_git: '' +linbin: + version: 0.1.3 + title: Binning and Plotting of Linearly Referenced Data + maintainer: Ethan Z. Welty + description: |- + Short for 'linear binning', the linbin package provides functions + for manipulating, binning, and plotting linearly referenced data. Although + developed for data collected on river networks, it can be used with any interval + or point data referenced to a 1-dimensional coordinate system. Flexible bin + generation and batch processing makes it easy to compute and visualize variables + at multiple scales, useful for identifying patterns within and between variables + and investigating the influence of scale of observation on data interpretation. + date_publication: '2021-04-20' + bug_reports: https://github.com/ezwelty/linbin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linbin + url_git: https://github.com/ezwelty/linbin +LinCal: + version: 1.0.1 + title: Static Univariate Frequentist and Bayesian Linear Calibration + maintainer: Derick L. Rivers + description: |- + Estimate and confidence/credible intervals for an unknown + regressor x0 given an observed y0. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LinCal + url_git: '' +lincom: + version: '1.2' + title: 'Linear Biomarker Combination: Empirical Performance Optimization' + maintainer: Yijian Huang + description: 'Perform two linear combination methods for biomarkers: (1) Empirical + performance optimization for specificity (or sensitivity) at a controlled sensitivity + (or specificity) level of Huang and Sanda (2022) , and + (2) weighted maximum score estimator with empirical minimization of averaged false + positive rate and false negative rate. Both adopt the algorithms of Huang and + Sanda (2022) . ''MOSEK'' solver is used and needs to be + installed; an academic license for ''MOSEK'' is free.' + date_publication: '2024-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lincom + url_git: '' +linconGaussR: + version: '0.1' + title: |- + Sampling Multivariate Normal Distribution under Linear + Constraints + maintainer: Yunyi Shen + description: Sample truncated multivariate Normal distribution following Gessner, + A., Kanjilal, O., & Hennig, P. (2019). Integrals over Gaussians under Linear Domain + Constraints. 108. . + date_publication: '2021-10-26' + bug_reports: https://github.com/YunyiShen/linconGaussR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linconGaussR + url_git: https://github.com/YunyiShen/linconGaussR +LindenmayeR: + version: 0.1.13 + title: Functions to Explore L-Systems (Lindenmayer Systems) + maintainer: Bryan Hanson + description: |- + L-systems or Lindenmayer systems are parallel rewriting systems which can + be used to simulate biological forms and certain kinds of fractals. + Briefly, in an L-system a series of symbols in a string are replaced + iteratively according to rules to give a more complex string. Eventually, + the symbols are translated into turtle graphics for plotting. Wikipedia has + a very good introduction: en.wikipedia.org/wiki/L-system This package + provides basic functions for exploring L-systems. + date_publication: '2017-07-31' + bug_reports: https://github.com/bryanhanson/LindenmayeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LindenmayeR + url_git: '' +lindia: + version: '0.10' + title: Automated Linear Regression Diagnostic + maintainer: Yeuk Yu Lee + description: |- + Provides a set of streamlined functions that allow + easy generation of linear regression diagnostic plots necessarily + for checking linear model assumptions. + This package is meant for easy scheming of linear + regression diagnostics, while preserving merits of + "The Grammar of Graphics" as implemented in 'ggplot2'. + See the 'ggplot2' website for more information regarding the + specific capability of graphics. + date_publication: '2023-08-10' + bug_reports: https://github.com/yeukyul/lindia/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lindia + url_git: https://github.com/yeukyul/lindia +LindleyPowerSeries: + version: 1.0.1 + title: Lindley Power Series Distribution + maintainer: Yuancheng Si + description: Computes the probability density function, the cumulative distribution + function, the hazard rate function, the quantile function and random generation + for Lindley Power Series distributions, see Nadarajah and Si (2018) . + date_publication: '2021-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LindleyPowerSeries + url_git: '' +linearModel: + version: 1.0.2 + title: Linear Model Functions + maintainer: Jared Studyvin + description: Functions to access and test results from a linear model. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=linearModel + url_git: '' +LinearRegressionMDE: + version: '1.0' + title: Minimum Distance Estimation in Linear Regression Model + maintainer: Jiwoong Kim + description: Consider linear regression model Y = Xb + error where the distribution + function of errors is unknown, but errors are independent and symmetrically distributed. + The package contains a function named LRMDE which takes Y and X as input and returns + minimum distance estimator of parameter b in the model. + date_publication: '2015-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LinearRegressionMDE + url_git: '' +lineartestr: + version: 1.0.0 + title: Linear Specification Testing + maintainer: Federico Garza + description: |- + Tests whether the linear hypothesis of a model + is correct specified using Dominguez-Lobato test. Also Ramsey's RESET (Regression Equation + Specification Error Test) test is implemented and Wald tests can be carried out. + Although RESET test is widely used to + test the linear hypothesis of a model, Dominguez and Lobato (2019) proposed a novel + approach that generalizes well known specification tests such as Ramsey's. This test + relies on wild-bootstrap; this package implements this approach to be + usable with any function that fits linear models and is compatible with + the update() function such as 'stats'::lm(), 'lfe'::felm() and 'forecast'::Arima(), + for ARMA (autoregressive–moving-average) models. + Also the package can handle custom statistics such as Cramer von Mises and Kolmogorov + Smirnov, described by the authors, and custom distributions such as Mammen (discrete + and continuous) and Rademacher. + Manuel A. Dominguez & Ignacio N. Lobato (2019) . + date_publication: '2020-06-12' + bug_reports: https://github.com/FedericoGarza/lineartestr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lineartestr + url_git: https://github.com/FedericoGarza/lineartestr +linelist: + version: 1.1.4 + title: Tagging and Validating Epidemiological Data + maintainer: Hugo Gruson + description: Provides tools to help storing and handling case line list data. The + 'linelist' class adds a tagging system to classical 'data.frame' objects to identify + key epidemiological data such as dates of symptom onset, epidemiological case + definition, age, gender or disease outcome. Once tagged, these variables can be + seamlessly used in downstream analyses, making data pipelines more robust and + reliable. + date_publication: '2024-06-17' + bug_reports: https://github.com/epiverse-trace/linelist/issues + url: https://epiverse-trace.github.io/linelist/ + url_cran: https://CRAN.R-project.org/package=linelist + url_git: https://github.com/epiverse-trace/linelist +linelistBayes: + version: '1.0' + title: |- + Bayesian Analysis of Epidemic Data Using Line List and Case + Count Approaches + maintainer: Chad Milando + description: |- + Provides tools for performing Bayesian inference on epidemiological + data to estimate the time-varying reproductive number and other related metrics. + These methods were published in Li and White (2021) . + This package supports analyses based on aggregated case count data and individual line list + data, facilitating enhanced surveillance and intervention planning for infectious + diseases like COVID-19. + date_publication: '2024-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=linelistBayes + url_git: '' +linemap: + version: 0.3.0 + title: Line Maps + maintainer: Timothée Giraud + description: |- + Create maps made of lines. The package contains one function: + linemap(). linemap() displays a map made of lines using a + raster or gridded data. + date_publication: '2023-11-28' + bug_reports: https://github.com/riatelab/linemap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linemap + url_git: https://github.com/riatelab/linemap +linERR: + version: '1.0' + title: Linear Excess Relative Risk Model + maintainer: David Moriña Soler + description: Fits a linear excess relative risk model by maximum likelihood, possibly + including several variables and allowing for lagged exposures. + date_publication: '2016-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=linERR + url_git: '' +lineup: + version: '0.44' + title: Lining Up Two Sets of Measurements + maintainer: Karl W Broman + description: |- + Tools for detecting and correcting sample mix-ups between two sets + of measurements, such as between gene expression data on two tissues. + Broman et al. (2015) . + date_publication: '2024-07-15' + bug_reports: https://github.com/kbroman/lineup/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lineup + url_git: https://github.com/kbroman/lineup +lineup2: + version: '0.6' + title: Lining Up Two Sets of Measurements + maintainer: Karl W Broman + description: |- + Tools for detecting and correcting sample mix-ups between two sets + of measurements, such as between gene expression data on two + tissues. This is a revised version of the 'lineup' package, to be + more general and not tied to the 'qtl' package. + date_publication: '2021-06-15' + bug_reports: https://github.com/kbroman/lineup2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lineup2 + url_git: https://github.com/kbroman/lineup2 +lineupjs: + version: 4.6.0 + title: |- + 'HTMLWidget' Wrapper of 'LineUp' for Visual Analysis of + Multi-Attribute Rankings + maintainer: Samuel Gratzl + description: |- + 'LineUp' is an interactive technique designed to create, visualize and explore rankings of items based on a set of heterogeneous attributes. + This is a 'htmlwidget' wrapper around the JavaScript library 'LineUp.js'. + It is designed to be used in 'R Shiny' apps and 'R Markddown' files. + Due to an outdated 'webkit' version of 'RStudio' it won't work in the integrated viewer. + date_publication: '2022-08-19' + bug_reports: https://github.com/lineupjs/lineup_htmlwidget/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lineupjs + url_git: https://github.com/lineupjs/lineup_htmlwidget/ +linevis: + version: 1.0.0 + title: Interactive Time Series Visualizations + maintainer: Thomas Charlon + description: |- + Create interactive time series visualizations. + 'linevis' includes an extensive API to manipulate time series after creation, + and supports getting data out of the visualization. Based on the + 'timevis' package and the 'vis.js' Timeline 'JavaScript' library . + date_publication: '2025-01-10' + bug_reports: https://gitlab.com/thomaschln/linevis/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linevis + url_git: https://gitlab.com/thomaschln/linevis +lingdist: + version: '1.0' + title: Fast Linguistic Distance and Alignment Computation + maintainer: Chao Kong + description: A fast generalized edit distance and string alignment computation mainly + for linguistic aims. As a generalization to the classic edit distance algorithms, + the package allows users to define custom cost for every symbol's insertion, deletion, + and substitution. The package also allows character combinations in any length + to be seen as a single symbol which is very useful for International Phonetic + Alphabet (IPA) transcriptions with diacritics. In addition to edit distance result, + users can get detailed alignment information such as all possible alignment scenarios + between two strings which is useful for testing, illustration or any further usage. + Either the distance matrix or its long table form can be obtained and tools to + do such conversions are provided. All functions in the package are implemented + in 'C++' and the distance matrix computation is parallelized leveraging the 'RcppThread' + package. + date_publication: '2023-10-12' + bug_reports: https://github.com/fncokg/lingdist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lingdist + url_git: https://github.com/fncokg/lingdist +lingglosses: + version: 0.0.8 + title: |- + Interlinear Glossed Linguistic Examples and Abbreviation Lists + Generation + maintainer: George Moroz + description: |- + Helps to render interlinear glossed linguistic examples in html + 'rmarkdown' documents and then semi-automatically compiles the list of + glosses at the end of the document. It also provides a database of linguistic + glosses. + date_publication: '2024-09-06' + bug_reports: https://github.com/agricolamz/lingglosses/issues + url: https://agricolamz.github.io/lingglosses/ + url_cran: https://CRAN.R-project.org/package=lingglosses + url_git: '' +lingmatch: + version: 1.0.7 + title: Linguistic Matching and Accommodation + maintainer: Micah Iserman + description: |- + Measure similarity between texts. Offers a variety of processing + tools and similarity metrics to facilitate flexible representation of texts and matching. + Implements forms of Language Style Matching (Ireland & Pennebaker, 2010) + and Latent Semantic Analysis (Landauer & Dumais, 1997) . + date_publication: '2024-05-03' + bug_reports: https://github.com/miserman/lingmatch/issues + url: https://miserman.github.io/lingmatch/ + url_cran: https://CRAN.R-project.org/package=lingmatch + url_git: '' +lingtypology: + version: 1.1.20 + title: Linguistic Typology and Mapping + maintainer: George Moroz + description: Provides R with the Glottolog database and + some more abilities for purposes of linguistic mapping. The Glottolog database + contains the catalogue of languages of the world. This package helps researchers + to make a linguistic maps, using philosophy of the Cross-Linguistic Linked Data + project , which allows for while at the same time facilitating + uniform access to the data across publications. A tutorial for this package is + available on GitHub pages and package + vignette. Maps created by this package can be used both for the investigation + and linguistic teaching. In addition, package provides an ability to download + data from typological databases such as WALS, AUTOTYP and some others and to create + your own database website. + date_publication: '2024-10-31' + bug_reports: https://github.com/ropensci/lingtypology/issues + url: https://ropensci.github.io/lingtypology/ + url_cran: https://CRAN.R-project.org/package=lingtypology + url_git: https://github.com/ropensci/lingtypology/ +linguisticsdown: + version: 1.2.0 + title: Easy Linguistics Document Writing with R Markdown + maintainer: Yongfu Liao + description: |- + Provides 'Shiny gadgets' to search, type, and insert IPA symbols + into documents or scripts, requiring only knowledge about phonetics or + 'X-SAMPA'. Also provides functions to facilitate the rendering of IPA + symbols in 'LaTeX' and PDF format, making IPA symbols properly rendered + in all output formats. A minimal R Markdown template for authoring + Linguistics related documents is also bundled with the package. Some + helper functions to facilitate authoring with R Markdown is also provided. + date_publication: '2019-03-01' + bug_reports: https://github.com/liao961120/linguisticsdown/issues + url: https://liao961120.github.io/linguisticsdown/ + url_cran: https://CRAN.R-project.org/package=linguisticsdown + url_git: https://github.com/liao961120/linguisticsdown +link: + version: 2024.4.0 + title: Hyperlink Automatic Detection + maintainer: Romain François + description: |- + Automatic detection of hyperlinks for packages and calls in the text + of 'rmarkdown' or 'quarto' documents. + date_publication: '2024-03-11' + bug_reports: https://github.com/tadascience/link/issues + url: https://link.tada.science/ + url_cran: https://CRAN.R-project.org/package=link + url_git: https://github.com/tadascience/link +link2GI: + version: 0.6-2 + title: |- + Linking Geographic Information Systems, Remote Sensing and Other + Command Line Tools + maintainer: Chris Reudenbach + description: Functions and tools for using open GIS and remote sensing command-line + interfaces in a reproducible environment. + date_publication: '2024-10-28' + bug_reports: https://github.com/r-spatial/link2GI/issues/ + url: https://r-spatial.github.io/link2GI/ + url_cran: https://CRAN.R-project.org/package=link2GI + url_git: https://github.com/r-spatial/link2GI/ +Linkage: + version: '0.9' + title: |- + Clustering Communication Networks Using the Stochastic Topic + Block Model Through Linkage.fr + maintainer: Charles Bouveyron + description: |- + It allows to cluster communication networks using the Stochastic + Topic Block Model by posting jobs through + the API of the linkage.fr server, which implements the clustering method. + The package also allows to visualize the clustering results returned by the server. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Linkage + url_git: '' +LinkageMapView: + version: 2.1.2 + title: Plot Linkage Group Maps with Quantitative Trait Loci + maintainer: Lisa Ouellette + description: |- + Produces high resolution, publication ready linkage maps + and quantitative trait loci maps. Input can be output from 'R/qtl', + simple text or comma delimited files. Output is currently + a portable document file. + date_publication: '2018-01-21' + bug_reports: https://github.com/louellette/LinkageMapView/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LinkageMapView + url_git: https://github.com/louellette/LinkageMapView +linkcomm: + version: 1.0-14 + title: |- + Tools for Generating, Visualizing, and Analysing Link + Communities in Networks + maintainer: Alex T. Kalinka + description: |- + Link communities reveal the nested and overlapping + structure in networks, and uncover the key nodes that form connections + to multiple communities. linkcomm provides a set of tools for + generating, visualizing, and analysing link communities in networks of + arbitrary size and type. The linkcomm package also includes tools for + generating, visualizing, and analysing Overlapping Cluster Generator + (OCG) communities. Kalinka and Tomancak (2011) . + date_publication: '2021-02-04' + bug_reports: '' + url: https://alextkalinka.github.io/linkcomm/ + url_cran: https://CRAN.R-project.org/package=linkcomm + url_git: https://github.com/alextkalinka/linkcomm +LinkedGASP: + version: '1.0' + title: Linked Emulator of a Coupled System of Simulators + maintainer: Ksenia N. Kyzyurova + description: 'Prototypes for construction of a Gaussian Stochastic Process emulator + (GASP) of a computer model. This is done within the objective Bayesian implementation + of the GASP. The package allows for construction of a linked GASP of the composite + computer model. Computational implementation follows the mathematical exposition + given in publication: Ksenia N. Kyzyurova, James O. Berger, Robert L. Wolpert. + Coupling computer models through linking their statistical emulators. SIAM/ASA + Journal on Uncertainty Quantification, 6(3): 1151-1171, (2018)..' + date_publication: '2018-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LinkedGASP + url_git: '' +linkedInadsR: + version: 0.1.0 + title: Access to 'LinkedIn' Ads via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect marketing data from 'LinkedIn' Ads using the 'Windsor.ai' + API . + date_publication: '2022-10-18' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=linkedInadsR + url_git: '' +LinkedMatrix: + version: 1.4.0 + title: Column-Linked and Row-Linked Matrices + maintainer: Alexander Grueneberg + description: |- + A class that links matrix-like objects (nodes) by rows or by + columns while behaving similarly to a base R matrix. Very large matrices + are supported if the nodes are file-backed matrices. + date_publication: '2020-05-22' + bug_reports: https://github.com/QuantGen/LinkedMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LinkedMatrix + url_git: https://github.com/QuantGen/LinkedMatrix +linkprediction: + version: 1.0-0 + title: Link Prediction Methods + maintainer: Michal Bojanowski + description: |- + Implementations of most of the existing proximity-based methods of + link prediction in graphs. Among the 20 implemented methods are e.g.: + Adamic L. and Adar E. (2003) , + Leicht E., Holme P., Newman M. (2006) , + Zhou T. and Zhang Y (2009) , and + Fouss F., Pirotte A., Renders J., and Saerens M. (2007) . + date_publication: '2018-10-19' + bug_reports: https://github.com/recon-icm/linkprediction/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linkprediction + url_git: https://github.com/recon-icm/linkprediction +linkspotter: + version: 1.3.0 + title: Bivariate Correlations Calculation and Visualization + maintainer: Alassane Samba + description: |- + Compute and visualize using the 'visNetwork' package all the bivariate correlations of a dataframe. + Several and different types of correlation coefficients (Pearson's r, Spearman's rho, Kendall's tau, + distance correlation, maximal information coefficient and + equal-freq discretization-based maximal normalized mutual information) are used according to + the variable couple type (quantitative vs categorical, quantitative vs quantitative, categorical vs categorical). + date_publication: '2020-07-23' + bug_reports: https://github.com/sambaala/linkspotter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linkspotter + url_git: https://github.com/sambaala/linkspotter +linl: + version: 0.0.5 + title: '''linl'' is not ''Letter''' + maintainer: Dirk Eddelbuettel + description: |- + A 'LaTeX' Letter class for 'rmarkdown', using the + 'pandoc-letter' template adapted for use with 'markdown'. + date_publication: '2023-01-12' + bug_reports: https://github.com/eddelbuettel/linl/issues + url: https://dirk.eddelbuettel.com/code/linl.html + url_cran: https://CRAN.R-project.org/package=linl + url_git: https://github.com/eddelbuettel/linl +linne: + version: 0.0.2 + title: Convenient 'CSS' + maintainer: John Coene + description: Conveniently generate 'CSS' using R code. + date_publication: '2020-10-26' + bug_reports: https://github.com/JohnCoene/linne/issues + url: https://linne.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=linne + url_git: '' +linpk: + version: 1.1.2 + title: Generate Concentration-Time Profiles from Linear PK Systems + maintainer: Benjamin Rich + description: |- + Generate concentration-time profiles from linear pharmacokinetic + (PK) systems, possibly with first-order absorption or zero-order infusion, + possibly with one or more peripheral compartments, and possibly under + steady-state conditions. Single or multiple doses may be specified. Secondary + (derived) PK parameters (e.g. Cmax, Ctrough, AUC, Tmax, half-life, etc.) are + computed. + date_publication: '2022-12-04' + bug_reports: https://github.com/benjaminrich/linpk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=linpk + url_git: https://github.com/benjaminrich/linpk +linprog: + version: 0.9-4 + title: Linear Programming / Optimization + maintainer: Arne Henningsen + description: |- + Can be used to solve Linear Programming / Linear + Optimization problems by using the simplex algorithm. + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=linprog + url_git: http://linprog.r-forge.r-project.org/ +LinRegInteractive: + version: 0.3-3 + title: Interactive Interpretation of Linear Regression Models + maintainer: Martin Meermeyer + description: |- + Interactive visualization of effects, response functions + and marginal effects for different kinds of regression models. In this version + linear regression models, generalized linear models, generalized additive + models and linear mixed-effects models are supported. + Major features are the interactive approach and the handling of the effects of categorical covariates: + if two or more factors are used as covariates every combination of the levels of each + factor is treated separately. The automatic calculation of + marginal effects and a number of possibilities to customize the graphical output + are useful features as well. + date_publication: '2020-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LinRegInteractive + url_git: '' +LINselect: + version: 1.1.5 + title: Selection of Linear Estimators + maintainer: Benjamin Auder + description: |- + Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators, + following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) . + In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso, + elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LINselect + url_git: '' +lintools: + version: 0.1.7 + title: Manipulation of Linear Systems of (in)Equalities + maintainer: Mark van der Loo + description: |- + Variable elimination (Gaussian elimination, Fourier-Motzkin elimination), + Moore-Penrose pseudoinverse, reduction to reduced row echelon form, value substitution, + projecting a vector on the convex polytope described by a system of (in)equations, + simplify systems by removing spurious columns and rows and collapse implied equalities, + test if a matrix is totally unimodular, compute variable ranges implied by linear + (in)equalities. + date_publication: '2023-01-16' + bug_reports: https://github.com/data-cleaning/lintools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lintools + url_git: https://github.com/data-cleaning/lintools +lintr: + version: 3.2.0 + title: A 'Linter' for R Code + maintainer: Michael Chirico + description: |- + Checks adherence to a given style, syntax errors and possible + semantic issues. Supports on the fly checking of R code edited with + 'RStudio IDE', 'Emacs', 'Vim', 'Sublime Text', 'Atom' and 'Visual + Studio Code'. + date_publication: '2025-02-12' + bug_reports: https://github.com/r-lib/lintr/issues + url: https://lintr.r-lib.org + url_cran: https://CRAN.R-project.org/package=lintr + url_git: https://github.com/r-lib/lintr +lipidmapsR: + version: 1.0.4 + title: Lipid Maps Rest Service + maintainer: Mingzhuo Tian + description: |- + Lipid Maps Rest service. Researchers can access the Lipid Maps Rest + service programmatically and conveniently integrate it into the current workflow + or packages. + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lipidmapsR + url_git: '' +LipidMS: + version: 3.0.5 + title: Lipid Annotation for LC-MS/MS DDA or DIA Data + maintainer: M Isabel Alcoriza-Balaguer + description: Lipid annotation in untargeted LC-MS lipidomics based on fragmentation + rules. Alcoriza-Balaguer MI, Garcia-Canaveras JC, Lopez A, Conde I, Juan O, Carretero + J, Lahoz A (2019) . + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LipidMS + url_git: '' +lipidomeR: + version: 0.1.2 + title: Integrative Visualizations of the Lipidome + maintainer: Tommi Suvitaival + description: |- + Create lipidome-wide heatmaps of statistics with the 'lipidomeR'. + The 'lipidomeR' provides a streamlined pipeline for the systematic + interpretation of the lipidome through publication-ready visualizations + of regression models fitted on lipidomics data. + With 'lipidomeR', associations between covariates and the lipidome + can be interpreted systematically and intuitively through heatmaps, where + lipids are categorized by the lipid class and are presented on + two-dimensional maps organized by the lipid size and level of saturation. + This way, the 'lipidomeR' helps you gain an immediate understanding of + the multivariate patterns in the lipidome already at first glance. + You can create lipidome-wide heatmaps of statistical associations, changes, + differences, variation, or other lipid-specific values. + The heatmaps are provided with publication-ready quality and the results + behind the visualizations are based on rigorous statistical models. + date_publication: '2020-03-15' + bug_reports: '' + url: https://tommi-s.github.io/ + url_cran: https://CRAN.R-project.org/package=lipidomeR + url_git: '' +LipidomicsR: + version: 0.3.6 + title: |- + Elegant Tools for Processing and Visualization of Lipidomics + Data + maintainer: Hengyu Zhu + description: An elegant tool for processing and visualizing lipidomics data generated + by mass spectrometry. 'LipidomicsR' simplifies channel and replicate handling + while providing thorough lipid species annotation. Its visualization capabilities + encompass principal components analysis plots, heatmaps, volcano plots, and radar + plots, enabling concise data summarization and quality assessment. Additionally, + it can generate bar plots and line plots to visualize the abundance of each lipid + species. + date_publication: '2024-04-22' + bug_reports: https://github.com/mingshi1/LipidomicsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LipidomicsR + url_git: https://github.com/mingshi1/LipidomicsR +LipinskiFilters: + version: 1.0.1 + title: Computes and Visualize Lipinski's Parameters + maintainer: Oche Ambrose George + description: This computes Lipinski Rule of Five parameters and offers visualization + for drug discovery. It analyzes molecular properties like molecular weight, hydrogen + bond donors, acceptors, and ALogP, providing histograms and pass/fail status plots + for efficient compound evaluation, aiding in drug development. + date_publication: '2024-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LipinskiFilters + url_git: '' +liqueueR: + version: 0.0.1 + title: Implements Queue, PriorityQueue and Stack Classes + maintainer: Andrew Collier + description: |- + Provides three classes: Queue, PriorityQueue and Stack. Queue is just a + "plain vanilla" FIFO queue; PriorityQueue orders items according to priority. Stack implements LIFO. + date_publication: '2016-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=liqueueR + url_git: https://github.com/DataWookie/liqueueR +lira: + version: 2.0.1 + title: LInear Regression in Astronomy + maintainer: Mauro Sereno + description: Performs Bayesian linear regression and forecasting in astronomy. The + method accounts for heteroscedastic errors in both the independent and the dependent + variables, intrinsic scatters (in both variables) and scatter correlation, time + evolution of slopes, normalization, scatters, Malmquist and Eddington bias, upper + limits and break of linearity. The posterior distribution of the regression parameters + is sampled with a Gibbs method exploiting the JAGS library. + date_publication: '2018-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lira + url_git: '' +lisa: + version: 0.1.2 + title: Color Palettes from Color Lisa + maintainer: Tyler Littlefield + description: |- + Contains 128 palettes from Color Lisa. All palettes are based on + masterpieces from the worlds greatest artists. For more information, see + . + date_publication: '2020-09-20' + bug_reports: https://github.com/tyluRp/lisa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lisa + url_git: https://github.com/tyluRp/lisa +lisrelToR: + version: '0.3' + title: Import Output from LISREL into R + maintainer: Sacha Epskamp + description: |- + This is an unofficial package aimed at automating the import of LISREL output in R. + This package or its maintainer is not in any way affiliated with the creators of LISREL and SSI, Inc. + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lisrelToR + url_git: '' +list: + version: 9.2.6 + title: |- + Statistical Methods for the Item Count Technique and List + Experiment + maintainer: Graeme Blair + description: |- + Allows researchers to conduct multivariate + statistical analyses of survey data with list experiments. This + survey methodology is also known as the item count technique or + the unmatched count technique and is an alternative to the commonly + used randomized response method. The package implements the methods + developed by Imai (2011) , + Blair and Imai (2012) , + Blair, Imai, and Lyall (2013) , + Imai, Park, and Greene (2014) , + Aronow, Coppock, Crawford, and Green (2015) , + Chou, Imai, and Rosenfeld (2017) , and + Blair, Chou, and Imai (2018) . + This includes a Bayesian MCMC implementation of regression for the + standard and multiple sensitive item list experiment designs and a + random effects setup, a Bayesian MCMC hierarchical regression model + with up to three hierarchical groups, the combined list experiment + and endorsement experiment regression model, a joint model of the + list experiment that enables the analysis of the list experiment as + a predictor in outcome regression models, a method for combining + list experiments with direct questions, and methods for diagnosing and + adjusting for response error. In addition, the package implements the + statistical test that is designed to detect certain failures of list + experiments, and a placebo test for the list experiment using data from + direct questions. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=list + url_git: '' +listArray: + version: 0.1.1 + title: Incomplete Array with Arbitrary R Objects as Indices + maintainer: Sigbert Klinke + description: The aim of the package is to create data objects which allow for accesses + like x["test"] and x["test","test"]. + date_publication: '2020-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=listArray + url_git: '' +listarrays: + version: 0.4.0 + title: |- + A Toolbox for Working with R Arrays in a Functional Programming + Style + maintainer: Tomasz Kalinowski + description: |- + A toolbox for R arrays. Flexibly split, bind, reshape, modify, + subset and name arrays. + date_publication: '2024-04-19' + bug_reports: https://github.com/t-kalinowski/listarrays/issues + url: https://t-kalinowski.github.io/listarrays/ + url_cran: https://CRAN.R-project.org/package=listarrays + url_git: https://github.com/t-kalinowski/listarrays +listcomp: + version: 0.4.1 + title: List Comprehensions + maintainer: Dirk Schumacher + description: |- + An implementation of list comprehensions as purely syntactic + sugar with a minor runtime overhead. It constructs nested for-loops and + executes the byte-compiled loops to collect the results. + date_publication: '2022-01-31' + bug_reports: https://github.com/dirkschumacher/listcomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=listcomp + url_git: https://github.com/dirkschumacher/listcomp +listcompr: + version: 0.4.0 + title: List Comprehension for R + maintainer: Patrick Roocks + description: |- + Syntactic shortcuts for creating synthetic lists, vectors, + data frames, and matrices using list comprehension. + date_publication: '2021-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=listcompr + url_git: https://github.com/patrickroocks/listcompr +listdown: + version: 0.5.7 + title: Create R Markdown from Lists + maintainer: Michael J. Kane + description: Programmatically create R Markdown documents from lists. + date_publication: '2023-04-03' + bug_reports: https://github.com/kaneplusplus/listdown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=listdown + url_git: https://github.com/kaneplusplus/listdown +listenv: + version: 0.9.1 + title: Environments Behaving (Almost) as Lists + maintainer: Henrik Bengtsson + description: List environments are environments that have list-like properties. For + instance, the elements of a list environment are ordered and can be accessed and + iterated over using index subsetting, e.g. 'x <- listenv(a = 1, b = 2); for (i + in seq_along(x)) x[[i]] <- x[[i]] ^ 2; y <- as.list(x)'. + date_publication: '2024-01-29' + bug_reports: https://github.com/HenrikBengtsson/listenv/issues + url: https://listenv.futureverse.org + url_cran: https://CRAN.R-project.org/package=listenv + url_git: https://github.com/HenrikBengtsson/listenv +LIStest: + version: '2.1' + title: |- + Tests of independence based on the Longest Increasing + Subsequence + maintainer: J. E. Garcia + description: Tests for independence between X and Y computed from a paired sample + (x1,y1),...(xn,yn) of (X,Y), using one of the following statistics (a) the Longest + Increasing Subsequence (Ln), (b) JLn, a Jackknife version of Ln or (c) JLMn, a + Jackknife version of the longest monotonic subsequence. This family of tests can + be applied under the assumption of continuity of X and Y. + date_publication: '2014-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LIStest + url_git: '' +listr: + version: 0.1.0 + title: Tools for Lists + maintainer: Christian Hohenfeld + description: |- + Tools for common operations on lists. Provided are short-cuts to + operations like selecting and merging data stored in lists. The functions in + this package are designed to be used with pipes. + date_publication: '2022-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=listr + url_git: '' +listviewer: + version: 4.0.0 + title: '''htmlwidget'' for Interactive Views of R Lists' + maintainer: Kent Russell + description: |- + R lists, especially nested lists, can be very difficult to + visualize or represent. Sometimes 'str()' is not enough, so this suite of + htmlwidgets is designed to help see, understand, and maybe even modify your R + lists. The function 'reactjson()' requires a package + 'reactR' that can be installed from CRAN or . + date_publication: '2023-09-30' + bug_reports: https://github.com/timelyportfolio/listviewer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=listviewer + url_git: https://github.com/timelyportfolio/listviewer +listWithDefaults: + version: 1.2.0 + title: List with Defaults + maintainer: Russell S. Pierce + description: |- + Provides a function that, as an alternative to base::list, allows + default values to be inherited from another list. + date_publication: '2017-06-08' + bug_reports: https://github.com/drknexus/listWithDefaults + url: '' + url_cran: https://CRAN.R-project.org/package=listWithDefaults + url_git: https://github.com/drknexus/listWithDefaults +lit: + version: 1.0.0 + title: Latent Interaction Testing for Genome-Wide Studies + maintainer: Andrew Bass + description: |- + Identifying latent genetic interactions in genome-wide association studies + using the Latent Interaction Testing (LIT) framework. + LIT is a flexible kernel-based approach that leverages information across + multiple traits to detect latent genetic interactions without specifying or + observing the interacting variable (e.g., environment). LIT accepts + standard PLINK files as inputs to analyze large genome-wide association studies. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lit + url_git: https://github.com/ajbass/lit +lite: + version: 1.1.1 + title: Likelihood-Based Inference for Time Series Extremes + maintainer: Paul J. Northrop + description: |- + Performs likelihood-based inference for stationary time series + extremes. The general approach follows Fawcett and Walshaw (2012) + . Marginal extreme value inferences are adjusted for + cluster dependence in the data using the methodology in Chandler and Bate + (2007) , producing an adjusted log-likelihood + for the model parameters. A log-likelihood for the extremal index is + produced using the K-gaps model of Suveges and Davison (2010) + . These log-likelihoods are combined to make + inferences about extreme values. Both maximum likelihood and Bayesian + approaches are available. + date_publication: '2024-07-17' + bug_reports: https://github.com/paulnorthrop/lite/issues + url: https://paulnorthrop.github.io/lite/ + url_cran: https://CRAN.R-project.org/package=lite + url_git: https://github.com/paulnorthrop/lite +litedown: + version: '0.6' + title: A Lightweight Version of R Markdown + maintainer: Yihui Xie + description: |- + Render R Markdown to Markdown (without using 'knitr'), and Markdown + to lightweight HTML or 'LaTeX' documents with the 'commonmark' package (instead + of 'Pandoc'). Some missing Markdown features in 'commonmark' are also + supported, such as raw HTML or 'LaTeX' blocks, 'LaTeX' math, superscripts, + subscripts, footnotes, element attributes, and appendices, + but not all 'Pandoc' Markdown features are (or will be) supported. With + additional JavaScript and CSS, you can also create HTML slides and articles. + This package can be viewed as a trimmed-down version of R Markdown and + 'knitr'. It does not aim at rich Markdown features or a large variety of + output formats (the primary formats are HTML and 'LaTeX'). Book and website + projects of multiple input documents are also supported. + date_publication: '2025-02-27' + bug_reports: https://github.com/yihui/litedown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=litedown + url_git: https://github.com/yihui/litedown +liteq: + version: 1.1.0 + title: Lightweight Portable Message Queue Using 'SQLite' + maintainer: Gábor Csárdi + description: |- + Temporary and permanent message queues for R. Built on top of + 'SQLite' databases. 'SQLite' provides locking, and makes it possible + to detect crashed consumers. Crashed jobs can be automatically marked + as "failed", or put in the queue again, potentially a limited number of times. + date_publication: '2019-03-08' + bug_reports: https://github.com/r-lib/liteq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=liteq + url_git: https://github.com/r-lib/liteq#readme +literanger: + version: 0.1.1 + title: Random Forests for Multiple Imputation Based on 'ranger' + maintainer: Stephen Wade + description: |- + An updated implementation of R package 'ranger' by Wright et al, + (2017) for training and predicting from random + forests, particularly suited to high-dimensional data, and for embedding in + 'Multiple Imputation by Chained Equations' (MICE) by van Buuren (2007) + . Ensembles of classification and regression + trees are currently supported. Sparse data of class 'dgCMatrix' (R package + 'Matrix') can be directly analyzed. Conventional bagged predictions are + available alongside an efficient prediction for MICE via the algorithm + proposed by Doove et al (2014) . Survival + and probability forests are not supported in the update, nor is data of + class 'gwaa.data' (R package 'GenABEL'); use the original 'ranger' package + for these analyses. + date_publication: '2024-09-22' + bug_reports: https://gitlab.com/stephematician/literanger/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=literanger + url_git: https://gitlab.com/stephematician/literanger +litRiddle: + version: 1.0.0 + title: Dataset and Tools to Research the Riddle of Literary Quality + maintainer: Maciej Eder + description: 'Dataset and functions to explore quality of literary novels. The package + is a part of the Riddle of Literary Quality project, and it contains the data + of a reader survey about fiction in Dutch, a description of the novels the readers + rated, and the results of stylistic measurements of the novels. The package also + contains functions to combine, analyze, and visualize these data. For more details, + see: Eder M, van Zundert J, Lensink S, van Dalen-Oskam K (2022). Replicating The + Riddle of Literary Quality: The litRiddle package for R. In _Digital Humanities + 2022: Conference Abstracts_, 636-637.' + date_publication: '2023-07-19' + bug_reports: '' + url: https://literaryquality.huygens.knaw.nl/ + url_cran: https://CRAN.R-project.org/package=litRiddle + url_git: '' +litteR: + version: 1.0.0 + title: Litter Analysis + maintainer: Dennis Walvoort + description: |- + Data sets on various litter types like beach litter, riverain + litter, floating litter, and seafloor litter are rapidly growing. This + package offers a simple user interface to analyse these litter data in + a consistent and reproducible way. It also provides functions to + facilitate several kinds of litter analysis, e.g., trend analysis, + power analysis, and baseline analysis. Under the hood, these functions + are also used by the user interface. See Schulz et al. (2019) + for details. MS-Windows users are + advised to run 'litteR' in 'RStudio'. See our vignette: Installation manual + for 'RStudio' and 'litteR'. + date_publication: '2022-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=litteR + url_git: '' +litterfitter: + version: 0.1.3 + title: Fit a Collection of Curves to Single Cohort Decomposition Data + maintainer: Will Cornwell + description: There is a long tradition of studying the flux of carbon from the biosphere + to the atmosphere by following a particular cohort of litter (wood, leaves, roots, + or other organic material) through time. The resulting data are mass remaining + and time. A variety of functional forms may be used to fit the resulting data. + Some work better empirically. Some are better connected to a process-based understanding. Some + have a small number of free parameters; others have more. This package matches + decomposition data to a family of these curves using likelihood--based fitting. + This package is based on published research by Cornwell & Weedon (2013) . + date_publication: '2023-08-29' + bug_reports: https://github.com/traitecoevo/litterfitter/issues + url: http://traitecoevo.github.io/litterfitter/ + url_cran: https://CRAN.R-project.org/package=litterfitter + url_git: https://github.com/traitecoevo/litterfitter/issues +littler: + version: 0.3.20 + title: R at the Command-Line via 'r' + maintainer: Dirk Eddelbuettel + description: |- + A scripting and command-line front-end + is provided by 'r' (aka 'littler') as a lightweight binary wrapper around + the GNU R language and environment for statistical computing and graphics. + While R can be used in batch mode, the r binary adds full support for + both 'shebang'-style scripting (i.e. using a hash-mark-exclamation-path + expression as the first line in scripts) as well as command-line use in + standard Unix pipelines. In other words, r provides the R language without + the environment. + date_publication: '2024-03-23' + bug_reports: https://github.com/eddelbuettel/littler/issues + url: https://dirk.eddelbuettel.com/code/littler.html + url_cran: https://CRAN.R-project.org/package=littler + url_git: https://github.com/eddelbuettel/littler +liureg: + version: 1.1.2 + title: Liu Regression with Liu Biasing Parameters and Statistics + maintainer: Imdad Ullah Muhammad + description: |- + Linear Liu regression coefficient's estimation and testing with different Liu related measures such as MSE, R-squared etc. + REFERENCES + i. Akdeniz and Kaciranlar (1995) + ii. Druilhet and Mom (2008) + iii. Imdadullah, Aslam, and Saima (2017) + iv. Liu (1993) + v. Liu (2001) . + date_publication: '2018-04-08' + bug_reports: http://rfaqs.com/contact + url: '' + url_cran: https://CRAN.R-project.org/package=liureg + url_git: '' +live: + version: 1.5.13 + title: Local Interpretable (Model-Agnostic) Visual Explanations + maintainer: Mateusz Staniak + description: |- + Interpretability of complex machine learning models is a growing concern. + This package helps to understand key factors that drive the + decision made by complicated predictive model (so called black box model). + This is achieved through local approximations that are either based on + additive regression like model or CART like model that allows for + higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) . + More details can be found in Staniak, Biecek (2018) . + date_publication: '2020-01-15' + bug_reports: https://github.com/ModelOriented/live/issues + url: '' + url_cran: https://CRAN.R-project.org/package=live + url_git: https://github.com/ModelOriented/live +liver: + version: '1.18' + title: '"Eating the Liver of Data Science"' + maintainer: Reza Mohammadi + description: Offers a suite of helper functions to simplify various data science + techniques for non-experts. This package aims to enable individuals with only + a minimal level of coding knowledge to become acquainted with these techniques + in an accessible manner. Inspired by an ancient Persian idiom, we liken this process + to "eating the liver of data science," suggesting a deep and intimate engagement + with the field of data science. This package includes functions for tasks such + as data partitioning for out-of-sample testing, calculating Mean Squared Error + (MSE) to assess prediction accuracy, and data transformations (z-score and min-max). + In addition to these helper functions, the 'liver' package also features several + intriguing datasets valuable for multivariate analysis. + date_publication: '2024-11-22' + bug_reports: '' + url: https://www.uva.nl/profile/a.mohammadi + url_cran: https://CRAN.R-project.org/package=liver + url_git: '' +ljr: + version: 1.4-0 + title: Logistic Joinpoint Regression + maintainer: Ryan Gill + description: Fits and tests logistic joinpoint models. + date_publication: '2016-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ljr + url_git: '' +LKT: + version: 1.7.0 + title: Logistic Knowledge Tracing + maintainer: Philip I. Pavlik Jr. + description: Computes Logistic Knowledge Tracing ('LKT') which is a general method + for tracking human learning in an educational software system. Please see Pavlik, + Eglington, and Harrel-Williams (2021) . + 'LKT' is a method to compute features of student data that are used as predictors + of subsequent performance. 'LKT' allows great flexibility in the choice of predictive + components and features computed for these predictive components. The system is + built on top of 'LiblineaR', which enables extremely fast solutions compared to + base glm() in R. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LKT + url_git: '' +llama: + version: 0.10.1 + title: Leveraging Learning to Automatically Manage Algorithms + maintainer: Lars Kotthoff + description: Provides functionality to train and evaluate algorithm selection models + for portfolios. + date_publication: '2021-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=llama + url_git: https://bitbucket.org/lkotthoff/llama +llbayesireg: + version: 1.0.0 + title: The L-Logistic Bayesian Regression + maintainer: Rosineide Fernando da Paz + description: 'R functions and data sets for the work Paz, R.F., Balakrishnan, N + and Bazán, J.L. (2018). L-logistic regression models: Prior sensitivity analysis, + robustness to outliers and applications. Brazilian Journal of Probability and + Statistics, .' + date_publication: '2019-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=llbayesireg + url_git: '' +LLIC: + version: 3.0.0 + title: Likelihood Criterion (LIC) Analysis for Laplace Regression Model + maintainer: Guangbao Guo + description: Performs likelihood criterion analysis using the Laplace regression + model to determine its optimal subset of variables. The methodology is based on + Guo et al. (2023), LIC criterion for optimal subset selection in distributed interval + estimation . + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LLIC + url_git: '' +LLM: + version: 1.1.0 + title: Logit Leaf Model Classifier for Binary Classification + maintainer: Arno De Caigny + description: Fits the Logit Leaf Model, makes predictions and visualizes the output. + (De Caigny et al., (2018) ). + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LLM + url_git: '' +LLMR: + version: 0.2.1 + title: Interface for Large Language Model APIs in R + maintainer: Ali Sanaei + description: A unified interface to interact with various Large Language Model (LLM) + APIs such as 'OpenAI' (see for details), + 'Anthropic' (see for details), + 'Groq' (see for details), 'Together + AI' (see for details), 'DeepSeek' (see + for details), 'Gemini' (see + for details), and 'Voyage AI' (see + for details). Allows users to configure API parameters, send messages, and retrieve + responses seamlessly within R. + date_publication: '2025-02-11' + bug_reports: https://github.com/asanaei/LLMR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LLMR + url_git: https://github.com/asanaei/LLMR +llogistic: + version: 1.0.3 + title: The L-Logistic Distribution + maintainer: Rosineide Fernando da Paz + description: Density, distribution function, quantile function and random generation + for the L-Logistic distribution with parameters m and phi. The parameter m is + the median of the distribution. + date_publication: '2019-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=llogistic + url_git: '' +LLSR: + version: 0.0.3.1 + title: Data Analysis of Liquid-Liquid Systems using R + maintainer: Diego F Coelho + description: Originally design to characterise Aqueous Two Phase Systems, LLSR provide + a simple way to analyse experimental data and obtain phase diagram parameters, + among other properties, systematically. The package will include (every other + update) new functions in order to comprise useful tools in liquid-liquid extraction + research. + date_publication: '2021-02-17' + bug_reports: https://github.com/diegofcoelho/LLSR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LLSR + url_git: '' +lm.beta: + version: 1.7-2 + title: Add Standardized Regression Coefficients to Linear-Model-Objects + maintainer: Stefan Behrendt + description: Adds standardized regression coefficients to objects created by 'lm'. + Also extends the S3 methods 'print', 'summary' and 'coef' with additional boolean + argument 'standardized' and provides 'xtable'-support. + date_publication: '2023-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lm.beta + url_git: '' +lm.br: + version: 2.9.8 + title: Linear Model with Breakpoint + maintainer: Marc Adams + description: |- + Exact significance tests for a changepoint in linear or multiple linear regression. + Confidence regions with exact coverage probabilities for the changepoint. Based on + Knowles, Siegmund and Zhang (1991) . + date_publication: '2024-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lm.br + url_git: '' +lmap: + version: 0.2.4 + title: Logistic Mapping + maintainer: Mark de Rooij + description: Set of tools for mapping of categorical response variables based on + principal component analysis (pca) and multidimensional unfolding (mdu). + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmap + url_git: '' +lmboot: + version: 0.0.1 + title: Bootstrap in Linear Models + maintainer: Megan Heyman + description: |- + Various efficient and robust bootstrap methods are implemented for + linear models with least squares estimation. Functions within this package + allow users to create bootstrap sampling distributions for model parameters, + test hypotheses about parameters, and visualize the bootstrap sampling or null + distributions. Methods implemented for linear models include the wild bootstrap by + Wu (1986) , the residual and paired bootstraps by + Efron (1979, ISBN:978-1-4612-4380-9), the delete-1 jackknife by + Quenouille (1956) , and the Bayesian bootstrap by + Rubin (1981) . + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmboot + url_git: '' +LMD: + version: 1.0.0 + title: A Self-Adaptive Approach for Demodulating Multi-Component Signal + maintainer: Shubhra Prakash + description: Local Mean Decomposition is an iterative and self-adaptive approach + for demodulating, processing, and analyzing multi-component amplitude modulated + and frequency modulated signals. This R package is based on the approach suggested + by Smith (2005) and the 'Python' library 'PyLMD'. + date_publication: '2022-09-20' + bug_reports: https://github.com/shubhra-opensource/LMD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LMD + url_git: https://github.com/shubhra-opensource/LMD +lmDiallel: + version: 1.0.1 + title: Linear Fixed/Mixed Effects Models for Diallel Crosses + maintainer: Andrea Onofri + description: Several service functions to be used to analyse datasets obtained from + diallel experiments within the frame of linear models in R, as described in Onofri + et al (2020) . + date_publication: '2023-04-19' + bug_reports: '' + url: https://www.statforbiology.com/lmDiallel/ + url_cran: https://CRAN.R-project.org/package=lmDiallel + url_git: '' +lmds: + version: 0.1.0 + title: Landmark Multi-Dimensional Scaling + maintainer: Robrecht Cannoodt + description: |2- + + A fast dimensionality reduction method scaleable to large numbers of samples. + Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, + but rather than calculating a complete distance matrix between all pairs of samples, + only the distances between a set of landmarks and the samples are calculated. + date_publication: '2019-09-27' + bug_reports: https://github.com/dynverse/lmds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lmds + url_git: http://github.com/dynverse/lmds +lme4: + version: 1.1-36 + title: Linear Mixed-Effects Models using 'Eigen' and S4 + maintainer: Ben Bolker + description: |- + Fit linear and generalized linear mixed-effects models. + The models and their components are represented using S4 classes and + methods. The core computational algorithms are implemented using the + 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue". + date_publication: '2025-01-11' + bug_reports: https://github.com/lme4/lme4/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lme4 + url_git: https://github.com/lme4/lme4/ +lme4breeding: + version: 1.0.50 + title: Relationship-Based Mixed-Effects Models + maintainer: Giovanny Covarrubias-Pazaran + description: |- + Fit relationship-based and customized mixed-effects models with complex variance-covariance structures using the 'lme4' machinery. The core computational algorithms are implemented using the + 'Eigen' 'C++' library for numerical linear algebra and 'RcppEigen' 'glue'. + date_publication: '2025-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lme4breeding + url_git: '' +lmeInfo: + version: 0.3.2 + title: Information Matrices for 'lmeStruct' and 'glsStruct' Objects + maintainer: Man Chen + description: |- + Provides analytic derivatives and information matrices for + fitted linear mixed effects (lme) models and generalized least squares (gls) models + estimated using lme() (from package 'nlme') and gls() (from package 'nlme'), respectively. + The package includes functions for estimating the sampling variance-covariance of variance + component parameters using the inverse Fisher information. The variance components include + the parameters of the random effects structure (for lme models), the variance structure, + and the correlation structure. The expected and average forms of the Fisher information matrix + are used in the calculations, and models estimated by full maximum likelihood or + restricted maximum likelihood are supported. The package also includes a function for estimating + standardized mean difference effect sizes (Pustejovsky, Hedges, and Shadish (2014) ) + based on fitted lme or gls models. + date_publication: '2023-04-17' + bug_reports: https://github.com/jepusto/lmeInfo/issues + url: https://jepusto.github.io/lmeInfo/ + url_cran: https://CRAN.R-project.org/package=lmeInfo + url_git: '' +LMERConvenienceFunctions: + version: '3.0' + title: Model Selection and Post-Hoc Analysis for (G)LMER Models + maintainer: '"Antoine Tremblay, Statistics Canada"' + description: The main function of the package is to perform backward selection of + fixed effects, forward fitting of the random effects, and post-hoc analysis using + parallel capabilities. Other functionality includes the computation of ANOVAs + with upper- or lower-bound p-values and R-squared values for each model term, + model criticism plots, data trimming on model residuals, and data visualization. + The data to run examples is contained in package LCF_data. + date_publication: '2020-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LMERConvenienceFunctions + url_git: '' +lmeresampler: + version: 0.2.4 + title: Bootstrap Methods for Nested Linear Mixed-Effects Models + maintainer: Adam Loy + description: |- + Bootstrap routines for nested linear mixed effects models fit using + either 'lme4' or 'nlme'. The provided 'bootstrap()' function implements the + parametric, residual, cases, random effect block (REB), and wild bootstrap + procedures. An overview of these procedures can be found + in Van der Leeden et al. (2008) , + Carpenter, Goldstein & Rasbash (2003) , + and Chambers & Chandra (2013) . + date_publication: '2023-02-11' + bug_reports: https://github.com/aloy/lmeresampler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lmeresampler + url_git: https://github.com/aloy/lmeresampler +lmerPerm: + version: 0.1.9 + title: |- + Perform Permutation Test on General Linear and Mixed Linear + Regression + maintainer: Wentao Zeng + description: |- + We provide a solution for performing permutation tests on linear and mixed linear regression models. It + allows users to obtain accurate p-values without making distributional assumptions about the data. By + generating a null distribution of the test statistics through repeated permutations of the response variable, + permutation tests provide a powerful alternative to traditional parameter tests (Holt et al. (2023) + ). In this early version, we focus on the permutation tests over observed + t values of beta coefficients, i.e.original t values generated by parameter tests. After generating a null + distribution of the test statistic through repeated permutations of the response variable, each observed t + values would be compared to the null distribution to generate a p-value. To improve the efficiency,a stop + criterion (Anscombe (1953) ) is adopted to force permutation to stop + if the estimated standard deviation of the value falls below a fraction of the estimated p-value. By doing so, + we avoid the need for massive calculations in exact permutation methods while still generating stable and accurate + p-values. + date_publication: '2023-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmerPerm + url_git: '' +lmerTest: + version: 3.1-3 + title: Tests in Linear Mixed Effects Models + maintainer: Rune Haubo Bojesen Christensen + description: |- + Provides p-values in type I, II or III anova and summary tables + for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A + Kenward-Roger method is also available via the pbkrtest package. Model selection + methods include step, drop1 and anova-like tables for random effects (ranova). + Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed + effects are also available. + date_publication: '2020-10-23' + bug_reports: https://github.com/runehaubo/lmerTestR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lmerTest + url_git: https://github.com/runehaubo/lmerTestR +lmeSplines: + version: 1.1-12 + title: Add Smoothing Spline Modelling Capability to `nlme` + maintainer: Andrzej Galecki + description: |- + Adds smoothing spline modelling capability to nlme. Fits + smoothing spline terms in Gaussian linear and nonlinear + mixed-effects models. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmeSplines + url_git: '' +LMest: + version: 3.2.5 + title: Generalized Latent Markov Models + maintainer: Francesco Bartolucci + description: Latent Markov models for longitudinal continuous and categorical data. + See Bartolucci, Pandolfi, Pennoni (2017). + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LMest + url_git: '' +lmf: + version: 1.2.1 + title: |- + Functions for Estimation and Inference of Selection in + Age-Structured Populations + maintainer: Thomas Kvalnes + description: |- + Provides methods for estimation and statistical + inference on directional and fluctuating selection in age-structured + populations. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmf + url_git: '' +LMfilteR: + version: 0.1.3.1 + title: |- + Filter Methods for Parameter Estimation in Linear and Non Linear + Regression Models + maintainer: Christian Llano Robayo + description: 'We present a method based on filtering algorithms to estimate the + parameters of linear, i.e. the coefficients and the variance of the error term. + The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, + S., Gordon, N. (2004, ISBN: 158053631X) resampling methods. Parameters of logistic + regression models are also estimated using an evolutionary particle filter method.' + date_publication: '2023-02-02' + bug_reports: https://github.com/ChrissCod/LMfilteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LMfilteR + url_git: '' +lmfor: + version: '1.6' + title: Functions for Forest Biometrics + maintainer: Lauri Mehtatalo + description: Functions for different purposes related to forest biometrics, including + illustrative graphics, numerical computation, modeling height-diameter relationships, + prediction of tree volumes, modelling of diameter distributions and estimation + off stand density using ITD. Several empirical datasets are also included. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmfor + url_git: '' +lmForc: + version: 1.0.0 + title: Linear Model Forecasting + maintainer: Nelson Rayl + description: |- + Introduces in-sample, out-of-sample, pseudo out-of-sample, and + benchmark model forecast tests and a new class for working with forecast data, Forecast. + date_publication: '2024-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmForc + url_git: '' +lmhelprs: + version: 0.4.0 + title: Helper Functions for Linear Model Analysis + maintainer: Shu Fai Cheung + description: |- + A collection of helper functions for multiple + regression models fitted by lm(). Most of them are simple + functions for simple tasks which can be done with coding, + but may not be easy for occasional users of R. Most of + the tasks addressed are those sometimes needed when + using the 'manymome' package (Cheung and Cheung, 2023, + ) and 'stdmod' package + (Cheung, Cheung, Lau, Hui, and Vong, 2022, + ). However, they can also be used + in other scenarios. + date_publication: '2024-10-15' + bug_reports: https://github.com/sfcheung/lmhelprs/issues + url: https://sfcheung.github.io/lmhelprs/ + url_cran: https://CRAN.R-project.org/package=lmhelprs + url_git: '' +lmls: + version: 0.1.1 + title: Gaussian Location-Scale Regression + maintainer: Hannes Riebl + description: |- + The Gaussian location-scale regression model is a multi-predictor + model with explanatory variables for the mean (= location) and the standard + deviation (= scale) of a response variable. This package implements maximum + likelihood and Markov chain Monte Carlo (MCMC) inference (using algorithms + from Girolami and Calderhead (2011) + and Nesterov (2009) ), a parametric + bootstrap algorithm, and diagnostic plots for the model class. + date_publication: '2024-11-20' + bug_reports: https://github.com/hriebl/lmls/issues + url: https://hriebl.github.io/lmls/ + url_cran: https://CRAN.R-project.org/package=lmls + url_git: https://github.com/hriebl/lmls +lmm: + version: '1.4' + title: Linear Mixed Models + maintainer: Jing hua Zhao + description: |- + It implements Expectation/Conditional Maximization Either (ECME) + and rapidly converging algorithms as well as + Bayesian inference for linear mixed models, + which is described in Schafer, J.L. (1998) + "Some improved procedures for linear mixed models". + Dept. of Statistics, The Pennsylvania State University. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmm + url_git: https://github.com/jinghuazhao/R +LMMELSM: + version: 0.2.0 + title: Fit Latent Multivariate Mixed Effects Location Scale Models + maintainer: Stephen Martin + description: In addition to modeling the expectation (location) of an outcome, mixed + effects location scale models (MELSMs) include submodels on the variance components + (scales) directly. This allows models on the within-group variance with mixed + effects, and between-group variances with fixed effects. The MELSM can be used + to model volatility, intraindividual variance, uncertainty, measurement error + variance, and more. Multivariate MELSMs (MMELSMs) extend the model to include + multiple correlated outcomes, and therefore multiple locations and scales. The + latent multivariate MELSM (LMMELSM) further includes multiple correlated latent + variables as outcomes. This package implements two-level mixed effects location + scale models on multiple observed or latent outcomes, and between-group variance + modeling. Williams, Martin, Liu, and Rast (2020) . + Hedeker, Mermelstein, and Demirtas (2008) . + date_publication: '2022-12-15' + bug_reports: https://github.com/stephenSRMMartin/LMMELSM + url: '' + url_cran: https://CRAN.R-project.org/package=LMMELSM + url_git: '' +lmmot: + version: 0.1.4 + title: Multiple Ordinal Tobit (MOT) Model + maintainer: Marvin N. Wright + description: Fit right censored Multiple Ordinal Tobit (MOT) model. + date_publication: '2017-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmmot + url_git: '' +lmmpar: + version: 0.1.0 + title: Parallel Linear Mixed Model + maintainer: Fulya Gokalp Yavuz + description: Embarrassingly Parallel Linear Mixed Model calculations spread across + local cores which repeat until convergence. + date_publication: '2017-08-03' + bug_reports: https://github.com/fulyagokalp/lmmpar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lmmpar + url_git: https://github.com/fulyagokalp/lmmpar +LMMsolver: + version: 1.0.9 + title: Linear Mixed Model Solver + maintainer: Bart-Jan van Rossum + description: |- + An efficient and flexible system to solve sparse mixed model + equations. Important applications are the use of splines to model spatial or temporal + trends as described in Boer (2023). (). + date_publication: '2025-01-14' + bug_reports: https://github.com/Biometris/LMMsolver/issues + url: https://biometris.github.io/LMMsolver/index.html + url_cran: https://CRAN.R-project.org/package=LMMsolver + url_git: https://github.com/Biometris/LMMsolver/ +LMMstar: + version: 1.1.0 + title: Repeated Measurement Models for Discrete Times + maintainer: Brice Ozenne + description: |- + Companion R package for the course "Statistical analysis of correlated and repeated measurements for health science researchers" + taught by the section of Biostatistics of the University of Copenhagen. + It implements linear mixed models where the model for the variance-covariance of the residuals is specified via patterns (compound symmetry, toeplitz, unstructured, ...). + Statistical inference for mean, variance, and correlation parameters is performed based on the observed information and a Satterthwaite approximation of the degrees of freedom. + Normalized residuals are provided to assess model misspecification. + Statistical inference can be performed for arbitrary linear or non-linear combination(s) of model coefficients. + Predictions can be computed conditional to covariates only or also to outcome values. + date_publication: '2024-05-12' + bug_reports: https://github.com/bozenne/LMMstar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LMMstar + url_git: https://github.com/bozenne/LMMstar +LMN: + version: 1.1.3 + title: Inference for Linear Models with Nuisance Parameters + maintainer: Martin Lysy + description: Efficient Frequentist profiling and Bayesian marginalization of parameters + for which the conditional likelihood is that of a multivariate linear regression + model. Arbitrary inter-observation error correlations are supported, with optimized + calculations provided for independent-heteroskedastic and stationary dependence + structures. + date_publication: '2022-08-22' + bug_reports: https://github.com/mlysy/LMN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LMN + url_git: https://github.com/mlysy/LMN +lmodel2: + version: 1.7-4 + title: Model II Regression + maintainer: Jari Oksanen + description: |- + Computes model II simple linear regression using ordinary + least squares (OLS), major axis (MA), standard major axis (SMA), and + ranged major axis (RMA). + date_publication: '2024-12-05' + bug_reports: https://github.com/vegandevs/lmodel2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lmodel2 + url_git: '' +LMoFit: + version: 0.1.7 + title: Advanced L-Moment Fitting of Distributions + maintainer: Mohanad Zaghloul + description: A complete framework for frequency analysis is provided by 'LMoFit'. + It has functions related to the determination of sample L-moments as in Hosking, + J.R.M. (1990) , the fitting of various + distributions as in Zaghloul et al. (2020) + and Hosking, J.R.M. (2019) , besides + plotting and manipulating L-space diagrams as in Papalexiou, S.M. & Koutsoyiannis, + D. (2016) for two-shape parametric distributions + on the L-moment ratio diagram. Additionally, the quantile, probability density, + and cumulative probability functions of various distributions are provided in + a user-friendly manner. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LMoFit + url_git: '' +lmom: + version: '3.2' + title: L-Moments + maintainer: J. R. M. Hosking + description: |- + Functions related to L-moments: computation of L-moments + and trimmed L-moments of distributions and data samples; parameter + estimation; L-moment ratio diagram; plot vs. quantiles of an + extreme-value distribution. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmom + url_git: '' +lmomco: + version: 2.5.1 + title: |- + L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, + and Many Distributions + maintainer: William Asquith + description: |- + Extensive functions for Lmoments (LMs) and probability-weighted moments (PWMs), + distribution parameter estimation, LMs for distributions, LM ratio diagrams, multivariate + Lcomoments, and asymmetric (asy) trimmed LMs (TLMs). Maximum likelihood and + maximum product spacings estimation are available. Right-tail and left-tail LM censoring + by threshold or indicator variable are available. LMs of residual (resid) and reversed + (rev) residual life are implemented along with 13 quantile operators for reliability analyses. + Exact analytical bootstrap estimates of order statistics, LMs, and LM var-covars are available. + Harri-Coble Tau34-squared Normality Test is available. Distributions with L, TL, and added + (+) support for right-tail censoring (RC) encompass: Asy Exponential (Exp) Power [L], + Asy Triangular [L], Cauchy [TL], Eta-Mu [L], Exp. [L], Gamma [L], Generalized (Gen) Exp + Poisson [L], Gen Extreme Value [L], Gen Lambda [L, TL], Gen Logistic [L], Gen Normal [L], + Gen Pareto [L+RC, TL], Govindarajulu [L], Gumbel [L], Kappa [L], Kappa-Mu [L], + Kumaraswamy [L], Laplace [L], Linear Mean Residual Quantile Function [L], Normal [L], + 3p log-Normal [L], Pearson Type III [L], Polynomial Density-Quantile 3 and 4 [L], + Rayleigh [L], Rev-Gumbel [L+RC], Rice [L], Singh Maddala [L], Slash [TL], 3p Student t [L], + Truncated Exponential [L], Wakeby [L], and Weibull [L]. + date_publication: '2024-05-04' + bug_reports: '' + url: https://www.amazon.com/dp/1463508417/ + url_cran: https://CRAN.R-project.org/package=lmomco + url_git: '' +Lmoments: + version: 1.3-1 + title: L-Moments and Quantile Mixtures + maintainer: Juha Karvanen + description: |- + Contains functions to estimate + L-moments and trimmed L-moments from the data. Also + contains functions to estimate the parameters of the normal + polynomial quantile mixture and the Cauchy polynomial quantile + mixture from L-moments and trimmed L-moments. + date_publication: '2019-03-15' + bug_reports: '' + url: http://users.jyu.fi/~jutakarv/ + url_cran: https://CRAN.R-project.org/package=Lmoments + url_git: '' +lmomPi: + version: 0.6.6 + title: |- + (Precipitation) Frequency Analysis and Variability with + L-Moments from 'lmom' + maintainer: Emanuele Cordano + description: |- + It is an extension of 'lmom' R package: 'pel...()','cdf...()',qua...()' function + families are lumped and called from one function per each family respectively in order to + create robust automatic tools to fit data with different probability + distributions and then to estimate probability values and return periods. The implemented functions are able to manage time series with constant and/or missing values without stopping + the execution with error messages. The package also contains tools to calculate several indices based on variability (e.g. 'SPI' , Standardized + Precipitation Index, see and ) for multiple time series or spatially gridded values. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmomPi + url_git: '' +lmomRFA: + version: '3.8' + title: Regional Frequency Analysis using L-Moments + maintainer: J. R. M. Hosking + description: |- + Functions for regional frequency analysis + using the methods of J. R. M. Hosking and J. R. Wallis (1997), + "Regional frequency analysis: an approach based on L-moments". + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmomRFA + url_git: '' +LMPdata: + version: 0.2.0 + title: Easy Import of the EU Labour Market Policy Data + maintainer: Aleksander Rutkowski + description: |- + European Commission's Labour Market Policy (LMP) database + () + provides information on labour market interventions, which are government + actions to help and support the unemployed and other disadvantaged groups in + the transition from unemployment or inactivity to work. It covers the EU + countries and Norway. This package provides functions for downloading and + importing the LMP data and metadata (codelists). + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LMPdata + url_git: https://github.com/alekrutkowski/LMPdata +lmPerm: + version: 2.1.0 + title: Permutation Tests for Linear Models + maintainer: Marco Torchiano + description: Linear model functions using permutation tests. + date_publication: '2016-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmPerm + url_git: https://github.com/mtorchiano/lmPerm +lmQCM: + version: 0.2.4 + title: An Algorithm for Gene Co-Expression Analysis + maintainer: Zhi Huang + description: 'Implementation based on Zhang, Jie & Huang, Kun (2014) + Normalized ImQCM: An Algorithm for Detecting Weak Quasi-Cliques in Weighted Graph + with Applications in Gene Co-Expression Module Discovery in Cancers. Cancer informatics, + 13, CIN-S14021.' + date_publication: '2022-10-10' + bug_reports: https://github.com/huangzhii/lmQCM/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=lmQCM + url_git: https://github.com/huangzhii/lmQCM/ +lmreg: + version: '1.2' + title: |- + Data and Functions Used in Linear Models and Regression with R: + An Integrated Approach + maintainer: Jinwen Qiu + description: |- + Data files and a few functions used in the book + 'Linear Models and Regression with R: An Integrated Approach' + by Debasis Sengupta and Sreenivas Rao Jammalamadaka (2019). + date_publication: '2019-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmreg + url_git: '' +lmridge: + version: 1.2.2 + title: Linear Ridge Regression with Ridge Penalty and Ridge Statistics + maintainer: Imdad Ullah Muhammad + description: |- + Linear ridge regression coefficient's estimation and testing with different ridge related measures such as MSE, R-squared etc. + REFERENCES + i. Hoerl and Kennard (1970) , + ii. Halawa and El-Bassiouni (2000) , + iii. Imdadullah, Aslam, and Saima (2017), + iv. Marquardt (1970) . + date_publication: '2023-01-15' + bug_reports: https://rfaqs.com/contact/ + url: '' + url_cran: https://CRAN.R-project.org/package=lmridge + url_git: '' +lmSubsets: + version: 0.5-2 + title: Exact Variable-Subset Selection in Linear Regression + maintainer: Marc Hofmann + description: |- + Exact and approximation algorithms for variable-subset + selection in ordinary linear regression models. Either compute all + submodels with the lowest residual sum of squares, or determine the + single-best submodel according to a pre-determined statistical + criterion. Hofmann et al. (2020) . + date_publication: '2021-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmSubsets + url_git: https://github.com/marc-hofmann/lmSubsets.R +lmtest: + version: 0.9-40 + title: Testing Linear Regression Models + maintainer: Achim Zeileis + description: |- + A collection of tests, data sets, and examples + for diagnostic checking in linear regression models. Furthermore, + some generic tools for inference in parametric models are provided. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmtest + url_git: '' +lmtestrob: + version: '0.1' + title: Outlier Robust Specification Testing + maintainer: Mikhail Zhelonkin + description: Robust test(s) for model diagnostics in regression. The current version + contains a robust test for functional specification (linearity). The test is based + on the robust bounded-influence test by Heritier and Ronchetti (1994) . + date_publication: '2023-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmtestrob + url_git: '' +lmtp: + version: 1.4.0 + title: |- + Non-Parametric Causal Effects of Feasible Interventions Based on + Modified Treatment Policies + maintainer: Nicholas Williams + description: |- + Non-parametric estimators for casual effects based on longitudinal modified treatment + policies as described in Diaz, Williams, Hoffman, and Schenck , traditional point treatment, + and traditional longitudinal effects. Continuous, binary, categorical treatments, and multivariate treatments are allowed as well are + censored outcomes. The treatment mechanism is estimated via a density ratio classification procedure + irrespective of treatment variable type. For both continuous and binary outcomes, additive treatment effects + can be calculated and relative risks and odds ratios may be calculated for binary outcomes. + date_publication: '2024-06-27' + bug_reports: https://github.com/nt-williams/lmtp/issues + url: https://beyondtheate.com/ + url_cran: https://CRAN.R-project.org/package=lmtp + url_git: https://github.com/nt-williams/lmtp +lmviz: + version: 0.2.0 + title: A Package to Visualize Linear Models Features and Play with Them + maintainer: Francesco Pauli + description: |- + Contains a suite of shiny applications + meant to explore linear model inference feature through simulation + and games. + date_publication: '2020-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lmviz + url_git: '' +lmw: + version: 0.0.2 + title: Linear Model Weights + maintainer: Noah Greifer + description: |- + Computes the implied weights of linear regression models for estimating + average causal effects and provides diagnostics based on these weights. These + diagnostics rely on the analyses in Chattopadhyay and Zubizarreta (2023) + where + several regression estimators are represented as weighting estimators, in connection + to inverse probability weighting. 'lmw' provides tools to diagnose + representativeness, balance, extrapolation, and influence for these models, + clarifying the target population of inference. Tools are also available to + simplify estimating treatment effects for specific target populations of interest. + date_publication: '2024-02-08' + bug_reports: https://github.com/ngreifer/lmw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lmw + url_git: https://github.com/ngreifer/lmw +lncDIFF: + version: 1.0.0 + title: Long Non-Coding RNA Differential Expression Analysis + maintainer: Qian Li + description: We developed an approach to detect differential expression features + in long non-coding RNA low counts, using generalized linear model with zero-inflated + exponential quasi likelihood ratio test. Methods implemented in this package are + described in Li (2019) . + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lncDIFF + url_git: '' +LncFinder: + version: 1.1.6 + title: LncRNA Identification and Analysis Using Heterologous Features + maintainer: Siyu Han + description: 'Long non-coding RNAs identification and analysis. Default models are + trained with human, mouse and wheat datasets by employing SVM. Features are based + on intrinsic composition of sequence, EIIP value (electron-ion interaction pseudopotential), + and secondary structure. This package can also extract other classic features + and build new classifiers. Reference: Han S., et al. (2019) .' + date_publication: '2024-09-28' + bug_reports: '' + url: https://lncfinder.osubmi.org/ + url_cran: https://CRAN.R-project.org/package=LncFinder + url_git: '' +LNIRT: + version: 0.5.1 + title: LogNormal Response Time Item Response Theory Models + maintainer: Konrad Klotzke + description: Allows the simultaneous analysis of responses and response times in + an Item Response Theory (IRT) modelling framework. Supports variable person speed + functions (intercept, trend, quadratic), and covariates for item and person (random) + parameters. Data missing-by-design can be specified. Parameter estimation is done + with a MCMC algorithm. LNIRT replaces the package CIRT, which was written by Rinke + Klein Entink. For reference, see the paper by Fox, Klein Entink and Van der Linden + (2007), "Modeling of Responses and Response Times with the Package cirt", Journal + of Statistical Software, . + date_publication: '2021-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LNIRT + url_git: '' +lnmCluster: + version: 0.3.1 + title: |- + Perform Logistic Normal Multinomial Clustering for Microbiome + Compositional Data + maintainer: Wangshu Tu + description: 'An implementation of logistic normal multinomial (LNM) clustering. + It is an extension of LNM mixture model proposed by Fang and Subedi (2020) , + and is designed for clustering compositional data. The package includes 3 extended + models: LNM Factor Analyzer (LNM-FA), LNM Bicluster Mixture Model (LNM-BMM) and + Penalized LNM Factor Analyzer (LNM-FA). There are several advantages of LNM models: + 1. LNM provides more flexible covariance structure; 2. Factor analyzer can reduce + the number of parameters to estimate; 3. Bicluster can simultaneously cluster + subjects and taxa, and provides significant biological insights; 4. Penalty term + allows sparse estimation in the covariance matrix. Details for model assumptions + and interpretation can be found in papers: Tu and Subedi (2021) + and Tu and Subedi (2022) .' + date_publication: '2022-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lnmCluster + url_git: '' +lnmixsurv: + version: 3.1.6 + title: Bayesian Mixture Log-Normal Survival Model + maintainer: Victor Hugo Soares Ney + description: Bayesian Survival models via the mixture of Log-Normal distribution + extends the well-known survival models and accommodates different behaviour over + time and considers higher censored survival times. The proposal combines mixture + distributions Fruhwirth-Schnatter(2006) , and data + augmentation techniques Tanner and Wong (1987) . + date_publication: '2024-09-03' + bug_reports: '' + url: https://vivianalobo.github.io/lnmixsurv/ + url_cran: https://CRAN.R-project.org/package=lnmixsurv + url_git: '' +LNPar: + version: 0.1.0 + title: Estimation and Testing for a Lognormal-Pareto Mixture + maintainer: Marco Bee + description: Estimates a lognormal-Pareto mixture by maximizing the profile likelihood + function. A likelihood ratio test for discriminating between lognormal and Pareto + tail is also implemented. See Bee, M. (2022) . + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LNPar + url_git: '' +loa: + version: 0.3.1.1 + title: Lattice Options and Add-Ins + maintainer: Karl Ropkins + description: |- + Various plots and functions that make use of the lattice/trellis plotting framework. + The plots, which include loaPlot(), loaMapPlot() and trianglePlot(), and use panelPal(), a function that + extends 'lattice' and 'hexbin' package methods to automate plot subscript and panel-to-panel + and panel-to-key synchronization/management. + date_publication: '2024-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loa + url_git: https://loa.r-forge.r-project.org/ +loadeR: + version: 1.3.0 + title: Load Data for Analysis System + maintainer: Oldemar Rodriguez + description: Provides a framework to load text and excel files through a 'shiny' + graphical interface. It allows renaming, transforming, ordering and removing variables. + It includes basic exploratory methods such as the mean, median, mode, normality + test, histogram and correlation. + date_publication: '2024-10-24' + bug_reports: https://github.com/PROMiDAT/loadeR/issues + url: https://promidat.website + url_cran: https://CRAN.R-project.org/package=loadeR + url_git: https://github.com/PROMiDAT/loadeR +loadings: + version: 0.5.1 + title: |- + Loadings for Principal Component Analysis and Partial Least + Squares + maintainer: Hiroyuki Yamamoto + description: Computing statistical hypothesis testing for loading in principal component + analysis (PCA) (Yamamoto, H. et al. (2014) ), orthogonal + smoothed PCA (OS-PCA) (Yamamoto, H. et al. (2021) ), + one-sided kernel PCA (Yamamoto, H. (2023) ), partial least + squares (PLS) and PLS discriminant analysis (PLS-DA) (Yamamoto, H. et al. (2009) + ), PLS with rank order of groups (PLS-ROG) + (Yamamoto, H. (2017) ), regularized canonical correlation + analysis discriminant analysis (RCCA-DA) (Yamamoto, H. et al. (2008) ), + multiset PLS and PLS-ROG (Yamamoto, H. (2022) ). + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loadings + url_git: '' +loadshaper: + version: 1.1.1 + title: Producing Load Shape with Target Peak and Load Factor + maintainer: Md Riaz Ahmed Khan + description: |- + Modifying a load shape to match specific peak and + load factor is a fundamental component for various power system + planning and operation studies. This package is an efficient tool + to modify a reference load shape while matching the desired peak + and load factor. The package offers both linear and non-linear method, + described in . + The user can control the shape of the final load shape by regulating + certain parameters. The package provides validation metrics for + assessing the derived load shape in terms of preserving time series + properties. It also offers powerful graphics, that allows the user to + visually assess the derived load shape. + date_publication: '2022-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loadshaper + url_git: '' +LoBrA: + version: '1.0' + title: |- + Generalized Spline Mixed Effect Models for Longitudinal Breath + Data + maintainer: Anne-Christin Hauschild + description: Automated analysis and modeling of longitudinal 'omics' data (e.g. + breath 'metabolomics') using generalized spline mixed effect models. Including + automated filtering of noise parameters and determination of breakpoints. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LoBrA + url_git: '' +LobsterCatch: + version: 0.1.0 + title: Models the Capture Processes in American Lobster Trap Fishery + maintainer: Nickchi Payman + description: 'Simulate lobster catch process in a trap fishery. Factors such as + lobster density on ocean floor, their movement, trap saturation and bait shrinkage + rate can be modeled. Details of the methods for modeling those processes can be + found in: Addison and Bell (1997) .' + date_publication: '2023-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LobsterCatch + url_git: '' +lobstr: + version: 1.1.2 + title: Visualize R Data Structures with Trees + maintainer: Hadley Wickham + description: |- + A set of tools for inspecting and understanding R data + structures inspired by str(). Includes ast() for visualizing abstract + syntax trees, ref() for showing shared references, cst() for showing + call stack trees, and obj_size() for computing object sizes. + date_publication: '2022-06-22' + bug_reports: https://github.com/r-lib/lobstr/issues + url: https://lobstr.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=lobstr + url_git: https://github.com/r-lib/lobstr +localboot: + version: 0.9.2 + title: Local Bootstrap Methods for Various Networks + maintainer: Tianhai Zu + description: |- + Network analysis usually requires estimating the uncertainty of + graph statistics. Through this package, we provide tools to bootstrap + various networks via local bootstrap procedure. Additionally, it includes + functions for generating probability matrices, creating network adjacency + matrices from probability matrices, and plotting network structures. + The reference will be updated soon. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=localboot + url_git: '' +LocalControl: + version: 1.1.4 + title: |- + Nonparametric Methods for Generating High Quality Comparative + Effectiveness Evidence + maintainer: Christophe G. Lambert + description: |- + Implements novel nonparametric approaches to address + biases and confounding when comparing treatments or exposures in + observational studies of outcomes. While designed and appropriate for use + in studies involving medicine and the life sciences, the package can be + used in other situations involving outcomes with multiple confounders. + The package implements a family of methods for non-parametric bias correction + when comparing treatments in observational studies, including survival + analysis settings, where competing risks and/or censoring may be present. + The approach extends to bias-corrected personalized predictions of treatment + outcome differences, and analysis of heterogeneity of treatment effect-sizes + across patient subgroups. For further details, please see: + Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl: + An R Package for Comparative Safety and Effectiveness Research. + Journal of Statistical Software. 2020. p. 1–32. Available from . + date_publication: '2024-09-04' + bug_reports: https://github.com/OHDSI/LocalControl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LocalControl + url_git: https://github.com/OHDSI/LocalControl +LocalCop: + version: 0.0.2 + title: Local Likelihood Inference for Conditional Copula Models + maintainer: Martin Lysy + description: Implements a local likelihood estimator for the dependence parameter + in bivariate conditional copula models. Copula family and local likelihood bandwidth + parameters are selected by leave-one-out cross-validation. The models are implemented + in 'TMB', meaning that the local score function is efficiently calculated via + automated differentiation (AD), such that quasi-Newton algorithms may be used + for parameter estimation. + date_publication: '2024-09-12' + bug_reports: https://github.com/mlysy/LocalCop/issues + url: https://mlysy.github.io/LocalCop/ + url_cran: https://CRAN.R-project.org/package=LocalCop + url_git: https://github.com/mlysy/LocalCop +localFDA: + version: 1.0.0 + title: Localization Processes for Functional Data Analysis + maintainer: Antonio Elías + description: |- + Implementation of a theoretically supported alternative to k-nearest neighbors for functional data + to solve problems of estimating unobserved segments of a partially observed functional data sample, + functional classification and outlier detection. The approximating neighbor curves are piecewise functions built from a functional sample. + Instead of a distance on a function space we use a locally defined distance function that satisfies stabilization criteria. + The package allows the implementation of the methodology and the replication of the results in Elías, A., Jiménez, R. and Yukich, J. (2020) . + date_publication: '2020-09-30' + bug_reports: https://github.com/aefdz/localFDA + url: '' + url_cran: https://CRAN.R-project.org/package=localFDA + url_git: https://github.com/aefdz/localFDA +localgauss: + version: '0.41' + title: Estimating Local Gaussian Parameters + maintainer: Tore Selland Kleppe + description: 'Computational routines for estimating local Gaussian parameters. Local + Gaussian parameters are useful for characterizing and testing for non-linear dependence + within bivariate data. See e.g. Tjostheim and Hufthammer, Local Gaussian correlation: + A new measure of dependence, Journal of Econometrics, 2013, Volume 172 (1), pages + 33-48 .' + date_publication: '2021-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=localgauss + url_git: '' +localICE: + version: 0.1.1 + title: Local Individual Conditional Expectation + maintainer: Martin Walter + description: 'Local Individual Conditional Expectation (''localICE'') is a local + explanation approach from the field of eXplainable Artificial Intelligence (XAI). + localICE is a model-agnostic XAI approach which provides three-dimensional local + explanations for particular data instances. The approach is proposed in the master + thesis of Martin Walter as an extension to ICE (see Reference). The three dimensions + are the two features at the horizontal and vertical axes as well as the target + represented by different colors. The approach is applicable for classification + and regression problems to explain interactions of two features towards the target. + For classification models, the number of classes can be more than two and each + class is added as a different color to the plot. The given instance is added to + the plot as two dotted lines according to the feature values. The localICE-package + can explain features of type factor and numeric of any machine learning model. + Automatically supported machine learning packages are ''mlr'', ''randomForest'', + ''caret'' or all other with an S3 predict function. For further model types from + other libraries, a predict function has to be provided as an argument in order + to get access to the model. Reference to the ICE approach: Alex Goldstein, Adam + Kapelner, Justin Bleich, Emil Pitkin (2013) .' + date_publication: '2020-02-07' + bug_reports: https://github.com/viadee/localICE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=localICE + url_git: https://github.com/viadee/localICE +localIV: + version: 0.3.1 + title: |- + Estimation of Marginal Treatment Effects using Local + Instrumental Variables + maintainer: Xiang Zhou + description: |- + In the generalized Roy model, the marginal treatment effect (MTE) can be used as + a building block for constructing conventional causal parameters such as the average treatment + effect (ATE) and the average treatment effect on the treated (ATT). Given a treatment selection + equation and an outcome equation, the function mte() estimates the MTE via the semiparametric + local instrumental variables method or the normal selection model. The function mte_at() evaluates + MTE at different values of the latent resistance u with a given X = x, and the function mte_tilde_at() + evaluates MTE projected onto the estimated propensity score. The function ace() estimates + population-level average causal effects such as ATE, ATT, or the marginal policy relevant + treatment effect. + date_publication: '2020-06-26' + bug_reports: https://github.com/xiangzhou09/localIV + url: '' + url_cran: https://CRAN.R-project.org/package=localIV + url_git: https://github.com/xiangzhou09/localIV +localModel: + version: '0.5' + title: |- + LIME-Based Explanations with Interpretable Inputs Based on + Ceteris Paribus Profiles + maintainer: Przemyslaw Biecek + description: |- + Local explanations of machine learning models describe, how features contributed to a single prediction. + This package implements an explanation method based on LIME + (Local Interpretable Model-agnostic Explanations, + see Tulio Ribeiro, Singh, Guestrin (2016) ) in which interpretable + inputs are created based on local rather than global behaviour of each original feature. + date_publication: '2021-09-14' + bug_reports: https://github.com/ModelOriented/localModel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=localModel + url_git: https://github.com/ModelOriented/localModel +localScore: + version: 2.0.1 + title: Package for Sequence Analysis by Local Score + maintainer: David Robelin + description: Functionalities for calculating the local score and calculating statistical + relevance (p-value) to find a local Score in a sequence of given distribution + (S. Mercier and J.-J. Daudin (2001) ) ; S. + Karlin and S. Altschul (1990) ; + S. Mercier, D. Cellier and F. Charlot (2003) + ; A. Lagnoux, S. Mercier and P. Valois (2017) + ). + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=localScore + url_git: '' +localsolver: + version: '2.3' + title: R API to LocalSolver + maintainer: Walerian Sokolowski + description: |- + The package converts R data onto input and data for LocalSolver, + executes optimization and exposes optimization results as R data. + LocalSolver (http://www.localsolver.com/) is an optimization engine + developed by Innovation24 (http://www.innovation24.fr/). It is designed to + solve large-scale mixed-variable non-convex optimization problems. The + localsolver package is developed and maintained by WLOG Solutions + (http://www.wlogsolutions.com/en/) in collaboration with Decision Support + and Analysis Division at Warsaw School of Economics + (http://www.sgh.waw.pl/en/). + date_publication: '2014-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=localsolver + url_git: '' +localsp: + version: 0.1.0 + title: Local Indicator of Stratified Power + maintainer: Wenbo Lv + description: Implements a local indicator of stratified power to analyze local spatial + stratified association and demonstrate how spatial stratified association changes + spatially and in local regions, as outlined in Hu et al. (2024) . + date_publication: '2025-01-27' + bug_reports: https://github.com/ausgis/localsp/issues + url: https://ausgis.github.io/localsp/ + url_cran: https://CRAN.R-project.org/package=localsp + url_git: https://github.com/ausgis/localsp +locaR: + version: 0.1.2 + title: A Set of Tools for Sound Localization + maintainer: Richard Hedley + description: A set of functions and tools to conduct acoustic source localization, + as well as organize and check localization data and results. The localization + functions implement the modified steered response power algorithm described by + Cobos et al. (2010) . + date_publication: '2023-02-16' + bug_reports: https://github.com/rhedley/locaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=locaR + url_git: https://github.com/rhedley/locaR +locateip: + version: 0.1.2 + title: Locate IP Addresses with 'ip-api' + maintainer: Judith Bourque + description: Download Internet Protocol (IP) address location and more from the + 'ip-api' application programming interface (API) . The package + makes it easy to get the latitude, longitude, country, region, and organisation + associated to the provided IP address. The information is conveniently returned + in a rectangular format. + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locateip + url_git: '' +locatexec: + version: 0.1.1 + title: Detection and Localization of Executable Files + maintainer: David Gohel + description: |- + A set of functions to locate some programs + available on the user machine. The package provides functions to locate + 'Node.js', 'npm', 'LibreOffice', 'Microsoft Word', 'Microsoft PowerPoint', + 'Microsoft Excel', 'Python', 'pip', 'Mozilla Firefox' and 'Google Chrome'. + User can test the availability of a program with eventually a version + and call it with function system2() or system(). This allows the use of + a single function to retrieve the path to a program regardless of the + operating system and its configuration. + date_publication: '2021-05-19' + bug_reports: https://github.com/ardata-fr/locatexec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=locatexec + url_git: '' +locationgamer: + version: 0.1.0 + title: Identification of Location Game Equilibria in Networks + maintainer: Maximilian Zellner + description: |- + Identification of equilibrium locations in location games (Hotelling (1929) + ). In these games, two competing actors place + customer-serving units in two locations simultaneously. Customers make the + decision to visit the location that is closest to them. The functions in + this package include Prim algorithm (Prim (1957) + ) to find the minimum spanning tree + connecting all network vertices, an implementation of Dijkstra algorithm + (Dijkstra (1959) ) to find the shortest distance and + path between any two vertices, a self-developed algorithm using elimination + of purely dominated strategies to find the equilibrium, and several plotting + functions. + date_publication: '2020-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locationgamer + url_git: '' +LocaTT: + version: 1.1.2 + title: Geographically-Conscious Taxonomic Assignment for Metabarcoding + maintainer: Kenen Goodwin + description: |- + A bioinformatics pipeline for performing taxonomic + assignment of DNA metabarcoding sequence data while considering + geographic location. A detailed tutorial is available at + . + A manuscript describing these methods is in preparation. + date_publication: '2024-09-05' + bug_reports: https://github.com/Urodelan/LocaTT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LocaTT + url_git: https://github.com/Urodelan/LocaTT +locfdr: + version: 1.1-8 + title: Computes Local False Discovery Rates + maintainer: Balasubramanian Narasimhan + description: Computation of local false discovery rates. + date_publication: '2015-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locfdr + url_git: '' +locfit: + version: 1.5-9.11 + title: Local Regression, Likelihood and Density Estimation + maintainer: Andy Liaw + description: Local regression, likelihood and density estimation methods as described + in the 1999 book by Loader. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locfit + url_git: '' +locits: + version: 1.7.7 + title: Test of Stationarity and Localized Autocovariance + maintainer: Guy Nason + description: |- + Provides test of second-order stationarity for time + series (for dyadic and arbitrary-n length data). Provides + localized autocovariance, with confidence intervals, + for locally stationary (nonstationary) time series. + See Nason, G P (2013) "A test for second-order stationarity and + approximate confidence intervals for localized autocovariance + for locally stationary time series." Journal of the Royal Statistical + Society, Series B, 75, 879-904. . + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locits + url_git: '' +Lock5Data: + version: 3.0.0 + title: 'Datasets for "Statistics: UnLocking the Power of Data"' + maintainer: Robin Lock + description: |- + Datasets for the third edition of "Statistics: Unlocking the Power of Data" by Lock^5 + Includes version of datasets from earlier editions. + date_publication: '2021-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Lock5Data + url_git: '' +LocKer: + version: '1.1' + title: |- + Locally Sparse Estimator of Generalized Varying Coefficient + Model for Asynchronous Longitudinal Data + maintainer: Rou Zhong + description: Locally sparse estimator of generalized varying coefficient model for + asynchronous longitudinal data by kernel-weighted estimating equation. + date_publication: '2022-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LocKer + url_git: '' +locpol: + version: 0.8.0 + title: Kernel Local Polynomial Regression + maintainer: Jorge Luis Ojeda Cabrera + description: |- + Computes local polynomial estimators for + the regression and also density. It comprises several + different utilities to handle kernel estimators. + date_publication: '2022-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locpol + url_git: '' +locpolExpectile: + version: 0.1.1 + title: Local Polynomial Expectile Regression + maintainer: Cécile Adam + description: Provides the local polynomial expectile regression method and different + bandwidth selection procedures. The codes include local polynomial univariate + expectile regression with several data-driven methods for bandwidth selection; + local linear bivariate and trivariate expectile regression; and partially linear + expectile regression, allowing for different errors structures (homoscedastic + error and various heteroscedastic error structures). For more details, see Adam + and Gijbels (2021a) and Adam and Gijbels (2021b) + . + date_publication: '2021-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locpolExpectile + url_git: '' +locStra: + version: '1.9' + title: Fast Implementation of (Local) Population Stratification Methods + maintainer: Georg Hahn + description: Fast implementations to compute the genetic covariance matrix, the + Jaccard similarity matrix, the s-matrix (the weighted Jaccard similarity matrix), + and the (classic or robust) genomic relationship matrix of a (dense or sparse) + input matrix (see Hahn, Lutz, Hecker, Prokopenko, Cho, Silverman, Weiss, and Lange + (2020) ). Full support for sparse matrices from the R-package + 'Matrix'. Additionally, an implementation of the power method (von Mises iteration) + to compute the largest eigenvector of a matrix is included, a function to perform + an automated full run of global and local correlations in population stratification + data, a function to compute sliding windows, and a function to invert minor alleles + and to select those variants/loci exceeding a minimal cutoff value. New functionality + in locStra allows one to extract the k leading eigenvectors of the genetic covariance + matrix, Jaccard similarity matrix, s-matrix, and genomic relationship matrix via + fast PCA without actually computing the similarity matrices. The fast PCA to compute + the k leading eigenvectors can now also be run directly from 'bed'+'bim'+'fam' + files. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=locStra + url_git: '' +LOCUS: + version: '1.0' + title: |- + Low-Rank Decomposition of Brain Connectivity Matrices with + Uniform Sparsity + maintainer: Jialu Ran + description: To decompose symmetric matrices such as brain connectivity matrices + so that one can extract sparse latent component matrices and also estimate mixing + coefficients, a blind source separation (BSS) method named LOCUS was proposed + in Wang and Guo (2023) . For brain connectivity matrices, the + outputs correspond to sparse latent connectivity traits and individual-level trait + loadings. + date_publication: '2022-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LOCUS + url_git: '' +locuszoomr: + version: 0.3.7 + title: Gene Locus Plot with Gene Annotations + maintainer: Myles Lewis + description: Publication-ready regional gene locus plots similar to those produced + by the web interface 'LocusZoom' , but running locally + in R. Genetic or genomic data with gene annotation tracks are plotted via R base + graphics, 'ggplot2' or 'plotly', allowing flexibility and easy customisation including + laying out multiple locus plots on the same page. It uses the 'LDlink' API + to query linkage disequilibrium data from the 1000 Genomes Project and can overlay + this on plots . + date_publication: '2025-02-10' + bug_reports: https://github.com/myles-lewis/locuszoomr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=locuszoomr + url_git: https://github.com/myles-lewis/locuszoomr +loder: + version: 0.2.1 + title: Dependency-Free Access to PNG Image Files + maintainer: Jon Clayden + description: |- + Read and write access to PNG image files using the LodePNG + library. The package has no external dependencies. + date_publication: '2022-12-16' + bug_reports: https://github.com/jonclayden/loder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=loder + url_git: https://github.com/jonclayden/loder +lodGWAS: + version: 1.0-7 + title: |- + Genome-Wide Association Analysis of a Biomarker Accounting for + Limit of Detection + maintainer: Ilja M. Nolte + description: |- + Genome-wide association (GWAS) analyses + of a biomarker that account for the limit of detection. + date_publication: '2015-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lodGWAS + url_git: '' +lodi: + version: 0.9.2 + title: Limit of Detection Imputation for Single-Pollutant Models + maintainer: Alexander Rix + description: |- + Impute observed values below the limit of detection (LOD) via + censored likelihood multiple imputation (CLMI) in single-pollutant + models, developed by Boss et al (2019) . + CLMI handles exposure detection limits that may change throughout the course + of exposure assessment. 'lodi' provides functions for imputing and + pooling for this method. + date_publication: '2020-02-07' + bug_reports: https://github.com/umich-cphds/lodi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lodi + url_git: https://github.com/umich-cphds/lodi +lodr: + version: '1.0' + title: Linear Model Fitting with LOD Covariates + maintainer: Kevin Donovan + description: Tools to fit linear regression model to data while taking into account + covariates with lower limit of detection (LOD). + date_publication: '2020-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lodr + url_git: '' +loedata: + version: 1.0.1 + title: Data Sets from "Lectures on Econometrics" by Chirok Han + maintainer: Chirok Han + description: |- + Data sets for Chirok Han (2022, ISBN:979-11-303-1497-6, + "Lectures on Econometrics"). Students, teachers, and self-learners will + find the data sets essential for replicating the results in the book. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loedata + url_git: '' +loewesadditivity: + version: 0.1.0 + title: Loewe's Additivity + maintainer: Shannon Gallagher + description: Estimate model parameters to determine whether two compounds have synergy, + antagonism, or Loewe's Additivity. + date_publication: '2020-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loewesadditivity + url_git: '' +lofifonts: + version: 0.1.3 + title: Text Rendering with Bitmap and Vector Fonts + maintainer: Mike Cheng + description: |- + Alternate font rendering is useful when rendering text to novel + graphics outputs where modern font rendering is not available or + where bespoke text positioning is required. Bitmap and vector fonts allow for + custom layout and rendering using pixel coordinates and line drawing. + Formatted text is created as a data.frame of pixel coordinates (for bitmap fonts) + or stroke coordinates (for vector fonts). All text can be easily + previewed as a matrix or raster image. + A selection of fonts is included with this package. + date_publication: '2024-11-08' + bug_reports: https://github.com/coolbutuseless/lofifonts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lofifonts + url_git: https://github.com/coolbutuseless/lofifonts +log: + version: 1.1.1 + title: Record Events and Issues + maintainer: John Coene + description: Logger to keep track of informational events and errors useful for + debugging. + date_publication: '2022-02-24' + bug_reports: https://github.com/devOpifex/log/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=log + url_git: '' +log4r: + version: 0.4.4 + title: A Fast and Lightweight Logging System for R, Based on 'log4j' + maintainer: Aaron Jacobs + description: |- + The log4r package is meant to provide a fast, lightweight, + object-oriented approach to logging in R based on the widely-emulated + 'log4j' system and etymology. + date_publication: '2024-10-12' + bug_reports: https://github.com/johnmyleswhite/log4r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=log4r + url_git: https://github.com/johnmyleswhite/log4r +LOGAN: + version: 1.0.1 + title: Log File Analysis in International Large-Scale Assessments + maintainer: Waldir Leoncio + description: |- + Enables users to handle the dataset cleaning for conducting + specific analyses with the log files from two international educational + assessments: the Programme for International Student Assessment (PISA, + ) and the Programme for the International + Assessment of Adult Competencies (PIAAC, + ). An illustration of the analyses can be + found on the LOGAN Shiny app () on + your browser. + date_publication: '2022-10-25' + bug_reports: https://github.com/derecost/LOGAN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LOGAN + url_git: '' +logbin: + version: 2.0.5 + title: Relative Risk Regression Using the Log-Binomial Model + maintainer: Mark W. Donoghoe + description: |- + Methods for fitting log-link GLMs and GAMs to binomial data, + including EM-type algorithms with more stable convergence properties than standard methods. + date_publication: '2021-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logbin + url_git: https://github.com/mdonoghoe/logbin +LogConcDEAD: + version: 1.6-10 + title: Log-Concave Density Estimation in Arbitrary Dimensions + maintainer: Yining Chen + description: Software for computing a log-concave (maximum likelihood) estimator + for independent and identically distributed data in any number of dimensions. + For a detailed description of the method see Cule, Samworth and Stewart (2010, + Journal of Royal Statistical Society Series B, ). + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogConcDEAD + url_git: '' +logconcens: + version: 0.17-4 + title: |- + Maximum Likelihood Estimation of a Log-Concave Density Based on + Censored Data + maintainer: Dominic Schuhmacher + description: Based on right or interval censored data, compute the maximum likelihood + estimator of a (sub)probability density under the assumption that it is log-concave. + For further information see Duembgen, Rufibach and Schuhmacher (2014) . + date_publication: '2024-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logconcens + url_git: '' +logcondens: + version: 2.1.8 + title: Estimate a Log-Concave Probability Density from Iid Observations + maintainer: Kaspar Rufibach + description: Given independent and identically distributed observations X(1), ..., + X(n), compute the maximum likelihood estimator (MLE) of a density as well as a + smoothed version of it under the assumption that the density is log-concave, see + Rufibach (2007) and Duembgen and Rufibach (2009). The main function of the package + is 'logConDens' that allows computation of the log-concave MLE and its smoothed + version. In addition, we provide functions to compute (1) the value of the density + and distribution function estimates (MLE and smoothed) at a given point (2) the + characterizing functions of the estimator, (3) to sample from the estimated distribution, + (5) to compute a two-sample permutation test based on log-concave densities, (6) + the ROC curve based on log-concave estimates within cases and controls, including + confidence intervals for given values of false positive fractions (7) computation + of a confidence interval for the value of the true density at a fixed point. Finally, + three datasets that have been used to illustrate log-concave density estimation + are made available. + date_publication: '2023-08-22' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=logcondens + url_git: '' +logcondiscr: + version: 1.0.6 + title: |- + Estimate a Log-Concave Probability Mass Function from Discrete + i.i.d. Observations + maintainer: Kaspar Rufibach + description: Given independent and identically distributed observations X(1), ..., + X(n), allows to compute the maximum likelihood estimator (MLE) of probability + mass function (pmf) under the assumption that it is log-concave, see Weyermann + (2007) and Balabdaoui, Jankowski, Rufibach, and Pavlides (2012). The main functions + of the package are 'logConDiscrMLE' that allows computation of the log-concave + MLE, 'logConDiscrCI' that computes pointwise confidence bands for the MLE, and + 'kInflatedLogConDiscr' that computes a mixture of a log-concave PMF and a point + mass at k. + date_publication: '2015-07-03' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=logcondiscr + url_git: '' +logger: + version: 0.4.0 + title: A Lightweight, Modern and Flexible Logging Utility + maintainer: Gergely Daróczi + description: |- + Inspired by the the 'futile.logger' R package and 'logging' + Python module, this utility provides a flexible and extensible way of + formatting and delivering log messages with low overhead. + date_publication: '2024-10-22' + bug_reports: https://github.com/daroczig/logger/issues + url: https://daroczig.github.io/logger/ + url_cran: https://CRAN.R-project.org/package=logger + url_git: '' +logging: + version: 0.10-108 + title: R Logging Package + maintainer: Walerian Sokolowski + description: |- + Pure R implementation of the ubiquitous log4j package. It offers hierarchic + loggers, multiple handlers per logger, level based filtering, space handling in messages + and custom formatting. + date_publication: '2019-07-14' + bug_reports: https://github.com/WLOGSolutions/r-logging/issues + url: '' + url_cran: https://CRAN.R-project.org/package=logging + url_git: https://github.com/WLOGSolutions/r-logging +loggit: + version: 2.1.1 + title: Modern Logging for the R Ecosystem + maintainer: Ryan Price + description: |2- + + An effortless 'ndjson' (newline-delimited 'JSON') logger, with two primary + log-writing interfaces. It provides a set of wrappings for base R's + message(), warning(), and stop() functions that maintain identical + functionality, but also log the handler message to an 'ndjson' log file. + 'loggit' also exports its internal 'loggit()' function for powerful and + configurable custom logging. No change in existing code is necessary to use + this package, and should only require additions to fully leverage the power + of the logging system. 'loggit' also provides a log reader for reading an + 'ndjson' log file into a data frame, log rotation, and live echo of the + 'ndjson' log messages to terminal 'stdout' for log capture by external + systems (like containers). 'loggit' is ideal for Shiny apps, data pipelines, + modeling work flows, and more. Please see the vignettes for detailed example + use cases. + date_publication: '2021-02-28' + bug_reports: https://github.com/ryapric/loggit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=loggit + url_git: https://github.com/ryapric/loggit +loggit2: + version: 2.3.1 + title: Easy-to-Use, Dependencyless Logger + maintainer: Matthias Ollech + description: |- + An easy-to-use 'ndjson' (newline-delimited 'JSON') logger. + It provides a set of wrappers for base R's message(), warning(), and + stop() functions that maintain identical functionality, but also log + the handler message to an 'ndjson' log file. + No change in existing code is necessary to use this package, + and only a few additional adjustments are needed to fully + utilize its potential. + date_publication: '2024-07-25' + bug_reports: https://github.com/MEO265/loggit2/issues + url: https://r-loggit.org/ + url_cran: https://CRAN.R-project.org/package=loggit2 + url_git: https://github.com/MEO265/loggit2 +logib: + version: 0.2.0 + title: Salary Analysis by the Swiss Federal Office for Gender Equality + maintainer: Marc Stöckli + description: |- + Implementation of the Swiss Confederation's standard analysis + model for salary analyses + in R. The + analysis is run at company-level and the model is intended for + medium-sized and large companies. It can technically be used with 50 + or more employees (apprentices, trainees/interns and expats are not + included in the analysis). Employees with at least 100 employees are + required by the Gender Equality Act to conduct an equal pay analysis. + This package allows users to run the equal salary analysis in R, + providing additional transparency with respect to the methodology and + simple automation possibilities. + date_publication: '2024-12-20' + bug_reports: https://github.com/admin-ebg/logib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=logib + url_git: https://github.com/admin-ebg/logib +logiBin: + version: '0.3' + title: Binning Variables to Use in Logistic Regression + maintainer: Sneha Tody + description: Fast binning of multiple variables using parallel processing. A summary + of all the variables binned is generated which provides the information value, + entropy, an indicator of whether the variable follows a monotonic trend or not, + etc. It supports rebinning of variables to force a monotonic trend as well as + manual binning based on pre specified cuts. The cut points of the bins are based + on conditional inference trees as implemented in the partykit package. The conditional + inference framework is described by Hothorn T, Hornik K, Zeileis A (2006) . + date_publication: '2018-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logiBin + url_git: '' +logicDT: + version: 1.0.5 + title: Identifying Interactions Between Binary Predictors + maintainer: Michael Lau + description: |- + A statistical learning method that tries to find the best set + of predictors and interactions between predictors for modeling binary or + quantitative response data in a decision tree. Several search algorithms + and ensembling techniques are implemented allowing for finetuning the + method to the specific problem. Interactions with quantitative + covariables can be properly taken into account by fitting local + regression models. Moreover, a variable importance measure for assessing + marginal and interaction effects is provided. Implements the + procedures proposed by Lau et al. (2024, ). + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logicDT + url_git: '' +LogicForest: + version: 2.1.1 + title: Logic Forest + maintainer: Melica Nikahd + description: Two classification ensemble methods based on logic regression models. LogForest() + uses a bagging approach to construct an ensemble of logic regression models. LBoost() + uses a combination of boosting and cross-validation to construct an ensemble of + logic regression models. Both methods are used for classification of binary responses + based on binary predictors and for identification of important variables and variable + interactions predictive of a binary outcome. Wolf, B.J., Slate, E.H., Hill, E.G. + (2010) . + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogicForest + url_git: '' +LogicReg: + version: 1.6.6 + title: Logic Regression + maintainer: Charles Kooperberg + description: |- + Routines for fitting Logic Regression models. Logic Regression is described + in Ruczinski, Kooperberg, and LeBlanc (2003) . Monte + Carlo Logic Regression is described in and Kooperberg and Ruczinski (2005) + . + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogicReg + url_git: '' +logihist: + version: '1.0' + title: Combined Graphs for Logistic Regression + maintainer: Marcelino de la Cruz + description: Provides histograms, boxplots and dotplots as alternatives to scatterplots + of data when plotting fitted logistic regressions. + date_publication: '2017-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logihist + url_git: '' +login: + version: 0.9.3 + title: '''shiny'' Login Module' + maintainer: Jason Bryer + description: |- + Framework for adding authentication to 'shiny' applications. + Provides flexibility as compared to other options for where user + credentials are saved, allows users to create their own accounts, and + password reset functionality. Bryer (2024) + . + date_publication: '2024-04-18' + bug_reports: https://github.com/jbryer/login/issues + url: https://jbryer.github.io/login/ + url_cran: https://CRAN.R-project.org/package=login + url_git: https://github.com/jbryer/login +logistf: + version: 1.26.0 + title: Firth's Bias-Reduced Logistic Regression + maintainer: Georg Heinze + description: |- + Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the log-likelihood by the Jeffreys + prior. Confidence intervals for regression coefficients can be computed by penalized profile likelihood. Firth's method was proposed as ideal + solution to the problem of separation in logistic regression, see Heinze and Schemper (2002) . If needed, the bias reduction can be turned off such that ordinary + maximum likelihood logistic regression is obtained. Two new modifications of Firth's method, FLIC and FLAC, lead to unbiased predictions and are now available + in the package as well, see Puhr et al (2017) . + date_publication: '2023-08-18' + bug_reports: https://github.com/georgheinze/logistf/issues/ + url: https://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/firth-correction/ + url_cran: https://CRAN.R-project.org/package=logistf + url_git: '' +logistic4p: + version: '1.6' + title: |- + Logistic Regression with Misclassification in Dependent + Variables + maintainer: Zhiyong Zhang + description: Error in a binary dependent variable, also known as misclassification, + has not drawn much attention in psychology. Ignoring misclassification in logistic + regression can result in misleading parameter estimates and statistical inference. + This package conducts logistic regression analysis with misspecification in outcome + variables. + date_publication: '2023-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logistic4p + url_git: '' +LogisticCopula: + version: 0.1.0 + title: A Copula Based Extension of Logistic Regression + maintainer: Simon Boge Brant + description: |- + An implementation of a method of extending a logistic regression + model beyond linear effects of the co-variates. The extension in is + constructed by first equating the logistic regression model to a naive Bayes + model where all the margins are specified to follow natural exponential + distributions conditional on Y, that is, a model for Y given X that is + specified through the distribution of X given Y, where the columns of X are + assumed to be mutually independent conditional on Y. Subsequently, the + model is expanded by adding vine - copulas to relax the assumption of + mutual independence, where pair-copulas are added in a stage-wise, forward + selection manner. Some heuristics are employed during the process of + selecting edges, as well as the families of pair-copula models. After each + component is added, the parameters are updated by a (smaller) number of + gradient steps to maximise the likelihood. When the algorithm has stopped + adding edges, based the criterion that a new edge should improve the + likelihood more than k times the number new parameters, the parameters are + updated with a larger number of gradient steps, or until convergence. + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogisticCopula + url_git: '' +LogisticCurveFitting: + version: 0.1.0 + title: Logistic Curve Fitting by Rhodes Method + maintainer: Debarghya Baul + description: A system for fitting Logistic Curve by Rhodes Method. Method for fitting + logistic curve by Rhodes Method is described in A.M.Gun,M.K.Gupta and B.Dasgupta(2019,ISBN:81-87567-81-3). + date_publication: '2022-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogisticCurveFitting + url_git: '' +logisticPCA: + version: '0.2' + title: Binary Dimensionality Reduction + maintainer: Andrew J. Landgraf + description: |- + Dimensionality reduction techniques for binary data including + logistic PCA. + date_publication: '2016-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logisticPCA + url_git: https://github.com/andland/logisticPCA +LogisticRCI: + version: '1.1' + title: Linear and Logistic Regression-Based Reliable Change Index + maintainer: Rafael de Andrade Moral + description: Here we provide an implementation of the linear and logistic regression-based + Reliable Change Index (RCI), to be used with lm and binomial glm model objects, + respectively, following Moral et al. . The RCI function + returns a score assumed to be approximately normally distributed, which is helpful + to detect patients that may present cognitive decline. + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogisticRCI + url_git: '' +logisticRR: + version: 0.3.0 + title: Adjusted Relative Risk from Logistic Regression + maintainer: Youjin Lee + description: Adjusted odds ratio conditional on potential confounders can be directly + obtained from logistic regression. However, those adjusted odds ratios have been + widely incorrectly interpreted as a relative risk. As relative risk is often of + interest in public health, we provide a simple code to return adjusted relative + risks from logistic regression model under potential confounders. + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logisticRR + url_git: https://github.com/youjin1207/logisticRR +logitFD: + version: '1.0' + title: Functional Principal Components Logistic Regression + maintainer: Manuel Escabias + description: |- + Functions for fitting a functional principal components logit regression model + in four different situations: ordinary and filtered functional principal components + of functional predictors, included in the model according to their variability + explanation power, and according to their prediction ability by stepwise methods. The + proposed methods were developed in Escabias et al (2004) + and Escabias et al (2005) + . + date_publication: '2022-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logitFD + url_git: '' +logitnorm: + version: 0.8.39 + title: Functions for the Logitnormal Distribution + maintainer: Thomas Wutzler + description: Density, distribution, quantile and random generation function for + the logitnormal distribution. Estimation of the mode and the first two moments. + Estimation of distribution parameters. + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logitnorm + url_git: '' +logitr: + version: 1.1.2 + title: Logit Models w/Preference & WTP Space Utility Parameterizations + maintainer: John Helveston + description: Fast estimation of multinomial (MNL) and mixed logit (MXL) models in + R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) + space utility parameterizations. Weighted models can also be estimated. An option + is available to run a parallelized multistart optimization loop with random starting + points in each iteration, which is useful for non-convex problems like MXL models + or models with WTP space utility parameterizations. The main optimization loop + uses the 'nloptr' package to minimize the negative log-likelihood function. Additional + functions are available for computing and comparing WTP from both preference space + and WTP space models and for predicting expected choices and choice probabilities + for sets of alternatives based on an estimated model. Mixed logit models can include + uncorrelated or correlated heterogeneity covariances and are estimated using maximum + simulated likelihood based on the algorithms in Train (2009) . + More details can be found in Helveston (2023) . + date_publication: '2024-07-24' + bug_reports: https://github.com/jhelvy/logitr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=logitr + url_git: https://github.com/jhelvy/logitr +logKDE: + version: 0.3.2 + title: |- + Computing Log-Transformed Kernel Density Estimates for Positive + Data + maintainer: Andrew Thomas Jones + description: Computes log-transformed kernel density estimates for positive data + using a variety of kernels. It follows the methods described in Jones, Nguyen + and McLachlan (2018) . + date_publication: '2018-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logKDE + url_git: '' +loglognorm: + version: 1.0.2 + title: Double Log Normal Distribution Functions + maintainer: Olaf Mersmann + description: Functions to sample from the double log normal distribution and calculate + the density, distribution and quantile functions. + date_publication: '2022-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loglognorm + url_git: '' +logmult: + version: 0.7.4 + title: Log-Multiplicative Models, Including Association Models + maintainer: Milan Bouchet-Valat + description: |- + Functions to fit log-multiplicative models using 'gnm', with + support for convenient printing, plots, and jackknife/bootstrap + standard errors. For complex survey data, models can be fitted from + design objects from the 'survey' package. Currently supported models + include UNIDIFF (Erikson & Goldthorpe, 1992), + a.k.a. log-multiplicative layer effect model (Xie, 1992) + , and several association models: + Goodman (1979) + row-column association models of the RC(M) and RC(M)-L families + with one or several dimensions; two skew-symmetric association + models proposed by Yamaguchi (1990) + and by van der Heijden & Mooijaart (1995) + Functions allow computing the intrinsic association coefficient + (see Bouchet-Valat (2022) ) + and the Altham (1970) index , + including via the Bayes shrinkage estimator proposed + by Zhou (2015) ; + and the RAS/IPF/Deming-Stephan algorithm. + date_publication: '2022-02-23' + bug_reports: https://github.com/nalimilan/logmult/issues + url: '' + url_cran: https://CRAN.R-project.org/package=logmult + url_git: https://github.com/nalimilan/logmult +lognorm: + version: 0.1.10 + title: Functions for the Lognormal Distribution + maintainer: Thomas Wutzler + description: |- + The lognormal distribution + (Limpert et al. (2001) ) + can characterize uncertainty that is bounded by zero. + This package provides estimation of distribution parameters, computation of + moments and other basic statistics, and an approximation of the distribution + of the sum of several correlated lognormally distributed variables + (Lo 2013 ) and the approximation of the + difference of two correlated lognormally distributed variables + (Lo 2012 ). + date_publication: '2021-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lognorm + url_git: https://github.com/bgctw/lognorm +logNormReg: + version: 0.5-0 + title: log Normal Linear Regression + maintainer: Vito M. R. Muggeo + description: |- + Functions to fits simple linear regression models with log normal errors + and identity link, i.e. taking the responses on the original scale. See + Muggeo (2018) . + date_publication: '2021-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logNormReg + url_git: '' +logOfGamma: + version: 0.0.1 + title: Natural Logarithms of the Gamma Function for Large Values + maintainer: Phillip Labuschagne + description: |- + Uses approximations to compute the natural logarithm of the Gamma + function for large values. + date_publication: '2017-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logOfGamma + url_git: '' +logos: + version: 0.1.0 + title: Access to the Hebrew, Greek, and English Version of the Bible + maintainer: JP Monteagudo + description: Access to the Greek New Testament (27 books) and the Old Testament + (39 books) and allow users to do textual analysis on the data. The New and Old + Testament have been provided in their original languages, Greek and Hebrew, respectively. + Additionally, the Revised American Standard Bible is also provided for users who'd + rather use a word–for–word modern English translation. + date_publication: '2025-02-18' + bug_reports: https://github.com/jpmonteagudo28/logos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=logos + url_git: https://github.com/jpmonteagudo28/logos +logr: + version: 1.3.8 + title: Creates Log Files + maintainer: David Bosak + description: |- + Contains functions to help create log files. The + package aims to overcome the difficulty of the base R sink() command. The + log_print() function will print to both the console and the file log, + without interfering in other write operations. + date_publication: '2024-05-09' + bug_reports: https://github.com/dbosak01/logr/issues + url: https://logr.r-sassy.org + url_cran: https://CRAN.R-project.org/package=logr + url_git: https://github.com/dbosak01/logr +LogRegEquiv: + version: 0.1.5 + title: Logistic Regression Equivalence + maintainer: Guy Ashiri-Prossner + description: Tools for assessing equivalence of similar Logistic Regression models. + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LogRegEquiv + url_git: '' +logrx: + version: 0.3.2 + title: A Logging Utility Focus on Clinical Trial Programming Workflows + maintainer: Nathan Kosiba + description: A utility to facilitate the logging and review of R programs in clinical + trial programming workflows. + date_publication: '2025-02-18' + bug_reports: https://github.com/pharmaverse/logrx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=logrx + url_git: https://github.com/pharmaverse/logrx +logspline: + version: 2.1.22 + title: Routines for Logspline Density Estimation + maintainer: Charles Kooperberg + description: |- + Contains routines for logspline density estimation. + The function oldlogspline() uses the same algorithm as the logspline package + version 1.0.x; i.e. the Kooperberg and Stone (1992) + algorithm (with an improved interface). The recommended routine logspline() + uses an algorithm from Stone et al (1997) . + date_publication: '2024-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=logspline + url_git: '' +lokern: + version: 1.1-12 + title: |- + Kernel Regression Smoothing with Local or Global Plug-in + Bandwidth + maintainer: Martin Maechler + description: |- + Kernel regression smoothing with adaptive local or global plug-in + bandwidth selection. + date_publication: '2024-07-30' + bug_reports: https://r-forge.r-project.org/R/?group_id=846 + url: '' + url_cran: https://CRAN.R-project.org/package=lokern + url_git: https://curves-etc.r-forge.r-project.org/ +lolliplot: + version: 0.2.2 + title: Plot Variants and Somatic Mutations + maintainer: Zhang Renliang + description: |- + Draw lolliplot using GRanges objects. this package was designed + only for drawing lolliplot. So, it's faster than 'trackViewer', but un-related + functions has been derived. + date_publication: '2023-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lolliplot + url_git: '' +lolog: + version: 1.3.1 + title: Latent Order Logistic Graph Models + maintainer: Ian E. Fellows + description: |- + Estimation of Latent Order Logistic (LOLOG) Models for Networks. + LOLOGs are a flexible and fully general class of statistical graph models. + This package provides functions for performing MOM, GMM and variational + inference. Visual diagnostics and goodness of fit metrics are provided. + See Fellows (2018) for a detailed description of the methods. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lolog + url_git: https://github.com/statnet/lolog +lolR: + version: '2.1' + title: Linear Optimal Low-Rank Projection + maintainer: Eric Bridgeford + description: Supervised learning techniques designed for the situation when the + dimensionality exceeds the sample size have a tendency to overfit as the dimensionality + of the data increases. To remedy this High dimensionality; low sample size (HDLSS) + situation, we attempt to learn a lower-dimensional representation of the data + before learning a classifier. That is, we project the data to a situation where + the dimensionality is more manageable, and then are able to better apply standard + classification or clustering techniques since we will have fewer dimensions to + overfit. A number of previous works have focused on how to strategically reduce + dimensionality in the unsupervised case, yet in the supervised HDLSS regime, few + works have attempted to devise dimensionality reduction techniques that leverage + the labels associated with the data. In this package and the associated manuscript + Vogelstein et al. (2017) , we provide several methods for feature + extraction, some utilizing labels and some not, along with easily extensible utilities + to simplify cross-validative efforts to identify the best feature extraction method. + Additionally, we include a series of adaptable benchmark simulations to serve + as a standard for future investigative efforts into supervised HDLSS. Finally, + we produce a comprehensive comparison of the included algorithms across a range + of benchmark simulations and real data applications. + date_publication: '2020-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lolR + url_git: https://github.com/neurodata/lol +LOMAR: + version: 0.5.0 + title: Localization Microscopy Data Analysis + maintainer: Jean-Karim Heriche + description: Read, register and compare point sets from single molecule localization + microscopy. + date_publication: '2024-09-26' + bug_reports: '' + url: https://git.embl.de/heriche/lomar + url_cran: https://CRAN.R-project.org/package=LOMAR + url_git: '' +lomb: + version: 2.5.0 + title: Lomb-Scargle Periodogram + maintainer: Thomas Ruf + description: 'Computes the Lomb-Scargle Periodogram and actogram for evenly or unevenly + sampled time series. Includes a randomization procedure to obtain exact p-values. + Partially based on C original by Press et al. (Numerical Recipes) and the Python + module Astropy. For more information see Ruf, T. (1999). The Lomb-Scargle periodogram + in biological rhythm research: analysis of incomplete and unequally spaced time-series. + Biological Rhythm Research, 30(2), 178-201.' + date_publication: '2024-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lomb + url_git: '' +long2lstmarray: + version: 0.2.0 + title: |- + Longitudinal Dataframes into Arrays for Machine Learning + Training + maintainer: Luis Garcez + description: |- + An easy tool to transform 2D longitudinal data into 3D arrays suitable for + Long short-term memory neural networks training. The array output can be + used by the 'keras' package. Long short-term memory neural networks are described + in: Hochreiter, S., & Schmidhuber, J. (1997) . + date_publication: '2022-11-28' + bug_reports: https://github.com/luisgarcez11/long2lstmarray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=long2lstmarray + url_git: https://github.com/luisgarcez11/long2lstmarray +LongCART: + version: '3.2' + title: |- + Recursive Partitioning for Longitudinal Data and Right Censored + Data Using Baseline Covariates + maintainer: Madan G Kundu + description: Constructs tree for continuous longitudinal data and survival data + using baseline covariates as partitioning variables according to the 'LongCART' + and 'SurvCART' algorithm, respectively. Later also included functions to calculate + conditional power and predictive power of success based on interim results and + probability of success for a prospective trial. + date_publication: '2022-05-17' + bug_reports: https://github.com/madanstat/LongCART/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LongCART + url_git: '' +longclust: + version: '1.5' + title: Model-Based Clustering and Classification for Longitudinal Data + maintainer: Paul D. McNicholas + description: Clustering or classification of longitudinal data based on a mixture + of multivariate t or Gaussian distributions with a Cholesky-decomposed covariance + structure. Details in McNicholas and Murphy (2010) and + McNicholas and Subedi (2012) . + date_publication: '2023-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longclust + url_git: '' +LongDat: + version: 1.1.3 + title: |- + A Tool for 'Covariate'-Sensitive Longitudinal Analysis on + 'omics' Data + maintainer: Chia-Yu Chen + description: |- + This tool takes longitudinal dataset as input and analyzes if there is significant + change of the features over time (a proxy for treatments), while detects and controls + for 'covariates' simultaneously. 'LongDat' is able to take in several data types as input, + including count, proportion, binary, ordinal and continuous data. The output table contains + p values, effect sizes and 'covariates' of each feature, making the downstream analysis easy. + date_publication: '2024-11-19' + bug_reports: https://github.com/CCY-dev/LongDat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LongDat + url_git: https://github.com/CCY-dev/LongDat +longevity: + version: 1.1.1 + title: Statistical Methods for the Analysis of Excess Lifetimes + maintainer: Leo Belzile + description: A collection of parametric and nonparametric methods for the analysis + of survival data. Parametric families implemented include Gompertz-Makeham, exponential + and generalized Pareto models and extended models. The package includes an implementation + of the nonparametric maximum likelihood estimator for arbitrary truncation and + censoring pattern based on Turnbull (1976) , + along with graphical goodness-of-fit diagnostics. Parametric models for positive + random variables and peaks over threshold models based on extreme value theory + are described in Rootzén and Zholud (2017) ; Belzile + et al. (2021) and Belzile et al. (2022) . + date_publication: '2024-07-19' + bug_reports: https://github.com/lbelzile/longevity/issues + url: https://lbelzile.github.io/longevity/ + url_cran: https://CRAN.R-project.org/package=longevity + url_git: '' +longit: + version: 0.1.0 + title: High Dimensional Longitudinal Data Analysis Using MCMC + maintainer: Atanu Bhattacharjee + description: |- + High dimensional longitudinal data analysis with Markov Chain Monte Carlo(MCMC). + Currently support mixed effect regression with or without missing observations by considering + covariance structures. It provides estimates by missing at random and missing not at random assumptions. + In this R package, we present Bayesian approaches that statisticians and clinical + researchers can easily use. The functions' methodology is based on the book "Bayesian Approaches in Oncology Using R and OpenBUGS" by + Bhattacharjee A (2020) . + date_publication: '2021-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longit + url_git: '' +longitudinal: + version: 1.1.13 + title: Analysis of Multiple Time Course Data + maintainer: Korbinian Strimmer + description: |- + Contains general data structures and + functions for longitudinal data with multiple variables, + repeated measurements, and irregularly spaced time points. + Also implements a shrinkage estimator of dynamical correlation + and dynamical covariance. + date_publication: '2021-11-13' + bug_reports: '' + url: https://strimmerlab.github.io/software/longitudinal/ + url_cran: https://CRAN.R-project.org/package=longitudinal + url_git: '' +longitudinalANAL: + version: '0.2' + title: Longitudinal Data Analysis + maintainer: Zhuowei Sun + description: 'Regression analysis of mixed sparse synchronous and asynchronous longitudinal + covariates. Please cite the manuscripts corresponding to this package: Sun, Z. + et al. (2023) and Liu, C. et al. (2023) .' + date_publication: '2023-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longitudinalANAL + url_git: '' +longitudinalcascade: + version: 0.3.2.6 + title: Longitudinal Cascade + maintainer: Noah Haber + description: Creates a series of sets of graphics and statistics related to the + longitudinal cascade, all included in a single object. The longitudinal cascade + inputs longitudinal data to identify gaps in the HIV and related cascades by observing + differences using time to event and survival methods. The stage definitions are + set by the user, with default standard options. Outputs include graphics, datasets, + and formal statistical tests. + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longitudinalcascade + url_git: '' +longitudinalData: + version: 2.4.7 + title: Longitudinal Data + maintainer: Christophe Genolini + description: Tools for longitudinal data and joint longitudinal data (used by packages + kml and kml3d). + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longitudinalData + url_git: '' +LongituRF: + version: '0.9' + title: Random Forests for Longitudinal Data + maintainer: Louis Capitaine + description: Random forests are a statistical learning method widely used in many + areas of scientific research essentially for its ability to learn complex relationships + between input and output variables and also its capacity to handle high-dimensional + data. However, current random forests approaches are not flexible enough to handle + longitudinal data. In this package, we propose a general approach of random forests + for high-dimensional longitudinal data. It includes a flexible stochastic model + which allows the covariance structure to vary over time. Furthermore, we introduce + a new method which takes intra-individual covariance into consideration to build + random forests. The method is fully detailled in Capitaine et.al. (2020) + Random forests for high-dimensional longitudinal data. + date_publication: '2020-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LongituRF + url_git: '' +longke: + version: 0.1.0 + title: |- + Nonparametric Predictive Model for Sparse and Irregular + Longitudinal Data + maintainer: Shixuan Wang + description: |- + The proposed method aims at predicting the longitudinal mean response trajectory by a + kernel-based estimator. The kernel estimator is constructed by imposing weights based on + subject-wise similarity on L2 metric space between predictor trajectories as well as time proximity. + Users could also perform variable selections to derive functional predictors with predictive significance + by the proposed multiplicative model with multivariate Gaussian kernels. + date_publication: '2023-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longke + url_git: '' +longmemo: + version: 1.1-3 + title: |- + Statistics for Long-Memory Processes (Book Jan Beran), and + Related Functionality + maintainer: Martin Maechler + description: |- + Datasets and Functionality from + 'Jan Beran' (1994). Statistics for Long-Memory Processes; Chapman & Hall. + Estimation of Hurst (and more) parameters for fractional Gaussian noise, + 'fARIMA' and 'FEXP' models. + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longmemo + url_git: '' +LongMemoryTS: + version: 0.1.0 + title: Long Memory Time Series + maintainer: Christian Leschinski + description: Long Memory Time Series is a collection of functions for estimation, + simulation and testing of long memory processes, spurious long memory processes + and fractionally cointegrated systems. + date_publication: '2019-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LongMemoryTS + url_git: '' +longmixr: + version: 1.0.0 + title: Longitudinal Consensus Clustering with 'flexmix' + maintainer: Jonas Hagenberg + description: |- + An adaption of the consensus clustering approach from + 'ConsensusClusterPlus' for longitudinal data. The longitudinal data is + clustered with flexible mixture models from 'flexmix', while the consensus + matrices are hierarchically clustered as in 'ConsensusClusterPlus'. By using + the flexibility from 'flexmix' and 'FactoMineR', one can use mixed data + types for the clustering. + date_publication: '2022-01-13' + bug_reports: https://github.com/cellmapslab/longmixr/issues + url: https://cellmapslab.github.io/longmixr/ + url_cran: https://CRAN.R-project.org/package=longmixr + url_git: '' +longpower: + version: 1.0.27 + title: Sample Size Calculations for Longitudinal Data + maintainer: Michael C. Donohue + description: |- + Compute power and sample size for linear models of longitudinal + data. Supported models include mixed-effects models and models fit by + generalized least squares and generalized estimating equations. The package + is described in Iddi and Donohue (2022) . Relevant + formulas are derived by Liu and Liang (1997) , + Diggle et al (2002) , and Lu, Luo, and Chen (2008) + . + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longpower + url_git: https://github.com/mcdonohue/longpower +longreadvqs: + version: 0.1.3 + title: Viral Quasispecies Comparison from Long-Read Sequencing Data + maintainer: Nakarin Pamornchainavakul + description: Performs variety of viral quasispecies diversity analyses [see Pamornchainavakul + et al. (2024) ] based on long-read sequence alignment. + Main functions include 1) sequencing error and other noise minimization and read + sampling, 2) Single nucleotide variant (SNV) profiles comparison, and 3) viral + quasispecies profiles comparison and visualization. + date_publication: '2024-08-26' + bug_reports: https://github.com/NakarinP/longreadvqs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=longreadvqs + url_git: https://github.com/NakarinP/longreadvqs +longROC: + version: '1.0' + title: |- + Time-Dependent Prognostic Accuracy with Multiply Evaluated Bio + Markers or Scores + maintainer: Alessio Farcomeni + description: Time-dependent Receiver Operating Characteristic curves, Area Under + the Curve, and Net Reclassification Indexes for repeated measures. It is based + on methods in Barbati and Farcomeni (2017) . + date_publication: '2017-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longROC + url_git: '' +longRPart2: + version: 0.2.3 + title: Recursive Partitioning of Longitudinal Data + maintainer: Ross Jacobucci + description: |- + Performs recursive partitioning of linear and nonlinear mixed effects models, + specifically for longitudinal data. The package is an + extension of the original 'longRPart' package by + Stewart and Abdolell (2013) . + date_publication: '2018-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longRPart2 + url_git: '' +longsurr: + version: '1.0' + title: Longitudinal Surrogate Marker Analysis + maintainer: Layla Parast + description: Assess the proportion of treatment effect explained by a longitudinal + surrogate marker as described in Agniel D and Parast L (2021) . + date_publication: '2022-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longsurr + url_git: '' +longurl: + version: 0.3.3 + title: Expand Short 'URLs' + maintainer: Bob Rudis + description: |- + Tools are provided to expand vectors of short URLs into long 'URLs'. + No 'API' services are used, which may mean that this operates more slowly than + 'API' services do (since they usually cache results of expansions that every + user of the service requests). You can setup your own caching layer with the + 'memoise' package if you wish to have a speedup during single sessions or add + larger dependencies, such as 'Redis', to gain a longer-term performance boost + at the expense of added complexity. + date_publication: '2020-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=longurl + url_git: '' +loo: + version: 2.8.0 + title: |- + Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian + Models + maintainer: Jonah Gabry + description: |- + Efficient approximate leave-one-out cross-validation (LOO) + for Bayesian models fit using Markov chain Monte Carlo, as + described in Vehtari, Gelman, and Gabry (2017) + . + The approximation uses Pareto smoothed importance sampling (PSIS), + a new procedure for regularizing importance weights. + As a byproduct of the calculations, we also obtain approximate + standard errors for estimated predictive errors and for the comparison + of predictive errors between models. The package also provides methods + for using stacking and other model weighting techniques to average + Bayesian predictive distributions. + date_publication: '2024-07-03' + bug_reports: https://github.com/stan-dev/loo/issues + url: https://mc-stan.org/loo/ + url_cran: https://CRAN.R-project.org/package=loo + url_git: '' +lookout: + version: 0.1.4 + title: Leave One Out Kernel Density Estimates for Outlier Detection + maintainer: Sevvandi Kandanaarachchi + description: |- + Outlier detection using leave-one-out kernel density estimates and + extreme value theory. The bandwidth for kernel density estimates is computed + using persistent homology, a technique in topological data analysis. Using + peak-over-threshold method, a generalized Pareto distribution is fitted to + the log of leave-one-out kde values to identify outliers. + date_publication: '2022-10-14' + bug_reports: '' + url: https://sevvandi.github.io/lookout/ + url_cran: https://CRAN.R-project.org/package=lookout + url_git: '' +lookup: + version: '1.0' + title: Functions Similar to VLOOKUP in Excel + maintainer: Kevin Wright + description: Simple functions to lookup items in key-value pairs. See Mehta (2021) + . + date_publication: '2021-04-14' + bug_reports: https://github.com/kwstat/lookup/issues + url: https://kwstat.github.io/lookup/ + url_cran: https://CRAN.R-project.org/package=lookup + url_git: '' +lookupTable: + version: '0.1' + title: Look-Up Tables using S4 + maintainer: Enzo Jia + description: |- + Fits look-up tables by filling entries with the mean or median values of observations + fall in partitions of the feature space. Partitions can be determined by user of the + package using input argument feature.boundaries, and dimensions of the feature space + can be any combination of continuous and categorical features provided by the data set. + A Predict function directly fetches corresponding entry value, and a default value is + defined as the mean or median of all available observations. + The table and other components are represented using the S4 class lookupTable. + date_publication: '2015-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lookupTable + url_git: '' +loon: + version: 1.4.1 + title: Interactive Statistical Data Visualization + maintainer: R. Wayne Oldford + description: An extendable toolkit for interactive data visualization and exploration. + date_publication: '2023-06-15' + bug_reports: https://github.com/great-northern-diver/loon/issues + url: https://great-northern-diver.github.io/loon/ + url_cran: https://CRAN.R-project.org/package=loon + url_git: '' +loon.data: + version: 0.1.3 + title: Data Used to Illustrate 'Loon' Functionality + maintainer: R. Wayne Oldford + description: Data used as examples in the 'loon' package. + date_publication: '2021-05-13' + bug_reports: '' + url: https://great-northern-diver.github.io/loon.data/ + url_cran: https://CRAN.R-project.org/package=loon.data + url_git: '' +loon.ggplot: + version: 1.3.4 + title: A Grammar of Interactive Graphics + maintainer: Zehao Xu + description: Provides a bridge between the 'loon' and 'ggplot2' packages. Extends + the grammar of ggplot to add clauses to create interactive 'loon' plots. Existing + ggplot(s) can be turned into interactive 'loon' plots and 'loon' plots into static + ggplot(s); the function 'loon.ggplot()' is the bridge from one plot structure + to the other. + date_publication: '2024-04-01' + bug_reports: https://github.com/great-northern-diver/loon.ggplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=loon.ggplot + url_git: '' +loon.shiny: + version: 1.0.3 + title: |- + Automatically Create a 'Shiny' App Based on Interactive 'Loon' + Widgets + maintainer: Zehao Xu + description: Package 'shiny' provides interactive web applications in R. Package + 'loon' is an interactive toolkit engaged in open-ended, creative and unscripted + data exploration. The 'loon.shiny' package can take 'loon' widgets and display + a selfsame 'shiny' app. + date_publication: '2022-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=loon.shiny + url_git: '' +loon.tourr: + version: 0.1.4 + title: Tour in 'Loon' + maintainer: Zehao Xu + description: Implement tour algorithms in interactive graphical system 'loon'. + date_publication: '2024-04-09' + bug_reports: https://github.com/z267xu/loon.tourr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=loon.tourr + url_git: '' +LoopAnalyst: + version: 1.2-7 + title: A Collection of Tools to Conduct Levins' Loop Analysis + maintainer: Alexis Dinno + description: Performs Levins' loop analysis of qualitatively-specified complex causal + systems. Loop analysis makes qualitative predictions of variable change in a system + of causally interdependent variables, where "qualitative" means direct causal + relationships and indirect causal effects are coded as sign only (i.e. increases, + decreases, no change, and ambiguous). This implementation includes output support + for graphs in .dot file format for use with visualization software such as 'graphviz' + (). 'LoopAnalyst' provides tools for the construction and + output of community matrices, computation and output of community effect matrices, + tables of correlations, adjoint, absolute feedback, weighted feedback and weighted + prediction matrices, change in life expectancy matrices, and feedback, path and + loop enumeration tools. + date_publication: '2024-04-08' + bug_reports: '' + url: https://alexisdinno.com/LoopAnalyst/ + url_cran: https://CRAN.R-project.org/package=LoopAnalyst + url_git: '' +LoopDetectR: + version: 0.1.2 + title: Comprehensive Feedback Loop Detection in ODE Models + maintainer: Katharina Baum + description: Detect feedback loops (cycles, circuits) between species (nodes) in + ordinary differential equation (ODE) models. Feedback loops are paths from a node + to itself without visiting any other node twice, and they have important regulatory + functions. Loops are reported with their order of participating nodes and their + length, and whether the loop is a positive or a negative feedback loop. An upper + limit of the number of feedback loops limits runtime (which scales with feedback + loop count). Model parametrizations and values of the modelled variables are accounted + for. Computation uses the characteristics of the Jacobian matrix as described + e.g. in Thomas and Kaufman (2002) . Input can + be the Jacobian matrix of the ODE model or the ODE function definition; in the + latter case, the Jacobian matrix is determined using 'numDeriv'. Graph-based algorithms + from 'igraph' are employed for path detection. + date_publication: '2020-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LoopDetectR + url_git: '' +LoopRig: + version: 0.1.1 + title: Integration and Analysis of Chromatin Loop Data + maintainer: Hassaan Maan + description: Common coordinate-based workflows involving processed chromatin loop + and genomic element data are considered and packaged into appropriate customizable + functions. Includes methods for linking element sets via chromatin loops and creating + consensus loop datasets. + date_publication: '2019-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LoopRig + url_git: '' +LOPART: + version: 2024.6.19 + title: Labeled Optimal Partitioning + maintainer: Toby Dylan Hocking + description: |- + Change-point detection algorithm with + label constraints and a penalty for each change outside of labels. + Read TD Hocking, A Srivastava (2023) + for details. + date_publication: '2024-06-20' + bug_reports: https://github.com/tdhock/LOPART/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LOPART + url_git: https://github.com/tdhock/LOPART +lorad: + version: 0.0.1.0 + title: Lowest Radial Distance Method of Marginal Likelihood Estimation + maintainer: Analisa Milkey + description: Estimates marginal likelihood from a posterior sample using the method + described in Wang et al. (2023) , which does not require + evaluation of any additional points and requires only the log of the unnormalized + posterior density for each sampled parameter vector. + date_publication: '2023-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lorad + url_git: '' +lordif: + version: 0.4.2 + title: |- + Logistic Ordinal Regression Differential Item Functioning using + IRT + maintainer: Seung W. Choi + description: |- + Performs analysis of Differential Item Functioning (DIF) for + dichotomous and polytomous items using an iterative hybrid of + ordinal logistic regression and item response theory (IRT) according to + Choi, Gibbons, and Crane (2011) . + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lordif + url_git: '' +lorec: + version: 0.6.1 + title: LOw Rand and sparsE Covariance matrix estimation + maintainer: Xi (Rossi) LUO + description: Estimate covariance matrices that contain low rank and sparse components + date_publication: '2014-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lorec + url_git: '' +lorem: + version: 1.0.0 + title: Generate Lorem Ipsum Text + maintainer: Garrick Aden-Buie + description: |- + Quickly generate lorem ipsum placeholder text. Easy to + integrate in RMarkdown documents. Includes an RStudio addin to insert + lorem ipsum into the current document. + date_publication: '2023-03-09' + bug_reports: https://github.com/gadenbuie/lorem/issues + url: http://pkg.garrickadenbuie.com/lorem/ + url_cran: https://CRAN.R-project.org/package=lorem + url_git: https://github.com/gadenbuie/lorem +lorentz: + version: 1.1-2 + title: The Lorentz Transform in Relativistic Physics + maintainer: Robin K. S. Hankin + description: |- + The Lorentz transform in special relativity; also the + gyrogroup structure of three-velocities. Performs active and + passive transforms and has the ability to use units in which the + speed of light is not unity. Includes some experimental + functionality for celerity and rapidity. For general relativity, + see the 'schwarzschild' package. + date_publication: '2025-01-23' + bug_reports: https://github.com/RobinHankin/lorentz/issues + url: https://robinhankin.github.io/lorentz/ + url_cran: https://CRAN.R-project.org/package=lorentz + url_git: https://github.com/RobinHankin/lorentz +lorenz: + version: 0.1.0 + title: |- + Tools for Deriving Income Inequality Estimates from Grouped + Income Data + maintainer: Andrew Carr + description: |- + Provides two methods of estimating income inequality statistics from binned income data, such as the income data provided in the Census. + These methods use different interpolation techniques to infer the distribution of incomes within income bins. One method is an implementation of + Jargowsky and Wheeler's mean-constrained integration over brackets (MCIB). The other method is based on a new technique, Lorenz interpolation, + which estimates income inequality by constructing an interpolated Lorenz curve based on the binned income data. These methods can be used to + estimate three income inequality measures: the Gini (the default measure returned), the Theil, and the Atkinson's index. + Jargowsky and Wheeler (2018) . + date_publication: '2020-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lorenz + url_git: '' +LorenzRegression: + version: 2.1.0 + title: Lorenz and Penalized Lorenz Regressions + maintainer: Alexandre Jacquemain + description: Inference for the Lorenz and penalized Lorenz regressions. More broadly, + the package proposes functions to assess inequality and graphically represent + it. The Lorenz Regression procedure is introduced in Heuchenne and Jacquemain + (2022) and in Jacquemain, A., C. Heuchenne, and + E. Pircalabelu (2024) . + date_publication: '2024-10-11' + bug_reports: https://github.com/AlJacq/LorenzRegression/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LorenzRegression + url_git: https://github.com/AlJacq/LorenzRegression +lori: + version: 2.2.3 + title: Imputation of High-Dimensional Count Data using Side Information + maintainer: Genevieve Robin + description: Analysis, imputation, and multiple imputation of count data using covariates. + LORI uses a log-linear Poisson model where main row and column effects, as well + as effects of known covariates and interaction terms can be fitted. The estimation + procedure is based on the convex optimization of the Poisson loss penalized by + a Lasso type penalty and a nuclear norm. LORI returns estimates of main effects, + covariate effects and interactions, as well as an imputed count table. The package + also contains a multiple imputation procedure. The methods are described in Robin, + Josse, Moulines and Sardy (2019) . + date_publication: '2024-11-18' + bug_reports: https://github.com/genevievelrobin/lori/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lori + url_git: '' +LorMe: + version: 1.1.0 + title: Lightening One-Code Resolving Microbial Ecology Solution + maintainer: Ningqi Wang + description: Provides a robust collection of functions tailored for microbial ecology + analysis, encompassing both data analysis and visualization. It introduces an + encapsulation feature that streamlines the process into a summary object. With + the initial configuration of this summary object, users can execute a wide range + of analyses with a single line of code, requiring only two essential parameters + for setup. The package delivers comprehensive outputs including analysis objects, + statistical outcomes, and visualization-ready data, enhancing the efficiency of + research workflows. Designed with user-friendliness in mind, it caters to both + novices and seasoned researchers, offering an intuitive interface coupled with + adaptable customization options to meet diverse analytical needs. + date_publication: '2024-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LorMe + url_git: '' +LOST: + version: 2.1.2 + title: Missing Morphometric Data Simulation and Estimation + maintainer: J. Arbour + description: |- + Functions for simulating missing morphometric + data randomly, with taxonomic bias and with anatomical bias. LOST also + includes functions for estimating linear and geometric morphometric data. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LOST + url_git: '' +lotri: + version: 1.0.0 + title: A Simple Way to Specify Symmetric, Block Diagonal Matrices + maintainer: Matthew L. Fidler + description: |- + Provides a simple mechanism to specify a symmetric block + diagonal matrices (often used for covariance matrices). This is based + on the domain specific language implemented in 'nlmixr2' but expanded + to create matrices in R generally instead of specifying parts of + matrices to estimate. It has expanded to include some matrix manipulation + functions that are generally useful for 'rxode2' and 'nlmixr2'. + date_publication: '2024-09-18' + bug_reports: https://github.com/nlmixr2/lotri/issues + url: https://nlmixr2.github.io/lotri/ + url_cran: https://CRAN.R-project.org/package=lotri + url_git: https://github.com/nlmixr2/lotri +lotterybr: + version: 0.2.0 + title: Lottery Datasets from Caixa Economica Federal + maintainer: Tomas Bernardes + description: 'A collection of functions designed to streamline the retrieval of + data from Brazilian lottery games operated by Caixa Econômica Federal, accessible + through the official website at . + Datasets for each game are conveniently stored on the GitHub page at . + Each game within this repository consists of two primary datasets: the winners + dataset and the numbers dataset. The winners dataset includes crucial information + such as the draw date, game type, potential matches, winners for each match, and + corresponding prize amounts. Meanwhile, the numbers dataset provides essential + details including the draw date, game type, and the numbers drawn during the respective + lottery event. By offering easy access to these datasets, the package facilitates + efficient data retrieval and analysis for researchers, analysts, and enthusiasts + interested in exploring the dynamics and outcomes of Brazilian lottery games.' + date_publication: '2024-06-07' + bug_reports: https://github.com/tomasbp2/lotterybr/issues + url: https://tomasbp2.github.io/lotterybr/ + url_cran: https://CRAN.R-project.org/package=lotterybr + url_git: https://github.com/tomasbp2/lotterybr +lovecraftr: + version: 1.2.0 + title: A Collection of Lovecraftian Tales and Texts + maintainer: Ruff Sergej + description: |- + A curated collection of Howard Phillips + Lovecraft's complete stories, collected for the purpose of text + analysis. + date_publication: '2024-12-14' + bug_reports: https://github.com/SergejRuff/lovecraftr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lovecraftr + url_git: https://github.com/SergejRuff/lovecraftr +lowmemtkmeans: + version: 0.1.2 + title: Low Memory Use Trimmed K-Means + maintainer: Andrew Thomas Jones + description: Performs the trimmed k-means clustering algorithm with lower memory + use. It also provides a number of utility functions such as BIC calculations. + date_publication: '2017-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lowmemtkmeans + url_git: '' +lowpassFilter: + version: 1.0-2 + title: Lowpass Filtering + maintainer: Pein Florian + description: Creates lowpass filters which are commonly used in ion channel recordings. + It supports generation of random numbers that are filtered, i.e. follow a model + for ion channel recordings, see . Furthermore, time + continuous convolutions of piecewise constant signals with the kernel of lowpass + filters can be computed. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lowpassFilter + url_git: '' +LowRankQP: + version: 1.0.6 + title: Low Rank Quadratic Programming + maintainer: John T. Ormerod + description: 'Solves quadratic programming problems where the Hessian is represented + as the product of two matrices. Thanks to Greg Hunt for helping getting this version + back on CRAN. The methods in this package are described in: Ormerod, Wand and + Koch (2008) "Penalised spline support vector classifiers: computational issues" + .' + date_publication: '2023-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LowRankQP + url_git: '' +LowWAFOMNX: + version: 1.1.1 + title: Low WAFOM Niederreiter-Xing Sequence + maintainer: Mutsuo Saito + description: |- + Implementation of Low Walsh Figure of Merit (WAFOM) sequence + based on Niederreiter-Xing sequence . + date_publication: '2017-08-25' + bug_reports: '' + url: https://mersennetwister-lab.github.io/LowWAFOMNX/ + url_cran: https://CRAN.R-project.org/package=LowWAFOMNX + url_git: '' +LowWAFOMSobol: + version: 1.1.1 + title: Low WAFOM Sobol Sequence + maintainer: Mutsuo Saito + description: |- + Implementation of Low Walsh Figure of Merit (WAFOM) sequence + based on Sobol sequence. + date_publication: '2017-08-29' + bug_reports: '' + url: https://mersennetwister-lab.github.io/LowWAFOMSobol/ + url_cran: https://CRAN.R-project.org/package=LowWAFOMSobol + url_git: '' +lpacf: + version: 1.0.1 + title: |- + Local Partial Autocorrelation Function Estimation for Locally + Stationary Wavelet Processes + maintainer: Rebecca Killick + description: Provides the method for computing the local partial autocorrelation + function for locally stationary wavelet time series from Killick, Knight, Nason, + Eckley (2020) . + date_publication: '2023-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpacf + url_git: '' +LPBkg: + version: '1.2' + title: Detecting New Signals under Background Mismodelling + maintainer: Sara Algeri + description: Given a postulated model and a set of data, the comparison density + is estimated and the deviance test is implemented in order to assess if the data + distribution deviates significantly from the postulated model. Finally, the results + are summarized in a CD-plot as described in Algeri S. (2019) . + date_publication: '2019-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPBkg + url_git: '' +lpc: + version: 1.0.2.1 + title: |- + Lassoed Principal Components for Testing Significance of + Features + maintainer: Daniela M Witten + description: Implements the LPC method of Witten&Tibshirani(Annals of Applied Statistics + 2008) for identification of significant genes in a microarray experiment. + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpc + url_git: '' +lpcde: + version: 0.1.6 + title: Boundary Adaptive Local Polynomial Conditional Density Estimator + maintainer: Rajita Chandak + description: Tools for estimation and inference of conditional densities, derivatives + and functions. This is the companion software for Cattaneo, Chandak, Jansson and + Ma (2024) . + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpcde + url_git: '' +LPCM: + version: 0.47-6 + title: Local Principal Curve Methods + maintainer: Jochen Einbeck + description: Fitting multivariate data patterns with local principal curves, including + tools for data compression (projection) and measuring goodness-of-fit; with some + additional functions for mean shift clustering. See Einbeck, Tutz and Evers (2005) + and Ameijeiras-Alonso and Einbeck (2023) . + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPCM + url_git: '' +lpda: + version: 1.0.1 + title: Linear Programming Discriminant Analysis + maintainer: Maria Jose Nueda + description: |- + Classification method obtained through linear programming. + It is advantageous with respect to the classical developments when the distribution of the variables + involved is unknown or when the number of variables is much greater than the number of individuals. + LPDA method is published in Nueda, et al. (2022) "LPDA: A new classification method based on linear programming". + . + date_publication: '2023-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpda + url_git: '' +lpdensity: + version: '2.5' + title: Local Polynomial Density Estimation and Inference + maintainer: Xinwei Ma + description: 'Without imposing stringent distributional assumptions or shape restrictions, + nonparametric estimation has been popular in economics and other social sciences + for counterfactual analysis, program evaluation, and policy recommendations. This + package implements a novel density (and derivatives) estimator based on local + polynomial regressions, documented in Cattaneo, Jansson and Ma (2022) : + lpdensity() to construct local polynomial based density (and derivatives) estimator, + and lpbwdensity() to perform data-driven bandwidth selection.' + date_publication: '2024-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpdensity + url_git: '' +LPDynR: + version: 1.0.5 + title: Land Productivity Dynamics Indicator + maintainer: Xavier Rotllan-Puig + description: |- + It uses 'phenological' and productivity-related variables derived from time series of vegetation + indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which + eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator + is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing + productivity. See www.sciencedirect.com/science/article/pii/S1470160X21010517/ for a description + of the methods used in the package to calculate the indicator. + date_publication: '2024-09-12' + bug_reports: https://github.com/xavi-rp/LPDynR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LPDynR + url_git: https://github.com/xavi-rp/LPDynR +LPGraph: + version: '2.1' + title: Nonparametric Smoothing of Laplacian Graph Spectra + maintainer: Kaijun Wang + description: |- + A nonparametric method to approximate Laplacian graph spectra of a network with + ordered vertices. This provides a computationally efficient algorithm for obtaining an + accurate and smooth estimate of the graph Laplacian basis. The approximation results can + then be used for tasks like change point detection, k-sample testing, and so on. The + primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report). + date_publication: '2020-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPGraph + url_git: '' +lphom: + version: 0.3.5-5 + title: Ecological Inference by Linear Programming under Homogeneity + maintainer: Jose M. Pavía + description: |- + Provides a bunch of algorithms based on linear programming for estimating, under + the homogeneity hypothesis, RxC ecological contingency tables (or vote transition matrices) + using mainly aggregate data (from voting units). + References: + Pavía and Romero (2022) . + Pavía (2023) . + Pavía and Romero (2024) . + Pavía (2024) A local convergent ecological inference algorithm for RxC tables. + Pavía and Penadés (2024). A bottom-up approach for ecological inference. + Romero, Pavía, Martín and Romero (2020) . + Acknowledgements: + The authors wish to thank Consellería de Educación, Universidades y Empleo, Generalitat Valenciana (grant AICO/2021/257) and Ministerio de Economía e Innovación (grant PID2021-128228NB-I00) for supporting this research. + date_publication: '2024-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lphom + url_git: '' +lpint: + version: '2.1' + title: |- + Local Polynomial Estimators of the Intensity Function and Its + Derivatives + maintainer: Feng Chen + description: Functions to estimate the intensity function and its derivative of + a given order of a multiplicative counting process using the local polynomial + method. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpint + url_git: '' +lpirfs: + version: 0.2.3 + title: Local Projections Impulse Response Functions + maintainer: Philipp Adämmer + description: |- + Provides functions to estimate and visualize linear as well as nonlinear impulse + responses based on local projections by Jordà (2005) . + The methods and the package are explained in detail in Adämmer (2019) . + date_publication: '2023-07-06' + bug_reports: https://github.com/adaemmerp/lpirfs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lpirfs + url_git: '' +LPKsample: + version: '2.1' + title: LP Nonparametric High Dimensional K-Sample Comparison + maintainer: Kaijun Wang + description: |- + LP nonparametric high-dimensional K-sample comparison method that includes + (i) confirmatory test, (ii) exploratory analysis, and (iii) options to output a + data-driven LP-transformed matrix for classification. The primary reference is + Mukhopadhyay, S. and Wang, K. (2020, Biometrika); . + date_publication: '2020-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPKsample + url_git: '' +lpl: + version: '0.11' + title: |- + Local Partial Likelihood Estimation and Simultaneous Confidence + Band + maintainer: Bingshu E. Chen + description: Local partial likelihood estimation by Fan, Lin and Zhou(2006) + and simultaneous confidence band is a set of tools to test the covariates-biomarker + interaction for survival data. Test for the covariates-biomarker interaction using + the bootstrap method and the asymptotic method with simultaneous confidence band + (Liu, Jiang and Chen (2015)). + date_publication: '2021-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpl + url_git: '' +LPM: + version: '3.2' + title: Linear Parametric Models Applied to Hydrological Series + maintainer: Corrado Tallerini + description: |- + Apply Univariate Long Memory Models, + Apply Multivariate Short Memory Models To Hydrological Dataset, + Estimate Intensity Duration Frequency curve to rainfall series. + NEW -- Calculate the monthly water requirement for herbaceous and arboreal + plants. + date_publication: '2024-06-15' + bug_reports: http://www.corradotallerini.altervista.org/Contatti.html + url: http://www.corradotallerini.altervista.org/LPM.html + url_cran: https://CRAN.R-project.org/package=LPM + url_git: '' +LPmerge: + version: '1.7' + title: Merging Linkage Maps by Linear Programming + maintainer: Jeffrey Endelman + description: Creates a consensus genetic map by merging linkage maps from different + populations. The software uses linear programming (LP) to efficiently minimize + the mean absolute error between the consensus map and the linkage maps. This + minimization is performed subject to linear inequality constraints that ensure + the ordering of the markers in the linkage maps is preserved. When marker order + is inconsistent between linkage maps, a minimum set of ordinal constraints is + deleted to resolve the conflicts. + date_publication: '2018-06-07' + bug_reports: '' + url: http://potatobreeding.cals.wisc.edu/software + url_cran: https://CRAN.R-project.org/package=LPmerge + url_git: '' +LPower: + version: 0.1.1 + title: |- + Calculates Power, Sample Size, or Detectable Effect for + Longitudinal Analyses + maintainer: David A. Schoenfeld + description: Computes power, or sample size or the detectable difference for a repeated + measures model with attrition. It requires the variance covariance matrix of the + observations but can compute this matrix for several common random effects models. + See Diggle, P, Liang, KY and Zeger, SL (1994, ISBN:9780198522843). + date_publication: '2019-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPower + url_git: '' +LPRelevance: + version: '3.3' + title: Relevance-Integrated Statistical Inference Engine + maintainer: Kaijun Wang + description: |- + Provide methods to perform customized inference at individual level by taking + contextual covariates into account. Three main functions are provided + in this package: (i) LASER(): it generates specially-designed artificial relevant + samples for a given case; (ii) g2l.proc(): computes customized fdr(z|x); and (iii) + rEB.proc(): performs empirical Bayes inference based on LASERs. The details can be + found in Mukhopadhyay, S., and Wang, K (2021, ). + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPRelevance + url_git: '' +lpridge: + version: 1.1-0 + title: Local Polynomial (Ridge) Regression + maintainer: Martin Maechler + description: Local Polynomial Regression with Ridging. + date_publication: '2023-12-08' + bug_reports: https://r-forge.r-project.org/R/?group_id=846 + url: '' + url_cran: https://CRAN.R-project.org/package=lpridge + url_git: https://curves-etc.r-forge.r-project.org/ +LPS: + version: 1.0.16 + title: |- + Linear Predictor Score, for Binary Inference from Multiple + Continuous Variables + maintainer: Sylvain Mareschal + description: An implementation of the Linear Predictor Score approach, as initiated + by Radmacher et al. (J Comput Biol 2001) and enhanced by Wright et al. (PNAS 2003) + for gene expression signatures. Several tools for unsupervised clustering of gene + expression data are also provided. + date_publication: '2021-05-29' + bug_reports: https://github.com/maressyl/R.LPS/issues + url: https://bioinformatics.ovsa.fr/LPS + url_cran: https://CRAN.R-project.org/package=LPS + url_git: '' +LPsmooth: + version: 0.1.3 + title: LP Smoothed Inference and Graphics + maintainer: Xiangyu Zhang + description: Classical tests of goodness-of-fit aim to validate the conformity of + a postulated model to the data under study. In their standard formulation, however, + they do not allow exploring how the hypothesized model deviates from the truth + nor do they provide any insight into how the rejected model could be improved + to better fit the data. To overcome these shortcomings, we establish a comprehensive + framework for goodness-of-fit which naturally integrates modeling, estimation, + inference and graphics. In this package, the deviance tests and comparison density + plots are performed to conduct the LP smoothed inference, where the letter L denotes + nonparametric methods based on quantiles and P stands for polynomials. Simulations + methods are used to perform variance estimation, inference and post-selection + adjustments. Algeri S. and Zhang X. (2020) . + date_publication: '2020-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LPsmooth + url_git: '' +lpSolve: + version: 5.6.23 + title: Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs + maintainer: Gábor Csárdi + description: |- + Lp_solve is freely available (under LGPL 2) software for + solving linear, integer and mixed integer programs. In this + implementation we supply a "wrapper" function in C and some R + functions that solve general linear/integer problems, + assignment problems, and transportation problems. This version + calls lp_solve version 5.5. + date_publication: '2024-12-14' + bug_reports: https://github.com/gaborcsardi/lpSolve/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lpSolve + url_git: https://github.com/gaborcsardi/lpSolve +lpSolveAPI: + version: 5.5.2.0-17.12 + title: R Interface to 'lp_solve' Version 5.5.2.0 + maintainer: Florian Schwendinger + description: |- + The lpSolveAPI package provides an R interface to 'lp_solve', + a Mixed Integer Linear Programming (MILP) solver with support for pure + linear, (mixed) integer/binary, semi-continuous and special ordered sets + (SOS) models. + date_publication: '2024-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lpSolveAPI + url_git: '' +LPWC: + version: 1.0.0 + title: Lag Penalized Weighted Correlation for Time Series Clustering + maintainer: Thevaa Chandereng + description: Computes a time series distance measure for clustering based on weighted + correlation and introduction of lags. The lags capture delayed responses in a + time series dataset. The timepoints must be specified. T. Chandereng, A. Gitter + (2020) . + date_publication: '2020-01-23' + bug_reports: https://github.com/gitter-lab/LPWC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LPWC + url_git: https://github.com/gitter-lab/LPWC +LqG: + version: 0.1.0 + title: |- + Robust Group Variable Screening Based on Maximum Lq-Likelihood + Estimation + maintainer: Rong Li + description: Produces a group screening procedure that is based on maximum Lq-likelihood + estimation, to simultaneously account for the group structure and data contamination + in variable screening. The methods are described in Li, Y., Li, R., Qin, Y., Lin, + C., & Yang, Y. (2021) Robust Group Variable Screening Based on Maximum Lq-likelihood + Estimation. Statistics in Medicine, 40:6818-6834.. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LqG + url_git: '' +lqmix: + version: '1.0' + title: Linear Quantile Mixture Models + maintainer: Maria Francesca Marino + description: Estimate linear quantile mixtures based on Time-Constant (TC) and/or + Time-Varying (TV), discrete, random coefficients. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lqmix + url_git: '' +lqmm: + version: 1.5.8 + title: Linear Quantile Mixed Models + maintainer: Marco Geraci + description: "Functions to fit quantile regression models for hierarchical\ndata + (2-level nested designs) as described in Geraci and\nBottai (2014, Statistics + and Computing) .\nA vignette is given in Geraci + (2014, Journal of Statistical Software)\n and included + in the package documents.\nThe packages also provides functions to fit quantile + models for\nindependent\tdata and for count responses." + date_publication: '2022-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lqmm + url_git: '' +lqr: + version: '5.2' + title: Robust Linear Quantile Regression + maintainer: Christian E. Galarza + description: It fits a robust linear quantile regression model using a new family + of zero-quantile distributions for the error term. Missing values and censored + observations can be handled as well. This family of distribution includes skewed + versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. + It also performs logistic quantile regression for bounded responses as shown in + Galarza et.al.(2020) . It provides estimates and + full inference. It also provides envelopes plots for assessing the fit and confidences + bands when several quantiles are provided simultaneously. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lqr + url_git: '' +lrd: + version: 0.1.0 + title: A Package for Processing Lexical Response Data + maintainer: Nicholas Maxwell + description: |- + Lexical response data is a package that + can be used for processing cued-recall, free-recall, + and sentence responses from memory experiments. + date_publication: '2021-12-09' + bug_reports: '' + url: https://npm27.github.io/lrd/ + url_cran: https://CRAN.R-project.org/package=lrd + url_git: '' +LREP: + version: 0.1.1 + title: Estimate and Test Exponential vs. Pareto Distributions + maintainer: Jiqiang Wu + description: The programs were developed for estimation of parameters and testing + exponential versus Pareto distribution during our work on hydrologic extremes. + See Kozubowski, T.J., A.K. Panorska, F. Qeadan, and A. Gershunov (2007) , + and Panorska, A.K., A. Gershunov, and T.J. Kozubowski (2007) . + date_publication: '2021-08-17' + bug_reports: https://github.com/jiqiaingwu/LREP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LREP + url_git: '' +lrequire: + version: 0.1.3 + title: |- + Sources an R "Module" with Caching & Encapsulation, Returning + Exported Vars + maintainer: Rick Wargo + description: |- + In the fashion of 'node.js' , requires a file, + sourcing into the current environment only the variables explicitly specified + in the module.exports or exports list variable. If the file was already sourced, + the result of the earlier sourcing is returned to the caller. + date_publication: '2016-02-22' + bug_reports: https://github.com/rickwargo/lrequire/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lrequire + url_git: https://github.com/rickwargo/lrequire +lrgs: + version: 0.5.4 + title: Linear Regression by Gibbs Sampling + maintainer: Adam Mantz + description: Implements a Gibbs sampler to do linear regression with multiple covariates, + multiple responses, Gaussian measurement errors on covariates and responses, Gaussian + intrinsic scatter, and a covariate prior distribution which is given by either + a Gaussian mixture of specified size or a Dirichlet process with a Gaussian base + distribution. Described further in Mantz (2016) . + date_publication: '2020-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lrgs + url_git: https://github.com/abmantz/lrgs +LRMF3: + version: 0.1.0 + title: Low Rank Matrix Factorization S3 Objects + maintainer: Alex Hayes + description: |- + Provides S3 classes to represent low rank matrix + decompositions. + date_publication: '2022-02-09' + bug_reports: https://github.com/RoheLab/LRMF3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LRMF3 + url_git: https://github.com/RoheLab/LRMF3 +lrstat: + version: 0.2.12 + title: |- + Power and Sample Size Calculation for Non-Proportional Hazards + and Beyond + maintainer: Kaifeng Lu + description: Performs power and sample size calculation for non-proportional hazards + model using the Fleming-Harrington family of weighted log-rank tests. The sequentially + calculated log-rank test score statistics are assumed to have independent increments + as characterized in Anastasios A. Tsiatis (1982) . + The mean and variance of log-rank test score statistics are calculated based on + Kaifeng Lu (2021) . The boundary crossing probabilities + are calculated using the recursive integration algorithm described in Christopher + Jennison and Bruce W. Turnbull (2000, ISBN:0849303168). The package can also be + used for continuous, binary, and count data. For continuous data, it can handle + missing data through mixed-model for repeated measures (MMRM). In crossover designs, + it can estimate direct treatment effects while accounting for carryover effects. + For binary data, it can design Simon's 2-stage, modified toxicity probability-2 + (mTPI-2), and Bayesian optimal interval (BOIN) trials. For count data, it can + design group sequential trials for negative binomial endpoints with censoring. + Additionally, it facilitates group sequential equivalence trials for all supported + data types. Moreover, it can design adaptive group sequential trials for changes + in sample size, error spending function, number and spacing or future looks. Finally, + it offers various options for adjusted p-values, including graphical and gatekeeping + procedures. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lrstat + url_git: '' +LRTesteR: + version: 1.2.1 + title: Likelihood Ratio Tests and Confidence Intervals + maintainer: Greg McMahan + description: |- + A collection of hypothesis tests and confidence intervals based on the likelihood ratio + . + date_publication: '2024-09-08' + bug_reports: https://github.com/gmcmacran/LRTesteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LRTesteR + url_git: https://github.com/gmcmacran/LRTesteR +LS2W: + version: 1.3.6 + title: |- + Locally Stationary Two-Dimensional Wavelet Process Estimation + Scheme + maintainer: Idris Eckley + description: Estimates two-dimensional local wavelet spectra. + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LS2W + url_git: '' +LS2Wstat: + version: 2.1-5 + title: A Multiscale Test of Spatial Stationarity for LS2W Processes + maintainer: Matt Nunes + description: Wavelet-based methods for testing stationarity and quadtree segmenting + of images, see Taylor et al (2014) . + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LS2Wstat + url_git: '' +lsa: + version: 0.73.3 + title: Latent Semantic Analysis + maintainer: Fridolin Wild + description: |- + The basic idea of latent semantic analysis (LSA) is, + that text do have a higher order (=latent semantic) structure which, + however, is obscured by word usage (e.g. through the use of synonyms + or polysemy). By using conceptual indices that are derived statistically + via a truncated singular value decomposition (a two-mode factor analysis) + over a given document-term matrix, this variability problem can be overcome. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsa + url_git: '' +LSAfun: + version: 0.7.1 + title: Applied Latent Semantic Analysis (LSA) Functions + maintainer: Fritz Guenther + description: |- + Provides functions that allow for convenient working with vector space models of semantics/distributional semantic models/word embeddings. + Originally built for LSA models (hence the name), but can be used for all such vector-based models. + For actually building a vector semantic space, use the package 'lsa' or other specialized software. + Downloadable semantic spaces can be found at . + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSAfun + url_git: '' +LSAmitR: + version: 1.0-3 + title: |- + Daten, Beispiele und Funktionen zu 'Large-Scale Assessment mit + R' + maintainer: Thomas Kiefer + description: |- + Dieses R-Paket stellt Zusatzmaterial in Form von Daten, Funktionen + und R-Hilfe-Seiten für den Herausgeberband Breit, S. und Schreiner, + C. (Hrsg.). (2016). "Large-Scale Assessment mit R: Methodische Grundlagen + der österreichischen Bildungsstandardüberprüfung." Wien: facultas. + (ISBN: 978-3-7089-1343-8, ) zur + Verfügung. + date_publication: '2022-06-01' + bug_reports: '' + url: https://www.iqs.gv.at/themen/bildungsforschung/publikationen/veroeffentlichte-publikationen + url_cran: https://CRAN.R-project.org/package=LSAmitR + url_git: '' +lsasim: + version: 2.1.6 + title: |- + Functions to Facilitate the Simulation of Large Scale Assessment + Data + maintainer: Waldir Leoncio + description: |- + Provides functions to simulate data from large-scale educational + assessments, including background questionnaire data and cognitive item + responses that adhere to a multiple-matrix sampled design. The theoretical + foundation can be found on + Matta, T.H., Rutkowski, L., Rutkowski, D. et al. (2018) + . + date_publication: '2025-01-22' + bug_reports: https://github.com/tmatta/lsasim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lsasim + url_git: '' +lsbclust: + version: '1.1' + title: Least-Squares Bilinear Clustering for Three-Way Data + maintainer: Pieter Schoonees + description: |- + Functions for performing least-squares bilinear clustering of + three-way data. The method uses the bilinear decomposition (or bi-additive + model) to model two-way matrix slices while clustering over the third way. + Up to four different types of clusters are included, one for each term of the + bilinear decomposition. In this way, matrices are clustered simultaneously on + (a subset of) their overall means, row margins, column margins and row-column + interactions. The orthogonality of the bilinear model results in separability of + the joint clustering problem into four separate ones. Three of these sub-problems + are specific k-means problems, while a special algorithm is implemented for the + interactions. Plotting methods are provided, including biplots for the low-rank + approximations of the interactions. + date_publication: '2019-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsbclust + url_git: '' +lsbs: + version: '0.1' + title: Bandwidth Selection for Level Sets and HDR Estimation + maintainer: Guangwei Weng + description: |- + Bandwidth selection for kernel density estimators of 2-d + level sets and highest density regions. It applies a plug-in + strategy to estimate the asymptotic risk function and minimize to + get the optimal bandwidth matrix. See Doss and Weng (2018) + for more detail. + date_publication: '2018-10-26' + bug_reports: '' + url: http://arxiv.org/abs/1806.00731 + url_cran: https://CRAN.R-project.org/package=lsbs + url_git: '' +LSD: + version: 4.1-0 + title: Lots of Superior Depictions + maintainer: Bjoern Schwalb + description: Create lots of colorful plots in a plethora of variations. Try the + LSD demotour(). + date_publication: '2020-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSD + url_git: '' +lsdbc: + version: 0.1.0 + title: Locally Scaled Density Based Clustering + maintainer: Fella Ulandari + description: Implementation of Locally Scaled Density Based Clustering (LSDBC) algorithm + proposed by Bicici and Yuret (2007) . This package + also contains some supporting functions such as betaCV() function and get_spectral() + function. + date_publication: '2020-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsdbc + url_git: '' +LSDinterface: + version: 1.2.2 + title: Interface Tools for LSD Simulation Results Files + maintainer: Marcelo C. Pereira + description: Interfaces R with LSD simulation models. Reads object-oriented data + in results files (.res[.gz]) produced by LSD and creates appropriate multi-dimensional + arrays in R. Supports multiple core parallel threads of multi-file data reading + for increased performance. Also provides functions to extract basic information + and statistics from data files. LSD (Laboratory for Simulation Development) is + free software developed by Marco Valente and Marcelo C. Pereira (documentation + and downloads available at ). + date_publication: '2024-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSDinterface + url_git: '' +LSDirf: + version: 0.1.3 + title: Impulse-Response Function Analysis for Agent-Based Models + maintainer: Marcelo C. Pereira + description: Performing impulse-response function (IRF) analysis of relevant variables + of agent-based simulation models, in particular for models described in 'LSD' + format. Based on the data produced by the simulation model, it performs both linear + and state-dependent IRF analysis, providing the tools required by the Counterfactual + Monte Carlo (CMC) methodology (Amendola and Pereira (2024) ), + including state identification and sensitivity. CMC proposes retrieving the causal + effect of shocks by exploiting the opportunity to directly observe the counterfactual + in a fully controlled experimental setup. 'LSD' (Laboratory for Simulation Development) + is free software available at ). + date_publication: '2024-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSDirf + url_git: '' +LSDsensitivity: + version: 1.3.0 + title: Sensitivity Analysis Tools for LSD Simulations + maintainer: Marcelo C. Pereira + description: Tools for sensitivity analysis of LSD simulation models. Reads object-oriented + data produced by LSD simulation models and performs screening and global sensitivity + analysis (Sobol decomposition method, Saltelli et al. (2008) ISBN:9780470725177). + A Kriging or polynomial meta-model (Kleijnen (2009) ) + is estimated using the simulation data to provide the data required by the Sobol + decomposition. LSD (Laboratory for Simulation Development) is free software developed + by Marco Valente and Marcelo C. Pereira (documentation and downloads available + at ). + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSDsensitivity + url_git: '' +LSE: + version: 1.0.0 + title: Constrained Least Squares and Generalized QR Factorization + maintainer: Sergio Andrés Cabrera Miranda + description: |- + The solution of equality constrained least squares problem (LSE) is + given through four analytics methods (Generalized QR Factorization, Lagrange + Multipliers, Direct Elimination and Null Space method). We expose the + orthogonal decomposition called Generalized QR Factorization (GQR) and also RQ + factorization. Finally some codes for the solution of LSE applied in + quaternions. + date_publication: '2022-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSE + url_git: https://github.com/sergio05acm/LSE +LSEbootLS: + version: 0.1.0 + title: |- + Bootstrap Methods for Regression Models with Locally Stationary + Errors + maintainer: Nicolas Loyola + description: Implements bootstrap methods for linear regression models with errors + following a time-varying process, focusing on approximating the distribution of + the least-squares estimator for regression models with locally stationary errors. + It enables the construction of bootstrap and classical confidence intervals for + regression coefficients, leveraging intensive simulation studies and real data + analysis. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSEbootLS + url_git: '' +lsei: + version: 1.3-0 + title: |- + Solving Least Squares or Quadratic Programming Problems under + Equality/Inequality Constraints + maintainer: Yong Wang + description: |- + It contains functions that solve least squares linear + regression problems under linear equality/inequality + constraints. Functions for solving quadratic programming + problems are also available, which transform such problems + into least squares ones first. It is developed based on the + 'Fortran' program of Lawson and Hanson (1974, 1995), which is + public domain and available at + . + date_publication: '2020-09-17' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~yongwang/ + url_cran: https://CRAN.R-project.org/package=lsei + url_git: '' +lsirm12pl: + version: 1.3.3 + title: Latent Space Item Response Model + maintainer: Jina Park + description: Analysis of dichotomous and continuous response data using latent factor + by both 1PL LSIRM and 2PL LSIRM as described in Jeon et al. (2021) . + It includes original 1PL LSIRM and 2PL LSIRM provided for binary response data + and its extension for continuous response data. Bayesian model selection with + spike-and-slab prior and method for dealing data with missing value under missing + at random, missing completely at random are also supported. Various diagnostic + plots are available to inspect the latent space and summary of estimated parameters. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsirm12pl + url_git: '' +lsl: + version: 0.5.6 + title: Latent Structure Learning + maintainer: Po-Hsien Huang + description: Fits structural equation modeling via penalized likelihood. + date_publication: '2017-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsl + url_git: '' +lslx: + version: 0.6.11 + title: |- + Semi-Confirmatory Structural Equation Modeling via Penalized + Likelihood or Least Squares + maintainer: Po-Hsien Huang + description: Fits semi-confirmatory structural equation modeling (SEM) via penalized + likelihood (PL) or penalized least squares (PLS). For details, please see Huang + (2020) . + date_publication: '2022-12-02' + bug_reports: https://github.com/psyphh/lslx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lslx + url_git: https://github.com/psyphh/lslx/wiki +lsm: + version: 0.2.1.4 + title: Estimation of the log Likelihood of the Saturated Model + maintainer: Jorge Villalba + description: |- + When the values of the outcome variable Y are either 0 or 1, + the function lsm() calculates the estimation of the log likelihood + in the saturated model. + This model is characterized by Llinas (2006, ISSN:2389-8976) in section 2.3 + through the assumptions 1 and 2. + The function LogLik() works (almost perfectly) when the number of independent + variables K is high, but for small K it calculates wrong values in some cases. + For this reason, when Y is dichotomous and the data are grouped in J populations, + it is recommended to use the function lsm() because it works very well for all K. + date_publication: '2024-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsm + url_git: '' +lsmeans: + version: 2.30-0 + title: Least-Squares Means + maintainer: Russell Lenth + description: |- + Obtain least-squares means for linear, generalized linear, + and mixed models. Compute contrasts or linear functions of + least-squares means, and comparisons of slopes. + Plots and compact letter displays. Least-squares means were proposed in + Harvey, W (1960) "Least-squares analysis of data with unequal subclass numbers", + Tech Report ARS-20-8, USDA National Agricultural Library, and discussed + further in Searle, Speed, and Milliken (1980) "Population marginal means + in the linear model: An alternative to least squares means", + The American Statistician 34(4), 216-221 . + NOTE: lsmeans now relies primarily on code in the 'emmeans' package. + 'lsmeans' will be archived in the near future. + date_publication: '2018-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lsmeans + url_git: '' +LSMonteCarlo: + version: '1.0' + title: American options pricing with Least Squares Monte Carlo method + maintainer: Mikhail A. Beketov + description: The package compiles functions for calculating prices of American put + options with Least Squares Monte Carlo method. The option types are plain vanilla + American put, Asian American put, and Quanto American put. The pricing algorithms + include variance reduction techniques such as Antithetic Variates and Control + Variates. Additional functions are given to derive "price surfaces" at different + volatilities and strikes, create 3-D plots, quickly generate Geometric Brownian + motion, and calculate prices of European options with Black & Scholes analytical + solution. + date_publication: '2013-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSMonteCarlo + url_git: '' +LSMRealOptions: + version: 0.2.1 + title: Value American and Real Options Through LSM Simulation + maintainer: Thomas Aspinall + description: The least-squares Monte Carlo (LSM) simulation method is a popular + method for the approximation of the value of early and multiple exercise options. + 'LSMRealOptions' provides implementations of the LSM simulation method to value + American option products and capital investment projects through real options + analysis. 'LSMRealOptions' values capital investment projects with cash flows + dependent upon underlying state variables that are stochastically evolving, providing + analysis into the timing and critical values at which investment is optimal. 'LSMRealOptions' + provides flexibility in the stochastic processes followed by underlying assets, + the number of state variables, basis functions and underlying asset characteristics + to allow a broad range of assets to be valued through the LSM simulation method. + Real options projects are further able to be valued whilst considering construction + periods, time-varying initial capital expenditures and path-dependent operational + flexibility including the ability to temporarily shutdown or permanently abandon + projects after initial investment has occurred. The LSM simulation method was + first presented in the prolific work of Longstaff and Schwartz (2001) . + date_publication: '2021-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSMRealOptions + url_git: '' +lsnstat: + version: 1.0.1 + title: '''La Societe Nouvelle'' API Access' + maintainer: Joris Blain + description: |- + Tools facilitating access to the 'macro_data' service of the + 'La Societe Nouvelle' API. It ensures an easy and fully-disclosed + access to all macro-level data used in the 'La Societe Nouvelle' + systems and the related metadata. Related API can be accessed from + . + date_publication: '2024-09-13' + bug_reports: https://github.com/La-Societe-Nouvelle/lsnstat/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=lsnstat + url_git: https://github.com/La-Societe-Nouvelle/lsnstat/ +lspartition: + version: '0.4' + title: |- + Nonparametric Estimation and Inference Procedures using + Partitioning-Based Least Squares Regression + maintainer: Yingjie Feng + description: 'Tools for statistical analysis using partitioning-based least squares + regression as described in Cattaneo, Farrell and Feng (2019a, ) + and Cattaneo, Farrell and Feng (2019b, ): lsprobust() for nonparametric + point estimation of regression functions and their derivatives and for robust + bias-corrected (pointwise and uniform) inference; lspkselect() for data-driven + selection of the IMSE-optimal number of knots; lsprobust.plot() for regression + plots with robust confidence intervals and confidence bands; lsplincom() for estimation + and inference for linear combinations of regression functions from different groups.' + date_publication: '2019-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lspartition + url_git: '' +LSPFP: + version: 1.0.3 + title: Lysate and Secretome Peptide Feature Plotter + maintainer: Gereon Poschmann + description: Creates plots of peptides from shotgun proteomics analysis of secretome + and lysate samples. These plots contain associated protein features and scores + for potential secretion and truncation. + date_publication: '2020-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSPFP + url_git: '' +lspline: + version: 1.0-0 + title: Linear Splines with Convenient Parametrisations + maintainer: Michal Bojanowski + description: |- + Linear splines with convenient parametrisations such that + (1) coefficients are slopes of consecutive segments or (2) coefficients are + slope changes at consecutive knots. Knots can be set manually or at break points + of equal-frequency or equal-width intervals covering the range of 'x'. + The implementation follows Greene (2003), chapter 7.2.5. + date_publication: '2017-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lspline + url_git: '' +lspls: + version: 0.2-2 + title: LS-PLS Models + maintainer: Bjørn-Helge Mevik + description: |- + Implements the LS-PLS (least squares - partial least squares) + method described in for instance Jørgensen, K., Segtnan, V. H., Thyholt, K., + Næs, T. (2004) "A Comparison of Methods for Analysing Regression Models with + Both Spectral and Designed Variables" + Journal of Chemometrics, 18(10), 451--464, . + date_publication: '2018-07-26' + bug_reports: https://github.com/bhmevik/lspls/issues + url: http://mevik.net/work/software/lspls.html + url_cran: https://CRAN.R-project.org/package=lspls + url_git: https://github.com/bhmevik/lspls +lsr: + version: 0.5.2 + title: Companion to "Learning Statistics with R" + maintainer: Danielle Navarro + description: |- + A collection of tools intended to make introductory + statistics easier to teach, including wrappers for common + hypothesis tests and basic data manipulation. It accompanies + Navarro, D. J. (2015). Learning Statistics with R: A Tutorial + for Psychology Students and Other Beginners, Version 0.6. + date_publication: '2021-12-01' + bug_reports: https://github.com/djnavarro/lsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lsr + url_git: https://github.com/djnavarro/lsr +LSRS: + version: 0.2.0 + title: Land Surface Remote Sensing + maintainer: Mehdi Sarparast + description: |- + Rapid satellite data streams in operational applications + have clear benefits for monitoring land cover, + especially when information can be delivered as fast as changing + surface conditions. Over the past decade, + remote sensing has become a key tool for monitoring and predicting + environmental variables by using satellite data. + This package presents the main applications in remote sensing for + land surface monitoring and land cover mapping (soil, vegetation, water...). + Tomlinson, C.J., Chapman, L., Thornes, E., Baker, C (2011) . + date_publication: '2018-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSRS + url_git: '' +lss2: + version: '1.1' + title: |- + The Accelerated Failure Time Model to Right Censored Data Based + on Least-Squares Principle + maintainer: Arvin Satwani + description: |- + Due to lack of proper inference procedure and software, + the ordinary linear regression model is seldom used in practice + for the analysis of right censored data. This paper presents an + S-Plus/R program that implements a recently developed inference + procedure (Jin, Lin and Ying, 2006) + for the accelerated failure time model based on the least-squares + principle. + date_publication: '2019-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lss2 + url_git: '' +LST: + version: 2.0.0 + title: Land Surface Temperature Retrieval for Landsat 8 + maintainer: Bappa Das + description: |- + Calculates Land Surface Temperature from Landsat band 10 and 11. + Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data. Jimenez-Munoz JC, Cristobal J, Sobrino JA, et al (2009). . + Land surface temperature retrieval from LANDSAT TM 5. Sobrino JA, Jiménez-Muñoz JC, Paolini L (2004). . + Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Srivastava PK, Majumdar TJ, Bhattacharya AK (2009). . + Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Valor E (1996). . + On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Van de Griend AA, Owe M (1993). . + Land Surface Temperature Retrieval from Landsat 8 TIRS—Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method. Yu X, Guo X, Wu Z (2014). . + Calibration and Validation of land surface temperature for Landsat8-TIRS sensor. Land product validation and evolution. Skoković D, Sobrino JA, Jimenez-Munoz JC, Soria G, Julien Y, Mattar C, Cristóbal J. (2014). + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LST + url_git: '' +LSTbook: + version: '0.6' + title: Data and Software for "Lessons in Statistical Thinking" + maintainer: Daniel Kaplan + description: |- + "Lessons in Statistical Thinking" D.T. Kaplan (2014) + + is a textbook for a first or second course in statistics that embraces + data wrangling, causal reasoning, modeling, statistical adjustment, + and simulation. 'LSTbook' supports the student-centered, tidy, + pipeline-oriented computing style featured in the book. + date_publication: '2024-12-07' + bug_reports: https://github.com/dtkaplan/LSTbook/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LSTbook + url_git: https://github.com/dtkaplan/LSTbook +LSTS: + version: '2.1' + title: Locally Stationary Time Series + maintainer: Mauricio Vargas + description: A set of functions that allow stationary analysis and locally stationary + time series analysis. + date_publication: '2021-07-29' + bug_reports: https://github.com/pachadotdev/LSTS/issues/ + url: https://pacha.dev/LSTS/ + url_cran: https://CRAN.R-project.org/package=LSTS + url_git: '' +LSVAR: + version: '1.2' + title: |- + Estimation of Low Rank Plus Sparse Structured Vector + Auto-Regressive (VAR) Model + maintainer: Peiliang Bai + description: Implementations of estimation algorithm of low rank plus sparse structured + VAR model by using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). It + relates to the algorithm in Sumanta, Li, and Michailidis (2019) . + date_publication: '2021-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSVAR + url_git: '' +LSWPlib: + version: 0.1.0 + title: |- + Simulation and Spectral Estimation of Locally Stationary Wavelet + Packet Processes + maintainer: Alessandro Cardinali + description: Library of functions for the statistical analysis and simulation of + Locally Stationary Wavelet Packet (LSWP) processes. The methods implemented by + this library are described in Cardinali and Nason (2017) . + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LSWPlib + url_git: '' +LSX: + version: 1.4.2 + title: Semi-Supervised Algorithm for Document Scaling + maintainer: Kohei Watanabe + description: |- + A word embeddings-based semi-supervised model for document scaling Watanabe (2020) . + LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove). + It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors. + date_publication: '2025-01-09' + bug_reports: https://github.com/koheiw/LSX/issues + url: https://koheiw.github.io/LSX/ + url_cran: https://CRAN.R-project.org/package=LSX + url_git: '' +ltable: + version: 2.0.4 + title: Easy to Make (Lazy) Tables + maintainer: Ocheredko Oleksandr + description: Constructs tables of counts and proportions out of data sets with possibility + to insert tables to Excel, Word, HTML, and PDF documents. Transforms tables to + data suitable for modelling. Features Gibbs sampling based log-linear (NB2) and + power analyses (original by Oleksandr Ocheredko ) for + tabulated data. + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ltable + url_git: '' +LTAR: + version: 0.1.0 + title: Tensor Forecasting Functions + maintainer: Kyle Caudle + description: A set of tools for forecasting the next step in a multidimensional + setting using tensors. In the examples, a forecast is made of sea surface temperatures + of a geographic grid (i.e. lat/long). Each observation is a matrix, the entries + in the matrix and the sea surface temperature at a particular lattitude/longitude. + Cates, J., Hoover, R. C., Caudle, K., Kopp, R., & Ozdemir, C. (2021) "Transform-Based + Tensor Auto Regression for Multilinear Time Series Forecasting" in 2021 20th IEEE + International Conference on Machine Learning and Applications (ICMLA) (pp. 461-466), + IEEE . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LTAR + url_git: '' +LTASR: + version: 0.1.4 + title: |- + Functions to Replicate the Center for Disease Control and + Prevention's 'LTAS' Software in R + maintainer: Stephen Bertke + description: |- + A suite of functions for reading in a rate file in XML format, + stratify a cohort, and calculate 'SMRs' from the stratified cohort and rate file. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LTASR + url_git: '' +LTCDM: + version: 1.0.0 + title: Latent Transition Cognitive Diagnosis Model with Covariates + maintainer: Qianru Liang + description: 'Implementation of the three-step approach of latent transition cognitive + diagnosis model (CDM) with covariates. This approach can be used to assess changes + in attribute mastery status and to evaluate the covariate effects on both the + initial states and transition probabilities over time using latent logistic regression. + Because stepwise approaches often yield biased estimates, correction for classification + error probabilities (CEPs) is considered in this approach. The three-step approach + for latent transition CDM with covariates involves the following steps: (1) fitting + a CDM to the response data without covariates at each time point separately, (2) + assigning examinees to latent states at each time point and computing the associated + CEPs, and (3) estimating the latent transition CDM with the known CEPs and computing + the regression coefficients. The method was proposed in Liang et al. (2023) + and demonstrated using mental health data in Liang et al. (in press; annotated + R code and data utilized in this example are available in Mendeley data) .' + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LTCDM + url_git: '' +lterdatasampler: + version: 0.1.1 + title: |- + Educational Dataset Examples from the Long Term Ecological + Research Program + maintainer: Allison Horst + description: Curated datasets from US Long Term Ecological Research sites. + date_publication: '2023-08-14' + bug_reports: https://github.com/lter/lterdatasampler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lterdatasampler + url_git: https://github.com/lter/lterdatasampler +lterpalettefinder: + version: 1.1.0 + title: |- + Extract Color Palettes from Photos and Pick Official LTER + Palettes + maintainer: Nicholas J Lyon + description: |- + Allows identification of palettes derived from LTER (Long Term Ecological Research) + photographs based on user criteria. + Also facilitates extraction of palettes from users' photos directly. + date_publication: '2023-01-20' + bug_reports: https://github.com/lter/lterpalettefinder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lterpalettefinder + url_git: '' +ltertools: + version: 1.2.0 + title: Tools Developed by the Long Term Ecological Research Community + maintainer: Nicholas Lyon + description: |- + Set of the data science tools created by various members of the Long Term + Ecological Research (LTER) community. These functions were initially written largely + as standalone operations and have later been aggregated into this package. + date_publication: '2025-02-21' + bug_reports: https://github.com/lter/ltertools/issues + url: https://lter.github.io/ltertools/ + url_cran: https://CRAN.R-project.org/package=ltertools + url_git: '' +LTFHPlus: + version: 2.1.2 + title: Implementation of LT-FH++ + maintainer: Emil Michael Pedersen + description: |- + Implementation of LT-FH++, an extension of + the liability threshold family history (LT-FH) model. + LT-FH++ uses a Gibbs sampler for sampling from the truncated + multivariate normal distribution and allows for + flexible family structures. LT-FH++ was first described in + Pedersen, Emil M., et al. (2022) + + as an extension to LT-FH with more flexible family structures, + and again as the age-dependent liability threshold (ADuLT) model + Pedersen, Emil M., et al. (2023) + + as an alternative to traditional time-to-event genome-wide + association studies, where family history was not considered. + date_publication: '2024-11-22' + bug_reports: https://github.com/EmilMiP/LTFHPlus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LTFHPlus + url_git: https://github.com/EmilMiP/LTFHPlus +ltm: + version: 1.2-0 + title: Latent Trait Models under IRT + maintainer: Dimitris Rizopoulos + description: Analysis of multivariate dichotomous and polytomous data using latent + trait models under the Item Response Theory approach. It includes the Rasch, the + Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and + the Generalized Partial Credit Models. + date_publication: '2022-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ltm + url_git: https://github.com/drizopoulos/ltm +ltmix: + version: 0.2.2 + title: |- + Left-Truncated Mixtures of Gamma, Weibull, and Lognormal + Distributions + maintainer: Martin Blostein + description: Mixture modelling of one-dimensional data using combinations of left-truncated + Gamma, Weibull, and Lognormal Distributions. Blostein, Martin & Miljkovic, Tatjana. + (2019) . + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ltmix + url_git: '' +ltmle: + version: 1.3-0 + title: Longitudinal Targeted Maximum Likelihood Estimation + maintainer: Joshua Schwab + description: |- + Targeted Maximum Likelihood Estimation ('TMLE') of + treatment/censoring specific mean outcome or marginal structural model for + point-treatment and longitudinal data. + date_publication: '2023-04-15' + bug_reports: https://github.com/joshuaschwab/ltmle/issues + url: http://joshuaschwab.github.io/ltmle/ + url_cran: https://CRAN.R-project.org/package=ltmle + url_git: https://github.com/joshuaschwab/ltmle +LTPDvar: + version: 1.2.1 + title: |- + LTPD and AOQL Plans for Acceptance Sampling Inspection by + Variables + maintainer: Nikola Kasprikova + description: Calculation of rectifying LTPD and AOQL plans for sampling inspection + by variables which minimize mean inspection cost per lot of process average quality. + date_publication: '2022-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LTPDvar + url_git: '' +LTRCtrees: + version: 1.1.1 + title: |- + Survival Trees to Fit Left-Truncated and Right-Censored and + Interval-Censored Survival Data + maintainer: Wenbo Jing + description: |- + Recursive partition algorithms designed for fitting survival tree with left-truncated and right censored (LTRC) data, as well as interval-censored data. + The LTRC trees can also be used to fit survival tree with time-varying covariates. + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LTRCtrees + url_git: '' +ltsa: + version: 1.4.6.1 + title: Linear Time Series Analysis + maintainer: A.I. McLeod + description: |- + Methods of developing linear time series modelling. + Methods are given for loglikelihood computation, forecasting + and simulation. + date_publication: '2024-09-18' + bug_reports: '' + url: http://www.stats.uwo.ca/faculty/aim + url_cran: https://CRAN.R-project.org/package=ltsa + url_git: '' +ltsk: + version: 1.1.2 + title: Local Time Space Kriging + maintainer: Dong Liang + description: Implements local spatial and local spatiotemporal Kriging based on + local spatial and local spatiotemporal variograms, respectively. The method is + documented in Kumar et al (2013) . + date_publication: '2024-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ltsk + url_git: '' +ltsspca: + version: 0.1.0 + title: Sparse Principal Component Based on Least Trimmed Squares + maintainer: Yixin Wang + description: Implementation of robust and sparse PCA algorithm of Wang and Van Aelst + (2019) . + date_publication: '2019-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ltsspca + url_git: '' +ltxsparklines: + version: 1.1.3 + title: Lightweight Sparklines for a LaTeX Document + maintainer: Boris Veytsman + description: |- + Sparklines are small plots (about one line of text high), + made popular by Edward Tufte. This package is the interface from R + to the LaTeX package sparklines by Andreas Loeffer and Dan Luecking + (). It can work with Sweave or + knitr or other engines that produce TeX. The package can be used to + plot vectors, matrices, data frames, time series (in ts or zoo format). + date_publication: '2022-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ltxsparklines + url_git: https://github.com/borisveytsman/ltxsparklines +luajr: + version: 0.1.8 + title: '''LuaJIT'' Scripting' + maintainer: Nicholas Davies + description: |- + An interface to 'LuaJIT' , a just-in-time + compiler for the 'Lua' scripting language . Allows + users to run 'Lua' code from 'R'. + date_publication: '2024-07-01' + bug_reports: https://github.com/nicholasdavies/luajr/issues + url: https://nicholasdavies.github.io/luajr/ + url_cran: https://CRAN.R-project.org/package=luajr + url_git: https://github.com/nicholasdavies/luajr +lubridate: + version: 1.9.4 + title: Make Dealing with Dates a Little Easier + maintainer: Vitalie Spinu + description: |- + Functions to work with date-times and time-spans: fast and + user friendly parsing of date-time data, extraction and updating of + components of a date-time (years, months, days, hours, minutes, and + seconds), algebraic manipulation on date-time and time-span objects. + The 'lubridate' package has a consistent and memorable syntax that + makes working with dates easy and fun. + date_publication: '2024-12-08' + bug_reports: https://github.com/tidyverse/lubridate/issues + url: https://lubridate.tidyverse.org + url_cran: https://CRAN.R-project.org/package=lubridate + url_git: https://github.com/tidyverse/lubridate +lubrilog: + version: 1.1.0 + title: Get Insights on 'lubridate' Operations + maintainer: Mikael Moise + description: |- + Provides a set of tools designed to enhance transparency and understanding of date-time manipulation functions from the 'lubridate' package. + It provides detailed feedback about the operations performed by 'lubridate' functions, allowing users to better comprehend and debug their code. + These insights serve as both a learning tool for newcomers and a debugging aid for programmers working with date-time data. + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lubrilog + url_git: https://github.com/arrismo/lubrilog +luca: + version: 1.0-6 + title: |- + Likelihood Inference from Case-Control Data under Covariate + Assumptions + maintainer: Ji-Hyung Shin + description: |- + Likelihood inference under covariate assumptions (LUCA) in case-control studies of a rare disease assuming independence or simple dependence of genetic and + non-genetic covariates. + date_publication: '2021-11-02' + bug_reports: '' + url: https://sfustatgen.github.io/research/luca.html + url_cran: https://CRAN.R-project.org/package=luca + url_git: '' +lucas: + version: '1.0' + title: Package to Download and Create the DB of LUCAS Data Harmonized + maintainer: Momchil Yordanov + description: Reproduces the harmonized DB of the ESTAT survey of the same name. + The survey data is served as separate spreadsheets with noticeable differences + in the collected attributes. The tool here presented carries out a series of instructions + that harmonize the attributes in terms of name, meaning, and occurrence, while + also introducing a series of new variables, instrumental to adding value to the + product. Outputs include one harmonized table with all the years, and three separate + geometries, corresponding to the theoretical point, the gps location where the + measurement was made and the 250m east-facing transect. + date_publication: '2020-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lucas + url_git: '' +lucid: + version: '1.8' + title: Printing Floating Point Numbers in a Human-Friendly Format + maintainer: Kevin Wright + description: |- + Print vectors (and data frames) of floating point numbers + using a non-scientific format optimized for human readers. Vectors + of numbers are rounded using significant digits, aligned at the + decimal point, and all zeros trailing the decimal point are dropped. + See: Wright (2016). Lucid: An R Package for Pretty-Printing Floating Point + Numbers. In JSM Proceedings, Statistical Computing Section. Alexandria, + VA: American Statistical Association. 2270-2279. + date_publication: '2021-04-16' + bug_reports: https://github.com/kwstat/lucid/issues + url: https://kwstat.github.io/lucid/ + url_cran: https://CRAN.R-project.org/package=lucid + url_git: '' +LUCIDus: + version: 3.0.3 + title: LUCID with Multiple Omics Data + maintainer: Qiran Jia + description: 'An implementation of estimating the Latent Unknown Clusters By Integrating + Multi-omics Data (LUCID) model (Peng (2019) ). + LUCID conducts integrated clustering using exposures, omics information (and outcome + information as an option). This package implements three different integration + strategies for multi-omics data analysis within the LUCID framework: LUCID early + integration (the original LUCID model), LUCID in parallel (intermediate integration), + and LUCID in serial (late integration). Automated model selection for each LUCID + model is available to obtain the optimal number of latent clusters, and an integrated + imputation approach is implemented to handle sporadic and list-wise missingness + in multi-omics data. Lasso-type regularity for exposure and omics features were + added. S3 methods for summary and plotting functions were fixed. Fixed minor bugs.' + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LUCIDus + url_git: '' +ludic: + version: 0.2.0 + title: Linkage Using Diagnosis Codes + maintainer: Boris P Hejblum + description: |- + Probabilistic record linkage without direct identifiers using only + diagnosis codes. Method is detailed in: Hejblum, Weber, Liao, Palmer, + Churchill, Szolovits, Murphy, Kohane & Cai (2019) ; + Zhang, Hejblum, Weber, Palmer, Churchill, Szolovits, Murphy, Liao, Kohane + & Cai (2021) . + date_publication: '2021-08-18' + bug_reports: https://github.com/borishejblum/ludic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ludic + url_git: '' +lue: + version: 0.2.1 + title: |- + Light Use Efficiency Model to Estimate Biomass and YIELD with + and Without Vapour Pressure Deficit + maintainer: Maninder Singh Dhillon + description: Contains LUE_BIOMASS(),LUE_BIOMASS_VPD(), LUE_YIELD() and LUE_YIELD_VPD() + to estimate aboveground biomass and crop yield firstly by calculating the Absorbed + Photosynthetically Active Radiation (APAR) and secondly the actual values of light + use efficiency with and without vapour presure deficit Shi et al.(2007) . + date_publication: '2018-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lue + url_git: '' +lulab.utils: + version: 0.0.4 + title: Supporting Functions Maintained by Zhen Lu + maintainer: Zhen Lu + description: Miscellaneous functions commonly used by LuLab. This package aims to + help more researchers on epidemiology to perform data management and visualization + more efficiently. + date_publication: '2024-10-07' + bug_reports: https://github.com/Leslie-Lu/lulab.utils/issues + url: https://leslie-lu.github.io/ + url_cran: https://CRAN.R-project.org/package=lulab.utils + url_git: '' +lulcc: + version: 1.0.4 + title: Land Use Change Modelling in R + maintainer: Simon Moulds + description: |- + Classes and methods for spatially explicit land use change + modelling in R. + date_publication: '2019-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lulcc + url_git: '' +lumberjack: + version: 1.3.1 + title: Track Changes in Data + maintainer: Mark van der Loo + description: |- + A framework that allows for easy logging of changes in data. + Main features: start tracking changes by adding a single line of code to + an existing script. Track changes in multiple datasets, using multiple + loggers. Add custom-built loggers or use loggers offered by other + packages. . + date_publication: '2023-03-29' + bug_reports: https://github.com/markvanderloo/lumberjack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lumberjack + url_git: https://github.com/markvanderloo/lumberjack +Luminescence: + version: 1.0.0 + title: Comprehensive Luminescence Dating Data Analysis + maintainer: Sebastian Kreutzer + description: |- + A collection of various R functions for the purpose of Luminescence + dating data analysis. This includes, amongst others, data import, export, + application of age models, curve deconvolution, sequence analysis and + plotting of equivalent dose distributions. + date_publication: '2025-02-21' + bug_reports: https://github.com/R-Lum/Luminescence/issues + url: https://r-lum.github.io/Luminescence/ + url_cran: https://CRAN.R-project.org/package=Luminescence + url_git: '' +lunar: + version: 0.2-1 + title: |- + Calculate Lunar Phase & Distance, Seasons and Related + Environmental Factors + maintainer: Emmanuel Lazaridis + description: |- + Provides functions to calculate lunar and other related + environmental covariates. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lunar + url_git: '' +lutz: + version: 0.3.2 + title: Look Up Time Zones of Point Coordinates + maintainer: Andy Teucher + description: |- + Input latitude and longitude values or an 'sf/sfc' POINT + object and get back the time zone in which they exist. Two methods are implemented. + One is very fast and uses 'Rcpp' in conjunction with data from the 'Javascript' library + (). This method also works outside of countries' + borders and in international waters, however speed comes at the cost of accuracy - near time + zone borders away from populated centres there is a chance that it will return the incorrect + time zone. The other method is slower but more accurate - it uses the 'sf' package to intersect + points with a detailed map of time zones from here: + . The package also + contains several utility functions for helping to understand and visualize + time zones, such as listing of world time zones, including information about + daylight savings times and their offsets from UTC. You can also plot a + time zone to visualize the UTC offset over a year and when daylight savings + times are in effect. + date_publication: '2023-10-17' + bug_reports: https://github.com/ateucher/lutz/issues + url: https://andyteucher.ca/lutz/ + url_cran: https://CRAN.R-project.org/package=lutz + url_git: https://github.com/ateucher/lutz +luz: + version: 0.4.0 + title: Higher Level 'API' for 'torch' + maintainer: Daniel Falbel + description: |- + A high level interface for 'torch' providing utilities to reduce the + the amount of code needed for common tasks, abstract away torch details and + make the same code work on both the 'CPU' and 'GPU'. It's flexible enough to + support expressing a large range of models. It's heavily inspired by 'fastai' by + Howard et al. (2020) , 'Keras' by Chollet et al. (2015) and + 'PyTorch Lightning' by Falcon et al. (2019) . + date_publication: '2023-04-17' + bug_reports: '' + url: https://mlverse.github.io/luz/ + url_cran: https://CRAN.R-project.org/package=luz + url_git: https://github.com/mlverse/luz +luzlogr: + version: 0.2.1 + title: Lightweight Logging for R Scripts + maintainer: Ben Bond-Lamberty + description: |- + Provides flexible but lightweight logging facilities for R scripts. + Supports priority levels for logs and messages, flagging messages, capturing + script output, switching logs, and logging to files or connections. + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=luzlogr + url_git: '' +LVGP: + version: 2.1.5 + title: |- + Latent Variable Gaussian Process Modeling with Qualitative and + Quantitative Input Variables + maintainer: Siyu Tao + description: |- + Fit response surfaces for datasets with latent-variable Gaussian process modeling, predict responses for new inputs, and plot latent variables locations in the latent space (only 1D or 2D). + The input variables of the datasets can be quantitative, qualitative/categorical or mixed. + The output variable of the datasets is a scalar (quantitative). + The optimization of the likelihood function is done using a successive approximation/relaxation algorithm similar to another GP modeling package "GPM". + The modeling method is published in "A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors" + by Yichi Zhang, Siyu Tao, Wei Chen, and Daniel W. Apley (2018) . The package is developed in IDEAL of Northwestern University. + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LVGP + url_git: '' +lvmcomp: + version: '1.2' + title: |- + Stochastic EM Algorithms for Latent Variable Models with a + High-Dimensional Latent Space + maintainer: Siliang Zhang + description: |- + Provides stochastic EM algorithms for latent variable models + with a high-dimensional latent space. So far, we provide functions for confirmatory item + factor analysis based on the multidimensional two parameter logistic (M2PL) model and the + generalized multidimensional partial credit model. These functions scale well for problems + with many latent traits (e.g., thirty or even more) and are virtually tuning-free. + The computation is facilitated by multiprocessing 'OpenMP' API. + For more information, please refer to: + Zhang, S., Chen, Y., & Liu, Y. (2018). An Improved Stochastic EM Algorithm for Large-scale + Full-information Item Factor Analysis. British Journal of Mathematical and Statistical + Psychology. . + date_publication: '2018-12-30' + bug_reports: https://github.com/slzhang-fd/lvmcomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=lvmcomp + url_git: https://github.com/slzhang-fd/lvmcomp +lvmisc: + version: 0.1.2 + title: Veras Miscellaneous + maintainer: Lucas Veras + description: |- + Contains a collection of useful + functions for basic data computation and manipulation, + wrapper functions for generating 'ggplot2' graphics, + including statistical model diagnostic plots, methods + for computing statistical models quality measures (such + as AIC, BIC, r squared, root mean squared error) and + general utilities. + date_publication: '2024-01-25' + bug_reports: https://github.com/verasls/lvmisc/issues + url: https://lveras.com/lvmisc/ + url_cran: https://CRAN.R-project.org/package=lvmisc + url_git: '' +lvnet: + version: 0.3.5 + title: Latent Variable Network Modeling + maintainer: Sacha Epskamp + description: 'Estimate, fit and compare Structural Equation Models (SEM) and network + models (Gaussian Graphical Models; GGM) using OpenMx. Allows for two possible + generalizations to include GGMs in SEM: GGMs can be used between latent variables + (latent network modeling; LNM) or between residuals (residual network modeling; + RNM). For details, see Epskamp, Rhemtulla and Borsboom (2017) .' + date_publication: '2019-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lvnet + url_git: '' +lvplot: + version: 0.2.1 + title: Letter Value 'Boxplots' + maintainer: Hadley Wickham + description: |- + Implements the letter value 'boxplot' which extends the + standard 'boxplot' to deal with both larger and smaller number of data + points by dynamically selecting the appropriate number of letter + values to display. + date_publication: '2022-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lvplot + url_git: '' +LW1949: + version: 1.1.0 + title: |- + An Automated Approach to Evaluating Dose-Effect Experiments + Following Litchfield and Wilcoxon (1949) + maintainer: Jean V. Adams + description: |- + The manual approach of Litchfield and Wilcoxon (1949) + + for evaluating dose-effect experiments + is automated so that the computer can do the work. + date_publication: '2017-03-20' + bug_reports: https://github.com/JVAdams/LW1949/issues + url: '' + url_cran: https://CRAN.R-project.org/package=LW1949 + url_git: https://github.com/JVAdams/LW1949 +lwc2022: + version: 1.0.0 + title: |- + Langa-Weir Classification of Cognitive Function for 2022 HRS + Data + maintainer: Cormac Monaghan + description: |- + Generates the Langa-Weir classification of cognitive function for + the 2022 Health and Retirement Study (HRS) cognition data. It is + particularly useful for researchers studying cognitive aging who wish to + work with the most recent release of HRS data. The package provides + user-friendly functions for data preprocessing, scoring, and classification + allowing users to easily apply the Langa-Weir classification system. + For details regarding the; + HRS and + Langa-Weir classifications . + date_publication: '2024-11-20' + bug_reports: https://github.com/C-Monaghan/lwc2022/issues + url: https://c-monaghan.github.io/lwc2022/ + url_cran: https://CRAN.R-project.org/package=lwc2022 + url_git: https://github.com/C-Monaghan/lwc2022 +LWFBrook90R: + version: 0.6.1 + title: |- + Simulate Evapotranspiration and Soil Moisture with the SVAT + Model LWF-Brook90 + maintainer: Paul Schmidt-Walter + description: |- + Provides a flexible and easy-to use interface for the soil vegetation + atmosphere transport (SVAT) model LWF-BROOK90, written in Fortran. + The model simulates daily transpiration, interception, soil and snow evaporation, + streamflow and soil water fluxes through a soil profile covered with vegetation, + as described in Hammel & Kennel (2001, ISBN:978-3-933506-16-0) and Federer et al. (2003) + . A set of high-level functions + for model set up, execution and parallelization provides easy access to plot-level SVAT + simulations, as well as multi-run and large-scale applications. + date_publication: '2024-10-16' + bug_reports: https://github.com/pschmidtwalter/LWFBrook90R/issues + url: https://pschmidtwalter.github.io/LWFBrook90R/ + url_cran: https://CRAN.R-project.org/package=LWFBrook90R + url_git: https://github.com/pschmidtwalter/LWFBrook90R +lwgeom: + version: 0.2-14 + title: Bindings to Selected 'liblwgeom' Functions for Simple Features + maintainer: Edzer Pebesma + description: Access to selected functions found in 'liblwgeom' , + the light-weight geometry library used by 'PostGIS' . + date_publication: '2024-02-21' + bug_reports: https://github.com/r-spatial/lwgeom/issues + url: https://r-spatial.github.io/lwgeom/ + url_cran: https://CRAN.R-project.org/package=lwgeom + url_git: https://github.com/r-spatial/lwgeom +lwqs: + version: 0.5.0 + title: Lagged Weighted Quantile Sum Regression + maintainer: Paul Curtin + description: Wrapper functions for the implementation of lagged weighted quantile + sum regression, as per 'Gennings et al' (2020) . + date_publication: '2021-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=lwqs + url_git: '' +LZeroSpikeInference: + version: 1.0.3 + title: Exact Spike Train Inference via L0 Optimization + maintainer: Sean Jewell + description: An implementation of algorithms described in Jewell and Witten (2017) + . + date_publication: '2017-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=LZeroSpikeInference + url_git: '' +lzstring: + version: 0.1.3 + title: Wrapper for 'lz-string' 'C++' Library + maintainer: Sam Parmar + description: |- + Provide access to the 'lz-string' + 'C++' library for + Lempel-Ziv (LZ) based compression and decompression of strings. + date_publication: '2024-10-21' + bug_reports: https://github.com/parmsam/lzstring-r/issues + url: https://parmsam.github.io/lzstring-r/ + url_cran: https://CRAN.R-project.org/package=lzstring + url_git: https://github.com/parmsam/lzstring-r +m2b: + version: '1.0' + title: Movement to Behaviour Inference using Random Forest + maintainer: Laurent Dubroca + description: |- + Prediction of behaviour from movement + characteristics using observation and random forest for the analyses of movement + data in ecology. + From movement information (speed, bearing...) the model predicts the + observed behaviour (movement, foraging...) using random forest. The + model can then extrapolate behavioural information to movement data + without direct observation of behaviours. + The specificity of this method relies on the derivation of multiple predictor variables from the + movement data over a range of temporal windows. This procedure allows to capture + as much information as possible on the changes and variations of movement and + ensures the use of the random forest algorithm to its best capacity. The method + is very generic, applicable to any set of data providing movement data together with + observation of behaviour. + date_publication: '2017-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=m2b + url_git: https://github.com/ldbk/m2b +m2r: + version: 1.0.2 + title: Interface to 'Macaulay2' + maintainer: David Kahle + description: |- + Persistent interface to 'Macaulay2' + and front-end tools facilitating its use in the 'R' ecosystem. For details see + Kahle et. al. (2020) . + date_publication: '2020-05-28' + bug_reports: https://github.com/coneill-math/m2r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=m2r + url_git: https://github.com/coneill-math/m2r +M2SMF: + version: '2.0' + title: |- + Multi-Modal Similarity Matrix Factorization for Integrative + Multi-Omics Data Analysis + maintainer: Xiaoyao Yin + description: |- + A new method to implement clustering from multiple modality data of certain samples, + the function M2SMF() jointly factorizes multiple similarity matrices into a shared sub-matrix + and several modality private sub-matrices, which is further used for clustering. Along with + this method, we also provide function to calculate the similarity matrix and function to + evaluate the best cluster number from the original data. + date_publication: '2019-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=M2SMF + url_git: '' +M2SMJF: + version: '1.0' + title: Multi-Modal Similarity Matrix Joint Factorization + maintainer: Xiaoyao Yin + description: |- + A new method to implement clustering from multiple modality data of certain samples, + the function M2SMjF() jointly factorizes multiple similarity matrices into a shared sub-matrix + and several modality private sub-matrices, which is further used for clustering. Along with + this method, we also provide function to calculate the similarity matrix and function to + evaluate the best cluster number from the original data. + date_publication: '2020-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=M2SMJF + url_git: '' +M3: + version: '0.4' + title: Reading M3 Files + maintainer: Jenise Swall + description: Provides functions to read in and manipulate air quality model output + from Models3-formatted files. This format is used by the Community Multiscale + Air Quality (CMAQ) model. + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=M3 + url_git: '' +M3JF: + version: 0.1.0 + title: |- + Multi-Modal Matrix Joint Factorization for Integrative + Multi-Omics Data Analysis + maintainer: Xiaoyao Yin + description: Multi modality data matrices are factorized conjointly into the multiplication + of a shared sub-matrix and multiple modality specific sub-matrices, group sparse + constraint is applied to the shared sub-matrix to capture the homogeneous and + heterogeneous information, respectively. Then the samples are classified by clustering + the shared sub-matrix with kmeanspp(), a new version of kmeans() developed here + to obtain concordant results. The package also provides the cluster number estimation + by rotation cost. Moreover, cluster specific features could be retrieved using + hypergeometric tests. + date_publication: '2023-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=M3JF + url_git: '' +m5: + version: 0.1.1 + title: '''M5 Forecasting'' Challenges Data' + maintainer: Krzysztof Joachimiak + description: |- + Contains functions, which facilitate downloading, loading and preparing data from 'M5 Forecasting' challenges (by 'University of Nicosia', hosted on 'Kaggle'). + The data itself is set of time series of different product sales in 'Walmart'. + The package also includes a ready-to-use built-in M5 subset named 'tiny_m5'. + For detailed information about the challenges, see: + Makridakis, S. & Spiliotis, E. & Assimakopoulos, V. (2020). . + date_publication: '2022-09-12' + bug_reports: https://github.com/krzjoa/m5/issues + url: https://krzjoa.github.io/m5/ + url_cran: https://CRAN.R-project.org/package=m5 + url_git: https://github.com/krzjoa/m5 +m61r: + version: 0.0.3 + title: Package About Data Manipulation in Pure Base R + maintainer: Jean-Marie Lepioufle + description: |- + Data manipulation in one package and in base R. + Minimal. No dependencies. + 'dplyr' and 'tidyr'-like in one place. + Nothing else than base R to build the package. + date_publication: '2022-05-06' + bug_reports: https://github.com/pv71u98h1/m61r/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=m61r + url_git: https://github.com/pv71u98h1/m61r/ +MAAPER: + version: 1.1.1 + title: |- + Analysis of Alternative Polyadenylation Using 3' End-Linked + Reads + maintainer: Wei Vivian Li + description: A computational method developed for model-based analysis of alternative + polyadenylation (APA) using 3' end-linked reads. It accurately assigns 3' RNA-seq + reads to polyA sites through statistical modeling, and generates multiple statistics + for APA analysis. Please also see Li WV, Zheng D, Wang R, Tian B (2021) . + date_publication: '2021-08-14' + bug_reports: '' + url: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02429-5 + url_cran: https://CRAN.R-project.org/package=MAAPER + url_git: https://github.com/Vivianstats/MAAPER +maat: + version: 1.1.0 + title: Multiple Administrations Adaptive Testing + maintainer: Seung W. Choi + description: |- + Provides an extension of the shadow-test approach to computerized adaptive + testing (CAT) implemented in the 'TestDesign' package for the assessment framework + involving multiple tests administered periodically throughout the year. This framework + is referred to as the Multiple Administrations Adaptive Testing (MAAT) and supports + multiple item pools vertically scaled and multiple phases (stages) of CAT within each test. + Between phases and tests, transitioning from one item pool (and associated constraints) + to another is allowed as deemed necessary to enhance the quality of measurement. + date_publication: '2022-05-18' + bug_reports: https://github.com/choi-phd/maat/issues/ + url: https://choi-phd.github.io/maat/ + url_cran: https://CRAN.R-project.org/package=maat + url_git: '' +mabacR: + version: 0.1.0 + title: Assisting Decision Makers + maintainer: Adam Slabadack + description: 'Easy implementation of the MABAC multi-criteria decision method, that + was introduced by Pamučar and Ćirović in the work entitled: "The selection of + transport and handling resources in logistics centers using Multi-Attributive + Border Approximation area Comparison (MABAC)" - + - which aimed to choose implements for logistics centers. This package receives + data, preferably in a spreadsheet, reads it and applies the mathematical algorithms + inherent to the MABAC method to generate a ranking with the optimal solution according + to the established criteria, weights and type of criteria. The data will be normalized, + weighted by the weights, the border area will be determined, the distances to + this border area will be calculated and finally a ranking with the optimal option + will be generated.' + date_publication: '2024-10-02' + bug_reports: https://github.com/slabaverse/mabacR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mabacR + url_git: https://github.com/slabaverse/mabacR +mable: + version: 4.1.1 + title: Maximum Approximate Bernstein/Beta Likelihood Estimation + maintainer: Zhong Guan + description: 'Fit data from a continuous population with a smooth density on finite + interval by an approximate Bernstein polynomial model which is a mixture of certain + beta distributions and find maximum approximate Bernstein likelihood estimator + of the unknown coefficients. Consequently, maximum likelihood estimates of the + unknown density, distribution functions, and more can be obtained. If the support + of the density is not the unit interval then transformation can be applied. This + is an implementation of the methods proposed by the author of this package published + in the Journal of Nonparametric Statistics: Guan (2016) + and Guan (2017) . For data with covariates, + under some semiparametric regression models such as Cox proportional hazards model + and the accelerated failure time model, the baseline survival function can be + estimated smoothly based on general interval censored data.' + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mable + url_git: '' +MABOUST: + version: 1.0.1 + title: Multi-Armed Bayesian Ordinal Utility-Based Sequential Trial + maintainer: Andrew Chapple + description: Conducts and simulates the MABOUST design, including making interim + decisions to stop a treatment for inferiority or stop the trial early for superiority + or equivalency. + date_publication: '2021-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MABOUST + url_git: '' +MacBehaviour: + version: 1.2.8 + title: Behavioural Studies of Large Language Models + maintainer: Xufeng Duan + description: Efficient way to design and conduct psychological experiments for testing + the performance of large language models. It simplifies the process of setting + up experiments and data collection via language models’ API, facilitating a smooth + workflow for researchers in the field of machine behaviour. + date_publication: '2024-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MacBehaviour + url_git: '' +macc: + version: 1.0.1 + title: Mediation Analysis of Causality under Confounding + maintainer: Yi Zhao + description: Performs causal mediation analysis under confounding or correlated + errors. This package includes a single level mediation model, a two-level mediation + model, and a three-level mediation model for data with hierarchical structures. + Under the two/three-level mediation model, the correlation parameter is identifiable + and is estimated based on a hierarchical-likelihood, a marginal-likelihood or + a two-stage method. See Zhao, Y., & Luo, X. (2014), Estimating Mediation Effects + under Correlated Errors with an Application to fMRI, for details. + date_publication: '2017-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=macc + url_git: '' +MACER: + version: 0.2.1 + title: Molecular Acquisition, Cleaning, and Evaluation in R 'MACER' + maintainer: Robert G Young + description: To assist biological researchers in assembling taxonomically and marker + focused molecular sequence data sets. 'MACER' accepts a list of genera as a user + input and uses NCBI-GenBank and BOLD as resources to download and assemble molecular + sequence datasets. These datasets are then assembled by marker, aligned, trimmed, + and cleaned. The use of this package allows the publication of specific parameters + to ensure reproducibility. The 'MACER' package has four core functions and an + example run through using all of these functions can be found in the associated + repository . + date_publication: '2022-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MACER + url_git: +MachineShop: + version: 3.8.0 + title: Machine Learning Models and Tools + maintainer: Brian J Smith + description: |- + Meta-package for statistical and machine learning with a unified + interface for model fitting, prediction, performance assessment, and + presentation of results. Approaches for model fitting and prediction of + numerical, categorical, or censored time-to-event outcomes include + traditional regression models, regularization methods, tree-based methods, + support vector machines, neural networks, ensembles, data preprocessing, + filtering, and model tuning and selection. Performance metrics are provided + for model assessment and can be estimated with independent test sets, split + sampling, cross-validation, or bootstrap resampling. Resample estimation + can be executed in parallel for faster processing and nested in cases of + model tuning and selection. Modeling results can be summarized with + descriptive statistics; calibration curves; variable importance; partial + dependence plots; confusion matrices; and ROC, lift, and other performance + curves. + date_publication: '2024-08-19' + bug_reports: https://github.com/brian-j-smith/MachineShop/issues + url: https://brian-j-smith.github.io/MachineShop/ + url_cran: https://CRAN.R-project.org/package=MachineShop + url_git: '' +macleish: + version: 0.3.9 + title: Retrieve Data from MacLeish Field Station + maintainer: Benjamin S. Baumer + description: |- + Download data from the Ada and Archibald MacLeish Field + Station in Whately, MA. The Ada + and Archibald MacLeish Field Station is a 260-acre patchwork of + forest and farmland located in West Whately, MA that provides opportunities + for faculty and students to pursue environmental research, outdoor + education, and low-impact recreation + (see for more information). + This package contains + weather data over several years, and spatial data on various man-made and + natural structures. + date_publication: '2022-07-06' + bug_reports: https://github.com/beanumber/macleish/issues + url: '' + url_cran: https://CRAN.R-project.org/package=macleish + url_git: https://github.com/beanumber/macleish +maclogp: + version: 0.1.1 + title: Measures of Uncertainty for Model Selection + maintainer: Yuanyuan Li + description: Following the common types of measures of uncertainty for parameter + estimation, two measures of uncertainty were proposed for model selection, see + Liu, Li and Jiang (2020) . The first measure is + a kind of model confidence set that relates to the variation of model selection, + called Mac. The second measure focuses on error of model selection, called LogP. + They are all computed via bootstrapping. This package provides functions to compute + these two measures. Furthermore, a similar model confidence set adapted from Bayesian + Model Averaging can also be computed using this package. + date_publication: '2021-04-22' + bug_reports: https://github.com/YuanyuanLi96/maclogp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maclogp + url_git: https://github.com/YuanyuanLi96/maclogp +macroBiome: + version: 0.4.0 + title: A Tool for Mapping the Distribution of the Biomes and Bioclimate + maintainer: Zoltán Szelepcsényi + description: |- + Procedures for simulating biomes by equilibrium vegetation + models, with a special focus on paleoenvironmental applications. + Three widely used equilibrium biome models are currently implemented in + the package: the Holdridge Life Zone (HLZ) system (Holdridge 1947, + ), the Köppen-Geiger classification + (KGC) system (Köppen 1936, + ) and the + BIOME model (Prentice et al. 1992, ). Three + climatic forest-steppe models are also implemented. + An approach for estimating monthly time series of relative sunshine + duration from temperature and precipitation data (Yin 1999, + ) is also adapted, allowing + process-based biome models to be combined with high-resolution + paleoclimate simulation datasets (e.g., CHELSA-TraCE21k v1.0 dataset: + ). + date_publication: '2024-01-16' + bug_reports: https://github.com/szelepcsenyi/macroBiome/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=macroBiome + url_git: https://github.com/szelepcsenyi/macroBiome +macrocol: + version: 0.1.0 + title: Colombian Macro-Financial Time Series Generator + maintainer: Pedro Alejandro Cabra-Acela + description: |- + This repository aims to contribute to the econometric models' production + with Colombian data, by providing a set of web-scrapping functions + of some of the main macro-financial indicators. All the sources are public and + free, but the advantage of these functions is that they directly download + and harmonize the information in R's environment. No need to import or download + additional files. You only need an internet connection! + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=macrocol + url_git: +macrosyntR: + version: 0.3.3 + title: Draw Ordered Oxford Grids and Chord Diagrams + maintainer: Sami El Hilali + description: |- + Use standard genomics file format (BED) and a table of orthologs to + illustrate synteny conservation at the genome-wide scale. + Significantly conserved linkage groups are identified as described in Simakov et al. (2020) + and displayed on an Oxford Grid (Edwards (1991) ) or a chord diagram as in Simakov et al. (2022) . + The package provides a function that uses a network-based greedy algorithm to find communities (Clauset et al. (2004) ) + and so automatically order the chromosomes on the plot to improve interpretability. + date_publication: '2023-11-14' + bug_reports: https://github.com/SamiLhll/macrosyntR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=macrosyntR + url_git: https://github.com/SamiLhll/macrosyntR +MacroZooBenthosWaterA: + version: 0.1.0 + title: Fresh Water Quality Analysis Based on Macrozoobenthos + maintainer: Donard Geci + description: 'Includes functions for calculating basic indices of macrozoobenthos + for water quality and is designed to provide researchers and environmental professionals + with a comprehensive tool for evaluating the ecological health of aquatic ecosystems.The + package is based on the following references: Paisley, M. F., Trigg, D. J. and + Walley, W. J. (2014). Arslan, N., Salur, A., Kalyoncu, H. + et al.(2016) . Hilsenhoff W.L. (1987). Hilsenhoff. + W.L. (1988) Barbour, M.T., Gerritsen, J., Snyder, B.D., and Stribling, J.B. (1999).' + date_publication: '2023-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MacroZooBenthosWaterA + url_git: '' +mactivate: + version: 0.6.6 + title: Multiplicative Activation + maintainer: Dave Zes + description: Provides methods and classes for adding m-activation ("multiplicative + activation") layers to MLR or multivariate logistic regression models. M-activation + layers created in this library detect and add input interaction (polynomial) effects + into a predictive model. M-activation can detect high-order interactions -- a + traditionally non-trivial challenge. Details concerning application, methodology, + and relevant survey literature can be found in this library's vignette, "About." + date_publication: '2021-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mactivate + url_git: '' +maczic: + version: 1.0.0 + title: Mediation Analysis for Count and Zero-Inflated Count Data + maintainer: Nancy Cheng + description: |- + Performs causal mediation analysis for count and zero-inflated + count data without or with a post-treatment confounder; calculates power + to detect prespecified causal mediation effects, direct effects, and + total effects; performs sensitivity analysis when there is a treatment- + induced mediator-outcome confounder as described by Cheng, J., Cheng, N.F., + Guo, Z., Gregorich, S., Ismail, A.I., Gansky, S.A. (2018) + . Implements Instrumental Variable (IV) + method to estimate the controlled (natural) direct and mediation effects, + and compute the bootstrap Confidence Intervals as described by Guo, Z., + Small, D.S., Gansky, S.A., Cheng, J. (2018) . This + software was made possible by Grant R03DE028410 from the National + Institute of Dental and Craniofacial Research, a component of the National + Institutes of Health. + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maczic + url_git: '' +MAd: + version: 0.8-3 + title: Meta-Analysis with Mean Differences + maintainer: AC Del Re + description: "A collection of functions for conducting a meta-analysis with mean + differences data. It uses recommended procedures as\tdescribed in The \tHandbook + of Research Synthesis and Meta-Analysis\t(Cooper, Hedges, & Valentine, 2009)." + date_publication: '2022-08-06' + bug_reports: '' + url: https://www.acdelre.com + url_cran: https://CRAN.R-project.org/package=MAd + url_git: '' +mada: + version: 0.5.11 + title: Meta-Analysis of Diagnostic Accuracy + maintainer: Philipp Doebler + description: Provides functions for diagnostic meta-analysis. Next to basic analysis + and visualization the bivariate Model of Reitsma et al. (2005) that is equivalent + to the HSROC of Rutter & Gatsonis (2001) can be fitted. A new approach based to + diagnostic meta-analysis of Holling et al. (2012) is also available. Standard + methods like summary, plot and so on are provided. + date_publication: '2022-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mada + url_git: r-forge.r-project.org/projects/mada/ +MadanText: + version: 0.1.0 + title: |- + Persian Text Mining Tool for Frequency Analysis, Statistical + Analysis, and Word Clouds + maintainer: Kido Ishikawa + description: |- + This is an open-source software designed specifically for text mining in the Persian language. It allows users to examine word frequencies, download data for analysis, and generate word clouds. This tool is particularly useful for researchers and analysts working with Persian language data. + This package mainly makes use of the 'PersianStemmer' (Safshekan, R., et al. (2019). ), + 'udpipe' (Wijffels, J., et al. (2023). ), + and 'shiny' (Chang, W., et al. (2023). ) packages. + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MadanText + url_git: '' +MadanTextNetwork: + version: 0.1.0 + title: Persian Text Mining Tool for Co-Occurrence Network + maintainer: Kido Ishikawa + description: |- + Provides an extension to 'MadanText' for creating and analyzing co-occurrence networks in Persian text data. + This package mainly makes use of the 'PersianStemmer' (Safshekan, R., et al. (2019). ), + 'udpipe' (Wijffels, J., et al. (2023). ), + and 'shiny' (Chang, W., et al. (2023). ) packages. + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MadanTextNetwork + url_git: '' +maddison: + version: '0.2' + title: The Maddison Project Database + maintainer: Eric Persson + description: |- + Contains the Maddison Project 2018 database, which provides + estimates of GDP per capita for all countries in the world between AD 1 and + 2016. See for more information. + date_publication: '2022-05-01' + bug_reports: https://github.com/expersso/maddison/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maddison + url_git: https://www.rug.nl/ggdc/historicaldevelopment/maddison/https://github.com/expersso/maddison +madgrad: + version: 0.1.0 + title: '''MADGRAD'' Method for Stochastic Optimization' + maintainer: Daniel Falbel + description: |- + A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic + Optimization algorithm. MADGRAD is a 'best-of-both-worlds' optimizer with the + generalization performance of stochastic gradient descent and at least as fast + convergence as that of Adam, often faster. A drop-in optim_madgrad() implementation + is provided based on Defazio et al (2020) . + date_publication: '2021-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=madgrad + url_git: '' +maditr: + version: 0.8.5 + title: |- + Fast Data Aggregation, Modification, and Filtering with Pipes + and 'data.table' + maintainer: Gregory Demin + description: |- + Provides pipe-style interface for 'data.table'. Package preserves all 'data.table' features without + significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data + manipulation tasks. For example, you can write 'take(mtcars, mean(mpg), by = am)' for aggregation or + 'let(mtcars, hp_wt = hp/wt, hp_wt_mpg = hp_wt/mpg)' for modification. Use 'take_if/let_if' for conditional + aggregation/modification. Additionally there are some conveniences such as automatic 'data.frame' + conversion to 'data.table'. + date_publication: '2024-11-11' + bug_reports: https://github.com/gdemin/maditr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maditr + url_git: https://github.com/gdemin/maditr +MADMMplasso: + version: 1.0.0 + title: Multi Variate Multi Response ADMM with Interaction Effects + maintainer: Waldir Leoncio + description: |- + This system allows one to model a multi-variate, multi-response + problem with interaction effects. It combines the usual squared error loss + for the multi-response problem with some penalty terms to encourage + responses that correlate to form groups and also allow for modeling main and + interaction effects that exit within the covariates. + The optimization method employed is the Alternating Direction Method of + Multipliers (ADMM). The implementation is based on the methodology + presented on Quachie Asenso, T., & Zucknick, M. (2023) + . + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MADMMplasso + url_git: '' +madness: + version: 0.2.8 + title: Automatic Differentiation of Multivariate Operations + maintainer: Steven E. Pav + description: |- + An object that supports automatic differentiation + of matrix- and multidimensional-valued functions with + respect to multidimensional independent variables. + Automatic differentiation is via 'forward accumulation'. + date_publication: '2023-08-21' + bug_reports: https://github.com/shabbychef/madness/issues + url: '' + url_cran: https://CRAN.R-project.org/package=madness + url_git: https://github.com/shabbychef/madness +MADPop: + version: 1.1.7 + title: MHC Allele-Based Differencing Between Populations + maintainer: Martin Lysy + description: |- + Tools for the analysis of population differences + using the Major Histocompatibility Complex (MHC) genotypes of samples + having a variable number of alleles (1-4) recorded for each + individual. A hierarchical Dirichlet-Multinomial model on the + genotype counts is used to pool small samples from multiple + populations for pairwise tests of equality. Bayesian inference is + implemented via the 'rstan' package. Bootstrapped and posterior + p-values are provided for chi-squared and likelihood ratio tests of + equal genotype probabilities. + date_publication: '2024-02-27' + bug_reports: https://github.com/mlysy/MADPop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MADPop + url_git: https://github.com/mlysy/MADPop +madr: + version: 1.0.0 + title: Model Averaged Double Robust Estimation + maintainer: Matthew Cefalu + description: Estimates average treatment effects using model average double robust + (MA-DR) estimation. The MA-DR estimator is defined as weighted average of double + robust estimators, where each double robust estimator corresponds to a specific + choice of the outcome model and the propensity score model. The MA-DR estimator + extend the desirable double robustness property by achieving consistency under + the much weaker assumption that either the true propensity score model or the + true outcome model be within a specified, possibly large, class of models. + date_publication: '2016-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=madr + url_git: '' +madrat: + version: 3.15.6 + title: May All Data be Reproducible and Transparent (MADRaT) * + maintainer: Jan Philipp Dietrich + description: |- + Provides a framework which should improve reproducibility and + transparency in data processing. It provides functionality such as + automatic meta data creation and management, rudimentary quality + management, data caching, work-flow management and data aggregation. + * The title is a wish not a promise. By no means we expect this + package to deliver everything what is needed to achieve full + reproducibility and transparency, but we believe that it supports + efforts in this direction. + date_publication: '2024-12-19' + bug_reports: https://github.com/pik-piam/madrat/issues + url: https://doi.org/10.5281/zenodo.1115490 + url_cran: https://CRAN.R-project.org/package=madrat + url_git: https://github.com/pik-piam/madrat +madshapR: + version: 1.1.0 + title: |- + Support Technical Processes Following 'Maelstrom Research' + Standards + maintainer: Guillaume Fabre + description: |- + Functions to support rigorous processes in data cleaning, + evaluation, and documentation across datasets from different studies based + on Maelstrom Research guidelines. The package includes the core functions + to evaluate and format the main inputs that define the process, diagnose + errors, and summarize and evaluate datasets and their associated + data dictionaries. The main outputs are clean datasets and associated + metadata, and tabular and visual summary reports. As described in + Maelstrom Research guidelines for rigorous retrospective data + harmonization (Fortier I and al. (2017) ). + date_publication: '2024-04-23' + bug_reports: https://github.com/maelstrom-research/madshapR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=madshapR + url_git: https://github.com/maelstrom-research/madshapR +madsim: + version: 1.2.1 + title: A Flexible Microarray Data Simulation Model + maintainer: Doulaye Dembele + description: |- + This function allows to generate two biological conditions synthetic + microarray dataset which has similar behavior to those currently + observed with common platforms. User provides a subset of parameters. + Available default parameters settings can be modified. + date_publication: '2016-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=madsim + url_git: '' +maestro: + version: 0.5.1 + title: Orchestration of Data Pipelines + maintainer: Will Hipson + description: Framework for creating and orchestrating data pipelines. Organize, + orchestrate, and monitor multiple pipelines in a single project. Use tags to decorate + functions with scheduling parameters and configuration. + date_publication: '2025-02-19' + bug_reports: https://github.com/whipson/maestro/issues + url: https://whipson.github.io/maestro/ + url_cran: https://CRAN.R-project.org/package=maestro + url_git: https://github.com/whipson/maestro +Maeswrap: + version: '1.7' + title: Wrapper Functions for MAESTRA/MAESPA + maintainer: Remko Duursma + description: A bundle of functions for modifying MAESTRA/MAESPA input files,reading + output files, and visualizing the stand in 3D. Handy for running sensitivity analyses, + scenario analyses, etc. + date_publication: '2015-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Maeswrap + url_git: '' +mafR: + version: 1.1.6 + title: Interface for Masked Autoregressive Flows + maintainer: François Rousset + description: Interfaces the Python library 'zuko' implementing Masked Autoregressive + Flows. See Rozet, Divo and Schnake (2023) and Papamakarios, + Pavlakou and Murray (2017) . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mafR + url_git: https://github.com/f-rousset/mafR +magclass: + version: 6.13.2 + title: Data Class and Tools for Handling Spatial-Temporal Data + maintainer: Jan Philipp Dietrich + description: |- + Data class for increased interoperability working with + spatial-temporal data together with corresponding functions and + methods (conversions, basic calculations and basic data manipulation). + The class distinguishes between spatial, temporal and other dimensions + to facilitate the development and interoperability of tools build for + it. Additional features are name-based addressing of data and internal + consistency checks (e.g. checking for the right data order in + calculations). + date_publication: '2024-01-19' + bug_reports: https://github.com/pik-piam/magclass/issues + url: https://doi.org/10.5281/zenodo.1158580 + url_cran: https://CRAN.R-project.org/package=magclass + url_git: https://github.com/pik-piam/magclass +MAGEE: + version: 1.4.2 + title: Mixed Model Association Test for GEne-Environment Interaction + maintainer: Han Chen + description: Use a 'glmmkin' class object (GMMAT package) from the null model to + perform generalized linear mixed model-based single-variant and variant set main + effect tests, gene-environment interaction tests, and joint tests for association, + as proposed in Wang et al. (2020) . + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAGEE + url_git: '' +magi: + version: 1.2.4 + title: MAnifold-Constrained Gaussian Process Inference + maintainer: Shihao Yang + description: |- + Provides fast and accurate inference for the parameter estimation problem in Ordinary Differential + Equations, including the case when there are unobserved system components. Implements the MAGI method + (MAnifold-constrained Gaussian process Inference) of Yang, Wong, and Kou (2021) . + A user guide is provided by the accompanying software paper Wong, Yang, and Kou (2024) . + date_publication: '2024-06-22' + bug_reports: '' + url: https://doi.org/10.18637/jss.v109.i04 + url_cran: https://CRAN.R-project.org/package=magi + url_git: '' +magic: + version: 1.6-1 + title: Create and Investigate Magic Squares + maintainer: Robin K. S. Hankin + description: |- + A collection of functions for the manipulation and + analysis of arbitrarily dimensioned arrays. The original motivation + for the package was the development of efficient, vectorized + algorithms for the creation and investigation of magic squares and + high-dimensional magic hypercubes. + date_publication: '2022-11-16' + bug_reports: https://github.com/RobinHankin/magic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=magic + url_git: https://github.com/RobinHankin/magic +magicaxis: + version: 2.4.5 + title: |- + Pretty Scientific Plotting with Minor-Tick and Log Minor-Tick + Support + maintainer: Aaron Robotham + description: Functions to make useful (and pretty) plots for scientific plotting. + Additional plotting features are added for base plotting, with particular emphasis + on making attractive log axis plots. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=magicaxis + url_git: '' +magicfor: + version: 0.1.0 + title: Magic Functions to Obtain Results from for Loops + maintainer: Koji Makiyama + description: Magic functions to obtain results from for loops. + date_publication: '2016-12-18' + bug_reports: https://github.com/hoxo-m/magicfor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=magicfor + url_git: https://github.com/hoxo-m/magicfor +magick: + version: 2.8.5 + title: Advanced Graphics and Image-Processing in R + maintainer: Jeroen Ooms + description: |- + Bindings to 'ImageMagick': the most comprehensive open-source image + processing library available. Supports many common formats (png, jpeg, tiff, + pdf, etc) and manipulations (rotate, scale, crop, trim, flip, blur, etc). + All operations are vectorized via the Magick++ STL meaning they operate either + on a single frame or a series of frames for working with layers, collages, + or animation. In RStudio images are automatically previewed when printed to + the console, resulting in an interactive editing environment. The latest + version of the package includes a native graphics device for creating + in-memory graphics or drawing onto images using pixel coordinates. + date_publication: '2024-09-20' + bug_reports: https://github.com/ropensci/magick/issues + url: https://docs.ropensci.org/magick/https://ropensci.r-universe.dev/magick + url_cran: https://CRAN.R-project.org/package=magick + url_git: '' +magickGUI: + version: 1.3.1 + title: GUI Tools for Interactive Image Processing with 'magick' + maintainer: Shota Ochi + description: Enables us to use the functions of the package 'magick' interactively. + date_publication: '2023-09-11' + bug_reports: https://github.com/ShotaOchi/magickGUI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=magickGUI + url_git: https://github.com/ShotaOchi/magickGUI +magicLamp: + version: 0.1.0 + title: '''WeMo Switch'' Smart Plug Utilities' + maintainer: Simon Garnier + description: |- + Set of utility functions to interact with 'WeMo Switch', a smart + plug that can be remotely controlled via wifi. The provided functions make + it possible to turn one or more 'WeMo Switch' plugs on and off in a + scriptable fashion. More information about 'WeMo Switch' can be found at + . + date_publication: '2017-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=magicLamp + url_git: https://github.com/swarm-lab/magicLamp +MAGMA.R: + version: 1.0.3 + title: MAny-Group MAtching + maintainer: Julian Urban + description: |- + Balancing quasi-experimental field research for effects of covariates is fundamental for drawing causal inference. Propensity Score Matching deals with this issue but current + techniques are restricted to binary treatment variables. Moreover, they provide several solutions without providing a comprehensive framework on choosing the best model. The + MAGMA R-package addresses these restrictions by offering nearest neighbor matching for two to four groups. It also includes the option to match data of a 2x2 design. In addition, + MAGMA includes a framework for evaluating the post-matching balance. The package includes functions for the matching process and matching reporting. We provide a tutorial on + MAGMA as vignette. More information on MAGMA can be found in Feuchter, M. D., Urban, J., Scherrer V., Breit, M. L., and Preckel F. (2022) . + date_publication: '2024-08-27' + bug_reports: https://github.com/JulianUrban/MAGMA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MAGMA.R + url_git: '' +MagmaClustR: + version: 1.2.1 + title: |- + Clustering and Prediction using Multi-Task Gaussian Processes + with Common Mean + maintainer: Arthur Leroy + description: |- + An implementation for the multi-task Gaussian processes with common + mean framework. Two main algorithms, called 'Magma' and 'MagmaClust', + are available to perform predictions for supervised learning problems, in + particular for time series or any functional/continuous data applications. + The corresponding articles has been respectively proposed by Arthur Leroy, + Pierre Latouche, Benjamin Guedj and Servane Gey (2022) + , and Arthur Leroy, Pierre Latouche, + Benjamin Guedj and Servane Gey (2023) . + Theses approaches leverage the learning of cluster-specific mean processes, + which are common across similar tasks, to provide enhanced prediction + performances (even far from data) at a linear computational cost (in + the number of tasks). 'MagmaClust' is a generalisation of 'Magma' + where the tasks are simultaneously clustered into groups, each being + associated to a specific mean process. User-oriented functions in the + package are decomposed into training, prediction and plotting + functions. Some basic features (classic kernels, training, prediction) of + standard Gaussian processes are also implemented. + date_publication: '2024-06-28' + bug_reports: https://github.com/ArthurLeroy/MagmaClustR/issues + url: https://arthurleroy.github.io/MagmaClustR/ + url_cran: https://CRAN.R-project.org/package=MagmaClustR + url_git: https://github.com/ArthurLeroy/MagmaClustR +magmaR: + version: 1.0.3 + title: R-Client for Interacting with the 'UCSF Data Library' + maintainer: Daniel Bunis + description: |- + A client for interacting with 'magma', the data warehouse of the + 'UCSF Data Library'. 'magmaR' includes functions for querying and + downloading data from 'magma', in order to enable working with such data in + R, as well as for uploading local data to 'magma'. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=magmaR + url_git: '' +MAGNAMWAR: + version: 2.0.4 + title: A Pipeline for Meta-Genome Wide Association + maintainer: John Chaston + description: |- + Correlates variation within the meta-genome to target species + phenotype variations in meta-genome with association studies. Follows + the pipeline described in Chaston, J.M. et al. (2014) . + date_publication: '2018-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAGNAMWAR + url_git: '' +magree: + version: '1.2' + title: |- + Implements the O'Connell-Dobson-Schouten Estimators of Agreement + for Multiple Observers + maintainer: Mark Clements + description: Implements an interface to the legacy Fortran code from O'Connell and + Dobson (1984) . Implements Fortran 77 code for the methods + developed by Schouten (1982) . Includes + estimates of average agreement for each observer and average agreement for each + subject. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=magree + url_git: '' +magrittr: + version: 2.0.3 + title: A Forward-Pipe Operator for R + maintainer: Lionel Henry + description: |- + Provides a mechanism for chaining commands with a new + forward-pipe operator, %>%. This operator will forward a value, or the + result of an expression, into the next function call/expression. + There is flexible support for the type of right-hand side expressions. + For more information, see package vignette. To quote Rene Magritte, + "Ceci n'est pas un pipe." + date_publication: '2022-03-30' + bug_reports: https://github.com/tidyverse/magrittr/issues + url: https://magrittr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=magrittr + url_git: https://github.com/tidyverse/magrittr +maGUI: + version: '4.0' + title: |- + A Graphical User Interface for Microarray Data Analysis and + Annotation + maintainer: Dhammapal Bharne + description: Provides a comprehensive graphical user interface for analysis of Affymetrix, + Agilent, Illumina, Nimblegen and other microarray data. It can perform miscellaneous + tasks such as gene set enrichment and test analyses, identifying gene symbols + and building co-expression network. It can also estimate sample size for atleast + two-fold expression change. The current version is its slenderized form for compatable + and flexible implementation. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maGUI + url_git: '' +maic: + version: 0.1.4 + title: Matching-Adjusted Indirect Comparison + maintainer: Rob Young + description: |- + A generalised workflow for generation of subject weights to be + used in Matching-Adjusted Indirect Comparison (MAIC) per Signorovitch et + al. (2012) , Signorovitch et al (2010) + . In MAIC, unbiased + comparison between outcomes of two trials is facilitated by weighting the + subject-level outcomes of one trial with weights derived such that the + weighted aggregate measures of the prognostic or effect modifying variables + are equal to those of the sample in the comparator trial. The functions and + classes included in this package wrap and abstract the process demonstrated + in the UK National Institute for Health and Care Excellence Decision + Support Unit (NICE DSU)'s example (Phillippo et al, (2016) [see URL]), + providing a repeatable and easily specifiable workflow for producing + multiple comparison variable sets against a variety of target studies, with + preprocessing for a number of aggregate target forms (e.g. mean, median, + domain limits). + date_publication: '2022-04-27' + bug_reports: '' + url: https://nicedsu.sites.sheffield.ac.uk/tsds/population-adjusted-indirect-comparisons-maic-and-stc + url_cran: https://CRAN.R-project.org/package=maic + url_git: https://github.com/heorltd/maic +maicChecks: + version: 0.1.2 + title: |- + Assessing the Numerical Feasibility for Conducting a + Matching-Adjusted Indirect Comparison (MAIC) + maintainer: Lillian Yau + description: A collection of easy-to-implement tools for checking whether a MAIC + can be conducted. An alternative way of calculating weights is also included. + These methods are introduced in Glimm & Yau (2021) . + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maicChecks + url_git: '' +maicplus: + version: 0.1.2 + title: Matching Adjusted Indirect Comparison + maintainer: Isaac Gravestock + description: |- + Facilitates performing matching adjusted indirect comparison + (MAIC) analysis where the endpoint of interest is either time-to-event + (e.g. overall survival) or binary (e.g. objective tumor response). The method + is described by Signorovitch et al (2012) . + date_publication: '2025-02-21' + bug_reports: https://github.com/hta-pharma/maicplus/issues + url: https://hta-pharma.github.io/maicplus/ + url_cran: https://CRAN.R-project.org/package=maicplus + url_git: https://github.com/hta-pharma/maicplus/ +MAICtools: + version: 0.1.1 + title: Performing Matched-Adjusted Indirect Comparisons (MAIC) + maintainer: Xiao Qi + description: |- + A generalised workflow for Matching-Adjusted Indirect + Comparison (MAIC) analysis, which supports both anchored and + non-anchored MAIC methods. In MAIC, unbiased trial outcome comparison + is achieved by weighting the subject-level outcomes of the + intervention trial so that the weighted aggregate measures of + prognostic or effect-modifying variables match those of the comparator + trial. Measurements supported include time-to-event (e.g., overall + survival) and binary (e.g., objective tumor response). The method is + described in Signorovitch et al. (2010) + and Signorovitch et al. (2012) + . + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAICtools + url_git: '' +mailchimpR: + version: 0.1.0 + title: Get Mailchimp Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Mailchimp using + the 'Windsor.ai' API . + date_publication: '2022-11-11' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=mailchimpR + url_git: '' +mailmerge: + version: 0.2.5 + title: Mail Merge Using R Markdown Documents and 'gmailr' + maintainer: Andrie de Vries + description: |- + Perform a mail merge (mass email) using the message defined in + markdown, the recipients in a 'csv' file, and gmail as the mailing engine. + With this package you can parse markdown documents as the body of email, and + the 'yaml' header to specify the subject line of the email. Any '{}' braces + in the email will be encoded with 'glue::glue()'. You can preview the email + in the RStudio viewer pane, and send (draft) email using 'gmailr'. + date_publication: '2022-08-14' + bug_reports: https://github.com/andrie/mailmerge/issues + url: https://andrie.github.io/mailmerge/ + url_cran: https://CRAN.R-project.org/package=mailmerge + url_git: https://github.com/andrie/mailmerge +mailR: + version: '0.8' + title: A Utility to Send Emails from R + maintainer: Rahul Premraj + description: |- + Interface to Apache Commons Email to send emails + from R. + date_publication: '2021-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mailR + url_git: https://github.com/rpremrajGit/mailR +mailtoR: + version: 0.1.0 + title: Creates a Friendly User Interface for Emails Sending in 'shiny' + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to generate a friendly user interface for emails sending. + The user can choose from the most popular free email services ('Gmail', 'Outlook', 'Yahoo') and his default email application. + The package is a wrapper for the 'Mailtoui' 'JavaScript' library. See for more information. + date_publication: '2020-06-25' + bug_reports: https://github.com/feddelegrand7/mailtoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mailtoR + url_git: https://github.com/feddelegrand7/mailtoR +MainExistingDatasets: + version: 1.0.2 + title: Main Existing Human Datasets + maintainer: Etienne Camenen + description: |- + Shiny for Open Science to visualize, share, and inventory the + main existing human datasets for researchers. + date_publication: '2023-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MainExistingDatasets + url_git: '' +MAINT.Data: + version: 2.7.1 + title: Model and Analyse Interval Data + maintainer: Pedro Duarte Silva + description: |- + Implements methodologies for modelling interval data by Normal + and Skew-Normal distributions, considering appropriate parameterizations of + the variance-covariance matrix that takes into account the intrinsic nature of + interval data, and lead to four different possible configuration structures. + The Skew-Normal parameters can be estimated by maximum likelihood, while Normal + parameters may be estimated by maximum likelihood or robust trimmed maximum + likelihood methods. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAINT.Data + url_git: '' +MajKMeans: + version: 0.1.0 + title: k-Means Algorithm with a Majorization-Minimization Method + maintainer: Sheikhi Ayyub + description: 'A hybrid of the K-means algorithm and a Majorization-Minimization + method to introduce a robust clustering. The reference paper is: Julien Mairal, + (2015) . The two most important functions in package ''MajKMeans'' + are cluster_km() and cluster_MajKm(). cluster_km() clusters data without Majorization-Minimization + and cluster_MajKm() clusters data with Majorization-Minimization method. Both + of these functions calculate the sum of squares (SS) of clustering.' + date_publication: '2020-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MajKMeans + url_git: '' +MajMinKmeans: + version: 0.1.0 + title: k-Means Algorithm with a Majorization-Minimization Method + maintainer: Sheikhi Ayyub + description: 'A hybrid of the K-means algorithm and a Majorization-Minimization + method to introduce a robust clustering. The reference paper is: Julien Mairal, + (2015) . The two most important functions in package ''MajMinKmeans'' + are cluster_km() and cluster_MajKm(). Cluster_km() clusters data without Majorization-Minimization + and cluster_MajKm() clusters data with Majorization-Minimization method. Both + of these functions calculate the sum of squares (SS) of clustering. Another useful + function is MajMinOptim(), which helps to find the optimum values of the Majorization-Minimization + estimator.' + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MajMinKmeans + url_git: '' +makedummies: + version: 1.2.1 + title: Create Dummy Variables from Categorical Data + maintainer: Toshiaki Ara + description: |- + Create dummy variables from categorical data. + This package can convert categorical data (factor and ordered) into + dummy variables and handle multiple columns simultaneously. + This package enables to select whether a dummy variable for base group + is included (for principal component analysis/factor analysis) or + excluded (for regression analysis) by an option. + 'makedummies' function accepts 'data.frame', 'matrix', and + 'tbl' (tibble) class (by 'tibble' package). + 'matrix' class data is automatically converted to 'data.frame' class. + date_publication: '2019-08-04' + bug_reports: https://github.com/toshi-ara/makedummies/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=makedummies + url_git: https://github.com/toshi-ara/makedummies +MakefileR: + version: '1.0' + title: Create 'Makefiles' Using R + maintainer: Kirill Müller + description: |- + A user-friendly interface for the construction of + 'Makefiles'. + date_publication: '2016-01-08' + bug_reports: https://github.com/krlmlr/MakefileR/issues + url: http://krlmlr.github.io/MakefileR + url_cran: https://CRAN.R-project.org/package=MakefileR + url_git: '' +makeFlow: + version: 1.0.2 + title: Visualizing Sequential Classifications + maintainer: Alex J. Krebs + description: A user-friendly tool for visualizing categorical or group movement. + date_publication: '2016-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=makeFlow + url_git: '' +makeit: + version: 1.0.1 + title: Run R Scripts if Needed + maintainer: Arni Magnusson + description: |- + Automation tool to run R scripts if needed, based on last modified + time. Implemented in base R with no additional software requirements, + organizational overhead, or structural requirements. In short: run an R script + if underlying files have changed, otherwise do nothing. + date_publication: '2023-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=makeit + url_git: https://github.com/arni-magnusson/makeit +makemyprior: + version: 1.2.2 + title: Intuitive Construction of Joint Priors for Variance Parameters + maintainer: Ingeborg Hem + description: 'Tool for easy prior construction and visualization. It helps to formulates + joint prior distributions for variance parameters in latent Gaussian models. The + resulting prior is robust and can be created in an intuitive way. A graphical + user interface (GUI) can be used to choose the joint prior, where the user can + click through the model and select priors. An extensive guide is available in + the GUI. The package allows for direct inference with the specified model and + prior. Using a hierarchical variance decomposition, we formulate a joint variance + prior that takes the whole model structure into account. In this way, existing + knowledge can intuitively be incorporated at the level it applies to. Alternatively, + one can use independent variance priors for each model components in the latent + Gaussian model. Details can be found in the accompanying scientific paper: Hem, + Fuglstad, Riebler (2024, Journal of Statistical Software, ).' + date_publication: '2024-08-23' + bug_reports: https://github.com/ingebogh/makemyprior/issues + url: '' + url_cran: https://CRAN.R-project.org/package=makemyprior + url_git: https://github.com/ingebogh/makemyprior +makePalette: + version: 0.1.2 + title: Make Palette + maintainer: Jorge L. C. Musaja + description: Functions that allow you to create your own color palette from an image, + using mathematical algorithms. + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=makePalette + url_git: https://github.com/musajajorge/makePalette +makepipe: + version: 0.2.2 + title: Pipeline Tools Inspired by 'GNU Make' + maintainer: Kinto Behr + description: |- + A suite of tools for transforming an existing workflow into a + self-documenting pipeline with very minimal upfront costs. Segments of + the pipeline are specified in much the same way a 'Make' rule is, by + declaring an executable recipe (which might be an R script), along + with the corresponding targets and dependencies. When the entire + pipeline is run through, only those recipes that need to be executed + will be. Meanwhile, execution metadata is captured behind the scenes + for later inspection. + date_publication: '2025-01-07' + bug_reports: https://github.com/kinto-b/makepipe/issues + url: https://kinto-b.github.io/makepipe/ + url_cran: https://CRAN.R-project.org/package=makepipe + url_git: https://github.com/kinto-b/makepipe +makeProject: + version: '1.0' + title: Creates an empty package framework for the LCFD format + maintainer: Noah Silverman + description: |- + This package creates an empty framework of files and + directories for the "Load, Clean, Func, Do" structure described + by Josh Reich. + date_publication: '2012-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=makeProject + url_git: '' +maketools: + version: 1.3.2 + title: Exploring and Testing the Toolchain and System Libraries + maintainer: Jeroen Ooms + description: |- + Helper functions that interface with the system utilities to learn + about the local build environment. Lets you explore 'make' rules to test the + local configuration, or query 'pkg-config' to find compiler flags and libs + needed for building packages with external dependencies. Also contains tools + to analyze which libraries that a installed R package linked to by inspecting + output from 'ldd' in combination with information from your distribution + package manager, e.g. 'rpm' or 'dpkg'. + date_publication: '2025-01-25' + bug_reports: https://github.com/jeroen/maketools/issues + url: https://jeroen.r-universe.dev/maketools + url_cran: https://CRAN.R-project.org/package=maketools + url_git: '' +makeunique: + version: 1.0.0 + title: Make Character Strings Unique + maintainer: Sam El-Kamand + description: |- + Make all elements of a character vector unique. + Differs from 'make.unique' by starting at 1 and allowing users to customise suffix format. + date_publication: '2022-10-13' + bug_reports: https://github.com/selkamand/makeunique/issues + url: '' + url_cran: https://CRAN.R-project.org/package=makeunique + url_git: https://github.com/selkamand/makeunique +MAKL: + version: 1.0.1 + title: Multiple Approximate Kernel Learning (MAKL) + maintainer: Ayyüce Begüm Bektaş + description: R package associated with the Multiple Approximate Kernel Learning + (MAKL) algorithm proposed in . The algorithm + fits multiple approximate kernel learning (MAKL) models that are fast, scalable + and interpretable. + date_publication: '2022-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAKL + url_git: '' +malan: + version: 1.0.3 + title: MAle Lineage ANalysis + maintainer: Mikkel Meyer Andersen + description: |- + MAle Lineage ANalysis by simulating + genealogies backwards and imposing short tandem repeats (STR) mutations forwards. + Intended for forensic Y chromosomal STR (Y-STR) haplotype analyses. + Numerous analyses are possible, e.g. number of matches and meiotic distance to matches. + Refer to papers mentioned in citation("malan") (DOI's: + , + and + ). + date_publication: '2023-11-28' + bug_reports: https://github.com/mikldk/malan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=malan + url_git: '' +malani: + version: '1.0' + title: Machine Learning Assisted Network Inference + maintainer: Mehrab Ghanat Bari + description: Find dark genes. These genes are often disregarded due to no detected + mutation or differential expression, but are important in coordinating the functionality + in cancer networks. + date_publication: '2016-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=malani + url_git: '' +malariaAtlas: + version: 1.6.3 + title: |- + An R Interface to Open-Access Malaria Data, Hosted by the + 'Malaria Atlas Project' + maintainer: Mauricio van den Berg + description: |- + A suite of tools to allow you to download all + publicly available parasite rate survey points, mosquito occurrence points and raster surfaces from + the 'Malaria Atlas Project' servers as well as utility functions for plotting + the downloaded data. + date_publication: '2024-08-26' + bug_reports: https://github.com/malaria-atlas-project/malariaAtlas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=malariaAtlas + url_git: https://github.com/malaria-atlas-project/malariaAtlas +malaytextr: + version: 0.1.3 + title: Text Mining for Bahasa Malaysia + maintainer: Zahier Nasrudin + description: |- + It is designed to work with text written in Bahasa Malaysia. We provide + functions and data sets that will make working with Bahasa Malaysia text much easier. + For word stemming in particular, we will look up the Malay words in a dictionary and + then proceed to remove "extra suffix" as explained in Khan, Rehman Ullah, + Fitri Suraya Mohamad, Muh Inam UlHaq, Shahren Ahmad Zadi Adruce, + Philip Nuli Anding, Sajjad Nawaz Khan, and Abdulrazak Yahya Saleh Al-Hababi + (2017) . This package includes + a dictionary of Malay words that may be used to perform word stemming, + a dataset of Malay stop words, a dataset of sentiment words + and a dataset of normalized words. + date_publication: '2023-01-17' + bug_reports: https://github.com/zahiernasrudin/malaytextr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=malaytextr + url_git: https://github.com/zahiernasrudin/malaytextr +maldipickr: + version: 1.3.1 + title: Dereplicate and Cherry-Pick Mass Spectrometry Spectra + maintainer: Charlie Pauvert + description: |- + Convenient wrapper functions for the analysis of + matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) + spectra data in order to select only representative spectra (also + called cherry-pick). The package covers the preprocessing and + dereplication steps (based on Strejcek, Smrhova, Junkova and Uhlik + (2018) ) needed to cluster MALDI-TOF + spectra before the final cherry-picking step. It enables the easy + exclusion of spectra and/or clusters to accommodate complex + cherry-picking strategies. Alternatively, cherry-picking using + taxonomic identification MALDI-TOF data is made easy with functions to + import inconsistently formatted reports. + date_publication: '2024-09-12' + bug_reports: https://github.com/ClavelLab/maldipickr/issues + url: https://clavellab.github.io/maldipickr/ + url_cran: https://CRAN.R-project.org/package=maldipickr + url_git: https://github.com/ClavelLab/maldipickr +MALDIquant: + version: 1.22.3 + title: Quantitative Analysis of Mass Spectrometry Data + maintainer: Sebastian Gibb + description: |- + A complete analysis pipeline for matrix-assisted laser + desorption/ionization-time-of-flight (MALDI-TOF) and other + two-dimensional mass spectrometry data. In addition to commonly + used plotting and processing methods it includes distinctive + features, namely baseline subtraction methods such as + morphological filters (TopHat) or the statistics-sensitive + non-linear iterative peak-clipping algorithm (SNIP), peak + alignment using warping functions, handling of replicated + measurements as well as allowing spectra with different + resolutions. + date_publication: '2024-08-19' + bug_reports: https://github.com/sgibb/MALDIquant/issues/ + url: https://strimmerlab.github.io/software/maldiquant/ + url_cran: https://CRAN.R-project.org/package=MALDIquant + url_git: https://github.com/sgibb/MALDIquant/ +MALDIquantForeign: + version: 0.14.1 + title: Import/Export Routines for 'MALDIquant' + maintainer: Sebastian Gibb + description: |- + Functions for reading (tab, csv, Bruker fid, Ciphergen + XML, mzXML, mzML, imzML, Analyze 7.5, CDF, mMass MSD) and + writing (tab, csv, mMass MSD, mzML, imzML) different file + formats of mass spectrometry data into/from 'MALDIquant' + objects. + date_publication: '2024-01-22' + bug_reports: https://github.com/sgibb/MALDIquantForeign/issues/ + url: https://strimmerlab.github.io/software/maldiquant/ + url_cran: https://CRAN.R-project.org/package=MALDIquantForeign + url_git: https://github.com/sgibb/MALDIquantForeign/ +MALDIrppa: + version: 1.1.0-2 + title: MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis + maintainer: Javier Palarea-Albaladejo + description: Provides methods for quality control and robust pre-processing and + analysis of MALDI mass spectrometry data (Palarea-Albaladejo et al. (2018) ). + date_publication: '2024-01-25' + bug_reports: https://github.com/Japal/MALDIrppa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MALDIrppa + url_git: https://github.com/Japal/MALDIrppa +mall: + version: 0.1.0 + title: |- + Run Multiple Large Language Model Predictions Against a Table, + or Vectors + maintainer: Edgar Ruiz + description: |- + Run multiple 'Large Language Model' predictions against a table. The + predictions run row-wise over a specified column. It works using a + one-shot prompt, along with the current row's content. The prompt that is used + will depend of the type of analysis needed. + date_publication: '2024-10-24' + bug_reports: '' + url: https://mlverse.github.io/mall/ + url_cran: https://CRAN.R-project.org/package=mall + url_git: '' +mallet: + version: 1.3.0 + title: An R Wrapper for the Java Mallet Topic Modeling Toolkit + maintainer: Måns Magnusson + description: |2- + + An R interface for the Java Machine Learning for Language Toolkit (mallet) + to estimate probabilistic topic models, such + as Latent Dirichlet Allocation. We can use the R package to read textual + data into mallet from R objects, run the Java implementation of mallet + directly in R, and extract results as R objects. The Mallet toolkit + has many functions, this wrapper focuses on the topic modeling sub-package + written by David Mimno. The package uses the rJava package to connect to a + JVM. + date_publication: '2022-07-20' + bug_reports: https://github.com/mimno/RMallet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mallet + url_git: https://github.com/mimno/RMallet +malvinas: + version: 0.1.0 + title: Islas Malvinas, Georgias Del Sur y Sándwich Del Sur + maintainer: Juan Cruz Rodriguez + description: |- + Data sets related to the Islas Malvinas /// Sets de datos relacionados a las Islas + Malvinas - La Nación Argentina ratifica su legítima e imprescriptible soberanía sobre las islas + Malvinas, Georgias del Sur y Sándwich del Sur y los espacios marítimos e insulares + correspondientes, por ser parte integrante del territorio nacional. La recuperación de dichos + territorios y el ejercicio pleno de la soberanía, respetando el modo de vida de sus habitantes y + conforme a los principios del Derecho Internacional, constituyen un objetivo permanente e + irrenunciable del pueblo argentino. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=malvinas + url_git: '' +MAMS: + version: 3.0.0 + title: Designing Multi-Arm Multi-Stage Studies + maintainer: Thomas Jaki + description: Designing multi-arm multi-stage studies with (asymptotically) normal + endpoints and known variance. + date_publication: '2024-09-30' + bug_reports: '' + url: https://tjaki.github.io/MAMS/ + url_cran: https://CRAN.R-project.org/package=MAMS + url_git: '' +ManagedCloudProvider: + version: 1.0.0 + title: |- + Providing the Kubernetes-Like Functions for the Non-Kubernetes + Cloud Service + maintainer: Jiefei Wang + description: |2- + + Providing the kubernetes-like class 'ManagedCloudProvider' as a child class of + the 'CloudProvider' class in the 'DockerParallel' package. The class is able to + manage the cloud instance made by the non-kubernetes cloud service. + For creating a provider for the non-kubernetes cloud service, the developer + needs to define a reference class inherited from 'ManagedCloudProvider' and + define the method for the generics runDockerWorkerContainers(), + getDockerWorkerStatus() and killDockerWorkerContainers(). For more information, please see + the vignette in this package and . + date_publication: '2021-06-14' + bug_reports: https://github.com/Jiefei-Wang/ManagedCloudProvider/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ManagedCloudProvider + url_git: https://github.com/Jiefei-Wang/ManagedCloudProvider +managelocalrepo: + version: 0.1.5 + title: Manage a CRAN-Style Local Repository + maintainer: Imanuel Costigan + description: |- + This will allow easier management of a CRAN-style repository on + local networks (i.e. not on CRAN). This might be necessary where hosted + packages contain intellectual property owned by a corporation. + date_publication: '2015-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=managelocalrepo + url_git: '' +MANCIE: + version: '1.4' + title: |- + Matrix Analysis and Normalization by Concordant Information + Enhancement + maintainer: Tao Wang + description: High-dimensional data integration is a critical but difficult problem + in genomics research because of potential biases from high-throughput experiments. + We present MANCIE, a computational method for integrating two genomic data sets + with homogenous dimensions from different sources based on a PCA procedure as + an approximation to a Bayesian approach. + date_publication: '2016-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MANCIE + url_git: '' +mand: + version: '2.0' + title: Multivariate Analysis for Neuroimaging Data + maintainer: Atsushi Kawaguchi + description: 'Several functions can be used to analyze neuroimaging data using multivariate + methods based on the ''msma'' package. The functions used in the book entitled + "Multivariate Analysis for Neuroimaging Data" (2021, ISBN-13: 978-0367255329) + are contained.' + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mand + url_git: '' +MandalaR: + version: 0.1.0 + title: Building Mandalas from Parametric Equations of Classical Curves + maintainer: Luciane Ferreira Alcoforado + description: Provides an algorithm for creating mandalas. From the perspective of + classic mathematical curves and rigid movements on the plane, the package allows + you to select curves and produce mandalas from the curve. The algorithm was developed + based on the book by Alcoforado et. al. entitled "Art, Geometry and Mandalas with + R" (2022) in press by the USP Open Books Portal. + date_publication: '2022-11-02' + bug_reports: '' + url: https://lucianealcoforado.shinyapps.io/Mandala/ + url_cran: https://CRAN.R-project.org/package=MandalaR + url_git: '' +mandelbrot: + version: 0.2.0 + title: Generates Views on the Mandelbrot Set + maintainer: Ben Moore + description: Estimates membership for the Mandelbrot set. + date_publication: '2017-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mandelbrot + url_git: '' +manet: + version: '2.0' + title: Multiple Allocation Model for Actor-Event Networks + maintainer: Veronica Vinciotti + description: Mixture model with overlapping clusters for binary actor-event data. + Parameters are estimated in a Bayesian framework. Model and inference are described + in Ranciati, Vinciotti, Wit (2017) Modelling actor-event network data via a mixture + model under overlapping clusters. Submitted. + date_publication: '2018-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=manet + url_git: '' +Mangrove: + version: '1.21' + title: Risk Prediction on Trees + maintainer: Luke Jostins + description: |- + Methods for performing genetic risk + prediction from genotype data. You can use it to perform risk + prediction for individuals, or for families with missing data. + date_publication: '2017-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mangrove + url_git: '' +manhattanly: + version: 0.3.0 + title: Interactive Q-Q and Manhattan Plots Using 'plotly.js' + maintainer: Sahir Bhatnagar + description: |- + Create interactive manhattan, Q-Q and volcano plots that are usable from the R console, + in 'Dash' apps, in the 'RStudio' viewer pane, in 'R Markdown' documents, and in 'Shiny' apps. + Hover the mouse pointer over a point to show details or drag a rectangle to + zoom. A manhattan plot is a popular graphical method for visualizing results + from high-dimensional data analysis such as a (epi)genome wide association study + (GWAS or EWAS), in which p-values, Z-scores, test statistics are plotted on a scatter + plot against their genomic position. Manhattan plots are used for visualizing + potential regions of interest in the genome that are associated with a phenotype. + Interactive manhattan plots allow the inspection of specific value (e.g. rs number or + gene name) by hovering the mouse over a cell, as well as zooming into a region of the + genome (e.g. a chromosome) by dragging a rectangle around the relevant area. + This work is based on the 'qqman' package and the 'plotly.js' + engine. It produces similar manhattan and Q-Q plots as the 'manhattan' and 'qq' + functions in the 'qqman' package, with the advantage of including extra annotation + information and interactive web-based visualizations directly from R. + Once uploaded to a 'plotly' account, 'plotly' graphs (and the data behind them) + can be viewed and modified in a web browser. + date_publication: '2021-04-26' + bug_reports: https://github.com/sahirbhatnagar/manhattanly/issues + url: https://sahirbhatnagar.com/manhattanly/ + url_cran: https://CRAN.R-project.org/package=manhattanly + url_git: https://github.com/sahirbhatnagar/manhattanly/ +manhplot: + version: '1.1' + title: The Manhattan++ Plot + maintainer: Chris Grace + description: This plot integrates annotation into a manhattan plot. The plot is + implemented as a heatmap, which is binned using -log10(p-value) and chromosome + position. Annotation currently supported is minor allele frequency and gene function + high impact variants. + date_publication: '2019-11-25' + bug_reports: https://github.com/cgrace1978/manhplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=manhplot + url_git: https://github.com/cgrace1978/manhplot/ +manifestoR: + version: 1.6.0 + title: Access and Process Data and Documents of the Manifesto Project + maintainer: Sven Regel + description: |- + Provides access to coded election programmes from the Manifesto + Corpus and to the Manifesto Project's Main Dataset and routines to analyse this + data. The Manifesto Project collects and + analyses election programmes across time and space to measure the political + preferences of parties. The Manifesto Corpus contains the collected and + annotated election programmes in the Corpus format of the package 'tm' to enable + easy use of text processing and text mining functionality. Specific functions + for scaling of coded political texts are included. + date_publication: '2024-05-16' + bug_reports: https://github.com/ManifestoProject/manifestoR/issues + url: https://manifesto-project.wzb.eu/ + url_cran: https://CRAN.R-project.org/package=manifestoR + url_git: https://github.com/ManifestoProject/manifestoR +manifold: + version: 0.1.1 + title: Operations for Riemannian Manifolds + maintainer: Xiongtao Dai + description: Implements operations for Riemannian manifolds, e.g., geodesic distance, + Riemannian metric, exponential and logarithm maps, etc. Also incorporates random + object generator on the manifolds. See Dai, Lin, and Müller (2021) . + date_publication: '2022-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=manifold + url_git: '' +ManifoldOptim: + version: 1.0.1 + title: |- + An R Interface to the 'ROPTLIB' Library for Riemannian Manifold + Optimization + maintainer: Sean R. Martin + description: |- + An R interface to version 0.3 of the 'ROPTLIB' optimization library + (see for more information). Optimize real- + valued functions over manifolds such as Stiefel, Grassmann, and Symmetric + Positive Definite matrices. For details see Martin et. al. (2020) . + Note that the optional ldr package used in some of this package's examples can be obtained from either JSS + or from the CRAN archives + . + date_publication: '2021-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ManifoldOptim + url_git: '' +manipulate: + version: 1.0.1 + title: Interactive Plots for RStudio + maintainer: JJ Allaire + description: Interactive plotting functions for use within RStudio.The manipulate + function accepts a plotting expression and a set ofcontrols (e.g. slider, + picker, checkbox, or button) which are usedto dynamically change values + within the expression. When a value ischanged using its corresponding + control the expression isautomatically re-executed and the plot is redrawn. + date_publication: '2014-12-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=manipulate + url_git: '' +manipulateWidget: + version: 0.11.1 + title: Add Even More Interactivity to Interactive Charts + maintainer: Veronique Bachelier + description: |- + Like package 'manipulate' does for static graphics, this package + helps to easily add controls like sliders, pickers, checkboxes, etc. that + can be used to modify the input data or the parameters of an interactive + chart created with package 'htmlwidgets'. + date_publication: '2021-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=manipulateWidget + url_git: https://github.com/rte-antares-rpackage/manipulateWidget +ManlyMix: + version: 0.1.15.1 + title: Manly Mixture Modeling and Model-Based Clustering + maintainer: Xuwen Zhu + description: The utility of this package includes finite mixture modeling and model-based + clustering through Manly mixture models by Zhu and Melnykov (2016) . + It also provides capabilities for forward and backward model selection procedures. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ManlyMix + url_git: '' +MAnorm2: + version: 1.2.2 + title: Tools for Normalizing and Comparing ChIP-seq Samples + maintainer: Shiqi Tu + description: |- + Chromatin immunoprecipitation followed by high-throughput + sequencing (ChIP-seq) is the premier technology for profiling genome-wide + localization of chromatin-binding proteins, including transcription + factors and histones with various modifications. + This package provides a robust method for normalizing ChIP-seq + signals across individual samples or groups of samples. It also designs + a self-contained system of statistical models for calling differential + ChIP-seq signals between two or more biological conditions as well as + for calling hypervariable ChIP-seq signals across samples. Refer to + Tu et al. (2021) and + Chen et al. (2022) + for associated statistical details. + date_publication: '2022-10-28' + bug_reports: https://github.com/tushiqi/MAnorm2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MAnorm2 + url_git: https://github.com/tushiqi/MAnorm2 +MANOVA.RM: + version: 0.5.4 + title: |- + Resampling-Based Analysis of Multivariate Data and Repeated + Measures Designs + maintainer: Sarah Friedrich + description: |- + Implemented are various tests for semi-parametric repeated measures + and general MANOVA designs that do neither assume multivariate normality nor + covariance homogeneity, i.e., the procedures are applicable for a wide range + of general multivariate factorial designs. In addition to asymptotic inference + methods, novel bootstrap and permutation approaches are implemented as well. These provide more + accurate results in case of small to moderate sample sizes. Furthermore, post-hoc + comparisons are provided for the multivariate analyses. + Friedrich, S., Konietschke, F. and Pauly, M. (2019) . + date_publication: '2023-08-25' + bug_reports: https://github.com/smn74/MANOVA.RM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MANOVA.RM + url_git: https://github.com/smn74/MANOVA.RM +manta: + version: 1.0.1 + title: Multivariate Asymptotic Non-Parametric Test of Association + maintainer: Diego Garrido-Martín + description: |- + The Multivariate Asymptotic Non-parametric Test of Association (MANTA) enables + non-parametric, asymptotic P-value computation for multivariate linear models. MANTA + relies on the asymptotic null distribution of the PERMANOVA test statistic. P-values are + computed using a highly accurate approximation of the corresponding cumulative distribution + function. Garrido-Martín et al. (2022) . + date_publication: '2023-10-10' + bug_reports: https://github.com/dgarrimar/manta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=manta + url_git: https://github.com/dgarrimar/manta +MantaID: + version: 1.0.4 + title: |- + A Machine-Learning Based Tool to Automate the Identification of + Biological Database IDs + maintainer: Zhengpeng Zeng + description: The number of biological databases is growing rapidly, but different + databases use different IDs to refer to the same biological entity. The inconsistency + in IDs impedes the integration of various types of biological data. To resolve + the problem, we developed 'MantaID', a data-driven, machine-learning based approach + that automates identifying IDs on a large scale. The 'MantaID' model's prediction + accuracy was proven to be 99%, and it correctly and effectively predicted 100,000 + ID entries within two minutes. 'MantaID' supports the discovery and exploitation + of ID patterns from large quantities of databases. (e.g., up to 542 biological + databases). An easy-to-use freely available open-source software R package, a + user-friendly web application, and API were also developed for 'MantaID' to improve + applicability. To our knowledge, 'MantaID' is the first tool that enables an automatic, + quick, accurate, and comprehensive identification of large quantities of IDs, + and can therefore be used as a starting point to facilitate the complex assimilation + and aggregation of biological data across diverse databases. + date_publication: '2024-09-09' + bug_reports: '' + url: https://molaison.github.io/MantaID/ + url_cran: https://CRAN.R-project.org/package=MantaID + url_git: '' +manydata: + version: 0.9.3 + title: A Portal for Global Governance Data + maintainer: James Hollway + description: |- + This is the core package for the many packages universe. + It includes functions to help researchers work with and contribute to + event datasets on global governance. + date_publication: '2024-05-06' + bug_reports: https://github.com/globalgov/manydata/issues + url: https://manydata.ch/ + url_cran: https://CRAN.R-project.org/package=manydata + url_git: https://github.com/globalgov/manydata +manydist: + version: 0.4.3 + title: Unbiased Distances for Mixed-Type Data + maintainer: Angelos Markos + description: |- + A comprehensive framework for calculating unbiased distances in datasets + containing mixed-type variables (numerical and categorical). The package implements + a general formulation that ensures multivariate additivity and commensurability, + meaning that variables contribute equally to the overall distance regardless of + their type, scale, or distribution. Supports multiple distance measures including + Gower's distance, Euclidean distance, Manhattan distance, and various categorical + variable distances such as simple matching, Eskin, occurrence frequency, and + association-based distances. Provides tools for variable scaling (standard + deviation, range, robust range, and principal component scaling), and handles + both independent and association-based category dissimilarities. Implements + methods to correct for biases that typically arise from different variable types, + distributions, and number of categories. Particularly useful for cluster analysis, + data visualization, and other distance-based methods when working with mixed data. + Methods based on van de Velden et al. (2024) + "Unbiased mixed variables distance". + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=manydist + url_git: '' +manymodelr: + version: 0.3.7 + title: Build and Tune Several Models + maintainer: Nelson Gonzabato + description: |- + Frequently one needs a convenient way to build and tune + several models in one go.The goal is to provide a number of machine learning convenience + functions. It provides the ability to build, tune and obtain predictions of + several models in one function. The models are built using functions from + 'caret' with easier to read syntax. + Kuhn(2014) . + date_publication: '2021-11-15' + bug_reports: https://github.com/Nelson-Gon/manymodelr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=manymodelr + url_git: https://github.com/Nelson-Gon/manymodelr +manymome: + version: 0.2.7 + title: |- + Mediation, Moderation and Moderated-Mediation After Model + Fitting + maintainer: Shu Fai Cheung + description: |- + Computes indirect effects, conditional effects, and conditional + indirect effects in a structural equation model or path model after model + fitting, with no need to define any user parameters or label any paths in + the model syntax, using the approach presented in Cheung and Cheung + (2024) . Can also form bootstrap + confidence intervals by doing bootstrapping only once and reusing the + bootstrap estimates in all subsequent computations. Supports bootstrap + confidence intervals for standardized (partially or completely) indirect + effects, conditional effects, and conditional indirect effects as described + in Cheung (2009) and Cheung, Cheung, Lau, Hui, + and Vong (2022) . Model fitting can be done by + structural equation modeling using lavaan() or regression using lm(). + date_publication: '2025-01-25' + bug_reports: https://github.com/sfcheung/manymome/issues + url: https://sfcheung.github.io/manymome/ + url_cran: https://CRAN.R-project.org/package=manymome + url_git: '' +manymome.table: + version: 0.4.0 + title: Publication-Ready Tables for 'manymome' Results + maintainer: Shu Fai Cheung + description: |- + Converts results from the 'manymome' package, + presented in Cheung and Cheung (2023) + , to publication-ready + tables. + date_publication: '2024-12-10' + bug_reports: https://github.com/sfcheung/manymome.table/issues + url: https://sfcheung.github.io/manymome.table/ + url_cran: https://CRAN.R-project.org/package=manymome.table + url_git: '' +manynet: + version: 1.3.2 + title: |- + Many Ways to Make, Modify, Map, Mark, and Measure Myriad + Networks + maintainer: James Hollway + description: |- + Many tools for making, modifying, mapping, marking, measuring, + and motifs and memberships of many different types of networks. + All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, + and on one-mode, two-mode (bipartite), and sometimes three-mode networks. + The package includes functions for importing and exporting, creating and generating networks, + modifying networks and node and tie attributes, + and describing and visualizing networks with sensible defaults. + date_publication: '2024-11-05' + bug_reports: https://github.com/stocnet/manynet/issues + url: https://stocnet.github.io/manynet/ + url_cran: https://CRAN.R-project.org/package=manynet + url_git: '' +ManyTests: + version: '1.2' + title: |- + Multiple Testing Procedures of Cox (2011) and Wong and Cox + (2007) + maintainer: Christiana Kartsonaki + description: Performs the multiple testing procedures of Cox (2011) + and Wong and Cox (2007) . + date_publication: '2016-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ManyTests + url_git: '' +MaOEA: + version: 0.6.2 + title: Many Objective Evolutionary Algorithm + maintainer: Dani Irawan + description: |- + A set of evolutionary algorithms to solve many-objective optimization. + Hybridization between the algorithms are also facilitated. Available algorithms are: + 'SMS-EMOA' + 'NSGA-III' + 'MO-CMA-ES' + The following many-objective benchmark problems are also provided: + 'DTLZ1'-'DTLZ4' from Deb, et al. (2001) and + 'WFG4'-'WFG9' from Huband, et al. (2005) . + date_publication: '2020-08-31' + bug_reports: https://github.com/dots26/MaOEA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MaOEA + url_git: https://github.com/dots26/MaOEA +maotai: + version: 0.2.6 + title: Tools for Matrix Algebra, Optimization and Inference + maintainer: Kisung You + description: Matrix is an universal and sometimes primary object/unit in applied + mathematics and statistics. We provide a number of algorithms for selected problems + in optimization and statistical inference. For general exposition to the topic + with focus on statistical context, see the book by Banerjee and Roy (2014, ISBN:9781420095388). + date_publication: '2025-02-27' + bug_reports: https://github.com/kisungyou/maotai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maotai + url_git: https://github.com/kisungyou/maotai +MAP: + version: 1.0.0 + title: Multimodal Automated Phenotyping + maintainer: Thomas Charlon + description: |- + Electronic health records (EHR) linked with biorepositories are + a powerful platform for translational studies. A major bottleneck exists + in the ability to phenotype patients accurately and efficiently. + Towards that end, we developed an automated high-throughput + phenotyping method integrating International + Classification of Diseases (ICD) codes and narrative data extracted + using natural language processing (NLP). Specifically, our proposed method, + called MAP (Map Automated Phenotyping algorithm), fits an ensemble of latent + mixture models on aggregated ICD and NLP counts along with healthcare + utilization. The MAP algorithm yields a predicted probability of phenotype + for each patient and a threshold for classifying subjects with phenotype + yes/no (See Katherine P. Liao, et al. (2019) .). + date_publication: '2024-12-02' + bug_reports: https://github.com/celehs/MAP/issues + url: https://celehs.github.io/MAP/ + url_cran: https://CRAN.R-project.org/package=MAP + url_git: '' +Map2NCBI: + version: '1.4' + title: Mapping Markers to the Nearest Genomic Feature + maintainer: Lauren Hanna + description: |- + Allows the user to generate a list of features (gene, pseudo, RNA, + CDS, and/or UTR) directly from NCBI database for any species with a current + build available. Option to save downloaded and formatted files is available, + and the user can prioritize the feature list based on type and assembly builds + present in the current build used. The user can then use the list of features + generated or provide a list to map a set of markers (designed for SNP markers + with a single base pair position available) to the closest feature based on + the map build. This function does require map positions of the markers to be + provided and the positions should be based on the build being queried through + NCBI. + date_publication: '2020-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Map2NCBI + url_git: '' +MAPA: + version: 2.0.7 + title: Multiple Aggregation Prediction Algorithm + maintainer: Nikolaos Kourentzes + description: Functions and wrappers for using the Multiple Aggregation Prediction + Algorithm (MAPA) for time series forecasting. MAPA models and forecasts time series + at multiple temporal aggregation levels, thus strengthening and attenuating the + various time series components for better holistic estimation of its structure. + For details see Kourentzes et al. (2014) . + date_publication: '2024-03-05' + bug_reports: https://github.com/trnnick/mapa/issues + url: https://kourentzes.com/forecasting/2014/04/19/multiple-aggregation-prediction-algorithm-mapa/ + url_cran: https://CRAN.R-project.org/package=MAPA + url_git: '' +mapaccuracy: + version: 0.1.2 + title: Unbiased Thematic Map Accuracy and Area + maintainer: Hugo Costa + description: Unbiased estimators of overall and per-class thematic map accuracy + and area published in Olofsson et al. (2014) and + Stehman (2014) . + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapaccuracy + url_git: '' +mapbayr: + version: 0.10.0 + title: MAP-Bayesian Estimation of PK Parameters + maintainer: Felicien Le Louedec + description: Performs maximum a posteriori Bayesian estimation of individual pharmacokinetic + parameters from a model defined in 'mrgsolve', typically for model-based therapeutic + drug monitoring. Internally computes an objective function value from model and + data, performs optimization and returns predictions in a convenient format. The + performance of the package was described by Le Louedec et al (2021) . + date_publication: '2023-07-17' + bug_reports: https://github.com/FelicienLL/mapbayr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapbayr + url_git: https://github.com/FelicienLL/mapbayr +mapboxapi: + version: 0.6.2 + title: R Interface to 'Mapbox' Web Services + maintainer: Kyle Walker + description: |- + Includes support for 'Mapbox' Navigation APIs, including directions, + isochrones, and route optimization; the Search API for forward and reverse geocoding; + the Maps API for interacting with 'Mapbox' vector tilesets and visualizing + 'Mapbox' maps in R; and 'Mapbox Tiling Service' and 'tippecanoe' for generating map tiles. + See for more information about the 'Mapbox' APIs. + date_publication: '2024-09-20' + bug_reports: https://github.com/walkerke/mapboxapi/issues + url: https://walker-data.com/mapboxapi/ + url_cran: https://CRAN.R-project.org/package=mapboxapi + url_git: https://github.com/walkerke/mapboxapi +mapboxer: + version: 0.4.0 + title: An R Interface to 'Mapbox GL JS' + maintainer: Stefan Kuethe + description: |- + Makes 'Mapbox GL JS' , + an open source JavaScript library that uses WebGL to render interactive maps, + available within R via the 'htmlwidgets' package. Visualizations can be used from the R console, + in R Markdown documents and in Shiny apps. + date_publication: '2020-11-04' + bug_reports: https://github.com/crazycapivara/mapboxer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapboxer + url_git: https://github.com/crazycapivara/mapboxer +mapcan: + version: 0.0.1 + title: |- + Tools for Plotting Canadian Choropleth Maps and Choropleth + Alternatives + maintainer: Andrew McCormack + description: A variety of functions that make it easy to plot standard choropleth + maps as well as choropleth alternatives in 'ggplot2'. + date_publication: '2019-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapcan + url_git: '' +mapchina: + version: 0.1.0 + title: China Administrative Divisions Geospatial Shapefile Data + maintainer: Mingchu Xu + description: Geospatial shapefile data of China administrative divisions to the + county/district-level. + date_publication: '2020-09-29' + bug_reports: https://github.com/xmc811/mapchina/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapchina + url_git: https://github.com/xmc811/mapchina +mapdata: + version: 2.3.1 + title: Extra Map Databases + maintainer: Alex Deckmyn + description: |- + Supplement to maps package, providing some larger and/or + higher-resolution databases. NOTE: this is a legacy package. The world map is out-dated. + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapdata + url_git: '' +mapdeck: + version: 0.3.5 + title: Interactive Maps Using 'Mapbox GL JS' and 'Deck.gl' + maintainer: David Cooley + description: |- + Provides a mechanism to plot an interactive map using 'Mapbox GL' + (), a javascript library for interactive maps, + and 'Deck.gl' (), a javascript library which uses 'WebGL' for + visualising large data sets. + date_publication: '2024-01-29' + bug_reports: https://github.com/SymbolixAU/mapdeck/issues + url: https://symbolixau.github.io/mapdeck/articles/mapdeck.html + url_cran: https://CRAN.R-project.org/package=mapdeck + url_git: '' +mapedit: + version: 0.6.0 + title: Interactive Editing of Spatial Data in R + maintainer: Tim Appelhans + description: |- + Suite of interactive functions and helpers for selecting and editing + geospatial data. + date_publication: '2020-02-02' + bug_reports: https://github.com/r-spatial/mapedit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapedit + url_git: https://github.com/r-spatial/mapedit +mapfit: + version: 1.0.0 + title: PH/MAP Parameter Estimation + maintainer: Hiroyuki Okamura + description: |- + Estimation methods for phase-type + distribution (PH) and Markovian arrival process (MAP) from + empirical data (point and grouped data) and density function. + The tool is based on the following researches: + Okamura et al. (2009) , + Okamura and Dohi (2009) , + Okamura et al. (2011) , + Okamura et al. (2013) , + Horvath and Okamura (2013) , + Okamura and Dohi (2016) . + date_publication: '2022-11-22' + bug_reports: https://github.com/okamumu/mapfit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapfit + url_git: https://github.com/okamumu/mapfit +MapGAM: + version: '1.3' + title: Mapping Smoothed Effect Estimates from Individual-Level Data + maintainer: Scott Bartell + description: Contains functions for mapping odds ratios, hazard ratios, or other + effect estimates using individual-level data such as case-control study data, + using generalized additive models (GAMs) or Cox models for smoothing with a two-dimensional + predictor (e.g., geolocation or exposure to chemical mixtures) while adjusting + linearly for confounding variables, using methods described by Kelsall and Diggle + (1998), Webster at al. (2006), and Bai et al. (2020). Includes convenient functions + for mapping point estimates and confidence intervals, efficient control sampling, + and permutation tests for the null hypothesis that the two-dimensional predictor + is not associated with the outcome variable (adjusting for confounders). + date_publication: '2023-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MapGAM + url_git: '' +mapgl: + version: 0.2.0 + title: Interactive Maps with 'Mapbox GL JS' and 'MapLibre GL JS' + maintainer: Kyle Walker + description: |- + Provides an interface to the 'Mapbox GL JS' () + and the 'MapLibre GL JS' () interactive mapping libraries to help users + create custom interactive maps in R. Users can create interactive globe visualizations; layer 'sf' objects to create + filled maps, circle maps, 'heatmaps', and three-dimensional graphics; and customize map styles and views. The package + also includes utilities to use 'Mapbox' and 'MapLibre' maps in 'Shiny' web applications. + date_publication: '2025-01-13' + bug_reports: https://github.com/walkerke/mapgl/issues + url: https://walker-data.com/mapgl/ + url_cran: https://CRAN.R-project.org/package=mapgl + url_git: '' +mapi: + version: 1.0.5 + title: Mapping Averaged Pairwise Information + maintainer: Sylvain Piry + description: |- + Mapping Averaged Pairwise Information (MAPI) is an + exploratory method providing graphical representations summarizing the + spatial variation of pairwise metrics (eg. distance, similarity + coefficient, ...) computed between georeferenced samples. + date_publication: '2022-01-19' + bug_reports: '' + url: https://www1.montpellier.inra.fr/CBGP/software/MAPI/ + url_cran: https://CRAN.R-project.org/package=mapi + url_git: '' +mapindia: + version: 1.0.1 + title: Plot Map of the Indian Subcontinent + maintainer: Shubham Dutta + description: |- + Get map data frames for the Indian subcontinent with different region + levels (e.g., district, state). The package also offers convenience functions + for plotting choropleths, visualizing spatial data, and handling state/district + codes. + date_publication: '2024-11-14' + bug_reports: https://github.com/shubhamdutta26/mapindia/issues + url: https://www.shubhamdutta.com/mapindia/ + url_cran: https://CRAN.R-project.org/package=mapindia + url_git: https://github.com/shubhamdutta26/mapindia +mapindiatools: + version: 1.0.1 + title: Mapping Data for 'mapindia' Package + maintainer: Shubham Dutta + description: |- + Provides a container for data used by the 'mapindia' package. + The data used by 'mapindia' has been extracted into this package so that the + file size of the 'mapindia' package can be reduced considerably. The data in + this package will be updated when latest data is available. + date_publication: '2024-10-31' + bug_reports: https://github.com/shubhamdutta26/mapindiatools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapindiatools + url_git: https://github.com/shubhamdutta26/mapindiatools +Mapinguari: + version: 2.0.1 + title: Process-Based Biogeographical Analysis + maintainer: Gabriel Caetano + description: Facilitates the incorporation of biological processes in biogeographical + analyses. It offers conveniences in fitting, comparing and extrapolating models + of biological processes such as physiology and phenology. These spatial extrapolations + can be informative by themselves, but also complement traditional correlative + species distribution models, by mixing environmental and process-based predictors. + Caetano et al (2020) . + date_publication: '2023-06-26' + bug_reports: https://github.com/gabrielhoc/Mapinguari/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Mapinguari + url_git: https://github.com/gabrielhoc/Mapinguari +mapiso: + version: 0.3.0 + title: Create Contour Polygons from Regular Grids + maintainer: Timothée Giraud + description: |- + Regularly spaced grids containing continuous data are transformed + to contour polygons. A grid can be defined by a data.frame (x, y, value), + an 'sf' object or a raster from 'terra'. + date_publication: '2023-05-12' + bug_reports: https://github.com/riatelab/mapiso/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=mapiso + url_git: https://github.com/riatelab/mapiso +MAPITR: + version: 1.1.2 + title: MArginal ePIstasis Test for Regions + maintainer: Michael Turchin + description: |- + A genetic analysis tool and variance component + model for identifying marginal epistasis between pathways + and the rest of the genome. 'MAPITR' uses as input a matrix + of genotypes, a vector of phenotypes, and a list of + pathways. 'MAPITR' then iteratively tests each pathway for + epistasis between any variants within the pathway versus + any variants remaining in the rest of the genome. 'MAPITR' + returns results in the form of p-values for every pathway + indicating whether the null model of there being no + epistatic interactions between a pathway and the rest of + the genome can be rejected. + date_publication: '2020-09-28' + bug_reports: https://github.com/mturchin20/MAPITR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MAPITR + url_git: https://github.com/mturchin20/MAPITR +maplegend: + version: 0.2.0 + title: Legends for Maps + maintainer: Timothée Giraud + description: |- + Create legends for maps and other graphics. Thematic maps need to + be accompanied by legible legends to be fully comprehensible. This package + offers a wide range of legends useful for cartography, some of which may + also be useful for other types of graphics. + date_publication: '2024-11-12' + bug_reports: https://github.com/riatelab/maplegend/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=maplegend + url_git: https://github.com/riatelab/maplegend/ +mapme.biodiversity: + version: 0.9.3 + title: Efficient Monitoring of Global Biodiversity Portfolios + maintainer: Darius A. Görgen + description: |- + Biodiversity areas, especially primary forest, serve a + multitude of functions for local economy, regional functionality of + the ecosystems as well as the global health of our planet. Recently, + adverse changes in human land use practices and climatic responses to + increased greenhouse gas emissions, put these biodiversity areas under + a variety of different threats. The present package helps to analyse a + number of biodiversity indicators based on freely available + geographical datasets. It supports computational efficient routines + that allow the analysis of potentially global biodiversity portfolios. + The primary use case of the package is to support evidence based + reporting of an organization's effort to protect biodiversity areas + under threat and to identify regions were intervention is most duly + needed. + date_publication: '2024-10-21' + bug_reports: https://github.com/mapme-initiative/mapme.biodiversity/issues + url: https://mapme-initiative.github.io/mapme.biodiversity/index.html + url_cran: https://CRAN.R-project.org/package=mapme.biodiversity + url_git: https://github.com/mapme-initiative/mapme.biodiversity/ +mapmisc: + version: 2.1.0 + title: Utilities for Producing Maps + maintainer: Patrick Brown + description: Provides a minimal, light-weight set of tools for producing nice looking + maps in R, with support for map projections. See Brown (2016) . + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapmisc + url_git: '' +mapmixture: + version: 1.2.0 + title: Spatial Visualisation of Admixture on a Projected Map + maintainer: Tom Jenkins + description: Visualise admixture as pie charts on a projected map, admixture as + traditional structure barplots or facet barplots, and scatter plots from genotype + principal components analysis. A 'shiny' app allows users to create admixture + maps interactively. Jenkins TL (2024) . + date_publication: '2025-01-23' + bug_reports: https://github.com/Tom-Jenkins/mapmixture/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapmixture + url_git: https://github.com/Tom-Jenkins/mapmixture +mappeR: + version: 2.0.2 + title: Construct and Visualize TDA Mapper Graphs + maintainer: George Clare Kennedy + description: |- + Topological data analysis (TDA) is a method of data analysis that + uses techniques from topology to analyze high-dimensional data. Here we + implement Mapper, an algorithm from this area developed by Singh, Mémoli and + Carlsson (2007) which generalizes the concept of a + Reeb graph . + date_publication: '2025-02-20' + bug_reports: https://github.com/Uiowa-Applied-Topology/mappeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mappeR + url_git: https://github.com/Uiowa-Applied-Topology/mappeR +MapperAlgo: + version: 1.0.2 + title: 'Topological Data Analysis: Mapper Algorithm' + maintainer: ChiChien Wang + description: The Mapper algorithm from Topological Data Analysis, the steps are + as follows 1. Define a filter (lens) function on the data. 2. Perform clustering + within each level set. 3. Generate a complex from the clustering results. + date_publication: '2025-02-15' + bug_reports: https://github.com/kennywang112/MapperAlgo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MapperAlgo + url_git: https://github.com/kennywang112/MapperAlgo/ +mapping: + version: 1.4.1 + title: Automatic Download, Linking, Manipulating Coordinates for Maps + maintainer: Alessio Serafini + description: Maps are an important tool to visualise variables distribution across + different spatial objects. The mapping process requires to link the data with + coordinates and then generate the correspondent map. This package provide coordinates, + linking and mapping functions for an automatic, flexible and easy approach of + external functions. The package provides an easy, flexible and automatic unit. + Geographical coordinates are provided in the package and automatically linked + with the input data to generate maps with internal provided functions or external + functions. Provide an easy, flexible and automatic approach to potentially download + updated coordinates, to link statistical units with coordinates and to aggregate + variables based on the spatial hierarchy of units. The object returned from the + package can be used for thematic maps with the build-in functions provided in + mapping or with other packages already available. + date_publication: '2023-12-12' + bug_reports: https://github.com/mappinguniverse/mapping/issues + url: https://mappinguniverse.github.io/mapping/index.html + url_cran: https://CRAN.R-project.org/package=mapping + url_git: '' +mappings: + version: '0.1' + title: Functions for Transforming Categorical Variables + maintainer: Benjamin Rich + description: |- + Easily create functions to map between different sets of values, + such as for re-labelling categorical variables. + date_publication: '2021-06-23' + bug_reports: https://github.com/benjaminrich/mappings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mappings + url_git: https://github.com/benjaminrich/mappings +mapplots: + version: 1.5.2 + title: Data Visualisation on Maps + maintainer: Hans Gerritsen + description: Create simple maps; add sub-plots like pie plots to a map or any other + plot; format, plot and export gridded data. The package was developed for displaying + fisheries data but most functions can be used for more generic data visualisation. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapplots + url_git: '' +mappoly: + version: 0.4.1 + title: Genetic Linkage Maps in Autopolyploids + maintainer: Marcelo Mollinari + description: |- + Construction of genetic maps in autopolyploid full-sib populations. + Uses pairwise recombination fraction estimation as the first + source of information to sequentially position allelic variants + in specific homologous chromosomes. For situations where pairwise + analysis has limited power, the algorithm relies on the multilocus + likelihood obtained through a hidden Markov model (HMM). + For more detail, please see Mollinari and Garcia (2019) + and Mollinari et al. (2020) + . + date_publication: '2024-03-06' + bug_reports: https://github.com/mmollina/MAPpoly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mappoly + url_git: https://github.com/mmollina/MAPpoly +mappp: + version: 1.0.0 + title: Map in Parallel with Progress + maintainer: Cole Brokamp + description: Provides one function, which is a wrapper around purrr::map() with + some extras on top, including parallel computation, progress bars, error handling, + and result caching. + date_publication: '2022-01-25' + bug_reports: https://github.com/cole-brokamp/mappp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mappp + url_git: https://github.com/cole-brokamp/mappp +mapproj: + version: 1.2.11 + title: Map Projections + maintainer: Alex Deckmyn + description: Converts latitude/longitude into projected coordinates. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapproj + url_git: '' +maps: + version: 3.4.2.1 + title: Draw Geographical Maps + maintainer: Alex Deckmyn + description: |- + Display of maps. Projection code and larger maps are in + separate packages ('mapproj' and 'mapdata'). + date_publication: '2024-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maps + url_git: '' +mapsapi: + version: 0.5.4 + title: '''sf''-Compatible Interface to ''Google Maps'' APIs' + maintainer: Michael Dorman + description: 'Interface to the ''Google Maps'' APIs: (1) routing directions based + on the ''Directions'' API, returned as ''sf'' objects, either as single feature + per alternative route, or a single feature per segment per alternative route; + (2) travel distance or time matrices based on the ''Distance Matrix'' API; (3) + geocoded locations based on the ''Geocode'' API, returned as ''sf'' objects, either + points or bounds; (4) map images using the ''Maps Static'' API, returned as ''stars'' + objects.' + date_publication: '2023-07-21' + bug_reports: https://github.com/michaeldorman/mapsapi/issues/ + url: https://michaeldorman.github.io/mapsapi/ + url_cran: https://CRAN.R-project.org/package=mapsapi + url_git: https://github.com/michaeldorman/mapsapi/ +mapscanner: + version: 0.1.1 + title: Print Maps, Draw on Them, Scan Them Back in + maintainer: Mark Padgham + description: |- + Enables preparation of maps to be printed and drawn on. + Modified maps can then be scanned back in, and hand-drawn marks + converted to spatial objects. + date_publication: '2024-07-18' + bug_reports: https://github.com/ropensci/mapscanner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapscanner + url_git: https://github.com/ropensci/mapscanner +mapsf: + version: 0.12.0 + title: Thematic Cartography + maintainer: Timothée Giraud + description: |- + Create and integrate thematic maps in your workflow. This package + helps to design various cartographic representations such as proportional + symbols, choropleth or typology maps. It also offers several functions to + display layout elements that improve the graphic presentation of maps + (e.g. scale bar, north arrow, title, labels). 'mapsf' maps 'sf' objects on + 'base' graphics. + date_publication: '2024-10-22' + bug_reports: https://github.com/riatelab/mapsf/issues/ + url: https://riatelab.github.io/mapsf/ + url_cran: https://CRAN.R-project.org/package=mapsf + url_git: '' +mapsFinland: + version: 0.2.2 + title: Maps of Finland + maintainer: Jari Haukka + description: Maps and other related data of Finland. + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapsFinland + url_git: '' +mapSpain: + version: 0.10.0 + title: Administrative Boundaries of Spain + maintainer: Diego Hernangómez + description: |- + Administrative Boundaries of Spain at several levels + (Autonomous Communities, Provinces, Municipalities) based on the + 'GISCO' 'Eurostat' database + and 'CartoBase SIANE' from 'Instituto Geografico Nacional' + . It also provides a 'leaflet' plugin and the + ability of downloading and processing static tiles. + date_publication: '2024-12-15' + bug_reports: https://github.com/rOpenSpain/mapSpain/issues + url: https://ropenspain.github.io/mapSpain/ + url_cran: https://CRAN.R-project.org/package=mapSpain + url_git: https://github.com/rOpenSpain/mapSpain +mapsPERU: + version: 2.0.0 + title: Maps of Peru + maintainer: Jorge L. C. Musaja + description: Information of the centroids and geographical limits of the regions, + departments, provinces and districts of Peru. + date_publication: '2023-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapsPERU + url_git: https://github.com/musajajorge/mapsPERU +mapsRinteractive: + version: 2.0.1 + title: Local Adaptation and Evaluation of Raster Maps + maintainer: Kristin Persson + description: Local adaptation and evaluation of maps of continuous attributes in + raster format by use of point location data. + date_publication: '2023-04-24' + bug_reports: https://github.com/kriper0217/mapsRinteractive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapsRinteractive + url_git: '' +mapStats: + version: '3.1' + title: Geographic Display of Survey Data Statistics + maintainer: Samuel Ackerman + description: Automated calculation and visualization of survey data statistics on + a color-coded (choropleth) map. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mapStats + url_git: '' +maptiles: + version: 0.9.0 + title: Download and Display Map Tiles + maintainer: Timothée Giraud + description: |- + To create maps from tiles, 'maptiles' downloads, composes and + displays tiles from a large number of providers (e.g. 'OpenStreetMap', + 'Stadia', 'Esri', 'CARTO', or 'Thunderforest'). + date_publication: '2025-02-04' + bug_reports: https://github.com/riatelab/maptiles/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=maptiles + url_git: https://github.com/riatelab/maptiles/ +maptpx: + version: 1.9-7 + title: MAP Estimation of Topic Models + maintainer: Matt Taddy + description: |- + Maximum a posteriori (MAP) estimation for topic models (i.e., Latent Dirichlet Allocation) in text analysis, + as described in Taddy (2012) 'On estimation and selection for topic models'. Previous versions of this code were included as part of the 'textir' package. If you want to take advantage of openmp parallelization, uncomment the relevant flags in src/MAKEVARS before compiling. + date_publication: '2020-05-28' + bug_reports: '' + url: http://taddylab.com + url_cran: https://CRAN.R-project.org/package=maptpx + url_git: '' +maptree: + version: 1.4-8 + title: Mapping, Pruning, and Graphing Tree Models + maintainer: Robert B. Gramacy + description: |- + Functions with example data for graphing, pruning, and + mapping models from hierarchical clustering, and classification + and regression trees. + date_publication: '2022-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maptree + url_git: '' +mapview: + version: 2.11.2 + title: Interactive Viewing of Spatial Data in R + maintainer: Tim Appelhans + description: |- + Quickly and conveniently create interactive + visualisations of spatial data with or without background maps. + Attributes of displayed features are fully queryable via pop-up + windows. Additional functionality includes methods to visualise true- + and false-color raster images and bounding boxes. + date_publication: '2023-10-13' + bug_reports: https://github.com/r-spatial/mapview/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mapview + url_git: https://github.com/r-spatial/mapview +maq: + version: 0.5.0 + title: Multi-Armed Qini + maintainer: Erik Sverdrup + description: |- + Policy evaluation using generalized Qini curves: Evaluate data-driven treatment + targeting rules for one or more treatment arms over different budget + constraints in experimental or observational settings under unconfoundedness. + date_publication: '2024-11-14' + bug_reports: https://github.com/grf-labs/maq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maq + url_git: https://github.com/grf-labs/maq +mAr: + version: 1.2-0 + title: Multivariate AutoRegressive Analysis + maintainer: S. M. Barbosa + description: R functions for the estimation and eigen-decomposition of multivariate + autoregressive models. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mAr + url_git: '' +mar1s: + version: 2.1.1 + title: Multiplicative AR(1) with Seasonal Processes + maintainer: Andrey Paramonov + description: |- + Multiplicative AR(1) with Seasonal is a stochastic + process model built on top of AR(1). The package provides the + following procedures for MAR(1)S processes: fit, compose, decompose, + advanced simulate and predict. + date_publication: '2018-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mar1s + url_git: https://github.com/aparamon/mar1s +maraca: + version: 0.7.1 + title: 'The Maraca Plot: Visualizing Hierarchical Composite Endpoints' + maintainer: Monika Huhn + description: |- + Supports visual interpretation of hierarchical composite + endpoints (HCEs). HCEs are complex constructs used as primary endpoints in + clinical trials, combining outcomes of different types into ordinal endpoints, + in which each patient contributes the most clinically important event (one and + only one) to the analysis. See Karpefors M et al. (2022) + . + date_publication: '2025-01-13' + bug_reports: https://github.com/AstraZeneca/maraca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maraca + url_git: https://github.com/AstraZeneca/maraca +marble: + version: 0.0.3 + title: |- + Robust Marginal Bayesian Variable Selection for Gene-Environment + Interactions + maintainer: Xi Lu + description: Recently, multiple marginal variable selection methods have been developed + and shown to be effective in Gene-Environment interactions studies. We propose + a novel marginal Bayesian variable selection method for Gene-Environment interactions + studies. In particular, our marginal Bayesian method is robust to data contamination + and outliers in the outcome variables. With the incorporation of spike-and-slab + priors, we have implemented the Gibbs sampler based on Markov Chain Monte Carlo. + The core algorithms of the package have been developed in 'C++'. + date_publication: '2024-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marble + url_git: https://github.com/xilustat/marble +march: + version: 3.3.2 + title: Markov Chains + maintainer: Andre Berchtold + description: |- + Computation of various Markovian models for categorical data + including homogeneous Markov chains of any order, MTD models, Hidden Markov + models, and Double Chain Markov Models. + date_publication: '2020-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=march + url_git: '' +marcher: + version: 0.0-2 + title: Migration and Range Change Estimation in R + maintainer: Eliezer Gurarie + description: 'A set of tools for likelihood-based estimation, model selection and + testing of two- and three-range shift and migration models for animal movement + data as described in Gurarie et al. (2017) . Provided + movement data (X, Y and Time), including irregularly sampled data, functions estimate + the time, duration and location of one or two range shifts, as well as the ranging + area and auto-correlation structure of the movment. Tests assess, for example, + whether the shift was "significant", and whether a two-shift migration was a true + return migration.' + date_publication: '2017-04-12' + bug_reports: https://github.com/EliGurarie/marcher/issues + url: '' + url_cran: https://CRAN.R-project.org/package=marcher + url_git: '' +marelac: + version: 2.1.11 + title: Tools for Aquatic Sciences + maintainer: Karline Soetaert + description: |- + Datasets, constants, conversion factors, and utilities for 'MArine', 'Riverine', + 'Estuarine', 'LAcustrine' and 'Coastal' science. + The package contains among others: (1) chemical and + physical constants and datasets, e.g. atomic weights, gas + constants, the earths bathymetry; (2) conversion factors + (e.g. gram to mol to liter, barometric units, + temperature, salinity); (3) physical functions, e.g. to + estimate concentrations of conservative substances, gas + transfer and diffusion coefficients, the Coriolis force + and gravity; (4) thermophysical properties of the + seawater, as from the UNESCO polynomial or from the more + recent derivation based on a Gibbs function. + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marelac + url_git: '' +MareyMap: + version: 1.3.7 + title: Estimation of Meiotic Recombination Rates Using Marey Maps + maintainer: Aurélie Siberchicot + description: Local recombination rates are graphically estimated across a genome + using Marey maps. + date_publication: '2024-01-23' + bug_reports: https://github.com/lbbe-software/MareyMap/issues + url: https://lbbe.univ-lyon1.fr/fr/mareymap;https://lbbe-shiny.univ-lyon1.fr/MareyMapOnline/ + url_cran: https://CRAN.R-project.org/package=MareyMap + url_git: '' +marg: + version: 1.2-2.1 + title: Approximate Marginal Inference for Regression-Scale Models + maintainer: Alessandra R. Brazzale + description: |- + Likelihood inference based on higher order approximations + for linear nonnormal regression models. + date_publication: '2018-04-16' + bug_reports: '' + url: http://statwww.epfl.ch/AA/ + url_cran: https://CRAN.R-project.org/package=marg + url_git: '' +margaret: + version: 0.1.4 + title: Scientometric Analysis Minciencias + maintainer: Bryan Arias + description: The target of 'margaret' is help to extract data from Minciencias to + analyze scientific production in Colombia. + date_publication: '2022-10-03' + bug_reports: https://github.com/coreofscience/margaret/issues + url: '' + url_cran: https://CRAN.R-project.org/package=margaret + url_git: https://github.com/coreofscience/margaret +MargCond: + version: 1.0.0 + title: Joint Marginal-Conditional Model + maintainer: James Proudfoot + description: Fits joint marginal conditional models for multivariate longitudinal + data, as in Proudfoot, Faig, Natarajan, and Xu (2018) . + Development of this package was supported by the UCSD Altman Translational Research + Institute, NIH grant UL1TR001442. The content is solely the responsibility of + the authors and does not necessarily represent the official views of the NIH. + date_publication: '2018-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MargCond + url_git: '' +marginaleffects: + version: 0.25.0 + title: |- + Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis + Tests + maintainer: Vincent Arel-Bundock + description: Compute and plot predictions, slopes, marginal means, and comparisons + (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine + learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence + tests. Calculate uncertainty estimates using the delta method, bootstrapping, + or simulation-based inference. Details can be found in Arel-Bundock, Greifer, + and Heiss (2024) . + date_publication: '2025-02-01' + bug_reports: https://github.com/vincentarelbundock/marginaleffects/issues + url: https://marginaleffects.com/ + url_cran: https://CRAN.R-project.org/package=marginaleffects + url_git: '' +marginalizedRisk: + version: 2024.5-17 + title: Estimating Marginalized Risk + maintainer: Youyi Fong + description: Estimates risk as a function of a marker by integrating over other + covariates in a conditional risk model. + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marginalizedRisk + url_git: '' +MarginalMediation: + version: 0.7.2 + title: Marginal Mediation + maintainer: Tyson S Barrett + description: |- + Provides the ability to perform "Marginal Mediation"--mediation + wherein the indirect and direct effects are in terms of the average marginal effects + (Bartus, 2005, ). + The style of the average marginal effects stems from Thomas Leeper's work on the "margins" package. + This framework allows the use of categorical mediators and outcomes with little change in interpretation + from the continuous mediators/outcomes. See for more details + on the method. + date_publication: '2022-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MarginalMediation + url_git: '' +margins: + version: 0.3.28 + title: Marginal Effects for Model Objects + maintainer: Ben Bolker + description: |- + An R port of the margins command from 'Stata', which can be used to + calculate marginal (or partial) effects from model objects. + date_publication: '2024-07-31' + bug_reports: https://github.com/bbolker/margins/issues + url: '' + url_cran: https://CRAN.R-project.org/package=margins + url_git: https://github.com/bbolker/margins +marima: + version: '2.2' + title: Multivariate ARIMA and ARIMA-X Analysis + maintainer: Henrik Spliid + description: |- + Multivariate ARIMA and ARIMA-X estimation using Spliid's + algorithm (marima()) and simulation (marima.sim()). + date_publication: '2017-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marima + url_git: '' +mark: + version: 0.8.2 + title: Miscellaneous, Analytic R Kernels + maintainer: Jordan Mark Barbone + description: |- + Miscellaneous functions and wrappers for development in other + packages created, maintained by Jordan Mark Barbone. + date_publication: '2024-12-07' + bug_reports: https://github.com/jmbarbone/mark/issues + url: https://jmbarbone.github.io/mark/ + url_cran: https://CRAN.R-project.org/package=mark + url_git: https://github.com/jmbarbone/mark +markdown: + version: '1.13' + title: Render Markdown with 'commonmark' + maintainer: Yihui Xie + description: |- + Render Markdown to full and lightweight HTML/LaTeX documents with + the 'commonmark' package. This package has been superseded by 'litedown'. + date_publication: '2024-06-04' + bug_reports: https://github.com/rstudio/markdown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=markdown + url_git: https://github.com/rstudio/markdown +markdownInput: + version: 0.1.2 + title: Shiny Module for a Markdown Input with Result Preview + maintainer: Julien Diot + description: |- + An R-Shiny module containing a "markdownInput". This input allows + the user to write some markdown code and to preview the result. This input + has been inspired by the "comment" window of . + date_publication: '2020-01-31' + bug_reports: https://github.com/juliendiot42/markdownInput/issues + url: '' + url_cran: https://CRAN.R-project.org/package=markdownInput + url_git: https://github.com/juliendiot42/markdownInput +marked: + version: 1.2.8 + title: Mark-Recapture Analysis for Survival and Abundance Estimation + maintainer: Jeff Laake + description: |- + Functions for fitting various models to capture-recapture data + including mixed-effects Cormack-Jolly-Seber(CJS) and multistate models and + the multi-variate state model structure for survival + estimation and POPAN structured Jolly-Seber models for abundance estimation. + There are also Hidden Markov model (HMM) implementations of CJS and multistate + models with and without state uncertainty and a simulation capability for HMM + models. + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marked + url_git: '' +markerpen: + version: 0.1.1 + title: Marker Gene Detection via Penalized Principal Component Analysis + maintainer: Yixuan Qiu + description: |- + Implementation of the 'MarkerPen' algorithm, short for marker gene detection + via penalized principal component analysis, described in the paper by Qiu, Wang, Lei, + and Roeder (2020, ). 'MarkerPen' is a semi-supervised + algorithm for detecting marker genes by combining prior marker information with bulk + transcriptome data. + date_publication: '2021-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=markerpen + url_git: '' +MarketMatching: + version: 1.2.1 + title: Market Matching and Causal Impact Inference + maintainer: Larsen Kim + description: For a given test market find the best control markets using time series + matching and analyze the impact of an intervention. The intervention could be + a marketing event or some other local business tactic that is being tested. The + workflow implemented in the Market Matching package utilizes dynamic time warping + (the 'dtw' package) to do the matching and the 'CausalImpact' package to analyze + the causal impact. In fact, this package can be considered a "workflow wrapper" + for those two packages. In addition, if you don't have a chosen set of test markets + to match, the Market Matching package can provide suggested test/control market + pairs and pseudo prospective power analysis (measuring causal impact at fake interventions). + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MarketMatching + url_git: '' +marketr: + version: 0.0.2 + title: Tidy Calculation of Marketing Metrics Plus Quick Analysis + maintainer: Chris Umphlett + description: |- + Facilitates tidy calculation of popular quantitative marketing + metrics. It also includes functions for doing analysis that will help + marketers and data analysts better understand the drivers and/or trends + of these metrics. These metrics include Customer Experience Index + and Net Promoter Score + . + date_publication: '2020-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marketr + url_git: '' +markets: + version: 1.1.5 + title: Estimation Methods for Markets in Equilibrium and Disequilibrium + maintainer: Pantelis Karapanagiotis + description: |- + Provides estimation methods for markets in equilibrium and + disequilibrium. Supports the estimation of an equilibrium and + four disequilibrium models with both correlated and independent shocks. + Also provides post-estimation analysis tools, such as aggregation, + marginal effect, and shortage calculations. See Karapanagiotis (2024) + for an overview of the functionality + and examples. The estimation methods are based on full information + maximum likelihood techniques given in + Maddala and Nelson (1974) . They are implemented + using the analytic derivative expressions calculated in + Karapanagiotis (2020) . Standard + errors can be estimated by adjusting for heteroscedasticity or clustering. + The equilibrium estimation constitutes a case of a system of linear, + simultaneous equations. Instead, the disequilibrium models replace the + market-clearing condition with a non-linear, + short-side rule and allow for different specifications of price dynamics. + date_publication: '2024-02-17' + bug_reports: https://github.com/pi-kappa-devel/markets/issues + url: https://markets.pikappa.eu/ + url_cran: https://CRAN.R-project.org/package=markets + url_git: https://github.com/pi-kappa-devel/markets/ +markmyassignment: + version: 0.8.8 + title: Automatic Marking of R Assignments + maintainer: Mans Magnusson + description: |- + Automatic marking of R assignments for students and teachers based + on 'testthat' test suites. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=markmyassignment + url_git: '' +markophylo: + version: 1.0.9 + title: Markov Chain Models for Phylogenetic Trees + maintainer: Utkarsh J. Dang + description: |- + Allows for fitting of maximum likelihood models using Markov chains + on phylogenetic trees for analysis of discrete character data. Examples of such + discrete character data include restriction sites, gene family presence/absence, + intron presence/absence, and gene family size data. Hypothesis-driven user- + specified substitution rate matrices can be estimated. Allows for biologically + realistic models combining constrained substitution rate matrices, site rate + variation, site partitioning, branch-specific rates, allowing for non-stationary + prior root probabilities, correcting for sampling bias, etc. See Dang and Golding + (2016) for more details. + date_publication: '2023-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=markophylo + url_git: '' +markovchain: + version: 0.10.0 + title: Easy Handling Discrete Time Markov Chains + maintainer: Giorgio Alfredo Spedicato + description: |- + Functions and S4 methods to create and manage discrete time Markov + chains more easily. In addition functions to perform statistical (fitting + and drawing random variates) and probabilistic (analysis of their structural + proprieties) analysis are provided. See Spedicato (2017) . + Some functions for continuous times Markov chains depend on the suggested ctmcd package. + date_publication: '2024-11-14' + bug_reports: https://github.com/spedygiorgio/markovchain/issues + url: '' + url_cran: https://CRAN.R-project.org/package=markovchain + url_git: https://github.com/spedygiorgio/markovchain/ +Markovchart: + version: 2.1.5 + title: Markov Chain-Based Cost-Optimal Control Charts + maintainer: Balazs Dobi + description: Functions for cost-optimal control charts with a focus on health care + applications. Compared to assumptions in traditional control chart theory, here, + we allow random shift sizes, random repair and random sampling times. The package + focuses on X-bar charts with a sample size of 1 (representing the monitoring of + a single patient at a time). The methods are described in Zempleni et al. (2004) + , Dobi and Zempleni (2019) and Dobi + and Zempleni (2019) . + date_publication: '2022-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Markovchart + url_git: '' +markovmix: + version: 0.1.3 + title: |- + Mixture of Markov Chains with Support of Higher Orders and + Multiple Sequences + maintainer: Xiurui Zhu + description: |- + Fit mixture of Markov chains of higher orders from multiple + sequences. It is also compatible with ordinary 1-component, 1-order or + single-sequence Markov chains. Various utility functions are provided + to derive transition patterns, transition probabilities per component + and component priors. In addition, print(), predict() and component + extracting/replacing methods are also defined as a convention of + mixture models. + date_publication: '2023-12-02' + bug_reports: https://github.com/zhuxr11/markovmix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=markovmix + url_git: https://github.com/zhuxr11/markovmix +markovMSM: + version: 0.1.3 + title: |- + Methods for Checking the Markov Condition in Multi-State + Survival Data + maintainer: Gustavo Soutinho + description: |- + The inference in multi-state models is traditionally performed under + a Markov assumption that claims that past and future of the process + are independent given the present state. In this package, we + consider tests of the Markov assumption that are applicable to + general multi-state models. Three approaches using existing + methodology are considered: a simple method based on including + covariates depending on the history in Cox models for the transition + intensities; methods based on measuring the discrepancy of the + non-Markov estimators of the transition probabilities to the + Markov Aalen-Johansen estimators; and, finally, methods that were + developed by considering summaries from families of log-rank + statistics where patients are grouped by the state occupied of the + process at a particular time point (see Soutinho G, Meira-Machado L + (2021) and Titman AC, Putter H + (2020) ). + date_publication: '2023-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=markovMSM + url_git: '' +markowitz: + version: 0.1.0 + title: Markowitz Criterion + maintainer: Luana Oliveira + description: The Markowitz criterion is a multicriteria decision-making method that + stands out in risk and uncertainty analysis in contexts where probabilities are + known. This approach represents an evolution of Pascal's criterion by incorporating + the dimension of variability. In this framework, the expected value reflects the + anticipated return, while the standard deviation serves as a measure of risk. + The 'markowitz' package provides a practical and accessible tool for implementing + this method, enabling researchers and professionals to perform analyses without + complex calculations. Thus, the package facilitates the application of the Markowitz + criterion. More details on the method can be found in Octave Jokung-Nguéna (2001, + ISBN 2100055372). + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=markowitz + url_git: https://github.com/luana1909/Markowitiz +MarkowitzR: + version: 1.0.3 + title: Statistical Significance of the Markowitz Portfolio + maintainer: Steven E. Pav + description: |- + A collection of tools for analyzing significance of + Markowitz portfolios, using the delta method on the second moment + matrix, . + date_publication: '2023-08-21' + bug_reports: https://github.com/shabbychef/MarkowitzR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MarkowitzR + url_git: https://github.com/shabbychef/MarkowitzR +marlod: + version: 0.1.2 + title: Marginal Modeling for Exposure Data with Values Below the LOD + maintainer: I-Chen Chen + description: Functions of marginal mean and quantile regression models are used + to analyze environmental exposure and biomonitoring data with repeated measurements + and non-detects (i.e., values below the limit of detection (LOD)), as well as + longitudinal exposure data that include non-detects and time-dependent covariates. + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marlod + url_git: '' +marmap: + version: 1.0.10 + title: Import, Plot and Analyze Bathymetric and Topographic Data + maintainer: Benoit Simon-Bouhet + description: Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, + ), GEBCO (General Bathymetric Chart of the Oceans, ) + and other sources, plot xyz data to prepare publication-ready figures, analyze + xyz data to extract transects, get depth / altitude based on geographical coordinates, + or calculate z-constrained least-cost paths. + date_publication: '2023-03-24' + bug_reports: https://github.com/ericpante/marmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=marmap + url_git: https://github.com/ericpante/marmap +MARMoT: + version: 0.0.4 + title: |- + Matching on Poset-Based Average Rank for Multiple Treatments + (MARMoT) + maintainer: Alberto Calore + description: |- + It contains the function to apply MARMoT balancing technique discussed in: Silan, Boccuzzo, Arpino (2021) , Silan, Belloni, Boccuzzo, (2023) ; + furthermore it contains a function for computing the Deloof's approximation of the average rank + (and also a parallelized version) and a function to compute the Absolute Standardized Bias. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MARMoT + url_git: '' +marp: + version: 0.1.0 + title: Model-Averaged Renewal Process + maintainer: Jie Kang + description: |- + To implement a model-averaging approach with different renewal + models, with a primary focus on forecasting large earthquakes. Based on + six renewal models (i.e., Poisson, Gamma, Log-Logistics, Weibull, + Log-Normal and BPT), model-averaged point estimates are calculated using + AIC (or BIC) weights. Additionally, both percentile and studentized + bootstrapped model-averaged confidence intervals are constructed. In + comparison, point and interval estimation from the individual or "best" + model (determined via model selection) can be retrieved. + date_publication: '2022-08-11' + bug_reports: https://github.com/kanji709/marp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=marp + url_git: https://github.com/kanji709/marp +marqLevAlg: + version: 2.0.8 + title: |- + A Parallelized General-Purpose Optimization Based on + Marquardt-Levenberg Algorithm + maintainer: Viviane Philipps + description: |- + This algorithm provides a numerical solution to the + problem of unconstrained local minimization (or maximization). It is particularly suited for complex problems and more efficient than + the Gauss-Newton-like algorithm when starting from points very + far from the final minimum (or maximum). Each iteration is parallelized and convergence relies on a stringent stopping criterion based on the first and second derivatives. See Philipps et al, 2021 . + date_publication: '2023-03-22' + bug_reports: https://github.com/VivianePhilipps/marqLevAlgParallel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=marqLevAlg + url_git: '' +marquee: + version: 1.0.0 + title: Markdown Parser and Renderer for R Graphics + maintainer: Thomas Lin Pedersen + description: |- + Provides the mean to parse and render markdown text with grid along + with facilities to define the styling of the text. + date_publication: '2025-01-20' + bug_reports: https://github.com/r-lib/marquee/issues + url: https://marquee.r-lib.org + url_cran: https://CRAN.R-project.org/package=marquee + url_git: https://github.com/r-lib/marquee +marradistrees: + version: '1.0' + title: |- + Plots a Tree-Like Representation of a Numerical Variable + (Marradi's Tree) + maintainer: Massimo Cannas + description: |- + Provides a single function plotting Marradi's trees: a graphical representation + of a numerical variable for comparing the variable mean and standard deviation across subgroups. See A. Marradi "L'analisi monovariata" (1993, ISBN: 9788820496876). + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=marradistrees + url_git: '' +MARSANNhybrid: + version: 0.1.0 + title: MARS Based ANN Hybrid Model + maintainer: Pankaj Das + description: Multivariate Adaptive Regression Spline (MARS) based Artificial Neural + Network (ANN) hybrid model is combined Machine learning hybrid approach which + selects important variables using MARS and then fits ANN on the extracted important + variables. + date_publication: '2021-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MARSANNhybrid + url_git: '' +MARSGWR: + version: 0.1.0 + title: |- + A Hybrid Spatial Model for Capturing Spatially Varying + Relationships Between Variables in the Data + maintainer: Nobin Chandra Paul + description: |- + It is a hybrid spatial model that combines the strength of two widely used regression models, MARS (Multivariate Adaptive Regression Splines) and + GWR (Geographically Weighted Regression) to provide an effective approach for predicting a response variable at unknown locations. The MARS model + is used in the first step of the development of a hybrid model to identify the most important predictor variables that assist in predicting the response + variable. For method details see, Friedman, J.H. (1991). .The GWR model is then used to predict the response variable at + testing locations based on these selected variables that account for spatial variations in the relationships between the variables. This hybrid model + can improve the accuracy of the predictions compared to using an individual model alone.This developed hybrid spatial model can be useful particularly in + cases where the relationship between the response variable and predictor variables is complex and non-linear, and varies across locations. + date_publication: '2023-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MARSGWR + url_git: '' +MARSS: + version: 3.11.9 + title: Multivariate Autoregressive State-Space Modeling + maintainer: Elizabeth Eli Holmes + description: |- + The MARSS package provides maximum-likelihood parameter + estimation for constrained and unconstrained linear multivariate autoregressive + state-space (MARSS) models, including partially deterministic models. MARSS models are a class + of dynamic linear model (DLM) and vector autoregressive model (VAR) + model. Fitting available via Expectation-Maximization (EM), BFGS (using optim), and 'TMB' + (using the 'marssTMB' companion package). Functions are provided for parametric and + innovations bootstrapping, Kalman filtering and smoothing, model selection criteria including + bootstrap AICb, confidences intervals via the Hessian approximation or bootstrapping, and all + conditional residual types. See the user guide for examples of dynamic factor analysis, + dynamic linear models, outlier and shock detection, and multivariate AR-p models. + Online workshops (lectures, eBook, and computer labs) + at . + date_publication: '2024-02-19' + bug_reports: https://github.com/atsa-es/MARSS/issues + url: https://atsa-es.github.io/MARSS/ + url_cran: https://CRAN.R-project.org/package=MARSS + url_git: '' +MARSSVRhybrid: + version: 0.1.0 + title: MARS SVR Hybrid + maintainer: Pankaj Das + description: Multivariate Adaptive Regression Spline (MARS) based Support Vector + Regression (SVR) hybrid model is combined Machine learning hybrid approach which + selects important variables using MARS and then fits SVR on the extracted important + variables. + date_publication: '2021-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MARSSVRhybrid + url_git: '' +MARVEL: + version: 1.4.0 + title: Revealing Splicing Dynamics at Single-Cell Resolution + maintainer: Sean Wen + description: Alternative splicing represents an additional and underappreciated + layer of complexity underlying gene expression profiles. Nevertheless, there remains + hitherto a paucity of software to investigate splicing dynamics at single-cell + resolution. 'MARVEL' enables splicing analysis of single-cell RNA-sequencing data + generated from plate- and droplet-based library preparation methods. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MARVEL + url_git: '' +MarZIC: + version: 1.0.0 + title: |- + Marginal Mediation Effects with Zero-Inflated Compositional + Mediator + maintainer: Zhigang Li + description: |- + A way to estimate and test marginal mediation effects for + zero-inflated compositional mediators. Estimates of Natural Indirect Effect (NIE), + Natural Direct Effect (NDE) of each taxon, as well as their standard errors and + confident intervals, were provided as outputs. Zeros will not be imputed during + analysis. See Wu et al. (2022) . + date_publication: '2023-12-04' + bug_reports: '' + url: https://www.mdpi.com/2073-4425/13/6/1049 + url_cran: https://CRAN.R-project.org/package=MarZIC + url_git: '' +mas: + version: '0.3' + title: Marker Association Studies + maintainer: Alencar Xavier + description: Genome-wide association analysis that accommodate membership information, + variance adjustment, and correlated responses. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mas + url_git: '' +maSAE: + version: 2.0.3 + title: Mandallaz' Model-Assisted Small Area Estimators + maintainer: Andreas Dominik Cullmann + description: |- + An S4 implementation of the unbiased extension of + the model- assisted synthetic-regression estimator proposed by + Mandallaz (2013) , Mandallaz et al. (2013) + and Mandallaz (2014) + . It yields smaller variances than the + standard bias correction, the generalised regression estimator. + date_publication: '2021-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maSAE + url_git: https://gitlab.com/fvafrCU/maSAE +mase: + version: 0.1.5.2 + title: Model-Assisted Survey Estimators + maintainer: Kelly McConville + description: |- + A set of model-assisted survey estimators and corresponding + variance estimators for single stage, unequal probability, without replacement + sampling designs. All of the estimators can be written as a generalized + regression estimator with the Horvitz-Thompson, ratio, post-stratified, and + regression estimators summarized by Sarndal et al. (1992, ISBN:978-0-387-40620-6). + Two of the estimators employ a statistical learning model as the assisting model: + the elastic net regression estimator, which is an extension of the lasso regression + estimator given by McConville et al. (2017) , and the + regression tree estimator described in McConville and Toth (2017) . + The variance estimators which approximate the joint inclusion probabilities can + be found in Berger and Tille (2009) and the + bootstrap variance estimator is presented in Mashreghi et al. (2016) + . + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mase + url_git: '' +mashr: + version: 0.2.79 + title: Multivariate Adaptive Shrinkage + maintainer: Peter Carbonetto + description: |- + Implements the multivariate adaptive shrinkage (mash) + method of Urbut et al (2019) for + estimating and testing large numbers of effects in many conditions + (or many outcomes). Mash takes an empirical Bayes approach to + testing and effect estimation; it estimates patterns of similarity + among conditions, then exploits these patterns to improve accuracy + of the effect estimates. The core linear algebra is implemented in + C++ for fast model fitting and posterior computation. + date_publication: '2023-10-18' + bug_reports: https://github.com/stephenslab/mashr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mashr + url_git: https://github.com/stephenslab/mashr +maskr: + version: 0.1.0 + title: Visual Class for Vectors with Non-Publishing Requirements + maintainer: Ian Powell + description: |- + Create vectors with sticky flags for elements that should not be + displayed. Numeric vectors have basic subset and arithmetic methods + implemented. + date_publication: '2024-08-23' + bug_reports: https://github.com/inpowell/maskr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maskr + url_git: https://github.com/inpowell/maskr +maskRangeR: + version: '1.1' + title: Mask Species Geographic Ranges + maintainer: Cory Merow + description: |- + Mask ranges based on expert + knowledge or remote sensing layers. These tools can + be combined to quantitatively and reproducibly + generate a new map or to update an existing map. + Methods include expert opinion and data-driven + tools to generate thresholds for binary masks. + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maskRangeR + url_git: '' +MASS: + version: 7.3-65 + title: Support Functions and Datasets for Venables and Ripley's MASS + maintainer: Brian Ripley + description: |- + Functions and datasets to support Venables and Ripley, + "Modern Applied Statistics with S" (4th edition, 2002). + date_publication: '2025-02-28' + bug_reports: '' + url: http://www.stats.ox.ac.uk/pub/MASS4/ + url_cran: https://CRAN.R-project.org/package=MASS + url_git: '' +masscor: + version: 0.0.7.1 + title: Mass Measurement Corrections + maintainer: Cristhian Paredes + description: |- + Mass measurement corrections and uncertainties using calibration + data, as recommended by EURAMET's guideline No. 18 (2015) + ISBN:978-3-942992-40-4 . The package provides classes, functions, and + methods for storing information contained in calibration certificates + and converting balance readings to both conventional mass and real mass. + For the latter, the Magnitude of the Air Buoyancy Correction factor employs + models (such as the CIMP-2007 formula revised by Picard, Davis, Gläser, and + Fujii (2008) ) to estimate the local air + density using measured environmental conditions. + date_publication: '2021-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=masscor + url_git: '' +MASSExtra: + version: 1.2.2 + title: Some 'MASS' Enhancements + maintainer: Bill Venables + description: |- + Some enhancements, extensions and additions + to the facilities of the recommended 'MASS' package + that are useful mainly for teaching purposes, with + more convenient default settings and user interfaces. + Key functions from 'MASS' are imported and re-exported + to avoid masking conflicts. In addition we provide + some additional functions mainly used to illustrate + coding paradigms and techniques, such as Gramm-Schmidt + orthogonalisation and generalised eigenvalue problems. + date_publication: '2023-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MASSExtra + url_git: '' +Massign: + version: 1.1.0 + title: Simple Matrix Construction + maintainer: Erik-Jan van Kesteren + description: |- + Constructing matrices for quick prototyping can be a nuisance, + requiring the user to think about how to fill the matrix with values using + the matrix() function. The %<-% operator solves that issue by allowing the + user to construct matrices using code that shows the actual matrices. + date_publication: '2018-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Massign + url_git: '' +massiveGST: + version: 1.2.3 + title: Competitive Gene Sets Test with the Mann-Whitney-Wilcoxon Test + maintainer: Stefano Maria Pagnotta + description: Friendly implementation of the Mann-Whitney-Wilcoxon test for competitive + gene set enrichment analysis. + date_publication: '2023-03-29' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=massiveGST + url_git: +massProps: + version: 0.2.0 + title: Calculate Mass Properties and Uncertainties of Tree Structures + maintainer: James Steven Jenkins + description: Recursively calculates mass properties (mass, center of mass, moments + and products of inertia, and optionally, their uncertainties) for arbitrary decomposition + trees. R. L. Zimmerman, J. H. Nakai. (2005) ). + date_publication: '2025-01-30' + bug_reports: https://github.com/jsjuni/massProps/issues + url: https://jsjuni.github.io/massProps/ + url_cran: https://CRAN.R-project.org/package=massProps + url_git: https://github.com/jsjuni/massProps +MASSTIMATE: + version: 2.0-1 + title: Body Mass Estimation Equations for Vertebrates + maintainer: Nicolas E. Campione + description: Estimation equations are from a variety of sources and associated error + estimation. + date_publication: '2020-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MASSTIMATE + url_git: '' +MassWateR: + version: 2.1.5 + title: Quality Control and Analysis of Massachusetts Water Quality Data + maintainer: Marcus Beck + description: |- + Methods for quality control and exploratory analysis of surface + water quality data collected in Massachusetts, USA. Functions are developed + to facilitate data formatting for the Water Quality Exchange Network + and reporting + of data quality objectives to state agencies. Quality control methods are + from Massachusetts Department of Environmental Protection (2020) + . + date_publication: '2024-10-20' + bug_reports: https://github.com/massbays-tech/MassWateR/issues + url: + url_cran: https://CRAN.R-project.org/package=MassWateR + url_git: +mastif: + version: '2.3' + title: Mast Inference and Forecasting + maintainer: James S. Clark + description: Analyzes production and dispersal of seeds dispersed from trees and + recovered in seed traps. Motivated by long-term inventory plots where seed collections + are used to infer seed production by each individual plant. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mastif + url_git: '' +MAT: + version: 2.3.2 + title: Multidimensional Adaptive Testing + maintainer: Seung W. Choi + description: Simulates Multidimensional Adaptive Testing using the multidimensional + three-parameter logistic model as described in Segall (1996) , + van der Linden (1999) , Reckase (2009) , + and Mulder & van der Linden (2009) . + date_publication: '2024-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAT + url_git: '' +MATA: + version: 0.7.1 + title: |- + Model-Averaged Tail Area (MATA) Confidence Interval and + Distribution + maintainer: Daniel Turek + description: |- + Calculates Model-Averaged Tail Area Wald + (MATA-Wald) confidence intervals, and MATA-Wald confidence densities + and distributions, which are constructed using single-model + frequentist estimators and model weights. See Turek and Fletcher + (2012) and Fletcher et al (2019) + for details. + date_publication: '2021-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MATA + url_git: '' +matahari: + version: 0.1.3 + title: Spy on Your R Session + maintainer: Sean Kross + description: |- + Conveniently log everything you type into the R console. Logs are + are stored as tidy data frames which can then be analyzed using 'tidyverse' + style tools. + date_publication: '2020-02-06' + bug_reports: https://github.com/jhudsl/matahari/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matahari + url_git: https://github.com/jhudsl/matahari +matchedcc: + version: 0.1.1 + title: '''Stata''-Like Matched Case-Control Analysis' + maintainer: Simon R Parker + description: |- + Calculate multiple statistics with confidence intervals for matched + case-control data including risk difference, risk ratio, relative + difference, and the odds ratio. Results are equivalent to those from + 'Stata', and you can choose how to format your input data. Methods used are + those described on page 56 the 'Stata' documentation for "Epitab - Tables + for Epidemologists" . + date_publication: '2024-11-21' + bug_reports: https://github.com/simpar1471/matchedcc/issues + url: https://simpar1471.github.io/matchedcc/ + url_cran: https://CRAN.R-project.org/package=matchedcc + url_git: https://github.com/simpar1471/matchedcc/ +matchFeat: + version: '1.0' + title: One-to-One Feature Matching + maintainer: David Degras + description: Statistical methods to match feature vectors between multiple datasets + in a one-to-one fashion. Given a fixed number of classes/distributions, for each + unit, exactly one vector of each class is observed without label. The goal is + to label the feature vectors using each label exactly once so to produce the best + match across datasets, e.g. by minimizing the variability within classes. Statistical + solutions based on empirical loss functions and probabilistic modeling are provided. + The 'Gurobi' software and its 'R' interface package are required for one of the + package functions (match.2x()) and can be obtained at + (free academic license). For more details, refer to Degras (2022) + "Scalable feature matching for large data collections" and Bandelt, Maas, and + Spieksma (2004) "Local search heuristics for + multi-index assignment problems with decomposable costs". + date_publication: '2022-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matchFeat + url_git: '' +MatchGATE: + version: 0.0.10 + title: Estimate Group Average Treatment Effects with Matching + maintainer: Zhaoqing Tian + description: Two novel matching-based methods for estimating group average treatment + effects (GATEs). The match_y1y0() and match_y1y0_bc() functions are used for imputing + the potential outcomes based on matching and bias-corrected matching techniques, + respectively. The EstGATE() function is employed to estimate the GATE after imputing + the potential outcomes. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MatchGATE + url_git: '' +Matching: + version: 4.10-15 + title: |- + Multivariate and Propensity Score Matching with Balance + Optimization + maintainer: Jasjeet Singh Sekhon + description: |- + Provides functions for multivariate and propensity score matching + and for finding optimal balance based on a genetic search algorithm. + A variety of univariate and multivariate metrics to + determine if balance has been obtained are also provided. For + details, see the paper by Jasjeet Sekhon + (2007, ). + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Matching + url_git: https://github.com/JasjeetSekhon/Matching +matchingMarkets: + version: 1.0-4 + title: Analysis of Stable Matchings + maintainer: Thilo Klein + description: |- + Implements structural estimators to correct for + the sample selection bias from observed outcomes in matching + markets. This includes one-sided matching of agents into groups + (Klein, 2015) + as well as two-sided matching of students to schools + (Aue et al., 2020) . + The package also contains algorithms to find stable matchings + in the three most common matching problems: the stable roommates + problem (Irving, 1985) , + the college admissions problem (Gale and Shapley, 1962) , + and the house allocation problem (Shapley and Scarf, 1974) . + date_publication: '2023-08-08' + bug_reports: https://github.com/thiloklein/matchingMarkets/issues + url: https://matchingMarkets.org + url_cran: https://CRAN.R-project.org/package=matchingMarkets + url_git: '' +matchingR: + version: 1.3.3 + title: Matching Algorithms in R and C++ + maintainer: Jan Tilly + description: |- + Computes matching algorithms quickly using Rcpp. + Implements the Gale-Shapley Algorithm to compute the stable + matching for two-sided markets, such as the stable marriage + problem and the college-admissions problem. Implements Irving's + Algorithm for the stable roommate problem. Implements the top + trading cycle algorithm for the indivisible goods trading problem. + date_publication: '2021-05-25' + bug_reports: https://github.com/jtilly/matchingR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=matchingR + url_git: https://github.com/jtilly/matchingR/ +MatchIt: + version: 4.7.0 + title: Nonparametric Preprocessing for Parametric Causal Inference + maintainer: Noah Greifer + description: |- + Selects matched samples of the original treated and + control groups with similar covariate distributions -- can be + used to match exactly on covariates, to match on propensity + scores, or perform a variety of other matching procedures. The + package also implements a series of recommendations offered in + Ho, Imai, King, and Stuart (2007) . (The + 'gurobi' package, which is not on CRAN, is optional and comes with + an installation of the Gurobi Optimizer, available at + .) + date_publication: '2025-01-12' + bug_reports: https://github.com/kosukeimai/MatchIt/issues + url: https://kosukeimai.github.io/MatchIt/ + url_cran: https://CRAN.R-project.org/package=MatchIt + url_git: https://github.com/kosukeimai/MatchIt +MatchLinReg: + version: 0.8.1 + title: Combining Matching and Linear Regression for Causal Inference + maintainer: Alireza S. Mahani + description: Core functions as well as diagnostic and calibration tools for combining + matching and linear regression for causal inference in observational studies. + date_publication: '2022-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MatchLinReg + url_git: '' +matchmaker: + version: 0.1.1 + title: Flexible Dictionary-Based Cleaning + maintainer: Zhian N. Kamvar + description: |- + Provides flexible dictionary-based + cleaning that allows users to specify implicit and explicit missing data, + regular expressions for both data and columns, and global matches, while + respecting ordering of factors. This package is part of the 'RECON' + () toolkit for outbreak analysis. + date_publication: '2020-02-21' + bug_reports: '' + url: https://www.repidemicsconsortium.org/matchmaker + url_cran: https://CRAN.R-project.org/package=matchmaker + url_git: https://github.com/reconhub/matchmaker +matchMulti: + version: 1.1.12.1 + title: Optimal Multilevel Matching using a Network Algorithm + maintainer: Sam Pimentel + description: |- + Performs multilevel matches for data with cluster- + level treatments and individual-level outcomes using a network + optimization algorithm. Functions for checking balance at the + cluster and individual levels are also provided, as are methods + for permutation-inference-based outcome analysis. Details in + Pimentel et al. (2018) . The optmatch + package, which is useful for running many of the provided + functions, may be downloaded from Github at + if not available on + CRAN. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matchMulti + url_git: '' +matchr: + version: 0.1.0 + title: Pattern Matching and Enumerated Types in R + maintainer: Christopher Mann + description: |- + Inspired by pattern matching and enum types in Rust + and many functional programming languages, this package offers + an updated version of the 'switch' function called 'Match' that + accepts atomic values, functions, expressions, and enum variants. + Conditions and return expressions are separated by '->' and + multiple conditions can be associated with the same return expression + using '|'. 'Match' also includes support for 'fallthrough'. The + package also replicates the Result and Option enums from Rust. + date_publication: '2021-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matchr + url_git: '' +MatchThem: + version: 1.2.1 + title: Matching and Weighting Multiply Imputed Datasets + maintainer: Farhad Pishgar + description: Provides essential tools for the pre-processing techniques of matching + and weighting multiply imputed datasets. The package includes functions for matching + within and across multiply imputed datasets using various methods, estimating + weights for units in the imputed datasets using multiple weighting methods, calculating + causal effect estimates in each matched or weighted dataset using parametric or + non-parametric statistical models, and pooling the resulting estimates according + to Rubin's rules (please see + for more details). + date_publication: '2024-04-02' + bug_reports: https://github.com/FarhadPishgar/MatchThem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MatchThem + url_git: https://github.com/FarhadPishgar/MatchThem +matconv: + version: 0.4.2 + title: A Code Converter from the Matlab/Octave Language to R + maintainer: Siddarta Jairam + description: |- + Transferring over a code base from Matlab to R is often a repetitive + and inefficient use of time. This package provides a translator for Matlab / + Octave code into R code. It does some syntax changes, but most of the heavy + lifting is in the function changes since the languages are so similar. + Options for different data structures and the functions that can be changed + are given. The Matlab code should be mostly in adherence to the standard + style guide but some effort has been made to accommodate different number of + spaces and other small syntax issues. This will not make the code more R + friendly and may not even run afterwards. However, the rudimentary syntax, + base function and data structure conversion is done quickly so that the + maintainer can focus on changes to the design structure. + date_publication: '2021-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matconv + url_git: '' +mateable: + version: 0.3.2 + title: Assess Mating Potential in Space and Time + maintainer: Stuart Wagenius + description: |- + Simulate, manage, visualize, and analyze spatially and temporally + explicit datasets of mating potential. Implements methods to calculate + synchrony, proximity, and compatibility.Synchrony calculations are based on + methods described in Augspurger (1983) , + Kempenaers (1993) , Ison et al. (2014) + , and variations on these, as described. + date_publication: '2023-02-04' + bug_reports: https://github.com/stuartWagenius/mateable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mateable + url_git: https://github.com/stuartWagenius/mateable +materialmodifier: + version: 1.2.0 + title: Apply Photo Editing Effects + maintainer: Hiroyuki Tsuda + description: |- + You can apply image processing effects that modifies the perceived material properties of objects + in photos, such as gloss, smoothness, and blemishes. This is an implementation of the algorithm proposed by + Boyadzhiev et al. (2015) "Band-Sifting Decomposition for Image Based Material Editing". + Documentation and practical tips of the package is available at . + date_publication: '2023-05-19' + bug_reports: https://github.com/tsuda16k/materialmodifier/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=materialmodifier + url_git: https://github.com/tsuda16k/materialmodifier +mathjaxr: + version: 1.6-0 + title: Using 'Mathjax' in Rd Files + maintainer: Wolfgang Viechtbauer + description: Provides 'MathJax' and macros to enable its use within Rd files for + rendering equations in the HTML help files. + date_publication: '2022-02-28' + bug_reports: https://github.com/wviechtb/mathjaxr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mathjaxr + url_git: https://github.com/wviechtb/mathjaxr +mathml: + version: '1.3' + title: Translate R Expressions to 'MathML' and 'LaTeX'/'MathJax' + maintainer: Matthias Gondan + description: |- + Translate R expressions to 'MathML' or 'MathJax'/'LaTeX' so that + they can be rendered in R markdown documents and shiny apps. This package + depends on R package 'rolog', which requires an installation of the + 'SWI'-'Prolog' runtime either from 'swi-prolog.org' or from R + package 'rswipl'. + date_publication: '2025-02-02' + bug_reports: https://github.com/mgondan/mathml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mathml + url_git: https://github.com/mgondan/mathml +mathpix: + version: 0.6.0 + title: Support for the 'Mathpix' API (Image to 'LaTeX') + maintainer: Jonathan Carroll + description: |- + Given an image of a formula (typeset or handwritten) this package + provides calls to the 'Mathpix' service to produce the 'LaTeX' code which should + generate that image, and pastes it into a (e.g. an 'rmarkdown') document. + See for full details. 'Mathpix' is an external service + and use of the API is subject to their terms and conditions. + date_publication: '2023-11-06' + bug_reports: https://github.com/jonocarroll/mathpix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mathpix + url_git: https://github.com/jonocarroll/mathpix +matlab: + version: 1.0.4.1 + title: '''MATLAB'' Emulation Package' + maintainer: P. Roebuck + description: Emulate 'MATLAB' code using 'R'. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matlab + url_git: '' +matlab2r: + version: 1.5.0 + title: Translation Layer from MATLAB to R + maintainer: Waldir Leoncio + description: |- + Allows users familiar with MATLAB to use MATLAB-named functions in + R. Several basic MATLAB functions are written in this package to mimic the + behavior of their original counterparts, with more to come as this package + grows. + date_publication: '2023-01-31' + bug_reports: https://github.com/ocbe-uio/matlab2r/issues + url: https://ocbe-uio.github.io/matlab2r/ + url_cran: https://CRAN.R-project.org/package=matlab2r + url_git: '' +matlabr: + version: 1.5.2 + title: An Interface for MATLAB using System Calls + maintainer: John Muschelli + description: |- + Provides users to call MATLAB from using the "system" command. + Allows users to submit lines of code or MATLAB m files. + This is in comparison to 'R.matlab', which creates a MATLAB server. + date_publication: '2018-08-13' + bug_reports: https://github.com/muschellij2/matlabr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matlabr + url_git: '' +matlib: + version: 1.0.0 + title: |- + Matrix Functions for Teaching and Learning Linear Algebra and + Multivariate Statistics + maintainer: Michael Friendly + description: |- + A collection of matrix functions for teaching and learning matrix + linear algebra as used in multivariate statistical methods. These functions are + mainly for tutorial purposes in learning matrix algebra ideas using R. In some + cases, functions are provided for concepts available elsewhere in R, but where + the function call or name is not obvious. In other cases, functions are provided + to show or demonstrate an algorithm. In addition, a collection of functions are + provided for drawing vector diagrams in 2D and 3D. + date_publication: '2024-10-02' + bug_reports: https://github.com/friendly/matlib/issues + url: http://friendly.github.io/matlib/ + url_cran: https://CRAN.R-project.org/package=matlib + url_git: https://github.com/friendly/matlib +matman: + version: 1.1.3 + title: Material Management + maintainer: Leon Binder + description: A set of functions, classes and methods for performing ABC and ABC/XYZ + analyses, identifying overperforming, underperforming and constantly performing + items, and plotting, analyzing as well as predicting the temporal development + of items. + date_publication: '2021-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matman + url_git: '' +matpow: + version: 0.1.2 + title: Matrix Powers + maintainer: Norm Matloff + description: |- + A general framework for computing powers of matrices. A + key feature is the capability for users to write callback functions, + called after each iteration, thus enabling customization for specific + applications. Diverse types of matrix classes/matrix multiplication + are accommodated. If the multiplication type computes in parallel, + then the package computation is also parallel. + date_publication: '2022-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matpow + url_git: '' +matrans: + version: 0.1.0 + title: Model Averaging-Assisted Optimal Transfer Learning + maintainer: Xiaonan Hu + description: Transfer learning, as a prevailing technique in computer sciences, + aims to improve the performance of a target model by leveraging auxiliary information + from heterogeneous source data. We provide novel tools for multi-source transfer + learning under statistical models based on model averaging strategies, including + linear regression models, partially linear models. Unlike existing transfer learning + approaches, this method integrates the auxiliary information through data-driven + weight assignments to avoid negative transfer. This is the first package for transfer + learning based on the optimal model averaging frameworks, providing efficient + implementations for practitioners in multi-source data modeling. The details are + described in Hu and Zhang (2023) . + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matrans + url_git: '' +matricks: + version: 0.8.2 + title: Useful Tricks for Matrix Manipulation + maintainer: Krzysztof Joachimiak + description: |- + Provides functions, which make matrix creation conciser + (such as the core package's function m() for rowwise matrix definition or + runifm() for random value matrices). + Allows to set multiple matrix values at once, by using list of formulae. + Provides additional matrix operators and dedicated plotting function. + date_publication: '2020-02-23' + bug_reports: https://github.com/krzjoa/matricks/issues + url: https://krzjoa.github.io/matricks/ + url_cran: https://CRAN.R-project.org/package=matricks + url_git: https://github.com/krzjoa/matricks +matRiks: + version: 0.1.3 + title: Generates Raven-Like Matrices According to Rules + maintainer: Andrea Brancaccio + description: |- + Generates Raven like matrices according to different rules and the response list associated to the matrix. The package can generate matrices composed of 4 or 9 cells, along with a response list of 11 elements (the correct response + 10 incorrect responses). The matrices can be generated according to both logical rules (i.e., the relationships between the elements in the matrix are manipulated to create the matrix) and visual-spatial rules (i.e., the visual or spatial characteristics of the elements are manipulated to generate the matrix). + The graphical elements of this package are based on the 'DescTools' package. + This package has been developed within the PRIN2020 Project (Prot. 20209WKCLL) titled "Computerized, Adaptive and Personalized Assessment of Executive Functions and Fluid Intelligence" and founded by the Italian Ministry of Education and Research. + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matRiks + url_git: '' +matrisk: + version: 0.1.0 + title: Macroeconomic-at-Risk + maintainer: Quentin Lajaunie + description: The Macroeconomics-at-Risk (MaR) approach is based on a two-step semi-parametric + estimation procedure that allows to forecast the full conditional distribution + of an economic variable at a given horizon, as a function of a set of factors. + These density forecasts are then be used to produce coherent forecasts for any + downside risk measure, e.g., value-at-risk, expected shortfall, downside entropy. + Initially introduced by Adrian et al. (2019) to reveal + the vulnerability of economic growth to financial conditions, the MaR approach + is currently extensively used by international financial institutions to provide + Value-at-Risk (VaR) type forecasts for GDP growth (Growth-at-Risk) or inflation + (Inflation-at-Risk). This package provides methods for estimating these models. + Datasets for the US and the Eurozone are available to allow testing of the Adrian + et al (2019) model. This package constitutes a useful toolbox (data and functions) + for private practitioners, scholars as well as policymakers. + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matrisk + url_git: '' +Matrix: + version: 1.7-2 + title: Sparse and Dense Matrix Classes and Methods + maintainer: Martin Maechler + description: |- + A rich hierarchy of sparse and dense matrix classes, + including general, symmetric, triangular, and diagonal matrices + with numeric, logical, or pattern entries. Efficient methods for + operating on such matrices, often wrapping the 'BLAS', 'LAPACK', + and 'SuiteSparse' libraries. + date_publication: '2025-01-23' + bug_reports: https://R-forge.R-project.org/tracker/?atid=294&group_id=61 + url: '' + url_cran: https://CRAN.R-project.org/package=Matrix + url_git: https://Matrix.R-forge.R-project.org +matrixcalc: + version: 1.0-6 + title: Collection of Functions for Matrix Calculations + maintainer: S. Thomas Kelly + description: |- + A collection of functions to support matrix calculations + for probability, econometric and numerical analysis. There are + additional functions that are comparable to APL functions which + are useful for actuarial models such as pension mathematics. + This package is used for teaching and research purposes at the + Department of Finance and Risk Engineering, New York + University, Polytechnic Institute, Brooklyn, NY 11201. + Horn, R.A. (1990) Matrix Analysis. ISBN 978-0521386326. + Lancaster, P. (1969) Theory of Matrices. ISBN 978-0124355507. + Lay, D.C. (1995) Linear Algebra: And Its Applications. ISBN 978-0201845563. + date_publication: '2022-09-14' + bug_reports: https://github.com/TomKellyGenetics/matrixcalc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixcalc + url_git: '' +MatrixCorrelation: + version: 0.10.0 + title: Matrix Correlation Coefficients + maintainer: Kristian Hovde Liland + description: |- + Computation and visualization of matrix correlation coefficients. + The main method is the Similarity of Matrices Index, while various related + measures like r1, r2, r3, r4, Yanai's GCD, RV, RV2, adjusted RV, Rozeboom's + linear correlation and Coxhead's coefficient are included + for comparison and flexibility. + date_publication: '2022-04-18' + bug_reports: https://github.com/khliland/MatrixCorrelation/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=MatrixCorrelation + url_git: https://github.com/khliland/MatrixCorrelation/ +matrixcut: + version: 0.0.1 + title: Determines Clustering Threshold Based on Similarity Values + maintainer: Matthew Cserhati + description: 'The user must supply a matrix filled with similarity values. The software + will search for significant differences between similarity values at different + hierarchical levels. The algorithm will return a Loess-smoothed plot of the similarity + values along with the inflection point, if there are any. There is the option + to search for an inflection point within a specified range. The package also has + a function that will return the matrix components at a specified cutoff. References: + Mullner. ; Cserhati, Carter. (2020, Journal of Creation 34(3):41-50), + .' + date_publication: '2023-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matrixcut + url_git: '' +matrixdist: + version: 1.1.9 + title: Statistics for Matrix Distributions + maintainer: Martin Bladt + description: |- + Tools for phase-type distributions including the following variants: + continuous, discrete, multivariate, in-homogeneous, right-censored, and regression. + Methods for functional evaluation, simulation and estimation using the + expectation-maximization (EM) algorithm are provided for all models. + The methods of this package are based on the following references. + Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm, + Olsson, M. (1996). Estimation of phase-type distributions from censored data, + Albrecher, H., & Bladt, M. (2019) , + Albrecher, H., Bladt, M., & Yslas, J. (2022) , + Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022) , + Bladt, M., & Yslas, J. (2022) , + Bladt, M. (2022) , + Bladt, M. (2023) , + Albrecher, H., Bladt, M., & Mueller, A. (2023) , + Bladt, M. & Yslas, J. (2023) . + date_publication: '2023-08-08' + bug_reports: https://github.com/martinbladt/matrixdist_1.0/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixdist + url_git: https://github.com/martinbladt/matrixdist_1.0 +MatrixEQTL: + version: '2.3' + title: |- + Matrix eQTL: Ultra Fast eQTL Analysis via Large Matrix + Operations + maintainer: Andrey A Shabalin + description: |- + Matrix eQTL is designed for fast eQTL analysis on large datasets. + Matrix eQTL can test for association between genotype + and gene expression using linear regression + with either additive or ANOVA genotype effects. + The models can include covariates to account for factors + as population stratification, gender, and clinical variables. + It also supports models with heteroscedastic and/or correlated errors, + false discovery rate estimation and + separate treatment of local (cis) and distant (trans) eQTLs. + For more details see Shabalin (2012) . + date_publication: '2019-12-22' + bug_reports: https://github.com/andreyshabalin/MatrixEQTL/issues + url: http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/ + url_cran: https://CRAN.R-project.org/package=MatrixEQTL + url_git: '' +MatrixExtra: + version: 0.1.15 + title: Extra Methods for Sparse Matrices + maintainer: David Cortes + description: |- + Extends sparse matrix and vector classes from the 'Matrix' package by providing: + (a) Methods and operators that work natively on CSR formats (compressed sparse row, + a.k.a. 'RsparseMatrix') such as slicing/sub-setting, assignment, rbind(), + mathematical operators for CSR and COO such as addition ("+") or sqrt(), and methods such as diag(); + (b) Multi-threaded matrix multiplication and cross-product for many types, + including the 'float32' type from 'float'; + (c) Coercion methods between pairs of classes which are not present in 'Matrix', + such as 'dgCMatrix' -> 'ngRMatrix', as well as convenience conversion functions; + (d) Utility functions for sparse matrices such as sorting the indices or removing + zero-valued entries; + (e) Fast transposes that work by outputting in the opposite storage format; + (f) Faster replacements for many 'Matrix' methods for all sparse types, such as + slicing and elementwise multiplication. + (g) Convenience functions for sparse objects, such as 'mapSparse' or a shorter 'show' method. + date_publication: '2024-01-22' + bug_reports: https://github.com/david-cortes/MatrixExtra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MatrixExtra + url_git: https://github.com/david-cortes/MatrixExtra +MatrixHMM: + version: 1.0.0 + title: |- + Parsimonious Families of Hidden Markov Models for Matrix-Variate + Longitudinal Data + maintainer: Salvatore D. Tomarchio + description: Implements three families of parsimonious hidden Markov models (HMMs) + for matrix-variate longitudinal data using the Expectation-Conditional Maximization + (ECM) algorithm. The package supports matrix-variate normal, t, and contaminated + normal distributions as emission distributions. For each hidden state, parsimony + is achieved through the eigen-decomposition of the covariance matrices associated + with the emission distribution. This approach results in a comprehensive set of + 98 parsimonious HMMs for each type of emission distribution. Atypical matrix detection + is also supported, utilizing the fitted (heavy-tailed) models. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MatrixHMM + url_git: '' +matrixLaplacian: + version: '1.0' + title: Normalized Laplacian Matrix and Laplacian Map + maintainer: Tianhao Wu + description: Constructs the normalized Laplacian matrix of a square matrix, returns + the eigenvectors (singular vectors) and visualization of normalized Laplacian + map. + date_publication: '2016-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matrixLaplacian + url_git: '' +MatrixLDA: + version: '0.2' + title: Penalized Matrix-Normal Linear Discriminant Analysis + maintainer: Aaron J. Molstad + description: Fits the penalized matrix-normal model to be used for linear discriminant + analysis with matrix-valued predictors. For a description of the method, see Molstad + and Rothman (2018) . + date_publication: '2018-08-06' + bug_reports: '' + url: ajmolstad@github.io + url_cran: https://CRAN.R-project.org/package=MatrixLDA + url_git: '' +MatrixMixtures: + version: 1.0.0 + title: Model-Based Clustering via Matrix-Variate Mixture Models + maintainer: Michael P.B. Gallaugher + description: Implements finite mixtures of matrix-variate contaminated normal distributions + via expectation conditional-maximization algorithm for model-based clustering, + as described in Tomarchio et al.(2020) . One key advantage of + this model is the ability to automatically detect potential outlying matrices + by computing their a posteriori probability of being typical or atypical points. + Finite mixtures of matrix-variate t and matrix-variate normal distributions are + also implemented by using expectation-maximization algorithms. + date_publication: '2021-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MatrixMixtures + url_git: '' +MatrixModels: + version: 0.5-3 + title: Modelling with Sparse and Dense Matrices + maintainer: Martin Maechler + description: |- + Modelling with sparse and dense 'Matrix' matrices, using + modular prediction and response module classes. + date_publication: '2023-11-06' + bug_reports: https://R-forge.R-project.org/tracker/?func=add&atid=294&group_id=61 + url: '' + url_cran: https://CRAN.R-project.org/package=MatrixModels + url_git: https://Matrix.R-forge.R-project.org/ +matrixmodp: + version: 0.2.0 + title: Working with Matrices over Finite Prime Fields + maintainer: Ryan Higginbottom + description: |- + Provides functions for row-reducing and inverting matrices with + entries in many of the finite fields (those with a prime number of + elements). With this package, users will be able to find the reduced row + echelon form (RREF) of a matrix and calculate the inverse of a (square, + invertible) matrix. + date_publication: '2024-07-02' + bug_reports: https://github.com/rhigginbottom/matrixmodp/issues + url: https://rhigginbottom.github.io/matrixmodp/ + url_cran: https://CRAN.R-project.org/package=matrixmodp + url_git: https://github.com/rhigginbottom/matrixmodp +matrixNormal: + version: 0.1.1 + title: The Matrix Normal Distribution + maintainer: Paul M. Hargarten + description: Computes densities, probabilities, and random deviates of the Matrix + Normal (Pocuca et al. (2019) ). Also includes simple + but useful matrix functions. See the vignette for more information. + date_publication: '2022-09-16' + bug_reports: https://github.com/phargarten2/matrixNormal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixNormal + url_git: '' +matrixProfile: + version: 0.5.0 + title: Matrix Profile + maintainer: Donghwan Kim + description: A simple and the early stage package for matrix profile based on the + paper of Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei + Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, and Eamonn Keogh (2016) + . This package calculates all-pairs-similarity for + a given window size for time series data. + date_publication: '2018-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matrixProfile + url_git: https://github.com/ainsuotain/matrixprofile +matrixprofiler: + version: 0.1.9 + title: Matrix Profile for R + maintainer: Francisco Bischoff + description: |- + This is the core functions needed by the 'tsmp' package. The + low level and carefully checked mathematical functions are here. + These are implementations of the Matrix Profile concept that was + created by CS-UCR . + date_publication: '2023-01-26' + bug_reports: https://github.com/matrix-profile-foundation/matrixprofiler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixprofiler + url_git: https://github.com/matrix-profile-foundation/matrixprofiler +matrixsampling: + version: 2.0.0 + title: Simulations of Matrix Variate Distributions + maintainer: Stéphane Laurent + description: 'Provides samplers for various matrix variate distributions: Wishart, + inverse-Wishart, normal, t, inverted-t, Beta type I, Beta type II, Gamma, confluent + hypergeometric. Allows to simulate the noncentral Wishart distribution without + the integer restriction on the degrees of freedom.' + date_publication: '2019-08-24' + bug_reports: https://github.com/stla/matrixsampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixsampling + url_git: https://github.com/stla/matrixsampling +matrixset: + version: 0.4.0 + title: Creating, Manipulating and Annotating Matrix Ensemble + maintainer: Pascal Croteau + description: |- + Creates an object that stores a matrix ensemble, matrices + that share the same common properties, where rows and columns can be + annotated. Matrices must have the same dimension and dimnames. Operators to + manipulate these objects are provided as well as mechanisms to apply + functions to these objects. + date_publication: '2025-01-08' + bug_reports: https://github.com/pascalcroteau/matrixset/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixset + url_git: https://github.com/pascalcroteau/matrixset +matrixStats: + version: 1.5.0 + title: |- + Functions that Apply to Rows and Columns of Matrices (and to + Vectors) + maintainer: Henrik Bengtsson + description: High-performing functions operating on rows and columns of matrices, + e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized + per data type and for subsetted calculations such that both memory usage and processing + time is minimized. There are also optimized vector-based methods, e.g. binMeans(), + madDiff() and weightedMedian(). + date_publication: '2025-01-07' + bug_reports: https://github.com/HenrikBengtsson/matrixStats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixStats + url_git: https://github.com/HenrikBengtsson/matrixStats +matrixStrucTest: + version: 1.0.0 + title: Tests of Matrix Structure for Construct Validation + maintainer: Brian D. Segal + description: Tests for block-diagonal structure in symmetric matrices (e.g. correlation + matrices) under the null hypothesis of exchangeable off-diagonal elements. As + described in Segal et al. (2019), these tests can be useful for construct validation + either by themselves or as a complement to confirmatory factor analysis. Monte + Carlo methods are used to approximate the permutation p-value with Hubert's Gamma + (Hubert, 1976) and a t-statistic. This package also implements the chi-squared + statistic described by Steiger (1980). Please see Segal, et al. (2019) + for more information. + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=matrixStrucTest + url_git: https://github.com/bdsegal/matrixStrucTest +matrixTests: + version: 0.2.3 + title: |- + Fast Statistical Hypothesis Tests on Rows and Columns of + Matrices + maintainer: Karolis Koncevičius + description: |- + Functions to perform fast statistical hypothesis tests on rows/columns of matrices. + The main goals are: 1) speed via vectorization, 2) output that is detailed and easy to use, + 3) compatibility with tests implemented in R (like those available in the 'stats' package). + date_publication: '2023-10-05' + bug_reports: https://github.com/karoliskoncevicius/matrixTests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matrixTests + url_git: https://github.com/karoliskoncevicius/matrixTests +matriz: + version: 1.0.1 + title: |- + Literature Matrix Synthesis Tools for Epidemiology and Health + Science Research + maintainer: JP Monteagudo + description: An easy-to-use workflow that provides tools to create, update and fill + literature matrices commonly used in research, specifically epidemiology and health + sciences research. The project is born out of need as an easy–to–use tool for + my research methods classes. + date_publication: '2025-02-05' + bug_reports: https://github.com/jpmonteagudo28/matriz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matriz + url_git: https://github.com/jpmonteagudo28/matriz +matsbyname: + version: 0.6.11 + title: |- + An Implementation of Matrix Mathematics that Respects Row and + Column Names + maintainer: Matthew Heun + description: An implementation of matrix mathematics wherein operations are performed + "by name." + date_publication: '2025-01-17' + bug_reports: https://github.com/MatthewHeun/matsbyname/issues + url: https://matthewheun.github.io/matsbyname/ + url_cran: https://CRAN.R-project.org/package=matsbyname + url_git: https://github.com/MatthewHeun/matsbyname +matsindf: + version: 0.4.8 + title: Matrices in Data Frames + maintainer: Matthew Heun + description: |- + Provides functions to collapse a tidy data frame into matrices in a data frame + and expand a data frame of matrices into a tidy data frame. + date_publication: '2024-02-01' + bug_reports: https://github.com/MatthewHeun/matsindf/issues + url: https://matthewheun.github.io/matsindf/ + url_cran: https://CRAN.R-project.org/package=matsindf + url_git: https://github.com/MatthewHeun/matsindf +MatSkew: + version: 0.1.5 + title: Matrix Skew-T Parameter Estimation + maintainer: Michael P.B. Gallaugher + description: 'Performs matrix skew-t parameter estimation, Gallaugher and McNicholas + (2017) .' + date_publication: '2019-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MatSkew + url_git: '' +MatTransMix: + version: 0.1.18 + title: |- + Clustering with Matrix Gaussian and Matrix Transformation + Mixture Models + maintainer: Xuwen Zhu + description: 'Provides matrix Gaussian mixture models, matrix transformation mixture + models and their model-based clustering results. The parsimonious models of the + mean matrices and variance covariance matrices are implemented with a total of + 196 variations. For more information, please check: Xuwen Zhu, Shuchismita Sarkar, + and Volodymyr Melnykov (2021), "MatTransMix: an R package for matrix model-based + clustering and parsimonious mixture modeling", .' + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MatTransMix + url_git: '' +matuR: + version: 0.0.1.0 + title: Athlete Maturation and Biobanding + maintainer: Jose Fernandez + description: Identifying maturation stages across young athletes is paramount for + talent identification. Furthermore, the concept of biobanding, or grouping of + athletes based on their biological development, instead of their chronological + age, has been widely researched. The goal of this package is to help professionals + working in the field of strength & conditioning and talent ID obtain common maturation + metrics and as well as to quickly visualize this information via several plotting + options. For the methods behind the computed maturation metrics implemented in + this package refer to Khamis, H. J., & Roche, A. F. (1994) , + Mirwald, R.L et al., (2002) and Cumming, + Sean P. et al., (2017) . + date_publication: '2020-11-19' + bug_reports: https://github.com/josedv82/matuR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=matuR + url_git: https://github.com/josedv82/matuR +mau: + version: 0.1.2 + title: Decision Models with Multi Attribute Utility Theory + maintainer: Pedro Guarderas + description: |- + Provides functions for the creation, evaluation and test of decision models based in + Multi Attribute Utility Theory (MAUT). Can process and evaluate local risk aversion utilities + for a set of indexes, compute utilities and weights for the whole decision tree defining the + decision model and simulate weights employing Dirichlet distributions under addition constraints + in weights. + date_publication: '2018-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mau + url_git: https://github.com/pedroguarderas/mau +mauricer: + version: 2.5.4 + title: Work with 'BEAST2' Packages + maintainer: Richèl J.C. Bilderbeek + description: |- + 'BEAST2' () is a widely used + Bayesian phylogenetic tool, that uses DNA/RNA/protein data + and many model priors to create a posterior of jointly estimated + phylogenies and parameters. + 'BEAST2' is commonly accompanied by 'BEAUti 2' (), + which, among others, allows one to install 'BEAST2' package. + This package allows to work with 'BEAST2' packages from 'R'. + date_publication: '2024-06-11' + bug_reports: https://github.com/ropensci/mauricer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mauricer + url_git: https://docs.ropensci.org/mauricer/(website)https://github.com/ropensci/mauricer +MAVE: + version: 1.3.11 + title: Methods for Dimension Reduction + maintainer: Hang Weiqiang + description: Functions for dimension reduction, using MAVE (Minimum Average Variance + Estimation), OPG (Outer Product of Gradient) and KSIR (sliced inverse regression + of kernel version). Methods for selecting the best dimension are also included. + Xia (2002) ; Xia (2007) ; + Wang (2008) . + date_publication: '2021-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MAVE + url_git: '' +maxaltall: + version: 0.1.0 + title: '''FASTA'' ML and ‘altall’ Sequences from IQ-TREE .state Files' + maintainer: Philip D. Kiser + description: Takes a .state file generated by IQ-TREE as an input and, for each + ancestral node present in the file, generates a FASTA-formatted maximum likelihood + (ML) sequence as well as an ‘AltAll’ sequence in which uncertain sites, determined + by the two parameters thres_1 and thres_2, have the maximum likelihood state swapped + with the next most likely state as described in Geeta N. Eick, Jamie T. Bridgham, + Douglas P. Anderson, Michael J. Harms, and Joseph W. Thornton (2017), "Robustness + of Reconstructed Ancestral Protein Functions to Statistical Uncertainty" . + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxaltall + url_git: '' +maxcombo: + version: '1.0' + title: |- + The Group Sequential Max-Combo Test for Comparing Survival + Curves + maintainer: Tom Prior + description: Functions for comparing survival curves using the max-combo test at + a single timepoint or repeatedly at successive respective timepoints while controlling + type I error (i.e., the group sequential setting), as published by Prior (2020) + . The max-combo test is a generalization of the + weighted log-rank test, which itself is a generalization of the log-rank test, + which is a commonly used statistical test for comparing survival curves, e.g., + during or after a clinical trial as part of an effort to determine if a new drug + or therapy is more effective at delaying undesirable outcomes than an established + drug or therapy or a placebo. + date_publication: '2020-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxcombo + url_git: '' +maxent.ot: + version: 1.0.0 + title: |- + Perform Phonological Analyses using Maximum Entropy Optimality + Theory + maintainer: Connor Mayer + description: |- + Fit Maximum Entropy Optimality Theory models to data sets, + generate the predictions made by such models for novel data, and compare the + fit of different models using a variety of metrics. The package is described + in Mayer, C., Tan, A., Zuraw, K. (in press) . + date_publication: '2024-09-23' + bug_reports: https://github.com/connormayer/maxent.ot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=maxent.ot + url_git: https://github.com/connormayer/maxent.ot +MaxentVariableSelection: + version: 1.0-3 + title: |- + Selecting the Best Set of Relevant Environmental Variables along + with the Optimal Regularization Multiplier for Maxent Niche + Modeling + maintainer: '"Alexander Jueterbock"' + description: |- + Complex niche models show low performance in identifying + the most important range-limiting environmental variables and in + transferring habitat suitability to novel environmental conditions + (Warren and Seifert, 2011 ; Warren et al., + 2014 ). This package helps to identify the + most important set of uncorrelated variables and to fine-tune Maxent's + regularization multiplier. In combination, this allows to constrain + complexity and increase performance of Maxent niche models (assessed + by information criteria, such as AICc (Akaike, 1974 + ), and by the area under the receiver + operating characteristic (AUC) (Fielding and Bell, 1997 + ). Users of this package should be + familiar with Maxent niche modelling. + date_publication: '2018-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MaxentVariableSelection + url_git: '' +maximin: + version: 1.0-6 + title: Space-Filling Design under Maximin Distance + maintainer: Furong Sun + description: Constructs a space-filling design under the criterion of maximum-minimum + distance. Both discrete and continuous searches are provided. + date_publication: '2024-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maximin + url_git: '' +MaximinInfer: + version: 2.0.0 + title: Inference for Maximin Effects in High-Dimensional Settings + maintainer: Zhenyu Wang + description: Implementation of the sampling and aggregation method for the covariate + shift maximin effect, which was proposed in . It constructs + the confidence interval for any linear combination of the high-dimensional maximin + effect. + date_publication: '2023-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MaximinInfer + url_git: '' +maxLik: + version: 1.5-2.1 + title: Maximum Likelihood Estimation and Related Tools + maintainer: Ott Toomet + description: |- + Functions for Maximum Likelihood (ML) estimation, non-linear + optimization, and related tools. It includes a unified way to call + different optimizers, and classes and methods to handle the results from + the Maximum Likelihood viewpoint. It also includes a number of convenience + tools for testing and developing your own models. + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxLik + url_git: '' +maxlike: + version: 0.1-11 + title: |- + Model Species Distributions by Estimating the Probability of + Occurrence Using Presence-Only Data + maintainer: Roeland Kindt + description: Provides a likelihood-based approach to modeling species distributions + using presence-only data. In contrast to the popular software program MAXENT, + this approach yields estimates of the probability of occurrence, which is a natural + descriptor of a species' distribution. + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxlike + url_git: '' +maxmatching: + version: 0.1.0 + title: Maximum Matching for General Weighted Graph + maintainer: Bowen Deng + description: |- + Computes the maximum matching for unweighted graph and maximum + matching for (un)weighted bipartite graph efficiently. + date_publication: '2017-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxmatching + url_git: '' +MaxMC: + version: 0.1.2 + title: Maximized Monte Carlo + maintainer: Gabriel Rodriguez-Rondon + description: An implementation of the Monte Carlo techniques described in details + by Dufour (2006) and Dufour and Khalaf (2007) + . The two main features available are the Monte + Carlo method with tie-breaker, mc(), for discrete statistics, and the Maximized + Monte Carlo, mmc(), for statistics with nuisance parameters. + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MaxMC + url_git: https://github.com/julienneves/MaxMC +maxnet: + version: 0.1.4 + title: Fitting 'Maxent' Species Distribution Models with 'glmnet' + maintainer: Steven Phillips + description: Procedures to fit species distributions models from occurrence records + and environmental variables, using 'glmnet' for model fitting. Model structure + is the same as for the 'Maxent' Java package, version 3.4.0, with the same feature + types and regularization options. See the 'Maxent' website + for more details. + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxnet + url_git: https://github.com/mrmaxent/maxnet +MaxPro: + version: 4.1-2 + title: Maximum Projection Designs + maintainer: Shan Ba + description: 'Generate maximum projection (MaxPro) designs for quantitative and/or + qualitative factors. Details of the MaxPro criterion can be found in: (1) Joseph, + Gul, and Ba. (2015) "Maximum Projection Designs for Computer Experiments", Biometrika, + 102, 371-380, and (2) Joseph, Gul, and Ba. (2018) "Designing Computer Experiments + with Multiple Types of Factors: The MaxPro Approach", Journal of Quality Technology, + to appear.' + date_publication: '2018-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MaxPro + url_git: '' +MaxSkew: + version: '1.1' + title: Orthogonal Data Projections with Maximal Skewness + maintainer: Cinzia Franceschini + description: It finds Orthogonal Data Projections with Maximal Skewness. The first + data projection in the output is the most skewed among all linear data projections. + The second data projection in the output is the most skewed among all data projections + orthogonal to the first one, and so on. + date_publication: '2017-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MaxSkew + url_git: '' +maxstablePCA: + version: 0.1.1 + title: |- + Apply a PCA Like Procedure Suited for Multivariate Extreme Value + Distributions + maintainer: Felix Reinbott + description: Dimension reduction for multivariate data of extreme events with a + PCA like procedure as described in Reinbott, Janßen, (2024), . + Tools for necessary transformations of the data are provided. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxstablePCA + url_git: '' +maxstat: + version: 0.7-25 + title: Maximally Selected Rank Statistics + maintainer: Torsten Hothorn + description: |- + Maximally selected rank statistics with + several p-value approximations. + date_publication: '2017-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=maxstat + url_git: '' +MaxWiK: + version: 1.0.5 + title: Machine Learning Method Based on Isolation Kernel Mean Embedding + maintainer: Yuri Nagornov + description: Incorporates Approximate Bayesian Computation to get a posterior distribution + and to select a model optimal parameter for an observation point. Additionally, + the meta-sampling heuristic algorithm is realized for parameter estimation, which + requires no model runs and is dimension-independent. A sampling scheme is also + presented that allows model runs and uses the meta-sampling for point generation. + A predictor is realized as the meta-sampling for the model output. All the algorithms + leverage a machine learning method utilizing the maxima weighted Isolation Kernel + approach, or 'MaxWiK'. The method involves transforming raw data to a Hilbert + space (mapping) and measuring the similarity between simulated points and the + maxima weighted Isolation Kernel mapping corresponding to the observation point. + Comprehensive details of the methodology can be found in the papers Iurii Nagornov + (2024) and Iurii Nagornov (2023) . + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MaxWiK + url_git: '' +maybe: + version: 1.1.0 + title: The Maybe Monad + maintainer: Andrew McNeil + description: |2- + + The maybe type represents the possibility of some value or nothing. + It is often used instead of throwing an error or returning `NULL`. + The advantage of using a maybe type over `NULL` is that it is both composable + and requires the developer to explicitly acknowledge the potential absence + of a value, helping to avoid the existence of unexpected behaviour. + date_publication: '2023-08-07' + bug_reports: https://github.com/armcn/maybe/issues + url: https://armcn.github.io/maybe/ + url_cran: https://CRAN.R-project.org/package=maybe + url_git: https://github.com/armcn/maybe +MazamaCoreUtils: + version: 0.5.3 + title: Utility Functions for Production R Code + maintainer: Jonathan Callahan + description: |- + A suite of utility functions providing functionality commonly + needed for production level projects such as logging, error handling, + cache management and date-time parsing. Functions for date-time parsing and + formatting require that time zones be specified explicitly, avoiding a common + source of error when working with environmental time series. + date_publication: '2024-12-03' + bug_reports: https://github.com/MazamaScience/MazamaCoreUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MazamaCoreUtils + url_git: https://github.com/MazamaScience/MazamaCoreUtils +MazamaLocationUtils: + version: 0.4.4 + title: Manage Spatial Metadata for Known Locations + maintainer: Jonathan Callahan + description: |- + Utility functions for discovering and managing metadata + associated with spatially unique "known locations". Applications include + all fields of environmental monitoring (e.g. air and water quality) where + data are collected at stationary sites. + date_publication: '2024-08-19' + bug_reports: https://github.com/MazamaScience/MazamaLocationUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MazamaLocationUtils + url_git: https://github.com/MazamaScience/MazamaLocationUtils +MazamaRollUtils: + version: 0.1.3 + title: Efficient Rolling Functions + maintainer: Jonathan Callahan + description: |- + A suite of compiled functions calculating rolling mins, means, + maxes and other statistics. This package is designed to meet the needs of + data processing systems for environmental time series. + date_publication: '2021-09-23' + bug_reports: https://github.com/MazamaScience/MazamaRollUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MazamaRollUtils + url_git: https://github.com/MazamaScience/MazamaRollUtils +MazamaSpatialPlots: + version: 0.3.0 + title: Thematic Plots for Mazama Spatial Datasets + maintainer: Jonathan Callahan + description: |- + A suite of convenience functions for generating US state and county + thematic maps using datasets from the MazamaSpatialUtils package. + date_publication: '2025-02-02' + bug_reports: https://github.com/MazamaScience/MazamaSpatialPlots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MazamaSpatialPlots + url_git: https://github.com/MazamaScience/MazamaSpatialPlots +MazamaSpatialUtils: + version: 0.8.7 + title: Spatial Data Download and Utility Functions + maintainer: Jonathan Callahan + description: |- + A suite of conversion functions to create internally standardized + spatial polygons data frames. Utility functions use these data sets to + return values such as country, state, time zone, watershed, etc. associated + with a set of longitude/latitude pairs. (They also make cool maps.) + date_publication: '2024-11-03' + bug_reports: https://github.com/MazamaScience/MazamaSpatialUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MazamaSpatialUtils + url_git: https://github.com/MazamaScience/MazamaSpatialUtils +MazamaTimeSeries: + version: 0.3.0 + title: Core Functionality for Environmental Time Series + maintainer: Jonathan Callahan + description: |- + Utility functions for working with environmental time series data from known + locations. The compact data model is structured as a list with two dataframes. A + 'meta' dataframe contains spatial and measuring device metadata associated with + deployments at known locations. A 'data' dataframe contains a 'datetime' column + followed by columns of measurements associated with each "device-deployment". + Ephemerides calculations are based on code originally found in NOAA's + "Solar Calculator" . + date_publication: '2024-03-08' + bug_reports: https://github.com/MazamaScience/MazamaTimeSeries/issues + url: https://mazamascience.github.io/MazamaTimeSeries/ + url_cran: https://CRAN.R-project.org/package=MazamaTimeSeries + url_git: https://github.com/MazamaScience/MazamaTimeSeries +MAZE: + version: 0.0.2 + title: Mediation Analysis for Zero-Inflated Mediators + maintainer: Meilin Jiang + description: A novel mediation analysis approach to address zero-inflated mediators + containing true zeros and false zeros. See Jiang et al (2023) "A Novel Causal + Mediation Analysis Approach for Zero-Inflated Mediators" for + more details. + date_publication: '2023-02-16' + bug_reports: https://github.com/meilinjiang/MAZE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MAZE + url_git: https://github.com/meilinjiang/MAZE +mazealls: + version: 0.2.0 + title: Generate Recursive Mazes + maintainer: Steven E. Pav + description: |- + Supports the generation of parallelogram, equilateral + triangle, regular hexagon, isosceles trapezoid, Koch snowflake, + 'hexaflake', Sierpinski triangle, Sierpinski carpet and Sierpinski + trapezoid mazes via 'TurtleGraphics'. Mazes are generated by the recursive method: + the domain is divided into sub-domains in which mazes are generated, + then dividing lines with holes are drawn between them, see + J. Buck, Recursive Division, . + date_publication: '2017-12-12' + bug_reports: https://github.com/shabbychef/mazealls/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mazealls + url_git: https://github.com/shabbychef/mazealls +mazeGen: + version: 0.1.3 + title: Elithorn Maze Generator + maintainer: Bao Sheng Loe (Aiden) + description: A maze generator that creates the Elithorn Maze (HTML file) and the + functions to calculate the associated maze parameters (i.e. Difficulty and Ability). + date_publication: '2017-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mazeGen + url_git: '' +mazeinda: + version: 0.0.2 + title: Monotonic Association on Zero-Inflated Data + maintainer: Alice Albasi + description: |- + Methods for calculating and testing the significance of + pairwise monotonic association from and based on the work of + Pimentel (2009) . Computation of association of vectors from one + or multiple sets can be performed in parallel thanks to the + packages 'foreach' and 'doMC'. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mazeinda + url_git: '' +mazing: + version: 1.0.5 + title: Utilities for Making and Plotting Mazes + maintainer: Kelly Street + description: Functionality for generating and plotting random mazes. The mazes are + based on matrices, so can only consist of vertical and horizontal lines along + a regular grid. But there is no need to use every possible space, so they can + take on many different shapes. + date_publication: '2021-10-05' + bug_reports: https://github.com/kstreet13/mazing/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mazing + url_git: '' +MB: + version: 0.1.1 + title: The Use of Marginal Distributions in Conditional Forecasting + maintainer: Bushra Alsaeed + description: A new way to predict time series using the marginal distribution table + in the absence of the significance of traditional models. + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MB + url_git: '' +MBA: + version: 0.1-2 + title: Multilevel B-Spline Approximation + maintainer: Andrew Finley + description: Functions to interpolate irregularly and regularly spaced data using + Multilevel B-spline Approximation (MBA). Functions call portions of the SINTEF + Multilevel B-spline Library written by Øyvind Hjelle which implements methods + developed by Lee, Wolberg and Shin (1997; ). + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBA + url_git: '' +MBAnalysis: + version: 2.0.2 + title: Multiblock Exploratory and Predictive Data Analysis + maintainer: Benjamin Mahieu + description: Exploratory and predictive methods for the analysis of several blocks + of variables measured on the same individuals. + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBAnalysis + url_git: '' +mbbe: + version: 0.1.0 + title: Model Based Bio-Equivalence + maintainer: Mark Sale + description: |- + Uses several Nonlinear Mixed effect (NONMEM) models (as NONMEM control files) + to perform bootstrap model averaging and Monte Carlo Simulation for Model Based + Bio-Equivalence (MBBE). Power is returned as the fraction of the simulations with + successful bioequivalence (BE) test, for maximum concentration (Cmax), Area under the + curve to the last observed value (AUClast) and Area under the curve extrapolate to + infinity (AUCinf). See Hooker, A. (2020) Improved bioequivalence assessment through + model-informed and model-based strategies . + date_publication: '2024-02-03' + bug_reports: https://github.com/certara/mbbe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbbe + url_git: https://github.com/certara/mbbe +mbbefd: + version: 0.8.13 + title: |- + Maxwell Boltzmann Bose Einstein Fermi Dirac Distribution and + Destruction Rate Modelling + maintainer: Christophe Dutang + description: |- + Distributions that are typically used for exposure rating in + general insurance, in particular to price reinsurance contracts. + The vignette shows code snippets to fit the distribution to + empirical data. See, e.g., Bernegger (1997) + freely available on-line. + date_publication: '2024-12-18' + bug_reports: https://github.com/spedygiorgio/mbbefd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbbefd + url_git: https://github.com/spedygiorgio/mbbefd +MBBEFDLite: + version: 0.0.5 + title: |- + Statistical Functions for the + Maxwell-Boltzmann-Bose-Einstein-Fermi-Dirac (MBBEFD) Family of + Distributions + maintainer: Avraham Adler + description: |- + Provides probability mass, distribution, quantile, random variate + generation, and method-of-moments parameter fitting for the MBBEFD family of + distributions used in insurance modeling as described in Bernegger (1997) + without any external dependencies. + date_publication: '2025-01-31' + bug_reports: https://github.com/aadler/MBBEFDLite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MBBEFDLite + url_git: https://github.com/aadler/MBBEFDLite +MBC: + version: 0.10-7 + title: Multivariate Bias Correction of Climate Model Outputs + maintainer: Alex J. Cannon + description: |- + Calibrate and apply multivariate bias correction algorithms + for climate model simulations of multiple climate variables. Three methods + described by Cannon (2016) and + Cannon (2018) are implemented — + (i) MBC Pearson correlation (MBCp), (ii) MBC rank correlation (MBCr), + and (iii) MBC N-dimensional PDF transform (MBCn) — as is the Rank + Resampling for Distributions and Dependences (R2D2) method. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBC + url_git: '' +MBCbook: + version: 0.1.2 + title: |- + Companion Package for the Book "Model-Based Clustering and + Classification for Data Science" + maintainer: Charles Bouveyron + description: The companion package provides all original data sets and functions + that are used in the book "Model-Based Clustering and Classification for Data + Science" by Charles Bouveyron, Gilles Celeux, T. Brendan Murphy and Adrian E. + Raftery (2019, ISBN:9781108644181). + date_publication: '2024-05-08' + bug_reports: https://github.com/cbouveyron/MBCbook/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MBCbook + url_git: https://github.com/cbouveyron/MBCbook +mbend: + version: 1.3.1 + title: Matrix Bending + maintainer: Mohammad Ali Nilforooshan + description: |- + Bending non-positive-definite (symmetric) matrices to positive-definite, using weighted and unweighted methods. + Jorjani, H., et al. (2003) . + Schaeffer, L. R. (2014) . + date_publication: '2020-10-11' + bug_reports: https://github.com/nilforooshan/mbend/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbend + url_git: https://github.com/nilforooshan/mbend +MBESS: + version: 4.9.3 + title: The MBESS R Package + maintainer: Ken Kelley + description: |- + Implements methods that are useful in designing research studies and analyzing data, with + particular emphasis on methods that are developed for or used within the behavioral, + educational, and social sciences (broadly defined). That being said, many of the methods + implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a + suite of functions for a variety of related topics, such as effect sizes, confidence intervals + for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size + planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and + minimum-risk point estimation perspectives), mediation analysis, various properties of + distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally + an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became + more general and now contains methods applicable and used in a wide variety of fields and is an + orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has + greatly benefited from others, see for a detailed + list of those that have contributed and other details. + date_publication: '2023-10-26' + bug_reports: '' + url: https://www3.nd.edu/~kkelley/site/MBESS.html + url_cran: https://CRAN.R-project.org/package=MBESS + url_git: '' +mbest: + version: '0.6' + title: Moment-Based Estimation for Hierarchical Models + maintainer: Patrick O. Perry + description: |- + Fast moment-based hierarchical model fitting. Implements + methods from the papers + "Fast Moment-Based Estimation for Hierarchical Models," by Perry (2017) + and + "Fitting a Deeply Nested Hierarchical Model to a Large Book Review + Dataset Using a Moment-Based Estimator," by Zhang, Schmaus, and Perry + (2018). + date_publication: '2018-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mbest + url_git: https://github.com/patperry/r-mbest +MBHdesign: + version: 2.3.15 + title: Spatial Designs for Ecological and Environmental Surveys + maintainer: Scott Foster + description: 'Provides spatially survey balanced designs using the quasi-random + number method described Robinson et al. (2013) and adjusted + in Robinson et al. (2017) . Designs using MBHdesign + can: 1) accommodate, without substantial detrimental effects on spatial balance, + legacy sites (Foster et al., 2017 ); 2) be based + on points or transects (foster et al. 2020 and produce + clustered samples (Foster et al. (in press). Additional information about the + package use itself is given in Foster (2021) .' + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBHdesign + url_git: '' +mbir: + version: 1.3.5 + title: Magnitude-Based Inferences + maintainer: Kyle Peterson + description: Allows practitioners and researchers a wholesale approach for deriving + magnitude-based inferences from raw data. A major goal of 'mbir' is to programmatically + detect appropriate statistical tests to run in lieu of relying on practitioners + to determine correct stepwise procedures independently. + date_publication: '2019-01-22' + bug_reports: '' + url: http://mbir-project.us/ + url_cran: https://CRAN.R-project.org/package=mbir + url_git: '' +mblm: + version: 0.12.1 + title: Median-Based Linear Models + maintainer: Lukasz Komsta + description: |- + Provides linear models based on Theil-Sen + single median and Siegel repeated medians. They are very robust + (29 or 50 percent breakdown point, respectively), and if no + outliers are present, the estimators are very similar to OLS. + date_publication: '2019-01-26' + bug_reports: '' + url: http://www.komsta.net/ + url_cran: https://CRAN.R-project.org/package=mblm + url_git: '' +MBmca: + version: 1.0.1-3 + title: Nucleic Acid Melting Curve Analysis + maintainer: Stefan Roediger + description: |- + Lightweight utilities for nucleic acid melting curve analysis are + important in life sciences and diagnostics. This software can be used for + the analysis and presentation of melting curve data from microbead-based + assays (surface melting curve analysis) and reactions in solution (e.g., + quantitative PCR (qPCR), real-time isothermal Amplification). Further + information are described in detail in two publications in The R Journal [ + ; + ]. + date_publication: '2021-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBmca + url_git: https://github.com/PCRuniversum/MBmca/ +MBMethPred: + version: 0.1.4.2 + title: Medulloblastoma Subgroups Prediction + maintainer: Edris Sharif Rahmani + description: 'Utilizing a combination of machine learning models (Random Forest, + Naive Bayes, K-Nearest Neighbor, Support Vector Machines, Extreme Gradient Boosting, + and Linear Discriminant Analysis) and a deep Artificial Neural Network model, + ''MBMethPred'' can predict medulloblastoma subgroups, including wingless (WNT), + sonic hedgehog (SHH), Group 3, and Group 4 from DNA methylation beta values. See + Sharif Rahmani E, Lawarde A, Lingasamy P, Moreno SV, Salumets A and Modhukur V + (2023), MBMethPred: a computational framework for the accurate classification + of childhood medulloblastoma subgroups using data integration and AI-based approaches. + Front. Genet. 14:1233657. for more details.' + date_publication: '2023-09-18' + bug_reports: https://github.com/sharifrahmanie/MBMethPred/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MBMethPred + url_git: https://github.com/sharifrahmanie/MBMethPred +mbmixture: + version: '0.6' + title: Microbiome Mixture Analysis + maintainer: Karl W Broman + description: |- + Evaluate whether a microbiome sample is a mixture of two + samples, by fitting a model for the number of read counts as a + function of single nucleotide polymorphism (SNP) allele and the + genotypes of two potential source samples. + Lobo et al. (2021) . + date_publication: '2024-11-27' + bug_reports: https://github.com/kbroman/mbmixture/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbmixture + url_git: https://github.com/kbroman/mbmixture +MBNMAdose: + version: 0.5.0 + title: Dose-Response MBNMA Models + maintainer: Hugo Pedder + description: |- + Fits Bayesian dose-response model-based network meta-analysis (MBNMA) + that incorporate multiple doses within an agent by modelling different dose-response functions, as + described by Mawdsley et al. (2016) . + By modelling dose-response relationships this can connect networks of evidence that might + otherwise be disconnected, and can improve precision on treatment estimates. Several common + dose-response functions are provided; others may be added by the user. Various characteristics + and assumptions can be flexibly added to the models, such as shared class effects. The consistency + of direct and indirect evidence in the network can be assessed using unrelated mean effects models + and/or by node-splitting at the treatment level. + date_publication: '2025-02-07' + bug_reports: '' + url: https://hugaped.github.io/MBNMAdose/ + url_cran: https://CRAN.R-project.org/package=MBNMAdose + url_git: '' +MBNMAtime: + version: 0.2.6 + title: Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models + maintainer: Hugo Pedder + description: |- + Fits Bayesian time-course models for model-based network meta-analysis (MBNMA) that allows inclusion of multiple + time-points from studies. Repeated measures over time are accounted for within studies by applying different time-course functions, + following the method of Pedder et al. (2019) . + The method allows synthesis of studies with multiple follow-up measurements that can account for time-course for a single or multiple + treatment comparisons. Several general time-course functions are provided; others may be added + by the user. Various characteristics can be flexibly added to the models, such as correlation between time points and shared + class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects + models and/or by node-splitting. + date_publication: '2025-01-29' + bug_reports: '' + url: https://hugaped.github.io/MBNMAtime/ + url_cran: https://CRAN.R-project.org/package=MBNMAtime + url_git: '' +mboost: + version: 2.9-11 + title: Model-Based Boosting + maintainer: Torsten Hothorn + description: |- + Functional gradient descent algorithm + (boosting) for optimizing general risk functions utilizing + component-wise (penalised) least squares estimates or regression + trees as base-learners for fitting generalized linear, additive + and interaction models to potentially high-dimensional data. + Models and algorithms are described in , + a hands-on tutorial is available from . + The package allows user-specified loss functions and base-learners. + date_publication: '2024-08-22' + bug_reports: https://github.com/boost-R/mboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mboost + url_git: https://github.com/boost-R/mboost +mbr: + version: 0.0.1 + title: Mass Balance Reconstruction + maintainer: Hung Nguyen + description: Mass-balance-adjusted Regression algorithm for streamflow reconstruction + at sub-annual resolution (e.g., seasonal or monthly). The algorithm implements + a penalty term to minimize the differences between the total sub-annual flows + and the annual flow. The method is described in Nguyen et al (2020) . + date_publication: '2021-02-16' + bug_reports: https://github.com/ntthung/mbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbr + url_git: https://github.com/ntthung/mbr +mbrdr: + version: 1.1.1 + title: Model-Based Response Dimension Reduction + maintainer: Jae Keun Yoo + description: Functions for model-based response dimension reduction. Usual dimension + reduction methods in multivariate regression focus on the reduction of predictors, + not responses. The response dimension reduction is theoretically founded in Yoo + and Cook (2008) . Later, three model-based response + dimension reduction approaches are proposed in Yoo (2016) + and Yoo (2019) . The method by Yoo and Cook (2008) + is based on non-parametric ordinary least squares, but the model-based approaches + are done through maximum likelihood estimation. For two model-based response dimension + reduction methods called principal fitted response reduction and unstructured + principal fitted response reduction, chi-squared tests are provided for determining + the dimension of the response subspace. + date_publication: '2022-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mbrdr + url_git: '' +mbreaks: + version: 1.0.1 + title: |- + Estimation and Inference for Structural Breaks in Linear + Regression Models + maintainer: Linh Nguyen + description: Functions provide comprehensive treatments for estimating, inferring, + testing and model selecting in linear regression models with structural breaks. + The tests, estimation methods, inference and information criteria implemented + are discussed in Bai and Perron (1998) "Estimating and Testing Linear Models with + Multiple Structural Changes" . + date_publication: '2024-11-11' + bug_reports: https://github.com/RoDivinity/mbreaks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbreaks + url_git: https://github.com/RoDivinity/mbreaks +mbRes: + version: 0.1.7 + title: Exploration of Multiple Biomarker Responses using Effect Size + maintainer: Duy Nghia Pham + description: |- + Summarize multiple biomarker responses of aquatic organisms to + contaminants using Cliff’s delta, as described in Pham & Sokolova (2023) + . + date_publication: '2023-03-29' + bug_reports: https://github.com/phamdn/mbRes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mbRes + url_git: '' +mbrglm: + version: 0.0.1 + title: Median Bias Reduction in Binomial-Response GLMs + maintainer: Euloge C. Kenne Pagui + description: Fit generalized linear models with binomial responses using a median + modified score approach (Kenne Pagui et al., 2016, ) + to median bias reduction. This method respects equivariance under reparameterizations + for each parameter component and also solves the infinite estimates problem (data + separation). + date_publication: '2017-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mbrglm + url_git: '' +MBSGS: + version: 1.1.0 + title: Multivariate Bayesian Sparse Group Selection with Spike and Slab + maintainer: Benoit Liquet + description: An implementation of a Bayesian sparse group model using spike and + slab priors in a regression context. It is designed for regression with a multivariate + response variable, but also provides an implementation for univariate response. + date_publication: '2017-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBSGS + url_git: '' +MBSP: + version: '4.0' + title: Multivariate Bayesian Model with Shrinkage Priors + maintainer: Ray Bai + description: Gibbs sampler for fitting multivariate Bayesian linear regression with + shrinkage priors (MBSP), using the three parameter beta normal family. The method + is described in Bai and Ghosh (2018) . + date_publication: '2023-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MBSP + url_git: '' +mbsts: + version: '3.0' + title: Multivariate Bayesian Structural Time Series + maintainer: Ning Ning + description: Tools for data analysis with multivariate Bayesian structural time + series (MBSTS) models. Specifically, the package provides facilities for implementing + general structural time series models, flexibly adding on different time series + components (trend, season, cycle, and regression), simulating them, fitting them + to multivariate correlated time series data, conducting feature selection on the + regression component. + date_publication: '2023-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mbsts + url_git: '' +mBvs: + version: '1.92' + title: Bayesian Variable Selection Methods for Multivariate Data + maintainer: Kyu Ha Lee + description: Bayesian variable selection methods for data with multivariate responses + and multiple covariates. The package contains implementations of multivariate + Bayesian variable selection methods for continuous data (Lee et al., Biometrics, + 2017 ) and zero-inflated count data (Lee et al., Biostatistics, + 2020 ). + date_publication: '2024-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mBvs + url_git: '' +mc.heterogeneity: + version: 0.1.2 + title: A Monte Carlo Based Heterogeneity Test for Meta-Analysis + maintainer: Ge Jiang + description: Implements a Monte Carlo Based Heterogeneity Test for standardized + mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed + odds ratio (OR) in Meta-Analysis Studies. Depending on the presence of moderators, + this Monte Carlo Based Test can be implemented in the random or mixed-effects + model. This package uses rma() function from the R package 'metafor' to obtain + parameter estimates and likelihood, so installation of R package 'metafor' is + required. This approach refers to the studies of Hedges (1981) , + Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & + Fowler (2004) , Viechtbauer (2010) , + and Zuckerman (1994, ISBN:978-0521432009). + date_publication: '2020-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mc.heterogeneity + url_git: '' +mc2d: + version: 0.2.1 + title: Tools for Two-Dimensional Monte-Carlo Simulations + maintainer: Regis Pouillot + description: A complete framework to build and study Two-Dimensional Monte-Carlo + simulations, aka Second-Order Monte-Carlo simulations. Also includes various distributions + (pert, triangular, Bernoulli, empirical discrete and continuous). + date_publication: '2024-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mc2d + url_git: '' +MCARtest: + version: 1.2.2 + title: Optimal Nonparametric Testing of Missing Completely at Random + maintainer: Thomas B. Berrett + description: Provides functions for carrying out nonparametric hypothesis tests + of the MCAR hypothesis based on the theory of Frechet classes and compatibility. + Also gives functions for computing halfspace representations of the marginal polytope + and related geometric objects. + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCARtest + url_git: '' +mcauchyd: + version: 1.3.3 + title: Multivariate Cauchy Distribution; Kullback-Leibler Divergence + maintainer: Pierre Santagostini + description: Distance between multivariate Cauchy distributions, as presented by + N. Bouhlel and D. Rousseau (2022) . Manipulation of multivariate + Cauchy distributions. + date_publication: '2024-12-23' + bug_reports: https://forgemia.inra.fr/imhorphen/mcauchyd/-/issues + url: https://forgemia.inra.fr/imhorphen/mcauchyd + url_cran: https://CRAN.R-project.org/package=mcauchyd + url_git: '' +MCAvariants: + version: 2.6.1 + title: Multiple Correspondence Analysis Variants + maintainer: Rosaria Lombardo + description: |- + Provides two variants of multiple correspondence analysis (ca): + multiple ca and ordered multiple ca via orthogonal polynomials of Emerson. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCAvariants + url_git: '' +mcb: + version: 0.1.15 + title: Model Confidence Bounds + maintainer: Heming Deng + description: When choosing proper variable selection methods, it is important to + consider the uncertainty of a certain method. The model confidence bound for variable + selection identifies two nested models (upper and lower confidence bound models) + containing the true model at a given confidence level. A good variable selection + method is the one of which the model confidence bound under a certain confidence + level has the shortest width. When visualizing the variability of model selection + and comparing different model selection procedures, model uncertainty curve is + a good graphical tool. A good variable selection method is the one of whose model + uncertainty curve will tend to arch towards the upper left corner. This function + aims to obtain the model confidence bound and draw the model uncertainty curve + of certain single model selection method under a coverage rate equal or little + higher than user-given confidential level. About what model confidence bound is + and how it work please see Li,Y., Luo,Y., Ferrari,D., Hu,X. and Qin,Y. (2019) + Model Confidence Bounds for Variable Selection. Biometrics, 75:392-403. . + Besides, 'flare' is needed only you apply the SQRT or LAD method ('mcb' totally + has 8 methods). Although 'flare' has been archived by CRAN, you can still get + it in and the latest version is useful + for 'mcb'. + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcb + url_git: '' +MCBackscattering: + version: 0.1.1 + title: Monte Carlo Simulation for Surface Backscattering + maintainer: Laszlo Baranyai + description: |- + Monte Carlo simulation is a stochastic method computing trajectories of photons in media. Surface backscattering is performing calculations in semi-infinite media and summarizing photon flux leaving the surface. This simulation is modeling the optical measurement of diffuse reflectance using an incident light beam. The semi-infinite media is considered to have flat surface. Media, typically biological tissue, is described by four optical parameters: absorption coefficient, scattering coefficient, anisotropy factor, refractive index. The media is assumed to be homogeneous. + Computational parameters of the simulation include: number of photons, radius of incident light beam, lowest photon energy threshold, intensity profile (halo) radius, spatial resolution of intensity profile. + You can find more information and validation in the Open Access paper. + Laszlo Baranyai (2020) . + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCBackscattering + url_git: '' +mcbette: + version: 1.15.3 + title: Model Comparison Using 'babette' + maintainer: Richèl J.C. Bilderbeek + description: |- + 'BEAST2' () is a widely used + Bayesian phylogenetic tool, that uses DNA/RNA/protein data + and many model priors to create a posterior of jointly estimated + phylogenies and parameters. + 'mcbette' allows to do a Bayesian model comparison over some + site and clock models, + using 'babette' (). + date_publication: '2024-08-19' + bug_reports: https://github.com/ropensci/mcbette/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcbette + url_git: https://github.com/ropensci/mcbette/ +mcbiopi: + version: 1.1.6 + title: Matrix Computation Based Identification of Prime Implicants + maintainer: Holger Schwender + description: |- + Computes the prime implicants or a minimal disjunctive normal form for a + logic expression presented by a truth table or a logic tree. Has been particularly + developed for logic expressions resulting from a logic regression analysis, i.e. + logic expressions typically consisting of up to 16 literals, where the prime implicants + are typically composed of a maximum of 4 or 5 literals. + date_publication: '2018-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcbiopi + url_git: '' +mcboost: + version: 0.4.3 + title: Multi-Calibration Boosting + maintainer: Sebastian Fischer + description: |- + Implements 'Multi-Calibration Boosting' (2018) and + 'Multi-Accuracy Boosting' (2019) for the multi-calibration of a machine learning model's prediction. + 'MCBoost' updates predictions for sub-groups in an iterative fashion in order to mitigate biases like poor calibration or large accuracy differences across subgroups. + Multi-Calibration works best in scenarios where the underlying data & labels are unbiased, but resulting models are. + This is often the case, e.g. when an algorithm fits a majority population while ignoring or under-fitting minority populations. + date_publication: '2024-04-12' + bug_reports: https://github.com/mlr-org/mcboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcboost + url_git: https://github.com/mlr-org/mcboost +mcca: + version: 0.7.0 + title: Multi-Category Classification Accuracy + maintainer: Ming Gao + description: |- + It contains six common multi-category classification accuracy evaluation measures. + All of these measures could be found in Li and Ming (2019) . Specifically, + Hypervolume Under Manifold (HUM), described in + Li and Fine (2008) . + Correct Classification Percentage (CCP), Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), R-Squared Value (RSQ), described in + Li, Jiang and Fine (2013) . + Polytomous Discrimination Index (PDI), described in + Van Calster et al. (2012) . + Li et al. (2018) . + We described all these above measures and our mcca package in + Li, Gao and D'Agostino (2019) . + date_publication: '2019-12-20' + bug_reports: https://github.com/gaoming96/mcca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcca + url_git: https://github.com/gaoming96/mcca +mccca: + version: 1.1.0.1 + title: |- + Visualizing Class Specific Heterogeneous Tendencies in + Categorical Data + maintainer: Mariko Takagishi + description: |- + Performing multiple-class cluster correspondence analysis(MCCCA). The main functions are create.MCCCAdata() to create a list to be applied to MCCCA, MCCCA() to apply MCCCA, and plot.mccca() for visualizing MCCCA result. Methods used in the + package refers to Mariko Takagishi and Michel van de Velden (2022). + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mccca + url_git: '' +mccf1: + version: '1.1' + title: |- + Creates the MCC-F1 Curve and Calculates the MCC-F1 Metric and + the Best Threshold + maintainer: Chang Cao + description: |- + The MCC-F1 analysis is a method to evaluate the performance of binary classifications. + The MCC-F1 curve is more reliable than the Receiver Operating Characteristic (ROC) curve and the Precision-Recall (PR)curve under imbalanced ground truth. + The MCC-F1 analysis also provides the MCC-F1 metric that integrates classifier performance over varying thresholds, and the best threshold of binary classification. + date_publication: '2019-11-11' + bug_reports: https://stackoverflow.com/questions/tagged/mccf1 + url: '' + url_cran: https://CRAN.R-project.org/package=mccf1 + url_git: https://bitbucket.org/hoffmanlab/mccf1/ +mcclust: + version: 1.0.1 + title: Process an MCMC Sample of Clusterings + maintainer: Arno Fritsch + description: |- + Implements methods for processing a sample of (hard) + clusterings, e.g. the MCMC output of a Bayesian clustering + model. Among them are methods that find a single best + clustering to represent the sample, which are based on the + posterior similarity matrix or a relabelling algorithm. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcclust + url_git: '' +MCCM: + version: 0.1.0 + title: Mixed Correlation Coefficient Matrix + maintainer: Ben Liu + description: The IRLS (Iteratively Reweighted Least Squares) and GMM (Generalized + Method of Moments) methods are applied to estimate mixed correlation coefficient + matrix (Pearson, Polyseries, Polychoric), which can be estimated in pairs or simultaneously. + For more information see Peng Zhang and Ben Liu (2024) ; + Ben Liu and Peng Zhang (2024) . + date_publication: '2024-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCCM + url_git: '' +mccmeiv: + version: '2.1' + title: |- + Analysis of Matched Case Control Data with a Mismeasured + Exposure that is Accompanied by Instrumental Variables + maintainer: Chris M Manuel + description: |- + Applying the methodology from Manuel et al. to estimate parameters using a matched + case control data with a mismeasured exposure variable that is accompanied by + instrumental variables (Submitted). + date_publication: '2019-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mccmeiv + url_git: '' +mccr: + version: 0.4.4 + title: The Matthews Correlation Coefficient + maintainer: Hitoshi Iuchi + description: The Matthews correlation coefficient (MCC) score is calculated (Matthews + BW (1975) ). + date_publication: '2017-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mccr + url_git: '' +MCDA: + version: 0.1.0 + title: Support for the Multicriteria Decision Aiding Process + maintainer: David Palma + description: |- + Support for the analyst in a Multicriteria Decision Aiding (MCDA) process with algorithms, + preference elicitation and data visualisation functions. Sébastien Bigaret, Richard Hodgett, Patrick Meyer, + Tatyana Mironova, Alexandru Olteanu (2017) Supporting the multi-criteria decision aiding process : + R and the MCDA package, Euro Journal On Decision Processes, Volume 5, Issue 1 - 4, + pages 169 - 194 . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCDA + url_git: https://github.com/paterijk/MCDA +mcemGLM: + version: 1.1.3 + title: |- + Maximum Likelihood Estimation for Generalized Linear Mixed + Models + maintainer: Felipe Acosta Archila + description: |- + Maximum likelihood estimation for generalized linear mixed models via Monte Carlo EM. + For a description of the algorithm see Brian S. Caffo, Wolfgang Jank and Galin L. Jones (2005) + . + date_publication: '2023-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcemGLM + url_git: '' +mcen: + version: 1.2.1 + title: Multivariate Cluster Elastic Net + maintainer: Ben Sherwood + description: Fits the Multivariate Cluster Elastic Net (MCEN) presented in Price + & Sherwood (2018) . The MCEN model simultaneously estimates + regression coefficients and a clustering of the responses for a multivariate response + model. Currently accommodates the Gaussian and binomial likelihood. + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcen + url_git: '' +mcga: + version: 3.0.7 + title: |- + Machine Coded Genetic Algorithms for Real-Valued Optimization + Problems + maintainer: Mehmet Hakan Satman + description: |- + Machine coded genetic algorithm (MCGA) is a fast tool for + real-valued optimization problems. It uses the byte + representation of variables rather than real-values. It + performs the classical crossover operations (uniform) on these + byte representations. Mutation operator is also similar to + classical mutation operator, which is to say, it changes a + randomly selected byte value of a chromosome by +1 or -1 with + probability 1/2. In MCGAs there is no need for + encoding-decoding process and the classical operators are + directly applicable on real-values. It is fast and can handle a + wide range of a search space with high precision. Using a + 256-unary alphabet is the main disadvantage of this algorithm + but a moderate size population is convenient for many problems. + Package also includes multi_mcga function for multi objective + optimization problems. This function sorts the chromosomes + using their ranks calculated from the non-dominated sorting + algorithm. + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcga + url_git: '' +mcgf: + version: 1.1.1 + title: Markov Chain Gaussian Fields Simulation and Parameter Estimation + maintainer: Tianxia Jia + description: |- + Simulating and estimating (regime-switching) Markov chain Gaussian + fields with covariance functions of the Gneiting class (Gneiting 2002) + . It supports parameter estimation by + weighted least squares and maximum likelihood methods, and produces Kriging + forecasts and intervals for existing and new locations. + date_publication: '2024-06-29' + bug_reports: https://github.com/tianxia-jia/mcgf/issues + url: https://tianxia-jia.github.io/mcgf/ + url_cran: https://CRAN.R-project.org/package=mcgf + url_git: https://github.com/tianxia-jia/mcgf +mcgibbsit: + version: 1.2.2 + title: |- + Warnes and Raftery's 'MCGibbsit' MCMC Run Length and Convergence + Diagnostic + maintainer: Gregory R. Warnes + description: |2- + + Implementation of Warnes & Raftery's MCGibbsit run-length and + convergence diagnostic for a set of (not-necessarily independent) + Markov Chain Monte Carlo (MCMC) samplers. It combines the quantile + estimate error-bounding approach of the Raftery and Lewis MCMC run + length diagnostic `gibbsit` with the between verses within chain + approach of the Gelman and Rubin MCMC convergence diagnostic. + date_publication: '2023-09-25' + bug_reports: https://github.com/r-gregmisc/mcgibbsit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcgibbsit + url_git: https://github.com/r-gregmisc/mcgibbsit +MChtest: + version: 1.0-3 + title: Monte Carlo Hypothesis Tests with Sequential Stopping + maintainer: Michael P. Fay + description: Performs Monte Carlo hypothesis tests, allowing a couple of different + sequential stopping boundaries. For example, a truncated sequential probability + ratio test boundary (Fay, Kim and Hachey, 2007 ) + and a boundary proposed by Besag and Clifford, 1991 . + Gives valid p-values and confidence intervals on p-values. + date_publication: '2019-05-16' + bug_reports: '' + url: https://www.niaid.nih.gov/about/brb-staff-fay + url_cran: https://CRAN.R-project.org/package=MChtest + url_git: '' +MCI: + version: 1.3.3 + title: Multiplicative Competitive Interaction (MCI) Model + maintainer: Thomas Wieland + description: Market area models are used to analyze and predict store choices and + market areas concerning retail and service locations. This package implements + two market area models (Huff Model, Multiplicative Competitive Interaction Model) + into R, while the emphases lie on 1.) fitting these models based on empirical + data via OLS regression and nonlinear techniques and 2.) data preparation and + processing (esp. interaction matrices and data preparation for the MCI Model). + date_publication: '2017-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCI + url_git: '' +MCID: + version: 0.1.0 + title: Estimating the Minimal Clinically Important Difference + maintainer: Zehua Zhou + description: |- + Apply the marginal classification method to achieve the purpose of providing + the point and interval estimates for the minimal clinically important difference + based on the classical anchor-based method. For more details of the methodology, please + see Zehua Zhou, Leslie J. Bisson and Jiwei Zhao (2021) . + date_publication: '2021-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCID + url_git: '' +MCL: + version: '1.0' + title: Markov Cluster Algorithm + maintainer: Ronja Foraita + description: Contains the Markov cluster algorithm (MCL) for identifying clusters + in networks and graphs. The algorithm simulates random walks on a (n x n) matrix + as the adjacency matrix of a graph. It alternates an expansion step and an inflation + step until an equilibrium state is reached. + date_publication: '2015-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCL + url_git: '' +mclm: + version: 0.2.7 + title: Mastering Corpus Linguistics Methods + maintainer: Mariana Montes + description: |- + Read, inspect and process corpus files for quantitative corpus linguistics. + Obtain concordances via regular expressions, tokenize texts, + and compute frequencies and association measures. Useful for collocation analysis, + keywords analysis and variationist studies (comparison of linguistic variants + and of linguistic varieties). + date_publication: '2022-10-03' + bug_reports: '' + url: https://masterclm.github.io/mclm/ + url_cran: https://CRAN.R-project.org/package=mclm + url_git: https://github.com/masterclm/mclm +mclogit: + version: 0.9.6 + title: |- + Multinomial Logit Models, with or without Random Effects or + Overdispersion + maintainer: Martin Elff + description: |- + Provides estimators for multinomial logit models in their + conditional logit and baseline logit variants, with or without random effects, + with or without overdispersion. + Random effects models are estimated using the PQL technique (based on a Laplace approximation) + or the MQL technique (based on a Solomon-Cox approximation). Estimates should be treated + with caution if the group sizes are small. + date_publication: '2022-10-27' + bug_reports: https://github.com/melff/mclogit/issues + url: http://mclogit.elff.eu + url_cran: https://CRAN.R-project.org/package=mclogit + url_git: https://github.com/melff/mclogit/ +mclust: + version: 6.1.1 + title: |- + Gaussian Mixture Modelling for Model-Based Clustering, + Classification, and Density Estimation + maintainer: Luca Scrucca + description: |- + Gaussian finite mixture models fitted via EM algorithm for + model-based clustering, classification, and density estimation, + including Bayesian regularization, dimension reduction for + visualisation, and resampling-based inference. + date_publication: '2024-04-29' + bug_reports: '' + url: https://mclust-org.github.io/mclust/ + url_cran: https://CRAN.R-project.org/package=mclust + url_git: '' +mclustAddons: + version: 0.9.1 + title: Addons for the 'mclust' Package + maintainer: Luca Scrucca + description: |- + Extend the functionality of the 'mclust' package for Gaussian + finite mixture modeling by including: density estimation for data with + bounded support (Scrucca, 2019 ); modal + clustering using MEM (Modal EM) algorithm for Gaussian mixtures + (Scrucca, 2021 ); entropy estimation via + Gaussian mixture modeling (Robin & Scrucca, 2023 + ); Gaussian mixtures modeling of + financial log-returns (Scrucca, 2024 ). + date_publication: '2024-11-13' + bug_reports: '' + url: https://mclust-org.github.io/mclustAddons/ + url_cran: https://CRAN.R-project.org/package=mclustAddons + url_git: '' +mclustcomp: + version: 0.3.3 + title: Measures for Comparing Clusters + maintainer: Kisung You + description: |- + Given a set of data points, a clustering is defined as a disjoint partition + where each pair of sets in a partition has no overlapping elements. + This package provides 25 methods that play a role somewhat similar to + distance or metric that measures similarity of two clusterings - or partitions. + For a more detailed description, see Meila, M. (2005) . + date_publication: '2021-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mclustcomp + url_git: '' +MCM: + version: 0.1.7 + title: Estimating and Testing Intergenerational Social Mobility Effect + maintainer: Jiahui Xu + description: Estimate and test inter-generational social mobility effect on an outcome + with cross-sectional or longitudinal data. + date_publication: '2022-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCM + url_git: '' +mcmapper: + version: 0.0.11 + title: |- + Mapping First Moment and C-Statistic to the Parameters of + Distributions for Risk + maintainer: Mohsen Sadatsafavi + description: Provides a series of numerical methods for extracting parameters of + distributions for risks based on knowing the expected value and c-statistics (e.g., + from a published report on the performance of a risk prediction model). This package + implements the methodology described in Sadatsafavi et al (2024) . + The core of the package is mcmap(), which takes a pair of (mean, c-statistic) + and the distribution type requested. This function provides a generic interface + to more customized functions (mcmap_beta(), mcmap_logitnorm(), mcmap_probitnorm()) + for specific distributions. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcmapper + url_git: '' +mcmc: + version: 0.9-8 + title: Markov Chain Monte Carlo + maintainer: Charles J. Geyer + description: |- + Simulates continuous distributions of random vectors using + Markov chain Monte Carlo (MCMC). Users specify the distribution by an + R function that evaluates the log unnormalized density. Algorithms + are random walk Metropolis algorithm (function metrop), simulated + tempering (function temper), and morphometric random walk Metropolis + (Johnson and Geyer, 2012, , + function morph.metrop), + which achieves geometric ergodicity by change of variable. + date_publication: '2023-11-16' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/mcmc/ + url_cran: https://CRAN.R-project.org/package=mcmc + url_git: https://github.com/cjgeyer/mcmc +MCMC.OTU: + version: 1.0.10 + title: |- + Bayesian Analysis of Multivariate Counts Data in DNA + Metabarcoding and Ecology + maintainer: Mikhail V. Matz + description: 'Poisson-lognormal generalized linear mixed model analysis of multivariate + counts data using MCMC, aiming to infer the changes in relative proportions of + individual variables. The package was originally designed for sequence-based analysis + of microbial communities ("metabarcoding", variables = operational taxonomic units, + OTUs), but can be used for other types of multivariate counts, such as in ecological + applications (variables = species). The results are summarized and plotted using + ''ggplot2'' functions. Includes functions to remove sample and variable outliers + and reformat counts into normalized log-transformed values for correlation and + principal component/coordinate analysis. Walkthrough and examples: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/walkthroughExample_mcmcOTU_R.txt.' + date_publication: '2016-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMC.OTU + url_git: '' +MCMC.qpcr: + version: 1.2.4 + title: Bayesian Analysis of qRT-PCR Data + maintainer: Mikhail V. Matz + description: 'Quantitative RT-PCR data are analyzed using generalized linear mixed + models based on lognormal-Poisson error distribution, fitted using MCMC. Control + genes are not required but can be incorporated as Bayesian priors or, when template + abundances correlate with conditions, as trackers of global effects (common to + all genes). The package also implements a lognormal model for higher-abundance + data and a "classic" model involving multi-gene normalization on a by-sample basis. + Several plotting functions are included to extract and visualize results. The + detailed tutorial is available here: .' + date_publication: '2020-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMC.qpcr + url_git: '' +MCMC4Extremes: + version: '1.1' + title: Posterior Distribution of Extreme Value Models in R + maintainer: Fernando Ferraz do Nascimento + description: Provides some function to perform posterior estimation for some distribution, + with emphasis to extreme value distributions. It contains some extreme datasets, + and functions that perform the runs of posterior points of the GPD and GEV distribution. + The package calculate some important extreme measures like return level for each + t periods of time, and some plots as the predictive distribution, and return level + plots. + date_publication: '2016-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMC4Extremes + url_git: '' +mcmcderive: + version: 0.1.2 + title: Derive MCMC Parameters + maintainer: Joe Thorley + description: |- + Generates derived parameter(s) from Monte Carlo Markov Chain + (MCMC) samples using R code. This allows Bayesian models to be fitted + without the inclusion of derived parameters which add unnecessary + clutter and slow model fitting. For more information on MCMC samples + see Brooks et al. (2011) . + date_publication: '2021-08-06' + bug_reports: https://github.com/poissonconsulting/mcmcderive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcmcderive + url_git: https://github.com/poissonconsulting/mcmcderive +mcmcensemble: + version: 3.1.0 + title: Ensemble Sampler for Affine-Invariant MCMC + maintainer: Hugo Gruson + description: |- + Provides ensemble samplers for + affine-invariant Monte Carlo Markov Chain, which allow a faster + convergence for badly scaled estimation problems. Two samplers are + proposed: the 'differential.evolution' sampler from ter Braak and + Vrugt (2008) and the 'stretch' sampler + from Goodman and Weare (2010) . + date_publication: '2024-03-20' + bug_reports: https://github.com/Bisaloo/mcmcensemble/issues + url: https://hugogruson.fr/mcmcensemble/ + url_cran: https://CRAN.R-project.org/package=mcmcensemble + url_git: https://github.com/Bisaloo/mcmcensemble +MCMCglmm: + version: '2.36' + title: MCMC Generalised Linear Mixed Models + maintainer: Jarrod Hadfield + description: Fits Multivariate Generalised Linear Mixed Models (and related models) + using Markov chain Monte Carlo techniques (Hadfield 2010 J. Stat. Soft.). + date_publication: '2024-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMCglmm + url_git: https://github.com/jarrodhadfield/MCMCglmm +mcmcOutput: + version: 0.1.3 + title: |- + Functions to Store, Manipulate and Display Markov Chain Monte + Carlo (MCMC) Output + maintainer: Ngumbang Juat + description: Implements a class ('mcmcOutput') for efficiently storing and handling + Markov chain Monte Carlo (MCMC) output, intended as an aid for those writing customized + MCMC samplers. A range of constructor methods are provided covering common output + formats. Functions are provided to generate summary and diagnostic statistics + and to display histograms or density plots of posterior distributions, for the + entire output, or subsets of draws, nodes, or parameters. + date_publication: '2022-11-17' + bug_reports: https://github.com/mikemeredith/mcmcOutput/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcmcOutput + url_git: https://github.com/mikemeredith/mcmcOutput +MCMCpack: + version: 1.7-1 + title: Markov Chain Monte Carlo (MCMC) Package + maintainer: Jong Hee Park + description: |- + Contains functions to perform Bayesian + inference using posterior simulation for a number of + statistical models. Most simulation is done in compiled C++ + written in the Scythe Statistical Library Version 1.0.3. All + models return 'coda' mcmc objects that can then be summarized + using the 'coda' package. Some useful + utility functions such as density functions, + pseudo-random number generators for statistical + distributions, a general purpose Metropolis sampling algorithm, + and tools for visualization are provided. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMCpack + url_git: '' +mcmcplots: + version: 0.4.3 + title: Create Plots from MCMC Output + maintainer: S. McKay Curtis + description: Functions for convenient plotting and viewing of MCMC output. + date_publication: '2018-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcmcplots + url_git: '' +MCMCprecision: + version: 0.4.0 + title: Precision of Discrete Parameters in Transdimensional MCMC + maintainer: Daniel W. Heck + description: |- + Estimates the precision of transdimensional Markov chain Monte Carlo + (MCMC) output, which is often used for Bayesian analysis of models with different + dimensionality (e.g., model selection). Transdimensional MCMC (e.g., reversible + jump MCMC) relies on sampling a discrete model-indicator variable to estimate + the posterior model probabilities. If only few switches occur between the models, + precision may be low and assessment based on the assumption of independent + samples misleading. Based on the observed transition matrix of the indicator + variable, the method of Heck, Overstall, Gronau, & Wagenmakers (2019, + Statistics & Computing, 29, 631-643) draws + posterior samples of the stationary distribution to (a) assess the uncertainty + in the estimated posterior model probabilities and (b) estimate the effective + sample size of the MCMC output. + date_publication: '2019-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMCprecision + url_git: https://github.com/danheck/MCMCprecision +mcmcr: + version: 0.6.2 + title: Manipulate MCMC Samples + maintainer: Joe Thorley + description: |- + Functions and classes to store, manipulate and summarise + Monte Carlo Markov Chain (MCMC) samples. For more information see + Brooks et al. (2011) . + date_publication: '2025-01-23' + bug_reports: https://github.com/poissonconsulting/mcmcr/issues + url: https://poissonconsulting.github.io/mcmcr/ + url_cran: https://CRAN.R-project.org/package=mcmcr + url_git: https://github.com/poissonconsulting/mcmcr +mcmcsae: + version: 0.7.8 + title: Markov Chain Monte Carlo Small Area Estimation + maintainer: Harm Jan Boonstra + description: |- + Fit multi-level models with possibly correlated + random effects using Markov Chain Monte Carlo simulation. + Such models allow smoothing over space and time and are useful in, + for example, small area estimation. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcmcsae + url_git: '' +mcmcse: + version: 1.5-0 + title: Monte Carlo Standard Errors for MCMC + maintainer: Dootika Vats + description: |- + Provides tools for computing Monte Carlo standard + errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE + computation for expectation and quantile estimators is + supported as well as multivariate estimations. The package also provides + functions for computing effective sample size and for plotting + Monte Carlo estimates versus sample size. + date_publication: '2021-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcmcse + url_git: '' +MCMCtreeR: + version: '1.1' + title: |- + Prepare MCMCtree Analyses and Plot Bayesian Divergence Time + Analyses Estimates on Trees + maintainer: Mark Puttick + description: Provides functions to prepare time priors for 'MCMCtree' analyses in + the 'PAML' software from Yang (2007) and plot time-scaled + phylogenies from any Bayesian divergence time analysis. Most time-calibrated node + prior distributions require user-specified parameters. The package provides functions + to refine these parameters, so that the resulting prior distributions accurately + reflect confidence in known, usually fossil, time information. These functions + also enable users to visualise distributions and write 'MCMCtree' ready input + files. Additionally, the package supplies flexible functions to visualise age + uncertainty on a plotted tree with using node bars, using branch widths proportional + to the age uncertainty, or by plotting the full posterior distributions on nodes. + Time-scaled phylogenetic plots can be visualised with absolute and geological + timescales . All plotting functions are applicable with output from any Bayesian + software, not just 'MCMCtree'. + date_publication: '2019-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCMCtreeR + url_git: '' +MCMCvis: + version: 0.16.3 + title: Tools to Visualize, Manipulate, and Summarize MCMC Output + maintainer: Casey Youngflesh + description: Performs key functions for MCMC analysis using minimal code - visualizes, + manipulates, and summarizes MCMC output. Functions support simple and straightforward + subsetting of model parameters within the calls, and produce presentable and 'publication-ready' + output. MCMC output may be derived from Bayesian model output fit with 'Stan', + 'NIMBLE', 'JAGS', and other software. + date_publication: '2023-10-17' + bug_reports: https://github.com/caseyyoungflesh/MCMCvis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MCMCvis + url_git: https://github.com/caseyyoungflesh/MCMCvis +mcMST: + version: 1.1.1 + title: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem + maintainer: Jakob Bossek + description: Algorithms to approximate the Pareto-front of multi-criteria minimum + spanning tree problems. + date_publication: '2023-03-13' + bug_reports: https://github.com/jakobbossek/mcMST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcMST + url_git: https://github.com/jakobbossek/mcMST +mcmsupply: + version: 1.1.1 + title: |- + Estimating Public and Private Sector Contraceptive Market Supply + Shares + maintainer: Hannah Comiskey + description: Family Planning programs and initiatives typically use nationally representative + surveys to estimate key indicators of a country’s family planning progress. However, + in recent years, routinely collected family planning services data (Service Statistics) + have been used as a supplementary data source to bridge gaps in the surveys. The + use of service statistics comes with the caveat that adjustments need to be made + for missing private sector contributions to the contraceptive method supply chain. + Evaluating the supply source of modern contraceptives often relies on Demographic + Health Surveys (DHS), where many countries do not have recent data beyond 2015/16. + Fortunately, in the absence of recent surveys we can rely on statistical model-based + estimates and projections to fill the knowledge gap. We present a Bayesian, hierarchical, + penalized-spline model with multivariate-normal spline coefficients, to account + for across method correlations, to produce country-specific,annual estimates for + the proportion of modern contraceptive methods coming from the public and private + sectors. This package provides a quick and convenient way for users to access + the DHS modern contraceptive supply share data at national and subnational administration + levels, estimate, evaluate and plot annual estimates with uncertainty for a sample + of low- and middle-income countries. Methods for the estimation of method supply + shares at the national level are described in Comiskey, Alkema, Cahill (2022) + . + date_publication: '2024-03-18' + bug_reports: '' + url: https://hannahcomiskey.github.io/mcmsupply/ + url_cran: https://CRAN.R-project.org/package=mcmsupply + url_git: '' +mco: + version: '1.17' + title: Multiple Criteria Optimization Algorithms and Related Functions + maintainer: Olaf Mersmann + description: |- + A collection of function to solve multiple criteria optimization problems + using genetic algorithms (NSGA-II). Also included is a collection of test functions. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mco + url_git: https://github.com/olafmersmann/mco +mcODE: + version: '1.1' + title: Monte Carlo Solution of First Order Differential Equations + maintainer: W.J. Braun + description: Two functions for simulating the solution of initial value problems + of the form g'(x) = G(x, g) with g(x0) = g0. One is an acceptance-rejection method. + The other is a method based on the Mean Value Theorem. + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcODE + url_git: '' +MCOE: + version: 0.4.0 + title: |- + Creates New Folders and Loads Standard Practices for Monterey + County Office of Education + maintainer: David Dobrowski + description: Basic Setup for Projects in R for Monterey County Office of Education. + It contains functions often used in the analysis of education data in the county + office including seeing if an item is not in a list, rounding in the manner the + general public expects, including logos for districts, switching between district + names and their county-district-school codes, accessing the local 'SQL' table + and making thematically consistent graphs. + date_publication: '2024-02-06' + bug_reports: https://github.com/dobrowski/MCOE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MCOE + url_git: https://github.com/dobrowski/MCOE +Mcomp: + version: '2.8' + title: Data from the M-Competitions + maintainer: Rob Hyndman + description: |2- + + The 1001 time series from the M-competition (Makridakis et al. 1982) and the 3003 time series from the IJF-M3 competition (Makridakis and Hibon, 2000) . + date_publication: '2018-06-19' + bug_reports: https://github.com/robjhyndman/Mcomp/issues + url: http://pkg.robjhyndman.com/Mcomp/ + url_cran: https://CRAN.R-project.org/package=Mcomp + url_git: https://github.com/robjhyndman/Mcomp +mcompanion: + version: '0.6' + title: Objects and Methods for Multi-Companion Matrices + maintainer: Georgi N. Boshnakov + description: |2- + + Provides a class for multi-companion matrices with methods for + arithmetic and factorization. A method for generation of + multi-companion matrices with prespecified spectral properties is + provided, as well as some utilities for periodically correlated and + multivariate time series models. See Boshnakov (2002) + and Boshnakov & Iqelan (2009) + . + date_publication: '2023-12-03' + bug_reports: https://github.com/GeoBosh/mcompanion/issues + url: https://geobosh.github.io/mcompanion/(doc) + url_cran: https://CRAN.R-project.org/package=mcompanion + url_git: https://github.com/GeoBosh/mcompanion(devel) +mcount: + version: 1.0.0 + title: Marginalized Count Regression Models + maintainer: Zhengyang Zhou + description: |- + Implementation of marginalized models for zero-inflated count data. This package provides a tool to implement an estimation algorithm for the marginalized count models, which + directly makes inference on the effect of each covariate on the marginal mean of the outcome. + The method involves the marginalized zero-inflated Poisson model described + in Long et al. (2014) . + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcount + url_git: '' +mcp: + version: 0.3.4 + title: Regression with Multiple Change Points + maintainer: Jonas Kristoffer Lindeløv + description: Flexible and informed regression with Multiple Change Points. 'mcp' + can infer change points in means, variances, autocorrelation structure, and any + combination of these, as well as the parameters of the segments in between. All + parameters are estimated with uncertainty and prediction intervals are supported + - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey + density ratio, posterior contrasts, and cross-validation. 'mcp' is described in + Lindeløv (submitted) and generalizes the approach + described in Carlin, Gelfand, & Smith (1992) and Stephens + (1994) . + date_publication: '2024-03-17' + bug_reports: https://github.com/lindeloev/mcp/issues + url: https://lindeloev.github.io/mcp/ + url_cran: https://CRAN.R-project.org/package=mcp + url_git: '' +MCPAN: + version: 1.1-21 + title: Multiple Comparisons Using Normal Approximation + maintainer: Frank Schaarschmidt + description: |- + Multiple contrast tests and simultaneous confidence + intervals based on normal approximation. With implementations for + binomial proportions in a 2xk setting (risk difference and odds ratio), + poly-3-adjusted tumour rates, biodiversity indices (multinomial data) + and expected values under lognormal assumption. Approximative power + calculation for multiple contrast tests of binomial and Gaussian data. + date_publication: '2018-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCPAN + url_git: '' +mcparallelDo: + version: 1.1.0 + title: |- + A Simplified Interface for Running Commands on Parallel + Processes + maintainer: Russell S. Pierce + description: |- + Provides a function that wraps + mcparallel() and mccollect() from 'parallel' with temporary variables and a + task handler. Wrapped in this way the results of an mcparallel() call + can be returned to the R session when the fork is complete + without explicitly issuing a specific mccollect() to retrieve the value. + Outside of top-level tasks, multiple mcparallel() jobs can be retrieved with + a single call to mcparallelDoCheck(). + date_publication: '2016-07-24' + bug_reports: https://github.com/drknexus/mcparallelDo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcparallelDo + url_git: https://github.com/drknexus/mcparallelDo +MCPMod: + version: 1.0-10.1 + title: Design and Analysis of Dose-Finding Studies + maintainer: Bjoern Bornkamp + description: |- + Implements a methodology for the design and analysis of dose-response studies that + combines aspects of multiple comparison procedures and modeling approaches + (Bretz, Pinheiro and Branson, 2005, Biometrics 61, 738-748, ). + The package provides tools for the analysis of dose finding trials as well as a variety + of tools necessary to plan a trial to be conducted with the MCP-Mod methodology. + Please note: The 'MCPMod' package will not be further developed, all future development of + the MCP-Mod methodology will be done in the 'DoseFinding' R-package. + date_publication: '2020-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCPMod + url_git: '' +MCPModBC: + version: '1.1' + title: Improved Inference in Multiple Comparison Procedure – Modelling + maintainer: Diego Gallardo + description: |- + Implementation of Multiple Comparison Procedures with Modeling + (MCP-Mod) procedure with bias-corrected estimators and second-order + covariance matrices as described in Diniz, Gallardo and Magalhaes (2023) + . + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCPModBC + url_git: '' +MCPModGeneral: + version: 0.1-3 + title: A Supplement to the 'DoseFinding' Package for the General Case + maintainer: Ian Laga + description: |- + Analyzes non-normal data via the Multiple Comparison Procedures and Modeling approach (MCP-Mod). Many functions rely on the 'DoseFinding' package. This package makes it so the user does not need to provide or calculate the mu vector and S matrix. Instead, the user typically supplies the data in its raw form, and this package will calculate the needed objects and passes them into the 'DoseFinding' functions. If the user wishes to primarily use the functions provided in the 'DoseFinding' package, a singular function (prepareGen()) will provide mu and S. The package currently handles power analysis and the MCP-Mod procedure for negative binomial, Poisson, and binomial data. The MCP-Mod procedure can also be applied to survival data, but power analysis is not available. + Bretz, F., Pinheiro, J. C., and Branson, M. (2005) . + Buckland, S. T., Burnham, K. P. and Augustin, N. H. (1997) . + Pinheiro, J. C., Bornkamp, B., Glimm, E. and Bretz, F. (2014) . + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCPModGeneral + url_git: '' +MCPModPack: + version: '0.5' + title: Simulation-Based Design and Analysis of Dose-Finding Trials + maintainer: Alex Dmitrienko + description: An efficient implementation of the MCPMod (Multiple Comparisons and + Modeling) method to support a simulation-based design and analysis of dose-finding + trials with normally distributed, binary and count endpoints (Bretz et al. (2005) + ). + date_publication: '2023-05-30' + bug_reports: https://github.com/medianasoft/MCPModPack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MCPModPack + url_git: https://github.com/medianasoft/MCPModPack +mcprofile: + version: 1.0-1 + title: |- + Testing Generalized Linear Hypotheses for Generalized Linear + Model Parameters by Profile Deviance + maintainer: Daniel Gerhard + description: Calculation of signed root deviance profiles for linear combinations + of parameters in a generalized linear model. Multiple tests and simultaneous confidence + intervals are provided. + date_publication: '2021-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcprofile + url_git: '' +mcprogress: + version: 0.1.1 + title: Progress Bars and Messages for Parallel Processes + maintainer: Myles Lewis + description: Tools for monitoring progress during parallel processing. Lightweight + package which acts as a wrapper around mclapply() and adds a progress bar to it + in 'RStudio' or 'Linux' environments. Simply replace your original call to mclapply() + with pmclapply(). A progress bar can also be displayed during parallelisation + via the 'foreach' package. Also included are functions to safely print messages + (including error messages) from within parallelised code, which can be useful + for debugging parallelised R code. + date_publication: '2024-09-26' + bug_reports: https://github.com/myles-lewis/mcprogress/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mcprogress + url_git: https://github.com/myles-lewis/mcprogress +MCPtests: + version: 1.0.1 + title: Multiples Comparisons Procedures + maintainer: Ben Deivide + description: |- + Performs the execution of the main procedures of multiple + comparisons in the literature, Scott-Knott (1974) , + Batista (2016) , including graphic representations + and export to different extensions of its results. An additional + part of the package is the presence of the performance evaluation + of the tests (Type I error per experiment and the power). This will + assist the user in making the decision for the chosen test. + date_publication: '2020-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCPtests + url_git: '' +mcr: + version: 1.3.3.1 + title: Method Comparison Regression + maintainer: Sergej Potapov + description: |- + Regression methods to quantify the relation between two measurement + methods are provided by this package. In particular it addresses regression + problems with errors in both variables and without repeated measurements. It + implements the CLSI recommendations (see J. A. Budd et al. + (2018, ) + for analytical method comparison and bias estimation using patient samples. + Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators + are implemented, see F. Dufey (2020, ) and + J. Raymaekers and F. Dufey (2022, ). + A comprehensive overview over the implemented methods and references can be found + in the manual pages "mcr-package" and "mcreg". + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcr + url_git: '' +mcradds: + version: 1.1.1 + title: Processing and Analyzing of Diagnostics Trials + maintainer: Kai Gu + description: |- + Provides methods and functions to analyze the quantitative or + qualitative performance for diagnostic assays, and outliers detection, + reader precision and reference range are discussed. Most of the methods + and algorithms refer to CLSI (Clinical & Laboratory Standards Institute) + recommendations and NMPA (National Medical Products Administration) + guidelines. In additional, relevant plots are constructed by 'ggplot2'. + date_publication: '2024-08-30' + bug_reports: https://github.com/kaigu1990/mcradds/issues + url: https://kaigu1990.github.io/mcradds/ + url_cran: https://CRAN.R-project.org/package=mcradds + url_git: https://github.com/kaigu1990/mcradds +mcreplicate: + version: 0.1.2 + title: Multi-Core Replicate + maintainer: Christopher Gandrud + description: |- + Multi-core replication function to make it easier to do fast + Monte Carlo simulation. Based on the mcreplicate() function from the + 'rethinking' package. The 'rethinking' package requires installing 'rstan', + which is onerous to install, while also not adding capabilities to this + function. + date_publication: '2021-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcreplicate + url_git: '' +mcrPioda: + version: 1.3.4 + title: |- + Method Comparison Regression - Mcr Fork for M- And MM-Deming + Regression + maintainer: Giorgio Pioda + description: |- + Regression methods to quantify the relation between two measurement + methods are provided by this package. In particular it addresses regression + problems with errors in both variables and without repeated measurements. It + implements the Clinical Laboratory Standard International (CLSI) + recommendations (see J. A. Budd et al. + (2018, ) + for analytical method comparison and bias estimation using patient samples. + Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators + are implemented, see F. Dufey (2020, ) and + J. Raymaekers and F. Dufey (2022, ). + Further the robust M-Deming and MM-Deming (experimental) are available, see + G. Pioda (2021, ). + A comprehensive overview over the implemented methods and references can be found + in the manual pages 'mcrPioda-package' and 'mcreg'. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcrPioda + url_git: '' +MCS: + version: 0.1.3 + title: Model Confidence Set Procedure + maintainer: Leopoldo Catania + description: Perform the model confidence set procedure of Hansen et al (2011) . + date_publication: '2017-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCS + url_git: '' +MCSim: + version: '1.0' + title: Determine the Optimal Number of Clusters + maintainer: Ahmed N. Albatineh + description: |- + Identifies the optimal number of clusters by calculating the similarity between + two clustering methods at the same number of clusters using the corrected indices of Rand and + Jaccard as described in Albatineh and Niewiadomska-Bugaj (2011). The number of clusters at + which the index attain its maximum more frequently is a candidate for being the optimal + number of clusters. + date_publication: '2018-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCSim + url_git: '' +mcStats: + version: 0.1.2 + title: Visualize Results of Statistical Hypothesis Tests + maintainer: Michael Czekanski + description: "Provides functionality to produce graphs of sampling distributions + of test \tstatistics from a variety of common statistical tests. With only a few + keystrokes, \tthe user can conduct a hypothesis test and visualize the test statistic + and \t\tcorresponding p-value through the shading of its sampling distribution. + Initially \tcreated for statistics at Middlebury College." + date_publication: '2020-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcStats + url_git: '' +mcstatsim: + version: 0.5.0 + title: |- + Monte Carlo Statistical Simulation Tools Using a Functional + Approach + maintainer: Imad EL BADISY + description: |- + A lightweight package designed to facilitate statistical + simulations through functional programming. It centralizes the simulation process into a single + higher-order function, enhancing manageability and usability without adding overhead from external + dependencies. The package includes ready-to-use functions for common simulation targets. A detailed example can be found on . + date_publication: '2024-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcstatsim + url_git: https://github.com/ielbadisy/mcstatsim +mctest: + version: 1.3.1 + title: Multicollinearity Diagnostic Measures + maintainer: Imdad Ullah Muhammad + description: Package computes popular and widely used multicollinearity diagnostic + measures and . Package + also indicates which regressors may be the reason of collinearity among regressors. + date_publication: '2020-06-29' + bug_reports: http://rfaqs.com/contact + url: '' + url_cran: https://CRAN.R-project.org/package=mctest + url_git: '' +mctq: + version: 0.3.2 + title: Tools to Process the Munich ChronoType Questionnaire (MCTQ) + maintainer: Daniel Vartanian + description: |- + A complete toolkit to process the Munich ChronoType + Questionnaire (MCTQ) for its three versions (standard, micro, and shift). + MCTQ is a quantitative and validated tool to assess chronotypes using + peoples' sleep behavior, originally presented by Till Roenneberg, Anna + Wirz-Justice, and Martha Merrow (2003, ). + date_publication: '2023-02-20' + bug_reports: https://github.com/ropensci/mctq/issues/ + url: https://docs.ropensci.org/mctq/ + url_cran: https://CRAN.R-project.org/package=mctq + url_git: https://github.com/ropensci/mctq/ +MCTrend: + version: 1.0.1 + title: Monte Carlo Trend Analysis + maintainer: Alonso Arriagada + description: 'Application of a test to rule out that trends detected in hydrological + time series are explained exclusively by the randomness of the climate. Based + on: Ricchetti, (2018) .' + date_publication: '2023-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MCTrend + url_git: '' +mcunit: + version: 0.3.2 + title: Unit Tests for MC Methods + maintainer: Axel Gandy + description: Unit testing for Monte Carlo methods, particularly Markov Chain Monte + Carlo (MCMC) methods, are implemented as extensions of the 'testthat' package. + The MCMC methods check whether the MCMC chain has the correct invariant distribution. + They do not check other properties of successful samplers such as whether the + chain can reach all points, i.e. whether is recurrent. The tests require the ability + to sample from the prior and to run steps of the MCMC chain. The methodology is + described in Gandy and Scott (2020) . + date_publication: '2021-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcunit + url_git: https://bitbucket.org/agandy/mcunit/ +mcvis: + version: 1.0.8 + title: Multi-Collinearity Visualization + maintainer: Kevin Wang + description: |- + Visualize the relationship between linear regression variables and causes of multi-collinearity. + Implements the method in Lin et. al. (2020) . + date_publication: '2021-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcvis + url_git: '' +mcwr: + version: 1.0.0 + title: Markov Chains with Rewards + maintainer: Daniel Schneider + description: |- + In the context of multistate models, which are popular in sociology, + demography, and epidemiology, Markov chain with rewards calculations can + help to refine transition timings and so obtain more accurate estimates. The + package code accommodates up to nine transient states and irregular age (time) + intervals. Traditional demographic life tables result as a special case. + Formulas and methods involved are explained in detail in the accompanying + article: Schneider / Myrskyla / van Raalte (2021): Flexible Transition Timing + in Discrete-Time Multistate Life Tables Using Markov Chains with Rewards, + MPIDR Working Paper WP-2021-002. + date_publication: '2021-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mcwr + url_git: '' +md: + version: 1.0.4 + title: |- + Selecting Bandwidth for Kernel Density Estimator with Minimum + Distance Method + maintainer: Genzo Kaga + description: Selects bandwidth for the kernel density estimator with minimum distance + method as proposed by Devroye and Lugosi (1996). The minimum distance method directly + selects the optimal kernel density estimator from countably infinite kernel density + estimators and indirectly selects the optimal bandwidth. This package selects + the optimal bandwidth from finite kernel density estimators. + date_publication: '2016-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=md + url_git: '' +md.log: + version: 0.2.0 + title: Produces Markdown Log File with a Built-in Function Call + maintainer: E. F. Haghish + description: |- + Produces clean and neat Markdown log file + and also provide an argument to include the function call inside the Markdown log. + date_publication: '2022-08-05' + bug_reports: https://github.com/haghish/md.log/issues + url: '' + url_cran: https://CRAN.R-project.org/package=md.log + url_git: https://github.com/haghish/md.log +md4r: + version: 0.5.2.0 + title: Markdown Parser Implemented using the 'MD4C' Library + maintainer: Colin Rundel + description: |- + Provides an R wrapper for the 'MD4C' (Markdown for 'C') library. + Functions exist for parsing markdown ('CommonMark' compliant) along with support for other common + markdown extensions (e.g. GitHub flavored markdown, 'LaTeX' equation support, etc.). The + package also provides a number of higher level functions for exploring and manipulating markdown + abstract syntax trees as well as translating and displaying the documents. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=md4r + url_git: '' +mda: + version: 0.5-5 + title: Mixture and Flexible Discriminant Analysis + maintainer: Trevor Hastie + description: |- + Mixture and flexible discriminant analysis, multivariate + adaptive regression splines (MARS), BRUTO, and vector-response smoothing splines. + Hastie, Tibshirani and Friedman (2009) "Elements of Statistical Learning (second edition, chap 12)" Springer, New York. + date_publication: '2024-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mda + url_git: '' +mDAG: + version: 1.2.2 + title: |- + Inferring Causal Network from Mixed Observational Data Using a + Directed Acyclic Graph + maintainer: Wujuan Zhong + description: Learning a mixed directed acyclic graph based on both continuous and + categorical data. + date_publication: '2019-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mDAG + url_git: '' +mdatools: + version: 0.14.2 + title: Multivariate Data Analysis for Chemometrics + maintainer: Sergey Kucheryavskiy + description: Projection based methods for preprocessing, exploring and analysis + of multivariate data used in chemometrics. S. Kucheryavskiy (2020) . + date_publication: '2024-08-19' + bug_reports: https://github.com/svkucheryavski/mdatools/issues + url: https://mda.tools + url_cran: https://CRAN.R-project.org/package=mdatools + url_git: '' +MDBED: + version: 1.0.0 + title: Moran-Downton Bivariate Exponential Distribution + maintainer: Luis F. Duque + description: |- + Provides 3D plots of the Moran-Downton bivariate exponential distribution (MDBED), + generates bivariate random values, and also provides values of the joint and conditional PDFs and CDFs. + Nagao M, Kadoya M (1971) . + Balakrishna N, Lai CD (2009) . + date_publication: '2020-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDBED + url_git: '' +mdbr: + version: 0.2.1 + title: Work with Microsoft Access Files + maintainer: Kiernan Nicholls + description: |- + Use the open source 'MDB Tools' utilities + . Primarily used for converting + proprietary Microsoft Access files to simple text files and then + reading those as data frames. + date_publication: '2024-03-12' + bug_reports: https://github.com/k5cents/mdbr/issues + url: https://k5cents.github.io/mdbr/ + url_cran: https://CRAN.R-project.org/package=mdbr + url_git: https://github.com/k5cents/mdbr +MDDC: + version: 1.0.0 + title: |- + Modified Detecting Deviating Cells Algorithm in + Pharmacovigilance + maintainer: Anran Liu + description: |- + Methods for detecting signals related to (adverse event, medical + product e.g. drugs, vaccines) pairs, a data generation function for + simulating pharmacovigilance datasets, and various utility functions. + For more details please see Liu A., Mukhopadhyay R., and Markatou M. + . + date_publication: '2024-10-04' + bug_reports: https://github.com/niuniular/MDDC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MDDC + url_git: https://github.com/niuniular/MDDC +mddmaps: + version: 1.3.0 + title: Download World Mammal Maps + maintainer: Angel Robles + description: |- + Lightweight maps of mammals of the world. These maps are a + comprehensive collection of maps aligned with the Mammal Diversity Database + taxonomy of the American Society of Mammalogists. They are generated at low + resolution for easy access, consultation and manipulation in shapefile + format. The package connects to a binary backup hosted in the Digital Ocean + cloud service and allows individual or batch download of any mammal species + in the mdd taxonomy by providing the scientific species name. + date_publication: '2024-05-14' + bug_reports: https://github.com/alrobles/mdd/issues + url: + url_cran: https://CRAN.R-project.org/package=mddmaps + url_git: +mde: + version: 0.3.2 + title: Missing Data Explorer + maintainer: Nelson Gonzabato + description: |- + Correct identification and handling of missing data is one of the most important steps in any analysis. To aid this process, 'mde' provides a very easy to use yet robust framework to quickly get an idea of where the missing data + lies and therefore find the most appropriate action to take. + Graham WJ (2009) . + date_publication: '2022-02-10' + bug_reports: https://github.com/Nelson-Gon/mde/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mde + url_git: https://github.com/Nelson-Gon/mde +mded: + version: 0.1-2 + title: Measuring the Difference Between Two Empirical Distributions + maintainer: Hideo Aizaki + description: Provides a function for measuring the difference between two independent + or non-independent empirical distributions and returning a significance level + of the difference. + date_publication: '2015-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mded + url_git: '' +MDEI: + version: '1.0' + title: Implementing the Method of Direct Estimation and Inference + maintainer: Marc Ratkovic + description: |- + Causal and statistical inference on an arbitrary treatment + effect curve requires care in both estimation and inference. This + package, implements the Method of Direct Estimation and Inference as introduced in "Estimation and Inference on Nonlinear and Heterogeneous Effects" by Ratkovic and Tingley (2023) . The method takes an outcome, variable of theoretical interest + (treatment), and set of variables and then returns a partial + derivative (marginal effect) of the treatment variable at each point + along with uncertainty intervals. The approach offers two advances. + First, a split-sample approach is used as a guard against over-fitting. + Second, the method uses a data-driven interval derived from conformal + inference, rather than relying on a normality assumption on the error + terms. + date_publication: '2023-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDEI + url_git: '' +mdendro: + version: 2.2.1 + title: Extended Agglomerative Hierarchical Clustering + maintainer: Alberto Fernandez + description: |- + A comprehensive collection of linkage methods for agglomerative + hierarchical clustering on a matrix of proximity data (distances or + similarities), returning a multifurcated dendrogram or multidendrogram. + Multidendrograms can group more than two clusters when ties in proximity data + occur, and therefore they do not depend on the order of the input data. + Descriptive measures to analyze the resulting dendrogram are additionally + provided. + date_publication: '2024-01-09' + bug_reports: '' + url: https://webs-deim.urv.cat/~sergio.gomez/mdendro.php + url_cran: https://CRAN.R-project.org/package=mdendro + url_git: '' +MDFS: + version: 1.5.5 + title: MultiDimensional Feature Selection + maintainer: Radosław Piliszek + description: |- + Functions for MultiDimensional Feature Selection (MDFS): + calculating multidimensional information gains, scoring variables, + finding important variables, plotting selection results. + This package includes an optional CUDA implementation that speeds up + information gain calculation using NVIDIA GPGPUs. + R. Piliszek et al. (2019) . + date_publication: '2024-12-12' + bug_reports: '' + url: https://www.mdfs.it/ + url_cran: https://CRAN.R-project.org/package=MDFS + url_git: '' +mdftracks: + version: 0.2.2 + title: Read and Write 'MTrackJ Data Files' + maintainer: Gerhard Burger + description: |- + 'MTrackJ' is an 'ImageJ' plugin for motion tracking and analysis (see + ). This package reads + and writes 'MTrackJ Data Files' ('.mdf', see + ). It supports + 2D data and read/writes cluster, point, and channel information. If desired, + generates track identifiers that are unique over the clusters. + See the project page for more information and examples. + date_publication: '2024-01-08' + bug_reports: https://github.com/burgerga/mdftracks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mdftracks + url_git: https://github.com/burgerga/mdftracks +mdgc: + version: 0.1.7 + title: Missing Data Imputation Using Gaussian Copulas + maintainer: Benjamin Christoffersen + description: |- + Provides functions to impute missing values using Gaussian + copulas for mixed data types as described by Christoffersen et al. + (2021) . The method is related to Hoff (2007) + and Zhao and Udell (2019) + but differs by making a direct approximation of the log marginal likelihood + using an extended version of the Fortran code created by Genz and Bretz + (2002) in addition to also support multinomial + variables. + date_publication: '2023-05-04' + bug_reports: https://github.com/boennecd/mdgc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mdgc + url_git: https://github.com/boennecd/mdgc +mdhglm: + version: '1.8' + title: Multivariate Double Hierarchical Generalized Linear Models + maintainer: Maengseok Noh + description: Allows various models for multivariate response variables where each + response is assumed to follow double hierarchical generalized linear models. In + double hierarchical generalized linear models, the mean, dispersion parameters + for variance of random effects, and residual variance can be further modeled as + random-effect models. + date_publication: '2018-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mdhglm + url_git: '' +MDimNormn: + version: 0.8.0 + title: Multi-Dimensional MA Normalization for Plate Effect + maintainer: Mun-Gwan Hong + description: |- + Normalize data to minimize the difference between sample plates + (batch effects). For given data in a matrix and grouping variable (or + plate), the function 'normn_MA' normalizes the data on MA coordinates. + More details are in the citation. The primary method is 'Multi-MA'. Other + fitting functions on MA coordinates can also be employed e.g. loess. + date_publication: '2015-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDimNormn + url_git: '' +mdir.logrank: + version: 0.0.4 + title: Multiple-Direction Logrank Test + maintainer: Sarah Friedrich + description: |- + Implemented are the one-sided and two-sided + multiple-direction logrank test for two-sample right + censored data. In addition to the statistics p-values are calculated: + 1. For the one-sided testing problem one p-value based on a + wild bootstrap approach is determined. 2. In the two-sided case + one p-value based on a chi-squared approximation and + a second p-values based on a permutation approach are calculated. + Ditzhaus, M. and Friedrich, S. (2018) . + Ditzhaus, M. and Pauly, M. (2018) . + date_publication: '2018-09-29' + bug_reports: http://github.com/marcdii/mdir.logrank/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mdir.logrank + url_git: '' +MDMA: + version: 1.1.0 + title: Mathijs Deen's Miscellaneous Auxiliaries + maintainer: Mathijs Deen + description: |- + Provides a variety of functions useful for data analysis, + selection, manipulation, and graphics. + date_publication: '2024-04-25' + bug_reports: https://github.com/mathijsdeen/MDMA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MDMA + url_git: https://github.com/mathijsdeen/MDMA +MDMAPR: + version: 0.2.3 + title: Molecular Detection Mapping and Analysis Platform + maintainer: Alka Benawra + description: |- + Runs a Shiny web application that merges raw 'qPCR' fluorescence data with related + metadata to visualize species presence/absence detection patterns and assess data quality. + The application calculates threshold values from raw fluorescence data using a method based + on the second derivative method, Luu-The et al (2005) , and utilizes + the ‘chipPCR’ package by Rödiger, Burdukiewicz, & Schierack (2015) + to calculate Cq values. The application has the ability to connect to a custom developed MySQL + database to populate the applications interface. The application allows users to interact with + visualizations such as a dynamic map, amplification curves and standard curves, that allow for + zooming and/or filtering. It also enables the generation of customized exportable reports based + on filtered mapping data. + date_publication: '2021-06-23' + bug_reports: https://github.com/HannerLab/MDMAPR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MDMAPR + url_git: https://github.com/HannerLab/MDMAPR +mdmb: + version: 1.9-22 + title: Model Based Treatment of Missing Data + maintainer: Alexander Robitzsch + description: |- + Contains model-based treatment of missing data for regression + models with missing values in covariates or the dependent + variable using maximum likelihood or Bayesian estimation + (Ibrahim et al., 2005; ; + Luedtke, Robitzsch, & West, 2020a, 2020b; + ). + The regression model can be nonlinear (e.g., interaction + effects, quadratic effects or B-spline functions). + Multilevel models with missing data in predictors are + available for Bayesian estimation. Substantive-model compatible + multiple imputation can be also conducted. + date_publication: '2024-07-15' + bug_reports: '' + url: https://sites.google.com/site/alexanderrobitzsch2/software + url_cran: https://CRAN.R-project.org/package=mdmb + url_git: https://github.com/alexanderrobitzsch/mdmb +MDMR: + version: 0.5.1 + title: Multivariate Distance Matrix Regression + maintainer: Daniel B. McArtor + description: Allows users to conduct multivariate distance matrix regression using + analytic p-values and compute measures of effect size. For details on the method, + see McArtor, Lubke, & Bergeman (2017) . + date_publication: '2018-02-14' + bug_reports: http://github.com/dmcartor/mdmr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MDMR + url_git: http://github.com/dmcartor/mdmr +MDOLS: + version: '1.0' + title: Inference of Quadratic Functional for Moderate-Dimensional OLS + maintainer: Xiao Guo + description: Statistical inference for quadratic functional of the moderate-dimensional + linear model in Guo and Cheng (2021) . + date_publication: '2021-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDOLS + url_git: '' +mdpeer: + version: 1.0.1 + title: |- + Graph-Constrained Regression with Enhanced Regularization + Parameters Selection + maintainer: Marta Karas + description: |- + Provides graph-constrained regression methods in which + regularization parameters are selected automatically via estimation of + equivalent Linear Mixed Model formulation. 'riPEER' (ridgified Partially + Empirical Eigenvectors for Regression) method employs a penalty term being + a linear combination of graph-originated and ridge-originated penalty terms, + whose two regularization parameters are ML estimators from corresponding + Linear Mixed Model solution; a graph-originated penalty term allows imposing + similarity between coefficients based on graph information given whereas + additional ridge-originated penalty term facilitates parameters estimation: + it reduces computational issues arising from singularity in a graph-originated + penalty matrix and yields plausible results in situations when graph information + is not informative. 'riPEERc' (ridgified Partially Empirical Eigenvectors + for Regression with constant) method utilizes addition of a diagonal matrix + multiplied by a predefined (small) scalar to handle the non-invertibility of + a graph Laplacian matrix. 'vrPEER' (variable reducted PEER) method performs + variable-reduction procedure to handle the non-invertibility of a graph + Laplacian matrix. + date_publication: '2017-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mdpeer + url_git: '' +MDPIexploreR: + version: 0.2.0 + title: Web Scraping and Bibliometric Analysis of MDPI Journals + maintainer: Pablo Gómez Barreiro + description: Provides comprehensive tools to scrape and analyze data from the MDPI + journals. It allows users to extract metrics such as submission-to-acceptance + times, article types, and whether articles are part of special issues. The package + can also visualize this information through plots. Additionally, 'MDPIexploreR' + offers tools to explore patterns of self-citations within articles and provides + insights into guest-edited special issues. + date_publication: '2024-10-15' + bug_reports: '' + url: https://pgomba.github.io/MDPI_explorer/ + url_cran: https://CRAN.R-project.org/package=MDPIexploreR + url_git: '' +MDplot: + version: 1.0.1 + title: Visualising Molecular Dynamics Analyses + maintainer: Christian Margreitter + description: |- + Provides automatization for plot generation succeeding common molecular dynamics analyses. + This includes straightforward plots, such as RMSD (Root-Mean-Square-Deviation) and + RMSF (Root-Mean-Square-Fluctuation) but also more sophisticated ones such as + dihedral angle maps, hydrogen bonds, cluster bar plots and + DSSP (Definition of Secondary Structure of Proteins) analysis. Currently able to load + GROMOS, GROMACS and AMBER formats, respectively. + date_publication: '2017-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDplot + url_git: https://github.com/MDplot/MDplot +MDPtoolbox: + version: 4.0.3 + title: Markov Decision Processes Toolbox + maintainer: Guillaume Chapron + description: 'The Markov Decision Processes (MDP) toolbox proposes functions related + to the resolution of discrete-time Markov Decision Processes: finite horizon, + value iteration, policy iteration, linear programming algorithms with some variants + and also proposes some functions related to Reinforcement Learning.' + date_publication: '2017-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDPtoolbox + url_git: '' +mds: + version: 0.3.2 + title: Medical Devices Surveillance + maintainer: Gary Chung + description: |- + A set of core functions for handling medical device event data in + the context of post-market surveillance, pharmacovigilance, signal detection + and trending, and regulatory reporting. Primary inputs are data on events by + device and data on exposures by device. Outputs include: standardized + device-event and exposure datasets, defined analyses, and time series. + date_publication: '2020-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mds + url_git: '' +mdscore: + version: 0.1-3 + title: Improved Score Tests for Generalized Linear Models + maintainer: Antonio Hermes M. da Silva-Junior + description: A set of functions to obtain modified score test for generalized linear + models. + date_publication: '2017-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mdscore + url_git: '' +MDSMap: + version: '1.1' + title: |- + High Density Genetic Linkage Mapping using Multidimensional + Scaling + maintainer: Bram Boskamp + description: Estimate genetic linkage maps for markers on a single chromosome (or + in a single linkage group) from pairwise recombination fractions or intermarker + distances using weighted metric multidimensional scaling. The methods are suitable + for autotetraploid as well as diploid populations. Options for assessing the fit + to a known map are also provided. Methods are discussed in detail in Preedy and + Hackett (2016) . + date_publication: '2018-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDSMap + url_git: '' +mdsOpt: + version: 0.7-6 + title: |- + Searching for Optimal MDS Procedure for Metric and + Interval-Valued Data + maintainer: Andrzej Dudek + description: |- + Selecting the optimal multidimensional scaling (MDS) procedure for metric data via metric MDS (ratio, interval, mspline) and nonmetric MDS (ordinal). Selecting the optimal multidimensional scaling (MDS) procedure for interval-valued data via metric MDS (ratio, interval, mspline).Selecting the optimal multidimensional scaling procedure for interval-valued data by varying all combinations of normalization and optimization methods.Selecting the optimal MDS procedure for statistical data referring to the evaluation of tourist attractiveness of Lower Silesian counties. + (Borg, I., Groenen, P.J.F., Mair, P. (2013) , + Walesiak, M. (2016) , + Walesiak, M. (2017) ). + date_publication: '2023-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mdsOpt + url_git: '' +MDSPCAShiny: + version: 0.1.0 + title: |- + Interactive Document for Working with Multidimensional Scaling + and Principal Component Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of multidimensional scaling and + principal component analysis using 'rmarkdown' and 'shiny' packages. Runtime examples + are provided in the package function as well as at . + date_publication: '2019-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDSPCAShiny + url_git: '' +mdsr: + version: 0.2.8 + title: Complement to 'Modern Data Science with R' + maintainer: Benjamin S. Baumer + description: |- + A complement to all editions of *Modern Data + Science with R* + (ISBN: 978-0367191498, publisher URL: + ). + This package contains data and code to complete exercises and + reproduce examples from the text. It also facilitates connections + to the SQL database server used in the book. All editions of the book are + supported by this package. + date_publication: '2024-08-19' + bug_reports: https://github.com/mdsr-book/mdsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mdsr + url_git: https://github.com/mdsr-book/mdsr +MDSS: + version: 1.0-1 + title: Modeling Human Dentin Serial Sectioning + maintainer: Takumi Tsutaya + description: |- + Modeling microstructures of + human tooth dentin and + horizontal serial-sectioning of the dentin. + Corresponding age range of dentin serial sections, + that is used in stable isotope analyses, + can be calculated by using this package. + date_publication: '2022-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MDSS + url_git: '' +mdw: + version: 2024.8-1 + title: Maximum Diversity Weighting + maintainer: Youyi Fong + description: Dimension-reduction methods aim at defining a score that maximizes + signal diversity. Three approaches, tree weight, maximum entropy weights, and + maximum variance weights are provided. These methods are described in He and Fong + (2019) . + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mdw + url_git: '' +meanr: + version: 0.1-6 + title: Sentiment Analysis Scorer + maintainer: Drew Schmidt + description: |- + Sentiment analysis is a popular technique in text mining that + attempts to determine the emotional state of some text. We provide a new + implementation of a common method for computing sentiment, whereby words are + scored as positive or negative according to a dictionary lookup. Then the + sum of those scores is returned for the document. We use the 'Hu' and 'Liu' + sentiment dictionary ('Hu' and 'Liu', 2004) + for determining sentiment. The scoring function is 'vectorized' by document, + and scores for multiple documents are computed in parallel via 'OpenMP'. + date_publication: '2023-12-10' + bug_reports: https://github.com/wrathematics/meanr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meanr + url_git: https://github.com/wrathematics/meanr +meanShiftR: + version: '0.56' + title: A Computationally Efficient Mean Shift Implementation + maintainer: Jonathan Lisic + description: |- + Performs mean shift classification using linear and + k-d tree based nearest neighbor implementations for the Gaussian, + Epanechnikov, and biweight product kernels. + date_publication: '2021-09-21' + bug_reports: https://github.com/jlisic/meanShiftR/issues + url: http://meanmean.me/meanshift/r/cran/2016/08/28/meanShiftR.html + url_cran: https://CRAN.R-project.org/package=meanShiftR + url_git: '' +meantables: + version: 0.1.2 + title: Make Quick Descriptive Tables for Continuous Variables + maintainer: Brad Cannell + description: |- + Quickly make tables of descriptive statistics (i.e., counts, + means, confidence intervals) for continuous variables. This + package is designed to work in a Tidyverse pipeline, and consideration + has been given to get results from R to 'Microsoft Word' ® with minimal pain. + date_publication: '2022-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meantables + url_git: '' +measr: + version: 1.0.0 + title: Bayesian Psychometric Measurement Using 'Stan' + maintainer: W. Jake Thompson + description: |- + Estimate diagnostic classification models (also called cognitive + diagnostic models) with 'Stan'. Diagnostic classification models are + confirmatory latent class models, as described by Rupp et al. + (2010, ISBN: 978-1-60623-527-0). Automatically generate 'Stan' code for the + general loglinear cognitive diagnostic diagnostic model proposed by + Henson et al. (2009) and other subtypes that + introduce additional model constraints. Using the generated 'Stan' code, + estimate the model evaluate the model's performance using model fit indices, + information criteria, and reliability metrics. + date_publication: '2024-01-30' + bug_reports: https://github.com/wjakethompson/measr/issues + url: https://measr.info + url_cran: https://CRAN.R-project.org/package=measr + url_git: https://github.com/wjakethompson/measr +measurementProtocol: + version: 0.1.1 + title: Send Data from R to the Measurement Protocol + maintainer: Mark Edmondson + description: |- + Send server-side tracking data from R. + The Measurement Protocol version 2 + + allows sending HTTP tracking events from R code. + date_publication: '2023-03-04' + bug_reports: https://github.com/MarkEdmondson1234/measurementProtocol + url: https://code.markedmondson.me/measurementProtocol/ + url_cran: https://CRAN.R-project.org/package=measurementProtocol + url_git: '' +measurements: + version: 1.5.1 + title: Tools for Units of Measurement + maintainer: Matthew A. Birk + description: |- + Collection of tools to make working with physical measurements + easier. Convert between metric and imperial units, or calculate a dimension's + unknown value from other dimensions' measurements. + date_publication: '2023-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=measurements + url_git: '' +measures: + version: '0.3' + title: Performance Measures for Statistical Learning + maintainer: Philipp Probst + description: Provides the biggest amount of statistical measures in the whole R + world. Includes measures of regression, (multiclass) classification and multilabel + classification. The measures come mainly from the 'mlr' package and were programed + by several 'mlr' developers. + date_publication: '2021-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=measures + url_git: '' +measuRing: + version: '0.5' + title: |- + Detection and Control of Tree-Ring Widths on Scanned Image + Sections + maintainer: Wilson Lara + description: 'Identification of ring borders on scanned image sections from dendrochronological + samples. Processing of image reflectances to produce gray matrices and time series + of smoothed gray values. Luminance data is plotted on segmented images for users + to perform both: visual identification of ring borders or control of automatic + detection. Routines to visually include/exclude ring borders on the R graphical + devices, or automatically detect ring borders using a linear detection algorithm. + This algorithm detects ring borders according to positive/negative extreme values + in the smoothed time-series of gray values. Most of the in-package routines can + be recursively implemented using the multiDetect() function.' + date_publication: '2018-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=measuRing + url_git: '' +meboot: + version: 1.4-9.4 + title: Maximum Entropy Bootstrap for Time Series + maintainer: Fred Viole + description: |- + Maximum entropy density based dependent data bootstrap. + An algorithm is provided to create a population of time series (ensemble) + without assuming stationarity. The reference paper (Vinod, H.D., 2004 ) explains + how the algorithm satisfies the ergodic theorem and the central limit theorem. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meboot + url_git: '' +MECfda: + version: 0.1.0 + title: Scalar-on-Function Regression with Measurement Error Correction + maintainer: Heyang Ji + description: |- + Solve scalar-on-function linear models, + including generalized linear mixed effect model and quantile linear regression model, + and bias correction estimation methods due to measurement error. + Details about the measurement error bias correction methods, see + Luan et al. (2023) , + Tekwe et al. (2022) , + Zhang et al. (2023) , + Tekwe et al. (2019) . + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MECfda + url_git: '' +MEclustnet: + version: 1.2.2 + title: |- + Fit the Mixture of Experts Latent Position Cluster Model to + Network Data + maintainer: Isobel Claire Gormley + description: Functions to facilitate model-based clustering of nodes in a network + in a mixture of experts setting, which incorporates covariate information on the + nodes in the modelling process. Isobel Claire Gormley and Thomas Brendan Murphy + (2010) . + date_publication: '2019-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEclustnet + url_git: '' +meconetcomp: + version: 0.6.1 + title: |- + Compare Microbial Networks of 'trans_network' Class of + 'microeco' Package + maintainer: Chi Liu + description: |- + Compare microbial co-occurrence networks created from 'trans_network' class of 'microeco' package . + This package is the extension of 'trans_network' class of 'microeco' package and especially useful when different networks are constructed and analyzed simultaneously. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meconetcomp + url_git: https://github.com/ChiLiubio/meconetcomp +mecor: + version: 1.0.0 + title: |- + Measurement Error Correction in Linear Models with a Continuous + Outcome + maintainer: Linda Nab + description: Covariate measurement error correction is implemented by means of regression + calibration by Carroll RJ, Ruppert D, Stefanski LA & Crainiceanu CM (2006, ISBN:1584886331), + efficient regression calibration by Spiegelman D, Carroll RJ & Kipnis V (2001) + and maximum + likelihood estimation by Bartlett JW, Stavola DBL & Frost C (2009) . + Outcome measurement error correction is implemented by means of the method of + moments by Buonaccorsi JP (2010, ISBN:1420066560) and efficient method of moments + by Keogh RH, Carroll RJ, Tooze JA, Kirkpatrick SI & Freedman LS (2014) . + Standard error estimation of the corrected estimators is implemented by means + of the Delta method by Rosner B, Spiegelman D & Willett WC (1990) + and Rosner B, Spiegelman D & Willett WC (1992) , + the Fieller method described by Buonaccorsi JP (2010, ISBN:1420066560), and the + Bootstrap by Carroll RJ, Ruppert D, Stefanski LA & Crainiceanu CM (2006, ISBN:1584886331). + date_publication: '2021-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mecor + url_git: https://github.com/LindaNab/mecor +mecoturn: + version: 0.3.0 + title: Decipher Microbial Turnover along a Gradient + maintainer: Chi Liu + description: Two pipelines are provided to study microbial turnover along a gradient, + including the beta diversity and microbial abundance change. The 'betaturn' class + consists of the steps of community dissimilarity matrix generation, matrix conversion, + differential test and visualization. The workflow of 'taxaturn' class includes + the taxonomic abundance calculation, abundance transformation, abundance change + summary, statistical analysis and visualization. Multiple statistical approaches + can contribute to the analysis of microbial turnover. + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mecoturn + url_git: https://github.com/ChiLiubio/mecoturn +MED: + version: 0.1.0 + title: Mediation by Tilted Balancing + maintainer: Gary Chan + description: Nonparametric estimation and inference for natural direct and indirect + effects by Chan, Imai, Yam and Zhang (2016) . + date_publication: '2018-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MED + url_git: '' +MedDataSets: + version: 0.1.0 + title: Comprehensive Medical, Disease, Treatment, and Drug Datasets + maintainer: Renzo Caceres Rossi + description: |- + Provides an extensive collection of datasets related to medicine, + diseases, treatments, drugs, and public health. This package covers topics + such as drug effectiveness, vaccine trials, survival rates, + infectious disease outbreaks, and medical treatments. The included datasets + span various health conditions, including AIDS, cancer, bacterial infections, + and COVID-19, along with information on pharmaceuticals and vaccines. These + datasets are sourced from the R ecosystem and other R packages, remaining + unaltered to ensure data integrity. This package serves as a valuable + resource for researchers, analysts, and healthcare professionals interested + in conducting medical and public health data analysis in R. + date_publication: '2024-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MedDataSets + url_git: https://github.com/lightbluetitan/meddatasets +MedDietCalc: + version: 0.1.1 + title: |- + Multi Calculator to Compute Scores of Adherence to Mediterranean + Diet + maintainer: Miguel Menendez + description: Multi Calculator of different scores to measure adherence to Mediterranean + Diet, to compute them in nutriepidemiological data. Additionally, a sample dataset + of this kind of data is provided, and some other minor tools useful in epidemiological + studies. + date_publication: '2019-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MedDietCalc + url_git: '' +mederrRank: + version: 0.1.0 + title: |- + Bayesian Methods for Identifying the Most Harmful Medication + Errors + maintainer: Sergio Venturini + description: 'Two distinct but related statistical approaches to the problem of + identifying the combinations of medication error characteristics that are more + likely to result in harm are implemented in this package: 1) a Bayesian hierarchical + model with optimal Bayesian ranking on the log odds of harm, and 2) an empirical + Bayes model that estimates the ratio of the observed count of harm to the count + that would be expected if error characteristics and harm were independent. In + addition, for the Bayesian hierarchical model, the package provides functions + to assess the sensitivity of results to different specifications of the random + effects distributions.' + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mederrRank + url_git: '' +MEDesigns: + version: 1.0.0 + title: Mating Environmental Designs + maintainer: Ashutosh Dalal + description: In breeding experiments, mating environmental (ME) designs are very + popular as mating designs are directly implemented in the field environment using + block or row-column designs. Here, three functions are given related to three + new methods which will generate mating diallel cross designs (Hinkelmann and Kempthorne, + 1963) or mating environmental (ME) designs along with design + parameters, C matrix, eigenvalues (EVs), degree of fractionations (DF) and canonical + efficiency factor (CEF). Another one function is added to check the properties + of a given ME diallel cross design. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEDesigns + url_git: '' +medExtractR: + version: 0.4.1 + title: Extraction of Medication Information from Clinical Text + maintainer: Leena Choi + description: 'Function and support for medication and dosing information extraction + from free-text clinical notes. Medication entities for the basic medExtractR implementation + that can be extracted include drug name, strength, dose amount, dose, frequency, + intake time, dose change, and time of last dose. The basic medExtractR is outlined + in Weeks, Beck, McNeer, Williams, Bejan, Denny, Choi (2020) . + The extended medExtractR_tapering implementation is intended to extract dosing + information for more tapering schedules, which are far more complex. The tapering + extension allows for the extraction of additional entities including dispense + amount, refills, dose schedule, time keyword, transition, and preposition.' + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=medExtractR + url_git: '' +medfate: + version: 4.8.0 + title: Mediterranean Forest Simulation + maintainer: Miquel De Cáceres + description: Simulate Mediterranean forest functioning and dynamics using cohort-based + description of vegetation [De Caceres et al. (2015) ; + De Caceres et al. (2021) ]. + date_publication: '2025-01-28' + bug_reports: https://github.com/emf-creaf/medfate/issues + url: https://emf-creaf.github.io/medfate/ + url_cran: https://CRAN.R-project.org/package=medfate + url_git: https://github.com/emf-creaf/medfate +medfateland: + version: 2.5.1 + title: Mediterranean Landscape Simulation + maintainer: Miquel De Cáceres + description: Simulate forest hydrology, forest function and dynamics over landscapes + [De Caceres et al. (2015) ]. Parallelization + is allowed in several simulation functions and simulations may be conducted including + spatial processes such as lateral water transfer and seed dispersal. + date_publication: '2025-01-28' + bug_reports: https://github.com/emf-creaf/medfateland/issues + url: https://emf-creaf.github.io/medfateland/ + url_cran: https://CRAN.R-project.org/package=medfateland + url_git: https://github.com/emf-creaf/medfateland +medflex: + version: 0.6-10 + title: Flexible Mediation Analysis Using Natural Effect Models + maintainer: Johan Steen + description: |- + Run flexible mediation analyses using natural effect models as described in + Lange, Vansteelandt and Bekaert (2012) , + Vansteelandt, Bekaert and Lange (2012) + and Loeys, Moerkerke, De Smet, Buysse, Steen and Vansteelandt (2013) . + date_publication: '2023-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=medflex + url_git: https://github.com/jmpsteen/medflex +mediacloudr: + version: 0.1.0 + title: Wrapper for the 'mediacloud.org' API + maintainer: Dix Jan + description: API wrapper to gather news stories, media information and tags from + the 'mediacloud.org' API, based on a multilevel query . + A personal API key is required. + date_publication: '2019-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mediacloudr + url_git: '' +MediaK: + version: '1.0' + title: Calculate MeDiA_K Distance + maintainer: Zizhuo Ren + description: Calculates MeDiA_K (means Mean Distance Association by K-nearest neighbor) + in order to detect nonlinear associations. + date_publication: '2015-12-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MediaK + url_git: '' +Mediana: + version: 1.0.8 + title: Clinical Trial Simulations + maintainer: Gautier Paux + description: |- + Provides a general framework for clinical trial simulations based + on the Clinical Scenario Evaluation (CSE) approach. The package supports a + broad class of data models (including clinical trials with continuous, binary, + survival-type and count-type endpoints as well as multivariate outcomes that are + based on combinations of different endpoints), analysis strategies and commonly + used evaluation criteria. + date_publication: '2019-05-08' + bug_reports: https://github.com/gpaux/Mediana/issues + url: http://gpaux.github.io/Mediana/ + url_cran: https://CRAN.R-project.org/package=Mediana + url_git: '' +MedianaDesigner: + version: '0.13' + title: Power and Sample Size Calculations for Clinical Trials + maintainer: Alex Dmitrienko + description: |2- + + Efficient simulation-based power and sample size calculations are supported for a + broad class of late-stage clinical trials. The following modules are included in + the package: + Adaptive designs with data-driven sample size or event count re-estimation, + Adaptive designs with data-driven treatment selection, + Adaptive designs with data-driven population selection, + Optimal selection of a futility stopping rule, + Event prediction in event-driven trials, + Adaptive trials with response-adaptive randomization (experimental module), + Traditional trials with multiple objectives (experimental module). + Traditional trials with cluster-randomized designs (experimental module). + date_publication: '2023-08-28' + bug_reports: https://github.com/medianasoft/MedianaDesigner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MedianaDesigner + url_git: https://github.com/medianasoft/MedianaDesigner +mediateP: + version: 0.2.0 + title: Mediation Analysis Based on the Product Method + maintainer: Chao Cheng + description: Functions for calculating the point and interval estimates of the natural + indirect effect (NIE), total effect (TE), and mediation proportion (MP), based + on the product approach. We perform the methods considered in Cheng, Spiegelman, + and Li (2021) Estimating the natural indirect effect and the mediation proportion + via the product method. + date_publication: '2022-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mediateP + url_git: '' +mediation: + version: 4.5.0 + title: Causal Mediation Analysis + maintainer: Teppei Yamamoto + description: We implement parametric and non parametric mediation analysis. This + package performs the methods and suggestions in Imai, Keele and Yamamoto (2010) + , Imai, Keele and Tingley (2010) , + Imai, Tingley and Yamamoto (2013) , Imai + and Yamamoto (2013) and Yamamoto (2013) . + In addition to the estimation of causal mediation effects, the software also allows + researchers to conduct sensitivity analysis for certain parametric models. + date_publication: '2019-10-08' + bug_reports: '' + url: https://imai.princeton.edu/projects/mechanisms.html + url_cran: https://CRAN.R-project.org/package=mediation + url_git: '' +mediationsens: + version: 0.0.3 + title: |- + Simulation-Based Sensitivity Analysis for Causal Mediation + Studies + maintainer: Xu Qin + description: |- + Simulation-based sensitivity analysis for causal mediation studies. It numerically and graphically evaluates the sensitivity of causal mediation analysis results + to the presence of unmeasured pretreatment confounding. The proposed method has primary advantages over existing methods. + First, using an unmeasured pretreatment confounder conditional associations with the treatment, mediator, and outcome as + sensitivity parameters, the method enables users to intuitively assess sensitivity in reference to prior knowledge about the + strength of a potential unmeasured pretreatment confounder. Second, the method accurately reflects the influence of unmeasured + pretreatment confounding on the efficiency of estimation of the causal effects. Third, the method can be implemented in + different causal mediation analysis approaches, including regression-based, simulation-based, and propensity score-based + methods. It is applicable to both randomized experiments and observational studies. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mediationsens + url_git: '' +medicaldata: + version: 0.2.0 + title: Data Package for Medical Datasets + maintainer: Peter Higgins + description: |- + Provides access to well-documented medical datasets for teaching. + Featuring several from the Teaching of Statistics in the Health Sciences + website , a few reconstructed datasets of historical significance in medical + research, some reformatted and extended from existing R packages, + and some data donations. + date_publication: '2021-08-16' + bug_reports: https://github.com/higgi13425/medicaldata/issues + url: https://higgi13425.github.io/medicaldata/ + url_cran: https://CRAN.R-project.org/package=medicaldata + url_git: https://github.com/higgi13425/medicaldata/ +medicalrisk: + version: '1.3' + title: Medical Risk and Comorbidity Tools for ICD-9-CM Data + maintainer: Patrick McCormick + description: |- + Generates risk estimates and comorbidity flags from ICD-9-CM + codes available in administrative medical datasets. The package supports + the Charlson Comorbidity Index, the Elixhauser Comorbidity + classification, the Revised Cardiac Risk Index, and the Risk Stratification + Index. Methods are table-based, fast, and use the 'plyr' package, so + parallelization is possible for large jobs. Also includes a sample of + real ICD-9 data for 100 patients from a publicly available dataset. + date_publication: '2020-02-29' + bug_reports: https://github.com/patrickmdnet/medicalrisk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=medicalrisk + url_git: https://github.com/patrickmdnet/medicalrisk +medicare: + version: 0.2.1 + title: Tools for Obtaining and Cleaning Medicare Public Use Files + maintainer: Robert Gambrel + description: |- + Publicly available data from Medicare frequently requires extensive + initial effort to extract desired variables and merge them; this package + formalizes the techniques I've found work best. More information on the + Medicare program, as well as guidance for the publicly available data this package + targets, can be found on CMS's website covering publicly available data. See . + date_publication: '2017-04-02' + bug_reports: http://www.github.com/robertgambrel/medicare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=medicare + url_git: http://www.github.com/robertgambrel/medicare +meditations: + version: 1.0.1 + title: Prints a Random Quote from Marcus Aurelius' Book Meditations + maintainer: Jacob Kaplan + description: Prints a random quote from Marcus Aurelius' book Meditations. + date_publication: '2019-01-16' + bug_reports: https://github.com/jacobkap/meditations/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meditations + url_git: https://github.com/jacobkap/meditations +MedLEA: + version: 1.0.2 + title: Morphological and Structural Features of Medicinal Leaves + maintainer: Thiyanga S. Talagala + description: Contains a dataset of morphological and structural features of 'Medicinal + LEAves (MedLEA)'. The features of each species is recorded by manually viewing + the medicinal plant repository available at (). + You can also download repository of leaf images of 1099 medicinal plants in Sri + Lanka. + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MedLEA + url_git: '' +medparser: + version: 0.1.0 + title: MedPC Text Parser + maintainer: Olivia Ortelli + description: Parses information from text files with specific utility aimed at pulling + information from Med Associate's (MPC) files. These functions allow for further + analysis of MPC files. + date_publication: '2024-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=medparser + url_git: '' +medrxivr: + version: 0.1.1 + title: Access and Search MedRxiv and BioRxiv Preprint Data + maintainer: Yaoxiang Li + description: |- + An increasingly important source of health-related bibliographic + content are preprints - preliminary versions of research articles that have + yet to undergo peer review. The two preprint repositories most relevant to + health-related sciences are medRxiv and + bioRxiv , both of which are operated by the Cold + Spring Harbor Laboratory. 'medrxivr' provides programmatic access to the + 'Cold Spring Harbour Laboratory (CSHL)' API , + allowing users to easily download medRxiv and bioRxiv preprint metadata + (e.g. title, abstract, publication date, author list, etc) into R. + 'medrxivr' also provides functions to search the downloaded preprint records + using regular expressions and Boolean logic, as well as helper functions + that allow users to export their search results to a .BIB file for easy + import to a reference manager and to download the full-text PDFs of + preprints matching their search criteria. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/medrxivr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=medrxivr + url_git: https://github.com/ropensci/medrxivr +medScan: + version: 1.0.2 + title: Large Scale Single Mediator Hypothesis Testing + maintainer: Michael Kleinsasser + description: |- + A collection of methods for large scale single mediator hypothesis + testing. The six included methods for testing the mediation effect are Sobel's + test, Max P test, joint significance test under the composite null hypothesis, + high dimensional mediation testing, divide-aggregate composite null test, + and Sobel's test under the composite null hypothesis. Du et al (2023) + . + date_publication: '2024-03-06' + bug_reports: https://github.com/umich-cphds/medScan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=medScan + url_git: https://github.com/umich-cphds/medScan +MEDseq: + version: 1.4.1 + title: Mixtures of Exponential-Distance Models with Covariates + maintainer: Keefe Murphy + description: Implements a model-based clustering method for categorical life-course + sequences relying on mixtures of exponential-distance models introduced by Murphy + et al. (2021) . A range of flexible precision parameter + settings corresponding to weighted generalisations of the Hamming distance metric + are considered, along with the potential inclusion of a noise component. Gating + covariates can be supplied in order to relate sequences to baseline characteristics + and sampling weights are also accommodated. The models are fitted using the EM + algorithm and tools for visualising the results are also provided. + date_publication: '2023-12-12' + bug_reports: https://github.com/Keefe-Murphy/MEDseq + url: '' + url_cran: https://CRAN.R-project.org/package=MEDseq + url_git: '' +meerva: + version: 0.2-2 + title: |- + Analysis of Data with Measurement Error Using a Validation + Subsample + maintainer: Walter K Kremers + description: Sometimes data for analysis are obtained using more convenient or less + expensive means yielding "surrogate" variables for what could be obtained more + accurately, albeit with less convenience; or less conveniently or at more expense + yielding "reference" variables, thought of as being measured without error. Analysis + of the surrogate variables measured with error generally yields biased estimates + when the objective is to make inference about the reference variables. Often it + is thought that ignoring the measurement error in surrogate variables only biases + effects toward the null hypothesis, but this need not be the case. Measurement + errors may bias parameter estimates either toward or away from the null hypothesis. If + one has a data set with surrogate variable data from the full sample, and also + reference variable data from a randomly selected subsample, then one can assess + the bias introduced by measurement error in parameter estimation, and use this + information to derive improved estimates based upon all available data. Formulaically + these estimates based upon the reference variables from the validation subsample + combined with the surrogate variables from the whole sample can be interpreted + as starting with the estimate from reference variables in the validation subsample, + and "augmenting" this with additional information from the surrogate variables. + This suggests the term "augmented" estimate. The meerva package calculates + these augmented estimates in the regression setting when there is a randomly selected + subsample with both surrogate and reference variables. Measurement errors may + be differential or non-differential, in any or all predictors (simultaneously) + as well as outcome. The augmented estimates derive, in part, from the multivariate + correlation between regression model parameter estimates from the reference variables + and the surrogate variables, both from the validation subset. Because the validation + subsample is chosen at random any biases imposed by measurement error, whether + non-differential or differential, are reflected in this correlation and these + correlations can be used to derive estimates for the reference variables using + data from the whole sample. The main functions in the package are meerva.fit + which calculates estimates for a dataset, and meerva.sim.block which simulates + multiple datasets as described by the user, and analyzes these datasets, storing + the regression coefficient estimates for inspection. The augmented estimates, + as well as how measurement error may arise in practice, is described in more detail + by Kremers WK (2021) and is an extension of the works by Chen + Y-H, Chen H. (2000) , Chen Y-H. (2002) , + Wang X, Wang Q (2015) and Tong J, Huang J, Chubak + J, et al. (2020) . + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meerva + url_git: '' +meetupapi: + version: 0.1.0 + title: Access 'Meetup' API + maintainer: Zac Davies + description: |- + Allows management of 'Meetup' groups via the . + Provided are a set of functions that enable fetching information of joined meetups, attendance, + and members. This package requires the use of an API key. + date_publication: '2018-02-20' + bug_reports: https://github.com/zacdav/meetupapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meetupapi + url_git: https://github.com/zacdav/meetupapi +mefa: + version: 3.2-9 + title: Multivariate Data Handling in Ecology and Biogeography + maintainer: Peter Solymos + description: A framework package aimed to provide standardized computational environment + for specialist work via object classes to represent the data coded by samples, + taxa and segments (i.e. subpopulations, repeated measures). It supports easy processing + of the data along with cross tabulation and relational data tables for samples + and taxa. An object of class `mefa' is a project specific compendium of the data + and can be easily used in further analyses. Methods are provided for extraction, + aggregation, conversion, plotting, summary and reporting of `mefa' objects. Reports + can be generated in plain text or LaTeX format. Vignette contains worked examples. + date_publication: '2024-05-20' + bug_reports: https://github.com/psolymos/mefa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mefa + url_git: https://github.com/psolymos/mefa +mefa4: + version: 0.3-11 + title: Multivariate Data Handling with S4 Classes and Sparse Matrices + maintainer: Peter Solymos + description: |- + An S4 update of the 'mefa' package + using sparse matrices for enhanced efficiency. + Sparse array-like objects are supported via + lists of sparse matrices. + date_publication: '2024-05-20' + bug_reports: https://github.com/psolymos/mefa4/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mefa4 + url_git: https://github.com/psolymos/mefa4 +mefdind: + version: '0.1' + title: Imports Data from MoE Spain + maintainer: Daniel Caro + description: |2- + + Imports indicator data provided by the Ministry of Education (MoE),Spain. + The data is stored at + Includes functions for reading, downloading, and selecting data + for main series. This package is not sponsored or supported by the MoE Spain. + Importa datos con indicadores del Ministerio de Educación y Formación Profesional (MEFD) de Españá. + Los datos están en + Contiene funciones para leer, descargar, y seleccionar bases de datos de series principales. + Este paquete no es patrocinado o respaldado por el MEFD. + date_publication: '2024-04-01' + bug_reports: https://github.com/eldafani/mefdind/issues + url: https://eldafani.github.io/mefdind/ + url_cran: https://CRAN.R-project.org/package=mefdind + url_git: https://github.com/eldafani/mefdind +MEFM: + version: 0.1.1 + title: Perform MEFM Estimation on Matrix Time Series + maintainer: Zetai Cen + description: To perform main effect matrix factor model (MEFM) estimation for a + given matrix time series as described in Lam and Cen (2024) . + Estimation of traditional matrix factor models is also supported. Supplementary + functions for testing MEFM over factor models are included. + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEFM + url_git: '' +Mega2R: + version: 1.1.0 + title: Accessing and Processing a 'Mega2' Genetic Database + maintainer: Daniel E. Weeks + description: |- + Uses as input genetic data that have been reformatted and + stored in a 'SQLite' database; this database is initially created + by the standalone 'mega2' C++ program (available freely from + ). Loads and manipulates + data frames containing genotype, phenotype, and family + information from the input 'SQLite' database, and decompresses + needed subsets of the genotype data, on the fly, in a memory + efficient manner. We have also created several more functions + that illustrate how to use the data frames as well as perform + useful tasks: these permit one to run the 'pedgene' package to + carry out gene-based association tests on family data using + selected marker subsets, to run the 'SKAT' package to carry out + gene-based association tests using selected marker subsets, to + run the 'famSKATRC' package to carry out gene-based association + tests on families (optionally) and with rare or common variants + using selected marker subsets, to output the 'Mega2R' data as a + VCF file and related files (for phenotype and family data), and + to convert the data frames into CoreArray Genomic Data Structure + (GDS) format. + date_publication: '2023-12-21' + bug_reports: https://groups.google.com/forum/#!forum/mega2-users + url: https://watson.hgen.pitt.edu/mega2/mega2r/ + url_cran: https://CRAN.R-project.org/package=Mega2R + url_git: '' +MEGB: + version: '0.1' + title: Gradient Boosting for Longitudinal Data + maintainer: Oyebayo Ridwan Olaniran + description: |- + Gradient boosting is a powerful statistical learning method known for its ability to model + complex relationships between predictors and outcomes while performing inherent variable selection. + However, traditional gradient boosting methods lack flexibility in handling longitudinal data where + within-subject correlations play a critical role. In this package, we propose a novel approach + Mixed Effect Gradient Boosting ('MEGB'), designed specifically for high-dimensional longitudinal data. + 'MEGB' incorporates a flexible semi-parametric model that embeds random effects within the gradient boosting + framework, allowing it to account for within-individual covariance over time. Additionally, the method + efficiently handles scenarios where the number of predictors greatly exceeds the number of observations + (p>>n) making it particularly suitable for genomics data and other large-scale biomedical studies. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEGB + url_git: '' +MEGENA: + version: 1.3.7 + title: Multiscale Clustering of Geometrical Network + maintainer: Won-Min Song + description: 'Co-Expression Network Analysis by adopting network embedding technique. + Song W.-M., Zhang B. (2015) Multiscale Embedded Gene Co-expression Network Analysis. + PLoS Comput Biol 11(11): e1004574. .' + date_publication: '2018-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEGENA + url_git: https://github.com/songw01/MEGENA +meifly: + version: 0.3.1 + title: Interactive Model Exploration using 'GGobi' + maintainer: Hadley Wickham + description: |- + Exploratory model analysis with . + Fit and graphical explore ensembles of linear models. + date_publication: '2022-05-20' + bug_reports: https://github.com/hadley/meifly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meifly + url_git: https://github.com/hadley/meifly +mekko: + version: 0.1.0 + title: 'Variable Width Bar Charts: Bar Mekko' + maintainer: Eric Rynerson + description: |- + Create variable width bar charts i.e. + "bar mekko" charts to include important quantitative context. + Closely related to mosaic, spine (or spinogram), matrix, + submarine, olympic, Mondrian or product plots and tree maps. + date_publication: '2018-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mekko + url_git: '' +melt: + version: 1.11.4 + title: Multiple Empirical Likelihood Tests + maintainer: Eunseop Kim + description: |- + Performs multiple empirical likelihood tests. It offers an + easy-to-use interface and flexibility in specifying hypotheses and + calibration methods, extending the framework to simultaneous + inferences. The core computational routines are implemented using the + 'Eigen' 'C++' library and 'RcppEigen' interface, with 'OpenMP' for + parallel computation. Details of the testing procedures are provided + in Kim, MacEachern, and Peruggia (2023) + . A companion paper by Kim, + MacEachern, and Peruggia (2024) is + available for further information. This work was supported by the U.S. + National Science Foundation under Grants No. SES-1921523 and + DMS-2015552. + date_publication: '2024-05-17' + bug_reports: https://github.com/ropensci/melt/issues + url: https://docs.ropensci.org/melt/ + url_cran: https://CRAN.R-project.org/package=melt + url_git: https://github.com/ropensci/melt +meltr: + version: 1.0.2 + title: Read Non-Rectangular Text Data + maintainer: Duncan Garmonsway + description: |- + The goal of 'meltr' is to provide a fast and friendly way to + read non-rectangular data, such as ragged forms of csv (comma-separated + values), tsv (tab-separated values), and fwf (fixed-width format) files. + date_publication: '2024-01-09' + bug_reports: https://github.com/r-lib/meltr/issues + url: https://r-lib.github.io/meltr/ + url_cran: https://CRAN.R-project.org/package=meltr + url_git: https://github.com/r-lib/meltr +meltt: + version: 0.4.3 + title: Matching Event Data by Location, Time and Type + maintainer: Karsten Donnay + description: Framework for merging and disambiguating event data based on spatiotemporal + co-occurrence and secondary event characteristics. It can account for intrinsic + "fuzziness" in the coding of events, varying event taxonomies and different geo-precision + codes. + date_publication: '2022-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meltt + url_git: '' +mem: + version: '2.18' + title: The Moving Epidemic Method + maintainer: Jose E. Lozano + description: The Moving Epidemic Method, created by T Vega and JE Lozano (2012, + 2015) , , allows + the weekly assessment of the epidemic and intensity status to help in routine + respiratory infections surveillance in health systems. Allows the comparison of + different epidemic indicators, timing and shape with past epidemics and across + different regions or countries with different surveillance systems. Also, it gives + a measure of the performance of the method in terms of sensitivity and specificity + of the alert week. + date_publication: '2023-06-20' + bug_reports: https://github.com/lozalojo/mem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mem + url_git: https://github.com/lozalojo/mem +memapp: + version: '2.16' + title: The Moving Epidemic Method Web Application + maintainer: Jose E. Lozano + description: The Moving Epidemic Method, created by T Vega and JE Lozano (2012, + 2015) , , allows + the weekly assessment of the epidemic and intensity status to help in routine + respiratory infections surveillance in health systems. Allows the comparison of + different epidemic indicators, timing and shape with past epidemics and across + different regions or countries with different surveillance systems. Also, it gives + a measure of the performance of the method in terms of sensitivity and specificity + of the alert week. 'memapp' is a web application created in the Shiny framework + for the 'mem' R package. + date_publication: '2023-06-20' + bug_reports: https://github.com/lozalojo/memapp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=memapp + url_git: https://github.com/lozalojo/memapp +meme: + version: 0.2.3 + title: Create Meme + maintainer: Guangchuang Yu + description: |- + The word 'Meme' was originated from the book, 'The Selfish Gene', authored by Richard Dawkins (1976). + It is a unit of culture that is passed from one generation to another and correlates to the gene, the unit of physical heredity. + The internet memes are captioned photos that are intended to be funny, ridiculous. + Memes behave like infectious viruses and travel from person to person quickly through social media. + The 'meme' package allows users to make custom memes. + date_publication: '2021-04-23' + bug_reports: https://github.com/GuangchuangYu/meme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meme + url_git: https://github.com/GuangchuangYu/meme/ +memery: + version: 0.6.0 + title: Internet Memes for Data Analysts + maintainer: Matthew Leonawicz + description: |- + Generates internet memes that optionally include a superimposed inset plot and other atypical features, + combining the visual impact of an attention-grabbing meme with graphic results of data analysis. + The package differs from related packages that focus on imitating and reproducing standard memes. + Some packages do this by interfacing with online meme generators whereas others achieve this natively. + This package takes the latter approach. It does not interface with online meme generators or require any authentication with external websites. + It reads images directly from local files or via URL and meme generation is done by the package. + While this is similar to the 'meme' package available on CRAN, it differs in that the focus is on + allowing for non-standard meme layouts and hybrids of memes mixed with graphs. + While this package can be used to make basic memes like an online meme generator would produce, + it caters primarily to hybrid graph-meme plots where the meme presentation can be seen as a backdrop highlighting + foreground graphs of data analysis results. + The package also provides support for an arbitrary number of meme text labels with arbitrary size, position and other attributes + rather than restricting to the standard top and/or bottom text placement. + This is useful for proper aesthetic interleaving of plots of data between meme image backgrounds and overlain text labels. + The package offers a selection of templates for graph placement and appearance with respect to the underlying meme. + Graph templates also permit additional template-specific customization. + Animated gif support is provided but this is optional and functional only if the 'magick' package is installed. + 'magick' is not required unless gif functionality is desired. + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/memery/issues + url: '' + url_cran: https://CRAN.R-project.org/package=memery + url_git: https://github.com/leonawicz/memery +memgene: + version: 1.0.2 + title: |- + Spatial Pattern Detection in Genetic Distance Data Using Moran's + Eigenvector Maps + maintainer: Paul Galpern + description: Can detect relatively weak spatial genetic patterns by using Moran's + Eigenvector Maps (MEM) to extract only the spatial component of genetic variation. Has + applications in landscape genetics where the movement and dispersal of organisms + are studied using neutral genetic variation. + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=memgene + url_git: '' +memify: + version: 0.1.1 + title: Constructing Functions That Keep State + maintainer: Bert Gunter + description: A simple way to construct and maintain functions that keep state i.e. + remember their argument lists. This can be useful when one needs to repeatedly + invoke the same function with only a small number of argument changes at each + invocation. + date_publication: '2021-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=memify + url_git: '' +memisc: + version: 0.99.31.8.2 + title: Management of Survey Data and Presentation of Analysis Results + maintainer: Martin Elff + description: |- + An infrastructure for the management of survey data including + value labels, definable missing values, recoding of variables, + production of code books, and import of (subsets of) 'SPSS' and + 'Stata' files is provided. Further, the package allows to produce + tables and data frames of arbitrary descriptive statistics and + (almost) publication-ready tables of regression model + estimates, which can be exported to 'LaTeX' and HTML. + date_publication: '2025-02-23' + bug_reports: https://github.com/melff/memisc/issues + url: https://melff.github.io/memisc/ + url_cran: https://CRAN.R-project.org/package=memisc + url_git: https://github.com/melff/memisc/ +memo: + version: 1.1.1 + title: In-Memory Caching of Repeated Computations (Memoization) + maintainer: Peter Meilstrup + description: |- + A simple in-memory, LRU cache that can be wrapped + around any function to memoize it. The cache is keyed on a hash of the input data (using 'digest') or on pointer equivalence. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=memo + url_git: '' +memochange: + version: 1.1.2 + title: |- + Testing for Structural Breaks under Long Memory and Testing for + Changes in Persistence + maintainer: Kai Wenger + description: |- + Test procedures and break point estimators for persistent processes that exhibit structural breaks in mean or in persistence. + On the one hand the package contains the most popular approaches for testing whether a time series exhibits a break in persistence from I(0) to I(1) or vice versa, such as those of Busetti and Taylor (2004) and Leybourne, Kim, and Taylor (2007). + The approach by Martins and Rodrigues (2014), which allows to detect changes from I(d1) to I(d2) with d1 and d2 being non-integers, is included as well. + In case the tests reject the null of constant persistence, various breakpoint estimators are available to detect the point of the break as well as the order of integration in the two regimes. + On the other hand the package contains the most popular approaches to test for a change-in-mean of a long-memory time series, which were recently reviewed by Wenger, Leschinski, and Sibbertsen (2018). + These include memory robust versions of the CUSUM, sup-Wald, and Wilcoxon type tests. The tests either utilize consistent estimates of the long-run variance or a self normalization approach in their test statistics. + Betken (2016) + Busetti and Taylor (2004) + Dehling, Rooch and Taqqu (2012) + Harvey, Leybourne and Taylor (2006) + Horvath and Kokoszka (1997) + Hualde and Iacone (2017) + Iacone, Leybourne and Taylor (2014) + Leybourne, Kim, Smith, and Newbold (2003) + Leybourne and Taylor (2004) + Leybourne, Kim, and Taylor (2007): + Martins and Rodrigues (2014) + Shao (2011) + Sibbertsen and Kruse (2009) + Wang (2008) + Wenger, Leschinski and Sibbertsen (2018) . + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=memochange + url_git: '' +memofunc: + version: 1.0.2 + title: Function Memoization + maintainer: Roy Wetherall + description: A simple way to memoize function results to improve performance by + eliminating unnecessary computation or data retrieval activities. + date_publication: '2021-02-22' + bug_reports: https://github.com/rwetherall/memofunc/issues + url: https://rwetherall.github.io/memofunc/ + url_cran: https://CRAN.R-project.org/package=memofunc + url_git: https://github.com/rwetherall/memofunc +memoiR: + version: 1.3-0 + title: R Markdown and Bookdown Templates to Publish Documents + maintainer: Eric Marcon + description: |- + Producing high-quality documents suitable for publication directly from R is made possible by the R Markdown ecosystem. + 'memoiR' makes it easy. + It provides templates to knit memoirs, articles and slideshows with helpers to publish the documents on GitHub Pages and activate continuous integration. + date_publication: '2025-01-07' + bug_reports: https://github.com/EricMarcon/memoiR/issues/ + url: https://ericmarcon.github.io/memoiR/ + url_cran: https://CRAN.R-project.org/package=memoiR + url_git: https://github.com/EricMarcon/memoiR/ +memoise: + version: 2.0.1 + title: '''Memoisation'' of Functions' + maintainer: Winston Chang + description: |- + Cache the results of a function so that when you + call it again with the same arguments it returns the previously computed + value. + date_publication: '2021-11-26' + bug_reports: https://github.com/r-lib/memoise/issues + url: https://memoise.r-lib.org + url_cran: https://CRAN.R-project.org/package=memoise + url_git: https://github.com/r-lib/memoise +memor: + version: 0.2.3 + title: A 'rmarkdown' Template that Can be Highly Customized + maintainer: Hao Zhu + description: |- + A 'rmarkdown' template that supports company logo, contact info, + watermarks and more. Currently restricted to 'Latex'/'Markdown'; a similar + 'HTML' theme will be added in the future. + date_publication: '2021-01-19' + bug_reports: https://github.com/hebrewseniorlife/memor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=memor + url_git: https://github.com/hebrewseniorlife/memor +memoria: + version: 1.0.0 + title: |- + Quantifying Ecological Memory in Palaeoecological Datasets and + Other Long Time-Series + maintainer: Blas M. Benito + description: Tools to quantify ecological memory in long time-series with Random + Forest models (Breiman 2001 ) fitted with the 'ranger' + library (Wright and Ziegler 2017 ). Particularly oriented + to palaeoecological datasets and simulated pollen curves produced by the 'virtualPollen' + package, but also applicable to other long time-series involving a set of environmental + drivers and a biotic response. + date_publication: '2019-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=memoria + url_git: '' +MEMSS: + version: 0.9-3 + title: Data Sets from Mixed-Effects Models in S + maintainer: Steve Walker + description: |- + Data sets and sample analyses from Pinheiro and Bates, + "Mixed-effects Models in S and S-PLUS" (Springer, 2000). + date_publication: '2019-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEMSS + url_git: '' +memuse: + version: 4.2-3 + title: Memory Estimation Utilities + maintainer: Drew Schmidt + description: |- + How much ram do you need to store a 100,000 by 100,000 matrix? + How much ram is your current R session using? How much ram do you even have? + Learn the scintillating answer to these and many more such questions with + the 'memuse' package. + date_publication: '2023-01-24' + bug_reports: https://github.com/shinra-dev/memuse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=memuse + url_git: https://github.com/shinra-dev/memuse +MendelianRandomization: + version: 0.10.0 + title: Mendelian Randomization Package + maintainer: Stephen Burgess + description: |- + Encodes several methods for performing Mendelian randomization + analyses with summarized data. Summarized data on genetic associations with the + exposure and with the outcome can be obtained from large consortia. These data + can be used for obtaining causal estimates using instrumental variable methods. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MendelianRandomization + url_git: '' +MEPDF: + version: '3.0' + title: |- + Creation of Empirical Density Functions Based on Multivariate + Data + maintainer: Martin Wiegand + description: |- + Based on the input data an n-dimensional cube with sub cells of user specified side length is created. + The number of sample points which fall in each sub cube is counted, and with the cell volume and overall sample + size an empirical probability can be computed. A number of cubes of higher resolution can be superimposed. The + basic method stems from J.L. Bentley in "Multidimensional Divide and Conquer". + J. L. Bentley (1980) . + Furthermore a simple kernel density estimation method is made available, as well as an expansion of Bentleys + method, which offers a kernel approach for the grid method. + date_publication: '2018-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MEPDF + url_git: '' +Mercator: + version: 1.1.5 + title: Clustering and Visualizing Distance Matrices + maintainer: Kevin R. Coombes + description: |- + Defines the classes used to explore, cluster and + visualize distance matrices, especially those arising from binary + data. See Abrams and colleagues, 2021, . + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mercator + url_git: http://oompa.r-forge.r-project.org/ +merDeriv: + version: 0.2-4 + title: Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models + maintainer: Ting Wang + description: Compute case-wise and cluster-wise derivative for mixed effects models + with respect to fixed effects parameter, random effect (co)variances, and residual + variance. This material is partially based on work supported by the National Science + Foundation under Grant Number 1460719. + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=merDeriv + url_git: https://github.com/nctingwang/merDeriv +mergedblocks: + version: 1.1.1 + title: Merged Block Randomization + maintainer: Stephanie van der Pas + description: Package to carry out merged block randomization (Van der Pas (2019), + ), a restricted randomization method designed for + small clinical trials (at most 100 subjects) or trials with small strata, for + example in multicentre trials. It can be used for more than two groups or unequal + randomization ratios. + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mergedblocks + url_git: '' +mergen: + version: 0.2.1 + title: |- + AI-Driven Code Generation, Explanation and Execution for Data + Analysis + maintainer: Altuna Akalin + description: Employing artificial intelligence to convert data analysis questions + into executable code, explanations, and algorithms. The self-correction feature + ensures the generated code is optimized for performance and accuracy. 'mergen' + features a user-friendly chat interface, enabling users to interact with the AI + agent and extract valuable insights from their data effortlessly. + date_publication: '2024-06-27' + bug_reports: https://github.com/BIMSBbioinfo/mergen/issues + url: https://bioinformatics.mdc-berlin.de/mergen/ + url_cran: https://CRAN.R-project.org/package=mergen + url_git: https://github.com/BIMSBbioinfo/mergen +mergenstudio: + version: '1.0' + title: |- + 'Mergen' Studio: An 'RStudio' Addin Wrapper for the 'Mergen' + Package + maintainer: Jacqueline Jansen + description: An 'RStudio' Addin wrapper for the 'mergen' package. This package employs + artificial intelligence to convert data analysis questions into executable code, + explanations, and algorithms. This package makes it easier to use Large Language + Models in your development environment by providing a chat-like interface, while + also allowing you to inspect and execute the returned code. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mergenstudio + url_git: '' +mergeTrees: + version: 0.1.3 + title: Aggregating Trees + maintainer: Audrey Hulot + description: |- + Aggregates a set of trees with the same leaves to create a consensus tree. The trees are typically + obtained via hierarchical clustering, hence the hclust format is used to encode both the aggregated trees and the final + consensus tree. The method is exact and proven to be O(nqlog(n)), n being the individuals and q being the number of trees to aggregate. + date_publication: '2019-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mergeTrees + url_git: '' +mergingTools: + version: 1.0.1 + title: |- + Tools to Merge Hardware Event Monitors (HEMs) Coming from + Separate Subexperiments into One Single Dataframe + maintainer: Sergi Vilardell + description: 'Implementation of two tools to merge Hardware Event Monitors (HEMs) + from different subexperiments. Hardware Reading and Merging (HRM), which uses + order statistics to merge; and MUlti-Correlation HEM (MUCH) which merges using + a multivariate normal distribution. The reference paper for HRM is: S. Vilardell, + I. Serra, R. Santalla, E. Mezzetti, J. Abella and F. J. Cazorla, "HRM: Merging + Hardware Event Monitors for Improved Timing Analysis of Complex MPSoCs," in IEEE + Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. + 39, no. 11, pp. 3662-3673, Nov. 2020, . For MUCH: + S. Vilardell, I. Serra, E. Mezzetti, J. Abella, and F. J. Cazorla. 2021. "MUCH: + exploiting pairwise hardware event monitor correlations for improved timing analysis + of complex MPSoCs". In Proceedings of the 36th Annual ACM Symposium on Applied + Computing (SAC ''21). Association for Computing Machinery. . + This work has been supported by the European Research Council (ERC) under the + European Union''s Horizon 2020 research and innovation programme (grant agreement + No. 772773).' + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mergingTools + url_git: '' +mermboost: + version: 0.1.0 + title: Gradient Boosting for Generalized Additive Mixed Models + maintainer: Lars Knieper + description: |- + Provides a novel framework to estimate mixed models + via gradient boosting. The implemented functions are based on 'mboost' and 'lme4'. + Hence, the family range is predetermined by 'lme4'. A correction mechanism + for cluster-constant covariates is implemented as well as an estimation of random + effects' covariance. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mermboost + url_git: '' +MERO: + version: 0.1.2 + title: |- + Performing Monte Carlo Expectation Maximization Random Forest + Imputation for Biological Data + maintainer: Mohamed Soudy + description: Perform missing value imputation for biological data using the random + forest algorithm, the imputation aim to keep the original mean and standard deviation + consistent after imputation. + date_publication: '2023-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MERO + url_git: '' +merror: + version: '3.0' + title: Accuracy and Precision of Measurements + maintainer: Richard A. Bilonick + description: |- + N>=3 methods are used to measure each of n items. + The data are used to estimate simultaneously systematic error (bias) + and random error (imprecision). Observed measurements for each method + or device are assumed to be linear functions of the unknown true values + and the errors are assumed normally distributed. Pairwise calibration + curves and plots can be easily generated. Unlike the 'ncb.od' function, + the 'omx' function builds a one-factor measurement error model using 'OpenMx' + and allows missing values, uses full information maximum likelihood to + estimate parameters, and provides both likelihood-based and bootstrapped + confidence intervals for all parameters, in addition to Wald-type intervals. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=merror + url_git: '' +merTools: + version: 0.6.2 + title: Tools for Analyzing Mixed Effect Regression Models + maintainer: Jared E. Knowles + description: |- + Provides methods for extracting results from mixed-effect model + objects fit with the 'lme4' package. Allows construction of prediction intervals + efficiently from large scale linear and generalized linear mixed-effects models. + This method draws from the simulation framework used in the Gelman and Hill (2007) textbook: + Data Analysis Using Regression and Multilevel/Hierarchical Models. + date_publication: '2024-02-08' + bug_reports: https://github.com/jknowles/merTools + url: '' + url_cran: https://CRAN.R-project.org/package=merTools + url_git: '' +meshed: + version: 0.2.3 + title: Bayesian Regression with Meshed Gaussian Processes + maintainer: Michele Peruzzi + description: Fits Bayesian regression models based on latent Meshed Gaussian Processes + (MGP) as described in Peruzzi, Banerjee, Finley (2020) , + Peruzzi, Banerjee, Dunson, and Finley (2021) , Peruzzi and Dunson + (2022) . Funded by ERC grant 856506 and NIH grant R01ES028804. + date_publication: '2022-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meshed + url_git: '' +MESS: + version: 0.5.12 + title: Miscellaneous Esoteric Statistical Scripts + maintainer: Claus Thorn Ekstrøm + description: |- + A mixed collection of useful and semi-useful diverse + statistical functions, some of which may even be referenced in + The R Primer book. + date_publication: '2023-08-20' + bug_reports: https://github.com/ekstroem/MESS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MESS + url_git: https://github.com/ekstroem/MESS +messaging: + version: 0.1.0 + title: Conveniently Issue Messages, Warnings, and Errors + maintainer: Richard Iannone + description: |- + Provides tools for creating and issuing nicely-formatted + text within R diagnostic messages and those messages given during + warnings and errors. The formatting of the messages can be + customized using templating features. Issues with singular and + plural forms can be handled through specialized syntax. + date_publication: '2018-05-27' + bug_reports: https://github.com/rich-iannone/messaging/issues + url: '' + url_cran: https://CRAN.R-project.org/package=messaging + url_git: https://github.com/rich-iannone/messaging +messi: + version: 0.1.2 + title: Mediation with External Summary Statistic Information + maintainer: Michael Kleinsasser + description: |- + Fits the MESSI, hard constraint, and unconstrained models in Boss + et al. (2023) for mediation analyses with external + summary-level information on the total effect. + date_publication: '2025-01-09' + bug_reports: https://github.com/umich-cphds/messi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=messi + url_git: https://github.com/umich-cphds/messi +messy: + version: 0.1.0 + title: Create Messy Data from Clean Data Frames + maintainer: Nicola Rennie + description: |- + For the purposes of teaching, it is often desirable to show + examples of working with messy data and how to clean it. This R package + creates messy data from clean, tidy data frames so that students have a + clean example to work towards. + date_publication: '2024-12-03' + bug_reports: https://github.com/nrennie/messy/issues + url: https://nrennie.rbind.io/messy/ + url_cran: https://CRAN.R-project.org/package=messy + url_git: https://github.com/nrennie/messy +messy.cats: + version: '1.0' + title: Employs String Distance Tools to Help Clean Categorical Data + maintainer: Harrison Karp + description: Matching with string distance has never been easier! 'messy.cats' contains + various functions that employ string distance tools in order to make data management + easier for users working with categorical data. Categorical data, especially user + inputted categorical data that often tends to be plagued by typos, can be difficult + to work with. 'messy.cats' aims to provide functions that make cleaning categorical + data simple and easy. + date_publication: '2022-11-30' + bug_reports: https://github.com/hkarp1/messy.cats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=messy.cats + url_git: '' +messydates: + version: 0.4.1 + title: A Flexible Class for Messy Dates + maintainer: James Hollway + description: |- + Contains a set of tools for constructing and coercing + into and from the "mdate" class. + This date class implements ISO 8601-2:2019(E) and + allows regular dates to be annotated + to express unspecified date components, + approximate or uncertain date components, + date ranges, and sets of dates. + This is useful for describing and analysing temporal information, + whether historical or recent, where date precision may vary. + date_publication: '2024-04-19' + bug_reports: https://github.com/globalgov/messydates/issues + url: https://globalgov.github.io/messydates/ + url_cran: https://CRAN.R-project.org/package=messydates + url_git: https://github.com/globalgov/messydates +Mestim: + version: 0.2.1 + title: |- + Computes the Variance-Covariance Matrix of Multidimensional + Parameters Using M-Estimation + maintainer: François Grolleau + description: Provides a flexible framework for estimating the variance-covariance + matrix of estimated parameters. Estimation relies on unbiased estimating functions + to compute the empirical sandwich variance. (i.e., M-estimation in the vein of + Tsiatis et al. (2019) . + date_publication: '2022-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mestim + url_git: '' +meta: + version: 8.0-2 + title: General Package for Meta-Analysis + maintainer: Guido Schwarzer + description: |- + User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker , "Meta-Analysis with R" (2015): + - common effect and random effects meta-analysis; + - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); + - three-level meta-analysis model; + - generalised linear mixed model; + - logistic regression with penalised likelihood for rare events; + - Hartung-Knapp method for random effects model; + - Kenward-Roger method for random effects model; + - prediction interval; + - statistical tests for funnel plot asymmetry; + - trim-and-fill method to evaluate bias in meta-analysis; + - meta-regression; + - cumulative meta-analysis and leave-one-out meta-analysis; + - import data from 'RevMan 5'; + - produce forest plot summarising several (subgroup) meta-analyses. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meta + url_git: https://github.com/guido-s/meta/https://link.springer.com/book/10.1007/978-3-319-21416-0 +meta.shrinkage: + version: 0.1.4 + title: Meta-Analyses for Simultaneously Estimating Individual Means + maintainer: Nanami Taketomi + description: |- + Implement meta-analyses for simultaneously estimating individual means with shrinkage, + isotonic regression and pretests. Include our original implementation of the isotonic regression via the pool-adjacent-violators algorithm (PAVA) algorithm. + For the pretest estimator, the confidence interval for individual means are provided. + Methodologies were published in + Taketomi et al. (2021) , Taketomi et al. (2022) , + Taketomi et al. (2023-) (under review). + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meta.shrinkage + url_git: '' +meta4diag: + version: 2.1.1 + title: Meta-Analysis for Diagnostic Test Studies + maintainer: Jingyi Guo + description: 'Bayesian inference analysis for bivariate meta-analysis of diagnostic + test studies using integrated nested Laplace approximation with INLA. A purpose + built graphic user interface is available. The installation of R package INLA + is compulsory for successful usage. The INLA package can be obtained from . + We recommend the testing version, which can be downloaded by running: install.packages("INLA", + repos=c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/testing"), + dep=TRUE).' + date_publication: '2021-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meta4diag + url_git: '' +MetaAnalyser: + version: 0.2.1 + title: |- + An Interactive Visualisation of Meta-Analysis as a Physical + Weighing Machine + maintainer: Christopher Jackson + description: |- + An interactive application to visualise meta-analysis data as a + physical weighing machine. The interface is based on the Shiny web application + framework, though can be run locally and with the user's own data. + date_publication: '2016-10-13' + bug_reports: https://github.com/chjackson/MetaAnalyser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetaAnalyser + url_git: https://github.com/chjackson/MetaAnalyser +metabias: + version: 0.1.1 + title: Meta-Analysis for Within-Study and/or Across-Study Biases + maintainer: Peter Solymos + description: |- + Provides common components (classes, methods, documentation) for + packages that conduct meta-analytic corrections and sensitivity analyses + for within-study and/or across-study biases in meta-analysis. See the packages + 'PublicationBias', 'phacking', and 'multibiasmeta'. These package implement + methods described in, respectively: Mathur & VanderWeele (2020) + ; Mathur (2022) ; + Mathur (2022) . + date_publication: '2023-08-18' + bug_reports: https://github.com/mathurlabstanford/metabias/issues + url: https://mathurlabstanford.github.io/metabias/ + url_cran: https://CRAN.R-project.org/package=metabias + url_git: https://github.com/mathurlabstanford/metabias +metaBLUE: + version: 1.0.0 + title: |- + BLUE for Combining Location and Scale Information in a + Meta-Analysis + maintainer: Xin Yang + description: |- + The sample mean and standard deviation are two commonly used statistics in meta-analyses, + but some trials use other summary statistics such as the median and quartiles to report the results. + Therefore, researchers need to transform those information back to the sample mean and + standard deviation. This package implemented sample mean estimators by Luo et al. (2016) , sample standard deviation estimators by Wan et al. (2014) , and the best linear unbiased estimators (BLUEs) of location and scale parameters by Yang et al. (2018, submitted) based on sample quantiles derived summaries in a meta-analysis. + date_publication: '2018-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaBLUE + url_git: '' +metaBMA: + version: 0.6.9 + title: |- + Bayesian Model Averaging for Random and Fixed Effects + Meta-Analysis + maintainer: Daniel W. Heck + description: |- + Computes the posterior model probabilities for standard meta-analysis models + (null model vs. alternative model assuming either fixed- or random-effects, respectively). + These posterior probabilities are used to estimate the overall mean effect size + as the weighted average of the mean effect size estimates of the random- and + fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & + Wagenmakers (2017, ). The user can define + a wide range of non-informative or informative priors for the mean effect size + and the heterogeneity coefficient. Moreover, using pre-compiled Stan models, + meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS) + priors can be fitted and tested. This allows to compute Bayes factors and + perform Bayesian model averaging across random- and fixed-effects meta-analysis + with and without moderators. For a primer on Bayesian model-averaged meta-analysis, + see Gronau, Heck, Berkhout, Haaf, & Wagenmakers (2021, ). + date_publication: '2023-09-13' + bug_reports: '' + url: https://danheck.github.io/metaBMA/ + url_cran: https://CRAN.R-project.org/package=metaBMA + url_git: https://github.com/danheck/metaBMA +metaboData: + version: 0.6.3 + title: Example Metabolomics Data Sets + maintainer: Jasen Finch + description: |- + Data sets from a variety of biological sample matrices, + analysed using a number of mass spectrometry based metabolomic analytical techniques. + The example data sets are stored remotely using GitHub releases + which can be accessed from R using the package. + The package also includes the 'abr1' FIE-MS data set from the 'FIEmspro' package . + date_publication: '2022-02-15' + bug_reports: https://github.com/aberHRML/metaboData/issues + url: https://aberhrml.github.io/metaboData/ + url_cran: https://CRAN.R-project.org/package=metaboData + url_git: '' +metabodecon: + version: 1.2.6 + title: Deconvolution and Alignment of 1d NMR Spectra + maintainer: Tobias Schmidt + description: |- + A framework for deconvolution, alignment and postprocessing + of 1-dimensional (1d) nuclear magnetic resonance (NMR) spectra, resulting in + a data matrix of aligned signal integrals. The deconvolution part uses the + algorithm described in Koh et al. (2009) . + The alignment part is based on functions from the 'speaq' package, described + in Beirnaert et al. (2018) and Vu et al. + (2011) . A detailed description and evaluation + of an early version of the package, 'MetaboDecon1D v0.2.2', can be found in + Haeckl et al. (2021) . + date_publication: '2025-01-21' + bug_reports: https://github.com/spang-lab/metabodecon/issues + url: https://spang-lab.github.io/metabodecon/ + url_cran: https://CRAN.R-project.org/package=metabodecon + url_git: https://github.com/spang-lab/metabodecon/ +MetabolAnalyze: + version: '1.3' + title: Probabilistic latent variable models for metabolomic data. + maintainer: Claire Gormley + description: Fits probabilistic principal components analysis,probabilistic + principal components and covariates analysis andmixtures of probabilistic + principal components models tometabolomic spectral data. + date_publication: '2012-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetabolAnalyze + url_git: '' +metabolic: + version: 0.1.2 + title: Datasets and Functions for Reproducing Meta-Analyses + maintainer: Felipe Mattioni Maturana + description: |- + Dataset and functions from the meta-analysis published in Medicine & Science in Sports & Exercise. + It contains all the data and functions to reproduce the analysis. + "Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: A Meta-analysis". + Felipe Mattioni Maturana, Peter Martus, Stephan Zipfel, Andreas M Nieß (2020) . + date_publication: '2023-10-10' + bug_reports: https://github.com/fmmattioni/metabolic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metabolic + url_git: https://github.com/fmmattioni/metabolic +MetabolicSurv: + version: 1.1.2 + title: |- + A Biomarker Validation Approach for Classification and + Predicting Survival Using Metabolomics Signature + maintainer: Olajumoke Evangelina Owokotomo + description: |- + An approach to identifies metabolic biomarker signature for metabolic data by discovering predictive metabolite for predicting survival and classifying patients into risk groups. + Classifiers are constructed as a linear combination of predictive/important metabolites, prognostic factors and treatment effects if necessary. + Several methods were implemented to reduce the metabolomics matrix such as the principle component analysis of Wold Svante et al. (1987) , + the LASSO method by Robert Tibshirani (1998) , the + elastic net approach by Hui Zou and Trevor Hastie (2005) . + Sensitivity analysis on the quantile used for the classification can also be accessed to check the deviation of the classification group based on the quantile specified. + Large scale cross validation can be performed in order to investigate the mostly selected predictive metabolites and for internal validation. During the evaluation process, validation is accessed using the hazard ratios (HR) distribution of the test set and inference is mainly based on resampling and permutations technique. + date_publication: '2021-06-11' + bug_reports: https://github.com/OlajumokeEvangelina/MetabolicSurv/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=MetabolicSurv + url_git: https://github.com/OlajumokeEvangelina/MetabolicSurv +MetabolicSyndrome: + version: 0.1.3 + title: Diagnosis of Metabolic Syndrome + maintainer: Jagadish Ramasamy + description: The modified Adult Treatment Panel -III guidelines (ATP-III) proposed + by American Heart Association (AHA) and National Heart, Lung and Blood Institute + (NHLBI) are used widely for the clinical diagnosis of Metabolic Syndrome. The + AHA-NHLBI criteria advise using parameters such as waist circumference (WC), systolic + blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), + triglycerides (TG) and high-density lipoprotein cholesterol (HDLC) for diagnosis + of metabolic syndrome. Each parameter has to be interpreted based on the proposed + cut-offs, making the diagnosis slightly complex and error-prone. This package + is developed by incorporating the modified ATP-III guidelines, and it will aid + in the easy and quick diagnosis of metabolic syndrome in busy healthcare settings + and also for research purposes. The modified ATP-III-AHA-NHLBI criteria for the + diagnosis is described by Grundy et al ., (2005) . + date_publication: '2023-08-18' + bug_reports: https://github.com/jagadishramasamy/metsynd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetabolicSyndrome + url_git: https://github.com/jagadishramasamy/metsynd +MetabolomicsBasics: + version: 1.4.5 + title: Basic Functions to Investigate Metabolomics Data Matrices + maintainer: Jan Lisec + description: A set of functions to investigate raw data from (metabol)omics experiments + intended to be used on a raw data matrix, i.e. following peak picking and signal + deconvolution. Functions can be used to normalize data, detect biomarkers and + perform sample classification. A detailed description of best practice usage may + be found in the publication . + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetabolomicsBasics + url_git: https://github.com/janlisec/MetabolomicsBasics +MetaboQC: + version: '1.1' + title: Normalize Metabolomic Data using QC Signal + maintainer: Monica Calderon-Santiago + description: |- + Takes QC signal for each day and normalize metabolomic + data that has been acquired in a certain period of time. At least + three QC per day are required. + date_publication: '2021-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaboQC + url_git: '' +metabup: + version: 0.1.3 + title: Bayesian Meta-Analysis Using Basic Uncertain Pooling + maintainer: Dexter Cahoy + description: Contains functions that allow Bayesian meta-analysis (1) with binomial + data, counts(y) and total counts (n) or, (2) with user-supplied point estimates + and associated variances. Case (1) provides an analysis based on the logit transformation + of the sample proportion. This methodology is also appropriate for combining data + from sample surveys and related sources. The functions can calculate the corresponding + similarity matrix. More details can be found in Cahoy and Sedransk (2023), Cahoy + and Sedransk (2022) , Evans and Sedransk (2001) + , and Malec and Sedransk (1992) . + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metabup + url_git: '' +metacart: + version: 2.0-3 + title: |- + Meta-CART: A Flexible Approach to Identify Moderators in + Meta-Analysis + maintainer: Juan Claramunt + description: Meta-CART integrates classification and regression trees (CART) into + meta-analysis. Meta-CART is a flexible approach to identify interaction effects + between moderators in meta-analysis. The method is described in Dusseldorp et + al. (2014) and Li et al. (2017) . + date_publication: '2020-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metacart + url_git: '' +metaCluster: + version: 0.1.1 + title: Metagenomic Clustering + maintainer: Dipro Sinha + description: Clustering in metagenomics is the process of grouping of microbial + contigs in species specific bins. This package contains functions that extract + genomic features from metagenome data, find the number of clusters for that given + data and find the best clustering algorithm for binning. + date_publication: '2024-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaCluster + url_git: '' +metacoder: + version: 0.3.8 + title: |- + Tools for Parsing, Manipulating, and Graphing Taxonomic + Abundance Data + maintainer: Zachary Foster + description: |- + Reads, plots, and manipulates large + taxonomic data sets, like those generated from modern high-throughput + sequencing, such as metabarcoding (i.e. amplification metagenomics, 16S + metagenomics, etc). It provides a tree-based visualization called "heat + trees" used to depict statistics for every taxon in a taxonomy using + color and size. It also provides various functions to do common tasks in + microbiome bioinformatics on data in the 'taxmap' format defined by the + 'taxa' package. The 'metacoder' package is described in the publication + by Foster et al. (2017) . + date_publication: '2025-02-11' + bug_reports: https://github.com/grunwaldlab/metacoder/issues + url: https://grunwaldlab.github.io/metacoder_documentation/ + url_cran: https://CRAN.R-project.org/package=metacoder + url_git: '' +metacom: + version: 1.5.3 + title: Analysis of the 'Elements of Metacommunity Structure' + maintainer: Tad Dallas + description: |- + Functions to analyze coherence, boundary clumping, and turnover + following the pattern-based metacommunity analysis of Leibold and Mikkelson + 2002 . The package also includes + functions to visualize ecological networks, and to calculate modularity + as a replacement to boundary clumping. + date_publication: '2020-03-23' + bug_reports: https://github.com/taddallas/metacom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metacom + url_git: '' +MetaComp: + version: 1.1.2 + title: EDGE Taxonomy Assignments Visualization + maintainer: Pavel Senin + description: |- + Implements routines for metagenome sample taxonomy assignments collection, + aggregation, and visualization. Accepts the EDGE-formatted output from GOTTCHA/GOTTCHA2, + BWA, Kraken, MetaPhlAn, DIAMOND, and Pangia. Produces SVG and PDF heatmap-like plots + comparing taxa abundances across projects. + date_publication: '2018-06-18' + bug_reports: https://github.com/seninp-bioinfo/MetaComp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetaComp + url_git: https://github.com/seninp-bioinfo/MetaComp +metaconfoundr: + version: 0.1.2 + title: Visualize 'Confounder' Control in Meta-Analyses + maintainer: Malcolm Barrett + description: |- + Visualize 'confounder' control in meta-analysis. + 'metaconfoundr' is an approach to evaluating bias in studies used in + meta-analyses based on the causal inference framework. Study groups + create a causal diagram displaying their assumptions about the + scientific question. From this, they develop a list of important + 'confounders'. Then, they evaluate whether studies controlled for + these variables well. 'metaconfoundr' is a toolkit to facilitate this + process and visualize the results as heat maps, traffic light plots, + and more. + date_publication: '2023-01-17' + bug_reports: https://github.com/malcolmbarrett/metaconfoundr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metaconfoundr + url_git: https://github.com/malcolmbarrett/metaconfoundr +metaConvert: + version: 1.0.2 + title: |- + An Automatic Suite for Estimation of Various Effect Size + Measures + maintainer: Corentin J. Gosling + description: |- + Automatically estimate 11 effect size measures from a well-formatted dataset. Various other functions can help, for example, removing dependency between several effect sizes, or identifying differences between two datasets. + This package is mainly designed to assist in conducting a systematic review with a meta-analysis but can be useful to any researcher interested in estimating an effect size. + date_publication: '2024-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaConvert + url_git: '' +metacore: + version: 0.1.3 + title: |- + A Centralized Metadata Object Focus on Clinical Trial Data + Programming Workflows + maintainer: Christina Fillmore + description: Create an immutable container holding metadata for the purpose of better + enabling programming activities and functionality of other packages within the + clinical programming workflow. + date_publication: '2024-05-02' + bug_reports: https://github.com/atorus-research/metacore/issues + url: https://atorus-research.github.io/metacore/ + url_cran: https://CRAN.R-project.org/package=metacore + url_git: https://github.com/atorus-research/metacore +MetaCycle: + version: 1.2.0 + title: Evaluate Periodicity in Large Scale Data + maintainer: Gang Wu + description: |- + There are two functions-meta2d and meta3d for + detecting rhythmic signals from time-series datasets. For analyzing + time-series datasets without individual information, 'meta2d' is + suggested, which could incorporates multiple methods from ARSER, + JTK_CYCLE and Lomb-Scargle in the detection of interested rhythms. For + analyzing time-series datasets with individual information, 'meta3d' is + suggested, which takes use of any one of these three methods to analyze + time-series data individual by individual and gives out integrated values + based on analysis result of each individual. + date_publication: '2019-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaCycle + url_git: '' +metadat: + version: 1.4-0 + title: Meta-Analysis Datasets + maintainer: Wolfgang Viechtbauer + description: A collection of meta-analysis datasets for teaching purposes, illustrating/testing + meta-analytic methods, and validating published analyses. + date_publication: '2025-02-04' + bug_reports: https://github.com/wviechtb/metadat/issues + url: https://wviechtb.github.io/metadat/ + url_cran: https://CRAN.R-project.org/package=metadat + url_git: https://github.com/wviechtb/metadat +metadeconfoundR: + version: 1.0.2 + title: |- + Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional + Data + maintainer: Till Birkner + description: |- + Using non-parametric tests, naive associations between omics + features and metadata in cross-sectional data-sets are detected. In a second + step, confounding effects between metadata associated to the same omics + feature are detected and labeled using nested post-hoc model comparison + tests, as first described in + Forslund, Chakaroun, Zimmermann-Kogadeeva, et al. (2021) . + The generated output can be graphically summarized using the built-in plotting function. + date_publication: '2024-06-25' + bug_reports: https://github.com/TillBirkner/metadeconfoundR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metadeconfoundR + url_git: https://github.com/TillBirkner/metadeconfoundR +metaDigitise: + version: 1.0.1 + title: Extract and Summarise Data from Published Figures + maintainer: Daniel Noble + description: High-throughput, flexible and reproducible extraction of data from + figures in primary research papers. metaDigitise() can extract data and / or automatically + calculate summary statistics for users from box plots, bar plots (e.g., mean and + errors), scatter plots and histograms. + date_publication: '2020-03-13' + bug_reports: https://github.com/daniel1noble/metaDigitise/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metaDigitise + url_git: '' +metadynminer: + version: 0.1.7 + title: |- + Tools to Read, Analyze and Visualize Metadynamics HILLS Files + from 'Plumed' + maintainer: Vojtech Spiwok + description: |- + Metadynamics is a state of the art biomolecular simulation technique. + 'Plumed' Tribello, G.A. et al. (2014) program makes + it possible to perform metadynamics using various simulation codes. The results of + metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package + 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. + It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) + to calculate a free energy surface from hills. Minima can be located and plotted on + the free energy surface. Transition states can be analyzed by Nudged Elastic Band + method by Henkelman, G. and Jonsson, H. (2000) . Free energy + surfaces, minima and transition paths can be plotted to produce publication quality + images. + date_publication: '2022-04-14' + bug_reports: '' + url: https://metadynamics.cz/metadynminer/ + url_cran: https://CRAN.R-project.org/package=metadynminer + url_git: '' +metadynminer3d: + version: 0.0.2 + title: |- + Tools to Read, Analyze and Visualize Metadynamics 3D HILLS Files + from 'Plumed' + maintainer: Vojtech Spiwok + description: |- + Metadynamics is a state of the art biomolecular simulation technique. + 'Plumed' Tribello, G.A. et al. (2014) program makes + it possible to perform metadynamics using various simulation codes. The results of + metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package + 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. + As an addendum, 'metadynaminer3d' is used to visualize 3D hills. It uses + a fast algorithm by Hosek, P. and Spiwok, V. (2016) + to calculate a free energy surface from hills. Minima can be located and plotted on + the free energy surface. Free energy surfaces and minima can be plotted to produce + publication quality images. + date_publication: '2022-04-14' + bug_reports: '' + url: https://metadynamics.cz/metadynminer3d/ + url_cran: https://CRAN.R-project.org/package=metadynminer3d + url_git: '' +metaEnsembleR: + version: 0.1.0 + title: Automated Intuitive Package for Meta-Ensemble Learning + maintainer: Ajay Arunachalam + description: Extends the base classes and methods of 'caret' package for integration + of base learners. The user can input the number of different base learners, and + specify the final learner, along with the train-validation-test data partition + split ratio. The predictions on the unseen new data is the resultant of the ensemble + meta-learning + of the heterogeneous learners aimed to reduce the generalization error in the + predictive models. It significantly lowers the barrier for the practitioners to + apply heterogeneous ensemble learning techniques in an amateur fashion to their + everyday predictive problems. + date_publication: '2020-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaEnsembleR + url_git: '' +metafolio: + version: 0.1.2 + title: |- + Metapopulation Simulations for Conserving Salmon Through + Portfolio Optimization + maintainer: Sean C. Anderson + description: |- + A tool to simulate salmon metapopulations and apply financial + portfolio optimization concepts. The package accompanies the paper + Anderson et al. (2015) . + date_publication: '2023-10-20' + bug_reports: https://github.com/seananderson/metafolio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metafolio + url_git: https://github.com/seananderson/metafolio +metafor: + version: 4.8-0 + title: Meta-Analysis Package for R + maintainer: Wolfgang Viechtbauer + description: A comprehensive collection of functions for conducting meta-analyses + in R. The package includes functions to calculate various effect sizes or outcome + measures, fit equal-, fixed-, random-, and mixed-effects models to such data, + carry out moderator and meta-regression analyses, and create various types of + meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, bubble, and + GOSH plots). For meta-analyses of binomial and person-time data, the package also + provides functions that implement specialized methods, including the Mantel-Haenszel + method, Peto's method, and a variety of suitable generalized linear (mixed-effects) + models (i.e., mixed-effects logistic and Poisson regression models). Finally, + the package provides functionality for fitting meta-analytic multivariate/multilevel + models that account for non-independent sampling errors and/or true effects (e.g., + due to the inclusion of multiple treatment studies, multiple endpoints, or other + forms of clustering). Network meta-analyses and meta-analyses accounting for known + correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. + An introduction to the package can be found in Viechtbauer (2010) . + date_publication: '2025-01-28' + bug_reports: https://github.com/wviechtb/metafor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metafor + url_git: https://www.metafor-project.orghttps://github.com/wviechtb/metaforhttps://wviechtb.github.io/metafor/https://www.wvbauer.com +metaforest: + version: 0.1.4 + title: Exploring Heterogeneity in Meta-Analysis using Random Forests + maintainer: Caspar J. van Lissa + description: Conduct random forests-based meta-analysis, obtain partial dependence + plots for metaforest and classic meta-analyses, and cross-validate and tune metaforest- + and classic meta-analyses in conjunction with the caret package. A requirement + of classic meta-analysis is that the studies being aggregated are conceptually + similar, and ideally, close replications. However, in many fields, there is substantial + heterogeneity between studies on the same topic. Classic meta-analysis lacks the + power to assess more than a handful of univariate moderators. MetaForest, by contrast, + has substantial power to explore heterogeneity in meta-analysis. It can identify + important moderators from a larger set of potential candidates (Van Lissa, 2020). + This is an appealing quality, because many meta-analyses have small sample sizes. + Moreover, MetaForest yields a measure of variable importance which can be used + to identify important moderators, and offers partial prediction plots to explore + the shape of the marginal relationship between moderators and effect size. + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaforest + url_git: '' +metafuse: + version: 2.0-1 + title: Fused Lasso Approach in Regression Coefficient Clustering + maintainer: Lu Tang + description: |- + Fused lasso method to cluster and estimate regression coefficients + of the same covariate across different data sets when a large number of + independent data sets are combined. Package supports Gaussian, binomial, + Poisson and Cox PH models. + date_publication: '2016-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metafuse + url_git: '' +metagam: + version: 0.4.0 + title: Meta-Analysis of Generalized Additive Models + maintainer: Oystein Sorensen + description: |- + Meta-analysis of generalized additive + models and generalized additive mixed models. A typical use case is + when data cannot be shared across locations, and an overall meta-analytic + fit is sought. 'metagam' provides functionality for removing individual + participant data from models computed using the 'mgcv' and 'gamm4' packages such + that the model objects can be shared without exposing individual data. + Furthermore, methods for meta-analysing these fits are provided. The implemented + methods are described in Sorensen et al. (2020), , + extending previous works by Schwartz and Zanobetti (2000) + and Crippa et al. (2018) . + date_publication: '2023-05-05' + bug_reports: https://github.com/Lifebrain/metagam/issues + url: https://lifebrain.github.io/metagam/ + url_cran: https://CRAN.R-project.org/package=metagam + url_git: https://github.com/Lifebrain/metagam +metaGE: + version: 1.2.1 + title: Meta-Analysis for Detecting Genotype x Environment Associations + maintainer: Annaïg De Walsche + description: |- + Provides functions to perform all steps of genome-wide + association meta-analysis for studying Genotype x Environment + interactions, from collecting the data to the manhattan plot. The + procedure accounts for the potential correlation between studies. In + addition to the Fixed and Random models, one can investigate the + relationship between QTL effects and some qualitative or quantitative + covariate via the test of contrast and the meta-regression, + respectively. The methodology is available from: (De Walsche, A., et + al. (2025) \doi{10.1371/journal.pgen.1011553}). + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaGE + url_git: '' +metagear: + version: '0.7' + title: |- + Comprehensive Research Synthesis Tools for Systematic Reviews + and Meta-Analysis + maintainer: Marc J. Lajeunesse + description: |- + Functionalities for facilitating systematic reviews, data + extractions, and meta-analyses. It includes a GUI (graphical user interface) + to help screen the abstracts and titles of bibliographic data; tools to assign + screening effort across multiple collaborators/reviewers and to assess inter- + reviewer reliability; tools to help automate the download and retrieval of + journal PDF articles from online databases; figure and image extractions + from PDFs; web scraping of citations; automated and manual data extraction + from scatter-plot and bar-plot images; PRISMA (Preferred Reporting Items for + Systematic Reviews and Meta-Analyses) flow diagrams; simple imputation tools + to fill gaps in incomplete or missing study parameters; generation of random + effects sizes for Hedges' d, log response ratio, odds ratio, and correlation + coefficients for Monte Carlo experiments; covariance equations for modelling + dependencies among multiple effect sizes (e.g., effect sizes with a common + control); and finally summaries that replicate analyses and outputs from + widely used but no longer updated meta-analysis software (i.e., metawin). + Funding for this package was supported by National Science Foundation (NSF) + grants DBI-1262545 and DEB-1451031. CITE: Lajeunesse, M.J. (2016) + Facilitating systematic reviews, data extraction and meta-analysis with the + metagear package for R. Methods in Ecology and Evolution 7, 323-330 + . + date_publication: '2021-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metagear + url_git: http://lajeunesse.myweb.usf.edu/https://github.com/mjlajeunesse/https://www.youtube.com/c/LajeunesseLab/ +metaggR: + version: 0.3.0 + title: Calculate the Knowledge-Weighted Estimate + maintainer: Ville Satopää + description: |2- + + According to a phenomenon known as "the wisdom of the crowds," + combining point estimates from multiple judges often provides a + more accurate aggregate estimate than using a point estimate from + a single judge. However, if the judges use shared information in + their estimates, the simple average will over-emphasize this common + component at the expense of the judges’ private information. + Asa Palley & Ville Satopää (2021) "Boosting the Wisdom of Crowds + Within a Single Judgment Problem: Selective Averaging Based on Peer Predictions" + proposes + a procedure for calculating a weighted average of the judges’ individual + estimates such that resulting aggregate estimate appropriately combines + the judges' collective information within a single estimation problem. + The authors use both simulation and data from six experimental studies + to illustrate that the weighting procedure outperforms existing averaging-like + methods, such as the equally weighted average, trimmed average, and median. + This aggregate estimate -- know as "the knowledge-weighted estimate" -- + inputs a) judges' estimates of a continuous outcome (E) and + b) predictions of others' average estimate of this outcome (P). + In this R-package, the function knowledge_weighted_estimate(E,P) + implements the knowledge-weighted estimate. Its use is illustrated + with a simple stylized example and on real-world experimental data. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaggR + url_git: '' +MetaHD: + version: 0.1.3 + title: |- + A Multivariate Meta-Analysis Model for High-Dimensional + Metabolomics Data + maintainer: Jayamini Liyanage + description: Performs multivariate meta-analysis for high-dimensional metabolomics + data for integrating and collectively analysing individual-level data generated + from multiple studies as well as for combining summary estimates. This approach + accounts for correlation between outcomes, considers variability within and between + studies, handles missing values and uses shrinkage estimation to allow for high + dimensionality. A detailed vignette with example datasets and code to prepare + data and analyses are available on . + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaHD + url_git: '' +metaHelper: + version: 1.0.0 + title: Transforms Statistical Measures Commonly Used for Meta-Analysis + maintainer: Robert Emprechtinger + description: |- + Helps calculate statistical values commonly used in meta-analysis. It provides several methods to compute different forms of standardized mean differences, as well as other values such as standard errors and standard deviations. + The methods used in this package are described in the following references: + Altman D G, Bland J M. (2011) + Borenstein, M., Hedges, L.V., Higgins, J.P.T. and Rothstein, H.R. (2009) + Chinn S. (2000) + Cochrane Handbook (2011) + Cooper, H., Hedges, L. V., & Valentine, J. C. (2009) + Cohen, J. (1977) + Ellis, P.D. (2009) + Goulet-Pelletier, J.-C., & Cousineau, D. (2018) + Hedges, L. V. (1981) + Hedges L. V., Olkin I. (1985) + Murad M H, Wang Z, Zhu Y, Saadi S, Chu H, Lin L et al. (2023) + Mayer M (2023) + Stackoverflow (2014) + Stackoverflow (2018) . + date_publication: '2024-07-28' + bug_reports: https://github.com/RobertEmprechtinger/metaHelper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metaHelper + url_git: https://github.com/RobertEmprechtinger/metaHelper +metaheuristicOpt: + version: 2.0.0 + title: Metaheuristic for Optimization + maintainer: Lala Septem Riza + description: 'An implementation of metaheuristic algorithms for continuous optimization. + Currently, the package contains the implementations of 21 algorithms, as follows: + particle swarm optimization (Kennedy and Eberhart, 1995), ant lion optimizer (Mirjalili, + 2015 ), grey wolf optimizer (Mirjalili et + al., 2014 ), dragonfly algorithm (Mirjalili, + 2015 ), firefly algorithm (Yang, 2009 ), + genetic algorithm (Holland, 1992, ISBN:978-0262581110), grasshopper optimisation + algorithm (Saremi et al., 2017 ), harmony + search algorithm (Mahdavi et al., 2007 ), moth + flame optimizer (Mirjalili, 2015 , sine cosine + algorithm (Mirjalili, 2016 ), whale optimization + algorithm (Mirjalili and Lewis, 2016 ), + clonal selection algorithm (Castro, 2002 ), differential + evolution (Das & Suganthan, 2011), shuffled frog leaping (Eusuff, Landsey & Pasha, + 2006), cat swarm optimization (Chu et al., 2006), artificial bee colony algorithm + (Karaboga & Akay, 2009), krill-herd algorithm (Gandomi & Alavi, 2012), cuckoo + search (Yang & Deb, 2009), bat algorithm (Yang, 2012), gravitational based search + (Rashedi et al., 2009) and black hole optimization (Hatamlou, 2013).' + date_publication: '2019-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaheuristicOpt + url_git: '' +metainc: + version: 0.2-0 + title: |- + Assessment of Inconsistency in Meta-Analysis using Decision + Thresholds + maintainer: Bernardo Sousa-Pinto + description: Assessment of inconsistency in meta-analysis by calculating the Decision + Inconsistency index (DI) and the Across-Studies Inconsistency (ASI) index. These + indices quantify inconsistency taking into account outcome-level decision thresholds. + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metainc + url_git: '' +MetaIntegration: + version: 0.1.2 + title: Ensemble Meta-Prediction Framework + maintainer: Michael Kleinsasser + description: |- + An ensemble meta-prediction framework to integrate multiple regression + models into a current study. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2020) + . + A meta-analysis framework along with two weighted estimators as the ensemble + of empirical Bayes estimators, which combines the estimates from the different + external models. The proposed framework is flexible and robust in the ways + that (i) it is capable of incorporating external models that use a slightly + different set of covariates; (ii) it is able to identify the most relevant + external information and diminish the influence of information that is less + compatible with the internal data; and (iii) it nicely balances the bias-variance + trade-off while preserving the most efficiency gain. The proposed estimators + are more efficient than the naive analysis of the internal data and other + naive combinations of external estimators. + date_publication: '2021-03-17' + bug_reports: https://github.com/umich-biostatistics/MetaIntegration/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetaIntegration + url_git: https://github.com/umich-biostatistics/MetaIntegration +metajam: + version: 0.3.1 + title: Easily Download Data and Metadata from 'DataONE' + maintainer: Julien Brun + description: |- + A set of tools to foster the development of reproducible analytical workflow by simplifying the download of data and + metadata from 'DataONE' () and easily importing this information into R. + date_publication: '2024-08-16' + bug_reports: https://github.com/NCEAS/metajam/issues + url: https://nceas.github.io/metajam/ + url_cran: https://CRAN.R-project.org/package=metajam + url_git: https://github.com/NCEAS/metajam +MetaLandSim: + version: 2.0.0 + title: Landscape and Range Expansion Simulation + maintainer: Frederico Mestre + description: |- + Tools to generate random landscape graphs, evaluate species + occurrence in dynamic landscapes, simulate future landscape occupation and + evaluate range expansion when new empty patches are available (e.g. as a + result of climate change). References: Mestre, F., Canovas, F., Pita, R., + Mira, A., Beja, P. (2016) ; Mestre, F., + Risk, B., Mira, A., Beja, P., Pita, R. (2017) + ; Mestre, F., Pita, R., Mira, A., Beja, + P. (2020) . + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaLandSim + url_git: '' +metaLik: + version: 0.43.0 + title: Likelihood Inference in Meta-Analysis and Meta-Regression Models + maintainer: Cristiano Varin + description: |- + First- and higher-order likelihood inference in + meta-analysis and meta-regression models. + date_publication: '2018-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaLik + url_git: '' +metalite: + version: 0.1.4 + title: ADaM Metadata Structure + maintainer: Yujie Zhao + description: |- + A metadata structure for clinical data analysis + and reporting based on Analysis Data Model (ADaM) datasets. + The package simplifies clinical analysis and reporting tool development + by defining standardized inputs, outputs, and workflow. + The package can be used to create analysis and reporting planning grid, + mock table, and validated analysis and reporting results based on + consistent inputs. + date_publication: '2024-08-22' + bug_reports: https://github.com/Merck/metalite/issues + url: https://merck.github.io/metalite/ + url_cran: https://CRAN.R-project.org/package=metalite + url_git: https://github.com/Merck/metalite +metalite.ae: + version: 0.1.3 + title: Adverse Events Analysis Using 'metalite' + maintainer: Yujie Zhao + description: |- + Analyzes adverse events in clinical trials using the 'metalite' + data structure. The package simplifies the workflow to create + production-ready tables, listings, and figures discussed in the + adverse events analysis chapters of + "R for Clinical Study Reports and Submission" + by Zhang et al. (2022) . + date_publication: '2024-10-23' + bug_reports: https://github.com/Merck/metalite.ae/issues + url: https://merck.github.io/metalite.ae/ + url_cran: https://CRAN.R-project.org/package=metalite.ae + url_git: https://github.com/Merck/metalite.ae +metalite.sl: + version: 0.1.0 + title: Subject-Level Analysis Using 'metalite' + maintainer: Benjamin Wang + description: |- + Analyzes subject-level data in clinical trials using the 'metalite' + data structure. The package simplifies the workflow to create + production-ready tables, listings, and figures discussed in the + subject-level analysis chapters of + "R for Clinical Study Reports and Submission" + by Zhang et al. (2022) . + date_publication: '2024-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metalite.sl + url_git: '' +metalite.table1: + version: 0.4.0 + title: Interactive Table of Descriptive Statistics in HTML + maintainer: Yilong Zhang + description: |- + Create an interactive table of descriptive statistics in HTML. + This table is typically used for exploratory analysis in a clinical study (referred to as 'Table 1'). + date_publication: '2024-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metalite.table1 + url_git: '' +MetAlyzer: + version: 1.1.0 + title: Read and Analyze 'MetIDQ™' Software Output Files + maintainer: Nils Mechtel + description: The 'MetAlyzer' S4 object provides methods to read and reformat metabolomics + data for convenient data handling, statistics and downstream analysis. The resulting + format corresponds to input data of the Shiny app 'MetaboExtract' (). + date_publication: '2024-12-06' + bug_reports: https://github.com/nilsmechtel/MetAlyzer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetAlyzer + url_git: https://github.com/nilsmechtel/MetAlyzer +metaMA: + version: 3.1.3 + title: Meta-Analysis for MicroArrays + maintainer: Samuel Blanck + description: |- + Combination of either p-values or modified effect sizes from different + studies to find differentially expressed genes. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaMA + url_git: '' +metamedian: + version: 1.1.1 + title: Meta-Analysis of Medians + maintainer: Sean McGrath + description: |- + Implements several methods to meta-analyze studies that report the + sample median of the outcome. When the primary studies are one-group + studies, the methods of McGrath et al. (2019) and + Ozturk and Balakrishnan (2020) can be applied to + estimate the pooled median. In the two-group context, the + methods of McGrath et al. (2020a) can be + applied to estimate the pooled difference of medians across groups. + Additionally, a number of methods (e.g., McGrath et al. (2020b) + , Cai et al. (2021) + , and McGrath et al. (2023) + ) are implemented to estimate + study-specific (difference of) means and their standard errors in order to + estimate the pooled (difference of) means. See McGrath et al. (in press) + for a detailed guide on using the package. + date_publication: '2023-12-14' + bug_reports: https://github.com/stmcg/metamedian/issues + url: https://doi.org/10.1002/jrsm.1686 + url_cran: https://CRAN.R-project.org/package=metamedian + url_git: https://github.com/stmcg/metamedian +metamer: + version: 0.3.0 + title: Create Data with Identical Statistics + maintainer: Elio Campitelli + description: |- + Creates data with identical statistics (metamers) using an iterative + algorithm proposed by Matejka & Fitzmaurice (2017) . + date_publication: '2022-06-23' + bug_reports: https://github.com/eliocamp/metamer/issues + url: https://eliocamp.github.io/metamer/ + url_cran: https://CRAN.R-project.org/package=metamer + url_git: '' +metamicrobiomeR: + version: '1.2' + title: |- + Microbiome Data Analysis & Meta-Analysis with GAMLSS-BEZI & + Random Effects + maintainer: Nhan Ho + description: |- + Generalized Additive Model for Location, Scale and Shape (GAMLSS) + with zero inflated beta (BEZI) family for analysis of microbiome relative abundance data + (with various options for data transformation/normalization to address compositional effects) and + random effects meta-analysis models for meta-analysis pooling estimates across microbiome studies + are implemented. + Random Forest model to predict microbiome age based on relative abundances of + shared bacterial genera with the Bangladesh data (Subramanian et al 2014), + comparison of multiple diversity indexes using linear/linear mixed effect models + and some data display/visualization are also implemented. + The reference paper is published by + Ho NT, Li F, Wang S, Kuhn L (2019) . + date_publication: '2020-11-09' + bug_reports: https://github.com/nhanhocu/metamicrobiomeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metamicrobiomeR + url_git: https://github.com/nhanhocu/metamicrobiomeR +metamisc: + version: 0.4.0 + title: Meta-Analysis of Diagnosis and Prognosis Research Studies + maintainer: Thomas Debray + description: Facilitate frequentist and Bayesian meta-analysis of diagnosis and + prognosis research studies. It includes functions to summarize multiple estimates + of prediction model discrimination and calibration performance (Debray et al., + 2019) . It also includes functions to evaluate funnel + plot asymmetry (Debray et al., 2018) . Finally, the package + provides functions for developing multivariable prediction models from datasets + with clustering (de Jong et al., 2021) . + date_publication: '2022-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metamisc + url_git: https://github.com/smartdata-analysis-and-statistics/metamisc +metan: + version: 1.19.0 + title: Multi Environment Trials Analysis + maintainer: Tiago Olivoto + description: |- + Performs stability analysis of multi-environment trial data + using parametric and non-parametric methods. Parametric methods + includes Additive Main Effects and Multiplicative Interaction (AMMI) + analysis by Gauch (2013) , Ecovalence + by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot + analysis by Yan & Kang (2003) , geometric + adaptability index by Mohammadi & Amri (2008) + , joint regression analysis by Eberhart + & Russel (1966) , + genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's + (2004) method, power law residuals (POLAR) statistics by Doring et al. + (2015) , scale-adjusted coefficient of + variation by Doring & Reckling (2018) , + stability variance by Shukla (1972) , + weighted average of absolute scores by Olivoto et al. (2019a) + , and multi-trait stability index by + Olivoto et al. (2019b) . + Non-parametric methods includes superiority index by Lin & Binns + (1988) , nonparametric measures of phenotypic + stability by Huehn (1990) , TOP third + statistic by Fox et al. (1990) . Functions for + computing biometrical analysis such as path analysis, canonical + correlation, partial correlation, clustering analysis, and tools for + inspecting, manipulating, summarizing and plotting typical + multi-environment trial data are also provided. + date_publication: '2024-12-15' + bug_reports: https://github.com/nepem-ufsc/metan/issues + url: https://nepem-ufsc.github.io/metan/ + url_cran: https://CRAN.R-project.org/package=metan + url_git: https://github.com/nepem-ufsc/metan +MetaNet: + version: 0.1.2 + title: Network Analysis for Omics Data + maintainer: Chen Peng + description: |- + Comprehensive network analysis package. + Calculate correlation network fastly, accelerate lots of analysis by parallel computing. + Support for multi-omics data, search sub-nets fluently. + Handle bigger data, more than 10,000 nodes in each omics. + Offer various layout method for multi-omics network and some interfaces to other software ('Gephi', 'Cytoscape', 'ggplot2'), easy to visualize. + Provide comprehensive topology indexes calculation, including ecological network stability. + date_publication: '2024-03-25' + bug_reports: https://github.com/Asa12138/MetaNet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetaNet + url_git: https://github.com/Asa12138/MetaNet +metanetwork: + version: 0.7.0 + title: Handling and Representing Trophic Networks in Space and Time + maintainer: Marc Ohlmann + description: A toolbox to handle and represent trophic networks in space or time + across aggregation levels. This package contains a layout algorithm specifically + designed for trophic networks, using dimension reduction on a diffusion graph + kernel and trophic levels. Importantly, this package provides a layout method + applicable for large trophic networks. + date_publication: '2022-12-05' + bug_reports: https://github.com/MarcOhlmann/metanetwork/issues + url: https://marcohlmann.github.io/metanetwork/ + url_cran: https://CRAN.R-project.org/package=metanetwork + url_git: https://github.com/MarcOhlmann/metanetwork +MetaNLP: + version: 0.1.3 + title: Natural Language Processing for Meta Analysis + maintainer: Maximilian Pilz + description: |- + Given a CSV file with titles and abstracts, the package creates a + document-term matrix that is lemmatized and stemmed and can directly be used to + train machine learning methods for automatic title-abstract screening in the + preparation of a meta analysis. + date_publication: '2024-11-07' + bug_reports: https://github.com/imbi-heidelberg/MetaNLP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetaNLP + url_git: https://github.com/imbi-heidelberg/MetaNLP +metansue: + version: '2.6' + title: |- + Meta-Analysis of Studies with Non-Statistically Significant + Unreported Effects + maintainer: Joaquim Radua + description: Novel method to unbiasedly include studies with Non-statistically Significant + Unreported Effects (NSUEs) in a meta-analysis. First, the function calculates + the interval where the unreported effects (e.g., t-values) should be according + to the threshold of statistical significance used in each study. Afterward, the + method uses maximum likelihood techniques to impute the expected effect size of + each study with NSUEs, accounting for between-study heterogeneity and potential + covariates. Multiple imputations of the NSUEs are then randomly created based + on the expected value, variance, and statistical significance bounds. Finally, + it conducts a restricted-maximum likelihood random-effects meta-analysis separately + for each set of imputations, and it performs estimations from these meta-analyses. + Please read the reference in 'metansue' for details of the procedure. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metansue + url_git: '' +metap: + version: '1.11' + title: Meta-Analysis of Significance Values + maintainer: Michael Dewey + description: |- + The canonical way to perform meta-analysis involves using effect sizes. + When they are not available this package provides a number of methods for + meta-analysis of significance values including the methods of Edgington, Fisher, + Lancaster, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; + and routines for graphical display. + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metap + url_git: '' +metapack: + version: '0.3' + title: Bayesian Meta-Analysis and Network Meta-Analysis + maintainer: Daeyoung Lim + description: Contains functions performing Bayesian inference for meta-analytic + and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, + the package implements Hui Yao, Sungduk Kim, Ming-Hui Chen, Joseph G. Ibrahim, + Arvind K. Shah, and Jianxin Lin (2015) and + Hao Li, Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. + Shah, Jianxin Lin (2021) . For maximal computational efficiency, + the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. + This software has been developed under the auspices of the National Institutes + of Health and Merck & Co., Inc., Kenilworth, NJ, USA. + date_publication: '2024-01-24' + bug_reports: https://github.com/daeyounglim/metapack/issues + url: https://events.stat.uconn.edu/metapack/ + url_cran: https://CRAN.R-project.org/package=metapack + url_git: '' +metaplot: + version: 0.8.4 + title: Data-Driven Plot Design + maintainer: Tim Bergsma + description: |- + Designs plots in terms of core structure. See 'example(metaplot)'. + Primary arguments are (unquoted) column names; order and type (numeric or not) + dictate the resulting plot. Specify any y variables, x variable, any groups variable, + and any conditioning variables to metaplot() to generate density plots, boxplots, + mosaic plots, scatterplots, scatterplot matrices, or conditioned plots. Use multiplot() + to arrange plots in grids. Wherever present, scalar column attributes 'label' and 'guide' + are honored, producing fully annotated plots with minimal effort. Attribute 'guide' + is typically units, but may be encoded() to provide interpretations of categorical + values (see '?encode'). Utility unpack() transforms scalar column attributes to row + values and pack() does the reverse, supporting tool-neutral storage of metadata along + with primary data. The package supports customizable aesthetics such as such as reference + lines, unity lines, smooths, log transformation, and linear fits. The user may choose + between trellis and ggplot output. Compact syntax and integrated metadata promote workflow + scalability. + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaplot + url_git: '' +metaplus: + version: 1.0-6 + title: Robust Meta-Analysis and Meta-Regression + maintainer: Ken Beath + description: Performs meta-analysis and meta-regression using standard and robust + methods with confidence intervals based on the profile likelihood. Robust methods + are based on alternative distributions for the random effect, either the t-distribution + (Lee and Thompson, 2008 or Baker and Jackson, 2008 ) + or mixtures of normals (Beath, 2014 ). + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaplus + url_git: '' +metapost: + version: 1.0-6 + title: Interface to 'MetaPost' + maintainer: Paul Murrell + description: |- + Provides an interface to 'MetaPost' (Hobby, 1998) + . + There are functions to generate an R description of a 'MetaPost' + curve, functions to generate 'MetaPost' code from an R description, + functions to process 'MetaPost' code, and functions to read + solved 'MetaPost' paths back into R. + date_publication: '2019-06-24' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2018/12/03/2018-12-metapost-three-ways/ + url_cran: https://CRAN.R-project.org/package=metapost + url_git: https://github.com/pmur002/metapost +metapower: + version: 0.2.2 + title: Power Analysis for Meta-Analysis + maintainer: Jason Griffin + description: |- + A simple and effective tool for computing and visualizing statistical power for meta-analysis, + including power analysis of main effects (Jackson & Turner, 2017), + test of homogeneity (Pigott, 2012), subgroup analysis, + and categorical moderator analysis (Hedges & Pigott, 2004). + date_publication: '2021-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metapower + url_git: '' +metapro: + version: 1.5.11 + title: Robust P-Value Combination Methods + maintainer: Sora Yoon + description: The meta-analysis is performed to increase the statistical power by + integrating the results from several experiments. The p-values are often combined + in meta-analysis when the effect sizes are not available. The 'metapro' R package + provides not only traditional methods (Becker BJ (1994, ISBN:0-87154-226-9), Mosteller, + F. & Bush, R.R. (1954, ISBN:0201048523) and Lancaster HO (1949, ISSN:00063444)), + but also new method named weighted Fisher’s method we developed. While the (weighted) + Z-method is suitable for finding features effective in most experiments, (weighted) + Fisher’s method is useful for detecting partially associated features. Thus, the + users can choose the function based on their purpose. Yoon et al. (2021) "Powerful + p-value combination methods to detect incomplete association" . + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metapro + url_git: '' +metaprotr: + version: 1.2.2 + title: Metaproteomics Post-Processing Analysis + maintainer: Aaron Millan-Oropeza + description: |2- + + Set of tools for descriptive analysis of metaproteomics data generated from high-throughput + mass spectrometry instruments. These tools allow to cluster peptides and proteins abundance, + expressed as spectral counts, and to manipulate them in groups of metaproteins. This information + can be represented using multiple visualization functions to portray the global metaproteome + landscape and to differentiate samples or conditions, in terms of abundance of metaproteins, + taxonomic levels and/or functional annotation. The provided tools allow to implement flexible + analytical pipelines that can be easily applied to studies interested in metaproteomics analysis. + date_publication: '2021-02-05' + bug_reports: '' + url: https://forgemia.inra.fr/pappso/metaprotr + url_cran: https://CRAN.R-project.org/package=metaprotr + url_git: '' +metaquant: + version: 0.1.1 + title: |- + Estimating Means, Standard Deviations and Visualising + Distributions using Quantiles + maintainer: Udara Kumaranathunga + description: |- + Implements a novel density-based approach for estimating unknown means, visualizing distributions, + and meta-analyses of quantiles. A detailed vignettes with example datasets and code to prepare data and analyses is available at . + The methods are described in the pre-print by De Livera, Prendergast and Kumaranathunga (2024, ). + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaquant + url_git: '' +metaRange: + version: 1.1.4 + title: |- + Framework to Build Mechanistic and Metabolic Constrained Species + Distribution Models + maintainer: Stefan Fallert + description: |- + Build spatially and temporally explicit + process-based species distribution models, that can include an arbitrary + number of environmental factors, species and processes including metabolic + constraints and species interactions. The focus of the package is simulating + populations of one or multiple species in a grid-based landscape and studying + the meta-population dynamics and emergent patterns that arise from the + interaction of species under complex environmental conditions. It + provides functions for common ecological processes such as + negative exponential, kernel-based dispersal (see + Nathan et al. (2012) ), + calculation of the environmental suitability based on cardinal values ( + Yin et al. (1995) , simplified by + Yan and Hunt (1999) see eq: 4), reproduction in + form of an Ricker model (see Ricker (1954) and + Cabral and Schurr (2010) ), + as well as metabolic scaling based on the metabolic theory of ecology + (see Brown et al. (2004) and + Brown, Sibly and Kodric-Brown (2012) + ). + date_publication: '2024-02-09' + bug_reports: https://github.com/metaRange/metaRange/issues + url: https://metaRange.github.io/metaRange/ + url_cran: https://CRAN.R-project.org/package=metaRange + url_git: '' +metarep: + version: 1.2.0 + title: Replicability-Analysis Tools for Meta-Analysis + maintainer: Iman Jaljuli + description: |- + User-friendly package for reporting replicability-analysis methods, affixed to meta-analyses summary. The replicability-analysis output provides an assessment of the investigated intervention, where it offers quantification of effect replicability and assessment of the consistency of findings. + - Replicability-analysis for fixed-effects and random-effect meta analysis: + - r(u)-value; + - lower bounds on the number of studies with replicated positive and\or negative effect; + - Allows detecting inconsistency of signals; + - forest plots with the summary of replicability analysis results; + - Allows Replicability-analysis with or without the common-effect assumption. + date_publication: '2023-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metarep + url_git: https://github.com/IJaljuli/metarep +metaRNASeq: + version: 1.0.7 + title: Meta-Analysis of RNA-Seq Data + maintainer: samuel Blanck + description: Implementation of two p-value combination techniques (inverse normal + and Fisher methods). A vignette is provided to explain how to perform a meta-analysis + from two independent RNA-seq experiments. + date_publication: '2021-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaRNASeq + url_git: '' +metaSDTreg: + version: 0.2.2 + title: Regression Models for Meta Signal Detection Theory + maintainer: Simon Bang Kristensen + description: Regression methods for the meta-SDT model. The package implements methods + for cognitive experiments of metacognition as described in Kristensen, S. B., + Sandberg, K., & Bibby, B. M. (2020). Regression methods for metacognitive sensitivity. + Journal of Mathematical Psychology, 94. . + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaSDTreg + url_git: '' +metaSEM: + version: 1.5.0 + title: Meta-Analysis using Structural Equation Modeling + maintainer: Mike Cheung + description: |- + A collection of functions for conducting meta-analysis using a + structural equation modeling (SEM) approach via the 'OpenMx' and + 'lavaan' packages. It also implements various procedures to + perform meta-analytic structural equation modeling on the + correlation and covariance matrices, see Cheung (2015) + . + date_publication: '2024-09-26' + bug_reports: https://github.com/mikewlcheung/metasem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metaSEM + url_git: https://github.com/mikewlcheung/metasem +metasens: + version: 1.5-2 + title: Statistical Methods for Sensitivity Analysis in Meta-Analysis + maintainer: Guido Schwarzer + description: |- + The following methods are implemented to evaluate how sensitive the results of a meta-analysis are to potential bias in meta-analysis and to support Schwarzer et al. (2015) , Chapter 5 'Small-Study Effects in Meta-Analysis': + - Copas selection model described in Copas & Shi (2001) ; + - limit meta-analysis by Rücker et al. (2011) ; + - upper bound for outcome reporting bias by Copas & Jackson (2004) ; + - imputation methods for missing binary data by Gamble & Hollis (2005) and Higgins et al. (2008) ; + - LFK index test and Doi plot by Furuya-Kanamori et al. (2018) . + date_publication: '2023-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metasens + url_git: https://github.com/guido-s/metasenshttps://link.springer.com/book/10.1007/978-3-319-21416-0 +MetaSKAT: + version: '0.90' + title: Meta Analysis for SNP-Set (Sequence) Kernel Association Test + maintainer: Seunggeun (Shawn) Lee + description: Functions for Meta-analysis Burden Test, Sequence Kernel Association + Test (SKAT) and Optimal SKAT (SKAT-O) by Lee et al. (2013) . + These methods use summary-level score statistics to carry out gene-based meta-analysis + for rare variants. + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaSKAT + url_git: '' +metasnf: + version: 2.0.0 + title: Meta Clustering with Similarity Network Fusion + maintainer: Prashanth S Velayudhan + description: Framework to facilitate patient subtyping with similarity network fusion + and meta clustering. The similarity network fusion (SNF) algorithm was introduced + by Wang et al. (2014) in . SNF is a data integration approach + that can transform high-dimensional and diverse data types into a single similarity + network suitable for clustering with minimal loss of information from each initial + data source. The meta clustering approach was introduced by Caruana et al. (2006) + in . Meta clustering involves generating a wide range + of cluster solutions by adjusting clustering hyperparameters, then clustering + the solutions themselves into a manageable number of qualitatively similar solutions, + and finally characterizing representative solutions to find ones that are best + for the user's specific context. This package provides a framework to easily transform + multi-modal data into a wide range of similarity network fusion-derived cluster + solutions as well as to visualize, characterize, and validate those solutions. + Core package functionality includes easy customization of distance metrics, clustering + algorithms, and SNF hyperparameters to generate diverse clustering solutions; + calculation and plotting of associations between features, between patients, and + between cluster solutions; and standard cluster validation approaches including + resampled measures of cluster stability, standard metrics of cluster quality, + and label propagation to evaluate generalizability in unseen data. Associated + vignettes guide the user through using the package to identify patient subtypes + while adhering to best practices for unsupervised learning. + date_publication: '2025-02-04' + bug_reports: https://github.com/BRANCHlab/metasnf/issues + url: https://branchlab.github.io/metasnf/ + url_cran: https://CRAN.R-project.org/package=metasnf + url_git: https://github.com/BRANCHlab/metasnf/ +MetaStan: + version: 1.0.0 + title: Bayesian Meta-Analysis via 'Stan' + maintainer: Burak Kuersad Guenhan + description: |- + Performs Bayesian meta-analysis, meta-regression and model-based meta-analysis + using 'Stan'. Includes binomial-normal hierarchical models and option to use + weakly informative priors for the heterogeneity parameter and the treatment effect + parameter which are described in Guenhan, Roever, and Friede (2020) . + date_publication: '2022-01-22' + bug_reports: https://github.com/gunhanb/MetaStan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetaStan + url_git: https://github.com/gunhanb/MetaStan +MetaSubtract: + version: '1.60' + title: |- + Subtracting Summary Statistics of One or more Cohorts from + Meta-GWAS Results + maintainer: Ilja M. Nolte + description: |- + If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. + The validation cohort needs to be independent from the meta-Genome-Wide-Association-Study (meta-GWAS) results. + 'MetaSubtract' will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. + It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. + It can also handle different meta-analysis methods. It can be used for whole GWAS, but also for a limited set of genetic markers. + See for application: Nolte I.M. et al. (2017); . + date_publication: '2020-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaSubtract + url_git: '' +metaSurvival: + version: 0.1.0 + title: Meta-Analysis of a Single Survival Curve + maintainer: Shubhram Pandey + description: To assess a summary survival curve from survival probabilities and + number of at-risk patients collected at various points in time in various studies, + and to test the between-strata heterogeneity. + date_publication: '2020-12-07' + bug_reports: https://github.com/shubhrampandey/metaSurvival/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metaSurvival + url_git: https://github.com/shubhrampandey/metaSurvival +metatest: + version: 1.0-5 + title: Fit and Test Metaregression Models + maintainer: Ingmar Visser + description: |- + Fits and tests meta regression models and generates a + number of useful test statistics: next to t- and z-tests, the likelihood ratio, + bartlett corrected likelihood ratio and permutation tests are performed on + the model coefficients. + date_publication: '2018-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metatest + url_git: '' +metathis: + version: 1.1.4 + title: HTML Metadata Tags for 'R Markdown' and 'Shiny' + maintainer: Garrick Aden-Buie + description: |- + Create meta tags for 'R Markdown' HTML documents and 'Shiny' + apps for customized social media cards, for accessibility, and quality + search engine indexing. 'metathis' currently supports HTML documents + created with 'rmarkdown', 'shiny', 'xaringan', 'pagedown', 'bookdown', + and 'flexdashboard'. + date_publication: '2023-07-11' + bug_reports: https://github.com/gadenbuie/metathis/issues + url: https://pkg.garrickadenbuie.com/metathis/ + url_cran: https://CRAN.R-project.org/package=metathis + url_git: https://github.com/gadenbuie/metathis +metatools: + version: 0.1.6 + title: Enable the Use of 'metacore' to Help Create and Check Dataset + maintainer: Christina Fillmore + description: Uses the metadata information stored in 'metacore' objects to check + and build metadata associated columns. + date_publication: '2024-07-23' + bug_reports: https://github.com/pharmaverse/metatools/issues + url: https://pharmaverse.github.io/metatools/ + url_cran: https://CRAN.R-project.org/package=metatools + url_git: https://github.com/pharmaverse/metatools +metaumbrella: + version: 1.1.0 + title: Umbrella Review Package for R + maintainer: Corentin J Gosling + description: 'A comprehensive range of facilities to perform umbrella reviews with + stratification of the evidence in R. The package accomplishes this aim by building + on three core functions that: (i) automatically perform all required calculations + in an umbrella review (including but not limited to meta-analyses), (ii) stratify + evidence according to various classification criteria, and (iii) generate a visual + representation of the results. Note that if you are not familiar with R, the core + features of this package are available from a web browser ().' + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metaumbrella + url_git: '' +MetaUtility: + version: 2.1.2 + title: Utility Functions for Conducting and Interpreting Meta-Analyses + maintainer: Maya B. Mathur + description: |- + Contains functions to estimate the proportion of effects stronger than a threshold + of scientific importance (function prop_stronger), to nonparametrically characterize the distribution of effects in a meta-analysis (calib_ests, pct_pval), + to make effect size conversions (r_to_d, r_to_z, z_to_r, d_to_logRR), to compute and format inference in a meta-analysis (format_CI, format_stat, tau_CI), to scrape results from + existing meta-analyses for re-analysis (scrape_meta, parse_CI_string, ci_to_var). + date_publication: '2021-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetaUtility + url_git: '' +metavcov: + version: 2.1.5 + title: |- + Computing Variances and Covariances, Visualization and Missing + Data Solution for Multivariate Meta-Analysis + maintainer: Min Lu + description: Collection of functions to compute within-study covariances for different + effect sizes, data visualization, and single and multiple imputations for missing + data. Effect sizes include correlation (r), mean difference (MD), standardized + mean difference (SMD), log odds ratio (logOR), log risk ratio (logRR), and risk + difference (RD). + date_publication: '2023-06-24' + bug_reports: https://github.com/luminwin/metavcov/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=metavcov + url_git: https://github.com/luminwin/metavcov +metaviz: + version: 0.3.1 + title: |- + Forest Plots, Funnel Plots, and Visual Funnel Plot Inference for + Meta-Analysis + maintainer: Michael Kossmeier + description: |- + A compilation of functions to create visually appealing and information-rich + plots of meta-analytic data using 'ggplot2'. Currently allows to create forest plots, + funnel plots, and many of their variants, such as rainforest plots, thick forest plots, + additional evidence contour funnel plots, and sunset funnel plots. In addition, functionalities + for visual inference with the funnel plot in the context of meta-analysis are provided. + date_publication: '2020-04-09' + bug_reports: https://github.com/Mkossmeier/metaviz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metaviz + url_git: https://github.com/Mkossmeier/metaviz +metawho: + version: 0.2.0 + title: |- + Meta-Analytical Implementation to Identify Who Benefits Most + from Treatments + maintainer: Shixiang Wang + description: |- + A tool for implementing so called 'deft' approach + (see Fisher, David J., et al. (2017) ) and model + visualization. + date_publication: '2019-12-06' + bug_reports: https://github.com/ShixiangWang/metawho/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metawho + url_git: https://github.com/ShixiangWang/metawho +MetBrewer: + version: 0.2.0 + title: |- + Color Palettes Inspired by Works at the Metropolitan Museum of + Art + maintainer: Blake Robert Mills + description: Palettes Inspired by Works at the Metropolitan Museum of Art in New + York. Currently contains over 50 color schemes and checks for colorblind-friendliness + of palettes. Colorblind accessibility checked using the '{colorblindcheck} package + by Jakub Nowosad'. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetBrewer + url_git: '' +MetChem: + version: '0.4' + title: Chemical Structural Similarity Analysis + maintainer: Stefano Cacciatore + description: A new pipeline to explore chemical structural similarity across metabolite. + It allows to classify metabolites in structurally-related modules and identify + common shared functional groups. KODAMA algorithm is used to highlight structural + similarity between metabolites. See Cacciatore S, Tenori L, Luchinat C, Bennett + PR, MacIntyre DA. (2017) Bioinformatics , Cacciatore + S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA , + and Abdel-Shafy EA, Melak T, MacIntyre DA, Zadra G, Zerbini LF, Piazza S, Cacciatore + S. (2023) Bioinformatics Advances . + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetChem + url_git: '' +meteo: + version: 2.0-3 + title: RFSI & STRK Interpolation for Meteo and Environmental Variables + maintainer: Aleksandar Sekulić + description: Random Forest Spatial Interpolation (RFSI, Sekulić et al. (2020) ) + and spatio-temporal geostatistical (spatio-temporal regression Kriging (STRK)) + interpolation for meteorological (Kilibarda et al. (2014) , + Sekulić et al. (2020) ) and other environmental + variables. Contains global spatio-temporal models calculated using publicly available + data. + date_publication: '2024-04-18' + bug_reports: https://github.com/AleksandarSekulic/Rmeteo/issues + url: https://www.r-pkg.org/pkg/meteo + url_cran: https://CRAN.R-project.org/package=meteo + url_git: https://r-forge.r-project.org/projects/meteo/ +meteoEVT: + version: 0.1.0 + title: |- + Computation and Visualization of Energetic and Vortical + Atmospheric Quantities + maintainer: Laura Mack + description: Energy-Vorticity theory (EVT) is the fundamental theory to describe + processes in the atmosphere by combining conserved quantities from hydrodynamics + and thermodynamics. The package 'meteoEVT' provides functions to calculate many + energetic and vortical quantities, like potential vorticity, Bernoulli function + and dynamic state index (DSI) [e.g. Weber and Nevir, 2008, ], + for given gridded data, like ERA5 reanalyses. These quantities can be studied + directly or can be used for many applications in meteorology, e.g., the objective + identification of atmospheric fronts. For this purpose, separate function are + provided that allow the detection of fronts based on the thermic front parameter + [Hewson, 1998, ], the F diagnostic [Parfitt et + al., 2017, ] and the DSI [Mack et al., 2022, ]. + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meteoEVT + url_git: https://github.com/noctiluc3nt/meteoEVT +meteoForecast: + version: '0.56' + title: Numerical Weather Predictions + maintainer: Oscar Perpinan Lamigueiro + description: Access to several Numerical Weather Prediction services both in raster + format and as a time series for a location. Currently it works with GFS , + MeteoGalicia , NAM + , + and RAP . + date_publication: '2023-03-08' + bug_reports: https://github.com/oscarperpinan/meteoForecast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meteoForecast + url_git: https://github.com/oscarperpinan/meteoForecast +meteoland: + version: 2.2.3 + title: Landscape Meteorology Tools + maintainer: Miquel De Cáceres + description: Functions to estimate weather variables at any position of a landscape + [De Caceres et al. (2018) ]. + date_publication: '2025-01-28' + bug_reports: https://github.com/emf-creaf/meteoland/issues + url: https://emf-creaf.github.io/meteoland/ + url_cran: https://CRAN.R-project.org/package=meteoland + url_git: https://github.com/emf-creaf/meteoland +meteor: + version: 0.4-5 + title: Meteorological Data Manipulation + maintainer: Robert J. Hijmans + description: A set of functions for weather and climate data manipulation, and other + helper functions, to support dynamic ecological modeling, particularly crop and + crop disease modeling. + date_publication: '2023-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=meteor + url_git: '' +meteorits: + version: 0.1.1 + title: Mixture-of-Experts Modeling for Complex Non-Normal Distributions + maintainer: Florian Lecocq + description: |- + Provides a unified mixture-of-experts (ME) modeling and + estimation framework with several original and flexible ME models to + model, cluster and classify heterogeneous data in many complex + situations where the data are distributed according to non-normal, + possibly skewed distributions, and when they might be corrupted by + atypical observations. Mixtures-of-Experts models for complex and + non-normal distributions ('meteorits') are originally introduced and + written in 'Matlab' by Faicel Chamroukhi. The references are mainly the + following ones. The references are mainly the following ones. + Chamroukhi F., Same A., Govaert, G. and Aknin P. (2009) . + Chamroukhi F. (2010) . + Chamroukhi F. (2015) . + Chamroukhi F. (2015) . + Chamroukhi F. (2016) . + Chamroukhi F. (2016) . + Chamroukhi F. (2017) . + date_publication: '2020-01-10' + bug_reports: https://github.com/fchamroukhi/MEteorits/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meteorits + url_git: https://github.com/fchamroukhi/MEteorits +meteospain: + version: 0.2.0 + title: Access to Spanish Meteorological Stations Services + maintainer: Victor Granda + description: |- + Access to different Spanish meteorological stations data services and APIs (AEMET, SMC, MG, + Meteoclimatic...). + date_publication: '2024-10-17' + bug_reports: https://github.com/emf-creaf/meteospain/issues + url: https://emf-creaf.github.io/meteospain/ + url_cran: https://CRAN.R-project.org/package=meteospain + url_git: https://github.com/emf-creaf/meteospain +meteR: + version: '1.2' + title: |- + Fitting and Plotting Tools for the Maximum Entropy Theory of + Ecology (METE) + maintainer: Cory Merow + description: |- + Fit and plot macroecological patterns predicted by the Maximum + Entropy Theory of Ecology (METE). + date_publication: '2016-06-27' + bug_reports: https://github.com/cmerow/meteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=meteR + url_git: https://github.com/cmerow/meteR +metevalue: + version: 0.2.4 + title: E-Value in the Omics Data Association Studies + maintainer: Yifan Yang + description: 'In the omics data association studies, it is common to conduct the + p-value corrections to control the false significance. Beyond the P-value corrections, + E-value is recently studied to facilitate multiple testing correction based on + V. Vovk and R. Wang (2021) . This package provides E-value + calculation for DNA methylation data and RNA-seq data. Currently, five data formats + are supported: DNA methylation levels using DMR detection tools (BiSeq, DMRfinder, + MethylKit, Metilene and other DNA methylation tools) and RNA-seq data. The relevant + references are listed below: Katja Hebestreit and Hans-Ulrich Klein (2022) ; + Altuna Akalin et.al (2012) .' + date_publication: '2023-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metevalue + url_git: '' +MetGen: + version: '0.5' + title: Stochastic Weather Generator + maintainer: Nesrine Farhani + description: An adaptation of the multi-variable stochastic weather generator proposed + in 'Rglimclim' to perform gap-filling and temporal extension at sub-daily resolution. + Simulation is performed based on large scale variables and climatic observation + data that could be generated from different gauged stations having geographical + proximity. SWG relies on reanalyses. Multi-variable dependence is taking into + account by using the decomposition of the product rule (in statistics) into conditional + probabilities. See . + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetGen + url_git: '' +MethComp: + version: 1.30.2 + title: Analysis of Agreement in Method Comparison Studies + maintainer: Claus Thorn Ekstrøm + description: 'Methods (standard and advanced) for analysis of agreement between + measurement methods. These cover Bland-Altman plots, Deming regression, Lin''s + Total deviation index, and difference-on-average regression. See Carstensen B. + (2010) "Comparing Clinical Measurement Methods: A Practical Guide (Statistics + in Practice)" for more information.' + date_publication: '2024-10-20' + bug_reports: https://github.com/ekstroem/MethComp/issues + url: http://BendixCarstensen.com/MethComp/ + url_cran: https://CRAN.R-project.org/package=MethComp + url_git: '' +methcon5: + version: 0.1.0 + title: |- + Identify and Rank CpG DNA Methylation Conservation Along the + Human Genome + maintainer: Emil Hvitfeldt + description: |- + Identify and rank CpG DNA methylation conservation along the human + genome. Specifically it includes bootstrapping methods to provide ranking + which should adjust for the differences in length as without it short + regions tend to get higher conservation scores. + date_publication: '2019-12-20' + bug_reports: https://github.com/EmilHvitfeldt/methcon5/issues + url: '' + url_cran: https://CRAN.R-project.org/package=methcon5 + url_git: https://github.com/EmilHvitfeldt/methcon5 +MethEvolSIM: + version: 0.1.7 + title: |- + Simulate DNA Methylation Dynamics on Different Genomic + Structures along Genealogies + maintainer: Sara Castillo Vicente + description: |- + DNA methylation is an epigenetic modification involved in genomic stability, + gene regulation, development and disease. + DNA methylation occurs mainly through the addition of a methyl group to cytosines, + for example to cytosines in a CpG dinucleotide context (CpG stands for a cytosine followed by a guanine). + Tissue-specific methylation patterns lead to genomic regions with different characteristic + methylation levels. + E.g. in vertebrates CpG islands (regions with high CpG content) that are associated to promoter regions of + expressed genes tend to be unmethylated. + 'MethEvolSIM' is a model-based simulation software for the generation and modification + of cytosine methylation patterns along a given tree, which can be a genealogy of + cells within an organism, a coalescent tree of DNA sequences sampled from a population, or a species tree. + The simulations are based on an extension of the model of + Grosser & Metzler (2020) and allows for changes of + the methylation states at single cytosine positions as well as simultaneous changes of methylation + frequencies in genomic structures like CpG islands. + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MethEvolSIM + url_git: '' +MethodCompare: + version: 1.1.0 + title: Evaluating Bias and Precision in Method Comparison Studies + maintainer: Thomas Blomet + description: |- + Evaluate bias and precision in method comparison + studies. One provides measurements for each method and it takes care of + the estimates. Multiple plots to evaluate bias, precision and compare + methods. + date_publication: '2025-02-09' + bug_reports: https://github.com/UBERLULU/MethodCompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MethodCompare + url_git: https://github.com/UBERLULU/MethodCompare +MethodOpt: + version: 1.0.0 + title: |- + Advanced Method Optimization for Spectra-Generating Sampling and + Analysis Instrumentation + maintainer: Stephanie Gamble + description: A graphical user interface to apply an advanced method optimization + algorithm to various sampling and analysis instruments. This includes generating + experimental designs, uploading and viewing data, and performing various analyses + to determine the optimal method. Details of the techniques used in this package + are published in Gamble, Granger, & Mannion (2024) . + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MethodOpt + url_git: '' +MeTo: + version: 0.1.1 + title: Meteorological Tools + maintainer: Ullrich Dettmann + description: |- + Meteorological Tools following the FAO56 irrigation paper of Allen et al. (1998) [1]. + Functions for calculating: + reference evapotranspiration (ETref), + extraterrestrial radiation (Ra), + net radiation (Rn), + saturation vapor pressure (satVP), + global radiation (Rs), + soil heat flux (G), + daylight hours, + and more. + [1] Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9). + date_publication: '2022-05-25' + bug_reports: https://bitbucket.org/UlliD/meto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MeTo + url_git: '' +metools: + version: 1.0.0 + title: Macroeconomics Tools + maintainer: João Victor Gomes de Araujo Santana + description: |- + Provides a number of functions to facilitate the handling and production of reports using time series data. + The package was developed to be understandable for beginners, so some functions aim to transform processes that would be + complex into functions with a few lines. The main advantage of using the 'metools' package is the ease of producing reports and + working with time series using a few lines of code, so the code is clean and easy to understand/maintain. + Learn more about the 'metools' at . + date_publication: '2020-06-26' + bug_reports: '' + url: https://metoolsr.wordpress.com + url_cran: https://CRAN.R-project.org/package=metools + url_git: https://github.com/jvg0mes/metools +MetProc: + version: 1.0.1 + title: |- + Separate Metabolites into Likely Measurement Artifacts and True + Metabolites + maintainer: Mark Chaffin + description: |- + Split an untargeted metabolomics data set into a set of likely true + metabolites and a set of likely measurement artifacts. This process involves + comparing missing rates of pooled plasma samples and biological samples. The + functions assume a fixed injection order of samples where biological samples are + randomized and processed between intermittent pooled plasma samples. By comparing + patterns of missing data across injection order, metabolites that appear in blocks + and are likely artifacts can be separated from metabolites that seem to have + random dispersion of missing data. The two main metrics used are: 1. the number of + consecutive blocks of samples with present data and 2. the correlation of missing rates + between biological samples and flanking pooled plasma samples. + date_publication: '2016-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetProc + url_git: '' +metR: + version: 0.18.0 + title: Tools for Easier Analysis of Meteorological Fields + maintainer: Elio Campitelli + description: |- + Many useful functions and extensions for dealing + with meteorological data in the tidy data framework. Extends 'ggplot2' + for better plotting of scalar and vector fields and provides commonly + used analysis methods in the atmospheric sciences. + date_publication: '2025-02-24' + bug_reports: https://github.com/eliocamp/metR/issues + url: https://eliocamp.github.io/metR/ + url_cran: https://CRAN.R-project.org/package=metR + url_git: '' +metrica: + version: 2.1.0 + title: Prediction Performance Metrics + maintainer: Adrian A. Correndo + description: A compilation of more than 80 functions designed to quantitatively + and visually evaluate prediction performance of regression (continuous variables) + and classification (categorical variables) of point-forecast models (e.g. APSIM, + DSSAT, DNDC, supervised Machine Learning). For regression, it includes functions + to generate plots (scatter, tiles, density, & Bland-Altman plot), and to estimate + error metrics (e.g. MBE, MAE, RMSE), error decomposition (e.g. lack of accuracy-precision), + model efficiency (e.g. NSE, E1, KGE), indices of agreement (e.g. d, RAC), goodness + of fit (e.g. r, R2), adjusted correlation coefficients (e.g. CCC, dcorr), symmetric + regression coefficients (intercept, slope), and mean absolute scaled error (MASE) + for time series predictions. For classification (binomial and multinomial), it + offers functions to generate and plot confusion matrices, and to estimate performance + metrics such as accuracy, precision, recall, specificity, F-score, Cohen's Kappa, + G-mean, and many more. For more details visit the vignettes . + date_publication: '2024-06-30' + bug_reports: https://github.com/adriancorrendo/metrica/issues + url: https://adriancorrendo.github.io/metrica/ + url_cran: https://CRAN.R-project.org/package=metrica + url_git: '' +MetricGraph: + version: 1.4.0 + title: Random Fields on Metric Graphs + maintainer: David Bolin + description: Facilitates creation and manipulation of metric graphs, such as street + or river networks. Further facilitates operations and visualizations of data on + metric graphs, and the creation of a large class of random fields and stochastic + partial differential equations on such spaces. These random fields can be used + for simulation, prediction and inference. In particular, linear mixed effects + models including random field components can be fitted to data based on computationally + efficient sparse matrix representations. Interfaces to the R packages 'INLA' and + 'inlabru' are also provided, which facilitate working with Bayesian statistical + models on metric graphs. The main references for the methods are Bolin, Simas + and Wallin (2024) , Bolin, Kovacs, Kumar and Simas (2023) + and Bolin, Simas and Wallin (2023) + and . + date_publication: '2024-12-13' + bug_reports: https://github.com/davidbolin/MetricGraph/issues + url: https://davidbolin.github.io/MetricGraph/ + url_cran: https://CRAN.R-project.org/package=MetricGraph + url_git: '' +metricminer: + version: 1.0.0 + title: Mine Metrics from Common Places on the Web + maintainer: Candace Savonen + description: |- + Mine metrics on common places on the web through the power of their APIs (application programming interfaces). + It also helps make the data in a format that is easily used for a dashboard or other purposes. + There is an associated dashboard template and tutorials that are underdevelopment that help you + fully utilize 'metricminer'. + date_publication: '2025-02-19' + bug_reports: https://github.com/fhdsl/metricminer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metricminer + url_git: https://github.com/fhdsl/metricminer +Metrics: + version: 0.1.4 + title: Evaluation Metrics for Machine Learning + maintainer: Michael Frasco + description: |- + An implementation of evaluation metrics in R that are commonly + used in supervised machine learning. It implements metrics for + regression, time series, binary classification, classification, + and information retrieval problems. It has zero dependencies and + a consistent, simple interface for all functions. + date_publication: '2018-07-09' + bug_reports: https://github.com/mfrasco/Metrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Metrics + url_git: https://github.com/mfrasco/Metrics +MetricsWeighted: + version: 1.0.3 + title: Weighted Metrics and Performance Measures for Machine Learning + maintainer: Michael Mayer + description: |- + Provides weighted versions of several metrics and performance + measures used in machine learning, including average unit deviances of + the Bernoulli, Tweedie, Poisson, and Gamma distributions, see + Jorgensen B. (1997, ISBN: 978-0412997112). The package also contains + a weighted version of generalized R-squared, see e.g. Cohen, J. et al. + (2002, ISBN: 978-0805822236). Furthermore, 'dplyr' chains are + supported. + date_publication: '2023-11-16' + bug_reports: https://github.com/mayer79/MetricsWeighted/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MetricsWeighted + url_git: https://github.com/mayer79/MetricsWeighted +metrix: + version: 1.1.0 + title: Water Quality Metrics Calculator + maintainer: Juan Manuel Cabrera + description: |- + Calculate different metrics based on aquatic + macroinvertebrate density data (individuals per square meter) to + assess water quality (Prat N et al. 2009). + date_publication: '2022-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metrix + url_git: '' +metro: + version: 0.9.3 + title: Washington Metropolitan Area Transit Authority API + maintainer: Kiernan Nicholls + description: |- + The Washington Metropolitan Area Transit Authority is a + government agency operating light rail and passenger buses in the + Washington D.C. area. With a free developer account, access their + 'Metro Transparent Data Sets API' to + return data frames of transit data for easy analysis. + date_publication: '2024-03-11' + bug_reports: https://github.com/k5cents/metro/issues + url: https://k5cents.github.io/metro/ + url_cran: https://CRAN.R-project.org/package=metro + url_git: https://github.com/k5cents/metro +metRology: + version: 0.9-29-2 + title: Support for Metrological Applications + maintainer: Stephen L R Ellison + description: |- + Provides classes and calculation and plotting functions + for metrology applications, including measurement uncertainty estimation + and inter-laboratory metrology comparison studies. + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metRology + url_git: https://r-forge.r-project.org/projects/metrology/ +metropolis: + version: 0.1.8 + title: The Metropolis Algorithm + maintainer: Alexander Keil + description: |- + Learning and using the Metropolis algorithm for + Bayesian fitting of a generalized linear model. The package vignette + includes examples of hand-coding a logistic model using several + variants of the Metropolis algorithm. The package also contains R + functions for simulating posterior distributions of Bayesian + generalized linear model parameters using guided, adaptive, + guided-adaptive and random walk Metropolis algorithms. The random walk + Metropolis algorithm was originally described in Metropolis et al + (1953); . + date_publication: '2020-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=metropolis + url_git: '' +mets: + version: 1.3.5 + title: Analysis of Multivariate Event Times + maintainer: Klaus K. Holst + description: |- + Implementation of various statistical models for multivariate + event history data . Including multivariate + cumulative incidence models , and bivariate random + effects probit models (Liability models) . + Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray, + Ghosh-Lin, Binomial regression) with fast computation of influence functions. + date_publication: '2025-01-11' + bug_reports: https://github.com/kkholst/mets/issues + url: https://kkholst.github.io/mets/ + url_cran: https://CRAN.R-project.org/package=mets + url_git: '' +MetSizeR: + version: 2.0.0 + title: |- + A Shiny App for Sample Size Estimation in Metabolomic + Experiments + maintainer: Kate Finucane + description: |- + Provides a Shiny application to estimate the sample size required + for a metabolomic experiment to achieve a desired statistical power. + Estimation is possible with or without available data from a pilot study. + date_publication: '2021-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MetSizeR + url_git: '' +metsyn: + version: 0.1.2 + title: Interface with the Meteo France Synop Data API + maintainer: Paul Poncet + description: |- + Provides an interface with the Meteo France Synop data API + (see + for more information). + The Meteo France Synop data are made of meteorological data recorded + every three hours on 62 French meteorological stations. + date_publication: '2018-11-14' + bug_reports: https://github.com/paulponcet/metsyn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=metsyn + url_git: https://github.com/paulponcet/metsyn +mev: + version: '1.17' + title: Modelling of Extreme Values + maintainer: Leo Belzile + description: Various tools for the analysis of univariate, multivariate and functional + extremes. Exact simulation from max-stable processes [Dombry, Engelke and Oesting + (2016) , R-Pareto processes for various parametric + models, including Brown-Resnick (Wadsworth and Tawn, 2014, ) + and Extremal Student (Thibaud and Opitz, 2015, ). Threshold + selection methods, including Wadsworth (2016) , + and Northrop and Coleman (2014) . Multivariate + extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., + Coles (2001) . + date_publication: '2024-07-09' + bug_reports: https://github.com/lbelzile/mev/issues/ + url: https://lbelzile.github.io/mev/ + url_cran: https://CRAN.R-project.org/package=mev + url_git: https://github.com/lbelzile/mev/ +mevr: + version: 1.1.1 + title: Fitting the Metastatistical Extreme Value Distribution MEVD + maintainer: Harald Schellander + description: Extreme value analysis with the metastatistical extreme value distribution + MEVD (Marani and Ignaccolo, 2015, ) and some + of its variants. In particular, analysis can be performed with the simplified + metastatistical extreme value distribution SMEV (Marra et al., 2019, ) + and the temporal metastatistical extreme value distribution TMEV (Falkensteiner + et al., 2023, ). Parameters can be estimated with + probability weighted moments, maximum likelihood and least squares. The data can + also be left-censored prior to a fit. Density, distribution function, quantile + function and random generation for the MEVD, SMEV and TMEV are included. In addition, + functions for the calculation of return levels including confidence intervals + are provided. For a description of use cases please see the provided references. + date_publication: '2024-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mevr + url_git: '' +mewAvg: + version: 0.3.1 + title: A Fixed Memeory Moving Expanding Window Average + maintainer: Adam L. Pintar + description: |- + Compute the average of a sequence of random vectors + in a moving expanding window using a fixed amount of memory. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mewAvg + url_git: '' +MexBrewer: + version: 0.0.2 + title: |- + Color Palettes Inspired by Works of Mexican Painters and + Muralists + maintainer: Antonio Páez + description: |- + Color palettes inspired by the works of + Mexican painters and muralists. The package includes functions that + return vectors of colors and also functions to use color and fill + scales in 'ggplot2' visualizations. + date_publication: '2023-01-18' + bug_reports: https://github.com/paezha/MexBrewer/issues + url: https://paezha.github.io/MexBrewer/ + url_cran: https://CRAN.R-project.org/package=MexBrewer + url_git: https://github.com/paezha/MexBrewer +mexhaz: + version: '2.6' + title: Mixed Effect Excess Hazard Models + maintainer: Hadrien Charvat + description: 'Fit flexible (excess) hazard regression models with the possibility + of including non-proportional effects of covariables and of adding a random effect + at the cluster level (corresponding to a shared frailty). A detailed description + of the package functionalities is provided in Charvat and Belot (2021) .' + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mexhaz + url_git: '' +mexicolors: + version: 0.2.0 + title: Mexican Politics-Inspired Color Palette Generator + maintainer: Alejandro Platas-López + description: |- + A color palette generator inspired by Mexican politics, with + colors ranging from red on the left to gray in the middle and green on the + right. Palette options range from only a few colors to several colors, but with + discrete and continuous options to offer greatest flexibility to the user. + This package allows for a range of applications, from mapping brief discrete scales + (e.g., four colors for Morena, PRI, and PAN) to continuous interpolated arrays + including dozens of shades graded from red to green. + date_publication: '2021-09-07' + bug_reports: https://github.com/alexplatasl/mexicolors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mexicolors + url_git: '' +mExplorer: + version: 1.0.0 + title: |- + Identifying Master Gene Regulators from Gene Expression and + DNA-Binding Data + maintainer: Juri Reimand + description: 'The method ''m:Explorer'' associates a given list of target genes + (e.g. those involved in a biological process) to gene regulators such as transcription + factors. Transcription factors that bind DNA near significantly many target genes + or correlate with target genes in transcriptional (microarray or RNAseq data) + are selected. Selection of candidate master regulators is carried out using multinomial + regression models, likelihood ratio tests and multiple testing correction. Reference: + m:Explorer: multinomial regression models reveal positive and negative regulators + of longevity in yeast quiescence. Juri Reimand, Anu Aun, Jaak Vilo, Juan M Vaquerizas, + Juhan Sedman and Nicholas M Luscombe. Genome Biology (2012) 13:R55 .' + date_publication: '2017-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mExplorer + url_git: '' +MF.beta4: + version: 1.1.1 + title: Measuring Ecosystem Multi-Functionality and Its Decomposition + maintainer: Anne Chao + description: |- + Provide simple functions to (i) compute a class of + multi-functionality measures for a single ecosystem for given + function weights, (ii) decompose gamma multi-functionality + for pairs of ecosystems and K ecosystems (K can be greater than 2) + into a within-ecosystem component (alpha multi-functionality) + and an among-ecosystem component (beta multi-functionality). + In each case, the correlation between functions can be corrected for. + Based on biodiversity and ecosystem function data, this software + also facilitates graphics for assessing biodiversity-ecosystem + functioning relationships across scales. + date_publication: '2024-12-08' + bug_reports: https://github.com/AnneChao/MF.beta4/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MF.beta4 + url_git: https://github.com/AnneChao/MF.beta4 +mfaces: + version: 0.1-4 + title: |- + Fast Covariance Estimation for Multivariate Sparse Functional + Data + maintainer: Cai Li + description: |- + Multivariate functional principal component analysis via fast covariance estimation for + multivariate sparse functional data or longitudinal data proposed by Li, Xiao, and Luo (2020) . + date_publication: '2022-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mfaces + url_git: '' +MFAg: + version: '2.0' + title: Multiple Factor Analysis (MFA) + maintainer: Paulo Cesar Ossani + description: Performs Multiple Factor Analysis method for quantitative, categorical, + frequency and mixed data, in addition to generating a lot of graphics, also has + other useful functions. + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MFAg + url_git: '' +mFD: + version: 1.0.7 + title: |- + Compute and Illustrate the Multiple Facets of Functional + Diversity + maintainer: Camille Magneville + description: |- + Computing functional traits-based distances between pairs of + species for species gathered in assemblages allowing to build several + functional spaces. The package allows to compute functional diversity + indices assessing the distribution of species (and of their dominance) in a + given functional space for each assemblage and the overlap between + assemblages in a given functional space, see: Chao et al. (2018) + , Maire et al. (2015) , + Mouillot et al. (2013) , Mouillot et al. + (2014) , Ricotta and Szeidl (2009) + . Graphical outputs are included. + Visit the 'mFD' website for more information, documentation and examples. + date_publication: '2024-02-26' + bug_reports: https://github.com/CmlMagneville/mFD/issues + url: https://cmlmagneville.github.io/mFD/ + url_cran: https://CRAN.R-project.org/package=mFD + url_git: https://github.com/CmlMagneville/mFD +mfdb: + version: 7.3-1 + title: MareFrame DB Querying Library + maintainer: Jamie Lentin + description: |- + Creates and manages a PostgreSQL database suitable for storing fisheries data + and aggregating ready for use within a Gadget model. + See for more information. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mfdb + url_git: '' +MFDFA: + version: '1.1' + title: MultiFractal Detrended Fluctuation Analysis + maintainer: Mohamed Laib + description: |- + Contains the MultiFractal Detrended Fluctuation Analysis (MFDFA), + MultiFractal Detrended Cross-Correlation Analysis (MFXDFA), and the Multiscale + Multifractal Analysis (MMA). The MFDFA() function proposed in this package was + used in Laib et al. ( and ). + See references for more information. Interested users can find a parallel version of + the MFDFA() function on GitHub. + date_publication: '2019-04-15' + bug_reports: '' + url: https://mlaib.github.io + url_cran: https://CRAN.R-project.org/package=MFDFA + url_git: '' +mFDP: + version: 0.2.1 + title: Control of the Median of the FDP + maintainer: Jesse Hemerik + description: |- + Methods for controlling the median of the false discovery proportion (mFDP). + Depending on the method, simultaneous or non-simultaneous inference is provided. + The methods take a vector of p-values or test statistics as input. + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mFDP + url_git: '' +mfGARCH: + version: 0.2.1 + title: Mixed-Frequency GARCH Models + maintainer: Onno Kleen + description: 'Estimating GARCH-MIDAS (MIxed-DAta-Sampling) models (Engle, Ghysels, + Sohn, 2013, ) and related statistical inference, accompanying + the paper "Two are better than one: Volatility forecasting using multiplicative + component GARCH models" by Conrad and Kleen (2020, ). The + GARCH-MIDAS model decomposes the conditional variance of (daily) stock returns + into a short- and long-term component, where the latter may depend on an exogenous + covariate sampled at a lower frequency.' + date_publication: '2021-06-17' + bug_reports: https://github.com/onnokleen/mfGARCH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mfGARCH + url_git: https://github.com/onnokleen/mfGARCH/ +mFilter: + version: 0.1-5 + title: Miscellaneous Time Series Filters + maintainer: Mehmet Balcilar + description: |- + The mFilter package implements several time series filters useful + for smoothing and extracting trend and cyclical components of a + time series. The routines are commonly used in economics and + finance, however they should also be interest to other areas. + Currently, Christiano-Fitzgerald, Baxter-King, + Hodrick-Prescott, Butterworth, and trigonometric regression + filters are included in the package. + date_publication: '2019-06-04' + bug_reports: '' + url: http://www.mbalcilar.net + url_cran: https://CRAN.R-project.org/package=mFilter + url_git: '' +mFLICA: + version: 0.1.6 + title: Leadership-Inference Framework for Multivariate Time Series + maintainer: Chainarong Amornbunchornvej + description: A leadership-inference framework for multivariate time series. The + framework for multiple-faction-leadership inference from coordinated activities + or 'mFLICA' uses a notion of a leader as an individual who initiates collective + patterns that everyone in a group follows. Given a set of time series of individual + activities, our goal is to identify periods of coordinated activity, find factions + of coordination if more than one exist, as well as identify leaders of each faction. + For each time step, the framework infers following relations between individual + time series, then identifying a leader of each faction whom many individuals follow + but it follows no one. A faction is defined as a group of individuals that everyone + follows the same leader. 'mFLICA' reports following relations, leaders of factions, + and members of each faction for each time step. Please see Chainarong Amornbunchornvej + and Tanya Berger-Wolf (2018) for methodology + and Chainarong Amornbunchornvej (2021) for software + when referring to this package in publications. + date_publication: '2024-06-11' + bug_reports: https://github.com/DarkEyes/mFLICA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mFLICA + url_git: https://github.com/DarkEyes/mFLICA +MFO: + version: 0.1.0 + title: Maximal Fat Oxidation and Kinetics Calculation + maintainer: Jorge R Fernandez-Santos + description: |- + Calculate the maximal fat oxidation, the exercise intensity that elicits the + maximal fat oxidation and the SIN model to represent the fat oxidation kinetics. + Three variables can be obtained from the SIN model: dilatation, symmetry and translation. + Examples of these methods can be found in Montes de Oca et al (2021) + and Chenevière et al. (2009) . + date_publication: '2022-02-11' + bug_reports: https://github.com/JorgeDelro/MFO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MFO + url_git: https://github.com/JorgeDelro/MFO +mfp: + version: 1.5.4.1 + title: Multivariable Fractional Polynomials + maintainer: Georg Heinze + description: Fractional polynomials are used to represent curvature in regression + models. A key reference is Royston and Altman, 1994. + date_publication: '2024-05-14' + bug_reports: https://github.com/georgheinze/mfp/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=mfp + url_git: '' +mfp2: + version: 1.0.0 + title: Multivariable Fractional Polynomial Models with Extensions + maintainer: Edwin Kipruto + description: Multivariable fractional polynomial algorithm simultaneously selects + variables and functional forms in both generalized linear models and Cox proportional + hazard models. Key references for this algorithm are Royston and Altman (1994) + and Sauerbrei and Royston (2008, ISBN:978-0-470-02842-1). In addition, it can + model a 'sigmoid' relationship between variable x and an outcome variable y using + the approximate cumulative distribution transformation proposed by Royston (2014) + . This feature distinguishes it from a standard + fractional polynomial function, which lacks the ability to achieve such modeling. + date_publication: '2023-11-14' + bug_reports: https://github.com/EdwinKipruto/mfp2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mfp2 + url_git: https://github.com/EdwinKipruto/mfp2 +MFPCA: + version: 1.3-10 + title: |- + Multivariate Functional Principal Component Analysis for Data + Observed on Different Dimensional Domains + maintainer: Clara Happ-Kurz + description: |- + Calculate a multivariate functional principal component analysis + for data observed on different dimensional domains. The estimation algorithm + relies on univariate basis expansions for each element of the multivariate + functional data (Happ & Greven, 2018) . + Multivariate and univariate functional data objects are + represented by S4 classes for this type of data implemented in the package + 'funData'. For more details on the general concepts of both packages and a case + study, see Happ-Kurz (2020) . + date_publication: '2022-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MFPCA + url_git: https://github.com/ClaraHapp/MFPCA +mfpp: + version: 0.0.8 + title: '''Matrix-Based Flexible Project Planning''' + maintainer: Zsolt T. Kosztyan + description: Matrix-Based Flexible Project Planning. This package models, plans, + and schedules flexible, such as agile, extreme, and hybrid project plans. The + package contains project planning, scheduling, and risk assessment functions. + Kosztyan (2022) . + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mfpp + url_git: https://github.com/kzst/mfpp +MFT: + version: '2.0' + title: The Multiple Filter Test for Change Point Detection + maintainer: Michael Messer + description: Provides statistical tests and algorithms for the detection of change + points in time series and point processes - particularly for changes in the mean + in time series and for changes in the rate and in the variance in point processes. + References - Michael Messer, Marietta Kirchner, Julia Schiemann, Jochen Roeper, + Ralph Neininger and Gaby Schneider (2014), A multiple filter test for the detection + of rate changes in renewal processes with varying variance . + Stefan Albert, Michael Messer, Julia Schiemann, Jochen Roeper, Gaby Schneider + (2017), Multi-scale detection of variance changes in renewal processes in the + presence of rate change points . Michael Messer, Kaue + M. Costa, Jochen Roeper and Gaby Schneider (2017), Multi-scale detection of rate + changes in spike trains with weak dependencies . + Michael Messer, Stefan Albert and Gaby Schneider (2018), The multiple filter test + for change point detection in time series . Michael + Messer, Hendrik Backhaus, Albrecht Stroh and Gaby Schneider (2019+) Peak detection + in time series. + date_publication: '2019-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MFT + url_git: '' +MfUSampler: + version: 1.1.0 + title: Multivariate-from-Univariate (MfU) MCMC Sampler + maintainer: Alireza S. Mahani + description: |- + Convenience functions for multivariate MCMC using univariate samplers including: + slice sampler with stepout and shrinkage (Neal (2003) ), + adaptive rejection sampler (Gilks and Wild (1992) ), + adaptive rejection Metropolis (Gilks et al (1995) ), and + univariate Metropolis with Gaussian proposal. + date_publication: '2022-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MfUSampler + url_git: '' +mfx: + version: 1.2-2 + title: Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs + maintainer: Alan Fernihough + description: |- + Estimates probit, logit, Poisson, negative binomial, + and beta regression models, returning their marginal effects, odds ratios, + or incidence rate ratios as an output. + Greene (2008, pp. 780-7) provides a textbook introduction to this topic. + date_publication: '2019-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mfx + url_git: '' +MG1StationaryProbability: + version: 0.1.2 + title: Computes Stationary Distribution for M/G/1 Queuing System + maintainer: Olga Zoldaka + description: |- + The idea of a computational algorithm described in the article by Andronov M. et al. (2022) . + The purpose of this package is to automate computations for a Markov-Modulated M/G/1 queuing system with alternating Poisson flow of arrivals. It offers a set of functions to calculate various mean indices of the system, including mean flow intensity, mean service busy and idle times, and the system's stationary probability. + date_publication: '2023-06-13' + bug_reports: https://github.com/MashroomMole/MG1StationaryProbability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MG1StationaryProbability + url_git: https://github.com/MashroomMole/MG1StationaryProbability +mgarchBEKK: + version: 0.0.5 + title: |- + Simulating, Estimating and Diagnosing MGARCH (BEKK and mGJR) + Processes + maintainer: Vehbi Sinan Tunalioglu + description: |- + Procedures to simulate, estimate and diagnose MGARCH + processes of BEKK and multivariate GJR (bivariate asymmetric GARCH + model) specification. + date_publication: '2022-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgarchBEKK + url_git: https://github.com/vst/mgarchBEKK/ +MGBT: + version: 1.0.7 + title: Multiple Grubbs-Beck Low-Outlier Test + maintainer: William H. Asquith + description: |- + Compute the multiple Grubbs-Beck low-outlier test on positively distributed + data and utilities for noninterpretive U.S. Geological Survey annual peak-streamflow + data processing discussed in Cohn et al. (2013) and + England et al. (2017) . + date_publication: '2021-07-21' + bug_reports: '' + url: https://doi.org/10.5066/P9CW9EF0 + url_cran: https://CRAN.R-project.org/package=MGBT + url_git: '' +mgc: + version: 2.0.2 + title: Multiscale Graph Correlation + maintainer: Eric Bridgeford + description: Multiscale Graph Correlation (MGC) is a framework developed by Vogelstein + et al. (2019) that extends global correlation procedures + to be multiscale; consequently, MGC tests typically require far fewer samples + than existing methods for a wide variety of dependence structures and dimensionalities, + while maintaining computational efficiency. Moreover, MGC provides a simple and + elegant multiscale characterization of the potentially complex latent geometry + underlying the relationship. + date_publication: '2020-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgc + url_git: https://github.com/neurodata/r-mgc +mgcv: + version: 1.9-1 + title: |- + Mixed GAM Computation Vehicle with Automatic Smoothness + Estimation + maintainer: Simon Wood + description: |- + Generalized additive (mixed) models, some of their extensions and + other generalized ridge regression with multiple smoothing + parameter estimation by (Restricted) Marginal Likelihood, + Generalized Cross Validation and similar, or using iterated + nested Laplace approximation for fully Bayesian inference. See + Wood (2017) for an overview. + Includes a gam() function, a wide variety of smoothers, 'JAGS' + support and distributions beyond the exponential family. + date_publication: '2023-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgcv + url_git: '' +mgcViz: + version: 0.1.11 + title: Visualisations for Generalized Additive Models + maintainer: Matteo Fasiolo + description: Extension of the 'mgcv' package, providing visual tools for Generalized + Additive Models that exploit the additive structure of such models, scale to large + data sets and can be used in conjunction with a wide range of response distributions. + The focus is providing visual methods for better understanding the model output + and for aiding model checking and development beyond simple exponential family + regression. The graphical framework is based on the layering system provided by + 'ggplot2'. + date_publication: '2023-10-06' + bug_reports: https://github.com/mfasiolo/mgcViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mgcViz + url_git: https://github.com/mfasiolo/mgcViz +MGDrivE: + version: 1.6.0 + title: Mosquito Gene Drive Explorer + maintainer: Héctor Manuel Sánchez Castellanos + description: |- + Provides a model designed to be a reliable testbed where various gene + drive interventions for mosquito-borne diseases control. It is being developed to + accommodate the use of various mosquito-specific gene drive systems within a + population dynamics framework that allows migration of individuals between patches + in landscape. Previous work developing the population dynamics can be found in Deredec et al. + (2001) and Hancock & Godfray (2007) , + and extensions to accommodate CRISPR homing dynamics in Marshall et al. (2017) + . + date_publication: '2020-10-05' + bug_reports: https://github.com/MarshallLab/MGDrivE/issues + url: https://marshalllab.github.io/MGDrivE/ + url_cran: https://CRAN.R-project.org/package=MGDrivE + url_git: '' +MGDrivE2: + version: 2.1.0 + title: Mosquito Gene Drive Explorer 2 + maintainer: Agastya Mondal + description: |- + A simulation modeling framework which significantly extends capabilities from the + 'MGDrivE' simulation package via a new mathematical and computational framework based on stochastic Petri nets. + For more information about 'MGDrivE', see our publication: Sánchez et al. (2019) + Some of the notable capabilities of 'MGDrivE2' include: incorporation of human populations, + epidemiological dynamics, time-varying parameters, and a continuous-time simulation + framework with various sampling algorithms for both deterministic and stochastic interpretations. + 'MGDrivE2' relies on the genetic inheritance structures provided in package 'MGDrivE', so we + suggest installing that package initially. + date_publication: '2023-03-04' + bug_reports: https://github.com/MarshallLab/MGDrivE/issues + url: https://marshalllab.github.io/MGDrivE/docs_v2/index.html + url_cran: https://CRAN.R-project.org/package=MGDrivE2 + url_git: '' +mgee2: + version: '0.6' + title: Marginal Analysis of Misclassified Longitudinal Ordinal Data + maintainer: Yuliang Xu + description: |- + Three estimating equation methods are provided in this package for marginal analysis of longitudinal ordinal data with misclassified responses and covariates. + The naive analysis which is solely based on the observed data without adjustment may lead to bias. + The corrected generalized estimating equations (GEE2) method which is unbiased requires the misclassification parameters to be known beforehand. + The corrected generalized estimating equations (GEE2) with validation subsample method estimates the misclassification parameters based on a given + validation set. This package is an implementation + of Chen (2013) . + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgee2 + url_git: '' +mggd: + version: 1.3.3 + title: |- + Multivariate Generalised Gaussian Distribution; Kullback-Leibler + Divergence + maintainer: Pierre Santagostini + description: Distance between multivariate generalised Gaussian distributions, as + presented by N. Bouhlel and A. Dziri (2019) . Manipulation + of multivariate generalised Gaussian distributions (methods presented by Gomez, + Gomez-Villegas and Marin (1998) and Pascal, Bombrun, + Tourneret and Berthoumieu (2013) ). + date_publication: '2024-12-23' + bug_reports: https://forgemia.inra.fr/imhorphen/mggd/-/issues + url: https://forgemia.inra.fr/imhorphen/mggd + url_cran: https://CRAN.R-project.org/package=mggd + url_git: '' +mgi.report.reader: + version: 0.1.3 + title: Read Mouse Genome Informatics Reports + maintainer: Ramiro Magno + description: |- + Provides readers for easy and consistent importing of + Mouse Genome Informatics (MGI) report files: + . These data + are provided by Baldarelli RM, Smith CL, Ringwald M, Richardson JE, Bult CJ, + Mouse Genome Informatics Group (2024) . + date_publication: '2024-07-07' + bug_reports: https://github.com/patterninstitute/mgi.report.reader/issues + url: https://www.pattern.institute/mgi.report.reader/ + url_cran: https://CRAN.R-project.org/package=mgi.report.reader + url_git: https://github.com/patterninstitute/mgi.report.reader/ +MGL: + version: '1.1' + title: Module Graphical Lasso + maintainer: Safiye Celik + description: 'An aggressive dimensionality reduction and network estimationtechnique + for a high-dimensional Gaussian graphical model (GGM). Pleaserefer to: + Efficient Dimensionality Reduction for High-Dimensional NetworkEstimation, + Safiye Celik, Benjamin A. Logsdon, Su-In Lee, Proceedings ofThe 31st International + Conference on Machine Learning, 2014, p. 1953--1961.' + date_publication: '2014-11-05' + bug_reports: '' + url: https://sites.google.com/a/cs.washington.edu/mgl/ + url_cran: https://CRAN.R-project.org/package=MGL + url_git: '' +mglasso: + version: 0.1.2 + title: Multiscale Graphical Lasso + maintainer: Edmond Sanou + description: |- + Inference of Multiscale graphical models with neighborhood + selection approach. The method is based on solving a convex + optimization problem combining a Lasso and fused-group Lasso + penalties. This allows to infer simultaneously a conditional + independence graph and a clustering partition. The optimization is + based on the Continuation with Nesterov smoothing in a + Shrinkage-Thresholding Algorithm solver (Hadj-Selem et al. 2018) + implemented in python. + date_publication: '2022-09-08' + bug_reports: '' + url: https://desanou.github.io/mglasso/ + url_cran: https://CRAN.R-project.org/package=mglasso + url_git: '' +MGLM: + version: 0.2.1 + title: Multivariate Response Generalized Linear Models + maintainer: Juhyun Kim + description: 'Provides functions that (1) fit multivariate discrete distributions, + (2) generate random numbers from multivariate discrete distributions, and (3) + run regression and penalized regression on the multivariate categorical response + data. Implemented models include: multinomial logit model, Dirichlet multinomial + model, generalized Dirichlet multinomial model, and negative multinomial model. + Making the best of the minorization-maximization (MM) algorithm and Newton-Raphson + method, we derive and implement stable and efficient algorithms to find the maximum + likelihood estimates. On a multi-core machine, multi-threading is supported.' + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MGLM + url_git: '' +mglmn: + version: 0.1.0 + title: Model Averaging for Multivariate GLM with Null Models + maintainer: Masatoshi Katabuchi + description: Tools for univariate and multivariate generalized linear models with + model averaging and null model technique. + date_publication: '2020-07-29' + bug_reports: https://github.com/mattocci27/mglmn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mglmn + url_git: https://github.com/mattocci27/mglmn +mgm: + version: 1.2-14 + title: Estimating Time-Varying k-Order Mixed Graphical Models + maintainer: Jonas Haslbeck + description: Estimation of k-Order time-varying Mixed Graphical Models and mixed + VAR(p) models via elastic-net regularized neighborhood regression. For details + see Haslbeck & Waldorp (2020) . + date_publication: '2023-09-05' + bug_reports: https://github.com/jmbh/mgm/issues + url: https://www.jstatsoft.org/article/view/v093i08 + url_cran: https://CRAN.R-project.org/package=mgm + url_git: '' +MGMM: + version: 1.0.1.1 + title: Missingness Aware Gaussian Mixture Models + maintainer: Zachary McCaw + description: Parameter estimation and classification for Gaussian Mixture Models + (GMMs) in the presence of missing data. This package complements existing implementations + by allowing for both missing elements in the input vectors and full (as opposed + to strictly diagonal) covariance matrices. Estimation is performed using an expectation + conditional maximization algorithm that accounts for missingness of both the cluster + assignments and the vector components. The output includes the marginal cluster + membership probabilities; the mean and covariance of each cluster; the posterior + probabilities of cluster membership; and a completed version of the input data, + with missing values imputed to their posterior expectations. For additional details, + please see McCaw ZR, Julienne H, Aschard H. "Fitting Gaussian mixture models on + incomplete data." . + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MGMM + url_git: '' +MGMS2: + version: 1.0.2 + title: '''MGMS2'' for Polymicrobial Samples' + maintainer: George Wendt + description: 'A glycolipid mass spectrometry technology has the potential to accurately + identify individual bacterial species from polymicrobial samples. To develop bacterial + identification algorithms (e.g. machine learning) using this glycolipid technology, + it is necessary to generate a large number of various in-silico polymicrobial + mass spectra that are similar to real mass spectra. ''MGMS2'' (Membrane Glycolipid + Mass Spectrum Simulator) generates such in-silico mass spectra, considering errors + in m/z (mass-to-charge ratio) and variances of intensity values, occasions of + missing signature ions, and noise peaks. It estimates summary statistics of monomicrobial + mass spectra for each strain or species and simulates polymicrobial glycolipid + mass spectra using the summary statistics of monomicrobial mass spectra. References: + Ryu, S.Y., Wendt, G.A., Chandler, C.E., Ernst, R.K. and Goodlett, D.R. (2019) + "Model-based Spectral Library Approach for + Bacterial Identification via Membrane Glycolipids." Gibb, S. and Strimmer, K. + (2012) "MALDIquant: a versatile R package + for the analysis of mass spectrometry data."' + date_publication: '2020-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MGMS2 + url_git: '' +MGPSDK: + version: 1.0.0 + title: Interact with the Maxar 'MGP' Application Programming Interfaces + maintainer: Nathan Carr + description: |- + Provides an interface to the Maxar Geospatial Platform (MGP) Application Programming Interface. + It facilitates imagery searches using the MGP Streaming Application Programming Interface via the Web Feature Service (WFS) method, and supports image downloads through Web Map Service (WMS) and Web Map Tile Service (WMTS) + Open Geospatial Consortium (OGC) methods. + Additionally, it integrates with the Maxar Geospatial Platform Basemaps Application Programming Interface for accessing Maxar basemaps imagery and seamlines. + The package also offers seamless integration with the Maxar Geospatial Platform Discovery Application Programming Interface, allowing users to search, filter, and sort Maxar content, + while retrieving detailed metadata in formats like SpatioTemporal Asset Catalog (STAC) and GeoJSON. + date_publication: '2023-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MGPSDK + url_git: '' +mgpStreamingSDK: + version: 0.2.0 + title: Interact with the Maxar MGP Streaming API + maintainer: Nathan Carr + description: This grants the functionality of the Maxar Geospatial Platform (MGP) + Streaming API. It can search for images using the WFS method. It can Download + images using WMS WMTS. It can also Download a full resolution image. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgpStreamingSDK + url_git: '' +MGSDA: + version: 1.6.1 + title: Multi-Group Sparse Discriminant Analysis + maintainer: Irina Gaynanova + description: Implements Multi-Group Sparse Discriminant Analysis proposal of I.Gaynanova, + J.Booth and M.Wells (2016), Simultaneous sparse estimation of canonical vectors + in the p>>N setting, JASA . + date_publication: '2023-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MGSDA + url_git: '' +mgss: + version: '1.2' + title: A Matrix-Free Multigrid Preconditioner for Spline Smoothing + maintainer: Martin Siebenborn + description: Data smoothing with penalized splines is a popular method and is well + established for one- or two-dimensional covariates. The extension to multiple + covariates is straightforward but suffers from exponentially increasing memory + requirements and computational complexity. This toolbox provides a matrix-free + implementation of a conjugate gradient (CG) method for the regularized least squares + problem resulting from tensor product B-spline smoothing with multivariate and + scattered data. It further provides matrix-free preconditioned versions of the + CG-algorithm where the user can choose between a simpler diagonal preconditioner + and an advanced geometric multigrid preconditioner. The main advantage is that + all algorithms are performed matrix-free and therefore require only a small amount + of memory. For further detail see Siebenborn & Wagner (2021). + date_publication: '2021-05-10' + bug_reports: https://github.com/SplineSmoothing/MGSS + url: '' + url_cran: https://CRAN.R-project.org/package=mgss + url_git: '' +mgsub: + version: 1.7.3 + title: Safe, Multiple, Simultaneous String Substitution + maintainer: Mark Ewing + description: |- + Designed to enable simultaneous substitution in strings in a safe fashion. + Safe means it does not rely on placeholders (which can cause errors in same length matches). + date_publication: '2021-07-28' + bug_reports: https://github.com/bmewing/mgsub/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mgsub + url_git: '' +mgwnbr: + version: 0.2.0 + title: Multiscale Geographically Weighted Negative Binomial Regression + maintainer: Juliana Rosa + description: |- + Fits a geographically weighted regression model with different scales + for each covariate. Uses the negative binomial distribution as default, + but also accepts the normal, Poisson, or logistic distributions. + Can fit the global versions of each regression and also the geographically + weighted alternatives with only one scale, since they are all particular + cases of the multiscale approach. + Hanchen Yu (2024). "Exploring Multiscale Geographically Weighted Negative Binomial Regression", Annals of the American Association of Geographers . + Fotheringham AS, Yang W, Kang W (2017). "Multiscale Geographically Weighted Regression (MGWR)", Annals of the American Association of Geographers . + Da Silva AR, Rodrigues TCV (2014). "Geographically Weighted Negative Binomial Regression - incorporating overdispersion", Statistics and Computing . + date_publication: '2024-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgwnbr + url_git: '' +mgwrhw: + version: 1.1.1.5 + title: |- + Displays GWR (Geographically Weighted Regression) and Mixed GWR + Output and Map + maintainer: Asy-Syaja'ul Haqqul Amin + description: |- + Display processing results using the GWR (Geographically Weighted Regression) method, display maps, and show the results of the Mixed GWR (Mixed Geographically Weighted Regression) model which automatically selects global variables based on variability between regions. This function refers to + Yasin, & Purhadi. (2012). "Mixed Geographically Weighted Regression Model (Case Study the Percentage of Poor Households in Mojokerto 2008)". European Journal of Scientific Research, 188-196. + . + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgwrhw + url_git: '' +mgwrsar: + version: '1.1' + title: GWR, Mixed GWR and Multiscale GWR with Spatial Autocorrelation + maintainer: Ghislain Geniaux + description: Functions for computing (Mixed and Multiscale) Geographically Weighted + Regression with spatial autocorrelation, Geniaux and Martinetti (2017) . + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mgwrsar + url_git: '' +mhazard: + version: 0.2.3 + title: |- + Nonparametric and Semiparametric Methods for Multivariate + Failure Time Data + maintainer: Eric Bair + description: |- + Nonparametric survival function estimates and semiparametric + regression for the multivariate failure time data with right-censoring. + For nonparametric survival function estimates, the Volterra, Dabrowska, + and Prentice-Cai estimates for bivariate failure time data may be + computed as well as the Dabrowska estimate for the trivariate failure + time data. Bivariate marginal hazard rate regression can be fitted for + the bivariate failure time data. Functions are also provided to compute + (bootstrap) confidence intervals and plot the estimates of the bivariate + survival function. For details, see "The Statistical Analysis of + Multivariate Failure Time Data: A Marginal Modeling Approach", Prentice, + R., Zhao, S. (2019, ISBN: 978-1-4822-5657-4), CRC Press. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mhazard + url_git: '' +mhcnuggetsr: + version: '1.1' + title: Call MHCnuggets + maintainer: Richèl J.C. Bilderbeek + description: |2- + + MHCnuggets () is a Python + tool to predict MHC class I and MHC class II epitopes. + This package allows one to call MHCnuggets from R. + date_publication: '2020-11-04' + bug_reports: https://github.com/richelbilderbeek/mhcnuggetsr + url: '' + url_cran: https://CRAN.R-project.org/package=mhcnuggetsr + url_git: https://github.com/richelbilderbeek/mhcnuggetsr/ +MHCtools: + version: 1.5.5 + title: Analysis of MHC Data in Non-Model Species + maintainer: Jacob Roved + description: |- + Fifteen tools for bioinformatics processing and analysis of major + histocompatibility complex (MHC) data. The functions are tailored for amplicon data + sets that have been filtered using the dada2 method (for more information on + dada2, visit ), but even other types of data + sets can be analyzed. + The ReplMatch() function matches replicates in data sets in order to evaluate + genotyping success. + The GetReplTable() and GetReplStats() functions perform such an evaluation. + The CreateFas() function creates a fasta file with all the sequences in the data + set. + The CreateSamplesFas() function creates individual fasta files for each sample in + the data set. + The DistCalc() function calculates Grantham, Sandberg, or p-distances from pairwise + comparisons of all sequences in a data set, and mean distances of all pairwise + comparisons within each sample in a data set. The function additionally outputs five + tables with physico-chemical z-descriptor values (based on Sandberg et al. 1998) for + each amino acid position in all sequences in the data set. These tables may be useful + for further downstream analyses, such as estimation of MHC supertypes. + The BootKmeans() function is a wrapper for the kmeans() function of the 'stats' + package, which allows for bootstrapping. Bootstrapping k-estimates may be + desirable in data sets, where e.g. BIC- vs. k-values do not produce clear + inflection points ("elbows"). BootKmeans() performs multiple runs of kmeans() and + estimates optimal k-values based on a user-defined threshold of BIC reduction. The + method is an automated and bootstrapped version of visually inspecting elbow plots + of BIC- vs. k-values. + The ClusterMatch() function is a tool for evaluating whether different k-means() + clustering models identify similar clusters, and summarize bootstrap model stats as + means for different estimated values of k. It is designed to take files produced by + the BootKmeans() function as input, but other data can be analyzed if the + descriptions of the required data formats are observed carefully. + The PapaDiv() function compares parent pairs in the data set and calculate their + joint MHC diversity, taking into account sequence variants that occur in both + parents. + The HpltFind() function infers putative haplotypes from families in the data + set. + The GetHpltTable() and GetHpltStats() functions evaluate the accuracy of + the haplotype inference. + The CreateHpltOccTable() function creates a binary (logical) haplotype-sequence + occurrence matrix from the output of HpltFind(), for easy overview of which + sequences are present in which haplotypes. + The HpltMatch() function compares haplotypes to help identify overlapping and + potentially identical types. + The NestTablesXL() function translates the output from HpltFind() to an Excel + workbook, that provides a convenient overview for evaluation and curating of the + inferred putative haplotypes. + date_publication: '2025-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MHCtools + url_git: '' +MHD: + version: 0.1.2 + title: Metric Halfspace Depth + maintainer: Xiongtao Dai + description: Metric halfspace depth for object data, generalizing Tukey's depth + for Euclidean data. Implementing the method described in Dai and Lopez-Pintado + (2022) . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MHD + url_git: '' +MHDA: + version: '1.4' + title: Massive Hierarchically Data Analysis + maintainer: Yarong Yang + description: Three main functions about analyzing massive data (missing observations + are allowed) considered from multiple layers of categories. + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MHDA + url_git: '' +mHG: + version: '1.1' + title: Minimum-Hypergeometric Test + maintainer: Kobi Perl + description: 'Runs a minimum-hypergeometric (mHG) test as described in: Eden, E. + (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa.' + date_publication: '2017-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mHG + url_git: '' +mHMMbayes: + version: 1.1.0 + title: Multilevel Hidden Markov Models Using Bayesian Estimation + maintainer: Emmeke Aarts + description: |- + An implementation of the multilevel (also known as mixed or random + effects) hidden Markov model using Bayesian estimation in R. The multilevel + hidden Markov model (HMM) is a generalization of the well-known hidden + Markov model, for the latter see Rabiner (1989) . The + multilevel HMM is tailored to accommodate (intense) longitudinal data of + multiple individuals simultaneously, see e.g., de Haan-Rietdijk et al. + . Using a multilevel framework, we allow + for heterogeneity in the model parameters (transition probability matrix and + conditional distribution), while estimating one overall HMM. The model can + be fitted on multivariate data with either a categorical, normal, or Poisson + distribution, and include individual level covariates (allowing for e.g., + group comparisons on model parameters). Parameters are estimated using + Bayesian estimation utilizing the forward-backward recursion within a hybrid + Metropolis within Gibbs sampler. Missing data (NA) in the dependent + variables is accommodated assuming MAR. The package also includes various + visualization options, a function to simulate data, and a function to obtain + the most likely hidden state sequence for each individual using the Viterbi + algorithm. + date_publication: '2024-04-01' + bug_reports: https://github.com/emmekeaarts/mHMMbayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mHMMbayes + url_git: '' +Mhorseshoe: + version: 0.1.3 + title: Approximate Algorithm for Horseshoe Prior + maintainer: Kang Mingi + description: |- + Provides exact and approximate algorithms for the horseshoe prior + in linear regression models, which were proposed by Johndrow et al. (2020) + . + date_publication: '2024-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mhorseshoe + url_git: '' +mhsmm: + version: 0.4.21 + title: Inference for Hidden Markov and Semi-Markov Models + maintainer: Jared O'Connell + description: Parameter estimation and prediction for hidden Markov and semi-Markov + models for data with multiple observation sequences. Suitable for equidistant + time series data, with multivariate and/or missing data. Allows user defined emission + distributions. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mhsmm + url_git: '' +mhtboot: + version: 1.3.3 + title: Multiple Hypothesis Test Based on Distribution of p Values + maintainer: Abhirup Mallik + description: |- + A framework for multiple hypothesis testing based on distribution + of p values. It is well known that the p values come from different + distribution for null and alternatives, in this package we provide + functions to detect that change. We provide a method for using the change + in distribution of p values as a way to detect the true signals in the + data. + date_publication: '2016-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mhtboot + url_git: '' +MHTdiscrete: + version: 1.0.1 + title: Multiple Hypotheses Testing for Discrete Data + maintainer: Yalin Zhu + description: |- + A comprehensive tool for almost all existing multiple testing + methods for discrete data. The package also provides some novel multiple testing + procedures controlling FWER/FDR for discrete data. Given discrete p-values + and their domains, the [method].p.adjust function returns adjusted p-values, + which can be used to compare with the nominal significant level alpha and make + decisions. For users' convenience, the functions also provide the output option + for printing decision rules. + date_publication: '2018-12-15' + bug_reports: https://github.com/allenzhuaz/MHTdiscrete/issues + url: https://allen.shinyapps.io/MTPs/ + url_cran: https://CRAN.R-project.org/package=MHTdiscrete + url_git: '' +MHTmult: + version: 0.1.0 + title: |- + Multiple Hypotheses Testing for Multiple Families/Groups + Structure + maintainer: Yalin Zhu + description: |- + A Comprehensive tool for almost all existing multiple testing + methods for multiple families. The package summarizes the existing methods for multiple families multiple testing procedures (MTPs) such as double FDR, group Benjamini-Hochberg (GBH) procedure and average FDR controlling procedure. The package also provides some novel multiple testing procedures using selective inference idea. + date_publication: '2017-05-01' + bug_reports: https://github.com/allenzhuaz/MHTmult/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MHTmult + url_git: '' +MHTrajectoryR: + version: 1.0.1 + title: |- + Bayesian Model Selection in Logistic Regression for the + Detection of Adverse Drug Reactions + maintainer: Mohammed Sedki + description: Spontaneous adverse event reports have a high potential for detecting + adverse drug reactions. However, due to their dimension, the analysis of such + databases requires statistical methods. We propose to use a logistic regression + whose sparsity is viewed as a model selection challenge. Since the model space + is huge, a Metropolis-Hastings algorithm carries out the model selection by maximizing + the BIC criterion. + date_publication: '2016-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MHTrajectoryR + url_git: '' +mhurdle: + version: 1.3-1 + title: Multiple Hurdle Tobit Models + maintainer: Yves Croissant + description: |- + Estimation of models with dependent variable left-censored at zero. + Null values may be caused by a selection process + Cragg (1971) , insufficient resources + Tobin (1958) , or infrequency of purchase + Deaton and Irish (1984) . + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mhurdle + url_git: '' +mi: + version: '1.1' + title: Missing Data Imputation and Model Checking + maintainer: Ben Goodrich + description: The mi package provides functions for data manipulation, imputing missing + values in an approximate Bayesian framework, diagnostics of the models used to + generate the imputations, confidence-building mechanisms to validate some of the + assumptions of the imputation algorithm, and functions to analyze multiply imputed + data sets with the appropriate degree of sampling uncertainty. + date_publication: '2022-06-06' + bug_reports: '' + url: http://www.stat.columbia.edu/~gelman/ + url_cran: https://CRAN.R-project.org/package=mi + url_git: '' +mi4p: + version: '1.2' + title: Multiple Imputation for Proteomics + maintainer: Frederic Bertrand + description: A framework for multiple imputation for proteomics is proposed by Marie + Chion, Christine Carapito and Frederic Bertrand (2021) . + It is dedicated to dealing with multiple imputation for proteomics. + date_publication: '2024-10-02' + bug_reports: https://github.com/mariechion/mi4p/issues/ + url: https://mariechion.github.io/mi4p/ + url_cran: https://CRAN.R-project.org/package=mi4p + url_git: https://github.com/mariechion/mi4p/ +MIAmaxent: + version: 1.3.1 + title: |- + A Modular, Integrated Approach to Maximum Entropy Distribution + Modeling + maintainer: Julien Vollering + description: |- + Tools for training, selecting, and evaluating maximum entropy + (and standard logistic regression) distribution models. This package + provides tools for user-controlled transformation of explanatory variables, + selection of variables by nested model comparison, and flexible model + evaluation and projection. It follows principles based on the maximum- + likelihood interpretation of maximum entropy modeling, and uses infinitely- + weighted logistic regression for model fitting. The package is described in + Vollering et al. (2019; ). + date_publication: '2024-08-23' + bug_reports: https://github.com/julienvollering/MIAmaxent/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MIAmaxent + url_git: https://github.com/julienvollering/MIAmaxent +MIC: + version: 1.0.2 + title: Analysis of Antimicrobial Minimum Inhibitory Concentration Data + maintainer: Alessandro Gerada + description: |- + Analyse, plot, and tabulate antimicrobial minimum inhibitory concentration (MIC) data. + Validate the results of an MIC experiment by comparing observed MIC values to + a gold standard assay, in line with standards from the International Organization for + Standardization (2021) . Perform MIC prediction from + whole genome sequence data stored in the Pathosystems Resource Integration Center (2013) + database or locally. + date_publication: '2025-02-07' + bug_reports: https://github.com/agerada/MIC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MIC + url_git: https://github.com/agerada/MIC +micar: + version: 1.1.2 + title: '''Mica'' Data Web Portal Client' + maintainer: Yannick Marcon + description: |- + 'Mica' is a server application used to create data web portals for + large-scale epidemiological studies or multiple-study consortia. 'Mica' helps + studies to provide scientifically robust data visibility and web presence + without significant information technology effort. 'Mica' provides a + structured description of consortia, studies, annotated and searchable data + dictionaries, and data access request management. This 'Mica' client allows + to perform data extraction for reporting purposes. + date_publication: '2021-04-16' + bug_reports: https://github.com/obiba/micar + url: https://www.obiba.org/https://www.obiba.org/pages/products/mica/https://doi.org/10.1093/ije/dyx180 + url_cran: https://CRAN.R-project.org/package=micar + url_git: '' +micd: + version: 1.1.1 + title: Multiple Imputation in Causal Graph Discovery + maintainer: Ronja Foraita + description: |- + Modified functions of the package 'pcalg' and some additional functions + to run the PC and the FCI (Fast Causal Inference) algorithm for constraint-based + causal discovery in incomplete and multiply imputed datasets. + Foraita R, Friemel J, Günther K, Behrens T, Bullerdiek J, Nimzyk R, Ahrens W, Didelez V (2020) ; + Andrews RM, Foraita R, Didelez V, Witte J (2021) ; Witte J, Foraita R, Didelez V (2022) . + date_publication: '2023-02-17' + bug_reports: https://github.com/bips-hb/micd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=micd + url_git: https://github.com/bips-hb/micd +mice: + version: 3.17.0 + title: Multivariate Imputation by Chained Equations + maintainer: Stef van Buuren + description: |- + Multiple imputation using Fully Conditional Specification (FCS) + implemented by the MICE algorithm as described in Van Buuren and + Groothuis-Oudshoorn (2011) . Each variable has + its own imputation model. Built-in imputation models are provided for + continuous data (predictive mean matching, normal), binary data (logistic + regression), unordered categorical data (polytomous logistic regression) + and ordered categorical data (proportional odds). MICE can also impute + continuous two-level data (normal model, pan, second-level variables). + Passive imputation can be used to maintain consistency between variables. + Various diagnostic plots are available to inspect the quality of the + imputations. + date_publication: '2024-11-27' + bug_reports: https://github.com/amices/mice/issues + url: https://amices.org/mice/ + url_cran: https://CRAN.R-project.org/package=mice + url_git: https://github.com/amices/mice +miceadds: + version: 3.17-44 + title: |- + Some Additional Multiple Imputation Functions, Especially for + 'mice' + maintainer: Alexander Robitzsch + description: |2- + + Contains functions for multiple imputation which + complements existing functionality in R. + In particular, several imputation methods for the + mice package (van Buuren & Groothuis-Oudshoorn, 2011, + ) are implemented. + Main features of the miceadds package include + plausible value imputation (Mislevy, 1991, + ), multilevel imputation for + variables at any level or with any number of hierarchical + and non-hierarchical levels (Grund, Luedtke & Robitzsch, + 2018, ; van Buuren, 2018, + Ch.7, ), imputation using + partial least squares (PLS) for high dimensional + predictors (Robitzsch, Pham & Yanagida, 2016), + nested multiple imputation (Rubin, 2003, + ), substantive model + compatible imputation (Bartlett et al., 2015, + ), and features + for the generation of synthetic datasets + (Reiter, 2005, ; + Nowok, Raab, & Dibben, 2016, ). + date_publication: '2024-01-09' + bug_reports: https://github.com/alexanderrobitzsch/miceadds/issues?state=open + url: https://sites.google.com/view/alexander-robitzsch/software + url_cran: https://CRAN.R-project.org/package=miceadds + url_git: https://github.com/alexanderrobitzsch/miceadds +miceafter: + version: 0.5.0 + title: Data and Statistical Analyses after Multiple Imputation + maintainer: Martijn Heymans + description: |2- + + Statistical Analyses and Pooling after Multiple Imputation. A large variety + of repeated statistical analysis can be performed and finally pooled. Statistical analysis + that are available are, among others, Levene's test, Odds and Risk Ratios, One sample + proportions, difference between proportions and linear and logistic regression models. + Functions can also be used in combination with the Pipe operator. + More and more statistical analyses and pooling functions will be added over time. + Heymans (2007) . + Eekhout (2017) . + Wiel (2009) . + Marshall (2009) . + Sidi (2021) . + Lott (2018) . + Grund (2021) . + date_publication: '2022-10-02' + bug_reports: https://github.com/mwheymans/miceafter/issues + url: https://mwheymans.github.io/miceafter/ + url_cran: https://CRAN.R-project.org/package=miceafter + url_git: '' +micEcon: + version: 0.6-18 + title: Microeconomic Analysis and Modelling + maintainer: Arne Henningsen + description: |- + Various tools for microeconomic analysis and microeconomic modelling, + e.g. estimating quadratic, Cobb-Douglas and Translog functions, + calculating partial derivatives and elasticities of these functions, + and calculating Hessian matrices, checking curvature + and preparing restrictions for imposing monotonicity of Translog functions. + date_publication: '2022-09-03' + bug_reports: '' + url: http://www.micEcon.org + url_cran: https://CRAN.R-project.org/package=micEcon + url_git: '' +micEconAids: + version: 0.6-20 + title: Demand Analysis with the Almost Ideal Demand System (AIDS) + maintainer: Arne Henningsen + description: |- + Functions and tools + for analysing consumer demand + with the Almost Ideal Demand System (AIDS) + suggested by Deaton and Muellbauer (1980). + date_publication: '2022-05-20' + bug_reports: '' + url: http://www.micEcon.org + url_cran: https://CRAN.R-project.org/package=micEconAids + url_git: '' +micEconCES: + version: 1.0-2 + title: |- + Analysis with the Constant Elasticity of Substitution (CES) + Function + maintainer: Arne Henningsen + description: |- + Tools for econometric analysis and economic modelling + with the traditional two-input Constant Elasticity of Substitution (CES) function + and with nested CES functions with three and four inputs. + The econometric estimation can be done by the Kmenta approximation, + or non-linear least-squares + using various gradient-based or global optimisation algorithms. + Some of these algorithms can constrain the parameters to certain ranges, + e.g. economically meaningful values. + Furthermore, the non-linear least-squares estimation + can be combined with a grid-search for the rho-parameter(s). + The estimation methods are described in Henningsen et al. (2021) + . + date_publication: '2023-01-06' + bug_reports: https://github.com/micEcon/micEconCES + url: http://www.micEcon.org + url_cran: https://CRAN.R-project.org/package=micEconCES + url_git: '' +micEconDistRay: + version: 0.1-2 + title: |- + Econometric Production Analysis with Ray-Based Distance + Functions + maintainer: Arne Henningsen + description: |- + Econometric analysis of multiple-input-multiple-output + production technologies with ray-based input distance functions as suggested + by Price and Henningsen (2022): "A Ray-Based Input Distance Function to Model + Zero-Valued Output Quantities: Derivation and an Empirical Application", + . + date_publication: '2023-05-12' + bug_reports: https://github.com/micEcon/micEconDistRay/issues + url: '' + url_cran: https://CRAN.R-project.org/package=micEconDistRay + url_git: https://github.com/micEcon/micEconDistRay +micEconIndex: + version: 0.1-8 + title: Price and Quantity Indices + maintainer: Arne Henningsen + description: |- + Tools for calculating Laspeyres, Paasche, and Fisher + price and quantity indices. + date_publication: '2022-06-21' + bug_reports: '' + url: http://www.micEcon.org + url_cran: https://CRAN.R-project.org/package=micEconIndex + url_git: '' +micEconSNQP: + version: 0.6-10 + title: Symmetric Normalized Quadratic Profit Function + maintainer: Arne Henningsen + description: |- + Tools for econometric production analysis + with the Symmetric Normalized Quadratic (SNQ) profit function, + e.g. estimation, imposing convexity in prices, + and calculating elasticities and shadow prices. + date_publication: '2022-06-21' + bug_reports: '' + url: http://www.micEcon.org + url_cran: https://CRAN.R-project.org/package=micEconSNQP + url_git: '' +miceFast: + version: 0.8.5 + title: Fast Imputations Using 'Rcpp' and 'Armadillo' + maintainer: Maciej Nasinski + description: |- + Fast imputations under the object-oriented programming paradigm. + Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'. + The biggest improvement in time performance could be achieve for a calculation where a grouping variable have to be used. + A single evaluation of a quantitative model for the multiple imputations is another major enhancement. + A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search. + date_publication: '2025-02-03' + bug_reports: https://github.com/Polkas/miceFast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miceFast + url_git: https://github.com/Polkas/miceFast +micemd: + version: 1.10.0 + title: Multiple Imputation by Chained Equations with Multilevel Data + maintainer: Vincent Audigier + description: Addons for the 'mice' package to perform multiple imputation using + chained equations with two-level data. Includes imputation methods dedicated to + sporadically and systematically missing values. Imputation of continuous, binary + or count variables are available. Following the recommendations of Audigier, V. + et al (2018) , the choice of the imputation method for + each variable can be facilitated by a default choice tuned according to the structure + of the incomplete dataset. Allows parallel calculation and overimputation for + 'mice'. + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=micemd + url_git: '' +micer: + version: 0.2.0 + title: Map Image Classification Efficacy + maintainer: Aaron Maxwell + description: Map image classification efficacy (MICE) adjusts the accuracy rate + relative to a random classification baseline (Shao et al. (2021) + and Tang et al. (2024)). Only the proportions from + the reference labels are considered, as opposed to the proportions from the reference + and predictions, as is the case for the Kappa statistic. This package offers means + to calculate MICE and adjusted versions of class-level user's accuracy (i.e., + precision) and producer's accuracy (i.e., recall) and F1-scores. Class-level metrics + are aggregated using macro-averaging. Functions are also made available to estimate + confidence intervals using bootstrapping and statistically compare two classification + results. + date_publication: '2025-01-20' + bug_reports: https://github.com/maxwell-geospatial/micer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=micer + url_git: https://github.com/maxwell-geospatial/micer +miceRanger: + version: 1.5.0 + title: Multiple Imputation by Chained Equations with Random Forests + maintainer: Sam Wilson + description: |- + Multiple Imputation has been shown to + be a flexible method to impute missing values by + Van Buuren (2007) . + Expanding on this, random forests have been shown + to be an accurate model by Stekhoven and Buhlmann + to impute missing values in datasets. + They have the added benefits of returning out of bag + error and variable importance estimates, as well as + being simple to run in parallel. + date_publication: '2021-09-06' + bug_reports: https://github.com/FarrellDay/miceRanger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miceRanger + url_git: https://github.com/FarrellDay/miceRanger +michelRodange: + version: 1.0.0 + title: The Works (in Luxembourguish) of Michel Rodange + maintainer: Bruno André Rodrigues coelho + description: |- + Michel Rodange was a Luxembourguish writer and poet who lived in the 19th century. + His most notable work is Rodange (1872, ISBN:1166177424), ("Renert oder de Fuuß am Frack an a Ma'nsgrëßt"), + but he also wrote many more works, including Rodange, Tockert (1928) + ("D'Léierchen - Dem Léiweckerche säi Lidd") and Rodange, Welter (1929) + ("Dem Grow Sigfrid seng Goldkuommer"). This package contains three datasets, each made from the + plain text versions of his works available on + . + date_publication: '2019-04-30' + bug_reports: https://github.com/b-rodrigues/michelRodange/issues + url: '' + url_cran: https://CRAN.R-project.org/package=michelRodange + url_git: https://github.com/b-rodrigues/michelRodange +miclust: + version: 1.2.8 + title: Multiple Imputation in Cluster Analysis + maintainer: Jose Barrera-Gomez + description: |- + Implementation of a framework for cluster analysis with selection of the + final number of clusters and an optional variable selection procedure. The package + is designed to integrate the results of multiple imputed datasets while accounting + for the uncertainty that the imputations introduce in the final results. In addition, + the package can also be used for a cluster analysis of the complete cases of a single + dataset. The package also includes specific methods to summarize and plot the results. + The methods are described in Basagana et al. (2013) . + date_publication: '2022-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miclust + url_git: '' +micompr: + version: 1.1.4 + title: Multivariate Independent Comparison of Observations + maintainer: Nuno Fachada + description: |- + A procedure for comparing multivariate samples associated with + different groups. It uses principal component analysis to convert + multivariate observations into a set of linearly uncorrelated statistical + measures, which are then compared using a number of statistical methods. The + procedure is independent of the distributional properties of samples and + automatically selects features that best explain their differences, avoiding + manual selection of specific points or summary statistics. It is appropriate + for comparing samples of time series, images, spectrometric measures or + similar multivariate observations. This package is described in Fachada et + al. (2016) . + date_publication: '2023-08-19' + bug_reports: https://github.com/nunofachada/micompr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=micompr + url_git: https://github.com/nunofachada/micompr +miCoPTCM: + version: '1.1' + title: Promotion Time Cure Model with Mis-Measured Covariates + maintainer: Aurelie Bertrand + description: |- + Fits Semiparametric Promotion Time Cure Models, taking into account (using a + corrected score approach or the SIMEX algorithm) or not the measurement error + in the covariates, using a backfitting approach to maximize the likelihood. + date_publication: '2020-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miCoPTCM + url_git: '' +microbats: + version: 0.1-1 + title: An Implementation of Bat Algorithm in R + maintainer: Seong Hyun Hwang + description: A nature-inspired metaheuristic algorithm based on the echolocation + behavior of microbats that uses frequency tuning to optimize problems in both + continuous and discrete dimensions. This R package makes it easy to implement + the standard bat algorithm on any user-supplied function. The algorithm was first + developed by Xin-She Yang in 2010 (, ). + date_publication: '2016-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microbats + url_git: https://github.com/stathwang/microbats +microbenchmark: + version: 1.5.0 + title: Accurate Timing Functions + maintainer: Joshua M. Ulrich + description: |- + Provides infrastructure to accurately measure and compare + the execution time of R expressions. + date_publication: '2024-09-04' + bug_reports: https://github.com/joshuaulrich/microbenchmark/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=microbenchmark + url_git: https://github.com/joshuaulrich/microbenchmark/ +microbial: + version: 0.0.21 + title: Do 16s Data Analysis and Generate Figures + maintainer: Kai Guo + description: |- + Provides functions to enhance the available + statistical analysis procedures in R by providing simple functions to + analysis and visualize the 16S rRNA data.Here we present a tutorial + with minimum working examples to demonstrate usage and dependencies. + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microbial + url_git: '' +microbiomeMQC: + version: 1.0.2 + title: Calculate 4 Key Reporting Measures + maintainer: Jacob Dehinsilu + description: Perform calculations for the WHO International Reference Reagents for + the microbiome. Using strain, species or genera abundance tables generated through + analysis of 16S ribosomal RNA sequencing or shotgun sequencing which included + a reference reagent. This package will calculate measures of sensitivity, False + positive relative abundance, diversity, and similarity based on mean average abundances + with respect to the reference reagent. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microbiomeMQC + url_git: '' +MicrobiomeStat: + version: '1.2' + title: Statistical Methods for Microbiome Compositional Data + maintainer: Jun Chen + description: A suite of methods for powerful and robust microbiome data analysis + addressing zero-inflation, phylogenetic structure and compositional effects (Zhou + et al. (2022)). The methods can be applied to + the analysis of other (high-dimensional) compositional data arising from sequencing + experiments. + date_publication: '2024-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MicrobiomeStat + url_git: '' +MicrobiomeSurv: + version: 0.1.0 + title: |- + Biomarker Validation for Microbiome-Based Survival + Classification and Prediction + maintainer: Thi Huyen Nguyen + description: |- + An approach to identify microbiome biomarker for time to event data by discovering microbiome for predicting survival and classifying subjects into risk groups. + Classifiers are constructed as a linear combination of important microbiome and treatment effects if necessary. + Several methods were implemented to estimate the microbiome risk score such as the LASSO method by Robert Tibshirani (1998) , Elastic net approach by Hui Zou and Trevor Hastie (2005) , supervised principle component analysis of Wold Svante et al. (1987) , and supervised partial least squares analysis by Inge S. Helland . + Sensitivity analysis on the quantile used for the classification can also be accessed to check the deviation of the classification group based on the quantile specified. Large scale cross validation can be performed in order to investigate the mostly selected microbiome and for internal validation. + During the evaluation process, validation is accessed using the hazard ratios (HR) distribution of the test set and inference is mainly based on resampling and permutations technique. + date_publication: '2023-10-12' + bug_reports: https://github.com/N-T-Huyen/MicrobiomeSurv/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=MicrobiomeSurv + url_git: https://github.com/N-T-Huyen/MicrobiomeSurv +microclass: + version: '1.2' + title: Methods for Taxonomic Classification of Prokaryotes + maintainer: Lars Snipen + description: |- + Functions for assigning 16S sequence data to a + taxonomic level in the tree-of-life for prokaryotes. + date_publication: '2020-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microclass + url_git: '' +microcontax: + version: '1.2' + title: The ConTax Data Package + maintainer: Lars Snipen + description: |- + The consensus taxonomy for prokaryotes is a set of data-sets for + best possible taxonomic classification based on 16S rRNA sequence data. + date_publication: '2020-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microcontax + url_git: '' +microCRAN: + version: 0.9.0-1 + title: Hosting an Independent CRAN Repository + maintainer: Stefan McKinnon Edwards + description: |- + Stand-alone HTTP capable R-package repository, + that fully supports R's install.packages() and available.packages(). + It also contains API endpoints for end-users to add/update packages. + This package can supplement 'miniCRAN', which has functions for maintaining + a local (partial) copy of 'CRAN'. + Current version is bare-minimum without any access-control or much security. + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microCRAN + url_git: '' +MicroDatosEs: + version: 0.8.15 + title: Utilities for Official Spanish Microdata + maintainer: Carlos J. Gil Bellosta + description: Provides utilities for reading and processing microdata from Spanish + official statistics with R. + date_publication: '2023-11-24' + bug_reports: '' + url: https://www.datanalytics.com/2012/08/06/un-paseo-por-el-paquete-microdatoses-y-la-epa-de-nuevo/ + url_cran: https://CRAN.R-project.org/package=MicroDatosEs + url_git: '' +microdiluteR: + version: 1.0.1 + title: Analysis of Broth Microdilution Assays + maintainer: Silvia Eckert + description: |- + A framework for analyzing broth microdilution assays in various + 96-well plate designs, visualizing results and providing descriptive and (simple) + inferential statistics (i.e. summary statistics and sign test). The functions are + designed to add metadata to 8 x 12 tables of absorption values, creating a tidy + data frame. Users can choose between clean-up procedures via function + parameters (which covers most cases) or user prompts (in cases with complex + experimental designs). Users can also choose between two validation methods, + i.e. exclusion of absorbance values above a certain threshold or manual exclusion + of samples. A function for visual inspection of samples with their absorption values + over time for certain group combinations helps with the decision. In addition, + the package includes functions to subtract the background absorption (usually + at time T0) and to calculate the growth performance compared to a baseline. + Samples can be visually inspected with their absorption values displayed across + time points for specific group combinations. Core functions of this package (i.e. + background subtraction, sample validation and statistics) were inspired by the + manual calculations that were applied in Tewes and Muller (2020) + . + date_publication: '2024-05-13' + bug_reports: https://github.com/silvia-eckert/microdiluteR/issues + url: https://silvia-eckert.github.io/microdiluteR/ + url_cran: https://CRAN.R-project.org/package=microdiluteR + url_git: '' +microeco: + version: 1.13.0 + title: Microbial Community Ecology Data Analysis + maintainer: Chi Liu + description: A series of statistical and plotting approaches in microbial community + ecology based on the R6 class. The classes are designed for data preprocessing, + taxa abundance plotting, alpha diversity analysis, beta diversity analysis, differential + abundance test, null model analysis, network analysis, machine learning, environmental + data analysis and functional analysis. + date_publication: '2025-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microeco + url_git: https://github.com/ChiLiubio/microeco +microhaplot: + version: 1.0.1 + title: Microhaplotype Constructor and Visualizer + maintainer: Thomas Ng + description: |- + A downstream bioinformatics tool to construct and assist + curation of microhaplotypes from short read sequences. + date_publication: '2019-10-03' + bug_reports: https://github.com/ngthomas/microhaplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=microhaplot + url_git: https://github.com/ngthomas/microhaplot +microinverterdata: + version: 0.2.0 + title: Collect your Microinverter Data + maintainer: Christophe Regouby + description: |- + Collect and normalize local microinverter energy and power production + data through off-cloud API requests. Currently supports 'APSystems', 'Enphase', + and 'Fronius' microinverters. + date_publication: '2024-10-24' + bug_reports: https://github.com/CamembR/microinverterdata/issues + url: https://camembr.github.io/microinverterdata/ + url_cran: https://CRAN.R-project.org/package=microinverterdata + url_git: https://github.com/CamembR/microinverterdata +MicroMacroMultilevel: + version: 0.4.0 + title: Micro-Macro Multilevel Modeling + maintainer: Nancy R Xu + description: |- + Most multilevel methodologies can only model macro-micro + multilevel situations in an unbiased way, wherein group-level predictors + (e.g., city temperature) are used to predict an individual-level + outcome variable (e.g., citizen personality). In contrast, + this R package enables researchers to model micro-macro situations, wherein + individual-level (micro) predictors (and other group-level predictors) are + used to predict a group-level (macro) outcome variable in an unbiased way. + date_publication: '2017-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MicroMacroMultilevel + url_git: '' +micromap: + version: 1.9.10 + title: Linked Micromap Plots + maintainer: Marcus W. Beck + description: |- + This group of functions simplifies the creation of linked micromap plots. Please + see for additional details. + date_publication: '2024-10-30' + bug_reports: https://github.com/USEPA/micromap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=micromap + url_git: +micromapST: + version: 3.1.0 + title: Linked Micromap Plots for U. S. and Other Geographic Areas + maintainer: Jim Pearson + description: |- + Provides the users with the ability to quickly create + linked micromap plots for a collection of geographic areas. + Linked micromap plots are visualizations of geo-referenced data + that link statistical graphics to an organized series of small + maps or graphic images. The Help description contains examples + of how to use the 'micromapST' function. Contained in this + package are border group datasets to support creating linked + micromap plots for the 50 U.S. states and District of Columbia + (51 areas), the U. S. 20 Seer Registries, the 105 counties in + the state of Kansas, the 62 counties of New York, the 24 + counties of Maryland, the 29 counties of Utah, the 32 + administrative areas in China, the 218 administrative areas in + the UK and Ireland (for testing only), the 25 districts in the + city of Seoul South Korea, and the 52 counties on the Africa + continent. + A border group dataset contains the boundaries related to the + data level areas, a second layer boundaries, a top or third + layer boundary, a parameter list of run options, and a cross + indexing table between area names, abbreviations, numeric + identification and alias matching strings for the specific + geographic area. By specifying a border group, the package + create linked micromap plots for any geographic region. The + user can create and provide their own border group dataset for + any area beyond the areas contained within the package. In version 3.0.0, + the 'BuildBorderGroup' function was upgraded to not use the retiring + 'maptools', 'rgdal', and 'rgeos' packages. + References: Carr and Pickle, Chapman and Hall/CRC, Visualizing + Data Patterns with Micromaps, CRC Press, 2010. Pickle, Pearson, + and Carr (2015), micromapST: Exploring and Communicating + Geospatial Patterns in US State Data., Journal of Statistical + Software, 63(3), 1-25., . + Copyrighted 2013, 2014, 2015, 2016, 2022, 2023, 2024, and 2025 by Carr, Pearson + and Pickle. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=micromapST + url_git: '' +MicroMoB: + version: 0.1.2 + title: Discrete Time Simulation of Mosquito-Borne Pathogen Transmission + maintainer: Sean L. Wu + description: |- + Provides a framework based on S3 dispatch for constructing models + of mosquito-borne pathogen transmission which are constructed from submodels of various + components (i.e. immature and adult mosquitoes, human populations). A consistent mathematical + expression for the distribution of bites on hosts means that different models + (stochastic, deterministic, etc.) can be coherently incorporated and updated + over a discrete time step. + date_publication: '2023-01-17' + bug_reports: https://github.com/dd-harp/MicroMoB/issues + url: https://dd-harp.github.io/MicroMoB/ + url_cran: https://CRAN.R-project.org/package=MicroMoB + url_git: https://github.com/dd-harp/MicroMoB +micromodal: + version: 1.0.0 + title: Create Simple and Elegant Modal Dialogs in 'shiny' + maintainer: Kennedy Mwavu + description: Enables you to create accessible modal dialogs, with confidence and + with minimal configuration. + date_publication: '2023-08-17' + bug_reports: https://github.com/kennedymwavu/micromodal/issues + url: https://mwavu.com/micromodal/ + url_cran: https://CRAN.R-project.org/package=micromodal + url_git: https://github.com/kennedymwavu/micromodal +MicroNiche: + version: 1.0.0 + title: Microbial Niche Measurements + maintainer: Damien Finn + description: |- + Measures niche breadth and overlap of microbial taxa from large matrices. + Niche breadth measurements include Levins' niche breadth (Bn) index, Hurlbert's Bn + and Feinsinger's proportional similarity (PS) index. (Feinsinger, P., Spears, E.E., + Poole, R.W. (1981) ). Niche overlap measurements include + Levin's Overlap (Ludwig, J.A. and Reynolds, J.F. (1988, ISBN:0471832359)) and a Jaccard + similarity index of Feinsinger's PS values between taxa pairs, as Proportional Overlap. + date_publication: '2020-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MicroNiche + url_git: '' +micronutr: + version: 0.1.1 + title: Determining Vitamin and Mineral Status of Populations + maintainer: Ernest Guevarra + description: |- + Vitamin and mineral deficiencies continue to be a significant + public health problem. This is particularly critical in developing countries + where deficiencies to vitamin A, iron, iodine, and other micronutrients + lead to adverse health consequences. Cross-sectional surveys are helpful in + answering questions related to the magnitude and distribution of + deficiencies of selected vitamins and minerals. This package provides tools + for calculating and determining select vitamin and mineral deficiencies + based on World Health Organization (WHO) guidelines found at + . + date_publication: '2024-04-09' + bug_reports: https://github.com/nutriverse/micronutr/issues + url: https://nutriverse.io/micronutr/ + url_cran: https://CRAN.R-project.org/package=micronutr + url_git: https://github.com/nutriverse/micronutr +micropan: + version: '2.1' + title: Microbial Pan-Genome Analysis + maintainer: Lars Snipen + description: A collection of functions for computations and visualizations of microbial + pan-genomes. + date_publication: '2020-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=micropan + url_git: '' +microplot: + version: 1.0-45 + title: Microplots (Sparklines) in 'LaTeX', 'Word', 'HTML', 'Excel' + maintainer: Richard M. Heiberger + description: |- + The microplot function writes a set of R graphics files to be used as + microplots (sparklines) in tables in either 'LaTeX', 'HTML', 'Word', + or 'Excel' files. For 'LaTeX', we provide methods for the + Hmisc::latex() generic function to construct 'latex' tabular + environments which include the graphs. These can be used directly + with the operating system 'pdflatex' or 'latex' command, or by using + one of 'Sweave', 'knitr', 'rmarkdown', or 'Emacs org-mode' as an + intermediary. For 'MS Word', the msWord() function uses the + 'flextable' package to construct 'Word' tables which include the + graphs. There are several distinct approaches for constructing HTML + files. The simplest is to use the msWord() function with argument + filetype="html". Alternatively, use either 'Emacs org-mode' or the + htmlTable::htmlTable() function to construct an 'HTML' file + containing tables which include the graphs. See the documentation + for our as.htmlimg() function. For 'Excel' use on 'Windows', the + file examples/irisExcel.xls includes 'VBA' code which brings the + individual panels into individual cells in the spreadsheet. + Examples in the examples and demo subdirectories are shown with + 'lattice' graphics, 'ggplot2' graphics, and 'base' graphics. + Examples for 'LaTeX' include 'Sweave' (both 'LaTeX'-style and + 'Noweb'-style), 'knitr', 'emacs org-mode', and 'rmarkdown' input + files and their 'pdf' output files. Examples for 'HTML' include + 'org-mode' and 'Rmd' input files and their webarchive 'HTML' output + files. In addition, the as.orgtable() function can display a + data.frame in an 'org-mode' document. The examples for 'MS Word' + (with either filetype="docx" or filetype="html") work with all + operating systems. The package does not require the installation of + 'LaTeX' or 'MS Word' to be able to write '.tex' or '.docx' files. + date_publication: '2022-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microplot + url_git: '' +microPop: + version: '1.6' + title: Process-Based Modelling of Microbial Populations + maintainer: Helen Kettle + description: |- + Modelling interacting microbial populations - example applications + include human gut microbiota, rumen microbiota and phytoplankton. Solves a + system of ordinary differential equations to simulate microbial growth and + resource uptake over time. This version contains network visualisation functions. + date_publication: '2022-02-03' + bug_reports: '' + url: https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12873 + url_cran: https://CRAN.R-project.org/package=microPop + url_git: '' +MicroSEC: + version: 2.1.6 + title: |- + Sequence Error Filter for Formalin-Fixed and Paraffin-Embedded + Samples + maintainer: Masachika Ikegami + description: |- + Clinical sequencing of tumor is usually performed on formalin-fixed + and paraffin-embedded samples and have many sequencing errors. We found that + the majority of these errors are detected in chimeric read caused by + single-strand DNA with micro-homology. Our filtering pipeline focuses on the + uneven distribution of the artifacts in each read and removes such errors in + formalin-fixed and paraffin-embedded samples without over-eliminating the + true mutations detected in fresh frozen samples. + date_publication: '2024-08-25' + bug_reports: https://github.com/MANO-B/MicroSEC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MicroSEC + url_git: https://github.com/MANO-B/MicroSEC/ +microseq: + version: 2.1.6 + title: Basic Biological Sequence Handling + maintainer: Lars Snipen + description: Basic functions for microbial sequence data analysis. The idea is to + use generic R data structures as much as possible, making R data wrangling possible + also for sequence data. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microseq + url_git: '' +microsimulation: + version: 1.4.4 + title: |- + Discrete Event Simulation in R and C++, with Tools for + Cost-Effectiveness Analysis + maintainer: Mark Clements + description: Discrete event simulation using both R and C++ (Karlsson et al 2016; + ). The C++ code is adapted from the SSIM library + , allowing for event-oriented simulation. + The code includes a SummaryReport class for reporting events and costs by age + and other covariates. The C++ code is available as a static library for linking + to other packages. A priority queue implementation is given in C++ together with + an S3 closure and a reference class implementation. Finally, some tools are provided + for cost-effectiveness analysis. + date_publication: '2024-08-19' + bug_reports: https://github.com/mclements/microsimulation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=microsimulation + url_git: https://github.com/mclements/microsimulation +Microsoft365R: + version: 2.4.0 + title: Interface to the 'Microsoft 365' Suite of Cloud Services + maintainer: Hong Ooi + description: An interface to the 'Microsoft 365' (formerly known as 'Office 365') + suite of cloud services, building on the framework supplied by the 'AzureGraph' + package. Enables access from R to data stored in 'Teams', 'SharePoint Online' + and 'OneDrive', including the ability to list drive folder contents, upload and + download files, send messages, and retrieve data lists. Also provides a full-featured + 'Outlook' email client, with the ability to send emails and manage emails and + mail folders. + date_publication: '2023-05-30' + bug_reports: https://github.com/Azure/Microsoft365R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Microsoft365R + url_git: https://github.com/Azure/Microsoft365Rhttps://github.com/Azure/AzureR +microsynth: + version: 2.0.44 + title: Synthetic Control Methods with Micro- And Meso-Level Data + maintainer: Michael Robbins + description: |- + A generalization of the 'Synth' package that is designed for + data at a more granular level (e.g., micro-level). Provides functions + to construct weights (including propensity score-type weights) and run + analyses for synthetic control methods with micro- and meso-level + data; see Robbins, Saunders, and Kilmer (2017) + and Robbins and Davenport (2021) + . + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=microsynth + url_git: '' +MicSim: + version: 2.0.1 + title: Performing Continuous-Time Microsimulation + maintainer: Sabine Zinn + description: This toolkit allows performing continuous-time microsimulation for + a wide range of life science (demography, social sciences, epidemiology) applications. + Individual life-courses are specified by a continuous-time multi-state model as + described in Zinn (2014) . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MicSim + url_git: '' +MICsplines: + version: '1.0' + title: |- + The Computing of Monotonic Spline Bases and Constrained + Least-Squares Estimates + maintainer: Yili Hong + description: 'Providing C implementation for the computing of monotonic spline bases, + including M-splines, I-splines, and C-splines, denoted by MIC splines. The definitions + of the spline bases are described in Meyer (2008) . The + package also provides the computing of constrained least-squares estimates when + a subset of or all of the regression coefficients are constrained to be non-negative.' + date_publication: '2021-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MICsplines + url_git: '' +micsr: + version: 0.1-1 + title: Microeconometrics with R + maintainer: Yves Croissant + description: 'Functions, data sets and examples for the book: Yves Croissant (2024) + "Microeconometrics with R", Chapman and Hall/CRC The R Series. The package includes + a set of estimators for models used in microeconometrics, especially for count + data and limited dependent variables. Test functions include score test, Hausman + test, Vuong test, Sargan test and conditional moment test. A small subset of the + data set used in the book is also included.' + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=micsr + url_git: '' +micss: + version: 0.2.0 + title: Modified Iterative Cumulative Sum of Squares Algorithm + maintainer: Andreu Sansó + description: |- + Companion package of Carrion-i-Silvestre & Sansó (2023): + "Generalized Extreme Value Approximation to the CUMSUMQ Test for Constant + Unconditional Variance in Heavy-Tailed Time Series". It implements the Modified + Iterative Cumulative Sum of Squares Algorithm, which is an extension of + the Iterative Cumulative Sum of Squares (ICSS) Algorithm of Inclan and Tiao (1994), and it checks for changes in the + unconditional variance of a time series controlling for the tail index of + the underlying distribution. The fourth order moment is estimated non-parametrically + to avoid the size problems when the innovations are non-Gaussian (see, Sansó et al., 2004). + Critical values and p-values are generated using a Generalized Extreme Value distribution approach. + References + Carrion-i-Silvestre J.J & Sansó A (2023) . + Inclan C & Tiao G.C (1994) , + Sansó A & Aragó V & Carrion-i-Silvestre J.L (2004) . + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=micss + url_git: '' +MiDA: + version: 0.1.2 + title: Microarray Data Analysis + maintainer: Elena Filatova + description: Set of functions designed to simplify transcriptome analysis and identification + of marker molecules using microarrays data. The package includes a set of functions + that allows performing full pipeline of analysis including data normalization, + summarisation, binary classification, FDR (False Discovery Rate) multiple comparison + and the definition of potential biological markers. + date_publication: '2019-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiDA + url_git: '' +midas: + version: 1.0.1 + title: Turn HTML 'Shiny' + maintainer: Nicholas Jhirad + description: |- + Contains functions for converting existing HTML/JavaScript + source into equivalent 'shiny' functions. Bootstraps the process of making + new 'shiny' functions by allowing us to turn HTML snippets directly into + R functions. + date_publication: '2017-07-05' + bug_reports: https://github.com/shapenaji/midas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=midas + url_git: '' +midas2: + version: 1.1.0 + title: |- + Bayesian Platform Design with Subgroup Efficacy + Exploration(MIDAS-2) + maintainer: Su Liwen + description: 'The rapid screening of effective and optimal therapies from large + numbers of candidate combinations, as well as exploring subgroup efficacy, remains + challenging, which necessitates innovative, integrated, and efficient trial designs(Yuan, + Y., et al. (2016) ). MIDAS-2 package enables quick and continuous + screening of promising combination strategies and exploration of their subgroup + effects within a unified platform design framework. We used a regression model + to characterize the efficacy pattern in subgroups. Information borrowing was applied + through Bayesian hierarchical model to improve trial efficiency considering the + limited sample size in subgroups(Cunanan, K. M., et al. (2019) ). + MIDAS-2 provides an adaptive drug screening and subgroup exploring framework to + accelerate immunotherapy development in an efficient, accurate, and integrated + fashion(Wathen, J. K., & Thall, P. F. (2017) ).' + date_publication: '2023-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=midas2 + url_git: '' +midasml: + version: 0.1.10 + title: |- + Estimation and Prediction Methods for High-Dimensional Mixed + Frequency Time Series Data + maintainer: Jonas Striaukas + description: The 'midasml' package implements estimation and prediction methods + for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression + models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) + polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information + on the 'midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) + . The package is equipped with the fast implementation + of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional + mixed frequency time-series data can also be easily manipulated with functions + provided in the package. + date_publication: '2022-04-29' + bug_reports: https://github.com/jstriaukas/midasml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=midasml + url_git: '' +midasr: + version: '0.8' + title: Mixed Data Sampling Regression + maintainer: Vaidotas Zemlys-Balevičius + description: |- + Methods and tools for mixed frequency time series data analysis. + Allows estimation, model selection and forecasting for MIDAS regressions. + date_publication: '2021-02-23' + bug_reports: https://github.com/mpiktas/midasr/issues + url: http://mpiktas.github.io/midasr/ + url_cran: https://CRAN.R-project.org/package=midasr + url_git: '' +midastouch: + version: '1.3' + title: Multiple Imputation by Distance Aided Donor Selection + maintainer: Philipp Gaffert + description: Contains the function mice.impute.midastouch(). Technically this function + is to be run from within the 'mice' package (van Buuren et al. 2011), type ??mice. + It substitutes the method 'pmm' within mice by 'midastouch'. The authors have + shown that 'midastouch' is superior to default 'pmm'. Many ideas are based on + Siddique / Belin 2008's MIDAS. + date_publication: '2016-02-07' + bug_reports: '' + url: https://www.uni-bamberg.de/fileadmin/uni/fakultaeten/sowi_lehrstuehle/statistik/Personen/Dateien_Florian/properPMM.pdf + url_cran: https://CRAN.R-project.org/package=midastouch + url_git: '' +midfieldr: + version: 1.0.2 + title: Tools and Methods for Working with MIDFIELD Data in 'R' + maintainer: Richard Layton + description: |- + Provides tools and demonstrates methods for working with individual + undergraduate student-level records (registrar's data) in 'R'. Tools include + filters for program codes, data sufficiency, and timely completion. Methods + include gathering blocs of records, computing quantitative metrics such as + graduation rate, and creating charts to visualize comparisons. 'midfieldr' + interacts with practice data provided in 'midfielddata', an R data package + available at . + 'midfieldr' also interacts with the full MIDFIELD database for users who have + access. This work is supported by the US National Science Foundation through + grant numbers 1545667 and 2142087. + date_publication: '2024-05-16' + bug_reports: https://github.com/MIDFIELDR/midfieldr/issues + url: https://midfieldr.github.io/midfieldr/ + url_cran: https://CRAN.R-project.org/package=midfieldr + url_git: '' +midi: + version: 0.1.0 + title: Microstructure Information from Diffusion Imaging + maintainer: Aymeric Stamm + description: |- + An implementation of a taxonomy of models of restricted diffusion + in biological tissues parametrized by the tissue geometry (axis, diameter, + density, etc.). This is primarily used in the context of diffusion magnetic + resonance (MR) imaging to model the MR signal attenuation in the presence of + diffusion gradients. The goal is to provide tools to simulate the MR signal + attenuation predicted by these models under different experimental + conditions. The package feeds a companion 'shiny' app available at + that serves as a graphical + interface to the models and tools provided by the package. Models currently + available are the ones in Neuman (1974) , Van + Gelderen et al. (1994) , Stanisz et al. (1997) + , Soderman & Jonsson (1995) + and Callaghan (1995) + . + date_publication: '2024-04-03' + bug_reports: https://github.com/lmjl-alea/midi/issues + url: https://lmjl-alea.github.io/midi/ + url_cran: https://CRAN.R-project.org/package=midi + url_git: https://github.com/lmjl-alea/midi +MIDN: + version: '1.0' + title: |- + Nearly Exact Sample Size Calculation for Exact Powerful + Nonrandomized Tests for Differences Between Binomial + Proportions + maintainer: Peter Ziegler + description: |- + Implementation of the mid-n algorithms presented in + Wellek S (2015) Statistica Neerlandica 69, 358-373 for exact + sample size calculation for superiority trials with binary outcome. + date_publication: '2016-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MIDN + url_git: '' +midoc: + version: 1.0.0 + title: A Decision-Making System for Multiple Imputation + maintainer: Elinor Curnow + description: A guidance system for analysis with missing data. It incorporates expert, + up-to-date methodology to help researchers choose the most appropriate analysis + approach when some data are missing. You provide the available data and the assumed + causal structure, including the likely causes of missing data. 'midoc' will advise + which analysis approaches can be used, and how best to perform them. 'midoc' follows + the framework for the treatment and reporting of missing data in observational + studies (TARMOS). Lee et al (2021). . + date_publication: '2024-10-02' + bug_reports: '' + url: https://elliecurnow.github.io/midoc/ + url_cran: https://CRAN.R-project.org/package=midoc + url_git: '' +midrangeMCP: + version: 3.1.1 + title: |- + Multiples Comparisons Procedures Based on Studentized Midrange + and Range Distributions + maintainer: Ben Deivide + description: |- + Apply tests of multiple comparisons based + on studentized 'midrange' and 'range' distributions. + The tests are: Tukey Midrange ('TM' test), + Student-Newman-Keuls Midrange ('SNKM' test), + Means Grouping Midrange ('MGM' test) and + Means Grouping Range ('MGR' test). The first two tests were published by + Batista and Ferreira (2020) . + The last two are being published. + date_publication: '2020-12-15' + bug_reports: https://github.com/bendeivide/midrangeMCP/issues + url: https://bendeivide.github.io/midrangeMCP/ + url_cran: https://CRAN.R-project.org/package=midrangeMCP + url_git: https://github.com/bendeivide/midrangeMCP +miesmuschel: + version: 0.0.4-2 + title: Mixed Integer Evolution Strategies + maintainer: Martin Binder + description: |- + Evolutionary black box optimization algorithms building on the + 'bbotk' package. 'miesmuschel' offers both ready-to-use optimization + algorithms, as well as their fundamental building blocks that can be used to + manually construct specialized optimization loops. The Mixed Integer Evolution + Strategies as described by Li et al. (2013) can be + implemented, as well as the multi-objective optimization algorithms NSGA-II + by Deb, Pratap, Agarwal, and Meyarivan (2002) . + date_publication: '2024-07-09' + bug_reports: https://github.com/mlr-org/miesmuschel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miesmuschel + url_git: https://github.com/mlr-org/miesmuschel +mifa: + version: 0.2.0 + title: Multiple Imputation for Exploratory Factor Analysis + maintainer: Tobias Busch + description: |- + Impute the covariance matrix of incomplete data so that factor + analysis can be performed. Imputations are made using multiple imputation + by Multivariate Imputation with Chained Equations (MICE) and combined with + Rubin's rules. Parametric Fieller confidence intervals and nonparametric + bootstrap confidence intervals can be obtained for the variance explained by + different numbers of principal components. The method is described in + Nassiri et al. (2018) . + date_publication: '2021-01-22' + bug_reports: https://github.com/teebusch/mifa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mifa + url_git: https://github.com/teebusch/mifa +mig: + version: '1.0' + title: Multivariate Inverse Gaussian Distribution + maintainer: Leo Belzile + description: Provides utilities for estimation for the multivariate inverse Gaussian + distribution of Minami (2003) , including random vector + generation and explicit estimators of the location vector and scale matrix. The + package implements kernel density estimators discussed in Belzile, Desgagnes, + Genest and Ouimet (2024) for smoothing multivariate + data on half-spaces. + date_publication: '2024-07-14' + bug_reports: https://github.com/lbelzile/mig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mig + url_git: '' +MigConnectivity: + version: 0.4.7 + title: Estimate Migratory Connectivity for Migratory Animals + maintainer: Jeffrey A. Hostetler + description: |- + Allows the user to estimate transition probabilities for + migratory animals between any two phases of the annual cycle, using a + variety of different data types. Also quantifies the strength of + migratory connectivity (MC), a standardized metric to quantify the + extent to which populations co-occur between two phases of the annual + cycle. Includes functions to estimate MC and the more traditional + metric of migratory connectivity strength (Mantel correlation) + incorporating uncertainty from multiple sources of sampling error. For + cross-species comparisons, methods are provided to estimate + differences in migratory connectivity strength, incorporating + uncertainty. See Cohen et al. (2018) , + Cohen et al. (2019) , and Roberts et al. + (2023) for details on some of these methods. + date_publication: '2024-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MigConnectivity + url_git: https://github.com/SMBC-NZP/MigConnectivity +MIGEE: + version: 0.1.0 + title: Impute Missing Values and Fitting Linear Mixed Effect Model + maintainer: Atanu Bhattacharjee + description: Implements methods for estimating generalized estimating equations + (GEE) with advanced options for flexible modeling and handling missing data. This + package provides tools to fit and analyze GEE models for longitudinal data, allowing + users to address missingness using a variety of imputation techniques. It supports + both univariate and multivariate modeling, visualization of missing data patterns, + and facilitates the transformation of data for efficient statistical analysis. + Designed for researchers working with complex datasets, it ensures robust estimation + and inference in longitudinal and clustered data settings. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MIGEE + url_git: '' +migest: + version: 2.0.4 + title: Methods for the Indirect Estimation of Bilateral Migration + maintainer: Guy J. Abel + description: Tools for estimating, measuring and working with migration data. + date_publication: '2023-11-18' + bug_reports: https://github.com/guyabel/migest/issues + url: http://guyabel.github.io/migest/ + url_cran: https://CRAN.R-project.org/package=migest + url_git: '' +migraph: + version: 1.4.5 + title: |- + Univariate and Multivariate Tests for Multimodal and Other + Networks + maintainer: James Hollway + description: |- + A set of tools for testing networks. + It includes functions for univariate and multivariate + conditional uniform graph and quadratic assignment procedure testing, + and network regression. + The package is a complement to + 'Multimodal Political Networks' (2021, ISBN:9781108985000), + and includes various datasets used in the book. + Built on the 'manynet' package, all functions operate with matrices, + edge lists, and 'igraph', 'network', and 'tidygraph' objects, + and on one-mode and two-mode (bipartite) networks. + date_publication: '2024-12-02' + bug_reports: https://github.com/stocnet/migraph/issues + url: https://stocnet.github.io/migraph/ + url_cran: https://CRAN.R-project.org/package=migraph + url_git: '' +migrate: + version: 0.5.0 + title: Create Credit State Migration (Transition) Matrices + maintainer: Michael Thomas + description: |- + Tools to help convert credit risk data at two timepoints + into traditional credit state migration (aka, "transition") matrices. + At a higher level, 'migrate' is intended to help an analyst understand + how risk moved in their credit portfolio over a time interval. + References to this methodology include: + 1. Schuermann, T. (2008) . + 2. Perederiy, V. (2017) . + date_publication: '2024-07-10' + bug_reports: https://github.com/ketchbrookanalytics/migrate/issues + url: https://ketchbrookanalytics.github.io/migrate/ + url_cran: https://CRAN.R-project.org/package=migrate + url_git: https://github.com/ketchbrookanalytics/migrate +migration.indices: + version: 0.3.1 + title: Migration Indices + maintainer: Gergely Daróczi + description: |- + Calculate various indices, like Crude Migration Rate, + different Gini indices or the Coefficient of Variation among others, to + show the (un)equality of migration. + date_publication: '2022-06-13' + bug_reports: https://github.com/daroczig/migration.indices/issues + url: '' + url_cran: https://CRAN.R-project.org/package=migration.indices + url_git: https://github.com/daroczig/migration.indices +MigrationDetectR: + version: 0.1.1 + title: Segment-Based Migration Detection Algorithm + maintainer: Johannes Mast + description: |- + Detection of migration events and segments of continuous residence + based on irregular time series of location data + as published in Chi et al. (2020) . + date_publication: '2023-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MigrationDetectR + url_git: '' +migui: + version: '1.3' + title: Graphical User Interface to the 'mi' Package + maintainer: Ben Goodrich + description: This GUI for the mi package walks the user through the steps of multiple + imputation and the analysis of completed data. + date_publication: '2022-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=migui + url_git: '' +miic: + version: 2.0.3 + title: |- + Learning Causal or Non-Causal Graphical Models Using Information + Theory + maintainer: Franck Simon + description: |- + Multivariate Information-based Inductive Causation, better known + by its acronym MIIC, is a causal discovery method, based on information + theory principles, which learns a large class of causal or non-causal + graphical models from purely observational data, while including the effects + of unobserved latent variables. Starting from a complete graph, the method + iteratively removes dispensable edges, by uncovering significant information + contributions from indirect paths, and assesses edge-specific confidences + from randomization of available data. The remaining edges are then oriented + based on the signature of causality in observational data. The recent more + interpretable MIIC extension (iMIIC) further distinguishes genuine causes + from putative and latent causal effects, while scaling to very large + datasets (hundreds of thousands of samples). Since the version 2.0, MIIC + also includes a temporal mode (tMIIC) to learn temporal causal graphs from + stationary time series data. MIIC has been applied to a wide range of + biological and biomedical data, such as single cell gene expression data, + genomic alterations in tumors, live-cell time-lapse imaging data + (CausalXtract), as well as medical records of patients. MIIC brings unique + insights based on causal interpretation and could be used in a broad range + of other data science domains (technology, climatology, economy, ...). + For more information, you can refer to: + Simon et al., eLife 2024, , + Ribeiro-Dantas et al., iScience 2024, , + Cabeli et al., NeurIPS 2021, , + Cabeli et al., Comput. Biol. 2020, , + Li et al., NeurIPS 2019, , + Verny et al., PLoS Comput. Biol. 2017, , + Affeldt et al., UAI 2015, . + Changes from the previous 1.5.3 release on CRAN are available at + . + date_publication: '2024-09-17' + bug_reports: https://github.com/miicTeam/miic_R_package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miic + url_git: https://github.com/miicTeam/miic_R_package +MIIPW: + version: 0.1.1 + title: IPW and Mean Score Methods for Time-Course Missing Data + maintainer: Atanu Bhattacharjee + description: |- + Contains functions for data analysis of Repeated measurement using GEE. Data may contain missing value in response and covariates. For parameter estimation through Fisher Scoring algorithm, Mean Score and Inverse Probability Weighted method combining with Multiple Imputation are used when there is missing value in covariates/response. + Reference for mean score method, inverse probability weighted method is + Wang et al(2007). + date_publication: '2023-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MIIPW + url_git: '' +MIIVefa: + version: 0.1.2 + title: |- + Exploratory Factor Analysis Using Model Implied Instrumental + Variables + maintainer: Lan Luo + description: |- + Data-driven approach for Exploratory Factor Analysis (EFA) + that uses Model Implied Instrumental Variables (MIIVs). The method + starts with a one factor model and arrives at a suggested model with + enhanced interpretability that allows cross-loadings and correlated + errors. + date_publication: '2024-02-17' + bug_reports: https://github.com/lluo0/MIIVefa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MIIVefa + url_git: https://github.com/lluo0/MIIVefa/ +MIIVsem: + version: 0.5.8 + title: |- + Model Implied Instrumental Variable (MIIV) Estimation of + Structural Equation Models + maintainer: Zachary Fisher + description: |- + Functions for estimating structural equation models using + instrumental variables. + date_publication: '2021-07-13' + bug_reports: https://github.com/zackfisher/MIIVsem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MIIVsem + url_git: https://github.com/zackfisher/MIIVsem +mikropml: + version: 1.6.1 + title: |- + User-Friendly R Package for Supervised Machine Learning + Pipelines + maintainer: Kelly Sovacool + description: |- + An interface to build machine learning models for + classification and regression problems. 'mikropml' implements the ML + pipeline described by Topçuoğlu et al. (2020) + with reasonable default options for data + preprocessing, hyperparameter tuning, cross-validation, testing, model + evaluation, and interpretation steps. See the website + for more information, + documentation, and examples. + date_publication: '2023-08-21' + bug_reports: https://github.com/SchlossLab/mikropml/issues + url: https://www.schlosslab.org/mikropml/ + url_cran: https://CRAN.R-project.org/package=mikropml + url_git: https://github.com/SchlossLab/mikropml +miLAG: + version: 1.0.5 + title: |- + Calculates Microbial Lag Duration (on the Population Level) from + Provided Growth Curve Data + maintainer: Bogna Smug + description: |- + Microbial growth is often measured by growth curves i.e. a table of population sizes and times of measurements. + This package allows to use such growth curve data to determine the duration of "microbial lag phase" i.e. the time needed for microbes to restart divisions. + It implements the most commonly used methods to calculate the lag duration, these methods are discussed and described in Opalek et.al. 2022. + Citation: Smug, B. J., Opalek, M., Necki, M., & Wloch-Salamon, D. (2024). Microbial lag calculator: A shiny-based application and an R package for calculating the duration of microbial lag phase. Methods in Ecology and Evolution, 15, 301–307 . + date_publication: '2025-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miLAG + url_git: '' +mildsvm: + version: 0.4.0 + title: Multiple-Instance Learning with Support Vector Machines + maintainer: Sean Kent + description: |- + Weakly supervised (WS), multiple instance (MI) data lives in + numerous interesting applications such as drug discovery, object + detection, and tumor prediction on whole slide images. The 'mildsvm' + package provides an easy way to learn from this data by training + Support Vector Machine (SVM)-based classifiers. It also contains + helpful functions for building and printing multiple instance data + frames. The core methods from 'mildsvm' come from the following + references: Kent and Yu (2022) ; Xiao, Liu, and Hao + (2018) ; Muandet et al. (2012) + ; + Chu and Keerthi (2007) ; and Andrews + et al. (2003) + . + Many functions use the 'Gurobi' optimization back-end to improve the + optimization problem speed; the 'gurobi' R package and associated + software can be downloaded from after + obtaining a license. + date_publication: '2022-07-14' + bug_reports: https://github.com/skent259/mildsvm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mildsvm + url_git: https://github.com/skent259/mildsvm +miLineage: + version: '2.1' + title: Association Tests for Microbial Lineages on a Taxonomic Tree + maintainer: Zheng-Zheng Tang + description: A variety of association tests for microbiome data analysis including + Quasi-Conditional Association Tests (QCAT) described in Tang Z.-Z. et al.(2017) + and Zero-Inflated Generalized Dirichlet Multinomial + (ZIGDM) tests described in Tang Z.-Z. & Chen G. (2017, submitted). + date_publication: '2018-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miLineage + url_git: '' +milorGWAS: + version: '0.7' + title: |- + Mixed Logistic Regression for Genome-Wide Analysis Studies + (GWAS) + maintainer: Hervé Perdry + description: |- + Fast approximate methods for mixed logistic regression in genome-wide analysis studies (GWAS). + Two computationnally efficient methods are proposed for obtaining effect size estimates (beta) in + Mixed Logistic Regression in GWAS: the Approximate Maximum Likelihood Estimate (AMLE), and the Offset + method. The wald test obtained with AMLE is identical to the score test. Data can be genotype matrices + in plink format, or dosage (VCF files). The methods are described in details in + Milet et al (2020) . + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=milorGWAS + url_git: '' +milr: + version: 0.3.1 + title: Multiple-Instance Logistic Regression with LASSO Penalty + maintainer: Ping-Yang Chen + description: |- + The multiple instance data set consists of many independent + subjects (called bags) and each subject is composed of several components + (called instances). The outcomes of such data set are binary or categorical responses, + and, we can only observe the subject-level outcomes. For example, in manufacturing + processes, a subject is labeled as "defective" if at least one of its own + components is defective, and otherwise, is labeled as "non-defective". The + 'milr' package focuses on the predictive model for the multiple instance + data set with binary outcomes and performs the maximum likelihood estimation + with the Expectation-Maximization algorithm under the framework of logistic + regression. Moreover, the LASSO penalty is attached to the likelihood function + for simultaneous parameter estimation and variable selection. + date_publication: '2020-10-31' + bug_reports: https://github.com/PingYangChen/milr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=milr + url_git: https://github.com/PingYangChen/milr +mimdo: + version: 0.1.0 + title: Multivariate Imputation by Mahalanobis Distance Optimization + maintainer: Geovert John Labita + description: Imputes missing values of an incomplete data matrix by minimizing the + Mahalanobis distance of each sample from the overall mean [Labita, GJ.D. and Tubo, + B.F. (2024) ]. + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mimdo + url_git: '' +mime: + version: '0.12' + title: Map Filenames to MIME Types + maintainer: Yihui Xie + description: |- + Guesses the MIME type from a filename extension using the data + derived from /etc/mime.types in UNIX-type systems. + date_publication: '2021-09-28' + bug_reports: https://github.com/yihui/mime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mime + url_git: https://github.com/yihui/mime +MIMER: + version: 1.0.3 + title: Data Wrangling for Antimicrobial Resistance Studies + maintainer: Anoop Velluva + description: |- + Designed for analyzing the Medical Information Mart for Intensive Care(MIMIC) dataset, + a repository of freely accessible electronic health records. MIMER(MIMIC-enabled Research) package, offers + a suite of data wrangling functions tailored specifically for preparing the dataset for research purposes, + particularly in antimicrobial resistance(AMR) studies. It simplifies complex data manipulation tasks, allowing + researchers to focus on their primary inquiries without being bogged down by wrangling complexities. + date_publication: '2024-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MIMER + url_git: '' +mimi: + version: 0.2.0 + title: Main Effects and Interactions in Mixed and Incomplete Data + maintainer: Genevieve Robin + description: Generalized low-rank models for mixed and incomplete data frames. The + main function may be used for dimensionality reduction of imputation of numeric, + binary and count data (simultaneously). Main effects such as column means, group + effects, or effects of row-column side information (e.g. user/item attributes + in recommendation system) may also be modelled in addition to the low-rank model. + Geneviève Robin, Olga Klopp, Julie Josse, Éric Moulines, Robert Tibshirani (2018) + . + date_publication: '2019-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mimi + url_git: '' +MiMIR: + version: '1.5' + title: Metabolomics-Based Models for Imputing Risk + maintainer: Daniele Bizzarri + description: Provides an intuitive framework for ad-hoc statistical analysis of + 1H-NMR metabolomics by Nightingale Health. It allows to easily explore new metabolomics + measurements assayed by Nightingale Health, comparing the distributions with a + large Consortium (BBMRI-nl); project previously published metabolic scores [, + , , , + , ]; and + calibrate the metabolic surrogate values to a desired dataset. + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiMIR + url_git: '' +mimiSBM: + version: 0.0.1.3 + title: Mixture of Multilayer Integrator Stochastic Block Models + maintainer: Kylliann De Santiago + description: 'Our approach uses a mixture of multilayer stochastic block models + to group co-membership matrices with similar information into components and to + partition observations into different clusters. See De Santiago (2023, ISBN: 978-2-87587-088-9).' + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mimiSBM + url_git: '' +MIMSunit: + version: 0.11.2 + title: |- + Algorithm to Compute Monitor Independent Movement Summary Unit + (MIMS-Unit) + maintainer: Qu Tang + description: |- + The MIMS-unit algorithm is developed to compute Monitor Independent + Movement Summary Unit, a measurement to summarize raw accelerometer data + while ensuring harmonized results across different devices. It also includes + scripts to reproduce results in the related publication + (John, D., Tang. Q., Albinali, F. and Intille, S. (2019) ). + date_publication: '2022-06-21' + bug_reports: https://github.com/mhealthgroup/MIMSunit/issues/ + url: https://mhealthgroup.github.io/MIMSunit/ + url_cran: https://CRAN.R-project.org/package=MIMSunit + url_git: https://github.com/mhealthgroup/MIMSunit/tree/master +mimsy: + version: 0.6.5 + title: |- + Calculate MIMS Dissolved Gas Concentrations Without Getting a + Headache + maintainer: Michelle Catherine Kelly + description: |- + Calculate dissolved gas concentrations from raw MIMS + (Membrane Inlet Mass Spectrometer) signal data. Use mimsy() on + a formatted CSV file to return dissolved gas concentrations + (mg and microMole) of N2, O2, Ar based on + gas solubility at temperature, pressure, and salinity. See references + Benson and Krause (1984), Garcia and Gordon (1992), Stull (1947), + and Hamme and Emerson (2004) for more information. Easily save the + output to a nicely-formatted multi-tab 'Excel' workbook with mimsy.save(). + Supports dual-temperature standard calibration for dual-bath MIMS setups. + date_publication: '2024-07-18' + bug_reports: https://github.com/michelleckelly/mimsy/issues + url: https://michelleckelly.github.io/mimsy/ + url_cran: https://CRAN.R-project.org/package=mimsy + url_git: https://github.com/michelleckelly/mimsy +minb: + version: 0.1.0 + title: Multiple-Inflated Negative Binomial Model + maintainer: Mingcong Wu + description: |- + Count data is prevalent and informative, with widespread + application in many fields such as social psychology, personality, and + public health. Classical statistical methods for the analysis of count + outcomes are commonly variants of the log-linear model, including + Poisson regression and Negative Binomial regression. However, a + typical problem with count data modeling is inflation, in the sense + that the counts are evidently accumulated on some integers. Such an + inflation problem could distort the distribution of the observed + counts, further bias estimation and increase error, making the classic + methods infeasible. Traditional inflated value selection methods based + on histogram inspection are easy to neglect true points and + computationally expensive in addition. Therefore, we propose a + multiple-inflated negative binomial model to handle count data + modeling with multiple inflated values, achieving data-driven inflated + value selection. The proposed approach provides simultaneous + identification of important regression predictors on the target count + response as well. More details about the proposed method are described in + Li, Y., Wu, M., Wu, M., & Ma, S. (2023) . + date_publication: '2023-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minb + url_git: '' +mind: + version: 1.1.0 + title: Multivariate Model Based Inference for Domains + maintainer: Andrea Fasulo + description: Allows users to produce estimates and MSE for multivariate variables + using Linear Mixed Model. The package follows the approach of Datta, Day and Basawa + (1999) . + date_publication: '2022-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mind + url_git: '' +MindOnStats: + version: '0.11' + title: Data sets included in Utts and Heckard's Mind on Statistics + maintainer: A. Jonathan R. Godfrey + description: 66 data sets that were imported using read.table() where appropriate + but more commonly after converting to a csv file for importing via read.csv(). + date_publication: '2014-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MindOnStats + url_git: '' +mineCitrus: + version: 1.0.0 + title: |- + Extract and Analyze Median Molecule Intensity from 'citrus' + Output + maintainer: Allison Throm + description: |- + Citrus is a computational technique developed for the analysis + of high dimensional cytometry data sets. This package extracts, statistically + analyzes, and visualizes marker expression from 'citrus' data. This code was used to + generate data for Figures 3 and 4 in the forthcoming manuscript: Throm et al. + “Identification of Enhanced Interferon-Gamma Signaling in Polyarticular Juvenile + Idiopathic Arthritis with Mass Cytometry”, JCI-Insight. For more information on Citrus, + please see: Bruggner et al. (2014) . To download + the 'citrus' package, please see . + date_publication: '2018-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mineCitrus + url_git: '' +mined: + version: 1.0-3 + title: Minimum Energy Designs + maintainer: Dianpeng Wang + description: This is a method (MinED) for mining probability distributions using + deterministic sampling which is proposed by Joseph, Wang, Gu, Lv, and Tuo (2019) + . The MinED samples can be used for approximating + the target distribution. They can be generated from a density function that is + known only up to a proportionality constant and thus, it might find applications + in Bayesian computation. Moreover, the MinED samples are generated with much fewer + evaluations of the density function compared to random sampling-based methods + such as MCMC and therefore, this method will be especially useful when the unnormalized + posterior is expensive or time consuming to evaluate. This research is supported + by a U.S. National Science Foundation grant DMS-1712642. + date_publication: '2022-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mined + url_git: '' +MinEDfind: + version: 0.1.3 + title: A Bayesian Design for Minimum Effective Dosing-Finding Trial + maintainer: Chia-Wei Hsu + description: The nonparametric two-stage Bayesian adaptive design is a novel phase + II clinical trial design for finding the minimum effective dose (MinED). This + design is motivated by the top priority and concern of clinicians when testing + a new drug, which is to effectively treat patients and minimize the chance of + exposing them to subtherapeutic or overly toxic doses. It is used to design single-agent + trials. + date_publication: '2020-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MinEDfind + url_git: '' +minerva: + version: 1.5.10 + title: |- + Maximal Information-Based Nonparametric Exploration for Variable + Analysis + maintainer: Michele Filosi + description: |- + Wrapper for 'minepy' implementation of Maximal + Information-based Nonparametric Exploration statistics (MIC and + MINE family). Detailed information of the ANSI C implementation of + 'minepy' can be found at . + date_publication: '2021-06-17' + bug_reports: '' + url: http://minepy.readthedocs.io/en/latest + url_cran: https://CRAN.R-project.org/package=minerva + url_git: '' +minesweeper: + version: 1.0.1 + title: Play Minesweeper + maintainer: Harry Thompson + description: |- + Play and record games of minesweeper using a graphics device that supports event handling. + Replay recorded games and save GIF animations of them. Based on classic minesweeper as detailed by + Crow P. (1997) . + date_publication: '2024-11-20' + bug_reports: https://github.com/hrryt/minesweeper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=minesweeper + url_git: https://github.com/hrryt/minesweeper +mineSweepR: + version: 0.1.1 + title: Mine Sweeper Game + maintainer: Xiurui Zhu + description: This is the very popular mine sweeper game! The game requires you to + find out tiles that contain mines through clues from unmasking neighboring tiles. + Each tile that does not contain a mine shows the number of mines in its adjacent + tiles. If you unmask all tiles that do not contain mines, you win the game; if + you unmask any tile that contains a mine, you lose the game. For further game + instructions, please run `help(run_game)` and check details. This game runs in + X11-compatible devices with `grDevices::x11()`. + date_publication: '2023-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mineSweepR + url_git: '' +minFactorial: + version: 0.1.0 + title: All Possible Minimally Changed Factorial Run Orders + maintainer: Bijoy Chanda + description: In many agricultural, engineering, industrial, post-harvest and processing + experiments, the number of factor level changes and hence the total number of + changes is of serious concern as such experiments may consists of hard-to-change + factors where it is physically very difficult to change levels of some factors + or sometime such experiments may require normalization time to obtain adequate + operating condition. For this reason, run orders that offer the minimum number + of factor level changes and at the same time minimize the possible influence of + systematic trend effects on the experimentation have been sought. Factorial designs + with minimum changes in factors level may be preferred for such situations as + these minimally changed run orders will minimize the cost of the experiments. + For method details see, Bhowmik, A.,Varghese, E., Jaggi, S. and Varghese, C. (2017).This + package used to construct all possible minimally changed factorial run orders + for different experimental set ups along with different statistical criteria to + measure the performance of these designs. It consist of the function minFactDesign(). + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minFactorial + url_git: '' +minic: + version: 1.0.1 + title: Minimization Methods for Ill-Conditioned Problems + maintainer: Bert van der Veen + description: Implementation of methods for minimizing ill-conditioned problems. + Currently only includes regularized (quasi-)newton optimization (Kanzow and Steck + et al. (2023), ). + date_publication: '2024-09-15' + bug_reports: https://github.com/BertvanderVeen/minic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=minic + url_git: https://github.com/BertvanderVeen/minic +miniCRAN: + version: 0.3.0 + title: Create a Mini Version of CRAN Containing Only Selected Packages + maintainer: Andrie de Vries + description: |- + Makes it possible to create an internally consistent + repository consisting of selected packages from CRAN-like repositories. + The user specifies a set of desired packages, and 'miniCRAN' recursively + reads the dependency tree for these packages, then downloads only this + subset. The user can then install packages from this repository directly, + rather than from CRAN. This is useful in production settings, e.g. server + behind a firewall, or remote locations with slow (or zero) Internet access. + date_publication: '2024-03-28' + bug_reports: https://github.com/andrie/miniCRAN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miniCRAN + url_git: https://github.com/andrie/miniCRAN +minidown: + version: 0.4.0 + title: |- + Create Simple Yet Powerful HTML Documents with Light Weight CSS + Frameworks + maintainer: Atsushi Yasumoto + description: |- + Create minimal, responsive, and style-agnostic HTML documents with + the lightweight CSS frameworks such as 'sakura', 'Water.css', and 'spcss'. + Powerful features include table of contents floating as a sidebar, + folding codes and results, and more. + date_publication: '2022-02-08' + bug_reports: https://github.com/atusy/minidown/issues + url: https://minidown.atusy.net + url_cran: https://CRAN.R-project.org/package=minidown + url_git: https://github.com/atusy/minidown +miniGUI: + version: 0.8-1 + title: Tcl/Tk Quick and Simple Function GUI + maintainer: Jorge Luis Ojeda Cabrera + description: |- + Quick and simple Tcl/Tk Graphical User Interface + to call functions. Also comprises a very simple experimental + GUI framework. + date_publication: '2018-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miniGUI + url_git: '' +miniLNM: + version: 0.1.0 + title: Miniature Logistic-Normal Multinomial Models + maintainer: Kris Sankaran + description: 'Logistic-normal Multinomial (LNM) models are common in problems with + multivariate count data. This package gives a simple implementation with a 30 + line ''Stan'' script. This lightweight implementation makes it an easy starting + point for other projects, in particular for downstream tasks that require analysis + of "compositional" data. It can be applied whenever a multinomial probability + parameter is thought to depend linearly on inputs in a transformed, log ratio + space. Additional utilities make it easy to inspect, create predictions, and draw + samples using the fitted models. More about the LNM can be found in Xia et al. + (2013) "A Logistic Normal Multinomial Regression Model for Microbiome Compositional + Data Analysis" and Sankaran and Holmes (2023) "Generative + Models: An Interdisciplinary Perspective" .' + date_publication: '2024-09-13' + bug_reports: https://github.com/krisrs1128/miniLNM/issues/ + url: https://krisrs1128.github.io/miniLNM/ + url_cran: https://CRAN.R-project.org/package=miniLNM + url_git: https://github.com/krisrs1128/miniLNM/ +minimalRSD: + version: 1.0.0 + title: Minimally Changed CCD and BBD + maintainer: Shwetank Lall + description: |- + Generate central composite designs (CCD)with full as well + as fractional factorial points (half replicate) and Box Behnken + designs (BBD) with minimally changed run sequence. + date_publication: '2017-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minimalRSD + url_git: '' +minimap: + version: 0.1.0 + title: Create Tile Grid Maps + maintainer: Sean Kross + description: |- + Create tile grid maps, which are like choropleth maps except each + region is represented with equal visual space. + date_publication: '2016-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minimap + url_git: http://github.com/seankross/minimap +minimax: + version: 1.1.1 + title: The Minimax Distribution Family + maintainer: Bill Venables + description: |- + The minimax family of distributions is a two-parameter + family like the beta family, but computationally a lot more + tractible. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minimax + url_git: '' +minimaxApprox: + version: 0.4.3 + title: |- + Implementation of Remez Algorithm for Polynomial and Rational + Function Approximation + maintainer: Avraham Adler + description: |- + Implements the algorithm of Remez (1962) for polynomial minimax + approximation and of Cody et al. (1968) for + rational minimax approximation. + date_publication: '2024-06-20' + bug_reports: https://github.com/aadler/MiniMaxApprox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=minimaxApprox + url_git: https://github.com/aadler/MiniMaxApprox +miniMeta: + version: 0.3.2 + title: Web Application to Run Meta-Analyses + maintainer: Theodore Lytras + description: |- + Shiny web application to run meta-analyses. + Essentially a graphical front-end to package 'meta' for R. + Can be useful as an educational tool, and for quickly + analyzing and sharing meta-analyses. + Provides output to quickly fill in GRADE (Grading of + Recommendations, Assessment, Development and Evaluations) + Summary-of-Findings tables. + Importantly, it allows further processing of the results + inside R, in case more specific analyses are needed. + date_publication: '2024-06-22' + bug_reports: https://github.com/thlytras/miniMeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miniMeta + url_git: https://github.com/thlytras/miniMeta +minioclient: + version: 0.0.6 + title: Interface to the 'MinIO' Client + maintainer: Carl Boettiger + description: |- + An R interface to the 'MinIO' Client. The 'MinIO' Client ('mc') + provides a modern alternative to UNIX commands like 'ls', 'cat', 'cp', + 'mirror', 'diff', 'find' etc. It supports 'filesystems' and Amazon "S3" + compatible cloud storage service ("AWS" Signature v2 and v4). + This package provides convenience functions for installing the 'MinIO' + client and running any operations, as described in the official + documentation, . + This package provides a flexible and high-performance alternative to 'aws.s3'. + date_publication: '2023-11-07' + bug_reports: https://github.com/cboettig/minioclient/issues + url: https://cboettig.github.io/minioclient/ + url_cran: https://CRAN.R-project.org/package=minioclient + url_git: https://github.com/cboettig/minioclient +miniPCH: + version: 0.4.0 + title: Survival Distributions with Piece-Wise Constant Hazards + maintainer: Tobias Fellinger + description: |- + Density, distribution function, ... hazard function, cumulative + hazard function, survival function for survival distributions with + piece-wise constant hazards and multiple states and methods to plot and + summarise those distributions. + A derivation of the used algorithms can be found in my masters thesis + . + date_publication: '2024-10-31' + bug_reports: https://github.com/SimNPH/miniPCH/issues/ + url: https://simnph.github.io/miniPCH/ + url_cran: https://CRAN.R-project.org/package=miniPCH + url_git: https://github.com/SimNPH/miniPCH +Minirand: + version: 0.1.3 + title: Minimization Randomization + maintainer: Man Jin + description: Randomization schedules are generated in the schemes with k (k>=2) + treatment groups and any allocation ratios by minimization algorithms. + date_publication: '2020-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Minirand + url_git: '' +minired: + version: 1.0.1 + title: R Interface to 'Redatam' Library + maintainer: Jaime Salvador + description: |- + This package is deprecated. Please use 'redatamx' instead. + Provides an API to work with 'Redatam' (see ) + databases in both formats: 'RXDB' (new format) and 'DICX' (old format) and running + 'Redatam' programs written in 'SPC' language. It's a wrapper around 'Redatam' + core and provides functions to open/close a database (redatam_open()/redatam_close()), + list entities and variables from the database (redatam_entities(), redatam_variables()) + and execute a 'SPC' program and gets the results as data frames + (redatam_query(), redatam_run()). + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minired + url_git: '' +miniUI: + version: 0.1.1.1 + title: Shiny UI Widgets for Small Screens + maintainer: Joe Cheng + description: |- + Provides UI widget and layout functions for writing Shiny apps + that work well on small screens. + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miniUI + url_git: '' +minMSE: + version: 0.5.1 + title: |- + Implementation of the minMSE Treatment Assignment Method for One + or Multiple Treatment Groups + maintainer: Sebastian O. Schneider + description: 'Performs treatment assignment for (field) experiments considering + available, possibly multivariate and continuous, information (covariates, observable + characteristics), that is: forms balanced treatment groups, according to the minMSE-method + as proposed by Schneider and Schlather (2017) .' + date_publication: '2021-11-26' + bug_reports: '' + url: https://www.sebastianoschneider.com + url_cran: https://CRAN.R-project.org/package=minMSE + url_git: '' +minpack.lm: + version: 1.2-4 + title: |- + R Interface to the Levenberg-Marquardt Nonlinear Least-Squares + Algorithm Found in MINPACK, Plus Support for Bounds + maintainer: Katharine M. Mullen + description: The nls.lm function provides an R interface to lmder and lmdif from + the MINPACK library, for solving nonlinear least-squares problems by a modification + of the Levenberg-Marquardt algorithm, with support for lower and upper parameter + bounds. The implementation can be used via nls-like calls using the nlsLM function. + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minpack.lm + url_git: '' +minqa: + version: 1.2.8 + title: |- + Derivative-Free Optimization Algorithms by Quadratic + Approximation + maintainer: Katharine M. Mullen + description: |- + Derivative-free optimization by quadratic approximation + based on an interface to Fortran implementations by M. J. D. + Powell. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minqa + url_git: http://optimizer.r-forge.r-project.org +minque: + version: 2.0.0 + title: Various Linear Mixed Model Analyses + maintainer: Jixiang Wu + description: 'This package offers three important components: (1) to construct a + use-defined linear mixed model, (2) to employ one of linear mixed model approaches: + minimum norm quadratic unbiased estimation (MINQUE) (Rao, 1971) for variance component + estimation and random effect prediction; and (3) to employ a jackknife resampling + technique to conduct various statistical tests. In addition, this package provides + the function for model or data evaluations.This R package offers fast computations + for large data sets analyses for various irregular data structures.' + date_publication: '2019-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minque + url_git: '' +minsample1: + version: 0.1.0 + title: The Minimum Sample Size + maintainer: Anik Paul + description: Using this package, one can determine the minimum sample size required + so that the absolute deviation of the sample mean and the population mean of a + distribution becomes less than some pre-determined epsilon, i.e. it helps the + user to determine the minimum sample size required to attain the pre-fixed precision + level by minimizing the difference between the sample mean and population mean. + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minsample1 + url_git: '' +minsample2: + version: 0.1.0 + title: The Minimum Sample Size + maintainer: Anik Paul + description: Using this package, one can determine the minimum sample size required + so that the mean square error of the sample mean and the population mean of a + distribution becomes less than some pre-determined epsilon, i.e. it helps the + user to determine the minimum sample size required to attain the pre-fixed precision + level by minimizing the difference between the sample mean and population mean. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minsample2 + url_git: '' +minSNPs: + version: 0.2.0 + title: Resolution-Optimised SNPs Searcher + maintainer: Ludwig Kian Soon Hoon + description: This is a R implementation of "Minimum SNPs" software as described + in "Price E.P., Inman-Bamber, J., Thiruvenkataswamy, V., Huygens, F and Giffard, + P.M." (2007) "Computer-aided identification of polymorphism + sets diagnostic for groups of bacterial and viral genetic variants." + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=minSNPs + url_git: https://github.com/ludwigHoon/minSNPs +MINTplates: + version: 1.0.1 + title: Encode "License-Plates" from Sequences and Decode Them Back + maintainer: Shanliang Zhong + description: 'It can be used to create/encode molecular "license-plates" from sequences + and to also decode the "license-plates" back to sequences. While initially created + for transfer RNA-derived small fragments (tRFs), this tool can be used for any + genomic sequences including but not limited to: tRFs, microRNAs, etc. The detailed + information can reference to Pliatsika V, Loher P, Telonis AG, Rigoutsos I (2016) + . It can also be used to annotate tRFs. The + detailed information can reference to Loher P, Telonis AG, Rigoutsos I (2017) + .' + date_publication: '2021-09-03' + bug_reports: '' + url: http://www.bio-inf.cn/ + url_cran: https://CRAN.R-project.org/package=MINTplates + url_git: '' +minty: + version: 0.0.5 + title: Minimal Type Guesser + maintainer: Chung-hong Chan + description: Port the type guesser from 'readr' (so-called 'readr' first edition + parsing engine, now superseded by 'vroom'). + date_publication: '2025-01-07' + bug_reports: https://github.com/gesistsa/minty/issues + url: https://gesistsa.github.io/minty/ + url_cran: https://CRAN.R-project.org/package=minty + url_git: https://github.com/gesistsa/minty +mintyr: + version: 0.1.0 + title: Streamlined Data Processing Tools for Genomic Selection + maintainer: Guo Meng + description: |- + A toolkit for genomic selection in animal breeding with + emphasis on multi-breed and multi-trait nested grouping operations. + Streamlines iterative analysis workflows when working with 'ASReml-R' + package. Includes utility functions for phenotypic data processing + commonly used by animal breeders. + date_publication: '2024-12-13' + bug_reports: https://github.com/tony2015116/mintyr/issues + url: https://tony2015116.github.io/mintyr/ + url_cran: https://CRAN.R-project.org/package=mintyr + url_git: '' +mipfp: + version: 3.2.1 + title: |- + Multidimensional Iterative Proportional Fitting and Alternative + Models + maintainer: Johan Barthelemy + description: |- + An implementation of the iterative proportional fitting (IPFP), + maximum likelihood, minimum chi-square and weighted least squares procedures + for updating a N-dimensional array with respect to given target marginal + distributions (which, in turn can be multidimensional). The package also + provides an application of the IPFP to simulate multivariate Bernoulli + distributions. + date_publication: '2018-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mipfp + url_git: https://github.com/jojo-/mipfp +mipplot: + version: 0.3.1 + title: |- + An Open-Source Tool for Visualization of Climate Mitigation + Scenarios + maintainer: Akimitsu Inoue + description: Generic functions to produce area/bar/box/line plots of data following + IAMC (Integrated Assessment Modeling Consortium) submission format. + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mipplot + url_git: '' +mirai: + version: 2.1.0 + title: Minimalist Async Evaluation Framework for R + maintainer: Charlie Gao + description: |- + Designed for simplicity, a 'mirai' evaluates an R expression + asynchronously in a parallel process, locally or distributed over the + network. The result is automatically available upon completion. Modern + networking and concurrency, built on 'nanonext' and 'NNG' (Nanomsg Next + Gen), ensures reliable and efficient scheduling over fast inter-process + communications or TCP/IP secured by TLS. Distributed computing can launch + remote resources via SSH or cluster managers. An inherently queued + architecture handles many more tasks than available processes, and requires + no storage on the file system. Innovative features include support for + otherwise non-exportable reference objects, event-driven promises, and + asynchronous parallel map. + date_publication: '2025-02-07' + bug_reports: https://github.com/shikokuchuo/mirai/issues + url: https://shikokuchuo.net/mirai/ + url_cran: https://CRAN.R-project.org/package=mirai + url_git: https://github.com/shikokuchuo/mirai/ +miRecSurv: + version: 1.0.2 + title: Left-Censored Recurrent Events Survival Models + maintainer: David Moriña + description: |- + Fitting recurrent events survival models for + left-censored data with multiple imputation of the number of previous episodes. + See Hernández-Herrera G, Moriña D, Navarro A. (2020) . + date_publication: '2021-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miRecSurv + url_git: '' +MIRES: + version: 0.1.0 + title: |- + Measurement Invariance Assessment Using Random Effects Models + and Shrinkage + maintainer: Stephen Martin + description: Estimates random effect latent measurement models, wherein the loadings, + residual variances, intercepts, latent means, and latent variances all vary across + groups. The random effect variances of the measurement parameters are then modeled + using a hierarchical inclusion model, wherein the inclusion of the variances (i.e., + whether it is effectively zero or non-zero) is informed by similar parameters + (of the same type, or of the same item). This additional hierarchical structure + allows the evidence in favor of partial invariance to accumulate more quickly, + and yields more certain decisions about measurement invariance. Martin, Williams, + and Rast (2020) . + date_publication: '2021-02-22' + bug_reports: https://github.com/stephenSRMMartin/MIRES/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MIRES + url_git: '' +miRetrieve: + version: 1.3.4 + title: miRNA Text Mining in Abstracts + maintainer: Julian Friedrich + description: |- + Providing tools for microRNA (miRNA) text mining. + miRetrieve summarizes miRNA literature by extracting, counting, and + analyzing miRNA names, thus aiming at gaining biological insights into a + large amount of text within a short period of time. To do so, miRetrieve + uses regular expressions to extract miRNAs and tokenization to + identify meaningful miRNA associations. In addition, miRetrieve uses + the latest miRTarBase version 8.0 (Hsi-Yuan Huang et al. (2020) + "miRTarBase 2020: updates to the experimentally validated microRNA–target + interaction database" ) to display field-specific + miRNA-mRNA interactions. The most important functions are available as a + Shiny web application under . + date_publication: '2021-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miRetrieve + url_git: '' +MiRKAT: + version: 1.2.3 + title: Microbiome Regression-Based Kernel Association Tests + maintainer: Anna Plantinga + description: |- + Test for overall association between microbiome composition data + and phenotypes via phylogenetic kernels. The phenotype can be univariate + continuous or binary (Zhao et al. (2015) ), + survival outcomes (Plantinga et al. (2017) ), + multivariate (Zhan et al. (2017) ) and + structured phenotypes (Zhan et al. (2017) ). + The package can also use robust regression (unpublished work) and + integrated quantile regression (Wang et al. (2021) ). + In each case, the microbiome community effect is modeled nonparametrically + through a kernel function, which can incorporate phylogenetic tree information. + date_publication: '2023-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiRKAT + url_git: '' +MiRNAQCD: + version: 1.1.3 + title: Micro-RNA Quality Control and Diagnosis + maintainer: Alessio Perinelli + description: 'A complete and dedicated analytical toolbox for quality control and + diagnosis based on subject-related measurements of micro-RNA (miRNA) expressions. + The package consists of a set of functions that allow to train, optimize and use + a Bayesian classifier that relies on multiplets of measured miRNA expressions. + The package also implements the quality control tools required to preprocess input + datasets. In addition, the package provides a function to carry out a statistical + analysis of miRNA expressions, which can give insights to improve the classifier''s + performance. The method implemented in the package was first introduced in L. + Ricci, V. Del Vescovo, C. Cantaloni, M. Grasso, M. Barbareschi and M. A. Denti, + "Statistical analysis of a Bayesian classifier based on the expression of miRNAs", + BMC Bioinformatics 16:287, 2015 . The package is + thoroughly described in M. Castelluzzo, A. Perinelli, S. Detassis, M. A. Denti + and L. Ricci, "MiRNA-QC-and-Diagnosis: An R package for diagnosis based on MiRNA + expression", SoftwareX 12:100569, 2020 . Please + cite both these works if you use the package for your analysis. DISCLAIMER: The + software in this package is for general research purposes only and is thus provided + WITHOUT ANY WARRANTY. It is NOT intended to form the basis of clinical decisions. + Please refer to the GNU General Public License 3.0 (GPLv3) for further information.' + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiRNAQCD + url_git: '' +miRNAss: + version: '1.5' + title: Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples + maintainer: Cristian Yones + description: |- + Machine learning method specifically designed for + pre-miRNA prediction. It takes advantage of unlabeled sequences to improve + the prediction rates even when there are just a few positive examples, when + the negative examples are unreliable or are not good representatives of + its class. Furthermore, the method can automatically search for negative + examples if the user is unable to provide them. MiRNAss can find a good + boundary to divide the pre-miRNAs from other groups of sequences; it + automatically optimizes the threshold that defines the classes boundaries, + and thus, it is robust to high class imbalance. Each step of the method is + scalable and can handle large volumes of data. + date_publication: '2020-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miRNAss + url_git: '' +mirrorselect: + version: 0.0.3 + title: Test CRAN/Bioconductor Mirror Speed + maintainer: Guangchuang Yu + description: Testing CRAN and Bioconductor mirror speed by recording download time + of 'src/base/COPYING' (for CRAN) and 'packages/release/bioc/html/ggtree.html' + (for Bioconductor). + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mirrorselect + url_git: '' +MiRSEA: + version: 1.1.1 + title: '''MicroRNA'' Set Enrichment Analysis' + maintainer: Junwei Han + description: The tools for 'MicroRNA Set Enrichment Analysis' can identify risk + pathways(or prior gene sets) regulated by microRNA set in the context of microRNA + expression data. (1) This package constructs a correlation profile of microRNA + and pathways by the hypergeometric statistic test. The gene sets of pathways derived + from the three public databases (Kyoto Encyclopedia of Genes and Genomes ('KEGG'); + 'Reactome'; 'Biocarta') and the target gene sets of microRNA are provided by four + databases('TarBaseV6.0'; 'mir2Disease'; 'miRecords'; 'miRTarBase';). (2) This + package can quantify the change of correlation between microRNA for each pathway(or + prior gene set) based on a microRNA expression data with cases and controls. (3) + This package uses the weighted Kolmogorov-Smirnov statistic to calculate an enrichment + score (ES) of a microRNA set that co-regulate to a pathway , which reflects the + degree to which a given pathway is associated with the specific phenotype. (4) + This package can provide the visualization of the results. + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiRSEA + url_git: '' +mirt: + version: 1.44.0 + title: Multidimensional Item Response Theory + maintainer: Phil Chalmers + description: |- + Analysis of discrete response data using + unidimensional and multidimensional item analysis models under the Item + Response Theory paradigm (Chalmers (2012) ). + Exploratory and confirmatory item factor analysis models + are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory + bi-factor and two-tier models are available for modeling item testlets using + dimension reduction EM algorithms, while multiple group analyses and + mixed effects designs are included for detecting differential item, bundle, + and test functioning, and for modeling item and person covariates. + Finally, latent class models such as the DINA, DINO, multidimensional latent class, + mixture IRT models, and zero-inflated response models are supported, as well + as a wide family of probabilistic unfolding models. + date_publication: '2025-01-28' + bug_reports: https://github.com/philchalmers/mirt/issues?state=open + url: https://philchalmers.github.io/mirt/ + url_cran: https://CRAN.R-project.org/package=mirt + url_git: https://github.com/philchalmers/mirt/wiki +mirtCAT: + version: '1.14' + title: |- + Computerized Adaptive Testing with Multidimensional Item + Response Theory + maintainer: Phil Chalmers + description: |- + Provides tools to generate HTML interfaces for adaptive + and non-adaptive tests using the shiny + package (Chalmers (2016) ). + Suitable for applying unidimensional and multidimensional + computerized adaptive tests (CAT) using item response theory methodology and for + creating simple questionnaires forms to collect response data directly in R. + Additionally, optimal test designs (e.g., "shadow testing") are supported + for tests that contain a large number of item selection constraints. + Finally, package contains tools useful for performing Monte Carlo simulations + for studying test item banks. + date_publication: '2024-07-12' + bug_reports: https://github.com/philchalmers/mirtCAT/issues?state=open + url: https://groups.google.com/forum/#!forum/mirt-package + url_cran: https://CRAN.R-project.org/package=mirtCAT + url_git: https://github.com/philchalmers/mirtCAT +miRtest: + version: '2.1' + title: Combined miRNA- And mRNA-Testing + maintainer: Stephan Artmann + description: Package for combined miRNA- and mRNA-testing. + date_publication: '2024-02-05' + bug_reports: '' + url: https://pubmed.ncbi.nlm.nih.gov/22723856/ + url_cran: https://CRAN.R-project.org/package=miRtest + url_git: '' +mirtjml: + version: 1.4.0 + title: |- + Joint Maximum Likelihood Estimation for High-Dimensional Item + Factor Analysis + maintainer: Siliang Zhang + description: |- + Provides constrained joint maximum likelihood estimation + algorithms for item factor analysis (IFA) based on multidimensional item response theory + models. So far, we provide functions for exploratory and confirmatory IFA based on the + multidimensional two parameter logistic (M2PL) model for binary response data. Comparing + with traditional estimation methods for IFA, the methods implemented in this package scale + better to data with large numbers of respondents, items, and latent factors. The computation + is facilitated by multiprocessing 'OpenMP' API. For more information, please refer to: + 1. Chen, Y., Li, X., & Zhang, S. (2018). Joint Maximum Likelihood Estimation for + High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23. + ; + 2. Chen, Y., Li, X., & Zhang, S. (2019). Structured Latent Factor Analysis for Large-scale Data: + Identifiability, Estimability, and Their Implications. Journal of the American Statistical + Association, . + date_publication: '2020-06-08' + bug_reports: https://github.com/slzhang-fd/mirtjml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mirtjml + url_git: https://github.com/slzhang-fd/mirtjml +mirtsvd: + version: '1.0' + title: SVD-Based Estimation for Exploratory Item Factor Analysis + maintainer: Haoran Zhang + description: |- + Provides singular value decomposition based estimation algorithms for exploratory item factor analysis (IFA) + based on multidimensional item response theory models. For more information, please refer to: + Zhang, H., Chen, Y., & Li, X. (2020). A note on exploratory item factor analysis by + singular value decomposition. Psychometrika, 1-15, . + date_publication: '2020-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mirtsvd + url_git: '' +misaem: + version: 1.0.1 + title: |- + Linear Regression and Logistic Regression with Missing + Covariates + maintainer: Julie Josse + description: Estimate parameters of linear regression and logistic regression with + missing covariates with missing data, perform model selection and prediction, + using EM-type algorithms. Jiang W., Josse J., Lavielle M., TraumaBase Group (2020) + . + date_publication: '2021-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misaem + url_git: https://github.com/julierennes/misaem +misc3d: + version: 0.9-1 + title: Miscellaneous 3D Plots + maintainer: Luke Tierney + description: |- + A collection of miscellaneous 3d plots, including + isosurfaces. + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misc3d + url_git: https://gitlab.com/luke-tierney/misc3d +miscF: + version: 0.1-5 + title: Miscellaneous Functions + maintainer: Dai Feng + description: |- + Various functions for random number generation, density + estimation, classification, curve fitting, and spatial + data analysis. + date_publication: '2020-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miscF + url_git: '' +miscFuncs: + version: 1.5-10 + title: |- + Miscellaneous Useful Functions Including LaTeX Tables, Kalman + Filtering, QQplots with Simulation-Based Confidence Intervals, + Linear Regression Diagnostics and Development Tools + maintainer: Benjamin M. Taylor + description: |- + Implementing various things including functions for LaTeX tables, + the Kalman filter, QQ-plots with simulation-based confidence intervals, linear regression diagnostics, web scraping, development tools, relative risk and odds + rati, GARCH(1,1) Forecasting. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miscFuncs + url_git: '' +miscIC: + version: 0.1.0 + title: Misclassified Interval Censored Time-to-Event Data + maintainer: Andrew Titman + description: Estimation of the survivor function for interval censored time-to-event + data subject to misclassification using nonparametric maximum likelihood estimation, + implementing the methods of Titman (2017) . Misclassification + probabilities can either be specified as fixed or estimated. Models with time + dependent misclassification may also be fitted. + date_publication: '2019-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miscIC + url_git: '' +misclassGLM: + version: 0.3.5 + title: |- + Computation of Generalized Linear Models with Misclassified + Covariates Using Side Information + maintainer: Stephan Dlugosz + description: |- + Estimates models that extend the standard GLM to take + misclassification into account. The models require side information from a secondary data set + on the misclassification process, i.e. some sort of misclassification + probabilities conditional on some common covariates. + A detailed description of the algorithm can be found in + Dlugosz, Mammen and Wilke (2015) . + date_publication: '2023-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misclassGLM + url_git: '' +MiscMath: + version: '1.0' + title: Miscellaneous Mathematical Tools + maintainer: W.J. Braun + description: Some basic math calculators for finding angles for triangles and for + finding the greatest common divisor of two numbers and so on. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiscMath + url_git: '' +miscset: + version: 1.1.0 + title: Miscellaneous Tools Set + maintainer: Sven E. Templer + description: |- + A collection of miscellaneous methods to simplify various tasks, + including plotting, data.frame and matrix transformations, environment + functions, regular expression methods, and string and logical operations, as + well as numerical and statistical tools. Most of the methods are simple but + useful wrappers of common base R functions, which extend S3 generics or + provide default values for important parameters. + date_publication: '2017-02-24' + bug_reports: https://github.com/setempler/miscset/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miscset + url_git: https://github.com/setempler/miscset +miscTools: + version: 0.6-28 + title: Miscellaneous Tools and Utilities + maintainer: Arne Henningsen + description: |- + Miscellaneous small tools and utilities. + Many of them facilitate the work with matrices, + e.g. inserting rows or columns, creating symmetric matrices, + or checking for semidefiniteness. + Other tools facilitate the work with regression models, + e.g. extracting the standard errors, + obtaining the number of (estimated) parameters, + or calculating R-squared values. + date_publication: '2023-05-03' + bug_reports: https://github.com/arne-henningsen/miscTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miscTools + url_git: https://github.com/arne-henningsen/miscTools +miselect: + version: 0.9.2 + title: Variable Selection for Multiply Imputed Data + maintainer: Michael Kleinsasser + description: |2- + + Penalized regression methods, such as lasso and elastic net, are used in + many biomedical applications when simultaneous regression coefficient + estimation and variable selection is desired. However, missing data + complicates the implementation of these methods, particularly when + missingness is handled using multiple imputation. Applying a variable + selection algorithm on each imputed dataset will likely lead + to different sets of selected predictors, making it difficult + to ascertain a final active set without resorting to ad hoc + combination rules. 'miselect' presents Stacked Adaptive Elastic Net (saenet) + and Grouped Adaptive LASSO (galasso) for continuous and binary outcomes, + developed by Du et al (2022) . They, + by construction, force selection of the same variables across multiply + imputed data. 'miselect' also provides cross validated variants of these + methods. + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=miselect + url_git: '' +mispitools: + version: 1.2.0 + title: Missing Person Identification Tools + maintainer: Franco Marsico + description: 'An open source software package written in R statistical language. + It consist in a set of decision making tools to conduct missing person searches. Particularly, + it allows computing optimal LR threshold for declaring potential matches in DNA-based + database search. More recently ''mispitools'' incorporates preliminary investigation + data based LRs. Statistical weight of different traces of evidence such as biological + sex, age and hair color are presented. For citing mispitools please use the following + references: Marsico and Caridi, 2023 and Marsico, + Vigeland et al. 2021 .' + date_publication: '2024-08-17' + bug_reports: https://github.com/MarsicoFL/mispitools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mispitools + url_git: https://github.com/MarsicoFL/mispitools +mispr: + version: 1.0.0 + title: Multiple Imputation with Sequential Penalized Regression + maintainer: Faisal Maqbool Zahid + description: Generates multivariate imputations using sequential regression with + L2 penalty. For more details see Zahid and Heumann (2018) . + date_publication: '2018-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mispr + url_git: '' +misPRIME: + version: 0.1.0 + title: Partial Replacement Imputation Estimation for Missing Covariates + maintainer: Zishu Zhan + description: |- + Partial Replacement Imputation Estimation (PRIME) can overcome problems caused by missing covariates in additive partially linear model. PRIME conducts imputation and regression simultaneously with known and unknown model structure. More details can be referred to + Zishu Zhan, Xiangjie Li and Jingxiao Zhang. (2022) . + date_publication: '2022-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misPRIME + url_git: '' +MiSPU: + version: '1.0' + title: Microbiome Based Sum of Powered Score (MiSPU) Tests + maintainer: Chong Wu + description: There is an increasing interest in investigating how the compositions + of microbial communities are associated with human health and disease. In this + package, we present a novel global testing method called aMiSPU, that is highly + adaptive and thus high powered across various scenarios, alleviating the issue + with the choice of a phylogenetic distance. Our simulations and real data analysis + demonstrated that aMiSPU test was often more powerful than several competing methods + while correctly controlling type I error rates. + date_publication: '2016-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MiSPU + url_git: '' +MisRepARMA: + version: 0.0.2 + title: Misreported Time Series Analysis + maintainer: David Moriña Soler + description: Provides a simple and trustworthy methodology for the analysis of misreported + continuous time series. See Moriña, D, Fernández-Fontelo, A, Cabaña, A, Puig P. + (2021) . + date_publication: '2021-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MisRepARMA + url_git: '' +missCforest: + version: 0.0.8 + title: Ensemble Conditional Trees for Missing Data Imputation + maintainer: Imad El Badisy + description: Single imputation based on the Ensemble Conditional Trees (i.e. Cforest + algorithm Strobl, C., Boulesteix, A. L., Zeileis, A., & Hothorn, T. (2007) ). + date_publication: '2023-01-17' + bug_reports: https://github.com/ielbadisy/missCforest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=missCforest + url_git: https://github.com/ielbadisy/missCforest +missCompare: + version: 1.0.3 + title: Intuitive Missing Data Imputation Framework + maintainer: Tibor V. Varga + description: |- + Offers a convenient pipeline to test and compare various missing data + imputation algorithms on simulated and real data. These include simpler methods, such as mean and median + imputation and random replacement, but also include more sophisticated algorithms already implemented in popular + R packages, such as 'mi', described by Su et al. (2011) ; 'mice', described by van Buuren + and Groothuis-Oudshoorn (2011) ; 'missForest', described by Stekhoven and Buhlmann (2012) + ; 'missMDA', described by Josse and Husson (2016) ; and + 'pcaMethods', described by Stacklies et al. (2007) . The central assumption behind + 'missCompare' is that structurally different datasets (e.g. larger datasets with a large number of correlated variables + vs. smaller datasets with non correlated variables) will benefit differently from different missing data imputation + algorithms. 'missCompare' takes measurements of your dataset and sets up a sandbox to try a curated list of standard and + sophisticated missing data imputation algorithms and compares them assuming custom missingness patterns. + 'missCompare' will also impute your real-life dataset for you after the selection of the best performing algorithm + in the simulations. The package also provides various post-imputation diagnostics and visualizations to help you + assess imputation performance. + date_publication: '2020-12-01' + bug_reports: https://github.com/Tirgit/missCompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=missCompare + url_git: '' +MissCP: + version: 0.1.1 + title: Change Point Detection with Missing Values + maintainer: Yanxi Liu + description: A four step change point detection method that can detect break points + with the presence of missing values proposed by Liu and Safikhani (2023) . + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MissCP + url_git: '' +missDeaths: + version: '2.8' + title: |- + Simulating and Analyzing Time to Event Data in the Presence of + Population Mortality + maintainer: Tomaz Stupnik + description: |- + Implements two methods: a nonparametric risk adjustment and a + data imputation method that use general population mortality tables to allow a + correct analysis of time to disease recurrence. Also includes a powerful set of + object oriented survival data simulation functions. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=missDeaths + url_git: '' +missDiag: + version: 1.0.1 + title: Comparing Observed and Imputed Values under MAR and MCAR + maintainer: Moritz Marbach + description: Implements the computation of discrepancy statistics summarizing differences + between the density of imputed and observed values and the construction of weights + to balance covariates that are part of the missing data mechanism as described + in Marbach (2021) . + date_publication: '2021-08-06' + bug_reports: https://github.com/sumtxt/missDiag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=missDiag + url_git: https://github.com/sumtxt/missDiag/ +missForest: + version: '1.5' + title: Nonparametric Missing Value Imputation using Random Forest + maintainer: Daniel J. Stekhoven + description: |- + The function 'missForest' in this package is used to + impute missing values particularly in the case of mixed-type + data. It uses a random forest trained on the observed values of + a data matrix to predict the missing values. It can be used to + impute continuous and/or categorical data including complex + interactions and non-linear relations. It yields an out-of-bag + (OOB) imputation error estimate without the need of a test set + or elaborate cross-validation. It can be run in parallel to + save computation time. + date_publication: '2022-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=missForest + url_git: https://github.com/stekhoven/missForest +missForestPredict: + version: '1.0' + title: |- + Missing Value Imputation using Random Forest for Prediction + Settings + maintainer: Elena Albu + description: |- + Missing data imputation based on the 'missForest' algorithm (Stekhoven, Daniel J (2012) ) + with adaptations for prediction settings. The function missForest() is used + to impute a (training) dataset with missing values and to learn imputation + models that can be later used for imputing new observations. + The function missForestPredict() is used to impute one or multiple new + observations (test set) using the models learned on the training data. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=missForestPredict + url_git: https://github.com/sibipx/missForestPredict +MissingHandle: + version: 0.1.1 + title: |- + Handles Missing Dates and Data and Converts into Weekly and + Monthly from Daily + maintainer: Mr. Sandip Garai + description: Many times, you will not find data for all dates. After first January, + 2011 you may have next data on 20th January, 2011 and so on. Also available dates + may have zero values. Try to gather all such kinds of data in different excel + sheets of a single excel file. Every sheet will contain two columns (1st one is + dates and second one is the data). After loading all the sheets into different + elements of a list, using this you can fill the gaps for all the sheets and mark + all the corresponding values as zeros. Here I am talking about daily data. Finally, + it will combine all the filled results into one data frame (first column is date + and other columns will be corresponding values of your sheets) and give one combined + data frame. Number of columns in the data frame will be number of sheets plus + one. Then imputation will be done. Daily to monthly and weekly conversion is also + possible. More details can be found in Garai and others (2023) . + date_publication: '2023-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MissingHandle + url_git: '' +missingHE: + version: 1.5.0 + title: Missing Outcome Data in Health Economic Evaluation + maintainer: Andrea Gabrio + description: |- + Contains a suite of functions for health economic evaluations with missing outcome data. + The package can fit different types of statistical models under a fully Bayesian approach using the software 'JAGS' (which should be installed locally and which is loaded in 'missingHE' via the 'R' package 'R2jags'). + Three classes of models can be fitted under a variety of missing data assumptions: selection models, pattern mixture models and hurdle models. + In addition to model fitting, 'missingHE' provides a set of specialised functions to assess model convergence and fit, and to summarise the statistical and economic results using different types of measures and graphs. + The methods implemented are described in Mason (2018) , Molenberghs (2000) and Gabrio (2019) . + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=missingHE + url_git: '' +MissingPlotLSD: + version: 0.1.0 + title: Missing Plot in LSD + maintainer: Debarghya Baul + description: A system for Analysis of LSD when there is one missing observation. + Methods for this process is described in A.M.Gun,M.K.Gupta,B.Dasgupta(2019,ISBN:81-87567-81-3). + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MissingPlotLSD + url_git: '' +MissingPlotRBD: + version: 1.1.0 + title: Missing Plot in RBD + maintainer: Arnab Roy + description: A system for Analysis of RBD when there is one missing observation. + Methods for this process is described in A.M.Gun,M.K.Gupta,B.Dasgupta(2019,ISBN:81-87567-81-3). + date_publication: '2022-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MissingPlotRBD + url_git: '' +missMDA: + version: '1.19' + title: Handling Missing Values with Multivariate Data Analysis + maintainer: Francois Husson + description: Imputation of incomplete continuous or categorical datasets; Missing + values are imputed with a principal component analysis (PCA), a multiple correspondence + analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple + imputation with and in PCA or MCA. + date_publication: '2023-11-17' + bug_reports: '' + url: http://factominer.free.fr/missMDA/index.html + url_cran: https://CRAN.R-project.org/package=missMDA + url_git: '' +MissMech: + version: 1.0.4 + title: |- + Testing Homoscedasticity, Multivariate Normality, and Missing + Completely at Random + maintainer: Mao Kobayashi + description: |- + To test whether the missing data mechanism, in a set of incompletely observed data, is one of missing completely at random (MCAR). + For detailed description see Jamshidian, M. Jalal, S., and Jansen, C. (2014). "MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR)", Journal of Statistical Software, 56(6), 1-31. . + date_publication: '2024-03-05' + bug_reports: https://github.com/indenkun/MissMech/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MissMech + url_git: https://github.com/indenkun/MissMech +missMethods: + version: 0.4.0 + title: Methods for Missing Data + maintainer: Tobias Rockel + description: |- + Supply functions for the creation and handling of missing + data as well as tools to evaluate missing data methods. Nearly all + possibilities of generating missing data discussed by Santos et al. + (2019) and some additional are + implemented. Functions are supplied to compare parameter estimates + and imputed values to true values to evaluate missing data methods. + Evaluations of these types are done, for example, by Cetin-Berber et + al. (2019) and Kim et al. (2005) + . + date_publication: '2022-09-16' + bug_reports: https://github.com/torockel/missMethods/issues + url: '' + url_cran: https://CRAN.R-project.org/package=missMethods + url_git: https://github.com/torockel/missMethods +missoNet: + version: 1.2.0 + title: Missingness in Multi-Task Regression with Network Estimation + maintainer: Yixiao Zeng + description: |- + Efficient procedures for fitting conditional graphical lasso + models that link a set of predictor variables to a set of response + variables (or tasks), even when the response data may contain missing + values. 'missoNet' simultaneously estimates the predictor + coefficients for all tasks by leveraging information from one another, + in order to provide more accurate predictions in comparison to + modeling them individually. Additionally, 'missoNet' estimates the + response network structure influenced by conditioning predictor + variables using a L1-regularized conditional Gaussian graphical model. + Unlike most penalized multi-task regression methods (e.g., MRCE), + 'missoNet' is capable of obtaining estimates even when the response + data is corrupted by missing values. The method automatically enjoys + the theoretical and computational benefits of convexity, and returns + solutions that are comparable to the estimates obtained without + missingness. + date_publication: '2023-07-19' + bug_reports: https://github.com/yixiao-zeng/missoNet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=missoNet + url_git: https://github.com/yixiao-zeng/missoNet +misspi: + version: 0.1.0 + title: Missing Value Imputation in Parallel + maintainer: Zhongli Jiang + description: |- + A framework that boosts the imputation of 'missForest' by Stekhoven, D.J. and Bühlmann, P. (2012) by harnessing parallel processing and through the fast Gradient Boosted Decision Trees (GBDT) implementation 'LightGBM' by Ke, Guolin et al.(2017) . 'misspi' has the following main advantages: + 1. Allows embrassingly parallel imputation on large scale data. + 2. Accepts a variety of machine learning models as methods with friendly user portal. + 3. Supports multiple initializations methods. + 4. Supports early stopping that prohibits unnecessary iterations. + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misspi + url_git: '' +Missplot: + version: 0.1.0 + title: Missing Plot Technique in Design of Experiment + maintainer: Shantanu Nayek + description: A system for testing differential effects among treatments in case + of Randomised Block Design and Latin Square Design when there is one missing observation. + Methods for this process are as described in A.M.Gun,M.K.Gupta and B.Dasgupta(2019,ISBN:81-87567-81-3). + date_publication: '2022-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Missplot + url_git: '' +missRanger: + version: 2.6.1 + title: Fast Imputation of Missing Values + maintainer: Michael Mayer + description: |- + Alternative implementation of the beautiful 'MissForest' + algorithm used to impute mixed-type data sets by chaining random + forests, introduced by Stekhoven, D.J. and Buehlmann, P. (2012) + . Under the hood, it uses the + lightning fast random forest package 'ranger'. Between the iterative + model fitting, we offer the option of using predictive mean matching. + This firstly avoids imputation with values not already present in the + original data (like a value 0.3334 in 0-1 coded variable). Secondly, + predictive mean matching tries to raise the variance in the resulting + conditional distributions to a realistic level. This would allow, + e.g., to do multiple imputation when repeating the call to + missRanger(). Out-of-sample application is supported as well. + date_publication: '2024-12-07' + bug_reports: https://github.com/mayer79/missRanger/issues + url: https://mayer79.github.io/missRanger/ + url_cran: https://CRAN.R-project.org/package=missRanger + url_git: https://github.com/mayer79/missRanger +missSBM: + version: 1.0.4 + title: Handling Missing Data in Stochastic Block Models + maintainer: Julien Chiquet + description: |- + When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0 + due to missing information between node pairs), it is possible to account for the underlying process + that generates those NAs. 'missSBM', presented in 'Barbillon, Chiquet and Tabouy' (2022) , + adjusts the popular stochastic block model from network data sampled under various missing data conditions, + as described in 'Tabouy, Barbillon and Chiquet' (2019) . + date_publication: '2023-10-24' + bug_reports: https://github.com/grossSBM/missSBM/issues + url: https://grosssbm.github.io/missSBM/ + url_cran: https://CRAN.R-project.org/package=missSBM + url_git: '' +missSOM: + version: 1.0.1 + title: Self-Organizing Maps with Built-in Missing Data Imputation + maintainer: Sara Rejeb + description: |- + The Self-Organizing Maps with Built-in Missing Data Imputation. Missing values are imputed and regularly updated during the online Kohonen algorithm. Our method can be used for data visualisation, clustering or imputation of missing data. It is an extension of the online algorithm of the 'kohonen' package. The method is described + in the article "Self-Organizing Maps for Exploration of Partially Observed Data and Imputation of Missing Values" by S. Rejeb, C. Duveau, T. Rebafka (2022) . + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=missSOM + url_git: '' +mistr: + version: 0.0.6 + title: Mixture and Composite Distributions + maintainer: Lukas Sablica + description: A flexible computational framework for mixture distributions with the + focus on the composite models. + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mistr + url_git: '' +mistral: + version: 2.2.2 + title: Methods in Structural Reliability + maintainer: Bertrand Iooss + description: Various reliability analysis methods for rare event inference (computing + failure probability and quantile from model/function outputs). + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mistral + url_git: '' +misty: + version: 0.7.0 + title: Miscellaneous Functions 'T. Yanagida' + maintainer: Takuya Yanagida + description: Miscellaneous functions for (1) data management (e.g., grand-mean and + group-mean centering, coding variables and reverse coding items, scale and cluster + scores, reading and writing Excel and SPSS files), (2) descriptive statistics + (e.g., frequency table, cross tabulation, effect size measures), (3) missing data + (e.g., descriptive statistics for missing data, missing data pattern, Little's + test of Missing Completely at Random, and auxiliary variable analysis), (4) multilevel + data (e.g., multilevel descriptive statistics, within-group and between-group + correlation matrix, multilevel confirmatory factor analysis, level-specific fit + indices, cross-level measurement equivalence evaluation, multilevel composite + reliability, and multilevel R-squared measures), (5) item analysis (e.g., confirmatory + factor analysis, coefficient alpha and omega, between-group and longitudinal measurement + equivalence evaluation), (6) statistical analysis (e.g., bootstrap confidence + intervals, collinearity and residual diagnostics, dominance analysis, between- + and within-subject analysis of variance, latent class analysis, t-test, z-test, + sample size determination), and (7) functions to interact with 'Blimp' and 'Mplus'. + date_publication: '2025-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misty + url_git: '' +misuvi: + version: 0.1.1 + title: Access the Michigan Substance Use Vulnerability Index (MI-SUVI) + maintainer: Brenden Smith + description: |- + Easily import the MI-SUVI data sets. The user can import data sets with full metrics, percentiles, Z-scores, or rankings. + Data is available at both the County and Zip Code Tabulation Area (ZCTA) levels. This package also includes a function to import + shape files for easy mapping and a function to access the full technical documentation. All data is sourced from the Michigan Department of Health and Human Services. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=misuvi + url_git: https://github.com/brendensm/misuvi +mitml: + version: 0.4-5 + title: Tools for Multiple Imputation in Multilevel Modeling + maintainer: Simon Grund + description: |- + Provides tools for multiple imputation of missing data in multilevel + modeling. Includes a user-friendly interface to the packages 'pan' and 'jomo', + and several functions for visualization, data management and the analysis + of multiply imputed data sets. + date_publication: '2023-03-08' + bug_reports: https://github.com/simongrund1/mitml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mitml + url_git: '' +MitoHEAR: + version: 0.1.0 + title: Quantification of Mitochondrial DNA Heteroplasmy + maintainer: Gabriele Lubatti + description: Allows the estimation and downstream statistical analysis of the mitochondrial + DNA Heteroplasmy calculated from single-cell datasets . + date_publication: '2022-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MitoHEAR + url_git: '' +mitools: + version: '2.4' + title: Tools for Multiple Imputation of Missing Data + maintainer: Thomas Lumley + description: |- + Tools to perform analyses and combine results from + multiple-imputation datasets. + date_publication: '2019-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mitools + url_git: '' +mitre: + version: 1.0.0 + title: Cybersecurity MITRE Standards Data and Digraphs + maintainer: Humbert Costas + description: |- + Extract, transform and load MITRE standards. + This package gives you an approach to cybersecurity data sets. + All data sets are build on runtime downloading raw data from MITRE public services. + MITRE is a government-funded research organization + based in Bedford and McLean. Current version includes most used standards as + data frames. It also provide a list of nodes and edges with all relationships. + date_publication: '2021-05-21' + bug_reports: https://github.com/motherhack3r/mitre/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mitre + url_git: https://github.com/motherhack3r/mitre +MittagLeffleR: + version: 0.4.1 + title: Mittag-Leffler Family of Distributions + maintainer: Peter Straka + description: |- + Implements the Mittag-Leffler function, distribution, + random variate generation, and estimation. Based on the Laplace-Inversion + algorithm by Garrappa, R. (2015) . + date_publication: '2021-09-06' + bug_reports: https://github.com/strakaps/MittagLeffleR/issues + url: https://strakaps.github.io/MittagLeffleR/ + url_cran: https://CRAN.R-project.org/package=MittagLeffleR + url_git: '' +miWQS: + version: 0.4.4 + title: Multiple Imputation Using Weighted Quantile Sum Regression + maintainer: Paul M. Hargarten + description: 'The miWQS package handles the uncertainty due to below the detection + limit in a correlated component mixture problem. Researchers want to determine + if a set/mixture of continuous and correlated components/chemicals is associated + with an outcome and if so, which components are important in that mixture. These + components share a common outcome but are interval-censored between zero and low + thresholds, or detection limits, that may be different across the components. + This package applies the multiple imputation (MI) procedure to the weighted quantile + sum regression (WQS) methodology for continuous, binary, or count outcomes (Hargarten + & Wheeler (2020) ). The imputation models are: + bootstrapping imputation (Lubin et.al (2004) ), univariate + Bayesian imputation (Hargarten & Wheeler (2020) ), + and multivariate Bayesian regression imputation.' + date_publication: '2021-04-02' + bug_reports: https://github.com/phargarten2/miWQS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=miWQS + url_git: '' +mix: + version: 1.0-13 + title: |- + Estimation/Multiple Imputation for Mixed Categorical and + Continuous Data + maintainer: Brian Ripley + description: |- + Estimation/multiple imputation programs for mixed categorical + and continuous data. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mix + url_git: '' +mixAK: + version: '5.8' + title: |- + Multivariate Normal Mixture Models and Mixtures of Generalized + Linear Mixed Models Including Model Based Clustering + maintainer: Arnošt Komárek + description: Contains a mixture of statistical methods including the MCMC methods + to analyze normal mixtures. Additionally, model based clustering methods are implemented + to perform classification based on (multivariate) longitudinal (or otherwise correlated) + data. The basis for such clustering is a mixture of multivariate generalized linear + mixed models. The package is primarily related to the publications Komárek (2009, + Comp. Stat. and Data Anal.) and Komárek and Komárková + (2014, J. of Stat. Soft.) . It also implements methods + published in Komárek and Komárková (2013, Ann. of Appl. Stat.) , + Hughes, Komárek, Bonnett, Czanner, García-Fiñana (2017, Stat. in Med.) , + Jaspers, Komárek, Aerts (2018, Biom. J.) and Hughes, + Komárek, Czanner, García-Fiñana (2018, Stat. Meth. in Med. Res) . + date_publication: '2024-09-16' + bug_reports: '' + url: https://msekce.karlin.mff.cuni.cz/~komarek/ + url_cran: https://CRAN.R-project.org/package=mixAK + url_git: '' +MixAll: + version: 1.5.16 + title: Clustering and Classification using Model-Based Mixture Models + maintainer: Serge Iovleff + description: |- + Algorithms and methods for model-based clustering and classification. + It supports various types of data: continuous, categorical and counting + and can handle mixed data of these types. It can fit Gaussian (with diagonal + covariance structure), gamma, categorical and Poisson models. The algorithms + also support missing values. + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixAll + url_git: '' +mixAR: + version: 0.22.8 + title: Mixture Autoregressive Models + maintainer: Georgi N. Boshnakov + description: |- + Model time series using mixture autoregressive (MAR) + models. Implemented are frequentist (EM) and Bayesian + methods for estimation, prediction and model + evaluation. See Wong and Li (2002) + , Boshnakov (2009) + ), and the extensive + references in the documentation. + date_publication: '2023-12-19' + bug_reports: https://github.com/GeoBosh/mixAR/issues + url: https://geobosh.github.io/mixAR/(doc) + url_cran: https://CRAN.R-project.org/package=mixAR + url_git: https://github.com/GeoBosh/mixAR/(devel) +mixbox: + version: 1.2.3 + title: Observed Fisher Information Matrix for Finite Mixture Model + maintainer: Mahdi Teimouri + description: |- + Developed for the following tasks. 1- simulating realizations from the canonical, + restricted, and unrestricted finite mixture models. 2- Monte Carlo approximation for + density function of the finite mixture models. 3- Monte Carlo approximation for the + observed Fisher information matrix, asymptotic standard error, and the corresponding + confidence intervals for parameters of the mixture models sing the method proposed by + Basford et al. (1997) . + date_publication: '2024-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixbox + url_git: '' +mixcat: + version: 1.0-4 + title: Mixed Effects Cumulative Link and Logistic Regression Models + maintainer: Georgios Papageorgiou + description: Mixed effects cumulative and baseline logit link models for the analysis + of ordinal or nominal responses, with non-parametric distribution for the random + effects. + date_publication: '2019-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixcat + url_git: '' +mixchar: + version: 0.1.0 + title: Mixture Model for the Deconvolution of Thermal Decay Curves + maintainer: Saras Windecker + description: |- + Deconvolution of thermal decay curves allows you to quantify proportions + of biomass components in plant litter. Thermal decay curves derived from + thermogravimetric analysis (TGA) are imported, modified, and then modelled in a + three- or four- part mixture model using the Fraser-Suzuki function. The output + is estimates for weights of pseudo-components corresponding to hemicellulose, + cellulose, and lignin. For more information see: Müller-Hagedorn, M. and Bockhorn, + H. (2007) , Órfão, J. J. M. and Figueiredo, J. L. + (2001) , and Yang, H. and Yan, R. and + Chen, H. and Zheng, C. and Lee, D. H. and Liang, D. T. (2006) . + date_publication: '2018-08-16' + bug_reports: http://github.com/smwindecker/mixchar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mixchar + url_git: http://github.com/smwindecker/mixchar +mixcure: + version: '2.0' + title: Mixture Cure Models + maintainer: Yingwei Peng + description: 'Implementation of parametric and semiparametric mixture cure models + based on existing R packages. See details of the models in Peng and Yu (2020) + .' + date_publication: '2020-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixcure + url_git: '' +mixdir: + version: 0.3.0 + title: Cluster High Dimensional Categorical Datasets + maintainer: Constantin Ahlmann-Eltze + description: |- + Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet + (Process) mixture of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used + to reduce the dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically + infer an appropriate number of latent classes or find k classes, as defined by the user. The model is based on a + paper by Dunson and Xing (2009) , but implements a scalable variational inference algorithm so that it is + applicable to large datasets. It is described and tested in the accompanying paper by + Ahlmann-Eltze and Yau (2018) . + date_publication: '2019-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixdir + url_git: https://github.com/const-ae/mixdir +mixdist: + version: 0.5-5 + title: Finite Mixture Distribution Models + maintainer: Peter Macdonald + description: Fit finite mixture distribution models to grouped data and conditional + data by maximum likelihood using a combination of a Newton-type algorithm and + the EM algorithm. + date_publication: '2018-06-04' + bug_reports: '' + url: https://ms.mcmaster.ca/peter/mix/mix.html + url_cran: https://CRAN.R-project.org/package=mixdist + url_git: '' +mixedBayes: + version: 0.1.5 + title: Bayesian Longitudinal Regularized Quantile Mixed Model + maintainer: Kun Fan + description: In longitudinal studies, the same subjects are measured repeatedly + over time, leading to correlations among the repeated measurements. Properly accounting + for the intra-cluster correlations in the presence of data heterogeneity and long + tailed distributions of the disease phenotype is challenging, especially in the + context of high dimensional regressions. In this package, we developed a Bayesian + quantile mixed effects model with spike- and -slab priors to dissect important + gene - environment interactions under longitudinal genomics studies. An efficient + Gibbs sampler has been developed to facilitate fast computation. The Markov chain + Monte Carlo algorithms of the proposed and alternative methods are efficiently + implemented in 'C++'. The development of this software package and the associated + statistical methods have been partially supported by an Innovative Research Award + from Johnson Cancer Research Center, Kansas State University. + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixedBayes + url_git: https://github.com/kunfa/mixedBayes +mixedbiastest: + version: 0.3.0 + title: Bias Diagnostic for Linear Mixed Models + maintainer: Andrew T. Karl + description: Provides a function to perform bias diagnostics on linear mixed models + fitted with lmer() from the 'lme4' package. Implements permutation tests for assessing + the bias of fixed effects, as described in Karl and Zimmerman (2021) . + Karl and Zimmerman (2020) provide R code for implementing + the test using 'mvglmmRank' output. Development of this package was assisted by + 'GPT o1-preview' for code structure and documentation. + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixedbiastest + url_git: '' +mixedCCA: + version: 1.6.2 + title: |- + Sparse Canonical Correlation Analysis for High-Dimensional Mixed + Data + maintainer: Irina Gaynanova + description: |- + Semi-parametric approach for sparse canonical correlation analysis + which can handle mixed data types: continuous, binary and truncated continuous. + Bridge functions are provided to connect Kendall's tau to latent correlation + under the Gaussian copula model. The methods are described in + Yoon, Carroll and Gaynanova (2020) and + Yoon, Mueller and Gaynanova (2021) . + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixedCCA + url_git: '' +MixedIndTests: + version: 1.2.0 + title: Tests of Randomness and Tests of Independence + maintainer: Bouchra R. Nasri + description: Functions for testing randomness for a univariate time series with + arbitrary distribution (discrete, continuous, mixture of both types) and for + testing independence between random variables with arbitrary distributions. The + test statistics are based on the multilinear empirical copula and multipliers + are used to compute P-values. The test of independence between random variables + appeared in Genest, Nešlehová, Rémillard & Murphy (2019) and the test of randomness + appeared in Nasri (2022). + date_publication: '2024-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixedIndTests + url_git: '' +MixedLevelRSDs: + version: 1.0.0 + title: Mixed Level Response Surface Designs + maintainer: Ashutosh Dalal + description: Response Surface Designs (RSDs) involving factors not all at same levels + are called Mixed Level RSDs (or Asymmetric RSDs). In many practical situations, + RSDs with asymmetric levels will be more suitable as it explores more regions + in the design space. (J.S. Mehta and M.N. Das (1968) . "Asymmetric + rotatable designs and orthogonal transformations").This package contains function + named ATORDs_I() for generating asymmetric third order rotatable designs (ATORDs) + based on third order designs given by Das and Narasimham (1962). Function ATORDs_II() generates + asymmetric third order rotatable designs developed using t-design of unequal set + sizes, which are smaller in size as compared to design generated by function ATORDs_I(). + In general, third order rotatable designs can be classified into two classes viz., + designs that are suitable for sequential experimentation and designs for non-sequential + experimentation. The sequential experimentation approach involves conducting the + trials step by step whereas, in the non-sequential experimentation approach, the + entire runs are executed in one go (M. N. Das and V. Narasimham (1962) . + "Construction of Rotatable Designs through Balanced Incomplete Block Designs"). ATORDs_I() + and ATORDs_II() functions generate non-sequential asymmetric third order designs. + Function named SeqTORD() generates symmetric sequential third order design in + blocks and also gives G-efficiency of the given design. Function named Asymseq() + generates asymmetric sequential third order designs in blocks (M. Hemavathi, + Eldho Varghese, Shashi Shekhar and Seema Jaggi (2020) . + "Sequential asymmetric third order rotatable designs (SATORDs)"). In response + surface design, situations may arise in which some of the factors are qualitative + in nature (Jyoti Divecha and Bharat Tarapara (2017) . + "Small, balanced, efficient, optimal, and near rotatable response surface designs + for factorial experiments asymmetrical in some quantitative, qualitative factors"). The + Function named QualRSD() generates second order design with qualitative factors + along with their D-efficiency and G-efficiency. The function named RotatabilityQ() + calculates a measure of rotatability (measure Q, 0 <= Q <= 1) given by Draper + and Pukelshiem(1990) for given a design based on a second order model, (Norman + R. Draper and Friedrich Pukelsheim(1990) . + "Another look at rotatability"). + date_publication: '2023-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixedLevelRSDs + url_git: '' +mixedLSR: + version: 0.1.0 + title: |- + Mixed, Low-Rank, and Sparse Multivariate Regression on + High-Dimensional Data + maintainer: Alexander White + description: |- + Mixed, low-rank, and sparse multivariate regression ('mixedLSR') provides tools for performing mixture regression when + the coefficient matrix is low-rank and sparse. 'mixedLSR' allows subgroup identification by alternating optimization + with simulated annealing to encourage global optimum convergence. This method is data-adaptive, automatically + performing parameter selection to identify low-rank substructures in the coefficient matrix. + date_publication: '2022-11-04' + bug_reports: https://github.com/alexanderjwhite/mixedLSR + url: https://alexanderjwhite.github.io/mixedLSR/ + url_cran: https://CRAN.R-project.org/package=mixedLSR + url_git: '' +mixedMem: + version: 1.1.2 + title: Tools for Discrete Multivariate Mixed Membership Models + maintainer: Y. Samuel Wang + description: |- + Fits mixed membership models with discrete multivariate data (with + or without repeated measures) following the general framework of Erosheva et al + (2004). This package uses a Variational EM approach by approximating the + posterior distribution of latent memberships and selecting hyperparameters + through a pseudo-MLE procedure. Currently supported data types are + Bernoulli, multinomial and rank (Plackett-Luce). The extended GoM model with + fixed stayers from Erosheva et al (2007) is now also supported. See Airoldi et al + (2014) for other examples of mixed membership models. + date_publication: '2020-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixedMem + url_git: '' +MixedPoisson: + version: '2.0' + title: Mixed Poisson Models + maintainer: Alicja Wolny-Dominiak + description: The estimation of the parameters in mixed Poisson models. + date_publication: '2016-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixedPoisson + url_git: '' +MixedPsy: + version: 1.2.0 + title: Statistical Tools for the Analysis of Psychophysical Data + maintainer: Alessandro Moscatelli + description: |- + Tools for the analysis of psychophysical data in R. This package allows to estimate the Point of Subjective Equivalence (PSE) + and the Just Noticeable Difference (JND), either from a psychometric function or from a Generalized Linear Mixed Model (GLMM). + Additionally, the package allows plotting the fitted models and the response data, simulating psychometric functions of different shapes, and simulating data sets. + For a description of the use of GLMMs applied to psychophysical data, refer to Moscatelli et al. (2012). + date_publication: '2025-02-18' + bug_reports: https://github.com/moskante/MixedPsy/issues + url: https://mixedpsychophysics.wordpress.com + url_cran: https://CRAN.R-project.org/package=MixedPsy + url_git: '' +mixedsde: + version: '5.0' + title: |- + Estimation Methods for Stochastic Differential Mixed Effects + Models + maintainer: Charlotte Dion + description: |- + Inference on stochastic differential models Ornstein-Uhlenbeck or + Cox-Ingersoll-Ross, with one or two random effects in the drift function. + date_publication: '2018-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixedsde + url_git: '' +MixedTS: + version: 1.0.4 + title: Mixed Tempered Stable Distribution + maintainer: Lorenzo Mercuri + description: We provide detailed functions for univariate Mixed Tempered Stable + distribution. + date_publication: '2015-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixedTS + url_git: '' +mixexp: + version: 1.2.7.1 + title: Design and Analysis of Mixture Experiments + maintainer: John Lawson + description: Functions for creating designs for mixture experiments, making ternary + contour plots, and making mixture effect plots. + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixexp + url_git: '' +MIXFIM: + version: '1.1' + title: Evaluation of the FIM in NLMEMs using MCMC + maintainer: Marie-Karelle Riviere-Jourdan + description: Evaluation and optimization of the Fisher Information Matrix in NonLinear + Mixed Effect Models using Markov Chains Monte Carlo for continuous and discrete + data. + date_publication: '2018-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MIXFIM + url_git: '' +MixfMRI: + version: 0.1-4 + title: Mixture fMRI Clustering Analysis + maintainer: Wei-Chen Chen + description: |- + Utilizing model-based clustering (unsupervised) + for functional magnetic resonance imaging (fMRI) data. + The developed methods (Chen and Maitra (2023) ) + include 2D and 3D clustering analyses + (for p-values with voxel locations) and + segmentation analyses (for p-values alone) for fMRI data where p-values + indicate significant level of activation responding to stimulate + of interesting. The analyses are mainly identifying active + voxel/signal associated with normal brain behaviors. + Analysis pipelines (R scripts) utilizing this package + (see examples in 'inst/workflow/') is also implemented with high + performance techniques. + date_publication: '2024-10-17' + bug_reports: https://github.com/snoweye/MixfMRI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MixfMRI + url_git: https://github.com/snoweye/MixfMRI +mixgb: + version: 1.5.2 + title: Multiple Imputation Through 'XGBoost' + maintainer: Yongshi Deng + description: |- + Multiple imputation using 'XGBoost', subsampling, and predictive mean + matching as described in Deng and Lumley (2023) + . The package supports various types of + variables, offers flexible settings, and enables saving an imputation model to impute + new data. Data processing and memory usage have been optimised to speed up + the imputation process. + date_publication: '2024-12-02' + bug_reports: https://github.com/agnesdeng/mixgb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mixgb + url_git: https://github.com/agnesdeng/mixgb +MixGHD: + version: 2.3.7 + title: |- + Model Based Clustering, Classification and Discriminant Analysis + Using the Mixture of Generalized Hyperbolic Distributions + maintainer: Cristina Tortora + description: Carries out model-based clustering, classification and discriminant + analysis using five different models. The models are all based on the generalized + hyperbolic distribution. The first model 'MGHD' (Browne and McNicholas (2015) + ) is the classical mixture of generalized hyperbolic distributions. + The 'MGHFA' (Tortora et al. (2016) ) is the mixture + of generalized hyperbolic factor analyzers for high dimensional data sets. The + 'MSGHD' is the mixture of multiple scaled generalized hyperbolic distributions, + the 'cMSGHD' is a 'MSGHD' with convex contour plots and the 'MCGHD', mixture + of coalesced generalized hyperbolic distributions is a new more flexible model + (Tortora et al. (2019). The paper related to the + software can be found at . + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixGHD + url_git: '' +mixhvg: + version: 1.0.1 + title: Mixture of Multiple Highly Variable Feature Selection Methods + maintainer: Ruzhang Zhao + description: 'Highly variable gene selection methods, including popular public available + methods, and also the mixture of multiple highly variable gene selection methods, + . Reference: .' + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixhvg + url_git: '' +mixIndependR: + version: 1.0.0 + title: Genetics and Independence Testing of Mixed Genetic Panels + maintainer: Bing Song + description: Developed to deal with multi-locus genotype data, this package is especially + designed for those panel which include different type of markers. Basic genetic + parameters like allele frequency, genotype frequency, heterozygosity and Hardy-Weinberg + test of mixed genetic data can be obtained. In addition, a new test for mutual + independence which is compatible for mixed genetic data is developed in this package. + date_publication: '2021-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixIndependR + url_git: https://github.com/ice4prince/mixIndependR +mixKernel: + version: 0.9-1 + title: Omics Data Integration Using Kernel Methods + maintainer: Nathalie Vialaneix + description: |- + Kernel-based methods are powerful methods for integrating + heterogeneous types of data. mixKernel aims at providing methods to combine + kernel for unsupervised exploratory analysis. Different solutions are + provided to compute a meta-kernel, in a consensus way or in a way that + best preserves the original topology of the data. mixKernel also integrates + kernel PCA to visualize similarities between samples in a non linear space + and from the multiple source point of view + . A method to select (as well as + funtions to display) important variables is also provided + . + date_publication: '2024-01-27' + bug_reports: https://forgemia.inra.fr/genotoul-bioinfo/mixKernel/-/issues + url: http://mixkernel.clementine.wf + url_cran: https://CRAN.R-project.org/package=mixKernel + url_git: '' +mixl: + version: 1.3.4 + title: |- + Simulated Maximum Likelihood Estimation of Mixed Logit Models + for Large Datasets + maintainer: Joseph Molloy + description: |- + Specification and estimation of multinomial logit + models. Large datasets and complex models are supported, with an + intuitive syntax. Multinomial Logit Models, Mixed models, random + coefficients and Hybrid Choice are all supported. For more + information, see Molloy et al. (2021) . + date_publication: '2024-02-07' + bug_reports: https://github.com/joemolloy/fast-mixed-mnl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mixl + url_git: https://github.com/joemolloy/fast-mixed-mnl +MixLFA: + version: 1.0.0 + title: Mixture of Longitudinal Factor Analysis Methods + maintainer: Amine Ounajim + description: Provides a function for the estimation of mixture of longitudinal factor + analysis models using the iterative expectation-maximization algorithm (Ounajim, + Slaoui, Louis, Billot, Frasca, Rigoard (2023) ) and several + tools for visualizing and interpreting the models' parameters. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixLFA + url_git: '' +mixlm: + version: 1.4.2 + title: Mixed Model ANOVA and Statistics for Education + maintainer: Kristian Hovde Liland + description: |- + The main functions perform mixed models analysis by least squares + or REML by adding the function r() to formulas of lm() and glm(). A collection of + text-book statistics for higher education is also included, e.g. modifications + of the functions lm(), glm() and associated summaries from the package 'stats'. + date_publication: '2025-01-14' + bug_reports: https://github.com/khliland/mixlm/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=mixlm + url_git: https://github.com/khliland/mixlm/ +MixMatrix: + version: 0.2.8 + title: Classification with Matrix Variate Normal and t Distributions + maintainer: Geoffrey Thompson + description: |- + Provides sampling and density functions for matrix + variate normal, t, and inverted t distributions; ML estimation for matrix + variate normal and t distributions using the EM algorithm, + including some restrictions on the parameters; and classification by linear and + quadratic discriminant analysis for matrix variate normal and t + distributions described in Thompson et al. (2019) . + Performs clustering with matrix variate normal and t mixture models. + date_publication: '2024-09-30' + bug_reports: https://github.com/gzt/MixMatrix/issues + url: https://gzt.github.io/MixMatrix/ + url_cran: https://CRAN.R-project.org/package=MixMatrix + url_git: https://github.com/gzt/MixMatrix/ +mixmeta: + version: 1.2.0 + title: An Extended Mixed-Effects Framework for Meta-Analysis + maintainer: Antonio Gasparrini + description: |- + A collection of functions to perform various meta-analytical models + through a unified mixed-effects framework, including standard univariate + fixed and random-effects meta-analysis and meta-regression, and non-standard + extensions such as multivariate, multilevel, longitudinal, and dose-response + models. + date_publication: '2021-10-16' + bug_reports: '' + url: http://www.ag-myresearch.com/package-mixmeta + url_cran: https://CRAN.R-project.org/package=mixmeta + url_git: https://github.com/gasparrini/mixmeta +mixOofA: + version: '1.0' + title: Design and Analysis of Order-of-Addition Mixture Experiments + maintainer: Baidya Nath Mandal + description: A facility to generate various classes of fractional designs for order-of-addition + experiments namely fractional order-of-additions orthogonal arrays, see Voelkel, + Joseph G. (2019). "The design of order-of-addition experiments." Journal of Quality + Technology 51:3, 230-241, . Provides facility + to construct component orthogonal arrays, see Jian-Feng Yang, Fasheng Sun and + Hongquan Xu (2020). "A Component Position Model, Analysis and Design for Order-of-Addition + Experiments." Technometrics, . Supports generation + of fractional designs for order-of-addition mixture experiments. Analysis of data + from order-of-addition mixture experiments is also supported. + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixOofA + url_git: '' +mixopt: + version: 0.1.3 + title: Mixed Variable Optimization + maintainer: Collin Erickson + description: |- + Mixed variable optimization for non-linear functions. + Can optimize function whose inputs are a combination of continuous, + ordered, and unordered variables. + date_publication: '2024-09-15' + bug_reports: https://github.com/CollinErickson/mixopt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mixopt + url_git: https://github.com/CollinErickson/mixopt +MixOptim: + version: 0.1.2 + title: Mixture Optimization Algorithm + maintainer: Cassandro Davi Emer + description: |- + Simple tools to perform mixture optimization based on the 'desirability' package by Max Kuhn. + It also provides a plot routine using 'ggplot2' and 'patchwork'. + date_publication: '2020-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixOptim + url_git: '' +mixPHM: + version: 0.7-2 + title: Mixtures of Proportional Hazard Models + maintainer: Patrick Mair + description: Fits multiple variable mixtures of various parametric proportional + hazard models using the EM-Algorithm. Proportionality restrictions can be imposed + on the latent groups and/or on the variables. Several survival distributions can + be specified. Missing values and censored values are allowed. Independence is + assumed over the single variables. + date_publication: '2015-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixPHM + url_git: '' +mixpoissonreg: + version: 1.0.0 + title: Mixed Poisson Regression for Overdispersed Count Data + maintainer: Alexandre B. Simas + description: Fits mixed Poisson regression models (Poisson-Inverse Gaussian or Negative-Binomial) + on data sets with response variables being count data. The models can have varying + precision parameter, where a linear regression structure (through a link function) + is assumed to hold on the precision parameter. The Expectation-Maximization algorithm + for both these models (Poisson Inverse Gaussian and Negative Binomial) is an important + contribution of this package. Another important feature of this package is the + set of functions to perform global and local influence analysis. See Barreto-Souza + and Simas (2016) for further details. + date_publication: '2021-03-10' + bug_reports: https://github.com/vpnsctl/mixpoissonreg/issues + url: https://vpnsctl.github.io/mixpoissonreg/ + url_cran: https://CRAN.R-project.org/package=mixpoissonreg + url_git: https://github.com/vpnsctl/mixpoissonreg/ +mixR: + version: 0.2.1 + title: Finite Mixture Modeling for Raw and Binned Data + maintainer: Youjiao Yu + description: Performs maximum likelihood estimation for finite mixture models for + families including Normal, Weibull, Gamma and Lognormal by using EM algorithm, + together with Newton-Raphson algorithm or bisection method when necessary. It + also conducts mixture model selection by using information criteria or bootstrap + likelihood ratio test. The data used for mixture model fitting can be raw data + or binned data. The model fitting process is accelerated by using R package 'Rcpp'. + date_publication: '2024-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixR + url_git: '' +mixRaschTools: + version: 1.1.1 + title: |- + Plotting and Average Theta Functions for Multiple Class Mixed + Rasch Models + maintainer: Pamela Trantham + description: |- + Provides supplemental functions for the 'mixRasch' + package (Willse, 2014), including a + plotting function to compare item parameters for multiple + class models and a function that provides average theta values for each class in + a mixture model. + date_publication: '2019-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixRaschTools + url_git: '' +MixRF: + version: '1.0' + title: |- + A Random-Forest-Based Approach for Imputing Clustered Incomplete + Data + maintainer: Jiebiao Wang + description: |- + It offers random-forest-based functions to impute clustered + incomplete data. The package is tailored for but not limited to imputing + multitissue expression data, in which a gene's expression is measured on the + collected tissues of an individual but missing on the uncollected tissues. + date_publication: '2016-04-06' + bug_reports: https://github.com/randel/MixRF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MixRF + url_git: https://github.com/randel/MixRF +MixSAL: + version: '1.0' + title: |- + Mixtures of Multivariate Shifted Asymmetric Laplace (SAL) + Distributions + maintainer: Brian C. Franczak + description: The current version of the 'MixSAL' package allows users to generate + data from a multivariate SAL distribution or a mixture of multivariate SAL distributions, + evaluate the probability density function of a multivariate SAL distribution or + a mixture of multivariate SAL distributions, and fit a mixture of multivariate + SAL distributions using the Expectation-Maximization (EM) algorithm (see Franczak + et. al, 2014, , for details). + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixSAL + url_git: '' +MixSemiRob: + version: 1.1.0 + title: 'Mixture Models: Parametric, Semiparametric, and Robust' + maintainer: Suyeon Kang + description: |- + Various functions are provided to estimate parametric mixture models + (with Gaussian, t, Laplace, log-concave distributions, etc.) and + non-parametric mixture models. The package performs hypothesis tests + and addresses label switching issues in mixture models. + The package also allows for parameter estimation in mixture of regressions, + proportion-varying mixture of regressions, and robust mixture of regressions. + date_publication: '2023-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixSemiRob + url_git: '' +MixSIAR: + version: 3.1.12 + title: Bayesian Mixing Models in R + maintainer: Brian Stock + description: |- + Creates and runs Bayesian mixing models to analyze + biological tracer data (i.e. stable isotopes, fatty acids), which estimate the + proportions of source (prey) contributions to a mixture (consumer). 'MixSIAR' + is not one model, but a framework that allows a user to create a mixing model + based on their data structure and research questions, via options for fixed/ + random effects, source data types, priors, and error terms. 'MixSIAR' incorporates + several years of advances since 'MixSIR' and 'SIAR'. + date_publication: '2020-10-20' + bug_reports: https://github.com/brianstock/MixSIAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MixSIAR + url_git: https://github.com/brianstock/MixSIAR +MixSim: + version: 1.1-8 + title: Simulating Data to Study Performance of Clustering Algorithms + maintainer: Wei-Chen Chen + description: |- + The utility of this package is in simulating mixtures of Gaussian + distributions with different levels of overlap between mixture + components. Pairwise overlap, defined as a sum of two + misclassification probabilities, measures the degree of + interaction between components and can be readily employed to + control the clustering complexity of datasets simulated from + mixtures. These datasets can then be used for systematic + performance investigation of clustering and finite mixture + modeling algorithms. Among other capabilities of 'MixSim', there + are computing the exact overlap for Gaussian mixtures, + simulating Gaussian and non-Gaussian data, simulating outliers + and noise variables, calculating various measures of agreement + between two partitionings, and constructing parallel + distribution plots for the graphical display of finite mixture + models. + date_publication: '2024-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixSim + url_git: '' +mixsmsn: + version: 1.1-10 + title: |- + Fitting Finite Mixture of Scale Mixture of Skew-Normal + Distributions + maintainer: Marcos Prates + description: 'Functions to fit finite mixture of scale mixture of skew-normal (FM-SMSN) + distributions, details in Prates, Lachos and Cabral (2013) , + Cabral, Lachos and Prates (2012) and Basso, Lachos, + Cabral and Ghosh (2010) .' + date_publication: '2021-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixsmsn + url_git: '' +mixSPE: + version: 0.9.2 + title: |- + Mixtures of Power Exponential and Skew Power Exponential + Distributions for Use in Model-Based Clustering and + Classification + maintainer: Utkarsh J. Dang + description: |- + Mixtures of skewed and elliptical distributions are implemented using mixtures of multivariate skew + power exponential and power exponential distributions, respectively. A generalized expectation-maximization + framework is used for parameter estimation. See citation() for how to cite. + date_publication: '2023-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixSPE + url_git: '' +mixsqp: + version: 0.3-54 + title: |- + Sequential Quadratic Programming for Fast Maximum-Likelihood + Estimation of Mixture Proportions + maintainer: Peter Carbonetto + description: |- + Provides an optimization method based on sequential + quadratic programming (SQP) for maximum likelihood estimation of + the mixture proportions in a finite mixture model where the + component densities are known. The algorithm is expected to obtain + solutions that are at least as accurate as the state-of-the-art + MOSEK interior-point solver (called by function "KWDual" in the + 'REBayes' package), and they are expected to arrive at solutions + more quickly when the number of samples is large and the number of + mixture components is not too large. This implements the "mix-SQP" + algorithm, with some improvements, described in Y. Kim, + P. Carbonetto, M. Stephens & M. Anitescu (2020) + . + date_publication: '2023-12-20' + bug_reports: https://github.com/stephenslab/mixsqp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mixsqp + url_git: https://github.com/stephenslab/mixsqp +mixSSG: + version: 2.1.1 + title: Clustering Using Mixtures of Sub Gaussian Stable Distributions + maintainer: Mahdi Teimouri + description: |- + Developed for model-based clustering using the finite mixtures of skewed sub-Gaussian + stable distributions developed by Teimouri (2022) and estimating + parameters of the symmetric stable distribution within the Bayesian framework. + date_publication: '2022-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixSSG + url_git: '' +mixtools: + version: 2.0.0 + title: Tools for Analyzing Finite Mixture Models + maintainer: Derek Young + description: 'Analyzes finite mixture models for various parametric and semiparametric + settings. This includes mixtures of parametric distributions (normal, multivariate + normal, multinomial, gamma), various Reliability Mixture Models (RMMs), mixtures-of-regressions + settings (linear regression, logistic regression, Poisson regression, linear regression + with changepoints, predictor-dependent mixing proportions, random effects regressions, + hierarchical mixtures-of-experts), and tools for selecting the number of components + (bootstrapping the likelihood ratio test statistic, mixturegrams, and model selection + criteria). Bayesian estimation of mixtures-of-linear-regressions models is available + as well as a novel data depth method for obtaining credible bands. This package + is based upon work supported by the National Science Foundation under Grant No. + SES-0518772 and the Chan Zuckerberg Initiative: Essential Open Source Software + for Science (Grant No. 2020-255193).' + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixtools + url_git: https://github.com/dsy109/mixtools +mixtox: + version: 1.4.0 + title: Dose Response Curve Fitting and Mixture Toxicity Assessment + maintainer: Xiangwei Zhu + description: |- + Curve Fitting of monotonic(sigmoidal) & non-monotonic(J-shaped) + dose-response data. Predicting mixture toxicity based on reference + models such as 'concentration addition', 'independent action', and 'generalized + concentration addition'. + date_publication: '2022-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixtox + url_git: https://github.com/ichxw/mixtox +mixtur: + version: 1.2.1 + title: Modelling Continuous Report Visual Short-Term Memory Studies + maintainer: Jim Grange + description: |- + A set of utility functions for analysing and modelling data from + continuous report short-term memory experiments using either the 2-component + mixture model of Zhang and Luck (2008) or the + 3-component mixture model of Bays et al. (2009) . Users + are also able to simulate from these models. + date_publication: '2023-04-06' + bug_reports: https://github.com/JimGrange/mixtur/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mixtur + url_git: https://github.com/JimGrange/mixtur +mixture: + version: 2.1.1 + title: Mixture Models for Clustering and Classification + maintainer: Paul D. McNicholas + description: An implementation of 14 parsimonious mixture models for model-based + clustering or model-based classification. Gaussian, Student's t, generalized hyperbolic, + variance-gamma or skew-t mixtures are available. All approaches work with missing + data. Celeux and Govaert (1995) , Browne and + McNicholas (2014) , Browne and McNicholas (2015) + . + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mixture + url_git: '' +MixtureMissing: + version: 3.0.4 + title: |- + Robust and Flexible Model-Based Clustering for Data Sets with + Missing Values at Random + maintainer: Hung Tong + description: |- + Implementations of various robust and flexible model-based clustering methods for data sets with missing values at random. + Two main models are: Multivariate Contaminated Normal Mixture (MCNM, Tong and Tortora, 2022, ) and + Multivariate Generalized Hyperbolic Mixture (MGHM, Wei et al., 2019, ). Mixtures via some special or limiting + cases of the multivariate generalized hyperbolic distribution are also included: Normal-Inverse Gaussian, Symmetric Normal-Inverse Gaussian, + Skew-Cauchy, Cauchy, Skew-t, Student's t, Normal, Symmetric Generalized Hyperbolic, Hyperbolic Univariate Marginals, + Hyperbolic, and Symmetric Hyperbolic. + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixtureMissing + url_git: '' +MixTwice: + version: '2.0' + title: Large-Scale Hypothesis Testing by Variance Mixing + maintainer: Zihao Zheng + description: 'Implements large-scale hypothesis testing by variance mixing. It takes + two statistics per testing unit -- an estimated effect and its associated squared + standard error -- and fits a nonparametric, shape-constrained mixture separately + on two latent parameters. It reports local false discovery rates (lfdr) and local + false sign rates (lfsr). Manuscript describing algorithm of MixTwice: Zheng et + al(2021) .' + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MixTwice + url_git: '' +MixviR: + version: 3.5.0 + title: Analysis and Exploration of Mixed Microbial Genomic Samples + maintainer: Michael Sovic + description: Tool for exploring DNA and amino acid variation and inferring the presence + of target lineages from microbial high-throughput genomic DNA samples that potentially + contain mixtures of variants/lineages. MixviR was originally created to help analyze + environmental SARS-CoV-2/Covid-19 samples from environmental sources such as wastewater + or dust, but can be applied to any microbial group. Inputs include reference genome + information in commonly-used file formats (fasta, bed) and one or more variant + call format (VCF) files, which can be generated with programs such as Illumina's + DRAGEN, the Genome Analysis Toolkit, or bcftools. See DePristo et al (2011) + and Danecek et al (2021) for these tools, respectively. + Available outputs include a table of mutations observed in the sample(s), estimates + of proportions of target lineages in the sample(s), and an R Shiny dashboard to + interactively explore the data. + date_publication: '2022-10-22' + bug_reports: https://groups.google.com/g/mixvir + url: '' + url_cran: https://CRAN.R-project.org/package=MixviR + url_git: https://github.com/mikesovic/MixviR +mixvlmc: + version: 0.2.1 + title: Variable Length Markov Chains with Covariates + maintainer: Fabrice Rossi + description: |- + Estimates Variable Length Markov Chains (VLMC) models and VLMC with + covariates models from discrete sequences. Supports model selection via + information criteria and simulation of new sequences from an estimated + model. See Bühlmann, P. and Wyner, A. J. (1999) + for VLMC and Zanin Zambom, A., Kim, S. and Lopes Garcia, N. (2022) + for VLMC with covariates. + date_publication: '2023-10-31' + bug_reports: https://github.com/fabrice-rossi/mixvlmc/issues + url: https://fabrice-rossi.github.io/mixvlmc/ + url_cran: https://CRAN.R-project.org/package=mixvlmc + url_git: https://github.com/fabrice-rossi/mixvlmc +mize: + version: 0.2.4 + title: Unconstrained Numerical Optimization Algorithms + maintainer: James Melville + description: |- + Optimization algorithms implemented in R, including + conjugate gradient (CG), Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the + limited memory BFGS (L-BFGS) methods. Most internal parameters can be set + through the call interface. The solvers hold up quite well for + higher-dimensional problems. + date_publication: '2020-08-30' + bug_reports: https://github.com/jlmelville/mize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mize + url_git: https://github.com/jlmelville/mize +mizer: + version: 2.5.3 + title: Dynamic Multi-Species Size Spectrum Modelling + maintainer: Gustav Delius + description: |- + A set of classes and methods to set up and run multi-species, trait + based and community size spectrum ecological models, focused on the marine + environment. + date_publication: '2024-10-17' + bug_reports: https://github.com/sizespectrum/mizer/issues + url: https://sizespectrum.org/mizer/ + url_cran: https://CRAN.R-project.org/package=mizer + url_git: https://github.com/sizespectrum/mizer +MJMbamlss: + version: 0.1.0 + title: Multivariate Joint Models with 'bamlss' + maintainer: Alexander Volkmann + description: Multivariate joint models of longitudinal and time-to-event data based + on functional principal components implemented with 'bamlss'. Implementation for + Volkmann, Umlauf, Greven (2023) . + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MJMbamlss + url_git: '' +MKclass: + version: '0.5' + title: Statistical Classification + maintainer: Matthias Kohl + description: Performance measures and scores for statistical classification such + as accuracy, sensitivity, specificity, recall, similarity coefficients, AUC, GINI + index, Brier score and many more. Calculation of optimal cut-offs and decision + stumps (Iba and Langley (1991), ) for + all implemented performance measures. Hosmer-Lemeshow goodness of fit tests (Lemeshow + and Hosmer (1982), ; Hosmer et al (1997), + ). Statistical + and epidemiological risk measures such as relative risk, odds ratio, number needed + to treat (Porta (2014), ). + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKclass + url_git: https://github.com/stamats/MKclass +mkde: + version: '0.4' + title: 2D and 3D Movement-Based Kernel Density Estimates (MKDEs) + maintainer: Robert Sinkovits + description: Provides functions to compute and visualize movement-based kernel density + estimates (MKDEs) for animal utilization distributions in 2 or 3 spatial dimensions. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mkde + url_git: '' +MKdescr: + version: '0.8' + title: Descriptive Statistics + maintainer: Matthias Kohl + description: Computation of standardized interquartile range (IQR), Huber-type skipped + mean (Hampel (1985), ), robust coefficient of variation (CV) + (Arachchige et al. (2019), ), robust signal to noise ratio (SNR), + z-score, standardized mean difference (SMD), as well as functions that support + graphical visualization such as boxplots based on quartiles (not hinges), negative + logarithms and generalized logarithms for 'ggplot2' (Wickham (2016), ISBN:978-3-319-24277-4). + date_publication: '2022-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKdescr + url_git: https://github.com/stamats/MKdescr +MKendall: + version: 1.5-4 + title: Matrix Kendall's Tau and Matrix Elliptical Factor Model + maintainer: Yalin Wang + description: Large-scale matrix-variate data have been widely observed nowadays + in various research areas such as finance, signal processing and medical imaging. + Modelling matrix-valued data by matrix-elliptical family not only provides a flexible + way to handle heavy-tail property and tail dependencies, but also maintains the + intrinsic row and column structure of random matrices. We proposed a new tool + named matrix Kendall's tau which is efficient for analyzing random elliptical + matrices. By applying this new type of Kendell’s tau to the matrix elliptical + factor model, we propose a Matrix-type Robust Two-Step (MRTS) method to estimate + the loading and factor spaces. See the details in He at al. (2022) . + In this package, we provide the algorithms for calculating sample matrix Kendall's + tau, the MRTS method and the Matrix Kendall's tau Eigenvalue-Ratio (MKER) method + which is used for determining the number of factors. + date_publication: '2024-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKendall + url_git: '' +mkin: + version: 1.2.9 + title: Kinetic Evaluation of Chemical Degradation Data + maintainer: Johannes Ranke + description: |- + Calculation routines based on the FOCUS Kinetics Report (2006, + 2014). Includes a function for conveniently defining differential equation + models, model solution based on eigenvalues if possible or using numerical + solvers. If a C compiler (on windows: 'Rtools') is installed, differential + equation models are solved using automatically generated C functions. + Non-constant errors can be taken into account using variance by variable or + two-component error models . Hierarchical + degradation models can be fitted using nonlinear mixed-effects model packages + as a back end . Please + note that no warranty is implied for correctness of results or fitness for a + particular purpose. + date_publication: '2025-02-13' + bug_reports: https://github.com/jranke/mkin/issues/ + url: https://pkgdown.jrwb.de/mkin/ + url_cran: https://CRAN.R-project.org/package=mkin + url_git: '' +MKinfer: + version: '1.2' + title: Inferential Statistics + maintainer: Matthias Kohl + description: Computation of various confidence intervals (Altman et al. (2000), + ISBN:978-0-727-91375-3; Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) including + bootstrapped versions (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) as + well as Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2), permutation + (Janssen (1997), ), bootstrap (Davison and + Hinkley (1997), ISBN:978-0-511-80284-3), intersection-union (Sozu et al. (2015), + ISBN:978-3-319-22005-5) and multiple imputation (Barnard and Rubin (1999), ) + t-test; furthermore, computation of intersection-union z-test as well as multiple + imputation Wilcoxon tests. Graphical visualization by volcano and Bland-Altman + plots (Bland and Altman (1986), ; Shieh (2018), + ). + date_publication: '2024-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKinfer + url_git: https://github.com/stamats/MKinfer +MKLE: + version: 1.0.1 + title: Maximum Kernel Likelihood Estimation + maintainer: Thomas Jaki + description: Package for fast computation of the maximum kernel likelihood estimator + (mkle). + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKLE + url_git: '' +MKMeans: + version: '3.1' + title: A Modern K-Means (MKMeans) Clustering Algorithm + maintainer: Yarong Yang + description: It's a Modern K-Means clustering algorithm allowing data of any number + of dimensions, any initial center, and any number of clusters to expect. + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKMeans + url_git: '' +MKmisc: + version: '1.9' + title: Miscellaneous Functions from M. Kohl + maintainer: Matthias Kohl + description: Contains several functions for statistical data analysis; e.g. for + sample size and power calculations, computation of confidence intervals and tests, + and generation of similarity matrices. + date_publication: '2022-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKmisc + url_git: https://github.com/stamats/MKmisc +mknapsack: + version: 0.1.0 + title: Multiple Knapsack Problem Solver + maintainer: Bulat Yapparov + description: |- + Package solves multiple knapsack optimisation problem. + Given a set of items, each with volume and value, + it will allocate them to knapsacks of a given size in a way that + value of top N knapsacks is as large as possible. + date_publication: '2018-04-10' + bug_reports: https://github.com/madedotcom/mknapsack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mknapsack + url_git: https://github.com/madedotcom/mknapsack +MKomics: + version: '0.7' + title: Omics Data Analysis + maintainer: Matthias Kohl + description: Similarity plots based on correlation and median absolute deviation + (MAD); adjusting colors for heatmaps; aggregate technical replicates; calculate + pairwise fold-changes and log fold-changes; compute one- and two-way ANOVA; simplified + interface to package 'limma' (Ritchie et al. (2015), + ) for moderated t-test and one-way ANOVA; Hamming and Levenshtein (edit) distance + of strings as well as optimal alignment scores for global (Needleman-Wunsch) and + local (Smith-Waterman) alignments with constant gap penalties (Merkl and Waack + (2009), ISBN:978-3-527-32594-8). + date_publication: '2021-08-08' + bug_reports: '' + url: https://www.stamats.de/ + url_cran: https://CRAN.R-project.org/package=MKomics + url_git: '' +MKpower: + version: '1.0' + title: Power Analysis and Sample Size Calculation + maintainer: Matthias Kohl + description: Power analysis and sample size calculation for Welch and Hsu (Hedderich + and Sachs (2018), ISBN:978-3-662-56657-2) t-tests including Monte-Carlo simulations + of empirical power and type-I-error. Power and sample size calculation for Wilcoxon + rank sum and signed rank tests via Monte-Carlo simulations. Power and sample size + required for the evaluation of a diagnostic test(-system) (Flahault et al. (2005), + ; Dobbin and Simon (2007), ) + as well as for a single proportion (Fleiss et al. (2003), ISBN:978-0-471-52629-2; + Piegorsch (2004), ; Thulin (2014), ), + comparing two negative binomial rates (Zhu and Lakkis (2014), ), + ANCOVA (Shieh (2020), ), reference ranges (Jennen-Steinmetz + and Wellek (2005), ), multiple primary endpoints (Sozu et + al. (2015), ISBN:978-3-319-22005-5), and AUC (Hanley and McNeil (1982), ). + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MKpower + url_git: https://github.com/stamats/MKpower +mkssd: + version: '1.2' + title: Efficient Multi-Level k-Circulant Supersaturated Designs + maintainer: B N Mandal + description: Generates efficient balanced non-aliased multi-level k-circulant supersaturated + designs by interchanging the elements of the generator vector. Attempts to generate + a supersaturated design that has chisquare efficiency more than user specified + efficiency level (mef). Displays the progress of generation of an efficient multi-level + k-circulant design through a progress bar. The progress of 100% means that one + full round of interchange is completed. More than one full round (typically 4-5 + rounds) of interchange may be required for larger designs. + date_publication: '2022-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mkssd + url_git: '' +ML.MSBD: + version: 1.2.1 + title: Maximum Likelihood Inference on Multi-State Trees + maintainer: Joelle Barido-Sottani + description: 'Inference of a multi-states birth-death model from a phylogeny, comprising + a number of states N, birth and death rates for each state and on which edges + each state appears. Inference is done using a hybrid approach: states are progressively + added in a greedy approach. For a fixed number of states N the best model is selected + via maximum likelihood. Reference: J. Barido-Sottani, T. G. Vaughan and T. Stadler + (2018) .' + date_publication: '2021-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ML.MSBD + url_git: '' +ML2Pvae: + version: 1.0.0.1 + title: Variational Autoencoder Models for IRT Parameter Estimation + maintainer: Geoffrey Converse + description: Based on the work of Curi, Converse, Hajewski, and Oliveira (2019) + . This package provides easy-to-use functions + which create a variational autoencoder (VAE) to be used for parameter estimation + in Item Response Theory (IRT) - namely the Multidimensional Logistic 2-Parameter + (ML2P) model. To use a neural network as such, nontrivial modifications to the + architecture must be made, such as restricting the nonzero weights in the decoder + according to some binary matrix Q. The functions in this package allow for straight-forward + construction, training, and evaluation so that minimal knowledge of 'tensorflow' + or 'keras' is required. + date_publication: '2022-05-23' + bug_reports: '' + url: https://converseg.github.io + url_cran: https://CRAN.R-project.org/package=ML2Pvae + url_git: '' +mlapi: + version: 0.1.1 + title: Abstract Classes for Building 'scikit-learn' Like API + maintainer: Dmitriy Selivanov + description: |- + Provides 'R6' abstract classes for building machine learning models + with 'scikit-learn' like API. is a popular module + for 'Python' programming language which design became de facto a standard + in industry for machine learning tasks. + date_publication: '2022-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlapi + url_git: '' +mlbench: + version: 2.1-6 + title: Machine Learning Benchmark Problems + maintainer: Kurt Hornik + description: |- + A collection of artificial and real-world machine learning + benchmark problems, including, e.g., several + data sets from the UCI repository. + date_publication: '2024-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlbench + url_git: '' +mlbplotR: + version: 1.1.0 + title: |- + Create 'ggplot2' and 'gt' Visuals with Major League Baseball + Logos + maintainer: Camden Kay + description: |- + Tools to help visualize Major League Baseball analysis in 'ggplot2' + and 'gt'. You provide team/player information and 'mlbplotR' will transform + that information into team colors, logos, or player headshots for graphics. + date_publication: '2023-06-20' + bug_reports: https://github.com/camdenk/mlbplotR/issues + url: https://camdenk.github.io/mlbplotR/ + url_cran: https://CRAN.R-project.org/package=mlbplotR + url_git: https://github.com/camdenk/mlbplotR +mlbstats: + version: 0.1.0 + title: Major League Baseball Player Statistics Calculator + maintainer: Philip D. Waggoner + description: Computational functions for player metrics in major league baseball + including batting, pitching, fielding, base-running, and overall player statistics. + This package is actively maintained with new metrics being added as they are developed. + date_publication: '2018-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlbstats + url_git: '' +MLCIRTwithin: + version: 2.1.1 + title: |- + Latent Class Item Response Theory (LC-IRT) Models under + Within-Item Multidimensionality + maintainer: Francesco Bartolucci + description: Framework for the Item Response Theory analysis of dichotomous and + ordinal polytomous outcomes under the assumption of within-item multidimensionality + and discreteness of the latent traits. The fitting algorithms allow for missing + responses and for different item parametrizations and are based on the Expectation-Maximization + paradigm. Individual covariates affecting the class weights may be included in + the new version together with possibility of constraints on all model parameters. + date_publication: '2019-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLCIRTwithin + url_git: '' +MLCM: + version: 0.4.3 + title: Maximum Likelihood Conjoint Measurement + maintainer: Guillermo Aguilar + description: 'Conjoint measurement is a psychophysical procedure in which stimulus + pairs are presented that vary along 2 or more dimensions and the observer is required + to compare the stimuli along one of them. This package contains functions to + estimate the contribution of the n scales to the judgment by a maximum likelihood + method under several hypotheses of how the perceptual dimensions interact. Reference: + Knoblauch & Maloney (2012) "Modeling Psychophysical Data in R". .' + date_publication: '2022-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLCM + url_git: '' +MLCOPULA: + version: 1.0.1 + title: Classification Models with Copula Functions + maintainer: Rogelio Salinas Gutiérrez + description: Provides several classifiers based on probabilistic models. These classifiers + allow to model the dependence structure of continuous features through bivariate + copula functions and graphical models, see Salinas-Gutiérrez et al. (2014) . + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLCOPULA + url_git: '' +MLDataR: + version: 1.0.1 + title: |- + Collection of Machine Learning Datasets for Supervised Machine + Learning + maintainer: Gary Hutson + description: |- + Contains a collection of datasets for working with machine learning tasks. + It will contain datasets for supervised machine learning Jiang (2020) and will include datasets for classification and regression. + The aim of this package is to use data generated around health and other domains. + date_publication: '2022-10-03' + bug_reports: https://github.com/StatsGary/MLDataR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLDataR + url_git: '' +mldr: + version: 0.4.3 + title: |- + Exploratory Data Analysis and Manipulation of Multi-Label Data + Sets + maintainer: David Charte + description: |- + Exploratory data analysis and manipulation functions for multi- + label data sets along with an interactive Shiny application to ease their use. + date_publication: '2019-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mldr + url_git: https://github.com/fcharte/mldr +mldr.datasets: + version: 0.4.2 + title: R Ultimate Multilabel Dataset Repository + maintainer: David Charte + description: |- + Large collection of multilabel datasets along with the functions + needed to export them to several formats, to make partitions, and to obtain + bibliographic information. + date_publication: '2019-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mldr.datasets + url_git: https://github.com/fcharte/mldr.datasets +mldr.resampling: + version: 0.2.3 + title: Resampling Algorithms for Multi-Label Datasets + maintainer: Miguel Ángel Dávila + description: Collection of the state of the art multi-label resampling algorithms. + The objective of these algorithms is to achieve balance in multi-label datasets. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mldr.resampling + url_git: '' +MLDS: + version: 0.5.1 + title: Maximum Likelihood Difference Scaling + maintainer: Kenneth Knoblauch + description: |- + Difference scaling is a method for scaling perceived + supra-threshold differences. The package contains functions that + allow the user to design and run a difference scaling experiment, + to fit the resulting data by maximum likelihood and test the + internal validity of the estimated scale. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLDS + url_git: '' +MLE: + version: '1.4' + title: |- + Maximum Likelihood Estimation of Various Univariate and + Multivariate Distributions + maintainer: Michail Tsagris + description: Several functions for maximum likelihood estimation of various univariate + and multivariate distributions. The list includes more than 100 functions for + univariate continuous and discrete distributions, distributions that lie on the + real line, the positive line, interval restricted, circular distributions. Further, + multivariate continuous and discrete distributions, distributions for compositional + and directional data, etc. Some references include Johnson N. L., Kotz S. and + Balakrishnan N. (1994). "Continuous Univariate Distributions, Volume 1" , + Johnson, Norman L. Kemp, Adrianne W. Kotz, Samuel (2005). "Univariate Discrete + Distributions". and Mardia, K. V. and Jupp, P. E. (2000). + "Directional Statistics". . + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLE + url_git: '' +mle.tools: + version: 1.0.0 + title: |- + Expected/Observed Fisher Information and Bias-Corrected Maximum + Likelihood Estimate(s) + maintainer: Josmar Mazucheli + description: Calculates the expected/observed Fisher information and the bias-corrected + maximum likelihood estimate(s) via Cox-Snell Methodology. + date_publication: '2017-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mle.tools + url_git: '' +mlearning: + version: 1.2.1 + title: |- + Machine Learning Algorithms with Unified Interface and Confusion + Matrices + maintainer: Philippe Grosjean + description: |- + A unified interface is provided to various machine learning + algorithms like linear or quadratic discriminant analysis, k-nearest + neighbors, random forest, support vector machine, ... It allows to train, + test, and apply cross-validation using similar functions and function + arguments with a minimalist and clean, formula-based interface. Missing data + are processed the same way as base and stats R functions for all algorithms, + both in training and testing. Confusion matrices are also provided with a rich + set of metrics calculated and a few specific plots. + date_publication: '2023-08-30' + bug_reports: https://github.com/SciViews/mlearning/issues + url: https://www.sciviews.org/mlearning/ + url_cran: https://CRAN.R-project.org/package=mlearning + url_git: '' +MLEce: + version: 2.1.0 + title: |- + Asymptotic Efficient Closed-Form Estimators for Multivariate + Distributions + maintainer: Jun Zhao + description: |- + Asymptotic efficient closed-form estimators (MLEces) are provided in this package for three multivariate distributions(gamma, Weibull and Dirichlet) whose maximum likelihood estimators (MLEs) are not in closed forms. Closed-form estimators are strong consistent, and have the similar asymptotic normal distribution like MLEs. But the calculation of MLEces are much faster than the corresponding MLEs. Further details and explanations of MLEces can be found in. + Jang, et al. (2023) . + Kim, et al. (2023) . + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLEce + url_git: '' +MLEcens: + version: 0.1-7.1 + title: Computation of the MLE for Bivariate Interval Censored Data + maintainer: Marloes Maathuis + description: |- + We provide functions to compute the nonparametric + maximum likelihood estimator (MLE) for + the bivariate distribution of (X,Y), when + realizations of (X,Y) cannot be observed directly. + To be more precise, we consider the situation + where we observe a set of rectangles in R^2 that are known + to contain the unobservable realizations of (X,Y). We + compute the MLE based on such a set of rectangles. + The methods can also be used for univariate censored data (see data set + 'cosmesis'), and for + censored data with competing risks (see data set 'menopause'). + We also provide functions to visualize the observed data and the MLE. + date_publication: '2024-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLEcens + url_git: '' +mlegp: + version: 3.1.9 + title: Maximum Likelihood Estimates of Gaussian Processes + maintainer: Garrett M. Dancik + description: |- + Maximum likelihood Gaussian process modeling for + univariate and multi-dimensional outputs with diagnostic plots + following Santner et al (2003) . + Contact the maintainer for a package version that includes + sensitivity analysis. + date_publication: '2022-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlegp + url_git: '' +mlelod: + version: 1.0.0.1 + title: MLE for Normally Distributed Data Censored by Limit of Detection + maintainer: Gregor Sega + description: Values below the limit of detection (LOD) are a problem in several + fields of science, and there are numerous approaches for replacing the missing + data. We present a new mathematical solution for maximum likelihood estimation + that allows us to estimate the true values of the mean and standard deviation + for normal distributions and is significantly faster than previous implementations. + The article with the details was submitted to JSS and can be currently seen on + . + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlelod + url_git: '' +mlergm: + version: '0.8' + title: Multilevel Exponential-Family Random Graph Models + maintainer: Jonathan Stewart + description: 'Estimates exponential-family random graph models for multilevel network + data, assuming the multilevel structure is observed. The scope, at present, covers + multilevel models where the set of nodes is nested within known blocks. The estimation + method uses Monte-Carlo maximum likelihood estimation (MCMLE) methods to estimate + a variety of canonical or curved exponential family models for binary random graphs. + MCMLE methods for curved exponential-family random graph models can be found in + Hunter and Handcock (2006) . The package supports + parallel computing, and provides methods for assessing goodness-of-fit of models + and visualization of networks.' + date_publication: '2021-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlergm + url_git: '' +MLeval: + version: '0.3' + title: Machine Learning Model Evaluation + maintainer: Christopher R John + description: Straightforward and detailed evaluation of machine learning models. + 'MLeval' can produce receiver operating characteristic (ROC) curves, precision-recall + (PR) curves, calibration curves, and PR gain curves. 'MLeval' accepts a data frame + of class probabilities and ground truth labels, or, it can automatically interpret + the Caret train function results from repeated cross validation, then select the + best model and analyse the results. 'MLeval' produces a range of evaluation metrics + with confidence intervals. + date_publication: '2020-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLeval + url_git: '' +mlexperiments: + version: 0.0.4 + title: Machine Learning Experiments + maintainer: Lorenz A. Kapsner + description: |- + Provides 'R6' objects to perform parallelized hyperparameter + optimization and cross-validation. Hyperparameter optimization can be + performed with Bayesian optimization (via 'ParBayesianOptimization' + ) and grid + search. The optimized hyperparameters can be validated using k-fold + cross-validation. Alternatively, hyperparameter optimization and + validation can be performed with nested cross-validation. While + 'mlexperiments' focuses on core wrappers for machine learning + experiments, additional learner algorithms can be supplemented by + inheriting from the provided learner base class. + date_publication: '2024-07-05' + bug_reports: https://github.com/kapsner/mlexperiments/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlexperiments + url_git: https://github.com/kapsner/mlexperiments +mlf: + version: 1.2.1 + title: Machine Learning Foundations + maintainer: Kyle Peterson + description: 'Offers a gentle introduction to machine learning concepts for practitioners + with a statistical pedigree: decomposition of model error (bias-variance trade-off), + nonlinear correlations, information theory and functional permutation/bootstrap + simulations. Székely GJ, Rizzo ML, Bakirov NK. (2007). . + Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ, Lander + ES, Mitzenmacher M, Sabeti PC. (2011). .' + date_publication: '2018-06-25' + bug_reports: '' + url: http://mlf-project.us/ + url_cran: https://CRAN.R-project.org/package=mlf + url_git: '' +mlfit: + version: 0.5.3 + title: Iterative Proportional Fitting Algorithms for Nested Structures + maintainer: Amarin Siripanich + description: |- + The Iterative Proportional Fitting (IPF) algorithm operates on count data. + This package offers implementations for several algorithms that extend this to + nested structures: 'parent' and 'child' items for both of which constraints can be provided. + The fitting algorithms include Iterative Proportional Updating , + Hierarchical IPF , Entropy Optimization , + and Generalized Raking . Additionally, a number of replication methods + is also provided such as 'Truncate, replicate, sample' . + date_publication: '2021-10-08' + bug_reports: https://github.com/mlfit/mlfit/issues + url: https://mlfit.github.io/mlfit/ + url_cran: https://CRAN.R-project.org/package=mlfit + url_git: https://github.com/mlfit/mlfit +mlflow: + version: 2.19.0 + title: Interface to 'MLflow' + maintainer: Matei Zaharia + description: |- + R interface to 'MLflow', open source platform for + the complete machine learning life cycle, see . + This package supports installing 'MLflow', tracking experiments, + creating and running projects, and saving and serving models. + date_publication: '2024-12-18' + bug_reports: https://github.com/mlflow/mlflow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlflow + url_git: https://github.com/mlflow/mlflow +MLFS: + version: 0.4.2 + title: Machine Learning Forest Simulator + maintainer: Jernej Jevsenak + description: |- + Climate-sensitive forest simulator based on the principles of + machine learning. It stimulates all key processes in the forest: radial growth, + height growth, mortality, crown recession, regeneration and harvesting. The + method for predicting tree heights was described by Skudnik and Jevšenak + (2022) , while the method for predicting + basal area increments (BAI) was described by Jevšenak and Skudnik (2021) + . + date_publication: '2022-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLFS + url_git: '' +MLGdata: + version: 0.1.0 + title: Datasets for Use with Salvan, Sartori and Pace (2020) + maintainer: Nicola Sartori + description: Contains the datasets for use with the book Salvan, Sartori and Pace + (2020, ISBN:978-88-470-4002-1) "Modelli Lineari Generalizzati". + date_publication: '2020-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLGdata + url_git: '' +MLGL: + version: 1.0.0 + title: Multi-Layer Group-Lasso + maintainer: Quentin Grimonprez + description: It implements a new procedure of variable selection in the context + of redundancy between explanatory variables, which holds true with high dimensional + data (Grimonprez et al. (2023) ). + date_publication: '2023-03-15' + bug_reports: https://github.com/modal-inria/MLGL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLGL + url_git: '' +MLID: + version: 1.0.1 + title: Multilevel Index of Dissimilarity + maintainer: Richard Harris + description: Tools and functions to fit a multilevel index of dissimilarity. + date_publication: '2017-03-06' + bug_reports: https://github.com/profrichharris/MLID/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLID + url_git: https://github.com/profrichharris/MLID +mlim: + version: 0.3.0 + title: Single and Multiple Imputation with Automated Machine Learning + maintainer: E. F. Haghish + description: |- + Machine learning algorithms have been used for performing + single missing data imputation and most recently, multiple imputations. + However, this is the first attempt for using automated machine learning algorithms + for performing both + single and multiple imputation. Automated machine learning is a procedure for + fine-tuning the model automatic, performing a random search for a model that + results in less error, without overfitting the data. The main idea is + to allow the model to set its own parameters for imputing each variable separately + instead of setting fixed predefined parameters to impute all variables + of the dataset. + Using automated machine learning, the package fine-tunes an Elastic + Net (default) or Gradient Boosting, Random Forest, Deep Learning, Extreme Gradient Boosting, + or Stacked Ensemble machine learning model (from one or a combination of other + supported algorithms) for imputing the missing + observations. This procedure has been implemented for the + first time by this package and is expected to outperform other packages for + imputing missing data that do not fine-tune their models. The multiple imputation + is implemented via bootstrapping without letting the duplicated observations to + harm the cross-validation procedure, which is the way imputed variables are evaluated. + Most notably, the package implements automated procedure for handling imputing imbalanced + data (class rarity problem), which happens when a factor variable has a level that is far more + prevalent than the other(s). This is known to result in biased predictions, hence, biased + imputation of missing data. However, the autobalancing procedure ensures that instead of + focusing on maximizing accuracy (classification error) in imputing factor variables, + a fairer procedure and imputation method is practiced. + date_publication: '2022-12-16' + bug_reports: https://github.com/haghish/mlim/issues + url: https://www.sv.uio.no/psi/english/people/aca/haghish/ + url_cran: https://CRAN.R-project.org/package=mlim + url_git: https://github.com/haghish/mlim +mllrnrs: + version: 0.0.4 + title: R6-Based ML Learners for 'mlexperiments' + maintainer: Lorenz A. Kapsner + description: |- + Enhances 'mlexperiments' + with additional + machine learning ('ML') learners. The package provides R6-based + learners for the following algorithms: 'glmnet' + , 'ranger' + , 'xgboost' + , and 'lightgbm' + . These can be used + directly with the 'mlexperiments' R package. + date_publication: '2024-07-05' + bug_reports: https://github.com/kapsner/mllrnrs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mllrnrs + url_git: https://github.com/kapsner/mllrnrs +mlma: + version: 6.3-1 + title: Multilevel Mediation Analysis + maintainer: Qingzhao Yu + description: 'Do multilevel mediation analysis with generalized additive multilevel + models. The analysis method is described in Yu and Li (2020), "Third-Variable + Effect Analysis with Multilevel Additive Models", PLoS ONE 15(10): e0241072.' + date_publication: '2023-08-29' + bug_reports: '' + url: https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html + url_cran: https://CRAN.R-project.org/package=mlma + url_git: '' +mlmc: + version: 2.1.1 + title: Multi-Level Monte Carlo + maintainer: Louis Aslett + description: |- + An implementation of MLMC (Multi-Level Monte Carlo), Giles (2008) + , Heinrich (1998) , + for R. This package builds on the original 'Matlab' and 'C++' implementations + by Mike Giles to provide a full MLMC driver and example level samplers. + Multi-core parallel sampling of levels is provided built-in. + date_publication: '2024-11-11' + bug_reports: https://github.com/louisaslett/mlmc/issues + url: https://mlmc.louisaslett.com/ + url_cran: https://CRAN.R-project.org/package=mlmc + url_git: https://github.com/louisaslett/mlmc +MLmetrics: + version: 1.1.3 + title: Machine Learning Evaluation Metrics + maintainer: Yachen Yan + description: |- + A collection of evaluation metrics, including loss, score and + utility functions, that measure regression, classification and ranking performance. + date_publication: '2024-04-13' + bug_reports: https://github.com/yanyachen/MLmetrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLmetrics + url_git: https://github.com/yanyachen/MLmetrics +mlmhelpr: + version: 0.1.1 + title: Multilevel/Mixed Model Helper Functions + maintainer: Louis Rocconi + description: A collection of miscellaneous helper function for running multilevel/mixed + models in 'lme4'. This package aims to provide functions to compute common tasks + when estimating multilevel models such as computing the intraclass correlation + and design effect, centering variables, estimating the proportion of variance + explained at each level, pseudo-R squared, random intercept and slope reliabilities, + tests for homogeneity of variance at level-1, and cluster robust and bootstrap + standard errors. The tests and statistics reported in the package are from Raudenbush + & Bryk (2002, ISBN:9780761919049), Hox et al. (2018, ISBN:9781138121362), and + Snijders & Bosker (2012, ISBN:9781849202015). + date_publication: '2024-05-21' + bug_reports: https://github.com/lrocconi/mlmhelpr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlmhelpr + url_git: https://github.com/lrocconi/mlmhelpr +mlmi: + version: 1.1.2 + title: Maximum Likelihood Multiple Imputation + maintainer: Jonathan Bartlett + description: Implements so called Maximum Likelihood Multiple Imputation as described + by von Hippel and Bartlett (2021) . A number of different + imputations are available, by utilising the 'norm', 'cat' and 'mix' packages. + Inferences can be performed either using combination rules similar to Rubin's + or using a likelihood score based approach based on theory by Wang and Robins + (1998) . + date_publication: '2023-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlmi + url_git: '' +MLML2R: + version: 0.3.3 + title: |- + Maximum Likelihood Estimation of DNA Methylation and + Hydroxymethylation Proportions + maintainer: Samara Kiihl + description: |- + Maximum likelihood estimates (MLE) of the proportions + of 5-mC and 5-hmC in the DNA using information from BS-conversion, + TAB-conversion, and oxBS-conversion methods. One can use information from all three methods + or any combination of two of them. Estimates are based on Binomial model by + Qu et al. (2013) and + Kiihl et al. (2019) . + date_publication: '2019-10-17' + bug_reports: https://github.com/samarafk/MLML2R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLML2R + url_git: https://github.com/samarafk/MLML2R +mlmm.gwas: + version: 1.0.6 + title: Pipeline for GWAS Using MLMM + maintainer: Clement Mabire + description: Pipeline for Genome-Wide Association Study using Multi-Locus Mixed + Model from Segura V, Vilhjálmsson BJ et al. (2012) . The + pipeline include detection of associated SNPs with MLMM, model selection by lowest + eBIC and p-value threshold, estimation of the effects of the SNPs in the selected + model and graphical functions. + date_publication: '2019-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlmm.gwas + url_git: '' +MLModelSelection: + version: '1.0' + title: Model Selection in Multivariate Longitudinal Data Analysis + maintainer: Kuo-Jung Lee + description: An efficient Gibbs sampling algorithm is developed for Bayesian multivariate + longitudinal data analysis with the focus on selection of important elements in + the generalized autoregressive matrix. It provides posterior samples and estimates + of parameters. In addition, estimates of several information criteria such as + Akaike information criterion (AIC), Bayesian information criterion (BIC), deviance + information criterion (DIC) and prediction accuracy such as the marginal predictive + likelihood (MPL) and the mean squared prediction error (MSPE) are provided for + model selection. + date_publication: '2020-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLModelSelection + url_git: https://github.com/kuojunglee/ +MLMOI: + version: 0.1.2 + title: Estimating Frequencies, Prevalence and Multiplicity of Infection + maintainer: Meraj Hashemi + description: The implemented methods reach out to scientists that seek to estimate + multiplicity of infection (MOI) and lineage (allele) frequencies and prevalences + at molecular markers using the maximum-likelihood method described in Schneider + (2018) , and Schneider and Escalante (2014) + . Users can import data from Excel files in + various formats, and perform maximum-likelihood estimation on the imported data + by the package's moimle() function. + date_publication: '2023-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLMOI + url_git: '' +mlmpower: + version: 1.0.9 + title: Power Analysis and Data Simulation for Multilevel Models + maintainer: Brian T. Keller + description: |- + A declarative language for specifying multilevel models, + solving for population parameters based on specified variance-explained effect + size measures, generating data, and conducting power analyses to determine + sample size recommendations. The specification allows for any number of + within-cluster effects, between-cluster effects, covariate effects + at either level, and random coefficients. Moreover, the models do not + assume orthogonal effects, and predictors can correlate at either level + and accommodate models with multiple interaction effects. + date_publication: '2024-10-20' + bug_reports: https://github.com/bkeller2/mlmpower/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlmpower + url_git: https://github.com/bkeller2/mlmpower +mlmRev: + version: 1.0-8 + title: Examples from Multilevel Modelling Software Review + maintainer: Steve Walker + description: |- + Data and examples from a multilevel modelling software review + as well as other well-known data sets from the multilevel modelling + literature. + date_publication: '2020-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlmRev + url_git: '' +mlms: + version: 1.0.2 + title: |- + Multilevel Monitoring System Data for Wells in the USGS INL + Aquifer Monitoring Network + maintainer: Jason C. Fisher + description: |- + Analysis-ready datasets detailing the Multilevel Monitoring System (MLMS) + wells within the U.S. Geological Survey's (USGS) aquifer-monitoring network at + the Idaho National Laboratory (INL) in Idaho, and the data collected within these + wells. Supported by the U.S. Department of Energy (DOE), the USGS collected + discrete measurements of hydraulic head at various depths from wells in the + eastern Snake River Plain (ESRP) aquifer over several years. These measurements + were derived from data on fluid pressure, fluid temperature, and atmospheric + pressure. Each well was equipped with an MLMS, which included valved measurement + ports, packer bladders, casing segments, and couplers. The MLMS facilitated + monitoring at multiple hydraulically isolated depth intervals, reaching + significant depths below the land surface. Additionally, groundwater samples + were collected from these wells over multiple years and analyzed for various + chemical and physical parameters. + date_publication: '2024-11-21' + bug_reports: https://code.usgs.gov/inl/mlms/-/issues + url: https://code.usgs.gov/inl/mlms + url_cran: https://CRAN.R-project.org/package=mlms + url_git: '' +mlmtools: + version: 1.0.2 + title: Multi-Level Model Assessment Kit + maintainer: Laura Jamison + description: Multilevel models (mixed effects models) are the statistical tool of + choice for analyzing multilevel data (Searle et al, 2009). These models account + for the correlated nature of observations within higher level units by adding + group-level error terms that augment the singular residual error of a standard + OLS regression. Multilevel and mixed effects models often require specialized + data pre-processing and further post-estimation derivations and graphics to gain + insight into model results. The package presented here, 'mlmtools', is a suite + of pre- and post-estimation tools for multilevel models in 'R'. Package implements + post-estimation tools designed to work with models estimated using 'lme4''s (Bates + et al., 2014) lmer() function, which fits linear mixed effects regression models. + Searle, S. R., Casella, G., & McCulloch, C. E. (2009, ISBN:978-0470009598). Bates, + D., Mächler, M., Bolker, B., & Walker, S. (2014) . + date_publication: '2022-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlmtools + url_git: '' +mlmts: + version: 1.1.2 + title: Machine Learning Algorithms for Multivariate Time Series + maintainer: Angel Lopez-Oriona + description: |- + An implementation of several machine learning algorithms for + multivariate time series. The package includes functions allowing the + execution of clustering, classification or outlier detection methods, + among others. It also incorporates a collection of multivariate time + series datasets which can be used to analyse the performance of new + proposed algorithms. Some of these datasets are stored in GitHub data + packages 'ueadata1' to 'ueadata8'. To access these data packages, run + 'install.packages(c('ueadata1', 'ueadata2', 'ueadata3', 'ueadata4', 'ueadata5', 'ueadata6', 'ueadata7', 'ueadata8'), repos='')'. + The installation takes a couple of minutes but we strongly encourage the + users to do it if they want to have available all datasets of mlmts. + Practitioners from a broad variety of fields could + benefit from the general framework provided by 'mlmts'. + date_publication: '2024-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlmts + url_git: '' +MLMusingR: + version: 0.4.0 + title: Practical Multilevel Modeling + maintainer: Francis Huang + description: Convenience functions and datasets to be used with Practical Multilevel + Modeling using R. The package includes functions for calculating group means, + group mean centered variables, and displaying some basic missing data information. + A function for computing robust standard errors for linear mixed models based + on Liang and Zeger (1986) and Bell and 'McCaffrey' + (2002) + is included as well as a function for checking for level-one homoskedasticity + (Raudenbush & Bryk, 2002, ISBN:076191904X). + date_publication: '2025-01-09' + bug_reports: https://github.com/flh3/MLMusingR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLMusingR + url_git: https://github.com/flh3/MLMusingR +mlogit: + version: 1.1-1 + title: Multinomial Logit Models + maintainer: Yves Croissant + description: |- + Maximum likelihood estimation of random utility discrete + choice models. The software is described in Croissant (2020) + and the underlying methods in + Train (2009) . + date_publication: '2020-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlogit + url_git: https://r-forge.r-project.org/projects/mlogit/ +mlogitBMA: + version: 0.1-9 + title: Bayesian Model Averaging for Multinomial Logit Models + maintainer: Hana Sevcikova + description: Provides a modified function bic.glm of the BMA package that can be + applied to multinomial logit (MNL) data. The data is converted to binary logit + using the Begg & Gray approximation. The package also contains functions for maximum + likelihood estimation of MNL. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlogitBMA + url_git: '' +mlpack: + version: 4.5.1 + title: '''Rcpp'' Integration for the ''mlpack'' Library' + maintainer: Ryan Curtin + description: |- + A fast, flexible machine learning library, written in C++, that + aims to provide fast, extensible implementations of cutting-edge + machine learning algorithms. See also Curtin et al. (2023) + . + date_publication: '2024-12-05' + bug_reports: https://github.com/mlpack/mlpack/issues + url: https://www.mlpack.org/doc/user/bindings/r.html + url_cran: https://CRAN.R-project.org/package=mlpack + url_git: https://github.com/mlpack/mlpack +MLpreemption: + version: 1.0.1 + title: Maximum Likelihood Estimation of the Niche Preemption Model + maintainer: Jan Graffelman + description: Provides functions for obtaining estimates of the parameter of the + niche preemption model (also known as the geometric series), in particular a maximum + likelihood estimator (Graffelman, 2021) . The niche + preemption model is a widely used model in ecology and biodiversity studies. + date_publication: '2021-02-11' + bug_reports: '' + url: http://www-eio.upc.edu/~jan/ + url_cran: https://CRAN.R-project.org/package=MLpreemption + url_git: '' +MLPUGS: + version: 0.2.0 + title: |- + Multi-Label Prediction Using Gibbs Sampling (and Classifier + Chains) + maintainer: Mikhail Popov + description: |- + An implementation of classifier chains (CC's) for multi-label + prediction. Users can employ an external package (e.g. 'randomForest', + 'C50'), or supply their own. The package can train a single set of CC's or + train an ensemble of CC's -- in parallel if running in a multi-core + environment. New observations are classified using a Gibbs sampler since + each unobserved label is conditioned on the others. The package includes + methods for evaluating the predictions for accuracy and aggregating across + iterations and models to produce binary or probabilistic classifications. + date_publication: '2016-07-06' + bug_reports: https://github.com/bearloga/MLPUGS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLPUGS + url_git: https://github.com/bearloga/MLPUGS +mlpwr: + version: 1.1.1 + title: A Power Analysis Toolbox to Find Cost-Efficient Study Designs + maintainer: Felix Zimmer + description: |- + We implement a surrogate modeling algorithm to guide simulation-based + sample size planning. The method is described in detail in our paper (Zimmer & + Debelak (2023) ). It supports multiple study design + parameters and optimization with respect to a cost function. It can find + optimal designs that correspond to a desired statistical power or that fulfill + a cost constraint. We also provide a tutorial paper (Zimmer et al. (2023) + ). + date_publication: '2024-10-03' + bug_reports: https://github.com/flxzimmer/mlpwr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlpwr + url_git: https://github.com/flxzimmer/mlpwr +mlquantify: + version: 0.2.0 + title: Algorithms for Class Distribution Estimation + maintainer: Andre Maletzke + description: |- + Quantification is a prominent machine learning task that has received an + increasing amount of attention in the last years. The objective is to predict the + class distribution of a data sample. This package is a collection of machine learning + algorithms for class distribution estimation. This package include algorithms from + different paradigms of quantification. These methods are described in the paper: + A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set + size in quantification assessment. In Proceedings of the Twenty-Ninth International + Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. + . + date_publication: '2022-01-20' + bug_reports: https://github.com/andregustavom/mlquantify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlquantify + url_git: https://github.com/andregustavom/mlquantify +mlr: + version: 2.19.2 + title: Machine Learning in R + maintainer: Martin Binder + description: |- + Interface to a large number of classification and regression + techniques, including machine-readable parameter descriptions. There + is also an experimental extension for survival analysis, clustering + and general, example-specific cost-sensitive learning. Generic + resampling, including cross-validation, bootstrapping and subsampling. + Hyperparameter tuning with modern optimization techniques, for single- + and multi-objective problems. Filter and wrapper methods for feature + selection. Extension of basic learners with additional operations + common in machine learning, also allowing for easy nested resampling. + Most operations can be parallelized. + date_publication: '2024-06-12' + bug_reports: https://github.com/mlr-org/mlr/issues + url: https://mlr.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr + url_git: https://github.com/mlr-org/mlr +mlr3: + version: 0.22.1 + title: Machine Learning in R - Next Generation + maintainer: Marc Becker + description: |- + Efficient, object-oriented programming on the + building blocks of machine learning. Provides 'R6' objects for tasks, + learners, resamplings, and measures. The package is geared towards + scalability and larger datasets by supporting parallelization and + out-of-memory data-backends like databases. While 'mlr3' focuses on + the core computational operations, add-on packages provide additional + functionality. + date_publication: '2024-11-27' + bug_reports: https://github.com/mlr-org/mlr3/issues + url: https://mlr3.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3 + url_git: https://github.com/mlr-org/mlr3 +mlr3batchmark: + version: 0.2.0 + title: Batch Experiments for 'mlr3' + maintainer: Marc Becker + description: |- + Extends the 'mlr3' package with a connector to the package + 'batchtools'. This allows to run large-scale benchmark experiments on + scheduled high-performance computing clusters. + date_publication: '2024-11-25' + bug_reports: https://github.com/mlr-org/mlr3batchmark/issues + url: https:///mlr3batchmark.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3batchmark + url_git: https://github.com/mlr-org/mlr3batchmark +mlr3benchmark: + version: 0.1.7 + title: Analysis and Visualisation of Benchmark Experiments + maintainer: Sebastian Fischer + description: |- + Implements methods for post-hoc analysis and + visualisation of benchmark experiments, for 'mlr3' and beyond. + date_publication: '2024-12-02' + bug_reports: https://github.com/mlr-org/mlr3benchmark/issues + url: https://mlr3benchmark.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3benchmark + url_git: https://github.com/mlr-org/mlr3benchmark +mlr3cluster: + version: 0.1.11 + title: Cluster Extension for 'mlr3' + maintainer: Maximilian Mücke + description: Extends the 'mlr3' package with cluster analysis. + date_publication: '2025-02-19' + bug_reports: https://github.com/mlr-org/mlr3cluster/issues + url: https://mlr3cluster.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3cluster + url_git: https://github.com/mlr-org/mlr3cluster +mlr3data: + version: 0.9.0 + title: Collection of Machine Learning Data Sets for 'mlr3' + maintainer: Marc Becker + description: |- + A small collection of interesting and educational machine + learning data sets which are used as examples in the 'mlr3' book + (), the use case gallery + (), or in other examples. All data + sets are properly preprocessed and ready to be analyzed by most + machine learning algorithms. Data sets are automatically added to the + dictionary of tasks if 'mlr3' is loaded. + date_publication: '2024-11-08' + bug_reports: https://github.com/mlr-org/mlr3data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlr3data + url_git: https://github.com/mlr-org/mlr3data +mlr3db: + version: 0.5.2 + title: Data Base Backend for 'mlr3' + maintainer: Michel Lang + description: |- + Extends the 'mlr3' package with a backend to + transparently work with databases such as 'SQLite', 'DuckDB', 'MySQL', + 'MariaDB', or 'PostgreSQL'. The package provides two additional backends: + 'DataBackendDplyr' relies on the abstraction of package 'dbplyr' to + interact with most DBMS. 'DataBackendDuckDB' operates on 'DuckDB' data bases + and also on Apache Parquet files. + date_publication: '2023-11-04' + bug_reports: https://github.com/mlr-org/mlr3db/issues + url: https:///mlr3db.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3db + url_git: https://github.com/mlr-org/mlr3db +mlr3fairness: + version: 0.3.2 + title: Fairness Auditing and Debiasing for 'mlr3' + maintainer: Florian Pfisterer + description: |2- + + Integrates fairness auditing and bias mitigation methods for the 'mlr3' ecosystem. + This includes fairness metrics, reporting tools, visualizations and bias mitigation techniques such as + "Reweighing" described in 'Kamiran, Calders' (2012) and + "Equalized Odds" described in 'Hardt et al.' (2016) . + Integration with 'mlr3' allows for auditing of ML models as well as convenient joint tuning of + machine learning algorithms and debiasing methods. + date_publication: '2023-05-04' + bug_reports: https://github.com/mlr-org/mlr3fairness/issues + url: https://mlr3fairness.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3fairness + url_git: https://github.com/mlr-org/mlr3fairness +mlr3fda: + version: 0.2.0 + title: Extending 'mlr3' to Functional Data Analysis + maintainer: Sebastian Fischer + description: |- + Extends the 'mlr3' ecosystem to functional analysis by adding + support for irregular and regular functional data as defined in the + 'tf' package. The package provides 'PipeOps' for preprocessing + functional columns and for extracting scalar features, thereby + allowing standard machine learning algorithms to be applied + afterwards. Available operations include simple functional features + such as the mean or maximum, smoothing, interpolation, flattening, and + functional 'PCA'. + date_publication: '2024-07-22' + bug_reports: https://github.com/mlr-org/mlr3fda/issues + url: https://mlr3fda.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3fda + url_git: https://github.com/mlr-org/mlr3fda +mlr3filters: + version: 0.8.1 + title: Filter Based Feature Selection for 'mlr3' + maintainer: Marc Becker + description: |- + Extends 'mlr3' with filter methods for feature selection. + Besides standalone filter methods built-in methods of any + machine-learning algorithm are supported. Partial scoring of + multivariate filter methods is supported. + date_publication: '2024-11-08' + bug_reports: https://github.com/mlr-org/mlr3filters/issues + url: https://mlr3filters.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3filters + url_git: https://github.com/mlr-org/mlr3filters +mlr3fselect: + version: 1.3.0 + title: Feature Selection for 'mlr3' + maintainer: Marc Becker + description: |- + Feature selection package of the 'mlr3' ecosystem. It selects + the optimal feature set for any 'mlr3' learner. The package works with + several optimization algorithms e.g. Random Search, Recursive Feature + Elimination, and Genetic Search. Moreover, it can automatically + optimize learners and estimate the performance of optimized feature + sets with nested resampling. + date_publication: '2025-01-16' + bug_reports: https://github.com/mlr-org/mlr3fselect/issues + url: https://mlr3fselect.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3fselect + url_git: https://github.com/mlr-org/mlr3fselect +mlr3hyperband: + version: 0.6.0 + title: Hyperband for 'mlr3' + maintainer: Marc Becker + description: |- + Successive Halving (Jamieson and Talwalkar (2016) + ) and Hyperband (Li et al. 2018 ) + optimization algorithm for the mlr3 ecosystem. The implementation in + mlr3hyperband features improved scheduling and parallelizes the evaluation + of configurations. The package includes tuners for hyperparameter + optimization in mlr3tuning and optimizers for black-box optimization in + bbotk. + date_publication: '2024-06-29' + bug_reports: https://github.com/mlr-org/mlr3hyperband/issues + url: https://mlr3hyperband.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3hyperband + url_git: https://github.com/mlr-org/mlr3hyperband +mlr3inferr: + version: 0.1.0 + title: Inference on the Generalization Error + maintainer: Sebastian Fischer + description: |- + An 'mlr3' extension that provides various resampling-based + confidence interval (CI) methods for estimating the generalization + error. These CI methods are implemented as 'mlr3' measures, enabling + the evaluation of individual algorithms on specific tasks as well as + the comparison of different learning algorithms. + date_publication: '2025-01-13' + bug_reports: https://github.com/mlr-org/mlr3inferr/issues + url: https://mlr3inferr.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3inferr + url_git: https://github.com/mlr-org/mlr3inferr +mlr3learners: + version: 0.9.0 + title: Recommended Learners for 'mlr3' + maintainer: Marc Becker + description: |- + Recommended Learners for 'mlr3'. Extends 'mlr3' with + interfaces to essential machine learning packages on CRAN. This + includes, but is not limited to: (penalized) linear and logistic + regression, linear and quadratic discriminant analysis, k-nearest + neighbors, naive Bayes, support vector machines, and gradient + boosting. + date_publication: '2024-11-23' + bug_reports: https://github.com/mlr-org/mlr3learners/issues + url: https://mlr3learners.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3learners + url_git: https://github.com/mlr-org/mlr3learners +mlr3mbo: + version: 0.2.8 + title: Flexible Bayesian Optimization + maintainer: Lennart Schneider + description: |- + A modern and flexible approach to Bayesian Optimization / Model + Based Optimization building on the 'bbotk' package. 'mlr3mbo' is a toolbox + providing both ready-to-use optimization algorithms as well as their fundamental + building blocks allowing for straightforward implementation of custom + algorithms. Single- and multi-objective optimization is supported as well as + mixed continuous, categorical and conditional search spaces. Moreover, using + 'mlr3mbo' for hyperparameter optimization of machine learning models within the + 'mlr3' ecosystem is straightforward via 'mlr3tuning'. Examples of ready-to-use + optimization algorithms include Efficient Global Optimization by Jones et al. + (1998) , ParEGO by Knowles (2006) + and SMS-EGO by Ponweiser et al. (2008) + . + date_publication: '2024-11-21' + bug_reports: https://github.com/mlr-org/mlr3mbo/issues + url: https://mlr3mbo.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3mbo + url_git: https://github.com/mlr-org/mlr3mbo +mlr3measures: + version: 1.0.0 + title: Performance Measures for 'mlr3' + maintainer: Marc Becker + description: |- + Implements multiple performance measures for supervised + learning. Includes over 40 measures for regression and + classification. Additionally, meta information about the performance + measures can be queried, e.g. what the best and worst possible + performances scores are. + date_publication: '2024-09-11' + bug_reports: https://github.com/mlr-org/mlr3measures/issues + url: https:///mlr3measures.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3measures + url_git: https://github.com/mlr-org/mlr3measures +mlr3misc: + version: 0.16.0 + title: Helper Functions for 'mlr3' + maintainer: Marc Becker + description: |- + Frequently used helper functions and assertions used in + 'mlr3' and its companion packages. Comes with helper functions for + functional programming, for printing, to work with 'data.table', as + well as some generally useful 'R6' classes. This package also + supersedes the package 'BBmisc'. + date_publication: '2024-11-28' + bug_reports: https://github.com/mlr-org/mlr3misc/issues + url: https://mlr3misc.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3misc + url_git: https://github.com/mlr-org/mlr3misc +mlr3oml: + version: 0.10.0 + title: Connector Between 'mlr3' and 'OpenML' + maintainer: Sebastian Fischer + description: |- + Provides an interface to 'OpenML.org' to list and download + machine learning data, tasks and experiments. The 'OpenML' objects can + be automatically converted to 'mlr3' objects. For a more + sophisticated interface with more upload options, see + the 'OpenML' package. + date_publication: '2024-06-04' + bug_reports: https://github.com/mlr-org/mlr3oml/issues + url: https://mlr3oml.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3oml + url_git: https://github.com/mlr-org/mlr3oml +mlr3pipelines: + version: 0.7.1 + title: Preprocessing Operators and Pipelines for 'mlr3' + maintainer: Martin Binder + description: |- + Dataflow programming toolkit that enriches 'mlr3' with a diverse + set of pipelining operators ('PipeOps') that can be composed into graphs. + Operations exist for data preprocessing, model fitting, and ensemble + learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can + therefore be resampled, benchmarked, and tuned. + date_publication: '2024-11-14' + bug_reports: https://github.com/mlr-org/mlr3pipelines/issues + url: https://mlr3pipelines.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3pipelines + url_git: https://github.com/mlr-org/mlr3pipelines +mlr3resampling: + version: 2024.9.6 + title: Resampling Algorithms for 'mlr3' Framework + maintainer: Toby Hocking + description: |- + A supervised learning algorithm inputs a train set, + and outputs a prediction function, which can be used on a test set. + If each data point belongs to a group + (such as geographic region, year, etc), then + how do we know if it is possible to train on one group, and predict + accurately on another group? Cross-validation can be used to determine + the extent to which this is possible, by first assigning fold IDs from + 1 to K to all data (possibly using stratification, usually by group + and label). Then we loop over test sets (group/fold combinations), + train sets (same group, other groups, all groups), and compute + test/prediction accuracy for each combination. Comparing + test/prediction accuracy between same and other, we can determine the + extent to which it is possible (perfect if same/other have similar + test accuracy for each group; other is usually somewhat less accurate + than same; other can be just as bad as featureless baseline when the + groups have different patterns). + For more information, + + describes the method in depth. + How many train samples are required to get accurate predictions on a + test set? Cross-validation can be used to answer this question, with + variable size train sets. + date_publication: '2024-09-11' + bug_reports: https://github.com/tdhock/mlr3resampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlr3resampling + url_git: https://github.com/tdhock/mlr3resampling +mlr3shiny: + version: 0.5.0 + title: Machine Learning in 'shiny' with 'mlr3' + maintainer: Laurens Tetzlaff + description: A web-based graphical user interface to provide the basic steps of + a machine learning workflow. It uses the functionalities of the 'mlr3' framework. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlr3shiny + url_git: '' +mlr3spatial: + version: 0.5.0 + title: Support for Spatial Objects Within the 'mlr3' Ecosystem + maintainer: Marc Becker + description: |- + Extends the 'mlr3' ML framework with methods for spatial + objects. Data storage and prediction are supported for packages + 'terra', 'raster' and 'stars'. + date_publication: '2024-03-09' + bug_reports: https://github.com/mlr-org/mlr3spatial/issues + url: https://mlr3spatial.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3spatial + url_git: https://github.com/mlr-org/mlr3spatial +mlr3spatiotempcv: + version: 2.3.2 + title: Spatiotemporal Resampling Methods for 'mlr3' + maintainer: Patrick Schratz + description: |- + Extends the mlr3 machine learning framework with + spatio-temporal resampling methods to account for the presence of + spatiotemporal autocorrelation (STAC) in predictor variables. STAC may + cause highly biased performance estimates in cross-validation if + ignored. A JSS article is available at . + date_publication: '2024-11-29' + bug_reports: https://github.com/mlr-org/mlr3spatiotempcv/issues + url: https://mlr3spatiotempcv.mlr-org.com/ + url_cran: https://CRAN.R-project.org/package=mlr3spatiotempcv + url_git: https://github.com/mlr-org/mlr3spatiotempcv +mlr3summary: + version: 0.1.0 + title: Model and Learner Summaries for 'mlr3' + maintainer: Susanne Dandl + description: |- + Concise and interpretable summaries for machine learning models + and learners of the 'mlr3' ecosystem. + The package takes inspiration from the summary function for (generalized) + linear models but extends it to non-parametric machine learning models, + based on generalization performance, model complexity, feature importances + and effects, and fairness metrics. + date_publication: '2024-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlr3summary + url_git: '' +mlr3superlearner: + version: 0.1.2 + title: Super Learner Fitting and Prediction + maintainer: Nicholas Williams + description: |- + An implementation of the Super Learner prediction algorithm from + van der Laan, Polley, and Hubbard (2007) . + date_publication: '2025-01-14' + bug_reports: https://github.com/mlr-org/mlr3verse/issues + url: https://mlr3verse.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3verse + url_git: https://github.com/mlr-org/mlr3verse +mlr3viz: + version: 0.10.1 + title: Visualizations for 'mlr3' + maintainer: Marc Becker + description: |- + Visualization package of the 'mlr3' ecosystem. It features + plots for mlr3 objects such as tasks, learners, predictions, benchmark + results, tuning instances and filters via the 'autoplot()' generic of + 'ggplot2'. The package draws plots with the 'viridis' color palette + and applies the minimal theme. Visualizations include barplots, + boxplots, histograms, ROC curves, and Precision-Recall curves. + date_publication: '2025-01-16' + bug_reports: https://github.com/mlr-org/mlr3viz/issues + url: https://mlr3viz.mlr-org.com + url_cran: https://CRAN.R-project.org/package=mlr3viz + url_git: https://github.com/mlr-org/mlr3viz +mlrCPO: + version: 0.3.7-7 + title: |- + Composable Preprocessing Operators and Pipelines for Machine + Learning + maintainer: Martin Binder + description: |- + Toolset that enriches 'mlr' with a diverse set of preprocessing + operators. Composable Preprocessing Operators ("CPO"s) are first-class + R objects that can be applied to data.frames and 'mlr' "Task"s to modify + data, can be attached to 'mlr' "Learner"s to add preprocessing to machine + learning algorithms, and can be composed to form preprocessing pipelines. + date_publication: '2024-02-20' + bug_reports: https://github.com/mlr-org/mlrCPO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlrCPO + url_git: https://github.com/mlr-org/mlrCPO +mlrintermbo: + version: 0.5.1-1 + title: Model-Based Optimization for 'mlr3' Through 'mlrMBO' + maintainer: Martin Binder + description: |- + The 'mlrMBO' package can ordinarily not be used for optimization within 'mlr3', because of + incompatibilities of their respective class systems. 'mlrintermbo' offers a compatibility + interface that provides 'mlrMBO' as an 'mlr3tuning' 'Tuner' object, for tuning of machine + learning algorithms within 'mlr3', as well as a 'bbotk' 'Optimizer' object for optimization + of general objective functions using the 'bbotk' black box optimization framework. The + control parameters of 'mlrMBO' are faithfully reproduced as a 'paradox' 'ParamSet'. + date_publication: '2024-06-07' + bug_reports: https://github.com/mb706/mlrintermbo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlrintermbo + url_git: https://github.com/mb706/mlrintermbo +mlrMBO: + version: 1.1.5.1 + title: |- + Bayesian Optimization and Model-Based Optimization of Expensive + Black-Box Functions + maintainer: Jakob Richter + description: |- + Flexible and comprehensive R toolbox for model-based optimization + ('MBO'), also known as Bayesian optimization. It implements the Efficient + Global Optimization Algorithm and is designed for both single- and multi- + objective optimization with mixed continuous, categorical and conditional + parameters. The machine learning toolbox 'mlr' provide dozens of regression + learners to model the performance of the target algorithm with respect to + the parameter settings. It provides many different infill criteria to guide + the search process. Additional features include multi-point batch proposal, + parallel execution as well as visualization and sophisticated logging + mechanisms, which is especially useful for teaching and understanding of + algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that + single components can be easily replaced or adapted by the user for specific + use cases. + date_publication: '2022-07-04' + bug_reports: https://github.com/mlr-org/mlrMBO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlrMBO + url_git: https://github.com/mlr-org/mlrMBO +mlrpro: + version: 0.1.2 + title: Stepwise Regression with Assumptions Checking + maintainer: Thidarat Thongsri + description: The stepwise regression with assumptions checking and the possible + Box-Cox transformation. + date_publication: '2022-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlrpro + url_git: '' +mlrv: + version: 0.1.2 + title: Long-Run Variance Estimation in Time Series Regression + maintainer: Lujia Bai + description: Plug-in and difference-based long-run covariance matrix estimation + for time series regression. Two applications of hypothesis testing are also provided. + The first one is for testing for structural stability in coefficient functions. + The second one is aimed at detecting long memory in time series regression. Lujia + Bai and Weichi Wu (2024) Zhou Zhou and Wei Biao Wu(2010) + Jianqing Fan and Wenyang Zhang Lujia Bai and Weichi + Wu(2024) Dimitris N. Politis, Joseph P. Romano, Michael + Wolf(1999) Weichi Wu and Zhou Zhou(2018). + date_publication: '2024-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlrv + url_git: '' +mlsbm: + version: 0.99.2 + title: Efficient Estimation of Bayesian SBMs & MLSBMs + maintainer: Carter Allen + description: Fit Bayesian stochastic block models (SBMs) and multi-level stochastic + block models (MLSBMs) using efficient Gibbs sampling implemented in 'Rcpp'. The + models assume symmetric, non-reflexive graphs (no self-loops) with unweighted, + binary edges. Data are input as a symmetric binary adjacency matrix (SBMs), or + list of such matrices (MLSBMs). + date_publication: '2021-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlsbm + url_git: '' +mlsjunkgen: + version: 0.1.2 + title: |- + Use the MLS Junk Generator Algorithm to Generate a Stream of + Pseudo-Random Numbers + maintainer: Steve Myles + description: |- + Generate a stream of pseudo-random numbers generated using the MLS + Junk Generator algorithm. Functions exist to generate single pseudo-random + numbers as well as a vector, data frame, or matrix of pseudo-random numbers. + date_publication: '2021-05-02' + bug_reports: https://github.com/scumdogsteev/mlsjunkgen/issues + url: https://stevemyles.site/mlsjunkgen/ + url_cran: https://CRAN.R-project.org/package=mlsjunkgen + url_git: https://github.com/scumdogsteev/mlsjunkgen +mlstrOpalr: + version: 1.0.3 + title: |- + Support Compatibility Between 'Maelstrom' R Packages and 'Opal' + Environment + maintainer: Guillaume Fabre + description: |- + Functions to support compatibility between 'Maelstrom' R packages + and 'Opal' environment. 'Opal' is the 'OBiBa' core database application for + biobanks. It is used to build data repositories that integrates data + collected from multiple sources. 'Opal Maelstrom' is a specific + implementation of this software. This 'Opal' client is specifically + designed to interact with 'Opal Maelstrom' distributions to perform + operations on the R server side. The user must have adequate credentials. + Please see for complete documentation. + date_publication: '2024-05-01' + bug_reports: https://github.com/maelstrom-research/mlstrOpalr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlstrOpalr + url_git: https://github.com/maelstrom-research/mlstrOpalr +mlsurvlrnrs: + version: 0.0.4 + title: R6-Based ML Survival Learners for 'mlexperiments' + maintainer: Lorenz A. Kapsner + description: |- + Enhances 'mlexperiments' + with additional + machine learning ('ML') learners for survival analysis. The package + provides R6-based survival learners for the following algorithms: + 'glmnet' , 'ranger' + , 'xgboost' + , and 'rpart' + . These can be used directly + with the 'mlexperiments' R package. + date_publication: '2024-07-05' + bug_reports: https://github.com/kapsner/mlsurvlrnrs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlsurvlrnrs + url_git: https://github.com/kapsner/mlsurvlrnrs +mlt: + version: 1.6-2 + title: Most Likely Transformations + maintainer: Torsten Hothorn + description: |- + Likelihood-based estimation of conditional transformation + models via the most likely transformation approach described in + Hothorn et al. (2018) and Hothorn (2020) + . Shift-scale (Siegfried et al, 2023, ) + and multivariate (Klein et al, 2022, ) transformation models + are part of this package. A package vignette is available from and + more convenient user interfaces to many models from . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlt + url_git: http://ctm.R-forge.R-project.org +mlt.docreg: + version: 1.1-10 + title: 'Most Likely Transformations: Documentation and Regression Tests' + maintainer: Torsten Hothorn + description: |- + Additional documentation, a package vignette and + regression tests for package mlt. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlt.docreg + url_git: http://ctm.R-forge.R-project.org +mltest: + version: 1.0.3 + title: Classification Evaluation Metrics + maintainer: G. Dudnik + description: |- + A fast, robust and easy-to-use calculation + of multi-class classification evaluation metrics based on confusion matrix. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mltest + url_git: '' +mltools: + version: 0.3.5 + title: Machine Learning Tools + maintainer: Ben Gorman + description: A collection of machine learning helper functions, particularly assisting + in the Exploratory Data Analysis phase. Makes heavy use of the 'data.table' package + for optimal speed and memory efficiency. Highlights include a versatile bin_data() + function, sparsify() for converting a data.table to sparse matrix format with + one-hot encoding, fast evaluation metrics, and empirical_cdf() for calculating + empirical Multivariate Cumulative Distribution Functions. + date_publication: '2018-05-12' + bug_reports: https://github.com/ben519/mltools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mltools + url_git: https://github.com/ben519/mltools +mlts: + version: 1.0.0 + title: Multilevel Latent Time Series Models with 'R' and 'Stan' + maintainer: Kenneth Koslowski + description: |- + Fit multilevel manifest or latent time-series models, including popular Dynamic Structural Equation Models (DSEM). + The models can be set up and modified with user-friendly functions and are fit to the data using 'Stan' for Bayesian inference. + Path models and formulas for user-defined models can be easily created with functions using 'knitr'. + Asparouhov, Hamaker, & Muthen (2018) . + date_publication: '2024-06-27' + bug_reports: https://github.com/munchfab/mlts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mlts + url_git: https://github.com/munchfab/mlts +mlVAR: + version: 0.5.2 + title: Multi-Level Vector Autoregression + maintainer: Sacha Epskamp + description: |- + Estimates the multi-level vector autoregression model on time-series data. + Three network structures are obtained: temporal networks, contemporaneous + networks and between-subjects networks. + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mlVAR + url_git: '' +MLVSBM: + version: 0.2.4 + title: A Stochastic Block Model for Multilevel Networks + maintainer: Saint-Clair Chabert-Liddell + description: |- + Simulation, inference and clustering of multilevel networks using a + Stochastic Block Model framework as described in Chabert-Liddell, Barbillon, + Donnet and Lazega (2021) . + A multilevel network is defined as the junction of two interaction networks, + the upper level or inter-organizational level and the lower level or + inter-individual level. The inter-level represents an affiliation + relationship. + date_publication: '2022-08-05' + bug_reports: https://github.com/Chabert-Liddell/MLVSBM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MLVSBM + url_git: https://github.com/Chabert-Liddell/MLVSBM +mlxR: + version: 4.2.0 + title: Simulation of Longitudinal Data + maintainer: Marc Lavielle + description: |- + Simulation and visualization of complex + models for longitudinal data. The models are encoded using the model coding + language 'Mlxtran' and automatically converted into C++ codes. + That allows one to implement very easily complex ODE-based models and complex + statistical models, including mixed effects models, for continuous, count, + categorical, and time-to-event data. + date_publication: '2021-01-19' + bug_reports: https://github.com/MarcLavielle/mlxR/issues + url: http://simulx.webpopix.org + url_cran: https://CRAN.R-project.org/package=mlxR + url_git: '' +MLZ: + version: 0.1.5 + title: Mean Length-Based Estimators of Mortality using TMB + maintainer: Quang Huynh + description: Estimation functions and diagnostic tools for mean length-based total + mortality estimators based on Gedamke and Hoenig (2006) . + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MLZ + url_git: '' +MM: + version: 1.6-8 + title: The Multiplicative Multinomial Distribution + maintainer: Robin K. S. Hankin + description: Various utilities for the Multiplicative Multinomial distribution. + date_publication: '2024-05-16' + bug_reports: https://github.com/RobinHankin/MM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MM + url_git: https://github.com/RobinHankin/MM +MM2Sdata: + version: 1.0.3 + title: Gene Expression Datasets for the 'MM2S' Package + maintainer: Benjamin Haibe-Kains + description: Gene Expression datasets for the 'MM2S' package. Contains normalized + expression data for Human Medulloblastoma ('GSE37418') as well as Mouse Medulloblastoma + models ('GSE36594'). Deena Gendoo et al. (2015) . + date_publication: '2019-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MM2Sdata + url_git: '' +MM4LMM: + version: 3.0.3 + title: Inference of Linear Mixed Models Through MM Algorithm + maintainer: Fabien Laporte + description: The main function MMEst() performs (Restricted) Maximum Likelihood + in a variance component mixed models using a Min-Max (MM) algorithm (Laporte, + F., Charcosset, A. & Mary-Huard, T. (2022) ). + date_publication: '2024-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MM4LMM + url_git: '' +mma: + version: 10.7-1 + title: Multiple Mediation Analysis + maintainer: Qingzhao Yu + description: |- + Used for general multiple mediation analysis. + The analysis method is described in Yu and Li (2022) (ISBN: 9780367365479) "Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS", published by Chapman and Hall/CRC; and Yu et al.(2017) "Exploring racial disparity in obesity: a mediation analysis considering geo-coded environmental factors", published on Spatial and Spatio-temporal Epidemiology, 21, 13-23. + date_publication: '2023-08-29' + bug_reports: '' + url: https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html + url_cran: https://CRAN.R-project.org/package=mma + url_git: '' +mmabig: + version: 3.2-0 + title: Multiple Mediation Analysis for Big Data Sets + maintainer: Qingzhao Yu + description: Used for general multiple mediation analysis with big data sets. + date_publication: '2023-08-29' + bug_reports: '' + url: https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html + url_cran: https://CRAN.R-project.org/package=mmabig + url_git: '' +MMAC: + version: 0.1.2 + title: Data for Mathematical Modeling and Applied Calculus + maintainer: Joel Kilty + description: 'Contains the data sets for the textbook "Mathematical Modeling and + Applied Calculus" by Joel Kilty and Alex M. McAllister. The book will be published + by Oxford University Press in 2018 with ISBN-13: 978-019882472.' + date_publication: '2018-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMAC + url_git: '' +MMAD: + version: 1.0.0 + title: MM Algorithm Based on the Assembly-Decomposition Technology + maintainer: Dengge Liu + description: |- + The Minorize-Maximization(MM) algorithm based on Assembly-Decomposition(AD) technology can be used for model estimation of parametric models, semi-parametric models and non-parametric models. We selected parametric models including left truncated normal distribution, type I multivariate zero-inflated generalized poisson distribution and multivariate compound zero-inflated generalized poisson distribution; semiparametric models include Cox model and gamma frailty model; nonparametric model is estimated for type II interval-censored data. These general methods are proposed based on the following papers, + Tian, Huang and Xu (2019) , + Huang, Xu and Tian (2019) , + Zhang and Huang (2022) . + date_publication: '2023-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMAD + url_git: '' +mmand: + version: 1.6.3 + title: Mathematical Morphology in Any Number of Dimensions + maintainer: Jon Clayden + description: |- + Provides tools for performing mathematical morphology operations, + such as erosion and dilation, on data of arbitrary dimensionality. Can also + be used for finding connected components, resampling, filtering, smoothing + and other image processing-style operations. + date_publication: '2023-02-07' + bug_reports: https://github.com/jonclayden/mmand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmand + url_git: https://github.com/jonclayden/mmand +mmap: + version: 0.6-22 + title: Map Pages of Memory + maintainer: Jeffrey A. Ryan + description: R interface to POSIX mmap and Window's MapViewOfFile. + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmap + url_git: '' +mmapcharr: + version: 0.3.0 + title: Memory-Map Character Files + maintainer: Florian Privé + description: |- + Uses memory-mapping to enable the random access of elements of + a text file of characters separated by characters as if it were a simple + R(cpp) matrix. + date_publication: '2019-02-26' + bug_reports: https://github.com/privefl/mmapcharr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmapcharr + url_git: https://github.com/privefl/mmapcharr +mmaqshiny: + version: 1.0.0 + title: Explore Air-Quality Mobile-Monitoring Data + maintainer: Adithi R. Upadhya + description: |- + Mobile-monitoring or "sensors on a mobile platform", is an increasingly + popular approach to measure high-resolution pollution data at the street level. + Coupled with location data, spatial visualisation of air-quality parameters + helps detect localized areas of high air-pollution, also called hotspots. + In this approach, portable sensors are mounted on a vehicle and driven on + predetermined routes to collect high frequency data (1 Hz). + 'mmaqshiny' is for analysing, visualising and spatial mapping of + high-resolution air-quality data collected by specific devices installed on + a moving platform. 1 Hz data of PM2.5 (mass concentrations of particulate + matter with size less than 2.5 microns), Black carbon mass concentrations + (BC), ultra-fine particle number concentrations, carbon dioxide along with + GPS coordinates and relative humidity (RH) data collected by popular + portable instruments (TSI DustTrak-8530, Aethlabs microAeth-AE51, TSI CPC3007, + LICOR Li-830, Garmin GPSMAP 64s, Omega USB RH probe respectively). It + incorporates device specific cleaning and correction algorithms. RH correction + is applied to DustTrak PM2.5 following the Chakrabarti et al., (2004) + . Provision is given to add linear + regression coefficients for correcting the PM2.5 data (if required). BC data + will be cleaned for the vibration generated noise, by adopting the statistical + procedure as explained in Apte et al., (2011) , + followed by a loading correction as suggested by Ban-Weiss et al., (2009) + . For the number concentration data, provision is + given for dilution correction factor (if a diluter is used with CPC3007; + default value is 1). The package joins the raw, cleaned and corrected data + from the above said instruments and outputs as a downloadable csv file. + date_publication: '2020-06-26' + bug_reports: https://github.com/meenakshi-kushwaha/mmaqshiny/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmaqshiny + url_git: https://github.com/meenakshi-kushwaha/mmaqshiny +mMARCH.AC: + version: 2.9.4.0 + title: Processing of Accelerometry Data with 'GGIR' in mMARCH + maintainer: Wei Guo + description: 'Mobile Motor Activity Research Consortium for Health (mMARCH) is a + collaborative network of studies of clinical and community samples that employ + common clinical, biological, and digital mobile measures across involved studies. + One of the main scientific goals of mMARCH sites is developing a better understanding + of the inter-relationships between accelerometry-measured physical activity (PA), + sleep (SL), and circadian rhythmicity (CR) and mental and physical health in children, + adolescents, and adults. Currently, there is no consensus on a standard procedure + for a data processing pipeline of raw accelerometry data, and few open-source + tools to facilitate their development. The R package ''GGIR'' is the most prominent + open-source software package that offers great functionality and tremendous user + flexibility to process raw accelerometry data. However, even with ''GGIR'', processing + done in a harmonized and reproducible fashion requires a non-trivial amount of + expertise combined with a careful implementation. In addition, novel accelerometry-derived + features of PA/SL/CR capturing multiscale, time-series, functional, distributional + and other complimentary aspects of accelerometry data being constantly proposed + and become available via non-GGIR R implementations. To address these issues, + mMARCH developed a streamlined harmonized and reproducible pipeline for loading + and cleaning raw accelerometry data, extracting features available through ''GGIR'' + as well as through non-GGIR R packages, implementing several data and feature + quality checks, merging all features of PA/SL/CR together, and performing multiple + analyses including Joint Individual Variation Explained (JIVE), an unsupervised + machine learning dimension reduction technique that identifies latent factors + capturing joint across and individual to each of three domains of PA/SL/CR. In + detail, the pipeline generates all necessary R/Rmd/shell files for data processing + after running ''GGIR'' for accelerometer data. In module 1, all csv files in the + ''GGIR'' output directory were read, transformed and then merged. In module 2, + the ''GGIR'' output files were checked and summarized in one excel sheet. In module + 3, the merged data was cleaned according to the number of valid hours on each + night and the number of valid days for each subject. In module 4, the cleaned + activity data was imputed by the average Euclidean norm minus one (ENMO) over + all the valid days for each subject. Finally, a comprehensive report of data processing + was created using Rmarkdown, and the report includes few exploratory plots and + multiple commonly used features extracted from minute level actigraphy data. Reference: + Guo W, Leroux A, Shou S, Cui L, Kang S, Strippoli MP, Preisig M, Zipunnikov V, + Merikangas K (2022) Processing of accelerometry data with GGIR in Motor Activity + Research Consortium for Health (mMARCH) Journal for the Measurement of Physical + Behaviour, 6(1): 37-44.' + date_publication: '2024-08-23' + bug_reports: https://github.com/WeiGuoNIMH/mMARCH.AC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mMARCH.AC + url_git: https://github.com/WeiGuoNIMH/mMARCH.AC +mmb: + version: 0.13.3 + title: Arbitrary Dependency Mixed Multivariate Bayesian Models + maintainer: Sebastian Hönel + description: |- + Supports Bayesian models with full and partial (hence + arbitrary) dependencies between random variables. Discrete and continuous + variables are supported, and conditional joint probabilities and probability + densities are estimated using Kernel Density Estimation (KDE). The full + general form, which implements an extension to Bayes' theorem, as well as + the simple form, which is just a Bayesian network, both support regression + through segmentation and KDE and estimation of probability or relative + likelihood of discrete or continuous target random variables. This package + also provides true statistical distance measures based on Bayesian models. + Furthermore, these measures can be facilitated on neighborhood searches, + and to estimate the similarity and distance between data points. + Related work is by Bayes (1763) + and by Scutari (2010) . + date_publication: '2020-09-23' + bug_reports: https://github.com/MrShoenel/R-mmb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmb + url_git: https://github.com/MrShoenel/R-mmb +mmc: + version: 0.0.3 + title: Multivariate Measurement Error Correction + maintainer: Jaejoon Song + description: Provides routines for multivariate measurement error correction. Includes + procedures for linear, logistic and Cox regression models. Bootstrapped standard + errors and confidence intervals can be obtained for corrected estimates. + date_publication: '2015-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmc + url_git: '' +mmcards: + version: 0.1.1 + title: Playing Cards Utility Functions + maintainer: Mackson Ncube + description: |- + Early insights in probability theory were largely influenced by + questions about gambling and games of chance, as noted by Blitzstein and + Hwang (2019, ISBN:978-1138369917). In modern times, playing cards continue + to serve as an effective teaching tool for probability, statistics, and even + 'R' programming, as demonstrated by Grolemund (2014, ISBN:978-1449359010). + The 'mmcards' package offers a collection of utility functions designed to + aid in the creation, manipulation, and utilization of playing card decks in + multiple formats. These include a standard 52-card deck, as well as + alternative decks such as decks defined by custom anonymous functions and + custom interleaved decks. Optimized for the development of educational + 'shiny' applications, the package is particularly useful for teaching + statistics and probability through card-based games. Functions include + shuffle_deck(), which creates either a shuffled standard deck or a shuffled + custom alternative deck; deal_card(), which takes a deck and returns a list + object containing both the dealt card and the updated deck; and i_deck(), + which adds image paths to card objects, further enriching the package's + utility in the development of interactive 'shiny' application card games. + date_publication: '2023-09-06' + bug_reports: https://github.com/mightymetrika/mmcards/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmcards + url_git: https://github.com/mightymetrika/mmcards +mmcif: + version: 0.1.1 + title: Mixed Multivariate Cumulative Incidence Functions + maintainer: Benjamin Christoffersen + description: |- + Fits the mixed cumulative incidence functions model suggested by + which decomposes within cluster + dependence of risk and timing. The estimation method supports computation in + parallel using a shared memory C++ implementation. A sandwich estimator of the + covariance matrix is available. Natural cubic splines are used to provide a + flexible model for the cumulative incidence functions. + date_publication: '2022-07-17' + bug_reports: https://github.com/boennecd/mmcif/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmcif + url_git: https://github.com/boennecd/mmcif +mmcm: + version: 1.2-8 + title: Modified Maximum Contrast Method + maintainer: Kengo Nagashima + description: |- + An implementation of modified maximum contrast methods (Sato et al. (2009) ; + Nagashima et al. (2011) ) and the maximum contrast method (Yoshimura et al. (1997) + ): Functions mmcm.mvt() and mcm.mvt() give P-value by using randomized quasi-Monte + Carlo method with pmvt() function of package 'mvtnorm', and mmcm.resamp() gives P-value by using a permutation method. + date_publication: '2020-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmcm + url_git: '' +mmconvert: + version: '0.10' + title: Mouse Map Converter + maintainer: Karl W Broman + description: Convert mouse genome positions between the build 39 physical map and + the genetic map of Cox et al. (2009) . + date_publication: '2023-04-25' + bug_reports: https://github.com/rqtl/mmconvert/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmconvert + url_git: https://github.com/rqtl/mmconvert +Mmcsd: + version: 1.0.0 + title: Modeling Complex Longitudinal Data in a Quick and Easy Way + maintainer: Pedro Pacheco + description: |- + Matching longitudinal methodology models with complex sampling design. It fits fixed + and random effects models and covariance structured models so far. It also + provides tools to perform statistical tests considering these specifications as described in : Pacheco, P. H. (2021). "Modeling complex longitudinal data in R: development of a statistical package." . + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mmcsd + url_git: '' +MMD: + version: 1.0.0 + title: |- + Minimal Multilocus Distance (MMD) for Source Attribution and + Loci Selection + maintainer: Francisco Perez-Reche + description: |- + The aim of the package is two-fold: (i) To implement + the MMD method for attribution of individuals to sources using + the Hamming distance between multilocus genotypes. (ii) To select + informative genetic markers based on information theory concepts + (entropy, mutual information and redundancy). The package implements the + functions introduced by Perez-Reche, F. J., Rotariu, O., Lopes, B. S., + Forbes, K. J. and Strachan, N. J. C. Mining whole genome sequence data to + efficiently attribute individuals to source populations. + Scientific Reports 10, 12124 (2020) . + See more details and examples in the README file. + date_publication: '2021-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMD + url_git: '' +MMDai: + version: 2.0.0 + title: |- + Multivariate Multinomial Distribution Approximation and + Imputation for Incomplete Categorical Data + maintainer: Chaojie Wang + description: A method to impute the missingness in categorical data. Details see + the paper . + date_publication: '2020-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMDai + url_git: '' +MMDCopula: + version: 0.2.1 + title: Robust Estimation of Copulas by Maximum Mean Discrepancy + maintainer: Alexis Derumigny + description: |- + Provides functions for the robust estimation of + parametric families of copulas using minimization of + the Maximum Mean Discrepancy, following the article + Alquier, Chérief-Abdellatif, Derumigny and Fermanian (2022) + . + date_publication: '2022-04-25' + bug_reports: https://github.com/AlexisDerumigny/MMDCopula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MMDCopula + url_git: '' +MMDvariance: + version: 0.0.9 + title: |- + Detecting Differentially Variable Genes Using the Mixture of + Marginal Distributions + maintainer: Weiliang Qiu + description: 'Gene selection based on variance using the marginal distributions + of gene profiles that characterized by a mixture of three-component multivariate + distributions. Please see the reference: Li X, Fu Y, Wang X, DeMeo DL, Tantisira + K, Weiss ST, Qiu W. (2018) .' + date_publication: '2018-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMDvariance + url_git: '' +mme: + version: 0.1-6 + title: Multinomial Mixed Effects Models + maintainer: E. Lopez-Vizcaino + description: |- + Fit Gaussian Multinomial mixed-effects models for small area estimation: Model 1, with one + random effect in each category of the response variable (Lopez-Vizcaino,E. et al., 2013) ; Model 2, introducing + independent time effect; Model 3, introducing correlated time effect. + mme calculates direct and parametric bootstrap MSE estimators (Lopez-Vizcaino,E et al., 2014) . + date_publication: '2019-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mme + url_git: '' +mmeln: + version: '1.5' + title: Estimation of Multinormal Mixture Distribution + maintainer: Charles-Edouard Giguere + description: |- + Fit multivariate mixture of normal distribution using + covariance structure. + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmeln + url_git: '' +MMeM: + version: 0.1.1 + title: Multivariate Mixed Effects Model + maintainer: Luyao Peng + description: |- + Analyzing data under multivariate mixed effects model using multivariate REML and multivariate Henderson3 methods. + See Meyer (1985) and Wesolowska Janczarek (1984) . + date_publication: '2021-09-08' + bug_reports: https://github.com/pengluyaoyao/MMeM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MMeM + url_git: '' +mmeta: + version: 3.0.1 + title: Multivariate Meta-Analysis + maintainer: Jiajie Chen + description: Multiple 2 by 2 tables often arise in meta-analysis which combines + statistical evidence from multiple studies. Two risks within the same study are + possibly correlated because they share some common factors such as environment + and population structure. This package implements a set of novel Bayesian approaches + for multivariate meta analysis when the risks within the same study are independent + or correlated. The exact posterior inference of odds ratio, relative risk, and + risk difference given either a single 2 by 2 table or multiple 2 by 2 tables is + provided. Luo, Chen, Su, Chu, (2014) , Chen, Luo, (2011) + , Chen, Chu, Luo, Nie, Chen, (2015) , + Chen, Luo, Chu, Su, Nie, (2014) , Chen, Luo, + Chu, Wei, (2013) . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmeta + url_git: '' +MMGFM: + version: 1.1.0 + title: Multi-Study Multi-Modality Generalized Factor Model + maintainer: Wei Liu + description: We introduce a generalized factor model designed to jointly analyze + high-dimensional multi-modality data from multiple studies by extracting study-shared + and specified factors. Our factor models account for heterogeneous noises and + overdispersion among modality variables with augmented covariates. We propose + an efficient and speedy variational estimation procedure for estimating model + parameters, along with a novel criterion for selecting the optimal number of factors. + More details can be referred to Liu et al. (2024) . + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMGFM + url_git: '' +mmibain: + version: 0.2.0 + title: Bayesian Informative Hypotheses Evaluation Web Applications + maintainer: Mackson Ncube + description: |- + Researchers often have expectations about the relations between means + of different groups or standardized regression coefficients; using informative + hypothesis testing to incorporate these expectations into the analysis through + order constraints increases statistical power + Vanbrabant and Rosseel (2020) . Another valuable + tool, the Bayes factor, can evaluate evidence for multiple hypotheses without + concerns about multiple testing, and can be used in Bayesian updating + Hoijtink, Mulder, van Lissa & Gu (2019) . The 'bain' + R package enables informative hypothesis testing using the Bayes factor. The + 'mmibain' package provides 'shiny' web applications based on 'bain'. The + RepliCrisis() function launches a 'shiny' card game to simulate the evaluation + of replication studies while the mmibain() function launches a 'shiny' + application to fit Bayesian informative hypotheses evaluation models from + 'bain'. + date_publication: '2024-05-23' + bug_reports: https://github.com/mightymetrika/mmibain/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmibain + url_git: https://github.com/mightymetrika/mmibain +mmiCATs: + version: 0.2.0 + title: Cluster Adjusted t Statistic Applications + maintainer: Mackson Ncube + description: |- + Simulation results detailed in Esarey and Menger (2019) + demonstrate that cluster adjusted t statistics (CATs) are an effective method + for correcting standard errors in scenarios with a small number of clusters. + The 'mmiCATs' package offers a suite of tools for working with CATs. The + mmiCATs() function initiates a 'shiny' web application, facilitating + the analysis of data utilizing CATs, as implemented in the cluster.im.glm() + function from the 'clusterSEs' package. Additionally, the pwr_func_lmer() + function is designed to simplify the process of conducting simulations to + compare mixed effects models with CATs models. For educational purposes, the + CloseCATs() function launches a 'shiny' application card game, aimed at enhancing + users' understanding of the conditions under which CATs should be preferred + over random intercept models. + date_publication: '2024-08-26' + bug_reports: https://github.com/mightymetrika/mmiCATs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmiCATs + url_git: https://github.com/mightymetrika/mmiCATs +MMINP: + version: 0.1.0 + title: |- + Microbe-Metabolite Interactions-Based Metabolic Profiles + Predictor + maintainer: Wenli Tang + description: |2- + + Implements a computational framework to predict microbial community-based + metabolic profiles with 'O2PLS' model. It provides procedures of model + training and prediction. Paired microbiome and metabolome data are needed + for modeling, and the trained model can be applied to predict metabolites + of analogous environments using new microbial feature abundances. + date_publication: '2022-07-04' + bug_reports: https://github.com/YuLab-SMU/MMINP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MMINP + url_git: https://github.com/YuLab-SMU/MMINP +mmints: + version: 0.2.0 + title: Workflows for Building Web Applications + maintainer: Mackson Ncube + description: |- + Sharing statistical methods or simulation frameworks through 'shiny' + applications often requires workflows for handling data. To help save and + display simulation results, the postgresUI() and postgresServer() functions + in 'mmints' help with persistent data storage using a 'PostgreSQL' database. + The 'mmints' package also offers data upload functionality through the + csvUploadUI() and csvUploadServer() functions which allow users to upload + data, view variables and their types, and edit variable types before fitting + statistical models within the 'shiny' application. These tools aim to + enhance efficiency and user interaction in 'shiny' based statistical and + simulation applications. + date_publication: '2025-02-12' + bug_reports: https://github.com/mightymetrika/mmints/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmints + url_git: https://github.com/mightymetrika/mmints +mmirestriktor: + version: 0.3.1 + title: Informative Hypothesis Testing Web Applications + maintainer: Mackson Ncube + description: |- + Offering enhanced statistical power compared to traditional + hypothesis testing methods, informative hypothesis testing allows researchers + to explicitly model their expectations regarding the relationships among + parameters. An important software tool for this framework is 'restriktor'. + The 'mmirestriktor' package provides 'shiny' web applications to implement + some of the basic functionality of 'restriktor'. The mmirestriktor() function + launches a 'shiny' application for fitting and analyzing models with + constraints. The FbarCards() function launches a card game application which + can help build intuition about informative hypothesis testing. The + iht_interpreter() helps interpret informative hypothesis testing results based + on guidelines in Vanbrabant and Rosseel (2020) . + date_publication: '2024-07-17' + bug_reports: https://github.com/mightymetrika/mmirestriktor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmirestriktor + url_git: https://github.com/mightymetrika/mmirestriktor +MMLR: + version: 0.2.0 + title: Fitting Markov-Modulated Linear Regression Models + maintainer: Nadezda Spiridovska + description: |- + A set of tools for fitting Markov-modulated linear regression, where responses Y(t) are time-additive, and model operates in the external environment, which is described as a continuous time Markov chain with finite state space. + Model is proposed by Alexander Andronov (2012) and algorithm of parameters estimation is based on eigenvalues and eigenvectors decomposition. + Markov-switching regression models have the same idea of varying the regression parameters randomly in accordance with external environment. The difference is that for Markov-modulated linear regression model the external environment is described as a continuous-time homogeneous irreducible Markov chain with known parameters while switching models consider Markov chain as unobserved and estimation procedure involves estimation of transition matrix. + These models have significant differences in terms of the analytical approach. + Also, package provides a set of data simulation tools for Markov-modulated linear regression (for academical/research purposes). + Research project No. 1.1.1.2/VIAA/1/16/075. + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMLR + url_git: '' +mmmgee: + version: '1.20' + title: |- + Simultaneous Inference for Multiple Linear Contrasts in GEE + Models + maintainer: Robin Ristl + description: |- + Provides global hypothesis tests, multiple testing procedures and simultaneous confidence intervals for multiple linear contrasts of regression + coefficients in a single generalized estimating equation (GEE) model or across multiple GEE models. GEE models are fit by a modified version of the 'geeM' package. + date_publication: '2019-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmmgee + url_git: '' +MMOC: + version: 0.1.1.0 + title: Multi-Omic Spectral Clustering using the Flag Manifold + maintainer: Charlie Carpenter + description: Multi-omic (or any multi-view) spectral clustering methods often assume + the same number of clusters across all datasets. We supply methods for multi-omic + spectral clustering when the number of distinct clusters differs among the omics + profiles (views). + date_publication: '2023-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMOC + url_git: '' +mmod: + version: 1.3.3 + title: Modern Measures of Population Differentiation + maintainer: David Winter + description: |- + Provides functions for measuring + population divergence from genotypic data. + date_publication: '2017-04-06' + bug_reports: https://github.com/dwinter/mmod/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmod + url_git: https://github.com/dwinter/mmod +mmodely: + version: 0.2.5 + title: |- + Modeling Multivariate Origins Determinants - Evolutionary + Lineages in Ecology + maintainer: David M Schruth + description: |2- + + Perform multivariate modeling of evolved traits, with special attention to + understanding the interplay of the multi-factorial determinants of their origins + in complex ecological settings (Stephens, 2007 ). + This software primarily concentrates on phylogenetic regression analysis, enabling + implementation of tree transformation averaging and visualization functionality. + Functions additionally support information theoretic approaches + (Grueber, 2011 ; + Garamszegi, 2011 ) + such as model averaging and selection of phylogenetic models. + Accessory functions are also implemented for coef standardization (Cade 2015), + selection uncertainty, and variable importance (Burnham & Anderson 2000). + There are other numerous functions for visualizing confounded variables, + plotting phylogenetic trees, as well as reporting and exporting modeling results. + Lastly, as challenges to ecology are inherently multifarious, and therefore often + multi-dataset, this package features several functions to support the identification, + interpolation, merging, and updating of missing data and outdated nomenclature. + date_publication: '2023-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmodely + url_git: '' +mMPA: + version: 1.2.0 + title: Implementation of Marker-Assisted Mini-Pooling with Algorithm + maintainer: '"Tao Liu, PhD"' + description: |- + To determine the number of quantitative assays needed for a sample + of data using pooled testing methods, which include mini-pooling (MP), MP + with algorithm (MPA), and marker-assisted MPA (mMPA). To estimate the number + of assays needed, the package also provides a tool to conduct Monte Carlo (MC) + to simulate different orders in which the sample would be collected to form pools. + Using MC avoids the dependence of the estimated number of assays on any specific + ordering of the samples to form pools. + date_publication: '2018-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mMPA + url_git: '' +mmpca: + version: 2.0.3 + title: Integrative Analysis of Several Related Data Matrices + maintainer: Felix Held + description: |- + A generalization of principal component analysis for integrative + analysis. The method finds principal components that describe single matrices + or that are common to several matrices. The solutions are sparse. Rank of + solutions is automatically selected using cross validation. The method is + described in Kallus et al. (2019) . + date_publication: '2022-11-15' + bug_reports: https://github.com/cyianor/mmpca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmpca + url_git: https://github.com/cyianor/mmpca +mmpp: + version: '0.6' + title: |- + Various Similarity and Distance Metrics for Marked Point + Processes + maintainer: Hideitsu Hino + description: Compute similarities and distances between marked point processes. + date_publication: '2017-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmpp + url_git: '' +mmr: + version: 0.1.0 + title: Matrix Multiplication on Data.frames + maintainer: Steve Condylios + description: |- + Simple helpers for matrix multiplication on data.frames. These allow for more + concise code during low level mathematical operations, and help ensure code is more + easily read, understood, and serviced. + date_publication: '2020-08-04' + bug_reports: https://github.com/stevecondylios/mmr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mmr + url_git: https://github.com/stevecondylios/mmr +MMRcaseselection: + version: 0.1.0 + title: Case Classification and Selection Based on Regression Results + maintainer: Ingo Rohlfing + description: |- + Researchers doing a mixed-methods analysis (nested analysis as + developed by Lieberman (2005) ) can + use the package for the classification of cases and case selection using + results of a linear regression. One can designate cases + as typical, deviant, extreme and pathway case and use different case + selection strategies for the choice of a case belonging to one of + these types. + date_publication: '2020-06-03' + bug_reports: https://github.com/ingorohlfing/MMRcaseselection + url: '' + url_cran: https://CRAN.R-project.org/package=MMRcaseselection + url_git: https://github.com/ingorohlfing/MMRcaseselection +mmrm: + version: 0.3.14 + title: Mixed Models for Repeated Measures + maintainer: Daniel Sabanes Bove + description: |- + Mixed models for repeated measures (MMRM) are a popular + choice for analyzing longitudinal continuous outcomes in randomized + clinical trials and beyond; see Cnaan, Laird and Slasor (1997) + + for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso + (2008) for a review. This package + implements MMRM based on the marginal linear model without random + effects using Template Model Builder ('TMB') which enables fast and + robust model fitting. Users can specify a variety of covariance + matrices, weight observations, fit models with restricted or standard + maximum likelihood inference, perform hypothesis testing with + Satterthwaite or Kenward-Roger adjustment, and extract least square + means estimates by using 'emmeans'. + date_publication: '2024-09-27' + bug_reports: https://github.com/openpharma/mmrm/issues + url: https://openpharma.github.io/mmrm/ + url_cran: https://CRAN.R-project.org/package=mmrm + url_git: '' +mmsample: + version: '0.1' + title: Multivariate Matched Sampling + maintainer: Eoin O'Connell + description: Subset a control group to match an intervention group on a set of features + using multivariate matching and propensity score calipers. Based on methods in + Rosenbaum and Rubin (1985). + date_publication: '2018-12-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmsample + url_git: '' +mmstat4: + version: 0.2.1 + title: Access to Teaching Materials from a ZIP File or GitHub + maintainer: Sigbert Klinke + description: |- + Provides access to teaching materials for various statistics courses, including R and Python programs, + Shiny apps, data, and PDF/HTML documents. These materials are stored on the Internet as a ZIP file + (e.g., in a GitHub repository) and can be downloaded and displayed or run locally. The content of the ZIP file + is temporarily or permanently stored. By default, the package uses the GitHub repository + 'sigbertklinke/mmstat4.data.' Additionally, the package includes 'association_measures.R' + from the archived package 'ryouready' by Mark Heckman and some auxiliary functions. + date_publication: '2024-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmstat4 + url_git: '' +mmtsne: + version: 0.1.0 + title: Multiple Maps t-SNE + maintainer: Benjamin J. Radford + description: |- + An implementation of multiple maps t-distributed stochastic + neighbor embedding (t-SNE). Multiple maps t-SNE is a method for + projecting high-dimensional data into several low-dimensional maps such that + non-metric space properties are better preserved than they would be by a single + map. Multiple maps t-SNE with only one map is equivalent to standard t-SNE. + When projecting onto more than one map, multiple maps t-SNE estimates a set + of latent weights that allow each point to contribute to one or more maps + depending on similarity relationships in the original data. This + implementation is a port of the original 'Matlab' library by Laurens van der + Maaten. + See Van der Maaten and Hinton (2012) . + This material is based upon work supported by the United States Air Force + and Defense Advanced Research Project Agency (DARPA) under Contract No. + FA8750-17-C-0020. + Any opinions, findings and conclusions or recommendations expressed in this + material are those of the author(s) and do not necessarily reflect the views + of the United States Air Force and Defense Advanced Research Projects Agency. + Distribution Statement A: Approved for Public Release; Distribution Unlimited. + date_publication: '2017-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mmtsne + url_git: '' +MMVBVS: + version: 0.8.0 + title: Missing Multivariate Bayesian Variable Selection + maintainer: Tae Kim + description: |- + A variable selection tool for multivariate normal variables with missing-at-random values using Bayesian Hierarchical Model. + Visualization functions show the posterior distribution of gamma (inclusion variables) and beta (coefficients). + Users can also visualize the heatmap of the posterior mean of covariance matrix. + Kim, T. Nicolae, D. (2019) . + Guan, Y. Stephens, M. (2011) . + date_publication: '2019-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MMVBVS + url_git: '' +MMWRweek: + version: 0.1.3 + title: Convert Dates to MMWR Day, Week, and Year + maintainer: Jarad Niemi + description: |- + The first day of any MMWR week is Sunday. + MMWR week numbering is sequential beginning with 1 + and incrementing with each week to a maximum of 52 + or 53. MMWR week #1 of an MMWR year is the first week + of the year that has at least four days in the calendar + year. This package provides functionality to convert + Dates to MMWR day, week, and year and the reverse. + date_publication: '2020-04-22' + bug_reports: '' + url: http://wwwn.cdc.gov/nndss/document/MMWR_Week_overview.pdf + url_cran: https://CRAN.R-project.org/package=MMWRweek + url_git: '' +MN: + version: '1.0' + title: Matrix Normal Distribution + maintainer: Michail Tsagris + description: 'Density computation, random matrix generation and maximum likelihood + estimation of the matrix normal distribution. References: Pocuca N., Gallaugher + M. P., Clark K. M. & McNicholas P. D. (2019). Assessing and Visualizing Matrix + Variate Normality. and the relevant wikipedia + page.' + date_publication: '2024-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MN + url_git: '' +MNARclust: + version: 1.1.0 + title: |- + Clustering Data with Non-Ignorable Missingness using + Semi-Parametric Mixture Models + maintainer: Matthieu Marbac + description: Clustering of data under a non-ignorable missingness mechanism. Clustering + is achieved by a semi-parametric mixture model and missingness is managed by using + the pattern-mixture approach. More details of the approach are available in Du + Roy de Chaumaray et al. (2020) . + date_publication: '2021-12-02' + bug_reports: '' + url: https://arxiv.org/abs/2009.07662 + url_cran: https://CRAN.R-project.org/package=MNARclust + url_git: '' +MNB: + version: 1.1.0 + title: Diagnostic Tools for a Multivariate Negative Binomial Model + maintainer: Jalmar Carrasco + description: |- + Diagnostic tools as residual analysis, global, + local and total-local influence for the multivariate model + from the random intercept Poisson generalized log gamma model + are available in this package. Including also, the estimation + process by maximum likelihood method, for details see + Fabio, L. F; Villegas, C. L.; Carrasco, J.M.F and de Castro, M. (2021) + . + date_publication: '2022-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MNB + url_git: '' +mnda: + version: 1.0.9 + title: Multiplex Network Differential Analysis (MNDA) + maintainer: Behnam Yousefi + description: |- + Interactions between different biological entities are crucial for the function of biological systems. + In such networks, nodes represent biological elements, such as genes, proteins and microbes, and their interactions can be defined by edges, which can be either binary or weighted. + The dysregulation of these networks can be associated with different clinical conditions such as diseases and response to treatments. + However, such variations often occur locally and do not concern the whole network. + To capture local variations of such networks, we propose multiplex network differential analysis (MNDA). + MNDA allows to quantify the variations in the local neighborhood of each node (e.g. gene) between the two given clinical states, and to test for statistical significance of such variation. + Yousefi et al. (2023) . + date_publication: '2023-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mnda + url_git: '' +mnet: + version: 0.1.4 + title: |- + Modeling Group Differences and Moderation Effects in Statistical + Network Models + maintainer: Jonas Haslbeck + description: A toolbox for modeling manifest and latent group differences and moderation + effects in various statistical network models. + date_publication: '2025-02-13' + bug_reports: https://github.com/jmbh/mnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mnet + url_git: '' +mnis: + version: 0.3.1 + title: |- + Easy Downloading Capabilities for the Members' Name Information + Service + maintainer: Evan Odell + description: |- + An API package for the Members' Name Information Service operated + by the UK parliament. Documentation for the API itself can be found + here: . + date_publication: '2021-04-03' + bug_reports: https://github.com/EvanOdell/mnis/issues + url: https://docs.evanodell.com/mnis + url_cran: https://CRAN.R-project.org/package=mnis + url_git: '' +mniw: + version: 1.0.2 + title: The Matrix-Normal Inverse-Wishart Distribution + maintainer: Martin Lysy + description: Density evaluation and random number generation for the Matrix-Normal + Inverse-Wishart (MNIW) distribution, as well as the the Matrix-Normal, Matrix-T, + Wishart, and Inverse-Wishart distributions. Core calculations are implemented + in a portable (header-only) C++ library, with matrix manipulations using the 'Eigen' + library for linear algebra. Also provided is a Gibbs sampler for Bayesian inference + on a random-effects model with multivariate normal observations. + date_publication: '2024-09-22' + bug_reports: https://github.com/mlysy/mniw/issues + url: https://mlysy.github.io/mniw/ + url_cran: https://CRAN.R-project.org/package=mniw + url_git: https://github.com/mlysy/mniw/ +mnlfa: + version: 0.3-4 + title: Moderated Nonlinear Factor Analysis + maintainer: Alexander Robitzsch + description: |2- + + Conducts moderated nonlinear factor analysis (e.g., Curran et al., 2014, + ). + Regularization methods are implemented for assessing non-invariant items. + Currently, the package includes dichotomous items and unidimensional + item response models. Extensions will be included in future package + versions. + date_publication: '2024-02-11' + bug_reports: '' + url: https://sites.google.com/view/alexander-robitzsch/software + url_cran: https://CRAN.R-project.org/package=mnlfa + url_git: https://github.com/alexanderrobitzsch/mnlfa +MNLpred: + version: 0.0.8 + title: Simulated Predicted Probabilities for Multinomial Logit Models + maintainer: Manuel Neumann + description: |- + Functions to easily return simulated predicted probabilities and + first differences for multinomial logit models. It takes a specified + scenario and a multinomial model to predict probabilities with a set of + coefficients, drawn from a simulated sampling distribution. The simulated + predictions allow for meaningful plots with means and confidence intervals. + The methodological approach is based on the principles laid out by King, + Tomz, and Wittenberg (2000) and Hanmer and Ozan Kalkan + (2016) . + date_publication: '2021-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MNLpred + url_git: '' +MNLR: + version: 0.1.0 + title: |- + Interactive Shiny Presentation for Working with Multinomial + Logistic Regression + maintainer: Kartikeya Bolar + description: An interactive presentation on the topic of Multinomial Logistic Regression. + It is helpful to those who want to learn Multinomial Logistic Regression quickly + and get a hands on experience. The presentation has a template for solving problems + on Multinomial Logistic Regression. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MNLR + url_git: '' +MNM: + version: 1.0-4 + title: |- + Multivariate Nonparametric Methods. An Approach Based on Spatial + Signs and Ranks + maintainer: Klaus Nordhausen + description: Multivariate tests, estimates and methods based on the identity score, + spatial sign score and spatial rank score are provided. The methods include one + and c-sample problems, shape estimation and testing, linear regression and principal + components. The methodology is described in Oja (2010) + and Nordhausen and Oja (2011) . + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MNM + url_git: '' +mnonr: + version: 1.0.0 + title: A Generator of Multivariate Non-Normal Random Numbers + maintainer: Wen Qu + description: 'A data generator of multivariate non-normal data in R. It combines + two different methods to generate non-normal data, one with user-specified multivariate + skewness and kurtosis (more details can be found in the paper: Qu, Liu, & Zhang, + 2019 ), and the other with the given marginal + skewness and kurtosis. The latter one is the widely-used Vale and Maurelli''s + method. It also contains a function to calculate univariate and multivariate (Mardia''s + Test) skew and kurtosis.' + date_publication: '2020-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mnonr + url_git: '' +mnorm: + version: 1.2.2 + title: Multivariate Normal Distribution + maintainer: Bogdan Potanin + description: Calculates and differentiates probabilities and density of (conditional) + multivariate normal distribution and Gaussian copula (with various marginal distributions) + using methods described in A. Genz (2004) , + A. Genz, F. Bretz (2009) , H. I. Gassmann (2003) + and E. Kossova, B. Potanin (2018) . + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mnorm + url_git: '' +mnormt: + version: 2.1.1 + title: |- + The Multivariate Normal and t Distributions, and Their Truncated + Versions + maintainer: Adelchi Azzalini + description: |- + Functions are provided for computing the density and the + distribution function of d-dimensional normal and "t" random variables, + possibly truncated (on one side or two sides), and for generating random + vectors sampled from these distributions, except sampling from the truncated + "t". Moments of arbitrary order of a multivariate truncated normal are + computed, and converted to cumulants up to order 4. + Probabilities are computed via non-Monte Carlo methods; different routines + are used in the case d=1, d=2, d=3, d>3, if d denotes the dimensionality. + date_publication: '2022-09-26' + bug_reports: '' + url: http://azzalini.stat.unipd.it/SW/Pkg-mnormt/ + url_cran: https://CRAN.R-project.org/package=mnormt + url_git: '' +MNormTest: + version: 1.1.1 + title: Multivariate Normal Hypothesis Testing + maintainer: Xifeng Zhang + description: Hypothesis testing of the parameters of multivariate normal distributions, + including the testing of a single mean vector, two mean vectors, multiple mean + vectors, a single covariance matrix, multiple covariance matrices, a mean and + a covariance matrix simultaneously, and the testing of independence of multivariate + normal random vectors. Huixuan, Gao (2005, ISBN:9787301078587), "Applied Multivariate + Statistical Analysis". + date_publication: '2024-10-23' + bug_reports: https://github.com/Astringency/MNormTest/issues + url: https://astringency.github.io/MNormTest/ + url_cran: https://CRAN.R-project.org/package=MNormTest + url_git: https://github.com/Astringency/MNormTest +MNP: + version: 3.1-5 + title: Fitting the Multinomial Probit Model + maintainer: Kosuke Imai + description: |- + Fits the Bayesian multinomial probit model via Markov chain + Monte Carlo. The multinomial probit model is often used to analyze + the discrete choices made by individuals recorded in survey data. + Examples where the multinomial probit model may be useful include the + analysis of product choice by consumers in market research and the + analysis of candidate or party choice by voters in electoral studies. + The MNP package can also fit the model with different choice sets for + each individual, and complete or partial individual choice orderings + of the available alternatives from the choice set. The estimation is + based on the efficient marginal data augmentation algorithm that is + developed by Imai and van Dyk (2005). "A Bayesian Analysis of the + Multinomial Probit Model Using the Data Augmentation." Journal of + Econometrics, Vol. 124, No. 2 (February), pp. 311-334. + Detailed examples are given in + Imai and van Dyk (2005). "MNP: R Package for Fitting the Multinomial + Probit Model." Journal of Statistical Software, Vol. 14, No. 3 (May), + pp. 1-32. . + date_publication: '2024-06-20' + bug_reports: https://github.com/kosukeimai/MNP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MNP + url_git: https://github.com/kosukeimai/MNP +mnreadR: + version: 2.1.7 + title: MNREAD Parameters Estimation and Curve Plotting + maintainer: Aurélie Calabrèse + description: |- + Allows to analyze the reading data obtained with the MNREAD Acuity + Chart, a continuous-text reading acuity chart for normal and low vision. + Provides the necessary functions to plot the MNREAD curve and estimate + automatically the four MNREAD parameters: Maximum Reading Speed, + Critical Print Size, Reading Acuity and Reading Accessibility Index. + Parameters can be estimated either with the standard method + or with a nonlinear mixed-effects (NLME) modeling. + See Calabrese et al. 2018 for more details . + date_publication: '2024-01-18' + bug_reports: '' + url: https://legge.psych.umn.edu/mnread-acuity-charts + url_cran: https://CRAN.R-project.org/package=mnreadR + url_git: '' +MNS: + version: '1.0' + title: Mixed Neighbourhood Selection + maintainer: Ricardo Pio Monti + description: An implementation of the mixed neighbourhood selection (MNS) algorithm. + The MNS algorithm can be used to estimate multiple related precision matrices. + In particular, the motivation behind this work was driven by the need to understand + functional connectivity networks across multiple subjects. This package also contains + an implementation of a novel algorithm through which to simulate multiple related + precision matrices which exhibit properties frequently reported in neuroimaging + analysis. + date_publication: '2015-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MNS + url_git: '' +mnt: + version: '1.3' + title: Affine Invariant Tests of Multivariate Normality + maintainer: Bruno Ebner + description: Various affine invariant multivariate normality tests are provided. + It is designed to accompany the survey article Ebner, B. and Henze, N. (2020) + titled "Tests for multivariate normality -- a critical review + with emphasis on weighted L^2-statistics". We implement new and time honoured + L^2-type tests of multivariate normality, such as the Baringhaus-Henze-Epps-Pulley + (BHEP) test, the Henze-Zirkler test, the test of Henze-Jiménes-Gamero, the test + of Henze-Jiménes-Gamero-Meintanis, the test of Henze-Visage, the Dörr-Ebner-Henze + test based on harmonic oscillator and the Dörr-Ebner-Henze test based on a double + estimation in a PDE. Secondly, we include the measures of multivariate skewness + and kurtosis by Mardia, Koziol, Malkovich and Afifi and Móri, Rohatgi and Székely, + as well as the associated tests. Thirdly, we include the tests of multivariate + normality by Cox and Small, the 'energy' test of Székely and Rizzo, the tests + based on spherical harmonics by Manzotti and Quiroz and the test of Pudelko. All + the functions and tests need the data to be a n x d matrix where n is the samplesize + (number of rows) and d is the dimension (number of columns). + date_publication: '2020-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mnt + url_git: '' +mob: + version: 0.4.2 + title: Monotonic Optimal Binning + maintainer: WenSui Liu + description: |- + Generate the monotonic binning and + perform the woe (weight of evidence) transformation for the logistic regression + used in the consumer credit scorecard development. The woe transformation is a piecewise + transformation that is linear to the log odds. For a numeric variable, all of its monotonic + functional transformations will converge to the same woe transformation. + date_publication: '2021-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mob + url_git: https://github.com/statcompute/mob +mobilityIndexR: + version: 0.2.1 + title: Calculates Transition Matrices and Mobility Indices + maintainer: Brett Mullins + description: Measures mobility in a population through transition matrices and mobility + indices. Relative, mixed, and absolute transition matrices are supported. The + Prais-Bibby, Absolute Movement, Origin Specific, and Weighted Group Mobility indices + are supported. Example income and grade data are included. + date_publication: '2021-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mobilityIndexR + url_git: '' +MoBPS: + version: 1.6.64 + title: Modular Breeding Program Simulator + maintainer: Torsten Pook + description: 'Framework for the simulation framework for the simulation of complex + breeding programs and compare their economic and genetic impact. The package is + also used as the background simulator for our a web-based interface . + Associated publication: Pook et al. (2020) .' + date_publication: '2021-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MoBPS + url_git: '' +mobr: + version: 3.0.0 + title: Measurement of Biodiversity + maintainer: Daniel McGlinn + description: |- + Functions for calculating metrics for the measurement biodiversity + and its changes across scales, treatments, and gradients. The methods + implemented in this package are described in: + Chase, J.M., et al. (2018) , + McGlinn, D.J., et al. (2019) , + McGlinn, D.J., et al. (2020) , and + McGlinn, D.J., et al. (2023) . + date_publication: '2024-08-17' + bug_reports: https://github.com/MoBiodiv/mobr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mobr + url_git: https://github.com/MoBiodiv/mobr +mobsim: + version: 0.3.2 + title: |- + Spatial Simulation and Scale-Dependent Analysis of Biodiversity + Changes + maintainer: Felix May + description: |- + Simulation, analysis and sampling of spatial + biodiversity data (May, Gerstner, McGlinn, Xiao & Chase 2017) + . + In the simulation tools user define the numbers of + species and individuals, the species abundance distribution and species + aggregation. Functions for analysis include species rarefaction + and accumulation curves, species-area relationships and the distance + decay of similarity. + date_publication: '2024-12-05' + bug_reports: https://github.com/MoBiodiv/mobsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mobsim + url_git: https://github.com/MoBiodiv/mobsim +moc.gapbk: + version: 0.1.3 + title: |- + Multi-Objective Clustering Algorithm Guided by a-Priori + Biological Knowledge + maintainer: Jorge Parraga-Alava + description: Implements the Multi-Objective Clustering Algorithm Guided by a-Priori + Biological Knowledge (MOC-GaPBK) which was proposed by Parraga-Alava, J. et. al. + (2018) . + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moc.gapbk + url_git: '' +MOCCA: + version: '1.4' + title: Multi-Objective Optimization for Collecting Cluster Alternatives + maintainer: Hans Kestler + description: Provides methods to analyze cluster alternatives based on multi-objective + optimization of cluster validation indices. For details see Kraus et al. (2011) + . + date_publication: '2020-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOCCA + url_git: '' +MOCHA: + version: 1.1.0 + title: Modeling for Single-Cell Open Chromatin Analysis + maintainer: Imran McGrath + description: |- + A statistical framework and analysis tool for open chromatin + analysis designed specifically for single cell ATAC-seq (Assay for + Transposase-Accessible Chromatin) data, after cell type/cluster + identification. These novel modules remove unwanted technical variation, + identify open chromatin, robustly models repeated measures in single cell + data, implement advanced statistical frameworks to model zero-inflation for + differential and co-accessibility analyses, and integrate with existing + databases and modules for downstream analyses to reveal biological insights. + MOCHA provides a statistical foundation for complex downstream analysis to + help advance the potential of single cell ATAC-seq for applied studies. + Methods for zero-inflated statistics are as described in: + Ghazanfar, S., Lin, Y., Su, X. et al. (2020) . + Pimentel, Ronald Silva, "Kendall's Tau and Spearman's Rho for Zero-Inflated + Data" (2009) . + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOCHA + url_git: '' +mockery: + version: 0.4.4 + title: Mocking Library for R + maintainer: Hadley Wickham + description: |- + The two main functionalities of this package are creating + mock objects (functions) and selectively intercepting calls to a given + function that originate in some other function. It can be used with + any testing framework available for R. Mock objects can be injected + with either this package's own stub() function or a similar + with_mock() facility present in the 'testthat' package. + date_publication: '2023-09-26' + bug_reports: https://github.com/r-lib/mockery/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mockery + url_git: https://github.com/r-lib/mockery +mockr: + version: 0.2.1 + title: Mocking in R + maintainer: Kirill Müller + description: |- + Provides a means to mock a package function, i.e., + temporarily substitute it for testing. Designed as a drop-in + replacement for the now deprecated 'testthat::with_mock()' and + 'testthat::local_mock()'. + date_publication: '2023-02-01' + bug_reports: https://github.com/krlmlr/mockr/issues + url: https://krlmlr.github.io/mockr/ + url_cran: https://CRAN.R-project.org/package=mockr + url_git: https://github.com/krlmlr/mockr +mockthat: + version: 0.2.8 + title: Function Mocking for Unit Testing + maintainer: Nicolas Bennett + description: |- + With the deprecation of mocking capabilities shipped with + 'testthat' as of 'edition 3' it is left to third-party packages to replace + this functionality, which in some test-scenarios is essential in order to + run unit tests in limited environments (such as no Internet connection). + Mocking in this setting means temporarily substituting a function with a + stub that acts in some sense like the original function (for example by + serving a HTTP response that has been cached as a file). The only exported + function 'with_mock()' is modeled after the eponymous 'testthat' function + with the intention of providing a drop-in replacement. + date_publication: '2022-11-01' + bug_reports: https://github.com/nbenn/mockthat/issues + url: https://nbenn.github.io/mockthat/ + url_cran: https://CRAN.R-project.org/package=mockthat + url_git: '' +mod: + version: 0.1.3 + title: Lightweight and Self-Contained Modules for Code Organization + maintainer: Siqi Zhang + description: Creates modules inline or from a file. Modules can contain any R object + and be nested. Each module have their own scope and package "search path" that + does not interfere with one another or the user's working environment. + date_publication: '2019-08-23' + bug_reports: https://github.com/iqis/mod/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mod + url_git: https://github.com/iqis/mod +mod09nrt: + version: '0.14' + title: |- + Extraction of Bands from MODIS Surface Reflectance Product MOD09 + NRT + maintainer: Rishabh Gupta + description: |- + Package for processing downloaded MODIS Surface reflectance + Product HDF files. Specifically, MOD09 surface reflectance product files, and + the associated MOD03 geolocation files (for MODIS-TERRA). The package will be + most effective if the user installs MRTSwath (MODIS Reprojection Tool for swath + products; , and + adds the directory with the MRTSwath executable to the default R PATH by editing + ~/.Rprofile. + date_publication: '2016-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mod09nrt + url_git: '' +mod2rm: + version: 0.2.1 + title: Moderation Analysis for Two-Instance Repeated Measures Designs + maintainer: Matthias Forstmann + description: 'Multiple moderation analysis for two-instance repeated measures designs, + with up to three simultaneous moderators (dichotomous and/or continuous) with + additive or multiplicative relationship. Includes analyses of simple slopes and + conditional effects at (automatically determined or manually set) values of the + moderator(s), as well as an implementation of the Johnson-Neyman procedure for + determining regions of significance in single moderator models. Based on Montoya, + A. K. (2018) "Moderation analysis in two-instance repeated measures designs: Probing + methods and multiple moderator models" .' + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mod2rm + url_git: '' +modACDC: + version: 2.0.1 + title: |- + Association of Covariance for Detecting Differential + Co-Expression + maintainer: Katelyn Queen + description: 'A series of functions to implement association of covariance for detecting + differential co-expression (ACDC), a novel approach for detection of differential + co-expression that simultaneously accommodates multiple phenotypes or exposures + with binary, ordinal, or continuous data types. Users can use the default method + which identifies modules by Partition or may supply their own modules. Also included + are functions to choose an information loss criterion (ILC) for Partition using + OmicS-data-based Complex trait Analysis (OSCA) and Genome-wide Complex trait Analysis + (GCTA). The manuscript describing these methods is as follows: Queen K, Nguyen + MN, Gilliland F, Chun S, Raby BA, Millstein J. "ACDC: a general approach for detecting + phenotype or exposure associated co-expression" (2023) .' + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modACDC + url_git: https://github.com/USCbiostats/ACDC +Modalclust: + version: '0.7' + title: Hierarchical Modal Clustering + maintainer: Surajit Ray + description: Performs Modal Clustering (MAC) including Hierarchical Modal Clustering + (HMAC) along with their parallel implementation (PHMAC) over several processors. These + model-based non-parametric clustering techniques can extract clusters in very + high dimensions with arbitrary density shapes. By default clustering is performed + over several resolutions and the results are summarised as a hierarchical tree. + Associated plot functions are also provided. There is a package vignette that + provides many examples. This version adheres to CRAN policy of not spanning more + than two child processes by default. + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Modalclust + url_git: '' +modeest: + version: 2.4.0 + title: Mode Estimation + maintainer: Paul Poncet + description: |- + Provides estimators of the mode of univariate + data or univariate distributions. + date_publication: '2019-11-18' + bug_reports: https://github.com/paulponcet/modeest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modeest + url_git: https://github.com/paulponcet/modeest +modehunt: + version: 1.0.7 + title: Multiscale Analysis for Density Functions + maintainer: Kaspar Rufibach + description: |- + Given independent and identically distributed observations X(1), ..., X(n) from a density f, + provides five methods to perform a multiscale analysis about f as well as the necessary critical + values. The first method, introduced in Duembgen and Walther (2008), provides simultaneous confidence statements + for the existence and location of local increases (or decreases) of f, based on all intervals I(all) spanned by + any two observations X(j), X(k). The second method approximates the latter approach by using only a subset of + I(all) and is therefore computationally much more efficient, but asymptotically equivalent. Omitting the additive + correction term Gamma in either method offers another two approaches which are more powerful on small scales and + less powerful on large scales, however, not asymptotically minimax optimal anymore. Finally, the block procedure is a + compromise between adding Gamma or not, having intermediate power properties. The latter is again asymptotically + equivalent to the first and was introduced in Rufibach and Walther (2010). + date_publication: '2015-07-03' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=modehunt + url_git: '' +model4you: + version: 0.9-8 + title: |- + Stratified and Personalised Models Based on Model-Based Trees + and Forests + maintainer: Heidi Seibold + description: |- + Model-based trees for subgroup analyses in clinical trials and + model-based forests for the estimation and prediction of personalised + treatment effects (personalised models). Currently partitioning of linear + models, lm(), generalised linear models, glm(), and Weibull models, + survreg(), is supported. Advanced plotting functionality is supported for + the trees and a test for parameter heterogeneity is provided for the + personalised models. For details on model-based trees for subgroup analyses + see Seibold, Zeileis and Hothorn (2016) ; for + details on model-based forests for estimation of individual treatment effects + see Seibold, Zeileis and Hothorn (2017) . + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=model4you + url_git: '' +modelbased: + version: 0.9.0 + title: Estimation of Model-Based Predictions, Contrasts and Means + maintainer: Dominique Makowski + description: |- + Implements a general interface for model-based estimations + for a wide variety of models, used in the computation of + marginal means, contrast analysis and predictions. For a list of supported models, + see 'insight::supported_models()'. + date_publication: '2025-02-05' + bug_reports: https://github.com/easystats/modelbased/issues + url: https://easystats.github.io/modelbased/ + url_cran: https://CRAN.R-project.org/package=modelbased + url_git: '' +modelbpp: + version: 0.1.5 + title: Model BIC Posterior Probability + maintainer: Shu Fai Cheung + description: |- + Fits the neighboring models of a fitted + structural equation model and assesses the model + uncertainty of the fitted model based on BIC posterior + probabilities, using the method presented in + Wu, Cheung, and Leung (2020) + . + date_publication: '2024-09-16' + bug_reports: https://github.com/sfcheung/modelbpp/issues + url: https://sfcheung.github.io/modelbpp/ + url_cran: https://CRAN.R-project.org/package=modelbpp + url_git: '' +modelc: + version: 1.0.0.0 + title: A Linear Model to 'SQL' Compiler + maintainer: Hugo Saavedra + description: This is a cross-platform linear model to 'SQL' compiler. It generates + 'SQL' from linear and generalized linear models. Its interface consists of a single + function, modelc(), which takes the output of lm() or glm() functions (or any + object which has the same signature) and outputs a 'SQL' character vector representing + the predictions on the scale of the response variable as described in Dunn & Smith + (2018) and originating in Nelder & Wedderburn + (1972) . The resultant 'SQL' can be included in a 'SELECT' + statement and returns output similar to that of the glm.predict() or lm.predict() + predictions, assuming numeric types are represented in the database using sufficient + precision. Currently log and identity link functions are supported. + date_publication: '2020-06-28' + bug_reports: https://github.com/sparkfish/modelc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modelc + url_git: https://github.com/sparkfish/modelc +Modelcharts: + version: 0.1.0 + title: Classification Model Charts + maintainer: Krishna Harsha K H + description: Provides two important functions for producing Gain chart and Lift + chart for any classification model. + date_publication: '2018-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Modelcharts + url_git: '' +modeldata: + version: 1.4.0 + title: Data Sets Useful for Modeling Examples + maintainer: Max Kuhn + description: |- + Data sets used for demonstrating or testing model-related + packages are contained in this package. + date_publication: '2024-06-19' + bug_reports: https://github.com/tidymodels/modeldata/issues + url: https://modeldata.tidymodels.org + url_cran: https://CRAN.R-project.org/package=modeldata + url_git: https://github.com/tidymodels/modeldata +modeldatatoo: + version: 0.3.0 + title: More Data Sets Useful for Modeling Examples + maintainer: Emil Hvitfeldt + description: |- + More data sets used for demonstrating or testing model-related + packages are contained in this package. The data sets are downloaded and + cached, allowing for more and bigger data sets. + date_publication: '2024-03-29' + bug_reports: https://github.com/tidymodels/modeldatatoo/issues + url: https://modeldatatoo.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=modeldatatoo + url_git: https://github.com/tidymodels/modeldatatoo +modeldb: + version: 0.3.0 + title: Fits Models Inside the Database + maintainer: Max Kuhn + description: |- + Uses 'dplyr' and 'tidyeval' to fit statistical models inside + the database. It currently supports KMeans and linear regression + models. + date_publication: '2023-11-01' + bug_reports: https://github.com/tidymodels/modeldb/issues + url: https://modeldb.tidymodels.org + url_cran: https://CRAN.R-project.org/package=modeldb + url_git: https://github.com/tidymodels/modeldb +modelDown: + version: '1.1' + title: Make Static HTML Website for Predictive Models + maintainer: Kamil Romaszko + description: |- + Website generator with HTML summaries for predictive models. + This package uses 'DALEX' explainers to describe global model behavior. + We can see how well models behave (tabs: Model Performance, Auditor), + how much each variable contributes to predictions (tabs: Variable Response) + and which variables are the most important for a given model (tabs: Variable Importance). + We can also compare Concept Drift for pairs of models (tabs: Drifter). + Additionally, data available on the website can be easily recreated in current R session. + Work on this package was financially supported by the NCN Opus grant 2017/27/B/ST6/01307 + at Warsaw University of Technology, Faculty of Mathematics and Information Science. + date_publication: '2020-04-15' + bug_reports: https://github.com/ModelOriented/modelDown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modelDown + url_git: https://github.com/ModelOriented/modelDown +modelenv: + version: 0.2.0 + title: Provide Tools to Register Models for Use in 'tidymodels' + maintainer: Emil Hvitfeldt + description: |- + An developer focused, low dependency package in 'tidymodels' that + provides functions to register how models are to be used. Functions to + register models are complimented with accessor functions to retrieve + registered model information to aid in model fitting and error handling. + date_publication: '2024-10-14' + bug_reports: https://github.com/tidymodels/modelenv/issues + url: http://modelenv.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=modelenv + url_git: https://github.com/tidymodels/modelenv +Modeler: + version: 3.4.7 + title: |- + Classes and Methods for Training and Using Binary Prediction + Models + maintainer: Kevin R. Coombes + description: |- + Defines classes and methods to learn models and use them + to predict binary outcomes. These are generic tools, but we also + include specific examples for many common classifiers. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Modeler + url_git: http://oompa.r-forge.r-project.org/ +modelfactory: + version: 1.0.0 + title: Combine Statistical Models into a Tibble for Comparison + maintainer: Will Tirone + description: |- + Statisticians often want to compare the fit of different models on + the same data set. However, this usually involves a lot of manual code to + fish items out of summary() or plain model objects. 'modelfactory' offers + the capability to pass multiple models in and get out metrics or + coefficients for quick comparison with easy-to-remember syntax. + date_publication: '2024-01-31' + bug_reports: https://github.com/WillTirone/modelfactory/issues + url: https://willtirone.github.io/modelfactory/ + url_cran: https://CRAN.R-project.org/package=modelfactory + url_git: https://github.com/WillTirone/modelfactory +modelfree: + version: '1.2' + title: Model-Free Estimation of a Psychometric Function + maintainer: Kamila Zychaluk + description: Local linear estimation of psychometric functions. Provides functions + for nonparametric estimation of a psychometric function and for estimation of + a derived threshold and slope, and their standard deviations and confidence intervals. + date_publication: '2023-05-20' + bug_reports: '' + url: https://personalpages.manchester.ac.uk/staff/d.h.foster/software-modelfree/latest/home.html + url_cran: https://CRAN.R-project.org/package=modelfree + url_git: '' +modelgrid: + version: 1.2.0 + title: |- + A Framework for Creating, Managing and Training Multiple 'caret' + Models + maintainer: Angel Robles + description: |- + A minimalistic but flexible framework that facilitates the + creation, management and training of multiple 'caret' models. A model grid + consists of two components, (1) a set of settings that is shared by all + models by default, and (2) specifications that apply only to the individual + models. When the model grid is trained, model and training specifications are + first consolidated from the shared and the model specific settings into + complete 'caret' model configurations. These models are then trained with + the 'train()' function from the 'caret' package. + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modelgrid + url_git: https://github.com/smaakage85/modelgrid +modelimpact: + version: 1.0.0 + title: |- + Functions to Assess the Business Impact of Churn Prediction + Models + maintainer: Peer Christensen + description: Calculate the financial impact of using a churn model in terms of cost, + revenue, profit and return on investment. + date_publication: '2021-05-06' + bug_reports: https://github.com/PeerChristensen/modelimpact/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modelimpact + url_git: https://github.com/PeerChristensen/modelimpact +modeLLtest: + version: 1.0.4 + title: Compare Models with Cross-Validated Log-Likelihood + maintainer: Shana Scogin + description: An implementation of the cross-validated difference in means (CVDM) + test by Desmarais and Harden (2014) (see also + Harden and Desmarais, 2011 ) and the cross-validated + median fit (CVMF) test by Desmarais and Harden (2012) . + These tests use leave-one-out cross-validated log-likelihoods to assist in selecting + among model estimations. You can also utilize data from Golder (2010) + and Joshi & Mason (2008) that are included to facilitate + examples from real-world analysis. + date_publication: '2022-05-05' + bug_reports: https://github.com/ShanaScogin/modeLLtest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modeLLtest + url_git: https://github.com/ShanaScogin/modeLLtest +ModelMap: + version: 3.4.0.4 + title: |- + Modeling and Map Production using Random Forest and Related + Stochastic Models + maintainer: Elizabeth Freeman + description: Creates sophisticated models of training data and validates the models + with an independent test set, cross validation, or Out Of Bag (OOB) predictions + on the training data. Create graphs and tables of the model validation results. + Applies these models to GIS .img files of predictors to create detailed prediction + surfaces. Handles large predictor files for map making, by reading in the .img + files in chunks, and output to the .txt file the prediction for each data chunk, + before reading the next chunk of data. + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ModelMap + url_git: '' +ModelMatrixModel: + version: 0.1.0 + title: Create Model Matrix and Save the Transforming Parameters + maintainer: Xinyong Tian + description: |- + The model.matrix() function in R is convenient for transforming training dataset for modeling. + But it does not save any parameter used in transformation, so it is hard to apply the same transformation + to test dataset or new dataset. This package is created to solve the problem. + date_publication: '2021-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ModelMatrixModel + url_git: '' +ModelMetrics: + version: 1.2.2.2 + title: Rapid Calculation of Model Metrics + maintainer: Tyler Hunt + description: Collection of metrics for evaluating models written in C++ using 'Rcpp'. + Popular metrics include area under the curve, log loss, root mean square error, + etc. + date_publication: '2020-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ModelMetrics + url_git: '' +modelObj: + version: '4.2' + title: A Model Object Framework for Regression Analysis + maintainer: Shannon T. Holloway + description: A utility library to facilitate the generalization of statistical methods + built on a regression framework. Package developers can use 'modelObj' methods + to initiate a regression analysis without concern for the details of the regression + model and the method to be used to obtain parameter estimates. The specifics of + the regression step are left to the user to define when calling the function. + The user of a function developed within the 'modelObj' framework creates as input + a 'modelObj' that contains the model and the R methods to be used to obtain parameter + estimates and to obtain predictions. In this way, a user can easily go from linear + to non-linear models within the same package. + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modelObj + url_git: '' +modelr: + version: 0.1.11 + title: Modelling Functions that Work with the Pipe + maintainer: Hadley Wickham + description: |- + Functions for modelling that help you seamlessly integrate + modelling into a pipeline of data manipulation and visualisation. + date_publication: '2023-03-22' + bug_reports: https://github.com/tidyverse/modelr/issues + url: https://modelr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=modelr + url_git: https://github.com/tidyverse/modelr +modelSSE: + version: 0.1-3 + title: |- + Modelling Infectious Disease Superspreading from Contact Tracing + Data + maintainer: Shi Zhao + description: Comprehensive analytical tools are provided to characterize infectious + disease superspreading from contact tracing surveillance data. The underlying + theoretical frameworks of this toolkit include branching process with transmission + heterogeneity (Lloyd-Smith et al. (2005) ), case cluster + size distribution (Nishiura et al. (2012) , Blumberg + et al. (2014) , and Kucharski and Althaus (2015) + ), and decomposition of reproduction + number (Zhao et al. (2022) ). + date_publication: '2023-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modelSSE + url_git: '' +modelStudio: + version: 3.1.2 + title: Interactive Studio for Explanatory Model Analysis + maintainer: Hubert Baniecki + description: |- + Automate the explanatory analysis of machine learning predictive + models. Generate advanced interactive model explanations in the form of + a serverless HTML site with only one line of code. This tool is + model-agnostic, therefore compatible with most of the black-box predictive + models and frameworks. The main function computes various (instance and + model-level) explanations and produces a customisable dashboard, which + consists of multiple panels for plots with their short descriptions. It is + possible to easily save the dashboard and share it with others. modelStudio + facilitates the process of Interactive Explanatory Model Analysis introduced + in Baniecki et al. (2023) . + date_publication: '2023-02-20' + bug_reports: https://github.com/ModelOriented/modelStudio/issues + url: https://modelstudio.drwhy.ai + url_cran: https://CRAN.R-project.org/package=modelStudio + url_git: https://github.com/ModelOriented/modelStudio +modelsummary: + version: 2.3.0 + title: |- + Summary Tables and Plots for Statistical Models and Data: + Beautiful, Customizable, and Publication-Ready + maintainer: Vincent Arel-Bundock + description: |- + Create beautiful and customizable tables to summarize several + statistical models side-by-side. Draw coefficient plots, multi-level + cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and + correlation matrices. This package supports dozens of statistical models, and + it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel, + RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr' + dynamic documents. Details can be found in Arel-Bundock (2022) + . + date_publication: '2025-02-02' + bug_reports: https://github.com/vincentarelbundock/modelsummary/issues/ + url: https://modelsummary.com + url_cran: https://CRAN.R-project.org/package=modelsummary + url_git: '' +modeltests: + version: 0.1.6 + title: Testing Infrastructure for Broom Model Generics + maintainer: Alex Hayes + description: |- + Provides a number of testthat tests that can be + used to verify that tidy(), glance() and augment() methods meet + consistent specifications. This allows methods for the same generic to + be spread across multiple packages, since all of those packages can + make the same guarantees to users about returned objects. + date_publication: '2024-05-03' + bug_reports: https://github.com/alexpghayes/modeltests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modeltests + url_git: https://github.com/alexpghayes/modeltests +modeltime: + version: 1.3.1 + title: The Tidymodels Extension for Time Series Modeling + maintainer: Matt Dancho + description: |- + The time series forecasting framework for use with the 'tidymodels' ecosystem. + Models include ARIMA, Exponential Smoothing, and additional time series models + from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" + (). + Refer to "Prophet: forecasting at scale" + (.). + date_publication: '2024-10-22' + bug_reports: https://github.com/business-science/modeltime/issues + url: https://business-science.github.io/modeltime/ + url_cran: https://CRAN.R-project.org/package=modeltime + url_git: https://github.com/business-science/modeltime +modeltime.ensemble: + version: 1.0.4 + title: Ensemble Algorithms for Time Series Forecasting with Modeltime + maintainer: Matt Dancho + description: |- + A 'modeltime' extension that implements time series ensemble forecasting methods including model averaging, + weighted averaging, and stacking. These techniques are popular methods + to improve forecast accuracy and stability. + date_publication: '2024-07-19' + bug_reports: https://github.com/business-science/modeltime.ensemble/issues + url: https://business-science.github.io/modeltime.ensemble/ + url_cran: https://CRAN.R-project.org/package=modeltime.ensemble + url_git: https://github.com/business-science/modeltime.ensemble +modeltime.resample: + version: 0.2.3 + title: Resampling Tools for Time Series Forecasting + maintainer: Matt Dancho + description: |2- + + A 'modeltime' extension that implements forecast resampling tools + that assess time-based model performance and stability for a single time series, + panel data, and cross-sectional time series analysis. + date_publication: '2023-04-12' + bug_reports: https://github.com/business-science/modeltime.resample/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modeltime.resample + url_git: https://github.com/business-science/modeltime.resample +modeltools: + version: 0.2-23 + title: Tools and Classes for Statistical Models + maintainer: Torsten Hothorn + description: |- + A collection of tools to deal with statistical models. + The functionality is experimental and the user interface is likely to + change in the future. The documentation is rather terse, but packages `coin' + and `party' have some working examples. However, if you find the + implemented ideas interesting we would be very interested in a discussion + of this proposal. Contributions are more than welcome! + date_publication: '2020-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modeltools + url_git: '' +modelwordcloud: + version: '0.1' + title: Model Word Clouds + maintainer: Peter Hurford + description: Makes a word cloud of text, sized by the frequency of the word, and + colored either by user-specified colors or colored by the strength of the coefficient + of that text derived from a regression model. + date_publication: '2017-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modelwordcloud + url_git: '' +moder: + version: 0.2.1 + title: Mode Estimation + maintainer: Lukas Jung + description: |- + Determines single or multiple modes (most frequent values). + Checks if missing values make this impossible, and returns 'NA' + in this case. Dependency-free source code. See Franzese and Iuliano (2019) + . + date_publication: '2023-05-07' + bug_reports: https://github.com/lhdjung/moder/issues + url: https://lhdjung.github.io/moder/ + url_cran: https://CRAN.R-project.org/package=moder + url_git: https://github.com/lhdjung/moder +moderate.mediation: + version: 0.0.10 + title: Causal Moderated Mediation Analysis + maintainer: Xu Qin + description: Causal moderated mediation analysis using the methods proposed by Qin + and Wang (2023) . Causal moderated mediation analysis + is crucial for investigating how, for whom, and where a treatment is effective + by assessing the heterogeneity of mediation mechanism across individuals and contexts. + This package enables researchers to estimate and test the conditional and moderated + mediation effects, assess their sensitivity to unmeasured pre-treatment confounding, + and visualize the results. The package is built based on the quasi-Bayesian Monte + Carlo method, because it has relatively better performance at small sample sizes, + and its running speed is the fastest. The package is applicable to a treatment + of any scale, a binary or continuous mediator, a binary or continuous outcome, + and one or more moderators of any scale. + date_publication: '2024-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moderate.mediation + url_git: '' +moderndive: + version: 0.7.0 + title: Tidyverse-Friendly Introductory Linear Regression + maintainer: Albert Y. Kim + description: 'Datasets and wrapper functions for tidyverse-friendly introductory + linear regression, used in "Statistical Inference via Data Science: A ModernDive + into R and the Tidyverse" available at .' + date_publication: '2024-09-01' + bug_reports: https://github.com/moderndive/moderndive/issues + url: https://moderndive.github.io/moderndive/ + url_cran: https://CRAN.R-project.org/package=moderndive + url_git: https://github.com/moderndive/moderndive/ +modernVA: + version: 0.1.3 + title: |- + An Implementation of Two Modern Education-Based Value-Added + Models + maintainer: Garritt L. Page + description: |- + Provides functions that fit two modern education-based value-added models. + One of these models is the quantile value-added model. This model + permits estimating a school's value-added based on specific quantiles of + the post-test distribution. Estimating value-added based on quantiles + of the post-test distribution provides a more complete picture of an + education institution's contribution to learning for students of all + abilities. See Page, G.L.; San Martín, E.; Orellana, J.; Gonzalez, J. (2017) + for more details. The second model is a temporally + dependent value-added model. This model takes into account the temporal + dependence that may exist in school performance between two cohorts in one + of two ways. The first is by modeling school random effects with a + non-stationary AR(1) process. The second is by modeling school effects + based on previous cohort's post-test performance. In addition to more + efficiently estimating value-added, this model permits making statements + about the persistence of a schools effectiveness. The standard value-added + model is also an option. + date_publication: '2023-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modernVA + url_git: '' +modest: + version: 0.3-1 + title: Model-Based Dose-Escalation Trials + maintainer: Philip Pallmann + description: User-friendly Shiny apps for designing and evaluating phase I cancer + clinical trials, with the aim to estimate the maximum tolerated dose (MTD) of + a novel drug, using a Bayesian decision procedure based on logistic regression. + date_publication: '2017-11-16' + bug_reports: https://github.com/PhilipPallmann/modest/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=modest + url_git: '' +ModEstM: + version: 0.0.1 + title: Mode Estimation, Even in the Multimodal Case + maintainer: Jerome Collet + description: Function ModEstM() is the only one of this package, it estimates the + modes of an empirical univariate distribution. It relies on the stats::density() + function, even for input control. Due to very good performance of the density + estimation, computation time is not an issue. The multiple modes are handled using + dplyr::group_by(). For conditions and rates of convergences, see Eddy (1980) . + date_publication: '2022-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ModEstM + url_git: '' +modesto: + version: 0.1.4 + title: Modeling and Analysis of Stochastic Systems + maintainer: Carlos Alberto Cardozo Delgado + description: |- + Compute important quantities when we consider stochastic systems that are observed continuously. + Such as, Cost model, Limiting distribution, Transition matrix, Transition distribution and Occupancy matrix. + The methods are described, for example, Ross S. (2014), Introduction to Probability Models. Eleven Edition. Academic Press. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modesto + url_git: '' +modEvA: + version: '3.30' + title: Model Evaluation and Analysis + maintainer: A. Marcia Barbosa + description: Analyses species distribution models and evaluates their performance. + It includes functions for variation partitioning, extracting variable importance, + computing several metrics of model discrimination and calibration performance, + optimizing prediction thresholds based on a number of criteria, performing multivariate + environmental similarity surface (MESS) analysis, and displaying various analytical + plots. Initially described in Barbosa et al. (2013) . + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modEvA + url_git: http://modeva.r-forge.r-project.org/ +modgetxl: + version: '0.4' + title: A 'shiny' Module for Reading Excel Sheets + maintainer: Yadu Balehosur + description: This is a shiny module that presents a file picker user interface to + get an Excel file name, and reads the Excel sheets using 'readxl' package and + returns the resulting sheet(s) as a vector and data in dataframe(s). + date_publication: '2020-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modgetxl + url_git: '' +modgo: + version: 1.0.1 + title: Mock Data Generation + maintainer: Georgios Koliopanos + description: Generation of synthetic data from a real dataset using the combination + of rank normal inverse transformation with the calculation of correlation matrix + . Completely artificial data may be generated through + the use of Generalized Lambda Distribution and Generalized Poisson Distribution + . Quantitative, binary, ordinal categorical, and survival + data may be simulated. Functionalities are offered to generate synthetic data + sets according to user's needs. + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modgo + url_git: '' +modi: + version: 0.1.2 + title: |- + Multivariate Outlier Detection and Imputation for Incomplete + Survey Data + maintainer: Beat Hulliger + description: |- + Algorithms for multivariate outlier detection when missing values + occur. Algorithms are based on Mahalanobis distance or data depth. + Imputation is based on the multivariate normal model or uses nearest + neighbour donors. The algorithms take sample designs, in particular + weighting, into account. The methods are described in Bill and Hulliger + (2016) . + date_publication: '2023-03-14' + bug_reports: https://github.com/martinSter/modi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modi + url_git: https://github.com/martinSter/modi +modifiedmk: + version: '1.6' + title: Modified Versions of Mann Kendall and Spearman's Rho Trend Tests + maintainer: Sandeep Kumar Patakamuri + description: |- + Power of non-parametric Mann-Kendall test and Spearman’s Rho test is highly influenced by serially correlated data. To address this issue, trend tests may be applied on the modified versions of the time series data by Block Bootstrapping (BBS), Prewhitening (PW) , Trend Free Prewhitening (TFPW), Bias Corrected Prewhitening and Variance Correction Approach by calculating effective sample size. + Mann, H. B. (1945).. + Kendall, M. (1975). Multivariate analysis. Charles Griffin&Company Ltd,. + sen, P. K. (1968).. + Önöz, B., & Bayazit, M. (2012) . + Hamed, K. H. (2009).. + Yue, S., & Wang, C. Y. (2002) . + Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002) . + Hamed, K. H., & Ramachandra Rao, A. (1998) . + Yue, S., & Wang, C. Y. (2004) . + date_publication: '2021-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modifiedmk + url_git: '' +modisfast: + version: 1.0.0 + title: Fast and Efficient Access to MODIS Earth Observation Data + maintainer: Paul Taconet + description: 'Programmatic interface to several NASA Earth Observation ''OPeNDAP'' + servers (Open-source Project for a Network Data Access Protocol) (). + Allows for easy downloads of MODIS subsets, as well as other Earth Observation + datacubes, in a time-saving and efficient way : by sampling it at the very downloading + phase (spatially, temporally and dimensionally).' + date_publication: '2024-11-12' + bug_reports: https://github.com/ptaconet/modisfast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modisfast + url_git: https://github.com/ptaconet/modisfast +MODISTools: + version: 1.1.5 + title: Interface to the 'MODIS Land Products Subsets' Web Services + maintainer: Koen Hufkens + description: |- + Programmatic interface to the Oak Ridge National Laboratories + 'MODIS Land Products Subsets' web services + (). Allows for easy + downloads of 'MODIS' time series directly to your R workspace or + your computer. + date_publication: '2023-09-17' + bug_reports: https://github.com/bluegreen-labs/MODISTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MODISTools + url_git: https://github.com/bluegreen-labs/MODISTools +modmarg: + version: 0.9.6 + title: Calculating Marginal Effects and Levels with Errors + maintainer: Annie Wang + description: |- + Calculate predicted levels and marginal effects, + using the delta method to calculate standard errors. This is an R-based + version of the 'margins' command from Stata. + date_publication: '2020-11-22' + bug_reports: https://github.com/anniejw6/modmarg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modmarg + url_git: https://github.com/anniejw6/modmarg +modMax: + version: '1.1' + title: Community Structure Detection via Modularity Maximization + maintainer: Maria Schelling + description: |- + The algorithms implemented here are used to detect the community structure of a network. + These algorithms follow different approaches, but are all based on the concept of modularity maximization. + date_publication: '2015-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modMax + url_git: '' +modnets: + version: 0.9.0 + title: Modeling Moderated Networks + maintainer: Trevor Swanson + description: Methods for modeling moderator variables in cross-sectional, temporal, + and multi-level networks. Includes model selection techniques and a variety of + plotting functions. Implements the methods described by Swanson (2020) . + date_publication: '2021-10-01' + bug_reports: https://github.com/tswanson222/modnets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modnets + url_git: https://github.com/tswanson222/modnets +modopt.matlab: + version: 1.0-2 + title: '''MatLab''-Style Modeling of Optimization Problems' + maintainer: Ronald Hochreiter + description: '''MatLab''-Style Modeling of Optimization Problems with ''R''. This + package provides a set of convenience functions to transform a ''MatLab''-style + optimization modeling structure to its ''ROI'' equivalent.' + date_publication: '2018-08-18' + bug_reports: '' + url: http://www.finance-r.com/ + url_cran: https://CRAN.R-project.org/package=modopt.matlab + url_git: '' +modQR: + version: 0.1.3 + title: Multiple-Output Directional Quantile Regression + maintainer: Pavel Boček + description: |- + Contains basic tools for performing + multiple-output quantile regression and computing + regression quantile contours by means of directional + regression quantiles. In the location case, one can thus + obtain halfspace depth contours in two to six dimensions. + Hallin, M., Paindaveine, D. and Šiman, M. (2010) + Multivariate quantiles and multiple-output regression quantiles: + from L1 optimization to halfspace depth. Annals of Statistics 38, 635-669 + For more references about the method, see Help pages. + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modQR + url_git: '' +modsem: + version: 1.0.6 + title: |- + Latent Interaction (and Moderation) Analysis in Structural + Equation Models (SEM) + maintainer: Kjell Solem Slupphaug + description: |- + Estimation of interaction (i.e., moderation) effects between latent variables + in structural equation models (SEM). + The supported methods are: + The constrained approach (Algina & Moulder, 2001). + The unconstrained approach (Marsh et al., 2004). + The residual centering approach (Little et al., 2006). + The double centering approach (Lin et al., 2010). + The latent moderated structural equations (LMS) approach (Klein & Moosbrugger, 2000). + The quasi-maximum likelihood (QML) approach (Klein & Muthén, 2007) (temporarily unavailable) + The constrained- unconstrained, residual- and double centering- approaches + are estimated via 'lavaan' (Rosseel, 2012), whilst the LMS- and QML- approaches + are estimated via 'modsem' it self. Alternatively model can be + estimated via 'Mplus' (Muthén & Muthén, 1998-2017). + References: + Algina, J., & Moulder, B. C. (2001). + . + "A note on estimating the Jöreskog-Yang model for latent variable interaction using 'LISREL' 8.3." + Klein, A., & Moosbrugger, H. (2000). + . + "Maximum likelihood estimation of latent interaction effects with the LMS method." + Klein, A. G., & Muthén, B. O. (2007). + . + "Quasi-maximum likelihood estimation of structural equation models with multiple interaction and quadratic effects." + Lin, G. C., Wen, Z., Marsh, H. W., & Lin, H. S. (2010). + . + "Structural equation models of latent interactions: Clarification of orthogonalizing and double-mean-centering strategies." + Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). + . + "On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables." + Marsh, H. W., Wen, Z., & Hau, K. T. (2004). + . + "Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction." + Muthén, L.K. and Muthén, B.O. (1998-2017). + "'Mplus' User’s Guide. Eighth Edition." + . + Rosseel Y (2012). + . + "'lavaan': An R Package for Structural Equation Modeling." + date_publication: '2025-01-20' + bug_reports: '' + url: https://modsem.org + url_cran: https://CRAN.R-project.org/package=modsem + url_git: '' +ModStatR: + version: 1.3.3 + title: Statistical Modelling in Action with R + maintainer: Frederic Bertrand + description: 'Datasets and functions for the book "Modélisation statistique par + la pratique avec R", F. Bertrand, E. Claeys and M. Maumy-Bertrand (2019, ISBN:9782100793525, + Dunod, Paris). The first chapter of the book is dedicated to an introduction to + the R statistical software. The second chapter deals with correlation analysis: + Pearson, Spearman and Kendall simple, multiple and partial correlation coefficients. + New wrapper functions for permutation tests or bootstrap of matrices of correlation + are provided with the package. The third chapter is dedicated to data exploration + with factorial analyses (PCA, CA, MCA, MDA) and clustering. The fourth chapter + is dedicated to regression analysis: fitting and model diagnostics are detailed. + The exercises focus on covariance analysis, logistic regression, Poisson regression, + two-way analysis of variance for fixed or random factors. Various example datasets + are shipped with the package: for instance on pokemon, world of warcraft, house + tasks or food nutrition analyses.' + date_publication: '2023-03-24' + bug_reports: https://github.com/fbertran/ModStatR/issues/ + url: https://fbertran.github.io/homepage/ + url_cran: https://CRAN.R-project.org/package=ModStatR + url_git: https://github.com/fbertran/ModStatR/ +ModTools: + version: 0.9.13 + title: Building Regression and Classification Models + maintainer: Andri Signorell + description: Consistent user interface to the most common regression and classification + algorithms, such as random forest, neural networks, C5 trees and support vector + machines, complemented with a handful of auxiliary functions, such as variable + importance and a tuning function for the parameters. + date_publication: '2024-09-30' + bug_reports: https://github.com/AndriSignorell/ModTools/issues + url: https://andrisignorell.github.io/ModTools/ + url_cran: https://CRAN.R-project.org/package=ModTools + url_git: https://github.com/AndriSignorell/ModTools/ +modTurPoint: + version: 0.1.0 + title: Estimate ED50 Based on Modified Turning Point Method + maintainer: Yongbo Gan + description: |- + Turning point method is a method proposed by Choi (1990) to + estimate 50 percent effective dose (ED50) in the study of drug sensitivity. The method has + its own advantages for that it can provide robust ED50 estimation. This package contains + the modified function of Choi's turning point method. + date_publication: '2018-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=modTurPoint + url_git: '' +moduleColor: + version: 1.8-4 + title: Basic Module Functions + maintainer: Peter Langfelder + description: Methods for color labeling, calculation of eigengenes, merging of closely + related modules. + date_publication: '2022-04-09' + bug_reports: '' + url: https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/BranchCutting/ + url_cran: https://CRAN.R-project.org/package=moduleColor + url_git: '' +modules: + version: 0.13.0 + title: Self Contained Units of Source Code + maintainer: Sebastian Warnholz + description: |- + Provides modules as an organizational unit for source code. Modules + enforce to be more rigorous when defining dependencies and have + a local search path. They can be used as a sub unit within packages + or in scripts. + date_publication: '2024-01-21' + bug_reports: https://github.com/wahani/modules/issues + url: '' + url_cran: https://CRAN.R-project.org/package=modules + url_git: https://github.com/wahani/modules +MOEADr: + version: 1.1.3 + title: Component-Wise MOEA/D Implementation + maintainer: Felipe Campelo + description: |- + Modular implementation of Multiobjective Evolutionary Algorithms + based on Decomposition (MOEA/D) [Zhang and Li (2007), + ] for quick assembling and + testing of new algorithmic components, as well as easy + replication of published MOEA/D proposals. The full framework is + documented in a paper published in the Journal of Statistical + Software []. + date_publication: '2023-01-08' + bug_reports: https://github.com/fcampelo/MOEADr/issues + url: https://fcampelo.github.io/MOEADr/ + url_cran: https://CRAN.R-project.org/package=MOEADr + url_git: '' +MoEClust: + version: 1.5.2 + title: |- + Gaussian Parsimonious Clustering Models with Covariates and a + Noise Component + maintainer: Keefe Murphy + description: Clustering via parsimonious Gaussian Mixtures of Experts using the + MoEClust models introduced by Murphy and Murphy (2020) . + This package fits finite Gaussian mixture models with a formula interface for + supplying gating and/or expert network covariates using a range of parsimonious + covariance parameterisations from the GPCM family via the EM/CEM algorithm. Visualisation + of the results of such models using generalised pairs plots and the inclusion + of an additional noise component is also facilitated. A greedy forward stepwise + search algorithm is provided for identifying the optimal model in terms of the + number of components, the GPCM covariance parameterisation, and the subsets of + gating/expert network covariates. + date_publication: '2023-12-11' + bug_reports: https://github.com/Keefe-Murphy/MoEClust + url: '' + url_cran: https://CRAN.R-project.org/package=MoEClust + url_git: '' +moexer: + version: 0.3.0 + title: |- + Interact with Moscow Exchange Informational and Statistical + Server ('ISS') + maintainer: Dmitry Zotikov + description: |- + This is a thin wrapper around the 'MOEX' 'ISS' REST interface, see + . It allows to quickly fetch price candles for a + particular security, obtain its profile information and so on. + date_publication: '2024-03-12' + bug_reports: https://github.com/x1o/moexer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=moexer + url_git: https://github.com/x1o/moexer +MOFAT: + version: '1.0' + title: Maximum One-Factor-at-a-Time Designs + maintainer: V. Roshan Joseph + description: Identifying important factors from a large number of potentially important + factors of a highly nonlinear and computationally expensive black box model is + a difficult problem. Xiao, Joseph, and Ray (2022) + proposed Maximum One-Factor-at-a-Time (MOFAT) designs for doing this. A MOFAT + design can be viewed as an improvement to the random one-factor-at-a-time (OFAT) + design proposed by Morris (1991) . The improvement + is achieved by exploiting the connection between Morris screening designs and + Monte Carlo-based Sobol' designs, and optimizing the design using a space-filling + criterion. This work is supported by a U.S. National Science Foundation (NSF) + grant CMMI-1921646 . + date_publication: '2022-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOFAT + url_git: '' +mogavs: + version: 1.1.0 + title: |- + Multiobjective Genetic Algorithm for Variable Selection in + Regression + maintainer: Tommi Pajala + description: Functions for exploring the best subsets in regression with a genetic + algorithm. The package is much faster than methods relying on complete enumeration, + and is suitable for data sets with large number of variables. For more information, + see Sinha, Malo & Kuosmanen (2015) . + date_publication: '2018-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mogavs + url_git: '' +mojson: + version: '0.1' + title: A Serialization-Style Flattening and Description for JSON + maintainer: Bo Wei + description: |- + Support JSON flattening in a long data frame way, where the nesting keys will be stored in the absolute path. It also + provides an easy way to summarize the basic description of a JSON list. The idea of 'mojson' is to transform a JSON object in an + absolute serialization way, which means the early key-value pairs will appear in the heading rows of the resultant data frame. + 'mojson' also provides an alternative way of comparing two different JSON lists, returning the left/inner/right-join style results. + date_publication: '2021-02-11' + bug_reports: https://github.com/chriswweibo/mojson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mojson + url_git: https://github.com/chriswweibo/mojson +mokken: + version: 3.1.2 + title: Conducts Mokken Scale Analysis + maintainer: L. Andries van der Ark + description: |- + Contains functions for performing Mokken + scale analysis on test and questionnaire data. + It includes an automated item selection algorithm, and various checks of model assumptions. + date_publication: '2024-06-18' + bug_reports: '' + url: https://sites.google.com/a/tilburguniversity.edu/avdrark/mokken + url_cran: https://CRAN.R-project.org/package=mokken + url_git: '' +molaR: + version: '5.3' + title: Dental Surface Complexity Measurement Tools + maintainer: James D. Pampush + description: |- + Surface topography calculations of Dirichlet's normal energy, + relief index, surface slope, and orientation patch count for teeth using scans of + enamel caps. + Importantly, for the relief index and orientation patch count calculations to + work, the scanned tooth files must be oriented with the occlusal plane parallel + to the x and y axes, and perpendicular to the z axis. The files should also be + simplified, and smoothed in some other software prior to uploading into R. + date_publication: '2023-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=molaR + url_git: '' +MoLE: + version: 1.0.1 + title: Modeling Language Evolution + maintainer: Sander Lestrade + description: Model for simulating language evolution in terms of cultural evolution + (Smith & Kirby (2008) ; Deacon 1997). The focus is + on the emergence of argument-marking systems (Dowty (1991) , + Van Valin 1999, Dryer 2002, Lestrade 2015a), i.e. noun marking (Aristar (1997) + , Lestrade (2010) ), person indexing + (Ariel 1999, Dahl (2000) , Bhat 2004), and word order + (Dryer 2013), but extensions are foreseen. Agents start out with a protolanguage + (a language without grammar; Bickerton (1981) , + Jackendoff 2002, Arbib (2015) ) and interact through + language games (Steels 1997). Over time, grammatical constructions emerge that + may or may not become obligatory (for which the tolerance principle is assumed; + Yang 2016). Throughout the simulation, uniformitarianism of principles is assumed + (Hopper (1987) , Givon (1995) , + Croft (2000), Saffran (2001) , Heine & Kuteva 2007), + in which maximal psychological validity is aimed at (Grice (1975) , + Levelt 1989, Gaerdenfors 2000) and language representation is usage based (Tomasello + 2003, Bybee 2010). In Lestrade (2015b) , Lestrade + (2015c) , and Lestrade (2016) ), + which reported on the results of preliminary versions, this package was announced + as WDWTW (for who does what to whom), but for reasons of pronunciation and generalization + the title was changed. + date_publication: '2017-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MoLE + url_git: '' +MolgenisArmadillo: + version: 2.9.0 + title: Armadillo Client for the Armadillo Service + maintainer: Mariska Slofstra + description: |- + A set of functions to manage data shared on a + 'MOLGENIS Armadillo' server. + date_publication: '2025-02-28' + bug_reports: https://github.com/molgenis/molgenis-r-armadillo/issues/ + url: https://molgenis.github.io/molgenis-r-armadillo/ + url_cran: https://CRAN.R-project.org/package=MolgenisArmadillo + url_git: https://github.com/molgenis/molgenis-r-armadillo/ +MolgenisAuth: + version: 0.0.25 + title: '''OpenID Connect'' Discovery and Authentication' + maintainer: Mariska Slofstra + description: |- + Discover 'OpenID Connect' endpoints and authenticate + using device flow. Used by 'MOLGENIS' packages. + date_publication: '2023-02-20' + bug_reports: https://github.com/molgenis/molgenis-r-auth/issues/ + url: https://molgenis.github.io/molgenis-r-auth/ + url_cran: https://CRAN.R-project.org/package=MolgenisAuth + url_git: https://github.com/molgenis/molgenis-r-auth/ +MOLHD: + version: '0.2' + title: Multiple Objective Latin Hypercube Design + maintainer: Ruizhe Hou + description: Generate the optimal maximin distance, minimax distance (only for low + dimensions), and maximum projection designs within the class of Latin hypercube + designs efficiently for computer experiments. Generate Pareto front optimal designs + for each two of the three criteria and all the three criteria within the class + of Latin hypercube designs efficiently. Provide criterion computing functions. + References of this package can be found in Morris, M. D. and Mitchell, T. J. (1995) + , Lu Lu and Christine M. Anderson-CookTimothy + J. Robinson (2011) , Joseph, V. R., Gul, E., and + Ba, S. (2015) . + date_publication: '2018-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOLHD + url_git: '' +mombf: + version: 3.5.4 + title: Model Selection with Bayesian Methods and Information Criteria + maintainer: David Rossell + description: Model selection and averaging for regression and mixtures, inclusing + Bayesian model selection and information criteria (BIC, EBIC, AIC, GIC). + date_publication: '2024-02-06' + bug_reports: https://github.com/davidrusi/mombf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mombf + url_git: https://github.com/davidrusi/mombf +momentchi2: + version: 0.1.5 + title: |- + Moment-Matching Methods for Weighted Sums of Chi-Squared Random + Variables + maintainer: Dean Bodenham + description: A collection of moment-matching methods for computing the cumulative + distribution function of a positively-weighted sum of chi-squared random variables. + Methods include the Satterthwaite-Welch method, Hall-Buckley-Eagleson method, + Wood's F method, and the Lindsay-Pilla-Basak method. + date_publication: '2016-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=momentchi2 + url_git: '' +momentfit: + version: '0.5' + title: Methods of Moments + maintainer: Pierre Chausse + description: Several classes for moment-based models are defined. The classes are + defined for moment conditions derived from a single equation or a system of equations. + The conditions can also be expressed as functions or formulas. Several methods + are also offered to facilitate the development of different estimation techniques. + The methods that are currently provided are the Generalized method of moments + (Hansen 1982; ), for single equations and systems of equation, + and the Generalized Empirical Likelihood (Smith 1997; , + Kitamura 1997; , Newey and Smith 2004; , + and Anatolyev 2005 ). + date_publication: '2023-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=momentfit + url_git: '' +moments: + version: 0.14.1 + title: Moments, Cumulants, Skewness, Kurtosis and Related Tests + maintainer: Lukasz Komsta + description: |- + Functions to calculate: moments, Pearson's kurtosis, + Geary's kurtosis and skewness; tests related to them + (Anscombe-Glynn, D'Agostino, Bonett-Seier). + date_publication: '2022-05-02' + bug_reports: '' + url: http://www.komsta.net/ + url_cran: https://CRAN.R-project.org/package=moments + url_git: '' +momentuHMM: + version: 1.5.5 + title: |- + Maximum Likelihood Analysis of Animal Movement Behavior Using + Multivariate Hidden Markov Models + maintainer: Brett McClintock + description: Extended tools for analyzing telemetry data using generalized hidden + Markov models. Features of momentuHMM (pronounced ``momentum'') include data pre-processing + and visualization, fitting HMMs to location and auxiliary biotelemetry or environmental + data, biased and correlated random walk movement models, hierarchical HMMs, multiple + imputation for incorporating location measurement error and missing data, user-specified + design matrices and constraints for covariate modelling of parameters, random + effects, decoding of the state process, visualization of fitted models, model + checking and selection, and simulation. See McClintock and Michelot (2018) . + date_publication: '2022-10-18' + bug_reports: https://github.com/bmcclintock/momentuHMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=momentuHMM + url_git: https://github.com/bmcclintock/momentuHMM +Momocs: + version: 1.4.1 + title: Morphometrics using R + maintainer: Vincent Bonhomme + description: |- + The goal of 'Momocs' is to provide a complete, convenient, + reproducible and open-source toolkit for 2D morphometrics. + It includes most common 2D morphometrics approaches on outlines, open outlines, + configurations of landmarks, traditional morphometrics, and facilities for data preparation, + manipulation and visualization with a consistent grammar throughout. + It allows reproducible, complex morphometrics analyses and other morphometrics approaches + should be easy to plug in, or develop from, on top of this canvas. + date_publication: '2023-11-13' + bug_reports: https://github.com/MomX/Momocs/issues + url: http://momx.github.io/Momocs/ + url_cran: https://CRAN.R-project.org/package=Momocs + url_git: https://github.com/MomX/Momocs/ +MomTrunc: + version: '6.1' + title: |- + Moments of Folded and Doubly Truncated Multivariate + Distributions + maintainer: Christian E. Galarza + description: It computes arbitrary products moments (mean vector and variance-covariance + matrix), for some double truncated (and folded) multivariate distributions. These + distributions belong to the family of selection elliptical distributions, which + includes well known skewed distributions as the unified skew-t distribution (SUT) + and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric + student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), + extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also + included. Density, probabilities and random deviates are also offered for these + members. + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MomTrunc + url_git: '' +monaco: + version: 0.2.2 + title: The 'Monaco' Editor as a HTML Widget + maintainer: Stéphane Laurent + description: A HTML widget rendering the 'Monaco' editor. The 'Monaco' editor is + the code editor which powers 'VS Code'. It is particularly well developed for + 'JavaScript'. In addition to the built-in features of the 'Monaco' editor, the + widget allows to prettify multiple languages, to view the 'HTML' rendering of + 'Markdown' code, and to view and resize 'SVG' images. + date_publication: '2022-05-18' + bug_reports: https://github.com/stla/monaco/issues + url: '' + url_cran: https://CRAN.R-project.org/package=monaco + url_git: https://github.com/stla/monaco +monad: + version: 0.1.1 + title: Operators and Generics for Monads + maintainer: Mikko Marttila + description: |- + Compose generic monadic function pipelines with %>>% and %>-% + based on implementing the 'S7' generics fmap() and bind(). Methods are + provided for the built-in list type and the maybe class from the + 'maybe' package. The concepts are modelled directly after the Monad + typeclass in Haskell, but adapted for idiomatic use in R. + date_publication: '2024-10-28' + bug_reports: https://github.com/mikmart/monad/issues + url: https://mikmart.github.io/monad/ + url_cran: https://CRAN.R-project.org/package=monad + url_git: https://github.com/mikmart/monad +MoNAn: + version: 1.1.0 + title: Mobility Network Analysis + maintainer: Per Block + description: |- + Implements the method to analyse weighted mobility networks or distribution networks as outlined in: + Block, P., Stadtfeld, C., & Robins, G. (2022) . + The purpose of the model is to analyse the structure of mobility, + incorporating exogenous predictors pertaining to individuals and locations + known from classical mobility analyses, as well as modelling emergent mobility + patterns akin to structural patterns known from the statistical analysis of social networks. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MoNAn + url_git: '' +monashtipr: + version: 0.1.0 + title: |- + An R API Wrapper for the Monash University Probabilistic Footy + Tipping Competition + maintainer: James Day + description: |- + An API wrapper for the 'Monash University Probabilistic Footy + Tipping Competition' . + Allows users to submit tips directly to the competition from R. + date_publication: '2022-03-21' + bug_reports: '' + url: https://jimmyday12.github.io/monash_tipr/ + url_cran: https://CRAN.R-project.org/package=monashtipr + url_git: https://github.com/jimmyday12/monash_tipr +mondate: + version: '1.0' + title: Keep Track of Dates in Terms of Months + maintainer: Dan Murphy + description: |- + Keep track of dates in terms of fractional calendar months + per Damien Laker "Time Calculations for Annualizing Returns: the Need for Standardization", + The Journal of Performance Measurement, 2008. + Model dates as of close of business. + Perform date arithmetic in units of "months" and "years". + Allow "infinite" dates to model "ultimate" time. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mondate + url_git: https://github.com/chiefmurph/mondate +Mondrian: + version: 1.1-1 + title: |- + A Simple Graphical Representation of the Relative Occurrence and + Co-Occurrence of Events + maintainer: Aurélie Siberchicot + description: |- + The unique function of this package allows representing in a single graph the relative occurrence and co-occurrence of events measured in a sample. + As examples, the package was applied to describe the occurrence and co-occurrence of different species of bacterial or viral symbionts infecting arthropods at the individual level. The graphics allows determining the prevalence of each symbiont and the patterns of multiple infections (i.e. how different symbionts share or not the same individual hosts). + We named the package after the famous painter as the graphical output recalls Mondrian’s paintings. + date_publication: '2024-01-19' + bug_reports: https://github.com/lbbe-software/Mondrian/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Mondrian + url_git: https://github.com/lbbe-software/Mondrian;https://lbbe-shiny.univ-lyon1.fr/Mondrian/inst/MondrianShiny/ +MonetDB.R: + version: 2.0.0 + title: Connect MonetDB to R + maintainer: Mitchell Weggemans + description: Allows to pull data from MonetDB into R. + date_publication: '2020-08-14' + bug_reports: '' + url: http://www.monetdb.org + url_cran: https://CRAN.R-project.org/package=MonetDB.R + url_git: '' +mongolite: + version: 3.1.0 + title: Fast and Simple 'MongoDB' Client for R + maintainer: Jeroen Ooms + description: |- + High-performance MongoDB client based on 'mongo-c-driver' and 'jsonlite'. + Includes support for aggregation, indexing, map-reduce, streaming, encryption, + enterprise authentication, and GridFS. The online user manual provides an overview + of the available methods in the package: . + date_publication: '2025-02-25' + bug_reports: https://github.com/jeroen/mongolite/issues + url: https://jeroen.r-universe.dev/mongolite + url_cran: https://CRAN.R-project.org/package=mongolite + url_git: '' +mongopipe: + version: 0.1.1 + title: Query MongoDB Documents with R + maintainer: Oliver Haag + description: Translate R code into MongoDB aggregation pipelines. + date_publication: '2021-01-20' + bug_reports: https://gitlab.com/rpkgs/mongopipe/-/issues + url: https://rpkgs.gitlab.io/mongopipe + url_cran: https://CRAN.R-project.org/package=mongopipe + url_git: https://gitlab.com/rpkgs/mongopipe +monitoR: + version: 1.0.7 + title: Acoustic Template Detection in R + maintainer: Sasha D. Hafner + description: Acoustic template detection and monitoring database interface. Create, + modify, save, and use templates for detection of animal vocalizations. View, verify, + and extract results. Upload a MySQL schema to a existing instance, manage survey + metadata, write and read templates and detections locally or to the database. + date_publication: '2018-02-14' + bug_reports: '' + url: http://www.uvm.edu/rsenr/vtcfwru/R/?Page=monitoR/monitoR.htm + url_cran: https://CRAN.R-project.org/package=monitoR + url_git: '' +monitOS: + version: 0.1.5 + title: |- + Monitoring Overall Survival in Pivotal Trials in Indolent + Cancers + maintainer: Thibaud Coroller + description: 'These guidelines are meant to provide a pragmatic, yet rigorous, help + to drug developers and decision makers, since they are shaped by three fundamental + ingredients: the clinically determined margin of detriment on OS that is unacceptably + high (delta null); the benefit on OS that is plausible given the mechanism of + action of the novel intervention (delta alt); and the quantity of information + (i.e. survival events) it is feasible to accrue given the clinical and drug development + setting. The proposed guidelines facilitate transparent discussions between stakeholders + focusing on the risks of erroneous decisions and what might be an acceptable trade-off + between power and the false positive error rate.' + date_publication: '2024-03-21' + bug_reports: '' + url: https://opensource.nibr.com/monitOS/ + url_cran: https://CRAN.R-project.org/package=monitOS + url_git: '' +monmlp: + version: 1.1.5 + title: |- + Multi-Layer Perceptron Neural Network with Optional Monotonicity + Constraints + maintainer: Alex J. Cannon + description: |- + Train and make predictions from a multi-layer perceptron neural + network with optional partial monotonicity constraints. + date_publication: '2017-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monmlp + url_git: '' +monobin: + version: 0.2.4 + title: Monotonic Binning for Credit Rating Models + maintainer: Andrija Djurovic + description: |- + Performs monotonic binning of numeric risk factor in credit rating models (PD, LGD, EAD) + development. All functions handle both binary and continuous target variable. + Functions that use isotonic regression in the first stage of binning process have an additional + feature for correction of minimum percentage of observations and minimum target rate per bin. + Additionally, monotonic trend can be identified based on raw data or, if known in advance, + forced by functions' argument. Missing values and other possible special values are treated + separately from so-called complete cases. + date_publication: '2022-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monobin + url_git: https://github.com/andrija-djurovic/monobin +monobinShiny: + version: 0.1.0 + title: Shiny User Interface for 'monobin' Package + maintainer: Andrija Djurovic + description: |- + This is an add-on package to the 'monobin' package that simplifies its use. It provides shiny-based user interface (UI) + that is especially handy for less experienced 'R' users as well as for those who intend to perform quick scanning + of numeric risk factors when building credit rating models. The additional functions implemented in + 'monobinShiny' that do no exist in 'monobin' package are: descriptive statistics, special case and outliers imputation. + The function descriptive statistics is exported and can be used in 'R' sessions independently from the user interface, + while special case and outlier imputation functions are written to be used with shiny UI. + date_publication: '2021-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monobinShiny + url_git: https://github.com/andrija-djurovic/monobinShiny +monochromeR: + version: 0.2.0 + title: Easily Create, View and Use Monochrome Colour Palettes + maintainer: Cara Thompson + description: |- + Generate a monochrome palette from a starting colour + for a specified number of colours. The package can also be used to display + colour palettes in the plot window, with or without hex codes and colour labels. + date_publication: '2023-09-06' + bug_reports: https://github.com/cararthompson/monochromeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=monochromeR + url_git: https://github.com/cararthompson/monochromeR +monoClust: + version: 1.2.1 + title: Perform Monothetic Clustering with Extensions to Circular Data + maintainer: Tan Tran + description: |- + Implementation of the Monothetic Clustering + algorithm (Chavent, 1998 ) on + continuous data sets. A lot of extensions are included in the package, + including applying Monothetic clustering on data sets with circular + variables, visualizations with the results, and permutation and + cross-validation based tests to support the decision on the number of + clusters. + date_publication: '2021-02-15' + bug_reports: https://github.com/vinhtantran/monoClust/issues + url: https://vinhtantran.github.io/monoClust/ + url_cran: https://CRAN.R-project.org/package=monoClust + url_git: https://github.com/vinhtantran/monoClust +monographaR: + version: 1.3.1 + title: Taxonomic Monographs Tools + maintainer: Marcelo Reginato + description: Contains functions intended to facilitate the production of plant taxonomic + monographs. The package includes functions to convert tables into taxonomic descriptions, + lists of collectors, examined specimens, identification keys (dichotomous and + interactive), and can generate a monograph skeleton. Additionally, wrapper functions + to batch the production of phenology histograms and distributional and diversity + maps are also available. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monographaR + url_git: '' +MonoInc: + version: '1.1' + title: Monotonic Increasing + maintainer: Michele Josey + description: Various imputation methods are utilized in this package, where one + can flag and impute non-monotonic data that is outside of a prespecified range. + date_publication: '2016-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MonoInc + url_git: '' +monolix2rx: + version: 0.0.4 + title: Converts 'Monolix' Models to 'rxode2' + maintainer: Matthew Fidler + description: |- + 'Monolix' is a tool for running mixed effects model using + 'saem'. This tool allows you to convert 'Monolix' models to 'rxode2' + (Wang, Hallow and James (2016) ) using the + form compatible with 'nlmixr2' (Fidler et al (2019) ). + If available, the 'rxode2' model will + read in the 'Monolix' data and compare the simulation for the + population model individual model and residual + model to immediately show how well the translation is + performing. This saves the model development time for people who are + creating an 'rxode2' model manually. Additionally, this package reads + in all the information to allow simulation with uncertainty (that is the + number of observations, the number of subjects, and the covariance + matrix) with a 'rxode2' model. This is complementary to the + 'babelmixr2' package that translates 'nlmixr2' models to 'Monolix' and can + convert the objects converted from 'monolix2rx' to a full 'nlmixr2' fit. While not + required, you can get/install the 'lixoftConnectors' package in the 'Monolix' + installation, as described at the following url . When + 'lixoftConnectors' is available, 'Monolix' can be used to load its model library + instead manually setting up text files (which only works with old versions of + 'Monolix'). + date_publication: '2024-11-28' + bug_reports: '' + url: https://nlmixr2.github.io/monolix2rx/ + url_cran: https://CRAN.R-project.org/package=monolix2rx + url_git: https://github.com/nlmixr2/monolix2rx/ +monomvn: + version: 1.9-21 + title: Estimation for MVN and Student-t Data with Monotone Missingness + maintainer: Robert B. Gramacy + description: |- + Estimation of multivariate normal (MVN) and student-t data of + arbitrary dimension where the pattern of missing data is monotone. + See Pantaleo and Gramacy (2010) . + Through the use of parsimonious/shrinkage regressions + (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, + the package can handle a nearly arbitrary amount of missing data. + The current version supports maximum likelihood inference and + a full Bayesian approach employing scale-mixtures for Gibbs sampling. + Monotone data augmentation extends this Bayesian approach to arbitrary + missingness patterns. A fully functional standalone interface to the + Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), + Horseshoe (from Carvalho, Polson, & Scott), and ridge regression + with model selection via Reversible Jump, and student-t errors + (from Geweke) is also provided. + date_publication: '2024-09-23' + bug_reports: '' + url: https://bobby.gramacy.com/r_packages/monomvn/ + url_cran: https://CRAN.R-project.org/package=monomvn + url_git: '' +MonoPhy: + version: 1.3.2 + title: Explore Monophyly of Taxonomic Groups in a Phylogeny + maintainer: Orlando Schwery + description: |- + Requires rooted phylogeny as input and creates a table of genera, their monophyly-status, which taxa cause problems in monophyly etc. Different information can be extracted from the output and a plot function allows visualization of the results in a number of ways. + "MonoPhy: a simple R package to find and visualize monophyly issues." Schwery, O. & O'Meara, B.C. (2016) . + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MonoPhy + url_git: '' +MonoPoly: + version: 0.3-10 + title: Functions to Fit Monotone Polynomials + maintainer: Berwin A. Turlach + description: |- + Functions for fitting monotone polynomials to data. + Detailed discussion of the methodologies used can be + found in Murray, Mueller and Turlach (2013) + and Murray, Mueller and + Turlach (2016) . + date_publication: '2019-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MonoPoly + url_git: '' +monoreg: + version: '2.1' + title: |- + Bayesian Monotonic Regression Using a Marked Point Process + Construction + maintainer: Olli Saarela + description: An extended version of the nonparametric Bayesian monotonic regression + procedure described in Saarela & Arjas (2011) , + allowing for multiple additive monotonic components in the linear predictor, and + time-to-event outcomes through case-base sampling. The extension and its applications, + including estimation of absolute risks, are described in Saarela & Arjas (2015) + . The package also implements the nonparametric ordinal + regression model described in Saarela, Rohrbeck & Arjas . + date_publication: '2023-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monoreg + url_git: '' +monotone: + version: 0.1.2 + title: Performs Monotone Regression + maintainer: Frank Busing + description: |- + The monotone package contains a fast up-and-down-blocks implementation for the pool-adjacent-violators algorithm + for simple linear ordered monotone regression, including two spin-off functions + for unimodal and bivariate monotone regression (see ). + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monotone + url_git: '' +MonotoneHazardRatio: + version: 0.2.0 + title: |- + Nonparametric Estimation and Inference of a Monotone Hazard + Ratio Function + maintainer: Yujian Wu + description: |- + Nonparametric estimation and inference of a non-decreasing monotone hazard + ratio from a right censored survival dataset. The + estimator is based on a generalized Grenander typed estimator, and the + inference procedure relies on direct plugin estimation of a first order derivative. More + details please refer to the paper "Nonparametric inference under a monotone + hazard ratio order" by Y. Wu and T. Westling (2023) . + date_publication: '2024-10-22' + bug_reports: https://github.com/Yujian-Wu/MonotoneHazardRatio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MonotoneHazardRatio + url_git: https://github.com/Yujian-Wu/MonotoneHazardRatio +monotonicity: + version: 1.3.1 + title: |- + Test for Monotonicity in Expected Asset Returns, Sorted by + Portfolios + maintainer: Siegfried Köstlmeier + description: Test for monotonicity in financial variables sorted by portfolios. + It is conventional practice in empirical research to form portfolios of assets + ranked by a certain sort variable. A t-test is then used to consider the mean + return spread between the portfolios with the highest and lowest values of the + sort variable. Yet comparing only the average returns on the top and bottom portfolios + does not provide a sufficient way to test for a monotonic relation between expected + returns and the sort variable. This package provides nonparametric tests for the + full set of monotonic patterns by Patton, A. and Timmermann, A. (2010) + and compares the proposed results with extant alternatives such as t-tests, Bonferroni + bounds, and multivariate inequality tests through empirical applications and simulations. + date_publication: '2019-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=monotonicity + url_git: https://github.com/skoestlmeier/monotonicity +MonotonicityTest: + version: '1.0' + title: Nonparametric Bootstrap Test for Regression Monotonicity + maintainer: Dylan Huynh + description: |- + Implements nonparametric bootstrap tests for detecting monotonicity + in regression functions from Hall, P. and Heckman, N. (2000) + Includes tools for visualizing results using Nadaraya-Watson kernel regression and supports + efficient computation with 'C++'. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MonotonicityTest + url_git: '' +monreg: + version: 0.1.4.1 + title: Nonparametric Monotone Regression + maintainer: Scott Kostyshak + description: Estimates monotone regression and variance functions in a nonparametric + model, based on Dette, Holger, Neumeyer, and Pilz (2006) . + date_publication: '2023-12-14' + bug_reports: https://gitlab.com/scottkosty/monreg/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=monreg + url_git: https://gitlab.com/scottkosty/monreg +Monte.Carlo.se: + version: 0.1.1 + title: Monte Carlo Standard Errors + maintainer: Dennis Boos + description: Computes Monte Carlo standard errors for summaries of Monte Carlo output. + Summaries and their standard errors are based on columns of Monte Carlo simulation + output. Dennis D. Boos and Jason A. Osborne (2015) . + date_publication: '2023-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Monte.Carlo.se + url_git: '' +MonteCarlo: + version: 1.0.6 + title: Automatic Parallelized Monte Carlo Simulations + maintainer: Christian Hendrik Leschinski + description: |- + Simplifies Monte Carlo simulation studies by automatically + setting up loops to run over parameter grids and parallelising + the Monte Carlo repetitions. It also generates LaTeX tables. + date_publication: '2019-01-31' + bug_reports: http://github.com/FunWithR/MonteCarlo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MonteCarlo + url_git: http://github.com/FunWithR/MonteCarlo +MonteCarloSEM: + version: 0.0.8 + title: Monte Carlo Data Simulation Package + maintainer: Fatih Orcan + description: |- + Monte Carlo simulation allows testing different conditions given to the correct structural equation models. This package runs Monte Carlo simulations under different conditions (such as sample size or normality of data). Within the package data sets can be simulated and run based on the given model. + First, continuous and normal data sets are generated based on the given model. Later Fleishman's power method (1978) is used to add non-normality if exists. + When data generation is completed (or when generated data sets are given) model test can also be run. + Please cite as "Orçan, F. (2021). MonteCarloSEM: An R Package to Simulate Data for SEM. International Journal of Assessment Tools in Education, 8 (3), 704-713." + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MonteCarloSEM + url_git: '' +moocore: + version: 0.1.2 + title: Core Mathematical Functions for Multi-Objective Optimization + maintainer: Manuel López-Ibáñez + description: Fast implementation of mathematical operations and performance metrics + for multi-objective optimization, including filtering and ranking of dominated + vectors according to Pareto optimality, computation of the empirical attainment + function, V.G. da Fonseca, C.M. Fonseca, A.O. Hall (2001) , + hypervolume metric, C.M. Fonseca, L. Paquete, M. López-Ibáñez (2006) , + epsilon indicator, inverted generational distance, and Vorob'ev threshold, expectation + and deviation, M. Binois, D. Ginsbourger, O. Roustant (2015) , + among others. + date_publication: '2024-09-18' + bug_reports: https://github.com/multi-objective/moocore/issues + url: https://multi-objective.github.io/moocore/r/ + url_cran: https://CRAN.R-project.org/package=moocore + url_git: https://github.com/multi-objective/moocore/tree/main/r +MOODE: + version: 1.0.1 + title: Multi-Objective Optimal Design of Experiments + maintainer: Vasiliki Koutra + description: Provides functionality to generate compound optimal designs for targeting + the multiple experimental objectives directly, ensuring that the full set of research + questions is answered as economically as possible. Designs can be found using + point or coordinate exchange algorithms combining estimation, inference and lack-of-fit + criteria that account for model inadequacy. Details and examples are given by + Koutra et al. (2024) . + date_publication: '2025-01-08' + bug_reports: https://github.com/vkstats/MOODE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MOODE + url_git: https://github.com/vkstats/MOODE +moodef: + version: 1.2.0 + title: Defining 'Moodle' Elements from R + maintainer: Jose Samos + description: |- + The main objective of this package is to support the + definition of 'Moodle' elements taking advantage of the power that R + offers. In this first version, it allows the definition of quizzes + to be included in the question bank. + date_publication: '2025-01-26' + bug_reports: https://github.com/josesamos/moodef/issues + url: https://josesamos.github.io/moodef/ + url_cran: https://CRAN.R-project.org/package=moodef + url_git: https://github.com/josesamos/moodef +moodlequizR: + version: 2.1.1 + title: Easily Create Fully Randomized 'Moodle' Test Questions + maintainer: Wolfgang Rolke + description: Routines to generate fully randomized 'moodle' quizzes. It also contains + 15 examples and a 'shiny' app. + date_publication: '2024-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moodlequizR + url_git: '' +moodleR: + version: 1.0.1 + title: Helper Functions to Work with 'Moodle' Data + maintainer: Aleksander Dietrichson + description: |- + A collection of functions to connect to a 'Moodle' database, cache relevant tables locally and generate learning analytics. + 'Moodle' is an open source Learning Management System (LMS) developed by MoodleHQ. For more information about Moodle, visit . + date_publication: '2022-08-15' + bug_reports: '' + url: https://chi2labs.github.io/moodleR/ + url_cran: https://CRAN.R-project.org/package=moodleR + url_git: https://github.com/chi2labs/moodleR +moonBook: + version: 0.3.1 + title: Functions and Datasets for the Book by Keon-Woong Moon + maintainer: Keon-Woong Moon + description: |- + Several analysis-related functions for the book entitled "R + statistics and graph for medical articles" (written in Korean), version 1, + by Keon-Woong Moon with Korean demographic data with several plot + functions. + date_publication: '2022-01-05' + bug_reports: https://github.com/cardiomoon/moonBook/issues + url: '' + url_cran: https://CRAN.R-project.org/package=moonBook + url_git: https://github.com/cardiomoon/moonBook +moonboot: + version: 1.0.1 + title: m-Out-of-n Bootstrap Functions + maintainer: Christoph Dalitz + description: |- + Functions and examples based on the m-out-of-n bootstrap suggested by + Politis, D.N. and Romano, J.P. (1994) . + Additionally there are functions to estimate the scaling factor tau + and the subsampling size m. For a detailed description and a full list + of references, see Dalitz, C. and Lögler, F. (2024) + . + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moonboot + url_git: '' +moose: + version: 0.0.1 + title: Mean Squared Out-of-Sample Error Projection + maintainer: Chris Rohlfs + description: 'Projects mean squared out-of-sample error for a linear regression + based upon the methodology developed in Rohlfs (2022) . It + consumes as inputs the lm object from an estimated OLS regression (based on the + "training sample") and a data.frame of out-of-sample cases (the "test sample") + that have non-missing values for the same predictors. The test sample may or may + not include data on the outcome variable; if it does, that variable is not used. + The aim of the exercise is to project what what mean squared out-of-sample error + can be expected given the predictor values supplied in the test sample. Output + consists of a list of three elements: the projected mean squared out-of-sample + error, the projected out-of-sample R-squared, and a vector of out-of-sample "hat" + or "leverage" values, as defined in the paper.' + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moose + url_git: '' +mop: + version: 0.1.2 + title: Mobility Oriented-Parity Metric + maintainer: Marlon E. Cobos + description: |- + A set of tools to perform multiple versions of the Mobility + Oriented-Parity metric. This multivariate analysis helps to characterize + levels of dissimilarity between a set of conditions of reference and another + set of conditions of interest. If predictive models are transferred to + conditions different from those over which models were calibrated (trained), + this metric helps to identify transfer conditions that differ + substantially from those of calibration. These tools are implemented + following principles proposed in Owens et al. (2013) + , and expanded to obtain more detailed + results that aid in interpretation. + date_publication: '2024-03-28' + bug_reports: https://github.com/marlonecobos/mop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mop + url_git: https://github.com/marlonecobos/mop +mopac: + version: 0.1.0 + title: Collection of Datasets Pertaining to Loop 1 "Mopac" + maintainer: Scott McKenzie + description: |- + Provides real & simulated datasets containing time-series traffic observations + and additional information pertaining to Loop 1 "Mopac" located in Austin, Texas. + date_publication: '2021-04-28' + bug_reports: https://github.com/sccmckenzie/mopac/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mopac + url_git: https://github.com/sccmckenzie/mopac +MOQA: + version: 2.0.0 + title: Basic Quality Data Assurance for Epidemiological Research + maintainer: Martin Bialke + description: With the provision of several tools and templates the MOSAIC project + (DFG-Grant Number HO 1937/2-1) supports the implementation of a central data management + in epidemiological research projects. The 'MOQA' package enables epidemiologists + with none or low experience in R to generate basic data quality reports for a + wide range of application scenarios. See for more + information. Please read and cite the corresponding open access publication (using + the former package-name) in METHODS OF INFORMATION IN MEDICINE by M. Bialke, H. + Rau, T. Schwaneberg, R. Walk, T. Bahls and W. Hoffmann (2017) . + . + date_publication: '2017-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOQA + url_git: '' +moranajp: + version: 0.9.7 + title: Morphological Analysis for Japanese + maintainer: Toshikazu Matsumura + description: |- + Supports morphological analysis for Japanese by using + 'MeCab' , + 'Sudachi' , + 'Chamame' , + or 'Ginza' . + Can input a data.frame and obtain all results of 'MeCab' and the row + number of the original data.frame as a text id. + date_publication: '2024-08-01' + bug_reports: https://github.com/matutosi/moranajp/issues + url: https://matutosi.github.io/moranajp/ + url_cran: https://CRAN.R-project.org/package=moranajp + url_git: https://github.com/matutosi/moranajp +moreparty: + version: '0.4' + title: A Toolbox for Conditional Inference Trees and Random Forests + maintainer: Nicolas Robette + description: 'Additions to ''party'' and ''partykit'' packages : tools for the interpretation + of forests (surrogate trees, prototypes, etc.), feature selection (see Gregorutti + et al (2017) , Hapfelmeier and Ulm (2013) , + Altmann et al (2010) ) and parallelized versions + of conditional forest and variable importance functions. Also modules and a shiny + app for conditional inference trees.' + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moreparty + url_git: '' +morepls: + version: '0.1' + title: Interpretation Tools for Partial Least Squares Regression + maintainer: Nicolas Robette + description: Various kinds of plots (observations, variables, correlations, weights, + regression coefficients and Variable Importance in the Projection) and aids to + interpretation (coefficients, Q2, correlations, redundancies) for partial least + squares regressions computed with the 'pls' package, following Tenenhaus (1998, + ISBN:2-7108-0735-1). + date_publication: '2024-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=morepls + url_git: '' +morestopwords: + version: 0.2.0 + title: All Stop Words in One Place + maintainer: Fabio Ashtar Telarico + description: 'A standalone package combining several stop-word lists for 65 languages + with a median of 329 stop words for language and over 1,000 entries for English, + Breton, Latin, Slovenian, and Ancient Greek! The user automatically gets access + to all the unique stop words contained in: the ''StopwordISO'' repository; the + ''Natural Language Toolkit'' for ''python''; the ''Snowball'' stop-word list; + the R package ''quanteda''; the ''marimo'' repository; the ''Perseus'' project; + and A. Berra''s list of stop words for Ancient Greek and Latin.' + date_publication: '2023-06-12' + bug_reports: https://github.com/FATelarico/morestopwords/issues + url: https://fatelarico.github.io/morestopwords.html + url_cran: https://CRAN.R-project.org/package=morestopwords + url_git: '' +morph: + version: 1.1.0 + title: 3D Segmentation of Voxels into Morphologic Classes + maintainer: Tarmo K. Remmel + description: Automatically segments a 3D array of voxels into mutually exclusive + morphological elements. This package extends existing work for segmenting 2D binary + raster data. A paper documenting this approach has been accepted for publication + in the journal Landscape Ecology. Detailed references will be updated here once + those are known. + date_publication: '2023-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=morph + url_git: '' +morphemepiece: + version: 1.2.3 + title: Morpheme Tokenization + maintainer: Jonathan Bratt + description: |- + Tokenize text into morphemes. The morphemepiece algorithm uses a + lookup table to determine the morpheme breakdown of words, and falls back on a + modified wordpiece tokenization algorithm for words not found in the lookup + table. + date_publication: '2022-04-16' + bug_reports: https://github.com/macmillancontentscience/morphemepiece/issues + url: '' + url_cran: https://CRAN.R-project.org/package=morphemepiece + url_git: https://github.com/macmillancontentscience/morphemepiece +morphemepiece.data: + version: 1.2.0 + title: Data for Morpheme Tokenization + maintainer: Jon Harmon + description: |- + Provides data about morphemes, the smallest units of meaning in a + language. + date_publication: '2022-04-18' + bug_reports: https://github.com/macmillancontentscience/morphemepiece.data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=morphemepiece.data + url_git: https://github.com/macmillancontentscience/morphemepiece.data +Morpho: + version: '2.12' + title: |- + Calculations and Visualisations Related to Geometric + Morphometrics + maintainer: Stefan Schlager + description: |- + A toolset for Geometric Morphometrics and mesh processing. This + includes (among other stuff) mesh deformations based on reference points, + permutation tests, detection of outliers, processing of sliding + semi-landmarks and semi-automated surface landmark placement. + date_publication: '2023-12-06' + bug_reports: https://github.com/zarquon42b/Morpho/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Morpho + url_git: https://github.com/zarquon42b/Morpho +morphomap: + version: '1.5' + title: Morphometric Maps, Bone Landmarking and Cross Sectional Geometry + maintainer: Antonio Profico + description: Extract cross sections from long bone meshes at specified intervals + along the diaphysis. Calculate two and three-dimensional morphometric maps, cross-sectional + geometric parameters, and semilandmarks on the periosteal and endosteal contours + of each cross section. + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=morphomap + url_git: '' +moRphomenses: + version: 1.0.3 + title: |- + Geometric Morphometric Tools to Align, Scale, and Compare + "Shape" of Menstrual Cycle Hormones + maintainer: Daniel Ehrlich + description: |- + Mitteroecker & Gunz (2009) describe + how geometric morphometric methods allow researchers to quantify the size + and shape of physical biological structures. We provide tools to extend geometric + morphometric principles to the study of non-physical structures, hormone profiles, + as outlined in Ehrlich et al (2021) . Easily transform + daily measures into multivariate landmark-based data. Includes custom functions + to apply multivariate methods for data exploration as well as hypothesis testing. + Also includes 'shiny' web app to streamline data exploration. Developed to study + menstrual cycle hormones but functions have been generalized and should be + applicable to any biomarker over any time period. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moRphomenses + url_git: +MorphoRegions: + version: 0.1.0 + title: |- + Analysis of Regionalization Patterns in Serially Homologous + Structures + maintainer: Amandine Gillet + description: |- + Computes the optimal number of regions (or subdivisions) and + their position in serial structures without a priori assumptions and to visualize + the results. After reducing data dimensionality with the built-in function for + data ordination, regions are fitted as segmented linear regressions + along the serial structure. Every region boundary + position and increasing number of regions are iteratively fitted and + the best model (number of regions and boundary positions) is selected + with an information criterion. This package expands on the previous + 'regions' package (Jones et al., Science 2018) with improved + computation and more fitting and plotting options. + date_publication: '2024-08-21' + bug_reports: https://github.com/aagillet/MorphoRegions/issues + url: https://aagillet.github.io/MorphoRegions/ + url_cran: https://CRAN.R-project.org/package=MorphoRegions + url_git: https://github.com/aagillet/MorphoRegions +Morphoscape: + version: 1.0.2 + title: Computation and Visualization of Adaptive Landscapes + maintainer: Blake Dickson + description: Implements adaptive landscape methods first described by Polly et al. + (2016) for the integration, analysis and visualization + of biological trait data on a phenotypic morphospace - typically defined by shape + metrics. + date_publication: '2023-05-18' + bug_reports: '' + url: https://blakedickson.github.io/Morphoscape/ + url_cran: https://CRAN.R-project.org/package=Morphoscape + url_git: '' +MorphoTools2: + version: 1.0.2.1 + title: Multivariate Morphometric Analysis + maintainer: Marek Šlenker + description: 'Tools for multivariate analyses of morphological data, wrapped in + one package, to make the workflow convenient and fast. Statistical and graphical + tools provide a comprehensive framework for checking and manipulating input data, + statistical analyses, and visualization of results. Several methods are provided + for the analysis of raw data, to make the dataset ready for downstream analyses. + Integrated statistical methods include hierarchical classification, principal + component analysis, principal coordinates analysis, non-metric multidimensional + scaling, and multiple discriminant analyses: canonical, stepwise, and classificatory + (linear, quadratic, and the non-parametric k nearest neighbours). The philosophy + of the package is described in Šlenker et al. 2022.' + date_publication: '2024-10-02' + bug_reports: https://github.com/MarekSlenker/MorphoTools2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MorphoTools2 + url_git: https://github.com/MarekSlenker/MorphoTools2 +morrowplots: + version: 0.2.0 + title: Historical Agricultural Data from the University of Illinois + maintainer: Sandi Caldrone + description: |- + Agricultural data for 1888-2021 from the Morrow Plots at the + University of Illinois. The world's second oldest ongoing agricultural + experiment, the Morrow Plots measure the impact of crop rotation and + fertility treatments on corn yields. The data includes planting information + and annual yield measures for corn grown continuously and in rotation with + other crops, in treated and untreated soil. + date_publication: '2025-01-08' + bug_reports: https://github.com/SandiCal/morrowplots/issues + url: https://SandiCal.github.io/morrowplots/ + url_cran: https://CRAN.R-project.org/package=morrowplots + url_git: https://github.com/SandiCal/morrowplots +morse: + version: 3.3.4 + title: Modelling Reproduction and Survival Data in Ecotoxicology + maintainer: Virgile Baudrot + description: |- + Advanced methods for a valuable quantitative environmental risk + assessment using Bayesian inference of survival and reproduction Data. Among + others, it facilitates Bayesian inference of the general unified + threshold model of survival (GUTS). See our companion paper + Baudrot and Charles (2021) , + as well as complementary details in Baudrot et al. (2018) + and Delignette-Muller et al. + (2017) . + date_publication: '2024-09-18' + bug_reports: https://gitlab.in2p3.fr/mosaic-software/morse/-/issues + url: https://gitlab.in2p3.fr/mosaic-software/morse + url_cran: https://CRAN.R-project.org/package=morse + url_git: '' +mort: + version: 0.0.1 + title: |- + Identifying Potential Mortalities and Expelled Tags in Aquatic + Acoustic Telemetry Arrays + maintainer: Rosie Smith + description: |- + A toolkit for identifying potential mortalities and expelled tags in aquatic acoustic telemetry arrays. + Designed for arrays with non-overlapping receivers. + date_publication: '2023-09-04' + bug_reports: https://github.com/rosieluain/mort/issues + url: https://rosieluain.github.io/mort/ + url_cran: https://CRAN.R-project.org/package=mort + url_git: https://github.com/rosieluain/mort +mortAAR: + version: 1.1.7 + title: Analysis of Archaeological Mortality Data + maintainer: Nils Mueller-Scheessel + description: |- + A collection of functions for the analysis of archaeological mortality + data (on the topic see e.g. Chamberlain 2006 + ). + It takes demographic data in different formats and displays the result in a standard life table + as well as plots the relevant indices (percentage of deaths, survivorship, probability of death, + life expectancy, percentage of population). It also checks for possible biases in the age + structure and applies corrections to life tables. + date_publication: '2025-01-12' + bug_reports: https://github.com/ISAAKiel/mortAAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mortAAR + url_git: https://github.com/ISAAKiel/mortAAR +MortalityGaps: + version: 1.0.0 + title: The Double-Gap Life Expectancy Forecasting Model + maintainer: Marius D. Pascariu + description: |- + Life expectancy is highly correlated over time among countries and + between males and females. These associations can be used to improve forecasts. + Here we have implemented a method for forecasting female life expectancy based on + analysis of the gap between female life expectancy in a country compared with + the record level of female life expectancy in the world. Second, to forecast + male life expectancy, the gap between male life expectancy and female life + expectancy in a country is analysed. We named this method the Double-Gap model. + For a detailed description of the method see Pascariu et al. (2017). + . + date_publication: '2018-07-20' + bug_reports: https://github.com/mpascariu/MortalityGaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MortalityGaps + url_git: https://github.com/mpascariu/MortalityGaps +MortalityLaws: + version: 2.1.0 + title: Parametric Mortality Models, Life Tables and HMD + maintainer: Marius D. Pascariu + description: |- + Fit the most popular human mortality 'laws', and construct + full and abridge life tables given various input indices. A mortality + law is a parametric function that describes the dying-out process of + individuals in a population during a significant portion of their + life spans. For a comprehensive review of the most important mortality + laws see Tabeau (2001) . + Practical functions for downloading data from various human mortality + databases are provided as well. + date_publication: '2024-01-15' + bug_reports: https://github.com/mpascariu/MortalityLaws/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MortalityLaws + url_git: https://github.com/mpascariu/MortalityLaws +MortalityTables: + version: 2.0.5 + title: A Framework for Various Types of Mortality / Life Tables + maintainer: Reinhold Kainhofer + description: |- + Classes to implement, analyze and plot cohort life tables + for actuarial calculations. Birth-year dependent cohort mortality + tables using a yearly trend to extrapolate from a base year are implemented, + as well as period life table, cohort life tables using an age shift, and + merged life tables. Additionally, several data sets from various countries + are included to provide widely-used tables out of the box. + date_publication: '2023-10-27' + bug_reports: https://gitlab.open-tools.net/R/r-mortality-tables/-/issues + url: https://gitlab.open-tools.net/R/r-mortality-tables + url_cran: https://CRAN.R-project.org/package=MortalityTables + url_git: '' +MortCast: + version: 2.8-0 + title: Estimation and Projection of Age-Specific Mortality Rates + maintainer: Hana Sevcikova + description: |- + Age-specific mortality rates are estimated and projected using + the Kannisto, Lee-Carter and related methods as described in + Sevcikova et al. (2016) . + date_publication: '2024-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MortCast + url_git: '' +mosaic: + version: 1.9.1 + title: Project MOSAIC Statistics and Mathematics Teaching Utilities + maintainer: Randall Pruim + description: |- + Data sets and utilities from Project MOSAIC () used + to teach mathematics, statistics, computation and modeling. Funded by the + NSF, Project MOSAIC is a community of educators working to tie together + aspects of quantitative work that students in science, technology, + engineering and mathematics will need in their professional lives, but + which are usually taught in isolation, if at all. + date_publication: '2024-02-23' + bug_reports: https://github.com/ProjectMOSAIC/mosaic/issues + url: https://www.mosaic-web.org/mosaic/ + url_cran: https://CRAN.R-project.org/package=mosaic + url_git: https://github.com/ProjectMOSAIC/mosaic +mosaicCalc: + version: 0.6.4 + title: R-Language Based Calculus Operations for Teaching + maintainer: Daniel Kaplan + description: |- + Software to support the introductory *MOSAIC Calculus* + textbook ), + one of many data- and modeling-oriented educational resources developed by + Project MOSAIC (). Provides symbolic and + numerical differentiation and integration, as well as support for + applied linear algebra (for data science), and differential equations/dynamics. + Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc. + The software is suitable for general use, but intended mainly for teaching calculus. + date_publication: '2024-07-26' + bug_reports: https://github.com/ProjectMOSAIC/mosaicCalc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mosaicCalc + url_git: https://github.com/ProjectMOSAIC/mosaicCalc +mosaicCore: + version: 0.9.4.0 + title: Common Utilities for Other MOSAIC-Family Packages + maintainer: Randall Pruim + description: |- + Common utilities used in other MOSAIC-family packages are + collected here. + date_publication: '2023-11-05' + bug_reports: https://github.com/ProjectMOSAIC/mosaicCore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mosaicCore + url_git: https://github.com/ProjectMOSAIC/mosaicCore +mosaicData: + version: 0.20.4 + title: Project MOSAIC Data Sets + maintainer: Randall Pruim + description: |- + Data sets from Project MOSAIC () used + to teach mathematics, statistics, computation and modeling. Funded by the + NSF, Project MOSAIC is a community of educators working to tie together + aspects of quantitative work that students in science, technology, + engineering and mathematics will need in their professional lives, but + which are usually taught in isolation, if at all. + date_publication: '2023-11-05' + bug_reports: https://github.com/ProjectMOSAIC/mosaicData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mosaicData + url_git: https://github.com/ProjectMOSAIC/mosaicData +mosaicModel: + version: 0.3.0 + title: |- + An Interface to Statistical Modeling Independent of Model + Architecture + maintainer: Daniel Kaplan + description: Provides functions for evaluating, displaying, and interpreting statistical + models. The goal is to abstract the operations on models from the particular architecture + of the model. For instance, calculating effect sizes rather than looking at coefficients. + The package includes interfaces to both regression and classification architectures, + including lm(), glm(), rlm() in 'MASS', random forests and recursive partitioning, + k-nearest neighbors, linear and quadratic discriminant analysis, and models produced + by the 'caret' package's train(). It's straightforward to add in other other model + architectures. + date_publication: '2017-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mosaicModel + url_git: '' +MOsemiind: + version: 0.1.0 + title: Marshall-Olkin Shock Models with Semi-Independent Time + maintainer: Andjela Mijanovic + description: |- + Provides tools for analyzing Marshall-Olkin shock models semi-independent time. + It includes interactive 'shiny' applications for exploring copula-based dependence + structures, along with functions for modeling and visualization. The methods are + based on Mijanovic and Popovic (2024, submitted) "An R package for Marshall-Olkin + shock models with semi-independent times." + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOsemiind + url_git: '' +mosqcontrol: + version: 0.1.0 + title: Mosquito Control Resource Optimization + maintainer: Travis Byrum + description: This project aims to make an accessible model for mosquito control + resource optimization. The model uses data provided by users to estimate the mosquito + populations in the sampling area for the sampling time period, and the optimal + time to apply a treatment or multiple treatments. + date_publication: '2020-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mosqcontrol + url_git: '' +MOST: + version: 0.1.2 + title: Multiphase Optimization Strategy + maintainer: John Dziak + description: |- + Provides functions similar to the 'SAS' macros previously provided + to accompany Collins, Dziak, and Li (2009) + and Dziak, Nahum-Shani, and Collins (2012) , papers + which outline practical benefits and challenges of factorial + and fractional factorial experiments for scientists interested + in developing biological and/or behavioral interventions, especially + in the context of the multiphase optimization strategy + (see Collins, Kugler & Gwadz 2016) . The package + currently contains three functions. First, RelativeCosts1() draws a graph + of the relative cost of complete and reduced factorial designs versus + other alternatives. Second, RandomAssignmentGenerator() returns a dataframe + which contains a list of random numbers that can be used to conveniently + assign participants to conditions in an experiment with + many conditions. Third, FactorialPowerPlan() estimates the power, detectable effect + size, or required sample size of a factorial or fractional factorial + experiment, for main effects or interactions, given several possible choices + of effect size metric, and allowing pretests and clustering. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOST + url_git: '' +mosum: + version: 1.2.7 + title: Moving Sum Based Procedures for Changes in the Mean + maintainer: Haeran Cho + description: Implementations of MOSUM-based statistical procedures and algorithms + for detecting multiple changes in the mean. This comprises the MOSUM procedure + for estimating multiple mean changes from Eichinger and Kirch (2018) + and the multiscale algorithmic extension from Cho and Kirch (2022) , + as well as the bootstrap procedure for generating confidence intervals about the + locations of change points as proposed in Cho and Kirch (2022) . + See also Meier, Kirch and Cho (2021) which accompanies + the R package. + date_publication: '2022-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mosum + url_git: '' +MoTBFs: + version: 1.4.1 + title: |- + Learning Hybrid Bayesian Networks using Mixtures of Truncated + Basis Functions + maintainer: Ana D. Maldonado + description: |- + Learning, manipulation and evaluation of mixtures of truncated basis functions + (MoTBFs), which include mixtures of polynomials (MOPs) and mixtures of truncated + exponentials (MTEs). MoTBFs are a flexible framework for modelling hybrid Bayesian + networks (I. Pérez-Bernabé, A. Salmerón, H. Langseth (2015) ; H. Langseth, T.D. Nielsen, I. Pérez-Bernabé, A. Salmerón (2014) ; I. Pérez-Bernabé, A. Fernández, R. Rumí, A. Salmerón (2016) ). The package provides functionality for learning univariate, multivariate and + conditional densities, with the possibility of incorporating prior knowledge. Structural + learning of hybrid Bayesian networks is also provided. A set of useful tools is provided, + including plotting, printing and likelihood evaluation. This package makes use of S3 + objects, with two new classes called 'motbf' and 'jointmotbf'. + date_publication: '2022-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MoTBFs + url_git: '' +MOTE: + version: 1.0.2 + title: Effect Size and Confidence Interval Calculator + maintainer: Erin M. Buchanan + description: |- + Measure of the Effect ('MOTE') is an effect size calculator, including a + wide variety of effect sizes in the mean differences family (all versions of d) and + the variance overlap family (eta, omega, epsilon, r). 'MOTE' provides non-central + confidence intervals for each effect size, relevant test statistics, and output + for reporting in APA Style (American Psychological Association, 2010, + ) with 'LaTeX'. In research, an over-reliance on p-values + may conceal the fact that a study is under-powered (Halsey, Curran-Everett, + Vowler, & Drummond, 2015 ). A test may be statistically + significant, yet practically inconsequential (Fritz, Scherndl, & Kühberger, 2012 + ). Although the American Psychological Association + has long advocated for the inclusion of effect sizes (Wilkinson & American + Psychological Association Task Force on Statistical Inference, 1999 + ), the vast majority of peer-reviewed, + published academic studies stop short of reporting effect sizes and confidence + intervals (Cumming, 2013, ). 'MOTE' simplifies + the use and interpretation of effect sizes and confidence intervals. For more + information, visit . + date_publication: '2019-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MOTE + url_git: '' +motif: + version: 0.6.4 + title: Local Pattern Analysis + maintainer: Jakub Nowosad + description: |- + Describes spatial patterns of categorical raster data for + any defined regular and irregular areas. + Patterns are described quantitatively using built-in signatures + based on co-occurrence matrices but also allows for + any user-defined functions. + It enables spatial analysis such as search, change detection, + and clustering to be performed on spatial patterns (Nowosad (2021) ). + date_publication: '2023-06-29' + bug_reports: https://github.com/Nowosad/motif/issues + url: https://jakubnowosad.com/motif/ + url_cran: https://CRAN.R-project.org/package=motif + url_git: '' +motifcluster: + version: 0.2.3 + title: Motif-Based Spectral Clustering of Weighted Directed Networks + maintainer: William George Underwood + description: |2- + + Tools for spectral clustering of weighted directed networks using motif + adjacency matrices. Methods perform well on large and sparse networks, and + random sampling methods for generating weighted directed networks are also + provided. Based on methodology detailed in Underwood, Elliott and Cucuringu + (2020) . + date_publication: '2022-11-18' + bug_reports: https://github.com/wgunderwood/motifcluster/issues + url: '' + url_cran: https://CRAN.R-project.org/package=motifcluster + url_git: https://github.com/wgunderwood/motifcluster +motifr: + version: 1.0.0 + title: Motif Analysis in Multi-Level Networks + maintainer: Mario Angst + description: |- + Tools for motif analysis in multi-level networks. + Multi-level networks combine multiple networks in one, e.g. + social-ecological networks. Motifs are small configurations of nodes + and edges (subgraphs) occurring in networks. 'motifr' can visualize + multi-level networks, count multi-level network motifs and compare + motif occurrences to baseline models. It also identifies contributions + of existing or potential edges to motifs to find critical or missing + edges. The package is in many parts an R wrapper for the excellent + 'SESMotifAnalyser' 'Python' package written by Tim Seppelt. + date_publication: '2020-12-10' + bug_reports: https://github.com/marioangst/motifr/issues + url: https://marioangst.github.io/motifr/ + url_cran: https://CRAN.R-project.org/package=motifr + url_git: '' +motmot: + version: 2.1.3 + title: Models of Trait Macroevolution on Trees + maintainer: Mark Puttick + description: "Functions for fitting models of trait evolution\non phylogenies for + continuous traits. The majority of functions\ndescribed in Thomas and Freckleton + (2012) \tand include functions that allow + for tests of variation in the rates of trait evolution." + date_publication: '2019-11-25' + bug_reports: '' + url: https://puttickbiology.wordpress.com/motmot/ + url_cran: https://CRAN.R-project.org/package=motmot + url_git: '' +motoRneuron: + version: 1.0.0 + title: |- + Analyzing Paired Neuron Discharge Times for Time-Domain + Synchronization + maintainer: Andrew Tweedell + description: |- + The temporal relationship between motor neurons can offer + explanations for neural strategies. We combined functions to reduce neuron + action potential discharge data and analyze it for short-term, time-domain + synchronization. Even more so, motoRneuron combines most available methods + for the determining cross correlation histogram peaks and most available + indices for calculating synchronization into simple functions. See + Nordstrom, Fuglevand, and Enoka (1992) + for a more thorough introduction. + date_publication: '2019-02-26' + bug_reports: http://github.com/tweedell/motoRneuron/issues + url: '' + url_cran: https://CRAN.R-project.org/package=motoRneuron + url_git: http://github.com/tweedell/motoRneuron +moult: + version: 2.3.1 + title: Models for Analysing Moult in Birds + maintainer: Birgit Erni + description: |- + Functions to estimate start and duration of moult from moult + data, based on models developed in Underhill + and Zucchini (1988, 1990). + date_publication: '2022-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moult + url_git: '' +mountainplot: + version: '1.4' + title: Mountain Plots, Folded Empirical Cumulative Distribution Plots + maintainer: Kevin Wright + description: |- + Lattice functions for drawing folded empirical cumulative + distribution plots, or mountain plots. A mountain plot is similar + to an empirical CDF plot, except that the curve increases from + 0 to 0.5, then decreases from 0.5 to 1 using an inverted scale at + the right side. See Monti (1995) . + date_publication: '2022-05-02' + bug_reports: https://github.com/kwstat/mountainplot/issues + url: https://kwstat.github.io/mountainplot/ + url_cran: https://CRAN.R-project.org/package=mountainplot + url_git: '' +mousetRajectory: + version: 0.2.1 + title: Mouse Trajectory Analyses for Behavioural Scientists + maintainer: Roland Pfister + description: |- + Helping psychologists and other behavioural scientists + to analyze mouse movement (and other 2-D trajectory) data. Bundles + together several functions that compute spatial measures (e.g., maximum + absolute deviation, area under the curve, sample entropy) or provide a + shorthand for procedures that are frequently used (e.g., time + normalization, linear interpolation, extracting initiation and movement + times). For more information on these dependent measures, see Wirth et al. + (2020) . + date_publication: '2023-09-08' + bug_reports: https://github.com/mc-schaaf/mousetRajectory/issues + url: https://mc-schaaf.github.io/mousetRajectory/ + url_cran: https://CRAN.R-project.org/package=mousetRajectory + url_git: https://github.com/mc-schaaf/mousetRajectory +mousetrap: + version: 3.2.3 + title: Process and Analyze Mouse-Tracking Data + maintainer: Pascal J. Kieslich + description: |- + Mouse-tracking, the analysis of mouse movements in computerized + experiments, is a method that is becoming increasingly popular in the + cognitive sciences. The mousetrap package offers functions for importing, + preprocessing, analyzing, aggregating, and visualizing mouse-tracking data. + An introduction into mouse-tracking analyses using mousetrap can be found + in Wulff, Kieslich, Henninger, Haslbeck, & Schulte-Mecklenbeck (2023) + (preprint: + ). + date_publication: '2024-01-19' + bug_reports: https://github.com/pascalkieslich/mousetrap/issues + url: https://pascalkieslich.github.io/mousetrap/ + url_cran: https://CRAN.R-project.org/package=mousetrap + url_git: https://github.com/pascalkieslich/mousetrap +move: + version: 4.2.6 + title: Visualizing and Analyzing Animal Track Data + maintainer: Bart Kranstauber + description: |- + Contains functions to access movement data stored in 'movebank.org' + as well as tools to visualize and statistically analyze animal movement data, + among others functions to calculate dynamic Brownian Bridge Movement Models. + Move helps addressing movement ecology questions. + date_publication: '2024-11-20' + bug_reports: https://gitlab.com/bartk/move/-/issues + url: https://bartk.gitlab.io/move/ + url_cran: https://CRAN.R-project.org/package=move + url_git: '' +move2: + version: 0.4.4 + title: Processing and Analysing Animal Trajectories + maintainer: Bart Kranstauber + description: Tools to handle, manipulate and explore trajectory data, with an emphasis + on data from tracked animals. The package is designed to support large studies + with several million location records and keep track of units where possible. + Data import directly from 'movebank' + and files is facilitated. + date_publication: '2025-02-10' + bug_reports: https://gitlab.com/bartk/move2/-/issues + url: https://bartk.gitlab.io/move2/ + url_cran: https://CRAN.R-project.org/package=move2 + url_git: '' +movecost: + version: '2.1' + title: |- + Calculation of Slope-Dependant Accumulated Cost Surface, + Least-Cost Paths, Least-Cost Corridors, Least-Cost Networks + Related to Human Movement Across the Landscape + maintainer: Gianmarco Alberti + description: Provides the facility to calculate non-isotropic accumulated cost surface, + least-cost paths, least-cost corridors, least-cost networks using a number of + human-movement-related cost functions that can be selected by the user. It just + requires a Digital Terrain Model, a start location and (optionally) destination + locations. See Alberti (2019) . + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=movecost + url_git: '' +movegroup: + version: 2024.03.05 + title: Visualizing and Quantifying Space Use Data for Groups of Animals + maintainer: Simon Dedman + description: |- + Offers an easy and automated way to scale up individual-level space use analysis to + that of groups. Contains a function from the 'move' package to calculate a dynamic Brownian + bridge movement model from movement data for individual animals, as well as functions to + visualize and quantify space use for individuals aggregated in groups. Originally written with + passive acoustic telemetry in mind, this package also provides functionality to account for + unbalanced acoustic receiver array designs, and satellite tag data. + date_publication: '2024-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=movegroup + url_git: '' +moveHMM: + version: '1.9' + title: Animal Movement Modelling using Hidden Markov Models + maintainer: Theo Michelot + description: |- + Provides tools for animal movement modelling using hidden Markov + models. These include processing of tracking data, fitting hidden Markov models + to movement data, visualization of data and fitted model, decoding of the state + process, etc. . + date_publication: '2023-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=moveHMM + url_git: https://github.com/TheoMichelot/moveHMM +movementsync: + version: 0.1.4 + title: |- + Analysis and Visualisation of Musical Audio and Video Movement + Synchrony Data + maintainer: Tuomas Eerola + description: |- + Analysis and visualisation of synchrony, interaction, and joint + movements from audio and video movement data of a group of music performers. The demo is data described in Clayton, Leante, and + Tarsitani (2021) , while example analyses + can be found in Clayton, Jakubowski, and Eerola (2019) + . Additionally, wavelet analysis + techniques have been applied to examine movement-related + musical interactions, as shown in Eerola et al. (2018) + . + date_publication: '2023-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=movementsync + url_git: '' +moveWindSpeed: + version: 0.2.4 + title: Estimate Wind Speeds from Bird Trajectories + maintainer: Bart Kranstauber + description: Estimating wind speed from trajectories of individually tracked birds + using a maximum likelihood approach. + date_publication: '2023-06-07' + bug_reports: https://gitlab.com/bartk/moveWindSpeed/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=moveWindSpeed + url_git: https://gitlab.com/bartk/moveWindSpeed +movieROC: + version: 0.1.2 + title: Visualizing the Decision Rules Underlying Binary Classification + maintainer: Sonia Perez-Fernandez + description: |- + Visualization of decision rules for binary classification and Receiver Operating Characteristic (ROC) curve estimation under different generalizations proposed in the literature: + - making the classification subsets flexible to cover those scenarios where both extremes of the + marker are associated with a higher risk of being positive, considering two thresholds + (gROC() function); + - transforming the marker by a proper function trying to improve the classification performance + (hROC() function); + - when dealing with multivariate markers, considering a proper transformation to univariate space + trying to maximize the resulting AUC of the TPR for each FPR (multiROC() function). + The classification regions behind each point of the ROC curve are displayed in both static + graphics (plot_buildROC(), plot_regions() or plot_funregions() function) or + videos (movieROC() function). + date_publication: '2024-11-08' + bug_reports: https://github.com/perezsonia/movieROC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=movieROC + url_git: '' +movMF: + version: 0.2-9 + title: Mixtures of von Mises-Fisher Distributions + maintainer: Kurt Hornik + description: Fit and simulate mixtures of von Mises-Fisher distributions. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=movMF + url_git: '' +mp: + version: 0.4.1 + title: Multidimensional Projection Techniques + maintainer: Francisco M. Fatore + description: |- + Multidimensional projection techniques are used to create two + dimensional representations of multidimensional data sets. + date_publication: '2016-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mp + url_git: '' +mpactr: + version: 0.1.0 + title: Correction of Preprocessed MS Data + maintainer: Patrick Schloss + description: 'An ''R'' implementation of the ''python'' program Metabolomics Peak + Analysis Computational Tool (''MPACT'') (Robert M. Samples, Sara P. Puckett, and + Marcy J. Balunas (2023) ). Filters in the package + serve to address common errors in tandem mass spectrometry preprocessing, including: + (1) isotopic patterns that are incorrectly split during preprocessing, (2) features + present in solvent blanks due to carryover between samples, (3) features whose + abundance is greater than user-defined abundance threshold in a specific group + of samples, for example media blanks, (4) ions that are inconsistent between technical + replicates, and (5) in-source fragment ions created during ionization before fragmentation + in the tandem mass spectrometry workflow.' + date_publication: '2024-09-10' + bug_reports: https://github.com/mums2/mpactr/issues + url: https://mums2.github.io/mpactr/ + url_cran: https://CRAN.R-project.org/package=mpactr + url_git: https://github.com/mums2/mpactr +mpae: + version: 0.1.2 + title: |- + Metodos Predictivos de Aprendizaje Estadistico (Statistical + Learning Predictive Methods) + maintainer: Ruben Fernandez-Casal + description: |- + Functions and datasets used in the book: Fernandez-Casal, R., + Costa, J. and Oviedo-de la Fuente, M. (2024) "Metodos predictivos de + aprendizaje estadistico" . + date_publication: '2024-03-21' + bug_reports: https://github.com/rubenfcasal/mpae/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mpae + url_git: https://github.com/rubenfcasal/mpae +mpath: + version: 0.4-2.26 + title: Regularized Linear Models + maintainer: Zhu Wang + description: |- + Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) , + Wang et al. (2015) , + Wang et al. (2016) , + Wang (2021) , + Wang (2024) . + date_publication: '2024-06-27' + bug_reports: https://github.com/zhuwang46/mpath + url: '' + url_cran: https://CRAN.R-project.org/package=mpath + url_git: https://github.com/zhuwang46/mpath +mpathr: + version: 1.0.2 + title: Easily Handling Data from the ‘m-Path’ Platform + maintainer: Merijn Mestdagh + description: |- + Provides tools for importing and cleaning Experience Sampling + Method (ESM) data collected via the 'm-Path' platform. The goal is + to provide with a few utility functions to be able to read and perform + some common operations in ESM data collected through the 'm-Path' + platform (). Functions include raw data + handling, format standardization, and basic data checks, as well as to + calculate the response rate in data from ESM studies. + date_publication: '2024-11-22' + bug_reports: https://github.com/m-path-io/mpathr/issues + url: https://m-path.io + url_cran: https://CRAN.R-project.org/package=mpathr + url_git: https://github.com/m-path-io/mpathr +mpathsenser: + version: 1.2.3 + title: Process and Analyse Data from m-Path Sense + maintainer: Koen Niemeijer + description: |- + Overcomes one of the major challenges in mobile (passive) + sensing, namely being able to pre-process the raw data that comes from + a mobile sensing app, specifically 'm-Path Sense' . + The main task of 'mpathsenser' is therefore to read 'm-Path Sense' + JSON files into a database and provide several convenience functions + to aid in data processing. + date_publication: '2024-03-29' + bug_reports: https://gitlab.kuleuven.be/ppw-okpiv/researchers/u0134047/mpathsenser/-/issues/ + url: https://gitlab.kuleuven.be/ppw-okpiv/researchers/u0134047/mpathsenser/ + url_cran: https://CRAN.R-project.org/package=mpathsenser + url_git: '' +MPBoost: + version: 0.1-6 + title: Treatment Allocation in Clinical Trials by the Maximal Procedure + maintainer: Ignacio López-de-Ullibarri + description: Performs treatment allocation in two-arm clinical trials by the maximal + procedure described by Berger et al. (2003) . To that end, + the algorithm provided by Salama et al. (2008) is implemented. + date_publication: '2024-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPBoost + url_git: '' +MPCI: + version: 1.0.7 + title: Multivariate Process Capability Indices (MPCI) + maintainer: Edgar Santos-Fernandez + description: 'It performs the followings Multivariate Process Capability Indices: + Shahriari et al. (1995) Multivariate Capability Vector, Taam et al. (1993) Multivariate + Capability Index (MCpm), Pan and Lee (2010) proposal (NMCpm) and the followings + based on Principal Component Analysis (PCA):Wang and Chen (1998), Xekalaki and + Perakis (2002) and Wang (2005). Two datasets are included.' + date_publication: '2015-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPCI + url_git: '' +MPCR: + version: 1.1.3 + title: Multi- And Mixed-Precision Computations + maintainer: Sameh Abdulah + description: 'Designed for multi- and mixed-precision computations, accommodating + 64-bit and 32-bit data structures. This flexibility enables fast execution across + various applications. The package enhances performance by optimizing operations + in both precision levels, which is achieved by integrating with high-speed ''BLAS'' + and ''LAPACK'' libraries like ''MKL'' and ''OpenBLAS''. Including a 32-bit option + caters to applications where high precision is unnecessary, accelerating computational + processes whenever feasible. The package also provides support for tile-based + algorithms in three linear algebra operations: CHOL(), TRSM(), and GEMM(). The + tile-based algorithm splits the matrix into smaller tiles, facilitating parallelization + through a predefined Directed Acyclic Graph (DAG) for each operation. Enabling + ''OpenMP'' enhances the efficiency of these operations, leveraging multi-core + parallelism. In this case, ''MPCR'' facilitates mixed-precision execution by permitting + varying precision levels for different tiles. This approach is advantageous in + numerous applications, as it maintains the accuracy of the application while accelerating + execution in scenarios where single-precision alone does not significantly affect + the accuracy of the application.' + date_publication: '2024-10-08' + bug_reports: https://github.com/stsds/MPCR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MPCR + url_git: https://github.com/stsds/MPCR +MPDiR: + version: '0.2' + title: Data Sets and Scripts for Modeling Psychophysical Data in R + maintainer: Ken Knoblauch + description: Data sets and scripts for Modeling Psychophysical Data in R (Springer). + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPDiR + url_git: '' +MPGE: + version: 1.0.0 + title: |- + A Two-Step Approach to Testing Overall Effect of + Gene-Environment Interaction for Multiple Phenotypes + maintainer: Arunabha Majumdar + description: 'Interaction between a genetic variant (e.g., a single nucleotide polymorphism) + and an environmental variable (e.g., physical activity) can have a shared effect + on multiple phenotypes (e.g., blood lipids). We implement a two-step method to + test for an overall interaction effect on multiple phenotypes. In first step, + the method tests for an overall marginal genetic association between the genetic + variant and the multivariate phenotype. The genetic variants which show an evidence + of marginal overall genetic effect in the first step are prioritized while testing + for an overall gene-environment interaction effect in the second step. Methodology + is available from: A Majumdar, KS Burch, S Sankararaman, B Pasaniuc, WJ Gauderman, + JS Witte (2020) .' + date_publication: '2020-10-23' + bug_reports: https://github.com/ArunabhaCodes/MPGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MPGE + url_git: https://github.com/ArunabhaCodes/MPGE +MPI: + version: 0.1.0 + title: Computation of Multidimensional Poverty Index (MPI) + maintainer: Kittiya Kukiattikun + description: Computing package for Multidimensional Poverty Index (MPI) using Alkire-Foster + method. Given N individuals, each person has D indicators of deprivation, the + package compute MPI value to represent the degree of poverty in a population. + The inputs are 1) an N by D matrix, which has the element (i,j) represents whether + an individual i is deprived in an indicator j (1 is deprived and 0 is not deprived), + and 2) the deprivation threshold. The main output is the MPI value, which has + the range between zero and one. MPI value is approaching one if almost all people + are deprived in all indicators, and it is approaching zero if almost no people + are deprived in any indicator. Please see Alkire S., Chatterjee, M., Conconi, + A., Seth, S. and Ana Vaz (2014) for The + Alkire-Foster methodology. + date_publication: '2022-04-05' + bug_reports: https://github.com/9POINTEIGHT/MPI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MPI + url_git: https://github.com/9POINTEIGHT/MPI +mpindex: + version: 0.2.1 + title: Multidimensional Poverty Index (MPI) + maintainer: Bhas Abdulsamad + description: A set of easy-to-use functions for computing the Multidimensional Poverty + Index (MPI). + date_publication: '2024-01-09' + bug_reports: https://github.com/yng-me/mpindex/issues + url: https://yng-me.github.io/mpindex/ + url_cran: https://CRAN.R-project.org/package=mpindex + url_git: https://github.com/yng-me/mpindex +mpitbR: + version: 1.0.1 + title: Calculate Alkire-Foster Multidimensional Poverty Measures + maintainer: Ignacio Girela + description: Estimate Multidimensional Poverty Indices disaggregated by population + subgroups based on the Alkire and Foster method (2011) . + This includes the calculation of standard errors and confidence intervals. Other + partial indices such as incidence, intensity and indicator-specific measures as + well as intertemporal changes analysis can also be estimated. The standard errors + and confidence intervals are calculated considering the complex survey design. + date_publication: '2025-02-11' + bug_reports: https://github.com/girelaignacio/mpitbR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mpitbR + url_git: https://github.com/girelaignacio/mpitbR +mplot: + version: 1.0.6 + title: Graphical Model Stability and Variable Selection Procedures + maintainer: Garth Tarr + description: |- + Model stability and variable inclusion plots [Mueller and Welsh + (2010, ); Murray, Heritier and Mueller + (2013, )] as well as the adaptive fence [Jiang et al. + (2008, ); Jiang et al. + (2009, )] for linear and generalised linear models. + date_publication: '2021-07-10' + bug_reports: '' + url: https://garthtarr.github.io/mplot/ + url_cran: https://CRAN.R-project.org/package=mplot + url_git: https://github.com/garthtarr/mplot +MplusAutomation: + version: 1.1.1 + title: |- + An R Package for Facilitating Large-Scale Latent Variable + Analyses in Mplus + maintainer: Michael Hallquist + description: |- + Leverages the R language to automate latent variable model estimation + and interpretation using 'Mplus', a powerful latent variable modeling program + developed by Muthen and Muthen (). Specifically, this package + provides routines for creating related groups of models, running batches of + models, and extracting and tabulating model parameters and fit statistics. + date_publication: '2024-01-30' + bug_reports: https://github.com/michaelhallquist/MplusAutomation/issues + url: https://michaelhallquist.github.io/MplusAutomation/ + url_cran: https://CRAN.R-project.org/package=MplusAutomation + url_git: '' +MplusLGM: + version: 1.0.0 + title: Automate Latent Growth Mixture Modelling in 'Mplus' + maintainer: Olivier Percie du Sert + description: |- + Provide a suite of functions for conducting and automating Latent Growth Modeling (LGM) in 'Mplus', including Growth Curve Model (GCM), Growth-Based Trajectory Model (GBTM) and Latent Class Growth Analysis (LCGA). + The package builds upon the capabilities of the 'MplusAutomation' package (Hallquist & Wiley, 2018) to streamline large-scale latent variable analyses. + “MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus.” Structural Equation Modeling, 25(4), 621–638. + The workflow implemented in this package follows the recommendations outlined in Van Der Nest et al. (2020). + “An Overview of Mixture Modeling for Latent Evolutions in Longitudinal Data: Modeling Approaches, Fit Statistics, and Software.” Advances in Life Course Research, 43, Article 100323. . + date_publication: '2025-02-03' + bug_reports: https://github.com/OlivierPDS/MplusLGM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MplusLGM + url_git: https://github.com/OlivierPDS/MplusLGM +mplusParallel.automation: + version: 0.0.1.1 + title: Parallel Processing Automation for 'Mplus' + maintainer: Jake Plantz + description: Offers automation tools to parallelize 'Mplus' operations when using + 'R' for data generation. It facilitates streamlined integration between 'Mplus' + and 'R', allowing users to run and manage multiple 'Mplus' models simultaneously + and efficiently in 'R'. + date_publication: '2023-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mplusParallel.automation + url_git: '' +MplusTrees: + version: 0.2.2 + title: Decision Trees with Structural Equation Models Fit in 'Mplus' + maintainer: Sarfaraz Serang + description: |- + Uses recursive partitioning to create homogeneous subgroups based on structural equation models + fit in 'Mplus', a stand-alone program developed by Muthen and Muthen. + date_publication: '2022-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MplusTrees + url_git: '' +mpm: + version: 1.0-23 + title: Multivariate Projection Methods + maintainer: Laure Cougnaud + description: |- + Exploratory graphical analysis of multivariate data, + specifically gene expression data with different projection + methods: principal component analysis, correspondence analysis, + spectral map analysis. + date_publication: '2022-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpm + url_git: http://mpm.r-forge.r-project.org +mpmcorrelogram: + version: 0.1-4 + title: Multivariate Partial Mantel Correlogram + maintainer: Marcelino de la Cruz + description: Functions to compute and plot multivariate (partial) Mantel correlograms. + date_publication: '2017-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpmcorrelogram + url_git: '' +mpmi: + version: 0.43.2.1 + title: Mixed-Pair Mutual Information Estimators + maintainer: Chris Pardy + description: |- + Uses a kernel smoothing approach to calculate Mutual Information + for comparisons between all types of variables including continuous vs + continuous, continuous vs discrete and discrete vs discrete. Uses a + nonparametric bias correction giving Bias Corrected Mutual Information + (BCMI). Implemented efficiently in Fortran 95 with OpenMP and suited to + large genomic datasets. + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpmi + url_git: https://r-forge.r-project.org/projects/mpmi/ +mpmsim: + version: 3.1.0 + title: |- + Simulation of Matrix Population Models with Defined Life History + Characteristics + maintainer: Owen Jones + description: |- + Allows users to simulate matrix population models with + particular characteristics based on aspects of life history such as + mortality trajectories and fertility trajectories. Also allows the + exploration of sampling error due to small sample size. + date_publication: '2024-10-12' + bug_reports: https://github.com/jonesor/mpmsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mpmsim + url_git: https://github.com/jonesor/mpmsim +MPN: + version: 0.4.0 + title: Most Probable Number and Other Microbial Enumeration Techniques + maintainer: John Ihrie + description: |- + Calculates the Most Probable Number (MPN) to quantify the + concentration (density) of microbes in serial dilutions of a laboratory + sample (described in Jarvis, 2010 ). + Also calculates the Aerobic Plate Count (APC) for similar microbial + enumeration experiments. + date_publication: '2024-10-22' + bug_reports: '' + url: https://pub-connect.foodsafetyrisk.org/microbial/mpncalc/ + url_cran: https://CRAN.R-project.org/package=MPN + url_git: '' +mpoly: + version: 1.1.1 + title: Symbolic Computation and More with Multivariate Polynomials + maintainer: David Kahle + description: Symbolic computing with multivariate polynomials in R. + date_publication: '2020-02-20' + bug_reports: https://github.com/dkahle/mpoly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mpoly + url_git: https://github.com/dkahle/mpoly +mpower: + version: 0.1.0 + title: Power Analysis via Monte Carlo Simulation for Correlated Data + maintainer: Phuc H. Nguyen + description: |- + A flexible framework for power analysis using Monte + Carlo simulation for settings in which considerations of the correlations + between predictors are important. Users can set up a data generative model + that preserves dependence structures among predictors given existing data + (continuous, binary, or ordinal). Users can also generate power curves to + assess the trade-offs between sample size, effect size, and power of a design. + This package includes several statistical models common in environmental + mixtures studies. For more details and tutorials, see Nguyen et al. (2022) . + date_publication: '2022-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpower + url_git: '' +mppR: + version: 1.5.0 + title: Multi-Parent Population QTL Analysis + maintainer: Vincent Garin + description: |- + Analysis of experimental multi-parent populations to detect regions + of the genome (called quantitative trait loci, QTLs) influencing + phenotypic traits measured in unique and multiple environments. + The population must be composed of crosses between a set of at + least three parents (e.g. factorial design, 'diallel', or nested + association mapping). The functions cover data processing, + QTL detection, and results visualization. The implemented methodology + is described in Garin, Wimmer, Mezmouk, Malosetti and van Eeuwijk (2017) + , in Garin, Malosetti + and van Eeuwijk (2020) , + and in Garin, Diallo, Tekete, Thera, ..., and Rami (2024) . + date_publication: '2024-02-22' + bug_reports: https://github.com/vincentgarin/mppR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mppR + url_git: https://github.com/vincentgarin/mppR +mpr: + version: 1.0.6 + title: Multi-Parameter Regression (MPR) + maintainer: Kevin Burke + description: Fitting Multi-Parameter Regression (MPR) models to right-censored survival + data. These are flexible parametric regression models which extend standard models, + for example, proportional hazards. See Burke & MacKenzie (2016) + and Burke et al (2020) . + date_publication: '2022-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpr + url_git: '' +MPS: + version: 2.3.1 + title: Estimating Through the Maximum Product Spacing Approach + maintainer: Mahdi Teimouri + description: 'Developed for computing the probability density function, computing + the cumulative distribution function, computing the quantile function, random + generation, drawing q-q plot, and estimating the parameters of 24 G-family of + statistical distributions via the maximum product spacing approach introduced + in . The set of families contains: beta + G distribution, beta exponential G distribution, beta extended G distribution, + exponentiated G distribution, exponentiated exponential Poisson G distribution, + exponentiated generalized G distribution, exponentiated Kumaraswamy G distribution, + gamma type I G distribution, gamma type II G distribution, gamma uniform G distribution, + gamma-X generated of log-logistic family of G distribution, gamma-X family of + modified beta exponential G distribution, geometric exponential Poisson G distribution, + generalized beta G distribution, generalized transmuted G distribution, Kumaraswamy + G distribution, log gamma type I G distribution, log gamma type II G distribution, + Marshall Olkin G distribution, Marshall Olkin Kumaraswamy G distribution, modified + beta G distribution, odd log-logistic G distribution, truncated-exponential skew-symmetric + G distribution, and Weibull G distribution.' + date_publication: '2019-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPS + url_git: '' +MPSEM: + version: 0.5-1 + title: Modelling Phylogenetic Signals using Eigenvector Maps + maintainer: Guillaume Guénard + description: |- + Computational tools to represent phylogenetic signals using adapted + eigenvector maps. + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPSEM + url_git: '' +mpspline2: + version: 0.1.6 + title: Mass-Preserving Spline Functions for Soil Data + maintainer: Lauren O'Brien + description: |- + A low-dependency implementation of GSIF::mpspline() , + which applies a mass-preserving spline to soil attributes. Splining soil data + is a safe way to make continuous down-profile estimates of attributes measured + over discrete, often discontinuous depth intervals. + date_publication: '2022-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpspline2 + url_git: '' +MPsychoR: + version: 0.10-8 + title: Modern Psychometrics with R + maintainer: Patrick Mair + description: Supplementary materials and datasets for the book "Modern Psychometrics + With R" (Mair, 2018, Springer useR! series). + date_publication: '2020-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPsychoR + url_git: '' +mpt: + version: 1.0-0 + title: Multinomial Processing Tree Models + maintainer: Florian Wickelmaier + description: |- + Fitting and testing multinomial processing tree (MPT) models, a + class of nonlinear models for categorical data. The parameters are the + link probabilities of a tree-like graph and represent the latent cognitive + processing steps executed to arrive at observable response categories + (Batchelder & Riefer, 1999 ; Erdfelder et al., 2009 + ; Riefer & Batchelder, 1988 + ). + date_publication: '2024-10-11' + bug_reports: '' + url: https://www.mathpsy.uni-tuebingen.de/wickelmaier/ + url_cran: https://CRAN.R-project.org/package=mpt + url_git: '' +MPTinR: + version: 1.14.1 + title: Analyze Multinomial Processing Tree Models + maintainer: Henrik Singmann + description: Provides a user-friendly way for the analysis of multinomial processing + tree (MPT) models (e.g., Riefer, D. M., and Batchelder, W. H. [1988]. Multinomial + modeling and the measurement of cognitive processes. Psychological Review, 95, + 318-339) for single and multiple datasets. The main functions perform model fitting + and model selection. Model selection can be done using AIC, BIC, or the Fisher + Information Approximation (FIA) a measure based on the Minimum Description Length + (MDL) framework. The model and restrictions can be specified in external files + or within an R script in an intuitive syntax or using the context-free language + for MPTs. The 'classical' .EQN file format for model files is also supported. + Besides MPTs, this package can fit a wide variety of other cognitive models such + as SDT models (see fit.model). It also supports multicore fitting and FIA calculation + (using the snowfall package), can generate or bootstrap data for simulations, + and plot predicted versus observed data. + date_publication: '2021-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPTinR + url_git: '' +MPTmultiverse: + version: 0.4-2 + title: Multiverse Analysis of Multinomial Processing Tree Models + maintainer: Henrik Singmann + description: |2- + + Statistical or cognitive modeling usually requires a number of more or less + arbitrary choices creating one specific path through a 'garden of forking paths'. + The multiverse approach (Steegen, Tuerlinckx, Gelman, & Vanpaemel, 2016, + ) offers a principled alternative in which results + for all possible combinations of reasonable modeling choices are reported. + MPTmultiverse performs a multiverse analysis for multinomial processing tree + (MPT, Riefer & Batchelder, 1988, ) models combining + maximum-likelihood/frequentist and Bayesian estimation approaches with + different levels of pooling (i.e., data aggregation). For the + frequentist approaches, no pooling (with and without parametric or nonparametric + bootstrap) and complete pooling are implemented using + MPTinR . + For the Bayesian approaches, no pooling, complete pooling, and three different + variants of partial pooling are implemented using + TreeBUGS . The main function is + fit_mpt() who performs the multiverse analysis in one call. + date_publication: '2020-06-24' + bug_reports: https://github.com/mpt-network/MPTmultiverse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MPTmultiverse + url_git: https://github.com/mpt-network/MPTmultiverse +MPV: + version: '1.64' + title: Data Sets from Montgomery, Peck and Vining + maintainer: W.J. Braun + description: |- + Most of this package consists of data sets from the + textbook Introduction + to Linear Regression Analysis, by Montgomery, Peck + and Vining. All data sets from the 3rd edition are included + and many from the 6th edition are also included. + The package also contains some additional data sets and functions. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MPV + url_git: '' +mpwR: + version: 0.1.5 + title: |- + Standardized Comparison of Workflows in Mass Spectrometry-Based + Bottom-Up Proteomics + maintainer: Oliver Kardell + description: |- + Useful functions to analyze proteomic workflows including + number of identifications, data completeness, missed cleavages, + quantitative and retention time precision etc. Various software + outputs are supported such as 'ProteomeDiscoverer', 'Spectronaut', + 'DIA-NN' and 'MaxQuant'. + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mpwR + url_git: '' +MQMF: + version: 0.1.5 + title: Modelling and Quantitative Methods in Fisheries + maintainer: Malcolm Haddon + description: |- + Complements the book + "Using R for Modelling and Quantitative Methods in Fisheries" + ISBN 9780367469894, published in + 2021 by Chapman & Hall in their "Using R series". + There are numerous functions and data-sets that are used in the + book's many practical examples. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MQMF + url_git: https://github.com/haddonm/MQMF/ +Mqrcm: + version: '1.3' + title: M-Quantile Regression Coefficients Modeling + maintainer: Paolo Frumento + description: Parametric modeling of M-quantile regression coefficient functions. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mqrcm + url_git: '' +mr.pivw: + version: 0.1.1 + title: |- + Penalized Inverse-Variance Weighted Estimator for Mendelian + Randomization + maintainer: Siqi Xu + description: The penalized inverse-variance weighted (pIVW) estimator is a Mendelian + randomization method for estimating the causal effect of an exposure variable + on an outcome of interest based on summary-level GWAS data. The pIVW estimator + accounts for weak instruments and balanced horizontal pleiotropy simultaneously. + See Xu S., Wang P., Fung W.K. and Liu Z. (2022) . + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mr.pivw + url_git: '' +MR.RGM: + version: 0.0.3 + title: Multivariate Bidirectional Mendelian Randomization Networks + maintainer: Bitan Sarkar + description: Addressing a central challenge encountered in Mendelian randomization + (MR) studies, where MR primarily focuses on discerning the effects of individual + exposures on specific outcomes and establishes causal links between them. Using + a network-based methodology, the intricacy involving interdependent outcomes due + to numerous factors has been tackled through this routine. Based on Ni et al. + (2018) , 'MR.RGM' extends to a broader exploration of the + causal landscape by leveraging on network structures and involves the construction + of causal graphs that capture interactions between response variables and consequently + between responses and instrument variables. 'MR.RGM' facilitates the navigation + of various data availability scenarios effectively by accommodating three input + formats, i.e., individual-level data and two types of summary-level data. In the + process, causal effects, adjacency matrices, and other essential parameters of + the complex biological networks, are estimated. Besides, 'MR.RGM' provides uncertainty + quantification for specific network structures among response variables. + date_publication: '2024-09-18' + bug_reports: https://github.com/bitansa/MR.RGM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MR.RGM + url_git: https://github.com/bitansa/MR.RGM +mratios: + version: 1.4.4 + title: Ratios of Coefficients in the General Linear Model + maintainer: Frank Schaarschmidt + description: Performs (simultaneous) inferences for ratios of linear combinations + of coefficients in the general linear model, linear mixed model, and for quantiles + in a one-way layout. Multiple comparisons and simultaneous confidence interval + estimations can be performed for ratios of treatment means in the normal one-way + layout with homogeneous and heterogeneous treatment variances, according to Dilba + et al. (2007) and Hasler + and Hothorn (2008) . Confidence interval estimations + for ratios of linear combinations of linear model parameters like in (multiple) + slope ratio and parallel line assays can be carried out. Moreover, it is possible + to calculate the sample sizes required in comparisons with a control based on + relative margins. For the simple two-sample problem, functions for a t-test for + ratio-formatted hypotheses and the corresponding confidence interval are provided + assuming homogeneous or heterogeneous group variances. + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mratios + url_git: '' +mrbayes: + version: 0.5.2 + title: Bayesian Summary Data Models for Mendelian Randomization Studies + maintainer: Tom Palmer + description: |- + Bayesian estimation of inverse variance weighted (IVW), + Burgess et al. (2013) , and MR-Egger, Bowden + et al. (2015) , summary data models for + Mendelian randomization analyses. + date_publication: '2024-08-19' + bug_reports: https://github.com/okezie94/mrbayes/issues + url: https://okezie94.github.io/mrbayes/ + url_cran: https://CRAN.R-project.org/package=mrbayes + url_git: https://github.com/okezie94/mrbayes +mrbin: + version: 1.8.0 + title: Metabolomics Data Analysis Functions + maintainer: Matthias Klein + description: |- + A collection of functions for processing and analyzing metabolite data. + The namesake function mrbin() converts 1D + or 2D Nuclear Magnetic Resonance data into a matrix of values suitable for further data analysis and + performs basic processing steps in a reproducible way. Negative values, a + common issue in such data, can be replaced by positive values (). All used + parameters are stored in a readable text file and can be restored from that + file to enable exact reproduction of the data at a later time. The function fia() ranks features according + to their impact on classifier models, especially artificial neural network models. + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mrbin + url_git: https://github.com/kleinomicslab/mrbin +mrbsizeR: + version: '1.3' + title: Scale Space Multiresolution Analysis of Random Signals + maintainer: Roman Flury + description: |- + A method for the multiresolution analysis of spatial fields and images to capture scale-dependent features. + mrbsizeR is based on scale space smoothing and uses differences of smooths at neighbouring scales for finding features on different scales. + To infer which of the captured features are credible, Bayesian analysis is used. + The scale space multiresolution analysis has three steps: (1) Bayesian signal reconstruction. + (2) Using differences of smooths, scale-dependent features of the reconstructed signal can be found. + (3) Posterior credibility analysis of the differences of smooths created. + The method has first been proposed by Holmstrom, Pasanen, Furrer, Sain (2011) and extended in Flury, Gerber, Schmid and Furrer (2021) . + date_publication: '2024-02-14' + bug_reports: https://github.com/romanflury/mrbsizeR/issues + url: https://romanflury.github.io/mrbsizeR/ + url_cran: https://CRAN.R-project.org/package=mrbsizeR + url_git: https://github.com/romanflury/mrbsizeR +mRc: + version: 0.1.0 + title: Multi-Visit Closed Population Mark-Recapture Estimates + maintainer: Kyle Dettloff + description: Compute bootstrap confidence intervals for the adjusted Schnabel and + Schumacher-Eschmeyer multi-visit mark-recapture estimators based on Dettloff (2023) + . + date_publication: '2023-08-28' + bug_reports: https://github.com/k-dettloff/mRc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mRc + url_git: https://github.com/k-dettloff/mRc +MRCE: + version: '2.4' + title: Multivariate Regression with Covariance Estimation + maintainer: Adam J. Rothman + description: Compute and select tuning parameters for the MRCE estimator proposed + by Rothman, Levina, and Zhu (2010) . This estimator + fits the multiple output linear regression model with a sparse estimator of the + error precision matrix and a sparse estimator of the regression coefficient matrix. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRCE + url_git: '' +mrct: + version: 0.0.1.0 + title: |- + Outlier Detection of Functional Data Based on the Minimum + Regularized Covariance Trace Estimator + maintainer: Jeremy Oguamalam + description: Detect outlying observations in functional data sets based on the minimum + regularized covariance trace (MRCT) estimator. Includes implementation of Oguamalam + et al. (2023) . + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mrct + url_git: '' +MRCV: + version: 0.4-0 + title: |- + Methods for Analyzing Multiple Response Categorical Variables + (MRCVs) + maintainer: Chris Bilder + description: |- + Provides functions for analyzing the association between + one single response categorical variable (SRCV) and one multiple response + categorical variable (MRCV), or between two or three MRCVs. A modified Pearson + chi-square statistic can be used to test for marginal independence for the one or + two MRCV case, or a more general loglinear modeling approach can be used to examine + various other structures of association for the two or three MRCV case. Bootstrap- + and asymptotic-based standardized residuals and model-predicted odds ratios are + available, in addition to other descriptive information. Statisical methods implemented + are described in Bilder et al. (2000) , + Bilder and Loughin (2004) , + Bilder and Loughin (2007) , + and Koziol and Bilder (2014) . + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRCV + url_git: '' +mrds: + version: 3.0.0 + title: Mark-Recapture Distance Sampling + maintainer: Laura Marshall + description: |- + Animal abundance estimation via conventional, multiple covariate + and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function + fitting is performed via maximum likelihood. Also included are diagnostics + and plotting for fitted detection functions. Abundance estimation is via a + Horvitz-Thompson-like estimator. + date_publication: '2024-10-23' + bug_reports: https://github.com/DistanceDevelopment/mrds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mrds + url_git: https://github.com/DistanceDevelopment/mrds/ +mreg: + version: 1.2.1 + title: Fits Regression Models When the Outcome is Partially Missing + maintainer: Simon Bond + description: Implements the methods described in Bond S, Farewell V, 2006, Exact + Likelihood Estimation for a Negative Binomial Regression Model with Missing Outcomes, + Biometrics. + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mreg + url_git: https://github.com/shug0131/mreg +mrf: + version: 0.1.6 + title: Multiresolution Forecasting + maintainer: Quirin Stier + description: 'Forecasting of univariate time series using feature extraction with + variable prediction methods is provided. Feature extraction is done with a redundant + Haar wavelet transform with filter h = (0.5, 0.5). The advantage of the approach + compared to typical Fourier based methods is an dynamic adaptation to varying + seasonalities. Currently implemented prediction methods based on the selected + wavelets levels and scales are a regression and a multi-layer perceptron. Forecasts + can be computed for horizon 1 or higher. Model selection is performed with an + evolutionary optimization. Selection criteria are currently the AIC criterion, + the Mean Absolute Error or the Mean Root Error. The data is split into three parts + for model selection: Training, test, and evaluation dataset. The training data + is for computing the weights of a parameter set. The test data is for choosing + the best parameter set. The evaluation data is for assessing the forecast performance + of the best parameter set on new data unknown to the model. This work is published + in Stier, Q.; Gehlert, T.; Thrun, M.C. Multiresolution Forecasting for Industrial + Applications. Processes 2021, 9, 1697. .' + date_publication: '2022-02-23' + bug_reports: https://github.com/Quirinms/MRFR/issues + url: https://www.deepbionics.org + url_cran: https://CRAN.R-project.org/package=mrf + url_git: '' +mrf2d: + version: '1.0' + title: Markov Random Field Models for Image Analysis + maintainer: Victor Freguglia + description: |- + Model fitting, sampling and visualization + for the (Hidden) Markov Random Field model with pairwise interactions and + general interaction structure from + Freguglia, Garcia & Bicas (2020) , + which has many popular models used in 2-dimensional lattices + as particular cases, like the Ising Model and Potts Model. + A complete manuscript describing the package is available in + Freguglia & Garcia (2022) . + date_publication: '2022-01-25' + bug_reports: https://github.com/Freguglia/mrf2d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mrf2d + url_git: https://github.com/Freguglia/mrf2d +MRFA: + version: '0.6' + title: |- + Fitting and Predicting Large-Scale Nonlinear Regression Problems + using Multi-Resolution Functional ANOVA (MRFA) Approach + maintainer: Chih-Li Sung + description: |- + Performs the MRFA approach proposed by Sung et al. (2020) to fit + and predict nonlinear regression problems, particularly for large-scale and + high-dimensional problems. The application includes deterministic or stochastic + computer experiments, spatial datasets, and so on. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRFA + url_git: '' +MRFcov: + version: 1.0.39 + title: Markov Random Fields with Additional Covariates + maintainer: Nicholas J Clark + description: |- + Approximate node interaction parameters of Markov Random Fields + graphical networks. Models can incorporate additional covariates, allowing users to estimate + how interactions between nodes in the graph are predicted to change across + covariate gradients. The general methods implemented in this package are described + in Clark et al. (2018) . + date_publication: '2023-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRFcov + url_git: https://github.com/nicholasjclark/MRFcov +mrfDepth: + version: 1.0.17 + title: |- + Depth Measures in Multivariate, Regression and Functional + Settings + maintainer: Jakob Raymaekers + description: |- + Tools to compute depth measures and implementations of related + tasks such as outlier detection, data exploration and + classification of multivariate, regression and functional data. + date_publication: '2024-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mrfDepth + url_git: '' +mrfse: + version: 0.4.2 + title: Markov Random Field Structure Estimator + maintainer: Rodrigo Carvalho + description: Three algorithms for estimating a Markov random field structure.Two + of them are an exact version and a simulated annealing version of a penalized + maximum conditional likelihood method similar to the Bayesian Information Criterion. + These algorithm are described in Frondana (2016) .The + third one is a greedy algorithm, described in Bresler (2015) model using a parallel backend. + Input data sets are split (chunked) and simulated in parallel using + mclapply() or future_lapply() + . + date_publication: '2022-03-17' + bug_reports: https://github.com/kylebaron/mrgsim.parallel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mrgsim.parallel + url_git: https://github.com/kylebaron/mrgsim.parallel +mrgsim.sa: + version: 0.2.0 + title: Sensitivity Analysis with 'mrgsolve' + maintainer: Kyle Baron + description: |- + Perform sensitivity analysis on ordinary differential equation + based models, including ad-hoc graphical analyses based on structured + sequences of parameters as well as local sensitivity analysis. Functions + are provided for creating inputs, simulating scenarios and plotting outputs. + date_publication: '2023-12-08' + bug_reports: https://github.com/kylebaron/mrgsim.sa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mrgsim.sa + url_git: https://github.com/kylebaron/mrgsim.sa +mrgsolve: + version: 1.5.2 + title: Simulate from ODE-Based Models + maintainer: Kyle T Baron + description: |- + Fast simulation from ordinary differential equation + (ODE) based models typically employed in quantitative pharmacology and + systems biology. + date_publication: '2024-10-18' + bug_reports: https://github.com/metrumresearchgroup/mrgsolve/issues + url: https://mrgsolve.org/docs/ + url_cran: https://CRAN.R-project.org/package=mrgsolve + url_git: https://github.com/metrumresearchgroup/mrgsolve +MRHawkes: + version: '1.0' + title: Multivariate Renewal Hawkes Process + maintainer: Tom Stindl + description: |- + Simulate a (bivariate) multivariate renewal Hawkes (MRHawkes) + self-exciting process, with given immigrant hazard rate functions and + offspring density function. Calculate the likelihood of a MRHawkes process + with given hazard rate functions and offspring density function for an + (increasing) sequence of event times. Calculate the Rosenblatt residuals of the + event times. Predict future event times based on observed event times up to a + given time. For details see Stindl and Chen (2018) . + date_publication: '2018-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRHawkes + url_git: '' +mri: + version: 1.0.1 + title: Modified Rand and Wallace Indices + maintainer: Marjan Cugmas + description: It provides functions to compute the values of different modifications + of the Rand and Wallace indices. The indices are used to measure the stability + or similarity of two partitions obtained on two different sets of units with a + non-empty intercept. Splitting and merging of clusters can (depends on the selected + index) have a different effect on the value of the indices. The indices are proposed + in Cugmas and Ferligoj (2018) . + date_publication: '2019-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mri + url_git: '' +mritc: + version: 0.5-3 + title: MRI Tissue Classification + maintainer: Jon Clayden + description: |- + Implements various methods for tissue classification in magnetic + resonance (MR) images of the brain, including normal mixture models + and hidden Markov normal mixture models, as outlined in Feng & + Tierney (2011) . These methods allow a + structural MR image to be classified into gray matter, white matter + and cerebrospinal fluid tissue types. + date_publication: '2023-01-27' + bug_reports: https://github.com/jonclayden/mritc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mritc + url_git: https://github.com/jonclayden/mritc +MRMCaov: + version: 0.3.0 + title: Multi-Reader Multi-Case Analysis of Variance + maintainer: Brian J Smith + description: |- + Estimation and comparison of the performances of diagnostic tests + in multi-reader multi-case studies where true case statuses (or ground + truths) are known and one or more readers provide test ratings for multiple + cases. Reader performance metrics are provided for area under and expected + utility of ROC curves, likelihood ratio of positive or negative tests, and + sensitivity and specificity. ROC curves can be estimated empirically or + with binormal or binormal likelihood-ratio models. Statistical comparisons + of diagnostic tests are based on the ANOVA model of Obuchowski-Rockette and + the unified framework of Hillis (2005) . The ANOVA + can be conducted with data from a full factorial, nested, or partially + paired study design; with random or fixed readers or cases; and covariances + estimated with the DeLong method, jackknifing, or an unbiased method. Smith + and Hillis (2020) . + date_publication: '2023-01-10' + bug_reports: https://github.com/brian-j-smith/MRMCaov/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MRMCaov + url_git: https://github.com/brian-j-smith/MRMCaov +MRMCbinary: + version: 1.0.5 + title: Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests + maintainer: Seungjae Lee + description: The goal of 'MRMCbinary' is to compare the performance of diagnostic + tests (i.e., sensitivity and specificity) for binary outcomes in multi-reader + multi-case (MRMC) studies. It is based on conditional logistic regression and + Cochran’s Q test (or McNemar’s test when the number of modalities is equal to + 2). + date_publication: '2025-02-20' + bug_reports: https://github.com/seungjae2525/MRMCbinary/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MRMCbinary + url_git: https://github.com/seungjae2525/MRMCbinary +MRMCsamplesize: + version: 1.0.0 + title: |- + Sample Size Estimations for Planning Multi-Reader Multi-Case + (MRMC) Studies Without Pilot Data + maintainer: Dennis Robert + description: |- + Sample size estimations for MRMC studies based on the Obuchowski-Rockette (OR) methodology is implemented. The function can calculate sample sizes where the + endpoint of interest in the study is either ROC AUC (Area-Under-the-Receiver-Operating-Characteristics-Curve) or sensitivity. The package can also return sample sizes for studies + expected to have clustering effect (e.g.- multiple pulmonary nodules per patient). All calculations assume that the study design is fully crossed (paired-reader, paired-case) where + each reader reads/interprets each case and that there are two interventions/imaging-modalities/techniques in the study. In addition to MRMC, it can also be used to estimate sample sizes + for standalone studies where sensitivity or AUC are the primary endpoints. + The methods implemented are based on the methods described in Zhou et.al. (2011) and Obuchowski (2000) . + date_publication: '2023-08-18' + bug_reports: https://github.com/technOslerphile/MRMCsamplesize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MRMCsamplesize + url_git: https://github.com/technOslerphile/MRMCsamplesize +MRmediation: + version: 1.0.1 + title: |- + A Causal Mediation Method with Methylated Region (MR) as the + Mediator + maintainer: Qi Yan + description: |- + A causal mediation approach under the counterfactual framework + to test the significance of total, direct and indirect effects. In this approach, + a group of methylated sites from a predefined region are utilized as the mediator, + and the functional transformation is used to reduce the possible high dimension + in the region-based methylated sites and account for their location information. + date_publication: '2020-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRmediation + url_git: '' +mrMLM: + version: 5.0.1 + title: Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for GWAS + maintainer: Yuan-Ming Zhang + description: Conduct multi-locus genome-wide association study under the framework + of multi-locus random-SNP-effect mixed linear model (mrMLM). First, each marker + on the genome is scanned. Bonferroni correction is replaced by a less stringent + selection criterion for significant test. Then, all the markers that are potentially + associated with the trait are included in a multi-locus genetic model, their effects + are estimated by empirical Bayes, and all the nonzero effects were further identified + by likelihood ratio test for significant QTL. The program may run on a desktop + or laptop computers. If marker genotypes in association mapping population are + almost homozygous, these methods in this software are very effective. If there + are many heterozygous marker genotypes, the IIIVmrMLM software is recommended. + Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, Wang SB, Dunwell JM, Zhang + YM, Wu R (2018, ), and Li M, Zhang YW, Zhang ZC, Xiang + Y, Liu MH, Zhou YH, Zuo JF, Zhang HQ, Chen Y, Zhang YM (2022, ). + date_publication: '2022-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mrMLM + url_git: '' +mrMLM.GUI: + version: 4.0.2 + title: |- + Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for + Genome-Wide Association Study with Graphical User Interface + maintainer: Yuanming Zhang + description: Conduct multi-locus genome-wide association study under the framework + of multi-locus random-SNP-effect mixed linear model (mrMLM). First, each marker + on the genome is scanned. Bonferroni correction is replaced by a less stringent + selection criterion for significant test. Then, all the markers that are potentially + associated with the trait are included in a multi-locus genetic model, their effects + are estimated by empirical Bayes and all the nonzero effects were further identified + by likelihood ratio test for true QTL. Wen YJ, Zhang H, Ni YL, Huang B, Zhang + J, Feng JY, Wang SB, Dunwell JM, Zhang YM, Wu R (2018) . + date_publication: '2020-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mrMLM.GUI + url_git: '' +mRMRe: + version: 2.1.2.2 + title: Parallelized Minimum Redundancy, Maximum Relevance (mRMR) + maintainer: Benjamin Haibe-Kains + description: |- + Computes mutual information matrices from continuous, categorical + and survival variables, as well as feature selection with minimum redundancy, + maximum relevance (mRMR) and a new ensemble mRMR technique. Published in + De Jay et al. (2013) . + date_publication: '2024-11-05' + bug_reports: '' + url: https://www.pmgenomics.ca/bhklab/ + url_cran: https://CRAN.R-project.org/package=mRMRe + url_git: '' +mro: + version: 0.1.1 + title: Multiple Correlation + maintainer: Abirami S + description: Computes multiple correlation coefficient when the data matrix is given + and tests its significance. + date_publication: '2017-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mro + url_git: '' +MRPC: + version: 3.1.0 + title: PC Algorithm with the Principle of Mendelian Randomization + maintainer: Audrey Fu + description: |- + A PC Algorithm with the Principle of Mendelian Randomization. This package implements the MRPC + (PC with the principle of Mendelian randomization) algorithm to infer causal graphs. It also + contains functions to simulate data under a certain topology, to visualize a graph in different + ways, and to compare graphs and quantify the differences. + See Badsha and Fu (2019) ,Badsha, Martin and Fu (2021) . + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRPC + url_git: '' +mRpostman: + version: 1.1.4 + title: An IMAP Client for R + maintainer: Allan Quadros + description: |- + An easy-to-use IMAP client that provides tools for message searching, + selective fetching of message attributes, mailbox management, attachment extraction, + and several other IMAP features, paving the way for e-mail data analysis in R. + date_publication: '2024-09-17' + bug_reports: https://github.com/allanvc/mRpostman/issues/ + url: https://allanvc.github.io/mRpostman/ + url_cran: https://CRAN.R-project.org/package=mRpostman + url_git: '' +MRQoL: + version: '1.0' + title: |- + Minimal Clinically Important Difference and Response Shift + Effect for Health-Related Quality of Life + maintainer: Ahmad Ousmen + description: We can calculate directly used this package the Minimal Clinically + Important Difference by applying the Anchor-based method and the Response shift + effect by applying the Then-Test method. + date_publication: '2015-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRQoL + url_git: '' +MRReg: + version: 0.1.5 + title: MDL Multiresolution Linear Regression Framework + maintainer: Chainarong Amornbunchornvej + description: We provide the framework to analyze multiresolution partitions (e.g. + country, provinces, subdistrict) where each individual data point belongs to only + one partition in each layer (e.g. i belongs to subdistrict A, province P, and + country Q). We assume that a partition in a higher layer subsumes lower-layer + partitions (e.g. a nation is at the 1st layer subsumes all provinces at the 2nd + layer). Given N individuals that have a pair of real values (x,y) that generated + from independent variable X and dependent variable Y. Each individual i belongs + to one partition per layer. Our goal is to find which partitions at which highest + level that all individuals in the these partitions share the same linear model + Y=f(X) where f is a linear function. The framework deploys the Minimum Description + Length principle (MDL) to infer solutions. The publication of this package is + at Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, and + Suttipong Thajchayapong (2021) . + date_publication: '2022-08-19' + bug_reports: https://github.com/DarkEyes/MRReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MRReg + url_git: https://github.com/DarkEyes/MRReg +mrregression: + version: 1.0.0 + title: |- + Regression Analysis for Very Large Data Sets via Merge and + Reduce + maintainer: Leo N. Geppert + description: |- + Frequentist and Bayesian linear regression for large data sets. Useful + when the data does not fit into memory (for both frequentist and Bayesian regression), + to make running time manageable (mainly for Bayesian regression), and to reduce + the total running time because of reduced or less severe memory-spillover into + the virtual memory. This is an implementation of Merge & Reduce for linear regression + as described in Geppert, L.N., Ickstadt, K., Munteanu, A., & Sohler, C. (2020). + 'Streaming statistical models via Merge & Reduce'. International Journal of + Data Science and Analytics, 1-17, . + date_publication: '2020-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mrregression + url_git: '' +MRTAnalysis: + version: 0.1.2 + title: Primary and Secondary Analyses for Micro-Randomized Trials + maintainer: Tianchen Qian + description: |2- + + Estimates marginal causal excursion effects and moderated causal excursion effects for micro-randomized trial (MRT). Applicable to MRT with binary treatment options and continuous or binary outcomes. The method for MRT with continuous outcomes is the weighted centered least squares (WCLS) by Boruvka et al. (2018) . The method for MRT with binary outcomes is the estimator for marginal excursion effect (EMEE) by Qian et al. (2021) . + date_publication: '2023-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRTAnalysis + url_git: '' +MRTSampleSize: + version: 0.3.0 + title: A Sample Size Calculator for Micro-Randomized Trials + maintainer: Peng Liao + description: Provide a sample size calculator for micro-randomized trials (MRTs) + based on methodology developed in Sample Size Calculations for Micro-randomized + Trials in mHealth by Liao et al. (2016) . + date_publication: '2020-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRTSampleSize + url_git: '' +MRTSampleSizeBinary: + version: 0.1.2 + title: Sample Size Calculator for MRT with Binary Outcomes + maintainer: Tianchen Qian + description: Provides a sample size calculator for micro-randomized trials (MRTs) + with binary outcomes based on Cohn et al. (2023) . Also + provides a power calculator when the sample size is input by the user. + date_publication: '2023-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRTSampleSizeBinary + url_git: '' +MRZero: + version: 0.2.0 + title: Diet Mendelian Randomization + maintainer: Stephen Burgess + description: Encodes several methods for performing Mendelian randomization analyses + with summarized data. Similar to the 'MendelianRandomization' package, but with + fewer bells and whistles, and less frequent updates. As described in Yavorska + (2017) and Broadbent (2020) . + date_publication: '2024-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MRZero + url_git: '' +msae: + version: 0.1.5 + title: Multivariate Fay Herriot Models for Small Area Estimation + maintainer: Novia Permatasari + description: Implements multivariate Fay-Herriot models for small area estimation. + It uses empirical best linear unbiased prediction (EBLUP) estimator. Multivariate + models consider the correlation of several target variables and borrow strength + from auxiliary variables to improve the effectiveness of a domain sample size. + Models which accommodated by this package are univariate model with several target + variables (model 0), multivariate model (model 1), autoregressive multivariate + model (model 2), and heteroscedastic autoregressive multivariate model (model + 3). Functions provide EBLUP estimators and mean squared error (MSE) estimator + for each model. These models were developed by Roberto Benavent and Domingo Morales + (2015) . + date_publication: '2022-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msae + url_git: '' +msaeHB: + version: 0.1.0 + title: |- + Multivariate Small Area Estimation using Hierarchical Bayesian + Method + maintainer: Novia Permatasari + description: Implements area level of multivariate small area estimation using Hierarchical + Bayesian method under Normal and T distribution. The 'rjags' package is employed + to obtain parameter estimates. For the reference, see Rao and Molina (2015) . + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msaeHB + url_git: '' +msaenet: + version: 3.1.2 + title: Multi-Step Adaptive Estimation Methods for Sparse Regressions + maintainer: Nan Xiao + description: |- + Multi-step adaptive elastic-net (MSAENet) algorithm for + feature selection in high-dimensional regressions proposed in + Xiao and Xu (2015) , + with support for multi-step adaptive MCP-net (MSAMNet) and + multi-step adaptive SCAD-net (MSASNet) methods. + date_publication: '2024-05-11' + bug_reports: https://github.com/nanxstats/msaenet/issues + url: https://nanx.me/msaenet/ + url_cran: https://CRAN.R-project.org/package=msaenet + url_git: https://github.com/nanxstats/msaenet +msaFACE: + version: 0.1.0 + title: Moving Subset Analysis FACE + maintainer: Lukas W. Lehnert + description: The new methodology "moving subset analysis" provides functions to + investigate the effect of environmental conditions on the CO2 fertilization effect + within longterm free air carbon enrichment (FACE) experiments. In general, the + functionality is applicable to derive the influence of a third variable (forcing + experiment-support variable) on the relation between a dependent and an independent + variable. + date_publication: '2016-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msaFACE + url_git: '' +msamp: + version: 1.0.0 + title: |- + Estimate Sample Size to Detect Bacterial Contamination in a + Product Lot + maintainer: Martine Ferguson + description: |- + Estimates the sample size needed to detect microbial contamination + in a lot with a user-specified detection probability and user-specified analytical sensitivity. + Various patterns of microbial contamination are accounted for: homogeneous (Poisson), + heterogeneous (Poisson-Gamma) or localized(Zero-inflated Poisson). + Ida Jongenburger et al. (2010) + "Impact of microbial distributions on food safety". + Leroy Simon (1963) + "Casualty Actuarial Society - The Negative Binomial and Poisson Distributions Compared". + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msamp + url_git: '' +msaR: + version: 0.6.0 + title: Multiple Sequence Alignment for R Shiny + maintainer: Zachary Charlop-Powers + description: |- + Visualizes multiple sequence alignments dynamically within the + Shiny web application framework. + date_publication: '2021-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msaR + url_git: '' +MSbox: + version: 1.4.8 + title: Mass Spectrometry Tools + maintainer: Yonghui Dong + description: |- + Common mass spectrometry tools described in John Roboz (2013) . It allows checking element + isotopes, calculating (isotope labelled) exact monoisitopic mass, m/z values and mass accuracy, and inspecting possible contaminant mass peaks, + examining possible adducts in electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI) + ion sources. + date_publication: '2022-12-08' + bug_reports: https://github.com/YonghuiDong/MSbox/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=MSbox + url_git: https://github.com/YonghuiDong/MSbox +MSBStatsData: + version: 0.0.2 + title: Data Sets for Courses at the Münster School of Business + maintainer: Michael Bücker + description: Provides sample data sets that are used in statistics and data science + courses at the Münster School of Business. The datasets refer to different business + topics but also other domains, e.g. sports, traffic, etc. + date_publication: '2024-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSBStatsData + url_git: '' +MSCA: + version: '1.0' + title: Clustering of Multiple Censored Time-to-Event Endpoints + maintainer: Marc Delord + description: 'Provides basic tools for computing clusters of instances described + by multiple time-to-event censored endpoints. From long-format datasets, where + one instance is described by one or more records of events, a procedure is used + to compute state matrices. Then, from state matrices, a procedure provides optimised + computation of the Jaccard distance between instances. The library is currently + in development, and more options and tools allowing graphical representation of + typologies are expected. For methodological details, see our methodological paper: + Delord M, Douiri A (2025) .' + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSCA + url_git: '' +msce: + version: 1.0.1 + title: Hazard of Multi-Stage Clonal Expansion Models + maintainer: Cristoforo Simonetto + description: Functions to calculate hazard and survival function of Multi-Stage + Clonal Expansion Models used in cancer epidemiology. For the Two-Stage Clonal + Expansion Model an exact solution is implemented assuming piecewise constant parameters. + Numerical solutions are provided for its extensions. + date_publication: '2020-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msce + url_git: '' +mschart: + version: 0.4.0 + title: |- + Chart Generation for 'Microsoft Word' and 'Microsoft PowerPoint' + Documents + maintainer: David Gohel + description: |- + Create native charts for 'Microsoft PowerPoint' and 'Microsoft Word' documents. + These can then be edited and annotated. Functions are provided to let users create charts, modify + and format their content. The chart's underlying data is automatically saved within the + 'Word' document or 'PowerPoint' presentation. It extends package 'officer' that does + not contain any feature for 'Microsoft' native charts production. + date_publication: '2022-11-30' + bug_reports: https://github.com/ardata-fr/mschart/issues + url: https://ardata-fr.github.io/officeverse/ + url_cran: https://CRAN.R-project.org/package=mschart + url_git: '' +MSclassifR: + version: 0.3.3 + title: Automated Classification of Mass Spectra + maintainer: Alexandre Godmer + description: 'Functions to classify mass spectra in known categories, and to determine + discriminant mass-over-charge values. It includes easy-to-use functions for pre-processing + mass spectra, functions to determine discriminant mass-over-charge values (m/z) + from a library of mass spectra corresponding to different categories, and functions + to predict the category (species, phenotypes, etc.) associated to a mass spectrum + from a list of selected mass-over-charge values. Three vignettes illustrating + how to use the functions of this package from real data sets are also available + online to help users: , + + and .' + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSclassifR + url_git: https://github.com/agodmer/MSclassifR_examples +MSclust: + version: 1.0.4 + title: Multiple-Scaled Clustering + maintainer: Cristina Tortora + description: |- + Model based clustering using + the multivariate multiple Scaled t (MST) and multivariate multiple + scaled contaminated normal (MSCN) distributions. The MST is an + extension of the multivariate Student-t distribution to include + flexible tail behaviors, Forbes, F. & Wraith, D. (2014) . The MSCN represents a heavy-tailed + generalization of the multivariate normal (MN) distribution to + model elliptical contoured scatters in the presence of mild outliers + (also referred to as "bad" points) and automatically detect bad points, Punzo, A. & Tortora, C. (2021) . + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSclust + url_git: '' +MSCMT: + version: 1.4.0 + title: Multivariate Synthetic Control Method Using Time Series + maintainer: Martin Becker + description: |- + Three generalizations of the synthetic control method (which has + already an implementation in package 'Synth') are implemented: first, + 'MSCMT' allows for using multiple outcome variables, second, time series + can be supplied as economic predictors, and third, a well-defined + cross-validation approach can be used. + Much effort has been taken to make the implementation as stable as possible + (including edge cases) without losing computational efficiency. + A detailed description of the main algorithms is given in + Becker and Klößner (2018) . + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSCMT + url_git: '' +MScombine: + version: '1.4' + title: |- + Combine Data from Positive and Negative Ionization Mode Finding + Common Entities + maintainer: Monica Calderon-Santiago + description: |- + Find common entities detected in both positive and negative + ionization mode, delete this entity in the less sensible mode and combine both + matrices. + date_publication: '2019-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MScombine + url_git: '' +mscp: + version: '1.0' + title: |- + Multiscale Change Point Detection via Gradual Bandwidth + Adjustment in Moving Sum Processes + maintainer: Michael Messer + description: Multiscale moving sum procedure for the detection of changes in expectation + in univariate sequences. References - Multiscale change point detection via gradual + bandwidth adjustment in moving sum processes (2021+), Tijana Levajkovic and Michael + Messer. + date_publication: '2021-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mscp + url_git: '' +MSCquartets: + version: '3.0' + title: Analyzing Gene Tree Quartets under the Multi-Species Coalescent + maintainer: John Rhodes + description: |- + Methods for analyzing and using quartets displayed on a collection + of gene trees, primarily to make inferences about the species tree or network + under the multi-species coalescent model. These include quartet hypothesis tests + for the model, as developed by Mitchell et al. (2019) , + simplex plots of quartet concordance factors as presented by Allman et al. (2020) + , species tree inference methods based on quartet + distances of Rhodes (2019) and Yourdkhani and + Rhodes (2019) , the NANUQ algorithm for inference + of level-1 species networks of Allman et al. (2019) , + the TINNIK algorithm for inference of the tree of blobs of an arbitrary + network of Allman et al.(2022) , and + NANUQ+ routines for resolving multifurcations in the tree of blobs to cycles as in + Allman et al.(2024) (forthcoming). + Software announcement by Rhodes et al. (2020) . + date_publication: '2024-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSCquartets + url_git: '' +MSCsimtester: + version: 1.0.0 + title: Tests of Multispecies Coalescent Gene Tree Simulator Output + maintainer: Elizabeth Allman + description: Statistical tests for validating multispecies coalescent gene tree + simulators, using pairwise distances and rooted triple counts. Background is given + by Allman, Banos, and Rhodes (2019) . + date_publication: '2021-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSCsimtester + url_git: '' +mscstexta4r: + version: 0.1.2 + title: |- + R Client for the Microsoft Cognitive Services Text Analytics + REST API + maintainer: Phil Ferriere + description: |- + R Client for the Microsoft Cognitive Services Text Analytics + REST API, including Sentiment Analysis, Topic Detection, Language Detection, + and Key Phrase Extraction. An account MUST be registered at the Microsoft + Cognitive Services website + in order to obtain a (free) API key. Without an API key, this package will + not work properly. + date_publication: '2016-06-23' + bug_reports: http://www.github.com/philferriere/mscstexta4r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mscstexta4r + url_git: https://github.com/philferriere/mscstexta4r +mscstts: + version: 0.6.3 + title: |- + R Client for the Microsoft Cognitive Services 'Text-to-Speech' + REST API + maintainer: John Muschelli + description: |- + R Client for the Microsoft Cognitive Services + 'Text-to-Speech' REST API, including voice synthesis. A valid account + must be registered at the Microsoft Cognitive Services website + in order to + obtain a (free) API key. Without an API key, this package will not + work properly. + date_publication: '2022-06-10' + bug_reports: https://github.com/muschellij2/mscstts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mscstts + url_git: https://github.com/muschellij2/mscstts +mscsweblm4r: + version: 0.1.2 + title: |- + R Client for the Microsoft Cognitive Services Web Language Model + REST API + maintainer: Phil Ferriere + description: |- + R Client for the Microsoft Cognitive Services Web Language Model + REST API, including Break Into Words, Calculate Conditional + Probability, Calculate Joint Probability, Generate Next Words, and List + Available Models. A valid account MUST be registered at the Microsoft + Cognitive Services website + in order to obtain a (free) API key. Without an API key, this package will + not work properly. + date_publication: '2016-06-15' + bug_reports: http://www.github.com/philferriere/mscsweblm4r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mscsweblm4r + url_git: https://github.com/philferriere/mscsweblm4r +msd: + version: 0.3.1 + title: Method of Successive Dichotomizations + maintainer: Chris Bradley + description: |- + Implements the method of successive dichotomizations by + Bradley and Massof (2018) , + which estimates item measures, person measures and ordered rating + category thresholds given ordinal rating scale data. + date_publication: '2021-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msd + url_git: '' +msde: + version: 1.0.5 + title: |- + Bayesian Inference for Multivariate Stochastic Differential + Equations + maintainer: Martin Lysy + description: Implements an MCMC sampler for the posterior distribution of arbitrary + time-homogeneous multivariate stochastic differential equation (SDE) models with + possibly latent components. The package provides a simple entry point to integrate + user-defined models directly with the sampler's C++ code, and parallelizes large + portions of the calculations when compiled with 'OpenMP'. + date_publication: '2021-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msde + url_git: '' +msdrought: + version: 0.1.0 + title: Seasonal Mid-Summer Drought Characteristics + maintainer: Ed Maurer + description: |- + Characterization of a mid-summer drought (MSD) with precipitation + based statistics. The MSD is a phenomenon of decreased rainfall during a + typical rainy season. It is a feature of rainfall in much of Central America + and is also found in other locations, typically those with a Mediterranean + climate. Details on the metrics are in Maurer et al. (2022) + . + date_publication: '2024-05-27' + bug_reports: https://github.com/Turner-SCU/msdrought/issues + url: https://turner-scu.github.io/msdrought/ + url_cran: https://CRAN.R-project.org/package=msdrought + url_git: https://github.com/Turner-SCU/msdrought +mseapca: + version: 2.0.3 + title: Metabolite Set Enrichment Analysis for Loadings + maintainer: Hiroyuki Yamamoto + description: Computing metabolite set enrichment analysis (MSEA) (Yamamoto, H. et + al. (2014) ) and single sample enrichment analysis + (SSEA) (Yamamoto, H. (2023) ). + date_publication: '2023-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mseapca + url_git: '' +msentropy: + version: 0.1.4 + title: Spectral Entropy for Mass Spectrometry Data + maintainer: Yuanyue Li + description: 'Clean the MS/MS spectrum, calculate spectral entropy, unweighted entropy + similarity, and entropy similarity for mass spectrometry data. The entropy similarity + is a novel similarity measure for MS/MS spectra which outperform the widely used + dot product similarity in compound identification. For more details, please refer + to the paper: Yuanyue Li et al. (2021) "Spectral entropy outperforms MS/MS dot + product similarity for small-molecule compound identification" .' + date_publication: '2023-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msentropy + url_git: https://github.com/YuanyueLi/MSEntropy +MSEtool: + version: 3.7.3 + title: Management Strategy Evaluation Toolkit + maintainer: Adrian Hordyk + description: |- + Development, simulation testing, and implementation of management procedures for fisheries + (see Carruthers & Hordyk (2018) ). + date_publication: '2024-11-22' + bug_reports: https://github.com/Blue-Matter/MSEtool/issues + url: https://msetool.openmse.com/ + url_cran: https://CRAN.R-project.org/package=MSEtool + url_git: '' +MSG: + version: '0.8' + title: Data and Functions for the Book Modern Statistical Graphics + maintainer: Yihui Xie + description: A companion to the Chinese book ``Modern Statistical Graphics''. + date_publication: '2021-07-21' + bug_reports: https://github.com/yihui/MSG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MSG + url_git: https://github.com/yihui/MSG +MSGARCH: + version: '2.51' + title: Markov-Switching GARCH Models + maintainer: Keven Bluteau + description: Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast + various Markov-Switching GARCH models as described in Ardia et al. (2019) . + date_publication: '2022-12-05' + bug_reports: https://github.com/keblu/MSGARCH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MSGARCH + url_git: https://github.com/keblu/MSGARCH +MSGARCHelm: + version: 0.1.0 + title: Hybridization of MS-GARCH and ELM Model + maintainer: Rajeev Ranjan Kumar + description: Implements the three parallel forecast combinations of Markov Switching + GARCH and extreme learning machine model along with the selection of appropriate + model for volatility forecasting. For method details see Hsiao C, Wan SK (2014). + , Hansen BE (2007). , + Elliott G, Gargano A, Timmermann A (2013). . + date_publication: '2020-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSGARCHelm + url_git: '' +msgps: + version: 1.3.5 + title: |- + Degrees of Freedom of Elastic Net, Adaptive Lasso and + Generalized Elastic Net + maintainer: Kei Hirose + description: |- + Computes the degrees of freedom of the lasso, + elastic net, generalized elastic net and adaptive lasso based + on the generalized path seeking algorithm. The optimal model + can be selected by model selection criteria including Mallows' + Cp, bias-corrected AIC (AICc), generalized cross validation + (GCV) and BIC. + date_publication: '2022-10-20' + bug_reports: '' + url: https://keihirose.com/ + url_cran: https://CRAN.R-project.org/package=msgps + url_git: '' +msgr: + version: 1.1.2 + title: |- + Extends Messages, Warnings and Errors by Adding Levels and Log + Files + maintainer: Chad Goymer + description: |- + Provides new functions info(), warn() and error(), similar to message(), + warning() and stop() respectively. However, the new functions can have a 'level' + associated with them, so that when executed the global level option determines whether + they are shown or not. This allows debug modes, outputting more information. The can also + output all messages to a log file. + date_publication: '2019-12-16' + bug_reports: https://github.com/ChadGoymer/msgr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=msgr + url_git: https://github.com/ChadGoymer/msgr +mshap: + version: 0.1.0 + title: Multiplicative SHAP Values for Two-Part Models + maintainer: Spencer Matthews + description: |- + Allows for the computation of mSHAP values on + two-part models as proposed by Matthews, S. and Hartman, B. + (2021) . + Also contains functions for simple plotting of + the results (or any SHAP values). For information about the + TreeSHAP algorithm that mSHAP builds on, see Lundberg, S.M., + Erion, G., Chen, H., DeGrave, A., Prutkin, J.M., Nair, B., Katz, + R., Himmelfarb, J., Bansal, N., Lee, S.I. (2020) + . + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mshap + url_git: '' +msig: + version: '1.0' + title: An R Package for Exploring Molecular Signatures Database + maintainer: Jing Zhang + description: |- + The Molecular Signatures Database ('MSigDB') is one of the most widely + used and comprehensive databases of gene sets for performing gene set + enrichment analysis . The 'msig' package provides + you with powerful, easy-to-use and flexible query functions for the 'MsigDB' + database. + There are 2 query modes in the 'msig' package: online query and local query. + Both queries contain 2 steps: gene set name and gene. + The online search is divided into 2 modes: registered search and + non-registered browse. For registered search, email that you registered should + be provided. + Local queries can be made from local database, which can be updated by msig_update() function. + date_publication: '2021-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msig + url_git: '' +msigdbr: + version: 7.5.1 + title: MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format + maintainer: Igor Dolgalev + description: |- + Provides the 'Molecular Signatures Database' (MSigDB) gene + sets typically used with the 'Gene Set Enrichment Analysis' (GSEA) + software (Subramanian et al. 2005 , + Liberzon et al. 2015 ) in a standard R + data frame with key-value pairs. The package includes the human genes + as listed in MSigDB as well as the corresponding symbols and IDs for + frequently studied model organisms such as mouse, rat, pig, fly, and + yeast. + date_publication: '2022-03-30' + bug_reports: https://github.com/igordot/msigdbr/issues + url: https://igordot.github.io/msigdbr/ + url_cran: https://CRAN.R-project.org/package=msigdbr + url_git: '' +MSigSeg: + version: 0.2.0 + title: Multiple SIGnal SEGmentation + maintainer: Xuanyu Liu + description: |- + Traditional methods typically detect breakpoints from individual signals, which means that when applied separately to multiple signals, the breakpoints are not aligned. + However, this package implements a common breakpoint detection approach for multiple piecewise constant signals, resulting in increased detection sensitivity and specificity. + By employing various techniques, optimal performance is ensured, and computation is accelerated. We hope that this package will be beneficial for researchers in signal processing, bioinformatics, economy, and other related fields. + The segmentation(), lambda_estimator() functions are the main functions of this package. + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSigSeg + url_git: '' +mSigTools: + version: 1.0.7 + title: Mutational Signature Analysis Tools + maintainer: Steven Rozen + description: |- + Utility functions for mutational signature analysis + as described in Alexandrov, L. B. (2020) + . + This package provides two groups of functions. One is + for dealing with mutational signature "exposures" + (i.e. the counts of mutations in a sample that are + due to each mutational signature). The other group of + functions is for matching or comparing sets of + mutational signatures. 'mSigTools' stands for + mutational Signature analysis Tools. + date_publication: '2023-01-13' + bug_reports: https://github.com/Rozen-Lab/mSigTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mSigTools + url_git: https://github.com/Rozen-Lab/mSigTools +mSimCC: + version: 0.0.3 + title: Micro Simulation Model for Cervical Cancer Prevention + maintainer: David Moriña Soler + description: Micro simulation model to reproduce natural history of cervical cancer + and cost-effectiveness evaluation of prevention strategies. See Georgalis L, de + Sanjose S, Esnaola M, Bosch F X, Diaz M (2016) + for more details. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mSimCC + url_git: '' +MSIMST: + version: '1.1' + title: |- + Bayesian Monotonic Single-Index Regression Model with the Skew-T + Likelihood + maintainer: Qingyang Liu + description: Incorporates a Bayesian monotonic single-index mixed-effect model with + a multivariate skew-t likelihood, specifically designed to handle survey weights + adjustments. Features include a simulation program and an associated Gibbs sampler + for model estimation. The single-index function is constrained to be monotonic + increasing, utilizing a customized Gaussian process prior for precise estimation. + The model assumes random effects follow a canonical skew-t distribution, while + residuals are represented by a multivariate Student-t distribution. Offers robust + Bayesian adjustments to integrate survey weight information effectively. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSIMST + url_git: https://github.com/rh8liuqy/MSIMST +MSinference: + version: 0.2.1 + title: Multiscale Inference for Nonparametric Time Trend(s) + maintainer: Marina Khismatullina + description: |- + Performs a multiscale analysis of a nonparametric + regression or nonparametric regressions with time series errors. In case + of one regression, with the help of this package it is possible to detect + the regions where the trend function is increasing or decreasing. + In case of multiple regressions, the test identifies regions where + the trend functions are different from each other. See + Khismatullina and Vogt (2020) , + Khismatullina and Vogt (2022) and + Khismatullina and Vogt (2023) + for more details on theory and applications. + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSinference + url_git: '' +MSiP: + version: 1.3.7 + title: '''MassSpectrometry'' Interaction Prediction' + maintainer: Matineh Rahmatbakhsh + description: The 'MSiP' is a computational approach to predict protein-protein interactions + from large-scale affinity purification mass 'spectrometry' (AP-MS) data. This + approach includes both spoke and matrix models for interpreting AP-MS data in + a network context. The "spoke" model considers only bait-prey interactions, whereas + the "matrix" model assumes that each of the identified proteins (baits and prey) + in a given AP-MS experiment interacts with each of the others. The spoke model + has a high false-negative rate, whereas the matrix model has a high false-positive + rate. Although, both statistical models have merits, a combination of both models + has shown to increase the performance of machine learning classifiers in terms + of their capabilities in discrimination between true and false positive interactions. + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSiP + url_git: '' +msir: + version: 1.3.3 + title: Model-Based Sliced Inverse Regression + maintainer: Luca Scrucca + description: An R package for dimension reduction based on finite Gaussian mixture + modeling of inverse regression. + date_publication: '2020-12-16' + bug_reports: '' + url: https://mclust-org.github.io/msir/ + url_cran: https://CRAN.R-project.org/package=msir + url_git: '' +mskcc.oncotree: + version: 0.1.1 + title: Interface to the 'OncoTree' API + maintainer: Ramiro Magno + description: |- + Programmatic access to 'OncoTree' API + . Get access to tumor main types, identifiers + and utility routines to map across to other tumor classification systems. + date_publication: '2022-10-11' + bug_reports: https://github.com/maialab/mskcc.oncotree/issues + url: https://maialab.org/mskcc.oncotree/ + url_cran: https://CRAN.R-project.org/package=mskcc.oncotree + url_git: '' +msltrend: + version: '1.0' + title: |- + Improved Techniques to Estimate Trend, Velocity and Acceleration + from Sea Level Records + maintainer: Phil J Watson + description: |- + Analysis of annual average ocean water level time series + from long (minimum length 80 years) individual records, providing improved + estimates of trend (mean sea level) and associated real-time velocities and + accelerations. Improved trend estimates are based on Singular Spectrum Analysis + methods. Various gap-filling options are included to accommodate incomplete time + series records. The package also contains a forecasting module to consider the + implication of user defined quantum of sea level rise between the end of the + available historical record and the year 2100. A wide range of screen and pdf + plotting options are available in the package. + date_publication: '2016-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msltrend + url_git: '' +msm: + version: 1.8.2 + title: Multi-State Markov and Hidden Markov Models in Continuous Time + maintainer: Christopher Jackson + description: |- + Functions for fitting continuous-time Markov and hidden + Markov multi-state models to longitudinal data. Designed for + processes observed at arbitrary times in continuous time (panel data) + but some other observation schemes are supported. Both Markov + transition rates and the hidden Markov output process can be modelled + in terms of covariates, which may be constant or piecewise-constant + in time. + date_publication: '2024-11-07' + bug_reports: https://github.com/chjackson/msm/issues + url: https://chjackson.github.io/msm/ + url_cran: https://CRAN.R-project.org/package=msm + url_git: https://github.com/chjackson/msm +msma: + version: '3.1' + title: Multiblock Sparse Multivariable Analysis + maintainer: Atsushi Kawaguchi + description: Several functions can be used to analyze multiblock multivariable data. + If the input is a single matrix, then principal components analysis (PCA) is implemented. + If the input is a list of matrices, then multiblock PCA is implemented. If the + input is two matrices, for exploratory and objective variables, then partial least + squares (PLS) analysis is implemented. If the input is two lists of matrices, + for exploratory and objective variables, then multiblock PLS analysis is implemented. + Additionally, if an extra outcome variable is specified, then a supervised version + of the methods above is implemented. For each method, sparse modeling is also + incorporated. Functions for selecting the number of components and regularized + parameters are also provided. + date_publication: '2024-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msma + url_git: '' +msme: + version: 0.5.3 + title: |- + Functions and Datasets for "Methods of Statistical Model + Estimation" + maintainer: Andrew Robinson + description: Functions and datasets from Hilbe, J.M., and Robinson, A.P. 2013. Methods + of Statistical Model Estimation. Chapman & Hall / CRC. + date_publication: '2018-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msme + url_git: '' +MSmix: + version: 1.0.2 + title: |- + Finite Mixtures of Mallows Models with Spearman Distance for + Full and Partial Rankings + maintainer: Cristina Mollica + description: Fit and analysis of finite Mixtures of Mallows models with Spearman + Distance for full and partial rankings with arbitrary missing positions. Inference + is conducted within the maximum likelihood framework via Expectation-Maximization + algorithms. Estimation uncertainty is tackled via diverse versions of bootstrapping + as well as via Hessian-based standard errors calculations. The most relevant reference + of the methods is Crispino, Mollica, Astuti and Tardella (2023) . + date_publication: '2024-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSmix + url_git: '' +MSML: + version: 1.0.0.1 + title: Model Selection Based on Machine Learning (ML) + maintainer: Moksedul Momin + description: Model evaluation based on a modified version of the recursive feature + elimination algorithm. This package is designed to determine the optimal model(s) + by leveraging all available features. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSML + url_git: https://github.com/mommy003/MSML +MSMwRA: + version: '1.5' + title: Multivariate Statistical Methods with R Applications + maintainer: Hasan BULUT + description: |- + Data sets in the book entitled "Multivariate Statistical Methods with R Applications", H.Bulut (2018). + The book was published in Turkish and the original name of this book will be "R Uygulamalari ile Cok Degiskenli Istatistiksel Yontemler". + date_publication: '2021-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSMwRA + url_git: '' +msos: + version: 1.2.0 + title: |- + Data Sets and Functions Used in Multivariate Statistics: Old + School by John Marden + maintainer: James Balamuta + description: |- + Multivariate Analysis methods and data sets used + in John Marden's book Multivariate Statistics: Old School (2015) . + This also serves as a companion package for the + STAT 571: Multivariate Analysis course offered by the Department of Statistics + at the University of Illinois at Urbana-Champaign ('UIUC'). + date_publication: '2020-10-31' + bug_reports: https://github.com/coatless/msos/issues + url: https://coatless.github.io/msos/ + url_cran: https://CRAN.R-project.org/package=msos + url_git: https://github.com/coatless/msos +MSoutcomes: + version: 0.2.0 + title: CORe Multiple Sclerosis Outcomes Toolkit + maintainer: Tomas Kalincik + description: |- + Enable operationalized evaluation of disease outcomes in + multiple sclerosis. ‘MSoutcomes’ requires longitudinally recorded + clinical data structured in long format. The package is based on the + research developed at Clinical Outcomes Research unit (CORe), + University of Melbourne and Neuroimmunology Centre, Royal Melbourne + Hospital. Kalincik et al. (2015) . + Lorscheider et al. (2016) . Sharmin et al. + (2022) . Dzau et al. (2023) + . + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSoutcomes + url_git: '' +MSPRT: + version: '3.0' + title: A Modified Sequential Probability Ratio Test (MSPRT) + maintainer: Sandipan Pramanik + description: |- + Given the maximum available sample size (N) for an experiment, and the target levels of Type I + and II error probabilities, this package designs a modified SPRT (MSPRT). For any designed MSPRT + the package can also obtain its operating characteristics and implement the test for a given + sequentially observed data. The MSPRT is defined in a manner very similar to Wald's initial proposal. + The proposed test has shown evidence of reducing the average sample size required to perform + statistical hypothesis tests at specified levels of significance and power. Currently, the package + implements one-sample proportion tests, one and two-sample z tests, and one and two-sample + t tests. A brief user guidance for this package is provided below. One can also refer to the + supplemental information for the same. + date_publication: '2020-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSPRT + url_git: '' +MSRDT: + version: 0.1.0 + title: Multi-State Reliability Demonstration Tests (MSRDT) + maintainer: Suiyao Chen + description: |- + This is a implementation of design methods for multi-state reliability demonstration tests (MSRDT) with failure count data, + which is associated with the work from the published paper "Multi-state Reliability Demonstration Tests" by Suiyao Chen et al. (2017) . + It implements two types of MSRDT, multiple periods (MP) and multiple failure modes (MFM). + For MP, two different scenarios with criteria on cumulative periods (Cum) or separate periods (Sep) are implemented respectively. + It also provides the implementation of conventional design method, namely binomial tests for failure count data. + date_publication: '2020-06-02' + bug_reports: https://github.com/ericchen12377/MSRDT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MSRDT + url_git: https://github.com/ericchen12377/MSRDT +mssearchr: + version: 0.2.0 + title: |- + Library Search Against Electron Ionization Mass Spectral + Databases + maintainer: Andrey Samokhin + description: |- + Perform library searches against electron ionization mass spectral + databases using either the API provided by 'MS Search' software + () or + custom implementations of the Identity and Similarity algorithms. + date_publication: '2024-12-09' + bug_reports: https://github.com/AndreySamokhin/mssearchr/issues + url: https://mass-spec.ru/projects/gcmsdata/mssearchr/eng/ + url_cran: https://CRAN.R-project.org/package=mssearchr + url_git: '' +msSPChelpR: + version: 0.9.1 + title: Helper Functions for Second Primary Cancer Analyses + maintainer: Marian Eberl + description: |- + A collection of helper functions for analyzing Second Primary Cancer data, + including functions to reshape data, to calculate patient states and analyze cancer incidence. + date_publication: '2024-01-23' + bug_reports: https://github.com/marianschmidt/msSPChelpR/issues + url: https://marianschmidt.github.io/msSPChelpR/ + url_cran: https://CRAN.R-project.org/package=msSPChelpR + url_git: '' +MSSQL: + version: 1.0.1 + title: Tools to Work with Microsoft SQL Server Databases via 'RODBC' + maintainer: Arni Magnusson + description: |- + Tools that extend the functionality of the 'RODBC' package to work + with Microsoft SQL Server databases. Makes it easier to browse the database + and examine individual tables and views. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSSQL + url_git: https://github.com/gfcm/MSSQL +MST: + version: '2.2' + title: Multivariate Survival Trees + maintainer: Peter Calhoun + description: |- + Constructs trees for multivariate survival data using marginal and frailty models. + Grows, prunes, and selects the best-sized tree. + date_publication: '2020-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MST + url_git: '' +mstate: + version: 0.3.3 + title: |- + Data Preparation, Estimation and Prediction in Multi-State + Models + maintainer: Hein Putter + description: Contains functions for data preparation, descriptives, hazard estimation + and prediction with Aalen-Johansen or simulation in competing risks and multi-state + models, see Putter, Fiocco, Geskus (2007) . + date_publication: '2024-07-11' + bug_reports: https://github.com/hputter/mstate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mstate + url_git: https://github.com/hputter/mstate +mStats: + version: 3.4.0 + title: Epidemiological Data Analysis + maintainer: Myo Minn Oo + description: |- + This is a tool for epidemiologist, medical data analyst, + medical or public health professionals. It contains three domains of functions: + 1) data management, 2) statistical analysis and 3) calculating + epidemiological measures. + date_publication: '2020-11-23' + bug_reports: https://github.com/myominnoo/mStats/issues + url: https://myominnoo.github.io/ + url_cran: https://CRAN.R-project.org/package=mStats + url_git: '' +mstclustering: + version: 1.0.0.0 + title: '"MST-Based Clustering"' + maintainer: Kevin Michael Frick + description: Implements a minimum-spanning-tree-based heuristic for k-means clustering + using a union-find disjoint set and the algorithm in Kruskal (1956) . + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mstclustering + url_git: '' +mstDIF: + version: 0.1.8 + title: A Collection of DIF Tests for Multistage Tests + maintainer: Rudolf Debelak + description: |- + A collection of statistical tests for the detection of differential + item functioning (DIF) in multistage tests. Methods entail logistic regression, + an adaptation of the simultaneous item bias test (SIBTEST), and various score-based tests. + The presented tests provide itemwise test for DIF along categorical, ordinal or metric covariates. Methods for uniform and non-uniform + DIF effects are available depending on which method is used. + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mstDIF + url_git: '' +mSTEM: + version: 1.0-1 + title: Multiple Testing of Local Extrema for Detection of Change Points + maintainer: Zhibing He + description: A new approach to detect change points based on smoothing and multiple + testing, which is for long data sequence modeled as piecewise constant functions + plus stationary Gaussian noise, see Dan Cheng and Armin Schwartzman (2015) . + date_publication: '2019-10-02' + bug_reports: '' + url: https://arxiv.org/abs/1504.06384 + url_cran: https://CRAN.R-project.org/package=mSTEM + url_git: '' +MSTest: + version: 0.1.5 + title: Hypothesis Testing for Markov Switching Models + maintainer: Gabriel Rodriguez Rondon + description: Implementation of hypothesis testing procedures described in Hansen + (1992) , Carrasco, Hu, & Ploberger (2014) , + Dufour & Luger (2017) , and Rodriguez Rondon + & Dufour (2024) + that can be used to identify the number of regimes in Markov switching models. + date_publication: '2025-02-24' + bug_reports: https://github.com/roga11/MSTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MSTest + url_git: https://github.com/roga11/MSTest +mstherm: + version: 0.4.7 + title: Analyze MS/MS Protein Melting Data + maintainer: Jeremy Volkening + description: |- + Software to aid in modeling and analyzing mass-spectrometry-based + proteome melting data. Quantitative data is imported and normalized and + thermal behavior is modeled at the protein level. Methods exist for + normalization, modeling, visualization, and export of results. For a + general introduction to MS-based thermal profiling, see Savitski et al. + (2014) . + date_publication: '2017-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mstherm + url_git: '' +mstknnclust: + version: 0.3.2 + title: MST-kNN Clustering Algorithm + maintainer: Jorge Parraga-Alava + description: Implements the MST-kNN clustering algorithm which was proposed by Inostroza-Ponta, + M. (2008) . + date_publication: '2023-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mstknnclust + url_git: '' +mstR: + version: '1.2' + title: Procedures to Generate Patterns under Multistage Testing + maintainer: David Magis + description: Generation of response patterns under dichotomous and polytomous computerized + multistage testing (MST) framework. It holds various item response theory (IRT) + and score-based methods to select the next module and estimate ability levels + (Magis, Yan and von Davier (2017, ISBN:978-3-319-69218-0)). + date_publication: '2018-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mstR + url_git: '' +mstrio: + version: 11.3.5.101 + title: Interface for 'MicroStrategy' REST API + maintainer: Piotr Kowal + description: |- + Interface for creating data sets and extracting data through the + 'MicroStrategy' REST API. Access the demo API at + . + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mstrio + url_git: '' +mstudentd: + version: 1.1.2 + title: Multivariate t Distribution + maintainer: Pierre Santagostini + description: Distance between multivariate t distributions, as presented by N. Bouhlel + and D. Rousseau (2023) . + date_publication: '2024-12-23' + bug_reports: https://forgemia.inra.fr/imhorphen/mstudentd/-/issues + url: https://forgemia.inra.fr/imhorphen/mstudentd + url_cran: https://CRAN.R-project.org/package=mstudentd + url_git: '' +msu: + version: 0.0.1 + title: Multivariate Symmetric Uncertainty and Other Measurements + maintainer: Elias Maciel + description: |- + Estimators for multivariate symmetrical uncertainty based + on the work of Gustavo Sosa et al. (2016) , + total correlation, information gain and symmetrical uncertainty of + categorical variables. + date_publication: '2017-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=msu + url_git: '' +MSwM: + version: '1.5' + title: Fitting Markov Switching Models + maintainer: Josep A. Sanchez-Espigares + description: Estimation, inference and diagnostics for Univariate Autoregressive + Markov Switching Models for Linear and Generalized Models. Distributions for the + series include gaussian, Poisson, binomial and gamma cases. The EM algorithm is + used for estimation (see Perlin (2012) ). + date_publication: '2021-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MSwM + url_git: '' +mt: + version: 2.0-1.20 + title: Metabolomics Data Analysis Toolbox + maintainer: Wanchang Lin + description: |- + Functions for metabolomics data analysis: data preprocessing, + orthogonal signal correction, PCA analysis, PCA-DA analysis, + PLS-DA analysis, classification, feature selection, correlation + analysis, data visualisation and re-sampling strategies. + date_publication: '2024-02-12' + bug_reports: https://github.com/wanchanglin/mt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mt + url_git: https://github.com/wanchanglin/mt +MTA: + version: 0.6.0 + title: Multiscalar Territorial Analysis + maintainer: Timothée Giraud + description: Build multiscalar territorial analysis based on various contexts. + date_publication: '2023-10-31' + bug_reports: https://github.com/riatelab/MTA/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=MTA + url_git: https://github.com/riatelab/MTA/ +MTAFT: + version: 0.1.0 + title: |- + Data-Driven Estimation for Multi-Threshold Accelerate Failure + Time Model + maintainer: Chuang WAN + description: Developed a data-driven estimation framework for the multi-threshold + accelerate failure time (MTAFT) model. The MTAFT model features different linear + forms in different subdomains, and one of the major challenges is determining + the number of threshold effects. The package introduces a data-driven approach + that utilizes a Schwarz' information criterion, which demonstrates consistency + under mild conditions. Additionally, a cross-validation (CV) criterion with an + order-preserved sample-splitting scheme is proposed to achieve consistent estimation, + without the need for additional parameters. The package establishes the asymptotic + properties of the parameter estimates and includes an efficient score-type test + to examine the existence of threshold effects. The methodologies are supported + by numerical experiments and theoretical results, showcasing their reliable performance + in finite-sample cases. + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MTAFT + url_git: '' +mtanan: + version: 0.0.1 + title: Single Valued Neutrosophic Kruskal-Wallis and Mann Whitney Tests + maintainer: Mohamad Taher Anan + description: |- + Dealing with neutrosophic data in single valued form using score, + accuracy and certainty functions to calculate ranks of Single Valued + Neutrosophic Set (SVNS), also to calculate the Mann-Whitney test, + and making a post-hoc test after rejecting the null hypothesis using the Neutrosophic + Statistics Kruskal-Wallis test. For more information see + Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022) + . + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mtanan + url_git: '' +MTAR: + version: 0.1.1 + title: Multi-Trait Analysis of Rare-Variant Association Study + maintainer: Lan Luo + description: Perform multi-trait rare-variant association tests using the summary + statistics and adjust for possible sample overlap. Package is based on "Multi-Trait + Analysis of Rare-Variant Association Summary Statistics using MTAR" by Luo, L., + Shen, J., Zhang, H., Chhibber, A. Mehrotra, D.V., Tang, Z., 2019 (submitted). + date_publication: '2020-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MTAR + url_git: '' +mtarm: + version: 0.1.2 + title: |- + Bayesian Estimation of Multivariate Threshold Autoregressive + Models + maintainer: Luis Hernando Vanegas + description: Estimation, inference and forecasting using the Bayesian approach for + multivariate threshold autoregressive (TAR) models in which the distribution used + to describe the noise process belongs to the class of Gaussian variance mixtures. + date_publication: '2024-07-22' + bug_reports: https://github.com/lhvanegasp/mtar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mtarm + url_git: '' +mtb: + version: 0.1.9 + title: My Toolbox for Assisting Document Editing and Data Presenting + maintainer: Y Hsu + description: |- + The purpose of this package is to share a collection of functions the author wrote during weekends for managing + kitchen and garden tasks, e.g. making plant growth charts or Thanksgiving kitchen schedule charts, etc. + Functions might include but not limited to: + (1) aiding summarizing time related data; + (2) generating axis transformation from data; and + (3) aiding Markdown (with html output) and Shiny file editing. + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mtb + url_git: https://github.com/yh202109/mtb +mtdesign: + version: 0.1.2 + title: Mander and Thompson Designs + maintainer: John Kirkpatrick + description: |- + Implements Mander & Thompson's (2010) + methods for two-stage designs + optimal under the alternative hypothesis for phase II [cancer] trials. Also + provides an implementation of Simon's (1989) + original methodology and + allows exploration of the operating characteristics of sub-optimal designs. + date_publication: '2024-11-05' + bug_reports: https://github.com/openpharma/mtdesign/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mtdesign + url_git: https://github.com/openpharma/mtdesign +MTDrh: + version: 0.1.0 + title: Mass Transportation Distance Rank Histogram + maintainer: Didem Sari + description: The Mass Transportation Distance rank histogram was developed to assess + the reliability of scenarios with equal or different probabilities of occurrence + . + date_publication: '2016-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MTDrh + url_git: '' +MTE: + version: '1.2' + title: |- + Maximum Tangent Likelihood Estimation for Robust Linear + Regression and Variable Selection + maintainer: Shaobo Li + description: |- + Several robust estimators for linear regression and variable selection are provided. + Included are Maximum tangent likelihood estimator by Qin, et al., (2017) , + least absolute deviance estimator and Huber regression. The penalized version of each of these + estimator incorporates L1 penalty function, i.e., LASSO and Adaptive Lasso. They are able to + produce consistent estimates for both fixed and high-dimensional settings. + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MTE + url_git: GitHub:https://github.com/shaobo-li/MTE +MTest: + version: 1.0.2 + title: A Procedure for Multicollinearity Testing using Bootstrap + maintainer: Víctor Morales-Oñate + description: 'Functions for detecting multicollinearity. This test gives statistical + support to two of the most famous methods for detecting multicollinearity in applied + work: Klein’s rule and Variance Inflation Factor (VIF). See the URL for the papers + associated with this package, as for instance, Morales-Oñate and Morales-Oñate + (2015) .' + date_publication: '2023-10-06' + bug_reports: https://github.com/vmoprojs/MTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MTest + url_git: https://github.com/vmoprojs/MTest +mthapower: + version: 0.1.1 + title: |- + Sample Size and Power for Association Studies Involving + Mitochondrial DNA Haplogroups + maintainer: Aurora Baluja + description: |- + Calculate Sample Size and Power for + Association Studies Involving Mitochondrial DNA Haplogroups. + Based on formulae by Samuels et al. AJHG, 2006. 78(4):713-720. . + date_publication: '2019-05-14' + bug_reports: https://github.com/aurora-mareviv/mthapower/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mthapower + url_git: https://github.com/aurora-mareviv/mthapower +mtlgmm: + version: 0.1.0 + title: |- + Unsupervised Multi-Task and Transfer Learning on Gaussian + Mixture Models + maintainer: Ye Tian + description: Unsupervised learning has been widely used in many real-world applications. + One of the simplest and most important unsupervised learning models is the Gaussian + mixture model (GMM). In this work, we study the multi-task learning problem on + GMMs, which aims to leverage potentially similar GMM parameter structures among + tasks to obtain improved learning performance compared to single-task learning. + We propose a multi-task GMM learning procedure based on the Expectation-Maximization + (EM) algorithm that not only can effectively utilize unknown similarity between + related tasks but is also robust against a fraction of outlier tasks from arbitrary + sources. The proposed procedure is shown to achieve minimax optimal rate of convergence + for both parameter estimation error and the excess mis-clustering error, in a + wide range of regimes. Moreover, we generalize our approach to tackle the problem + of transfer learning for GMMs, where similar theoretical results are derived. + Finally, we demonstrate the effectiveness of our methods through simulations and + a real data analysis. To the best of our knowledge, this is the first work studying + multi-task and transfer learning on GMMs with theoretical guarantees. This package + implements the algorithms proposed in Tian, Y., Weng, H., & Feng, Y. (2022) . + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mtlgmm + url_git: '' +MTLR: + version: 0.2.1 + title: Survival Prediction with Multi-Task Logistic Regression + maintainer: Humza Haider + description: |- + An implementation of Multi-Task Logistic Regression (MTLR) for R. + This package is based on the method proposed by Yu et al. (2011) which utilized MTLR for generating individual survival curves + by learning feature weights which vary across time. This model was further extended to account for left and interval censored data. + date_publication: '2019-06-03' + bug_reports: https://github.com/haiderstats/MTLR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MTLR + url_git: https://github.com/haiderstats/MTLR +MTPS: + version: 1.0.2 + title: Multi-Task Prediction using Stacking Algorithms + maintainer: Li Xing + description: 'Simultaneous multiple outcomes prediction based on revised stacking + algorithms, which enables the integration of information from predictions of individual + models. An implementation of methodologies proposed in our paper: Li Xing, Mary + L Lesperance, Xuekui Zhang. (2019) Bioinformatics, "Simultaneous prediction of + multiple outcomes using revised stacking algorithms" .' + date_publication: '2023-06-14' + bug_reports: '' + url: https://doi.org/10.1093/bioinformatics/btz531 + url_cran: https://CRAN.R-project.org/package=MTPS + url_git: '' +mtrank: + version: 0.1-1 + title: Ranking using Probabilistic Models and Treatment Choice Criteria + maintainer: Theodoros Evrenoglou + description: Implementation of a novel frequentist approach to produce clinically + relevant treatment hierarchies in network meta-analysis. The method is based on + treatment choice criteria (TCC) and probabilistic ranking models, as described + by Evrenoglou et al. (2024) . The TCC are defined + using a rule based on the minimal clinically important difference. Using the defined + TCC, the study-level data (i.e., treatment effects and standard errors) are first + transformed into a preference format, indicating either a treatment preference + (e.g., treatment A > treatment B) or a tie (treatment A = treatment B). The preference + data are then synthesized using a probabilistic ranking model, which estimates + the latent ability parameter of each treatment and produces the final treatment + hierarchy. This parameter represents each treatment’s ability to outperform all + the other competing treatments in the network. Consequently, larger ability estimates + indicate higher positions in the ranking list. + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mtrank + url_git: https://github.com/TEvrenoglou/mtrank +MtreeRing: + version: 1.4.5 + title: |- + A Shiny Application for Automatic Measurements of Tree-Ring + Widths on Digital Images + maintainer: Jingning Shi + description: Use morphological image processing and edge detection algorithms to + automatically measure tree ring widths on digital images. Users can also manually + mark tree rings on species with complex anatomical structures. The arcs of inner-rings + and angles of successive inclined ring boundaries are used to correct ring-width + series. The package provides a Shiny-based application, allowing R beginners to + easily analyze tree ring images and export ring-width series in standard file + formats. + date_publication: '2021-04-19' + bug_reports: https://github.com/ropensci/MtreeRing/issues + url: https://docs.ropensci.org/MtreeRing + url_cran: https://CRAN.R-project.org/package=MtreeRing + url_git: https://github.com/ropensci/MtreeRing +MTS: + version: 1.2.1 + title: |- + All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) + and Estimating Multivariate Volatility Models + maintainer: Ruey S. Tsay + description: Multivariate Time Series (MTS) is a general package for analyzing multivariate + linear time series and estimating multivariate volatility models. It also handles + factor models, constrained factor models, asymptotic principal component analysis + commonly used in finance and econometrics, and principal volatility component + analysis. (a) For the multivariate linear time series analysis, the package performs + model specification, estimation, model checking, and prediction for many widely + used models, including vector AR models, vector MA models, vector ARMA models, + seasonal vector ARMA models, VAR models with exogenous variables, multivariate + regression models with time series errors, augmented VAR models, and Error-correction + VAR models for co-integrated time series. For model specification, the package + performs structural specification to overcome the difficulties of identifiability + of VARMA models. The methods used for structural specification include Kronecker + indices and Scalar Component Models. (b) For multivariate volatility modeling, + the MTS package handles several commonly used models, including multivariate exponentially + weighted moving-average volatility, Cholesky decomposition volatility models, + dynamic conditional correlation (DCC) models, copula-based volatility models, + and low-dimensional BEKK models. The package also considers multiple tests for + conditional heteroscedasticity, including rank-based statistics. (c) Finally, + the MTS package also performs forecasting using diffusion index , transfer function + analysis, Bayesian estimation of VAR models, and multivariate time series analysis + with missing values.Users can also use the package to simulate VARMA models, to + compute impulse response functions of a fitted VARMA model, and to calculate theoretical + cross-covariance matrices of a given VARMA model. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MTS + url_git: '' +mtscr: + version: 1.0.2 + title: Multidimensional Top Scoring for Creativity Research + maintainer: Jakub Jędrusiak + description: |- + Implementation of Multidimensional Top Scoring + method for creativity assessment proposed in + Boris Forthmann, Maciej Karwowski, Roger E. Beaty (2023) . + date_publication: '2024-12-12' + bug_reports: https://github.com/jakub-jedrusiak/mtscr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mtscr + url_git: https://github.com/jakub-jedrusiak/mtscr +mtsdi: + version: 0.3.5 + title: Multivariate Time Series Data Imputation + maintainer: Washington Junger + description: This is an EM algorithm based method for imputation of missing values + in multivariate normal time series. The imputation algorithm accounts for both + spatial and temporal correlation structures. Temporal patterns can be modeled + using an ARIMA(p,d,q), optionally with seasonal components, a non-parametric cubic + spline or generalized additive models with exogenous covariates. This algorithm + is specially tailored for climate data with missing measurements from several + monitors along a given region. + date_publication: '2018-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mtsdi + url_git: '' +mtsta: + version: 0.0.0.1 + title: |- + Accessing the Red List of Montane Tree Species of the Tropical + Andes + maintainer: Paul E. Santos Andrade + description: Access the 'Red List of Montane Tree Species of the Tropical Andes' + Tejedor Garavito et al.(2014, ISBN:978-1-905164-60-8). This package allows users + to search for globally threatened tree species within the andean montane forests, + including cloud forests and seasonal (wet) forests above 1500 m a.s.l. + date_publication: '2023-09-19' + bug_reports: https://github.com/PaulESantos/mtsta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mtsta + url_git: https://github.com/PaulESantos/mtsta +MTSYS: + version: 1.2.0 + title: Methods in Mahalanobis-Taguchi (MT) System + maintainer: Akifumi Okayama + description: |- + Mahalanobis-Taguchi (MT) system is a collection of multivariate + analysis methods developed for the field of quality engineering. MT system + consists of two families depending on their purpose. One is a family of + Mahalanobis-Taguchi (MT) methods (in the broad sense) for diagnosis (see + Woodall, W. H., Koudelik, R., Tsui, K. L., Kim, S. B., Stoumbos, Z. G., and + Carvounis, C. P. (2003) ) and the other is a + family of Taguchi (T) methods for forecasting (see Kawada, H., and Nagata, Y. + (2015) ). The MT package contains three basic methods + for the family of MT methods and one basic method for the family of T + methods. The MT method (in the narrow sense), the Mahalanobis-Taguchi + Adjoint (MTA) methods, and the Recognition-Taguchi (RT) method are for the + MT method and the two-sided Taguchi (T1) method is for the family of T + methods. In addition, the Ta and Tb methods, which are the improved versions + of the T1 method, are included. + date_publication: '2017-09-10' + bug_reports: https://github.com/okayaa/MTSYS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MTSYS + url_git: https://github.com/okayaa/MTSYS +mtvc: + version: 1.1.0 + title: Multiple Counting Process Structure for Survival Analysis + maintainer: Elia Gonzato + description: |- + Counting process structure is fundamental to model time varying covariates. + This package restructures dataframes in the counting process format for one or more variables. + F. W. Dekker, et al. (2008) . + date_publication: '2024-02-09' + bug_reports: https://github.com/egonzato/mtvc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mtvc + url_git: https://github.com/egonzato/mtvc +MUACz: + version: 2.1.0 + title: |- + Generate MUAC and BMI z-Scores and Percentiles for Children and + Adolescents + maintainer: Lazarus Mramba + description: |- + Generates mid upper arm circumference (MUAC) and body mass index (BMI) + for age z-scores and percentiles based on LMS method for children and + adolescents up to 19 years that can be used to assess nutritional and health status and + define risk of adverse health events. + date_publication: '2020-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MUACz + url_git: '' +MuChPoint: + version: 0.6.3 + title: Multiple Change Point + maintainer: Brault Vincent + description: |- + Nonparametric approach to estimate the location of block boundaries (change-points) of + non-overlapping blocks in a random symmetric matrix which consists of random variables whose + distribution changes from block to block. + BRAULT Vincent, OUADAH Sarah, SANSONNET Laure and LEVY-LEDUC Celine (2017) . + date_publication: '2022-04-08' + bug_reports: https://github.com/Lionning/MuChPoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MuChPoint + url_git: https://github.com/Lionning/MuChPoint +muckrock: + version: 0.1.0 + title: Data on Freedom of Information Act Requests + maintainer: Oliver Keyes + description: |- + A data package containing public domain information on requests made by the + 'MuckRock' (https://www.muckrock.com/) project under the United States + Freedom of Information Act. + date_publication: '2016-06-06' + bug_reports: https://github.com/Ironholds/muckrock/issues + url: '' + url_cran: https://CRAN.R-project.org/package=muckrock + url_git: https://github.com/Ironholds/muckrock/ +mudfold: + version: 1.1.21 + title: Multiple UniDimensional unFOLDing + maintainer: Spyros Balafas + description: 'Nonparametric unfolding item response theory (IRT) model for dichotomous + data (see W.H. Van Schuur (1984). Structure in Political Beliefs: A New Model + for Stochastic Unfolding with Application to European Party Activists, and W.J.Post + (1992). Nonparametric Unfolding Models: A Latent Structure Approach). The package + implements MUDFOLD (Multiple UniDimensional unFOLDing), an iterative item selection + algorithm that constructs unfolding scales from dichotomous preferential-choice + data without explicitly assuming a parametric form of the item response functions. + Scale diagnostics from Post(1992) and estimates for the person locations proposed + by Johnson(2006) and Van Schuur(1984) are also available. This model can be seen + as the unfolding variant of Mokken(1971) scaling method.' + date_publication: '2022-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mudfold + url_git: https://github.com/cran/mudfold +mueRelativeRisk: + version: 0.1.1 + title: Relative Risk Based on the Ratio of Median Unbiased Estimates + maintainer: Rickey Carter + description: Implements an estimator for relative risk based on the median unbiased + estimator. The relative risk estimator is well defined and performs satisfactorily + for a wide range of data configurations. The details of the method are available + in Carter et al (2010) . + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mueRelativeRisk + url_git: '' +muhaz: + version: 1.2.6.4 + title: Hazard Function Estimation in Survival Analysis + maintainer: David Winsemius + description: |- + Produces a smooth estimate of the hazard + function for censored data. + date_publication: '2021-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=muhaz + url_git: '' +muir: + version: 0.1.0 + title: Exploring Data with Tree Data Structures + maintainer: Justin Alford + description: A simple tool allowing users to easily and dynamically explore or document + a data set using a tree structure. + date_publication: '2015-05-02' + bug_reports: https://github.com/alforj/muir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=muir + url_git: https://github.com/alforj/muir +mulea: + version: 1.1.1 + title: |- + Enrichment Analysis Using Multiple Ontologies and False + Discovery Rate + maintainer: Tamas Stirling + description: |- + Background - Traditional gene set enrichment analyses are + typically limited to a few ontologies and do not account for the + interdependence of gene sets or terms, resulting in overcorrected p-values. + To address these challenges, we introduce mulea, an R package offering + comprehensive overrepresentation and functional enrichment analysis. + Results - mulea employs a progressive empirical false discovery rate + (eFDR) method, specifically designed for interconnected biological data, + to accurately identify significant terms within diverse ontologies. mulea + expands beyond traditional tools by incorporating a wide range of + ontologies, encompassing Gene Ontology, pathways, regulatory elements, + genomic locations, and protein domains. This flexibility enables + researchers to tailor enrichment analysis to their specific questions, + such as identifying enriched transcriptional regulators in gene expression + data or overrepresented protein domains in protein sets. To facilitate + seamless analysis, mulea provides gene sets (in standardised GMT format) + for 27 model organisms, covering 22 ontology types from 16 databases and + various identifiers resulting in almost 900 files. Additionally, the + muleaData ExperimentData Bioconductor package simplifies access to these + pre-defined ontologies. Finally, mulea's architecture allows for easy + integration of user-defined ontologies, or GMT files from external + sources (e.g., MSigDB or Enrichr), expanding its applicability across + diverse research areas. Conclusions - mulea is distributed as a CRAN R + package. It offers researchers a powerful and flexible toolkit for + functional enrichment analysis, addressing limitations of traditional + tools with its progressive eFDR and by supporting a variety of ontologies. + Overall, mulea fosters the exploration of diverse biological questions + across various model organisms. + date_publication: '2024-11-19' + bug_reports: https://github.com/ELTEbioinformatics/mulea/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mulea + url_git: https://github.com/ELTEbioinformatics/mulea +mulgar: + version: 1.0.2 + title: |- + Functions for Pre-Processing Data for Multivariate Data + Visualisation using Tours + maintainer: Dianne Cook + description: |- + This is a companion to the book Cook, D. and Laa, U. (2023) + "Interactively exploring high-dimensional data and models in R". + by Cook and Laa. It contains useful functions for processing data in preparation for + visualising with a tour. There are also several sample data sets. + date_publication: '2023-08-25' + bug_reports: https://github.com/dicook/mulgar/issues + url: https://dicook.github.io/mulgar/ + url_cran: https://CRAN.R-project.org/package=mulgar + url_git: https://github.com/dicook/mulgar +MullerPlot: + version: 0.1.3 + title: |- + Generates Muller Plot from Population/Abundance/Frequency + Dynamics Data + maintainer: Farnoush Farahpour + description: |- + Generates Muller plot from parental/genealogy/phylogeny information and population/abundance/frequency dynamics data. + Muller plots are plots which combine information about succession of different OTUs (genotypes, phenotypes, species, ...) and information about dynamics of their abundances (populations or frequencies) over time. They are powerful and fascinating tools to visualize evolutionary dynamics. They may be employed also in study of diversity and its dynamics, i.e. how diversity emerges and how changes over time. They are called Muller plots in honor of Hermann Joseph Muller which used them to explain his idea of Muller's ratchet (Muller, 1932, American Naturalist). + A big difference between Muller plots and normal box plots of abundances is that a Muller plot depicts not only the relative abundances but also succession of OTUs based on their genealogy/phylogeny/parental relation. In a Muller plot, horizontal axis is time/generations and vertical axis represents relative abundances of OTUs at the corresponding times/generations. Different OTUs are usually shown with polygons with different colors and each OTU originates somewhere in the middle of its parent area in order to illustrate their succession in evolutionary process. + To generate a Muller plot one needs the genealogy/phylogeny/parental relation of OTUs and their abundances over time. + MullerPlot package has the tools to generate Muller plots which clearly depict the origin of successors of OTUs. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MullerPlot + url_git: '' +mully: + version: 2.1.38 + title: Create, Modify and Visualize Multi-Layered Networks + maintainer: Zaynab Hammoud + description: |- + Allows the user to create graphs with multiple layers. The user can also modify the layers, the nodes, and the edges. The graph can also be visualized. + Zaynab Hammoud and Frank Kramer (2018) . + More about multilayered graphs and their usage can be found in our review paper: + Zaynab Hammoud and Frank Kramer (2020) . + date_publication: '2023-02-22' + bug_reports: https://github.com/frankkramer-lab/mully/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mully + url_git: https://github.com/frankkramer-lab/mully +mulSEM: + version: '1.0' + title: Some Multivariate Analyses using Structural Equation Modeling + maintainer: Mike Cheung + description: |- + A set of functions for some multivariate analyses utilizing a + structural equation modeling (SEM) approach through the 'OpenMx' package. + These analyses include canonical correlation analysis (CANCORR), + redundancy analysis (RDA), and multivariate principal component regression (MPCR). + It implements procedures discussed in Gu and Cheung (2023) , + Gu, Yung, and Cheung (2019) , and + Gu et al. (2023) . + date_publication: '2024-02-04' + bug_reports: https://github.com/mikewlcheung/mulsem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mulSEM + url_git: https://github.com/mikewlcheung/mulsem +mulset: + version: 1.0.0 + title: Multiset Intersection Generator + maintainer: Ivan Tomic + description: Computes efficient data distributions from highly inconsistent datasets + with many missing values using multi-set intersections. Based upon hash functions, + 'mulset' can quickly identify intersections from very large matrices of input + vectors across columns and rows and thus provides scalable solution for dealing + with missing values. Tomic et al. (2019) . + date_publication: '2019-03-08' + bug_reports: https://github.com/LogIN-/mulset/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mulset + url_git: https://github.com/LogIN-/mulset +mult.latent.reg: + version: 0.2.1 + title: Regression and Clustering in Multivariate Response Scenarios + maintainer: Yingjuan Zhang + description: Fitting multivariate response models with random effects on one or + two levels; whereby the (one-dimensional) random effect represents a latent variable + approximating the multivariate space of outcomes, after possible adjustment for + covariates. The method is particularly useful for multivariate, highly correlated + outcome variables with unobserved heterogeneities. Applications include regression + with multivariate responses, as well as multivariate clustering or ranking problems. + See Zhang and Einbeck (2024) . + date_publication: '2024-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mult.latent.reg + url_git: '' +MultBiplotR: + version: 23.11.0 + title: Multivariate Analysis Using Biplots in R + maintainer: Jose Luis Vicente Villardon + description: 'Several multivariate techniques from a biplot perspective. It is the + translation (with many improvements) into R of the previous package developed + in ''Matlab''. The package contains some of the main developments of my team during + the last 30 years together with some more standard techniques. Package includes: + Classical Biplots, HJ-Biplot, Canonical Biplots, MANOVA Biplots, Correspondence + Analysis, Canonical Correspondence Analysis, Canonical STATIS-ACT, Logistic Biplots + for binary and ordinal data, Multidimensional Unfolding, External Biplots for + Principal Coordinates Analysis or Multidimensional Scaling, among many others. + References can be found in the help of each procedure.' + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultBiplotR + url_git: '' +multbxxc: + version: 1.0.3 + title: Auxiliary Routines for Influx Software + maintainer: Serguei Sokol + description: 'Contains auxiliary routines for influx software. This packages is + not intended to be used directly. Influx was published here: Sokol et al. (2012) + .' + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multbxxc + url_git: https://github.com/sgsokol/influx/ +multcomp: + version: 1.4-28 + title: Simultaneous Inference in General Parametric Models + maintainer: Torsten Hothorn + description: |- + Simultaneous tests and confidence intervals + for general linear hypotheses in parametric models, including + linear, generalized linear, linear mixed effects, and survival models. + The package includes demos reproducing analyzes presented + in the book "Multiple Comparisons Using R" (Bretz, Hothorn, + Westfall, 2010, CRC Press). + date_publication: '2025-01-29' + bug_reports: '' + url: https://www.routledge.com/Multiple-Comparisons-Using-R/Bretz-Hothorn-Westfall/p/book/9781584885740 + url_cran: https://CRAN.R-project.org/package=multcomp + url_git: http://multcomp.R-forge.R-project.org +multcompView: + version: 0.1-10 + title: Visualizations of Paired Comparisons + maintainer: Luciano Selzer + description: |- + Convert a logical vector or a vector of + p-values or a correlation, difference, or distance + matrix into a display identifying the pairs for + which the differences were not significantly + different. Designed for use in conjunction with + the output of functions like TukeyHSD, dist{stats}, + simint, simtest, csimint, csimtest{multcomp}, + friedmanmc, kruskalmc{pgirmess}. + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multcompView + url_git: '' +multDM: + version: 1.1.4 + title: Multivariate Version of the Diebold-Mariano Test + maintainer: Krzysztof Drachal + description: 'Allows to perform the multivariate version of the Diebold-Mariano + test for equal predictive ability of multiple forecast comparison. Main reference: + Mariano, R.S., Preve, D. (2012) .' + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multDM + url_git: '' +multe: + version: 1.1.0 + title: Multiple Treatment Effects Regression + maintainer: Michal Kolesár + description: |- + Implements contamination bias diagnostics and alternative + estimators for regressions with multiple treatments. The implementation is + based on Goldsmith-Pinkham, Hull, and Kolesár (2024) + . + date_publication: '2024-07-12' + bug_reports: https://github.com/kolesarm/multe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multe + url_git: https://github.com/kolesarm/multe +MultEq: + version: '2.4' + title: Multiple Equivalence Tests and Simultaneous Confidence Intervals + maintainer: Mario Hasler + description: |- + Equivalence tests and related confidence intervals for the + comparison of two treatments, simultaneously for one or many normally + distributed, primary response variables (endpoints). The step-up + procedure of Quan et al. (2001) is both applied for differences and + extended to ratios of means. A related single-step procedure is also + available. + date_publication: '2022-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultEq + url_git: '' +multfisher: + version: '1.1' + title: Optimal Exact Tests for Multiple Binary Endpoints + maintainer: Robin Ristl + description: |- + Calculates exact hypothesis tests to compare a treatment and a reference group with respect to multiple binary endpoints. + The tested null hypothesis is an identical multidimensional distribution of successes and failures in both groups. The alternative + hypothesis is a larger success proportion in the treatment group in at least one endpoint. The tests are based on the multivariate + permutation distribution of subjects between the two groups. For this permutation distribution, rejection regions are calculated + that satisfy one of different possible optimization criteria. In particular, regions with maximal exhaustion of the nominal + significance level, maximal power under a specified alternative or maximal number of elements can be found. Optimization is achieved + by a branch-and-bound algorithm. By application of the closed testing principle, the global hypothesis tests are extended to multiple + testing procedures. + date_publication: '2018-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multfisher + url_git: '' +multgee: + version: 1.9.0 + title: |- + GEE Solver for Correlated Nominal or Ordinal Multinomial + Responses + maintainer: Anestis Touloumis + description: |- + GEE solver for correlated nominal or ordinal multinomial responses + using a local odds ratios parameterization. + date_publication: '2023-09-02' + bug_reports: https://github.com/AnestisTouloumis/multgee/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multgee + url_git: https://github.com/AnestisTouloumis/multgee +multiActionButton: + version: 1.0.0 + title: Multi Action Button for 'Shiny' Applications + maintainer: Stéphane Laurent + description: |- + Provides a multi action button for usage in 'shiny' + applications. + date_publication: '2022-06-22' + bug_reports: https://github.com/stla/multiActionButton/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multiActionButton + url_git: https://github.com/stla/multiActionButton +multiApply: + version: 2.1.4 + title: Apply Functions to Multiple Multidimensional Arrays or Vectors + maintainer: An-Chi Ho + description: |- + The base apply function and its variants, as well as the related + functions in the 'plyr' package, typically apply user-defined functions to a + single argument (or a list of vectorized arguments in the case of mapply). The + 'multiApply' package extends this paradigm with its only function, Apply, which + efficiently applies functions taking one or a list of multiple unidimensional + or multidimensional arrays (or combinations thereof) as input. The input + arrays can have different numbers of dimensions as well as different dimension + lengths, and the applied function can return one or a list of unidimensional or + multidimensional arrays as output. This saves development time by preventing the + R user from writing often error-prone and memory-inefficient loops dealing with + multiple complex arrays. Also, a remarkable feature of Apply is the transparent + use of multi-core through its parameter 'ncores'. In contrast to the base apply + function, this package suggests the use of 'target dimensions' as opposite + to the 'margins' for specifying the dimensions relevant to the function to be + applied. + date_publication: '2023-03-28' + bug_reports: https://earth.bsc.es/gitlab/ces/multiApply/-/issues + url: https://earth.bsc.es/gitlab/ces/multiApply + url_cran: https://CRAN.R-project.org/package=multiApply + url_git: '' +multiAssetOptions: + version: 0.1-2 + title: Finite Difference Method for Multi-Asset Option Valuation + maintainer: Michael Eichenberger + description: Efficient finite difference method for valuing European and American + multi-asset options. + date_publication: '2021-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiAssetOptions + url_git: '' +MultiATSM: + version: 1.2.0 + title: Multicountry Term Structure of Interest Rates Models + maintainer: Rubens Moura + description: Estimation routines for several classes of affine term structure of + interest rates models. All the models are based on the single-country unspanned + macroeconomic risk framework from Joslin, Priebsch, and Singleton (2014, JF) . + Multicountry extensions such as the ones of Jotikasthira, Le, and Lundblad (2015, + JFE) , Candelon and Moura (2023, EM) , + and Candelon and Moura (Forthcoming, JFEC) are also + available. + date_publication: '2025-01-27' + bug_reports: https://github.com/rubensmoura87/MultiATSM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MultiATSM + url_git: https://github.com/rubensmoura87/MultiATSM +MultiBD: + version: 0.2.0 + title: Multivariate Birth-Death Processes + maintainer: Marc A. Suchard + description: |- + Computationally efficient functions to provide direct likelihood-based + inference for partially-observed multivariate birth-death processes. Such processes + range from a simple Yule model to the complex susceptible-infectious-removed model + in disease dynamics. Efficient likelihood evaluation facilitates maximum likelihood + estimation and Bayesian inference. + date_publication: '2016-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiBD + url_git: '' +multibias: + version: 1.6.3 + title: Simultaneous Multi-Bias Adjustment + maintainer: Paul Brendel + description: |- + Quantify the causal effect of a binary exposure on a binary + outcome with adjustment for multiple biases. The functions can + simultaneously adjust for any combination of uncontrolled confounding, + exposure/outcome misclassification, and selection bias. + The underlying method generalizes the concept of combining inverse + probability of selection weighting with predictive value weighting. + Simultaneous multi-bias analysis can be used to enhance the validity + and transparency of real-world evidence obtained from observational, + longitudinal studies. Based on the work from Paul Brendel, Aracelis Torres, + and Onyebuchi Arah (2023) . + date_publication: '2025-02-23' + bug_reports: https://github.com/pcbrendel/multibias/issues + url: http://www.paulbrendel.com/multibias/ + url_cran: https://CRAN.R-project.org/package=multibias + url_git: https://github.com/pcbrendel/multibias +multibiasmeta: + version: 0.2.2 + title: Sensitivity Analysis for Multiple Biases in Meta-Analyses + maintainer: Peter Solymos + description: |- + Meta-analyses can be compromised by studies' internal biases (e.g., + confounding in nonrandomized studies) as well as by publication bias. This + package conducts sensitivity analyses for the joint effects of these biases + (per Mathur (2022) ). These sensitivity analyses + address two questions: (1) For a given severity of internal bias across + studies and of publication bias, how much could the results change?; and + (2) For a given severity of publication bias, how severe would internal bias + have to be, hypothetically, to attenuate the results to the null or by a given + amount? + date_publication: '2023-08-23' + bug_reports: https://github.com/mathurlabstanford/multibiasmeta/issues + url: https://mathurlabstanford.github.io/multibiasmeta/ + url_cran: https://CRAN.R-project.org/package=multibiasmeta + url_git: https://github.com/mathurlabstanford/multibiasmeta +multibiplotGUI: + version: '1.1' + title: Multibiplot Analysis in R + maintainer: Ana Belen Nieto Librero + description: |- + Provides a GUI with which users can construct and interact + with Multibiplot Analysis. + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multibiplotGUI + url_git: '' +multiblock: + version: 0.8.9.0 + title: Multiblock Data Fusion in Statistics and Machine Learning + maintainer: Kristian Hovde Liland + description: |- + Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1) + "Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences". + This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting + functions, several real data sets and six vignettes covering a range different applications. + date_publication: '2025-01-20' + bug_reports: https://github.com/khliland/multiblock/issues/ + url: https://khliland.github.io/multiblock/ + url_cran: https://CRAN.R-project.org/package=multiblock + url_git: https://github.com/khliland/multiblock/ +multibreakeR: + version: 0.1.0 + title: Tests for a Structural Change in Multivariate Time Series + maintainer: Loic Marechal + description: |- + Flexible implementation of a structural change point detection algorithm for multivariate time series. + It authorizes inclusion of trends, exogenous variables, and break test on the intercept or on the full vector autoregression system. + Bai, Lumsdaine, and Stock (1998) . + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multibreakeR + url_git: https://github.com/loicym/multibreakeR +multibridge: + version: 1.2.0 + title: Evaluating Multinomial Order Restrictions with Bridge Sampling + maintainer: Alexandra Sarafoglou + description: |- + Evaluate hypotheses concerning the distribution of multinomial + proportions using bridge sampling. The bridge sampling routine is able to + compute Bayes factors for hypotheses that entail inequality constraints, + equality constraints, free parameters, and mixtures of all three. These + hypotheses are tested against the encompassing hypothesis, that all parameters + vary freely or against the null hypothesis that all category proportions are equal. + For more information see Sarafoglou et al. (2020) . + date_publication: '2022-11-01' + bug_reports: https://github.com/asarafoglou/multibridge/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multibridge + url_git: https://github.com/asarafoglou/multibridge/ +multiCA: + version: '1.1' + title: Multinomial Cochran-Armitage Trend Test + maintainer: Aniko Szabo + description: |- + Implements a generalization of the Cochran-Armitage trend test to + multinomial data. In addition to an overall test, multiple testing adjusted + p-values for trend in individual outcomes and power calculation is + available. + date_publication: '2017-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiCA + url_git: '' +multicastR: + version: 2.0.0 + title: A Companion to the Multi-CAST Collection + maintainer: Nils Norman Schiborr + description: |- + Provides a basic interface for accessing annotation data from + the Multi-CAST collection, a database of spoken natural language texts + edited by Geoffrey Haig and Stefan Schnell. The collection draws from a + diverse set of languages and has been annotated across multiple levels. + Annotation data is downloaded on request from the servers of the + University of Bamberg. See the Multi-CAST website + for more information and a list + of related publications. + date_publication: '2021-02-22' + bug_reports: '' + url: https://multicast.aspra.uni-bamberg.de/ + url_cran: https://CRAN.R-project.org/package=multicastR + url_git: '' +multichull: + version: 3.0.1 + title: A Generic Convex-Hull-Based Model Selection Method + maintainer: Kristof Meers + description: Given a set of models for which a measure of model (mis)fit and model + complexity is provided, CHull(), developed by Ceulemans and Kiers (2006) , + determines the models that are located on the boundary of the convex hull and + selects an optimal model by means of the scree test values. + date_publication: '2024-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multichull + url_git: '' +multiclassPairs: + version: 0.4.3 + title: Build MultiClass Pair-Based Classifiers using TSPs or RF + maintainer: Nour-al-dain Marzouka + description: 'A toolbox to train a single sample classifier that uses in-sample + feature relationships. The relationships are represented as feature1 < feature2 + (e.g. gene1 < gene2). We provide two options to go with. First is based on ''switchBox'' + package which uses Top-score pairs algorithm. Second is a novel implementation + based on random forest algorithm. For simple problems we recommend to use one-vs-rest + using TSP option due to its simplicity and for being easy to interpret. For complex + problems RF performs better. Both lines filter the features first then combine + the filtered features to make the list of all the possible rules (i.e. rule1: + feature1 < feature2, rule2: feature1 < feature3, etc...). Then the list of rules + will be filtered and the most important and informative rules will be kept. The + informative rules will be assembled in an one-vs-rest model or in an RF model. We + provide a detailed description with each function in this package to explain the + filtration and training methodology in each line. Reference: Marzouka & Eriksson + (2021) .' + date_publication: '2021-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiclassPairs + url_git: https://github.com/NourMarzouka/multiclassPairs +MultiClassROC: + version: 0.1.0 + title: ROC Curves for Multi-Class Analysis + maintainer: Marton Varga + description: Function multiroc() can be used for computing and visualizing Receiver + Operating Characteristics (ROC) and Area Under the Curve (AUC) for multi-class + classification problems. It supports both One-vs-One approach by M.Bishop, C. + (2006, ISBN:978-0-387-31073-2) and One-vs-All approach by Murphy P., K. (2012, + ISBN:9780262018029). + date_publication: '2023-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiClassROC + url_git: '' +multicmp: + version: '1.1' + title: |- + Flexible Modeling of Multivariate Count Data via the + Multivariate Conway-Maxwell-Poisson Distribution + maintainer: Diag Davenport + description: A toolkit containing statistical analysis models motivated by multivariate + forms of the Conway-Maxwell-Poisson (COM-Poisson) distribution for flexible modeling + of multivariate count data, especially in the presence of data dispersion. Currently + the package only supports bivariate data, via the bivariate COM-Poisson distribution + described in Sellers et al. (2016) . Future development + will extend the package to higher-dimensional data. + date_publication: '2018-06-29' + bug_reports: https://github.com/diagdavenport/multicmp/issues + url: http://dx.doi.org/10.1016/j.jmva.2016.04.007 + url_cran: https://CRAN.R-project.org/package=multicmp + url_git: '' +MultiCOAP: + version: '1.1' + title: |- + High-Dimensional Covariate-Augmented Overdispersed Multi-Study + Poisson Factor Model + maintainer: Wei Liu + description: We introduce factor models designed to jointly analyze high-dimensional + count data from multiple studies by extracting study-shared and specified factors. + Our factor models account for heterogeneous noises and overdispersion among counts + with augmented covariates. We propose an efficient and speedy variational estimation + procedure for estimating model parameters, along with a novel criterion for selecting + the optimal number of factors and the rank of regression coefficient matrix. More + details can be referred to Liu et al. (2024) . + date_publication: '2024-03-07' + bug_reports: https://github.com/feiyoung/MultiCOAP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MultiCOAP + url_git: https://github.com/feiyoung/MultiCOAP +multiColl: + version: '2.0' + title: Collinearity Detection in a Multiple Linear Regression Model + maintainer: R. Salmeron + description: The detection of worrying approximate collinearity in a multiple linear + regression model is a problem addressed in all existing statistical packages. + However, we have detected deficits regarding to the incorrect treatment of qualitative + independent variables and the role of the intercept of the model. The objective + of this package is to correct these deficits. In this package will be available + detection and treatment techniques traditionally used as the recently developed. + date_publication: '2022-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiColl + url_git: http://colldetreat.r-forge.r-project.org/ +multicool: + version: 1.0.1 + title: Permutations of Multisets in Cool-Lex Order + maintainer: James Curran + description: A set of tools to permute multisets without loops or hash tables and + to generate integer partitions. The permutation functions are based on C code + from Aaron Williams. Cool-lex order is similar to colexicographical order. The + algorithm is described in Williams, A. Loopless Generation of Multiset Permutations + by Prefix Shifts. SODA 2009, Symposium on Discrete Algorithms, New York, United + States. The permutation code is distributed without restrictions. The code for + stable and efficient computation of multinomial coefficients comes from Dave Barber. + The code can be download from + and is distributed without conditions. The package also generates the integer + partitions of a positive, non-zero integer n. The C++ code for this is based on + Python code from Jerome Kelleher which can be found here . + The C++ code and Python code are distributed without conditions. + date_publication: '2024-02-05' + bug_reports: https://github.com/jmcurran/multicool/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multicool + url_git: https://github.com/jmcurran/multicool +multid: + version: 1.0.0 + title: Multivariate Difference Between Two Groups + maintainer: Ville-Juhani Ilmarinen + description: |- + Estimation of multivariate differences between two groups (e.g., multivariate sex differences) with regularized regression methods and predictive approach. See Lönnqvist & Ilmarinen (2021) and Ilmarinen et al. (2023) . + Includes tools that help in understanding difference score reliability, predictions of difference score variables, conditional intra-class correlations, and heterogeneity of variance estimates. Package development was supported by the Academy of Finland research grant 338891. + date_publication: '2024-02-15' + bug_reports: https://github.com/vjilmari/multid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multid + url_git: '' +multiDimBio: + version: 1.2.2 + title: Multivariate Analysis and Visualization for Biological Data + maintainer: Samuel V. Scarpino + description: Code to support a systems biology research program from inception through + publication. The methods focus on dimension reduction approaches to detect patterns + in complex, multivariate experimental data and places an emphasis on informative + visualizations. The goal for this project is to create a package that will evolve + over time, thereby remaining relevant and reflective of current methods and techniques. As + a result, we encourage suggested additions to the package, both methodological + and graphical. + date_publication: '2020-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiDimBio + url_git: '' +multidplyr: + version: 0.1.3 + title: A Multi-Process 'dplyr' Backend + maintainer: Hadley Wickham + description: |- + Partition a data frame across multiple worker processes to + provide simple multicore parallelism. + date_publication: '2023-03-22' + bug_reports: https://github.com/tidyverse/multidplyr/issues + url: https://multidplyr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=multidplyr + url_git: https://github.com/tidyverse/multidplyr +multifamm: + version: 0.1.1 + title: Multivariate Functional Additive Mixed Models + maintainer: Alexander Volkmann + description: |- + An implementation for multivariate functional additive mixed + models (multiFAMM), see Volkmann et al. (2021, ). It builds on developed methods for univariate sparse + functional regression models and multivariate functional principal component + analysis. This package contains the function to run a multiFAMM and some + convenience functions useful when working with large models. An additional + package on GitHub contains more convenience functions to reproduce the + analyses of the corresponding paper + (). + date_publication: '2021-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multifamm + url_git: '' +multiFANOVA: + version: 0.1.0 + title: Multiple Contrast Tests for Functional Data + maintainer: Lukasz Smaga + description: The provided package implements multiple contrast tests for functional + data (Munko et al., 2023, ). These procedures enable us to evaluate + the overall hypothesis regarding equality, as well as specific hypotheses defined + by contrasts. In particular, we can perform post hoc tests to examine particular + comparisons of interest. Different experimental designs are supported, e.g., one-way + and multi-way analysis of variance for functional data. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiFANOVA + url_git: '' +multifear: + version: 0.1.3 + title: Multiverse Analyses for Conditioning Data + maintainer: Angelos-Miltiadis Krypotos + description: A suite of functions for performing analyses, based on a multiverse + approach, for conditioning data. Specifically, given the appropriate data, the + functions are able to perform t-tests, analyses of variance, and mixed models + for the provided data and return summary statistics and plots. The function is + also able to return for all those tests p-values, confidence intervals, and Bayes + factors. The methods are described in Lonsdorf, Gerlicher, Klingelhofer-Jens, + & Krypotos (2022) . + date_publication: '2023-09-23' + bug_reports: https://github.com/AngelosPsy/multifear/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multifear + url_git: https://github.com/AngelosPsy/multifear +MultiFit: + version: 1.1.1 + title: |- + Multiscale Fisher's Independence Test for Multivariate + Dependence + maintainer: S. Gorsky + description: Test for independence of two random vectors, learn and report the dependency + structure. For more information, see Gorsky, Shai and Li Ma, Multiscale Fisher's + Independence Test for Multivariate Dependence, Biometrika, accepted, January 2022. + date_publication: '2022-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiFit + url_git: '' +multifunc: + version: 0.9.4 + title: Analysis of Ecological Drivers on Ecosystem Multifunctionality + maintainer: Jarrett Byrnes + description: |- + Methods for the analysis of how ecological drivers affect the + multifunctionality of an ecosystem based on methods of Byrnes et al. + 2016 and Byrnes et al. + 2022 . Most standard + methods in the literature are implemented (see vignettes) in a tidy + format. + date_publication: '2022-05-25' + bug_reports: https://github.com/jebyrnes/multifunc/issues + url: https://jebyrnes.github.io/multifunc/ + url_cran: https://CRAN.R-project.org/package=multifunc + url_git: https://github.com/jebyrnes/multifunc +multifwf: + version: 0.2.2 + title: Read Fixed Width Format Files Containing Lines of Different Type + maintainer: Panos Rontogiannis + description: |- + Read a table of fixed width formatted data of different types into + a data.frame for each type. + date_publication: '2015-12-24' + bug_reports: https://github.com/prontog/multifwf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multifwf + url_git: https://github.com/prontog/multifwf +MultiGlarmaVarSel: + version: '1.0' + title: Variable Selection in Sparse Multivariate GLARMA Models + maintainer: Marina Gomtsyan + description: Performs variable selection in high-dimensional sparse GLARMA models. + For further details we refer the reader to the paper Gomtsyan et al. (2022), . + date_publication: '2022-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiGlarmaVarSel + url_git: '' +multigraph: + version: 0.99-3 + title: Plot and Manipulate Multigraphs + maintainer: Antonio Rivero Ostoic + description: Functions to plot and manipulate multigraphs, signed and valued graphs, + bipartite graphs, multilevel graphs, and Cayley graphs with various layout options. + date_publication: '2024-05-14' + bug_reports: https://github.com/mplex/multigraph/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=multigraph + url_git: https://github.com/mplex/multigraph/ +multigraphr: + version: 0.2.0 + title: |- + Probability Models and Statistical Analysis of Random + Multigraphs + maintainer: Termeh Shafie + description: Methods and models for analysing multigraphs as introduced by Shafie + (2015) , including methods to study local and global + properties and goodness of fit tests. + date_publication: '2024-02-20' + bug_reports: https://github.com/termehs/multigraphr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multigraphr + url_git: https://github.com/termehs/multigraphr +MultiGrey: + version: 0.1.0 + title: |- + Fitting and Forecasting of Grey Model for Multivariate Time + Series Data + maintainer: Pradip Basak + description: |- + Grey model is commonly used in time series forecasting when statistical assumptions are violated with a limited number of data points. The minimum number of data points + required to fit a grey model is four observations. This package fits Grey model of First order and One Variable, i.e., GM (1,1) for multivariate time series data and returns + the parameters of the model, model evaluation criteria and h-step ahead forecast values for each of the time series variables. For method details see, Akay, D. and Atak, M. (2007) , + Hsu, L. and Wang, C. (2007).. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiGrey + url_git: '' +MultiGroupO: + version: 0.4.0 + title: MultiGroup Method and Simulation Data Analysis + maintainer: Carolina Millap/'an + description: |- + Two method new of multigroup and simulation of data. + The first technique called multigroup PCA (mgPCA) this multivariate exploration approach + that has the idea of considering the structure of groups and / or different types + of variables. On the other hand, the second multivariate technique called Multigroup Dimensionality + Reduction (MDR) it is another multivariate exploration method that is based on + projections. In addition, a method called Single Dimension Exploration (SDE) was + incorporated for to analyze the exploration of the data. It could help us in a better + way to observe the behavior of the multigroup data with certain variables of interest. + date_publication: '2024-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiGroupO + url_git: '' +MultiGroupSequential: + version: 1.1.0 + title: Group-Sequential Procedures with Multiple Hypotheses + maintainer: Xiaodong Luo + description: It is often challenging to strongly control the family-wise type-1 + error rate in the group-sequential trials with multiple endpoints (hypotheses). + The inflation of type-1 error rate comes from two sources (S1) repeated testing + individual hypothesis and (S2) simultaneous testing multiple hypotheses. The 'MultiGroupSequential' + package is intended to help researchers to tackle this challenge. The procedures + provided include the sequential procedures described in Luo and Quan (2023) + and the graphical procedure proposed by Maurer and Bretz (2013) . + Luo and Quan (2013) describes three procedures, and the functions to implement + these procedures are (1) seqgspgx() implements a sequential graphical procedure + based on the group-sequential p-values; (2) seqgsphh() implements a sequential + Hochberg/Hommel procedure based on the group-sequential p-values; and (3) seqqvalhh() + implements a sequential Hochberg/Hommel procedure based on the q-values. In addition, + seqmbgx() implements the sequential graphical procedure described in Maurer and + Bretz (2013). + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiGroupSequential + url_git: '' +MultiJoin: + version: 0.1.1 + title: |- + Enables Efficient Joining of Data File on Common Fields using + the Unix Utility Join + maintainer: '"Markus Loecher"' + description: |- + Wrapper around the Unix join facility which is more efficient than the built-in R routine merge(). + The package enables the joining of multiple files on disk at once. + The files can be compressed and various filters can be deployed before joining. + Compiles only under Unix. + date_publication: '2018-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiJoin + url_git: '' +MultiKink: + version: 0.2.0 + title: Estimation and Inference for Multi-Kink Quantile Regression + maintainer: Chuang Wan + description: Estimation and inference for multiple kink quantile regression for + longitudinal data and the i.i.d data. A bootstrap restarting iterative segmented + quantile algorithm is proposed to estimate the multiple kink quantile regression + model conditional on a given number of change points. The number of kinks is also + allowed to be unknown. In such case, the backward elimination algorithm and the + bootstrap restarting iterative segmented quantile algorithm are combined to select + the number of change points based on a quantile BIC. For longitudinal data, we + also develop the GEE estimator to incorporate the within-subject correlations. A + score-type based test statistic is also developed for testing the existence of + kink effect. The package is based on the paper, ``Wei Zhong, Chuang Wan and Wenyang + Zhang (2022). Estimation and inference for multikink quantile regression, JBES'' + and ``Chuang Wan, Wei Zhong, Wenyang Zhang and Changliang Zou (2022). Multi-kink + quantile regression for longitudinal data with application to progesterone data + analysis, Biometrics". + date_publication: '2023-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiKink + url_git: '' +multilandr: + version: 1.0.0 + title: Landscape Analysis at Multiple Spatial Scales + maintainer: Pablo Yair Huais + description: Provides a tidy workflow for landscape-scale analysis. 'multilandr' + offers tools to generate landscapes at multiple spatial scales and compute landscape + metrics, primarily using the 'landscapemetrics' package. It also features utility + functions for plotting and analyzing multi-scale landscapes, exploring correlations + between metrics, filtering landscapes based on specific conditions, generating + landscape gradients for a given metric, and preparing datasets for further statistical + analysis. Documentation about 'multilandr' is provided in an introductory vignette + included in this package and in the paper by Huais (2024) ; + see citation("multilandr") for details. + date_publication: '2025-02-14' + bug_reports: https://github.com/phuais/multilandr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multilandr + url_git: https://github.com/phuais/multilandr +MultiLCIRT: + version: '2.11' + title: Multidimensional Latent Class Item Response Theory Models + maintainer: Francesco Bartolucci + description: Framework for the Item Response Theory analysis of dichotomous and + ordinal polytomous outcomes under the assumption of multidimensionality and discreteness + of the latent traits. The fitting algorithms allow for missing responses and for + different item parameterizations and are based on the Expectation-Maximization + paradigm. Individual covariates affecting the class weights may be included in + the new version (since 2.1). + date_publication: '2017-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiLCIRT + url_git: '' +multilevel: + version: '2.7' + title: Multilevel Functions + maintainer: Paul Bliese + description: Tools used by organizational researchers for the analysis of multilevel + data. Includes four broad sets of tools. First, functions for estimating within-group + agreement and reliability indices. Second, functions for manipulating multilevel + and longitudinal (panel) data. Third, simulations for estimating power and generating + multilevel data. Fourth, miscellaneous functions for estimating reliability and + performing simple calculations and data transformations. + date_publication: '2022-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multilevel + url_git: '' +multilevelcoda: + version: 1.3.1 + title: Estimate Bayesian Multilevel Models for Compositional Data + maintainer: Flora Le + description: |- + Implement Bayesian Multilevel Modelling for compositional data + in a multilevel framework. Compute multilevel compositional data and + Isometric log ratio (ILR) at between and within-person levels, + fit Bayesian multilevel models for compositional predictors and outcomes, + and run post-hoc analyses such as isotemporal substitution models. + References: + Le, Stanford, Dumuid, and Wiley (2024) , + Le, Dumuid, Stanford, and Wiley (2024) . + date_publication: '2024-11-23' + bug_reports: https://github.com/florale/multilevelcoda/issues + url: https://florale.github.io/multilevelcoda/ + url_cran: https://CRAN.R-project.org/package=multilevelcoda + url_git: https://github.com/florale/multilevelcoda +multilevelmediation: + version: 0.4.1 + title: Utility Functions for Multilevel Mediation Analysis + maintainer: Carl F. Falk + description: |- + The ultimate goal is to support 2-2-1, 2-1-1, and 1-1-1 models for + multilevel mediation, the option of a moderating variable for either the a, b, + or both paths, and covariates. Currently the 1-1-1 model is supported + and several options of random effects; the initial code for bootstrapping was + evaluated in simulations by Falk, Vogel, Hammami, and Miočević (2024) . + Support for Bayesian estimation using 'brms' comprises ongoing work. Currently + only continuous mediators and outcomes are supported. Factors for any + predictors must be numerically represented. + date_publication: '2025-01-10' + bug_reports: https://github.com/falkcarl/multilevelmediation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multilevelmediation + url_git: '' +multilevelmod: + version: 1.0.0 + title: Model Wrappers for Multi-Level Models + maintainer: Hannah Frick + description: |- + Bindings for hierarchical regression models for use with the + 'parsnip' package. Models include longitudinal generalized linear + models (Liang and Zeger, 1986) , and + mixed-effect models (Pinheiro and Bates) + . + date_publication: '2022-06-17' + bug_reports: '' + url: http://multilevelmod.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=multilevelmod + url_git: https://github.com/tidymodels/multilevelmod +multilevelPSA: + version: 1.2.5 + title: Multilevel Propensity Score Analysis + maintainer: Jason Bryer + description: |- + Conducts and visualizes propensity score analysis for multilevel, + or clustered data. Bryer & Pruzek (2011) . + date_publication: '2018-03-22' + bug_reports: https://github.com/jbryer/multilevelPSA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multilevelPSA + url_git: http://github.com/jbryer/multilevelPSA +multilevelTools: + version: 0.1.1 + title: Multilevel and Mixed Effects Model Diagnostics and Effect Sizes + maintainer: Joshua F. Wiley + description: |- + Effect sizes, diagnostics and performance metrics for + multilevel and mixed effects models. + Includes marginal and conditional 'R2' estimates for linear mixed effects models + based on Johnson (2014) . + date_publication: '2020-03-04' + bug_reports: https://github.com/JWiley/multilevelTools/issues + url: http://joshuawiley.com/multilevelTools + url_cran: https://CRAN.R-project.org/package=multilevelTools + url_git: https://github.com/JWiley/multilevelTools +multilevLCA: + version: 2.0.1 + title: |- + Estimates and Plots Single-Level and Multilevel Latent Class + Models + maintainer: Roberto Di Mari + description: Efficiently estimates single- and multilevel latent class models with + covariates, allowing for output visualization in all specifications. For more + technical details, see Lyrvall et al (2023) . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multilevLCA + url_git: '' +multilinguer: + version: 0.2.4 + title: Gentle Language Installer for R User + maintainer: Chanyub Park + description: |- + Provides install functions of other languages + such as 'java', 'python'. + date_publication: '2022-08-12' + bug_reports: https://github.com/mrchypark/multilinguer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multilinguer + url_git: https://github.com/mrchypark/multilinguer +multilink: + version: 0.1.1 + title: Multifile Record Linkage and Duplicate Detection + maintainer: Serge Aleshin-Guendel + description: Implementation of the methodology of Aleshin-Guendel & Sadinle (2022) + . It handles the general problem of multifile + record linkage and duplicate detection, where any number of files are to be linked, + and any of the files may have duplicates. + date_publication: '2023-06-09' + bug_reports: https://github.com/aleshing/multilink/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multilink + url_git: https://github.com/aleshing/multilink +multimark: + version: 2.1.6 + title: |- + Capture-Mark-Recapture Analysis using Multiple Non-Invasive + Marks + maintainer: Brett T. McClintock + description: |- + Traditional and spatial capture-mark-recapture analysis with + multiple non-invasive marks. The models implemented in 'multimark' combine + encounter history data arising from two different non-invasive "marks", + such as images of left-sided and right-sided pelage patterns of bilaterally + asymmetrical species, to estimate abundance and related demographic + parameters while accounting for imperfect detection. Bayesian models are + specified using simple formulae and fitted using Markov chain Monte Carlo. + Addressing deficiencies in currently available software, 'multimark' also + provides a user-friendly interface for performing Bayesian multimodel + inference using non-spatial or spatial capture-recapture data consisting of a single + conventional mark or multiple non-invasive marks. See McClintock (2015) and Maronde et al. (2020) . + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multimark + url_git: '' +multiMarker: + version: 1.0.1 + title: |- + Latent Variable Model to Infer Food Intake from Multiple + Biomarkers + maintainer: Silvia D'Angelo + description: A latent variable model based on factor analytic and mixture of experts + models, designed to infer food intake from multiple biomarkers data. The model + is framed within a Bayesian hierarchical framework, which provides flexibility + to adapt to different biomarker distributions and facilitates inference on food + intake from biomarker data alone, along with the associated uncertainty. Details + are in D'Angelo, et al. (2020) . + date_publication: '2020-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiMarker + url_git: '' +multimedia: + version: 0.2.0 + title: Multimodal Mediation Analysis + maintainer: Kris Sankaran + description: 'Multimodal mediation analysis is an emerging problem in microbiome + data analysis. Multimedia make advanced mediation analysis techniques easy to + use, ensuring that all statistical components are transparent and adaptable to + specific problem contexts. The package provides a uniform interface to direct + and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence + interval construction, and sensitivity analysis. More details are available in + Jiang et al. (2024) "multimedia: Multimodal Mediation Analysis of Microbiome Data" + .' + date_publication: '2024-09-18' + bug_reports: https://github.com/krisrs1128/multimedia/issues/ + url: https://krisrs1128.github.io/multimedia/ + url_cran: https://CRAN.R-project.org/package=multimedia + url_git: https://github.com/krisrs1128/multimedia/ +multimix: + version: 1.0-10 + title: |- + Fit Mixture Models Using the Expectation Maximisation (EM) + Algorithm + maintainer: James Curran + description: |- + A set of functions which use the Expectation Maximisation (EM) + algorithm (Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977) + Maximum likelihood from + incomplete data via the EM algorithm, Journal of the Royal Statistical + Society, 39(1), 1--22) to take a finite mixture model approach to + clustering. The package is designed to cluster multivariate data that have + categorical and continuous variables and that possibly contain missing + values. The method is described in Hunt, L. and Jorgensen, M. (1999) + Australian & New Zealand Journal of Statistics + 41(2), 153--171 and Hunt, L. and Jorgensen, M. (2003) + Mixture model clustering for mixed data + with missing information, Computational Statistics & Data Analysis, 41(3-4), + 429--440. + date_publication: '2023-01-18' + bug_reports: https://github.com/jmcurran/multimix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multimix + url_git: https://github.com/jmcurran/multimix +multimode: + version: '1.5' + title: Mode Testing and Exploring + maintainer: Jose Ameijeiras-Alonso + description: Different examples and methods for testing (including different proposals + described in Ameijeiras-Alonso et al., 2019 ) and + exploring (including the mode tree, mode forest and SiZer) the number of modes + using nonparametric techniques . + date_publication: '2021-03-20' + bug_reports: '' + url: https://doi.org/10.18637/jss.v097.i09 + url_cran: https://CRAN.R-project.org/package=multimode + url_git: '' +multimolang: + version: 0.1.1 + title: '''multimolang'': Multimodal Language Analysis' + maintainer: Brian Herreño Jiménez + description: Process 'OpenPose' human body keypoints for computer vision, including + data structuring and user-defined linear transformations for standardization. + It optionally, includes metadata extraction from filenames in the UCLA 'NewsScape' + archive. + date_publication: '2024-12-09' + bug_reports: https://github.com/daedalusLAB/multimolang/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multimolang + url_git: https://github.com/daedalusLAB/multimolang +multimorbidity: + version: 0.5.1 + title: |- + Harmonizing Various Comorbidity, Multimorbidity, and Frailty + Measures + maintainer: Wyatt Bensken + description: |- + Identifying comorbidities, frailty, and multimorbidity in claims + and administrative data is often a duplicative process. + The functions contained in this package are meant to first prepare the data to a format + acceptable by all other packages, then provide a uniform and simple approach to + generate comorbidity and multimorbidity metrics based on these claims data. The package + is ever evolving to include new metrics, and is always looking for new measures to include. + The citations used in this package include the following publications: + Anne Elixhauser, Claudia Steiner, D. Robert Harris, Rosanna M. Coffey (1998) , + Brian J Moore, Susan White, Raynard Washington, et al. (2017) , + Mary E. Charlson, Peter Pompei, Kathy L. Ales, C. Ronald MacKenzie (1987) , + Richard A. Deyo, Daniel C. Cherkin, Marcia A. Ciol (1992) , + Hude Quan, Vijaya Sundararajan, Patricia Halfon, et al. (2005) , + Dae Hyun Kim, Sebastian Schneeweiss, Robert J Glynn, et al. (2018) , + Melissa Y Wei, David Ratz, Kenneth J Mukamal (2020) , + Kathryn Nicholson, Amanda L. Terry, Martin Fortin, et al. (2015) , + Martin Fortin, José Almirall, and Kathryn Nicholson (2017). + date_publication: '2023-02-15' + bug_reports: https://github.com/WYATTBENSKEN/multimorbidity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multimorbidity + url_git: https://github.com/WYATTBENSKEN/multimorbidity +multiness: + version: 1.0.2 + title: MULTIplex NEtworks with Shared Structure + maintainer: Peter W. MacDonald + description: |- + Model fitting and simulation for Gaussian and logistic inner + product MultiNeSS models for multiplex networks. The package implements + a convex fitting algorithm with fully adaptive parameter tuning, + including options for edge cross-validation. For more details see + MacDonald et al. (2020). + date_publication: '2022-11-25' + bug_reports: https://github.com/peterwmacd/multiness/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=multiness + url_git: https://github.com/peterwmacd/multiness/ +multinet: + version: 4.2.1 + title: Analysis and mining of multilayer social networks + maintainer: Matteo Magnani + description: Functions for the creation/generation and analysis of multilayer social + networks . + date_publication: '2024-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multinet + url_git: '' +multinets: + version: 0.2.2 + title: Multilevel Networks Analysis + maintainer: Neylson Crepalde + description: |- + Analyze multilevel networks as described in Lazega et al (2008) + and in Lazega and Snijders + (2016, ISBN:978-3-319-24520-1). The package was developed essentially as an + extension to 'igraph'. + date_publication: '2019-12-14' + bug_reports: https://github.com/neylsoncrepalde/multinets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multinets + url_git: https://github.com/neylsoncrepalde/multinets +multinma: + version: 0.7.2 + title: Bayesian Network Meta-Analysis of Individual and Aggregate Data + maintainer: David M. Phillippo + description: |- + Network meta-analysis and network meta-regression models for + aggregate data, individual patient data, and mixtures of both individual + and aggregate data using multilevel network meta-regression as described by + Phillippo et al. (2020) . Models are estimated in a + Bayesian framework using 'Stan'. + date_publication: '2024-09-16' + bug_reports: https://github.com/dmphillippo/multinma/issues + url: https://dmphillippo.github.io/multinma/ + url_cran: https://CRAN.R-project.org/package=multinma + url_git: https://github.com/dmphillippo/multinma +MultinomialCI: + version: '1.2' + title: |- + Simultaneous Confidence Intervals for Multinomial Proportions + According to the Method by Sison and Glaz + maintainer: Pablo J. Villacorta + description: |- + An implementation of a method for building simultaneous confidence intervals for the probabilities of a multinomial distribution given a set of observations, proposed by Sison and Glaz in their paper: + Sison, C.P and J. Glaz. Simultaneous confidence intervals and sample size determination for multinomial proportions. Journal of the American Statistical Association, 90:366-369 (1995). + The method is an R translation of the SAS code implemented by May and Johnson in their paper: + May, W.L. and W.D. Johnson. Constructing two-sided simultaneous confidence intervals for multinomial proportions for small counts in a large number of cells. Journal of Statistical Software 5(6) (2000). + Paper and code available at . + date_publication: '2021-05-11' + bug_reports: https://ccia.ugr.es/~pjvi/ + url: https://ccia.ugr.es/~pjvi/ + url_cran: https://CRAN.R-project.org/package=MultinomialCI + url_git: '' +multinomialLogitMix: + version: '1.1' + title: |- + Clustering Multinomial Count Data under the Presence of + Covariates + maintainer: Panagiotis Papastamoulis + description: Methods for model-based clustering of multinomial counts under the + presence of covariates using mixtures of multinomial logit models, as implemented + in Papastamoulis (2023) . These models are estimated + under a frequentist as well as a Bayesian setup using the Expectation-Maximization + algorithm and Markov chain Monte Carlo sampling (MCMC), respectively. The (unknown) + number of clusters is selected according to the Integrated Completed Likelihood + criterion (for the frequentist model), and estimating the number of non-empty + components using overfitting mixture models after imposing suitable sparse prior + assumptions on the mixing proportions (in the Bayesian case), see Rousseau and + Mengersen (2011) . In the latter case, various + MCMC chains run in parallel and are allowed to switch states. The final MCMC output + is suitably post-processed in order to undo label switching using the Equivalence + Classes Representatives (ECR) algorithm, as described in Papastamoulis (2016) + . + date_publication: '2023-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multinomialLogitMix + url_git: '' +multinomineq: + version: 0.2.6 + title: |- + Bayesian Inference for Multinomial Models with Inequality + Constraints + maintainer: Daniel W. Heck + description: |2- + + Implements Gibbs sampling and Bayes factors for multinomial models with + linear inequality constraints on the vector of probability parameters. As + special cases, the model class includes models that predict a linear order + of binomial probabilities (e.g., p[1] < p[2] < p[3] < .50) and mixture models + assuming that the parameter vector p must be inside the convex hull of a + finite number of predicted patterns (i.e., vertices). A formal definition of + inequality-constrained multinomial models and the implemented computational + methods is provided in: Heck, D.W., & Davis-Stober, C.P. (2019). + Multinomial models with linear inequality constraints: Overview and improvements + of computational methods for Bayesian inference. Journal of Mathematical + Psychology, 91, 70-87. . + Inequality-constrained multinomial models have applications in the area of + judgment and decision making to fit and test random utility models + (Regenwetter, M., Dana, J., & Davis-Stober, C.P. (2011). Transitivity of + preferences. Psychological Review, 118, 42–56, ) or to + perform outcome-based strategy classification to select the decision strategy + that provides the best account for a vector of observed choice frequencies + (Heck, D.W., Hilbig, B.E., & Moshagen, M. (2017). From information + processing to decisions: Formalizing and comparing probabilistic choice models. + Cognitive Psychology, 96, 26–40. ). + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multinomineq + url_git: https://github.com/danheck/multinomineq +multIntTestFunc: + version: 0.3.0 + title: Provides Test Functions for Multivariate Integration + maintainer: Klaus Herrmann + description: |- + Provides implementations of functions that can be used to + test multivariate integration routines. The package covers six + different integration domains (unit hypercube, unit ball, unit sphere, + standard simplex, non-negative real numbers and R^n). For each domain + several functions with different properties (smooth, + non-differentiable, ...) are available. The functions are available in + all dimensions n >= 1. For each function the exact value of the + integral is known and implemented to allow testing the accuracy of + multivariate integration routines. Details on the available test + functions can be found at on the development website. + date_publication: '2024-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multIntTestFunc + url_git: https://github.com/KlausHerrmann/multIntTestFunc +MultiObjMatch: + version: 1.0.0 + title: Multi-Objective Matching Algorithm + maintainer: Shichao Han + description: |- + Matching algorithm based on network-flow structure. + Users are able to modify the emphasis on three different + optimization goals: two different distance measures and + the number of treated units left unmatched. The method is proposed by Pimentel + and Kelz (2019) . + The 'rrelaxiv' package, which provides an alternative solver for + the underlying network flow problems, carries an + academic license and is not available on CRAN, but + may be downloaded from Github at + . + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiObjMatch + url_git: '' +multiocc: + version: 0.2.1 + title: Fits Multivariate Spatio-Temporal Occupancy Model + maintainer: Staci Hepler + description: Spatio-temporal multivariate occupancy models can handle multiple species + in occupancy models. This method for fitting such models is described in Hepler + and Erhardt (2021) "A spatiotemporal model for multivariate occupancy data" . + date_publication: '2023-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiocc + url_git: '' +MultiOrd: + version: 2.4.3 + title: Generation of Multivariate Ordinal Variates + maintainer: Ran Gao + description: A method for multivariate ordinal data generation given marginal distributions + and correlation matrix based on the methodology proposed by Demirtas (2006) . + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiOrd + url_git: '' +multipanelfigure: + version: 2.1.6 + title: Infrastructure to Assemble Multi-Panel Figures (from Grobs) + maintainer: Johannes Graumann + description: |- + Tools to create a layout for figures made of multiple panels, and + to fill the panels with base, 'lattice', 'ggplot2' and 'ComplexHeatmap' + plots, grobs, as well as content from all image formats supported by + 'ImageMagick' (accessed through 'magick'). + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multipanelfigure + url_git: '' +MultiPhen: + version: 2.0.3 + title: A Package to Test for Multi-Trait Association + maintainer: Lachlan Coin + description: |- + Performs genetic association tests between SNPs + (one-at-a-time) and multiple phenotypes (separately or in joint + model). + date_publication: '2020-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiPhen + url_git: '' +MultipleBreakpoints: + version: 0.1.0 + title: |- + Estimating Multiple Breakpoints for a Sequence of Realizations + of Bernoulli Variables + maintainer: Nicolas Froelich + description: The iterative procedure estimates structural changes in the success + probability of Bernoulli variables. It estimates the number and location of the + breakpoints as well as the success probability of the different sequences between + the breakpoints. In addition, it provides a graphical illustration of the result. + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultipleBreakpoints + url_git: '' +MultipleBubbles: + version: 0.2.0 + title: Test and Detection of Explosive Behaviors for Time Series + maintainer: Pedro Araujo + description: Provides the Augmented Dickey-Fuller test and its variations to check + the existence of bubbles (explosive behavior) for time series, based on the article + by Peter C. B. Phillips, Shuping Shi and Jun Yu (2015a) . + Some functions may take a while depending on the size of the data used, or the + number of Monte Carlo replications applied. + date_publication: '2018-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultipleBubbles + url_git: '' +multipleDL: + version: 1.0.0 + title: |- + Addressing Detection Limits by Cumulative Probability Models + (CPMs) + maintainer: Yuqi Tian + description: Build CPMs (cumulative probability models, also known as cumulative + link models) to account for detection limits (both single and multiple detection + limits) in response variables. Conditional quantiles and conditional CDFs can + be calculated based on fitted models. The package implements methods described + in Tian, Y., Li, C., Tu, S., James, N. T., Harrell, F. E., & Shepherd, B. E. (2022). + "Addressing Detection Limits with Semiparametric Cumulative Probability Models". + . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multipleDL + url_git: '' +multipleNCC: + version: 1.2-4 + title: Weighted Cox-Regression for Nested Case-Control Data + maintainer: Nathalie C. Stoer + description: |- + Fit Cox proportional hazard models with a weighted + partial likelihood. It handles one or multiple endpoints, additional matching + and makes it possible to reuse controls for other endpoints + Stoer NC and Samuelsen SO (2016) . + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multipleNCC + url_git: '' +multipleOutcomes: + version: '0.4' + title: |- + Asymptotic Covariance Matrix of Regression Models for Multiple + Outcomes + maintainer: Han Zhang + description: Regression models can be fitted for multiple outcomes simultaneously. + This package computes estimates of parameters across fitted models and returns + the matrix of asymptotic covariance. Various applications of this package, including + CUPED (Controlled Experiments Utilizing Pre-Experiment Data), multiple comparison + adjustment, are illustrated. + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multipleOutcomes + url_git: '' +MultipleRegression: + version: 0.1.0 + title: Multiple Regression Analysis + maintainer: Alcinei Mistico Azevedo + description: 'Tools to analysis of experiments having two or more quantitative explanatory + variables and one quantitative dependent variable. Experiments can be without + repetitions or with a statistical design (Hair JF, 2016) . + Pacote para uma analise de experimentos havendo duas ou mais variaveis explicativas + quantitativas e uma variavel dependente quantitativa. Os experimentos podem ser + sem repeticoes ou com delineamento estatistico (Hair JF, 2016) .' + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultipleRegression + url_git: '' +multiplestressR: + version: 0.1.1 + title: |- + Additive and Multiplicative Null Models for Multiple Stressor + Data + maintainer: Benjamin Burgess + description: |- + An implementation of the additive (Gurevitch et al., 2000 ) + and multiplicative (Lajeunesse, 2011 ) factorial null models for + multiple stressor data (Burgess et al., 2021 ). Effect sizes + are able to be calculated for either null model, and subsequently classified into one of + four different interaction classifications (e.g., antagonistic or synergistic interactions). + Analyses can be conducted on data for single experiments through to large meta-analytical datasets. + Minimal input (or statistical knowledge) is required, with any output easily understood. + Summary figures are also able to be easily generated. + date_publication: '2021-10-26' + bug_reports: '' + url: https://benjburgess.github.io/multiplestressR/ + url_cran: https://CRAN.R-project.org/package=multiplestressR + url_git: '' +multiplex: + version: '3.9' + title: Algebraic Tools for the Analysis of Multiple Social Networks + maintainer: Antonio Rivero Ostoic + description: |- + Algebraic procedures for analyses of multiple social networks are delivered with this + package as described in Ostoic (2020) . 'multiplex' makes + possible, among other things, to create and manipulate multiplex, multimode, and + multilevel network data with different formats. Effective ways are available to treat + multiple networks with routines that combine algebraic systems like the partially ordered + semigroup with decomposition procedures or semiring structures with the relational + bundles occurring in different types of multivariate networks. 'multiplex' provides also + an algebraic approach for affiliation networks through Galois derivations between families + of the pairs of subsets in the two domains of the network with visualization options. + date_publication: '2025-01-29' + bug_reports: https://github.com/mplex/multiplex/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=multiplex + url_git: https://github.com/mplex/multiplex/ +MultiplierDEA: + version: 0.1.19 + title: Multiplier Data Envelopment Analysis and Cross Efficiency + maintainer: Aurobindh Kalathil Puthanpura + description: 'Functions are provided for calculating efficiency using multiplier + DEA (Data Envelopment Analysis): Measuring the efficiency of decision making units + (Charnes et al., 1978 ) and cross efficiency + using single and two-phase approach. In addition, it includes some datasets for + calculating efficiency and cross efficiency.' + date_publication: '2022-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiplierDEA + url_git: '' +multipol: + version: 1.0-9 + title: Multivariate Polynomials + maintainer: Robin K. S. Hankin + description: |- + Various utilities to manipulate multivariate polynomials. The + package is almost completely superceded by the 'spray' and 'mvp' packages, + which are much more efficient. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multipol + url_git: '' +multiRDPG: + version: 1.0.1 + title: Multiple Random Dot Product Graphs + maintainer: Agnes Martine Nielsen + description: |- + Fits the Multiple Random Dot Product Graph Model and performs a test + for whether two networks come from the same distribution. Both methods are + proposed in Nielsen, A.M., Witten, D., (2018) "The Multiple Random Dot Product Graph + Model", arXiv preprint (Submitted to Journal of Computational + and Graphical Statistics). + date_publication: '2018-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiRDPG + url_git: '' +multirich: + version: 2.1.3 + title: Calculate Multivariate Richness via UTC and sUTC + maintainer: Alexander Keyel + description: |- + Functions to calculate Unique Trait Combinations (UTC) and scaled + Unique Trait Combinations (sUTC) as measures of multivariate richness. The + package can also calculate beta-diversity for trait richness and can + partition this into nestedness-related and turnover components. The code + will also calculate several measures of overlap. See Keyel and Wiegand + (2016) for more details. + date_publication: '2021-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multirich + url_git: '' +multiridge: + version: '1.11' + title: Fast Cross-Validation for Multi-Penalty Ridge Regression + maintainer: Mark A. van de Wiel + description: Multi-penalty linear, logistic and cox ridge regression, including + estimation of the penalty parameters by efficient (repeated) cross-validation + and marginal likelihood maximization. Multiple high-dimensional data types that + require penalization are allowed, as well as unpenalized variables. Paired and + preferential data types can be specified. See Van de Wiel et al. (2021), . + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiridge + url_git: '' +MultiRNG: + version: 1.2.4 + title: Multivariate Pseudo-Random Number Generation + maintainer: Ran Gao + description: 'Pseudo-random number generation for 11 multivariate distributions: + Normal, t, Uniform, Bernoulli, Hypergeometric, Beta (Dirichlet), Multinomial, + Dirichlet-Multinomial, Laplace, Wishart, and Inverted Wishart. The details of + the method are explained in Demirtas (2004) .' + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiRNG + url_git: '' +MultiRobust: + version: 1.0.5 + title: Multiply Robust Methods for Missing Data Problems + maintainer: Shixiao Zhang + description: Multiply robust estimation for population mean (Han and Wang 2013) + , regression analysis (Han 2014) + (Han 2016) and quantile regression (Han et al. 2019) + . + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiRobust + url_git: '' +multiROC: + version: 1.1.1 + title: |- + Calculating and Visualizing ROC and PR Curves Across Multi-Class + Classifications + maintainer: Runmin Wei + description: Tools to solve real-world problems with multiple classes classifications + by computing the areas under ROC and PR curve via micro-averaging and macro-averaging. + The vignettes of this package can be found via . + The methodology is described in V. Van Asch (2013) + and Pedregosa et al. (2011) . + date_publication: '2018-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiROC + url_git: '' +MultIS: + version: 0.6.2 + title: |- + Reconstruction of Clones from Integration Site Readouts and + Visualization + maintainer: Sebastian Wagner + description: |- + Tools necessary to reconstruct clonal affiliations from + temporally and/or spatially separated measurements of viral + integration sites. For this means it utilizes correlations present + in the relative readouts of the integration sites. Furthermore, + facilities for filtering of the data and visualization of different + steps in the pipeline are provided with the package. + date_publication: '2021-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultIS + url_git: '' +MultiscaleDTM: + version: 0.9.1 + title: Multi-Scale Geomorphometric Terrain Attributes + maintainer: Alexander Ilich + description: Calculates multi-scale geomorphometric terrain attributes from regularly + gridded digital terrain models using a variable focal windows size (Ilich et al. + (2023) ). + date_publication: '2025-01-21' + bug_reports: https://github.com/ailich/MultiscaleDTM/issues + url: https://ailich.github.io/MultiscaleDTM/ + url_cran: https://CRAN.R-project.org/package=MultiscaleDTM + url_git: https://github.com/ailich/MultiscaleDTM +multiselect: + version: 0.1.0 + title: |- + Selecting Combinations of Predictors by Leveraging Multiple AUCs + for an Ordered Multilevel Outcome + maintainer: Allison Meisner + description: Uses multiple AUCs to select a combination of predictors when the outcome + has multiple (ordered) levels and the focus is discriminating one particular level + from the others. This method is most naturally applied to settings where the outcome + has three levels. (Meisner, A, Parikh, CR, and Kerr, KF (2017) .) + date_publication: '2018-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiselect + url_git: '' +multisensi: + version: 2.1-1 + title: Multivariate Sensitivity Analysis + maintainer: Hervé Monod + description: Functions to perform sensitivity analysis on a model with multivariate + output. + date_publication: '2018-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multisensi + url_git: '' +multisite.accuracy: + version: '1.3' + title: Estimation of Accuracy in Multisite Machine-Learning Models + maintainer: Joaquim Radua + description: 'The effects of the site may severely bias the accuracy of a multisite + machine-learning model, even if the analysts removed them when fitting the model + in the ''training set'' and applying the model in the ''test set'' (Solanes et + al., Neuroimage 2023, 265:119800). This simple R package estimates the accuracy + of a multisite machine-learning model unbiasedly, as described in (Solanes et + al., Psychiatry Research: Neuroimaging 2021, 314:111313). It currently supports + the estimation of sensitivity, specificity, balanced accuracy (for binary or multinomial + variables), the area under the curve, correlation, mean squarer error, and hazard + ratio for binomial, multinomial, gaussian, and survival (time-to-event) outcomes.' + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multisite.accuracy + url_git: '' +MultisiteMediation: + version: 0.0.4 + title: Causal Mediation Analysis in Multisite Trials + maintainer: Xu Qin + description: Multisite causal mediation analysis using the methods proposed by Qin + and Hong (2017) , Qin, Hong, Deutsch, and Bein (2019) + , and Qin, Deutsch, and Hong (2021) . + It enables causal mediation analysis in multisite trials, in which individuals + are assigned to a treatment or a control group at each site. It allows for estimation + and hypothesis testing for not only the population average but also the between-site + variance of direct and indirect effects transmitted through one single mediator + or two concurrent (conditionally independent) mediators. This strategy conveniently + relaxes the assumption of no treatment-by-mediator interaction while greatly simplifying + the outcome model specification without invoking strong distributional assumptions. + This package also provides a function that can further incorporate a sample weight + and a nonresponse weight for multisite causal mediation analysis in the presence + of complex sample and survey designs and non-random nonresponse, to enhance both + the internal validity and external validity. The package also provides a weighting-based + balance checking function for assessing the remaining overt bias. + date_publication: '2021-09-05' + bug_reports: https://github.com/Xu-Qin/MultisiteMediation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MultisiteMediation + url_git: https://github.com/Xu-Qin/MultisiteMediation +MultiSkew: + version: 1.1.1 + title: Measures, Tests and Removes Multivariate Skewness + maintainer: Cinzia Franceschini + description: Computes the third multivariate cumulant of either the raw, centered + or standardized data. Computes the main measures of multivariate skewness, together + with their bootstrap distributions. Finally, computes the least skewed linear + projections of the data. + date_publication: '2017-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiSkew + url_git: '' +multisom: + version: '1.3' + title: Clustering a Data Set using Multi-SOM Algorithm + maintainer: Sarra Chair + description: 'Implements two versions of the algorithm namely: stochastic and batch. + The package determines also the best number of clusters and offers to the user + the best clustering scheme from different results.' + date_publication: '2017-05-23' + bug_reports: '' + url: https://sites.google.com/site/malikacharrad/research/multisom-package + url_cran: https://CRAN.R-project.org/package=multisom + url_git: '' +multispatialCCM: + version: '1.3' + title: Multispatial Convergent Cross Mapping + maintainer: Adam Clark + description: The multispatial convergent cross mapping algorithm can be used as + a test for causal associations between pairs of processes represented by time + series. This is a combination of convergent cross mapping (CCM), described in + Sugihara et al., 2012, Science, 338, 496-500, and dew-drop regression, described + in Hsieh et al., 2008, American Naturalist, 171, 71–80. The algorithm allows CCM + to be implemented on data that are not from a single long time series. Instead, + data can come from many short time series, which are stitched together using bootstrapping. + date_publication: '2023-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multispatialCCM + url_git: '' +MultiStatM: + version: 2.0.0 + title: Multivariate Statistical Methods + maintainer: Emanuele Taufer + description: |- + Algorithms to build set partitions and commutator matrices and their use in the + construction of multivariate d-Hermite polynomials; estimation and derivation of theoretical vector moments and vector + cumulants of multivariate distributions; conversion formulae for multivariate moments and cumulants. Applications to + estimation and derivation of multivariate measures of skewness and kurtosis; estimation and derivation of asymptotic + covariances for d-variate Hermite polynomials, multivariate moments and cumulants and measures of skewness and kurtosis. + The formulae implemented are discussed in Terdik (2021, ISBN:9783030813925), "Multivariate Statistical Methods". + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiStatM + url_git: '' +multitaper: + version: 1.0-17 + title: Spectral Analysis Tools using the Multitaper Method + maintainer: Karim Rahim + description: Implements multitaper spectral analysis using discrete prolate spheroidal + sequences (Slepians) and sine tapers. It includes an adaptive weighted multitaper + spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex + demodulation. The Slepians sequences are generated efficiently using a tridiagonal + matrix solution, and jackknifed confidence intervals are available for most estimates. + This package is an implementation of the method described in D.J. Thomson (1982) + "Spectrum estimation and harmonic analysis" . + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multitaper + url_git: https://github.com/krahim/multitaper/ +multitool: + version: 0.1.4 + title: Run Multiverse Style Analyses + maintainer: Ethan Young + description: |- + Run the same analysis over a range of arbitrary data processing + decisions. 'multitool' provides an interface for creating alternative + analysis pipelines and turning them into a grid of all possible pipelines. + Using this grid as a blueprint, you can model your data across all possible + pipelines and summarize the results. + date_publication: '2024-02-08' + bug_reports: https://github.com/ethan-young/multitool/issues + url: https://ethan-young.github.io/multitool/ + url_cran: https://CRAN.R-project.org/package=multitool + url_git: https://github.com/ethan-young/multitool +MultiTraits: + version: 0.3.0 + title: Analyzing and Visualizing Multidimensional Plant Traits + maintainer: Yan He + description: Implements analytical methods for multidimensional plant traits, including + Competitors-Stress tolerators-Ruderals strategy analysis using leaf traits, Leaf-Height-Seed + strategy analysis, Niche Periodicity Table analysis, and Trait Network analysis. + Provides functions for data analysis, visualization, and network metrics calculation. + Methods are based on Grime (1974) , Pierce et al. (2017) + , Westoby (1998) , Yang + et al. (2022) , Winemiller et al. (2015) , + He et al. (2020) . + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiTraits + url_git: '' +multiUS: + version: 1.2.3 + title: |- + Functions for the Courses Multivariate Analysis and Computer + Intensive Methods + maintainer: Cugmas Marjan + description: Provides utility functions for multivariate analysis (factor analysis, + discriminant analysis, and others). The package is primary written for the course + Multivariate analysis and for the course Computer intensive methods at the masters + program of Applied Statistics at University of Ljubljana. + date_publication: '2023-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiUS + url_git: '' +multivar: + version: 1.1.0 + title: |- + Penalized Estimation of Multiple-Subject Vector Autoregressive + (multi-VAR) Models + maintainer: Zachary Fisher + description: Functions for simulating, estimating and forecasting stationary Vector + Autoregressive (VAR) models for multiple subject data using the penalized multi-VAR + framework in Fisher, Kim and Pipiras (2020) . + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multivar + url_git: '' +multivariance: + version: 2.4.1 + title: Measuring Multivariate Dependence Using Distance Multivariance + maintainer: Björn Böttcher + description: |- + Distance multivariance is a measure of dependence which can be used to detect + and quantify dependence of arbitrarily many random vectors. The necessary functions are + implemented in this packages and examples are given. It includes: distance multivariance, + distance multicorrelation, dependence structure detection, tests of independence and + copula versions of distance multivariance based on the Monte Carlo empirical transform. + Detailed references are given in the package description, as starting point for the + theoretic background we refer to: + B. Böttcher, Dependence and Dependence Structures: Estimation and Visualization Using + the Unifying Concept of Distance Multivariance. Open Statistics, Vol. 1, No. 1 (2020), + . + date_publication: '2021-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multivariance + url_git: '' +MultivariateAnalysis: + version: 0.5.0 + title: Pacote Para Analise Multivariada + maintainer: Alcinei Mistico Azevedo + description: |- + Package with multivariate analysis methodologies for experiment evaluation. + The package estimates dissimilarity measures, builds dendrograms, obtains MANOVA, + principal components, canonical variables, etc. (Pacote com metodologias de analise + multivariada para avaliação de experimentos. O pacote estima medidas de dissimilaridade, + construi de dendogramas, obtem a MANOVA, componentes principais, variaveis canonicas, etc.) + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultivariateAnalysis + url_git: '' +MultivariateRandomForest: + version: 1.1.5 + title: Models Multivariate Cases Using Random Forests + maintainer: Raziur Rahman + description: |- + Models and predicts multiple output features in single random forest considering the + linear relation among the output features, see details in Rahman et al (2017). + date_publication: '2017-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultivariateRandomForest + url_git: '' +multivarious: + version: 0.2.0 + title: Extensible Data Structures for Multivariate Analysis + maintainer: Bradley Buchsbaum + description: Provides a set of basic and extensible data structures and functions + for multivariate analysis, including dimensionality reduction techniques, projection + methods, and preprocessing functions. The aim of this package is to offer a flexible + and user-friendly framework for multivariate analysis that can be easily extended + for custom requirements and specific data analysis tasks. + date_publication: '2024-03-28' + bug_reports: '' + url: https://bbuchsbaum.github.io/multivarious/ + url_cran: https://CRAN.R-project.org/package=multivarious + url_git: '' +MultiVarMI: + version: '1.0' + title: Multiple Imputation for Multivariate Data + maintainer: Rawan Allozi + description: Fully parametric Bayesian multiple imputation framework for massive + multivariate data of different variable types as seen in Demirtas, H. (2017) . + date_publication: '2018-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiVarMI + url_git: '' +MultiVarSel: + version: 1.1.3 + title: Variable Selection in a Multivariate Linear Model + maintainer: Marie Perrot-Dockès + description: |- + It performs variable selection in a multivariate linear model by estimating the covariance matrix + of the residuals then use it to remove the dependence that may exist among the responses and eventually performs variable selection by using the Lasso criterion. + The method is described in the paper Perrot-Dockès et al. (2017) . + date_publication: '2019-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiVarSel + url_git: '' +multivator: + version: 1.1-11 + title: A Multivariate Emulator + maintainer: Robin K. S. Hankin + description: A multivariate generalization of the emulator package. + date_publication: '2023-08-22' + bug_reports: https://github.com/RobinHankin/multivator + url: '' + url_cran: https://CRAN.R-project.org/package=multivator + url_git: https://github.com/RobinHankin/multivator +multiverse: + version: 0.6.2 + title: Create 'multiverse analysis' in R + maintainer: Abhraneel Sarma + description: |- + Implement 'multiverse' style analyses (Steegen S., Tuerlinckx F, Gelman A., Vanpaemal, W., 2016) + to show the robustness of statistical inference. + 'Multiverse analysis' is a philosophy of statistical reporting where paper authors + report the outcomes of many different statistical analyses in order to show how + fragile or robust their findings are. The 'multiverse' package + (Sarma A., Kale A., Moon M., Taback N., Chevalier F., Hullman J., Kay M., 2021) + allows users to concisely and flexibly implement 'multiverse-style' + analysis, which involve declaring alternate ways of performing an analysis step, in R and R Notebooks. + date_publication: '2024-10-07' + bug_reports: https://github.com/MUCollective/multiverse/issues/ + url: https://mucollective.github.io/multiverse/ + url_cran: https://CRAN.R-project.org/package=multiverse + url_git: https://github.com/mucollective/multiverse/ +multiview: + version: '0.8' + title: Cooperative Learning for Multi-View Analysis + maintainer: Balasubramanian Narasimhan + description: Cooperative learning combines the usual squared error loss of predictions + with an agreement penalty to encourage the predictions from different data views + to agree. By varying the weight of the agreement penalty, we get a continuum of + solutions that include the well-known early and late fusion approaches. Cooperative + learning chooses the degree of agreement (or fusion) in an adaptive manner, using + a validation set or cross-validation to estimate test set prediction error. In + the setting of cooperative regularized linear regression, the method combines + the lasso penalty with the agreement penalty (Ding, D., Li, S., Narasimhan, B., + Tibshirani, R. (2021) ). + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiview + url_git: '' +multiwave: + version: '1.4' + title: Estimation of Multivariate Long-Memory Models Parameters + maintainer: Sophie Achard + description: |- + Computation of an estimation of the long-memory parameters and + the long-run covariance matrix using a multivariate model + (Lobato (1999) ; Shimotsu (2007) ). Two semi-parametric methods are + implemented: a Fourier based approach (Shimotsu (2007) ) and a wavelet based + approach (Achard and Gannaz (2016) ). + date_publication: '2019-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiwave + url_git: '' +multiway: + version: 1.0-6 + title: Component Models for Multi-Way Data + maintainer: Nathaniel E. Helwig + description: Fits multi-way component models via alternating least squares algorithms + with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, + Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor + Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis. + date_publication: '2019-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=multiway + url_git: '' +MultiwayRegression: + version: '1.2' + title: Perform Tensor-on-Tensor Regression + maintainer: Eric F. Lock + description: Functions to predict one multi-way array (i.e., a tensor) from another + multi-way array, using a low-rank CANDECOMP/PARAFAC (CP) factorization and a ridge + (L_2) penalty [Lock, EF (2018) ]. Also includes + functions to sample from the Bayesian posterior of a tensor-on-tensor model. + date_publication: '2019-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultiwayRegression + url_git: '' +multiwayvcov: + version: 1.2.3 + title: Multi-Way Standard Error Clustering + maintainer: Nathaniel Graham + description: |- + Exports two functions implementing + multi-way clustering using the method suggested by Cameron, Gelbach, & + Miller (2011) and cluster (or block) + bootstrapping for estimating variance-covariance matrices. Normal one and + two-way clustering matches the results of other common statistical + packages. Missing values are handled transparently and rudimentary + parallelization support is provided. + date_publication: '2016-05-05' + bug_reports: '' + url: http://sites.google.com/site/npgraham1/research/code + url_cran: https://CRAN.R-project.org/package=multiwayvcov + url_git: '' +MultNonParam: + version: 1.3.9 + title: Multivariate Nonparametric Methods + maintainer: John E. Kolassa + description: A collection of multivariate nonparametric methods, selected in part + to support an MS level course in nonparametric statistical methods. Methods include + adjustments for multiple comparisons, implementation of multivariate Mann-Whitney-Wilcoxon + testing, inversion of these tests to produce a confidence region, some permutation + tests for linear models, and some algorithms for calculating exact probabilities + associated with one- and two- stage testing involving Mann-Whitney-Wilcoxon statistics. Supported + by grant NSF DMS 1712839. See Kolassa and Seifu (2013) . + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultNonParam + url_git: '' +MultOrdRS: + version: 0.1-3 + title: Model Multivariate Ordinal Responses Including Response Styles + maintainer: Gunther Schauberger + description: In the case of multivariate ordinal responses, parameter estimates + can be severely biased if personal response styles are ignored. This packages + provides methods to account for personal response styles and to explain the effects + of covariates on the response style, as proposed by Schauberger and Tutz 2021 + . The method is implemented both for the multivariate + cumulative model and the multivariate adjacent categories model. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultOrdRS + url_git: '' +multpois: + version: 0.3.3 + title: Analyze Nominal Response Data with the Multinomial-Poisson Trick + maintainer: Jacob O. Wobbrock + description: |- + Dichotomous responses having two categories can be analyzed + with stats::glm() or lme4::glmer() using the family=binomial option. + Unfortunately, polytomous responses with three or more unordered + categories cannot be analyzed similarly because there is no analogous + family=multinomial option. For between-subjects data, + nnet::multinom() can address this need, but it cannot handle random + factors and therefore cannot handle repeated measures. To address this + gap, we transform nominal response data into counts for each categorical + alternative. These counts are then analyzed using (mixed) Poisson regression + as per Baker (1994) . Omnibus analyses of variance can be + run along with post hoc pairwise comparisons. For users wishing to analyze nominal + responses from surveys or experiments, the functions in this package essentially + act as though stats::glm() or lme4::glmer() provide a family=multinomial option. + date_publication: '2025-02-09' + bug_reports: https://github.com/wobbrock/multpois/issues + url: '' + url_cran: https://CRAN.R-project.org/package=multpois + url_git: https://github.com/wobbrock/multpois/ +MultRegCMP: + version: 0.1.0 + title: |- + Bayesian Multivariate Conway-Maxwell-Poisson Regression Model + for Correlated Count Data + maintainer: Mauro Florez + description: Fits a Bayesian Regression Model for multivariate count data. This + model assumes that the data is distributed according to the Conway-Maxwell-Poisson + distribution, and for each response variable it is associate different covariates. + This model allows to account for correlations between the counts by using latent + effects based on the Chib and Winkelmann (2001) + proposal. + date_publication: '2024-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MultRegCMP + url_git: '' +MultSurvTests: + version: '0.2' + title: Permutation Tests for Multivariate Survival Analysis + maintainer: Lukas Arnroth + description: Multivariate version of the two-sample Gehan and logrank tests, as + described in L.J Wei & J.M Lachin (1984) and Persson et al. (2019). + date_publication: '2021-06-18' + bug_reports: https://github.com/lukketotte/MultSurvTests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MultSurvTests + url_git: https://github.com/lukketotte/MultSurvTests +multvardiv: + version: 1.0.10 + title: Multivariate Probability Distributions, Statistical Divergence + maintainer: Pierre Santagostini + description: |- + Multivariate generalized Gaussian distribution, + Multivariate Cauchy distribution, + Multivariate t distribution. + Distance between two distributions (see N. Bouhlel and A. Dziri (2019): , + N. Bouhlel and D. Rousseau (2022): , + N. Bouhlel and D. Rousseau (2023): ). + Manipulation of these multivariate probability distributions. + date_publication: '2024-12-20' + bug_reports: https://forgemia.inra.fr/imhorphen/multvardiv/-/issues + url: https://forgemia.inra.fr/imhorphen/multvardiv + url_cran: https://CRAN.R-project.org/package=multvardiv + url_git: '' +multxpert: + version: 0.1.1 + title: Common Multiple Testing Procedures and Gatekeeping Procedures + maintainer: Eric Nantz + description: |- + Implementation of commonly used p-value-based and + parametric multiple testing procedures (computation of adjusted + p-values and simultaneous confidence intervals) and parallel + gatekeeping procedures based on the methodology presented in + the book "Multiple Testing Problems in Pharmaceutical + Statistics" (edited by Alex Dmitrienko, Ajit C. Tamhane and + Frank Bretz) published by Chapman and Hall/CRC Press 2009. + date_publication: '2019-10-02' + bug_reports: '' + url: http://multxpert.com/wiki/MultXpert_package + url_cran: https://CRAN.R-project.org/package=multxpert + url_git: '' +MulvariateRandomForestVarImp: + version: 0.0.2 + title: Variable Importance Measures for Multivariate Random Forests + maintainer: Dogonadze Nika + description: Calculates two sets of post-hoc variable importance measures for multivariate + random forests. The first set of variable importance measures are given by the + sum of mean split improvements for splits defined by feature j measured on user-defined + examples (i.e., training or testing samples). The second set of importance measures + are calculated on a per-outcome variable basis as the sum of mean absolute difference + of node values for each split defined by feature j measured on user-defined examples + (i.e., training or testing samples). The user can optionally threshold both sets + of importance measures to include only splits that are statistically significant + as measured using an F-test. + date_publication: '2021-12-15' + bug_reports: https://github.com/Megatvini/VIM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MulvariateRandomForestVarImp + url_git: https://github.com/Megatvini/VIM/ +MuMIn: + version: 1.48.4 + title: Multi-Model Inference + maintainer: Kamil Bartoń + description: |- + Tools for model selection and model averaging with support for a + wide range of statistical models. Automated model selection through + subsets of the maximum model, with optional constraints for model + inclusion. Averaging of model parameters and predictions based on + model weights derived from information criteria (AICc and alike) + or custom model weighting schemes. + date_publication: '2024-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MuMIn + url_git: '' +munfold: + version: 0.3.5 + title: Metric Unfolding + maintainer: Martin Elff + description: |- + Multidimensional unfolding using Schoenemann's algorithm for metric + and Procrustes rotation of unfolding results. + date_publication: '2016-02-08' + bug_reports: '' + url: http://www.elff.eu/software/munfold/ + url_cran: https://CRAN.R-project.org/package=munfold + url_git: http://github.com/melff/munfold/ +munsell: + version: 0.5.1 + title: Utilities for Using Munsell Colours + maintainer: Charlotte Wickham + description: |- + Provides easy access to, and manipulation of, the Munsell + colours. Provides a mapping between Munsell's + original notation (e.g. "5R 5/10") and hexadecimal strings suitable + for use directly in R graphics. Also provides utilities + to explore slices through the Munsell colour tree, to transform + Munsell colours and display colour palettes. + date_publication: '2024-04-01' + bug_reports: https://github.com/cwickham/munsell/issues + url: '' + url_cran: https://CRAN.R-project.org/package=munsell + url_git: https://github.com/cwickham/munsell/ +munsellinterpol: + version: 3.1-0 + title: |- + Interpolate Munsell Renotation Data from Hue Value/Chroma to + CIE/RGB + maintainer: Glenn Davis + description: Methods for interpolating data in the Munsell color system following + the ASTM D-1535 standard. Hues and chromas with decimal values can be interpolated + and converted to/from the Munsell color system and CIE xyY, CIE XYZ, CIE Lab, + CIE Luv, or RGB. Includes ISCC-NBS color block lookup. Based on the work by + Paul Centore, "The Munsell and Kubelka-Munk Toolbox". + date_publication: '2025-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=munsellinterpol + url_git: '' +MuPETFlow: + version: 0.1.1 + title: |- + Multiple Ploidy Estimation Tool for all Species Compatible with + Flow Cytometry + maintainer: Cintia Gómez-Muñoz + description: A graphical user interface tool to estimate ploidy from DNA cells stained + with fluorescent dyes and analyzed by flow cytometry, following the methodology + of Gómez-Muñoz and Fischer (2024) . Features include + multiple file uploading and configuration, peak fluorescence intensity detection, + histogram visualizations, peak error curation, ploidy and genome size calculations, + and easy results export. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MuPETFlow + url_git: '' +muRL: + version: 0.1-13 + title: Mailmerge using R, LaTeX, and the Web + maintainer: Ryan T. Moore + description: Provides mailmerge methods for reading spreadsheets of addresses and + other relevant information to create standardized but customizable letters. Provides + a method for mapping US ZIP codes, including those of letter recipients. Provides + a method for parsing and processing html code from online job postings of the + American Political Science Association. + date_publication: '2023-08-22' + bug_reports: '' + url: https://www.ryantmoore.org/software.murl.html + url_cran: https://CRAN.R-project.org/package=muRL + url_git: '' +murphydiagram: + version: 0.12.2 + title: Murphy Diagrams for Forecast Comparisons + maintainer: Fabian Krueger + description: |- + Data and code for the paper by Ehm, Gneiting, Jordan and + Krueger ('Of Quantiles and Expectiles: Consistent Scoring Functions, Choquet + Representations, and Forecast Rankings', JRSS-B, 2016 ). + date_publication: '2019-12-06' + bug_reports: '' + url: https://sites.google.com/site/fk83research/code + url_cran: https://CRAN.R-project.org/package=murphydiagram + url_git: '' +muRty: + version: 0.3.1 + title: Murty's Algorithm for k-Best Assignments + maintainer: Aljaz Jelenko + description: Calculates k-best solutions and costs for an assignment problem following + the method outlined in Murty (1968) . + date_publication: '2020-02-29' + bug_reports: https://github.com/arg0naut91/muRty/issues + url: '' + url_cran: https://CRAN.R-project.org/package=muRty + url_git: https://github.com/arg0naut91/muRty +MUS: + version: 0.1.6 + title: |- + Monetary Unit Sampling and Estimation Methods, Widely Used in + Auditing + maintainer: Henning Prömpers + description: Sampling and evaluation methods to apply Monetary Unit Sampling (or + in older literature Dollar Unit Sampling) during an audit of financial statements. + date_publication: '2019-03-20' + bug_reports: https://github.com/alsguimaraes/MUS + url: '' + url_cran: https://CRAN.R-project.org/package=MUS + url_git: '' +musclesyneRgies: + version: 1.2.5 + title: Extract Muscle Synergies from Electromyography + maintainer: Alessandro Santuz + description: |- + Provides a framework to factorise electromyography (EMG) data. + Tools are provided for raw data pre-processing, non negative matrix factorisation, + classification of factorised data and plotting of obtained outcomes. + In particular, reading from ASCII files is supported, along with wide-used + filtering approaches to process EMG data. All steps include one or more sensible + defaults that aim at simplifying the workflow. Yet, all functions are largely + tunable at need. Example data sets are included. + date_publication: '2022-07-19' + bug_reports: https://github.com/alesantuz/musclesyneRgies/issues + url: '' + url_cran: https://CRAN.R-project.org/package=musclesyneRgies + url_git: https://github.com/alesantuz/musclesyneRgies +music: + version: 0.1.2 + title: Learn and Experiment with Music Theory + maintainer: Efstathios D. Gennatas + description: An aid for learning and using music theory. You can build chords, scales, + and chord progressions using 12-note equal temperament tuning (12-ET) or user-defined + tuning. Includes functions to visualize notes on a piano using ASCII plots in + the console and to plot waveforms using base graphics. It allows simple playback + of notes and chords using the 'audio' package. + date_publication: '2022-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=music + url_git: https://github.com/egenn/music +musica: + version: 0.1.3 + title: Multiscale Climate Model Assessment + maintainer: Martin Hanel + description: Provides functions allowing for (1) easy aggregation of multivariate + time series into custom time scales, (2) comparison of statistical summaries between + different data sets at multiple time scales (e.g. observed and bias-corrected + data), (3) comparison of relations between variables and/or different data sets + at multiple time scales (e.g. correlation of precipitation and temperature in + control and scenario simulation) and (4) transformation of time series at custom + time scales. + date_publication: '2016-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=musica + url_git: '' +musicNMR: + version: '1.0' + title: Conversion of Nuclear Magnetic Resonance Spectra in Audio Files + maintainer: Stefano Cacciatore + description: 'A collection of functions for converting and visualization the free + induction decay of mono dimensional nuclear magnetic resonance (NMR) spectra into + an audio file. It facilitates the conversion of Bruker datasets in files WAV. + The sound of NMR signals could provide an alternative to the current representation + of the individual metabolic fingerprint and supply equally significant information. + The package includes also NMR spectra of the urine samples provided by four healthy + donors. Based on Cacciatore S, Saccenti E, Piccioli M. Hypothesis: the sound of + the individual metabolic phenotype? Acoustic detection of NMR experiments. OMICS. + 2015;19(3):147-56. .' + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=musicNMR + url_git: '' +musicXML: + version: 1.0.1 + title: Data Sonification using 'musicXML' + maintainer: Benjamin Renard + description: |- + A set of tools to facilitate data sonification and handle the 'musicXML' format . + Several classes are defined for basic musical objects such as note pitch, note duration, note, measure and score. + Moreover, sonification utilities functions are provided, e.g. to map data into musical attributes such as pitch, loudness or duration. + A typical sonification workflow hence looks like: get data; map them to musical attributes; create and write the 'musicXML' score, + which can then be further processed using specialized music software (e.g. 'MuseScore', 'GuitarPro', etc.). + Examples can be found in the blog , the presentation by Renard and Le Bescond (2022, ) or the poster by Renard et al. (2023, ). + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=musicXML + url_git: '' +mutationtypes: + version: 0.0.1 + title: |- + Validate and Convert Mutational Impacts Using Standard Genomic + Dictionaries + maintainer: Sam El-Kamand + description: |- + Check concordance of a vector of mutation impacts with standard dictionaries such as Sequence Ontology (SO) , Mutation Annotation Format (MAF) or Prediction and Annotation of Variant Effects (PAVE) . + It enables conversion between SO/PAVE and MAF terms and selection of the most severe consequence where multiple ampersand (&) delimited impacts are given. + date_publication: '2023-12-14' + bug_reports: https://github.com/selkamand/mutationtypes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mutationtypes + url_git: https://github.com/selkamand/mutationtypes +mutoss: + version: 0.1-13 + title: Unified Multiple Testing Procedures + maintainer: Kornelius Rohmeyer + description: |- + Designed to ease the application and comparison of multiple + hypothesis testing procedures for FWER, gFWER, FDR and FDX. Methods are + standardized and usable by the accompanying 'mutossGUI'. + date_publication: '2023-03-14' + bug_reports: https://github.com/kornl/mutoss/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=mutoss + url_git: https://github.com/kornl/mutoss/ +mutossGUI: + version: 0.1-12 + title: A Graphical User Interface for the MuToss Project + maintainer: Kornelius Rohmeyer + description: Provides a graphical user interface for the MuToss Project. + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mutossGUI + url_git: http://mutoss.r-forge.r-project.org/ +mutSignatures: + version: 2.1.1 + title: Decipher Mutational Signatures from Somatic Mutational Catalogs + maintainer: Damiano Fantini + description: Cancer cells accumulate DNA mutations as result of DNA damage and DNA + repair processes. This computational framework is aimed at deciphering DNA mutational + signatures operating in cancer. The framework includes modules that support raw + data import and processing, mutational signature extraction, and results interpretation + and visualization. The framework accepts widely used file formats storing information + about DNA variants, such as Variant Call Format files. The framework performs + Non-Negative Matrix Factorization to extract mutational signatures explaining + the observed set of DNA mutations. Bootstrapping is performed as part of the analysis. + The framework supports parallelization and is optimized for use on multi-core + systems. The software was described by Fantini D et al (2020) + and is based on a custom R-based implementation of the original MATLAB WTSI framework + by Alexandrov LB et al (2013) . + date_publication: '2020-11-09' + bug_reports: '' + url: https://www.data-pulse.com/dev_site/mutsignatures/ + url_cran: https://CRAN.R-project.org/package=mutSignatures + url_git: '' +mutualinf: + version: 2.0.3 + title: Computation and Decomposition of the Mutual Information Index + maintainer: Cristian Angulo-Gonzalez + description: |- + The Mutual Information Index (M) introduced to social science literature by + Theil and Finizza (1971) is a multigroup + segregation measure that is highly decomposable and that according to Frankel + and Volij (2011) and Mora and Ruiz-Castillo + (2011) satisfies the Strong Unit + Decomposability and Strong Group Decomposability properties. This package allows + computing and decomposing the total index value into its "between" and + "within" terms. These last terms can also be decomposed into their + contributions, either by group or unit characteristics. The factors that produce + each "within" term can also be displayed at the user's request. The results can + be computed considering a variable or sets of variables that define separate + clusters. + date_publication: '2025-01-19' + bug_reports: https://github.com/RafaelFuentealbaC/mutualinf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mutualinf + url_git: https://github.com/RafaelFuentealbaC/mutualinf +MuViCP: + version: 1.3.2 + title: |- + MultiClass Visualizable Classification using Combination of + Projections + maintainer: Mohit Dayal + description: An ensemble classifier for multiclass classification. This is a novel + classifier that natively works as an ensemble. It projects data on a large number + of matrices, and uses very simple classifiers on each of these projections. The + results are then combined, ideally via Dempster-Shafer Calculus. + date_publication: '2016-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MuViCP + url_git: '' +MUVR2: + version: 0.1.0 + title: Multivariate Methods with Unbiased Variable Selection + maintainer: Yingxiao Yan + description: |- + Predictive multivariate modelling for metabolomics. + Types: Classification and regression. + Methods: Partial Least Squares, Random Forest ans Elastic Net + Data structures: Paired and unpaired Validation: repeated double cross-validation (Westerhuis et al. (2008), Filzmoser et al. (2009)) + Variable selection: Performed internally, through tuning in the inner cross-validation loop. + date_publication: '2024-09-16' + bug_reports: https://github.com/MetaboComp/MUVR2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MUVR2 + url_git: https://github.com/MetaboComp/MUVR2 +MVA: + version: 1.0-9 + title: An Introduction to Applied Multivariate Analysis with R + maintainer: Torsten Hothorn + description: |- + Functions, data sets, analyses and examples from the book + `An Introduction to Applied Multivariate Analysis with R' + (Brian S. Everitt and Torsten Hothorn, Springer, 2011). + date_publication: '2025-01-29' + bug_reports: '' + url: http://dx.doi.org/10.1007/978-1-4419-9650-3 + url_cran: https://CRAN.R-project.org/package=MVA + url_git: '' +mvabund: + version: 4.2.1 + title: Statistical Methods for Analysing Multivariate Abundance Data + maintainer: David Warton + description: |- + A set of tools for displaying, modeling and analysing + multivariate abundance data in community ecology. See + 'mvabund-package.Rd' for details of overall package organization. + The package is implemented with the Gnu Scientific Library + () and 'Rcpp' + () 'R' / 'C++' classes. + date_publication: '2022-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvabund + url_git: '' +MVar: + version: 2.2.5 + title: Multivariate Analysis + maintainer: Paulo Cesar Ossani + description: Multivariate analysis, having functions that perform simple correspondence + analysis (CA) and multiple correspondence analysis (MCA), principal components + analysis (PCA), canonical correlation analysis (CCA), factorial analysis (FA), + multidimensional scaling (MDS), linear (LDA) and quadratic discriminant analysis + (QDA), hierarchical and non-hierarchical cluster analysis, simple and multiple + linear regression, multiple factor analysis (MFA) for quantitative, qualitative, + frequency (MFACT) and mixed data, biplot, scatter plot, projection pursuit (PP), + grant tour method and other useful functions for the multivariate analysis. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVar + url_git: '' +MVar.pt: + version: 2.2.5 + title: Analise multivariada (brazilian portuguese) + maintainer: Paulo Cesar Ossani + description: Analise multivariada, tendo funcoes que executam analise de correspondencia + simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise + de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional + (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster + hierarquico e nao hierarquico, regressao linear simples e multipla, analise de + multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia + (MFACT) e dados mistos, biplot, scatter plot, projection pursuit (PP), grant tour + e outras funcoes uteis para a analise multivariada. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVar.pt + url_git: '' +MvBinary: + version: '1.1' + title: |- + Modelling Multivariate Binary Data with Blocks of Specific + One-Factor Distribution + maintainer: Mohammed Sedki + description: Modelling Multivariate Binary Data with Blocks of Specific One-Factor + Distribution. Variables are grouped into independent blocks. Each variable is + described by two continuous parameters (its marginal probability and its dependency + strength with the other block variables), and one binary parameter (positive or + negative dependency). Model selection consists in the estimation of the repartition + of the variables into blocks. It is carried out by the maximization of the BIC + criterion by a deterministic (faster) algorithm or by a stochastic (more time + consuming but optimal) algorithm. Tool functions facilitate the model interpretation. + date_publication: '2016-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MvBinary + url_git: '' +mvbutils: + version: 2.8.232 + title: |- + Workspace Organization, Code and Documentation Editing, Package + Prep and Editing, Etc + maintainer: Mark V. Bravington + description: Hierarchical workspace tree, code editing and backup, easy package + prep, editing of packages while loaded, per-object lazy-loading, easy documentation, + macro functions, and miscellaneous utilities. Needed by debug package. + date_publication: '2018-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvbutils + url_git: '' +mvcauchy: + version: '1.1' + title: Multivariate Cauchy Distribution + maintainer: Michail Tsagris + description: 'The Cauchy distribution is a special case of the t distribution when + the degrees of freedom are equal to 1. The functions are related to the multivariate + Cauchy distribution and include simulation, computation of the density, maximum + likelihood estimation, contour plot of the bivariate Cauchy distribution, and + discriminant analysis. References include: Nadarajah S. and Kotz S. (2008). "Estimation + methods for the multivariate t distribution". Acta Applicandae Mathematicae, 102(1): + 99--118. , and Kanti V. Mardia, John T. Kent and + John M. Bibby (1979). "Multivariate analysis", ISBN:978-0124712522. Academic Press, + London.' + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvcauchy + url_git: '' +mvcor: + version: '1.1' + title: Correlation Coefficients for Multivariate Data + maintainer: Michail Tsagris + description: 'Correlation coefficients for multivariate data, namely the squared + correlation coefficient and the RV coefficient (multivariate generalization of + the squared Pearson correlation coefficient). References include Mardia K.V., + Kent J.T. and Bibby J.M. (1979). "Multivariate Analysis". ISBN: 978-0124712522. + London: Academic Press.' + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvcor + url_git: '' +mvctm: + version: '1.2' + title: Multivariate Variance Components Tests for Multilevel Data + maintainer: Denis Larocque + description: Permutation tests for variance components for 2-level, 3-level and + 4-level data with univariate or multivariate responses. + date_publication: '2018-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvctm + url_git: '' +mvdalab: + version: '1.7' + title: Multivariate Data Analysis Laboratory + maintainer: Nelson Lee Afanador + description: An open-source implementation of latent variable methods and multivariate + modeling tools. The focus is on exploratory analyses using dimensionality reduction + methods including low dimensional embedding, classical multivariate statistical + tools, and tools for enhanced interpretation of machine learning methods (i.e. + intelligible models to provide important information for end-users). Target + domains include extension to dedicated applications e.g. for manufacturing process + modeling, spectroscopic analyses, and data mining. + date_publication: '2022-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvdalab + url_git: '' +mvDFA: + version: 0.0.4 + title: Multivariate Detrended Fluctuation Analysis + maintainer: Julien Patrick Irmer + description: 'This R package provides an implementation of multivariate extensions + of a well-known fractal analysis technique, Detrended Fluctuations Analysis (DFA; + Peng et al., 1995), for multivariate time series: multivariate + DFA (mvDFA). Several coefficients are implemented that take into account the correlation + structure of the multivariate time series to varying degrees. These coefficients + may be used to analyze long memory and changes in the dynamic structure that would + by univariate DFA. Therefore, this R package aims to extend and complement the + original univariate DFA (Peng et al., 1995) for estimating the scaling properties + of nonstationary time series.' + date_publication: '2023-06-15' + bug_reports: https://github.com/jpirmer/mvDFA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvDFA + url_git: https://github.com/jpirmer/mvDFA +MVET: + version: 0.1.0 + title: Multivariate Estimates and Tests + maintainer: Yeonseok Choi + description: Multivariate estimation and testing, currently a package for testing + parametric data. To deal with parametric data, various multivariate normality + tests and outlier detection are performed and visualized using the 'ggplot2' package. + Homogeneity tests for covariance matrices are also possible, as well as the Hotelling's + T-square test and the multivariate analysis of variance test. We are exploring + additional tests and visualization techniques, such as profile analysis and randomized + complete block design, to be made available in the future and making them easily + accessible to users. + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVET + url_git: https://github.com/YeonSeok-Choi/MVET +mvgam: + version: 1.1.4 + title: Multivariate (Dynamic) Generalized Additive Models + maintainer: Nicholas J Clark + description: 'Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. + Users can build nonlinear State-Space models that can incorporate semiparametric + effects in observation and process components, using a wide range of observation + families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian + Monte Carlo in the software ''Stan''. References: Clark & Wells (2022) .' + date_publication: '2025-02-19' + bug_reports: https://github.com/nicholasjclark/mvgam/issues + url: https://nicholasjclark.github.io/mvgam/ + url_cran: https://CRAN.R-project.org/package=mvgam + url_git: https://github.com/nicholasjclark/mvgam +mvgb: + version: 0.0.6 + title: |- + Multivariate Probabilities of Scale Mixtures of Multivariate + Normal Distributions via the Genz and Bretz (2002) QRSVN Method + maintainer: Bruce Swihart + description: |- + Generates multivariate subgaussian stable probabilities using the QRSVN + algorithm as detailed in Genz and Bretz (2002) + but by sampling positive stable variates not chi/sqrt(nu). + date_publication: '2024-10-03' + bug_reports: https://github.com/swihart/mvgb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvgb + url_git: https://github.com/swihart/mvgb +mvglmmRank: + version: 1.2-4 + title: |- + Multivariate Generalized Linear Mixed Models for Ranking Sports + Teams + maintainer: Andrew T. Karl + description: |- + Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation as documented by Broatch and Karl (2018) , + Karl, Yang, and Lohr (2014) , and by + Karl (2012) . Karl and Zimmerman use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling. + date_publication: '2023-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvglmmRank + url_git: '' +mvGPS: + version: 1.2.2 + title: Causal Inference using Multivariate Generalized Propensity Score + maintainer: Justin Williams + description: |2- + + Methods for estimating and utilizing the multivariate generalized + propensity score (mvGPS) for multiple continuous exposures described in + Williams, J.R, and Crespi, C.M. (2020) . The methods allow + estimation of a dose-response surface relating the joint distribution of multiple + continuous exposure variables to an outcome. Weights are constructed assuming a + multivariate normal density for the marginal and conditional distribution of + exposures given a set of confounders. Confounders can be different for different + exposure variables. The weights are designed to achieve balance across all + exposure dimensions and can be used to estimate dose-response surfaces. + date_publication: '2021-12-07' + bug_reports: https://github.com/williazo/mvGPS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvGPS + url_git: https://github.com/williazo/mvGPS +mvhist: + version: '1.1' + title: Multivariate Histograms + maintainer: John P. Nolan + description: Tabulate and plot directional and other multivariate histograms. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvhist + url_git: '' +mvhtests: + version: '1.1' + title: Multivariate Hypothesis Tests + maintainer: Michail Tsagris + description: 'Hypothesis tests for multivariate data. Tests for one and two mean + vectors, multivariate analysis of variance, tests for one, two or more covariance + matrices. References include: Mardia K.V., Kent J.T. and Bibby J.M. (1979). Multivariate + Analysis. ISBN: 978-0124712522. London: Academic Press.' + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvhtests + url_git: '' +mvinfluence: + version: 0.9.0 + title: |- + Influence Measures and Diagnostic Plots for Multivariate Linear + Models + maintainer: Michael Friendly + description: |- + Computes regression deletion diagnostics for multivariate linear models and provides some associated + diagnostic plots. The diagnostic measures include hat-values (leverages), generalized Cook's distance, and + generalized squared 'studentized' residuals. Several types of plots to detect influential observations are + provided. + date_publication: '2022-09-20' + bug_reports: https://github.com/friendly/mvinfluence/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvinfluence + url_git: https://github.com/friendly/mvinfluence +MVisAGe: + version: 0.2.1 + title: Compute and Visualize Bivariate Associations + maintainer: Vonn Walter + description: |- + Pearson and Spearman correlation coefficients are commonly used to quantify the strength + of bivariate associations of genomic variables. For example, correlations of gene-level + DNA copy number and gene expression measurements may be used to assess the impact of + DNA copy number changes on gene expression in tumor tissue. 'MVisAGe' enables users to + quickly compute and visualize the correlations in order to assess the effect of regional + genomic events such as changes in DNA copy number or DNA methylation level. Please see + Walter V, Du Y, Danilova L, Hayward MC, Hayes DN, 2018. Cancer Research + . + date_publication: '2018-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVisAGe + url_git: '' +MVLM: + version: 0.1.4 + title: Multivariate Linear Model with Analytic p-Values + maintainer: Daniel B. McArtor + description: Allows a user to conduct multivariate multiple regression using analytic + p-values rather than classic approximate F-tests. + date_publication: '2017-03-26' + bug_reports: http://github.com/dmcartor/MVLM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=MVLM + url_git: http://github.com/dmcartor/MVLM +mvLSW: + version: 1.2.5 + title: Multivariate, Locally Stationary Wavelet Process Estimation + maintainer: Daniel Grose + description: 'Tools for analysing multivariate time series with wavelets. This includes: + simulation of a multivariate locally stationary wavelet (mvLSW) process from a + multivariate evolutionary wavelet spectrum (mvEWS); estimation of the mvEWS, local + coherence and local partial coherence. See Park, Eckley and Ombao (2014) + for details.' + date_publication: '2022-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvLSW + url_git: '' +mvLSWimpute: + version: 0.1.1 + title: |- + Imputation Methods for Multivariate Locally Stationary Time + Series + maintainer: Matt Nunes + description: Implementation of imputation techniques based on locally stationary + wavelet time series forecasting methods from Wilson, R. E. et al. (2021) . + date_publication: '2022-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvLSWimpute + url_git: '' +mvMAPIT: + version: 2.0.3 + title: Multivariate Genome Wide Marginal Epistasis Test + maintainer: Julian Stamp + description: |- + Epistasis, commonly defined as the interaction between genetic + loci, is known to play an important role in the phenotypic variation of + complex traits. As a result, many statistical methods have been developed to + identify genetic variants that are involved in epistasis, and nearly all of + these approaches carry out this task by focusing on analyzing one trait at a + time. Previous studies have shown that jointly modeling multiple phenotypes + can often dramatically increase statistical power for association mapping. In + this package, we present the 'multivariate MArginal ePIstasis Test' + ('mvMAPIT') – a multi-outcome generalization of a recently proposed epistatic + detection method which seeks to detect marginal epistasis or the combined + pairwise interaction effects between a given variant and all other variants. + By searching for marginal epistatic effects, one can identify genetic variants + that are involved in epistasis without the need to identify the exact + partners with which the variants interact – thus, potentially alleviating + much of the statistical and computational burden associated with conventional + explicit search based methods. Our proposed 'mvMAPIT' builds upon this + strategy by taking advantage of correlation structure between traits to + improve the identification of variants involved in epistasis. + We formulate 'mvMAPIT' as a multivariate linear mixed model and develop a + multi-trait variance component estimation algorithm for efficient parameter + inference and P-value computation. Together with reasonable model + approximations, our proposed approach is scalable to moderately sized + genome-wide association studies. + Crawford et al. (2017) . + Stamp et al. (2023) . + date_publication: '2023-09-26' + bug_reports: '' + url: https://lcrawlab.github.io/mvMAPIT/ + url_cran: https://CRAN.R-project.org/package=mvMAPIT + url_git: https://github.com/lcrawlab/mvMAPIT +mvmesh: + version: '1.6' + title: Multivariate Meshes and Histograms in Arbitrary Dimensions + maintainer: John P. Nolan + description: |- + Define, manipulate and plot meshes on simplices, spheres, balls, rectangles and tubes. + Directional and other multivariate histograms are provided. + date_publication: '2020-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvmesh + url_git: '' +mvmeta: + version: 1.0.3 + title: Multivariate and Univariate Meta-Analysis and Meta-Regression + maintainer: Antonio Gasparrini + description: Collection of functions to perform fixed and random-effects multivariate + and univariate meta-analysis and meta-regression. + date_publication: '2019-12-10' + bug_reports: '' + url: http://www.ag-myresearch.com/package-mvmeta + url_cran: https://CRAN.R-project.org/package=mvmeta + url_git: '' +mvMISE: + version: '1.0' + title: |- + A General Framework of Multivariate Mixed-Effects Selection + Models + maintainer: Jiebiao Wang + description: |- + Offers a general framework of multivariate mixed-effects + models for the joint analysis of multiple correlated outcomes with clustered + data structures and potential missingness proposed by Wang et al. (2018) . The missingness of outcome values may + depend on the values themselves (missing not at random and non-ignorable), + or may depend on only the covariates (missing at random and ignorable), or both. + This package provides functions for two models: 1) mvMISE_b() + allows correlated outcome-specific random intercepts with a factor-analytic + structure, and 2) mvMISE_e() allows the correlated outcome-specific + error terms with a graphical lasso penalty on the error precision matrix. Both functions + are motivated by the multivariate data analysis on data with clustered structures + from labelling-based quantitative proteomic studies. These models and functions + can also be applied to univariate and multivariate analyses of clustered data + with balanced or unbalanced design and no missingness. + date_publication: '2018-06-10' + bug_reports: https://github.com/randel/mvMISE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvMISE + url_git: https://github.com/randel/mvMISE +mvMonitoring: + version: 0.2.4 + title: |- + Multi-State Adaptive Dynamic Principal Component Analysis for + Multivariate Process Monitoring + maintainer: Gabriel Odom + description: |- + Use multi-state splitting to apply Adaptive-Dynamic PCA (ADPCA) to + data generated from a continuous-time multivariate industrial or natural + process. Employ PCA-based dimension reduction to extract linear combinations + of relevant features, reducing computational burdens. For a description of + ADPCA, see , the 2016 paper from Kazor et al. + The multi-state application of ADPCA is from a manuscript under current + revision entitled "Multi-State Multivariate Statistical Process Control" by + Odom, Newhart, Cath, and Hering, and is expected to appear in Q1 of 2018. + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvMonitoring + url_git: https://github.com/gabrielodom/mvMonitoring +mvMORPH: + version: 1.2.1 + title: |- + Multivariate Comparative Tools for Fitting Evolutionary Models + to Morphometric Data + maintainer: Julien Clavel + description: |- + Fits multivariate (Brownian Motion, Early Burst, ACDC, Ornstein-Uhlenbeck and Shifts) models of continuous traits evolution on trees and time series. 'mvMORPH' also proposes high-dimensional multivariate comparative tools (linear models using Generalized Least Squares and multivariate tests) based on penalized likelihood. See + Clavel et al. (2015) , Clavel et al. (2019) , and Clavel & Morlon (2020) . + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvMORPH + url_git: https://github.com/JClavel/mvMORPH +MVN: + version: '5.9' + title: Multivariate Normality Tests + maintainer: Selcuk Korkmaz + description: |- + Performs multivariate normality tests and graphical approaches and + implements multivariate outlier detection and univariate normality of marginal + distributions through plots and tests, and performs multivariate Box-Cox transformation + (Korkmaz et al, (2014), ). + date_publication: '2021-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVN + url_git: '' +mvna: + version: 2.0.1 + title: |- + Nelson-Aalen Estimator of the Cumulative Hazard in Multistate + Models + maintainer: Arthur Allignol + description: Computes the Nelson-Aalen estimator of the cumulative transition hazard + for arbitrary Markov multistate models . + date_publication: '2017-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvna + url_git: '' +MVNBayesian: + version: 0.0.8-11 + title: Bayesian Analysis Framework for MVN (Mixture) Distribution + maintainer: ZHANG Chen + description: |- + Tools of Bayesian analysis framework using the method + suggested by Berger (1985) for + multivariate normal (MVN) distribution and multivariate normal + mixture (MixMVN) distribution: + a) calculating Bayesian posteriori of (Mix)MVN distribution; + b) generating random vectors of (Mix)MVN distribution; + c) Markov chain Monte Carlo (MCMC) for (Mix)MVN distribution. + date_publication: '2018-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVNBayesian + url_git: https://github.com/CubicZebra/MVNBayesian +mvnfast: + version: 0.2.8 + title: Fast Multivariate Normal and Student's t Methods + maintainer: Matteo Fasiolo + description: |- + Provides computationally efficient tools related to the + multivariate normal and Student's t distributions. The main functionalities + are: simulating multivariate random vectors, evaluating multivariate normal or + Student's t densities and Mahalanobis distances. These tools are very efficient + thanks to the use of C++ code and of the OpenMP API. + date_publication: '2023-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvnfast + url_git: https://github.com/mfasiolo/mvnfast/ +mvngGrAd: + version: 0.1.6 + title: Moving Grid Adjustment in Plant Breeding Field Trials + maintainer: Frank Technow + description: |- + Package for moving grid adjustment + in plant breeding field trials. + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvngGrAd + url_git: '' +mvnimpute: + version: 1.0.1 + title: Simultaneously Impute the Missing and Censored Values + maintainer: Hesen Li + description: Implementing a multiple imputation algorithm for multivariate data + with missing and censored values under a coarsening at random assumption (Heitjan + and Rubin, 1991). The multiple imputation algorithm + is based on the data augmentation algorithm proposed by Tanner and Wong (1987). + The Gibbs sampling algorithm is adopted to to update the model parameters and + draw imputations of the coarse data. + date_publication: '2022-07-06' + bug_reports: https://github.com/hli226/mvnimpute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvnimpute + url_git: https://github.com/hli226/mvnimpute +mvnmle: + version: 0.1-11.2 + title: ML Estimation for Multivariate Normal Data with Missing Values + maintainer: Mao Kobayashi + description: |- + Finds the Maximum Likelihood (ML) Estimate of the mean vector + and variance-covariance matrix for multivariate normal data + with missing values. + date_publication: '2023-02-27' + bug_reports: https://github.com/indenkun/mvnmle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvnmle + url_git: https://github.com/indenkun/mvnmle +mvnormalTest: + version: 1.0.0 + title: Powerful Tests for Multivariate Normality + maintainer: Yian Zhang + description: |- + A simple informative powerful test (mvnTest()) for multivariate normality proposed by + Zhou and Shao (2014) , which combines kurtosis + with Shapiro-Wilk test that is easy for biomedical researchers to understand and + easy to implement in all dimensions. This package also contains some other multivariate + normality tests including Fattorini's FA test (faTest()), Mardia's skewness and kurtosis + test (mardia()), Henze-Zirkler's test (mhz()), Bowman and Shenton's test (msk()), + Royston’s H test (msw()), and Villasenor-Alva and Gonzalez-Estrada's test (msw()). Empirical + power calculation functions for these tests are also provided. In addition, this package + includes some functions to generate several types of multivariate distributions mentioned in + Zhou and Shao (2014). + date_publication: '2020-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvnormalTest + url_git: '' +mvnormtest: + version: 0.1-9-3 + title: Normality Test for Multivariate Variables + maintainer: Sławomir Jarek + description: Generalization of Shapiro-Wilk test for multivariate variables. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvnormtest + url_git: '' +mvnpermute: + version: 1.0.1 + title: Generate New Multivariate Normal Samples from Permutations + maintainer: Mark Abney + description: |- + Given a vector of multivariate normal data, a matrix of + covariates and the data covariance matrix, generate new multivariate normal + samples that have the same covariance matrix based on permutations of + the transformed data residuals. + date_publication: '2022-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvnpermute + url_git: https://github.com/markabney/MVNpermute +mvnTest: + version: 1.1-0 + title: Goodness of Fit Tests for Multivariate Normality + maintainer: Natalya Pya + description: Routines for assessing multivariate normality. Implements three Wald's + type chi-squared tests; non-parametric Anderson-Darling and Cramer-von Mises tests; + Doornik-Hansen test, Royston test and Henze-Zirkler test. + date_publication: '2016-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvnTest + url_git: '' +MVNtestchar: + version: 1.1.3 + title: |- + Test for Multivariate Normal Distribution Based on a + Characterization + maintainer: William Fairweather + description: |- + Provides a test of multivariate normality of an unknown sample + that does not require estimation of the nuisance parameters, the mean and covariance + matrix. Rather, a sequence of transformations removes these nuisance parameters and + results in a set of sample matrices that are positive definite. These matrices are + uniformly distributed on the space of positive definite matrices in the unit + hyper-rectangle if and only if the original data is multivariate normal (Fairweather, + 1973, Doctoral dissertation, University of Washington). The package performs a + goodness of fit test of this hypothesis. In addition to the test, functions in the + package give visualizations of the support region of positive definite matrices for + bivariate samples. + date_publication: '2020-07-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVNtestchar + url_git: '' +mvord: + version: 1.2.5 + title: Multivariate Ordinal Regression Models + maintainer: Laura Vana + description: |- + A flexible framework for fitting multivariate + ordinal regression models with composite likelihood methods. Methodological details are given in Hirk, Hornik, Vana (2020) . + date_publication: '2024-08-30' + bug_reports: https://github.com/lauravana/mvord/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvord + url_git: https://github.com/lauravana/mvord +mvoutlier: + version: 2.1.1 + title: Multivariate Outlier Detection Based on Robust Methods + maintainer: P. Filzmoser + description: 'Various methods for multivariate outlier detection: arw, a Mahalanobis-type + method with an adaptive outlier cutoff value; locout, a method incorporating local + neighborhood; pcout, a method for high-dimensional data; mvoutlier.CoDa, a method + for compositional data. References are provided in the corresponding help files.' + date_publication: '2021-07-30' + bug_reports: '' + url: http://cstat.tuwien.ac.at/filz/ + url_cran: https://CRAN.R-project.org/package=mvoutlier + url_git: '' +mvp: + version: 1.0-18 + title: Fast Symbolic Multivariate Polynomials + maintainer: Robin K. S. Hankin + description: |- + Fast manipulation of symbolic multivariate polynomials + using the 'Map' class of the Standard Template Library. The package + uses print and coercion methods from the 'mpoly' package but + offers speed improvements. It is comparable in speed to the 'spray' + package for sparse arrays, but retains the symbolic benefits of + 'mpoly'. To cite the package in publications, use Hankin 2022 + . Uses 'disordR' discipline. + date_publication: '2025-01-31' + bug_reports: https://github.com/RobinHankin/mvp/issues + url: https://robinhankin.github.io/mvp/ + url_cran: https://CRAN.R-project.org/package=mvp + url_git: https://github.com/RobinHankin/mvp +MVPBT: + version: 1.2-1 + title: |- + Publication Bias Tests for Meta-Analysis of Diagnostic Accuracy + Test + maintainer: Hisashi Noma + description: Generalized Egger tests for detecting publication bias in meta-analysis + for diagnostic accuracy test (Noma (2020) , Noma (2022) + ). These publication bias tests are generally more + powerful compared with the conventional univariate publication bias tests and + can incorporate correlation information between the outcome variables. + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVPBT + url_git: '' +mvpd: + version: 0.0.4 + title: |- + Multivariate Product Distributions for Elliptically Contoured + Distributions + maintainer: Bruce Swihart + description: |- + Estimates multivariate subgaussian stable densities + and probabilities as well as generates random variates using product + distribution theory. A function for estimating the parameters from + data to fit a distribution to data is also provided, using the + method from Nolan (2013) . + date_publication: '2023-09-03' + bug_reports: https://github.com/swihart/mvpd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvpd + url_git: https://github.com/swihart/mvpd +mvProbit: + version: 0.1-10 + title: Multivariate Probit Models + maintainer: Arne Henningsen + description: |- + Tools for estimating multivariate probit models, + calculating conditional and unconditional expectations, + and calculating marginal effects on conditional and unconditional + expectations. + date_publication: '2021-01-11' + bug_reports: '' + url: http://www.sampleSelection.org + url_cran: https://CRAN.R-project.org/package=mvProbit + url_git: '' +mvQuad: + version: 1.0-8 + title: Methods for Multivariate Quadrature + maintainer: Constantin Weiser + description: |- + Provides methods to construct multivariate grids, which can be used + for multivariate quadrature. This grids can be based on different quadrature + rules like Newton-Cotes formulas (trapezoidal-, Simpson's- rule, ...) or Gauss + quadrature (Gauss-Hermite, Gauss-Legendre, ...). For the construction of the + multidimensional grid the product-rule or the combination- technique can be + applied. + date_publication: '2023-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvQuad + url_git: https://github.com/weiserc/mvQuad/ +MVQuickGraphs: + version: 0.1.2 + title: Quick Multivariate Graphs + maintainer: Douglas Whitaker + description: |- + Functions used for graphing in multivariate contexts. These + functions are designed to support produce reasonable graphs with minimal + input of graphing parameters. The motivation for these functions was to + support students learning multivariate concepts and R - there may be + other functions and packages better-suited to practical data analysis. For + details about the ellipse methods see Johnson and Wichern (2007, + ISBN:9780131877153). + date_publication: '2020-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVQuickGraphs + url_git: '' +MVR: + version: 1.33.0 + title: Mean-Variance Regularization + maintainer: Jean-Eudes Dazard + description: |- + This is a non-parametric method for joint adaptive mean-variance regularization and variance stabilization of high-dimensional data. It is suited for handling difficult problems posed by high-dimensional multivariate datasets (p >> n paradigm). Among those are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. Key features include: + (i) Normalization and/or variance stabilization of the data, + (ii) Computation of mean-variance-regularized t-statistics (F-statistics to follow), + (iii) Generation of diverse diagnostic plots, + (iv) Computationally efficient implementation using C/C++ interfacing and an option for parallel computing to enjoy a faster and easier experience in the R environment. + date_publication: '2018-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVR + url_git: https://github.com/jedazard/MVR +mvrsquared: + version: 0.1.5 + title: |- + Compute the Coefficient of Determination for Vector or Matrix + Outcomes + maintainer: Tommy Jones + description: |- + Compute the coefficient of determination for outcomes in n-dimensions. + May be useful for multidimensional predictions (such as a multinomial model) or + calculating goodness of fit from latent variable models such as probabilistic + topic models like latent Dirichlet allocation or deterministic topic models + like latent semantic analysis. Based on Jones (2019) . + date_publication: '2023-07-15' + bug_reports: https://github.com/TommyJones/mvrsquared/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mvrsquared + url_git: https://github.com/TommyJones/mvrsquared +mvs: + version: 2.0.0 + title: Methods for High-Dimensional Multi-View Learning + maintainer: Wouter van Loon + description: |- + Methods for high-dimensional multi-view learning based on the multi-view stacking (MVS) framework. + For technical details on the MVS and stacked penalized logistic regression (StaPLR) methods see Van Loon, Fokkema, Szabo, & De Rooij (2020) and Van Loon et al. (2022) . + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvs + url_git: '' +mvShapiroTest: + version: '1.0' + title: Generalized Shapiro-Wilk test for multivariate normality + maintainer: Elizabeth Gonzalez Estrada + description: This package implements the generalization of the Shapiro-Wilk testfor + multivariate normality proposed by Villasenor-Alva andGonzalez-Estrada + (2009). + date_publication: '2013-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvShapiroTest + url_git: '' +mvSLOUCH: + version: 2.7.6 + title: |- + Multivariate Stochastic Linear Ornstein-Uhlenbeck Models for + Phylogenetic Comparative Hypotheses + maintainer: Krzysztof Bartoszek + description: Fits multivariate Ornstein-Uhlenbeck types of models to continues trait + data from species related by a common evolutionary history. See K. Bartoszek, + J, Pienaar, P. Mostad, S. Andersson, T. F. Hansen (2012) . + The suggested PCMBaseCpp package (which significantly speeds up the likelihood + calculations) can be obtained from . + date_publication: '2023-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvSLOUCH + url_git: '' +mvst: + version: 1.1.1 + title: Bayesian Inference for the Multivariate Skew-t Model + maintainer: Antonio Parisi + description: |- + Estimates the multivariate skew-t and nested models, as described in the + articles Liseo, B., Parisi, A. (2013). Bayesian inference for the multivariate skew-normal + model: a population Monte Carlo approach. Comput. Statist. Data Anal. + and in Parisi, A., Liseo, B. (2017). Objective Bayesian + analysis for the multivariate skew-t model. Statistical Methods & Applications + . + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvst + url_git: '' +mvSUSY: + version: 0.1.0 + title: Multivariate Surrogate Synchrony + maintainer: Wolfgang Tschacher + description: Multivariate Surrogate Synchrony ('mvSUSY') estimates the synchrony + within datasets that contain more than two time series. 'mvSUSY' was developed + from Surrogate Synchrony ('SUSY') with respect to implementing surrogate controls, + and extends synchrony estimation to multivariate data. 'mvSUSY' works as described + in Meier & Tschacher (2021). + date_publication: '2023-11-07' + bug_reports: https://github.com/wtschacher/mvSUSY/issues + url: https://wtschacher.github.io/mvSUSY/ + url_cran: https://CRAN.R-project.org/package=mvSUSY + url_git: '' +MVT: + version: 0.3-81 + title: Estimation and Testing for the Multivariate t-Distribution + maintainer: Felipe Osorio + description: |- + Routines to perform estimation and inference under the multivariate + t-distribution . Currently, the following methodologies + are implemented: multivariate mean and covariance estimation, hypothesis testing + about equicorrelation and homogeneity of variances, the Wilson-Hilferty transformation, + QQ-plots with envelopes and random variate generation. + date_publication: '2024-09-24' + bug_reports: '' + url: http://mvt.mat.utfsm.cl/ + url_cran: https://CRAN.R-project.org/package=MVT + url_git: '' +MVTests: + version: 2.2.2 + title: Multivariate Hypothesis Tests + maintainer: Hasan BULUT + description: 'Multivariate hypothesis tests and the confidence intervals. It can + be used to test the hypothesizes about mean vector or vectors (one-sample, two + independent samples, paired samples), covariance matrix (one or more matrices), + and the correlation matrix. Moreover, it can be used for robust Hotelling T^2 + test at one sample case in high dimensional data. For this package, we have benefited + from the studies Rencher (2003), Nel and Merwe (1986) , + Tatlidil (1996), Tsagris (2014), Villasenor Alva and Estrada (2009) .' + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MVTests + url_git: '' +mvtmeta: + version: '1.1' + title: Multivariate Meta-Analysis + maintainer: Han Chen + description: Functions to run fixed effects or random effects multivariate meta-analysis. + date_publication: '2020-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvtmeta + url_git: '' +mvtnorm: + version: 1.3-3 + title: Multivariate Normal and t Distributions + maintainer: Torsten Hothorn + description: |- + Computes multivariate normal and t probabilities, quantiles, random deviates, + and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae + parameterised by Cholesky factors of covariance or precision matrices are implemented + for interval-censored and exact data, or a mix thereof. Score functions for these + log-likelihoods are available. A class representing multiple lower triangular matrices + and corresponding methods are part of this package. + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvtnorm + url_git: http://mvtnorm.R-forge.R-project.org +mvtsplot: + version: 1.0-5 + title: Multivariate Time Series Plot + maintainer: Roger D. Peng + description: A function for plotting multivariate time series data. + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvtsplot + url_git: https://github.com/rdpeng/mvtsplot +mvvg: + version: 0.1.0 + title: Matrix-Variate Variance-Gamma Distribution + maintainer: Samuel Soon + description: Rudimentary functions for sampling and calculating density from the + matrix-variate variance-gamma distribution. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mvvg + url_git: '' +mwa: + version: 0.4.4 + title: Causal Inference in Spatiotemporal Event Data + maintainer: Sebastian Schutte + description: Implementation of Matched Wake Analysis (mwa) for studying causal relationships + in spatiotemporal event data, introduced by Schutte and Donnay (2014) . + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mwa + url_git: '' +mwcsr: + version: 0.1.9 + title: |- + Solvers for Maximum Weight Connected Subgraph Problem and Its + Variants + maintainer: Alexander Loboda + description: |- + Algorithms for solving various Maximum + Weight Connected Subgraph Problems, including variants with + budget constraints, cardinality constraints, weighted edges and signals. + The package represents an R interface to high-efficient solvers based on + relax-and-cut approach (Álvarez-Miranda E., Sinnl M. (2017) ) + mixed-integer programming (Loboda A., Artyomov M., and Sergushichev A. (2016) ) + and simulated annealing. + date_publication: '2024-09-09' + bug_reports: https://github.com/ctlab/mwcsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=mwcsr + url_git: https://github.com/ctlab/mwcsr +mwlaxeref: + version: 0.0.1 + title: Cross-References Lake Identifiers Between Different Data Sets + maintainer: Paul Frater + description: |- + Handy helper package for cross-referencing lake identifiers + among different data sets in the Midwestern United States. There are + multiple different state, regional, and federal agencies that have + different identifiers on lakes. This package helps you to go between them. + date_publication: '2024-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mwlaxeref + url_git: '' +MWright: + version: 0.3.2 + title: Mainardi-Wright Family of Distributions + maintainer: Dexter Cahoy + description: |- + Implements random number generation, plotting, and estimation algorithms for the two-parameter one-sided and two-sided M-Wright (Mainardi-Wright) family. + The M-Wright distributions naturally generalize the widely used one-sided (Airy and half-normal or half-Gaussian) and symmetric (Airy and Gaussian or normal) models. + These are widely studied in time-fractional differential equations. References: Cahoy and Minkabo (2017) ; Cahoy (2012) ; Cahoy (2012) ; Cahoy (2011); Mainardi, Mura, and Pagnini (2010) . + date_publication: '2019-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=MWright + url_git: '' +mwshiny: + version: 2.1.0 + title: '''Shiny'' for Multiple Windows' + maintainer: Hannah De los Santos + description: |- + A simple function, mwsApp(), that runs a 'shiny' app spanning multiple, + connected windows. This uses all standard 'shiny' conventions, and depends only on + the 'shiny' package. + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mwshiny + url_git: '' +mwTensor: + version: 1.1.0 + title: Multi-Way Component Analysis + maintainer: Koki Tsuyuzaki + description: For single tensor data, any matrix factorization method can be specified + the matricised tensor in each dimension by Multi-way Component Analysis (MWCA). + An originally extended MWCA is also implemented to specify and decompose multiple + matrices and tensors simultaneously (CoupledMWCA). See the reference section of + GitHub README.md , for details of the methods. + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mwTensor + url_git: https://github.com/rikenbit/mwTensor +mxcc: + version: 0.0.1 + title: Maxwell Control Charts + maintainer: Zsolt T. Kosztyan + description: Computes Control limits, coefficients of control limits, various performance + metrics and depicts control charts for monitoring Maxwell-distributed quality + characteristics. + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mxcc + url_git: https://github.com/kzst/mxcc +mxfda: + version: 0.2.2-1 + title: A Functional Data Analysis Package for Spatial Single Cell Data + maintainer: Alex Soupir + description: |- + Methods and tools for deriving spatial summary functions from single-cell imaging + data and performing functional data analyses. Functions can be applied to other single-cell + technologies such as spatial transcriptomics. Functional regression and functional principal component analysis methods + are in the 'refund' package while calculation of the + spatial summary functions are from the 'spatstat' package . + date_publication: '2025-02-19' + bug_reports: https://github.com/julia-wrobel/mxfda/issues/ + url: http://juliawrobel.com/mxfda/ + url_cran: https://CRAN.R-project.org/package=mxfda + url_git: https://github.com/julia-wrobel/mxfda/ +mxkssd: + version: '1.2' + title: Efficient Mixed-Level k-Circulant Supersaturated Designs + maintainer: B N Mandal + description: Generates efficient balanced mixed-level k-circulant supersaturated + designs by interchanging the elements of the generator vector. Attempts to generate + a supersaturated design that has EfNOD efficiency more than user specified efficiency + level (mef). Displays the progress of generation of an efficient mixed-level k-circulant + design through a progress bar. The progress of 100 per cent means that one full + round of interchange is completed. More than one full round (typically 4-5 rounds) + of interchange may be required for larger designs. For more details, please see + Mandal, B.N., Gupta V. K. and Parsad, R. (2011). Construction of Efficient Mixed-Level + k-Circulant Supersaturated Designs, Journal of Statistical Theory and Practice, + 5:4, 627-648, . + date_publication: '2022-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mxkssd + url_git: '' +mxmmod: + version: 1.1.0 + title: Measurement Model of Derivatives in 'OpenMx' + maintainer: Kyle D. Husmann + description: |- + Provides a convenient interface in 'OpenMx' for building + Estabrook's (2015) Measurement Model of + Derivatives (MMOD). + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mxmmod + url_git: '' +mxnorm: + version: 1.0.3 + title: Apply Normalization Methods to Multiplexed Images + maintainer: Coleman Harris + description: |- + Implements methods to normalize multiplexed imaging data, including + statistical metrics and visualizations to quantify technical variation in + this data type. Reference for methods listed here: Harris, C., Wrobel, J., + & Vandekar, S. (2022). mxnorm: An R Package to Normalize Multiplexed Imaging + Data. Journal of Open Source Software, 7(71), 4180, + . + date_publication: '2023-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mxnorm + url_git: '' +mxsem: + version: 0.1.0 + title: Specify 'OpenMx' Models with a 'lavaan'-Style Syntax + maintainer: Jannik H. Orzek + description: |- + Provides a 'lavaan'-like syntax for 'OpenMx' models. The syntax supports + definition variables, bounds, and parameter transformations. This allows for + latent growth curve models with person-specific measurement occasions, moderated + nonlinear factor analysis and much more. + date_publication: '2024-07-28' + bug_reports: https://github.com/jhorzek/mxsem/issues + url: https://jhorzek.github.io/mxsem/ + url_cran: https://CRAN.R-project.org/package=mxsem + url_git: https://github.com/jhorzek/mxsem/ +My.stepwise: + version: 0.1.0 + title: Stepwise Variable Selection Procedures for Regression Analysis + maintainer: Fu-Chang Hu + description: |- + The stepwise variable selection procedure (with iterations + between the 'forward' and 'backward' steps) can be used to obtain + the best candidate final regression model in regression analysis. + All the relevant covariates are put on the 'variable list' to be + selected. The significance levels for entry (SLE) and for stay + (SLS) are usually set to 0.15 (or larger) for being conservative. + Then, with the aid of substantive knowledge, the best candidate + final regression model is identified manually by dropping the + covariates with p value > 0.05 one at a time until all regression + coefficients are significantly different from 0 at the chosen alpha + level of 0.05. + date_publication: '2017-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=My.stepwise + url_git: '' +mycaas: + version: 0.0.1 + title: My Computerized Adaptive Assessment + maintainer: Andrea Brancaccio + description: |- + Implementation of adaptive assessment procedures based + on Knowledge Space Theory (KST, Doignon & Falmagne, 1999 ) and Formal Psychological Assessment + (FPA, Spoto, Stefanutti & Vidotto, 2010 ) frameworks. An adaptive assessment is a type of evaluation that + adjusts the difficulty and nature of subsequent questions based on the + test taker's responses to previous ones. The package contains functions + to perform and simulate an adaptive assessment. Moreover, it is + integrated with two 'Shiny' interfaces, making it both accessible and + user-friendly. The package has been partially funded by the European Union - + NextGenerationEU and by the Ministry of University and Research (MUR), + National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, + Investment 1.5, project “RAISE - Robotics and AI for Socio-economic + Empowerment” (ECS00000035). + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mycaas + url_git: '' +Mychisq: + version: 0.1.3 + title: Chi-Squared Test for Goodness of Fit and Independence Test + maintainer: Atchanut Rattanalertnusorn + description: |- + The chi-squared test for goodness of fit + and independence test. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Mychisq + url_git: '' +myClim: + version: 1.4.0 + title: Microclimatic Data Processing + maintainer: Vojtěch Kalčík + description: |- + Handling the microclimatic data in R. The 'myClim' workflow begins + at the reading data primary from microclimatic dataloggers, + but can be also reading of meteorological station data from files. + Cleaning time step, time zone settings and metadata collecting is the next step of the work flow. + With 'myClim' tools one can crop, join, downscale, and convert microclimatic data formats, sort them into localities, + request descriptive characteristics and compute microclimatic variables. + Handy plotting functions are provided with smart defaults. + date_publication: '2025-02-21' + bug_reports: '' + url: http://labgis.ibot.cas.cz/myclim/index.html + url_cran: https://CRAN.R-project.org/package=myClim + url_git: https://github.com/ibot-geoecology/myClim +mycobacrvR: + version: '1.1' + title: |- + Integrative Immunoinformatics for Mycobacterial Diseases in R + Platform + maintainer: S. Ramachandran + description: The mycobacrvR package contains utilities to provide detailed information + for B cell and T cell epitopes for predicted adhesins from various servers such + as ABCpred, Bcepred, Bimas, Propred, NetMHC and IEDB. Please refer the URL below + to download data files (data_mycobacrvR.zip) used in functions of this package. + date_publication: '2022-05-13' + bug_reports: '' + url: https://mycobacteriarv.igib.res.in/download.html + url_cran: https://CRAN.R-project.org/package=mycobacrvR + url_git: '' +mycor: + version: 0.1.1 + title: Automatic Correlation and Regression Test in a 'data.frame' + maintainer: Keon-Woong Moon + description: |- + Perform correlation and linear regression test + among the numeric fields in a data.frame automatically + and make plots using pairs or lattice::parallelplot. + date_publication: '2018-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mycor + url_git: https://github.com/cardiomoon/mycor +myCRAN: + version: '1.1' + title: Graph of Daily and Cumulative Downloads of your Packages + maintainer: Barry Zeeberg + description: |- + Plot the daily and cumulative number of downloads of your packages. + It is designed to be slightly more convenient than the several similar programs. If you want to run this each morning, + you do not need to keep typing in the names of your packages. Also, this combines the daily and cumulative counts in one + run, you do not need to run separate programs to get both types of information. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=myCRAN + url_git: '' +mzipmed: + version: 1.4.0 + title: Mediation using MZIP Model + maintainer: Andrew Sims + description: We implement functions allowing for mediation analysis to be performed + in cases where the mediator is a count variable with excess zeroes. First a function + is provided allowing users to perform analysis for zero-inflated count variables + using the marginalized zero-inflated Poisson (MZIP) model (Long et al. 2014 ). + Using the counterfactual approach to mediation and MZIP we can obtain natural + direct and indirect effects for the overall population. Using delta method processes + variance estimation can be performed instantaneously. Alternatively, bootstrap + standard errors can be used. We also provide functions for cases with exposure-mediator + interactions with four-way decomposition of total effect. + date_publication: '2023-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=mzipmed + url_git: '' +n1qn1: + version: 6.0.1-12 + title: |- + Port of the 'Scilab' 'n1qn1' Module for Unconstrained BFGS + Optimization + maintainer: Matthew Fidler + description: |- + Provides 'Scilab' 'n1qn1'. This takes more memory than traditional L-BFGS. The n1qn1 routine is useful since it allows prespecification of a Hessian. + If the Hessian is near enough the truth in optimization it can speed up the optimization problem. The algorithm is described in the + 'Scilab' optimization documentation located at + . This version uses manually modified code from 'f2c' to make this a C only binary. + date_publication: '2024-09-17' + bug_reports: https://github.com/nlmixr2/n1qn1c/issues + url: '' + url_cran: https://CRAN.R-project.org/package=n1qn1 + url_git: https://github.com/nlmixr2/n1qn1c +N2H4: + version: 0.8.4 + title: Handling Methods for Naver News Text Crawling + maintainer: Chanyub Park + description: |- + Provides some functions to get Korean text sample from news articles in + Naver which is popular news portal service in Korea. + date_publication: '2024-02-25' + bug_reports: https://github.com/forkonlp/N2H4/issues + url: https://forkonlp.github.io/N2H4/ + url_cran: https://CRAN.R-project.org/package=N2H4 + url_git: https://github.com/forkonlp/N2H4 +N2R: + version: 1.0.3 + title: |- + Fast and Scalable Approximate k-Nearest Neighbor Search Methods + using 'N2' Library + maintainer: Evan Biederstedt + description: Implements methods to perform fast approximate K-nearest neighbor search + on input matrix. Algorithm based on the 'N2' implementation of an approximate + nearest neighbor search using hierarchical Navigable Small World (NSW) graphs. + The original algorithm is described in "Efficient and Robust Approximate Nearest + Neighbor Search Using Hierarchical Navigable Small World Graphs", Y. Malkov and + D. Yashunin, , . + date_publication: '2024-02-26' + bug_reports: https://github.com/kharchenkolab/N2R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=N2R + url_git: https://github.com/kharchenkolab/N2R +na.tools: + version: 0.3.1 + title: |- + Comprehensive Library for Working with Missing (NA) Values in + Vectors + maintainer: Christopher Brown + description: |2- + + This comprehensive toolkit provide a consistent and + extensible framework for working with missing values in vectors. The + companion package 'tidyimpute' provides similar functionality for list-like + and table-like structures). + Functions exist for detection, removal, replacement, imputation, + recollection, etc. of 'NAs'. + date_publication: '2018-06-25' + bug_reports: https://github.com/decisionpatterns/na.tools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=na.tools + url_git: https://github.com/decisionpatterns/na.tools +naaccr: + version: 3.1.1 + title: Read Cancer Records in the NAACCR Format + maintainer: Nathan Werth + description: |- + Functions for reading cancer record files which follow a format + defined by the North American Association of Central Cancer Registries + (NAACCR). + date_publication: '2024-09-20' + bug_reports: https://github.com/WerthPADOH/naaccr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=naaccr + url_git: https://github.com/WerthPADOH/naaccr +nabor: + version: 0.5.0 + title: |- + Wraps 'libnabo', a Fast K Nearest Neighbour Library for Low + Dimensions + maintainer: Gregory Jefferis + description: |- + An R wrapper for 'libnabo', an exact or approximate k nearest + neighbour library which is optimised for low dimensional spaces (e.g. 3D). + 'libnabo' has speed and space advantages over the 'ANN' library wrapped by + package 'RANN'. 'nabor' includes a knn function that is designed as a + drop-in replacement for 'RANN' function nn2. In addition, objects which + include the k-d tree search structure can be returned to speed up repeated + queries of the same set of target points. + date_publication: '2018-07-11' + bug_reports: https://github.com/jefferis/nabor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nabor + url_git: https://github.com/jefferis/naborhttps://github.com/ethz-asl/libnabo +NAC: + version: 0.1.0 + title: Network-Adjusted Covariates for Community Detection + maintainer: Yaofang Hu + description: 'Incorporating node-level covariates for community detection has gained + increasing attention these years. This package provides the function for implementing + the novel community detection algorithm known as Network-Adjusted Covariates for + Community Detection (NAC), which is designed to detect latent community structure + in graphs with node-level information, i.e., covariates. This algorithm can handle + models such as the degree-corrected stochastic block model (DCSBM) with covariates. + NAC specifically addresses the discrepancy between the community structure inferred + from the adjacency information and the community structure inferred from the covariates + information. For more detailed information, please refer to the reference paper: + Yaofang Hu and Wanjie Wang (2023) . In addition to NAC, this + package includes several other existing community detection algorithms that are + compared to NAC in the reference paper. These algorithms are Spectral Clustering + On Ratios-of Eigenvectors (SCORE), network-based regularized spectral clustering + (Net-based), covariate-based spectral clustering (Cov-based), covariate-assisted + spectral clustering (CAclustering) and semidefinite programming (SDP).' + date_publication: '2023-12-04' + bug_reports: '' + url: https://arxiv.org/abs/2306.15616 + url_cran: https://CRAN.R-project.org/package=NAC + url_git: '' +NACHO: + version: 2.0.6 + title: NanoString Quality Control Dashboard + maintainer: Mickaël Canouil + description: |- + NanoString nCounter data are gene expression assays + where there is no need for the use of enzymes or amplification + protocols and work with fluorescent barcodes (Geiss et al. (2018) + ). Each barcode is assigned a + messenger-RNA/micro-RNA (mRNA/miRNA) which after bonding with its + target can be counted. As a result each count of a specific barcode + represents the presence of its target mRNA/miRNA. 'NACHO' (NAnoString + quality Control dasHbOard) is able to analyse the exported NanoString + nCounter data and facilitates the user in performing a quality + control. 'NACHO' does this by visualising quality control metrics, + expression of control genes, principal components and sample specific + size factors in an interactive web application. + date_publication: '2024-01-12' + bug_reports: https://github.com/mcanouil/NACHO/issues + url: https://m.canouil.dev/NACHO/ + url_cran: https://CRAN.R-project.org/package=NACHO + url_git: https://github.com/mcanouil/NACHO/ +NADA: + version: 1.6-1.1 + title: Nondetects and Data Analysis for Environmental Data + maintainer: Lopaka Lee + description: |- + Contains methods described by Dennis Helsel in + his book "Nondetects And Data Analysis: Statistics + for Censored Environmental Data". + date_publication: '2020-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NADA + url_git: '' +NADA2: + version: 1.1.8 + title: Data Analysis for Censored Environmental Data + maintainer: Paul Julian + description: |- + Contains methods described by Dennis Helsel in + his book "Statistics for Censored Environmental Data + using Minitab and R" (2011) and courses and videos at + . This package adds new functions to + the `NADA` Package. + date_publication: '2024-09-06' + bug_reports: https://github.com/SwampThingPaul/NADA2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NADA2 + url_git: https://github.com/SwampThingPaul/NADA2 +nadiv: + version: 2.18.0 + title: (Non)Additive Genetic Relatedness Matrices + maintainer: Matthew Wolak + description: |- + Constructs (non)additive genetic relationship matrices, and their + inverses, from a pedigree to be used in linear mixed effect models (A.K.A. + the 'animal model'). Also includes other functions to facilitate the use of + animal models. Some functions have been created to be used in conjunction + with the R package 'asreml' for the 'ASReml' software, which can be + obtained upon purchase from 'VSN' international + (). + date_publication: '2024-05-23' + bug_reports: https://github.com/matthewwolak/nadiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nadiv + url_git: https://github.com/matthewwolak/nadiv +NAEPirtparams: + version: 1.0.0 + title: IRT Parameters for the National Assessment of Education Progress + maintainer: Sun-joo Lee + description: This data package contains the Item Response Theory (IRT) parameters + for the National Center for Education Statistics (NCES) items used on the National + Assessment of Education Progress (NAEP) from 1990 to 2015. The values in these + tables are used along with NAEP data to turn student item responses into scores + and include information about item difficulty, discrimination, and guessing parameter + for 3 parameter logit (3PL) items. Parameters for Generalized Partial Credit Model + (GPCM) items are also included. The adjustments table contains the information + regarding the treatment of items (e.g., deletion of an item or a collapsing of + response categories), when these items did not appear to fit the item response + models used to describe the NAEP data. Transformation constants change the score + estimates that are obtained from the IRT scaling program to the NAEP reporting + metric. Values from the years 2000 - 2013 were taken from the NCES website + and values from 1990 - 1998 and 2015 were extracted from their NAEP data files. + All subtest names were reduced and homogenized to one word (e.g. "Reading to gain + information" became "information"). The various subtest names for univariate transformation + constants were all homogenized to "univariate". + date_publication: '2021-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NAEPirtparams + url_git: '' +NAEPprimer: + version: 1.0.1 + title: The NAEP Primer + maintainer: Emmanuel Sikali + description: Contains a sample of the 2005 Grade 8 Mathematics data from the National + Assessment of Educational Progress (NAEP). This data set is called the NAEP Primer. + date_publication: '2016-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NAEPprimer + url_git: '' +naflex: + version: 0.1.1 + title: Flexible Options for Handling Missing Values + maintainer: Danny Parsons + description: |- + For use in summary functions to omit missing values + conditionally using specified checks. + date_publication: '2024-10-15' + bug_reports: https://github.com/dannyparsons/naflex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=naflex + url_git: https://github.com/dannyparsons/naflex +naijR: + version: 0.6.1 + title: Operations to Ease Data Analyses Specific to Nigeria + maintainer: Victor Ordu + description: |- + A set of convenience functions as well as geographical/political + data about Nigeria, aimed at simplifying work with data and information that + are specific to the country. + date_publication: '2024-10-10' + bug_reports: https://github.com/ropensci/naijR/issues + url: https://docs.ropensci.org/naijR/ + url_cran: https://CRAN.R-project.org/package=naijR + url_git: '' +NaileR: + version: 1.2.2 + title: Interpreting Latent Variables with AI + maintainer: Sébastien Lê + description: A small package designed for interpreting continuous and categorical + latent variables. You provide a data set with a latent variable you want to understand + and some other explanatory variables. It provides a description of the latent + variable based on the explanatory variables. It also provides a name to the latent + variable. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NaileR + url_git: '' +NAIR: + version: 1.0.4 + title: Network Analysis of Immune Repertoire + maintainer: Brian Neal + description: |- + Pipelines for studying the adaptive immune repertoire of T cells + and B cells via network analysis based on receptor sequence similarity. + Relate clinical outcomes to immune repertoires based on their network + properties, or to particular clusters and clones within a repertoire. + Yang et al. (2023) . + date_publication: '2024-03-03' + bug_reports: '' + url: https://mlizhangx.github.io/Network-Analysis-for-Repertoire-Sequencing-/ + url_cran: https://CRAN.R-project.org/package=NAIR + url_git: https://github.com/mlizhangx/Network-Analysis-for-Repertoire-Sequencing- +naive: + version: 1.2.3 + title: Empirical Extrapolation of Time Feature Patterns + maintainer: Giancarlo Vercellino + description: An application for the empirical extrapolation of time features selecting + and summarizing the most relevant patterns in time sequences. + date_publication: '2023-06-20' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/naive + url_cran: https://CRAN.R-project.org/package=naive + url_git: '' +naivebayes: + version: 1.0.0 + title: High Performance Implementation of the Naive Bayes Algorithm + maintainer: Michal Majka + description: |- + In this implementation of the Naive Bayes classifier + following class conditional distributions are available: 'Bernoulli', + 'Categorical', 'Gaussian', 'Poisson', 'Multinomial' and non-parametric + representation of the class conditional density estimated via Kernel + Density Estimation. Implemented classifiers handle missing data and + can take advantage of sparse data. + date_publication: '2024-03-16' + bug_reports: https://github.com/majkamichal/naivebayes/issues + url: https://majkamichal.github.io/naivebayes/ + url_cran: https://CRAN.R-project.org/package=naivebayes + url_git: https://github.com/majkamichal/naivebayes +naivereg: + version: 1.0.5 + title: |- + Nonparametric Additive Instrumental Variable Estimator and + Related IV Methods + maintainer: Qingliang Fan + description: 'In empirical studies, instrumental variable (IV) regression is the + signature method to solve the endogeneity problem. If we enforce the exogeneity + condition of the IV, it is likely that we end up with a large set of IVs without + knowing which ones are good. Also, one could face the model uncertainty for structural + equation, as large micro dataset is commonly available nowadays. This package + uses adaptive group lasso and B-spline methods to select the nonparametric components + of the IV function, with the linear function being a special case (naivereg). + The package also incorporates two stage least squares estimator (2SLS), generalized + method of moment (GMM), generalized empirical likelihood (GEL) methods post instrument + selection, logistic-regression instrumental variables estimator (LIVE, for dummy + endogenous variable problem), double-selection plus instrumental variable estimator + (DS-IV) and double selection plus logistic regression instrumental variable estimator + (DS-LIVE), where the double selection methods are useful for high-dimensional + structural equation models. The naivereg is nonparametric version of ''ivregress'' + in ''Stata'' with IV selection and high dimensional features. The package is based + on the paper by Q. Fan and W. Zhong, "Nonparametric Additive Instrumental Variable + Estimator: A Group Shrinkage Estimation Perspective" (2018), Journal of Business + & Economic Statistics as well as a series + of working papers led by the same authors.' + date_publication: '2020-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=naivereg + url_git: '' +nakagami: + version: 1.1.0 + title: Functions for the Nakagami Distribution + maintainer: Jonas Moss + description: |- + Density, distribution function, quantile function and random + generation for the Nakagami distribution of Nakagami (1960) + . + date_publication: '2021-09-14' + bug_reports: https://github.com/JonasMoss/nakagami/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nakagami + url_git: https://github.com/JonasMoss/nakagami +NAM: + version: 1.7.3 + title: Nested Association Mapping + maintainer: Alencar Xavier + description: Designed for association studies in nested association mapping (NAM) + panels, experimental and random panels. The method is described by Xavier et al. + (2015) . It includes tools for genome-wide + associations of multiple populations, marker quality control, population genetics + analysis, genome-wide prediction, solving mixed models and finding variance components + through likelihood and Bayesian methods. + date_publication: '2019-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NAM + url_git: '' +name: + version: 0.0.1 + title: Tools for Working with Names + maintainer: Christopher T. Kenny + description: |- + A system for organizing column names in data. Aimed at supporting a + prefix-based and suffix-based column naming scheme. Extends 'dplyr' functionality + to add ordering by function and more explicit renaming. + date_publication: '2022-08-11' + bug_reports: https://github.com/christopherkenny/name/issues + url: https://christophertkenny.com/name/ + url_cran: https://CRAN.R-project.org/package=name + url_git: https://github.com/christopherkenny/name +namedropR: + version: 2.4.1 + title: Create Visual Citations for Presentations and Posters + maintainer: Christian A. Gebhard + description: |- + Provides 'visual citations' containing the metadata of a + scientific paper and a 'QR' code. A 'visual citation' is a banner + containing title, authors, journal and year of a publication. This + package can create such banners based on 'BibTeX' and 'BibLaTeX' + references or call the reference metadata from 'Crossref'-API. The + banners include a QR code pointing to the 'DOI'. The resulting HTML + object or PNG image can be included in a presentation to point the + audience to good resources for further reading. Styling is possible + via predefined designs or via custom 'CSS'. This package is not + intended as replacement for proper reference manager packages, but a + tool to enrich scientific presentation slides and conference posters. + date_publication: '2022-08-28' + bug_reports: https://github.com/nucleic-acid/namedropR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=namedropR + url_git: https://github.com/nucleic-acid/namedropR +NameNeedle: + version: 1.2.7 + title: Using Needleman-Wunsch to Match Sample Names + maintainer: Kevin R. Coombes + description: |- + The Needleman-Wunsch global alignment algorithm can be + used to find approximate matches between sample names in different + data sets. See Wang et al. (2010) . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NameNeedle + url_git: http://oompa.r-forge.r-project.org/ +namer: + version: 0.1.9 + title: Names Your 'R Markdown' Chunks + maintainer: Colin Gillespie + description: |- + It names the 'R Markdown' chunks of files based on the + filename. + date_publication: '2025-01-23' + bug_reports: https://github.com/jumpingrivers/namer/issues + url: https://jumpingrivers.github.io/namer/ + url_cran: https://CRAN.R-project.org/package=namer + url_git: https://github.com/jumpingrivers/namer +nametagger: + version: 0.1.3 + title: Named Entity Recognition in Texts using 'NameTag' + maintainer: Jan Wijffels + description: |- + Wraps the 'nametag' library , allowing users to find and extract entities (names, persons, locations, addresses, ...) in raw text and build your own entity recognition models. + Based on a maximum entropy Markov model which is described in Strakova J., Straka M. and Hajic J. (2013) . + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nametagger + url_git: https://github.com/bnosac/nametagger +nandb: + version: 2.1.0 + title: Number and Brightness Image Analysis + maintainer: Rory Nolan + description: |- + Calculation of molecular number and brightness from + fluorescence microscopy image series. The software was published in a + 2016 paper . The seminal paper for + the technique is Digman et al. 2008 . + A review of the technique was published in 2017 + . + date_publication: '2021-05-16' + bug_reports: https://github.com/rorynolan/nandb/issues + url: https://rorynolan.github.io/nandb/ + url_cran: https://CRAN.R-project.org/package=nandb + url_git: https://github.com/rorynolan/nandb +naniar: + version: 1.1.0 + title: Data Structures, Summaries, and Visualisations for Missing Data + maintainer: Nicholas Tierney + description: |- + Missing values are ubiquitous in data and need to be explored and + handled in the initial stages of analysis. 'naniar' provides data + structures and functions that facilitate the plotting of missing values and + examination of imputations. This allows missing data dependencies to be + explored with minimal deviation from the common work patterns of 'ggplot2' + and tidy data. The work is fully discussed at Tierney & Cook (2023) + . + date_publication: '2024-03-05' + bug_reports: https://github.com/njtierney/naniar/issues + url: http://naniar.njtierney.com/ + url_cran: https://CRAN.R-project.org/package=naniar + url_git: https://github.com/njtierney/naniar +nanoarrow: + version: 0.6.0 + title: Interface to the 'nanoarrow' 'C' Library + maintainer: Dewey Dunnington + description: |- + Provides an 'R' interface to the 'nanoarrow' 'C' library and the + 'Apache Arrow' application binary interface. Functions to import and + export 'ArrowArray', 'ArrowSchema', and 'ArrowArrayStream' 'C' structures + to and from 'R' objects are provided alongside helpers to facilitate zero-copy + data transfer among 'R' bindings to libraries implementing the 'Arrow' 'C' + data interface. + date_publication: '2024-10-13' + bug_reports: https://github.com/apache/arrow-nanoarrow/issues + url: https://arrow.apache.org/nanoarrow/latest/r/ + url_cran: https://CRAN.R-project.org/package=nanoarrow + url_git: https://github.com/apache/arrow-nanoarrow +nanonext: + version: 1.5.1 + title: NNG (Nanomsg Next Gen) Lightweight Messaging Library + maintainer: Charlie Gao + description: |- + R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ. NNG is + a socket library for reliable, high-performance messaging over in-process, + IPC, TCP, WebSocket and secure TLS transports. Implements 'Scalability + Protocols', a standard for common communications patterns including + publish/subscribe, request/reply and service discovery. As its own threaded + concurrency framework, provides a toolkit for asynchronous programming and + distributed computing. Intuitive 'aio' objects resolve automatically when + asynchronous operations complete, and synchronisation primitives allow R to + wait upon events signalled by concurrent threads. + date_publication: '2025-02-16' + bug_reports: https://github.com/shikokuchuo/nanonext/issues + url: https://shikokuchuo.net/nanonext/ + url_cran: https://CRAN.R-project.org/package=nanonext + url_git: https://github.com/shikokuchuo/nanonext/ +nanoparquet: + version: 0.4.2 + title: Read and Write 'Parquet' Files + maintainer: Gábor Csárdi + description: |- + Self-sufficient reader and writer for flat 'Parquet' files. + Can read most 'Parquet' data types. Can write many 'R' data types, + including factors and temporal types. See docs for limitations. + date_publication: '2025-02-22' + bug_reports: https://github.com/r-lib/nanoparquet/issues + url: https://nanoparquet.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=nanoparquet + url_git: https://github.com/r-lib/nanoparquet +nanostringr: + version: 0.5.0 + title: |- + Performs Quality Control, Data Normalization, and Batch Effect + Correction for 'NanoString nCounter' Data + maintainer: Derek Chiu + description: |- + Provides quality control (QC), normalization, and batch + effect correction operations for 'NanoString nCounter' data, Talhouk + et al. (2016) . Various metrics are + used to determine which samples passed or failed QC. Gene expression + should first be normalized to housekeeping genes, before a + reference-based approach is used to adjust for batch effects. Raw + NanoString data can be imported in the form of Reporter Code Count + (RCC) files. + date_publication: '2025-02-05' + bug_reports: https://github.com/TalhoukLab/nanostringr/issues + url: https://talhouklab.github.io/nanostringr/ + url_cran: https://CRAN.R-project.org/package=nanostringr + url_git: https://github.com/TalhoukLab/nanostringr/ +nanotime: + version: 0.3.11 + title: Nanosecond-Resolution Time Support for R + maintainer: Dirk Eddelbuettel + description: |- + Full 64-bit resolution date and time functionality with + nanosecond granularity is provided, with easy transition to and from + the standard 'POSIXct' type. Three additional classes offer interval, + period and duration functionality for nanosecond-resolution timestamps. + date_publication: '2025-01-10' + bug_reports: https://github.com/eddelbuettel/nanotime/issues + url: https://eddelbuettel.github.io/nanotime/ + url_cran: https://CRAN.R-project.org/package=nanotime + url_git: https://github.com/eddelbuettel/nanotime +NAP: + version: '1.1' + title: Non-Local Alternative Priors in Psychology + maintainer: Sandipan Pramanik + description: |- + Conducts Bayesian Hypothesis tests of a point null hypothesis against a two-sided alternative + using Non-local Alternative Prior (NAP) for one- and two-sample z- and t-tests + (Pramanik and Johnson, 2022). Under the alternative, the NAP is assumed on the standardized + effects size in one-sample tests and on their differences in two-sample tests. The package + considers two types of NAP densities: (1) the normal moment prior, and (2) the composite alternative. + In fixed design tests, the functions calculate the Bayes factors and the expected weight of evidence + for varied effect size and sample size. The package also provides a sequential testing framework using the + Sequential Bayes Factor (SBF) design. The functions calculate the operating characteristics (OC) + and the average sample number (ASN), and also conducts sequential tests for a sequentially observed data. + date_publication: '2022-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NAP + url_git: '' +naptanr: + version: 1.0.1 + title: Call the 'NaPTAN' API Through R + maintainer: Francesca Bryden + description: An R wrapper for pulling data from the National Public Transport Access + Nodes ('NaPTAN') API (). + This allows users to download 'NaPTAN' transport information, for the full dataset, + by ATCO region code, or by name of region. + date_publication: '2022-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=naptanr + url_git: '' +naptime: + version: 1.3.0 + title: A Flexible and Robust Sys.sleep() Replacement + maintainer: Russell S. Pierce + description: |- + Provides a near drop-in replacement for base::Sys.sleep() that allows more types of input + to produce delays in the execution of code and can silence/prevent typical sources of error. + date_publication: '2017-02-23' + bug_reports: https://github.com/drknexus/naptime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=naptime + url_git: URL:https://github.com/drknexus/naptime +nardl: + version: 0.1.6 + title: Nonlinear Cointegrating Autoregressive Distributed Lag Model + maintainer: Taha Zaghdoudi + description: Computes the nonlinear cointegrating autoregressive distributed lag + model with automatic bases aic and bic lags selection of independent variables + proposed by (Shin, Yu & Greenwood-Nimmo, 2014 ). + date_publication: '2021-01-06' + bug_reports: https://github.com/zedtaha/nardl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nardl + url_git: https://github.com/zedtaha/nardl +narray: + version: 0.5.1 + title: Subset- And Name-Aware Array Utility Functions + maintainer: Michael Schubert + description: |- + Stacking arrays according to dimension names, subset-aware + splitting and mapping of functions, intersecting along arbitrary + dimensions, converting to and from data.frames, and many other helper + functions. + date_publication: '2022-10-02' + bug_reports: https://github.com/mschubert/narray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=narray + url_git: https://github.com/mschubert/narray +naryn: + version: 2.6.30 + title: Native Access Medical Record Retriever for High Yield Analytics + maintainer: Aviezer Lifshitz + description: |- + A toolkit for medical records data analysis. The 'naryn' + package implements an efficient data structure for storing medical + records, and provides a set of functions for data extraction, + manipulation and analysis. + date_publication: '2024-09-27' + bug_reports: https://github.com/tanaylab/naryn/issues + url: https://tanaylab.github.io/naryn/ + url_cran: https://CRAN.R-project.org/package=naryn + url_git: '' +nasadata: + version: 0.9.0 + title: Interface to Various NASA API's + maintainer: Eduardo Flores + description: |- + Provides functions to access NASA's Earth Imagery and Assets API + and the Earth Observatory Natural Event Tracker (EONET) webservice. + date_publication: '2016-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nasadata + url_git: '' +nasapower: + version: 4.2.2 + title: NASA POWER API Client + maintainer: Adam H. Sparks + description: |- + An API client for NASA POWER global meteorology, surface + solar energy and climatology data API. POWER (Prediction Of Worldwide + Energy Resources) data are freely available for download with varying + spatial resolutions dependent on the original data and with several + temporal resolutions depending on the POWER parameter and community. + This work is funded through the NASA Earth Science Directorate Applied + Science Program. For more on the data themselves, the methodologies + used in creating, a web- based data viewer and web access, please see + . + date_publication: '2024-12-18' + bug_reports: https://github.com/ropensci/nasapower/issues + url: https://docs.ropensci.org/nasapower/ + url_cran: https://CRAN.R-project.org/package=nasapower + url_git: '' +nasaweather: + version: '0.1' + title: Collection of datasets from the ASA 2006 data expo + maintainer: '''Hadley Wickham''' + description: |- + This package contains tidied data from the ASA 2006 data expo, + as well as a number of useful other related data sets. + date_publication: '2014-07-22' + bug_reports: '' + url: http://stat-computing.org/dataexpo/2006/ + url_cran: https://CRAN.R-project.org/package=nasaweather + url_git: http://github.com/hadley/nasaweather +nascaR.data: + version: 2.2.0 + title: NASCAR Race Data + maintainer: Kyle Grealis + description: 'A collection of NASCAR race, driver, owner and manufacturer data across + the three major NASCAR divisions: NASCAR Cup Series, NASCAR Xfinity Series, and + NASCAR Craftsman Truck Series. The curated data begins with the 1949 season and + extends through the end of the 2024 season. Explore race, season, or career performance + for drivers, teams, and manufacturers throughout NASCAR''s history. Data was sourced + with permission from DriverAverages.com.' + date_publication: '2025-02-12' + bug_reports: '' + url: https://azimuth-project.tech/nascaR.data/ + url_cran: https://CRAN.R-project.org/package=nascaR.data + url_git: '' +NasdaqDataLink: + version: 1.0.0 + title: API Wrapper for Nasdaq Data Link + maintainer: Jamie Couture + description: Functions for interacting directly with the Nasdaq Data Link API to + offer data in a number of formats usable in R, downloading a zip with all data + from a Nasdaq Data Link database, and the ability to search. This R package uses + the Nasdaq Data Link API. For more information go to . + For more help on the package itself go to . + date_publication: '2022-06-22' + bug_reports: https://github.com/nasdaq/data-link-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NasdaqDataLink + url_git: https://github.com/nasdaq/data-link-r +naspaclust: + version: 0.2.1 + title: Nature-Inspired Spatial Clustering + maintainer: Bahrul Ilmi Nasution + description: Implement and enhance the performance of spatial fuzzy clustering using + Fuzzy Geographically Weighted Clustering with various optimization algorithms, + mainly from Xin She Yang (2014) with book entitled Nature-Inspired + Optimization Algorithms. The optimization algorithm is useful to tackle the disadvantages + of clustering inconsistency when using the traditional approach. The distance + measurements option is also provided in order to increase the quality of clustering + results. The Fuzzy Geographically Weighted Clustering with nature inspired optimisation + algorithm was firstly developed by Arie Wahyu Wijayanto and Ayu Purwarianti (2014) + using Artificial Bee Colony algorithm. + date_publication: '2021-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=naspaclust + url_git: '' +nat: + version: 1.8.24 + title: NeuroAnatomy Toolbox for Analysis of 3D Image Data + maintainer: Gregory Jefferis + description: |- + NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D + biological image data, especially traced neurons. Reads and writes 3D images + in NRRD and 'Amira' AmiraMesh formats and reads surfaces in 'Amira' hxsurf + format. Traced neurons can be imported from and written to SWC and 'Amira' + LineSet and SkeletonGraph formats. These data can then be visualised in 3D + via 'rgl', manipulated including applying calculated registrations, e.g. + using the 'CMTK' registration suite, and analysed. There is also a simple + representation for neurons that have been subjected to 3D skeletonisation + but not formally traced; this allows morphological comparison between + neurons including searches and clustering (via the 'nat.nblast' extension + package). + date_publication: '2024-02-05' + bug_reports: https://github.com/natverse/nat/issues + url: https://natverse.org/ + url_cran: https://CRAN.R-project.org/package=nat + url_git: https://github.com/natverse/nat +nat.nblast: + version: 1.6.7 + title: |- + NeuroAnatomy Toolbox ('nat') Extension for Assessing Neuron + Similarity and Clustering + maintainer: Gregory Jefferis + description: |- + Extends package 'nat' (NeuroAnatomy Toolbox) by providing a + collection of NBLAST-related functions for neuronal morphology comparison (Costa et al. (2016) ). + date_publication: '2023-06-14' + bug_reports: https://github.com/natverse/nat.nblast/issues + url: https://natverse.org/nat.nblast/ + url_cran: https://CRAN.R-project.org/package=nat.nblast + url_git: '' +nat.templatebrains: + version: '1.1' + title: |- + NeuroAnatomy Toolbox ('nat') Extension for Handling Template + Brains + maintainer: Gregory Jefferis + description: |- + Extends package 'nat' (NeuroAnatomy Toolbox) by + providing objects and functions for handling template brains. + date_publication: '2023-06-14' + bug_reports: https://github.com/natverse/nat.templatebrains/issues + url: http://natverse.org/nat.templatebrains/ + url_cran: https://CRAN.R-project.org/package=nat.templatebrains + url_git: https://github.com/natverse/nat.templatebrains +nat.utils: + version: 0.6.1 + title: File System Utility Functions for 'NeuroAnatomy Toolbox' + maintainer: Gregory Jefferis + description: |- + Utility functions that may be of general interest + but are specifically required by the 'NeuroAnatomy Toolbox' ('nat'). + Includes functions to provide a basic make style system to update + files based on timestamp information, file locking and 'touch' + utility. Convenience functions for working with file paths include + 'abs2rel', 'split_path' and 'common_path'. Finally there are utility + functions for working with 'zip' and 'gzip' files including integrity + tests. + date_publication: '2023-06-07' + bug_reports: https://github.com/natverse/nat.utils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nat.utils + url_git: https://github.com/natverse/nat.utils +natcpp: + version: 0.1.0 + title: Fast C++ Primitives for the 'NeuroAnatomy Toolbox' + maintainer: Gregory Jefferis + description: |- + Fast functions implemented in C++ via 'Rcpp' to support the + 'NeuroAnatomy Toolbox' ('nat') ecosystem. These functions provide large + speed-ups for basic manipulation of neuronal skeletons over pure R + functions found in the 'nat' package. The expectation is that end + users will not use this package directly, but instead the 'nat' + package will automatically use routines from this package when it is + available to enable large performance gains. + date_publication: '2021-07-13' + bug_reports: https://github.com/natverse/natcpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=natcpp + url_git: https://github.com/natverse/natcpp +natmanager: + version: 0.5.1 + title: Install the 'Natverse' Packages from Scratch + maintainer: Gregory Jefferis + description: |- + Provides streamlined installation for packages from the 'natverse', + a suite of R packages for computational neuroanatomy built on top of the + 'nat' 'NeuroAnatomy Toolbox' package. Installation of the complete + 'natverse' suite requires a 'GitHub' user account and personal access token + 'GITHUB_PAT'. 'natmanager' will help the end user set this up if necessary. + date_publication: '2023-09-11' + bug_reports: https://github.com/natverse/natmanager/issues + url: http://natverse.org/natmanager/ + url_cran: https://CRAN.R-project.org/package=natmanager + url_git: https://github.com/natverse/natmanager +NatParksPalettes: + version: 0.2.0 + title: Color Palettes Inspired by National Parks + maintainer: Kevin Blake + description: Color palettes for data visualization inspired by National Parks. Currently + contains 15 color schemes and checks for colorblind-friendliness of palettes. + date_publication: '2022-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NatParksPalettes + url_git: https://github.com/kevinsblake/NatParksPalettes +natserv: + version: 1.0.0 + title: '''NatureServe'' Interface' + maintainer: Scott Chamberlain + description: |- + Interface to 'NatureServe' (). + Includes methods to get data, image metadata, search taxonomic names, + and make maps. + date_publication: '2020-05-16' + bug_reports: https://github.com/ropensci/natserv/issues + url: https://docs.ropensci.org/natserv + url_cran: https://CRAN.R-project.org/package=natserv + url_git: https://github.com/ropensci/natserv +natstrat: + version: 2.0.0 + title: Obtain Unweighted Natural Strata that Balance Many Covariates + maintainer: Katherine Brumberg + description: |- + Natural strata can be used in observational studies to balance + the distributions of many covariates across any number of treatment + groups and any number of comparisons. These strata have proportional + amounts of units within each stratum across the treatments, allowing + for simple interpretation and aggregation across strata. Within each + stratum, the units are chosen using randomized rounding of a linear + program that balances many covariates. + To solve the linear program, the 'Gurobi' commercial optimization software + is recommended, but not required. The 'gurobi' R package can be installed following the instructions + at . + date_publication: '2021-10-15' + bug_reports: https://github.com/kkbrum/natstrat/issues + url: https://kkbrum.github.io/natstrat/ + url_cran: https://CRAN.R-project.org/package=natstrat + url_git: https://github.com/kkbrum/natstrat +natural: + version: 0.9.0 + title: Estimating the Error Variance in a High-Dimensional Linear Model + maintainer: Guo Yu + description: Implementation of the two error variance estimation methods in high-dimensional + linear models of Yu, Bien (2017) . + date_publication: '2018-01-16' + bug_reports: https://github.com/hugogogo/natural/issues + url: https://arxiv.org/abs/1712.02412 + url_cran: https://CRAN.R-project.org/package=natural + url_git: '' +naturaList: + version: 0.5.2 + title: Classify Occurrences by Confidence Levels in the Species ID + maintainer: Arthur Vinicius Rodrigues + description: |- + Classify occurrence records based on confidence + levels of species identification. In addition, implement tools to filter + occurrences inside grid cells and to manually check for possibles errors with + an interactive shiny application. + date_publication: '2024-02-06' + bug_reports: https://github.com/avrodrigues/naturaList/issues + url: '' + url_cran: https://CRAN.R-project.org/package=naturaList + url_git: https://github.com/avrodrigues/naturaList +naturalsort: + version: 0.1.3 + title: Natural Ordering + maintainer: Kosei Abe + description: |- + Provides functions related to human natural ordering. + It handles adjacent digits in a character sequence as a number so that + natural sort function arranges a character vector by their numbers, not digit + characters. It is typically seen when operating systems lists file names. For + example, a sequence a-1.png, a-2.png, a-10.png looks naturally ordered because 1 + < 2 < 10 and natural sort algorithm arranges so whereas general sort algorithms + arrange it into a-1.png, a-10.png, a-2.png owing to their third and fourth + characters. + date_publication: '2016-08-30' + bug_reports: https://github.com/kos59125/naturalsort/issues + url: '' + url_cran: https://CRAN.R-project.org/package=naturalsort + url_git: '' +NatureSounds: + version: 1.0.5 + title: Animal Sounds for Bioacustic Analysis + maintainer: Marcelo Araya-Salas + description: Collection of example animal sounds for bioacoustic analysis. + date_publication: '2025-01-17' + bug_reports: https://github.com/maRce10/NatureSounds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NatureSounds + url_git: https://github.com/maRce10/NatureSounds +navigation: + version: 0.0.1 + title: |- + Analyze the Impact of Sensor Error Modelling on Navigation + Performance + maintainer: Lionel Voirol + description: |- + Implements the framework presented in Cucci, D. A., Voirol, L., Khaghani, M. and Guerrier, S. (2023) which allows to analyze the impact of sensor error modeling on the performance of integrated navigation (sensor fusion) based on inertial measurement unit (IMU), Global Positioning System (GPS), and barometer data. + The framework relies on Monte Carlo simulations in which a Vanilla Extended Kalman filter is coupled with realistic and user-configurable noise generation mechanisms to recover a reference trajectory from noisy measurements. + The evaluation of several statistical metrics of the solution, aggregated over hundreds of simulated realizations, provides reasonable estimates of the expected performances of the system in real-world conditions. + date_publication: '2023-05-16' + bug_reports: https://github.com/SMAC-Group/navigation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=navigation + url_git: https://github.com/SMAC-Group/navigation +navigatr: + version: 0.2.1 + title: Navigation Menu for Pipe-Friendly Data Processing + maintainer: Mizuki Uchida + description: |- + Provides a navigation menu to enable pipe-friendly data processing for hierarchical data structures. + By activating the menu items, you can perform operations on each item while maintaining the overall structure in attributes. + date_publication: '2023-03-26' + bug_reports: https://github.com/UchidaMizuki/navigatr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=navigatr + url_git: https://github.com/UchidaMizuki/navigatr +nawtilus: + version: 0.1.4 + title: Navigated Weighting for the Inverse Probability Weighting + maintainer: Hiroto Katsumata + description: |- + Implements the navigated weighting (NAWT) proposed by Katsumata (2020) + , which improves the inverse probability weighting by + utilizing estimating equations suitable for a specific pre-specified parameter + of interest (e.g., the average treatment effects or the average treatment + effects on the treated) in propensity score estimation. It includes the + covariate balancing propensity score proposed by Imai and Ratkovic (2014) + , which uses covariate balancing conditions in + propensity score estimation. The point estimate of the parameter of interest + as well as coefficients for propensity score estimation and their + uncertainty are produced using the M-estimation. The same functions can be + used to estimate average outcomes in missing outcome cases. + date_publication: '2020-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nawtilus + url_git: '' +NB.MClust: + version: 1.1.1 + title: Negative Binomial Model-Based Clustering + maintainer: Qian Li + description: |- + Model-based clustering of high-dimensional non-negative + data that follow Generalized Negative Binomial distribution. All functions + in this package applies to either continuous or integer data. Correlation + between variables are allowed, while samples are assumed to be independent. + date_publication: '2017-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NB.MClust + url_git: '' +NBAloveR: + version: 0.1.3.3 + title: Help Basketball Data Analysis + maintainer: Koki Ando + description: |- + Provides interface to the online basketball data resources such as + Basketball reference API and helps + R users analyze basketball data. + date_publication: '2019-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBAloveR + url_git: '' +nbapalettes: + version: 0.1.0 + title: An NBA Jersey Palette Generator + maintainer: Murray Josh + description: Palettes generated from NBA jersey colorways. + date_publication: '2021-01-07' + bug_reports: https://github.com/murrayjw/nbapalettes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nbapalettes + url_git: https://github.com/murrayjw/nbapalettes +NBBDesigns: + version: 1.1.0 + title: Neighbour Balanced Block Designs (NBBDesigns) + maintainer: Ashutosh Dalal + description: 'Neighbour-balanced designs ensure that no treatment is disadvantaged + unfairly by its surroundings. The treatment allocation in these designs is such + that every treatment appears equally often as a neighbour with every other treatment. + Neighbour Balanced Designs are employed when there is a possibility of neighbour + effects from treatments used in adjacent experimental units. In the literature, + a vast number of such designs have been developed. This package generates some + efficient neighbour balanced block designs which are balanced and partially variance + balanced for estimating the contrast pertaining to direct and neighbour effects, + as well as provides a function for analysing the data obtained from such trials + (Azais, J.M., Bailey, R.A. and Monod, H. (1993). "A catalogue of efficient neighbour + designs with border plots". Biometrics, 49, 1252-1261 ; Tomar, J. S., Jaggi, Seema + and Varghese, Cini (2005). "On totally balanced + block designs for competition effects"). This package contains functions named + nbbd1(),nbbd2(),nbbd3(),pnbbd1() and pnbbd2() which generates neighbour balanced + block designs within a specified range of number of treatment (v). It contains + another function named anlys()for performing the analysis of data generated from + such trials.' + date_publication: '2023-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBBDesigns + url_git: '' +nbc4va: + version: '1.2' + title: Bayes Classifier for Verbal Autopsy Data + maintainer: Richard Wen + description: |- + An implementation of the Naive Bayes Classifier (NBC) algorithm + used for Verbal Autopsy (VA) built on code from Miasnikof et al (2015) + . + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nbc4va + url_git: '' +NbClust: + version: 3.0.1 + title: Determining the Best Number of Clusters in a Data Set + maintainer: Malika Charrad + description: It provides 30 indexes for determining the optimal number of clusters + in a data set and offers the best clustering scheme from different results to + the user. + date_publication: '2022-05-02' + bug_reports: '' + url: https://sites.google.com/site/malikacharrad/research/nbclust-package + url_cran: https://CRAN.R-project.org/package=NbClust + url_git: '' +nbconv: + version: 1.0.1 + title: Evaluate Arbitrary Negative Binomial Convolutions + maintainer: Gregory Bedwell + description: 'Three distinct methods are implemented for evaluating the sums of + arbitrary negative binomial distributions. These methods are: Furman''s exact + probability mass function (Furman (2007) ), saddlepoint + approximation, and a method of moments approximation. Functions are provided to + calculate the density function, the distribution function and the quantile function + of the convolutions in question given said evaluation methods. Functions for generating + random deviates from negative binomial convolutions and for directly calculating + the mean, variance, skewness, and excess kurtosis of said convolutions are also + provided.' + date_publication: '2023-07-06' + bug_reports: https://github.com/gbedwell/nbconv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nbconv + url_git: https://github.com/gbedwell/nbconv +nbconvertR: + version: 1.3.2 + title: Vignette Engine Wrapping Jupyter Notebooks + maintainer: Philipp Angerer + description: |2- + + Calls the 'Jupyter' script 'nbconvert' to create vignettes from + notebooks. Those notebooks ('.ipynb' files) are files containing rich text, + code, and its output. Code cells can be edited and evaluated interactively. + See for more information. + date_publication: '2019-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nbconvertR + url_git: '' +NBDdirichlet: + version: '1.4' + title: |- + NBD-Dirichlet Model of Consumer Buying Behavior for Marketing + Research + maintainer: Feiming Chen + description: The Dirichlet (aka NBD-Dirichlet) model describes the purchase incidence + and brand choice of consumer products. We estimate the model and summarize various + theoretical quantities of interest to marketing researchers. Also provides functions + for making tables that compare observed and theoretical statistics. + date_publication: '2022-05-29' + bug_reports: '' + url: https://ani.stat.fsu.edu/~fchen/statistics/R-package-NBDdirichlet/how-to-use-Dirichlet-marketing-model.html + url_cran: https://CRAN.R-project.org/package=NBDdirichlet + url_git: '' +NBDesign: + version: 2.0.0 + title: |- + Design and Monitoring of Clinical Trials with Negative Binomial + Endpoint + maintainer: Xiaodong Luo + description: |- + Calculate various functions needed for design and monitoring clinical trials with negative binomial endpoint + with variable follow-up. This version has a few changes compared to the previous version 1.0.0, including + (1) correct a typo in Type 1 censoring, mtbnull=bnull and (2) restructure the code to account for shape parameter equal to zero, i.e. Poisson scenario. + date_publication: '2020-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBDesign + url_git: '' +nberwp: + version: 1.2.0 + title: NBER Working Papers + maintainer: Benjamin Davies + description: Catalogue of NBER working papers published between June 1973 and December + 2021. + date_publication: '2022-03-27' + bug_reports: https://github.com/bldavies/nberwp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nberwp + url_git: https://github.com/bldavies/nberwp +NBLDA: + version: 1.0.1 + title: Negative Binomial Linear Discriminant Analysis + maintainer: Dincer Goksuluk + description: 'We proposed a package for the classification task which uses Negative + Binomial distribution within Linear Discriminant Analysis (NBLDA). It is an extension + of the ''PoiClaClu'' package to Negative Binomial distribution. The classification + algorithms are based on the papers Dong et al. (2016, ISSN: 1471-2105) and Witten, + DM (2011, ISSN: 1932-6157) for NBLDA and PLDA, respectively. Although PLDA is + a sparse algorithm and can be used for variable selection, the algorithm proposed + by Dong et al. is not sparse. Therefore, it uses all variables in the classifier. + Here, we extend Dong et al.''s algorithm to the sparse case by shrinking overdispersion + towards 0 (Yu et al., 2013, ISSN: 1367-4803) and offset parameter towards 1 (as + proposed by Witten DM, 2011). We support only the classification task with this + version.' + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBLDA + url_git: '' +nblR: + version: 0.0.4 + title: Data Extraction of Australian NBL Basketball Statistics + maintainer: Jason Zivkovic + description: |- + Allow users to obtain basketball statistics for + the Australian basketball league 'NBL'. + Stats include play-by-play, shooting locations, results and + box scores for teams and players. + date_publication: '2023-02-06' + bug_reports: https://github.com/JaseZiv/nblR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nblR + url_git: https://github.com/JaseZiv/nblR +nbody: + version: '1.41' + title: Gravitational N-Body Simulation + maintainer: Danail Obreschkow + description: Run simple direct gravitational N-body simulations. The package can + access different external N-body simulators (e.g. GADGET-4 by Springel et al. + (2021) ), but also has a simple built-in simulator. + This default simulator uses a variable block time step and lets the user choose + between a range of integrators, including 4th and 6th order integrators for high-accuracy + simulations. Basic top-hat smoothing is available as an option. The code also + allows the definition of background particles that are fixed or in uniform motion, + not subject to acceleration by other particles. + date_publication: '2024-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nbody + url_git: '' +nbpMatching: + version: 1.5.6 + title: Functions for Optimal Non-Bipartite Matching + maintainer: Cole Beck + description: |- + Perform non-bipartite matching and matched randomization. A + "bipartite" matching utilizes two separate groups, e.g. smokers being + matched to nonsmokers or cases being matched to controls. A "non-bipartite" + matching creates mates from one big group, e.g. 100 hospitals being + randomized for a two-arm cluster randomized trial or 5000 children who + have been exposed to various levels of secondhand smoke and are being + paired to form a greater exposure vs. lesser exposure comparison. At the + core of a non-bipartite matching is a N x N distance matrix for N potential + mates. The distance between two units expresses a measure of similarity or + quality as mates (the lower the better). The 'gendistance()' and + 'distancematrix()' functions assist in creating this. The 'nonbimatch()' + function creates the matching that minimizes the total sum of distances + between mates; hence, it is referred to as an "optimal" matching. The + 'assign.grp()' function aids in performing a matched randomization. Note + bipartite matching can be performed using the prevent option in + 'gendistance()'. + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nbpMatching + url_git: https://github.com/couthcommander/nbpMatching +NBPSeq: + version: 0.3.1 + title: Negative Binomial Models for RNA-Sequencing Data + maintainer: Yanming Di + description: |- + Negative Binomial (NB) models for two-group comparisons and + regression inferences from RNA-Sequencing Data. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBPSeq + url_git: '' +NBR: + version: 0.1.5 + title: Network-Based R-Statistics using Mixed Effects Models + maintainer: Zeus Gracia-Tabuenca + description: |- + An implementation of network-based statistics in R using mixed effects models. + Theoretical background for Network-Based Statistics can be found in Zalesky et al. (2010) + . For Mixed Effects Models check the + R package . + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBR + url_git: '' +NBShiny: + version: 0.1.0 + title: Interactive Document for Working with Naive Bayes Classification + maintainer: Kartikeya Bolar + description: An interactive document on the topic of naive Bayes classification analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBShiny + url_git: '' +NBShiny2: + version: 0.1.0 + title: Interactive Document for Working with Naive Bayes Classification + maintainer: Kartikeya Bolar + description: An interactive document on the topic of naive Bayes classification analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBShiny2 + url_git: '' +NBShiny3: + version: 0.1.0 + title: Interactive Document for Working with Naive Bayes Classification + maintainer: Kartikeya Bolar + description: An interactive document on the topic of naive Bayes classification analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2020-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBShiny3 + url_git: '' +nbTransmission: + version: 1.1.4 + title: Naive Bayes Transmission Analysis + maintainer: Sarah V Leavitt + description: Estimates the relative transmission probabilities between cases in + an infectious disease outbreak or cluster using naive Bayes. Included are various + functions to use these probabilities to estimate transmission parameters such + as the generation/serial interval and reproductive number as well as finding the + contribution of covariates to the probabilities and visualizing results. The ideal + use is for an infectious disease dataset with metadata on the majority of cases + but more informative data such as contact tracing or pathogen whole genome sequencing + on only a subset of cases. For a detailed description of the methods see Leavitt + et al. (2020) . + date_publication: '2024-01-30' + bug_reports: https://github.com/sarahleavitt/nbTransmission/issues + url: https://sarahleavitt.github.io/nbTransmission/ + url_cran: https://CRAN.R-project.org/package=nbTransmission + url_git: '' +NBtsVarSel: + version: '1.0' + title: |- + Variable Selection in a Specific Regression Time Series of + Counts + maintainer: Marina Gomtsyan + description: Performs variable selection in sparse negative binomial GLARMA (Generalised + Linear Autoregressive Moving Average) models. For further details we refer the + reader to the paper Gomtsyan (2023), . + date_publication: '2023-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NBtsVarSel + url_git: '' +nc: + version: 2025.1.21 + title: Named Capture to Data Tables + maintainer: Toby Hocking + description: |- + User-friendly functions for extracting a data + table (row for each match, column for each group) + from non-tabular text data using regular expressions, + and for melting columns that match a regular expression. + Patterns are defined using a readable syntax + that makes it easy to build complex patterns + in terms of simpler, re-usable sub-patterns. + Named R arguments are translated to column names + in the output; capture groups without names are used + internally in order to provide a standard interface + to three regular expression 'C' libraries + ('PCRE', 'RE2', 'ICU'). + Output can also include numeric columns via + user-specified type conversion functions. + date_publication: '2025-01-21' + bug_reports: https://github.com/tdhock/nc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nc + url_git: https://github.com/tdhock/nc +NCA: + version: 4.0.2 + title: Necessary Condition Analysis + maintainer: Govert Buijs + description: |- + Performs a Necessary Condition Analysis (NCA). (Dul, J. 2016. Necessary Condition Analysis (NCA). ''Logic and Methodology of 'Necessary but not Sufficient' causality." Organizational Research Methods 19(1), 10-52) . + NCA identifies necessary (but not sufficient) conditions in datasets, where x causes (e.g. precedes) y. Instead of drawing a regression line ''through the middle of the data'' in an xy-plot, NCA draws the ceiling line. The ceiling line y = f(x) separates the area with observations from the area without observations. + (Nearly) all observations are below the ceiling line: y <= f(x). The empty zone is in the upper left hand corner of the xy-plot (with the convention that the x-axis is ''horizontal'' and the y-axis is ''vertical'' and that values increase ''upwards'' and ''to the right''). The ceiling line is a (piecewise) linear non-decreasing line: a linear step function or a straight line. It indicates which level of x (e.g. an effort or input) is necessary but not sufficient for a (desired) level of y (e.g. good performance or output). A quick start guide for using this package can be found here: or . + date_publication: '2024-11-09' + bug_reports: '' + url: https://www.erim.eur.nl/necessary-condition-analysis/ + url_cran: https://CRAN.R-project.org/package=NCA + url_git: '' +ncaavolleyballr: + version: 0.4.1 + title: Extract Data from NCAA Women's and Men's Volleyball Website + maintainer: Jeffrey R. Stevens + description: |- + Extracts team records/schedules and player statistics for the + 2020-2024 National Collegiate Athletic Association (NCAA) women's and men's + divisions I, II, and III volleyball teams from . + Functions can aggregate statistics for teams, conferences, divisions, or + custom groups of teams. + date_publication: '2025-01-23' + bug_reports: https://github.com/JeffreyRStevens/ncaavolleyballr/issues + url: https://jeffreyrstevens.github.io/ncaavolleyballr/ + url_cran: https://CRAN.R-project.org/package=ncaavolleyballr + url_git: https://github.com/JeffreyRStevens/ncaavolleyballr +ncappc: + version: 0.3.0 + title: NCA Calculations and Population Model Diagnosis + maintainer: Andrew C. Hooker + description: |- + A flexible tool that can perform + (i) traditional non-compartmental analysis (NCA) and + (ii) Simulation-based posterior predictive checks for population + pharmacokinetic (PK) and/or pharmacodynamic (PKPD) models using NCA metrics. + date_publication: '2018-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ncappc + url_git: '' +ncar: + version: 0.5.0 + title: Noncompartmental Analysis for Pharmacokinetic Report + maintainer: Kyun-Seop Bae + description: |- + Conduct a noncompartmental analysis with industrial strength. + Some features are + 1) CDISC SDTM terms + 2) Automatic or manual slope selection + 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method + 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method + 5) Produce pdf, rtf, text report files. + * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107). + date_publication: '2023-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ncar + url_git: '' +ncbit: + version: 2013.03.29.1 + title: Retrieve and Build NBCI Taxonomic Data + maintainer: Jon Eastman + description: |- + Makes NCBI taxonomic data locally available and + searchable as an R object. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ncbit + url_git: '' +NCC: + version: '1.0' + title: |- + Simulation and Analysis of Platform Trials with Non-Concurrent + Controls + maintainer: Pavla Krotka + description: |- + Design and analysis of flexible platform trials with non-concurrent controls. Functions for data generation, analysis, visualization and running simulation studies are provided. + The implemented analysis methods are described in: + Bofill Roig et al. (2022) , + Saville et al. (2022) and + Schmidli et al. (2014) . + date_publication: '2023-03-03' + bug_reports: '' + url: https://pavlakrotka.github.io/NCC/ + url_cran: https://CRAN.R-project.org/package=NCC + url_git: https://github.com/pavlakrotka/NCC +ncdf4: + version: '1.23' + title: |- + Interface to Unidata netCDF (Version 4 or Earlier) Format Data + Files + maintainer: David Pierce + description: Provides a high-level R interface to data files written using Unidata's + netCDF library (version 4 or earlier), which are binary data files that are portable + across platforms and include metadata information in addition to the data sets. Using + this package, netCDF files (either version 4 or "classic" version 3) can be opened + and data sets read in easily. It is also easy to create new netCDF dimensions, + variables, and files, in either version 3 or 4 format, and manipulate existing + netCDF files. This package replaces the former ncdf package, which only worked + with netcdf version 3 files. For various reasons the names of the functions have + had to be changed from the names in the ncdf package. The old ncdf package is + still available at the URL given below, if you need to have backward compatibility. It + should be possible to have both the ncdf and ncdf4 packages installed simultaneously + without a problem. However, the ncdf package does not provide an interface for + netcdf version 4 files. + date_publication: '2024-08-17' + bug_reports: '' + url: https://cirrus.ucsd.edu/~pierce/ncdf/ + url_cran: https://CRAN.R-project.org/package=ncdf4 + url_git: '' +ncdf4.helpers: + version: 0.3-6 + title: Helper Functions for Use with the 'ncdf4' Package + maintainer: Lee Zeman + description: |- + Contains a collection of helper functions for dealing with + 'NetCDF' files + opened using 'ncdf4', particularly 'NetCDF' files that conform to the + Climate and Forecast (CF) Metadata Conventions + . + date_publication: '2021-10-15' + bug_reports: https://github.com/pacificclimate/ncdf4.helpers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ncdf4.helpers + url_git: '' +ncdfCF: + version: 0.3.0 + title: Easy Access to NetCDF Files with CF Metadata Conventions + maintainer: Patrick Van Laake + description: |- + Network Common Data Form ('netCDF') files are widely used for + scientific data. Library-level access in R is provided through packages + 'RNetCDF' and 'ncdf4'. Package 'ncdfCF' is built on top of 'RNetCDF' and + makes the data and its attributes available as a set of R6 classes that are + informed by the Climate and Forecasting Metadata Conventions. Access to the + data uses standard R subsetting operators and common function forms. + date_publication: '2025-01-19' + bug_reports: https://github.com/pvanlaake/ncdfCF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ncdfCF + url_git: https://github.com/pvanlaake/ncdfCF +ncdfgeom: + version: 1.1.6 + title: '''NetCDF'' Geometry and Time Series' + maintainer: David Blodgett + description: Tools to create time series and geometry 'NetCDF' files. + date_publication: '2024-01-25' + bug_reports: https://github.com/DOI-USGS/ncdfgeom/issues + url: https://code.usgs.gov/water/ncdfgeom + url_cran: https://CRAN.R-project.org/package=ncdfgeom + url_git: '' +ncdump: + version: 0.0.5 + title: Extract Metadata from 'NetCDF' Files as Data Frames + maintainer: Michael D. Sumner + description: |- + Tools for handling 'NetCDF' metadata in data frames. The metadata is provided + as relations in tabular form, to avoid having to scan printed header output or to navigate + nested lists of raw metadata. + date_publication: '2025-02-11' + bug_reports: https://github.com/hypertidy/ncdump/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ncdump + url_git: https://github.com/hypertidy/ncdump +ncf: + version: 1.3-2 + title: Spatial Covariance Functions + maintainer: Ottar N. Bjornstad + description: |- + Spatial (cross-)covariance and related geostatistical tools: the + nonparametric (cross-)covariance function , the spline correlogram, the + nonparametric phase coherence function, local indicators of spatial + association (LISA), (Mantel) correlogram, (Partial) Mantel test. + date_publication: '2022-05-07' + bug_reports: https://github.com/objornstad/ncf/issues + url: https://ento.psu.edu/directory/onb1 + url_cran: https://CRAN.R-project.org/package=ncf + url_git: '' +ncmeta: + version: 0.4.0 + title: Straightforward 'NetCDF' Metadata + maintainer: Michael Sumner + description: |- + Extract metadata from 'NetCDF' data sources, these can be files, file handles or + servers. This package leverages and extends the lower level functions of the 'RNetCDF' package + providing a consistent set of functions that all return data frames. We introduce named concepts + of 'grid', 'axis' and 'source' which are all meaningful entities without formal definition in the + 'NetCDF' library . 'RNetCDF' matches the library + itself with only the named concepts of 'variables', 'dimensions' and 'attributes'. + date_publication: '2024-03-25' + bug_reports: https://github.com/hypertidy/ncmeta/issues + url: https://hypertidy.github.io/ncmeta/ + url_cran: https://CRAN.R-project.org/package=ncmeta + url_git: https://github.com/hypertidy/ncmeta +NCmisc: + version: 1.2.0 + title: |- + Miscellaneous Functions for Creating Adaptive Functions and + Scripts + maintainer: Nicholas Cooper + description: |- + A set of handy functions. Includes a versatile one line progress bar, one + line function timer with detailed output, time delay function, text histogram, object + preview, CRAN package search, simpler package installer, Linux command install check, + a flexible Mode function, top function, simulation of correlated data, and more. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NCmisc + url_git: '' +ncodeR: + version: 0.2.0.1 + title: Techniques for Automated Classifiers + maintainer: Cody L Marquart + description: 'A set of techniques that can be used to develop, validate, and implement + automated classifiers. A powerful tool for transforming raw data into meaningful + information, ''ncodeR'' (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: + 0578191687) is designed specifically for working with big data: large document + collections, logfiles, and other text data.' + date_publication: '2019-11-19' + bug_reports: https://gitlab.com/epistemic-analytics/qe-packages/ncoder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ncodeR + url_git: '' +ncpen: + version: 1.0.0 + title: |- + Unified Algorithm for Non-convex Penalized Estimation for + Generalized Linear Models + maintainer: Dongshin Kim + description: |- + An efficient unified nonconvex penalized estimation algorithm for + Gaussian (linear), binomial Logit (logistic), Poisson, multinomial Logit, + and Cox proportional hazard regression models. + The unified algorithm is implemented based on the convex concave procedure and + the algorithm can be applied to most of the existing nonconvex penalties. + The algorithm also supports convex penalty: + least absolute shrinkage and selection operator (LASSO). + Supported nonconvex penalties include + smoothly clipped absolute deviation (SCAD), + minimax concave penalty (MCP), truncated LASSO penalty (TLP), + clipped LASSO (CLASSO), sparse ridge (SRIDGE), + modified bridge (MBRIDGE) and modified log (MLOG). + For high-dimensional data (data set with many variables), + the algorithm selects relevant variables producing a parsimonious regression model. + Kim, D., Lee, S. and Kwon, S. (2018) , + Lee, S., Kwon, S. and Kim, Y. (2016) , + Kwon, S., Lee, S. and Kim, Y. (2015) . + (This research is funded by Julian Virtue Professorship from Center for Applied Research at Pepperdine + Graziadio Business School and the National Research Foundation of Korea.) + date_publication: '2018-11-17' + bug_reports: https://github.com/zeemkr/ncpen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ncpen + url_git: https://github.com/zeemkr/ncpen +NCSampling: + version: '1.0' + title: Nearest Centroid (NC) Sampling + maintainer: Gavin Melville + description: Provides functionality for performing Nearest Centroid (NC) Sampling. + The NC sampling procedure was developed for forestry applications and selects + plots for ground measurement so as to maximize the efficiency of imputation estimates. + It uses multiple auxiliary variables and multivariate clustering to search for + an optimal sample. Further details are given in Melville G. & Stone C. (2016) + . + date_publication: '2017-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NCSampling + url_git: '' +NCSCopula: + version: 1.0.1 + title: Non-Central Squared Copula Models Estimation + maintainer: Bouchra R. Nasri + description: Inference and dependence measure for the non-central squared Gaussian, + Student, Clayton, Gumbel, and Frank copula models.The description of the methodology + is taken from Section 3 of Nasri, Remillard and Bouezmarni (2019) . + date_publication: '2019-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NCSCopula + url_git: '' +NCutYX: + version: 0.1.0 + title: |- + Clustering of Omics Data of Multiple Types with a Multilayer + Network Representation + maintainer: Sebastian J. Teran Hidalgo + description: |- + Omics data come in different forms: gene expression, methylation, copy number, protein measurements and more. + 'NCutYX' allows clustering of variables, of samples, and both variables and samples (biclustering), + while incorporating the dependencies across multiple types of Omics data. + (SJ Teran Hidalgo et al (2017), ). + date_publication: '2018-02-09' + bug_reports: https://github.com/Seborinos/NCutYX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NCutYX + url_git: https://github.com/Seborinos/NCutYX +ncvreg: + version: 3.15.0 + title: |- + Regularization Paths for SCAD and MCP Penalized Regression + Models + maintainer: Patrick Breheny + description: |- + Fits regularization paths for linear regression, GLM, and Cox + regression models using lasso or nonconvex penalties, in particular the + minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) + penalty, with options for additional L2 penalties (the "elastic net" idea). + Utilities for carrying out cross-validation as well as post-fitting + visualization, summarization, inference, and prediction are also provided. + For more information, see Breheny and Huang (2011) + or visit the ncvreg homepage . + date_publication: '2025-02-11' + bug_reports: https://github.com/pbreheny/ncvreg/issues + url: https://pbreheny.github.io/ncvreg/ + url_cran: https://CRAN.R-project.org/package=ncvreg + url_git: https://github.com/pbreheny/ncvreg +nda: + version: 0.2.4 + title: Generalized Network-Based Dimensionality Reduction and Analysis + maintainer: Zsolt T. Kosztyan + description: Non-parametric dimensionality reduction function. Reduction with and + without feature selection. Plot functions. Automated feature selections. Kosztyan + et. al. (2024) . + date_publication: '2025-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nda + url_git: https://github.com/kzst/nda +ndi: + version: 0.1.5 + title: Neighborhood Deprivation Indices + maintainer: Ian D. Buller + description: |- + Computes various metrics of socio-economic deprivation and disparity in + the United States. Some metrics are considered "spatial" because they + consider the values of neighboring (i.e., adjacent) census geographies in + their computation, while other metrics are "aspatial" because they only + consider the value within each census geography. Two types of aspatial + neighborhood deprivation indices (NDI) are available: including: + (1) based on Messer et al. (2006) + and (2) based on Andrews et al. (2020) + and Slotman et al. (2022) + who use variables chosen by Roux and Mair (2010) + . Both are a decomposition of multiple + demographic characteristics from the U.S. Census Bureau American Community + Survey 5-year estimates (ACS-5; 2006-2010 onward). Using data from the ACS-5 + (2005-2009 onward), the package can also (1) compute the spatial Racial Isolation + Index (RI) based on Anthopolos et al. (2011) , + (2) compute the spatial Educational Isolation Index (EI) based on Bravo et al. + (2021) , (3) compute the aspatial Index of + Concentration at the Extremes (ICE) based on Feldman et al. (2015) + and Krieger et al. (2016) + , (4) compute the aspatial racial/ethnic + Dissimilarity Index based on Duncan & Duncan (1955) , (5) + compute the aspatial income or racial/ethnic Atkinson Index based on Atkinson + (1970) , (6) aspatial racial/ethnic Isolation + Index (II) based on Shevky & Williams (1949; ISBN-13:978-0-837-15637-8) and Bell + (1954) , (7) aspatial racial/ethnic Correlation Ratio + based on Bell (1954) and White (1986) , + (8) aspatial racial/ethnic Location Quotient (LQ) based on Merton (1939) + and Sudano et al. (2013) + , and (9) aspatial racial/ethnic Local + Exposure and Isolation metric based on Bemanian & Beyer (2017) + . Also using data from the ACS-5 (2005-2009 + onward), the package can retrieve the aspatial Gini Index based Gini (1921) + . + date_publication: '2024-01-23' + bug_reports: https://github.com/idblr/ndi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ndi + url_git: https://github.com/idblr/ndi +ndjson: + version: 0.9.0 + title: Wicked-Fast Streaming 'JSON' ('ndjson') Reader + maintainer: Bob Rudis + description: |- + Streaming 'JSON' ('ndjson') has one 'JSON' record per-line + and many modern 'ndjson' files contain large numbers of records. + These constructs may not be columnar in nature, but it is often + useful to read in these files and "flatten" the structure out to + enable working with the data in an R 'data.frame'-like context. + Functions are provided that make it possible to read in plain + 'ndjson' files or compressed ('gz') 'ndjson' files and either + validate the format of the records or create "flat" 'data.table' + structures from them. + date_publication: '2022-10-17' + bug_reports: https://github.com/hrbrmstr/ndjson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ndjson + url_git: https://github.com/hrbrmstr/ndjson +ndl: + version: 0.2.18 + title: Naive Discriminative Learning + maintainer: Tino Sering + description: |- + Naive discriminative learning implements learning and + classification models based on the Rescorla-Wagner equations and their + equilibrium equations. + date_publication: '2018-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ndl + url_git: '' +NDP: + version: 0.1.0 + title: Interactive Presentation for Working with Normal Distribution + maintainer: Kartikeya Bolar + description: An interactive presentation on the topic of normal distribution using + 'rmarkdown' and 'shiny' packages. It is helpful to those who want to learn normal + distribution quickly and get a hands on experience. The presentation has a template + for solving problems on normal distribution. Runtime examples are provided in + the package function as well as at . + date_publication: '2019-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NDP + url_git: '' +ndtv: + version: 0.13.4 + title: Network Dynamic Temporal Visualizations + maintainer: Skye Bender-deMoll + description: Renders dynamic network data from 'networkDynamic' objects as movies, + interactive animations, or other representations of changing relational structures + and attributes. + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ndtv + url_git: https://github.com/statnet/ndtv +nearfar: + version: '1.3' + title: Near-Far Matching + maintainer: Joseph Rigdon + description: Near-far matching is a study design technique for preprocessing observational + data to mimic a pair-randomized trial. Individuals are matched to be near on measured + confounders and far on levels of an instrumental variable. Methods outlined in + further detail in Rigdon, Baiocchi, and Basu (2018) . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nearfar + url_git: '' +neat: + version: 1.2.4 + title: Efficient Network Enrichment Analysis Test + maintainer: Mirko Signorelli + description: |- + Includes functions and examples to compute NEAT, the Network + Enrichment Analysis Test described in Signorelli et al. (2016, + ). + date_publication: '2024-02-01' + bug_reports: '' + url: https://mirkosignorelli.github.io/r + url_cran: https://CRAN.R-project.org/package=neat + url_git: '' +neatmaps: + version: 2.1.0 + title: Heatmaps for Multiple Network Data + maintainer: Philippe Boileau + description: |- + Simplify the exploratory data analysis process for multiple network + data sets with the help of hierarchical clustering, consensus + clustering and heatmaps. Multiple network data consists of multiple + disjoint networks that have common variables (e.g. ego networks). + This package contains the necessary tools for exploring such data, + from the data pre-processing stage to the creation of dynamic + visualizations. + date_publication: '2019-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neatmaps + url_git: https://github.com/PhilBoileau/neatmaps +neatR: + version: 0.2.0 + title: Neat Data for Presentation + maintainer: Shivaprakash Suresh + description: |- + Utilities for unambiguous, neat and legible + representation of data (date, time stamp, numbers, percentages and strings) + for presentation of analysis , aiming for elegance and consistency. + The purpose of this package is to format data, that is better + for presentation and any automation jobs that reports numbers. + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neatR + url_git: '' +neatRanges: + version: 0.1.4 + title: Tidy Up Date/Time Ranges + maintainer: Aljaz Jelenko + description: Collapse, partition, combine, fill gaps in and expand date/time ranges. + date_publication: '2022-10-18' + bug_reports: https://github.com/arg0naut91/neatRanges/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neatRanges + url_git: https://github.com/arg0naut91/neatRanges +neatStats: + version: 1.13.3 + title: Neat and Painless Statistical Reporting + maintainer: Gáspár Lukács + description: |- + User-friendly, clear and simple statistics, primarily for + publication in psychological science. The main functions are wrappers for + other packages, but there are various additions as well. Every relevant step + from data aggregation to reportable printed statistics is covered for basic + experimental designs. + date_publication: '2022-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neatStats + url_git: https://github.com/gasparl/neatstats +nebula: + version: 1.5.3 + title: |- + Negative Binomial Mixed Models Using Large-Sample Approximation + for Differential Expression Analysis of ScRNA-Seq Data + maintainer: Liang He + description: A fast negative binomial mixed model for conducting association analysis + of multi-subject single-cell data. It can be used for identifying marker genes, + differential expression and co-expression analyses. The model includes subject-level + random effects to account for the hierarchical structure in multi-subject single-cell + data. See He et al. (2021) . + date_publication: '2024-02-15' + bug_reports: https://github.com/lhe17/nebula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nebula + url_git: https://github.com/lhe17/nebula +Necklaces: + version: '1.0' + title: Necklaces and Bracelets + maintainer: Giuseppe Guarino + description: Tools to generate Necklaces, Bracelets, Lyndon words and de Bruijn + sequences. The generation relies on integer partitions and uses the 'KStatistics' + package. Methods used in the package refers to E. Di Nardo and G. Guarino (2022) + . + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Necklaces + url_git: '' +necountries: + version: 0.1-1 + title: Countries of the World + maintainer: Yves Croissant + description: |- + Based on Natural Earth , a subset of countries can + easily be selected with their administrative boundaries, joined with an external + data frame and plotted as a thematic map. + date_publication: '2024-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=necountries + url_git: '' +needmining: + version: 0.1.1 + title: A Simple Needmining Implementation + maintainer: Dorian Proksch + description: |- + Showcasing needmining (the semi-automatic extraction of customer needs from + social media data) with Twitter data. It uses the handling of the Twitter API provided by + the package 'rtweet' and the textmining algorithms provided by the package 'tm'. + Niklas Kuehl (2016) wrote an introduction to the topic of needmining. + date_publication: '2019-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=needmining + url_git: '' +needs: + version: 0.0.3 + title: Attaches and Installs Packages + maintainer: Josh Katz + description: A simple function for easier package loading and auto-installation. + date_publication: '2016-03-28' + bug_reports: https://github.com/joshkatz/needs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=needs + url_git: https://github.com/joshkatz/needs +NegativeControlOutcomeAdjustment: + version: 0.0.6 + title: Estimation of Vaccine Efficacy using Negative Control Outcomes + maintainer: Bill Wheeler + description: Methods to reduce confounding bias from unmeasured confounders in observational + studies of vaccine efficacy using negative control outcomes. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NegativeControlOutcomeAdjustment + url_git: '' +NegBinBetaBinreg: + version: '1.0' + title: Negative Binomial and Beta Binomial Bayesian Regression Models + maintainer: Edilberto Cepeda + description: The Negative Binomial regression with mean and shape modeling and mean + and variance modeling and Beta Binomial regression with mean and dispersion modeling. + date_publication: '2016-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NegBinBetaBinreg + url_git: '' +negenes: + version: 1.0-12 + title: Estimating the Number of Essential Genes in a Genome + maintainer: Karl W Broman + description: |- + Estimating the number of essential genes in a genome on + the basis of data from a random transposon mutagenesis experiment, + through the use of a Gibbs sampler. + Lamichhane et al. (2003) . + date_publication: '2019-08-05' + bug_reports: https://github.com/kbroman/negenes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=negenes + url_git: https://github.com/kbroman/negenes +negligible: + version: 0.1.9 + title: |- + A Collection of Functions for Negligible Effect/Equivalence + Testing + maintainer: Robert Cribbie + description: |- + Researchers often want to evaluate whether there is a negligible + relationship among variables. The 'negligible' package provides functions that + are useful for conducting negligible effect testing (also called + equivalence testing). For example, there are functions for evaluating the + equivalence of means or the presence of a negligible association + (correlation or regression). Beribisky, N., Mara, C., & Cribbie, R. A. (2020) . + Beribisky, N., Davidson, H., Cribbie, R. A. (2019) . + Shiskina, T., Farmus, L., & Cribbie, R. A. (2018) . + Mara, C. & Cribbie, R. A. (2017) . + Counsell, A. & Cribbie, R. A. (2015) . + van Wieringen, K. & Cribbie, R. A. (2014) . + Goertzen, J. R. & Cribbie, R. A. (2010) . + Cribbie, R. A., Gruman, J. & Arpin-Cribbie, C. (2004) . + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=negligible + url_git: '' +Neighboot: + version: 1.0.1 + title: Neighborhood Bootstrap Method for RDS + maintainer: Mamadou Yauck + description: A bootstrap method for Respondent-Driven Sampling (RDS) that relies + on the underlying structure of the RDS network to estimate uncertainty. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Neighboot + url_git: '' +neighbours: + version: 0.1-3 + title: Neighbourhood Functions for Local-Search Algorithms + maintainer: Enrico Schumann + description: |- + Neighbourhood functions are key components of + local-search algorithms such as Simulated Annealing or + Threshold Accepting. These functions take a solution and + return a slightly-modified copy of it, i.e. a neighbour. + The package provides a function neighbourfun() that + constructs such neighbourhood functions, based on + parameters such as admissible ranges for elements in a + solution. Supported are numeric and logical solutions. + The algorithms were originally created for + portfolio-optimisation applications, but can be used for + other models as well. Several recipes for neighbour + computations are taken from "Numerical Methods and + Optimization in Finance" by M. Gilli, D. Maringer and + E. Schumann (2019, ISBN:978-0128150658). + date_publication: '2023-09-21' + bug_reports: '' + url: http://enricoschumann.net/R/packages/neighbours/ + url_cran: https://CRAN.R-project.org/package=neighbours + url_git: https://github.com/enricoschumann/neighbours +neighbr: + version: 1.0.3 + title: Classification, Regression, Clustering with K Nearest Neighbors + maintainer: Dmitriy Bolotov + description: |- + Classification, regression, and clustering with k nearest neighbors + algorithm. Implements several distance and similarity measures, covering + continuous and logical features. Outputs ranked neighbors. Most features of + this package are directly based on the PMML specification for KNN. + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neighbr + url_git: '' +neldermead: + version: 1.0-12 + title: R Port of the 'Scilab' Neldermead Module + maintainer: Sebastien Bihorel + description: |- + Provides several direct search optimization algorithms based on the + simplex method. The provided algorithms are direct search algorithms, i.e. + algorithms which do not use the derivative of the cost function. They are + based on the update of a simplex. The following algorithms are available: the + fixed shape simplex method of Spendley, Hext and Himsworth (unconstrained + optimization with a fixed shape simplex, 1962) , + the variable shape simplex method of Nelder and Mead (unconstrained optimization + with a variable shape simplex made, 1965) , and + Box's complex method (constrained optimization with a variable shape simplex, + 1965) . + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neldermead + url_git: '' +nemBM: + version: 1.00.01 + title: |- + Using Network Evolution Models to Generate Networks with + Selected Blockmodel Type + maintainer: Marjan Cugmas + description: To study network evolution models and different blockmodeling approaches. + Various functions enable generating (temporal) networks with a selected blockmodel + type, taking into account selected local network mechanisms. The development of + this package is financially supported the Slovenian Research Agency (www.arrs.gov.si) + within the research program P5<96>0168 and the research project J5-2557 (Comparison + and evaluation of different approaches to blockmodeling dynamic networks by simulations + with application to Slovenian co-authorship networks). + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nemBM + url_git: '' +nemtr: + version: 0.0.1.0 + title: Nonparametric Extended Median Test - Cumulative Summation Method + maintainer: Caleb Greski + description: |- + Calculates a cumulative summation nonparametric extended + median test based on the work of Brown & Schaffer (2020) . + It then generates a control chart to assess processes and determine if any streams are out of control. + date_publication: '2023-01-18' + bug_reports: https://github.com/calebgreski/nemtr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nemtr + url_git: https://github.com/calebgreski/nemtr +neo2R: + version: 2.4.2 + title: Neo4j to R + maintainer: Patrice Godard + description: |- + The aim of neo2R is to provide simple and low level connectors + for querying neo4j graph databases (). + The objects returned by the query functions are either lists or data.frames + with very few post-processing. + It allows fast processing of queries returning many records. + And it let the user handle post-processing according to the data model + and his needs. + date_publication: '2024-01-18' + bug_reports: https://github.com/patzaw/neo2r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neo2R + url_git: https://github.com/patzaw/neo2r +neo4jshell: + version: 0.1.2 + title: Querying and Managing 'Neo4J' Databases in 'R' + maintainer: Keith McNulty + description: |- + Sends queries to a specified 'Neo4J' graph database, capturing results in a dataframe where appropriate. + Other useful functions for the importing and management of data on the 'Neo4J' server and basic local server admin. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neo4jshell + url_git: '' +neo4r: + version: 0.1.1 + title: A 'Neo4J' Driver + maintainer: Colin Fay + description: |- + A Modern and Flexible 'Neo4J' Driver, allowing you to query + data on a 'Neo4J' server and handle the results in R. It's modern in + the sense it provides a driver + that can be easily integrated in a data analysis workflow, especially by + providing an API working smoothly with other data analysis and graph + packages. It's flexible in the way it returns the results, by + trying to stay as close as + possible to the way 'Neo4J' returns data. That way, you have the control + over the way you will compute the results. At the same time, the result + is not too complex, so that the "heavy lifting" of data wrangling is not + left to the user. + date_publication: '2019-02-15' + bug_reports: https://github.com/neo4j-rstats/neo4r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neo4r + url_git: https://github.com/neo4j-rstats/neo4r +neodistr: + version: 0.1.1 + title: Neo-Normal Distribution + maintainer: Achmad Syahrul Choir + description: |- + Provides functions for calculating the + density, cumulative distribution, quantile, and random number of + neo-normal distribution. It also interfaces with the 'brms' package, + allowing the use of the neo-normal distribution as a custom family. + This integration enables the application of various 'brms' formulas + for neo-normal regression. The package implements the following + distributions: Modified to be Stable as Normal from Burr (MSNBurr), Modified to be Stable as Normal from Burr-IIa (MSNBurr-IIa), Generalized of MSNBurr (GMSNBurr), and Jones-Faddy Skew-t. + References: + Choir, A. S. (2020).Unpublished Dissertation. + Iriawan, N. (2000).Unpublished Dissertation. + Jones, M. C. and Faddy,M. J. (2003).. + Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) . + date_publication: '2024-06-26' + bug_reports: https://github.com/madsyair/neodistr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neodistr + url_git: https://github.com/madsyair/neodistr +neojags: + version: 0.1.5 + title: |- + Neo-Normal Distributions Family for Markov Chain Monte Carlo + (MCMC) Models in 'JAGS' + maintainer: Achmad Syahrul Choir + description: |- + A 'JAGS' extension module provides neo-normal distributions + family including MSNBurr, MSNBurr-IIa, GMSNBurr, Lunetta Exponential Power, + Fernandez-Steel Skew t, Fernandez-Steel Skew Normal, Fernandez-Osiewalski-Steel + Skew Exponential Power, Jones Skew Exponential Power. + References: + Choir, A. S. (2020). "The New Neo-Normal Distributions and Their Properties".Unpublished Dissertation. + Denwood, M.J. (2016) . + Fernandez, C., Osiewalski, J., & Steel, M. F. (1995) . + Fernandez, C., & Steel, M. F. (1998) . + Iriawan, N. (2000). "Computationally Intensive Approaches to Inference in NeoNormal Linear Models".Unpublished Dissertation. + Mineo, A., & Ruggieri, M. (2005) . + Rigby, R. A., & Stasinopoulos, D. M. (2005) . + Lunetta, G. (1963). "Di una Generalizzazione dello Schema della Curva Normale". + Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) . + date_publication: '2024-10-10' + bug_reports: https://github.com/madsyair/neojags/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neojags + url_git: https://github.com/madsyair/neojags +NEONiso: + version: 0.7.2 + title: Tools to Calibrate and Work with NEON Atmospheric Isotope Data + maintainer: Rich Fiorella + description: |- + Functions for downloading, + calibrating, and analyzing atmospheric isotope data bundled + into the eddy covariance data products of the National Ecological + Observatory Network (NEON) . + Calibration tools are provided for carbon and water isotope products. + Carbon isotope calibration details are found in Fiorella et al. (2021) + , and the readme + file at . Tools for calibrating water + isotope products have been added as of 0.6.0, but have known deficiencies + and should be considered experimental and unsupported. + date_publication: '2025-02-13' + bug_reports: https://github.com/lanl/NEONiso/issues + url: https://lanl.github.io/NEONiso/ + url_cran: https://CRAN.R-project.org/package=NEONiso + url_git: https://github.com/lanl/NEONiso +neonOS: + version: 1.1.0 + title: Basic Data Wrangling for NEON Observational Data + maintainer: Claire Lunch + description: |- + NEON observational data are provided via the NEON Data Portal + and NEON API, and can be downloaded and reformatted by the 'neonUtilities' package. NEON observational data + (human-observed measurements, and analyses derived from human-collected samples, such as tree diameters and + algal chemistry) are published in a format consisting of one or more tabular data files. This package provides + tools for performing common operations on NEON observational data, including checking for duplicates and + joining tables. + date_publication: '2024-06-14' + bug_reports: https://github.com/NEONScience/NEON-OS-data-processing/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neonOS + url_git: https://github.com/NEONScience/NEON-OS-data-processing +neonPlantEcology: + version: 1.6.1 + title: Process NEON Plant Data for Ecological Analysis + maintainer: Adam Mahood + description: Downloading and organizing plant presence and percent cover data from + the National Ecological Observatory Network . + date_publication: '2024-05-30' + bug_reports: https://github.com/admahood/neonPlantEcology/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neonPlantEcology + url_git: https://github.com/admahood/neonPlantEcology +neonSoilFlux: + version: 1.0.0 + title: |- + Compute Soil Carbon Fluxes for the National Ecological + Observatory Network Sites + maintainer: John Zobitz + description: Acquires and synthesizes soil carbon fluxes at sites located in the + National Ecological Observatory Network (NEON). Provides flux estimates and associated + uncertainty as well as key environmental measurements (soil water, temperature, + CO2 concentration) that are used to compute soil fluxes. + date_publication: '2024-05-25' + bug_reports: https://github.com/jmzobitz/neonSoilFlux/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neonSoilFlux + url_git: https://github.com/jmzobitz/neonSoilFlux +neonstore: + version: 0.5.1 + title: NEON Data Store + maintainer: Carl Boettiger + description: |- + The National Ecological Observatory Network (NEON) provides access + to its numerous data products through its REST API, + . This package provides a + high-level user interface for downloading and storing NEON data products. + Unlike 'neonUtilities', this package will avoid repeated downloading, + provides persistent storage, and improves performance. 'neonstore' can also + construct a local 'duckdb' database of stacked tables, making it possible + to work with tables that are far to big to fit into memory. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neonstore + url_git: '' +neonUtilities: + version: 2.4.3 + title: Utilities for Working with NEON Data + maintainer: Claire Lunch + description: |- + NEON data packages can be accessed through the NEON Data Portal + or through the NEON Data API (see for documentation). Data delivered from + the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files + can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting + data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and + converting formats. For more information, see the readme file at . + date_publication: '2024-12-05' + bug_reports: https://github.com/NEONScience/NEON-utilities/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neonUtilities + url_git: https://github.com/NEONScience/NEON-utilities +neotoma2: + version: 1.0.5 + title: Working with the Neotoma Paleoecology Database + maintainer: Dominguez Vidana Socorro + description: |- + Access and manipulation of data using the Neotoma Paleoecology Database. + . + date_publication: '2024-08-20' + bug_reports: https://github.com/NeotomaDB/neotoma2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neotoma2 + url_git: https://github.com/NeotomaDB/neotoma2 +nephro: + version: '1.5' + title: Utilities for Nephrology + maintainer: Cristian Pattaro + description: Set of functions to estimate kidney function and other traits of interest + in nephrology. + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nephro + url_git: '' +NEpiC: + version: 1.0.1 + title: |- + Network Assisted Algorithm for Epigenetic Studies Using Mean and + Variance Combined Signals + maintainer: Peifeng Ruan + description: 'Package for a Network assisted algorithm for Epigenetic studies using + mean and variance Combined signals: NEpiC. NEpiC combines both signals in mean + and variance differences in methylation level between case and control groups + searching for differentially methylated sub-networks (modules) using the protein-protein + interaction network.' + date_publication: '2016-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NEpiC + url_git: '' +neptune: + version: 0.2.3 + title: |- + MLOps Metadata Store - Experiment Tracking and Model Registry + for Production Teams + maintainer: Rafal Jankowski + description: |- + An interface to Neptune. A metadata store for MLOps, built for teams that run a lot of experiments. + It gives you a single place to log, store, display, organize, compare, and query all your model-building metadata. + Neptune is used for: + • Experiment tracking: Log, display, organize, and compare ML experiments in a single place. + • Model registry: Version, store, manage, and query trained models, and model building metadata. + • Monitoring ML runs live: Record and monitor model training, evaluation, or production runs live + For more information see . + date_publication: '2022-04-13' + bug_reports: https://github.com/neptune-ai/neptune-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neptune + url_git: https://github.com/neptune-ai/neptune-r +nesRdata: + version: 0.3.1 + title: National Eutrophication Survey Data + maintainer: Joseph Stachelek + description: Serves data from the United States Environmental Protection Agency + (USEPA) National Eutrophication Survey . + date_publication: '2020-04-30' + bug_reports: https://github.com/jsta/nesRdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nesRdata + url_git: https://github.com/jsta/nesRdata +nestcolor: + version: 0.1.3 + title: Colors for NEST Graphs + maintainer: Joe Zhu + description: |- + Clinical reporting figures require to use consistent colors + and configurations. As a part of the Roche open-source clinical + reporting project, namely the NEST project, the 'nestcolor' package + specifies the color code and default theme with specifying 'ggplot2' + theme parameters. Users can easily customize color and theme settings + before using the reset of NEST packages to ensure consistent settings + in both static and interactive output at the downstream. + date_publication: '2025-01-21' + bug_reports: https://github.com/insightsengineering/nestcolor/issues + url: https://insightsengineering.github.io/nestcolor/ + url_cran: https://CRAN.R-project.org/package=nestcolor + url_git: https://github.com/insightsengineering/nestcolor/ +NestedCategBayesImpute: + version: 1.2.1 + title: |- + Modeling, Imputing and Generating Synthetic Versions of Nested + Categorical Data in the Presence of Impossible Combinations + maintainer: Olanrewaju Akande + description: This tool set provides a set of functions to fit the nested Dirichlet + process mixture of products of multinomial distributions (NDPMPM) model for nested + categorical household data in the presence of impossible combinations. It has + direct applications in imputing missing values for and generating synthetic versions + of nested household data. + date_publication: '2019-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NestedCategBayesImpute + url_git: '' +nestedcv: + version: 0.7.12 + title: Nested Cross-Validation with 'glmnet' and 'caret' + maintainer: Myles Lewis + description: Implements nested k*l-fold cross-validation for lasso and elastic-net + regularised linear models via the 'glmnet' package and other machine learning + models via the 'caret' package . Cross-validation + of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature + selection are provided. Described as double cross-validation by Stone (1977) . + Also implemented is a method using outer CV to measure unbiased model performance + metrics when fitting Bayesian linear and logistic regression shrinkage models + using the horseshoe prior over parameters to encourage a sparse model as described + by Piironen & Vehtari (2017) . + date_publication: '2024-11-27' + bug_reports: https://github.com/myles-lewis/nestedcv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nestedcv + url_git: https://github.com/myles-lewis/nestedcv +nestedLogit: + version: 0.3.2 + title: Nested Dichotomy Logistic Regression Models + maintainer: Michael Friendly + description: |- + Provides functions for specifying and fitting nested + dichotomy logistic regression models for a multi-category response and + methods for summarising and plotting those models. Nested dichotomies are + statistically independent, and hence provide an additive decomposition + of tests for the overall 'polytomous' response. When the dichotomies + make sense substantively, this method can be a simpler alternative to + the standard 'multinomial' logistic model which compares response + categories to a reference level. See: J. Fox (2016), "Applied + Regression Analysis and Generalized Linear Models", 3rd Ed., ISBN + 1452205663. + date_publication: '2023-06-22' + bug_reports: https://github.com/friendly/nestedLogit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nestedLogit + url_git: https://github.com/friendly/nestedLogit +NestedMenu: + version: 0.2.0 + title: A Nested Menu Widget for 'Shiny' Applications + maintainer: Stéphane Laurent + description: |- + Provides a nested menu widget for usage in 'Shiny' + applications. This is useful for hierarchical choices (e.g. continent, + country, city). + date_publication: '2022-09-16' + bug_reports: https://github.com/stla/NestedMenu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NestedMenu + url_git: https://github.com/stla/NestedMenu +nestedmodels: + version: 1.1.0 + title: Tidy Modelling for Nested Data + maintainer: Ashby Thorpe + description: |- + A modelling framework for nested data using the 'tidymodels' + ecosystem. Specify how to nest data using the 'recipes' package, create + testing and training splits using 'rsample', and fit models to this data + using the 'parsnip' and 'workflows' packages. Allows any model to be fit + to nested data. + date_publication: '2023-09-30' + bug_reports: https://github.com/ashbythorpe/nestedmodels/issues + url: https://ashbythorpe.github.io/nestedmodels/ + url_cran: https://CRAN.R-project.org/package=nestedmodels + url_git: https://github.com/ashbythorpe/nestedmodels +nestedpp: + version: 0.2.0 + title: Performance Profiles and Nested Performance Profiles + maintainer: Brais Gonzalez-Rodriguez + description: Library to plot performance profiles (Dolan and More (2002) ) + and nested performance profiles (Hekmati and Mirhajianmoghadam (2019) ) + for a given data frame. + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nestedpp + url_git: '' +nestfs: + version: 1.0.3 + title: Cross-Validated (Nested) Forward Selection + maintainer: Marco Colombo + description: |- + Implementation of forward selection based on cross-validated + linear and logistic regression. + date_publication: '2022-12-13' + bug_reports: https://github.com/mcol/nestfs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nestfs + url_git: https://github.com/mcol/nestfs +NestMRMC: + version: '1.0' + title: Single Reader Between-Cases AUC Estimator in Nested Data + maintainer: Hongfei Du + description: This R package provides a calculation of between-cases AUC estimate, + corresponding covariance, and variance estimate in the nested data problem. Also, + the package has the function to simulate the nested data. The calculated between-cases + AUC estimate is used to evaluate the reader's diagnostic performance in clinical + tasks with nested data. For more details on the above methods, please refer to + the paper by H Du, S Wen, Y Guo, F Jin, BD Gallas (2022) . + date_publication: '2022-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NestMRMC + url_git: '' +nestr: + version: 0.1.2 + title: Build Nesting or Hierarchical Structures + maintainer: Emi Tanaka + description: Facilitates building a nesting or hierarchical structure as a list + or data frame by using a human friendly syntax. + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nestr + url_git: '' +net4pg: + version: 0.1.1 + title: |- + Handle Ambiguity of Protein Identifications from Shotgun + Proteomics + maintainer: Laura Fancello + description: |- + In shotgun proteomics, shared peptides (i.e., peptides that might + originate from different proteins sharing homology, from different + proteoforms due to alternative mRNA splicing, post-translational + modifications, proteolytic cleavages, and/or allelic variants) represent a + major source of ambiguity in protein identifications. The 'net4pg' package + allows to assess and handle ambiguity of protein identifications. It + implements methods for two main applications. First, it allows to represent + and quantify ambiguity of protein identifications by means of graph + connected components (CCs). In graph theory, CCs are defined as the largest + subgraphs in which any two vertices are connected to each other by a path + and not connected to any other of the vertices in the supergraph. Here, + proteins sharing one or more peptides are thus gathered in the same CC + (multi-protein CC), while unambiguous protein identifications constitute CCs + with a single protein vertex (single-protein CCs). Therefore, the proportion + of single-protein CCs and the size of multi-protein CCs can be used to + measure the level of ambiguity of protein identifications. The package + implements a strategy to efficiently calculate graph connected + components on large datasets and allows to visually inspect them. + Secondly, the 'net4pg' package allows to exploit the increasing + availability of matched transcriptomic and proteomic datasets to + reduce ambiguity of protein identifications. More precisely, it + implement a transcriptome-based filtering strategy fundamentally + consisting in the removal of those proteins whose corresponding + transcript is not expressed in the sample-matched transcriptome. The + underlying assumption is that, according to the central dogma of + biology, there can be no proteins without the corresponding + transcript. Most importantly, the package allows to visually inspect + the effect of the filtering on protein identifications and quantify + ambiguity before and after filtering by means of graph connected + components. As such, it constitutes a reproducible and transparent + method to exploit transcriptome information to enhance protein + identifications. All methods implemented in the 'net4pg' package are fully + described in Fancello and Burger (2022) . + date_publication: '2022-09-07' + bug_reports: https://github.com/laurafancello/net4pg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=net4pg + url_git: https://github.com/laurafancello/net4pg +netassoc: + version: 0.7.0 + title: Inference of Species Associations from Co-Occurrence Data + maintainer: Benjamin Blonder + description: Infers species associations from community matrices. Uses local and + (optional) regional-scale co-occurrence data by comparing observed partial correlation + coefficients between species to those estimated from regional species distributions. + Extends Gaussian graphical models to a null modeling framework. Provides interface + to a variety of inverse covariance matrix estimation methods. + date_publication: '2022-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netassoc + url_git: '' +netClust: + version: 1.0.1 + title: Model-Based Clustering of Network Data + maintainer: Shuchismita Sarkar + description: Clustering unilayer and multilayer network data by means of finite + mixtures is the main utility of 'netClust'. + date_publication: '2020-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netClust + url_git: '' +NetCluster: + version: '0.2' + title: Clustering for networks + maintainer: Sean J Westwood + description: |- + Facilitates network clustering and evaluation of cluster + configurations. + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetCluster + url_git: '' +netcmc: + version: 1.0.2 + title: |- + Spatio-Network Generalised Linear Mixed Models for Areal Unit + and Network Data + maintainer: George Gerogiannis + description: Implements a class of univariate and multivariate spatio-network generalised + linear mixed models for areal unit and network data, with inference in a Bayesian + setting using Markov chain Monte Carlo (MCMC) simulation. The response variable + can be binomial, Gaussian, or Poisson. Spatial autocorrelation is modelled by + a set of random effects that are assigned a conditional autoregressive (CAR) prior + distribution following the Leroux model (Leroux et al. (2000) ). + Network structures are modelled by a set of random effects that reflect a multiple + membership structure (Browne et al. (2001) ). + date_publication: '2022-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netcmc + url_git: '' +netCoin: + version: 2.1.0 + title: Interactive Analytic Networks + maintainer: Modesto Escobar + description: Create interactive analytic networks. It joins the data analysis power + of R to obtain coincidences, co-occurrences and correlations, and the visualization + libraries of 'JavaScript' in one package. + date_publication: '2025-01-15' + bug_reports: https://github.com/Modesto-Escobar/netCoin-2.x/issues + url: https://modesto-escobar.github.io/netCoin-2.x/ + url_cran: https://CRAN.R-project.org/package=netCoin + url_git: '' +netcom: + version: 2.1.7 + title: NETwork COMparison Inference + maintainer: Ryan Langendorf + description: Infer system functioning with empirical NETwork COMparisons. These + methods are part of a growing paradigm in network science that uses relative comparisons + of networks to infer mechanistic classifications and predict systemic interventions. + They have been developed and applied in Langendorf and Burgess (2021) , + Langendorf (2020) , and Langendorf and Goldberg (2019) + . + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netcom + url_git: https://github.com/langendorfr/netcom +netcontrol: + version: '0.1' + title: Control Theory Methods for Networks + maintainer: Teague R. Henry + description: |- + Implementations of various control theory methods for use + in brain and psychological networks. Contains controllability + statistics from Pasqualetti, Zampieri & Bullo (2014) , + optimal control algorithms from Lewis, Vrabie & Syrmos (2012, ISBN:978-0-470-63349-6), and various utilities. + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netcontrol + url_git: '' +NetCoupler: + version: 0.1.0 + title: |- + Inference of Causal Links Between a Network and an External + Variable + maintainer: Luke Johnston + description: |- + The 'NetCoupler' algorithm identifies potential direct effects of + correlated, high-dimensional variables formed as a network with an external + variable. The external variable may act as the dependent/response variable + or as an independent/predictor variable to the network. + date_publication: '2022-04-08' + bug_reports: https://github.com/NetCoupler/NetCoupler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NetCoupler + url_git: https://github.com/NetCoupler/NetCoupler +NetDA: + version: 0.2.0 + title: |- + Network-Based Discriminant Analysis Subject to Multi-Label + Classes + maintainer: Li-Pang Chen + description: Implementation of discriminant analysis with network structures in + predictors accommodated to do classification and prediction. + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetDA + url_git: '' +netdiffuseR: + version: 1.22.6 + title: Analysis of Diffusion and Contagion Processes on Networks + maintainer: George Vega Yon + description: |- + Empirical statistical analysis, visualization and simulation of + diffusion and contagion processes on networks. The package implements algorithms + for calculating network diffusion statistics such as transmission rate, hazard + rates, exposure models, network threshold levels, infectiousness (contagion), + and susceptibility. The package is inspired by work published in Valente, + et al., (2015) ; Valente (1995) , Myers (2000) , Iyengar and others (2011) + , Burt (1987) ; among others. + date_publication: '2023-08-30' + bug_reports: https://github.com/USCCANA/netdiffuseR/issues + url: https://USCCANA.github.io/netdiffuseR/ + url_cran: https://CRAN.R-project.org/package=netdiffuseR + url_git: https://github.com/USCCANA/netdiffuseR +NetExplorer: + version: 0.0.2 + title: Network Explorer + maintainer: Sosa Sebastian + description: Social network analysis has become an essential tool in the study of + complex systems. 'NetExplorer' allows to visualize and explore complex systems. + It is based on 'd3js' library that brings 1) Graphical user interface; 2) Circular, + linear, multilayer and force Layout; 3) Network live exploration and 4) SVG exportation. + date_publication: '2021-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetExplorer + url_git: '' +NetFACS: + version: 0.5.0 + title: Network Applications to Facial Communication Data + maintainer: Alan V. Rincon + description: |- + Functions to analyze and visualize communication data, + based on network theory and resampling methods. + Farine, D. R. (2017) ; + Carsey, T., & Harden, J. (2014) . + Primarily targeted at datasets of facial expressions coded with the Facial Action Coding System. + Ekman, P., Friesen, W. V., & Hager, J. C. (2002). "Facial action coding system - investigator's guide" . + date_publication: '2022-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetFACS + url_git: '' +netgsa: + version: 4.0.5 + title: Network-Based Gene Set Analysis + maintainer: Michael Hellstern + description: Carry out network-based gene set analysis by incorporating external + information about interactions among genes, as well as novel interactions learned + from data. Implements methods described in Shojaie A, Michailidis G (2010) , + Shojaie A, Michailidis G (2009) , and Ma J, Shojaie + A, Michailidis G (2016) . + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netgsa + url_git: https://github.com/mikehellstern/netgsa +netgwas: + version: 1.14.3 + title: Network-Based Genome Wide Association Studies + maintainer: Pariya Behrouzi + description: |- + A multi-core R package that contains a set of tools based on copula graphical + models for accomplishing the three interrelated goals in genetics and genomics in an + unified way: (1) linkage map construction, (2) constructing linkage disequilibrium + networks, and (3) exploring high-dimensional genotype-phenotype network and genotype- + phenotype-environment interactions networks. + The 'netgwas' package can deal with biparental inbreeding and outbreeding species with + any ploidy level, namely diploid (2 sets of chromosomes), triploid (3 sets of chromosomes), + tetraploid (4 sets of chromosomes) and so on. We target on high-dimensional data where + number of variables p is considerably larger than number of sample sizes (p >> n). + The computations is memory-optimized using the sparse matrix output. The 'netgwas' + implements the methodological developments in Behrouzi and Wit (2017) + and Behrouzi and Wit (2017) . + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netgwas + url_git: '' +netie: + version: '1.0' + title: Antigen T Cell Interaction Estimation + maintainer: Tianshi Lu + description: The Bayesian hierarchical model named antigen-T cell interaction estimation + is to estimate the history of the immune pressure on the evolution of the tumor + clones.The model is based on the estimation result from Andrew Roth (2014) . + date_publication: '2021-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netie + url_git: '' +NetIndices: + version: 1.4.4.1 + title: |- + Estimating Network Indices, Including Trophic Structure of + Foodwebs in R + maintainer: Karline Soetaert + description: 'Given a network (e.g. a food web), estimates several network indices. + These include: Ascendency network indices, Direct and indirect dependencies, Effective + measures, Environ network indices, General network indices, Pathway analysis, + Network uncertainty indices and constraint efficiencies and the trophic level + and omnivory indices of food webs.' + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetIndices + url_git: '' +NetInt: + version: 1.0.0 + title: Methods for Unweighted and Weighted Network Integration + maintainer: Jessica Gliozzo + description: |- + Implementation of network integration approaches + comprising unweighted and weighted integration methods. Unweighted integration + is performed considering the average, per-edge average, maximum and minimum of + networks edges. Weighted integration takes into account a weight for each + network during the fusion process, where the weights express + the ''predictiveness strength'' of each network considering a specific predictive + task. Weights can be learned using a machine learning algorithm able to associate + the weights to the assessment of the accuracy of the learning algorithm + trained on the network itself. The implemented methods can be applied to + effectively integrate different biological networks modelling a wide range + of problems in bioinformatics (e.g. disease gene prioritization, protein + function prediction, drug repurposing, clinical outcome prediction). + date_publication: '2022-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetInt + url_git: '' +netknitr: + version: 0.2.1 + title: Knit Network Map for any Dataset + maintainer: Jayachandra N + description: Designed to create interactive and visually compelling network maps + using R Shiny. It allows users to quickly analyze CSV files and visualize complex + relationships, structures, and connections within data by leveraging powerful + network analysis libraries and dynamic web interfaces. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netknitr + url_git: '' +NetLogoR: + version: 1.0.5 + title: Build and Run Spatially Explicit Agent-Based Models + maintainer: Eliot J B McIntire + description: |- + Build and run spatially explicit + agent-based models using only the R platform. 'NetLogoR' follows the same + framework as the 'NetLogo' software + (Wilensky (1999) ) and is a translation + in R of the structure and functions of 'NetLogo'. + 'NetLogoR' provides new R classes to define model agents and functions to + implement spatially explicit agent-based models in the R environment. + This package allows benefiting of the fast and easy coding phase from the + highly developed 'NetLogo' framework, coupled with the versatility, power + and massive resources of the R software. + Examples of two models from the NetLogo software repository + (Ants ) and + Wolf-Sheep-Predation + (), + and a third, Butterfly, from + Railsback and Grimm (2012) , all + written using 'NetLogoR' are available. + The 'NetLogo' code of the original version of these + models is provided alongside. + A programming guide inspired from the 'NetLogo' Programming Guide + () and a dictionary + of 'NetLogo' primitives () + equivalences are also available. + NOTE: To increment 'time', these functions can use a for loop or can be + integrated with a discrete event simulator, such as 'SpaDES' + (). + The suggested package 'fastshp' can be installed with + 'install.packages("fastshp", repos = (""), type = "source")'. + date_publication: '2024-01-08' + bug_reports: https://github.com/PredictiveEcology/NetLogoR/issues + url: https://netlogor.predictiveecology.org + url_cran: https://CRAN.R-project.org/package=NetLogoR + url_git: https://github.com/PredictiveEcology/NetLogoR/ +netmap: + version: 0.1.4 + title: Represent Network Objects on a Map + maintainer: Matteo Dimai + description: Represent 'network' or 'igraph' objects whose vertices can be represented + by features in an 'sf' object as a network graph surmising a 'sf' plot. Fits into + 'ggplot2' grammar. + date_publication: '2024-02-26' + bug_reports: https://github.com/artod83/netmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=netmap + url_git: https://github.com/artod83/netmap +netmediate: + version: 1.0.1 + title: Micro-Macro Analysis for Social Networks + maintainer: Scott Duxbury + description: |- + Estimates micro effects on macro structures (MEMS) and average micro mediated effects (AMME). + URL: . + BugReports: . + Robins, Garry, Phillipa Pattison, and Jodie Woolcock (2005) . + Snijders, Tom A. B., and Christian E. G. Steglich (2015) . + Imai, Kosuke, Luke Keele, and Dustin Tingley (2010) . + Duxbury, Scott (2023) . + Duxbury, Scott (2024) . + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netmediate + url_git: '' +netmeta: + version: 3.1-1 + title: Network Meta-Analysis using Frequentist Methods + maintainer: Guido Schwarzer + description: |- + A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) and supporting Schwarzer et al. (2015) , Chapter 8 "Network Meta-Analysis": + - frequentist network meta-analysis following Rücker (2012) ; + - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) ; + - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) , or penalised logistic regression (Evrenoglou et al., 2022) ; + - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) ; + - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) ; + - split direct and indirect evidence to check consistency (Dias et al., 2010) , (Efthimiou et al., 2019) ; + - league table with network meta-analysis results; + - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) ; + - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) ; + - measures characterizing the flow of evidence between two treatments by König et al. (2013) ; + - automated drawing of network graphs described in Rücker & Schwarzer (2016) ; + - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) ; (Rücker & Schwarzer, 2017) ; + - contribution matrix as described in Papakonstantinou et al. (2018) and Davies et al. (2022) ; + - subgroup network meta-analysis. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netmeta + url_git: https://github.com/guido-s/netmeta +netmhc2pan: + version: 1.3.2 + title: Interface to 'NetMHCIIpan' + maintainer: Richèl J.C. Bilderbeek + description: |- + The field of immunology benefits from software that can + predict which peptide sequences trigger an immune response. + 'NetMHCIIpan' is a such a tool: it predicts the + binding strength of a short peptide to a Major Histocompatibility + Complex class II (MHC-II) molecule. + 'NetMHCIIpan' can be used from a web server at + + or from the command-line, using a local installation. This package + allows to call 'NetMHCIIpan' from R. + date_publication: '2023-11-08' + bug_reports: https://github.com/richelbilderbeek/netmhc2pan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=netmhc2pan + url_git: https://github.com/richelbilderbeek/netmhc2pan/ +NetMix: + version: 0.2.0.2 + title: Dynamic Mixed-Membership Network Regression Model + maintainer: Santiago Olivella + description: |- + Stochastic collapsed variational inference on mixed-membership stochastic blockmodel for networks, + incorporating node-level predictors of mixed-membership vectors, as well as + dyad-level predictors. For networks observed over time, the model defines a hidden + Markov process that allows the effects of node-level predictors to evolve in discrete, + historical periods. In addition, the package offers a variety of utilities for + exploring results of estimation, including tools for conducting posterior + predictive checks of goodness-of-fit and several plotting functions. The package + implements methods described in Olivella, Pratt and Imai (2019) 'Dynamic Stochastic + Blockmodel Regression for Social Networks: Application to International Conflicts', + available at . + date_publication: '2023-12-13' + bug_reports: https://github.com/solivella/NetMix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NetMix + url_git: '' +NetOrigin: + version: 1.1-6 + title: Origin Estimation for Propagation Processes on Complex Networks + maintainer: Juliane Manitz + description: 'Performs network-based source estimation. Different approaches are + available: effective distance median, recursive backtracking, and centrality-based + source estimation. Additionally, we provide public transportation network data + as well as methods for data preparation, source estimation performance analysis + and visualization.' + date_publication: '2023-09-04' + bug_reports: https://github.com/jmanitz/NetOrigin/issues + url: https://netorigin.manitz.org/ + url_cran: https://CRAN.R-project.org/package=NetOrigin + url_git: '' +netplot: + version: 0.3-0 + title: Beautiful Graph Drawing + maintainer: George Vega Yon + description: |- + A graph visualization engine that emphasizes on + aesthetics at the same time providing default parameters that yield + out-of-the-box-nice visualizations. The package is built on top of + 'The Grid Graphics Package' and seamlessly work with 'igraph' and + 'network' objects. + date_publication: '2024-06-30' + bug_reports: https://github.com/USCCANA/netplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=netplot + url_git: https://github.com/USCCANA/netplot +NetPreProc: + version: '1.2' + title: Network Pre-Processing and Normalization + maintainer: Giorgio Valentini + description: Network Pre-Processing and normalization. Methods for normalizing graphs, + including Chua normalization, Laplacian normalization, Binary magnification, min-max + normalization and others. Methods to sparsify adjacency matrices. Methods for + graph pre-processing and for filtering edges of the graph. + date_publication: '2022-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetPreProc + url_git: '' +netrankr: + version: 1.2.4 + title: Analyzing Partial Rankings in Networks + maintainer: David Schoch + description: |- + Implements methods for centrality related analyses of networks. + While the package includes the possibility to build more than 20 indices, + its main focus lies on index-free assessment of centrality via partial + rankings obtained by neighborhood-inclusion or positional dominance. These + partial rankings can be analyzed with different methods, including + probabilistic methods like computing expected node ranks and relative + rank probabilities (how likely is it that a node is more central than another?). + The methodology is described in depth in the vignettes and in + Schoch (2018) . + date_publication: '2025-02-05' + bug_reports: https://github.com/schochastics/netrankr/issues + url: https://schochastics.github.io/netrankr/ + url_cran: https://CRAN.R-project.org/package=netrankr + url_git: https://github.com/schochastics/netrankr/ +netregR: + version: 1.0.1 + title: Regression of Network Responses + maintainer: Frank W. Marrs + description: Regress network responses (both directed and undirected) onto covariates + of interest that may be actor-, relation-, or network-valued. In addition, compute + principled variance estimates of the coefficients assuming that the errors are + jointly exchangeable. Missing data is accommodated. Additionally implements building + and inversion of covariance matrices under joint exchangeability, and generates + random covariance matrices from this class. For more detail on methods, see Marrs, + Fosdick, and McCormick (2017) . + date_publication: '2018-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netregR + url_git: '' +NetRep: + version: 1.2.7 + title: Permutation Testing Network Module Preservation Across Datasets + maintainer: Scott Ritchie + description: |- + Functions for assessing the replication/preservation of a network + module's topology across datasets through permutation testing; Ritchie et al. + (2015) . + date_publication: '2023-08-19' + bug_reports: https://github.com/sritchie73/NetRep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NetRep + url_git: '' +netropy: + version: 0.2.0 + title: Statistical Entropy Analysis of Network Data + maintainer: Termeh Shafie + description: Statistical entropy analysis of network data as introduced by Frank + and Shafie (2016) , and a in textbook which is in + progress. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netropy + url_git: https://github.com/termehs/netropy +nets: + version: 0.9.1 + title: Network Estimation for Time Series + maintainer: Christian Brownlees + description: Sparse VAR estimation based on LASSO. + date_publication: '2020-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nets + url_git: https://github.com/ctbrownlees/R-Package-nets +NetSci: + version: 1.0.1 + title: |- + Calculates Basic Network Measures Commonly Used in Network + Medicine + maintainer: Deisy Morselli Gysi + description: Calculates network measures commonly used in Network Medicine. Measures + such as the Largest Connected Component, the Relative Largest Connected Component, + Proximity and Separation are calculated along with their statistical significance. + Significance can be computed both using a degree-preserving randomization and + non-degree preserving. + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetSci + url_git: '' +netseer: + version: 0.1.1 + title: Graph Prediction from a Graph Time Series + maintainer: Sevvandi Kandanaarachchi + description: |- + Predicting the structure of a graph including new nodes and edges using + a time series of graphs. Flux balance analysis, a linear and integer programming + technique used in biochemistry is used with time series prediction methods to + predict the graph structure at a future time point + Kandanaarachchi (2024) . + date_publication: '2024-11-12' + bug_reports: '' + url: https://sevvandi.github.io/netseer/ + url_cran: https://CRAN.R-project.org/package=netseer + url_git: '' +netseg: + version: 1.0-2 + title: Measures of Network Segregation and Homophily + maintainer: Michal Bojanowski + description: |- + Segregation is a network-level property such that edges between + predefined groups of vertices are relatively less likely. Network homophily + is a individual-level tendency to form relations with people who are similar + on some attribute (e.g. gender, music taste, social status, etc.). In general + homophily leads to segregation, but segregation might arise without + homophily. This package implements descriptive indices measuring + homophily/segregation. It is a computational companion + to Bojanowski & Corten (2014) . + date_publication: '2023-07-01' + bug_reports: https://github.com/mbojan/netseg/issues + url: https://mbojan.github.io/netseg/ + url_cran: https://CRAN.R-project.org/package=netseg + url_git: '' +netSEM: + version: 0.6.2 + title: Network Structural Equation Modeling + maintainer: Laura S. Bruckman + description: |- + The network structural equation modeling conducts a network + statistical analysis on a data frame of coincident observations of + multiple continuous variables [1]. + It builds a pathway model by exploring a pool of domain knowledge guided + candidate statistical relationships between each of the variable pairs, + selecting the 'best fit' on the basis of a specific criteria such as + adjusted r-squared value. + This material is based upon work supported by the U.S. National Science + Foundation Award EEC-2052776 and EEC-2052662 for the MDS-Rely IUCRC Center, + under the NSF Solicitation: + NSF 20-570 Industry-University Cooperative Research Centers Program + [1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang, + Carl K. Wang, Ivan Chou, Jiayang Sun, and Roger H. French. (2013) + . + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netSEM + url_git: '' +netShiny: + version: '1.0' + title: Tool for Comparison and Visualization of Multiple Networks + maintainer: Pariya Behrouzi + description: We developed a comprehensive tool that helps with visualization and + analysis of networks with the same variables across multiple factor levels. The + 'netShiny' contains most of the popular network features such as centrality measures, + modularity, and other summary statistics (e.g. clustering coefficient). It also + contains known tools to look at the (dis)similarities between two networks, such + as pairwise distance measures between networks, set operations on the nodes of + the networks, distribution of the weights of the edges and a network representing + the difference between two correlation matrices. The package 'netShiny' also contains + tools to perform bootstrapping and find clusters in networks. See the 'netShiny' + manual for more information, documentation and examples. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=netShiny + url_git: '' +NetSimR: + version: 0.1.5 + title: Actuarial Functions for Non-Life Insurance Modelling + maintainer: Yiannis Parizas + description: |- + Assists actuaries and other insurance modellers in pricing, + reserving and capital modelling for non-life insurance and + reinsurance modelling. Provides functions that help model + excess levels, capping and pure Incurred but not reported + claims (pure IBNR). + Includes capped mean, exposure curves and increased limit + factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced + LogNormal-Pareto and Sliced Gamma-Pareto distributions. + Includes mean, probability density function (pdf), cumulative + probability function (cdf) and inverse cumulative probability + function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto + distributions. + Includes calculating pure IBNR exposure with LogNormal and + Gamma distribution for reporting delay. + Includes three shiny tools, one to simulate insurance claims applying + reinsurance structures, fit generalised linear models and fit claims + frequency or severity distributions. + Methods used in the package refer to + Free for All by Yiannis Parizas (2023) ; + Escaping the triangle by Yiannis Parizas (2019) ; + Take to excess by Yiannis Parizas (2019) . + date_publication: '2023-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetSimR + url_git: '' +netstat: + version: 0.1.2 + title: Retrieve Network Statistics Including Available TCP Ports + maintainer: Steve Condylios + description: |- + R interface for the 'netstat' command line utility used to retrieve and parse + commonly used network statistics, including available and in-use + transmission control protocol (TCP) ports. Primers offering technical background information + on the 'netstat' command line utility are available in the "Linux System Administrator's Manual" + by Michael Kerrisk (2014) + , and on the Microsoft website (2017) + . + date_publication: '2022-08-28' + bug_reports: https://github.com/stevecondylios/netstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=netstat + url_git: https://github.com/stevecondylios/netstat +nett: + version: 1.0.0 + title: Network Analysis and Community Detection + maintainer: Arash A. Amini + description: |- + Features tools for the network data analysis and community detection. + Provides multiple methods for fitting, model selection and goodness-of-fit testing in degree-corrected stochastic blocks models. + Most of the computations are fast and scalable for sparse networks, esp. for Poisson versions of the models. + Implements the following: + Amini, Chen, Bickel and Levina (2013) + Bickel and Sarkar (2015) + Lei (2016) + Wang and Bickel (2017) + Zhang and Amini (2020) + Le and Levina (2022) . + date_publication: '2022-11-09' + bug_reports: https://github.com/aaamini/nett/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nett + url_git: https://github.com/aaamini/nett +nettskjemar: + version: 0.1.4 + title: Connect to the 'nettskjema.no' API of the University of Oslo + maintainer: Athanasia Mo Mowinckel + description: |- + Enables users to retrieve data, meta-data, and codebooks + from . The data from the API is richer than from the + online data portal. Mowinckel (2021) . + date_publication: '2021-05-20' + bug_reports: https://github.com/LCBC-UiO/nettskjemar/issues + url: https://zenodo.org/badge/latestdoi/206264675 + url_cran: https://CRAN.R-project.org/package=nettskjemar + url_git: https://github.com/LCBC-UiO/nettskjemar +netUtils: + version: 0.8.3 + title: A Collection of Tools for Network Analysis + maintainer: David Schoch + description: Provides a collection of network analytic (convenience) functions which + are missing in other standard packages. This includes triad census with attributes + , core-periphery models , + and several graph generators. Most functions are build upon 'igraph'. + date_publication: '2024-10-10' + bug_reports: https://github.com/schochastics/netUtils/issues + url: https://schochastics.github.io/netUtils/ + url_cran: https://CRAN.R-project.org/package=netUtils + url_git: https://github.com/schochastics/netUtils/ +NetWeaver: + version: 0.0.6 + title: |- + Graphic Presentation of Complex Genomic and Network Data + Analysis + maintainer: Minghui Wang + description: Implements various simple function utilities and flexible pipelines + to generate circular images for visualizing complex genomic and network data analysis + features. + date_publication: '2019-02-26' + bug_reports: https://github.com/mw201608/NetWeaver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NetWeaver + url_git: https://github.com/mw201608/NetWeaver/ +network: + version: 1.19.0 + title: Classes for Relational Data + maintainer: Carter T. Butts + description: Tools to create and modify network objects. The network class can + represent a range of relational data types, and supports arbitrary vertex/edge/graph + attributes. + date_publication: '2024-12-09' + bug_reports: '' + url: https://statnet.org/ + url_cran: https://CRAN.R-project.org/package=network + url_git: '' +networkABC: + version: 0.8-1 + title: |- + Network Reverse Engineering with Approximate Bayesian + Computation + maintainer: Frederic Bertrand + description: We developed an inference tool based on approximate Bayesian computation + to decipher network data and assess the strength of the inferred links between + network's actors. It is a new multi-level approximate Bayesian computation (ABC) + approach. At the first level, the method captures the global properties of the + network, such as a scale-free structure and clustering coefficients, whereas the + second level is targeted to capture local properties, including the probability + of each couple of genes being linked. Up to now, Approximate Bayesian Computation + (ABC) algorithms have been scarcely used in that setting and, due to the computational + overhead, their application was limited to a small number of genes. On the contrary, + our algorithm was made to cope with that issue and has low computational cost. + It can be used, for instance, for elucidating gene regulatory network, which is + an important step towards understanding the normal cell physiology and complex + pathological phenotype. Reverse-engineering consists in using gene expressions + over time or over different experimental conditions to discover the structure + of the gene network in a targeted cellular process. The fact that gene expression + data are usually noisy, highly correlated, and have high dimensionality explains + the need for specific statistical methods to reverse engineer the underlying network. + date_publication: '2022-10-19' + bug_reports: https://github.com/fbertran/networkABC/issues/ + url: https://fbertran.github.io/networkABC/ + url_cran: https://CRAN.R-project.org/package=networkABC + url_git: https://github.com/fbertran/networkABC/ +NetworkChange: + version: '0.8' + title: Bayesian Package for Network Changepoint Analysis + maintainer: Jong Hee Park + description: Network changepoint analysis for undirected network data. The package + implements a hidden Markov network change point model (Park and Sohn (2020)). + Functions for break number detection using the approximate marginal likelihood + and WAIC are also provided. + date_publication: '2022-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkChange + url_git: https://github.com/jongheepark/NetworkChange +NetworkComparisonTest: + version: 2.2.2 + title: |- + Statistical Comparison of Two Networks Based on Several + Invariance Measures + maintainer: Don van den Bergh + description: |- + This permutation based hypothesis test, suited for several types of data + supported by the estimateNetwork function of the bootnet package (Epskamp & Fried, 2018), + assesses the difference between two networks based on several invariance measures (network + structure invariance, global strength invariance, edge invariance, several centrality + measures, etc.). Network structures are estimated with l1-regularization. The Network + Comparison Test is suited for comparison of independent (e.g., two different groups) and + dependent samples (e.g., one group that is measured twice). See van Borkulo et al. (2021), + available from . + date_publication: '2023-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkComparisonTest + url_git: '' +NetworkComparr: + version: 0.0.0.9 + title: Statistical Comparison of Networks + maintainer: Lara Trani + description: 'A permutation-based hypothesis test for statistical comparison of + two networks based on the invariance measures of the R package ''NetworkComparisonTest'' + by van Borkulo et al. (2022), : network structure invariance, + global strength invariance, edge invariance, and various centrality measures. + Edgelists from dependent or independent samples are used as input. These edgelists + are generated from concept maps and summed into two comparable group networks. + The networks can be directed or undirected.' + date_publication: '2023-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkComparr + url_git: '' +networkD3: + version: '0.4' + title: D3 JavaScript Network Graphs from R + maintainer: Christopher Gandrud + description: |- + Creates 'D3' 'JavaScript' network, tree, dendrogram, and Sankey + graphs from 'R'. + date_publication: '2017-03-18' + bug_reports: https://github.com/christophergandrud/networkD3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=networkD3 + url_git: '' +NetworkDistance: + version: 0.3.4 + title: Distance Measures for Networks + maintainer: Kisung You + description: Network is a prevalent form of data structure in many fields. As an + object of analysis, many distance or metric measures have been proposed to define + the concept of similarity between two networks. We provide a number of distance + measures for networks. See Jurman et al (2011) + for an overview on spectral class of inter-graph distance measures. + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkDistance + url_git: '' +networkDynamic: + version: 0.11.5 + title: Dynamic Extensions for Network Objects + maintainer: Skye Bender-deMoll + description: Simple interface routines to facilitate the handling of network objects + with complex intertemporal data. This is a part of the "statnet" suite of packages + for network analysis. + date_publication: '2024-11-22' + bug_reports: '' + url: https://statnet.org/ + url_cran: https://CRAN.R-project.org/package=networkDynamic + url_git: '' +networkDynamicData: + version: 0.2.1 + title: Dynamic (Longitudinal) Network Datasets + maintainer: Skye Bender-deMoll + description: A collection of dynamic network data sets from various sources and + multiple authors represented as 'networkDynamic'-formatted objects. + date_publication: '2016-01-12' + bug_reports: '' + url: http://statnet.org + url_cran: https://CRAN.R-project.org/package=networkDynamicData + url_git: '' +NetworkExtinction: + version: 1.0.3 + title: Extinction Simulation in Ecological Networks + maintainer: Derek Corcoran + description: |- + Simulates the extinction of species in ecological networks and it analyzes + its cascading effects, described in Dunne et al. (2002) . + date_publication: '2023-03-31' + bug_reports: '' + url: https://derek-corcoran-barrios.github.io/NetworkExtinction/ + url_cran: https://CRAN.R-project.org/package=NetworkExtinction + url_git: '' +networkGen: + version: 0.1.1 + title: Network Maze Generator + maintainer: Bao Sheng Loe (Aiden) + description: A network Maze generator that creates different types of network mazes. + date_publication: '2017-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=networkGen + url_git: '' +NetworkInference: + version: 1.2.4 + title: Inferring Latent Diffusion Networks + maintainer: Fridolin Linder + description: This is an R implementation of the netinf algorithm (Gomez Rodriguez, + Leskovec, and Krause, 2010). Given a set of events + that spread between a set of nodes the algorithm infers the most likely stable + diffusion network that is underlying the diffusion process. + date_publication: '2019-02-28' + bug_reports: https://github.com/desmarais-lab/NetworkInference/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkInference + url_git: '' +networkLite: + version: 1.1.0 + title: |- + An Simplified Implementation of the 'network' Package + Functionality + maintainer: Samuel Jenness + description: |- + An implementation of some of the core 'network' package functionality based on a + simplified data structure that is faster in many research applications. This package is designed + for back-end use in the 'statnet' family of packages, including 'EpiModel'. Support is provided for + binary and weighted, directed and undirected, bipartite and unipartite networks; no current + support for multigraphs, hypergraphs, or loops. + date_publication: '2025-01-08' + bug_reports: https://github.com/EpiModel/networkLite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=networkLite + url_git: https://github.com/EpiModel/networkLite/ +networkR: + version: 0.1.2 + title: Network Analysis and Visualization + maintainer: Claus Thorn Ekstrøm + description: |- + Collection of functions for fast manipulation, handling, and analysis of large-scale + networks based on family and social data. Functions are utility functions used to manipulate data + in three "formats": sparse adjacency matrices, pedigree trio family data, and pedigree family data. + When possible, the functions should be able to handle millions of data points quickly for use in combination + with data from large public national registers and databases. + Kenneth Lange (2003, ISBN:978-8181281135). + date_publication: '2019-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=networkR + url_git: '' +NetworkReg: + version: '2.0' + title: |- + Generalized Linear Regression Models on Network-Linked Data with + Statistical Inference + maintainer: Jianxiang Wang + description: Linear regression model and generalized linear models with nonparametric + network effects on network-linked observations. The model is originally proposed + by Le and Li (2022) and is assumed on observations + that are connected by a network or similar relational data structure. A more recent + work by Wang, Le and Li (2024) further extends + the framework to generalized linear models. All these models are implemented in + the current package. The model does not assume that the relational data or network + structure to be precisely observed; thus, the method is provably robust to a certain + level of perturbation of the network structure. The package contains the estimation + and inference function for the model. + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkReg + url_git: '' +NetworkRiskMeasures: + version: 0.1.4 + title: Risk Measures for (Financial) Networks + maintainer: Carlos Cinelli + description: Implements some risk measures for (financial) networks, such as DebtRank, + Impact Susceptibility, Impact Diffusion and Impact Fluidity. + date_publication: '2020-03-05' + bug_reports: https://github.com/carloscinelli/NetworkRiskMeasures/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkRiskMeasures + url_git: https://github.com/carloscinelli/NetworkRiskMeasures +networkscaleup: + version: 0.1-2 + title: Network Scale-Up Models for Aggregated Relational Data + maintainer: Ian Laga + description: Provides a variety of Network Scale-up Models for researchers to analyze + Aggregated Relational Data, mostly through the use of Stan. In this version, the + package implements models from Laga, I., Bao, L., and Niu, X (2021) , + Zheng, T., Salganik, M. J., and Gelman, A. (2006) , + Killworth, P. D., Johnsen, E. C., McCarty, C., Shelley, G. A., and Bernard, H. + R. (1998) , and Killworth, P. D., McCarty, + C., Bernard, H. R., Shelley, G. A., and Johnsen, E. C. (1998) . + date_publication: '2024-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=networkscaleup + url_git: '' +networksem: + version: '0.2' + title: Network Structural Equation Modeling + maintainer: Zhiyong Zhang + description: Several methods have been developed to integrate structural equation + modeling techniques with network data analysis to examine the relationship between + network and non-network data. Both node-based and edge-based information can be + extracted from the network data to be used as observed variables in structural + equation modeling. To facilitate the application of these methods, model specification + can be performed in the familiar syntax of the 'lavaan' package, ensuring ease + of use for researchers. Technical details and examples can be found at . + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=networksem + url_git: '' +NetworkToolbox: + version: 1.4.2 + title: |- + Methods and Measures for Brain, Cognitive, and Psychometric + Network Analysis + maintainer: Alexander Christensen + description: Implements network analysis and graph theory measures used in neuroscience, + cognitive science, and psychology. Methods include various filtering methods and + approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershgoren, + Mantegna, & Ben-Jacob, 2010 ), Information Filtering + Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 ), + and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 ). + Brain methods include the recently developed Connectome Predictive Modeling (see + references in package). Also implements several network measures including local + network characteristics (e.g., centrality), community-level network characteristics + (e.g., community centrality), global network characteristics (e.g., clustering + coefficient), and various other measures associated with the reliability and reproducibility + of network analysis. + date_publication: '2021-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NetworkToolbox + url_git: '' +networktools: + version: 1.6.0 + title: Tools for Identifying Important Nodes in Networks + maintainer: Payton Jones + description: Includes assorted tools for network analysis. Bridge centrality; goldbricker; + MDS, PCA, & eigenmodel network plotting. + date_publication: '2025-02-25' + bug_reports: https://github.com/paytonjjones/networktools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=networktools + url_git: '' +networktree: + version: 1.0.1 + title: Recursive Partitioning of Network Models + maintainer: Payton Jones + description: 'Network trees recursively partition the data with respect to covariates. + Two network tree algorithms are available: model-based trees based on a multivariate + normal model and nonparametric trees based on covariance structures. After partitioning, + correlation-based networks (psychometric networks) can be fit on the partitioned + data. For details see Jones, Mair, Simon, & Zeileis (2020) .' + date_publication: '2021-02-04' + bug_reports: https://github.com/paytonjjones/networktree/issues + url: https://paytonjjones.github.io/networktree/ + url_cran: https://CRAN.R-project.org/package=networktree + url_git: '' +NeuralEstimators: + version: 0.1.3 + title: Likelihood-Free Parameter Estimation using Neural Networks + maintainer: Matthew Sainsbury-Dale + description: An 'R' interface to the 'Julia' package 'NeuralEstimators.jl'. The + package facilitates the user-friendly development of neural point estimators, + which are neural networks that map data to a point summary of the posterior distribution. + These estimators are likelihood-free and amortised, in the sense that, after an + initial setup cost, inference from observed data can be made in a fraction of + the time required by conventional approaches; see Sainsbury-Dale, Zammit-Mangion, + and Huser (2024) for further details and an + accessible introduction. The package also enables the construction of neural networks + that approximate the likelihood-to-evidence ratio in an amortised manner, allowing + one to perform inference based on the likelihood function or the entire posterior + distribution; see Zammit-Mangion, Sainsbury-Dale, and Huser (2024, Sec. 5.2) , + and the references therein. The package accommodates any model for which simulation + is feasible by allowing the user to implicitly define their model through simulated + data. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NeuralEstimators + url_git: '' +neuralGAM: + version: 1.1.1 + title: |- + Interpretable Neural Network Based on Generalized Additive + Models + maintainer: Ines Ortega-Fernandez + description: Neural network framework based on Generalized Additive Models from + Hastie & Tibshirani (1990, ISBN:9780412343902), which trains a different neural + network to estimate the contribution of each feature to the response variable. + The networks are trained independently leveraging the local scoring and backfitting + algorithms to ensure that the Generalized Additive Model converges and it is additive. + The resultant Neural Network is a highly accurate and interpretable deep learning + model, which can be used for high-risk AI practices where decision-making should + be based on accountable and interpretable algorithms. + date_publication: '2024-04-19' + bug_reports: https://github.com/inesortega/neuralGAM/issues + url: https://inesortega.github.io/neuralGAM/ + url_cran: https://CRAN.R-project.org/package=neuralGAM + url_git: https://github.com/inesortega/neuralGAM +neuralnet: + version: 1.44.2 + title: Training of Neural Networks + maintainer: Marvin N. Wright + description: |- + Training of neural networks using backpropagation, + resilient backpropagation with (Riedmiller, 1994) or without + weight backtracking (Riedmiller and Braun, 1993) or the + modified globally convergent version by Anastasiadis et al. + (2005). The package allows flexible settings through + custom-choice of error and activation function. Furthermore, + the calculation of generalized weights (Intrator O & Intrator + N, 1993) is implemented. + date_publication: '2019-02-07' + bug_reports: https://github.com/bips-hb/neuralnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neuralnet + url_git: https://github.com/bips-hb/neuralnet +NeuralNetTools: + version: 1.5.3 + title: Visualization and Analysis Tools for Neural Networks + maintainer: Marcus W. Beck + description: |- + Visualization and analysis tools to aid in the interpretation of + neural network models. Functions are available for plotting, + quantifying variable importance, conducting a sensitivity analysis, and + obtaining a simple list of model weights. + date_publication: '2022-01-06' + bug_reports: https://github.com/fawda123/NeuralNetTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NeuralNetTools + url_git: '' +NeuralSens: + version: 1.1.3 + title: Sensitivity Analysis of Neural Networks + maintainer: Jaime Pizarroso Gonzalo + description: |- + Analysis functions to quantify inputs importance in neural network models. + Functions are available for calculating and plotting the inputs importance and obtaining + the activation function of each neuron layer and its derivatives. The importance of a given + input is defined as the distribution of the derivatives of the output with respect to that + input in each training data point . + date_publication: '2024-05-11' + bug_reports: https://github.com/JaiPizGon/NeuralSens/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NeuralSens + url_git: https://github.com/JaiPizGon/NeuralSens +neurobase: + version: 1.32.4 + title: |- + 'Neuroconductor' Base Package with Helper Functions for 'nifti' + Objects + maintainer: John Muschelli + description: |- + Base package for 'Neuroconductor', which includes many helper + functions that interact with objects of class 'nifti', implemented by + package 'oro.nifti', for reading/writing and also other manipulation + functions. + date_publication: '2024-05-09' + bug_reports: https://github.com/muschellij2/neurobase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neurobase + url_git: '' +neuroblastoma: + version: 2023.9.3 + title: Neuroblastoma Copy Number Profiles + maintainer: Toby Dylan Hocking + description: |2- + + Annotated neuroblastoma copy number profiles, + a benchmark data set for change-point detection algorithms, + as described by Hocking et al. . + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neuroblastoma + url_git: '' +NeuroDecodeR: + version: 0.2.0 + title: Decode Information from Neural Activity + maintainer: Ethan Meyers + description: |- + Neural decoding is method of analyzing neural data that + uses a pattern classifiers to predict experimental conditions based + on neural activity. 'NeuroDecodeR' is a system of objects that + makes it easy to run neural decoding analyses. For more information + on neural decoding see Meyers & Kreiman (2011) + . + date_publication: '2024-03-15' + bug_reports: https://github.com/emeyers/NeuroDecodeR/issues + url: https://emeyers.github.io/NeuroDecodeR/ + url_cran: https://CRAN.R-project.org/package=NeuroDecodeR + url_git: https://github.com/emeyers/NeuroDecodeR +neurohcp: + version: 0.9.0 + title: Human 'Connectome' Project Interface + maintainer: John Muschelli + description: |- + Downloads and reads data from Human 'Connectome' Project + using Amazon Web Services ('AWS') + 'S3' buckets. + date_publication: '2020-10-14' + bug_reports: https://github.com/muschellij2/neurohcp/issues + url: https://db.humanconnectome.org + url_cran: https://CRAN.R-project.org/package=neurohcp + url_git: '' +neuroim: + version: 0.0.6 + title: Data Structures and Handling for Neuroimaging Data + maintainer: Bradley Buchsbaum + description: |- + A collection of data structures that represent + volumetric brain imaging data. The focus is on basic data handling for 3D + and 4D neuroimaging data. In addition, there are function to read and write + NIFTI files and limited support for reading AFNI files. + date_publication: '2016-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neuroim + url_git: '' +neuroimaGene: + version: 0.1.2 + title: Transcriptomic Atlas of Neuroimaging Derived Phenotypes + maintainer: Xavier Bledsoe + description: |- + Contains functions to query and visualize the Neuroimaging features + associated with genetically regulated gene expression (GReX). The primary utility, + neuroimaGene(), relies on a list of user-defined genes and returns a table of + neuroimaging features (NIDPs) associated with each gene. This resource + is designed to assist in the interpretation of genome-wide and transcriptome-wide + association studies that evaluate brain related traits. Bledsoe (2024) + . In addition there are several visualization + functions that generate summary plots and 2-dimensional visualizations of regional + brain measures. Mowinckel (2020). + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neuroimaGene + url_git: '' +neuromplex: + version: 1.0-1 + title: Neural Multiplexing Analysis + maintainer: Surya Tokdar + description: Statistical methods for whole-trial and time-domain analysis of single + cell neural response to multiple stimuli presented simultaneously. The package + is based on the paper by C Glynn, ST Tokdar, A Zaman, VC Caruso, JT Mohl, SM Willett, + and JM Groh (2021) "Analyzing second order stochasticity of neural spiking under + stimuli-bundle exposure", is in press for publication by the Annals of Applied + Statistics. A preprint may be found at . + date_publication: '2021-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neuromplex + url_git: '' +neuRosim: + version: 0.2-14 + title: Simulate fMRI Data + maintainer: Karsten Tabelow + description: |- + Generates functional Magnetic Resonance Imaging (fMRI) + time series or 4D data. Some high-level + functions are created for fast data generation with only + a few arguments and a diversity of functions to define + activation and noise. For more advanced users it is possible + to use the low-level functions and manipulate the arguments. + See Welvaert et al. (2011) . + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neuRosim + url_git: '' +neuroUp: + version: 0.3.1 + title: Plan Sample Size for Task fMRI Research using Bayesian Updating + maintainer: Eduard Klapwijk + description: |- + Calculate the precision in mean differences (raw or Cohen's D) and + correlation coefficients for different sample sizes. Uses permutations of the + collected functional magnetic resonance imaging (fMRI) region of interest data. + Method described in Klapwijk, Jongerling, Hoijtink and Crone (2024) + . + date_publication: '2024-08-28' + bug_reports: https://github.com/eduardklap/neuroUp/issues + url: https://eduardklap.github.io/neuroUp/ + url_cran: https://CRAN.R-project.org/package=neuroUp + url_git: https://github.com/eduardklap/neuroUp +neutralitytestr: + version: 0.0.3 + title: Test for a Neutral Evolutionary Model in Cancer Sequencing Data + maintainer: Marc Williams + description: Package takes frequencies of mutations as reported by high throughput + sequencing data from cancer and fits a theoretical neutral model of tumour evolution. + Package outputs summary statistics and contains code for plotting the data and + model fits. See Williams et al 2016 and Williams et al 2017 + for further details of the method. + date_publication: '2021-02-16' + bug_reports: https://github.com/marcjwilliams1/neutralitytestr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=neutralitytestr + url_git: https://github.com/marcjwilliams1/neutralitytestr +neutrostat: + version: 0.0.2 + title: Neutrosophic Statistics + maintainer: Zsolt T. Kosztyan + description: Analyzes data involving imprecise and vague information. Provides summary + statistics and describes the characteristics of neutrosophic data, as defined + by Florentin Smarandache (2013).. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=neutrostat + url_git: https://github.com/kzst/neutrostat +nevada: + version: 0.2.0 + title: Network-Valued Data Analysis + maintainer: Aymeric Stamm + description: |- + A flexible statistical framework for network-valued data analysis. + It leverages the complexity of the space of distributions on graphs by using + the permutation framework for inference as implemented in the 'flipr' package. + Currently, only the two-sample testing problem is covered and generalization + to k samples and regression will be added in the future as well. It is a + 4-step procedure where the user chooses a suitable representation of the + networks, a suitable metric to embed the representation into a metric space, + one or more test statistics to target specific aspects of the distributions + to be compared and a formula to compute the permutation p-value. Two types + of inference are provided: a global test answering whether there is a + difference between the distributions that generated the two samples and a + local test for localizing differences on the network structure. The latter + is assumed to be shared by all networks of both samples. References: Lovato, + I., Pini, A., Stamm, A., Vantini, S. (2020) "Model-free two-sample test for + network-valued data" ; Lovato, I., Pini, A., + Stamm, A., Taquet, M., Vantini, S. (2021) "Multiscale null hypothesis + testing for network-valued data: Analysis of brain networks of patients with + autism" . + date_publication: '2023-09-03' + bug_reports: https://github.com/astamm/nevada/issues/ + url: https://astamm.github.io/nevada/ + url_cran: https://CRAN.R-project.org/package=nevada + url_git: https://github.com/astamm/nevada/ +neverhpfilter: + version: 0.4-0 + title: An Alternative to the Hodrick-Prescott Filter + maintainer: Justin M. Shea + description: |- + In the working paper titled "Why You Should Never Use the Hodrick-Prescott + Filter", James D. Hamilton proposes a new alternative to economic time series + filtering. The neverhpfilter package provides functions and data for reproducing his work. Hamilton (2017) . + date_publication: '2021-06-18' + bug_reports: https://github.com/JustinMShea/neverhpfilter/issues + url: https://justinmshea.github.io/neverhpfilter/ + url_cran: https://CRAN.R-project.org/package=neverhpfilter + url_git: '' +new.dist: + version: 0.1.1 + title: Alternative Continuous and Discrete Distributions + maintainer: Ramazan Akman + description: |- + The aim is to develop an R package, which is the 'new.dist' + package, for the probability (density) function, the + distribution function, the quantile function and the + associated random number generation function for discrete and + continuous distributions, which have recently been proposed + in the literature. This package implements the following + distributions: The Power Muth Distribution, a Bimodal Weibull + Distribution, the Discrete Lindley Distribution, The + Gamma-Lomax Distribution, Weighted Geometric Distribution, a + Power Log-Dagum Distribution, Kumaraswamy Distribution, + Lindley Distribution, the Unit-Inverse Gaussian Distribution, + EP Distribution, Akash Distribution, Ishita Distribution, + Maxwell Distribution, the Standard Omega Distribution, + Slashed Generalized Rayleigh Distribution, Two-Parameter + Rayleigh Distribution, Muth Distribution, Uniform-Geometric + Distribution, Discrete Weibull Distribution. + date_publication: '2023-12-09' + bug_reports: https://github.com/akmn35/new.dist/issues + url: https://akmn35.github.io/new.dist/ + url_cran: https://CRAN.R-project.org/package=new.dist + url_git: https://github.com/akmn35/new.dist +Newdistns: + version: '2.1' + title: |- + Computes Pdf, Cdf, Quantile and Random Numbers, Measures of + Inference for 19 General Families of Distributions + maintainer: Saralees Nadarajah + description: 'Computes the probability density function, cumulative distribution + function, quantile function, random numbers and measures of inference for the + following general families of distributions (each family defined in terms of + an arbitrary cdf G): Marshall Olkin G distributions, exponentiated G distributions, + beta G distributions, gamma G distributions, Kumaraswamy G distributions, generalized + beta G distributions, beta extended G distributions, gamma G distributions, gamma + uniform G distributions, beta exponential G distributions, Weibull G distributions, + log gamma G I distributions, log gamma G II distributions, exponentiated generalized + G distributions, exponentiated Kumaraswamy G distributions, geometric exponential + Poisson G distributions, truncated-exponential skew-symmetric G distributions, + modified beta G distributions, and exponentiated exponential Poisson G distributions.' + date_publication: '2016-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Newdistns + url_git: '' +newFocus: + version: '1.1' + title: True Discovery Guarantee by Combining Partial Closed Testings + maintainer: Ningning Xu + description: Closed testing has been proved powerful for true discovery guarantee. + The computation of closed testing is, however, quite burdensome. A general way + to reduce computational complexity is to combine partial closed testings for some + prespecified feature sets of interest. Partial closed testings are performed at + Bonferroni-corrected alpha level to guarantee the lower bounds for the number + of true discoveries in prespecified sets are simultaneously valid. For any post + hoc chosen sets of interest, coherence property is used to get the lower bound. + In this package, we implement closed testing with globaltest to calculate the + lower bound for number of true discoveries, see Ningning Xu et.al (2021) + for detailed description. + date_publication: '2021-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=newFocus + url_git: '' +newIMVC: + version: 0.1.0 + title: A Robust Integrated Mean Variance Correlation + maintainer: Han Pan + description: Measure the dependence structure between two random variables with + a new correlation coefficient and extend it to hypothesis test, feature screening + and false discovery rate control. + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=newIMVC + url_git: '' +NewmanOmics: + version: 1.0.13 + title: |- + Extending the Newman Studentized Range Statistic to + Transcriptomics + maintainer: Kevin R. Coombes + description: |- + Extends the classical Newman studentized range statistic + in various ways that can be applied to genome-scale transcriptomic + or other expression data. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NewmanOmics + url_git: http://oompa.r-forge.r-project.org/ +newsanchor: + version: 0.1.1 + title: Client for the News API + maintainer: Buhl Yannik + description: Interface to gather news from the 'News API', based on a multilevel + query . A personal API key is required. + date_publication: '2019-06-29' + bug_reports: https://github.com/correlaid/newsanchor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=newsanchor + url_git: '' +newscatcheR: + version: 0.1.2 + title: |- + Programmatically Collect Normalized News from (Almost) Any + Website + maintainer: Novica Nakov + description: |- + Programmatically collect normalized news from + (almost) any website. An 'R' clone of the + 'Python' module. + date_publication: '2023-09-20' + bug_reports: https://github.com/discindo/newscatcheR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=newscatcheR + url_git: https://github.com/discindo/newscatcheR/ +newsmap: + version: 0.9.0 + title: Semi-Supervised Model for Geographical Document Classification + maintainer: Kohei Watanabe + description: |- + Semissupervised model for geographical document classification (Watanabe 2018) . + This package currently contains seed dictionaries in English, German, French, Spanish, Italian, Russian, Hebrew, Arabic, Turkish, Japanese and Chinese (Simplified and Traditional). + date_publication: '2024-05-23' + bug_reports: https://github.com/koheiw/newsmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=newsmap + url_git: https://github.com/koheiw/newsmap +newsmd: + version: 0.5.1 + title: Creation of NEWS.md File + maintainer: Jakob Gepp + description: |- + Adding updates (version or bullet points) to the NEWS.md + file. + date_publication: '2023-04-17' + bug_reports: https://github.com/Dschaykib/newsmd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=newsmd + url_git: https://github.com/Dschaykib/newsmd +newTestSurvRec: + version: 1.0.2 + title: Statistical Tests to Compare Curves with Recurrent Events + maintainer: Carlos Martinez + description: Implements the routines to compare the survival curves with recurrent + events, including the estimations of survival curves. The first model is a model + for recurrent event, when the data are correlated or not correlated. It was proposed + by Wang and Chang (1999) . In the independent case, the survival + function can be estimated by the generalization of the limit product model of + Pena (2001) . + date_publication: '2018-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=newTestSurvRec + url_git: '' +nextGenShinyApps: + version: '2.1' + title: |- + Craft Exceptional 'R Shiny' Applications and Dashboards with + Novel Responsive Tools + maintainer: Obinna Obianom + description: Novel responsive tools for developing R based 'Shiny' dashboards and + applications. The scripts and style sheets are based on 'jQuery' + and 'Bootstrap' . + date_publication: '2024-07-29' + bug_reports: https://github.com/oobianom/nextGenShinyApps + url: https://nextgenshinyapps.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=nextGenShinyApps + url_git: '' +nexus: + version: 0.4.0 + title: Sourcing Archaeological Materials by Chemical Composition + maintainer: Nicolas Frerebeau + description: |- + Exploration and analysis of compositional data in the + framework of Aitchison (1986, ISBN: 978-94-010-8324-9). This package + provides tools for chemical fingerprinting and source tracking of + ancient materials. + date_publication: '2025-01-14' + bug_reports: https://github.com/tesselle/nexus/issues + url: https://packages.tesselle.org/nexus/ + url_cran: https://CRAN.R-project.org/package=nexus + url_git: https://github.com/tesselle/nexus +nFactors: + version: 2.4.1.1 + title: |- + Parallel Analysis and Other Non Graphical Solutions to the + Cattell Scree Test + maintainer: Gilles Raiche + description: |- + Indices, heuristics and strategies to help determine the number of factors/components to retain: + 1. Acceleration factor (af with or without Parallel Analysis); + 2. Optimal Coordinates (noc with or without Parallel Analysis); + 3. Parallel analysis (components, factors and bootstrap); + 4. lambda > mean(lambda) (Kaiser, CFA and related); + 5. Cattell-Nelson-Gorsuch (CNG); + 6. Zoski and Jurs multiple regression (b, t and p); + 7. Zoski and Jurs standard error of the regression coeffcient (sescree); + 8. Nelson R2; + 9. Bartlett khi-2; + 10. Anderson khi-2; + 11. Lawley khi-2 and + 12. Bentler-Yuan khi-2. + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nFactors + url_git: '' +NFCP: + version: 1.2.1 + title: N-Factor Commodity Pricing Through Term Structure Estimation + maintainer: Thomas Aspinall + description: Commodity pricing models are (systems of) stochastic differential equations + that are utilized for the valuation and hedging of commodity contingent claims + (i.e. derivative products on the commodity) and other commodity related investments. + Commodity pricing models that capture market dynamics are of great importance + to commodity market participants in order to exercise sound investment and risk-management + strategies. Parameters of commodity pricing models are estimated through maximum + likelihood estimation, using available term structure futures data of a commodity. + 'NFCP' (n-factor commodity pricing) provides a framework for the modeling, parameter + estimation, probabilistic forecasting, option valuation and simulation of commodity + prices through state space and Monte Carlo methods, risk-neutral valuation and + Kalman filtering. 'NFCP' allows the commodity pricing model to consist of n correlated + factors, with both random walk and mean-reverting elements. The n-factor commodity + pricing model framework was first presented in the work of Cortazar and Naranjo + (2006) . Examples presented in 'NFCP' replicate the two-factor + crude oil commodity pricing model presented in the prolific work of Schwartz and + Smith (2000) with the approximate term structure + futures data applied within this study provided in the 'NFCP' package. + date_publication: '2022-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NFCP + url_git: '' +nfer: + version: 1.1.3 + title: Event Stream Abstraction using Interval Logic + maintainer: Sean Kauffman + description: |- + This is the R API for the 'nfer' formalism (). + 'nfer' was developed to specify event stream abstractions for spacecraft + telemetry such as the Mars Science Laboratory. Users write rules using + a syntax that borrows heavily from Allen's Temporal Logic that, when + applied to an event stream, construct a hierarchy of temporal intervals + with data. The R API supports loading rules from a file or mining them + from historical data. Traces of events or pools of intervals are + provided as data frames. + date_publication: '2023-04-12' + bug_reports: https://bitbucket.org/seanmk/nfer/issues + url: http://nfer.io/ + url_cran: https://CRAN.R-project.org/package=nfer + url_git: '' +nfl4th: + version: 1.0.4 + title: |- + Functions to Calculate Optimal Fourth Down Decisions in the + National Football League + maintainer: Ben Baldwin + description: |- + A set of functions to estimate outcomes of fourth down + plays in the National Football League and obtain fourth down plays + from and . + date_publication: '2023-08-21' + bug_reports: https://github.com/nflverse/nfl4th/issues + url: https://www.nfl4th.com/ + url_cran: https://CRAN.R-project.org/package=nfl4th + url_git: https://github.com/nflverse/nfl4th/ +nflfastR: + version: 5.0.0 + title: Functions to Efficiently Access NFL Play by Play Data + maintainer: Ben Baldwin + description: |- + A set of functions to access National Football + League play-by-play data from . + date_publication: '2024-11-26' + bug_reports: https://github.com/nflverse/nflfastR/issues + url: https://www.nflfastr.com/ + url_cran: https://CRAN.R-project.org/package=nflfastR + url_git: https://github.com/nflverse/nflfastR +nflplotR: + version: 1.4.0 + title: NFL Logo Plots in 'ggplot2' and 'gt' + maintainer: Sebastian Carl + description: |- + A set of functions to visualize National Football League + analysis in 'ggplot2' plots and 'gt' tables. + date_publication: '2024-08-21' + bug_reports: https://github.com/nflverse/nflplotR/issues + url: https://nflplotr.nflverse.com + url_cran: https://CRAN.R-project.org/package=nflplotR + url_git: https://github.com/nflverse/nflplotR +nflreadr: + version: 1.4.1 + title: Download 'nflverse' Data + maintainer: Tan Ho + description: |- + A minimal package for downloading data from 'GitHub' + repositories of the 'nflverse' project. + date_publication: '2024-07-29' + bug_reports: https://github.com/nflverse/nflreadr/issues + url: https://nflreadr.nflverse.com + url_cran: https://CRAN.R-project.org/package=nflreadr + url_git: https://github.com/nflverse/nflreadr +nflseedR: + version: 1.2.0 + title: Functions to Efficiently Simulate and Evaluate NFL Seasons + maintainer: Sebastian Carl + description: |- + A set of functions to simulate National Football League + seasons including the sophisticated tie-breaking procedures. + date_publication: '2023-01-05' + bug_reports: https://github.com/nflverse/nflseedR/issues + url: https://nflseedr.com + url_cran: https://CRAN.R-project.org/package=nflseedR + url_git: https://github.com/nflverse/nflseedR +NFLSimulatoR: + version: 0.4.0 + title: Simulating Plays and Drives in the NFL + maintainer: Ryan Elmore + description: |- + The intent here is to enable the simulation of plays/drives and + evaluate game-play strategies in the National Football League (NFL). + Built-in strategies include going for it on fourth down and varying the + proportion of passing/rushing plays during a drive. The user should be + familiar with nflscrapR data before trying to write his/her own + strategies. This work is inspired by a blog post by Mike Lopez, + currently the Director of Data and Analytics at the NFL, Lopez (2019) . + date_publication: '2022-08-19' + bug_reports: https://github.com/rtelmore/NFLSimulatoR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=NFLSimulatoR + url_git: https://github.com/rtelmore/NFLSimulatoR/ +nflverse: + version: 1.0.3 + title: Easily Install and Load the 'nflverse' + maintainer: Sebastian Carl + description: |- + The 'nflverse' is a set of packages dedicated to data of the + National Football League. This package is designed to make it easy to + install and load multiple 'nflverse' packages in a single step. Learn + more about the 'nflverse' at . + date_publication: '2023-08-14' + bug_reports: https://github.com/nflverse/nflverse/issues + url: https://nflverse.nflverse.com/ + url_cran: https://CRAN.R-project.org/package=nflverse + url_git: https://github.com/nflverse/nflverse +nftbart: + version: '2.1' + title: Nonparametric Failure Time Bayesian Additive Regression Trees + maintainer: Rodney Sparapani + description: 'Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees + (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive + Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures + (DPM). An NFT BART model is of the form Y = mu + f(x) + sd(x) E where functions + f and sd have BART and HBART priors, respectively, while E is a nonparametric + error distribution due to a DPM LIO prior hierarchy. See the following for a complete + description of the model at .' + date_publication: '2023-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nftbart + url_git: '' +nFunNN: + version: '1.0' + title: |- + Nonlinear Functional Principal Component Analysis using Neural + Networks + maintainer: Rou Zhong + description: Implementation for 'nFunNN' method, which is a novel nonlinear functional + principal component analysis method using neural networks. The crucial function + of this package is nFunNNmodel(). + date_publication: '2024-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nFunNN + url_git: '' +NFWdist: + version: 0.1.0 + title: The Standard Distribution Functions for the 3D NFW Profile + maintainer: Aaron Robotham + description: Density, distribution function, quantile function and random generation + for the 3D Navarro, Frenk & White (NFW) profile. For details see Robotham & Howlett + (2018) . + date_publication: '2018-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NFWdist + url_git: '' +ngboostForecast: + version: 0.1.1 + title: Probabilistic Time Series Forecasting + maintainer: Resul Akay + description: Probabilistic time series forecasting via Natural Gradient Boosting + for Probabilistic Prediction. + date_publication: '2022-08-06' + bug_reports: https://github.com/Akai01/ngboostForecast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ngboostForecast + url_git: https://github.com/Akai01/ngboostForecast +NGBVS: + version: 0.3.0 + title: Bayesian Variable Selection for SNP Data using Normal-Gamma + maintainer: Abdulaziz Alenazi + description: Posterior distribution of case-control fine-mapping. Specifically, + Bayesian variable selection for single-nucleotide polymorphism (SNP) data using + the normal-gamma prior. Alenazi A.A., Cox A., Juarez M,. Lin W-Y. and Walters, + K. (2019) Bayesian variable selection using partially observed categorical prior + information in fine-mapping association studies, Genetic Epidemiology. . + date_publication: '2022-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NGBVS + url_git: '' +NGCHM: + version: 1.0.4 + title: Next Generation Clustered Heat Maps + maintainer: Mary A Rohrdanz + description: |- + Next-Generation Clustered Heat Maps (NG-CHMs) allow for + dynamic exploration of heat map data in a web browser. 'NGCHM' allows + users to create both stand-alone HTML files containing a + Next-Generation Clustered Heat Map, and .ngchm files to view in the + NG-CHM viewer. See Ryan MC, Stucky M, et al (2020) + for more details. + date_publication: '2024-12-17' + bug_reports: '' + url: https://md-anderson-bioinformatics.github.io/NGCHM-R/ + url_cran: https://CRAN.R-project.org/package=NGCHM + url_git: https://github.com/MD-Anderson-Bioinformatics/NGCHM-R +NGLVieweR: + version: 1.4.0 + title: Interactive 3D Visualization of Molecular Structures + maintainer: Niels van der Velden + description: |- + Provides an 'htmlwidgets' interface to 'NGL.js' . + 'NGLvieweR' can be used to visualize and interact with protein databank ('PDB') and structural files in R and Shiny applications. + It includes a set of API functions to manipulate the viewer after creation in Shiny. + date_publication: '2024-11-22' + bug_reports: https://github.com/nvelden/NGLVieweR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NGLVieweR + url_git: https://github.com/nvelden/NGLVieweR +ngram: + version: 3.2.3 + title: Fast n-Gram 'Tokenization' + maintainer: Drew Schmidt + description: |- + An n-gram is a sequence of n "words" taken, in order, from a + body of text. This is a collection of utilities for creating, + displaying, summarizing, and "babbling" n-grams. The + 'tokenization' and "babbling" are handled by very efficient C + code, which can even be built as its own standalone library. + The babbler is a simple Markov chain. The package also offers + a vignette with complete example 'workflows' and information about + the utilities offered in the package. + date_publication: '2023-12-10' + bug_reports: https://github.com/wrathematics/ngram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ngram + url_git: https://github.com/wrathematics/ngram +ngramr: + version: 1.10.0 + title: Retrieve and Plot Google n-Gram Data + maintainer: Sean Carmody + description: |- + Retrieve and plot word frequencies through time from the "Google + Ngram Viewer" . + date_publication: '2025-01-10' + bug_reports: https://github.com/seancarmody/ngramr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ngramr + url_git: https://github.com/seancarmody/ngramr +ngramrr: + version: 0.2.0 + title: A Simple General Purpose N-Gram Tokenizer + maintainer: Chung-hong Chan + description: |- + A simple n-gram (contiguous sequences of n items from a + given sequence of text) tokenizer to be used with the 'tm' package with no + 'rJava'/'RWeka' dependency. + date_publication: '2016-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ngramrr + url_git: https://github.com/chainsawriot/ngramrr +ngspatial: + version: 1.2-2 + title: |- + Fitting the Centered Autologistic and Sparse Spatial Generalized + Linear Mixed Models for Areal Data + maintainer: John Hughes + description: |- + Provides tools for analyzing spatial data, especially non- + Gaussian areal data. The current version supports the sparse restricted + spatial regression model of Hughes and Haran (2013) , + the centered autologistic model of Caragea and Kaiser (2009) , + and the Bayesian spatial filtering model of Hughes (2017) . + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ngspatial + url_git: '' +NHANES: + version: 2.1.0 + title: Data from the US National Health and Nutrition Examination Study + maintainer: Randall Pruim + description: |- + Body Shape and related measurements from the US National Health + and Nutrition Examination Survey (NHANES, 1999-2004). See + http://www.cdc.gov/nchs/nhanes.htm for details. + date_publication: '2015-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NHANES + url_git: '' +nhanesA: + version: '1.3' + title: NHANES Data Retrieval + maintainer: Christopher Endres + description: |- + Utility to retrieve data from the National Health and Nutrition + Examination Survey (NHANES) website . + date_publication: '2025-01-10' + bug_reports: https://github.com/cjendres1/nhanes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nhanesA + url_git: '' +nhdplusTools: + version: 1.3.1 + title: NHDPlus Tools + maintainer: David Blodgett + description: Tools for traversing and working with National Hydrography Dataset + Plus (NHDPlus) data. All methods implemented in 'nhdplusTools' are available in + the NHDPlus documentation available from the US Environmental Protection Agency + . + date_publication: '2025-02-14' + bug_reports: https://github.com/doi-usgs/nhdplusTools/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=nhdplusTools + url_git: https://doi-usgs.github.io/nhdplusTools/https://github.com/doi-usgs/nhdplusTools/ +nhdR: + version: 0.6.1 + title: Tools for Working with the National Hydrography Dataset + maintainer: Jemma Stachelek + description: |- + Tools for working with the National Hydrography Dataset, with + functions for querying, downloading, and networking both the NHD + + and NHDPlus datasets. + date_publication: '2023-08-12' + bug_reports: https://github.com/jsta/nhdR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nhdR + url_git: https://github.com/jsta/nhdR +nhlapi: + version: 0.1.4 + title: A Minimum-Dependency 'R' Interface to the 'NHL' API + maintainer: Jozef Hajnala + description: Retrieves and processes the data exposed by the open 'NHL' API. This + includes information on players, teams, games, tournaments, drafts, standings, + schedules and other endpoints. A lower-level interface to access the data via + URLs directly is also provided. + date_publication: '2021-02-20' + bug_reports: https://github.com/jozefhajnala/nhlapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nhlapi + url_git: https://github.com/jozefhajnala/nhlapi +NHLData: + version: 1.0.0 + title: Scores for Every Season Since the Founding of the NHL in 1917 + maintainer: D. Lukke Sweet + description: Each dataset contains scores for every game during a specific season + of the NHL. + date_publication: '2017-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NHLData + url_git: '' +nhm: + version: 0.1.1 + title: Non-Homogeneous Markov and Hidden Markov Multistate Models + maintainer: Andrew Titman + description: Fits non-homogeneous Markov multistate models and misclassification-type + hidden Markov models in continuous time to intermittently observed data. Implements + the methods in Titman (2011) . Uses direct + numerical solution of the Kolmogorov forward equations to calculate the transition + probabilities. + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nhm + url_git: '' +NHPoisson: + version: '3.3' + title: Modelling and Validation of Non Homogeneous Poisson Processes + maintainer: Ana C. Cebrian + description: Tools for modelling, ML estimation, validation analysis and simulation + of non homogeneous Poisson processes in time. + date_publication: '2020-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NHPoisson + url_git: '' +nhppp: + version: 1.0.2 + title: Simulating Nonhomogeneous Poisson Point Processes + maintainer: Thomas Trikalinos + description: 'Simulates events from one dimensional nonhomogeneous Poisson point + processes (NHPPPs) as per Trikalinos and Sereda (2024, + and 2024, ). Functions are based on three algorithms + that provably sample from a target NHPPP: the time-transformation of a homogeneous + Poisson process (of intensity one) via the inverse of the integrated intensity + function (Cinlar E, "Theory of stochastic processes" (1975, ISBN:0486497996)); + the generation of a Poisson number of order statistics from a fixed density function; + and the thinning of a majorizing NHPPP via an acceptance-rejection scheme (Lewis + PAW, Shedler, GS (1979) ).' + date_publication: '2025-01-09' + bug_reports: https://github.com/bladder-ca/nhppp/issues + url: https://bladder-ca.github.io/nhppp/ + url_cran: https://CRAN.R-project.org/package=nhppp + url_git: https://github.com/bladder-ca/nhppp +nhs.predict: + version: 1.4.0 + title: Breast Cancer Survival and Therapy Benefits + maintainer: Giovanni Tramonti + description: |- + Calculate Overall Survival or Recurrence-Free Survival for breast cancer patients, using 'NHS Predict'. + The time interval for the estimation can be set up to 15 years, with default at 10. + Incremental therapy benefits are estimated for hormone therapy, chemotherapy, trastuzumab, and bisphosphonates. + An additional function, suited for SCAN audits, features a more user-friendly version of the code, with fewer inputs, but necessitates + the correct standardised inputs. + This work is not affiliated with the development of 'NHS Predict' and its underlying statistical model. + Details on 'NHS Predict' can be found at: . + The web version of 'NHS Predict': . + A small dataset of 50 fictional patient observations is provided for the purpose of running examples with the main two functions, + and an additional dataset is provided for running example with the dedicated SCAN function. + date_publication: '2020-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nhs.predict + url_git: '' +NHSDataDictionaRy: + version: 1.2.5 + title: NHS Data Dictionary Toolset for NHS Lookups + maintainer: Gary Hutson + description: |- + Providing a common set of simplified web scraping tools for working with the NHS Data Dictionary . + The intended usage is to access the data elements section of the NHS Data Dictionary to access key lookups. + The benefits of having it in this package are that the lookups are the live lookups on the website and will not need to be maintained. + This package was commissioned by the NHS-R community to provide this consistency of lookups. + The OpenSafely lookups have now been added . + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NHSDataDictionaRy + url_git: '' +nhsnumber: + version: 0.1.2 + title: Tools for Working with NHS Number Checksums + maintainer: Mark Sellors + description: |- + Provides functions for working with NHS number checksums. + The UK's National Health Service issues NHS numbers to all users of its + services and this package implements functions for verifying that the + numbers are valid according to the checksum scheme the NHS use. + Numbers can be validated and checksums created. + date_publication: '2021-12-06' + bug_reports: https://github.com/sellorm/nhsnumber/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nhsnumber + url_git: https://github.com/sellorm/nhsnumber +NHSRdatasets: + version: 0.3.0 + title: NHS and Healthcare-Related Data for Education and Training + maintainer: Chris Mainey + description: 'Free United Kingdom National Health Service (NHS) and other healthcare, + or population health-related data for education and training purposes. This package + contains synthetic data based on real healthcare datasets, or cuts of open-licenced + official data. This package exists to support skills development in the NHS-R + community: .' + date_publication: '2021-03-14' + bug_reports: https://github.com/nhs-r-community/NHSRdatasets/issues + url: https://nhs-r-community.github.io/NHSRdatasets/ + url_cran: https://CRAN.R-project.org/package=NHSRdatasets + url_git: https://github.com/nhs-r-community/NHSRdatasets +NHSRplotthedots: + version: 0.1.0 + title: Draw XmR Charts for NHSE/I 'Making Data Count' Programme + maintainer: Christopher Reading + description: |- + Provides tools for drawing Statistical Process Control (SPC) charts. This package supports the NHSE/I + programme 'Making Data Count', and allows users to draw XmR charts, use change points and apply rules with summary + indicators for when rules are breached. + date_publication: '2021-11-03' + bug_reports: '' + url: https://nhs-r-community.github.io/NHSRplotthedots/ + url_cran: https://CRAN.R-project.org/package=NHSRplotthedots + url_git: '' +nhstplot: + version: 1.3.0 + title: Plot Null Hypothesis Significance Tests + maintainer: Nils Myszkowski + description: Illustrate graphically the most common Null Hypothesis Significance + Testing procedures. More specifically, this package provides functions to plot + Chi-Squared, F, t (one- and two-tailed) and z (one- and two-tailed) tests, by + plotting the probability density under the null hypothesis as a function of the + different test statistic values. Although highly flexible (color theme, fonts, + etc.), only the minimal number of arguments (observed test statistic, degrees + of freedom) are necessary for a clear and useful graph to be plotted, with the + observed test statistic and the p value, as well as their corresponding value + labels. The axes are automatically scaled to present the relevant part and the + overall shape of the probability density function. This package is especially + intended for education purposes, as it provides a helpful support to help explain + the Null Hypothesis Significance Testing process, its use and/or shortcomings. + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nhstplot + url_git: '' +niaidMI: + version: 1.1.0 + title: Markov Model Multiple Imputation for NIAID OS + maintainer: Nathan Morris + description: |- + The implementation of Markov Model Multiple Imputation + with the application to COVID-19 scale, NIAID OS. + date_publication: '2022-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=niaidMI + url_git: '' +niarules: + version: 0.2.0 + title: |- + Numerical Association Rule Mining using Population-Based + Nature-Inspired Algorithms + maintainer: Iztok Jr. Fister + description: |- + Framework is devoted to mining numerical association rules through the + utilization of nature-inspired algorithms for optimization. Drawing inspiration + from the 'NiaARM' 'Python' and the 'NiaARM' 'Julia' packages, this repository + introduces the capability to perform numerical association rule mining in + the R programming language. + Fister Jr., Iglesias, Galvez, Del Ser, Osaba and Fister (2018) . + date_publication: '2025-02-20' + bug_reports: https://github.com/firefly-cpp/niarules/issues + url: '' + url_cran: https://CRAN.R-project.org/package=niarules + url_git: https://github.com/firefly-cpp/niarules +nic: + version: 0.0.2 + title: Nature Inspired Colours + maintainer: Thiyanga S. Talagala + description: Color palettes based on nature inspired colours in "Sri Lanka". + date_publication: '2023-03-13' + bug_reports: https://github.com/thiyangt/nic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nic + url_git: https://github.com/thiyangt/nic +nice: + version: 0.4-2 + title: Get or Set UNIX Niceness + maintainer: Charles J. Geyer + description: Get or set UNIX priority (niceness) of running R process. + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nice + url_git: '' +NicheBarcoding: + version: '1.0' + title: Niche-model-Based Species Identification + maintainer: Cai-qing YANG + description: |- + Species Identification using DNA Barcodes Integrated with + Environmental Niche Models. + date_publication: '2021-12-21' + bug_reports: https://github.com/Yangcq-Ivy/NicheBarcoding + url: '' + url_cran: https://CRAN.R-project.org/package=NicheBarcoding + url_git: https://github.com/Yangcq-Ivy/NicheBarcoding +nicheROVER: + version: 1.1.2 + title: |- + Niche Region and Niche Overlap Metrics for Multidimensional + Ecological Niches + maintainer: Martin Lysy + description: Implementation of a probabilistic method to calculate 'nicheROVER' + (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator + data (e.g., stable isotopes, environmental variables, etc.). The niche region + is defined as the joint probability density function of the multidimensional niche + indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted + for in a Bayesian framework, and the method can be extended to three or more indicator + dimensions. It provides directional estimates of niche overlap, accounts for + species-specific distributions in multivariate niche space, and produces unique + and consistent bivariate projections of the multivariate niche region. The article + by Swanson et al. (2015) provides a detailed description + of the methodology. See the package vignette for a worked example using fish + stable isotope data. + date_publication: '2023-10-13' + bug_reports: https://github.com/mlysy/nicheROVER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nicheROVER + url_git: https://github.com/mlysy/nicheROVER +nichetools: + version: 0.3.2 + title: Complementary Package to 'nicheROVER' and 'SIBER' + maintainer: Benjamin L. Hlina + description: |- + Provides functions complementary to packages 'nicheROVER' and 'SIBER' + allowing the user to extract Bayesian estimates from data objects created + by the packages 'nicheROVER' and 'SIBER'. Please see the following + publications for detailed methods on 'nicheROVER' and 'SIBER' + Hansen et al. (2015) , + Jackson et al. (2011) , and + Layman et al. (2007) , + respectfully. + date_publication: '2024-09-30' + bug_reports: https://github.com/benjaminhlina/nichetools/issues + url: https://benjaminhlina.github.io/nichetools/ + url_cran: https://CRAN.R-project.org/package=nichetools + url_git: https://github.com/benjaminhlina/nichetools +nichevol: + version: 0.1.20 + title: |- + Tools for Ecological Niche Evolution Assessment Considering + Uncertainty + maintainer: Marlon E. Cobos + description: |- + A collection of tools that allow users to perform critical steps + in the process of assessing ecological niche evolution over phylogenies, with + uncertainty incorporated explicitly in reconstructions. The method proposed + here for ancestral reconstruction of ecological niches characterizes species' + niches using a bin-based approach that incorporates uncertainty in estimations. + Compared to other existing methods, the approaches presented here reduce risk + of overestimation of amounts and rates of ecological niche evolution. The + main analyses include: initial exploration of environmental data in occurrence + records and accessible areas, preparation of data for phylogenetic analyses, + executing comparative phylogenetic analyses of ecological niches, and plotting + for interpretations. Details on the theoretical background and methods used + can be found in: Owens et al. (2020) , + Peterson et al. (1999) , + Soberón and Peterson (2005) , + Peterson (2011) , + Barve et al. (2011) , + Machado-Stredel et al. (2021) , + Owens et al. (2013) , + Saupe et al. (2018) , and + Cobos et al. (2021) . + date_publication: '2023-03-10' + bug_reports: https://github.com/marlonecobos/nichevol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nichevol + url_git: https://github.com/marlonecobos/nichevol +nieve: + version: 0.1.3 + title: Miscellaneous Utilities for Extreme Value Analysis + maintainer: Yves Deville + description: |- + Provides utility functions and objects for Extreme Value + Analysis. These include probability functions with their exact + derivatives w.r.t. the parameters that can be used for estimation + and inference, even with censored observations. The + transformations exchanging the two parameterizations of Peaks Over + Threshold (POT) models: Poisson-GP and Point-Process are also + provided with their derivatives. + date_publication: '2023-10-05' + bug_reports: https://github.com/yvesdeville/nieve/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=nieve + url_git: https://github.com/yvesdeville/nieve/ +nifti.io: + version: 1.0.0 + title: Read and Write NIfTI Files + maintainer: Timothy Koscik + description: |- + Tools for reading and writing NIfTI-1.1 (NII) files, including optimized voxelwise read/write operations and a simplified method to write dataframes to NII. + Specification of the NIfTI-1.1 format can be found here . + Scientific publication first using these tools + Koscik TR, Man V, Jahn A, Lee CH, Cunningham WA (2020) "Decomposing the neural pathways in a simple, value-based choice." Neuroimage, 214, 116764. + date_publication: '2021-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nifti.io + url_git: '' +nifti.pbcor: + version: '1.0' + title: Parcel-Based Correlation Between NIfTI Images + maintainer: Joaquim Radua + description: Estimate the correlation between two NIfTI images across random parcellations + of the images (Fortea et al., under review). This approach overcomes the problems + of both voxel-based correlations (neighbor voxels may be spatially dependent) + and atlas-based correlations (the correlation may depend on the atlas used). + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nifti.pbcor + url_git: '' +NightDay: + version: 1.0.1.1 + title: Night and Day Boundary Plot Function + maintainer: Max Hughes-Brandl + description: Computes and plots the boundary between night and day. + date_publication: '2018-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NightDay + url_git: '' +nilde: + version: 1.1-7 + title: |- + Nonnegative Integer Solutions of Linear Diophantine Equations + with Applications + maintainer: Natalya Pya Arnqvist + description: Routines for enumerating all existing nonnegative integer solutions + of a linear Diophantine equation. The package provides routines for solving 0-1, + bounded and unbounded knapsack problems; 0-1, bounded and unbounded subset sum + problems; additive partitioning of natural numbers; and one-dimensional bin-packing + problem. + date_publication: '2022-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nilde + url_git: '' +NiLeDAM: + version: '0.3' + title: Monazite Dating for the NiLeDAM Team + maintainer: Nathalie Vialaneix + description: |- + Th-U-Pb electron microprobe age dating of monazite, as originally + described in . + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NiLeDAM + url_git: '' +nima: + version: 0.6.2 + title: Nima Hejazi's R Toolbox + maintainer: Nima Hejazi + description: |- + Miscellaneous R functions developed as collateral damage over the + course of work in statistical and scientific computing for research. These + include, for example, utilities that supplement existing idiosyncrasies of + the R language, extend existing plotting functionality and aesthetics, help + prepare data objects for imputation, and extend access to command line tools + and systems-level information. + date_publication: '2020-03-06' + bug_reports: https://github.com/nhejazi/nima/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nima + url_git: https://github.com/nhejazi/nima +NIMAA: + version: 0.2.1 + title: Nominal Data Mining Analysis + maintainer: Mohieddin Jafari + description: 'Functions for nominal data mining based on bipartite graphs, which + build a pipeline for analysis and missing values imputation. Methods are mainly + from the paper: Jafari, Mohieddin, et al. (2021) , + some new ones are also included.' + date_publication: '2022-04-11' + bug_reports: https://github.com/jafarilab/NIMAA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NIMAA + url_git: https://github.com/jafarilab/NIMAA +nimble: + version: 1.3.0 + title: MCMC, Particle Filtering, and Programmable Hierarchical Modeling + maintainer: Christopher Paciorek + description: |- + A system for writing hierarchical statistical models largely + compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models + and do basic R-style math, and compiling both models and nimbleFunctions via + custom-generated C++. 'NIMBLE' includes default methods for MCMC, Laplace + Approximation, Monte Carlo Expectation Maximization, and some other tools. + The nimbleFunction system makes it easy to do things like implement new MCMC + samplers from R, customize the assignment of samplers to different parts of + a model from R, and compile the new samplers automatically via C++ alongside + the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language + by making it extensible: New distributions and functions can be added, + including as calls to external compiled code. Although most people think + of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, + one can use 'NIMBLE' for writing arbitrary other kinds of model-generic + algorithms as well. A full User Manual is available at . + date_publication: '2024-12-17' + bug_reports: https://github.com/nimble-dev/nimble/issues + url: https://r-nimble.org + url_cran: https://CRAN.R-project.org/package=nimble + url_git: https://github.com/nimble-dev/nimble +nimbleAPT: + version: 1.0.7 + title: Adaptive Parallel Tempering for 'NIMBLE' + maintainer: David Pleydell + description: Functions for adaptive parallel tempering (APT) with NIMBLE models. + Adapted from 'Lacki' & 'Miasojedow' (2016) and + 'Miasojedow, Moulines and Vihola' (2013) . + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nimbleAPT + url_git: https://github.com/DRJP/nimbleAPT +nimbleCarbon: + version: 0.2.5 + title: Bayesian Analyses of Radiocarbon Dates with NIMBLE + maintainer: Enrico Crema + description: Provides utility functions and custom probability distribution for + Bayesian analyses of radiocarbon dates within the 'nimble' modelling framework. It + includes various population growth models, nimbleFunction objects, as well as + a suite of functions for prior and posterior predictive checks for demographic + inference (Crema and Shoda (2021) ) and other + analyses. + date_publication: '2023-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nimbleCarbon + url_git: '' +nimbleEcology: + version: 0.5.0 + title: Distributions for Ecological Models in 'nimble' + maintainer: Benjamin R. Goldstein + description: |- + Common ecological distributions for 'nimble' models in the form of nimbleFunction objects. + Includes Cormack-Jolly-Seber, occupancy, dynamic occupancy, hidden Markov, dynamic hidden Markov, and N-mixture models. + (Jolly (1965) , Seber (1965) , Turek et al. (2016) ). + date_publication: '2024-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nimbleEcology + url_git: https://github.com/nimble-dev/nimbleEcology +nimbleHMC: + version: 0.2.3 + title: |- + Hamiltonian Monte Carlo and Other Gradient-Based MCMC Sampling + Algorithms for 'nimble' + maintainer: Daniel Turek + description: Provides gradient-based MCMC sampling algorithms for use with the MCMC + engine provided by the 'nimble' package. This includes two versions of Hamiltonian + Monte Carlo (HMC) No-U-Turn (NUTS) sampling, and (under development) Langevin + samplers. The `NUTS_classic` sampler implements the original HMC-NUTS algorithm + as described in Hoffman and Gelman (2014) . The + `NUTS` sampler is a modern version of HMC-NUTS sampling matching the HMC sampler + available in version 2.32.2 of Stan (Stan Development Team, 2023). In addition, + convenience functions are provided for generating and modifying MCMC configuration + objects which employ HMC sampling. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nimbleHMC + url_git: '' +nimbleNoBounds: + version: 1.0.3 + title: Transformed Distributions for Improved MCMC Efficiency + maintainer: David Pleydell + description: A collection of common univariate bounded probability distributions + transformed to the unbounded real line, for the purpose of increased MCMC efficiency. + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nimbleNoBounds + url_git: https://github.com/DRJP/nimbleNoBounds +nimbleSCR: + version: 0.2.1 + title: Spatial Capture-Recapture (SCR) Methods Using 'nimble' + maintainer: Daniel Turek + description: Provides utility functions, distributions, and fitting methods for + Bayesian Spatial Capture-Recapture (SCR) and Open Population Spatial Capture-Recapture + (OPSCR) modelling using the nimble package (de Valpine et al. 2017 ). Development of the package was motivated primarily by the need for flexible + and efficient analysis of large-scale SCR data (Bischof et al. 2020 ). Computational methods and techniques implemented in nimbleSCR include those + discussed in Turek et al. 2021 ; among others. For a recent + application of nimbleSCR, see Milleret et al. (2021) . + date_publication: '2022-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nimbleSCR + url_git: '' +nimbleSMC: + version: 0.11.1 + title: Sequential Monte Carlo Methods for 'nimble' + maintainer: Christopher Paciorek + description: |- + Includes five particle filtering algorithms for use with state space + models in the 'nimble' system: 'Auxiliary', 'Bootstrap', 'Ensemble Kalman filter', + 'Iterated Filtering 2', and 'Liu-West', as described in Michaud et al. (2021), + . A full User Manual is available at + . + date_publication: '2024-06-14' + bug_reports: '' + url: https://r-nimble.org + url_cran: https://CRAN.R-project.org/package=nimbleSMC + url_git: https://github.com/nimble-dev/nimbleSMC +nipals: + version: '1.0' + title: |- + Principal Components Analysis using NIPALS or Weighted EMPCA, + with Gram-Schmidt Orthogonalization + maintainer: Kevin Wright + description: |- + Principal Components Analysis of a matrix using Non-linear + Iterative Partial Least Squares or weighted Expectation Maximization + PCA with Gram-Schmidt orthogonalization of the scores and loadings. + Optimized for speed. See Andrecut (2009) . + date_publication: '2024-12-02' + bug_reports: https://github.com/kwstat/nipals/issues + url: https://kwstat.github.io/nipals/ + url_cran: https://CRAN.R-project.org/package=nipals + url_git: '' +nipnTK: + version: 0.2.0 + title: |- + National Information Platforms for Nutrition Anthropometric Data + Toolkit + maintainer: Ernest Guevarra + description: |- + An implementation of the National Information Platforms for + Nutrition or NiPN's analytic methods for assessing quality of anthropometric + datasets that include measurements of weight, height or length, middle upper + arm circumference, sex and age. The focus is on anthropometric status but + many of the presented methods could be applied to other variables. + date_publication: '2024-04-06' + bug_reports: https://github.com/nutriverse/nipnTK/issues + url: https://nutriverse.io/nipnTK/ + url_cran: https://CRAN.R-project.org/package=nipnTK + url_git: https://github.com/nutriverse/nipnTK +NipponMap: + version: '0.2' + title: Japanese Map Data and Functions + maintainer: Susumu Tanimura + description: Digital map data of Japan for choropleth mapping, including a circle + cartogram. + date_publication: '2018-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NipponMap + url_git: '' +NIPTeR: + version: 1.0.2 + title: |- + Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal + Testing + maintainer: Lennart Johansson + description: |- + Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal + Testing. + date_publication: '2016-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NIPTeR + url_git: '' +NIRStat: + version: '1.1' + title: |- + Novel Statistical Methods for Studying Near-Infrared + Spectroscopy (NIRS) Time Series Data + maintainer: Yikai Wang + description: 'Provides transfusion-related differential tests on Near-infrared spectroscopy + (NIRS) time series with detection limit, which contains two testing statistics: + Mean Area Under the Curve (MAUC) and slope statistic. This package applied a penalized + spline method within imputation setting. Testing is conducted by a nested permutation + approach within imputation. Refer to Guo et al (2018) + for further details.' + date_publication: '2020-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NIRStat + url_git: '' +NISTnls: + version: 0.9-13 + title: Nonlinear least squares examples from NIST + maintainer: Douglas Bates + description: Datasets for testing nonlinear regression routines. + date_publication: '2012-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NISTnls + url_git: '' +NISTunits: + version: 1.0.1 + title: Fundamental Physical Constants and Unit Conversions from NIST + maintainer: Jose Gama + description: |- + Fundamental physical constants (Quantity, Value, Uncertainty, Unit) for + SI (International System of Units) and non-SI units, plus unit conversions + Based on the data from NIST (National Institute of Standards and Technology, USA) + date_publication: '2016-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NISTunits + url_git: '' +NitrogenUptake2016: + version: 0.2.3 + title: |- + Data and Source Code From: Nitrogen Uptake and Allocation + Estimates for Spartina Alterniflora and Distichlis Spicata + maintainer: Troy D. Hill + description: 'Contains data, code, and figures from Hill et al. 2018a (Journal of + Experimental Marine Biology and Ecology; ) and + Hill et al. 2018b (Data In Brief ). Datasets document + plant allometry, stem heights, nutrient and stable isotope content, and sediment + denitrification enzyme assays. The data and analysis offer an examination of nitrogen + uptake and allocation in two salt marsh plant species.' + date_publication: '2018-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NitrogenUptake2016 + url_git: https://github.com/troyhill/NitrogenUptake2016 +nivm: + version: '0.5' + title: Noninferiority Tests with Variable Margins + maintainer: Michael P. Fay + description: Noninferiority tests for difference in failure rates at a prespecified + control rate or prespecified time. For details, see Fay and Follmann, 2016 . + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nivm + url_git: '' +nixmass: + version: 1.0.2 + title: |- + Snow Water Equivalent Modeling with the 'Delta.snow' Model and + Empirical Regression Models + maintainer: Harald Schellander + description: Snow water equivalent is modeled with the process based 'delta.snow' + model and empirical regression models using relationships between density and + diverse at-site parameters. The methods are described in Winkler et al. (2021) + , Guyennon et al. (2019) , + Pistocchi (2016) , Jonas et al. (2009) + and Sturm et al. (2010) . + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nixmass + url_git: '' +nixtlar: + version: 0.6.2 + title: A Software Development Kit for 'Nixtla''s 'TimeGPT' + maintainer: Mariana Menchero + description: |- + A Software Development Kit for working with 'Nixtla''s 'TimeGPT', a foundation + model for time series forecasting. 'API' is an acronym for 'application + programming interface'; this package allows users to interact with + 'TimeGPT' via the 'API'. You can set and validate 'API' keys and generate forecasts + via 'API' calls. It is compatible with 'tsibble' and base R. For more details + visit . + date_publication: '2024-10-28' + bug_reports: https://github.com/Nixtla/nixtlar/issues + url: https://nixtla.github.io/nixtlar/ + url_cran: https://CRAN.R-project.org/package=nixtlar + url_git: https://github.com/Nixtla/nixtlar +njgeo: + version: 0.1.0 + title: |- + Tools for Geocoding Addresses in New Jersey using the 'NJOGIS' + API + maintainer: Gavin Rozzi + description: Provides an R interface to free geocoding REST APIs maintained by the + New Jersey Office of GIS + and commonly used shapefiles. + date_publication: '2022-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=njgeo + url_git: '' +nJira: + version: 0.1.1 + title: SQL Like Query Interface for 'Jira' + maintainer: Nikhil Choudhry + description: 'SQL like query interface to fetch data from any ''Jira'' installation. + The data is fetched using ''Jira'' REST API, which can be found at the following + URL: .' + date_publication: '2020-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nJira + url_git: '' +njtr1: + version: 0.3.2 + title: Download, Analyze & Clean New Jersey Car Crash Data + maintainer: Gavin Rozzi + description: |- + Download and analyze motor vehicle crash data released by the New Jersey Department of Transportation (NJDOT). + The data in this package is collected through the filing of NJTR-1 form by police officers, which provide a standardized way of documenting a motor vehicle crash that occurred in New Jersey. + 3 different data tables containing data on crashes, vehicles & pedestrians released from 2001 to the present can be downloaded & cleaned using this package. + date_publication: '2022-04-28' + bug_reports: https://github.com/gavinrozzi/njtr1/issues/ + url: https://gavinrozzi.github.io/njtr1/ + url_cran: https://CRAN.R-project.org/package=njtr1 + url_git: https://github.com/gavinrozzi/njtr1/ +NlcOptim: + version: '0.6' + title: Solve Nonlinear Optimization with Nonlinear Constraints + maintainer: Xianyan Chen + description: Optimization for nonlinear objective and constraint functions. Linear + or nonlinear equality and inequality constraints are allowed. It accepts the + input parameters as a constrained matrix. + date_publication: '2019-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NlcOptim + url_git: '' +nlcv: + version: 0.3.5 + title: Nested Loop Cross Validation + maintainer: Laure Cougnaud + description: |- + Nested loop cross validation for classification purposes for misclassification error rate estimation. + The package supports several methodologies for feature selection: random forest, Student t-test, limma, + and provides an interface to the following classification methods in the 'MLInterfaces' package: linear, + quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized + linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of + the classifier are included: plot of the ranks of the features, scores plot for a specific + classification algorithm and number of features, misclassification rate + for the different number of features and classification algorithms tested and ROC plot. + For further details about the methodology, please check: + Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004) + . + date_publication: '2018-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlcv + url_git: '' +nleqslv: + version: 3.3.5 + title: Solve Systems of Nonlinear Equations + maintainer: Berend Hasselman + description: |- + Solve a system of nonlinear equations using a Broyden or a Newton method + with a choice of global strategies such as line search and trust region. + There are options for using a numerical or user supplied Jacobian, + for specifying a banded numerical Jacobian and for allowing + a singular or ill-conditioned Jacobian. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nleqslv + url_git: '' +nlgm: + version: '1.0' + title: Non Linear Growth Models + maintainer: Michail Tsagris + description: 'Six growth models are fitted using non-linear least squares. These + are the Richards, the 3, 4 and 5 parameter logistic, the Gompetz and the Weibull + growth models. Reference: Reddy T., Shkedy Z., van Rensburg C. J., Mwambi H., + Debba P., Zuma K. and Manda, S. (2021). "Short-term real-time prediction of total + number of reported COVID-19 cases and deaths in South Africa: a data driven approach". + BMC medical research methodology, 21(1), 1-11. .' + date_publication: '2022-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlgm + url_git: '' +NlinTS: + version: 1.4.5 + title: Models for Non Linear Causality Detection in Time Series + maintainer: Youssef Hmamouche + description: Models for non-linear time series analysis and causality detection. + The main functionalities of this package consist of an implementation of the classical + causality test (C.W.J.Granger 1980) , and a + non-linear version of it based on feed-forward neural networks. This package contains + also an implementation of the Transfer Entropy , + and the continuous Transfer Entropy using an approximation based on the k-nearest + neighbors . There are also some other useful tools, + like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented + test of stationarity, and the discrete and continuous entropy and mutual information. + date_publication: '2021-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NlinTS + url_git: '' +nlist: + version: 0.3.3 + title: Lists of Numeric Atomic Objects + maintainer: Joe Thorley + description: |- + Create and manipulate numeric list ('nlist') objects. An + 'nlist' is an S3 list of uniquely named numeric objects. An numeric + object is an integer or double vector, matrix or array. An 'nlists' + object is a S3 class list of 'nlist' objects with the same names, + dimensionalities and typeofs. Numeric list objects are of interest + because they are the raw data inputs for analytic engines such as + 'JAGS', 'STAN' and 'TMB'. Numeric lists objects, which are useful for + storing multiple realizations of of simulated data sets, can be + converted to coda::mcmc and coda::mcmc.list objects. + date_publication: '2021-09-02' + bug_reports: https://github.com/poissonconsulting/nlist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlist + url_git: https://github.com/poissonconsulting/nlist +nlive: + version: 0.7.0 + title: |- + Automated Estimation of Sigmoidal and Piecewise Linear Mixed + Models + maintainer: Maude Wagner + description: Estimation of relatively complex nonlinear mixed-effects models, including + the Sigmoidal Mixed Model and the Piecewise Linear Mixed Model with abrupt or + smooth transition, through a single intuitive line of code and with automated + generation of starting values. + date_publication: '2025-02-15' + bug_reports: https://github.com/MaudeWagner/nlive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlive + url_git: https://github.com/MaudeWagner/nlive +nlme: + version: 3.1-167 + title: Linear and Nonlinear Mixed Effects Models + maintainer: R Core Team + description: Fit and compare Gaussian linear and nonlinear mixed-effects models. + date_publication: '2025-01-27' + bug_reports: https://bugs.r-project.org + url: '' + url_cran: https://CRAN.R-project.org/package=nlme + url_git: '' +nlmeU: + version: 0.70-9 + title: |- + Datasets and Utility Functions Enhancing Functionality of 'nlme' + Package + maintainer: Andrzej Galecki + description: |- + Datasets and utility functions enhancing functionality of nlme package. Datasets, functions and scripts are described in book titled 'Linear Mixed-Effects Models: + A Step-by-Step Approach' by Galecki and Burzykowski (2013). Package is under development. + date_publication: '2022-05-02' + bug_reports: '' + url: http://www-personal.umich.edu/~agalecki/ + url_cran: https://CRAN.R-project.org/package=nlmeU + url_git: '' +nlmeVPC: + version: '2.6' + title: Visual Model Checking for Nonlinear Mixed Effect Model + maintainer: Eun-Kyung Lee + description: Various visual and numerical diagnosis methods for the nonlinear mixed + effect model, including visual predictive checks, numerical predictive checks, + and coverage plots (Karlsson and Holford, 2008, ). + date_publication: '2022-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlmeVPC + url_git: '' +nlmixr2: + version: 3.0.2 + title: Nonlinear Mixed Effects Models in Population PK/PD + maintainer: Matthew Fidler + description: |- + Fit and compare nonlinear mixed-effects models in differential + equations with flexible dosing information commonly seen in pharmacokinetics + and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 + ). Differential equation solving is + by compiled C code provided in the 'rxode2' package + (Wang, Hallow, and James 2015 ). + date_publication: '2025-02-20' + bug_reports: https://github.com/nlmixr2/nlmixr2/issues/ + url: https://nlmixr2.org/ + url_cran: https://CRAN.R-project.org/package=nlmixr2 + url_git: https://github.com/nlmixr2/nlmixr2/ +nlmixr2data: + version: 2.0.9 + title: Nonlinear Mixed Effects Models in Population PK/PD, Data + maintainer: Matthew Fidler + description: |- + Datasets for 'nlmixr2' and 'rxode2'. 'nlmixr2' is used for fitting and comparing + nonlinear mixed-effects models in differential + equations with flexible dosing information commonly seen in pharmacokinetics + and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 + ). Differential equation solving is + by compiled C code provided in the 'rxode2' package + (Wang, Hallow, and James 2015 ). + date_publication: '2024-01-31' + bug_reports: https://github.com/nlmixr2/nlmixr2data/issues/ + url: https://nlmixr2.github.io/nlmixr2data/ + url_cran: https://CRAN.R-project.org/package=nlmixr2data + url_git: https://github.com/nlmixr2/nlmixr2data/ +nlmixr2est: + version: 3.0.4 + title: |- + Nonlinear Mixed Effects Models in Population PK/PD, Estimation + Routines + maintainer: Matthew Fidler + description: |- + Fit and compare nonlinear mixed-effects models in + differential equations with flexible dosing information commonly seen + in pharmacokinetics and pharmacodynamics (Almquist, Leander, and + Jirstrand 2015 ). Differential equation + solving is by compiled C code provided in the 'rxode2' package (Wang, + Hallow, and James 2015 ). + date_publication: '2025-02-19' + bug_reports: '' + url: https://nlmixr2.github.io/nlmixr2est/ + url_cran: https://CRAN.R-project.org/package=nlmixr2est + url_git: https://github.com/nlmixr2/nlmixr2est +nlmixr2extra: + version: 3.0.2 + title: |- + Nonlinear Mixed Effects Models in Population PK/PD, Extra + Support Functions + maintainer: Matthew Fidler + description: |- + Fit and compare nonlinear mixed-effects models in + differential equations with flexible dosing information commonly seen + in pharmacokinetics and pharmacodynamics (Almquist, Leander, and + Jirstrand 2015 ). Differential equation + solving is by compiled C code provided in the 'rxode2' package (Wang, + Hallow, and James 2015 ). This package is for + support functions like preconditioned fits + , boostrap and stepwise covariate + selection. + date_publication: '2025-02-17' + bug_reports: https://github.com/nlmixr2/nlmixr2extra/issues/ + url: https://nlmixr2.github.io/nlmixr2extra/ + url_cran: https://CRAN.R-project.org/package=nlmixr2extra + url_git: https://github.com/nlmixr2/nlmixr2extra/ +nlmixr2lib: + version: 0.3.0 + title: A Model Library for 'nlmixr2' + maintainer: Bill Denney + description: |- + A model library for 'nlmixr2'. The models include + (and plan to include) pharmacokinetic, pharmacodynamic, and + disease models used in pharmacometrics. Where applicable, + references for each model are included in the meta-data for + each individual model. The package also includes model + composition and modification functions to make model updates + easier. + date_publication: '2024-10-07' + bug_reports: '' + url: https://nlmixr2.github.io/nlmixr2lib/ + url_cran: https://CRAN.R-project.org/package=nlmixr2lib + url_git: https://github.com/nlmixr2/nlmixr2lib +nlmixr2plot: + version: 3.0.1 + title: |- + Nonlinear Mixed Effects Models in Population PK/PD, Plot + Functions + maintainer: Matthew Fidler + description: |- + Fit and compare nonlinear mixed-effects models in + differential equations with flexible dosing information commonly seen + in pharmacokinetics and pharmacodynamics (Almquist, Leander, and + Jirstrand 2015 ). Differential equation + solving is by compiled C code provided in the 'rxode2' package (Wang, + Hallow, and James 2015 ). This package is for + 'ggplot2' plotting methods for 'nlmixr2' objects. + date_publication: '2025-02-14' + bug_reports: https://github.com/nlmixr2/nlmixr2plot/issues/ + url: https://nlmixr2.github.io/nlmixr2plot/ + url_cran: https://CRAN.R-project.org/package=nlmixr2plot + url_git: https://github.com/nlmixr2/nlmixr2plot +nlmixr2rpt: + version: 0.2.0 + title: |- + Templated Word and PowerPoint Reporting of 'nlmixr2' Fitting + Results + maintainer: John Harrold + description: This allows you to generate reporting workflows around 'nlmixr2' analyses + with outputs in Word and PowerPoint. You can specify figures, tables and report + structure in a user-definable 'YAML' file. Also you can use the internal functions + to access the figures and tables to allow their including in other outputs (e.g. + R Markdown). + date_publication: '2023-06-06' + bug_reports: https://github.com/nlmixr2/nlmixr2rpt/issues + url: https://nlmixr2.github.io/nlmixr2rpt/ + url_cran: https://CRAN.R-project.org/package=nlmixr2rpt + url_git: '' +nlmm: + version: 1.1.0 + title: Generalized Laplace Mixed-Effects Models + maintainer: Marco Geraci + description: |- + Provides functions to fit linear mixed models + based on convolutions of the generalized Laplace (GL) distribution. + The GL mixed-effects model includes four special cases with normal random + effects and normal errors (NN), normal random effects and Laplace errors (NL), + Laplace random effects and normal errors (LN), and Laplace random effects + and Laplace errors (LL). The methods are described in Geraci and Farcomeni (2020, + Statistical Methods in Medical Research) . + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlmm + url_git: '' +nlmrt: + version: 2016.3.2 + title: Functions for Nonlinear Least Squares Solutions + maintainer: John C. Nash + description: |- + Replacement for nls() tools for working with nonlinear least squares problems. + The calling structure is similar to, but much simpler than, that of the nls() + function. Moreover, where nls() specifically does NOT deal with small or zero + residual problems, nlmrt is quite happy to solve them. It also attempts to be + more robust in finding solutions, thereby avoiding 'singular gradient' messages + that arise in the Gauss-Newton method within nls(). The Marquardt-Nash approach + in nlmrt generally works more reliably to get a solution, though this may be + one of a set of possibilities, and may also be statistically unsatisfactory. + Added print and summary as of August 28, 2012. + date_publication: '2016-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlmrt + url_git: '' +nlMS: + version: '1.1' + title: Non-Linear Model Selection + maintainer: Carme Font + description: 'Package to select best model among several linear and nonlinear models. + The main function uses the gnls() function from the ''nlme'' package to fit the + data to nine regression models, named: "linear", "quadratic", "cubic", "logistic", + "exponential", "power", "monod", "haldane", "logit".' + date_publication: '2019-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlMS + url_git: '' +nlnet: + version: '1.4' + title: |- + Nonlinear Network, Clustering, and Variable Selection Based on + DCOL + maintainer: Tianwei Yu + description: 'It includes four methods: DCOL-based K-profiles clustering, non-linear + network reconstruction, non-linear hierarchical clustering, and variable selection + for generalized additive model. References: Tianwei Yu (2018); + Haodong Liu and others (2016); Kai Wang and + others (2015); Tianwei Yu and others (2010).' + date_publication: '2020-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlnet + url_git: '' +nlopt: + version: 0.1.1 + title: Call Optimization Solvers with .nl Files + maintainer: Brais Gonzalez-Rodriguez + description: The purpose of this library is to to call different optimization solvers + (such as Gonzalez Rodriguez et al. (2022) , Tawarmalani + and Sahinidis (2005) , and Byrd et al. (2006) ) + to solve problems given by a standard nl file. + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlopt + url_git: '' +nloptr: + version: 2.1.1 + title: R Interface to NLopt + maintainer: Aymeric Stamm + description: |- + Solve optimization problems using an R interface to NLopt. NLopt is a + free/open-source library for nonlinear optimization, providing a common + interface for a number of different free optimization routines available + online as well as original implementations of various other algorithms. + See for more + information on the available algorithms. Building from included sources + requires 'CMake'. On Linux and 'macOS', if a suitable system build of + NLopt (2.7.0 or later) is found, it is used; otherwise, it is built + from included sources via 'CMake'. On Windows, NLopt is obtained through + 'rwinlib' for 'R <= 4.1.x' or grabbed from the appropriate toolchain for + 'R >= 4.2.0'. + date_publication: '2024-06-25' + bug_reports: https://github.com/astamm/nloptr/issues + url: https://astamm.github.io/nloptr/ + url_cran: https://CRAN.R-project.org/package=nloptr + url_git: https://github.com/astamm/nloptr +NLP: + version: 0.3-2 + title: Natural Language Processing Infrastructure + maintainer: Kurt Hornik + description: Basic classes and methods for Natural Language Processing. + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NLP + url_git: '' +NLPclient: + version: '1.0' + title: Stanford 'CoreNLP' Annotation Client + maintainer: Florian Schwendinger + description: |- + Stanford 'CoreNLP' annotation client. + Stanford 'CoreNLP' integrates all + NLP tools from the Stanford Natural Language Processing Group, + including a part-of-speech (POS) tagger, a named entity recognizer (NER), + a parser, and a coreference resolution system, and provides model files + for the analysis of English. More information can be found in the README. + date_publication: '2019-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NLPclient + url_git: '' +nlpembeds: + version: 1.0.0 + title: Natural Language Processing Embeddings + maintainer: Thomas Charlon + description: Provides efficient methods to compute co-occurrence matrices, pointwise + mutual information (PMI) and singular value decomposition (SVD). In the biomedical + and clinical settings, one challenge is the huge size of databases, e.g. when + analyzing data of millions of patients over tens of years. To address this, this + package provides functions to efficiently compute monthly co-occurrence matrices, + which is the computational bottleneck of the analysis, by using the 'RcppAlgos' + package and sparse matrices. Furthermore, the functions can be called on 'SQL' + databases, enabling the computation of co-occurrence matrices of tens of gigabytes + of data, representing millions of patients over tens of years. Partly based on + Hong C. (2021) . + date_publication: '2025-02-04' + bug_reports: https://gitlab.com/thomaschln/nlpembeds/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlpembeds + url_git: https://gitlab.com/thomaschln/nlpembeds +nlpred: + version: 1.0.1 + title: |- + Estimators of Non-Linear Cross-Validated Risks Optimized for + Small Samples + maintainer: David Benkeser + description: Methods for obtaining improved estimates of non-linear cross-validated + risks are obtained using targeted minimum loss-based estimation, estimating equations, + and one-step estimation (Benkeser, Petersen, van der Laan (2019), ). + Cross-validated area under the receiver operating characteristics curve (LeDell, + Petersen, van der Laan (2015), ) and other metrics are + included. + date_publication: '2020-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlpred + url_git: '' +nlpsem: + version: '0.3' + title: |- + Linear and Nonlinear Longitudinal Process in Structural Equation + Modeling Framework + maintainer: Jin Liu + description: 'Provides computational tools for nonlinear longitudinal models, in + particular the intrinsically nonlinear models, in four scenarios: (1) univariate + longitudinal processes with growth factors, with or without covariates including + time-invariant covariates (TICs) and time-varying covariates (TVCs); (2) multivariate + longitudinal processes that facilitate the assessment of correlation or causation + between multiple longitudinal variables; (3) multiple-group models for scenarios + (1) and (2) to evaluate differences among manifested groups, and (4) longitudinal + mixture models for scenarios (1) and (2), with an assumption that trajectories + are from multiple latent classes. The methods implemented are introduced in Jin + Liu (2023) .' + date_publication: '2023-09-12' + bug_reports: https://github.com/Veronica0206/nlpsem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlpsem + url_git: https://github.com/Veronica0206/nlpsem +NLPutils: + version: 0.0-5.1 + title: Natural Language Processing Utilities + maintainer: Kurt Hornik + description: Utilities for Natural Language Processing. + date_publication: '2023-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NLPutils + url_git: '' +NLPwavelet: + version: '1.0' + title: Bayesian Wavelet Analysis Using Non-Local Priors + maintainer: Nilotpal Sanyal + description: Performs Bayesian wavelet analysis using individual non-local priors + as described in Sanyal & Ferreira (2017) and non-local + prior mixtures as described in Sanyal (2025) . + date_publication: '2025-02-13' + bug_reports: https://github.com/nilotpalsanyal/NLPwavelet/issues + url: https://nilotpalsanyal.github.io/NLPwavelet/ + url_cran: https://CRAN.R-project.org/package=NLPwavelet + url_git: '' +nlraa: + version: 1.9.7 + title: Nonlinear Regression for Agricultural Applications + maintainer: Fernando Miguez + description: Additional nonlinear regression functions using self-start (SS) algorithms. + One of the functions is the Beta growth function proposed by Yin et al. (2003) + . There are several other functions with breakpoints (e.g. + linear-plateau, plateau-linear, exponential-plateau, plateau-exponential, quadratic-plateau, + plateau-quadratic and bilinear), a non-rectangular hyperbola and a bell-shaped + curve. Twenty eight (28) new self-start (SS) functions in total. This package + also supports the publication 'Nonlinear regression Models and applications in + agricultural research' by Archontoulis and Miguez (2015) , + a book chapter with similar material + and a publication by Oddi et. al. (2019) in Ecology and Evolution . + The function 'nlsLMList' uses 'nlsLM' for fitting, but it is otherwise almost + identical to 'nlme::nlsList'.In addition, this release of the package provides + functions for conducting simulations for 'nlme' and 'gnls' objects as well as + bootstrapping. These functions are intended to work with the modeling framework + of the 'nlme' package. It also provides four vignettes with extended examples. + date_publication: '2023-12-19' + bug_reports: https://github.com/femiguez/nlraa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlraa + url_git: '' +nlreg: + version: 1.2-2.2 + title: Higher Order Inference for Nonlinear Heteroscedastic Models + maintainer: Alessandra R. Brazzale + description: |- + Likelihood inference based on higher order approximations + for nonlinear models with possibly non constant variance. + date_publication: '2019-01-30' + bug_reports: '' + url: http://statwww.epfl.ch/AA/ + url_cran: https://CRAN.R-project.org/package=nlreg + url_git: '' +nlrr: + version: '0.1' + title: Non-Linear Relative Risk Estimation and Plotting + maintainer: Yiqiang Zhan + description: Estimate the non-linear odds ratio and plot it against a continuous + exposure. + date_publication: '2015-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlrr + url_git: '' +nlrx: + version: 0.4.5 + title: |- + Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via + 'XML' + maintainer: Sebastian Hanss + description: |- + Setup, run and analyze 'NetLogo' () model simulations in 'R'. + 'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments. + However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses. + The user defines all information that is needed in an intuitive framework, using class objects. + Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user. + By nesting model calls in future environments, large simulation design with many runs can be executed in parallel. + This also enables simulating 'NetLogo' experiments on remote high performance computing machines. + In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system. + date_publication: '2024-01-29' + bug_reports: https://github.com/ropensci/nlrx/issues/ + url: https://docs.ropensci.org/nlrx/ + url_cran: https://CRAN.R-project.org/package=nlrx + url_git: https://github.com/ropensci/nlrx/ +nls.multstart: + version: 2.0.0 + title: Robust Non-Linear Regression using AIC Scores + maintainer: Daniel Padfield + description: Non-linear least squares regression with the Levenberg-Marquardt algorithm + using multiple starting values for increasing the chance that the minimum found + is the global minimum. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nls.multstart + url_git: '' +nls2: + version: 0.3-4 + title: Non-Linear Regression with Brute Force + maintainer: G. Grothendieck + description: Adds brute force and multiple starting values to nls. + date_publication: '2024-07-14' + bug_reports: https://github.com/ggrothendieck/nls2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nls2 + url_git: https://github.com/ggrothendieck/nls2 +nlsem: + version: 0.8-1 + title: Fitting Structural Equation Mixture Models + maintainer: Nora Umbach + description: |- + Estimation of structural equation models with nonlinear effects + and underlying nonnormal distributions. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlsem + url_git: https://github.com/nwickel/nlsem +nlshrink: + version: 1.0.1 + title: |- + Non-Linear Shrinkage Estimation of Population Eigenvalues and + Covariance Matrices + maintainer: Pratik Ramprasad + description: |- + Non-linear shrinkage estimation of population eigenvalues and covariance + matrices, based on publications by Ledoit and Wolf (2004, 2015, 2016). + date_publication: '2016-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlshrink + url_git: '' +nlsic: + version: 1.0.4 + title: Non Linear Least Squares with Inequality Constraints + maintainer: Serguei Sokol + description: |- + We solve non linear least squares problems with optional + equality and/or inequality constraints. Non linear iterations are + globalized with back-tracking method. Linear problems are solved by + dense QR decomposition from 'LAPACK' which can limit the size of + treated problems. On the other side, we avoid condition number + degradation which happens in classical quadratic programming approach. + Inequality constraints treatment on each non + linear iteration is based on 'NNLS' method (by Lawson and Hanson). + We provide an original function 'lsi_ln' for solving linear least squares + problem with inequality constraints in least norm sens. Thus if Jacobian of + the problem is rank deficient a solution still can be provided. + However, truncation errors are probable in this case. + Equality constraints are treated by using a basis of Null-space. + User defined function calculating residuals must return a list having + residual vector (not their squared sum) and Jacobian. If Jacobian is + not in the returned list, package 'numDeriv' is used to calculated + finite difference version of Jacobian. The 'NLSIC' method was fist + published in Sokol et al. (2012) . + date_publication: '2023-06-26' + bug_reports: https://github.com/MathsCell/nlsic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlsic + url_git: https://github.com/MathsCell/nlsic +nlsMicrobio: + version: 1.0-0 + title: Nonlinear Regression in Predictive Microbiology + maintainer: Aurelie Siberchicot + description: Data sets and nonlinear regression models dedicated to predictive microbiology. + date_publication: '2024-02-13' + bug_reports: https://github.com/lbbe-software/nlsMicrobio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlsMicrobio + url_git: https://github.com/lbbe-software/nlsMicrobio +nlsmsn: + version: 0.0-6 + title: |- + Fitting Nonlinear Models with Scale Mixture of Skew-Normal + Distributions + maintainer: Marcos Prates + description: Fit univariate non-linear scale mixture of skew-normal(NL-SMSN) regression, + details in Garay, Lachos and Abanto-Valle (2011) + and Lachos, Bandyopadhyay and Garay (2011) . + date_publication: '2021-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlsmsn + url_git: '' +nlsr: + version: 2023.8.31 + title: Functions for Nonlinear Least Squares Solutions - Updated 2022 + maintainer: John C Nash + description: |- + Provides tools for working with nonlinear least squares problems. + For the estimation of models reliable and robust tools than nls(), where the + the Gauss-Newton method frequently stops with 'singular gradient' messages. + This is accomplished by using, where possible, analytic derivatives to compute + the matrix of derivatives and a stabilization of the solution of the estimation + equations. Tools for approximate or externally supplied derivative matrices + are included. Bounds and masks on parameters are handled properly. + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlsr + url_git: '' +nlstac: + version: 0.2.0 + title: An R Package for Fitting Separable Nonlinear Models + maintainer: Rafael Benitez + description: |- + Set of functions implementing the algorithm described in Fernandez + Torvisco et al. (2018) for fitting separable nonlinear regression curves. + See Fernandez Torvisco, Rodriguez-Arias Fernandez and Cabello Sanchez (2018) + . + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlstac + url_git: '' +nlstools: + version: 2.1-0 + title: Tools for Nonlinear Regression Analysis + maintainer: Aurelie Siberchicot + description: Several tools for assessing the quality of fit of a gaussian nonlinear + model are provided. + date_publication: '2024-02-13' + bug_reports: https://github.com/lbbe-software/nlstools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nlstools + url_git: https://github.com/lbbe-software/nlstools +NlsyLinks: + version: 2.2.2 + title: Utilities and Kinship Information for Research with the NLSY + maintainer: S. Mason Garrison + description: |- + Utilities and kinship information for behavior genetics and + developmental research using the National Longitudinal Survey of Youth + (NLSY; ). + date_publication: '2024-10-10' + bug_reports: https://github.com/nlsy-links/NlsyLinks/issues + url: https://nlsy-links.github.io/NlsyLinks/ + url_cran: https://CRAN.R-project.org/package=NlsyLinks + url_git: https://github.com/nlsy-links/NlsyLinks +nlt: + version: 2.2-1 + title: A Nondecimated Lifting Transform for Signal Denoising + maintainer: Matt Nunes + description: |- + Uses a modified lifting algorithm on which it builds the + nondecimated lifting transform. It has applications in wavelet + shrinkage. + date_publication: '2018-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlt + url_git: '' +nltm: + version: 1.4.5 + title: Non-Linear Transformation Models + maintainer: Mark Clements + description: |- + Fits a non-linear transformation model ('nltm') for + analyzing survival data, see Tsodikov (2003) . The + class of 'nltm' includes the following currently supported + models: Cox proportional hazard, proportional hazard cure, + proportional odds, proportional hazard - proportional hazard + cure, proportional hazard - proportional odds cure, Gamma + frailty, and proportional hazard - proportional odds. + date_publication: '2023-12-03' + bug_reports: https://github.com/mclements/nltm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nltm + url_git: https://github.com/mclements/nltm +nlts: + version: 1.0-2 + title: Nonlinear Time Series Analysis + maintainer: Ottar N. Bjornstad + description: R functions for (non)linear time series analysis with an emphasis on + nonparametric autoregression and order estimation, and tests for linearity / additivity. + date_publication: '2018-10-12' + bug_reports: '' + url: http://ento.psu.edu/directory/onb1 + url_cran: https://CRAN.R-project.org/package=nlts + url_git: '' +nLTT: + version: 1.4.9 + title: Calculate the NLTT Statistic + maintainer: Thijs Janzen + description: |- + Provides functions to calculate the normalised Lineage-Through- + Time (nLTT) statistic, given two phylogenetic trees. The nLTT statistic measures + the difference between two Lineage-Through-Time curves, where each curve is + normalised both in time and in number of lineages. + date_publication: '2023-08-21' + bug_reports: https://github.com/thijsjanzen/nLTT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nLTT + url_git: https://github.com/thijsjanzen/nLTT +nlWaldTest: + version: 1.1.3 + title: Wald Test of Nonlinear Restrictions and Nonlinear CI + maintainer: Oleh Komashko + description: |- + Wald Test for nonlinear restrictions on model parameters and confidence + intervals for nonlinear functions of parameters using delta-method. Applicable + after ANY model, provided parameters estimates and their covariance matrix are + available. + date_publication: '2016-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nlWaldTest + url_git: '' +NMA: + version: 1.4-3 + title: Network Meta-Analysis Based on Multivariate Meta-Analysis Models + maintainer: Hisashi Noma + description: Network meta-analysis tools based on contrast-based approach using + the multivariate meta-analysis and meta-regression models (Noma et al. (2023) + ). Standard analysis tools for network meta-analysis and meta-regression + (e.g., synthesis analysis, ranking analysis, and creating league table) are available + by simple commands. For inconsistency analyses, the local and global inconsistency + tests based on the Higgins' design-by-treatment interaction model can be applied. + Also, the side-splitting and the Jackson's random inconsistency model are available. + Standard graphical tools for network meta-analysis (e.g., network plot, ranked + forest plot, and transitivity analysis) can also be utilized. For the synthesis + analyses, the Noma-Hamura's improved REML (restricted maximum likelihood)-based + methods (Noma et al. (2023) ) are + adopted as the default methods. + date_publication: '2024-05-17' + bug_reports: '' + url: https://www.ism.ac.jp/~noma/file/software/NMA.r + url_cran: https://CRAN.R-project.org/package=NMA + url_git: '' +NMADiagT: + version: 0.1.2 + title: Network Meta-Analysis of Multiple Diagnostic Tests + maintainer: Boyang Lu + description: |- + Implements HSROC (hierarchical summary receiver operating characteristic) model developed by Ma, Lian, Chu, Ibrahim, and Chen (2018) + and hierarchical model developed by Lian, Hodges, and Chu (2019) for performing meta-analysis for 1-5 diagnostic tests to simultaneously + compare multiple tests within a missing data framework. This package evaluates the accuracy of + multiple diagnostic tests and also gives graphical representation of the results. + date_publication: '2020-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMADiagT + url_git: '' +nmaINLA: + version: 1.1.0 + title: |- + Network Meta-Analysis using Integrated Nested Laplace + Approximations + maintainer: Burak Kuersad Guenhan + description: |- + Performs network meta-analysis using integrated nested Laplace approximations ('INLA') + which is described in Guenhan, Held, and Friede (2018) . + Includes methods to assess the heterogeneity and inconsistency in the network. + Contains more than ten different network meta-analysis dataset. + 'INLA' package can be obtained from . + date_publication: '2021-07-21' + bug_reports: https://github.com/gunhanb/nmaINLA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nmaINLA + url_git: https://github.com/gunhanb/nmaINLA +NMAoutlier: + version: 0.2.0 + title: Detecting Outliers in Network Meta-Analysis + maintainer: Maria Petropoulou + description: |- + A set of functions providing several outlier (i.e., studies with extreme findings) and influential detection measures and methodologies in network meta-analysis : + - simple outlier and influential detection measures + - outlier and influential detection measures by considering study deletion (shift the mean) + - plots for outlier and influential detection measures + - Q-Q plot for network meta-analysis + - Forward Search algorithm in network meta-analysis. + - forward plots to monitor statistics in each step of the forward search algorithm + - forward plots for summary estimates and their confidence intervals in each step of forward search algorithm. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMAoutlier + url_git: https://github.com/petropouloumaria/NMAoutlier +nmaplateplot: + version: 1.0.2 + title: The Plate Plot for Network Meta-Analysis Results + maintainer: Zhenxun Wang + description: |- + A graphical display of results from network meta-analysis (NMA). + It is suitable for outcomes like odds ratio (OR), risk ratio (RR), + risk difference (RD) and standardized mean difference (SMD). + It also has an option to visually display and compare + the surface under the cumulative ranking (SUCRA) of different treatments. + date_publication: '2024-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nmaplateplot + url_git: '' +nmarank: + version: 0.3-0 + title: Complex Hierarchy Questions in Network Meta-Analysis + maintainer: Theodoros Papakonstantinou + description: Derives the most frequent hierarchies along with their probability + of occurrence. One can also define complex hierarchy criteria and calculate their + probability. Methodology based on Papakonstantinou et al. (2021) . + date_publication: '2023-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nmarank + url_git: https://github.com/tpapak/nmarank +nmathresh: + version: 0.1.6 + title: Thresholds and Invariant Intervals for Network Meta-Analysis + maintainer: David Phillippo + description: |- + Calculation and presentation of decision-invariant bias adjustment + thresholds and intervals for Network Meta-Analysis, as described by + Phillippo et al. (2018) . These describe the + smallest changes to the data that would result in a change of decision. + date_publication: '2020-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nmathresh + url_git: '' +NMcalc: + version: 0.0.4 + title: Basic Calculations for PK/PD Modeling + maintainer: Philip Delff + description: Essentials for PK/PD (pharmacokinetics/pharmacodynamics) such as area + under the curve, (geometric) coefficient of variation, and other calculations + that are not part of base R. This is not a noncompartmental analysis (NCA) package. + date_publication: '2024-08-26' + bug_reports: https://github.com/philipdelff/NMdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NMcalc + url_git: '' +NMdata: + version: 0.1.9 + title: |- + Preparation, Checking and Post-Processing Data for PK/PD + Modeling + maintainer: Philip Delff + description: Efficient tools for preparation, checking and post-processing of data + in PK/PD (pharmacokinetics/pharmacodynamics) modeling, with focus on use of Nonmem. + Attention is paid to ensure consistency, traceability, and Nonmem compatibility + of Data. Rigorously checks final Nonmem datasets. Implemented in 'data.table', + but easily integrated with 'base' and 'tidyverse'. + date_publication: '2025-01-24' + bug_reports: https://github.com/nmautoverse/NMdata/issues + url: https://nmautoverse.github.io/NMdata/ + url_cran: https://CRAN.R-project.org/package=NMdata + url_git: '' +NMF: + version: '0.28' + title: |- + Algorithms and Framework for Nonnegative Matrix Factorization + (NMF) + maintainer: Nicolas Sauwen + description: |- + Provides a framework to perform Non-negative Matrix + Factorization (NMF). The package implements a set of already published algorithms + and seeding methods, and provides a framework to test, develop and plug + new/custom algorithms. Most of the built-in algorithms have been optimized + in C++, and the main interface function provides an easy way of performing + parallel computations on multicore machines. + date_publication: '2024-08-22' + bug_reports: '' + url: http://renozao.github.io/NMF/ + url_cran: https://CRAN.R-project.org/package=NMF + url_git: '' +nmfbin: + version: 0.2.1 + title: Non-Negative Matrix Factorization for Binary Data + maintainer: Michal Ovadek + description: Factorize binary matrices into rank-k components using the logistic + function in the updating process. See e.g. Tomé et al (2015) + . + date_publication: '2023-09-21' + bug_reports: '' + url: https://michalovadek.github.io/nmfbin/ + url_cran: https://CRAN.R-project.org/package=nmfbin + url_git: '' +NMFN: + version: 2.0.1 + title: Non-Negative Matrix Factorization + maintainer: Suhai (Timothy) Liu + description: Non-negative Matrix Factorization. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMFN + url_git: '' +NMI: + version: '2.0' + title: Normalized Mutual Information of Community Structure in Network + maintainer: Tianhao Wu + description: Calculates the normalized mutual information (NMI) of two community + structures in network analysis. + date_publication: '2016-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMI + url_git: '' +Nmisc: + version: 0.3.7 + title: Miscellaneous Functions Used at 'Numeract LLC' + maintainer: Mike Badescu + description: |- + Contains functions useful for debugging, set operations on vectors, + and 'UTC' date and time functionality. It adds a few vector manipulation + verbs to 'purrr' and 'dplyr' packages. It can also generate an R file to + install and update packages to simplify deployment into production. The + functions were developed at the data science firm 'Numeract LLC' and are + used in several packages and projects. + date_publication: '2021-04-28' + bug_reports: https://github.com/numeract/Nmisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Nmisc + url_git: https://github.com/numeract/Nmisc +Nmix: + version: 2.0.5 + title: Bayesian Inference on Univariate Normal Mixtures + maintainer: Peter Green + description: |- + A program for Bayesian analysis of univariate normal mixtures with an unknown number + of components, following the approach of Richardson and Green (1997) . + This makes use of reversible jump Markov chain Monte Carlo methods that are capable of jumping + between the parameter sub-spaces corresponding to different numbers of components in the mixture. + A sample from the full joint distribution of all unknown variables is thereby generated, + and this can be used as a basis for a thorough presentation of many aspects of the posterior + distribution. + date_publication: '2023-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Nmix + url_git: '' +nmixgof: + version: 0.1.1 + title: Goodness of Fit Checks for Binomial N-Mixture Models + maintainer: Jonas Knape + description: |- + Provides residuals and overdispersion metrics to assess the fit of N-mixture models obtained using the package 'unmarked'. + Details on the methods are given in Knape et al. (2017) . + date_publication: '2025-02-12' + bug_reports: https://github.com/jknape/nmixgof/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nmixgof + url_git: https://github.com/jknape/nmixgof +NMMIPW: + version: 0.1.0 + title: Inverse Probability Weighting under Non-Monotone Missing + maintainer: Andrew Ying + description: We fit inverse probability weighting estimator and the augmented inverse + probability weighting for non-monotone missing at random data. + date_publication: '2021-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMMIPW + url_git: '' +NMOF: + version: 2.10-1 + title: Numerical Methods and Optimization in Finance + maintainer: Enrico Schumann + description: |- + Functions, examples and data from the first and + the second edition of "Numerical Methods and Optimization in + Finance" by M. Gilli, D. Maringer and E. Schumann (2019, + ISBN:978-0128150658). The package provides implementations + of optimisation heuristics (Differential Evolution, Genetic + Algorithms, Particle Swarm Optimisation, Simulated Annealing + and Threshold Accepting), and other optimisation tools, such + as grid search and greedy search. There are also functions + for the valuation of financial instruments such as bonds and + options, for portfolio selection and functions that help + with stochastic simulations. + date_publication: '2024-11-03' + bug_reports: '' + url: https://enricoschumann.net/NMOF.htm + url_cran: https://CRAN.R-project.org/package=NMOF + url_git: https://gitlab.com/NMOF +NMRphasing: + version: 1.0.6 + title: |- + Phase Error Correction and Baseline Correction for One + Dimensional ('1D') 'NMR' Data + maintainer: Aixiang Jiang + description: 'There are three distinct approaches for phase error correction, they + are: a single linear model with a choice of optimization functions, multiple linear + models with optimization function choices and a shrinkage-based method. The methodology + is based on our new algorithms and various references (Binczyk et al. (2015) ,Chen + et al. (2002) , de Brouwer (2009) , + Džakula (2000) , Ernst (1969) , + Liland et al. (2010) ).' + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMRphasing + url_git: '' +nmrrr: + version: 1.0.0 + title: Binning and Visualizing NMR Spectra in Environmental Samples + maintainer: Kaizad Patel + description: |- + A reproducible workflow for binning and visualizing NMR (nuclear magnetic resonance) spectra from environmental samples. The 'nmrrr' package is intended for post-processing of NMR data, including importing, merging and, cleaning data from multiple files, visualizing NMR spectra, performing binning/integrations for compound classes, and relative abundance calculations. + This package can be easily inserted into existing analysis workflows by users to help with analyzing and interpreting NMR data. + date_publication: '2023-05-10' + bug_reports: https://github.com/kaizadp/nmrrr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nmrrr + url_git: https://github.com/kaizadp/nmrrr +NMsim: + version: 0.1.6 + title: Seamless 'Nonmem' Simulation Platform + maintainer: Philip Delff + description: A complete and seamless 'Nonmem' simulation interface within R. Turns + 'Nonmem' control streams into simulation control streams, executes them with specified + simulation input data and returns the results. The simulation is performed by + 'Nonmem', eliminating manual work and risks of re-implementation of models in + other tools. + date_publication: '2025-02-05' + bug_reports: https://github.com/NMautoverse/NMsim/issues + url: https://NMautoverse.github.io/NMsim/ + url_cran: https://CRAN.R-project.org/package=NMsim + url_git: '' +nmslibR: + version: 1.0.7 + title: Non Metric Space (Approximate) Library + maintainer: Lampros Mouselimis + description: A Non-Metric Space Library ('NMSLIB' ) + wrapper, which according to the authors "is an efficient cross-platform similarity + search library and a toolkit for evaluation of similarity search methods. The + goal of the 'NMSLIB' Library is to create an + effective and comprehensive toolkit for searching in generic non-metric spaces. + Being comprehensive is important, because no single method is likely to be sufficient + in all cases. Also note that exact solutions are hardly efficient in high dimensions + and/or non-metric spaces. Hence, the main focus is on approximate methods". The + wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on + the 'NMSLIB' 'Python' Library. + date_publication: '2023-02-01' + bug_reports: https://github.com/mlampros/nmslibR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nmslibR + url_git: https://github.com/mlampros/nmslibR +NMTox: + version: 0.1.0 + title: Dose-Response Relationship Analysis of Nanomaterial Toxicity + maintainer: Rahmasari Nur Azizah + description: |- + Perform an exploration and a preliminary analysis on the dose- + response relationship of nanomaterial toxicity. Several functions are + provided for data exploration, including functions for creating a subset of + dataset, frequency tables and plots. Inference for order restricted dose- + response data is performed by testing the significance of monotonic + dose-response relationship, using Williams, Marcus, M, Modified M and + Likelihood ratio tests. Several methods of multiplicity adjustment + are also provided. Description of the methods can be found in . + date_publication: '2022-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMTox + url_git: '' +NMVANOVA: + version: 1.1.0 + title: Novice Model Variation ANOVA + maintainer: Joseph Lipoff + description: Due to 'Rstudio's' status as open source software, we believe it will + be utilized frequently for future data analysis by users whom lack formal training + or experience with 'R'. The 'NMVANOVA' (Novice Model Variation ANOVA) a streamlined + variation of experimental design functions that allows novice 'Rstudio' users + to perform different model variations one-way analysis of variance without downloading multiple + libraries or packages. Users can easily manipulate the data block, and needed + inputs so that users only have to plugin the four designed variables/values. + date_publication: '2019-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NMVANOVA + url_git: '' +nmw: + version: 0.1.5 + title: |- + Understanding Nonlinear Mixed Effects Modeling for Population + Pharmacokinetics + maintainer: Kyun-Seop Bae + description: This shows how NONMEM(R) software works. NONMEM's classical estimation + methods like 'First Order(FO) approximation', 'First Order Conditional Estimation(FOCE)', + and 'Laplacian approximation' are explained. + date_publication: '2023-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nmw + url_git: '' +nn2poly: + version: 0.1.2 + title: |- + Neural Network Weights Transformation into Polynomial + Coefficients + maintainer: Pablo Morala + description: |- + Implements a method that builds the coefficients of a polynomial + model that performs almost equivalently as a given neural network + (densely connected). This is achieved using Taylor expansion at the + activation functions. The obtained polynomial coefficients can be used + to explain features (and their interactions) importance in the neural network, + therefore working as a tool for interpretability or eXplainable Artificial + Intelligence (XAI). See Morala et al. 2021 , + and 2023 . + date_publication: '2024-11-11' + bug_reports: '' + url: https://ibidat.github.io/nn2poly/ + url_cran: https://CRAN.R-project.org/package=nn2poly + url_git: '' +nna: + version: 0.0.2.1 + title: Nearest-Neighbor Analysis + maintainer: Cristiano Pereira + description: |- + Calculates spatial pattern analysis using a T-square sample procedure. + This method is based on two measures "x" and "y". + "x" - Distance from the random point to the nearest individual. + "y" - Distance from individual to its nearest neighbor. + This is a methodology commonly used in phytosociology or marine benthos ecology to analyze the species' distribution (random, uniform or clumped patterns). + Ludwig & Reynolds (1988, ISBN:0471832359). + date_publication: '2018-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nna + url_git: '' +NNbenchmark: + version: 3.2.0 + title: Datasets and Functions to Benchmark Neural Network Packages + maintainer: Patrice Kiener + description: Datasets and functions to benchmark (convergence, speed, ease of use) + R packages dedicated to regression with neural networks (no classification in + this version). The templates for the tested packages are available in the R, R + Markdown and HTML formats at + and . The submitted + article to the R-Journal can be read at . + date_publication: '2021-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NNbenchmark + url_git: https://github.com/pkR-pkR/NNbenchmark +nncc: + version: 2.0.0 + title: Nearest Neighbors Matching of Case-Control Data + maintainer: Beau Bruce + description: |- + Provides nearest-neighbors matching and + analysis of case-control data. Cui, Z., Marder, E. P., Click, E. S., + Hoekstra, R. M., & Bruce, B. B. (2022) . + date_publication: '2024-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nncc + url_git: '' +nndiagram: + version: 1.0.0 + title: |- + Generator of 'LaTeX' Code for Drawing Neural Network Diagrams + with 'TikZ' + maintainer: Chencheng Fang + description: Generates 'LaTeX' code for drawing well-formatted neural network diagrams + with 'TikZ'. Users have to define number of neurons on each layer, and optionally + define neuron connections they would like to keep or omit, layers they consider + to be oversized and neurons they would like to draw with lighter color. They can + also specify the title of diagram, color, opacity of figure, labels of layers, + input and output neurons. In addition, this package helps to produce 'LaTeX' code + for drawing activation functions which are crucial in neural network analysis. + To make the code work in a 'LaTeX' editor, users need to install and import some + 'TeX' packages including 'TikZ' in the setting of 'TeX' file. + date_publication: '2023-04-18' + bug_reports: https://github.com/ccfang2/nndiagram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nndiagram + url_git: https://github.com/ccfang2/nndiagram +nnet: + version: 7.3-20 + title: Feed-Forward Neural Networks and Multinomial Log-Linear Models + maintainer: Brian Ripley + description: |- + Software for feed-forward neural networks with a single + hidden layer, and for multinomial log-linear models. + date_publication: '2025-01-01' + bug_reports: '' + url: http://www.stats.ox.ac.uk/pub/MASS4/ + url_cran: https://CRAN.R-project.org/package=nnet + url_git: '' +nnfor: + version: 0.9.9 + title: Time Series Forecasting with Neural Networks + maintainer: Nikolaos Kourentzes + description: |- + Automatic time series modelling with neural networks. + Allows fully automatic, semi-manual or fully manual specification of networks. For details of the + specification methodology see: (i) Crone and Kourentzes (2010) ; + and (ii) Kourentzes et al. (2014) . + date_publication: '2023-11-15' + bug_reports: https://github.com/trnnick/nnfor/issues + url: https://kourentzes.com/forecasting/2019/01/16/tutorial-for-the-nnfor-r-package/ + url_cran: https://CRAN.R-project.org/package=nnfor + url_git: '' +nnGarrote: + version: 1.0.4 + title: |- + Non-Negative Garrote Estimation with Penalized Initial + Estimators + maintainer: Anthony Christidis + description: |- + Functions to compute the non-negative garrote estimator as + proposed by Breiman (1995) + with the penalized initial estimators extension as proposed by + Yuan and Lin (2007) . + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nnGarrote + url_git: '' +nngeo: + version: 0.4.8 + title: k-Nearest Neighbor Join for Spatial Data + maintainer: Michael Dorman + description: K-nearest neighbor search for projected and non-projected 'sf' spatial + layers. Nearest neighbor search uses (1) C code from 'GeographicLib' for lon-lat + point layers, (2) function knn() from package 'nabor' for projected point layers, + or (3) function st_distance() from package 'sf' for line or polygon layers. The + package also includes several other utility functions for spatial analysis. + date_publication: '2024-04-17' + bug_reports: https://github.com/michaeldorman/nngeo/issues/ + url: https://michaeldorman.github.io/nngeo/ + url_cran: https://CRAN.R-project.org/package=nngeo + url_git: https://github.com/michaeldorman/nngeo/ +nnlasso: + version: '0.3' + title: |- + Non-Negative Lasso and Elastic Net Penalized Generalized Linear + Models + maintainer: Baidya Nath Mandal + description: Estimates of coefficients of lasso penalized linear regression and + generalized linear models subject to non-negativity constraints on the parameters + using multiplicative iterative algorithm. Entire regularization path for a sequence + of lambda values can be obtained. Functions are available for creating plots of + regularization path, cross validation and estimating coefficients at a given lambda + value. There is also provision for obtaining standard error of coefficient estimates. + date_publication: '2016-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nnlasso + url_git: '' +nnlib2Rcpp: + version: 0.2.9 + title: |- + A Tool for Creating Custom Neural Networks in C++ and using Them + in R + maintainer: Vasilis Nikolaidis + description: Contains a module to define neural networks from custom components + and versions of Autoencoder, BP, LVQ, MAM NN. + date_publication: '2024-10-10' + bug_reports: https://github.com/VNNikolaidis/nnlib2Rcpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nnlib2Rcpp + url_git: https://github.com/VNNikolaidis/nnlib2Rcpp +nnls: + version: '1.6' + title: |- + The Lawson-Hanson Algorithm for Non-Negative Least Squares + (NNLS) + maintainer: Katharine Mullen + description: |- + An R interface to the Lawson-Hanson implementation of an + algorithm for non-negative least squares (NNLS). Also allows + the combination of non-negative and non-positive constraints. + date_publication: '2024-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nnls + url_git: '' +NNMIS: + version: 1.0.1 + title: |- + Nearest Neighbor Based Multiple Imputation for Survival Data + with Missing Covariates + maintainer: Chiu-Hsieh Hsu + description: 'Imputation for both missing covariates and censored observations (optional) + for survival data with missing covariates by the nearest neighbor based multiple + imputation algorithm as described in Hsu et al. (2006) , + and Hsu and Yu (2018) . Note that the current version + can only impute for a situation with one missing covariate.' + date_publication: '2019-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NNMIS + url_git: '' +nnR: + version: 0.1.0 + title: Neural Networks Made Algebraic + maintainer: Shakil Rafi + description: |- + Do algebraic operations on neural networks. We seek here to implement + in R, operations on neural networks and their resulting approximations. Our operations derive + their descriptions mainly from + Rafi S., Padgett, J.L., and Nakarmi, U. (2024), "Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials", , + Grohs P., Hornung, F., Jentzen, A. et al. (2023), "Space-time error estimates for deep neural network approximations for differential equations", , + Jentzen A., Kuckuck B., von Wurstemberger, P. (2023), "Mathematical Introduction to Deep Learning Methods, Implementations, and Theory" . + Our implementation is meant mainly as a pedagogical tool, and proof of concept. Faster implementations with + deeper vectorizations may be made in future versions. + date_publication: '2024-02-14' + bug_reports: https://github.com/2shakilrafi/nnR/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc + url: '' + url_cran: https://CRAN.R-project.org/package=nnR + url_git: https://github.com/2shakilrafi/nnR/ +NNS: + version: '11.1' + title: Nonlinear Nonparametric Statistics + maintainer: Fred Viole + description: 'Nonlinear nonparametric statistics using partial moments. Partial + moments are the elements of variance and asymptotically approximate the area of + f(x). These robust statistics provide the basis for nonlinear analysis while + retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, + Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, + Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and + Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, + D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).' + date_publication: '2025-02-17' + bug_reports: https://github.com/OVVO-Financial/NNS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NNS + url_git: '' +nnspat: + version: 0.1.2 + title: Nearest Neighbor Methods for Spatial Patterns + maintainer: Elvan Ceyhan + description: |- + Contains the functions for testing the spatial patterns (of segregation, spatial symmetry, + association, disease clustering, species correspondence, and reflexivity) based on nearest neighbor relations, + especially using contingency tables such as + nearest neighbor contingency tables (Ceyhan (2010) and + Ceyhan (2017) and references therein), + nearest neighbor symmetry contingency tables (Ceyhan (2014) ), + species correspondence contingency tables and reflexivity contingency tables (Ceyhan (2018) + for two (or higher) dimensional data. + The package also contains functions for generating patterns of segregation, association, + uniformity in a multi-class setting (Ceyhan (2014) ), + and various non-random labeling patterns for disease clustering + in two dimensional cases (Ceyhan (2014) + ), and for visualization of all these patterns + for the two dimensional data. + The tests are usually (asymptotic) normal z-tests or chi-square tests. + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nnspat + url_git: '' +nnt: + version: 0.1.4 + title: The Number Needed to Treat (NNT) for Survival Endpoint + maintainer: Zhao Yang + description: |- + Estimate the NNT using the proposed method in Yang and Yin's paper (2019) + , in which the NNT-RMST (number needed to + treat based on the restricted mean survival time) is defined as the RMST (restricted + mean survival time) in the control group divided by the difference in RMSTs + between the treatment and control groups up to a chosen time t. + date_publication: '2020-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nnt + url_git: '' +NNTbiomarker: + version: 0.29.11 + title: Calculate Design Parameters for Biomarker Validation Studies + maintainer: Roger Day + description: |- + Helps a clinical trial team discuss + the clinical goals of a well-defined biomarker with a diagnostic, + staging, prognostic, or predictive purpose. From this discussion will + come a statistical plan for a (non-randomized) validation trial. + Both prospective and retrospective trials are supported. In a specific + focused discussion, investigators should determine the range of + "discomfort" for the NNT, number needed to treat. The meaning of + the discomfort range, [NNTlower, NNTupper], is that within this range + most physicians would feel discomfort either in treating or withholding + treatment. A pair of NNT values bracketing that range, NNTpos and NNTneg, + become the targets of the study's design. If the trial can demonstrate + that a positive biomarker test yields an NNT less than NNTlower, + and that a negative biomarker test yields an NNT less than NNTlower, + then the biomarker may be useful for patients. A highlight of the package + is visualization of a "contra-Bayes" theorem, which produces criteria for + retrospective case-controls studies. + date_publication: '2015-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NNTbiomarker + url_git: '' +nnTensor: + version: 1.3.0 + title: Non-Negative Tensor Decomposition + maintainer: Koki Tsuyuzaki + description: Some functions for performing non-negative matrix factorization, non-negative + CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating + toy model data. See Andrzej Cichock et al (2009) and the reference section of + GitHub README.md , for details of the methods. + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nnTensor + url_git: https://github.com/rikenbit/nnTensor +nntmvn: + version: 1.2.0 + title: Draw Samples of Truncated Multivariate Normal Distributions + maintainer: Jian Cao + description: Draw samples from truncated multivariate normal distribution using + the sequential nearest neighbor (SNN) method introduced in "Scalable Sampling + of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation" + . + date_publication: '2025-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nntmvn + url_git: '' +NO.PING.PONG: + version: 0.1.8.7 + title: Incorporating Previous Findings When Evaluating New Data + maintainer: Brian P. O'Connor + description: |- + Functions for revealing what happens when effect size estimates + from previous studies are taken into account when evaluating each new dataset + in a study sequence. The analyses can be conducted for cumulative + meta-analyses and for Bayesian data analyses. The package contains sample + data for a wide selection of research topics. Jointly considering + previous findings along with new data is more likely to result in correct + conclusions than does the traditional practice of not incorporating previous + findings, which often results in a back and forth ping-pong of conclusions + when evaluating a sequence of studies. + O'Connor & Ermacora (2021, ). + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NO.PING.PONG + url_git: '' +noah: + version: 0.1.0 + title: Create Unique Pseudonymous Animal Names + maintainer: Tobias Busch + description: |- + Generate pseudonymous animal names that are delightful and easy to + remember like the Likable Leech and the Proud Chickadee. A unique pseudonym + can be created for every unique element in a vector or row in a data frame. + Pseudonyms can be customized and tracked over time, so that the same input + is always assigned the same pseudonym. + date_publication: '2021-01-18' + bug_reports: https://github.com/Teebusch/noah/issues + url: '' + url_cran: https://CRAN.R-project.org/package=noah + url_git: https://github.com/Teebusch/noah +NobBS: + version: 1.0.0 + title: Nowcasting by Bayesian Smoothing + maintainer: Sarah McGough + description: A Bayesian approach to estimate the number of occurred-but-not-yet-reported + cases from incomplete, time-stamped reporting data for disease outbreaks. 'NobBS' + learns the reporting delay distribution and the time evolution of the epidemic + curve to produce smoothed nowcasts in both stable and time-varying case reporting + settings, as described in McGough et al. (2020) . + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NobBS + url_git: '' +noctua: + version: 2.6.2 + title: |- + Connect to 'AWS Athena' using R 'AWS SDK' 'paws' ('DBI' + Interface) + maintainer: Dyfan Jones + description: |- + Designed to be compatible with the 'R' package 'DBI' (Database Interface) + when connecting to Amazon Web Service ('AWS') Athena . + To do this the 'R' 'AWS' Software Development Kit ('SDK') 'paws' + is used as a driver. + date_publication: '2023-08-08' + bug_reports: https://github.com/DyfanJones/noctua/issues + url: '' + url_cran: https://CRAN.R-project.org/package=noctua + url_git: https://github.com/DyfanJones/noctua +nodbi: + version: 0.11.0 + title: '''NoSQL'' Database Connector' + maintainer: Ralf Herold + description: |- + Simplified JSON document database access and manipulation, + providing a common API across supported 'NoSQL' databases + 'Elasticsearch', 'CouchDB', 'MongoDB' as well as + 'SQLite/JSON1', 'PostgreSQL', and 'DuckDB'. + date_publication: '2024-11-10' + bug_reports: https://github.com/ropensci/nodbi/issues + url: https://docs.ropensci.org/nodbi/ + url_cran: https://CRAN.R-project.org/package=nodbi + url_git: https://github.com/ropensci/nodbi +node2vec: + version: 0.1.0 + title: Algorithmic Framework for Representational Learning on Graphs + maintainer: Yang Tian + description: 'Given any graph, the ''node2vec'' algorithm can learn continuous feature + representations for the nodes, which can then be used for various downstream machine + learning tasks.The techniques are detailed in the paper "node2vec: Scalable Feature + Learning for Networks" by Aditya Grover, Jure Leskovec(2016),available at .' + date_publication: '2021-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=node2vec + url_git: '' +nodeSub: + version: 1.2.8 + title: Simulate DNA Alignments Using Node Substitutions + maintainer: Thijs Janzen + description: |- + Simulate DNA sequences for the node substitution model. + In the node substitution model, substitutions accumulate additionally + during a speciation event, providing a potential mechanistic explanation for + substitution rate variation. This package provides tools to simulate + such a process, simulate a reference process with only substitutions along + the branches, and provides tools to infer phylogenies from alignments. More + information can be found in Janzen (2021) . + date_publication: '2023-11-14' + bug_reports: https://github.com/thijsjanzen/nodeSub + url: '' + url_cran: https://CRAN.R-project.org/package=nodeSub + url_git: https://github.com/thijsjanzen/nodeSub +nodiv: + version: 1.4.2 + title: Compares the Distribution of Sister Clades Through a Phylogeny + maintainer: Michael Krabbe Borregaard + description: 'An implementation of the nodiv algorithm, see Borregaard, M.K., Rahbek, + C., Fjeldsaa, J., Parra, J.L., Whittaker, R.J. & Graham, C.H. 2014. Node-based + analysis of species distributions. Methods in Ecology and Evolution 5(11): 1225-1235. + . Package for phylogenetic analysis of species distributions. + The main function goes through each node in the phylogeny, compares the distributions + of the two descendant nodes, and compares the result to a null model. This highlights + nodes where major distributional divergence have occurred. The distributional + divergence for these nodes is mapped.' + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nodiv + url_git: https://github.com/mkborregaard/nodiv +noegletalR: + version: 0.2.1 + title: Tidy Tibbles of Noegletal + maintainer: Frederik Larsen + description: |- + Work with data from in a tidy manner. Tidy + up previously downloaded data or retrieve new data directly from the + comfort of R. You can also browse an up-to-date list of available + data, including thorough variable descriptions. + date_publication: '2024-09-12' + bug_reports: https://github.com/FrLars21/noegletalR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=noegletalR + url_git: https://github.com/FrLars21/noegletalR +nofrills: + version: 0.3.2 + title: Low-Cost Anonymous Functions + maintainer: Eugene Ha + description: |- + Provides a compact variation of the usual syntax of function + declaration, in order to support tidyverse-style quasiquotation of a + function's arguments and body. + date_publication: '2022-02-03' + bug_reports: https://github.com/egnha/nofrills/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nofrills + url_git: https://github.com/egnha/nofrills +noia: + version: 0.97.3 + title: |- + Implementation of the Natural and Orthogonal InterAction (NOIA) + Model + maintainer: Arnaud Le Rouzic + description: The NOIA model, as described extensively in Alvarez-Castro & Carlborg + (2007), is a framework facilitating the estimation of genetic effects and genotype-to-phenotype + maps. This package provides the basic tools to perform linear and multilinear + regressions from real populations (provided the phenotype and the genotype of + every individuals), estimating the genetic effects from different reference points, + the genotypic values, and the decomposition of genetic variances in a multi-locus, + 2 alleles system. This package is presented in Le Rouzic & Alvarez-Castro (2008). + date_publication: '2023-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noia + url_git: https://github.com/lerouzic/noia +noise: + version: 1.0.2 + title: |- + Estimation of Intrinsic and Extrinsic Noise from Single-Cell + Data + maintainer: Audrey Q. Fu + description: Functions to calculate estimates of intrinsic and extrinsic noise from + the two-reporter single-cell experiment, as in Elowitz, M. B., A. J. Levine, E. + D. Siggia, and P. S. Swain (2002) Stochastic gene expression in a single cell. + Science, 297, 1183-1186. Functions implement multiple estimators developed for + unbiasedness or min Mean Squared Error (MSE) in Fu, A. Q. and Pachter, L. (2016). + Estimating intrinsic and extrinsic noise from single-cell gene expression measurements. + Statistical Applications in Genetics and Molecular Biology, 15(6), 447-471. + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noise + url_git: '' +noisemodel: + version: 1.0.2 + title: Noise Models for Classification Datasets + maintainer: José A. Sáez + description: |- + Implementation of models for the controlled introduction of errors in + classification datasets. This package contains the noise models described in + Saez (2022) that allow corrupting class labels, + attributes and both simultaneously. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noisemodel + url_git: '' +noisyCE2: + version: 1.1.0 + title: Cross-Entropy Optimisation of Noisy Functions + maintainer: Flavio Santi + description: |- + Cross-Entropy optimisation of unconstrained deterministic and noisy + functions illustrated in Rubinstein and Kroese (2004, ISBN: + 978-1-4419-1940-3) through a highly flexible and customisable function which + allows user to define custom variable domains, sampling distributions, + updating and smoothing rules, and stopping criteria. Several built-in + methods and settings make the package very easy-to-use under standard + optimisation problems. + date_publication: '2020-11-09' + bug_reports: https://github.com/f-santi/noisyCE2/issues + url: https://www.flaviosanti.it/software/noisyCE2 + url_cran: https://CRAN.R-project.org/package=noisyCE2 + url_git: '' +noisyr: + version: 1.0.0 + title: Noise Quantification in High Throughput Sequencing Output + maintainer: Ilias Moutsopoulos + description: |- + Quantifies and removes technical noise from high-throughput + sequencing data. Two approaches are used, one based on the count + matrix, and one using the alignment BAM files directly. + Contains several options for every step of the process, as well + as tools to quality check and assess the stability of output. + date_publication: '2021-04-16' + bug_reports: https://github.com/Core-Bioinformatics/noisyR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=noisyr + url_git: https://github.com/Core-Bioinformatics/noisyR +noisySBM: + version: 0.1.4 + title: 'Noisy Stochastic Block Mode: Graph Inference by Multiple Testing' + maintainer: Tabea Rebafka + description: |- + Variational Expectation-Maximization algorithm to fit the noisy stochastic block model to an observed dense graph + and to perform a node clustering. Moreover, a graph inference procedure to recover the underlying + binary graph. This procedure comes with a control of the false discovery rate. The method is described + in the article "Powerful graph inference with false discovery rate control" by T. Rebafka, + E. Roquain, F. Villers (2020) . + date_publication: '2020-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noisySBM + url_git: '' +noisysbmGGM: + version: 0.1.2.3 + title: Noisy Stochastic Block Model for GGM Inference + maintainer: Valentin Kilian + description: Greedy Bayesian algorithm to fit the noisy stochastic block model to + an observed sparse graph. Moreover, a graph inference procedure to recover Gaussian + Graphical Model (GGM) from real data. This procedure comes with a control of the + false discovery rate. The method is described in the article "Enhancing the Power + of Gaussian Graphical Model Inference by Modeling the Graph Structure" by Kilian, + Rebafka, and Villers (2024) . + date_publication: '2024-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noisysbmGGM + url_git: '' +nolock: + version: 1.1.0 + title: |- + Append 'WITH (NOLOCK)' to 'SQL' Queries, Get Packages in Active + Script + maintainer: Arkadiusz W. Pajda + description: |- + Provides a suite of tools that can assist in enhancing the + processing efficiency of 'SQL' and 'R' scripts. + - The 'libr_unused()' retrieves a vector of package names that are called + within an 'R' script but are never actually used in the script. + - The 'libr_used()' retrieves a vector of package names actively utilized + within an 'R' script; packages loaded using 'library()' but not actually + used in the script will not be included. + - The 'libr_called()' retrieves a vector of all package names which are + called within an 'R' script. + - 'nolock()' appends 'WITH (nolock)' to all tables in 'SQL' queries. This + facilitates reading from databases in scenarios where non-blocking reads are + preferable, such as in high-transaction environments. + date_publication: '2023-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nolock + url_git: '' +nombre: + version: 0.4.1 + title: Number Names + maintainer: Alexander Rossell Hayes + description: |- + Converts numeric vectors to character vectors of English + number names. Provides conversion to cardinals, ordinals, numerators, + and denominators. Supports negative and non-integer numbers. + date_publication: '2022-05-23' + bug_reports: https://github.com/rossellhayes/nombre/issues + url: https://nombre.rossellhayes.com + url_cran: https://CRAN.R-project.org/package=nombre + url_git: https://github.com/rossellhayes/nombre +nomclust: + version: 2.8.0 + title: Hierarchical Cluster Analysis of Nominal Data + maintainer: Zdenek Sulc + description: |- + Similarity measures for hierarchical clustering of objects characterized by + nominal (categorical) variables. Evaluation criteria for nominal data clustering. + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nomclust + url_git: '' +nominatimlite: + version: 0.4.2 + title: Interface with 'Nominatim' API Service + maintainer: Diego Hernangómez + description: |- + Lite interface for getting data from 'OSM' service + 'Nominatim' . Extract + coordinates from addresses, find places near a set of coordinates and + return spatial objects on 'sf' format. + date_publication: '2024-12-17' + bug_reports: https://github.com/dieghernan/nominatimlite/issues + url: https://dieghernan.github.io/nominatimlite/ + url_cran: https://CRAN.R-project.org/package=nominatimlite + url_git: https://github.com/dieghernan/nominatimlite +nomisr: + version: 0.4.7 + title: Access 'Nomis' UK Labour Market Data + maintainer: Evan Odell + description: |- + Access UK official statistics from the 'Nomis' database. + 'Nomis' includes data from the Census, the Labour Force Survey, DWP benefit + statistics and other economic and demographic data from the Office for + National Statistics, based around statistical geographies. See + for full API documentation. + date_publication: '2022-06-11' + bug_reports: https://github.com/ropensci/nomisr/issues + url: https://docs.evanodell.com/nomisr + url_cran: https://CRAN.R-project.org/package=nomisr + url_git: https://github.com/ropensci/nomisr +nomnoml: + version: 0.3.0 + title: Sassy 'UML' Diagrams + maintainer: Andrie de Vries + description: |- + A tool for drawing sassy 'UML' (Unified Modeling Language) diagrams + based on a simple syntax, see . Supports styling, + R Markdown and exporting diagrams in the PNG format. Note: you need a chromium based + browser installed on your system. + date_publication: '2023-11-20' + bug_reports: https://github.com/rstudio/nomnoml/issues + url: https://rstudio.github.io/nomnoml/ + url_cran: https://CRAN.R-project.org/package=nomnoml + url_git: '' +nomogramEx: + version: '3.0' + title: Extract Equations from a Nomogram + maintainer: Zhicheng Du + description: |2- + + A nomogram can not be easily applied, + because it is difficult to calculate the points or even the survival probability. + The package, including a function of nomogramEx(), + is to extract the polynomial equations to calculate the points of each variable, + and the survival probability corresponding to the total points. + date_publication: '2017-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nomogramEx + url_git: '' +nomogramFormula: + version: 1.2.0.0 + title: Calculate Total Points and Probabilities for Nomogram + maintainer: Jing Zhang + description: |2- + + A nomogram, which can be carried out in 'rms' package, provides a + graphical explanation of a prediction process. However, it is not very easy + to draw straight lines, read points and probabilities accurately. Even, it + is hard for users to calculate total points and probabilities for all + subjects. + This package provides formula_rd() and formula_lp() functions to fit the + formula of total points with raw data and linear predictors respectively by + polynomial regression. Function points_cal() will help you calculate the + total points. prob_cal() can be used to calculate the probabilities after + lrm(), cph() or psm() regression. + For more complex condition, interaction or restricted cubic spine, TotalPoints.rms() + can be used. + date_publication: '2020-01-28' + bug_reports: https://github.com/yikeshu0611/nomogramFormula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nomogramFormula + url_git: https://github.com/yikeshu0611/nomogramFormula +NonCompart: + version: 0.7.0 + title: Noncompartmental Analysis for Pharmacokinetic Data + maintainer: Kyun-Seop Bae + description: |- + Conduct a noncompartmental analysis with industrial strength. + Some features are + 1) Use of CDISC SDTM terms + 2) Automatic or manual slope selection + 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method + 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method + * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107). + date_publication: '2023-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NonCompart + url_git: '' +noncompliance: + version: 0.2.2 + title: |- + Causal Inference in the Presence of Treatment Noncompliance + Under the Binary Instrumental Variable Model + maintainer: Wen Wei Loh + description: |- + A finite-population significance test of the 'sharp' causal null hypothesis that + treatment exposure X has no effect on final outcome Y, within the principal stratum of Compliers. + A generalized likelihood ratio test statistic is used, and the resulting p-value is exact. + Currently, it is assumed that there are only Compliers and Never Takers in the population. + date_publication: '2016-02-15' + bug_reports: '' + url: https://www.stat.washington.edu/~wloh/ + url_cran: https://CRAN.R-project.org/package=noncompliance + url_git: '' +noncomplyR: + version: '1.0' + title: Bayesian Analysis of Randomized Experiments with Non-Compliance + maintainer: Scott Coggeshall + description: 'Functions for Bayesian analysis of data from randomized experiments + with non-compliance. The functions are based on the models described in Imbens + and Rubin (1997) . Currently only two types of outcome + models are supported: binary outcomes and normally distributed outcomes. Models + can be fit with and without the exclusion restriction and/or the strong access + monotonicity assumption. Models are fit using the data augmentation algorithm + as described in Tanner and Wong (1987) .' + date_publication: '2017-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noncomplyR + url_git: '' +nonet: + version: 0.4.0 + title: Weighted Average Ensemble without Training Labels + maintainer: Aviral Vijay + description: It provides ensemble capabilities to supervised and unsupervised learning + models predictions without using training labels. It decides the relative weights + of the different models predictions by using best models predictions as response + variable and rest of the mo. User can decide the best model, therefore, It provides + freedom to user to ensemble models based on their design solutions. + date_publication: '2019-01-15' + bug_reports: https://github.com/GSLabDev/nonet/issues + url: https://open.gslab.com/nonet/ + url_cran: https://CRAN.R-project.org/package=nonet + url_git: '' +nonLinearDotPlot: + version: 0.5.0 + title: Non Linear Dot Plots + maintainer: Sören Döring + description: 'Non linear dot plots are diagrams that allow dots of varying size + to be constructed, so that columns with a large number of samples are reduced + in height. Implementation of algorithm described in: Nils Rodrigues and Daniel + Weiskopf, "Nonlinear Dot Plots", IEEE Transactions on Visualization and Computer + Graphics, vol. 24, no. 1, pp. 616-625, 2018. .' + date_publication: '2023-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonLinearDotPlot + url_git: '' +nonlinearICP: + version: 0.1.2.1 + title: Invariant Causal Prediction for Nonlinear Models + maintainer: Christina Heinze-Deml + description: |- + Performs 'nonlinear Invariant Causal Prediction' to estimate the + causal parents of a given target variable from data collected in + different experimental or environmental conditions, extending + 'Invariant Causal Prediction' from Peters, Buehlmann and Meinshausen (2016), + , to nonlinear settings. For more details, see C. Heinze-Deml, + J. Peters and N. Meinshausen: 'Invariant Causal Prediction for Nonlinear Models', + . + date_publication: '2017-07-31' + bug_reports: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nonlinearICP + url_git: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests +NonlinearTSA: + version: 0.5.0 + title: Nonlinear Time Series Analysis + maintainer: Burak Guris + description: Function and data sets in the book entitled "Nonlinear Time Series + Analysis with R Applications" B.Guris (2020). The book will be published in Turkish + and the original name of this book will be "R Uygulamali Dogrusal Olmayan Zaman + Serileri Analizi". It is possible to perform nonlinearity tests, nonlinear unit + root tests, nonlinear cointegration tests and estimate nonlinear error correction + models by using the functions written in this package. The Momentum Threshold + Autoregressive (MTAR), the Smooth Threshold Autoregressive (STAR) and the Self + Exciting Threshold Autoregressive (SETAR) type unit root tests can be performed + using the functions written. In addition, cointegration tests using the Momentum + Threshold Autoregressive (MTAR), the Smooth Threshold Autoregressive (STAR) and + the Self Exciting Threshold Autoregressive (SETAR) models can be applied. It is + possible to estimate nonlinear error correction models. The Granger causality + test performed using nonlinear models can also be applied. + date_publication: '2021-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NonlinearTSA + url_git: '' +nonlinearTseries: + version: 0.3.1 + title: Nonlinear Time Series Analysis + maintainer: Constantino A. Garcia + description: |- + Functions for nonlinear time series analysis. This package permits + the computation of the most-used nonlinear statistics/algorithms + including generalized correlation dimension, information dimension, + largest Lyapunov exponent, sample entropy and Recurrence + Quantification Analysis (RQA), among others. Basic routines + for surrogate data testing are also included. Part of this work + was based on the book "Nonlinear time series analysis" by + Holger Kantz and Thomas Schreiber (ISBN: 9780521529020). + date_publication: '2024-09-23' + bug_reports: https://github.com/constantino-garcia/nonlinearTseries/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nonlinearTseries + url_git: https://github.com/constantino-garcia/nonlinearTseries +nonmem2R: + version: 0.2.5 + title: |- + Loading NONMEM Output Files with Functions for Visual Predictive + Checks (VPC) and Goodness of Fit (GOF) Plots + maintainer: Magnus Astrand + description: Loading NONMEM (NONlinear Mixed-Effect Modeling, ) + and PSN (Perl-speaks-NONMEM, ) output + files to extract parameter estimates, provide visual predictive check (VPC) and + goodness of fit (GOF) plots, and simulate with parameter uncertainty. + date_publication: '2024-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonmem2R + url_git: '' +nonmem2rx: + version: 0.1.6 + title: Converts 'NONMEM' Models to 'rxode2' + maintainer: Matthew Fidler + description: |- + 'NONMEM' has been a tool for running nonlinear mixed + effects models since the 80s and is still used today (Bauer 2019 + ). This tool allows you to convert + 'NONMEM' models to 'rxode2' (Wang, Hallow and James (2016) + ) and with simple models 'nlmixr2' syntax + (Fidler et al (2019) ). The 'nlmixr2' + syntax requires the residual specification to be included and it + is not always translated. If available, the 'rxode2' model will + read in the 'NONMEM' data and compare the simulation for the + population model ('PRED') individual model ('IPRED') and residual + model ('IWRES') to immediately show how well the translation is + performing. This saves the model development time for people who are + creating an 'rxode2' model manually. Additionally, this package reads + in all the information to allow simulation with uncertainty (that is the + number of observations, the number of subjects, and the covariance + matrix) with a 'rxode2' model. This is complementary to the + 'babelmixr2' package that translates 'nlmixr2' models to 'NONMEM' and can + convert the objects converted from 'nonmem2rx' to a full 'nlmixr2' fit. + date_publication: '2024-11-28' + bug_reports: '' + url: https://nlmixr2.github.io/nonmem2rx/ + url_cran: https://CRAN.R-project.org/package=nonmem2rx + url_git: https://github.com/nlmixr2/nonmem2rx/ +nonmemica: + version: 1.0.11 + title: Create and Evaluate NONMEM Models in a Project Context + maintainer: Tim Bergsma + description: |- + Systematically creates and modifies NONMEM(R) control streams. Harvests + NONMEM output, builds run logs, creates derivative data, generates diagnostics. + NONMEM (ICON Development Solutions ) is software for + nonlinear mixed effects modeling. See 'package?nonmemica'. + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonmemica + url_git: '' +nonneg.cg: + version: 0.1.6-1 + title: Non-Negative Conjugate-Gradient Minimizer + maintainer: David Cortes + description: |- + Minimize a differentiable function subject to all the variables being non-negative (i.e. >= 0), + using a Conjugate-Gradient algorithm based on a modified Polak-Ribiere-Polyak formula as described in + (Li, Can, 2013, ). + date_publication: '2021-09-26' + bug_reports: https://github.com/david-cortes/nonneg_cg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nonneg.cg + url_git: https://github.com/david-cortes/nonneg_cg +nonnest2: + version: 0.5-8 + title: Tests of Non-Nested Models + maintainer: Edgar Merkle + description: |- + Testing non-nested models via theory supplied by Vuong (1989) . + Includes tests of model distinguishability and of model fit that can be applied + to both nested and non-nested models. Also includes functionality to obtain + confidence intervals associated with AIC and BIC. This material is partially based on + work supported by the National Science Foundation under Grant Number SES-1061334. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonnest2 + url_git: https://github.com/qpsy/nonnest2 +NonNorMvtDist: + version: 1.0.2 + title: |- + Multivariate Lomax (Pareto Type II) and Its Related + Distributions + maintainer: Zhixin Lun + description: 'Implements calculation of probability density function, cumulative + distribution function, equicoordinate quantile function and survival function, + and random numbers generation for the following multivariate distributions: Lomax + (Pareto Type II), generalized Lomax, Mardia’s Pareto of Type I, Logistic, Burr, + Cook-Johnson’s uniform, F and Inverted Beta. See Tapan Nayak (1987) .' + date_publication: '2020-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NonNorMvtDist + url_git: '' +nonpar: + version: 1.0.2 + title: A Collection of Nonparametric Hypothesis Tests + maintainer: D. Lukke Sweet + description: |- + Contains the following 5 nonparametric hypothesis tests: + The Sign Test, + The 2 Sample Median Test, + Miller's Jackknife Procedure, + Cochran's Q Test, & + The Stuart-Maxwell Test. + date_publication: '2020-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonpar + url_git: '' +nonparaeff: + version: 0.5-13 + title: Nonparametric Methods for Measuring Efficiency and Productivity + maintainer: Dong-hyun Oh + description: Efficiency and productivity indices are measured using this package. + This package contains functions for measuring efficiency and productivity of decision + making units (DMUs) under the framework of Data Envelopment Analysis (DEA) and + its variations. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonparaeff + url_git: '' +nonparametric.bayes: + version: 0.0.1 + title: Project Code - Nonparametric Bayes + maintainer: Erik-Cristian Seulean + description: Basic implementation of a Gibbs sampler for a Chinese Restaurant Process + along with some visual aids to help understand how the sampling works. This is + developed as part of a postgraduate school project for an Advanced Bayesian Nonparametric + course. It is inspired by Tamara Broderick's presentation on Nonparametric Bayesian + statistics given at the Simons institute. + date_publication: '2021-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nonparametric.bayes + url_git: '' +Nonpareil: + version: 3.5.3 + title: Metagenome Coverage Estimation and Projections for 'Nonpareil' + maintainer: Luis M. Rodriguez-R + description: |- + Plot, process, and analyze NPO files produced by + 'Nonpareil' . + date_publication: '2024-06-28' + bug_reports: '' + url: http://enve-omics.ce.gatech.edu/nonpareil/ + url_cran: https://CRAN.R-project.org/package=Nonpareil + url_git: '' +NonParRolCor: + version: 0.8.0 + title: |- + a Non-Parametric Statistical Significance Test for Rolling + Window Correlation + maintainer: Josue M. Polanco-Martinez + description: Estimates and plots (as a single plot and as a heat map) the rolling + window correlation coefficients between two time series and computes their statistical + significance, which is carried out through a non-parametric computing-intensive + method. This method addresses the effects due to the multiple testing (inflation + of the Type I error) when the statistical significance is estimated for the rolling + window correlation coefficients. The method is based on Monte Carlo simulations + by permuting one of the variables (e.g., the dependent) under analysis and keeping + fixed the other variable (e.g., the independent). We improve the computational + efficiency of this method to reduce the computation time through parallel computing. + The 'NonParRolCor' package also provides examples with synthetic and real-life + environmental time series to exemplify its use. Methods derived from R. Telford + (2013) and J.M. Polanco-Martinez + and J.L. Lopez-Martinez (2021) . + date_publication: '2022-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NonParRolCor + url_git: '' +NonProbEst: + version: 0.2.4 + title: Estimation in Nonprobability Sampling + maintainer: Luis Castro Martín + description: |- + Different inference procedures are proposed in the literature to correct for selection bias that might be introduced with non-random selection mechanisms. A class of methods to correct for selection bias is to apply a statistical model to predict the units not in the sample (super-population modeling). Other studies use calibration or Statistical Matching (statistically match nonprobability and probability samples). To date, the more relevant methods are weighting by Propensity Score Adjustment (PSA). + The Propensity Score Adjustment method was originally developed to construct weights by estimating response probabilities and using them in Horvitz–Thompson type estimators. This method is usually used by combining a non-probability sample with a reference sample to construct propensity models for the non-probability sample. Calibration can be used in a posterior way to adding information of auxiliary variables. + Propensity scores in PSA are usually estimated using logistic regression models. Machine learning classification algorithms can be used as alternatives for logistic regression as a technique to estimate propensities. + The package 'NonProbEst' implements some of these methods and thus provides a wide options to work with data coming from a non-probabilistic sample. + date_publication: '2020-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NonProbEst + url_git: '' +nonprobsvy: + version: 0.1.1 + title: Inference Based on Non-Probability Samples + maintainer: Łukasz Chrostowski + description: 'Statistical inference with non-probability samples when auxiliary + information from external sources such as probability samples or population totals + or means is available. Details can be found in: Wu et al. (2020) , + Kim et al. (2021) , Wu et al. (2023) , + Kim et al. (2021) , + Kim et al. (2020) .' + date_publication: '2024-11-14' + bug_reports: https://github.com/ncn-foreigners/nonprobsvy/issues + url: https://ncn-foreigners.github.io/nonprobsvy/ + url_cran: https://CRAN.R-project.org/package=nonprobsvy + url_git: https://github.com/ncn-foreigners/nonprobsvy +nonsmooth: + version: 1.0.0 + title: Nonparametric Methods for Smoothing Nonsmooth Data + maintainer: John R.J. Thompson + description: Nonparametric methods for smoothing regression function data with change-points, + utilizing range kernels for iterative and anisotropic smoothing methods. For further + details, see the paper by John R.J. Thompson (2024) . + date_publication: '2024-07-03' + bug_reports: https://github.com/jrjthompson/R-package-nonsmooth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nonsmooth + url_git: https://github.com/jrjthompson/R-package-nonsmooth/ +nopaco: + version: 1.0.9 + title: Non-Parametric Concordance Coefficient + maintainer: Rowan Kuiper + description: |- + A non-parametric test for multi-observer concordance and + differences between concordances in (un)balanced data. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nopaco + url_git: '' +nopp: + version: 1.1.2 + title: Nash Optimal Party Positions + maintainer: Stefano M. Iacus + description: |- + Estimation of party/candidate ideological positions + that correspond to a Nash equilibrium along a + one-dimensional space. + date_publication: '2022-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nopp + url_git: '' +nor1mix: + version: 1.3-3 + title: Normal aka Gaussian 1-d Mixture Models + maintainer: Martin Maechler + description: |- + Onedimensional Normal (i.e. Gaussian) Mixture Models (S3) Classes, + for, e.g., density estimation or clustering algorithms research and teaching; + providing the widely used Marron-Wand densities. Efficient random + number generation and graphics. Fitting to data by efficient ML (Maximum + Likelihood) or traditional EM estimation. + date_publication: '2024-04-06' + bug_reports: https://r-forge.r-project.org/R/?group_id=846 + url: '' + url_cran: https://CRAN.R-project.org/package=nor1mix + url_git: https://curves-etc.r-forge.r-project.org/ +nord: + version: 1.0.0 + title: |- + Arctic Ice Studio's Nord and Group of Seven Inspired Colour + Palettes for 'ggplot2' + maintainer: Jake Kaupp + description: Provides the Arctic Ice Studio's Nord and Group of Seven inspired colour + palettes for use with 'ggplot2' via custom functions. + date_publication: '2019-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nord + url_git: '' +nordklimdata1: + version: '1.2' + title: Dataset for Climate Analysis with Data from the Nordic Region + maintainer: Jose Gama + description: |- + The Nordklim dataset 1.0 is a unique and useful achievement for climate + analysis. It includes observations of twelve different climate elements from + more than 100 stations in the Nordic region, in time span over 100 years. + The project contractors were NORDKLIM/NORDMET on behalf of the National + meteorological services in Denmark (DMI), Finland (FMI), Iceland (VI), + Norway (DNMI) and Sweden (SMHI). + date_publication: '2015-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nordklimdata1 + url_git: '' +norm: + version: 1.0-11.1 + title: Analysis of Multivariate Normal Datasets with Missing Values + maintainer: John Fox + description: |- + An integrated set of functions for the analysis of + multivariate normal datasets with missing values, including implementation of + the EM algorithm, data augmentation, and multiple imputation. + date_publication: '2023-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=norm + url_git: '' +NORMA: + version: '0.1' + title: Builds General Noise SVRs + maintainer: Jesus Prada + description: Builds general noise SVR models using Naive Online R Minimization Algorithm, + NORMA, an optimization method based on classical stochastic gradient descent suitable + for computing SVR models in an online setting. + date_publication: '2017-01-24' + bug_reports: '' + url: http://link.springer.com/chapter/10.1007/978-3-319-19222-2_47 + url_cran: https://CRAN.R-project.org/package=NORMA + url_git: '' +normaliseR: + version: 0.1.2 + title: Re-Scale Vectors and Time-Series Features + maintainer: Trent Henderson + description: |- + Provides standardized access to a range of re-scaling methods for numerical vectors + and time-series features calculated within the 'theft' ecosystem. + date_publication: '2024-02-29' + bug_reports: https://github.com/hendersontrent/normaliseR/issues + url: https://hendersontrent.github.io/normaliseR/ + url_cran: https://CRAN.R-project.org/package=normaliseR + url_git: '' +NormalityAssessment: + version: 0.1.0 + title: A Graphical User Interface for Testing Normality Visually + maintainer: Christopher Casement + description: |- + Package including an interactive Shiny application for + testing normality visually. + date_publication: '2022-11-09' + bug_reports: https://github.com/ccasement/NormalityAssessment/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NormalityAssessment + url_git: https://github.com/ccasement/NormalityAssessment +normalize: + version: 0.1.0 + title: Centering and Scaling of Numeric Data + maintainer: Lennart Oelschläger + description: |- + Provides a simple method for centering and scaling of numeric data. + Certain columns or rows can be ignored when normalizing or be normalized jointly. + date_publication: '2023-11-01' + bug_reports: https://github.com/loelschlaeger/normalize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=normalize + url_git: https://github.com/loelschlaeger/normalize +normalizeH: + version: 1.0.0 + title: Normalize Hadamard Matrix + maintainer: Baidya Nath Mandal + description: Normalize a given Hadamard matrix. A Hadamard matrix is said to be + normalized when its first row and first column entries are all 1, see Hedayat, + A. and Wallis, W. D. (1978) "Hadamard matrices and their applications. The Annals + of Statistics, 1184-1238." . + date_publication: '2022-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=normalizeH + url_git: '' +NormalLaplace: + version: 0.3-1 + title: The Normal Laplace Distribution + maintainer: David Scott + description: |- + Functions for the normal Laplace distribution. Currently, it + provides limited functionality. Density, distribution and quantile + functions, random number generation, and moments are provided. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NormalLaplace + url_git: https://r-forge.r-project.org/projects/rmetrics/ +normalp: + version: 0.7.2.1 + title: Routines for Exponential Power Distribution + maintainer: Angelo M. Mineo + description: 'A collection of utilities referred to Exponential Power distribution, + also known as General Error Distribution (see Mineo, A.M. and Ruggieri, M. (2005), + A software Tool for the Exponential Power Distribution: The normalp package. In + Journal of Statistical Software, Vol. 12, Issue 4).' + date_publication: '2023-12-11' + bug_reports: '' + url: https://www.unipa.it/persone/docenti/m/angelo.mineo + url_cran: https://CRAN.R-project.org/package=normalp + url_git: '' +normalr: + version: 1.0.0 + title: Normalisation of Multiple Variables in Large-Scale Datasets + maintainer: Kevin Chang + description: |- + The robustness of many of the statistical techniques, such as factor analysis, applied in + the social sciences rests upon the assumption of item-level normality. However, when dealing + with real data, these assumptions are often not met. The Box-Cox transformation (Box & Cox, 1964) + provides an optimal transformation for non-normal variables. Yet, for + large datasets of continuous variables, its application in current software programs is cumbersome + with analysts having to take several steps to normalise each variable. We present an R package + 'normalr' that enables researchers to make convenient optimal transformations of multiple variables + in datasets. This R package enables users to quickly and accurately: (1) anchor all of their + variables at 1.00, (2) select the desired precision with which the optimal lambda is estimated, + (3) apply each unique exponent to its variable, (4) rescale resultant values to within their + original X1 and X(n) ranges, and (5) provide original and transformed estimates of skewness, + kurtosis, and other inferential assessments of normality. + date_publication: '2018-03-30' + bug_reports: https://github.com/kcha193/normalr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=normalr + url_git: https://github.com/kcha193/normalr +NormData: + version: '1.1' + title: Derivation of Regression-Based Normative Data + maintainer: Wim Van der Elst + description: Normative data are often used to estimate the relative position of + a raw test score in the population. This package allows for deriving regression-based + normative data. It includes functions that enable the fitting of regression models + for the mean and residual (or variance) structures, test the model assumptions, + derive the normative data in the form of normative tables or automatic scoring + sheets, and estimate confidence intervals for the norms. This package accompanies + the book Van der Elst, W. (2024). Regression-based normative data for psychological + assessment. A hands-on approach using R. Springer Nature. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NormData + url_git: '' +NormExpression: + version: 0.1.1 + title: Normalize Gene Expression Data using Evaluated Methods + maintainer: Shan Gao + description: |- + It provides a framework and a fast and simple way for researchers to evaluate methods (particularly some data-driven methods or their own methods) and then select a best one for data normalization in the gene expression analysis, based on the consistency of metrics and the consistency of datasets. + Zhenfeng Wu, Weixiang Liu, Xiufeng Jin, Deshui Yu, Hua Wang, Gustavo Glusman, Max Robinson, Lin Liu, Jishou Ruan and Shan Gao (2018) . + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NormExpression + url_git: '' +normfluodbf: + version: 2.0.0 + title: |- + Cleans and Normalizes FLUOstar DBF and DAT Files from 'Liposome' + Flux Assays + maintainer: Tingwei Adeck + description: Cleans and Normalizes FLUOstar DBF and DAT Files obtained from liposome + flux assays. Users should verify extended usage of the package on files from other + assay types. + date_publication: '2024-09-27' + bug_reports: https://github.com/AlphaPrime7/normfluodbf/issues + url: https://alphaprime7.github.io/normfluodbf/ + url_cran: https://CRAN.R-project.org/package=normfluodbf + url_git: https://github.com/AlphaPrime7/normfluodbf +norMmix: + version: 0.2-0 + title: Direct MLE for Multivariate Normal Mixture Distributions + maintainer: Nicolas Trutmann + description: |- + Multivariate Normal (i.e. Gaussian) Mixture Models (S3) Classes. + Fitting models to data using 'MLE' (maximum likelihood estimation) for + multivariate normal mixtures via smart parametrization using the 'LDL' + (Cholesky) decomposition, see McLachlan and Peel (2000, ISBN:9780471006268), + Celeux and Govaert (1995) . + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=norMmix + url_git: '' +NormPsy: + version: 1.0.8 + title: Normalisation of Psychometric Tests + maintainer: Cecile Proust-Lima + description: Functions for normalizing psychometric test scores. The normalization + aims at correcting the metrological properties of the psychometric tests such + as the ceiling and floor effects and the curvilinearity (unequal interval scaling). + Functions to compute and plot predictions in the natural scale of the psychometric + test from the estimates of a linear mixed model estimated on the normalized scores + are also provided. See Philipps et al (2014) for details. + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NormPsy + url_git: '' +nortest: + version: 1.0-4 + title: Tests for Normality + maintainer: Uwe Ligges + description: |- + Five omnibus tests for testing the composite hypothesis of + normality. + date_publication: '2015-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nortest + url_git: '' +nortestARMA: + version: 1.0.2 + title: Neyman Smooth Tests of Normality for the Errors of ARMA Models + maintainer: Pierre Lafaye de Micheaux + description: Tests the goodness-of-fit to the Normal distribution for the errors + of an ARMA model. + date_publication: '2017-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nortestARMA + url_git: '' +nortsTest: + version: 1.1.2 + title: Assessing Normality of Stationary Process + maintainer: Asael Alonzo Matamoros + description: Despite that several tests for normality in stationary processes have + been proposed in the literature, consistent implementations of these tests in + programming languages are limited. Seven normality test are implemented. The asymptotic + Lobato & Velasco's, asymptotic Epps, Psaradakis and Vávra, Lobato & Velasco's + and Epps sieve bootstrap approximations, El bouch et al., and the random projections + tests for univariate stationary process. Some other diagnostics such as, unit + root test for stationarity, seasonal tests for seasonality, and arch effect test + for volatility; are also performed. Additionally, the El bouch test performs normality + tests for bivariate time series. The package also offers residual diagnostic for + linear time series models developed in several packages. + date_publication: '2024-01-25' + bug_reports: https://github.com/asael697/nortsTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nortsTest + url_git: https://github.com/asael697/nortsTest +nos: + version: 2.0.0 + title: Compute Node Overlap and Segregation in Ecological Networks + maintainer: Thomas Matthews + description: |- + Calculate NOS (node overlap and segregation) and + the associated metrics described in Strona and Veech (2015) + and Strona et al. (2018) + . The functions provided in the + package enable assessment of structural patterns ranging from + complete node segregation to perfect nestedness in a variety + of network types. In addition, they provide a measure of + network modularity. + date_publication: '2024-03-22' + bug_reports: https://github.com/txm676/nos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nos + url_git: https://github.com/txm676/nos +nosoi: + version: 1.1.2 + title: A Forward Agent-Based Transmission Chain Simulator + maintainer: Sebastian Lequime + description: The aim of 'nosoi' (pronounced no.si) is to provide a flexible agent-based + stochastic transmission chain/epidemic simulator (Lequime et al. Methods in Ecology + and Evolution 11:1002-1007). It is named after the daimones of plague, sickness + and disease that escaped Pandora's jar in the Greek mythology. 'nosoi' is able + to take into account the influence of multiple variable on the transmission process + (e.g. dual-host systems (such as arboviruses), within-host viral dynamics, transportation, + population structure), alone or taken together, to create complex but relatively + intuitive epidemiological simulations. + date_publication: '2024-02-09' + bug_reports: https://github.com/slequime/nosoi/issues + url: https://slequime.github.io/nosoi/ + url_cran: https://CRAN.R-project.org/package=nosoi + url_git: https://github.com/slequime/nosoi +NostalgiR: + version: 1.0.2 + title: Advanced Text-Based Plots + maintainer: Hien D. Nguyen + description: Provides functions to produce advanced ascii graphics, directly to + the terminal window. This package utilizes the txtplot() function from the 'txtplot' + package, to produce text-based histograms, empirical cumulative distribution function + plots, scatterplots with fitted and regression lines, quantile plots, density + plots, image plots, and contour plots. + date_publication: '2015-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NostalgiR + url_git: '' +not: + version: '1.6' + title: Narrowest-Over-Threshold Change-Point Detection + maintainer: Yining Chen + description: 'Provides efficient implementation of the Narrowest-Over-Threshold + methodology for detecting an unknown number of change-points occurring at unknown + locations in one-dimensional data following ''deterministic signal + noise'' model. + Currently implemented scenarios are: piecewise-constant signal, piecewise-constant + signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic + signal, piecewise-constant signal and with piecewise-constant variance of the + noise. For details, see Baranowski, Chen and Fryzlewicz (2019) .' + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=not + url_git: '' +notebookutils: + version: 1.5.3 + title: |- + Dummy R APIs Used in 'Azure Synapse Analytics' for Local + Developments + maintainer: runtimeexp + description: |- + This is a pure dummy interfaces package which mirrors 'MsSparkUtils' APIs of 'Azure Synapse Analytics' for R users, + customer of Azure Synapse can download this package from CRAN for local development. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=notebookutils + url_git: '' +notifyme: + version: 0.3.0 + title: Send Alerts to your Cellphone and Phillips Hue Lights + maintainer: James Black + description: Functions to flash your hue lights, or text yourself, from R. Designed + to be used with long running scripts. + date_publication: '2016-11-27' + bug_reports: https://github.com/epijim/notifyme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=notifyme + url_git: https://github.com/epijim/notifyme +NovelDistns: + version: 0.1.0 + title: |- + Computes PDF, CDF, Quantile, Random Numbers and Measures of + Inference for 3 General Families of Distributions + maintainer: Mutua Kilai + description: Computes the probability density function, the cumulative density function, + quantile function, random numbers and measures of inference for the following + families exponentiated generalized gull alpha power family, exponentiated gull + alpha powerfamily, gull alpha power family. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NovelDistns + url_git: '' +novelforestSG: + version: 2.1.0 + title: Dataset from the Novel Forests of Singapore + maintainer: Hao Ran Lai + description: |2- + + The raw dataset and model used in Lai et al. (2021) + Decoupled responses of native and exotic tree diversities to + distance from old-growth forest and soil phosphorous in + novel secondary forests. Applied Vegetation Science, 24, e12548. + date_publication: '2024-01-15' + bug_reports: https://github.com/hrlai/novelforestSG/issues + url: https://hrlai.github.io/novelforestSG/ + url_cran: https://CRAN.R-project.org/package=novelforestSG + url_git: https://github.com/hrlai/novelforestSG +novelqualcodes: + version: 0.13.1 + title: |- + Visualise the Path to a Stopping Point in Qualitative Interviews + Based on Novel Codes + maintainer: Desi Quintans + description: |- + In semi-structured interviews that use the 'framework' method, it + is not always clear how refinements to interview questions affect the + decision of when to stop interviews. The trend of 'novel' and 'duplicate' + interview codes (novel codes are information that other interviewees have + not previously mentioned) provides insight into the richness of qualitative + information. This package provides tools to visualise when refinements occur + and how that affects the trends of novel and duplicate codes. These + visualisations, when used progressively as new interviews are finished, can + help the researcher to decide on a stopping point for their interviews. + date_publication: '2024-02-08' + bug_reports: https://github.com/DesiQuintans/novelqualcodes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=novelqualcodes + url_git: https://github.com/DesiQuintans/novelqualcodes +NoviceDeveloperResources: + version: 1.2.0 + title: Resources to Assist Novice Developers + maintainer: Barry Zeeberg + description: 'Assist novice developers when preparing a single package or a set + of integrated packages to submit to CRAN. Automate the following individual or + batch processing: check local source packages; build local .tar.gz source files; + install packages from local .tar.gz files; detect conflicts between function names + in the environment.' + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NoviceDeveloperResources + url_git: '' +NoviceDeveloperResources2: + version: 1.1.0 + title: Further Resources to Assist Novice Developers + maintainer: Barry Zeeberg + description: 'Assist novice developers when preparing a single package or a set + of integrated packages to submit to CRAN. Provide additional resources to facilitate + the automation of the following individual or batch processing: check local source + packages; build local .tar.gz source files; install packages from local .tar.gz + files; detect conflicts between function names in the environment. The additional + resources include determining the identity and ordering of the packages to process + when updating an imported package.' + date_publication: '2024-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NoviceDeveloperResources2 + url_git: '' +noweb: + version: 1.1-4 + title: The 'noweb' System for R + maintainer: Terry Therneau + description: The noweb system for source code, implemented in R. + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=noweb + url_git: '' +Nozzle.R1: + version: 1.1-1.1 + title: Nozzle Reports + maintainer: Nils Gehlenborg + description: |- + The Nozzle package provides an API to generate HTML + reports with dynamic user interface elements based on + JavaScript and CSS (Cascading Style Sheets). Nozzle was + designed to facilitate summarization and rapid browsing of + complex results in data analysis pipelines where multiple + analyses are performed frequently on big data sets. The package + can be applied to any project where user-friendly reports need + to be created. + date_publication: '2022-06-23' + bug_reports: http://www.github.com/parklab/nozzle/issues + url: http://gdac.broadinstitute.org/nozzle + url_cran: https://CRAN.R-project.org/package=Nozzle.R1 + url_git: http://github.com/parklab/nozzle +np: + version: 0.60-18 + title: Nonparametric Kernel Smoothing Methods for Mixed Data Types + maintainer: Jeffrey S. Racine + description: Nonparametric (and semiparametric) kernel methods that seamlessly handle + a mix of continuous, unordered, and ordered factor data types. We would like to + gratefully acknowledge support from the Natural Sciences and Engineering Research + Council of Canada (NSERC, ), the Social Sciences + and Humanities Research Council of Canada (SSHRC, ), + and the Shared Hierarchical Academic Research Computing Network (SHARCNET, ). + We would also like to acknowledge the contributions of the GNU GSL authors. In + particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated + support for quantile knots (in addition to uniform knots), providing missing functionality + for derivatives, and for extending the splines beyond their endpoints. + date_publication: '2024-12-10' + bug_reports: https://github.com/JeffreyRacine/R-Package-np/issues + url: '' + url_cran: https://CRAN.R-project.org/package=np + url_git: https://github.com/JeffreyRacine/R-Package-np +nparACT: + version: '0.8' + title: Non-Parametric Measures of Actigraphy Data + maintainer: Christine Blume + description: 'Computes interdaily stability (IS), intradaily variability (IV) & + the relative amplitude (RA) from actigraphy data as described in Blume et al. + (2016) and van Someren et al. (1999) . + Additionally, it also computes L5 (i.e. the 5 hours with lowest average actigraphy + amplitude) and M10 (the 10 hours with highest average amplitude) as well as the + respective start times. The flex versions will also compute the L-value for a + user-defined number of minutes. IS describes the strength of coupling of a rhythm + to supposedly stable zeitgebers. It varies between 0 (Gaussian Noise) and 1 for + perfect IS. IV describes the fragmentation of a rhythm, i.e. the frequency and + extent of transitions between rest and activity. It is near 0 for a perfect sine + wave, about 2 for Gaussian noise and may be even higher when a definite ultradian + period of about 2 hrs is present. RA is the relative amplitude of a rhythm. Note + that to obtain reliable results, actigraphy data should cover a reasonable number + of days.' + date_publication: '2017-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nparACT + url_git: '' +nparcomp: + version: '3.0' + title: Multiple Comparisons and Simultaneous Confidence Intervals + maintainer: Kerstin Rubarth + description: With this package, it is possible to compute nonparametric simultaneous + confidence intervals for relative contrast effects in the unbalanced one way layout. + Moreover, it computes simultaneous p-values. The simultaneous confidence intervals + can be computed using multivariate normal distribution, multivariate t-distribution + with a Satterthwaite Approximation of the degree of freedom or using multivariate + range preserving transformations with Logit or Probit as transformation function. + 2 sample comparisons can be performed with the same methods described above. There + is no assumption on the underlying distribution function, only that the data have + to be at least ordinal numbers. See Konietschke et al. (2015) + for details. + date_publication: '2019-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nparcomp + url_git: '' +nparLD: + version: '2.2' + title: |- + Nonparametric Analysis of Longitudinal Data in Factorial + Experiments + maintainer: Frank Konietschke + description: |- + Performs nonparametric + analysis of longitudinal data in factorial experiments. + Longitudinal data are those which are collected from the same + subjects over time, and they frequently arise in biological + sciences. Nonparametric methods do not require distributional + assumptions, and are applicable to a variety of data types + (continuous, discrete, purely ordinal, and dichotomous). Such + methods are also robust with respect to outliers and for small + sample sizes. + date_publication: '2022-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nparLD + url_git: '' +nparMD: + version: 0.2.1 + title: Nonparametric Analysis of Multivariate Data in Factorial Designs + maintainer: Maximilian Kiefel + description: |- + Analysis of multivariate data with two-way completely randomized + factorial design. The analysis is based on fully nonparametric, rank-based + methods and uses test statistics based on the Dempster's ANOVA, Wilk's Lambda, + Lawley-Hotelling and Bartlett-Nanda-Pillai criteria. The multivariate + response is allowed to be ordinal, quantitative, binary or a mixture of the + different variable types. The package offers two functions performing the + analysis, one for small and the other for large sample sizes. The underlying methodology + is largely described in Bathke and Harrar (2016) and in + Munzel and Brunner (2000) . + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nparMD + url_git: '' +nparsurv: + version: 0.1.0 + title: |- + Nonparametric Tests for Main Effects, Simple Effects and + Interaction Effect in a Factorial Design with Censored Data + maintainer: Christine Kroener + description: Nonparametric Tests for Main Effects, Simple Effects and Interaction + Effect with Censored Data and Two Factorial Influencing Variables. + date_publication: '2017-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nparsurv + url_git: '' +NPBayesImputeCat: + version: '0.5' + title: Non-Parametric Bayesian Multiple Imputation for Categorical Data + maintainer: Jingchen Hu + description: These routines create multiple imputations of missing at random categorical + data, and create multiply imputed synthesis of categorical data, with or without + structural zeros. Imputations and syntheses are based on Dirichlet process mixtures + of multinomial distributions, which is a non-parametric Bayesian modeling approach + that allows for flexible joint modeling, described in Manrique-Vallier and Reiter + (2014) . + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPBayesImputeCat + url_git: '' +NPBBBDAefficiency: + version: 0.1.0 + title: |- + A-Efficiency for Nested Partially Balanced Bipartite Block + (NPBBB) Designs + maintainer: Vinayaka + description: 'Nested Partially Balanced Bipartite Block (NPBBB) designs involve + two levels of blocking: (i) The block design (ignoring sub-block classification) + serves as a partially balanced bipartite block (PBBB) design, and (ii) The sub-block + design (ignoring block classification) also serves as a PBBB design. More details + on constructions of the PBBB designs and their characterization properties are + available in Vinayaka et al.(2023) . This package + calculates A-efficiency values for both block and sub-block structures, along + with all parameters of a given NPBBB design.' + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPBBBDAefficiency + url_git: '' +npboottprm: + version: 0.3.2 + title: Nonparametric Bootstrap Test with Pooled Resampling + maintainer: Mackson Ncube + description: |- + Addressing crucial research questions often necessitates a small + sample size due to factors such as distinctive target populations, rarity + of the event under study, time and cost constraints, ethical concerns, or + group-level unit of analysis. Many readily available analytic methods, + however, do not accommodate small sample sizes, and the choice of the best + method can be unclear. The 'npboottprm' package enables the execution of + nonparametric bootstrap tests with pooled resampling to help fill this gap. + Grounded in the statistical methods for small sample size studies detailed + in Dwivedi, Mallawaarachchi, and Alvarado (2017) , the + package facilitates a range of statistical tests, encompassing independent + t-tests, paired t-tests, and one-way Analysis of Variance (ANOVA) F-tests. + The nonparboot() function undertakes essential computations, yielding + detailed outputs which include test statistics, effect sizes, confidence + intervals, and bootstrap distributions. Further, 'npboottprm' incorporates + an interactive 'shiny' web application, nonparboot_app(), offering intuitive, + user-friendly data exploration. + date_publication: '2024-09-13' + bug_reports: https://github.com/mightymetrika/npboottprm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npboottprm + url_git: https://github.com/mightymetrika/npboottprm +npboottprmFBar: + version: 0.2.0 + title: Informative Nonparametric Bootstrap Test with Pooled Resampling + maintainer: Mackson Ncube + description: |- + Sample sizes are often small due to hard to reach target populations, + rare target events, time constraints, limited budgets, or ethical considerations. + Two statistical methods with promising performance in small samples are the + nonparametric bootstrap test with pooled resampling method, which is the + focus of Dwivedi, Mallawaarachchi, and Alvarado (2017) , + and informative hypothesis testing, which is implemented in the 'restriktor' + package. The 'npboottprmFBar' package uses the nonparametric bootstrap test + with pooled resampling method to implement informative hypothesis testing. + The bootFbar() function can be used to analyze data with this method and the + persimon() function can be used to conduct performance simulations on type-one + error and statistical power. + date_publication: '2024-09-08' + bug_reports: https://github.com/mightymetrika/npboottprmFBar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npboottprmFBar + url_git: https://github.com/mightymetrika/npboottprmFBar +npbr: + version: '1.8' + title: Nonparametric Boundary Regression + maintainer: Thibault Laurent + description: A variety of functions for the best known and most innovative approaches + to nonparametric boundary estimation. The selected methods are concerned with + empirical, smoothed, unrestricted as well as constrained fits under both separate + and multiple shape constraints. They cover robust approaches to outliers as well + as data envelopment techniques based on piecewise polynomials, splines, local + linear fitting, extreme values and kernel smoothing. The package also seamlessly + allows for Monte Carlo comparisons among these different estimation methods. Its + use is illustrated via a number of empirical applications and simulated examples. + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npbr + url_git: '' +NPCD: + version: 1.0-11 + title: Nonparametric Methods for Cognitive Diagnosis + maintainer: Yi Zheng + description: An array of nonparametric and parametric estimation methods for cognitive + diagnostic models, including nonparametric classification of examinee attribute + profiles, joint maximum likelihood estimation (JMLE) of examinee attribute profiles + and item parameters, and nonparametric refinement of the Q-matrix, as well as + conditional maximum likelihood estimation (CMLE) of examinee attribute profiles + given item parameters and CMLE of item parameters given examinee attribute profiles. + Currently the nonparametric methods in the package support both conjunctive and + disjunctive models, and the parametric methods in the package support the DINA + model, the DINO model, the NIDA model, the G-NIDA model, and the R-RUM model. + date_publication: '2019-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPCD + url_git: '' +NPCDTools: + version: '1.0' + title: The Nonparametric Classification Methods for Cognitive Diagnosis + maintainer: Weixuan Xiao + description: Statistical tools for analyzing cognitive diagnosis (CD) data collected + from small settings using the nonparametric classification (NPCD) framework. The + core methods of the NPCD framework includes the nonparametric classification (NPC) + method developed by Chiu and Douglas (2013) and + the general NPC (GNPC) method developed by Chiu, Sun, and Bian (2018) + and Chiu and Köhn (2019) . An extension of the + NPCD framework included in the package is the nonparametric method for multiple-choice + items (MC-NPC) developed by Wang, Chiu, and Koehn (2023) . Functions + associated with various extensions concerning the evaluation, validation, and + feasibility of the CD analysis are also provided. These topics include the completeness + of Q-matrix, Q-matrix refinement method, as well as Q-matrix estimation. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPCDTools + url_git: '' +NPCirc: + version: 3.1.1 + title: Nonparametric Circular Methods + maintainer: Maria Alonso-Pena + description: |- + Nonparametric smoothing methods for density and regression estimation involving circular data, + including the estimation of the mean regression function and other conditional characteristics. + date_publication: '2022-11-10' + bug_reports: '' + url: https://www.jstatsoft.org/v61/i09/ + url_cran: https://CRAN.R-project.org/package=NPCirc + url_git: '' +npclust: + version: 0.1.1 + title: Nonparametric Tests for Incomplete Clustered Data + maintainer: Yue Cui + description: Nonparametric tests for clustered data in pre-post intervention design + documented in Cui and Harrar (2021) and Harrar and + Cui (2022) . Other than the main test results + mentioned in the reference paper, this package also provides a function to calculate + the sample size allocations for the input long format data set, and also a function + for adjusted/unadjusted confidence intervals calculations. There are also functions + to visualize the distribution of data across different intervention groups over + time, and also the adjusted/unadjusted confidence intervals. + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npclust + url_git: '' +NPCox: + version: '1.3' + title: Nonparametric and Semiparametric Proportional Hazards Model + maintainer: Qi Yang + description: An estimation procedure for the analysis of nonparametric proportional + hazards model (e.g. h(t) = h0(t)exp(b(t)'Z)), providing estimation of b(t) and + its pointwise standard errors, and semiparametric proportional hazards model (e.g. + h(t) = h0(t)exp(b(t)'Z1 + c*Z2)), providing estimation of b(t), c and their standard + errors. More details can be found in Lu Tian et al. (2005) . + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPCox + url_git: '' +npcp: + version: 0.2-6 + title: |- + Some Nonparametric CUSUM Tests for Change-Point Detection in + Possibly Multivariate Observations + maintainer: Ivan Kojadinovic + description: |- + Provides nonparametric CUSUM tests for detecting changes + in possibly serially dependent univariate or low-dimensional + multivariate observations. Retrospective tests sensitive to changes + in the expectation, the variance, the covariance, the + autocovariance, the distribution function, Spearman's rho, Kendall's + tau, Gini's mean difference, and the copula are provided, as well as + a test for detecting changes in the distribution of independent + block maxima (with environmental studies in mind). The package also + contains a test sensitive to changes in the autocopula and a + combined test of stationarity sensitive to changes in the + distribution function and the autocopula. The latest additions are + an open-end sequential test based on the retrospective CUSUM + statistic that can be used for monitoring changes in the mean of + possibly serially dependent univariate observations, as well as + closed-end and open-end sequential tests based on empirical + distribution functions that can be used for monitoring changes in + the contemporary distribution of possibly serially dependent + univariate or low-dimensional multivariate observations. + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npcp + url_git: '' +npcs: + version: 0.1.1 + title: Neyman-Pearson Classification via Cost-Sensitive Learning + maintainer: Ching-Tsung Tsai + description: We connect the multi-class Neyman-Pearson classification (NP) problem + to the cost-sensitive learning (CS) problem, and propose two algorithms (NPMC-CX + and NPMC-ER) to solve the multi-class NP problem through cost-sensitive learning + tools. Under certain conditions, the two algorithms are shown to satisfy multi-class + NP properties. More details are available in the paper "Neyman-Pearson Multi-class + Classification via Cost-sensitive Learning" (Ye Tian and Yang Feng, 2021). + date_publication: '2023-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npcs + url_git: '' +npcure: + version: 0.1-5 + title: Nonparametric Estimation in Mixture Cure Models + maintainer: Ignacio López-de-Ullibarri + description: Performs nonparametric estimation in mixture cure models, and significance + tests for the cure probability. For details, see López-Cheda et al. (2017a) + and López-Cheda et al. (2017b) . + date_publication: '2020-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npcure + url_git: '' +npcurePK: + version: 1.0-2 + title: Mixture Cure Model Estimation with Cure Status Partially Known + maintainer: Wende Clarence Safari + description: Performs nonparametric estimation in mixture cure models when the cure + status is partially known. For details, see Safari et al (2021) , + Safari et al (2022) and Safari et al (2023) . + date_publication: '2023-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npcurePK + url_git: '' +npde: + version: '3.5' + title: |- + Normalised Prediction Distribution Errors for Nonlinear + Mixed-Effect Models + maintainer: Emmanuelle Comets + description: Provides routines to compute normalised prediction distribution errors, + a metric designed to evaluate non-linear mixed effect models such as those used + in pharmacokinetics and pharmacodynamics. + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npde + url_git: '' +npDoseResponse: + version: '0.1' + title: Nonparametric Estimation and Inference on Dose-Response Curves + maintainer: Yikun Zhang + description: |- + A novel integral estimator for estimating the causal effects with continuous treatments (or dose-response curves) and a localized derivative estimator for estimating the derivative effects. The inference on the dose-response curve and its derivative is conducted via nonparametric bootstrap. + The reference paper is Zhang, Chen, and Giessing (2024) . + date_publication: '2024-05-28' + bug_reports: https://github.com/zhangyk8/npDoseResponse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npDoseResponse + url_git: https://github.com/zhangyk8/npDoseResponse/ +npExact: + version: '0.2' + title: |- + Exact Nonparametric Hypothesis Tests for the Mean, Variance and + Stochastic Inequality + maintainer: Oliver Reiter + description: Provides several novel exact hypothesis tests with minimal assumptions + on the errors. The tests are exact, meaning that their p-values are correct for + the given sample sizes (the p-values are not derived from asymptotic analysis). + The test for stochastic inequality is for ordinal comparisons based on two independent + samples and requires no assumptions on the errors. The other tests include tests + for the mean and variance of a single sample and comparing means in independent + samples. All these tests only require that the data has known bounds (such as + percentages that lie in [0,100]. These bounds are part of the input. + date_publication: '2018-12-03' + bug_reports: https://github.com/zauster/npExact/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npExact + url_git: https://github.com/zauster/npExact +NPFD: + version: 1.0.0 + title: N-Power Fourier Deconvolution + maintainer: Akin Anarat + description: Provides tools for non-parametric Fourier deconvolution using the N-Power + Fourier Deconvolution (NPFD) method. This package includes methods for density + estimation (densprf()) and sample generation (createSample()), enabling users + to perform statistical analyses on mixed or replicated data sets. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPFD + url_git: '' +NPflow: + version: 0.13.5 + title: |- + Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry + Data + maintainer: Boris P Hejblum + description: |- + Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions + modeling oriented towards flow-cytometry data preprocessing applications. Method is + detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) . + date_publication: '2024-01-13' + bug_reports: https://github.com/sistm/NPflow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NPflow + url_git: '' +nph: + version: '2.1' + title: |- + Planning and Analysing Survival Studies under Non-Proportional + Hazards + maintainer: Robin Ristl + description: |- + Piecewise constant hazard functions are used to flexibly model survival distributions with non-proportional hazards and + to simulate data from the specified distributions. A function to calculate weighted log-rank tests for the comparison of two + hazard functions is included. Also, a function to calculate a test using the maximum of a set of test statistics from weighted + log-rank tests (MaxCombo test) is provided. This test utilizes the asymptotic multivariate normal joint distribution of the + separate test statistics. The correlation is estimated from the data. These methods are described in Ristl et al. (2021) + . + Finally, a function is provided for the estimation and inferential statistics of various parameters that quantify the difference + between two survival curves. Eligible parameters are differences in survival probabilities, log survival probabilities, + complementary log log (cloglog) transformed survival probabilities, quantiles of the survival functions, log transformed quantiles, + restricted mean survival times, as well as an average hazard ratio, the Cox model score statistic (logrank statistic), and the + Cox-model hazard ratio. Adjustments for multiple testing and simultaneous confidence intervals are calculated using a multivariate + normal approximation to the set of selected parameters. + date_publication: '2022-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nph + url_git: '' +NPHazardRate: + version: '0.1' + title: Nonparametric Hazard Rate Estimation + maintainer: Dimitrios Bagkavos + description: Provides functions and examples for histogram, kernel (classical, variable + bandwidth and transformations based), discrete and semiparametric hazard rate + estimators. + date_publication: '2018-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPHazardRate + url_git: '' +NPHMC: + version: '2.3' + title: |- + Sample Size Calculation for the Proportional Hazards Mixture + Cure Model + maintainer: Chao Cai + description: An R-package for calculating sample size of a survival trial with or + without cure fractions. + date_publication: '2022-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPHMC + url_git: '' +nphPower: + version: 1.1.0 + title: Sample Size Calculation under Non-Proportional Hazards + maintainer: Huan Cheng + description: |- + Performs combination tests and sample size calculation for + fixed design with survival endpoints using combination tests under either + proportional hazards or non-proportional hazards. The combination tests + include maximum weighted log-rank test and projection test. The sample + size calculation procedure is very flexible, allowing for user-defined + hazard ratio function and considering various trial conditions like + staggered entry, drop-out etc. The sample size calculation also applies to + various cure models such as proportional hazards cure model, cure model with + (random) delayed treatments effects. Trial simulation function is also provided + to facilitate the empirical power calculation. The references for + projection test and maximum weighted logrank test include Brendel et al. (2014) + and Cheng and He (2021) . The + references for sample size calculation under proportional hazard include + Schoenfeld (1981) and Freedman (1982) . + The references for calculation under non-proportional hazards include + Lakatos (1988) and Cheng and He (2023) . + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nphPower + url_git: https://github.com/hcheng99/nphPower +nphRCT: + version: 0.1.1 + title: Non-Proportional Hazards in Randomized Controlled Trials + maintainer: Dominic Magirr + description: Perform a stratified weighted log-rank test in a randomized controlled + trial. Tests can be visualized as a difference in average score on the two treatment + arms. These methods are described in Magirr and Burman (2018) , + Magirr (2020) , and Magirr and Jimenez (2022) . + date_publication: '2024-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nphRCT + url_git: '' +npi: + version: 0.2.0 + title: Access the U.S. National Provider Identifier Registry API + maintainer: Frank Farach + description: |- + Access the United States National Provider Identifier + Registry API . Obtain and transform + administrative data linked to a specific individual or organizational + healthcare provider, or perform advanced searches based on provider name, + location, type of service, credentials, and other attributes exposed by + the API. + date_publication: '2022-11-14' + bug_reports: https://github.com/ropensci/npi/issues/ + url: https://docs.ropensci.org/npi/ + url_cran: https://CRAN.R-project.org/package=npi + url_git: https://github.com/ropensci/npi/ +npIntFactRep: + version: '1.5' + title: |- + Nonparametric Interaction Tests for Factorial Designs with + Repeated Measures + maintainer: Jos Feys + description: 'Returns nonparametric aligned rank tests for the interaction in two-way + factorial designs, on R data sets with repeated measures in ''wide'' format. Five + ANOVAs tables are reported. A PARAMETRIC one on the original data, one for a CHECK + upon the interaction alignments, and three aligned rank tests: one on the aligned + REGULAR, one on the FRIEDMAN, and one on the KOCH ranks. In these rank tests, + only the resulting values for the interaction are relevant.' + date_publication: '2015-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npIntFactRep + url_git: '' +NPIstats: + version: 0.1.0 + title: Nonparametric Predictive Inference + maintainer: Tahani Coolen-Maturi + description: 'An implementation of the Nonparametric Predictive Inference approach + in R. It provides tools for quantifying uncertainty via lower and upper probabilities. + It includes useful functions for pairwise and multiple comparisons: comparing + two groups with and without terminated tails, selecting the best group, selecting + the subset of best groups, selecting the subset including the best group.' + date_publication: '2021-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPIstats + url_git: '' +npiv: + version: 0.1.3 + title: Nonparametric Instrumental Variables Estimation and Inference + maintainer: Timothy Christensen + description: Implements methods introduced in Chen, Christensen, and Kankanala (2024) + for estimating and constructing uniform confidence + bands for nonparametric structural functions using instrumental variables, including + data-driven choice of tuning parameters. All methods in this package apply to + nonparametric regression as a special case. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npiv + url_git: '' +nplplot: + version: '4.7' + title: Plotting Linkage and Association Results + maintainer: Daniel E. Weeks + description: |- + Provides routines for plotting + linkage and association results along a chromosome, + with marker names displayed along the top border. + There are also routines for generating BED and BedGraph + custom tracks for viewing in the UCSC genome browser. + The data reformatting program Mega2 uses this + package to plot output from a variety of + programs. + date_publication: '2023-12-20' + bug_reports: '' + url: https://watson.hgen.pitt.edu/register/ + url_cran: https://CRAN.R-project.org/package=nplplot + url_git: '' +nplr: + version: 0.1-8 + title: N-Parameter Logistic Regression + maintainer: Tymoteusz Kwiecinski + description: Performing drug response analyses and IC50 estimations using n-Parameter + logistic regression. Can also be applied to proliferation analyses. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nplr + url_git: https://github.com/mini-pw/nplr +nplyr: + version: 0.2.0 + title: A Grammar of Nested Data Manipulation + maintainer: Mark Rieke + description: |- + Provides functions for manipulating nested data frames in a + list-column using 'dplyr' syntax. Rather than + unnesting, then manipulating a data frame, 'nplyr' allows users to + manipulate each nested data frame directly. 'nplyr' is a wrapper for 'dplyr' + functions that provide tools for common data manipulation steps: filtering + rows, selecting columns, summarising grouped data, among others. + date_publication: '2023-02-14' + bug_reports: https://github.com/markjrieke/nplyr/issues + url: https://markjrieke.github.io/nplyr/ + url_cran: https://CRAN.R-project.org/package=nplyr + url_git: https://github.com/markjrieke/nplyr +npmlda: + version: 1.0.0 + title: Nonparametric Models for Longitudinal Data + maintainer: Xin Tian + description: |- + Support the book: Wu CO and Tian X (2018). Nonparametric Models for Longitudinal Data. + Chapman & Hall/CRC (to appear); and provide fit for using global and local smoothing methods + for the conditional-mean and conditional-distribution based models with longitudinal Data. + date_publication: '2018-02-12' + bug_reports: https://github.com/npmldabook/npmlda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npmlda + url_git: https://github.com/npmldabook/npmlda/ +NPMLEcmprsk: + version: '3.0' + title: |- + Type-Specific Failure Rate and Hazard Rate on Competing Risks + Data + maintainer: Chung-Hsing Chen + description: Given a failure type, the function computes covariate-specific probability + of failure over time and covariate-specific conditional hazard rate based on possibly + right-censored competing risk data. Specifically, it computes the non-parametric + maximum-likelihood estimates of these quantities and their asymptotic variances + in a semi-parametric mixture model for competing-risks data, as described in Chang + et al. (2007a). + date_publication: '2018-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPMLEcmprsk + url_git: '' +npmlreg: + version: 0.46-5 + title: |- + Nonparametric Maximum Likelihood Estimation for Random Effect + Models + maintainer: Jochen Einbeck + description: |- + Nonparametric maximum likelihood estimation or Gaussian + quadrature for overdispersed generalized linear models and + variance component models. + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npmlreg + url_git: '' +npmr: + version: 1.3.1 + title: Nuclear Penalized Multinomial Regression + maintainer: Scott Powers + description: |- + Fit multinomial logistic regression with a penalty on the nuclear + norm of the estimated regression coefficient matrix, using proximal + gradient descent. + date_publication: '2023-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npmr + url_git: '' +npmv: + version: 2.4.1 + title: Nonparametric Comparison of Multivariate Samples + maintainer: Amanda Ellis + description: Performs analysis of one-way multivariate data, for small samples using + Nonparametric techniques. Using approximations for ANOVA Type, Wilks' Lambda, + Lawley Hotelling, and Bartlett Nanda Pillai Test statics, the package compares + the multivariate distributions for a single explanatory variable. The comparison + is also performed using a permutation test for each of the four test statistics. + The package also performs an all-subsets algorithm regarding variables and regarding + factor levels. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npmv + url_git: '' +npordtests: + version: '1.2' + title: |- + Nonparametric Tests for Equality of Location Against Ordered + Alternatives + maintainer: Bulent Altunkaynak + description: Performs nonparametric tests for equality of location against ordered + alternatives. + date_publication: '2019-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npordtests + url_git: '' +NPP: + version: 0.6.0 + title: Normalized Power Prior Bayesian Analysis + maintainer: Zifei Han + description: |- + Posterior sampling in several commonly used distributions using + normalized power prior as described in + Duan, Ye and Smith (2006) and + Ibrahim et.al. (2015) . + Sampling of the power parameter is achieved via + either independence Metropolis-Hastings or random walk Metropolis-Hastings + based on transformation. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NPP + url_git: '' +nppbib: + version: 1.2-0 + title: |- + Nonparametric Partially-Balanced Incomplete Block Design + Analysis + maintainer: David Allingham + description: |- + Implements a nonparametric statistical test for rank or score data + from partially-balanced incomplete block-design experiments. + date_publication: '2020-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nppbib + url_git: https://github.com/dalling1 +npphen: + version: 2.0.0 + title: |- + Vegetation Phenological Cycle and Anomaly Detection using Remote + Sensing Data + maintainer: José A. Lastra + description: |- + Calculates phenological cycle and anomalies using a non-parametric + approach applied to time series of vegetation indices derived from remote sensing data + or field measurements. The package implements basic and high-level functions for + manipulating vector data (numerical series) and raster data (satellite derived products). + Processing of very large raster files is supported. For more information, please check + the following paper: + Chávez et al. (2023) . + date_publication: '2023-10-12' + bug_reports: https://github.com/labGRS/npphen/issues + url: https://labgrs.github.io/npphen/ + url_cran: https://CRAN.R-project.org/package=npphen + url_git: https://github.com/labGRS/npphen +NPRED: + version: 1.1.0 + title: 'Predictor Identifier: Nonparametric Prediction' + maintainer: Ze Jiang + description: Partial informational correlation (PIC) is used to identify the meaningful + predictors to the response from a large set of potential predictors. Details of + methodologies used in the package can be found in Sharma, A., Mehrotra, R. (2014). + , Sharma, A., Mehrotra, R., Li, J., & Jha, S. (2016). + , and Mehrotra, R., & Sharma, A. (2006). . + date_publication: '2024-07-25' + bug_reports: https://github.com/zejiang-unsw/NPRED/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NPRED + url_git: https://github.com/zejiang-unsw/NPRED#readme +npreg: + version: 1.1.0 + title: Nonparametric Regression via Smoothing Splines + maintainer: Nathaniel E. Helwig + description: Multiple and generalized nonparametric regression using smoothing spline + ANOVA models and generalized additive models, as described in Helwig (2020) . + Includes support for Gaussian and non-Gaussian responses, smoothers for multiple + types of predictors (including random intercepts), interactions between smoothers + of mixed types, eight different methods for smoothing parameter selection, and + flexible tools for diagnostics, inference, and prediction. + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npreg + url_git: '' +npregderiv: + version: '1.0' + title: |- + Nonparametric Estimation of the Derivatives of a Regression + Function + maintainer: Olga Savchuk + description: Estimating the first and second derivatives of a regression function + by the method of Wang and Lin (2015) . + date_publication: '2020-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npregderiv + url_git: '' +npregfast: + version: 1.5.2 + title: |- + Nonparametric Estimation of Regression Models with + Factor-by-Curve Interactions + maintainer: Marta Sestelo + description: |- + A method for obtaining nonparametric estimates of regression models + with or without factor-by-curve interactions using local polynomial kernel + smoothers or splines. Additionally, a parametric model (allometric model) can be + estimated. + date_publication: '2022-09-02' + bug_reports: https://github.com/sestelo/npregfast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npregfast + url_git: '' +nprobust: + version: 0.4.0 + title: |- + Nonparametric Robust Estimation and Inference Methods using + Local Polynomial Regression and Kernel Density Estimation + maintainer: Sebastian Calonico + description: 'Tools for data-driven statistical analysis using local polynomial + regression and kernel density estimation methods as described in Calonico, Cattaneo + and Farrell (2018, ): lprobust() for local + polynomial point estimation and robust bias-corrected inference, lpbwselect() + for local polynomial bandwidth selection, kdrobust() for kernel density point + estimation and robust bias-corrected inference, kdbwselect() for kernel density + bandwidth selection, and nprobust.plot() for plotting results. The main methodological + and numerical features of this package are described in Calonico, Cattaneo and + Farrell (2019, ).' + date_publication: '2020-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nprobust + url_git: '' +nproc: + version: 2.1.5 + title: |- + Neyman-Pearson (NP) Classification Algorithms and NP Receiver + Operating Characteristic (NP-ROC) Curves + maintainer: Yang Feng + description: |- + In many binary classification applications, such as disease + diagnosis and spam detection, practitioners commonly face the need to limit + type I error (i.e., the conditional probability of misclassifying a class 0 + observation as class 1) so that it remains below a desired threshold. To address + this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; + it minimizes type II error (i.e., the conditional probability of misclassifying + a class 1 observation as class 0) while enforcing an upper bound, alpha, on the + type I error. Although the NP paradigm has a century-long history in hypothesis + testing, it has not been well recognized and implemented in classification + schemes. Common practices that directly limit the empirical type I error to + no more than alpha do not satisfy the type I error control objective because + the resulting classifiers are still likely to have type I errors much larger + than alpha. As a result, the NP paradigm has not been properly implemented + for many classification scenarios in practice. In this work, we develop the + first umbrella algorithm that implements the NP paradigm for all scoring-type + classification methods, including popular methods such as logistic regression, + support vector machines and random forests. Powered by this umbrella algorithm, + we propose a novel graphical tool for NP classification methods: NP receiver + operating characteristic (NP-ROC) bands, motivated by the popular receiver + operating characteristic (ROC) curves. NP-ROC bands will help choose in a data + adaptive way and compare different NP classifiers. + date_publication: '2020-01-13' + bug_reports: '' + url: http://advances.sciencemag.org/content/4/2/eaao1659 + url_cran: https://CRAN.R-project.org/package=nproc + url_git: '' +npROCRegression: + version: 1.0-7 + title: Kernel-Based Nonparametric ROC Regression Modelling + maintainer: Maria Xose Rodriguez-Alvarez + description: Implements several nonparametric regression approaches for the inclusion + of covariate information on the receiver operating characteristic (ROC) framework. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npROCRegression + url_git: '' +nprotreg: + version: 1.1.1 + title: Nonparametric Rotations for Sphere-Sphere Regression + maintainer: Giovanni Lafratta + description: |- + Fits sphere-sphere regression models by estimating locally weighted + rotations. Simulation of sphere-sphere data according to non-rigid rotation + models. Provides methods for bias reduction applying iterative procedures + within a Newton-Raphson learning scheme. Cross-validation is exploited to select + smoothing parameters. See Marco Di Marzio, Agnese Panzera & Charles C. Taylor + (2018) . + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nprotreg + url_git: '' +npsf: + version: 0.8.0 + title: |- + Nonparametric and Stochastic Efficiency and Productivity + Analysis + maintainer: Oleg Badunenko + description: Nonparametric efficiency measurement and statistical inference via + DEA type estimators (see Färe, Grosskopf, and Lovell (1994) , + Kneip, Simar, and Wilson (2008) and Badunenko + and Mozharovskyi (2020) ) as well as Stochastic + Frontier estimators for both cross-sectional data and 1st, 2nd, and 4th generation + models for panel data (see Kumbhakar and Lovell (2003) , + Badunenko and Kumbhakar (2016) ). The stochastic + frontier estimators can handle both half-normal and truncated normal models with + conditional mean and heteroskedasticity. The marginal effects of determinants + can be obtained. + date_publication: '2020-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npsf + url_git: '' +npsm: + version: 2.0.0 + title: Nonparametric Statistical Methods + maintainer: John Kloke + description: Accompanies the book "Nonparametric Statistical Methods Using R, 2nd + Edition" by Kloke and McKean (2024, ISBN:9780367651350). Includes methods, datasets, + and random number generation useful for the study of robust and/or nonparametric + statistics. Emphasizes classical nonparametric methods for a variety of designs + --- especially one-sample and two-sample problems. Includes methods for general + scores, including estimation and testing for the two-sample location problem as + well as Hogg's adaptive method. + date_publication: '2024-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npsm + url_git: https://github.com/kloke/npsm +npsp: + version: 0.7-13 + title: Nonparametric Spatial Statistics + maintainer: Ruben Fernandez-Casal + description: |- + Multidimensional nonparametric spatial (spatio-temporal) geostatistics. + S3 classes and methods for multidimensional: linear binning, + local polynomial kernel regression (spatial trend estimation), density and variogram estimation. + Nonparametric methods for simultaneous inference on both spatial trend + and variogram functions (for spatial processes). + Nonparametric residual kriging (spatial prediction). + For details on these methods see, for example, Fernandez-Casal and Francisco-Fernandez (2014) + or Castillo-Paez et al. (2019) . + date_publication: '2024-02-19' + bug_reports: https://github.com/rubenfcasal/npsp/issues/ + url: https://rubenfcasal.github.io/npsp/ + url_cran: https://CRAN.R-project.org/package=npsp + url_git: https://github.com/rubenfcasal/npsp/ +npsurv: + version: 0.5-0 + title: Nonparametric Survival Analysis + maintainer: Yong Wang + description: |- + Non-parametric survival analysis of exact and + interval-censored observations. The methods implemented + are developed by Wang (2007) + , Wang (2008) + , Wang and Taylor (2013) + and Wang and Fani (2018) + . + date_publication: '2020-09-20' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~yongwang/ + url_cran: https://CRAN.R-project.org/package=npsurv + url_git: '' +npsurvSS: + version: 1.1.0 + title: |- + Sample Size and Power Calculation for Common Non-Parametric + Tests in Survival Analysis + maintainer: Godwin Yung + description: |- + A number of statistical tests have been proposed to compare two + survival curves, including the difference in (or ratio of) t-year + survival, difference in (or ratio of) p-th percentile survival, difference in + (or ratio of) restricted mean survival time, and the weighted log-rank test. + Despite the multitude of options, the convention in survival studies is to assume + proportional hazards and to use the unweighted log-rank test for design and + analysis. This package provides sample size and power + calculation for all of the above statistical tests with allowance for + flexible accrual, censoring, and survival (eg. Weibull, piecewise-exponential, + mixture cure). It is the companion R package to the paper by Yung and Liu (2020) + . Specific to the weighted log-rank test, users may + specify which approximations they wish to use to estimate the large-sample mean + and variance. The default option has been shown to provide substantial + improvement over the conventional sample size and power equations based on Schoenfeld + (1981) . + date_publication: '2024-05-08' + bug_reports: https://github.com/godwinyyung/npsurvSS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=npsurvSS + url_git: https://github.com/godwinyyung/npsurvSS +nptest: + version: '1.1' + title: Nonparametric Bootstrap and Permutation Tests + maintainer: Nathaniel E. Helwig + description: Robust nonparametric bootstrap and permutation tests for location, + correlation, and regression problems, as described in Helwig (2019a) + and Helwig (2019b) . Univariate and multivariate + tests are supported. For each problem, exact tests and Monte Carlo approximations + are available. Five different nonparametric bootstrap confidence intervals are + implemented. Parallel computing is implemented via the 'parallel' package. + date_publication: '2023-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nptest + url_git: '' +npwbs: + version: 0.2.0 + title: Nonparametric Multiple Change Point Detection Using WBS + maintainer: Gordon J. Ross + description: Implements the procedure from G. J. Ross (2021) - "Nonparametric Detection + of Multiple Location-Scale Change Points via Wild Binary Segmentation" . + This uses a version of Wild Binary Segmentation to detect multiple location-scale + (i.e. mean and/or variance) change points in a sequence of univariate observations, + with a strict control on the probability of incorrectly detecting a change point + in a sequence which does not contain any. + date_publication: '2021-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=npwbs + url_git: '' +nrba: + version: 0.3.1 + title: Methods for Conducting Nonresponse Bias Analysis (NRBA) + maintainer: Ben Schneider + description: |- + Facilitates nonresponse bias analysis (NRBA) + for survey data. Such data may arise from a complex + sampling design with features such as stratification, clustering, or + unequal probabilities of selection. Multiple types of analyses may be + conducted: comparisons of response rates across subgroups; comparisons + of estimates before and after weighting adjustments; comparisons of + sample-based estimates to external population totals; tests of + systematic differences in covariate means between respondents + and full samples; tests of independence between response status + and covariates; and modeling of outcomes and response status as a + function of covariates. Extensive documentation and references are + provided for each type of analysis. Krenzke, Van de Kerckhove, + and Mohadjer (2005) + and Lohr and Riddles (2016) + provide an overview of the methods implemented in this package. + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nrba + url_git: '' +nRegression: + version: 0.5.1 + title: |- + Simulation-Based Calculations of Sample Size for Linear and + Logistic Regression + maintainer: Srivastav Budugutta + description: Provides a function designed to estimate the minimal sample size required + to attain a specific statistical power in the context of linear regression and + logistic regression models through simulations. + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nRegression + url_git: '' +NRejections: + version: 1.2.0 + title: Metrics for Multiple Testing with Correlated Outcomes + maintainer: Maya B. Mathur + description: Implements methods in Mathur and VanderWeele (in preparation) to characterize + global evidence strength across W correlated ordinary least squares (OLS) hypothesis + tests. Specifically, uses resampling to estimate a null interval for the total + number of rejections in, for example, 95% of samples generated with no associations + (the global null), the excess hits (the difference between the observed number + of rejections and the upper limit of the null interval), and a test of the global + null based on the number of rejections. + date_publication: '2020-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NRejections + url_git: '' +nricens: + version: '1.6' + title: |- + NRI for Risk Prediction Models with Time to Event and Binary + Response Data + maintainer: Eisuke Inoue + description: Calculating the net reclassification improvement (NRI) for risk prediction + models with time to event and binary data. + date_publication: '2018-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nricens + url_git: '' +NSAE: + version: 0.4.0 + title: Nonstationary Small Area Estimation + maintainer: Saurav Guha + description: Executes nonstationary Fay-Herriot model and nonstationary generalized + linear mixed model for small area estimation.The empirical best linear unbiased + predictor (EBLUP) under stationary and nonstationary Fay-Herriot models and empirical + best predictor (EBP) under nonstationary generalized linear mixed model along + with the mean squared error estimation are included. EBLUP for prediction of non-sample + area is also included under both stationary and nonstationary Fay-Herriot models. + This extension to the Fay-Herriot model that accounts for the presence of spatial + nonstationarity was developed by Hukum Chandra, Nicola Salvati and Ray Chambers + (2015) and nonstationary generalized linear mixed model + was developed by Hukum Chandra, Nicola Salvati and Ray Chambers (2017) . + This package is dedicated to the memory of Dr. Hukum Chandra who passed away while + the package creation was in progress. + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NSAE + url_git: '' +nsarfima: + version: 0.2.0.0 + title: Methods for Fitting and Simulating Non-Stationary ARFIMA Models + maintainer: Benjamin Groebe + description: Routines for fitting and simulating data under autoregressive fractionally + integrated moving average (ARFIMA) models, without the constraint of covariance + stationarity. Two fitting methods are implemented, a pseudo-maximum likelihood + method and a minimum distance estimator. Mayoral, L. (2007) . + Beran, J. (1995) . + date_publication: '2020-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsarfima + url_git: '' +nscancor: + version: 0.7.0-6 + title: Non-Negative and Sparse CCA + maintainer: Christian Sigg + description: |- + Two implementations of canonical correlation analysis + (CCA) that are based on iterated regression. By choosing the + appropriate regression algorithm for each data domain, it is + possible to enforce sparsity, non-negativity or other kinds of + constraints on the projection vectors. Multiple canonical + variables are computed sequentially using a generalized + deflation scheme, where the additional correlation not + explained by previous variables is maximized. nscancor() is + used to analyze paired data from two domains, and has the same + interface as cancor() from the 'stats' package (plus some extra + parameters). mcancor() is appropriate for analyzing data from + three or more domains. See + + and Sigg et al. (2007) for more + details. + date_publication: '2023-03-31' + bug_reports: https://github.com/chrsigg/nscancor/issues + url: https://sigg-iten.ch/research/ + url_cran: https://CRAN.R-project.org/package=nscancor + url_git: '' +NScluster: + version: 1.3.6-1 + title: |- + Simulation and Estimation of the Neyman-Scott Type Spatial + Cluster Models + maintainer: Masami Saga + description: |- + Simulation and estimation for Neyman-Scott spatial cluster point + process models and their extensions, based on the methodology in Tanaka, Ogata, + and Stoyan (2008) . To estimate parameters by the + simplex method, parallel computation using 'OpenMP' application programming + interface is available. For more details see Tanaka, Saga and Nakano + . + date_publication: '2023-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NScluster + url_git: '' +nse: + version: '1.21' + title: Numerical Standard Errors Computation in R + maintainer: Keven Bluteau + description: Collection of functions designed to calculate numerical standard error + (NSE) of univariate time series as described in Ardia et al. (2018) + and Ardia and Bluteau (2017) . + date_publication: '2022-11-10' + bug_reports: https://github.com/keblu/nse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nse + url_git: https://github.com/keblu/nse +nseq: + version: 0.1.1 + title: Count of Sequential Events + maintainer: Raphael Saldanha + description: Count the occurrence of sequences of values in a vector that meets + certain conditions of length and magnitude. The method is based on the Run Length + Encoding algorithm, available with base R, inspired by A. H. Robinson and C. Cherry + (1967) . + date_publication: '2024-05-31' + bug_reports: https://github.com/rfsaldanha/nseq/issues + url: https://rfsaldanha.github.io/nseq/ + url_cran: https://CRAN.R-project.org/package=nseq + url_git: '' +nser: + version: 1.5.3 + title: |- + Bhavcopy and Live Market Data from National Stock Exchange (NSE) + & Bombay Stock Exchange (BSE) India + maintainer: Nandan Patil + description: Download Current & Historical Bhavcopy. Get Live Market data from NSE + India of Equities and Derivatives (F&O) segment. Data source . + date_publication: '2024-07-26' + bug_reports: https://github.com/nandp1/nser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nser + url_git: https://github.com/nandp1/nser/ +nsga2R: + version: '1.1' + title: Elitist Non-Dominated Sorting Genetic Algorithm + maintainer: Ming-Chang (Alan) Lee + description: |- + Box-constrained multiobjective optimization using the + elitist non-dominated sorting genetic algorithm - NSGA-II. + Fast non-dominated sorting, crowding distance, tournament + selection, simulated binary crossover, and polynomial + mutation are called in the main program. The methods are + described in Deb et al. (2002) . + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsga2R + url_git: '' +nsga3: + version: 0.0.3 + title: |- + An Implementation of Non-Dominated Sorting Genetic Algorithm III + for Feature Selection + maintainer: Artem Shramko + description: |- + An adaptation of Non-dominated Sorting Genetic Algorithm III for multi objective + feature selection tasks. Non-dominated Sorting Genetic Algorithm III is a genetic algorithm + that solves multiple optimization problems simultaneously by applying a non-dominated sorting + technique. It uses a reference points based selection operator to explore + solution space and preserve diversity. See the original paper by K. Deb and + H. Jain (2014) for a detailed description. + date_publication: '2019-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsga3 + url_git: '' +NSM3: + version: '1.19' + title: |- + Functions and Datasets to Accompany Hollander, Wolfe, and + Chicken - Nonparametric Statistical Methods, Third Edition + maintainer: Grant Schneider + description: Designed to replace the tables which were in the back of the first + two editions of Hollander and Wolfe - Nonparametric Statistical Methods. Exact + procedures are performed when computationally possible. Monte Carlo and Asymptotic + procedures are performed otherwise. For those procedures included in the base + packages, our code simply provides a wrapper to standardize the output with the + other procedures in the package. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NSM3 + url_git: '' +nsm3data: + version: '0.1' + title: Datasets to Accompany Hollander, Wolfe, and Chicken NSM3 + maintainer: Sejin Kim + description: Designed to add datasets which are used in the Nonparametric Statistical + Methods textbook, 3rd edition. + date_publication: '2022-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsm3data + url_git: '' +NSO1212: + version: 1.4.0 + title: National Statistical Office of Mongolia's Open Data API Handler + maintainer: Makhgal Ganbold + description: National Statistical Office of Mongolia (NSO) is the national statistical + service and an organization of Mongolian government. NSO provides open access + to official data via its API . The package NSO1212 + has functions for accessing the API service. The functions are compatible with + the API v2.0 and get data sets and its detailed informations from the API. + date_publication: '2021-09-29' + bug_reports: https://github.com/galaamn/NSO1212/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NSO1212 + url_git: https://github.com/galaamn/NSO1212 +nsp: + version: 1.0.0 + title: Inference for Multiple Change-Points in Linear Models + maintainer: Piotr Fryzlewicz + description: |- + Implementation of Narrowest Significance Pursuit, a general and + flexible methodology for automatically detecting localised regions in data sequences + which each must contain a change-point (understood as an abrupt change in the + parameters of an underlying linear model), at a prescribed global significance level. + Narrowest Significance Pursuit works with a wide range of distributional assumptions + on the errors, and yields exact desired finite-sample coverage probabilities, + regardless of the form or number of the covariates. For details, see P. Fryzlewicz + (2021) . + date_publication: '2021-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsp + url_git: '' +nspmix: + version: 1.5-0 + title: Nonparametric and Semiparametric Mixture Estimation + maintainer: Yong Wang + description: |- + Mainly for maximum likelihood estimation of nonparametric + and semiparametric mixture models, but can also be used + for fitting finite mixtures. The algorithms are + developed in Wang (2007) + and Wang (2010) + . + date_publication: '2020-09-20' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~yongwang/ + url_cran: https://CRAN.R-project.org/package=nspmix + url_git: '' +nsprcomp: + version: 0.5.1-2 + title: Non-Negative and Sparse PCA + maintainer: Christian Sigg + description: |- + Two methods for performing a constrained principal + component analysis (PCA), where non-negativity and/or sparsity + constraints are enforced on the principal axes (PAs). The + function 'nsprcomp' computes one principal component (PC) after + the other. Each PA is optimized such that the corresponding PC + has maximum additional variance not explained by the previous + components. In contrast, the function 'nscumcomp' jointly + computes all PCs such that the cumulative variance is maximal. + Both functions have the same interface as the 'prcomp' function + from the 'stats' package (plus some extra parameters), and both + return the result of the analysis as an object of class + 'nsprcomp', which inherits from 'prcomp'. See + + and Sigg et al. (2008) for more + details. + date_publication: '2018-06-05' + bug_reports: https://github.com/chrsigg/nsprcomp/issues + url: https://sigg-iten.ch/research/ + url_cran: https://CRAN.R-project.org/package=nsprcomp + url_git: '' +NSR: + version: 0.1.0 + title: '''Native Status Resolver''' + maintainer: Brian Maitner + description: Provides access to the 'Native Status Resolver' (NSR) + API through R. The user supplies plant taxonomic names and political divisions + and the package returns information about their likely native status (e.g., native, + non-native,endemic), along with information on how those decisions were made. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NSR + url_git: '' +nsRFA: + version: 0.7-17 + title: Non-Supervised Regional Frequency Analysis + maintainer: Alberto Viglione + description: |- + A collection of statistical tools for objective (non-supervised) applications + of the Regional Frequency Analysis methods in hydrology. + The package refers to the index-value method and, more precisely, helps the + hydrologist to: (1) regionalize the index-value; (2) form homogeneous regions + with similar growth curves; (3) fit distribution functions to the + empirical regional growth curves. + Most of the methods are those described in the Flood Estimation Handbook + (Centre for Ecology & Hydrology, 1999, ISBN:9781906698003). + Homogeneity tests from Hosking and Wallis (1993) + and Viglione et al. (2007) are available. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsRFA + url_git: '' +nsROC: + version: '1.1' + title: Non-Standard ROC Curve Analysis + maintainer: Sonia Perez Fernandez + description: |- + Tools for estimating Receiver Operating Characteristic (ROC) curves, + building confidence bands, comparing several curves both for dependent and + independent data, estimating the cumulative-dynamic ROC curve in presence of + censored data, and performing meta-analysis studies, among others. + date_publication: '2018-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nsROC + url_git: '' +NST: + version: 3.1.10 + title: Normalized Stochasticity Ratio + maintainer: Daliang Ning + description: To estimate ecological stochasticity in community assembly. Understanding + the community assembly mechanisms controlling biodiversity patterns is a central + issue in ecology. Although it is generally accepted that both deterministic and + stochastic processes play important roles in community assembly, quantifying their + relative importance is challenging. The new index, normalized stochasticity ratio + (NST), is to estimate ecological stochasticity, i.e. relative importance of stochastic + processes, in community assembly. With functions in this package, NST can be calculated + based on different similarity metrics and/or different null model algorithms, + as well as some previous indexes, e.g. previous Stochasticity Ratio (ST), Standard + Effect Size (SES), modified Raup-Crick metrics (RC). Functions for permutational + test and bootstrapping analysis are also included. Previous ST is published by + Zhou et al (2014) . NST is modified from ST by considering + two alternative situations and normalizing the index to range from 0 to 1 (Ning + et al 2019) . A modified version, MST, is a special + case of NST, used in some recent or upcoming publications, e.g. Liang et al (2020) + . SES is calculated as described in Kraft et + al (2011) . RC is calculated as reported by Chase + et al (2011) and Stegen et al (2013) . + Version 3 added NST based on phylogenetic beta diversity, used by Ning et al (2020) + . + date_publication: '2022-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NST + url_git: https://github.com/DaliangNing/NST +nswgeo: + version: 0.5.0 + title: Geospatial Data and Maps for New South Wales, Australia + maintainer: Carl Suster + description: |- + Geospatial data for creating maps of New South Wales (NSW), + Australia, and some helpers to work with common problems like normalising + postcodes. Registers its data with 'cartographer'. + date_publication: '2024-12-17' + bug_reports: https://github.com/cidm-ph/nswgeo/issues + url: https://cidm-ph.github.io/nswgeo/ + url_cran: https://CRAN.R-project.org/package=nswgeo + url_git: https://github.com/cidm-ph/nswgeo +nsyllable: + version: 1.0.1 + title: Count Syllables in Character Vectors + maintainer: Kenneth Benoit + description: Counts syllables in character vectors for English words. Imputes syllables + as the number of vowel sequences for words not found. + date_publication: '2022-02-28' + bug_reports: https://github.com/quanteda/nsyllable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nsyllable + url_git: https://github.com/quanteda/nsyllable +ntdr: + version: 0.4.0 + title: Retrieve Data from the National Transit Database + maintainer: Harald Kliems + description: |- + Downloads the latest 'National Transit Database' data, + processes it, and returns in a tidy data format. + date_publication: '2024-10-25' + bug_reports: https://github.com/vgXhc/ntdr/issues + url: https://vgxhc.github.io/ntdr/ + url_cran: https://CRAN.R-project.org/package=ntdr + url_git: https://github.com/vgXhc/ntdr +ntfy: + version: 0.0.6 + title: Lightweight Wrapper to the 'ntfy.sh' Service + maintainer: Jonathan Carroll + description: |- + The 'ntfy' (pronounce: notify) service is a simple HTTP-based pub-sub + notification service. It allows you to send notifications to your phone or + desktop via scripts from any computer, entirely without signup, cost or + setup. It's also open source if you want to run your own. + Visit for more details. + date_publication: '2024-11-06' + bug_reports: https://github.com/jonocarroll/ntfy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ntfy + url_git: https://github.com/jonocarroll/ntfy +NTLKwIEx: + version: 0.1.0 + title: Computation of NTLKwIEx Distribution Properties + maintainer: Théophile Otodji + description: Implements statistical tools for analyzing, simulating, and computing + properties of the New Topp-Leone Kumaraswamy Inverse Exponential (NTLKwIEx) distribution. + See Atchadé M, Otodji T, and Djibril A (2024) and Atchadé + M, Otodji T, Djibril A, and N'bouké M (2023) for + details. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NTLKwIEx + url_git: '' +ntranova: + version: 0.0.1 + title: Two Way Neutrosophic ANOVA + maintainer: Mohamad Taher Anan + description: |- + Dealing with neutrosophic data of the form N=D+I(where N is a Neutrosophic number + ,D is the determinant part of the number and I is the indeterminacy part) + using the neutrosophic two way anova test keeps the type I error low. + This algorithm calculates the fisher statistics when we have a neutrosophic + data, also tests two hypothesizes, first is to test differences between treatments, + and second is to test differences between sectors. For more information see + Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022) + . + date_publication: '2024-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ntranova + url_git: '' +NTS: + version: 1.1.3 + title: Nonlinear Time Series Analysis + maintainer: Xialu Liu + description: 'Simulation, estimation, prediction procedure, and model identification + methods for nonlinear time series analysis, including threshold autoregressive + models, Markov-switching models, convolutional functional autoregressive models, + nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. + More examples and details about this package can be found in the book "Nonlinear + Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: + 978-1-119-26407-1).' + date_publication: '2023-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NTS + url_git: '' +ntsDatasets: + version: 0.2.0 + title: Neutrosophic Data Sets + maintainer: Amin Roshani + description: Provides a collection of datasets related to neutrosophic sets for + statistical modeling and analysis. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ntsDatasets + url_git: https://github.com/a-roshani/ntsDatasets +ntsDists: + version: 2.1.1 + title: Neutrosophic Distributions + maintainer: Danial Mazarei + description: Computes the pdf, cdf, quantile function and generating random numbers + for neutrosophic distributions. This family have been developed by different authors + in the recent years. See Patro and Smarandache (2016) + and Rao et al (2023) . + date_publication: '2024-04-17' + bug_reports: https://github.com/dmazarei/ntsDists/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ntsDists + url_git: https://github.com/dmazarei/ntsDists +NTSS: + version: 0.1.3 + title: Nonparametric Tests in Spatial Statistics + maintainer: Jiří Dvořák + description: |- + Nonparametric test of independence between a pair of spatial objects + (random fields, point processes) based on random shifts with torus or variance correction. See + Mrkvička et al. (2021) , + Dvořák et al. (2022) , + Dvořák and Mrkvička (2024) . + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NTSS + url_git: '' +NU.Learning: + version: '1.5' + title: |- + Nonparametric and Unsupervised Learning from Cross-Sectional + Observational Data + maintainer: Bob Obenchain + description: |- + Especially when cross-sectional data are observational, effects of treatment selection + bias and confounding are best revealed by using Nonparametric and Unsupervised methods to + "Design" the analysis of the given data ...rather than the collection of "designed data". + Specifically, the "effect-size distribution" that best quantifies a potentially causal + relationship between a numeric y-Outcome variable and either a binary t-Treatment or + continuous e-Exposure variable needs to consist of BLOCKS of relatively well-matched + experimental units (e.g. patients) that have the most similar X-confounder characteristics. + Since our NU Learning approach will form BLOCKS by "clustering" experimental units in + confounder X-space, the implicit statistical model for learning is One-Way ANOVA. Within + Block measures of effect-size are then either [a] LOCAL Treatment Differences (LTDs) between + Within-Cluster y-Outcome Means ("new" minus "control") when treatment choice is + Binary or else [b] LOCAL Rank Correlations (LRCs) when the e-Exposure variable is numeric + with (hopefully many) more than two levels. An Instrumental Variable (IV) method is also + provided so that Local Average y-Outcomes (LAOs) within BLOCKS may also contribute + information for effect-size inferences when X-Covariates are assumed to influence Treatment + choice or Exposure level but otherwise have no direct effects on y-Outcomes. Finally, a + "Most-Like-Me" function provides histograms of effect-size distributions to aid + Doctor-Patient (or Researcher-Society) communications about Heterogeneous Outcomes. + Obenchain and Young (2013) ; Obenchain, Young and Krstic + (2019) . + date_publication: '2023-09-30' + bug_reports: '' + url: http://localcontrolstatistics.org + url_cran: https://CRAN.R-project.org/package=NU.Learning + url_git: '' +nucim: + version: 1.0.11 + title: Nucleome Imaging Toolbox + maintainer: Volker Schmid + description: |2- + + Tools for 4D nucleome imaging. + Quantitative analysis of the 3D nuclear landscape recorded with super-resolved fluorescence microscopy. + See Volker J. Schmid, Marion Cremer, Thomas Cremer (2017) . + date_publication: '2021-06-10' + bug_reports: https://github.com/bioimaginggroup/nucim/issues + url: https://bioimaginggroup.github.io/nucim/ + url_cran: https://CRAN.R-project.org/package=nucim + url_git: '' +NUCOMBog: + version: 1.0.4.2 + title: |- + NUtrient Cycling and COMpetition Model Undisturbed Open Bog + Ecosystems in a Temperate to Sub-Boreal Climate + maintainer: J.W.M. Pullens + description: Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed + open bog ecosystems in a temperate to sub-boreal climate. The executable of the + model can downloaded from . + date_publication: '2018-05-20' + bug_reports: https://github.com/jeroenpullens/NUCOMBog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NUCOMBog + url_git: https://github.com/jeroenpullens/NUCOMBog/ +NUETON: + version: 0.1.0 + title: Nitrogen Use Efficiency Toolkit on Numerics + maintainer: Shubham Love + description: Comprehensive R package designed to facilitate the calculation of Nitrogen + Use Efficiency (NUE) indicators using experimentally derived data. The package + incorporates 23 parameters categorized into six fertilizer-based, four plant-based, + three soil-based, three isotope-based, two ecology-based, and four system-based + indicators, providing a versatile platform for NUE assessment. As of the current + version, 'NUETON' serves as a starting point for users to compute NUE indicators + from their experimental data. Future updates are planned to enhance the package's + capabilities, including robust data visualization tools and error margin consideration + in calculations. Additionally, statistical methods will be integrated to ensure + the accuracy and reliability of the calculated indicators. All formulae used in + 'NUETON' are thoroughly referenced within the source code, and the package is + released as open source software. Users are encouraged to provide feedback and + contribute to the improvement of this package. It is important to note that the + current version of 'NUETON' is not intended for rigorous research purposes, and + users are responsible for validating their results. The package developers do + not assume liability for any inaccuracies in calculations. This package includes + content from Congreves KA, Otchere O, Ferland D, Farzadfar S, Williams S and Arcand + MM (2021) 'Nitrogen Use Efficiency Definitions of Today and Tomorrow.' Front. + Plant Sci. 12:637108. . The article is available + under the Creative Commons Attribution License (CC BY) C. 2021 Congreves, Otchere, + Ferland, Farzadfar, Williams and Arcand. + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NUETON + url_git: '' +nuggets: + version: 1.4.0 + title: Extensible Data Pattern Searching Framework + maintainer: Michal Burda + description: |- + Extensible framework for + subgroup discovery (Atzmueller (2015) ), + contrast patterns (Chen (2022) ), + emerging patterns (Dong (1999) ), + association rules (Agrawal (1994) ) and + conditional correlations (Hájek (1978) ). + Both crisp (Boolean, binary) and fuzzy data are supported. + It generates conditions in the form of elementary conjunctions, evaluates + them on a dataset and checks the induced sub-data for interesting statistical + properties. A user-defined function may be defined to evaluate on each generated + condition to search for custom patterns. + date_publication: '2025-01-08' + bug_reports: https://github.com/beerda/nuggets/issues + url: https://beerda.github.io/nuggets/ + url_cran: https://CRAN.R-project.org/package=nuggets + url_git: https://github.com/beerda/nuggets +nullabor: + version: 0.3.15 + title: Tools for Graphical Inference + maintainer: Di Cook + description: |- + Tools for visual inference. Generate null data sets + and null plots using permutation and simulation. Calculate distance metrics + for a lineup, and examine the distributions of metrics. + date_publication: '2025-02-10' + bug_reports: https://github.com/dicook/nullabor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nullabor + url_git: https://github.com/dicook/nullabor +numbat: + version: 1.4.2 + title: Haplotype-Aware CNV Analysis from scRNA-Seq + maintainer: Teng Gao + description: 'A computational method that infers copy number variations (CNVs) in + cancer scRNA-seq data and reconstructs the tumor phylogeny. ''numbat'' integrates + signals from gene expression, allelic ratio, and population haplotype structures + to accurately infer allele-specific CNVs in single cells and reconstruct their + lineage relationship. ''numbat'' can be used to: 1. detect allele-specific copy + number variations from single-cells; 2. differentiate tumor versus normal cells + in the tumor microenvironment; 3. infer the clonal architecture and evolutionary + history of profiled tumors. ''numbat'' does not require tumor/normal-paired DNA + or genotype data, but operates solely on the donor scRNA-data data (for example, + 10x Cell Ranger output). Additional examples and documentations are available + at . For details on the method please + see Gao et al. Nature Biotechnology (2022) .' + date_publication: '2024-09-20' + bug_reports: '' + url: https://kharchenkolab.github.io/numbat/ + url_cran: https://CRAN.R-project.org/package=numbat + url_git: https://github.com/kharchenkolab/numbat/ +numberize: + version: 1.0.1 + title: Convert Words to Numbers in Multiple Languages + maintainer: Bankole Ahadzie + description: |- + Converts written out numbers into their equivalent numbers. + Supports numbers written out in English, French, or Spanish. + date_publication: '2024-10-28' + bug_reports: https://github.com/epiverse-trace/numberize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=numberize + url_git: https://github.com/epiverse-trace/numberize +numberofalleles: + version: 1.0.1 + title: |- + Compute the Probability Distribution of the Number of Alleles in + a DNA Mixture + maintainer: Maarten Kruijver + description: The number of distinct alleles observed in a DNA mixture is informative + of the number of contributors to the mixture. The package provides methods for + computing the probability distribution of the number of distinct alleles in a + mixture for a given set of allele frequencies. The mixture contributors may be + related according to a provided pedigree. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numberofalleles + url_git: '' +numbers: + version: 0.8-5 + title: Number-Theoretic Functions + maintainer: Hans W. Borchers + description: |2- + + Provides number-theoretic functions for factorization, prime + numbers, twin primes, primitive roots, modular logarithm and + inverses, extended GCD, Farey series and continued fractions. + Includes Legendre and Jacobi symbols, some divisor functions, + Euler's Phi function, etc. + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numbers + url_git: '' +numbersBR: + version: 0.0.2 + title: Validate, Compare and Format Identification Numbers from Brazil + maintainer: Wilson Freitas + description: |- + Validate, format and compare identification numbers used in Brazil. + These numbers are used to identify individuals (CPF), vehicles (RENAVAN), + companies (CNPJ) and etc. + Functions to format, validate and compare these numbers have been + implemented in a vectorized way in order to speed up + validations and comparisons in big datasets. + date_publication: '2018-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numbersBR + url_git: '' +numDeriv: + version: 2016.8-1.1 + title: Accurate Numerical Derivatives + maintainer: Paul Gilbert + description: |- + Methods for calculating (usually) accurate + numerical first and second order derivatives. Accurate calculations + are done using 'Richardson''s' extrapolation or, when applicable, a + complex step derivative is available. A simple difference + method is also provided. Simple difference is (usually) less accurate + but is much quicker than 'Richardson''s' extrapolation and provides a + useful cross-check. + Methods are provided for real scalar and vector valued functions. + date_publication: '2019-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numDeriv + url_git: http://optimizer.r-forge.r-project.org/ +Numero: + version: 1.9.8 + title: Statistical Framework to Define Subgroups in Complex Datasets + maintainer: Ville-Petteri Makinen + description: 'High-dimensional datasets that do not exhibit a clear intrinsic clustered + structure pose a challenge to conventional clustering algorithms. For this reason, + we developed an unsupervised framework that helps scientists to better subgroup + their datasets based on visual cues, please see Gao S, Mutter S, Casey A, Makinen + V-P (2019) Numero: a statistical framework to define multivariable subgroups in + complex population-based datasets, Int J Epidemiology, 48:369-37, . + The framework includes the necessary functions to construct a self-organizing + map of the data, to evaluate the statistical significance of the observed data + patterns, and to visualize the results.' + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Numero + url_git: '' +numform: + version: 0.7.0 + title: Tools to Format Numbers for Publication + maintainer: Tyler Rinker + description: |- + Format numbers and plots for publication; includes the removal of leading zeros, + standardization of number of digits, addition of affixes, and a p-value formatter. These + tools combine the functionality of several 'base' functions such as 'paste()', + 'format()', and 'sprintf()' into specific use case functions that are named in a way + that is consistent with usage, making their names easy to remember and easy to deploy. + date_publication: '2021-10-09' + bug_reports: https://github.com/trinker/numform/issues + url: '' + url_cran: https://CRAN.R-project.org/package=numform + url_git: https://github.com/trinker/numform +numGen: + version: 0.1.1 + title: Number Series Generator + maintainer: Bao Sheng Loe (Aiden) + description: A number series generator that creates number series items based on + cognitive models. + date_publication: '2017-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numGen + url_git: '' +numKM: + version: 0.2.0 + title: Create a Kaplan-Meier Plot with Numbers at Risk + maintainer: Zhicheng Du + description: To add the table of numbers at risk below the Kaplan-Meier plot. + date_publication: '2020-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numKM + url_git: '' +numOSL: + version: '2.8' + title: Numeric Routines for Optically Stimulated Luminescence Dating + maintainer: Jun Peng + description: |- + Optimizing regular numeric problems in optically stimulated luminescence dating, + such as: equivalent dose calculation, dose rate determination, growth curve fitting, decay + curve decomposition, statistical age model optimization, and statistical plot visualization. + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=numOSL + url_git: '' +NUSS: + version: 0.1.0 + title: Mixed N-Grams and Unigram Sequence Segmentation + maintainer: Oskar Kosch + description: |- + Segmentation of short text sequences - like hashtags - into the + separated words sequence, done with the use of dictionary, which may be + built on custom corpus of texts. Unigram dictionary is used to find most + probable sequence, and n-grams approach is used to determine possible + segmentation given the text corpus. + date_publication: '2024-08-19' + bug_reports: https://github.com/theogrost/NUSS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NUSS + url_git: https://github.com/theogrost/NUSS +NutrienTrackeR: + version: 1.3.0 + title: Food Composition Information and Dietary Assessment + maintainer: Rafael Ayala + description: |- + Provides a tool set for food information and dietary assessment. It + uses food composition data from several reference databases, including: 'USDA' (United States), + 'CIQUAL' (France), 'BEDCA' (Spain), 'CNF' (Canada) and 'STFCJ' (Japan). 'NutrienTrackeR' calculates + the intake levels for both macronutrient and micronutrients, and compares them with the recommended + dietary allowances (RDA). It includes a number of visualization tools, such as time series + plots of nutrient intake, and pie-charts showing the main foods contributing to the intake + level of a given nutrient. A shiny app exposing the main functionalities of the package is also + provided. + date_publication: '2023-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NutrienTrackeR + url_git: '' +nutriNetwork: + version: 0.1.2 + title: Structure Learning with Copula Graphical Model + maintainer: Pariya Behrouzi + description: |- + Statistical tool for learning the structure of direct associations among variables for + continuous data, discrete data and mixed discrete-continuous data. The package is based + on the copula graphical model in Behrouzi and Wit (2017) . + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nutriNetwork + url_git: '' +nutrition: + version: 1.1.0 + title: Useful Functions for People on a Diet + maintainer: Waldir Leoncio + description: |- + Contains a collection of functions for performing different kinds + of calculation that are of interest to someone following a diet plan. + Calculators for the Basal Metabolic Rate are based on Mifflin et al. (1990) + and McArdle, W. D., Katch, F. I., & + Katch, V. L. (2010, ISBN:9780812109917). + date_publication: '2023-09-28' + bug_reports: https://github.com/wleoncio/nutrition/issues + url: https://wleoncio.github.io/nutrition/ + url_cran: https://CRAN.R-project.org/package=nutrition + url_git: '' +nuts: + version: 1.1.0 + title: Convert European Regional Data + maintainer: Moritz Hennicke + description: |- + Motivated by changing administrative boundaries over time, + the 'nuts' package can convert European regional data with NUTS codes + between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1, + NUTS 2 and NUTS 3). The package uses spatial interpolation as in Lam + (1983) based on granular (100m x + 100m) area, population and land use data provided by the European + Commission's Joint Research Center. + date_publication: '2024-07-13' + bug_reports: https://github.com/ropensci/nuts + url: https://docs.ropensci.org/nuts/ + url_cran: https://CRAN.R-project.org/package=nuts + url_git: https://github.com/ropensci/nuts +NVAR: + version: 0.1.0 + title: Nonlinear Vector Autoregression Models + maintainer: Jingmeng Cui + description: |- + Estimate nonlinear vector autoregression models (also known as the + next generation reservoir computing) for nonlinear dynamic systems. The + algorithm was described by Gauthier et al. (2021) . + date_publication: '2024-01-18' + bug_reports: https://github.com/Sciurus365/NVAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=NVAR + url_git: https://github.com/Sciurus365/NVAR +NVCSSL: + version: '2.0' + title: Nonparametric Varying Coefficient Spike-and-Slab Lasso + maintainer: Ray Bai + description: Fits Bayesian regularized varying coefficient models with the Nonparametric + Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) + . Functions to fit frequentist penalized varying coefficients + are also provided, with the option of employing the group lasso penalty of Yuan + and Lin (2006) , the group minimax concave + penalty (MCP) of Breheny and Huang , or the group + smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) + . + date_publication: '2023-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=NVCSSL + url_git: '' +nvctr: + version: 0.1.4 + title: |- + The n-vector Approach to Geographical Position Calculations + using an Ellipsoidal Model of Earth + maintainer: Enrico Spinielli + description: |- + The n-vector framework uses the normal vector to + the Earth ellipsoid (called n-vector) as a non-singular position + representation that turns out to be very convenient for practical + position calculations. The n-vector is simple to use and gives exact + answers for all global positions, and all distances, for both + ellipsoidal and spherical Earth models. This package is a translation + of the 'Matlab' library from FFI, the Norwegian Defence Research + Establishment, as described in Gade (2010) + . + date_publication: '2020-10-28' + bug_reports: https://github.com/euctrl-pru/nvctr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nvctr + url_git: https://github.com/euctrl-pru/nvctr +nvmix: + version: 0.1-1 + title: Multivariate Normal Variance Mixtures + maintainer: Marius Hofert + description: |- + Functions for working with (grouped) multivariate normal variance mixture + distributions (evaluation of distribution functions and densities, + random number generation and parameter estimation), including + Student's t distribution for non-integer degrees-of-freedom as well as the grouped t + distribution and copula with multiple degrees-of-freedom parameters. + See for a high-level description of select functionality. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nvmix + url_git: '' +nycflights13: + version: 1.0.2 + title: Flights that Departed NYC in 2013 + maintainer: Hadley Wickham + description: |- + Airline on-time data for all flights departing NYC in 2013. + Also includes useful 'metadata' on airlines, airports, weather, and + planes. + date_publication: '2021-04-12' + bug_reports: https://github.com/hadley/nycflights13/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nycflights13 + url_git: https://github.com/hadley/nycflights13 +nycflights23: + version: 0.1.0 + title: |- + Flights and Other Useful Metadata for NYC Outbound Flights in + 2023 + maintainer: Chester Ismay + description: Updating the now 10-year-old 'nycflights13' data package. It contains + information about all flights that departed from the three main New York City + airports in 2023 and metadata on airlines, airports, weather, and planes. + date_publication: '2024-03-09' + bug_reports: https://github.com/moderndive/nycflights23/issues/ + url: https://moderndive.github.io/nycflights23/ + url_cran: https://CRAN.R-project.org/package=nycflights23 + url_git: https://github.com/moderndive/nycflights23/ +nzelect: + version: 0.4.0 + title: New Zealand Election Data + maintainer: Peter Ellis + description: |- + Convenient access to New Zealand election + results by voting place. Voting places have been matched to Regional Council, + Territorial Authority, and Area Unit, to facilitate matching with additional data. + Opinion polls since 2002 and some convenience analytical function are also supplied. + date_publication: '2017-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=nzelect + url_git: '' +nzffdr: + version: 2.1.0 + title: |- + Import, Clean and Update Data from the New Zealand Freshwater + Fish Database + maintainer: Finnbar Lee + description: Access the New Zealand Freshwater Fish Database from R and a few functions + to clean the data once in R. + date_publication: '2022-11-08' + bug_reports: '' + url: https://flee598.github.io/nzffdr/ + url_cran: https://CRAN.R-project.org/package=nzffdr + url_git: '' +nzilbb.labbcat: + version: 1.3-0 + title: Accessing Data Stored in 'LaBB-CAT' Instances + maintainer: Robert Fromont + description: |- + 'LaBB-CAT' is a web-based language corpus management + system developed by the New Zealand Institute of Language, Brain + and Behaviour (NZILBB) - see . + This package defines functions for accessing corpus data in a 'LaBB-CAT' + instance. You must have at least version 20230224.1731 of 'LaBB-CAT' + to use this package. + For more information about 'LaBB-CAT', see + Robert Fromont and Jennifer Hay (2008) + or + Robert Fromont (2017) . + date_publication: '2023-07-19' + bug_reports: '' + url: https://nzilbb.github.io/labbcat-R/ + url_cran: https://CRAN.R-project.org/package=nzilbb.labbcat + url_git: '' +nzilbb.vowels: + version: 0.3.1 + title: Vowel Covariation Tools + maintainer: Joshua Wilson Black + description: |- + Tools to support research on vowel covariation. Methods are provided to + support Principal Component Analysis workflows (as in Brand et al. (2021) + and Wilson Black et al. (2023) + ). + date_publication: '2024-11-29' + bug_reports: https://github.com/nzilbb/nzilbb_vowels/issues/ + url: https://nzilbb.github.io/nzilbb_vowels/ + url_cran: https://CRAN.R-project.org/package=nzilbb.vowels + url_git: https://github.com/nzilbb/nzilbb_vowels +nzpullover: + version: 0.3.0 + title: Driving Offences in New Zealand Between 2009 and 2016 + maintainer: Duncan Garmonsway + description: |- + Datasets of driving offences and fines in New Zealand between 2009 and 2017. + Originally published by the New Zealand Police at + . + date_publication: '2018-02-25' + bug_reports: https://github.com/nacnudus/nzpullover/issues + url: '' + url_cran: https://CRAN.R-project.org/package=nzpullover + url_git: https://github.com/nacnudus/nzpullover +o2geosocial: + version: 1.1.3 + title: Reconstruction of Transmission Chains from Surveillance Data + maintainer: Alexis Robert + description: Bayesian reconstruction of who infected whom during past outbreaks + using routinely-collected surveillance data. Inference of transmission trees using + genotype, age specific social contacts, distance between cases and onset dates + of the reported cases. (Robert A, Kucharski AJ, Gastanaduy PA, Paul P, Funk S. + (2020) ). + date_publication: '2024-06-21' + bug_reports: https://github.com/alxsrobert/o2geosocial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=o2geosocial + url_git: https://github.com/alxsrobert/o2geosocial +o2plsda: + version: 0.0.25 + title: Multiomics Data Integration + maintainer: Kai Guo + description: |- + Provides functions to do 'O2PLS-DA' analysis for multiple omics data integration. + The algorithm came from "O2-PLS, a two-block (X±Y) latent variable regression (LVR) method with an integral OSC filter" + which published by Johan Trygg and Svante Wold at 2003 . + 'O2PLS' is a bidirectional multivariate regression method that aims to separate the covariance between + two data sets (it was recently extended to multiple data sets) (Löfstedt and Trygg, 2011 ; Löfstedt et al., 2012 ) + from the systematic sources of variance being specific for each data set separately. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=o2plsda + url_git: '' +oaColors: + version: 0.0.4 + title: OpenAnalytics Colors Package + maintainer: Jason Waddell + description: Provides carefully chosen color palettes as used a.o. at OpenAnalytics + . + date_publication: '2015-11-30' + bug_reports: '' + url: http://www.openanalytics.eu + url_cran: https://CRAN.R-project.org/package=oaColors + url_git: '' +oai: + version: 0.4.0 + title: General Purpose 'Oai-PMH' Services Client + maintainer: Michal Bojanowski + description: |- + A general purpose client to work with any 'OAI-PMH' + (Open Archives Initiative Protocol for 'Metadata' Harvesting) service. + The 'OAI-PMH' protocol is described at + . + Functions are provided to work with the 'OAI-PMH' verbs: 'GetRecord', + 'Identify', 'ListIdentifiers', 'ListMetadataFormats', 'ListRecords', and + 'ListSets'. + date_publication: '2022-11-10' + bug_reports: https://github.com/ropensci/oai/issues + url: https://docs.ropensci.org/oai/ + url_cran: https://CRAN.R-project.org/package=oai + url_git: https://github.com/ropensci/oai +OAIHarvester: + version: 0.3-5 + title: Harvest Metadata Using OAI-PMH Version 2.0 + maintainer: Kurt Hornik + description: |- + Harvest metadata using the Open Archives Initiative Protocol for Metadata + Harvesting (OAI-PMH) version 2.0 (for more information, see + ). + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OAIHarvester + url_git: '' +oaii: + version: 0.5.0 + title: '''OpenAI'' API R Interface' + maintainer: Cezary Kuran + description: |- + A comprehensive set of helpers that streamline data transmission + and processing, making it effortless to interact with the 'OpenAI' API. + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oaii + url_git: https://github.com/cezarykuran/oaii +oaPlots: + version: 0.0.25 + title: OpenAnalytics Plots Package + maintainer: Jason Waddell + description: Offers a suite of functions for enhancing R plots. + date_publication: '2015-11-30' + bug_reports: '' + url: http://www.openanalytics.eu + url_cran: https://CRAN.R-project.org/package=oaPlots + url_git: '' +oaqc: + version: 2.0.0 + title: Computation of the Orbit-Aware Quad Census + maintainer: David Schoch + description: |- + Implements the efficient algorithm by Ortmann and Brandes (2017) + to compute the orbit-aware frequency distribution of induced and non-induced quads, i.e. subgraphs of size four. Given an edge matrix, data frame, or a graph object (e.g., 'igraph'), the orbit-aware counts are computed respective each of the edges and nodes. + date_publication: '2024-10-07' + bug_reports: https://github.com/schochastics/oaqc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oaqc + url_git: https://github.com/schochastics/oaqc +Oarray: + version: 1.4-9 + title: Arrays with Arbitrary Offsets + maintainer: Robin K. S. Hankin + description: Generalise the starting point of the array index. + date_publication: '2018-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Oarray + url_git: '' +OasisR: + version: 3.1.1 + title: |- + Outright Tool for the Analysis of Spatial Inequalities and + Segregation + maintainer: Mihai Tivadar + description: |- + A comprehensive set of indexes and tests for social segregation analysis, + as described in Tivadar (2019) - 'OasisR': An R Package to Bring Some Order + to the World of Segregation Measurement . + The package is the most complete existing tool and it clarifies + many ambiguities and errors regarding the definition of segregation + indices. Additionally, 'OasisR' introduces several resampling methods + that enable testing their statistical significance + (randomization tests, bootstrapping, and jackknife methods). + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OasisR + url_git: '' +oaxaca: + version: 0.1.5 + title: Blinder-Oaxaca Decomposition + maintainer: Marek Hlavac + description: An implementation of the Blinder-Oaxaca decomposition for linear regression + models. + date_publication: '2022-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oaxaca + url_git: '' +obAnalytics: + version: 0.1.1 + title: Limit Order Book Analytics + maintainer: Philip Stubbings + description: |- + Data processing, visualisation and analysis of Limit Order Book + event data. + date_publication: '2016-11-11' + bug_reports: https://github.com/phil8192/ob-analytics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=obAnalytics + url_git: https://github.com/phil8192/ob-analytics +OBASpatial: + version: '1.9' + title: Objective Bayesian Analysis for Spatial Regression Models + maintainer: Alejandro Ordonez + description: It makes an objective Bayesian analysis of the spatial regression model + using both the normal (NSR) and student-T (TSR) distributions. The functions provided + give prior and posterior objective densities and allow default Bayesian estimation + of the model regression parameters. Details can be found in Ordonez et al. (2020) + . + date_publication: '2022-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OBASpatial + url_git: '' +obcost: + version: 0.1.0 + title: Obesity Cost Database + maintainer: Tianyue Zang + description: 'This database contains necessary data relevant to medical costs on + obesity throughout the United States. This database, in form of an R package, + could output necessary data frames relevant to obesity costs, where the clients + could easily manipulate the output using difference parameters, e.g. relative + risks for each illnesses. This package contributes to parts of our published journal + named "Modeling the Economic Cost of Obesity Risk and Its Relation to the Health + Insurance Premium in the United States: A State Level Analysis". Please use the + following citation for the journal: Woods Thomas, Tatjana Miljkovic (2022) "Modeling + the Economic Cost of Obesity Risk and Its Relation to the Health Insurance Premium + in the United States: A State Level Analysis" . The + database is composed of the following main tables: 1. Relative_Risks: (constant) + Relative risks for a given disease group with a risk factor of obesity; 2. Disease_Cost: + (obesity_cost_disease) Supplementary output with all variables related to individual + disease groups in a given state and year; 3. Full_Cost: (obesity_cost_full) Complete + output with all variables used to make cost calculations, as well as cost calculations + in a given state and year; 4. National_Summary: (obesity_cost_national_summary) + National summary cost calculations in a given year. Three functions are included + to assist users in calling and adjusting the mentioned tables and they are data_load(), + data_produce(), and rel_risk_fun().' + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=obcost + url_git: '' +obfuscatoR: + version: 0.2.2 + title: Obfuscation Game Designs + maintainer: Erlend Dancke Sandorf + description: 'When people make decisions, they may do so using a wide variety of + decision rules. The package allows users to easily create obfuscation games to + test the obfuscation hypothesis. It provides an easy to use interface and multiple + options designed to vary the difficulty of the game and tailor it to the user''s + needs. For more detail: Chorus et al., 2021, Obfuscation maximization-based decision-making: + Theory, methodology and first empirical evidence, Mathematical Social Sciences, + 109, 28-44, .' + date_publication: '2023-09-07' + bug_reports: '' + url: https://obfuscator.edsandorf.me + url_cran: https://CRAN.R-project.org/package=obfuscatoR + url_git: https://github.com/edsandorf/obfuscatoR +OBIC: + version: 3.0.3 + title: Calculate the Open Bodem Index (OBI) Score + maintainer: Sven Verweij + description: |- + The Open Bodem Index (OBI) is a method to evaluate the quality of soils of agricultural fields in The Netherlands and the sustainability of the current agricultural practices. + The OBI score is based on four main criteria: chemical, physical, biological and management, which consist of more than 21 indicators. + By providing results of a soil analysis and management info the 'OBIC' package can be use to calculate he scores, indicators and derivatives that are used by the OBI. + More information about the Open Bodem Index can be found at . + date_publication: '2024-09-09' + bug_reports: https://github.com/AgroCares/Open-Bodem-Index-Calculator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OBIC + url_git: https://github.com/AgroCares/Open-Bodem-Index-Calculator +objectProperties: + version: 0.6.8 + title: A Factory of Self-Describing Properties + maintainer: Michael Lawrence + description: Supports the definition of sets of properties on objects. Observers + can listen to changes on individual properties or the set as a whole. The properties + are meant to be fully self-describing. In support of this, there is a framework + for defining enumerated types, as well as other bounded types, as S4 classes. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=objectProperties + url_git: '' +objectremover: + version: 0.8.1 + title: |- + 'RStudio' Addin for Removing Objects from the Global Environment + Based on Patterns and Object Type + maintainer: Alan Yeung + description: An 'RStudio' addin to assist with removing objects from the global + environment. Features include removing objects according to name patterns and + object type. During the course of an analysis, temporary objects are often created + and this tool assists with removing them quickly. This can be useful when memory + management within 'R' is important. + date_publication: '2021-08-16' + bug_reports: https://github.com/alan-y/objectremover/issues + url: '' + url_cran: https://CRAN.R-project.org/package=objectremover + url_git: https://github.com/alan-y/objectremover +objectSignals: + version: 0.10.3 + title: Observer Pattern for S4 + maintainer: Michael Lawrence + description: |- + A mutable Signal object can report changes to its state, + clients could register functions so that they are called whenever + the signal is emitted. The signal could be emitted, disconnected, + blocked, unblocked, and buffered. + date_publication: '2022-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=objectSignals + url_git: '' +OBL: + version: 0.2.1 + title: Optimum Block Length + maintainer: Daniel James + description: Obtain optimum block from Non-overlapping Block Bootstrap method. + date_publication: '2022-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OBL + url_git: '' +oblicubes: + version: 0.1.2 + title: 3D Rendering Using Obliquely Projected Cubes and Cuboids + maintainer: Trevor L Davis + description: Three-dimensional rendering for 'grid' and 'ggplot2' graphics using + cubes and cuboids drawn with an oblique projection. As a special case also supports + primary view orthographic projections. Can be viewed as an extension to the 'isocubes' + package . + date_publication: '2022-08-27' + bug_reports: https://github.com/trevorld/oblicubes/issues + url: https://trevorldavis.com/R/oblicubes/ + url_cran: https://CRAN.R-project.org/package=oblicubes + url_git: '' +obliqueRSF: + version: 0.1.2 + title: Oblique Random Forests for Right-Censored Time-to-Event Data + maintainer: Byron Jaeger + description: Oblique random survival forests incorporate linear combinations of + input variables into random survival forests (Ishwaran, 2008 ). + Regularized Cox proportional hazard models (Simon, 2016 ) + are used to identify optimal linear combinations of input variables. + date_publication: '2022-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=obliqueRSF + url_git: '' +OBMbpkg: + version: 1.0.0 + title: Estimate the Population Size for the Mb Capture-Recapture Model + maintainer: John Snyder + description: Applies an objective Bayesian method to the Mb capture-recapture model + to estimate the population size N. The Mb model is a class of capture-recapture + methods used to account for variations in capture probability due to animal behavior. Under + the Mb formulation, the initial capture of an animal may effect the probability + of subsequent captures due to their becoming "trap happy" or "trap shy." + date_publication: '2017-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OBMbpkg + url_git: '' +OBRE: + version: 0.2-0 + title: Optimal B-Robust Estimator Tools + maintainer: Fabio Piacenza + description: |- + An implementation for computing Optimal B-Robust Estimators of two-parameter + distribution. The procedure is composed of some equations + that are evaluated alternatively until the solution is reached. Some tools + for analyzing the estimates are included. The most relevant is + covariance matrix computation using a closed formula. + date_publication: '2023-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OBRE + url_git: '' +Observation: + version: 0.3.0 + title: Collect and Process Physical Activity Direct Observation Data + maintainer: Paul R. Hibbing + description: |- + Two-part system for first collecting then managing direct + observation data, as described by Hibbing PR, Ellingson LD, + Dixon PM, & Welk GJ (2018) . + date_publication: '2022-09-05' + bug_reports: https://github.com/paulhibbing/Observation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Observation + url_git: https://github.com/paulhibbing/Observation +OBsMD: + version: '12.0' + title: Objective Bayesian Model Discrimination in Follow-Up Designs + maintainer: Marta Nai Ruscone + description: Implements the objective Bayesian methodology proposed in Consonni + and Deldossi in order to choose the optimal experiment that better discriminate + between competing models, see Deldossi and Nai Ruscone (2020) . + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OBsMD + url_git: '' +obsSens: + version: '1.4' + title: Sensitivity Analysis for Observational Studies + maintainer: Greg Snow + description: Observational studies are limited in that there could be an unmeasured + variable related to both the response variable and the primary predictor. If + this unmeasured variable were included in the analysis it would change the relationship + (possibly changing the conclusions). Sensitivity analysis is a way to see how + much of a relationship needs to exist with the unmeasured variable before the + conclusions change. This package provides tools for doing a sensitivity analysis + for regression (linear, logistic, and cox) style models. + date_publication: '2022-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=obsSens + url_git: '' +oc: + version: 1.2.1 + title: Optimal Classification Roll Call Analysis Software + maintainer: William May + description: |- + Estimates optimal classification (Poole 2000) + scores from roll call votes supplied though a 'rollcall' + object from package 'pscl'. + date_publication: '2023-02-06' + bug_reports: https://github.com/wmay/oc/issues + url: https://legacy.voteview.com/oc_in_R.htm + url_cran: https://CRAN.R-project.org/package=oc + url_git: https://github.com/wmay/oc +OCA: + version: '0.5' + title: Optimal Capital Allocations + maintainer: Jilber Urbina + description: Computes optimal capital allocations based on some standard principles + such as Haircut, Overbeck type II and the Covariance Allocation Principle. It + also provides some shortcuts for obtaining the Value at Risk and the Expectation + Shortfall, using both the normal and the t-student distribution, see Urbina and + Guillén (2014) and Urbina (2013). + date_publication: '2023-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OCA + url_git: '' +occ: + version: '1.2' + title: Estimation of PET Neuroreceptor Occupancies + maintainer: Joaquim Radua + description: Estimate the positron emission tomography (PET) neuroreceptor occupancies + from the total volumes of distribution of a set of regions of interest. Fitting + methods include the simple 'reference region', 'ordinary least squares' (sometimes + known as occupancy plot), and 'restricted maximum likelihood estimation'. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=occ + url_git: '' +occCite: + version: 0.5.9 + title: Querying and Managing Large Biodiversity Occurrence Datasets + maintainer: Hannah L. Owens + description: |- + Facilitates the gathering of biodiversity occurrence data + from disparate sources. Metadata is managed throughout the process to facilitate + reporting and enhanced ability to repeat analyses. + date_publication: '2024-10-28' + bug_reports: https://github.com/ropensci/occCite/issues + url: https://docs.ropensci.org/occCite/ + url_cran: https://CRAN.R-project.org/package=occCite + url_git: '' +occumb: + version: 1.1.0 + title: Site Occupancy Modeling for Environmental DNA Metabarcoding + maintainer: Keiichi Fukaya + description: |- + Fits multispecies site occupancy models to environmental DNA + metabarcoding data collected using spatially-replicated survey design. + Model fitting results can be used to evaluate and compare the effectiveness + of species detection to find an efficient survey design. + Reference: Fukaya et al. (2022) . + date_publication: '2024-03-26' + bug_reports: https://github.com/fukayak/occumb/issues + url: https://fukayak.github.io/occumb/ + url_cran: https://CRAN.R-project.org/package=occumb + url_git: https://github.com/fukayak/occumb +occupancy: + version: '1.2' + title: Probability Functions for Occupancy Distributions + maintainer: Ben O'Neill + description: |- + The classical and extended occupancy distributions occur in cases where balls are randomly allocated + to bins. The PDF, CDF, quantile functions, generation of random variates, and calculating + the first four central moments of the distributions are implemented as described in + O’Neill (2019) . + date_publication: '2021-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=occupancy + url_git: '' +occupationMeasurement: + version: 0.3.2 + title: Interactively Measure Occupations in Interviews and Beyond + maintainer: Jan Simson + description: |- + Perform interactive occupation coding during interviews as + described in Peycheva, D., Sakshaug, J., Calderwood, L. (2021) + and Schierholz, M., Gensicke, M., Tschersich, N., Kreuter, F. (2018) . + Generate suggestions for occupational categories based on free text + input, with pre-trained machine learning models in German and a ready-to-use + shiny application provided for quick and easy data collection. + date_publication: '2023-09-27' + bug_reports: https://github.com/occupationMeasurement/occupationMeasurement/issues + url: https://occupationMeasurement.github.io/occupationMeasurement/ + url_cran: https://CRAN.R-project.org/package=occupationMeasurement + url_git: https://github.com/occupationMeasurement/occupationMeasurement +ocd: + version: '1.1' + title: High-Dimensional Multiscale Online Changepoint Detection + maintainer: Yudong Chen + description: Implements the algorithm in Chen, Wang and Samworth (2020) + for online detection of sudden mean changes in a sequence of high-dimensional + observations. It also implements methods by Mei (2010) , + Xie and Siegmund (2013) and Chan (2017) . + date_publication: '2020-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ocd + url_git: '' +oce: + version: 1.8-3 + title: Analysis of Oceanographic Data + maintainer: Dan Kelley + description: |- + Supports the analysis of Oceanographic data, including 'ADCP' + measurements, measurements made with 'argo' floats, 'CTD' measurements, + sectional data, sea-level time series, coastline and topographic data, etc. + Provides specialized functions for calculating seawater properties such as + potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. + Produces graphical displays that conform to the conventions of the + Oceanographic literature. This package is discussed extensively by + Kelley (2018) "Oceanographic Analysis with R" . + date_publication: '2024-08-17' + bug_reports: https://github.com/dankelley/oce/issues + url: https://dankelley.github.io/oce/ + url_cran: https://CRAN.R-project.org/package=oce + url_git: '' +oceanexplorer: + version: 0.1.0 + title: Explore Our Planet's Oceans with NOAA + maintainer: Martin Schobben + description: |- + Provides tools for easy exploration of the world ocean atlas of + the US agency National Oceanic and Atmospheric Administration (NOAA). It + includes functions to extract NetCDF data from the repository and code to + visualize several physical and chemical parameters of the ocean. A Shiny app + further allows interactive exploration of the data. The methods for data + collecting and quality checks are described in several papers, which can be + found here: . + date_publication: '2023-10-16' + bug_reports: https://github.com/MartinSchobben/oceanexplorer/issues + url: https://martinschobben.github.io/oceanexplorer/ + url_cran: https://CRAN.R-project.org/package=oceanexplorer + url_git: https://github.com/MartinSchobben/oceanexplorer +oceanic: + version: 0.1.8 + title: Location Identify Tool + maintainer: shiao chih hao + description: |- + Determine the sea area where the fishing boat operates. + The latitude and longitude of geographic coordinates are used to match oceanic areas and economic sea areas. + You can plot the distribution map with dotplot() function. + Please refer to Flanders Marine Institute (2020) . + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oceanic + url_git: '' +oceanis: + version: 1.8.5 + title: Cartography for Statistical Analysis + maintainer: Sébastien Novella + description: |- + Creating maps for statistical analysis such as proportional circles, choropleth, typology and flows. Some functions use 'shiny' or 'leaflet' technologies for dynamism and interactivity. + The great features are : + - Create maps in a web environment where the parameters are modifiable on the fly ('shiny' and 'leaflet' technologies). + - Create interactive maps through zoom and pop-up ('leaflet' technology). + - Create frozen maps with the possibility to add labels. + date_publication: '2022-07-13' + bug_reports: https://github.com/insee-psar-at/oceanis-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oceanis + url_git: https://github.com/insee-psar-at/oceanis-package/ +oceanmap: + version: 0.1.6 + title: A Plotting Toolbox for 2D Oceanographic Data + maintainer: Robert K. Bauer + description: Plotting toolbox for 2D oceanographic data (satellite data, sea surface + temperature, chlorophyll, ocean fronts & bathymetry). Recognized classes and formats + include netcdf, Raster, '.nc' and '.gz' files. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oceanmap + url_git: '' +OceanView: + version: 1.0.7 + title: Visualisation of Oceanographic Data and Model Output + maintainer: Karline Soetaert + description: Functions for transforming and viewing 2-D and 3-D (oceanographic) + data and model output. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OceanView + url_git: '' +oceanwaves: + version: 0.2.0 + title: Ocean Wave Statistics + maintainer: Luke Miller + description: |- + Calculate ocean wave height summary statistics and process data + from bottom-mounted pressure sensor data loggers. Derived primarily from + MATLAB functions provided by U. Neumeier at + . Wave number + calculation based on the algorithm in Hunt, J. N. (1979, ISSN:0148-9895) + "Direct Solution of Wave Dispersion Equation", American Society of Civil + Engineers Journal of the Waterway, Port, Coastal, and Ocean Division, + Vol 105, pp 457-459. + date_publication: '2021-06-02' + bug_reports: https://github.com/millerlp/oceanwaves/issues + url: https://millerlp.github.io/oceanwaves/ + url_cran: https://CRAN.R-project.org/package=oceanwaves + url_git: https://github.com/millerlp/oceanwaves +oceCens: + version: 0.1.2 + title: Ordered Composite Endpoints with Censoring + maintainer: Michael P. Fay + description: |- + Estimates win ratio or Mann-Whitney parameter for two group + comparisons using ordered composite endpoints with right censoring + as described in Follmann, Fay, Hamasaki, and Evans (2020). + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oceCens + url_git: '' +ocedata: + version: 0.2.2 + title: Oceanographic Data Sets for 'oce' Package + maintainer: Dan Kelley + description: |- + Several Oceanographic data sets are provided for use + by the 'oce' package and for other purposes. + date_publication: '2022-08-19' + bug_reports: https://github.com/dankelley/ocedata/issues + url: https://dankelley.github.io/ocedata/ + url_cran: https://CRAN.R-project.org/package=ocedata + url_git: '' +ocf: + version: 1.0.3 + title: Ordered Correlation Forest + maintainer: Riccardo Di Francesco + description: |- + Machine learning estimator specifically optimized for predictive modeling of ordered non-numeric outcomes. 'ocf' provides forest-based estimation of the + conditional choice probabilities and the covariates’ marginal effects. Under an "honesty" condition, the estimates are consistent and asymptotically normal + and standard errors can be obtained by leveraging the weight-based representation of the random forest predictions. Please reference the use as Di Francesco (2025) + . + date_publication: '2025-02-03' + bug_reports: https://github.com/riccardo-df/ocf/issues + url: https://riccardo-df.github.io/ocf/ + url_cran: https://CRAN.R-project.org/package=ocf + url_git: https://github.com/riccardo-df/ocf +ockc: + version: '1.1' + title: Order Constrained Solutions in k-Means Clustering + maintainer: Sebastian Krey + description: |- + Extends 'flexclust' with an R implementation of order constrained + solutions in k-means clustering (Steinley and Hubert, 2008, ). + date_publication: '2022-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ockc + url_git: '' +oclust: + version: 0.2.0 + title: Gaussian Model-Based Clustering with Outliers + maintainer: Paul D. McNicholas + description: Provides a function to detect and trim outliers in Gaussian mixture + model-based clustering using methods described in Clark and McNicholas (2022) + . + date_publication: '2022-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oclust + url_git: '' +OCNet: + version: 1.2.2 + title: Optimal Channel Networks + maintainer: Luca Carraro + description: |- + Generate and analyze Optimal Channel Networks (OCNs): + oriented spanning trees reproducing all scaling features characteristic + of real, natural river networks. As such, they can be used in a variety + of numerical experiments in the fields of hydrology, ecology and + epidemiology. See Carraro et al. (2020) + for a presentation of the package; Rinaldo et al. (2014) + for a theoretical overview on the OCN + concept; Furrer and Sain (2010) for the + construct used. + date_publication: '2024-04-16' + bug_reports: https://github.com/lucarraro/OCNet/issues + url: https://lucarraro.github.io/OCNet/ + url_cran: https://CRAN.R-project.org/package=OCNet + url_git: '' +ocp: + version: 0.1.1 + title: Bayesian Online Changepoint Detection + maintainer: Andrea Pagotto + description: |- + Implements the Bayesian online changepoint + detection method by Adams and MacKay (2007) + for univariate or multivariate data. + Gaussian and Poisson probability models are implemented. + Provides post-processing functions with + alternative ways to extract changepoints. + date_publication: '2019-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ocp + url_git: '' +ocs4R: + version: 0.2-3 + title: Interface to Open Collaboration Services (OCS) REST API + maintainer: Emmanuel Blondel + description: Provides an Interface to Open Collaboration Services 'OCS' () + REST API. + date_publication: '2022-03-17' + bug_reports: https://github.com/eblondel/ocs4R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ocs4R + url_git: https://github.com/eblondel/ocs4R +OCSdata: + version: 1.0.2 + title: Download Data from the 'Open Case Studies' Repository + maintainer: Carrie Wright + description: |2- + + Provides functions to access and download data from the 'Open Case Studies' + repositories on 'GitHub' . Different functions enable + users to grab the data they need at different sections in the case study, as well as + download the whole case study repository. All the user needs to do is input the name of + the case study being worked on. The package relies on the httr::GET() function to access + files through the 'GitHub' API. The functions usethis::use_zip() and usethis::create_from_github() + are used to clone and/or download the case study repositories. To cite an individual case study, + please see the respective 'README' file at . + + + + + + + + + + + . + date_publication: '2021-08-20' + bug_reports: https://github.com/opencasestudies/OCSdata/issues + url: https://doi.org/10.5281/zenodo.5214347 + url_cran: https://CRAN.R-project.org/package=OCSdata + url_git: https://github.com/opencasestudies/OCSdata +octopucs: + version: 0.1.1 + title: Statistical Support for Hierarchical Clusters + maintainer: Roger Guevara + description: Generates n hierarchical clustering hypotheses on subsets of classifiers + (usually species in community ecology studies). The n clustering hypotheses are + combined to generate a generalized cluster, and computes three metrics of support. + 1) The average proportion of elements conforming the group in each of the n clusters + (integrity). And 2) the contamination, i.e., the average proportion of elements + from other groups that enter a focal group. 3) The probability of existence of + the group gives the integrity and contamination in a Bayesian approach. + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=octopucs + url_git: '' +octopus: + version: 0.4.2 + title: A Database Management Tool + maintainer: Marcus Codrescu + description: |- + A database management tool built as a 'shiny' application. Connect to various + databases to send queries, upload files, preview tables, and more. + date_publication: '2024-01-10' + bug_reports: https://github.com/MCodrescu/octopus/issues + url: https://mcodrescu.github.io/octopus/ + url_cran: https://CRAN.R-project.org/package=octopus + url_git: https://github.com/MCodrescu/octopus +octopusR: + version: 1.0.1 + title: Interact with the 'Octopus Energy' API + maintainer: James McMahon + description: |- + A simple wrapper for the 'Octopus Energy' API + . It handles + authentication, by storing a provided API key and meter details. + Implemented endpoints include 'products' for viewing tariff details + and 'consumption' for viewing meter consumption data. + date_publication: '2023-06-09' + bug_reports: https://github.com/Moohan/octopusR/issues + url: https://moohan.github.io/octopusR/ + url_cran: https://CRAN.R-project.org/package=octopusR + url_git: https://github.com/Moohan/octopusR +od: + version: 0.5.1 + title: Manipulate and Map Origin-Destination Data + maintainer: Robin Lovelace + description: |- + The aim of 'od' is to provide tools and example datasets for + working with origin-destination ('OD') datasets of the type used to + describe aggregate urban mobility patterns (Carey et al. 1981) + . The package builds on functions for + working with 'OD' data in the package 'stplanr', (Lovelace and Ellison + 2018) with a focus on computational + efficiency and support for the 'sf' class system (Pebesma 2018) + . With few dependencies and a simple class + system based on data frames, the package is intended to facilitate + efficient analysis of 'OD' datasets and to provide a place for + developing new functions. The package enables the creation and + analysis of geographic entities representing large scale mobility + patterns, from daily travel between zones in cities to migration + between countries. + date_publication: '2024-08-20' + bug_reports: https://github.com/itsleeds/od/issues + url: https://itsleeds.github.io/od/ + url_cran: https://CRAN.R-project.org/package=od + url_git: https://github.com/itsleeds/od +ODataQuery: + version: 0.5.3 + title: Querying on 'OData' + maintainer: Laurent Verweijen + description: |- + Make querying on 'OData' easier. It exposes an 'ODataQuery' object + that can be manipulated and provides features such as selection, filtering + and ordering. + date_publication: '2021-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ODataQuery + url_git: '' +ODB: + version: 1.2.1 + title: Open Document Databases (.odb) Management + maintainer: Sylvain Mareschal + description: Functions to create, connect, update and query 'HSQL' databases embedded + in Open Document Databases files, as 'OpenOffice' and 'LibreOffice' do. + date_publication: '2020-03-11' + bug_reports: https://github.com/maressyl/R.ODB/issues + url: http://bioinformatics.ovsa.fr/ODB + url_cran: https://CRAN.R-project.org/package=ODB + url_git: '' +odbc: + version: 1.6.0 + title: Connect to ODBC Compatible Databases (using the DBI Interface) + maintainer: Hadley Wickham + description: A DBI-compatible interface to ODBC databases. + date_publication: '2025-02-28' + bug_reports: https://github.com/r-dbi/odbc/issues + url: https://odbc.r-dbi.org + url_cran: https://CRAN.R-project.org/package=odbc + url_git: https://github.com/r-dbi/odbc +odbr: + version: 0.1.1 + title: Download Data from Brazil's Origin Destination Surveys + maintainer: Haydee Svab + description: Download data from Brazil's Origin Destination Surveys. The package + covers both data from household travel surveys, dictionaries of variables, and + the spatial geometries of surveys conducted in different years and across various + urban areas in Brazil. For some cities, the package will include enhanced versions + of the data sets with variables "harmonized" across different years. + date_publication: '2025-02-14' + bug_reports: https://github.com/hsvab/odbr/issues + url: https://hsvab.github.io/odbr/ + url_cran: https://CRAN.R-project.org/package=odbr + url_git: https://github.com/hsvab/odbr +oddnet: + version: 0.1.1 + title: Anomaly Detection in Temporal Networks + maintainer: Sevvandi Kandanaarachchi + description: |- + Anomaly detection in dynamic, temporal networks. The package + 'oddnet' uses a feature-based method to identify anomalies. First, it computes + many features for each network. Then it models the features using time series + methods. Using time series residuals it detects anomalies. This way, the + temporal dependencies are accounted for when identifying anomalies + (Kandanaarachchi, Hyndman 2022) . + date_publication: '2024-02-11' + bug_reports: '' + url: https://sevvandi.github.io/oddnet/ + url_cran: https://CRAN.R-project.org/package=oddnet + url_git: '' +odds.converter: + version: 1.4.8 + title: Betting Odds Conversion + maintainer: Marco Blume + description: |- + Conversion between the most common odds types for sports betting. + Hong Kong odds, US odds, Decimal odds, Indonesian odds, Malaysian odds, and raw + Probability are covered in this package. + date_publication: '2018-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=odds.converter + url_git: '' +odds.n.ends: + version: 0.1.4 + title: |- + Odds Ratios, Contingency Table, and Model Significance from a + Generalized Linear Model Object + maintainer: Jenine Harris + description: Computes odds ratios and 95% confidence intervals from a generalized + linear model object. It also computes model significance with the chi-squared + statistic and p-value and it computes model fit using a contingency table to determine + the percent of observations for which the model correctly predicts the value of + the outcome. Calculates model sensitivity and specificity. + date_publication: '2021-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=odds.n.ends + url_git: '' +oddsapiR: + version: 0.0.3 + title: Access Live Sports Odds from the Odds API + maintainer: Saiem Gilani + description: |- + A utility to quickly obtain clean and tidy sports + odds from The Odds API . + date_publication: '2023-03-19' + bug_reports: https://github.com/sportsdataverse/oddsapiR/issues + url: https://oddsapiR.sportsdataverse.org/(docs) + url_cran: https://CRAN.R-project.org/package=oddsapiR + url_git: https://github.com/sportsdataverse/oddsapiR(repo) +OddsPlotty: + version: 1.0.2 + title: Odds Plot to Visualise a Logistic Regression Model + maintainer: Gary Hutson + description: |- + Uses the outputs of a logistic regression model, from caret , to build an odds plot. + This allows for the rapid visualisation of odds plot ratios and works best with the outputs of CARET's GLM model class, by returning the final trained model. + date_publication: '2021-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OddsPlotty + url_git: https://github.com/StatsGary/OddsPlotty +oddsratio: + version: 2.0.1 + title: Odds Ratio Calculation for GAM(M)s & GLM(M)s + maintainer: Patrick Schratz + description: |- + Simplified odds ratio calculation of GAM(M)s & + GLM(M)s. Provides structured output (data frame) of all predictors and + their corresponding odds ratios and confident intervals for further + analyses. It helps to avoid false references of predictors and + increments by specifying these parameters in a list instead of using + 'exp(coef(model))' (standard approach of odds ratio calculation for + GLMs) which just returns a plain numeric output. For GAM(M)s, odds + ratio calculation is highly simplified with this package since it + takes care of the multiple 'predict()' calls of the chosen predictor + while holding other predictors constant. Also, this package allows + odds ratio calculation of percentage steps across the whole predictor + distribution range for GAM(M)s. In both cases, confident intervals + are returned additionally. Calculated odds ratio of GAM(M)s can be + inserted into the smooth function plot. + date_publication: '2020-05-24' + bug_reports: https://github.com/pat-s/oddsratio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oddsratio + url_git: https://github.com/pat-s/oddsratio +oddstream: + version: 0.5.0 + title: Outlier Detection in Data Streams + maintainer: Priyanga Dilini Talagala + description: |- + We proposes a framework that provides real time support for early detection of + anomalous series within a large collection of streaming time series data. By definition, anomalies + are rare in comparison to a system's typical behaviour. We define an anomaly as an observation that + is very unlikely given the forecast distribution. The algorithm first forecasts a boundary for the + system's typical behaviour using a representative sample of the typical behaviour of the system. An + approach based on extreme value theory is used for this boundary prediction process. Then a sliding + window is used to test for anomalous series within the newly arrived collection of series. Feature + based representation of time series is used as the input to the model. To cope with concept drift, + the forecast boundary for the system's typical behaviour is updated periodically. More details + regarding the algorithm can be found in Talagala, P. D., Hyndman, R. J., Smith-Miles, K., et al. + (2019) . + date_publication: '2019-12-16' + bug_reports: https://github.com/pridiltal/oddstream/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oddstream + url_git: '' +odeGUTS: + version: 1.0.3 + title: Solve ODE for GUTS-RED-SD and GUTS-RED-IT Using Compiled Code + maintainer: Benoit Goussen + description: |- + Allows performing forwards prediction for the General Unified + Threshold model of Survival using compiled ode code. This package + was created to avoid dependency with the 'morse' package that requires + the installation of 'JAGS'. This package is based on functions from + the 'morse' package v3.3.1: Virgile Baudrot, Sandrine Charles, + Marie Laure Delignette-Muller, Wandrille Duchemin, Benoit Goussen, + Nils Kehrein, Guillaume Kon-Kam-King, Christelle Lopes, Philippe Ruiz, + Alexander Singer and Philippe Veber (2021) . + date_publication: '2024-10-04' + bug_reports: https://github.com/bgoussen/odeGUTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=odeGUTS + url_git: https://github.com/bgoussen/odeGUTS +ODEnetwork: + version: 1.3.2 + title: Network of Differential Equations + maintainer: Dirk Surmann + description: |- + Simulates a network of ordinary differential equations of order + two. The package provides an easy interface to construct networks. In addition + you are able to define different external triggers to manipulate the trajectory. + The method is described by Surmann, Ligges, and Weihs (2014) . + date_publication: '2020-04-03' + bug_reports: https://github.com/surmann/ODEnetwork/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ODEnetwork + url_git: https://github.com/surmann/ODEnetwork +ODEsensitivity: + version: 1.1.2 + title: Sensitivity Analysis of Ordinary Differential Equations + maintainer: Dirk Surmann + description: |- + Performs sensitivity analysis in ordinary differential equation (ode) models. + The package utilize the ode interface from 'deSolve' and connects it with the + sensitivity analysis from 'sensitivity'. Additionally we add a method to + run the sensitivity analysis on variables with class 'ODEnetwork'. A detailed + plotting function provides outputs on the calculations. + The method is described by Weber, Theers, Surmann, Ligges, and Weihs (2018) . + date_publication: '2019-01-09' + bug_reports: https://github.com/surmann/ODEsensitivity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ODEsensitivity + url_git: https://github.com/surmann/ODEsensitivity +odetector: + version: 1.0.1 + title: Outlier Detection Using Partitioning Clustering Algorithms + maintainer: Zeynel Cebeci + description: An object is called "outlier" if it remarkably deviates from the other + objects in a data set. Outlier detection is the process to find outliers by using + the methods that are based on distance measures, clustering and spatial methods + (Ben-Gal, 2005 ). It is one of the intensively studied research + topics for identification of novelties, frauds, anomalies, deviations or exceptions + in addition to its use for outlier removing in data processing. This package provides + the implementations of some novel approaches to detect the outliers based on typicality + degrees that are obtained with the soft partitioning clustering algorithms such + as Fuzzy C-means and its variants. + date_publication: '2022-11-08' + bug_reports: https://github.com/zcebeci/odetector/issues + url: '' + url_cran: https://CRAN.R-project.org/package=odetector + url_git: https://github.com/zcebeci/odetector +odin: + version: 1.2.7 + title: ODE Generation and Integration + maintainer: Rich FitzJohn + description: |- + Generate systems of ordinary differential equations + (ODE) and integrate them, using a domain specific language + (DSL). The DSL uses R's syntax, but compiles to C in order to + efficiently solve the system. A solver is not provided, but + instead interfaces to the packages 'deSolve' and 'dde' are + generated. With these, while solving the differential equations, + no allocations are done and the calculations remain entirely in + compiled code. Alternatively, a model can be transpiled to R for + use in contexts where a C compiler is not present. After + compilation, models can be inspected to return information about + parameters and outputs, or intermediate values after calculations. + 'odin' is not targeted at any particular domain and is suitable + for any system that can be expressed primarily as mathematical + expressions. Additional support is provided for working with + delays (delay differential equations, DDE), using interpolated + functions during interpolation, and for integrating quantities + that represent arrays. + date_publication: '2025-02-07' + bug_reports: https://github.com/mrc-ide/odin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=odin + url_git: https://github.com/mrc-ide/odin +odk: + version: '1.5' + title: Convert 'ODK' or 'XLSForm' to 'SPSS' Data Frame + maintainer: Muntashir-Al-Arefin + description: After develop a 'ODK' frame, we can link + the frame to 'Google Sheets' and collect + data through 'Android' . This data uploaded to a 'Google + sheets'. odk2spss() function help to convert the 'odk' frame into 'SPSS' + frame. Also able to add downloaded 'Google sheets' data or read data from 'Google + sheets' by using 'ODK' frame 'submission_url'. + date_publication: '2017-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=odk + url_git: '' +ODMeans: + version: 0.2.1 + title: 'OD-Means: k-Means for Origin-Destination' + maintainer: Sebastian Moreno + description: |- + OD-means is a hierarchical adaptive k-means algorithm based on origin-destination pairs. + In the first layer of the hierarchy, the clusters are separated automatically based on the variation + of the within-cluster distance of each cluster until convergence. The second layer of the hierarchy + corresponds to the sub clustering process of small clusters based on the distance between the origin + and destination of each cluster. + date_publication: '2024-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ODMeans + url_git: '' +odr: + version: 1.4.4 + title: |- + Optimal Design and Statistical Power for Experimental Studies + Investigating Main, Mediation, and Moderation Effects + maintainer: Zuchao Shen + description: |- + Calculate the optimal sample size allocation that + produces the highest statistical power for experimental + studies under a budget constraint, and + perform power analyses with and without accommodating + cost structures of sampling. The designs cover single-level + and multilevel experiments detecting main, mediation, + and moderation effects (and some combinations). + The references for the proposed methods include: + (1) Shen, Z., & Kelcey, B. (2020). + Optimal sample allocation under unequal costs in + cluster-randomized trials. + Journal of Educational and Behavioral Statistics, 45(4): 446-474. + . + (2) Shen, Z., & Kelcey, B. (2022b). Optimal sample allocation for + three-level multisite cluster-randomized trials. + Journal of Research on Educational Effectiveness, 15 (1), 130-150. + . + (3) Shen, Z., & Kelcey, B. (2022a). Optimal sample allocation in + multisite randomized trials. The Journal of Experimental Education. + . + (4) Champely, S. (2020). pwr: Basic functions for power analysis + (Version 1.3-0) [Software]. Available from + . + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=odr + url_git: '' +ODRF: + version: 0.0.4 + title: Oblique Decision Random Forest for Classification and Regression + maintainer: Yu Liu + description: |- + The oblique decision tree (ODT) uses linear combinations of + predictors as partitioning variables in a decision tree. Oblique + Decision Random Forest (ODRF) is an ensemble of multiple ODTs + generated by feature bagging. Both can be used for classification and + regression as supplements to the classical CART of Breiman (1984) + and Random Forest of Breiman (2001) + respectively. + date_publication: '2023-05-28' + bug_reports: https://github.com/liuyu-star/ODRF/issues + url: https://liuyu-star.github.io/ODRF/ + url_cran: https://CRAN.R-project.org/package=ODRF + url_git: '' +ODS: + version: 0.2.0 + title: Statistical Methods for Outcome-Dependent Sampling Designs + maintainer: Yinghao Pan + description: |- + Outcome-dependent sampling (ODS) schemes are cost-effective ways to enhance study efficiency. + In ODS designs, one observes the exposure/covariates with a probability that depends on the outcome + variable. Popular ODS designs include case-control for binary outcome, case-cohort for time-to-event + outcome, and continuous outcome ODS design (Zhou et al. 2002) . + Because ODS data has biased sampling nature, standard statistical analysis such as linear regression + will lead to biases estimates of the population parameters. This package implements four statistical + methods related to ODS designs: (1) An empirical likelihood method analyzing the primary continuous + outcome with respect to exposure variables in continuous ODS design (Zhou et al., 2002). (2) A partial + linear model analyzing the primary outcome in continuous ODS design (Zhou, Qin and Longnecker, 2011) + . (3) Analyze a secondary outcome in continuous ODS design + (Pan et al. 2018) . (4) An estimated likelihood method analyzing a secondary + outcome in case-cohort data (Pan et al. 2017) . + date_publication: '2018-11-19' + bug_reports: https://github.com/Yinghao-Pan/ODS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ODS + url_git: https://github.com/Yinghao-Pan/ODS +ODT: + version: 1.0.0 + title: Optimal Decision Trees Algorithm + maintainer: Katyna Sada Del Real + description: Implements a tree-based method specifically designed for personalized + medicine applications. By using genomic and mutational data, 'ODT' efficiently + identifies optimal drug recommendations tailored to individual patient profiles. + The 'ODT' algorithm constructs decision trees that bifurcate at each node, selecting + the most relevant markers (discrete or continuous) and corresponding treatments, + thus ensuring that recommendations are both personalized and statistically robust. + This iterative approach enhances therapeutic decision-making by refining treatment + suggestions until a predefined group size is achieved. Moreover, the simplicity + and interpretability of the resulting trees make the method accessible to healthcare + professionals. Includes functions for training the decision tree, making predictions + on new samples or patients, and visualizing the resulting tree. For detailed insights + into the methodology, please refer to Gimeno et al. (2023) . + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ODT + url_git: '' +OECD: + version: 0.2.5 + title: Search and Extract Data from the OECD + maintainer: Eric Persson + description: |- + Search and extract data from the Organization for Economic + Cooperation and Development (OECD). + date_publication: '2021-12-01' + bug_reports: https://github.com/expersso/OECD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OECD + url_git: https://github.com/expersso/OECD +OEFPIL: + version: 0.1.1 + title: |- + Optimal Estimation of Function Parameters by Iterated + Linearization + maintainer: Stanislav Zamecnik + description: |- + Package for estimating the parameters of a nonlinear function using iterated linearization via Taylor series. Method is based on Kubáček (2000) ISBN: 80-244-0093-6. The algorithm is a generalization of the procedure given in Köning, R., Wimmer, G. + and Witkovský, V. (2014) . + date_publication: '2021-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OEFPIL + url_git: '' +oeli: + version: 0.7.1 + title: Utilities for Developing Data Science Software + maintainer: Lennart Oelschläger + description: |- + Some general helper functions that I (and maybe others) find useful + when developing data science software. + date_publication: '2024-11-27' + bug_reports: https://github.com/loelschlaeger/oeli/issues + url: http://loelschlaeger.de/oeli/ + url_cran: https://CRAN.R-project.org/package=oeli + url_git: https://github.com/loelschlaeger/oeli +oem: + version: 2.0.12 + title: 'Orthogonalizing EM: Penalized Regression for Big Tall Data' + maintainer: Jared Huling + description: |- + Solves penalized least squares problems for big tall data + using the orthogonalizing EM algorithm of Xiong et al. (2016) + . The main fitting function is oem() and the + functions cv.oem() and xval.oem() are for cross validation, the latter being an + accelerated cross validation function for linear models. The big.oem() function + allows for out of memory fitting. A description of the underlying methods and + code interface is described in Huling and Chien (2022) . + date_publication: '2024-07-31' + bug_reports: https://github.com/jaredhuling/oem/issues + url: https://arxiv.org/abs/1801.09661 + url_cran: https://CRAN.R-project.org/package=oem + url_git: https://github.com/jaredhuling/oem +oenb: + version: 0.0.2 + title: Tools for the OeNB Data Web Service + maintainer: Franz X. Mohr + description: Tools to access data from the data web service of the Oesterreichische + Nationalbank (OeNB), . + date_publication: '2021-03-22' + bug_reports: https://github.com/franzmohr/oenb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oenb + url_git: https://github.com/franzmohr/oenb +OenoKPM: + version: 2.4.1 + title: |- + Modeling the Kinetics of Carbon Dioxide Production in Alcoholic + Fermentation + maintainer: Angelo Gava + description: 'Developed to help researchers who need to model the kinetics of carbon + dioxide (CO2) production in alcoholic fermentation of wines, beers and other fermented + products. The following models are available for modeling the carbon dioxide production + curve as a function of time: 5PL, Gompertz and 4PL. This package has different + functions, which applied can: perform the modeling of the data obtained in the + fermentation and return the coefficients, analyze the model fit and return different + statistical metrics, and calculate the kinetic parameters: Maximum production + of carbon dioxide; Maximum rate of production of carbon dioxide; Moment in which + maximum fermentation rate occurs; Duration of the latency phase for carbon dioxide + production; Carbon dioxide produced until maximum fermentation rate occurs. In + addition, a function that generates graphs with the observed and predicted data + from the models, isolated and combined, is available. Gava, A., Borsato, D., & + Ficagna, E. (2020)."Effect of mixture of fining agents on the fermentation kinetics + of base wine for sparkling wine production: Use of methodology for modeling". + .' + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OenoKPM + url_git: '' +oesr: + version: 0.1.0 + title: Methods for the Office of Evaluation Sciences + maintainer: Ryan T. Moore + description: Methods for statistical analysis and reporting preferred by the US + Office of Evaluation Sciences (OES). This package prepares data from standard + model output objects (such as from \code{lm()} and \code{estimatr::lm_robust()}) + and creates visualizations of treatment effects from the prepared quantities, + according to the standards of the US Office of Evaluation Sciences. + date_publication: '2023-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oesr + url_git: '' +oews2020: + version: 1.0.0 + title: May 2020 Occupational Employment and Wage Statistics + maintainer: Christopher Mann + description: |- + Contains data from the May 2020 Occupational Employment and + Wage Statistics data release from the U.S. Bureau of Labor Statistics. The + dataset covers employment and wages across occupations, industries, states, + and at the national level. Metropolitan data is not included. + date_publication: '2022-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oews2020 + url_git: '' +oews2021: + version: 1.0.0 + title: May 2021 Occupational Employment and Wage Statistics + maintainer: Christopher Mann + description: |- + Contains data from the May 2021 Occupational Employment and + Wage Statistics data release from the U.S. Bureau of Labor Statistics. The + dataset covers employment and wages across occupations, industries, states, + and at the national level. Metropolitan data is not included. + date_publication: '2022-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oews2021 + url_git: '' +officedown: + version: 0.3.3 + title: Enhanced 'R Markdown' Format for 'Word' and 'PowerPoint' + maintainer: David Gohel + description: |- + Allows production of 'Microsoft' corporate documents from 'R Markdown' by + reusing formatting defined in 'Microsoft Word' documents. You can reuse table styles, + list styles but also add column sections, landscape oriented pages. Table and image + captions as well as cross-references are transformed into 'Microsoft Word' fields, + allowing documents edition and merging without issue with references; the syntax + conforms to the 'bookdown' cross-reference definition. Objects generated by + the 'officer' package are also supported in the 'knitr' chunks. + 'Microsoft PowerPoint' presentations also benefit from this as well as the + ability to produce editable vector graphics in 'PowerPoint' and also to + define placeholder where content is to be added. + date_publication: '2024-07-16' + bug_reports: https://github.com/davidgohel/officedown/discussions + url: https://ardata-fr.github.io/officeverse/ + url_cran: https://CRAN.R-project.org/package=officedown + url_git: '' +officer: + version: 0.6.7 + title: Manipulation of Microsoft Word and PowerPoint Documents + maintainer: David Gohel + description: |- + Access and manipulate 'Microsoft Word', 'RTF' and 'Microsoft + PowerPoint' documents from R. The package focuses on tabular and + graphical reporting from R; it also provides two functions that let + users get document content into data objects. A set of functions lets + add and remove images, tables and paragraphs of text in new or + existing documents. The package does not require any installation of + Microsoft products to be able to write Microsoft files. + date_publication: '2024-10-09' + bug_reports: https://github.com/davidgohel/officer/issues + url: https://ardata-fr.github.io/officeverse/ + url_cran: https://CRAN.R-project.org/package=officer + url_git: '' +offlineChange: + version: 0.0.4 + title: Detect Multiple Change Points from Time Series + maintainer: Jiahuan Ye + description: |- + Detect the number and locations of change points. The locations can be either exact or in terms of ranges, + depending on the available computational resource. The method is based on Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh (2017) . + date_publication: '2020-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=offlineChange + url_git: '' +offsetreg: + version: 1.1.0 + title: An Extension of 'Tidymodels' Supporting Offset Terms + maintainer: Matt Heaphy + description: |- + Extend the 'tidymodels' ecosystem to + enable the creation of predictive models with offset terms. Models with + offsets are most useful when working with count data or when fitting an + adjustment model on top of an existing model with a prior expectation. + The former situation is common in insurance where data is often weighted by + exposures. The latter is common in life insurance where industry mortality + tables are often used as a starting point for setting assumptions. + date_publication: '2024-04-11' + bug_reports: https://github.com/mattheaphy/offsetreg/issues + url: https://mattheaphy.github.io/offsetreg/ + url_cran: https://CRAN.R-project.org/package=offsetreg + url_git: https://github.com/mattheaphy/offsetreg/ +ofGEM: + version: '1.0' + title: |- + A Meta-Analysis Approach with Filtering for Identifying + Gene-Level Gene-Environment Interactions with Genetic + Association Data + maintainer: Jiebiao Wang + description: Offers a gene-based meta-analysis test with filtering to detect gene-environment + interactions (GxE) with association data, proposed by Wang et al. (2018) . + It first conducts a meta-filtering test to filter out unpromising SNPs by combining + all samples in the consortia data. It then runs a test of omnibus-filtering-based + GxE meta-analysis (ofGEM) that combines the strengths of the fixed- and random-effects + meta-analysis with meta-filtering. It can also analyze data from multiple ethnic + groups. + date_publication: '2018-07-13' + bug_reports: https://github.com/randel/ofGEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ofGEM + url_git: https://github.com/randel/ofGEM +ofpetrial: + version: 0.1.2 + title: Design on-Farm Precision Field Agronomic Trials + maintainer: Taro Mieno + description: A comprehensive system for designing and implementing on-farm precision + field agronomic trials. You provide field data, tell 'ofpetrial' how to design + a trial, and get readily-usable trial design files and a report checks the validity + and reliability of the trial design. + date_publication: '2024-12-11' + bug_reports: https://github.com/DIFM-Brain/ofpetrial/issues + url: https://difm-brain.github.io/ofpetrial/ + url_cran: https://CRAN.R-project.org/package=ofpetrial + url_git: '' +OGI: + version: 1.0.0 + title: Objective General Index + maintainer: Masaki Hamada + description: |- + Consider a data matrix of n individuals with p variates. The objective general index (OGI) + is a general index that combines the p variates into a univariate index in order to rank the n + individuals. The OGI is always positively correlated with each of the variates. + More details can be found in Sei (2016) . + date_publication: '2017-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OGI + url_git: '' +oglcnac: + version: 0.1.5 + title: Processing and Analysis of 'O-GlcNAcAtlas' Data + maintainer: Yaoxiang Li + description: |- + Provides tools for processing and analyzing data from the 'O-GlcNAcAtlas' database , + as described in Ma (2021) . It integrates 'UniProt' API calls + to retrieve additional information. It is specifically designed for research workflows + involving 'O-GlcNAcAtlas' data, providing a flexible and user-friendly interface for customizing + and downloading processed results. Interactive elements allow users to easily adjust parameters + and handle various biological datasets. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oglcnac + url_git: '' +oglmx: + version: 3.0.0.0 + title: Estimation of Ordered Generalized Linear Models + maintainer: Nathan Carroll + description: Ordered models such as ordered probit and ordered logit presume that + the error variance is constant across observations. In the case that this assumption + does not hold estimates of marginal effects are typically biased (Weiss (1997)). + This package allows for generalization of ordered probit and ordered logit models + by allowing the user to specify a model for the variance. Furthermore, the package + includes functions to calculate the marginal effects. Wrapper functions to estimate + the standard limited dependent variable models are also included. + date_publication: '2018-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oglmx + url_git: '' +ogrdbstats: + version: 0.5.2 + title: |- + Analysis of Adaptive Immune Receptor Repertoire Germ Line + Statistics + maintainer: William Lees + description: |- + Multiple tools are now available for inferring the personalised + germ line set from an adaptive immune receptor repertoire. + Output from these tools is converted to + a single format and supplemented with rich data such as usage and + characterisation of 'novel' germ line alleles. This data can be + particularly useful when considering the validity of novel inferences. Use + of the analysis provided is described in . + date_publication: '2024-11-03' + bug_reports: https://github.com/airr-community/ogrdbstats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ogrdbstats + url_git: https://github.com/airr-community/ogrdbstats +OHCSpackage: + version: 0.1.5 + title: Prepare Housing Data for Analysis + maintainer: Ilythia Morley + description: Prepares census and core housing needs data, specifically designed + for use with Statistics Canada data and standardized input data. The package offers + functions for tidying, organizing, and splitting complex data tables, making it + easier for users to perform analyses on the data. 'OHCSpackage''' is particularly + useful for those working with census data that has a consistent format, number + of rows, and number of columns. With this package, users can save time and streamline + their data preparation processes. + date_publication: '2023-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OHCSpackage + url_git: '' +OhdsiReportGenerator: + version: 1.0.1 + title: |- + Observational Health Data Sciences and Informatics Report + Generator + maintainer: Jenna Reps + description: Extract results into R from the Observational Health Data Sciences + and Informatics result database (see ) + and generate reports/presentations via 'quarto' that summarize results in HTML + format. Learn more about 'OhdsiReportGenerator' at . + date_publication: '2025-02-26' + bug_reports: https://github.com/OHDSI/OhdsiReportGenerator/issues + url: https://ohdsi.github.io/OhdsiReportGenerator/ + url_cran: https://CRAN.R-project.org/package=OhdsiReportGenerator + url_git: https://github.com/OHDSI/OhdsiReportGenerator +OhdsiShinyAppBuilder: + version: 1.0.0 + title: |- + Viewing Observational Health Data Sciences and Informatics + Results via 'shiny' Modules + maintainer: Jenna Reps + description: Users can build a single 'shiny' app for exploring population characterization, + population-level causal effect estimation, and patient-level prediction results + generated via the R analyses packages in 'HADES' (see ). + Learn more about 'OhdsiShinyAppBuilder' at . + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OhdsiShinyAppBuilder + url_git: '' +ohenery: + version: 0.1.2 + title: Modeling of Ordinal Random Variables via Softmax Regression + maintainer: Steven E. Pav + description: |- + Supports the modeling of ordinal random variables, + like the outcomes of races, via Softmax regression, + under the Harville and + Henery models. + date_publication: '2024-10-25' + bug_reports: https://github.com/shabbychef/ohenery/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ohenery + url_git: https://github.com/shabbychef/ohenery +Ohit: + version: 1.0.0 + title: OGA+HDIC+Trim and High-Dimensional Linear Regression Models + maintainer: Hai-Tang Chiou + description: 'Ing and Lai (2011) proposed a high-dimensional + model selection procedure that comprises three steps: orthogonal greedy algorithm + (OGA), high-dimensional information criterion (HDIC), and Trim. The first two + steps, OGA and HDIC, are used to sequentially select input variables and determine + stopping rules, respectively. The third step, Trim, is used to delete irrelevant + variables remaining in the second step. This package aims at fitting a high-dimensional + linear regression model via OGA+HDIC+Trim.' + date_publication: '2017-09-06' + bug_reports: '' + url: http://mx.nthu.edu.tw/~cking/pdf/IngLai2011.pdf + url_cran: https://CRAN.R-project.org/package=Ohit + url_git: '' +oHMMed: + version: 1.0.2 + title: HMMs with Ordered Hidden States and Emission Densities + maintainer: Michal Majka + description: |- + Inference using a class of Hidden Markov models + (HMMs) called 'oHMMed'(ordered HMM with emission densities + ): The 'oHMMed' algorithms identify + the number of comparably homogeneous regions within observed sequences + with autocorrelation patterns. These are modelled as discrete hidden + states; the observed data points are then realisations of continuous + probability distributions with state-specific means that enable + ordering of these distributions. The observed sequence is labelled + according to the hidden states, permitting only neighbouring states + that are also neighbours within the ordering of their associated + distributions. The parameters that characterise these state-specific + distributions are then inferred. Relevant for application to genomic + sequences, time series, or any other sequence data with serial + autocorrelation. + date_publication: '2024-04-19' + bug_reports: https://github.com/LynetteCaitlin/oHMMed/issues + url: https://lynettecaitlin.github.io/oHMMed/ + url_cran: https://CRAN.R-project.org/package=oHMMed + url_git: https://github.com/LynetteCaitlin/oHMMed +ohoegdm: + version: 0.1.0 + title: |- + Ordinal Higher-Order Exploratory General Diagnostic Model for + Polytomous Data + maintainer: James Joseph Balamuta + description: |- + Perform a Bayesian estimation of the ordinal exploratory + Higher-order General Diagnostic Model (OHOEGDM) for Polytomous Data + described by Culpepper, S. A. and Balamuta, J. J. (In Press) . + date_publication: '2022-02-24' + bug_reports: https://github.com/tmsalab/ohoegdm/issues + url: https://tmsalab.github.io/ohoegdm/ + url_cran: https://CRAN.R-project.org/package=ohoegdm + url_git: https://github.com/tmsalab/ohoegdm +OHPL: + version: 1.4.1 + title: Ordered Homogeneity Pursuit Lasso for Group Variable Selection + maintainer: Nan Xiao + description: |- + Ordered homogeneity pursuit lasso (OHPL) + algorithm for group variable selection proposed in Lin et al. (2017) + . The OHPL method exploits the + homogeneity structure in high-dimensional data and enjoys the + grouping effect to select groups of important variables + automatically. This feature makes it particularly useful for + high-dimensional datasets with strongly correlated variables, + such as spectroscopic data. + date_publication: '2024-07-20' + bug_reports: https://github.com/nanxstats/OHPL/issues + url: https://ohpl.io + url_cran: https://CRAN.R-project.org/package=OHPL + url_git: https://github.com/nanxstats/OHPL +ohsome: + version: 0.2.2 + title: An 'ohsome API' Client + maintainer: Oliver Fritz + description: |- + A client that grants access to the power of the 'ohsome API' + from R. It lets you analyze the rich data source of the + 'OpenStreetMap (OSM)' history. You can retrieve the geometry of 'OSM' + data at specific points in time, and you can get aggregated statistics + on the evolution of 'OSM' elements and specify your own temporal, + spatial and/or thematic filters. + date_publication: '2023-08-30' + bug_reports: https://github.com/GIScience/ohsome-r/issues + url: https://docs.ohsome.org/ohsome-api/stable/ + url_cran: https://CRAN.R-project.org/package=ohsome + url_git: https://github.com/GIScience/ohsome-r +ohtadstats: + version: 2.1.1 + title: Tomoka Ohta D Statistics + maintainer: Paul F. Petrowski + description: |- + Calculate's Tomoka Ohta's partitioning of linkage disequilibrium, + deemed D-statistics, for pairs of loci. Petrowski et al. (2019) . + date_publication: '2019-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ohtadstats + url_git: https://github.com/pfpetrowski/OhtaDStats +ohun: + version: 1.0.2 + title: Optimizing Acoustic Signal Detection + maintainer: Marcelo Araya-Salas + description: |- + Facilitates the automatic detection of acoustic signals, + providing functions to diagnose and optimize the performance of detection + routines. Detections from other software can also be explored and optimized. + This package has been peer-reviewed by rOpenSci. + Araya-Salas et al. (2022) . + date_publication: '2024-08-19' + bug_reports: https://github.com/ropensci/ohun/issues/ + url: https://docs.ropensci.org/ohun/ + url_cran: https://CRAN.R-project.org/package=ohun + url_git: https://github.com/ropensci/ohun/ +oii: + version: 1.0.2.1 + title: Crosstab and Statistical Tests for OII MSc Stats Course + maintainer: Scott Hale + description: Provides simple crosstab output with optional statistics (e.g., Goodman-Kruskal + Gamma, Somers' d, and Kendall's tau-b) as well as two-way and one-way tables. + The package is used within the statistics component of the Masters of Science + (MSc) in Social Science of the Internet at the Oxford Internet Institute (OII), + University of Oxford, but the functions should be useful for general data analysis + and especially for analysis of categorical and ordinal data. + date_publication: '2017-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oii + url_git: '' +ojsr: + version: 0.1.5 + title: Crawler and Data Scraper for Open Journal System ('OJS') + maintainer: Gaston Becerra + description: |- + Crawler for 'OJS' pages and scraper for meta-data from articles. + You can crawl 'OJS' archives, issues, articles, galleys, and search results. + You can scrape articles metadata from their head tag in html, + or from Open Archives Initiative ('OAI') records. + Most of these functions rely on 'OJS' routing conventions + (). + date_publication: '2024-11-13' + bug_reports: https://github.com/gastonbecerra/ojsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ojsr + url_git: https://github.com/gastonbecerra/ojsr +OkNNE: + version: 1.0.1 + title: |- + A k-Nearest Neighbours Ensemble via Optimal Model Selection for + Regression + maintainer: Amjad Ali + description: Optimal k Nearest Neighbours Ensemble is an ensemble of base k nearest + neighbour models each constructed on a bootstrap sample with a random subset of + features. k closest observations are identified for a test point "x" (say), in + each base k nearest neighbour model to fit a stepwise regression to predict the + output value of "x". The final predicted value of "x" is the mean of estimates + given by all the models. The implemented model takes training and test datasets + and trains the model on training data to predict the test data. Ali, A., Hamraz, + M., Kumam, P., Khan, D.M., Khalil, U., Sulaiman, M. and Khan, Z. (2020) . + date_publication: '2022-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OkNNE + url_git: '' +okxAPI: + version: 0.1.1 + title: An Unofficial Wrapper for 'okx exchange v5' API + maintainer: Yongchao Fang + description: An unofficial wrapper for 'okx exchange v5' API , + including 'REST' API and 'WebSocket' API. + date_publication: '2023-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=okxAPI + url_git: '' +OLCPM: + version: 0.1.2 + title: Online Change Point Detection for Matrix-Valued Time Series + maintainer: Long Yu + description: We provide two algorithms for monitoring change points with online + matrix-valued time series, under the assumption of a two-way factor structure. + The algorithms are based on different calculations of the second moment matrices. + One is based on stacking the columns of matrix observations, while another is + by a more delicate projected approach. A well-known fact is that, in the presence + of a change point, a factor model can be rewritten as a model with a larger number + of common factors. In turn, this entails that, in the presence of a change point, + the number of spiked eigenvalues in the second moment matrix of the data increases. + Based on this, we propose two families of procedures - one based on the fluctuations + of partial sums, and one based on extreme value theory - to monitor whether the + first non-spiked eigenvalue diverges after a point in time in the monitoring horizon, + thereby indicating the presence of a change point. This package also provides + some simple functions for detecting and removing outliers, imputing missing entries + and testing moments. See more details in He et al. (2021). + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OLCPM + url_git: '' +olctools: + version: 0.3.0 + title: Open Location Code Handling in R + maintainer: Oliver Keyes + description: |- + 'Open Location Codes' + are a Google-created standard for identifying geographic locations. 'olctools' provides + utilities for validating, encoding and decoding entries that follow this + standard. + date_publication: '2016-05-09' + bug_reports: https://github.com/ironholds/olctools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=olctools + url_git: https://github.com/Ironholds/olctools +oldr: + version: 0.2.3 + title: An Implementation of Rapid Assessment Method for Older People + maintainer: Ernest Guevarra + description: |- + An implementation of the Rapid Assessment Method for Older People + or RAM-OP . + It provides various functions that allow the user to design and plan the + assessment and analyse the collected data. RAM-OP provides accurate and + reliable estimates of the needs of older people. + date_publication: '2025-01-24' + bug_reports: https://github.com/rapidsurveys/oldr/issues + url: https://rapidsurveys.io/oldr/ + url_cran: https://CRAN.R-project.org/package=oldr + url_git: https://github.com/rapidsurveys/oldr +OlinkAnalyze: + version: 4.2.0 + title: Facilitate Analysis of Proteomic Data from Olink + maintainer: Kathleen Nevola + description: |- + A collection of functions to facilitate analysis of proteomic + data from Olink, primarily NPX data that has been exported from Olink + Software. The functions also work on QUANT data from + Olink by log- transforming the QUANT data. The functions are focused + on reading data, facilitating data wrangling and quality control + analysis, performing statistical analysis and generating figures to + visualize the results of the statistical analysis. The goal of this + package is to help users extract biological insights from proteomic + data run on the Olink platform. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OlinkAnalyze + url_git: https://olink.com/https://github.com/Olink-Proteomics/OlinkRPackage +ollamar: + version: 1.2.2 + title: '''Ollama'' Language Models' + maintainer: Hause Lin + description: |- + An interface to easily run local language models with 'Ollama' server + and API endpoints (see for details). It lets + you run open-source large language models locally on your machine. + date_publication: '2025-01-08' + bug_reports: https://github.com/hauselin/ollama-r/issues + url: https://hauselin.github.io/ollama-r/ + url_cran: https://CRAN.R-project.org/package=ollamar + url_git: https://github.com/hauselin/ollama-r +ollg: + version: 1.0.0 + title: Computes some Measures of OLL-G Family of Distributions + maintainer: Danial Mazarei + description: Computes the pdf, cdf, quantile function, hazard function and generating + random numbers for Odd log-logistic family (OLL-G). This family have been developed + by different authors in the recent years. See Alizadeh (2019) + for example. + date_publication: '2022-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ollg + url_git: https://github.com/dmazarei/ollg +ollggamma: + version: 1.0.2 + title: Odd Log-Logistic Generalized Gamma Probability Distribution + maintainer: Matheus H. J. Saldanha + description: Density, distribution function, quantile function and random generation + for the Odd Log-Logistic Generalized Gamma proposed in Prataviera, F. et al (2017) + . + date_publication: '2020-02-20' + bug_reports: https://github.com/matheushjs/ollggamma + url: https://mjsaldanha.com/posts/ollggamma + url_cran: https://CRAN.R-project.org/package=ollggamma + url_git: '' +olr: + version: '1.1' + title: Optimal Linear Regression + maintainer: Mathew Fok + description: |- + The optimal linear regression olr(), runs all the possible combinations of linear regression + equations. The olr() returns the equation which has the greatest adjusted R-squared term or the greatest R-squared term based + on the user's discretion. Essentially, the olr() returns the best fit equation out of all the possible equations. R-squared increases + with the addition of an explanatory variable whether it is 'significant' or not, thus this was developed to eliminate that conundrum. + Adjusted R-squared is preferred to overcome this phenomenon, but each combination will still produce different results and this will + return the best one. Complimentary functions are included which list all of the equations, all of the equations in ascending order, + a function to give the user a specific model's summary, and the list of adjusted R-squared terms & R-squared terms. + A 'Python' version is available at: . + date_publication: '2020-01-08' + bug_reports: '' + url: https://pypi.org/project/olr/ + url_cran: https://CRAN.R-project.org/package=olr + url_git: https://github.com/MatHatter +olsrr: + version: 0.6.1 + title: Tools for Building OLS Regression Models + maintainer: Aravind Hebbali + description: |- + Tools designed to make it easier for users, particularly beginner/intermediate R users + to build ordinary least squares regression models. Includes comprehensive regression output, + heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, + model fit assessment and variable selection procedures. + date_publication: '2024-11-06' + bug_reports: https://github.com/rsquaredacademy/olsrr/issues + url: https://olsrr.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=olsrr + url_git: https://github.com/rsquaredacademy/olsrr +OLStrajr: + version: 0.1.0 + title: Ordinary Least Squares Trajectory Analysis + maintainer: Mackson Ncube + description: |- + The 'OLStrajr' package provides comprehensive functions for ordinary + least squares (OLS) trajectory analysis and case-by-case OLS regression as + outlined in Carrig, Wirth, and Curran (2004) + and Rogosa and Saner (1995) . It encompasses two + primary functions, OLStraj() and cbc_lm(). The OLStraj() function simplifies + the estimation of individual growth curves over time via OLS regression, with + options for visualizing both group-level and individual-level growth trajectories + and support for linear and quadratic models. The cbc_lm() function facilitates + case-by-case OLS estimates and provides unbiased mean population intercept and + slope estimators by averaging OLS intercepts and slopes across cases. It further + offers standard error calculations across bootstrap replicates and computation + of 95% confidence intervals based on empirical distributions from the resampling + processes. + date_publication: '2023-06-19' + bug_reports: https://github.com/mightymetrika/OLStrajr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OLStrajr + url_git: https://github.com/mightymetrika/OLStrajr +OlympicRshiny: + version: 1.0.2 + title: '''Shiny'' Application for Olympic Data' + maintainer: Amalan Mahendran + description: |- + 'Shiny' Application to visualize Olympic Data. From 1896 to + 2016. Even Winter Olympics events are included. Data is from Kaggle at + . + date_publication: '2024-11-20' + bug_reports: https://github.com/Amalan-ConStat/OlympicRshiny/issues + url: https://amalan-con-stat.shinyapps.io/OlympicRshiny/ + url_cran: https://CRAN.R-project.org/package=OlympicRshiny + url_git: https://github.com/Amalan-ConStat/OlympicRshiny +OmegaG: + version: 1.0.1 + title: |- + Omega-Generic: Composite Reliability of Multidimensional + Measures + maintainer: Yujiao Mai + description: |2- + + It is a computer tool to estimate the item-sum score's reliability (composite reliability, CR) in multidimensional scales with overlapping items. An item that measures more than one domain construct is called an overlapping item. + The estimation is based on factor models allowing unlimited cross-factor loadings such as exploratory structural equation modeling (ESEM) and Bayesian structural equation modeling (BSEM). The factor models include correlated-factor models and bi-factor models. Specifically for bi-factor models, a type of hierarchical factor model, the package estimates the CR hierarchical subscale/hierarchy and CR subscale/scale total. The CR estimator 'Omega-generic' was proposed by Mai, Srivastava, and Krull (2021) . The current version can only handle continuous data. + Yujiao Mai contributes to the algorithms, R programming, and application example. Deo Kumar Srivastava contributes to the algorithms and the application example. Kevin R. Krull contributes to the application example. The package 'OmegaG' was sponsored by American Lebanese Syrian Associated Charities (ALSAC). However, the contents of 'OmegaG' do not necessarily represent the policy of the ALSAC. + date_publication: '2021-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OmegaG + url_git: '' +OmicKriging: + version: 1.4.0 + title: Poly-Omic Prediction of Complex TRaits + maintainer: Hae Kyung Im + description: |- + It provides functions to generate a correlation matrix + from a genetic dataset and to use this matrix to predict the phenotype of an + individual by using the phenotypes of the remaining individuals through + kriging. Kriging is a geostatistical method for optimal prediction or best + unbiased linear prediction. It consists of predicting the value of a + variable at an unobserved location as a weighted sum of the variable at + observed locations. Intuitively, it works as a reverse linear regression: + instead of computing correlation (univariate regression coefficients are + simply scaled correlation) between a dependent variable Y and independent + variables X, it uses known correlation between X and Y to predict Y. + date_publication: '2016-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OmicKriging + url_git: '' +OmicNavigator: + version: 1.13.13 + title: Open-Source Software for 'Omic' Data Analysis and Visualization + maintainer: John Blischak + description: |2- + + A tool for interactive exploration of the results from 'omics' + experiments to facilitate novel discoveries from high-throughput biology. The + software includes R functions for the 'bioinformatician' to deposit study + metadata and the outputs from statistical analyses (e.g. differential + expression, enrichment). These results are then exported to an interactive + JavaScript dashboard that can be interrogated on the user's local machine or + deployed online to be explored by collaborators. The dashboard includes + 'sortable' tables, interactive plots including network visualization, and + fine-grained filtering based on statistical significance. + date_publication: '2023-08-25' + bug_reports: https://github.com/abbvie-external/OmicNavigator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OmicNavigator + url_git: https://github.com/abbvie-external/OmicNavigator +omics: + version: 0.1-5 + title: '''--omics'' Data Analysis Toolbox' + maintainer: Gianluca Campanella + description: |- + A collection of functions to analyse '--omics' datasets such as DNA + methylation and gene expression profiles. + date_publication: '2016-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=omics + url_git: '' +OmicSense: + version: 0.2.0 + title: Biosensor Development using Omics Data + maintainer: Takahiko Koizumi + description: |- + A method for the quantitative prediction using omics data. + This package provides functions to construct the quantitative prediction + model using omics data. + date_publication: '2023-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OmicSense + url_git: +OmicsPLS: + version: 2.0.2 + title: Data Integration with Two-Way Orthogonal Partial Least Squares + maintainer: Said el Bouhaddani + description: |- + Performs the O2PLS data integration method for two datasets, yielding joint and data-specific parts for each dataset. + The algorithm automatically switches to a memory-efficient approach to fit O2PLS to high dimensional data. + It provides a rigorous and a faster alternative cross-validation method to select the number of components, + as well as functions to report proportions of explained variation and to construct plots of the results. + See the software article by el Bouhaddani et al (2018) , + and Trygg and Wold (2003) . + It also performs Sparse Group (Penalized) O2PLS, see Gu et al (2020) and cross-validation for the degree of sparsity. + date_publication: '2021-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OmicsPLS + url_git: '' +OmicsQC: + version: 1.1.0 + title: Nominating Quality Control Outliers in Genomic Profiling Studies + maintainer: Paul C. Boutros + description: A method that analyzes quality control metrics from multi-sample genomic + sequencing studies and nominates poor quality samples for exclusion. Per sample + quality control data are transformed into z-scores and aggregated. The distribution + of aggregated z-scores are modelled using parametric distributions. The parameters + of the optimal model, selected either by goodness-of-fit statistics or user-designation, + are used for outlier nomination. Two implementations of the Cosine Similarity + Outlier Detection algorithm are provided with flexible parameters for dataset + customization. + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OmicsQC + url_git: '' +omicsTools: + version: 1.0.5 + title: Omics Data Process Toolbox + maintainer: Yaoxiang Li + description: Processing and analyzing omics data from genomics, transcriptomics, + proteomics, and metabolomics platforms. It provides functions for preprocessing, + normalization, visualization, and statistical analysis, as well as machine learning + algorithms for predictive modeling. 'omicsTools' is an essential tool for researchers + working with high-throughput omics data in fields such as biology, bioinformatics, + and medicine.The QC-RLSC (quality control–based robust LOESS signal correction) + algorithm is used for normalization. Dunn et al. (2011) . + date_publication: '2023-07-03' + bug_reports: https://github.com/YaoxiangLi/omicsTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=omicsTools + url_git: https://github.com/YaoxiangLi/omicsTools +omicwas: + version: 0.8.0 + title: Cell-Type-Specific Association Testing in Bulk Omics Experiments + maintainer: Fumihiko Takeuchi + description: |- + In bulk epigenome/transcriptome experiments, molecular expression + is measured in a tissue, which is a mixture of multiple types of cells. + This package tests association of a disease/phenotype with a molecular marker + for each cell type. + The proportion of cell types in each sample needs to be given as input. + The package is applicable to epigenome-wide association study (EWAS) and + differential gene expression analysis. + Takeuchi and Kato (submitted) + "omicwas: cell-type-specific epigenome-wide and transcriptome association study". + date_publication: '2020-10-08' + bug_reports: https://github.com/fumi-github/omicwas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=omicwas + url_git: https://github.com/fumi-github/omicwas +Omisc: + version: 0.1.5 + title: Univariate Bootstrapping and Other Things + maintainer: Patrick O'Keefe + description: 'Primarily devoted to implementing the Univariate Bootstrap (as well + as the Traditional Bootstrap). In addition there are multiple functions for DeFries-Fulker + behavioral genetics models. The univariate bootstrapping functions, DeFries-Fulker + functions, regression and traditional bootstrapping functions form the original + core. Additional features may come online later, however this software is a work + in progress. For more information about univariate bootstrapping see: Lee and + Rodgers (1998) and Beasley et al (2007) .' + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Omisc + url_git: '' +omnibus: + version: 1.2.14 + title: Helper Tools for Managing Data, Dates, Missing Values, and Text + maintainer: Adam B. Smith + description: |- + An assortment of helper functions for managing data (e.g., + rotating values in matrices by a user-defined angle, switching from + row- to column-indexing), dates (e.g., intuiting year from messy date + strings), handling missing values (e.g., removing elements/rows across + multiple vectors or matrices if any have an NA), text (e.g., + flushing reports to the console in real-time); and combining data frames + with different schema (copying, filling, or concatenating columns or + applying functions before combining). + date_publication: '2024-09-17' + bug_reports: https://github.com/adamlilith/omnibus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=omnibus + url_git: https://github.com/adamlilith/omnibus +OmnibusFisher: + version: '1.0' + title: A Modified Fisher’s Method to Test Overall Gene-Level Effect + maintainer: Qi Yan + description: |- + The separate p-values of SNPs, RNA expressions and DNA + methylations are calculated by KM regression. The correlation between + different omics data are taken into account. This method can be applied to + either samples with all three types of omics data or samples with two types. + date_publication: '2018-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OmnibusFisher + url_git: '' +omock: + version: 0.3.2 + title: |- + Creation of Mock Observational Medical Outcomes Partnership + Common Data Model + maintainer: Mike Du + description: |- + Creates mock data for testing and package development for the + Observational Medical Outcomes Partnership common data model. The + package offers functions crafted with pipeline-friendly + implementation, enabling users to effortlessly include only the + necessary tables for their testing needs. + date_publication: '2025-01-23' + bug_reports: https://github.com/ohdsi/omock/issues + url: https://ohdsi.github.io/omock/ + url_cran: https://CRAN.R-project.org/package=omock + url_git: https://github.com/ohdsi/omock +omopgenerics: + version: 1.1.0 + title: Methods and Classes for the OMOP Common Data Model + maintainer: Martí Català + description: |- + Provides definitions of core classes and methods used by analytic + pipelines that query the OMOP (Observational Medical Outcomes Partnership) + common data model. + date_publication: '2025-02-25' + bug_reports: https://github.com/darwin-eu/omopgenerics/issues + url: https://darwin-eu.github.io/omopgenerics/ + url_cran: https://CRAN.R-project.org/package=omopgenerics + url_git: '' +OmopSketch: + version: 0.2.2 + title: Characterise Tables of an OMOP Common Data Model Instance + maintainer: Cecilia Campanile + description: |- + Summarises key information in data mapped to the Observational + Medical Outcomes Partnership (OMOP) common data model. Assess suitability to + perform specific epidemiological studies and explore the different domains + to obtain feasibility counts and trends. + date_publication: '2025-01-28' + bug_reports: https://github.com/OHDSI/OmopSketch/issues + url: https://OHDSI.github.io/OmopSketch/ + url_cran: https://CRAN.R-project.org/package=OmopSketch + url_git: '' +OmopViewer: + version: 0.2.0 + title: Visualise OMOP Results using 'shiny' Applications + maintainer: Martí Català + description: |- + Visualise results obtained from analysing data mapped to the + Observational Medical Outcomes Partnership (OMOP) common data model using + 'shiny' applications. + date_publication: '2024-11-27' + bug_reports: '' + url: https://ohdsi.github.io/OmopViewer/ + url_cran: https://CRAN.R-project.org/package=OmopViewer + url_git: '' +ompr: + version: 1.0.4 + title: Model and Solve Mixed Integer Linear Programs + maintainer: Dirk Schumacher + description: |- + Model mixed integer linear programs in an algebraic way directly in R. + The model is solver-independent and thus offers the possibility + to solve a model with different solvers. It currently only supports + linear constraints and objective functions. See the 'ompr' + website for more information, + documentation and examples. + date_publication: '2023-09-09' + bug_reports: https://github.com/dirkschumacher/ompr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ompr + url_git: https://github.com/dirkschumacher/ompr +ompr.roi: + version: 1.0.2 + title: |- + A Solver for 'ompr' that Uses the R Optimization Infrastructure + ('ROI') + maintainer: Dirk Schumacher + description: |- + A solver for 'ompr' based on the R Optimization Infrastructure ('ROI'). + The package makes all solvers in 'ROI' available to solve 'ompr' models. Please see the + 'ompr' website and package docs for more information + and examples on how to use it. + date_publication: '2023-09-09' + bug_reports: https://github.com/dirkschumacher/ompr.roi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ompr.roi + url_git: https://github.com/dirkschumacher/ompr.roi +omsvg: + version: 0.1.0 + title: Build and Transform 'SVG' Objects + maintainer: Richard Iannone + description: |- + Build 'SVG' components using element-based functions. With + an 'svg' object, we can modify its graphical elements with a suite of + transform functions. + date_publication: '2021-02-10' + bug_reports: https://github.com/rich-iannone/omsvg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=omsvg + url_git: https://github.com/rich-iannone/omsvg +omu: + version: 1.1.2 + title: |- + A Metabolomics Analysis Tool for Intuitive Figures and + Convenient Metadata Collection + maintainer: Connor Tiffany + description: Facilitates the creation of intuitive figures to describe metabolomics + data by utilizing Kyoto Encyclopedia of Genes and Genomes (KEGG) hierarchy data, + and gathers functional orthology and gene data from the KEGG-REST API. + date_publication: '2024-03-06' + bug_reports: https://github.com/connor-reid-tiffany/Omu/issues + url: https://www.kegg.jp/kegg/rest/keggapi.html + url_cran: https://CRAN.R-project.org/package=omu + url_git: https://github.com/connor-reid-tiffany/Omu +onadata: + version: '0.1' + title: |- + Data Sets for Keith McNulty's Handbook of Graphs and Networks in + People Analytics + maintainer: Keith McNulty + description: |- + Data sets for network analysis related to People Analytics. + Contains various data sets from the book 'Handbook of Graphs and Networks in People Analytics' + by Keith McNulty (2021). + date_publication: '2022-01-24' + bug_reports: '' + url: https://ona-book.org + url_cran: https://CRAN.R-project.org/package=onadata + url_git: '' +OnAge: + version: 1.0.1 + title: Test of Between-Group Differences in the Onset of Senescence + maintainer: Aurélie Siberchicot + description: |- + Implementation of a likelihood ratio test of differential + onset of senescence between two groups. Given two groups with + measures of age and of an individual trait likely to be subjected to + senescence (e.g. body mass), 'OnAge' provides an asymptotic p-value + for the null hypothesis that senescence starts at the same age in + both groups. The package implements the procedure used in + Douhard et al. (2017) . + date_publication: '2017-10-20' + bug_reports: '' + url: https://lbbe.univ-lyon1.fr/OnAge.html + url_cran: https://CRAN.R-project.org/package=OnAge + url_git: '' +onbabynames: + version: 0.0.1 + title: Names Given to Babies in Ontario Between 1917 and 2018 + maintainer: Marc-Andre Desautels + description: |- + A database containing the names + of the babies born in Ontario between 1917 and 2018. + Counts of fewer than 5 names were suppressed for privacy. + date_publication: '2021-05-03' + bug_reports: https://github.com/desautm/onbabynames/issues + url: '' + url_cran: https://CRAN.R-project.org/package=onbabynames + url_git: +OnboardClient: + version: 1.0.0 + title: Bindings for Onboard Data's Building Data API + maintainer: Christopher Dudas-Thomas + description: Provides a wrapper for the Onboard Data building data API . + Along with streamlining access to the API, this package simplifies access to sensor + time series data, metadata (sensors, equipment, and buildings), and details about + the Onboard data model/ontology. + date_publication: '2022-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OnboardClient + url_git: '' +onbrand: + version: 1.0.6 + title: Templated Reporting Workflows in Word and PowerPoint + maintainer: John Harrold + description: Automated reporting in Word and PowerPoint can require customization + for each organizational template. This package works around this by adding standard + reporting functions and an abstraction layer to facilitate automated reporting + workflows that can be replicated across different organizational templates. + date_publication: '2024-09-23' + bug_reports: https://github.com/john-harrold/onbrand/issues + url: https://onbrand.ubiquity.tools/ + url_cran: https://CRAN.R-project.org/package=onbrand + url_git: '' +onc.api: + version: 2.0.1.0 + title: Oceans 2.0 API Client Library + maintainer: Bennit Mueller + description: Allows users to discover and retrieve Ocean Networks Canada's oceanographic + data in raw, text, image, audio, video or any other format available. Provides + a class that wraps web service calls and business logic so that users can download + data with a single line of code. + date_publication: '2021-08-21' + bug_reports: '' + url: https://wiki.oceannetworks.ca/display/O2A/Oceans+2.0+API+Home + url_cran: https://CRAN.R-project.org/package=onc.api + url_git: '' +once: + version: 0.4.1 + title: Execute Expensive Operations Only Once + maintainer: Gordon McDonald + description: Allows you to easily execute expensive compute operations only once, + and save the resulting object to disk. + date_publication: '2022-08-31' + bug_reports: '' + url: https://gdmcdonald.github.io/once/ + url_cran: https://CRAN.R-project.org/package=once + url_git: '' +oncmap: + version: 0.1.5 + title: Analyze Data from Electronic Adherence Monitoring Devices + maintainer: Michal Kouril + description: |- + Medication adherence, defined as medication-taking behavior that aligns with the agreed-upon + treatment protocol, is critical for realizing the benefits of prescription medications. + Medication adherence can be assessed using electronic adherence monitoring devices (EAMDs), + pill bottles or boxes that contain a computer chip that records the date and time of each + opening (or “actuation”). Before researchers can use EAMD data, they must apply a series of + decision rules to transform actuation data into adherence data. + The purpose of this R package ('oncmap') is to transform EAMD actuations in the form of a raw .csv file, + information about the patient, regimen, and non-monitored periods into two daily adherence values -- + Dose Taken and Correct Dose Taken. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oncmap + url_git: '' +OncoBayes2: + version: 0.8-9 + title: Bayesian Logistic Regression for Oncology Dose-Escalation Trials + maintainer: Sebastian Weber + description: |- + Bayesian logistic regression model with optional + EXchangeability-NonEXchangeability parameter modelling for flexible + borrowing from historical or concurrent data-sources. The safety model + can guide dose-escalation decisions for adaptive oncology Phase I + dose-escalation trials which involve an arbitrary number of + drugs. Please refer to Neuenschwander et al. (2008) + and Neuenschwander et al. (2016) + for details on the methodology. + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OncoBayes2 + url_git: '' +OncoDataSets: + version: 0.1.0 + title: |- + A Comprehensive Collection of Cancer Types and Cancer-Related + Datasets + maintainer: Renzo Caceres Rossi + description: |- + Offers a rich collection of data focused on cancer research, covering survival rates, genetic studies, biomarkers, and epidemiological insights. + Designed for researchers, analysts, and bioinformatics practitioners, the package includes datasets on various cancer types such as melanoma, leukemia, breast, ovarian, and lung cancer, among others. + It aims to facilitate advanced research, analysis, and understanding of cancer epidemiology, genetics, and treatment outcomes. + date_publication: '2024-12-10' + bug_reports: https://github.com/lightbluetitan/oncodatasets/issues + url: https://lightbluetitan.github.io/oncodatasets/ + url_cran: https://CRAN.R-project.org/package=OncoDataSets + url_git: https://github.com/lightbluetitan/oncodatasets +Oncofilterfast: + version: 1.0.0 + title: Aids in the Analysis of Genes Influencing Cancer Survival + maintainer: Pheonix Chen + description: Aids in the analysis of genes influencing cancer survival by including + a principal function, calculator(), which calculates the P-value for each provided + gene under the optimal cutoff in cancer survival studies. Grounded in methodologies + from significant works, this package references Therneau's 'survival' package + (Therneau, 2024; ) and the survival + analysis extensions by Therneau and Grambsch (2000, ISBN 0-387-98784-3). It also + integrates the 'survminer' package by Kassambara et al. (2021; ), + enhancing survival curve visualizations with 'ggplot2'. + date_publication: '2024-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Oncofilterfast + url_git: '' +oncomsm: + version: 0.1.4 + title: Bayesian Multi-State Models for Early Oncology + maintainer: Kevin Kunzmann + description: |- + Implements methods to fit a parametric Bayesian multi-state model + to tumor response data. + The model can be used to sample from the predictive distribution to impute + missing data and calculate probability of success for custom decision + criteria in early clinical trials during an ongoing trial. + The inference is implemented using 'stan'. + date_publication: '2023-04-17' + bug_reports: https://github.com/Boehringer-Ingelheim/oncomsm/issues + url: https://boehringer-ingelheim.github.io/oncomsm/ + url_cran: https://CRAN.R-project.org/package=oncomsm + url_git: https://github.com/Boehringer-Ingelheim/oncomsm +oncoPredict: + version: '1.2' + title: Drug Response Modeling and Biomarker Discovery + maintainer: Robert Gruener + description: |- + Allows for building drug response models using screening data between bulk RNA-Seq and a drug response metric and two additional tools for biomarker discovery that have been developed by the Huang Laboratory at University of Minnesota. + There are 3 main functions within this package. + (1) calcPhenotype is used to build drug response models on RNA-Seq data and impute them on any other RNA-Seq dataset given to the model. + (2) GLDS is used to calculate the general level of drug sensitivity, which can improve biomarker discovery. + (3) IDWAS can take the results from calcPhenotype and link the imputed response back to available genomic (mutation and CNV alterations) to identify biomarkers. + Each of these functions comes from a paper from the Huang research laboratory. Below gives the relevant paper for each function. + calcPhenotype - Geeleher et al, Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. + GLDS - Geeleher et al, Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models. + IDWAS - Geeleher et al, Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies. + date_publication: '2024-04-05' + bug_reports: https://github.com/HuangLabUMN/oncoPredict/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oncoPredict + url_git: https://github.com/HuangLabUMN/oncoPredict +OncoSubtype: + version: 1.0.0 + title: |- + Predict Cancer Subtypes Based on TCGA Data using Machine + Learning Method + maintainer: Dadong Zhang + description: Provide functionality for cancer subtyping using nearest centroids + or machine learning methods based on TCGA data. + date_publication: '2024-03-22' + bug_reports: https://github.com/DadongZ/OncoSubtype/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OncoSubtype + url_git: https://github.com/DadongZ/OncoSubtype +Oncotree: + version: 0.3.5 + title: Estimating Oncogenetic Trees + maintainer: Aniko Szabo + description: |- + Construct and evaluate directed tree structures that + model the process of occurrence of genetic alterations during carcinogenesis + as described in Szabo, A. and Boucher, K (2002) . + date_publication: '2023-09-27' + bug_reports: https://github.com/anikoszabo/Oncotree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Oncotree + url_git: https://github.com/anikoszabo/Oncotree +oncrawlR: + version: 0.2.0 + title: Machine Learning for S.E.O + maintainer: Vincent Terrasi + description: |- + Measures different aspects of page content, structure and performance for SEO (Search Engine Optimization). + Aspects covered include HTML tags used in SEO, duplicate and near-duplicate content, structured data, on-site linking structure and popularity transfer, and many other amazing things. + This package can be used to generate a real, full SEO audit report, which serves to detect errors or inefficiencies on a page that can be corrected in order to optimise its performance on search engines. + date_publication: '2020-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oncrawlR + url_git: '' +One4All: + version: '0.5' + title: Validate, Share, and Download Data + maintainer: Hannah Sherrod + description: Designed to enhance data validation and management processes by employing + a set of functions that read a set of rules from a 'CSV' or 'Excel' file and apply + them to a dataset. Funded by the National Renewable Energy Laboratory and Possibility + Lab, maintained by the Moore Institute for Plastic Pollution Research. + date_publication: '2024-07-02' + bug_reports: https://github.com/Moore-Institute-4-Plastic-Pollution-Res/One4All/issues + url: https://moore-institute-4-plastic-pollution-res.github.io/One4All/ + url_cran: https://CRAN.R-project.org/package=One4All + url_git: https://github.com/Moore-Institute-4-Plastic-Pollution-Res/One4All +OneArm2stage: + version: 1.2.1 + title: |- + Phase II Single-Arm Two-Stage Designs with Time-to-Event + Outcomes + maintainer: Xiaomeng Yuan + description: |- + Two-stage design for single-arm phase II + trials with time-to-event endpoints (e.g., clinical trials on + immunotherapies among cancer patients) can be calculated using this package. + Two notable advantages of the package: 1) It provides flexible choices from + three design methods (optimal, minmax, and admissible), and 2) the power of + the design is more accurately calculated using the exact variance in the + one-sample log-rank test. The package can be used for 1) planning the sample + sizes and other design parameters, and 2) conducting the interim and final + analyses for the Go/No-go decisions. More details about the design method + can be found in: Wu, J, Chen L, Wei J, Weiss H, Chauhan A. (2020). + . + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OneArm2stage + url_git: '' +OneArmTTE: + version: '1.0' + title: One-Arm Clinical Trial Designs for Time-to-Event Endpoint + maintainer: Heng Zhou + description: Get operating characteristics of one-arm clinical trial designs for + time-to-event endpoint through simulation and perform analysis with time-to-event + data. + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OneArmTTE + url_git: '' +oneclust: + version: 0.3.0 + title: Maximum Homogeneity Clustering for Univariate Data + maintainer: Nan Xiao + description: |- + Maximum homogeneity clustering algorithm for one-dimensional data + described in W. D. Fisher (1958) + via dynamic programming. + date_publication: '2024-03-11' + bug_reports: https://github.com/nanxstats/oneclust/issues + url: https://nanx.me/oneclust/ + url_cran: https://CRAN.R-project.org/package=oneclust + url_git: https://github.com/nanxstats/oneclust +onehot: + version: 0.1.1 + title: Fast Onehot Encoding for Data.frames + maintainer: Eric E. Graves + description: |- + Quickly create numeric matrices for machine learning algorithms + that require them. It converts factor columns into onehot vectors. + date_publication: '2017-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onehot + url_git: '' +oneinfl: + version: 1.0.1 + title: Estimates OIPP and OIZTNB Regression Models + maintainer: Ryan T. Godwin + description: |- + Estimates one-inflated positive Poisson (OIPP) and + one-inflated zero-truncated negative binomial (OIZTNB) regression + models. A suite of ancillary statistical tools are also provided, + including: estimation of positive Poisson (PP) and zero-truncated + negative binomial (ZTNB) models; marginal effects and their standard + errors; diagnostic likelihood ratio and Wald tests; plotting; + predicted counts and expected responses; and random variate + generation. The models and tools, as well as four applications, are + shown in Godwin, R. T. (2024). "One-inflated zero-truncated count + regression models" arXiv preprint . + date_publication: '2025-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oneinfl + url_git: '' +onelogin: + version: 0.2.0 + title: Interact with the 'OneLogin' API + maintainer: Alex Gold + description: |- + The identity provider ['OneLogin'] is used for + authentication via Single Sign On (SSO). This package provides an R interface to their API. + date_publication: '2019-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onelogin + url_git: '' +OneR: + version: '2.2' + title: |- + One Rule Machine Learning Classification Algorithm with + Enhancements + maintainer: Holger von Jouanne-Diedrich + description: Implements the One Rule (OneR) Machine Learning classification algorithm + (Holte, R.C. (1993) ) with enhancements for sophisticated + handling of numeric data and missing values together with extensive diagnostic + functions. It is useful as a baseline for machine learning models and the rules + are often helpful heuristics. + date_publication: '2017-05-05' + bug_reports: https://github.com/vonjd/OneR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OneR + url_git: https://github.com/vonjd/OneR +OneSampleLogRankTest: + version: 0.9.2 + title: One-Sample Log-Rank Test + maintainer: Divy Kangeyan + description: |- + The log-rank test is performed to assess the survival outcomes between two group. + When there is no proper control group or obtaining such data is cumbersome, one sample + log-rank test can be applied. This package performs one sample log-rank test as described in Finkelstein et al. (2003) and variation of the + test for small sample sizes which is detailed in FD Liddell (1984) paper. Visualization function in the package + generates Kaplan-Meier Curve comparing survival curve of the general population against that of the population of interest. + date_publication: '2024-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OneSampleLogRankTest + url_git: '' +OneSampleMR: + version: 0.1.5 + title: |- + One Sample Mendelian Randomization and Instrumental Variable + Analyses + maintainer: Tom Palmer + description: |- + Useful functions for one-sample (individual level data) + Mendelian randomization and instrumental variable analyses. The + package includes implementations of; the Sanderson and Windmeijer + (2016) conditional F-statistic, + the multiplicative structural mean model Hernán and Robins (2006) + , and two-stage predictor + substitution and two-stage residual inclusion estimators explained by + Terza et al. (2008) . + date_publication: '2024-06-26' + bug_reports: https://github.com/remlapmot/OneSampleMR/issues/ + url: https://remlapmot.github.io/OneSampleMR/ + url_cran: https://CRAN.R-project.org/package=OneSampleMR + url_git: https://github.com/remlapmot/OneSampleMR +ONEST: + version: 0.1.0 + title: Observers Needed to Evaluate Subjective Tests + maintainer: Gang Han + description: |2- + + This ONEST software implements the method of assessing the pathologist agreement in reading PD-L1 assays (Reisenbichler et al. (2020 )), to determine the minimum number of evaluators needed to estimate agreement involving a large number of raters. Input to the program should be binary(1/0) pathology data, where “0” may stand for negative and “1” for positive. Additional examples were given using the data from Rimm et al. (2017 ). + date_publication: '2021-07-26' + bug_reports: https://github.com/hangangtrue/ONEST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ONEST + url_git: https://github.com/hangangtrue/ONEST +OneStep: + version: 0.9.4 + title: One-Step Estimation + maintainer: Christophe Dutang + description: |- + Provide principally an eponymic function that numerically computes + the Le Cam's one-step estimator for an independent and identically distributed sample. + One-step estimation is asymptotically + efficient (see L. Le Cam (1956) ) + and can be computed faster than the maximum likelihood estimator for large observation + samples, see e.g. Brouste et al. (2021) . + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OneStep + url_git: '' +onetime: + version: 0.2.0 + title: Run Code Only Once + maintainer: David Hugh-Jones + description: |- + Allows code to be run only once on a given computer, using + lockfiles. Typical use cases include startup messages shown only when a + package is loaded for the very first time. + date_publication: '2023-09-03' + bug_reports: https://github.com/hughjonesd/onetime/issues + url: https://hughjonesd.github.io/onetime/ + url_cran: https://CRAN.R-project.org/package=onetime + url_git: https://github.com/hughjonesd/onetime +OneTwoSamples: + version: 1.1-0 + title: Deal with One and Two (Normal) Samples + maintainer: Frederic Bertrand + description: |- + We introduce an R function + one_two_sample() which can deal with one and two (normal) + samples, Ying-Ying Zhang, Yi Wei (2012) . + For one normal sample x, the function reports + descriptive statistics, plot, interval estimation and test of + hypothesis of x. For two normal samples x and y, the function + reports descriptive statistics, plot, interval estimation and + test of hypothesis of x and y, respectively. It also reports + interval estimation and test of hypothesis of mu1-mu2 (the + difference of the means of x and y) and sigma1^2 / sigma2^2 + (the ratio of the variances of x and y), tests whether x and y + are from the same population, finds the correlation coefficient + of x and y if x and y have the same length. + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OneTwoSamples + url_git: '' +onewaytests: + version: '3.0' + title: One-Way Tests in Independent Groups Designs + maintainer: Osman Dag + description: Performs one-way tests in independent groups designs including homoscedastic + and heteroscedastic tests. These are one-way analysis of variance (ANOVA), Welch's + heteroscedastic F test, Welch's heteroscedastic F test with trimmed means and + Winsorized variances, Brown-Forsythe test, Alexander-Govern test, James second + order test, Kruskal-Wallis test, Scott-Smith test, Box F test, Johansen F test, + Generalized tests equivalent to Parametric Bootstrap and Fiducial tests, Alvandi's + F test, Alvandi's generalized p-value, approximate F test, B square test, Cochran + test, Weerahandi's generalized F test, modified Brown-Forsythe test, adjusted + Welch's heteroscedastic F test, Welch-Aspin test, Permutation F test. The package + performs pairwise comparisons and graphical approaches. Also, the package includes + Student's t test, Welch's t test and Mann-Whitney U test for two samples. Moreover, + it assesses variance homogeneity and normality of data in each group via tests + and plots (Dag et al., 2018, ). + date_publication: '2023-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onewaytests + url_git: '' +onion: + version: 1.5-3 + title: Octonions and Quaternions + maintainer: Robin K. S. Hankin + description: |2- + + Quaternions and Octonions are four- and eight- dimensional + extensions of the complex numbers. They are normed division + algebras over the real numbers and find applications in spatial + rotations (quaternions), and string theory and relativity + (octonions). The quaternions are noncommutative and the octonions + nonassociative. See the package vignette for more details. + date_publication: '2024-03-29' + bug_reports: https://github.com/RobinHankin/onion/issues + url: '' + url_cran: https://CRAN.R-project.org/package=onion + url_git: https://github.com/RobinHankin/onion +onlineBcp: + version: 0.1.8 + title: Online Bayesian Methods for Change Point Analysis + maintainer: Hongyan Xu + description: |- + It implements the online Bayesian methods for change point analysis. It can + also perform missing data imputation with methods from 'VIM'. The reference + is Yigiter A, Chen J, An L, Danacioglu N (2015) . + The link to the package is . + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onlineBcp + url_git: '' +onlineCOV: + version: '1.3' + title: |- + Online Change Point Detection in High-Dimensional Covariance + Structure + maintainer: Jun Li + description: Implement a new stopping rule to detect anomaly in the covariance structure + of high-dimensional online data. The detection procedure can be applied to Gaussian + or non-Gaussian data with a large number of components. Moreover, it allows both + spatial and temporal dependence in data. The dependence can be estimated by a + data-driven procedure. The level of threshold in the stopping rule can be determined + at a pre-selected average run length. More detail can be seen in Li, L. and Li, + J. (2020) "Online Change-Point Detection in High-Dimensional Covariance Structure + with Application to Dynamic Networks." . + date_publication: '2020-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onlineCOV + url_git: '' +onlineforecast: + version: 1.0.2 + title: Forecast Modelling for Online Applications + maintainer: Peder Bacher + description: 'A framework for fitting adaptive forecasting models. Provides a way + to use forecasts as input to models, e.g. weather forecasts for energy related + forecasting. The models can be fitted recursively and can easily be setup for + updating parameters when new data arrives. See the included vignettes, the website + and the paper "onlineforecast: An R package for + adaptive and recursive forecasting" .' + date_publication: '2023-10-12' + bug_reports: https://lab.compute.dtu.dk/packages/onlineforecast/-/issues + url: https://onlineforecasting.org + url_cran: https://CRAN.R-project.org/package=onlineforecast + url_git: '' +onlinePCA: + version: 1.3.2 + title: Online Principal Component Analysis + maintainer: David Degras + description: Online PCA for multivariate and functional data using perturbation + methods, low-rank incremental methods, and stochastic optimization methods. + date_publication: '2023-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onlinePCA + url_git: '' +onlineretail: + version: 0.1.2 + title: Online Retail Dataset + maintainer: Allan Quadros + description: |- + Transactions occurring for a UK-based and registered, non-store online + retail between 01/12/2010 and 09/12/2011 (Chen et. al., 2012, ). + This dataset is included in this package with the donor's permission, Dr. Daqing Chen. + date_publication: '2021-05-15' + bug_reports: https://github.com/allanvc/onlineretail/issues/ + url: https://doi.org/10.1057/dbm.2012.17 + url_cran: https://CRAN.R-project.org/package=onlineretail + url_git: https://github.com/allanvc/onlineretail/ +onls: + version: 0.1-2 + title: Orthogonal Nonlinear Least-Squares Regression + maintainer: Andrej-Nikolai Spiess + description: Fits two-dimensional data by means of orthogonal nonlinear least-squares + using Levenberg-Marquardt minimization and provides functionality for fit diagnostics + and plotting. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onls + url_git: '' +onmaRg: + version: 1.0.3 + title: Import Public Health Ontario's Ontario Marginalization Index + maintainer: William Conley + description: |- + The Ontario Marginalization Index is a socioeconomic model that is built on Statistics Canada census data. + The model consists of four dimensions: In 2021, these dimensions were updated to "Material Resources" (previously called "Material Deprivation"), "Households and Dwellings" (previously called "Residential Instability"), "Age and Labour Force" (previously called "Dependency"), and "Racialized and Newcomer Populations" (previously called "Ethnic Concentration"). + This update reflects a movement away from deficit-based language. 2021 data will load with these new dimension names, wheras 2011 and 2016 data will load with the historical dimension names. + Each of these dimensions are imported for a variety of geographic levels (DA, CD, etc.) for the 2021, 2011 and 2016 administrations of the census. + These data sets contribute to community analysis of equity with respect to Ontario's Anti-Racism Act. + The Ontario Marginalization Index data is retrieved from the Public Health Ontario website: . + The shapefile data is retrieved from the Statistics Canada website: . + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=onmaRg + url_git: '' +onnx: + version: 0.0.3 + title: R Interface to 'ONNX' + maintainer: Yuan Tang + description: |- + R Interface to 'ONNX' - Open Neural Network Exchange . + 'ONNX' provides an open source format for machine learning models. + It defines an extensible computation graph model, as well as definitions + of built-in operators and standard data types. + date_publication: '2021-04-16' + bug_reports: https://github.com/onnx/onnx-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=onnx + url_git: https://github.com/onnx/onnx-r +OnomasticDiversity: + version: '0.1' + title: Onomastic Diversity Measures + maintainer: Maria Jose Ginzo Villamayor + description: Different measures which can be used to quantify similarities between + regions. These measures are isonymy, isonymy between, Lasker distance, coefficients + of Hedrick and Nei. In addition, it calculates biodiversity indices such as Margalef, + Menhinick, Simpson, Shannon, Shannon-Wiener, Sheldon, Heip, Hill Numbers, Geometric + Mean and Cressie and Read statistics. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OnomasticDiversity + url_git: '' +onpoint: + version: '1.1' + title: Helper Functions for Point Pattern Analysis + maintainer: Maximilian H.K. Hesselbarth + description: |- + Growing collection of helper functions for point pattern analysis. Most functions + are designed to work with the 'spatstat' () package. The focus of + most functions are either null models or summary functions for spatial point patterns. + For a detailed description of all null models and summary functions, see + Wiegand and Moloney (2014, ISBN:9781420082548). + date_publication: '2025-02-10' + bug_reports: https://github.com/r-spatialecology/onpoint/issues + url: https://r-spatialecology.github.io/onpoint/ + url_cran: https://CRAN.R-project.org/package=onpoint + url_git: '' +onsr: + version: 1.0.2 + title: Client for the 'ONS' API + maintainer: Kostas Vasilopoulos + description: |- + Client for the 'Office of National Statistics' + ('ONS') API . + date_publication: '2023-12-21' + bug_reports: https://github.com/kvasilopoulos/onsr/issues + url: https://kvasilopoulos.github.io/onsr/ + url_cran: https://CRAN.R-project.org/package=onsr + url_git: '' +onsvplot: + version: 0.3.2 + title: |- + National Road Safety Observatory (ONSV) Style for 'ggplot2' + Graphics + maintainer: Pedro Augusto Borges Santos + description: |- + Helps to create 'ggplot2' charts in the style used by the National + Road Safety Observatory (ONSV). The package includes functions to + customize 'ggplot2' objects with new theme and colors. + date_publication: '2023-09-05' + bug_reports: https://github.com/pabsantos/onsvplot/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=onsvplot + url_git: https://github.com/pabsantos/onsvplot/ +onsvtables: + version: 0.1.0 + title: National Road Safety Observatory (ONSV) Styles for 'gt' Tables + maintainer: João Pedro Melani Saraiva + description: |- + Wrapper functions for customizing HTML + tables from the 'gt' package to the ONSV style. + date_publication: '2024-05-25' + bug_reports: https://github.com/ONSV/onsvtables/issues + url: https://onsv.github.io/onsvtables/ + url_cran: https://CRAN.R-project.org/package=onsvtables + url_git: https://github.com/ONSV/onsvtables +ontoFAST: + version: 1.0.0 + title: Interactive Annotation of Characters with Biological Ontologies + maintainer: Sergei Tarasov + description: Tools for annotating characters (character matrices) with anatomical + and phenotype ontologies. Includes functions for visualising character annotations + and creating simple queries using ontological relationships. + date_publication: '2021-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ontoFAST + url_git: https://github.com/sergeitarasov/ontoFAST +ontologics: + version: 0.7.4 + title: Code-Logics to Handle Ontologies + maintainer: Steffen Ehrmann + description: |- + Provides tools to build and work with an ontology of linked (open) + data in a tidy workflow. It is inspired by the Food and Agrilculture + Organizations (FAO) caliper platform + and + makes use of the Simple Knowledge Organisation System (SKOS). + date_publication: '2025-01-17' + bug_reports: https://github.com/luckinet/ontologics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ontologics + url_git: https://github.com/luckinet/ontologics +ontologyIndex: + version: '2.12' + title: Reading Ontologies into R + maintainer: Daniel Greene + description: 'Functions for reading ontologies into R as lists and manipulating + sets of ontological terms - ''ontologyX: A suite of R packages for working with + ontological data'', Greene et al 2017 .' + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ontologyIndex + url_git: '' +ontologyPlot: + version: '1.7' + title: Visualising Sets of Ontological Terms + maintainer: Daniel Greene + description: Create R plots visualising ontological terms and the relationships + between them with various graphical options - Greene et al. 2017 . + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ontologyPlot + url_git: '' +ontologySimilarity: + version: '2.7' + title: Calculating Ontological Similarities + maintainer: Daniel Greene + description: Calculate similarity between ontological terms and sets of ontological + terms based on term information content and assess statistical significance of + similarity in the context of a collection of terms sets - Greene et al. 2017 . + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ontologySimilarity + url_git: '' +ontophylo: + version: 1.1.3 + title: Ontology-Informed Phylogenetic Comparative Analyses + maintainer: Diego S. Porto + description: |- + Provides new tools for analyzing discrete trait data integrating bio-ontologies and phylogenetics. It expands on the previous work of Tarasov et al. (2019) . The PARAMO pipeline allows to reconstruct ancestral phenomes treating groups of morphological traits as a single complex character. The pipeline incorporates knowledge from ontologies during the amalgamation of individual character stochastic maps. + Here we expand the current PARAMO functionality by adding new statistical methods for inferring evolutionary phenome dynamics using non-homogeneous Poisson process (NHPP). The new functionalities include: (1) reconstruction of evolutionary rate shifts of phenomes across lineages and time; (2) reconstruction of morphospace dynamics through time; and (3) estimation of rates of phenome evolution at different levels of anatomical hierarchy (e.g., entire body or specific regions only). The package also includes user-friendly tools for visualizing evolutionary rates of different anatomical regions using vector images of the organisms of interest. + date_publication: '2024-01-10' + bug_reports: https://github.com/diegosasso/ontophylo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ontophylo + url_git: https://github.com/diegosasso/ontophylo +OOBCurve: + version: '0.3' + title: Out of Bag Learning Curve + maintainer: Philipp Probst + description: Provides functions to calculate the out-of-bag learning curve for random + forests for any measure that is available in the 'mlr' package. Supported random + forest packages are 'randomForest' and 'ranger' and trained models of these packages + with the train function of 'mlr'. The main function is OOBCurve() that calculates + the out-of-bag curve depending on the number of trees. With the OOBCurvePars() + function out-of-bag curves can also be calculated for 'mtry', 'sample.fraction' + and 'min.node.size' for the 'ranger' package. + date_publication: '2018-08-30' + bug_reports: https://github.com/PhilippPro/OOBCurve/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OOBCurve + url_git: https://github.com/PhilippPro/OOBCurve +oolong: + version: 0.6.1 + title: Create Validation Tests for Automated Content Analysis + maintainer: Chung-hong Chan + description: Intended to create standard human-in-the-loop validity tests for typical + automated content analysis such as topic modeling and dictionary-based methods. + This package offers a standard workflow with functions to prepare, administer + and evaluate a human-in-the-loop validity test. This package provides functions + for validating topic models using word intrusion, topic intrusion (Chang et al. + 2009, ) + and word set intrusion (Ying et al. 2021) tests. This + package also provides functions for generating gold-standard data which are useful + for validating dictionary-based methods. The default settings of all generated + tests match those suggested in Chang et al. (2009) and Song et al. (2020) . + date_publication: '2024-04-15' + bug_reports: https://github.com/gesistsa/oolong/issues + url: https://gesistsa.github.io/oolong/ + url_cran: https://CRAN.R-project.org/package=oolong + url_git: https://github.com/gesistsa/oolong +oompaBase: + version: 3.2.9 + title: Class Unions, Matrix Operations, and Color Schemes for OOMPA + maintainer: Kevin R. Coombes + description: |- + Provides the class unions that must be + preloaded in order for the basic tools in the OOMPA (Object-Oriented + Microarray and Proteomics Analysis) project to be defined and loaded. + It also includes vectorized operations for row-by-row means, + variances, and t-tests. Finally, it provides new color schemes. + Details on the packages in the OOMPA project can be found at + . + date_publication: '2019-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oompaBase + url_git: http://oompa.r-forge.r-project.org/ +oompaData: + version: 3.1.4 + title: Data to Illustrate OOMPA Algorithms + maintainer: Kevin R. Coombes + description: |- + This is a data-only package to provide example data for + other packages that are part of the "Object-Oriented Microrray and + Proteomics Analysis" suite of packages. These are described in more + detail at the package URL. + date_publication: '2024-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oompaData + url_git: http://oompa.r-forge.r-project.org/ +ooplah: + version: 0.2.0 + title: Helper Functions for Class Object-Oriented Programming + maintainer: Raphael Sonabend + description: |- + Helper functions for coding object-oriented programming with + a focus on R6. Includes functions for assertions and testing, looping, + and re-usable design patterns including Abstract and Decorator + classes. + date_publication: '2022-01-21' + bug_reports: https://github.com/xoopR/ooplah/issues + url: https://xoopR.github.io/ooplah/ + url_cran: https://CRAN.R-project.org/package=ooplah + url_git: https://github.com/xoopR/ooplah +OOR: + version: 0.1.4 + title: Optimistic Optimization in R + maintainer: M. Binois + description: Implementation of optimistic optimization methods for global optimization + of deterministic or stochastic functions. The algorithms feature guarantees of + the convergence to a global optimum. They require minimal assumptions on the (only + local) smoothness, where the smoothness parameter does not need to be known. They + are expected to be useful for the most difficult functions when we have no information + on smoothness and the gradients are unknown or do not exist. Due to the weak assumptions, + however, they can be mostly effective only in small dimensions, for example, for + hyperparameter tuning. + date_publication: '2023-08-23' + bug_reports: https://github.com/mbinois/OOR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OOR + url_git: https://github.com/mbinois/OOR +OOS: + version: 1.0.0 + title: Out-of-Sample Time Series Forecasting + maintainer: Tyler J. Pike + description: |- + A comprehensive and cohesive API for the out-of-sample forecasting workflow: + data preparation, forecasting - including both traditional econometric time series models and + modern machine learning techniques - forecast combination, model and error analysis, and + forecast visualization. + date_publication: '2021-03-17' + bug_reports: https://github.com/tylerJPike/OOS/issues + url: https://tylerjpike.github.io/OOS/ + url_cran: https://CRAN.R-project.org/package=OOS + url_git: https://github.com/tylerJPike/OOS +oosse: + version: 1.0.11 + title: Out-of-Sample R² with Standard Error Estimation + maintainer: Stijn Hawinkel + description: Estimates out-of-sample R² through bootstrap or cross-validation as + a measure of predictive performance. In addition, a standard error for this point + estimate is provided, and confidence intervals are constructed. + date_publication: '2024-02-07' + bug_reports: https://github.com/sthawinke/oosse + url: '' + url_cran: https://CRAN.R-project.org/package=oosse + url_git: '' +oottest: + version: 0.9.1 + title: Out-of-Treatment Testing + maintainer: Philipp Külpmann + description: |- + Implements the out-of-treatment testing from Kuelpmann and Kuzmics (2020) based on the Vuong Test introduced in Vuong (1989) . + Out-of treatment testing allows for a direct, pairwise likelihood comparison of theories, calibrated with pre-existing data. + date_publication: '2022-04-27' + bug_reports: https://github.com/PhilippKuelpmann/oottest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oottest + url_git: https://github.com/PhilippKuelpmann/oottest +opa: + version: 0.8.3 + title: An Implementation of Ordinal Pattern Analysis + maintainer: Timothy Beechey + description: |- + Quantifies hypothesis to data fit for repeated measures + and longitudinal data, as described by Thorngate (1987) + and Grice et al., (2015) + . Hypothesis and data are encoded as + pairwise relative orderings which are then compared to determine the + percentage of orderings in the data that are matched by the hypothesis. + date_publication: '2024-03-11' + bug_reports: https://github.com/timbeechey/opa/issues + url: https://timbeechey.github.io/opa/ + url_cran: https://CRAN.R-project.org/package=opa + url_git: '' +opalr: + version: 3.4.2 + title: '''Opal'' Data Repository Client and ''DataSHIELD'' Utils' + maintainer: Yannick Marcon + description: |- + Data integration Web application for biobanks by 'OBiBa'. 'Opal' is + the core database application for biobanks. Participant data, once + collected from any data source, must be integrated and stored in a central + data repository under a uniform model. 'Opal' is such a central repository. + It can import, process, validate, query, analyze, report, and export data. + 'Opal' is typically used in a research center to analyze the data acquired at + assessment centres. Its ultimate purpose is to achieve seamless + data-sharing among biobanks. This 'Opal' client allows to interact with 'Opal' + web services and to perform operations on the R server side. 'DataSHIELD' + administration tools are also provided. + date_publication: '2024-09-18' + bug_reports: https://github.com/obiba/opalr/issues/ + url: https://www.obiba.org/opalr/ + url_cran: https://CRAN.R-project.org/package=opalr + url_git: https://github.com/obiba/opalr/ +OPC: + version: 0.0.2 + title: The Online Principal Component Estimation Method + maintainer: Chunjie Wei + description: The online principal component method can process the online data set. + The philosophy of the package is described in Guo G. (2018) . + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OPC + url_git: '' +opdisDownsampling: + version: 1.0.1 + title: |- + Optimal Distribution Preserving Down-Sampling of Bio-Medical + Data + maintainer: Jorn Lotsch + description: An optimized method for distribution-preserving class-proportional + down-sampling of bio-medical data. + date_publication: '2024-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=opdisDownsampling + url_git: '' +OPDOE: + version: 1.0-10 + title: Optimal Design of Experiments + maintainer: Albrecht Gebhardt + description: |- + Several function related to Experimental Design are implemented here, see + "Optimal Experimental Design with R" by Rasch D. et. al (ISBN 9781439816974). + date_publication: '2018-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OPDOE + url_git: '' +openai: + version: 0.4.1 + title: R Wrapper for OpenAI API + maintainer: Iegor Rudnytskyi + description: |- + An R wrapper of OpenAI API endpoints (see + for details). This package + covers Models, Completions, Chat, Edits, Images, Embeddings, Audio, Files, + Fine-tunes, Moderations, and legacy Engines endpoints. + date_publication: '2023-03-15' + bug_reports: https://github.com/irudnyts/openai/issues + url: https://irudnyts.github.io/openai/ + url_cran: https://CRAN.R-project.org/package=openai + url_git: https://github.com/irudnyts/openai +openair: + version: 2.18-2 + title: Tools for the Analysis of Air Pollution Data + maintainer: David Carslaw + description: |- + Tools to analyse, interpret and understand air pollution + data. Data are typically regular time series and air quality + measurement, meteorological data and dispersion model output can be + analysed. The package is described in Carslaw and Ropkins (2012, + ) and subsequent papers. + date_publication: '2024-03-11' + bug_reports: https://github.com/davidcarslaw/openair/issues + url: https://davidcarslaw.github.io/openair/ + url_cran: https://CRAN.R-project.org/package=openair + url_git: https://github.com/davidcarslaw/openair +openairmaps: + version: 0.9.1 + title: Create Maps of Air Pollution Data + maintainer: Jack Davison + description: |- + Combine the air quality data analysis methods of 'openair' + with the JavaScript 'Leaflet' () library. + Functionality includes plotting site maps, "directional analysis" + figures such as polar plots, and air mass trajectories. + date_publication: '2024-11-19' + bug_reports: https://github.com/davidcarslaw/openairmaps/issues + url: https://davidcarslaw.github.io/openairmaps/ + url_cran: https://CRAN.R-project.org/package=openairmaps + url_git: https://github.com/davidcarslaw/openairmaps +openaistream: + version: 0.3.0 + title: Streaming Capabilities for 'OpenAI API' Interactions + maintainer: Li Gen + description: |- + Based on the 'httr2' framework, the 'OpenAI' interface supports streaming calls and model training. + For more details on the API methods implemented, see the 'OpenAI' platform documentation at . + date_publication: '2024-06-07' + bug_reports: https://github.com/libingfei/openaistream/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openaistream + url_git: https://github.com/libingfei/openaistream +openalexR: + version: 1.4.0 + title: |- + Getting Bibliographic Records from 'OpenAlex' Database Using + 'DSL' API + maintainer: Massimo Aria + description: |- + A set of tools to extract bibliographic content from + 'OpenAlex' database using API . + date_publication: '2024-07-11' + bug_reports: https://github.com/ropensci/openalexR/issues + url: https://docs.ropensci.org/openalexR/ + url_cran: https://CRAN.R-project.org/package=openalexR + url_git: https://github.com/ropensci/openalexR +openappr: + version: 0.2.0 + title: Retrieve App Data from 'OpenAppBuilder' + maintainer: Lily Clements + description: Provides an interface to connect R with the + 'OpenAppBuilder' platform, enabling users to retrieve and work with user and notification + data for analysis and processing. It is designed for developers and analysts to + seamlessly integrate data from 'OpenAppBuilder' into R workflows via a 'Postgres' + database connection, allowing direct querying and import of app data into R. + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=openappr + url_git: '' +openbankeR: + version: 0.1.1 + title: R Client for Querying the UK 'Open Banking' ('Open Data') API + maintainer: Nik Lilovski + description: Creates a client with queries for the UK 'Open Banking' ('Open Data') + API. + date_publication: '2022-02-22' + bug_reports: https://github.com/nik01010/openbankeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openbankeR + url_git: https://github.com/nik01010/openbankeR +openblender: + version: 0.5.81 + title: Request API Services + maintainer: Daniel V. Pinacho + description: Interface to make HTTP requests to 'OpenBlender' API services. Go to + for more information. + date_publication: '2020-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=openblender + url_git: '' +opencage: + version: 0.2.2 + title: Geocode with the OpenCage API + maintainer: Daniel Possenriede + description: |- + Geocode with the OpenCage API, either from place name to longitude + and latitude (forward geocoding) or from longitude and latitude to the name + and address of a location (reverse geocoding), see + . + date_publication: '2021-02-20' + bug_reports: https://github.com/ropensci/opencage/issues + url: https://docs.ropensci.org/opencage/ + url_cran: https://CRAN.R-project.org/package=opencage + url_git: https://github.com/ropensci/opencage +OpenCL: + version: 0.2-10 + title: Interface allowing R to use OpenCL + maintainer: Simon Urbanek + description: This package provides an interface to OpenCL, allowing R to leverage + computing power of GPUs and other HPC accelerator devices. + date_publication: '2023-12-22' + bug_reports: '' + url: http://www.rforge.net/OpenCL/ + url_cran: https://CRAN.R-project.org/package=OpenCL + url_git: '' +opencpu: + version: 2.2.14 + title: Producing and Reproducing Results + maintainer: Jeroen Ooms + description: |- + A system for embedded scientific computing and reproducible research with R. + The OpenCPU server exposes a simple but powerful HTTP api for RPC and data interchange + with R. This provides a reliable and scalable foundation for statistical services or + building R web applications. The OpenCPU server runs either as a single-user development + server within the interactive R session, or as a multi-user Linux stack based on Apache2. + The entire system is fully open source and permissively licensed. The OpenCPU website + has detailed documentation and example apps. + date_publication: '2024-10-04' + bug_reports: https://github.com/opencpu/opencpu/issues + url: https://www.opencpu.orghttps://opencpu.r-universe.dev/opencpu + url_cran: https://CRAN.R-project.org/package=opencpu + url_git: '' +openCR: + version: 2.2.7 + title: Open Population Capture-Recapture + maintainer: Murray Efford + description: Non-spatial and spatial open-population capture-recapture analysis. + date_publication: '2024-10-23' + bug_reports: https://github.com/MurrayEfford/openCR/issues/ + url: https://www.otago.ac.nz/density/ + url_cran: https://CRAN.R-project.org/package=openCR + url_git: https://github.com/MurrayEfford/openCR/ +opencv: + version: 0.4.1 + title: Bindings to 'OpenCV' Computer Vision Library + maintainer: Jeroen Ooms + description: |- + Exposes some of the available 'OpenCV' algorithms, + such as a QR code scanner, and edge, body or face detection. These can either be + applied to analyze static images, or to filter live video footage from a camera device. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/opencv/issues + url: https://docs.ropensci.org/opencv/https://ropensci.r-universe.dev/opencv + url_cran: https://CRAN.R-project.org/package=opencv + url_git: '' +opendataformat: + version: 2.1.3 + title: Reading and Writing Open Data Format Files + maintainer: Tom Hartl + description: The Open Data Format (ODF) is a new, non-proprietary, multilingual, + metadata enriched, and zip-compressed data format with metadata structured in + the Data Documentation Initiative (DDI) Codebook standard. This package allows + reading and writing of data files in the Open Data Format (ODF) in R, and displaying + metadata in different languages. For further information on the Open Data Format, + see . + date_publication: '2025-02-11' + bug_reports: https://github.com/opendataformat/r-package-opendataformat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=opendataformat + url_git: https://github.com/opendataformat/r-package-opendataformat +opendatatoronto: + version: 0.1.5 + title: Access the City of Toronto Open Data Portal + maintainer: Sharla Gelfand + description: |- + Access data from the "City of Toronto + Open Data Portal" () directly from R. + date_publication: '2022-04-13' + bug_reports: https://github.com/sharlagelfand/opendatatoronto/issues + url: https://sharlagelfand.github.io/opendatatoronto/ + url_cran: https://CRAN.R-project.org/package=opendatatoronto + url_git: https://github.com/sharlagelfand/opendatatoronto/ +opendotaR: + version: 0.1.4 + title: Interface for OpenDota API + maintainer: Kari Gunnarsson + description: |- + Enables the usage of the OpenDota API from , get game lists, and download JSON's of parsed replays from + the OpenDota API. Also has functionality to execute own code to extract the specific parts of the JSON file. + date_publication: '2017-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=opendotaR + url_git: '' +openEBGM: + version: 0.9.1 + title: EBGM Disproportionality Scores for Adverse Event Data Mining + maintainer: John Ihrie + description: |- + An implementation of DuMouchel's (1999) + Bayesian data mining method for the market basket problem. + Calculates Empirical Bayes Geometric Mean (EBGM) and posterior quantile scores + using the Gamma-Poisson Shrinker (GPS) model to find unusually large cell + counts in large, sparse contingency tables. Can be used to find unusually high + reporting rates of adverse events associated with products. In general, can be + used to mine any database where the co-occurrence of two variables or items is + of interest. Also calculates relative and proportional reporting ratios. + Builds on the work of the 'PhViD' package, from which much of the code is + derived. Some of the added features include stratification to adjust for + confounding variables and data squashing to improve computational efficiency. + Includes an implementation of the EM algorithm for hyperparameter estimation + loosely derived from the 'mederrRank' package. + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=openEBGM + url_git: '' +openeo: + version: 1.3.1 + title: Client Interface for 'openEO' Servers + maintainer: Florian Lahn + description: Access data and processing functionalities of 'openEO' compliant back-ends + in R. + date_publication: '2024-02-17' + bug_reports: https://github.com/Open-EO/openeo-r-client/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openeo + url_git: https://github.com/Open-EO/openeo-r-client +openFDA: + version: 0.1.0 + title: '''openFDA'' API' + maintainer: Simon Parker + description: |- + The 'openFDA' API facilitates access to Federal Drug Agency (FDA) + data on drugs, devices, foodstuffs, tobacco, and more with 'httr2'. This + package makes the API easily accessible, returning objects which the user can + convert to JSON data and parse. Kass-Hout TA, Xu Z, Mohebbi M et al. (2016) + . + date_publication: '2024-10-18' + bug_reports: https://github.com/simpar1471/openFDA/issues + url: https://simpar1471.github.io/openFDA/ + url_cran: https://CRAN.R-project.org/package=openFDA + url_git: https://github.com/simpar1471/openFDA +opengraph: + version: 0.0.2 + title: Process Metadata from the Open Graph Protocol + maintainer: Christopher T. Kenny + description: |- + Social media sites often embed cards when links are shared, based on + metadata in the 'Open Graph Protocol' (). This supports extracting + that metadata from a website. It further allows for the creation of tags to + add to a website to support the 'Open Graph Protocol' and provides a list of the + standard tags and their required properties. + date_publication: '2024-12-10' + bug_reports: '' + url: https://christophertkenny.com/opengraph/ + url_cran: https://CRAN.R-project.org/package=opengraph + url_git: https://github.com/christopherkenny/opengraph +OpEnHiMR: + version: 0.1.1 + title: |- + Optimization Based Ensemble Model for Prediction of Histone + Modifications in Rice + maintainer: Dipro Sinha + description: The comprehensive knowledge of epigenetic modifications in plants, + encompassing histone modifications in regulating gene expression, is not completely + ingrained. It is noteworthy that histone deacetylation and histone H3 lysine 27 + trimethylation (H3K27me3) play a role in repressing transcription in eukaryotes. + In contrast, histone acetylation (H3K9ac) and H3K4me3 have been inevitably linked + to the stimulation of gene expression, which significantly influences plant development + and plays a role in plant responses to biotic and abiotic stresses. To our knowledge + this the first multiclass classifier for predicting histone modification in plants. + . + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OpEnHiMR + url_git: '' +OpenImageR: + version: 1.3.0 + title: An Image Processing Toolkit + maintainer: Lampros Mouselimis + description: 'Incorporates functions for image preprocessing, filtering and image + recognition. The package takes advantage of ''RcppArmadillo'' to speed up computationally + intensive functions. The histogram of oriented gradients descriptor is a modification + of the ''findHOGFeatures'' function of the ''SimpleCV'' computer vision platform, + the average_hash(), dhash() and phash() functions are based on the ''ImageHash'' + python library. The Gabor Feature Extraction functions are based on ''Matlab'' + code of the paper, "CloudID: Trustworthy cloud-based and cross-enterprise biometric + identification" by M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, Expert Systems + with Applications, vol. 42, no. 21, pp. 7905-7916, 2015, . + The ''SLIC'' and ''SLICO'' superpixel algorithms were explained in detail in (i) + "SLIC Superpixels Compared to State-of-the-art Superpixel Methods", Radhakrishna + Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, + IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, num. + 11, p. 2274-2282, May 2012, and (ii) "SLIC Superpixels", + Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and + Sabine Suesstrunk, EPFL Technical Report no. 149300, June 2010.' + date_publication: '2023-07-08' + bug_reports: https://github.com/mlampros/OpenImageR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OpenImageR + url_git: https://github.com/mlampros/OpenImageR +openintro: + version: 2.5.0 + title: |- + Datasets and Supplemental Functions from 'OpenIntro' Textbooks + and Labs + maintainer: Mine Çetinkaya-Rundel + description: |- + Supplemental functions and data for 'OpenIntro' resources, which + includes open-source textbooks and resources for introductory statistics + (). The package contains datasets used in our + open-source textbooks along with custom plotting functions for reproducing + book figures. Note that many functions and examples include color + transparency; some plotting elements may not show up properly (or at all) + when run in some versions of Windows operating system. + date_publication: '2024-05-31' + bug_reports: https://github.com/OpenIntroStat/openintro/issues + url: http://openintrostat.github.io/openintro/ + url_cran: https://CRAN.R-project.org/package=openintro + url_git: https://github.com/OpenIntroStat/openintro/ +OpenLand: + version: 1.0.3 + title: Quantitative Analysis and Visualization of LUCC + maintainer: Reginal Exavier + description: |- + Tools for the analysis of land use and cover (LUC) time series. It + includes support for loading spatiotemporal raster data and synthesized + spatial plotting. Several LUC change (LUCC) metrics in regular or irregular + time intervals can be extracted and visualized through one- and multistep + sankey and chord diagrams. A complete intensity analysis according to + Aldwaik and Pontius (2012) is + implemented, including tools for the generation of standardized multilevel + output graphics. + date_publication: '2024-05-03' + bug_reports: https://github.com/reginalexavier/OpenLand/issues + url: https://reginalexavier.github.io/OpenLand/ + url_cran: https://CRAN.R-project.org/package=OpenLand + url_git: https://github.com/reginalexavier/OpenLand +openmeteo: + version: 0.2.4 + title: Retrieve Weather Data from the Open-Meteo API + maintainer: Tom Pisel + description: |- + A client for the Open-Meteo API that retrieves Open-Meteo + weather data in a tidy format. No API key is required. The API specification + is located at . + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=openmeteo + url_git: '' +openmetrics: + version: 0.3.0 + title: A 'Prometheus' Client for R Using the 'OpenMetrics' Format + maintainer: Aaron Jacobs + description: |- + Provides a client for the open-source monitoring and alerting + toolkit, 'Prometheus', that emits metrics in the 'OpenMetrics' format. Allows + users to automatically instrument 'Plumber' and 'Shiny' applications, collect + standard process metrics, as well as define custom counter, gauge, and + histogram metrics of their own. + date_publication: '2020-11-09' + bug_reports: https://github.com/atheriel/openmetrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openmetrics + url_git: https://github.com/atheriel/openmetrics +OpenMindat: + version: 1.0.0 + title: Quickly Retrieve Datasets from the 'mindat.org' API + maintainer: Xiang Que + description: '''Mindat'' (''mindat.org'') is one of the world''s most widely used + databases of mineral species and their distribution. Many scientists in mineralogy, + geochemistry, petrology, and other Earth and planetary disciplines have been using + the ''Mindat'' data. Still, an open data service and the machine interface have + never been fully established. To meet the overwhelming data needs, the ''Mindat'' + team has built an API () for data access.''OpenMindat'' + R package provides valuable functions to bridge the data highway, connecting users'' + data requirements to the ''Mindat'' API server and assist with retrieval and initial + processing to improve efficiency further and lower the barrier of data query and + access to scientists. ''OpenMindat'' provides friendly and extensible data retrieval + functions, including the subjects of geomaterials (e.g., rocks, minerals, synonyms, + variety, mixture, and commodity), localities, and the IMA (International Mineralogical + Association)-approved mineral list. ''OpenMindat'' R package will accelerate the + process of data-intensive studies in mineral informatics and lead to more scientific + discoveries.' + date_publication: '2024-02-15' + bug_reports: https://github.com/quexiang/OpenMindat/issues + url: https://quexiang.github.io/OpenMindat/ + url_cran: https://CRAN.R-project.org/package=OpenMindat + url_git: https://github.com/quexiang/OpenMindat +OpenML: + version: '1.12' + title: Open Machine Learning and Open Data Platform + maintainer: Giuseppe Casalicchio + description: |- + We provide an R interface to 'OpenML.org' which is an online machine learning platform where researchers can access open data, download and upload data sets, share their machine learning tasks and experiments and organize them online to work and collaborate with other researchers. + The R interface allows to query for data sets with specific properties, and allows the downloading and uploading of data sets, tasks, flows and runs. + See for more information. + date_publication: '2022-10-19' + bug_reports: https://github.com/openml/openml-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OpenML + url_git: https://github.com/openml/openml-r +openMSE: + version: 1.0.1 + title: Easily Install and Load the 'openMSE' Packages + maintainer: Adrian Hordyk + description: |- + The 'openMSE' package is designed for building operating models, + doing simulation modelling and management strategy evaluation for fisheries. + 'openMSE' is an umbrella package for the 'MSEtool' (Management Strategy Evaluation + toolkit), 'DLMtool' (Data-Limited Methods toolkit), and + SAMtool (Stock Assessment Methods toolkit) packages. By loading and installing + 'openMSE', users have access to the full functionality contained within + these packages. Learn more about 'openMSE' at . + date_publication: '2024-09-24' + bug_reports: https://github.com/Blue-Matter/openMSE/issues + url: https://openmse.com/ + url_cran: https://CRAN.R-project.org/package=openMSE + url_git: https://github.com/Blue-Matter/openMSE +OpenMx: + version: 2.21.13 + title: Extended Structural Equation Modelling + maintainer: Robert M. Kirkpatrick + description: |- + Create structural equation models that can be manipulated programmatically. + Models may be specified with matrices or paths (LISREL or RAM) + Example models include confirmatory factor, multiple group, mixture + distribution, categorical threshold, modern test theory, differential + Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. + equations, state space, and many others. + Support and advanced package binaries available at . + The software is described in Neale, Hunter, Pritikin, Zahery, Brick, + Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) . + date_publication: '2024-10-19' + bug_reports: http://openmx.ssri.psu.edu/forums + url: http://openmx.ssri.psu.edu + url_cran: https://CRAN.R-project.org/package=OpenMx + url_git: https://github.com/OpenMx/OpenMx +openNLP: + version: 0.2-7 + title: Apache OpenNLP Tools Interface + maintainer: Kurt Hornik + description: |- + An interface to the Apache OpenNLP tools (version 1.5.3). + The Apache OpenNLP library is a machine learning based toolkit for the + processing of natural language text written in Java. + It supports the most common NLP tasks, such as tokenization, sentence + segmentation, part-of-speech tagging, named entity extraction, chunking, + parsing, and coreference resolution. + See for more information. + date_publication: '2019-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=openNLP + url_git: '' +openNLPdata: + version: 1.5.3-5 + title: Apache OpenNLP Jars and Basic English Language Models + maintainer: Kurt Hornik + description: Apache OpenNLP jars and basic English language models. + date_publication: '2024-03-11' + bug_reports: '' + url: https://opennlp.apache.org/ + url_cran: https://CRAN.R-project.org/package=openNLPdata + url_git: '' +OpeNoise: + version: 0.2-18 + title: Environmental Noise Pollution Data Analysis + maintainer: Pasquale Scordino + description: Provides analyse, interpret and understand noise pollution data. Data + are typically regular time series measured with sound meter. The package is partially + described in Fogola, Grasso, Masera and Scordino (2023, ). + date_publication: '2024-11-20' + bug_reports: https://github.com/Arpapiemonte/openoise-analysis/issues/ + url: https://arpapiemonte.github.io/openoise-analysis/ + url_cran: https://CRAN.R-project.org/package=OpeNoise + url_git: https://github.com/Arpapiemonte/openoise-analysis/ +OpenRange: + version: 0.0.1 + title: Code to Access Open Access Species Range Maps + maintainer: Brian Maitner + description: Allows access to a proof-of-concept database containing Open Access + species range models and relevant metadata. Access to the database is via both + 'PostgreSQL' connection and API , + allowing diverse use-cases. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OpenRange + url_git: '' +OpenRepGrid: + version: 0.1.16 + title: Tools to Analyze Repertory Grid Data + maintainer: Mark Heckmann + description: |- + Analyze repertory grids, a qualitative-quantitative + data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across + various domains ranging from clinical psychology to marketing. The package contains functions + to quantitatively analyze and visualize repertory grid data (e.g. 'Fransella', 'Bell', & 'Bannister', + 2004, ISBN: 978-0-470-09080-0). The package is part of the The package is part of the + project. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OpenRepGrid + url_git: https://github.com/markheckmann/OpenRepGrid +OpenRepGrid.ic: + version: 0.6.2 + title: Interpretive Clustering for Repertory Grids + maintainer: Mark Heckmann + description: |- + Shiny UI to identify cliques of related constructs in repertory grid data. + See Burr, King, & Heckmann (2020) for a description + of the interpretive clustering (IC) method. + date_publication: '2024-02-19' + bug_reports: https://github.com/markheckmann/OpenRepGrid.ic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OpenRepGrid.ic + url_git: https://github.com/markheckmann/OpenRepGrid.ic +openrouteservice: + version: 0.6.2 + title: An 'openrouteservice' API Client + maintainer: Andrzej K. Oleś + description: |- + The client streamlines access to the services provided by . + It allows you to painlessly query for directions, isochrones, time-distance matrices, geocoding, elevation, points of interest, and more. + date_publication: '2025-02-08' + bug_reports: https://github.com/GIScience/openrouteservice-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openrouteservice + url_git: https://github.com/GIScience/openrouteservice-r +openscoring: + version: 1.0.4 + title: '''Open Scoring'' API Client' + maintainer: Jakub Jędrusiak + description: |- + Creativity research involves the need to score open-ended problems. + Usually done by humans, automatic scoring using AI becomes more + and more accurate. This package provides a simple interface to + the 'Open Scoring' API , leading creativity scoring technology by + Organiscak et al. (2023) . With it, + you can score your own data directly from an R script. + date_publication: '2024-08-24' + bug_reports: https://github.com/jakub-jedrusiak/openscoring/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openscoring + url_git: https://github.com/jakub-jedrusiak/openscoring +openSkies: + version: 1.2.1 + title: Retrieval, Analysis and Visualization of Air Traffic Data + maintainer: Rafael Ayala + description: |- + Provides functionalities and data structures to retrieve, analyze and visualize aviation + data. It includes a client interface to the 'OpenSky' API . It allows + retrieval of flight information, as well as aircraft state vectors. + date_publication: '2024-04-03' + bug_reports: https://github.com/Rafael-Ayala/openSkies/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openSkies + url_git: '' +OpenSpecy: + version: 1.4.0 + title: Analyze, Process, Identify, and Share Raman and (FT)IR Spectra + maintainer: Win Cowger + description: |- + Raman and (FT)IR spectral analysis tool for plastic particles and + other environmental samples (Cowger et al. 2021, + ). With read_any(), Open Specy provides a + single function for reading individual, batch, or map spectral data files + like .asp, .csv, .jdx, .spc, .spa, .0, and .zip. process_spec() simplifies + processing spectra, including smoothing, baseline correction, + range restriction and flattening, intensity conversions, wavenumber + alignment, and min-max normalization. Spectra can be identified in batch + using an onboard reference library (Cowger et al. 2020, + ) using match_spec(). A Shiny app is available + via run_app() or online at . + date_publication: '2024-11-04' + bug_reports: https://github.com/wincowgerDEV/OpenSpecy-package/issues/ + url: https://wincowger.com/OpenSpecy-package/ + url_cran: https://CRAN.R-project.org/package=OpenSpecy + url_git: https://github.com/wincowgerDEV/OpenSpecy-package/ +openssl: + version: 2.3.2 + title: |- + Toolkit for Encryption, Signatures and Certificates Based on + OpenSSL + maintainer: Jeroen Ooms + description: |- + Bindings to OpenSSL libssl and libcrypto, plus custom SSH key parsers. + Supports RSA, DSA and EC curves P-256, P-384, P-521, and curve25519. Cryptographic + signatures can either be created and verified manually or via x509 certificates. + AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric + (public key) encryption or EC for Diffie Hellman. High-level envelope functions + combine RSA and AES for encrypting arbitrary sized data. Other utilities include key + generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random + number generator, and 'bignum' math methods for manually performing crypto + calculations on large multibyte integers. + date_publication: '2025-02-03' + bug_reports: https://github.com/jeroen/openssl/issues + url: https://jeroen.r-universe.dev/openssl + url_cran: https://CRAN.R-project.org/package=openssl + url_git: '' +OpenStreetMap: + version: 0.4.0 + title: Access to Open Street Map Raster Images + maintainer: Ian Fellows + description: |- + Accesses high resolution raster maps using the OpenStreetMap + protocol. Dozens of road, satellite, and topographic map servers are directly + supported, including Apple, Mapnik, Bing, and stamen. Additionally raster maps + may be constructed using custom tile servers. Maps can be + plotted using either base graphics, or ggplot2. This package is not affiliated + with the OpenStreetMap.org mapping project. + date_publication: '2023-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OpenStreetMap + url_git: https://github.com/ifellows/ROSMhttps://www.fellstat.com +opentripplanner: + version: 0.5.2 + title: Setup and connect to 'OpenTripPlanner' + maintainer: Malcolm Morgan + description: |- + Setup and connect to 'OpenTripPlanner' (OTP) . + OTP is an open source platform for multi-modal and multi-agency + journey planning written in 'Java'. The package allows you to manage a local version or + connect to remote OTP server to find walking, cycling, driving, or transit routes. + This package has been peer-reviewed by rOpenSci (v. 0.2.0.0). + date_publication: '2024-05-06' + bug_reports: https://github.com/ropensci/opentripplanner/issues + url: https://docs.ropensci.org/opentripplanner/ + url_cran: https://CRAN.R-project.org/package=opentripplanner + url_git: https://github.com/ropensci/opentripplanner +openVA: + version: 1.1.2 + title: Automated Method for Verbal Autopsy + maintainer: Zehang Richard Li + description: Implements multiple existing open-source algorithms for coding cause + of death from verbal autopsies. The methods implemented include 'InterVA4' by + Byass et al (2012) , 'InterVA5' by Byass at al (2019) + , 'InSilicoVA' by McCormick et al (2016) , + 'NBC' by Miasnikof et al (2015) , and a replication + of 'Tariff' method by James et al (2011) and Serina, + et al. (2015) . It also provides tools for data + manipulation tasks commonly used in Verbal Autopsy analysis and implements easy + graphical visualization of individual and population level statistics. The 'NBC' + method is implemented by the 'nbc4va' package that can be installed from . + Note that this package was not developed by authors affiliated with the Institute + for Health Metrics and Evaluation and thus unintentional discrepancies may exist + in the implementation of the 'Tariff' method. + date_publication: '2024-01-29' + bug_reports: https://github.com/verbal-autopsy-software/openVA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=openVA + url_git: https://github.com/verbal-autopsy-software/openVA +openxlsx: + version: 4.2.8 + title: Read, Write and Edit xlsx Files + maintainer: Jan Marvin Garbuszus + description: |- + Simplifies the creation of Excel .xlsx files by providing a + high level interface to writing, styling and editing worksheets. + Through the use of 'Rcpp', read/write times are comparable to the + 'xlsx' and 'XLConnect' packages with the added benefit of removing the + dependency on Java. + date_publication: '2025-01-25' + bug_reports: https://github.com/ycphs/openxlsx/issues + url: https://ycphs.github.io/openxlsx/index.html + url_cran: https://CRAN.R-project.org/package=openxlsx + url_git: https://github.com/ycphs/openxlsx +openxlsx2: + version: '1.13' + title: Read, Write and Edit 'xlsx' Files + maintainer: Jan Marvin Garbuszus + description: |- + Simplifies the creation of 'xlsx' files by + providing a high level interface to writing, styling and editing + worksheets. + date_publication: '2025-02-15' + bug_reports: https://github.com/JanMarvin/openxlsx2/issues + url: https://janmarvin.github.io/openxlsx2/ + url_cran: https://CRAN.R-project.org/package=openxlsx2 + url_git: https://github.com/JanMarvin/openxlsx2 +opera: + version: 1.2.0 + title: Online Prediction by Expert Aggregation + maintainer: Pierre Gaillard + description: |- + Misc methods to form online predictions, for regression-oriented + time-series, by combining a finite set of forecasts provided by the user. See + Cesa-Bianchi and Lugosi (2006) for an overview. + date_publication: '2021-12-06' + bug_reports: https://github.com/dralliag/opera/issues + url: http://pierre.gaillard.me/opera.html + url_cran: https://CRAN.R-project.org/package=opera + url_git: '' +operator.tools: + version: 1.6.3 + title: Utilities for Working with R's Operators + maintainer: Christopher Brown + description: |- + Provides a collection of utilities that allow programming with + R's operators. Routines allow classifying operators, + translating to and from an operator and its underlying function, and inverting + some operators (e.g. comparison operators), etc. All methods can be extended + to custom infix operators. + date_publication: '2017-02-28' + bug_reports: https://github.com/decisionpatterns/operator.tools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=operator.tools + url_git: https://github.com/decisionpatterns/operator.tools +operators: + version: 0.1-8 + title: Additional Binary Operators + maintainer: Romain Francois + description: |- + A set of binary operators for common tasks such as regex + manipulation. + date_publication: '2015-07-11' + bug_reports: https://github.com/romainfrancois/operators/issues + url: '' + url_cran: https://CRAN.R-project.org/package=operators + url_git: https://github.com/romainfrancois/operators +opGMMassessment: + version: '0.4' + title: Optimized Automated Gaussian Mixture Assessment + maintainer: Jorn Lotsch + description: Necessary functions for optimized automated evaluation of the number + and parameters of Gaussian mixtures in one-dimensional data. Various methods are + available for parameter estimation and for determining the number of modes in + the mixture. A detailed description of the methods ca ben found in Lotsch, J., + Malkusch, S. and A. Ultsch. (2022) . + date_publication: '2024-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=opGMMassessment + url_git: '' +OPI: + version: 3.0.2 + title: Open Perimetry Interface + maintainer: Andrew Turpin + description: 'Implementation of the Open Perimetry Interface (OPI) for simulating + and controlling visual field machines using R. The OPI is a standard for interfacing + with visual field testing machines (perimeters) first started as an open source + project with support of Haag-Streit in 2010. It specifies basic functions that + allow many visual field tests to be constructed. As of February 2022 it is fully + implemented on the Haag-Streit Octopus 900 and ''CrewT ImoVifa'' (''Topcon Tempo'') + with partial implementations on the Centervue Compass, Kowa AP 7000 and Android + phones. It also has a cousin: the R package ''visualFields'', which has tools + for analysing and manipulating visual field data.' + date_publication: '2024-07-09' + bug_reports: '' + url: https://opi.lei.org.au/ + url_cran: https://CRAN.R-project.org/package=OPI + url_git: '' +opinAr: + version: 1.0.0 + title: Argentina's Public Opinion Toolbox + maintainer: Juan Pablo Ruiz Nicolini + description: A toolbox for working with public opinion data from Argentina. It facilitates + access to microdata and the calculation of indicators of the Trust in Government + Index (ICG), prepared by the Torcuato Di Tella University. Although we will try + to document everything possible in English, by its very nature Spanish will be + the main language. El paquete fue pensado como una caja de herramientas para el + trabajo con datos de opinión pública de Argentina. El mismo facilita el acceso + a los microdatos y el cálculos de indicadores del Índice de Confianza en el Gobierno + (ICG), elaborado por la Universidad Torcuato Di Tella. + date_publication: '2024-03-05' + bug_reports: https://github.com/PoliticaArgentina/opinAr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=opinAr + url_git: https://github.com/PoliticaArgentina/opinAr +opitools: + version: 1.8.0 + title: Analyzing the Opinions in a Big Text Document + maintainer: Monsuru Adepeju + description: |- + Designed for performing impact analysis of + opinions in a digital text document (DTD). The + package allows a user to assess the extent to which a theme + or subject within a document impacts the overall opinion + expressed in the document. The package can be applied to a wide + range of opinion-based DTD, including commentaries on social media + platforms (such as 'Facebook', 'Twitter' and 'Youtube'), + online products reviews, and so on. + The utility of 'opitools' was originally demonstrated + in Adepeju and Jimoh (2021) in the + assessment of COVID-19 impacts on neighbourhood policing using + Twitter data. Further examples can be found in the vignette of + the package. + date_publication: '2021-07-29' + bug_reports: https://github.com/MAnalytics/opitools/issues/1 + url: '' + url_cran: https://CRAN.R-project.org/package=opitools + url_git: https://github.com/MAnalytics/opitools +OPL: + version: 1.0.2 + title: Optimal Policy Learning + maintainer: Federico Brogi + description: |- + Provides functions for optimal policy learning in socioeconomic applications helping users to learn the most effective policies based + on data in order to maximize empirical welfare. Specifically, 'OPL' allows to find "treatment assignment rules" that maximize the overall + welfare, defined as the sum of the policy effects estimated over all the policy beneficiaries. Documentation about 'OPL' is provided by + several international articles via Athey et al (2021, ), Kitagawa et al (2018, ), + Cerulli (2022, ), the paper by Cerulli (2021, ) + and the book by Gareth et al (2013, ). + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OPL + url_git: '' +Opportunistic: + version: '1.2' + title: |- + Routing Distribution, Broadcasts, Transmissions and Receptions + in an Opportunistic Network + maintainer: Christian E. Galarza + description: Computes the routing distribution, the expectation of the number of + broadcasts, transmissions and receptions considering an Opportunistic transport + model. It provides theoretical results and also estimated values based on Monte + Carlo simulations. + date_publication: '2017-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Opportunistic + url_git: '' +oppr: + version: 1.0.4 + title: Optimal Project Prioritization + maintainer: Jeffrey O Hanson + description: |- + A decision support tool for prioritizing conservation projects. + Prioritizations can be developed by maximizing expected feature richness, + expected phylogenetic diversity, the number of features that meet + persistence targets, or identifying a set of projects that meet persistence + targets for minimal cost. Constraints (e.g. lock in specific actions) and + feature weights can also be specified to further customize prioritizations. + After defining a project prioritization problem, solutions can be obtained + using exact algorithms, heuristic algorithms, or random processes. In + particular, it is recommended to install the 'Gurobi' optimizer (available + from ) because it can identify optimal solutions + very quickly. Finally, methods are provided for comparing different + prioritizations and evaluating their benefits. For more information, see + Hanson et al. (2019) . + date_publication: '2022-09-08' + bug_reports: https://github.com/prioritizr/oppr/issues + url: https://prioritizr.github.io/oppr/ + url_cran: https://CRAN.R-project.org/package=oppr + url_git: '' +OPSR: + version: 0.1.2 + title: Ordinal Probit Switching Regression + maintainer: Daniel Heimgartner + description: |- + Estimates ordinal probit switching regression models - a Heckman + type selection model with an ordinal selection and continuous outcomes. + Different model specifications are allowed for each treatment/regime. For + more details on the method, see Wang & Mokhtarian (2024) + or Chiburis & Lokshin (2007) . + date_publication: '2024-11-01' + bug_reports: https://github.com/dheimgartner/OPSR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OPSR + url_git: https://github.com/dheimgartner/OPSR +Opt5PL: + version: 0.1.1 + title: Optimal Designs for the 5-Parameter Logistic Model + maintainer: Seung Won Hyun + description: Obtain and evaluate various optimal designs for the 3, 4, and 5-parameter + logistic models. The optimal designs are obtained based on the numerical algorithm + in Hyun, Wong, Yang (2018) . + date_publication: '2018-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Opt5PL + url_git: '' +optband: + version: 0.2.2 + title: '''surv'' Object Confidence Bands Optimized by Area' + maintainer: Sam Tracy + description: |- + Given a certain coverage level, obtains simultaneous confidence + bands for the survival and cumulative hazard functions such that the area + between is minimized. Produces an approximate solution based on local time + arguments. + date_publication: '2023-03-31' + bug_reports: https://github.com/seasamgo/optband/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optband + url_git: https://github.com/seasamgo/optband +optbdmaeAT: + version: 1.0.1 + title: Optimal Block Designs for Two-Colour cDNA Microarray Experiments + maintainer: Dibaba Bayisa Gemechu + description: Computes A-, MV-, D- and E-optimal or near-optimal block designs for + two-colour cDNA microarray experiments using the linear fixed effects and mixed + effects models where the interest is in a comparison of all possible elementary + treatment contrasts. The algorithms used in this package are based on the treatment + exchange and array exchange algorithms of Debusho, Gemechu and Haines (2016, unpublished). + The package also provides an optional method of using the graphical user interface + (GUI) R package tcltk to ensure that it is user friendly. + date_publication: '2017-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optbdmaeAT + url_git: '' +optbin: + version: '1.4' + title: Optimal Binning of Data + maintainer: Greg Kreider + description: |- + Defines thresholds for breaking data into a number of + discrete levels, minimizing the (mean) squared error within all bins. + date_publication: '2024-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optbin + url_git: '' +optBiomarker: + version: 1.0-28 + title: |- + Estimation of Optimal Number of Biomarkers for Two-Group + Microarray Based Classifications at a Given Error Tolerance + Level for Various Classification Rules + maintainer: Mizanur Khondoker + description: |- + Estimates optimal number of biomarkers for two-group + classification based on microarray data. + date_publication: '2021-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optBiomarker + url_git: '' +OptCirClust: + version: 0.0.4 + title: |- + Circular, Periodic, or Framed Data Clustering: Fast, Optimal, + and Reproducible + maintainer: Joe Song + description: |- + Fast, optimal, and reproducible clustering algorithms for + circular, periodic, or framed data. The algorithms introduced here + are based on a core algorithm for optimal framed clustering the authors + have developed (Debnath & Song 2021) . + The runtime of these algorithms is O(K N log^2 N), where K is the number + of clusters and N is the number of circular data points. On a desktop + computer using a single processor core, millions of data points can be + grouped into a few clusters within seconds. One can apply the algorithms + to characterize events along circular DNA molecules, circular RNA + molecules, and circular genomes of bacteria, chloroplast, and + mitochondria. One can also cluster climate data along any given + longitude or latitude. Periodic data clustering can be formulated as + circular clustering. The algorithms offer a general high-performance + solution to circular, periodic, or framed data clustering. + date_publication: '2021-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptCirClust + url_git: '' +optDesignSlopeInt: + version: 1.1.1 + title: |- + Optimal Designs for Estimating the Slope Divided by the + Intercept + maintainer: Adam Kapelner + description: |- + Aids practitioners to optimally design experiments + that measure the slope divided by the intercept and provides confidence intervals for the ratio. + date_publication: '2023-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optDesignSlopeInt + url_git: '' +OPTeCD: + version: 1.0.0 + title: Optimal Partial Tetra-Allele Cross Designs + maintainer: Ashutosh Dalal + description: Tetra-allele cross often referred as four-way cross or double cross + or four-line cross are those type of mating designs in which every cross is obtained + by mating amongst four inbred lines. A tetra-allele cross can be obtained by crossing + the resultant of two unrelated diallel crosses. A common triallel cross involving + four inbred lines A, B, C and D can be symbolically represented as (A X B) X (C + X D) or (A, B, C, D) or (A B C D) etc. Tetra-allele cross can be broadly categorized + as Complete Tetra-allele Cross (CTaC) and Partial Tetra-allele Crosses (PTaC). + Rawlings and Cockerham (1962) firstly introduced and gave + the method of analysis for tetra-allele cross hybrids using the analysis method + of single cross hybrids under the assumption of no linkage. The set of all possible + four-way mating between several genotypes (individuals, clones, homozygous lines, + etc.) leads to a CTaC. If there are N number of inbred lines involved in a CTaC, + the the total number of crosses, T = N*(N-1)*(N-2)*(N-3)/8. When more number of + lines are to be considered, the total number of crosses in CTaC also increases. + Thus, it is almost impossible for the investigator to carry out the experimentation + with limited available resource material. This situation lies in taking a fraction + of CTaC with certain underlying properties, known as PTaC. + date_publication: '2024-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OPTeCD + url_git: '' +optedr: + version: 2.2.0 + title: Calculating Optimal and D-Augmented Designs + maintainer: Carlos de la Calle-Arroyo + description: Calculates D-, Ds-, A-, I- and L-optimal designs for non-linear models, + via an implementation of the cocktail algorithm (Yu, 2011, ). + Compares designs via their efficiency, and augments any design with a controlled + efficiency. An efficient rounding function has been provided to transform approximate + designs to exact designs. + date_publication: '2025-02-11' + bug_reports: https://github.com/Kezrael/optedr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optedr + url_git: https://github.com/kezrael/optedr +optextras: + version: 2019-12.4 + title: Tools to Support Optimization Possibly with Bounds and Masks + maintainer: John C Nash + description: |- + Tools to assist in safely applying user generated objective and + derivative function to optimization programs. These are primarily function + minimization methods with at most bounds and masks on the parameters. + Provides a way to check the basic computation of objective functions that + the user provides, along with proposed gradient and Hessian functions, + as well as to wrap such functions to avoid failures when inadmissible parameters + are provided. Check bounds and masks. Check scaling or optimality conditions. + Perform an axial search to seek lower points on the objective function surface. + Includes forward, central and backward gradient approximation codes. + date_publication: '2019-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optextras + url_git: '' +OptGS: + version: '1.2' + title: Near-Optimal Group-Sequential Designs for Continuous Outcomes + maintainer: James Wason + description: Optimal group-sequential designs minimise some function of the expected + and maximum sample size whilst controlling the type I error rate and power at + a specified level. 'OptGS' provides functions to quickly search for near-optimal + group-sequential designs for normally distributed outcomes. The methods used are + described in Wason, JMS (2015) . + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptGS + url_git: '' +OptHedging: + version: '1.0' + title: |- + Estimation of value and hedging strategy of call and put + options. + maintainer: Bruno Remillard + description: Estimation of value and hedging strategy of call and put options, based + on optimal hedging and Monte Carlo method, from Chapter 3 of 'Statistical Methods + for Financial Engineering', by Bruno Remillard, CRC Press, (2013). + date_publication: '2013-10-11' + bug_reports: '' + url: http://www.brunoremillard.com + url_cran: https://CRAN.R-project.org/package=OptHedging + url_git: '' +OptHoldoutSize: + version: 0.1.0.0 + title: |- + Estimation of Optimal Size for a Holdout Set for Updating a + Predictive Score + maintainer: James Liley + description: 'Predictive scores must be updated with care, because actions taken + on the basis of existing risk scores causes bias in risk estimates from the updated + score. A holdout set is a straightforward way to manage this problem: a proportion + of the population is ''held-out'' from computation of the previous risk score. + This package provides tools to estimate a size for this holdout set and associated + errors. Comprehensive vignettes are included. Please see: Haidar-Wehbe S, Emerson + SR, Aslett LJM, Liley J (2022) for details of methods.' + date_publication: '2022-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptHoldoutSize + url_git: '' +optic: + version: 1.0.1 + title: Simulation Tool for Causal Inference Using Longitudinal Data + maintainer: Pedro Nascimento de Lima + description: |- + Implements a simulation study to assess the strengths and + weaknesses of causal inference methods for estimating policy effects + using panel data. See Griffin et al. (2021) + and Griffin et al. (2022) + for a description of our methods. + date_publication: '2023-08-08' + bug_reports: https://github.com/randcorporation/optic/issues + url: https://randcorporation.github.io/optic/ + url_cran: https://CRAN.R-project.org/package=optic + url_git: https://github.com/randcorporation/optic +optical: + version: 1.7.1 + title: Optimal Item Calibration + maintainer: Mahmood Ul Hassan + description: |- + The restricted optimal design method is implemented to optimally + allocate a set of items that require calibration to a group of examinees. + The optimization process is based on the method described in detail by + Ul Hassan and Miller in their works published in (2019) + and (2021) . + To use the method, preliminary item characteristics must be provided as input. + These characteristics can either be expert guesses or based on previous + calibration with a small number of examinees. The item characteristics + should be described in the form of parameters for an Item Response + Theory (IRT) model. These models can include the Rasch model, the + 2-parameter logistic model, the 3-parameter logistic model, or a mixture + of these models. The output consists of a set of rules for each item + that determine which examinees should be assigned to each item. The + efficiency or gain achieved through the optimal design is quantified by + comparing it to a random allocation. This comparison allows for an + assessment of how much improvement or advantage is gained by using the + optimal design approach. This work was supported by the Swedish Research Council + (Vetenskapsrådet) Grant 2019-02706. + date_publication: '2023-05-25' + bug_reports: https://github.com/scenic555/optical/issues + url: https://scenic555.github.io/optical/ + url_cran: https://CRAN.R-project.org/package=optical + url_git: https://github.com/scenic555/optical +opticskxi: + version: 1.2.0 + title: OPTICS K-Xi Density-Based Clustering + maintainer: Thomas Charlon + description: Density-based clustering methods are well adapted to the clustering + of high-dimensional data and enable the discovery of core groups of various shapes + despite large amounts of noise. This package provides a novel density-based cluster + extraction method, OPTICS k-Xi, and a framework to compare k-Xi models using distance-based + metrics to investigate datasets with unknown number of clusters. The vignette + first introduces density-based algorithms with simulated datasets, then presents + and evaluates the k-Xi cluster extraction method. Finally, the models comparison + framework is described and experimented on 2 genetic datasets to identify groups + and their discriminating features. The k-Xi algorithm is a novel OPTICS cluster + extraction method that specifies directly the number of clusters and does not + require fine-tuning of the steepness parameter as the OPTICS Xi method. Combined + with a framework that compares models with varying parameters, the OPTICS k-Xi + method can identify groups in noisy datasets with unknown number of clusters. + Results on summarized genetic data of 1,200 patients are in Charlon T. (2019) + . + date_publication: '2025-02-26' + bug_reports: https://gitlab.com/thomaschln/opticskxi/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=opticskxi + url_git: https://gitlab.com/thomaschln/opticskxi +opticut: + version: 0.1-3 + title: |- + Likelihood Based Optimal Partitioning and Indicator Species + Analysis + maintainer: Peter Solymos + description: |- + Likelihood based optimal partitioning and indicator + species analysis. Finding the best binary partition for each species + based on model selection, with the possibility to take into account + modifying/confounding variables as described + in Kemencei et al. (2014) . + The package implements binary and multi-level response models, + various measures of uncertainty, Lorenz-curve based thresholding, + with native support for parallel computations. + date_publication: '2024-05-21' + bug_reports: https://github.com/psolymos/opticut/issues + url: '' + url_cran: https://CRAN.R-project.org/package=opticut + url_git: https://github.com/psolymos/opticut +optifunset: + version: '1.0' + title: Set Options if Unset + maintainer: Nicholas Hamilton + description: A single function 'options.ifunset(...)' is contained herewith, which + allows the user to set a global option ONLY if it is not already set. By this + token, for package maintainers this function can be used in preference to the + standard 'options(...)' function, making provision for THEIR end user to place + 'options(...)' directives within their '.Rprofile' file, which will not be overridden + at the point when a package is loaded. + date_publication: '2015-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optifunset + url_git: '' +optigrab: + version: 0.9.2.1 + title: Command-Line Parsing for an R World + maintainer: Christopher Brown + description: |- + Parse options from the command-line using a simple, clean syntax. + It requires little or no specification and supports short and long options, + GNU-, Java- or Microsoft- style syntaxes, verb commands and more. + date_publication: '2019-01-07' + bug_reports: https://github.com/decisionpatterns/optigrab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optigrab + url_git: https://github.com/decisionpatterns/optigrab +optim.functions: + version: '0.1' + title: Standard Benchmark Optimization Functions + maintainer: Thomas Torsney-Weir + description: |- + A set of standard benchmark optimization functions for R and + a common interface to sample them. + date_publication: '2017-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optim.functions + url_git: '' +OptimalCutpoints: + version: 1.1-5 + title: Computing Optimal Cutpoints in Diagnostic Tests + maintainer: Monica Lopez Raton + description: Computes optimal cutpoints for diagnostic tests or continuous markers. + Various approaches for selecting optimal cutoffs have been implemented, including + methods based on cost-benefit analysis and diagnostic test accuracy measures (Sensitivity/Specificity, + Predictive Values and Diagnostic Likelihood Ratios). Numerical and graphical output + for all methods is easily obtained. + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptimalCutpoints + url_git: '' +OptimalDesign: + version: 1.0.1 + title: A Toolbox for Computing Efficient Designs of Experiments + maintainer: Lenka Filova + description: Algorithms for D-, A-, I-, and c-optimal designs. Some of the functions + in this package require the 'gurobi' software and its accompanying R package. + For their installation, please follow the instructions at + and the file gurobi_inst.txt, respectively. + date_publication: '2019-12-02' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=OptimalDesign + url_git: '' +optimall: + version: 1.1.1 + title: Allocate Samples Among Strata + maintainer: Jasper Yang + description: Functions for the design process of survey sampling, with specific + tools for multi-wave and multi-phase designs. Perform optimum allocation using + Neyman (1934) or Wright (2012) + allocation, split strata based on quantiles or values of known variables, randomly + select samples from strata, allocate sampling waves iteratively, and organize + a complex survey design. Also includes a Shiny application for observing the effects + of different strata splits. + date_publication: '2024-06-03' + bug_reports: https://github.com/yangjasp/optimall/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optimall + url_git: https://github.com/yangjasp/optimall +OptimalRerandExpDesigns: + version: '1.1' + title: Optimal Rerandomization Experimental Designs + maintainer: Adam Kapelner + description: |- + This is a tool to find the optimal rerandomization threshold in non-sequential experiments. We offer three procedures based + on assumptions made on the residuals distribution: (1) normality assumed (2) excess kurtosis assumed (3) entire distribution assumed. + Illustrations are included. Also included is a routine to unbiasedly estimate Frobenius norms of variance-covariance matrices. + Details of the method can be found in "Optimal Rerandomization via a Criterion that Provides Insurance Against Failed Experiments" + Adam Kapelner, Abba M. Krieger, Michael Sklar and David Azriel (2020) . + date_publication: '2021-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptimalRerandExpDesigns + url_git: https://github.com/kapelner/OptimalRerandExpDesigns +OptimalSurrogate: + version: '1.0' + title: Model Free Approach to Quantifying Surrogacy + maintainer: Layla Parast + description: Identifies an optimal transformation of a surrogate marker such that + the proportion of treatment effect explained can be inferred based on the transformation + of the surrogate and nonparametrically estimates two model-free quantities of + this proportion. Details are described in Wang et al (2020) . + date_publication: '2022-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptimalSurrogate + url_git: '' +optimalThreshold: + version: '1.0' + title: Bayesian Methods for Optimal Threshold Estimation + maintainer: Yoann Blangero + description: Functions to estimate the optimal threshold of diagnostic markers or + treatment selection markers. The optimal threshold is the marker value that maximizes + the utility of the marker based-strategy (for diagnostic or treatment selection) + in a given population. The utility function depends on the type of marker (diagnostic + or treatment selection), but always takes into account the preferences of the + patients or the physician in the decision process. For estimating the optimal + threshold, ones must specify the distributions of the marker in different groups + (defined according to the type of marker, diagnostic or treatment selection) and + provides data to estimate the parameters of these distributions. Ones must also + provide some features of the target populations (disease prevalence or treatment + efficacies) as well as the preferences of patients or physicians. The functions + rely on Bayesian inference which helps producing several indicators derived from + the optimal threshold. See Blangero, Y, Rabilloud, M, Ecochard, R, and Subtil, + F (2019) for the original article that describes + the estimation method for treatment selection markers and Subtil, F, and Rabilloud, + M (2019) for diagnostic markers. + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimalThreshold + url_git: '' +OptimalTiming: + version: 0.1.0 + title: Optimal Timing Identification + maintainer: Xiao Lin + description: Identify the optimal timing for new treatment initiation during multiple + state disease transition, including multistate model fitting, simulation of mean + residual lifetime for a given transition state, and estimation of confidence interval. + The method is referred to de Wreede, L., Fiocco, M., & Putter, H. (2011) . + date_publication: '2017-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptimalTiming + url_git: '' +OptimaRegion: + version: '1.2' + title: Confidence Regions for Optima of Response Surfaces + maintainer: Enrique del Castillo + description: Computes confidence regions on the location of response surface optima. + Response surface models can be up to cubic polynomial models in up to 5 controllable + factors, or Thin Plate Spline models in 2 controllable factors. + date_publication: '2023-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptimaRegion + url_git: '' +optimbase: + version: 1.0-10 + title: R Port of the 'Scilab' Optimbase Module + maintainer: Sebastien Bihorel + description: |- + Provides a set of commands to manage an abstract + optimization method. The goal is to provide a building block + for a large class of specialized optimization methods. This + package manages: the number of variables, the minimum and + maximum bounds, the number of non linear inequality + constraints, the cost function, the logging system, various + termination criteria, etc... + date_publication: '2022-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimbase + url_git: '' +optimCheck: + version: 1.0.1 + title: Graphical and Numerical Checks for Mode-Finding Routines + maintainer: Martin Lysy + description: Tools for checking that the output of an optimization algorithm is + indeed at a local mode of the objective function. This is accomplished graphically + by calculating all one-dimensional "projection plots" of the objective function, + i.e., varying each input variable one at a time with all other elements of the + potential solution being fixed. The numerical values in these plots can be readily + extracted for the purpose of automated and systematic unit-testing of optimization + routines. + date_publication: '2024-09-05' + bug_reports: https://github.com/mlysy/optimCheck/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optimCheck + url_git: https://github.com/mlysy/optimCheck +optimg: + version: 0.1.2 + title: General-Purpose Gradient-Based Optimization + maintainer: Vithor Rosa Franco + description: |- + Provides general purpose tools for helping users to implement steepest + gradient descent methods for function optimization; for details see + Ruder (2016) . Currently, the Steepest 2-Groups + Gradient Descent and the Adaptive Moment Estimation (Adam) are the + methods implemented. Other methods will be implemented in the future. + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimg + url_git: https://github.com/vthorrf/optimg +optimization: + version: 1.0-9 + title: |- + Flexible Optimization of Complex Loss Functions with State and + Parameter Space Constraints + maintainer: Kai Husmann + description: |- + Flexible optimizer with numerous input specifications for detailed + parameterisation. Designed for complex loss functions with state and + parameter space constraints. Visualization tools for validation and analysis + of the convergence are included. + date_publication: '2022-02-15' + bug_reports: https://github.com/kaihusmann/optimization/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optimization + url_git: https://github.com/kaihusmann/optimization +optimizeR: + version: 1.1.2 + title: Unified Framework for Numerical Optimizers + maintainer: Lennart Oelschläger + description: |- + Provides a unified object-oriented framework for numerical + optimizers in R. Allows for both minimization and maximization with any + optimizer, optimization over more than one function argument, measuring of + computation time, setting a time limit for long optimization tasks. + date_publication: '2024-11-27' + bug_reports: https://github.com/loelschlaeger/optimizeR/issues + url: https://loelschlaeger.de/optimizeR/ + url_cran: https://CRAN.R-project.org/package=optimizeR + url_git: https://github.com/loelschlaeger/optimizeR/ +optimLanduse: + version: 1.2.1 + title: Robust Land-Use Optimization + maintainer: Kai Husmann + description: Robust multi-criteria land-allocation optimization that explicitly + accounts for the uncertainty of the indicators in the objective function. Solves + the problem of allocating scarce land to various land-use options with regard + to multiple, coequal indicators. The method aims to find the land allocation that + represents the indicator composition with the best possible trade-off under uncertainty. + optimLanduse includes the actual optimization procedure as described by Knoke + et al. (2016) and the post-hoc calculation of the portfolio + performance as presented by Gosling et al. (2020) . + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimLanduse + url_git: https://github.com/Forest-Economics-Goettingen/optimLanduse/ +OptimModel: + version: 2.0-1 + title: |- + Perform Nonlinear Regression Using 'optim' as the Optimization + Engine + maintainer: Steven Novick + description: 'A wrapper for ''optim'' for nonlinear regression problems; see Nocedal + J and Write S (2006, ISBN: 978-0387-30303-1). Performs ordinary least squares + (OLS), iterative re-weighted least squares (IRWLS), and maximum likelihood (MLE). + Also includes the robust outlier detection (ROUT) algorithm; see Motulsky, H and + Brown, R (2006).' + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptimModel + url_git: '' +optimos.prime: + version: 0.1.2 + title: |- + Optimos Prime Helps Calculate Autoecological Data for Biological + Species + maintainer: Joaquín Cochero + description: |- + Calculates autoecological data (optima and tolerance ranges) of a biological species + given an environmental matrix. The package calculates by weighted averaging, using the number of occurrences to adjust the + tolerance assigned to each taxon to estimate optima and tolerance range in cases where taxa + have unequal occurrences. See the detailed methodology by Birks et al. (1990) , and a + case example by Potapova and Charles (2003) . + date_publication: '2020-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimos.prime + url_git: '' +optimParallel: + version: 1.0-2 + title: Parallel Version of the L-BFGS-B Optimization Method + maintainer: Florian Gerber + description: Provides a parallel version of the L-BFGS-B method of optim(). The + main function of the package is optimParallel(), which has the same usage and + output as optim(). Using optimParallel() can significantly reduce the optimization + time. + date_publication: '2021-02-11' + bug_reports: https://github.com/florafauna/optimParallel-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optimParallel + url_git: https://github.com/florafauna/optimParallel-R +optimsimplex: + version: 1.0-8 + title: R Port of the 'Scilab' Optimsimplex Module + maintainer: Sebastien Bihorel + description: |- + Provides a building block for optimization algorithms + based on a simplex. The 'optimsimplex' package may be used in the + following optimization methods: the simplex method of Spendley + et al. (1962) , the method of + Nelder and Mead (1965) , Box's algorithm for + constrained optimization (1965) , the + multi-dimensional search by Torczon (1989) + , etc... + date_publication: '2022-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimsimplex + url_git: '' +optimStrat: + version: '2.4' + title: Choosing the Sample Strategy + maintainer: Edgar Bueno + description: Intended to assist in the choice of the sampling strategy to implement + in a survey. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optimStrat + url_git: '' +optimus: + version: 0.2.0 + title: Model Based Diagnostics for Multivariate Cluster Analysis + maintainer: Mitchell Lyons + description: |- + Assessment and diagnostics for comparing competing + clustering solutions, using predictive models. The main intended + use is for comparing clustering/classification solutions of + ecological data (e.g. presence/absence, counts, ordinal scores) to + 1) find an optimal partitioning solution, 2) identify + characteristic species and 3) refine a classification by merging + clusters that increase predictive performance. However, in a more + general sense, this package can do the above for any set of + clustering solutions for i observations of j variables. + date_publication: '2018-01-16' + bug_reports: https://github.com/mitchest/optimus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optimus + url_git: https://github.com/mitchest/optimus/ +optimx: + version: 2024-12.2 + title: Expanded Replacement and Extension of the 'optim' Function + maintainer: John C Nash + description: |- + Provides a replacement and extension of the optim() + function to call to several function minimization codes in R in a single + statement. These methods handle smooth, possibly box constrained functions + of several or many parameters. Note that function 'optimr()' was prepared to + simplify the incorporation of minimization codes going forward. Also implements some + utility codes and some extra solvers, including safeguarded Newton methods. + Many methods previously separate are now included here. + This is the version for CRAN. + date_publication: '2024-12-10' + bug_reports: https://github.com/nashjc/optimx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optimx + url_git: https://github.com/nashjc/optimx +optional: + version: 2.0.1 + title: Optional Types and Pattern Matching + maintainer: Antoine Champion + description: Introduces optional types with some() and none, as well as match_with() + from functional languages. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optional + url_git: '' +OptionPricing: + version: 0.1.2 + title: Option Pricing with Efficient Simulation Algorithms + maintainer: Wolfgang Hormann + description: Efficient Monte Carlo Algorithms for the price and the sensitivities + of Asian and European Options under Geometric Brownian Motion. + date_publication: '2023-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptionPricing + url_git: '' +options: + version: 0.3.0 + title: Simple, Consistent Package Options + maintainer: Doug Kelkhoff + description: |- + Simple mechanisms for defining and interpreting package options. Provides + helpers for interpreting environment variables, global options, defining + default values and more. + date_publication: '2024-12-12' + bug_reports: https://codeberg.org/dgkf/options/issues + url: https://dgkf.github.io/options/ + url_cran: https://CRAN.R-project.org/package=options + url_git: '' +optionstrat: + version: 1.4.1 + title: |- + Utilizes the Black-Scholes Option Pricing Model to Perform + Strategic Option Analysis and Plot Option Strategies + maintainer: John T. Buynak + description: |- + Utilizes the Black-Scholes-Merton option pricing model to + calculate key option analytics and perform graphical analysis of various option strategies. + Provides functions to calculate the option premium and option + greeks of European-style options. + date_publication: '2019-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optionstrat + url_git: '' +optiscale: + version: 1.2.3 + title: Optimal Scaling + maintainer: Dave Armstrong + description: |- + Optimal scaling of a data vector, relative to a set of targets, is + obtained through a least-squares transformation subject to appropriate measurement + constraints. The targets are usually predicted values from a statistical + model. If the data are nominal level, then the transformation must be + identity-preserving. If the data are ordinal level, then the + transformation must be monotonic. If the data are discrete, then tied data + values must remain tied in the optimal transformation. If the data are + continuous, then tied data values can be untied in the optimal + transformation. + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optiscale + url_git: '' +optiSel: + version: 2.0.9 + title: Optimum Contribution Selection and Population Genetics + maintainer: Robin Wellmann + description: A framework for the optimization of breeding programs via optimum contribution + selection and mate allocation. An easy to use set of function for computation + of optimum contributions of selection candidates, and of the population genetic + parameters to be optimized. These parameters can be estimated using pedigree or + genotype information, and include kinships, kinships at native haplotype segments, + and breed composition of crossbred individuals. They are suitable for managing + genetic diversity, removing introgressed genetic material, and accelerating genetic + gain. Additionally, functions are provided for computing genetic contributions + from ancestors, inbreeding coefficients, the native effective size, the native + genome equivalent, pedigree completeness, and for preparing and plotting pedigrees. + The methods are described in:\n Wellmann, R., and Pfeiffer, I. (2009) .\n + Wellmann, R., and Bennewitz, J. (2011) .\n Wellmann, + R., Hartwig, S., Bennewitz, J. (2012) .\n de Cara, + M. A. R., Villanueva, B., Toro, M. A., Fernandez, J. (2013) .\n + Wellmann, R., Bennewitz, J., Meuwissen, T.H.E. (2014) .\n + Wellmann, R. (2019) . + date_publication: '2024-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optiSel + url_git: '' +optiSolve: + version: '1.0' + title: Linear, Quadratic, and Rational Optimization + maintainer: Robin Wellmann + description: Solver for linear, quadratic, and rational programs with linear, quadratic, + and rational constraints. A unified interface to different R packages is provided. + Optimization problems are transformed into equivalent formulations and solved + by the respective package. For example, quadratic programming problems with linear, + quadratic and rational constraints can be solved by augmented Lagrangian minimization + using package 'alabama', or by sequential quadratic programming using solver 'slsqp'. Alternatively, + they can be reformulated as optimization problems with second order cone constraints + and solved with package 'cccp'. + date_publication: '2021-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optiSolve + url_git: '' +optistock: + version: 0.0.2 + title: Determine Optimum Stocking Times Used in Fishery Enhancements + maintainer: Paul Frater + description: |- + A collection of functions that aid in calculating the optimum + time to stock hatchery reared fish into a body of water given the growth, + mortality and cost of raising a particular number of individuals to a certain + length. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optistock + url_git: '' +OptM: + version: 0.1.8 + title: Estimating the Optimal Number of Migration Edges from 'Treemix' + maintainer: Robert Fitak + description: |- + The popular population genetic software 'Treemix' by + 'Pickrell and Pritchard' (2012) + estimates the number of migration edges on a population tree. + However, it can be difficult to determine the number of migration + edges to include. Previously, it was customary to stop adding migration + edges when 99.8% of variation in the data was explained, but 'OptM' + automates this process using an ad hoc statistic based on the + second-order rate of change in the log likelihood. 'OptM' also + has added functionality for various threshold modeling + to compare with the ad hoc statistic. + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptM + url_git: '' +optmatch: + version: 0.10.8 + title: Functions for Optimal Matching + maintainer: Josh Errickson + description: |- + Distance based bipartite matching using minimum cost flow, oriented + to matching of treatment and control groups in observational studies ('Hansen' + and 'Klopfer' 2006 ). Routines are provided to + generate distances from generalised linear models (propensity score + matching), formulas giving variables on which to limit matched distances, + stratified or exact matching directives, or calipers, alone or in + combination. + date_publication: '2024-09-19' + bug_reports: https://github.com/markmfredrickson/optmatch/issues + url: http://optmat.ch + url_cran: https://CRAN.R-project.org/package=optmatch + url_git: https://github.com/markmfredrickson/optmatch +optparse: + version: 1.7.5 + title: Command Line Option Parser + maintainer: Trevor L. Davis + description: |- + A command line parser inspired by Python's 'optparse' library to + be used with Rscript to write "#!" shebang scripts that accept short and + long flag/options. + date_publication: '2024-04-16' + bug_reports: https://github.com/trevorld/r-optparse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optparse + url_git: https://github.com/trevorld/r-optparse +optR: + version: 1.2.5 + title: Optimization Toolbox for Solving Linear Systems + maintainer: Prakash + description: |- + Solves linear systems of form Ax=b via Gauss elimination, + LU decomposition, Gauss-Seidel, Conjugate Gradient Method (CGM) and Cholesky methods. + date_publication: '2016-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optR + url_git: '' +optrcdmaeAT: + version: 1.0.0 + title: |- + Optimal Row-Column Designs for Two-Colour cDNA Microarray + Experiments + maintainer: Dibaba Bayisa Gemechu + description: Computes A-, MV-, D- and E-optimal or near-optimal row-column designs + for two-colour cDNA microarray experiments using the linear fixed effects and + mixed effects models where the interest is in a comparison of all pairwise treatment + contrasts. The algorithms used in this package are based on the array exchange + and treatment exchange algorithms adopted from Debusho, Gemechu and Haines (2016, + unpublished) algorithms after adjusting for the row-column designs setup. The + package also provides an optional method of using the graphical user interface + (GUI) R package tcltk to ensure that it is user friendly. + date_publication: '2017-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optrcdmaeAT + url_git: '' +optrefine: + version: 1.1.0 + title: Optimally Refine Strata + maintainer: Katherine Brumberg + description: Splits initial strata into refined strata that optimize covariate balance. + For more information, please email the author for a copy of the accompanying manuscript. + To solve the linear program, the 'Gurobi' commercial optimization software is + recommended, but not required. The 'gurobi' R package can be installed following + the instructions at . + date_publication: '2023-04-18' + bug_reports: https://github.com/kkbrum/optrefine/issues + url: https://kkbrum.github.io/optrefine/ + url_cran: https://CRAN.R-project.org/package=optrefine + url_git: https://github.com/kkbrum/optrefine +optRF: + version: 1.1.0 + title: |- + Optimising Random Forest Stability by Determining the Optimal + Number of Trees + maintainer: Thomas Martin Lange + description: Calculating the stability of random forest with certain numbers of + trees. The non-linear relationship between stability and numbers of trees is described + using a logistic regression model and used to estimate the optimal number of trees. + date_publication: '2025-02-03' + bug_reports: https://github.com/tmlange/optRF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=optRF + url_git: https://github.com/tmlange/optRF +OPTS: + version: '0.1' + title: Optimization via Subsampling (OPTS) + maintainer: Mihai Giurcanu + description: Subsampling based variable selection for low dimensional generalized + linear models. The methods repeatedly subsample the data minimizing an information + criterion (AIC/BIC) over a sequence of nested models for each subsample. Marinela + Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable + selection for generalized linear models. + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OPTS + url_git: '' +OptSig: + version: '2.2' + title: |- + Optimal Level of Significance for Regression and Other + Statistical Tests + maintainer: Jae H. Kim + description: |- + The optimal level of significance is calculated based on a decision-theoretic approach. The optimal level is chosen so that the expected loss from hypothesis testing is minimized. A range of statistical tests are covered, including the test for the population mean, population proportion, and a linear restriction in a multiple regression model. + The details are covered in Kim and Choi (2020) , and Kim (2021) . + date_publication: '2022-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OptSig + url_git: '' +OPTtesting: + version: 1.0.0 + title: Optimal Testing + maintainer: Lijia Wang + description: Optimal testing under general dependence. The R package implements + procedures proposed in Wang, Han, and Tong (2022). The package includes parameter + estimation procedures, the computation for the posterior probabilities, and the + testing procedure. + date_publication: '2022-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OPTtesting + url_git: '' +optweight: + version: 0.2.5 + title: Targeted Stable Balancing Weights Using Optimization + maintainer: Noah Greifer + description: Use optimization to estimate weights that balance covariates for binary, + multinomial, and continuous treatments in the spirit of Zubizarreta (2015) . + The degree of balance can be specified for each covariate. In addition, sampling + weights can be estimated that allow a sample to generalize to a population specified + with given target moments of covariates. + date_publication: '2019-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=optweight + url_git: '' +opusminer: + version: 0.1-1 + title: OPUS Miner Algorithm for Filtered Top-k Association Discovery + maintainer: Christoph Bergmeir + description: Provides a simple R interface to the OPUS Miner algorithm (implemented + in C++) for finding the top-k productive, non-redundant itemsets from transaction + data. The OPUS Miner algorithm uses the OPUS search algorithm to efficiently + discover the key associations in transaction data, in the form of self-sufficient + itemsets, using either leverage or lift. See + for more information in relation to the OPUS Miner algorithm. + date_publication: '2020-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=opusminer + url_git: '' +OralOpioids: + version: 2.0.4 + title: Retrieving Oral Opioid Information + maintainer: Ankona Banerjee + description: |- + Provides details such as Morphine Equivalent Dose (MED), + brand name and opioid content which are calculated of all oral opioids + authorized for sale by Health Canada and the FDA based on their Drug Identification Number (DIN) or National Drug Code (NDC). + MEDs are calculated based on recommendations by Canadian Institute for Health Information (CIHI) and Von Korff et al (2008) + and information obtained from Health Canada's Drug Product Database's monthly data dump or FDA Daily database for Canadian and US databases respectively. + Please note in no way should output from this package be a substitute for medical advise. + All medications should only be consumed on prescription from a licensed healthcare provider. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OralOpioids + url_git: https://github.com/ankonahouston/OralOpioids +orbital: + version: 0.3.0 + title: Predict with 'tidymodels' Workflows in Databases + maintainer: Emil Hvitfeldt + description: |- + Turn 'tidymodels' workflows into objects containing the + sufficient sequential equations to perform predictions. These smaller + objects allow for low dependency prediction locally or directly in + databases. + date_publication: '2024-12-22' + bug_reports: https://github.com/tidymodels/orbital/issues + url: https://orbital.tidymodels.org + url_cran: https://CRAN.R-project.org/package=orbital + url_git: https://github.com/tidymodels/orbital +orca: + version: 1.1-3 + title: Computation of Graphlet Orbit Counts in Sparse Graphs + maintainer: Tomaz Hocevar + description: |- + Implements orbit counting using a fast combinatorial approach. + Counts orbits of nodes and edges from edge matrix or data frame, or a + graph object from the graph package. + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orca + url_git: '' +orcamentoBR: + version: 1.0.2 + title: Download Official Data on Brazil's Federal Budget + maintainer: Daniel G. Reiss + description: |- + Allows users to download and analyze official data on Brazil's federal budget through the 'SPARQL' endpoint + provided by the Integrated Budget and Planning System ('SIOP'). This package enables access to detailed information on budget + allocations and expenditures of the federal government, making it easier to analyze and visualize these data. Technical + information on the Brazilian federal budget is available (Portuguese only) at . + The 'SIOP' endpoint is available at . + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orcamentoBR + url_git: '' +orclus: + version: 0.2-6 + title: |- + Subspace Clustering Based on Arbitrarily Oriented Projected + Cluster Generation + maintainer: Gero Szepannek + description: Functions to perform subspace clustering and classification. + date_publication: '2018-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orclus + url_git: '' +ORCME: + version: 2.0.2 + title: Order Restricted Clustering for Microarray Experiments + maintainer: Rudradev Sengupta + description: |- + Provides clustering of genes with similar + dose response (or time course) profiles. It implements the method + described by Lin et al. (2012). + date_publication: '2015-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ORCME + url_git: '' +Orcs: + version: 1.2.3 + title: Omnidirectional R Code Snippets + maintainer: Florian Detsch + description: |- + I tend to repeat the same code chunks over and over again. At + first, this was fine for me and I paid little attention to such redundancies. + A little later, when I got tired of manually replacing Linux filepaths with + the referring Windows versions, and vice versa, I started to stuff some very + frequently used work-steps into functions and, even later, into a proper R + package. And that's what this package is - a hodgepodge of various R functions + meant to simplify (my) everyday-life coding work without, at the same time, + being devoted to a particular scope of application. + date_publication: '2023-01-06' + bug_reports: https://github.com/fdetsch/Orcs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Orcs + url_git: https://github.com/fdetsch/Orcs +ordbetareg: + version: '0.8' + title: Ordered Beta Regression Models with 'brms' + maintainer: Robert Kubinec + description: |- + Implements ordered beta regression models, which are for modeling continuous variables with upper and lower bounds, such as + survey sliders, dose-response relationships and indexes. For more information, see + Kubinec (2023) . The package is a front-end to the R package 'brms', which + facilitates a range of regression specifications, including hierarchical, dynamic and + multivariate modeling. + date_publication: '2025-02-03' + bug_reports: https://github.com/saudiwin/ordbetareg_pack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ordbetareg + url_git: '' +OrdCD: + version: 1.1.2 + title: Ordinal Causal Discovery + maintainer: Yang Ni + description: Algorithms for ordinal causal discovery. This package aims to enable + users to discover causality for observational ordinal categorical data with greedy + and exhaustive search. See Ni, Y., & Mallick, B. (2022) + "Ordinal Causal Discovery. Proceedings of the 38th Conference on Uncertainty in + Artificial Intelligence, (UAI 2022), PMLR 180:1530–1540". + date_publication: '2023-05-17' + bug_reports: https://github.com/nySTAT/OrdCD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OrdCD + url_git: https://github.com/nySTAT/OrdCD +ordcrm: + version: 1.0.0 + title: |- + Likelihood-Based Continual Reassessment Method (CRM) Dose + Finding Designs + maintainer: Emily V. Dressler + description: |- + Provides the setup and calculations needed + to run a likelihood-based continual reassessment method (CRM) + dose finding trial and performs simulations to assess design + performance under various scenarios. 3 dose finding designs + are included in this package: ordinal proportional odds model + (POM) CRM, ordinal continuation ratio (CR) model CRM, and the + binary 2-parameter logistic model CRM. + These functions allow customization of design characteristics + to vary sample size, cohort sizes, target dose-limiting + toxicity (DLT) rates, discrete or continuous dose levels, + combining ordinal grades 0 and 1 into one category, and + incorporate safety and/or stopping rules. + For POM and CR model designs, ordinal toxicity grades are + specified by common terminology criteria for adverse events + (CTCAE) version 4.0. + Function 'pseudodata' creates the necessary starting models + for these 3 designs, and function 'nextdose' estimates the + next dose to test in a cohort of patients for a target DLT + rate. + We also provide the function 'crmsimulations' to assess the + performance of these 3 dose finding designs under various + scenarios. + date_publication: '2016-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordcrm + url_git: '' +ordDisp: + version: 2.1.1 + title: Separating Location and Dispersion in Ordinal Regression Models + maintainer: Moritz Berger + description: Estimate location-shift models or rating-scale models accounting for + response styles (RSRS) for the regression analysis of ordinal responses. + date_publication: '2020-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordDisp + url_git: '' +orderanalyzer: + version: 1.0.0 + title: Extracting Order Position Tables from PDF-Based Order Documents + maintainer: Michael Scholz + description: |- + Functions for extracting text and tables from + PDF-based order documents. It provides an n-gram-based approach for identifying + the language of an order document. It furthermore uses R-package 'pdftools' to + extract the text from an order document. In the case that the PDF document is + only including an image (because it is scanned document), R package 'tesseract' + is used for OCR. Furthermore, the package provides functionality for identifying + and extracting order position tables in order documents based on a clustering approach. + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orderanalyzer + url_git: '' +ordering: + version: 0.7.0 + title: |- + Test, Check, Verify, Investigate the Monotonic Properties of + Vectors + maintainer: Christopher Brown + description: |- + Functions to test/check/verify/investigate the ordering of vectors. + The 'is_[strictly_]*' family of functions test vectors for + 'sorted', 'monotonic', 'increasing', 'decreasing' order; 'is_constant' + and 'is_incremental' test for the degree of ordering. `ordering` + provides a numeric indication of ordering -2 (strictly decreasing) to + 2 (strictly increasing). + date_publication: '2018-11-19' + bug_reports: https://github.com/decisionpatterns/ordering/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ordering + url_git: https://github.com/decisionpatterns/ordering +orderly: + version: 1.4.3 + title: Lightweight Reproducible Reporting + maintainer: Rich FitzJohn + description: |- + Order, create and store reports from R. By defining a + lightweight interface around the inputs and outputs of an + analysis, a lot of the repetitive work for reproducible research + can be automated. We define a simple format for organising and + describing work that facilitates collaborative reproducible + research and acknowledges that all analyses are run multiple + times over their lifespans. + date_publication: '2021-09-22' + bug_reports: https://github.com/vimc/orderly/issues + url: https://www.vaccineimpact.org/orderly/ + url_cran: https://CRAN.R-project.org/package=orderly + url_git: https://github.com/vimc/orderly +orders: + version: 0.1.8 + title: |- + Sampling from k-th Order Statistics of New Families of + Distributions + maintainer: Carlos Alberto Cardozo Delgado + description: |- + Set of tools to generate samples of k-th order statistics and others quantities of interest from new families of distributions. + The main references for this package are: C. Kleiber and S. Kotz (2003) Statistical size distributions in economics and actuarial sciences; Gentle, J. (2009), Computational Statistics, Springer-Verlag; + Naradajah, S. and Rocha, R. (2016), and Stasinopoulos, M. and Rigby, R. (2015), . + The families of distributions are: Benini distributions, Burr distributions, Dagum distributions, Feller-Pareto distributions, Generalized Pareto distributions, Inverse Pareto distributions, The Inverse Paralogistic distributions, Marshall-Olkin G distributions, exponentiated G distributions, beta G distributions, + gamma G distributions, Kumaraswamy G distributions, generalized beta G distributions, + beta extended G distributions, gamma G distributions, gamma uniform G distributions, beta exponential G distributions, Weibull G distributions, log gamma G I distributions, log gamma G II distributions, + exponentiated generalized G distributions, exponentiated Kumaraswamy G distributions, geometric exponential Poisson G distributions, truncated-exponential skew-symmetric G distributions, modified beta G distributions, + exponentiated exponential Poisson G distributions, Poisson-inverse gaussian distributions, Skew normal type 1 distributions, Skew student t distributions, Singh-Maddala distributions, Sinh-Arcsinh distributions, Sichel distributions, Zero inflated Poisson distributions. + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orders + url_git: '' +orderstats: + version: 0.1.0 + title: Efficiently Generates Random Order Statistic Variables + maintainer: Christian Sims + description: All the methods in this package generate a vector of uniform order + statistics using a beta distribution and use an inverse cumulative distribution + function for some distribution to give a vector of random order statistic variables + for some distribution. This is much more efficient than using a loop since it + is directly sampling from the order statistic distribution. + date_publication: '2017-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orderstats + url_git: '' +OrdFacReg: + version: 1.0.6 + title: |- + Least Squares, Logistic, and Cox-Regression with Ordered + Predictors + maintainer: Kaspar Rufibach + description: In biomedical studies, researchers are often interested in assessing + the association between one or more ordinal explanatory variables and an outcome + variable, at the same time adjusting for covariates of any type. The outcome variable + may be continuous, binary, or represent censored survival times. In the absence + of a precise knowledge of the response function, using monotonicity constraints + on the ordinal variables improves efficiency in estimating parameters, especially + when sample sizes are small. This package implements an active set algorithm that + efficiently computes such estimators. + date_publication: '2015-07-04' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=OrdFacReg + url_git: '' +ordgam: + version: 0.9.1 + title: Additive Model for Ordinal Data using Laplace P-Splines + maintainer: Philippe Lambert + description: 'Additive proportional odds model for ordinal data using Laplace P-splines. + The combination of Laplace approximations and P-splines enable fast and flexible + inference in a Bayesian framework. Specific approximations are proposed to account + for the asymmetry in the marginal posterior distributions of non-penalized parameters. + For more details, see Lambert and Gressani (2023) + ; Preprint: ).' + date_publication: '2023-09-14' + bug_reports: https://github.com/plambertULiege/ordgam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ordgam + url_git: +ordiBreadth: + version: '1.0' + title: Ordinated Diet Breadth + maintainer: James A. Fordyce + description: Calculates ordinated diet breadth with some plotting functions. + date_publication: '2015-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordiBreadth + url_git: '' +ordinal: + version: 2023.12-4.1 + title: Regression Models for Ordinal Data + maintainer: Rune Haubo Bojesen Christensen + description: |- + Implementation of cumulative link (mixed) models also known + as ordered regression models, proportional odds models, proportional + hazards models for grouped survival times and ordered logit/probit/... + models. Estimation is via maximum likelihood and mixed models are fitted + with the Laplace approximation and adaptive Gauss-Hermite quadrature. + Multiple random effect terms are allowed and they may be nested, crossed or + partially nested/crossed. Restrictions of symmetry and equidistance can be + imposed on the thresholds (cut-points/intercepts). Standard model + methods are available (summary, anova, drop-methods, step, + confint, predict etc.) in addition to profile methods and slice + methods for visualizing the likelihood function and checking + convergence. + date_publication: '2024-08-19' + bug_reports: https://github.com/runehaubo/ordinal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ordinal + url_git: https://github.com/runehaubo/ordinal +ordinalbayes: + version: 0.1.1 + title: Bayesian Ordinal Regression for High-Dimensional Data + maintainer: Kellie J. Archer + description: |- + Provides a function for fitting various penalized Bayesian + cumulative link ordinal response models when the number of parameters + exceeds the sample size. These models have been described in + Zhang and Archer (2021) . + date_publication: '2022-04-06' + bug_reports: https://github.com/kelliejarcher/ordinalbayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalbayes + url_git: https://github.com/kelliejarcher/ordinalbayes +ordinalCont: + version: 2.0.2 + title: Ordinal Regression Analysis for Continuous Scales + maintainer: Maurizio Manuguerra + description: |- + A regression framework for response variables which are continuous + self-rating scales such as the Visual Analog Scale (VAS) used in pain + assessment, or the Linear Analog Self-Assessment (LASA) scales in quality + of life studies. These scales measure subjects' perception of an intangible + quantity, and cannot be handled as ratio variables because of their inherent + non-linearity. We treat them as ordinal variables, measured on a continuous + scale. A function (the g function) connects the scale with an underlying + continuous latent variable. The link function is the inverse of the CDF of the + assumed underlying distribution of the latent variable. A variety of + link functions are currently implemented. Such models are described in Manuguerra et al (2020) . + date_publication: '2020-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalCont + url_git: '' +ordinalForest: + version: 2.4-4 + title: |- + Ordinal Forests: Prediction and Variable Ranking with Ordinal + Target Variables + maintainer: Roman Hornung + description: |- + The ordinal forest (OF) method allows ordinal regression with high-dimensional + and low-dimensional data. After having constructed an OF prediction rule using a training dataset, + it can be used to predict the values of the ordinal target variable for new observations. + Moreover, by means of the (permutation-based) variable importance measure of OF, it is also + possible to rank the covariates with respect to their importance in the prediction of the + values of the ordinal target variable. + OF is presented in Hornung (2020). + NOTE: Starting with package version 2.4, it is also possible to obtain class probability + predictions in addition to the class point predictions. Moreover, the variable importance values + can also be based on the class probability predictions. Preliminary results indicate that + this might lead to a better discrimination between influential and non-influential covariates. + The main functions of the package are: ordfor() (construction of OF) and predict.ordfor() + (prediction of the target variable values of new observations). + References: + Hornung R. (2020) Ordinal Forests. Journal of Classification 37, 4–17. + . + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalForest + url_git: '' +ordinalgmifs: + version: 1.0.8 + title: Ordinal Regression for High-Dimensional Data + maintainer: Kellie J. Archer + description: Provides a function for fitting cumulative link, adjacent category, + forward and backward continuation ratio, and stereotype ordinal response models + when the number of parameters exceeds the sample size, using the the generalized + monotone incremental forward stagewise method. + date_publication: '2023-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalgmifs + url_git: '' +ordinalLBM: + version: '1.0' + title: |- + Co-Clustering of Ordinal Data via Latent Continuous Random + Variables + maintainer: Marco Corneli + description: It implements functions for simulation and estimation of the ordinal + latent block model (OLBM), as described in Corneli, Bouveyron and Latouche (2019). + date_publication: '2019-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalLBM + url_git: '' +ordinalNet: + version: '2.12' + title: Penalized Ordinal Regression + maintainer: Michael Wurm + description: |- + Fits ordinal regression models with elastic net penalty. + Supported model families include cumulative probability, stopping ratio, + continuation ratio, and adjacent category. These families are a subset of + vector glm's which belong to a model class we call the elementwise link + multinomial-ordinal (ELMO) class. Each family in this class links a vector + of covariates to a vector of class probabilities. Each of these families + has a parallel form, which is appropriate for ordinal response data, as + well as a nonparallel form that is appropriate for an unordered categorical + response, or as a more flexible model for ordinal data. The parallel model + has a single set of coefficients, whereas the nonparallel model has a set of + coefficients for each response category except the baseline category. It is + also possible to fit a model with both parallel and nonparallel terms, which + we call the semi-parallel model. The semi-parallel model has the flexibility + of the nonparallel model, but the elastic net penalty shrinks it toward the + parallel model. For details, refer to Wurm, Hanlon, and Rathouz (2021) + . + date_publication: '2022-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalNet + url_git: '' +ordinalpattern: + version: 0.2.6 + title: Tests Based on Ordinal Patterns + maintainer: Angelika Silbernagel + description: 'Ordinal patterns describe the dynamics of a time series by looking + at the ranks of subsequent observations. By comparing ordinal patterns of two + times series, Schnurr (2014) defines a robust + and non-parametric dependence measure: the ordinal pattern coefficient. Functions + to calculate this and a method to detect a change in the pattern coefficient proposed + in Schnurr and Dehling (2017) are provided. + Furthermore, the package contains a function for calculating the ordinal pattern + frequencies. Generalized ordinal patterns as proposed by Schnurr and Fischer (2022) + are also considered.' + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalpattern + url_git: '' +ordinalRR: + version: '1.1' + title: |- + Analysis of Repeatability and Reproducibility Studies with + Ordinal Measurements + maintainer: Ken Ryan + description: Implements Bayesian data analyses of balanced repeatability and reproducibility + studies with ordinal measurements. Model fitting is based on MCMC posterior sampling + with 'rjags'. Function ordinalRR() directly carries out the model fitting, and + this function has the flexibility to allow the user to specify key aspects of + the model, e.g., fixed versus random effects. Functions for preprocessing data + and for the numerical and graphical display of a fitted model are also provided. + There are also functions for displaying the model at fixed (user-specified) parameters + and for simulating a hypothetical data set at a fixed (user-specified) set of + parameters for a random-effects rater population. For additional technical details, + refer to Culp, Ryan, Chen, and Hamada (2018) and cite this Technometrics paper + when referencing any aspect of this work. The demo of this package reproduces + results from the Technometrics paper. + date_publication: '2020-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordinalRR + url_git: '' +ordinalsimr: + version: 0.1.3 + title: Compare Ordinal Endpoints Using Simulations + maintainer: Pat Callahan + description: Simultaneously evaluate multiple ordinal outcome measures. Applied + data analysts in particular are faced with uncertainty in choosing appropriate + statistical tests for ordinal data. The included 'shiny' application allows users + to simulate outcomes given different ordinal data distributions. + date_publication: '2025-01-29' + bug_reports: https://github.com/NeuroShepherd/ordinalsimr/issues + url: https://neuroshepherd.github.io/ordinalsimr/ + url_cran: https://CRAN.R-project.org/package=ordinalsimr + url_git: https://github.com/NeuroShepherd/ordinalsimr +OrdMonReg: + version: 1.0.3 + title: |- + Compute least squares estimates of one bounded or two ordered + isotonic regression curves + maintainer: Kaspar Rufibach + description: 'We consider the problem of estimating two isotonic regression curves + g1* and g2* under the constraint that they are ordered, i.e. g1* <= g2*. Given + two sets of n data points y_1, ..., y_n and z_1, ..., z_n that are observed at + (the same) deterministic design points x_1, ..., x_n, the estimates are obtained + by minimizing the Least Squares criterion L(a, b) = sum_{i=1}^n (y_i - a_i)^2 + w1(x_i) + sum_{i=1}^n (z_i - b_i)^2 w2(x_i) over the class of pairs of vectors + (a, b) such that a and b are isotonic and a_i <= b_i for all i = 1, ..., n. We + offer two different approaches to compute the estimates: a projected subgradient + algorithm where the projection is calculated using a PAVA as well as Dykstra''s + cyclical projection algorithm.' + date_publication: '2011-12-01' + bug_reports: '' + url: http://www.ceremade.dauphine.fr/~fadoua + url_cran: https://CRAN.R-project.org/package=OrdMonReg + url_git: '' +OrdNor: + version: 2.2.3 + title: |- + Concurrent Generation of Ordinal and Normal Data with Given + Correlation Matrix and Marginal Distributions + maintainer: Ran Gao + description: |- + Implementation of a procedure for generating samples from a mixed distribution of ordinal and normal random variables with a pre-specified correlation matrix and marginal distributions. + The details of the method are explained in Demirtas et al. (2015) . + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OrdNor + url_git: '' +ordPens: + version: 1.1.0 + title: |- + Selection, Fusion, Smoothing and Principal Components Analysis + for Ordinal Variables + maintainer: Aisouda Hoshiyar + description: Selection, fusion, and/or smoothing of ordinally scaled independent + variables using a group lasso, fused lasso or generalized ridge penalty, as well + as non-linear principal components analysis for ordinal variables using a second-order + difference/smoothing penalty. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ordPens + url_git: '' +ordr: + version: 0.1.1 + title: A 'tidyverse' Extension for Ordinations and Biplots + maintainer: Jason Cory Brunson + description: |- + Ordination comprises several multivariate exploratory and + explanatory techniques with theoretical foundations in geometric data + analysis; see Podani (2000, ISBN:90-5782-067-6) for techniques and + applications and Le Roux & Rouanet (2005) for + foundations. + Greenacre (2010, ISBN:978-84-923846) shows how the most established of + these, including principal components analysis, correspondence analysis, + multidimensional scaling, factor analysis, and discriminant analysis, + rely on eigen-decompositions or singular value decompositions of + pre-processed numeric matrix data. + These decompositions give rise to a set of shared coordinates along which + the row and column elements can be measured. The overlay of their + scatterplots on these axes, introduced by Gabriel (1971) + , is called a biplot. + 'ordr' provides inspection, extraction, manipulation, and visualization + tools for several popular ordination classes supported by a set of recovery + methods. It is inspired by and designed to integrate into 'tidyverse' + workflows provided by Wickham et al (2019) . + date_publication: '2022-10-20' + bug_reports: https://github.com/corybrunson/ordr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ordr + url_git: https://github.com/corybrunson/ordr +ore: + version: 1.7.4.1 + title: An R Interface to the Onigmo Regular Expression Library + maintainer: Jon Clayden + description: |- + Provides an alternative to R's built-in functionality for handling + regular expressions, based on the Onigmo library. Offers first-class + compiled regex objects, partial matching and function-based substitutions, + amongst other features. + date_publication: '2023-12-05' + bug_reports: https://github.com/jonclayden/ore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ore + url_git: https://github.com/jonclayden/ore +oreo: + version: '1.0' + title: Large Amplitude Oscillatory Shear (LAOS) + maintainer: Serena Berretta + description: The Sequence of Physical Processes (SPP) framework is a way of interpreting + the transient data derived from oscillatory rheological tests. It is designed + to allow both the linear and non-linear deformation regimes to be understood within + a single unified framework. This code provides a convenient way to determine the + SPP framework metrics for a given sample of oscillatory data. It will produce + a text file containing the SPP metrics, which the user can then plot using their + software of choice. It can also produce a second text file with additional derived + data (components of tangent, normal, and binormal vectors), as well as pre-plotted + figures if so desired. It is the R version of the Package SPP by Simon Rogers + Group for Soft Matter (Simon A. Rogers, Brian M. Erwin, Dimitris Vlassopoulos, + Michel Cloitre (2011) ). + date_publication: '2021-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oreo + url_git: '' +orf: + version: 0.1.4 + title: Ordered Random Forests + maintainer: Gabriel Okasa + description: |- + An implementation of the Ordered Forest estimator as developed + in Lechner & Okasa (2019) . The Ordered Forest flexibly + estimates the conditional probabilities of models with ordered categorical + outcomes (so-called ordered choice models). Additionally to common machine + learning algorithms the 'orf' package provides functions for estimating + marginal effects as well as statistical inference thereof and thus provides + similar output as in standard econometric models for ordered choice. The + core forest algorithm relies on the fast C++ forest implementation from + the 'ranger' package (Wright & Ziegler, 2017) . + date_publication: '2022-07-23' + bug_reports: https://github.com/okasag/orf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=orf + url_git: https://github.com/okasag/orf +ORFID: + version: 1.0.2 + title: |- + Manage and Summarize Data from Oregon RFID ORMR and ORSR Antenna + Readers + maintainer: Annika Putt + description: Automates and standardizes the import of raw data from Oregon RFID + (radio-frequency identification) ORMR (Oregon RFID Multi-Reader) and ORSR (Oregon + RFID Single Reader) antenna readers. Compiled data can then be combined within + multi-reader arrays for further analysis, including summarizing tag and reader + detections, determining tag direction, and calculating antenna efficiency. + date_publication: '2022-12-15' + bug_reports: https://github.com/hugo-marques/ORFID/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ORFID + url_git: https://github.com/hugo-marques/ORFID +org: + version: 2024.6.5 + title: Organising Projects + maintainer: Richard Aubrey White + description: 'A system to help you organize projects. Most analyses have three (or + more) main sections: code, results, and data, each with different requirements + (version control/sharing/encryption). You provide folder locations and ''org'' + helps you take care of the details.' + date_publication: '2024-06-04' + bug_reports: https://github.com/csids/org/issues + url: https://www.csids.no/org/ + url_cran: https://CRAN.R-project.org/package=org + url_git: https://github.com/csids/org +organizr: + version: 0.1.0 + title: Shortcuts for File Creation with Informative Prefixes + maintainer: Johannes Brachem + description: |- + Provides functions for quickly creating R and Python scripts, as + well as 'Rmarkdown' or Quarto documents with automatically assigned name + prefixes. Prefixes are either file counts (e.g. "001") or dates + (e.g. "2022-09-26"). + date_publication: '2022-09-29' + bug_reports: https://github.com/jobrachem/organizr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=organizr + url_git: https://github.com/jobrachem/organizr +OrgMassSpecR: + version: 0.5-3 + title: Organic Mass Spectrometry + maintainer: Nathan Dodder + description: Organic/biological mass spectrometry data analysis. + date_publication: '2017-08-13' + bug_reports: '' + url: http://OrgMassSpec.github.io/ + url_cran: https://CRAN.R-project.org/package=OrgMassSpecR + url_git: '' +orgR: + version: 0.9.0 + title: Analyse Text Files Created by Emacs' Org mode + maintainer: Yi Tang + description: Provides functionality to process text files created by Emacs' Org + mode, and decompose the content to the smallest components (headlines, body, tag, + clock entries etc). Emacs is an extensible, customizable text editor and Org + mode is for keeping notes, maintaining TODO lists, planning projects. Allows + users to analyze org files as data frames in R, e.g., to convieniently group tasks + by tag into project and calculate total working hours. Also provides some help + functions like search.parent, gg.pie (visualise working hours in ggplot2) and + tree.headlines (visualise headline stricture in tree format) to help user managing + their complex org files. + date_publication: '2014-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orgR + url_git: '' +orgutils: + version: 0.5-0 + title: Helper Functions for Org Files + maintainer: Enrico Schumann + description: |- + Helper functions for Org files (): + a generic function 'toOrg' for transforming R objects into Org + markup (most useful for data frames; there are also methods for + Dates/POSIXt) and a function to read Org tables into data frames. + date_publication: '2024-01-31' + bug_reports: '' + url: http://enricoschumann.net/R/packages/orgutils/ + url_cran: https://CRAN.R-project.org/package=orgutils + url_git: '' +ORIClust: + version: 1.0-2 + title: |- + Order-Restricted Information Criterion-Based Clustering + Algorithm + maintainer: Tianqing Liu + description: |- + A user-friendly R-based software package for + gene clustering. Clusters are given by genes matched to + prespecified profiles across various ordered treatment groups. + It is particularly useful for analyzing data obtained from + short time-course or dose-response microarray experiments. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ORIClust + url_git: '' +orientlib: + version: 0.10.5 + title: Support for Orientation Data + maintainer: Duncan Murdoch + description: |- + Representations, conversions and display of orientation SO(3) data. + See the orientlib help topic for details. + date_publication: '2023-01-10' + bug_reports: https://github.com/dmurdoch/orientlib/issues + url: https://dmurdoch.github.io/orientlib/ + url_cran: https://CRAN.R-project.org/package=orientlib + url_git: https://github.com/dmurdoch/orientlib +origami: + version: 1.0.7 + title: Generalized Framework for Cross-Validation + maintainer: Jeremy Coyle + description: |- + A general framework for the application of cross-validation schemes + to particular functions. By allowing arbitrary lists of results, origami + accommodates a range of cross-validation applications. This implementation + was first described by Coyle and Hejazi (2018) . + date_publication: '2022-10-19' + bug_reports: https://github.com/tlverse/origami/issues + url: https://tlverse.org/origami/ + url_cran: https://CRAN.R-project.org/package=origami + url_git: '' +OrigamiPlot: + version: 0.2.0 + title: |- + A Visualization Tool Enhancing Radar Plot Visualizations for + Multivariate Data + maintainer: Yiwen Lu + description: A visualization tool for multivariate data. This package maintains + the original functionality of a radar chart and avoids potential misuse of its + connected regions, with newly added features to better assist multi-criteria decision-making. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OrigamiPlot + url_git: '' +origin: + version: 1.2.0 + title: |- + Explicitly Qualifying Namespaces by Automatically Adding 'pkg::' + to Functions + maintainer: Matthias Nistler + description: |- + Automatically adding 'pkg::' to a function, i.e. mutate() + becomes dplyr::mutate(). It is up to the user to determine which + packages should be used explicitly, whether to include base R packages + or use the functionality on selected text, a file, or a complete + directory. User friendly logging is provided in the 'RStudio' Markers + pane. Lives in the spirit of 'lintr' and 'styler'. Can also be used + for checking which packages are actually used in a project. + date_publication: '2024-11-24' + bug_reports: https://github.com/mnist91/origin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=origin + url_git: https://github.com/mnist91/origin +ORION: + version: 1.0.3 + title: Ordinal Relations + maintainer: HA Kestler + description: Functions to handle ordinal relations reflected within the feature + space. Those function allow to search for ordinal relations in multi-class datasets. + One can check whether proposed relations are reflected in a specific feature representation. + Furthermore, it provides functions to filter, organize and further analyze those + ordinal relations. + date_publication: '2022-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ORION + url_git: '' +ORIONZ.G: + version: 1.0.1 + title: |- + EAP Scoring in Exploratory FA Solutions with Correlated + Residuals + maintainer: David Navarro-Gonzalez + description: |- + Obtaining Bayes Expected A Posteriori (EAP) individual score + estimates based on linear and non-linear extended Exploratoy Factor Analysis + solutions that include a correlated-residual structure. + date_publication: '2024-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ORIONZ.G + url_git: '' +ORKM: + version: 0.8.0.0 + title: The Online Regularized K-Means Clustering Algorithm + maintainer: Guangbao Guo + description: |- + Algorithm of online regularized k-means to deal with online multi(single) view data. + The philosophy of the package is described in Guo G. (2020) + . + date_publication: '2024-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ORKM + url_git: '' +orloca: + version: '5.6' + title: Operations Research LOCational Analysis Models + maintainer: Manuel Munoz-Marquez + description: |- + Objects and methods to handle and solve the min-sum location problem, also known as Fermat-Weber problem. The min-sum location problem search for a point such that the weighted sum of the distances to the demand points are minimized. See "The Fermat-Weber location problem revisited" by Brimberg, Mathematical Programming, 1, pg. 71-76, 1995. . + General global optimization algorithms are used to solve the problem, along with the adhoc Weiszfeld method, see "Sur le point pour lequel la Somme des distances de n points donnes est minimum", by Weiszfeld, Tohoku Mathematical Journal, First Series, 43, pg. 355-386, 1937 or "On the point for which the sum of the distances to n given points is minimum", by E. Weiszfeld and F. Plastria, Annals of Operations Research, 167, pg. 7-41, 2009. . + date_publication: '2024-02-07' + bug_reports: '' + url: http://knuth.uca.es/orloca/ + url_cran: https://CRAN.R-project.org/package=orloca + url_git: '' +orloca.es: + version: '4.9' + title: |- + Spanish version of orloca package. Modelos de localizacion en + investigacion operativa + maintainer: Manuel Munoz-Marquez + description: |- + Help and demo in Spanish of the orloca package. (Ayuda y demo en espanol del paquete orloca.) Objetos y metodos para manejar y resolver el problema de localizacion de suma minima, tambien conocido como problema de Fermat-Weber. El problema de localizacion de suma minima busca un punto tal que la suma ponderada de las distancias a los puntos de demanda se minimice. Vease "The Fermat-Weber location problem revisited" por Brimberg, Mathematical Programming, 1, pag. 71-76, 1995. . + Se usan algoritmos generales de optimizacion global para resolver el problema, junto con el metodo adhoc Weiszfeld, vease "Sur le point pour lequel la Somme des distance de n points donnes est minimum", por Weiszfeld, Tohoku Mathematical Journal, First Series, 43, pag. 355-386, 1937 o "On the point for which the sum of the distances to n given points is minimum", por E. Weiszfeld y F. Plastria, Annals of Operations Research, 167, pg. 7-41, 2009. . + date_publication: '2020-03-06' + bug_reports: '' + url: http://knuth.uca.es/orloca + url_cran: https://CRAN.R-project.org/package=orloca.es + url_git: '' +ormPlot: + version: 0.3.6 + title: Advanced Plotting of Ordinal Regression Models + maintainer: Richard Meitern + description: |- + An extension to the Regression Modeling Strategies package that + facilitates plotting ordinal regression model predictions together with + confidence intervals for each dependent variable level. + It also adds a functionality to plot the model summary as a modifiable + object. + date_publication: '2023-09-13' + bug_reports: '' + url: https://doi.org/10.1186/s12889-019-8072-7 + url_cran: https://CRAN.R-project.org/package=ormPlot + url_git: '' +oro.dicom: + version: 0.5.3 + title: Rigorous - DICOM Input / Output + maintainer: Brandon Whitcher + description: |- + Data input/output functions for data that conform to the + Digital Imaging and Communications in Medicine (DICOM) standard, part + of the Rigorous Analytics bundle. + date_publication: '2019-10-28' + bug_reports: '' + url: http://rig.oro.us.com + url_cran: https://CRAN.R-project.org/package=oro.dicom + url_git: '' +oro.nifti: + version: 0.11.4 + title: 'Rigorous - ''NIfTI'' + ''ANALYZE'' + ''AFNI'' : Input / Output' + maintainer: Brandon Whitcher + description: |- + Functions for the input/output and visualization of + medical imaging data that follow either the 'ANALYZE', 'NIfTI' or 'AFNI' + formats. This package is part of the Rigorous Analytics bundle. + date_publication: '2022-08-10' + bug_reports: https://github.com/bjw34032/oro.nifti/issues + url: https://rigorousanalytics.blogspot.com + url_cran: https://CRAN.R-project.org/package=oro.nifti + url_git: '' +oro.pet: + version: 0.2.7 + title: Rigorous - Positron Emission Tomography + maintainer: Brandon Whitcher + description: |- + Image analysis techniques for positron emission tomography + (PET) that form part of the Rigorous Analytics bundle. + date_publication: '2022-08-20' + bug_reports: '' + url: http://rig.oro.us.com + url_cran: https://CRAN.R-project.org/package=oro.pet + url_git: '' +orsifronts: + version: 0.2.0 + title: Southern Ocean Frontal Distributions (Orsi) + maintainer: Michael D. Sumner + description: |- + A data set package with the "Orsi" and "Park/Durand" fronts as + 'SpatialLinesDataFrame' objects. The Orsi et al. (1995) fronts are published at + the Southern Ocean Atlas Database Page, and the Park et al. (2019) fronts are published at the 'SEANOE' + Altimetry-derived Antarctic Circumpolar Current fronts page, please see package CITATION for details. + date_publication: '2021-05-04' + bug_reports: https://github.com/AustralianAntarcticDivision/orsifronts/issues + url: https://australianantarcticdivision.github.io/orsifronts/ + url_cran: https://CRAN.R-project.org/package=orsifronts + url_git: '' +orsk: + version: 1.0-8 + title: |- + Converting Odds Ratio to Relative Risk in Cohort Studies with + Partial Data Information + maintainer: Zhu Wang + description: Convert odds ratio to relative risk in cohort studies with partial + data information (Wang (2013) ). + date_publication: '2023-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orsk + url_git: '' +ORTH.Ord: + version: 1.0.1 + title: |- + Alternating Logistic Regression with Orthogonalized Residuals + for Correlated Ordinal Outcomes + maintainer: Can Meng + description: A modified version of alternating logistic regressions (ALR) with estimation + based on orthogonalized residuals (ORTH) is implemented, which use paired estimating + equations to jointly estimate parameters in marginal mean and within-association + models. The within-cluster association between ordinal responses is modeled by + global pairwise odds ratios (POR). A finite-sample bias correction is provided + to POR parameter estimates based on matrix multiplicative adjusted orthogonalized + residuals (MMORTH) for correcting estimating equations, and different bias-corrected + variance estimators such as BC1, BC2, and BC3. + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ORTH.Ord + url_git: '' +orthGS: + version: 0.1.6 + title: |- + Orthology vs Paralogy Relationships among Glutamine Synthetase + from Plants + maintainer: Elena Aledo + description: Tools to analyze and infer orthology and paralogy relationships between + glutamine synthetase proteins in seed plants. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orthGS + url_git: '' +orthoDr: + version: 0.6.8 + title: |- + Semi-Parametric Dimension Reduction Models Using Orthogonality + Constrained Optimization + maintainer: Ruoqing Zhu + description: |- + Utilize an orthogonality constrained optimization algorithm of + Wen & Yin (2013) to solve a variety of + dimension reduction problems in the semiparametric framework, such as + Ma & Zhu (2012) , Ma & Zhu (2013) + , Sun, Zhu, Wang & Zeng (2019) + and Zhou, Zhu & Zeng (2021) . The package also + implements some existing dimension reduction methods such as hMave by Xia, Zhang, + & Xu (2010) and partial SAVE by Feng, Wen & Zhu (2013) + . It also serves as a general purpose + optimization solver for problems with orthogonality constraints, i.e., in Stiefel + manifold. Parallel computing for approximating the gradient is enabled through 'OpenMP'. + date_publication: '2024-03-13' + bug_reports: https://github.com/teazrq/orthoDr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=orthoDr + url_git: https://github.com/teazrq/orthoDr +orthogonalsplinebasis: + version: 0.1.7 + title: Orthogonal B-Spline Basis Functions + maintainer: Andrew Redd + description: |- + Represents the basis functions for B-splines in a simple matrix + formulation that facilitates, taking integrals, derivatives, and + making orthogonal the basis functions. + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orthogonalsplinebasis + url_git: https://github.com/halpo/obsplines +OrthoPanels: + version: 1.2-4 + title: |- + Dynamic Panel Models with Orthogonal Reparameterization of Fixed + Effects + maintainer: Mark Pickup + description: |- + Implements the orthogonal reparameterization + approach recommended by Lancaster (2002) to estimate dynamic panel + models with fixed effects (and optionally: panel specific + intercepts). The approach uses a likelihood-based estimator and + produces estimates that are asymptotically unbiased as N goes to + infinity, with a T as low as 2. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OrthoPanels + url_git: '' +orthopolynom: + version: 1.0-6.1 + title: |- + Collection of Functions for Orthogonal and Orthonormal + Polynomials + maintainer: Frederick Novomestky + description: |- + A collection of functions to construct sets of orthogonal + polynomials and their recurrence relations. Additional + functions are provided to calculate the derivative, integral, + value and roots of lists of polynomial objects. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=orthopolynom + url_git: '' +ORTSC: + version: 1.0.0 + title: Connects to Google Cloud API for Label Detection + maintainer: Mohamed Soudy + description: Connects to Google cloud vision to + perform label detection and repurpose this feature for image classification. + date_publication: '2021-02-10' + bug_reports: https://github.com/MohmedSoudy/ORTSC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ORTSC + url_git: https://github.com/MohmedSoudy/ORTSC +oRus: + version: 1.0.0 + title: Operational Research User Stories + maintainer: Melina Vidoni + description: |- + A first implementation of automated parsing of user stories, when used + to defined functional requirements for operational research mathematical + models. It allows reading user stories, splitting them on the who-what-why template, + and classifying them according to the parts of the mathematical model that + they represent. Also provides semantic grouping of stories, + for project management purposes. + date_publication: '2020-07-07' + bug_reports: https://github.com/melvidoni/oRus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oRus + url_git: https://github.com/melvidoni/oRus +OryzaProbe: + version: 0.1.0 + title: Rice Microarray Probe ID Conversion, from Probe ID to RAP-DB ID + maintainer: Youming Liu + description: |- + Microarray probe ID is not convenient for further enrichment analysis and target gene selection. + The package is created for the rice microarray probe ID conversion. + This package can convert microarray probe ID from GPL6864 , GPL8852 , and GPL2025 platforms to RAP-DB ID. RAP-DB "The Rice Annotation Project Database" is a well-known database for rice Oryza sativa, and the gene ID in this database is widely used in many areas related to rice research. + For multiple probes representing a single gene, This package can merge them by taking the mean, max, or min value of these probes. + Or we can keep multiple probes by appending sequence numbers to duplicate the RAP-DB ID. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OryzaProbe + url_git: '' +osc: + version: 1.0.5 + title: Orthodromic Spatial Clustering + maintainer: Steffen Kriewald + description: Allows distance based spatial clustering of georeferenced data by implementing + the City Clustering Algorithm - CCA. Multiple versions allow clustering for a + matrix, raster and single coordinates on a plain (Euclidean distance) or on a + sphere (great-circle or orthodromic distance). + date_publication: '2019-12-19' + bug_reports: '' + url: https://www.pik-potsdam.de/~kriewald/osc/ + url_cran: https://CRAN.R-project.org/package=osc + url_git: '' +oscar: + version: 1.2.1 + title: |- + Optimal Subset Cardinality Regression (OSCAR) Models Using the + L0-Pseudonorm + maintainer: Teemu Daniel Laajala + description: |- + Optimal Subset Cardinality Regression (OSCAR) models offer + regularized linear regression using the L0-pseudonorm, conventionally + known as the number of non-zero coefficients. The package estimates an + optimal subset of features using the L0-penalization via + cross-validation, bootstrapping and visual diagnostics. Effective + Fortran implementations are offered along the package for finding + optima for the DC-decomposition, which is used for transforming the + discrete L0-regularized optimization problem into a continuous + non-convex optimization task. These optimization modules include DBDC + ('Double Bundle method for nonsmooth DC optimization' as described in + Joki et al. (2018) ) and LMBM ('Limited + Memory Bundle Method for large-scale nonsmooth optimization' as + in Haarala et al. (2004) ). The + OSCAR models are comprehensively exemplified in Halkola et al. (2023) + ). Multiple regression model families + are supported: Cox, logistic, and Gaussian. + date_publication: '2023-10-02' + bug_reports: https://github.com/Syksy/oscar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oscar + url_git: https://github.com/Syksy/oscar +OscillatorGenerator: + version: 0.1.0 + title: |- + Generation of Customizable, Discretized Time Series of + Oscillating Species + maintainer: Arne Schoch + description: The supplied code allows for the generation of discrete time series + of oscillating species. General shapes can be selected by means of individual + functions, which are widely customizable by means of function arguments. All code + was developed in the Biological Information Processing Group at the BioQuant Center + at Heidelberg University, Germany. + date_publication: '2018-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OscillatorGenerator + url_git: '' +OSCV: + version: '1.0' + title: One-Sided Cross-Validation + maintainer: Olga Savchuk + description: 'Functions for implementing different versions of the OSCV method in + the kernel regression and density estimation frameworks. The package mainly supports + the following articles: (1) Savchuk, O.Y., Hart, J.D. (2017). Fully robust one-sided + cross-validation for regression functions. Computational Statistics, + and (2) Savchuk, O.Y. (2017). One-sided cross-validation for nonsmooth density + functions, .' + date_publication: '2017-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OSCV + url_git: '' +osd: + version: '0.1' + title: |- + Orthogonal Signal Deconvolution for Spectra Deconvolution in + GC-MS and GCxGC-MS Data + maintainer: Xavier Domingo-Almenara + description: Compound deconvolution for chromatographic data, including gas chromatography + - mass spectrometry (GC-MS) and comprehensive gas chromatography - mass spectrometry + (GCxGC-MS). The package includes functions to perform independent component analysis + - orthogonal signal deconvolution (ICA-OSD), independent component regression + (ICR), multivariate curve resolution (MCR-ALS) and orthogonal signal deconvolution + (OSD) alone. + date_publication: '2016-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=osd + url_git: '' +osdatahub: + version: 0.2.0 + title: Easier Interaction with the Ordnance Survey Data Hub + maintainer: Chris Jochem + description: |- + Ordnance Survey ('OS') is the national mapping agency for Great + Britain and produces a large variety of mapping and geospatial products. + Much of OS's data is available via the OS Data Hub , + a platform that hosts both free and premium data products. 'osdatahub' + provides a user-friendly way to access, query, and download these data. + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=osdatahub + url_git: '' +osDesign: + version: '1.8' + title: Design, Planning and Analysis of Observational Studies + maintainer: Sebastien Haneuse + description: 'A suite of functions for the design of case-control and two-phase + studies, and the analysis of data that arise from them. Functions in this packages + provides Monte Carlo based evaluation of operating characteristics such as powers + for estimators of the components of a logistic regression model. For additional + detail see: Haneuse S, Saegusa T and Lumley T (2011).' + date_publication: '2020-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=osDesign + url_git: '' +OSDR: + version: 1.1.4 + title: Finds an Optimal System of Distinct Representatives + maintainer: Massimo Cannas + description: |- + Provides routines for finding an Optimal System of Distinct Representatives (OSDR), + as defined by D.Gale (1968) . + date_publication: '2022-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OSDR + url_git: '' +OSFD: + version: '3.0' + title: Output Space-Filling Design + maintainer: Shangkun Wang + description: |- + Methods to generate a design in the input space that sequentially fills the output space of a black-box function. The output space-filling designs are helpful in inverse design or feature-based modeling problems. + See Wang, Shangkun, Adam P. Generale, Surya R. Kalidindi, and V. Roshan Joseph. (2024), Sequential designs for filling output spaces, Technometrics, 66, 65–76. for details. This work is supported by U.S. National Foundation grant CMMI-1921646. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OSFD + url_git: '' +osfr: + version: 0.2.9 + title: Interface to the 'Open Science Framework' ('OSF') + maintainer: Aaron Wolen + description: |- + An interface for interacting with 'OSF' (). 'osfr' + enables you to access open research materials and data, or create and + manage your own private or public projects. + date_publication: '2022-09-25' + bug_reports: https://github.com/ropensci/osfr/issues + url: https://docs.ropensci.org/osfr/ + url_cran: https://CRAN.R-project.org/package=osfr + url_git: https://github.com/ropensci/osfr +oshka: + version: 0.1.2 + title: Recursive Quoted Language Expansion + maintainer: Brodie Gaslam + description: |- + Expands quoted language by recursively replacing any symbol that + points to quoted language with the language it points to. The recursive + process continues until only symbols that point to non-language objects + remain. The resulting quoted language can then be evaluated normally. This + differs from the traditional 'quote'/'eval' pattern because it resolves + intermediate language objects that would interfere with evaluation. + date_publication: '2017-10-14' + bug_reports: https://github.com/brodieG/oshka/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oshka + url_git: https://github.com/brodieG/oshka +oskeyring: + version: 0.1.6 + title: Raw System Credential Store Access from R + maintainer: Gábor Csárdi + description: |- + Aims to support all features of the system credential store, + including non-portable ones. Supports 'Keychain' on 'macOS', and + 'Credential Manager' on 'Windows'. See the 'keyring' package if you + need a portable 'API'. + date_publication: '2023-04-11' + bug_reports: https://github.com/r-lib/oskeyring/issues + url: https://r-lib.github.io/oskeyring/ + url_cran: https://CRAN.R-project.org/package=oskeyring + url_git: https://github.com/r-lib/oskeyring#readme +OSLdecomposition: + version: 1.0.0 + title: Signal Component Analysis for Optically Stimulated Luminescence + maintainer: Dirk Mittelstraß + description: |- + Function library for the identification and separation of exponentially + decaying signal components in continuous-wave optically stimulated luminescence measurements. + A special emphasis is laid on luminescence dating with quartz, which is known for + systematic errors due to signal components with unequal physical behaviour. + Also, this package enables an easy to use signal decomposition of + data sets imported and analysed with the R package 'Luminescence'. + This includes the optional automatic creation of HTML reports. Further information and tutorials + can be found at . + date_publication: '2022-08-12' + bug_reports: https://github.com/DirkMittelstrass/OSLdecomposition/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OSLdecomposition + url_git: '' +osmapiR: + version: 0.2.2 + title: '''OpenStreetMap'' API' + maintainer: Joan Maspons + description: |- + Interface to 'OpenStreetMap API' for fetching and saving data + from/to the 'OpenStreetMap' database + (). + date_publication: '2024-11-18' + bug_reports: https://github.com/ropensci/osmapiR/issues + url: https://docs.ropensci.org/osmapiR/ + url_cran: https://CRAN.R-project.org/package=osmapiR + url_git: https://github.com/ropensci/osmapiR +osmclass: + version: 0.1.3 + title: Classify Open Street Map Features + maintainer: Sebastian Krantz + description: |- + Classify Open Street Map (OSM) features into meaningful functional + or analytical categories. Designed for OSM PBF files, e.g. from + imported as spatial data frames. A classification consists of a list of categories that are related to + certain OSM tags and values. Given a layer from an OSM PBF file and a classification, the main + osm_classify() function returns a classification data table giving, for each feature, the primary and + alternative categories (if there is overlap) assigned, and the tag(s) and value(s) matched on. + The package also contains a classification of OSM features by economic function/significance, + following Krantz (2023) . + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=osmclass + url_git: '' +osmdata: + version: 0.2.5 + title: |- + Import 'OpenStreetMap' Data as Simple Features or Spatial + Objects + maintainer: Mark Padgham + description: |- + Download and import of 'OpenStreetMap' ('OSM') data as 'sf' + or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web + server () and processed with very fast 'C++' + routines for return to 'R'. + date_publication: '2023-08-14' + bug_reports: https://github.com/ropensci/osmdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=osmdata + url_git: https://docs.ropensci.org/osmdata/(website)https://github.com/ropensci/osmdata/(devel) +osmextract: + version: 0.5.2 + title: Download and Import Open Street Map Data Extracts + maintainer: Andrea Gilardi + description: |- + Match, download, convert and import Open Street Map data extracts + obtained from several providers. + date_publication: '2024-11-22' + bug_reports: https://github.com/ropensci/osmextract/issues + url: https://docs.ropensci.org/osmextract/ + url_cran: https://CRAN.R-project.org/package=osmextract + url_git: https://github.com/ropensci/osmextract +OSMscale: + version: 0.5.20 + title: Add a Scale Bar to 'OpenStreetMap' Plots + maintainer: Berry Boessenkool + description: |- + Functionality to handle and project lat-long coordinates, easily download background maps + and add a correct scale bar to 'OpenStreetMap' plots in any map projection. + date_publication: '2023-10-13' + bug_reports: https://github.com/brry/OSMscale/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OSMscale + url_git: https://github.com/brry/OSMscale +OSNMTF: + version: 0.1.0 + title: Orthogonal Sparse Non-Negative Matrix Tri-Factorization + maintainer: Xiaoyao Yin + description: |- + A novel method to implement cancer subtyping and subtype specific drug targets identification via non-negative matrix tri-factorization. + To improve the interpretability, we introduce orthogonal constraint to the row coefficient matrix and column coefficient matrix. To meet the prior knowledge + that each subtype should be strongly associated with few gene sets, we introduce sparsity constraint to the association sub-matrix. The average residue was + introduced to evaluate the row and column cluster numbers. This is part of the work "Liver Cancer Analysis via Orthogonal Sparse Non-Negative Matrix Tri- + Factorization" which will be submitted to BBRC. + date_publication: '2019-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OSNMTF + url_git: '' +osqp: + version: 0.6.3.3 + title: Quadratic Programming Solver using the 'OSQP' Library + maintainer: Balasubramanian Narasimhan + description: Provides bindings to the 'OSQP' solver. The 'OSQP' solver is a numerical + optimization package or solving convex quadratic programs written in 'C' and based + on the alternating direction method of multipliers. See + for details. + date_publication: '2024-06-08' + bug_reports: https://github.com/osqp/osqp-r/issues + url: https://osqp.org + url_cran: https://CRAN.R-project.org/package=osqp + url_git: '' +osrm: + version: 4.2.0 + title: |- + Interface Between R and the OpenStreetMap-Based Routing Service + OSRM + maintainer: Timothée Giraud + description: |- + An interface between R and the 'OSRM' API. 'OSRM' is a routing + service based on 'OpenStreetMap' data. See for more + information. This package enables the computation of routes, trips, isochrones and + travel distances matrices (travel time and kilometric distance). + date_publication: '2024-05-06' + bug_reports: https://github.com/riatelab/osrm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=osrm + url_git: https://github.com/riatelab/osrm +osrmr: + version: 0.1.36 + title: Wrapper for the 'OSRM' API + maintainer: Adrian Staempfli + description: |- + Wrapper around the 'Open Source Routing Machine (OSRM)' + API . 'osrmr' works with API versions + 4 and 5 and can handle servers that run locally as well as the + 'OSRM' webserver. + date_publication: '2021-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=osrmr + url_git: '' +OssaNMA: + version: 0.1.2 + title: Optimal Sample Size and Allocation with a Network Meta-Analysis + maintainer: Fangshu Ye + description: A system for calculating the minimum total sample size needed to achieve + a prespecified power or the optimal allocation for each treatment group with a + fixed total sample size to maximize the power. + date_publication: '2023-04-26' + bug_reports: https://github.com/fangshuye/OssaNMA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OssaNMA + url_git: https://github.com/fangshuye/OssaNMA +OSsurvival: + version: '1.0' + title: Assessing Surrogacy with a Censored Outcome + maintainer: Layla Parast + description: Identifies the optimal transformation of a surrogate marker and estimates + the proportion of treatment explained (PTE) by the optimally-transformed surrogate + at an earlier time point when the primary outcome of interest is a censored time-to-event + outcome; details are described in Wang et al (2021) . + date_publication: '2022-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OSsurvival + url_git: '' +Ostats: + version: 0.2.0 + title: O-Stats, or Pairwise Community-Level Niche Overlap Statistics + maintainer: Quentin D. Read + description: |- + O-statistics, or overlap statistics, measure the degree of community-level trait overlap. + They are estimated by fitting nonparametric kernel density functions to each species’ trait + distribution and calculating their areas of overlap. For instance, the median pairwise overlap + for a community is calculated by first determining the overlap of each species pair + in trait space, and then taking the median overlap of each species pair in a community. + This median overlap value is called the O-statistic (O for overlap). + The Ostats() function calculates separate univariate overlap statistics for each trait, + while the Ostats_multivariate() function calculates a single multivariate overlap statistic for all traits. + O-statistics can be evaluated against null models to obtain standardized effect sizes. + 'Ostats' is part of the collaborative Macrosystems Biodiversity Project "Local- to continental-scale + drivers of biodiversity across the National Ecological Observatory Network (NEON)." + For more information on this project, see the Macrosystems Biodiversity Website + (). Calculation of O-statistics is described in + Read et al. (2018) , and a teaching module for introducing the + underlying biological concepts at an undergraduate level is described in Grady et al. + (2018) . + date_publication: '2022-09-12' + bug_reports: https://github.com/NEON-biodiversity/Ostats/issues + url: https://neon-biodiversity.github.io/Ostats/ + url_cran: https://CRAN.R-project.org/package=Ostats + url_git: '' +OSTE: + version: '1.0' + title: Optimal Survival Trees Ensemble + maintainer: Naz Gul + description: |- + Function for growing survival trees ensemble ('Naz Gul', 'Nosheen Faiz', 'Dan Brawn', 'Rafal Kulakowski', 'Zardad Khan', and 'Berthold Lausen' (2020) ) is given. + The trees are grown by the method of random survival forest ('Marvin Wright', 'Andreas Ziegler' (2017) ). + The survival trees grown are assessed for both individual and collective performances. + The ensemble can give promising results on fewer survival trees selected in the final ensemble. + date_publication: '2021-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OSTE + url_git: '' +osum: + version: 0.1.0 + title: Provide Summary Information About R Objects + maintainer: Zivan Karaman + description: |- + Inspired by 'S-PLUS' function objects.summary(), provides a + function with the same name that returns data class, storage mode, + mode, type, dimension, and size information for R objects in the + specified environment. Various filtering and sorting options are also + proposed. + date_publication: '2024-08-26' + bug_reports: https://github.com/zivankaraman/osum/issues + url: https://zivankaraman.github.io/osum/ + url_cran: https://CRAN.R-project.org/package=osum + url_git: https://github.com/zivankaraman/osum +otargen: + version: 1.1.5 + title: Access Open Target Genetics + maintainer: Amir Feizi + description: Interact seamlessly with Open Target Genetics' GraphQL endpoint to + query and retrieve tidy data tables, facilitating the analysis of genetic data. + For more information about the Open Target Genetics API (). + date_publication: '2024-09-21' + bug_reports: https://github.com/amirfeizi/otargen/issues + url: https://amirfeizi.github.io/otargen/ + url_cran: https://CRAN.R-project.org/package=otargen + url_git: '' +OTclust: + version: 1.0.6 + title: |- + Mean Partition, Uncertainty Assessment, Cluster Validation and + Visualization Selection for Cluster Analysis + maintainer: Lixiang Zhang + description: Providing mean partition for ensemble clustering by optimal transport + alignment(OTA), uncertainty measures for both partition-wise and cluster-wise + assessment and multiple visualization functions to show uncertainty, for instance, + membership heat map and plot of covering point set. A partition refers to an overall + clustering result. Jia Li, Beomseok Seo, and Lin Lin (2019) . + Lixiang Zhang, Lin Lin, and Jia Li (2020) . + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OTclust + url_git: '' +OTE: + version: 1.0.1 + title: |- + Optimal Trees Ensembles for Regression, Classification and Class + Membership Probability Estimation + maintainer: Zardad Khan + description: Functions for creating ensembles of optimal trees for regression, classification + (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M., Mahmoud, O., Adler, W., + & Lausen, B. (2019). (2019) ) and class membership + probability estimation (Khan, Z, Gul, A, Mahmoud, O, Miftahuddin, M, Perperoglou, + A, Adler, W & Lausen, B (2016) ) are given. + A few trees are selected from an initial set of trees grown by random forest for + the ensemble on the basis of their individual and collective performance. Three + different methods of tree selection for the case of classification are given. + The prediction functions return estimates of the test responses and their class + membership probabilities. Unexplained variations, error rates, confusion matrix, + Brier scores, etc. are also returned for the test data. + date_publication: '2020-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OTE + url_git: '' +otinference: + version: 0.1.0 + title: Inference for Optimal Transport + maintainer: Max Sommerfeld + description: |- + Sample from the limiting distributions of empirical Wasserstein + distances under the null hypothesis and under the alternative. Perform a + two-sample test on multivariate data using these limiting distributions and + binning. + date_publication: '2017-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=otinference + url_git: '' +otp: + version: 0.1.1 + title: One Time Password Generation and Verification + maintainer: Randy Lai + description: |- + Generating and validating One-time Password based on + Hash-based Message Authentication Code (HOTP) + and Time Based One-time Password (TOTP) + according to RFC 4226 and + RFC 6238 . + date_publication: '2024-01-23' + bug_reports: https://github.com/randy3k/otp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=otp + url_git: https://github.com/randy3k/otp +otpr: + version: 0.5.1 + title: An R Wrapper for the 'OpenTripPlanner' REST API + maintainer: Marcus Young + description: |- + A wrapper for the 'OpenTripPlanner' + REST API. Queries are submitted to the relevant 'OpenTripPlanner' API resource, the response + is parsed and useful R objects are returned. + date_publication: '2022-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=otpr + url_git: '' +OTrecod: + version: 0.1.2 + title: Data Fusion using Optimal Transportation Theory + maintainer: Gregory Guernec + description: In the context of data fusion, the package provides a set of functions + dedicated to the solving of 'recoding problems' using optimal transportation theory + (Gares, Guernec, Savy (2019) and Gares, Omer (2020) + ). From two databases with no overlapping part + except a subset of shared variables, the functions of the package assist users + until obtaining a unique synthetic database, where the missing information is + fully completed. + date_publication: '2022-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OTrecod + url_git: '' +otrimle: + version: '2.0' + title: Robust Model-Based Clustering + maintainer: Pietro Coretto + description: Performs robust cluster analysis allowing for outliers and noise that + cannot be fitted by any cluster. The data are modelled by a mixture of Gaussian + distributions and a noise component, which is an improper uniform distribution + covering the whole Euclidean space. Parameters are estimated by (pseudo) maximum + likelihood. This is fitted by a EM-type algorithm. See Coretto and Hennig (2016) + , and Coretto and Hennig (2017) . + date_publication: '2021-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=otrimle + url_git: '' +otrKM: + version: 0.2.1 + title: |- + Optimal Treatment Regimes in Survival Contexts with + Kaplan-Meier-Like Estimators + maintainer: Junwen Xia + description: |- + Provide methods for estimating optimal treatment regimes in survival contexts + with Kaplan-Meier-like estimators when no unmeasured confounding assumption is + satisfied (Jiang, R., Lu, W., Song, R., and Davidian, M. (2017) ) + and when no unmeasured confounding assumption fails to hold and a binary instrument + is available (Xia, J., Zhan, Z., Zhang, J. (2022) ). + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=otrKM + url_git: '' +OTRselect: + version: '1.2' + title: Variable Selection for Optimal Treatment Decision + maintainer: Shannon T. Holloway + description: |- + A penalized regression framework that can simultaneously estimate + the optimal treatment strategy and identify important variables. + Appropriate for either censored or uncensored continuous response. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OTRselect + url_git: '' +otsfeatures: + version: 1.0.0 + title: Ordinal Time Series Analysis + maintainer: Angel Lopez-Oriona + description: |- + An implementation of several functions for feature extraction in + ordinal time series datasets. Specifically, some of the features proposed by + Weiss (2019) can be computed. + These features can be used to perform inferential tasks or to feed machine + learning algorithms for ordinal time series, among others. The package also includes some + interesting datasets containing financial time series. Practitioners from a + broad variety of fields could benefit from the general framework provided + by 'otsfeatures'. + date_publication: '2023-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=otsfeatures + url_git: '' +ottr: + version: 1.5.1 + title: An R Autograding Extension for Otter-Grader + maintainer: Christopher Pyles + description: |- + An R autograding extension for Otter-Grader (). It supports + grading R scripts, R Markdown documents, and R Jupyter Notebooks. + date_publication: '2024-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ottr + url_git: '' +ottrpal: + version: 1.2.1 + title: |- + Companion Tools for Open-Source Tools for Training Resources + (OTTR) + maintainer: Candace Savonen + description: |- + Tools for converting Open-Source Tools for Training Resources + (OTTR) courses into Leanpub or Coursera courses. 'ottrpal' is for use + with the OTTR Template repository to create courses. + date_publication: '2024-01-09' + bug_reports: https://github.com/jhudsl/ottrpal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ottrpal + url_git: https://github.com/jhudsl/ottrpal +otuSummary: + version: 0.1.2 + title: |- + Summarizing OTU Table Regarding the Composition, Abundance and + Beta Diversity of Abundant and Rare Biospheres + maintainer: Sizhong Yang + description: Summarizes the taxonomic composition, diversity contribution of the + rare and abundant community by using OTU (operational taxonomic unit) table which + was generated by analyzing pipeline of 'QIIME' or 'mothur'. The rare biosphere + in this package is subset by the relative abundance threshold (for details about + rare biosphere please see Lynch and Neufeld (2015) ). + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=otuSummary + url_git: https://github.com/cam315/otuSummary +OTUtable: + version: 1.1.2 + title: |- + North Temperate Lakes - Microbial Observatory 16S Time Series + Data and Functions + maintainer: Alexandra Linz + description: 'Analyses of OTU tables produced by 16S rRNA gene amplicon sequencing, + as well as example data. It contains the data and scripts used in the paper Linz, + et al. (2017) "Bacterial community composition and dynamics spanning five years + in freshwater bog lakes," .' + date_publication: '2018-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OTUtable + url_git: '' +ouch: + version: '2.20' + title: |- + Ornstein-Uhlenbeck Models for Phylogenetic Comparative + Hypotheses + maintainer: Aaron A. King + description: Fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic + tree. + date_publication: '2024-07-04' + bug_reports: https://github.com/kingaa/ouch/issues/ + url: https://kingaa.github.io/ouch/ + url_cran: https://CRAN.R-project.org/package=ouch + url_git: '' +ouladFormat: + version: 1.1.2 + title: |- + Loads and Formats the Open University Learning Analytics Dataset + for Data Analysis + maintainer: Emma Howard + description: |- + The Open University Learning Analytics Dataset (OULAD) is available from + Kuzilek et al. (2017) . The 'ouladFormat' + package loads, cleans and formats the OULAD for data analysis (each row of the + returned data set is an individual student). The package’s main function, + combined_dataset(), allows the user to choose whether the returned + data set includes assessment, demographics, virtual learning environment (VLE), + or registration variables etc. + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ouladFormat + url_git: '' +outbreaker2: + version: 1.1.3 + title: |- + Bayesian Reconstruction of Disease Outbreaks by Combining + Epidemiologic and Genomic Data + maintainer: Finlay Campbell + description: |- + Bayesian reconstruction of disease outbreaks using epidemiological + and genetic information. Jombart T, Cori A, Didelot X, Cauchemez S, Fraser + C and Ferguson N. 2014. . Campbell, F, + Cori A, Ferguson N, Jombart T. 2019. . + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=outbreaker2 + url_git: '' +outbreaks: + version: 1.9.0 + title: A Collection of Disease Outbreak Data + maintainer: Finlay Campbell + description: |- + Empirical or simulated disease outbreak data, provided either as + RData or as text files. + date_publication: '2020-09-28' + bug_reports: https://github.com/reconhub/outbreaks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=outbreaks + url_git: https://github.com/reconhub/outbreaks +outcomerate: + version: 1.0.1 + title: AAPOR Survey Outcome Rates + maintainer: Rafael Pilliard Hellwig + description: Standardized survey outcome rate functions, including the response + rate, contact rate, cooperation rate, and refusal rate. These outcome rates allow + survey researchers to measure the quality of survey data using definitions published + by the American Association of Public Opinion Research (AAPOR). For details on + these standards, see AAPOR (2016) . + date_publication: '2018-10-06' + bug_reports: https://github.com/ropensci/outcomerate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=outcomerate + url_git: https://github.com/ropensci/outcomerate +OutcomeWeights: + version: 0.1.1 + title: Outcome Weights of Treatment Effect Estimators + maintainer: Michael C. Knaus + description: |- + Many treatment effect estimators can be written as weighted outcomes. + These weights have established use cases like checking covariate balancing via packages like 'cobalt'. + This package takes the original estimator objects and outputs these outcome weights. + It builds on the general framework of Knaus (2024) . + This version is compatible with the 'grf' package and provides an internal implementation of Double Machine Learning. + date_publication: '2024-12-20' + bug_reports: https://github.com/MCKnaus/OutcomeWeights/issues + url: '' + url_cran: https://CRAN.R-project.org/package=OutcomeWeights + url_git: https://github.com/MCKnaus/OutcomeWeights +outForest: + version: 1.0.1 + title: Multivariate Outlier Detection and Replacement + maintainer: Michael Mayer + description: |- + Provides a random forest based implementation of the method + described in Chapter 7.1.2 (Regression model based anomaly detection) + of Chandola et al. (2009) . It works as + follows: Each numeric variable is regressed onto all other variables + by a random forest. If the scaled absolute difference between observed + value and out-of-bag prediction of the corresponding random forest is + suspiciously large, then a value is considered an outlier. The package + offers different options to replace such outliers, e.g. by realistic + values found via predictive mean matching. Once the method is trained + on a reference data, it can be applied to new data. + date_publication: '2023-05-21' + bug_reports: https://github.com/mayer79/outForest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=outForest + url_git: https://github.com/mayer79/outForest +outlierensembles: + version: 0.1.2 + title: A Collection of Outlier Ensemble Algorithms + maintainer: Sevvandi Kandanaarachchi + description: |- + Ensemble functions for outlier/anomaly detection. There is a new ensemble method proposed using + Item Response Theory. Existing outlier ensemble methods from Schubert et al (2012) , + Chiang et al (2017) and Aggarwal and Sathe (2015) + are also included. + date_publication: '2025-02-22' + bug_reports: '' + url: https://sevvandi.github.io/outlierensembles/ + url_cran: https://CRAN.R-project.org/package=outlierensembles + url_git: '' +outliers: + version: '0.15' + title: Tests for Outliers + maintainer: Lukasz Komsta + description: |- + A collection of some tests commonly used for identifying + outliers. + date_publication: '2022-03-26' + bug_reports: '' + url: http://www.komsta.net/ + url_cran: https://CRAN.R-project.org/package=outliers + url_git: '' +outliers.ts.oga: + version: 1.0.1 + title: Efficient Outlier Detection for Large Time Series Databases + maintainer: Pedro Galeano + description: Programs for detecting and cleaning outliers in single time series + and in time series from homogeneous and heterogeneous databases using an Orthogonal + Greedy Algorithm (OGA) for saturated linear regression models. The programs implement + the procedures presented in the paper entitled "Efficient Outlier Detection for + Large Time Series Databases" by Pedro Galeano, Daniel Peña and Ruey S. Tsay (2025), + working paper, Universidad Carlos III de Madrid. Version 1.0.1 contains some improvements + to the algorithm, so the results may vary slightly compared to those obtained + with version 0.0.1. + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=outliers.ts.oga + url_git: '' +OutliersLearn: + version: 1.0.0 + title: |- + Educational Outlier Package with Common Outlier Detection + Algorithms + maintainer: Andres Missiego Manjon + description: |- + Provides implementations of some of the most important outlier detection algorithms. + Includes a tutorial mode option that shows a description of each algorithm and provides + a step-by-step execution explanation of how it identifies outliers from the given data + with the specified input parameters. References include the works of Azzedine Boukerche, + Lining Zheng, and Omar Alfandi (2020) , Abir Smiti (2020) + , and Xiaogang Su, Chih-Ling Tsai (2011) + . + date_publication: '2024-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OutliersLearn + url_git: '' +OutliersO3: + version: 0.6.3 + title: Draws Overview of Outliers (O3) Plots + maintainer: Antony Unwin + description: Potential outliers are identified for all combinations of a dataset's + variables. O3 plots are described in Unwin(2019) . + The available methods are HDoutliers() from the package 'HDoutliers', FastPCS() + from the package 'FastPCS', mvBACON() from 'robustX', adjOutlyingness() from 'robustbase', + DectectDeviatingCells() from 'cellWise', covMcd() from 'robustbase'. + date_publication: '2020-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OutliersO3 + url_git: '' +outliertree: + version: 1.10.0 + title: Explainable Outlier Detection Through Decision Tree Conditioning + maintainer: David Cortes + description: |- + Outlier detection method that flags suspicious values within observations, + constrasting them against the normal values in a user-readable format, potentially + describing conditions within the data that make a given outlier more rare. + Full procedure is described in Cortes (2020) . + Loosely based on the 'GritBot' software. + date_publication: '2024-09-06' + bug_reports: https://github.com/david-cortes/outliertree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=outliertree + url_git: https://github.com/david-cortes/outliertree +outqrf: + version: 1.0.0 + title: Find the Outlier by Quantile Random Forests + maintainer: Tengfei Xu + description: Provides a method to find the outlier in custom data by quantile random + forests method. Introduced by Meinshausen Nicolai (2006) . + It directly calls the ranger() function of the 'ranger' package to perform data + fitting and prediction. We also implement the evaluation of outlier prediction + results. Compared with random forest detection of outliers, this method has higher + accuracy and stability on large datasets. + date_publication: '2024-09-10' + bug_reports: https://github.com/flystar233/outqrf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=outqrf + url_git: https://github.com/flystar233/outqrf +outreg: + version: 0.2.2 + title: Regression Table for Publication + maintainer: Kota Mori + description: |- + Create regression tables for publication. + Currently supports 'lm', 'glm', 'survreg', and 'ivreg' outputs. + date_publication: '2017-03-14' + bug_reports: https://github.com/kota7/outreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=outreg + url_git: https://github.com/kota7/outreg +OutSeekR: + version: 1.0.0 + title: |- + Statistical Approach to Outlier Detection in RNA-Seq and Related + Data + maintainer: Paul Boutros + description: |- + An approach to outlier detection in RNA-seq and related data + based on five statistics. 'OutSeekR' implements an outlier test by comparing + the distributions of these statistics in observed data with those of + simulated null data. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OutSeekR + url_git: '' +OUwie: + version: '2.10' + title: Analysis of Evolutionary Rates in an OU Framework + maintainer: Jeremy Beaulieu + description: Estimates rates for continuous character evolution under Brownian motion + and a new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength + of the pull and stochastic motion to vary across selective regimes. Beaulieu et + al (2012). + date_publication: '2022-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OUwie + url_git: https://github.com/thej022214/OUwie +overdisp: + version: 0.1.2 + title: Overdispersion in Count Data Multiple Regression Analysis + maintainer: Rafael Freitas Souza + description: |- + Detection of overdispersion in count data for multiple regression analysis. + Log-linear count data regression is one of the most popular techniques for predictive + modeling where there is a non-negative discrete quantitative dependent variable. In + order to ensure the inferences from the use of count data models are appropriate, + researchers may choose between the estimation of a Poisson model and a negative binomial + model, and the correct decision for prediction from a count data estimation is directly + linked to the existence of overdispersion of the dependent variable, conditional to the + explanatory variables. Based on the studies of Cameron and Trivedi (1990) + and Cameron and Trivedi (2013, ISBN:978-1107667273), + the overdisp() command is a contribution to researchers, providing a fast and secure + solution for the detection of overdispersion in count data. Another advantage is that + the installation of other packages is unnecessary, since the command runs in the basic + R language. + date_publication: '2023-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=overdisp + url_git: '' +overlap: + version: 0.3.9 + title: |- + Estimates of Coefficient of Overlapping for Animal Activity + Patterns + maintainer: Liz A.D. Campbell + description: |- + Provides functions to fit kernel density functions to + data on temporal activity patterns of animals; estimate coefficients + of overlapping of densities for two species; and calculate bootstrap + estimates of confidence intervals. As in Ridout and Linkie (2009) . + date_publication: '2024-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=overlap + url_git: '' +overlapping: + version: '2.2' + title: Estimation of Overlapping in Empirical Distributions + maintainer: Massimiliano Pastore + description: Functions for estimating the overlapping area of two or more kernel + density estimations from empirical data. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=overlapping + url_git: '' +overlapptest: + version: '1.3' + title: Test Overlapping of Polygons Against Random Rotation + maintainer: Marcelino de la Cruz + description: Tests the observed overlapping polygon area in a collection of polygons + against a null model of random rotation, as explained in De la Cruz et al. (2017) + . + date_publication: '2023-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=overlapptest + url_git: '' +overture: + version: 0.4-0 + title: Tools for Writing MCMC + maintainer: Kurtis Shuler + description: |- + Simplifies MCMC setup by automatically looping through sampling + functions and saving the results. Reduces the memory footprint of running + MCMC and saves samples to disk as the chain runs. Allows samples from the + chain to be analyzed while the MCMC is still running. Provides functions + for commonly performed operations such as calculating Metropolis acceptance + ratios and creating adaptive Metropolis samplers. References: Roberts and + Rosenthal (2009) . + date_publication: '2019-08-10' + bug_reports: https://github.com/kurtis-s/overture/issues + url: '' + url_cran: https://CRAN.R-project.org/package=overture + url_git: https://github.com/kurtis-s/overture +overturemapsr: + version: 0.1.0 + title: Download Overture Maps Data in R + maintainer: Dennis Irorere + description: Overture Maps offers free and open geospatial map data sourced from + various providers and standardized to a common schema. This tool allows you to + download Overture Maps data for a specific region of interest and convert it to + several different file formats. For more information, visit . + date_publication: '2025-02-14' + bug_reports: https://github.com/denironyx/overturemapsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=overturemapsr + url_git: https://github.com/denironyx/overturemapsr +overtureR: + version: 0.2.4 + title: Load 'Overture' Datasets as 'dbplyr' and 'sf'-Ready Data Frames + maintainer: Arthur Gailes + description: |- + An integrated R interface to the 'Overture' API + (). Allows R users to return 'Overture' data as + 'dbplyr' data frames or materialized 'sf' spatial data frames. + date_publication: '2024-12-11' + bug_reports: https://github.com/arthurgailes/overtureR/issues + url: https://arthurgailes.github.io/overtureR/ + url_cran: https://CRAN.R-project.org/package=overtureR + url_git: https://github.com/arthurgailes/overtureR +overviewR: + version: 0.0.13 + title: Easily Extracting Information About Your Data + maintainer: Cosima Meyer + description: |- + Makes it easy to display descriptive information on a data + set. Getting an easy overview of a data set by displaying and + visualizing sample information in different tables (e.g., time and + scope conditions). The package also provides publishable 'LaTeX' code + to present the sample information. + date_publication: '2023-02-15' + bug_reports: https://github.com/cosimameyer/overviewR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=overviewR + url_git: https://github.com/cosimameyer/overviewR +OVL.CI: + version: 0.1.0 + title: |- + Inference on the Overlap Coefficient: The Binormal Approach and + Alternatives + maintainer: Alba M. Franco-Pereira + description: Provides functions to construct confidence intervals for the Overlap + Coefficient (OVL). OVL measures the similarity between two distributions through + the overlapping area of their distribution functions. Given its intuitive description + and ease of visual representation by the straightforward depiction of the amount + of overlap between the two corresponding histograms based on samples of measurements + from each one of the two distributions, the development of accurate methods for + confidence interval construction can be useful for applied researchers. Implements + methods based on the work of Franco-Pereira, A.M., Nakas, C.T., Reiser, B., and + Pardo, M.C. (2021) . + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OVL.CI + url_git: '' +OVtool: + version: 1.0.3 + title: Omitted Variable Tool + maintainer: Lane Burgette + description: This tool was designed to assess the sensitivity of research findings + to omitted variables when estimating causal effects using propensity score (PS) + weighting. This tool produces graphics and summary results that will enable a + researcher to quantify the impact an omitted variable would have on their results. + Burgette et al. (2021) describe the methodology behind the primary function in + this package, ov_sim. The method is demonstrated in Griffin et al. (2020) . + date_publication: '2021-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OVtool + url_git: '' +owd: + version: 1.0.6 + title: Open Working Directory + maintainer: Benjamin G. Feakins + description: Open the current working directory (or a given directory path) in your + computer's file manager. + date_publication: '2020-08-05' + bug_reports: https://github.com/Feakster/owd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=owd + url_git: https://github.com/Feakster/owd +owdbr: + version: 1.0.1.1 + title: Open Welfare Data Brazil + maintainer: Joao Pedro Oliveira dos Santos + description: Tools for collecting municipal-level data + from several Brazilian governmental social programs. + date_publication: '2019-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=owdbr + url_git: https://github.com/kimjoaoun/owdbr +OWEA: + version: 0.1.2 + title: |- + Optimal Weight Exchange Algorithm for Optimal Designs for Three + Models + maintainer: Shuai Hao + description: |- + An implementation of optimal weight exchange algorithm Yang(2013) for three models. + They are Crossover model with subject dropout, crossover model with proportional + first order residual effects and interference model. You can use it to find either + A-opt or D-opt approximate designs. Exact designs can be automatically rounded + from approximate designs and relative efficiency is provided as well. + date_publication: '2022-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OWEA + url_git: '' +owidapi: + version: 0.1.0 + title: Access the Our World in Data Chart API + maintainer: Christoph Scheuch + description: |- + Retrieve data from the Our World in Data (OWID) Chart API + . OWID provides public access to + more than 5,000 charts focusing on global problems such as poverty, + disease, hunger, climate change, war, existential risks, and inequality. + date_publication: '2025-02-27' + bug_reports: https://github.com/tidy-intelligence/r-owidapi/issues + url: https://tidy-intelligence.github.io/r-owidapi/ + url_cran: https://CRAN.R-project.org/package=owidapi + url_git: https://github.com/tidy-intelligence/r-owidapi +owidR: + version: 1.4.2 + title: Import Data from Our World in Data + maintainer: Piers York + description: Import data from 'Our World in Data', an organisation which publishes + research and data on global economic and social issues. + date_publication: '2023-10-30' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=owidR + url_git: +owmr: + version: 0.8.2 + title: OpenWeatherMap API Wrapper + maintainer: Stefan Kuethe + description: |- + Accesses OpenWeatherMap's (owm) API. + 'owm' itself is a service providing weather data in the past, in the future and now. + Furthermore, 'owm' serves weather map layers usable in frameworks like 'leaflet'. + In order to access the API, you need to sign up for an API key. There are free and paid plans. + Beside functions for fetching weather data from 'owm', 'owmr' supplies + tools to tidy up fetched data (for fast and simple access) and to show it on leaflet maps. + date_publication: '2020-01-11' + bug_reports: https://github.com/crazycapivara/owmr/issues/ + url: https://crazycapivara.github.io/owmr/ + url_cran: https://CRAN.R-project.org/package=owmr + url_git: https://github.com/crazycapivara/owmr/ +ows4R: + version: '0.4' + title: Interface to OGC Web-Services (OWS) + maintainer: Emmanuel Blondel + description: |- + Provides an Interface to Web-Services defined as standards by the Open Geospatial Consortium (OGC), including Web Feature Service + (WFS) for vector data, Web Coverage Service (WCS), Catalogue Service (CSW) for ISO/OGC metadata, Web Processing Service (WPS) for data processes, + and associated standards such as the common web-service specification (OWS) and OGC Filter Encoding. Partial support is provided for the Web Map + Service (WMS). The purpose is to add support for additional OGC service standards such as Web Coverage Processing Service (WCPS), the Sensor + Observation Service (SOS), or even new standard services emerging such OGC API or SensorThings. + date_publication: '2024-06-26' + bug_reports: https://github.com/eblondel/ows4R/issues + url: https://eblondel.github.io/ows4R/ + url_cran: https://CRAN.R-project.org/package=ows4R + url_git: https://github.com/eblondel/ows4R +ox: + version: 0.1.0 + title: Shorthand if-Else + maintainer: Dawid Kałędkowski + description: |- + Short hand if-else function to easily switch the values depending + on a logical condition. + date_publication: '2021-12-15' + bug_reports: https://github.com/gogonzo/ox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ox + url_git: '' +oxcAAR: + version: 1.1.1 + title: Interface to 'OxCal' Radiocarbon Calibration + maintainer: Hinz Martin + description: A set of tools that enables using 'OxCal' from within R. 'OxCal' () + is a standard archaeological tool intended to provide 14C calibration and analysis + of archaeological and environmental chronological information. 'OxcAAR' allows + simple calibration with 'Oxcal' and plotting of the results as well as the execution + of sophisticated ('OxCal') code and the import of the results of bulk analysis + and complex Bayesian sequential calibration. + date_publication: '2021-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oxcAAR + url_git: '' +OxyBS: + version: '1.5' + title: Processing of Oxy-Bisulfite Microarray Data + maintainer: E. Andres Houseman + description: |2- + + Provides utilities for processing of Oxy-Bisulfite microarray data + (e.g. via the Illumina Infinium platform, ) + with tandem arrays, one using conventional + bisulfite conversion, the other using oxy-bisulfite conversion. + date_publication: '2017-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=OxyBS + url_git: '' +oysteR: + version: 0.1.1 + title: Scans R Projects for Vulnerable Third Party Dependencies + maintainer: Colin Gillespie + description: |- + Collects a list of your third party R packages, and + scans them with the 'OSS' Index provided by 'Sonatype', reporting back + on any vulnerabilities that are found in the third party packages you + use. + date_publication: '2021-01-10' + bug_reports: https://github.com/sonatype-nexus-community/oysteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=oysteR + url_git: https://github.com/sonatype-nexus-community/oysteR +oz: + version: 1.0-22 + title: Plot the Australian Coastline and States + maintainer: Kurt Hornik + description: |- + Functions for plotting Australia's coastline and state + boundaries. + date_publication: '2023-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=oz + url_git: '' +ozbabynames: + version: 0.1.0 + title: Australian Popular Baby Names + maintainer: Rob Hyndman + description: Data on the most popular baby names by sex and year, and for each state + in Australia, as provided by the state and territory governments. The quality + and quantity of the data varies with the state. + date_publication: '2024-10-25' + bug_reports: https://github.com/robjhyndman/ozbabynames/issues + url: https://pkg.robjhyndman.com/ozbabynames/ + url_cran: https://CRAN.R-project.org/package=ozbabynames + url_git: https://github.com/robjhyndman/ozbabynames +ozmaps: + version: 0.4.5 + title: Australia Maps + maintainer: Michael Sumner + description: |- + Maps of Australian coastline and administrative regions. Data + can be drawn or accessed directly as simple features objects. Includes + simple functions for country or state maps of Australia and in-built data + sets of administrative regions from the Australian Bureau of Statistics + . Layers include electoral divisions and local + government areas, simplified from the original sources but with sufficient + detail to allow mapping of a local municipality. + date_publication: '2021-08-03' + bug_reports: https://github.com/mdsumner/ozmaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ozmaps + url_git: https://github.com/mdsumner/ozmaps +p3state.msm: + version: 1.3.2 + title: Analyzing Survival Data from an Illness-Death Model + maintainer: Luis Meira-Machado + description: |- + Contains functions for data preparation, + prediction of transition probabilities, + estimating semi-parametric regression models + and for implementing nonparametric estimators + for other quantities. See Meira-Machado and + Roca-Pardiñas (2011) . + date_publication: '2023-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=p3state.msm + url_git: '' +pa: + version: 1.2-4 + title: Performance Attribution for Equity Portfolios + maintainer: Yang Lu + description: 'It provides tools for conducting performance attribution for equity + portfolios. The package uses two methods: the Brinson method and a regression-based + analysis.' + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pa + url_git: '' +paar: + version: 1.0.1 + title: Precision Agriculture Data Analysis + maintainer: Pablo Paccioretti + description: |- + Precision agriculture spatial data + depuration and homogeneous zones (management zone) delineation. + The package includes functions that performs protocols for data cleaning + management zone delineation and zone comparison; protocols are described in + Paccioretti et al., (2020) . + date_publication: '2024-07-30' + bug_reports: https://github.com/PPaccioretti/paar/issues + url: https://ppaccioretti.github.io/paar/ + url_cran: https://CRAN.R-project.org/package=paar + url_git: https://github.com/PPaccioretti/paar +PAC: + version: 1.1.4 + title: |- + Partition-Assisted Clustering and Multiple Alignments of + Networks + maintainer: Ye Henry Li + description: Implements partition-assisted clustering and multiple alignments of + networks. It 1) utilizes partition-assisted clustering to find robust and accurate + clusters and 2) discovers coherent relationships of clusters across multiple samples. + It is particularly useful for analyzing single-cell data set. Please see Li et + al. (2017) for detail method description. + date_publication: '2021-02-18' + bug_reports: '' + url: https://doi.org/10.1371/journal.pcbi.1005875 + url_cran: https://CRAN.R-project.org/package=PAC + url_git: '' +pack: + version: 0.1-1 + title: Convert values to/from raw vectors + maintainer: Josh Ulrich + description: Functions to easily convert data to binary formats other programs/machines + can understand. + date_publication: '' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pack + url_git: '' +packageDiff: + version: '0.1' + title: Compare R Package Differences + maintainer: Cole Beck + description: |- + It provides utility functions for investigating changes within R + packages. The pkgInfo() function extracts package information such as + exported and non-exported functions as well as their arguments. The + pkgDiff() function compares this information for two versions of a package + and creates a diff file viewable in a browser. + date_publication: '2020-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=packageDiff + url_git: https://github.com/couthcommander/packageDiff +packagefinder: + version: 0.3.5 + title: |- + Comfortable Search for R Packages on CRAN, Either Directly from + the R Console or with an R Studio Add-in + maintainer: Joachim Zuckarelli + description: Search for R packages on CRAN directly from the R console, based on + the packages' titles, short and long descriptions, or other fields. Combine multiple + keywords with logical operators ('and', 'or'), view detailed information on any + package and keep track of the latest package contributions to CRAN. If you don't + want to search from the R console, use the comfortable R Studio add-in. + date_publication: '2023-08-08' + bug_reports: https://github.com/jsugarelli/packagefinder/issues + url: http://www.zuckarelli.de/packagefinder/tutorial.html + url_cran: https://CRAN.R-project.org/package=packagefinder + url_git: https://github.com/jsugarelli/packagefinder/ +packagepal: + version: 0.1.0 + title: Guidelines and Checklists for Building CRAN-Worthy Packages + maintainer: Lee Durbin + description: |- + Provides essential checklists for R package developers, whether + you're creating your first package or beginning a new project. This tool + guides you through each step of the development process, including specific + considerations for submitting your package to the Comprehensive R Archive + Network (CRAN). Simplify your workflow and ensure adherence to best + practices with 'packagepal'. + date_publication: '2023-08-14' + bug_reports: https://github.com/lddurbin/packagepal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=packagepal + url_git: https://github.com/lddurbin/packagepal +packager: + version: 1.15.2 + title: Create, Build and Maintain Packages + maintainer: Andreas Dominik Cullmann + description: |- + Helper functions for package creation, building and + maintenance. Designed to work with a build system such as 'GNU make' or + package 'fakemake' to help you to conditionally work through the stages of + package development (such as spell checking, linting, testing, before + building and checking a package). + date_publication: '2023-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=packager + url_git: https://gitlab.com/fvafrcu/packager +packageRank: + version: 0.9.4 + title: |- + Computation and Visualization of Package Download Counts and + Percentile Ranks + maintainer: Peter Li + description: |- + Compute and visualize the cross-sectional and longitudinal number + and rank percentile of package downloads from Posit/RStudio's CRAN mirror. + date_publication: '2024-11-13' + bug_reports: https://github.com/lindbrook/packageRank/issues + url: '' + url_cran: https://CRAN.R-project.org/package=packageRank + url_git: https://github.com/lindbrook/packageRank +packcircles: + version: 0.3.7 + title: Circle Packing + maintainer: Michael Bedward + description: Algorithms to find arrangements of non-overlapping circles. + date_publication: '2024-11-21' + bug_reports: https://github.com/mbedward/packcircles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=packcircles + url_git: https://github.com/mbedward/packcircles +packer: + version: 0.1.3 + title: An Opinionated Framework for Using 'JavaScript' + maintainer: John Coene + description: |2- + + Enforces good practice and provides convenience functions to make work with 'JavaScript' + not just easier but also scalable. It is a robust wrapper to 'NPM', 'yarn', and 'webpack' that + enables to compartmentalize 'JavaScript' code, leverage 'NPM' and 'yarn' packages, include + 'TypeScript', 'React', or 'Vue' in web applications, and much more. + date_publication: '2022-05-28' + bug_reports: https://github.com/JohnCoene/packer/issues + url: https://packer.john-coene.com + url_cran: https://CRAN.R-project.org/package=packer + url_git: https://github.com/JohnCoene/packer +packHV: + version: '2.2' + title: A few Useful Functions for Statisticians + maintainer: Hugo Varet + description: 'Various useful functions for statisticians: describe data, plot Kaplan-Meier + curves with numbers of subjects at risk, compare data sets, display spaghetti-plot, + build multi-contingency tables...' + date_publication: '2019-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=packHV + url_git: '' +packMBPLSDA: + version: 0.9.0 + title: Multi-Block Partial Least Squares Discriminant Analysis + maintainer: Marion Brandolini-Bunlon + description: 'Several functions are provided to implement a MBPLSDA : components + search, optimal model components number search, optimal model validity test by + permutation tests, observed values evaluation of optimal model parameters and + predicted categories, bootstrap values evaluation of optimal model parameters + and predicted cross-validated categories. The use of this package is described + in Brandolini-Bunlon et al (2019. Multi-block PLS discriminant analysis for the + joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10):134).' + date_publication: '2022-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=packMBPLSDA + url_git: '' +packrat: + version: 0.9.2 + title: |- + A Dependency Management System for Projects and their R Package + Dependencies + maintainer: Aron Atkins + description: |- + Manage the R packages your project depends on in an isolated, + portable, and reproducible way. + date_publication: '2023-09-05' + bug_reports: https://github.com/rstudio/packrat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=packrat + url_git: https://github.com/rstudio/packrat +PACLasso: + version: 1.0.0 + title: Penalized and Constrained Lasso Optimization + maintainer: Courtney Paulson + description: |- + An implementation of both the equality and inequality constrained lasso + functions for the algorithm described in "Penalized and Constrained Optimization" + by James, Paulson, and Rusmevichientong (Journal of the American Statistical Association, 2019; + see for a full-text version of the paper). + The algorithm here is designed to allow users to define linear constraints (either equality + or inequality constraints) and use a penalized regression approach to solve the constrained + problem. The functions here are used specifically for constraints with the lasso formulation, + but the method described in the PaC paper can be used for a variety of scenarios. In addition + to the simple examples included here with the corresponding functions, complete code to + entirely reproduce the results of the paper is available online through the Journal of the + American Statistical Association. + date_publication: '2019-04-29' + bug_reports: '' + url: http://www-bcf.usc.edu/~gareth/research/PAC.pdf + url_cran: https://CRAN.R-project.org/package=PACLasso + url_git: '' +pacman: + version: 0.5.1 + title: Package Management Tool + maintainer: Tyler Rinker + description: |- + Tools to more conveniently perform tasks associated with + add-on packages. pacman conveniently wraps library and package + related functions and names them in an intuitive and consistent + fashion. It seeks to combine functionality from lower level + functions which can speed up workflow. + date_publication: '2019-03-11' + bug_reports: https://github.com/trinker/pacman/issues?state=open + url: '' + url_cran: https://CRAN.R-project.org/package=pacman + url_git: https://github.com/trinker/pacman +paco: + version: 0.4.2 + title: Procrustes Application to Cophylogenetic Analysis + maintainer: Matthew Hutchinson + description: |- + Procrustes analyses to infer co-phylogenetic + matching between pairs of phylogenetic trees. + date_publication: '2020-08-25' + bug_reports: '' + url: https://www.uv.es/cophylpaco/ + url_cran: https://CRAN.R-project.org/package=paco + url_git: '' +pacotest: + version: 0.4.2 + title: |- + Testing for Partial Copulas and the Simplifying Assumption in + Vine Copulas + maintainer: Malte S. Kurz + description: Routines for two different test types, the Constant Conditional Correlation + (CCC) test and the Vectorial Independence (VI) test are provided (Kurz and Spanhel + (2022) ). The tests can be applied to check whether a + conditional copula coincides with its partial copula. Functions to test whether + a regular vine copula satisfies the so-called simplifying assumption or to test + a single copula within a regular vine copula to be a (j-1)-th order partial copula + are available. The CCC test comes with a decision tree approach to allow testing + in high-dimensional settings. + date_publication: '2022-11-04' + bug_reports: https://github.com/MalteKurz/pacotest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pacotest + url_git: '' +pacs: + version: 0.6.0 + title: Supplementary Tools for R Packages Developers + maintainer: Maciej Nasinski + description: |- + Supplementary utils for CRAN maintainers and R packages developers. + Validating the library, packages and lock files. + Exploring a complexity of a specific package like evaluating its size in bytes with all dependencies. + The shiny app complexity could be explored too. + Assessing the life duration of a specific package version. + Checking a CRAN package check page status for any errors and warnings. + Retrieving a DESCRIPTION or NAMESPACE file for any package version. + Comparing DESCRIPTION or NAMESPACE files between different package versions. + Getting a list of all releases for a specific package. + The Bioconductor is partly supported. + date_publication: '2024-09-27' + bug_reports: https://github.com/Polkas/pacs/issues + url: https://polkas.github.io/pacs/ + url_cran: https://CRAN.R-project.org/package=pacs + url_git: https://github.com/Polkas/pacs +pacta.multi.loanbook: + version: 0.1.1 + title: Run 'PACTA' on Multiple Loan Books Easily + maintainer: Jacob Kastl + description: |- + Run Paris Agreement Capital Transition Assessment ('PACTA') analyses + on multiple loan books in a structured way. Provides access to standard + 'PACTA' metrics and additional 'PACTA'-related metrics for multiple loan books. + Results take the form of 'csv' files and plots and are exported to + user-specified project paths. + date_publication: '2025-01-09' + bug_reports: '' + url: https://rmi-pacta.github.io/pacta.multi.loanbook/ + url_cran: https://CRAN.R-project.org/package=pacta.multi.loanbook + url_git: https://github.com/RMI-PACTA/pacta.multi.loanbook/ +pacu: + version: 0.1.44 + title: Precision Agriculture Computational Utilities + maintainer: dos Santos Caio + description: Support for a variety of commonly used precision agriculture operations. + Includes functions to download and process raw satellite images from Sentinel-2 + . Includes functions + that download vegetation index statistics for a given period of time, without + the need to download the raw images . + There are also functions to download and visualize weather data in a historical + context. Lastly, the package also contains functions to process yield monitor + data. These functions can build polygons around recorded data points, evaluate + the overlap between polygons, clean yield data, and smooth yield maps. + date_publication: '2024-12-17' + bug_reports: https://github.com/cldossantos/pacu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pacu + url_git: '' +PACVr: + version: 1.0.11 + title: Plastome Assembly Coverage Visualization + maintainer: Michael Gruenstaeudl + description: Visualizes the coverage depth of a complete plastid genome as well + as the equality of its inverted repeat regions in relation to the circular, quadripartite + genome structure and the location of individual genes. For more information, please + see Gruenstaeudl and Jenke (2020) . + date_publication: '2024-04-10' + bug_reports: https://github.com/michaelgruenstaeudl/PACVr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PACVr + url_git: https://github.com/michaelgruenstaeudl/PACVr +Pade: + version: 1.0.7 + title: Padé Approximant Coefficients + maintainer: Avraham Adler + description: |- + Given a vector of Taylor series coefficients of sufficient length + as input, the function returns the numerator and denominator coefficients + for the Padé approximant of appropriate order (Baker, 1975) + . + date_publication: '2024-06-19' + bug_reports: https://github.com/aadler/Pade/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Pade + url_git: https://github.com/aadler/Pade +padr: + version: 0.6.3 + title: Quickly Get Datetime Data Ready for Analysis + maintainer: Edwin Thoen + description: |- + Transforms datetime data into a format ready for analysis. + It offers two core functionalities; aggregating data to a higher level interval + (thicken) and imputing records where observations were absent (pad). + date_publication: '2024-11-21' + bug_reports: https://github.com/EdwinTh/padr/issues + url: https://edwinth.github.io/padr/ + url_cran: https://CRAN.R-project.org/package=padr + url_git: https://github.com/EdwinTh/padr +pafdR: + version: '1.0' + title: |- + Book Companion for Processing and Analyzing Financial Data with + R + maintainer: Marcelo Perlin + description: Provides access to material from the book "Processing and Analyzing + Financial Data with R" by Marcelo Perlin (2017) available at . + date_publication: '2017-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pafdR + url_git: '' +PAFit: + version: 1.2.10 + title: Generative Mechanism Estimation in Temporal Complex Networks + maintainer: Thong Pham + description: Statistical methods for estimating preferential attachment and node + fitness generative mechanisms in temporal complex networks are provided. Thong + Pham et al. (2015) . Thong Pham et al. (2016) + . Thong Pham et al. (2020) . + Thong Pham et al. (2021) . + date_publication: '2024-03-28' + bug_reports: https://github.com/thongphamthe/PAFit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PAFit + url_git: https://github.com/thongphamthe/PAFit +pafr: + version: 0.0.2 + title: Read, Manipulate and Visualize 'Pairwise mApping Format' Data + maintainer: David Winter + description: |- + Provides functions to read, process and visualize pairwise sequence + alignments in the 'PAF' format used by 'minimap2' and other whole-genome aligners. + 'minimap2' is described by Li H. (2018) . + date_publication: '2020-12-08' + bug_reports: https://github.com/dwinter/pafr/issues + url: https://dwinter.github.io/pafr/ + url_cran: https://CRAN.R-project.org/package=pafr + url_git: '' +pagedown: + version: '0.22' + title: Paginate the HTML Output of R Markdown with CSS for Print + maintainer: Yihui Xie + description: |- + Use the paged media properties in CSS and the JavaScript + library 'paged.js' to split the content of an HTML document into discrete + pages. Each page can have its page size, page numbers, margin boxes, and + running headers, etc. Applications of this package include books, letters, + reports, papers, business cards, resumes, and posters. + date_publication: '2025-01-07' + bug_reports: https://github.com/rstudio/pagedown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pagedown + url_git: https://github.com/rstudio/pagedown +pagemap: + version: 0.1.3 + title: Create Mini Map for Web Pages + maintainer: Wei Su + description: Quickly and easily add a mini map to your 'rmarkdown' html documents. + date_publication: '2021-09-02' + bug_reports: https://github.com/swsoyee/pagemapR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pagemap + url_git: https://github.com/swsoyee/pagemapR +pagenum: + version: '1.3' + title: Put Page Numbers on Graphics + maintainer: Kevin Wright + description: A simple way to add page numbers to base/ggplot/lattice graphics. + date_publication: '2024-07-17' + bug_reports: https://github.com/kwstat/pagenum/issues + url: https://kwstat.github.io/pagenum/ + url_cran: https://CRAN.R-project.org/package=pagenum + url_git: '' +pageviews: + version: 0.6.0 + title: An API Client for Wikimedia Traffic Data + maintainer: Os Keyes + description: |- + Pageview data from the 'Wikimedia' sites, such as + 'Wikipedia' , from entire projects to per-article + levels of granularity, through the new RESTful API and data source . + date_publication: '2024-03-04' + bug_reports: https://github.com/ironholds/pageviews + url: '' + url_cran: https://CRAN.R-project.org/package=pageviews + url_git: https://github.com/ironholds/pageviews +PAGFL: + version: 1.1.3 + title: |- + Joint Estimation of Latent Groups and Group-Specific + Coefficients in Panel Data Models + maintainer: Paul Haimerl + description: |- + Latent group structures are a common challenge in panel data analysis. Disregarding group-level heterogeneity can introduce bias. Conversely, estimating individual coefficients for each cross-sectional unit is inefficient and may lead to high uncertainty. + This package addresses the issue of unobservable group structures by implementing the pairwise adaptive group fused Lasso (PAGFL) by Mehrabani (2023) . PAGFL identifies latent group structures and group-specific coefficients in a single step. + On top of that, we extend the PAGFL to time-varying coefficient functions. + date_publication: '2025-02-20' + bug_reports: https://github.com/Paul-Haimerl/PAGFL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PAGFL + url_git: https://github.com/Paul-Haimerl/PAGFL +pagoda2: + version: 1.0.12 + title: Single Cell Analysis and Differential Expression + maintainer: Evan Biederstedt + description: Analyzing and interactively exploring large-scale single-cell RNA-seq + datasets. 'pagoda2' primarily performs normalization and differential gene expression + analysis, with an interactive application for exploring single-cell RNA-seq datasets. + It performs basic tasks such as cell size normalization, gene variance normalization, + and can be used to identify subpopulations and run differential expression within + individual samples. 'pagoda2' was written to rapidly process modern large-scale + scRNAseq datasets of approximately 1e6 cells. The companion web application allows + users to explore which gene expression patterns form the different subpopulations + within your data. The package also serves as the primary method for preprocessing + data for conos, . This package interacts + with data available through the 'p2data' package, which is available in a 'drat' + repository. To access this data package, see the instructions at . + The size of the 'p2data' package is approximately 6 MB. + date_publication: '2024-02-27' + bug_reports: https://github.com/kharchenkolab/pagoda2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pagoda2 + url_git: https://github.com/kharchenkolab/pagoda2 +PAGWAS: + version: '2.0' + title: Pathway Analysis Methods for Genomewide Association Data + maintainer: Marina Evangelou + description: 'Bayesian hierarchical methods for pathway analysis of genomewide association + data: Normal/Bayes factors and Sparse Normal/Adaptive lasso. The Frequentist Fisher''s + product method is included as well.' + date_publication: '2015-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PAGWAS + url_git: '' +PAICE: + version: 1.0.2 + title: Phylogeographic Analysis of Island Colonization Events + maintainer: Alberto J. Coello + description: Estimation of the number of colonization events between islands of + the same archipelago for a species. It uses rarefaction curves to control for + both field and genetic sample sizes as it was described in Coello et al. (2022) + . + date_publication: '2024-07-15' + bug_reports: https://github.com/PAICEcode/PAICE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PAICE + url_git: +painbow: + version: 1.0.1 + title: Use XKCD's "Painbow" Colormap in ggplot2 + maintainer: Steve Haroz + description: XKCD described a supposedly "bad" colormap that it called a "Painbow" + (see ). But simple tests demonstrate that under some circumstances, + the colormap can perform very well, and people can find information that is difficult + to detect with the ggplot2 default and even supposedly "good" colormaps like viridis. + This library let's you use the Painbow in your own ggplot graphs. + date_publication: '2021-11-11' + bug_reports: https://github.com/steveharoz/painbow/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=painbow + url_git: https://github.com/steveharoz/painbow +painter: + version: 0.1.0 + title: Creation and Manipulation of Color Palettes + maintainer: Brody Sandel + description: |- + Functions for creating color palettes, visualizing + palettes, modifying colors, and assigning colors for plotting. + date_publication: '2018-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=painter + url_git: '' +paintingr: + version: 0.1.0 + title: Painting Palettes Generator + maintainer: Dean Li + description: Color palettes generated from paintings. + date_publication: '2022-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paintingr + url_git: '' +paintmap: + version: '1.0' + title: Plotting Paintmaps + maintainer: Daniel Greene + description: |- + Plots matrices of colours as grids of coloured squares - aka heatmaps, + guaranteeing legible row and column names, + without transformation of values, + without re-ordering rows or columns, + and without dendrograms. + date_publication: '2016-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paintmap + url_git: '' +PairedData: + version: 1.1.1 + title: Paired Data Analysis + maintainer: Stephane Champely + description: Many datasets and a set of graphics (based on ggplot2), statistics, + effect sizes and hypothesis tests are provided for analysing paired data with + S4 class. + date_publication: '2018-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PairedData + url_git: '' +pairsD3: + version: 0.1.3 + title: D3 Scatterplot Matrices + maintainer: Garth Tarr + description: |- + Creates an interactive scatterplot matrix using the D3 JavaScript + library. See for more information on D3. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pairsD3 + url_git: https://github.com/garthtarr/pairsD3/ +PairViz: + version: 1.3.6 + title: Visualization using Graph Traversal + maintainer: Catherine Hurley + description: |- + Improving graphics by ameliorating order effects, using Eulerian tours + and Hamiltonian decompositions of graphs. References for the methods presented + here are C.B. Hurley and R.W. Oldford (2010) and + C.B. Hurley and R.W. Oldford (2011) . + date_publication: '2022-08-12' + bug_reports: '' + url: https://cbhurley.github.io/PairViz/ + url_cran: https://CRAN.R-project.org/package=PairViz + url_git: '' +pairwise: + version: 0.6.1-0 + title: Rasch Model Parameters by Pairwise Algorithm + maintainer: Joerg-Henrik Heine + description: |- + Performs the explicit calculation + -- not estimation! -- of the Rasch item parameters for dichotomous and + polytomous item responses, using a pairwise comparison approach. Person + parameters (WLE) are calculated according to Warm's weighted likelihood + approach. + date_publication: '2023-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pairwise + url_git: '' +pairwiseCI: + version: 0.1-27 + title: Confidence Intervals for Two Sample Comparisons + maintainer: Frank Schaarschmidt + description: |- + Calculation of the parametric, nonparametric confidence intervals + for the difference or ratio of location parameters, nonparametric confidence interval + for the Behrens-Fisher problem and for the difference, ratio and odds-ratio of binomial + proportions for comparison of independent samples. Common wrapper functions to split + data sets and apply confidence intervals or tests to these subsets. + A by-statement allows calculation of CI separately for the levels of further factors. + CI are not adjusted for multiplicity. + date_publication: '2019-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pairwiseCI + url_git: '' +pak: + version: 0.8.0.1 + title: Another Approach to Package Installation + maintainer: Gábor Csárdi + description: |- + The goal of 'pak' is to make package installation faster and + more reliable. In particular, it performs all HTTP operations in + parallel, so metadata resolution and package downloads are fast. + Metadata and package files are cached on the local disk as well. 'pak' + has a dependency solver, so it finds version conflicts before + performing the installation. This version of 'pak' supports CRAN, + 'Bioconductor' and 'GitHub' packages as well. + date_publication: '2025-01-16' + bug_reports: https://github.com/r-lib/pak/issues + url: https://pak.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=pak + url_git: https://github.com/r-lib/pak +PakNAcc: + version: 0.1.0 + title: '''shiny'' App for National Accounts' + maintainer: Muhammad Yaseen + description: Provides a comprehensive suite of tools for analyzing Pakistan's Quarterly + National Accounts data. Users can gain detailed insights into Pakistan's economic + performance, visualize quarterly trends, and detect patterns and anomalies in + key economic indicators. Compare sector contributions—including agriculture, industry, + and services—to understand their influence on economic growth or decline. Customize + analyses by filtering and manipulating data to focus on specific areas of interest. + Ideal for policymakers, researchers, and analysts aiming to make informed, data-driven + decisions based on timely and detailed economic insights. + date_publication: '2024-11-11' + bug_reports: https://github.com/myaseen208/PakNAcc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PakNAcc + url_git: '' +PakPC: + version: 0.3.0 + title: '''shiny'' App to Analyze Pakistan''s Population Census Data' + maintainer: Muhammad Yaseen + description: Provides tools for analyzing Pakistan's Population Censuses data via + the 'PakPC2023' and 'PakPC2017' R packages. Designed for researchers, policymakers, + and professionals, the app enables in-depth numerical and graphical analysis, + including detailed cross-tabulations and insights. With diverse statistical models + and visualization options, it supports informed decision-making in social and + economic policy. This tool enhances users' ability to explore and interpret census + data, providing valuable insights for effective planning and analysis across various + fields. + date_publication: '2024-12-09' + bug_reports: https://github.com/myaseen208/PakPC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PakPC + url_git: '' +PakPC2017: + version: 1.0.0 + title: Pakistan Population Census 2017 + maintainer: Muhammad Yaseen + description: Provides data sets and functions for exploration of Pakistan Population + Census 2017 (). + date_publication: '2018-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PakPC2017 + url_git: https://github.com/MYaseen208/PakPC2017 +PakPC2023: + version: 0.2.0 + title: Pakistan Population Census 2023 + maintainer: Muhammad Yaseen + description: Provides data sets and functions for exploration of Pakistan Population + Census 2023 (). + date_publication: '2024-11-02' + bug_reports: https://github.com/myaseen208/PakPC2023/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PakPC2023 + url_git: https://github.com/myaseen208/PakPC2023https://myaseen208.com/PakPC2023/ +PakPMICS2014Ch: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2014 Child + Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: Provides data set and functions for exploration of Multiple Indicator + Cluster Survey (MICS) 2014 Child questionnaire data for Punjab, Pakistan (). + date_publication: '2017-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PakPMICS2014Ch + url_git: https://github.com/MYaseen208/PakPMICS2014Ch +PakPMICS2014HH: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2014 Household + Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2014 Household questionnaire data for Punjab, Pakistan (). + date_publication: '2017-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PakPMICS2014HH + url_git: https://github.com/MYaseen208/PakPMICS2014HH +PakPMICS2014HL: + version: 0.1.1 + title: |- + Multiple Indicator Cluster Survey (MICS) 2014 Household Listing + Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: Provides data set and function for exploration of Multiple Indicator + Cluster Survey 2014 Household Listing questionnaire data for Punjab, Pakistan. + date_publication: '2021-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PakPMICS2014HL + url_git: https://github.com/MYaseen208/PakPMICS2014HL +PakPMICS2014Wm: + version: 0.1.1 + title: |- + Multiple Indicator Cluster Survey (MICS) 2014 Women + Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: Provides data set and function for exploration of Multiple Indicator + Cluster Survey 2014 Women (age 15-49 years) questionnaire data for Punjab, Pakistan. + date_publication: '2021-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PakPMICS2014Wm + url_git: https://github.com/MYaseen208/PakPMICS2014Wm +PakPMICS2018: + version: 1.2.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2017-18 Data for + Punjab, Pakistan + maintainer: Muhammad Yaseen + description: 'Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2017-18 data for Punjab, Pakistan. The results of the present + survey are critically important for the purposes of SDG monitoring, as the survey + produces information on 32 global SDG indicators. The data was collected from + 53,840 households selected at the second stage with systematic random sampling + out of a sample of 2,692 clusters selected using Probability Proportional to size + sampling. Six questionnaires were used in the survey: (1) a household questionnaire + to collect basic demographic information on all de jure household members (usual + residents), the household, and the dwelling; (2) a water quality testing questionnaire + administered in three households in each cluster of the sample; (3) a questionnaire + for individual women administered in each household to all women age 15-49 years; + (4) a questionnaire for individual men administered in every second household + to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers + (or caretakers) of all children under 5 living in the household; and (6) a questionnaire + for children age 5-17 years, administered to the mother (or caretaker) of one + randomly selected child age 5-17 years living in the household.' + date_publication: '2024-11-10' + bug_reports: https://github.com/myaseen208/PakPMICS2018/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PakPMICS2018 + url_git: https://myaseen208.com/PakPMICS2018/https://CRAN.R-project.org/package=PakPMICS2018https://github.com/myaseen208/PakPMICS2018 +PakPMICS2018bh: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2017-18 Birth History + of Children Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: 'Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. + The results of the present survey are critically important for the purposes of + SDG monitoring, as the survey produces information on 32 global SDG indicators. + The data was collected from 53,840 households selected at the second stage with + systematic random sampling out of a sample of 2,692 clusters selected using Probability + Proportional to size sampling. Six questionnaires were used in the survey: (1) + a household questionnaire to collect basic demographic information on all de jure + household members (usual residents), the household, and the dwelling; (2) a water + quality testing questionnaire administered in three households in each cluster + of the sample; (3) a questionnaire for individual women administered in each household + to all women age 15-49 years; (4) a questionnaire for individual men administered + in every second household to all men age 15-49 years; (5) an under-5 questionnaire, + administered to mothers (or caretakers) of all children under 5 living in the + household; and (6) a questionnaire for children age 5-17 years, administered to + the mother (or caretaker) of one randomly selected child age 5-17 years living + in the household ().' + date_publication: '2019-06-03' + bug_reports: '' + url: https://myaseen208.github.io/PakPMICS2018bh/ + url_cran: https://CRAN.R-project.org/package=PakPMICS2018bh + url_git: https://github.com/myaseen208/PakPMICS2018bh +PakPMICS2018fs: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2017-18 Children Age + 5-17 Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: 'Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2017-18 Children Age 5-17 questionnaire data for Punjab, + Pakistan. The results of the present survey are critically important for the purposes + of Sustainable Development Goals (SDGs) monitoring, as the survey produces information + on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected + from 53,840 households selected at the second stage with systematic random sampling + out of a sample of 2,692 clusters selected using probability proportional to size + sampling. Six questionnaires were used in the survey: (1) a household questionnaire + to collect basic demographic information on all de jure household members (usual + residents), the household, and the dwelling; (2) a water quality testing questionnaire + administered in three households in each cluster of the sample; (3) a questionnaire + for individual women administered in each household to all women age 15-49 years; + (4) a questionnaire for individual men administered in every second household + to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers + (or caretakers) of all children under 5 living in the household; and (6) a questionnaire + for children age 5-17 years, administered to the mother (or caretaker) of one + randomly selected child age 5-17 years living in the household ().' + date_publication: '2019-06-07' + bug_reports: '' + url: https://myaseen208.github.io/PakPMICS2018fs/ + url_cran: https://CRAN.R-project.org/package=PakPMICS2018fs + url_git: https://github.com/myaseen208/PakPMICS2018fs +PakPMICS2018hh: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2017-18 Household + Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: 'Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. + The results of the present survey are critically important for the purposes of + Sustainable Development Goals (SDGs) monitoring, as the survey produces information + on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected + from 53,840 households selected at the second stage with systematic random sampling + out of a sample of 2,692 clusters selected using probability proportional to size + sampling. Six questionnaires were used in the survey: (1) a household questionnaire + to collect basic demographic information on all de jure household members (usual + residents), the household, and the dwelling; (2) a water quality testing questionnaire + administered in three households in each cluster of the sample; (3) a questionnaire + for individual women administered in each household to all women age 15-49 years; + (4) a questionnaire for individual men administered in every second household + to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers + (or caretakers) of all children under 5 living in the household; and (6) a questionnaire + for children age 5-17 years, administered to the mother (or caretaker) of one + randomly selected child age 5-17 years living in the household ().' + date_publication: '2019-06-07' + bug_reports: '' + url: https://myaseen208.github.io/PakPMICS2018hh/ + url_cran: https://CRAN.R-project.org/package=PakPMICS2018hh + url_git: https://github.com/myaseen208/PakPMICS2018hh +PakPMICS2018mm: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2017-18 Maternal + Mortality Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: 'Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2017-18 Maternal Mortality questionnaire data for Punjab, + Pakistan. The results of the present survey are critically important for the purposes + of Sustainable Development Goals (SDGs) monitoring, as the survey produces information + on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected + from 53,840 households selected at the second stage with systematic random sampling + out of a sample of 2,692 clusters selected using probability proportional to size + sampling. Six questionnaires were used in the survey: (1) a household questionnaire + to collect basic demographic information on all de jure household members (usual + residents), the household, and the dwelling; (2) a water quality testing questionnaire + administered in three households in each cluster of the sample; (3) a questionnaire + for individual women administered in each household to all women age 15-49 years; + (4) a questionnaire for individual men administered in every second household + to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers + (or caretakers) of all children under 5 living in the household; and (6) a questionnaire + for children age 5-17 years, administered to the mother (or caretaker) of one + randomly selected child age 5-17 years living in the household ().' + date_publication: '2019-06-08' + bug_reports: '' + url: https://myaseen208.github.io/PakPMICS2018mm/ + url_cran: https://CRAN.R-project.org/package=PakPMICS2018mm + url_git: https://github.com/myaseen208/PakPMICS2018mm +PakPMICS2018mn: + version: 0.1.0 + title: |- + Multiple Indicator Cluster Survey (MICS) 2017-18 Men + Questionnaire Data for Punjab, Pakistan + maintainer: Muhammad Yaseen + description: 'Provides data set and function for exploration of Multiple Indicator + Cluster Survey (MICS) 2017-18 Men questionnaire data for Punjab, Pakistan. The + results of the present survey are critically important for the purposes of Sustainable + Development Goals (SDGs) monitoring, as the survey produces information on 32 + global Sustainable Development Goals (SDGs) indicators. The data was collected + from 53,840 households selected at the second stage with systematic random sampling + out of a sample of 2,692 clusters selected using probability proportional to size + sampling. Six questionnaires were used in the survey: (1) a household questionnaire + to collect basic demographic information on all de jure household members (usual + residents), the household, and the dwelling; (2) a water quality testing questionnaire + administered in three households in each cluster of the sample; (3) a questionnaire + for individual women administered in each household to all women age 15-49 years; + (4) a questionnaire for individual men administered in every second household + to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers + (or caretakers) of all children under 5 living in the household; and (6) a questionnaire + for children age 5-17 years, administered to the mother (or caretaker) of one + randomly selected child age 5-17 years living in the household ().' + date_publication: '2019-06-11' + bug_reports: '' + url: https://myaseen208.github.io/PakPMICS2018mn/ + url_cran: https://CRAN.R-project.org/package=PakPMICS2018mn + url_git: https://github.com/myaseen208/PakPMICS2018mn +pakret: + version: 0.2.2 + title: Cite 'R' Packages on the Fly in 'R Markdown' and 'Quarto' + maintainer: Arnaud Gallou + description: |- + References and cites 'R' and 'R' packages on the fly in 'R + Markdown' and 'Quarto'. 'pakret' provides a minimalistic API that + generates preformatted citations of 'R' and 'R' packages, and adds + their reference to a '.bib' file directly from within your document. + date_publication: '2024-10-23' + bug_reports: https://github.com/arnaudgallou/pakret/issues + url: https://arnaudgallou.github.io/pakret/ + url_cran: https://CRAN.R-project.org/package=pakret + url_git: https://github.com/arnaudgallou/pakret +palaeoSig: + version: 2.1-3 + title: Significance Tests for Palaeoenvironmental Reconstructions + maintainer: Richard Telford + description: |- + Several tests of quantitative palaeoenvironmental reconstructions + from microfossil assemblages, including the null model tests of the + statistically significant of reconstructions developed by Telford and Birks + (2011) , and tests of the effect of + spatial autocorrelation on transfer function model performance using methods + from Telford and Birks (2009) and + Trachsel and Telford (2016) . Age-depth models with + generalized mixed-effect regression from Heegaard et al (2005) + are also included. + date_publication: '2023-03-10' + bug_reports: https://github.com/richardjtelford/palaeoSig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=palaeoSig + url_git: https://github.com/richardjtelford/palaeoSig +palaeoverse: + version: 1.4.0 + title: Prepare and Explore Data for Palaeobiological Analyses + maintainer: Lewis A. Jones + description: |- + Provides functionality to support data preparation and exploration for + palaeobiological analyses, improving code reproducibility and accessibility. The + wider aim of 'palaeoverse' is to bring the palaeobiological community together + to establish agreed standards. The package currently includes functionality for + data cleaning, binning (time and space), exploration, summarisation and + visualisation. Reference datasets (i.e. Geological Time Scales ) + and auxiliary functions are also provided. Details can be found in: + Jones et al., (2023) . + date_publication: '2024-10-14' + bug_reports: https://github.com/palaeoverse/palaeoverse/issues + url: https://palaeoverse.palaeoverse.org + url_cran: https://CRAN.R-project.org/package=palaeoverse + url_git: https://github.com/palaeoverse/palaeoverse +palasso: + version: 1.0.0 + title: Sparse Regression with Paired Covariates + maintainer: Armin Rauschenberger + description: Implements sparse regression with paired covariates (). + The paired lasso is designed for settings where each covariate in one set forms + a pair with a covariate in the other set (one-to-one correspondence). For the + optional correlation shrinkage, install ashr () + and CorShrink () from GitHub (see README). + date_publication: '2024-09-26' + bug_reports: https://github.com/rauschenberger/palasso/issues + url: https://rauschenberger.github.io/palasso/ + url_cran: https://CRAN.R-project.org/package=palasso + url_git: https://github.com/rauschenberger/palasso +pald: + version: 0.0.4 + title: Partitioned Local Depth for Community Structure in Data + maintainer: Lucy D'Agostino McGowan + description: |- + Implementation of the Partitioned Local Depth (PaLD) + approach which provides a measure of local depth and the cohesion of a point + to another which (together with a universal threshold for distinguishing + strong and weak ties) may be used to reveal local and global structure in + data, based on methods described in Berenhaut, Moore, and Melvin (2022) + . No extraneous inputs, distributional + assumptions, iterative procedures nor optimization criteria are employed. + This package includes functions for computing local depths and cohesion as + well as flexible functions for plotting community networks and displays of + cohesion against distance. + date_publication: '2024-04-18' + bug_reports: https://github.com/LucyMcGowan/pald/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pald + url_git: https://github.com/LucyMcGowan/pald +paleoAM: + version: 1.0.1 + title: Simulating Assemblage Models of Abundance for the Fossil Record + maintainer: David W Bapst + description: Provides functions for fitting abundance distributions over environmental + gradients to the species in ecological communities, and tools for simulating the + fossil assemblages from those abundance models for such communities, as well as + simulating assemblages across various patterns of sedimentary history and sampling. + These tools are for particular use with fossil records with detailed age models + and abundance distributions used for calculating environmental gradients from + ordinations or other indices based on fossil assemblages. + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paleoAM + url_git: '' +paleobioDB: + version: 1.0.0 + title: Download and Process Data from the Paleobiology Database + maintainer: Adrián Castro Insua + description: |- + Includes functions to wrap most endpoints of the 'PaleobioDB' + API and functions to visualize and process the fossil data. The API + documentation for the Paleobiology Database can be found at + . + date_publication: '2024-02-29' + bug_reports: https://github.com/ropensci/paleobioDB/issues + url: https://docs.ropensci.org/paleobioDB/ + url_cran: https://CRAN.R-project.org/package=paleobioDB + url_git: https://github.com/ropensci/paleobioDB +paleobuddy: + version: 1.1.0 + title: Simulating Diversification Dynamics + maintainer: Bruno do Rosario Petrucci + description: 'Simulation of species diversification, fossil records, and phylogenies. + While the literature on species birth-death simulators is extensive, including + important software like ''paleotree'' and ''APE'', we concluded there were interesting + gaps to be filled regarding possible diversification scenarios. Here we strove + for flexibility over focus, implementing a large array of regimens for users to + experiment with and combine. In this way, ''paleobuddy'' can be used in complement + to other simulators as a flexible jack of all trades, or, in the case of scenarios + implemented only here, can allow for robust and easy simulations for novel situations. + Environmental data modified from that in ''RPANDA'': Morlon H. et al (2016) .' + date_publication: '2025-02-05' + bug_reports: https://github.com/brpetrucci/paleobuddy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paleobuddy + url_git: https://github.com/brpetrucci/paleobuddy +paleoDiv: + version: 0.4.0 + title: Extracting and Visualizing Paleobiodiversity + maintainer: Darius Nau + description: Contains various tools for conveniently downloading and editing taxon-specific + datasets from the Paleobiology Database , extracting information + on abundance, temporal distribution of subtaxa and taxonomic diversity through + deep time, and visualizing these data in relation to phylogeny and stratigraphy. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paleoDiv + url_git: '' +paleomorph: + version: 0.1.4 + title: Geometric Morphometric Tools for Paleobiology + maintainer: Tim Lucas + description: Fill missing symmetrical data with mirroring, calculate Procrustes + alignments with or without scaling, and compute standard or vector correlation + and covariance matrices (congruence coefficients) of 3D landmarks. Tolerates missing + data for all analyses. + date_publication: '2017-04-19' + bug_reports: https://github.com/timcdlucas/paleomorph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paleomorph + url_git: https://github.com/timcdlucas/paleomorph/ +paleopop: + version: 2.1.7 + title: |- + Pattern-Oriented Modeling Framework for Coupled Niche-Population + Paleo-Climatic Models + maintainer: July Pilowsky + description: |- + This extension of the poems pattern-oriented modeling (POM) framework + provides a collection of modules and functions customized for paleontological + time-scales, and optimized for single-generation transitions and large populations, + across multiple generations. + date_publication: '2025-01-07' + bug_reports: https://github.com/GlobalEcologyLab/paleopop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paleopop + url_git: https://github.com/GlobalEcologyLab/paleopop/ +paleotree: + version: 3.4.7 + title: Paleontological and Phylogenetic Analyses of Evolution + maintainer: David W. Bapst + description: |- + Provides tools for transforming, a posteriori time-scaling, and + modifying phylogenies containing extinct (i.e. fossil) lineages. In particular, + most users are interested in the functions timePaleoPhy, bin_timePaleoPhy, + cal3TimePaleoPhy and bin_cal3TimePaleoPhy, which date cladograms of + fossil taxa using stratigraphic data. This package also contains a large number + of likelihood functions for estimating sampling and diversification rates from + different types of data available from the fossil record (e.g. range data, + occurrence data, etc). paleotree users can also simulate diversification and + sampling in the fossil record using the function simFossilRecord, which is a + detailed simulator for branching birth-death-sampling processes composed of + discrete taxonomic units arranged in ancestor-descendant relationships. Users + can use simFossilRecord to simulate diversification in incompletely sampled + fossil records, under various models of morphological differentiation (i.e. + the various patterns by which morphotaxa originate from one another), and + with time-dependent, longevity-dependent and/or diversity-dependent rates of + diversification, extinction and sampling. Additional functions allow users to + translate simulated ancestor-descendant data from simFossilRecord into standard + time-scaled phylogenies or unscaled cladograms that reflect the relationships + among taxon units. + date_publication: '2024-07-06' + bug_reports: https://github.com/dwbapst/paleotree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paleotree + url_git: https://github.com/dwbapst/paleotree +paleoTS: + version: 0.6.2 + title: Analyze Paleontological Time-Series + maintainer: Gene Hunt + description: |- + Facilitates analysis of paleontological sequences of trait values. + Functions are provided to fit, using maximum likelihood, simple + evolutionary models (including unbiased random walks, directional + evolution,stasis, Ornstein-Uhlenbeck, covariate-tracking) and + complex models (punctuation, mode shifts). + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paleoTS + url_git: '' +palette: + version: 0.0.2 + title: Color Scheme Helpers + maintainer: Christopher T. Kenny + description: |- + Hexadecimal codes are typically used to represent colors in R. + Connecting these codes to their colors requires practice or memorization. + 'palette' provides a 'vctrs' class for working with color palettes, including + printing and plotting functions. The goal of the class is to place visual + representations of color palettes directly on or, at least, next to their + corresponding character representations. Palette extensions also are provided + for data frames using 'pillar'. + date_publication: '2024-03-15' + bug_reports: https://github.com/christopherkenny/palette/issues + url: https://christophertkenny.com/palette/ + url_cran: https://CRAN.R-project.org/package=palette + url_git: https://github.com/christopherkenny/palette +paletteer: + version: 1.6.0 + title: Comprehensive Collection of Color Palettes + maintainer: Emil Hvitfeldt + description: |- + The choices of color palettes in R can be quite + overwhelming with palettes spread over many packages with many + different API's. This packages aims to collect all color palettes + across the R ecosystem under the same package with a streamlined API. + date_publication: '2024-01-21' + bug_reports: https://github.com/EmilHvitfeldt/paletteer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paletteer + url_git: https://github.com/EmilHvitfeldt/paletteer +paletteknife: + version: 0.4.2 + title: |- + Create Colour Scales and Legend from Continuous or Categorical + Vectors + maintainer: John Hobbs + description: |- + Streamlines the steps for adding colour scales and associated legends + when working with base R graphics, especially for interactive use. Popular + palettes are included and pretty legends produced when mapping a large + variety of vector classes to a colour scale. An additional helper for + adding axes and grid lines complements the base::plot() work flow. + date_publication: '2022-04-20' + bug_reports: https://github.com/johnxhobbs/paletteknife/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paletteknife + url_git: https://github.com/johnxhobbs/paletteknife +palettes: + version: 0.2.1 + title: Methods for Colour Vectors and Colour Palettes + maintainer: Michael McCarthy + description: |- + Provides a comprehensive library for colour vectors and colour + palettes using a new family of colour classes (palettes_colour and + palettes_palette) that always print as hex codes with colour previews. + Capabilities include: formatting, casting and coercion, extraction and + updating of components, plotting, colour mixing arithmetic, and colour + interpolation. + date_publication: '2024-07-13' + bug_reports: https://github.com/mccarthy-m-g/palettes/issues + url: https://mccarthy-m-g.github.io/palettes/ + url_cran: https://CRAN.R-project.org/package=palettes + url_git: https://github.com/mccarthy-m-g/palettes +palettesForR: + version: 0.1.2 + title: GPL Palettes Copied from 'Gimp' and 'Inkscape' + maintainer: Francois Rebaudo + description: |- + A set of palettes imported from 'Gimp' distributed + under GPL3 (), and 'Inkscape' + distributed under GPL2 (). + date_publication: '2019-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=palettesForR + url_git: https://github.com/frareb/palettesForR +palettetown: + version: 0.1.1 + title: Use Pokemon Inspired Colour Palettes + maintainer: Tim Lucas + description: |- + Use Pokemon(R) inspired palettes with additional 'ggplot2' scales. + Palettes are the colours in each Pokemon's sprite, ordered by how common + they are in the image. The first 386 Pokemon are currently provided. + date_publication: '2016-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=palettetown + url_git: https://github.com/timcdlucas/palettetown +palinsol: + version: '1.0' + title: Insolation for Palaeoclimate Studies + maintainer: Michel Crucifix + description: 'R package to compute Incoming Solar Radiation (insolation) for palaeoclimate + studies. Features three solutions: Berger (1978), Berger and Loutre (1991) and + Laskar et al. (2004). Computes daily-mean, season-averaged and annual means and + for all latitudes, and polar night dates.' + date_publication: '2023-05-21' + bug_reports: https://github.com/mcrucifix/palinsol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=palinsol + url_git: https://github.com/mcrucifix/palinsol +palm: + version: 1.1.5 + title: Fitting Point Process Models via the Palm Likelihood + maintainer: Ben Stevenson + description: Functions to fit point process models using the Palm likelihood. First + proposed by Tanaka, Ogata, and Stoyan (2008) , maximisation + of the Palm likelihood can provide computationally efficient parameter estimation + for point process models in situations where the full likelihood is intractable. + This package is chiefly focused on Neyman-Scott point processes, but can also + fit the void processes proposed by Jones-Todd et al. (2019) . + The development of this package was motivated by the analysis of capture-recapture + surveys on which individuals cannot be identified---the data from which can conceptually + be seen as a clustered point process (Stevenson, Borchers, and Fewster, 2019 ). + As such, some of the functions in this package are specifically for the estimation + of cetacean density from two-camera aerial surveys. + date_publication: '2023-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=palm + url_git: https://github.com/b-steve/palm +palmerpenguins: + version: 0.1.1 + title: Palmer Archipelago (Antarctica) Penguin Data + maintainer: Allison Horst + description: Size measurements, clutch observations, and blood isotope ratios for + adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the + Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made + available by Dr. Kristen Gorman and the Palmer Station Long Term Ecological Research + (LTER) Program. + date_publication: '2022-08-15' + bug_reports: https://github.com/allisonhorst/palmerpenguins/issues + url: https://allisonhorst.github.io/palmerpenguins/ + url_cran: https://CRAN.R-project.org/package=palmerpenguins + url_git: https://github.com/allisonhorst/palmerpenguins +PaLMr: + version: 0.2.0 + title: Interface for 'Google Pathways Language Model 2 (PaLM 2)' + maintainer: Li Yuan + description: '''Google Pathways Language Model 2 (PaLM 2)'' as a coding and writing + assistant designed for ''R''. With a range of functions, including natural language + processing and coding optimization, to assist ''R'' developers in simplifying + tedious coding tasks and content searching.' + date_publication: '2024-01-22' + bug_reports: https://github.com/lygitdata/PaLMr/issues + url: https://palmr.ly.gd.edu.kg/ + url_cran: https://CRAN.R-project.org/package=PaLMr + url_git: '' +palmtree: + version: 0.9-1 + title: Partially Additive (Generalized) Linear Model Trees + maintainer: Heidi Seibold + description: |- + This is an implementation of model-based trees with global model + parameters (PALM trees). The PALM tree algorithm is an extension to the MOB + algorithm (implemented in the 'partykit' package), where some parameters are + fixed across all groups. Details about the method can be found in Seibold, + Hothorn, Zeileis (2016) . The package offers coef(), + logLik(), plot(), and predict() functions for PALM trees. + date_publication: '2020-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=palmtree + url_git: '' +palr: + version: 0.4.0 + title: Colour Palettes for Data + maintainer: Michael D. Sumner + description: |- + Colour palettes for data, based on some well known public data + sets. Includes helper functions to map absolute values to known palettes, and + capture the work of image colour mapping as raster data sets. + date_publication: '2023-11-06' + bug_reports: https://github.com/AustralianAntarcticDivision/palr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=palr + url_git: https://github.com/AustralianAntarcticDivision/palr +pals: + version: '1.9' + title: Color Palettes, Colormaps, and Tools to Evaluate Them + maintainer: Kevin Wright + description: |- + A comprehensive collection of color palettes, colormaps, and + tools to evaluate them. See Kovesi (2015) . + date_publication: '2024-07-16' + bug_reports: https://github.com/kwstat/pals/issues + url: https://kwstat.github.io/pals/ + url_cran: https://CRAN.R-project.org/package=pals + url_git: '' +pam: + version: 1.0.2 + title: Fast and Efficient Processing of PAM Data + maintainer: Julien Böhm + description: Processing Chlorophyll Fluorescence & P700 Absorbance data generated + by WALZ hardware. Four models are provided for the regression of Pi curves, which + can be compared with each other in order to select the most suitable model for + the data set. Control plots ensure the successful verification of each regression. + Bundled output of alpha, ETRmax, Ik etc. enables fast and reliable further processing + of the data. + date_publication: '2025-02-25' + bug_reports: https://github.com/biotoolbox/pam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pam + url_git: https://github.com/biotoolbox/pam +PamBinaries: + version: 1.9.0 + title: Read and Process 'Pamguard' Binary Data + maintainer: Taiki Sakai + description: |- + Functions for easily reading and processing binary data files created by + 'Pamguard' (). All functions for directly reading the + binary data files are based on 'MATLAB' code written by Michael Oswald. + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PamBinaries + url_git: '' +PAmeasures: + version: 0.1.0 + title: |- + Prediction and Accuracy Measures for Nonlinear Models and for + Right-Censored Time-to-Event Data + maintainer: Xiaoyan Wang + description: |- + We propose a pair of summary measures for the predictive power of a prediction + function based on a regression model. The regression model can be linear + or nonlinear, parametric, semi-parametric, or nonparametric, and correctly + specified or mis-specified. The first measure, R-squared, is an extension of + the classical R-squared statistic for a linear model, quantifying the prediction + function's ability to capture the variability of the response. The second + measure, L-squared, quantifies the prediction function's bias for predicting the + mean regression function. When used together, they give a complete summary of + the predictive power of a prediction function. Please refer to Gang Li and Xiaoyan Wang (2016) for more details. + date_publication: '2018-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PAmeasures + url_git: '' +PAMhm: + version: 0.1.2 + title: Generate Heatmaps Based on Partitioning Around Medoids (PAM) + maintainer: Vidal Fey + description: |- + Data are partitioned (clustered) into k clusters "around medoids", which is + a more robust version of K-means implemented in the function pam() in the 'cluster' package. + The PAM algorithm is described in Kaufman and Rousseeuw (1990) . + Please refer to the pam() function documentation for more references. + Clustered data is plotted as a split heatmap allowing visualisation of representative + "group-clusters" (medoids) in the data as separated fractions of the graph while those + "sub-clusters" are visualised as a traditional heatmap based on hierarchical clustering. + date_publication: '2021-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PAMhm + url_git: '' +pamm: + version: '1.122' + title: Power Analysis for Random Effects in Mixed Models + maintainer: Julien Martin + description: Simulation functions to assess or explore the power of a dataset to + estimates significant random effects (intercept or slope) in a mixed model. The + functions are based on the "lme4" and "lmerTest" packages. + date_publication: '2023-08-28' + bug_reports: https://github.com/JulienGAMartin/pamm_R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pamm + url_git: https://github.com/JulienGAMartin/pamm_R +PAMmisc: + version: 1.12.4 + title: Miscellaneous Functions for Passive Acoustic Analysis + maintainer: Taiki Sakai + description: |- + A collection of miscellaneous functions for passive acoustics. + Much of the content here is adapted to R from code written by other people. + If you have any ideas of functions to add, please contact Taiki Sakai. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PAMmisc + url_git: '' +pammtools: + version: 0.5.93 + title: |- + Piece-Wise Exponential Additive Mixed Modeling Tools for + Survival Analysis + maintainer: Andreas Bender + description: |- + The Piece-wise exponential (Additive Mixed) Model + (PAMM; Bender and others (2018) ) is a + powerful model class for the analysis of survival (or time-to-event) data, + based on Generalized Additive (Mixed) Models (GA(M)Ms). It offers intuitive specification and robust estimation of complex survival models with stratified baseline hazards, random effects, time-varying effects, time-dependent covariates and cumulative effects (Bender and others (2019)), as well as support for left-truncated, competing risks and recurrent events data. + pammtools provides tidy workflow for survival analysis with PAMMs, + including data simulation, transformation and other functions for data + preprocessing and model post-processing as well as visualization. + date_publication: '2024-02-25' + bug_reports: https://github.com/adibender/pammtools/issues + url: https://adibender.github.io/pammtools/ + url_cran: https://CRAN.R-project.org/package=pammtools + url_git: '' +PAMpal: + version: 1.2.1 + title: Load and Process Passive Acoustic Data + maintainer: Taiki Sakai + description: |- + Tools for loading and processing passive acoustic data. Read in data + that has been processed in 'Pamguard' (), apply a suite + processing functions, and export data for reports or external modeling tools. Parameter + calculations implement methods by Oswald et al (2007) , + Griffiths et al (2020) and Baumann-Pickering et al (2010) + . + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PAMpal + url_git: '' +pampe: + version: 1.1.2 + title: |- + Implementation of the Panel Data Approach Method for Program + Evaluation + maintainer: Ainhoa Vega-Bayo + description: Implements the Panel Data Approach Method for program evaluation as + developed in Hsiao, Ching and Ki Wan (2012). pampe estimates the effect of an + intervention by comparing the evolution of the outcome for a unit affected by + an intervention or treatment to the evolution of the unit had it not been affected + by the intervention. + date_publication: '2015-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pampe + url_git: '' +pamr: + version: '1.57' + title: 'Pam: Prediction Analysis for Microarrays' + maintainer: Balasubramanian Narasimhan + description: Some functions for sample classification in microarrays. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pamr + url_git: '' +PAMscapes: + version: 0.10.0 + title: Tools for Summarising and Analysing Soundscape Data + maintainer: Taiki Sakai + description: |- + A variety of tools relevant to the analysis + of marine soundscape data. There are tools for downloading AIS (automatic identification system) + data from Marine Cadastre , + connecting AIS data to GPS coordinates, plotting summaries of various soundscape + measurements, and downloading relevant environmental variables (wind, swell height) from the + National Center for Atmospheric Research data server . + Most tools were developed to work well with output from 'Triton' software, but can be adapted + to work with any similar measurements. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PAMscapes + url_git: '' +pan: + version: '1.9' + title: Multiple Imputation for Multivariate Panel or Clustered Data + maintainer: Jing hua Zhao + description: |- + It provides functions and examples for maximum likelihood estimation for + generalized linear mixed models and Gibbs sampler for multivariate linear + mixed models with incomplete data, as described in Schafer JL (1997) + "Imputation of missing covariates under a multivariate linear mixed model". + Technical report 97-04, Dept. of Statistics, The Pennsylvania State University. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pan + url_git: '' +PANACEA: + version: 1.0.1 + title: Personalized Network-Based Anti-Cancer Therapy Evaluation + maintainer: Ege Ulgen + description: |- + Identification of the most appropriate pharmacotherapy for each + patient based on genomic alterations is a major challenge in personalized + oncology. 'PANACEA' is a collection of personalized anti-cancer drug + prioritization approaches utilizing network methods. The methods utilize + personalized "driverness" scores from 'driveR' to rank drugs, mapping these + onto a protein-protein interaction network. The "distance-based" method + scores each drug based on these scores and distances between drugs and genes + to rank given drugs. The "RWR" method propagates these scores via a + random-walk with restart framework to rank the drugs. The methods are + described in detail in Ulgen E, Ozisik O, Sezerman OU. 2023. PANACEA: + network-based methods for pharmacotherapy prioritization in personalized + oncology. Bioinformatics . + date_publication: '2023-08-19' + bug_reports: https://github.com/egeulgen/PANACEA/issues + url: https://egeulgen.github.io/PANACEA/ + url_cran: https://CRAN.R-project.org/package=PANACEA + url_git: https://github.com/egeulgen/PANACEA +pAnalysis: + version: '2.0' + title: Benchmarking and Rescaling R2 using Noise Percentile Analysis + maintainer: Joseph G Kreke + description: Provides the tools needed to benchmark the R2 value corresponding to + a certain acceptable noise level while also providing a rescaling function based + on that noise level yielding a new value of R2 we refer to as R2k which is independent + of both the number of degrees of freedom and the noise distribution function. + date_publication: '2016-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pAnalysis + url_git: '' +PanCanVarSel: + version: 0.0.3 + title: Pan-Cancer Variable Selection + maintainer: Arnab Maity + description: |- + Provides function for performing Bayesian survival regression using + Horseshoe prior in the accelerated failure time model with log normal assumption + in order to achieve high dimensional pan-cancer variable selection as developed in + Maity et. al. (2019) . + date_publication: '2019-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PanCanVarSel + url_git: '' +pandemics: + version: 0.1.0 + title: Monitoring a Developing Pandemic with Available Data + maintainer: María Dolores Martínez-Miranda + description: |- + Full dynamic system to describe and forecast the spread and the severity + of a developing pandemic, based on available data. These data are number of infections, + hospitalizations, deaths and recoveries notified each day. The system consists of three + transitions, infection-infection, infection-hospital and hospital-death/recovery. + The intensities of these transitions are dynamic and estimated using non-parametric local + linear estimators. The package can be used to provide forecasts and survival indicators + such as the median time spent in hospital and the probability that a patient who has been + in hospital for a number of days can leave it alive. Methods are described in Gámiz, + Mammen, Martínez-Miranda, and Nielsen (2024) and + . + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pandemics + url_git: '' +pander: + version: 0.6.6 + title: An R 'Pandoc' Writer + maintainer: Gergely Daróczi + description: |- + Contains some functions catching all messages, 'stdout' and other + useful information while evaluating R code and other helpers to return user + specified text elements (like: header, paragraph, table, image, lists etc.) + in 'pandoc' markdown or several type of R objects similarly automatically + transformed to markdown format. Also capable of exporting/converting (the + resulting) complex 'pandoc' documents to e.g. HTML, 'PDF', 'docx' or 'odt'. This + latter reporting feature is supported in brew syntax or with a custom reference + class with a smarty caching 'backend'. + date_publication: '2025-03-01' + bug_reports: https://github.com/rapporter/pander/issues + url: https://rapporter.github.io/pander/ + url_cran: https://CRAN.R-project.org/package=pander + url_git: '' +pandoc: + version: 0.2.0 + title: Manage and Run Universal Converter 'Pandoc' from 'R' + maintainer: Christophe Dervieux + description: |- + Provides a set of tools to install, manage and run several + 'Pandoc' versions. + date_publication: '2023-08-24' + bug_reports: https://github.com/cderv/pandoc/issues + url: https://cderv.github.io/pandoc/ + url_cran: https://CRAN.R-project.org/package=pandoc + url_git: https://github.com/cderv/pandoc +pandocfilters: + version: 0.1-6 + title: Pandoc Filters for R + maintainer: Florian Schwendinger + description: |- + The document converter 'pandoc' is widely used + in the R community. One feature of 'pandoc' is that it can produce and consume + JSON-formatted abstract syntax trees (AST). This allows to transform a given + source document into JSON-formatted AST, alter it by so called filters and pass + the altered JSON-formatted AST back to 'pandoc'. This package provides functions + which allow to write such filters in native R code. + Although this package is inspired by the Python package 'pandocfilters' + , it provides additional convenience functions which make it simple to use the 'pandocfilters' package as a + report generator. Since 'pandocfilters' inherits most of it's functionality + from 'pandoc' it can create documents in many formats + (for more information see ) but is also bound to the same + limitations as 'pandoc'. + date_publication: '2022-08-11' + bug_reports: '' + url: https://pandoc.org/ + url_cran: https://CRAN.R-project.org/package=pandocfilters + url_git: https://github.com/jgm/pandocfilters/ +panelaggregation: + version: 0.1.1 + title: Aggregate Longitudinal Survey Data + maintainer: Matthias Bannert + description: |- + Aggregate Business Tendency Survey Data (and other qualitative + surveys) to time series at various aggregation levels. Run aggregation of + survey data in a speedy, re-traceable and a easily deployable way. + Aggregation is substantially accelerated by use of data.table. + This package intends to provide an interface that is less general and abstract than data.table but rather geared towards + survey researchers. + date_publication: '2017-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=panelaggregation + url_git: '' +PanelCount: + version: 2.0.1 + title: |- + Random Effects and/or Sample Selection Models for Panel Count + Data + maintainer: Jing Peng + description: |- + A high performance package implementing random effects and/or + sample selection models for panel count data. The details of the models are discussed in Peng and Van den Bulte (2023) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PanelCount + url_git: '' +panelhetero: + version: 1.0.1 + title: Panel Data Analysis with Heterogeneous Dynamics + maintainer: Takahide Yanagi + description: |- + Understanding the dynamics of potentially heterogeneous variables is important in statistical applications. + This package provides tools for estimating the degree of heterogeneity across cross-sectional units in the panel data analysis. + The methods are developed by Okui and Yanagi (2019) and Okui and Yanagi (2020) . + date_publication: '2023-05-30' + bug_reports: '' + url: https://tkhdyanagi.github.io/panelhetero/ + url_cran: https://CRAN.R-project.org/package=panelhetero + url_git: '' +PanelMatch: + version: 2.2.0 + title: |- + Matching Methods for Causal Inference with Time-Series + Cross-Sectional Data + maintainer: In Song Kim + description: |- + Implements a set of methodological tools + that enable researchers to apply matching methods to + time-series cross-sectional data. Imai, Kim, and Wang + (2023) + proposes a nonparametric generalization of the + difference-in-differences estimator, which does not rely + on the linearity assumption as often done in + practice. Researchers first select a method of matching + each treated observation for a given unit in a + particular time period with control observations from + other units in the same time period that have a similar + treatment and covariate history. These methods include + standard matching methods based on propensity score and + Mahalanobis distance, as well as weighting methods. Once + matching and refinement is done, + treatment effects can be estimated with + standard errors. The package also offers diagnostics for researchers to assess the quality + of their results. + date_publication: '2024-06-04' + bug_reports: https://github.com/insongkim/PanelMatch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PanelMatch + url_git: '' +panelPomp: + version: 1.5.0.0 + title: Inference for Panel Partially Observed Markov Processes + maintainer: Jesse Wheeler + description: Data analysis based on panel partially-observed Markov process (PanelPOMP) + models. To implement such models, simulate them and fit them to panel data, 'panelPomp' + extends some of the facilities provided for time series data by the 'pomp' package. + Implemented methods include filtering (panel particle filtering) and maximum likelihood + estimation (Panel Iterated Filtering) as proposed in Breto, Ionides and King (2020) + "Panel Data Analysis via Mechanistic Models" . + date_publication: '2024-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=panelPomp + url_git: '' +panelr: + version: 0.7.8 + title: |- + Regression Models and Utilities for Repeated Measures and Panel + Data + maintainer: Jacob A. Long + description: |- + Provides an object type and associated tools for storing and + wrangling panel data. Implements several methods for creating regression + models that take advantage of the unique aspects of + panel data. Among other capabilities, automates the "within-between" + (also known as "between-within" and "hybrid") panel regression specification + that combines the desirable aspects of both fixed effects and random effects + econometric models and fits them as multilevel models + (Allison, 2009 ; + Bell & Jones, 2015 ). These models can also be + estimated via generalized estimating equations + (GEE; McNeish, 2019 ) and Bayesian + estimation is (optionally) supported via 'Stan'. + Supports estimation of asymmetric effects models via first differences + (Allison, 2019 ) as well as a generalized + linear model extension thereof using GEE. + date_publication: '2023-08-22' + bug_reports: https://github.com/jacob-long/panelr + url: https://panelr.jacob-long.com + url_cran: https://CRAN.R-project.org/package=panelr + url_git: '' +panelsummary: + version: 0.1.2.1 + title: Create Publication-Ready Regression Tables with Panels + maintainer: Michael Topper + description: Create an automated regression table that is well-suited for models + that are estimated with multiple dependent variables. 'panelsummary' extends 'modelsummary' + (Arel-Bundock, V. (2022) ) by allowing regression tables + to be split into multiple sections with a simple function call. Utilize familiar + arguments such as fmt, estimate, statistic, vcov, conf_level, stars, coef_map, + coef_omit, coef_rename, gof_map, and gof_omit from 'modelsummary' to clean the + table, and additionally, add a row for the mean of the dependent variable without + external manipulation. + date_publication: '2023-08-16' + bug_reports: https://github.com/michaeltopper1/panelsummary/issues + url: https://michaeltopper1.github.io/panelsummary/ + url_cran: https://CRAN.R-project.org/package=panelsummary + url_git: https://github.com/michaeltopper1/panelsummary +panelSUR: + version: 0.1.0 + title: |- + Two-Way Error Component SUR Systems Estimation on Unbalanced + Panel Data + maintainer: Laura Barbieri + description: |- + Generalized Least Squares (GLS) estimation of Seemingly Unrelated Regression + (SUR) systems on unbalanced panel in the one/two-way cases also taking into + account the possibility of cross equation restrictions. Methodological details + can be found in Biørn (2004) and Platoni, + Sckokai, Moro (2012) . + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=panelSUR + url_git: '' +PanelTM: + version: '1.0' + title: |- + Two- And Three-Way Dynamic Panel Threshold Regression Model for + Change Point Detection + maintainer: F. Marta L. Di Lascio + description: Estimation of two- and three-way dynamic panel threshold regression + models (Di Lascio and Perazzini (2024) ; + Di Lascio and Perazzini (2022, ISBN:978-88-9193-231-0); Seo and Shin (2016) ) + through the generalized method of moments based on the first difference transformation + and the use of instrumental variables. The models can be used to find a change + point detection in the time series. In addition, random number generation is also + implemented. + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PanelTM + url_git: '' +panelvar: + version: 0.5.6 + title: Panel Vector Autoregression + maintainer: Robert Ferstl + description: |- + We extend two general methods of moment estimators to panel vector + autoregression models (PVAR) with p lags of endogenous variables, predetermined + and strictly exogenous variables. This general PVAR model contains the first + difference GMM estimator by Holtz-Eakin et al. (1988) , + Arellano and Bond (1991) and the system GMM estimator + by Blundell and Bond (1998) . We also + provide specification tests (Hansen overidentification test, lag selection + criterion and stability test of the PVAR polynomial) and classical structural + analysis for PVAR models such as orthogonal and generalized impulse response + functions, bootstrapped confidence intervals for impulse response analysis and + forecast error variance decompositions. + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=panelvar + url_git: '' +panelView: + version: 1.1.18 + title: Visualizing Panel Data + maintainer: Yiqing Xu + description: 'Visualizes panel data. It has three main functionalities: (1) it plots + the treatment status and missing values in a panel dataset; (2) it visualizes + the temporal dynamics of a main variable of interest; (3) it depicts the bivariate + relationships between a treatment variable and an outcome variable either by unit + or in aggregate. For details, see .' + date_publication: '2024-06-17' + bug_reports: '' + url: https://yiqingxu.org/packages/panelview/index.html + url_cran: https://CRAN.R-project.org/package=panelView + url_git: '' +panelWranglR: + version: 1.2.13 + title: Panel Data Wrangling Tools + maintainer: Juraj Szitás + description: |- + Leading/lagging a panel, creating dummy variables, + taking panel differences, looking for panel autocorrelations, + and more. Implemented via a 'data.table' back end. + date_publication: '2019-10-03' + bug_reports: https://github.com/JSzitas/panelWranglR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=panelWranglR + url_git: https://github.com/JSzitas/panelWranglR +pangaear: + version: 1.1.0 + title: Client for the 'Pangaea' Database + maintainer: Scott Chamberlain + description: |- + Tools to interact with the 'Pangaea' Database + (), including functions for searching for data, + fetching 'datasets' by 'dataset' 'ID', and working with the 'Pangaea' + 'OAI-PMH' service. + date_publication: '2021-05-14' + bug_reports: https://github.com/ropensci/pangaear/issues + url: https://docs.ropensci.org/pangaear/(documentation) + url_cran: https://CRAN.R-project.org/package=pangaear + url_git: https://github.com/ropensci/pangaear(devel) +PanJen: + version: '1.6' + title: A Semi-Parametric Test for Specifying Functional Form + maintainer: Cathrine Ulla Jensen + description: A central decision in a parametric regression is how to specify the + relation between an dependent variable and each explanatory variable. This package + provides a semi-parametric tool for comparing different transformations of an explanatory + variables in a parametric regression. The functions is relevant in a situation, + where you would use a box-cox or Box-Tidwell transformations. In contrast to + the classic power-transformations, the methods in this package allows for theoretical + driven user input and the possibility to compare with a non-parametric transformation. + date_publication: '2017-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PanJen + url_git: '' +pannotator: + version: 1.0.0.4 + title: Visualisation and Annotation of 360 Degree Imagery + maintainer: Nunzio Knerr + description: |- + Provides a customisable R 'shiny' app for immersively + visualising, mapping and annotating panospheric (360 degree) imagery. + The flexible interface allows annotation of any geocoded images using + up to 4 user specified dropdown menus. The app uses 'leaflet' to + render maps that display the geo-locations of images and panellum + , a lightweight panorama viewer for the web, + to render images in virtual 360 degree viewing mode. Key functions + include the ability to draw on & export parts of 360 images for + downstream applications. Users can also draw polygons and points on + map imagery related to the panoramic images and export them for + further analysis. Downstream applications include using annotations to + train Artificial Intelligence/Machine Learning (AI/ML) models and + geospatial modelling and analysis of camera based survey data. + date_publication: '2024-11-11' + bug_reports: https://github.com/NunzioKnerr/pannotator_package_source/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pannotator + url_git: https://github.com/NunzioKnerr/pannotator_package_source +panstarrs: + version: 0.2.2 + title: Interface to the Pan-STARRS API + maintainer: Grigory Uskov + description: |- + An interface to the API for 'Pan-STARRS1', a data archive of + the PS1 wide-field astronomical survey. The package allows access to + the PS1 catalog and to the PS1 images. (see + for more + information). You can use it to plan astronomical observations, make + guidance pictures, find magnitudes in five broadband filters (g, r, i, + z, y) and more. + date_publication: '2024-05-02' + bug_reports: https://github.com/uskovgs/PanSTARRS/issues + url: https://uskovgs.github.io/PanSTARRS/ + url_cran: https://CRAN.R-project.org/package=panstarrs + url_git: '' +PantaRhei: + version: 0.1.2 + title: Plots Sankey Diagrams + maintainer: Patrick Bogaart + description: |- + Sankey diagrams are a powerfull and visually attractive way + to visualize the flow of conservative substances through a system. + They typically consists of a network of nodes, and fluxes between them, + where the total balance in each internal node is 0, i.e. input equals output. + Sankey diagrams are typically used to display energy systems, material flow accounts etc. + Unlike so-called alluvial plots, Sankey diagrams also allow for cyclic flows: + flows originating from a single node can, either direct or indirect, contribute to the input of that same node. + This package, named after the Greek aphorism Panta Rhei (everything flows), + provides functions to create publication-quality diagrams, using data in tables (or spread sheets) + and a simple syntax. + date_publication: '2020-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PantaRhei + url_git: '' +papaja: + version: 0.1.3 + title: |- + Prepare American Psychological Association Journal Articles with + R Markdown + maintainer: Frederik Aust + description: |- + Tools to create dynamic, submission-ready manuscripts, which + conform to American Psychological Association manuscript guidelines. We + provide R Markdown document formats for manuscripts (PDF and Word) and + revision letters (PDF). Helper functions facilitate reporting statistical + analyses or create publication-ready tables and plots. + date_publication: '2024-10-24' + bug_reports: https://github.com/crsh/papaja/issues + url: '' + url_cran: https://CRAN.R-project.org/package=papaja + url_git: https://github.com/crsh/papaja +papci: + version: 0.1.0 + title: Prevalence Adjusted PPV Confidence Interval + maintainer: Cui Guo + description: Positive predictive value (PPV) defined as the conditional probability + of clinical trial assay (CTA) being positive given Companion diagnostic device + (CDx) being positive is a key performance parameter for evaluating the clinical + validity utility of a companion diagnostic test in clinical bridging studies. + When bridging study patients are enrolled based on CTA assay results, Binomial-based + confidence intervals (CI) may are not appropriate for PPV CI estimation. Bootstrap + CIs which are not restricted by the Binomial assumption may be used for PPV CI + estimation only when PPV is not 100%. Bootstrap CI is not valid when PPV is 100% + and becomes a single value of [1, 1]. We proposed a risk ratio-based method for + constructing CI for PPV. By simulation we illustrated that the coverage probability + of the proposed CI is close to the nominal value even when PPV is high and negative + percent agreement (NPA) is close to 100%. There is a lack of R package for PPV + CI calculation. we developed a publicly available R package along with this shiny + app to implement the proposed approach and some other existing methods. + date_publication: '2021-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=papci + url_git: '' +papeR: + version: 1.0-5 + title: A Toolbox for Writing Pretty Papers and Reports + maintainer: Benjamin Hofner + description: |- + A toolbox for writing 'knitr', 'Sweave' or other 'LaTeX'- or 'markdown'-based + reports and to prettify the output of various estimated models. + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=papeR + url_git: https://github.com/hofnerb/papeR +paperplanes: + version: 0.0.1.9 + title: Distance Recordings from a Paper Plane Folding/Flying Experiment + maintainer: Andreas Leha + description: This is a data only package, that provides distances from a paper plane + experiment. + date_publication: '2017-02-14' + bug_reports: https://gitlab.gwdg.de/aleha/paperplanes/issues + url: https://gitlab.gwdg.de/aleha/paperplanes + url_cran: https://CRAN.R-project.org/package=paperplanes + url_git: '' +parabar: + version: 1.4.2 + title: Progress Bar for Parallel Tasks + maintainer: Mihai Constantin + description: |- + A simple interface in the form of R6 classes for executing tasks in + parallel, tracking their progress, and displaying accurate progress bars. + date_publication: '2024-12-17' + bug_reports: https://github.com/mihaiconstantin/parabar/issues + url: https://parabar.mihaiconstantin.com + url_cran: https://CRAN.R-project.org/package=parabar + url_git: '' +parade: + version: '0.1' + title: Pen's Income Parades + maintainer: Marek Hlavac + description: 'Tool for producing Pen''s parade graphs, useful for visualizing inequalities + in income, wages or other variables, as proposed by Pen (1971, ISBN: 978-0140212594). + Income or another economic variable is captured by the vertical axis, while the + population is arranged in ascending order of income along the horizontal axis. + Pen''s income parades provide an easy-to-interpret visualization of economic inequalities.' + date_publication: '2019-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parade + url_git: '' +paradox: + version: 1.0.1 + title: Define and Work with Parameter Spaces for Complex Algorithms + maintainer: Martin Binder + description: |- + Define parameter spaces, constraints and + dependencies for arbitrary algorithms, to program on such spaces. Also + includes statistical designs and random samplers. Objects are + implemented as 'R6' classes. + date_publication: '2024-07-09' + bug_reports: https://github.com/mlr-org/paradox/issues + url: https://paradox.mlr-org.com + url_cran: https://CRAN.R-project.org/package=paradox + url_git: https://github.com/mlr-org/paradox +parafac4microbiome: + version: 1.0.3 + title: |- + Parallel Factor Analysis Modelling of Longitudinal Microbiome + Data + maintainer: Geert Roelof van der Ploeg + description: |- + Creation and selection of PARAllel FACtor Analysis (PARAFAC) + models of longitudinal microbiome data. You can import your own data with + our import functions or use one of the example datasets to create your own + PARAFAC models. Selection of the optimal number of components can be done + using assessModelQuality() and assessModelStability(). The selected model can + then be plotted using plotPARAFACmodel(). The Parallel Factor + Analysis method was originally described by Caroll and Chang (1970) + and Harshman (1970) + . + date_publication: '2024-09-24' + bug_reports: https://github.com/GRvanderPloeg/parafac4microbiome/issues + url: https://grvanderploeg.github.io/parafac4microbiome/ + url_cran: https://CRAN.R-project.org/package=parafac4microbiome + url_git: https://github.com/GRvanderPloeg/parafac4microbiome +parallelDist: + version: 0.2.6 + title: Parallel Distance Matrix Computation using Multiple Threads + maintainer: Alexander Eckert + description: |- + A fast parallelized alternative to R's native 'dist' function to + calculate distance matrices for continuous, binary, and multi-dimensional + input matrices, which supports a broad variety of 41 predefined distance + functions from the 'stats', 'proxy' and 'dtw' R packages, as well as user- + defined functions written in C++. For ease of use, the 'parDist' function + extends the signature of the 'dist' function and uses the same parameter + naming conventions as distance methods of existing R packages. The package + is mainly implemented in C++ and leverages the 'RcppParallel' package to + parallelize the distance computations with the help of the 'TinyThread' + library. Furthermore, the 'Armadillo' linear algebra library is used for + optimized matrix operations during distance calculations. The curiously + recurring template pattern (CRTP) technique is applied to avoid virtual + functions, which improves the Dynamic Time Warping calculations while + the implementation stays flexible enough to support different DTW step + patterns and normalization methods. + date_publication: '2022-02-03' + bug_reports: https://github.com/alexeckert/parallelDist/issues + url: https://www.alexandereckert.com/projects/#r-packages + url_cran: https://CRAN.R-project.org/package=parallelDist + url_git: https://github.com/alexeckert/parallelDist +ParallelLogger: + version: 3.3.1 + title: |- + Support for Parallel Computation, Logging, and Function + Automation + maintainer: Martijn Schuemie + description: |- + Support for parallel computation with progress bar, and option to stop or proceed on errors. Also provides logging to console and disk, + and the logging persists in the parallel threads. Additional functions support function call automation with delayed execution (e.g. for executing functions in + parallel). + date_publication: '2024-08-23' + bug_reports: https://github.com/OHDSI/ParallelLogger/issues + url: https://ohdsi.github.io/ParallelLogger/ + url_cran: https://CRAN.R-project.org/package=ParallelLogger + url_git: https://github.com/OHDSI/ParallelLogger +parallelly: + version: 1.42.0 + title: Enhancing the 'parallel' Package + maintainer: Henrik Bengtsson + description: Utility functions that enhance the 'parallel' package and support the + built-in parallel backends of the 'future' package. For example, availableCores() + gives the number of CPU cores available to your R process as given by the operating + system, 'cgroups' and Linux containers, R options, and environment variables, + including those set by job schedulers on high-performance compute clusters. If + none is set, it will fall back to parallel::detectCores(). Another example is + makeClusterPSOCK(), which is backward compatible with parallel::makePSOCKcluster() + while doing a better job in setting up remote cluster workers without the need + for configuring the firewall to do port-forwarding to your local computer. + date_publication: '2025-01-30' + bug_reports: https://github.com/futureverse/parallelly/issues + url: https://parallelly.futureverse.org + url_cran: https://CRAN.R-project.org/package=parallelly + url_git: https://github.com/futureverse/parallelly +parallelMap: + version: 1.5.1 + title: Unified Interface to Parallelization Back-Ends + maintainer: Bernd Bischl + description: |- + Unified parallelization framework for multiple + back-end, designed for internal package and interactive usage. The + main operation is parallel mapping over lists. Supports 'local', + 'multicore', 'mpi' and 'BatchJobs' mode. Allows tagging of the + parallel operation with a level name that can be later selected by the + user to switch on parallel execution for exactly this operation. + date_publication: '2021-06-28' + bug_reports: https://github.com/mlr-org/parallelMap/issues + url: https://parallelmap.mlr-org.com + url_cran: https://CRAN.R-project.org/package=parallelMap + url_git: https://github.com/mlr-org/parallelMap +parallelMCMCcombine: + version: '2.0' + title: Combining Subset MCMC Samples to Estimate a Posterior Density + maintainer: Erin Conlon + description: See Miroshnikov and Conlon (2014) . + Recent Bayesian Markov chain Monto Carlo (MCMC) methods have been developed for + big data sets that are too large to be analyzed using traditional statistical + methods. These methods partition the data into non-overlapping subsets, and perform + parallel independent Bayesian MCMC analyses on the data subsets, creating independent + subposterior samples for each data subset. These independent subposterior samples + are combined through four functions in this package, including averaging across + subset samples, weighted averaging across subsets samples, and kernel smoothing + across subset samples. The four functions assume the user has previously run the + Bayesian analysis and has produced the independent subposterior samples outside + of the package; the functions use as input the array of subposterior samples. + The methods have been demonstrated to be useful for Bayesian MCMC models including + Bayesian logistic regression, Bayesian Gaussian mixture models and Bayesian hierarchical + Poisson-Gamma models. The methods are appropriate for Bayesian hierarchical models + with hyperparameters, as long as data values in a single level of the hierarchy + are not split into subsets. + date_publication: '2021-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parallelMCMCcombine + url_git: '' +parallelpam: + version: 1.4.3 + title: Parallel Partitioning-Around-Medoids (PAM) for Big Sets of Data + maintainer: Juan Domingo + description: |- + Application of the Partitioning-Around-Medoids (PAM) clustering algorithm described in Schubert, E. and Rousseeuw, P.J.: + "Fast and eager k-medoids clustering: O(k) runtime improvement of the PAM, CLARA, and CLARANS algorithms." Information Systems, + vol. 101, p. 101804, (2021). . + It uses a binary format for storing and retrieval of matrices developed for the 'jmatrix' package but the functionality of 'jmatrix' + is included here, so you do not need to install it. Also, it is used by package 'scellpam', so if you have installed it, you do not need + to install this package. + PAM can be applied to sets of data whose dissimilarity matrix can be very big. It has been tested with up to 100.000 points. + It does this with the help of the code developed for other package, 'jmatrix', which allows the matrix not to be loaded in 'R' memory (which + would force it to be of double type) but it gets from disk, which allows using float (or even smaller data types). Moreover, the + dissimilarity matrix is calculated in parallel if the computer has several cores so it can open many threads. The initial part + of the PAM algorithm can be done with the BUILD or LAB algorithms; the BUILD algorithm has been implemented in parallel. The optimization + phase implements the FastPAM1 algorithm, also in parallel. Finally, calculation of silhouette is available and also implemented in parallel. + date_publication: '2024-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parallelpam + url_git: '' +ParallelPC: + version: '1.2' + title: |- + Paralellised Versions of Constraint Based Causal Discovery + Algorithms + maintainer: Thuc Duy Le + description: Parallelise constraint based causality discovery and causal inference + methods. The parallelised algorithms in the package will generate the same results + as that of the 'pcalg' package but will be much more efficient. + date_publication: '2015-12-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ParallelPC + url_git: '' +parallelPlot: + version: 0.4.0 + title: '`htmlwidget` for a Parallel Coordinates Plot' + maintainer: David Chazalviel + description: Create a parallel coordinates plot, using `htmlwidgets` package and + `d3.js`. + date_publication: '2024-06-17' + bug_reports: https://gitlab.com/drti/parallelplot/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parallelPlot + url_git: https://gitlab.com/drti/parallelplot +param2moment: + version: 0.1.2 + title: |- + Raw, Central and Standardized Moments of Parametric + Distributions + maintainer: Tingting Zhan + description: |- + To calculate the raw, + central and standardized + moments from distribution + parameters. To solve the + distribution parameters based + on user-provided mean, standard + deviation, skewness and + kurtosis. Normal, skew-normal, + skew-t and Tukey g-&-h + distributions are supported, + for now. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=param2moment + url_git: '' +paramDemo: + version: 1.0.2 + title: |- + Parametric and Non-Parametric Demographic Functions and + Applications + maintainer: Fernando Colchero + description: Calculate parametric mortality and Fertility models, following packages + 'BaSTA' in Colchero, Jones and Rebke (2012) + and 'BaFTA' , summary statistics (e.g. ageing + rates, life expectancy, lifespan equality, etc.), life table and product limit + estimators from census data. + date_publication: '2025-01-16' + bug_reports: https://github.com/fercol/paramDemo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paramDemo + url_git: '' +parameters: + version: 0.24.1 + title: Processing of Model Parameters + maintainer: Daniel Lüdecke + description: |- + Utilities for processing the parameters of various + statistical models. Beyond computing p values, CIs, and other indices + for a wide variety of models (see list of supported models using the + function 'insight::supported_models()'), this package implements + features like bootstrapping or simulating of parameters and models, + feature reduction (feature extraction and variable selection) as well + as functions to describe data and variable characteristics (e.g. + skewness, kurtosis, smoothness or distribution). + date_publication: '2025-01-14' + bug_reports: https://github.com/easystats/parameters/issues + url: https://easystats.github.io/parameters/ + url_cran: https://CRAN.R-project.org/package=parameters + url_git: '' +paramGUI: + version: 2.2.0 + title: A Shiny GUI for some Parameter Estimation Examples + maintainer: Joris Snellenburg + description: |- + Allows specification and fitting of some parameter estimation + examples inspired by time-resolved spectroscopy via a Shiny GUI. + date_publication: '2023-01-08' + bug_reports: https://github.com/glotaran/paramGUI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paramGUI + url_git: https://github.com/glotaran/paramGUI/ +ParamHelpers: + version: 1.14.2 + title: |- + Helpers for Parameters in Black-Box Optimization, Tuning and + Machine Learning + maintainer: Martin Binder + description: |- + Functions for parameter descriptions and operations in + black-box optimization, tuning and machine learning. Parameters can be + described (type, constraints, defaults, etc.), combined to parameter + sets and can in general be programmed on. A useful OptPath object + (archive) to log function evaluations is also provided. + date_publication: '2025-01-09' + bug_reports: https://github.com/mlr-org/ParamHelpers/issues + url: https://paramhelpers.mlr-org.com + url_cran: https://CRAN.R-project.org/package=ParamHelpers + url_git: https://github.com/mlr-org/ParamHelpers +paramhetero: + version: 1.0.0 + title: |- + Numeric and Visual Comparisons of Heterogeneity in Parametric + Models + maintainer: Travis Loux + description: |- + Performs statistical tests to compare coefficients and residual + variance across models. Also provides graphical methods for + assessing heterogeneity in coefficients and residuals. Currently supports + linear and generalized linear models. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paramhetero + url_git: '' +paramix: + version: 0.0.1 + title: |- + Aggregate and Disaggregate Continuous Parameters for + Compartmental Models + maintainer: Carl Pearson + description: |- + A convenient framework for aggregating and disaggregating continuously + varying parameters (for example, case fatality ratio, with age) for proper + parametrization of lower-resolution compartmental models (for example, with + broad age categories) and subsequent upscaling of model outputs to high resolution + (for example, as needed when calculating age-sensitive measures like years-life-lost). + date_publication: '2024-12-09' + bug_reports: '' + url: https://cmmid.github.io/paramix/ + url_cran: https://CRAN.R-project.org/package=paramix + url_git: '' +paramlink: + version: 1.1-5 + title: Parametric Linkage and Other Pedigree Analysis in R + maintainer: Magnus Dehli Vigeland + description: |- + NOTE: 'PARAMLINK' HAS BEEN SUPERSEDED BY THE 'PED SUITE' + PACKAGES (). 'PARAMLINK' IS + MAINTAINED ONLY FOR LEGACY PURPOSES AND SHOULD NOT BE USED IN NEW + PROJECTS. A suite of tools for analysing pedigrees with marker data, + including parametric linkage analysis, forensic computations, + relatedness analysis and marker simulations. The core of the package + is an implementation of the Elston-Stewart algorithm for pedigree + likelihoods, extended to allow mutations as well as complex + inbreeding. Features for linkage analysis include singlepoint LOD + scores, power analysis, and multipoint analysis (the latter through a + wrapper to the 'MERLIN' software). Forensic applications include + exclusion probabilities, genotype distributions and conditional + simulations. Data from the 'Familias' software can be imported and + analysed in 'paramlink'. Finally, 'paramlink' offers many utility + functions for creating, manipulating and plotting pedigrees with or + without marker data (the actual plotting is done by the 'kinship2' + package). + date_publication: '2022-04-15' + bug_reports: https://github.com/magnusdv/paramlink/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paramlink + url_git: https://github.com/magnusdv/paramlink +paramlink2: + version: 1.0.6 + title: Parametric Linkage Analysis + maintainer: Magnus Dehli Vigeland + description: |- + Parametric linkage analysis of monogenic traits in medical + pedigrees. Features include singlepoint analysis, multipoint analysis + via 'MERLIN' (Abecasis et al. (2002) ), + visualisation of log of the odds (LOD) scores and summaries of linkage + peaks. Disease models may be specified to accommodate phenocopies, + reduced penetrance and liability classes. 'paramlink2' is part of the + 'pedsuite' package ecosystem, presented in 'Pedigree Analysis in R' + (Vigeland, 2021, ISBN:9780128244302). + date_publication: '2024-09-07' + bug_reports: https://github.com/magnusdv/paramlink2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paramlink2 + url_git: https://github.com/magnusdv/paramlink2 +params: + version: 0.7.7 + title: Simplify Parameters + maintainer: Sahil Seth + description: |- + An interface to simplify organizing parameters used in a package, + using external configuration files. This attempts to provide a cleaner + alternative to options(). + date_publication: '2025-02-07' + bug_reports: https://github.com/sahilseth/params/issues + url: '' + url_cran: https://CRAN.R-project.org/package=params + url_git: https://github.com/sahilseth/params +paramsim: + version: 0.1.0 + title: Parameterized Simulation + maintainer: Daniel James + description: This function obtains a Random Number Generator (RNG) or collection + of RNGs that replicate the required parameter(s) of a distribution for a time + series of data. Consider the case of reproducing a time series data set of size + 20 that uses an autoregressive (AR) model with phi = 0.8 and standard deviation + equal to 1. When one checks the arima.sin() function's estimated parameters, it's + possible that after a single trial or a few more, one won't find the precise parameters. + This enables one to look for the ideal RNG setting for a simulation that will + accurately duplicate the desired parameters. + date_publication: '2023-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paramsim + url_git: '' +paramtest: + version: 0.1.0 + title: Run a Function Iteratively While Varying Parameters + maintainer: Jeffrey Hughes + description: |- + Run simulations or other functions while easily varying parameters + from one iteration to the next. Some common use cases would be grid search + for machine learning algorithms, running sets of simulations (e.g., + estimating statistical power for complex models), or bootstrapping under + various conditions. See the 'paramtest' documentation for more information + and examples. + date_publication: '2017-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paramtest + url_git: '' +paran: + version: 1.5.3 + title: Horn's Test of Principal Components/Factors + maintainer: Alexis Dinno + description: An implementation of Horn's technique for numerically and graphically + evaluating the components or factors retained in a principle components analysis + (PCA) or common factor analysis (FA). Horn's method contrasts eigenvalues produced + through a PCA or FA on a number of random data sets of uncorrelated variables + with the same number of variables and observations as the experimental or observational + data set to produce eigenvalues for components or factors that are adjusted for + the sample error-induced inflation. Components with adjusted eigenvalues greater + than one are retained. paran may also be used to conduct parallel analysis following + Glorfeld's (1995) suggestions to reduce the likelihood of over-retention. + date_publication: '2024-04-14' + bug_reports: '' + url: https://alexisdinno.com/Software/index.shtml#paran + url_cran: https://CRAN.R-project.org/package=paran + url_git: '' +ParBayesianOptimization: + version: 1.2.6 + title: Parallel Bayesian Optimization of Hyperparameters + maintainer: Samuel Wilson + description: |- + Fast, flexible framework for implementing Bayesian optimization of model + hyperparameters according to the methods described in Snoek et al. . + The package allows the user to run scoring function in parallel, save intermediary + results, and tweak other aspects of the process to fully utilize the computing resources + available to the user. + date_publication: '2022-10-18' + bug_reports: https://github.com/AnotherSamWilson/ParBayesianOptimization/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ParBayesianOptimization + url_git: https://github.com/AnotherSamWilson/ParBayesianOptimization +parcats: + version: 0.0.5 + title: Interactive Parallel Categories Diagrams for 'easyalluvial' + maintainer: Bjoern Koneswarakantha + description: |- + Complex graphical representations of data are best explored using interactive elements. + 'parcats' adds interactive graphing capabilities to the 'easyalluvial' package. + The 'plotly.js' parallel categories diagrams offer a good framework for + creating interactive flow graphs that allow manual drag and drop sorting of dimensions + and categories, highlighting single flows and displaying mouse over information. The + 'plotly.js' dependency is quite heavy and therefore is outsourced into a separate package. + date_publication: '2023-12-10' + bug_reports: https://github.com/erblast/parcats/issues/ + url: https://erblast.github.io/parcats/ + url_cran: https://CRAN.R-project.org/package=parcats + url_git: '' +parcr: + version: 0.5.2 + title: Construct Parsers for Structured Text Files + maintainer: Douwe Molenaar + description: |- + Construct parser combinator functions, higher order functions that + parse input. Construction of such parsers is transparent and easy. Their main + application is the parsing of structured text files like those generated by + laboratory instruments. Based on a paper by Hutton (1992) + . + date_publication: '2024-06-07' + bug_reports: https://github.com/SystemsBioinformatics/parcr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parcr + url_git: https://github.com/SystemsBioinformatics/parcr +ParDNAcopy: + version: '2.0' + title: |- + Parallel implementation of the "segment" function of package + "DNAcopy" + maintainer: Guoli Sun + description: Parallelized version of the "segment" function from Bioconductor package + "DNAcopy", utilizing multi-core computation on host CPU + date_publication: '2014-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ParDNAcopy + url_git: '' +PaRe: + version: 0.1.15 + title: A Way to Perform Code Review or QA on Other Packages + maintainer: Maarten van Kessel + description: |- + Reviews other packages during code review by looking at their + dependencies, code style, code complexity, and how internally defined + functions interact with one another. + date_publication: '2024-12-02' + bug_reports: https://github.com/darwin-eu-dev/PaRe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PaRe + url_git: https://github.com/darwin-eu-dev/PaRe +Pareto: + version: 2.4.5 + title: The Pareto, Piecewise Pareto and Generalized Pareto Distribution + maintainer: Ulrich Riegel + description: |- + Utilities for the Pareto, piecewise Pareto and generalized Pareto distribution + that are useful for reinsurance pricing. In particular, the package provides + a non-trivial algorithm that can be used to match the expected losses of a + tower of reinsurance layers with a layer-independent collective risk model. + The theoretical background of the matching algorithm and most other methods + are described in Ulrich Riegel (2018) . + date_publication: '2023-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Pareto + url_git: https://github.com/ulrichriegel/Pareto#pareto +ParetoPosStable: + version: '1.1' + title: Computing, Fitting and Validating the PPS Distribution + maintainer: Antonio Jose Saez-Castillo + description: |- + Statistical functions to describe a Pareto Positive Stable (PPS) + distribution and fit it to real data. Graphical and statistical tools to + validate the fits are included. + date_publication: '2015-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ParetoPosStable + url_git: '' +parfm: + version: 2.7.7 + title: Parametric Frailty Models + maintainer: Federico Rotolo + description: |- + Fits Parametric Frailty Models by maximum marginal likelihood. + Possible baseline hazards: + exponential, Weibull, inverse Weibull (Fréchet), + Gompertz, lognormal, log-skew-normal, and loglogistic. + Possible Frailty distributions: + gamma, positive stable, inverse Gaussian and lognormal. + date_publication: '2023-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parfm + url_git: '' +pargasite: + version: 2.1.1 + title: Pollution-Associated Risk Geospatial Analysis Site + maintainer: Jaehyun Joo + description: |- + Offers tools to estimate and visualize levels of major pollutants + (CO, NO2, SO2, Ozone, PM2.5 and PM10) across the conterminous + United States for user-defined time ranges. Provides functions to + retrieve pollutant data from the U.S. Environmental Protection + Agency’s 'Air Quality System' (AQS) API service + for + interactive visualization through a 'shiny' application, allowing + users to explore pollutant levels for a given location over time + relative to the National Ambient Air Quality Standards (NAAQS). + date_publication: '2024-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pargasite + url_git: '' +parglm: + version: 0.1.7 + title: Parallel GLM + maintainer: Benjamin Christoffersen + description: |- + Provides a parallel estimation method for generalized + linear models without compiling with a multithreaded LAPACK or BLAS. + date_publication: '2021-10-14' + bug_reports: https://github.com/boennecd/parglm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parglm + url_git: https://github.com/boennecd/parglm +pARI: + version: 1.1.2 + title: Permutation-Based All-Resolutions Inference + maintainer: Angela Andreella + description: Computes the All-Resolution Inference method in the permutation framework, + i.e., simultaneous lower confidence bounds for the number of true discoveries. + . + date_publication: '2024-09-06' + bug_reports: https://github.com/angeella/pARI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pARI + url_git: https://github.com/angeella/pARI +Paris2024Colours: + version: 0.2.0 + title: |- + Color Palettes Inspired by Paris 2024 Olympic and Paralympic + Games + maintainer: Maxime Kuntz + description: |- + Palettes inspired by Paris 2024 Olympic and Paralympic Games for + data visualizations. Length of color palettes is configurable. + date_publication: '2024-06-20' + bug_reports: https://github.com/maximekuntz/Paris2024Colours/issues + url: https://maximekuntz.github.io/Paris2024Colours/ + url_cran: https://CRAN.R-project.org/package=Paris2024Colours + url_git: https://github.com/maximekuntz/Paris2024Colours +parma: + version: '1.7' + title: Portfolio Allocation and Risk Management Applications + maintainer: Alexios Galanos + description: Provision of a set of models and methods for use in the allocation + and management of capital in financial portfolios. + date_publication: '2022-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parma + url_git: https://github.com/alexiosg/parma +parmigene: + version: 1.1.1 + title: |- + Parallel Mutual Information Estimation for Gene Network + Reconstruction + maintainer: Gabriele Sales + description: |- + Parallel estimation of the mutual information based on entropy + estimates from k-nearest neighbors distances and algorithms for the + reconstruction of gene regulatory networks + (Sales et al, 2011 ). + date_publication: '2024-10-21' + bug_reports: https://github.com/sales-lab/parmigene/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parmigene + url_git: https://github.com/sales-lab/parmigene +parmsurvfit: + version: 0.1.0 + title: Parametric Models for Survival Data + maintainer: Ashley Jacobson + description: |- + Executes simple parametric models for right-censored + survival data. Functionality emulates capabilities in 'Minitab', including + fitting right-censored data, assessing fit, plotting survival functions, + and summary statistics and probabilities. + date_publication: '2018-12-07' + bug_reports: https://github.com/apjacobson/parmsurvfit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parmsurvfit + url_git: https://github.com/apjacobson/parmsurvfit +paropt: + version: 0.3.3 + title: Parameter Optimizing of ODE-Systems + maintainer: Krämer Konrad + description: |- + Enable optimization of parameters of ordinary differential equations. + Therefore, using 'SUNDIALS' to solve the ODE-System (see Hindmarsh, Alan C., Peter N. Brown, Keith E. Grant, Steven L. Lee, Radu Serban, Dan E. Shumaker, and Carol S. Woodward. (2005) ). + Furthermore, for optimization the particle swarm algorithm is used (see: Akman, Devin, Olcay Akman, and Elsa Schaefer. (2018) and Sengupta, Saptarshi, Sanchita Basak, and Richard Peters. (2018) ). + date_publication: '2024-02-22' + bug_reports: https://github.com/Konrad1991/paropt + url: '' + url_cran: https://CRAN.R-project.org/package=paropt + url_git: '' +parqr: + version: 0.1.0 + title: Read in Multi-Part Parquet Files + maintainer: John Waller + description: Reads in multi-part parquet files. Will read in parquet files that + have not been previously coalesced into one file. Convenient for reading in moderately + sized, but split files. + date_publication: '2021-07-15' + bug_reports: https://github.com/jhnwllr/parqr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parqr + url_git: https://github.com/jhnwllr/parqr +parquetize: + version: 0.5.7 + title: Convert Files to Parquet Format + maintainer: Damien Dotta + description: |- + Collection of functions to get files in parquet format. + Parquet is a columnar storage file format . + The files to convert can be of several formats + ("csv", "RData", "rds", "RSQLite", + "json", "ndjson", "SAS", "SPSS"...). + date_publication: '2024-03-04' + bug_reports: https://github.com/ddotta/parquetize/issues + url: https://ddotta.github.io/parquetize/ + url_cran: https://CRAN.R-project.org/package=parquetize + url_git: https://github.com/ddotta/parquetize +parsec: + version: 1.2.7 + title: Partial Orders in Socio-Economics + maintainer: Alberto Arcagni + description: Implements tools for the analysis of partially ordered data, with a + particular focus on the evaluation of multidimensional systems of indicators and + on the analysis of poverty. References, Fattore M. (2016) + Fattore M., Arcagni A. (2016) Arcagni A. (2017) + . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parsec + url_git: '' +parsedate: + version: 1.3.2 + title: |- + Recognize and Parse Dates in Various Formats, Including All ISO + 8601 Formats + maintainer: Gábor Csárdi + description: |- + Parse dates automatically, without the need of specifying a + format. Currently it includes the git date parser. It can also + recognize and parse all ISO 8601 formats. + date_publication: '2024-12-09' + bug_reports: https://github.com/gaborcsardi/parsedate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parsedate + url_git: https://github.com/gaborcsardi/parsedate +parsel: + version: 0.3.0 + title: Parallel Dynamic Web-Scraping Using 'RSelenium' + maintainer: Till Tietz + description: |- + A system to increase the efficiency of dynamic web-scraping with 'RSelenium' + by leveraging parallel processing. You provide a function wrapper for your 'RSelenium' + scraping routine with a set of inputs, and 'parsel' runs it in several browser instances. + Chunked input processing as well as error catching and logging ensures seamless + execution and minimal data loss, even when unforeseen 'RSelenium' errors occur. You can additionally + build safe scraping functions with minimal coding by utilizing constructor functions that act as wrappers + around 'RSelenium' methods. + date_publication: '2023-02-22' + bug_reports: https://github.com/till-tietz/parsel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parsel + url_git: https://github.com/till-tietz/parsel +parseLatex: + version: 0.3.0 + title: Parse 'LaTeX' Code + maintainer: Duncan Murdoch + description: |- + Exports an enhanced version of the tools::parseLatex() + function to handle 'LaTeX' syntax more accurately. Also + includes numerous functions for searching and modifying + 'LaTeX' source. + date_publication: '2025-02-20' + bug_reports: https://github.com/dmurdoch/parseLatex/issues + url: https://dmurdoch.github.io/parseLatex/ + url_cran: https://CRAN.R-project.org/package=parseLatex + url_git: https://github.com/dmurdoch/parseLatex +parsermd: + version: 0.1.3 + title: Formal Parser and Related Tools for R Markdown Documents + maintainer: Colin Rundel + description: |- + An implementation of a formal grammar and parser for R Markdown documents + using the Boost Spirit X3 library. It also includes a collection of high level + functions for working with the resulting abstract syntax tree. + date_publication: '2024-01-16' + bug_reports: https://github.com/rundel/parsermd/issues + url: https://rundel.github.io/parsermd/ + url_cran: https://CRAN.R-project.org/package=parsermd + url_git: https://github.com/rundel/parsermd +parseRPDR: + version: 1.1.2 + title: |- + Parse and Manipulate Research Patient Data Registry ('RPDR') + Text Queries + maintainer: Marton Kolossvary + description: |- + Functions to load Research Patient Data Registry ('RPDR') text queries from Partners Healthcare institutions into R. + The package also provides helper functions to manipulate data and execute common procedures + such as finding the closest radiological exams considering a given timepoint, or creating a DICOM header database + from the downloaded images. All functionalities are parallelized for fast and efficient analyses. + date_publication: '2025-01-19' + bug_reports: https://github.com/martonkolossvary/parseRPDR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parseRPDR + url_git: https://github.com/martonkolossvary/parseRPDR +parSim: + version: 0.1.5 + title: Parallel Simulation Studies + maintainer: Sacha Epskamp + description: |- + Perform flexible simulation studies using one or multiple computer cores. + The package is set up to be usable on high-performance clusters in addition + to being run locally, see examples on . + date_publication: '2023-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parSim + url_git: '' +parsnip: + version: 1.3.0 + title: A Common API to Modeling and Analysis Functions + maintainer: Max Kuhn + description: |- + A common interface is provided to allow users to specify a + model without having to remember the different argument names across + different functions or computational engines (e.g. 'R', 'Spark', + 'Stan', 'H2O', etc). + date_publication: '2025-02-14' + bug_reports: https://github.com/tidymodels/parsnip/issues + url: https://parsnip.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=parsnip + url_git: https://github.com/tidymodels/parsnip +PartCensReg: + version: '1.39' + title: |- + Estimation and Diagnostics for Partially Linear Censored + Regression Models Based on Heavy-Tailed Distributions + maintainer: Marcela Nunez Lemus + description: It estimates the parameters of a partially linear regression censored + model via maximum penalized likelihood through of ECME algorithm. The model belong + to the semiparametric class, that including a parametric and nonparametric component. + The error term considered belongs to the scale-mixture of normal (SMN) distribution, + that includes well-known heavy tails distributions as the Student-t distribution, + among others. To examine the performance of the fitted model, case-deletion and + local influence techniques are provided to show its robust aspect against outlying + and influential observations. This work is based in Ferreira, C. S., & Paula, + G. A. (2017) but considering the SMN family. + date_publication: '2018-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PartCensReg + url_git: '' +partDSA: + version: 0.9.14 + title: Partitioning Using Deletion, Substitution, and Addition Moves + maintainer: Annette Molinaro + description: |- + A novel tool for generating a piecewise + constant estimation list of increasingly complex predictors + based on an intensive and comprehensive search over the entire + covariate space. + date_publication: '2017-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=partDSA + url_git: '' +partialised: + version: 0.1.1 + title: Partialised Functions + maintainer: Mizuki Uchida + description: |- + Provides a 'partialised' class that extends the partialising + function of 'purrr' by making it easier to change the arguments. This is + similar to the function-like object in 'Julia' + (). + date_publication: '2022-11-04' + bug_reports: https://github.com/UchidaMizuki/partialised/issues + url: '' + url_cran: https://CRAN.R-project.org/package=partialised + url_git: https://github.com/UchidaMizuki/partialised +Partiallyoverlapping: + version: '2.0' + title: Partially Overlapping Samples Tests + maintainer: Ben Derrick + description: |- + Tests for a comparison of two partially overlapping samples. + A comparison of means using the partially overlapping samples t-test: + See Derrick, Russ, Toher and White (2017), Test + statistics for the comparison of means for two samples which include + both paired observations and independent observations, Journal of + Modern Applied Statistical Methods, 16(1). + A comparison of proportions using the partially overlapping samples z-test: + See Derrick, Dobson-Mckittrick, Toher and White (2015), Test statistics + for comparing two proportions with partially overlapping samples. + Journal of Applied Quantitative Methods, 10(3). + date_publication: '2018-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Partiallyoverlapping + url_git: '' +PartialNetwork: + version: 1.0.4 + title: Estimating Peer Effects Using Partial Network Data + maintainer: Aristide Houndetoungan + description: Implements IV-estimator and Bayesian estimator for linear-in-means + Spatial Autoregressive (SAR) model (see LeSage, 1997 ; + Lee, 2004 ; Bramoullé et al., 2009 ), + while assuming that only a partial information about the network structure is + available. Examples are when the adjacency matrix is not fully observed or when + only consistent estimation of the network formation model is available (see Boucher + and Houndetoungan ). + date_publication: '2024-05-15' + bug_reports: https://github.com/ahoundetoungan/PartialNetwork/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PartialNetwork + url_git: https://github.com/ahoundetoungan/PartialNetwork +particle.swarm.optimisation: + version: '1.0' + title: Optimisation with Particle Swarm Optimisation + maintainer: Theo Brunet + description: 'A toolbox to create a particle swarm optimisation (PSO), the package + contains two classes: the Particle and the Particle Swarm, this two class is used + to run the PSO with methods to easily print, plot and save the result.' + date_publication: '2021-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=particle.swarm.optimisation + url_git: '' +particles: + version: 0.2.4 + title: A Graph Based Particle Simulator Based on D3-Force + maintainer: Thomas Lin Pedersen + description: |- + Simulating particle movement in 2D space has many + application. The 'particles' package implements a particle simulator + based on the ideas behind the 'd3-force' 'JavaScript' library. + 'particles' implements all forces defined in 'd3-force' as well as + others such as vector fields, traps, and attractors. + date_publication: '2024-12-03' + bug_reports: https://github.com/thomasp85/particles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=particles + url_git: https://github.com/thomasp85/particles +parTimeROC: + version: 0.1.0 + title: Parametric Time-Dependent Receiver Operating Characteristic + maintainer: Faiz Azhar + description: |- + Producing the time-dependent receiver operating characteristic (ROC) curve through parametric approaches. Tools for + generating random data, fitting, predicting and check goodness of fit are prepared. The methods are + developed from the theoretical framework of proportional hazard model and copula functions. + Using this package, users can now simulate parametric time-dependent ROC and run experiment + to understand the behavior of the curve under different scenario. + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=parTimeROC + url_git: '' +partition: + version: 0.2.2 + title: Agglomerative Partitioning Framework for Dimension Reduction + maintainer: Malcolm Barrett + description: |- + A fast and flexible framework for agglomerative partitioning. + 'partition' uses an approach called Direct-Measure-Reduce to create + new variables that maintain the user-specified minimum level of + information. Each reduced variable is also interpretable: the original + variables map to one and only one variable in the reduced data set. + 'partition' is flexible, as well: how variables are selected to + reduce, how information loss is measured, and the way data is reduced + can all be customized. 'partition' is based on the Partition + framework discussed in Millstein et al. (2020) + . + date_publication: '2024-10-09' + bug_reports: https://github.com/USCbiostats/partition/issues + url: https://uscbiostats.github.io/partition/ + url_cran: https://CRAN.R-project.org/package=partition + url_git: https://github.com/USCbiostats/partition +partitionBEFsp: + version: '1.0' + title: Methods for Calculating the Loreau & Hector 2001 BEF Partition + maintainer: Adam Clark + description: |- + A collection of functions that can be used to estimate selection and complementarity effects, + sensu Loreau & Hector (2001) , even in cases where data are only available for + a random subset of species (i.e. incomplete sample-level data). A full derivation and explanation of the + statistical corrections used here is available in Clark et al. (2019) . + date_publication: '2019-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=partitionBEFsp + url_git: '' +partitionComparison: + version: 0.2.6 + title: Implements Measures for the Comparison of Two Partitions + maintainer: Fabian Ball + description: |- + Provides several measures ((dis)similarity, distance/metric, + correlation, entropy) for comparing two partitions of the same set of + objects. The different measures can be assigned to three different + classes: Pair comparison (containing the famous Jaccard and Rand + indices), set based, and information theory based. + Many of the implemented measures can be found in + Albatineh AN, Niewiadomska-Bugaj M and Mihalko D (2006) + and + Meila M (2007) . + Partitions are represented by vectors of class labels which allow a + straightforward integration with existing clustering algorithms + (e.g. kmeans()). The package is mostly based on the S4 object system. + date_publication: '2023-08-23' + bug_reports: https://github.com/KIT-IISM-EM/partitionComparison/issues + url: '' + url_cran: https://CRAN.R-project.org/package=partitionComparison + url_git: https://github.com/KIT-IISM-EM/partitionComparison +partitionMetric: + version: '1.1' + title: Compute a distance metric between two partitions of a set + maintainer: David Weisman + description: |- + partitionMetric computes a distance between two partitions + of a set. + date_publication: '2014-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=partitionMetric + url_git: '' +partitions: + version: 1.10-7 + title: Additive Partitions of Integers + maintainer: Robin K. S. Hankin + description: |- + Additive partitions of integers. Enumerates the + partitions, unequal partitions, and restricted partitions of an + integer; the three corresponding partition functions are also given. + Set partitions and now compositions and riffle shuffles are + included. + date_publication: '2022-07-21' + bug_reports: https://github.com/RobinHankin/partitions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=partitions + url_git: https://github.com/RobinHankin/partitions +partools: + version: 1.1.6 + title: Tools for the 'Parallel' Package + maintainer: Norm Matloff + description: |- + Miscellaneous utilities for parallelizing large + computations. Alternative to MapReduce. + File splitting and distributed operations such as sort and aggregate. + "Software Alchemy" method for parallelizing most statistical methods, + presented in N. Matloff, Parallel Computation for Data Science, + Chapman and Hall, 2015. Includes a debugging aid. + date_publication: '2017-04-10' + bug_reports: https://github.com/matloff/partools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=partools + url_git: https://github.com/matloff/partools +partR2: + version: 0.9.2 + title: Partitioning R2 in GLMMs + maintainer: Martin A. Stoffel + description: |- + Partitioning the R2 of GLMMs into variation explained by each + predictor and combination of predictors using semi-partial (part) R2 and + inclusive R2. Methods are based on the R2 for GLMMs described in + Nakagawa & Schielzeth (2013) and Nakagawa, Johnson & Schielzeth (2017). + date_publication: '2024-03-04' + bug_reports: https://github.com/mastoffel/partR2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=partR2 + url_git: https://github.com/mastoffel/partR2 +partsm: + version: 1.1-3 + title: Periodic Autoregressive Time Series Models + maintainer: Matthieu Stigler + description: 'Basic functions to fit and predict periodic autoregressive time series + models. These models are discussed in the book P.H. Franses (1996) "Periodicity + and Stochastic Trends in Economic Time Series", Oxford University Press. Data + set analyzed in that book is also provided. NOTE: the package was orphaned during + several years. It is now only maintained, but no major enhancements are expected, + and the maintainer cannot provide any support.' + date_publication: '2020-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=partsm + url_git: https://github.com/MatthieuStigler/partsm +parttime: + version: 0.1.2 + title: Partial Datetime Handling + maintainer: Doug Kelkhoff + description: |2- + + Datetimes and timestamps are invariably an imprecise notation, with any + partial representation implying some amount of uncertainty. To handle this, + 'parttime' provides classes for embedding partial missingness as a central + part of its datetime classes. This central feature allows for more ergonomic + use of datetimes for challenging datetime computation, including + calculations of overlapping date ranges, imputations, and more thoughtful + handling of ambiguity that arises from uncertain time zones. This package was + developed first and foremost with pharmaceutical applications in mind, but + aims to be agnostic to application to accommodate general use cases just as + conveniently. + date_publication: '2024-01-24' + bug_reports: https://github.com/dgkf/parttime/issues + url: https://dgkf.github.io/parttime/ + url_cran: https://CRAN.R-project.org/package=parttime + url_git: https://github.com/dgkf/parttime +parttree: + version: 0.1.0 + title: Visualize Simple 2-D Decision Tree Partitions + maintainer: Grant McDermott + description: |- + Visualize the partitions of simple decision trees, involving one or + two predictors, on the scale of the original data. Provides an intuitive + alternative to traditional tree diagrams, by visualizing how a decision tree + divides the predictor space in a simple 2D plot alongside the original data. + The 'parttree' package supports both classification and regression trees + from 'rpart' and 'partykit', as well as trees produced by popular frontend + systems like 'tidymodels' and 'mlr3'. Visualization methods are provided for + both base R graphics and 'ggplot2'. + date_publication: '2025-01-16' + bug_reports: https://github.com/grantmcdermott/parttree/issues + url: https://grantmcdermott.com/parttree/ + url_cran: https://CRAN.R-project.org/package=parttree + url_git: '' +party: + version: 1.3-18 + title: A Laboratory for Recursive Partytioning + maintainer: Torsten Hothorn + description: |- + A computational toolbox for recursive partitioning. + The core of the package is ctree(), an implementation of + conditional inference trees which embed tree-structured + regression models into a well defined theory of conditional + inference procedures. This non-parametric class of regression + trees is applicable to all kinds of regression problems, including + nominal, ordinal, numeric, censored as well as multivariate response + variables and arbitrary measurement scales of the covariates. + Based on conditional inference trees, cforest() provides an + implementation of Breiman's random forests. The function mob() + implements an algorithm for recursive partitioning based on + parametric models (e.g. linear models, GLMs or survival + regression) employing parameter instability tests for split + selection. Extensible functionality for visualizing tree-structured + regression models is available. The methods are described in + Hothorn et al. (2006) , + Zeileis et al. (2008) and + Strobl et al. (2007) . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=party + url_git: http://party.R-forge.R-project.org +partykit: + version: 1.2-23 + title: A Toolkit for Recursive Partytioning + maintainer: Torsten Hothorn + description: |- + A toolkit with infrastructure for representing, summarizing, and + visualizing tree-structured regression and classification models. This + unified infrastructure can be used for reading/coercing tree models from + different sources ('rpart', 'RWeka', 'PMML') yielding objects that share + functionality for print()/plot()/predict() methods. Furthermore, new and improved + reimplementations of conditional inference trees (ctree()) and model-based + recursive partitioning (mob()) from the 'party' package are provided based + on the new infrastructure. A description of this package was published + by Hothorn and Zeileis (2015) . + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=partykit + url_git: http://partykit.r-forge.r-project.org/partykit/ +parzer: + version: 0.4.1 + title: Parse Messy Geographic Coordinates + maintainer: Alban Sagouis + description: |- + Parse messy geographic coordinates from various character formats + to decimal degree numeric values. Parse coordinates into + their parts (degree, minutes, seconds); calculate hemisphere + from coordinates; pull out individually degrees, + minutes, or seconds; add and subtract degrees, minutes, + and seconds. C++ code herein originally inspired from code + written by Jeffrey D. Bogan, but then completely re-written. + date_publication: '2021-12-20' + bug_reports: https://github.com/ropensci/parzer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=parzer + url_git: https://github.com/ropensci/parzer(devel)https://docs.ropensci.org/parzer/(docs) +PAS: + version: 1.2.5 + title: Polygenic Analysis System (PAS) + maintainer: Zhiqiu Hu + description: An R package for polygenic trait analysis. + date_publication: '2018-06-13' + bug_reports: '' + url: http://statgen.ucr.edu + url_cran: https://CRAN.R-project.org/package=PAS + url_git: '' +pasadr: + version: '1.0' + title: |- + An Implementation of Process-Aware Stealthy Attack + Detection(PASAD) + maintainer: Donghwan Kim + description: 'Anomaly detection method based on the paper "Truth will out: Departure-based + process-level detection of stealthy attacks on control systems" from Wissam Aoudi, + Mikel Iturbe, and Magnus Almgren (2018) . Also referred + to the following implementation: .' + date_publication: '2021-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pasadr + url_git: https://github.com/ainsuotain/pasadr +PASenseWear: + version: '1.0' + title: |- + Summarize Daily Physical Activity from 'SenseWear' Accelerometer + Data + maintainer: Yukun Zhang + description: Provide summary table of daily physical activity and per-person/grouped + heat map for accelerometer data from SenseWear Armband. See + for more information about SenseWear Armband. + date_publication: '2016-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PASenseWear + url_git: '' +pass.lme: + version: 0.9.0 + title: Power and Sample Size for Linear Mixed Effect Models + maintainer: Marco Chak Yan YU + description: Power and sample size calculation for testing fixed effect coefficients + in multilevel linear mixed effect models with one or more than one independent + populations. Laird, Nan M. and Ware, James H. (1982) . + date_publication: '2019-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pass.lme + url_git: '' +PASSED: + version: 1.2-2 + title: Calculate Power and Sample Size for Two Sample Mean Tests + maintainer: Jinpu Li + description: |- + Power calculations are a critical component of any research study to determine the + minimum sample size necessary to detect differences between multiple groups. Here we + present an 'R' package, 'PASSED', that performs power and sample size calculations for + the test of two-sample means or ratios with data following beta, + gamma (Chang et al. (2011), ), normal, + Poisson (Gu et al. (2008), ), binomial, geometric, and + negative binomial (Zhu and Lakkis (2014), ) distributions. + date_publication: '2023-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PASSED + url_git: '' +PAsso: + version: 0.1.10 + title: Assessing the Partial Association Between Ordinal Variables + maintainer: Xiaorui (Jeremy) Zhu + description: |- + An implementation of the unified framework for assessing partial association + between ordinal variables after adjusting for a set of covariates (Dungang Liu, Shaobo + Li, Yan Yu and Irini Moustaki (2020), accepted by the Journal of the American + Statistical Association). This package provides a set of tools to quantify, visualize, + and test partial associations between multiple ordinal variables. It can produce a number + of $phi$ measures, partial regression plots, 3-D plots, and $p$-values for testing + $H_0: phi=0$ or $H_0: phi <= delta$. + date_publication: '2021-06-18' + bug_reports: https://github.com/XiaoruiZhu/PAsso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PAsso + url_git: GitHub:https://github.com/XiaoruiZhu/PAsso +passport: + version: 0.3.0 + title: Travel Smoothly Between Country Name and Code Formats + maintainer: Edward Visel + description: |- + Smooths the process of working with country names and codes via + powerful parsing, standardization, and conversion utilities arranged in a + simple, consistent API. Country name formats include multiple sources + including the Unicode Common Locale Data + Repository (CLDR, ) common-sense standardized + names in hundreds of languages. + date_publication: '2020-11-07' + bug_reports: https://github.com/alistaire47/passport/issues + url: https://alistaire47.github.io/passport/ + url_cran: https://CRAN.R-project.org/package=passport + url_git: https://github.com/alistaire47/passport +passt: + version: 0.1.3 + title: Probability Associator Time (PASS-T) + maintainer: Johannes Titz + description: |- + Simulates judgments of frequency and duration based on + the Probability Associator Time (PASS-T) model. PASS-T is a memory + model based on a simple competitive artificial neural network. It + can imitate human judgments of frequency and duration, which have + been extensively studied in cognitive psychology + (e.g. Hintzman (1970) , Betsch et al. (2010) + ). The PASS-T model + is an extension of the PASS model (Sedlmeier, 2002, + ISBN:0198508638). The package provides an easy way to run + simulations, which can then be compared with empirical data in + human judgments of frequency and duration. + date_publication: '2021-05-03' + bug_reports: https://github.com/johannes-titz/passt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=passt + url_git: https://github.com/johannes-titz/passt +password: + version: 1.0-0 + title: Create Random Passwords + maintainer: Enrico Schumann + description: Create random passwords of letters, numbers and punctuation. + date_publication: '2016-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=password + url_git: '' +pastaPlot: + version: 0.1.0 + title: Spaghetti-Plot Fixed and Random Effects of Linear Mixed Models + maintainer: Jan-Felix Palnau + description: Plot both fixed and random effects of linear mixed models, multilevel + models in a single spaghetti plot. The package allows to visualize the effect + of a predictor on a criterion between different levels of a grouping variable. + Additionally, confidence intervals can be displayed for fixed effects. Calculation + of predicted values of random effects allows only models with one random intercept + and/or one random slope to be plotted. Confidence intervals and predicted values + of fixed effects are computed using the 'ggpredict' function from the 'ggeffects' + package. Lüdecke, D. (2018) . + date_publication: '2024-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pastaPlot + url_git: '' +pastboon: + version: 0.1.4 + title: Simulation of Parameterized Stochastic Boolean Networks + maintainer: Mohammad Taheri-Ledari + description: 'A Boolean network is a particular kind of discrete dynamical system + where the variables are simple binary switches. Despite its simplicity, Boolean + network modeling has been a successful method to describe the behavioral pattern + of various phenomena. Applying stochastic noise to Boolean networks is a useful + approach for representing the effects of various perturbing stimuli on complex + systems. A number of methods have been developed to control noise effects on Boolean + networks using parameters integrated into the update rules. This package provides + functions to examine three such methods: Boolean network with perturbations (BNp), + described by Trairatphisan et al. (2013) , stochastic + discrete dynamical systems (SDDS), proposed by Murrugarra et al. (2012) , + and Boolean network with probabilistic edge weights (PEW), presented by Deritei + et al. (2022) . This package includes source + code derived from the ''BoolNet'' package, which is licensed under the Artistic + License 2.0.' + date_publication: '2025-01-24' + bug_reports: https://github.com/taherimo/pastboon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pastboon + url_git: '' +pastclim: + version: 2.2.0 + title: Manipulate Time Series of Climate Reconstructions + maintainer: Andrea Manica + description: |- + Methods to easily extract and manipulate climate + reconstructions for ecological and anthropological analyses, as described + in Leonardi et al. (2023) . The package includes datasets + of palaeoclimate reconstructions, present observations, and future projections + from multiple climate models. + date_publication: '2025-02-23' + bug_reports: https://github.com/EvolEcolGroup/pastclim/issues + url: https://evolecolgroup.github.io/pastclim/ + url_cran: https://CRAN.R-project.org/package=pastclim + url_git: https://github.com/EvolEcolGroup/pastclim +pasteAsComment: + version: 0.2.1 + title: |- + 'RStudio' Addin to Paste the Clipboard as a Comment Block or a + 'roxygen' Block + maintainer: Stéphane Laurent + description: Provides a 'RStudio' addin allowing to paste the content of the clipboard + as a comment block or as 'roxygen' lines. This is very useful to insert an example + in the 'roxygen' block. + date_publication: '2023-09-14' + bug_reports: https://github.com/stla/pasteAsComment/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pasteAsComment + url_git: https://github.com/stla/pasteAsComment +pastecs: + version: 1.4.2 + title: Package for Analysis of Space-Time Ecological Series + maintainer: Philippe Grosjean + description: |- + Regularisation, decomposition and analysis of space-time series. + The pastecs R package is a PNEC-Art4 and IFREMER (Benoit Beliaeff + ) initiative to bring PASSTEC 2000 functionalities to R. + date_publication: '2024-02-01' + bug_reports: https://github.com/SciViews/pastecs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pastecs + url_git: https://github.com/SciViews/pastecs +PASWR: + version: '1.3' + title: Probability and Statistics with R + maintainer: Alan T. Arnholt + description: |- + Functions and data sets for the text Probability and Statistics + with R. + date_publication: '2022-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PASWR + url_git: '' +PASWR2: + version: 1.0.5 + title: Probability and Statistics with R, Second Edition + maintainer: Alan T. Arnholt + description: |- + Functions and data sets for the text Probability and Statistics + with R, Second Edition. + date_publication: '2021-09-04' + bug_reports: https://github.com/alanarnholt/PASWR2/issues + url: https://alanarnholt.github.io/PASWR2/ + url_cran: https://CRAN.R-project.org/package=PASWR2 + url_git: https://github.com/alanarnholt/PASWR2 +patchDVI: + version: 1.11.3 + title: Package to Patch '.dvi' or '.synctex' Files + maintainer: Duncan Murdoch + description: |- + Functions to patch specials in '.dvi' files, + or entries in '.synctex' files. Works with concordance=TRUE + in Sweave, knitr or R Markdown to link sources to previews. + date_publication: '2024-10-21' + bug_reports: https://github.com/dmurdoch/patchDVI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=patchDVI + url_git: https://github.com/dmurdoch/patchDVI +patchSynctex: + version: 0.1-4 + title: Communication Between Editor and Viewer for Literate Programs + maintainer: Emmanuel Charpentier + description: |- + This utility eases the debugging of literate documents + ('noweb' files) by patching the synchronization information + (the '.synctex(.gz)' file) produced by 'pdflatex' with + concordance information produced by 'Sweave' or 'knitr' and + 'Sweave' or 'knitr' ; this allows for bilateral communication + between a text editor (visualizing the 'noweb' source) and + a viewer (visualizing the resultant 'PDF'), thus bypassing + the intermediate 'TeX' file. + date_publication: '2016-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=patchSynctex + url_git: https://github.com/EmmanuelCharpentier/patchSynctex +patchwork: + version: 1.3.0 + title: The Composer of Plots + maintainer: Thomas Lin Pedersen + description: |- + The 'ggplot2' package provides a strong API for sequentially + building up a plot, but does not concern itself with composition of multiple + plots. 'patchwork' is a package that expands the API to allow for + arbitrarily complex composition of plots by, among others, providing + mathematical operators for combining multiple plots. Other packages that try + to address this need (but with a different approach) are 'gridExtra' and + 'cowplot'. + date_publication: '2024-09-16' + bug_reports: https://github.com/thomasp85/patchwork/issues + url: https://patchwork.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=patchwork + url_git: https://github.com/thomasp85/patchwork +patentr: + version: 0.1.4 + title: Access USPTO Bulk Data in Tidy Rectangular Format + maintainer: Raoul Wadhwa + description: |- + Converts TXT and XML data curated by the United States Patent and + Trademark Office (USPTO). Allows conversion of bulk data after downloading + directly from the USPTO bulk data website, eliminating need for users to + wrangle multiple data formats to get large patent databases in tidy, + rectangular format. Data details can be found on the USPTO website + . Currently, all 3 formats: 1. TXT data + (1976-2001); 2. XML format 1 data (2002-2004); and 3. XML format 2 data + (2005-current) can be converted to rectangular, CSV format. + Relevant literature that uses data from USPTO includes Wada (2020) + and Plaza & Albert (2008) + . + date_publication: '2021-09-12' + bug_reports: https://github.com/JYProjs/patentr/issues + url: https://JYProjs.github.io/patentr/ + url_cran: https://CRAN.R-project.org/package=patentr + url_git: '' +patentsview: + version: 0.3.0 + title: An R Client to the 'PatentsView' API + maintainer: Christopher Baker + description: |- + Provides functions to simplify the 'PatentsView' API + () query language, + send GET and POST requests to the API's seven endpoints, and parse the data + that comes back. + date_publication: '2021-09-25' + bug_reports: https://github.com/ropensci/patentsview/issues + url: https://docs.ropensci.org/patentsview/index.html + url_cran: https://CRAN.R-project.org/package=patentsview + url_git: '' +Path.Analysis: + version: '0.1' + title: Path Coefficient Analysis + maintainer: Ali Arminian + description: 'Facilitates the performance of several analyses, including simple + and sequential path coefficient analysis, correlation estimate, drawing correlogram, + Heatmap, and path diagram. When working with raw data, that includes one or more + dependent variables along with one or more independent variables are available, + the path coefficient analysis can be conducted. It allows for testing direct effects, + which can be a vital indicator in path coefficient analysis. The process of preparing + the dataset rule is explained in detail in the vignette file "Path.Analysis_manual.Rmd". + You can find this in the folders labelled "data" and "~/inst/extdata". Also see: + 1)the ''lavaan'', 2)a sample of sequential path analysis in ''metan'' suggested + by Olivoto and Lúcio (2020) , 3)the simple ''PATHSAS'' + macro written in ''SAS'' by Cramer et al. (1999) , + and 4)the semPlot() function of ''OpenMx'' as initial tools for conducting path + coefficient analyses and SEM (Structural Equation Modeling). To gain a comprehensive + understanding of path coefficient analysis, both in theory and practice, see a + ''Minitab'' macro developed by Arminian, A. in the paper by Arminian et al. (2008) + .' + date_publication: '2024-09-25' + bug_reports: https://github.com/abeyran/Path.Analysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Path.Analysis + url_git: https://github.com/abeyran/Path.Analysis +path.chain: + version: 1.0.0 + title: Concise Structure for Chainable Paths + maintainer: Krzysztof Joachimiak + description: |- + Provides path_chain class and functions, which facilitates loading and saving + directory structure in YAML configuration files via 'config' package. + The file structure you created during exploration can be transformed + into legible section in the config file, and then easily loaded for further usage. + date_publication: '2024-10-08' + bug_reports: https://github.com/krzjoa/path.chain/issues + url: https://krzjoa.github.io/path.chain/ + url_cran: https://CRAN.R-project.org/package=path.chain + url_git: https://github.com/krzjoa/path.chain +pathfindR: + version: 2.4.2 + title: Enrichment Analysis Utilizing Active Subnetworks + maintainer: Ege Ulgen + description: |- + Enrichment analysis enables researchers to uncover mechanisms + underlying a phenotype. However, conventional methods for enrichment + analysis do not take into account protein-protein interaction information, + resulting in incomplete conclusions. 'pathfindR' is a tool for enrichment + analysis utilizing active subnetworks. The main function identifies active + subnetworks in a protein-protein interaction network using a user-provided + list of genes and associated p values. It then performs enrichment analyses + on the identified subnetworks, identifying enriched terms (i.e. pathways or, + more broadly, gene sets) that possibly underlie the phenotype of interest. + 'pathfindR' also offers functionalities to cluster the enriched terms and + identify representative terms in each cluster, to score the enriched terms + per sample and to visualize analysis results. The enrichment, clustering and + other methods implemented in 'pathfindR' are described in detail in + Ulgen E, Ozisik O, Sezerman OU. 2019. 'pathfindR': An R Package for + Comprehensive Identification of Enriched Pathways in Omics Data Through + Active Subnetworks. Front. Genet. . + date_publication: '2025-02-17' + bug_reports: https://github.com/egeulgen/pathfindR/issues + url: https://egeulgen.github.io/pathfindR/ + url_cran: https://CRAN.R-project.org/package=pathfindR + url_git: https://github.com/egeulgen/pathfindR +pathfindR.data: + version: 2.1.0 + title: Data Package for 'pathfindR' + maintainer: Ege Ulgen + description: |- + This is a data-only package, containing data needed to run the CRAN + package 'pathfindR', a package for enrichment analysis utilizing active + subnetworks. This package contains protein-protein interaction network data, + data related to gene sets and example input/output data. + date_publication: '2024-04-27' + bug_reports: https://github.com/egeulgen/pathfindR.data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pathfindR.data + url_git: https://github.com/egeulgen/pathfindR.data +pathling: + version: 7.0.0 + title: A Library for using 'Pathling' + maintainer: '"Australian e-Health Research Centre, CSIRO"' + description: R API for 'Pathling', a tool for querying and transforming electronic + health record data that is represented using the 'Fast Healthcare Interoperability + Resources' (FHIR) standard - see . + date_publication: '2024-05-22' + bug_reports: https://github.com/aehrc/pathling/issues + url: https://pathling.csiro.au/ + url_cran: https://CRAN.R-project.org/package=pathling + url_git: '' +pathlit: + version: 0.1.0 + title: An SDK for the PathLit Engine + maintainer: Riasat Ali Istiaque + description: |- + This wrapper houses PathLit API endpoints for R. The usage of + these endpoints require the use of an API key which can be obtained at + . + date_publication: '2021-07-22' + bug_reports: '' + url: https://www.pathlit.io + url_cran: https://CRAN.R-project.org/package=pathlit + url_git: '' +pathmodelfit: + version: 1.0.5 + title: Path Component Fit Indices for Latent Structural Equation Models + maintainer: Steven Andrew Culpepper + description: |- + Functions for computing fit indices for + evaluating the path component of latent variable structural equation models. + Available fit indices include RMSEA-P and NSCI-P originally presented and evaluated + by Williams and O'Boyle (2011) and demonstrated by + O'Boyle and Williams (2011) and Williams, O'Boyle, & Yu (2020) + . Also included are fit indices described by + Hancock and Mueller (2011) . + date_publication: '2020-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pathmodelfit + url_git: '' +paths: + version: 0.1.1 + title: |- + An Imputation Approach to Estimating Path-Specific Causal + Effects + maintainer: Minh Trinh + description: |- + In causal mediation analysis with multiple causally ordered mediators, a set of path-specific + effects are identified under standard ignorability assumptions. This package implements an imputation + approach to estimating these effects along with a set of bias formulas for conducting sensitivity analysis + (Zhou and Yamamoto ). It contains two main functions: paths() for estimating + path-specific effects and sens() for conducting sensitivity analysis. Estimation uncertainty is quantified + using the nonparametric bootstrap. + date_publication: '2021-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=paths + url_git: '' +pathviewr: + version: 1.1.7 + title: Wrangle, Analyze, and Visualize Animal Movement Data + maintainer: Vikram B. Baliga + description: |- + Tools to import, clean, and visualize movement data, + particularly from motion capture systems such as Optitrack's + 'Motive', the Straw Lab's 'Flydra', or from other sources. We provide + functions to remove artifacts, standardize tunnel position and tunnel + axes, select a region of interest, isolate specific trajectories, fill + gaps in trajectory data, and calculate 3D and per-axis velocity. For + experiments of visual guidance, we also provide functions that use + subject position to estimate perception of visual stimuli. + date_publication: '2023-03-08' + bug_reports: https://github.com/ropensci/pathviewr/issues/ + url: https://docs.ropensci.org/pathviewr/ + url_cran: https://CRAN.R-project.org/package=pathviewr + url_git: https://github.com/ropensci/pathviewr/ +PathwaySpace: + version: 1.0.0 + title: Spatial Projection of Network Signals along Geodesic Paths + maintainer: Mauro Castro + description: For a given graph containing vertices, edges, and a signal associated + with the vertices, the 'PathwaySpace' package performs a convolution operation, + which involves a weighted combination of neighboring vertices and their associated + signals. The package then uses a decay function to project these signals, creating + geodesic paths on a 2D-image space. 'PathwaySpace' could have various applications, + such as visualizing and analyzing network data in a graphical format that highlights + the relationships and signal strengths between vertices. It can be particularly + useful for understanding the influence of signals through complex networks. By + combining graph theory, signal processing, and visualization, the 'PathwaySpace' + package provides a novel way of representing and analyzing graph data. + date_publication: '2024-11-12' + bug_reports: https://github.com/sysbiolab/PathwaySpace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PathwaySpace + url_git: https://github.com/sysbiolab/PathwaySpace +pathwayTMB: + version: 0.1.3 + title: Pathway Based Tumor Mutational Burden + maintainer: Junwei Han + description: A systematic bioinformatics tool to develop a new pathway-based gene + panel for tumor mutational burden (TMB) assessment (pathway-based tumor mutational + burden, PTMB), using somatic mutations files in an efficient manner from either + The Cancer Genome Atlas sources or any in-house studies as long as the data is + in mutation annotation file (MAF) format. Besides, we develop a multiple machine + learning method using the sample's PTMB profiles to identify cancer-specific dysfunction + pathways, which can be a biomarker of prognostic and predictive for cancer immunotherapy. + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pathwayTMB + url_git: '' +PatientLevelPrediction: + version: 6.4.0 + title: Develop Clinical Prediction Models Using the Common Data Model + maintainer: Egill Fridgeirsson + description: |- + A user friendly way to create patient level prediction models using + the Observational Medical Outcomes Partnership Common Data Model. Given a cohort + of interest and an outcome of interest, the package can use data in the Common + Data Model to build a large set of features. These features can then be used to + fit a predictive model with a number of machine learning algorithms. This is + further described in Reps (2017) . + date_publication: '2025-02-11' + bug_reports: https://github.com/OHDSI/PatientLevelPrediction/issues + url: https://ohdsi.github.io/PatientLevelPrediction/ + url_cran: https://CRAN.R-project.org/package=PatientLevelPrediction + url_git: https://github.com/OHDSI/PatientLevelPrediction +PatientProfiles: + version: 1.3.0 + title: |- + Identify Characteristics of Patients in the OMOP Common Data + Model + maintainer: Marti Catala + description: Identify the characteristics of patients in data mapped to the Observational + Medical Outcomes Partnership (OMOP) common data model. + date_publication: '2025-02-26' + bug_reports: https://github.com/darwin-eu/PatientProfiles/issues + url: https://darwin-eu.github.io/PatientProfiles/ + url_cran: https://CRAN.R-project.org/package=PatientProfiles + url_git: '' +patientProfilesVis: + version: 2.0.9 + title: Visualization of Patient Profiles + maintainer: Laure Cougnaud + description: |- + Creation of patient profile visualizations for + exploration, diagnostic or monitoring purposes during a clinical trial. + These static visualizations display a patient-specific overview + of the evolution during the trial time frame of + parameters of interest (as laboratory, ECG, vital signs), + presence of adverse events, exposure to a treatment; + associated with metadata patient information, + as demography, concomitant medication. + The visualizations can be tailored for specific domain(s) or endpoint(s) of interest. + Visualizations are exported into patient profile report(s) + or can be embedded in custom report(s). + date_publication: '2024-06-18' + bug_reports: https://github.com/openanalytics/patientProfilesVis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=patientProfilesVis + url_git: https://github.com/openanalytics/patientProfilesVis +patrick: + version: 0.3.0 + title: Parameterized Unit Testing + maintainer: Michael Quinn + description: |- + This is an extension of the 'testthat' package that + lets you add parameters to your unit tests. Parameterized unit tests + are often easier to read and more reliable, since they follow the DNRY + (do not repeat yourself) rule. + date_publication: '2025-01-27' + bug_reports: https://github.com/google/patrick/issues + url: '' + url_cran: https://CRAN.R-project.org/package=patrick + url_git: https://github.com/google/patrick +pattern.checks: + version: 0.1.0 + title: Identifies Patterned Responses in Scales + maintainer: JASEEL C K + description: Identifies the entries with patterned responses for psychometric scales. + The patterns included in the package are identical (a, a, a), ascending (a, b, + c), descending (c, b, a), alternative (a, b, a, b / a, b, c, a, b, c). + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pattern.checks + url_git: '' +patternator: + version: 0.1.0 + title: |- + Feature Extraction from Female Brown Anole Lizard Dorsal + Patterns + maintainer: Seong Hyun Hwang + description: Provides a set of functions to efficiently recognize and clean the + continuous dorsal pattern of a female brown anole lizard (Anolis sagrei) traced + from 'ImageJ', an open platform for scientific image analysis (see + for more information), and extract common features such as the pattern sinuosity + indices, coefficient of variation, and max-min width. + date_publication: '2017-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=patternator + url_git: https://github.com/stathwang/patternator +patterncausality: + version: 0.2.1 + title: Pattern Causality Algorithm + maintainer: Hui Wang + description: A comprehensive package for detecting and analyzing causal relationships + in complex systems using pattern-based approaches. Key features include state + space reconstruction, pattern identification, and causality strength evaluation. + date_publication: '2025-02-15' + bug_reports: https://github.com/skstavroglou/pattern_causality/issues + url: '' + url_cran: https://CRAN.R-project.org/package=patterncausality + url_git: https://github.com/skstavroglou/pattern_causality/ +patternize: + version: 0.0.5 + title: Quantification of Color Pattern Variation + maintainer: Steven Van Belleghem + description: |- + Quantification of variation in organismal color patterns as + obtained from image data. Patternize defines homology between pattern positions + across images either through fixed landmarks or image registration. Pattern + identification is performed by categorizing the distribution of colors using RGB + thresholds or image segmentation. + date_publication: '2023-08-22' + bug_reports: https://github.com/StevenVB12/patternize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=patternize + url_git: https://github.com/StevenVB12/patternize +patternplot: + version: 1.0.0 + title: |- + Versatile Pie Charts, Ring Charts, Bar Charts and Box Plots + using Patterns, Colors and Images + maintainer: Chunqiao Luo + description: Creates aesthetically pleasing and informative pie charts, ring charts, + bar charts and box plots with colors, patterns, and images. + date_publication: '2020-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=patternplot + url_git: '' +Patterns: + version: '1.5' + title: |- + Deciphering Biological Networks with Patterned Heterogeneous + Measurements + maintainer: Frederic Bertrand + description: A modeling tool dedicated to biological network modeling (Bertrand + and others 2020, ). It allows for single or + joint modeling of, for instance, genes and proteins. It starts with the selection + of the actors that will be the used in the reverse engineering upcoming step. + An actor can be included in that selection based on its differential measurement + (for instance gene expression or protein abundance) or on its time course profile. + Wrappers for actors clustering functions and cluster analysis are provided. It + also allows reverse engineering of biological networks taking into account the + observed time course patterns of the actors. Many inference functions are provided + and dedicated to get specific features for the inferred network such as sparsity, + robust links, high confidence links or stable through resampling links. Some simulation + and prediction tools are also available for cascade networks (Jung and others + 2014, ). Example of use with microarray or + RNA-Seq data are provided. + date_publication: '2024-05-06' + bug_reports: https://github.com/fbertran/Patterns/issues/ + url: https://fbertran.github.io/Patterns/ + url_cran: https://CRAN.R-project.org/package=Patterns + url_git: https://github.com/fbertran/Patterns/ +pavo: + version: 2.9.0 + title: |- + Perceptual Analysis, Visualization and Organization of Spectral + Colour Data + maintainer: Thomas White + description: |- + A cohesive framework for the spectral and spatial analysis of + colour described in Maia, Eliason, Bitton, Doucet & Shawkey (2013) + and Maia, Gruson, Endler & White (2019) + . + date_publication: '2023-09-24' + bug_reports: https://github.com/rmaia/pavo/issues + url: http://pavo.colrverse.com + url_cran: https://CRAN.R-project.org/package=pavo + url_git: https://github.com/rmaia/pavo/ +pawacc: + version: 1.2.3 + title: Physical Activity with Accelerometers + maintainer: Marco Geraci + description: Functions to process, format and store ActiGraph GT1M and GT3X accelerometer + data. + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pawacc + url_git: '' +paws: + version: 0.8.0 + title: Amazon Web Services Software Development Kit + maintainer: Dyfan Jones + description: |- + Interface to Amazon Web Services , + including storage, database, and compute services, such as 'Simple + Storage Service' ('S3'), 'DynamoDB' 'NoSQL' database, and 'Lambda' + functions-as-a-service. + date_publication: '2025-02-10' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws + url_cran: https://CRAN.R-project.org/package=paws + url_git: https://github.com/paws-r/paws +paws.analytics: + version: 0.8.0 + title: '''Amazon Web Services'' Analytics Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' 'analytics' services, + including 'Elastic MapReduce' 'Hadoop' and 'Spark' big data service, + 'Elasticsearch' search engine, and more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.analytics + url_cran: https://CRAN.R-project.org/package=paws.analytics + url_git: https://github.com/paws-r/paws +paws.application.integration: + version: 0.8.0 + title: '''Amazon Web Services'' Application Integration Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' application integration + services, including 'Simple Queue Service' ('SQS') message queue, + 'Simple Notification Service' ('SNS') publish/subscribe messaging, and + more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.application.integration + url_cran: https://CRAN.R-project.org/package=paws.application.integration + url_git: https://github.com/paws-r/paws +paws.common: + version: 0.8.1 + title: Paws Low-Level Amazon Web Services API + maintainer: Dyfan Jones + description: |- + Functions for making low-level API requests to Amazon Web Services + . The functions handle building, signing, and + sending requests, and receiving responses. They are designed to help build + higher-level interfaces to individual services, such as Simple Storage + Service (S3). + date_publication: '2025-02-09' + bug_reports: https://github.com/paws-r/paws/issues + url: '' + url_cran: https://CRAN.R-project.org/package=paws.common + url_git: https://github.com/paws-r/paws +paws.compute: + version: 0.8.0 + title: '''Amazon Web Services'' Compute Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' compute services, + including 'Elastic Compute Cloud' ('EC2'), 'Lambda' + functions-as-a-service, containers, batch processing, and more + . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.compute + url_cran: https://CRAN.R-project.org/package=paws.compute + url_git: https://github.com/paws-r/paws +paws.cost.management: + version: 0.8.0 + title: '''Amazon Web Services'' Cost Management Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' cost management services, + including cost and usage reports, budgets, pricing, and more + . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.cost.management + url_cran: https://CRAN.R-project.org/package=paws.cost.management + url_git: https://github.com/paws-r/paws +paws.customer.engagement: + version: 0.8.0 + title: '''Amazon Web Services'' Customer Engagement Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' customer engagement + services, including 'Simple Email Service', 'Connect' contact center + service, and more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.customer.engagement + url_cran: https://CRAN.R-project.org/package=paws.customer.engagement + url_git: https://github.com/paws-r/paws +paws.database: + version: 0.8.0 + title: '''Amazon Web Services'' Database Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' database services, + including 'Relational Database Service' ('RDS'), 'DynamoDB' 'NoSQL' + database, and more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.database + url_cran: https://CRAN.R-project.org/package=paws.database + url_git: https://github.com/paws-r/paws +paws.developer.tools: + version: 0.8.0 + title: '''Amazon Web Services'' Developer Tools Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' developer tools services, + including version control, continuous integration and deployment, and + more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.developer.tools + url_cran: https://CRAN.R-project.org/package=paws.developer.tools + url_git: https://github.com/paws-r/paws +paws.end.user.computing: + version: 0.8.0 + title: '''Amazon Web Services'' End User Computing Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' end user computing + services, including collaborative document editing, mobile intranet, + and more . + date_publication: '2025-02-10' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.end.user.computing + url_cran: https://CRAN.R-project.org/package=paws.end.user.computing + url_git: https://github.com/paws-r/paws +paws.machine.learning: + version: 0.8.0 + title: '''Amazon Web Services'' Machine Learning Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' machine learning services, + including 'SageMaker' managed machine learning service, natural + language processing, speech recognition, translation, and more + . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.machine.learning + url_cran: https://CRAN.R-project.org/package=paws.machine.learning + url_git: https://github.com/paws-r/paws +paws.management: + version: 0.8.0 + title: '''Amazon Web Services'' Management & Governance Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' management and governance + services, including 'CloudWatch' application and infrastructure + monitoring, 'Auto Scaling' for automatically scaling resources, and + more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.management + url_cran: https://CRAN.R-project.org/package=paws.management + url_git: https://github.com/paws-r/paws +paws.networking: + version: 0.8.0 + title: '''Amazon Web Services'' Networking & Content Delivery Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' networking and content + delivery services, including 'Route 53' Domain Name System service, + 'CloudFront' content delivery, load balancing, and more + . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.networking + url_cran: https://CRAN.R-project.org/package=paws.networking + url_git: https://github.com/paws-r/paws +paws.security.identity: + version: 0.8.0 + title: '''Amazon Web Services'' Security, Identity, & Compliance Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' security, identity, and + compliance services, including the 'Identity & Access Management' + ('IAM') service for managing access to services and resources, and + more . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.security.identity + url_cran: https://CRAN.R-project.org/package=paws.security.identity + url_git: https://github.com/paws-r/paws +paws.storage: + version: 0.8.0 + title: '''Amazon Web Services'' Storage Services' + maintainer: Dyfan Jones + description: |- + Interface to 'Amazon Web Services' storage services, + including 'Simple Storage Service' ('S3') and more + . + date_publication: '2025-02-08' + bug_reports: https://github.com/paws-r/paws/issues + url: https://paws-r.r-universe.dev/paws.storage + url_cran: https://CRAN.R-project.org/package=paws.storage + url_git: https://github.com/paws-r/paws +pawscore: + version: 1.0.3 + title: Pain Assessment at Withdrawal Speeds (PAWS) + maintainer: Colin Twomey + description: |- + Automated pain scoring from paw withdrawal tracking data. Based on + Jones et al. (2020) "A machine-vision approach for automated pain + measurement at millisecond timescales" . + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pawscore + url_git: '' +pbANOVA: + version: 0.1.0 + title: Parametric Bootstrap for ANOVA Models + maintainer: Sarah Alver + description: |- + Parametric bootstrap (PB) has been used for + three-way ANOVA model with unequal group variances. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pbANOVA + url_git: '' +pbapply: + version: 1.7-2 + title: Adding Progress Bar to '*apply' Functions + maintainer: Peter Solymos + description: |- + A lightweight package that adds + progress bar to vectorized R functions + ('*apply'). The implementation can easily be added + to functions where showing the progress is + useful (e.g. bootstrap). The type and style of the + progress bar (with percentages or remaining time) + can be set through options. + Supports several parallel processing backends including future. + date_publication: '2023-06-27' + bug_reports: https://github.com/psolymos/pbapply/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pbapply + url_git: https://github.com/psolymos/pbapply +pbatR: + version: 2.2-17 + title: |- + Pedigree/Family-Based Genetic Association Tests Analysis and + Power + maintainer: Thomas Hoffmann + description: This R package provides power calculations via internal simulation + methods. The package also provides a frontend to the now abandoned PBAT program + (developed by Christoph Lange), and reads in the corresponding output and displays + results and figures when appropriate. The license of this R package itself is + GPL. However, to have the program interact with the PBAT program for some functionality + of the R package, users must additionally obtain the PBAT program from Christoph + Lange, and accept his license. Both the data analysis and power calculations have + command line and graphical interfaces using tcltk. + date_publication: '2024-01-29' + bug_reports: '' + url: https://academic.oup.com/bioinformatics/article-abstract/22/24/3103/208723 + url_cran: https://CRAN.R-project.org/package=pbatR + url_git: '' +pbbd: + version: 1.0.0 + title: Position Balanced and Nearly Position Balanced Block Designs + maintainer: B N Mandal + description: Generates a position balanced or nearly position balanced block design + with given parameters. This package can also convert a given proper and equireplicate + block design into a position balanced or nearly position balanced block design. + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pbbd + url_git: '' +pbcc: + version: 0.0.7 + title: Percentile-Based Control Chart + maintainer: Zsolt T. Kosztyan + description: Design and implementation of Percentile-based Shewhart Control Charts + for continuous data. Faraz (2019) . + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pbcc + url_git: https://github.com/kzst/pbcc +PBD: + version: '1.4' + title: Protracted Birth-Death Model of Diversification + maintainer: Rampal S. Etienne + description: |- + Conducts maximum likelihood analysis and simulation of the + protracted birth-death model of diversification. See + Etienne, R.S. & J. Rosindell 2012 ; + Lambert, A., H. Morlon & R.S. Etienne 2014, ; + Etienne, R.S., H. Morlon & A. Lambert 2014, . + date_publication: '2017-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBD + url_git: '' +pbdMPI: + version: 0.5-2 + title: |- + R Interface to MPI for HPC Clusters (Programming with Big Data + Project) + maintainer: Wei-Chen Chen + description: |- + A simplified, efficient, interface to MPI for HPC clusters. It is + a derivation and rethinking of the Rmpi package. pbdMPI embraces the + prevalent parallel programming style on HPC clusters. Beyond the + interface, a collection of functions for global work with + distributed data and resource-independent RNG reproducibility is + included. It is based on S4 classes and methods. + date_publication: '2024-09-18' + bug_reports: https://github.com/snoweye/pbdMPI/issues + url: https://pbdr.org/ + url_cran: https://CRAN.R-project.org/package=pbdMPI + url_git: '' +pbdSLAP: + version: 0.3-7 + title: Programming with Big Data -- Scalable Linear Algebra Packages + maintainer: Wei-Chen Chen + description: |- + Utilizing scalable linear algebra packages mainly + including 'BLACS', 'PBLAS', and 'ScaLAPACK' in double precision via + 'pbdMPI' based on 'ScaLAPACK' version 2.0.2. + date_publication: '2024-11-13' + bug_reports: https://github.com/snoweye/pbdSLAP/issues + url: https://pbdr.org/ + url_cran: https://CRAN.R-project.org/package=pbdSLAP + url_git: '' +pbdZMQ: + version: 0.3-13 + title: Programming with Big Data -- Interface to 'ZeroMQ' + maintainer: Wei-Chen Chen + description: |- + 'ZeroMQ' is a well-known library for high-performance + asynchronous messaging in scalable, distributed applications. This + package provides high level R wrapper functions to easily utilize + 'ZeroMQ'. We mainly focus on interactive client/server programming + frameworks. For convenience, a minimal 'ZeroMQ' library (4.2.2) + is shipped with 'pbdZMQ', which can be used if no system installation + of 'ZeroMQ' is available. A few wrapper functions compatible with + 'rzmq' are also provided. + date_publication: '2024-09-17' + bug_reports: https://github.com/snoweye/pbdZMQ/issues + url: https://pbdr.org/ + url_cran: https://CRAN.R-project.org/package=pbdZMQ + url_git: '' +PBIBD: + version: '1.3' + title: Partially Balanced Incomplete Block Designs + maintainer: Kush Sharma + description: The PBIB designs are important type of incomplete block designs having + wide area of their applications for example in agricultural experiments, in plant + breeding, in sample surveys etc. This package constructs various series of PBIB + designs and assists in checking all the necessary conditions of PBIB designs and + the association scheme on which these designs are based on. It also assists in + calculating the efficiencies of PBIB designs with any number of associate classes. + The package also constructs Youden-m square designs which are Row-Column designs + for the two-way elimination of heterogeneity. The incomplete columns of these + Youden-m square designs constitute PBIB designs. With the present functionality, + the package will be of immense importance for the researchers as it will help + them to construct PBIB designs, to check if their PBIB designs and association + scheme satisfy various necessary conditions for the existence, to calculate the + efficiencies of PBIB designs based on any association scheme and to construct + Youden-m square designs for the two-way elimination of heterogeneity. R. C. Bose + and K. R. Nair (1939) . + date_publication: '2017-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBIBD + url_git: '' +PBImisc: + version: '1.0' + title: |- + A Set of Datasets Used in My Classes or in the Book 'Modele + Liniowe i Mieszane w R, Wraz z Przykladami w Analizie Danych' + maintainer: Przemyslaw Biecek + description: |- + A set of datasets and functions used in the book + 'Modele liniowe i mieszane w R, wraz z przykladami w analizie danych'. + Datasets either come from real studies or are created to be as similar + as possible to real studies. + date_publication: '2016-02-25' + bug_reports: '' + url: http://www.biecek.pl/R/ + url_cran: https://CRAN.R-project.org/package=PBImisc + url_git: '' +PBIR: + version: 0.1-0 + title: |- + Estimating the Probability of Being in Response and Related + Outcomes + maintainer: Lu Tian + description: |- + Make statistical inference on the probability of being in response, + the duration of response, and the cumulative response rate up to a given time point. + The method can be applied to analyze phase II randomized clinical trials with the endpoints + being time to treatment response and time to progression or death. + date_publication: '2020-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBIR + url_git: '' +pbivnorm: + version: 0.6.0 + title: Vectorized Bivariate Normal CDF + maintainer: Brenton Kenkel + description: Provides a vectorized R function for calculatingprobabilities + from a standard bivariate normal CDF. + date_publication: '2015-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pbivnorm + url_git: https://github.com/brentonk/pbivnorm +pbkrtest: + version: 0.5.3 + title: |- + Parametric Bootstrap, Kenward-Roger and Satterthwaite Based + Methods for Test in Mixed Models + maintainer: Søren Højsgaard + description: |- + Computes p-values based on (a) Satterthwaite or + Kenward-Rogers degree of freedom methods and (b) parametric bootstrap + for mixed effects models as implemented in the 'lme4' + package. Implements parametric bootstrap test for generalized linear + mixed models as implemented in 'lme4' and generalized linear + models. The package is documented in the paper by Halekoh and + Højsgaard, (2012, ). Please see + 'citation("pbkrtest")' for citation details. + date_publication: '2024-06-26' + bug_reports: '' + url: https://people.math.aau.dk/~sorenh/software/pbkrtest/ + url_cran: https://CRAN.R-project.org/package=pbkrtest + url_git: '' +pbm: + version: 1.2.1 + title: Protein Binding Models + maintainer: Jonathan Davies + description: Binding models which are useful when analysing protein-ligand interactions + by techniques such as Biolayer Interferometry (BLI) or Surface Plasmon Resonance + (SPR). Naman B. Shah, Thomas M. Duncan (2014) . Hoang H. Nguyen + et al. (2015) . After initial binding parameters are known, + binding curves can be simulated and parameters can be varied. The models within + this package may also be used to fit a curve to measured binding data using non-linear + regression. + date_publication: '2021-03-28' + bug_reports: https://github.com/jonathanrd/pbm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pbm + url_git: https://github.com/jonathanrd/pbm +pbmcapply: + version: 1.5.1 + title: Tracking the Progress of Mc*pply with Progress Bar + maintainer: Kevin kuang + description: |- + A light-weight package helps you track and visualize + the progress of parallel version of vectorized R functions (mc*apply). + Parallelization (mc.core > 1) works only on *nix (Linux, Unix such as macOS) system due to + the lack of fork() functionality, which is essential for mc*apply, on Windows. + date_publication: '2022-04-28' + bug_reports: https://github.com/kvnkuang/pbmcapply/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pbmcapply + url_git: https://github.com/kvnkuang/pbmcapply +PBNPA: + version: 0.0.3 + title: Permutation Based Non-Parametric Analysis of CRISPR Screen Data + maintainer: Gaoxiang Jia + description: |- + Permutation based + non-parametric analysis of CRISPR screen data. Details about this algorithm are published in the following paper published on BMC genomics, Jia et al. (2017) : A permutation-based non-parametric analysis of CRISPR screen data. Please cite this paper if you use this algorithm for your paper. + date_publication: '2018-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBNPA + url_git: '' +pbo: + version: 1.3.5 + title: Probability of Backtest Overfitting + maintainer: Matt Barry + description: |- + Following the method of Bailey et al., computes for a collection + of candidate models the probability of backtest overfitting, the + performance degradation and probability of loss, and the stochastic + dominance. + date_publication: '2022-05-26' + bug_reports: https://github.com/mrbcuda/pbo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pbo + url_git: https://github.com/mrbcuda/pbo +pbox: + version: 0.1.8 + title: Exploring Multivariate Spaces with Probability Boxes + maintainer: Ahmed T. Hammad + description: |- + Advanced statistical library offering a method to encapsulate and query the probability space of a + dataset effortlessly using Probability Boxes (p-boxes). Its distinctive feature lies in the ease with + which users can navigate and analyze marginal, joint, and conditional probabilities while taking into account + the underlying correlation structure inherent in the data using copula theory and models. A comprehensive explanation is available in the paper + "pbox: Exploring Multivariate Spaces with Probability Boxes" to be published in the Journal of Statistical Software. + date_publication: '2024-05-27' + bug_reports: https://github.com/athammad/pbox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pbox + url_git: https://github.com/athammad/pbox +pbr: + version: 0.0.2 + title: Find a Cold One Near You + maintainer: Paul Frater + description: |- + In short, this package is a locator for cool, refreshing beverages. + It will find and return the nearest location where you can get a cold one. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pbr + url_git: '' +pBrackets: + version: 1.0.1 + title: Plot Brackets + maintainer: Andreas Schulz + description: Adds different kinds of brackets to a plot, including braces, chevrons, + parentheses or square brackets. + date_publication: '2021-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pBrackets + url_git: '' +pbs: + version: '1.1' + title: Periodic B Splines + maintainer: swang1 + description: Periodic B Splines Basis + date_publication: '2013-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pbs + url_git: '' +PBSadmb: + version: 1.1.6 + title: ADMB for R Using Scripts or GUI + maintainer: Rowan Haigh + description: |- + A collection of software provides R support for 'ADMB' + (Automatic Differentiation Model Builder) and a 'GUI' + interface facilitates the conversion of 'ADMB' template + code to 'C code' followed by compilation to a binary executable. + Stand-alone functions can also be run by users + not interested in clicking a 'GUI'. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBSadmb + url_git: https://github.com/pbs-software/pbs-admb +PBSddesolve: + version: 1.13.4 + title: Solver for Delay Differential Equations + maintainer: Rowan Haigh + description: |- + Functions for solving systems of delay differential equations by + interfacing with numerical routines written by Simon N. Wood, including + contributions from Benjamin J. Cairns. These numerical routines first + appeared in Simon Wood's 'solv95' program. This package includes a vignette + and a complete user's guide. 'PBSddesolve' originally appeared on CRAN under + the name 'ddesolve'. That version is no longer supported. The current name + emphasizes a close association with other 'PBS' packages, particularly + 'PBSmodelling'. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBSddesolve + url_git: https://github.com/pbs-software/pbs-ddesolve +PBSmapping: + version: 2.74.1 + title: Mapping Fisheries Data and Spatial Analysis Tools + maintainer: Rowan Haigh + description: |- + This software has evolved from fisheries research conducted at the + Pacific Biological Station (PBS) in 'Nanaimo', British Columbia, Canada. It + extends the R language to include two-dimensional plotting features similar + to those commonly available in a Geographic Information System (GIS). + Embedded C code speeds algorithms from computational geometry, such as + finding polygons that contain specified point events or converting between + longitude-latitude and Universal Transverse Mercator (UTM) coordinates. + Additionally, we include 'C++' code developed by Angus Johnson for the + 'Clipper' library, data for a global shoreline, and other data sets in the + public domain. Under the user's R library directory '.libPaths()', + specifically in './PBSmapping/doc', a complete user's guide is offered and + should be consulted to use package functions effectively. + date_publication: '2024-09-25' + bug_reports: '' + url: https://www.angusj.com/clipper2/Docs/Overview.htm + url_cran: https://CRAN.R-project.org/package=PBSmapping + url_git: https://github.com/pbs-software/pbs-mapping +PBSmodelling: + version: 2.69.3 + title: 'GUI Tools Made Easy: Interact with Models and Explore Data' + maintainer: Rowan Haigh + description: |- + Provides software to facilitate the design, testing, and operation + of computer models. It focuses particularly on tools that make it easy to + construct and edit a customized graphical user interface ('GUI'). Although our + simplified 'GUI' language depends heavily on the R interface to the 'Tcl/Tk' + package, a user does not need to know 'Tcl/Tk'. Examples illustrate models + built with other R packages, including 'PBSmapping', 'PBSddesolve', and 'BRugs'. + A complete user's guide 'PBSmodelling-UG.pdf' shows how to use this package + effectively. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBSmodelling + url_git: https://github.com/pbs-software/pbs-modelling +PBtDesigns: + version: 1.0.0 + title: Partially Balanced t-Designs (PBtDesigns) + maintainer: Ashutosh Dalal + description: The t-designs represent a generalized class of balanced incomplete + block designs in which the number of blocks in which any t-tuple of treatments + (t >= 2) occur together is a constant. When the focus of an experiment lies in + grading and selecting treatment subgroups, t-designs would be preferred over the + conventional ones, as they have the additional advantage of t-tuple balance. t-designs + can be advantageously used in identifying the best crop-livestock combination + for a particular location in Integrated Farming Systems that will help in generating + maximum profit. But as the number of components increases, the number of possible + t-component combinations will also increase. Most often, combinations derived + from specific components are only practically feasible, for example, in a specific + locality, farmers may not be interested in keeping a pig or goat and hence combinations + involving these may not be of any use in that locality. In such situations partially + balanced t-designs with few selected combinations appearing in a constant number + of blocks (while others not at all appearing) may be useful (Sayantani Karmakar, + Cini Varghese, Seema Jaggi & Mohd Harun (2021)). + Further, every location may not have the resources to form equally sized homogeneous + blocks. Partially balanced t-designs with unequal block sizes (Damaraju Raghavarao + & Bei Zhou (1998). Sayantani Karmakar, Cini Varghese, + Seema Jaggi & Mohd Harun (2022)." Partially Balanced t-designs with unequal block + sizes") prove to be more suitable for such situations.This package generates three + series of partially balanced t-designs namely Series 1, Series 2 and Series 3. + Series 1 and Series 2 are designs having equal block sizes and with treatment + structures 4(t + 1) and a prime number, respectively. Series 3 consists of designs + with unequal block sizes and with treatment structure n(n-1)/2. This package is + based on the function named PBtD() for generating partially balanced t-designs + along with their parameters, information matrices, average variance factors and + canonical efficiency factors. + date_publication: '2023-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PBtDesigns + url_git: '' +pbv: + version: 0.5-47 + title: Probabilities for Bivariate Normal Distribution + maintainer: Alexander Robitzsch + description: |2- + + Computes probabilities of the bivariate normal distribution + in a vectorized R function (Drezner & Wesolowsky, 1990, + ). + date_publication: '2023-11-30' + bug_reports: '' + url: https://sites.google.com/view/alexander-robitzsch/software + url_cran: https://CRAN.R-project.org/package=pbv + url_git: https://github.com/alexanderrobitzsch/pbv +pcadapt: + version: 4.4.0 + title: Fast Principal Component Analysis for Outlier Detection + maintainer: Florian Privé + description: |- + Methods to detect genetic markers involved in biological + adaptation. 'pcadapt' provides statistical tools for outlier detection based on + Principal Component Analysis. Implements the method described in (Luu, 2016) + and later revised in (Privé, 2020) + . + date_publication: '2024-09-24' + bug_reports: https://github.com/bcm-uga/pcadapt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcadapt + url_git: https://github.com/bcm-uga/pcadapt +PCADSC: + version: 0.8.0 + title: |- + Tools for Principal Component Analysis-Based Data Structure + Comparisons + maintainer: Anne H. Petersen + description: |- + A suite of non-parametric, visual tools for assessing differences in data structures + for two datasets that contain different observations of the same variables. These tools are all + based on Principal Component Analysis (PCA) and thus effectively address differences in the structures + of the covariance matrices of the two datasets. The PCASDC tools consist of easy-to-use, + intuitive plots that each focus on different aspects of the PCA decompositions. The cumulative eigenvalue + (CE) plot describes differences in the variance components (eigenvalues) of the deconstructed covariance matrices. The + angle plot presents the information loss when moving from the PCA decomposition of one dataset to the + PCA decomposition of the other. The chroma plot describes the loading patterns of the two datasets, thereby + presenting the relative weighting and importance of the variables from the original dataset. + date_publication: '2017-04-19' + bug_reports: https://github.com/annepetersen1/PCADSC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PCADSC + url_git: https://github.com/annepetersen1/PCADSC +pcal: + version: 1.0.0 + title: Calibration of P-Values for Point Null Hypothesis Testing + maintainer: Pedro Fonseca + description: |- + Calibrate p-values under a robust perspective using the methods developed + by Sellke, Bayarri, and Berger (2001) and obtain + measures of the evidence provided by the data in favor of point null hypotheses + which are safer and more straightforward to interpret. + date_publication: '2020-07-06' + bug_reports: https://github.com/pedro-teles-fonseca/pcal/issues + url: https://pedro-teles-fonseca.github.io/pcal/ + url_cran: https://CRAN.R-project.org/package=pcal + url_git: https://github.com/pedro-teles-fonseca/pcal +pcaL1: + version: 1.5.7 + title: L1-Norm PCA Methods + maintainer: Paul Brooks + description: |- + Implementations of several methods for principal component analysis + using the L1 norm. The package depends on COIN-OR Clp version >= + 1.17.4. The methods implemented are + PCA-L1 (Kwak 2008) , + L1-PCA (Ke and Kanade 2003, 2005) , + L1-PCA* (Brooks, Dula, and Boone 2013) , + L1-PCAhp (Visentin, Prestwich and Armagan 2016) + , + wPCA (Park and Klabjan 2016) , + awPCA (Park and Klabjan 2016) , + PCA-Lp (Kwak 2014) , and + SharpEl1-PCA (Brooks and Dula, submitted). + date_publication: '2023-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcaL1 + url_git: '' +pcalg: + version: 2.7-12 + title: Methods for Graphical Models and Causal Inference + maintainer: Markus Kalisch + description: |- + Functions for causal structure + learning and causal inference using graphical models. The main algorithms + for causal structure learning are PC (for observational data without hidden + variables), FCI and RFCI (for observational data with hidden variables), + and GIES (for a mix of data from observational studies + (i.e. observational data) and data from experiments + involving interventions (i.e. interventional data) without hidden + variables). For causal inference the IDA algorithm, the Generalized + Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) + and some related functions are implemented. Functions for incorporating + background knowledge are provided. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcalg + url_git: https://pcalg.r-forge.r-project.org/ +pCalibrate: + version: 0.2-1 + title: Bayesian Calibrations of p-Values + maintainer: Manuela Ott + description: Implements transformations of p-values to the smallest possible Bayes + factor within the specified class of alternative hypotheses, as described in Held + & Ott (2018, ). Covers several common + testing scenarios such as z-tests, t-tests, likelihood ratio tests and the F-test. + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pCalibrate + url_git: '' +pcalls: + version: '1.0' + title: Pricing of Different Types of Call + maintainer: Elia Degiorgi + description: Compute the price of different types of call using different methods. + The types available are Vanilla European Calls, Vanilla American Calls and American + Digital Calls. Available methods are Montecarlo Simulation, Montecarlo Simulation + with Antithetic Variates, Black-Scholes and the Binary Tree. + date_publication: '2020-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcalls + url_git: '' +PCAmatchR: + version: 0.3.3 + title: Match Cases to Controls Based on Genotype Principal Components + maintainer: Derek W. Brown + description: |- + Matches cases to controls based on genotype principal components (PC). + In order to produce better results, matches are based on the weighted + distance of PCs where the weights are equal to the % variance explained + by that PC. A weighted Mahalanobis distance metric (Kidd et al. (1987) + ) is used to determine matches. + date_publication: '2022-12-01' + bug_reports: https://github.com/machiela-lab/PCAmatchR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PCAmatchR + url_git: https://github.com/machiela-lab/PCAmatchR +PCAmixdata: + version: '3.1' + title: Multivariate Analysis of Mixed Data + maintainer: Marie Chavent + description: |- + Implements principal component analysis, orthogonal rotation and multiple + factor analysis for a mixture of quantitative and qualitative variables. + date_publication: '2017-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCAmixdata + url_git: '' +pcaone: + version: 1.1.0 + title: |- + Fast and Accurate Randomized Singular Value Decomposition + Algorithms with 'PCAone' + maintainer: Zilong Li + description: Fast and Accurate Randomized Singular Value Decomposition (RSVD) methods + proposed in the 'PCAone' paper by Li (2023) . + date_publication: '2024-09-25' + bug_reports: https://github.com/Zilong-Li/PCAoneR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcaone + url_git: https://github.com/Zilong-Li/PCAoneR +PCAPAM50: + version: 1.0.3 + title: Enhanced 'PAM50' Subtyping of Breast Cancer + maintainer: Praveen-Kumar Raj-Kumar + description: Accurate classification of breast cancer tumors based on gene expression + data is not a trivial task, and it lacks standard practices.The 'PAM50' classifier, + which uses 50 gene centroid correlation distances to classify tumors, faces challenges + with balancing estrogen receptor (ER) status and gene centering. The 'PCAPAM50' + package leverages principal component analysis and iterative 'PAM50' calls to + create a gene expression-based ER-balanced subset for gene centering, avoiding + the use of protein expression-based ER data resulting into an enhanced Breast + Cancer subtyping. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCAPAM50 + url_git: '' +pcaPP: + version: 2.0-5 + title: Robust PCA by Projection Pursuit + maintainer: Valentin Todorov + description: |- + Provides functions for robust PCA by projection pursuit. + The methods are described in Croux et al. (2006) , + Croux et al. (2013) , + Todorov and Filzmoser (2013) . + date_publication: '2024-08-19' + bug_reports: https://github.com/valentint/pcaPP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcaPP + url_git: https://github.com/valentint/pcaPP +pcatsAPIclientR: + version: 1.1.0 + title: '''PCATS'' API Client' + maintainer: Michal Kouril + description: |- + Provides an R interface to the 'PCATS' API + , + allowing R users to submit tasks and retrieve results. + date_publication: '2023-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcatsAPIclientR + url_git: '' +PCBS: + version: 0.1.1 + title: Principal Component BiSulfite + maintainer: Kathryn Lande + description: 'A system for fast, accurate, and flexible whole genome bisulfite sequencing + (WGBS) data analysis of two-condition comparisons. Principal Component BiSulfite, + ''PCBS'', assigns methylated loci eigenvector values from the treatment-delineating + principal component in lieu of running millions of pairwise statistical tests, + which dramatically increases analysis flexibility and reduces computational requirements. + Methods: .' + date_publication: '2024-08-27' + bug_reports: https://github.com/katlande/PCBS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PCBS + url_git: https://github.com/katlande/PCBS +pccc: + version: 1.0.5 + title: Pediatric Complex Chronic Conditions + maintainer: Seth Russell + description: |- + An implementation of the pediatric complex chronic conditions (CCC) + classification system using R and C++. + date_publication: '2020-06-02' + bug_reports: https://github.com/CUD2V/pccc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pccc + url_git: https://github.com/CUD2V/pccc +PCDimension: + version: 1.1.13 + title: Finding the Number of Significant Principal Components + maintainer: Kevin R. Coombes + description: |- + Implements methods to automate the Auer-Gervini graphical + Bayesian approach for determining the number of significant + principal components. Automation uses clustering, change points, or + simple statistical models to distinguish "long" from "short" steps + in a graph showing the posterior number of components as a function + of a prior parameter. See . + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCDimension + url_git: http://oompa.r-forge.r-project.org/ +pcdpca: + version: '0.4' + title: |- + Dynamic Principal Components for Periodically Correlated + Functional Time Series + maintainer: Lukasz Kidzinski + description: |- + Method extends multivariate and functional dynamic principal components + to periodically correlated multivariate time series. This package allows you to + compute true dynamic principal components in the presence of periodicity. + We follow implementation guidelines as described in Kidzinski, Kokoszka and + Jouzdani (2017), in Principal component analysis of periodically correlated + functional time series . + date_publication: '2017-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcdpca + url_git: '' +pcds: + version: 0.1.8 + title: Proximity Catch Digraphs and Their Applications + maintainer: Elvan Ceyhan + description: |- + Contains the functions for construction and visualization of various families + of the proximity catch digraphs (PCDs), see (Ceyhan (2005) ISBN:978-3-639-19063-2), + for computing the graph invariants for testing the patterns of segregation and association against complete spatial randomness (CSR) + or uniformity in one, two and three dimensional cases. + The package also has tools for generating points from these spatial patterns. + The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) + ) and arc density (Ceyhan et al. (2006) ; + Ceyhan et al. (2007) ). The PCD families considered are Arc-Slice PCDs, + Proportional-Edge PCDs, and Central Similarity PCDs. + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcds + url_git: '' +pcds.ugraph: + version: 0.1.1 + title: |- + Underlying Graphs of Proximity Catch Digraphs and Their + Applications + maintainer: Elvan Ceyhan + description: |- + Contains the functions for construction and visualization of underlying and reflexivity graphs of + the three families of the proximity catch digraphs (PCDs), see (Ceyhan (2005) ISBN:978-3-639-19063-2), + and for computing the edge density of these PCD-based graphs which are then + used for testing the patterns of segregation and association against complete spatial randomness (CSR)) + or uniformity in one and two dimensional cases. + The PCD families considered are Arc-Slice PCDs, Proportional-Edge (PE) PCDs (Ceyhan et al. (2006) ) + and Central Similarity PCDs (Ceyhan et al. (2007) ). + See also (Ceyhan (2016) ) for edge density of the underlying and + reflexivity graphs of PE-PCDs. + The package also has tools for visualization of PCD-based graphs for one, two, and three dimensional data. + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcds.ugraph + url_git: '' +pcensmix: + version: 1.2-1 + title: Model Fitting to Progressively Censored Mixture Data + maintainer: Lida Fallah + description: |- + Functions for generating progressively Type-II censored data in + a mixture structure and fitting models using a constrained EM algorithm. It can also + create a progressive Type-II censored version of a given real dataset to be considered for + model fitting. + date_publication: '2017-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcensmix + url_git: '' +pcev: + version: 2.2.2 + title: Principal Component of Explained Variance + maintainer: Maxime Turgeon + description: |- + Principal component of explained variance (PCEV) is a statistical + tool for the analysis of a multivariate response vector. It is a dimension- + reduction technique, similar to Principal component analysis (PCA), that seeks + to maximize the proportion of variance (in the response vector) being explained + by a set of covariates. + date_publication: '2018-02-03' + bug_reports: http://github.com/GreenwoodLab/pcev/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcev + url_git: http://github.com/GreenwoodLab/pcev +pcFactorStan: + version: 1.5.4 + title: Stan Models for the Paired Comparison Factor Model + maintainer: Joshua N. Pritikin + description: |- + Provides convenience functions and pre-programmed + Stan models related to the paired comparison factor model. Its purpose + is to make fitting paired comparison data using Stan easy. This + package is described in Pritikin (2020) . + date_publication: '2023-09-13' + bug_reports: https://github.com/jpritikin/pcFactorStan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcFactorStan + url_git: https://github.com/jpritikin/pcFactorStan +PCFAM: + version: '1.0' + title: |- + Computation of Ancestry Scores with Mixed Families and Unrelated + Individuals + maintainer: Yi-Hui Zhou + description: We provide several algorithms to compute the genotype ancestry scores + (such as eigenvector projections) in the case where highly correlated individuals + are involved. + date_publication: '2017-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCFAM + url_git: '' +pcg: + version: '1.1' + title: Preconditioned Conjugate Gradient Algorithm for solving Ax=b + maintainer: B N Mandal + description: The package solves linear system of equations Ax=b by using Preconditioned + Conjugate Gradient Algorithm where A is real symmetric positive definite matrix. + A suitable preconditioner matrix may be provided by user. This can also be used + to minimize quadratic function (x'Ax)/2-bx for unknown x. + date_publication: '2014-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcg + url_git: '' +pcgen: + version: 0.2.0 + title: |- + Reconstruction of Causal Networks for Data with Random Genetic + Effects + maintainer: Pariya Behrouzi + description: |- + Implements the pcgen algorithm, which is a modified version of the standard pc-algorithm, + with specific conditional independence tests and modified orientation rules. pcgen extends + the approach of Valente et al. (2010) with reconstruction of + direct genetic effects. + date_publication: '2019-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcgen + url_git: '' +PCGII: + version: 1.1.2 + title: Partial Correlation Graph with Information Incorporation + maintainer: Hao Wang + description: Large-scale gene expression studies allow gene network construction + to uncover associations among genes. This package is developed for estimating + and testing partial correlation graphs with prior information incorporated. + date_publication: '2024-02-02' + bug_reports: '' + url: https://haowang47.github.io/PCGII/ + url_cran: https://CRAN.R-project.org/package=PCGII + url_git: '' +PCGSE: + version: 0.5.0 + title: Principal Component Gene Set Enrichment + maintainer: H. Robert Frost + description: Contains logic for computing the statistical association of variable + groups, i.e., gene sets, with respect to the principal components of genomic data. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCGSE + url_git: '' +pch: + version: '2.1' + title: Piecewise Constant Hazard Models for Censored and Truncated Data + maintainer: Paolo Frumento + description: |- + Piecewise constant hazard models for survival data. + The package allows for right-censored, left-truncated, and interval-censored data. + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pch + url_git: '' +pchc: + version: '1.3' + title: Bayesian Network Learning with the PCHC and Related Algorithms + maintainer: Michail Tsagris + description: |- + Bayesian network learning using the PCHC, FEDHC, MMHC and variants of these algorithms. PCHC stands for PC Hill-Climbing, a new hybrid algorithm that uses PC to construct the skeleton of the BN and then + applies the Hill-Climbing greedy search. More algorithms and variants have been added, such as MMHC, FEDHC, and the Tabu search variants, PCTABU, MMTABU and FEDTABU. + The relevant papers are: + a) Tsagris M. (2021). "A new scalable Bayesian network learning algorithm with applications to economics". Computational Economics, 57(1): 341-367. . + b) Tsagris M. (2022). "The FEDHC Bayesian Network Learning Algorithm". Mathematics 2022, 10(15): 2604. . + date_publication: '2024-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pchc + url_git: '' +pci: + version: 1.0.1 + title: A Collection of Process Capability Index Functions + maintainer: Sam Semegne + description: |- + A collection of process capability index functions, such as + C_p(), C_pk(), C_pm(), and others, along with metadata about each, like + 'LaTeX' equations and 'R' expressions. Its primary purpose is to form a + foundation for other quality control packages to build on top of, by providing + basic resources and functions. The indices belong to the field of statistical + quality control, and quantify the degree to which a manufacturing process is + able to create items that adhere to a certain standard of quality. For details + see Montgomery, D. C. (2019, ISBN:978-1-119-39930-8). + date_publication: '2024-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pci + url_git: https://github.com/samsemegne/pci +PCICt: + version: 0.5-4.4 + title: |- + Implementation of POSIXct Work-Alike for 365 and 360 Day + Calendars + maintainer: James Hiebert + description: |- + Provides a work-alike to R's POSIXct class which implements + 360- and 365-day calendars in addition to the gregorian calendar. + date_publication: '2023-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCICt + url_git: '' +pcIRT: + version: 0.2.4 + title: IRT Models for Polytomous and Continuous Item Responses + maintainer: Christine Hohensinn + description: Estimates the multidimensional polytomous Rasch model (Rasch, 1961) + with conditional maximum likelihood estimation. + date_publication: '2019-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcIRT + url_git: https://github.com/christinehohensinn/pcIRT +PCL: + version: '1.0' + title: Proximal Causal Learning + maintainer: Andrew Ying + description: We fit causal models using proxies. We implement two stage proximal + least squares estimator. E.J. Tchetgen Tchetgen, A. Ying, Y. Cui, X. Shi, and + W. Miao. (2020). An Introduction to Proximal Causal Learning. arXiv e-prints, + arXiv-2009 . + date_publication: '2021-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCL + url_git: '' +pcLasso: + version: '1.2' + title: Principal Components Lasso + maintainer: Rob Tibshirani + description: |- + A method for fitting the entire regularization path + of the principal components lasso for linear and + logistic regression models. The algorithm uses cyclic coordinate descent + in a path-wise fashion. See URL below for more information on the algorithm. + See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' + . + date_publication: '2020-09-03' + bug_reports: '' + url: https://arxiv.org/abs/1810.04651 + url_cran: https://CRAN.R-project.org/package=pcLasso + url_git: '' +PCLassoReg: + version: 1.0.0 + title: Group Regression Models for Risk Protein Complex Identification + maintainer: Wei Liu + description: Two protein complex-based group regression models (PCLasso and PCLasso2) + for risk protein complex identification. PCLasso is a prognostic model that identifies + risk protein complexes associated with survival. PCLasso2 is a classification + model that identifies risk protein complexes associated with classes. For more + information, see Wang and Liu (2021) . + date_publication: '2021-10-26' + bug_reports: https://github.com/weiliu123/PCLassoReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PCLassoReg + url_git: https://github.com/weiliu123/PCLassoReg +pcmabc: + version: 1.1.3 + title: |- + Approximate Bayesian Computations for Phylogenetic Comparative + Methods + maintainer: Krzysztof Bartoszek + description: Fits by ABC, the parameters of a stochastic process modelling the phylogeny + and evolution of a suite of traits following the tree. The user may define an + arbitrary Markov process for the trait and phylogeny. Importantly, trait-dependent + speciation models are handled and fitted to data. See K. Bartoszek, P. Lio' (2019) + . The suggested geiger package can be obtained + from CRAN's archive , + suggested to take latest version. Otherwise its required code is present in the + pcmabc package. The suggested distory package can be obtained from CRAN's archive + , suggested to take latest + version. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcmabc + url_git: '' +PCMBase: + version: 1.2.14 + title: |- + Simulation and Likelihood Calculation of Phylogenetic + Comparative Models + maintainer: Venelin Mitov + description: |- + Phylogenetic comparative methods represent models of continuous trait + data associated with the tips of a phylogenetic tree. Examples of such models + are Gaussian continuous time branching stochastic processes such as Brownian + motion (BM) and Ornstein-Uhlenbeck (OU) processes, which regard the data at the + tips of the tree as an observed (final) state of a Markov process starting from + an initial state at the root and evolving along the branches of the tree. The + PCMBase R package provides a general framework for manipulating such models. + This framework consists of an application programming interface for specifying + data and model parameters, and efficient algorithms for simulating trait evolution + under a model and calculating the likelihood of model parameters for an assumed + model and trait data. The package implements a growing collection of models, + which currently includes BM, OU, BM/OU with jumps, two-speed OU as well as mixed + Gaussian models, in which different types of the above models can be associated + with different branches of the tree. The PCMBase package is limited to + trait-simulation and likelihood calculation of (mixed) Gaussian phylogenetic + models. The PCMFit package provides functionality for inference of + these models to tree and trait data. The package web-site + + provides access to the documentation and other resources. + date_publication: '2024-03-15' + bug_reports: https://github.com/venelin/PCMBase/issues + url: https://venelin.github.io/PCMBase/ + url_cran: https://CRAN.R-project.org/package=PCMBase + url_git: '' +PCMBaseCpp: + version: 0.1.9 + title: Fast Likelihood Calculation for Phylogenetic Comparative Models + maintainer: Venelin Mitov + description: |- + Provides a C++ backend for multivariate phylogenetic comparative + models implemented in the R-package 'PCMBase'. Can be used in combination + with 'PCMBase' to enable fast and parallel likelihood calculation. Implements + the pruning likelihood calculation algorithm described in Mitov et al. (2018) + . Uses the 'SPLITT' C++ library for parallel tree traversal + described in Mitov and Stadler (2018) . + date_publication: '2020-03-23' + bug_reports: https://github.com/venelin/PCMBaseCpp/issues + url: https://venelin.github.io + url_cran: https://CRAN.R-project.org/package=PCMBaseCpp + url_git: https://github.com/venelin/PCMBaseCpp +PCMRS: + version: 0.1-4 + title: Model Response Styles in Partial Credit Models + maintainer: Gunther Schauberger + description: Implementation of PCMRS (Partial Credit Model with Response Styles) + as proposed in by Tutz, Schauberger and Berger (2018) + . PCMRS is an extension of the regular partial credit model. PCMRS allows for + an additional person parameter that characterizes the response style of the person. + By taking the response style into account, the estimates of the item parameters + are less biased than in partial credit models. + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCMRS + url_git: '' +pcnetmeta: + version: '2.8' + title: Patient-Centered Network Meta-Analysis + maintainer: Lifeng Lin + description: |- + Performs Bayesian arm-based network meta-analysis for datasets with binary, continuous, and count outcomes + (Zhang et al., 2014 ; + Lin et al., 2017 ). + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcnetmeta + url_git: '' +PCObw: + version: 0.0.1 + title: |- + Bandwidth Selector with Penalized Comparison to Overfitting + Criterion + maintainer: S. Varet + description: |- + Bandwidth selector according to the Penalised Comparison to Overfitting (P.C.O.) + criterion as described in Varet, S., Lacour, C., Massart, P., Rivoirard, V., (2019) + . + It can be used with univariate and multivariate data. + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCObw + url_git: '' +pCODE: + version: 0.9.4 + title: |- + Estimation of an Ordinary Differential Equation Model by + Parameter Cascade Method + maintainer: Haixu Wang + description: An implementation of the parameter cascade method in Ramsay, J. O., + Hooker,G., Campbell, D., and Cao, J. (2007) for estimating ordinary differential + equation models with missing or complete observations. It combines smoothing method + and profile estimation to estimate any non-linear dynamic system. The package + also offers variance estimates for parameters of interest based on either bootstrap + or Delta method. + date_publication: '2022-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pCODE + url_git: https://github.com/alex-haixuw/PCODE +PCovR: + version: 2.7.2 + title: Principal Covariates Regression + maintainer: Kristof Meers + description: Analyzing regression data with many and/or highly collinear predictor + variables, by simultaneously reducing the predictor variables to a limited number + of components and regressing the criterion variables on these components (de Jong + S. & Kiers H. A. L. (1992) ). Several rotation + and model selection options are provided. + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCovR + url_git: '' +PCPS: + version: 1.0.7 + title: Principal Coordinates of Phylogenetic Structure + maintainer: Vanderlei Julio Debastiani + description: Set of functions for analysis of Principal Coordinates of Phylogenetic + Structure (PCPS). + date_publication: '2020-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCPS + url_git: '' +pcr: + version: 1.2.2 + title: Analyzing Real-Time Quantitative PCR Data + maintainer: Mahmoud Ahmed + description: |- + Calculates the amplification efficiency and curves from real-time + quantitative PCR (Polymerase Chain Reaction) data. Estimates the relative + expression from PCR data using the double delta CT and the standard curve + methods Livak & Schmittgen (2001) . Tests for + statistical significance using two-group tests and linear regression + Yuan et al. (2006) . + date_publication: '2020-04-01' + bug_reports: https://github.com/MahShaaban/pcr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcr + url_git: https://github.com/MahShaaban/pcr +PCRA: + version: '1.2' + title: Companion to Portfolio Construction and Risk Analysis + maintainer: Doug Martin + description: |- + A collection of functions and data sets that support teaching + a quantitative finance MS level course on Portfolio Construction and Risk + Analysis, and the writing of a textbook for such a course. The package is + unique in providing several real-world data sets that may be used for problem + assignments and student projects. The data sets include cross-sections of + stock data from the Center for Research on Security Prices, LLC (CRSP), + corresponding factor exposures data from S&P Global, and several SP500 data + sets. + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCRA + url_git: '' +PCS: + version: '1.3' + title: Calculate the Probability of Correct Selection (PCS) + maintainer: Jason Wilson + description: Given k populations (can be in thousands), what is the probability + that a given subset of size t contains the true top t populations? This package + finds this probability and offers three tuning parameters (G, d, L) to relax the + definition. + date_publication: '2022-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCS + url_git: '' +pcse: + version: 1.9.1.1 + title: Panel-Corrected Standard Error Estimation in R + maintainer: Delia Bailey + description: |- + A function to estimate + panel-corrected standard errors. Data may contain balanced or + unbalanced panels. + date_publication: '2018-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pcse + url_git: '' +PCSinR: + version: 0.1.0 + title: Parallel Constraint Satisfaction Networks in R + maintainer: Felix Henninger + description: |- + Parallel Constraint Satisfaction (PCS) models are an increasingly + common class of models in Psychology, with applications to reading and word + recognition (McClelland & Rumelhart, 1981), judgment and decision making + (Glöckner & Betsch, 2008; Glöckner, Hilbig, & Jekel, 2014), and several + other fields (e.g. Read, Vanman, & Miller, 1997). In each of these fields, + they provide a quantitative model of psychological phenomena, with precise + predictions regarding choice probabilities, decision times, and often the degree + of confidence. This package provides the necessary functions to create and + simulate basic Parallel Constraint Satisfaction networks within R. + date_publication: '2016-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PCSinR + url_git: https://github.com/felixhenninger/PCSinR +pcsstools: + version: 0.1.2 + title: Tools for Regression Using Pre-Computed Summary Statistics + maintainer: Jack Wolf + description: |- + Defines functions to describe regression models using only + pre-computed summary statistics (i.e. means, variances, and covariances) + in place of individual participant data. + Possible models include linear models for linear combinations, products, + and logical combinations of phenotypes. + Implements methods presented in + Wolf et al. (2021) + Wolf et al. (2020) and + Gasdaska et al. (2019) . + date_publication: '2023-09-06' + bug_reports: https://github.com/jackmwolf/pcsstools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcsstools + url_git: https://github.com/jackmwolf/pcsstools/ +pcSteiner: + version: 1.0.0.1 + title: |- + Convenient Tool for Solving the Prize-Collecting Steiner Tree + Problem + maintainer: Aleksei Krasikov + description: |- + The Prize-Collecting Steiner Tree problem asks to find a subgraph + connecting a given set of vertices with the most expensive nodes and least + expensive edges. Since it is proven to be NP-hard, exact and efficient algorithm + does not exist. This package provides convenient functionality for obtaining an + approximate solution to this problem using loopy belief propagation algorithm. + date_publication: '2022-05-23' + bug_reports: https://github.com/krashkov/pcSteiner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcSteiner + url_git: https://github.com/krashkov/pcSteiner +pctax: + version: 0.1.3 + title: Professional Comprehensive Omics Data Analysis + maintainer: Chen Peng + description: |- + Provides a comprehensive suite of tools for analyzing omics data. It includes functionalities for alpha diversity analysis, beta + diversity analysis, differential abundance analysis, community assembly analysis, visualization of phylogenetic tree, and + functional enrichment analysis. With a progressive approach, the package offers a range of analysis methods to explore and + understand the complex communities. It is designed to support researchers and practitioners in conducting in-depth and + professional omics data analysis. + date_publication: '2024-12-02' + bug_reports: https://github.com/Asa12138/pctax/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pctax + url_git: https://github.com/Asa12138/pctax +pcts: + version: 0.15.7 + title: Periodically Correlated and Periodically Integrated Time Series + maintainer: Georgi N. Boshnakov + description: |- + Classes and methods for modelling and simulation of + periodically correlated (PC) and periodically integrated time + series. Compute theoretical periodic autocovariances and related + properties of PC autoregressive moving average models. Some original + methods including Boshnakov & Iqelan (2009) + , Boshnakov (1996) + . + date_publication: '2023-11-25' + bug_reports: https://github.com/GeoBosh/pcts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcts + url_git: https://geobosh.github.io/pcts/(doc)https://github.com/GeoBosh/pcts/(devel) +pcutils: + version: 0.2.7 + title: Some Useful Functions for Statistics and Visualization + maintainer: Chen Peng + description: |- + Offers a range of utilities and functions for everyday programming tasks. 1.Data Manipulation. Such as grouping + and merging, column splitting, and character expansion. 2.File Handling. Read and convert files in popular + formats. 3.Plotting Assistance. Helpful utilities for generating color palettes, validating color formats, and + adding transparency. 4.Statistical Analysis. Includes functions for pairwise comparisons and multiple testing + corrections, enabling perform statistical analyses with ease. 5.Graph Plotting, Provides efficient tools for + creating doughnut plot and multi-layered doughnut plot; Venn diagrams, including traditional Venn diagrams, + upset plots, and flower plots; Simplified functions for creating stacked bar plots, or a box plot with + alphabets group for multiple comparison group. + date_publication: '2024-11-27' + bug_reports: https://github.com/Asa12138/pcutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcutils + url_git: https://github.com/Asa12138/pcutils +pcv: + version: 1.1.0 + title: Procrustes Cross-Validation + maintainer: Sergey Kucheryavskiy + description: Implements Procrustes cross-validation method for Principal Component + Analysis, Principal Component Regression and Partial Least Squares regression + models. S. Kucheryavskiy (2023) . + date_publication: '2023-08-12' + bug_reports: https://github.com/svkucheryavski/pcv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pcv + url_git: https://github.com/svkucheryavski/pcv +pcvr: + version: 1.1.1.0 + title: Plant Phenotyping and Bayesian Statistics + maintainer: Josh Sumner + description: |- + Analyse common types of plant phenotyping data, provide a simplified interface + to longitudinal growth modeling and select Bayesian statistics, + and streamline use of 'PlantCV' output. + Several Bayesian methods and reporting guidelines for Bayesian methods are described in + Kruschke (2018) , + Kruschke (2013) , and Kruschke (2021) . + date_publication: '2024-11-06' + bug_reports: https://github.com/danforthcenter/pcvr/issues + url: https://plantcv.org/ + url_cran: https://CRAN.R-project.org/package=pcvr + url_git: https://github.com/danforthcenter/pcvr +pda: + version: 1.2.7 + title: Privacy-Preserving Distributed Algorithms + maintainer: Jiajie Chen + description: 'A collection of privacy-preserving distributed algorithms for conducting + multi-site data analyses. The regression analyses can be linear regression for + continuous outcome, logistic regression for binary outcome, Cox proportional hazard + regression for time-to event outcome, Poisson regression for count outcome, or + multi-categorical regression for nominal or ordinal outcome. The PDA algorithm + runs on a lead site and only requires summary statistics from collaborating sites, + with one or few iterations. The package can be used together with the online system + () for safe and convenient collaboration. For + more information, please visit our software websites: , + and .' + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pda + url_git: '' +pdc: + version: 1.0.3 + title: Permutation Distribution Clustering + maintainer: Andreas M. Brandmaier + description: Permutation Distribution Clustering is a clustering method for time + series. Dissimilarity of time series is formalized as the divergence between their + permutation distributions. The permutation distribution was proposed as measure + of the complexity of a time series. + date_publication: '2015-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdc + url_git: '' +pdcor: + version: '1.0' + title: Fast and Light-Weight Partial Distance Correlation + maintainer: Michail Tsagris + description: 'Fast and memory-less computation of the partial distance correlation + for vectors and matrices. Permutation-based and asymptotic hypothesis testing + for zero partial distance correlation are also performed. References include: + Szekely G. J. and Rizzo M. L. (2014). "Partial distance correlation with methods + for dissimilarities". The Annals Statistics, 42(6): 2382--2412. . + Shen C., Panda S. and Vogelstein J. T. (2022). "The Chi-Square Test of Distance + Correlation". Journal of Computational and Graphical Statistics, 31(1): 254--262. + . Szekely G. J. and Rizzo M. L. (2023). "The + Energy of Data and Distance Correlation". Chapman and Hall/CRC. .' + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdcor + url_git: '' +PDE: + version: 1.4.10 + title: Extract Tables and Sentences from PDFs with User Interface + maintainer: Erik Stricker + description: |- + The PDE (Pdf Data Extractor) allows the extraction of + information and tables optionally based on search words from + PDF (Portable Document Format) files and enables the visualization + of the results, both by providing a convenient user-interface. + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDE + url_git: '' +pder: + version: 1.0-2 + title: Panel Data Econometrics with R + maintainer: Yves Croissant + description: Data sets for the Panel Data Econometrics with R + book. + date_publication: '2022-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pder + url_git: '' +pdfCluster: + version: 1.0-4 + title: Cluster Analysis via Nonparametric Density Estimation + maintainer: Menardi Giovanna + description: |- + Cluster analysis via nonparametric density + estimation is performed. Operationally, the kernel method is used throughout to estimate + the density. Diagnostics methods for evaluating the quality of the clustering + are available. The package includes also a routine to estimate the + probability density function obtained by the kernel method, given a set of + data with arbitrary dimensions. + date_publication: '2022-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdfCluster + url_git: '' +PDFEstimator: + version: '4.5' + title: Multivariate Nonparametric Probability Density Estimator + maintainer: Jenny Farmer + description: Farmer, J., D. Jacobs (2108) . A + multivariate nonparametric density estimator based on the maximum-entropy method. Accurately + predicts a probability density function (PDF) for random data using a novel iterative + scoring function to determine the best fit without overfitting to the sample. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDFEstimator + url_git: '' +pdfetch: + version: 0.3.3 + title: |- + Fetch Economic and Financial Time Series Data from Public + Sources + maintainer: Abiel Reinhart + description: |- + Download economic and financial time series from public sources, + including the St Louis Fed's FRED system, Yahoo Finance, the US Bureau of Labor Statistics, + the US Energy Information Administration, the World Bank, Eurostat, the European Central Bank, + the Bank of England, the UK's Office of National Statistics, Deutsche Bundesbank, and INSEE. + date_publication: '2024-12-17' + bug_reports: https://github.com/abielr/pdfetch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pdfetch + url_git: https://github.com/abielr/pdfetch +pdfminer: + version: '1.0' + title: Read Portable Document Format (PDF) Files + maintainer: Florian Schwendinger + description: |- + Provides an interface to 'PDFMiner' + a 'Python' package for extracting information from 'PDF'-files. + 'PDFMiner' has the goal to get all information available in a 'PDF'-file, + position of the characters, font type, font size and informations about lines. + Which makes it the perfect starting point for extracting tables from 'PDF'-files. + More information can be found in the package 'README'-file. + date_publication: '2020-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdfminer + url_git: '' +pdfsearch: + version: 0.3.0 + title: Search Tools for PDF Files + maintainer: Brandon LeBeau + description: |- + Includes functions for keyword search of pdf files. There is + also a wrapper that includes searching of all files within a single + directory. + date_publication: '2019-01-09' + bug_reports: https://github.com/lebebr01/pdfsearch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pdfsearch + url_git: https://github.com/lebebr01/pdfsearch +pdftables: + version: '0.1' + title: Programmatic Conversion of PDF Tables + maintainer: Eric Persson + description: |- + Allows the user to convert PDF tables to formats more amenable to + analysis ('.csv', '.xml', or '.xlsx') by wrapping the PDFTables API. + In order to use the package, the user needs to sign up for an API account + on the PDFTables website (). + The package works by taking a PDF file as input, uploading it to PDFTables, + and returning a file with the extracted data. + date_publication: '2016-02-15' + bug_reports: https://www.github.com/expersso/pdftables/issues + url: https://pdftables.com + url_cran: https://CRAN.R-project.org/package=pdftables + url_git: https://www.github.com/expersso/pdftables +pdftools: + version: 3.4.1 + title: Text Extraction, Rendering and Converting of PDF Documents + maintainer: Jeroen Ooms + description: |- + Utilities based on 'libpoppler' for extracting text, fonts, attachments and + metadata from a PDF file. Also supports high quality rendering of PDF documents into + PNG, JPEG, TIFF format, or into raw bitmap vectors for further processing in R. + date_publication: '2024-09-20' + bug_reports: https://github.com/ropensci/pdftools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pdftools + url_git: https://docs.ropensci.org/pdftools/(website)https://github.com/ropensci/pdftools#readme(devel)https://poppler.freedesktop.org(upstream) +pdi: + version: 0.4.2 + title: Phenotypic Index Measures for Oak Decline Severity + maintainer: Jasen Finch + description: Oak declines are complex disease syndromes and consist of many visual + indicators that include aspects of tree size, crown condition and trunk condition. + This can cause difficulty in the manual classification of symptomatic and non-symptomatic + trees from what is in reality a broad spectrum of oak tree health condition. Two + phenotypic oak decline indexes have been developed to quantitatively describe + and differentiate oak decline syndromes in Quercus robur. This package provides + a toolkit to generate these decline indexes from phenotypic descriptors using + the machine learning algorithm random forest. The methodology for generating these + indexes is outlined in Finch et al. (2121) . + date_publication: '2021-02-09' + bug_reports: https://github.com/jasenfinch/pdi/issues + url: https://jasenfinch.github.io/pdi + url_cran: https://CRAN.R-project.org/package=pdi + url_git: '' +pdist: + version: 1.2.1 + title: Partitioned Distance Function + maintainer: Jeffrey Wong + description: |- + Computes the euclidean distance between rows of a matrix X + and rows of another matrix Y. Previously, this could be done + by binding the two matrices together and calling 'dist', but + this creates unnecessary computation by computing the distances + between a row of X and another row of X, and likewise for Y. + pdist strictly computes distances across the two matrices, not + within the same matrix, making computations significantly + faster for certain use cases. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdist + url_git: https://github.com/jeffwong/pdist +PDM: + version: '0.1' + title: Photogrammetric Distances Measurer + maintainer: J.F. Palomeque-Gonzalez + description: Measures real distances in pictures. With PDM() function, you can choose + one '*.jpg' file, select the measure in mm of scale, starting and and finishing + point in the graphical scale, the name of the measure, and starting and and finishing + point of the measures. After, ask the user for a new measure. + date_publication: '2016-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDM + url_git: '' +PDMIF: + version: 0.1.0 + title: Fits Heterogeneous Panel Data Models + maintainer: Tomohiro Ando + description: 'Fits heterogeneous panel data models with interactive effects for + linear regression, logistic, count, probit, quantile, and clustering. Based on + Ando, T. and Bai, J. (2015) "A simple new test for slope homogeneity in panel + data models with interactive effects" , Ando, + T. and Bai, J. (2015) "Asset Pricing with a General Multifactor Structure" , Ando, T. and Bai, J. (2016) "Panel data models with + grouped factor structure under unknown group membership" , + Ando, T. and Bai, J. (2017) "Clustering huge number of financial time series: + A panel data approach with high-dimensional predictors and factor structures" + , Ando, T. and Bai, J. (2020) "Quantile co-movement + in financial markets" , Ando, T., Bai, J. + and Li, K. (2021) "Bayesian and maximum likelihood analysis of large-scale panel + choice models with unobserved heterogeneity" .' + date_publication: '2022-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDMIF + url_git: '' +pdmod: + version: 1.0.1 + title: |- + Proximal/Distal Modeling Framework for Pavlovian Conditioning + Phenomena + maintainer: Chloe Bracis + description: Fits a model of Pavlovian conditioning phenomena, such as response + extinction and spontaneous recovery, and partial reinforcement extinction effects. + Competing proximal and distal reward predictions, computed using fast and slow + learning rates, combine according to their uncertainties and the recency of information. + The resulting mean prediction drives the response rate. + date_publication: '2018-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdmod + url_git: '' +PDN: + version: 0.1.0 + title: Personalized Disease Network + maintainer: Zhenbang Wang + description: |- + Building patient level networks for prediction of + medical outcomes and draw the cluster of network. + This package is based on paper Personalized disease + networks for understanding and predicting cardiovascular + diseases and other complex processes + (See Cabrera et al. ). + date_publication: '2017-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDN + url_git: '' +pdp: + version: 0.8.2 + title: Partial Dependence Plots + maintainer: Brandon M. Greenwell + description: |- + A general framework for constructing partial dependence (i.e., + marginal effect) plots from various types machine learning models + in R. + date_publication: '2024-10-28' + bug_reports: https://github.com/bgreenwell/pdp/issues + url: http://bgreenwell.github.io/pdp/ + url_cran: https://CRAN.R-project.org/package=pdp + url_git: https://github.com/bgreenwell/pdp +PdPDB: + version: 2.0.1 + title: Pattern Discovery in PDB Structures of Metalloproteins + maintainer: Luca Belmonte + description: |- + Looks for amino acid and/or nucleotide patterns and/or small + ligands coordinated to a given prosthetic centre. Files have to be in the local + file system and contain proper extension. + date_publication: '2017-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PdPDB + url_git: '' +pdqr: + version: 0.3.1 + title: Work with Custom Distribution Functions + maintainer: Evgeni Chasnovski + description: |- + Create, transform, and summarize custom random + variables with distribution functions (analogues of 'p*()', 'd*()', + 'q*()', and 'r*()' functions from base R). Two types of distributions + are supported: "discrete" (random variable has finite number of output + values) and "continuous" (infinite number of values in the form of + continuous random variable). Functions for distribution + transformations and summaries are available. Implemented approaches + often emphasize approximate and numerical solutions: all distributions + assume finite support and finite values of density function; some + methods implemented with simulation techniques. + date_publication: '2023-05-12' + bug_reports: https://github.com/echasnovski/pdqr/issues + url: https://echasnovski.github.io/pdqr/ + url_cran: https://CRAN.R-project.org/package=pdqr + url_git: https://github.com/echasnovski/pdqr +PDQutils: + version: 0.1.6 + title: |- + PDQ Functions via Gram Charlier, Edgeworth, and Cornish Fisher + Approximations + maintainer: Steven E. Pav + description: |- + A collection of tools for approximating the 'PDQ' functions + (respectively, the cumulative distribution, density, and quantile) of + probability distributions via classical expansions involving moments and + cumulants. + date_publication: '2017-03-18' + bug_reports: https://github.com/shabbychef/PDQutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PDQutils + url_git: https://github.com/shabbychef/PDQutils +pdR: + version: 1.9.3 + title: |- + Threshold Model and Unit Root Tests in Cross-Section and Time + Series Data + maintainer: Ho Tsung-wu + description: Threshold model, panel version of Hylleberg et al. (1990) + seasonal unit root tests, and panel unit root test of Chang (2002) . + date_publication: '2024-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdR + url_git: '' +PDSCE: + version: 1.2.1 + title: Positive Definite Sparse Covariance Estimators + maintainer: Adam J. Rothman + description: |- + Compute and tune some positive definite and sparse covariance + estimators. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDSCE + url_git: '' +PDShiny: + version: 0.1.0 + title: '''Probability Distribution Shiny''' + maintainer: Kartikeya Bolar + description: Interactive shiny application for working with Probability Distributions. + Calculations and Graphs are provided. + date_publication: '2018-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDShiny + url_git: '' +pdSpecEst: + version: 1.2.4 + title: An Analysis Toolbox for Hermitian Positive Definite Matrices + maintainer: Joris Chau + description: |- + An implementation of data analysis tools for samples of symmetric or + Hermitian positive definite matrices, such as collections of covariance matrices + or spectral density matrices. The tools in this package can be used to perform: (i) + intrinsic wavelet transforms for curves (1D) or surfaces (2D) of Hermitian positive + definite matrices with applications to dimension reduction, denoising and clustering in the + space of Hermitian positive definite matrices; and (ii) exploratory data analysis and inference + for samples of positive definite matrices by means of intrinsic data depth functions and + rank-based hypothesis tests in the space of Hermitian positive definite matrices. + date_publication: '2020-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdSpecEst + url_git: https://github.com/JorisChau/pdSpecEst +pdt: + version: 0.0.2 + title: Permutation Distancing Test + maintainer: Jan Houtveen + description: |- + Permutation (randomisation) test for single-case phase design data with + two phases (e.g., pre- and post-treatment). Correction for dependency of observations + is done through stepwise resampling the time series while varying + the distance between observations. The required distance 0,1,2,3.. is determined + based on repeated dependency testing while stepwise increasing the distance. + In preparation: Vroegindeweij et al. "A Permutation distancing test + for single-case observational AB phase design data: A Monte Carlo simulation study". + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pdt + url_git: '' +PDtoolkit: + version: 1.2.0 + title: |- + Collection of Tools for PD Rating Model Development and + Validation + maintainer: Andrija Djurovic + description: |- + The goal of this package is to cover the most common steps in probability of default (PD) rating model development and validation. + The main procedures available are those that refer to univariate, bivariate, multivariate analysis, calibration and validation. + Along with accompanied 'monobin' and 'monobinShiny' packages, 'PDtoolkit' provides functions which are suitable for different + data transformation and modeling tasks such as: + imputations, monotonic binning of numeric risk factors, binning of categorical risk factors, weights of evidence (WoE) and + information value (IV) calculations, WoE coding (replacement of risk factors modalities with WoE values), risk factor clustering, + area under curve (AUC) calculation and others. Additionally, package provides set of validation functions for testing homogeneity, + heterogeneity, discriminatory and predictive power of the model. + date_publication: '2023-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDtoolkit + url_git: https://github.com/andrija-djurovic/PDtoolkit +PDXpower: + version: 1.0.4 + title: |- + Time to Event Outcome in Experimental Designs of Pre-Clinical + Studies + maintainer: Shanpeng Li + description: |- + Conduct simulation-based customized power calculation + for clustered time to event data in a mixed crossed/nested design, + where a number of cell lines and a number of mice within each cell line are considered to achieve a desired statistical power, + motivated by Eckel-Passow and colleagues (2021) and Li and colleagues (2024) . + This package provides two commonly used models for powering a design, linear mixed effects and Cox frailty model. Both models account for + within-subject (cell line) correlation while holding different distributional assumptions about the outcome. + Alternatively, the counterparts of fixed effects model are also available, which produces similar estimates of statistical power. + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PDXpower + url_git: '' +pdxTrees: + version: 0.4.0 + title: Data Package of Portland, Oregon Trees + maintainer: Kelly McConville + description: An engaging collection of datasets from Portland Parks and Recreation. + The city of Portland inventoried every tree in over 170 parks and along the streets + in 96 neighborhoods. + date_publication: '2020-08-17' + bug_reports: https://github.com/mcconvil/pdxTrees/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pdxTrees + url_git: https://github.com/mcconvil/pdxTrees +pdynmc: + version: 0.9.12 + title: |- + Moment Condition Based Estimation of Linear Dynamic Panel Data + Models + maintainer: Markus Fritsch + description: |- + Linear dynamic panel data modeling based on linear and + nonlinear moment conditions as proposed by + Holtz-Eakin, Newey, and Rosen (1988) , + Ahn and Schmidt (1995) , + and Arellano and Bover (1995) . + Estimation of the model parameters relies on the Generalized + Method of Moments (GMM) and instrumental variables (IV) estimation, + numerical optimization (when nonlinear moment conditions are + employed) and the computation of closed form solutions (when + estimation is based on linear moment conditions). One-step, + two-step and iterated estimation is available. For inference + and specification + testing, Windmeijer (2005) + and doubly corrected standard errors + (Hwang, Kang, Lee, 2021 ) + are available. Additionally, serial correlation tests, tests for + overidentification, and Wald tests are provided. Functions for + visualizing panel data structures and modeling results obtained + from GMM estimation are also available. The plot methods include + functions to plot unbalanced panel structure, coefficient ranges + and coefficient paths across GMM iterations (the latter is + implemented according to the plot shown in + Hansen and Lee, 2021 ). + For a more detailed description of the GMM-based functionality, + please see Fritsch, Pua, Schnurbus (2021) . + For more details on the IV-based estimation routines, + see Fritsch, Pua, and Schnurbus (WP, 2024) and + Han and Phillips (2010) . + date_publication: '2025-02-20' + bug_reports: https://github.com/markusfritsch/pdynmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pdynmc + url_git: https://github.com/markusfritsch/pdynmc +peacesciencer: + version: 1.1.0 + title: Tools and Data for Quantitative Peace Science Research + maintainer: Steve Miller + description: |- + These are useful tools and data sets for the study of quantitative + peace science. The goal for this package is to include tools and data sets + for doing original research that mimics well what a user would have to previously + get from a software package that may not be well-sourced or well-supported. + Those software bundles were useful the extent to which they encourage replications + of long-standing analyses by starting the data-generating process from scratch. However, + a lot of the functionality can be done relatively quickly and more transparently + in the R programming language. + date_publication: '2023-03-24' + bug_reports: https://github.com/svmiller/peacesciencer/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=peacesciencer + url_git: https://github.com/svmiller/peacesciencer/ +PEACH: + version: 0.1.1 + title: Pareto Enrichment Analysis for Combining Heterogeneous Datasets + maintainer: Jinyan Chan + description: A meta gene set analysis tool developed based on principles of Pareto + dominance (William B T Mock (2011) ). It is + designed to combine gene set analysis p-values from multiple transcriptome datasets + (e.g., microarray and RNA-Seq). The novel Pareto method for p-value combination + allows PEACH to properly model heterogeneity and correlation in Omics datasets. + date_publication: '2021-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEACH + url_git: '' +Peacock.test: + version: '1.0' + title: Two and Three Dimensional Kolmogorov-Smirnov Two-Sample Tests + maintainer: Yuanhui Xiao + description: |- + The original definition of the two and three dimensional Kolmogorov-Smirnov two-sample + test statistics given by Peacock (1983) is implemented. Two R-functions: peacock2 and peacock3, + are provided to compute the test statistics in two and three dimensional spaces, respectively. + Note the Peacock test is different from the Fasano and Franceschini test (1987). The latter is + a variant of the Peacock test. + date_publication: '2016-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Peacock.test + url_git: '' +peacots: + version: 1.3.2 + title: Periodogram Peaks in Correlated Time Series + maintainer: Stilianos Louca + description: 'Calculates the periodogram of a time series, maximum-likelihood fits + an Ornstein-Uhlenbeck state space (OUSS) null model and evaluates the statistical + significance of periodogram peaks against the OUSS null hypothesis. The OUSS is + a parsimonious model for stochastically fluctuating variables with linear stabilizing + forces, subject to uncorrelated measurement errors. Contrary to the classical + white noise null model for detecting cyclicity, the OUSS model can account for + temporal correlations typically occurring in ecological and geological time series. + Citation: Louca, Stilianos and Doebeli, Michael (2015) .' + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=peacots + url_git: '' +PeakError: + version: 2023.9.4 + title: Compute the Label Error of Peak Calls + maintainer: Toby Dylan Hocking + description: |- + Chromatin immunoprecipitation DNA sequencing results in genomic + tracks that show enriched regions or peaks where proteins are bound. + This package implements fast C code that computes the true and false + positives with respect to a database of annotated region labels. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PeakError + url_git: '' +peakRAM: + version: 1.0.2 + title: Monitor the Total and Peak RAM Used by an Expression or Function + maintainer: Thomas Quinn + description: |- + When working with big data sets, RAM conservation is critically + important. However, it is not always enough to just monitor the + size of the objects created. So-called "copy-on-modify" behavior, + characteristic of R, means that some expressions or functions may + require an unexpectedly large amount of RAM overhead. For example, + replacing a single value in a matrix duplicates that matrix in the + back-end, making this task require twice as much RAM as that used + by the matrix itself. This package makes it easy to monitor the total + and peak RAM used so that developers can quickly identify and + eliminate RAM hungry code. + date_publication: '2017-01-16' + bug_reports: http://github.com/tpq/peakRAM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=peakRAM + url_git: http://github.com/tpq/peakRAM +PeakSegDisk: + version: 2024.10.1 + title: Disk-Based Constrained Change-Point Detection + maintainer: Toby Dylan Hocking + description: |- + Disk-based implementation of + Functional Pruning Optimal Partitioning with up-down constraints + for single-sample peak calling + (independently for each sample and genomic problem), + can handle huge data sets (10^7 or more). + date_publication: '2024-10-02' + bug_reports: https://github.com/tdhock/PeakSegDisk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PeakSegDisk + url_git: https://github.com/tdhock/PeakSegDisk +PeakSegDP: + version: 2024.1.24 + title: |- + Dynamic Programming Algorithm for Peak Detection in ChIP-Seq + Data + maintainer: Toby Dylan Hocking + description: |- + A quadratic time dynamic programming algorithm + can be used to compute an approximate solution to the problem of + finding the most likely changepoints + with respect to the Poisson likelihood, subject + to a constraint on the number of segments, and the changes which must + alternate: up, down, up, down, etc. For more info read + + "PeakSeg: constrained optimal segmentation and supervised penalty learning + for peak detection in count data" by TD Hocking et al, + proceedings of ICML2015. + date_publication: '2024-01-24' + bug_reports: https://github.com/tdhock/PeakSegDP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PeakSegDP + url_git: https://github.com/tdhock/PeakSegDP +PeakSegJoint: + version: 2024.12.4 + title: Joint Peak Detection in Several ChIP-Seq Samples + maintainer: Toby Dylan Hocking + description: |- + Jointly segment several ChIP-seq samples to find the peaks + which are the same and different across samples. The fast approximate + maximum Poisson likelihood algorithm is described in + "PeakSegJoint: fast supervised peak detection via joint segmentation + of multiple count data samples" + + by TD Hocking and G Bourque. + date_publication: '2024-12-04' + bug_reports: https://github.com/tdhock/PeakSegJoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PeakSegJoint + url_git: https://github.com/tdhock/PeakSegJoint +PeakSegOptimal: + version: 2024.10.1 + title: Optimal Segmentation Subject to Up-Down Constraints + maintainer: Toby Dylan Hocking + description: |- + Computes optimal changepoint models using the + Poisson likelihood for non-negative count data, + subject to the PeakSeg constraint: + the first change must be up, second change down, third change up, etc. + For more info about the models and algorithms, + read "Constrained Dynamic Programming and Supervised Penalty Learning + Algorithms for Peak Detection" + by TD Hocking et al. + date_publication: '2024-10-02' + bug_reports: https://github.com/tdhock/PeakSegOptimal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PeakSegOptimal + url_git: https://github.com/tdhock/PeakSegOptimal +pearson7: + version: 1.0-3 + title: |- + Maximum Likelihood Inference for the Pearson VII Distribution + with Shape Parameter 3/2 + maintainer: John Hughes + description: |- + Supports maximum likelihood inference for the Pearson VII + distribution with shape parameter 3/2 and free location and scale + parameters. This distribution is relevant when estimating the velocity of + processive motor proteins with random detachment. + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pearson7 + url_git: '' +PearsonDS: + version: 1.3.1 + title: Pearson Distribution System + maintainer: Martin Becker + description: |- + Implementation of the Pearson distribution system, including full + support for the (d,p,q,r)-family of functions for probability distributions + and fitting via method of moments and maximum likelihood method. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PearsonDS + url_git: '' +PearsonICA: + version: 1.2-5 + title: |- + Independent Component Analysis using Score Functions from the + Pearson System + maintainer: Juha Karvanen + description: |- + The Pearson-ICA algorithm is a mutual information-based + method for blind separation of statistically independent source + signals. It has been shown that the minimization of mutual + information leads to iterative use of score functions, i.e. + derivatives of log densities. The Pearson system allows + adaptive modeling of score functions. The flexibility of the + Pearson system makes it possible to model a wide range of + source distributions including asymmetric distributions. The + algorithm is designed especially for problems with asymmetric + sources but it works for symmetric sources as well. + date_publication: '2022-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PearsonICA + url_git: '' +pec: + version: 2023.04.12 + title: |- + Prediction Error Curves for Risk Prediction Models in Survival + Analysis + maintainer: Thomas A. Gerds + description: |- + Validation of risk predictions obtained from survival models and + competing risk models based on censored data using inverse weighting and + cross-validation. Most of the 'pec' functionality has been moved to 'riskRegression'. + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pec + url_git: '' +pecora: + version: 0.1.2 + title: Permutation Conditional Random Tests + maintainer: Angela Andreella + description: It provides functions to perform permutation conditional random one-sample + and two-samples t-tests in a multivariate framework. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pecora + url_git: '' +pedalfast.data: + version: 1.0.2 + title: PEDALFAST Data + maintainer: Peter DeWitt + description: |- + Data files and documentation for PEDiatric vALidation oF vAriableS + in TBI (PEDALFAST). The data was used in "Functional Status Scale in + Children With Traumatic Brain Injury: A Prospective Cohort Study" by Bennett, + Dixon, et al (2016) . + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pedalfast.data + url_git: '' +pedbp: + version: 2.0.2 + title: Pediatric Blood Pressure + maintainer: Peter DeWitt + description: |- + Data and utilities for estimating pediatric blood pressure + percentiles by sex, age, and optionally height (stature) as described in + Martin et.al. (2022) . + Blood pressure percentiles for children under one year of age come from Gemelli + et.al. (1990) . Estimates of blood pressure + percentiles for children at least one year of age are informed by + data from the National Heart, Lung, and Blood Institute (NHLBI) and the + Centers for Disease Control and Prevention (CDC) + or from Lo et.al. (2013) + . The flowchart for selecting the informing + data source comes from Martin et.al. (2022) + . + date_publication: '2025-01-07' + bug_reports: https://github.com/dewittpe/pedbp/issues/ + url: http://www.peteredewitt.com/pedbp/ + url_cran: https://CRAN.R-project.org/package=pedbp + url_git: https://github.com/dewittpe/pedbp/ +pedbuildr: + version: 0.3.0 + title: Pedigree Reconstruction + maintainer: Magnus Dehli Vigeland + description: |- + Reconstruct pedigrees from genotype data, by optimising the + likelihood over all possible pedigrees subject to given restrictions. + Tailor-made plots facilitate evaluation of the output. This package is + part of the 'pedsuite' ecosystem for pedigree analysis. In + particular, it imports 'pedprobr' for calculating pedigree likelihoods + and 'forrel' for estimating pairwise relatedness. + date_publication: '2023-08-22' + bug_reports: https://github.com/magnusdv/pedbuildr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedbuildr + url_git: https://github.com/magnusdv/pedbuildr +pedFamilias: + version: 0.2.4 + title: Import and Export 'Familias' Files + maintainer: Magnus Dehli Vigeland + description: |- + Tools for exchanging pedigree data between the 'pedsuite' + packages and the 'Familias' software for forensic kinship computations + (Egeland et al. (2000) ). These + functions were split out from the 'forrel' package to streamline + maintenance and provide a lightweight alternative for packages otherwise + independent of 'forrel'. + date_publication: '2024-09-06' + bug_reports: https://github.com/magnusdv/pedFamilias/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedFamilias + url_git: https://github.com/magnusdv/pedFamilias +pedgene: + version: '3.9' + title: Gene-Level Variant Association Tests for Pedigree Data + maintainer: Jason Sinnwell + description: 'Gene-level variant association tests with disease status for pedigree + data: kernel and burden association statistics.' + date_publication: '2024-04-10' + bug_reports: '' + url: https://analytictools.mayo.edu/research/pedgene/ + url_cran: https://CRAN.R-project.org/package=pedgene + url_git: '' +pedigree: + version: 1.4.2 + title: Pedigree Functions + maintainer: Albart Coster + description: Pedigree related functions. + date_publication: '2022-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pedigree + url_git: '' +pedigreemm: + version: 0.3-5 + title: Pedigree-Based Mixed-Effects Models + maintainer: Ana Ines Vazquez + description: Fit pedigree-based mixed-effects models. + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pedigreemm + url_git: https://github.com/anainesvs/pedigreemm/ +pedigreeTools: + version: '0.3' + title: Versatile Functions for Working with Pedigrees + maintainer: Paulino Perez Rodriguez + description: |- + Tools to sort, edit and prune pedigrees and to extract the inbreeding coefficients + and the relationship matrix (includes code for pedigrees from self-pollinated species). + The use of pedigree data is central to genetics research within the animal and plant breeding communities to predict + breeding values. The relationship matrix between the individuals can be derived from pedigree structure + ('Vazquez et al., 2010') . + date_publication: '2024-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pedigreeTools + url_git: https://github.com/Rpedigree/pedigreeTools/ +pedMermaid: + version: 1.0.2 + title: Pedigree Mermaid Syntax + maintainer: Mohammad Ali Nilforooshan + description: |- + Generate Mermaid syntax for a pedigree flowchart from a pedigree data frame. + Mermaid syntax is commonly used to generate plots, charts, diagrams, and flowcharts. It is a textual syntax for creating reproducible illustrations. This package generates Mermaid syntax from a pedigree data frame to visualize a pedigree flowchart. The Mermaid syntax can be embedded in a Markdown or R Markdown file, or viewed on Mermaid editors and renderers. Links' shape, style, and orientation can be customized via function arguments, and nodes' shapes and styles can be customized via optional columns in the pedigree data frame. + date_publication: '2024-04-09' + bug_reports: https://github.com/nilforooshan/pedMermaid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedMermaid + url_git: https://github.com/nilforooshan/pedMermaid +pedmut: + version: 0.7.1 + title: Mutation Models for Pedigree Likelihood Computations + maintainer: Magnus Dehli Vigeland + description: |- + A collection of functions for modelling mutations in + pedigrees with marker data, as used e.g. in likelihood computations + with microsatellite data. Implemented models include equal, + proportional and stepwise models, as well as random models for + experimental work, and custom models allowing the user to apply any + valid mutation matrix. Allele lumping is done following the + lumpability criteria of Kemeny and Snell (1976), ISBN:0387901922. + date_publication: '2023-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pedmut + url_git: https://github.com/magnusdv/pedmut +pedometrics: + version: 0.12.1 + title: Miscellaneous Pedometric Tools + maintainer: Alessandro Samuel-Rosa + description: |- + An R implementation of methods employed in the field of pedometrics, soil science + discipline dedicated to studying the spatial, temporal, and spatio-temporal variation of soil + using statistical and computational methods. The methods found here include the calibration of + linear regression models using covariate selection strategies, computation of summary validation + statistics for predictions, generation of summary plots, evaluation of the local quality of a + geostatistical model of uncertainty, and so on. Other functions simply extend the + functionalities of or facilitate the usage of functions from other packages that are commonly + used for the analysis of soil data. Formerly available versions of suggested packages no longer + available from CRAN can be obtained from the CRAN archive + . + date_publication: '2022-06-19' + bug_reports: https://github.com/Laboratorio-de-Pedometria/pedometrics-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedometrics + url_git: https://github.com/Laboratorio-de-Pedometria/pedometrics-package +pedprobr: + version: 0.9.4 + title: Probability Computations on Pedigrees + maintainer: Magnus Dehli Vigeland + description: |- + An implementation of the Elston-Stewart algorithm for + calculating pedigree likelihoods given genetic marker data (Elston and + Stewart (1971) ). The standard algorithm is + extended to allow inbred founders. 'pedprobr' is part of the 'ped + suite', a collection of packages for pedigree analysis in R. In + particular, 'pedprobr' depends on 'pedtools' for pedigree + manipulations and 'pedmut' for mutation modelling. For more + information, see 'Pedigree Analysis in R' (Vigeland, 2021, + ISBN:9780128244302). + date_publication: '2024-05-08' + bug_reports: https://github.com/magnusdv/pedprobr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedprobr + url_git: https://github.com/magnusdv/pedprobr +pedquant: + version: 0.2.4 + title: Public Economic Data and Quantitative Analysis + maintainer: Shichen Xie + description: |2- + + Provides an interface to access public economic and financial data for + economic research and quantitative analysis. The data sources including + NBS, FRED, Sina, Eastmoney and etc. It also provides quantitative + functions for trading strategies based on the 'data.table', 'TTR', + 'PerformanceAnalytics' and etc packages. + date_publication: '2024-01-10' + bug_reports: https://github.com/ShichenXie/pedquant/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedquant + url_git: https://github.com/ShichenXie/pedquant +pedSimulate: + version: 1.4.3 + title: Pedigree, Genetic Merit, Phenotype, and Genotype Simulation + maintainer: Mohammad Ali Nilforooshan + description: |- + Simulate pedigree, genetic merits and phenotypes with random/non-random matings followed by random/non-random selection with different intensities and patterns in males and females. Genotypes can be simulated for a given pedigree, or an appended pedigree to an existing pedigree with genotypes. + Mrode, R. A. (2005) ; + Nilforooshan, M.A. (2022) . + date_publication: '2023-09-26' + bug_reports: https://github.com/nilforooshan/pedSimulate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pedSimulate + url_git: https://github.com/nilforooshan/pedSimulate +pedsuite: + version: 1.3.1 + title: |- + Easy Installation of the 'pedsuite' Packages for Pedigree + Analysis + maintainer: Magnus Dehli Vigeland + description: |- + The 'pedsuite' is a collection of packages for pedigree + analysis, covering applications in forensic genetics, medical genetics + and more. A detailed presentation of the 'pedsuite' is given in the + book 'Pedigree Analysis in R' (Vigeland, 2021, ISBN: 9780128244302). + date_publication: '2024-09-06' + bug_reports: https://github.com/magnusdv/pedsuite/issues + url: https://magnusdv.github.io/pedsuite/ + url_cran: https://CRAN.R-project.org/package=pedsuite + url_git: https://github.com/magnusdv/pedsuite +pedtools: + version: 2.8.0 + title: Creating and Working with Pedigrees and Marker Data + maintainer: Magnus Dehli Vigeland + description: |- + A comprehensive collection of tools for creating, + manipulating and visualising pedigrees and genetic marker data. + Pedigrees can be read from text files or created on the fly with + built-in functions. A range of utilities enable modifications like + adding or removing individuals, breaking loops, and merging pedigrees. + An online tool for creating pedigrees interactively, based on + 'pedtools', is available at . + 'pedtools' is the hub of the 'pedsuite', a collection of packages for + pedigree analysis. A detailed presentation of the 'pedsuite' is given + in the book 'Pedigree Analysis in R' (Vigeland, 2021, + ISBN:9780128244302). + date_publication: '2025-01-25' + bug_reports: '' + url: https://magnusdv.github.io/pedsuite/ + url_cran: https://CRAN.R-project.org/package=pedtools + url_git: https://github.com/magnusdv/pedtools +pedtricks: + version: 0.4.2 + title: Visualize, Summarize and Simulate Data from Pedigrees + maintainer: Julien Martin + description: |- + Sensitivity and power analysis, + for calculating statistics describing pedigrees from wild populations, + and for visualizing pedigrees. + date_publication: '2024-09-09' + bug_reports: https://github.com/JulienGAMartin/pedtricks/issues + url: https://juliengamartin.github.io/pedtricks/ + url_cran: https://CRAN.R-project.org/package=pedtricks + url_git: '' +peermodels: + version: 0.10.3 + title: |- + Client-Side R API Wrapper for Peer Models Network Model + Repository + maintainer: amin adibi + description: Enables direct cloud access to health care decision models hosted on + the PRISM server of the Peer Models Network. + date_publication: '2022-02-25' + bug_reports: '' + url: https://www.peermodelsnetwork.com + url_cran: https://CRAN.R-project.org/package=peermodels + url_git: '' +PeerPerformance: + version: 2.3.1 + title: Luck-Corrected Peer Performance Analysis in R + maintainer: David Ardia + description: |- + Provides functions to perform the peer performance + analysis of funds' returns as described in Ardia and Boudt (2018) . + date_publication: '2024-11-13' + bug_reports: https://github.com/ArdiaD/PeerPerformance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PeerPerformance + url_git: https://github.com/ArdiaD/PeerPerformance +pegas: + version: '1.3' + title: Population and Evolutionary Genetics Analysis System + maintainer: Emmanuel Paradis + description: Functions for reading, writing, plotting, analysing, and manipulating + allelic and haplotypic data, including from VCF files, and for the analysis of + population nucleotide sequences and micro-satellites including coalescent analyses, + linkage disequilibrium, population structure (Fst, Amova) and equilibrium (HWE), + haplotype networks, minimum spanning tree and network, and median-joining networks. + date_publication: '2023-12-13' + bug_reports: '' + url: https://emmanuelparadis.github.io/pegas.html + url_cran: https://CRAN.R-project.org/package=pegas + url_git: '' +PEGroupTesting: + version: '1.0' + title: Population Proportion Estimation using Group Testing + maintainer: Qingyang Zhang + description: The population proportion using group testing can be estimated by different + methods. Four functions including p.mle(), p.gart(), p.burrow() and p.order() + are provided to implement four estimating methods including the maximum likelihood + estimate, Gart's estimate, Burrow's estimate, and order statistic estimate. + date_publication: '2016-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEGroupTesting + url_git: '' +PEIMAN2: + version: 0.1.0 + title: |- + Post-Translational Modification Enrichment, Integration, and + Matching Analysis + maintainer: Payman Nickchi + description: Functions and mined database from 'UniProt' focusing on post-translational + modifications to do single enrichment analysis (SEA) and protein set enrichment + analysis (PSEA). Payman Nickchi, Mehdi Mirzaie, Marc Baumann, Amir Ata Saei, Mohieddin + Jafari (2022) . + date_publication: '2022-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEIMAN2 + url_git: '' +PEIP: + version: 2.2-5 + title: Geophysical Inverse Theory and Optimization + maintainer: Jonathan M. Lees + description: Several functions introduced in Aster et al.'s book on inverse theory. + The functions are often translations of MATLAB code developed by the authors to + illustrate concepts of inverse theory as applied to geophysics. Generalized inversion, + tomographic inversion algorithms (conjugate gradients, 'ART' and 'SIRT'), non-linear + least squares, first and second order Tikhonov regularization, roughness constraints, + and procedures for estimating smoothing parameters are included. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEIP + url_git: '' +PEkit: + version: 1.0.0.1000 + title: Partition Exchangeability Toolkit + maintainer: Ali Amiryousefi + description: Bayesian supervised predictive classifiers, hypothesis testing, and + parametric estimation under Partition Exchangeability are implemented. The two + classifiers presented are the marginal classifier (that assumes test data is i.i.d.) + next to a more computationally costly but accurate simultaneous classifier (that + finds a labelling for the entire test dataset at once based on simultanous use + of all the test data to predict each label). We also provide the Maximum Likelihood + Estimation (MLE) of the only underlying parameter of the partition exchangeability + generative model as well as hypothesis testing statistics for equality of this + parameter with a single value, alternative, or multiple samples. We present functions + to simulate the sequences from Ewens Sampling Formula as the realisation of the + Poisson-Dirichlet distribution and their respective probabilities. + date_publication: '2021-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEkit + url_git: '' +pell: + version: 0.1.0 + title: Data About Historic Pell Grant Distribution in the US + maintainer: Arafath Hossain + description: |- + Historic Pell grant data as provided by the US Department of Education. + This package contains data about how much pell grant was awarded by which institution in + which year. + This data comes from the US Department of Education. Raw data can be downloaded from here: . + date_publication: '2022-08-16' + bug_reports: https://github.com/Curious-Joe/pell/issues + url: https://curious-joe.github.io/pell/ + url_cran: https://CRAN.R-project.org/package=pell + url_git: https://github.com/Curious-Joe/pell +PELVIS: + version: 2.0.4 + title: |- + Probabilistic Sex Estimate using Logistic Regression, Based on + VISual Traits of the Human Os Coxae + maintainer: Frédéric Santos + description: An R-Shiny application implementing a method of sexing the human os + coxae based on logistic regressions and Bruzek's nonmetric traits . + date_publication: '2023-08-08' + bug_reports: https://gitlab.com/f-santos/pelvis/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PELVIS + url_git: https://gitlab.com/f-santos/pelvis/ +pema: + version: 0.1.3 + title: Penalized Meta-Analysis + maintainer: Caspar J van Lissa + description: |- + Conduct penalized meta-analysis, see Van Lissa, Van Erp, & Clapper + (2023) . In meta-analysis, there are + often between-study differences. These can be coded as moderator variables, + and controlled for using meta-regression. However, if the number of + moderators is large relative to the number of studies, such an analysis may + be overfit. Penalized meta-regression is useful in these cases, because + it shrinks the regression slopes of irrelevant moderators towards zero. + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pema + url_git: https://github.com/cjvanlissa/pema +pempi: + version: 1.0.0 + title: Proportion Estimation with Marginal Proxy Information + maintainer: Stéphane Guerrier + description: A system contains easy-to-use tools for the conditional estimation + of the prevalence of an emerging or rare infectious diseases using the methods + proposed in Guerrier et al. (2023) . + date_publication: '2023-10-09' + bug_reports: https://github.com/stephaneguerrier/pempi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pempi + url_git: https://github.com/stephaneguerrier/pempi +pems.utils: + version: 0.3.0.7 + title: |- + Portable Emissions (and Other Mobile) Measurement System + Utilities + maintainer: Karl Ropkins + description: |- + Utility functions for the handling, analysis and visualisation of data + from portable emissions measurement systems ('PEMS') and other similar + mobile activity monitoring devices. The package includes a dedicated 'pems' + data class that manages many of the quality control, unit handling and data + archiving issues that can hinder efforts to standardise 'PEMS' research. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pems.utils + url_git: http://pems.r-forge.r-project.org/ +pemultinom: + version: 0.1.1 + title: L1-Penalized Multinomial Regression with Statistical Inference + maintainer: Ye Tian + description: 'We aim for fitting a multinomial regression model with Lasso penalty + and doing statistical inference (calculating confidence intervals of coefficients + and p-values for individual variables). It implements 1) the coordinate descent + algorithm to fit an l1-penalized multinomial regression model (parameterized with + a reference level); 2) the debiasing approach to obtain the inference results, + which is described in "Tian, Y., Rusinek, H., Masurkar, A. V., & Feng, Y. (2024). + L1‐Penalized Multinomial Regression: Estimation, Inference, and Prediction, With + an Application to Risk Factor Identification for Different Dementia Subtypes. + Statistics in Medicine, 43(30), 5711-5747."' + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pemultinom + url_git: '' +penAFT: + version: 0.3.0 + title: |- + Fit the Regularized Gehan Estimator with Elastic Net and Sparse + Group Lasso Penalties + maintainer: Aaron J. Molstad + description: The semiparametric accelerated failure time (AFT) model is an attractive + alternative to the Cox proportional hazards model. This package provides a suite + of functions for fitting one popular estimator of the semiparametric AFT model, + the regularized Gehan estimator. Specifically, we provide functions for cross-validation, + prediction, coefficient extraction, and visualizing both trace plots and cross-validation + curves. For further details, please see Suder, P. M. and Molstad, A. J., (2022+) + Scalable algorithms for semiparametric accelerated failure time models in high + dimensions, to appear in Statistics in Medicine . + date_publication: '2023-04-18' + bug_reports: '' + url: ajmolstad.github.io/research + url_cran: https://CRAN.R-project.org/package=penAFT + url_git: '' +penalized: + version: 0.9-52 + title: |- + L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation + in GLMs and in the Cox Model + maintainer: Jelle Goeman + description: |- + Fitting possibly high dimensional penalized + regression models. The penalty structure can be any combination + of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a + positivity constraint on the regression coefficients. The + supported regression models are linear, logistic and Poisson + regression and the Cox Proportional Hazards model. + Cross-validation routines allow optimization of the tuning + parameters. + date_publication: '2022-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=penalized + url_git: '' +penalizedcdf: + version: 0.1.0 + title: Estimate a Penalized Linear Model using the CDF Penalty Function + maintainer: Daniele Cuntrera + description: |- + Utilize the CDF penalty function to estimate a penalized linear model. + It enables you to display some graphical representations and determine whether the Karush-Kuhn-Tucker conditions are met. + For more details about the theory, please refer to Cuntrera, D., Augugliaro, L., & Muggeo, V. M. (2022) . + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=penalizedcdf + url_git: '' +penalizedclr: + version: 2.0.0 + title: Integrative Penalized Conditional Logistic Regression + maintainer: Vera Djordjilovi'c + description: |- + Implements L1 and L2 penalized conditional logistic regression with penalty + factors allowing for integration of multiple data sources. Implements + stability selection for variable selection. + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=penalizedclr + url_git: '' +penalizedSVM: + version: 1.1.4 + title: Feature Selection SVM using Penalty Functions + maintainer: Frederic Bertrand + description: |- + Support Vector Machine (SVM) classification with simultaneous feature selection using penalty + functions is implemented. The smoothly clipped absolute deviation (SCAD), + 'L1-norm', 'Elastic Net' ('L1-norm' and 'L2-norm') and 'Elastic + SCAD' (SCAD and 'L2-norm') penalties are available. The tuning + parameters can be found using either a fixed grid or a interval + search. + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=penalizedSVM + url_git: '' +penaltyLearning: + version: 2024.9.3 + title: Penalty Learning + maintainer: Toby Dylan Hocking + description: |- + Implementations of algorithms from + Learning Sparse Penalties for Change-point Detection + using Max Margin Interval Regression, by + Hocking, Rigaill, Vert, Bach + + published in proceedings of ICML2013. + date_publication: '2024-10-02' + bug_reports: https://github.com/tdhock/penaltyLearning/issues + url: '' + url_cran: https://CRAN.R-project.org/package=penaltyLearning + url_git: https://github.com/tdhock/penaltyLearning +pencal: + version: 2.2.3 + title: |- + Penalized Regression Calibration (PRC) for the Dynamic + Prediction of Survival + maintainer: Mirko Signorelli + description: |- + Computes penalized regression calibration (PRC), a + statistical method for the dynamic prediction of survival when many + longitudinal predictors are available. PRC is described in Signorelli + (2024) and in Signorelli et al. (2021) + . + date_publication: '2025-02-07' + bug_reports: '' + url: https://mirkosignorelli.github.io/r + url_cran: https://CRAN.R-project.org/package=pencal + url_git: '' +pencopulaCond: + version: '0.2' + title: Estimating Non-Simplified Vine Copulas Using Penalized Splines + maintainer: Christian Schellhase + description: Estimating Non-Simplified Vine Copulas Using Penalized Splines. + date_publication: '2017-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pencopulaCond + url_git: '' +PenCoxFrail: + version: 2.0.0 + title: Regularization in Cox Frailty Models + maintainer: Andreas Groll + description: Different regularization approaches for Cox Frailty Models by penalization + methods are provided. + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PenCoxFrail + url_git: '' +pendensity: + version: 0.2.13 + title: Density Estimation with a Penalized Mixture Approach + maintainer: Christian Schellhase + description: Estimation of univariate (conditional) densities using penalized B-splines + with automatic selection of optimal smoothing parameter. + date_publication: '2019-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pendensity + url_git: '' +penfa: + version: 0.1.1 + title: Single- And Multiple-Group Penalized Factor Analysis + maintainer: Elena Geminiani + description: |- + Fits single- and multiple-group penalized factor analysis models + via a trust-region algorithm with integrated automatic multiple tuning + parameter selection (Geminiani et al., 2021 ). + Available penalties include lasso, adaptive lasso, scad, mcp, and ridge. + date_publication: '2021-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=penfa + url_git: https://github.com/egeminiani/penfa +PenIC: + version: 1.0.0 + title: |- + Semiparametric Regression Analysis of Interval-Censored Data + using Penalized Splines + maintainer: Yan Liu + description: |- + Currently incorporate the generalized odds-rate model (a type of linear + transformation model) for interval-censored data based on penalized monotonic B-Spline. + More methods under other semiparametric models such as cure model or additive model will + be included in future versions. For more details see Lu, M., Liu, Y., Li, C. and Sun, J. + (2019) . + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PenIC + url_git: '' +penMSM: + version: '0.99' + title: Estimating Regularized Multi-state Models Using L1 Penalties + maintainer: Holger Reulen + description: Structured fusion Lasso penalized estimation of multi-state models + with the penalty applied to absolute effects and absolute effect differences (i.e., + effects on transition-type specific hazard rates). + date_publication: '2015-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=penMSM + url_git: '' +penPHcure: + version: 1.0.2 + title: Variable Selection in PH Cure Model with Time-Varying Covariates + maintainer: Alessandro Beretta + description: Implementation of the semi-parametric proportional-hazards (PH) of + Sy and Taylor (2000) extended to time-varying + covariates. Estimation and variable selection are based on the methodology described + in Beretta and Heuchenne (2019) ; confidence + intervals of the parameter estimates may be computed using a bootstrap approach. + Moreover, data following the PH cure model may be simulated using a method similar + to Hendry (2014) , where the event-times are generated on + a continuous scale from a piecewise exponential distribution conditional on time-varying + covariates. + date_publication: '2019-12-03' + bug_reports: https://github.com/a-beretta/penPHcure/issues + url: '' + url_cran: https://CRAN.R-project.org/package=penPHcure + url_git: https://github.com/a-beretta/penPHcure +penppml: + version: 0.2.4 + title: Penalized Poisson Pseudo Maximum Likelihood Regression + maintainer: Joao Cruz + description: |- + A set of tools that enables efficient estimation of penalized + Poisson Pseudo Maximum Likelihood regressions, using lasso or ridge penalties, for models + that feature one or more sets of high-dimensional fixed effects. The methodology is based on + Breinlich, Corradi, Rocha, Ruta, Santos Silva, and Zylkin (2021) + and takes advantage of the method of alternating projections of Gaure (2013) + for dealing with HDFE, as well as + the coordinate descent algorithm of Friedman, Hastie and Tibshirani (2010) + for fitting lasso regressions. The package is also able to carry out + cross-validation and to implement the plugin lasso of Belloni, Chernozhukov, Hansen and Kozbur (2016) + . + date_publication: '2025-02-08' + bug_reports: https://github.com/tomzylkin/penppml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=penppml + url_git: https://github.com/tomzylkin/penppml +pense: + version: 2.2.2 + title: Penalized Elastic Net S/MM-Estimator of Regression + maintainer: David Kepplinger + description: |- + Robust penalized (adaptive) elastic net S and M estimators for + linear regression. The methods are proposed in + Cohen Freue, G. V., Kepplinger, D., Salibián-Barrera, M., and Smucler, E. + (2019) . + The package implements the extensions and algorithms described in + Kepplinger, D. (2020) . + date_publication: '2024-07-27' + bug_reports: https://github.com/dakep/pense-rpkg/issues + url: https://dakep.github.io/pense-rpkg/ + url_cran: https://CRAN.R-project.org/package=pense + url_git: https://github.com/dakep/pense-rpkg +pensim: + version: 1.3.6 + title: |- + Simulation of High-Dimensional Data and Parallelized Repeated + Penalized Regression + maintainer: Levi Waldron + description: |- + Simulation of continuous, correlated high-dimensional data with + time to event or binary response, and parallelized functions for Lasso, + Ridge, and Elastic Net penalized regression with repeated starts and + two-dimensional tuning of the Elastic Net. + date_publication: '2022-12-09' + bug_reports: https://github.com/waldronlab/pensim/issues + url: https://waldronlab.io/pensim/ + url_cran: https://CRAN.R-project.org/package=pensim + url_git: '' +pensynth: + version: 0.5.1 + title: Penalized Synthetic Control Estimation + maintainer: Erik-Jan van Kesteren + description: |- + Estimate penalized synthetic control models + and perform hold-out validation to determine their + penalty parameter. This method is based on the work by + Abadie & L'Hour (2021) . + Penalized synthetic controls smoothly interpolate between + one-to-one matching and the synthetic control method. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pensynth + url_git: https://github.com/vankesteren/pensynth +peopleanalytics: + version: 0.1.0 + title: |- + Data Sets for Craig Starbuck's Book, "The Fundamentals of People + Analytics: With Applications in R" + maintainer: Craig Starbuck + description: 'Data sets associated with modeling examples in Craig Starbuck''s book, + "The Fundamentals of People Analytics: With Applications in R".' + date_publication: '2022-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=peopleanalytics + url_git: '' +peopleanalyticsdata: + version: 0.2.1 + title: |- + Data Sets for Keith McNulty's Handbook of Regression Modeling in + People Analytics + maintainer: Keith McNulty + description: |- + Data sets for statistical inference modeling related to People Analytics. + Contains various data sets from the book 'Handbook of Regression Modeling in People Analytics' + by Keith McNulty (2020). + date_publication: '2021-04-13' + bug_reports: '' + url: http://peopleanalytics-regression-book.org + url_cran: https://CRAN.R-project.org/package=peopleanalyticsdata + url_git: '' +pEPA: + version: '1.0' + title: Tests of Equal Predictive Accuracy for Panels of Forecasts + maintainer: Krzysztof Drachal + description: 'Allows to perform the tests of equal predictive accuracy for panels + of forecasts. Main references: Qu et al. (2024) + and Akgun et al. (2024) .' + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pEPA + url_git: '' +PEPBVS: + version: '2.1' + title: Bayesian Variable Selection using Power-Expected-Posterior Prior + maintainer: Konstantina Charmpi + description: |- + Performs Bayesian variable selection under normal linear + models for the data with the model parameters following as prior distributions either + the power-expected-posterior (PEP) or the intrinsic (a special case of the former) + (Fouskakis and Ntzoufras (2022) , + Fouskakis and Ntzoufras (2020) ). + The prior distribution on model space is the uniform over all models + or the uniform on model dimension (a special case of the beta-binomial prior). + The selection is performed by either implementing a full enumeration + and evaluation of all possible models or using the Markov Chain + Monte Carlo Model Composition (MC3) algorithm (Madigan and York (1995) ). + Complementary functions for hypothesis testing, estimation and + predictions under Bayesian model averaging, as well as, plotting and + printing the results are also provided. The results can be compared to the + ones obtained under other well-known priors on model parameters and model spaces. + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEPBVS + url_git: '' +pepe: + version: 1.2.0 + title: Data Manipulation + maintainer: Seyma Kalay + description: Is designed to make easier printing summary statistics (for continues + and factor level) tables in Latex, and plotting by factor. + date_publication: '2022-05-13' + bug_reports: https://github.com/seymakalay/pepe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pepe + url_git: https://github.com/seymakalay/pepe +peperr: + version: '1.5' + title: Parallelised Estimation of Prediction Error + maintainer: Frederic Bertrand + description: |- + Designed for prediction error estimation + through resampling techniques, possibly accelerated by parallel + execution on a compute cluster. Newly developed model fitting + routines can be easily incorporated. Methods used in the package are detailed in + Porzelius Ch., Binder H. and Schumacher M. (2009) + and were used, for instance, in + Porzelius Ch., Schumacher M.and Binder H. (2011) . + date_publication: '2023-03-22' + bug_reports: https://github.com/fbertran/peperr/issues/ + url: https://fbertran.github.io/peperr/ + url_cran: https://CRAN.R-project.org/package=peperr + url_git: https://github.com/fbertran/peperr/ +PepMapViz: + version: 1.0.0 + title: |- + A Versatile Toolkit for Peptide Mapping, Visualization, and + Comparative Exploration + maintainer: Zhenru Zhou + description: |- + A versatile R visualization package that empowers + researchers with comprehensive visualization tools for seamlessly mapping peptides + to protein sequences, identifying distinct domains and regions of interest, + accentuating mutations, and highlighting post-translational modifications, + all while enabling comparisons across diverse experimental conditions. + Potential applications of 'PepMapViz' include the visualization of cross-software + mass spectrometry results at the peptide level for specific protein and domain + details in a linearized format and post-translational modification coverage + across different experimental conditions; unraveling insights into disease + mechanisms. It also enables visualization of major histocompatibility complex-presented peptides in + different antibody regions predicting immunogenicity in antibody drug development. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PepMapViz + url_git: '' +peppm: + version: 0.0.1 + title: Piecewise Exponential Distribution with Random Time Grids + maintainer: Fabio Demarqui + description: Fits the Piecewise Exponential distribution with random time grids + using the clustering structure of the Product Partition Models. Details of the + implemented model can be found in Demarqui et al. (2008) . + date_publication: '2020-06-25' + bug_reports: https://github.com/fndemarqui/peppm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=peppm + url_git: https://github.com/fndemarqui/peppm +pepr: + version: 0.5.0 + title: Reading Portable Encapsulated Projects + maintainer: Nathan Sheffield + description: |- + A PEP, or Portable Encapsulated Project, is a dataset that + subscribes to the PEP structure for organizing metadata. It is written using + a simple YAML + CSV format, it is your one-stop solution to metadata + management across data analysis environments. This package reads this + standardized project configuration structure into R. + Described in Sheffield et al. (2021) . + date_publication: '2023-11-21' + bug_reports: https://github.com/pepkit/pepr + url: '' + url_cran: https://CRAN.R-project.org/package=pepr + url_git: '' +PepSAVIms: + version: 0.9.1 + title: PepSAVI-MS Data Analysis + maintainer: Pritchard David + description: |- + An implementation of the data processing and data analysis portion + of a pipeline named the PepSAVI-MS which is currently under development by + the Hicks laboratory at the University of North Carolina. The statistical + analysis package presented herein provides a collection of software tools + used to facilitate the prioritization of putative bioactive peptides from a + complex biological matrix. Tools are provided to deconvolute mass + spectrometry features into a single representation for each peptide charge + state, filter compounds to include only those possibly contributing to the + observed bioactivity, and prioritize these remaining compounds for those + most likely contributing to each bioactivity data set. + date_publication: '2016-12-17' + bug_reports: https://github.com/dpritchLibre/PepSAVIms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PepSAVIms + url_git: https://github.com/dpritchLibre/PepSAVIms +Peptides: + version: 2.4.6 + title: |- + Calculate Indices and Theoretical Physicochemical Properties of + Protein Sequences + maintainer: Daniel Osorio + description: Includes functions to calculate several physicochemical properties + and indices for amino-acid sequences as well as to read and plot 'XVG' output + files from the 'GROMACS' molecular dynamics package. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Peptides + url_git: https://github.com/dosorio/Peptides/ +peptoolkit: + version: 0.0.1 + title: A Toolkit for Using Peptide Sequences in Machine Learning + maintainer: Josep-Ramon Codina + description: This toolkit is designed for manipulation and analysis of peptides. + It provides functionalities to assist researchers in peptide engineering and proteomics. + Users can manipulate peptides by adding amino acids at every position, count occurrences + of each amino acid at each position, and transform amino acid counts based on + probabilities. The package offers functionalities to select the best versus the + worst peptides and analyze these peptides, which includes counting specific residues, + reducing peptide sequences, extracting features through One Hot Encoding (OHE), + and utilizing Quantitative Structure-Activity Relationship (QSAR) properties (based + in the package 'Peptides' by Osorio et al. (2015) ). + This package is intended for both researchers and bioinformatics enthusiasts working + on peptide-based projects, especially for their use with machine learning. + date_publication: '2023-07-13' + bug_reports: https://github.com/jrcodina/peptoolkit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=peptoolkit + url_git: https://github.com/jrcodina/peptoolkit +peramo: + version: 0.1.3 + title: Permutation Tests for Randomization Model + maintainer: Duy Nghia Pham + description: |- + Perform permutation-based hypothesis testing for randomized + experiments as suggested in Ludbrook & Dudley (1998) + and Ernst (2004) , introduced in Pham et al. + (2022) . + date_publication: '2023-05-31' + bug_reports: https://github.com/phamdn/peramo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=peramo + url_git: '' +perARMA: + version: '1.7' + title: Periodic Time Series Analysis + maintainer: Karolina Marek + description: |- + Identification, model fitting and estimation for time series with periodic structure. + Additionally, procedures for simulation of periodic processes + and real data sets are included. + Hurd, H. L., Miamee, A. G. (2007) + Box, G. E. P., Jenkins, G. M., Reinsel, G. (1994) + Brockwell, P. J., Davis, R. A. (1991, ISBN:978-1-4419-0319-8) + Bretz, F., Hothorn, T., Westfall, P. (2010, ISBN: 9780429139543) + Westfall, P. H., Young, S. S. (1993, ISBN:978-0-471-55761-6) + Bloomfield, P., Hurd, H. L.,Lund, R. (1994) + + Dehay, D., Hurd, H. L. (1994, ISBN:0-7803-1023-3) + Vecchia, A. (1985) + Vecchia, A. (1985) + Jones, R., Brelsford, W. (1967) + Makagon, A. (1999) + + Sakai, H. (1989) + Gladyshev, E. G. (1961) + + Ansley (1979) + Hurd, H. L., Gerr, N. L. (1991) . + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perARMA + url_git: '' +Perc: + version: 0.1.6 + title: |- + Using Percolation and Conductance to Find Information Flow + Certainty in a Direct Network + maintainer: Jessica Vandeleest + description: |- + To find the certainty of dominance interactions with indirect + interactions being considered. + date_publication: '2021-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Perc + url_git: '' +perccalc: + version: 1.0.5 + title: Estimate Percentiles from an Ordered Categorical Variable + maintainer: Jorge Cimentada + description: An implementation of two functions that estimate values for percentiles + from an ordered categorical variable as described by Reardon (2011, isbn:978-0-87154-372-1). + One function estimates percentile differences from two percentiles while the other + returns the values for every percentile from 1 to 100. + date_publication: '2019-12-17' + bug_reports: '' + url: https://cimentadaj.github.io/perccalc/ + url_cran: https://CRAN.R-project.org/package=perccalc + url_git: https://github.com/cimentadaj/perccalc +PerFit: + version: 1.4.6 + title: Person Fit + maintainer: Jorge N. Tendeiro + description: |- + Several person-fit statistics + (PFSs; Meijer and Sijtsma, 2001, ) + are offered. These statistics allow assessing whether + individual response patterns to tests or questionnaires are (im)plausible given + the other respondents in the sample or given a specified item response theory model. Some PFSs apply to + dichotomous data, such as the likelihood-based PFSs (lz, lz*) and the group-based PFSs + (personal biserial correlation, caution index, (normed) number of Guttman errors, + agreement/disagreement/dependability statistics, U3, ZU3, NCI, Ht). PFSs suitable to polytomous data include + extensions of lz, U3, and (normed) number of Guttman errors. + date_publication: '2021-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PerFit + url_git: '' +PerfMeas: + version: 1.2.5 + title: Performance Measures for Ranking and Classification Tasks + maintainer: Giorgio Valentini + description: Implementation of different performance measures for classification + and ranking tasks including Area Under the Receiving Characteristic Curve (AUROC) + and Area Under the Precision Recall Curve (AUPRC), precision at a given recall, + F-score for single and multiple classes. + date_publication: '2022-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PerfMeas + url_git: '' +performance: + version: 0.13.0 + title: Assessment of Regression Models Performance + maintainer: Daniel Lüdecke + description: |- + Utilities for computing measures to assess model quality, + which are not directly provided by R's 'base' or 'stats' packages. + These include e.g. measures like r-squared, intraclass correlation + coefficient (Nakagawa, Johnson & Schielzeth (2017) + ), root mean squared error or functions to + check models for overdispersion, singularity or zero-inflation and + more. Functions apply to a large variety of regression models, + including generalized linear models, mixed effects models and Bayesian + models. References: Lüdecke et al. (2021) . + date_publication: '2025-01-15' + bug_reports: https://github.com/easystats/performance/issues + url: https://easystats.github.io/performance/ + url_cran: https://CRAN.R-project.org/package=performance + url_git: '' +PerformanceAnalytics: + version: 2.0.8 + title: Econometric Tools for Performance and Risk Analysis + maintainer: Brian G. Peterson + description: |- + Collection of econometric functions for performance and risk + analysis. In addition to standard risk and performance metrics, this + package aims to aid practitioners and researchers in utilizing the latest + research in analysis of non-normal return streams. In general, it is most + tested on return (rather than price) data on a regular scale, but most + functions will work with irregular return data as well, and increasing + numbers of functions will work with P&L or price data where possible. + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PerformanceAnalytics + url_git: https://github.com/braverock/PerformanceAnalytics +performanceEstimation: + version: 1.1.0 + title: |- + An Infra-Structure for Performance Estimation of Predictive + Models + maintainer: Luis Torgo + description: |- + An infra-structure for estimating the predictive performance of + predictive models. In this context, it can also be used to compare and/or select + among different alternative ways of solving one or more predictive tasks. The + main goal of the package is to provide a generic infra-structure to estimate + the values of different metrics of predictive performance using different + estimation procedures. These estimation tasks can be applied to any solutions + (workflows) to the predictive tasks. The package provides easy to use standard + workflows that allow the usage of any available R modeling algorithm together + with some pre-defined data pre-processing steps and also prediction post- + processing methods. It also provides means for addressing issues related with + the statistical significance of the observed differences. + date_publication: '2016-10-13' + bug_reports: https://github.com/ltorgo/performanceEstimation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=performanceEstimation + url_git: https://github.com/ltorgo/performanceEstimation +peRiodiCS: + version: 0.5.0 + title: Functions for Generating Periodic Curves + maintainer: Crt Ahlin + description: |2- + + Functions for generating variants of curves: + restricted cubic spline, periodic restricted cubic spline, + periodic cubic spline. Periodic splines can be used to model data + that has periodic nature / seasonality. + date_publication: '2018-07-05' + bug_reports: https://github.com/crtahlin/peRiodiCS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=peRiodiCS + url_git: '' +PeriodicTable: + version: 0.1.2 + title: Periodic Table of the Elements + maintainer: Julien Idé + description: |- + Provides a dataset containing properties for chemical elements. + Helper functions are also provided to access some atomic properties. + date_publication: '2017-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PeriodicTable + url_git: '' +periscope: + version: 1.0.4 + title: Enterprise Streamlined 'Shiny' Application Framework + maintainer: Constance Brett + description: |- + An enterprise-targeted scalable and UI-standardized 'shiny' framework + including a variety of developer convenience functions with the goal of both + streamlining robust application development while assisting with creating a + consistent user experience regardless of application or developer. + date_publication: '2023-11-06' + bug_reports: https://github.com/cb4ds/periscope/issues + url: http://periscopeapps.org:3838 + url_cran: https://CRAN.R-project.org/package=periscope + url_git: https://github.com/cb4ds/periscope +periscope2: + version: 0.2.3 + title: |- + Enterprise Streamlined 'shiny' Application Framework Using + 'bs4Dash' + maintainer: Mohammed Ali + description: |- + A framework for building enterprise, scalable and UI-standardized 'shiny' applications. + It brings enhanced features such as 'bootstrap' v4 , + additional and enhanced 'shiny' modules, customizable UI features, as well as an enhanced application file + organization paradigm. This update allows developers to harness the ability to build powerful applications and + enriches the 'shiny' developers' experience when building and maintaining applications. + date_publication: '2024-03-06' + bug_reports: https://github.com/Aggregate-Genius/periscope2/issues + url: http://periscopeapps.org:3838 + url_cran: https://CRAN.R-project.org/package=periscope2 + url_git: https://github.com/Aggregate-Genius/periscope2 +PERK: + version: 0.0.9.2 + title: Predicting Environmental Concentration and Risk + maintainer: Kishore Kumar Jagadeesan + description: |- + A Shiny Web Application to predict and visualize concentrations of pharmaceuticals in the aqueous environment. + Jagadeesan K., Barden R. and Kasprzyk-Hordern B. (2022) . + date_publication: '2023-01-25' + bug_reports: https://github.com/jkkishore85/PERK/issues + url: https://jkkishore85.github.io/PERK/ + url_cran: https://CRAN.R-project.org/package=PERK + url_git: https://github.com/jkkishore85/PERK/ +perm: + version: 1.0-0.4 + title: Exact or Asymptotic Permutation Tests + maintainer: Michael P. Fay + description: Perform Exact or Asymptotic permutation tests [see Fay and Shaw ]. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perm + url_git: '' +PermAlgo: + version: '1.2' + title: Permutational Algorithm to Simulate Survival Data + maintainer: Marie-Pierre Sylvestre + description: |- + This version of the permutational algorithm generates a + dataset in which event and censoring times are conditional on + an user-specified list of covariates, some or all of which are + time-dependent. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PermAlgo + url_git: '' +PerMallows: + version: '1.14' + title: Permutations and Mallows Distributions + maintainer: Ekhine Irurozki + description: |- + Includes functions to work with the Mallows and Generalized Mallows + Models. The considered distances are Kendall's-tau, Cayley, Hamming and Ulam + and it includes functions for making inference, sampling and learning such + distributions, some of which are novel in the literature. As a by-product, + PerMallows also includes operations for permutations, paying special attention + to those related with the Kendall's-tau, Cayley, Ulam and Hamming distances. It + is also possible to generate random permutations at a given distance, or with + a given number of inversions, or cycles, or fixed points or even with a given + length on LIS (longest increasing subsequence). + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PerMallows + url_git: '' +PERMANOVA: + version: 0.2.0 + title: |- + Multivariate Analysis of Variance Based on Distances and + Permutations + maintainer: Laura Vicente-Gonzalez + description: Calculates multivariate analysis of variance based on permutations + and some associated pictorial representations. The pictorial representation is + based on the principal coordinates of the group means. There are some original + results that will be published soon. + date_publication: '2021-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PERMANOVA + url_git: '' +PerMat: + version: 0.1.0 + title: Performance Metrics in Predictive Modeling + maintainer: Pankaj Das + description: Performance metric provides different performance measures like mean + squared error, root mean square error, mean absolute deviation, mean absolute + percentage error etc. of a fitted model. These can provide a way for forecasters + to quantitatively compare the performance of competing models. For method details + see (i) Pankaj Das (2020) . + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PerMat + url_git: '' +permChacko: + version: 1.0.1 + title: Chacko Test for Order-Restriction with Permutation + maintainer: Waldir Leoncio + description: |- + Implements an extension of the Chacko chi-square test for + ordered vectors (Chacko, 1966, ). + Our extension brings the Chacko test to the computer age by implementing + a permutation test to offer a numeric estimate of the p-value, which is + particularly useful when the analytic solution is not available. + date_publication: '2024-09-18' + bug_reports: https://github.com/ocbe-uio/permChacko/issues + url: https://ocbe-uio.github.io/permChacko/ + url_cran: https://CRAN.R-project.org/package=permChacko + url_git: '' +PermCor: + version: 0.1.0 + title: Robust Permutation Tests of Correlation Coefficients + maintainer: Mengyu Fang + description: |- + Provides tools for statistical testing of correlation coefficients through robust + permutation method and large sample approximation method. Tailored to different types + of correlation coefficients including Pearson correlation coefficient, weighted + Pearson correlation coefficient, Spearman correlation coefficient, and Lin's + concordance correlation coefficient.The robust permutation test controls type I error + under general scenarios when sample size is small and two variables are dependent but + uncorrelated. The large sample approximation test generally controls type I error when + the sample size is large (>200). + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PermCor + url_git: '' +permGS: + version: 0.2.5 + title: Permutational Group Sequential Test for Time-to-Event Data + maintainer: Matthias Brueckner + description: Permutational group-sequential tests for time-to-event data based on + the log-rank test statistic. Supports exact permutation test when the censoring + distributions are equal in the treatment and the control group and approximate + imputation-permutation methods when the censoring distributions are different. + date_publication: '2017-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=permGS + url_git: '' +permimp: + version: 1.0-2 + title: Conditional Permutation Importance + maintainer: Dries Debeer + description: |- + An add-on to the 'party' package, with a faster implementation + of the partial-conditional permutation importance for random forests. The + standard permutation importance is implemented exactly the same as in + the 'party' package. The conditional permutation importance can be + computed faster, with an option to be backward compatible to the 'party' + implementation. The package is compatible with random forests fit using the + 'party' and the 'randomForest' package. The methods are described in + Strobl et al. (2007) and + Debeer and Strobl (2020) . + date_publication: '2021-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=permimp + url_git: '' +permPATH: + version: '1.3' + title: Permutation Based Gene Expression Pathway Analysis + maintainer: Ivo D. Shterev + description: Can be used to carry out permutation based gene expression pathway + analysis. This work was supported by a National Institute of Allergy and Infectious + Disease/National Institutes of Health contract (No. HHSN272200900059C). + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=permPATH + url_git: '' +perms: + version: '1.14' + title: Fast Permutation Computation + maintainer: Per August Jarval Moen + description: Implements the algorithm of Christensen (2024) + for estimating marginal likelihoods via permutation counting. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perms + url_git: '' +permubiome: + version: 1.3.2 + title: |- + A Permutation Based Test for Biomarker Discovery in Microbiome + Data + maintainer: Alfonso Benitez-Paez + description: 'The permubiome R package was created to perform a permutation-based + non-parametric analysis on microbiome data for biomarker discovery aims. This + test executes thousands of comparisons in a pairwise manner, after a random shuffling + of data into the different groups of study with a prior selection of the microbiome + features with the largest variation among groups. Previous to the permutation + test itself, data can be normalized according to different methods proposed to + handle microbiome data (''proportions'' or ''Anders''). The median-based differences + between groups resulting from the multiple simulations are fitted to a normal + distribution with the aim to calculate their significance. A multiple testing + correction based on Benjamini-Hochberg method (fdr) is finally applied to extract + the differentially presented features between groups of your dataset. LATEST UPDATES: + v1.1 and olders incorporates function to parse COLUMN format; v1.2 and olders + incorporates -optimize- function to maximize evaluation of features with largest + inter-class variation; v1.3 and olders includes the -size.effect- function to + perform estimation statistics using the bootstrap-coupled approach implemented + in the ''dabestr'' (>=0.3.0) R package. Current v1.3.2 fixed bug with "Class" + recognition and updated ''dabestr'' functions.' + date_publication: '2023-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=permubiome + url_git: '' +permuco: + version: 1.1.3 + title: |- + Permutation Tests for Regression, (Repeated Measures) + ANOVA/ANCOVA and Comparison of Signals + maintainer: Jaromil Frossard + description: Functions to compute p-values based on permutation tests. Regression, + ANOVA and ANCOVA, omnibus F-tests, marginal unilateral and bilateral t-tests are + available. Several methods to handle nuisance variables are implemented (Kherad-Pajouh, + S., & Renaud, O. (2010) ; Kherad-Pajouh, S., + & Renaud, O. (2014) ; Winkler, A. M., Ridgway, + G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) ). + An extension for the comparison of signals issued from experimental conditions + (e.g. EEG/ERP signals) is provided. Several corrections for multiple testing are + possible, including the cluster-mass statistic (Maris, E., & Oostenveld, R. (2007) + ) and the threshold-free cluster enhancement + (Smith, S. M., & Nichols, T. E. (2009) ). + date_publication: '2024-08-25' + bug_reports: https://github.com/jaromilfrossard/permuco/issues + url: '' + url_cran: https://CRAN.R-project.org/package=permuco + url_git: https://github.com/jaromilfrossard/permuco +PermutationR: + version: 0.1.0 + title: Conduct Permutation Analysis of Variance in R + maintainer: Osama Abdalla + description: Conduct permutation One-Way or Two-Way Analysis of Variance in R. Use + different permutation types for two-way designs. + date_publication: '2022-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PermutationR + url_git: '' +permutations: + version: 1.1-6 + title: 'The Symmetric Group: Permutations of a Finite Set' + maintainer: Robin K. S. Hankin + description: |- + Manipulates invertible functions from a finite set to + itself. Can transform from word form to cycle form and + back. To cite the package in publications please use + Hankin (2020) "Introducing the permutations R package", + SoftwareX, volume 11 . + date_publication: '2025-02-11' + bug_reports: https://github.com/RobinHankin/permutations/issues + url: https://robinhankin.github.io/permutations/ + url_cran: https://CRAN.R-project.org/package=permutations + url_git: https://github.com/RobinHankin/permutations +permute: + version: 0.9-7 + title: Functions for Generating Restricted Permutations of Data + maintainer: Gavin L. Simpson + description: A set of restricted permutation designs for freely exchangeable, line + transects (time series), and spatial grid designs plus permutation of blocks (groups + of samples) is provided. 'permute' also allows split-plot designs, in which the + whole-plots or split-plots or both can be freely-exchangeable or one of the restricted + designs. The 'permute' package is modelled after the permutation schemes of 'Canoco + 3.1' (and later) by Cajo ter Braak. + date_publication: '2022-01-27' + bug_reports: https://github.com/gavinsimpson/permute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=permute + url_git: https://github.com/gavinsimpson/permute +permutes: + version: '2.8' + title: Permutation Tests for Time Series Data + maintainer: Cesko C. Voeten + description: |- + Helps you determine the analysis window to use when analyzing densely-sampled + time-series data, such as EEG data, using permutation testing (Maris & Oostenveld, 2007) + . These permutation tests can help identify the timepoints + where significance of an effect begins and ends, and the results can be plotted in various + types of heatmap for reporting. Mixed-effects models are supported using an implementation of + the approach by Lee & Braun (2012) . + date_publication: '2023-09-28' + bug_reports: https://gitlab.com/cvoeten/permutes/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=permutes + url_git: '' +permutest: + version: 1.0.0 + title: |- + Run Permutation Tests and Construct Associated Confidence + Intervals + maintainer: Amanda Glazer + description: Implements permutation tests for any test statistic and randomization + scheme and constructs associated confidence intervals as described in Glazer and + Stark (2024) . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=permutest + url_git: '' +perplexR: + version: 0.0.3 + title: A Coding Assistant using Perplexity's Large Language Models + maintainer: Gabriel Kaiser + description: |- + A coding assistant using Perplexity's Large Language Models + API. A set of functions and 'RStudio' add-ins + that aim to help R developers. + date_publication: '2024-03-29' + bug_reports: https://github.com/GabrielKaiserQFin/perplexR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=perplexR + url_git: https://github.com/GabrielKaiserQFin/perplexR +PerRegMod: + version: 4.4.3 + title: Fitting Periodic Coefficients Linear Regression Models + maintainer: Slimane Regui + description: Provides tools for fitting periodic coefficients regression models + to data where periodicity plays a crucial role. It allows users to model and analyze + relationships between variables that exhibit cyclical or seasonal patterns, offering + functions for estimating parameters and testing the periodicity of coefficients + in linear regression models. For simple periodic coefficient regression model + see Regui et al. (2024) . + date_publication: '2024-12-02' + bug_reports: '' + url: https://doi.org/10.1080/03610918.2024.2314662 + url_cran: https://CRAN.R-project.org/package=PerRegMod + url_git: '' +perry: + version: 0.3.1 + title: |- + Resampling-Based Prediction Error Estimation for Regression + Models + maintainer: Andreas Alfons + description: |- + Tools that allow developers to write functions for prediction + error estimation with minimal programming effort and assist users with + model selection in regression problems. + date_publication: '2021-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perry + url_git: '' +perryExamples: + version: 0.1.1 + title: |- + Examples for Integrating Prediction Error Estimation into + Regression Models + maintainer: Andreas Alfons + description: Examples for integrating package 'perry' for prediction error estimation + into regression models. + date_publication: '2021-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perryExamples + url_git: '' +persDx: + version: 0.5.0 + title: |- + Personalized Diagnostics Rules for Subgroup Identification and + Personalized Biomarker Discovery + maintainer: Yunro Chung + description: Tailoring the optimal biomarker(s) for disease screening or diagnosis + based on subjects' individual characteristics. + date_publication: '2023-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=persDx + url_git: '' +PerseusR: + version: 0.3.4 + title: Perseus R Interop + maintainer: Jan Rudolph + description: Enables the interoperability between the Perseus platform for omics + data analysis (Tyanova et al. 2016) and R. It provides + the foundation for developing and running Perseus plugins implemented in R by + providing all required input and output handling, including data and parameter + parsing as described in Rudolph and Cox 2018 . + date_publication: '2018-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PerseusR + url_git: '' +PersianStemmer: + version: '1.0' + title: Persian Stemmer for Text Analysis + maintainer: Roozbeh Safshekan + description: Allows users to stem Persian texts for text analysis. + date_publication: '2019-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PersianStemmer + url_git: '' +PersomicsArray: + version: '1.0' + title: Automated Persomics Array Image Extraction + maintainer: John Smestad + description: |- + Automated identification of printed array positions from high content + microscopy images and the export of those positions as individual images + written to output as multi-layered tiff files. + date_publication: '2016-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PersomicsArray + url_git: '' +personalized: + version: 0.2.7 + title: |- + Estimation and Validation Methods for Subgroup Identification + and Personalized Medicine + maintainer: Jared Huling + description: |- + Provides functions for fitting and validation of models for subgroup + identification and personalized medicine / precision medicine under the general subgroup + identification framework of Chen et al. (2017) . + This package is intended for use for both randomized controlled trials and + observational studies and is described in detail in Huling and Yu (2021) + . + date_publication: '2022-06-27' + bug_reports: https://github.com/jaredhuling/personalized/issues + url: https://jaredhuling.org/personalized/ + url_cran: https://CRAN.R-project.org/package=personalized + url_git: '' +personalized2part: + version: 0.0.1 + title: Two-Part Estimation of Treatment Rules for Semi-Continuous Data + maintainer: Jared Huling + description: |- + Implements the methodology of Huling, Smith, and + Chen (2020) , which allows for subgroup identification + for semi-continuous outcomes by estimating individualized treatment rules. It uses a two-part + modeling framework to handle semi-continuous data by separately modeling the positive part + of the outcome and an indicator of whether each outcome is positive, but still results in a + single treatment rule. High dimensional data is handled with a cooperative lasso penalty, + which encourages the coefficients in the two models to have the same sign. + date_publication: '2020-09-10' + bug_reports: https://github.com/jaredhuling/personalized2part/issues + url: '' + url_cran: https://CRAN.R-project.org/package=personalized2part + url_git: https://github.com/jaredhuling/personalized2part +personalr: + version: 1.0.3 + title: Automated Personal Package Setup + maintainer: Sebastian Carl + description: |- + Functions to setup a personal R package that attaches given + libraries and exports personal helper functions. + date_publication: '2022-08-11' + bug_reports: https://github.com/mrcaseb/personalr/issues + url: https://mrcaseb.github.io/personalr/index.html + url_cran: https://CRAN.R-project.org/package=personalr + url_git: https://github.com/mrcaseb/personalr +personr: + version: 1.0.0 + title: Test Your Personality + maintainer: Renfei Mao + description: |- + An R-package-version of an open online science-based personality + test from , + providing a better-designed interface and a more detailed report. + The core command launch_test() opens a personality test in your browser, + and generates a report after you click "Submit". In this report, your results + are compared with other people's, to show what these results mean. + Other people's data is from . + date_publication: '2020-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=personr + url_git: https://github.com/flujoo/personr +perspectev: + version: '1.1' + title: Permutation of Species During Turnover Events + maintainer: Kenneth B. Hoehn + description: 'Provides a robust framework for analyzing the extent to which differential + survival with respect to higher level trait variation is reducible to lower level + variation. In addition to its primary test, it also provides functions for simulation-based + power analysis, reading in common data set formats, and visualizing results. Temporarily + contains an edited version of function hr.mcp() from package ''wild1'', written + by Glen Sargeant. For tutorial see: http://evolve.zoo.ox.ac.uk/Evolve/Perspectev.html.' + date_publication: '2015-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perspectev + url_git: '' +persval: + version: 1.1.1 + title: Computing Personal Values Scores + maintainer: Giuseppe Corbelli + description: |- + Compute personal values scores from various questionnaires based on the theoretical constructs proposed by professor Shalom H. Schwartz. Designed for researchers and practitioners in psychology, sociology, and related fields, the package facilitates the quantification and visualization of different dimensions related to personal values from survey data. It incorporates the recommended statistical adjustment to enhance the accuracy and interpretation of the results. + Note: The package 'persval' is independently developed based on the personal values theoretical framework, and is not directly endorsed by professor Schwartz. + date_publication: '2024-09-25' + bug_reports: https://github.com/g-corbelli/persval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=persval + url_git: https://github.com/g-corbelli/persval +perturbR: + version: 0.1.3 + title: Random Perturbation of Count Matrices + maintainer: KM Gates + description: |- + The perturbR() function incrementally perturbs network edges (using the rewireR function)and compares the resulting community detection solutions + from the rewired networks with the solution found for the original network. + These comparisons aid in understanding the stability of the + original solution. The package requires symmetric, weighted (specifically, count) matrices/networks. + date_publication: '2019-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=perturbR + url_git: '' +peruflorads43: + version: 0.1.1 + title: |- + Reviewed Official Classification of Endangered Wild Flora + Species in Peru + maintainer: Paul E. Santos Andrade + description: Provide users with a convenient way to access and analyze information + on endangered plant species in Peru based on `Decreto Supremo N 043-2006-AG - + Aprueban categorizacion de especies amenazadas de flora silvestre`. + date_publication: '2023-08-21' + bug_reports: https://github.com/PaulESantos/peruflorads43/issues + url: https://paulesantos.github.io/peruflorads43/ + url_cran: https://CRAN.R-project.org/package=peruflorads43 + url_git: https://github.com/PaulESantos/peruflorads43 +peruse: + version: 0.3.1 + title: A Tidy API for Sequence Iteration and Set Comprehension + maintainer: Jacob Goldsmith + description: A friendly API for sequence iteration and set comprehension. + date_publication: '2021-03-08' + bug_reports: https://github.com/jacgoldsm/peruse/issues + url: https://jacgoldsm.github.io/peruse/ + url_cran: https://CRAN.R-project.org/package=peruse + url_git: https://github.com/jacgoldsm/peruse +perutimber: + version: 0.1.0 + title: Catalogue of the Timber Forest Species of the Peruvian Amazon + maintainer: Paul E. Santos Andrade + description: Access the data of the 'Catalogue of the Timber Forest Species of the + Peruvian Amazon' Vásquez Martínez, R., & Rojas Gonzáles, R.D.P.(2022). + date_publication: '2023-09-20' + bug_reports: https://github.com/PaulESantos/perutimber/issues + url: https://paulesantos.github.io/perutimber/ + url_cran: https://CRAN.R-project.org/package=perutimber + url_git: https://github.com/PaulESantos/perutimber +pesel: + version: 0.7.5 + title: Automatic Estimation of Number of Principal Components in PCA + maintainer: Piotr Sobczyk + description: |- + Automatic estimation of number of principal components in PCA + with PEnalized SEmi-integrated Likelihood (PESEL). See Piotr Sobczyk, Malgorzata Bogdan, Julie Josse + "Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood" + (2017) . + date_publication: '2023-10-17' + bug_reports: https://github.com/psobczyk/pesel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pesel + url_git: https://github.com/psobczyk/pesel +PesticideLoadIndicator: + version: 1.3.1 + title: Computes Danish Pesticide Load Indicator + maintainer: Niklas Moehring + description: Computes the Danish Pesticide Load Indicator as described in Kudsk + et al. (2018) and Moehring et al. (2019) + for pesticide use data. Additionally offers + the possibility to directly link pesticide use data to pesticide properties given + access to the Pesticide properties database (Lewis et al., 2016) . + date_publication: '2022-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PesticideLoadIndicator + url_git: '' +pestr: + version: 0.8.2 + title: Interface to Download Data on Pests and Hosts from 'EPPO' + maintainer: Michal Jan Czyz + description: |- + Set of tools to automatize extraction of data on pests from 'EPPO + Data Services' and 'EPPO Global Database' and to put them into tables with + human readable format. Those function use 'EPPO database API', thus you + first need to register on (free of charge). + Additional helpers allow to download, check and connect to + 'SQLite EPPO database'. + date_publication: '2021-01-20' + bug_reports: https://github.com/mczyzj/pestr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pestr + url_git: https://github.com/mczyzj/pestr +Petersen: + version: 2025.3.1 + title: Estimators for Two-Sample Capture-Recapture Studies + maintainer: Carl Schwarz + description: |- + A comprehensive implementation of Petersen-type estimators + and its many variants for two-sample capture-recapture studies. + A conditional likelihood approach is used that allows + for tag loss; non reporting of tags; reward tags; categorical, geographical and temporal stratification; + partial stratification; reverse capture-recapture; + and continuous variables in modeling the probability of capture. + Many examples from fisheries management are presented. + date_publication: '2025-02-24' + bug_reports: https://github.com/cschwarz-stat-sfu-ca/Petersen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Petersen + url_git: https://github.com/cschwarz-stat-sfu-ca/Petersen +petersenlab: + version: 1.1.0 + title: A Collection of R Functions by the Petersen Lab + maintainer: Isaac T. Petersen + description: |- + A collection of R functions that are widely used by the Petersen + Lab. Included are functions for various purposes, including evaluating the + accuracy of judgments and predictions, performing scoring of assessments, + generating correlation matrices, conversion of data between various types, + data management, psychometric evaluation, extensions related to latent + variable modeling, various plotting capabilities, and other miscellaneous + useful functions. By making the package available, we hope to make our + methods reproducible and replicable by others and to help others perform + their data processing and analysis methods more easily and efficiently. The + codebase is provided in Petersen (2024) and on + CRAN: . The package is described in + "Principles of Psychological Assessment: With Applied Examples in R" + (Petersen, 2024, 2025) , + , . + date_publication: '2025-02-03' + bug_reports: https://github.com/DevPsyLab/petersenlab/issues + url: https://devpsylab.github.io/petersenlab/ + url_cran: https://CRAN.R-project.org/package=petersenlab + url_git: https://github.com/DevPsyLab/petersenlab +PEtests: + version: 0.1.0 + title: Power-Enhanced (PE) Tests for High-Dimensional Data + maintainer: Xiufan Yu + description: |- + Two-sample power-enhanced mean tests, covariance tests, and simultaneous tests on mean vectors and covariance matrices for high-dimensional data. Methods of these PE tests are presented in + Yu, Li, and Xue (2022) ; + Yu, Li, Xue, and Li (2022) . + date_publication: '2023-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PEtests + url_git: '' +PetfindeR: + version: 2.1.0 + title: '''Petfinder'' API Wrapper' + maintainer: Aaron Schlegel + description: |2- + + Wrapper of the 'Petfinder API' that implements + methods for interacting with and extracting data from the 'Petfinder' database. The 'Petfinder + REST API' allows access to the 'Petfinder' database, one of the largest online databases of + adoptable animals and animal welfare organizations across North America. + date_publication: '2020-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PetfindeR + url_git: https://github.com/aschleg/PetfindeR +petitr: + version: '1.0' + title: Relative Growth Rate + maintainer: Jean-Sebastien Pierre + description: 'Calculates the relative growth rate (RGR) of a series of individuals + by building a life table and solving the Lotka-Birch equation. (See Birch, L. + C. 1948. The intrinsic rate of natural increase of an insect population. - Journal + of Animal Ecology 17: 15-26) .' + date_publication: '2018-03-16' + bug_reports: '' + url: none + url_cran: https://CRAN.R-project.org/package=petitr + url_git: '' +petrinetR: + version: 0.3.0 + title: Building, Visualizing, Exporting and Replaying Petri Nets + maintainer: Gert Janssenswillen + description: |- + Functions for the construction of Petri Nets. Petri Nets can be replayed by firing enabled transitions. + Silent transitions will be hidden by the execution handler. Also includes functionalities for the visualization of Petri Nets and + export of Petri Nets to PNML (Petri Net Markup Language) files. + date_publication: '2023-04-03' + bug_reports: https://github.com/bupaverse/petrinetR/issues + url: https://bupar.net + url_cran: https://CRAN.R-project.org/package=petrinetR + url_git: https://github.com/bupaverse/petrinetR +pewdata: + version: 0.3.2 + title: Reproducible Retrieval of Pew Research Center Datasets + maintainer: Frederick Solt + description: |- + Reproducible, programmatic retrieval of survey datasets from the + Pew Research Center. + date_publication: '2021-04-08' + bug_reports: https://github.com/fsolt/pewdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pewdata + url_git: https://github.com/fsolt/pewdata +pexm: + version: 1.1.3 + title: Loading a JAGS Module for the Piecewise Exponential Distribution + maintainer: Vinicius Mayrink + description: Load the Just Another Gibbs Sampling (JAGS) module 'pexm'. The module + provides the tools to work with the Piecewise Exponential (PE) distribution in + a Bayesian model with the corresponding Markov Chain Monte Carlo algorithm (Gibbs + Sampling) implemented via JAGS. Details about the module implementation can be + found in Mayrink et al. (2021) . + date_publication: '2023-11-29' + bug_reports: https://github.com/vdinizm/pexm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pexm + url_git: https://github.com/vdinizm/pexm +pez: + version: 1.2-4 + title: Phylogenetics for the Environmental Sciences + maintainer: William D. Pearse + description: |- + Eco-phylogenetic and community phylogenetic analyses. + Keeps community ecological and phylogenetic data matched up and + comparable using 'comparative.comm' objects. Wrappers for common + community phylogenetic indices ('pez.shape', 'pez.evenness', + 'pez.dispersion', and 'pez.dissimilarity' metrics). Implementation + of Cavender-Bares (2004) correlation of phylogenetic and + ecological matrices ('fingerprint.regression'). Phylogenetic + Generalised Linear Mixed Models (PGLMMs; 'pglmm') following Ives & + Helmus (2011) and Rafferty & Ives (2013). Simulation of null + assemblages, traits, and phylogenies ('scape', 'sim.meta.comm'). + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pez + url_git: '' +pfica: + version: 0.1.3 + title: Independent Components Analysis Techniques for Functional Data + maintainer: Marc Vidal + description: |- + Performs smoothed (and non-smoothed) principal/independent components analysis + of functional data. Various functional pre-whitening approaches are implemented as + discussed in Vidal and Aguilera (2022) “Novel whitening approaches in functional + settings", . Further whitening representations of functional + data can be derived in terms of a few principal components, providing an avenue + to explore hidden structures in low dimensional settings: see Vidal, + Rosso and Aguilera (2021) “Bi-smoothed functional independent component + analysis for EEG artifact removal”, . + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pfica + url_git: https://github.com/m-vidal/pfica +PFIM: + version: '6.1' + title: Population Fisher Information Matrix + maintainer: Romain Leroux + description: |- + Evaluate or optimize designs for nonlinear mixed effects models using the Fisher Information matrix. Methods used in the package refer to + Mentré F, Mallet A, Baccar D (1997) , + Retout S, Comets E, Samson A, Mentré F (2007) , + Bazzoli C, Retout S, Mentré F (2009) , + Le Nagard H, Chao L, Tenaillon O (2011) , + Combes FP, Retout S, Frey N, Mentré F (2013) and + Seurat J, Tang Y, Mentré F, Nguyen TT (2021) . + date_publication: '2024-10-23' + bug_reports: '' + url: http://www.pfim.biostat.fr/ + url_cran: https://CRAN.R-project.org/package=PFIM + url_git: '' +PFLR: + version: 1.1.0 + title: Estimating Penalized Functional Linear Regression + maintainer: Haolun Shi + description: Implementation of commonly used penalized functional linear regression + models, including the Smooth and Locally Sparse (SLoS) method by Lin et al. (2016) + , Nested Group bridge Regression (NGR) method + by Guan et al. (2020) , Functional Linear Regression + That's interpretable (FLIRTI) by James et al. (2009) , + and the Penalized B-spline regression method. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PFLR + url_git: '' +pfr: + version: 1.0.1 + title: Interface to the 'C++' Library 'Pf' + maintainer: Taylor Brown + description: |- + Builds and runs 'c++' code for classes that encapsulate state space model, particle filtering algorithm pairs. + Algorithms include the Bootstrap Filter from Gordon et al. (1993) , the generic SISR filter, + the Auxiliary Particle Filter from Pitt et al (1999) , and a variety of Rao-Blackwellized + particle filters inspired by Andrieu et al. (2002) . For more details on the 'c++' library + 'pf', see Brown (2020) . + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pfr + url_git: '' +pg: + version: 0.2.4 + title: Polya Gamma Distribution Sampler + maintainer: James Balamuta + description: |- + Provides access to a high performant random distribution + sampler for the Polya Gamma Distribution using either 'C++' headers for + 'Rcpp' or 'RcppArmadillo' and 'R'. + date_publication: '2023-07-22' + bug_reports: https://github.com/tmsalab/pg/issues + url: https://tmsalab.github.io/pg/ + url_cran: https://CRAN.R-project.org/package=pg + url_git: https://github.com/tmsalab/pg +PGaGEV: + version: 0.1.0 + title: Power Garima-Generalized Extreme Value Distribution + maintainer: Kittipong Klinjan + description: |- + Density, distribution function, quantile function, + and random generation function based on Kittipong Klinjan,Tipat Sottiwan and Sirinapa Aryuyuen (2024). + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PGaGEV + url_git: '' +pgam: + version: 0.4.17 + title: Poisson-Gamma Additive Models + maintainer: Washington Junger + description: This work is an extension of the state space model for Poisson count + data, Poisson-Gamma model, towards a semiparametric specification. Just like the + generalized additive models (GAM), cubic splines are used for covariate smoothing. + The semiparametric models are fitted by an iterative process that combines maximization + of likelihood and backfitting algorithm. + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgam + url_git: '' +pgdraw: + version: '1.1' + title: Generate Random Samples from the Polya-Gamma Distribution + maintainer: Daniel F. Schmidt + description: Generates random samples from the Polya-Gamma distribution using an + implementation of the algorithm described in J. Windle's PhD thesis (2013) . + The underlying implementation is in C. + date_publication: '2019-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgdraw + url_git: '' +PGEE: + version: '1.5' + title: Penalized Generalized Estimating Equations in High-Dimension + maintainer: Gul Inan + description: Fits penalized generalized estimating equations to longitudinal data + with high-dimensional covariates. + date_publication: '2017-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PGEE + url_git: '' +pgee.mixed: + version: 0.1.0 + title: |- + Penalized Generalized Estimating Equations for Bivariate Mixed + Outcomes + maintainer: Ved Deshpande + description: |- + Perform simultaneous estimation and variable selection for correlated bivariate + mixed outcomes (one continuous outcome and one binary outcome per cluster) using + penalized generalized estimating equations. In addition, clustered Gaussian and binary + outcomes can also be modeled. The SCAD, MCP, and LASSO penalties are supported. + Cross-validation can be performed to find the optimal regularization parameter(s). + date_publication: '2016-12-21' + bug_reports: http://github.com/kaos42/pgee.mixed/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pgee.mixed + url_git: http://github.com/kaos42/pgee.mixed +pgenlibr: + version: 0.4.0 + title: PLINK 2 Binary (.pgen) Reader + maintainer: Christopher Chang + description: |- + A thin wrapper over PLINK 2's core libraries which provides an R + interface for reading .pgen files. A minimal .pvar loader is also + included. Chang et al. (2015) \doi{10.1186/s13742-015-0047-8}. + date_publication: '2025-01-15' + bug_reports: https://github.com/chrchang/plink-ng/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pgenlibr + url_git: '' +pgirmess: + version: 2.0.3 + title: Spatial Analysis and Data Mining for Field Ecologists + maintainer: Patrick Giraudoux + description: Set of tools for reading, writing and transforming spatial and seasonal + data, model selection and specific statistical tests for ecologists. It includes + functions to interpolate regular positions of points between landmarks, to discretize + polylines into regular point positions, link distant observations to points and + convert a bounding box in a spatial object. It also provides miscellaneous functions + for field ecologists such as spatial statistics and inference on diversity indexes, + writing data.frame with Chinese characters. + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgirmess + url_git: https://github.com/pgiraudoux/pgirmess +pgKDEsphere: + version: 1.0.1 + title: |- + Parametrically Guided Kernel Density Estimator for Spherical + Data + maintainer: María Alonso-Pena + description: Nonparametric density estimation for (hyper)spherical data by means + of a parametrically guided kernel estimator (adaptation of the method of Hjort + and Glad (1995) to the spherical setting). The package + also allows the data-driven selection of the smoothing parameter and the representation + of the estimated density for circular and spherical data. Estimators of the density + without guide can also be obtained. + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgKDEsphere + url_git: '' +pglm: + version: 0.2-3 + title: Panel Generalized Linear Models + maintainer: Yves Croissant + description: |- + Estimation of panel models for glm-like models: + this includes binomial models (logit and probit), count models (poisson and negbin) + and ordered models (logit and probit), as described in: + Baltagi (2013) Econometric Analysis of Panel Data, ISBN-13:978-1-118-67232-7, + Hsiao (2014) Analysis of Panel Data and + Croissant and Millo (2018), Panel Data Econometrics with R, ISBN:978-1-118-94918-4. + date_publication: '2021-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pglm + url_git: '' +PGM2: + version: 1.0-1 + title: Nested Resolvable Designs and their Associated Uniform Designs + maintainer: Mohamed Laib + description: |- + Construction method of nested resolvable designs from + a projective geometry defined on Galois field of order 2. The obtained + Resolvable designs are used to build uniform design. The presented results + are based on and A. Boudraa et al. (See references). + date_publication: '2016-12-17' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=PGM2 + url_git: '' +pgmm: + version: 1.2.7 + title: Parsimonious Gaussian Mixture Models + maintainer: Paul D. McNicholas + description: Carries out model-based clustering or classification using parsimonious + Gaussian mixture models. McNicholas and Murphy (2008) , + McNicholas (2010) , McNicholas and Murphy (2010) + , McNicholas et al. (2010) . + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgmm + url_git: '' +pgnorm: + version: '2.0' + title: The p-Generalized Normal Distribution + maintainer: Steve Kalke + description: |- + Evaluation of the pdf and the cdf of the univariate, + noncentral, p-generalized normal distribution. Sampling from + the univariate, noncentral, p-generalized normal distribution + using either the p-generalized polar method, the p-generalized + rejecting polar method, the Monty Python method, the Ziggurat + method or the method of Nardon and Pianca. The package also + includes routines for the simulation of the bivariate, + p-generalized uniform distribution and the simulation of the + corresponding angular distribution. + date_publication: '2015-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgnorm + url_git: '' +pGPx: + version: 0.1.4 + title: Pseudo-Realizations for Gaussian Process Excursions + maintainer: Dario Azzimonti + description: Computes pseudo-realizations from the posterior distribution of a Gaussian + Process (GP) with the method described in Azzimonti et al. (2016) . + The realizations are obtained from simulations of the field at few well chosen + points that minimize the expected distance in measure between the true excursion + set of the field and the approximate one. Also implements a R interface for (the + main function of) Distance Transform of sampled Functions (). + date_publication: '2023-08-23' + bug_reports: '' + url: https://doi.org/10.1137/141000749 + url_cran: https://CRAN.R-project.org/package=pGPx + url_git: '' +pgraph: + version: '1.6' + title: Build Dependency Graphs using Projection + maintainer: Yang Feng + description: Implements a general framework for creating dependency graphs using + projection as introduced in Fan, Feng and Xia (2019). Both lasso + and sparse additive model projections are implemented. Both Pearson correlation + and distance covariance options are available to generate the graph. + date_publication: '2020-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgraph + url_git: '' +PGRdup: + version: 0.2.3.9 + title: |- + Discover Probable Duplicates in Plant Genetic Resources + Collections + maintainer: J. Aravind + description: |- + Provides functions to aid the identification of probable/possible + duplicates in Plant Genetic Resources (PGR) collections using + 'passport databases' comprising of information records of each constituent + sample. These include methods for cleaning the data, creation of a + searchable Key Word in Context (KWIC) index of keywords associated with + sample records and the identification of nearly identical records with + similar information by fuzzy, phonetic and semantic matching of keywords. + date_publication: '2023-08-31' + bug_reports: https://github.com/aravind-j/PGRdup/issues + url: https://doi.org/10.5281/zenodo.841963 + url_cran: https://CRAN.R-project.org/package=PGRdup + url_git: https://github.com/aravind-j/PGRdup +pGRN: + version: 0.3.5 + title: |- + Single-Cell RNA Sequencing Pseudo-Time Based Gene Regulatory + Network Inference + maintainer: Gangcai Xie + description: Inference and visualize gene regulatory network based on single-cell + RNA sequencing pseudo-time information. + date_publication: '2023-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pGRN + url_git: '' +pgsc: + version: 1.0.0 + title: Computes Powell's Generalized Synthetic Control Estimator + maintainer: Philip Barrett + description: |- + Computes the generalized synthetic control estimator described in + Powell (2017) . Provides both point estimates, and hypothesis testing. + date_publication: '2018-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pgsc + url_git: https://github.com/philipbarrett/pgsc +pgTools: + version: 1.0.2 + title: Functions for Generating PostgreSQL Statements/Scripts + maintainer: Timothy Conwell + description: |- + Create PostgreSQL statements/scripts from R, optionally executing the SQL statements. + Common SQL operations are included, although not every configurable option is available at this time. + SQL output is intended to be compliant with PostgreSQL syntax specifications. PostgreSQL documentation is available here + . + date_publication: '2023-03-24' + bug_reports: https://github.com/tconwell/pgTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pgTools + url_git: https://github.com/tconwell/pgTools +PH1XBAR: + version: 0.11.2 + title: Phase I Shewhart X-Bar Chart + maintainer: Yuhui Yao + description: 'The purpose of ''PH1XBAR'' is to build a Phase I Shewhart control + chart for the basic Shewhart, the variance components and the ARMA models in R + for subgrouped and individual data. More details can be found: Yao and Chakraborti + (2020) , Yao and Chakraborti (2021) , + and Yao et al. (2023) .' + date_publication: '2024-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PH1XBAR + url_git: https://github.com/bolus123/PH1XBAR +ph2bayes: + version: 0.0.2 + title: Bayesian Single-Arm Phase II Designs + maintainer: Kengo Nagashima + description: |- + An implementation of Bayesian single-arm phase II design methods for binary outcome based on posterior + probability (Thall and Simon (1994) ) and predictive probability (Lee and Liu (2008) ). + date_publication: '2018-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ph2bayes + url_git: '' +ph2bye: + version: 0.1.4 + title: Phase II Clinical Trial Design Using Bayesian Methods + maintainer: Yalin Zhu + description: |- + Calculate the Bayesian posterior/predictive probability and + determine the sample size and stopping boundaries for single-arm Phase II design. + date_publication: '2016-08-21' + bug_reports: '' + url: https://allen.shinyapps.io/BayesDesign/ + url_cran: https://CRAN.R-project.org/package=ph2bye + url_git: '' +ph2mult: + version: 0.1.1 + title: Phase II Clinical Trial Design for Multinomial Endpoints + maintainer: Yalin Zhu + description: 'Provide multinomial design methods under intersection-union test (IUT) + and union-intersection test (UIT) scheme for Phase II trial. The design types + include : Minimax (minimize the maximum sample size), Optimal (minimize the expected + sample size), Admissible (minimize the Bayesian risk) and Maxpower (maximize the + exact power level).' + date_publication: '2016-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ph2mult + url_git: '' +phacking: + version: 0.2.1 + title: Sensitivity Analysis for p-Hacking in Meta-Analyses + maintainer: Peter Solymos + description: |- + Fits right-truncated meta-analysis (RTMA), a bias correction for + the joint effects of p-hacking (i.e., manipulation of results within studies + to obtain significant, positive estimates) and traditional publication bias + (i.e., the selective publication of studies with significant, positive + results) in meta-analyses [see Mathur MB (2022). "Sensitivity analysis for + p-hacking in meta-analyses." .]. Unlike publication + bias alone, p-hacking that favors significant, positive results (termed + "affirmative") can distort the distribution of affirmative results. To + bias-correct results from affirmative studies would require strong assumptions + on the exact nature of p-hacking. In contrast, joint p-hacking and publication + bias do not distort the distribution of published nonaffirmative results when + there is stringent p-hacking (e.g., investigators who hack always eventually + obtain an affirmative result) or when there is stringent publication bias + (e.g., nonaffirmative results from hacked studies are never published). This + means that any published nonaffirmative results are from unhacked studies. + Under these assumptions, RTMA involves analyzing only the published + nonaffirmative results to essentially impute the full underlying distribution + of all results prior to selection due to p-hacking and/or publication bias. + The package also provides diagnostic plots described in Mathur (2022). + date_publication: '2023-07-17' + bug_reports: https://github.com/mathurlabstanford/phacking/issues + url: https://mathurlabstanford.github.io/phacking/ + url_cran: https://CRAN.R-project.org/package=phacking + url_git: https://github.com/mathurlabstanford/phacking +PhageCocktail: + version: 1.0.3 + title: Design of the Best Phage Cocktail + maintainer: Maria Victoria Diaz-Galian + description: |- + There are 4 possible methods: "ExhaustiveSearch"; "ExhaustivePhi"; "ClusteringSearch"; and "ClusteringPhi". + "ExhaustiveSearch"--> gives you the best phage cocktail from a phage-bacteria + infection network. It checks different phage cocktail sizes from 1 to 7 and + only stops before if it lyses all bacteria. Other option is when users have + decided not to obtain a phage cocktail size higher than a limit value. + "ExhaustivePhi"--> firstly, it finds Phi out. Phi is a formula + indicating the necessary phage cocktail size. Phi needs nestedness temperature + and fill, which are internally calculated. This function will only look for the + best combination (phage cocktail) with a Phi size. + "ClusteringSearch"--> firstly, an agglomerative hierarchical clustering using + Ward's algorithm is calculated for phages. They will be clustered according to + bacteria lysed by them. PhageCocktail() chooses how many clusters are needed in + order to select 1 phage per cluster. Using the phages selected during the + clustering, it checks different phage cocktail sizes from 1 to 7 and only stops + before if it lyses all bacteria. Other option is when users have decided not to + obtain a phage cocktail size higher than a limit value. + "ClusteringPhi"--> firstly, an agglomerative hierarchical clustering using Ward's + algorithm is calculated for phages. They will be clustered according to bacteria + lysed by them. PhageCocktail() chooses how many clusters are needed in order to + select 1 phage per cluster. Once the function has one phage per cluster, it + calculates Phi. If the number of clusters is less than Phi number, it will be + changed to obtain, as minimum, this quantity of candidates (phages). Then, it + calculates the best combination of Phi phages using those selected during the + clustering with Ward algorithm. + If you use PhageCocktail, please cite it as: + "PhageCocktail: An R Package to Design Phage Cocktails from Experimental + Phage-Bacteria Infection Networks". María Victoria Díaz-Galián, Miguel A. + Vega-Rodríguez, Felipe Molina. Computer Methods and Programs in Biomedicine, + 221, 106865, Elsevier Ireland, Clare, Ireland, 2022, pp. 1-9, ISSN: 0169-2607. + . + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PhageCocktail + url_git: '' +phangorn: + version: 2.12.1 + title: Phylogenetic Reconstruction and Analysis + maintainer: Klaus Schliep + description: |- + Allows for estimation of phylogenetic trees and networks + using Maximum Likelihood, Maximum Parsimony, distance methods and + Hadamard conjugation (Schliep 2011). Offers methods for tree comparison, + model selection and visualization of phylogenetic networks as described in + Schliep et al. (2017). + date_publication: '2024-09-17' + bug_reports: https://github.com/KlausVigo/phangorn/issues + url: https://klausvigo.github.io/phangorn/ + url_cran: https://CRAN.R-project.org/package=phangorn + url_git: https://github.com/KlausVigo/phangorn +phantSEM: + version: 1.0.0.0 + title: |- + Create Phantom Variables in Structural Equation Models for + Sensitivity Analyses + maintainer: Alexis Georgeson + description: Create phantom variables, which are variables that were not observed, + for the purpose of sensitivity analyses for structural equation models. The package + makes it easier for a user to test different combinations of covariances between + the phantom variable(s) and observed variables. The package may be used to assess + a model's or effect's sensitivity to temporal bias (e.g., if cross-sectional data + were collected) or confounding bias. + date_publication: '2023-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phantSEM + url_git: '' +pharmaRTF: + version: 0.1.4 + title: Enhanced RTF Wrapper for Use with Existing Table Packages + maintainer: Michael Stackhouse + description: |- + Enhanced RTF wrapper written in R for use with existing R tables + packages such as 'Huxtable' or 'GT'. This package fills a gap where tables in + certain packages can be written out to RTF, but cannot add certain metadata + or features to the document that are required/expected in a report for a + regulatory submission, such as multiple levels of titles and footnotes, + making the document landscape, and controlling properties such as margins. + date_publication: '2021-09-28' + bug_reports: https://github.com/atorus-research/pharmaRTF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pharmaRTF + url_git: '' +pharmaverse: + version: 0.0.2 + title: Navigate 'Pharmaverse' + maintainer: Ari Siggaard Knoph + description: |- + The 'pharmaverse' is a set of packages that compose multiple pathways + through clinical data generation and reporting in the pharmaceutical industry. + This package is designed to guide users to our work-spaces on 'GitHub', 'Slack' + and 'LinkedIn' as well as our website and examples. + Learn more about the 'pharmaverse' at . + date_publication: '2023-03-15' + bug_reports: https://github.com/pharmaverse/pharmaverse-pkg/issues + url: https://pharmaverse.org + url_cran: https://CRAN.R-project.org/package=pharmaverse + url_git: https://github.com/pharmaverse/pharmaverse-pkg +pharmaverseadam: + version: 1.1.0 + title: ADaM Test Data for the 'Pharmaverse' Family of Packages + maintainer: Edoardo Mancini + description: |- + A set of Analysis Data Model (ADaM) datasets constructed using the + Study Data Tabulation Model (SDTM) datasets contained in the 'pharmaversesdtm' package and + the template scripts from the 'admiral' family of packages. ADaM dataset specifications + are described in the CDISC ADaM implementation guide, accessible by creating a free account on . + date_publication: '2024-10-25' + bug_reports: '' + url: https://pharmaverse.github.io/pharmaverseadam/ + url_cran: https://CRAN.R-project.org/package=pharmaverseadam + url_git: https://github.com/pharmaverse/pharmaverseadam/ +pharmaversesdtm: + version: 1.2.0 + title: SDTM Test Data for the 'Pharmaverse' Family of Packages + maintainer: Edoardo Mancini + description: |- + A set of Study Data Tabulation Model (SDTM) datasets from the Clinical + Data Interchange Standards Consortium (CDISC) pilot project used for testing + and developing Analysis Data Model (ADaM) datasets inside the pharmaverse + family of packages. SDTM dataset specifications are described in the CDISC SDTM implementation guide, + accessible by creating a free account on . + date_publication: '2025-01-23' + bug_reports: '' + url: https://pharmaverse.github.io/pharmaversesdtm/ + url_cran: https://CRAN.R-project.org/package=pharmaversesdtm + url_git: https://github.com/pharmaverse/pharmaversesdtm/ +pharmr: + version: 1.4.0 + title: Interface to the 'Pharmpy' 'Pharmacometrics' Library + maintainer: Rikard Nordgren + description: Interface to the 'Pharmpy' 'pharmacometrics' library. The 'Reticulate' + package is used to interface Python from R. + date_publication: '2024-12-04' + bug_reports: https://github.com/pharmpy/pharmr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pharmr + url_git: https://github.com/pharmpy/pharmr +phase: + version: 1.2.9 + title: Analyse Biological Time-Series Data + maintainer: Lakshman Abhilash + description: 'Compiles functions to trim, bin, visualise, and analyse activity/sleep + time-series data collected from the Drosophila Activity Monitor (DAM) system (Trikinetics, + USA). The following methods were used to compute periodograms - Chi-square periodogram: + Sokolove and Bushell (1978) , Lomb-Scargle periodogram: + Lomb (1976) , Scargle (1982) and + Ruf (1999) , and Autocorrelation: Eijzenbach et + al. (1986) . Identification of activity + peaks is done after using a Savitzky-Golay filter (Savitzky and Golay (1964) ) + to smooth raw activity data. Three methods to estimate anticipation of activity + are used based on the following papers - Slope method: Fernandez et al. (2020) + , Harrisingh method: Harrisingh et al. (2007) , + and Stoleru method: Stoleru et al. (2004) . Rose plots + and circular analysis are based on methods from - Batschelet (1981) + and Zar (2010) .' + date_publication: '2023-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phase + url_git: '' +Phase123: + version: '2.1' + title: Simulating and Conducting Phase 123 Trials + maintainer: Andrew G Chapple + description: Contains three simulation functions for implementing the entire Phase + 123 trial and the separate Eff-Tox and Phase 3 portions of the trial, which may + be beneficial for use on clusters. The functions AssignEffTox() and RandomizeEffTox() + assign doses to patient cohorts during phase 12 and Reoptimize() determines the + optimal dose to continue with during Phase 3. The functions ReturnMeansAgent() + and ReturnMeanControl() gives the true mean survival for the agent doses and control + and ReturnOCS() gives the operating characteristics of the design. + date_publication: '2019-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Phase123 + url_git: '' +Phase12Compare: + version: '1.5' + title: |- + Simulates SPSO and Efftox Phase 12 Trials with Correlated + Outcomes + maintainer: Andrew G Chapple + description: Simulating and conducting four phase 12 clinical trials with correlated + binary bivariate outcomes described. Uses the 'Efftox' (efficacy and toxicity + tradeoff, ) + and SPSO (Semi-Parametric Stochastic Ordering) models with Utility and Desirability + based objective functions for dose finding. + date_publication: '2020-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Phase12Compare + url_git: '' +phase1PRMD: + version: 1.0.2 + title: |- + Personalized Repeated Measurement Design for Phase I Clinical + Trials + maintainer: Lu Zhang + description: |- + Implements Bayesian phase I repeated measurement design that + accounts for multidimensional toxicity endpoints and longitudinal efficacy + measure from multiple treatment cycles. The package provides flags to + fit a variety of model-based phase I design, including 1 stage models with + or without individualized dose modification, 3-stage models with or without + individualized dose modification, etc. Functions are provided to recommend + dosage selection based on the data collected in the available patient cohorts + and to simulate trial characteristics given design parameters. + Yin, Jun, et al. (2017) . + date_publication: '2020-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phase1PRMD + url_git: '' +phase1RMD: + version: 1.0.9 + title: Repeated Measurement Design for Phase I Clinical Trial + maintainer: Jun Yin + description: Implements our Bayesian phase I repeated measurement design that accounts + for multidimensional toxicity endpoints from multiple treatment cycles. The package + also provides a novel design to account for both multidimensional toxicity endpoints + and early-stage efficacy endpoints in the phase I design. For both designs, functions + are provided to recommend the next dosage selection based on the data collected + in the available patient cohorts and to simulate trial characteristics given design + parameters. Yin, Jun, et al. (2017) . + date_publication: '2020-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phase1RMD + url_git: '' +phaseR: + version: 2.2.1 + title: |- + Phase Plane Analysis of One- And Two-Dimensional Autonomous ODE + Systems + maintainer: Michael J Grayling + description: |- + Performs a qualitative analysis of one- and two-dimensional + autonomous ordinary differential equation systems, using phase plane methods. + Programs are available to identify and classify equilibrium points, plot the + direction field, and plot trajectories for multiple initial conditions. In + the one-dimensional case, a program is also available to plot the phase + portrait. Whilst in the two-dimensional case, programs are additionally + available to plot nullclines and stable/unstable manifolds of saddle points. + Many example systems are provided for the user. For further details can be + found in Grayling (2014) . + date_publication: '2022-09-02' + bug_reports: https://github.com/mjg211/phaseR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phaseR + url_git: https://github.com/mjg211/phaseR +PhaseType: + version: 0.3.0 + title: Inference for Phase-Type Distributions + maintainer: Louis Aslett + description: |- + Functions to perform Bayesian inference on absorption time data for + Phase-type distributions. The methods of Bladt et al (2003) + and Aslett (2012) + are provided. + date_publication: '2024-09-14' + bug_reports: https://github.com/louisaslett/PhaseType/issues + url: https://www.louisaslett.com/PhaseType/ + url_cran: https://CRAN.R-project.org/package=PhaseType + url_git: https://github.com/louisaslett/PhaseType +PhaseTypeR: + version: 1.0.4 + title: General-Purpose Phase-Type Functions + maintainer: Iker Rivas-González + description: |- + General implementation of core function from phase-type + theory. 'PhaseTypeR' can be used to model continuous and discrete + phase-type distributions, both univariate and multivariate. The + package includes functions for outputting the mean and (co)variance of + phase-type distributions; their density, probability and quantile + functions; functions for random draws; functions for + reward-transformation; and functions for plotting the distributions as + networks. For more information on these functions please refer to + Bladt and Nielsen (2017, ISBN: 978-1-4939-8377-3) and Campillo Navarro + (2019) + . + date_publication: '2022-07-21' + bug_reports: https://github.com/rivasiker/PhaseTypeR/issues + url: https://rivasiker.github.io/PhaseTypeR/ + url_cran: https://CRAN.R-project.org/package=PhaseTypeR + url_git: https://github.com/rivasiker/PhaseTypeR +phateR: + version: 1.0.7 + title: |- + PHATE - Potential of Heat-Diffusion for Affinity-Based + Transition Embedding + maintainer: Scott Gigante + description: |- + PHATE is a tool for visualizing high dimensional single-cell data + with natural progressions or trajectories. PHATE uses a novel conceptual framework + for learning and visualizing the manifold inherent to biological systems in which + smooth transitions mark the progressions of cells from one state to another. + To see how PHATE can be applied to single-cell RNA-seq datasets from hematopoietic + stem cells, human embryonic stem cells, and bone marrow samples, check out our publication in Nature Biotechnology + at . + date_publication: '2021-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phateR + url_git: '' +PHclust: + version: 0.1.0 + title: Poisson Hurdle Clustering for Sparse Microbiome Data + maintainer: Zhili Qiao + description: Clustering analysis for sparse microbiome data, based on a Poisson + hurdle model. + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PHclust + url_git: '' +phd: + version: '0.2' + title: Permutation Testing in High-Dimensional Linear Models + maintainer: Jesse Hemerik + description: |- + Provides permutation methods for testing in high-dimensional linear models. + The tests are often robust against heteroscedasticity and non-normality + and usually perform well under anti-sparsity. + See Hemerik, Thoresen and Finos (2021) . + date_publication: '2022-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phd + url_git: '' +phdcocktail: + version: 0.1.0 + title: Enhance the Ease of R Experience as an Emerging Researcher + maintainer: Dahham Alsoud + description: |- + A toolkit of functions to help: i) effortlessly transform collected data into a + publication ready format, ii) generate insightful visualizations from clinical data, iii) report + summary statistics in a publication-ready format, iv) efficiently export, save and reload R objects + within the framework of R projects. + date_publication: '2023-12-04' + bug_reports: https://github.com/DahhamAlsoud/phdcocktail/issues + url: https://dahhamalsoud.github.io/phdcocktail/ + url_cran: https://CRAN.R-project.org/package=phdcocktail + url_git: https://github.com/DahhamAlsoud/phdcocktail +pheatmap: + version: 1.0.12 + title: Pretty Heatmaps + maintainer: Raivo Kolde + description: |- + Implementation of heatmaps that offers more control + over dimensions and appearance. + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pheatmap + url_git: '' +pheble: + version: 0.1.0 + title: Classifying High-Dimensional Phenotypes with Ensemble Learning + maintainer: Jay Devine + description: |- + A system for binary and multi-class classification of + high-dimensional phenotypic data using ensemble learning. By combining + predictions from different classification models, this package attempts + to improve performance over individual learners. The pre-processing, + training, validation, and testing are performed end-to-end to minimize + user input and simplify the process of classification. + date_publication: '2023-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pheble + url_git: '' +PheCAP: + version: 1.2.1 + title: |- + High-Throughput Phenotyping with EHR using a Common Automated + Pipeline + maintainer: PARSE LTD + description: |- + Implement surrogate-assisted feature extraction (SAFE) and + common machine learning approaches to train and validate phenotyping models. + Background and details about the methods can be found at + Zhang et al. (2019) , + Yu et al. (2017) , and + Liao et al. (2015) . + date_publication: '2020-09-17' + bug_reports: https://github.com/celehs/PheCAP/issues + url: https://celehs.github.io/PheCAP/ + url_cran: https://CRAN.R-project.org/package=PheCAP + url_git: https://github.com/celehs/PheCAP +phecodemap: + version: 0.1.0 + title: Visualization for PheCode Mapping with ICD-9 and ICD-10-CM Codes + maintainer: PARSE LTD + description: 'To build a shiny app for visualization of the hierarchy of PheCode + Mapping with International Classification of Diseases (ICD). The same PheCode + hierarchy is displayed in two ways: as a sunburst plot and as a tree.' + date_publication: '2022-01-15' + bug_reports: https://github.com/celehs/phecodemap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phecodemap + url_git: https://github.com/celehs/phecodemap +PHEindicatormethods: + version: 2.1.0 + title: Common Public Health Statistics and their Confidence Intervals + maintainer: Georgina Anderson + description: |- + Functions to calculate commonly used public health statistics and + their confidence intervals using methods approved for use in the production + of Public Health England indicators such as those presented via Fingertips + (). It provides functions for the generation + of proportions, crude rates, means, directly standardised rates, indirectly + standardised rates, standardised mortality ratios, slope and relative index + of inequality and life expectancy. + Statistical methods are referenced in the following publications. + Breslow NE, Day NE (1987) . + Dobson et al (1991) . + Armitage P, Berry G (2002) . + Wilson EB. (1927) . + Altman DG et al (2000, ISBN: 978-0-727-91375-3). + Chiang CL. (1968, ISBN: 978-0-882-75200-6). + Newell C. (1994, ISBN: 978-0-898-62451-9). + Eayres DP, Williams ES (2004) . + Silcocks PBS et al (2001) . + Low and Low (2004) . + Fingertips Public Health Technical Guide: . + date_publication: '2024-12-12' + bug_reports: https://github.com/ukhsa-collaboration/PHEindicatormethods/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PHEindicatormethods + url_git: '' +phenesse: + version: 0.1.2 + title: Estimate Phenological Metrics using Presence-Only Data + maintainer: Michael Belitz + description: |- + Generates Weibull-parameterized estimates of phenology for any percentile of + a distribution using the framework established in Cooke (1979) + . Extensive testing against other + estimators suggest the weib_percentile() function is especially useful in + generating more accurate and less biased estimates of onset and offset + (Belitz et al. 2020 . Non-parametric + bootstrapping can be used to generate confidence intervals around those + estimates, although this is computationally expensive. Additionally, this + package offers an easy way to perform non-parametric bootstrapping to + generate confidence intervals for quantile estimates, mean estimates, + or any statistical function of interest. + date_publication: '2020-07-28' + bug_reports: https://github.com/mbelitz/phenesse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phenesse + url_git: https://github.com/mbelitz/phenesse +phenex: + version: 1.4-5 + title: Auxiliary Functions for Phenological Data Analysis + maintainer: Daniel Doktor + description: |- + Provides some easy-to-use functions for + spatial analyses of (plant-) phenological data + sets and satellite observations of vegetation. + date_publication: '2017-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phenex + url_git: '' +PHENIX: + version: 1.3.1 + title: Phenotypic Integration Index + maintainer: A. J. Muñoz-Pajares + description: Provides functions to estimate the size-controlled phenotypic integration + index, a novel method by Torices & Méndez (2014) to solve problems due to individual + size when estimating integration (namely, larger individuals have larger components, + which will drive a correlation between components only due to resource availability + that might obscure the observed measures of integration). In addition, the package + also provides the classical estimation by Wagner (1984), bootstrapping and jackknife + methods to calculate confidence intervals and a significance test for both integration + indices. + date_publication: '2017-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PHENIX + url_git: '' +phenmod: + version: 1.2-7 + title: |- + Auxiliary Functions for Phenological Data Processing, Modelling + and Result Handling + maintainer: Maximilian Lange + description: Provides functions for phenological data preprocessing, modelling and + result handling. For more information, please refer to Lange et al. (2016) . + date_publication: '2022-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phenmod + url_git: '' +phenModel: + version: '1.0' + title: Insect Phenology Model Evaluation Based on Daily Temperatures + maintainer: Rafael de Andrade Moral + description: Generates predicted stage change days for an insect, based on daily + temperatures and development rate parameters, as developed by Pollard (2014) . + A few example datasets are included and implemented for P. vulgatissima, the blue + willow beetle, but the approach can be readily applied to other species that display + similar behaviour. + date_publication: '2019-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phenModel + url_git: '' +pheno: + version: 1.7-0 + title: Auxiliary Functions for Phenological Data Analysis + maintainer: Maximilian Lange + description: |- + Provides some easy-to-use functions for time series + analyses of (plant-) phenological data sets. These functions + mainly deal with the estimation of combined phenological time + series and are usually wrappers for functions that are already + implemented in other R packages adapted to the special + structure of phenological data and the needs of phenologists. + Some date conversion functions to handle Julian dates are also + provided. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pheno + url_git: '' +phenocamr: + version: 1.1.5 + title: |- + Facilitates 'PhenoCam' Data Access and Time Series + Post-Processing + maintainer: Koen Hufkens + description: |2- + + Programmatic interface to the 'PhenoCam' web services (). + Allows for easy downloading of 'PhenoCam' data directly to your R workspace + or your computer and provides post-processing routines for consistent and easy + timeseries outlier detection, smoothing and estimation of phenological transition dates. + Methods for this package are described in detail in Hufkens et. al (2018) . + date_publication: '2022-07-20' + bug_reports: https://github.com/bluegreen-labs/phenocamr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phenocamr + url_git: https://github.com/bluegreen-labs/phenocamr +phenoCDM: + version: 0.1.3 + title: |- + Continuous Development Models for Incremental Time-Series + Analysis + maintainer: Bijan Seyednasrollah + description: Using the Bayesian state-space approach, we developed a continuous + development model to quantify dynamic incremental changes in the response variable. + While the model was originally developed for daily changes in forest green-up, + the model can be used to predict any similar process. The CDM can capture both + timing and rate of nonlinear processes. Unlike statics methods, which aggregate + variations into a single metric, our dynamic model tracks the changing impacts + over time. The CDM accommodates nonlinear responses to variation in predictors, + which changes throughout development. + date_publication: '2018-05-02' + bug_reports: https://github.com/bnasr/phenoCDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phenoCDM + url_git: '' +phenofit: + version: 0.3.9 + title: Extract Remote Sensing Vegetation Phenology + maintainer: Dongdong Kong + description: |2- + + The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and + growing season dividing method and a practical snow elimination method + based on Whittaker were proposed. 7 curve fitting methods and 4 phenology + extraction methods were provided. Parameters boundary are considered for + every curve fitting methods according to their ecological meaning. + And 'optimx' is used to select best optimization method for different + curve fitting methods. + Reference: + Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction + package, phenofit version 0.3.1, ; + Kong, D., Zhang, Y., Wang, D., Chen, J., & Gu, X. (2020). Photoperiod Explains + the Asynchronization Between Vegetation Carbon Phenology and Vegetation Greenness + Phenology. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005636. + ; + Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing + global MODIS EVI time series on the Google Earth Engine. + ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13–24; + Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology + on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). + Agric. For. Meteorol. 248, 408–417. . + date_publication: '2024-01-23' + bug_reports: https://github.com/eco-hydro/phenofit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phenofit + url_git: https://github.com/eco-hydro/phenofit +phenolocrop: + version: 0.0.2 + title: Time-Series Models to the Crop Phenology + maintainer: Shoji Taniguchi + description: |- + Fit a time-series model + to a crop phenology data, such as time-series rice canopy height. + This package returns the model parameters as the summary statistics of crop phenology, + and these parameters will be useful to characterize the growth pattern of each cultivar and + predict manually-measured traits, such as days to heading and biomass. + Please see Taniguchi et al. (2022) for detail. + This package has been designed for scientific use. + Use for commercial purposes shall not be allowed. + date_publication: '2023-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phenolocrop + url_git: '' +phenology: + version: '10.1' + title: |- + Tools to Manage a Parametric Function that Describes Phenology + and More + maintainer: Marc Girondot + description: Functions used to fit and test the phenology of species based on counts. + Based on Girondot, M. (2010) for the phenology function, + Girondot, M. (2017) for the convolution of + negative binomial, Girondot, M. and Rizzo, A. (2015) + for Bayesian estimate, Pfaller JB, ..., Girondot M (2019) + for tag-loss estimate, Hancock J, ..., Girondot M (2019) + for nesting history, Laloe J-O, ..., Girondot M, Hays GC (2020) + for aggregating several seasons. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phenology + url_git: '' +phenomap: + version: 2.0.1 + title: Projecting Satellite-Derived Phenology in Space + maintainer: Christian John + description: This takes in a series of multi-layer raster files and returns a phenology + projection raster, following methodologies described in John (2016) . + date_publication: '2023-10-12' + bug_reports: https://github.com/JepsonNomad/phenomap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phenomap + url_git: https://github.com/JepsonNomad/phenomap +phenopix: + version: 2.4.5 + title: Process Digital Images of a Vegetation Cover + maintainer: Gianluca Filippa + description: A collection of functions to process digital images, depict greenness + index trajectories and extract relevant phenological stages. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phenopix + url_git: '' +PheNorm: + version: 0.1.0 + title: |- + Unsupervised Gold-Standard Label Free Phenotyping Algorithm for + EHR Data + maintainer: Clara-Lea Bonzel + description: The algorithm combines the most predictive variable, such as count + of the main International Classification of Diseases (ICD) codes, and other Electronic + Health Record (EHR) features (e.g. health utilization and processed clinical note + data), to obtain a score for accurate risk prediction and disease classification. + In particular, it normalizes the surrogate to resemble gaussian mixture and leverages + the remaining features through random corruption denoising. Background and details + about the method can be found at Yu et al. (2018) . + date_publication: '2021-01-07' + bug_reports: https://github.com/celehs/PheNorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PheNorm + url_git: https://github.com/celehs/PheNorm +Phenotype: + version: 0.1.0 + title: A Tool for Phenotypic Data Processing + maintainer: Peng Zhao + description: Large-scale phenotypic data processing is essential in research. Researchers + need to eliminate outliers from the data in order to obtain true and reliable + results. Best linear unbiased prediction (BLUP) is a standard method for estimating + random effects of a mixed model. This method can be used to process phenotypic + data under different conditions and is widely used in animal and plant breeding. + The 'Phenotype' can remove outliers from phenotypic data and performs the best + linear unbiased prediction (BLUP), help researchers quickly complete phenotypic + data analysis. H.P.Piepho. (2008) . + date_publication: '2020-08-06' + bug_reports: https://github.com/biozhp/Phenotype/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Phenotype + url_git: https://github.com/biozhp/Phenotype +PhenotypeR: + version: 0.1.3 + title: Assess Study Cohorts Using a Common Data Model + maintainer: Edward Burn + description: |- + Phenotype study cohorts in data mapped to the + Observational Medical Outcomes Partnership Common Data Model. Diagnostics + are run at the database, code list, cohort, and population level to assess + whether study cohorts are ready for research. + date_publication: '2025-02-16' + bug_reports: '' + url: https://ohdsi.github.io/PhenotypeR/ + url_cran: https://CRAN.R-project.org/package=PhenotypeR + url_git: '' +PhenotypeSimulator: + version: 0.3.4 + title: |- + Flexible Phenotype Simulation from Different Genetic and Noise + Models + maintainer: Hannah Meyer + description: |- + Simulation is a critical part of method development and assessment + in quantitative genetics. 'PhenotypeSimulator' allows for the flexible + simulation of phenotypes under different models, including genetic variant + and infinitesimal genetic effects (reflecting population structure) as well + as non-genetic covariate effects, observational noise and additional + correlation effects. The different phenotype components are combined into a + final phenotype while controlling for the proportion of variance explained + by each of the components. For each effect component, the number of + variables, their distribution and the design of their effect across traits + can be customised. For the simulation of the genetic effects, external + genotype data from a number of standard software ('plink', 'hapgen2'/ + 'impute2', 'genome', 'bimbam', simple text files) can be imported. The final + simulated phenotypes and its components can be automatically saved into .rds + or .csv files. In addition, they can be saved in formats compatible with + commonly used genetic association software ('gemma', 'bimbam', 'plink', + 'snptest', 'LiMMBo'). + date_publication: '2021-07-16' + bug_reports: https://github.com/HannahVMeyer/PhenotypeSimulator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PhenotypeSimulator + url_git: https://github.com/HannahVMeyer/PhenotypeSimulator +PHENTHAUproc: + version: '1.1' + title: Phenology Modelling of Thaumetopoea Processionea + maintainer: Lorenz Bachfischer + description: Methods to calculate and present 'PHENTHAUproc', an early warning and + decision support system for hazard assessment and control of oak processionary + moth (OPM) using local and spatial temperature data. It was created by Halbig + et al. 2024 () at FVA () + Forest Research Institute Baden-Wuerttemberg, Germany and at BOKU - University + of Natural Ressources and Life Sciences, Vienna, Austria. + date_publication: '2024-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PHENTHAUproc + url_git: '' +phers: + version: 1.0.2 + title: Calculate Phenotype Risk Scores + maintainer: Jake Hughey + description: |- + Use phenotype risk scores based on linked clinical and genetic data + to study Mendelian disease and rare genetic variants. See Bastarache et al. + 2018 . + date_publication: '2023-03-26' + bug_reports: '' + url: https://phers.hugheylab.org + url_cran: https://CRAN.R-project.org/package=phers + url_git: https://github.com/hugheylab/phers +PHeval: + version: '1.1' + title: |- + Evaluation of the Proportional Hazards Assumption and Test for + Comparing Survival Curves with a Standardized Score Process + maintainer: Cecile Chauvel + description: Provides tools for the test for the comparison of survival curves, + the evaluation of the goodness-of-fit and the predictive capacity of the proportional + hazards model. + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PHeval + url_git: '' +PheVis: + version: 1.0.4 + title: |- + Automatic Phenotyping of Electronic Health Record at Visit + Resolution + maintainer: Thomas Ferte + description: 'Using Electronic Health Record (EHR) is difficult because most of + the time the true characteristic of the patient is not available. Instead we can + retrieve the International Classification of Disease code related to the disease + of interest or we can count the occurrence of the Unified Medical Language System. + None of them is the true phenotype which needs chart review to identify. However + chart review is time consuming and costly. ''PheVis'' is an algorithm which is + phenotyping (i.e identify a characteristic) at the visit level in an unsupervised + fashion. It can be used for chronic or acute diseases. An example of how to use + ''PheVis'' is available in the vignette. Basically there are two functions that + are to be used: `train_phevis()` which trains the algorithm and `test_phevis()` + which get the predicted probabilities. The detailed method is described in preprint + by Ferté et al. (2020) .' + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PheVis + url_git: '' +Phi2rho: + version: 1.0.1 + title: Owen's T Function and Bivariate Normal Integral + maintainer: Janez Komelj + description: |- + Computes the Owen's T function or the bivariate + normal integral using one of the following: + modified Euler's arctangent series, tetrachoric + series, or Vasicek's series. For the methods, + see Komelj, J. (2023) + (or reprint with better typography) + and Vasicek, O. A. (1998) . + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Phi2rho + url_git: '' +phia: + version: 0.3-1 + title: Post-Hoc Interaction Analysis + maintainer: Helios De Rosario-Martinez + description: |- + Analysis of terms in linear, generalized and mixed linear models, + on the basis of multiple comparisons of factor contrasts. Specially suited + for the analysis of interaction terms. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phia + url_git: https://github.com/heliosdrm/phia +phiDelta: + version: 1.0.1 + title: Tool for Phi Delta Analysis of Features + maintainer: Ursula Neumann + description: Analysis of features by phi delta diagrams. In particular, functions + for reading data and calculating phi and delta as well as the functionality to + plot it. Moreover it is possible to do further analysis on the data by generating + rankings. For more information on phi delta diagrams, see also Giuliano Armano + (2015) . + date_publication: '2018-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phiDelta + url_git: '' +philentropy: + version: 0.9.0 + title: |- + Similarity and Distance Quantification Between Probability + Functions + maintainer: Hajk-Georg Drost + description: Computes 46 optimized distance and similarity measures for comparing + probability functions (Drost (2018) ). These comparisons + between probability functions have their foundations in a broad range of scientific + disciplines from mathematics to ecology. The aim of this package is to provide + a core framework for clustering, classification, statistical inference, goodness-of-fit, + non-parametric statistics, information theory, and machine learning tasks that + are based on comparing univariate or multivariate probability functions. + date_publication: '2024-11-12' + bug_reports: https://github.com/drostlab/philentropy/issues + url: https://drostlab.github.io/philentropy/ + url_cran: https://CRAN.R-project.org/package=philentropy + url_git: https://github.com/drostlab/philentropy +PhilipsHue: + version: 1.0.0 + title: R Interface to the Philips Hue API + maintainer: Justin Brantley + description: |- + Control Philips Hue smart lighting. Use this package to + connect to a Hue bridge on your local network (remote authentication + not yet supported) and control your smart lights through the Philips + Hue API. All API V1 endpoints are supported. See API documentation at + . + date_publication: '2022-05-06' + bug_reports: https://gitlab.com/fascinatingfingers/philipshue/-/issues + url: https://fascinatingfingers.gitlab.io/philipshue + url_cran: https://CRAN.R-project.org/package=PhilipsHue + url_git: https://gitlab.com/fascinatingfingers/philipshue +PHInfiniteEstimates: + version: 2.9.5 + title: Tools for Inference in the Presence of a Monotone Likelihood + maintainer: John E. Kolassa + description: Proportional hazards estimation in the presence of a partially monotone + likelihood has difficulties, in that finite estimators do not exist. These difficulties + are related to those arising from logistic and multinomial regression. References + for methods are given in the separate function documents. Supported by grant + NSF DMS 1712839. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PHInfiniteEstimates + url_git: '' +PhitestR: + version: 0.2.0 + title: Analyzing the Heterogeneity of Single-Cell Populations + maintainer: Wei Vivian Li + description: A bioinformatics method developed for analyzing the heterogeneity of + single-cell populations. Phitest provides an objective and automatic method to + evaluate the performance of clustering and quality of cell clusters. + date_publication: '2022-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PhitestR + url_git: '' +phm: + version: 1.1.2 + title: Phrase Mining + maintainer: Ellie Small + description: |- + Functions to extract and handle commonly occurring principal phrases + obtained from collections of texts. + date_publication: '2024-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phm + url_git: '' +phoenics: + version: '0.5' + title: Pathways Longitudinal and Differential Analysis in Metabolomics + maintainer: Camille Guilmineau + description: |- + Perform a differential analysis at pathway level based on metabolite quantifications and information on pathway metabolite composition. + The method is based on a Principal Component Analysis step and on a linear mixed model. + Automatic query of metabolic pathways is also implemented. + date_publication: '2025-01-29' + bug_reports: https://forgemia.inra.fr/panoramics/phoenics/-/issues + url: https://forgemia.inra.fr/panoramics/phoenics + url_cran: https://CRAN.R-project.org/package=phoenics + url_git: '' +phoenix: + version: 1.1.1 + title: The Phoenix Pediatric Sepsis and Septic Shock Criteria + maintainer: Peter DeWitt + description: |- + Implementation of the Phoenix and Phoenix-8 Sepsis Criteria as + described in "Development and Validation of the Phoenix Criteria for + Pediatric Sepsis and Septic Shock" by Sanchez-Pinto, Bennett, DeWitt, + Russell et al. (2024) (Drs. Sanchez-Pinto + and Bennett contributed equally to this manuscript; Dr. DeWitt and Mr. + Russell contributed equally to the manuscript), "International Consensus + Criteria for Pediatric Sepsis and Septic Shock" by Schlapbach, Watson, + Sorce, Argent, et al. (2024) (Drs Schlapbach, + Watson, Sorce, and Argent contributed equally) and the application note + "phoenix: an R package and Python module for calculating the Phoenix + pediatric sepsis score and criteria" by DeWitt, Russell, Rebull, + Sanchez-Pinto, and Bennett (2024) . + date_publication: '2024-07-08' + bug_reports: https://github.com/CU-DBMI-Peds/phoenix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phoenix + url_git: https://github.com/CU-DBMI-Peds/phoenix/ +phonenumber: + version: 0.2.3 + title: Convert Letters to Numbers and Back as on a Telephone Keypad + maintainer: Steve Myles + description: |- + Convert English letters to numbers or numbers to English + letters as on a telephone keypad. When converting letters to numbers, + a character vector is returned with "A," "B," or "C" becoming 2, "D," + "E", or "F" becoming 3, etc. When converting numbers to letters, a + character vector is returned with multiple elements (i.e., "2" becomes + a vector of "A," "B," and "C"). + date_publication: '2021-05-01' + bug_reports: https://github.com/scumdogsteev/phonenumber/issues + url: https://stevemyles.site/phonenumber/ + url_cran: https://CRAN.R-project.org/package=phonenumber + url_git: https://github.com/scumdogsteev/phonenumber +phonetisr: + version: 0.1.0 + title: A Naive IPA Tokeniser + maintainer: Stefano Coretta + description: |- + It provides users with functions to parse International Phonetic + Alphabet (IPA) transcriptions into individual phones (tokenisation) based on + default IPA symbols and optional user specified multi-character phones. The + tokenised transcriptions can be used for obtaining counts of phones or for + searching for words matching phonetic patterns. + date_publication: '2025-02-26' + bug_reports: '' + url: https://stefanocoretta.github.io/phonetisr/ + url_cran: https://CRAN.R-project.org/package=phonetisr + url_git: https://github.com/stefanocoretta/phonetisr +phonfieldwork: + version: 0.0.17 + title: Linguistic Phonetic Fieldwork Tools + maintainer: George Moroz + description: 'There are a lot of different typical tasks that have to be solved + during phonetic research and experiments. This includes creating a presentation + that will contain all stimuli, renaming and concatenating multiple sound files + recorded during a session, automatic annotation in ''Praat'' TextGrids (this is + one of the sound annotation standards provided by ''Praat'' software, see Boersma + & Weenink 2020 ), creating an html table with + annotations and spectrograms, and converting multiple formats (''Praat'' TextGrid, + ''ELAN'', ''EXMARaLDA'', ''Audacity'', subtitles ''.srt'', and ''FLEx'' flextext). + All of these tasks can be solved by a mixture of different tools (any programming + language has programs for automatic renaming, and Praat contains scripts for concatenating + and renaming files, etc.). ''phonfieldwork'' provides a functionality that will + make it easier to solve those tasks independently of any additional tools. You + can also compare the functionality with other packages: ''rPraat'' , + ''textgRid'' .' + date_publication: '2024-07-29' + bug_reports: https://github.com/ropensci/phonfieldwork/issues + url: https://docs.ropensci.org/phonfieldwork/ + url_cran: https://CRAN.R-project.org/package=phonfieldwork + url_git: '' +phonics: + version: 1.3.10 + title: Phonetic Spelling Algorithms + maintainer: James Howard + description: |- + Provides a collection of phonetic algorithms including + Soundex, Metaphone, NYSIIS, Caverphone, and others. The package is + documented in . + date_publication: '2021-07-11' + bug_reports: https://github.com/k3jph/phonics-in-r/issues + url: https://jameshoward.us/phonics-in-r/ + url_cran: https://CRAN.R-project.org/package=phonics + url_git: '' +phonR: + version: 1.0-7 + title: Tools for Phoneticians and Phonologists + maintainer: Daniel R. McCloy + description: Tools for phoneticians and phonologists, including functions for normalization + and plotting of vowels. + date_publication: '2016-08-25' + bug_reports: https://github.com/drammock/phonR/issues + url: http://drammock.github.io/phonR/ + url_cran: https://CRAN.R-project.org/package=phonR + url_git: '' +phonTools: + version: 0.2-2.2 + title: Tools for Phonetic and Acoustic Analyses + maintainer: Santiago Barreda + description: Contains tools for the organization, display, and analysis of the sorts + of data frequently encountered in phonetics research and experimentation, including + the easy creation of IPA vowel plots, and the creation and manipulation of WAVE + audio files. + date_publication: '2023-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phonTools + url_git: '' +phosphoricons: + version: 0.2.1 + title: '''Phosphor'' Icons for R' + maintainer: Victor Perrier + description: |- + Use 'Phosphor' icons in 'shiny' applications or 'rmarkdown' documents. Icons are available in + 5 different weights and can be customized by setting color, size, orientation and more. + date_publication: '2024-04-08' + bug_reports: https://github.com/dreamRs/phosphoricons/issues + url: https://dreamrs.github.io/phosphoricons/ + url_cran: https://CRAN.R-project.org/package=phosphoricons + url_git: https://github.com/dreamRs/phosphoricons +photobiology: + version: 0.12.0 + title: Photobiological Calculations + maintainer: Pedro J. Aphalo + description: |- + Definitions of classes, methods, operators and functions for use + in photobiology and radiation meteorology and climatology. Calculation of + effective (weighted) and not-weighted irradiances/doses, fluence rates, + transmittance, reflectance, absorptance, absorbance and diverse ratios and + other derived quantities from spectral data. Local maxima and minima: peaks, + valleys and spikes. Conversion between energy-and photon-based units. + Wavelength interpolation. Astronomical calculations related solar angles and + day length. Colours and vision. This package is part of the 'r4photobiology' + suite, Aphalo, P. J. (2015) . + date_publication: '2025-02-02' + bug_reports: https://github.com/aphalo/photobiology/issues + url: https://docs.r4photobiology.info/photobiology/ + url_cran: https://CRAN.R-project.org/package=photobiology + url_git: https://github.com/aphalo/photobiology +photobiologyFilters: + version: 0.6.0 + title: Spectral Transmittance and Spectral Reflectance Data + maintainer: Pedro J. Aphalo + description: |- + Spectral 'transmittance' data for frequently used filters and + similar materials. Plastic sheets and films; photography filters; + theatrical gels; machine-vision filters; various types of window glass; + optical glass and some laboratory plastics and glassware. Spectral + reflectance data for frequently encountered materials. Part of the + 'r4photobiology' suite, Aphalo P. J. (2015) . + date_publication: '2024-02-27' + bug_reports: https://github.com/aphalo/photobiologyfilters/issues + url: https://docs.r4photobiology.info/photobiologyFilters/ + url_cran: https://CRAN.R-project.org/package=photobiologyFilters + url_git: https://github.com/aphalo/photobiologyfilters +photobiologyInOut: + version: 0.4.30 + title: Read Spectral and Logged Data from Foreign Files + maintainer: Pedro J. Aphalo + description: |- + Functions for reading, and in some cases writing, foreign files + containing spectral data from spectrometers and their associated software, + output from daylight simulation models in common use, and some spectral + data repositories. As well as functions for exchange of spectral data with + other R packages. Part of the 'r4photobiology' suite, + Aphalo P. J. (2015) . + date_publication: '2025-02-02' + bug_reports: https://github.com/aphalo/photobiologyinout/issues/ + url: https://docs.r4photobiology.info/photobiologyInOut/ + url_cran: https://CRAN.R-project.org/package=photobiologyInOut + url_git: '' +photobiologyLamps: + version: 0.5.2 + title: Spectral Irradiance Data for Lamps + maintainer: Pedro J. Aphalo + description: |- + Spectral emission data for some frequently used lamps including + bulbs and flashlights based on led emitting diodes (LEDs) but excluding + LEDs available as electronic components. Original spectral irradiance data + for incandescent-, LED- and discharge lamps are included. They are + complemented by data on the effect of temperature on the emission by + fluorescent tubes. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) + . + date_publication: '2023-10-24' + bug_reports: https://github.com/aphalo/photobiologylamps/issues + url: https://www.r4photobiology.info/ + url_cran: https://CRAN.R-project.org/package=photobiologyLamps + url_git: https://github.com/aphalo/photobiologylamps +photobiologyLEDs: + version: 0.5.2 + title: Spectral Data for Light-Emitting-Diodes + maintainer: Pedro J. Aphalo + description: |- + Spectral emission data for some frequently used light emitting + diodes available as electronic components. Part of the 'r4photobiology' + suite, Aphalo P. J. (2015) . + date_publication: '2023-11-01' + bug_reports: https://github.com/aphalo/photobiologyLEDs/issues + url: https://docs.r4photobiology.info/photobiologyLEDs/ + url_cran: https://CRAN.R-project.org/package=photobiologyLEDs + url_git: https://github.com/aphalo/photobiologyLEDs +photobiologyPlants: + version: 0.6.0 + title: Plant Photobiology Related Functions and Data + maintainer: Pedro J. Aphalo + description: |- + Provides functions for quantifying visible (VIS) and ultraviolet + (UV) radiation in relation to the photoreceptors Phytochromes, + Cryptochromes, and UVR8 which are present in plants. It also includes data + sets on the optical properties of plants. Part of the 'r4photobiology' + suite, Aphalo P. J. (2015) . + date_publication: '2025-01-12' + bug_reports: https://github.com/aphalo/photobiologyplants/issues + url: '' + url_cran: https://CRAN.R-project.org/package=photobiologyPlants + url_git: https://docs.r4photobiology.info/photobiologyPlants/https://github.com/aphalo/photobiologyplants +photobiologySensors: + version: 0.5.1 + title: Response Data for Light Sensors + maintainer: Pedro J. Aphalo + description: |- + Spectral response data for broadband ultraviolet and visible + radiation sensors. Angular response data for broadband ultraviolet and visible + radiation sensors and diffusers used as entrance optics. Data obtained from + multiple sources were used: author-supplied data from scientific research + papers, sensor-manufacturer supplied data, and published sensor + specifications. Part of the 'r4photobiology' suite Aphalo P. J. (2015) + . + date_publication: '2023-10-24' + bug_reports: https://github.com/aphalo/photobiologysensors/issues + url: https://www.r4photobiology.info + url_cran: https://CRAN.R-project.org/package=photobiologySensors + url_git: https://github.com/aphalo/photobiologysensors +photobiologySun: + version: 0.5.0 + title: Data for Sunlight Spectra + maintainer: Pedro J. Aphalo + description: |- + Data for the extraterrestrial solar spectral irradiance and ground + level solar spectral irradiance and irradiance. In addition data for + shade light under vegetation and irradiance time series from different + broadband sensors. Part of the + 'r4photobiology' suite, Aphalo P. J. (2015) . + date_publication: '2024-04-01' + bug_reports: https://github.com/aphalo/photobiologySun/issues + url: http://www.r4photobiology.info + url_cran: https://CRAN.R-project.org/package=photobiologySun + url_git: https://github.com/aphalo/photobiologySun +photobiologyWavebands: + version: 0.5.2 + title: Waveband Definitions for UV, VIS, and IR Radiation + maintainer: Pedro J. Aphalo + description: |- + Constructors of waveband objects for commonly used biological + spectral weighting functions (BSWFs) and for different wavebands describing + named ranges of wavelengths in the ultraviolet (UV), visible (VIS) + and infrared (IR) regions of the electromagnetic spectrum. Part of the + 'r4photobiology' suite, Aphalo P. J. (2015) . + date_publication: '2023-10-24' + bug_reports: https://github.com/aphalo/photobiologywavebands/issues + url: https://docs.r4photobiology.info/photobiologyWavebands/ + url_cran: https://CRAN.R-project.org/package=photobiologyWavebands + url_git: https://github.com/aphalo/photobiologywavebands +photon: + version: 0.3.5 + title: High-Performance Geocoding using 'photon' + maintainer: Jonas Lieth + description: |- + Features unstructured, structured and reverse geocoding using the + 'photon' geocoding API . + Facilitates the setup of local 'photon' instances to enable offline + geocoding. + date_publication: '2025-02-24' + bug_reports: https://github.com/jslth/photon/issues + url: https://jslth.github.io/photon/ + url_cran: https://CRAN.R-project.org/package=photon + url_git: https://github.com/jslth/photon/ +PhotosynQ: + version: 0.2.3 + title: Connect to PhotosynQ + maintainer: Sebastian Kuhlgert + description: |- + Connect R to the PhotosynQ platform (). It allows to login and logout, + as well as receive project information and project data. Further it transforms the received JSON objects + into a data frame, which can be used for the final data analysis. + date_publication: '2021-07-13' + bug_reports: https://github.com/Photosynq/PhotosynQ-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PhotosynQ + url_git: https://github.com/Photosynq/PhotosynQ-R +photosynthesis: + version: 2.1.5 + title: Tools for Plant Ecophysiology & Modeling + maintainer: Chris Muir + description: |- + Contains modeling and analytical tools for plant ecophysiology. + MODELING: Simulate C3 photosynthesis using the Farquhar, von Caemmerer, + Berry (1980) model as described in Buckley and + Diaz-Espejo (2015) . It uses units to ensure that + parameters are properly specified and transformed before calculations. + Temperature response functions get automatically "baked" into all + parameters based on leaf temperature following Bernacchi et al. (2002) + . The package includes boundary layer, cuticular, + stomatal, and mesophyll conductances to CO2, which each can vary on the + upper and lower portions of the leaf. Use straightforward functions to + simulate photosynthesis over environmental gradients such as Photosynthetic + Photon Flux Density (PPFD) and leaf temperature, or over trait gradients + such as CO2 conductance or photochemistry. + ANALYTICAL TOOLS: Fit ACi (Farquhar et al. (1980) ) + and AQ curves (Marshall & Biscoe (1980) ), + temperature responses (Heskel et al. (2016) ; + Kruse et al. (2008) , Medlyn et al. + (2002) , Hobbs et al. (2013) + ), respiration in the light (Kok (1956) + , Walker & Ort (2015) , + Yin et al. (2009) , Yin et al. (2011) + ), mesophyll conductance (Harley et al. (1992) + ), pressure-volume curves (Koide et al. (2000) + , Sack et al. (2003) + , Tyree et al. (1972) + ), hydraulic vulnerability curves (Ogle et al. (2009) + , Pammenter et al. (1998) + ), and tools for running sensitivity + analyses particularly for variables with uncertainty (e.g. g_mc(), gamma_star(), + R_d()). + date_publication: '2024-11-24' + bug_reports: https://github.com/cdmuir/photosynthesis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=photosynthesis + url_git: https://github.com/cdmuir/photosynthesis +photosynthesisLRC: + version: 1.0.6 + title: Nonlinear Least Squares Models for Photosynthetic Light Response + maintainer: Rebekah Davis + description: Provides functions for modeling, comparing, and visualizing photosynthetic + light response curves using established mechanistic and empirical models like + the rectangular hyperbola Michaelis-Menton based models ((eq1 (Baly (1935) )) + (eq2 (Kaipiainenn (2009) )) (eq3 (Smith (1936) + ))), hyperbolic tangent based models ((eq4 (Jassby + & Platt (1976) )) (eq5 (Abe et al. (2009) ))), + the non-rectangular hyperbola model (eq6 (Prioul & Chartier (1977) )), + exponential based models ((eq8 (Webb et al. (1974) )), + (eq9 (Prado & de Moraes (1997) ))), and finally the Ye + model (eq11 (Ye (2007) )). Each of these nonlinear + least squares models are commonly used to express photosynthetic response under + changing light conditions and has been well supported in the literature, but distinctions + in each mathematical model represent moderately different assumptions about physiology + and trait relationships which ultimately produce different calculated functional + trait values. These models were all thoughtfully discussed and curated by Lobo + et al. (2013) to express the importance of selecting + an appropriate model for analysis, and methods were established in Davis et al. + (in review) to evaluate the impact of analytical choice in phylogenetic analysis + of the function-valued traits. Gas exchange data on 28 wild sunflower species + from Davis et al.are included as an example data set here. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=photosynthesisLRC + url_git: https://github.com/heliotropichuman/photosynthesisLRC +phrases: + version: '0.1' + title: Phrasal Verbs in English Club Website + maintainer: Suman Khanal + description: |- + Contains all phrasal verbs listed in + as data frame. Useful for educational purpose as well as for text mining. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phrases + url_git: https://github.com/sumanstats/phrases +phreeqc: + version: 3.8.7 + title: R Interface to Geochemical Modeling Software + maintainer: S.R. Charlton + description: |- + A geochemical modeling program developed by the US Geological + Survey that is designed to perform a wide variety of aqueous geochemical + calculations, including speciation, batch-reaction, one-dimensional + reactive-transport, and inverse geochemical calculations. + date_publication: '2025-02-26' + bug_reports: https://github.com/usgs-coupled/iphreeqc/issues + url: https://www.usgs.gov/software/phreeqc-version-3 + url_cran: https://CRAN.R-project.org/package=phreeqc + url_git: '' +phsmethods: + version: 1.0.2 + title: Standard Methods for Use in Public Health Scotland + maintainer: Tina Fu + description: |- + A collection of methods for commonly undertaken analytical + tasks, primarily developed for Public Health Scotland (PHS) analysts, + but the package is also generally useful to others working in the + healthcare space, particularly since it has functions for working with + Community Health Index (CHI) numbers. The package can help to make + data manipulation and analysis more efficient and reproducible. + date_publication: '2024-01-08' + bug_reports: https://github.com/Public-Health-Scotland/phsmethods/issues + url: https://public-health-scotland.github.io/phsmethods/ + url_cran: https://CRAN.R-project.org/package=phsmethods + url_git: https://github.com/Public-Health-Scotland/phsmethods +PHSMM: + version: '1.0' + title: |- + Penalised Maximum Likelihood Estimation for Hidden Semi-Markov + Models + maintainer: Jennifer Pohle + description: 'Provides tools for penalised maximum likelihood estimation of hidden + semi-Markov models (HSMMs) with flexible state dwell-time distributions. These + include functions for model fitting, model checking and state-decoding. The package + considers HSMMs for univariate time series with state-dependent gamma, normal, + Poisson or Bernoulli distributions. For details, see Pohle, J., Adam, T. and Beumer, + L.T. (2021): Flexible estimation of the state dwell-time distribution in hidden + semi-Markov models. .' + date_publication: '2021-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PHSMM + url_git: '' +phuassess: + version: '1.1' + title: Proportional Habitat Use Assessment + maintainer: Caterina Pisani + description: Assessment of habitat selection by means of the permutation-based combination + of sign tests (Fattorini et al., 2014 ). To exemplify + the application of this procedure, habitat selection is assessed for a population + of European Brown Hares settled in central Italy. + date_publication: '2016-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phuassess + url_git: '' +phyclust: + version: 0.1-34 + title: Phylogenetic Clustering (Phyloclustering) + maintainer: Wei-Chen Chen + description: |- + Phylogenetic clustering (phyloclustering) is an evolutionary + Continuous Time Markov Chain model-based approach to identify + population structure from molecular data without assuming + linkage equilibrium. The package phyclust (Chen 2011) provides a + convenient implementation of phyloclustering for DNA and SNP data, + capable of clustering individuals into subpopulations and identifying + molecular sequences representative of those subpopulations. It is + designed in C for performance, interfaced with R for visualization, + and incorporates other popular open source programs including + ms (Hudson 2002) , + seq-gen (Rambaut and Grassly 1997) + , + Hap-Clustering (Tzeng 2005) and + PAML baseml (Yang 1997, 2007) , + , + for simulating data, additional analyses, and searching the best tree. + See the phyclust website for more information, documentations and + examples. + date_publication: '2023-09-06' + bug_reports: https://github.com/snoweye/phyclust/issues + url: https://snoweye.github.io/phyclust/ + url_cran: https://CRAN.R-project.org/package=phyclust + url_git: '' +phyext2: + version: 0.0.4 + title: |- + An Extension (for Package 'SigTree') of Some of the Classes in + Package 'phylobase' + maintainer: John R. Stevens + description: Based on (but not identical to) the no-longer-maintained package 'phyext', + provides enhancements to 'phylobase' classes, specifically for use by package + 'SigTree'; provides classes and methods which help users manipulate branch-annotated + trees (as in 'SigTree'); also provides support for a few other extra features. + date_publication: '2015-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phyext2 + url_git: '' +phylepic: + version: 0.2.0 + title: Combined Visualisation of Phylogenetic and Epidemiological Data + maintainer: Carl Suster + description: |- + A collection of utilities and 'ggplot2' extensions to assist with + visualisations in genomic epidemiology. This includes the 'phylepic' chart, + a visual combination of a phylogenetic tree and a matched epidemic curve. + The included 'ggplot2' extensions such as date axes binned by week are + relevant for other applications in epidemiology and beyond. The approach is + described in Suster et al. (2024) . + date_publication: '2024-05-31' + bug_reports: https://github.com/cidm-ph/phylepic/issues + url: https://cidm-ph.github.io/phylepic/ + url_cran: https://CRAN.R-project.org/package=phylepic + url_git: https://github.com/cidm-ph/phylepic +phylin: + version: 2.0.2 + title: Spatial Interpolation of Genetic Data + maintainer: Pedro Tarroso + description: |- + The spatial interpolation of genetic distances between + samples is based on a modified kriging method that + accepts a genetic distance matrix and generates a map of + probability of lineage presence. This package also offers + tools to generate a map of potential contact zones + between groups with user-defined thresholds in the tree + to account for old and recent divergence. Additionally, + it has functions for IDW interpolation using genetic data + and midpoints. + date_publication: '2019-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylin + url_git: https://github.com/ptarroso/phylin +phylobase: + version: 0.8.12 + title: Base Package for Phylogenetic Structures and Comparative Data + maintainer: Francois Michonneau + description: |- + Provides a base S4 class for comparative methods, incorporating + one or more trees and trait data. + date_publication: '2024-01-30' + bug_reports: https://github.com/fmichonneau/phylobase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phylobase + url_git: https://github.com/fmichonneau/phylobase +phylocanvas: + version: 0.1.3 + title: |- + Interactive Phylogenetic Trees Using the 'Phylocanvas' + JavaScript Library + maintainer: zachary charlop-powers + description: Create and customize interactive phylogenetic trees using the 'phylocanvas' + JavaScript library and the 'htmlwidgets' package. These trees can be used directly + from the R console, from 'RStudio', in Shiny apps, and in R Markdown documents. See + for more information on the 'phylocanvas' library. + date_publication: '2017-10-30' + bug_reports: https://github.com/zachcp/phylocanvas/issues + url: http://phylocanvas.org/ + url_cran: https://CRAN.R-project.org/package=phylocanvas + url_git: https://github.com/zachcp/phylocanvas +phylocomr: + version: 0.3.4 + title: Interface to 'Phylocom' + maintainer: Luna Luisa Sanchez Reyes + description: |- + Interface to 'Phylocom' (), + a library for analysis of 'phylogenetic' community structure and + character evolution. Includes low level methods for interacting with + the three executables, as well as higher level interfaces for methods + like 'aot', 'ecovolve', 'bladj', 'phylomatic', and more. + date_publication: '2023-04-22' + bug_reports: https://github.com/ropensci/phylocomr/issues + url: https://docs.ropensci.org/phylocomr/ + url_cran: https://CRAN.R-project.org/package=phylocomr + url_git: https://github.com/ropensci/phylocomr +PhylogeneticEM: + version: 1.8.0 + title: Automatic Shift Detection using a Phylogenetic EM + maintainer: Paul Bastide + description: |- + Implementation of the automatic shift detection method for + Brownian Motion (BM) or Ornstein–Uhlenbeck (OU) models of trait evolution on + phylogenies. Some tools to handle equivalent shifts configurations are also + available. See Bastide et al. (2017) and + Bastide et al. (2018) . + date_publication: '2025-02-14' + bug_reports: https://github.com/pbastide/PhylogeneticEM/issues + url: https://pbastide.github.io/PhylogeneticEM/ + url_cran: https://CRAN.R-project.org/package=PhylogeneticEM + url_git: https://github.com/pbastide/PhylogeneticEM +PHYLOGR: + version: 1.0.11 + title: Functions for Phylogenetically Based Statistical Analyses + maintainer: Ramon Diaz-Uriarte + description: |- + Manipulation and analysis of phylogenetically simulated + data sets and phylogenetically based analyses using GLS. + date_publication: '2020-04-14' + bug_reports: '' + url: http://ligarto.org/rdiaz + url_cran: https://CRAN.R-project.org/package=PHYLOGR + url_git: '' +phylogram: + version: 2.1.0 + title: Dendrograms for Evolutionary Analysis + maintainer: Shaun Wilkinson + description: |- + Contains functions for developing phylogenetic trees as + deeply-nested lists ("dendrogram" objects). + Enables bi-directional conversion between dendrogram and + "phylo" objects + (see Paradis et al (2004) ), + and features several tools for command-line tree + manipulation and import/export via Newick parenthetic text. + date_publication: '2018-06-25' + bug_reports: http://github.com/ropensci/phylogram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phylogram + url_git: http://github.com/ropensci/phylogram +phylolm: + version: 2.6.5 + title: Phylogenetic Linear Regression + maintainer: Lam Si Tung Ho + description: Provides functions for fitting phylogenetic linear models and phylogenetic + generalized linear models. The computation uses an algorithm that is linear in + the number of tips in the tree. The package also provides functions for simulating + continuous or binary traits along the tree. Other tools include functions to test + the adequacy of a population tree. + date_publication: '2024-09-30' + bug_reports: https://github.com/lamho86/phylolm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phylolm + url_git: https://github.com/lamho86/phylolm +phylolm.hp: + version: 0.0-3 + title: |- + Hierarchical Partitioning of R2 for Phylogenetic Linear + Regression + maintainer: Jiangshan Lai + description: Conducts hierarchical partitioning to calculate individual contributions + of phylogenetic tree and predictors (groups) towards total R2 for phylogenetic + linear regression models. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylolm.hp + url_git: https://github.com/laijiangshan/phylolm.hp +phylometrics: + version: 0.0.1 + title: Estimating Statistical Errors of Phylogenetic Metrics + maintainer: Xia Hua + description: |- + Provides functions to estimate statistical errors of phylogenetic + metrics particularly to detect binary trait influence on diversification, as + well as a function to simulate trees with fixed number of sampled taxa and trait + prevalence. + date_publication: '2015-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylometrics + url_git: '' +phylopairs: + version: 0.1.0 + title: Comparative Analyses of Lineage-Pair Traits + maintainer: Sean A. S. Anderson + description: Facilitates the testing of causal relationships among lineage-pair + traits in a phylogenetically informed context. Lineage-pair traits are characters + that are defined for pairs of lineages instead of individual taxa. Examples include + the strength of reproductive isolation, range overlap, competition coefficient, + diet niche similarity, and relative hybrid fitness. Users supply a lineage-pair + dataset and a phylogeny. 'phylopairs' calculates a covariance matrix for the pairwise-defined + data and provides built-in models to test for relationships among variables while + taking this covariance into account. Bayesian sampling is run through built-in + 'Stan' programs via the 'rstan' package. The various models and methods that this + package makes available are described in Anderson et al. (In Review), Coyne and + Orr (1989) , Fitzpatrick (2002) , + and Castillo (2007) . + date_publication: '2024-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylopairs + url_git: '' +phylopath: + version: 1.3.0 + title: Perform Phylogenetic Path Analysis + maintainer: Wouter van der Bijl + description: |- + A comprehensive and easy to use R implementation of confirmatory + phylogenetic path analysis as described by Von Hardenberg and Gonzalez-Voyer + (2012) . + date_publication: '2024-06-11' + bug_reports: https://github.com/Ax3man/phylopath/issues + url: https://Ax3man.github.io/phylopath/ + url_cran: https://CRAN.R-project.org/package=phylopath + url_git: '' +phyloraster: + version: 2.2.0 + title: Evolutionary Diversity Metrics for Raster Data + maintainer: Gabriela Alves-Ferreira + description: |- + Phylogenetic Diversity (PD, Faith 1992), Evolutionary + Distinctiveness (ED, Isaac et al. 2007), Phylogenetic Endemism (PE, + Rosauer et al. 2009; Laffan et al. 2016), and Weighted Endemism (WE, + Laffan et al. 2016) for presence-absence raster. Faith, D. P. (1992) + Isaac, N. J. et al. (2007) + Laffan, S. W. et al. (2016) + Rosauer, D. et al. (2009) + . + date_publication: '2025-02-28' + bug_reports: https://github.com/gabferreira/phyloraster/issues + url: https:https://gabferreira.github.io/phyloraster/ + url_cran: https://CRAN.R-project.org/package=phyloraster + url_git: https://github.com/gabferreira/phyloraster +phyloregion: + version: 1.0.8 + title: Biogeographic Regionalization and Macroecology + maintainer: Barnabas H. Daru + description: |- + Computational infrastructure for biogeography, community ecology, + and biodiversity conservation (Daru et al. 2020) . + It is based on the methods described in Daru et al. (2020) . + The original conceptual work is described in Daru et al. (2017) + on patterns and processes of biogeographical regionalization. Additionally, the package + contains fast and efficient functions to compute more standard conservation measures + such as phylogenetic diversity, phylogenetic endemism, evolutionary distinctiveness + and global endangerment, as well as compositional turnover (e.g., beta diversity). + date_publication: '2023-08-15' + bug_reports: https://github.com/darunabas/phyloregion/issues + url: https://phyloregion.com/index.html + url_cran: https://CRAN.R-project.org/package=phyloregion + url_git: https://github.com/darunabas/phyloregion +phylosamp: + version: 1.0.1 + title: Sample Size Calculations for Molecular and Phylogenetic Studies + maintainer: Justin Lessler + description: |- + Implements novel tools for estimating sample sizes needed for phylogenetic studies, including + studies focused on estimating the probability of true pathogen transmission between two cases given phylogenetic linkage and studies focused on tracking pathogen variants at a population level. Methods described in Wohl, Giles, and Lessler (2021) and in Wohl, Lee, DiPrete, and Lessler (2023). + date_publication: '2023-05-23' + bug_reports: https://github.com/HopkinsIDD/phylosamp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phylosamp + url_git: https://github.com/HopkinsIDD/phylosamp +phylosem: + version: 1.1.4 + title: Phylogenetic Structural Equation Model + maintainer: James Thorson + description: |- + Applies phylogenetic comparative methods (PCM) and phylogenetic trait imputation using + structural equation models (SEM), extending methods from Thorson et al. (2023) . + This implementation includes a minimal set of features, to + allow users to easily read all of the documentation and source code. PCM using SEM + includes phylogenetic linear models and structural equation models as nested submodels, + but also allows imputation of missing values. Features and comparison with other packages + are described in Thorson and van der Bijl (2023) . + date_publication: '2024-04-02' + bug_reports: https://github.com/James-Thorson-NOAA/phylosem/issues + url: https://james-thorson-noaa.github.io/phylosem/ + url_cran: https://CRAN.R-project.org/package=phylosem + url_git: '' +phyloseqGraphTest: + version: 0.1.1 + title: Graph-Based Permutation Tests for Microbiome Data + maintainer: Julia Fukuyama + description: |- + Provides functions for graph-based multiple-sample + testing and visualization of microbiome data, in particular data + stored in 'phyloseq' objects. The tests are based on those + described in Friedman and Rafsky (1979) + , and the tests are described + in more detail in Callahan et al. (2016) + . + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phyloseqGraphTest + url_git: https://github.com/jfukuyama/phyloseqGraphTest +phylosignal: + version: 1.3.1 + title: Exploring the Phylogenetic Signal in Continuous Traits + maintainer: Francois Keck + description: A collection of tools to explore the phylogenetic signal in univariate + and multivariate data. The package provides functions to plot traits data against + a phylogenetic tree, different measures and tests for the phylogenetic signal, + methods to describe where the signal is located and a phylogenetic clustering + method. + date_publication: '2023-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylosignal + url_git: '' +phylosignalDB: + version: 0.2.2 + title: Explore Phylogenetic Signals Using Distance-Based Methods + maintainer: Liang Yao + description: A unified method, called M statistic, is provided for detecting phylogenetic + signals in continuous traits, discrete traits, and multi-trait combinations. Blomberg + and Garland (2002) provided a widely accepted + statistical definition of the phylogenetic signal, which is the "tendency for + related species to resemble each other more than they resemble species drawn at + random from the tree". The M statistic strictly adheres to the definition of phylogenetic + signal, formulating an index and developing a method of testing in strict accordance + with the definition, instead of relying on correlation analysis or evolutionary + models. The novel method equivalently expressed the textual definition of the + phylogenetic signal as an inequality equation of the phylogenetic and trait distances + and constructed the M statistic. Also, there are more distance-based methods under + development. + date_publication: '2025-01-16' + bug_reports: https://github.com/anonymous-eco/phylosignalDB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phylosignalDB + url_git: https://github.com/anonymous-eco/phylosignalDB +phylospatial: + version: 1.0.0 + title: Spatial Phylogenetic Analysis + maintainer: Matthew Kling + description: |- + Conduct various analyses on spatial phylogenetics. Use your data + on an evolutionary tree and geographic distributions of the terminal taxa + to compute diversity and endemism metrics, test significance with null + model randomization, analyze community turnover and biotic regionalization, + and perform spatial conservation prioritizations. All functions support + quantitative community data in addition to binary data. + date_publication: '2025-01-24' + bug_reports: '' + url: https://matthewkling.github.io/phylospatial/ + url_cran: https://CRAN.R-project.org/package=phylospatial + url_git: '' +phylotate: + version: '1.3' + title: Phylogenies with Annotations + maintainer: Daniel Beer + description: |- + Functions to read and write APE-compatible phylogenetic + trees in NEXUS and Newick formats, while preserving annotations. + date_publication: '2019-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylotate + url_git: '' +phylotools: + version: 0.2.2 + title: Phylogenetic Tools for Eco-Phylogenetics + maintainer: Jinlong Zhang + description: |- + A collection of tools for building RAxML supermatrix using + PHYLIP or aligned FASTA files. These functions will be + useful for building large phylogenies using multiple markers. + date_publication: '2017-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phylotools + url_git: https://github.com/helixcn/phylotools +phyloTop: + version: 2.1.2 + title: Calculating Topological Properties of Phylogenies + maintainer: Michelle Kendall + description: Tools for calculating and viewing topological properties of phylogenetic + trees. + date_publication: '2023-01-24' + bug_reports: '' + url: https://michellekendall.github.io/phyloTop/ + url_cran: https://CRAN.R-project.org/package=phyloTop + url_git: https://github.com/MichelleKendall/phyloTop +phylotypr: + version: 0.1.1 + title: Classifying DNA Sequences to Taxonomic Groupings + maintainer: Pat Schloss + description: Classification based analysis of DNA sequences to taxonomic groupings. + This package primarily implements Naive Bayesian Classifier from the Ribosomal + Database Project. This approach has traditionally been used to classify 16S rRNA + gene sequences to bacterial taxonomic outlines; however, it can be used for any + type of gene sequence. The method was originally described by Wang, Garrity, Tiedje, + and Cole in Applied and Environmental Microbiology 73(16):5261-7 . + The package also provides functions to read in 'FASTA'-formatted sequence data. + date_publication: '2025-02-21' + bug_reports: https://github.com/mothur/phylotypr/issues + url: https://mothur.org/phylotypr/ + url_cran: https://CRAN.R-project.org/package=phylotypr + url_git: https://github.com/mothur/phylotypr +phylter: + version: 0.9.11 + title: Detect and Remove Outliers in Phylogenomics Datasets + maintainer: Aurélie Siberchicot + description: |- + Analyzis and filtering of phylogenomics datasets. + It takes an input either a collection of gene trees (then transformed to matrices) or directly a collection of gene matrices and performs an iterative process to identify + what species in what genes are outliers, and whose elimination significantly improves the concordance between the input matrices. The methods builds upon the Distatis approach (Abdi et al. (2005) ), a generalization of classical multidimensional scaling to multiple distance matrices. + date_publication: '2023-08-24' + bug_reports: https://github.com/damiendevienne/phylter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=phylter + url_git: '' +phyr: + version: 1.1.0 + title: Model Based Phylogenetic Analysis + maintainer: Daijiang Li + description: |- + A collection of functions to do model-based phylogenetic analysis. + It includes functions to calculate community phylogenetic diversity, + to estimate correlations among functional traits while accounting for + phylogenetic relationships, and to fit phylogenetic generalized linear + mixed models. The Bayesian phylogenetic generalized linear mixed models + are fitted with the 'INLA' package (). + date_publication: '2020-12-18' + bug_reports: https://github.com/daijiang/phyr/issues + url: https://daijiang.github.io/phyr/ + url_cran: https://CRAN.R-project.org/package=phyr + url_git: https://github.com/daijiang/phyr/ +phyreg: + version: 1.0.2 + title: The Phylogenetic Regression of Grafen (1989) + maintainer: Alan Grafen + description: Provides general linear model facilities (single y-variable, multiple + x-variables with arbitrary mixture of continuous and categorical and arbitrary + interactions) for cross-species data. The method is, however, based on the nowadays + rather uncommon situation in which uncertainty about a phylogeny is well represented + by adopting a single polytomous tree. The theory is in A. Grafen (1989, Proc. + R. Soc. B 326, 119-157) and aims to cope with both recognised phylogeny (closely + related species tend to be similar) and unrecognised phylogeny (a polytomy usually + indicates ignorance about the true sequence of binary splits). + date_publication: '2018-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phyreg + url_git: '' +PhysActBedRest: + version: '1.1' + title: Marks Periods of 'Bedrest' in Actigraph Accelerometer Data + maintainer: J. Dustin Tracy + description: Contains a function to categorize accelerometer readings collected + in free-living (e.g., for 24 hours/day for 7 days), preprocessed and compressed + as counts (unit-less value) in a specified time period termed epoch (e.g., 1 minute) + as either bedrest (sleep) or active. The input is a matrix with a timestamp column + and a column with number of counts per epoch. The output is the same dataframe + with an additional column termed bedrest. In the bedrest column each line (epoch) + contains a function-generated classification 'br' or 'a' denoting bedrest/sleep + and activity, respectively. The package is designed to be used after wear/nonwear + marking function in the 'PhysicalActivity' package. Version 1.1 adds preschool + thresholds and corrects for possible errors in algorithm implementation. + date_publication: '2020-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PhysActBedRest + url_git: '' +PhysicalActivity: + version: 0.2-4 + title: Process Accelerometer Data for Physical Activity Measurement + maintainer: Leena Choi + description: |- + It provides a function "wearingMarking" for classification of monitor + wear and nonwear time intervals in accelerometer data collected to assess + physical activity. The package also contains functions for making plot for + accelerometer data and obtaining the summary of various information including + daily monitor wear time and the mean monitor wear time during valid days. + "deliveryPred" and "markDelivery" can classify days for ActiGraph delivery by mail; + "deliveryPreprocess" can process accelerometry data for analysis by zeropadding incomplete + days and removing low activity days; "markPAI" can categorize physical activity + intensity level based on user-defined cut-points of accelerometer counts. It also + supports importing ActiGraph AGD files with "readActigraph" and "queryActigraph" functions. + date_publication: '2021-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PhysicalActivity + url_git: '' +PhySortR: + version: 1.0.9 + title: A Fast, Flexible Tool for Sorting Phylogenetic Trees + maintainer: Timothy Stephens + description: |- + Screens and sorts phylogenetic trees in both traditional and + extended Newick format. Allows for the fast and flexible screening (within + a tree) of Exclusive clades that comprise only the target taxa and/or Non- + Exclusive clades that includes a defined portion of non-target taxa. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PhySortR + url_git: '' +phytoclass: + version: 2.0.0 + title: Estimate Chla Concentrations of Phytoplankton Groups + maintainer: Alexander Hayward + description: |- + Determine the chlorophyll a (Chl a) concentrations of different + phytoplankton groups based on their pigment biomarkers. The method uses + non-negative matrix factorisation and simulated annealing to minimise error + between the observed and estimated values of pigment concentrations + (Hayward et al. (2023) ). + The approach is similar to the widely used 'CHEMTAX' program + (Mackey et al. 1996) , but is more straightforward, + accurate, and not reliant on initial guesses for the pigment to Chl a + ratios for phytoplankton groups. + date_publication: '2024-11-14' + bug_reports: https://github.com/phytoclass/phytoclass/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=phytoclass + url_git: https://github.com/phytoclass/phytoclass/ +phytools: + version: 2.4-4 + title: Phylogenetic Tools for Comparative Biology (and Other Things) + maintainer: Liam J. Revell + description: A wide range of methods for phylogenetic analysis - concentrated in + phylogenetic comparative biology, but also including numerous techniques for visualizing, + analyzing, manipulating, reading or writing, and even inferring phylogenetic trees. + Included among the functions in phylogenetic comparative biology are various for + ancestral state reconstruction, model-fitting, and simulation of phylogenies and + trait data. A broad range of plotting methods for phylogenies and comparative + data include (but are not restricted to) methods for mapping trait evolution on + trees, for projecting trees into phenotype space or a onto a geographic map, and + for visualizing correlated speciation between trees. Lastly, numerous functions + are designed for reading, writing, analyzing, inferring, simulating, and manipulating + phylogenetic trees and comparative data. For instance, there are functions for + computing consensus phylogenies from a set, for simulating phylogenetic trees + and data under a range of models, for randomly or non-randomly attaching species + or clades to a tree, as well as for a wide range of other manipulations and analyses + that phylogenetic biologists might find useful in their research. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=phytools + url_git: https://github.com/liamrevell/phytools +PhytosanitaryCalculator: + version: 1.1.3 + title: Phytosanitary Calculator for Inspection Plans Based on Risks + maintainer: Gustavo Ramirez-Valverde + description: A 'Shiny' application for calculating phytosanitary inspection plans + based on risks. It generates a diagram of pallets in a lot, highlights the units + to be sampled, and documents them based on the selected sampling method (simple + random or systematic sampling). + date_publication: '2024-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PhytosanitaryCalculator + url_git: '' +piar: + version: 0.8.1 + title: Price Index Aggregation + maintainer: Steve Martin + description: |- + Most price indexes are made with a two-step procedure, where + period-over-period elemental indexes are first calculated for a collection + of elemental aggregates at each point in time, and then aggregated according + to a price index aggregation structure. These indexes can then be chained + together to form a time series that gives the evolution of prices with + respect to a fixed base period. This package contains a collection of + functions that revolve around this work flow, making it easy to build + standard price indexes, and implement the methods described by + Balk (2008, ), von der Lippe (2007, + ), and the CPI manual (2020, + ) for bilateral price indexes. + date_publication: '2024-09-12' + bug_reports: https://github.com/marberts/piar/issues + url: https://marberts.github.io/piar/ + url_cran: https://CRAN.R-project.org/package=piar + url_git: https://github.com/marberts/piar +PiC: + version: 1.0.3 + title: Pointcloud Interactive Computation for Forest Structure Analysis + maintainer: Roberto Ferrara + description: |- + Provides advanced algorithms for analyzing pointcloud data in + forestry applications. Key features include fast voxelization of + large datasets; segmentation of point clouds into forest floor, + understorey, canopy, and wood components. The package enables + efficient processing of large-scale forest pointcloud data, offering + insights into forest structure, connectivity, and fire risk + assessment. Algorithms to analyze pointcloud data (.xyz input file). + For more details, see Ferrara & Arrizza (2025) . + For single tree segmentation details, see Ferrara et al. (2018) + . + date_publication: '2025-02-18' + bug_reports: https://github.com/rupppy/PiC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PiC + url_git: https://github.com/rupppy/PiC +picante: + version: 1.8.2 + title: Integrating Phylogenies and Ecology + maintainer: Steven W. Kembel + description: Functions for phylocom integration, community analyses, null-models, + traits and evolution. Implements numerous ecophylogenetic approaches including + measures of community phylogenetic and trait diversity, phylogenetic signal, estimation + of trait values for unobserved taxa, null models for community and phylogeny randomizations, + and utility functions for data input/output and phylogeny plotting. A full description + of package functionality and methods are provided by Kembel et al. (2010) . + date_publication: '2020-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=picante + url_git: '' +PICBayes: + version: '1.0' + title: Bayesian Models for Partly Interval-Censored Data + maintainer: Chun Pan + description: Contains functions to fit proportional hazards (PH) model to partly + interval-censored (PIC) data (Pan et al. (2020) ), + PH model with spatial frailty to spatially dependent PIC data (Pan and Cai (2021) + ), and mixed effects PH model to clustered + PIC data. Each random intercept/random effect can follow both a normal prior and + a Dirichlet process mixture prior. It also includes the corresponding functions + for general interval-censored data. + date_publication: '2021-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PICBayes + url_git: '' +picClip: + version: 0.1.0 + title: Paste Box Input for 'Shiny' + maintainer: Matt Deppe + description: |- + Provides a 'Shiny' input widget, pasteBoxInput, + that allows users to paste images directly into a 'Shiny' + application. The pasted images are captured as Base64 + encoded strings and can be used within the application + for various purposes, such as display or further processing. + This package is particularly useful for applications that + require easy and quick image uploads without the need for + traditional file selection dialog boxes. + date_publication: '2023-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=picClip + url_git: https://github.com/deppemj/picClip +picker: + version: 0.2.6 + title: Pick Data Points from a Deck.gl Scatterplot + maintainer: Alex Pickering + description: |- + Performant interactive scatterplot for ~ 1 million points. Zoom, pan, + and pick points. Includes tooltips, labels, a grid overlay, legend, and + coupled interactions across multiple plots. + date_publication: '2022-03-31' + bug_reports: https://github.com/hms-dbmi/picker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=picker + url_git: https://github.com/hms-dbmi/picker +picohdr: + version: 0.1.1 + title: Read, Write and Manipulate High Dynamic Range Images + maintainer: Mike Cheng + description: |- + High Dynamic Range (HDR) images support a large range in luminosity + between the lightest and darkest regions of an image. To capture this range, + data in HDR images is often stored as floating point numbers and in formats + that capture more data and channels than standard image types. This package supports + reading and writing two types of HDR images; PFM (Portable Float Map) + and OpenEXR images. HDR images can be converted to lower + dynamic ranges (for viewing) using tone-mapping. A number of + tone-mapping algorithms are included which are based on + Reinhard (2002) "Photographic tone reproduction for digital images" + . + date_publication: '2024-10-28' + bug_reports: https://github.com/coolbutuseless/picohdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=picohdr + url_git: https://github.com/coolbutuseless/picohdr +picR: + version: 1.0.0 + title: Predictive Information Criteria for Model Selection + maintainer: Javier Flores + description: |- + Computation of predictive information criteria (PIC) from select model object classes + for model selection in predictive contexts. In contrast to the more widely used Akaike + Information Criterion (AIC), which are derived under the assumption that target(s) of prediction + (i.e. validation data) are independently and identically distributed to the fitting data, the PIC + are derived under less restrictive assumptions and thus generalize AIC to the more practically + relevant case of training/validation data heterogeneity. The methodology featured in this package is based on Flores (2021) "A new class of information criteria for improved prediction in the presence of training/validation data heterogeneity". + date_publication: '2022-10-24' + bug_reports: https://github.com/javenrflo/picR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=picR + url_git: https://github.com/javenrflo/picR +pid: + version: '0.50' + title: Process Improvement using Data + maintainer: Kevin Dunn + description: |- + A collection of scripts and data files for the statistics text: + "Process Improvement using Data" and the online + course "Experimentation for Improvement" found on Coursera. The package + contains code for designed experiments, data sets and other convenience + functions used in the book. + date_publication: '2018-11-23' + bug_reports: https://bitbucket.org/kevindunn/r-pid + url: https://learnche.org/pid + url_cran: https://CRAN.R-project.org/package=pid + url_git: '' +PIE: + version: 1.0.0 + title: A Partially Interpretable Model with Black-Box Refinement + maintainer: Jingyi Yang + description: Implements a novel predictive model, Partially Interpretable Estimators + (PIE), which jointly trains an interpretable model and a black-box model to achieve + high predictive performance as well as partial model. See the paper, Wang, Yang, + Li, and Wang (2021) . + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PIE + url_git: '' +PieceExpIntensity: + version: 1.0.4 + title: |- + Bayesian Model to Find Changepoints Based on Rates and Count + Data + maintainer: Andrew G. Chapple + description: This function fits a reversible jump Bayesian piecewise exponential + model that also includes the intensity of each event considered along with the + rate of events. + date_publication: '2018-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PieceExpIntensity + url_git: '' +piecemaker: + version: 1.0.2 + title: Tools for Preparing Text for Tokenizers + maintainer: Jon Harmon + description: |- + Tokenizers break text into pieces that are more usable by + machine learning models. Many tokenizers share some preparation steps. + This package provides those shared steps, along with a simple + tokenizer. + date_publication: '2023-06-02' + bug_reports: https://github.com/macmillancontentscience/piecemaker/issues + url: https://macmillancontentscience.github.io/piecemaker/ + url_cran: https://CRAN.R-project.org/package=piecemaker + url_git: https://github.com/macmillancontentscience/piecemaker +piecenorms: + version: 1.1.0 + title: Calculate a Piecewise Normalised Score Using Class Intervals + maintainer: David Hammond + description: Provides an implementation of piecewise normalisation techniques useful + when dealing with the communication of skewed and highly skewed data. It also + provides utilities that recommends a normalisation technique based on the distribution + of the data. + date_publication: '2024-07-29' + bug_reports: https://github.com/david-hammond/piecenorms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=piecenorms + url_git: https://github.com/david-hammond/piecenorms +piecepackr: + version: 1.14.1 + title: Board Game Graphics + maintainer: Trevor L. Davis + description: Functions to make board game graphics with the 'ggplot2', 'grid', 'rayrender', + 'rayvertex', and 'rgl' packages. Specializes in game diagrams, animations, and + "Print & Play" layouts for the 'piecepack' but + can make graphics for other board game systems. Includes configurations for several + public domain game systems such as checkers, (double-18) dominoes, go, 'piecepack', + playing cards, etc. + date_publication: '2025-01-12' + bug_reports: https://github.com/piecepackr/piecepackr/issues + url: https://trevorldavis.com/piecepackr/(blog) + url_cran: https://CRAN.R-project.org/package=piecepackr + url_git: '' +piecewiseSEM: + version: 2.3.0.1 + title: Piecewise Structural Equation Modeling + maintainer: Jon Lefcheck + description: |- + Implements piecewise structural equation modeling from a single + list of structural equations, with new methods for non-linear, latent, and + composite variables, standardized coefficients, query-based prediction and + indirect effects. See for more. + date_publication: '2024-06-11' + bug_reports: https://github.com/jslefche/piecewiseSEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=piecewiseSEM + url_git: https://github.com/jslefche/ +PieGlyph: + version: 1.0.0 + title: Axis Invariant Scatter Pie Plots + maintainer: Rishabh Vishwakarma + description: Extends 'ggplot2' to help replace points in a scatter plot with pie-chart + glyphs showing the relative proportions of different categories. The pie glyphs + are independent of the axes and plot dimensions, to prevent distortions when the + plot dimensions are changed. + date_publication: '2024-06-28' + bug_reports: https://github.com/rishvish/PieGlyph/issues + url: https://rishvish.github.io/PieGlyph/ + url_cran: https://CRAN.R-project.org/package=PieGlyph + url_git: https://github.com/rishvish/PieGlyph +piggyback: + version: 0.1.5 + title: Managing Larger Data on a GitHub Repository + maintainer: Carl Boettiger + description: |- + Because larger (> 50 MB) data files cannot easily be committed to git, + a different approach is required to manage data associated with an analysis in a + GitHub repository. This package provides a simple work-around by allowing larger + (up to 2 GB) data files to piggyback on a repository as assets attached to individual + GitHub releases. These files are not handled by git in any way, but instead are + uploaded, downloaded, or edited directly by calls through the GitHub API. These + data files can be versioned manually by creating different releases. This approach + works equally well with public or private repositories. Data can be uploaded + and downloaded programmatically from scripts. No authentication is required to + download data from public repositories. + date_publication: '2023-07-10' + bug_reports: https://github.com/ropensci/piggyback/issues + url: '' + url_cran: https://CRAN.R-project.org/package=piggyback + url_git: https://github.com/ropensci/piggyback +pii: + version: 1.3.0 + title: Search Data Frames for Personally Identifiable Information + maintainer: Jacob Patterson-Stein + description: Check a data frame for personal information, including names, location, + disability status, and geo-coordinates. + date_publication: '2025-01-13' + bug_reports: https://github.com/jacobpstein/pii/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pii + url_git: https://github.com/jacobpstein/pii +Pijavski: + version: 1.0.3 + title: Global Univariate Minimization + maintainer: Gleb Beliakov + description: Global univariate minimization of Lipschitz functions is performed + by using Pijavski method, which was published in Pijavski (1972) . + date_publication: '2020-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Pijavski + url_git: '' +pikchr: + version: '1.0' + title: R Wrapper for 'pikchr' (PIC) Diagram Language + maintainer: Andre Leite + description: An 'R' interface to 'pikchr' (, pronounced “picture”), + a 'PIC'-like markup language for creating diagrams within technical documentation. + Originally developed by Brian Kernighan, 'PIC' has been adapted into 'pikchr' + by D. Richard Hipp, the creator of 'SQLite'. 'pikchr' is designed to be embedded + in fenced code blocks of Markdown or other documentation markup languages, making + it ideal for generating diagrams in text-based formats. This package allows R + users to seamlessly integrate the descriptive syntax of 'pikchr' for diagram creation + directly within the 'R' environment. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pikchr + url_git: +pillar: + version: 1.10.1 + title: Coloured Formatting for Columns + maintainer: Kirill Müller + description: |- + Provides 'pillar' and 'colonnade' generics designed + for formatting columns of data using the full range of colours + provided by modern terminals. + date_publication: '2025-01-07' + bug_reports: https://github.com/r-lib/pillar/issues + url: https://pillar.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=pillar + url_git: https://github.com/r-lib/pillar +pim: + version: 2.0.4 + title: Fit Probabilistic Index Models + maintainer: Joris Meys + description: |- + Fit a probabilistic index model as described in + Thas et al, 2012: . The interface to the + modeling function has changed in this new version. The old version is + still available at R-Forge. + date_publication: '2025-01-08' + bug_reports: https://github.com/CenterForStatistics-UGent/pim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pim + url_git: https://github.com/CenterForStatistics-UGent/pim +pimeta: + version: 1.1.3 + title: Prediction Intervals for Random-Effects Meta-Analysis + maintainer: Kengo Nagashima + description: |- + An implementation of prediction intervals for random-effects meta-analysis: + Higgins et al. (2009) , Partlett and Riley (2017) + , and Nagashima et al. (2019) , + . + date_publication: '2019-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pimeta + url_git: '' +pinfsc50: + version: 1.3.0 + title: |- + Sequence ('FASTA'), Annotation ('GFF') and Variants ('VCF') for + 17 Samples of 'P. Infestans" and 1 'P. Mirabilis' + maintainer: Brian J. Knaus + description: |- + Genomic data for the plant pathogen "Phytophthora infestans." It + includes a variant file ('VCF'), a sequence file ('FASTA') and an annotation file + ('GFF'). This package is intended to be used as example data for packages that + work with genomic data. + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pinfsc50 + url_git: '' +pingers: + version: 0.1.1 + title: Identify, Ping, and Log Internet Provider Connection Data + maintainer: Jesse Vent + description: |- + To assist you with troubleshooting internet connection issues and + assist in isolating packet loss on your network. It does this by allowing you to + retrieve the top trace route destinations your internet provider uses, and recursively + ping each server in series while capturing the results and writing them to a log file. + Each iteration it queries the destinations again, before shuffling the sequence of + destinations to ensure the analysis is unbiased and consistent across each trace route. + date_publication: '2018-10-26' + bug_reports: https://github.com/JesseVent/pingers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pingers + url_git: https://github.com/JesseVent/pingers +pingr: + version: 2.0.5 + title: Check if a Remote Computer is Up + maintainer: Gábor Csárdi + description: |- + Check if a remote computer is up. It can either just call the + system ping command, or check a specified TCP port. + date_publication: '2024-12-12' + bug_reports: https://github.com/r-lib/pingr/issues + url: https://r-lib.github.io/pingr/ + url_cran: https://CRAN.R-project.org/package=pingr + url_git: https://github.com/r-lib/pingr +PINMA: + version: 1.1-2 + title: |- + Improved Methods for Constructing Prediction Intervals for + Network Meta-Analysis + maintainer: Hisashi Noma + description: Improved methods to construct prediction intervals for network meta-analysis. + The parametric bootstrap and Kenward-Roger-type adjustment by Noma et al. (2022) + are implementable. + date_publication: '2023-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PINMA + url_git: '' +pinnacle.data: + version: 0.1.4 + title: Market Odds Data from Pinnacle + maintainer: Marco Blume + description: Market odds from from Pinnacle, an online sports betting bookmaker + (see for more information). Included are datasets for + the Major League Baseball (MLB) 2016 season and the USA election 2016. These datasets + can be used to build models and compare statistical information with the information + from prediction markets.The Major League Baseball (MLB) 2016 dataset can be used + for sabermetrics analysis and also can be used in conjunction with other popular + Major League Baseball (MLB) datasets such as Retrosheets or the Lahman package + by merging by GameID. + date_publication: '2017-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pinnacle.data + url_git: https://github.com/marcoblume/pinnacle.data +pinochet: + version: 0.1.0 + title: Data About the Victims of the Pinochet Regime, 1973-1990 + maintainer: Danilo Freire + description: Packages data about the victims of the Pinochet regime as compiled + by the Chilean National Commission for Truth and Reconciliation Report (1991, + ISBN:9780268016463). + date_publication: '2019-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pinochet + url_git: http://github.com/danilofreire/pinochet +pinp: + version: 0.0.11 + title: '''pinp'' is not ''PNAS''' + maintainer: Dirk Eddelbuettel + description: |- + A 'PNAS'-alike style for 'rmarkdown', derived from the 'Proceedings of the + National Academy of Sciences of the United States of America' ('PNAS') 'LaTeX' style, + and adapted for use with 'markdown' and 'pandoc'. + date_publication: '2024-12-08' + bug_reports: https://github.com/eddelbuettel/pinp/issues + url: http://dirk.eddelbuettel.com/code/pinp.html + url_cran: https://CRAN.R-project.org/package=pinp + url_git: https://github.com/eddelbuettel/pinp +pins: + version: 1.4.0 + title: Pin, Discover, and Share Resources + maintainer: Julia Silge + description: |- + Publish data sets, models, and other R objects, making it + easy to share them across projects and with your colleagues. You can + pin objects to a variety of "boards", including local folders (to + share on a networked drive or with 'DropBox'), 'Posit Connect', + 'AWS S3', and more. + date_publication: '2024-10-07' + bug_reports: https://github.com/rstudio/pins-r/issues + url: https://pins.rstudio.com/ + url_cran: https://CRAN.R-project.org/package=pins + url_git: https://github.com/rstudio/pins-r +PINSPlus: + version: 2.0.7 + title: Clustering Algorithm for Data Integration and Disease Subtyping + maintainer: Van-Dung Pham + description: 'Provides a robust approach for omics data integration and disease + subtyping. PINSPlus is fast and supports the analysis of large datasets with hundreds + of thousands of samples and features. The software automatically determines the + optimal number of clusters and then partitions the samples in a way such that + the results are robust against noise and data perturbation (Nguyen et al. (2019) + , Nguyen et al. (2017), + Nguyen et al. (2021)).' + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PINSPlus + url_git: '' +PINstimation: + version: 0.1.2 + title: Estimation of the Probability of Informed Trading + maintainer: Montasser Ghachem + description: 'A comprehensive bundle of utilities for the estimation of probability + of informed trading models: original PIN in Easley and O''Hara (1992) and Easley + et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in + Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, + 2012). Implementations of various estimation methods suggested in the literature + are included. Additional compelling features comprise posterior probabilities, + an implementation of an expectation-maximization (EM) algorithm, and PIN decomposition + into layers, and into bad/good components. Versatile data simulation tools, and + trade classification algorithms are among the supplementary utilities. The package + provides fast, compact, and precise utilities to tackle the sophisticated, error-prone, + and time-consuming estimation procedure of informed trading, and this solely using + the raw trade-level data.' + date_publication: '2023-03-20' + bug_reports: https://github.com/monty-se/PINstimation/issues + url: https://www.pinstimation.com + url_cran: https://CRAN.R-project.org/package=PINstimation + url_git: https://github.com/monty-se/PINstimation +pinterestadsR: + version: 0.1.0 + title: Access to Pinterest Ads via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: |- + Collect marketing data from Pinterest Ads using the 'Windsor.ai' API . + Use four spaces when indenting paragraphs within the Description. + date_publication: '2022-10-17' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=pinterestadsR + url_git: '' +pinyin: + version: 1.1.6 + title: |- + Convert Chinese Characters into Pinyin, Sijiao, Wubi or Other + Codes + maintainer: Peng Zhao + description: Convert Chinese characters into Pinyin (the official romanization system + for Standard Chinese in mainland China, Malaysia, Singapore, and Taiwan. See + for details), Sijiao (four or five numerical digits per character. See .), + Wubi (an input method with five strokes. See ) + or user-defined codes. + date_publication: '2019-05-02' + bug_reports: https://github.com/pzhaonet/pinyin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pinyin + url_git: https://github.com/pzhaonet/pinyin +pioneeR: + version: 0.5.0 + title: Productivity and Efficiency Analysis using DEA + maintainer: Ove Haugland Jakobsen + description: |- + Measure productivity and efficiency using Data Envelopment Analysis + (DEA). Available methods include DEA under different technology assumptions, + bootstrapping of efficiency scores and calculation of the Malmquist + productivity index. Analyses can be performed either in the console or with + the provided 'shiny' app. See Banker, R.; Charnes, A.; Cooper, W.W. (1984) + , Färe, R.; Grosskopf, S. (1996) . + date_publication: '2024-10-25' + bug_reports: https://github.com/Riksrevisjonen/pioneeR/issues + url: https://riksrevisjonen.github.io/pioneeR/ + url_cran: https://CRAN.R-project.org/package=pioneeR + url_git: https://github.com/Riksrevisjonen/pioneeR +pipe.design: + version: 0.5.1 + title: |- + Dual-Agent Dose Escalation for Phase I Trials using the PIPE + Design + maintainer: Michael Sweeting + description: Implements the Product of Independent beta Probabilities dose Escalation + (PIPE) design for dual-agent Phase I trials as described in Mander AP, Sweeting + MJ (2015) . + date_publication: '2017-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pipe.design + url_git: '' +pipebind: + version: 0.1.2 + title: |- + Flexible Binding for Complex Function Evaluation with the Base R + |> Pipe + maintainer: Brenton M. Wiernik + description: |- + Provides a simple function to bind a piped object to a placeholder + symbol to enable complex function evaluation with the base R |> pipe. + date_publication: '2023-08-30' + bug_reports: https://github.com/bwiernik/pipebind/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pipebind + url_git: https://github.com/bwiernik/pipebind/ +pipefittr: + version: 0.1.2 + title: Convert Nested Functions to Pipes + maintainer: Sahil Seth + description: To take nested function calls and convert them to a more readable form + using pipes from package 'magrittr'. + date_publication: '2016-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pipefittr + url_git: '' +pipeflow: + version: 0.2.2 + title: Lightweight, General-Purpose Data Analysis Pipelines + maintainer: Roman Pahl + description: |- + A lightweight yet powerful framework for building robust data + analysis pipelines. With 'pipeflow', you initialize a pipeline with your + dataset and construct workflows step by step by adding R functions. + You can modify, remove, or insert steps and parameters at any stage, + while 'pipeflow' ensures the pipeline's integrity. + Overall, this package offers a beginner-friendly framework that simplifies + and streamlines the development of data analysis pipelines by making + them modular, intuitive, and adaptable. + date_publication: '2024-12-22' + bug_reports: https://github.com/rpahl/pipeflow/issues + url: https://rpahl.github.io/pipeflow/ + url_cran: https://CRAN.R-project.org/package=pipeflow + url_git: https://github.com/rpahl/pipeflow +pipeliner: + version: 0.1.1 + title: Machine Learning Pipelines for R + maintainer: Alex Ioannides + description: |- + A framework for defining 'pipelines' of functions for applying data transformations, + model estimation and inverse-transformations, resulting in predicted value generation (or + model-scoring) functions that automatically apply the entire pipeline of functions required to go + from input to predicted output. + date_publication: '2016-12-19' + bug_reports: https://github.com/alexioannides/pipeliner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pipeliner + url_git: https://github.com/alexioannides/pipeliner +pipenostics: + version: 0.2.0 + title: |- + Diagnostics, Reliability and Predictive Maintenance of Pipeline + Systems + maintainer: Yuri Possokhov + description: |- + Functions representing some useful empirical and data-driven + models of heat loss, corrosion diagnostics, reliability and predictive + maintenance of pipeline systems. The package is an option for technical + engineering departments of heat generating and heat transfer companies + that use or plan to use regulatory calculations in their activities. + Methods are described in + Timashev et al. (2016) , + A.C.Reddy (2017) , + Minenergo (2008) , + Minenergo (2005) , + Xing LU. (2014) . + date_publication: '2024-04-04' + bug_reports: https://github.com/omega1x/pipenostics/issues + url: https://omega1x.github.io/pipenostics/ + url_cran: https://CRAN.R-project.org/package=pipenostics + url_git: '' +pipeR: + version: 0.6.1.3 + title: Multi-Paradigm Pipeline Implementation + maintainer: Kun Ren + description: |- + Provides various styles of function chaining methods: Pipe + operator, Pipe object, and pipeline function, each representing a distinct + pipeline model yet sharing almost a common set of features: A value can be + piped to the first unnamed argument of a function and to dot symbol in an + enclosed expression. The syntax is designed to make the pipeline more + readable and friendly to a wide range of operations. + date_publication: '2016-04-04' + bug_reports: https://github.com/renkun-ken/pipeR/issues + url: https://renkun.me/pipeR + url_cran: https://CRAN.R-project.org/package=pipeR + url_git: https://github.com/renkun-ken/pipeR +piqp: + version: 0.2.2 + title: |- + R Interface to Proximal Interior Point Quadratic Programming + Solver + maintainer: Balasubramanian Narasimhan + description: An embedded proximal interior point quadratic programming solver, which + can solve dense and sparse quadratic programs, described in Schwan, Jiang, Kuhn, + and Jones (2023) . Combining an infeasible interior + point method with the proximal method of multipliers, the algorithm can handle + ill-conditioned convex quadratic programming problems without the need for linear + independence of the constraints. The solver is written in header only 'C++ 14' + leveraging the 'Eigen' library for vectorized linear algebra. For small dense + problems, vectorized instructions and cache locality can be exploited more efficiently. + Allocation free problem updates and re-solves are also provided. + date_publication: '2023-08-14' + bug_reports: https://github.com/PREDICT-EPFL/piqp-r/issues + url: https://predict-epfl.github.io/piqp-r/ + url_cran: https://CRAN.R-project.org/package=piqp + url_git: '' +piratings: + version: 0.1.9 + title: Calculate Pi Ratings for Teams Competing in Sport Matches + maintainer: Lars Van Cutsem + description: |- + Calculate and optimize dynamic performance ratings of association football + teams competing in matches, in accordance with the method used in + the research paper "Determining the level of ability of football teams by + dynamic ratings based on the relative discrepancies in scores between adversaries", + by Constantinou and Fenton (2013) + + This dynamic rating system has proven to provide superior + results for predicting association football outcomes. + date_publication: '2019-05-27' + bug_reports: https://github.com/larsvancutsem/piratings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=piratings + url_git: '' +pisaRT: + version: 2.0.2 + title: Small Example Response and Response Time Data from PISA 2018 + maintainer: Benjamin Becker + description: Scored responses and responses times from the Canadian subsample of + the PISA 2018 assessment, accessible as the "Cognitive items total time/visits + data file" by OECD (2020) . + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pisaRT + url_git: '' +piton: + version: 1.0.0 + title: Parsing Expression Grammars in Rcpp + maintainer: Os Keyes + description: |- + A wrapper around the 'Parsing Expression Grammar Template Library', a C++11 library for generating + Parsing Expression Grammars, that makes it accessible within Rcpp. With this, developers can implement + their own grammars and easily expose them in R packages. + date_publication: '2020-11-15' + bug_reports: https://github.com/Ironholds/piton/issues + url: '' + url_cran: https://CRAN.R-project.org/package=piton + url_git: https://github.com/Ironholds/piton +pivmet: + version: 0.6.0 + title: Pivotal Methods for Bayesian Relabelling and k-Means Clustering + maintainer: Leonardo Egidi + description: |- + Collection of pivotal algorithms + for: relabelling the MCMC chains in order to undo the label + switching problem in Bayesian mixture models; + fitting sparse finite mixtures; + initializing the centers of the classical k-means algorithm + in order to obtain a better clustering solution. + For further details see + Egidi, Pappadà, Pauli and Torelli (2018b). + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pivmet + url_git: https://github.com/leoegidi/pivmet +PivotalP: + version: 0.1.2 + title: |- + Prediction for Future Data from Mixture Distributions Gamma, + Beta, Weibull and Normal + maintainer: K. S. Khalil + description: Functions to get prediction intervals and prediction points of future + observations from mixture distributions like gamma, beta, Weibull and normal. + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PivotalP + url_git: '' +pivotaltrackR: + version: 0.2.0 + title: A Client for the 'Pivotal Tracker' API + maintainer: Neal Richardson + description: |- + 'Pivotal Tracker' is a project + management software-as-a-service that provides a REST API. This package + provides an R interface to that API, allowing you to query it and work with + its responses. + date_publication: '2021-01-10' + bug_reports: https://github.com/nealrichardson/pivotaltrackR/issues + url: https://enpiar.com/r/pivotaltrackR/ + url_cran: https://CRAN.R-project.org/package=pivotaltrackR + url_git: https://github.com/nealrichardson/pivotaltrackR/ +pivotea: + version: 1.0.2 + title: Create Pivot Table Easily + maintainer: Toshikazu Matsumura + description: Pivot easily by specifying rows, columns, values and split. + date_publication: '2024-07-13' + bug_reports: '' + url: https://matutosi.github.io/pivotea/ + url_cran: https://CRAN.R-project.org/package=pivotea + url_git: https://github.com/matutosi/pivotea +pivottabler: + version: 1.5.5 + title: Create Pivot Tables + maintainer: Christopher Bailiss + description: |- + Create regular pivot tables with just a few lines of R. + More complex pivot tables can also be created, e.g. pivot tables + with irregular layouts, multiple calculations and/or derived + calculations based on multiple data frames. Pivot tables are + constructed using R only and can be written to a range of + output formats (plain text, 'HTML', 'Latex' and 'Excel'), + including with styling/formatting. + date_publication: '2023-10-01' + bug_reports: https://github.com/cbailiss/pivottabler/issues + url: http://www.pivottabler.org.uk/ + url_cran: https://CRAN.R-project.org/package=pivottabler + url_git: https://github.com/cbailiss/pivottabler +piwikproR: + version: 0.4.0 + title: Access 'Piwik Pro' Website Statistics + maintainer: Martin Stingl + description: Run Queries against the API of 'Piwik Pro' . + The result is a tibble. + date_publication: '2022-09-01' + bug_reports: https://github.com/dfv-ms/piwikproR/issues + url: https://piwikpror.rstats-tips.net + url_cran: https://CRAN.R-project.org/package=piwikproR + url_git: '' +pixarfilms: + version: 0.2.1 + title: Pixar Films and Achievements + maintainer: Eric Leung + description: |- + Data about Disney Pixar films provided by Wikipedia. This + package contains data about the films, the people involved, and their + awards. + date_publication: '2021-07-27' + bug_reports: https://github.com/erictleung/pixarfilms/issues + url: https://erictleung.com/pixarfilms/ + url_cran: https://CRAN.R-project.org/package=pixarfilms + url_git: https://github.com/erictleung/pixarfilms +pixelclasser: + version: 1.1.1 + title: Classifies Image Pixels by Colour + maintainer: Carlos Real + description: Contains functions to classify the pixels of an image file by its colour. + It implements a simple form of the techniques known as Support Vector Machine + adapted to this particular problem. + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pixelclasser + url_git: '' +pixelpuzzle: + version: 1.0.1 + title: Puzzle Game for the R Console + maintainer: Roland Krasser + description: |- + Puzzle game that can be played in the R console. + Restore the pixel art by shifting rows. + date_publication: '2023-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pixelpuzzle + url_git: https://github.com/rolkra/pixelpuzzle +pixels: + version: 0.1.1 + title: Tools for Working with Image Pixels + maintainer: Daniel Falbel + description: |- + Provides tools to show and draw image pixels using 'HTML' widgets + and 'Shiny' applications. It can be used to visualize the 'MNIST' dataset + for handwritten digit recognition or to create new image recognition datasets. + date_publication: '2020-12-04' + bug_reports: https://github.com/javierluraschi/pixels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pixels + url_git: https://github.com/javierluraschi/pixels +pixiedust: + version: 0.9.4 + title: Tables so Beautifully Fine-Tuned You Will Believe It's Magic + maintainer: Benjamin Nutter + description: |- + The introduction of the 'broom' package has made converting model + objects into data frames as simple as a single function. While the 'broom' + package focuses on providing tidy data frames that can be used in advanced + analysis, it deliberately stops short of providing functionality for reporting + models in publication-ready tables. 'pixiedust' provides this functionality with + a programming interface intended to be similar to 'ggplot2's system of layers + with fine tuned control over each cell of the table. Options for output include + printing to the console and to the common markdown formats (markdown, HTML, and + LaTeX). With a little 'pixiedust' (and happy thoughts) tables can really fly. + date_publication: '2023-10-10' + bug_reports: https://github.com/nutterb/pixiedust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pixiedust + url_git: https://github.com/nutterb/pixiedust +pixmap: + version: 0.4-13 + title: Bitmap Images / Pixel Maps + maintainer: Achim Zeileis + description: Functions for import, export, visualization and other manipulations + of bitmapped images. + date_publication: '2024-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pixmap + url_git: '' +PJFM: + version: 0.1.0 + title: Variational Inference for High-Dimensional Joint Frailty Model + maintainer: Jiehuan Sun + description: |- + Joint frailty models have been widely used to study the associations between recurrent events and a survival outcome. However, existing joint frailty models only consider one or a few recurrent events + and cannot deal with high-dimensional recurrent events. This package can be used to fit our recently developed penalized joint frailty model that can handle high-dimensional recurrent events. + Specifically, an adaptive lasso penalty is imposed on the parameters for the effects of the recurrent events on the survival outcome, which allows for variable selection. + Also, our algorithm is computationally efficient, which is based on the Gaussian variational approximation method. + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PJFM + url_git: '' +PK: + version: 1.3-6 + title: Basic Non-Compartmental Pharmacokinetics + maintainer: Thomas Jaki + description: Estimation of pharmacokinetic parameters using non-compartmental theory. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PK + url_git: '' +pk.unit.trans: + version: 0.1.0 + title: |- + Achieve Numerical Conversion Between Units Commonly Used in + Pharmacokinetics + maintainer: Fu Yongchao + description: |- + Achieve internal conversions of mass units, molar units, + and volume units commonly used in pharmacokinetics, + as well as conversions between mass units and molar units. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pk.unit.trans + url_git: '' +pk4adi: + version: 0.1.3.2 + title: PK for Anesthetic Depth Indicators + maintainer: Feng Jiang + description: |- + Calculate and compare the prediction probability (PK) values for Anesthetic Depth Indicators. + The PK values are widely used for measuring the performance of anesthetic depth and were first + proposed by the group of Dr. Warren D. Smith in the paper + Warren D. Smith; Robert C. Dutton; Ty N. Smith (1996) and + Warren D. Smith; Robert C. Dutton; Ty N. Smith (1996) . + The authors provided two 'Microsoft Excel' files in xls format for calculating and comparing PK values. + This package provides an easy-to-use API for calculating and comparing PK values in R. + date_publication: '2023-07-16' + bug_reports: https://github.com/xfz329/rpk4adi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pk4adi + url_git: https://github.com/xfz329/rpk4adi +PKbioanalysis: + version: 0.2.0 + title: Pharmacokinetic Bioanalysis Experiments Design and Exploration + maintainer: Omar Elashkar + description: |- + Automate pharmacokinetic/pharmacodynamic bioanalytical procedures based on best practices and regulatory recommendations. + The package impose regulatory constrains and sanity checking for common bioanalytical procedures. + Additionally, 'PKbioanalysis' provides a relational infrastructure for plate management and injection sequence. + date_publication: '2024-10-02' + bug_reports: https://github.com/OmarAshkar/PKbioanalysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PKbioanalysis + url_git: https://github.com/OmarAshkar/PKbioanalysis +PKconverter: + version: '1.5' + title: The Parameter Converter of the Pharmacokinetic Models + maintainer: Eun-Kyung Lee + description: |- + Pharmacokinetics is the study of drug absorption, distribution, + metabolism, and excretion. The pharmacokinetics model explains that how the + drug concentration change as the drug moves through the different compartments + of the body. For pharmacokinetic modeling and analysis, it is essential + to understand the basic pharmacokinetic parameters. All parameters are + considered, but only some of parameters are used in the model. Therefore, + we need to convert the estimated parameters to the other parameters after + fitting the specific pharmacokinetic model. This package is developed to help + this converting work. For more detailed explanation of pharmacokinetic + parameters, see "Gabrielsson and Weiner" (2007), "ISBN-10: 9197651001"; + "Benet and Zia-Amirhosseini" (1995) ; + "Mould and Upton" (2012) ; + "Mould and Upton" (2013) . + date_publication: '2020-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PKconverter + url_git: '' +pkdata: + version: 0.1.0 + title: Creates Pharmacokinetic/Pharmacodynamic (PK/PD) Data + maintainer: Cole Beck + description: |- + Prepare pharmacokinetic/pharmacodynamic (PK/PD) data for PK/PD analyses. + This package provides functions to standardize infusion and bolus dose data while + linking it to drug level or concentration data. + date_publication: '2020-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pkdata + url_git: '' +pkgbuild: + version: 1.4.6 + title: Find Tools Needed to Build R Packages + maintainer: Gábor Csárdi + description: |- + Provides functions used to build R packages. Locates + compilers needed to build R packages on various platforms and ensures + the PATH is configured appropriately so R can use them. + date_publication: '2025-01-16' + bug_reports: https://github.com/r-lib/pkgbuild/issues + url: https://pkgbuild.r-lib.org + url_cran: https://CRAN.R-project.org/package=pkgbuild + url_git: https://github.com/r-lib/pkgbuild +pkgcache: + version: 2.2.3 + title: Cache 'CRAN'-Like Metadata and R Packages + maintainer: Gábor Csárdi + description: |- + Metadata and package cache for CRAN-like repositories. This + is a utility package to be used by package management tools that want + to take advantage of caching. + date_publication: '2024-09-12' + bug_reports: https://github.com/r-lib/pkgcache/issues + url: https://r-lib.github.io/pkgcache/ + url_cran: https://CRAN.R-project.org/package=pkgcache + url_git: https://github.com/r-lib/pkgcache +pkgcond: + version: 0.1.1 + title: Classed Error and Warning Conditions + maintainer: Andrew Redd + description: |- + This provides utilities for creating classed error and warning + conditions based on where the error originated. + date_publication: '2021-04-28' + bug_reports: https://github.com/RDocTaskForce/pkgcond/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pkgcond + url_git: https://github.com/RDocTaskForce/pkgcond +pkgconfig: + version: 2.0.3 + title: Private Configuration for 'R' Packages + maintainer: Gábor Csárdi + description: |- + Set configuration options on a per-package basis. + Options set by a given package only apply to that package, + other packages are unaffected. + date_publication: '2019-09-22' + bug_reports: https://github.com/r-lib/pkgconfig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pkgconfig + url_git: https://github.com/r-lib/pkgconfig#readme +pkgdepends: + version: 0.8.0 + title: Package Dependency Resolution and Downloads + maintainer: Gábor Csárdi + description: |- + Find recursive dependencies of 'R' packages from various + sources. Solve the dependencies to obtain a consistent set of packages + to install. Download packages, and install them. It supports packages + on 'CRAN', 'Bioconductor' and other 'CRAN-like' repositories, + 'GitHub', package 'URLs', and local package trees and files. It caches + metadata and package files via the 'pkgcache' package, and performs + all 'HTTP' requests, downloads, builds and installations in parallel. + 'pkgdepends' is the workhorse of the 'pak' package. + date_publication: '2024-09-12' + bug_reports: https://github.com/r-lib/pkgdepends/issues + url: https://r-lib.github.io/pkgdepends/ + url_cran: https://CRAN.R-project.org/package=pkgdepends + url_git: https://github.com/r-lib/pkgdepends +pkgdepR: + version: 1.1.1 + title: Statically Determine Function Dependencies Between Packages + maintainer: Ed Peyton + description: |- + Statically determine and visualize the function dependencies + within and across packages. This may be useful for managing function + dependencies across a code base of multiple R packages. + date_publication: '2024-11-19' + bug_reports: https://github.com/edpeyton/pkgdepR/issues + url: https://pkgdepR.org/ + url_cran: https://CRAN.R-project.org/package=pkgdepR + url_git: '' +pkgdown: + version: 2.1.1 + title: Make Static HTML Documentation for a Package + maintainer: Hadley Wickham + description: |- + Generate an attractive and useful website from a source + package. 'pkgdown' converts your documentation, vignettes, 'README', + and more to 'HTML' making it easy to share information about your + package online. + date_publication: '2024-09-17' + bug_reports: https://github.com/r-lib/pkgdown/issues + url: https://pkgdown.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=pkgdown + url_git: https://github.com/r-lib/pkgdown +pkgfilecache: + version: 0.1.5 + title: Download and Manage Optional Package Data + maintainer: Tim Schäfer + description: Manage optional data for your package. The data can be hosted anywhere, + and you have to give a Uniform Resource Locator (URL) for each file. File integrity + checks are supported. This is useful for package authors who need to ship more + than the 5 Megabyte of data currently allowed by the the Comprehensive R Archive + Network (CRAN). + date_publication: '2024-02-02' + bug_reports: https://github.com/dfsp-spirit/pkgfilecache/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pkgfilecache + url_git: https://github.com/dfsp-spirit/pkgfilecache +pkggraph: + version: 0.2.3 + title: |- + A Consistent and Intuitive Platform to Explore the Dependencies + of Packages on the Comprehensive R Archive Network Like + Repositories + maintainer: KS Srikanth + description: Interactively explore various dependencies of a package(s) (on the + Comprehensive R Archive Network Like repositories) and perform analysis using + tidy philosophy. Most of the functions return a 'tibble' object (enhancement of + 'dataframe') which can be used for further analysis. The package offers functions + to produce 'network' and 'igraph' dependency graphs. The 'plot' method produces + a static plot based on 'ggnetwork' and 'plotd3' function produces an interactive + D3 plot based on 'networkD3'. + date_publication: '2018-11-15' + bug_reports: https://github.com/talegari/pkggraph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pkggraph + url_git: https://github.com/talegari/pkggraph +pkgGraphR: + version: 0.3.1 + title: Graph the Relationship Between Functions in an R Package + maintainer: David Oliver + description: It is often useful when developing an R package to track the relationship + between functions in order to appropriately test and track changes. This package + generates a graph of the relationship between all R functions in a package. It + can also be used on any directory containing .R files which can be very useful + for 'shiny' apps or other non-package workflows. + date_publication: '2025-01-07' + bug_reports: https://gitlab.com/doliv071/pkggraphr/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pkgGraphR + url_git: https://gitlab.com/doliv071/pkggraphr +pkgKitten: + version: 0.2.4 + title: Create Simple Packages Which Do not Upset R Package Checks + maintainer: Dirk Eddelbuettel + description: |- + Provides a function kitten() which creates cute little + packages which pass R package checks. This sets it apart from + package.skeleton() which it calls, and which leaves imperfect files + behind. As this is not exactly helpful for beginners, kitten() offers + an alternative. Unit test support can be added via the 'tinytest' + package (if present), and documentation-creation support can be + added via 'roxygen2' (if present). + date_publication: '2024-08-30' + bug_reports: https://github.com/eddelbuettel/pkgkitten/issues + url: https://eddelbuettel.github.io/pkgkitten/ + url_cran: https://CRAN.R-project.org/package=pkgKitten + url_git: https://github.com/eddelbuettel/pkgkitten +pkglite: + version: 0.2.4 + title: Compact Package Representations + maintainer: Nan Xiao + description: |- + A tool, grammar, and standard to represent and exchange + R package source code as text files. Converts one or more source + packages to a text file and restores the package structures from the file. + date_publication: '2024-11-09' + bug_reports: https://github.com/Merck/pkglite/issues + url: https://merck.github.io/pkglite/ + url_cran: https://CRAN.R-project.org/package=pkglite + url_git: https://github.com/Merck/pkglite +pkgload: + version: 1.4.0 + title: Simulate Package Installation and Attach + maintainer: Lionel Henry + description: |- + Simulates the process of installing a package and then + attaching it. This is a key part of the 'devtools' package as it + allows you to rapidly iterate while developing a package. + date_publication: '2024-06-28' + bug_reports: https://github.com/r-lib/pkgload/issues + url: https://pkgload.r-lib.org + url_cran: https://CRAN.R-project.org/package=pkgload + url_git: https://github.com/r-lib/pkgload +pkgndep: + version: 1.99.3 + title: Analyze Dependency Heaviness of R Packages + maintainer: Zuguang Gu + description: |- + A new metric named 'dependency heaviness' is proposed that measures the number + of additional dependency packages that a parent package brings to its child package + and are unique to the dependency packages imported by all other parents. + The dependency heaviness analysis is visualized by a customized heatmap. + The package is described in . + We have also performed the dependency heaviness analysis on the CRAN/Bioconductor + package ecosystem and the results are implemented as a web-based database + which provides comprehensive tools for querying dependencies of individual R packages. + The systematic analysis on the CRAN/Bioconductor ecosystem is described in + . From 'pkgndep' version 2.0.0, the heaviness + database includes snapshots of the CRAN/Bioconductor ecosystems for many old R versions. + date_publication: '2023-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pkgndep + url_git: https://github.com/jokergoo/pkgndep +pkgnet: + version: 0.5.0 + title: Get Network Representation of an R Package + maintainer: Brian Burns + description: |- + Tools from the domain of graph theory can be used to quantify the complexity + and vulnerability to failure of a software package. That is the guiding philosophy + of this package. 'pkgnet' provides tools to analyze the dependencies between functions + in an R package and between its imported packages. See the pkgnet website for vignettes + and other supplementary information. + date_publication: '2024-05-03' + bug_reports: https://github.com/uptake/pkgnet/issues + url: https://uptake.github.io/pkgnet/ + url_cran: https://CRAN.R-project.org/package=pkgnet + url_git: https://github.com/uptake/pkgnet +pkgnews: + version: 0.0.2 + title: Retrieve R Package News Files + maintainer: Owen Jones + description: |- + Read R package news files, regardless of whether or not the package + is installed. + date_publication: '2021-03-12' + bug_reports: https://github.com/owenjonesuob/pkgnews/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pkgnews + url_git: https://github.com/owenjonesuob/pkgnews +pkgsearch: + version: 3.1.4 + title: Search and Query CRAN R Packages + maintainer: Gábor Csárdi + description: |- + Search CRAN metadata about packages by keyword, popularity, + recent activity, package name and more. Uses the 'R-hub' search + server, see and the CRAN metadata database, that + contains information about CRAN packages. Note that this is _not_ a + CRAN project. + date_publication: '2025-01-09' + bug_reports: https://github.com/r-hub/pkgsearch/issues + url: https://r-hub.github.io/pkgsearch/ + url_cran: https://CRAN.R-project.org/package=pkgsearch + url_git: https://github.com/r-hub/pkgsearch +pkgverse: + version: 0.0.1 + title: Build a Meta-Package Universe + maintainer: Michael Wayne Kearney + description: |- + Build your own universe of packages similar to the 'tidyverse' + package with this meta-package creator. Create a + package-verse, or meta package, by supplying a custom name for the + collection of packages and the vector of desired package names to include– + and optionally supply a destination directory, an indicator of whether to + keep the created package directory, and/or a vector of verbs implement via + the 'usethis' package. + date_publication: '2018-11-14' + bug_reports: https://github.com/mkearney/pkgverse/issues + url: https://pkgverse.mikewk.com + url_cran: https://CRAN.R-project.org/package=pkgverse + url_git: '' +PKI: + version: 0.1-14 + title: Public Key Infrastucture for R Based on the X.509 Standard + maintainer: Simon Urbanek + description: Public Key Infrastucture functions such as verifying certificates, + RSA encription and signing which can be used to build PKI infrastructure and perform + cryptographic tasks. + date_publication: '2024-06-15' + bug_reports: '' + url: http://www.rforge.net/PKI + url_cran: https://CRAN.R-project.org/package=PKI + url_git: '' +PKLMtest: + version: 1.0.1 + title: Classification Based MCAR Test + maintainer: Meta-Lina Spohn + description: Implementation of a KL-based (Kullback-Leibler) test for MCAR (Missing + Completely At Random) in the context of missing data as introduced in Michel et + al. (2021) . + date_publication: '2021-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PKLMtest + url_git: '' +pkmon: + version: '1.1' + title: |- + Least-Squares Estimator under k-Monotony Constraint for Discrete + Functions + maintainer: Francois Deslandes + description: We implement two least-squares estimators under k-monotony constraint + using a method based on the Support Reduction Algorithm from Groeneboom et al + (2008) . The first one is a projection estimator + on the set of k-monotone discrete functions. The second one is a projection on + the set of k-monotone discrete probabilities. This package provides functions + to generate samples from the spline basis from Lefevre and Loisel (2013) , + and from mixtures of splines. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pkmon + url_git: '' +PKNCA: + version: 0.11.0 + title: Perform Pharmacokinetic Non-Compartmental Analysis + maintainer: Bill Denney + description: |- + Compute standard Non-Compartmental Analysis (NCA) parameters for + typical pharmacokinetic analyses and summarize them. + date_publication: '2024-06-19' + bug_reports: https://github.com/billdenney/pknca/issues + url: https://billdenney.github.io/pknca/ + url_cran: https://CRAN.R-project.org/package=PKNCA + url_git: https://github.com/billdenney/pknca +PKPDsim: + version: 1.4.0 + title: Tools for Performing Pharmacokinetic-Pharmacodynamic Simulations + maintainer: Ron Keizer + description: |- + Simulate dose regimens for pharmacokinetic-pharmacodynamic (PK-PD) + models described by differential equation (DE) systems. Simulation using + ADVAN-style analytical equations is also supported (Abuhelwa et al. (2015) + ). + date_publication: '2024-08-19' + bug_reports: '' + url: https://insightrx.github.io/PKPDsim/ + url_cran: https://CRAN.R-project.org/package=PKPDsim + url_git: https://github.com/InsightRX/PKPDsim +pkr: + version: 0.1.3 + title: Pharmacokinetics in R + maintainer: Kyun-Seop Bae + description: |- + Conduct a noncompartmental analysis as closely as possible to the most widely used commercial software. + Some features are + 1) CDISC SDTM terms + 2) Automatic slope selection with the same criterion of WinNonlin(R) + 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method + 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method + * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107). + date_publication: '2022-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pkr + url_git: '' +pks: + version: 0.6-1 + title: Probabilistic Knowledge Structures + maintainer: Florian Wickelmaier + description: |- + Fitting and testing probabilistic knowledge structures, + especially the basic local independence model (BLIM, Doignon & Flamagne, + 1999) and the simple learning model (SLM), using the minimum discrepancy + maximum likelihood (MDML) method (Heller & Wickelmaier, 2013 + ). + date_publication: '2024-09-16' + bug_reports: '' + url: https://www.mathpsy.uni-tuebingen.de/wickelmaier/ + url_cran: https://CRAN.R-project.org/package=pks + url_git: '' +pKSEA: + version: 0.0.1 + title: Prediction-Based Kinase-Substrate Enrichment Analysis + maintainer: Peter Liao + description: |- + A tool for inferring kinase activity changes from + phosphoproteomics data. 'pKSEA' uses kinase-substrate + prediction scores to weight observed changes in + phosphopeptide abundance to calculate a phosphopeptide-level + contribution score, then sums up these contribution scores by + kinase to obtain a phosphoproteome-level kinase activity + change score (KAC score). 'pKSEA' then assesses the + significance of changes in predicted substrate abundances for + each kinase using permutation testing. This results in a + permutation score (pKSEA significance score) reflecting the + likelihood of a similarly high or low KAC from random chance, + which can then be interpreted in an analogous manner to an + empirically calculated p-value. 'pKSEA' contains default + databases of kinase-substrate predictions from 'NetworKIN' + (NetworKINPred_db) + Horn, et. al (2014) + and of known kinase-substrate links from 'PhosphoSitePlus' + (KSEAdb) + Hornbeck PV, et. al (2015) . + date_publication: '2017-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pKSEA + url_git: '' +pksensi: + version: 1.2.3 + title: |- + Global Sensitivity Analysis in Physiologically Based Kinetic + Modeling + maintainer: Nan-Hung Hsieh + description: |- + Applying the global sensitivity analysis workflow to investigate + the parameter uncertainty and sensitivity in physiologically based + kinetic (PK) models, especially the physiologically based + pharmacokinetic/toxicokinetic model with multivariate outputs. + The package also provides some functions to check the convergence + and sensitivity of model parameters. The workflow was first mentioned + in Hsieh et al., (2018) , then further + refined (Hsieh et al., 2020 ). + date_publication: '2022-09-21' + bug_reports: https://github.com/nanhung/pksensi/issues + url: https://nanhung.github.io/pksensi/ + url_cran: https://CRAN.R-project.org/package=pksensi + url_git: https://github.com/nanhung/pksensi +PL94171: + version: 1.1.3 + title: Tabulate P.L. 94-171 Redistricting Data Summary Files + maintainer: Cory McCartan + description: |- + Tools to process legacy format summary redistricting data files + produced by the United States Census Bureau pursuant to P.L. 94-171. These + files are generally available earlier but are difficult to work with as-is. + date_publication: '2025-02-19' + bug_reports: https://github.com/CoryMcCartan/PL94171/issues + url: https://corymccartan.com/PL94171/ + url_cran: https://CRAN.R-project.org/package=PL94171 + url_git: https://github.com/CoryMcCartan/PL94171/ +plac: + version: 0.1.3 + title: |- + A Pairwise Likelihood Augmented Cox Estimator for Left-Truncated + Data + maintainer: Fan Wu + description: |- + A semi-parametric estimation method for the Cox model + with left-truncated data using augmented information + from the marginal of truncation times. + date_publication: '2023-07-02' + bug_reports: https://github.com/942kid/plac/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plac + url_git: https://github.com/942kid/plac +placer: + version: 0.1.3 + title: PLastic ACcumulation Estimate using R (PLACER) + maintainer: Davi Castro-Tavares + description: |- + Assessment of the prevalence of plastic + debris in bird nests based on bootstrap replicates. The package allows for + calculating bootstrapped 95% confidence intervals for the estimated prevalence + of debris. Combined with a Bayesian approach, the resampling simulations can + be also used to define appropriate sample sizes to detect prevalence of plastics. + The method has wide application, and can also be applied to estimate confidence + intervals and define sample sizes for the prevalence of plastics ingested by any + other organisms. The method is described in Tavares et al. (Submitted). + date_publication: '2019-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=placer + url_git: '' +PlackettLuce: + version: 0.4.3 + title: Plackett-Luce Models for Rankings + maintainer: Heather Turner + description: |- + Functions to prepare rankings data and fit the Plackett-Luce model + jointly attributed to Plackett (1975) and Luce + (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized + to accommodate ties of any order in the ranking. Partial rankings, in which + only a subset of items are ranked in each ranking, are also accommodated in + the implementation. Disconnected/weakly connected networks implied by the + rankings may be handled by adding pseudo-rankings with a hypothetical item. + Optionally, a multivariate normal prior may be set on the log-worth + parameters and ranker reliabilities may be incorporated as proposed by + Raman and Joachims (2014) . Maximum a + posteriori estimation is used when priors are set. Methods are provided to + estimate standard errors or quasi-standard errors for inference as well as + to fit Plackett-Luce trees. See the package website or vignette for further + details. + date_publication: '2023-06-16' + bug_reports: https://github.com/hturner/PlackettLuce/issues + url: https://hturner.github.io/PlackettLuce/ + url_cran: https://CRAN.R-project.org/package=PlackettLuce + url_git: https://github.com/hturner/PlackettLuce +plainview: + version: 0.2.1 + title: Plot Raster Images Interactively on a Plain HTML Canvas + maintainer: Tim Appelhans + description: |- + Provides methods for plotting potentially large (raster) images + interactively on a plain HTML canvas. In contrast to package 'mapview' + data are plotted without background map, but data can be projected to + any spatial coordinate reference system. + Supports plotting of classes 'RasterLayer', 'RasterStack', 'RasterBrick' + (from package 'raster') as well as 'png' files located on disk. + Interactivity includes zooming, panning, and mouse location information. + In case of multi-layer 'RasterStacks' or 'RasterBricks', RGB image plots + are created (similar to 'raster::plotRGB' - but interactive). + date_publication: '2023-07-11' + bug_reports: '' + url: https://r-spatial.github.io/plainview/ + url_cran: https://CRAN.R-project.org/package=plainview + url_git: '' +plan: + version: 0.4-5 + title: Tools for Project Planning + maintainer: Dan Kelley + description: Supports the creation of 'burndown' charts and 'gantt' diagrams. + date_publication: '2023-08-19' + bug_reports: '' + url: https://dankelley.github.io/plan/ + url_cran: https://CRAN.R-project.org/package=plan + url_git: https://github.com/dankelley/plan +Planesmuestra: + version: '0.1' + title: |- + Functions for Calculating Dodge Romig, MIL STD 105E and MIL STD + 414 Acceptance Sampling Plan + maintainer: Erick Marroquin + description: Calculates an acceptance sampling plan, (sample size and acceptance + number) based in MIL STD 105E, Dodge Romig and MIL STD 414 tables and procedures. + The arguments for each function are related to lot size, inspection level and + quality level. The specific plan operating curve (OC), is calculated by the binomial + distribution. + date_publication: '2016-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Planesmuestra + url_git: '' +PlanetNICFI: + version: 1.0.5 + title: Processing of the 'Planet NICFI' Satellite Imagery + maintainer: Lampros Mouselimis + description: It includes functions to download and process the 'Planet NICFI' (Norway's + International Climate and Forest Initiative) Satellite Imagery utilizing the Planet + Mosaics API . + 'GDAL' (library for raster and vector geospatial data formats) and 'aria2c' (paralleled + download utility) must be installed and configured in the user's Operating System. + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlanetNICFI + url_git: https://github.com/mlampros/PlanetNICFI +planets: + version: 0.1.0 + title: Simple and Accessible Data from all Known Planets + maintainer: Alejandro Jiménez Rico + description: The goal of 'planets' is to provide of very simple and accessible data + containing basic information from all known planets. + date_publication: '2019-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=planets + url_git: '' +planningML: + version: 1.0.1 + title: |- + A Sample Size Calculator for Machine Learning Applications in + Healthcare + maintainer: Xinying Fang + description: 'Advances in automated document classification has led to identifying + massive numbers of clinical concepts from handwritten clinical notes. These high + dimensional clinical concepts can serve as highly informative predictors in building + classification algorithms for identifying patients with different clinical conditions, + commonly referred to as patient phenotyping. However, from a planning perspective, + it is critical to ensure that enough data is available for the phenotyping algorithm + to obtain a desired classification performance. This challenge in sample size + planning is further exacerbated by the high dimension of the feature space and + the inherent imbalance of the response class. Currently available sample size + planning methods can be categorized into: (i) model-based approaches that predict + the sample size required for achieving a desired accuracy using a linear machine + learning classifier and (ii) learning curve-based approaches (Figueroa et al. + (2012) ) that fit an inverse power law curve to pilot + data to extrapolate performance. We develop model-based approaches for imbalanced + data with correlated features, deriving sample size formulas for performance metrics + that are sensitive to class imbalance such as Area Under the receiver operating + characteristic Curve (AUC) and Matthews Correlation Coefficient (MCC). This is + done using a two-step approach where we first perform feature selection using + the innovated High Criticism thresholding method (Hall and Jin (2010) ), + then determine the sample size by optimizing the two performance metrics. Further, + we develop software in the form of an R package named ''planningML'' and an ''R'' + ''Shiny'' app to facilitate the convenient implementation of the developed model-based + approaches and learning curve approaches for imbalanced data. We apply our methods + to the problem of phenotyping rare outcomes using the MIMIC-III electronic health + record database. We show that our developed methods which relate training data + size and performance on AUC and MCC, can predict the true or observed performance + from linear ML classifiers such as LASSO and SVM at different training data sizes. + Therefore, in high-dimensional classification analysis with imbalanced data and + correlated features, our approach can efficiently and accurately determine the + sample size needed for machine-learning based classification.' + date_publication: '2023-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=planningML + url_git: '' +planr: + version: 0.5.1 + title: Tools for Supply Chain Management, Demand and Supply Planning + maintainer: Nicolas Nguyen + description: Perform flexible and quick calculations for Demand and Supply Planning, + such as projected inventories and coverages, as well as replenishment plan. For + any time bucket, daily, weekly or monthly, and any granularity level, product + or group of products. + date_publication: '2025-02-23' + bug_reports: https://github.com/nguyennico/planr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=planr + url_git: https://github.com/nguyennico/planr +planscorer: + version: 0.0.2 + title: Score Redistricting Plans with 'PlanScore' + maintainer: Christopher T. Kenny + description: |- + Provides access to the 'PlanScore' Application Programming Interface + () for scoring redistricting + plans. Allows for upload of plans from block assignment files and shape files. + For shapes in memory, such as from 'sf' or 'redist', it processes them to save + and upload. Includes tools for tidying responses and saving output from the + website. + date_publication: '2024-09-24' + bug_reports: https://github.com/christopherkenny/planscorer/issues + url: http://christophertkenny.com/planscorer/ + url_cran: https://CRAN.R-project.org/package=planscorer + url_git: https://github.com/christopherkenny/planscorer +plantecophys: + version: 1.4-6 + title: Modelling and Analysis of Leaf Gas Exchange Data + maintainer: Remko Duursma + description: |- + Coupled leaf gas exchange model, A-Ci curve simulation and + fitting, Ball-Berry stomatal conductance models, + leaf energy balance using Penman-Monteith, Cowan-Farquhar + optimization, humidity unit conversions. + See Duursma (2015) . + date_publication: '2021-03-31' + bug_reports: https://bitbucket.org/remkoduursma/plantecophys/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plantecophys + url_git: https://bitbucket.org/remkoduursma/plantecophys +plantphysioR: + version: 1.0.0 + title: Fundamental Formulas for Plant Physiology + maintainer: Ramesh Ramasamy + description: Functions tailored for scientific and student communities involved + in plant science research. Functionalities encompass estimation chlorophyll content + according to Arnon (1949) , determination water potential + of Polyethylene glycol(PEG)6000 as in Michel and Kaufmann (1973) and + functions related to estimation of yield related indices like Abiotic tolerance + index as given by Moosavi et al.(2008), Geometric + mean productivity (GMP) by Fernandez (1992) , Golden Mean + by Moradi et al.(2012), HAM by Schneider et al.(1997),MPI + and TOL by Hossain etal., (1990), + RDI by Fischer et al. (1979),SSI by Fisher et al.(1978), + STI by Fernandez (1993),YSI by Bouslama & Schapaugh (1984), + Yield index by Gavuzzi et al.(1997). + date_publication: '2024-03-27' + bug_reports: https://github.com/rameshram96/plantphysioR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plantphysioR + url_git: https://github.com/rameshram96/plantphysioR +plantTracker: + version: 1.1.0 + title: Extract Demographic and Competition Data from Fine-Scale Maps + maintainer: Alice Stears + description: |- + Extracts growth, survival, and local neighborhood density + information from repeated, fine-scale maps of organism occurrence. Further + information about this package can be found in our journal article, + "plantTracker: An R package to translate maps of plant occurrence into + demographic data" published in 2022 in Methods in Ecology and Evolution + (Stears, et al., 2022) . + date_publication: '2023-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plantTracker + url_git: https://github.com/aestears/plantTracker +plaqr: + version: '2.0' + title: Partially Linear Additive Quantile Regression + maintainer: Adam Maidman + description: Estimation, prediction, thresholding, transformation, and plotting + for partially linear additive quantile regression. Intuitive functions for fitting + and plotting partially linear additive quantile regression models. Uses and works + with functions from the 'quantreg' package. + date_publication: '2017-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plaqr + url_git: '' +plasma: + version: 1.1.3 + title: Partial LeAst Squares for Multiomic Analysis + maintainer: Kevin R. Coombes + description: |- + Contains tools for supervised analyses of incomplete, overlapping + multiomics datasets. Applies partial least squares in multiple steps to find + models that predict survival outcomes. See Yamaguchi et al. (2023) + . + date_publication: '2024-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plasma + url_git: http://oompa.r-forge.r-project.org/ +PlasmaMutationDetector: + version: 1.7.2 + title: Tumor Mutation Detection in Plasma + maintainer: Yves Rozenholc + description: |- + Aims at detecting single nucleotide variation + (SNV) and insertion/deletion (INDEL) in circulating tumor DNA (ctDNA), used + as a surrogate marker for tumor, at each base position of an Next Generation + Sequencing (NGS) analysis. Mutations are assessed by comparing the minor-allele + frequency at each position to the measured PER in control samples. + date_publication: '2018-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlasmaMutationDetector + url_git: '' +Plasmidprofiler: + version: 0.1.6 + title: Visualization of Plasmid Profile Results + maintainer: Adrian Zetner + description: |- + Contains functions developed to combine the results of querying a plasmid database using + short-read sequence typing with the results of a blast analysis against the query results. + date_publication: '2017-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Plasmidprofiler + url_git: '' +plasso: + version: 0.1.2 + title: Cross-Validated (Post-) Lasso + maintainer: Glaisner Stefan + description: |- + Built on top of the 'glmnet' library by Friedman, Hastie and Tibshirani (2010) , the 'plasso' package follows Knaus (2022) and comes up with two functions that estimate least squares Lasso and Post-Lasso models. + The plasso() function adds coefficient paths for a Post-Lasso model to the standard 'glmnet' output. + On top of that cv.plasso() cross-validates the coefficient paths for both the Lasso and Post-Lasso model and provides optimal hyperparameter values for the penalty term lambda. + date_publication: '2023-12-03' + bug_reports: https://github.com/stefan-1997/plasso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plasso + url_git: https://github.com/stefan-1997/plasso +plater: + version: 1.0.5 + title: Read, Tidy, and Display Data from Microtiter Plates + maintainer: Sean Hughes + description: |- + Tools for interacting with data from experiments done in microtiter + plates. Easily read in plate-shaped data and convert it to tidy format, + combine plate-shaped data with tidy data, and view tidy data in plate shape. + date_publication: '2024-10-25' + bug_reports: https://github.com/ropensci/plater/issues + url: https://docs.ropensci.org/plater/ + url_cran: https://CRAN.R-project.org/package=plater + url_git: https://github.com/ropensci/plater +platetools: + version: 0.1.7 + title: Tools and Plots for Multi-Well Plates + maintainer: Scott Warchal + description: |- + Collection of functions for working with multi-well microtitre + plates, mainly 96, 384 and 1536 well plates. + date_publication: '2024-03-07' + bug_reports: https://github.com/swarchal/platetools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=platetools + url_git: https://github.com/swarchal/platetools +PlatformDesign: + version: 2.1.4 + title: |- + Optimal Two-Period Multiarm Platform Design with New + Experimental Arms Added During the Trial + maintainer: Xiaomeng Yuan + description: |- + Design parameters of the optimal two-period multiarm platform design + (controlling for either family-wise error rate or pair-wise error rate) can be calculated + using this package, allowing pre-planned deferred arms to be added during the trial. More + details about the design method can be found in the paper: Pan, H., Yuan, X. and Ye, J. + (2022) "An optimal two-period multiarm platform design with new experimental arms added + during the trial". Manuscript submitted for publication. For additional references: Dunnett, + C. W. (1955) . + date_publication: '2022-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlatformDesign + url_git: '' +platowork: + version: 0.0.1 + title: Data from a Test of the PlatoWork tDCS Headset + maintainer: Lasse Hjorth Madsen + description: |- + Data and analysis from an experiment with improving touch + typing speed, using the tDCS PlatoWork headset produced by PlatoScience. + date_publication: '2021-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=platowork + url_git: https://github.com/lassehjorthmadsen/platowork +plattice: + version: '1.1' + title: Lattice Plot for Panel Data + maintainer: Michail Tsagris + description: It creates a lattice plot to visualize panel or longitudinal data. + The observed values are plotted as dots and the fitted values as lines, both against + time. The plot is customizable and easy to edit, even if you do not know how to + construct a lattice plot from scratch. + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plattice + url_git: '' +Platypus: + version: 3.6.0 + title: Single-Cell Immune Repertoire and Gene Expression Analysis + maintainer: Alexander Yermanos + description: 'We present ''Platypus'', an open-source software platform providing + a user-friendly interface to investigate B-cell receptor and T-cell receptor repertoires + from scSeq experiments. ''Platypus'' provides a framework to automate and ease + the analysis of single-cell immune repertoires while also incorporating transcriptional + information involving unsupervised clustering, gene expression and gene ontology. + This R version of ''Platypus'' is part of the ''ePlatypus'' ecosystem for computational + analysis of immunogenomics data: Yermanos et al. (2021) , + Cotet et al. (2023) .' + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Platypus + url_git: '' +play: + version: 0.1.3 + title: Visualize Sports Data + maintainer: Joe Chelladurai + description: |- + Provides functions to visualise sports data. Converts data into a + format suitable for plotting charts. Helps to ease the process of working with + messy sports data to a more user friendly format. Football data is accessed + through 'worldfootballR' '' which + gets data from 'FBref' , 'Transfermarkt' , + 'Understat' , and 'fotmob' . + date_publication: '2023-01-25' + bug_reports: https://github.com/joe-chelladurai/play/issues + url: https://joe-chelladurai.github.io/play/ + url_cran: https://CRAN.R-project.org/package=play + url_git: '' +PlayerChart: + version: 1.0.0 + title: 'Generate Pizza Chart: Player Stats 0-100' + maintainer: Amal Panwar + description: 'Create an interactive pizza chart visualizing a specific player''s + statistics across various attributes in a sports dataset. The chart is constructed + based on input parameters: ''data'', a dataframe containing player data for any + sports; ''player_stats_col'', a vector specifying the names of the columns from + the dataframe that will be used to create slices in the pizza chart, with statistics + ranging between 0 and 100; ''name_col'', specifying the name of the column in + the dataframe that contains the player names; and ''player_name'', representing + the specific player whose statistics will be visualized in the chart, serving + as the chart title.' + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlayerChart + url_git: '' +PlayerRatings: + version: 1.1-0 + title: Dynamic Updating Methods for Player Ratings Estimation + maintainer: Alec Stephenson + description: |- + Implements schemes for estimating player or + team skill based on dynamic updating. Implemented methods include + Elo, Glicko, Glicko-2 and Stephenson. Contains pdf documentation + of a reproducible analysis using approximately two million chess + matches. Also contains an Elo based method for multi-player games + where the result is a placing or a score. This includes zero-sum + games such as poker and mahjong. + date_publication: '2020-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlayerRatings + url_git: '' +pldamixture: + version: 0.1.1 + title: Post-Linkage Data Analysis Based on Mixture Modelling + maintainer: Priyanjali Bukke + description: Perform inference in the secondary analysis setting with linked data + potentially containing mismatch errors. Only the linked data file may be accessible + and information about the record linkage process may be limited or unavailable. + Implements the 'General Framework for Regression with Mismatched Data' developed + by Slawski et al. (2023) . The framework uses a + mixture model for pairs of linked records whose two components reflect distributions + conditional on match status, i.e., correct match or mismatch. Inference is based + on composite likelihood and the Expectation-Maximization (EM) algorithm. The package + currently supports Cox Proportional Hazards Regression (right-censored data only) + and Generalized Linear Regression Models (Gaussian, Gamma, Poisson, and Logistic + (binary models only)). Information about the underlying record linkage process + can be incorporated into the method if available (e.g., assumed overall mismatch + rate, safe matches, predictors of match status, or predicted probabilities of + correct matches). + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pldamixture + url_git: https://github.com/bpriy/pldamixture +plde: + version: 0.1.2 + title: Penalized Log-Density Estimation Using Legendre Polynomials + maintainer: JungJun Lee + description: We present a penalized log-density estimation method using Legendre + polynomials with lasso penalty to adjust estimate's smoothness. Re-expressing + the logarithm of the density estimator via a linear combination of Legendre polynomials, + we can estimate parameters by maximizing the penalized log-likelihood function. + Besides, we proposed an implementation strategy that builds on the coordinate + decent algorithm, together with the Bayesian information criterion (BIC). + date_publication: '2018-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plde + url_git: '' +pleio: + version: '1.9' + title: Pleiotropy Test for Multiple Traits on a Genetic Marker + maintainer: Jason Sinnwell + description: Perform tests for pleiotropy of multiple traits of various variable + types on genotypes for a genetic marker. + date_publication: '2023-12-11' + bug_reports: '' + url: https://bioinformaticstools.mayo.edu/research/pleio/ + url_cran: https://CRAN.R-project.org/package=pleio + url_git: '' +pleiotest: + version: 1.0.0 + title: Fast Sequential Pleiotropy Test + maintainer: Fernando Aguate + description: It performs a fast multi-trait genome-wide association analysis based + on seemingly unrelated regressions. It tests for pleiotropic effects based on + a series of Intersection-Union Wald tests. The package can handle large and unbalanced + data and plot results. + date_publication: '2021-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pleiotest + url_git: https://github.com/FerAguate/pleiotest +pleLMA: + version: 0.2.1 + title: |- + Pseudo-Likelihood Estimation of Log-Multiplicative Association + Models + maintainer: Carolyn J. Anderson + description: |- + Log-multiplicative association models (LMA) are + models for cross-classifications of categorical variables + where interactions are represented by products of category + scale values and an association parameter. Maximum + likelihood estimation (MLE) fails for moderate to large + numbers of categorical variables. The 'pleLMA' package + overcomes this limitation of MLE by using pseudo-likelihood + estimation to fit the models to small or large + cross-classifications dichotomous or multi-category variables. + Originally proposed by Besag (1974, + ), pseudo-likelihood + estimation takes large complex models and breaks it down + into smaller ones. Rather than maximizing the likelihood + of the joint distribution of all the variables, a + pseudo-likelihood function, which is the product likelihoods + from conditional distributions, is maximized. LMA models can + be derived from a number of different frameworks including + (but not limited to) graphical models and uni-dimensional + and multi-dimensional item response theory models. More + details about the models and estimation can be found in + the vignette. + date_publication: '2021-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pleLMA + url_git: '' +PLEXI: + version: 1.0.0 + title: Multiplex Network Analysis + maintainer: Behnam Yousefi + description: |- + Interactions between different biological entities are crucial for the function of biological systems. + In such networks, nodes represent biological elements, such as genes, proteins and microbes, and their interactions can be defined by edges, which can be either binary or weighted. + The dysregulation of these networks can be associated with different clinical conditions such as diseases and response to treatments. + However, such variations often occur locally and do not concern the whole network. + To capture local variations of such networks, we propose multiplex network differential analysis (MNDA). + MNDA allows to quantify the variations in the local neighborhood of each node (e.g. gene) between the two given clinical states, and to test for statistical significance of such variation. + Yousefi et al. (2023) . + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLEXI + url_git: '' +PLFD: + version: 0.2.0 + title: Portmanteau Local Feature Discrimination for Matrix-Variate Data + maintainer: Zengchao Xu + description: |- + The portmanteau local feature discriminant approach first identifies the local + discriminant features and their differential structures, then constructs the + discriminant rule by pooling the identified local features together. This method + is applicable to high-dimensional matrix-variate data. + See the paper by Xu, Luo and Chen (2021, ). + date_publication: '2023-01-10' + bug_reports: https://github.com/paradoxical-rhapsody/PLFD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PLFD + url_git: https://github.com/paradoxical-rhapsody/PLFD +plfm: + version: 2.2.6 + title: Probabilistic Latent Feature Analysis + maintainer: Michel Meulders + description: Functions for estimating probabilistic latent feature models with a + disjunctive, conjunctive or additive mapping rule on (aggregated) binary three-way + data. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plfm + url_git: '' +plfMA: + version: '2.0' + title: A GUI to View, Design and Export Various Graphs of Data + maintainer: Dhammapal Bharne + description: Provides a graphical user interface for viewing and designing various + types of graphs of the data. The graphs can be saved in different formats of an + image. + date_publication: '2022-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plfMA + url_git: '' +plgp: + version: 1.1-12 + title: Particle Learning of Gaussian Processes + maintainer: Robert B. Gramacy + description: |- + Sequential Monte Carlo (SMC) inference for fully Bayesian + Gaussian process (GP) regression and classification models by + particle learning (PL) following Gramacy & Polson (2011) . + The sequential nature of inference + and the active learning (AL) hooks provided facilitate thrifty + sequential design (by entropy) and optimization + (by improvement) for classification and + regression models, respectively. + This package essentially provides a generic + PL interface, and functions (arguments to the interface) which + implement the GP models and AL heuristics. Functions for + a special, linked, regression/classification GP model and + an integrated expected conditional improvement (IECI) statistic + provide for optimization in the presence of unknown constraints. + Separable and isotropic Gaussian, and single-index correlation + functions are supported. + See the examples section of ?plgp and demo(package="plgp") + for an index of demos. + date_publication: '2022-10-19' + bug_reports: '' + url: https://bobby.gramacy.com/r_packages/plgp/ + url_cran: https://CRAN.R-project.org/package=plgp + url_git: '' +plgraphics: + version: '1.2' + title: User Oriented Plotting Functions + maintainer: Werner A. Stahel + description: |- + Plots with high flexibility and easy handling, including + informative regression diagnostics for many models. + date_publication: '2023-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plgraphics + url_git: '' +pliman: + version: 3.0.0 + title: Tools for Plant Image Analysis + maintainer: Tiago Olivoto + description: |- + Tools for both single and batch image manipulation and + analysis (Olivoto, 2022 ) and + phytopathometry (Olivoto et al., 2022 ). + The tools can be used for the quantification of leaf area, object + counting, extraction of image indexes, shape measurement, object + landmark identification, and Elliptical Fourier Analysis of object + outlines (Claude (2008) ). The package + also provides a comprehensive pipeline for generating shapefiles with + complex layouts and supports high-throughput phenotyping of RGB, + multispectral, and hyperspectral orthomosaics. This functionality + facilitates field phenotyping using UAV- or satellite-based imagery. + date_publication: '2024-11-06' + bug_reports: https://github.com/nepem-ufsc//pliman/issues + url: https://nepem-ufsc.github.io/pliman/ + url_cran: https://CRAN.R-project.org/package=pliman + url_git: https://github.com/nepem-ufsc//pliman +PLindleyROC: + version: 0.1.2 + title: |- + Receiver Operating Characteristic Based on Power Lindley + Distribution + maintainer: Ertan Akgenç + description: Receiver Operating Characteristic (ROC) analysis is performed assuming + samples are from the Power Lindley distribution. Specificity, sensitivity, area + under the curve and ROC curve are provided. + date_publication: '2024-11-13' + bug_reports: https://github.com/ErtanSU/PLindleyROC/issues + url: https://ertansu.github.io/PLindleyROC/ + url_cran: https://CRAN.R-project.org/package=PLindleyROC + url_git: https://github.com/ErtanSU/PLindleyROC +plink: + version: 1.5-1 + title: IRT Separate Calibration Linking Methods + maintainer: Jonathan P. Weeks + description: |- + Item response theory based methods are used to compute + linking constants and conduct chain linking of unidimensional + or multidimensional tests for multiple groups under a common + item design. The unidimensional methods include the Mean/Mean, + Mean/Sigma, Haebara, and Stocking-Lord methods for dichotomous + (1PL, 2PL and 3PL) and/or polytomous (graded response, partial + credit/generalized partial credit, nominal, and multiple-choice + model) items. The multidimensional methods include the least + squares method and extensions of the Haebara and Stocking-Lord + method using single or multiple dilation parameters for + multidimensional extensions of all the unidimensional + dichotomous and polytomous item response models. The package + also includes functions for importing item and/or ability + parameters from common IRT software, conducting IRT true score + and observed score equating, and plotting item response + curves/surfaces, vector plots, information plots, and comparison + plots for examining parameter drift. + date_publication: '2017-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plink + url_git: '' +plinkFile: + version: 0.2.1 + title: '''PLINK'' (and ''GCTA'') File Helpers' + maintainer: Xiaoran Tong + description: Reads/write binary genotype file compatible with 'PLINK' + into/from a R matrix; traverse genotype data one windows of variants at a time, + like apply() or a for loop; reads/writes genotype relatedness/kinship matrices + created by 'PLINK' + or 'GCTA' into/from a R square + matrix. It is best used for bringing data produced by 'PLINK' and 'GCTA' into + R workflow. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plinkFile + url_git: '' +plinkQC: + version: 0.3.4 + title: Genotype Quality Control with 'PLINK' + maintainer: Hannah Meyer + description: |- + Genotyping arrays enable the direct measurement of an individuals + genotype at thousands of markers. 'plinkQC' facilitates genotype quality + control for genetic association studies as described by Anderson and + colleagues (2010) . It makes 'PLINK' basic + statistics (e.g. missing genotyping rates per individual, allele frequencies + per genetic marker) and relationship functions accessible from 'R' and + generates a per-individual and per-marker quality control report. + Individuals and markers that fail the quality control can subsequently be + removed to generate a new, clean dataset. Removal of individuals based on + relationship status is optimised to retain as many individuals as possible + in the study. + date_publication: '2021-07-15' + bug_reports: https://github.com/meyer-lab-cshl/plinkQC/issues + url: https://meyer-lab-cshl.github.io/plinkQC/ + url_cran: https://CRAN.R-project.org/package=plinkQC + url_git: '' +PLIS: + version: '1.2' + title: Multiplicity Control using Pooled LIS Statistic + maintainer: Zhi Wei + description: |- + A multiple testing procedure for testing several groups of + hypotheses is implemented. Linear dependency among the hypotheses + within the same group is modeled by using hidden Markov Models. + It is noted that a smaller p value does not necessarily imply + more significance due to the dependency. A typical application is + to analyze genome wide association studies datasets, where SNPs + from the same chromosome are treated as a group and exhibit + strong linear genomic dependency. See Wei Z, Sun W, Wang K, + Hakonarson H (2009) for more details. + date_publication: '2022-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLIS + url_git: '' +plm: + version: 2.6-5 + title: Linear Models for Panel Data + maintainer: Kevin Tappe + description: |- + A set of estimators for models and (robust) covariance matrices, and tests for panel data + econometrics, including within/fixed effects, random effects, between, first-difference, + nested random effects as well as instrumental-variable (IV) and Hausman-Taylor-style models, + panel generalized method of moments (GMM) and general FGLS models, + mean groups (MG), demeaned MG, and common correlated effects (CCEMG) and pooled (CCEP) estimators + with common factors, variable coefficients and limited dependent variables models. + Test functions include model specification, serial correlation, cross-sectional dependence, + panel unit root and panel Granger (non-)causality. Typical references are general econometrics + text books such as Baltagi (2021), Econometric Analysis of Panel Data (), + Hsiao (2014), Analysis of Panel Data (), and Croissant and Millo (2018), + Panel Data Econometrics with R (). + date_publication: '2025-01-17' + bug_reports: https://github.com/ycroissant/plm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plm + url_git: https://github.com/ycroissant/plm +PLMIX: + version: 2.1.1 + title: |- + Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for + Partial Rankings/Orderings + maintainer: Cristina Mollica + description: Fit finite mixtures of Plackett-Luce models for partial top rankings/orderings + within the Bayesian framework. It provides MAP point estimates via EM algorithm + and posterior MCMC simulations via Gibbs Sampling. It also fits MLE as a special + case of the noninformative Bayesian analysis with vague priors. In addition to + inferential techniques, the package assists other fundamental phases of a model-based + analysis for partial rankings/orderings, by including functions for data manipulation, + simulation, descriptive summary, model selection and goodness-of-fit evaluation. + Main references on the methods are Mollica and Tardella (2017) + and Mollica and Tardella (2014) . + date_publication: '2019-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLMIX + url_git: '' +PLmixed: + version: 0.1.7 + title: |- + Estimate (Generalized) Linear Mixed Models with Factor + Structures + maintainer: Nicholas Rockwood + description: |- + Utilizes the 'lme4' and 'optimx' packages (previously the optim() + function from 'stats') to estimate (generalized) linear mixed models (GLMM) + with factor structures using a profile likelihood approach, as outlined in + Jeon and Rabe-Hesketh (2012) and + Rockwood and Jeon (2019) . + Factor analysis and item response models can be extended to allow + for an arbitrary number of nested and crossed random effects, + making it useful for multilevel and cross-classified models. + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLmixed + url_git: '' +plmmr: + version: 4.2.0 + title: Penalized Linear Mixed Models for Correlated Data + maintainer: Patrick J. Breheny + description: |- + Fits penalized linear mixed models that correct for + unobserved confounding factors. 'plmmr' infers and corrects for the + presence of unobserved confounding effects such as population + stratification and environmental heterogeneity. It then fits a linear + model via penalized maximum likelihood. Originally designed for the + multivariate analysis of single nucleotide polymorphisms (SNPs) + measured in a genome-wide association study (GWAS), 'plmmr' eliminates + the need for subpopulation-specific analyses and post-analysis p-value + adjustments. Functions for the appropriate processing of 'PLINK' + files are also supplied. For examples, see the package homepage. + . + date_publication: '2025-02-18' + bug_reports: '' + url: https://pbreheny.github.io/plmmr/ + url_cran: https://CRAN.R-project.org/package=plmmr + url_git: https://github.com/pbreheny/plmmr/ +pln: + version: 0.2-3 + title: Polytomous Logit-Normit (Graded Logistic) Model Estimation + maintainer: Carl F. Falk + description: |- + Performs bivariate composite likelihood and full + information maximum likelihood estimation for polytomous + logit-normit (graded logistic) item response theory (IRT) + models. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pln + url_git: '' +PLNmodels: + version: 1.2.0 + title: Poisson Lognormal Models + maintainer: Julien Chiquet + description: |- + The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, + 2021 ) can be used for + a variety of multivariate problems when count data are at play, including + principal component analysis for count data, discriminant analysis, model-based clustering and + network inference. Implements variational algorithms to fit such models accompanied with a set of + functions for visualization and diagnostic. + date_publication: '2024-03-05' + bug_reports: https://github.com/pln-team/PLNmodels/issues + url: https://pln-team.github.io/PLNmodels/ + url_cran: https://CRAN.R-project.org/package=PLNmodels + url_git: '' +plnr: + version: 2022.11.23 + title: A System for Planing Analyses + maintainer: Richard Aubrey White + description: |- + A system to plan analyses within the mental model + where you have one (or more) datasets and want to run either A) the same + function multiple times with different arguments, or B) multiple functions. + This is appropriate when you have multiple strata (e.g. locations, age groups) + that you want to apply the same function to, or you have multiple variables + (e.g. exposures) that you want to apply the same statistical method to, or + when you are creating the output for a report and you need multiple different + tables or graphs. + date_publication: '2022-11-23' + bug_reports: https://github.com/csids/plnr/issues + url: https://www.csids.no/plnr/ + url_cran: https://CRAN.R-project.org/package=plnr + url_git: https://github.com/csids/plnr +plogr: + version: 0.2.0 + title: The 'plog' C++ Logging Library + maintainer: Kirill Müller + description: |2- + + A simple header-only logging library for C++. + Add 'LinkingTo: plogr' to 'DESCRIPTION', and '#include ' in your C++ modules to use it. + date_publication: '2018-03-25' + bug_reports: https://github.com/krlmlr/plogr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plogr + url_git: https://github.com/krlmlr/plogr#readme +PLordprob: + version: '1.1' + title: Multivariate Ordered Probit Model via Pairwise Likelihood + maintainer: Euloge Clovis Kenne Pagui + description: Multivariate ordered probit model, i.e. the extension of the scalar + ordered probit model where the observed variables have dimension greater than + one. Estimation of the parameters is done via maximization of the pairwise likelihood, + a special case of the composite likelihood obtained as product of bivariate marginal + distributions. The package uses the Fortran 77 subroutine SADMVN by Alan Genz, + with minor adaptations made by Adelchi Azzalini in his "mvnormt" package for evaluating + the two-dimensional Gaussian integrals involved in the pairwise log-likelihood. + Optimization of the latter objective function is performed via quasi-Newton box-constrained + optimization algorithm, as implemented in nlminb. + date_publication: '2018-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLordprob + url_git: '' +PLORN: + version: 0.1.1 + title: Prediction with Less Overfitting and Robust to Noise + maintainer: Takahiko Koizumi + description: |- + A method for the quantitative prediction with much predictors. + This package provides functions to construct the quantitative prediction + model with less overfitting and robust to noise. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLORN + url_git: https://github.com/takakoizumi/PLORN +plot.matrix: + version: 1.6.2 + title: Visualizes a Matrix as Heatmap + maintainer: Sigbert Klinke + description: Visualizes a matrix object plainly as heatmap. It provides S3 functions + to plot simple matrices and loading matrices. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plot.matrix + url_git: https://github.com/sigbertklinke/plot.matrix(developmentversion) +plot3D: + version: 1.4.1 + title: Plotting Multi-Dimensional Data + maintainer: Karline Soetaert + description: Functions for viewing 2-D and 3-D data, including perspective plots, + slice plots, surface plots, scatter plots, etc. Includes data sets from oceanography. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plot3D + url_git: '' +plot3Drgl: + version: 1.0.4 + title: Plotting Multi-Dimensional Data - Using 'rgl' + maintainer: Karline Soetaert + description: The 'rgl' implementation of plot3D functions. + date_publication: '2023-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plot3Drgl + url_git: '' +plot4fun: + version: 0.1.1 + title: Just Plot for Fun + maintainer: Chen Peng + description: |- + Explore the world of R graphics with fun and interesting plot functions! + Use make_LED() to create dynamic LED screens, draw interconnected rings with Olympic_rings(), + and make festive Chinese couplets with chunlian(). + Unleash your creativity and turn data into exciting visuals! + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plot4fun + url_git: '' +plotBart: + version: 0.1.7 + title: Diagnostic and Plotting Functions to Supplement 'bartCause' + maintainer: Joseph Marlo + description: |- + Functions to assist in diagnostics and plotting during the causal inference modeling process. + Supplements the 'bartCause' package. + date_publication: '2022-05-27' + bug_reports: https://github.com/priism-center/plotBart/issues + url: https://priism-center.github.io/plotBart/ + url_cran: https://CRAN.R-project.org/package=plotBart + url_git: https://github.com/priism-center/plotBart +plotbb: + version: 0.0.6 + title: Grammar of Graphics for 'base' Plot + maintainer: Guangchuang Yu + description: Proof of concept for implementing grammar of graphics using base plot. + The bbplot() function initializes a 'bbplot' object to store input data, aesthetic + mapping, a list of layers and theme elements. The object will be rendered as a + graphic using base plot command if it is printed. + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotbb + url_git: '' +PlotBivInvGaus: + version: 0.1.0 + title: Density Contour Plot for Bivariate Inverse Gaussian Distribution + maintainer: Bhushan Saswade + description: Create the density contour plot for bivariate inverse Gaussian distribution + for given non negative random variables. + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlotBivInvGaus + url_git: '' +plotcli: + version: 0.1.0 + title: Command Line Interface Plotting + maintainer: Claas Heuer + description: |- + The 'plotcli' package provides terminal-based plotting in R. + It supports colored scatter plots, line plots, bar plots, and box plots. The package allows users + to customize plot appearance, add titles, labels, ticks, and legends, and output the plot as a text-based visualization. + date_publication: '2024-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotcli + url_git: https://github.com/cheuerde/plotcli +PlotContour: + version: 0.1.0 + title: Plot Contour Line + maintainer: Olivia Cheronet + description: This function plots a contour line with a user-defined probability + and tightness of fit. + date_publication: '2019-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlotContour + url_git: '' +plotdap: + version: 1.0.3 + title: |- + Easily Visualize Data from 'ERDDAP' Servers via the 'rerddap' + Package + maintainer: Roy Mendelssohn + description: Easily visualize and animate 'tabledap' and 'griddap' objects obtained + via the 'rerddap' package in a simple one-line command, using either base graphics + or 'ggplot2' graphics. 'plotdap' handles extracting and reshaping the data, map + projections and continental outlines. Optionally the data can be animated through + time using the 'gganmiate' package. + date_publication: '2023-10-17' + bug_reports: https://github.com/rmendels/plotdap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotdap + url_git: https://github.com/rmendels/plotdap +plotDK: + version: 0.1.0 + title: |- + Plot Summary Statistics as Choropleth Maps of Danish + Administrative Areas + maintainer: Kristian Stendorff Nielsen + description: |- + Provides a ggplot2 front end to plot summary statistics on danish provinces, + regions, municipalities, and zipcodes. The needed geoms of each of the four levels are + inherent in the package, thus making these types of plots easy for the user. This is essentially + an updated port of the previously available 'mapDK' package by Sebastian Barfort. + date_publication: '2021-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotDK + url_git: '' +PlotFTIR: + version: 1.1.0 + title: Plot FTIR Spectra + maintainer: Philip Bulsink + description: |- + The goal of 'PlotFTIR' is to easily and quickly kick-start the production of journal-quality Fourier Transform Infra-Red (FTIR) spectral plots in R using 'ggplot2'. The produced plots can be published directly or further modified by 'ggplot2' functions. + L'objectif de 'PlotFTIR' est de démarrer facilement et rapidement la production des tracés spectraux de spectroscopie infrarouge à transformée de Fourier (IRTF) de qualité journal dans R à l'aide de 'ggplot2'. Les tracés produits peuvent être publiés directement ou modifiés davantage par les fonctions 'ggplot2'. + date_publication: '2025-02-05' + bug_reports: https://github.com/NRCan/PlotFTIR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PlotFTIR + url_git: https://github.com/NRCan/PlotFTIR +plotfunctions: + version: '1.4' + title: |- + Various Functions to Facilitate Visualization of Data and + Analysis + maintainer: Jacolien van Rij + description: 'When analyzing data, plots are a helpful tool for visualizing data + and interpreting statistical models. This package provides a set of simple tools + for building plots incrementally, starting with an empty plot region, and adding + bars, data points, regression lines, error bars, gradient legends, density distributions + in the margins, and even pictures. The package builds further on R graphics by + simply combining functions and settings in order to reduce the amount of code + to produce for the user. As a result, the package does not use formula input or + special syntax, but can be used in combination with default R plot functions. + Note: Most of the functions were part of the package ''itsadug'', which is now + split in two packages: 1. the package ''itsadug'', which contains the core functions + for visualizing and evaluating nonlinear regression models, and 2. the package + ''plotfunctions'', which contains more general plot functions.' + date_publication: '2020-04-28' + bug_reports: '' + url: https://jacolienvanrij.com/tutorials.html + url_cran: https://CRAN.R-project.org/package=plotfunctions + url_git: '' +plotGMM: + version: 0.2.2 + title: Tools for Visualizing Gaussian Mixture Models + maintainer: Philip Waggoner + description: |- + The main function, plot_GMM, is used for plotting output from Gaussian mixture models (GMMs), + including both densities and overlaying mixture weight component curves from the fit GMM. The package + also include the function, plot_cut_point, which plots the cutpoint (mu) from the GMM over a histogram + of the distribution with several color options. Finally, the package includes the function, plot_mix_comps, + which is used in the plot_GMM function, and can be used to create a custom plot for overlaying mixture + component curves from GMMs. For the plot_mix_comps function, usage most often will be specifying + the "fun" argument within "stat_function" in a ggplot2 object. + date_publication: '2020-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotGMM + url_git: '' +plothelper: + version: 0.1.9 + title: |- + New Plots Based on 'ggplot2' and Functions to Create Regular + Shapes + maintainer: Jiang Wu + description: |- + An extension to 'ggplot2' and 'magick'. It contains + three groups of functions: Functions in the first group draw 'ggplot2' - based plots: geom_shading_bar() draws barplot + with shading colors in each bar. geom_rect_cm(), geom_circle_cm() and geom_ellipse_cm() draw rectangles, circles + and ellipses with centimeter as their unit. Thus their sizes do not change when the coordinate system or the aspect ratio + changes. annotation_transparent_text() draws labels with transparent texts. annotation_shading_polygon() draws irregular + polygons with shading colors. Functions in the second group generate coordinates for regular shapes and make linear transformations. Functions in the third group are 'magick' - based functions facilitating image processing. + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plothelper + url_git: https://github.com/githubwwwjjj/plothelper/blob/master/README.md +plotHMM: + version: 2023.8.28 + title: Plot Hidden Markov Models + maintainer: Toby Hocking + description: |- + Hidden Markov Models are useful for modeling + sequential data. This package provides several functions + implemented in C++ for explaining the algorithms used for + Hidden Markov Models (forward, backward, decoding, + learning). + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotHMM + url_git: '' +plotluck: + version: 1.1.1 + title: '''ggplot2'' Version of "I''m Feeling Lucky!"' + maintainer: Stefan Schroedl + description: |- + Examines the characteristics of a data frame and a formula to + automatically choose the most suitable type of plot out of the following supported + options: scatter, violin, box, bar, density, hexagon bin, spine plot, and + heat map. The aim of the package is to let the user focus on what to plot, + rather than on the "how" during exploratory data analysis. It also automates + handling of observation weights, logarithmic axis scaling, reordering of + factor levels, and overlaying smoothing curves and median lines. Plots are + drawn using 'ggplot2'. + date_publication: '2019-06-26' + bug_reports: https://github.com/stefan-schroedl/plotluck/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotluck + url_git: https://github.com/stefan-schroedl/plotluck +plotly: + version: 4.10.4 + title: Create Interactive Web Graphics via 'plotly.js' + maintainer: Carson Sievert + description: Create interactive web graphics from 'ggplot2' graphs and/or a custom + interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the + grammar of graphics. + date_publication: '2024-01-13' + bug_reports: https://github.com/plotly/plotly.R/issues + url: https://plotly-r.com + url_cran: https://CRAN.R-project.org/package=plotly + url_git: https://github.com/plotly/plotly.R +plotlyGeoAssets: + version: 0.0.2 + title: Render 'Plotly' Maps without an Internet Connection + maintainer: Carson Sievert + description: Includes 'JavaScript' files that allow 'plotly' maps to render without + an internet connection. + date_publication: '2019-01-08' + bug_reports: https://github.com/cpsievert/plotlyGeoAssets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotlyGeoAssets + url_git: https://github.com/cpsievert/plotlyGeoAssets +plotMCMC: + version: 2.0.1 + title: MCMC Diagnostic Plots + maintainer: Arni Magnusson + description: |- + Markov chain Monte Carlo diagnostic plots. The purpose of the + package is to combine existing tools from the 'coda' and 'lattice' packages, + and make it easy to adjust graphical details. + date_publication: '2020-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotMCMC + url_git: '' +plotMElm: + version: 0.1.5 + title: Plot Marginal Effects from Linear Models + maintainer: Christopher Gandrud + description: |- + Plot marginal effects for interactions estimated + from linear models. + date_publication: '2018-05-28' + bug_reports: https://github.com/christophergandrud/plotMElm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotMElm + url_git: '' +plotmm: + version: 0.1.2 + title: Tidy Tools for Visualizing Mixture Models + maintainer: Philip Waggoner + description: |- + The main function, plot_mm(), is used for (gg)plotting output from mixture models, + including both densities and overlaying mixture weight component curves from the fit models in line with the + tidy principles. The package includes several additional functions for added plot customization. + Supported model objects include: 'mixtools', 'EMCluster', and 'flexmix', with more from each in active dev. + Supported mixture model specifications include mixtures of univariate Gaussians, multivariate Gaussians, Gammas, + logistic regressions, linear regressions, and Poisson regressions. + date_publication: '2025-01-08' + bug_reports: https://github.com/pdwaggoner/plotmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotmm + url_git: '' +plotmo: + version: 3.6.4 + title: Plot a Model's Residuals, Response, and Partial Dependence Plots + maintainer: Stephen Milborrow + description: |- + Plot model surfaces for a wide variety of models + using partial dependence plots and other techniques. + Also plot model residuals and other information on the model. + date_publication: '2024-08-31' + bug_reports: '' + url: http://www.milbo.users.sonic.net + url_cran: https://CRAN.R-project.org/package=plotmo + url_git: '' +plotor: + version: 0.5.2 + title: Produces an Odds Ratio Plot from a Logistic Regression Model + maintainer: Craig Parylo + description: |- + Produces an Odds Ratio (OR) Plot to visualise the result of a + logistic regression analysis. + Provide it with a binomial regression model produced by 'glm()' and it will + convert the estimates to odds ratios with a 95% confidence interval and + plot the results using 'ggplot2'. + date_publication: '2025-02-09' + bug_reports: https://github.com/craig-parylo/plotor/issues + url: https://craig-parylo.github.io/plotor/ + url_cran: https://CRAN.R-project.org/package=plotor + url_git: https://github.com/craig-parylo/plotor +plotpc: + version: 1.0.4 + title: Plot Principal Component Histograms Around a Scatter Plot + maintainer: Stephen Milborrow + description: |- + Plot principal component histograms around a bivariate + scatter plot. + date_publication: '2015-09-27' + bug_reports: '' + url: http://www.milbo.users.sonic.net + url_cran: https://CRAN.R-project.org/package=plotpc + url_git: '' +PlotPrjNetworks: + version: 1.0.0 + title: Useful Networking Tools for Project Management + maintainer: Joaquin Bienvenido Ordieres Mere + description: Useful set of tools for plotting network diagrams in any kind of project. + date_publication: '2015-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PlotPrjNetworks + url_git: '' +plotprotein: + version: '1.0' + title: Development of Visualization Tools for Protein Sequence + maintainer: Yao Geng + description: The image of the amino acid transform on the protein level is drawn, + and the automatic routing of the functional elements such as the domain and the + mutation site is completed. + date_publication: '2017-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotprotein + url_git: '' +plotrix: + version: 3.8-4 + title: Various Plotting Functions + maintainer: Duncan Murdoch + description: Lots of plots, various labeling, axis and color scaling functions. + The author/maintainer died in September 2023. + date_publication: '2023-11-10' + bug_reports: https://github.com/dmurdoch/plotrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotrix + url_git: https://github.com/dmurdoch/plotrix +plotROC: + version: 2.3.1 + title: Generate Useful ROC Curve Charts for Print and Interactive Use + maintainer: Michael C. Sachs + description: |- + Most ROC curve plots obscure the cutoff values and inhibit + interpretation and comparison of multiple curves. This attempts to address + those shortcomings by providing plotting and interactive tools. Functions + are provided to generate an interactive ROC curve plot for web use, and + print versions. A Shiny application implementing the functions is also + included. + date_publication: '2023-10-06' + bug_reports: https://github.com/sachsmc/plotROC/issues/ + url: https://sachsmc.github.io/plotROC/ + url_cran: https://CRAN.R-project.org/package=plotROC + url_git: '' +plotscale: + version: 0.1.6 + title: Scale Graphics Devices Using Plot Dimensions + maintainer: Tim Bergsma + description: |- + Figures rendered on graphics devices are usually + rescaled to fit pre-determined device dimensions. 'plotscale' + implements the reverse: desired plot dimensions are specified + and device dimensions are calculated to accommodate marginal + material, giving consistent proportions for plot elements. + Default methods support grid graphics such as lattice and ggplot. + See "example('devsize')" and "vignette('plotscale')". + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotscale + url_git: '' +plotscaper: + version: 0.2.8 + title: Explore Your Data with Interactive Figures + maintainer: Adam Bartonicek + description: |- + A framework for creating interactive figures for data exploration. + All plots are automatically linked and support several kinds of interactive features, + including selection, zooming, panning, and parameter manipulation. The figures + can be interacted with either manually, using a mouse and a keyboard, + or by running code from inside an active R session. + date_publication: '2025-02-23' + bug_reports: https://github.com/bartonicek/plotscaper/issues + url: https://bartonicek.github.io/plotscaper/ + url_cran: https://CRAN.R-project.org/package=plotscaper + url_git: https://github.com/bartonicek/plotscaper +plotSEMM: + version: '2.4' + title: |- + Graphing Nonlinear Relations Among Latent Variables from + Structural Equation Mixture Models + maintainer: Phil Chalmers + description: |- + Contains a graphical user interface to generate the diagnostic + plots proposed by Bauer (2005; ), + Pek & Chalmers (2015; ), and + Pek, Chalmers, R. Kok, & Losardo (2015; ) to investigate + nonlinear bivariate relationships in latent regression models using structural + equation mixture models (SEMMs). + date_publication: '2017-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotSEMM + url_git: https://github.com/philchalmers/plotSEMM +plotthis: + version: 0.5.1 + title: |- + High-Level Plotting Built Upon 'ggplot2' and Other Plotting + Packages + maintainer: Panwen Wang + description: |- + Provides high-level API and a wide range of options to create stunning, publication-quality plots effortlessly. + It is built upon 'ggplot2' and other plotting packages, and is designed to be easy to use and to work seamlessly with 'ggplot2' objects. + It is particularly useful for creating complex plots with multiple layers, facets, and annotations. + It also provides a set of functions to create plots for specific types of data, such as Venn diagrams, alluvial diagrams, and phylogenetic trees. + The package is designed to be flexible and customizable, and to work well with the 'ggplot2' ecosystem. + The API can be found at . + date_publication: '2025-02-04' + bug_reports: https://github.com/pwwang/plotthis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plotthis + url_git: https://github.com/pwwang/plotthishttps://pwwang.github.io/plotthis/ +PlotTools: + version: 0.3.1 + title: Add Continuous Legends to Plots + maintainer: Martin R. Smith + description: |- + Annotate plots with legends for continuous variables and colour + spectra using the base graphics plotting tools; and manipulate irregular + polygons. + date_publication: '2024-09-03' + bug_reports: https://github.com/ms609/PlotTools/issues/ + url: https://ms609.github.io/PlotTools/ + url_cran: https://CRAN.R-project.org/package=PlotTools + url_git: https://github.com/ms609/PlotTools/ +plotwidgets: + version: 0.5.1 + title: |- + Spider Plots, ROC Curves, Pie Charts and More for Use in Other + Plots + maintainer: January Weiner + description: |- + Small self-contained plots for use in larger plots or to + delegate plotting in other functions. Also contains a number of + alternative color palettes and HSL color space based tools to modify + colors or palettes. + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plotwidgets + url_git: '' +plpoisson: + version: 0.3.1 + title: Prediction Limits for Poisson Distribution + maintainer: Luca Sartore + description: |- + Prediction limits for the Poisson distribution + are produced from both frequentist and Bayesian viewpoints. Limiting results + are provided in a Bayesian setting with uniform, Jeffreys and gamma as prior + distributions. More details on the methodology are discussed in Bejleri and + Nandram (2018) and Bejleri, Sartore and + Nandram (2021) . + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plpoisson + url_git: '' +PLreg: + version: 0.4.1 + title: Power Logit Regression for Modeling Bounded Data + maintainer: Felipe Queiroz + description: |- + Power logit regression models for bounded + continuous data, in which the density generator may be normal, Student-t, + power exponential, slash, hyperbolic, sinh-normal, or type II logistic. + Diagnostic tools associated with the fitted model, such as the residuals, + local influence measures, leverage measures, and goodness-of-fit statistics, + are implemented. The estimation process follows the maximum likelihood approach + and, currently, the package supports two types of estimators: the usual maximum + likelihood estimator and the penalized maximum likelihood estimator. More details + about power logit regression models are described in + Queiroz and Ferrari (2022) . + date_publication: '2023-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLreg + url_git: https://github.com/ffqueiroz/PLreg +PLRModels: + version: '1.4' + title: Statistical Inference in Partial Linear Regression Models + maintainer: Ana Lopez-Cheda + description: Contains statistical inference tools applied to Partial Linear Regression + (PLR) models. Specifically, point estimation, confidence intervals estimation, + bandwidth selection, goodness-of-fit tests and analysis of covariance are considered. + Kernel-based methods, combined with ordinary least squares estimation, are used + and time series errors are allowed. In addition, these techniques are also implemented + for both parametric (linear) and nonparametric regression models. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLRModels + url_git: '' +pls: + version: 2.8-5 + title: Partial Least Squares and Principal Component Regression + maintainer: Kristian Hovde Liland + description: |- + Multivariate regression methods + Partial Least Squares Regression (PLSR), Principal Component + Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS). + date_publication: '2024-09-15' + bug_reports: https://github.com/khliland/pls/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pls + url_git: https://github.com/khliland/pls +plsdepot: + version: 0.2.0 + title: Partial Least Squares (PLS) Data Analysis Methods + maintainer: Frederic Bertrand + description: |- + Different methods for PLS analysis of + one or two data tables such as Tucker's Inter-Battery, NIPALS, + SIMPLS, SIMPLS-CA, PLS Regression, and PLS Canonical Analysis. + The main reference for this software is the awesome book (in + French) 'La Regression PLS: Theorie et Pratique' by Michel + Tenenhaus. + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plsdepot + url_git: '' +plsdof: + version: 0.3-2 + title: |- + Degrees of Freedom and Statistical Inference for Partial Least + Squares Regression + maintainer: Frederic Bertrand + description: |- + The plsdof package provides Degrees of Freedom estimates + for Partial Least Squares (PLS) Regression. Model selection for + PLS is based on various information criteria (aic, bic, gmdl) + or on cross-validation. Estimates for the mean and covariance + of the PLS regression coefficients are available. They allow + the construction of approximate confidence intervals and the + application of test procedures (Kramer and Sugiyama + 2012 ). + Further, cross-validation procedures for Ridge Regression and + Principal Components Regression are available. + date_publication: '2022-11-30' + bug_reports: https://github.com/fbertran/plsdof/issues/ + url: https://fbertran.github.io/plsdof/ + url_cran: https://CRAN.R-project.org/package=plsdof + url_git: https://github.com/fbertran/plsdof/ +plsgenomics: + version: 1.5-3 + title: PLS Analyses for Genomics + maintainer: Ghislain Durif + description: |- + Routines for PLS-based genomic analyses, + implementing PLS methods for classification with + microarray data and prediction of transcription factor + activities from combined ChIP-chip analysis. The >=1.2-1 + versions include two new classification methods for microarray + data: GSIM and Ridge PLS. The >=1.3 versions includes a + new classification method combining variable selection and + compression in logistic regression context: logit-SPLS; and + an adaptive version of the sparse PLS. + date_publication: '2024-03-28' + bug_reports: https://github.com/gdurif/plsgenomics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plsgenomics + url_git: https://github.com/gdurif/plsgenomics +PLSiMCpp: + version: 1.0.4 + title: Methods for Partial Linear Single Index Model + maintainer: Shunyao Wu + description: Estimation, hypothesis tests, and variable selection in partially linear + single-index models. Please see H. (2010) at for more + details. + date_publication: '2022-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLSiMCpp + url_git: '' +plsmmLasso: + version: 1.1.0 + title: |- + Variable Selection and Inference for Partial Semiparametric + Linear Mixed-Effects Model + maintainer: Sami Leon + description: |- + Implements a partial linear semiparametric mixed-effects model (PLSMM) featuring a random intercept and applies a lasso penalty to both the fixed effects and the coefficients associated with the nonlinear function. + The model also accommodates interactions between the nonlinear function and a grouping variable, allowing for the capture of group-specific nonlinearities. Nonlinear functions are modeled using a set of bases functions. Estimation is conducted using a penalized Expectation-Maximization algorithm, and the package offers flexibility in choosing between various information criteria for model selection. + Post-selection inference is carried out using a debiasing method, while inference on the nonlinear functions employs a bootstrap approach. + date_publication: '2024-06-04' + bug_reports: https://github.com/Sami-Leon/plsmmLasso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plsmmLasso + url_git: https://github.com/Sami-Leon/plsmmLasso +plsmod: + version: 1.0.0 + title: Model Wrappers for Projection Methods + maintainer: Max Kuhn + description: |- + Bindings for additional regression models for use with the + 'parsnip' package, including ordinary and spare partial least squares + models for regression and classification (Rohart et al (2017) + ). + date_publication: '2022-09-06' + bug_reports: https://github.com/tidymodels/plsmod/issues + url: https://plsmod.tidymodels.org + url_cran: https://CRAN.R-project.org/package=plsmod + url_git: https://github.com/tidymodels/plsmod +plsmselect: + version: 0.2.0 + title: |- + Linear and Smooth Predictor Modelling with Penalisation and + Variable Selection + maintainer: Indrayudh Ghosal + description: |- + Fit a model with potentially many linear and smooth predictors. Interaction + effects can also be quantified. Variable selection is done using penalisation. For l1-type penalties + we use iterative steps alternating between using linear predictors (lasso) and smooth predictors + (generalised additive model). + date_publication: '2019-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plsmselect + url_git: '' +plspm: + version: 0.5.1 + title: Partial Least Squares Path Modeling (PLS-PM) + maintainer: Frederic Bertrand + description: |- + Partial Least Squares Path Modeling (PLS-PM), Tenenhaus, Esposito Vinzi, Chatelin, Lauro (2005) , + analysis for both metric and non-metric data, as well as REBUS analysis, Esposito Vinzi, Trinchera, Squillacciotti, and Tenenhaus (2008) . + date_publication: '2024-01-23' + bug_reports: https://github.com/gastonstat/plspm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plspm + url_git: https://github.com/gastonstat/plspm +plsRbeta: + version: 0.3.0 + title: Partial Least Squares Regression for Beta Regression Models + maintainer: Frederic Bertrand + description: Provides Partial least squares Regression for (weighted) beta regression + models (Bertrand 2013, ) and k-fold + cross-validation of such models using various criteria. It allows for missing + data in the explanatory variables. Bootstrap confidence intervals constructions + are also available. + date_publication: '2023-03-15' + bug_reports: https://github.com/fbertran/plsRbeta/issues/ + url: https://fbertran.github.io/plsRbeta/ + url_cran: https://CRAN.R-project.org/package=plsRbeta + url_git: https://github.com/fbertran/plsRbeta/ +plsRcox: + version: 1.7.7 + title: |- + Partial Least Squares Regression for Cox Models and Related + Techniques + maintainer: Frederic Bertrand + description: Provides Partial least squares Regression and various regular, sparse + or kernel, techniques for fitting Cox models in high dimensional settings , + Bastien, P., Bertrand, F., Meyer N., Maumy-Bertrand, M. (2015), Deviance residuals-based + sparse PLS and sparse kernel PLS regression for censored data, Bioinformatics, + 31(3):397-404. Cross validation criteria were studied in , Bertrand, + F., Bastien, Ph. and Maumy-Bertrand, M. (2018), Cross validating extensions of + kernel, sparse or regular partial least squares regression models to censored + data. + date_publication: '2022-11-29' + bug_reports: https://github.com/fbertran/plsRcox/issues/ + url: http://fbertran.github.io/plsRcox/ + url_cran: https://CRAN.R-project.org/package=plsRcox + url_git: https://github.com/fbertran/plsRcox/ +plsRglm: + version: 1.5.1 + title: Partial Least Squares Regression for Generalized Linear Models + maintainer: Frederic Bertrand + description: Provides (weighted) Partial least squares Regression for generalized + linear models and repeated k-fold cross-validation of such models using various + criteria . It allows for missing data in the explanatory variables. + Bootstrap confidence intervals constructions are also available. + date_publication: '2023-03-14' + bug_reports: https://github.com/fbertran/plsRglm/issues/ + url: https://fbertran.github.io/plsRglm/ + url_cran: https://CRAN.R-project.org/package=plsRglm + url_git: https://github.com/fbertran/plsRglm/ +PLStests: + version: 0.1.0 + title: Model Checking for High-Dimensional GLMs via Random Projections + maintainer: Wen Chen + description: |- + Provides methods for testing the goodness-of-fit + of generalized linear models (GLMs) using random projections. It is + specifically designed for high-dimensional scenarios where the number + of predictors substantially exceeds the sample size. The statistical + methodologies implemented in this package are detailed in the paper by + Wen Chen and Falong Tan (2024, ). + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PLStests + url_git: '' +plsVarSel: + version: 0.9.12 + title: Variable Selection in Partial Least Squares + maintainer: Kristian Hovde Liland + description: |- + Interfaces and methods for variable selection in Partial Least + Squares. The methods include filter methods, wrapper methods and embedded + methods. Both regression and classification is supported. + date_publication: '2024-05-22' + bug_reports: https://github.com/khliland/plsVarSel/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=plsVarSel + url_git: https://github.com/khliland/plsVarSel/ +pltesim: + version: '1.0' + title: |- + Simulate Probabilistic Long-Term Effects in Models with Temporal + Dependence + maintainer: Christopher Gandrud + description: |- + Calculates and depicts probabilistic long-term effects + in binary models with temporal dependence variables. The package performs + two tasks. First, it calculates the change in the probability of the event + occurring given a change in a theoretical variable. Second, it calculates + the rolling difference in the future probability of the event for two + scenarios: one where the event occurred at a given time and one where the + event does not occur. The package is consistent with the recent movement to + depict meaningful and easy-to-interpret quantities of interest with the + requisite measures of uncertainty. It is the first to make it easy for + researchers to interpret short- and long-term effects of explanatory + variables in binary autoregressive models, which can have important + implications for the correct interpretation of these models. + date_publication: '2017-06-26' + bug_reports: https://github.com/christophergandrud/pltesim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pltesim + url_git: '' +plu: + version: 0.3.0 + title: Dynamically Pluralize Phrases + maintainer: Alexander Rossell Hayes + description: |- + Converts English phrases to singular or plural form based on + the length of an associated vector. Contains helper functions to + create natural language lists from vectors and to include the length + of a vector in natural language. + date_publication: '2023-09-23' + bug_reports: https://github.com/rossellhayes/plu/issues + url: https://pkg.rossellhayes.com/plu/ + url_cran: https://CRAN.R-project.org/package=plu + url_git: https://github.com/rossellhayes/plu +plug: + version: 0.1.0 + title: Secure and Intuitive Access to 'Plug' Interface + maintainer: Andre Leite + description: Provides a secure and user-friendly interface to interact with the + 'Plug' 'API'. It enables developers to store and manage + tokens securely using the 'keyring' package, retrieve data from 'API' endpoints + with the 'httr2' package, and handle large datasets with chunked data fetching. + Designed for simplicity and security, the package facilitates seamless integration + with 'Plug' ecosystem. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plug + url_git: +plugdensity: + version: 0.8-5 + title: Plug-in Kernel Density Estimation + maintainer: Martin Maechler + description: |- + Kernel density estimation with global bandwidth selection + via "plug-in". + date_publication: '2023-12-08' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=846&atid=3357 + url: '' + url_cran: https://CRAN.R-project.org/package=plugdensity + url_git: http://curves-etc.r-forge.r-project.org/ +plumber: + version: 1.3.0 + title: An API Generator for R + maintainer: Barret Schloerke + description: |- + Gives the ability to automatically generate and serve an HTTP API + from R functions using the annotations in the R documentation around your + functions. + date_publication: '2025-02-19' + bug_reports: https://github.com/rstudio/plumber/issues + url: https://www.rplumber.io + url_cran: https://CRAN.R-project.org/package=plumber + url_git: https://github.com/rstudio/plumber +plumberDeploy: + version: 0.2.1 + title: Plumber Deployment + maintainer: Bruno Tremblay + description: |- + Gives the ability to automatically deploy a plumber API + from R functions on 'DigitalOcean' and other cloud-based servers. + date_publication: '2021-03-22' + bug_reports: https://github.com/meztez/plumberDeploy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plumberDeploy + url_git: https://github.com/meztez/plumberDeploy +plumbertableau: + version: 0.1.1 + title: Turn 'Plumber' APIs into 'Tableau' Extensions + maintainer: James Blair + description: |- + Build 'Plumber' APIs that can be used in 'Tableau' workbooks. + Annotations in R comments allow APIs to conform to the 'Tableau Analytics + Extension' specification, so that R code can be used to power 'Tableau' + workbooks. + date_publication: '2023-12-19' + bug_reports: https://github.com/rstudio/plumbertableau/issues + url: https://rstudio.github.io/plumbertableau/ + url_cran: https://CRAN.R-project.org/package=plumbertableau + url_git: https://github.com/rstudio/plumbertableau +plumbr: + version: 0.6.10 + title: Mutable and Dynamic Data Models + maintainer: Michael Lawrence + description: |- + The base R data.frame, like any vector, is + copied upon modification. This behavior is at odds with + that of GUIs and interactive graphics. To rectify this, + plumbr provides a mutable, dynamic tabular data model. + Models may be chained together to form the complex + plumbing necessary for sophisticated graphical + interfaces. Also included is a + general framework for linking datasets; an typical + use case would be a linked brush. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plumbr + url_git: https://github.com/ggobi/plumbr/wiki +plume: + version: 0.2.5 + title: A Simple Author Handler for Scientific Writing + maintainer: Arnaud Gallou + description: |- + Handles and formats author information in scientific writing + in 'R Markdown' and 'Quarto'. 'plume' provides easy-to-use and + flexible tools for injecting author metadata in 'YAML' headers as well + as generating author and contribution lists (among others) as strings + from tabular data. + date_publication: '2024-09-02' + bug_reports: https://github.com/arnaudgallou/plume/issues + url: https://arnaudgallou.github.io/plume/ + url_cran: https://CRAN.R-project.org/package=plume + url_git: https://github.com/arnaudgallou/plume +pluscode: + version: 0.1.0 + title: Encoder for Google 'Pluscodes' + maintainer: Michael Doyle + description: Retrieves a 'pluscode' by inputting latitude and longitude. Includes + additional functions to retrieve neighbouring 'pluscodes'. + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pluscode + url_git: '' +plusCode2: + version: 0.1.0 + title: Coordinates to 'Plus Code' Conversion Tool + maintainer: Armando d'Aniello + description: Generates 'Plus Code' of geometric objects or data frames that contain + them, giving the possibility to specify the precision of the area. The main feature + of the package comes from the open-source code developed by 'Google Inc.' present + in the repository . + For details about 'Plus Code', visit or . + date_publication: '2024-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=plusCode2 + url_git: https://github.com/Armando-d/plusCode2 +plutor: + version: 0.1.0 + title: Useful Functions for Visualization + maintainer: William Song + description: |- + In ancient Roman mythology, 'Pluto' was the ruler of the underworld + and presides over the afterlife. 'Pluto' was frequently conflated with + 'Plutus', the god of wealth, because mineral wealth was found underground. + When plotting with R, you try once, twice, practice again and again, and finally + you get a pretty figure you want. It's a 'plot tour', a tour about repetition + and reward. Hope 'plutor' helps you on the tour! + date_publication: '2023-10-27' + bug_reports: https://github.com/william-swl/plutor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=plutor + url_git: https://github.com/william-swl/plutor +plyr: + version: 1.8.9 + title: Tools for Splitting, Applying and Combining Data + maintainer: Hadley Wickham + description: |- + A set of tools that solves a common set of problems: you need + to break a big problem down into manageable pieces, operate on each + piece and then put all the pieces back together. For example, you + might want to fit a model to each spatial location or time point in + your study, summarise data by panels or collapse high-dimensional + arrays to simpler summary statistics. The development of 'plyr' has + been generously supported by 'Becton Dickinson'. + date_publication: '2023-10-02' + bug_reports: https://github.com/hadley/plyr/issues + url: http://had.co.nz/plyr + url_cran: https://CRAN.R-project.org/package=plyr + url_git: https://github.com/hadley/plyr +pm3: + version: 0.2.0 + title: Propensity Score Matching for Unordered 3-Group Data + maintainer: Qiang LIU + description: |- + You can use this program for 3 sets of categorical data for propensity score matching. + Assume that the data has 3 different categorical variables. You can use it to perform propensity matching of baseline indicator groupings. + The matching will make the differences in the baseline data smaller. + This method was described by Alvaro Fuentes (2022) . + date_publication: '2024-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pm3 + url_git: '' +PMA: + version: 1.2-4 + title: Penalized Multivariate Analysis + maintainer: Balasubramanian Narasimhan + description: |- + Performs Penalized Multivariate Analysis: a penalized + matrix decomposition, sparse principal components analysis, + and sparse canonical correlation analysis, described in + Witten, Tibshirani and Hastie (2009) + and Witten and Tibshirani + (2009) Extensions of sparse canonical correlation analysis, + with applications to genomic data + . + date_publication: '2024-09-03' + bug_reports: https://github.com/bnaras/PMA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PMA + url_git: https://github.com/bnaras/PMA +PMAPscore: + version: 0.1.1 + title: Identify Prognosis-Related Pathways Altered by Somatic Mutation + maintainer: Junwei Han + description: We innovatively defined a pathway mutation accumulate perturbation + score (PMAPscore) to reflect the position and the cumulative effect of the genetic + mutations at the pathway level. Based on the PMAPscore of pathways, identified + prognosis-related pathways altered by somatic mutation and predict immunotherapy + efficacy by constructing a multiple-pathway-based risk model (Tarca, Adi Laurentiu + et al (2008) ). + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PMAPscore + url_git: '' +pmartR: + version: 2.4.6 + title: |- + Panomics Marketplace - Quality Control and Statistical Analysis + for Panomics Data + maintainer: Lisa Bramer + description: 'Provides functionality for quality control processing and statistical + analysis of mass spectrometry (MS) omics data, in particular proteomic (either + at the peptide or the protein level), lipidomic, and metabolomic data, as well + as RNA-seq based count data and nuclear magnetic resonance (NMR) data. This includes + data transformation, specification of groups that are to be compared against each + other, filtering of features and/or samples, data normalization, data summarization + (correlation, PCA), and statistical comparisons between defined groups. Implements + methods described in: Webb-Robertson et al. (2014) . Webb-Robertson + et al. (2011) . Matzke et al. (2011) . Matzke + et al. (2013) . Polpitiya et al. (2008) . Webb-Robertson + et al. (2010) .' + date_publication: '2024-10-14' + bug_reports: https://github.com/pmartR/pmartR/issues + url: https://pmartr.github.io/pmartR/ + url_cran: https://CRAN.R-project.org/package=pmartR + url_git: https://github.com/pmartR/pmartR +pmc: + version: 1.0.6 + title: Phylogenetic Monte Carlo + maintainer: Carl Boettiger + description: |- + Monte Carlo based model choice for applied phylogenetics of + continuous traits. Method described in Carl Boettiger, Graham Coop, + Peter Ralph (2012) Is your phylogeny informative? Measuring + the power of comparative methods, Evolution 66 (7) + 2240-51. . + date_publication: '2023-10-03' + bug_reports: https://github.com/cboettig/pmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmc + url_git: https://github.com/cboettig/pmc +pmcalibration: + version: 0.2.0 + title: Calibration Curves for Clinical Prediction Models + maintainer: Stephen Rhodes + description: |- + Fit calibrations curves for clinical prediction models and calculate several associated + metrics (Eavg, E50, E90, Emax). Ideally predicted probabilities from a prediction model + should align with observed probabilities. Calibration curves relate predicted probabilities + (or a transformation thereof) to observed outcomes via a flexible non-linear smoothing function. + 'pmcalibration' allows users to choose between several smoothers (regression splines, generalized + additive models/GAMs, lowess, loess). Both binary and time-to-event outcomes are supported. + See Van Calster et al. (2016) ; + Austin and Steyerberg (2019) ; + Austin et al. (2020) . + date_publication: '2025-02-21' + bug_reports: https://github.com/stephenrho/pmcalibration/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmcalibration + url_git: https://github.com/stephenrho/pmcalibration +pmclust: + version: 0.2-1 + title: |- + Parallel Model-Based Clustering using + Expectation-Gathering-Maximization Algorithm for Finite Mixture + Gaussian Model + maintainer: Wei-Chen Chen + description: |- + Aims to utilize model-based clustering (unsupervised) + for high dimensional and ultra large data, especially in a distributed + manner. The code employs 'pbdMPI' to perform a + expectation-gathering-maximization algorithm + for finite mixture Gaussian + models. The unstructured dispersion matrices are assumed in the + Gaussian models. The implementation is default in the single program + multiple data programming model. The code can be executed + through 'pbdMPI' and MPI' implementations such as 'OpenMPI' + and 'MPICH'. + See the High Performance Statistical Computing website + + for more information, documents and examples. + date_publication: '2021-02-11' + bug_reports: https://github.com/snoweye/pmclust/issues + url: https://pbdr.org/ + url_cran: https://CRAN.R-project.org/package=pmclust + url_git: '' +PMCMR: + version: '4.4' + title: Calculate Pairwise Multiple Comparisons of Mean Rank Sums + maintainer: Thorsten Pohlert + description: |- + Note, that the 'PMCMR' package is superset + by the novel 'PMCMRplus' package. The 'PMCMRplus' + package contains all functions from + 'PMCMR' and many more parametric and non-parametric + multiple comparison procedures, one-factorial trend + tests, as well as improved method functions, + such as print, summary and plot. + The 'PMCMR' package is no longer maintained, + but kept for compatibility of reverse depending + packages for some time. + date_publication: '2021-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PMCMR + url_git: '' +PMCMRplus: + version: 1.9.12 + title: |- + Calculate Pairwise Multiple Comparisons of Mean Rank Sums + Extended + maintainer: Thorsten Pohlert + description: |- + For one-way layout experiments the one-way ANOVA can + be performed as an omnibus test. All-pairs multiple comparisons + tests (Tukey-Kramer test, Scheffe test, LSD-test) + and many-to-one tests (Dunnett test) for normally distributed + residuals and equal within variance are available. Furthermore, + all-pairs tests (Games-Howell test, Tamhane's T2 test, + Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one + (Tamhane-Dunnett Test) for normally distributed residuals + and heterogeneous variances are provided. Van der Waerden's normal + scores test for omnibus, all-pairs and many-to-one tests is + provided for non-normally distributed residuals and homogeneous + variances. The Kruskal-Wallis, BWS and Anderson-Darling + omnibus test and all-pairs tests + (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- + Fligner test) as well as many-to-one (Nemenyi test, Dunn test, + U-test) are given for the analysis of variance by ranks. + Non-parametric trend tests (Jonckheere test, Cuzick test, + Johnson-Mehrotra test, Spearman test) are included. + In addition, a Friedman-test for one-way ANOVA with repeated + measures on ranks (CRBD) and Skillings-Mack test for unbalanced + CRBD is provided with consequent all-pairs tests (Nemenyi test, + Siegel test, Miller test, Conover test, Exact test) + and many-to-one tests (Nemenyi test, Demsar test, Exact test). + A trend can be tested with Pages's test. Durbin's test + for a two-way balanced incomplete block design (BIBD) is given + in this package as well as Gore's test for CRBD with multiple + observations per cell is given. Outlier tests, Mandel's k- and + h statistic as well as functions for Type I error and Power + analysis as well as generic summary, print and plot methods + are provided. + date_publication: '2024-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PMCMRplus + url_git: '' +pmd: + version: 0.2.7 + title: |- + Paired Mass Distance Analysis for GC/LC-MS Based Non-Targeted + Analysis and Reactomics Analysis + maintainer: Miao YU + description: Paired mass distance (PMD) analysis proposed in Yu, Olkowicz and Pawliszyn + (2018) and PMD based reactomics analysis proposed + in Yu and Petrick (2020) for gas/liquid chromatography–mass + spectrometry (GC/LC-MS) based non-targeted analysis. PMD analysis including GlobalStd + algorithm and structure/reaction directed analysis. GlobalStd algorithm could + found independent peaks in m/z-retention time profiles based on retention time + hierarchical cluster analysis and frequency analysis of paired mass distances + within retention time groups. Structure directed analysis could be used to find + potential relationship among those independent peaks in different retention time + groups based on frequency of paired mass distances. Reactomics analysis could + also be performed to build PMD network, assign sources and make biomarker reaction + discovery. GUIs for PMD analysis is also included as 'shiny' applications. + date_publication: '2025-01-15' + bug_reports: https://github.com/yufree/pmd/issues + url: https://yufree.github.io/pmd/ + url_cran: https://CRAN.R-project.org/package=pmd + url_git: '' +pMEM: + version: 0.1-1 + title: Predictive Moran's Eigenvector Maps + maintainer: Guillaume Guénard + description: |- + Calculation of Predictive Moran's eigenvector maps (pMEM), as + defined by Guénard and Legendre (In Press) "Spatially-explicit predictions + using spatial eigenvector maps" . Methods in + Ecology and Evolution. This method enables scientists to predict the values of + spatially-structured environmental variables. Multiple types of pMEM are + defined, each one implemented on the basis of spatial weighting function + taking a range parameter, and sometimes also a shape parameter. The code's + modular nature enables programers to implement new pMEM by defining new + spatial weighting functions. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pMEM + url_git: '' +pmetar: + version: 0.5.0 + title: Processing METAR Weather Reports + maintainer: Pawel Cwiek + description: |- + Allows to download current and historical METAR weather reports + extract and parse basic parameters and present main weather information. + Current reports are downloaded from Aviation Weather Center + and historical reports from + Iowa Environmental Mesonet web page of Iowa State University + ASOS-AWOS-METAR . + date_publication: '2023-10-25' + bug_reports: https://github.com/prcwiek/pmetar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmetar + url_git: https://github.com/prcwiek/pmetar +pmev: + version: 0.1.2 + title: Calculates Earned Value for a Project Schedule + maintainer: David Hammond + description: Given a project schedule and associated costs, this package calculates + the earned value to date. It is an implementation of Project Management Body of + Knowledge (PMBOK) methodologies (reference Project Management Institute. (2021). + A guide to the Project Management Body of Knowledge (PMBOK guide) (7th ed.). Project + Management Institute, Newtown Square, PA, ISBN 9781628256673 (pdf)). + date_publication: '2024-08-27' + bug_reports: https://github.com/david-hammond/pmev/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmev + url_git: https://github.com/david-hammond/pmev +PMEvapotranspiration: + version: 0.1.0 + title: |- + Calculation of the Penman-Monteith Evapotranspiration using + Weather Variables + maintainer: Dr. Himadri Shekhar Roy + description: The Food and Agriculture Organization-56 Penman-Monteith is one of + the important method for estimating evapotranspiration from vegetated land areas. + This package helps to calculate reference evapotranspiration using the weather + variables collected from weather station. Evapotranspiration is the process of + water transfer from the land surface to the atmosphere through evaporation from + soil and other surfaces and transpiration from plants. The package aims to support + agricultural, hydrological, and environmental research by offering accurate and + accessible reference evapotranspiration calculation. This package has been developed + using concept of Córdova et al. (2015) and Debnath + et al. (2015) . + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PMEvapotranspiration + url_git: '' +pmhtutorial: + version: '1.5' + title: Minimal Working Examples for Particle Metropolis-Hastings + maintainer: Johan Dahlin + description: |- + Routines for state estimate in a linear + Gaussian state space model and a simple stochastic volatility model using + particle filtering. Parameter inference is also carried out in these models + using the particle Metropolis-Hastings algorithm that includes the particle + filter to provided an unbiased estimator of the likelihood. This package is + a collection of minimal working examples of these algorithms and is only + meant for educational use and as a start for learning to them on your own. + date_publication: '2019-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmhtutorial + url_git: https://github.com/compops/pmh-tutorial-rpkg +pmlbr: + version: 0.3.0 + title: |- + Interface to the Penn Machine Learning Benchmarks Data + Repository + maintainer: Trang Le + description: |- + Check available classification and regression data sets from the PMLB repository and download them. + The PMLB repository () contains a curated collection of data sets for evaluating and comparing machine learning algorithms. + These data sets cover a range of applications, and include binary/multi-class classification problems and + regression problems, as well as combinations of categorical, ordinal, and continuous features. + There are currently over 150 datasets included in the PMLB repository. + date_publication: '2025-02-28' + bug_reports: https://github.com/EpistasisLab/pmlbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmlbr + url_git: https://github.com/EpistasisLab/pmlbr +pmledecon: + version: 0.2.1 + title: Deconvolution Density Estimation using Penalized MLE + maintainer: Yun Cai + description: Given a sample with additive measurement error, the package estimates + the deconvolution density - that is, the density of the underlying distribution + of the sample without measurement error. The method maximises the log-likelihood + of the estimated density, plus a quadratic smoothness penalty. The distribution + of the measurement error can be either a known family, or can be estimated from + a "pure error" sample. For known error distributions, the package supports Normal, + Laplace or Beta distributed error. For unknown error distribution, a pure error + sample independent from the data is used. + date_publication: '2022-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmledecon + url_git: '' +pmml: + version: 2.5.2 + title: Generate PMML for Various Models + maintainer: Dmitriy Bolotov + description: The Predictive Model Markup Language (PMML) is an XML-based language + which provides a way for applications to define machine learning, statistical + and data mining models and to share models between PMML compliant applications. + More information about the PMML industry standard and the Data Mining Group can + be found at . The generated PMML can be imported into any PMML + consuming application, such as Zementis Predictive Analytics products. The package + isofor (used for anomaly detection) can be installed with devtools::install_github("gravesee/isofor"). + date_publication: '2022-03-04' + bug_reports: https://github.com/SoftwareAG/r-pmml/issues + url: https://open-source.softwareag.com/r-pmml/ + url_cran: https://CRAN.R-project.org/package=pmml + url_git: https://github.com/SoftwareAG/r-pmml +pmmlTransformations: + version: 1.3.3 + title: Transforms Input Data from a PMML Perspective + maintainer: Dmitriy Bolotov + description: |- + Allows for data to be transformed before using it to construct models. Builds structures to allow functions in the PMML package to + output transformation details in addition to the model in the resulting PMML file. The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at . The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products, which integrate with web services, relational database systems and deploy natively on Hadoop in conjunction with Hive, Spark or Storm, as well as allow predictive analytics to be executed for IBM z Systems mainframe applications and real-time, streaming analytics platforms. + date_publication: '2019-06-11' + bug_reports: '' + url: https://www.softwareag.com/zementis + url_cran: https://CRAN.R-project.org/package=pmmlTransformations + url_git: '' +pmparser: + version: 1.0.21 + title: |- + Create and Maintain a Relational Database of Data from + PubMed/MEDLINE + maintainer: Jake Hughey + description: |- + Provides a simple interface for extracting various elements from + the publicly available PubMed XML files, incorporating PubMed's regular + updates, and combining the data with the NIH Open Citation Collection. See + Schoenbachler and Hughey (2021) . + date_publication: '2025-01-14' + bug_reports: '' + url: https://pmparser.hugheylab.org + url_cran: https://CRAN.R-project.org/package=pmparser + url_git: https://github.com/hugheylab/pmparser +pmr: + version: 1.2.5.1 + title: Probability Models for Ranking Data + maintainer: Paul H. Lee + description: Descriptive statistics (mean rank, pairwise frequencies, and marginal + matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), + probability models (Luce models, distance-based models, and rank-ordered logit + models) and visualization with multidimensional preference analysis for ranking + data are provided. Current, only complete rankings are supported by this package. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmr + url_git: '' +pmsampsize: + version: 1.1.3 + title: Sample Size for Development of a Prediction Model + maintainer: Joie Ensor + description: 'Computes the minimum sample size required for the development of a + new multivariable prediction model using the criteria proposed by Riley et al. + (2018) . pmsampsize can be used to calculate the minimum + sample size for the development of models with continuous, binary or survival + (time-to-event) outcomes. Riley et al. (2018) lay out + a series of criteria the sample size should meet. These aim to minimise the overfitting + and to ensure precise estimation of key parameters in the prediction model.' + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmsampsize + url_git: '' +pmultinom: + version: 1.0.0 + title: One-Sided Multinomial Probabilities + maintainer: Alexander Davis + description: Implements multinomial CDF (P(N1<=n1, ..., Nk<=nk)) and tail probabilities + (P(N1>n1, ..., Nk>nk)), as well as probabilities with both constraints (P(l1. + date_publication: '2018-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmultinom + url_git: '' +pmvalsampsize: + version: 0.1.0 + title: Sample Size for External Validation of a Prediction Model + maintainer: Joie Ensor + description: Computes the minimum sample size required for the external validation + of an existing multivariable prediction model using the criteria proposed by Archer + (2020) and Riley (2021) . + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmvalsampsize + url_git: '' +pmwg: + version: 0.2.7 + title: Particle Metropolis Within Gibbs + maintainer: Gavin Cooper + description: |- + Provides an R implementation of the Particle Metropolis within + Gibbs sampler for model parameter, covariance matrix and random effect + estimation. A more general implementation of the sampler based on the paper + by Gunawan, D., Hawkins, G. E., Tran, M. N., Kohn, R., & Brown, S. D. + (2020) . An HTML tutorial document describing + the package is available at + and + includes several detailed examples, some background and troubleshooting + steps. + date_publication: '2024-01-31' + bug_reports: https://github.com/university-of-newcastle-research/pmwg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmwg + url_git: https://github.com/university-of-newcastle-research/pmwg +PMwR: + version: 1.0-1 + title: Portfolio Management with R + maintainer: Enrico Schumann + description: |- + Tools for the practical management of financial + portfolios: backtesting investment and trading strategies, + computing profit/loss and returns, analysing trades, + handling lists of transactions, reporting, and more. The + package provides a small set of reliable, efficient and + convenient tools for processing and analysing + trade/portfolio data. The manual provides all the details; + it is available from + . + Examples and descriptions of new features are provided at + . + date_publication: '2024-10-19' + bug_reports: '' + url: https://enricoschumann.net/PMwR/ + url_cran: https://CRAN.R-project.org/package=PMwR + url_git: https://gitlab.com/enricoschumann/PMwR +pmxcode: + version: 0.2.0 + title: Create Pharmacometric Models + maintainer: Sebastien Bihorel + description: |- + Provides a user interface to create or modify pharmacometric + models for various modeling and simulation software platforms. + date_publication: '2025-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmxcode + url_git: '' +pmxcv: + version: 0.0.1.0 + title: Integration-Based Coefficients of Variance + maintainer: John Prybylski + description: 'Estimate coefficient of variance percent (CV%) for any arbitrary distribution, + including some built-in estimates for commonly-used transformations in pharmacometrics. + Methods are described in various sources, but applied here as summarized in: Prybylski, + (2024) .' + date_publication: '2024-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmxcv + url_git: '' +pmxpartab: + version: 0.5.0 + title: Parameter Tables for PMx Analyses + maintainer: Benjamin Rich + description: |- + Generate nicely formatted HTML tables to display estimation results for + pharmacometric models. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pmxpartab + url_git: '' +pmxTools: + version: '1.3' + title: Pharmacometric and Pharmacokinetic Toolkit + maintainer: Justin Wilkins + description: |- + Pharmacometric tools for common data analytical tasks; closed-form solutions for calculating concentrations at given + times after dosing based on compartmental PK models (1-compartment, 2-compartment and 3-compartment, covering infusions, zero- + and first-order absorption, and lag times, after single doses and at steady state, per Bertrand & Mentre (2008) + ); parametric simulation from NONMEM-generated parameter estimates + and other output; and parsing, tabulating and plotting results generated by Perl-speaks-NONMEM (PsN). + date_publication: '2023-02-21' + bug_reports: https://github.com/kestrel99/pmxTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pmxTools + url_git: https://github.com/kestrel99/pmxTools +PNADcIBGE: + version: 0.7.5 + title: Downloading, Reading and Analyzing PNADC Microdata + maintainer: Gabriel Assuncao + description: |- + Provides tools for downloading, reading and analyzing the Continuous National + Household Sample Survey - PNADC, a household survey from Brazilian Institute + of Geography and Statistics - IBGE. The data must be downloaded from the official + website . Further analysis must be made using package 'survey'. + date_publication: '2024-02-01' + bug_reports: https://github.com/Gabriel-Assuncao/PNADcIBGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PNADcIBGE + url_git: '' +PNAR: + version: '1.7' + title: Poisson Network Autoregressive Models + maintainer: Michail Tsagris + description: 'Quasi likelihood-based methods for estimating linear and log-linear + Poisson Network Autoregression models with p lags and covariates. Tools for testing + the linearity versus several non-linear alternatives. Tools for simulation of + multivariate count distributions, from linear and non-linear PNAR models, by using + a specific copula construction. References include: Armillotta, M. and K. Fokianos + (2023). "Nonlinear network autoregression". Annals of Statistics, 51(6): 2526--2552. + . Armillotta, M. and K. Fokianos (2024). "Count network + autoregression". Journal of Time Series Analysis, 45(4): 584--612. . + Armillotta, M., Tsagris, M. and Fokianos, K. (2024). "Inference for Network Count + Time Series with the R Package PNAR". The R Journal, 15/4: 255--269. .' + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PNAR + url_git: '' +pnd: + version: 0.0.6 + title: |- + Parallel Numerical Derivatives, Gradients, Jacobians, and + Hessians of Arbitrary Accuracy Order + maintainer: Andreï Victorovitch Kostyrka + description: |- + Calculation of numerical derivatives through + finite-difference approximations with parallel capabilities and optimal + step-size selection to improve accuracy. These functions facilitate + efficient computation of derivatives, gradients, Jacobians, and Hessians, + allowing for more evaluations to reduce the mathematical and machine errors. + Designed for compatibility with the 'numDeriv' package, + which has not received updates in several years, it introduces advanced features + such as computing derivatives of arbitrary order, improving + the accuracy of Hessian approximations by avoiding repeated differencing, + and parallelising slow functions on Windows, Mac, and Linux. + date_publication: '2025-02-25' + bug_reports: https://github.com/Fifis/pnd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pnd + url_git: https://github.com/Fifis/pnd +PNDSIBGE: + version: 0.1.1 + title: |- + Downloading, Reading and Analyzing PNDS Microdata - Package in + Development + maintainer: Gabriel Assuncao + description: |- + Provides tools for downloading, reading and analyzing the National + Survey of Demographic and Health - PNDS, a household survey from Brazilian Institute + of Geography and Statistics - IBGE. The data must be downloaded from the official + website . Further analysis must be made using package 'survey'. + date_publication: '2024-02-01' + bug_reports: https://github.com/Gabriel-Assuncao/PNDSIBGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PNDSIBGE + url_git: '' +png: + version: 0.1-8 + title: Read and write PNG images + maintainer: Simon Urbanek + description: This package provides an easy and simple way to read, write and display + bitmap images stored in the PNG format. It can read and write both files and in-memory + raw vectors. + date_publication: '2022-11-29' + bug_reports: '' + url: http://www.rforge.net/png/ + url_cran: https://CRAN.R-project.org/package=png + url_git: '' +PNSIBGE: + version: 0.2.1 + title: Downloading, Reading and Analyzing PNS Microdata + maintainer: Gabriel Assuncao + description: |- + Provides tools for downloading, reading and analyzing the National + Survey of Health - PNS, a household survey from Brazilian Institute + of Geography and Statistics - IBGE. The data must be downloaded from the official + website . Further analysis must be made using package 'survey'. + date_publication: '2024-02-01' + bug_reports: https://github.com/Gabriel-Assuncao/PNSIBGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PNSIBGE + url_git: '' +PNWColors: + version: 0.1.0 + title: Color Palettes Inspired by Nature in the US Pacific Northwest + maintainer: Jake Lawlor + description: |- + PNW-Inspired Palettes for 'R' data visualizations. Palettes are variable + in length and checked for colorblind accessibility from hue, saturation, + and lightness value scaling using the 'Chroma.js Color Palette Helper' + . + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PNWColors + url_git: https://github.com/jakelawlor/PNWColors +PoA: + version: 1.2.1 + title: Finds the Price of Anarchy for Routing Games + maintainer: Hector Haffenden + description: Computes the optimal flow, Nash flow and the Price of Anarchy for any + routing game defined within the game theoretical framework. The input is a routing + game in the form of it’s cost and flow functions. Then transforms this into an + optimisation problem, allowing both Nash and Optimal flows to be solved by nonlinear + optimisation. See and Knight and + Harper (2013) for more information. + date_publication: '2019-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoA + url_git: '' +pocketapi: + version: '0.1' + title: Wrapper Around the 'Pocket' API + maintainer: Frie Preu + description: Functions that interface with the 'Pocket' API (). + Allows the user to get, add, and modify items in their own 'Pocket' account. + date_publication: '2020-11-20' + bug_reports: https://github.com/CorrelAid/pocketapi//issues + url: '' + url_cran: https://CRAN.R-project.org/package=pocketapi + url_git: https://github.com/CorrelAid/pocketapi/ +POCRE: + version: 0.6.0 + title: Penalized Orthogonal-Components Regression + maintainer: Dabao Zhang + description: Penalized orthogonal-components regression (POCRE) is a supervised + dimension reduction method for high-dimensional data. It sequentially constructs + orthogonal components (with selected features) which are maximally correlated + to the response residuals. POCRE can also construct common components for multiple + responses and thus build up latent-variable models. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POCRE + url_git: '' +pocrm: + version: '0.13' + title: Dose Finding in Drug Combination Phase I Trials Using PO-CRM + maintainer: '"Brewer, Ben (arb5mt)"' + description: Provides functions to implement and simulate the partial order continual + reassessment method (PO-CRM) of Wages, Conaway and O'Quigley (2011) + for use in Phase I trials of combinations of agents. Provides a function for generating + a set of initial guesses (skeleton) for the toxicity probabilities at each combination + that correspond to the set of possible orderings of the toxicity probabilities + specified by the user. + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pocrm + url_git: '' +POD: + version: 1.2.0 + title: Probability of Detection for Qualitative PCR Methods + maintainer: Markus Boenn + description: |- + This tool computes the probability of detection (POD) curve and the limit of detection (LOD), i.e. the number of copies of the target DNA sequence required to ensure a 95 % probability of detection (LOD95). Other quantiles of the LOD can be specified. + This is a reimplementation of the mathematical-statistical modelling of the validation of qualitative polymerase chain reaction (PCR) methods within a single laboratory as provided by the commercial tool 'PROLab' . The modelling itself has been described by Uhlig et al. (2015) . + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POD + url_git: '' +PoDBAY: + version: 1.4.3 + title: Vaccine Efficacy Estimation Package + maintainer: Julie Dudasova (MSD) + description: Set of functions that implement the PoDBAY method, described in the + publication 'A method to estimate probability of disease and vaccine efficacy + from clinical trial immunogenicity data' by Julie Dudasova, Regina Laube, Chandni + Valiathan, Matthew C. Wiener, Ferdous Gheyas, Pavel Fiser, Justina Ivanauskaite, + Frank Liu and Jeffrey R. Sachs (NPJ Vaccines, 2021), . + date_publication: '2021-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoDBAY + url_git: '' +podcleaner: + version: 0.1.2 + title: Legacy Scottish Post Office Directories Cleaner + maintainer: Olivier Bautheac + description: |- + Attempts to clean optical character recognition (OCR) errors in + legacy Scottish Post Office Directories. Further attempts to match records from + trades and general directories. + date_publication: '2022-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=podcleaner + url_git: '' +PODES: + version: 0.1.0 + title: Village Potential Statistics of Indonesia + maintainer: Fadhlul Mubarak + description: Village potential statistics (PODES) collects various information on + village potential and challenges faced by villages in Indonesia. Information related + to village potential includes economy, security, health, employment, communication + and information, sports, entertainment, development, community empowerment, education, + socio-culture, transportation in the village. Information related to challenges + includes natural disasters, public health, environmental pollution, social problems + and security disturbances that occur in the village. + date_publication: '2024-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PODES + url_git: '' +poems: + version: 1.3.2 + title: Pattern-Oriented Ensemble Modeling System + maintainer: July Pilowsky + description: 'A framework of interoperable R6 classes (Chang, 2020, ) + for building ensembles of viable models via the pattern-oriented modeling (POM) + approach (Grimm et al.,2005, ). The package includes + classes for encapsulating and generating model parameters, and managing the POM + workflow. The workflow includes: model setup; generating model parameters via + Latin hyper-cube sampling (Iman & Conover, 1980, ); + running multiple sampled model simulations; collating summary results; and validating + and selecting an ensemble of models that best match known patterns. By default, + model validation and selection utilizes an approximate Bayesian computation (ABC) + approach (Beaumont et al., 2002, ), although + alternative user-defined functionality could be employed. The package includes + a spatially explicit demographic population model simulation engine, which incorporates + default functionality for density dependence, correlated environmental stochasticity, + stage-based transitions, and distance-based dispersal. The user may customize + the simulator by defining functionality for translocations, harvesting, mortality, + and other processes, as well as defining the sequence order for the simulator + processes. The framework could also be adapted for use with other model simulators + by utilizing its extendable (inheritable) base classes.' + date_publication: '2025-02-24' + bug_reports: https://github.com/GlobalEcologyLab/poems/issues + url: https://globalecologylab.github.io/poems/ + url_cran: https://CRAN.R-project.org/package=poems + url_git: https://github.com/GlobalEcologyLab/poems +POET: + version: '2.0' + title: Principal Orthogonal ComplEment Thresholding (POET) Method + maintainer: Martina Mincheva + description: |- + Estimate large covariance matrices in approximate factor + models by thresholding principal orthogonal complements. + date_publication: '2016-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POET + url_git: '' +pogit: + version: 1.3.0 + title: Bayesian Variable Selection for a Poisson-Logistic Model + maintainer: Michaela Dvorzak + description: |- + Bayesian variable selection for regression models of under-reported + count data as well as for (overdispersed) Poisson, negative binomal and + binomial logit regression models using spike and slab priors. + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pogit + url_git: '' +PogromcyDanych: + version: 1.7.1 + title: |- + DataCrunchers (PogromcyDanych) is the Massive Online Open Course + that Brings R and Statistics to the People + maintainer: Przemyslaw Biecek + description: The data sets used in the online course ,,PogromcyDanych''. You can + process data in many ways. The course Data Crunchers will introduce you to this + variety. For this reason we will work on datasets of different size (from several + to several hundred thousand rows), with various level of complexity (from two + to two thousand columns) and prepared in different formats (text data, quantitative + data and qualitative data). All of these data sets were gathered in a single big + package called PogromcyDanych to facilitate access to them. It contains all sorts + of data sets such as data about offer prices of cars, results of opinion polls, + information about changes in stock market indices, data about names given to newborn + babies, ski jumping results or information about outcomes of breast cancer patients + treatment. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PogromcyDanych + url_git: '' +poibin: + version: '1.6' + title: The Poisson Binomial Distribution + maintainer: Yili Hong + description: 'Implementation of both the exact and approximation methods for computing + the cdf of the Poisson binomial distribution as described in Hong (2013) . It also provides the pmf, quantile function, and + random number generation for the Poisson binomial distribution. The C code for + fast Fourier transformation (FFT) is written by R Core Team (2019), + which implements the FFT algorithm in Singleton (1969) .' + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poibin + url_git: '' +PoiClaClu: + version: 1.0.2.1 + title: |- + Classification and Clustering of Sequencing Data Based on a + Poisson Model + maintainer: Daniela Witten + description: Implements the methods described in the paper, Witten (2011) Classification + and Clustering of Sequencing Data using a Poisson Model, Annals of Applied Statistics + 5(4) 2493-2518. + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoiClaClu + url_git: '' +poilog: + version: 0.4.2.1 + title: Poisson Lognormal and Bivariate Poisson Lognormal Distribution + maintainer: Vidar Grotan + description: |- + Functions for obtaining the density, random deviates + and maximum likelihood estimates of the Poisson lognormal + distribution and the bivariate Poisson lognormal distribution. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poilog + url_git: '' +POINT: + version: '1.3' + title: Protein Structure Guided Local Test + maintainer: Shannon T. Holloway + description: Provides an implementation of a rare variant association test that + utilizes protein tertiary structure to increase signal and to identify likely + causal variants. Performs structure-guided collapsing, which leads to local tests + that borrow information from neighboring variants on a protein and that provide + association information on a variant-specific level. For details of the implemented + method see West, R. M., Lu, W., Rotroff, D. M., Kuenemann, M., Chang, S-M., Wagner + M. J., Buse, J. B., Motsinger-Reif, A., Fourches, D., and Tzeng, J-Y. (2019) . + date_publication: '2023-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POINT + url_git: '' +pointblank: + version: 0.12.2 + title: |- + Data Validation and Organization of Metadata for Local and + Remote Tables + maintainer: Richard Iannone + description: |- + Validate data in data frames, 'tibble' objects, 'Spark' + 'DataFrames', and database tables. Validation pipelines can be made using + easily-readable, consecutive validation steps. Upon execution of the + validation plan, several reporting options are available. User-defined + thresholds for failure rates allow for the determination of appropriate + reporting actions. Many other workflows are available including an + information management workflow, where the aim is to record, collect, and + generate useful information on data tables. + date_publication: '2024-10-23' + bug_reports: https://github.com/rstudio/pointblank/issues + url: https://rstudio.github.io/pointblank/ + url_cran: https://CRAN.R-project.org/package=pointblank + url_git: https://github.com/rstudio/pointblank +pointdensityP: + version: 0.3.5 + title: Point Density for Geospatial Data + maintainer: Paul Evangelista + description: |- + The function pointdensity returns a density count and the temporal average for + every point in the original list. The dataframe returned includes four + columns: lat, lon, count, and date_avg. The "lat" column is the original + latitude data; the "lon" column is the original longitude data; the "count" + is the density count of the number of points within a radius of + radius*grid_size (the neighborhood); and the date_avg column includes the + average date of each point in the neighborhood. + date_publication: '2020-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pointdensityP + url_git: '' +PointedSDMs: + version: 2.1.3 + title: |- + Fit Models Derived from Point Processes to Species Distributions + using 'inlabru' + maintainer: Philip Mostert + description: |- + Integrated species distribution modeling is a rising field in quantitative ecology thanks to significant rises in the quantity of data available, increases in computational speed and the proven benefits of using such models. + Despite this, the general software to help ecologists construct such models in an easy-to-use framework is lacking. + We therefore introduce the R package 'PointedSDMs': which provides the tools to help ecologists set up integrated models and perform inference on them. + There are also functions within the package to help run spatial cross-validation for model selection, as well as generic plotting and predicting functions. + An introduction to these methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) . + date_publication: '2025-01-13' + bug_reports: https://github.com/PhilipMostert/PointedSDMs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PointedSDMs + url_git: https://github.com/PhilipMostert/PointedSDMs +PointFore: + version: 0.2.0 + title: |- + Interpretation of Point Forecasts as State-Dependent Quantiles + and Expectiles + maintainer: Patrick Schmidt + description: |- + Estimate specification models for the state-dependent level of an optimal quantile/expectile forecast. + Wald Tests and the test of overidentifying restrictions are implemented. Plotting of the estimated specification model is possible. + The package contains two data sets with forecasts and realizations: the daily accumulated precipitation at London, UK from the high-resolution model of the + European Centre for Medium-Range Weather Forecasts (ECMWF, ) and GDP growth Greenbook data by the US Federal Reserve. + See Schmidt, Katzfuss and Gneiting (2015) for more details on the identification and estimation of a directive behind a point forecast. + date_publication: '2019-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PointFore + url_git: '' +pointr: + version: 0.2.0 + title: Working Comfortably with Pointers and Shortcuts to R Objects + maintainer: Joachim Zuckarelli + description: R has no built-in pointer functionality. The 'pointr' package fills + this gap and lets you create pointers to R objects, including subsets of dataframes. + This makes your R code more readable and maintainable. + date_publication: '2021-01-06' + bug_reports: https://github.com/jsugarelli/pointr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pointr + url_git: https://github.com/jsugarelli/pointr/ +pointRes: + version: 2.0.2 + title: Analyzing Pointer Years and Components of Resilience + maintainer: Marieke van der Maaten-Theunissen + description: Functions to calculate and plot event and pointer years as well as + resilience indices. Designed for dendroecological applications, but also suitable + to analyze patterns in other ecological time series. + date_publication: '2023-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pointRes + url_git: '' +PoisBinNonNor: + version: 1.3.3 + title: Data Generation with Poisson, Binary and Continuous Components + maintainer: Ran Gao + description: |- + Generation of multiple count, binary and continuous variables simultaneously + given the marginal characteristics and association structure. Throughout the package, + the word 'Poisson' is used to imply count data under the assumption of Poisson distribution. + The details of the method are explained in Amatya et al. (2015) . + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoisBinNonNor + url_git: '' +poisbinom: + version: 1.0.1 + title: A Faster Implementation of the Poisson-Binomial Distribution + maintainer: Santiago Olivella + description: Provides the probability, distribution, and quantile functions and + random number generator for the Poisson-Binomial distribution. This package relies + on FFTW to implement the discrete Fourier transform, so that it is much faster + than the existing implementation of the same algorithm in R. + date_publication: '2017-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poisbinom + url_git: '' +PoisBinOrd: + version: 1.4.3 + title: Data Generation with Poisson, Binary and Ordinal Components + maintainer: Ran Gao + description: |- + Generation of multiple count, binary and ordinal variables simultaneously + given the marginal characteristics and association structure. Throughout the package, + the word 'Poisson' is used to imply count data under the assumption of Poisson distribution. The details of the method are explained in Amatya, A. and Demirtas, H. (2015) . + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoisBinOrd + url_git: '' +PoisBinOrdNonNor: + version: 1.5.3 + title: Generation of Up to Four Different Types of Variables + maintainer: Ran Gao + description: Generation of a chosen number of count, binary, ordinal, and continuous + random variables, with specified correlations and marginal properties. The details + of the method are explained in Demirtas (2012) . + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoisBinOrdNonNor + url_git: '' +PoisBinOrdNor: + version: 1.6.3 + title: |- + Data Generation with Poisson, Binary, Ordinal and Normal + Components + maintainer: Ran Gao + description: |- + Generation of multiple count, binary, ordinal and normal variables simultaneously given the marginal characteristics and association structure. + The details of the method are explained in Demirtas et al. (2012) . + date_publication: '2021-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoisBinOrdNor + url_git: '' +poisDoubleSamp: + version: 1.1.1 + title: Confidence Intervals with Poisson Double Sampling + maintainer: David Kahle + description: |- + Functions to create confidence intervals for ratios of Poisson + rates under misclassification using double sampling. Implementations of the + methods described in Kahle, D., P. Young, B. Greer, and D. Young (2016). + "Confidence Intervals for the Ratio of Two Poisson Rates Under One-Way + Differential Misclassification Using Double Sampling." Computational + Statistics & Data Analysis, 95:122–132. + date_publication: '2022-05-10' + bug_reports: https://github.com/dkahle/poisDoubleSamp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poisDoubleSamp + url_git: https://github.com/dkahle/poisDoubleSamp +poisFErobust: + version: 2.0.0 + title: Poisson Fixed Effects Robust + maintainer: Evan Wright + description: |- + Computation of robust standard errors of Poisson fixed effects + models, following Wooldridge (1999). + date_publication: '2020-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poisFErobust + url_git: https://bitbucket.org/ew-btb/poisson-fe-robust +poismf: + version: 0.4.0-4 + title: |- + Factorization of Sparse Counts Matrices Through Poisson + Likelihood + maintainer: David Cortes + description: |- + Creates a non-negative low-rank approximate factorization of a sparse counts matrix by maximizing Poisson + likelihood with L1/L2 regularization (e.g. for implicit-feedback recommender systems or bag-of-words-based topic modeling) + (Cortes, (2018) ), which usually leads to very sparse user and item factors (over 90% zero-valued). + Similar to hierarchical Poisson factorization (HPF), but follows an optimization-based approach with regularization + instead of a hierarchical prior, and is fit through gradient-based methods instead of variational inference. + date_publication: '2023-03-26' + bug_reports: https://github.com/david-cortes/poismf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poismf + url_git: https://github.com/david-cortes/poismf +PoisNonNor: + version: 1.6.3 + title: Simultaneous Generation of Count and Continuous Data + maintainer: Ran Gao + description: Generation of count (assuming Poisson distribution) and continuous + data (using Fleishman polynomials) simultaneously. The details of the method are + explained in Demirtas et al. (2012) . + date_publication: '2021-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoisNonNor + url_git: '' +PoisNor: + version: 1.3.3 + title: |- + Simultaneous Generation of Multivariate Data with Poisson and + Normal Marginals + maintainer: Ran Gao + description: |- + Generates multivariate data with count and continuous variables with a pre-specified correlation matrix. The count and continuous variables are assumed to have Poisson and normal marginals, respectively. The data generation mechanism is a combination of the normal to anything principle and a connection between Poisson and normal correlations in the mixture. + The details of the method are explained in Yahav et al. (2012) . + date_publication: '2021-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoisNor + url_git: '' +poisson.glm.mix: + version: '1.4' + title: Fit High Dimensional Mixtures of Poisson GLMs + maintainer: Panagiotis Papastamoulis + description: Mixtures of Poisson Generalized Linear Models for high dimensional + count data clustering. The (multivariate) responses can be partitioned into set + of blocks. Three different parameterizations of the linear predictor are considered. + The models are estimated according to the EM algorithm with an efficient initialization + scheme . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poisson.glm.mix + url_git: '' +PoissonBinomial: + version: 1.2.7 + title: |- + Efficient Computation of Ordinary and Generalized Poisson + Binomial Distributions + maintainer: Florian Junge + description: Efficient implementations of multiple exact and approximate methods + as described in Hong (2013) , Biscarri, Zhao & + Brunner (2018) and Zhang, Hong & Balakrishnan + (2018) for computing the probability mass, + cumulative distribution and quantile functions, as well as generating random numbers + for both the ordinary and generalized Poisson binomial distribution. + date_publication: '2024-09-17' + bug_reports: https://github.com/fj86/PoissonBinomial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PoissonBinomial + url_git: https://github.com/fj86/PoissonBinomial +poissoned: + version: 0.1.3 + title: Poisson Disk Sampling in 2D and 3D + maintainer: Mike Cheng + description: |- + Poisson disk sampling is a method of generating blue noise + sample patterns where all samples are at least a specified distance + apart. Poisson samples may be generated in two or three dimensions + with this package. The algorithm used is an + implementation of Bridson's "Fast Poisson disk sampling in + arbitrary dimensions" . + date_publication: '2024-10-21' + bug_reports: https://github.com/coolbutuseless/poissoned/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poissoned + url_git: https://github.com/coolbutuseless/poissoned +PoissonMultinomial: + version: '1.1' + title: The Poisson-Multinomial Distribution + maintainer: Yili Hong + description: Implementation of the exact, normal approximation, and simulation-based + methods for computing the probability mass function (pmf) and cumulative distribution + function (cdf) of the Poisson-Multinomial distribution, together with a random + number generator for the distribution. The exact method is based on multi-dimensional + fast Fourier transformation (FFT) of the characteristic function of the Poisson-Multinomial + distribution. The normal approximation method uses a multivariate normal distribution + to approximate the pmf of the distribution based on central limit theorem. The + simulation method is based on the law of large numbers. Details about the methods + are available in Lin, Wang, and Hong (2022) . + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoissonMultinomial + url_git: '' +PoissonPCA: + version: 1.0.3 + title: Poisson-Noise Corrected PCA + maintainer: Toby Kenney + description: For a multivariate dataset with independent Poisson measurement error, + calculates principal components of transformed latent Poisson means. T. Kenney, + T. Huang, H. Gu (2019) . + date_publication: '2021-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoissonPCA + url_git: '' +poissonreg: + version: 1.0.1 + title: Model Wrappers for Poisson Regression + maintainer: Hannah Frick + description: |- + Bindings for Poisson regression models for use with the + 'parsnip' package. Models include simple generalized linear models, + Bayesian models, and zero-inflated Poisson models (Zeileis, Kleiber, + and Jackman (2008) ). + date_publication: '2022-08-22' + bug_reports: https://github.com/tidymodels/poissonreg/issues + url: https://poissonreg.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=poissonreg + url_git: https://github.com/tidymodels/poissonreg +poistweedie: + version: 1.0.2 + title: Poisson-Tweedie Exponential Family Models + maintainer: David Pechel Cactcha + description: Simulation of models Poisson-Tweedie. + date_publication: '2023-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poistweedie + url_git: '' +pokemon: + version: 0.1.3 + title: Pokemon Data in English and Brazilian Portuguese + maintainer: William Amorim + description: |- + Provides a dataset of Pokemon information in + both English and Brazilian Portuguese. The dataset contains 949 rows and + 22 columns, including information such as the Pokemon's name, ID, height, + weight, stats, type, and more. + date_publication: '2023-03-22' + bug_reports: https://github.com/williamorim/pokemon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pokemon + url_git: https://github.com/williamorim/pokemon +PolarCAP: + version: 1.0.1 + title: Access the Polarization in Comparative Attitudes Project + maintainer: Isaac Mehlhaff + description: |- + Distributes data from the Polarization in Comparative Attitudes Project. Helper + functions enable data retrieval in wide and tidy formats for user-defined + countries and years. Provides support for case-insensitive country names in many + languages. Mehlhaff (2022) . + date_publication: '2023-07-10' + bug_reports: https://github.com/imehlhaff/PolarCAP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PolarCAP + url_git: https://github.com/imehlhaff/PolarCAP +polaroid: + version: 0.1.0 + title: Create Hex Stickers with 'shiny' + maintainer: Jinhwan Kim + description: |- + Create hexagonal shape sticker image. + 'polaroid' can be used in user's web browser. + 'polaroid' can be used in 'shinyapps.io'. + In both way, user can download created 'hexSticker' as 'PNG' image. + 'polaroid' is built based on 'argonDash', 'colourpicker' and 'hexSticker' R package. + date_publication: '2023-11-18' + bug_reports: https://github.com/jhk0530/polaroid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polaroid + url_git: https://github.com/jhk0530/polaroid +poLCA: + version: 1.6.0.1 + title: Polytomous Variable Latent Class Analysis + maintainer: Drew Linzer + description: |- + Latent class analysis and latent class regression models + for polytomous outcome variables. Also known as latent structure analysis. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poLCA + url_git: https://github.com/dlinzer/poLCA +poldis: + version: 0.1.2 + title: Analyse Political Texts + maintainer: Henrique Sposito + description: |- + Wrangle and annotate different types of political texts. + It also introduces Urgency Analysis, + a new method for the analysis of urgency in political texts. + date_publication: '2024-09-04' + bug_reports: https://github.com/henriquesposito/poldis/issues + url: http://henriquesposito.com/poldis/ + url_cran: https://CRAN.R-project.org/package=poldis + url_git: '' +PolicyPortfolios: + version: '0.3' + title: Tools for Managing, Measuring and Visualizing Policy Portfolios + maintainer: Xavier Fernández i Marín + description: |- + Tools for simplifying the creation and management of data structures + suitable for dealing with policy portfolios, that is, two-dimensional spaces + of policy instruments and policy targets. The package also allows to generate measures of + portfolio characteristics and facilitates their visualization. + date_publication: '2022-03-11' + bug_reports: https://github.com/xfim/PolicyPortfolios/issues + url: http://xavier-fim.net/packages/PolicyPortfolios/ + url_cran: https://CRAN.R-project.org/package=PolicyPortfolios + url_git: https://github.com/xfim/PolicyPortfolios +policytree: + version: 1.2.3 + title: |- + Policy Learning via Doubly Robust Empirical Welfare Maximization + over Trees + maintainer: Erik Sverdrup + description: |- + Learn optimal policies via doubly robust empirical + welfare maximization over trees. Given doubly robust reward estimates, this package + finds a rule-based treatment prescription policy, where the policy takes the form of + a shallow decision tree that is globally (or close to) optimal. + date_publication: '2024-06-13' + bug_reports: https://github.com/grf-labs/policytree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=policytree + url_git: https://github.com/grf-labs/policytree +polimetrics: + version: 1.2.1.14 + title: R Tools for Political Measures + maintainer: Vann Jr Burrel + description: 'This is a collection of data and functions for common metrics in political + science research. Data measuring ideology, and functions calculating geographical + diffusion and ideological diffusion - geog.diffuse() and ideo.dist(), respectively. + Functions derived from methods developed in: Soule and King (2006) , + Berry et al. (1998) , Cruz-Aceves and Mallinson (2019) , + and Grossback et al. (2004) .' + date_publication: '2022-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polimetrics + url_git: '' +poliscidata: + version: 2.3.0 + title: |- + Datasets and Functions Featured in Pollock and Edwards, an R + Companion to Essentials of Political Analysis, Second Edition + maintainer: Barry Edwards + description: |- + Bundles the datasets and functions used in the textbook by Philip + Pollock and Barry Edwards, an R Companion to Essentials of Political Analysis, + Second Edition. + date_publication: '2020-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poliscidata + url_git: '' +polished: + version: 0.8.1 + title: Authentication and Hosting for 'shiny' Apps + maintainer: Andy Merlino + description: |- + Authentication, user administration, hosting, and additional infrastructure for 'shiny' apps. See + for additional documentation and examples. + date_publication: '2023-02-11' + bug_reports: https://github.com/tychobra/polished/issues + url: https://polished.tech + url_cran: https://CRAN.R-project.org/package=polished + url_git: https://github.com/tychobra/polished +PolisheR: + version: 1.0.0 + title: Interfacing 'NaileR' with 'Shiny' + maintainer: Sébastien Lê + description: A very small package for more convenient use of 'NaileR'. You provide + a data set containing a latent variable you want to understand. It generates a + description and an interpretation of this latent variable using a Large Language + Model. For perceptual data, it describes the stimuli used in the experiment. + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolisheR + url_git: '' +polite: + version: 0.1.3 + title: Be Nice on the Web + maintainer: Dmytro Perepolkin + description: 'Be responsible when scraping data from websites by following polite + principles: introduce yourself, ask for permission, take slowly and never ask + twice.' + date_publication: '2023-06-30' + bug_reports: https://github.com/dmi3kno/polite/issues + url: https://dmi3kno.github.io/polite/ + url_cran: https://CRAN.R-project.org/package=polite + url_git: https://github.com/dmi3kno/polite +politeness: + version: 0.9.3 + title: Detecting Politeness Features in Text + maintainer: Mike Yeomans + description: Detecting markers of politeness in English natural language. This package + allows researchers to easily visualize and quantify politeness between groups + of documents. This package combines prior research on the linguistic markers of + politeness. We thank the Spencer Foundation, the Hewlett Foundation, and Harvard's + Institute for Quantitative Social Science for support. + date_publication: '2023-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=politeness + url_git: '' +politicsR: + version: 0.1.0 + title: Calculating Political System Metrics + maintainer: Denisson Silva + description: |- + A toolbox to facilitate the calculation of political system indicators for researchers. + This package offers a variety of basic indicators related to electoral systems, party systems, elections, + and parliamentary studies, as well as others. Main references are: + Loosemore and Hanby (1971) ; + Gallagher (1991) ; + Laakso and Taagepera (1979) ; + Rae (1968) ; + Hirschmaņ (1945) ; + Kesselman (1966) ; + Jones and Mainwaring (2003) ; + Rice (1925) ; + Pedersen (1979) ; + SANTOS (2002) . + date_publication: '2023-03-16' + bug_reports: https://github.com/silvadenisson/politicsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=politicsR + url_git: '' +polle: + version: '1.5' + title: Policy Learning + maintainer: Andreas Nordland + description: Package for evaluating user-specified finite stage policies and learning + optimal treatment policies via doubly robust loss functions. Policy learning methods + include doubly robust learning of the blip/conditional average treatment effect + and sequential policy tree learning. The package also include methods for optimal + subgroup analysis. See Nordland and Holst (2022) + for documentation and references. + date_publication: '2024-09-06' + bug_reports: https://github.com/AndreasNordland/polle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polle + url_git: '' +pollen: + version: 0.82.0 + title: Analysis of Aerobiological Data + maintainer: Jakub Nowosad + description: |- + Supports analysis of aerobiological data. + Available features include determination of pollen season limits, + replacement of outliers (Kasprzyk and Walanus (2014) ), + calculation of growing degree days (Baskerville and Emin (1969) ), + and determination of the base temperature for growing degree days + (Yang et al. (1995) + provides model objects to use the bodysize function internally. All models are + described in Kendall et al (2018) . + date_publication: '2018-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pollimetry + url_git: '' +pollster: + version: 0.1.6 + title: Calculate Crosstab and Topline Tables of Weighted Survey Data + maintainer: John D. Johnson + description: |- + Calculate common types of tables for weighted survey data. + Options include topline and (2-way and 3-way) crosstab tables of + categorical or ordinal data as well as summary tables of weighted + numeric variables. Optionally, include the margin of error at + selected confidence intervals including the design effect. The + design effect is calculated as described by + Kish (1965) beginning + on page 257. Output takes the form of tibbles (simple data frames). + This package conveniently handles labelled data, such as that + commonly used by 'Stata' and 'SPSS.' Complex survey design is + not supported at this time. + date_publication: '2023-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pollster + url_git: '' +polmineR: + version: 0.8.9 + title: Verbs and Nouns for Corpus Analysis + maintainer: Andreas Blaette + description: |- + Package for corpus analysis using the Corpus Workbench + ('CWB', ) as an efficient back end for indexing + and querying large corpora. The package offers functionality to flexibly create + subcorpora and to carry out basic statistical operations (count, co-occurrences + etc.). The original full text of documents can be reconstructed and inspected at + any time. Beyond that, the package is intended to serve as an interface to + packages implementing advanced statistical procedures. Respective data structures + (document-term matrices, term-co-occurrence matrices etc.) can be created based + on the indexed corpora. + date_publication: '2023-10-29' + bug_reports: https://github.com/PolMine/polmineR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polmineR + url_git: https://github.com/PolMine/polmineR +polspline: + version: 1.1.25 + title: Polynomial Spline Routines + maintainer: Charles Kooperberg + description: |- + Routines for the polynomial spline fitting routines + hazard regression, hazard estimation with flexible tails, logspline, + lspec, polyclass, and polymars, by C. Kooperberg and co-authors. + date_publication: '2024-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polspline + url_git: '' +Poly4AT: + version: 1.0.1 + title: Access 'INVEKOS' API for Field Polygons + maintainer: Sebastian Wieser + description: A 'shiny' app that allows to access and use the 'INVEKOS' API for field + polygons in Austria. API documentation is available at . + date_publication: '2024-10-21' + bug_reports: https://github.com/farmse988/Poly4AT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Poly4AT + url_git: https://github.com/farmse988/Poly4AT +polyaAeppli: + version: 2.0.2 + title: Implementation of the Polya-Aeppli Distribution + maintainer: Conrad Burden + description: Functions for evaluating the mass density, cumulative distribution + function, quantile function and random variate generation for the Polya-Aeppli + distribution, also known as the geometric compound Poisson distribution. More + information on the implementation can be found at Conrad J. Burden (2014) . + date_publication: '2022-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polyaAeppli + url_git: '' +polyapost: + version: 1.7-1 + title: Simulating from the Polya Posterior + maintainer: Glen Meeden + description: |- + Simulate via Markov chain Monte Carlo (hit-and-run algorithm) + a Dirichlet distribution conditioned to satisfy a finite set of linear + equality and inequality constraints (hence to lie in a convex polytope + that is a subset of the unit simplex). + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polyapost + url_git: '' +Polychrome: + version: 1.5.1 + title: Qualitative Palettes with Many Colors + maintainer: Kevin R. Coombes + description: |- + Tools for creating, viewing, and assessing qualitative + palettes with many (20-30 or more) colors. See Coombes and colleagues + (2019) . + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Polychrome + url_git: http://oompa.r-forge.r-project.org/ +polyclip: + version: 1.10-7 + title: Polygon Clipping + maintainer: Adrian Baddeley + description: R port of Angus Johnson's open source library 'Clipper'. Performs polygon + clipping operations (intersection, union, set minus, set difference) for polygonal + regions of arbitrary complexity, including holes. Computes offset polygons (spatial + buffer zones, morphological dilations, Minkowski dilations) for polygonal regions + and polygonal lines. Computes Minkowski Sum of general polygons. There is a function + for removing self-intersections from polygon data. + date_publication: '2024-07-23' + bug_reports: https://github.com/baddstats/polyclip/issues + url: https://www.angusj.com + url_cran: https://CRAN.R-project.org/package=polyclip + url_git: https://github.com/baddstats/polyclip +polycor: + version: 0.8-1 + title: Polychoric and Polyserial Correlations + maintainer: John Fox + description: |- + Computes polychoric and polyserial correlations by quick "two-step" methods or ML, + optionally with standard errors; tetrachoric and biserial correlations are special cases. + date_publication: '2022-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polycor + url_git: https://r-forge.r-project.org/projects/polycor/ +PolycrossDesigns: + version: 1.1.0 + title: Polycross Designs ("PolycrossDesigns") + maintainer: Ashutosh Dalal + description: A polycross is the pollination by natural hybridization of a group + of genotypes, generally selected, grown in isolation from other compatible genotypes + in such a way to promote random open pollination. A particular practical application + of the polycross method occurs in the production of a synthetic variety resulting + from cross-pollinated plants. Laying out these experiments in appropriate designs, + known as polycross designs, would not only save experimental resources but also + gather more information from the experiment. Different experimental situations + may arise in polycross nurseries which may be requiring different polycross designs + (Varghese et. al. (2015) . " Experimental designs + for open pollination in polycross trials"). This package contains a function named + PD() which generates nine types of polycross designs suitable for various experimental + situations. + date_publication: '2022-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolycrossDesigns + url_git: '' +polyCub: + version: 0.9.2 + title: Cubature over Polygonal Domains + maintainer: Sebastian Meyer + description: |- + Numerical integration of continuously differentiable + functions f(x,y) over simple closed polygonal domains. + The following cubature methods are implemented: + product Gauss cubature (Sommariva and Vianello, 2007, + ), + the simple two-dimensional midpoint rule + (wrapping 'spatstat.geom' functions), and + adaptive cubature for radially symmetric functions via line + integrate() along the polygon boundary (Meyer and Held, 2014, + , Supplement B). + For simple integration along the axes, the 'cubature' package + is more appropriate. + date_publication: '2025-02-11' + bug_reports: https://github.com/bastistician/polyCub/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polyCub + url_git: https://github.com/bastistician/polyCub +polyglotr: + version: 1.5.2 + title: Translate Text + maintainer: Tomer Iwan + description: |- + Provide easy methods to translate pieces of text. + Functions send requests to translation services online. + date_publication: '2024-08-23' + bug_reports: https://github.com/Tomeriko96/polyglotr/issues + url: https://tomeriko96.github.io/polyglotr/ + url_cran: https://CRAN.R-project.org/package=polyglotr + url_git: https://github.com/Tomeriko96/polyglotr/ +PolyHaplotyper: + version: 1.0.1 + title: |- + Assignment of Haplotypes Based on SNP Dosages in Diploids and + Polyploids + maintainer: Roeland E. Voorrips + description: |- + Infer the genetic composition of individuals + in terms of haplotype dosages for a haploblock, based + on bi-allelic marker dosages, for any ploidy level. + Reference: Voorrips and Tumino: PolyHaplotyper: haplotyping in polyploids based on bi-allelic marker dosage data. + Submitted to BMC Bioinformatics (2021). + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolyHaplotyper + url_git: '' +polyhedralCubature: + version: 1.1.0 + title: Multiple Integration over Convex Polyhedra + maintainer: Stéphane Laurent + description: |- + Evaluation of multiple integrals over convex polyhedra. This + is useful when the bounds of the integrals are some linear + combinations of the variables. + date_publication: '2023-11-22' + bug_reports: https://github.com/stla/polyhedralCubature/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polyhedralCubature + url_git: https://github.com/stla/polyhedralCubature +polykde: + version: 1.0.0 + title: Polyspherical Kernel Density Estimation + maintainer: Eduardo García-Portugués + description: |- + Kernel density estimation on the polysphere, hypersphere, and + circle. Includes functions for density estimation, regression estimation, + ridge estimation, bandwidth selection, kernels, samplers, and homogeneity + tests. Companion package to García-Portugués and Meilán-Vila (2024) + and García-Portugués and Meilán-Vila + (2023) . + date_publication: '2025-02-17' + bug_reports: https://github.com/egarpor/polykde/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polykde + url_git: https://github.com/egarpor/polykde +polylabelr: + version: 0.3.0 + title: Find the Pole of Inaccessibility (Visual Center) of a Polygon + maintainer: Johan Larsson + description: |- + A wrapper around the C++ library 'polylabel' from 'Mapbox', + providing an efficient routine for finding the approximate pole of + inaccessibility of a polygon, which usually serves as an excellent candidate + for labeling of a polygon. + date_publication: '2024-11-19' + bug_reports: https://github.com/jolars/polylabelr/issues + url: https://jolars.github.io/polylabelr/ + url_cran: https://CRAN.R-project.org/package=polylabelr + url_git: https://github.com/jolars/polylabelr +polymapR: + version: 1.1.6 + title: Linkage Analysis in Outcrossing Polyploids + maintainer: Peter Bourke + description: |- + Creation of linkage maps in polyploid species from marker dosage + scores of an F1 cross from two heterozygous parents. Currently works for outcrossing diploid, autotriploid, autotetraploid and autohexaploid species, + as well as segmental allotetraploids. Methods are described in a manuscript of Bourke et al. (2018) . Since version 1.1.0, + both discrete and probabilistic genotypes are acceptable input; for more details on the latter see Liao et al. (2021) . + date_publication: '2024-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polymapR + url_git: '' +polymatching: + version: 1.0.1 + title: A Matching Algorithm for Designs with Multiple Groups + maintainer: Giovanni Nattino + description: |- + Includes functions implementing the conditionally optimal matching algorithm, + which can be used to generate matched samples in designs with multiple groups. The algorithm + is described in Nattino, Song and Lu (2022) . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polymatching + url_git: '' +polyMatrix: + version: 0.9.16 + title: Infrastructure for Manipulation Polynomial Matrices + maintainer: Nikolai Ryzhkov + description: |2- + + Implementation of class "polyMatrix" for storing a matrix of polynomials and implements + basic matrix operations; including a determinant and characteristic polynomial. + It is based on the package 'polynom' and uses a lot of its methods to implement matrix operations. + This package includes 3 methods of triangularization of polynomial matrices: + Extended Euclidean algorithm which is most classical but numerically unstable; + Sylvester algorithm based on LQ decomposition; + Interpolation algorithm is based on LQ decomposition and Newton interpolation. + Both methods are described in + D. Henrion & M. Sebek, Reliable numerical methods for polynomial matrix triangularization, + IEEE Transactions on Automatic Control (Volume 44, Issue 3, Mar 1999, Pages 497-508) + and in + Salah Labhalla, Henri Lombardi & Roger Marlin, + Algorithmes de calcule de la reduction de Hermite d'une matrice a coefficients polynomeaux, + Theoretical Computer Science (Volume 161, Issue 1-2, July 1996, Pages 69-92) . + date_publication: '2021-07-18' + bug_reports: https://github.com/namezys/polymatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polyMatrix + url_git: https://github.com/namezys/polymatrix +polynom: + version: 1.4-1 + title: |- + A Collection of Functions to Implement a Class for Univariate + Polynomial Manipulations + maintainer: Bill Venables + description: |- + A collection of functions to implement a class for univariate + polynomial manipulations. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polynom + url_git: '' +PolynomF: + version: 2.0-8 + title: Polynomials in R + maintainer: Bill Venables + description: |- + Implements univariate polynomial operations in R, including + polynomial arithmetic, finding zeros, plotting, and some operations on + lists of polynomials. + date_publication: '2024-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolynomF + url_git: '' +PolyPatEx: + version: 0.9.2 + title: Paternity Exclusion in Autopolyploid Species + maintainer: Alexander Zwart + description: |- + Functions to perform paternity exclusion via allele + matching, in autopolyploid species having ploidy 4, 6, or 8. The + marker data used can be genotype data (copy numbers known) or + 'allelic phenotype data' (copy numbers not known). + date_publication: '2016-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolyPatEx + url_git: '' +polypharmacy: + version: 1.0.0 + title: Calculate Several Polypharmacy Indicators + maintainer: Guillaume Boucher + description: |- + Analyse prescription drug deliveries to calculate several indicators of polypharmacy corresponding to the various definitions found in the literature. + Bjerrum, L., Rosholm, J. U., Hallas, J., & Kragstrup, J. (1997) . + Chan, D.-C., Hao, Y.-T., & Wu, S.-C. (2009a) . + Fincke, B. G., Snyder, K., Cantillon, C., Gaehde, S., Standring, P., Fiore, L., ... Gagnon, D.R. (2005) . + Hovstadius, B., Astrand, B., & Petersson, G. (2009) . + Hovstadius, B., Astrand, B., & Petersson, G. (2010) . + Kennerfalk, A., Ruigómez, A., Wallander, M.-A., Wilhelmsen, L., & Johansson, S. (2002) . + Masnoon, N., Shakib, S., Kalisch-Ellett, L., & Caughey, G. E. (2017) . + Narayan, S. W., & Nishtala, P. S. (2015) . + Nishtala, P. S., & Salahudeen, M. S. (2015) . + Park, H. Y., Ryu, H. N., Shim, M. K., Sohn, H. S., & Kwon, J. W. (2016) . + Veehof, L., Stewart, R., Haaijer-Ruskamp, F., & Jong, B. M. (2000) . + date_publication: '2021-07-12' + bug_reports: https://github.com/guiboucher/polypharmacy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polypharmacy + url_git: '' +polypoly: + version: 0.0.3 + title: Helper Functions for Orthogonal Polynomials + maintainer: Tristan Mahr + description: Tools for reshaping, plotting, and manipulating matrices of orthogonal + polynomials. + date_publication: '2022-10-20' + bug_reports: https://github.com/tjmahr/polypoly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polypoly + url_git: https://github.com/tjmahr/polypoly +polyqtlR: + version: 0.1.1 + title: QTL Analysis in Autopolyploid Bi-Parental F1 Populations + maintainer: Peter Bourke + description: |- + Quantitative trait loci (QTL) analysis and exploration of meiotic patterns in + autopolyploid bi-parental F1 populations. + For all ploidy levels, identity-by-descent (IBD) probabilities can be estimated. + Significance thresholds, exploring QTL allele effects and visualising results are provided. + For more background and to reference the package see . + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polyqtlR + url_git: '' +polyRAD: + version: 2.0.0 + title: |- + Genotype Calling with Uncertainty from Sequencing Data in + Polyploids and Diploids + maintainer: Lindsay V. Clark + description: |- + Read depth data from genotyping-by-sequencing (GBS) or restriction + site-associated DNA sequencing (RAD-seq) are imported and used to make Bayesian + probability estimates of genotypes in polyploids or diploids. The genotype + probabilities, posterior mean genotypes, or most probable genotypes can then + be exported for downstream analysis. 'polyRAD' is described by Clark et al. + (2019) , and the Hind/He statistic for marker + filtering is described by Clark et al. (2022) . + A variant calling pipeline for highly duplicated genomes is also included and + is described by Clark et al. (2020, Version 1) . + date_publication: '2022-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polyRAD + url_git: https://github.com/lvclark/polyRAD +polyreg: + version: 0.8.0 + title: Polynomial Regression + maintainer: Norm Matloff + description: Automate formation and evaluation of polynomial regression models. + The motivation for this package is described in 'Polynomial Regression As an Alternative + to Neural Nets' by Xi Cheng, Bohdan Khomtchouk, Norman Matloff, and Pete Mohanty + (). + date_publication: '2022-03-31' + bug_reports: https://github.com/matloff/polyreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polyreg + url_git: https://github.com/matloff/polyreg +polysat: + version: 1.7-7 + title: Tools for Polyploid Microsatellite Analysis + maintainer: Lindsay V. Clark + description: |- + A collection of tools to handle microsatellite data of + any ploidy (and samples of mixed ploidy) where allele copy number is not + known in partially heterozygous genotypes. It can import and export data in + ABI 'GeneMapper', 'Structure', 'ATetra', 'Tetrasat'/'Tetra', 'GenoDive', 'SPAGeDi', + 'POPDIST', 'STRand', and binary presence/absence formats. It can calculate + pairwise distances between individuals using a stepwise mutation model or + infinite alleles model, with or without taking ploidies and allele frequencies + into account. These distances can be used for the calculation of clonal + diversity statistics or used for further analysis in R. Allelic diversity + statistics and Polymorphic Information Content are also available. polysat can + assist the user in estimating the ploidy of samples, and it can estimate allele + frequencies in populations, calculate pairwise or global differentiation statistics + based on those frequencies, and export allele frequencies to 'SPAGeDi' and 'adegenet'. + Functions are also included for assigning alleles to isoloci in cases where one pair + of microsatellite primers amplifies alleles from two or more independently + segregating isoloci. polysat is described by Clark and Jasieniuk (2011) + and Clark and Schreier (2017) + . + date_publication: '2022-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polysat + url_git: https://github.com/lvclark/polysat/wiki +polySegratio: + version: 0.2-5 + title: |- + Simulate and Test Marker Dosage for Dominant Markers in + Autopolyploids + maintainer: Peter Baker + description: |- + Perform classic chi-squared tests and Ripol et al(1999) + binomial confidence interval approach for autopolyploid + dominant markers. Also, dominant markers may be generated + for families of offspring where either one or both of the + parents possess the marker. Missing values and + misclassified markers may be generated at random. + date_publication: '2018-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polySegratio + url_git: '' +polySegratioMM: + version: 0.6-4 + title: Bayesian Mixture Models for Marker Dosage in Autopolyploids + maintainer: Peter Baker + description: Fits Bayesian mixture models to estimate marker dosage for dominant + markers in autopolyploids using JAGS (1.0 or greater) as outlined in Baker et + al "Bayesian estimation of marker dosage in sugarcane and other autopolyploids" + (2010, ). May be used in conjunction with polySegratio + for simulation studies and comparison with standard methods. + date_publication: '2018-03-23' + bug_reports: https://github.com/petebaker/polysegratiomm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=polySegratioMM + url_git: https://github.com/petebaker/polysegratiomm +PolyTree: + version: 0.0.1 + title: Estimate Causal Polytree from Data + maintainer: Sourav Chatterjee + description: Given a data matrix with rows representing data vectors and columns + representing variables, produces a directed polytree for the underlying causal + structure. Based on the algorithm developed in Chatterjee and Vidyasagar (2022) + . The method is fully nonparametric, making no use of linearity + assumptions, and especially useful when the number of variables is large. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolyTree + url_git: '' +PolyTrend: + version: '1.2' + title: Trend Classification Algorithm + maintainer: Hristo Tomov + description: This algorithm classifies the trends into linear, quadratic, cubic, + concealed and no-trend types. The "concealed trends" are those trends that possess + quadratic or cubic forms, but the net change from the start of the time period + to the end of the time period hasn't been significant. The "no-trend" category + includes simple linear trends with statistically in-significant slope coefficient. + date_publication: '2016-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PolyTrend + url_git: '' +polywog: + version: 0.4-1 + title: Bootstrapped Basis Regression with Oracle Model Selection + maintainer: Brenton Kenkel + description: |- + Routines for flexible functional form estimation via basis + regression, with model selection via the adaptive LASSO or SCAD to prevent + overfitting. + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=polywog + url_git: https://github.com/brentonk/polywog-package +POMADE: + version: 0.2.0 + title: Power for Meta-Analysis of Dependent Effects + maintainer: Mikkel H. Vembye + description: Provides functions to compute and plot power levels, minimum detectable + effect sizes, and minimum required sample sizes for the test of the overall average + effect size in meta-analysis of dependent effect sizes. + date_publication: '2024-02-13' + bug_reports: https://github.com/MikkelVembye/POMADE/issues + url: https://mikkelvembye.github.io/POMADE/ + url_cran: https://CRAN.R-project.org/package=POMADE + url_git: '' +POMaSPU: + version: 1.0.0 + title: |- + Adaptive Association Tests for Multiple Phenotypes using + Proportional Odds Model (POM-aSPU) + maintainer: Junghi Kim + description: POM-aSPU test evaluates an association between an ordinal response + and multiple phenotypes, for details see Kim and Pan (2017) . + date_publication: '2017-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POMaSPU + url_git: '' +pomcheckr: + version: 0.1.1 + title: Graphical Check for Proportional Odds Assumption + maintainer: Melissa Wong + description: |- + Implements the method described at the UCLA Statistical + Consulting site + for checking if the proportional odds assumption holds for a + cumulative logit model. + date_publication: '2021-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pomcheckr + url_git: '' +pomdp: + version: 1.2.4 + title: |- + Infrastructure for Partially Observable Markov Decision + Processes (POMDP) + maintainer: Michael Hahsler + description: Provides the infrastructure to define and analyze the solutions of + Partially Observable Markov Decision Process (POMDP) models. Interfaces for various + exact and approximate solution algorithms are available including value iteration, + point-based value iteration and SARSOP. Smallwood and Sondik (1973) . + date_publication: '2024-12-05' + bug_reports: https://github.com/mhahsler/pomdp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pomdp + url_git: https://github.com/mhahsler/pomdp +pomdpSolve: + version: 1.0.4 + title: |- + Interface to 'pomdp-solve' for Partially Observable Markov + Decision Processes + maintainer: Michael Hahsler + description: Installs an updated version of 'pomdp-solve', a program to solve Partially + Observable Markov Decision Processes (POMDPs) using a variety of exact and approximate + value iteration algorithms. A convenient R infrastructure is provided in the separate + package pomdp. Kaelbling, Littman and Cassandra (1998) . + date_publication: '2023-08-31' + bug_reports: https://github.com/mhahsler/pomdpSolve/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pomdpSolve + url_git: https://github.com/mhahsler/pomdpSolve +Pomic: + version: 1.0.4 + title: Pattern Oriented Modelling Information Criterion + maintainer: Cyril Piou + description: Calculations of an information criterion are proposed to check the + quality of simulations results of Agent-based models (ABM/IBM) or other non-linear + rule-based models. The POMDEV measure (Pattern Oriented Modelling DEViance) is + based on the Kullback-Leibler divergence and likelihood theory. It basically indicates + the deviance of simulation results from field observations. Once POMDEV scores + and metropolis-hasting sampling on different model versions are effectuated, POMIC + scores (Pattern Oriented Modelling Information Criterion) can be calculated. This + method could be further developed to incorporate multiple patterns assessment. + Piou C, U Berger and V Grimm (2009) . + date_publication: '2018-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Pomic + url_git: '' +pomodoro: + version: 3.8.0 + title: Predictive Power of Linear and Tree Modeling + maintainer: Seyma Kalay + description: Runs generalized and multinominal logistic (GLM and MLM) models, as + well as random forest (RF), Bagging (BAG), and Boosting (BOOST). This package + prints out to predictive outcomes easy for the selected data and data splits. + date_publication: '2022-03-26' + bug_reports: https://github.com/seymakalay/pomodoro/issues + url: https://seymakalay.github.io/pomodoro/ + url_cran: https://CRAN.R-project.org/package=pomodoro + url_git: https://github.com/seymakalay/pomodoro +pomp: + version: '6.1' + title: Statistical Inference for Partially Observed Markov Processes + maintainer: Aaron A. King + description: Tools for data analysis with partially observed Markov process (POMP) + models (also known as stochastic dynamical systems, hidden Markov models, and + nonlinear, non-Gaussian, state-space models). The package provides facilities + for implementing POMP models, simulating them, and fitting them to time series + data by a variety of frequentist and Bayesian methods. It is also a versatile + platform for implementation of inference methods for general POMP models. + date_publication: '2025-01-08' + bug_reports: https://github.com/kingaa/pomp/issues/ + url: https://kingaa.github.io/pomp/ + url_cran: https://CRAN.R-project.org/package=pomp + url_git: '' +pompom: + version: 0.2.1 + title: Person-Oriented Method and Perturbation on the Model + maintainer: Xiao Yang + description: |- + An implementation of a hybrid method of person-oriented method and perturbation on the model. Pompom is the initials of the two methods. The hybrid method will provide a multivariate intraindividual variability metric (iRAM). The person-oriented method used in this package refers to uSEM (unified structural equation modeling, see Kim et al., 2007, Gates et al., 2010 and Gates et al., 2012 for details). Perturbation on the model was conducted according to impulse response analysis introduced in Lutkepohl (2007). + Kim, J., Zhu, W., Chang, L., Bentler, P. M., & Ernst, T. (2007) . + Gates, K. M., Molenaar, P. C. M., Hillary, F. G., Ram, N., & Rovine, M. J. (2010) . + Gates, K. M., & Molenaar, P. C. M. (2012) . + Lutkepohl, H. (2007, ISBN:3540262393). + date_publication: '2021-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pompom + url_git: '' +pompp: + version: 0.1.3 + title: Presence-Only for Marked Point Process + maintainer: Guido Alberti Moreira + description: |- + Inspired by Moreira and Gamerman (2022) , + this methodology expands the idea by including Marks in the point process. + Using efficient 'C++' code, the estimation is possible and made faster with + 'OpenMP' enabled computers. This package was + developed under the project PTDC/MAT-STA/28243/2017, supported by + Portuguese funds through the Portuguese Foundation for Science and + Technology (FCT). + date_publication: '2022-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pompp + url_git: '' +POMS: + version: 1.0.1 + title: Phylogenetic Organization of Metagenomic Signals + maintainer: Gavin Douglas + description: |- + Code to identify functional enrichments across diverse taxa + in phylogenetic tree, particularly where these taxa differ in + abundance across samples in a non-random pattern. The motivation for + this approach is to identify microbial functions encoded by diverse + taxa that are at higher abundance in certain samples compared to + others, which could indicate that such functions are broadly adaptive + under certain conditions. See 'GitHub' repository for tutorial and + examples: . Citation: Gavin M. Douglas, Molly G. Hayes, Morgan G. I. Langille, Elhanan Borenstein (2022) . + date_publication: '2022-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POMS + url_git: '' +poobly: + version: 0.1.1 + title: Poolability Tests in Panel Data + maintainer: Christos Adam + description: |- + Homogeneity tests of the coefficients in panel data. Currently, + only the Hsiao test for determining coefficient homogeneity between + the panel data individuals is implemented, as described in Hsiao + (2022), "Analysis of Panel Data" (). + date_publication: '2025-01-15' + bug_reports: https://github.com/cadam00/poobly/issues + url: https://cadam00.github.io/poobly/ + url_cran: https://CRAN.R-project.org/package=poobly + url_git: https://github.com/cadam00/poobly +pooh: + version: 0.3-2 + title: Partial Orders and Relations + maintainer: Charles J. Geyer + description: |- + Finds equivalence classes corresponding to a symmetric relation + or undirected graph. Finds total order consistent with partial order + or directed graph (so-called topological sort). + date_publication: '2017-03-27' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/pooh/ + url_cran: https://CRAN.R-project.org/package=pooh + url_git: '' +pool: + version: 1.0.4 + title: Object Pooling + maintainer: Hadley Wickham + description: |- + Enables the creation of object pools, which make it less + computationally expensive to fetch a new object. Currently the only + supported pooled objects are 'DBI' connections. + date_publication: '2024-10-07' + bug_reports: https://github.com/rstudio/pool/issues + url: https://rstudio.github.io/pool/ + url_cran: https://CRAN.R-project.org/package=pool + url_git: https://github.com/rstudio/pool +poolABC: + version: 1.0.0 + title: Approximate Bayesian Computation with Pooled Sequencing Data + maintainer: João Carvalho + description: |- + Provides functions to simulate Pool-seq data under models of + demographic formation and to import Pool-seq data from real populations. + Implements two ABC algorithms for performing parameter estimation and + model selection using Pool-seq data. Cross-validation can also be + performed to assess the accuracy of ABC estimates and model choice. + Carvalho et al., (2022) . + date_publication: '2023-08-08' + bug_reports: https://github.com/joao-mcarvalho/poolABC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poolABC + url_git: https://github.com/joao-mcarvalho/poolABC +PoolBal: + version: 0.1-0 + title: Balancing Central and Marginal Rejection of Pooled p-Values + maintainer: Chris Salahub + description: When using pooled p-values to adjust for multiple testing, there is + an inherent balance that must be struck between rejection based on weak evidence + spread among many tests and strong evidence in a few, explored in Salahub and + Olford (2023) . This package provides functionality to compute + marginal and central rejection levels and the centrality quotient for p-value + pooling functions and provides implementations of the chi-squared quantile pooled + p-value (described in Salahub and Oldford (2023)) and a proposal from Heard and + Rubin-Delanchy (2018) to control the quotient's value. + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoolBal + url_git: '' +PoolDilutionR: + version: 1.0.0 + title: |- + Calculate Gross Biogeochemical Flux Rates from Isotope Pool + Dilution Data + maintainer: Kendalynn A. Morris + description: |- + Pool dilution is a isotope tracer technique wherein a + biogeochemical pool is artifically enriched with its heavy isotopologue + and the gross productive and consumptive fluxes of that pool are + quantified by the change in pool size and isotopic composition over time. + This package calculates gross production and consumption rates from + closed-system isotopic pool dilution time series data. Pool size + concentrations and heavy isotope (e.g., 15N) content are measured over time + and the model optimizes production rate (P) and the first order rate + constant (k) by minimizing error in the model-predicted total pool size, + as well as the isotopic signature. The model optimizes rates by weighting + information against the signal:noise ratio of concentration and heavy- + isotope signatures using measurement precision as well as the magnitude of + change over time. The calculations used here are based on von Fischer and + Hedin (2002) with some modifications. + date_publication: '2023-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoolDilutionR + url_git: '' +PooledCohort: + version: 0.0.2 + title: |- + Predicted Risk for CVD using Pooled Cohort Equations, PREVENT + Equations, and Other Contemporary CVD Risk Calculators + maintainer: Byron Jaeger + description: |- + The 2017 American College of Cardiology and American Heart + Association blood pressure guideline recommends using 10-year predicted + atherosclerotic cardiovascular disease risk to guide the decision to + initiate or intensify antihypertensive medication. The guideline recommends + using the Pooled Cohort risk prediction equations to predict 10-year + atherosclerotic cardiovascular disease risk. This package implements the + original Pooled Cohort risk prediction equations and also incorporates + updated versions based on more contemporary data and statistical methods. + date_publication: '2024-03-09' + bug_reports: https://github.com/bcjaeger/PooledCohort/issues + url: https://bcjaeger.github.io/PooledCohort/ + url_cran: https://CRAN.R-project.org/package=PooledCohort + url_git: https://github.com/bcjaeger/PooledCohort +PooledMeanGroup: + version: '1.0' + title: Pooled Mean Group Estimation of Dynamic Heterogenous Panels + maintainer: Lech Kujawski + description: Calculates the pooled mean group (PMG) estimator for dynamic panel + data models, as described by Pesaran, Shin and Smith (1999) . + date_publication: '2017-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PooledMeanGroup + url_git: '' +pooledpeaks: + version: 1.1.0 + title: Genetic Analysis of Pooled Samples + maintainer: Kathleen Kuesters + description: |- + Analyzing genetic data obtained from pooled samples. + This package can read in Fragment Analysis output files, process the data, + and score peaks, as well as facilitate various analyses, including cluster + analysis, calculation of genetic distances and diversity indices, + as well as bootstrap resampling for statistical inference. Specifically + tailored to handle genetic data efficiently, researchers can explore + population structure, genetic differentiation, and genetic relatedness + among samples. We updated some functions from Covarrubias-Pazaran et al. + (2016) to allow for the use of new file formats + and referenced the following to write our genetic analysis functions: + Long et al. (2022) , Jost (2008) + , Nei (1973) + , Foulley et al. (2006) + , Chao et al. (2008) + . + date_publication: '2025-02-01' + bug_reports: https://github.com/kmkuesters/pooledpeaks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pooledpeaks + url_git: https://github.com/kmkuesters/pooledpeaks +poolfstat: + version: 3.0.0 + title: |- + Computing f-Statistics and Building Admixture Graphs Based on + Allele Count or Pool-Seq Read Count Data + maintainer: Mathieu Gautier + description: Functions for the computation of F-, f- and D-statistics (e.g., Fst, + hierarchical F-statistics, Patterson's F2, F3, F3*, F4 and D parameters) in population + genomics studies from allele count or Pool-Seq read count data and for the fitting, + building and visualization of admixture graphs. The package also includes several + utilities to manipulate Pool-Seq data stored in standard format (e.g., such as + 'vcf' files or 'rsync' files generated by the the 'PoPoolation' software) and + perform conversion to alternative format (as used in the 'BayPass' and 'SelEstim' + software). As of version 2.0, the package also includes utilities to manipulate + standard allele count data (e.g., stored in TreeMix, BayPass and SelEstim format). + date_publication: '2024-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poolfstat + url_git: '' +poolHelper: + version: 1.1.0 + title: Simulates Pooled Sequencing Genetic Data + maintainer: João Carvalho + description: |- + Simulates pooled sequencing data under a variety of conditions. + Also allows for the evaluation of the average absolute difference between allele frequencies + computed from genotypes and those computed from pooled data. + Carvalho et al., (2022) . + date_publication: '2023-06-29' + bug_reports: https://github.com/joao-mcarvalho/poolHelper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poolHelper + url_git: https://github.com/joao-mcarvalho/poolHelper +pooling: + version: 1.1.2 + title: Fit Poolwise Regression Models + maintainer: Dane R. Van Domelen + description: Functions for calculating power and fitting regression models in studies + where a biomarker is measured in "pooled" samples rather than for each individual. + Approaches for handling measurement error follow the framework of Schisterman + et al. (2010) . + date_publication: '2020-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pooling + url_git: '' +poolr: + version: 1.1-1 + title: Methods for Pooling P-Values from (Dependent) Tests + maintainer: Ozan Cinar + description: Functions for pooling/combining the results (i.e., p-values) from (dependent) + hypothesis tests. Included are Fisher's method, Stouffer's method, the inverse + chi-square method, the Bonferroni method, Tippett's method, and the binomial test. + Each method can be adjusted based on an estimate of the effective number of tests + or using empirically derived null distribution using pseudo replicates. For Fisher's, + Stouffer's, and the inverse chi-square method, direct generalizations based on + multivariate theory are also available (leading to Brown's method, Strube's method, + and the generalized inverse chi-square method). An introduction can be found in + Cinar and Viechtbauer (2022) . + date_publication: '2022-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poolr + url_git: '' +PoolTestR: + version: 0.2.0 + title: Prevalence and Regression for Pool-Tested (Group-Tested) Data + maintainer: Angus McLure + description: |- + An easy-to-use tool for working with presence/absence tests + on 'pooled' or 'grouped' samples. The primary application is for + estimating prevalence of a marker in a population based on the results + of tests on pooled specimens. This sampling method is often employed + in surveillance of rare conditions in humans or animals (e.g. + molecular xenomonitoring). The package was initially conceived as an + R-based alternative to the molecular xenomonitoring software, + 'PoolScreen' . However, + it goes further, allowing for estimates of prevalence to be adjusted + for hierarchical sampling frames, and perform flexible mixed-effect + regression analyses (McLure et al. Environmental Modelling and + Software. ). The package is + currently in early stages, however more features are planned or in the + works: e.g. adjustments for imperfect test specificity/sensitivity, + functions for helping with optimal experimental design, and functions + for spatial modelling. + date_publication: '2024-12-05' + bug_reports: https://github.com/AngusMcLure/PoolTestR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PoolTestR + url_git: https://github.com/AngusMcLure/PoolTestR +poolVIM: + version: 1.0.0 + title: |- + Gene-Based Association Tests using the Actual Impurity Reduction + (AIR) Variable Importance + maintainer: Stefano Nembrini + description: Gene-based association tests using the actual impurity reduction (AIR) + variable importance. The function aggregates AIR importance measures from a group + of SNPs or probes and outputs a p-value for each gene. The procedures builds upon + the method described in and will be published + soon. + date_publication: '2018-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poolVIM + url_git: '' +poorman: + version: 0.2.7 + title: A Poor Man's Dependency Free Recreation of 'dplyr' + maintainer: Nathan Eastwood + description: A replication of key functionality from 'dplyr' and the wider 'tidyverse' + using only 'base'. + date_publication: '2023-10-30' + bug_reports: https://github.com/nathaneastwood/poorman/issues + url: https://nathaneastwood.github.io/poorman/ + url_cran: https://CRAN.R-project.org/package=poorman + url_git: https://github.com/nathaneastwood/poorman +pop: + version: '0.1' + title: A Flexible Syntax for Population Dynamic Modelling + maintainer: Nick Golding + description: Population dynamic models underpin a range of analyses and applications + in ecology and epidemiology. The various approaches for analysing population dynamics + models (MPMs, IPMs, ODEs, POMPs, PVA) each require the model to be defined in + a different way. This makes it difficult to combine different modelling approaches + and data types to solve a given problem. 'pop' aims to provide a flexible and + easy to use common interface for constructing population dynamic models and enabling + to them to be fitted and analysed in lots of different ways. + date_publication: '2016-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pop + url_git: '' +pop.lion: + version: 1.0.1 + title: Models for Simulating Lion Populations + maintainer: Guillaume Chapron + description: Simulate the dynamic of lion populations using a specific Individual-Based + Model (IBM) compiled in C. + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pop.lion + url_git: '' +pop.wolf: + version: '1.0' + title: Models for Simulating Wolf Populations + maintainer: Guillaume Chapron + description: Simulate the dynamic of wolf populations using a specific Individual-Based + Model (IBM) compiled in C, see Chapron et al. (2016) . + date_publication: '2022-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pop.wolf + url_git: '' +popbayes: + version: 1.2.0 + title: Bayesian Model to Estimate Population Trends from Counts Series + maintainer: Nicolas Casajus + description: |- + Infers the trends of one or several animal populations over time + from series of counts. It does so by accounting for count precision + (provided or inferred based on expert knowledge, e.g. guesstimates), + smoothing the population rate of increase over time, and accounting for the + maximum demographic potential of species. Inference is carried out in a + Bayesian framework. This work is part of the FRB-CESAB working group + AfroBioDrivers + . + date_publication: '2023-06-15' + bug_reports: https://github.com/frbcesab/popbayes/issues + url: https://frbcesab.github.io/popbayes/ + url_cran: https://CRAN.R-project.org/package=popbayes + url_git: https://github.com/frbcesab/popbayes +popbio: + version: '2.8' + title: Construction and Analysis of Matrix Population Models + maintainer: Chris Stubben + description: Construct and analyze projection matrix models from a demography study + of marked individuals classified by age or stage. The package covers methods described + in Matrix Population Models by Caswell (2001) and Quantitative Conservation Biology + by Morris and Doak (2002). + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=popbio + url_git: '' +popdemo: + version: 1.3-1 + title: Demographic Modelling Using Projection Matrices + maintainer: Iain Stott + description: |- + Tools for modelling populations and demography using matrix projection models, + with deterministic and stochastic model implementations. Includes population projection, + indices of short- and long-term population size and growth, perturbation analysis, + convergence to stability or stationarity, and diagnostic and manipulation tools. + date_publication: '2021-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=popdemo + url_git: '' +PoPdesign: + version: 1.1.0 + title: Posterior Predictive (PoP) Design for Phase I Clinical Trials + maintainer: Xinying Fang + description: The primary goal of phase I clinical trials is to find the maximum + tolerated dose (MTD). To reach this objective, we introduce a new design for phase + I clinical trials, the posterior predictive (PoP) design. The PoP design is an + innovative model-assisted design that is as simply as the conventional algorithmic + designs as its decision rules can be pre-tabulated prior to the onset of trial, + but is of more flexibility of selecting diverse target toxicity rates and cohort + sizes. The PoP design has desirable properties, such as coherence and consistency. + Moreover, the PoP design provides better empirical performance than the BOIN and + Keyboard design with respect to high average probabilities of choosing the MTD + and slightly lower risk of treating patients at subtherapeutic or overly toxic + doses. + date_publication: '2024-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoPdesign + url_git: '' +PopED: + version: 0.7.0 + title: Population (and Individual) Optimal Experimental Design + maintainer: Andrew C. Hooker + description: |- + Optimal experimental designs for both population and individual + studies based on nonlinear mixed-effect models. Often this is based on a + computation of the Fisher Information Matrix. This package was developed + for pharmacometric problems, and examples and predefined models are available + for these types of systems. The methods are described in Nyberg et al. + (2012) , and Foracchia et al. (2004) + . + date_publication: '2024-10-07' + bug_reports: https://github.com/andrewhooker/PopED/issues + url: https://andrewhooker.github.io/PopED/ + url_cran: https://CRAN.R-project.org/package=PopED + url_git: https://github.com/andrewhooker/PopED +popEpi: + version: 0.4.13 + title: Functions for Epidemiological Analysis using Population Data + maintainer: Joonas Miettinen + description: |- + Enables computation of epidemiological statistics, including + those where counts or mortality rates of the reference population are + used. Currently supported: excess hazard models (Dickman, Sloggett, + Hills, and Hakulinen (2012) ), rates, mean + survival times, relative/net survival (in particular the Ederer II + (Ederer and Heise (1959)) and Pohar Perme (Pohar Perme, Stare, and + Esteve (2012) ) estimators), and + standardized incidence and mortality ratios, all of which can be + easily adjusted for by covariates such as age. Fast splitting and + aggregation of 'Lexis' objects (from package 'Epi') and other + computations achieved using 'data.table'. + date_publication: '2025-01-31' + bug_reports: https://github.com/FinnishCancerRegistry/popEpi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=popEpi + url_git: https://github.com/FinnishCancerRegistry/popEpi +PopGenHelpR: + version: 1.3.2 + title: Streamline Population Genomic and Genetic Analyses + maintainer: Keaka Farleigh + description: Estimate commonly used population genomic statistics and generate publication + quality figures. 'PopGenHelpR' uses vcf, 'geno' (012), and csv files to generate + output. + date_publication: '2024-08-02' + bug_reports: https://github.com/kfarleigh/PopGenHelpR/issues + url: https://kfarleigh.github.io/PopGenHelpR/ + url_cran: https://CRAN.R-project.org/package=PopGenHelpR + url_git: '' +popgenr: + version: '0.2' + title: |- + Accompaniment to Population Genetics with R: An Introduction for + Life Scientists + maintainer: Aki Jarl Laruson + description: 'Provides several data sets and functions to accompany the book "Population + Genetics with R: An Introduction for Life Scientists" (2021, ISBN:9780198829546).' + date_publication: '2021-02-25' + bug_reports: '' + url: https://global.oup.com/academic/product/population-genetics-with-r-9780198829546?cc=gb&lang=en# + url_cran: https://CRAN.R-project.org/package=popgenr + url_git: '' +PopGenReport: + version: '3.1' + title: |- + A Simple Framework to Analyse Population and Landscape Genetic + Data + maintainer: Bernd Gruber + description: |- + Provides beginner friendly framework to analyse population genetic + data. Based on 'adegenet' objects it uses 'knitr' to create comprehensive reports on spatial genetic data. + For detailed information how to use the package refer to the comprehensive + tutorials or visit . + date_publication: '2023-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PopGenReport + url_git: https://github.com/green-striped-gecko/PopGenReport +POPInf: + version: 1.0.0 + title: Assumption-Lean and Data-Adaptive Post-Prediction Inference + maintainer: Jiacheng Miao + description: Implementation of assumption-lean and data-adaptive post-prediction + inference (POPInf), for valid and efficient statistical inference based on data + predicted by machine learning. See Miao, Miao, Wu, Zhao, and Lu (2023) . + date_publication: '2024-02-20' + bug_reports: '' + url: https://arxiv.org/abs/2311.14220 + url_cran: https://CRAN.R-project.org/package=POPInf + url_git: https://github.com/qlu-lab/POPInf +popkin: + version: 1.3.23 + title: Estimate Kinship and FST under Arbitrary Population Structure + maintainer: Alejandro Ochoa + description: Provides functions to estimate the kinship matrix of individuals from + a large set of biallelic SNPs, and extract inbreeding coefficients and the generalized + FST (Wright's fixation index). Method described in Ochoa and Storey (2021) . + date_publication: '2023-01-07' + bug_reports: https://github.com/StoreyLab/popkin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=popkin + url_git: https://github.com/StoreyLab/popkin/ +popPCR: + version: 0.1.1.1 + title: |- + Classify Digital PCR Droplets by Fitting Fluorescence + Populations + maintainer: Joyce Emlyn Guiao + description: 'Estimates DNA target concentration by classifying digital PCR (polymerase + chain reaction) droplets as positive, negative, or rain, using Expectation-Maximization + Clustering. The fitting is accomplished using the ''EMMIXskew'' R package (v. + 1.0.3) by Kui Wang, Angus Ng, and Geoff McLachlan (2018) as based on their paper + "Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell + Sorting Data" .' + date_publication: '2021-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=popPCR + url_git: '' +poppr: + version: 2.9.6 + title: Genetic Analysis of Populations with Mixed Reproduction + maintainer: Zhian N. Kamvar + description: |- + Population genetic analyses for hierarchical analysis of partially + clonal populations built upon the architecture of the 'adegenet' package. + Originally described in Kamvar, Tabima, and Grünwald (2014) + with version 2.0 described in Kamvar, Brooks, and + Grünwald (2015) . + date_publication: '2024-03-15' + bug_reports: https://github.com/grunwaldlab/poppr/issues/ + url: https://grunwaldlab.github.io/poppr/ + url_cran: https://CRAN.R-project.org/package=poppr + url_git: https://github.com/grunwaldlab/poppr/ +popPyramid: + version: 0.1.1 + title: Population Pyramids + maintainer: Jorge L. C. Musaja + description: Functions that facilitate the elaboration of population pyramids. + date_publication: '2021-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=popPyramid + url_git: https://github.com/musajajorge/popPyramid +popReconstruct: + version: 1.0-6 + title: Reconstruct Human Populations of the Recent Past + maintainer: '"Mark C. Wheldon"' + description: 'Implements the Bayesian hierarchical model described by Wheldon, Raftery, + Clark and Gerland (see: ) for simultaneously + estimating age-specific population counts, fertility rates, mortality rates and + net international migration flows, at the national level.' + date_publication: '2019-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=popReconstruct + url_git: '' +popsom7: + version: 7.0.0 + title: A User-Friendly Implementation of Self-Organizing Maps + maintainer: Lutz Hamel + description: |- + Self-organizing maps with a number of distinguishing features: + (1) Automatic centroid detection and cluster visualization using starbursts, for more details see the paper "Improved Interpretability of the Unified Distance Matrix with Connected Components" by Hamel and Brown (2011) in . + (2) Two models of the data: (a) a self organizing map model, (b) a centroid based clustering model. + (3) A number of easily accessible quality metrics, Hamel (2016) . + date_publication: '2025-02-19' + bug_reports: https://github.com/lutzhamel/popsom7/issues + url: '' + url_cran: https://CRAN.R-project.org/package=popsom7 + url_git: https://github.com/lutzhamel/popsom7 +popstudy: + version: 1.0.1 + title: Applied Techniques to Demographic and Time Series Analysis + maintainer: Cesar Gamboa-Sanabria + description: |- + The use of overparameterization is proposed with combinatorial analysis to test a broader spectrum of possible ARIMA models. + In the selection of ARIMA models, the most traditional methods such as correlograms or others, do not usually cover many alternatives to define the number of coefficients to be estimated in the model, which represents an estimation method that is not the best. + The popstudy package contains several tools for statistical analysis in demography and time series based in Shryock research (Shryock et. al. (1980) ). + date_publication: '2023-10-17' + bug_reports: '' + url: https://www.cesargamboasanabria.com + url_cran: https://CRAN.R-project.org/package=popstudy + url_git: '' +poptrend: + version: 0.2.0 + title: |- + Estimate Smooth and Linear Trends from Population Count Survey + Data + maintainer: Jonas Knape + description: |- + Functions to estimate and plot smooth or linear population trends, or population indices, + from animal or plant count survey data. + date_publication: '2023-11-22' + bug_reports: https://github.com/jknape/poptrend/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poptrend + url_git: https://github.com/jknape/poptrend +PopulateR: + version: '1.13' + title: Create Data Frames for the Micro-Simulation of Human Populations + maintainer: Michelle Gosse + description: |- + Tools for constructing detailed synthetic human populations + from frequency tables. Add ages based on age groups and sex, create households, add + students to education facilities, create employers, add employers to employees, and + create interpersonal networks. + date_publication: '2025-01-29' + bug_reports: https://github.com/programgirl/PopulateR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PopulateR + url_git: https://github.com/programgirl/PopulateR +population: + version: '0.3' + title: Models for Simulating Populations + maintainer: Guillaume Chapron + description: Run population simulations using an Individual-Based Model (IBM) compiled + in C. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=population + url_git: '' +PopulationGrowthR: + version: 0.1.1 + title: Linear Population Growth Scenarios + maintainer: Biman Chakraborty + description: Fit linear splines to species time series to detect population growth + scenarios based on Hyndman, R J and Mesgaran, M B and Cousens, R D (2015) . + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PopulationGrowthR + url_git: '' +populationPDXdesign: + version: 1.0.3 + title: Designing Population PDX Studies + maintainer: Maria Luisa Guerriero + description: |- + Run simulations to assess the impact of various designs features + and the underlying biological behaviour on the outcome of a Patient Derived + Xenograft (PDX) population study. This project can either be deployed to a + server as a 'shiny' app or installed locally as a package and run the app + using the command 'populationPDXdesignApp()'. + date_publication: '2018-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=populationPDXdesign + url_git: '' +populR: + version: 0.2.1 + title: Population Downscaling Using Areal Interpolation + maintainer: Marios Batsaris + description: |- + Given a + set of source zone polygons such as + census tracts or city blocks alongside with population counts and a + target zone of incogruent yet superimposed polygon features (such as + individual buildings) populR transforms population counts from the + former to the latter using Areal Interpolation methods. + date_publication: '2023-03-13' + bug_reports: https://github.com/mbatsaris/populR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=populR + url_git: https://github.com/mbatsaris/populR/ +poputils: + version: 0.3.3 + title: Demographic Analysis and Data Manipulation + maintainer: John Bryant + description: |- + Perform tasks commonly encountered when + preparing and analysing demographic data. + Some functions are intended for end users, and + others for developers. Includes functions for + working with life tables. + date_publication: '2024-09-14' + bug_reports: https://github.com/bayesiandemography/poputils/issues + url: https://bayesiandemography.github.io/poputils/ + url_cran: https://CRAN.R-project.org/package=poputils + url_git: https://github.com/bayesiandemography/poputils +PopVar: + version: 1.3.2 + title: |- + Genomic Breeding Tools: Genetic Variance Prediction and + Cross-Validation + maintainer: Jeffrey Neyhart + description: |- + The main attribute of 'PopVar' is the prediction of genetic variance in bi-parental populations, + from which the package derives its name. 'PopVar' contains a set of functions that use phenotypic and genotypic + data from a set of candidate parents to 1) predict the mean, genetic variance, and superior progeny value of all, + or a defined set of pairwise bi-parental crosses, and 2) perform cross-validation to estimate genome-wide prediction + accuracy of multiple statistical models. More details are available in Mohammadi, Tiede, and Smith (2015, ). + A dataset 'think_barley.rda' is included for reference and examples. + date_publication: '2024-10-20' + bug_reports: https://github.com/UMN-BarleyOatSilphium/PopVar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PopVar + url_git: https://github.com/UMN-BarleyOatSilphium/PopVar +porridge: + version: 0.3.3 + title: Ridge-Type Penalized Estimation of a Potpourri of Models + maintainer: Wessel N. van Wieringen + description: The name of the package is derived from the French, 'pour' ridge, and + provides functionality for ridge-type estimation of a potpourri of models. Currently, + this estimation concerns that of various Gaussian graphical models from different + study designs. Among others it considers the regular Gaussian graphical model + and a mixture of such models. The porridge-package implements the estimation of + the former either from i) data with replicated observations by penalized loglikelihood + maximization using the regular ridge penalty on the parameters (van Wieringen, + Chen, 2021) or ii) from non-replicated data by means of either a ridge estimator + with multiple shrinkage targets (as presented in van Wieringen et al. 2020, ) + or the generalized ridge estimator that allows for both the inclusion of quantitative + and qualitative prior information on the precision matrix via element-wise penalization + and shrinkage (van Wieringen, 2019, ). Additionally, + the porridge-package facilitates the ridge penalized estimation of a mixture of + Gaussian graphical models (Aflakparast et al., 2018). On another note, the package + also includes functionality for ridge-type estimation of the generalized linear + model (as presented in van Wieringen, Binder, 2022, ). + date_publication: '2024-02-21' + bug_reports: '' + url: https://www.math.vu.nl/~wvanwie/ + url_cran: https://CRAN.R-project.org/package=porridge + url_git: '' +port4me: + version: 0.7.1 + title: Get the Same, Personal, Free 'TCP' Port over and over + maintainer: Henrik Bengtsson + description: An R implementation of the cross-platform, language-independent "port4me" + algorithm (), which (1) finds a free + Transmission Control Protocol ('TCP') port in [1024,65535] that the user can open, + (2) is designed to work in multi-user environments, (3), gives different users, + different ports, (4) gives the user the same port over time with high probability, + (5) gives different ports for different software tools, and (6) requires no configuration. + date_publication: '2024-03-01' + bug_reports: https://github.com/HenrikBengtsson/port4me/issues + url: '' + url_cran: https://CRAN.R-project.org/package=port4me + url_git: https://github.com/HenrikBengtsson/port4me +PortalHacienda: + version: 0.1.7 + title: Acceder Con R a Los Datos Del Portal De Hacienda + maintainer: Fernando Garcia Diaz + description: |- + Obtener listado de datos, acceder y extender series del Portal de + Datos de Hacienda.Las proyecciones se realizan con 'forecast', + Hyndman RJ, Khandakar Y (2008) . + Search, download and forecast time-series from the Ministry of Economy + of Argentina. Forecasts are built with the 'forecast' package, + Hyndman RJ, Khandakar Y (2008) . + date_publication: '2023-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PortalHacienda + url_git: https://github.com/fmgarciadiaz/PortalHacienda-CRAN +portalr: + version: 0.4.3 + title: Create Useful Summaries of the Portal Data + maintainer: Glenda M. Yenni + description: |- + Download and generate summaries for the rodent, + plant, ant, and weather data from the Portal Project. Portal is a + long-term (and ongoing) experimental monitoring site in the Chihuahuan + desert. The raw data files can be found at + . + date_publication: '2024-09-23' + bug_reports: https://github.com/weecology/portalr/issues + url: https://weecology.github.io/portalr/ + url_cran: https://CRAN.R-project.org/package=portalr + url_git: https://github.com/weecology/portalr +portes: + version: '6.0' + title: Portmanteau Tests for Time Series Models + maintainer: Esam Mahdi + description: Contains common univariate and multivariate portmanteau test statistics + for time series models. These tests are based on using asymptotic distributions + such as chi-square distribution and based on using the Monte Carlo significance + tests. Also, it can be used to simulate from univariate and multivariate seasonal + time series models. + date_publication: '2023-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=portes + url_git: '' +portfolio: + version: 0.5-3 + title: Analysing Equity Portfolios + maintainer: Daniel Gerlanc + description: |- + Classes for analysing and implementing equity portfolios, + including routines for generating tradelists and calculating + exposures to user-specified risk factors. + date_publication: '2024-08-24' + bug_reports: https://github.com/dgerlanc/portfolio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=portfolio + url_git: https://github.com/dgerlanc/portfolio +portfolio.optimization: + version: 1.0-0 + title: Contemporary Portfolio Optimization + maintainer: Ronald Hochreiter + description: Simplify your portfolio optimization process by applying a contemporary + modeling way to model and solve your portfolio problems. While most approaches + and packages are rather complicated this one tries to simplify things and is agnostic + regarding risk measures as well as optimization solvers. Some of the methods implemented + are described by Konno and Yamazaki (1991) , Rockafellar + and Uryasev (2001) and Markowitz (1952) . + date_publication: '2018-08-24' + bug_reports: '' + url: http://www.finance-r.com/ + url_cran: https://CRAN.R-project.org/package=portfolio.optimization + url_git: '' +PortfolioAnalytics: + version: 2.1.0 + title: |- + Portfolio Analysis, Including Numerical Methods for Optimization + of Portfolios + maintainer: Brian G. Peterson + description: Portfolio optimization and analysis routines and graphics. + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PortfolioAnalytics + url_git: https://github.com/braverock/PortfolioAnalytics +portfolioBacktest: + version: 0.4.1 + title: Automated Backtesting of Portfolios over Multiple Datasets + maintainer: Daniel P. Palomar + description: |- + Automated backtesting of multiple portfolios over multiple + datasets of stock prices in a rolling-window fashion. Intended for + researchers and practitioners to backtest a set of different portfolios, + as well as by a course instructor to assess the students in their portfolio + design in a fully automated and convenient manner, with results conveniently + formatted in tables and plots. Each portfolio design is easily defined as a + function that takes as input a window of the stock prices and outputs the + portfolio weights. Multiple portfolios can be easily specified as a list + of functions or as files in a folder. Multiple datasets can be conveniently + extracted randomly from different markets, different time periods, and + different subsets of the stock universe. The results can be later assessed + and ranked with tables based on a number of performance criteria (e.g., + expected return, volatility, Sharpe ratio, drawdown, turnover rate, return + on investment, computational time, etc.), as well as plotted in a number of + ways with nice barplots and boxplots. + date_publication: '2022-04-22' + bug_reports: https://github.com/dppalomar/portfolioBacktest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=portfolioBacktest + url_git: https://github.com/dppalomar/portfolioBacktest +PortfolioOptim: + version: 1.1.1 + title: Small/Large Sample Portfolio Optimization + maintainer: Andrzej Palczewski + description: Two functions for financial portfolio optimization by linear programming + are provided. One function implements Benders decomposition algorithm and can + be used for very large data sets. The other, applicable for moderate sample sizes, + finds optimal portfolio which has the smallest distance to a given benchmark portfolio. + date_publication: '2019-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PortfolioOptim + url_git: '' +portion: + version: 0.1.0 + title: Extracting a Data Portion + maintainer: Lennart Oelschläger + description: |- + Provides a simple method to extract portions of a vector, matrix, or data.frame. + The relative portion size and the way the portion is selected can be chosen. + date_publication: '2023-10-31' + bug_reports: https://github.com/loelschlaeger/portion/issues + url: '' + url_cran: https://CRAN.R-project.org/package=portion + url_git: https://github.com/loelschlaeger/portion +portn: + version: 1.0.0 + title: Portfolio Analysis for Nature + maintainer: Seong Yun + description: |- + The functions are designed to find the efficient mean-variance frontier or + portfolio weights for static portfolio (called Markowitz portfolio) analysis in resource + economics or nature conservation. Using the nonlinear programming solver ('Rsolnp'), + this package deals with the quadratic minimization of the variance-covariances without + shorting (i.e., non-negative portfolio weights) studied in Ando and Mallory (2012) + . See the examples, testing versions, and more details from: + . + date_publication: '2023-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=portn + url_git: https://github.com/ysd2004/portn +PortRisk: + version: 1.1.0 + title: Portfolio Risk Analysis + maintainer: Sourish Das + description: Risk Attribution of a portfolio with Volatility Risk Analysis. + date_publication: '2015-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PortRisk + url_git: '' +portsort: + version: 0.1.0 + title: Factor-Based Portfolio Sorts + maintainer: Alex Dickerson + description: |- + Designed to aid both academic researchers and asset managers in conducting factor based portfolio sorts. + Provides functionality to sort assets into portfolios for up to three factors via a conditional or unconditional sorting procedure. + date_publication: '2018-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=portsort + url_git: '' +portvine: + version: 1.0.3 + title: Vine Based (Un)Conditional Portfolio Risk Measure Estimation + maintainer: Emanuel Sommer + description: |- + Following Sommer (2022) + portfolio level risk estimates (e.g. Value at Risk, Expected + Shortfall) are estimated by modeling each asset univariately by an + ARMA-GARCH model and then their cross dependence via a Vine Copula + model in a rolling window fashion. One can even condition on + variables/time series at certain quantile levels to stress test the + risk measure estimates. + date_publication: '2024-01-18' + bug_reports: https://github.com/EmanuelSommer/portvine/issues + url: https://emanuelsommer.github.io/portvine/ + url_cran: https://CRAN.R-project.org/package=portvine + url_git: https://github.com/EmanuelSommer/portvine +poset: + version: 1.0.0 + title: Analysis of Partially Ordered Data + maintainer: Lu Mao + description: |- + Win ratio approach to partially ordered data, such as multivariate ordinal + responses under product (consensus) or prioritized order. Two-sample tests and multiplicative + regression models are implemented (Mao, 2024, under revision). + date_publication: '2024-06-19' + bug_reports: '' + url: https://sites.google.com/view/lmaowisc/ + url_cran: https://CRAN.R-project.org/package=poset + url_git: '' +POSetR: + version: 1.1.4 + title: Partially Ordered Sets in R + maintainer: Alberto Arcagni + description: Provides a set of basic tools for generating, analyzing, summarizing + and visualizing finite partially ordered sets. In particular, it implements flexible + and very efficient algorithms for the extraction of linear extensions and for + the computation of mutual ranking probabilities and other user-defined functionals, + over them. The package is meant as a computationally efficient "engine", for the + implementation of data analysis procedures, on systems of multidimensional ordinal + indicators and partially ordered data, in the spirit of Fattore, M. (2016) "Partially + ordered sets and the measurement of multidimensional ordinal deprivation", Social + Indicators Research , and Fattore M. and Arcagni, + A. (2018) "A reduced posetic approach to the measurement of multidimensional ordinal + deprivation", Social Indicators Research . + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POSetR + url_git: '' +PoSI: + version: '1.1' + title: Valid Post-Selection Inference for Linear LS Regression + maintainer: Wan Zhang + description: |2- + + In linear LS regression, calculate for a given design matrix + the multiplier K of coefficient standard errors such that the + confidence intervals [b - K*SE(b), b + K*SE(b)] have a + guaranteed coverage probability for all coefficient estimates + b in any submodels after performing arbitrary model selection. + date_publication: '2020-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoSI + url_git: '' +PoSIAdjRSquared: + version: 0.0.0.1 + title: Post-Selection Inference for Adjusted R Squared + maintainer: Sarah Pirenne + description: Conduct post-selection inference for regression coefficients in linear + models after they have been selected by adjusted R squared. The p-values and confidence + intervals are valid after model selection with the same data. This allows the + user to use all data for both model selection and inference without losing control + over the type I error rate. The provided tests are more powerful than data splitting, + which bases inference on less data since it discards all information used for + selection. + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoSIAdjRSquared + url_git: '' +posologyr: + version: 1.2.8 + title: Individual Dose Optimization using Population Pharmacokinetics + maintainer: Cyril Leven + description: |- + Personalize drug regimens using individual pharmacokinetic (PK) and + pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic + drug monitoring (TDM) data with a population model, 'posologyr' offers + accurate posterior estimates and helps compute optimal individualized dosing + regimens. The empirical Bayes estimates are computed following the method + described by Kang et al. (2012) . + date_publication: '2025-02-04' + bug_reports: https://github.com/levenc/posologyr/issues + url: https://levenc.github.io/posologyr/ + url_cran: https://CRAN.R-project.org/package=posologyr + url_git: https://github.com/levenc/posologyr +PosRatioDist: + version: 1.2.1 + title: |- + Quotient of Random Variables Conditioned to the Positive + Quadrant + maintainer: Yuancheng Si + description: Computes the exact probability density function of X/Y conditioned + on positive quadrant for series of bivariate distributions,for more details see + Nadarajah,Song and Si (2019) . + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PosRatioDist + url_git: '' +POSSA: + version: 0.6.4 + title: Power Simulation for Sequential Analyses and Multiple Hypotheses + maintainer: Gáspár Lukács + description: |- + Calculates, via simulation, power and appropriate stopping + alpha boundaries (and/or futility bounds) for sequential analyses (i.e., + group sequential design) as well as for multiple hypotheses (multiple tests + included in an analysis), given any specified global error rate. This enables + the sequential use of practically any significance test, as long as the + underlying data can be simulated in advance to a reasonable approximation. + Lukács (2022) . + date_publication: '2023-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POSSA + url_git: https://github.com/gasparl/possa +postcards: + version: 0.2.3 + title: Create Beautiful, Simple Personal Websites + maintainer: Sean Kross + description: |- + A collection of R Markdown templates for creating simple and easy + to personalize single page websites. + date_publication: '2022-01-07' + bug_reports: https://github.com/seankross/postcards/issues + url: '' + url_cran: https://CRAN.R-project.org/package=postcards + url_git: https://github.com/seankross/postcards +PostcodesioR: + version: 0.3.1 + title: API Wrapper Around 'Postcodes.io' + maintainer: Eryk Walczak + description: |- + Free UK geocoding using data from Office for National Statistics. + It is using several functions to get information about post codes, outward + codes, reverse geocoding, nearest post codes/outward codes, validation, or + randomly generate a post code. API wrapper around . + date_publication: '2021-12-01' + bug_reports: https://github.com/ropensci/PostcodesioR/issues + url: https://docs.ropensci.org/PostcodesioR/ + url_cran: https://CRAN.R-project.org/package=PostcodesioR + url_git: '' +postdoc: + version: 1.4.0 + title: Minimal and Uncluttered Package Documentation + maintainer: Jeroen Ooms + description: |- + Generates simple and beautiful one-page HTML reference manuals + with package documentation. Math rendering and syntax highlighting are done + server-side in R such that no JavaScript libraries are needed in the + browser, which makes the documentation portable and fast to load. + date_publication: '2024-09-30' + bug_reports: https://github.com/ropensci/postdoc/issues + url: https://ropensci.r-universe.dev/postdochttps://docs.ropensci.org/postdoc/ + url_cran: https://CRAN.R-project.org/package=postdoc + url_git: '' +posterdown: + version: '1.0' + title: Generate PDF Conference Posters Using R Markdown + maintainer: Brent Thorne + description: |- + Use 'rmarkdown' and 'pagedown' to generate + HTML and PDF conference posters. + date_publication: '2019-10-09' + bug_reports: https://github.com/brentthorne/posterdown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=posterdown + url_git: https://github.com/brentthorne/posterdown +posterior: + version: 1.6.1 + title: Tools for Working with Posterior Distributions + maintainer: Paul-Christian Bürkner + description: |- + Provides useful tools for both users and developers of packages + for fitting Bayesian models or working with output from Bayesian models. + The primary goals of the package are to: + (a) Efficiently convert between many different useful formats of + draws (samples) from posterior or prior distributions. + (b) Provide consistent methods for operations commonly performed on draws, + for example, subsetting, binding, or mutating draws. + (c) Provide various summaries of draws in convenient formats. + (d) Provide lightweight implementations of state of the art posterior + inference diagnostics. References: Vehtari et al. (2021) + . + date_publication: '2025-02-27' + bug_reports: https://github.com/stan-dev/posterior/issues + url: https://mc-stan.org/posterior/ + url_cran: https://CRAN.R-project.org/package=posterior + url_git: '' +PosteriorBootstrap: + version: 0.1.2 + title: Non-Parametric Sampling with Parallel Monte Carlo + maintainer: James Robinson + description: |- + An implementation of a non-parametric statistical model using a + parallelised Monte Carlo sampling scheme. The method implemented in this + package allows non-parametric inference to be regularized for small sample + sizes, while also being more accurate than approximations such as + variational Bayes. The concentration parameter is an effective sample size + parameter, determining the faith we have in the model versus the data. When + the concentration is low, the samples are close to the exact Bayesian + logistic regression method; when the concentration is high, the samples are + close to the simplified variational Bayes logistic regression. The method is + described in full in the paper Lyddon, Walker, and Holmes (2018), + "Nonparametric learning from Bayesian models with randomized objective + functions" . + date_publication: '2023-03-12' + bug_reports: https://github.com/alan-turing-institute/PosteriorBootstrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PosteriorBootstrap + url_git: https://github.com/alan-turing-institute/PosteriorBootstrap/ +postGGIR: + version: 2.4.0.2 + title: Data Processing after Running 'GGIR' for Accelerometer Data + maintainer: Wei Guo + description: Generate all necessary R/Rmd/shell files for data processing after + running 'GGIR' (v2.4.0) for accelerometer data. In part 1, all csv files in the + GGIR output directory were read, transformed and then merged. In part 2, the GGIR + output files were checked and summarized in one excel sheet. In part 3, the merged + data was cleaned according to the number of valid hours on each night and the + number of valid days for each subject. In part 4, the cleaned activity data was + imputed by the average Euclidean norm minus one (ENMO) over all the valid days + for each subject. Finally, a comprehensive report of data processing was created + using Rmarkdown, and the report includes few exploratory plots and multiple commonly + used features extracted from minute level actigraphy data. + date_publication: '2022-01-06' + bug_reports: https://github.com/dora201888/postGGIR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=postGGIR + url_git: https://github.com/dora201888/postGGIR +postHoc: + version: 0.1.3 + title: Tools for Post-Hoc Analysis + maintainer: Rodrigo Labouriau + description: |- + Implements a range of facilities for post-hoc analysis and + summarizing linear models, generalized linear models and + generalized linear mixed models, including grouping and clustering + via pairwise comparisons using graph representations and efficient + algorithms for finding maximal cliques of a graph. + Includes also non-parametric toos for post-hoc analysis. + It has S3 methods for printing summarizing, and producing plots, + line and barplots suitable for post-hoc analyses. + date_publication: '2020-06-02' + bug_reports: '' + url: https://tildeweb.au.dk/au33031/astatlab/software/posthoc + url_cran: https://CRAN.R-project.org/package=postHoc + url_git: '' +postinfectious: + version: 0.1.0 + title: |- + Estimating the Incubation Period Distribution of Post-Infectious + Syndrome + maintainer: Char Leung + description: Functions to estimate the incubation period distribution of post-infectious + syndrome which is defined as the time between the symptom onset of the antecedent + infection and that of the post-infectious syndrome. + date_publication: '2019-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=postinfectious + url_git: '' +postlightmercury: + version: '1.2' + title: Parses Web Pages using Postlight Mercury + maintainer: Mikkel Freltoft Krogsholm + description: |- + This is a wrapper for the Mercury Parser API. The Mercury Parser is + a single API endpoint that takes a URL and gives you back the content reliably + and easily. + With just one API request, Mercury takes any web article and returns + only the relevant content — headline, author, body text, relevant images and + more — free from any clutter. It’s reliable, easy-to-use and free. + See the webpage here: . + date_publication: '2017-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=postlightmercury + url_git: '' +postlogic: + version: 0.1.0.1 + title: Infix and Postfix Logic Operators + maintainer: Andrew Redd + description: |- + Provides adds postfix and infix logic operators for + if, then, unless, and otherwise. + date_publication: '2019-12-18' + bug_reports: https://github.com/RDocTaskForce/postlogic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=postlogic + url_git: https://github.com/RDocTaskForce/postlogic +POSTm: + version: '1.4' + title: |- + Phylogeny-Guided OTU-Specific Association Test for Microbiome + Data + maintainer: Shannon T. Holloway + description: |- + Implements the Phylogeny-Guided Microbiome OTU-Specific Association + Test method, which boosts the testing power by adaptively borrowing + information from phylogenetically close OTUs (operational taxonomic units) + of the target OTU. This method + is built on a kernel machine regression framework and allows for flexible + modeling of complex microbiome effects, adjustments for covariates, and + can accommodate both continuous and binary outcomes. + date_publication: '2024-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POSTm + url_git: '' +postpack: + version: 0.5.4 + title: |- + Utilities for Processing Posterior Samples Stored in + 'mcmc.lists' + maintainer: Ben Staton + description: |- + The aim of 'postpack' is to provide the infrastructure for a standardized workflow for 'mcmc.list' objects. + These objects can be used to store output from models fitted with Bayesian inference using + 'JAGS', 'WinBUGS', 'OpenBUGS', 'NIMBLE', 'Stan', or even custom MCMC algorithms. Although the 'coda' R package provides + some methods for these objects, it is somewhat limited in easily performing post-processing tasks for + specific nodes. Models are ever increasing in their complexity and the number of tracked nodes, and oftentimes + a user may wish to summarize/diagnose sampling behavior for only a small subset of nodes at a time + for a particular question or figure. Thus, many 'postpack' functions support performing tasks on a + subset of nodes, where the subset is specified with regular expressions. The functions in 'postpack' + streamline the extraction, summarization, and diagnostics of specific monitored nodes after model fitting. + Further, because there is rarely only ever one model under consideration, 'postpack' scales efficiently + to perform the same tasks on output from multiple models simultaneously, facilitating rapid assessment + of model sensitivity to changes in assumptions. + date_publication: '2022-12-21' + bug_reports: https://github.com/bstaton1/postpack/issues + url: https://bstaton1.github.io/postpack/ + url_cran: https://CRAN.R-project.org/package=postpack + url_git: '' +POT: + version: 1.1-11 + title: Generalized Pareto Distribution and Peaks Over Threshold + maintainer: Christophe Dutang + description: |- + Some functions useful to perform a Peak Over Threshold + analysis in univariate and bivariate cases, see Beirlant et al. (2004) + . A user guide is available in the vignette. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=POT + url_git: https://pot.r-forge.r-project.org/ +potential: + version: 0.2.0 + title: Implementation of the Potential Model + maintainer: Timothée Giraud + description: |- + Provides functions to compute the potential model as defined by + Stewart (1941) . Several options are available + to customize the model, such as the possibility to fine-tune the distance + friction functions or to use custom distance matrices. Some computations are + parallelized to improve their efficiency. + date_publication: '2022-07-05' + bug_reports: https://github.com/riatelab/potential/issues + url: '' + url_cran: https://CRAN.R-project.org/package=potential + url_git: https://github.com/riatelab/potential +poth: + version: 0.2-0 + title: Precision of Treatment Hierarchy (POTH) + maintainer: Augustine Wigle + description: Calculate POTH for treatment hierarchies from frequentist and Bayesian + network meta-analysis. POTH quantifies the certainty in a treatment hierarchy. + Subset POTH, POTH residuals, and cumulative POTH can also be calculated to improve + interpretation of treatment hierarchies. + date_publication: '2024-11-01' + bug_reports: https://github.com/augustinewigle/poth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=poth + url_git: https://github.com/augustinewigle/poth +potions: + version: 0.2.0 + title: Easy Options Management + maintainer: Martin Westgate + description: |- + Store and retrieve data from options() using syntax derived from + the 'here' package. 'potions' makes it straightforward to update and + retrieve options, either in the workspace or during package development, + without overwriting global options. + date_publication: '2023-08-23' + bug_reports: https://github.com/AtlasOfLivingAustralia/potions/issues + url: https://potions.ala.org.au + url_cran: https://CRAN.R-project.org/package=potions + url_git: '' +potools: + version: 0.2.4 + title: Tools for Internationalization and Portability in R Packages + maintainer: Michael Chirico + description: |- + Translating messages in R packages is managed using the po + top-level directory and the 'gettext' program. This package provides + some helper functions for building this support in R packages, e.g. + common validation & I/O tasks. + date_publication: '2023-10-30' + bug_reports: https://github.com/MichaelChirico/potools/issues + url: https://michaelchirico.github.io/potools/ + url_cran: https://CRAN.R-project.org/package=potools + url_git: https://github.com/MichaelChirico/potools +potts: + version: 0.5-11 + title: Markov Chain Monte Carlo for Potts Models + maintainer: Charles J. Geyer + description: |- + Do Markov chain Monte Carlo (MCMC) simulation of Potts models + (Potts, 1952, ), + which are the multi-color generalization of Ising models + (so, as as special case, also simulates Ising models). + Use the Swendsen-Wang algorithm (Swendsen and Wang, 1987, + ) so MCMC is fast. + Do maximum composite likelihood estimation of parameters + (Besag, 1975, , + Lindsay, 1988, ). + date_publication: '2022-08-12' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/mcmc/ + url_cran: https://CRAN.R-project.org/package=potts + url_git: '' +PottsUtils: + version: 0.3-3.1 + title: Utility Functions of the Potts Models + maintainer: Dai Feng + description: |- + There are three sets of functions. The first produces + basic properties of a graph and generates samples from + multinomial distributions to facilitate the simulation + functions (they maybe used for other purposes as well). + The second provides various simulation functions for a + Potts model in Potts, R. B. (1952) + . + The third currently includes only one function which + computes the normalizing constant of a Potts model + based on simulation results. + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PottsUtils + url_git: '' +pould: + version: 1.0.1 + title: Phased or Unphased Linkage Disequilibrium + maintainer: Steven Mack + description: Computes the D', Wn, and conditional asymmetric linkage disequilibrium + (ALD) measures for pairs of genetic loci. Performs these linkage disequilibrium + (LD) calculations on phased genotype data recorded using Genotype List (GL) String + or columnar formats. Alternatively, generates expectation-maximization (EM) estimated + haplotypes from phased data, or performs LD calculations on EM estimated haplotypes. + Performs sign tests comparing LD values for phased and unphased datasets, and + generates heat-maps for each LD measure. Described by Osoegawa et al. (2019a) + , and Osoegawa et. al. (2019b) . + date_publication: '2020-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pould + url_git: '' +POUMM: + version: 2.1.7 + title: The Phylogenetic Ornstein-Uhlenbeck Mixed Model + maintainer: Venelin Mitov + description: |- + The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to + estimate the phylogenetic heritability of continuous traits, to test + hypotheses of neutral evolution versus stabilizing selection, to quantify + the strength of stabilizing selection, to estimate measurement error and to + make predictions about the evolution of a phenotype and phenotypic variation + in a population. The package implements combined maximum likelihood and + Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed + Model, fast parallel likelihood calculation, maximum likelihood + inference of the genotypic values at the tips, functions for summarizing and + plotting traces and posterior samples, functions for simulation of a univariate + continuous trait evolution model along a phylogenetic tree. So far, the + package has been used for estimating the heritability of quantitative traits + in macroevolutionary and epidemiological studies, see e.g. + Bertels et al. (2017) and + Mitov and Stadler (2018) . The algorithm for + parallel POUMM likelihood calculation has been published in + Mitov and Stadler (2019) . + date_publication: '2020-10-27' + bug_reports: https://github.com/venelin/POUMM/issues + url: https://venelin.github.io/POUMM/index.html + url_cran: https://CRAN.R-project.org/package=POUMM + url_git: https://github.com/venelin/POUMM +POV: + version: 0.1.4 + title: Partition of Variation Variance Component Analysis Method + maintainer: Paul Deen + description: |- + An implementation of the Partition Of variation (POV) method as + developed by Dr. Thomas A Little in + 1993 for the analysis of semiconductor data for hard drive manufacturing. + POV is based on sequential sum of squares and is an exact method that + explains all observed variation. It quantitates both the between and within + factor variation effects and can quantitate the influence of both continuous + and categorical factors. + date_publication: '2020-11-16' + bug_reports: https://github.com/PaulAntonDeen/POV-R-Package/issues + url: https://thomasalittleconsulting.com + url_cran: https://CRAN.R-project.org/package=POV + url_git: https://github.com/PaulAntonDeen/POV-R-Package +povmap: + version: 1.0.1 + title: Extension to the 'emdi' Package + maintainer: Ifeanyi Edochie + description: |- + The R package 'povmap' supports small area estimation of means and + poverty headcount rates. It adds several new features to the 'emdi' package + (see "The R Package emdi for Estimating and Mapping Regionally Disaggregated + Indicators" by Kreutzmann et al. (2019) ). + These include new options for incorporating survey weights, ex-post + benchmarking of estimates, two additional transformations, several new + convenient functions to assist with reporting results, and a wrapper function + to facilitate access from 'Stata'. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=povmap + url_git: https://github.com/SSA-Statistical-Team-Projects/povmap +pow.int: + version: '1.3' + title: Binary Exponentiation + maintainer: Jonathan Debove + description: Fast exponentiation when the exponent is an integer. + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pow.int + url_git: '' +powdist: + version: 0.1.4 + title: Power and Reversal Power Distributions + maintainer: Susan Anyosa + description: Density, distribution function, quantile function and random generation + for the family of power and reversal power distributions. + date_publication: '2017-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powdist + url_git: '' +powdR: + version: 1.3.0 + title: Full Pattern Summation of X-Ray Powder Diffraction Data + maintainer: Benjamin Butler + description: |- + Full pattern summation of X-ray powder diffraction data as + described in Chipera and Bish (2002) and + Butler and Hillier (2021) . + Derives quantitative estimates of crystalline and amorphous phase + concentrations in complex mixtures. + date_publication: '2021-08-13' + bug_reports: https://github.com/benmbutler/powdR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=powdR + url_git: https://github.com/benmbutler/powdR +power.transform: + version: 1.0.0 + title: Location and Scale Invariant Power Transformations + maintainer: Alex Zwanenburg + description: |- + Location- and scale-invariant Box-Cox and Yeo-Johnson power transformations + allow for transforming variables with distributions distant from 0 to + normality. Transformers are implemented as S4 objects. These allow for + transforming new instances to normality after optimising fitting parameters + on other data. A test for central normality allows for rejecting + transformations that fail to produce a suitably normal distribution, + independent of sample number. + date_publication: '2024-09-13' + bug_reports: https://github.com/oncoray/power.transform/issues + url: '' + url_cran: https://CRAN.R-project.org/package=power.transform + url_git: https://github.com/oncoray/power.transform +Power2Stage: + version: 0.5-4 + title: |- + Power and Sample-Size Distribution of 2-Stage Bioequivalence + Studies + maintainer: Detlew Labes + description: |- + Contains functions to obtain the operational characteristics of + bioequivalence studies in Two-Stage Designs (TSD) via simulations. + date_publication: '2021-11-20' + bug_reports: https://github.com/Detlew/Power2Stage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Power2Stage + url_git: https://github.com/Detlew/Power2Stage +poweRbal: + version: 0.0.1.1 + title: Phylogenetic Tree Models and the Power of Tree Shape Statistics + maintainer: Sophie Kersting + description: |- + The first goal of this package is to provide a multitude of tree models, + i.e., functions that generate rooted binary trees with a given number of leaves. + Second, the package allows for an easy evaluation and comparison of tree shape + statistics by estimating their power to differentiate between different tree models. + Please note that this R package was developed alongside the manuscript + "Tree balance in phylogenetic models" by + S. J. Kersting, K. Wicke, and M. Fischer (2024) , + which provides further background and the respective mathematical definitions. + This project was supported by the project ArtIGROW, which is a part of the + WIR!-Alliance ArtIFARM – Artificial Intelligence in Farming funded by the + German Federal Ministry of Education and Research (No. 03WIR4805). + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=poweRbal + url_git: '' +powerbiR: + version: 0.1.0 + title: An Interface to the 'Power BI REST APIs' + maintainer: Christian Vermehren + description: |- + Makes it easy to push data to 'Power BI' using R and the 'Power BI + REST APIs' (see ). + A set of functions for turning data frames into 'Power BI' datasets and + refreshing these datasets are provided. Administrative tasks such as + monitoring refresh statuses and pulling metadata about workspaces and users + are also supported. + date_publication: '2022-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerbiR + url_git: '' +powerbydesign: + version: 1.0.5 + title: Power Estimates for ANOVA Designs + maintainer: Frank Papenmeier + description: |- + Functions for bootstrapping the power of ANOVA designs + based on estimated means and standard deviations of the conditions. + Please refer to the documentation of the boot.power.anova() function + for further details. + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerbydesign + url_git: '' +powerCompRisk: + version: 1.0.1 + title: |- + Power Analysis Tool for Joint Testing Hazards with Competing + Risks Data + maintainer: Eric Kawaguchi + description: A power analysis tool for jointly testing the cause-1 cause-specific + hazard and the any-cause hazard with competing risks data. + date_publication: '2018-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerCompRisk + url_git: '' +powerEQTL: + version: 0.3.4 + title: |- + Power and Sample Size Calculation for Bulk Tissue and + Single-Cell eQTL Analysis + maintainer: Weiliang Qiu + description: |- + Power and sample size calculation for bulk tissue and single-cell eQTL analysis + based on ANOVA, simple linear regression, or linear mixed effects model. It can also calculate power/sample size + for testing the association of a SNP to a continuous type phenotype. + Please see the reference: Dong X, Li X, Chang T-W, Scherzer CR, Weiss ST, Qiu W. (2021) . + date_publication: '2021-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerEQTL + url_git: https://github.com/sterding/powerEQTLandhttps://bwhbioinfo.shinyapps.io/powerEQTL/ +PoweREST: + version: 0.1.0 + title: |- + A Bootstrap-Based Power Estimation Tool for Spatial + Transcriptomics + maintainer: Lan Shui + description: Power estimation and sample size calculation for 10X Visium Spatial + Transcriptomics data to detect differential expressed genes between two conditions + based on bootstrap resampling. See Shui et al. (2024) + for method details. + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PoweREST + url_git: '' +powerGWASinteraction: + version: 1.1.3 + title: Power Calculations for GxE and GxG Interactions for GWAS + maintainer: Charles Kooperberg + description: Analytical power calculations for GxE and GxG interactions for case-control + studies of candidate genes and genome-wide association studies (GWAS). This includes + power calculation for four two-step screening and testing procedures. It can + also calculate power for GxE and GxG without any screening. + date_publication: '2015-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerGWASinteraction + url_git: '' +powerHE: + version: 1.0.0 + title: Power and Sample Size Calculations with Hierarchical Endpoints + maintainer: Sarah Wu + description: |- + Calculate sample size or power for hierarchical endpoints. + The package can handle any type of outcomes (binary, continuous, count, ordinal, + time-to-event) and any number of such endpoints. It allows users to calculate + sample size with a given power or to calculate power with a given sample size + for hypothesis testing based on win ratios, win odds, net benefit, or DOOR + (desirability of outcome ranking) as treatment effect between two groups for + hierarchical endpoints. The methods of this package are described further in + the paper by Barnhart, H. X. et al. (2024, ). + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerHE + url_git: '' +powerindexR: + version: '1.6' + title: Measuring the Power in Voting Systems + maintainer: Livino M. Armijos-Toro + description: This R package allows the determination of some distributions of the + voters' power when passing laws in weighted voting situations. + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerindexR + url_git: '' +powerjoin: + version: 0.1.0 + title: Extensions of 'dplyr' and 'fuzzyjoin' Join Functions + maintainer: Antoine Fabri + description: |- + We extend 'dplyr' and 'fuzzyjoin' join functions with + features to preprocess the data, apply various data checks, and deal with + conflicting columns. + date_publication: '2022-11-03' + bug_reports: https://github.com/moodymudskipper/powerjoin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=powerjoin + url_git: https://github.com/moodymudskipper/powerjoin +powerLATE: + version: 0.1.2 + title: Generalized Power Analysis for LATE + maintainer: Eddie Yang + description: An implementation of the generalized power analysis for the local average + treatment effect (LATE), proposed by Bansak (2020) . Power + analysis is in the context of estimating the LATE (also known as the complier + average causal effect, or CACE), with calculations based on a test of the null + hypothesis that the LATE equals 0 with a two-sided alternative. The method uses + standardized effect sizes to place a conservative bound on the power under minimal + assumptions. Package allows users to recover power, sample size requirements, + or minimum detectable effect sizes. Package also allows users to work with absolute + effects rather than effect sizes, to specify an additional assumption to narrow + the bounds, and to incorporate covariate adjustment. + date_publication: '2024-05-29' + bug_reports: https://github.com/kbansak/powerLATE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=powerLATE + url_git: https://github.com/kbansak/powerLATE_tutorial +poweRlaw: + version: 1.0.0 + title: Analysis of Heavy Tailed Distributions + maintainer: Colin Gillespie + description: |- + An implementation of maximum likelihood estimators for a + variety of heavy tailed distributions, including both the discrete and + continuous power law distributions. Additionally, a goodness-of-fit + based approach is used to estimate the lower cut-off for the scaling + region. + date_publication: '2025-02-03' + bug_reports: https://github.com/csgillespie/poweRlaw/issues + url: http://csgillespie.github.io/poweRlaw/ + url_cran: https://CRAN.R-project.org/package=poweRlaw + url_git: https://github.com/csgillespie/poweRlaw +powerly: + version: 1.8.6 + title: Sample Size Analysis for Psychological Networks and More + maintainer: Mihai Constantin + description: |- + An implementation of the sample size computation method for network + models proposed by Constantin et al. (2021) . + The implementation takes the form of a three-step recursive algorithm + designed to find an optimal sample size given a model specification and a + performance measure of interest. It starts with a Monte Carlo simulation + step for computing the performance measure and a statistic at various sample + sizes selected from an initial sample size range. It continues with a + monotone curve-fitting step for interpolating the statistic across the entire + sample size range. The final step employs stratified bootstrapping to quantify + the uncertainty around the fitted curve. + date_publication: '2022-09-09' + bug_reports: https://github.com/mihaiconstantin/powerly/issues + url: https://powerly.dev + url_cran: https://CRAN.R-project.org/package=powerly + url_git: '' +powerMediation: + version: 0.3.4 + title: Power/Sample Size Calculation for Mediation Analysis + maintainer: Weiliang Qiu + description: |- + Functions to + calculate power and sample size for testing + (1) mediation effects; + (2) the slope in a simple linear regression; + (3) odds ratio in a simple logistic regression; + (4) mean change for longitudinal study with 2 time points; + (5) interaction effect in 2-way ANOVA; and + (6) the slope in a simple Poisson regression. + date_publication: '2021-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerMediation + url_git: '' +powerNLSEM: + version: 0.1.2 + title: Simulation-Based Power Estimation (MSPE) for Nonlinear SEM + maintainer: Julien Patrick Irmer + description: |- + Model-implied simulation-based power estimation (MSPE) for + nonlinear (and linear) SEM, path analysis and regression analysis. A + theoretical framework is used to approximate the relation between + power and sample size for given type I error rates and effect sizes. + The package offers an adaptive search algorithm to find the optimal N for + given effect sizes and type I error rates. Plots can be used to visualize + the power relation to N for different parameters of interest (POI). + Theoretical justifications are given in Irmer et al. + (2024a) and detailed description + are given in Irmer et al. (2024b) . + date_publication: '2024-09-27' + bug_reports: https://github.com/jpirmer/powerNLSEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=powerNLSEM + url_git: https://github.com/jpirmer/powerNLSEM +PowerNormal: + version: 1.2.0 + title: Power Normal Distribution + maintainer: Gualberto Segundo Agamez Montalvo + description: |- + Miscellaneous functions for a descriptive analysis and initial Bayesian and classical + inference for the power parameter of the the Power Normal (PN) distribution. This + miscellaneous will be extend for more distributions into the power family and the + three-parameter model. + date_publication: '2017-07-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PowerNormal + url_git: '' +powerpkg: + version: '1.6' + title: Power Analyses for the Affected Sib Pair and the TDT Design + maintainer: Daniel E. Weeks + description: |- + There are two main functions: (1) To estimate the power of testing for linkage using an + affected sib pair design, as a function of the recurrence risk + ratios. We will use analytical power formulae as implemented in + R. These are based on a Mathematica notebook created by Martin + Farrall. (2) To examine how the power of the transmission + disequilibrium test (TDT) depends on the disease allele + frequency, the marker allele frequency, the strength of the + linkage disequilibrium, and the magnitude of the genetic + effect. We will use an R program that implements the power + formulae of Abel and Muller-Myhsok (1998). These formulae allow + one to quickly compute power of the TDT approach under a + variety of different conditions. This R program was modeled on + Martin Farrall's Mathematica notebook. + date_publication: '2022-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerpkg + url_git: '' +powerPLS: + version: 0.2.0 + title: Power Analysis for PLS Classification + maintainer: Angela Andreella + description: It estimates power and sample size for Partial Least Squares-based + methods described in Andreella, et al., (2024), . + date_publication: '2024-09-30' + bug_reports: https://github.com/angeella/powerPLS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=powerPLS + url_git: https://github.com/angeella/powerPLS +PowerSDI: + version: 1.0.0 + title: Calculate Standardised Drought Indices Using NASA POWER Data + maintainer: Gabriel Constantino Blain + description: |- + A set of functions designed to calculate the standardised + precipitation and standardised precipitation evapotranspiration indices + using NASA POWER data as described in Blain et al. (2023) + . These indices are calculated using a reference + data source. The functions verify if the indices' estimates meet the + assumption of normality and how well NASA POWER estimates represent + real-world data. Indices are calculated in a routine mode. Potential + evapotranspiration amounts and the difference between rainfall and potential + evapotranspiration are also calculated. The functions adopt a basic time + scale that splits each month into four periods. Days 1 to 7, days 8 to 14, + days 15 to 21, and days 22 to 28, 29, 30, or 31, where 'TS=4' corresponds to + a 1-month length moving window (calculated 4 times per month) and 'TS=48' + corresponds to a 12-month length moving window (calculated 4 times per + month). + date_publication: '2024-01-15' + bug_reports: https://github.com/gabrielblain/PowerSDI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PowerSDI + url_git: https://github.com/gabrielblain/PowerSDI +powerSurvEpi: + version: 0.1.3 + title: |- + Power and Sample Size Calculation for Survival Analysis of + Epidemiological Studies + maintainer: Weiliang Qiu + description: |- + Functions to calculate power and + sample size for testing main effect or interaction effect in + the survival analysis of epidemiological studies + (non-randomized studies), taking into account the + correlation between the covariate of the + interest and other covariates. Some calculations also take + into account the competing risks and stratified analysis. + This package also includes + a set of functions to calculate power and sample size + for testing main effect in the survival analysis of + randomized clinical trials and conditional logistic regression for nested case-control study. + date_publication: '2021-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=powerSurvEpi + url_git: '' +powertools: + version: 0.1.2 + title: Power and Sample Size Tools + maintainer: Catherine M. Crespi + description: |- + Power and sample size calculations for a variety of study designs and + outcomes. Methods include t tests, ANOVA (including tests for interactions, + simple effects and contrasts), proportions, categorical data (chi-square tests + and proportional odds), linear, logistic and Poisson regression, alternative + and coprimary endpoints, power for confidence intervals, correlation + coefficient tests, cluster randomized trials, individually randomized group + treatment trials, multisite trials, treatment-by-covariate interaction effects + and nonparametric tests of location. Utilities are provided for + computing various effect sizes. Companion package to the book + "Power and Sample Size in R", Crespi (2025, ISBN:9781138591622). + date_publication: '2024-11-21' + bug_reports: https://github.com/powerandsamplesize/powertools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=powertools + url_git: https://github.com/powerandsamplesize/powertools +PowerTOST: + version: 1.5-6 + title: Power and Sample Size for (Bio)Equivalence Studies + maintainer: Detlew Labes + description: |- + Contains functions to calculate power and sample size for + various study designs used in bioequivalence studies. Use known.designs() to + see the designs supported. Power and sample size can be obtained based on + different methods, amongst them prominently the TOST procedure (two one-sided + t-tests). See README and NEWS for further information. + date_publication: '2024-03-18' + bug_reports: https://github.com/Detlew/PowerTOST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PowerTOST + url_git: https://github.com/Detlew/PowerTOST +PowerUpR: + version: 1.1.0 + title: Power Analysis Tools for Multilevel Randomized Experiments + maintainer: Metin Bulus + description: |2- + + Includes tools to calculate statistical power, minimum detectable effect size (MDES), MDES difference (MDESD), and minimum required sample size for various multilevel randomized experiments (MRE) with continuous outcomes. + Accomodates 14 types of MRE designs to detect main treatment effect, seven types of MRE designs to detect moderated treatment effect (2-1-1, 2-1-2, 2-2-1, 2-2-2, 3-3-1, 3-3-2, and 3-3-3 designs; - - ), + five types of MRE designs to detect mediated treatment effects (2-1-1, 2-2-1, 3-1-1, 3-2-1, and 3-3-1 designs; - - ), four types of partially nested (PN) design to detect main treatment effect, + and three types of PN designs to detect mediated treatment effects (2/1, 3/1, 3/2; / ). + See 'PowerUp!' Excel series at . + date_publication: '2021-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PowerUpR + url_git: '' +powRICLPM: + version: 0.2.1 + title: Perform Power Analysis for the RI-CLPM and STARTS Model + maintainer: Jeroen Mulder + description: |- + Perform user-friendly power analyses for the random + intercept cross-lagged panel model (RI-CLPM) and the bivariate stable trait + autoregressive trait state (STARTS) model. The strategy as proposed by + Mulder (2023) is implemented. Extensions + include the use of parameter constraints over time, bounded estimation, + generation of data with skewness and kurtosis, and the option to setup the power + analysis for Mplus. + date_publication: '2024-10-26' + bug_reports: https://github.com/JeroenDMulder/powRICLPM/issues/ + url: https://jeroendmulder.github.io/powRICLPM/ + url_cran: https://CRAN.R-project.org/package=powRICLPM + url_git: '' +PP: + version: 0.6.3-11 + title: Person Parameter Estimation + maintainer: Jan Steinfeld + description: |- + The PP package includes estimation of (MLE, WLE, MAP, EAP, ROBUST) + person parameters for the 1,2,3,4-PL model and the GPCM (generalized + partial credit model). The parameters are estimated under the assumption + that the item parameters are known and fixed. The package is useful e.g. in + the case that items from an item pool / item bank with known item parameters + are administered to a new population of test-takers and an ability + estimation for every test-taker is needed. + date_publication: '2021-05-27' + bug_reports: https://github.com/jansteinfeld/PP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PP + url_git: https://github.com/jansteinfeld/PP +PPbigdata: + version: 1.0.0 + title: Projection Pursuit for Big Data Based on Data Nuggets + maintainer: Yajie Duan + description: |- + Perform 1-dim/2-dim projection pursuit, grand tour and guided tour for big data based on data nuggets. + Reference papers: [1] Beavers et al., (2024) . + [2] Duan, Y., Cabrera, J., & Emir, B. (2023). "A New Projection Pursuit Index for Big Data." . + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPbigdata + url_git: '' +pPCA: + version: '1.1' + title: |- + Partial Principal Component Analysis of Partitioned Large Sparse + Matrices + maintainer: Srika Raja + description: |- + Performs partial principal component analysis of a large sparse matrix. + The matrix may be stored as a list of matrices to be concatenated (implicitly) horizontally. + Useful application includes cases where the number of total nonzero entries exceed the capacity of + 32 bit integers (e.g., with large Single Nucleotide Polymorphism data). + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pPCA + url_git: '' +ppcc: + version: '1.2' + title: Probability Plot Correlation Coefficient Test + maintainer: Thorsten Pohlert + description: |- + Calculates the Probability Plot Correlation Coefficient (PPCC) + between a continuous variable X and a specified distribution. The corresponding + composite hypothesis test that was first introduced by + Filliben (1975) + can be performed to test whether the sample + X is element of either the Normal, log-Normal, Exponential, + Uniform, Cauchy, Logistic, Generalized Logistic, Gumbel (GEVI), Weibull, + Generalized Extreme Value, Pearson III (Gamma 2), Mielke's Kappa, Rayleigh + or Generalized Logistic Distribution. The PPCC test is performed with + a fast Monte-Carlo simulation. + date_publication: '2020-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppcc + url_git: '' +PPCDT: + version: 0.2.0 + title: An Optimal Subset Selection for Distributed Hypothesis Testing + maintainer: Guangbao Guo + description: In the era of big data, data redundancy and distributed characteristics + present novel challenges to data analysis. This package introduces a method for + estimating optimal subsets of redundant distributed data, based on PPCDT (Conjunction + of Power and P-value in Distributed Settings). Leveraging PPC technology, this + approach can efficiently extract valuable information from redundant distributed + data and determine the optimal subset. Experimental results demonstrate that this + method not only enhances data quality and utilization efficiency but also assesses + its performance effectively. The philosophy of the package is described in Guo + G. (2020) . + date_publication: '2024-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPCDT + url_git: '' +PPCI: + version: 0.1.5 + title: Projection Pursuit for Cluster Identification + maintainer: David Hofmeyr + description: |- + Implements recently developed projection + pursuit algorithms for finding optimal linear cluster + separators. The clustering algorithms use optimal + hyperplane separators based on minimum density, Pavlidis et. al (2016) ; + minimum normalised cut, Hofmeyr (2017) ; + and maximum variance ratio clusterability, Hofmeyr and Pavlidis (2015) . + date_publication: '2020-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPCI + url_git: '' +ppclust: + version: 1.1.0.1 + title: Probabilistic and Possibilistic Cluster Analysis + maintainer: Zeynel Cebeci + description: Partitioning clustering divides the objects in a data set into non-overlapping + subsets or clusters by using the prototype-based probabilistic and possibilistic + clustering algorithms. This package covers a set of the functions for Fuzzy C-Means + (Bezdek, 1974) , Possibilistic C-Means (Krishnapuram + & Keller, 1993) , Possibilistic Fuzzy C-Means (Pal et al, + 2005) , Possibilistic Clustering Algorithm (Yang + et al, 2006) , Possibilistic C-Means with Repulsion + (Wachs et al, 2006) and the other variants of hard + and soft clustering algorithms. The cluster prototypes and membership matrices + required by these partitioning algorithms are initialized with different initialization + techniques that are available in the package 'inaparc'. As the distance metrics, + not only the Euclidean distance but also a set of the commonly used distance metrics + are available to use with some of the algorithms in the package. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppclust + url_git: '' +ppcor: + version: '1.1' + title: Partial and Semi-Partial (Part) Correlation + maintainer: Seongho Kim + description: |- + Calculates partial and semi-partial + (part) correlations along with p-value. + date_publication: '2015-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppcor + url_git: '' +ppcSpatial: + version: 0.3.0 + title: Spatial Analysis of Pakistan Population Census + maintainer: Muhammad Yaseen + description: Spatial Analysis for exploration of Pakistan Population Census 2017 + (). It uses data from R package + 'PakPC2017'. + date_publication: '2023-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppcSpatial + url_git: https://github.com/MYaseen208/ppcSpatial +ppdiag: + version: 0.1.1 + title: Diagnosis and Visualizations Tools for Temporal Point Processes + maintainer: Owen G. Ward + description: |- + A suite of diagnostic tools for univariate point processes. + This includes tools for simulating and fitting both common and more + complex temporal point processes. We also include functions to + visualise these point processes and collect existing diagnostic + tools of Brown et al. (2002) and + Wu et al. (2021) , + which can be used to assess the fit of a chosen point process + model. + date_publication: '2021-08-12' + bug_reports: https://github.com/OwenWard/ppdiag/issues + url: https://owenward.github.io/ppdiag/ + url_cran: https://CRAN.R-project.org/package=ppdiag + url_git: '' +ppendemic: + version: 0.1.8 + title: A Glimpse at the Diversity of Peru's Endemic Plants + maintainer: Paul E. Santos Andrade + description: 'Introducing a novel and updated database showcasing Peru''s endemic + plants. This meticulously compiled and revised botanical collection encompasses + a remarkable assemblage of over 7,249 distinct species. The data for this resource + was sourced from the work of Govaerts, R., Nic Lughadha, E., Black, N. et al., + titled ''The World Checklist of Vascular Plants: A continuously updated resource + for exploring global plant diversity'', published in Sci Data 8, 215 (2021) .' + date_publication: '2024-07-14' + bug_reports: https://github.com/PaulESantos/ppendemic/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=ppendemic + url_git: https://github.com/PaulESantos/ppendemic/ +PPforest: + version: 0.1.3 + title: Projection Pursuit Classification Forest + maintainer: Natalia da Silva + description: Implements projection pursuit forest algorithm for supervised classification. + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPforest + url_git: https://github.com/natydasilva/PPforest +ppgam: + version: 1.0.2 + title: Generalised Additive Point Process Models + maintainer: Ben Youngman + description: |- + Methods for fitting point processes with parameters of generalised additive + model (GAM) form are provided. For an introduction to point processes see Cox, D.R & + Isham, V. (Point Processes, 1980, CRC Press), GAMs see Wood, S.N. (2017) + , and the fitting approach see Wood, S.N., Pya, N. & + Safken, B. (2016) . + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppgam + url_git: '' +ppgm: + version: 1.0.3 + title: |- + PaleoPhyloGeographic Modeling of Climate Niches and Species + Distributions + maintainer: Alexandra Howard + description: |- + Reconstruction of paleoclimate niches using phylogenetic comparative + methods and projection reconstructed niches onto paleoclimate maps. + The user can specify various models of trait evolution or estimate the best fit + model, include fossils, use one or multiple phylogenies for inference, and make + animations of shifting suitable habitat through time. This model was first used + in Lawing and Polly (2011), and further implemented in Lawing et al (2016) and + Rivera et al (2020). + Lawing and Polly (2011) "Pleistocene climate, + phylogeny and climate envelope models: An integrative approach to better + understand species' response to climate change" + Lawing et al (2016) "Including fossils in phylogenetic + climate reconstructions: A deep time perspective on the climatic niche evolution + and diversification of spiny lizards (Sceloporus)" + Rivera et al (2020) "Reconstructing historical shifts + in suitable habitat of Sceloporus lineages using phylogenetic niche modelling.". + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppgm + url_git: '' +ppgmmga: + version: '1.3' + title: |- + Projection Pursuit Based on Gaussian Mixtures and Evolutionary + Algorithms + maintainer: Luca Scrucca + description: Projection Pursuit (PP) algorithm for dimension reduction based on + Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms + (GAs) to maximise an approximated negentropy index. For more details see Scrucca + and Serafini (2019) . + date_publication: '2023-11-17' + bug_reports: https://github.com/luca-scr/ppgmmga/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ppgmmga + url_git: https://github.com/luca-scr/ppgmmga +ppitables: + version: 0.5.5 + title: |- + Lookup Tables to Generate Poverty Likelihoods and Rates using + the Poverty Probability Index (PPI) + maintainer: Ernest Guevarra + description: |- + The Poverty Probability Index (PPI) is a poverty measurement tool + for organizations and businesses with a mission to serve the poor. The PPI + is statistically-sound, yet simple to use: the answers to 10 questions about + a household’s characteristics and asset ownership are scored to compute the + likelihood that the household is living below the poverty line – or above by + only a narrow margin. This package contains country-specific lookup data tables + used as reference to determine the poverty likelihood of a household based + on their score from the country-specific PPI questionnaire. These lookup + tables have been extracted from documentation of the PPI found at + and managed by Innovations for Poverty Action + . + date_publication: '2024-04-12' + bug_reports: https://github.com/katilingban/ppitables/issues + url: https://katilingban.io/ppitables/ + url_cran: https://CRAN.R-project.org/package=ppitables + url_git: https://github.com/katilingban/ppitables +PPLasso: + version: '2.0' + title: Prognostic Predictive Lasso for Biomarker Selection + maintainer: Wencan Zhu + description: 'We provide new tools for the identification of prognostic and predictive + biomarkers. For further details we refer the reader to the paper: Zhu et al. Identification + of prognostic and predictive biomarkers in high-dimensional data with PPLasso. + BMC Bioinformatics. 2023 Jan 23;24(1):25.' + date_publication: '2023-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPLasso + url_git: '' +ppmf: + version: 0.1.3 + title: Read Census Privacy Protected Microdata Files + maintainer: Christopher T. Kenny + description: Implements data processing described in + to align modern differentially private data with formatting of older US Census + data releases. The primary goal is to read in Census Privacy Protected Microdata + Files data in a reproducible way. This includes tools for aggregating to relevant + levels of geography by creating geographic identifiers which match the US Census + Bureau's numbering. Additionally, there are tools for grouping race numeric identifiers + into categories, consistent with OMB (Office of Management and Budget) classifications. + Functions exist for downloading and linking to existing sources of privacy protected + microdata. + date_publication: '2021-12-15' + bug_reports: https://github.com/christopherkenny/ppmf/issues + url: https://www.christophertkenny.com/ppmf/ + url_cran: https://CRAN.R-project.org/package=ppmf + url_git: https://github.com/christopherkenny/ppmf/ +ppmHR: + version: '1.0' + title: |- + Privacy-Protecting Hazard Ratio Estimation in Distributed Data + Networks + maintainer: Di Shu + description: 'An implementation of the one-step privacy-protecting method for estimating + the overall and site-specific hazard ratios using inverse probability weighted + Cox models in distributed data network studies, as proposed by Shu, Yoshida, Fireman, + and Toh (2019) . This method only requires sharing + of summary-level riskset tables instead of individual-level data. Both the conventional + inverse probability weights and the stabilized weights are implemented.' + date_publication: '2020-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppmHR + url_git: '' +PPMiss: + version: 0.1.1 + title: |- + Copula-Based Estimator for Long-Range Dependent Processes under + Missing Data + maintainer: Taiane Schaedler Prass + description: Implements the copula-based estimator for univariate long-range dependent + processes, introduced in Pumi et al. (2023) . + Notably, this estimator is capable of handling missing data and has been shown + to perform exceptionally well, even when up to 70% of data is missing (as reported + in ) and has been found to outperform several other commonly + applied estimators. + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPMiss + url_git: '' +ppmlasso: + version: '1.4' + title: Point Process Models with LASSO-Type Penalties + maintainer: Ian Renner + description: Toolkit for fitting point process models with sequences of LASSO penalties + ("regularisation paths"), as described in Renner, I.W. and Warton, D.I. (2013) + . Regularisation paths of Poisson point + process models or area-interaction models can be fitted with LASSO, adaptive LASSO + or elastic net penalties. A number of criteria are available to judge the bias-variance + tradeoff. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppmlasso + url_git: '' +PPMR: + version: '1.0' + title: Probabilistic Two Sample Mendelian Randomization + maintainer: Michael Kleinsasser + description: |- + Efficient statistical inference of two-sample MR (Mendelian Randomization) analysis. + It can account for the correlated instruments and the horizontal pleiotropy, + and can provide the accurate estimates of both causal effect and horizontal + pleiotropy effect as well as the two corresponding p-values. There are two main + functions in the 'PPMR' package. One is PMR_individual() for individual level data, + the other is PMR_summary() for summary data. + date_publication: '2019-08-09' + bug_reports: https://github.com/umich-biostatistics/PPMR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PPMR + url_git: '' +ppmSuite: + version: 0.3.4 + title: |- + A Collection of Models that Employ Product Partition + Distributions as a Prior on Partitions + maintainer: Garritt L. Page + description: |- + Provides a suite of functions that fit models that use PPM type priors for partitions. + Models include hierarchical Gaussian and probit ordinal models with a (covariate + dependent) PPM. If a covariate dependent product partition model is selected, + then all the options detailed in Page, G.L.; Quintana, F.A. (2018) + are available. If covariate values are missing, + then the approach detailed in Page, G.L.; Quintana, F.A.; Mueller, P (2020) + is employed. Also included in the package is + a function that fits a Gaussian likelihood spatial product partition model that is + detailed in Page, G.L.; Quintana, F.A. (2016) , and + multivariate PPM change point models that are detailed in Quinlan, J.J.; Page, G.L.; + Castro, L.M. (2023) . In addition, a function that fits a + univariate or bivariate functional data model that employs a PPM or a PPMx to + cluster curves based on B-spline coefficients is provided. + date_publication: '2023-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppmSuite + url_git: '' +PPQplan: + version: 1.1.0 + title: |- + Process Performance Qualification (PPQ) Plans in Chemistry, + Manufacturing and Controls (CMC) Statistical Analysis + maintainer: Yalin Zhu + description: Assessment for statistically-based PPQ sampling plan, including calculating + the passing probability, optimizing the baseline and high performance cutoff points, + visualizing the PPQ plan and power dynamically. The analytical idea is based on + the simulation methods from the textbook Burdick, R. K., LeBlond, D. J., Pfahler, + L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical + Methods for CMC Applications. In Statistical Applications for Chemistry, Manufacturing + and Controls (CMC) in the Pharmaceutical Industry (pp. 227-250). Springer, Cham. + date_publication: '2020-10-08' + bug_reports: https://github.com/allenzhuaz/PPQplan/issues + url: https://allenzhuaz.github.io/PPQplan/ + url_cran: https://CRAN.R-project.org/package=PPQplan + url_git: https://github.com/allenzhuaz/PPQplan +ppRank: + version: 0.1.1 + title: Classification of Algorithms + maintainer: Iago Augusto de Carvalho + description: Implements the Bi-objective Lexicographical Classification method and + Performance Assessment Ratio at 10% metric for algorithm classification. Constructs + matrices representing algorithm performance under multiple criteria, facilitating + decision-making in algorithm selection and evaluation. Analyzes and compares algorithm + performance based on various metrics to identify the most suitable algorithms + for specific tasks. This package includes methods for algorithm classification + and evaluation, with examples provided in the documentation. Carvalho (2019) presents + a statistical evaluation of algorithmic computational experimentation with infeasible + solutions . Moreira and Carvalho (2023) analyze + power in preprocessing methodologies for datasets with missing values . + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppRank + url_git: '' +ppRep: + version: 0.42.3 + title: Analysis of Replication Studies using Power Priors + maintainer: Samuel Pawel + description: Provides functionality for Bayesian analysis of replication studies + using power prior approaches (Pawel et al., 2023) . + date_publication: '2023-10-19' + bug_reports: https://github.com/SamCH93/ppRep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ppRep + url_git: https://github.com/SamCH93/ppRep +PPRL: + version: 0.3.8 + title: Privacy Preserving Record Linkage + maintainer: Dorothea Rukasz + description: A toolbox for deterministic, probabilistic and privacy-preserving record + linkage techniques. Combines the functionality of the 'Merge ToolBox' () + with current privacy-preserving techniques. + date_publication: '2022-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPRL + url_git: '' +pprof: + version: 1.0.1 + title: Modeling, Standardization and Testing for Provider Profiling + maintainer: Xiaohan Liu + description: |- + Implements linear and generalized linear models for provider profiling, + incorporating both fixed and random effects. For large-scale providers, the linear + profiled-based method and the SerBIN method for binary data + reduce the computational burden. Provides post-modeling features, such as + indirect and direct standardization measures, hypothesis testing, + confidence intervals, and post-estimation visualization. + For more information, see Wu et al. (2022) . + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pprof + url_git: https://github.com/UM-KevinHe/pprof +pps: + version: '1.0' + title: PPS Sampling + maintainer: Jack G. Gambino + description: Functions to select samples using PPS (probability proportional to + size) sampling. The package also includes a function for stratified simple random + sampling, a function to compute joint inclusion probabilities for Sampford's method + of PPS sampling, and a few utility functions. The user's guide pps-ug.pdf is included + in the .../pps/doc directory. The methods are described in standard survey sampling + theory books such as Cochran's "Sampling Techniques"; see the user's guide for + references. + date_publication: '2021-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pps + url_git: '' +ppsbm: + version: 1.0.0 + title: Clustering in Longitudinal Networks + maintainer: Daphné Giorgi + description: |- + Stochastic block model used for dynamic graphs represented by Poisson processes. + To model recurrent interaction events in continuous time, an extension of the stochastic block model is proposed where every individual belongs to a latent group and interactions between two individuals follow a conditional inhomogeneous Poisson process with intensity driven by the individuals’ latent groups. The model is shown to be identifiable and its estimation is based on a semiparametric variational expectation-maximization algorithm. Two versions of the method are developed, using either a nonparametric histogram approach (with an adaptive choice of the partition size) or kernel intensity estimators. The number of latent groups can be selected by an integrated classification likelihood criterion. + Y. Baraud and L. Birgé (2009). . + C. Biernacki, G. Celeux and G. Govaert (2000). . + M. Corneli, P. Latouche and F. Rossi (2016). . + J.-J. Daudin, F. Picard and S. Robin (2008). . + A. P. Dempster, N. M. Laird and D. B. Rubin (1977). . + G. Grégoire (1993). . + L. Hubert and P. Arabie (1985). . + M. Jordan, Z. Ghahramani, T. Jaakkola and L. Saul (1999). . + C. Matias, T. Rebafka and F. Villers (2018). . + C. Matias and S. Robin (2014). . + H. Ramlau-Hansen (1983). . + P. Reynaud-Bouret (2006). . + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppsbm + url_git: '' +ppseq: + version: 0.2.5 + title: |- + Design Clinical Trials using Sequential Predictive Probability + Monitoring + maintainer: Emily C. Zabor + description: Functions are available to calibrate designs over a range of posterior + and predictive thresholds, to plot the various design options, and to obtain the + operating characteristics of optimal accuracy and optimal efficiency designs. + date_publication: '2024-09-04' + bug_reports: https://github.com/zabore/ppseq/issues + url: https://www.emilyzabor.com/ppseq/ + url_cran: https://CRAN.R-project.org/package=ppseq + url_git: https://github.com/zabore/ppseq +PPSFS: + version: 0.1.0 + title: |- + Partial Profile Score Feature Selection in High-Dimensional + Generalized Linear Interaction Models + maintainer: Zengchao Xu + description: |2- + + This is an implementation of the partial profile score feature + selection (PPSFS) approach to generalized linear (interaction) models. + The PPSFS is highly scalable even for ultra-high-dimensional feature space. + See the paper by Xu, Luo and Chen (2021, ). + date_publication: '2022-03-21' + bug_reports: https://github.com/paradoxical-rhapsody/PPSFS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PPSFS + url_git: https://github.com/paradoxical-rhapsody/PPSFS +ppsr: + version: 0.0.5 + title: Predictive Power Score + maintainer: Paul van der Laken + description: |- + The Predictive Power Score (PPS) is an asymmetric, data-type-agnostic score + that can detect linear or non-linear relationships between two variables. + The score ranges from 0 (no predictive power) to 1 (perfect predictive power). + PPS can be useful for data exploration purposes, in the same way correlation analysis is. + For more information on PPS, see . + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ppsr + url_git: '' +PPTcirc: + version: 0.2.3 + title: Projected Polya Tree for Circular Data + maintainer: Karla Mayra Perez + description: |- + Provides functionality for the prior and posterior projected Polya tree for the analysis of circular data + (Nieto-Barajas and Nunez-Antonio (2019) ). + date_publication: '2022-08-30' + bug_reports: https://github.com/Karlampm/PPTcirc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PPTcirc + url_git: https://github.com/Karlampm/PPTcirc +PPtreeViz: + version: 2.0.4 + title: Projection Pursuit Classification Tree Visualization + maintainer: Eun-Kyung Lee + description: |- + Tools for exploring projection pursuit classification tree using + various projection pursuit indexes. + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PPtreeViz + url_git: '' +pqantimalarials: + version: '0.2' + title: |- + web tool for estimating under-five deaths caused by poor-quality + antimalarials in sub-Saharan Africa + maintainer: J. Patrick Renschler + description: |- + This package allows users to calculate the number of + under-five child deaths caused by consumption of poor quality + antimalarials across 39 sub-Saharan nations. The package supports one + function, that starts an interactive web tool created using + the shiny R package. The web tool runs locally on the user's machine. + The web tool allows users to set input parameters (prevalence of poor + quality antimalarials, case fatality rate of children who take poor + quality antimalarials, and sample size) which are then used to perform + an uncertainty analysis following the Latin hypercube + sampling scheme. Users can download the output figures as PDFs, and the + output data as CSVs. Users can also download their input parameters + for reference. This package was designed to accompany the analysis + presented in: + J. Patrick Renschler, Kelsey Walters, Paul Newton, Ramanan Laxminarayan + "Estimated under-five deaths associated with poor-quality + antimalarials in sub-Saharan Africa", 2014. Paper submitted. + date_publication: '2014-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pqantimalarials + url_git: '' +pql: + version: 0.1.0 + title: |- + A Partitioned Quasi-Likelihood for Distributed Statistical + Inference + maintainer: Guangbao Guo + description: In the big data setting, working data sets are often distributed on + multiple machines. However, classical statistical methods are often developed + to solve the problems of single estimation or inference. We employ a novel parallel + quasi-likelihood method in generalized linear models, to make the variances between + different sub-estimators relatively similar. Estimates are obtained from projection + subsets of data and later combined by suitably-chosen unknown weights. The philosophy + of the package is described in Guo G. (2020) . + date_publication: '2024-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pql + url_git: '' +PQLseq: + version: 1.2.1 + title: |- + Efficient Mixed Model Analysis of Count Data in Large-Scale + Genomic Sequencing Studies + maintainer: Jiaqiang Zhu + description: An efficient tool designed for differential analysis of large-scale + RNA sequencing (RNAseq) data and Bisulfite sequencing (BSseq) data in the presence + of individual relatedness and population structure. 'PQLseq' first fits a Generalized + Linear Mixed Model (GLMM) with adjusted covariates, predictor of interest and + random effects to account for population structure and individual relatedness, + and then performs Wald tests for each gene in RNAseq or site in BSseq. + date_publication: '2021-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PQLseq + url_git: '' +pqrBayes: + version: 1.1.1 + title: Bayesian Penalized Quantile Regression + maintainer: Cen Wu + description: |- + Bayesian regularized quantile regression utilizing sparse priors to + impose exact sparsity leads to efficient Bayesian shrinkage estimation, variable + selection and statistical inference. In this package, we have implemented robust + Bayesian variable selection with spike-and-slab priors under high-dimensional + linear regression models (Fan et al. (2024) and + Ren et al. (2023) ), and regularized quantile varying + coefficient models (Zhou et al.(2023) ). In particular, + valid robust Bayesian inferences under both models in the presence of heavy-tailed errors + can be validated on finite samples. The Markov Chain Monte Carlo (MCMC) algorithms + of the proposed and alternative models are implemented in C++. + date_publication: '2025-02-23' + bug_reports: https://github.com/cenwu/pqrBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pqrBayes + url_git: https://github.com/cenwu/pqrBayes +pqrfe: + version: '1.1' + title: Penalized Quantile Regression with Fixed Effects + maintainer: Ian Meneghel Danilevicz + description: Quantile regression with fixed effects is a general model for longitudinal + data. Here we proposed to solve it by several methods. The estimation methods + include three loss functions as check, asymmetric least square and asymmetric + Huber functions; and three structures as simple regression, fixed effects and + fixed effects with penalized intercepts by LASSO. + date_publication: '2022-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pqrfe + url_git: '' +PRA: + version: 0.3.0 + title: Project Risk Analysis + maintainer: Paul Govan + description: |- + Data analysis for Project Risk Management via the Second Moment Method, + Monte Carlo Simulation, Contingency Analysis, Sensitivity Analysis, Earned Value Management, + Learning Curves, Design Structure Matrices, and more. + date_publication: '2024-08-20' + bug_reports: https://github.com/paulgovan/PRA/issues + url: https://paulgovan.github.io/PRA/ + url_cran: https://CRAN.R-project.org/package=PRA + url_git: https://github.com/paulgovan/PRA +praatpicture: + version: 1.4.0 + title: '''Praat Picture'' Style Plots of Acoustic Data' + maintainer: Rasmus Puggaard-Rode + description: Quickly and easily generate plots of acoustic data aligned with transcriptions + similar to those made in 'Praat' using either derived signals generated directly + in R with 'wrassp' or imported derived signals from 'Praat'. Provides easy and + fast out-of-the-box solutions but also a high extent of flexibility. Also provides + options for embedding audio in figures and animating figures. + date_publication: '2025-01-14' + bug_reports: https://github.com/rpuggaardrode/praatpicture/issues + url: '' + url_cran: https://CRAN.R-project.org/package=praatpicture + url_git: https://github.com/rpuggaardrode/praatpicture +prabclus: + version: 2.3-4 + title: |- + Functions for Clustering and Testing of Presence-Absence, + Abundance and Multilocus Genetic Data + maintainer: Christian Hennig + description: |- + Distance-based parametric bootstrap tests for clustering with + spatial neighborhood information. Some distance measures, + Clustering of presence-absence, abundance and multilocus genetic data + for species delimitation, nearest neighbor + based noise detection. Genetic distances between communities. + Tests whether various distance-based regressions + are equal. Try package?prabclus for on overview. + date_publication: '2024-09-24' + bug_reports: '' + url: https://www.unibo.it/sitoweb/christian.hennig/en/ + url_cran: https://CRAN.R-project.org/package=prabclus + url_git: '' +pracma: + version: 2.4.4 + title: Practical Numerical Math Functions + maintainer: Hans W. Borchers + description: |2- + + Provides a large number of functions from numerical analysis and + linear algebra, numerical optimization, differential equations, + time series, plus some well-known special mathematical functions. + Uses 'MATLAB' function names where appropriate to simplify porting. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pracma + url_git: '' +pracpac: + version: 0.2.0 + title: Practical 'R' Packaging in 'Docker' + maintainer: VP Nagraj + description: Streamline the creation of 'Docker' images with 'R' packages and dependencies + embedded. The 'pracpac' package provides a 'usethis'-like interface to creating + Dockerfiles with dependencies managed by 'renv'. The 'pracpac' functionality is + described in Nagraj and Turner (2023) . + date_publication: '2023-06-18' + bug_reports: https://github.com/signaturescience/pracpac/issues + url: https://signaturescience.github.io/pracpac/ + url_cran: https://CRAN.R-project.org/package=pracpac + url_git: https://github.com/signaturescience/pracpac/ +PracticalEquiDesign: + version: 0.0.3 + title: Design of Practical Equivalence Trials + maintainer: Zachary McCaw + description: Sample size calculations for practical equivalence trial design with + a time to event endpoint. + date_publication: '2021-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PracticalEquiDesign + url_git: '' +practicalSigni: + version: 0.1.2 + title: Practical Significance Ranking of Regressors and Exact t Density + maintainer: Hrishikesh Vinod + description: |- + Consider a possibly nonlinear nonparametric regression + with p regressors. We provide evaluations by 13 methods to rank + regressors by their practical significance or importance using + various methods, including machine learning tools. Comprehensive + methods are as follows. + m6=Generalized partial correlation coefficient or + GPCC by Vinod (2021) and + Vinod (2022). + m7= a generalization of psychologists' effect size incorporating + nonlinearity and many variables. + m8= local linear partial (dy/dxi) using the 'np' package for kernel + regressions. + m9= partial (dy/dxi) using the 'NNS' package. + m10= importance measure using the 'NNS' boost function. + m11= Shapley Value measure of importance (cooperative game theory). + m12 and m13= two versions of the random forest algorithm. + Taraldsen's exact density for sampling distribution of correlations added. + date_publication: '2023-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=practicalSigni + url_git: '' +PracTools: + version: '1.5' + title: Designing and Weighting Survey Samples + maintainer: Richard Valliant + description: Functions and datasets to support Valliant, Dever, and Kreuter (2018), + , "Practical Tools for Designing and Weighting + Survey Samples". Contains functions for sample size calculation for survey samples + using stratified or clustered one-, two-, and three-stage sample designs, and + single-stage audit sample designs. Functions are included that will group geographic + units accounting for distances apart and measures of size. Other functions compute + variance components for multistage designs and sample sizes in two-phase designs. + A number of example data sets are included. + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PracTools + url_git: '' +prais: + version: 1.1.3 + title: Prais-Winsten Estimator for AR(1) Serial Correlation + maintainer: Franz X. Mohr + description: The Prais-Winsten estimator (Prais & Winsten, 1954) takes into account + AR(1) serial correlation of the errors in a linear regression model. The procedure + recursively estimates the coefficients and the error autocorrelation of the specified + model until sufficient convergence of the AR(1) coefficient is attained. + date_publication: '2024-11-25' + bug_reports: https://github.com/franzmohr/prais/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prais + url_git: https://github.com/franzmohr/prais +praise: + version: 1.0.0 + title: Praise Users + maintainer: Gabor Csardi + description: |- + Build friendly R packages that + praise their users if they have done something + good, or they just need it to feel better. + date_publication: '2015-08-11' + bug_reports: https://github.com/gaborcsardi/praise/issues + url: '' + url_cran: https://CRAN.R-project.org/package=praise + url_git: https://github.com/gaborcsardi/praise +PRANA: + version: 1.0.6 + title: Pseudo-Value Regression Approach for Network Analysis (PRANA) + maintainer: Seungjun Ahn + description: A novel pseudo-value regression approach for the differential co-expression + network analysis in expression data, which can incorporate additional clinical + variables in the model. This is a direct regression modeling for the differential + network analysis, and it is therefore computationally amenable for the most users. + The full methodological details can be found in Ahn S et al (2023) . + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRANA + url_git: '' +praznik: + version: 11.0.0 + title: Tools for Information-Based Feature Selection and Scoring + maintainer: Miron B. Kursa + description: |- + A toolbox of fast, native and parallel implementations of various information-based importance criteria estimators and feature selection filters based on them, inspired by the overview by Brown, Pocock, Zhao and Lujan (2012) . + Contains, among other, minimum redundancy maximal relevancy ('mRMR') method by Peng, Long and Ding (2005) ; joint mutual information ('JMI') method by Yang and Moody (1999) ; double input symmetrical relevance ('DISR') method by Meyer and Bontempi (2006) as well as joint mutual information maximisation ('JMIM') method by Bennasar, Hicks and Setchi (2015) . + date_publication: '2022-05-20' + bug_reports: https://gitlab.com/mbq/praznik/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=praznik + url_git: https://gitlab.com/mbq/praznik +prcbench: + version: 1.1.8 + title: Testing Workbench for Precision-Recall Curves + maintainer: Takaya Saito + description: |- + A testing workbench to evaluate tools that calculate precision-recall curves. + Saito and Rehmsmeier (2015) . + date_publication: '2023-03-12' + bug_reports: https://github.com/evalclass/prcbench/issues + url: https://evalclass.github.io/prcbench/ + url_cran: https://CRAN.R-project.org/package=prcbench + url_git: https://github.com/evalclass/prcbench +prclust: + version: '1.3' + title: Penalized Regression-Based Clustering Method + maintainer: Chong Wu + description: Clustering is unsupervised and exploratory in nature. Yet, it can be + performed through penalized regression with grouping pursuit. In this package, + we provide two algorithms for fitting the penalized regression-based clustering + (PRclust) with non-convex grouping penalties, such as group truncated lasso, MCP + and SCAD. One algorithm is based on quadratic penalty and difference convex method. + Another algorithm is based on difference convex and ADMM, called DC-ADD, which + is more efficient. Generalized cross validation and stability based method were + provided to select the tuning parameters. Rand index, adjusted Rand index and + Jaccard index were provided to estimate the agreement between estimated cluster + memberships and the truth. + date_publication: '2016-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prclust + url_git: '' +prcr: + version: 0.2.1 + title: Person-Centered Analysis + maintainer: Joshua M Rosenberg + description: Provides an easy-to-use yet adaptable set of tools to conduct person-center + analysis using a two-step clustering procedure. As described in Bergman and El-Khouri + (1999) , + hierarchical clustering is performed to determine the initial partition for the + subsequent k-means clustering procedure. + date_publication: '2020-02-09' + bug_reports: https://github.com/jrosen48/prcr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prcr + url_git: https://github.com/jrosen48/prcr +PRDA: + version: 1.0.0 + title: Conduct a Prospective or Retrospective Design Analysis + maintainer: Claudio Zandonella Callegher + description: |- + An implementation of the "Design Analysis" proposed by + Gelman and Carlin (2014) . It combines + the evaluation of Power-Analysis with other inferential-risks as + Type-M error (i.e. Magnitude) and Type-S error (i.e. Sign). See also + Altoè et al. (2020) and + Bertoldo et al. (2020) . + date_publication: '2020-12-08' + bug_reports: https://github.com/ClaudioZandonella/PRDA/issues + url: https://claudiozandonella.github.io/PRDA/ + url_cran: https://CRAN.R-project.org/package=PRDA + url_git: https://github.com/ClaudioZandonella/PRDA +pre: + version: 1.0.7 + title: Prediction Rule Ensembles + maintainer: Marjolein Fokkema + description: |- + Derives prediction rule ensembles (PREs). Largely follows the + procedure for deriving PREs as described in Friedman & Popescu (2008; + ), with adjustments and improvements. The + main function pre() derives prediction rule ensembles consisting of + rules and/or linear terms for continuous, binary, count, multinomial, + and multivariate continuous responses. Function gpe() derives + generalized prediction ensembles, consisting of rules, hinge and linear + functions of the predictor variables. + date_publication: '2024-01-12' + bug_reports: https://github.com/marjoleinF/pre/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pre + url_git: https://github.com/marjoleinF/pre +PRECAST: + version: 1.6.5 + title: Embedding and Clustering with Alignment for Spatial Datasets + maintainer: Wei Liu + description: An efficient data integration method is provided for multiple spatial + transcriptomics data with non-cluster-relevant effects such as the complex batch + effects. It unifies spatial factor analysis simultaneously with spatial clustering + and embedding alignment, requiring only partially shared cell/domain clusters + across datasets. More details can be referred to Wei Liu, et al. (2023) . + date_publication: '2024-03-19' + bug_reports: https://github.com/feiyoung/PRECAST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PRECAST + url_git: https://github.com/feiyoung/PRECAST +precintcon: + version: 2.3.0 + title: Precipitation Intensity, Concentration and Anomaly Analysis + maintainer: Lucas Venezian Povoa + description: |- + It contains functions to analyze the precipitation + intensity, concentration and anomaly. + date_publication: '2016-07-17' + bug_reports: https://github.com/lucasvenez/precintcon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=precintcon + url_git: https://github.com/lucasvenez/precintcon +pRecipe: + version: 3.0.2 + title: Precipitation R Recipes + maintainer: Mijael Rodrigo Vargas Godoy + description: |- + An open-access tool/framework to download, validate, visualize, and + analyze multi-source precipitation data. More information and an example of + implementation can be found in Vargas Godoy and Markonis (2023, + ). + date_publication: '2024-12-07' + bug_reports: https://github.com/MiRoVaGo/pRecipe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pRecipe + url_git: https://github.com/MiRoVaGo/pRecipe +precisely: + version: 0.1.2 + title: Estimate Sample Size Based on Precision Rather than Power + maintainer: Malcolm Barrett + description: |- + Estimate sample size based on precision rather than power. + 'precisely' is a study planning tool to calculate sample size based on + precision. Power calculations are focused on whether or not an + estimate will be statistically significant; calculations of precision + are based on the same principles as power calculation but turn the + focus to the width of the confidence interval. 'precisely' is based on + the work of 'Rothman and Greenland' (2018). + date_publication: '2021-10-10' + bug_reports: https://github.com/malcolmbarrett/precisely/issues + url: '' + url_cran: https://CRAN.R-project.org/package=precisely + url_git: https://github.com/malcolmbarrett/precisely +precisePlacement: + version: 0.1.0 + title: |- + Suite of Functions to Help Get Plot Elements Exactly Where You + Want Them + maintainer: Jasper Watson + description: Provides a selection of tools that make it easier to place elements + onto a (base R) plot exactly where you want them. It allows users to identify + points and distances on a plot in terms of inches, pixels, margin lines, data + units, and proportions of the plotting space, all in a manner more simple than + manipulating par(). + date_publication: '2021-06-15' + bug_reports: https://github.com/rntq472/precisePlacement/issues + url: '' + url_cran: https://CRAN.R-project.org/package=precisePlacement + url_git: '' +PreciseSums: + version: '0.7' + title: Accurate Floating Point Sums and Products + maintainer: Matthew Fidler + description: |- + Most of the time floating point arithmetic does + approximately the right thing. When adding sums or having products + of numbers that greatly differ in magnitude, the floating point + arithmetic may be incorrect. This package implements the Kahan + (1965) sum , Neumaier (1974) sum + , pairwise-sum (adapted from 'NumPy', + See Castaldo (2008) for a discussion of + accuracy), and arbitrary precision sum (adapted from the fsum in + 'Python' ; Shewchuk (1997) + ). In addition, + products are changed to long double precision for accuracy, or + changed into a log-sum for accuracy. + date_publication: '2024-09-17' + bug_reports: https://github.com/nlmixr2/PreciseSums/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=PreciseSums + url_git: https://github.com/nlmixr2/PreciseSums +precmed: + version: 1.1.0 + title: Precision Medicine + maintainer: Thomas Debray + description: A doubly robust precision medicine approach to fit, cross-validate + and visualize prediction models for the conditional average treatment effect (CATE). + It implements doubly robust estimation and semiparametric modeling approach of + treatment-covariate interactions as proposed by Yadlowsky et al. (2020) . + date_publication: '2024-10-05' + bug_reports: https://github.com/smartdata-analysis-and-statistics/precmed/issues + url: https://smartdata-analysis-and-statistics.github.io/precmed/ + url_cran: https://CRAN.R-project.org/package=precmed + url_git: https://github.com/smartdata-analysis-and-statistics/precmed +precommit: + version: 0.4.3 + title: Pre-Commit Hooks + maintainer: Lorenz Walthert + description: |- + Useful git hooks for R building on top of the multi-language + framework 'pre-commit' for hook management. This package provides git + hooks for common tasks like formatting files with 'styler' or spell + checking as well as wrapper functions to access the 'pre-commit' + executable. + date_publication: '2024-07-22' + bug_reports: '' + url: https://lorenzwalthert.github.io/precommit/ + url_cran: https://CRAN.R-project.org/package=precommit + url_git: https://github.com/lorenzwalthert/precommit +precondition: + version: 0.1.0 + title: Lightweight Precondition, Postcondition, and Sanity Checks + maintainer: Taras Zakharko + description: |- + Implements fast, safe, and customizable assertions routines, which + can be used in place of base::stopifnot(). + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=precondition + url_git: '' +precrec: + version: 0.14.4 + title: |- + Calculate Accurate Precision-Recall and ROC (Receiver Operator + Characteristics) Curves + maintainer: Takaya Saito + description: |- + Accurate calculations and visualization of precision-recall and ROC (Receiver Operator Characteristics) + curves. Saito and Rehmsmeier (2015) . + date_publication: '2023-10-11' + bug_reports: https://github.com/evalclass/precrec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=precrec + url_git: https://github.com/evalclass/precrec +PredCRG: + version: 1.0.2 + title: Computational Prediction of Proteins Encoded by Circadian Genes + maintainer: Prabina Kumar Meher + description: A computational model for predicting proteins encoded by circadian + genes. The support vector machine has been employed with Laplace kernel for prediction + of circadian proteins, where compositional, transitional and physico-chemical + features were utilized as numeric features. User can predict for the test dataset + using the proposed computational model. Besides, the user can also build their + own training model using their training dataset, followed by prediction for the + test set. + date_publication: '2020-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PredCRG + url_git: '' +predfairness: + version: 0.1.0 + title: Discrimination Mitigation for Machine Learning Models + maintainer: Thaís de Bessa Gontijo de Oliveira + description: |- + Based on different statistical definitions of discrimination, several methods have been proposed to detect and mitigate social inequality in machine learning models. + This package aims to provide an alternative to fairness treatment in predictive models. The ROC method implemented in this package + is described by Kamiran, Karim and Zhang (2012) . + date_publication: '2021-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predfairness + url_git: '' +predhy: + version: 2.1.1 + title: Genomic Prediction of Hybrid Performance + maintainer: Yang Xu + description: Performs genomic prediction of hybrid performance using eight GS methods + including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, LightGBM and XGBoost. + It also provides fast cross-validation and mating design scheme for training population + (Xu S et al (2016) ; Xu S (2017) ). + date_publication: '2024-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predhy + url_git: '' +predhy.GUI: + version: 2.0.1 + title: |- + Genomic Prediction of Hybrid Performance with Graphical User + Interface + maintainer: Yuxiang Zhang + description: |- + Performs genomic prediction of hybrid performance using eight GS methods including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, XGBoost and LightGBM. + GBLUP: genomic best liner unbiased prediction, RKHS: reproducing kernel Hilbert space, PLS: partial least squares regression, LASSO: least absolute shrinkage and selection operator, XGBoost: extreme gradient boosting, LightGBM: light gradient boosting machine. + It also provides fast cross-validation and mating design scheme for training population (Xu S et al (2016) ; Xu S (2017) ). + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predhy.GUI + url_git: '' +predict3d: + version: 0.1.5 + title: Draw Three Dimensional Predict Plot Using Package 'rgl' + maintainer: Keon-Woong Moon + description: |- + Draw 2 dimensional and three dimensional plot for multiple regression models using package 'ggplot2' and 'rgl'. + Supports linear models (lm), generalized linear models (glm) and local polynomial regression fittings (loess). + date_publication: '2024-04-05' + bug_reports: https://github.com/cardiomoon/predict3d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=predict3d + url_git: https://github.com/cardiomoon/predict3d +PredictABEL: + version: 1.2-4 + title: Assessment of Risk Prediction Models + maintainer: Suman Kundu + description: |- + We included functions to assess the performance of + risk models. The package contains functions for the various measures that are + used in empirical studies, including univariate and multivariate odds ratios + (OR) of the predictors, the c-statistic (or area under the receiver operating + characteristic (ROC) curve (AUC)), Hosmer-Lemeshow goodness of fit test, + reclassification table, net reclassification improvement (NRI) and + integrated discrimination improvement (IDI). Also included are functions + to create plots, such as risk distributions, ROC curves, calibration plot, + discrimination box plot and predictiveness curves. In addition to functions + to assess the performance of risk models, the package includes functions to + obtain weighted and unweighted risk scores as well as predicted risks using + logistic regression analysis. These logistic regression functions are + specifically written for models that include genetic variables, but they + can also be applied to models that are based on non-genetic risk factors only. + Finally, the package includes function to construct a simulated dataset with + genotypes, genetic risks, and disease status for a hypothetical population, which + is used for the evaluation of genetic risk models. + date_publication: '2020-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PredictABEL + url_git: '' +prediction: + version: 0.3.18 + title: Tidy, Type-Safe 'prediction()' Methods + maintainer: Ben Bolker + description: A one-function package containing prediction(), a type-safe alternative + to predict() that always returns a data frame. The summary() method provides a + data frame with average predictions, possibly over counterfactual versions of + the data (à la the margins command in 'Stata'). Marginal effect estimation is + provided by the related package, 'margins' . + The package currently supports common model types (e.g., lm, glm) from the 'stats' + package, as well as numerous other model classes from other add-on packages. See + the README file or main package documentation page for a complete listing. + date_publication: '2024-06-11' + bug_reports: https://github.com/bbolker/prediction/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prediction + url_git: https://github.com/bbolker/prediction +predictionInterval: + version: 1.0.0 + title: |- + Prediction Interval Functions for Assessing Replication Study + Results + maintainer: David Stanley + description: |- + A common problem faced by journal reviewers and authors is the question of + whether the results of a replication study are consistent with the original + published study. One solution to this problem is to examine the effect size + from the original study and generate the range of effect sizes that could + reasonably be obtained (due to random sampling) in a replication attempt + (i.e., calculate a prediction interval). This package has functions that calculate + the prediction interval for the correlation (i.e., r), + standardized mean difference (i.e., d-value), and mean. + date_publication: '2016-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predictionInterval + url_git: '' +PredictionR: + version: 1.0-12 + title: Prediction for Future Data from any Continuous Distribution + maintainer: Hadeer A. Ghonem + description: Functions to get prediction intervals and prediction points of future + observations from any continuous distribution. + date_publication: '2020-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PredictionR + url_git: '' +predictMe: + version: '0.1' + title: Visualize Individual Prediction Performance + maintainer: Marcel Miché + description: Enables researchers to visualize the prediction performance of any + algorithm on the individual level (or close to it), given that the predicted outcome + is either binary or continuous. Visual results are instantly comprehensible. + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predictMe + url_git: https://github.com/mmiche/predictMe +predictmeans: + version: 1.1.1 + title: Predicted Means for Linear and Semiparametric Models + maintainer: Dongwen Luo + description: |- + Providing functions to diagnose and make inferences from various linear models, + such as those obtained from 'aov', 'lm', 'glm', 'gls', 'lme', 'lmer', 'glmmTMB' and 'semireg'. + Inferences include predicted means and standard errors, contrasts, multiple comparisons, + permutation tests, adjusted R-square and graphs. + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predictmeans + url_git: '' +predictNMB: + version: 0.2.1 + title: Evaluate Clinical Prediction Models by Net Monetary Benefit + maintainer: Rex Parsons + description: |- + Estimates when and where a model-guided treatment strategy may + outperform a treat-all or treat-none approach by Monte Carlo simulation and + evaluation of the Net Monetary Benefit. Details can be viewed in + Parsons et al. (2023) . + date_publication: '2023-06-03' + bug_reports: https://github.com/ropensci/predictNMB/issues + url: https://docs.ropensci.org/predictNMB/ + url_cran: https://CRAN.R-project.org/package=predictNMB + url_git: '' +predictoR: + version: 4.1.1 + title: Predictive Data Analysis System + maintainer: Oldemar Rodriguez + description: Perform a supervised data analysis on a database through a 'shiny' + graphical interface. It includes methods such as K-Nearest Neighbors, Decision + Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, + Deep Learning, Support Vector Machines and Bayesian Methods. + date_publication: '2024-10-31' + bug_reports: https://github.com/PROMiDAT/predictoR/issues + url: https://promidat.website/ + url_cran: https://CRAN.R-project.org/package=predictoR + url_git: '' +PredictorSelect: + version: 0.1.0 + title: |- + Out-of-Sample Predictability in Predictive Regressions with Many + Predictor Candidates + maintainer: Rong Peng + description: Consider a linear predictive regression setting with a potentially + large set of candidate predictors. This work is concerned with detecting the presence + of out of sample predictability based on out of sample mean squared error comparisons + given in Gonzalo and Pitarakis (2023) . + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PredictorSelect + url_git: '' +predictrace: + version: 2.0.1 + title: |- + Predict the Race and Gender of a Given Name Using Census and + Social Security Administration Data + maintainer: Jacob Kaplan + description: |- + Predicts the most common race of a surname and based on U.S. Census + data, and the most common first named based on U.S. Social Security Administration data. + date_publication: '2023-07-05' + bug_reports: https://github.com/jacobkap/predictrace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=predictrace + url_git: https://github.com/jacobkap/predictrace +predicts: + version: 0.1-17 + title: Spatial Prediction Tools + maintainer: Robert J. Hijmans + description: Methods for spatial predictive modeling, especially for spatial distribution + models. This includes algorithms for model fitting and prediction, as well as + methods for model evaluation. + date_publication: '2024-11-23' + bug_reports: https://github.com/rspatial/predicts/issues/ + url: https://rspatial.org/sdm/ + url_cran: https://CRAN.R-project.org/package=predicts + url_git: '' +predieval: + version: 0.1.1 + title: |- + Assessing Performance of Prediction Models for Predicting + Patient-Level Treatment Benefit + maintainer: Orestis Efthimiou + description: Methods for assessing the performance of a prediction model with respect + to identifying patient-level treatment benefit. All methods are applicable for + continuous and binary outcomes, and for any type of statistical or machine-learning + prediction model as long as it uses baseline covariates to predict outcomes under + treatment and control. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predieval + url_git: https://github.com/esm-ispm-unibe-ch/predieval +predint: + version: 2.2.1 + title: Prediction Intervals + maintainer: Max Menssen + description: |- + An implementation of prediction intervals for overdispersed count data, + for overdispersed binomial data and for linear random effects models. + date_publication: '2024-03-04' + bug_reports: https://github.com/MaxMenssen/predint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=predint + url_git: https://github.com/MaxMenssen/predint +predkmeans: + version: 0.1.1 + title: Covariate Adaptive Clustering + maintainer: Joshua Keller + description: Implements the predictive k-means method for clustering observations, + using a mixture of experts model to allow covariates to influence cluster centers. + Motivated by air pollution epidemiology settings, where cluster membership needs + to be predicted across space. Includes functions for predicting cluster membership + using spatial splines and principal component analysis (PCA) scores using either + multinomial logistic regression or support vector machines (SVMs). For method + details see Keller et al. (2017) . + date_publication: '2019-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predkmeans + url_git: '' +PredPsych: + version: '0.4' + title: Predictive Approaches in Psychology + maintainer: Atesh Koul + description: |2- + + Recent years have seen an increased interest in novel methods + for analyzing quantitative data from experimental psychology. Currently, however, they lack an + established and accessible software framework. Many existing implementations provide no guidelines, + consisting of small code snippets, or sets of packages. In addition, the use of existing packages + often requires advanced programming experience. 'PredPsych' is a user-friendly toolbox based on + machine learning predictive algorithms. It comprises of multiple functionalities for multivariate + analyses of quantitative behavioral data based on machine learning models. + date_publication: '2019-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PredPsych + url_git: '' +predReliability: + version: 0.1.0 + title: |- + Estimates Reliability of Individual Supervised Learning + Predictions + maintainer: Simon Cof + description: |- + An implementation of reliability estimation methods described in the paper (Bosnic, Z., & Kononenko, I. (2008) ), which allows you to test the reliability of a single predicted instance made + by your model and prediction function. It also allows you to make a correlation test to estimate which reliability estimate is the most + accurate for your model. + date_publication: '2020-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predReliability + url_git: '' +predRupdate: + version: 0.2.0 + title: Prediction Model Validation and Updating + maintainer: Glen P. Martin + description: |- + Evaluate the predictive performance of an existing (i.e. previously + developed) prediction/ prognostic model given relevant information about the + existing prediction model (e.g. coefficients) and a new dataset. Provides a + range of model updating methods that help tailor the existing model to the + new dataset; see Su et al. (2018) . Techniques + to aggregate multiple existing prediction models on the new data are also + provided; see Debray et al. (2014) and Martin et al. + (2018) ). + date_publication: '2024-08-23' + bug_reports: https://github.com/GlenMartin31/predRupdate/issues + url: https://glenmartin31.github.io/predRupdate/ + url_cran: https://CRAN.R-project.org/package=predRupdate + url_git: https://github.com/GlenMartin31/predRupdate +PredTest: + version: 0.1.0 + title: Preparing Data For, and Calculating the Prediction Test + maintainer: Neal Montgomery + description: Global hypothesis tests combine information across multiple endpoints + to test a single hypothesis. The prediction test is a recently proposed global + hypothesis test with good performance for small sample sizes and many endpoints + of interest. The test is also flexible in the types and combinations of expected + results across the individual endpoints. This package provides functions for data + processing and calculation of the prediction test. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PredTest + url_git: '' +predtools: + version: 0.0.3 + title: Prediction Model Tools + maintainer: Amin Adibi + description: Provides additional functions for evaluating predictive models, including + plotting calibration curves and model-based Receiver Operating Characteristic + (mROC) based on Sadatsafavi et al (2021) . + date_publication: '2023-06-05' + bug_reports: https://github.com/resplab/predtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=predtools + url_git: https://github.com/resplab/predtools +predtoolsTS: + version: 0.1.1 + title: Time Series Prediction Tools + maintainer: Alberto Vico Moreno + description: |- + Makes the time series prediction easier by automatizing this process + using four main functions: prep(), modl(), pred() and postp(). Features different + preprocessing methods to homogenize variance and to remove trend and seasonality. + Also has the potential to bring together different predictive models to make comparatives. + Features ARIMA and Data Mining Regression models (using caret). + date_publication: '2018-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=predtoolsTS + url_git: https://github.com/avm00016/predtoolsTS +pref: + version: 0.4.0 + title: Preference Voting with Explanatory Graphics + maintainer: Denis Mollison + description: |- + Implements the Single Transferable Vote (STV) electoral system, with + clear explanatory graphics. The core function stv() uses Meek's method, the purest + expression of the simple principles of STV, but which requires electronic + counting. It can handle votes expressing equal preferences for subsets of + the candidates. A function stv.wig() implementing the Weighted Inclusive + Gregory method, as used in Scottish council elections, is also provided, + and with the same options, as described in the manual. The required vote + data format is as an R list: a function pref.data() is provided to transform + some commonly used data formats into this format. + References for methodology: + Hill, Wichmann and Woodall (1987) , + Hill, David (2006) , + Mollison, Denis (2023) , + (see also the package manual pref_pkg_manual.pdf). + date_publication: '2024-02-02' + bug_reports: https://github.com/denismollison/pref/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pref + url_git: https://github.com/denismollison/pref +prefeR: + version: 0.1.3 + title: R Package for Pairwise Preference Elicitation + maintainer: John Lepird + description: |- + Allows users to derive multi-objective weights from pairwise comparisons, which + research shows is more repeatable, transparent, and intuitive other techniques. These weights + can be rank existing alternatives or to define a multi-objective utility function for optimization. + date_publication: '2022-04-24' + bug_reports: '' + url: https://jlepird.github.io/prefeR/ + url_cran: https://CRAN.R-project.org/package=prefeR + url_git: https://github.com/jlepird/prefeR +preference: + version: 1.1.6 + title: 2-Stage Preference Trial Design and Analysis + maintainer: Michael Kane + description: |- + Design and analyze two-stage randomized trials with a continuous + outcome measure. The package contains functions to compute the required + sample size needed to detect a given preference, treatment, and selection + effect; alternatively, the package contains functions that can report the + study power given a fixed sample size. Finally, analysis functions are + provided to test each effect using either summary data (i.e. means, + variances) or raw study data . + date_publication: '2020-09-09' + bug_reports: https://github.com/kaneplusplus/preference/issues + url: '' + url_cran: https://CRAN.R-project.org/package=preference + url_git: https://github.com/kaneplusplus/preference +prefmod: + version: 0.8-36 + title: Utilities to Fit Paired Comparison Models for Preferences + maintainer: Marco Johannes Maier + description: Generates design matrix for analysing real paired comparisons and derived + paired comparison data (Likert type items/ratings or rankings) using a loglinear + approach. Fits loglinear Bradley-Terry model (LLBT) exploiting an eliminate feature. + Computes pattern models for paired comparisons, rankings, and ratings. Some treatment + of missing values (MCAR and MNAR). Fits latent class (mixture) models for paired + comparison, rating and ranking patterns using a non-parametric ML approach. + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prefmod + url_git: '' +PreKnitPostHTMLRender: + version: 0.1.0 + title: Pre-Knitting Processing and Post HTML-Rendering Processing + maintainer: Chin Soon Lim + description: Dynamize headers or R code within 'Rmd' files to prevent proliferation + of 'Rmd' files for similar reports. Add in external HTML document within 'rmarkdown' + rendered HTML doc. + date_publication: '2016-06-06' + bug_reports: https://github.com/chinsoon12/PreKnitPostHTMLRender + url: '' + url_cran: https://CRAN.R-project.org/package=PreKnitPostHTMLRender + url_git: https://github.com/chinsoon12/PreKnitPostHTMLRender +PReMiuM: + version: 3.2.13 + title: Dirichlet Process Bayesian Clustering, Profile Regression + maintainer: Silvia Liverani + description: Bayesian clustering using a Dirichlet process mixture model. This model + is an alternative to regression models, non-parametrically linking a response + vector to covariate data through cluster membership. The package allows Bernoulli, + Binomial, Poisson, Normal, survival and categorical response, as well as Normal + and discrete covariates. It also allows for fixed effects in the response model, + where a spatial CAR (conditional autoregressive) term can be also included. Additionally, + predictions may be made for the response, and missing values for the covariates + are handled. Several samplers and label switching moves are implemented along + with diagnostic tools to assess convergence. A number of R functions for post-processing + of the output are also provided. In addition to fitting mixtures, it may additionally + be of interest to determine which covariates actively drive the mixture components. + This is implemented in the package as variable selection. The main reference for + the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) . + date_publication: '2024-01-09' + bug_reports: '' + url: https://www.silvialiverani.com/software/ + url_cran: https://CRAN.R-project.org/package=PReMiuM + url_git: '' +prenoms: + version: 0.0.1 + title: Names Given to Babies in Quebec Between 1980 and 2020 + maintainer: Marc-Andre Desautels + description: |- + A database containing the names + of the babies born in Quebec between 1980 and 2020. + date_publication: '2021-04-27' + bug_reports: https://github.com/desautm/prenoms/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prenoms + url_git: +prepdat: + version: 1.0.8 + title: Preparing Experimental Data for Statistical Analysis + maintainer: Ayala S. Allon + description: |- + Prepares data for statistical analysis (e.g., analysis of variance + ;ANOVA) by enabling the user to easily and quickly merge (using the + file_merge() function) raw data files into one merged table and then + aggregate the merged table (using the prep() function) into a finalized + table while keeping track and summarizing every step of the preparation. + The finalized table contains several possibilities for dependent measures of + the dependent variable. Most suitable when measuring variables in an + interval or ratio scale (e.g., reaction-times) and/or discrete values such + as accuracy. Main functions included are file_merge() and prep(). The + file_merge() function vertically merges individual data files (in a long + format) in which each line is a single observation to one single dataset. + The prep() function aggregates the single dataset according to any + combination of grouping variables (i.e., between-subjects and + within-subjects independent variables, respectively), and returns a data + frame with a number of dependent measures for further analysis for each cell + according to the combination of provided grouping variables. Dependent + measures for each cell include among others means before and after rejecting + all values according to a flexible standard deviation criteria, number of + rejected values according to the flexible standard deviation criteria, + proportions of rejected values according to the flexible standard deviation + criteria, number of values before rejection, means after rejecting values + according to procedures described in Van Selst & Jolicoeur (1994; suitable + when measuring reaction-times), standard deviations, medians, means according + to any percentile (e.g., 0.05, 0.25, 0.75, 0.95) and harmonic means. The data + frame prep() returns can also be exported as a txt file to be used for + statistical analysis in other statistical programs. + date_publication: '2016-09-23' + bug_reports: http://github.com/ayalaallon/prepdat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prepdat + url_git: http://github.com/ayalaallon/prepdat +pRepDesigns: + version: 1.2.0 + title: Partially Replicated (p-Rep) Designs + maintainer: Vinaykumar L.N. + description: |- + Early generation breeding trials are to be conducted in multiple + environments where it may not be possible to replicate all the + lines in each environment due to scarcity of resources. For such + situations, partially replicated (p-Rep) designs have wide + application potential as only a proportion of the test lines are + replicated at each environment. A collection of several utility + functions related to p-Rep designs have been developed. Here, the + package contains six functions for a complete stepwise analytical + study of these designs. Five functions pRep1(), pRep2(), pRep3(), + pRep4() and pRep5(), are used to generate five new series of p-Rep + designs and also compute average variance factors and canonical + efficiency factors of generated designs. A fourth function NCEV() + is used to generate incidence matrix (N), information matrix (C), + canonical efficiency factor (E) and average variance factor (V). + This function is general in nature and can be used for studying the + characterization properties of any block design. A construction + procedure for p-Rep designs was given by Williams et al.(2011) + which was tedious and time consuming. + Here, in this package, five different methods have been given to + generate p-Rep designs easily. + date_publication: '2024-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pRepDesigns + url_git: '' +prepplot: + version: 1.0-1 + title: Prepare Figure Region for Base Graphics + maintainer: Ulrike Groemping + description: A figure region is prepared, creating a plot region with suitable background + color, grid lines or shadings, and providing axes and labeling if not suppressed. + Subsequently, information carrying graphics elements can be added (points, lines, + barplot with add=TRUE and so forth). + date_publication: '2021-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prepplot + url_git: '' +PreProcess: + version: 3.1.7 + title: Basic Functions for Pre-Processing Microarrays + maintainer: Kevin R. Coombes + description: |- + Provides classes to pre-process microarray gene + expression data as part of the OOMPA collection of packages + described at . + date_publication: '2019-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PreProcess + url_git: http://oompa.r-forge.r-project.org/ +PreProcessing: + version: 0.1.0 + title: Various Preprocessing Transformations of Numeric Data Matrices + maintainer: Swamiji Pravedson + description: |- + Preprocess numeric data matrices into desired transformed representations. + Standardization, Unitization, Cubitization and adaptive intervals are offered. + date_publication: '2021-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PreProcessing + url_git: '' +PreProcessRecordLinkage: + version: 1.0.1 + title: Preprocessing Record Linkage + maintainer: Leila Marvian Mashhad + description: |- + In this record linkage package, data preprocessing has been meticulously executed + to cover a wide range of datasets, ensuring that variable names are standardized using synonyms. + This approach facilitates seamless data integration and analysis across various datasets. While users + have the flexibility to modify variable names, the system intelligently ensures that + changes are only permitted when they do not compromise data consistency or essential variable essence. + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PreProcessRecordLinkage + url_git: '' +PREPShiny: + version: 0.1.0 + title: Interactive Document for Preprocessing the Dataset + maintainer: Kartikeya Bolar + description: An interactive document for preprocessing the dataset using 'rmarkdown' + and 'shiny' packages. Runtime examples are provided in the package function as + well as at . + date_publication: '2019-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PREPShiny + url_git: '' +preputils: + version: 1.0.3 + title: Utilities for Preparation of Data Analysis + maintainer: Josef Frank + description: Miscellaneous small utilities are provided to mitigate issues with + messy, inconsistent or high dimensional data and help for preprocessing and preparing + analyses. + date_publication: '2020-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=preputils + url_git: '' +prereg: + version: 0.6.0 + title: R Markdown Templates to Preregister Scientific Studies + maintainer: Frederik Aust + description: Provides a collection of templates to author preregistration documents + for scientific studies in PDF format. + date_publication: '2022-01-20' + bug_reports: https://github.com/crsh/prereg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prereg + url_git: https://github.com/crsh/prereg +preregr: + version: 0.2.9 + title: |- + Specify (Pre)Registrations and Export Them Human- And + Machine-Readably + maintainer: Gjalt-Jorn Peters + description: |- + Preregistrations, or more generally, registrations, enable + explicit timestamped and (often but not necessarily publicly) frozen + documentation of plans and expectations as well as decisions and + justifications. In research, preregistrations are commonly used to + clearly document plans and facilitate justifications of deviations from + those plans, as well as decreasing the effects of publication bias by + enabling identification of research that was conducted but not published. + Like reporting guidelines, (pre)registration forms often have specific + structures that facilitate systematic reporting of important items. The + 'preregr' package facilitates specifying (pre)registrations in R and + exporting them to a human-readable format (using R Markdown partials or + exporting to an 'HTML' file) as well as human-readable embedded data + (using 'JSON'), as well as importing such exported (pre)registration + specifications from such embedded 'JSON'. + date_publication: '2023-05-05' + bug_reports: https://gitlab.com/r-packages/preregr/-/issues + url: https://preregr.opens.science + url_cran: https://CRAN.R-project.org/package=preregr + url_git: '' +PresenceAbsence: + version: 1.1.11 + title: Presence-Absence Model Evaluation + maintainer: Elizabeth Freeman + description: Provides a set of functions useful when evaluating the results of presence-absence + models. Package includes functions for calculating threshold dependent measures + such as confusion matrices, pcc, sensitivity, specificity, and Kappa, and produces + plots of each measure as the threshold is varied. It will calculate optimal threshold + choice according to a choice of optimization criteria. It also includes functions + to plot the threshold independent ROC curves along with the associated AUC (area + under the curve). + date_publication: '2023-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PresenceAbsence + url_git: '' +presens: + version: 2.1.0 + title: Interface for PreSens Fiber Optic Data + maintainer: Matthew A. Birk + description: |- + Makes output files from select PreSens Fiber Optic Oxygen + Transmitters easier to work with in R. See for more + information about PreSens (Precision Sensing GmbH). Note: this package is + neither created nor maintained by PreSens. + date_publication: '2016-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=presens + url_git: '' +presenter: + version: 0.1.2 + title: Present Data with Style + maintainer: Harrison Tietze + description: |- + Consists of custom wrapper functions using packages + 'openxlsx', 'flextable', and 'officer' to create highly formatted MS office friendly output of your data frames. + These viewer friendly outputs are intended to match expectations of professional looking presentations + in business and consulting scenarios. The functions are opinionated in the sense that they expect the input data + frame to have certain properties in order to take advantage of the automated formatting. + date_publication: '2023-02-02' + bug_reports: https://github.com/Harrison4192/presenter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=presenter + url_git: https://github.com/Harrison4192/presenter +presentes: + version: 0.1.0 + title: Registry of Victims of State Terrorism in Argentina + maintainer: Diego Kozlowski + description: |- + Compilation and digitalization of the official registry of victims of state terrorism in Argentina during the last + military coup. The original data comes from RUVTE-ILID (2019) and . The title, presentes, comes from present in spanish. + date_publication: '2019-11-05' + bug_reports: https://github.com/DiegoKoz/presentes/issues + url: https://diegokoz.github.io/presentes/ + url_cran: https://CRAN.R-project.org/package=presentes + url_git: '' +preseqR: + version: 4.0.0 + title: Predicting Species Accumulation Curves + maintainer: Chao Deng + description: Originally as an R version of Preseq , the + package has extended its functionality to predict the r-species accumulation curve + (r-SAC), which is the number of species represented at least r times as a function + of the sampling effort. When r = 1, the curve is known as the species accumulation + curve, or the library complexity curve in high-throughput genomic sequencing. + The package includes both parametric and nonparametric methods, as described by + Deng C, et al. (2018) . + date_publication: '2018-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=preseqR + url_git: '' +presize: + version: 0.3.7 + title: Precision Based Sample Size Calculation + maintainer: Alan G. Haynes + description: |- + Bland (2009) recommended to + base study sizes on the width of the confidence interval rather the power of + a statistical test. The goal of 'presize' is to provide functions for such + precision based sample size calculations. For a given sample size, the + functions will return the precision (width of the confidence interval), and + vice versa. + date_publication: '2023-02-27' + bug_reports: https://github.com/CTU-Bern/presize/issues + url: https://ctu-bern.github.io/presize/ + url_cran: https://CRAN.R-project.org/package=presize + url_git: https://github.com/CTU-Bern/presize +presmoothedTP: + version: 0.1.0 + title: |- + Presmoothed Landmark Aalen-Johansen Estimator of Transition + Probabilities for Complex Multi-State Models + maintainer: Gustavo Soutinho + description: |- + Multi-state models are essential tools in longitudinal data analysis. + One primary goal of these models is the estimation of transition + probabilities, a critical metric for predicting clinical prognosis + across various stages of diseases or medical conditions. Traditionally, + inference in multi-state models relies on the Aalen-Johansen (AJ) + estimator which is consistent under the Markov assumption. However, + in many practical applications, the Markovian nature of the process + is often not guaranteed, limiting the applicability of the AJ + estimator in more complex scenarios. This package extends the landmark Aalen-Johansen + estimator (Putter, H, Spitoni, C (2018) ) + incorporating presmoothing techniques described by Soutinho, + Meira-Machado and Oliveira (2020) , + offering a robust alternative for estimating transition probabilities + in non-Markovian multi-state models with multiple states and potential + reversible transitions. + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=presmoothedTP + url_git: '' +presmTP: + version: 1.1.0 + title: Methods for Transition Probabilities + maintainer: Gustavo Soutinho + description: |- + Provides a function for estimating the transition probabilities in an illness-death model. + The transition probabilities can be estimated from the unsmoothed landmark estimators developed + by de Una-Alvarez and Meira-Machado (2015) . + Presmoothed estimates can also be obtained through the use of a parametric family of binary + regression curves, such as logit, probit or cauchit. The additive logistic regression model + and nonparametric regression are also alternatives which have been implemented. + The idea behind the presmoothed landmark estimators is to use the presmoothing techniques + developed by Cao et al. (2005) in the + landmark estimation of the transition probabilities. + date_publication: '2019-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=presmTP + url_git: '' +PressPurt: + version: 1.0.2 + title: Indeterminacy of Networks via Press Perturbations + maintainer: David Koslicki + description: This is a computational package designed to identify the most sensitive + interactions within a network which must be estimated most accurately in order + to produce qualitatively robust predictions to a press perturbation. This is accomplished + by enumerating the number of sign switches (and their magnitude) in the net effects + matrix when an edge experiences uncertainty. The package produces data and visualizations + when uncertainty is associated to one or more edges in the network and according + to a variety of distributions. The software requires the network to be described + by a system of differential equations but only requires as input a numerical Jacobian + matrix evaluated at an equilibrium point. This package is based on Koslicki, D., + & Novak, M. (2017) . + date_publication: '2020-10-19' + bug_reports: https://github.com/dkoslicki/PressPurt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PressPurt + url_git: https://github.com/dkoslicki/PressPurt +pressuRe: + version: 0.2.5 + title: Imports, Processes, and Visualizes Biomechanical Pressure Data + maintainer: Scott Telfer + description: Allows biomechanical pressure data from a range of systems to be imported + and processed in a reproducible manner. Automatic and manual tools are included + to let the user define regions (masks) to be analyzed. Also includes functions + for visualizing and animating pressure data. Example methods are described in + Shi et al., (2022) , Lee et al., (2014) , + van der Zward et al., (2014) , Najafi et al., (2010) + , Cavanagh and Rodgers (1987) . + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pressuRe + url_git: https://github.com/Telfer/pressuRe +pretest: + version: '0.2' + title: |- + A Novel Approach to Predictive Accuracy Testing in Nested + Environments + maintainer: Rong Peng + description: This repository contains the codes for using the predictive accuracy + comparison tests developed in Pitarakis, J. (2023) . + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pretest + url_git: '' +prettifyAddins: + version: 2.6.1 + title: |- + 'RStudio' Addins to Prettify 'JavaScript', 'C++', 'Python', and + More + maintainer: Stéphane Laurent + description: |- + Provides 'RStudio' addins to prettify 'HTML', 'CSS', 'SCSS', + 'JavaScript', 'JSX', 'Markdown', 'C(++)', 'LaTeX', 'Python', 'Julia', + 'XML', 'Java', 'JSON', 'Ruby', and to reindent 'C(++)', 'Fortran', + 'Java', 'Julia', 'Python', 'SAS', 'Scala', 'Shell', 'SQL' and + "TypeScript". Two kinds of addins are provided: 'Prettify' and + 'Indent'. The 'Indent' addins only reindent the code, while the + 'Prettify' addins also modify the code, e.g. trailing semi-colons are + added to 'JavaScript' code when they are missing. + date_publication: '2023-09-14' + bug_reports: https://github.com/stla/prettifyAddins/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prettifyAddins + url_git: https://github.com/stla/prettifyAddins +prettyB: + version: 0.2.2 + title: Pretty Base Graphics + maintainer: Colin Gillespie + description: |- + Drop-in replacements for standard base graphics + functions. The replacements are prettier versions of the originals. + date_publication: '2021-02-10' + bug_reports: https://github.com/jumpingrivers/prettyB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prettyB + url_git: https://github.com/jumpingrivers/prettyB/ +prettycode: + version: 1.1.0 + title: Pretty Print R Code in the Terminal + maintainer: Gábor Csárdi + description: |- + Replace the standard print method for functions with one that + performs syntax highlighting, using ANSI colors, if the terminal + supports them. + date_publication: '2019-12-16' + bug_reports: https://github.com/r-lib/prettycode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prettycode + url_git: https://github.com/r-lib/prettycode#readme +PrettyCols: + version: 1.1.0 + title: Pretty Colour Palettes + maintainer: Nicola Rennie + description: Defines aesthetically pleasing colour palettes. + date_publication: '2024-06-19' + bug_reports: https://github.com/nrennie/PrettyCols/issues + url: https://nrennie.rbind.io/PrettyCols/ + url_cran: https://CRAN.R-project.org/package=PrettyCols + url_git: https://github.com/nrennie/PrettyCols +prettydoc: + version: 0.4.1 + title: Creating Pretty Documents from R Markdown + maintainer: Yixuan Qiu + description: |- + Creating tiny yet beautiful documents and vignettes from R + Markdown. The package provides the 'html_pretty' output format as an + alternative to the 'html_document' and 'html_vignette' engines that + convert R Markdown into HTML pages. Various themes and syntax highlight + styles are supported. + date_publication: '2021-01-10' + bug_reports: https://github.com/yixuan/prettydoc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prettydoc + url_git: https://github.com/yixuan/prettydoc +prettyglm: + version: 1.0.1 + title: Pretty Summaries of Generalized Linear Model Coefficients + maintainer: Jared Fowler + description: |- + One of the main advantages of using Generalised Linear Models + is their interpretability. The goal of 'prettyglm' is to provide a + set of functions which easily create beautiful coefficient summaries + which can readily be shared and explained. 'prettyglm' helps users + create coefficient summaries which include categorical base levels, + variable importance and type III p.values. 'prettyglm' also creates + beautiful relativity plots for categorical, continuous and splined + coefficients. + date_publication: '2023-09-06' + bug_reports: '' + url: https://jared-fowler.github.io/prettyglm/ + url_cran: https://CRAN.R-project.org/package=prettyglm + url_git: '' +prettyGraphs: + version: 2.1.6 + title: Publication-Quality Graphics + maintainer: Derek Beaton + description: |- + Simple and crisp publication-quality graphics for the ExPosition family of packages. + See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) . + date_publication: '2018-12-18' + bug_reports: https://github.com/derekbeaton/ExPosition-Family_OLD + url: '' + url_cran: https://CRAN.R-project.org/package=prettyGraphs + url_git: '' +prettymapr: + version: 0.2.5 + title: Scale Bar, North Arrow, and Pretty Margins in R + maintainer: Dewey Dunnington + description: |- + Automates the process of creating a scale bar and north arrow in + any package that uses base graphics to plot in R. Bounding box tools help find + and manipulate extents. Finally, there is a function to automate the process + of setting margins, plotting the map, scale bar, and north arrow, and resetting + graphic parameters upon completion. + date_publication: '2024-02-23' + bug_reports: https://github.com/paleolimbot/prettymapr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prettymapr + url_git: https://github.com/paleolimbot/prettymapr +prettyR: + version: 2.2-3 + title: Pretty Descriptive Stats + maintainer: Jim Lemon + description: |- + Functions for conventionally formatting descriptive stats, + reshaping data frames and formatting R output as HTML. + date_publication: '2019-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prettyR + url_git: '' +prettyunits: + version: 1.2.0 + title: Pretty, Human Readable Formatting of Quantities + maintainer: Gabor Csardi + description: |- + Pretty, human readable formatting of quantities. + Time intervals: '1337000' -> '15d 11h 23m 20s'. + Vague time intervals: '2674000' -> 'about a month ago'. + Bytes: '1337' -> '1.34 kB'. + Rounding: '99' with 3 significant digits -> '99.0' + p-values: '0.00001' -> '<0.0001'. + Colors: '#FF0000' -> 'red'. + Quantities: '1239437' -> '1.24 M'. + date_publication: '2023-09-24' + bug_reports: https://github.com/r-lib/prettyunits/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prettyunits + url_git: https://github.com/r-lib/prettyunits +prevalence: + version: 0.4.1 + title: Tools for Prevalence Assessment Studies + maintainer: Brecht Devleesschauwer + description: 'The prevalence package provides Frequentist and Bayesian methods for + prevalence assessment studies. IMPORTANT: the truePrev functions in the prevalence + package call on JAGS (Just Another Gibbs Sampler), which therefore has to be available + on the user''s system. JAGS can be downloaded from .' + date_publication: '2022-06-03' + bug_reports: https://github.com/brechtdv/prevalence/issues + url: http://prevalence.cbra.be/ + url_cran: https://CRAN.R-project.org/package=prevalence + url_git: '' +prevederer: + version: 0.0.1 + title: Wrapper for the 'Prevedere' API + maintainer: Wil Davis + description: |- + Easy and efficient access to the API provided by 'Prevedere', + an industry insights and predictive analytics company. Query and + download indicators, models and workbenches built with 'Prevedere' for further + analysis and reporting . + date_publication: '2019-07-23' + bug_reports: https://github.com/wkdavis/prevederer/issues + url: https://api.prevedere.com/index.html + url_cran: https://CRAN.R-project.org/package=prevederer + url_git: https://github.com/wkdavis/prevederer +preventr: + version: 0.11.0 + title: An Implementation of the PREVENT and Pooled Cohort Equations + maintainer: Martin Mayer + description: |- + Implements the American Heart Association Predicting + Risk of cardiovascular disease EVENTs (PREVENT) equations from Khan + SS, Matsushita K, Sang Y, and colleagues (2023) + , with optional comparison + with their de facto predecessor, the Pooled Cohort Equations from the + American Heart Association and American College of Cardiology (2013) + and the revision to the Pooled + Cohort Equations from Yadlowsky and colleagues (2018) + . + date_publication: '2025-01-26' + bug_reports: '' + url: https://martingmayer.com/preventr + url_cran: https://CRAN.R-project.org/package=preventr + url_git: https://github.com/martingmayer/preventr +previsionio: + version: 11.7.0 + title: '''Prevision.io'' R SDK' + maintainer: Florian Laroumagne + description: For working with the 'Prevision.io' AI model management platform's + API . + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=previsionio + url_git: '' +PrevMap: + version: 1.5.4 + title: Geostatistical Modelling of Spatially Referenced Prevalence Data + maintainer: Emanuele Giorgi + description: |- + Provides functions for both likelihood-based + and Bayesian analysis of spatially referenced prevalence data. For a tutorial on the use of the R package, see Giorgi and Diggle (2017) . + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PrevMap + url_git: '' +prevR: + version: 5.0.0 + title: |- + Estimating Regional Trends of a Prevalence from a DHS and + Similar Surveys + maintainer: Joseph Larmarange + description: |- + Spatial estimation of a prevalence surface + or a relative risks surface, using data from a Demographic and Health + Survey (DHS) or an analog survey, see Larmarange et al. (2011) + . + date_publication: '2023-05-15' + bug_reports: https://github.com/larmarange/prevR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prevR + url_git: https://github.com/larmarange/prevR/ +prevtoinc: + version: 0.12.0 + title: |- + Prevalence to Incidence Calculations for Point-Prevalence + Studies in a Nosocomial Setting + maintainer: Niklas Willrich + description: |- + Functions to simulate point prevalence studies (PPSs) of healthcare-associated infections (HAIs) and to convert prevalence to incidence in steady state setups. + Companion package to the preprint Willrich et al., From prevalence to incidence - a new approach in the hospital setting; + , where methods are explained in detail. + date_publication: '2019-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prevtoinc + url_git: '' +pRF: + version: '1.2' + title: Permutation Significance for Random Forests + maintainer: Ankur Chakravarthy + description: |- + Estimate False Discovery Rates (FDRs) for importance metrics from + random forest runs. + date_publication: '2016-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pRF + url_git: '' +PriceIndices: + version: 0.2.3 + title: Calculating Bilateral and Multilateral Price Indexes + maintainer: Jacek Białek + description: |- + Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020) + , Białek (2019) or Białek (2020) . + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PriceIndices + url_git: '' +pricelevels: + version: 1.3.0 + title: Spatial Price Level Comparisons + maintainer: Sebastian Weinand + description: Price comparisons within or between countries provide an overall measure + of the relative difference in prices, often denoted as price levels. This package + provides index number methods for such price comparisons (e.g., The World Bank, + 2011, ). Moreover, it contains functions for sampling + and characterizing price data. + date_publication: '2024-05-22' + bug_reports: https://github.com/sweinand/pricelevels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pricelevels + url_git: https://github.com/sweinand/pricelevels +priceR: + version: 1.0.2 + title: Economics and Pricing Tools + maintainer: Steve Condylios + description: |- + Functions to aid in micro and macro economic analysis and handling of price and + currency data. Includes extraction of relevant inflation and exchange rate data from World Bank + API, data cleaning/parsing, and standardisation. Inflation adjustment + calculations as found in Principles of Macroeconomics by Gregory Mankiw et al (2014). Current + and historical end of day exchange rates for 171 currencies from the European Central Bank + Statistical Data Warehouse (2020) . + date_publication: '2024-08-17' + bug_reports: https://github.com/stevecondylios/priceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=priceR + url_git: https://github.com/stevecondylios/priceR +pricesensitivitymeter: + version: 1.3.0 + title: Van Westendorp Price Sensitivity Meter Analysis + maintainer: Max Alletsee + description: |- + An implementation of the van Westendorp Price + Sensitivity Meter in R, which is a survey-based approach + to analyze consumer price preferences and sensitivity + (van Westendorp 1976, isbn:9789283100386). + date_publication: '2024-02-25' + bug_reports: https://github.com/max-alletsee/pricesensitivitymeter/issues + url: https://max-alletsee.github.io/pricesensitivitymeter/ + url_cran: https://CRAN.R-project.org/package=pricesensitivitymeter + url_git: https://github.com/max-alletsee/pricesensitivitymeter +prim: + version: 1.0.22 + title: Patient Rule Induction Method (PRIM) + maintainer: Tarn Duong + description: Patient Rule Induction Method (PRIM) for bump hunting in high-dimensional + data. + date_publication: '2024-11-28' + bug_reports: '' + url: https://www.mvstat.net/tduong/ + url_cran: https://CRAN.R-project.org/package=prim + url_git: '' +PRIMAL: + version: 1.0.2 + title: Parametric Simplex Method for Sparse Learning + maintainer: Zichong Li + description: Implements a unified framework of parametric simplex method for a variety + of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse + quantile regression, sparse support vector machines, and compressive sensing) + combined with efficient hyper-parameter selection strategies. The core algorithm + is implemented in C++ with Eigen3 support for portable high performance linear + algebra. For more details about parametric simplex method, see Haotian Pang (2017) + . + date_publication: '2020-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRIMAL + url_git: '' +primarycensored: + version: 1.1.0 + title: Primary Event Censored Distributions + maintainer: Sam Abbott + description: |- + Provides functions for working with primary + event censored distributions and 'Stan' implementations for use in Bayesian + modeling. Primary event censored distributions are useful for modeling + delayed reporting scenarios in epidemiology and other fields (Charniga et + al. (2024) ). It also provides support for + arbitrary delay distributions, a range of common primary distributions, and + allows for truncation and secondary event censoring to be accounted for + (Park et al. (2024) ). A subset of + common distributions also have analytical solutions implemented, allowing + for faster computation. In addition, it provides multiple methods for + fitting primary event censored distributions to data via optional + dependencies. + date_publication: '2025-02-10' + bug_reports: https://github.com/epinowcast/primarycensored/issues + url: https://primarycensored.epinowcast.org + url_cran: https://CRAN.R-project.org/package=primarycensored + url_git: https://github.com/epinowcast/primarycensored +primate: + version: 0.2.0 + title: Tools and Methods for Primatological Data Science + maintainer: David Schruth + description: Data from All the World's Primates relational SQL database and other + tabular datasets are made available via drivers and connection functions. Additionally + we provide several functions and examples to facilitate the merging and aggregation + of these tabular inputs. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=primate + url_git: '' +primefactr: + version: 0.1.1 + title: Use Prime Factorization for Computations + maintainer: Florian Privé + description: |- + Use Prime Factorization for simplifying computations, + for instance for ratios of large factorials. + date_publication: '2018-05-19' + bug_reports: https://github.com/privefl/primefactr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=primefactr + url_git: https://github.com/privefl/primefactr +primePCA: + version: '1.2' + title: Projected Refinement for Imputation of Missing Entries in PCA + maintainer: Ziwei Zhu + description: Implements the primePCA algorithm, developed and analysed in Zhu, Z., + Wang, T. and Samworth, R. J. (2019) High-dimensional principal component analysis + with heterogeneous missingness. . + date_publication: '2021-08-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=primePCA + url_git: '' +PRIMEplus: + version: 1.0.16 + title: Study Design for Immunotherapy Clinical Trials + maintainer: Bill Wheeler + description: Perform sample size, power calculation and subsequent analysis for + Immuno-oncology (IO) trials composed of responders and non-responders. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRIMEplus + url_git: '' +primer: + version: 1.2.0 + title: Functions and Data for the Book, a Primer of Ecology with R + maintainer: Hank Stevens + description: Functions are primarily functions for systems of ordinary differential + equations, difference equations, and eigenanalysis and projection of demographic + matrices; data are for examples. + date_publication: '2021-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=primer + url_git: '' +primerTree: + version: 1.0.6 + title: |- + Visually Assessing the Specificity and Informativeness of Primer + Pairs + maintainer: Matt Cannon + description: |- + Identifies potential target sequences for a given + set of primers and generates phylogenetic trees annotated with the + taxonomies of the predicted amplification products. + date_publication: '2022-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=primerTree + url_git: '' +primes: + version: 1.6.1 + title: Fast Functions for Prime Numbers + maintainer: Paul Egeler + description: |- + Fast functions for dealing with prime numbers, such as testing + whether a number is prime and generating a sequence prime numbers. + Additional functions include finding prime factors and Ruth-Aaron pairs, + finding next and previous prime numbers in the series, finding or estimating + the nth prime, estimating the number of primes less than or equal to an + arbitrary number, computing primorials, prime k-tuples (e.g., twin primes), + finding the greatest common divisor and smallest (least) common multiple, + testing whether two numbers are coprime, and computing Euler's totient + function. Most functions are vectorized for speed and convenience. + date_publication: '2025-02-04' + bug_reports: https://github.com/ironholds/primes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=primes + url_git: https://github.com/ironholds/primes +PRIMME: + version: 3.2-6 + title: Eigenvalues and Singular Values and Vectors from Large Matrices + maintainer: Eloy Romero + description: |2- + + R interface to 'PRIMME' , a C library for computing a few + eigenvalues and their corresponding eigenvectors of a real symmetric or complex + Hermitian matrix, or generalized Hermitian eigenproblem. It can also compute + singular values and vectors of a square or rectangular matrix. 'PRIMME' finds + largest, smallest, or interior singular/eigenvalues and can use preconditioning + to accelerate convergence. General description of the methods are provided in the papers + Stathopoulos (2010, ) and Wu (2017, ). + See 'citation("PRIMME")' for details. + date_publication: '2024-01-09' + bug_reports: https://github.com/primme/primme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PRIMME + url_git: https://www.cs.wm.edu/~andreas/software/https://github.com/primme/primme +princurve: + version: 2.1.6 + title: Fit a Principal Curve in Arbitrary Dimension + maintainer: Robrecht Cannoodt + description: |- + Fitting a principal curve to a data matrix in arbitrary dimensions. + Hastie and Stuetzle (1989) . + date_publication: '2021-01-18' + bug_reports: https://github.com/rcannood/princurve/issues + url: '' + url_cran: https://CRAN.R-project.org/package=princurve + url_git: https://github.com/rcannood/princurve +PrInDT: + version: 1.0.1 + title: |- + Prediction and Interpretation in Decision Trees for + Classification and Regression + maintainer: Claus Weihs + description: |- + Optimization of conditional inference trees from the package 'party' + for classification and regression. + For optimization, the model space is searched for the best tree on the full sample by + means of repeated subsampling. Restrictions are allowed so that only trees are accepted + which do not include pre-specified uninterpretable split results (cf. Weihs & Buschfeld, 2021a). + The function PrInDT() represents the basic resampling loop for 2-class classification (cf. Weihs + & Buschfeld, 2021a). The function RePrInDT() (repeated PrInDT()) allows for repeated + applications of PrInDT() for different percentages of the observations of the large and the + small classes (cf. Weihs & Buschfeld, 2021c). The function NesPrInDT() (nested PrInDT()) + allows for an extra layer of subsampling for a specific factor variable (cf. Weihs & Buschfeld, + 2021b). The functions PrInDTMulev() and PrInDTMulab() deal with multilevel and multilabel + classification. In addition to these PrInDT() variants for classification, the function + PrInDTreg() has been developed for regression problems. Finally, the function PostPrInDT() + allows for a posterior analysis of the distribution of a specified variable in the terminal + nodes of a given tree. + References are: + -- Weihs, C., Buschfeld, S. (2021a) "Combining Prediction and Interpretation in + Decision Trees (PrInDT) - a Linguistic Example" ; + -- Weihs, C., Buschfeld, S. (2021b) "NesPrInDT: Nested undersampling in PrInDT" + ; + -- Weihs, C., Buschfeld, S. (2021c) "Repeated undersampling in PrInDT (RePrInDT): Variation + in undersampling and prediction, and ranking of predictors in ensembles" . + date_publication: '2023-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PrInDT + url_git: '' +printr: + version: '0.3' + title: |- + Automatically Print R Objects to Appropriate Formats According + to the 'knitr' Output Format + maintainer: Yihui Xie + description: |- + Extends the S3 generic function knit_print() in 'knitr' + to automatically print some objects using an appropriate format such as + Markdown or LaTeX. For example, data frames are automatically printed as + tables, and the help() pages can also be rendered in 'knitr' documents. + date_publication: '2023-03-08' + bug_reports: https://github.com/yihui/printr/issues + url: https://yihui.org/printr/ + url_cran: https://CRAN.R-project.org/package=printr + url_git: '' +prinvars: + version: 1.0.0 + title: Principal Variables + maintainer: Ron Holzapfel + description: Provides methods for reducing the number of features within a data + set. See Bauer JO (2021) and Bauer JO, Drabant B + (2021) for more information on principal loading + analysis. + date_publication: '2023-01-09' + bug_reports: https://github.com/Ronho/prinvars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prinvars + url_git: https://github.com/Ronho/prinvars +prioGene: + version: 1.0.1 + title: |- + Candidate Gene Prioritization for Non-Communicable Diseases + Based on Functional Information + maintainer: Erqiang Hu + description: |- + In gene sequencing methods, the topological features of protein-protein interaction (PPI) networks are + often used, such as ToppNet . In this study, a candidate gene prioritization method + was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease + PPI networks with weights for nodes and edges based on functional information. + date_publication: '2020-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prioGene + url_git: '' +prior3D: + version: 0.1.5 + title: 3D Prioritization Algorithm + maintainer: Christos Adam + description: |- + Three-dimensional systematic conservation planning, conducting + nested prioritization analyses across multiple depth levels and + ensuring efficient resource allocation throughout the water column. + It provides a structured workflow designed to address biodiversity + conservation and management challenges in the 3 dimensions, while + facilitating users’ choices and parameterization (Doxa et al. 2025 + ). + date_publication: '2025-01-25' + bug_reports: https://github.com/cadam00/prior3D/issues + url: https://cadam00.github.io/prior3D/ + url_cran: https://CRAN.R-project.org/package=prior3D + url_git: https://github.com/cadam00/prior3D +priorCON: + version: 0.1.4 + title: |- + Graph Community Detection Methods into Systematic Conservation + Planning + maintainer: Christos Adam + description: |- + An innovative tool-set that incorporates graph community detection + methods into systematic conservation planning. It is designed to + enhance spatial prioritization by focusing on the protection of + areas with high ecological connectivity. Unlike traditional + approaches that prioritize individual planning units, 'priorCON' + focuses on clusters of features that exhibit strong ecological + linkages. The 'priorCON' package is built upon the 'prioritizr' + package , using commercial + and open-source exact algorithm solvers that ensure optimal + solutions to prioritization problems. + date_publication: '2025-01-24' + bug_reports: https://github.com/cadam00/priorCON/issues + url: https://cadam00.github.io/priorCON/ + url_cran: https://CRAN.R-project.org/package=priorCON + url_git: https://github.com/cadam00/priorCON +PriorGen: + version: '2.0' + title: Generates Prior Distributions for Proportions + maintainer: Konstantinos Pateras + description: |2- + + Translates beliefs into prior information in the form of Beta and Gamma distributions. + It can be used for the generation of priors on the prevalence of disease and + the sensitivity/specificity of diagnostic tests and any other binomial experiment. + date_publication: '2023-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PriorGen + url_git: '' +prioriactions: + version: 0.5.0 + title: Multi-Action Conservation Planning + maintainer: Jose Salgado-Rojas + description: |- + This uses a mixed integer mathematical programming (MIP) + approach for building and solving multi-action planning problems, + where the goal is to find an optimal combination of management actions that + abate threats, in an efficient way while accounting for spatial aspects. + Thus, optimizing the connectivity and conservation effectiveness of + the prioritized units and of the deployed actions. The package is capable of + handling different commercial (gurobi, CPLEX) and non-commercial (symphony, CBC) MIP solvers. + Gurobi optimization solver can be installed using comprehensive instructions in + the 'gurobi' installation vignette of the prioritizr package (available in + ). Instead, 'CPLEX' + optimization solver can be obtain from IBM CPLEX web page (available here + ). Additionally, + the 'rcbc' R package (available at + ) can be used to obtain solutions + using the CBC optimization software (). Methods used in the + package refers to Salgado-Rojas et al. (2020) , + Beyer et al. (2016) , Cattarino et al. (2015) + and Watts et al. (2009) . + See the prioriactions website for more information, documentations and examples. + date_publication: '2023-08-13' + bug_reports: https://github.com/prioriactions/prioriactions/issues + url: https://prioriactions.github.io/prioriactions/ + url_cran: https://CRAN.R-project.org/package=prioriactions + url_git: https://github.com/prioriactions/prioriactions +prioritizr: + version: 8.0.6 + title: Systematic Conservation Prioritization in R + maintainer: Richard Schuster + description: |- + Systematic conservation prioritization using mixed integer linear + programming (MILP). It provides a flexible interface for building and + solving conservation planning problems. Once built, conservation planning + problems can be solved using a variety of commercial and open-source exact + algorithm solvers. By using exact algorithm solvers, solutions can be + generated that are guaranteed to be optimal (or within a pre-specified + optimality gap). Furthermore, conservation problems can be constructed to + optimize the spatial allocation of different management actions or zones, + meaning that conservation practitioners can identify solutions that benefit + multiple stakeholders. To solve large-scale or complex conservation + planning problems, users should install the Gurobi optimization software + (available from ) and the 'gurobi' R package (see + Gurobi Installation Guide vignette for details). Users can also install the + IBM CPLEX software () and + the 'cplexAPI' R package (available at ). + Additionally, the 'rcbc' R package (available at + ) can be used to generate solutions + using the CBC optimization software (). For further details, see Hanson et al. (2024) . + date_publication: '2025-01-09' + bug_reports: https://github.com/prioritizr/prioritizr/issues + url: https://prioritizr.net + url_cran: https://CRAN.R-project.org/package=prioritizr + url_git: https://github.com/prioritizr/prioritizr +prioritizrdata: + version: 0.3.2 + title: Conservation Planning Datasets + maintainer: Richard Schuster + description: |- + Conservation planning datasets for learning how to use the + 'prioritizr' package . + date_publication: '2023-04-06' + bug_reports: https://github.com/prioritizr/prioritizrdata/issues + url: https://prioritizr.github.io/prioritizrdata/ + url_cran: https://CRAN.R-project.org/package=prioritizrdata + url_git: https://github.com/prioritizr/prioritizrdata +priorityelasticnet: + version: 0.2.0 + title: |- + Comprehensive Analysis of Multi-Omics Data Using an Offset-Based + Method + maintainer: Laila Qadir Musib + description: |- + Priority-ElasticNet extends the Priority-LASSO method (Klau et al. (2018) ) by incorporating the ElasticNet penalty, allowing for both L1 and L2 regularization. + This approach fits successive ElasticNet models for several blocks of (omics) data with different priorities, using the predicted values from each block as an offset for the subsequent block. + It also offers robust options to handle block-wise missingness in multi-omics data, improving the flexibility and applicability of the model in the presence of incomplete datasets. + date_publication: '2025-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=priorityelasticnet + url_git: '' +prioritylasso: + version: 0.3.1 + title: Analyzing Multiple Omics Data with an Offset Approach + maintainer: Roman Hornung + description: Fits successive Lasso models for several blocks of (omics) data with + different priorities and takes the predicted values as an offset for the next + block. Also offers options to deal with block-wise missingness in multi-omics + data. + date_publication: '2023-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prioritylasso + url_git: '' +priorsense: + version: 1.0.4 + title: Prior Diagnostics and Sensitivity Analysis + maintainer: Noa Kallioinen + description: Provides functions for prior and likelihood sensitivity analysis in + Bayesian models. Currently it implements methods to determine the sensitivity + of the posterior to power-scaling perturbations of the prior and likelihood. + date_publication: '2024-11-01' + bug_reports: '' + url: https://n-kall.github.io/priorsense/ + url_cran: https://CRAN.R-project.org/package=priorsense + url_git: '' +prism: + version: 0.2.1 + title: Access Data from the Oregon State Prism Climate Project + maintainer: Alan Butler + description: |- + Allows users to access the Oregon State Prism climate data + (). Using the web service API data + can easily downloaded in bulk and loaded into R for spatial analysis. + Some user friendly visualizations are also provided. + date_publication: '2023-10-18' + bug_reports: https://github.com/ropensci/prism/issues + url: https://docs.ropensci.org/prism/ + url_cran: https://CRAN.R-project.org/package=prism + url_git: https://github.com/ropensci/prism +PRISM.forecast: + version: 0.2.1 + title: |- + Penalized Regression with Inferred Seasonality Module - + Forecasting Unemployment Initial Claims using 'Google Trends' + Data + maintainer: Dingdong Yi + description: Implements Penalized Regression with Inferred Seasonality Module (PRISM) + to generate forecast estimation of weekly unemployment initial claims using 'Google + Trends' data. It includes required data and tools for backtesting the performance + in 2007-2020. + date_publication: '2020-10-21' + bug_reports: https://github.com/ryanddyi/prism/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PRISM.forecast + url_git: https://github.com/ryanddyi/prism +PRISMA: + version: 0.2-7 + title: Protocol Inspection and State Machine Analysis + maintainer: Tammo Krueger + description: |- + Loads and processes huge text + corpora processed with the sally toolbox (). + sally acts as a very fast preprocessor which splits the text files into + tokens or n-grams. These output files can then be read with the PRISMA + package which applies testing-based token selection and has some + replicate-aware, highly tuned non-negative matrix factorization and + principal component analysis implementation which allows the processing of + very big data sets even on desktop machines. + date_publication: '2018-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRISMA + url_git: '' +PRISMA2020: + version: 1.1.1 + title: Make Interactive 'PRISMA' Flow Diagrams + maintainer: Chris Pritchard + description: |- + Systematic reviews should be described in a high degree of + methodological detail. The 'PRISMA' Statement calls for a high level of + reporting detail in systematic reviews and meta-analyses. An integral part + of the methodological description of a review is a flow diagram. + This package produces an interactive flow diagram that conforms to the + 'PRISMA2020' preprint. When made interactive, the reader/user can click + on each box and be directed to another website or file online (e.g. a + detailed description of the screening methods, or a list of excluded full + texts), with a mouse-over tool tip that describes the information linked + to in more detail. Interactive versions can be saved as HTML files, + whilst static versions for inclusion in manuscripts can be saved as + HTML, PDF, PNG, SVG, PS or WEBP files. + date_publication: '2023-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRISMA2020 + url_git: '' +prismadiagramR: + version: 1.0.0 + title: Creates a Prisma Diagram using 'DiagrammeR' + maintainer: Lionel Duarte + description: Creates 'PRISMA' diagram from a minimal + dataset of included and excluded studies and allows for more custom diagrams. + 'PRISMA' diagrams are used to track the identification, screening, eligibility, + and inclusion of studies in a systematic review. + date_publication: '2020-05-04' + bug_reports: https://github.com/ltrainstg/prismadiagramR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prismadiagramR + url_git: https://github.com/ltrainstg/prismadiagramR +prismatic: + version: 1.1.2 + title: Color Manipulation Tools + maintainer: Emil Hvitfeldt + description: |- + Manipulate and visualize colors in a intuitive, + low-dependency and functional way. + date_publication: '2024-04-10' + bug_reports: https://github.com/EmilHvitfeldt/prismatic/issues + url: https://emilhvitfeldt.github.io/prismatic/ + url_cran: https://CRAN.R-project.org/package=prismatic + url_git: https://github.com/EmilHvitfeldt/prismatic +prismjs: + version: 2.1.0 + title: Server-Side Syntax Highlighting + maintainer: Jeroen Ooms + description: |- + Prism is a lightweight, extensible syntax + highlighter, built with modern web standards in mind. This package provides + server-side rendering in R using 'V8' such that no JavaScript library is + required in the resulting HTML documents. Over 400 languages are supported. + date_publication: '2025-01-07' + bug_reports: https://github.com/ropensci/prismjs/issues + url: https://ropensci.r-universe.dev/prismjshttps://docs.ropensci.org/prismjs/ + url_cran: https://CRAN.R-project.org/package=prismjs + url_git: '' +prisonbrief: + version: 0.1.2 + title: Downloads and Parses World Prison Brief Data + maintainer: Danilo Freire + description: Download, parses and tidies information from the World Prison Brief + project . + date_publication: '2021-02-18' + bug_reports: '' + url: https://danilofreire.github.io/prisonbrief/ + url_cran: https://CRAN.R-project.org/package=prisonbrief + url_git: '' +prithulib: + version: 1.0.2 + title: Perform Random Experiments + maintainer: Prithul Chaturvedi + description: |- + Enables user to perform the following: + 1. Roll 'n' number of die/dice (roll()). + 2. Toss 'n' number of coin(s) (toss()). + 3. Play the game of Rock, Paper, Scissors. + 4. Choose 'n' number of card(s) from a pack of 52 playing cards (Joker optional). + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prithulib + url_git: '' +PrivateLR: + version: 1.2-22 + title: Differentially Private Regularized Logistic Regression + maintainer: Staal A. Vinterbo + description: |- + Implements two differentially private algorithms for + estimating L2-regularized logistic regression coefficients. A randomized + algorithm F is epsilon-differentially private (C. Dwork, Differential + Privacy, ICALP 2006 ), if + |log(P(F(D) in S)) - log(P(F(D') in S))| <= epsilon + for any pair D, D' of datasets that differ in exactly one record, any + measurable set S, and the randomness is taken over the choices F makes. + date_publication: '2018-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PrivateLR + url_git: '' +PRMethods: + version: 0.1.0 + title: |- + D-Hondt, Sainte-Lague, and Modified Sainte-Lague Methods for + Seat Allocation + maintainer: Pau Bello Pérez + description: Calculates seat allocation using the D-Hondt method, Sainte-Lague method, + and Modified Sainte-Lague method, all commonly used in proportional representation + electoral systems. For more information on these methods, see Michael Gallagher + (1991). + date_publication: '2025-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRMethods + url_git: '' +PRNG: + version: 0.0.2.1.2 + title: A Pseudo-Random Number Generator + maintainer: Sajad Ahmad Mir + description: Provides functions for generating pseudo-random numbers that follow + a uniform distribution [0,1]. Randomness tests were conducted using the National + Institute of Standards and Technology test suite, + along with additional tests. The sequence generated depends on the initial values + and parameters. The package includes a linear congruence map as the decision map + and three chaotic maps to generate the pseudo-random sequence, which follow a + uniform distribution. Other distributions can be generated from the uniform distribution + using the Inversion Principle Method and BOX-Muller transformation. Small perturbations + in seed values result in entirely different sequences of numbers due to the sensitive + nature of the maps being used. The chaotic nature of the maps helps achieve randomness + in the generator. Additionally, the generator is capable of producing random bits. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRNG + url_git: '' +prnsamplr: + version: 1.0.0 + title: Permanent Random Number Sampling + maintainer: Kira Coder Gylling + description: |- + Survey sampling using permanent random numbers (PRN's). A solution + to the problem of unknown overlap between survey samples, which leads to a + low precision in estimates when the survey is repeated or combined with + other surveys. The PRN solution is to supply the U(0, 1) random numbers to + the sampling procedure, instead of having the sampling procedure generate + them. In Lindblom (2014) , and therein cited + papers, it is shown how this is carried out and how it improves the + estimates. This package supports two common fixed-size sampling procedures + (simple random sampling and probability-proportional-to-size sampling) and + includes a function for transforming the PRN's in order to control the + sample overlap. + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prnsamplr + url_git: '' +pro: + version: 0.1.1 + title: Point-Process Response Model for Optogenetics + maintainer: Xi (Rossi) LUO + description: Optogenetics is a new tool to study neuronal circuits that have been + genetically modified to allow stimulation by flashes of light. This package implements + the methodological framework, Point-process Response model for Optogenetics (PRO), + for analyzing data from these experiments. This method provides explicit nonlinear + transformations to link the flash point-process with the spiking point-process. Such + response functions can be used to provide important and interpretable scientific + insights into the properties of the biophysical process that governs neural spiking + in response to optogenetic stimulation. + date_publication: '2015-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pro + url_git: '' +ProActive: + version: 0.1.0 + title: Detect Elevations and Gaps in Mapped Sequencing Read Coverage + maintainer: Jessie Maier + description: |- + Automate the detection of gaps and elevations in mapped sequencing + read coverage using a 2D pattern-matching algorithm. 'ProActive' detects, characterizes + and visualizes read coverage patterns in both genomes and metagenomes. Optionally, + users may provide gene annotations associated with their genome or metagenome + in the form of a .gff file. In this case, 'ProActive' will generate an additional + output table containing the gene annotations found within the detected regions of gapped + and elevated read coverage. Additionally, users can search for gene + annotations of interest in the output read coverage plots. + date_publication: '2025-01-21' + bug_reports: https://github.com/jlmaier12/ProActive/issues + url: https://jlmaier12.github.io/ProActive/ + url_cran: https://CRAN.R-project.org/package=ProActive + url_git: https://github.com/jlmaier12/ProActive +ProAE: + version: 1.0.3 + title: PRO-CTCAE Scoring, Analysis, and Graphical Tools + maintainer: Blake Langlais + description: |- + A collection of tools to facilitate standardized analysis + and graphical procedures when using the National Cancer Institute’s + Patient-Reported Outcomes version of the Common Terminology Criteria for + Adverse Events (PRO-CTCAE) and other PRO measurements. + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProAE + url_git: '' +probably: + version: 1.0.3 + title: Tools for Post-Processing Predicted Values + maintainer: Max Kuhn + description: |- + Models can be improved by post-processing class + probabilities, by: recalibration, conversion to hard probabilities, + assessment of equivocal zones, and other activities. 'probably' + contains tools for conducting these operations as well as calibration + tools and conformal inference techniques for regression models. + date_publication: '2024-02-23' + bug_reports: https://github.com/tidymodels/probably/issues + url: https://probably.tidymodels.org + url_cran: https://CRAN.R-project.org/package=probably + url_git: https://github.com/tidymodels/probably +ProbBayes: + version: '1.1' + title: Probability and Bayesian Modeling + maintainer: Jim Albert + description: 'Functions and datasets to accompany J. Albert and J. Hu, "Probability + and Bayesian Modeling", CRC Press, (2019, ISBN: 1138492566).' + date_publication: '2020-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProbBayes + url_git: https://github.com/bayesball/ProbBayes +ProbBreed: + version: 1.0.4.5 + title: Probability Theory for Selecting Candidates in Plant Breeding + maintainer: Saulo Chaves + description: Use probability theory under the Bayesian framework for calculating + the risk of selecting candidates in a multi-environment context. Contained are + functions used to fit a Bayesian multi-environment model (based on the available + presets), extract posterior values and maximum posterior values, compute the variance + components, check the model’s convergence, and calculate the probabilities. For + both across and within-environments scopes, the package computes the probability + of superior performance and the pairwise probability of superior performance. + Furthermore, the probability of superior stability and the pairwise probability + of superior stability across environments is estimated. A joint probability of + superior performance and stability is also provided. + date_publication: '2025-02-03' + bug_reports: https://github.com/saulo-chaves/ProbBreed/issues + url: https://saulo-chaves.github.io/ProbBreed_site/ + url_cran: https://CRAN.R-project.org/package=ProbBreed + url_git: https://github.com/saulo-chaves/ProbBreed +probe: + version: '1.1' + title: Sparse High-Dimensional Linear Regression with PROBE + maintainer: Alexander McLain + description: Implements an efficient and powerful Bayesian approach for sparse high-dimensional + linear regression. It uses minimal prior assumptions on the parameters through + plug-in empirical Bayes estimates of hyperparameters. An efficient Parameter-Expanded + Expectation-Conditional-Maximization (PX-ECM) algorithm estimates maximum a posteriori + (MAP) values of regression parameters and variable selection probabilities. The + PX-ECM results in a robust computationally efficient coordinate-wise optimization, + which adjusts for the impact of other predictor variables. The E-step is motivated + by the popular two-group approach to multiple testing. The result is a PaRtitiOned + empirical Bayes Ecm (PROBE) algorithm applied to sparse high-dimensional linear + regression, implemented using one-at-a-time or all-at-once type optimization. + More information can be found in McLain, Zgodic, and Bondell (2022) . + date_publication: '2023-10-31' + bug_reports: https://github.com/alexmclain/PROBE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=probe + url_git: '' +ProbeDeveloper: + version: 1.1.0 + title: Develop Hybridization Probes + maintainer: Junhui Li + description: Hybridization probes for target sequences can be made based on melting + temperature value calculated by R package 'TmCalculator' + and methods extended from Beliveau, B. J.,(2018) , + and those hybridization probes can be used to capture specific target regions + in fluorescence in situ hybridization and next generation sequence experiments. + date_publication: '2022-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProbeDeveloper + url_git: '' +ProbitSpatial: + version: '1.1' + title: Probit with Spatial Dependence, SAR, SEM and SARAR Models + maintainer: Davide Martinetti + description: Fast estimation of binomial spatial probit regression models with spatial + autocorrelation for big datasets. + date_publication: '2021-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProbitSpatial + url_git: '' +ProbMarg: + version: 1.0.1 + title: |- + Computing Logit & Probit Predicted Probabilities & Marginal + Effects + maintainer: Tim Liao + description: |- + Computes predicted probabilities and marginal effects for + binary & ordinal logit and probit, (partial) generalized ordinal & + multinomial logit models estimated with the glm(), clm() (in the + 'ordinal' package), and vglm() (in the 'VGAM' package) functions. + date_publication: '2020-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProbMarg + url_git: '' +probout: + version: 1.1.2 + title: |- + Unsupervised Multivariate Outlier Probabilities for Large + Datasets + maintainer: Chris Fraley + description: Estimates unsupervised outlier probabilities for multivariate numeric + data with many observations from a nonparametric outlier statistic. + date_publication: '2022-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=probout + url_git: '' +probs: + version: 0.9.9 + title: Elementary Probability on Finite Sample Spaces + maintainer: Joe gr. Schlarmann + description: |- + Performs elementary probability calculations on finite sample spaces, which may be represented by data frames or lists. + This package is meant to rescue some widely used functions from the archived 'prob' package (see ). + Functionality includes setting up sample spaces, counting tools, defining probability spaces, performing set algebra, calculating probability and conditional probability, tools for simulation and checking the law of large numbers, adding random variables, and finding marginal distributions. Characteristic functions for all base R distributions are included. + date_publication: '2024-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=probs + url_git: '' +ProbSamplingI: + version: '2.0' + title: Probabilistic Sampling Design and Strategies + maintainer: Jorge Barón + description: |- + It allows the user to determine sample sizes, select probabilistic samples, + make estimates of different parameters for the total finite population and in studio domains, + using the main design drawings. + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProbSamplingI + url_git: '' +PROBShiny: + version: 0.1.0 + title: Interactive Document for Working with Basic Probability + maintainer: Kartikeya Bolar + description: An interactive document on the topic of basic probability using 'rmarkdown' + and 'shiny' packages. Runtime examples are provided in the package function as + well as at . + date_publication: '2019-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PROBShiny + url_git: '' +probstats4econ: + version: 0.3.1 + title: |- + Companion Package to Probability and Statistics for Economics + and Business + maintainer: Nathan Gardner Hattersley + description: 'Utilities for multiple hypothesis testing, companion datasets from + "Probability and Statistics for Economics and Business: An Introduction Using + R" by Jason Abrevaya (MIT Press, under contract).' + date_publication: '2024-08-23' + bug_reports: '' + url: https://probstats4econ.com/package.html + url_cran: https://CRAN.R-project.org/package=probstats4econ + url_git: '' +ProbYX: + version: 1.1-0.1 + title: Inference for the Stress-Strength Model R = P(Y, and + adds the directory with the MRTSwath executable to the default R PATH by editing + ~/.Rprofile. + date_publication: '2016-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proccalibrad + url_git: '' +ProcData: + version: 0.3.2 + title: Process Data Analysis + maintainer: Xueying Tang + description: |- + Provides tools for exploratory process data analysis. Process data refers to the data describing + participants' problem-solving processes in computer-based assessments. It is often recorded in computer + log files. This package provides functions to read, process, and write process data. It also implements + two feature extraction methods to compress the information stored in process data into standard + numerical vectors. This package also provides recurrent neural network based models that relate response processes + with other binary or scale variables of interest. The functions that involve training and evaluating neural networks + are wrappers of functions in 'keras'. + date_publication: '2021-04-01' + bug_reports: https://github.com/xytangtang/ProcData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ProcData + url_git: '' +proceduralnames: + version: 0.2.2 + title: Several Methods for Procedural Name Generation + maintainer: Michael Mahoney + description: |- + A small, dependency-free way to generate random names. Methods + provided include the adjective-surname approach of Docker containers + (''), + and combinations of common English or Spanish words. + date_publication: '2022-08-11' + bug_reports: https://github.com/mikemahoney218/proceduralnames/issues + url: https://mikemahoney218.github.io/proceduralnames/ + url_cran: https://CRAN.R-project.org/package=proceduralnames + url_git: https://github.com/mikemahoney218/proceduralnames +processanimateR: + version: 1.0.5 + title: Process Map Token Replay Animation + maintainer: Felix Mannhardt + description: |- + Provides animated process maps based on the 'procesmapR' package. + Cases stored in event logs created with with 'bupaR' S3 class eventlog() are + rendered as tokens (SVG shapes) and animated according to their occurrence + times on top of the process map. For rendering SVG animations ('SMIL') and the + 'htmlwidget' package are used. + date_publication: '2022-07-20' + bug_reports: https://github.com/bupaverse/processanimateR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=processanimateR + url_git: https://github.com/bupaverse/processanimateR/ +processcheckR: + version: 0.1.4 + title: Rule-Based Conformance Checking of Business Process Event Data + maintainer: Gert Janssenswillen + description: 'Check compliance of event-data from (business) processes with respect + to specified rules. Rules supported are of three types: frequency (activities + that should (not) happen x number of times), order (succession between activities) + and exclusiveness (and and exclusive choice between activities).' + date_publication: '2022-10-03' + bug_reports: https://github.com/bupaverse/processcheckr/issues + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=processcheckR + url_git: https://github.com/bupaverse/processcheckr +processmapR: + version: 0.5.6 + title: Construct Process Maps Using Event Data + maintainer: Gert Janssenswillen + description: Visualize event logs using directed graphs, i.e. process maps. Part + of the 'bupaR' framework. + date_publication: '2024-12-03' + bug_reports: https://github.com/bupaverse/processmapr/issues/ + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=processmapR + url_git: https://github.com/bupaverse/processmapr/ +processmonitR: + version: 0.1.0 + title: Building Process Monitoring Dashboards + maintainer: gert.janssenswillen@uhasselt.be + description: Functions for constructing dashboards for business process monitoring. + Building on the event log objects class from package 'bupaR'. Allows the use to + assemble custom shiny dashboards based on process data. + date_publication: '2017-06-18' + bug_reports: '' + url: https://www.bupar.net + url_cran: https://CRAN.R-project.org/package=processmonitR + url_git: '' +processpredictR: + version: 0.1.0 + title: Process Prediction + maintainer: Gert Janssenswillen + description: 'Means to predict process flow, such as process outcome, next activity, + next time, remaining time, and remaining trace. Off-the-shelf predictive models + based on the concept of Transformers are provided, as well as multiple ways to + customize the models. This package is partly based on work described in Zaharah + A. Bukhsh, Aaqib Saeed, & Remco M. Dijkman. (2021). "ProcessTransformer: Predictive + Business Process Monitoring with Transformer Network" .' + date_publication: '2023-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=processpredictR + url_git: '' +processx: + version: 3.8.6 + title: Execute and Control System Processes + maintainer: Gábor Csárdi + description: |- + Tools to run system processes in the background. It can + check if a background process is running; wait on a background process + to finish; get the exit status of finished processes; kill background + processes. It can read the standard output and error of the processes, + using non-blocking connections. 'processx' can poll a process for + standard output or error, with a timeout. It can also poll several + processes at once. + date_publication: '2025-02-21' + bug_reports: https://github.com/r-lib/processx/issues + url: https://processx.r-lib.org + url_cran: https://CRAN.R-project.org/package=processx + url_git: https://github.com/r-lib/processx +proclhmm: + version: 1.0.0 + title: Latent Hidden Markov Models for Response Process Data + maintainer: Xueying Tang + description: |- + Provides functions for simulating from and fitting the latent hidden + Markov models for response process data (Tang, 2024) . + It also includes functions for simulating from and fitting ordinary hidden Markov models. + date_publication: '2024-06-05' + bug_reports: https://github.com/xytangtang/proclhmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=proclhmm + url_git: '' +procmaps: + version: 0.0.5 + title: Portable Address Space Mapping + maintainer: Kirill Müller + description: |- + Portable '/proc/self/maps' as a data frame. + Determine which library or other region is mapped to a specific + address of a process. -- + R packages can contain native code, compiled to shared libraries at build or + installation time. + When loaded, each shared library occupies a portion of the address space of + the main process. + When only a machine instruction pointer is available (e.g. from a backtrace + during error inspection or profiling), the address space map determines + which library this instruction pointer corresponds to. + date_publication: '2023-01-20' + bug_reports: https://github.com/r-prof/procmaps/issues + url: https://r-prof.github.io/procmaps/ + url_cran: https://CRAN.R-project.org/package=procmaps + url_git: https://github.com/r-prof/procmaps +ProcMod: + version: 1.0.8 + title: Informative Procrustean Matrix Correlation + maintainer: Eric Coissac + description: Estimates corrected Procrustean correlation between matrices for removing + overfitting effect. Coissac Eric and Gonindard-Melodelima Christelle (2019) . + date_publication: '2021-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProcMod + url_git: '' +procs: + version: 1.0.6 + title: Recreates Some 'SAS®' Procedures in 'R' + maintainer: David Bosak + description: |- + Contains functions to simulate the most commonly used + 'SAS®' procedures. Specifically, the package aims to + simulate the functionality of 'proc freq', 'proc means', 'proc ttest', + 'proc reg', 'proc transpose', 'proc sort', and 'proc print'. + The simulation will include recreating + all statistics with the highest fidelity possible. + date_publication: '2024-03-06' + bug_reports: https://github.com/dbosak01/procs/issues + url: https://procs.r-sassy.org + url_cran: https://CRAN.R-project.org/package=procs + url_git: https://github.com/dbosak01/procs +ProDenICA: + version: '1.1' + title: |- + Product Density Estimation for ICA using Tilted Gaussian Density + Estimates + maintainer: Trevor Hastie + description: A direct and flexible method for estimating an ICA model. This approach + estimates the densities for each component directly via a tilted Gaussian. The + tilt functions are estimated via a GAM Poisson model. Details can be found in + "Elements of Statistical Learning (2nd Edition)" in Section 14.7.4. + date_publication: '2022-02-21' + bug_reports: '' + url: https://hastie.su.domains/ElemStatLearn/printings/ESLII_print12_toc.pdf + url_cran: https://CRAN.R-project.org/package=ProDenICA + url_git: '' +prodest: + version: 1.0.1 + title: Production Function Estimation + maintainer: Gabriele Rovigatti + description: Implements the methods proposed by Olley, G.S. and Pakes, A. (1996) + , Levinsohn, J. and Petrin, A. (2003) , + Ackerberg, D.A. and Caves, K. and Frazer, G. (2015) and + Wooldridge, J.M. (2009) for structural productivity + estimation . + date_publication: '2018-06-19' + bug_reports: https://github.com/GabrieleRovigatti/prodest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prodest + url_git: https://github.com/GabrieleRovigatti/prodest/tree/master/prodest +prodigenr: + version: 0.7.0 + title: Research Project Directory Generator + maintainer: Luke Johnston + description: |- + Create a project directory structure, along with typical + files for that project. This allows projects to be quickly and easily + created, as well as for them to be standardized. Designed specifically + with scientists in mind (mainly bio-medical researchers, but likely + applies to other fields). + date_publication: '2024-12-13' + bug_reports: https://github.com/rostools/prodigenr/issues + url: https://rostools.github.io/prodigenr/ + url_cran: https://CRAN.R-project.org/package=prodigenr + url_git: https://github.com/rostools/prodigenr +prodlim: + version: 2024.06.25 + title: Product-Limit Estimation for Censored Event History Analysis + maintainer: Thomas A. Gerds + description: |- + Fast and user friendly implementation of nonparametric estimators + for censored event history (survival) analysis. Kaplan-Meier and + Aalen-Johansen method. + date_publication: '2024-06-24' + bug_reports: https://github.com/tagteam/prodlim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prodlim + url_git: '' +productivity: + version: 1.1.0 + title: Indices of Productivity Using Data Envelopment Analysis (DEA) + maintainer: Yann Desjeux + description: |2- + + Levels and changes of productivity and profitability are measured with various indices. + The package contains the multiplicatively complete Färe-Primont, Fisher, Hicks-Moorsteen, + Laspeyres, Lowe, and Paasche indices, as well as the classic Malmquist productivity index. + Färe-Primont and Lowe indices verify the transitivity property and can therefore be used for + multilateral or multitemporal comparison. + Fisher, Hicks-Moorsteen, Laspeyres, Malmquist, and Paasche indices are not transitive and are + only to be used for binary comparison. + All indices can also be decomposed into different components, providing insightful information + on the sources of productivity and profitability changes. + In the use of Malmquist productivity index, the technological change index can be further + decomposed into bias technological change components. + The package also allows to prohibit technological regression (negative technological change). In + the case of the Fisher, Hicks-Moorsteen, Laspeyres, Paasche and the transitive Färe-Primont + and Lowe indices, it is furthermore possible to rule out technological change. + Deflated shadow prices can also be obtained. Besides, the package allows parallel computing as + an option, depending on the user's computer configuration. + All computations are carried out with the nonparametric Data Envelopment Analysis (DEA), and + several assumptions regarding returns to scale are available. + All DEA linear programs are implemented using 'lp_solve'. + date_publication: '2018-03-28' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=2245 + url: '' + url_cran: https://CRAN.R-project.org/package=productivity + url_git: '' +productplots: + version: 0.1.1 + title: Product Plots for R + maintainer: Hadley Wickham + description: |- + Framework for visualising tables of counts, proportions + and probabilities. The framework is called product plots, alluding to + the computation of area as a product of height and width, and the + statistical concept of generating a joint distribution from the + product of conditional and marginal distributions. The framework, + with extensions, is sufficient to encompass over 20 visualisations + previously described in fields of statistical graphics and 'infovis', + including bar charts, mosaic plots, 'treemaps', equal area plots and + fluctuation diagrams. + date_publication: '2016-07-02' + bug_reports: https://github.com/hadley/productplots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=productplots + url_git: https://github.com/hadley/productplots +ProFAST: + version: '1.4' + title: |- + Probabilistic Factor Analysis for Spatially-Aware Dimension + Reduction + maintainer: Wei Liu + description: |- + Probabilistic factor analysis for spatially-aware dimension reduction across multi-section spatial transcriptomics data with millions of spatial locations. + More details can be referred to Wei Liu, et al. (2023) . + date_publication: '2024-03-18' + bug_reports: https://github.com/feiyoung/ProFAST/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ProFAST + url_git: https://github.com/feiyoung/ProFAST +ProfessR: + version: 2.4-3 + title: Grades Setting and Exam Maker + maintainer: Jonathan M. Lees + description: |- + Programs to determine student grades and create + examinations from Question banks. Programs will create numerous + multiple choice exams, randomly shuffled, for different versions of same question list. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProfessR + url_git: '' +profExtrema: + version: 0.2.1 + title: Compute and Visualize Profile Extrema Functions + maintainer: Dario Azzimonti + description: Computes profile extrema functions for arbitrary functions. If the + function is expensive-to-evaluate it computes profile extrema by emulating the + function with a Gaussian process (using package 'DiceKriging'). In this case uncertainty + quantification on the profile extrema can also be computed. The different plotting + functions for profile extrema give the user a tool to better locate excursion + sets. + date_publication: '2020-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=profExtrema + url_git: '' +proffer: + version: 0.2.2 + title: Profile R Code and Visualize with 'Pprof' + maintainer: William Michael Landau + description: |- + Like similar profiling tools, + the 'proffer' package automatically detects + sources of slowness in R code. + The distinguishing feature of 'proffer' is its utilization of + 'pprof', which supplies interactive visualizations + that are efficient and easy to interpret. + Behind the scenes, the 'profile' package converts + native Rprof() data to a protocol buffer + that 'pprof' understands. + For the documentation of 'proffer', + visit . + To learn about the implementations and methodologies of + 'pprof', 'profile', and protocol buffers, + visit . + , + and , respectively. + date_publication: '2024-11-15' + bug_reports: https://github.com/r-prof/proffer/issues + url: https://r-prof.github.io/proffer/ + url_cran: https://CRAN.R-project.org/package=proffer + url_git: https://github.com/r-prof/proffer +profile: + version: 1.0.3 + title: Read, Manipulate, and Write Profiler Data + maintainer: Kirill Müller + description: |- + Defines a data structure for profiler data, and methods to read and + write from the 'Rprof' and 'pprof' file formats. + date_publication: '2022-08-22' + bug_reports: https://github.com/r-prof/profile/issues + url: https://r-prof.github.io/profile/ + url_cran: https://CRAN.R-project.org/package=profile + url_git: https://github.com/r-prof/profile +ProfileLikelihood: + version: '1.3' + title: |- + Profile Likelihood for a Parameter in Commonly Used Statistical + Models + maintainer: Leena Choi + description: Provides profile likelihoods for a parameter of interest in commonly + used statistical models. The models include linear models, generalized linear + models, proportional odds models, linear mixed-effects models, and linear models + for longitudinal responses fitted by generalized least squares. The package also + provides plots for normalized profile likelihoods as well as the maximum profile + likelihood estimates and the kth likelihood support intervals. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProfileLikelihood + url_git: '' +profileModel: + version: 0.6.1 + title: Profiling Inference Functions for Various Model Classes + maintainer: Ioannis Kosmidis + description: Provides tools that can be used to calculate, evaluate, plot and use + for inference the profiles of *arbitrary* inference functions for *arbitrary* + 'glm'-like fitted models with linear predictors. More information on the methods + that are implemented can be found in Kosmidis (2008) . + date_publication: '2021-01-08' + bug_reports: https://github.com/ikosmidis/profileModel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=profileModel + url_git: https://github.com/ikosmidis/profileModel +profileR: + version: 0.3-5 + title: Profile Analysis of Multivariate Data in R + maintainer: Christopher David Desjardins + description: |- + A suite of multivariate methods and data visualization + tools to implement profile analysis and cross-validation techniques described in + Davison & Davenport (2002) , Bulut (2013), and other published and unpublished resources. + The package includes routines to perform criterion-related profile analysis, profile analysis + via multidimensional scaling, moderated profile analysis, profile analysis by group, and a + within-person factor model to derive score profiles. + date_publication: '2018-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=profileR + url_git: '' +profiplots: + version: 0.2.3 + title: Profinit Plotting Theme + maintainer: Dominik Matula + description: |- + Help unify visual output of R analyses in the Profinit EU company. + So far, there are color and fill scales for 'ggplot2', plotting theme for + 'ggplot2', color palettes and utils to make the tools default choices. + date_publication: '2023-11-16' + bug_reports: '' + url: https://profinit.eu + url_cran: https://CRAN.R-project.org/package=profiplots + url_git: '' +profmem: + version: 0.6.0 + title: Simple Memory Profiling for R + maintainer: Henrik Bengtsson + description: A simple and light-weight API for memory profiling of R expressions. The + profiling is built on top of R's built-in memory profiler ('utils::Rprofmem()'), + which records every memory allocation done by R (also native code). + date_publication: '2020-12-13' + bug_reports: https://github.com/HenrikBengtsson/profmem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=profmem + url_git: https://github.com/HenrikBengtsson/profmem +profoc: + version: 1.3.3 + title: Probabilistic Forecast Combination Using CRPS Learning + maintainer: Jonathan Berrisch + description: Combine probabilistic forecasts using CRPS learning algorithms proposed + in Berrisch, Ziel (2021) . + The package implements multiple online learning algorithms like Bernstein online + aggregation; see Wintenberger (2014) . Quantile + regression is also implemented for comparison purposes. Model parameters can be + tuned automatically with respect to the loss of the forecast combination. Methods + like predict(), update(), plot() and print() are available for convenience. This + package utilizes the optim C++ library for numeric optimization . + date_publication: '2024-09-21' + bug_reports: https://github.com/BerriJ/profoc/issues + url: https://profoc.berrisch.biz + url_cran: https://CRAN.R-project.org/package=profoc + url_git: https://github.com/BerriJ/profoc +ProfoundData: + version: 0.2.1 + title: Downloading and Exploring Data from the PROFOUND Database + maintainer: Florian Hartig + description: |- + Provides an R interface for the PROFOUND database . The + PROFOUND database contains a wide range of data to evaluate vegetation models and simulate climate + impacts at the forest stand scale. It includes 9 forest sites across Europe, and provides for them a site + description as well as soil, climate, CO2, Nitrogen deposition, tree-level, forest stand-level + and remote sensing data. Moreover, for a subset of 5 sites, also time series of carbon fluxes, + energy balances and soil water are available. + date_publication: '2020-03-30' + bug_reports: https://github.com/COST-FP1304-PROFOUND/ProfoundData/issues + url: https://cost-fp1304-profound.github.io/ProfoundData/ + url_cran: https://CRAN.R-project.org/package=ProfoundData + url_git: '' +profr: + version: 0.3.3 + title: An Alternative Display for Profiling Information + maintainer: Hadley Wickham + description: |- + An alternative data structure and visual rendering + for the profiling information generated by Rprof. + date_publication: '2018-12-05' + bug_reports: https://github.com/hadley/profr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=profr + url_git: https://github.com/hadley/profr +profrep: + version: 1.0.0 + title: Profile Repeatability + maintainer: Ursula K. Beattie + description: |- + Calculates profile repeatability for replicate stress response + curves, or similar time-series data. Profile repeatability is an individual + repeatability metric that uses the variances at each timepoint, the maximum + variance, the number of crossings (lines that cross over each other), and + the number of replicates to compute the repeatability score. + For more information see Reed et al. (2019) . + date_publication: '2023-12-04' + bug_reports: https://github.com/ubeattie/profrep/issues + url: https://ubeattie.github.io/profrep/ + url_cran: https://CRAN.R-project.org/package=profrep + url_git: '' +proftools: + version: 0.99-3 + title: Profile Output Processing Tools for R + maintainer: Luke Tierney + description: Tools for examining Rprof profile output. + date_publication: '2020-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proftools + url_git: '' +profvis: + version: 0.4.0 + title: Interactive Visualizations for Profiling R Code + maintainer: Hadley Wickham + description: Interactive visualizations for profiling R code. + date_publication: '2024-09-20' + bug_reports: https://github.com/r-lib/profvis/issues + url: https://profvis.r-lib.org + url_cran: https://CRAN.R-project.org/package=profvis + url_git: https://github.com/r-lib/profvis +progenyClust: + version: '1.2' + title: Finding the Optimal Cluster Number Using Progeny Clustering + maintainer: C.W. Hu + description: Implementing the Progeny Clustering algorithm, the 'progenyClust' package + assesses the clustering stability and identifies the optimal clustering number + for a given data matrix. It uses k-means clustering as a default, provides a tailored + hierarchical clustering function, and can be customized to work with other clustering + algorithms and different parameter settings. The package includes a main function + progenyClust(), plot and summary methods for 'progenyClust' object, a function + hclust.progenyClust() for hierarchical clustering, and two example datasets (test + and cell) for testing. + date_publication: '2016-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=progenyClust + url_git: '' +ProgModule: + version: 0.1.0 + title: Identification of Prognosis-Related Mutually Exclusive Modules + maintainer: Junwei Han + description: A novel tool to identify candidate driver modules for predicting the + prognosis of patients by integrating exclusive coverage of mutations with clinical + characteristics in cancer. + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProgModule + url_git: '' +progress: + version: 1.2.3 + title: Terminal Progress Bars + maintainer: Gábor Csárdi + description: |- + Configurable Progress bars, they may include percentage, + elapsed time, and/or the estimated completion time. They work in + terminals, in 'Emacs' 'ESS', 'RStudio', 'Windows' 'Rgui' and the + 'macOS' 'R.app'. The package also provides a 'C++' 'API', that works + with or without 'Rcpp'. + date_publication: '2023-12-06' + bug_reports: https://github.com/r-lib/progress/issues + url: http://r-lib.github.io/progress/ + url_cran: https://CRAN.R-project.org/package=progress + url_git: https://github.com/r-lib/progress#readme +progressr: + version: 0.15.1 + title: An Inclusive, Unifying API for Progress Updates + maintainer: Henrik Bengtsson + description: A minimal, unifying API for scripts and packages to report progress + updates from anywhere including when using parallel processing. The package is + designed such that the developer can to focus on what progress should be reported + on without having to worry about how to present it. The end user has full control + of how, where, and when to render these progress updates, e.g. in the terminal + using utils::txtProgressBar(), cli::cli_progress_bar(), in a graphical user interface + using utils::winProgressBar(), tcltk::tkProgressBar() or shiny::withProgress(), + via the speakers using beepr::beep(), or on a file system via the size of a file. + Anyone can add additional, customized, progression handlers. The 'progressr' package + uses R's condition framework for signaling progress updated. Because of this, + progress can be reported from almost anywhere in R, e.g. from classical for and + while loops, from map-reduce API:s like the lapply() family of functions, 'purrr', + 'plyr', and 'foreach'. It will also work with parallel processing via the 'future' + framework, e.g. future.apply::future_lapply(), furrr::future_map(), and 'foreach' + with 'doFuture'. The package is compatible with Shiny applications. + date_publication: '2024-11-22' + bug_reports: https://github.com/futureverse/progressr/issues + url: https://progressr.futureverse.org + url_cran: https://CRAN.R-project.org/package=progressr + url_git: https://github.com/futureverse/progressr +PROJ: + version: 0.5.0 + title: Generic Coordinate System Transformations Using 'PROJ' + maintainer: Michael D. Sumner + description: |- + A wrapper around the generic coordinate transformation software 'PROJ' + that transforms coordinates from one coordinate reference system ('CRS') + to another. This includes cartographic projections as well as geodetic transformations. The intention is for this + package to be used by user-packages such as 'reproj', and that the older 'PROJ.4' and version 5 + pathways be provided by the 'proj4' package. + date_publication: '2024-06-12' + bug_reports: https://github.com/hypertidy/PROJ/issues + url: https://hypertidy.github.io/PROJ/ + url_cran: https://CRAN.R-project.org/package=PROJ + url_git: https://github.com/hypertidy/PROJ +proj4: + version: 1.0-14 + title: |- + A simple interface to the PROJ.4 cartographic projections + library + maintainer: Simon Urbanek + description: |- + A simple interface to lat/long projection and datum + transformation of the PROJ.4 cartographic projections library. It + allows transformation of geographic coordinates from one projection + and/or datum to another. + date_publication: '2024-01-14' + bug_reports: https://github.com/s-u/proj4/issues + url: https://www.rforge.net/proj4/ + url_cran: https://CRAN.R-project.org/package=proj4 + url_git: '' +ProjectionBasedClustering: + version: 1.2.2 + title: Projection Based Clustering + maintainer: Michael Thrun + description: A clustering approach applicable to every projection method is proposed + here. The two-dimensional scatter plot of any projection method can construct + a topographic map which displays unapparent data structures by using distance + and density information of the data. The generalized U*-matrix renders this visualization + in the form of a topographic map, which can be used to automatically define the + clusters of high-dimensional data. The whole system is based on Thrun and Ultsch, + "Using Projection based Clustering to Find Distance and Density based Clusters + in High-Dimensional Data" . Selecting the correct + projection method will result in a visualization in which mountains surround each + cluster. The number of clusters can be determined by counting valleys on the topographic + map. Most projection methods are wrappers for already available methods in R. + By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code + of the 'dredviz' software package, and the Curvilinear Component Analysis (CCA) + is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R. + date_publication: '2024-06-14' + bug_reports: https://github.com/Mthrun/ProjectionBasedClustering/issues + url: https://www.deepbionics.org + url_cran: https://CRAN.R-project.org/package=ProjectionBasedClustering + url_git: '' +projections: + version: 0.6.1 + title: Project Future Case Incidence + maintainer: Thibaut Jombart + description: Provides functions and graphics for projecting daily incidence based + on past incidence, and estimates of the serial interval and reproduction number. + Projections are based on a branching process using a Poisson-distributed number + of new cases per day, similar to the model used for estimating R in 'EpiEstim' + or in 'earlyR', and described by Nouvellet et al. (2017) . + The package provides the S3 class 'projections' which extends 'matrix', with accessors + and additional helpers for handling, subsetting, merging, or adding these objects, + as well as dedicated printing and plotting methods. + date_publication: '2024-12-06' + bug_reports: https://github.com/reconhub/projections/issues + url: https://www.repidemicsconsortium.org/projections/ + url_cran: https://CRAN.R-project.org/package=projections + url_git: '' +ProjectManagement: + version: 2.0.2 + title: Management of Deterministic and Stochastic Projects + maintainer: Juan Carlos Gonçalves Dosantos + description: Management problems of deterministic and stochastic projects. It obtains + the duration of a project and the appropriate slack for each activity in a deterministic + context. In addition it obtains a schedule of activities' time (Castro, Gómez + & Tejada (2007) ). It also allows the management + of resources. When the project is done, and the actual duration for each activity + is known, then it can know how long the project is delayed and make a fair delivery + of the delay between each activity (Bergantiños, Valencia-Toledo & Vidal-Puga + (2018) ). In a stochastic context it can estimate + the average duration of the project and plot the density of this duration, as + well as, the density of the early and last times of the chosen activities. As + in the deterministic case, it can make a distribution of the delay generated by + observing the project already carried out. + date_publication: '2024-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProjectManagement + url_git: '' +projects: + version: 2.1.3 + title: A Project Infrastructure for Researchers + maintainer: Nik Krieger + description: |- + Provides a project infrastructure with a focus on + manuscript creation. Creates a project folder with a single command, + containing subdirectories for specific components, templates for + manuscripts, and so on. + date_publication: '2021-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=projects + url_git: '' +ProjectTemplate: + version: 0.11.0 + title: Automates the Creation of New Statistical Analysis Projects + maintainer: Kenton White + description: |- + Provides functions to + automatically build a directory structure for a new R + project. Using this structure, 'ProjectTemplate' + automates data loading, preprocessing, library + importing and unit testing. + date_publication: '2024-07-01' + bug_reports: https://github.com/KentonWhite/ProjectTemplate/issues + url: http://projecttemplate.net + url_cran: https://CRAN.R-project.org/package=ProjectTemplate + url_git: '' +projmgr: + version: 0.1.1 + title: Task Tracking and Project Management with GitHub + maintainer: Emily Riederer + description: |- + Provides programmatic access to 'GitHub' API with a + focus on project management. Key functionality includes + setting up issues and milestones from R objects or 'YAML' configurations, + querying outstanding or completed tasks, and generating progress updates + in tables, charts, and RMarkdown reports. Useful for those using 'GitHub' in personal, + professional, or academic settings with an emphasis on streamlining + the workflow of data analysis projects. + date_publication: '2024-01-24' + bug_reports: https://github.com/emilyriederer/projmgr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=projmgr + url_git: https://github.com/emilyriederer/projmgr +projpred: + version: 2.8.0 + title: Projection Predictive Feature Selection + maintainer: Frank Weber + description: |2- + + Performs projection predictive feature selection for generalized linear + models (Piironen, Paasiniemi, and Vehtari, 2020, ) + with or without multilevel or additive terms (Catalina, Bürkner, and + Vehtari, 2022, ), for + some ordinal and nominal regression models (Weber, Glass, and Vehtari, 2023, + ), and for many other regression models (using the latent + projection by Catalina, Bürkner, and Vehtari, 2021, , + which can also be applied to most of the former models). The package is + compatible with the 'rstanarm' and 'brms' packages, but other reference + models can also be used. See the vignettes and the documentation for more + information and examples. + date_publication: '2023-12-15' + bug_reports: https://github.com/stan-dev/projpred/issues/ + url: https://mc-stan.org/projpred/ + url_cran: https://CRAN.R-project.org/package=projpred + url_git: '' +ProliferativeIndex: + version: 1.0.1 + title: Calculates and Analyzes the Proliferative Index + maintainer: Brittany Lasseigne + description: |- + Provides functions for calculating and analyzing the proliferative + index (PI) from an RNA-seq dataset. As described in Ramaker & Lasseigne, + et al. bioRxiv, 2016 . + date_publication: '2018-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ProliferativeIndex + url_git: '' +prolific.api: + version: 0.5.2 + title: A User-Friendly Interface for Accessing the Prolific API + maintainer: Simon Lenau + description: A user-friendly interface for creating and managing empirical crowd-sourcing + studies via API access to . + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prolific.api + url_git: '' +prolsirm: + version: 0.1.0 + title: Procrustes Matching for Latent Space Item Response Model + maintainer: Jinwen Luo + description: Procrustes matching of the posterior samples of person and item latent + positions from latent space item response models. The methods implemented in this + package are based on work by Borg, I., Groenen, P. (1997, ISBN:978-0-387-94845-4), + Jeon, M., Jin, I. H., Schweinberger, M., Baugh, S. (2021) , + and Andrew, D. M., Kevin M. Q., Jong Hee Park. (2011) . + date_publication: '2023-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prolsirm + url_git: '' +prome: + version: 1.9.1.0 + title: Patient-Reported Outcome Data Analysis with Stan + maintainer: Bin Wang + description: Algorithms and subroutines for patient-reported outcome data analysis. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prome + url_git: '' +PROMETHEE: + version: '1.1' + title: |- + Preference Ranking Organization METHod for Enrichment of + Evaluations + maintainer: Francesco Vidoli + description: |- + Functions which can be used to support the Multicriteria Decision Analysis (MCDA) process + involving multiple criteria, by PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations). + date_publication: '2019-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PROMETHEE + url_git: '' +promethee123: + version: 0.1.0 + title: PROMETHEE I, II, and III Methods + maintainer: Miguel Angelo Lellis Moreira + description: |- + The PROMETHEE method is a multi-criteria decision-making method addressing with outranking problems. + The method establishes a preference structure between the alternatives, having a preference function for + each criterion. IN this context, three variants of the method is carried out: PROMETHEE I (Partial Outranking), + PROMETHEE II (Total Outranking), and PROMETHEE III (Outranking by Intervals). + date_publication: '2020-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=promethee123 + url_git: '' +PrometheeTools: + version: 0.1.0 + title: PROMETHEE and GLNF for Ranking and Sorting Problems + maintainer: Felipe Barrera + description: |- + PROMETHEE (Preference Ranking Organisation METHod for Enrichment of + Evaluations) based method assesses alternatives to obtain partial and complete + rankings. The package also provides the GLNF (Global Local Net Flow) sorting + algorithm to classify alternatives into ordered categories, as well as an index + function to measure the classification quality. Barrera, F., Segura, M., & + Maroto, C. (2023) . Brans, J.P.; De Smet, Y., (2016) + . + date_publication: '2023-09-01' + bug_reports: https://github.com/ifelipebj/PrometheeTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PrometheeTools + url_git: https://github.com/ifelipebj/PrometheeTools +promises: + version: 1.3.2 + title: Abstractions for Promise-Based Asynchronous Programming + maintainer: Joe Cheng + description: |- + Provides fundamental abstractions for doing asynchronous + programming in R using promises. Asynchronous programming is useful + for allowing a single R process to orchestrate multiple tasks in the + background while also attending to something else. Semantics are + similar to 'JavaScript' promises, but with a syntax that is idiomatic + R. + date_publication: '2024-11-28' + bug_reports: https://github.com/rstudio/promises/issues + url: https://rstudio.github.io/promises/ + url_cran: https://CRAN.R-project.org/package=promises + url_git: https://github.com/rstudio/promises +promor: + version: 0.2.1 + title: Proteomics Data Analysis and Modeling Tools + maintainer: Chathurani Ranathunge + description: A comprehensive, user-friendly package for label-free proteomics data + analysis and machine learning-based modeling. Data generated from 'MaxQuant' can + be easily used to conduct differential expression analysis, build predictive models + with top protein candidates, and assess model performance. promor includes a suite + of tools for quality control, visualization, missing data imputation (Lazar et. + al. (2016) ), differential expression analysis + (Ritchie et. al. (2015) ), and machine learning-based + modeling (Kuhn (2008) ). + date_publication: '2023-07-17' + bug_reports: https://github.com/caranathunge/promor/issues + url: https://caranathunge.github.io/promor/ + url_cran: https://CRAN.R-project.org/package=promor + url_git: https://github.com/caranathunge/promor +promote: + version: 1.1.1 + title: Client for the 'Alteryx Promote' API + maintainer: Paul E. Promote + description: |- + Deploy, maintain, and invoke predictive models using the 'Alteryx + Promote' REST API. 'Alteryx Promote' is available at the URL: + . + date_publication: '2019-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=promote + url_git: https://github.com/alteryx/promote-r-client +promotionImpact: + version: 0.1.5 + title: Analysis & Measurement of Promotion Effectiveness + maintainer: Nahyun Kim + description: Analysis and measurement of promotion effectiveness on a given target + variable (e.g. daily sales). After converting promotion schedule into dummy or + smoothed predictor variables, the package estimates the effects of these variables + controlled for trend/periodicity/structural change using prophet by Taylor and + Letham (2017) and some prespecified variables + (e.g. start of a month). + date_publication: '2021-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=promotionImpact + url_git: https://github.com/ncsoft/promotionImpact +prompt: + version: 1.0.2 + title: Dynamic 'R' Prompt + maintainer: Gábor Csárdi + description: |- + Set the 'R' prompt dynamically, from a function. The package + contains some examples to include various useful dynamic information + in the prompt: the status of the last command (success or failure); + the amount of memory allocated by the current 'R' process; the name of + the R package(s) loaded by 'pkgload' and/or 'devtools'; various 'git' + information: the name of the active branch, whether it is dirty, + if it needs pushes pulls. You can also create your own prompt if you + don't like the predefined examples. + date_publication: '2023-08-31' + bug_reports: https://github.com/gaborcsardi/prompt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prompt + url_git: https://github.com/gaborcsardi/prompt +prompter: + version: 1.2.0 + title: Add Tooltips in 'Shiny' Apps with 'Hint.css' + maintainer: Etienne Bacher + description: |- + In 'Shiny' apps, it is sometimes useful to store information + on a particular item in a tooltip. 'Prompter' allows you to easily + create such tooltips, using 'Hint.css'. + date_publication: '2024-04-08' + bug_reports: https://github.com/etiennebacher/prompter/issues + url: https://prompter.etiennebacher.com + url_cran: https://CRAN.R-project.org/package=prompter + url_git: https://github.com/etiennebacher/prompter +promptr: + version: 1.0.0 + title: Format and Complete Few-Shot LLM Prompts + maintainer: Joe Ornstein + description: Format and submit few-shot prompts to OpenAI's Large Language Models + (LLMs). Designed to be particularly useful for text classification problems in + the social sciences. Methods are described in Ornstein, Blasingame, and Truscott + (2024) . + date_publication: '2024-08-23' + bug_reports: https://github.com/joeornstein/promptr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=promptr + url_git: https://github.com/joeornstein/promptr +promr: + version: 0.1.3 + title: Prometheus 'PromQL' Query Client for 'R' + maintainer: Dom Dwyer + description: |- + A native 'R' client library for querying the 'Prometheus' + time-series database, using the 'PromQL' query language. + date_publication: '2022-08-24' + bug_reports: https://github.com/domodwyer/promr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=promr + url_git: https://github.com/domodwyer/promr +prop.comb.RR: + version: '1.2' + title: Analyzing Combination of Proportions and Relative Risk + maintainer: Maria Alvarez + description: Carrying out inferences about any linear combination of proportions + and the ratio of two proportions. + date_publication: '2017-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prop.comb.RR + url_git: '' +propagate: + version: 1.0-6 + title: Propagation of Uncertainty + maintainer: Andrej-Nikolai Spiess + description: Propagation of uncertainty using higher-order Taylor expansion and + Monte Carlo simulation. + date_publication: '2018-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=propagate + url_git: '' +PropCIs: + version: 0.3-0 + title: Various Confidence Interval Methods for Proportions + maintainer: Ralph Scherer + description: Computes two-sample confidence intervals for single, paired and independent + proportions. + date_publication: '2018-02-23' + bug_reports: https://github.com/shearer/PropCIs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PropCIs + url_git: https://github.com/shearer/PropCIs +PropClust: + version: 1.4-7 + title: Propensity Clustering and Decomposition + maintainer: Peter Langfelder + description: |- + Implementation of propensity clustering and + decomposition as described in Ranola et al. (2013) . + Propensity decomposition can be viewed on the + one hand as a generalization of the eigenvector-based + approximation of correlation networks, and on the other hand as + a generalization of random multigraph models and + conformity-based decompositions. + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PropClust + url_git: '' +properties: + version: 0.0-9 + title: Parse 'Java' Properties Files for 'R Service Bus' Applications + maintainer: Daan Seynaeve + description: |- + Allows to parse 'Java' properties files in the context of + 'R Service Bus' applications. + date_publication: '2018-03-10' + bug_reports: '' + url: https://www.rservicebus.io/ + url_cran: https://CRAN.R-project.org/package=properties + url_git: '' +prophet: + version: '1.0' + title: Automatic Forecasting Procedure + maintainer: Sean Taylor + description: |- + Implements a procedure for forecasting time series data based on + an additive model where non-linear trends are fit with yearly, weekly, and + daily seasonality, plus holiday effects. It works best with time series + that have strong seasonal effects and several seasons of historical data. + Prophet is robust to missing data and shifts in the trend, and typically + handles outliers well. + date_publication: '2021-03-30' + bug_reports: https://github.com/facebook/prophet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prophet + url_git: https://github.com/facebook/prophet +proporz: + version: 1.5.0 + title: Proportional Apportionment + maintainer: Flavio Poletti + description: |- + Calculate seat apportionment for legislative bodies with + various methods. The algorithms include divisor or highest averages methods + (e.g. Jefferson, Webster or Adams), largest remainder methods and + biproportional apportionment. + Gaffke, N. & Pukelsheim, F. (2008) + Oelbermann, K. F. (2016) . + date_publication: '2024-04-03' + bug_reports: https://github.com/polettif/proporz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=proporz + url_git: https://github.com/polettif/proporz +propOverlap: + version: '1.0' + title: |- + Feature (gene) selection based on the Proportional Overlapping + Scores + maintainer: Osama Mahmoud + description: A package for selecting the most relevant features (genes) in the high-dimensional + binary classification problems. The discriminative features are identified using + analyzing the overlap between the expression values across both classes. The package + includes functions for measuring the proportional overlapping score for each gene + avoiding the outliers effect. The used measure for the overlap is the one defined + in the "Proportional Overlapping Score (POS)" technique for feature selection. + A gene mask which represents a gene's classification power can also be produced + for each gene (feature). The set size of the selected genes might be set by the + user. The minimum set of genes that correctly classify the maximum number of the + given tissue samples (observations) can be also produced. + date_publication: '2014-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=propOverlap + url_git: '' +PropScrRand: + version: 1.1.2 + title: |- + Propensity Score Methods for Assigning Treatment in Randomized + Trials + maintainer: Travis Loux + description: Contains functions to run propensity-biased allocation to balance covariate + distributions in sequential trials and propensity-constrained randomization to + balance covariate distributions in trials with known baseline covariates at time + of randomization. Currently only supports trials comparing two groups. + date_publication: '2024-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PropScrRand + url_git: '' +proPubBills: + version: '0.1' + title: '''ProPublica'' U.S. Congress Bills API Wrapper' + maintainer: Nadine Fischoff + description: An API wrapper around the 'ProPublica' API + for U.S. Congressional Bills. Users can include their API key, U.S. Congress, + branch, and offset ranges, to return a dataframe of all results within those parameters. + This package is different from the 'RPublica' package because it is for the 'ProPublica' + U.S. Congress data API, and the 'RPublica' package is for the Nonprofit Explorer, + Forensics, and Free the Files data APIs. + date_publication: '2017-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proPubBills + url_git: '' +ProPublicaR: + version: 1.1.4 + title: Access Functions for ProPublica's APIs + maintainer: Aleksander Dietrichson + description: |- + Provides wrapper functions to access the ProPublica's Congress and Campaign Finance APIs. + The Congress API provides near real-time access to legislative data from the House of + Representatives, the Senate and the Library of Congress. + The Campaign Finance API provides data from United States Federal Election Commission + filings and other sources. The API covers summary information for candidates and + committees, as well as certain types of itemized data. + For more information about these APIs go to: . + date_publication: '2023-09-06' + bug_reports: https://github.com/dietrichson/ProPublicaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ProPublicaR + url_git: '' +PROreg: + version: '1.3' + title: Patient Reported Outcomes Regression Analysis + maintainer: Josu Najera-Zuloaga + description: It offers a wide variety of techniques, such as graphics, recoding, + or regression models, for a comprehensive analysis of patient-reported outcomes + (PRO). Especially novel is the broad range of regression models based on the beta-binomial + distribution useful for analyzing binomial data with over-dispersion in cross-sectional, + longitudinal, or multidimensional response studies (see Najera-Zuloaga J., Lee + D.-J. and Arostegui I. (2019) ). + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PROreg + url_git: '' +PROscorer: + version: 0.0.4 + title: |- + Functions to Score Commonly-Used Patient-Reported Outcome (PRO) + Measures and Other Psychometric Instruments + maintainer: Ray Baser + description: |- + An extensible repository of accurate, up-to-date functions to + score commonly used patient-reported outcome (PRO), quality of life + (QOL), and other psychometric and psychological measures. + 'PROscorer', together with the 'PROscorerTools' package, is a system + to facilitate the incorporation of PRO measures into research studies + and clinical settings in a scientifically rigorous and reproducible + manner. These packages and their vignettes are intended to help + establish and promote best practices for scoring PRO and PRO-like + measures in research. The 'PROscorer' Instrument Descriptions vignette + contains descriptions of each instrument scored by 'PROscorer', complete + with references. These instrument descriptions are suitable for inclusion + in formal study protocol documents, grant proposals, and manuscript Method + sections. Each 'PROscorer' function is composed of helper functions + from the 'PROscorerTools' package, and users are encouraged to + contribute new functions to 'PROscorer'. More scoring functions are + currently in development and will be added in future updates. + date_publication: '2023-10-16' + bug_reports: https://github.com/raybaser/PROscorer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PROscorer + url_git: https://github.com/raybaser/PROscorer +PROscorerTools: + version: 0.0.4 + title: |- + Tools to Score Patient-Reported Outcome (PRO) and Other + Psychometric Measures + maintainer: Ray Baser + description: |- + Provides a reliable and flexible toolbox to score + patient-reported outcome (PRO), Quality of Life (QOL), and other + psychometric measures. The guiding philosophy is that scoring errors can + be eliminated by using a limited number of well-tested, well-behaved + functions to score PRO-like measures. The workhorse of the package is + the 'scoreScale' function, which can be used to score most single-scale + measures. It can reverse code items that need to be reversed before + scoring and pro-rate scores for missing item data. Currently, three + different types of scores can be output: summed item scores, mean item + scores, and scores scaled to range from 0 to 100. The 'PROscorerTools' + functions can be used to write new functions that score more complex + measures. In fact, 'PROscorerTools' functions are the building blocks of + the scoring functions in the 'PROscorer' package (which is a repository + of functions that score specific commonly-used instruments). Users are + encouraged to use 'PROscorerTools' to write scoring functions for their + favorite PRO-like instruments, and to submit these functions for + inclusion in 'PROscorer' (a tutorial vignette will be added soon). The + long-term vision for the 'PROscorerTools' and 'PROscorer' packages is to + provide an easy-to-use system to facilitate the incorporation of PRO + measures into research studies in a scientifically rigorous and + reproducible manner. These packages and their vignettes are intended to + help establish and promote "best practices" for scoring and describing + PRO-like measures in research. + date_publication: '2023-10-17' + bug_reports: https://github.com/MSKCC-Epi-Bio/PROscorerTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PROscorerTools + url_git: https://github.com/MSKCC-Epi-Bio/PROscorerTools +PROsetta: + version: 0.4.1 + title: Linking Patient-Reported Outcomes Measures + maintainer: Seung W. Choi + description: |- + Perform scale linking to establish relationships between instruments + that measure similar constructs according to the PROsetta Stone methodology, as in Choi, Schalet, Cook, & Cella (2014) . + date_publication: '2023-02-03' + bug_reports: https://github.com/choi-phd/PROsetta/issues + url: https://www.prosettastone.org/(projectdescription) + url_cran: https://CRAN.R-project.org/package=PROsetta + url_git: '' +ProSGPV: + version: 1.0.0 + title: Penalized Regression with Second-Generation P-Values + maintainer: Yi Zuo + description: |- + Implementation of penalized regression with second-generation p-values for variable + selection. The algorithm can handle linear regression, GLM, and Cox regression. S3 methods print(), summary(), coef(), predict(), and plot() are available for the algorithm. Technical details + can be found at Zuo et al. (2021) . + date_publication: '2021-08-06' + bug_reports: https://github.com/zuoyi93/ProSGPV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ProSGPV + url_git: https://github.com/zuoyi93/ProSGPV +prospectr: + version: 0.2.7 + title: |- + Miscellaneous Functions for Processing and Sample Selection of + Spectroscopic Data + maintainer: Leonardo Ramirez-Lopez + description: |- + Functions to preprocess spectroscopic data + and conduct (representative) sample selection/calibration sampling. + date_publication: '2024-02-16' + bug_reports: https://github.com/l-ramirez-lopez/prospectr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prospectr + url_git: https://github.com/l-ramirez-lopez/prospectr +PROSPER: + version: 0.3.3 + title: Simulation of Weed Population Dynamics + maintainer: Christoph v. Redwitz + description: |- + An environment to simulate the development of annual plant populations with regard to population dynamics and genetics, especially herbicide resistance. It combines genetics on the individual level (Renton et al. 2011) with a stochastic development on the population level (Daedlow, 2015). + Renton, M, Diggle, A, Manalil, S and Powles, S (2011) + Daedlow, Daniel (2015, doctoral dissertation: University of Rostock, Faculty of Agriculture and Environmental Sciences.) + date_publication: '2020-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PROSPER + url_git: '' +ProSportsDraftData: + version: 1.0.3 + title: Professional Sports Draft Data + maintainer: Benjamin Ginsburg + description: 'We provide comprehensive draft data for major professional sports + leagues, including the National Football League (NFL), National Basketball Association + (NBA), and National Hockey League (NHL). It offers access to both historical and + current draft data, allowing for detailed analysis and research on player biases + and player performance. The package is useful for sports fans and researchers + interested in identifying biases and trends within scouting reports. Created by + web scraping data from leading websites that cover professional sports player + scouting reports, the package allows users to filter and summarize data for analytical + purposes. For further details on the methods used, please refer to Wickham (2022) + "rvest: Easily Harvest (Scrape) Web Pages" + and Harrison (2023) "RSelenium: R Bindings for Selenium WebDriver" .' + date_publication: '2024-09-03' + bug_reports: https://github.com/Ginsburg1/ProSportsDraftData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ProSportsDraftData + url_git: https://github.com/Ginsburg1/ProSportsDraftData +protag: + version: 1.0.0 + title: Search Tagged Peptides & Draw Highlighted Mass Spectra + maintainer: Bo Yuan + description: 'In a typical protein labelling procedure, proteins are chemically + tagged with a functional group, usually at specific sites, then digested into + peptides, which are then analyzed using matrix-assisted laser desorption ionization + - time of flight mass spectrometry (MALDI-TOF MS) to generate peptide fingerprint. + Relative to the control, peptides that are heavier by the mass of the labelling + group are informative for sequence determination. Searching for peptides with + such mass shifts, however, can be difficult. This package, designed to tackle + this inconvenience, takes as input the mass list of two or multiple MALDI-TOF + MS mass lists, and makes pairwise comparisons between the labeled groups vs. control, + and restores centroid mass spectra with highlighted peaks of interest for easier + visual examination. Particularly, peaks differentiated by the mass of the labelling + group are defined as a “pair”, those with equal masses as a “match”, and all the + other peaks as a “mismatch”.For more bioanalytical background information, refer + to following publications: Jingjing Deng (2015) ; + Elizabeth Chang (2016) .' + date_publication: '2019-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=protag + url_git: '' +ProtE: + version: 1.0.3 + title: |- + Processing Proteomics Data, Statistical Analysis and + Visualization + maintainer: Theodoros Margelos + description: The 'Proteomics Eye' ('ProtE') offers a comprehensive and intuitive + framework for the univariate analysis of label-free proteomics data. By integrating + essential data wrangling and processing steps into a single function, 'ProtE' + streamlines pairwise statistical comparisons for categorical variables. It provides + quality checks and generates publication-ready visualizations, enabling efficient + and robust data analysis. 'ProtE' is compatible with proteomics data outputs from + 'MaxQuant' (Cox & Mann, (2008) ), 'DIA-NN' (Demichev et + al., (2020) ), and 'Proteome Discoverer' (Thermo + Fisher Scientific, version 2.5). The package leverages 'ggplot2' for visualization + (Wickham, (2016) ) and 'limma' for statistical + analysis (Ritchie et al., (2015) ). + date_publication: '2025-02-18' + bug_reports: https://github.com/theomargel/ProtE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ProtE + url_git: https://github.com/theomargel/ProtE +protein8k: + version: 0.0.1 + title: Perform Analysis and Create Visualizations of Proteins + maintainer: Simon Liles + description: |- + Read Protein Data Bank (PDB) files, performs its analysis, and + presents the result using different visualization types including 3D. The + package also has additional capability for handling Virus Report data from + the National Center for Biotechnology Information (NCBI) database. + Nature Structural Biology 10, 980 (2003) . + US National Library of Medicine (2021) . + date_publication: '2021-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=protein8k + url_git: '' +ProteoBayes: + version: 1.0.0 + title: Bayesian Statistical Tools for Quantitative Proteomics + maintainer: Arthur Leroy + description: |- + Bayesian toolbox for quantitative proteomics. In particular, this + package provides functions to generate synthetic datasets, execute Bayesian + differential analysis methods, and display results as, described in the + associated article Marie Chion and Arthur Leroy (2023) . + date_publication: '2023-07-19' + bug_reports: '' + url: https://mariechion.github.io/ProteoBayes/ + url_cran: https://CRAN.R-project.org/package=ProteoBayes + url_git: '' +proteomicsCV: + version: 0.4.0 + title: |- + Calculates the Percentage CV for Mass Spectrometry-Based + Proteomics Data + maintainer: Alejandro Brenes + description: Calculates the percentage coefficient of variation (CV) for mass spectrometry-based + proteomic data. The CV can be calculated with the traditional formula for raw + (non log transformed) intensity data, or log transformed data. + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proteomicsCV + url_git: '' +proteus: + version: 1.1.4 + title: Multiform Seq2Seq Model for Time-Feature Analysis + maintainer: Giancarlo Vercellino + description: Seq2seq time-feature analysis based on variational model, with a wide + range of distributions available for the latent variable. + date_publication: '2023-10-21' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/proteus + url_cran: https://CRAN.R-project.org/package=proteus + url_git: '' +protHMM: + version: 0.1.1 + title: Protein Feature Extraction from Profile Hidden Markov Models + maintainer: Shayaan Emran + description: |- + Calculates a comprehensive list of features from profile hidden Markov models (HMMs) of proteins. + Adapts and ports features for use with HMMs instead of Position Specific Scoring Matrices, in order to take + advantage of more accurate multiple sequence alignment by programs such as 'HHBlits' Remmert et al. (2012) + and 'HMMer' Eddy (2011) . Features calculated by + this package can be used for protein fold classification, protein structural class prediction, + sub-cellular localization and protein-protein interaction, among other tasks. Some examples of features + extracted are found in Song et al. (2018) , Jin & Zhu (2021) , + Lyons et al. (2015) and Saini et al. (2015) . + date_publication: '2023-07-05' + bug_reports: https://github.com/semran9/protHMM/issues + url: https://semran9.github.io/protHMM/ + url_cran: https://CRAN.R-project.org/package=protHMM + url_git: '' +proto: + version: 1.0.0 + title: Prototype Object-Based Programming + maintainer: Hadley Wickham + description: |- + An object oriented system using object-based, also + called prototype-based, rather than class-based object oriented ideas. + date_publication: '2016-10-29' + bug_reports: https://github.com/hadley/proto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=proto + url_git: https://github.com/hadley/proto +protoclust: + version: 1.6.4 + title: Hierarchical Clustering with Prototypes + maintainer: Jacob Bien + description: |- + Performs minimax linkage hierarchical clustering. Every cluster + has an associated prototype element that represents that cluster as + described in Bien, J., and Tibshirani, R. (2011), "Hierarchical Clustering + with Prototypes via Minimax Linkage," The Journal of the American + Statistical Association, 106(495), 1075-1084. + date_publication: '2022-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=protoclust + url_git: '' +protolite: + version: 2.3.1 + title: Highly Optimized Protocol Buffer Serializers + maintainer: Jeroen Ooms + description: |- + Pure C++ implementations for reading and writing several common data + formats based on Google protocol-buffers. Currently supports 'rexp.proto' for + serialized R objects, 'geobuf.proto' for binary geojson, and 'mvt.proto' for + vector tiles. This package uses the auto-generated C++ code by protobuf-compiler, + hence the entire serialization is optimized at compile time. The 'RProtoBuf' + package on the other hand uses the protobuf runtime library to provide a general- + purpose toolkit for reading and writing arbitrary protocol-buffer data in R. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/protolite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=protolite + url_git: https://github.com/jeroen/protolitehttps://jeroen.r-universe.dev/protolite +proton: + version: '1.0' + title: The Proton Game + maintainer: Przemysław Biecek + description: |- + 'The Proton Game' is a console-based data-crunching game for younger and older data scientists. + Act as a data-hacker and find Slawomir Pietraszko's credentials to the Proton server. + You have to solve four data-based puzzles to find the login and password. + There are many ways to solve these puzzles. You may use loops, data filtering, ordering, aggregation or other tools. + Only basics knowledge of R is required to play the game, yet the more functions you know, the more approaches you can try. + The knowledge of dplyr is not required but may be very helpful. + This game is linked with the ,,Pietraszko's Cave'' story available at http://biecek.pl/BetaBit/Warsaw. + It's a part of Beta and Bit series. + You will find more about the Beta and Bit series at http://biecek.pl/BetaBit. + date_publication: '2015-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proton + url_git: '' +protoshiny: + version: 0.1.0 + title: |- + Interactive Dendrograms for Visualizing Hierarchical Clusters + with Prototypes + maintainer: Andee Kaplan + description: |- + Shiny app to interactively visualize hierarchical clustering with prototypes. + For details on hierarchical clustering with prototypes, see + Bien and Tibshirani (2011) . This package currently launches the application. + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=protoshiny + url_git: '' +prototest: + version: '1.2' + title: Inference on Prototypes from Clusters of Features + maintainer: Stephen Reid + description: Procedures for testing for group-wide signal in clusters of variables. + Tests can be performed for single groups in isolation (univariate) or multiple + groups together (multivariate). Specific tests include the exact and approximate + (un)selective likelihood ratio tests described in Reid et al (2015), the selective + F test and marginal screening prototype test of Reid and Tibshirani (2015). User + may pre-specify columns to be included in prototype formation, or allow the function + to select them itself. A mixture of these two is also possible. Any variable selection + is accounted for using the selective inference framework. Options for non-sampling + and hit-and-run null reference distributions. + date_publication: '2019-02-03' + bug_reports: '' + url: http://arxiv.org/abs/1511.07839 + url_cran: https://CRAN.R-project.org/package=prototest + url_git: '' +protr: + version: 1.7-4 + title: |- + Generating Various Numerical Representation Schemes for Protein + Sequences + maintainer: Nan Xiao + description: |- + Comprehensive toolkit for generating various numerical + features of protein sequences described in Xiao et al. (2015) + . For full functionality, + the software 'ncbi-blast+' is needed, see + + for more information. + date_publication: '2024-09-11' + bug_reports: https://github.com/nanxstats/protr/issues + url: https://nanx.me/protr/ + url_cran: https://CRAN.R-project.org/package=protr + url_git: https://github.com/nanxstats/protr +ProTrackR: + version: 0.4.4 + title: Manipulate and Play 'ProTracker' Modules + maintainer: Pepijn de Vries + description: |- + 'ProTracker' is a popular music tracker to sequence + music on a Commodore Amiga machine. This package offers the + opportunity to import, export, manipulate and play 'ProTracker' + module files. Even though the file format could be considered + archaic, it still remains popular to this date. This package + intends to contribute to this popularity and therewith + keeping the legacy of 'ProTracker' and the Commodore Amiga + alive. + date_publication: '2025-01-13' + bug_reports: https://github.com/pepijn-devries/ProTrackR/issues + url: https://pepijn-devries.github.io/ProTrackR/ + url_cran: https://CRAN.R-project.org/package=ProTrackR + url_git: https://github.com/pepijn-devries/ProTrackR/ +ProTrackR2: + version: 0.0.5 + title: Manipulate and Play 'ProTracker' Modules + maintainer: Pepijn de Vries + description: |- + 'ProTracker' is a popular music tracker to sequence + music on a Commodore Amiga machine. This package offers the + opportunity to import, export, manipulate and play 'ProTracker' + module files. Even though the file format could be considered + archaic, it still remains popular to this date. This package + intends to contribute to this popularity and therewith + keeping the legacy of 'ProTracker' and the Commodore Amiga + alive. This package is the successor of 'ProTrackR' providing + better performance. + date_publication: '2024-11-09' + bug_reports: https://github.com/pepijn-devries/ProTrackR2/issues + url: https://pepijn-devries.github.io/ProTrackR2/ + url_cran: https://CRAN.R-project.org/package=ProTrackR2 + url_git: https://github.com/pepijn-devries/ProTrackR2 +protti: + version: 0.9.1 + title: |- + Bottom-Up Proteomics and LiP-MS Quality Control and Data + Analysis Tools + maintainer: Jan-Philipp Quast + description: Useful functions and workflows for proteomics quality control and data + analysis of both limited proteolysis-coupled mass spectrometry (LiP-MS) (Feng + et. al. (2014) ) and regular bottom-up proteomics experiments. + Data generated with search tools such as 'Spectronaut', 'MaxQuant' and 'Proteome + Discover' can be easily used due to flexibility of functions. + date_publication: '2024-10-21' + bug_reports: https://github.com/jpquast/protti/issues + url: https://jpquast.github.io/protti/ + url_cran: https://CRAN.R-project.org/package=protti + url_git: https://github.com/jpquast/protti +protViz: + version: 0.7.9 + title: |- + Visualizing and Analyzing Mass Spectrometry Related Data in + Proteomics + maintainer: Christian Panse + description: |- + Helps with quality checks, visualizations + and analysis of mass spectrometry data, coming from proteomics + experiments. The package is developed, tested and used at the Functional + Genomics Center Zurich . We use this package + mainly for prototyping, teaching, and having fun with proteomics data. + But it can also be used to do data analysis for small scale data sets. + date_publication: '2023-12-12' + bug_reports: https://github.com/cpanse/protViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=protViz + url_git: https://github.com/cpanse/protViz/ +proustr: + version: 0.4.0 + title: Tools for Natural Language Processing in French + maintainer: Colin Fay + description: |- + Tools for Natural Language Processing in French and texts from Marcel Proust's collection + "A La Recherche Du Temps Perdu". The novels contained in this collection are + "Du cote de chez Swann ", "A l'ombre des jeunes filles en fleurs","Le Cote de Guermantes", + "Sodome et Gomorrhe I et II", "La Prisonniere", "Albertine disparue", and "Le Temps retrouve". + date_publication: '2019-02-05' + bug_reports: https://github.com/ColinFay/proustr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=proustr + url_git: https://github.com/ColinFay/proustr +provDebugR: + version: 1.0.1 + title: A Time-Travelling Debugger + maintainer: Barbara Lerner + description: |- + Uses provenance post-execution to help the user understand + and debug their script by providing functions to look at intermediate steps and + data values, their forwards and backwards lineage, and to understand the + steps leading up to warning and error messages. 'provDebugR' uses + provenance produced by 'rdtLite' (available on CRAN), stored in PROV-JSON format. + date_publication: '2021-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=provDebugR + url_git: '' +provenance: + version: '4.4' + title: Statistical Toolbox for Sedimentary Provenance Analysis + maintainer: Pieter Vermeesch + description: Bundles a number of established statistical methods to facilitate the + visual interpretation of large datasets in sedimentary geology. Includes functionality + for adaptive kernel density estimation, principal component analysis, correspondence + analysis, multidimensional scaling, generalised procrustes analysis and individual + differences scaling using a variety of dissimilarity measures. Univariate provenance + proxies, such as single-grain ages or (isotopic) compositions are compared with + the Kolmogorov-Smirnov, Kuiper, Wasserstein-2 or Sircombe-Hazelton L2 distances. + Categorical provenance proxies such as chemical compositions are compared with + the Aitchison and Bray-Curtis distances,and count data with the chi-square distance. + Varietal data can either be converted to one or more distributional datasets, + or directly compared using the multivariate Wasserstein distance. Also included + are tools to plot compositional and count data on ternary diagrams and point-counting + data on radial plots, to calculate the sample size required for specified levels + of statistical precision, and to assess the effects of hydraulic sorting on detrital + compositions. Includes an intuitive query-based user interface for users who are + not proficient in R. + date_publication: '2025-01-12' + bug_reports: '' + url: https://www.ucl.ac.uk/~ucfbpve/provenance/ + url_cran: https://CRAN.R-project.org/package=provenance + url_git: '' +proverbs: + version: 0.4.0 + title: Print a Daily Bible Proverb to Console + maintainer: Brad Lindblad + description: |- + A simple package to grab a Bible proverb corresponding to the + day of the month. + date_publication: '2023-11-18' + bug_reports: https://github.com/bradlindblad/proverbs/issues + url: https://bradlindblad.github.io/proverbs/ + url_cran: https://CRAN.R-project.org/package=proverbs + url_git: https://github.com/bradlindblad/proverbs +provExplainR: + version: 1.1.1 + title: Compare Provenance Collections to Explain Changed Script Outputs + maintainer: Barbara Lerner + description: |2- + + Inspects provenance collected by the 'rdt' or 'rdtLite' packages, + or other tools providing compatible PROV JSON output created by + the execution of a script, and find differences between two provenance + collections. Factors under examination included the hardware and + software used to execute the script, versions of attached libraries, + use of global variables, modified inputs and outputs, and changes + in main and sourced scripts. Based on detected changes, 'provExplainR' + can be used to study how these factors affect the behavior of + the script and generate a promising diagnosis of the causes of different + script results. More information about 'rdtLite' and associated tools is available + at and Barbara Lerner, + Emery Boose, and Luis Perez (2018), Using Introspection to Collect + Provenance in R, Informatics, . + date_publication: '2022-08-15' + bug_reports: https://github.com/End-to-end-provenance/provExplainR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=provExplainR + url_git: https://github.com/End-to-end-provenance +provGraphR: + version: 1.0.1 + title: Creates Adjacency Matrices for Lineage Searches + maintainer: Barbara Lerner + description: |- + Creates and manages a provenance graph corresponding to the + provenance created by the 'rdtLite' package, which + collects provenance from R scripts. 'rdtLite' is available on CRAN. + The provenance format is an extension of the + W3C PROV JSON format (). + The extended JSON provenance format is described + in . + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=provGraphR + url_git: '' +provParseR: + version: '1.0' + title: Pulls Information from Prov.Json Files + maintainer: Barbara Lerner + description: |- + R functions to access provenance information collected by 'rdt' or + 'rdtLite'. The information is stored inside a 'ProvInfo' object and can be + accessed through a collection of functions that will return the requested + data. The exact format of the JSON created by 'rdt' and 'rdtLite' is described + in . + date_publication: '2022-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=provParseR + url_git: https://github.com/End-to-end-provenance +provSummarizeR: + version: 1.5.1 + title: |- + Summarizes Provenance Related to Inputs and Outputs of a Script + or Console Commands + maintainer: Emery Boose + description: |- + Reads the provenance collected by the 'rdtLite' or 'rdt' packages, + or other tools providing compatible PROV JSON output, created by the + execution of a script or a console session, and provides a human-readable + summary identifying the input and output files, the scripts used (if any), + errors and warnings produced, and the environment in which it was executed. + It can also optionally package all the files into a zip file. The exact + format of the PROV JSON file created by 'rdtLite' and 'rdt' is described + in . More + information about 'rdtLite' and associated tools is available at + and Lerner, Boose, and Perez + (2018), Using Introspection to Collect Provenance in R, Informatics, + . + date_publication: '2022-08-17' + bug_reports: https://github.com/End-to-end-provenance/provSummarizeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=provSummarizeR + url_git: https://github.com/End-to-end-provenance +provTraceR: + version: '1.0' + title: Uses Provenance to Trace File Lineage for One or more R Scripts + maintainer: Emery Boose + description: |- + Uses provenance collected by 'rdtLite' package or comparable tool + to display information about input files, output files, and exchanged files + for a single R script or a series of R scripts. + date_publication: '2020-08-11' + bug_reports: https://github.com/End-to-end-provenance/provTraceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=provTraceR + url_git: https://github.com/End-to-end-provenance +provViz: + version: 1.0.9 + title: Provenance Visualizer + maintainer: Barbara Lerner + description: |- + Displays provenance graphically for provenance collected by the 'rdt' or + 'rdtLite' packages, or other tools providing compatible PROV JSON output. The exact + format of the JSON created by 'rdt' and 'rdtLite' is described in + . More information about + rdtLite and associated tools is available at + and Barbara Lerner, Emery Boose, and Luis Perez (2018), Using Introspection to Collect + Provenance in R, Informatics, . + date_publication: '2022-08-19' + bug_reports: https://github.com/End-to-end-provenance/provViz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=provViz + url_git: https://github.com/ProvTools/provViz +proxirr: + version: '0.4' + title: Alpha and Beta Proximity to Irreplaceability + maintainer: Daniele Baisero + description: |- + Functions to measure Alpha and Beta Proximity to Irreplaceability. + The methods for Alpha and Beta irreplaceability were first described in: + Baisero D., Schuster R. & Plumptre A.J. + Redefining and Mapping Global Irreplaceability. + Conservation Biology 2021;1-11. + . + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proxirr + url_git: '' +proxy: + version: 0.4-27 + title: Distance and Similarity Measures + maintainer: David Meyer + description: Provides an extensible framework for the efficient calculation of auto- + and cross-proximities, along with implementations of the most popular ones. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=proxy + url_git: '' +proxyC: + version: 0.4.1 + title: Computes Proximity in Large Sparse Matrices + maintainer: Kohei Watanabe + description: |2- + + Computes proximity between rows or columns of large matrices efficiently in C++. + Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. + Among several built-in similarity/distance measures, computation of correlation, + cosine similarity and Euclidean distance is particularly fast. + date_publication: '2024-04-07' + bug_reports: https://github.com/koheiw/proxyC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=proxyC + url_git: https://github.com/koheiw/proxyC +prozor: + version: 0.3.1 + title: Minimal Protein Set Explaining Peptide Spectrum Matches + maintainer: Witold Wolski + description: |- + Determine minimal protein set explaining + peptide spectrum matches. Utility functions for creating fasta amino acid databases with decoys and contaminants. + Peptide false discovery rate estimation for target decoy search results on psm, precursor, peptide and protein + level. Computing dynamic swath window sizes based on MS1 or MS2 signal distributions. + date_publication: '2021-12-07' + bug_reports: https://github.com/protviz/prozor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=prozor + url_git: https://github.com/protviz/prozor +PRP: + version: 0.1.1 + title: Bayesian Prior and Posterior Predictive Replication Assessment + maintainer: Yi Zhao + description: |- + Utilize the Bayesian prior and posterior predictive checking + approach to provide a statistical assessment of replication success + and failure. The package is based on the methods proposed in + Zhao,Y., Wen X.(2021) . + date_publication: '2021-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRP + url_git: '' +prqlr: + version: 0.10.0 + title: R Bindings for the 'prqlc' Rust Library + maintainer: Tatsuya Shima + description: |- + Provides a function to convert 'PRQL' strings to 'SQL' strings. + Combined with other R functions that take 'SQL' as an argument, + 'PRQL' can be used on R. + date_publication: '2025-01-29' + bug_reports: https://github.com/PRQL/prqlc-r/issues + url: https://prql.github.io/prqlc-r/ + url_cran: https://CRAN.R-project.org/package=prqlr + url_git: https://github.com/PRQL/prqlc-r +prrd: + version: 0.0.6 + title: Parallel Runs of Reverse Depends + maintainer: Dirk Eddelbuettel + description: |- + Reverse depends for a given package are queued such that multiple + workers can run the reverse-dependency tests in parallel. + date_publication: '2024-03-06' + bug_reports: https://github.com/eddelbuettel/prrd/issues + url: https://dirk.eddelbuettel.com/code/prrd.html + url_cran: https://CRAN.R-project.org/package=prrd + url_git: https://github.com/eddelbuettel/prrd +PRROC: + version: 1.3.1 + title: Precision-Recall and ROC Curves for Weighted and Unweighted Data + maintainer: Jan Grau + description: 'Computes the areas under the precision-recall (PR) and ROC curve for + weighted (e.g., soft-labeled) and unweighted data. In contrast to other implementations, + the interpolation between points of the PR curve is done by a non-linear piecewise + function. In addition to the areas under the curves, the curves themselves can + also be computed and plotted by a specific S3-method. References: Davis and Goadrich + (2006) ; Keilwagen et al. (2014) ; + Grau et al. (2015) .' + date_publication: '2018-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRROC + url_git: '' +PRSim: + version: '1.5' + title: |- + Stochastic Simulation of Streamflow Time Series using Phase + Randomization + maintainer: Manuela Brunner + description: |- + Provides a simulation framework to simulate streamflow time series with similar main characteristics as observed data. These characteristics include the distribution of daily streamflow values and their temporal correlation as expressed by short- and long-range dependence. The approach is based on the randomization of the phases of the Fourier transform or the phases of the wavelet transform. The function prsim() is applicable to single site simulation and uses the Fourier transform. The function prsim.wave() extends the approach to multiple sites and is based on the complex wavelet transform. The function prsim.weather() extends the approach to multiple variables for weather generation. We further use the flexible four-parameter Kappa distribution, which allows for the extrapolation to yet unobserved low and high flows. Alternatively, the empirical or any other distribution can be used. + A detailed description of the simulation approach for single sites and an application example can be found in Brunner et al. (2019) . + A detailed description and evaluation of the wavelet-based multi-site approach can be found in Brunner and Gilleland (2020) . + A detailed description and evaluation of the multi-variable and multi-site weather generator can be found in Brunner et al. (2021) . + A detailed description and evaluation of the non-stationary streamflow generator can be found in Brunner and Gilleland (2024) . + date_publication: '2024-04-08' + bug_reports: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel/-/issues + url: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel + url_cran: https://CRAN.R-project.org/package=PRSim + url_git: '' +PRSPGx: + version: 0.3.0 + title: Construct PGx PRS + maintainer: Song Zhai + description: Construct pharmacogenomics (PGx) polygenic risk score (PRS) with PRS-PGx-Unadj + (unadjusted), PRS-PGx-CT (clumping and thresholding), PRS-PGx-L, -GL, -SGL (penalized + regression), PRS-PGx-Bayes (Bayesian regression). Package is based on ''Pharmacogenomics + Polyenic Risk Score for Drug Response Prediction Using PRS-PGx Methods'' by Zhai, + S., Zhang, H., Mehrotra, D.V., and Shen, J., 2021 (submitted). + date_publication: '2022-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRSPGx + url_git: '' +pRSR: + version: 3.1.1 + title: Test of Periodicity using Response Surface Regression + maintainer: M. S. Islam + description: Tests periodicity in short time series using response surface regression. + date_publication: '2016-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pRSR + url_git: '' +prt: + version: 0.2.0 + title: Tabular Data Backed by Partitioned 'fst' Files + maintainer: Nicolas Bennett + description: Intended for larger-than-memory tabular data, 'prt' objects provide + an interface to read row and/or column subsets into memory as data.table objects. + Data queries, constructed as 'R' expressions, are evaluated using the non-standard + evaluation framework provided by 'rlang' and file-backing is powered by the fast + and efficient 'fst' package. + date_publication: '2023-04-09' + bug_reports: https://github.com/nbenn/prt/issues + url: https://nbenn.github.io/prt/ + url_cran: https://CRAN.R-project.org/package=prt + url_git: '' +PRTree: + version: 0.1.2 + title: Probabilistic Regression Trees + maintainer: Alisson Silva Neimaier + description: |- + Probabilistic Regression Trees (PRTree). Functions for fitting and predicting PRTree models with some adaptations to handle missing values. The main calculations are performed in 'FORTRAN', resulting in highly efficient algorithms. + This package's implementation is based on the PRTree methodology described in Alkhoury, S.; Devijver, E.; Clausel, M.; Tami, M.; Gaussier, E.; Oppenheim, G. (2020) - "Smooth And Consistent Probabilistic Regression Trees" . + date_publication: '2024-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PRTree + url_git: '' +prWarp: + version: 1.0.1 + title: Warping Landmark Configurations + maintainer: Anne Le Maitre + description: Compute bending energies, principal warps, partial warp scores, and + the non-affine component of shape variation for 2D landmark configurations, as + well as Mardia-Dryden distributions and self-similar distributions of landmarks, + as described in Mitteroecker et al. (2020) . Working + examples to decompose shape variation into small-scale and large-scale components, + and to decompose the total shape variation into outline and residual shape components + are provided. Two landmark datasets are provided, that quantify skull morphology + in humans and papionin primates, respectively from Mitteroecker et al. (2020) + and Grunstra et al. (2020) . + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=prWarp + url_git: '' +pryr: + version: 0.1.6 + title: Tools for Computing on the Language + maintainer: Hadley Wickham + description: |- + Useful tools to pry back the covers of R and understand the + language at a deeper level. + date_publication: '2023-01-17' + bug_reports: https://github.com/hadley/pryr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pryr + url_git: https://github.com/hadley/pryr +Przewodnik: + version: 0.16.12 + title: |- + Datasets and Functions Used in the Book 'Przewodnik po Pakiecie + R' + maintainer: Przemyslaw Biecek + description: |- + Data sets and functions used in the polish book + "Przewodnik po pakiecie R" (The Hitchhiker's Guide to the R). + See more at . Among others you will find here + data about housing prices, cancer patients, running times and many others. + date_publication: '2016-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Przewodnik + url_git: '' +ps: + version: 1.9.0 + title: List, Query, Manipulate System Processes + maintainer: Gábor Csárdi + description: |- + List, query and manipulate all system processes, on + 'Windows', 'Linux' and 'macOS'. + date_publication: '2025-02-18' + bug_reports: https://github.com/r-lib/ps/issues + url: https://ps.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=ps + url_git: https://github.com/r-lib/ps +PSAboot: + version: 1.3.8 + title: Bootstrapping for Propensity Score Analysis + maintainer: Jason Bryer + description: |- + It is often advantageous to test a hypothesis more than once + in the context of propensity score analysis (Rosenbaum, 2012) + . The functions in this package facilitate + bootstrapping for propensity score analysis (PSA). By default, + bootstrapping using two classification tree methods (using 'rpart' and + 'ctree' functions), two matching methods (using 'Matching' and + 'MatchIt' packages), and stratification with logistic regression. A + framework is described for users to implement additional propensity + score methods. Visualizations are emphasized for diagnosing balance; + exploring the correlation relationships between bootstrap samples and + methods; and to summarize results. + date_publication: '2023-10-23' + bug_reports: https://github.com/jbryer/PSAboot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PSAboot + url_git: https://github.com/jbryer/PSAboot +PSAgraphics: + version: 2.1.3 + title: Propensity Score Analysis Graphics + maintainer: Jason Bryer + description: |- + A collection of functions that primarily produce graphics to + aid in a Propensity Score Analysis (PSA). Functions include: cat.psa + and box.psa to test balance within strata of categorical and + quantitative covariates, circ.psa for a representation of the + estimated effect size by stratum, loess.psa that provides a graphic + and loess based effect size estimate, and various balance functions + that provide measures of the balance achieved via a PSA in a + categorical covariate. + date_publication: '2024-03-05' + bug_reports: https://github.com/jbryer/PSAgraphics/issues + url: https://jbryer.github.io/PSAgraphics/ + url_cran: https://CRAN.R-project.org/package=PSAgraphics + url_git: '' +PSAWR: + version: 0.1.0 + title: |- + 'Pushshift' API Wrapper for 'Reddit' Submission and Comment + Search + maintainer: David Schoch + description: Connects to the API of to search for 'Reddit' + comments and submissions. + date_publication: '2023-02-28' + bug_reports: https://github.com/schochastics/PSAWR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PSAWR + url_git: https://github.com/schochastics/PSAWR/ +psBayesborrow: + version: 1.1.0 + title: Bayesian Information Borrowing with Propensity Score Matching + maintainer: Yusuke Yamaguchi + description: Hybrid control design is a way to borrow information from external + controls to augment concurrent controls in a randomized controlled trial and is + expected to overcome the feasibility issue when adequate randomized controlled + trials cannot be conducted. A major challenge in the hybrid control design is + its inability to eliminate a prior-data conflict caused by systematic imbalances + in measured or unmeasured confounding factors between patients in the concurrent + treatment/control group and external controls. To prevent the prior-data conflict, + a combined use of propensity score matching and Bayesian commensurate prior has + been proposed in the context of hybrid control design. The propensity score matching + is first performed to guarantee the balance in baseline characteristics, and then + the Bayesian commensurate prior is constructed while discounting the information + based on the similarity in outcomes between the concurrent and external controls. + 'psBayesborrow' is a package to implement the propensity score matching and the + Bayesian analysis with commensurate prior, as well as to conduct a simulation + study to assess operating characteristics of the hybrid control design, where + users can choose design parameters in flexible and straightforward ways depending + on their own application. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psBayesborrow + url_git: '' +psbcGroup: + version: '1.7' + title: |- + Penalized Parametric and Semiparametric Bayesian Survival Models + with Shrinkage and Grouping Priors + maintainer: Kyu Ha Lee + description: 'Algorithms to implement various Bayesian penalized survival regression + models including: semiparametric proportional hazards models with lasso priors + (Lee et al., Int J Biostat, 2011 ) and three other + shrinkage and group priors (Lee et al., Stat Anal Data Min, 2015 ); + parametric accelerated failure time models with group/ordinary lasso prior (Lee + et al. Comput Stat Data Anal, 2017 ).' + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psbcGroup + url_git: '' +psbcSpeedUp: + version: 2.0.7 + title: Penalized Semiparametric Bayesian Cox Models + maintainer: Zhi Zhao + description: Algorithms to speed up the Bayesian Lasso Cox model (Lee et al., Int + J Biostat, 2011 ) and the Bayesian Lasso Cox with + mandatory variables (Zucknick et al. Biometrical J, 2015 ). + date_publication: '2024-07-01' + bug_reports: https://github.com/ocbe-uio/psbcSpeedUp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psbcSpeedUp + url_git: https://github.com/ocbe-uio/psbcSpeedUp +psborrow: + version: 0.2.2 + title: Bayesian Dynamic Borrowing with Propensity Score + maintainer: Isaac Gravestock + description: A tool which aims to help evaluate the effect of external borrowing + using an integrated approach described in Lewis et al., (2019) + that combines propensity score and Bayesian dynamic borrowing methods. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psborrow + url_git: '' +psborrow2: + version: 0.0.4.0 + title: Bayesian Dynamic Borrowing Analysis and Simulation + maintainer: Matt Secrest + description: |- + Bayesian dynamic borrowing is an approach to incorporating external + data to supplement a randomized, controlled trial analysis in which + external data are incorporated in a dynamic way (e.g., based on similarity + of outcomes); see Viele 2013 for an overview. + This package implements the hierarchical commensurate prior approach to dynamic borrowing + as described in Hobbes 2011 . + There are three main functionalities. First, 'psborrow2' provides a user-friendly + interface for applying dynamic borrowing on the study results handles the Markov Chain + Monte Carlo sampling on behalf of the user. Second, 'psborrow2' provides a + simulation framework to compare different borrowing parameters (e.g. full borrowing, no + borrowing, dynamic borrowing) and other trial and borrowing characteristics + (e.g. sample size, covariates) in a unified way. Third, 'psborrow2' provides + a set of functions to generate data for simulation studies, and also allows + the user to specify their own data generation process. This package is designed to + use the sampling functions from 'cmdstanr' which can be installed from + . + date_publication: '2025-02-12' + bug_reports: https://github.com/Genentech/psborrow2/issues + url: https://genentech.github.io/psborrow2/index.html + url_cran: https://CRAN.R-project.org/package=psborrow2 + url_git: https://github.com/Genentech/psborrow2 +psc: + version: 1.1.0 + title: Personalised Synthetic Controls + maintainer: Richard Jackson + description: Allows the comparison of data cohorts (DC) against a Counter Factual + Model (CFM) and measures the difference in terms of an efficacy parameter. Allows + the application of Personalised Synthetic Controls. + date_publication: '2024-12-12' + bug_reports: https://github.com/richJJackson/psc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psc + url_git: https://github.com/richjjackson/psc/ +PSCBS: + version: 0.67.0 + title: Analysis of Parent-Specific DNA Copy Numbers + maintainer: Henrik Bengtsson + description: Segmentation of allele-specific DNA copy number data and detection + of regions with abnormal copy number within each parental chromosome. Both tumor-normal + paired and tumor-only analyses are supported. + date_publication: '2024-02-17' + bug_reports: https://github.com/HenrikBengtsson/PSCBS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PSCBS + url_git: https://github.com/HenrikBengtsson/PSCBS +pscl: + version: 1.5.9 + title: Political Science Computational Laboratory + maintainer: Simon Jackman + description: "Bayesian analysis of item-response theory (IRT) models,\nroll call + analysis; computing highest density regions;\nmaximum likelihood estimation of + zero-inflated and hurdle models for count data;\ngoodness-of-fit measures for + GLMs;\ndata sets used in writing\tand teaching; seats-votes curves." + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pscl + url_git: https://github.com/atahk/pscl +pscore: + version: 0.4.0 + title: Standardizing Physiological Composite Risk Endpoints + maintainer: Joshua F. Wiley + description: |- + Provides a number of functions to + simplify and automate the scoring, comparison, and evaluation of + different ways of creating composites of data. It is particularly + aimed at facilitating the creation of physiological composites of + metabolic syndrome symptom score (MetSSS) and allostatic load (AL). + Provides a wrapper to calculate the MetSSS on new data using the + Healthy Hearts formula. + date_publication: '2022-05-13' + bug_reports: https://github.com/JWiley/score-project/issues + url: https://score-project.org + url_cran: https://CRAN.R-project.org/package=pscore + url_git: https://github.com/JWiley/score-project +PScr: + version: '1.1' + title: Estimation for the Power Series Cure Rate Model + maintainer: Diego Gallardo + description: |- + Provide estimation for particular cases of the power series cure rate model + . For the distribution of the concurrent causes the + alternative models are the Poisson, logarithmic, negative binomial and Bernoulli (which + are includes in the original work), the polylogarithm model + and the Flory-Schulz . + The estimation procedure is based on the EM algorithm discussed in + . + For the distribution of the time-to-event the alternative models are slash half-normal, + Weibull, gamma and Birnbaum-Saunders distributions. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PScr + url_git: '' +psd: + version: 2.1.1 + title: |- + Adaptive, Sine-Multitaper Power Spectral Density and Cross + Spectrum Estimation + maintainer: Andrew J. Barbour + description: |- + Produces power spectral density estimates through iterative + refinement of the optimal number of sine-tapers at each frequency. This + optimization procedure is based on the method of Riedel and Sidorenko + (1995), which minimizes the Mean Square Error (sum of variance and bias) + at each frequency, but modified for computational stability. The same + procedure can now be used to calculate the cross spectrum (multivariate + analyses). + date_publication: '2022-01-31' + bug_reports: https://github.com/abarbour/psd/issues + url: BarbourandParker(2014):https://doi.org/10.1016/j.cageo.2013.09.015 + url_cran: https://CRAN.R-project.org/package=psd + url_git: https://github.com/abarbour/psd +psData: + version: 0.2.2 + title: Download Regularly Maintained Political Science Data Sets + maintainer: Christopher Gandrud + description: |- + This R package includes functions for gathering commonly used and + regularly maintained data set in political science. It also includes + functions for combining components from these data sets into variables that + have been suggested in the literature, but are not regularly maintained. + date_publication: '2016-09-03' + bug_reports: https://github.com/christophergandrud/psData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psData + url_git: '' +PSDistr: + version: 0.0.1 + title: Distributions Derived from Normal Distribution + maintainer: Piotr Sulewski + description: 'Presentation of distributions such as: two-piece power normal (TPPN), + plasticizing component (PC), DS normal (DSN), expnormal (EN), Sulewski plasticizing + component (SPC), easily changeable kurtosis (ECK) distributions. Density, distribution + function, quantile function and random generation are presented. For details on + this method see: Sulewski (2019) , Sulewski + (2021) , Sulewski (2021) , + Sulewski (2022) <"New members of the Johnson family of probability dis-tributions: + properties and application">, Sulewski, Volodin (2022) , + Sulewski (2023) .' + date_publication: '2023-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSDistr + url_git: '' +psdr: + version: 1.0.1 + title: Use Time Series to Generate and Compare Power Spectral Density + maintainer: Yong-Han Hank Cheng + description: |- + Functions that allow you to generate and compare power spectral density (PSD) + plots given time series data. Fast Fourier Transform (FFT) is used to take a time series + data, analyze the oscillations, and then output the frequencies of these oscillations + in the time series in the form of a PSD plot.Thus given a time series, the dominant + frequencies in the time series can be identified. Additional functions in this package + allow the dominant frequencies of multiple groups of time series to be compared with each other. + To see example usage with the main functions of this package, please visit + this site: . + The mathematical operations used to generate the PSDs are described in these sites: + . + . + date_publication: '2021-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psdr + url_git: '' +pseudo: + version: 1.4.3 + title: Computes Pseudo-Observations for Modeling + maintainer: Kevin Rodrigues + description: 'Various functions for computing pseudo-observations for censored data + regression. Computes pseudo-observations for modeling: competing risks based on + the cumulative incidence function, survival function based on the restricted mean, survival + function based on the Kaplan-Meier estimator see Klein et al. (2008) .' + date_publication: '2017-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pseudo + url_git: '' +pseudobibeR: + version: '1.2' + title: Aggregate Counts of Linguistic Features + maintainer: David Brown + description: |- + Calculates the lexicogrammatical and functional features described + by Biber (1985) and widely used for + text-type, register, and genre classification tasks. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pseudobibeR + url_git: '' +pseudoCure: + version: 1.0.0 + title: |- + A Pseudo-Observations Approach for Analyzing Survival Data with + a Cure Fraction + maintainer: Sy Han (Steven) Chiou + description: A collection of easy-to-use tools for regression analysis of survival + data with a cure fraction proposed in Su et al. (2022) . + The modeling framework is based on the Cox proportional hazards mixture cure model + and the bounded cumulative hazard (promotion time cure) model. The pseudo-observations + approach is utilized to assess covariate effects and embedded in the variable + selection procedure. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pseudoCure + url_git: '' +pseudohouseholds: + version: 0.1.1 + title: Generate Pseudohouseholds on Road Networks in Regions + maintainer: Christopher Belanger + description: |- + Given an arbitrary set of spatial regions and road networks, + generate a set of representative points, or pseudohouseholds, that + can be used for travel burden analysis. Parallel processing is + supported. + date_publication: '2023-07-19' + bug_reports: https://github.com/chris31415926535/pseudohouseholds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pseudohouseholds + url_git: https://github.com/chris31415926535/pseudohouseholds +pseudorank: + version: 1.0.4 + title: Pseudo-Ranks + maintainer: Martin Happ + description: Efficient calculation of pseudo-ranks and (pseudo)-rank based test + statistics. In case of equal sample sizes, pseudo-ranks and mid-ranks are equal. + When used for inference mid-ranks may lead to paradoxical results. Pseudo-ranks + are in general not affected by such a problem. See Happ et al. (2020, ) + for details. + date_publication: '2025-02-20' + bug_reports: https://github.com/happma/pseudorank/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=pseudorank + url_git: https://github.com/happma/pseudorank/ +pseval: + version: 1.3.1 + title: |- + Methods for Evaluating Principal Surrogates of Treatment + Response + maintainer: Michael C Sachs + description: |- + Contains the core methods for the evaluation of principal + surrogates in a single clinical trial. Provides a flexible interface for + defining models for the risk given treatment and the surrogate, the models + for integration over the missing counterfactual surrogate responses, and the + estimation methods. Estimated maximum likelihood and pseudo-score can be used + for estimation, and the bootstrap for inference. A variety of post-estimation + summary methods are provided, including print, summary, plot, and testing. + date_publication: '2019-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pseval + url_git: '' +PSF: + version: '0.5' + title: |- + Forecasting of Univariate Time Series Using the Pattern + Sequence-Based Forecasting (PSF) Algorithm + maintainer: Neeraj Bokde + description: |- + Pattern Sequence Based Forecasting (PSF) takes univariate + time series data as input and assist to forecast its future values. + This algorithm forecasts the behavior of time series + based on similarity of pattern sequences. Initially, clustering is done with the + labeling of samples from database. The labels associated with samples are then + used for forecasting the future behaviour of time series data. The further + technical details and references regarding PSF are discussed in Vignette. + date_publication: '2022-05-01' + bug_reports: https://github.com/neerajdhanraj/PSF/issues + url: https://www.neerajbokde.in/viggnette/2021-10-13-PSF/ + url_cran: https://CRAN.R-project.org/package=PSF + url_git: '' +psfmi: + version: 1.4.0 + title: |- + Prediction Model Pooling, Selection and Performance Evaluation + Across Multiply Imputed Datasets + maintainer: Martijn Heymans + description: "\nPooling, backward and forward selection of linear, logistic and + Cox regression models in\nmultiply imputed datasets. Backward and forward selection + can be done\nfrom the pooled model using Rubin's Rules (RR), the D1, D2, D3, D4 + and\nthe median p-values method. This is also possible for Mixed models.\nThe + models can contain continuous, dichotomous, categorical and restricted\ncubic + spline predictors and interaction terms between\tall these type of predictors.\nThe + stability of the models\tcan be evaluated using (cluster) bootstrapping. The package\nfurther + contains functions to pool model performance measures as ROC/AUC, Reclassification,\nR-squared, + scaled Brier score, H&L test and calibration\tplots for logistic regression models.\nInternal + validation can be done across multiply imputed datasets with cross-validation + or\nbootstrapping. The adjusted intercept after shrinkage of pooled regression + coefficients\ncan be obtained. Backward and forward selection as part of internal + validation is possible.\nA function to externally validate logistic prediction + models in multiple imputed\ndatasets is available and a function to compare models. + For Cox models a strata variable\ncan be included.\nEekhout (2017) .\nWiel + (2009) .\nMarshall (2009) ." + date_publication: '2023-06-17' + bug_reports: https://github.com/mwheymans/psfmi/issues/ + url: https://mwheymans.github.io/psfmi/ + url_cran: https://CRAN.R-project.org/package=psfmi + url_git: '' +PSGD: + version: 1.0.4 + title: Projected Subset Gradient Descent + maintainer: Anthony Christidis + description: |- + Functions to generate ensembles of generalized linear models using + a greedy projected subset gradient descent algorithm. The sparsity + and diversity tuning parameters are selected by cross-validation. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSGD + url_git: '' +PSGoft: + version: 0.0.1 + title: Modified Lilliefors Goodness-of-Fit Normality Test + maintainer: Piotr Sulewski + description: 'Presentation of a new goodness-of-fit normality test based on the + Lilliefors method. For details on this method see: Sulewski (2019) .' + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSGoft + url_git: '' +psgp: + version: 0.3-21 + title: Projected Spatial Gaussian Process Methods + maintainer: Ben Ingram + description: Implements projected sparse Gaussian process Kriging (Ingram 'et. al.', + 2008, ) as an additional method for the 'intamap' + package. More details on implementation (Barillec 'et. al.', 2010, ). + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psgp + url_git: '' +psHarmonize: + version: 0.3.5 + title: Creates a Harmonized Dataset Based on a Set of Instructions + maintainer: John Stephen + description: |- + Functions which facilitate harmonization of data from multiple + different datasets. Data harmonization involves taking data sources with + differing values, creating coding instructions to create a harmonized + set of values, then making those data modifications. 'psHarmonize' will + assist with data modification once the harmonization instructions are + written. Coding instructions are written by the user to create a + "harmonization sheet". This sheet catalogs variable names, domains + (e.g. clinical, behavioral, outcomes), provides R code instructions for + mapping or conversion of data, specifies the variable name in the + harmonized data set, and tracks notes. The package will then harmonize + the source datasets according to the harmonization sheet to create a + harmonized dataset. Once harmonization is finished, the package also has + functions that will create descriptive statistics using 'RMarkdown'. Data + Harmonization guidelines have been described by Fortier I, Raina P, + Van den Heuvel ER, et al. (2017) . Additional + details of our R package have been described by Stephen JJ, Carolan P, + Krefman AE, et al. (2024) . + date_publication: '2025-01-15' + bug_reports: https://github.com/NUDACC/psHarmonize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psHarmonize + url_git: https://github.com/NUDACC/psHarmonize +psica: + version: 1.0.2 + title: |- + Decision Tree Analysis for Probabilistic Subgroup Identification + with Multiple Treatments + maintainer: Oleg Sysoev + description: |- + In the situation when multiple alternative treatments or + interventions available, different population groups may respond differently + to different treatments. This package implements a method that discovers + the population subgroups in which a certain treatment has a better effect + than the other alternative treatments. This is done by first estimating the + treatment effect for a given treatment and its uncertainty by computing random + forests, and the resulting model is summarized by a decision tree in which the + probabilities that the given treatment is best for a given subgroup is shown in + the corresponding terminal node of the tree. + date_publication: '2020-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psica + url_git: '' +psidR: + version: '2.3' + title: Build Panel Data Sets from PSID Raw Data + maintainer: Florian Oswald + description: |- + Makes it easy to build panel data in wide format from Panel Survey + of Income Dynamics (PSID) delivered raw data. Downloads data directly from + the PSID server using the 'SAScii' package. 'psidR' takes care of merging + data from each wave onto a cross-period index file, so that individuals can be + followed over time. The user must specify which years they are interested in, + and the 'PSID' variable names (e.g. ER21003) for each year (they differ in each + year). The package offers helper functions to retrieve variable names from different + waves. There are different panel data designs and sample subsetting criteria + implemented ("SRC", "SEO", "immigrant" and "latino" samples). More information about + the PSID can be obtained at . + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psidR + url_git: https://github.com/floswald/psidR +psidread: + version: 1.0.3 + title: |- + Streamline Building Panel Data from Panel Study of Income + Dynamics ('PSID') Raw Files + maintainer: Shuyi Qiu + description: Streamline the management, creation, and formatting of panel data from + the Panel Study of Income Dynamics ('PSID') + using this user-friendly tool. Simply define variable names and input code book + details directly from the 'PSID' official website, and this toolbox will efficiently + facilitate the data preparation process, transforming raw 'PSID' files into a + well-organized format ready for further analysis. + date_publication: '2024-02-05' + bug_reports: https://github.com/Qcrates/psidread/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psidread + url_git: https://github.com/Qcrates/psidread +PSIM: + version: 0.1.0 + title: Preference Selection Index Method (PSIM) + maintainer: Luana Oliveira + description: The Preference Selection Index Method was created in (2010) and provides + an innovative approach to determining the relative importance of criteria without + pairwise comparisons, unlike the Analytic Hierarchy Process. The Preference Selection + Index Method uses statistical methods to calculate the criteria weights and reflects + their relative importance in the final decision-making process, offering an objective + and non-subjective solution. This method is beneficial in multi-criteria decision + analysis. The 'PSIM' package provides a practical and accessible tool for implementing + the Preference Selection Index Method in R. It calculates the weights of criteria + and makes the method available to researchers, analysts, and professionals without + the need to develop complex calculations manually. More details about the Preference + Selection Index Method can be found in Maniya K. and Bhatt M. G.(2010) . + date_publication: '2024-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSIM + url_git: https://github.com/luana1909/PSIM +PSIndependenceTest: + version: 0.0.1 + title: |- + Independence Tests for Two-Way, Three-Way and Four-Way + Contingency Tables + maintainer: Piotr Sulewski + description: 'Presentation two independence tests for two-way, three-way and four-way + contingency tables. These tests are: the modular test and the logarithmic minimum + test. For details on this method see: Sulewski (2017) , + Sulewski (2018) , Sulewski (2019) , + Sulewski (2021) .' + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSIndependenceTest + url_git: '' +PSinference: + version: 0.2.2 + title: Inference for Released Plug-in Sampling Single Synthetic Dataset + maintainer: Ricardo Moura + description: Considering the singly imputed synthetic data generated via plug-in + sampling under the multivariate normal model, draws inference procedures including + the generalized variance, the sphericity test, the test for independence between + two subsets of variables, and the test for the regression of one set of variables + on the other. For more details see Klein et al. (2021) . + date_publication: '2024-12-10' + bug_reports: https://github.com/ricardomourarpm/PSinference/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PSinference + url_git: https://github.com/ricardomourarpm/PSinference +PSLM2015: + version: 0.2.0 + title: Pakistan Social and Living Standards Measurement Survey 2014-15 + maintainer: Muhammad Yaseen + description: Data and statistics of Pakistan Social and Living Standards Measurement + (PSLM) survey 2014-15 from Pakistan Bureau of Statistics (). + date_publication: '2017-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSLM2015 + url_git: https://github.com/MYaseen208/PSLM2015 +psm3mkv: + version: 0.3.2 + title: Evaluate Partitioned Survival and State Transition Models + maintainer: Dominic Muston + description: |- + Fits and evaluates three-state partitioned survival analyses + (PartSAs) and Markov models (clock forward or clock reset) to + progression and overall survival data typically collected in oncology clinical trials. These model structures are typically considered in + cost-effectiveness modeling in advanced/metastatic cancer indications. + Muston (2024). "Informing structural assumptions for three state oncology cost-effectiveness models through model efficiency and fit". Applied Health Economics and Health Policy. + date_publication: '2024-06-07' + bug_reports: https://github.com/Merck/psm3mkv/issues + url: https://merck.github.io/psm3mkv/ + url_cran: https://CRAN.R-project.org/package=psm3mkv + url_git: https://github.com/Merck/psm3mkv +psmineR: + version: 0.1.0 + title: Performance Spectrum Miner for Event Data + maintainer: Gert Janssenswillen + description: Compute detailed and aggregated performance spectrum for event data. + The detailed performance spectrum describes the event data in terms of segments, + where the performance of each segment is measured and plotted for any occurrences + of this segment over time and can be classified, e.g., regarding the overall population. + The aggregated performance spectrum visualises the amount of cases of particular + performance over time. Denisov, V., Fahland, D., & van der Aalst, W. M. P. (2018) + . + date_publication: '2022-10-10' + bug_reports: https://github.com/bupaverse/psmineR/issues + url: https://bupar.net/ + url_cran: https://CRAN.R-project.org/package=psmineR + url_git: https://github.com/bupaverse/psmineR/ +pso: + version: 1.0.4 + title: Particle Swarm Optimization + maintainer: Claus Bendtsen + description: Provides an implementation of particle swarm optimisation consistent + with the standard PSO 2007/2011 by Maurice Clerc. Additionally a number of ancillary + routines are provided for easy testing and graphics. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pso + url_git: '' +psoptim: + version: '1.0' + title: Particle Swarm Optimization + maintainer: Krzysztof Ciupke + description: Particle swarm optimization - a basic variant. + date_publication: '2016-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psoptim + url_git: '' +psp: + version: 1.0.2 + title: Parameter Space Partitioning MCMC for Global Model Evaluation + maintainer: Lenard Dome + description: Implements an n-dimensional parameter space partitioning algorithm + for evaluating the global behaviour of formal computational models as described + by Pitt, Kim, Navarro and Myung (2006) . + date_publication: '2024-07-24' + bug_reports: https://github.com/lenarddome/psp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psp + url_git: https://github.com/lenarddome/psp +pspatreg: + version: 1.1.2 + title: |- + Spatial and Spatio-Temporal Semiparametric Regression Models + with Spatial Lags + maintainer: Roman Minguez + description: |- + Estimation and inference of spatial and spatio-temporal + semiparametric models including spatial or spatio-temporal non-parametric + trends, parametric and non-parametric covariates and, possibly, a spatial + lag for the dependent variable and temporal correlation in the noise. + The spatio-temporal trend can be decomposed in ANOVA way including main and + interaction functional terms. Use of SAP algorithm to estimate the spatial + or spatio-temporal trend and non-parametric covariates. The methodology of + these models can be found in next references + Basile, R. et al. (2014), ; + Rodriguez-Alvarez, M.X. et al. (2015) and, + particularly referred to the focus of the package, Minguez, R., + Basile, R. and Durban, M. (2020) . + date_publication: '2023-10-06' + bug_reports: https://github.com/rominsal/pspatreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pspatreg + url_git: https://github.com/rominsal/pspatreg +pspearman: + version: 0.3-1 + title: Spearman's Rank Correlation Test + maintainer: Petr Savicky + description: |- + Spearman's rank correlation test with precomputed exact + null distribution for n <= 22. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pspearman + url_git: '' +pspline: + version: 1.0-21 + title: Penalized Smoothing Splines + maintainer: Brian Ripley + description: Smoothing splines with penalties on order m derivatives. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pspline + url_git: '' +PSPManalysis: + version: 0.3.9 + title: Analysis of Physiologically Structured Population Models + maintainer: Andre M. de Roos + description: |- + Performs demographic, bifurcation and evolutionary analysis of physiologically structured population models, which is a class of models that consistently translates continuous-time models of individual life history to the population level. + A model of individual life history has to be implemented specifying the individual-level functions that determine the life history, such as development and mortality rates and fecundity. + M.A. Kirkilionis, O. Diekmann, B. Lisser, M. Nool, B. Sommeijer & A.M. de Roos (2001) . + O.Diekmann, M.Gyllenberg & J.A.J.Metz (2003) . + A.M. de Roos (2008) . + date_publication: '2023-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSPManalysis + url_git: '' +PSpower: + version: 0.1.0 + title: Sample Size Calculation for Propensity Score Analysis + maintainer: Bo Liu + description: Sample size calculations in causal inference with observational data + are increasingly desired. This package is a tool to calculate sample size under + prespecified power with minimal summary quantities needed. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSpower + url_git: '' +psqn: + version: 0.3.2 + title: Partially Separable Quasi-Newton + maintainer: Benjamin Christoffersen + description: |- + Provides quasi-Newton methods to minimize partially separable + functions. The methods are largely described by + Nocedal and Wright (2006) . + date_publication: '2024-09-22' + bug_reports: https://github.com/boennecd/psqn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psqn + url_git: https://github.com/boennecd/psqn +PSS.Health: + version: 1.1.4 + title: Power and Sample Size for Health Researchers via Shiny + maintainer: Rogério Boff Borges + description: |- + Power and Sample Size for Health Researchers is a Shiny application that brings together a + series of functions related to sample size and power calculations for common analysis in the healthcare + field. There are functionalities to calculate the power, sample size to estimate or test hypotheses for means and + proportions (including test for correlated groups, equivalence, non-inferiority and superiority), association, correlations coefficients, + regression coefficients (linear, logistic, gamma, and Cox), linear mixed model, + Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, + limit of agreement on Bland-Altman plots, + area under the curve, sensitivity and specificity incorporating the prevalence of disease. + You can also use the online version at . + date_publication: '2024-12-20' + bug_reports: '' + url: https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/ + url_cran: https://CRAN.R-project.org/package=PSS.Health + url_git: '' +PSSIM: + version: 0.1.0 + title: Test of Independence & Image Structural Similarity Measure PSSIM + maintainer: Haiyan Wang + description: |- + Test-based Image structural similarity measure and test of independence. + This package implements the key functions of two tasks: (1) computing + image structural similarity measure PSSIM of Wang, Maldonado and + Silwal (2011) ; + and (2) test of independence between a response and + a covariate in presence of heteroscedastic treatment effects + proposed by Wang, Tolos, and Wang (2010) . + date_publication: '2020-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSSIM + url_git: '' +PSSMCOOL: + version: 0.2.4 + title: Features Extracted from Position Specific Scoring Matrix (PSSM) + maintainer: Alireza mohammadi + description: |- + Returns almost all features that has been extracted from Position Specific + Scoring Matrix (PSSM) so far, which is a matrix of L rows (L is protein length) + and 20 columns produced by 'PSI-BLAST' which is a program to produce + PSSM Matrix from multiple sequence alignment of proteins + see for mor details. some + of these features are described in Zahiri, J., et al.(2013) + , + Saini, H., et al.(2016) + , + Ding, S., et al.(2014) + , + Cheng, C.W., et al.(2008) + , + Juan, E.Y., et al.(2009) + . + date_publication: '2022-01-04' + bug_reports: https://github.com/BioCool-Lab/PSSMCOOL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PSSMCOOL + url_git: https://github.com/BioCool-Lab/PSSMCOOL +pssmooth: + version: 1.0.3 + title: |- + Flexible and Efficient Evaluation of Principal + Surrogates/Treatment Effect Modifiers + maintainer: Michal Juraska + description: 'Implements estimation and testing procedures for evaluating an intermediate + biomarker response as a principal surrogate of a clinical response to treatment + (i.e., principal stratification effect modification analysis), as described in + Juraska M, Huang Y, and Gilbert PB (2020), Inference on treatment effect modification + by biomarker response in a three-phase sampling design, Biostatistics, 21(3): + 545-560 . The methods avoid the restrictive + ''placebo structural risk'' modeling assumption common to past methods and further + improve robustness by the use of nonparametric kernel smoothing for biomarker + density estimation. A randomized controlled two-group clinical efficacy trial + is assumed with an ordered categorical or continuous univariate biomarker response + measured at a fixed timepoint post-randomization and with a univariate baseline + surrogate measure allowed to be observed in only a subset of trial participants + with an observed biomarker response (see the flexible three-phase sampling design + in the paper for details). Bootstrap-based procedures are available for pointwise + and simultaneous confidence intervals and testing of four relevant hypotheses. + Summary and plotting functions are provided for estimation results.' + date_publication: '2020-11-18' + bug_reports: https://github.com/mjuraska/pssmooth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pssmooth + url_git: https://github.com/mjuraska/pssmooth +psSubpathway: + version: 0.1.3 + title: Flexible Identification of Phenotype-Specific Subpathways + maintainer: Junwei Han + description: |- + A network-based systems biology tool for flexible identification of phenotype-specific subpathways in the cancer gene expression data + with multiple categories (such as multiple subtype or developmental stages of cancer). Subtype Set Enrichment Analysis (SubSEA) and Dynamic Changed + Subpathway Analysis (DCSA) are developed to flexible identify subtype specific and dynamic changed subpathways respectively. The operation modes + include extraction of subpathways from biological pathways, inference of subpathway activities in the context of gene expression data, identification + of subtype specific subpathways with SubSEA, identification of dynamic changed subpathways associated with the cancer developmental stage with DCSA, + and visualization of the activities of resulting subpathways by using box plots and heat maps. Its capabilities render the tool could find the specific + abnormal subpathways in the cancer dataset with multi-phenotype samples. + date_publication: '2024-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psSubpathway + url_git: '' +PST: + version: 0.94.1 + title: Probabilistic Suffix Trees and Variable Length Markov Chains + maintainer: Alexis Gabadinho + description: 'Provides a framework for analysing state sequences with probabilistic + suffix trees (PST), the construction that stores variable length Markov chains + (VLMC). Besides functions for learning and optimizing VLMC models, the PST library + includes many additional tools to analyse sequence data with these models: visualization + tools, functions for sequence prediction and artificial sequences generation, + as well as for context and pattern mining. The package is specifically adapted + to the field of social sciences by allowing to learn VLMC models from sets of + individual sequences possibly containing missing values, and by accounting for + case weights. The library also allows to compute probabilistic divergence between + two models, and to fit segmented VLMC, where sub-models fitted to distinct strata + of the learning sample are stored in a single PST. This software results from + research work executed within the framework of the Swiss National Centre of Competence + in Research LIVES, which is financed by the Swiss National Science Foundation. + The authors are grateful to the Swiss National Science Foundation for its financial + support.' + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PST + url_git: https://r-forge.r-project.org/projects/pst +Pstat: + version: '1.2' + title: Assessing Pst Statistics + maintainer: Blondeau Da Silva Stephane + description: Calculating Pst values to assess differentiation among populations + from a set of quantitative traits is the primary purpose of such a package. The + bootstrap method provides confidence intervals and distribution histograms of + Pst. Variations of Pst in function of the parameter c/h^2 are studied as well. + Finally, the package proposes different transformations especially to eliminate + any variation resulting from allometric growth (calculation of residuals from + linear regressions, Reist standardizations or Aitchison transformation). + date_publication: '2017-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Pstat + url_git: '' +pstest: + version: 0.1.3.900 + title: Specification Tests for Parametric Propensity Score Models + maintainer: Pedro H. C. Sant'Anna + description: |- + The propensity score is one of the most widely used tools in + studying the causal effect of a treatment, intervention, or policy. Given that + the propensity score is usually unknown, it has to be estimated, implying that + the reliability of many treatment effect estimators depends on the correct + specification of the (parametric) propensity score. This package implements the + data-driven nonparametric diagnostic tools for detecting propensity score + misspecification proposed by Sant'Anna and Song (2019) . + date_publication: '2019-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pstest + url_git: https://github.com/pedrohcgs/pstest +PStrata: + version: 0.0.5 + title: Principal Stratification Analysis in R + maintainer: Bo Liu + description: Estimating causal effects in the presence of post-treatment confounding + using principal stratification. 'PStrata' allows for customized monotonicity assumptions + and exclusion restriction assumptions, with automatic full Bayesian inference + supported by 'Stan'. The main function to use in this package is PStrata(), which + provides posterior estimates of principal causal effect with uncertainty quantification. + Visualization tools are also provided for diagnosis and interpretation. See Liu + and Li (2023) for details. + date_publication: '2023-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PStrata + url_git: '' +psvd: + version: 0.1-0 + title: Eigendecomposition, Singular-Values and the Power Method + maintainer: Doulaye Dembele + description: |- + For a data matrix with m rows and n columns (m>=n), the power + method is used to compute, simultaneously, the eigendecomposition + of a square symmetric matrix. This result is used to obtain the + singular value decomposition (SVD) and the principal component + analysis (PCA) results. Compared to the classical SVD method, + the first r singular values can be computed. + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psvd + url_git: '' +psvmSDR: + version: 1.0.2 + title: Unified Principal Sufficient Dimension Reduction Package + maintainer: Jungmin Shin + description: A unified and user-friendly framework for applying the principal sufficient + dimension reduction methods for both linear and nonlinear cases. The package has + an extendable power by varying loss functions for the support vector machine, + even for an user-defined arbitrary function, unless those are convex and differentiable + everywhere over the support (Li et al. (2011) ). Also, + it provides a real-time sufficient dimension reduction update procedure using + the principal least squares support vector machine (Artemiou et al. (2021) ). + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psvmSDR + url_git: '' +PSW: + version: 1.1-3 + title: Propensity Score Weighting Methods for Dichotomous Treatments + maintainer: Huzhang Mao + description: 'Provides propensity score weighting methods to control for confounding + in causal inference with dichotomous treatments and continuous/binary outcomes. + It includes the following functional modules: (1) visualization of the propensity + score distribution in both treatment groups with mirror histogram, (2) covariate + balance diagnosis, (3) propensity score model specification test, (4) weighted + estimation of treatment effect, and (5) augmented estimation of treatment effect + with outcome regression. The weighting methods include the inverse probability + weight (IPW) for estimating the average treatment effect (ATE), the IPW for average + treatment effect of the treated (ATT), the IPW for the average treatment effect + of the controls (ATC), the matching weight (MW), the overlap weight (OVERLAP), + and the trapezoidal weight (TRAPEZOIDAL). Sandwich variance estimation is provided + to adjust for the sampling variability of the estimated propensity score. These + methods are discussed by Hirano et al (2003) , Lunceford + and Davidian (2004) , Li and Greene (2013) , + and Li et al (2016) .' + date_publication: '2018-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSW + url_git: '' +PSweight: + version: 2.1.0 + title: |- + Propensity Score Weighting for Causal Inference with + Observational Studies and Randomized Trials + maintainer: Yukang Zeng + description: Supports propensity score weighting analysis of observational studies + and randomized trials. Enables the estimation and inference of average causal + effects with binary and multiple treatments using overlap weights (ATO), inverse + probability of treatment weights (ATE), average treatment effect among the treated + weights (ATT), matching weights (ATM) and entropy weights (ATEN), with and without + propensity score trimming. These weights are members of the family of balancing + weights introduced in Li, Morgan and Zaslavsky (2018) + and Li and Li (2019) . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PSweight + url_git: https://github.com/thuizhou/PSweight +psy: + version: '1.2' + title: Various Procedures Used in Psychometrics + maintainer: Bruno Falissard + description: |- + Kappa, ICC, reliability coefficient, parallel analysis, + multi-traits multi-methods, spherical representation of a correlation matrix. + date_publication: '2022-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psy + url_git: '' +psycCleaning: + version: 0.1.1 + title: Data Cleaning for Psychological Analyses + maintainer: Jason Moy + description: Useful for preparing and cleaning data. It includes functions to center + data, reverse coding, dummy code and effect code data, and more. + date_publication: '2023-11-05' + bug_reports: '' + url: https://jasonmoy28.github.io/psycCleaning/ + url_cran: https://CRAN.R-project.org/package=psycCleaning + url_git: '' +psych: + version: 2.4.12 + title: |- + Procedures for Psychological, Psychometric, and Personality + Research + maintainer: William Revelle + description: A general purpose toolbox developed originally for personality, psychometric + theory and experimental psychology. Functions are primarily for multivariate + analysis and scale construction using factor analysis, principal component analysis, + cluster analysis and reliability analysis, although others provide basic descriptive + statistics. Item Response Theory is done using factor analysis of tetrachoric + and polychoric correlations. Functions for analyzing data at multiple levels include + within and between group statistics, including correlations and factor analysis. Validation + and cross validation of scales developed using basic machine learning algorithms + are provided, as are functions for simulating and testing particular item and + test structures. Several functions serve as a useful front end for structural + equation modeling. Graphical displays of path diagrams, including mediation models, + factor analysis and structural equation models are created using basic graphics. + Some of the functions are written to support a book on psychometric theory as + well as publications in personality research. For more information, see the + web page. + date_publication: '2024-12-23' + bug_reports: '' + url: https://personality-project.org/r/psych/https://personality-project.org/r/psych-manual.pdf + url_cran: https://CRAN.R-project.org/package=psych + url_git: '' +psychmeta: + version: 2.7.0 + title: Psychometric Meta-Analysis Toolkit + maintainer: Jeffrey A. Dahlke + description: Tools for computing bare-bones and psychometric meta-analyses and for + generating psychometric data for use in meta-analysis simulations. Supports bare-bones, + individual-correction, and artifact-distribution methods for meta-analyzing correlations + and d values. Includes tools for converting effect sizes, computing sporadic artifact + corrections, reshaping meta-analytic databases, computing multivariate corrections + for range variation, and more. Bugs can be reported to + or . + date_publication: '2024-06-19' + bug_reports: https://github.com/psychmeta/psychmeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psychmeta + url_git: '' +psycho: + version: 0.6.1 + title: |- + Efficient and Publishing-Oriented Workflow for Psychological + Science + maintainer: Dominique Makowski + description: |- + The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, + to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output + of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity. + date_publication: '2021-01-19' + bug_reports: https://github.com/neuropsychology/psycho.R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psycho + url_git: https://github.com/neuropsychology/psycho.R +psychometric: + version: '2.4' + title: Applied Psychometric Theory + maintainer: Thomas D. Fletcher + description: |- + Contains functions useful for correlation theory, + meta-analysis (validity-generalization), reliability, + item analysis, inter-rater reliability, and classical utility. + date_publication: '2023-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psychometric + url_git: '' +psychomix: + version: 1.1-9 + title: Psychometric Mixture Models + maintainer: Achim Zeileis + description: |- + Psychometric mixture models based on 'flexmix' infrastructure. At the moment Rasch mixture models + with different parameterizations of the score distribution (saturated vs. mean/variance specification), + Bradley-Terry mixture models, and MPT mixture models are implemented. These mixture models can be estimated + with or without concomitant variables. See Frick et al. (2012) and + Frick et al. (2015) for details on the Rasch mixture models. + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psychomix + url_git: '' +psychonetrics: + version: '0.13' + title: Structural Equation Modeling and Confirmatory Network Analysis + maintainer: Sacha Epskamp + description: Multi-group (dynamical) structural equation models in combination with + confirmatory network models from cross-sectional, time-series and panel data . + Allows for confirmatory testing and fit as well as exploratory model search. + date_publication: '2024-06-20' + bug_reports: https://github.com/SachaEpskamp/psychonetrics/issues + url: http://psychonetrics.org/ + url_cran: https://CRAN.R-project.org/package=psychonetrics + url_git: '' +psychotools: + version: 0.7-4 + title: Psychometric Modeling Infrastructure + maintainer: Achim Zeileis + description: |- + Infrastructure for psychometric modeling such as data classes (for + item response data and paired comparisons), basic model fitting functions (for + Bradley-Terry, Rasch, parametric logistic IRT, generalized partial credit, + rating scale, multinomial processing tree models), extractor functions for + different types of parameters (item, person, threshold, discrimination, + guessing, upper asymptotes), unified inference and visualizations, and various + datasets for illustration. Intended as a common lightweight and efficient + toolbox for psychometric modeling and a common building block for fitting + psychometric mixture models in package "psychomix" and trees based on + psychometric models in package "psychotree". + date_publication: '2024-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psychotools + url_git: '' +psychotree: + version: 0.16-1 + title: Recursive Partitioning Based on Psychometric Models + maintainer: Achim Zeileis + description: |- + Recursive partitioning based on psychometric models, + employing the general MOB algorithm (from package partykit) to obtain + Bradley-Terry trees, Rasch trees, rating scale and partial credit trees, and + MPT trees, trees for 1PL, 2PL, 3PL and 4PL models and generalized partial + credit models. + date_publication: '2024-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psychotree + url_git: '' +psychReport: + version: 3.0.2 + title: Reproducible Reports in Psychology + maintainer: Ian G Mackenzie + description: Helper functions for producing reports in Psychology (Reproducible + Research). Provides required formatted strings (APA style) for use in 'Knitr'/'Latex' + integration within *.Rnw files. + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psychReport + url_git: '' +psychrolib: + version: 2.5.2 + title: Psychrometric Properties of Moist and Dry Air + maintainer: Hongyuan Jia + description: |2- + + Implementation of 'PsychroLib' + library which contains + functions to enable the calculation properties of moist and dry air in both + metric (SI) and imperial (IP) systems of units. References: Meyer, D. and + Thevenard, D (2019) . + date_publication: '2021-05-29' + bug_reports: https://github.com/psychrometrics/psychrolib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=psychrolib + url_git: https://github.com/psychrometrics/psychrolib +psychTools: + version: 2.4.3 + title: |- + Tools to Accompany the 'psych' Package for Psychological + Research + maintainer: William Revelle + description: Support functions, data sets, and vignettes for the 'psych' package. + Contains several of the biggest data sets for the 'psych' package as well as four + vignettes. A few helper functions for file manipulation are included as well. + For more information, see the web page. + date_publication: '2024-03-19' + bug_reports: '' + url: https://personality-project.org/r/psych/https://personality-project.org/r/psych-manual.pdf + url_cran: https://CRAN.R-project.org/package=psychTools + url_git: '' +PsychWordVec: + version: '2023.9' + title: Word Embedding Research Framework for Psychological Science + maintainer: Han-Wu-Shuang Bao + description: |2- + + An integrative toolbox of word embedding research that provides: + (1) a collection of 'pre-trained' static word vectors in the '.RData' + compressed format ; + (2) a series of functions to process, analyze, and visualize word vectors; + (3) a range of tests to examine conceptual associations, including + the Word Embedding Association Test + and the Relative Norm Distance , + with permutation test of significance; + (4) a set of training methods to locally train (static) word vectors + from text corpora, including 'Word2Vec' , + 'GloVe' , and 'FastText' ; + (5) a group of functions to download 'pre-trained' language models + (e.g., 'GPT', 'BERT') and extract contextualized (dynamic) word vectors + (based on the R package 'text'). + date_publication: '2023-09-27' + bug_reports: https://github.com/psychbruce/PsychWordVec/issues + url: https://psychbruce.github.io/PsychWordVec/ + url_cran: https://CRAN.R-project.org/package=PsychWordVec + url_git: '' +psycModel: + version: 0.5.0 + title: Integrated Toolkit for Psychological Analysis and Modeling in R + maintainer: Jason Moy + description: |- + A beginner-friendly R package for modeling in psychology or + related field. It allows fitting models, plotting, checking goodness + of fit, and model assumption violations all in one place. It also + produces beautiful and easy-to-read output. + date_publication: '2023-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psycModel + url_git: https://github.com/jasonmoy28/psycModel +PsyControl: + version: 1.0.0.0 + title: CUSUM Person Fit Statistics + maintainer: Maxwell Hong + description: Person fit statistics based on Quality Control measures are provided + for questionnaires and tests given a specified IRT model. Statistics based on + Cumulative Sum (CUSUM) charts are provided. Options are given for banks with polytomous + and dichotomous data. + date_publication: '2017-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PsyControl + url_git: '' +psymetadata: + version: 1.0.1 + title: Open Datasets from Meta-Analyses in Psychology Research + maintainer: Josue E. Rodriguez + description: Data and examples from meta-analyses in psychology research. + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psymetadata + url_git: '' +psyntur: + version: 0.1.0 + title: Helper Tools for Teaching Statistical Data Analysis + maintainer: Mark Andrews + description: |- + Provides functions and data-sets that are helpful + for teaching statistics and data analysis. It was originally designed for use + when teaching students in the Psychology Department at Nottingham Trent University. + date_publication: '2021-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psyntur + url_git: '' +psyphy: + version: '0.3' + title: Functions for Analyzing Psychophysical Data in R + maintainer: Ken Knoblauch + description: An assortment of functions that could be useful in analyzing data from + psychophysical experiments. It includes functions for calculating d' from several + different experimental designs, links for m-alternative forced-choice (mafc) data + to be used with the binomial family in glm (and possibly other contexts) and self-Start + functions for estimating gamma values for CRT screen calibrations. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=psyphy + url_git: '' +psyverse: + version: 0.2.6 + title: Decentralized Unequivocality in Psychological Science + maintainer: Gjalt-Jorn Peters + description: |- + The constructs used to study the human psychology have + many definitions and corresponding instructions for eliciting + and coding qualitative data pertaining to constructs' content and + for measuring the constructs. This plethora of definitions and + instructions necessitates unequivocal reference to specific + definitions and instructions in empirical and secondary research. + This package implements a human- and machine-readable standard for + specifying construct definitions and instructions for measurement + and qualitative research based on 'YAML'. This standard facilitates + systematic unequivocal reference to specific construct definitions + and corresponding instructions in a decentralized manner (i.e. + without requiring central curation; Peters (2020) + ). + date_publication: '2023-03-05' + bug_reports: https://gitlab.com/r-packages/psyverse/-/issues + url: https://psyverse.one + url_cran: https://CRAN.R-project.org/package=psyverse + url_git: '' +ptable: + version: 1.0.0 + title: Generation of Perturbation Tables for the Cell-Key Method + maintainer: Tobias Enderle + description: |- + Tabular data from statistical institutes and agencies are mostly + confidential and must be protected prior to publications. The cell-key + method is a post-tabular Statistical Disclosure Control perturbation + technique that adds random noise to tabular data. The statistical + properties of the perturbations are defined by some noise probability + distributions - also referred to as perturbation tables. + This tool can be used to create the perturbation tables based on a maximum + entropy approach as described for example in Giessing (2016) + . The perturbation tables created can + finally be used to apply a cell-key method to frequency count or magnitude + tables. + date_publication: '2023-03-01' + bug_reports: https://github.com/sdcTools/ptable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ptable + url_git: https://github.com/sdcTools/ptable +PTAk: + version: 2.0.0 + title: Principal Tensor Analysis on k Modes + maintainer: Didier G. Leibovici + description: 'A multiway method to decompose a tensor (array) of any order, as a + generalisation of SVD also supporting non-identity metrics and penalisations. + 2-way SVD with these extensions is also available. The package includes also some + other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP with these extensions.' + date_publication: '2023-03-25' + bug_reports: '' + url: https://www.GeotRYcs.com + url_cran: https://CRAN.R-project.org/package=PTAk + url_git: '' +PTE: + version: '1.7' + title: Personalized Treatment Evaluator + maintainer: Adam Kapelner + description: 'We provide inference for personalized medicine models. Namely, we + answer the questions: (1) how much better does a purported personalized recommendation + engine for treatments do over a business-as-usual approach and (2) is that difference + statistically significant?' + date_publication: '2019-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PTE + url_git: '' +PTERP: + version: '1.0' + title: PTE and RP for Optimally-Transformed Surrogate + maintainer: Layla Parast + description: Evaluates the strength of a surrogate marker by estimating the proportion + of treatment effect explained (PTE) and relative power(RP) for the optimally-transformed + version of the surrogate. Details available in Wang et al (2022) . + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PTERP + url_git: '' +ptetools: + version: 1.0.0 + title: Panel Treatment Effects Tools + maintainer: Brantly Callaway + description: Generic code for estimating treatment effects with panel data. The + idea is to break into separate steps organizing the data, looping over groups + and time periods, computing group-time average treatment effects, and aggregating + group-time average treatment effects. Often, one is able to implement a new identification/estimation + procedure by simply replacing the step on estimating group-time average treatment + effects. See several different examples of this approach in the package documentation. + date_publication: '2025-02-13' + bug_reports: https://github.com/bcallaway11/ptetools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ptetools + url_git: https://github.com/bcallaway11/ptetools +ptinpoly: + version: '2.8' + title: Point-in-Polyhedron Test (2D and 3D) + maintainer: Jose M. Maisog + description: |- + Function pip3d() tests whether a point in 3D space is + within, exactly on, or outside an enclosed surface defined by a triangular mesh. + Function pip2d() tests whether a point in 2D space is within, exactly on, or outside a polygon. + For a reference, see: Liu et al., A new point containment test algorithm based on preprocessing + and determining triangles, Computer-Aided Design 42(12):1143-1150. + date_publication: '2020-06-02' + bug_reports: '' + url: http://ptinpoly.pbworks.com + url_cran: https://CRAN.R-project.org/package=ptinpoly + url_git: '' +pTITAN2: + version: 1.0.2 + title: Permutations of Treatment Labels and TITAN2 Analysis + maintainer: Peter DeWitt + description: |- + Permute treatment labels for taxa and environmental gradients to + generate an empirical distribution of change points. This is an extension + for the 'TITAN2' package . + date_publication: '2022-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pTITAN2 + url_git: https://github.com/USEPA/pTITAN2 +ptm: + version: 1.0.1 + title: Analyses of Protein Post-Translational Modifications + maintainer: Juan Carlos Aledo + description: |- + Contains utilities for the analysis of post-translational modifications (PTMs) in proteins, + with particular emphasis on the sulfoxidation of methionine residues. Features include the ability to download, + filter and analyze data from the sulfoxidation database 'MetOSite'. Utilities to search and characterize S-aromatic motifs in proteins are also provided. + In addition, functions to analyze sequence environments around modifiable residues in proteins can be found. + For instance, 'ptm' allows to search for amino acids either overrepresented or avoided around the modifiable + residues from the proteins of interest. Functions tailored to test statistical hypothesis related to + these differential sequence environments are also implemented. + Further and detailed information regarding the methods in this package can be found in (Aledo (2020) ). + date_publication: '2024-05-21' + bug_reports: '' + url: https://metositeptm.com + url_cran: https://CRAN.R-project.org/package=ptm + url_git: https://bitbucket.org/jcaledo/ptm +ptmixed: + version: 1.1.3 + title: Poisson-Tweedie Generalized Linear Mixed Model + maintainer: Mirko Signorelli + description: |- + Fits the Poisson-Tweedie generalized linear mixed model + described in Signorelli et al. (2021, ). + Likelihood approximation based on adaptive Gauss Hermite quadrature + rule. + date_publication: '2022-08-18' + bug_reports: '' + url: https://mirkosignorelli.github.io/r + url_cran: https://CRAN.R-project.org/package=ptmixed + url_git: '' +ptools: + version: 2.0.0 + title: Tools for Poisson Data + maintainer: Andrew Wheeler + description: Functions used for analyzing count data, mostly crime counts. Includes + checking difference in two Poisson counts (e-test), checking the fit for a Poisson + distribution, small sample tests for counts in bins, Weighted Displacement Difference + test (Wheeler and Ratcliffe, 2018) , to evaluate + crime changes over time in treated/control areas. Additionally includes functions + for aggregating spatial data and spatial feature engineering. + date_publication: '2023-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ptools + url_git: https://github.com/apwheele/ptools +PtProcess: + version: 3.3-16 + title: Time Dependent Point Process Modelling + maintainer: David Harte + description: Fits and analyses time dependent marked point process models with an + emphasis on earthquake modelling. For a more detailed introduction to the package, + see the topic "PtProcess". A list of recent changes can be found in the topic + "Change Log". + date_publication: '2021-05-03' + bug_reports: '' + url: https://www.statsresearch.co.nz/dsh/sslib/ + url_cran: https://CRAN.R-project.org/package=PtProcess + url_git: '' +ptspotter: + version: 1.0.2 + title: Helper Functions for Use with "ProjectTemplate" + maintainer: Rich Leyshon + description: |- + Utility functions produced specifically for (but not limited + to) working with 'ProjectTemplate' data pipelines. This package helps + to quickly create and manage sequentially numbered scripts, quickly + set up logging with 'log4r' and functions to help debug and monitor + procedures. + date_publication: '2023-08-13' + bug_reports: https://github.com/r-leyshon/ptspotter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ptspotter + url_git: https://github.com/r-leyshon/ptspotter +PTSR: + version: 0.1.2 + title: Positive Time Series Regression + maintainer: Taiane Schaedler Prass + description: |- + A collection of functions to simulate, estimate and forecast a wide range of regression based dynamic models for positive time series. + This package implements the results presented in Prass, T.S.; Carlos, J.H.; Taufemback, C.G. and Pumi, G. (2022). "Positive Time Series Regression" . + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PTSR + url_git: '' +pttstability: + version: '1.4' + title: Particle-Takens Stability + maintainer: Adam Clark + description: |- + Includes a collection of functions presented in "Measuring stability in ecological systems without static equilibria" by Clark et al. (2022) in Ecosphere. + These can be used to estimate the parameters of a stochastic state space model (i.e. a model where + a time series is observed with error). The goal of this package is to estimate the variability + around a deterministic process, both in terms of observation error - i.e. variability due to + imperfect observations that does not influence system state - and in terms of process noise - i.e. + stochastic variation in the actual state of the process. Unlike classical methods for estimating + variability, this package does not necessarily assume that the deterministic state is fixed (i.e. + a fixed-point equilibrium), meaning that variability around a dynamic trajectory can be estimated + (e.g. stochastic fluctuations during predator-prey dynamics). + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pttstability + url_git: '' +ptvapi: + version: 2.0.5 + title: Access the 'Public Transport Victoria' Timetable API + maintainer: David Neuzerling + description: |- + Access the 'Public Transport Victoria' Timetable API + , + with results returned as familiar R data structures. Retrieve information on + stops, routes, disruptions, departures, and more. + date_publication: '2024-02-18' + bug_reports: https://github.com/mdneuzerling/ptvapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ptvapi + url_git: https://github.com/mdneuzerling/ptvapi +ptw: + version: 1.9-16 + title: Parametric Time Warping + maintainer: Ron Wehrens + description: |- + Parametric Time Warping aligns patterns, i.e. it aims to + put corresponding features at the same locations. The algorithm + searches for an optimal polynomial describing the warping. It + is possible to align one sample to a reference, several samples + to the same reference, or several samples to several + references. One can choose between calculating individual + warpings, or one global warping for a set of samples and one + reference. Two optimization criteria are implemented: RMS (Root + Mean Square error) and WCC (Weighted Cross Correlation). Both + warping of peak profiles and of peak lists are supported. A + vignette for the latter is contained in the inst/doc directory + of the source package - the vignette source can be found on + the package github site. + date_publication: '2022-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ptw + url_git: https://github.com/rwehrens/ptw +ptwikiwords: + version: 0.0.3 + title: Words Used in Portuguese Wikipedia + maintainer: Daniel Falbel + description: |- + Contains a dataset of words used in 15.000 randomly extracted pages + from the Portuguese Wikipedia (). + date_publication: '2016-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ptwikiwords + url_git: https://github.com/dfalbel/ptwikiwords +PTwins: + version: 0.1.1 + title: Percentile Estimation of Fetal Weight for Twins by Chorionicity + maintainer: Luis Mariano Esteban + description: Package to Percentile estimation of fetal weight for twins by chorionicity + (dichorionic-diamniotic or monochorionic-diamniotic). + date_publication: '2019-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PTwins + url_git: '' +PTXQC: + version: 1.1.2 + title: Quality Report Generation for MaxQuant and mzTab Results + maintainer: Chris Bielow + description: |- + Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the + MaxQuant software suite (from .txt files) or mzTab files (ideally from OpenMS 'QualityControl' tool). + Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. + Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) + . + date_publication: '2025-01-09' + bug_reports: https://github.com/cbielow/PTXQC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PTXQC + url_git: https://github.com/cbielow/PTXQC +ptycho: + version: 1.1-4 + title: Bayesian Variable Selection with Hierarchical Priors + maintainer: Laurel Stell + description: |2- + + Bayesian variable selection for linear regression models using hierarchical + priors. There is a prior that combines information across responses and one + that combines information across covariates, as well as a standard spike and + slab prior for comparison. An MCMC samples from the marginal posterior + distribution for the 0-1 variables indicating if each covariate belongs to the + model for each response. + date_publication: '2015-11-12' + bug_reports: '' + url: web.stanford.edu/~lstell/ptycho/ + url_cran: https://CRAN.R-project.org/package=ptycho + url_git: '' +PubChemR: + version: 2.1.3 + title: Interface to the 'PubChem' Database for Chemical Data Retrieval + maintainer: Selcuk Korkmaz + description: |- + Provides an interface to the 'PubChem' database via the PUG REST and + PUG View services. This package allows users to automatically + access chemical and biological data from 'PubChem', including compounds, substances, assays, and various other data types. + Functions are available to retrieve data in different formats, perform searches, and access detailed annotations. + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PubChemR + url_git: https://github.com/selcukorkmaz/PubChemR +pubh: + version: 2.0.0 + title: A Toolbox for Public Health and Epidemiology + maintainer: Josie Athens + description: |- + A toolbox for making R functions and capabilities more + accessible to students and professionals from Epidemiology and + Public Health related disciplines. Includes a function to report + coefficients and confidence intervals from models using robust + standard errors (when available), functions that expand 'ggplot2' + plots and functions relevant for introductory papers in Epidemiology + or Public Health. Please note that use of the + provided data sets is for educational purposes only. + date_publication: '2024-10-08' + bug_reports: https://github.com/josie-athens/pubh/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pubh + url_git: '' +public.ctn0094data: + version: 1.0.6 + title: De-Identified Data from CTN-0094 + maintainer: Raymond Balise + description: |- + These are harmonized datasets produced as part of the Clinical + Trials Network (CTN) protocol number 0094. This is a US National Institute + of Drug Abuse (NIDA) funded project; to learn more go to + . These are datasets which have + the data harmonized from CTN-0027 (), + CTN-0030 (), and CTN-0051 + (). + date_publication: '2023-10-01' + bug_reports: https://github.com/CTN-0094/public.ctn0094data/issues + url: https://ctn-0094.github.io/public.ctn0094data/ + url_cran: https://CRAN.R-project.org/package=public.ctn0094data + url_git: '' +public.ctn0094extra: + version: 1.0.4 + title: Helper Files for the CTN-0094 Relational Database + maintainer: Gabriel Odom + description: |- + Engineered features and "helper" functions ancillary to the + 'public.ctn0094data' package, extending this package for ease of use (see + ). This + 'public.ctn0094data' package contains harmonized datasets from some of the + National Institute of Drug Abuse's Clinical Trials Network (NIDA's CTN) + projects. Specifically, the CTN-0094 project is to harmonize and de-identify + clinical trials data from the CTN-0027, CTN-0030, and CTN-51 studies for + opioid use disorder. This current version is built from 'public.ctn0094data' + v. 1.0.6. + date_publication: '2023-11-22' + bug_reports: https://github.com/CTN-0094/public.ctn0094extra/issues + url: https://ctn-0094.github.io/public.ctn0094extra/ + url_cran: https://CRAN.R-project.org/package=public.ctn0094extra + url_git: '' +PublicationBias: + version: 2.4.0 + title: Sensitivity Analysis for Publication Bias in Meta-Analyses + maintainer: Peter Solymos + description: |- + Performs sensitivity analysis for publication bias in meta-analyses + (per Mathur & VanderWeele, 2020 []). These analyses + enable statements such as: "For publication bias to shift the observed point + estimate to the null, 'significant' results would need to be at least + 30-fold more likely to be published than negative or 'nonsignificant' + results." Comparable statements can be made regarding shifting to a chosen + non-null value or shifting the confidence interval. Provides a worst-case + meta-analytic point estimate under maximal publication bias obtained simply + by conducting a standard meta-analysis of only the negative and + "nonsignificant" studies. + date_publication: '2023-08-18' + bug_reports: https://github.com/mathurlabstanford/PublicationBias/issues + url: https://mathurlabstanford.github.io/PublicationBias/ + url_cran: https://CRAN.R-project.org/package=PublicationBias + url_git: https://github.com/mathurlabstanford/PublicationBias +PublicWorksFinanceIT: + version: 0.3.1 + title: |- + Soil Defense Investments in Italy: Data Retrieval, Analysis, + Visualization + maintainer: Lorena Ricciotti + description: |- + Facilitates the retrieval and analysis of financial data related to public works in Italy, + focusing on soil defense investments. It extracts data from 'OpenCoesione', 'OpenBDAP', + and the 'ReNDiS' database, eliminating the need for direct access to these platforms. + The package boasts a user-friendly design, featuring real time updates and a set of functions + tailored for data retrieval and visualization. + See the webpages for further information + , + , and + . + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PublicWorksFinanceIT + url_git: '' +publipha: + version: 0.1.2 + title: Bayesian Meta-Analysis with Publications Bias and P-Hacking + maintainer: Jonas Moss + description: |- + Tools for Bayesian estimation of meta-analysis models that account + for publications bias or p-hacking. For publication bias, this package + implements a variant of the p-value based selection model of Hedges (1992) + with discrete selection probabilities. It also + implements the mixture of truncated normals model for p-hacking described + in Moss and De Bin (2019) . + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=publipha + url_git: '' +Publish: + version: 2023.01.17 + title: |- + Format Output of Various Routines in a Suitable Way for Reports + and Publication + maintainer: Thomas A. Gerds + description: |- + A bunch of convenience functions that transform the results of some basic statistical analyses + into table format nearly ready for publication. This includes descriptive tables, tables of + logistic regression and Cox regression results as well as forest plots. + date_publication: '2023-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Publish + url_git: '' +pubmed.mineR: + version: 1.0.21 + title: Text Mining of PubMed Abstracts + maintainer: S. Ramachandran + description: Text mining of PubMed Abstracts (text and XML) from . + date_publication: '2024-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pubmed.mineR + url_git: '' +PubMedMining: + version: 1.0.0 + title: Text-Mining of the 'PubMed' Repository + maintainer: Jeff DIDIER + description: |- + Easy function for text-mining the 'PubMed' repository based on defined sets of terms. + The relationship between fix-terms (related to your research topic) and pub-terms (terms which pivot around your research focus) + is calculated using the pointwise mutual information algorithm ('PMI'). Church, Kenneth Ward and Hanks, Patrick (1990) + A text file is generated with the 'PMI'-scores for each fix-term. Then for each collocation pairs (a fix-term + a pub-term), + a text file is generated with related article titles and publishing years. Additional Author section will follow in the next version updates. + date_publication: '2020-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PubMedMining + url_git: '' +pubmedR: + version: 0.0.3 + title: |- + Gathering Metadata About Publications, Grants, Clinical Trials + from 'PubMed' Database + maintainer: Massimo Aria + description: A set of tools to extract bibliographic content from 'PubMed' database + using 'NCBI' REST API . + date_publication: '2020-07-09' + bug_reports: https://github.com/massimoaria/pubmedR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pubmedR + url_git: https://github.com/massimoaria/pubmedR +pubmedtk: + version: 1.0.4 + title: '''Pubmed'' Toolkit' + maintainer: Benjamin Gregory Carlisle + description: |- + Provides various functions for retrieving and + interpreting information from 'Pubmed' via the API, + . + date_publication: '2024-03-05' + bug_reports: https://github.com/bgcarlisle/pubmedtk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pubmedtk + url_git: https://github.com/bgcarlisle/pubmedtk +PubMedWordcloud: + version: 0.3.6 + title: '''Pubmed'' Word Clouds' + maintainer: Felix Yanhui Fan + description: Create a word cloud using the abstract of publications from 'Pubmed'. + date_publication: '2019-03-01' + bug_reports: '' + url: http://felixfan.github.io/PubMedWordcloud/ + url_cran: https://CRAN.R-project.org/package=PubMedWordcloud + url_git: '' +pubtatordb: + version: 0.1.4 + title: Create and Query a Local 'PubTator' Database + maintainer: Zachary Colburn + description: '''PubTator'' + is a National Center for Biotechnology Information (NCBI) tool that enhances the + annotation of articles on PubMed . It makes + it possible to rapidly identify potential relationships between genes or proteins + using text mining techniques. In contrast, manually searching for and reading + the annotated articles would be very time consuming. ''PubTator'' offers both + an online interface and a RESTful API, however, neither of these approaches are + well suited for frequent, high-throughput analyses. The package ''pubtatordb'' + provides a set of functions that make it easy for the average R user to download + ''PubTator'' annotations, create, and then query a local version of the database.' + date_publication: '2019-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pubtatordb + url_git: '' +pudu: + version: 0.1.0 + title: C++ Tools for Cleaning Strings + maintainer: Mauricio Vargas Sepulveda + description: |- + Provides function declarations and inline function definitions that + facilitate cleaning strings in C++ code before passing them to R. + date_publication: '2025-01-14' + bug_reports: https://github.com/pachadotdev/pudu/issues + url: https://pacha.dev/pudu/ + url_cran: https://CRAN.R-project.org/package=pudu + url_git: https://github.com/pachadotdev/pudu +PUGMM: + version: 0.1.0 + title: Parsimonious Ultrametric Gaussian Mixture Models + maintainer: Giorgia Zaccaria + description: Finite Gaussian mixture models with parsimonious extended ultrametric + covariance structures estimated via a grouped coordinate ascent algorithm, which + is equivalent to the Expectation-Maximization algorithm. The thirteen ultrametric + covariance structures implemented allow for the inspection of different hierarchical + relationships among variables. The estimation of an ultrametric correlation matrix + is included as a function. The methodologies are described in Cavicchia, Vichi, + Zaccaria (2024) , Cavicchia, Vichi, Zaccaria (2022) + and Cavicchia, Vichi, Zaccaria (2020) . + date_publication: '2024-05-10' + bug_reports: https://github.com/giorgiazaccaria/PUGMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PUGMM + url_git: https://github.com/giorgiazaccaria/PUGMM +PUlasso: + version: 3.2.5 + title: High-Dimensional Variable Selection with Presence-Only Data + maintainer: Hyebin Song + description: Efficient algorithm for solving PU (Positive and Unlabeled) problem + in low or high dimensional setting with lasso or group lasso penalty. The algorithm + uses Maximization-Minorization and (block) coordinate descent. Sparse calculation + and parallel computing are supported for the computational speed-up. See Hyebin + Song, Garvesh Raskutti (2018) . + date_publication: '2023-12-18' + bug_reports: https://github.com/hsong1/PUlasso/issues + url: https://arxiv.org/abs/1711.08129 + url_cran: https://CRAN.R-project.org/package=PUlasso + url_git: '' +pullword: + version: '0.3' + title: R Interface to Pullword Service + maintainer: Tong He + description: |- + R Interface to Pullword Service for natural language processing + in Chinese. It enables users to extract valuable words from text by deep learning models. + For more details please visit the official site (in Chinese) . + date_publication: '2021-07-13' + bug_reports: https://github.com/hetong007/pullword/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pullword + url_git: '' +puls: + version: 0.1.2 + title: Partitioning Using Local Subregions + maintainer: Tan Tran + description: |- + A method of clustering functional data using + subregion information of the curves. It is intended to supplement the + 'fda' and 'fda.usc' packages in functional data object clustering. It + also facilitates the printing and plotting of the results in a tree + format and limits the partitioning candidates into a specific set of + subregions. + date_publication: '2021-02-16' + bug_reports: https://github.com/vinhtantran/puls/issues + url: https://vinhtantran.github.io/puls/ + url_cran: https://CRAN.R-project.org/package=puls + url_git: https://github.com/vinhtantran/puls +pulsar: + version: 0.3.11 + title: |- + Parallel Utilities for Lambda Selection along a Regularization + Path + maintainer: Zachary Kurtz + description: Model selection for penalized graphical models using the Stability + Approach to Regularization Selection ('StARS'), with options for speed-ups including + Bounded StARS (B-StARS), batch computing, and other stability metrics (e.g., graphlet + stability G-StARS). Christian L. Müller, Richard Bonneau, Zachary Kurtz (2016) + . + date_publication: '2023-09-24' + bug_reports: https://github.com/zdk123/pulsar/issues + url: https://arxiv.org/abs/1605.07072 + url_cran: https://CRAN.R-project.org/package=pulsar + url_git: https://github.com/zdk123/pulsar +pumilioR: + version: 1.3.1 + title: Pumilio in R + maintainer: Luis J. Villanueva-Rivera + description: R package to query and get data out of a Pumilio sound archive system + (http://ljvillanueva.github.io/pumilio/). + date_publication: '2016-11-23' + bug_reports: https://github.com/ljvillanueva/pumilioR/issues + url: http://ljvillanueva.github.io/pumilioR/ + url_cran: https://CRAN.R-project.org/package=pumilioR + url_git: '' +PUMP: + version: 1.0.3 + title: Power Under Multiplicity Project + maintainer: Luke Miratrix + description: Estimates power, minimum detectable effect size (MDES) and sample size + requirements. The context is multilevel randomized experiments with multiple outcomes. + The estimation takes into account the use of multiple testing procedures. Development + of this package was supported by a grant from the Institute of Education Sciences + (R305D170030). For a full package description, including a detailed technical + appendix, see . + date_publication: '2024-02-29' + bug_reports: https://github.com/MDRCNY/PUMP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PUMP + url_git: https://github.com/MDRCNY/PUMP +puniform: + version: 0.2.7 + title: Meta-Analysis Methods Correcting for Publication Bias + maintainer: Robbie C.M. van Aert + description: |- + Provides meta-analysis methods that correct for + publication bias and outcome reporting bias. Four methods and a visual tool + are currently included in the package. The p-uniform method as described in + van Assen, van Aert, and Wicherts (2015) + can be used for estimating the average effect size, testing the null hypothesis + of no effect, and testing for publication bias using only the statistically + significant effect sizes of primary studies. The second method in the package + is the p-uniform* method as described in van Aert and van Assen (2023) + . This method is an extension of the p-uniform + method that allows for estimation of the average effect size and the + between-study variance in a meta-analysis, and uses both the statistically + significant and nonsignificant effect sizes. The third method in the package + is the hybrid method as described in van Aert and van Assen (2018) + . The hybrid method is a meta-analysis method + for combining a conventional study and replication/preregistered study while + taking into account statistical significance of the conventional study. This + method was extended in van Aert (2023) such that it allows for the inclusion + of multiple conventional and replication/preregistered studies. The p-uniform + and hybrid method are based on the statistical theory that the distribution + of p-values is uniform conditional on the population effect size. The fourth + method in the package is the Snapshot Bayesian Hybrid Meta-Analysis Method as + described in van Aert and van Assen (2018) . + This method computes posterior probabilities for four true effect sizes (no, + small, medium, and large) based on an original study and replication while + taking into account publication bias in the original study. The method can + also be used for computing the required sample size of the replication akin + to power analysis in null-hypothesis significance testing. The meta-plot is + a visual tool for meta-analysis that provides information on the primary + studies in the meta-analysis, the results of the meta-analysis, and + characteristics of the research on the effect under study (van Assen et al., 2023). + Helper functions to apply the Correcting for Outcome Reporting Bias (CORB) + method to correct for outcome reporting bias in a meta-analysis (van Aert & + Wicherts, 2023). + date_publication: '2023-09-19' + bug_reports: https://github.com/RobbievanAert/puniform/issues + url: '' + url_cran: https://CRAN.R-project.org/package=puniform + url_git: https://github.com/RobbievanAert/puniform +PUPAK: + version: 0.1.1 + title: |- + Parameter Estimation, and Plot Visualization of Adsorption + Kinetic Models + maintainer: Chester Deocaris + description: Contains model fitting functions for linear and non-linear adsorption + kinetic and diffusion models. Adsorption kinetics is used for characterizing the + rate of solute adsorption and the time necessary for the adsorption process. Adsorption + kinetics offers vital information on adsorption rate, adsorbent performance in + response time, and mass transfer processes. In addition, diffusion models are + included in the package as solute diffusion affects the adsorption kinetic experiments. + This package consists of 20 adsorption and diffusion models, including Pseudo + First Order (PFO), Pseudo Second Order (PSO), Elovich, and Weber-Morris model + (commonly called the intraparticle model) stated by Plazinski et al. (2009) . + This package also contains a summary function where the statistical errors of + each model are ranked for a more straightforward determination of the best fit + model. + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PUPAK + url_git: '' +PupillometryR: + version: 0.0.5 + title: A Unified Pipeline for Pupillometry Data + maintainer: Samuel Forbes + description: |- + Provides a unified pipeline to clean, prepare, plot, + and run basic analyses on pupillometry experiments. + date_publication: '2023-09-15' + bug_reports: https://github.com/samhforbes/PupillometryR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PupillometryR + url_git: '' +PupilPre: + version: 0.6.2 + title: Preprocessing Pupil Size Data + maintainer: Aki-Juhani Kyröläinen + description: |- + Pupillometric data collected using SR Research Eyelink eye trackers + requires significant preprocessing. This package contains functions for + preparing pupil dilation data for visualization and statistical analysis. + Specifically, it provides a pipeline of functions which aid in data validation, + the removal of blinks/artifacts, downsampling, and baselining, among others. + Additionally, plotting functions for creating grand average and conditional + average plots are provided. See the vignette for samples of the functionality. + The package is designed for handling data collected with SR Research + Eyelink eye trackers using Sample Reports created in SR Research Data + Viewer. + date_publication: '2020-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PupilPre + url_git: '' +PUPMCR: + version: 0.2.0 + title: |- + Image-Based Identification of Color Based on Rayner (1970) + Terminology and Known Fungal Pigments + maintainer: Chester Deocaris + description: Image-based color matching using the "Mycological Colour Chart" by + Rayner (1970, ISBN:9780851980263) and its associated fungal pigments. This package + will assist mycologists in identifying color during morphological analysis. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PUPMCR + url_git: '' +PUPMSI: + version: 0.1.0 + title: Moisture Sorption Isotherm Modeling Program + maintainer: Chester Deocaris + description: Contains sixteen moisture sorption isotherm models, which evaluate + the fitness of adsorption and desorption curves for further understanding of the + relationship between moisture content and water activity. Fitness evaluation is + conducted through parameter estimation and error analysis. Moreover, graphical + representation, hysteresis area estimation, and isotherm classification through + the equation of Blahovec & Yanniotis (2009) + which is based on the classification system introduced by Brunauer et. al. (1940) + are also included for the visualization of models and + hysteresis. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PUPMSI + url_git: '' +puremoe: + version: 1.0.2 + title: Pubmed Unified REtrieval for Multi-Output Exploration + maintainer: Jason Timm + description: Access a variety of 'PubMed' data through a single, user-friendly interface, + including abstracts , bibliometrics from 'iCite' + , pubtations from 'PubTator3' , + and full-text records from 'PMC' . + date_publication: '2024-10-15' + bug_reports: https://github.com/jaytimm/puremoe/issues + url: https://jaytimm.github.io/puremoe/ + url_cran: https://CRAN.R-project.org/package=puremoe + url_git: https://github.com/jaytimm/puremoe +pureseqtmr: + version: '1.4' + title: Predict Transmembrane Protein Topology + maintainer: Richèl J.C. Bilderbeek + description: |- + Proteins reside in either the cell plasma or in the + cell membrane. A membrane protein goes through the + membrane at least once. Given the amino acid sequence of a + membrane protein, the tool + 'PureseqTM' (, + as described in "Efficient And Accurate Prediction Of Transmembrane + Topology From Amino acid sequence only.", Wang, Qing, et al (2019), + ), + can predict the topology of a membrane protein. This package + allows one to use 'PureseqTM' from R. + date_publication: '2023-04-06' + bug_reports: https://github.com/richelbilderbeek/pureseqtmr/ + url: '' + url_cran: https://CRAN.R-project.org/package=pureseqtmr + url_git: https://github.com/richelbilderbeek/pureseqtmr/ +purge: + version: 0.2.1 + title: Purge Training Data from Models + maintainer: Marc Maier + description: |- + Enables the removal of training data from fitted R models while + retaining predict functionality. The purged models are more portable as their + memory footprints do not scale with the training sample size. + date_publication: '2017-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=purge + url_git: '' +purgeR: + version: 1.8.2 + title: Inbreeding-Purging Estimation in Pedigreed Populations + maintainer: Eugenio López-Cortegano + description: |- + Inbreeding-purging analysis of pedigreed populations, including the computation of the inbreeding coefficient, partial, ancestral and purged inbreeding coefficients, and measures of the opportunity of purging related to the individual reduction of inbreeding load. + In addition, functions to calculate the effective population size and other parameters relevant to population genetics are included. + See López-Cortegano E. (2021) . + date_publication: '2023-11-28' + bug_reports: https://gitlab.com/elcortegano/purgeR/-/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=purgeR + url_git: https://gitlab.com/elcortegano/purgeR/ +purging: + version: 1.0.0 + title: |- + Simple Method for Purging Mediation Effects among Independent + Variables + maintainer: Philip D. Waggoner + description: Simple method of purging independent variables of mediating effects. + First, regress the direct variable on the indirect variable. Then, used the stored + residuals as the new purged (direct) variable in the updated specification. This + purging process allows for use of a new direct variable uncorrelated with the + indirect variable. Please cite the method and/or package using Waggoner, Philip + D. (2018) . + date_publication: '2018-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=purging + url_git: '' +PurpleAir: + version: 1.0.1 + title: Query the 'PurpleAir' Application Programming Interface + maintainer: Cole Brokamp + description: Send requests to the 'PurpleAir' Application Programming Interface + (API; ). Check a 'PurpleAir' API + key and get information about the related organization. Download real-time data + from a single 'PurpleAir' sensor or many sensors by sensor identifier, geographical + bounding box, or time since modified. Download historical data from a single sensor. + date_publication: '2024-10-08' + bug_reports: https://github.com/cole-brokamp/PurpleAir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PurpleAir + url_git: https://github.com/cole-brokamp/PurpleAir +PurpleAirAPI: + version: 0.1.0 + title: Historical Data Retrieval from 'PurpleAir' Sensors via API + maintainer: Heba Abdelrazzak + description: |- + Provides tools for retrieving and analyzing air quality data + from 'PurpleAir' sensors through their API. Functions enable downloading + historical measurements, accessing sensor metadata, and managing API + request limitations through chunked data retrieval. For more information + about the 'PurpleAir' API, see . + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PurpleAirAPI + url_git: https://github.com/heba-razzak/PurpleAirAPI +purrr: + version: 1.0.4 + title: Functional Programming Tools + maintainer: Hadley Wickham + description: |- + A complete and consistent functional programming toolkit for + R. + date_publication: '2025-02-05' + bug_reports: https://github.com/tidyverse/purrr/issues + url: https://purrr.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=purrr + url_git: https://github.com/tidyverse/purrr +purrrlyr: + version: 0.0.8 + title: Tools at the Intersection of 'purrr' and 'dplyr' + maintainer: Lionel Henry + description: |- + Some functions at the intersection of 'dplyr' and + 'purrr' that formerly lived in 'purrr'. + date_publication: '2022-03-29' + bug_reports: https://github.com/hadley/purrrlyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=purrrlyr + url_git: https://github.com/hadley/purrrlyr +Pursuit: + version: 1.0.5 + title: Projection Pursuit + maintainer: Paulo Cesar Ossani + description: Projection pursuit (PP) with 17 methods and grand tour with 3 methods. + Being that projection pursuit searches for low-dimensional linear projections + in high-dimensional data structures, while grand tour is a technique used to explore + multivariate statistical data through animation. + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Pursuit + url_git: '' +pushbar: + version: 0.1.0 + title: Create Sliders for 'Shiny' + maintainer: John Coene + description: Create sliders from left, right, top and bottom which may include any + html or 'Shiny' input or output. + date_publication: '2019-03-15' + bug_reports: https://github.com/JohnCoene/pushbar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pushbar + url_git: https://github.com/JohnCoene/pushbar +pushoverr: + version: 1.1.0 + title: Send Push Notifications using 'Pushover' + maintainer: Brian Connelly + description: |- + Send push notifications to mobile devices or the desktop + using 'Pushover' . These notifications can + display things such as results, job status, plots, or any other text + or numeric data. + date_publication: '2021-11-16' + bug_reports: https://github.com/briandconnelly/pushoverr/issues + url: https://briandconnelly.github.io/pushoverr/ + url_cran: https://CRAN.R-project.org/package=pushoverr + url_git: https://github.com/briandconnelly/pushoverr +puzzle: + version: 0.0.1 + title: Assembling Data Sets for Non-Linear Mixed Effects Modeling + maintainer: Mario Gonzalez Sales + description: To Simplify the time consuming and error prone task of assembling complex + data sets for non-linear mixed effects modeling. Users are able to select from + different absorption processes such as zero and first order, or a combination + of both. Furthermore, data sets containing data from several entities, responses, + and covariates can be simultaneously assembled. + date_publication: '2019-11-28' + bug_reports: https://github.com/syneoshealth/puzzle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=puzzle + url_git: https://github.com/syneoshealth/puzzle +PVAClone: + version: 0.1-7 + title: Population Viability Analysis with Data Cloning + maintainer: Peter Solymos + description: |- + Likelihood based population viability analysis in the + presence of observation error and missing data. + The package can be used to fit, compare, predict, + and forecast various growth model types using data cloning. + date_publication: '2024-01-23' + bug_reports: https://github.com/psolymos/PVAClone/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PVAClone + url_git: https://github.com/psolymos/PVAClone +pvaluefunctions: + version: 1.6.2 + title: |- + Creates and Plots P-Value Functions, S-Value Functions, + Confidence Distributions and Confidence Densities + maintainer: Denis Infanger + description: Contains functions to compute and plot confidence distributions, confidence + densities, p-value functions and s-value (surprisal) functions for several commonly + used estimates. Instead of just calculating one p-value and one confidence interval, + p-value functions display p-values and confidence intervals for many levels thereby + allowing to gauge the compatibility of several parameter values with the data. + These methods are discussed by Infanger D, Schmidt-Trucksäss A. (2019) ; + Poole C. (1987) ; Schweder T, Hjort NL. (2002) ; + Bender R, Berg G, Zeeb H. (2005) ; Singh K, Xie M, + Strawderman WE. (2007) ; Rothman KJ, Greenland + S, Lash TL. (2008, ISBN:9781451190052); Amrhein V, Trafimow D, Greenland S. (2019) + ; Greenland S. (2019) + and Rafi Z, Greenland S. (2020) . + date_publication: '2021-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pvaluefunctions + url_git: https://github.com/DInfanger/pvaluefunctions +pvar: + version: 2.2.7 + title: Calculation and Application of p-Variation + maintainer: Vygantas Butkus + description: |- + The calculation of p-variation of the finite sample data. + This package is a realisation of the procedure described in Butkus, V. & Norvaisa, R. Lith Math J (2018). + The formal definitions and reference into literature are given in vignette. + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pvar + url_git: '' +pvclass: + version: '1.4' + title: P-Values for Classification + maintainer: Niki Zumbrunnen + description: |- + Computes nonparametric p-values for the potential class + memberships of new observations as well as cross-validated + p-values for the training data. The p-values are based on + permutation tests applied to an estimated Bayesian likelihood + ratio, using a plug-in statistic for the Gaussian model, 'k + nearest neighbors', 'weighted nearest neighbors' or + 'penalized logistic regression'. + Additionally, it provides graphical displays and quantitative + analyses of the p-values. + date_publication: '2017-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pvclass + url_git: '' +pvclust: + version: 2.2-0 + title: |- + Hierarchical Clustering with P-Values via Multiscale Bootstrap + Resampling + maintainer: Ryota Suzuki + description: |- + An implementation of multiscale bootstrap resampling for + assessing the uncertainty in hierarchical cluster analysis. + It provides SI (selective inference) p-value, AU (approximately unbiased) + p-value and BP (bootstrap probability) value for each cluster in a dendrogram. + date_publication: '2019-11-19' + bug_reports: '' + url: http://stat.sys.i.kyoto-u.ac.jp/prog/pvclust/ + url_cran: https://CRAN.R-project.org/package=pvclust + url_git: '' +pvcurveanalysis: + version: 1.0.0 + title: Analysis of Pressure Volume Curves + maintainer: Anna Raesch + description: Enables the manufacturing, analysis and display of pressure volume + curves. From the progression of the curves, turgor loss point, osmotic potential + and apoplastic fraction can be derived. Methods adapted from Bartlett, Scoffoni + and Sack (2012) . + date_publication: '2021-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pvcurveanalysis + url_git: '' +pvda: + version: 0.0.4 + title: Disproportionality Functions for Pharmacovigilance + maintainer: Michele Fusaroli + description: Tools for performing disproportionality analysis using the information + component, proportional reporting rate and the reporting odds ratio. The anticipated + use is passing data to the da() function, which executes the disproportionality + analysis. See Norén et al (2011) and Montastruc + et al (2011) for further details. + date_publication: '2025-01-17' + bug_reports: https://github.com/OskarGauffin/pvda/issues + url: https://oskargauffin.github.io/pvda/ + url_cran: https://CRAN.R-project.org/package=pvda + url_git: '' +pvldcurve: + version: 1.2.6 + title: |- + Simplifies the Analysis of Pressure Volume and Leaf Drying + Curves + maintainer: Anna Raesch + description: Simplifies the manufacturing, analysis and display of pressure volume + and leaf drying curves. From the progression of the curves turgor loss point, + osmotic potential, apoplastic fraction as well as minimum conductance and stomatal + closure can be derived. Methods adapted from Bartlett, Scoffoni, Sack (2012) + and Sack, Scoffoni, PrometheusWikiContributors (2011) . + date_publication: '2020-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pvldcurve + url_git: '' +pvLRT: + version: 0.5.1 + title: Likelihood Ratio Test-Based Approaches to Pharmacovigilance + maintainer: Saptarshi Chakraborty + description: A suite of likelihood ratio test based methods to use in pharmacovigilance. + Contains various testing and post-processing functions. + date_publication: '2023-03-06' + bug_reports: https://github.com/c7rishi/pvLRT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pvLRT + url_git: '' +PVR: + version: '0.3' + title: |- + Phylogenetic Eigenvectors Regression and Phylogentic + Signal-Representation Curve + maintainer: Thiago Santos + description: Estimates (and controls for) phylogenetic signal through phylogenetic + eigenvectors regression (PVR) and phylogenetic signal-representation (PSR) curve, + along with some plot utilities. + date_publication: '2018-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PVR + url_git: '' +PvSTATEM: + version: 0.2.2 + title: |- + Reading, Quality Control and Preprocessing of MBA (Multiplex + Bead Assay) Data + maintainer: Tymoteusz Kwiecinski + description: Speeds up the process of loading raw data from MBA (Multiplex Bead + Assay) examinations, performs quality control checks, and automatically normalises + the data, preparing it for more advanced, downstream tasks. The main objective + of the package is to create a simple environment for a user, who does not necessarily + have experience with R language. The package is developed within the project of + the same name - 'PvSTATEM', which is an international project aiming for malaria + elimination. + date_publication: '2025-02-27' + bug_reports: https://github.com/mini-pw/PvSTATEM/issues + url: https://mini-pw.github.io/PvSTATEM/ + url_cran: https://CRAN.R-project.org/package=PvSTATEM + url_git: https://github.com/mini-pw/PvSTATEM +PWEALL: + version: 1.3.0.1 + title: |- + Design and Monitoring of Survival Trials Accounting for Complex + Situations + maintainer: Xiaodong Luo + description: |- + Calculates various functions needed for design and monitoring survival trials + accounting for complex situations such as delayed treatment effect, treatment crossover, non-uniform accrual, + and different censoring distributions between groups. The event time distribution is assumed to be + piecewise exponential (PWE) distribution and the entry time is assumed to be piecewise uniform distribution. + As compared with Version 1.2.1, two more types of hybrid crossover are added. + A bug is corrected in the function "pwecx" that calculates the crossover-adjusted survival, distribution, + density, hazard and cumulative hazard functions. + Also, to generate the crossover-adjusted event time random variable, a more efficient + algorithm is used and the output includes crossover indicators. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PWEALL + url_git: '' +PWEV: + version: 0.1.0 + title: PSO Based Weighted Ensemble Algorithm for Volatility Modelling + maintainer: Dr. Ranjit Kumar Paul + description: Price volatility refers to the degree of variation in series over a + certain period of time. This volatility is especially noticeable in agricultural + commodities, adding uncertainty for farmers, traders, and others in the agricultural + supply chain. Commonly and popularly used four volatility models viz, GARCH, Glosten + Jagannatan Runkle-GARCH (GJR-GARCH) model, exponentially weighted moving average + (EWMA) model and Multiplicative Error Model (MEM) are selected and implemented. + PWAVE, weighted ensemble model based on particle swarm optimization (PSO) is proposed + to combine the forecast obtained from all the candidate models. This package has + been developed using algorithm of Paul et al. + and Yeasin and Paul (2024) . + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PWEV + url_git: '' +PWEXP: + version: 0.5.0 + title: Piecewise Exponential Distribution Prediction Model + maintainer: Tianchen Xu + description: Build piecewise exponential survival model for study design (planning) + and event/timeline prediction. + date_publication: '2024-03-12' + bug_reports: https://github.com/zjph602xtc/PWEXP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=PWEXP + url_git: https://github.com/zjph602xtc/PWEXP +PWIR: + version: 0.0.3 + title: |- + Provides a Function to Calculate Prize Winner Indices Based on + Bibliometric Data + maintainer: Robin Haunschild + description: A function 'PWI()' that calculates prize winner indices based on bibliometric + data is provided. The default is the 'Derek de Solla Price Memorial Medal'. Users + can provide recipients of other prizes. + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PWIR + url_git: '' +pwlmm: + version: 1.1.1 + title: PWIGLS for Two-Level Multivariate and Multilevel Linear Models + maintainer: Alinne Veiga + description: Estimates two-level multilevel linear model and two-level multivariate + linear multilevel model with weights following Probability Weighted Iterative + Generalised Least Squares approach. For details see Veiga et al.(2014) . + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwlmm + url_git: '' +pwr: + version: 1.3-0 + title: Basic Functions for Power Analysis + maintainer: Helios De Rosario + description: Power analysis functions along the lines of Cohen (1988). + date_publication: '2020-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwr + url_git: https://github.com/heliosdrm/pwr +pwr2: + version: '1.0' + title: |- + Power and Sample Size Analysis for One-way and Two-way ANOVA + Models + maintainer: Pengcheng Lu + description: User friendly functions for power and sample size analysis at one-way + and two-way ANOVA settings take either effect size or delta and sigma as arguments. + They are designed for both one-way and two-way ANOVA settings. In addition, a + function for plotting power curves is available for power comparison, which can + be easily visualized by statisticians and clinical researchers. + date_publication: '2017-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwr2 + url_git: '' +pwr2ppl: + version: 0.5.0 + title: Power Analyses for Common Designs (Power to the People) + maintainer: Chris Aberson + description: |- + Statistical power analysis for designs including t-tests, correlations, + multiple regression, ANOVA, mediation, and logistic regression. Functions accompany + Aberson (2019) . + date_publication: '2022-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwr2ppl + url_git: '' +pwr4exp: + version: 0.1.0 + title: Power Analysis for Research Experiments + maintainer: Kai Wang + description: |- + Provides tools for calculating statistical power and determining sample size + for a variety of experimental designs used in agricultural and biological research, + including completely randomized, block, and split-plot designs. Supports customized + designs and allows specification of main effects, interactions, and contrasts for + accurate power analysis. + date_publication: '2024-10-11' + bug_reports: https://github.com/an-ethz/pwr4exp/issues + url: https://an-ethz.github.io/pwr4exp/ + url_cran: https://CRAN.R-project.org/package=pwr4exp + url_git: https://github.com/an-ethz/pwr4exp +pwrAB: + version: 0.1.0 + title: Power Analysis for AB Testing + maintainer: William Cha + description: |- + Power analysis for AB testing. The calculations are based on the Welch's unequal variances t-test, + which is generally preferred over the Student's t-test when sample sizes and variances of the two groups are + unequal, which is frequently the case in AB testing. In such situations, the Student's t-test will give + biased results due to using the pooled standard deviation, unlike the Welch's t-test. + date_publication: '2017-06-06' + bug_reports: http://github.com/williamcha/pwrAB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pwrAB + url_git: http://github.com/williamcha/pwrAB +pwrFDR: + version: 3.2.4 + title: FDR Power + maintainer: Grant Izmirlian + description: |- + Computing Average and TPX Power under various BHFDR type sequential + procedures. All of these procedures involve control of some summary of the + distribution of the FDP, e.g. the proportion of discoveries which are false + in a given experiment. The most widely known of these, the BH-FDR procedure, + controls the FDR which is the mean of the FDP. A lesser known procedure, due + to Lehmann and Romano, controls the FDX, or probability that the FDP exceeds + a user provided threshold. This is less conservative than FWE control + procedures but much more conservative than the BH-FDR proceudre. This + package and the references supporting it introduce a new procedure for + controlling the FDX which we call the BH-FDX procedure. This procedure + iteratively identifies, given alpha and lower threshold delta, an alpha* + less than alpha at which BH-FDR guarantees FDX control. This uses + asymptotic approximation and is only slightly more conservative than the + BH-FDR procedure. Likewise, we can think of the power in multiple testing + experiments in terms of a summary of the distribution of the True Positive + Proportion (TPP), the portion of tests truly non-null distributed that are + called significant. The package will compute power, sample size or any other + missing parameter required for power defined as (i) the mean of the TPP + (average power) or (ii) the probability that the TPP exceeds a given value, + lambda, (TPX power) via asymptotic approximation. All supplied theoretical + results are also obtainable via simulation. The suggested approach is to + narrow in on a design via the theoretical approaches and then make final + adjustments/verify the results by simulation. The theoretical results are + described in Izmirlian, G (2020) Statistics and Probability letters, + "", and an applied paper describing the + methodology with a simulation study is in preparation. + See citation("pwrFDR"). + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwrFDR + url_git: '' +PwrGSD: + version: 2.3.8 + title: Power in a Group Sequential Design + maintainer: Grant Izmirlian + description: |- + Tools for the evaluation of interim analysis plans for sequentially + monitored trials on a survival endpoint; tools to construct efficacy and + futility boundaries, for deriving power of a sequential design at a specified + alternative, template for evaluating the performance of candidate plans at a + set of time varying alternatives. See Izmirlian, G. (2014) . + date_publication: '2024-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PwrGSD + url_git: '' +pwrRasch: + version: 0.1-2 + title: Statistical Power Simulation for Testing the Rasch Model + maintainer: Takuya Yanagida + description: Statistical power simulation for testing the Rasch Model based on a + three-way analysis of variance design with mixed classification. + date_publication: '2015-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwrRasch + url_git: '' +pwrss: + version: 0.3.1 + title: Statistical Power and Sample Size Calculation Tools + maintainer: Metin Bulus + description: 'Statistical power and minimum required sample size calculations for + (1) testing a proportion (one-sample) against a constant, (2) testing a mean + (one-sample) against a constant, (3) testing difference between two proportions + (independent samples), (4) testing difference between two means or groups (parametric + and non-parametric tests for independent and paired samples), (5) testing a correlation + (one-sample) against a constant, (6) testing difference between two correlations + (independent samples), (7) testing a single coefficient in multiple linear regression, + logistic regression, and Poisson regression (with standardized or unstandardized + coefficients, with no covariates or covariate adjusted), (8) testing an indirect + effect (with standardized or unstandardized coefficients, with no covariates or + covariate adjusted) in the mediation analysis (Sobel, Joint, and Monte Carlo tests), + (9) testing an R-squared against zero in linear regression, (10) testing an R-squared + difference against zero in hierarchical regression, (11) testing an eta-squared + or f-squared (for main and interaction effects) against zero in analysis of variance + (could be one-way, two-way, and three-way), (12) testing an eta-squared or f-squared + (for main and interaction effects) against zero in analysis of covariance (could + be one-way, two-way, and three-way), (13) testing an eta-squared or f-squared + (for between, within, and interaction effects) against zero in one-way repeated + measures analysis of variance (with non-sphericity correction and repeated measures + correlation), and (14) testing goodness-of-fit or independence for contingency + tables. Alternative hypothesis can be formulated as "not equal", "less", "greater", + "non-inferior", "superior", or "equivalent" in (1), (2), (3), and (4); as "not + equal", "less", or "greater" in (5), (6), (7) and (8); but always as "greater" + in (9), (10), (11), (12), (13), and (14). Reference: Bulus and Polat (2023) .' + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwrss + url_git: '' +pwt: + version: 7.1-1 + title: Penn World Table (Versions 5.6, 6.x, 7.x) + maintainer: Achim Zeileis + description: The Penn World Table provides purchasing power parity andnational + income accounts converted to international prices for189 countries for + some or all of the years 1950-2010. + date_publication: '2013-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwt + url_git: '' +pwt10: + version: 10.01-0 + title: Penn World Table (Version 10.x) + maintainer: Achim Zeileis + description: |- + The Penn World Table 10.x () provides information + on relative levels of income, output, input, and productivity + for 183 countries between 1950 and 2019. + date_publication: '2023-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwt10 + url_git: '' +pwt8: + version: 8.1-1 + title: Penn World Table (Version 8.x) + maintainer: Achim Zeileis + description: |- + The Penn World Table 8.x provides information on relative levels of + income, output, inputs, and productivity for 167 countries + between 1950 and 2011. + date_publication: '2017-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwt8 + url_git: '' +pwt9: + version: 9.1-0 + title: Penn World Table (Version 9.x) + maintainer: Achim Zeileis + description: |- + The Penn World Table 9.x () provides information + on relative levels of income, output, inputs, and productivity + for 182 countries between 1950 and 2017. + date_publication: '2019-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pwt9 + url_git: '' +pxmake: + version: 0.15.1 + title: Make PX-Files in R + maintainer: Johan Ejstrud + description: |- + Create PX-files from scratch or read and modify existing ones. + Includes a function for every PX keyword, making metadata manipulation + simple and human-readable. + date_publication: '2025-02-17' + bug_reports: https://github.com/StatisticsGreenland/pxmake/issues + url: https://statisticsgreenland.github.io/pxmake/ + url_cran: https://CRAN.R-project.org/package=pxmake + url_git: https://github.com/StatisticsGreenland/pxmake +pxR: + version: 0.42.7 + title: PC-Axis with R + maintainer: Carlos J. Gil Bellosta + description: Provides a set of functions for reading and writing PC-Axis files, + used by different statistical organizations around the globe for data dissemination. + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pxR + url_git: https://github.com/cjgb/pxR +pxweb: + version: 0.17.0 + title: R Interface to PXWEB APIs + maintainer: Mans Magnusson + description: |- + Generic interface for the PX-Web/PC-Axis API. The + PX-Web/PC-Axis API is used by organizations such as Statistics Sweden + and Statistics Finland to disseminate data. The R package can interact + with all PX-Web/PC-Axis APIs to fetch information about the data + hierarchy, extract metadata and extract and parse statistics to R + data.frame format. PX-Web is a solution to disseminate PC-Axis data + files in dynamic tables on the web. Since 2013 PX-Web contains an API + to disseminate PC-Axis files. + date_publication: '2024-01-29' + bug_reports: https://github.com/rOpenGov/pxweb/issues + url: https://ropengov.github.io/pxweb/ + url_cran: https://CRAN.R-project.org/package=pxweb + url_git: https://github.com/rOpenGov/pxweb/ +PxWebApiData: + version: 1.0.0 + title: PX-Web Data by API + maintainer: Øyvind Langsrud + description: Function to read PX-Web data into R via API. The example code reads + data from the three national statistical institutes, Statistics Norway, Statistics + Sweden and Statistics Finland. + date_publication: '2024-11-01' + bug_reports: https://github.com/statisticsnorway/ssb-pxwebapidata/issues + url: https://statisticsnorway.github.io/ssb-pxwebapidata/ + url_cran: https://CRAN.R-project.org/package=PxWebApiData + url_git: https://github.com/statisticsnorway/ssb-pxwebapidata +pycno: + version: '1.4' + title: Pycnophylactic Interpolation + maintainer: Francesca Bitonti + description: |- + Given a SpatialPolygonsDataFrame and a set of populations for each polygon, + compute a population density estimate based on Tobler's pycnophylactic interpolation + algorithm. The result is a SpatialGridDataFrame. + Methods are described in Tobler Waldo R. (1979) . + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pycno + url_git: '' +pyinit: + version: 1.1.3 + title: Pena-Yohai Initial Estimator for Robust S-Regression + maintainer: David Kepplinger + description: |- + Deterministic Pena-Yohai initial estimator for robust S estimators + of regression. The procedure is described in detail in + Pena, D., & Yohai, V. (1999) . + date_publication: '2022-04-26' + bug_reports: https://github.com/dakep/pyinit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pyinit + url_git: https://github.com/dakep/pyinit +pylintR: + version: 0.1.0 + title: Lint 'Python' Files with a R Command or a 'RStudio' Addin + maintainer: Stéphane Laurent + description: Allow to run 'pylint' on Python files with a R command or a 'RStudio' + addin. The report appears in the RStudio viewer pane as a formatted HTML file. + date_publication: '2021-10-12' + bug_reports: https://github.com/stla/pylintR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pylintR + url_git: https://github.com/stla/pylintR +pyMTurkR: + version: 1.1.6 + title: A Client for the 'MTurk' Requester API + maintainer: Vineet Bansal + description: Provides access to the latest 'Amazon Mechanical Turk' ('MTurk') + Requester API (version '2017–01–17'), replacing the now deprecated 'MTurkR' package. + date_publication: '2024-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pyMTurkR + url_git: '' +pyramid: + version: '1.5' + title: Draw Population Pyramid + maintainer: Minato Nakazawa + description: |- + Drawing population pyramid using (1) data.frame or (2) vectors. + The former is named as pyramid() and the latter pyramids(), as wrapper + function of pyramid(). pyramidf() is the function to draw population + pyramid within the specified frame. + date_publication: '2019-07-15' + bug_reports: '' + url: http://minato.sip21c.org/swtips/Rgraphics.html#PYRAMID + url_cran: https://CRAN.R-project.org/package=pyramid + url_git: '' +pysd2r: + version: 0.1.0 + title: API to 'Python' Library 'pysd' + maintainer: Jim Duggan + description: |- + Using the R package 'reticulate', this package creates an interface to the 'pysd' toolset. + The package provides an R interface to a number of 'pysd' functions, and can read files in + 'Vensim' 'mdl' format, and 'xmile' format. The resulting simulations are returned as a 'tibble', and from + that the results can be processed using 'dplyr' and 'ggplot2'. The package has been tested using 'python3'. + date_publication: '2018-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=pysd2r + url_git: '' +pysparklyr: + version: 0.1.6 + title: Provides a 'PySpark' Back-End for the 'sparklyr' Package + maintainer: Edgar Ruiz + description: |- + It enables 'sparklyr' to integrate with 'Spark Connect', and + 'Databricks Connect' by providing a wrapper over the 'PySpark' 'python' + library. + date_publication: '2025-02-14' + bug_reports: https://github.com/mlverse/pysparklyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pysparklyr + url_git: https://github.com/mlverse/pysparklyr +PytrendsLongitudinalR: + version: 0.1.4 + title: Create Longitudinal Google Trends Data + maintainer: Taeyong Park + description: |- + 'Google Trends' provides cross-sectional and time-series data on searches, but lacks readily available + longitudinal data. Researchers, who want to create longitudinal 'Google Trends' on their own, face practical challenges, such as normalized counts that make it difficult to combine + cross-sectional and time-series data and limitations in data formats and timelines that limit data + granularity over extended time periods. + This package addresses these issues and enables researchers to generate longitudinal 'Google Trends' data. + This package is built on 'pytrends', a Python library that acts as the unofficial 'Google Trends API' to collect 'Google Trends' data. As long as the 'Google Trends API', 'pytrends' and all their dependencies are working, this package will work. + During testing, we noticed that for the same input (keyword, topic, data_format, timeline), the output index can vary from time to time. Besides, if the keyword is not very popular, then the resulting dataset will contain a lot of zeros, which will greatly affect the final result. While this package has no control over the accuracy or quality of 'Google Trends' data, once the data is created, this package coverts it to longitudinal data. + In addition, the user may encounter a 429 Too Many Requests error when using cross_section() and time_series() to collect 'Google Trends' data. This error indicates that the user has exceeded the rate limits set by the 'Google Trends API'. For more information about the 'Google Trends API' - 'pytrends', visit . + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=PytrendsLongitudinalR + url_git: '' +pzfx: + version: 0.3.0 + title: Read and Write 'GraphPad Prism' Files + maintainer: Yue Jiang + description: Read and write 'GraphPad Prism' '.pzfx' files in R. + date_publication: '2020-07-04' + bug_reports: https://github.com/Yue-Jiang/pzfx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=pzfx + url_git: https://github.com/Yue-Jiang/pzfx +Q2q: + version: 0.1.2 + title: Interpolating Age-Specific Mortality Rates at All Ages + maintainer: Farid FLICI + description: Mortality rates are typically provided in an abridged format, i.e., + by age groups 0, [1, 5], [5, 10]', '[10, 15]', and so on. Some applications necessitate + a detailed (single) age description. Despite the large number of proposed approaches + in the literature, only a few methods ensure great performance at both younger + and higher ages. For example, the 6-term 'Lagrange' interpolation function is + well suited to mortality interpolation at younger ages (with irregular intervals), + but not at older ages. The 'Karup-King' method, on the other hand, performs well + at older ages but is not suitable for younger ones. Interested readers can find + a full discussion of the two stated methods in the book Shryock, Siegel, and Associates + (1993).The Q2q package combines the two methods to allow for the interpolation + of mortality rates across all age groups. It begins by implementing each method + independently, and then the resulting curves are linked using a 5-age averaged + error between the two partial curves. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Q2q + url_git: https://github.com/Farid-FLICI/Q2q +Q7: + version: 0.1.0 + title: Types and Features for Object Oriented Programming + maintainer: Siqi Zhang + description: |2- + + Construct message-passing style objects with types and features. Q7 types uses composition instead of inheritance in creating derived types, allowing defining any code segment as feature and associating any feature to any object. Compared to R6, Q7 is simpler and more flexible, and is more friendly in syntax. + date_publication: '2020-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Q7 + url_git: '' +qacBase: + version: 1.0.3 + title: Functions to Facilitate Exploratory Data Analysis + maintainer: Kabacoff Robert + description: |- + Functions for descriptive statistics, + data management, and data visualization. + date_publication: '2022-02-09' + bug_reports: https://github.com/rkabacoff/qacBase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qacBase + url_git: https://github.com/rkabacoff/qacBase +qad: + version: 1.0.4 + title: Quantification of Asymmetric Dependence + maintainer: Nicolas Dietrich + description: |- + A copula-based measure for quantifying asymmetry in dependence and associations. Documentation and theory about 'qad' is provided + by the paper by Junker, Griessenberger & Trutschnig (2021, ), and the paper by Trutschnig (2011, ). + date_publication: '2022-12-14' + bug_reports: https://github.com/griefl/qad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qad + url_git: https://github.com/griefl/qad +QAEnsemble: + version: 1.0.0 + title: Ensemble Quadratic and Affine Invariant Markov Chain Monte Carlo + maintainer: Weston Roda + description: |- + The Ensemble Quadratic and Affine Invariant Markov chain Monte + Carlo algorithms provide an efficient way to perform Bayesian inference in + difficult parameter space geometries. The Ensemble Quadratic Monte Carlo + algorithm was developed by Militzer (2023) . + The Ensemble Affine Invariant algorithm was developed by Goodman and Weare + (2010) and it was implemented in Python by + Foreman-Mackey et al (2013) . The Quadratic + Monte Carlo method was shown to perform better than the Affine Invariant + method in the paper by Militzer (2023) and + the Quadratic Monte Carlo method is the default method used. The Chen-Shao + Highest Posterior Density Estimation algorithm is used for obtaining + credible intervals and the potential scale reduction factor diagnostic is + used for checking the convergence of the chains. + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QAEnsemble + url_git: '' +QAIG: + version: 0.1.7 + title: Automatic Item Generator for Quantitative Multiple-Choice Items + maintainer: Subhabrata Patra (Shubh) + description: |- + A tool for automatic generation of sibling items from a parent item model defined by + the user. It is an implementation of the process automatic item generation (AIG) focused + on generating quantitative multiple-choice type of items (see Embretson, Kingston + (2018) ). + date_publication: '2020-05-20' + bug_reports: https://github.com/shubh-b/QAIG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QAIG + url_git: https://github.com/shubh-b/QAIG +qap: + version: 0.1-2 + title: Heuristics for the Quadratic Assignment Problem (QAP) + maintainer: Michael Hahsler + description: Implements heuristics for the Quadratic Assignment Problem (QAP). Although, + the QAP was introduced as a combinatorial optimization problem for the facility + location problem in operations research, it also has many applications in data + analysis. The problem is NP-hard and the package implements a simulated annealing + heuristic. + date_publication: '2022-06-27' + bug_reports: https://github.com/mhahsler/qap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qap + url_git: https://github.com/mhahsler/qap +qape: + version: '2.1' + title: Quantile of Absolute Prediction Errors + maintainer: Alicja Wolny-Dominiak + description: Estimates QAPE using bootstrap procedures. The residual, parametric + and double bootstrap is used. The test of normality using Cholesky decomposition + is added. Y pop is defined. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qape + url_git: '' +Qapprox: + version: 0.2.0 + title: |- + Approximation to the Survival Functions of Quadratic Forms of + Gaussian Variables + maintainer: Hong Zhang + description: Calculates the right-tail probability of quadratic forms of Gaussian + variables using the skewness-kurtosis ratio matching method, modified Liu-Tang-Zhang + method and Satterthwaite-Welch method. The technical details can be found in Hong + Zhang, Judong Shen and Zheyang Wu (2020) . + date_publication: '2021-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Qapprox + url_git: '' +qbinplots: + version: 0.3.3 + title: Quantile Binned Plots + maintainer: Edwin de Jonge + description: |- + Create quantile binned and conditional plots for Exploratory Data + Analysis. The package provides several plotting functions that are all based + on quantile binning. The plots are created with 'ggplot2' and 'patchwork' + and can be further adjusted. + date_publication: '2025-02-24' + bug_reports: https://github.com/edwindj/qbinplots/issues + url: https://edwindj.github.io/qbinplots/ + url_cran: https://CRAN.R-project.org/package=qbinplots + url_git: '' +qbld: + version: 1.0.3 + title: Quantile Regression for Binary Longitudinal Data + maintainer: Ayush Agarwal + description: |- + Implements the Bayesian quantile regression model for binary longitudinal data + (QBLD) developed in Rahman and Vossmeyer (2019) . + The model handles both fixed and random effects and implements both a blocked + and an unblocked Gibbs sampler for posterior inference. + date_publication: '2022-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qbld + url_git: '' +QBMS: + version: 1.5.0 + title: Query the Breeding Management System(s) + maintainer: Khaled Al-Shamaa + description: |- + This R package assists breeders in linking data systems with their analytic pipelines, + a crucial step in digitizing breeding processes. It supports querying and retrieving + phenotypic and genotypic data from systems like 'EBS' , + 'BMS' , 'BreedBase' , and + 'GIGWA' (using 'BrAPI' calls). + Extra helper functions support environmental data sources, including + 'TerraClimate' and 'FAO' + 'HWSDv2' soil database. + date_publication: '2024-09-18' + bug_reports: https://github.com/icarda-git/QBMS/issues + url: https://icarda-git.github.io/QBMS/ + url_cran: https://CRAN.R-project.org/package=QBMS + url_git: '' +qboxplot: + version: '0.2' + title: Quantile-Based Boxplot + maintainer: Tom Pike + description: Produce quantile-based box-and-whisker plot(s). + date_publication: '2017-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qboxplot + url_git: '' +qbr: + version: 1.3.0 + title: Access the 'Quickbase' JSON API + maintainer: John Erdmann + description: |- + Programmatically access the 'Quickbase' JSON API . + You supply parameters for an API call, 'qbr' delivers an http request to the + API endpoint and returns its response. Outputs follow 'tidyverse' philosophy. + date_publication: '2025-01-10' + bug_reports: https://github.com/BHII-KSC/qbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qbr + url_git: https://github.com/BHII-KSC/qbr +QCA: + version: '3.23' + title: Qualitative Comparative Analysis + maintainer: Adrian Dusa + description: |- + An extensive set of functions to perform Qualitative Comparative Analysis: + crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA') + and fuzzy sets ('fsQCA'), using a GUI - graphical user interface. + 'QCA' is a methodology that bridges the qualitative and quantitative + divide in social science research. It uses a Boolean minimization + algorithm, resulting in a minimal causal configuration associated + with a given phenomenon. + date_publication: '2024-12-04' + bug_reports: https://github.com/dusadrian/QCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QCA + url_git: https://github.com/dusadrian/QCA +QCAcluster: + version: 0.1.0 + title: Tools for the Analysis of Clustered Data in QCA + maintainer: Ingo Rohlfing + description: |- + Clustered set-relational data in Qualitative Comparative Analysis + (QCA) can have a hierarchical structure, a panel structure or repeated cross + sections. 'QCAcluster' allows QCA researchers to supplement the analysis + of pooled the data with a disaggregated perspective focusing on selected + partitions of the data. The pooled data can be partitioned along the + dimensions of the clustered data (individual cross sections or time series) + to perform partition-specific truth table minimizations. Empirical + researchers can further calculate the weight that each partition has on the + parameters of the pooled solution and the diversity of the cases under + analysis within and across partitions + (see ). + date_publication: '2021-10-26' + bug_reports: https://github.com/ingorohlfing/QCAcluster/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QCAcluster + url_git: https://github.com/ingorohlfing/QCAcluster +qcapower: + version: 0.1.0 + title: Estimate Power and Required Sample Size in QCA + maintainer: Ingo Rohlfing + description: |- + Researchers working with Qualitative Comparative Analysis (QCA) + can use the package to estimate power of a sufficient term + using permutation tests. A term can be anything: A condition, conjunction or + disjunction of any combination of these. The package further allows users to plot + the estimation results and to estimate the number of cases required to achieve a + certain level of power, given a prespecified null and alternative hypothesis. + Reference for the article introducing power estimation for QCA is: + Rohlfing, Ingo (2018) + (ungated version: ). + date_publication: '2020-03-02' + bug_reports: https://github.com/ingorohlfing/qcapower + url: '' + url_cran: https://CRAN.R-project.org/package=qcapower + url_git: https://github.com/ingorohlfing/qcapower +QCApro: + version: 1.1-2 + title: |- + Advanced Functionality for Performing and Evaluating Qualitative + Comparative Analysis + maintainer: Alrik Thiem + description: Provides advanced functionality for performing configurational comparative + research with Qualitative Comparative Analysis (QCA), including crisp-set, multi-value, + and fuzzy-set QCA. It also offers advanced tools for sensitivity diagnostics and + methodological evaluations of QCA. + date_publication: '2018-01-11' + bug_reports: '' + url: http://www.alrik-thiem.net/;https://www.researchgate.net/profile/Alrik_Thiem + url_cran: https://CRAN.R-project.org/package=QCApro + url_git: '' +QCAtools: + version: 0.2.3 + title: Helper Functions for QCA in R + maintainer: Jirka Lewandowski + description: |- + Helper functions for Qualitative Comparative Analysis: evaluate and + plot Boolean formulae on fuzzy set score data, apply Boolean operations, compute + consistency and coverage measures. + date_publication: '2017-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QCAtools + url_git: '' +qcauchyreg: + version: '1.0' + title: Quantile Regression Quasi-Cauchy + maintainer: Jose Sergio Case de Oliveira + description: Quasi-Cauchy quantile regression, proposed by de Oliveira, Ospina, + Leiva, Figueroa-Zuniga and Castro (2023) . This + regression model is useful for the case where you want to model data of a nature + limited to the intervals [0,1], (0,1], [0,1) or (0,1) and you want to use a quantile + approach. + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qcauchyreg + url_git: '' +qCBA: + version: '1.0' + title: |- + Postprocessing of Rule Classification Models Learnt on Quantized + Data + maintainer: Tomáš Kliegr + description: |- + Implements the Quantitative Classification-based on + Association Rules (QCBA) algorithm (). + QCBA postprocesses rule classification models making them typically smaller and in some cases more accurate. + Supported are 'CBA' implementations from 'rCBA', 'arulesCBA' and 'arc' packages, and 'CPAR', 'CMAR', 'FOIL2' and 'PRM' implementations + from 'arulesCBA' package and 'SBRL' implementation from the 'sbrl' package. The result of the post-processing is an ordered CBA-like rule list. + date_publication: '2024-08-28' + bug_reports: https://github.com/kliegr/QCBA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qCBA + url_git: https://github.com/kliegr/QCBA +qcc: + version: '2.7' + title: Quality Control Charts + maintainer: Luca Scrucca + description: Shewhart quality control charts for continuous, attribute and count + data. Cusum and EWMA charts. Operating characteristic curves. Process capability + analysis. Pareto chart and cause-and-effect chart. Multivariate control charts. + date_publication: '2017-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qcc + url_git: https://github.com/luca-scr/qcc +qccrs: + version: 0.1.0 + title: Quality Control Charts under Repetitive Sampling + maintainer: Muhammad Yaseen + description: Functions to calculate Average Sample Numbers (ASN), Average Run Length + (ARL1) and value of k, k1 and k2 for quality control charts under repetitive sampling + as given in Aslam et al. (2014) (). + date_publication: '2018-12-03' + bug_reports: '' + url: https://myaseen208.github.io/qccrs/ + url_cran: https://CRAN.R-project.org/package=qccrs + url_git: https://github.com/myaseen208/qccrs +QCEWAS: + version: 1.2-3 + title: Fast and Easy Quality Control of EWAS Results Files + maintainer: Peter J. van der Most + description: |- + Tools for (automated and manual) quality control of + the results of Epigenome-Wide Association Studies. + date_publication: '2023-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QCEWAS + url_git: '' +QCGWAS: + version: 1.0-9 + title: Quality Control of Genome Wide Association Study Results + maintainer: Peter J. van der Most + description: Tools for (automated and manual) quality control of the results of + Genome Wide Association Studies. + date_publication: '2022-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QCGWAS + url_git: '' +qch: + version: 2.0.0 + title: Query Composite Hypotheses + maintainer: Tristan Mary-Huard + description: |- + Provides functions for the joint analysis of Q sets of + p-values obtained for the same list of items. This joint analysis is + performed by querying a composite hypothesis, i.e. an arbitrary + complex combination of simple hypotheses, as described in Mary-Huard + et al. (2021) and De Walsche et + al.(2023) . In this approach, the + Q-uplet of p-values associated with each item is distributed as a + multivariate mixture, where each of the 2^Q components corresponds to + a specific combination of simple hypotheses. The dependence between + the p-value series is considered using a Gaussian copula function. A + p-value for the composite hypothesis test is derived from the + posterior probabilities. + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qch + url_git: '' +qcluster: + version: 1.2.1 + title: Clustering via Quadratic Scoring + maintainer: Luca Coraggio + description: Performs tuning of clustering models, methods and algorithms including + the problem of determining an appropriate number of clusters. Validation of cluster + analysis results is performed via quadratic scoring using resampling methods, + as in Coraggio, L. and Coretto, P. (2023) . + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qcluster + url_git: '' +qcpm: + version: '0.4' + title: Quantile Composite Path Modeling + maintainer: Giuseppe Lamberti + description: |- + Implements the Quantile Composite-based Path Modeling approach + (Davino and Vinzi, 2016 ; + Dolce et al., 2021 ). The method complements the traditional PLS Path Modeling approach, analyzing the entire distribution of outcome variables and, therefore, overcoming the classical exploration of only average effects. It exploits quantile regression to investigate changes in the relationships among constructs and between constructs and observed variables. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qcpm + url_git: '' +qcQpcr: + version: '1.5' + title: Histone ChIP-Seq qPCR Analyzer + maintainer: Alireza Lorzadeh + description: Quality control of chromatin immunoprecipitation libraries (ChIP-seq) + by quantitative polymerase chain reaction (qPCR). This function calculates Enrichment + value with respect to reference for each histone modification (specific to 'Vii7' + software ). + This function is applicable to full panel of histone modifications described by + International Human Epigenomic Consortium (IHEC). + date_publication: '2018-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qcQpcr + url_git: '' +qcr: + version: '1.4' + title: Quality Control Review + maintainer: Miguel Flores + description: |- + Univariate and multivariate SQC tools that completes and increases + the SQC techniques available in R. Apart from integrating different R packages + devoted to SQC ('qcc','MSQC'), provides nonparametric tools that are highly + useful when Gaussian assumption is not met. + This package computes standard univariate control charts for individual measurements, + 'X-bar', 'S', 'R', 'p', 'np', 'c', 'u', 'EWMA' and 'CUSUM'. In addition, it + includes functions to perform multivariate control charts such as 'Hotelling T2', + 'MEWMA' and 'MCUSUM'. As representative feature, multivariate nonparametric + alternatives based on data depth are implemented in this package: 'r', 'Q' and + 'S' control charts. In addition, Phase I and II control charts for functional + data are included. This package also allows the estimation of the most complete + set of capability indices from first to fourth generation, covering the nonparametric + alternatives, and performing the corresponding capability analysis graphical outputs, + including the process capability plots. See Flores et al. (2021) . + date_publication: '2022-03-02' + bug_reports: https://github.com/mflores72000/qcr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qcr + url_git: https://github.com/mflores72000/qcr +QCSimulator: + version: 0.0.1 + title: A 5-Qubit Quantum Computing Simulator + maintainer: Tinniam V Ganesh + description: |- + Simulates a 5 qubit Quantum Computer and evaluates quantum circuits with 1,2 + qubit quantum gates. + date_publication: '2016-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QCSimulator + url_git: https://github.com/tvganesh/QCSimulator +QCSIS: + version: '0.1' + title: |- + Sure Independence Screening via Quantile Correlation and + Composite Quantile Correlation + maintainer: Xuejun Ma + description: Quantile correlation-sure independence screening (QC-SIS) and composite + quantile correlation-sure independence screening (CQC-SIS) for ultrahigh-dimensional + data. + date_publication: '2015-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QCSIS + url_git: '' +qcv: + version: '1.0' + title: Quantifying Construct Validity + maintainer: R. Michael Furr + description: |- + Primarily, the 'qcv' package computes key indices related to the Quantifying Construct + Validity procedure (QCV; Westen & Rosenthal, 2003 ; + see also Furr & Heuckeroth, in press). The qcv() function is the heart of the 'qcv' package, + but additional functions in the package provide useful ancillary information related to the QCV procedure. + date_publication: '2018-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qcv + url_git: '' +qdap: + version: 2.4.6 + title: |- + Bridging the Gap Between Qualitative Data and Quantitative + Analysis + maintainer: Tyler Rinker + description: |- + Automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse + including frequency counts of sentence types, words, sentences, turns of talk, syllables and other assorted + analysis tasks. The package provides parsing tools for preparing transcript data. Many functions enable the user + to aggregate data by any number of grouping variables, providing analysis and seamless integration with other R + packages that undertake higher level analysis and visualization of text. This affords the user a more efficient + and targeted analysis. 'qdap' is designed for transcript analysis, however, many functions are applicable to other + areas of Text Mining/ Natural Language Processing. + date_publication: '2023-05-11' + bug_reports: https://github.com/trinker/qdap/issues + url: https://trinker.github.io/qdap/ + url_cran: https://CRAN.R-project.org/package=qdap + url_git: '' +qdapDictionaries: + version: 1.0.7 + title: Dictionaries and Word Lists for the 'qdap' Package + maintainer: Tyler Rinker + description: |- + A collection of text analysis dictionaries and word lists for use with + the 'qdap' package. + date_publication: '2018-03-05' + bug_reports: http://github.com/trinker/qdapDictionaries/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qdapDictionaries + url_git: http://trinker.github.com/qdapDictionaries/ +qdapRegex: + version: 0.7.8 + title: Regular Expression Removal, Extraction, and Replacement Tools + maintainer: Tyler Rinker + description: |- + A collection of regular expression tools associated with + the 'qdap' package that may be useful outside of the context of + discourse analysis. Tools include + removal/extraction/replacement of abbreviations, dates, dollar + amounts, email addresses, hash tags, numbers, percentages, + citations, person tags, phone numbers, times, and zip codes. + date_publication: '2023-10-17' + bug_reports: https://github.com/trinker/qdapRegex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qdapRegex + url_git: https://github.com/trinker/qdapRegex +qdapTools: + version: 1.3.7 + title: Tools for the 'qdap' Package + maintainer: Tyler Rinker + description: |- + A collection of tools associated with the 'qdap' package that may be useful outside of the + context of text analysis. + date_publication: '2023-05-10' + bug_reports: https://github.com/trinker/qdapTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qdapTools + url_git: https://github.com/trinker/qdapTools +QDComparison: + version: '3.0' + title: |- + Modern Nonparametric Tools for Two-Sample Quantile and + Distribution Comparisons + maintainer: David Jungreis + description: Allows practitioners to determine (i) if two univariate distributions + (which can be continuous, discrete, or even mixed) are equal, (ii) how two distributions + differ (shape differences, e.g., location, scale, etc.), and (iii) where two distributions + differ (at which quantiles), all using nonparametric LP statistics. The primary + reference is Jungreis, D. (2019, Technical Report). + date_publication: '2019-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QDComparison + url_git: '' +QDiabetes: + version: 1.0-2 + title: Type 2 Diabetes Risk Calculator + maintainer: Benjamin G. Feakins + description: Calculate the risk of developing type 2 diabetes using risk prediction + algorithms derived by 'ClinRisk'. + date_publication: '2021-02-11' + bug_reports: https://github.com/Feakster/qdiabetes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QDiabetes + url_git: https://github.com/Feakster/qdiabetes +qdm: + version: 0.1-0 + title: |- + Fitting a Quadrilateral Dissimilarity Model to Same-Different + Judgments + maintainer: Nora Umbach + description: |- + This package provides different specifications of a Quadrilateral + Dissimilarity Model which can be used to fit same-different judgments + in order to get a predicted matrix that satisfies regular minimality + [Colonius & Dzhafarov, 2006, Measurement and representations of + sensations, Erlbaum]. From such a matrix, Fechnerian distances can be + computed. + date_publication: '2014-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qdm + url_git: '' +qeML: + version: '1.1' + title: Quick and Easy Machine Learning Tools + maintainer: Norm Matloff + description: |- + The letters 'qe' in the package title stand for "quick and + easy," alluding to the convenience goal of the package. We bring + together a variety of machine learning (ML) tools from standard R + packages, providing wrappers with a simple, convenient, + and uniform interface. + date_publication: '2023-11-09' + bug_reports: https://github.com/matloff/qeML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qeML + url_git: https://github.com/matloff/qeML +Qest: + version: 1.0.1 + title: Quantile-Based Estimator + maintainer: Gianluca Sottile + description: 'Quantile-based estimators (Q-estimators) can be used to fit any parametric + distribution, using its quantile function. Q-estimators are usually more robust + than standard maximum likelihood estimators. The method is described in: Sottile + G. and Frumento P. (2022). Robust estimation and regression with parametric quantile + functions. .' + date_publication: '2024-01-23' + bug_reports: '' + url: https://www.sciencedirect.com/science/article/abs/pii/S0167947322000512 + url_cran: https://CRAN.R-project.org/package=Qest + url_git: '' +QF: + version: 0.0.6 + title: Density, Cumulative and Quantile Functions of Quadratic Forms + maintainer: Aldo Gardini + description: The computation of quadratic form (QF) distributions is often not trivial + and it requires numerical routines. The package contains functions aimed at evaluating + the exact distribution of quadratic forms (QFs) and ratios of QFs. In particular, + we propose to evaluate density, quantile and distribution functions of positive + definite QFs and ratio of independent positive QFs by means of an algorithm based + on the numerical inversion of Mellin transforms. + date_publication: '2021-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QF + url_git: '' +qfa: + version: '4.0' + title: Quantile-Frequency Analysis (QFA) of Time Series + maintainer: Ta-Hsin Li + description: |- + Quantile-frequency analysis (QFA) of time series based on trigonometric quantile regression. + Spline quantile regression (SQR) for regression coefficient estimation. + References: + [1] Li, T.-H. (2012) "Quantile periodograms", Journal of the American Statistical + Association, 107, 765–776, . + [2] Li, T.-H. (2014) Time Series with Mixed Spectra, CRC Press, + [3] Li, T.-H. (2022) "Quantile Fourier transform, quantile series, and nonparametric + estimation of quantile spectra", . + [4] Li, T.-H. (2024) "Quantile crossing spectrum and spline autoregression + estimation," . + [5] Li, T.-H. (2024) "Spline autoregression method for estimation of quantile spectrum", + . + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qfa + url_git: https://github.com/IBM/qfa +QFASA: + version: 1.2.1 + title: Quantitative Fatty Acid Signature Analysis + maintainer: Connie Stewart + description: |- + Accurate estimates of the diets of predators are required + in many areas of ecology, but for many species current methods are + imprecise, limited to the last meal, and often biased. The diversity + of fatty acids and their patterns in organisms, coupled with the + narrow limitations on their biosynthesis, properties of digestion in + monogastric animals, and the prevalence of large storage reservoirs of + lipid in many predators, led to the development of quantitative + fatty acid signature analysis (QFASA) to study predator diets. + date_publication: '2024-08-27' + bug_reports: https://github.com/cstewartGH/QFASA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QFASA + url_git: '' +qfasar: + version: 1.2.1 + title: Quantitative Fatty Acid Signature Analysis in R + maintainer: Jeffrey F. Bromaghin + description: |- + An implementation of Quantitative Fatty Acid Signature + Analysis (QFASA) in R. QFASA is a method of estimating the diet + composition of predators. The fundamental unit of information in + QFASA is a fatty acid signature (signature), which is a vector of + proportions describing the composition of fatty acids within lipids. + Signature data from at least one predator and from samples of all + potential prey types are required. Calibration coefficients, which + adjust for the differential metabolism of individual fatty acids by + predators, are also required. Given those data inputs, a predator + signature is modeled as a mixture of prey signatures and its diet + estimate is obtained as the mixture that minimizes a measure of + distance between the observed and modeled signatures. A variety of + estimation options and simulation capabilities are implemented. + Please refer to the vignette for additional details and references. + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qfasar + url_git: '' +qfratio: + version: 1.1.1 + title: |- + Moments and Distributions of Ratios of Quadratic Forms Using + Recursion + maintainer: Junya Watanabe + description: |- + Evaluates moments of ratios (and products) of quadratic forms + in normal variables, specifically using recursive algorithms developed by + Bao and Kan (2013) and Hillier et al. + (2014) . Also provides distribution, + quantile, and probability density functions of simple ratios of quadratic + forms in normal variables with several algorithms. Originally developed as + a supplement to Watanabe (2023) for + evaluating average evolvability measures in evolutionary quantitative + genetics, but can be used for a broader class of statistics. Generating + functions for these moments are also closely related to the top-order zonal + and invariant polynomials of matrix arguments. + date_publication: '2024-02-09' + bug_reports: https://github.com/watanabe-j/qfratio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qfratio + url_git: https://github.com/watanabe-j/qfratio +QFRM: + version: 1.0.1 + title: Pricing of Vanilla and Exotic Option Contracts + maintainer: Oleg Melnikov + description: |2- + + Option pricing (financial derivatives) techniques mainly following textbook 'Options, Futures and Other Derivatives', 9ed by John C.Hull, 2014. Prentice Hall. Implementations are via binomial tree option model (BOPM), Black-Scholes model, Monte Carlo simulations, etc. + This package is a result of Quantitative Financial Risk Management course (STAT 449 and STAT 649) at Rice University, Houston, TX, USA, taught by Oleg Melnikov, statistics PhD student, as of Spring 2015. + date_publication: '2015-07-28' + bug_reports: '' + url: http://Oleg.Rice.edu + url_cran: https://CRAN.R-project.org/package=QFRM + url_git: '' +QGA: + version: '1.0' + title: Quantum Genetic Algorithm + maintainer: Giulio Barcaroli + description: 'Function that implements the Quantum Genetic Algorithm, first proposed + by Han and Kim in 2000. This is an R implementation of the ''python'' application + developed by Lahoz-Beltra (). + Each optimization problem is represented as a maximization one, where each solution + is a sequence of (qu)bits. Following the quantum paradigm, these qubits are in + a superposition state: when measuring them, they collapse in a 0 or 1 state. After + measurement, the fitness of the solution is calculated as in usual genetic algorithms. + The evolution at each iteration is oriented by the application of two quantum + gates to the amplitudes of the qubits: (1) a rotation gate (always); (2) a Pauli-X + gate (optionally). The rotation is based on the theta angle values: higher values + allow a quicker evolution, and lower values avoid local maxima. The Pauli-X gate + is equivalent to the classical mutation operator and determines the swap between + alfa and beta amplitudes of a given qubit. The package has been developed in such + a way as to permit a complete separation between the engine, and the particular + problem subject to combinatorial optimization.' + date_publication: '2024-05-31' + bug_reports: https://github.com/barcaroli/QGA/issues + url: https://barcaroli.github.io/QGA/ + url_cran: https://CRAN.R-project.org/package=QGA + url_git: https://github.com/barcaroli/QGA/ +qgam: + version: 1.3.4 + title: Smooth Additive Quantile Regression Models + maintainer: Matteo Fasiolo + description: |- + Smooth additive quantile regression models, fitted using + the methods of Fasiolo et al. (2020) . + See Fasiolo at al. (2021) for an introduction to the package. Differently from + 'quantreg', the smoothing parameters are estimated automatically by marginal + loss minimization, while the regression coefficients are estimated using either + PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian + credible intervals of the estimated effects have approximately the correct + coverage. The main function is qgam() which is similar to gam() in 'mgcv', but + fits non-parametric quantile regression models. + date_publication: '2021-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qgam + url_git: '' +QGameTheory: + version: 0.1.2 + title: Quantum Game Theory Simulator + maintainer: Indranil Ghosh + description: 'General purpose toolbox for simulating quantum versions of game theoretic + models (Flitney and Abbott 2002) . Quantum (Nielsen and + Chuang 2010, ISBN:978-1-107-00217-3) versions of models that have been handled + are: Penny Flip Game (David A. Meyer 1998) , Prisoner''s + Dilemma (J. Orlin Grabbe 2005) , Two Person Duel (Flitney + and Abbott 2004) , Battle of the Sexes (Nawaz and Toor + 2004) , Hawk and Dove Game (Nawaz and Toor 2010) , + Newcomb''s Paradox (Piotrowski and Sladkowski 2002) and + Monty Hall Problem (Flitney and Abbott 2002) .' + date_publication: '2020-06-12' + bug_reports: https://github.com/indrag49/QGameTheory/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QGameTheory + url_git: https://github.com/indrag49/QGameTheory +qGaussian: + version: 0.1.8 + title: The q-Gaussian Distribution + maintainer: Wagner Santos de Lima + description: |- + Density, distribution function, quantile function and + random generation for the q-gaussian distribution with parameters mu and sig. + date_publication: '2018-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qGaussian + url_git: '' +qgcomp: + version: 2.17.4 + title: Quantile G-Computation + maintainer: Alexander Keil + description: |- + G-computation for a set of time-fixed exposures with + quantile-based basis functions, possibly under linearity and + homogeneity assumptions. This approach estimates a regression line + corresponding to the expected change in the outcome (on the link + basis) given a simultaneous increase in the quantile-based category + for all exposures. Works with continuous, binary, and right-censored + time-to-event outcomes. Reference: Alexander P. Keil, Jessie P. + Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and + Alexandra J. White (2019) A quantile-based g-computation approach to + addressing the effects of exposure mixtures; . + date_publication: '2025-02-23' + bug_reports: https://github.com/alexpkeil1/qgcomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qgcomp + url_git: https://github.com/alexpkeil1/qgcomp/ +qgcompint: + version: 0.7.0 + title: |- + Quantile G-Computation Extensions for Effect Measure + Modification + maintainer: Alexander Keil + description: |- + G-computation for a set of time-fixed exposures + with quantile-based basis functions, possibly under linearity and + homogeneity assumptions. Effect measure modification in this method is a way + to assess how the effect of the mixture varies by a binary, categorical or continuous variable. + Reference: Alexander P. Keil, Jessie P. + Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and + Alexandra J. White (2019) A quantile-based g-computation approach to + addressing the effects of exposure mixtures; . + date_publication: '2022-03-22' + bug_reports: https://github.com/alexpkeil1/qgcomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qgcompint + url_git: https://github.com/alexpkeil1/qgcomp/ +qgg: + version: 1.1.6 + title: Statistical Tools for Quantitative Genetic Analyses + maintainer: Peter Soerensen + description: |- + Provides an infrastructure for efficient processing of large-scale genetic and phenotypic data including core functions for: 1) fitting linear mixed models, 2) constructing marker-based genomic relationship matrices, 3) estimating genetic parameters (heritability and correlation), 4) performing genomic prediction and genetic risk profiling, and 5) single or multi-marker association analyses. + Rohde et al. (2019) . + date_publication: '2024-12-16' + bug_reports: https://github.com/psoerensen/qgg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qgg + url_git: https://github.com/psoerensen/qgg +QGglmm: + version: 0.8.0 + title: |- + Estimate Quantitative Genetics Parameters from Generalised + Linear Mixed Models + maintainer: Pierre de Villemereuil + description: Compute various quantitative genetics parameters from a Generalised + Linear Mixed Model (GLMM) estimates. Especially, it yields the observed phenotypic + mean, phenotypic variance and additive genetic variance. + date_publication: '2025-01-20' + bug_reports: https://github.com/devillemereuil/qgglmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QGglmm + url_git: '' +qgisprocess: + version: 0.4.1 + title: Use 'QGIS' Processing Algorithms + maintainer: Floris Vanderhaeghe + description: |- + Provides seamless access to the 'QGIS' + () processing toolbox using the standalone + 'qgis_process' command-line utility. Both native and third-party + (plugin) processing providers are supported. Beside referring data + sources from file, also common objects from 'sf', 'terra' and 'stars' + are supported. The native processing algorithms are documented by QGIS.org + (2024) . + date_publication: '2024-10-06' + bug_reports: https://github.com/r-spatial/qgisprocess/issues + url: https://r-spatial.github.io/qgisprocess/ + url_cran: https://CRAN.R-project.org/package=qgisprocess + url_git: https://github.com/r-spatial/qgisprocess +qgraph: + version: 1.9.8 + title: |- + Graph Plotting Methods, Psychometric Data Visualization and + Graphical Model Estimation + maintainer: Sacha Epskamp + description: Fork of qgraph - Weighted network visualization and analysis, as well + as Gaussian graphical model computation. See Epskamp et al. (2012) . + date_publication: '2023-11-03' + bug_reports: https://github.com/SachaEpskamp/qgraph + url: '' + url_cran: https://CRAN.R-project.org/package=qgraph + url_git: '' +qgshiny: + version: 0.1.0 + title: |- + A 'shiny' Application for Active Learning Instruction in + Introductory Quantitative Genetics + maintainer: Jeffrey Neyhart + description: |- + A 'shiny' application for teaching introductory quantitative genetics + and plant breeding through interactive simulations. The application relies on + established plant breeding and quantitative genetic theory found in + Falconer and Mackay (1996, ISBN:0582243025) and Bernardo (2010, ISBN:978-0972072427). + date_publication: '2020-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qgshiny + url_git: '' +QHOT: + version: 0.1.0 + title: QTL Hotspot Detection + maintainer: ManHsia Yang + description: This function produces both the numerical and graphical summaries of + the QTL hotspot detection in the genomes that are available on the worldwide web + including the flanking markers of QTLs. + date_publication: '2019-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QHOT + url_git: '' +QHScrnomo: + version: 3.0.1 + title: Construct Nomograms for Competing Risks Regression Models + maintainer: Zajichek Alex + description: |- + Nomograms are constructed to predict the cumulative incidence + rate which is calculated after adjusting for competing causes to the event of interest. + K-fold cross-validation is implemented to validate predictive accuracy using a competing-risk version of the concordance index. + Methods are as described in: Kattan MW, Heller G, + Brennan MF (2003). + date_publication: '2024-03-18' + bug_reports: https://github.com/ClevelandClinicQHS/QHScrnomo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QHScrnomo + url_git: https://github.com/ClevelandClinicQHS/QHScrnomo +QI: + version: 0.1.0 + title: Quantity-Intensity Relationship of Soil Potassium + maintainer: Bappa Das + description: |- + The quantity-intensity (Q/I) relationships, first introduced by Beckett + (1964), can be employed to assess the K supplying capacity of different soils + based on solid-solution exchange equilibria. Such relationships describe the + changes in K+ concentration in the soil solution (or the intensity factor) in + relation to the corresponding changes in K+ at exchange sites of the soil + (or the capacity or quantity factor). Activity ratio of K to Ca or Ca+Mg + is generally used as the variable denoting the intensity, whereas, change + in exchangeable K is used to denote the quantity factor. + date_publication: '2022-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QI + url_git: '' +qicharts: + version: 0.5.8 + title: Quality Improvement Charts + maintainer: Jacob Anhoej + description: |- + Functions for making run charts + [Anhoej, Olesen (2014) ] and basic + Shewhart control charts [Mohammed, Worthington, Woodall (2008) + ] for measure and count data. + The main function, qic(), creates run and control charts and has a + simple interface with a rich set of options to control data analysis + and plotting, including options for automatic data aggregation by + subgroups, easy analysis of before-and-after data, exclusion of one + or more data points from analysis, and splitting charts into + sequential time periods. + Missing values and empty subgroups are handled gracefully. + date_publication: '2021-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qicharts + url_git: '' +qicharts2: + version: 0.7.5 + title: Quality Improvement Charts + maintainer: Jacob Anhoej + description: |- + Functions for making run charts, Shewhart control charts and + Pareto charts for continuous quality improvement. Included control charts + are: I, MR, Xbar, S, T, C, U, U', P, P', and G charts. Non-random variation + in the form of minor to moderate persistent shifts in data over time is + identified by the Anhoej rules for unusually long runs and unusually few + crossing [Anhoej, Olesen (2014) ]. + Non-random variation in the form of larger, possibly transient, shifts is + identified by Shewhart's 3-sigma rule [Mohammed, Worthington, Woodall (2008) + ]. + date_publication: '2024-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qicharts2 + url_git: https://github.com/anhoej/qicharts2 +qif: + version: '1.5' + title: Quadratic Inference Function + maintainer: Michael Kleinsasser + description: |- + Developed to perform the estimation and inference for regression + coefficient parameters in longitudinal marginal models using the method of + quadratic inference functions. Like generalized estimating equations, this + method is also a quasi-likelihood inference method. It has been showed that + the method gives consistent estimators of the regression coefficients even if + the correlation structure is misspecified, and it is more efficient than GEE + when the correlation structure is misspecified. Based on Qu, A., Lindsay, + B.G. and Li, B. (2000) . + date_publication: '2019-07-20' + bug_reports: https://github.com/umich-biostatistics/qif/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qif + url_git: '' +qiitr: + version: 0.1.1 + title: R Interface to Qiita API + maintainer: Hiroaki Yutani + description: |- + Qiita is a technical knowledge sharing and collaboration platform for programmers. + See for more information. + date_publication: '2020-05-16' + bug_reports: https://github.com/yutannihilation/qiitr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qiitr + url_git: https://github.com/yutannihilation/qiitr +Qindex: + version: 0.1.7 + title: |- + Continuous and Dichotomized Index Predictors Based on + Distribution Quantiles + maintainer: Tingting Zhan + description: |- + Select optimal functional regression or dichotomized + quantile predictors for survival/logistic/numeric outcome + and perform optimistic bias correction for any optimally + dichotomized numeric predictor(s), as in Yi, et. al. + (2023) . + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Qindex + url_git: '' +Qindex.data: + version: 0.1.3 + title: Data for Package 'Qindex' + maintainer: Tingting Zhan + description: Example data used in package 'Qindex'. + date_publication: '2025-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Qindex.data + url_git: '' +qkerntool: + version: '1.19' + title: |- + Q-Kernel-Based and Conditionally Negative Definite Kernel-Based + Machine Learning Tools + maintainer: Yusen Zhang + description: |- + Nonlinear machine learning tool for classification, clustering + and dimensionality reduction. It integrates 12 q-kernel functions and + 15 conditional negative definite kernel functions and includes the + q-kernel and conditional negative definite kernel version of + density-based spatial clustering of applications with noise, + spectral clustering, generalized discriminant analysis, principal + component analysis, multidimensional scaling, locally linear embedding, + sammon's mapping and t-Distributed stochastic neighbor embedding. + date_publication: '2019-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qkerntool + url_git: '' +qlcal: + version: 0.0.14 + title: R Bindings to the Calendaring Functionality of 'QuantLib' + maintainer: Dirk Eddelbuettel + description: |- + 'QuantLib' bindings are provided for R using 'Rcpp' via an evolved version + of the initial header-only 'Quantuccia' project offering an subset of 'QuantLib' (now + maintained separately just for the calendaring subset). See the included file 'AUTHORS' + for a full list of contributors to 'QuantLib' (and hence also 'Quantuccia'). + date_publication: '2025-01-23' + bug_reports: https://github.com/qlcal/qlcal-r/issues + url: https://dirk.eddelbuettel.com/code/qlcal-r.html + url_cran: https://CRAN.R-project.org/package=qlcal + url_git: https://github.com/qlcal/qlcal-r +qlcData: + version: '0.3' + title: Processing Data for Quantitative Language Comparison + maintainer: Michael Cysouw + description: |- + Functionality to read, recode, and transcode data as used in + quantitative language comparison, specifically to deal with multilingual + orthographic variation (Moran & Cysouw (2018) ) + and with the recoding of nominal data. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qlcData + url_git: '' +qlcMatrix: + version: 0.9.8 + title: |- + Utility Sparse Matrix Functions for Quantitative Language + Comparison + maintainer: Michael Cysouw + description: Extension of the functionality of the 'Matrix' package for using sparse + matrices. Some of the functions are very general, while other are highly specific + for special data format as used for quantitative language comparison. + date_publication: '2024-05-08' + bug_reports: https://github.com/cysouw/qlcMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qlcMatrix + url_git: https://github.com/cysouw/qlcMatrix +qlcVisualize: + version: '0.4' + title: Visualization for Quantitative Language Comparison + maintainer: Michael Cysouw + description: |- + Collection of visualizations as used in quantitative language + comparison. Currently implemented are visualisations dealing nominal data with + multiple levels ("level map" and "factor map"), and assistance for making + weighted geographical Voronoi-maps ("weighted map"). + date_publication: '2024-08-01' + bug_reports: https://github.com/cysouw/qlcVisualize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qlcVisualize + url_git: https://github.com/cysouw/qlcVisualize +QLearning: + version: 0.1.1 + title: Reinforcement Learning using the Q Learning Algorithm + maintainer: Liam Bressler + description: |- + Implements Q-Learning, a model-free form of reinforcement + learning, described in work by Strehl, Li, Wiewiora, Langford & + Littman (2006) . + date_publication: '2017-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QLearning + url_git: '' +qlifetable: + version: 0.0.2-5 + title: Managing and Building of Quarterly Life Tables + maintainer: Jose M. Pavía + description: |- + Manages, builds and computes statistics and datasets for the + construction of quarterly (sub-annual) life tables by exploiting micro-data from + either a general or an insured population. + References: + Pavía and Lledó (2022) . + Pavía and Lledó (2023) . + Acknowledgements: + The authors wish to thank Consellería de Educación, Universidades y Empleo, Generalitat Valenciana (grant AICO/2021/257), Ministerio de Ciencia e Innovación (grant PID2021-128228NB-I00) and Fundación Mapfre (grant 'Modelización espacial e intra-anual de la mortalidad en España. Una herramienta automática para el cálculo de productos de vida') for supporting this research. + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qlifetable + url_git: '' +qmap: + version: 1.0-6 + title: |- + Statistical Transformations for Post-Processing Climate Model + Output + maintainer: Lukas Gudmundsson + description: Empirical adjustment of the distribution of variables originating from + (regional) climate model simulations using quantile mapping. + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qmap + url_git: '' +qmd: + version: 1.1.2 + title: Quantification of Multivariate Dependence + maintainer: Nicolas Dietrich + description: A multivariate copula-based dependence measure. For more information, + see Griessenberger, Junker, Trutschnig (2022), On a multivariate copula-based + dependence measure and its estimation, Electronic Journal of Statistics, 16, 2206-2251. + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qmd + url_git: '' +qmethod: + version: 1.8.4 + title: Analysis of Subjective Perspectives Using Q Methodology + maintainer: Aiora Zabala + description: |- + Analysis of Q methodology, used to identify distinct perspectives existing within a group. + This methodology is used across social, health and environmental sciences to understand diversity of attitudes, discourses, or decision-making styles (for more information, see ). + A single function runs the full analysis. Each step can be run separately using the corresponding functions: for automatic flagging of Q-sorts (manual flagging is optional), for statement scores, for distinguishing and consensus statements, and for general characteristics of the factors. + The package allows to choose either principal components or centroid factor extraction, manual or automatic flagging, a number of mathematical methods for rotation (or none), and a number of correlation coefficients for the initial correlation matrix, among many other options. + Additional functions are available to import and export data (from raw *.CSV, 'HTMLQ' and 'FlashQ' *.CSV, 'PQMethod' *.DAT and 'easy-htmlq' *.JSON files), to print and plot, to import raw data from individual *.CSV files, and to make printable cards. + The package also offers functions to print Q cards and to generate Q distributions for study administration. + See further details in the package documentation, and in the web pages below, which include a cookbook, guidelines for more advanced analysis (how to perform manual flagging or change the sign of factors), data management, and a graphical user interface (GUI) for online and offline use. + date_publication: '2023-03-28' + bug_reports: https://github.com/aiorazabala/qmethod/issues + url: http://aiorazabala.github.io/qmethod/ + url_cran: https://CRAN.R-project.org/package=qmethod + url_git: https://github.com/aiorazabala/qmethod +qmj: + version: 0.2.1 + title: Quality Scores for the Russell 3000 + maintainer: Yanrong Song + description: |- + Produces quality scores for each of the US companies from + the Russell 3000, following the approach described in + "Quality Minus Junk" (Asness, Frazzini, & Pedersen, 2013) + . + The package includes datasets for users who wish to view the most recently + uploaded quality scores. It also provides tools to automatically gather + relevant financials and stock price information, allowing users to update + their data and customize their universe for further analysis. + date_publication: '2025-01-15' + bug_reports: https://github.com/anttsou/qmj/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qmj + url_git: '' +qMRI: + version: 1.2.7.8 + title: Methods for Quantitative Magnetic Resonance Imaging ('qMRI') + maintainer: Karsten Tabelow + description: |- + Implementation of methods for estimation of quantitative maps + from Multi-Parameter Mapping (MPM) acquisitions (Weiskopf et al. (2013) + ) and analysis of Inversion Recovery MRI data. + Usage of the package is described in + Polzehl and Tabelow (2023), + "Magnetic Resonance Brain Imaging", 2nd Edition, Chapter 6 and 7, Springer, Use R! Series. + . + J. Polzehl and K. Tabelow (2023), "Magnetic Resonance Brain Imaging - Modeling and Data Analysis Using R: Code and Data." + provides extensive example code and data. + date_publication: '2024-12-09' + bug_reports: '' + url: https://www.wias-berlin.de/research/ats/imaging/ + url_cran: https://CRAN.R-project.org/package=qMRI + url_git: '' +qmrparser: + version: 0.1.6 + title: Parser Combinator in R + maintainer: Juan Gea + description: Basic functions for building parsers, with an application to PC-AXIS + format files. + date_publication: '2022-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qmrparser + url_git: '' +qmvs: + version: 0.2.2 + title: Queueing Model of Visual Search + maintainer: Yiqi Li + description: The queueing model of visual search models the accuracy and response + time data in a visual search experiment using queueing models with finite customer + population and stopping criteria of completing the service for finite number of + customers. It implements the conceptualization of a hybrid model proposed by Moore + and Wolfe (2001), in which visual stimuli enter the processing one after the other + and then are identified in parallel. This package provides functions that simulate + the specified queueing process and calculate the Wasserstein distance between + the empirical response times and the model prediction. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qmvs + url_git: '' +qoi: + version: 0.1.0 + title: Read and Write QOI Images + maintainer: Johannes Friedrich + description: The new QOI file format offers a very simple but efficient image compression + algorithm. This package provides an easy and simple way to read, write and display + bitmap images stored in the QOI (Quite Ok Image) format. It can read and write + both files and in-memory raw vectors. + date_publication: '2024-04-17' + bug_reports: https://github.com/JohannesFriedrich/qoi4R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qoi + url_git: https://github.com/JohannesFriedrich/qoi4R +QoLMiss: + version: 0.1.0 + title: Scales Score Calculation from Quality of Life Data + maintainer: Atanu Bhattacharjee + description: 'There are three functions: qol, miss_qol and miss_patient takes input + of the data set containing the answers of QOL questionnaire. It will compute the + three types of domain based scale scores: Global, Functional, and Symptoms. In + case of missing data, the miss_qol and miss_patient functions will make the required + changes and then calculate the domain-wise scale scores. Finally, provide an output + replacing the question columns with the domain-based scale scores in the original + data set.' + date_publication: '2022-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QoLMiss + url_git: '' +qountstat: + version: 0.1.1 + title: Statistical Analysis of Count Data and Quantal Data + maintainer: Benjamin Daniels + description: |- + Methods for statistical analysis of count data and quantal data. + For the analysis of count data an implementation of the Closure Principle Computational Approach Test ("CPCAT") is provided (Lehmann, R et al. (2016) ), as well as an implementation of a "Dunnett GLM" approach using a Quasi-Poisson regression (Hothorn, L, Kluxen, F (2020) ). + For the analysis of quantal data an implementation of the Closure Principle Fisher–Freeman–Halton test ("CPFISH") is provided (Lehmann, R et al. (2018) ). P-values and no/lowest observed (adverse) effect concentration values are calculated. + All implemented methods include further functions to evaluate the power and the minimum detectable difference using a bootstrapping approach. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qountstat + url_git: '' +qpcR: + version: 1.4-1 + title: Modelling and Analysis of Real-Time PCR Data + maintainer: Andrej-Nikolai Spiess + description: Model fitting, optimal model selection and calculation of various features + that are essential in the analysis of quantitative real-time polymerase chain + reaction (qPCR). + date_publication: '2018-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qpcR + url_git: '' +qPCRhelper: + version: 0.1.0 + title: qPCR Ct Values to Expression Values + maintainer: Wilson Jr. Aala + description: |- + Computes normalized cycle threshold (Ct) values (delta Ct) from raw quantitative polymerase + chain reaction (qPCR) Ct values and conducts test of significance using t.test(). Plots expression + values based from log2(2^(-1*delta delta Ct)) across groups per gene of interest. Methods for calculation + of delta delta Ct and relative expression (2^(-1*delta delta Ct)) values are described in: + Livak & Schmittgen, (2001) . + date_publication: '2023-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qPCRhelper + url_git: '' +qPCRtools: + version: 1.0.1 + title: Tools for qPCR + maintainer: Xiang LI + description: PKG_DESC. + date_publication: '2023-11-02' + bug_reports: https://github.com/lixiang117423/qPCRtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qPCRtools + url_git: https://github.com/lixiang117423/qPCRtools +qpdf: + version: 1.3.4 + title: Split, Combine and Compress PDF Files + maintainer: Jeroen Ooms + description: |- + Content-preserving transformations transformations of PDF files such + as split, combine, and compress. This package interfaces directly to the 'qpdf' + C++ library and does not require any command + line utilities. Note that 'qpdf' does not read actual content from PDF files: + to extract text and data you need the 'pdftools' package. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/qpdf/issues + url: https://docs.ropensci.org/qpdf/https://ropensci.r-universe.dev/qpdf + url_cran: https://CRAN.R-project.org/package=qpdf + url_git: '' +qpmadr: + version: 1.1.0-0 + title: Interface to the 'qpmad' Quadratic Programming Solver + maintainer: Eric Anderson + description: Efficiently solve quadratic problems with linear inequality, equality + and box constraints. The method used is outlined in D. Goldfarb, and A. Idnani + (1983) . + date_publication: '2021-06-23' + bug_reports: https://github.com/anderic1/qpmadr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qpmadr + url_git: https://github.com/anderic1/qpmadr +qpNCA: + version: 1.1.6 + title: Noncompartmental Pharmacokinetic Analysis by qPharmetra + maintainer: Jan Huisman + description: |- + Computes noncompartmental pharmacokinetic parameters + for drug concentration profiles. For each profile, data + imputations and adjustments are made as necessary and + basic parameters are estimated. Supports single dose, multi-dose, + and multi-subject data. Supports steady-state calculations + and various routes of drug administration. See ?qpNCA and vignettes. + Methodology follows Rowland and Tozer (2011, ISBN:978-0-683-07404-8), + Gabrielsson and Weiner (1997, ISBN:978-91-9765-100-4), and + Gibaldi and Perrier (1982, ISBN:978-0824710422). + date_publication: '2021-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qpNCA + url_git: '' +qPRAentry: + version: 0.1.0 + title: Quantitative Pest Risk Assessment at the Entry Step + maintainer: Martina Cendoya + description: |- + Supports risk assessors in performing the entry step of the + quantitative Pest Risk Assessment. It allows the estimation of the + amount of a plant pest entering a risk assessment area (in terms of + founder populations) through the calculation of the imported + commodities that could be potential pathways of pest entry, and the + development of a pathway model. Two 'Shiny' apps based on the + functionalities of the package are included, that simplify the process + of assessing the risk of entry of plant pests. The approach is based + on the work of the European Food Safety Authority (EFSA PLH Panel et + al., 2018) . + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qPRAentry + url_git: '' +qqboxplot: + version: 0.3.0 + title: Implementation of the Q-Q Boxplot + maintainer: Jordan Rodu + description: |- + A system to implement the Q-Q boxplot. It is implemented as an + extension to 'ggplot2'. The Q-Q boxplot is an amalgam of the boxplot and the + Q-Q plot and allows the user to rapidly examine summary statistics and tail + behavior for multiple distributions in the same pane. As an extension of + the 'ggplot2' implementation of the boxplot, possible modifications to the + boxplot extend to the Q-Q boxplot. + date_publication: '2022-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qqboxplot + url_git: '' +qqconf: + version: 1.3.2 + title: Creates Simultaneous Testing Bands for QQ-Plots + maintainer: Eric Weine + description: |- + Provides functionality for creating Quantile-Quantile (QQ) and Probability-Probability (PP) plots with simultaneous + testing bands to asses significance of sample deviation from a reference distribution . + date_publication: '2023-04-14' + bug_reports: https://github.com/eweine/qqconf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qqconf + url_git: https://github.com/eweine/qqconf +qqman: + version: 0.1.9 + title: Q-Q and Manhattan Plots for GWAS Data + maintainer: Stephen Turner + description: Create Q-Q and manhattan plots for GWAS data from PLINK results. + date_publication: '2023-08-23' + bug_reports: https://github.com/stephenturner/qqman/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qqman + url_git: https://github.com/stephenturner/qqman +qqplotr: + version: 0.0.6 + title: Quantile-Quantile Plot Extensions for 'ggplot2' + maintainer: Adam Loy + description: Extensions of 'ggplot2' Q-Q plot functionalities. + date_publication: '2023-01-25' + bug_reports: https://github.com/aloy/qqplotr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qqplotr + url_git: https://github.com/aloy/qqplotr +qqtest: + version: 1.2.0 + title: Self Calibrating Quantile-Quantile Plots for Visual Testing + maintainer: Wayne Oldford + description: |- + Provides the function qqtest which incorporates uncertainty in its + qqplot display(s) so that the user might have a better sense of the + evidence against the specified distributional hypothesis. qqtest draws a + quantile quantile plot for visually assessing whether the data come from a + test distribution that has been defined in one of many ways. The vertical + axis plots the data quantiles, the horizontal those of a test distribution. + The default behaviour generates 1000 samples from the test distribution and + overlays the plot with shaded pointwise interval estimates for the ordered + quantiles from the test distribution. A small number of independently + generated exemplar quantile plots can also be overlaid. Both the interval + estimates and the exemplars provide different comparative information to + assess the evidence provided by the qqplot for or against the hypothesis + that the data come from the test distribution (default is normal or + gaussian). Finally, a visual test of significance (a lineup plot) can also + be displayed to test the null hypothesis that the data come from the test + distribution. + date_publication: '2020-03-16' + bug_reports: '' + url: https://rwoldford.github.io/qqtest/ + url_cran: https://CRAN.R-project.org/package=qqtest + url_git: https://github.com/rwoldford/qqtest +qqvases: + version: 1.0.0 + title: Animated Normal Quantile-Quantile Plots + maintainer: Robert Stine + description: Presents an explanatory animation of normal quantile-quantile plots + based on a water-filling analogy. The animation presents a normal QQ plot as + the parametric plot of the water levels in vases defined by two distributions. The + distributions decorate the axes in the normal QQ plot and are optionally shown + as vases adjacent to the plot. The package draws QQ plots for several distributions, + either as samples or continuous functions. + date_publication: '2016-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qqvases + url_git: '' +QR: + version: 0.1.3 + title: QR Factorization without Pivoting + maintainer: Juan Claramunt Gonzalez + description: This function performs QR factorization without pivoting to a real + or complex matrix. It is based on Anderson. E. and ten others (1999) "LAPACK Users' + Guide". Third Edition. SIAM. + date_publication: '2022-07-17' + bug_reports: '' + url: http://www.netlib.org/lapack/explore-html/df/dc5/group__variants_g_ecomputational_ga3766ea903391b5cf9008132f7440ec7b.html + url_cran: https://CRAN.R-project.org/package=QR + url_git: '' +qra: + version: 0.2.7 + title: Quantal Response Analysis for Dose-Mortality Data + maintainer: John Maindonald + description: |- + Functions are provided that implement the + use of the Fieller's formula methodology, for + calculating a confidence interval for a ratio of + (commonly, correlated) means. See Fieller (1954) + . Here, + the application of primary interest is to studies + of insect mortality response to increasing doses + of a fumigant, or, e.g., to time in coolstorage. + The formula is used to calculate a confidence + interval for the dose or time required to achieve + a specified mortality proportion, commonly 0.5 + or 0.99. Vignettes demonstrate link functions + that may be considered, checks on fitted models, + and alternative choices of error family. Note + in particular the betabinomial error family. + See also Maindonald, Waddell, and Petry (2001) + . + date_publication: '2021-10-29' + bug_reports: https://github.com/jhmaindonald/qra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qra + url_git: https://github.com/jhmaindonald/qra +QRAGadget: + version: 0.3.0 + title: A 'Shiny' Gadget for Interactive 'QRA' Visualizations + maintainer: Paul Govan + description: |- + Upload raster data and easily create interactive quantitative risk analysis 'QRA' visualizations. Select + from numerous color palettes, base-maps, and different configurations. + date_publication: '2023-06-23' + bug_reports: https://github.com/paulgovan/qragadget/issues + url: http://paulgovan.github.io/QRAGadget/ + url_cran: https://CRAN.R-project.org/package=QRAGadget + url_git: https://github.com/paulgovan/qragadget +QRank: + version: '1.0' + title: A Novel Quantile Regression Approach for eQTL discovery + maintainer: Xiaoyu Song + description: A Quantile Rank-score based test for the identification of expression + quantitative trait loci. + date_publication: '2017-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QRank + url_git: '' +qrcm: + version: '3.1' + title: Quantile Regression Coefficients Modeling + maintainer: Paolo Frumento + description: Parametric modeling of quantile regression coefficient functions. + date_publication: '2024-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrcm + url_git: '' +qrcmNP: + version: 0.2.1 + title: |- + Nonlinear and Penalized Quantile Regression Coefficients + Modeling + maintainer: Gianluca Sottile + description: Nonlinear and Penalized parametric modeling of quantile regression + coefficient functions. Sottile G, Frumento P, Chiodi M and Bottai M (2020) . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrcmNP + url_git: '' +qrcode: + version: 0.3.0 + title: Generate QRcodes with R + maintainer: Thierry Onkelinx + description: |- + Create static QR codes in R. The content of the QR code is + exactly what the user defines. We don't add a redirect URL, making it + impossible for us to track the usage of the QR code. This allows to + generate fast, free to use and privacy friendly QR codes. + date_publication: '2024-09-29' + bug_reports: https://github.com/ThierryO/qrcode/issues + url: https://thierryo.github.io/qrcode/ + url_cran: https://CRAN.R-project.org/package=qrcode + url_git: https://github.com/ThierryO/qrcode +QregBB: + version: 1.0.0 + title: Block Bootstrap Methods for Quantile Regression in Time Series + maintainer: Karl Gregory + description: 'Implements moving-blocks bootstrap and extended tapered-blocks bootstrap, + as well as smooth versions of each, for quantile regression in time series. This + package accompanies the paper: Gregory, K. B., Lahiri, S. N., & Nordman, D. J. + (2018). A smooth block bootstrap for quantile regression with time series. The + Annals of Statistics, 46(3), 1138-1166.' + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QregBB + url_git: '' +QRegVCM: + version: '1.2' + title: Quantile Regression in Varying-Coefficient Models + maintainer: '"Andriyana.Y"' + description: Quantile regression in varying-coefficient models (VCM) using one particular + nonparametric technique called P-splines. The functions can be applied on three + types of VCM; (1) Homoscedastic VCM, (2) Simple heteroscedastic VCM, and (3) General + heteroscedastic VCM. + date_publication: '2018-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QRegVCM + url_git: '' +qrencoder: + version: 0.1.0 + title: Quick Response Code (QR Code) / Matrix Barcode Creator + maintainer: Bob Rudis + description: |- + Quick Response codes (QR codes) are a type of matrix bar code and can be + used to authenticate transactions, provide access to multi-factor authentication + services and enable general data transfer in an image. QR codes use four standardized + encoding modes (numeric, alphanumeric, byte/binary, and kanji) to efficiently store + data. Matrix barcode generation is performed efficiently in C via the included + 'libqrencoder' library created by Kentaro Fukuchi. + date_publication: '2016-09-16' + bug_reports: https://github.com/hrbrmstr/qrencoder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qrencoder + url_git: http://github.com/hrbrmstr/qrencoder +qreport: + version: 1.0-1 + title: Statistical Reporting with 'Quarto' + maintainer: Frank Harrell + description: |- + Provides statistical components, tables, and graphs + that are useful in 'Quarto' and 'RMarkdown' reports and that produce 'Quarto' + elements for special formatting such as tabs and marginal notes and graphs. + Some of the functions produce entire report sections with tabs, e.g., + the missing data report created by missChk(). Functions for inserting + variables and tables inside 'graphviz' and 'mermaid' diagrams are included, + and so are special clinical trial graphics for adverse event reporting. + date_publication: '2024-05-26' + bug_reports: '' + url: https://hbiostat.org/R/qreport/ + url_cran: https://CRAN.R-project.org/package=qreport + url_git: '' +QRIpkg: + version: 0.2.2 + title: Quantile Regression Index Score + maintainer: Si Gao + description: The QRI_func() function performs quantile regression analysis using + age and sex as predictors to calculate the Quantile Regression Index (QRI) score + for each individual’s regional brain imaging metrics and then averages across + the regional scores to generate an average tissue specific score for each subject. + The QRI_plot() is used to plot QRI and generate the normative curves for individual + measurements. + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QRIpkg + url_git: '' +qris: + version: 1.1.1 + title: |- + Quantile Regression Model for Residual Lifetime Using an Induced + Smoothing Approach + maintainer: Kyu Hyun Kim + description: 'A collection of functions is provided by this package to fit quantiles + regression models for censored residual lifetimes. It provides various options + for regression parameters estimation: the induced smoothing approach (smooth), + and L1-minimization (non-smooth). It also implements the estimation methods for + standard errors of the regression parameters estimates based on an efficient partial + multiplier bootstrap method and robust sandwich estimator. Furthermore, a simultaneous + procedure of estimating regression parameters and their standard errors via an + iterative updating procedure is implemented (iterative). For more details, see + Kim, K. H., Caplan, D. J., & Kang, S. (2022), "Smoothed quantile regression for + censored residual life", Computational Statistics, 1-22 .' + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qris + url_git: https://github.com/Kyuhyun07/qris +QRISK3: + version: 0.6.0 + title: 10-Year Cardiovascular Disease Risk Calculator (QRISK3 2017) + maintainer: Yan Li + description: This function aims to calculate risk of developing cardiovascular disease + of individual patients in next 10 years. This unofficial package was based on + published open-sourced free risk prediction algorithm QRISK3-2017 . + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QRISK3 + url_git: '' +qrjoint: + version: 2.0-9 + title: Joint Estimation in Linear Quantile Regression + maintainer: Surya Tokdar + description: Joint estimation of quantile specific intercept and slope parameters + in a linear regression setting. + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrjoint + url_git: '' +qrlabelr: + version: 0.2.0 + title: Generate Machine- And Human-Readable Plot Labels for Experiments + maintainer: Alexander Wireko Kena + description: |- + A no-frills open-source solution for designing plot labels affixed with QR + codes. It features 'EasyQrlabelr', a 'BrAPI-compliant' 'shiny' app that + simplifies the process of plot label design for non-R users. It builds on the + methods described by Wu 'et al.' (2020) . + date_publication: '2023-12-20' + bug_reports: https://github.com/awkena/qrlabelr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qrlabelr + url_git: '' +qrLMM: + version: '2.3' + title: Quantile Regression for Linear Mixed-Effects Models + maintainer: Christian E. Galarza + description: |- + Quantile regression (QR) for Linear + Mixed-Effects Models via the asymmetric Laplace distribution (ALD). + It uses the Stochastic Approximation of the EM (SAEM) algorithm for + deriving exact maximum likelihood estimates and full inference results + for the fixed-effects and variance components. + It also provides graphical summaries for assessing the algorithm + convergence and fitting results. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrLMM + url_git: '' +QRM: + version: 0.4-31 + title: |- + Provides R-Language Code to Examine Quantitative Risk Management + Concepts + maintainer: Bernhard Pfaff + description: |- + Provides functions/methods to accompany the book + Quantitative Risk Management: Concepts, Techniques and Tools by + Alexander J. McNeil, Ruediger Frey, and Paul Embrechts. + date_publication: '2020-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QRM + url_git: '' +qrmdata: + version: 2024-03-04-2 + title: Data Sets for Quantitative Risk Management Practice + maintainer: Marius Hofert + description: |- + Various data sets (stocks, stock indices, constituent data, FX, + zero-coupon bond yield curves, volatility, commodities) for Quantitative + Risk Management practice. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrmdata + url_git: '' +qrmix: + version: 0.9.0 + title: Quantile Regression Mixture Models + maintainer: Maria de los Angeles Resa + description: Implements the robust algorithm for fitting finite mixture models based + on quantile regression proposed by Emir et al., 2017 (unpublished). + date_publication: '2017-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrmix + url_git: '' +qrmtools: + version: 0.0-17 + title: Tools for Quantitative Risk Management + maintainer: Marius Hofert + description: |- + Functions and data sets for reproducing selected results from + the book "Quantitative Risk Management: Concepts, Techniques and Tools". + Furthermore, new developments and auxiliary functions for Quantitative + Risk Management practice. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrmtools + url_git: '' +qrng: + version: 0.0-10 + title: (Randomized) Quasi-Random Number Generators + maintainer: Marius Hofert + description: |- + Functionality for generating (randomized) quasi-random numbers in + high dimensions. + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrng + url_git: '' +qrNLMM: + version: '3.4' + title: Quantile Regression for Nonlinear Mixed-Effects Models + maintainer: Christian E. Galarza + description: |- + Quantile regression (QR) for Nonlinear + Mixed-Effects Models via the asymmetric Laplace distribution (ALD). + It uses the Stochastic Approximation of the EM (SAEM) algorithm for + deriving exact maximum likelihood estimates and full inference results + for the fixed-effects and variance components. + It also provides prediction and graphical summaries for assessing the algorithm + convergence and fitting results. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrNLMM + url_git: '' +qrnn: + version: 2.1.1 + title: Quantile Regression Neural Network + maintainer: Alex J. Cannon + description: |- + Fit quantile regression neural network models with optional + left censoring, partial monotonicity constraints, generalized additive + model constraints, and the ability to fit multiple non-crossing quantile + functions following Cannon (2011) + and Cannon (2018) . + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qrnn + url_git: '' +qs: + version: 0.27.2 + title: Quick Serialization of R Objects + maintainer: Travers Ching + description: Provides functions for quickly writing and reading any R object to + and from disk. + date_publication: '2024-10-01' + bug_reports: https://github.com/qsbase/qs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qs + url_git: https://github.com/qsbase/qs +qs2: + version: 0.1.4 + title: Efficient Serialization of R Objects + maintainer: Travers Ching + description: 'Streamlines and accelerates the process of saving and loading R objects, + improving speed and compression compared to other methods. The package provides + two compression formats: the ''qs2'' format, which uses R serialization via the + C API while optimizing compression and disk I/O, and the ''qdata'' format, featuring + custom serialization for slightly faster performance and better compression. Additionally, + the ''qs2'' format can be directly converted to the standard ''RDS'' format, ensuring + long-term compatibility with future versions of R.' + date_publication: '2024-12-12' + bug_reports: https://github.com/qsbase/qs2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qs2 + url_git: https://github.com/qsbase/qs2 +QSARdata: + version: '1.3' + title: Quantitative Structure Activity Relationship (QSAR) Data Sets + maintainer: Max Kuhn + description: Molecular descriptors and outcomes for several public domain data sets + date_publication: '2013-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QSARdata + url_git: http://qsardata.r-forge.r-project.org/ +qsimulatR: + version: 1.1.1 + title: A Quantum Computer Simulator + maintainer: Carsten Urbach + description: |- + A quantum computer simulator framework with up to 24 qubits. It allows to + define general single qubit gates and general controlled single + qubit gates. For convenience, it currently provides the + most common gates (X, Y, Z, H, Z, S, T, Rx, Ry, Rz, CNOT, SWAP, Toffoli or + CCNOT, Fredkin or CSWAP). 'qsimulatR' also implements noise models. + 'qsimulatR' supports plotting of circuits and is able to + export circuits to 'Qiskit' , a python package + which can be used to run on IBM's hardware . + date_publication: '2023-10-16' + bug_reports: https://github.com/HISKP-LQCD/qsimulatR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qsimulatR + url_git: https://github.com/HISKP-LQCD/qsimulatR +qslice: + version: 0.3.1 + title: Implementations of Various Slice Samplers + maintainer: David B. Dahl + description: |- + Implementations of the quantile slice sampler of Heiner et al. (2024+, in preparation) as well as other popular slice samplers are provided. + Helper functions for specifying pseudo-target distributions are included, both for diagnostics and for tuning the quantile slice sampler. + Other implemented methods include the generalized elliptical slice sampler of Nishihara et al. (2014), and stepping-out slice sampler of Neal (2003), + and independence Metropolis-Hastings sampler. + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qslice + url_git: '' +qsort: + version: 0.2.3 + title: Scoring Q-Sort Data + maintainer: David N Sousa + description: |- + Computes scores from Q-sort data, using criteria sorts and + derived scales from subsets of items. + The 'qsort' package includes descriptions and scoring procedures + for four different Q-sets commonly used in developmental psychology research: + Attachment Q-set (version 3.0) (Waters, 1995, ); + California Child Q-set (Block and Block, 1969, ); + Maternal Behaviour Q-set (version 3.1) + (Pederson et al., 1999, ); + Preschool Q-set (Baumrind, 1968 revised by Wanda Bronson, ). + date_publication: '2018-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qsort + url_git: '' +qsplines: + version: 1.0.1 + title: Quaternions Splines + maintainer: Stéphane Laurent + description: |- + Provides routines to create some quaternions splines: + Barry-Goldman algorithm, De Casteljau algorithm, and Kochanek-Bartels + algorithm. The implementations are based on the Python library + 'splines'. Quaternions splines allow to construct spherical curves. + References: Barry and Goldman , + Kochanek and Bartels . + date_publication: '2023-02-27' + bug_reports: https://github.com/stla/qsplines/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qsplines + url_git: https://github.com/stla/qsplines +qspray: + version: 3.1.0 + title: Multivariate Polynomials with Rational Coefficients + maintainer: Stéphane Laurent + description: |- + Symbolic calculation and evaluation of multivariate + polynomials with rational coefficients. This package is strongly + inspired by the 'spray' package. It provides a function to + compute Gröbner bases (reference ). It + also includes some features for symmetric polynomials, such as the Hall + inner product. + The header file of the C++ code can be used by other packages. It + provides the templated class 'Qspray' that can be used to represent and + to deal with multivariate polynomials with another type of coefficients. + date_publication: '2024-07-27' + bug_reports: https://github.com/stla/qspray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qspray + url_git: https://github.com/stla/qspray +qst: + version: 0.1.2 + title: Store Tables in SQL Database + maintainer: Magnus Thor Torfason + description: |- + Provides functions for quickly writing (and + reading back) a data.frame to file in 'SQLite' format. The name + stands for *Store Tables using 'SQLite'*, or alternatively for *Quick + Store Tables* (either way, it could be pronounced as *Quest*). + For data.frames containing the supported data + types it is intended to work as a drop-in replacement for the + 'write_*()' and 'read_*()' functions provided by similar packages. + date_publication: '2020-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qst + url_git: '' +qsub: + version: 1.1.3 + title: Running Commands Remotely on 'Gridengine' Clusters + maintainer: Robrecht Cannoodt + description: |- + Run lapply() calls in parallel by submitting them to + 'gridengine' clusters using the 'qsub' command. + date_publication: '2021-09-23' + bug_reports: https://github.com/rcannood/qsub/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qsub + url_git: https://github.com/rcannood/qsub +qte: + version: 1.3.1 + title: Quantile Treatment Effects + maintainer: Brantly Callaway + description: Provides several methods for computing the Quantile Treatment Effect + (QTE) and Quantile Treatment Effect on the Treated (QTT). The main cases covered + are (i) Treatment is randomly assigned, (ii) Treatment is as good as randomly + assigned after conditioning on some covariates (also called conditional independence + or selection on observables) using the methods developed in Firpo (2007) , + (iii) Identification is based on a Difference in Differences assumption (several + varieties are available in the package e.g. Athey and Imbens (2006) + Callaway and Li (2019) , Callaway, Li, and Oka (2018) ). + date_publication: '2022-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qte + url_git: '' +QTE.RD: + version: 1.1.0 + title: |- + Quantile Treatment Effects under the Regression Discontinuity + Design + maintainer: Jungmo Yoon + description: Provides comprehensive methods for testing, estimating, and conducting + uniform inference on quantile treatment effects (QTEs) in sharp regression discontinuity + (RD) designs, incorporating covariates and implementing robust bias correction + methods of Qu, Yoon, Perron (2024) . + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QTE.RD + url_git: '' +qtkit: + version: 1.1.1 + title: Quantitative Text Kit + maintainer: Jerid Francom + description: |- + Support package for the textbook "An Introduction to + Quantitative Text Analysis for Linguists: Reproducible Research Using + R" (Francom, 2024) . Includes functions to + acquire, clean, and analyze text data as well as functions to document + and share the results of text analysis. The package is designed to be + used in conjunction with the book, but can also be used as a standalone + package for text analysis. + date_publication: '2025-01-14' + bug_reports: https://github.com/qtalr/qtkit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qtkit + url_git: '' +qtl: + version: '1.70' + title: Tools for Analyzing QTL Experiments + maintainer: Karl W Broman + description: |- + Analysis of experimental crosses to identify genes + (called quantitative trait loci, QTLs) contributing to variation in + quantitative traits. + Broman et al. (2003) . + date_publication: '2024-08-22' + bug_reports: https://github.com/kbroman/qtl/issues + url: https://rqtl.org + url_cran: https://CRAN.R-project.org/package=qtl + url_git: https://github.com/kbroman/qtl +QTL.gCIMapping: + version: '3.4' + title: QTL Genome-Wide Composite Interval Mapping + maintainer: Yuanming Zhang + description: Conduct multiple quantitative trait loci (QTL) and QTL-by-environment + interaction (QEI) mapping via ordinary or compressed variance component mixed + models with random- or fixed QTL/QEI effects. First, each position on the genome + is detected in order to obtain a negative logarithm P-value curve against genome + position. Then, all the peaks on each effect (additive or dominant) curve or on + each locus curve are viewed as potential main-effect QTLs and QEIs, all their + effects are included in a multi-locus model, their effects are estimated by both + least angle regression and empirical Bayes (or adaptive lasso) in backcross and + F2 populations, and true QTLs and QEIs are identified by likelihood radio test. + See Zhou et al. (2022) and Wen et al. (2018) . + date_publication: '2022-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QTL.gCIMapping + url_git: '' +QTL.gCIMapping.GUI: + version: 2.1.1 + title: |- + QTL Genome-Wide Composite Interval Mapping with Graphical User + Interface + maintainer: Yuanming Zhang + description: Conduct multiple quantitative trait loci (QTL) mapping under the framework + of random-QTL-effect linear mixed model. First, each position on the genome is + detected in order to obtain a negative logarithm P-value curve against genome + position. Then, all the peaks on each effect (additive or dominant) curve are + viewed as potential QTL, all the effects of the potential QTL are included in + a multi-QTL model, their effects are estimated by empirical Bayes in doubled haploid + population or by adaptive lasso in F2 population, and true QTL are identified + by likelihood radio test. See Wen et al. (2018) . + date_publication: '2020-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QTL.gCIMapping.GUI + url_git: '' +qtl2: + version: '0.36' + title: Quantitative Trait Locus Mapping in Experimental Crosses + maintainer: Karl W Broman + description: |- + Provides a set of tools to perform quantitative + trait locus (QTL) analysis in experimental crosses. It is a + reimplementation of the 'R/qtl' package to better handle + high-dimensional data and complex cross designs. + Broman et al. (2019) . + date_publication: '2024-05-13' + bug_reports: https://github.com/rqtl/qtl2/issues + url: https://kbroman.org/qtl2/ + url_cran: https://CRAN.R-project.org/package=qtl2 + url_git: https://github.com/rqtl/qtl2 +qtl2convert: + version: '0.30' + title: Convert Data among QTL Mapping Packages + maintainer: Karl W Broman + description: Functions to convert data structures among the 'qtl2', 'qtl', and 'DOQTL' + packages for mapping quantitative trait loci (QTL). + date_publication: '2024-04-04' + bug_reports: https://github.com/rqtl/qtl2convert/issues + url: https://kbroman.org/qtl2/ + url_cran: https://CRAN.R-project.org/package=qtl2convert + url_git: https://github.com/rqtl/qtl2convert +qtl2fst: + version: '0.30' + title: Database Storage of Genotype Probabilities for QTL Mapping + maintainer: Karl W Broman + description: Uses the 'fst' package to store genotype probabilities on disk for + the 'qtl2' package. These genotype probabilities are a central data object for + mapping quantitative trait loci (QTL), but they can be quite large. The facilities + in this package enable the genotype probabilities to be stored on disk, leading + to reduced memory usage with only a modest increase in computation time. + date_publication: '2024-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qtl2fst + url_git: https://github.com/rqtl/qtl2fst +qtl2ggplot: + version: 1.2.4 + title: Data Visualization for QTL Experiments + maintainer: Brian S Yandell + description: |- + Functions to plot QTL (quantitative trait loci) analysis + results and related diagnostics. + Part of 'qtl2', an upgrade of the 'qtl' + package to better handle high-dimensional data and complex cross + designs. + date_publication: '2024-03-15' + bug_reports: https://github.com/byandell/qtl2ggplot/issues + url: https://kbroman.org/qtl2/ + url_cran: https://CRAN.R-project.org/package=qtl2ggplot + url_git: https://github.com/byandell/qtl2ggplot +qtl2pattern: + version: 1.2.1 + title: Pattern Support for 'qtl2' Package + maintainer: Brian S Yandell + description: |- + Routines in 'qtl2' to study allele patterns in quantitative trait loci (QTL) + mapping over a chromosome. + Useful in crosses with more than two alleles to identify how sets of alleles, + genetically different strands at the same locus, have different response levels. + Plots show profiles over a chromosome. + Can handle multiple traits together. + See . + date_publication: '2023-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qtl2pattern + url_git: https://github.com/byandell/qtl2pattern +qtl2pleio: + version: 1.4.3 + title: Testing Pleiotropy in Multiparental Populations + maintainer: Frederick J Boehm + description: |- + We implement an + adaptation of Jiang & Zeng's (1995) likelihood ratio test for testing + the null hypothesis of pleiotropy against the alternative hypothesis, + two separate quantitative trait loci. The test differs from that in Jiang & Zeng (1995) + and that in Tian et al. (2016) in + that our test accommodates multiparental populations. + date_publication: '2020-12-02' + bug_reports: https://github.com/fboehm/qtl2pleio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qtl2pleio + url_git: https://github.com/fboehm/qtl2pleio +qtlbook: + version: 0.18-8 + title: Datasets for the R/qtl Book + maintainer: Karl W Broman + description: |- + Datasets for the book, A Guide to QTL Mapping with R/qtl. + Broman and Sen (2009) . + date_publication: '2019-06-28' + bug_reports: https://github.com/kbroman/qtlbook/issues + url: http://rqtl.org/book + url_cran: https://CRAN.R-project.org/package=qtlbook + url_git: https://github.com/kbroman/qtlbook +qtlc: + version: '1.0' + title: Densitometric Analysis of Thin-Layer Chromatography Plates + maintainer: Ivan D. Pavicevic + description: Densitometric evaluation of the photo-archived quantitative thin-layer + chromatography (TLC) plates. + date_publication: '2016-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qtlc + url_git: '' +qtlcharts: + version: '0.16' + title: Interactive Graphics for QTL Experiments + maintainer: Karl W Broman + description: |- + Web-based interactive charts (using D3.js) for the analysis of + experimental crosses to identify genetic loci (quantitative trait + loci, QTL) contributing to variation in quantitative traits. + Broman (2015) . + date_publication: '2022-01-07' + bug_reports: https://github.com/kbroman/qtlcharts/issues + url: https://kbroman.org/qtlcharts/ + url_cran: https://CRAN.R-project.org/package=qtlcharts + url_git: https://github.com/kbroman/qtlcharts +qtlDesign: + version: '0.953' + title: Design of QTL (Quantitative Trait Locus) Experiments + maintainer: Saunak Sen + description: |- + Design of QTL (quantitative trait locus) experiments + involves choosing which strains to cross, the type of cross, + genotyping strategies, phenotyping strategies, and the number of + progeny to raise and phenotype. This package provides tools to help + make such choices. + Sen and others (2007) . + date_publication: '2024-04-15' + bug_reports: '' + url: http://www.senresearch.org + url_cran: https://CRAN.R-project.org/package=qtlDesign + url_git: '' +QTLEMM: + version: 3.0.0 + title: QTL Mapping and Hotspots Detection + maintainer: Ping-Yuan Chung + description: |- + For QTL mapping, this package comprises several functions designed to execute diverse + tasks, such as simulating or analyzing data, calculating significance thresholds, and + visualizing QTL mapping results. The single-QTL or multiple-QTL method, which enables + the fitting and comparison of various statistical models, is employed to analyze the + data for estimating QTL parameters. The models encompass linear regression, permutation + tests, normal mixture models, and truncated normal mixture models. The Gaussian stochastic + process is utilized to compute significance thresholds for QTL detection on a genetic + linkage map within experimental populations. Two types of data, complete genotyping, and + selective genotyping data from various experimental populations, including backcross, F2, + recombinant inbred (RI) populations, and advanced intercrossed (AI) populations, are + considered in the QTL mapping analysis. For QTL hotspot detection, statistical methods can + be developed based on either utilizing individual-level data or summarized data. We have + proposed a statistical framework capable of handling both individual-level data and + summarized QTL data for QTL hotspot detection. Our statistical framework can overcome the + underestimation of thresholds resulting from ignoring the correlation structure among + traits. Additionally, it can identify different types of hotspots with minimal computational + cost during the detection process. Here, we endeavor to furnish the R codes for our QTL + mapping and hotspot detection methods, intended for general use in genes, genomics, and + genetics studies. The QTL mapping methods for the complete and selective genotyping designs + are based on the multiple interval mapping (MIM) model proposed by Kao, C.-H. , Z.-B. Zeng + and R. D. Teasdale (1999) and H.-I Lee, H.-A. Ho and + C.-H. Kao (2014) , respectively. The QTL hotspot detection + analysis is based on the method by Wu, P.-Y., M.-.H. Yang, and C.-H. Kao (2021) + . + date_publication: '2025-02-21' + bug_reports: https://github.com/py-chung/QTLEMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QTLEMM + url_git: https://github.com/py-chung/QTLEMM +qtlhot: + version: 1.0.4 + title: Inference for QTL Hotspots + maintainer: Brian S. Yandell + description: |- + Functions to infer co-mapping trait hotspots and causal models. + Chaibub Neto E, Keller MP, Broman AF, Attie AD, Jansen RC, Broman KW, Yandell BS (2012) + Quantile-based permutation thresholds for QTL hotspots. Genetics 191 : 1355-1365. + . + Chaibub Neto E, Broman AT, Keller MP, Attie AD, Zhang B, Zhu J, Yandell BS (2013) + Modeling causality for pairs of phenotypes in system genetics. Genetics 193 : 1003-1013. + . + date_publication: '2018-04-05' + bug_reports: '' + url: http://www.stat.wisc.edu/~yandell/statgen + url_cran: https://CRAN.R-project.org/package=qtlhot + url_git: '' +qtlnet: + version: 1.5.4 + title: Causal Inference of QTL Networks + maintainer: Brian S. Yandell + description: |- + Functions to Simultaneously Infer Causal Graphs and Genetic Architecture. + Includes acyclic and cyclic graphs for data from an experimental cross with a modest number (<10) of phenotypes driven by + a few genetic loci (QTL). + Chaibub Neto E, Keller MP, Attie AD, Yandell BS (2010) + Causal Graphical Models in Systems Genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes. + Annals of Applied Statistics 4: 320-339. + . + date_publication: '2020-04-13' + bug_reports: '' + url: http://www.stat.wisc.edu/~yandell/sysgen + url_cran: https://CRAN.R-project.org/package=qtlnet + url_git: '' +qtlpoly: + version: 0.2.4 + title: Random-Effect Multiple QTL Mapping in Autopolyploids + maintainer: Gabriel de Siqueira Gesteira + description: Performs random-effect multiple interval mapping (REMIM) in full-sib + families of autopolyploid species based on restricted maximum likelihood (REML) + estimation and score statistics, as described in Pereira et al. (2020) . + date_publication: '2024-03-25' + bug_reports: https://github.com/gabrielgesteira/QTLpoly/issues + url: https://gabrielgesteira.github.io/QTLpoly/ + url_cran: https://CRAN.R-project.org/package=qtlpoly + url_git: '' +QTLRel: + version: '1.14' + title: |- + Tools for Mapping of Quantitative Traits of Genetically Related + Individuals and Calculating Identity Coefficients from + Pedigrees + maintainer: Riyan Cheng + description: This software provides tools for quantitative trait mapping in populations + such as advanced intercross lines where relatedness among individuals should not + be ignored. It can estimate background genetic variance components, impute missing + genotypes, simulate genotypes, perform a genome scan for putative quantitative + trait loci (QTL), and plot mapping results. It also has functions to calculate + identity coefficients from pedigrees, especially suitable for pedigrees that consist + of a large number of generations, or estimate identity coefficients from genotypic + data in certain circumstances. + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QTLRel + url_git: '' +QTOCen: + version: 0.1.1 + title: Quantile-Optimal Treatment Regimes with Censored Data + maintainer: Yu Zhou + description: |- + Provides methods for estimation of mean- and quantile-optimal treatment regimes from censored data. + Specifically, we have developed distinct functions for three types of right censoring for static treatment using quantile criterion: (1) independent/random censoring, (2) treatment-dependent random censoring, and (3) covariates-dependent random censoring. It also includes a function to estimate quantile-optimal dynamic treatment regimes for independent censored data. Finally, this package also includes a simulation data generative model of a dynamic treatment experiment proposed in literature. + date_publication: '2019-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QTOCen + url_git: '' +Qtools: + version: 1.5.9 + title: Utilities for Quantiles + maintainer: Marco Geraci + description: |- + Functions for unconditional and conditional quantiles. These + include methods for transformation-based quantile regression, + quantile-based measures of location, scale and shape, methods for quantiles + of discrete variables, quantile-based multiple imputation, restricted + quantile regression, directional quantile classification, and quantile + ratio regression. + A vignette is given in Geraci (2016, The R Journal) and included in the package. + date_publication: '2023-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Qtools + url_git: '' +qtwAcademic: + version: 2022.12.13 + title: '''Quarto'' Website Templates for Academics' + maintainer: Chi Zhang + description: |- + Provides three 'Quarto' website templates as an R project, which are commonly used by academics. + Templates for personal websites and course/workshop websites are included, as well as a template with minimal content for customization. + date_publication: '2022-12-22' + bug_reports: https://github.com/andreaczhang/qtwAcademic/issues + url: https://andreaczhang.github.io/qtwAcademic/ + url_cran: https://CRAN.R-project.org/package=qtwAcademic + url_git: https://github.com/andreaczhang/qtwAcademic +quadcleanR: + version: 1.1.0 + title: Cleanup and Visualization of Quadrat Data + maintainer: Dominique Maucieri + description: |- + A tool that can be customized to aid in the clean up of ecological data + collected using quadrats and can crop quadrats to ensure comparability between + quadrats collected under different methodologies. + date_publication: '2022-10-17' + bug_reports: https://github.com/DominiqueMaucieri/quadcleanR/issues + url: https://dominiquemaucieri.com/quadcleanR/ + url_cran: https://CRAN.R-project.org/package=quadcleanR + url_git: https://github.com/DominiqueMaucieri/quadcleanR +quadform: + version: 0.0-2 + title: Efficient Evaluation of Quadratic Forms + maintainer: Robin K. S. Hankin + description: |- + A range of quadratic forms are evaluated, using efficient methods. + Unnecessary transposes are not performed. Complex values are handled + consistently. + date_publication: '2024-05-14' + bug_reports: https://github.com/RobinHankin/quadform/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quadform + url_git: https://github.com/RobinHankin/quadform +quadmatrix: + version: 0.1.0 + title: Solving Quadratic Matrix Equations + maintainer: Siva Rajesh Kasa + description: Given inputs A,B and C, this package solves the matrix equation A*X^2 + - B*X - C = 0. + date_publication: '2018-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quadmatrix + url_git: '' +quadmesh: + version: 0.5.5 + title: Quadrangle Mesh + maintainer: Michael D. Sumner + description: |- + Create surface forms from matrix or 'raster' data for flexible plotting and + conversion to other mesh types. The functions 'quadmesh' or 'triangmesh' + produce a continuous surface as a 'mesh3d' object as used by the 'rgl' + package. This is used for plotting raster data in 3D (optionally with + texture), and allows the application of a map projection without data loss and + many processing applications that are restricted by inflexible regular grid rasters. + There are discrete forms of these continuous surfaces available with + 'dquadmesh' and 'dtriangmesh' functions. + date_publication: '2022-08-31' + bug_reports: https://github.com/hypertidy/quadmesh/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quadmesh + url_git: https://github.com/hypertidy/quadmesh +quadprog: + version: 1.5-8 + title: Functions to Solve Quadratic Programming Problems + maintainer: Berwin A. Turlach + description: |- + This package contains routines and documentation for + solving quadratic programming problems. + date_publication: '2019-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quadprog + url_git: '' +quadprogXT: + version: 0.0.5 + title: Quadratic Programming with Absolute Value Constraints + maintainer: Bob Harlow + description: |- + Extends the quadprog package to solve quadratic programs with + absolute value constraints and absolute values in the objective function. + date_publication: '2020-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quadprogXT + url_git: '' +quadraticSD: + version: 0.1.0 + title: Visualizing the SD using a Quadratic Curve + maintainer: Siddhanta Phuyal + description: |- + Given a dataset, the user is invited to utilize the Empirical Cumulative Distribution Function (ECDF) + to guess interactively the mean and the mean deviation. Thereafter, + using the quadratic curve the user can guess the Root Mean Squared Deviation (RMSD) + and visualize the standard deviation (SD). + For details, see Sarkar and Rashid (2019), + Have You Seen the Standard Deviaton?, Nepalese Journal of Statistics, Vol. 3, 1-10. + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quadraticSD + url_git: '' +QuadratiK: + version: 1.1.3 + title: |- + Collection of Methods Constructed using Kernel-Based Quadratic + Distances + maintainer: Giovanni Saraceno + description: |- + It includes test for multivariate normality, test for uniformity on the d-dimensional + Sphere, non-parametric two- and k-sample tests, random generation of points from the Poisson + kernel-based density and clustering algorithm for spherical data. For more information see + Saraceno G., Markatou M., Mukhopadhyay R. and Golzy M. (2024) + + Markatou, M. and Saraceno, G. (2024) , + Ding, Y., Markatou, M. and Saraceno, G. (2023) , + and Golzy, M. and Markatou, M. (2020) . + date_publication: '2025-02-04' + bug_reports: https://github.com/ropensci/QuadratiK/issues + url: https://docs.ropensci.org/QuadratiK/ + url_cran: https://CRAN.R-project.org/package=QuadratiK + url_git: https://github.com/ropensci/QuadratiK/ +QuadRoot: + version: 0.2.1 + title: Quadratic Root for any Quadratic Equation + maintainer: Pankaj Das + description: It will assist the user to find simple quadratic roots from any quadratic + equation. + date_publication: '2023-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuadRoot + url_git: '' +quadrupen: + version: 0.2-12 + title: Sparsity by Worst-Case Quadratic Penalties + maintainer: Julien Chiquet + description: |- + Fits classical sparse regression models with + efficient active set algorithms by solving quadratic problems as described by + Grandvalet, Chiquet and Ambroise (2017) . Also provides a few + methods for model selection purpose (cross-validation, stability selection). + date_publication: '2024-06-25' + bug_reports: https://github.com/jchiquet/quadrupenCRAN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quadrupen + url_git: https://github.com/jchiquet/quadrupenCRAN +quadtree: + version: 0.1.14 + title: Region Quadtrees for Spatial Data + maintainer: Derek Friend + description: |- + Provides functionality for working with raster-like quadtrees + (also called “region quadtrees”), which allow for variable-sized + cells. The package allows for flexibility in the quadtree creation + process. Several functions defining how to split and aggregate cells + are provided, and custom functions can be written for both of these + processes. In addition, quadtrees can be created using other quadtrees + as “templates”, so that the new quadtree's structure is identical to + the template quadtree. The package also includes functionality for + modifying quadtrees, querying values, saving quadtrees to a file, and + calculating least-cost paths using the quadtree as a resistance + surface. + date_publication: '2023-08-29' + bug_reports: https://github.com/dfriend21/quadtree/issues/ + url: https://dfriend21.github.io/quadtree/ + url_cran: https://CRAN.R-project.org/package=quadtree + url_git: https://github.com/dfriend21/quadtree/ +quadVAR: + version: 0.1.2 + title: Quadratic Vector Autoregression + maintainer: Jingmeng Cui + description: |- + Estimate quadratic vector autoregression models with the + strong hierarchy using the Regularization Algorithm under Marginality + Principle (RAMP) by Hao et al. (2018) + , compare the performance with + linear models, and construct networks with partial derivatives. + date_publication: '2025-02-11' + bug_reports: https://github.com/Sciurus365/quadVAR/issues + url: https://sciurus365.github.io/quadVAR/ + url_cran: https://CRAN.R-project.org/package=quadVAR + url_git: https://github.com/Sciurus365/quadVAR +qualitycontrol: + version: 0.1.0 + title: Unified Framework for Data Quality Control + maintainer: Luis Garcez + description: |- + An easy framework to set a quality control workflow on a dataset. + Includes a various range of functions that allow to establish an adaptable + data quality control. + date_publication: '2022-11-28' + bug_reports: https://github.com/luisgarcez11/qualitycontrol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qualitycontrol + url_git: https://github.com/luisgarcez11/qualitycontrol +qualmap: + version: 0.2.2 + title: |- + Opinionated Approach for Digitizing Semi-Structured Qualitative + GIS Data + maintainer: Christopher Prener + description: |- + Provides a set of functions for taking qualitative GIS data, hand drawn on a map, and + converting it to a simple features object. These tools are focused on data that are drawn on a map + that contains some type of polygon features. For each area identified on the map, the id numbers + of these polygons can be entered as vectors and transformed using qualmap. + date_publication: '2024-01-09' + bug_reports: https://github.com/chris-prener/qualmap/issues + url: https://chris-prener.github.io/qualmap/ + url_cran: https://CRAN.R-project.org/package=qualmap + url_git: '' +qualpalr: + version: 0.4.4 + title: Automatic Generation of Qualitative Color Palettes + maintainer: Johan Larsson + description: |- + Automatic generation of maximally distinct qualitative color palettes, + optionally tailored to color deficiency. A list of colors or a subspace + of a color space is used as input and then projected to the DIN99d color space, + where colors that are maximally distinct are chosen algorithmically. + date_publication: '2023-09-13' + bug_reports: https://github.com/jolars/qualpalr/issues + url: https://jolars.github.io/qualpalr/ + url_cran: https://CRAN.R-project.org/package=qualpalr + url_git: '' +qualtRics: + version: 3.2.1 + title: Download 'Qualtrics' Survey Data + maintainer: Julia Silge + description: |- + Provides functions to access survey results directly into R + using the 'Qualtrics' API. 'Qualtrics' + is an online survey and data + collection software platform. See for + more information about the 'Qualtrics' API. This package is + community-maintained and is not officially supported by 'Qualtrics'. + date_publication: '2024-08-16' + bug_reports: https://github.com/ropensci/qualtRics/issues + url: https://docs.ropensci.org/qualtRics/ + url_cran: https://CRAN.R-project.org/package=qualtRics + url_git: https://github.com/ropensci/qualtRics +qualV: + version: 0.3-5 + title: Qualitative Validation Methods + maintainer: Thomas Petzoldt + description: |- + Qualitative methods for the validation of dynamic models. + It contains (i) an orthogonal set of deviance measures for absolute, + relative and ordinal scale and (ii) approaches accounting for time + shifts. The first approach transforms time to take time delays and speed + differences into account. The second divides the time series into + interval units according to their main features and finds the longest + common subsequence (LCS) using a dynamic programming algorithm. + date_publication: '2023-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=qualV + url_git: http://qualV.R-Forge.R-Project.org/ +qualvar: + version: 0.2.0 + title: |- + Implements Indices of Qualitative Variation Proposed by Wilcox + (1973) + maintainer: Joel Gombin + description: |- + Implements indices of qualitative variation proposed by Wilcox + (1973). + date_publication: '2018-01-03' + bug_reports: https://www.github.com/joelgombin/qualvar/issues + url: http://joelgombin.github.io/qualvar/ + url_cran: https://CRAN.R-project.org/package=qualvar + url_git: '' +QUALYPSO: + version: '2.3' + title: |- + Partitioning Uncertainty Components of an Incomplete Ensemble of + Climate Projections + maintainer: Guillaume Evin + description: |- + These functions use data augmentation and Bayesian techniques for the assessment of single-member and incomplete ensembles of climate projections. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. + - Evin, G., B. Hingray, J. Blanchet, N. Eckert, S. Morin, and D. Verfaillie. (2019) . + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QUALYPSO + url_git: '' +Quandl: + version: 2.11.0 + title: API Wrapper for Quandl.com + maintainer: Dave Dotson + description: Functions for interacting directly with the Quandl API to offer data + in a number of formats usable in R, downloading a zip with all data from a Quandl + database, and the ability to search. This R package uses the Quandl API. For more + information go to . For more help on the package itself + go to . + date_publication: '2021-08-11' + bug_reports: https://github.com/quandl/quandl-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Quandl + url_git: https://github.com/quandl/quandl-r +QuantBondCurves: + version: 0.3.1 + title: Calculates Bond Values and Interest Rate Curves for Finance + maintainer: Camilo Díaz + description: |- + Values different types of assets and calibrates discount curves + for quantitative financial analysis. It covers fixed coupon assets, + floating note assets, interest and cross currency swaps with different + payment frequencies. Enables the calibration of spot, instantaneous forward + and basis curves, making it a powerful tool for accurate and flexible bond + valuation and curve generation. The valuation and calibration techniques + presented here are consistent with industry standards and incorporates + author's own calculations. Tuckman, B., Serrat, A. (2022, ISBN: 978-1-119-83555-4). + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuantBondCurves + url_git: '' +quantCurves: + version: 1.0.0 + title: Estimate Quantiles Curves + maintainer: Sandie Ferrigno + description: Non-parametric methods as local normal regression, polynomial local + regression and penalized cubic B-splines regression are used to estimate quantiles + curves. See Fan and Gijbels (1996) and Perperoglou + et al.(2019) . + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantCurves + url_git: '' +quantdates: + version: 2.0.4 + title: Manipulate Dates for Finance + maintainer: Juan Pablo Bermudez + description: Functions to manipulate dates and count days for quantitative finance + analysis. The 'quantdates' package considers leap, holidays and business days + for relevant calendars in a financial context to simplify quantitative finance + calculations, consistent with International Swaps and Derivatives Association + (ISDA) (2006) regulations. + date_publication: '2024-07-04' + bug_reports: https://github.com/quantilma/quantdates/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quantdates + url_git: https://github.com/quantilma/quantdates +quantdr: + version: 1.2.2 + title: Dimension Reduction Techniques for Conditional Quantiles + maintainer: Eliana Christou + description: |- + An implementation of dimension reduction techniques + for conditional quantiles. Nonparametric estimation of + conditional quantiles is also available. + date_publication: '2022-05-09' + bug_reports: https://github.com/elianachristou/quantdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quantdr + url_git: https://github.com/elianachristou/quantdr +quanteda: + version: 4.2.0 + title: Quantitative Analysis of Textual Data + maintainer: Kenneth Benoit + description: |- + A fast, flexible, and comprehensive framework for + quantitative text analysis in R. Provides functionality for corpus management, + creating and manipulating tokens and n-grams, exploring keywords in context, + forming and manipulating sparse matrices + of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and + distances, applying content dictionaries, applying supervised and unsupervised machine learning, + visually representing text and text analyses, and more. + date_publication: '2025-01-08' + bug_reports: https://github.com/quanteda/quanteda/issues + url: https://quanteda.io + url_cran: https://CRAN.R-project.org/package=quanteda + url_git: '' +quanteda.textmodels: + version: 0.9.10 + title: Scaling Models and Classifiers for Textual Data + maintainer: Kenneth Benoit + description: |- + Scaling models and classifiers for sparse matrix objects representing + textual data in the form of a document-feature matrix. Includes original + implementations of 'Laver', 'Benoit', and Garry's (2003) , + 'Wordscores' model, the Perry and 'Benoit' (2017) class affinity scaling model, + and the 'Slapin' and 'Proksch' (2008) 'wordfish' + model, as well as methods for correspondence analysis, latent semantic analysis, + and fast Naive Bayes and linear 'SVMs' specially designed for sparse textual data. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quanteda.textmodels + url_git: https://github.com/quanteda/quanteda.textmodels +quanteda.textplots: + version: '0.95' + title: Plots for the Quantitative Analysis of Textual Data + maintainer: Kenneth Benoit + description: |- + Plotting functions for visualising textual data. Extends 'quanteda' and + related packages with plot methods designed specifically for text data, textual statistics, + and models fit to textual data. Plot types include word clouds, lexical dispersion plots, + scaling plots, network visualisations, and word 'keyness' plots. + date_publication: '2024-08-28' + bug_reports: https://github.com/quanteda/quanteda.textplots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quanteda.textplots + url_git: '' +quanteda.textstats: + version: 0.97.2 + title: Textual Statistics for the Quantitative Analysis of Textual Data + maintainer: Kenneth Benoit + description: |- + Textual statistics functions formerly in the 'quanteda' package. + Textual statistics for characterizing and comparing textual data. Includes + functions for measuring term and document frequency, the co-occurrence of + words, similarity and distance between features and documents, feature entropy, + keyword occurrence, readability, and lexical diversity. These functions + extend the 'quanteda' package and are specially designed for sparse textual data. + date_publication: '2024-09-03' + bug_reports: https://github.com/quanteda/quanteda.textstats/issues + url: https://quanteda.io + url_cran: https://CRAN.R-project.org/package=quanteda.textstats + url_git: '' +quantification: + version: 0.2.0 + title: Quantification of Qualitative Survey Data + maintainer: Joachim Zuckarelli + description: Provides different functions for quantifying qualitative survey data. + It supports the Carlson-Parkin method, the regression approach, the balance approach + and the conditional expectations method. + date_publication: '2016-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantification + url_git: '' +quantileDA: + version: '1.2' + title: Quantile Classifier + maintainer: Cinzia Viroli + description: Code for centroid, median and quantile classifiers. + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantileDA + url_git: '' +QuantileGH: + version: 0.1.7 + title: |- + Quantile Least Mahalanobis Distance Estimator for Tukey g-&-h + Mixture + maintainer: Tingting Zhan + description: |- + Functions for simulation, estimation, and model + selection of finite mixtures of Tukey g-and-h + distributions. + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuantileGH + url_git: '' +QuantileGradeR: + version: 0.1.1 + title: Quantile-Adjusted Restaurant Grading + maintainer: Zoe Ashwood + description: 'Implementation of the food safety restaurant grading system adopted + by Public Health - Seattle & King County (see Ashwood, Z.C., Elias, B., and Ho. + D.E. "Improving the Reliability of Food Safety Disclosure: A Quantile Adjusted + Restaurant Grading System for Seattle-King County" (working paper)). As reported + in the accompanying paper, this package allows jurisdictions to easily implement + refinements that address common challenges with unadjusted grading systems. First, + in contrast to unadjusted grading, where the most recent single routine inspection + is the primary determinant of a grade, grading inputs are allowed to be flexible. + For instance, it is straightforward to base the grade on average inspection scores + across multiple inspection cycles. Second, the package can identify quantile cutoffs + by inputting substantively meaningful regulatory thresholds (e.g., the proportion + of establishments receiving sufficient violation points to warrant a return visit). + Third, the quantile adjustment equalizes the proportion of establishments in a + flexible number of grading categories (e.g., A/B/C) across areas (e.g., ZIP codes, + inspector areas) to account for inspector differences. Fourth, the package implements + a refined quantile adjustment that addresses two limitations with the stats::quantile() + function when applied to inspection score datasets with large numbers of score + ties. The quantile adjustment algorithm iterates over quantiles until, over all + restaurants in all areas, grading proportions are within a tolerance of desired + global proportions. In addition the package allows a modified definition of "quantile" + from "Nearest Rank". Instead of requiring that at least p[1]% of restaurants receive + the top grade and at least (p[1]+p[2])% of restaurants receive the top or second + best grade for quantiles p, the algorithm searches for cutoffs so that as close + as possible p[1]% of restaurants receive the top grade, and as close as possible + to p[2]% of restaurants receive the second top grade.' + date_publication: '2017-02-06' + bug_reports: '' + url: http://www.kingcounty.gov/depts/health/environmental-health/food-safety/inspection-system/food-safety-rating.aspx + url_cran: https://CRAN.R-project.org/package=QuantileGradeR + url_git: '' +QuantileNPCI: + version: 0.9.0 + title: Nonparametric Confidence Intervals for Quantiles + maintainer: Li Yan + description: Based on Alan D. Hutson (1999) , "Calculating + nonparametric confidence intervals for quantiles using fractional order statistics", + Journal of Applied Statistics, 26:3, 343-353. + date_publication: '2019-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuantileNPCI + url_git: '' +quantilogram: + version: 3.1.1 + title: Cross-Quantilogram + maintainer: Tatsushi Oka + description: |- + Estimation and inference methods for the cross-quantilogram. + The cross-quantilogram is a measure of nonlinear dependence between + two variables, based on either unconditional or conditional quantile + functions. It can be considered an extension of the correlogram, + which is a correlation function over multiple lag periods that mainly + focuses on linear dependency. One can use the cross-quantilogram to + detect the presence of directional predictability from one time series + to another. This package provides a statistical inference method + based on the stationary bootstrap. For detailed theoretical and + empirical explanations, see Linton and Whang (2007) for univariate + time series analysis and Han, Linton, Oka and Whang (2016) for + multivariate time series analysis. The full references for these key + publications are as follows: (1) Linton, O., and Whang, Y. J. (2007). + The quantilogram: with an application to evaluating directional + predictability. Journal of Econometrics, 141(1), 250-282 + ; (2) Han, H., Linton, O., Oka, T., + and Whang, Y. J. (2016). The cross-quantilogram: measuring quantile + dependence and testing directional predictability between time series. + Journal of Econometrics, 193(1), 251-270 + . + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantilogram + url_git: '' +quantities: + version: 0.2.3 + title: Quantity Calculus for R Vectors + maintainer: Iñaki Ucar + description: |- + Integration of the 'units' and 'errors' packages for a complete + quantity calculus system for R vectors, matrices and arrays, with automatic + propagation, conversion, derivation and simplification of magnitudes and + uncertainties. Documentation about 'units' and 'errors' is provided in the + papers by Pebesma, Mailund & Hiebert (2016, ) and + by Ucar, Pebesma & Azcorra (2018, ), included in + those packages as vignettes; see 'citation("quantities")' for details. + date_publication: '2025-01-18' + bug_reports: https://github.com/r-quantities/quantities/issues + url: https://r-quantities.github.io/quantities/ + url_cran: https://CRAN.R-project.org/package=quantities + url_git: https://github.com/r-quantities/quantities +quantkriging: + version: 0.1.0 + title: Quantile Kriging for Stochastic Simulations with Replication + maintainer: Kevin R. Quinlan + description: A re-implementation of quantile kriging. Quantile kriging was described + by Plumlee and Tuo (2014) . With computational + savings when dealing with replication from the recent paper by Binois, Gramacy, + and Ludovski (2018) it is now possible to + apply quantile kriging to a wider class of problems. In addition to fitting the + model, other useful tools are provided such as the ability to automatically perform + leave-one-out cross validation. + date_publication: '2020-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantkriging + url_git: '' +quantmod: + version: 0.4.26 + title: Quantitative Financial Modelling Framework + maintainer: Joshua M. Ulrich + description: Specify, build, trade, and analyse quantitative financial trading strategies. + date_publication: '2024-02-14' + bug_reports: https://github.com/joshuaulrich/quantmod/issues + url: https://www.quantmod.com/ + url_cran: https://CRAN.R-project.org/package=quantmod + url_git: https://github.com/joshuaulrich/quantmod +QuantNorm: + version: 1.0.5 + title: |- + Mitigating the Adverse Impact of Batch Effects in Sample Pattern + Detection + maintainer: Teng Fei + description: Modifies the distance matrix obtained from data with batch effects, + so as to improve the performance of sample pattern detection, such as clustering, + dimension reduction, and construction of networks between subjects. The method + has been published in Bioinformatics (Fei et al, 2018, ). + Also available on 'GitHub' . + date_publication: '2019-02-01' + bug_reports: https://github.com/tengfei-emory/QuantNorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QuantNorm + url_git: '' +quantoptr: + version: 0.1.3 + title: Algorithms for Quantile- And Mean-Optimal Treatment Regimes + maintainer: Yu Zhou + description: Estimation methods for optimal treatment regimes under three different + criteria, namely marginal quantile, marginal mean, and mean absolute difference. + For the first two criteria, both one-stage and two-stage estimation method are + implemented. A doubly robust estimator for estimating the quantile-optimal treatment + regime is also included. + date_publication: '2018-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantoptr + url_git: '' +QuantPsyc: + version: '1.6' + title: Quantitative Psychology Tools + maintainer: Thomas D. Fletcher + description: |- + Contains tools useful for data screening, testing + moderation (Cohen et. al. 2003), + mediation (MacKinnon et. al. 2002) + and estimating power (Murphy & Myors 2014). + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuantPsyc + url_git: '' +quantreg: + version: '6.00' + title: Quantile Regression + maintainer: Roger Koenker + description: |- + Estimation and inference methods for models for conditional quantile functions: + Linear and nonlinear parametric and non-parametric (total variation penalized) models + for conditional quantiles of a univariate response and several methods for handling + censored survival data. Portfolio selection methods based on expected shortfall + risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press, + and Koenker, R. et al. (2017) Handbook of Quantile Regression, + CRC Press, . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantreg + url_git: '' +quantreg.nonpar: + version: '1.0' + title: Nonparametric Series Quantile Regression + maintainer: Ivan Fernandez-Val + description: Implements the nonparametric quantile regression method developed by + Belloni, Chernozhukov, and Fernandez-Val (2011) to partially linear quantile models. + Provides point estimates of the conditional quantile function and its derivatives + based on series approximations to the nonparametric part of the model. Provides + pointwise and uniform confidence intervals using analytic and resampling methods. + date_publication: '2016-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantreg.nonpar + url_git: '' +quantregForest: + version: 1.3-7.1 + title: Quantile Regression Forests + maintainer: Loris Michel + description: |- + Quantile Regression Forests is a tree-based ensemble + method for estimation of conditional quantiles. It is + particularly well suited for high-dimensional data. Predictor + variables of mixed classes can be handled. The package is + dependent on the package 'randomForest', written by Andy Liaw. + date_publication: '2024-10-07' + bug_reports: https://github.com/lorismichel/quantregForest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quantregForest + url_git: https://github.com/lorismichel/quantregForest +QuantRegGLasso: + version: 1.0.0 + title: |- + Adaptively Weighted Group Lasso for Semiparametric Quantile + Regression Models + maintainer: Wen-Ting Wang + description: |- + Implements an adaptively weighted group Lasso procedure for simultaneous variable selection and structure identification in varying + coefficient quantile regression models and additive quantile regression models with ultra-high dimensional covariates. The methodology, grounded + in a strong sparsity condition, establishes selection consistency under certain weight conditions. To address the challenge of tuning parameter + selection in practice, a BIC-type criterion named high-dimensional information criterion (HDIC) is proposed. The Lasso procedure, guided by + HDIC-determined tuning parameters, maintains selection consistency. Theoretical findings are strongly supported by simulation studies. + (Toshio Honda, Ching-Kang Ing, Wei-Ying Wu, 2019, ). + date_publication: '2024-01-16' + bug_reports: https://github.com/egpivo/QuantRegGLasso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=QuantRegGLasso + url_git: https://github.com/egpivo/SpatPCA +quantregGrowth: + version: 1.7-1 + title: |- + Non-Crossing Additive Regression Quantiles and Non-Parametric + Growth Charts + maintainer: Vito M. R. Muggeo + description: |- + Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms, including varying coefficients, via B-splines with L1-norm difference penalties. + Random intercepts and variable selection are allowed via the lasso penalties. + The smoothing parameters are estimated as part of the model fitting, see Muggeo and others (2021) . Monotonicity and concavity + constraints on the fitted curves are allowed, see Muggeo and others (2013) , + and also or some code examples. + date_publication: '2024-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantregGrowth + url_git: '' +quantregRanger: + version: '1.0' + title: Quantile Regression Forests for 'ranger' + maintainer: Philipp Probst + description: This is the implementation of quantile regression forests for the fast + random forest package 'ranger'. + date_publication: '2017-12-15' + bug_reports: https://github.com/PhilippPro/quantregRanger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quantregRanger + url_git: https://github.com/PhilippPro/quantregRanger +quantsig: + version: 0.1.0 + title: Sigmoidal Quantile Function Estimator + maintainer: Han Yu + description: |- + A sigmoidal quantile function estimator based on a newly defined + generalized expectile function. The generalized sigmoidal quantile function + can estimate quantiles beyond the range of the data, which is important for + certain applications given smaller sample sizes. The package is based on the + method introduced in Hutson (2024) . + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quantsig + url_git: '' +quantspec: + version: 1.2-4 + title: Quantile-Based Spectral Analysis of Time Series + maintainer: Tobias Kley + description: |- + Methods to determine, smooth and plot quantile periodograms for + univariate and multivariate time series. See Kley (2016) + for a description and tutorial. + date_publication: '2024-07-11' + bug_reports: https://github.com/tobiaskley/quantspec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quantspec + url_git: https://github.com/tobiaskley/quantspec +QuantumOps: + version: 3.0.1 + title: |- + Performs Common Linear Algebra Operations Used in Quantum + Computing and Implements Quantum Algorithms + maintainer: Salonik Resch + description: Contains basic structures and operations used frequently in quantum + computing. Intended to be a convenient tool to help learn quantum mechanics and + algorithms. Can create arbitrarily sized kets and bras and implements quantum + gates, inner products, and tensor products. Creates arbitrarily controlled versions + of all gates and can simulate complete or partial measurements of kets. Has functionality + to convert functions into equivalent quantum gates and model quantum noise. Includes + larger applications, such as Steane error correction , + Quantum Fourier Transform and Shor's algorithm (Shor 1999), Grover's algorithm + (1996), Quantum Approximation Optimization Algorithm (QAOA) (Farhi, Goldstone, + and Gutmann 2014) , and a variational quantum classifier (Schuld + 2018) . Can be used with the gridsynth algorithm + to perform decomposition into the Clifford+T set. + date_publication: '2020-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuantumOps + url_git: '' +quarks: + version: 1.1.4 + title: |- + Simple Methods for Calculating and Backtesting Value at Risk and + Expected Shortfall + maintainer: Sebastian Letmathe + description: |- + Enables the user to calculate Value at Risk (VaR) + and Expected Shortfall (ES) by means of various types of historical + simulation. Currently plain-, age-, volatility-weighted- and filtered + historical simulation are implemented in this package. Volatility weighting + can be carried out via an exponentially weighted moving average model + (EWMA) or other GARCH-type models. The performance can be assessed via + Traffic Light Test, Coverage Tests and Loss Functions. The methods of the + package are described in Gurrola-Perez, P. and Murphy, D. (2015) + as well as McNeil, J., + Frey, R., and Embrechts, P. (2015) . + date_publication: '2024-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quarks + url_git: '' +quarrint: + version: 1.0.0 + title: |- + Interaction Prediction Between Groundwater and Quarry Extension + Using Discrete Choice Models and Artificial Neural Networks + maintainer: Johan Barthelemy + description: |- + An implementation of two interaction indices between extractive + activity and groundwater resources based on hazard and vulnerability + parameters used in the assessment of natural hazards. One index is based + on a discrete choice model and the other is relying on an artificial + neural network. + date_publication: '2016-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quarrint + url_git: https://github.com/jojo-/quarrint +Quartet: + version: 1.2.7 + title: |- + Comparison of Phylogenetic Trees Using Quartet and Split + Measures + maintainer: Martin R. Smith + description: |- + Calculates the number of four-taxon subtrees consistent with a pair + of cladograms, calculating the symmetric quartet distance of Bandelt & Dress + (1986), Reconstructing the shape of a tree from observed dissimilarity data, + Advances in Applied Mathematics, 7, 309-343 , + and using the tqDist algorithm of Sand et al. (2014), tqDist: a library for + computing the quartet and triplet distances between binary or general trees, + Bioinformatics, 30, 2079–2080 + for pairs of binary trees. + date_publication: '2024-10-31' + bug_reports: https://github.com/ms609/Quartet/issues/ + url: https://ms609.github.io/Quartet/ + url_cran: https://CRAN.R-project.org/package=Quartet + url_git: https://github.com/ms609/Quartet/ +quartets: + version: 0.1.1 + title: Datasets to Help Teach Statistics + maintainer: Lucy D'Agostino McGowan + description: |- + In the spirit of Anscombe's quartet, this package includes datasets + that demonstrate the importance of visualizing your data, the importance of + not relying on statistical summary measures alone, and why additional + assumptions about the data generating mechanism are needed when estimating + causal effects. The package includes "Anscombe's Quartet" (Anscombe 1973) , + D'Agostino McGowan & Barrett (2023) "Causal Quartet" , + "Datasaurus Dozen" (Matejka & Fitzmaurice 2017), "Interaction Triptych" (Rohrer & Arslan 2021) , "Rashomon Quartet" (Biecek et al. 2023) , and + Gelman "Variation and Heterogeneity Causal Quartets" (Gelman et al. 2023) . + date_publication: '2023-04-13' + bug_reports: https://github.com/r-causal/quartets/issues + url: https://r-causal.github.io/quartets/ + url_cran: https://CRAN.R-project.org/package=quartets + url_git: https://github.com/r-causal/quartets +quarto: + version: 1.4.4 + title: R Interface to 'Quarto' Markdown Publishing System + maintainer: Christophe Dervieux + description: |- + Convert R Markdown documents and 'Jupyter' notebooks to a + variety of output formats using 'Quarto'. + date_publication: '2024-07-20' + bug_reports: https://github.com/quarto-dev/quarto-r/issues + url: https://quarto-dev.github.io/quarto-r/ + url_cran: https://CRAN.R-project.org/package=quarto + url_git: https://github.com/quarto-dev/quarto-r +quaxnat: + version: 1.0.1 + title: Estimation of Natural Regeneration Potential + maintainer: Maximilian Axer + description: |- + Functions for estimating the potential dispersal of tree species + using regeneration densities and dispersal distances to nearest seed trees. + A quantile regression is implemented to determine the dispersal potential. + Spatial prediction can be used to identify natural regeneration potential for forest restoration as described in Axer et al (2021) . + date_publication: '2024-10-28' + bug_reports: https://github.com/MaximilianAxer/quaxnat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quaxnat + url_git: https://github.com/MaximilianAxer/quaxnat +QuClu: + version: 1.0.1 + title: Quantile-Based Clustering Algorithms + maintainer: Laura Anderlucci + description: 'Various quantile-based clustering algorithms: algorithm CU (Common + theta and Unscaled variables), algorithm CS (Common theta and Scaled variables + through lambda_j), algorithm VU (Variable-wise theta_j and Unscaled variables) + and algorithm VW (Variable-wise theta_j and Scaled variables through lambda_j). + Hennig, C., Viroli, C., Anderlucci, L. (2019) "Quantile-based clustering." Electronic + Journal of Statistics. 13 (2) 4849 - 4883 .' + date_publication: '2022-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuClu + url_git: '' +queryBuilder: + version: 0.1.0 + title: Programmatic Way to Construct Complex Filtering Queries + maintainer: Krystian Igras + description: |- + Syntax for defining complex filtering expressions in a programmatic way. + A filtering query, built as a nested list configuration, can be easily stored in other formats like 'YAML' or 'JSON'. + What's more, it's possible to convert such configuration to a valid expression that can be applied to + popular 'dplyr' package operations. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=queryBuilder + url_git: '' +queryparser: + version: 0.3.2 + title: Translate 'SQL' Queries into 'R' Expressions + maintainer: Ian Cook + description: Translate 'SQL' 'SELECT' statements into lists of 'R' expressions. + date_publication: '2023-01-09' + bug_reports: https://github.com/ianmcook/queryparser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=queryparser + url_git: https://github.com/ianmcook/queryparser +queryup: + version: 1.0.5 + title: Query the 'UniProtKB' REST API + maintainer: Guillaume Voisinne + description: |- + Retrieve protein information from + the 'UniProtKB' REST API (see ). + date_publication: '2023-06-05' + bug_reports: https://github.com/VoisinneG/queryup/issues + url: '' + url_cran: https://CRAN.R-project.org/package=queryup + url_git: https://github.com/VoisinneG/queryup +quest: + version: 0.2.0 + title: Prepare Questionnaire Data for Analysis + maintainer: David Disabato + description: Offers a suite of functions to prepare questionnaire data for analysis + (perhaps other types of data as well). By data preparation, I mean data analytic + tasks to get your raw data ready for statistical modeling (e.g., regression). + There are functions to investigate missing data, reshape data, validate responses, + recode variables, score questionnaires, center variables, aggregate by groups, + shift scores (i.e., leads or lags), etc. It provides functions for both single + level and multilevel (i.e., grouped) data. With a few exceptions (e.g., ncases()), + functions without an "s" at the end of their primary word (e.g., center_by()) + act on atomic vectors, while functions with an "s" at the end of their primary + word (e.g., centers_by()) act on multiple columns of a data.frame. + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quest + url_git: '' +questionr: + version: 0.7.8 + title: Functions to Make Surveys Processing Easier + maintainer: Julien Barnier + description: |- + Set of functions to make the processing and analysis of + surveys easier : interactive shiny apps and addins for data recoding, + contingency tables, dataset metadata handling, and several convenience + functions. + date_publication: '2023-01-31' + bug_reports: https://github.com/juba/questionr/issues + url: https://juba.github.io/questionr/ + url_cran: https://CRAN.R-project.org/package=questionr + url_git: '' +QuESTr: + version: 0.1.1 + title: |- + Constructing Quantitative Environment Sensor using + Transcriptomes + maintainer: Takahiko Koizumi + description: |- + A method for prediction of environmental conditions based on + transcriptome data linked with the environmental gradients. This package + provides functions to overview gene-environment relationships, to construct + the prediction model, and to predict environmental conditions where the + transcriptomes were generated. This package can quest for candidate genes + for the model construction even in non-model organisms' transcriptomes + without any genetic information. + date_publication: '2022-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuESTr + url_git: https://github.com/takakoizumi/QuESTr +queuecomputer: + version: 1.2.0 + title: Computationally Efficient Queue Simulation + maintainer: Anthony Ebert + description: |- + Implementation of a computationally efficient method for + simulating queues with arbitrary arrival and service times. + Please see Ebert, Wu, Mengersen & Ruggeri (2020, ) + for further details. + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=queuecomputer + url_git: https://github.com/AnthonyEbert/queuecomputer +queueing: + version: 0.2.12 + title: Analysis of Queueing Networks and Models + maintainer: Pedro Canadilla + description: |- + It provides versatile tools for analysis of birth and death based Markovian Queueing Models + and Single and Multiclass Product-Form Queueing Networks. + It implements M/M/1, M/M/c, M/M/Infinite, M/M/1/K, M/M/c/K, M/M/c/c, M/M/1/K/K, M/M/c/K/K, M/M/c/K/m, M/M/Infinite/K/K, + Multiple Channel Open Jackson Networks, Multiple Channel Closed Jackson Networks, + Single Channel Multiple Class Open Networks, Single Channel Multiple Class Closed Networks + and Single Channel Multiple Class Mixed Networks. + Also it provides a B-Erlang, C-Erlang and Engset calculators. + This work is dedicated to the memory of D. Sixto Rios Insua. + date_publication: '2019-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=queueing + url_git: '' +quickblock: + version: 0.2.2 + title: Quick Threshold Blocking + maintainer: Fredrik Savje + description: |- + Provides functions for assigning treatments in randomized experiments using + near-optimal threshold blocking. The package is made with large data sets in + mind and derives blocks more than an order of magnitude quicker than other + methods. + date_publication: '2024-07-31' + bug_reports: https://github.com/fsavje/quickblock/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quickblock + url_git: https://github.com/fsavje/quickblock +quickcheck: + version: 0.1.3 + title: Property Based Testing + maintainer: Andrew McNeil + description: |- + Property based testing, inspired by + the original 'QuickCheck'. This package builds on + the property based testing framework provided by + 'hedgehog' and is designed to seamlessly integrate with + 'testthat'. + date_publication: '2023-10-11' + bug_reports: https://github.com/armcn/quickcheck/issues + url: https://armcn.github.io/quickcheck/ + url_cran: https://CRAN.R-project.org/package=quickcheck + url_git: https://github.com/armcn/quickcheck +quickcode: + version: 1.0.5 + title: Quick and Essential 'R' Tricks for Better Scripts + maintainer: Obinna Obianom + description: The NOT functions, 'R' tricks and a compilation of some simple quick + plus often used 'R' codes to improve your scripts. Improve the quality and reproducibility + of 'R' scripts. + date_publication: '2025-02-03' + bug_reports: https://github.com/oobianom/quickcode/issues + url: https://quickcode.rpkg.net + url_cran: https://CRAN.R-project.org/package=quickcode + url_git: '' +QuickJSR: + version: 1.6.0 + title: Interface for the 'QuickJS' Lightweight 'JavaScript' Engine + maintainer: Andrew R. Johnson + description: |- + An 'R' interface to the 'QuickJS' portable 'JavaScript' + engine. The engine and all 'R' to 'JavaScript' interoperability is bundled + within the package, requiring no dependencies beyond a 'C' compiler. + date_publication: '2025-02-26' + bug_reports: https://github.com/andrjohns/QuickJSR/issues + url: https://bellard.org/quickjs/ + url_cran: https://CRAN.R-project.org/package=QuickJSR + url_git: https://github.com/andrjohns/QuickJSR +quickmatch: + version: 0.2.3 + title: Quick Generalized Full Matching + maintainer: Fredrik Savje + description: |- + Provides functions for constructing near-optimal generalized full matching. + Generalized full matching is an extension of the original full matching method + to situations with more intricate study designs. The package is made with + large data sets in mind and derives matches more than an order of magnitude + quicker than other methods. + date_publication: '2024-07-31' + bug_reports: https://github.com/fsavje/quickmatch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quickmatch + url_git: https://github.com/fsavje/quickmatch +quickNmix: + version: 1.1.1 + title: Asymptotic N-Mixture Model Fitting + maintainer: Matthew RP Parker + description: 'For fitting N-mixture models using either FFT or asymptotic approaches. + FFT N-mixture models extend the work of Cowen et al. (2017) . + Asymptotic N-mixture models extend the work of Dail and Madsen (2011) , + to consider asymptotic solutions to the open population N-mixture models. The + FFT models are derived and described in "Parker, M.R.P., Elliott, L., Cowen, L.L.E. + (2022). Computational efficiency and precision for replicated-count and batch-marked + hidden population models [Manuscript in preparation]. Department of Statistics + and Actuarial Sciences, Simon Fraser University.". The asymptotic models are derived + and described in: "Parker, M.R.P., Elliott, L., Cowen, L.L.E., Cao, J. (2022). + Fast asymptotic solutions for N-mixtures on large populations [Manuscript in preparation]. + Department of Statistics and Actuarial Sciences, Simon Fraser University.".' + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quickNmix + url_git: '' +quickPlot: + version: 1.0.2 + title: A System of Plotting Optimized for Speed and Modularity + maintainer: Eliot J B McIntire + description: |- + A high-level plotting system, compatible with `ggplot2` objects, + maps from `sf`, `terra`, `raster`, `sp`. It is built primarily on the + 'grid' package. The objective of the package is to provide a plotting system + that is built for speed and modularity. This is useful for quick visualizations + when testing code and for plotting multiple figures to the same device from + independent sources that may be independent of one another (i.e., different + function or modules the create the visualizations). The suggested package + 'fastshp' can be installed from the repository + (). + date_publication: '2023-07-02' + bug_reports: https://github.com/PredictiveEcology/quickPlot/issues + url: https://quickplot.predictiveecology.org + url_cran: https://CRAN.R-project.org/package=quickPlot + url_git: https://github.com/PredictiveEcology/quickPlot +quickpsy: + version: 0.1.5.1 + title: Fits Psychometric Functions for Multiple Groups + maintainer: Linares Daniel + description: |- + Quickly fits and plots psychometric functions (normal, logistic, + Weibull or any or any function defined by the user) for multiple groups. + date_publication: '2019-10-02' + bug_reports: '' + url: http://dlinares.org/quickpsy.html + url_cran: https://CRAN.R-project.org/package=quickpsy + url_git: '' +quickPWCR: + version: '1.2' + title: Quickly Construct and Rate Large Binary Pairwised Comparisons + maintainer: Xiaohao Yang + description: |- + A collection of functions for constructing large pairwised comparisons + and rating them using Elo rating system with supporting parallel processing. + The method of random sample pairs is based on Reservoir Sampling proposed by + JVitter (1985) . + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quickPWCR + url_git: '' +quickReg: + version: 1.5.0 + title: |- + Build Regression Models Quickly and Display the Results Using + 'ggplot2' + maintainer: Xikun Han + description: |- + A set of functions to extract results from regression models and + plot the effect size using 'ggplot2' seamlessly. While 'broom' is useful to + convert statistical analysis objects into tidy data frames, 'coefplot' is adept at showing + multivariate regression results. With specific outcome, this package could build regression models + automatically, extract results into a data frame and provide a quicker way to summarize + models' statistical findings using 'ggplot2'. + date_publication: '2017-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quickReg + url_git: '' +quickregression: + version: '0.2' + title: Quick Linear Regression + maintainer: Darshan Maniyar + description: Helps to perform linear regression analysis by reducing manual effort. + Reduces the independent variables based on specified p-value and Variance Inflation + Factor (VIF) level. + date_publication: '2017-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quickregression + url_git: '' +quicR: + version: 2.1.0 + title: RT-QuIC Data Formatting and Analysis + maintainer: Gage Rowden + description: 'Designed for the curation and analysis of data generated from real-time + quaking-induced conversion (RT-QuIC) assays first described by Atarashi et al. + (2011) . ''quicR'' calculates useful metrics such as maxpoint + ratio: Rowden et al. (2023) ; time-to-threshold: Shi + et al. (2013) ; and maximum slope. Integration with + the output from plate readers allows for seamless input of raw data into the R + environment.' + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quicR + url_git: '' +QuICSeedR: + version: 0.1.2 + title: Analyze Data for Fluorophore-Assisted Seed Amplification Assays + maintainer: Manci Li + description: A toolkit for analysis and visualization of data from fluorophore-assisted + seed amplification assays, such as Real-Time Quaking-Induced Conversion (RT-QuIC) + and Fluorophore-Assisted Protein Misfolding Cyclic Amplification (PMCA). 'QuICSeedR' + addresses limitations in existing software by automating data processing, supporting + large-scale analysis, and enabling comparative studies of analysis methods. It + incorporates methods described in Henderson et al. (2015) , + Li et al. (2020) , Rowden et al. (2023) , + Haley et al. (2013) , and Mair and Wilcox (2020) + . Please refer to the original publications for + details. + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QuICSeedR + url_git: '' +quid: + version: 0.0.1 + title: Bayesian Mixed Models for Qualitative Individual Differences + maintainer: Lukas Klima + description: |- + Test whether equality and order constraints hold for all + individuals simultaneously by comparing Bayesian mixed models through Bayes + factors. A tutorial style vignette and a quickstart guide are available, via + vignette("manual", "quid"), and vignette("quickstart", "quid") respectively. + See Haaf and Rouder (2017) ; Haaf, Klaassen and Rouder + (2019) ; and Rouder & Haaf (2021) . + date_publication: '2021-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quid + url_git: '' +quiddich: + version: 1.0.0 + title: QUick IDentification of DIagnostic CHaracters + maintainer: A. Luise Kuehn + description: 'Provides tools for an automated identification of diagnostic molecular + characters, i.e. such columns in a given nucleotide or amino acid alignment that + allow to distinguish taxa from each other. These characters can then be used to + complement the formal descriptions of the taxa, which are often based on morphological + and anatomical features. Especially for morphologically cryptic species, this + will be helpful. QUIDDICH distinguishes between four different types of diagnostic + characters. For more information, see "Kuehn, A.L., Haase, M. 2019. QUIDDICH: + QUick IDentification of DIagnostic CHaracters."' + date_publication: '2019-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quiddich + url_git: '' +quietR: + version: 0.1.0 + title: Simplify Output Verbosity + maintainer: Thomas Johnson + description: |- + Simplifies output suppression logic in R packages, as it's common + to develop some form of it in R. 'quietR' intends to simplify that problem + and allow a set of simple toggle functions to be used to suppress console + output. + date_publication: '2019-06-17' + bug_reports: https://github.com/thomascjohnson/quietR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quietR + url_git: https://github.com/thomascjohnson/quietR +quiltr: + version: 0.1.0 + title: Qualtrics for Labelling Text using R + maintainer: Christopher Barrie + description: Functions to convert text data for labelling into format appropriate + for importing into Qualtrics. Supports multiple language, including right-to-left + scripts as well as different response types. Outputs an Advance Format .txt file + that read into Qualtrics. + date_publication: '2021-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quiltr + url_git: '' +quincunx: + version: 0.1.7 + title: REST API Client for the 'PGS' Catalog + maintainer: Ramiro Magno + description: |- + Programmatic access to the 'PGS' Catalog. + This package provides easy access to 'PGS' Catalog data by + accessing the REST API . + date_publication: '2023-07-04' + bug_reports: https://github.com/ramiromagno/quincunx/issues + url: https://rmagno.eu/quincunx/ + url_cran: https://CRAN.R-project.org/package=quincunx + url_git: https://github.com/ramiromagno/quincunx +quint: + version: 2.2.2 + title: Qualitative Interaction Trees + maintainer: Elise Dusseldorp + description: Grows a qualitative interaction tree. Quint is a tool for subgroup + analysis, suitable for data from a two-arm randomized controlled trial. More information + in Dusseldorp, E., Doove, L., & Van Mechelen, I. (2016) . + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quint + url_git: '' +quollr: + version: 0.1.1 + title: Visualising How Nonlinear Dimension Reduction Warps Your Data + maintainer: Jayani P.G. Lakshika + description: |- + To construct a model in 2D + space from 2D embedding data and then lift it to the high-dimensional + space. Additionally, it provides tools to visualize the model in 2D + space and to overlay the fitted model on data using the tour + technique. Furthermore, it facilitates the generation of summaries of + high-dimensional distributions. + date_publication: '2024-03-05' + bug_reports: https://github.com/JayaniLakshika/quollr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quollr + url_git: https://github.com/JayaniLakshika/quollr +quoradsR: + version: 0.1.0 + title: Get 'Quora' Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from 'Quora' Ads + using the 'Windsor.ai' API . + date_publication: '2022-11-02' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=quoradsR + url_git: '' +quotedargs: + version: 0.1.3 + title: A Way of Writing Functions that Quote their Arguments + maintainer: Radford Neal + description: |- + A facility for writing functions that quote their arguments, + may sometimes evaluate them in the environment where they were quoted, + and may pass them as quoted to other functions. + date_publication: '2019-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=quotedargs + url_git: '' +quRan: + version: 0.1.0 + title: Complete Text of the Qur'an + maintainer: Andrew Heiss + description: |- + Full text, in data frames containing one row per verse, of the + Qur'an in Arabic (with and without vowels) and in English (the Yusuf Ali + and Saheeh International translations), formatted to be convenient for + text analysis. + date_publication: '2019-01-17' + bug_reports: https://github.com/andrewheiss/quRan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=quRan + url_git: https://github.com/andrewheiss/quRan +QurvE: + version: 1.1.1 + title: |- + Robust and User-Friendly Analysis of Growth and Fluorescence + Curves + maintainer: Nicolas T. Wirth + description: |- + High-throughput analysis of growth curves and fluorescence + data using three methods: linear regression, growth model fitting, and + smooth spline fit. Analysis of dose-response relationships via + smoothing splines or dose-response models. Complete data analysis + workflows can be executed in a single step via user-friendly wrapper + functions. The results of these workflows are summarized in detailed + reports as well as intuitively navigable 'R' data containers. A 'shiny' + application provides access to all features without + requiring any programming knowledge. The package is described in further + detail in Wirth et al. (2023) . + date_publication: '2024-01-26' + bug_reports: https://github.com/NicWir/QurvE/issues + url: https://nicwir.github.io/QurvE/ + url_cran: https://CRAN.R-project.org/package=QurvE + url_git: https://github.com/NicWir/QurvE +Qval: + version: 1.1.1 + title: The Q-Matrix Validation Methods Framework + maintainer: Haijiang Qin + description: Provide a variety of Q-matrix validation methods for the generalized + cognitive diagnosis models, including the method based on the generalized deterministic + input, noisy, and gate model (G-DINA) by de la Torre (2011) + discrimination index (the GDI method) by de la Torre and Chiu (2016) , + the step-wise Wald test method (the Wald method) by Ma and de la Torre (2020) + , the Hull method by Najera et al. (2021) , + the multiple logistic regression‑based Q‑matrix validation method (the MLR-B method) + by Tu et al. (2022) , the beta method based on + signal detection theory by Li and Chen (2024) and Q-matrix + validation based on relative fit index by Chen et la. (2013) . + Different research methods and iterative procedures during Q-matrix validating + are available. + date_publication: '2025-01-09' + bug_reports: '' + url: https://haijiangqin.com/Qval/ + url_cran: https://CRAN.R-project.org/package=Qval + url_git: '' +qvcalc: + version: 1.0.4 + title: Quasi Variances for Factor Effects in Statistical Models + maintainer: David Firth + description: Functions to compute quasi variances and associated measures of approximation + error. + date_publication: '2025-01-24' + bug_reports: https://github.com/DavidFirth/qvcalc/issues + url: https://davidfirth.github.io/qvcalc/ + url_cran: https://CRAN.R-project.org/package=qvcalc + url_git: '' +qvirus: + version: 0.0.3 + title: |- + Quantum Computing for Analyzing CD4 Lymphocytes and + Antiretroviral Therapy + maintainer: Juan Pablo Acuña González + description: Resources, tutorials, and code snippets dedicated to exploring the + intersection of quantum computing and artificial intelligence (AI) in the context + of analyzing Cluster of Differentiation 4 (CD4) lymphocytes and optimizing antiretroviral + therapy (ART) for human immunodeficiency virus (HIV). With the emergence of quantum + artificial intelligence and the development of small-scale quantum computers, + there's an unprecedented opportunity to revolutionize the understanding of HIV + dynamics and treatment strategies. This project leverages the R package 'qsimulatR' + (Ostmeyer and Urbach, 2023, ), a + quantum computer simulator, to explore these applications in quantum computing + techniques, addressing the challenges in studying CD4 lymphocytes and enhancing + ART efficacy. + date_publication: '2024-10-26' + bug_reports: https://github.com/juanv66x/qvirus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=qvirus + url_git: https://github.com/juanv66x/qvirus +qwalkr: + version: 0.1.0 + title: Handle Continuous-Time Quantum Walks with R + maintainer: Vitor Marques + description: 'Functions and tools for creating, visualizing, and investigating properties + of continuous-time quantum walks, including efficient calculation of matrices + such as the mixing matrix, average mixing matrix, and spectral decomposition of + the Hamiltonian. E. Farhi (1997): ; C. Godsil (2011) + .' + date_publication: '2023-09-27' + bug_reports: https://github.com/vitormarquesr/qwalkr/issues + url: https://vitormarquesr.github.io/qwalkr/ + url_cran: https://CRAN.R-project.org/package=qwalkr + url_git: https://github.com/vitormarquesr/qwalkr +QWDAP: + version: 1.1.20 + title: Quantum Walk-Based Data Analysis and Prediction + maintainer: Binghuang Pan + description: The modeling and prediction of graph-associated time series(GATS) based + on continuous time quantum walk. This software is mainly used for feature extraction, + modeling, prediction and result evaluation of GATS, including continuous time + quantum walk simulation, feature selection, regression analysis, time series prediction, + and series fit calculation. A paper is attached to the package for reference. + date_publication: '2024-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QWDAP + url_git: '' +qwraps2: + version: 0.6.1 + title: Quick Wraps 2 + maintainer: Peter DeWitt + description: |- + A collection of (wrapper) functions the creator found useful + for quickly placing data summaries and formatted regression results into + '.Rnw' or '.Rmd' files. Functions for generating commonly used graphics, + such as receiver operating curves or Bland-Altman plots, are also provided + by 'qwraps2'. 'qwraps2' is a updated version of a package 'qwraps'. The + original version 'qwraps' was never submitted to CRAN but can be found at + . The implementation and limited scope + of the functions within 'qwraps2' is + fundamentally different from 'qwraps'. + date_publication: '2024-10-15' + bug_reports: https://github.com/dewittpe/qwraps2/issues + url: http://www.peteredewitt.com/qwraps2/ + url_cran: https://CRAN.R-project.org/package=qwraps2 + url_git: https://github.com/dewittpe/qwraps2/ +QZ: + version: 0.2-3 + title: Generalized Eigenvalues and QZ Decomposition + maintainer: Wei-Chen Chen + description: |- + Generalized eigenvalues and eigenvectors + use QZ decomposition (generalized Schur decomposition). + The decomposition needs an N-by-N non-symmetric + matrix A or paired matrices (A,B) with eigenvalues reordering + mechanism. The decomposition functions are mainly based Fortran + subroutines in complex*16 and double precision of LAPACK + library (version 3.10.0 or later). + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=QZ + url_git: '' +R.AlphA.Home: + version: 1.0.0 + title: |- + Feel at Home using R, Thanks to Shortcuts Functions Making it + Simple + maintainer: Raphaël Flambard + description: A collection of personal functions designed to simplify and streamline + common R programming tasks. This package provides reusable tools and shortcuts + for frequently used calculations and workflows. + date_publication: '2025-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R.AlphA.Home + url_git: '' +r.blip: + version: '1.1' + title: Bayesian Network Learning Improved Project + maintainer: Mauro Scanagatta + description: 'Allows the user to learn Bayesian networks from datasets containing + thousands of variables. It focuses on score-based learning, mainly the ''BIC'' + and the ''BDeu'' score functions. It provides state-of-the-art algorithms for + the following tasks: (1) parent set identification - Mauro Scanagatta (2015) ; + (2) general structure optimization - Mauro Scanagatta (2018) , + Mauro Scanagatta (2018) ; + (3) bounded treewidth structure optimization - Mauro Scanagatta (2016) ; + (4) structure learning on incomplete data sets - Mauro Scanagatta (2018) . + Distributed under the LGPL-3 by IDSIA.' + date_publication: '2019-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r.blip + url_git: '' +R.cache: + version: 0.16.0 + title: |- + Fast and Light-Weight Caching (Memoization) of Objects and + Results to Speed Up Computations + maintainer: Henrik Bengtsson + description: Memoization can be used to speed up repetitive and computational expensive + function calls. The first time a function that implements memoization is called + the results are stored in a cache memory. The next time the function is called + with the same set of parameters, the results are momentarily retrieved from the + cache avoiding repeating the calculations. With this package, any R object can + be cached in a key-value storage where the key can be an arbitrary set of R objects. The + cache memory is persistent (on the file system). + date_publication: '2022-07-21' + bug_reports: https://github.com/HenrikBengtsson/R.cache/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R.cache + url_git: https://github.com/HenrikBengtsson/R.cache +R.devices: + version: 2.17.2 + title: Unified Handling of Graphics Devices + maintainer: Henrik Bengtsson + description: |- + Functions for creating plots and image files in a unified way + regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.). Default + device options as well as scales and aspect ratios are controlled in a uniform + way across all device types. Switching output format requires minimal changes + in code. This package is ideal for large-scale batch processing, because it + will never leave open graphics devices or incomplete image files behind, even on + errors or user interrupts. + date_publication: '2024-01-29' + bug_reports: https://github.com/HenrikBengtsson/R.devices/issues + url: https://henrikbengtsson.github.io/R.devices/ + url_cran: https://CRAN.R-project.org/package=R.devices + url_git: https://github.com/HenrikBengtsson/R.devices +R.filesets: + version: 2.15.1 + title: |- + Easy Handling of and Access to Files Organized in Structured + Directories + maintainer: Henrik Bengtsson + description: 'A file set refers to a set of files located in one or more directories + on the file system. This package provides classes and methods to locate, setup, + subset, navigate and iterate such sets. The API is designed such that these classes + can be extended via inheritance to provide a richer API for special file formats. Moreover, + a specific name format is defined such that filenames and directories can be considered + to have full names which consists of a name followed by comma-separated tags. This + adds additional flexibility to identify file sets and individual files. NOTE: + This package''s API should be considered to be in an beta stage. Its main purpose + is currently to support the aroma.* packages, where it is one of the main core + components; if you decide to build on top of this package, please contact the + author first.' + date_publication: '2024-01-24' + bug_reports: https://github.com/HenrikBengtsson/R.filesets/issues + url: https://www.aroma-project.org/ + url_cran: https://CRAN.R-project.org/package=R.filesets + url_git: https://github.com/HenrikBengtsson/R.filesets +R.huge: + version: 0.10.1 + title: Methods for Accessing Huge Amounts of Data [deprecated] + maintainer: Henrik Bengtsson + description: 'DEPRECATED. Do not start building new projects based on this package. + Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), + BufferedMatrix (Bioconductor). The main usage of it was inside the aroma.affymetrix + package. (The package currently provides a class representing a matrix where the + actual data is stored in a binary format on the local file system. This way the + size limit of the data is set by the file system and not the memory.)' + date_publication: '2024-01-24' + bug_reports: https://github.com/HenrikBengtsson/R.huge/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R.huge + url_git: https://github.com/HenrikBengtsson/R.huge +r.jive: + version: '2.4' + title: Perform JIVE Decomposition for Multi-Source Data + maintainer: Michael J. O'Connell + description: 'Performs the Joint and Individual Variation Explained (JIVE) decomposition + on a list of data sets when the data share a dimension, returning low-rank matrices + that capture the joint and individual structure of the data [O''Connell, MJ and + Lock, EF (2016) ]. It provides two methods + of rank selection when the rank is unknown, a permutation test and a Bayesian + Information Criterion (BIC) selection algorithm. Also included in the package + are three plotting functions for visualizing the variance attributed to each data + source: a bar plot that shows the percentages of the variability attributable + to joint and individual structure, a heatmap that shows the structure of the variability, + and principal component plots.' + date_publication: '2020-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r.jive + url_git: '' +R.matlab: + version: 3.7.0 + title: Read and Write MAT Files and Call MATLAB from Within R + maintainer: Henrik Bengtsson + description: Methods readMat() and writeMat() for reading and writing MAT files. For + user with MATLAB v6 or newer installed (either locally or on a remote host), the + package also provides methods for controlling MATLAB (trademark) via R and sending + and retrieving data between R and MATLAB. + date_publication: '2022-08-25' + bug_reports: https://github.com/HenrikBengtsson/R.matlab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R.matlab + url_git: https://github.com/HenrikBengtsson/R.matlab +R.methodsS3: + version: 1.8.2 + title: S3 Methods Simplified + maintainer: Henrik Bengtsson + description: Methods that simplify the setup of S3 generic functions and S3 methods. Major + effort has been made in making definition of methods as simple as possible with + a minimum of maintenance for package developers. For example, generic functions + are created automatically, if missing, and naming conflict are automatically solved, + if possible. The method setMethodS3() is a good start for those who in the future + may want to migrate to S4. This is a cross-platform package implemented in pure + R that generates standard S3 methods. + date_publication: '2022-06-13' + bug_reports: https://github.com/HenrikBengtsson/R.methodsS3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R.methodsS3 + url_git: https://github.com/HenrikBengtsson/R.methodsS3 +R.oo: + version: 1.27.0 + title: R Object-Oriented Programming with or without References + maintainer: Henrik Bengtsson + description: Methods and classes for object-oriented programming in R with or without + references. Large effort has been made on making definition of methods as simple + as possible with a minimum of maintenance for package developers. The package + has been developed since 2001 and is now considered very stable. This is a cross-platform + package implemented in pure R that defines standard S3 classes without any tricks. + date_publication: '2024-11-01' + bug_reports: https://github.com/HenrikBengtsson/R.oo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R.oo + url_git: https://github.com/HenrikBengtsson/R.oo +r.proxy: + version: 0.1.3 + title: Set Proxy in R Console + maintainer: Yonghe Xia + description: |- + The use of proxies is required in certain network + environments. Despite the power of system level software, it is still + inconvenient to switch proxy networks at random in R's console. This + package is designed to provide one-click switching between proxy and + non-proxy states. + date_publication: '2023-08-15' + bug_reports: https://github.com/xiayh17/r.proxy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r.proxy + url_git: https://github.com/xiayh17/r.proxy +R.rsp: + version: 0.46.0 + title: Dynamic Generation of Scientific Reports + maintainer: Henrik Bengtsson + description: The RSP markup language makes any text-based document come alive. RSP + provides a powerful markup for controlling the content and output of LaTeX, HTML, + Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. 'Today's date + is <%=Sys.Date()%>'. Contrary to many other literate programming languages, with + RSP it is straightforward to loop over mixtures of code and text sections, e.g. + in month-by-month summaries. RSP has also several preprocessing directives for + incorporating static and dynamic contents of external files (local or online) + among other things. Functions rstring() and rcat() make it easy to process RSP + strings, rsource() sources an RSP file as it was an R script, while rfile() compiles + it (even online) into its final output format, e.g. rfile('report.tex.rsp') generates + 'report.pdf' and rfile('report.md.rsp') generates 'report.html'. RSP is ideal + for self-contained scientific reports and R package vignettes. It's easy to use + - if you know how to write an R script, you'll be up and running within minutes. + date_publication: '2024-02-17' + bug_reports: https://github.com/HenrikBengtsson/R.rsp/issues + url: https://henrikbengtsson.github.io/R.rsp/ + url_cran: https://CRAN.R-project.org/package=R.rsp + url_git: https://github.com/HenrikBengtsson/R.rsp +R.temis: + version: 0.1.3 + title: Integrated Text Mining Solution + maintainer: Milan Bouchet-Valat + description: |- + An integrated solution to perform + a series of text mining tasks such as importing and cleaning a corpus, and + analyses like terms and documents counts, lexical summary, terms + co-occurrences and documents similarity measures, graphs of terms, + correspondence analysis and hierarchical clustering. Corpora can be imported + from spreadsheet-like files, directories of raw text files, + as well as from 'Dow Jones Factiva', 'LexisNexis', 'Europresse' and 'Alceste' files. + date_publication: '2021-05-12' + bug_reports: https://github.com/nalimilan/R.TeMiS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R.temis + url_git: https://github.com/nalimilan/R.TeMiS +R.utils: + version: 2.13.0 + title: Various Programming Utilities + maintainer: Henrik Bengtsson + description: Utility functions useful when programming and developing R packages. + date_publication: '2025-02-24' + bug_reports: https://github.com/HenrikBengtsson/R.utils/issues + url: https://henrikbengtsson.github.io/R.utils/ + url_cran: https://CRAN.R-project.org/package=R.utils + url_git: https://github.com/HenrikBengtsson/R.utils +R0: + version: 1.3-1 + title: |- + Estimation of R0 and Real-Time Reproduction Number from + Epidemics + maintainer: Thomas Obadia + description: |- + Estimation of reproduction numbers for disease outbreak, based on + incidence data. The R0 package implements several documented methods. It is + therefore possible to compare estimations according to the methods used. + Depending on the methods requested by user, basic reproduction number + (commonly denoted as R0) or real-time reproduction number (referred to as + R(t)) is computed, along with a 95% Confidence Interval. Plotting outputs + will give different graphs depending on the methods requested : basic + reproductive number estimations will only show the epidemic curve + (collected data) and an adjusted model, whereas real-time methods will also + show the R(t) variations throughout the outbreak time period. Sensitivity + analysis tools are also provided, and allow for investigating effects of + varying Generation Time distribution or time window on estimates. + date_publication: '2023-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R0 + url_git: https://github.com/tobadia/R0 +r02pro: + version: '0.2' + title: 'R Programming: Zero to Pro' + maintainer: Yang Feng + description: 'This is a companion package of the book "R Programming: Zero to Pro" . + It contains the datasets used in the book and provides interactive exercises corresponding + to the book. It covers a wide range of topics including visualization, data transformation, + tidying data, data input and output.' + date_publication: '2023-05-31' + bug_reports: '' + url: https://r02pro.github.io/ + url_cran: https://CRAN.R-project.org/package=r02pro + url_git: '' +R1magic: + version: 0.3.4 + title: 'Compressive Sampling: Sparse Signal Recovery Utilities' + maintainer: Mehmet Suzen + description: Utilities for sparse signal recovery suitable for compressed sensing. + L1, L2 and TV penalties, DFT basis matrix, simple sparse signal generator, mutual + cumulative coherence between two matrices and examples, Lp complex norm, scaling + back regression coefficients. + date_publication: '2023-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R1magic + url_git: '' +R2Addhaz: + version: 0.1.0 + title: |- + R2 Measure of Explained Variation under the Additive Hazards + Model + maintainer: Denise Rava + description: R^2 measure of explained variation under the semiparametric additive + hazards model is estimated. The measure can be used as a measure of predictive + capability and therefore it can be adopted in model selection process. Rava, D. + and Xu, R. (2020) . + date_publication: '2020-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2Addhaz + url_git: '' +R2admb: + version: 0.7.16.3 + title: '''ADMB'' to R Interface Functions' + maintainer: Ben Bolker + description: |- + A series of functions to call 'AD Model Builder' (i.e., + compile and run models) from within R, read the results back + into R as 'admb' objects, and provide standard accessors (i.e. + coef(), vcov(), etc.) + date_publication: '2022-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2admb + url_git: '' +R2BayesX: + version: 1.1-5 + title: Estimate Structured Additive Regression Models with 'BayesX' + maintainer: Nikolaus Umlauf + description: An R interface to estimate structured additive regression (STAR) models + with 'BayesX'. + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2BayesX + url_git: '' +R2BEAT: + version: 1.0.5 + title: Multistage Sampling Allocation and Sample Selection + maintainer: Andrea Fasulo + description: Multivariate optimal allocation for different domains in one and two + stages stratified sample design. 'R2BEAT' extends the Neyman (1934) – Tschuprow + (1923) allocation method to the case of several variables, adopting a generalization + of the Bethel’s proposal (1989). 'R2BEAT' develops this methodology but, moreover, + it allows to determine the sample allocation in the multivariate and multi-domains + case of estimates for two-stage stratified samples. It also allows to perform + both Primary Stage Units and Secondary Stage Units selection. This package requires + the availability of 'ReGenesees', that can be installed from . + date_publication: '2023-05-25' + bug_reports: https://github.com/barcaroli/R2BEAT/issues + url: https://barcaroli.github.io/R2BEAT/ + url_cran: https://CRAN.R-project.org/package=R2BEAT + url_git: '' +r2country: + version: 2.0.2.4.0 + title: |- + Country Data with Names, Capitals, Currencies, Populations, + Time, Languages and so on + maintainer: Obinna Obianom + description: Obtain information about countries around the globe. Information for + names, states, languages, time, capitals, currency and many more. Data source + are 'Wikipedia' , 'TimeAndDate' + and 'CountryCode' . + date_publication: '2024-08-01' + bug_reports: https://github.com/oobianom/r2country + url: https://r2country.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=r2country + url_git: '' +r2d2: + version: 1.0.2 + title: |- + Bivariate (Two-Dimensional) Confidence Region and Frequency + Distribution + maintainer: Arni Magnusson + description: |- + Generic functions to analyze the distribution of two continuous + variables: 'conf2d' to calculate a smooth empirical confidence region, and + 'freq2d' to calculate a frequency distribution. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r2d2 + url_git: https://github.com/arni-magnusson/r2d2 +R2D2ordinal: + version: 1.0.0 + title: Implements Pseudo-R2D2 Prior for Ordinal Regression + maintainer: Eric Yanchenko + description: Implements the pseudo-R2D2 prior for ordinal regression from the paper + "Psuedo-R2D2 prior for high-dimensional ordinal regression" by Yanchenko (2025) + . In particular, it provides code to evaluate the + probability distribution function for the cut-points, compute the log-likelihood, + calculate the hyper-parameters for the global variance parameter, find the distribution + of McFadden's coefficient-of-determination, and fit the model in 'rstan'. Please + cite the paper if you use these codes. + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2D2ordinal + url_git: '' +r2d3: + version: 0.2.6 + title: Interface to 'D3' Visualizations + maintainer: Nick Strayer + description: |- + Suite of tools for using 'D3', a library for producing dynamic, interactive data + visualizations. Supports translating objects into 'D3' friendly data structures, rendering + 'D3' scripts, publishing 'D3' visualizations, incorporating 'D3' in R Markdown, creating + interactive 'D3' applications with Shiny, and distributing 'D3' based 'htmlwidgets' in R + packages. + date_publication: '2022-02-28' + bug_reports: https://github.com/rstudio/r2d3/issues + url: https://rstudio.github.io/r2d3/ + url_cran: https://CRAN.R-project.org/package=r2d3 + url_git: https://github.com/rstudio/r2d3 +r2dictionary: + version: '0.2' + title: A Mini-Dictionary for 'R', 'Shiny' and 'Rmarkdown' Documents + maintainer: Obinna Obianom + description: Despite the predominant use of R for data manipulation and various + robust statistical calculations, in recent years, more people from various disciplines + are beginning to use R for other purposes. A critical milestone that has enabled + large influx of users in the R community is the development of the Tidyverse family + of packages and Rmarkdown. With the latter, one can write all kinds of documents + and produce output in formats such html and pdf very easily. In doing this seemlessly, + further tools are needed for such users to easily and freely write in R for all + kinds of purposes. The r2dictionary introduces a means for users to directly search + for definitions of terms within the R environment. + date_publication: '2023-07-17' + bug_reports: https://github.com/oobianom/r2dictionary + url: https://r2dictionary.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=r2dictionary + url_git: '' +r2dii.analysis: + version: 0.5.1 + title: Measure Climate Scenario Alignment of Corporate Loans + maintainer: Jacob Kastl + description: |- + These tools help you to assess if a corporate lending + portfolio aligns with climate goals. They summarize key climate + indicators attributed to the portfolio (e.g. production, emission + factors), and calculate alignment targets based on climate scenarios. + They implement in R the last step of the free software 'PACTA' (Paris + Agreement Capital Transition Assessment; + ). Financial institutions use 'PACTA' + to study how their capital allocation decisions align with climate + change mitigation goals. + date_publication: '2025-02-18' + bug_reports: https://github.com/RMI-PACTA/r2dii.analysis/issues + url: https://rmi-pacta.github.io/r2dii.analysis/ + url_cran: https://CRAN.R-project.org/package=r2dii.analysis + url_git: https://github.com/RMI-PACTA/r2dii.analysis +r2dii.data: + version: 0.6.0 + title: |- + Datasets to Measure the Alignment of Corporate Loan Books with + Climate Goals + maintainer: Alex Axthelm + description: |- + These datasets support the implementation in R of the + software 'PACTA' (Paris Agreement Capital Transition Assessment), + which is a free tool that calculates the alignment between corporate + lending portfolios and climate scenarios + (). Financial institutions use + 'PACTA' to study how their capital allocation decisions align with + climate change mitigation goals. Because both financial institutions + and market data providers keep their data private, this package + provides fake, public data to enable the development and use of + 'PACTA' in R. + date_publication: '2024-06-20' + bug_reports: https://github.com/RMI-PACTA/r2dii.data/issues + url: https://rmi-pacta.github.io/r2dii.data/ + url_cran: https://CRAN.R-project.org/package=r2dii.data + url_git: https://github.com/RMI-PACTA/r2dii.data +r2dii.match: + version: 0.4.0 + title: Tools to Match Corporate Lending Portfolios with Climate Data + maintainer: Jacob Kastl + description: |- + These tools implement in R a fundamental part of the software + 'PACTA' (Paris Agreement Capital Transition Assessment), which is a + free tool that calculates the alignment between financial portfolios + and climate scenarios (). Financial + institutions use 'PACTA' to study how their capital allocation + decisions align with climate change mitigation goals. This package + matches data from corporate lending portfolios to asset level data + from market-intelligence databases (e.g. power plant capacities, + emission factors, etc.). This is the first step to assess if a + financial portfolio aligns with climate goals. + date_publication: '2025-02-14' + bug_reports: https://github.com/RMI-PACTA/r2dii.match/issues + url: https://rmi-pacta.github.io/r2dii.match/ + url_cran: https://CRAN.R-project.org/package=r2dii.match + url_git: https://github.com/RMI-PACTA/r2dii.match +r2dii.plot: + version: 0.5.1 + title: |- + Visualize the Climate Scenario Alignment of a Financial + Portfolio + maintainer: Monika Furdyna + description: |- + Create plots to visualize the alignment of a corporate + lending financial portfolio to climate change scenarios based on + climate indicators (production and emission intensities) across key + climate relevant sectors of the 'PACTA' methodology (Paris Agreement Capital + Transition Assessment; ). + Financial institutions use 'PACTA' to study how their capital + allocation decisions align with climate change mitigation goals. + date_publication: '2025-02-18' + bug_reports: https://github.com/RMI-PACTA/r2dii.plot/issues + url: https://rmi-pacta.github.io/r2dii.plot/ + url_cran: https://CRAN.R-project.org/package=r2dii.plot + url_git: https://github.com/RMI-PACTA/r2dii.plot +R2DT: + version: '0.2' + title: Translation of Base R-Like Functions for 'data.table' Objects + maintainer: Robin Van Oirbeek + description: Some heavily used base R functions are reconstructed to also be compliant + to data.table objects. Also, some general helper functions that could be of interest + for working with data.table objects are included. + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2DT + url_git: '' +r2fireworks: + version: 0.1.0 + title: |- + Enhance Your 'Rmarkdown' and 'shiny' Apps with Dazzling + Fireworks Celebrations + maintainer: Obinna Obianom + description: Implementation of 'JQuery' and 'CSS' styles to + allow the display of fireworks on a document. Toolkit to easily incorporate celebratory + splashes in 'Rmarkdown' and 'shiny' apps. + date_publication: '2024-01-16' + bug_reports: https://github.com/oobianom/r2fireworks/issues + url: https://r2fireworks.obi.obianom.com/ + url_cran: https://CRAN.R-project.org/package=r2fireworks + url_git: '' +r2glmm: + version: 0.1.2 + title: Computes R Squared for Mixed (Multilevel) Models + maintainer: Byron Jaeger + description: |- + The model R squared and semi-partial R squared for the linear and + generalized linear mixed model (LMM and GLMM) are computed with confidence + limits. The R squared measure from Edwards et.al (2008) + is extended to the GLMM using penalized quasi-likelihood (PQL) estimation + (see Jaeger et al. 2016 ). Three methods + of computation are provided and described as follows. First, The + Kenward-Roger approach. Due to some inconsistency between the 'pbkrtest' + package and the 'glmmPQL' function, the Kenward-Roger approach in the + 'r2glmm' package is limited to the LMM. Second, The method introduced + by Nakagawa and Schielzeth (2013) + and later extended by Johnson (2014) . + The 'r2glmm' package only computes marginal R squared for the LMM and does + not generalize the statistic to the GLMM; however, confidence limits and + semi-partial R squared for fixed effects are useful additions. Lastly, an + approach using standardized generalized variance (SGV) can be used for + covariance model selection. Package installation instructions can be found + in the readme file. + date_publication: '2017-08-05' + bug_reports: https://github.com/bcjaeger/r2glmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r2glmm + url_git: https://github.com/bcjaeger/r2glmm +R2HTML: + version: 2.3.4 + title: HTML Exportation for R Objects + maintainer: Milan Bouchet-Valat + description: |- + Includes HTML function and methods to write in an HTML + file. Thus, making HTML reports is easy. Includes a function + that allows redirection on the fly, which appears to be very + useful for teaching purpose, as the student can keep a copy of + the produced output to keep all that he did during the course. + Package comes with a vignette describing how to write HTML + reports for statistical analysis. Finally, a driver for 'Sweave' + allows to parse HTML flat files containing R code and to + automatically write the corresponding outputs (tables and + graphs). + date_publication: '2024-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2HTML + url_git: https://github.com/nalimilan/R2HTML +R2jags: + version: 0.8-9 + title: Using R to Run 'JAGS' + maintainer: Yu-Sung Su + description: Providing wrapper functions to implement Bayesian analysis in JAGS. Some + major features include monitoring convergence of a MCMC model using Rubin and + Gelman Rhat statistics, automatically running a MCMC model till it converges, + and implementing parallel processing of a MCMC model for multiple chains. + date_publication: '2024-10-13' + bug_reports: https://github.com/suyusung/R2jags/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=R2jags + url_git: '' +r2mlm: + version: 0.3.7 + title: R-Squared Measures for Multilevel Models + maintainer: Mairead Shaw + description: |- + Generates both total- and level-specific R-squared measures from + Rights and Sterba’s (2019) framework of R-squared measures for multilevel + models with random intercepts and/or slopes, which is based on a complete + decomposition of variance. Additionally generates graphical + representations of these R-squared measures to allow visualizing and + interpreting all measures in the framework together as an integrated set. + This framework subsumes 10 previously-developed R-squared measures for + multilevel models as special cases of 5 measures from the framework, and it + also includes several newly-developed measures. Measures in the framework + can be used to compute R-squared differences when comparing multilevel + models (following procedures in Rights & Sterba (2020) ). + Bootstrapped confidence intervals can also be calculated. To use the + confidence interval functionality, download bootmlm from . + date_publication: '2023-12-20' + bug_reports: https://github.com/mkshaw/r2mlm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r2mlm + url_git: https://github.com/mkshaw/r2mlm +R2MLwiN: + version: 0.8-9 + title: Running 'MLwiN' from Within R + maintainer: Zhengzheng Zhang + description: |- + An R command interface to the 'MLwiN' multilevel + modelling software package. + date_publication: '2024-01-30' + bug_reports: '' + url: http://www.bristol.ac.uk/cmm/software/r2mlwin/ + url_cran: https://CRAN.R-project.org/package=R2MLwiN + url_git: https://r-forge.r-project.org/projects/r2mlwin/ +R2OpenBUGS: + version: 3.2-3.2.1 + title: Running OpenBUGS from R + maintainer: Neal Thomas + description: |- + Using this package, + it is possible to call a BUGS model, summarize inferences and + convergence in a table and graph, and save the simulations in arrays for easy access + in R. + date_publication: '2020-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2OpenBUGS + url_git: '' +r2pmml: + version: 0.30.0 + title: Convert R Models to PMML + maintainer: Villu Ruusmann + description: |- + R wrapper for the JPMML-R library , + which converts R models to Predictive Model Markup Language (PMML). + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r2pmml + url_git: https://github.com/jpmml/r2pmml +r2pptx: + version: 0.1.0 + title: Object Oriented R -> PowerPoint + maintainer: Matt Lehman + description: |- + Provides a friendly, object oriented API for creating PowerPoint + slide decks in R. + date_publication: '2021-09-15' + bug_reports: https://github.com/mattle24/r2pptx/issues + url: https://mattle24.github.io/r2pptx/ + url_cran: https://CRAN.R-project.org/package=r2pptx + url_git: https://github.com/mattle24/r2pptx +r2r: + version: 0.1.2 + title: R-Object to R-Object Hash Maps + maintainer: Valerio Gherardi + description: |- + Implementation of hash tables (hash sets and hash maps) in R, + featuring arbitrary R objects as keys, + arbitrary hash and key-comparison functions, + and customizable behaviour upon queries of missing keys. + date_publication: '2024-11-09' + bug_reports: https://github.com/vgherard/r2r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r2r + url_git: https://github.com/vgherard/r2r +r2redux: + version: 1.0.18 + title: R2 Statistic + maintainer: Moksedul Momin + description: R2 statistic for significance test. Variance and covariance of R2 values + used to assess the 95% CI and p-value of the R2 difference. + date_publication: '2025-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r2redux + url_git: https://github.com/mommy003/r2redux +r2resize: + version: 1.9.2 + title: |- + In-Text Resize for Images, Tables and Fancy Resize Containers in + 'shiny', 'rmarkdown' and 'quarto' Documents + maintainer: Obinna Obianom + description: Automatic resizing toolbar for containers, images and tables. Various + resizer or expandable container functionalities are also included. Most suitable + to include in 'shiny', 'markdown' and 'quarto' documents. + date_publication: '2024-11-25' + bug_reports: https://github.com/oobianom/r2resize/issues + url: https://r2resize.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=r2resize + url_git: '' +R2ROC: + version: 1.0.1 + title: AUC Statistics + maintainer: Moksedul Momin + description: Area under the receiver operating characteristic curves (AUC) statistic + for significance test. Variance and covariance of AUC values used to assess the + 95% Confidence interval (CI) and p-value of the AUC difference for both nested + and non-nested model. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2ROC + url_git: https://github.com/mommy003/R2ROC +r2rtf: + version: 1.1.3 + title: |- + Easily Create Production-Ready Rich Text Format (RTF) Tables and + Figures + maintainer: Benjamin Wang + description: |- + Create production-ready Rich Text Format (RTF) tables and figures + with flexible format. + date_publication: '2025-02-28' + bug_reports: https://github.com/Merck/r2rtf/issues + url: https://merck.github.io/r2rtf/ + url_cran: https://CRAN.R-project.org/package=r2rtf + url_git: https://github.com/Merck/r2rtf +R2sample: + version: 3.0.0 + title: Various Methods for the Two Sample Problem + maintainer: Wolfgang Rolke + description: |- + The routine twosample_test() in this package runs the + two sample test using various test statistic. The p values are + found via permutation or large sample theory. The routine twosample_power() allows the + calculation of the power in various cases, and plot_power() draws the corresponding power graphs. + The routine run.studies allows a user to quickly study the power of a new method and + how it compares to some of the standard ones. + date_publication: '2025-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2sample + url_git: '' +r2shortcode: + version: '0.2' + title: |- + Shorten Function Names of Functions in Another Package and + Create an Index to Make Them Accessible + maintainer: Obinna Obianom + description: When creating a package, authors may sometimes struggle with coming + up with easy and straightforward function names, and at the same time hoping that + other packages do not already have the same function names. In trying to meet + this goal, sometimes, function names are not descriptive enough and may confuse + the potential users. The purpose of this package is to serve as a package function + short form generator and also provide shorthand names for other functions. Having + this package will entice authors to create long function names without the fear + of users not wanting to use their packages because of the long names. In a way, + everyone wins - the authors can use long descriptive function names, and the users + can use this package to make short functions names while still using the package + in question. + date_publication: '2024-04-05' + bug_reports: https://github.com/oobianom/r2shortcode + url: '' + url_cran: https://CRAN.R-project.org/package=r2shortcode + url_git: https://github.com/oobianom/r2shortcode +r2social: + version: 1.2.1 + title: |- + Seamless Integration of Sharing and Connect Buttons in Markdown + and Apps + maintainer: Obinna Obianom + description: Implementation of 'JQuery' and 'CSS' styles to + allow easy incorporation of various social media elements on a page. The elements + include addition of share buttons or connect with us buttons or hyperlink buttons + to 'Shiny' applications or dashboards and 'Rmarkdown' documents.Sharing capability + on social media platforms including 'Facebook' , 'Linkedin' + , 'X/Twitter' , 'Tumblr' , + 'Pinterest' , 'Whatsapp' , + 'Reddit' , 'Baidu' , 'Blogger' + , 'Weibo' , 'Instagram' , + 'Telegram' , 'Youtube' . + date_publication: '2024-07-29' + bug_reports: https://github.com/oobianom/r2social/issues + url: https://r2social.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=r2social + url_git: '' +r2spss: + version: 0.3.2 + title: Format R Output to Look Like SPSS + maintainer: Andreas Alfons + description: 'Create plots and LaTeX tables that look like SPSS output for use in + teaching materials. Rather than copying-and-pasting SPSS output into documents, + R code that mocks up SPSS output can be integrated directly into dynamic LaTeX + documents with tools such as knitr. Functionality includes statistical techniques + that are typically covered in introductory statistics classes: descriptive statistics, + common hypothesis tests, ANOVA, and linear regression, as well as box plots, histograms, + scatter plots, and line plots (including profile plots).' + date_publication: '2022-05-25' + bug_reports: https://github.com/aalfons/r2spss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r2spss + url_git: https://github.com/aalfons/r2spss +r2stl: + version: 1.0.3 + title: Visualizing Data using a 3D Printer + maintainer: Paul J. Northrop + description: |- + Converts data to STL (stereolithography) files + that can be used to feed a 3-dimensional printer. The + 3-dimensional output from a function can be materialized + into a solid surface in a plastic material, therefore allowing + more detailed examination. There are many possible uses for + this new tool, such as to examine mathematical expressions + with very irregular shapes, to aid teaching people with + impaired vision, to create raised relief maps from digital + elevation maps (DEMs), to bridge the gap between mathematical + tools and rapid prototyping, and many more. Ian Walker created + the function r2stl() and Jose' Gama assembled the package. + date_publication: '2024-03-13' + bug_reports: https://github.com/paulnorthrop/r2stl/issues + url: https://paulnorthrop.github.io/r2stl/ + url_cran: https://CRAN.R-project.org/package=r2stl + url_git: https://github.com/paulnorthrop/r2stl +r2sundials: + version: 6.5.0-5 + title: Wrapper for 'SUNDIALS' Solving ODE and Sensitivity Problem + maintainer: Serguei Sokol + description: Wrapper for widely used 'SUNDIALS' software (SUite of Nonlinear and + DIfferential/ALgebraic Equation Solvers) and more precisely to its 'CVODES' solver. + It is aiming to solve ordinary differential equations (ODE) and optionally pending + forward sensitivity problem. The wrapper is made 'R' friendly by allowing to pass + custom parameters to user's callback functions. Such functions can be both written + in 'R' and in 'C++' ('RcppArmadillo' flavor). In case of 'C++', performance is + greatly improved so this option is highly advisable when performance matters. + If provided, Jacobian matrix can be calculated either in dense or sparse format. + In the latter case 'rmumps' package is used to solve corresponding linear systems. + Root finding and pending event management are optional and can be specified as + 'R' or 'C++' functions too. This makes them a very flexible tool for controlling + the ODE system during the time course simulation. 'SUNDIALS' library was published + in Hindmarsh et al. (2005) . + date_publication: '2024-07-22' + bug_reports: https://github.com/sgsokol/r2sundials/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r2sundials + url_git: '' +r2symbols: + version: '1.4' + title: Symbols for 'Markdown' and 'Shiny' Application + maintainer: Obinna Obianom + description: Direct insertion of over 1000 symbols (e.g. currencies, letters, emojis, + arrows, mathematical symbols and so on) into 'Rmarkdown' documents and 'Shiny' + applications by incorporating 'HTML' hex codes. + date_publication: '2023-03-11' + bug_reports: https://github.com/oobianom/r2symbols/issues + url: https://r2symbols.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=r2symbols + url_git: '' +R2ucare: + version: 1.0.2 + title: Goodness-of-Fit Tests for Capture-Recapture Models + maintainer: Olivier Gimenez + description: |- + Performs goodness-of-fit tests for capture-recapture models as + described by Gimenez et al. (2018) . + Also contains several functions to process capture-recapture data. + date_publication: '2022-07-11' + bug_reports: https://github.com/oliviergimenez/R2ucare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R2ucare + url_git: https://github.com/oliviergimenez/R2ucare +R2WinBUGS: + version: 2.1-22.1 + title: Running 'WinBUGS' and 'OpenBUGS' from 'R' / 'S-PLUS' + maintainer: Uwe Ligges + description: |- + Invoke a 'BUGS' model in 'OpenBUGS' or 'WinBUGS', a class "bugs" for 'BUGS' + results and functions to work with that class. + Function write.model() allows a 'BUGS' model file to be written. + The class and auxiliary functions could be used with other MCMC programs, including 'JAGS'. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R2WinBUGS + url_git: '' +r311: + version: 0.3.7 + title: Interface to the 'open311' Standard + maintainer: Jonas Lieth + description: |- + Access and handle APIs that use the international 'open311' + 'GeoReport v2' standard for civic issue tracking + . Retrieve civic service types and + request data. Select and add available 'open311' endpoints and + jurisdictions. Implicitly supports custom queries and 'open311' extensions. + Requires a minimal number of hard dependencies while still allowing the + integration in common R formats ('xml2', 'tibble', 'sf'). + date_publication: '2024-07-16' + bug_reports: https://github.com/JsLth/r311/issues + url: https://jslth.github.io/r311/ + url_cran: https://CRAN.R-project.org/package=r311 + url_git: https://github.com/jslth/r311 +r3dmol: + version: 0.1.2 + title: Create Interactive 3D Visualizations of Molecular Data + maintainer: Wei Su + description: |- + Create rich and fully interactive 3D visualizations of molecular data. + Visualizations can be included in Shiny apps and R markdown documents, or viewed + from the R console and 'RStudio' Viewer. 'r3dmol' includes an extensive API + to manipulate the visualization after creation, and supports getting data out of + the visualization into R. Based on the '3dmol.js' and the 'htmlwidgets' R package. + date_publication: '2021-03-14' + bug_reports: https://github.com/swsoyee/r3dmol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r3dmol + url_git: https://github.com/swsoyee/r3dmol +r3js: + version: 0.0.2 + title: '''WebGL''-Based 3D Plotting using the ''three.js'' Library' + maintainer: Sam Wilks + description: |- + Provides R and 'JavaScript' functions to allow 'WebGL'-based 3D plotting + using the 'three.js' 'JavaScript' library. Interactivity through roll-over + highlighting and toggle buttons is also supported. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r3js + url_git: '' +r3PG: + version: 0.1.6 + title: Simulating Forest Growth using the 3-PG Model + maintainer: Volodymyr Trotsiuk + description: Provides a flexible and easy-to-use interface for the Physiological + Processes Predicting Growth (3-PG) model written in Fortran. The r3PG serves as + a flexible and easy-to-use interface for the 3-PGpjs (monospecific, evenaged and + evergreen forests) described in Landsberg & Waring (1997) + and the 3-PGmix (deciduous, uneven-aged or mixed-species forests) described in + Forrester & Tang (2016) . + date_publication: '2023-09-19' + bug_reports: https://github.com/trotsiuk/r3PG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r3PG + url_git: https://github.com/trotsiuk/r3PG +R3port: + version: 0.2.5 + title: Report Functions to Create HTML and PDF Files + maintainer: Richard Hooijmaijers + description: |- + Create and combine HTML and PDF reports from within R. + Possibility to design tables and listings for reporting and also include R plots. + date_publication: '2023-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R3port + url_git: https://github.com/RichardHooijmaijers/R3port +R4CouchDB: + version: 0.7.5 + title: A R Convenience Layer for CouchDB 2.0 + maintainer: Thomas Bock + description: |- + Provides a collection of functions for basic + database and document management operations such as add, get, list access + or delete. Every cdbFunction() gets and returns a list() containing the + connection setup. Such a list can be generated by cdbIni(). + date_publication: '2017-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R4CouchDB + url_git: https://github.com/wactbprot/R4CouchDB +r4ds.tutorials: + version: 0.3.0 + title: Tutorials for "R for Data Science" + maintainer: David Kane + description: |- + When assigned "R for Data Science" (Wickham, Çetinkaya-Rundel, + and Grolemund (2023, ISBN: 1492097402)), students should read the book and + type in all the associated R commands themselves. Sadly, that never happens. + These tutorials allow students to demonstrate (and their instructors + to be sure) that all work has been completed. See Kane (2023) + from + the 'tutorial.helpers' package for a background discussion. + date_publication: '2024-07-03' + bug_reports: https://github.com/PPBDS/r4ds.tutorials/issues + url: https://ppbds.github.io/r4ds.tutorials/ + url_cran: https://CRAN.R-project.org/package=r4ds.tutorials + url_git: https://github.com/PPBDS/r4ds.tutorials +r4googleads: + version: 0.1.1 + title: '''Google Ads API'' Interface' + maintainer: Johannes Burkhardt + description: |- + Interface for the 'Google Ads API'. 'Google Ads' is an online + advertising service that enables advertisers to display advertising to web + users (see for more information). + date_publication: '2022-02-28' + bug_reports: https://github.com/banboo-data/r4googleads/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r4googleads + url_git: https://github.com/banboo-data/r4googleads +R4HCR: + version: '0.1' + title: R for Health Care Research + maintainer: Jason L. Oke + description: A collection of datasets that accompany the forthcoming book "R for + Health Care Research". + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R4HCR + url_git: '' +r4lineups: + version: 0.1.1 + title: Statistical Inference on Lineup Fairness + maintainer: Colin Tredoux + description: |- + Since the early 1970s eyewitness testimony researchers have recognised the + importance of estimating properties such as lineup bias (is the lineup biased against + the suspect, leading to a rate of choosing higher than one would expect by chance?), + and lineup size (how many reasonable choices are in fact available to the witness? + A lineup is supposed to consist of a suspect and a number of additional members, + or foils, whom a poor-quality witness might mistake for the perpetrator). Lineup + measures are descriptive, in the first instance, but since the earliest articles in + the literature researchers have recognised the importance of reasoning inferentially + about them. This package contains functions to compute various properties of + laboratory or police lineups, and is intended for use by researchers in forensic + psychology and/or eyewitness testimony research. Among others, the r4lineups package + includes functions for calculating lineup proportion, functional size, various + estimates of effective size, diagnosticity ratio, homogeneity of the diagnosticity + ratio, ROC curves for confidence x accuracy data and the degree of similarity of + faces in a lineup. + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=r4lineups + url_git: '' +r4ss: + version: 1.44.0 + title: R Code for Stock Synthesis + maintainer: Ian G. Taylor + description: |- + A collection of R functions for use with Stock Synthesis, a + fisheries stock assessment modeling platform written in ADMB by Dr. Richard + D. Methot at the NOAA Northwest Fisheries Science Center. The functions + include tools for summarizing and plotting results, manipulating files, + visualizing model parameterizations, and various other common stock + assessment tasks. + This version of '{r4ss}' is compatible with Stock Synthesis versions + 3.24 through 3.30 (specifically version 3.30.19.01, from April + 2022). + date_publication: '2022-05-26' + bug_reports: https://github.com/r4ss/r4ss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r4ss + url_git: https://github.com/r4ss/r4ss +r5r: + version: '2.0' + title: Rapid Realistic Routing with 'R5' + maintainer: Rafael H. M. Pereira + description: |- + Rapid realistic routing on multimodal transport networks + (walk, bike, public transport and car) using 'R5', the Rapid Realistic + Routing on Real-world and Reimagined networks engine + . The package allows users to generate + detailed routing analysis or calculate travel time matrices using + seamless parallel computing on top of the R5 Java machine. While R5 + is developed by Conveyal, the package r5r is independently developed + by a team at the Institute for Applied Economic Research (Ipea) with + contributions from collaborators. Apart from the documentation in this + package, users will find additional information on R5 documentation at + . Although we try to keep new releases of + r5r in synchrony with R5, the development of R5 follows Conveyal's + independent update process. Hence, users should confirm the R5 version + implied by the Conveyal user manual (see + ) corresponds with the R5 version + that r5r depends on. This version of r5r depends on R5 v7.1. + date_publication: '2024-04-11' + bug_reports: https://github.com/ipeaGIT/r5r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r5r + url_git: https://github.com/ipeaGIT/r5r +R6: + version: 2.6.1 + title: Encapsulated Classes with Reference Semantics + maintainer: Winston Chang + description: |- + Creates classes with reference semantics, similar to R's + built-in reference classes. Compared to reference classes, R6 classes + are simpler and lighter-weight, and they are not built on S4 classes + so they do not require the methods package. These classes allow public + and private members, and they support inheritance, even when the + classes are defined in different packages. + date_publication: '2025-02-15' + bug_reports: https://github.com/r-lib/R6/issues + url: https://r6.r-lib.org + url_cran: https://CRAN.R-project.org/package=R6 + url_git: https://github.com/r-lib/R6 +R62S3: + version: 1.4.1 + title: Automatic Method Generation from R6 + maintainer: Raphael Sonabend + description: After defining an R6 class, R62S3 is used to automatically generate + optional S3/S4 generics and methods for dispatch. Also allows piping for R6 objects. + date_publication: '2020-03-09' + bug_reports: https://github.com/RaphaelS1/R62S3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R62S3 + url_git: https://github.com/RaphaelS1/R62S3/ +R6causal: + version: 0.8.3 + title: R6 Class for Structural Causal Models + maintainer: Juha Karvanen + description: The implemented R6 class 'SCM' aims to simplify working with structural + causal models. The missing data mechanism can be defined as a part of the structural + model. The class contains methods for 1) defining a structural causal model via + functions, text or conditional probability tables, 2) printing basic information + on the model, 3) plotting the graph for the model using packages 'igraph' or 'qgraph', + 4) simulating data from the model, 5) applying an intervention, 6) checking the + identifiability of a query using the R packages 'causaleffect' and 'dosearch', + 7) defining the missing data mechanism, 8) simulating incomplete data from the + model according to the specified missing data mechanism and 9) checking the identifiability + in a missing data problem using the R package 'dosearch'. In addition, there are + functions for running experiments and doing counterfactual inference using simulation. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=R6causal + url_git: '' +R6DS: + version: 1.2.0 + title: R6 Reference Class Based Data Structures + maintainer: Yukai Yang + description: |- + Provides reference classes implementing some useful data structures. + The package implements these data structures by using the reference class R6. + Therefore, the classes of the data structures are also reference classes which means that their instances are passed by reference. + The implemented data structures include stack, queue, double-ended queue, doubly linked list, set, dictionary and binary search tree. + See for example for more information about the data structures. + date_publication: '2019-05-21' + bug_reports: https://github.com/yukai-yang/R6DS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=R6DS + url_git: https://github.com/yukai-yang/R6DS +r6extended: + version: 0.1.2 + title: Extension for 'R6' Base Class + maintainer: Peter Meissner + description: |- + Useful methods and data fields to extend the + bare bones 'R6' class provided by the 'R6' package - ls-method, + hashes, warning- and message-method, general get-method and a + debug-method that assigns self and private to the global environment. + date_publication: '2019-02-12' + bug_reports: https://github.com/petermeissner/r6extended/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r6extended + url_git: https://github.com/petermeissner/r6extended +r6methods: + version: 0.1.0 + title: Make Methods for R6 Classes + maintainer: Jakub Sobolewski + description: |- + Generate boilerplate code for R6 classes. Given R6 class create getters + and/or setters for selected class fields or use RStudio addins to insert methods + straight into class definition. + date_publication: '2021-03-16' + bug_reports: https://github.com/jakubsob/r6methods/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r6methods + url_git: https://github.com/jakubsob/r6methods +R6P: + version: 0.4.0 + title: Design Patterns in R + maintainer: Harel Lustiger + description: |- + Build robust and maintainable software with object-oriented design + patterns in R. Design patterns abstract and present in neat, well-defined + components and interfaces the experience of many software designers and + architects over many years of solving similar problems. These are solutions + that have withstood the test of time with respect to re-usability, + flexibility, and maintainability. 'R6P' provides abstract base classes with + examples for a few known design patterns. The patterns were selected by + their applicability to analytic projects in R. Using these patterns in R + projects have proven effective in dealing with the complexity that + data-driven applications possess. + date_publication: '2024-12-22' + bug_reports: https://github.com/tidylab/R6P/issues + url: https://tidylab.github.io/R6P/ + url_cran: https://CRAN.R-project.org/package=R6P + url_git: https://github.com/tidylab/R6P +r6qualitytools: + version: 1.0.1 + title: R6-Based Statistical Methods for Quality Science + maintainer: Fabian Encarnacion + description: A comprehensive suite of statistical tools for Quality Management, + designed around the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle + used in Six Sigma methodology. Based on the discontinued CRAN package 'qualitytools', + this package refactors its original design by incorporating 'R6' object-oriented + programming for increased flexibility and performance. It replaces traditional + graphics with modern, interactive visualizations using 'ggplot2' and 'plotly'. + Built on 'tidyverse' principles, it simplifies data manipulation and visualization, + offering an intuitive approach to quality science. + date_publication: '2024-10-03' + bug_reports: https://github.com/Fabianenc/r6qualitytools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=r6qualitytools + url_git: https://github.com/Fabianenc/r6qualitytools +ra4bayesmeta: + version: 1.0-8 + title: Reference Analysis for Bayesian Meta-Analysis + maintainer: Manuela Ott + description: Functionality for performing a principled reference analysis in the + Bayesian normal-normal hierarchical model used for Bayesian meta-analysis, as + described in Ott, Plummer and Roos (2021) . Computes a reference + posterior, induced by a minimally informative improper reference prior for the + between-study (heterogeneity) standard deviation. Determines additional proper + anti-conservative (and conservative) prior benchmarks. Includes functions for + reference analyses at both the posterior and the prior level, which, given the + data, quantify the informativeness of a heterogeneity prior of interest relative + to the minimally informative reference prior and the proper prior benchmarks. + The functions operate on data sets which are compatible with the 'bayesmeta' package. + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ra4bayesmeta + url_git: '' +rabi: + version: 1.0.2 + title: |- + Generate Codes to Uniquely and Robustly Identify Individuals for + Animal Behavior Studies + maintainer: Andrew Taylor Burchill + description: 'Facilitates the design and generation of optimal color (or symbol) + codes that can be used to mark and identify individual animals. These codes are + made such that the IDs are robust to partial erasure: even if sections of the + code are lost, the entire identity of the animal can be reconstructed. Thus, animal + subjects are not confused and no ambiguity is introduced.' + date_publication: '2019-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rabi + url_git: '' +RABR: + version: 0.1.1 + title: Simulations for Response Adaptive Block Randomization Design + maintainer: Tianyu Zhan + description: Conduct simulations of the Response Adaptive Block Randomization (RABR) + design to evaluate its type I error rate, power and operating characteristics + for binary and continuous endpoints. For more details of the proposed method, + please refer to Zhan et al. (2021) . + date_publication: '2022-08-17' + bug_reports: https://github.com/tian-yu-zhan/RABR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RABR + url_git: https://github.com/tian-yu-zhan/RABR +RAC: + version: 1.5.5 + title: R Package for Aqua Culture + maintainer: Baldan D. + description: Solves the individual bioenergetic balance for different aquaculture + sea fish (Sea Bream and Sea Bass; Brigolin et al., 2014 ) + and shellfish (Mussel and Clam; Brigolin et al., 2009 ; + Solidoro et al., 2000 ). Allows for spatialized model + runs and population simulations. + date_publication: '2023-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RAC + url_git: '' +racademyocean: + version: 0.3.3 + title: Client for 'AcademyOcean API' + maintainer: Alexey Seleznev + description: |- + Provide function for work with 'AcademyOcean API' + . + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=racademyocean + url_git: '' +RaceID: + version: 0.3.9 + title: |- + Identification of Cell Types, Inference of Lineage Trees, and + Prediction of Noise Dynamics from Single-Cell RNA-Seq Data + maintainer: Dominic Grün + description: Application of 'RaceID' allows inference of cell types and prediction + of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) + ). 'VarID2' is part of this package and allows quantification + of biological gene expression noise at single-cell resolution (Rosales-Alvarez, + R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, + D. (2023) ). + date_publication: '2024-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RaceID + url_git: '' +raceland: + version: 1.2.1 + title: |- + Pattern-Based Zoneless Method for Analysis and Visualization of + Racial Topography + maintainer: Jakub Nowosad + description: |- + Implements a computational framework for a pattern-based, + zoneless analysis, and visualization of (ethno)racial topography + (Dmowska, Stepinski, and Nowosad (2020) ). + It is a reimagined + approach for analyzing residential segregation and racial diversity based on + the concept of 'landscape’ used in the domain of landscape ecology. + date_publication: '2023-04-14' + bug_reports: https://github.com/Nowosad/raceland/issues + url: https://jakubnowosad.com/raceland/ + url_cran: https://CRAN.R-project.org/package=raceland + url_git: '' +racir: + version: 2.0.0 + title: Rapid A/Ci Response (RACiR) Data Analysis + maintainer: Joseph Stinziano + description: |- + Contains functions useful for reading in Licor 6800 files, + correcting and analyzing rapid A/Ci response (RACiR) data. Requires some + user interaction to adjust the calibration (empty chamber) data file to + a useable range. Calibration uses a 1st to 5th order polynomial as + suggested in Stinziano et al. (2017) . + Data can be processed individually or batch processed for all files paired + with a given calibration file. RACiR is a trademark of LI-COR Biosciences, + and used with permission. + date_publication: '2020-08-03' + bug_reports: https://github.com/jstinzi/racir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=racir + url_git: https://github.com/jstinzi/racir +Racmacs: + version: 1.2.9 + title: Antigenic Cartography Macros + maintainer: Sam Wilks + description: |- + A toolkit for making antigenic maps from immunological assay data, + in order to quantify and visualize antigenic differences between different + pathogen strains as described in + Smith et al. (2004) and used in the World + Health Organization influenza vaccine strain selection process. Additional + functions allow for the diagnostic evaluation of antigenic maps and an + interactive viewer is provided to explore antigenic relationships amongst + several strains and incorporate the visualization of associated genetic + information. + date_publication: '2023-11-30' + bug_reports: https://github.com/acorg/Racmacs/issues + url: https://acorg.github.io/Racmacs/ + url_cran: https://CRAN.R-project.org/package=Racmacs + url_git: https://github.com/acorg/Racmacs/ +ractivecampaign: + version: 0.2.0 + title: Loading Data from 'ActiveCampaign API v3' + maintainer: Alexey Seleznev + description: |- + Interface for loading data from 'ActiveCampaign API v3' + . Provide functions + for getting data by deals, contacts, accounts, campaigns and messages. + date_publication: '2021-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ractivecampaign + url_git: '' +rADA: + version: 1.1.9 + title: Statistical Analysis and Cut-Point Determination of Immunoassays + maintainer: Emma Gail + description: Systematically transform immunoassay data, evaluate if the data is + normally distributed, and pick the right method for cut point determination based + on that evaluation. This package can also produce plots that are needed for reports, + so data analysis and visualization can be done easily. + date_publication: '2021-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rADA + url_git: '' +radar: + version: 1.0.0 + title: Fundamental Formulas for Radar + maintainer: Jose' Gama + description: |- + Fundamental formulas for Radar, for attenuation, range, velocity, + effectiveness, power, scatter, doppler, geometry, radar equations, etc. + Based on Nick Guy's Python package PyRadarMet + date_publication: '2014-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=radar + url_git: '' +radarBoxplot: + version: 1.0.5 + title: Implementation of the Radar-Boxplot + maintainer: Caio Hamamura + description: |- + Creates the radar-boxplot, a plot that was created by the + author during his Ph.D. in forest resources. + The radar-boxplot is a visualization feature suited for + multivariate classification/clustering. It provides an intuitive + deep understanding of the data. + date_publication: '2021-10-07' + bug_reports: https://github.com/caiohamamura/radarBoxplot-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=radarBoxplot + url_git: https://github.com/caiohamamura/radarBoxplot-R +radarchart: + version: 0.3.1 + title: Radar Chart from 'Chart.js' + maintainer: Doug Ashton + description: |- + Create interactive radar charts using the 'Chart.js' 'JavaScript' library + and the 'htmlwidgets' package. 'Chart.js' is a + lightweight library that supports several types of simple chart using the 'HTML5' + canvas element. This package provides an R interface specifically to the + radar chart, sometimes called a spider chart, for visualising multivariate data. + date_publication: '2016-12-20' + bug_reports: https://github.com/mangothecat/radarchart/issues + url: '' + url_cran: https://CRAN.R-project.org/package=radarchart + url_git: https://github.com/mangothecat/radarchart +RadData: + version: 1.0.2 + title: Nuclear Decay Data for Dosimetric Calculations - ICRP 107 + maintainer: Mark Hogue + description: |- + Nuclear Decay Data for Dosimetric Calculations from the + International Commission on Radiological Protection from ICRP + Publication 107. Ann. ICRP 38 (3). Eckerman, Keith and Endo, Akira 2008 + + . + This is a database of the physical data needed in calculations of + radionuclide-specific protection and operational quantities. The + data is prescribed by the ICRP, the international authority on + radiation dose standards, for estimating dose from the intake of or + exposure to radionuclides in the workplace and the environment. + The database contains information on the half-lives, decay chains, + and yields and energies of radiations emitted in nuclear transformations + of 1252 radionuclides of 97 elements. + date_publication: '2024-04-12' + bug_reports: https://github.com/markhogue/RadData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RadData + url_git: https://github.com/markhogue/RadData +RadEro: + version: 1.0.5 + title: Cs-137 Conversion Model + maintainer: Arturo Catala + description: |- + A straightforward model to estimate soil migration rates across various soil contexts. + Based on the compartmental, vertically-resolved, physically-based mass balance model of Soto and Navas (2004) + and Soto and Navas (2008) . + 'RadEro' provides a user-friendly interface in R, utilizing input data such as 137Cs inventories and parameters directly derived + from soil samples (e.g., fine fraction density, effective volume) to accurately capture the 137Cs distribution within the soil profile. + The model simulates annual 137Cs fallout, radioactive decay, and vertical diffusion, with the diffusion coefficient calculated + from 137Cs reference inventory profiles. Additionally, it allows users to input custom parameters as calibration coefficients. + The RadEro user manual and protocol, including detailed instructions on how to format input data and configuration files, can be found at the following link: . + date_publication: '2024-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RadEro + url_git: '' +RadialVisGadgets: + version: 0.2.0 + title: Interactive Gadgets for Radial Visualization Approaches + maintainer: José Matute + description: Shiny-based interactive gadgets of radial visualization methods and + extensions thereof. + date_publication: '2020-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RadialVisGadgets + url_git: https://github.com/jmatute/RadialShinyGadgets +radiant: + version: 1.6.6 + title: Business Analytics using R and Shiny + maintainer: Vincent Nijs + description: |- + A platform-independent browser-based interface for business + analytics in R, based on the shiny package. The application combines the + functionality of 'radiant.data', 'radiant.design', 'radiant.basics', + 'radiant.model', and 'radiant.multivariate'. + date_publication: '2024-05-21' + bug_reports: https://github.com/radiant-rstats/radiant/issues + url: '' + url_cran: https://CRAN.R-project.org/package=radiant + url_git: https://github.com/radiant-rstats/radiant +radiant.basics: + version: 1.6.6 + title: 'Basics Menu for Radiant: Business Analytics using R and Shiny' + maintainer: Vincent Nijs + description: |- + The Radiant Basics menu includes interfaces for probability + calculation, central limit theorem simulation, comparing means and proportions, + goodness-of-fit testing, cross-tabs, and correlation. The application extends + the functionality in 'radiant.data'. + date_publication: '2024-05-15' + bug_reports: https://github.com/radiant-rstats/radiant.basics/issues/ + url: https://radiant-rstats.github.io/radiant.basics/ + url_cran: https://CRAN.R-project.org/package=radiant.basics + url_git: https://github.com/radiant-rstats/radiant.basics/ +radiant.data: + version: 1.6.7 + title: 'Data Menu for Radiant: Business Analytics using R and Shiny' + maintainer: Vincent Nijs + description: |- + The Radiant Data menu includes interfaces for loading, saving, + viewing, visualizing, summarizing, transforming, and combining data. It also + contains functionality to generate reproducible reports of the analyses + conducted in the application. + date_publication: '2024-10-23' + bug_reports: https://github.com/radiant-rstats/radiant.data/issues/ + url: https://radiant-rstats.github.io/radiant.data/ + url_cran: https://CRAN.R-project.org/package=radiant.data + url_git: https://github.com/radiant-rstats/radiant.data/ +radiant.design: + version: 1.6.6 + title: 'Design Menu for Radiant: Business Analytics using R and Shiny' + maintainer: Vincent Nijs + description: |- + The Radiant Design menu includes interfaces for design of + experiments, sampling, and sample size calculation. The application extends + the functionality in 'radiant.data'. + date_publication: '2024-05-15' + bug_reports: https://github.com/radiant-rstats/radiant.design/issues/ + url: https://radiant-rstats.github.io/radiant.design/ + url_cran: https://CRAN.R-project.org/package=radiant.design + url_git: https://github.com/radiant-rstats/radiant.design/ +radiant.model: + version: 1.6.7 + title: 'Model Menu for Radiant: Business Analytics using R and Shiny' + maintainer: Vincent Nijs + description: |- + The Radiant Model menu includes interfaces for linear and logistic + regression, naive Bayes, neural networks, classification and regression trees, + model evaluation, collaborative filtering, decision analysis, and simulation. + The application extends the functionality in 'radiant.data'. + date_publication: '2024-10-11' + bug_reports: https://github.com/radiant-rstats/radiant.model/issues/ + url: https://radiant-rstats.github.io/radiant.model/ + url_cran: https://CRAN.R-project.org/package=radiant.model + url_git: https://github.com/radiant-rstats/radiant.model/ +radiant.multivariate: + version: 1.6.6 + title: |- + Multivariate Menu for Radiant: Business Analytics using R and + Shiny + maintainer: Vincent Nijs + description: |- + The Radiant Multivariate menu includes interfaces for perceptual + mapping, factor analysis, cluster analysis, and conjoint analysis. The + application extends the functionality in 'radiant.data'. + date_publication: '2024-05-20' + bug_reports: https://github.com/radiant-rstats/radiant.multivariate/issues/ + url: https://radiant-rstats.github.io/radiant.multivariate/ + url_cran: https://CRAN.R-project.org/package=radiant.multivariate + url_git: https://github.com/radiant-rstats/radiant.multivariate/ +RadioSonde: + version: '4.2' + title: Tools for Plotting Skew-T Diagrams and Wind Profiles + maintainer: Doug Nychka + description: |- + A + collection of programs for + plotting SKEW-T,log p diagrams and wind profiles for data + collected by radiosondes (the typical weather balloon-borne + instrument). The format of this plot with companion lines to + assess atmospheric stability are both standard in meteorology + and difficult to create from basic graphics functions. Hence + this package. One novel feature is being able add several + profiles to the same plot for comparison. + Use "help(ExampleSonde)" for an explanation of the variables + needed and how they should be named in a data frame. See + for the package home page. + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RadioSonde + url_git: '' +radir: + version: 1.0.4 + title: Inverse-Regression Estimation of Radioactive Doses + maintainer: David Moriña Soler + description: Radioactive doses estimation using individual chromosomal aberrations + information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015) . + date_publication: '2019-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=radir + url_git: '' +radlibs: + version: 0.2.0 + title: Build Your Own Madlibs! + maintainer: Stephanie Kirmer + description: |- + Make your phrase or sentence into something funny! Pass a string with the keywords in, + and get out a bit of humor. + date_publication: '2020-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=radlibs + url_git: '' +RadOnc: + version: 1.1.9 + title: Analytical Tools for Radiation Oncology + maintainer: Reid F. Thompson + description: Designed for the import, analysis, and visualization of dosimetric + and volumetric data in Radiation Oncology, the tools herein enable import of dose-volume + histogram information from multiple treatment planning system platforms and 3D + structural representations and dosimetric information from 'DICOM-RT' files. These + tools also enable subsequent visualization and statistical analysis of these data. + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RadOnc + url_git: '' +radous: + version: 0.1.3 + title: Query Random User Data from the Random User Generator API + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Generate random user data from the Random User Generator API. + For more information, see . + date_publication: '2021-05-23' + bug_reports: https://github.com/feddelegrand7/radous/issues + url: '' + url_cran: https://CRAN.R-project.org/package=radous + url_git: https://github.com/feddelegrand7/radous +radsafer: + version: 2.3.0 + title: Radiation Safety + maintainer: Mark Hogue + description: |- + Provides functions for radiation safety, also known as + "radiation protection" and "radiological control". The science of + radiation protection is called "health physics" and its engineering + functions are called "radiological engineering". Functions in this + package cover many of the computations needed by radiation safety + professionals. Examples include: obtaining updated calibration and + source check values for radiation monitors to account for radioactive + decay in a reference source, simulating instrument readings to better + understand measurement uncertainty, correcting instrument readings + for geometry and ambient atmospheric conditions. Many of these + functions are described in Johnson and Kirby (2011, ISBN-13: + 978-1609134198). Utilities are also included for developing inputs + and processing outputs with radiation transport codes, such as MCNP, + a general-purpose Monte Carlo N-Particle code that can be used for + neutron, photon, electron, or coupled neutron/photon/electron transport + (Werner et. al. (2018) ). + date_publication: '2023-07-12' + bug_reports: https://github.com/markhogue/radsafer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=radsafer + url_git: https://github.com/markhogue/radsafer +RADstackshelpR: + version: 0.1.0 + title: Optimize the De Novo Stacks Pipeline via R + maintainer: Devon DeRaad + description: |- + Offers a handful of useful wrapper functions which streamline + the reading, analyzing, and visualizing of variant call format (vcf) files in R. + This package was designed to facilitate an explicit pipeline for optimizing + Stacks (Rochette et al., 2019) () + parameters during de novo (without a reference genome) assembly and variant + calling of restriction-enzyme associated DNA sequence (RADseq) data. The + pipeline implemented here is based on the 2017 paper "Lost in Parameter Space" + (Paris et al., 2017) () which + establishes clear recommendations for optimizing the parameters + 'm', 'M', and 'n', during the process of assembling loci. + date_publication: '2021-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RADstackshelpR + url_git: '' +Radviz: + version: 0.9.3 + title: Project Multidimensional Data in 2D Space + maintainer: Yann Abraham + description: |- + An implementation of the radviz projection in R. It enables the visualization of + multidimensional data while maintaining the relation to the original dimensions. + This package provides functions to create and plot radviz projections, and a number of summary + plots that enable comparison and analysis. For reference see Ankerst *et al.* (1996) + () for original implementation, + see Di Caro *et al* (2012) () + for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) + () for the original Freeviz implementation. + date_publication: '2022-03-25' + bug_reports: https://github.com/yannabraham/Radviz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Radviz + url_git: https://github.com/yannabraham/Radviz +RAdwords: + version: 0.1.18 + title: Loading Google Adwords Data into R + maintainer: Johannes Burkhardt + description: |- + Aims at loading Google Adwords data into R. Adwords is an online + advertising service that enables advertisers to display advertising copy to web + users (see for more information). + Therefore the package implements three main features. First, the package + provides an authentication process for R with the Google Adwords API (see + for more information) via OAUTH2. + Second, the package offers an interface to apply the Adwords query language in + R and query the Adwords API with ad-hoc reports. Third, the received data are + transformed into suitable data formats for further data processing and data + analysis. + date_publication: '2019-01-28' + bug_reports: https://github.com/jburkhardt/RAdwords/issues + url: https://developers.google.com/adwords + url_cran: https://CRAN.R-project.org/package=RAdwords + url_git: https://github.com/jburkhardt/RAdwords +raem: + version: 0.1.0 + title: |- + Analytic Element Modeling of Steady Single-Layer Groundwater + Flow + maintainer: Cas Neyens + description: |- + A model of single-layer groundwater flow in steady-state + under the Dupuit-Forchheimer assumption can be created by placing + elements such as wells, area-sinks and line-sinks at arbitrary + locations in the flow field. Output variables include hydraulic head + and the discharge vector. Particle traces can be computed numerically + in three dimensions. The underlying theory is described in Haitjema + (1995) and references + therein. + date_publication: '2024-08-23' + bug_reports: https://github.com/cneyens/raem/issues + url: https://cneyens.github.io/raem/ + url_cran: https://CRAN.R-project.org/package=raem + url_git: https://github.com/cneyens/raem +rafalib: + version: 1.0.0 + title: Convenience Functions for Routine Data Exploration + maintainer: Rafael A. Irizarry + description: A series of shortcuts for routine tasks originally developed by Rafael + A. Irizarry to facilitate data exploration. + date_publication: '2015-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rafalib + url_git: '' +RAFS: + version: 0.2.5 + title: Robust Aggregative Feature Selection + maintainer: Radosław Piliszek + description: |- + A cross-validated minimal-optimal feature selection algorithm. + It utilises popularity counting, hierarchical clustering with feature dissimilarity measures, + and prefiltering with all-relevant feature selection method to obtain the minimal-optimal set of features. + date_publication: '2025-01-29' + bug_reports: '' + url: https://www.mdfs.it/ + url_cran: https://CRAN.R-project.org/package=RAFS + url_git: '' +rafsi: + version: 0.0.2 + title: Ranking of Alternatives with the RAFSI Method + maintainer: Mateus Vanzetta + description: |- + Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval Method is designed to perform multi-criteria decision-making (MCDM), developed by Mališa Žižovic in 2020 (). + It calculates the final sorted rankings based on a decision matrix where rows represent alternatives + and columns represent criteria. The method uses: + - A numeric vector of weights for each criterion (the sum of weights must be 1). + - A numeric vector of ideal values for each criterion. + - A numeric vector of anti-ideal values for each criterion. + - Numeric values representing the extent to which the ideal value is preferred over the anti-ideal value, + and the extent to which the anti-ideal value is considered worse. + The function standardizes the decision matrix, normalizes the data, applies weights, and returns the + final sorted rankings. + date_publication: '2024-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rafsi + url_git: '' +Rage: + version: 1.8.0 + title: Life History Metrics from Matrix Population Models + maintainer: Owen Jones + description: |- + Functions for calculating life history metrics using matrix + population models ('MPMs'). Described in Jones et al. (2021) + . + date_publication: '2025-01-07' + bug_reports: https://github.com/jonesor/Rage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rage + url_git: https://github.com/jonesor/Rage +ragg: + version: 1.3.3 + title: Graphic Devices Based on AGG + maintainer: Thomas Lin Pedersen + description: |- + Anti-Grain Geometry (AGG) is a high-quality and + high-performance 2D drawing library. The 'ragg' package provides a set + of graphic devices based on AGG to use as alternative to the raster + devices provided through the 'grDevices' package. + date_publication: '2024-09-11' + bug_reports: https://github.com/r-lib/ragg/issues + url: https://ragg.r-lib.org + url_cran: https://CRAN.R-project.org/package=ragg + url_git: https://github.com/r-lib/ragg +RagGrid: + version: 0.2.0 + title: A Wrapper of the 'JavaScript' Library 'agGrid' + maintainer: Srikkanth M + description: |- + Data objects in 'R' can be rendered as 'HTML' tables using the + 'JavaScript' library 'ag-grid' (typically via 'R Markdown' or 'Shiny'). The + 'ag-grid' library has been included in this 'R' package. The package name + 'RagGrid' is an abbreviation of 'R agGrid'. + date_publication: '2018-08-12' + bug_reports: https://github.com/no-types/RagGrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RagGrid + url_git: https://github.com/no-types/RagGrid/ +rags2ridges: + version: 2.2.7 + title: |- + Ridge Estimation of Precision Matrices from High-Dimensional + Data + maintainer: Carel F.W. Peeters + description: |- + Proper L2-penalized maximum likelihood estimators for precision + matrices and supporting functions to employ these estimators in a graphical + modeling setting. For details, see Peeters, Bilgrau, & van Wieringen (2022) + and associated publications. + date_publication: '2023-10-14' + bug_reports: '' + url: https://cfwp.github.io/rags2ridges/ + url_cran: https://CRAN.R-project.org/package=rags2ridges + url_git: https://github.com/CFWP/rags2ridges +ragtop: + version: 1.1.1 + title: Pricing Equity Derivatives with Extensions of Black-Scholes + maintainer: Brian K. Boonstra + description: |- + Algorithms to price American and European + equity options, convertible bonds and a + variety of other financial derivatives. It uses an + extension of the usual Black-Scholes model in which + jump to default may occur at a probability specified + by a power-law link between stock price and hazard + rate as found in the paper by Takahashi, Kobayashi, + and Nakagawa (2001) . We + use ideas and techniques from Andersen and + Buffum (2002) and + Linetsky (2006) . + date_publication: '2020-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ragtop + url_git: '' +rai: + version: 1.0.0 + title: Revisiting-Alpha-Investing for Polynomial Regression + maintainer: Kory D. Johnson + description: |- + A modified implementation of stepwise regression that greedily searches + the space of interactions among features in order to build polynomial regression models. + Furthermore, the hypothesis tests conducted are valid-post model selection + due to the use of a revisiting procedure that implements an alpha-investing + rule. As a result, the set of rejected sequential hypotheses is proven to + control the marginal false discover rate. When not searching for polynomials, + the package provides a statistically valid algorithm + to run and terminate stepwise regression. For more information, see + Johnson, Stine, and Foster (2019) . + date_publication: '2019-07-02' + bug_reports: https://github.com/korydjohnson/rai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rai + url_git: https://github.com/korydjohnson/rai +rainbow: + version: '3.8' + title: Bagplots, Boxplots and Rainbow Plots for Functional Data + maintainer: Han Lin Shang + description: Visualizing functional data and identifying functional outliers. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rainbow + url_git: '' +RAINBOWR: + version: 0.1.35 + title: Genome-Wide Association Study with SNP-Set Methods + maintainer: Kosuke Hamazaki + description: 'By using ''RAINBOWR'' (Reliable Association INference By Optimizing + Weights with R), users can test multiple SNPs (Single Nucleotide Polymorphisms) + simultaneously by kernel-based (SNP-set) methods. This package can also be applied + to haplotype-based GWAS (Genome-Wide Association Study). Users can test not only + additive effects but also dominance and epistatic effects. In detail, please check + our paper on PLOS Computational Biology: Kosuke Hamazaki and Hiroyoshi Iwata (2020) + .' + date_publication: '2024-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RAINBOWR + url_git: '' +raincin: + version: 1.0.3 + title: Ranking with Incomplete Information + maintainer: Jiangtao Gou + description: 'Various statistical and mathematical ranking and rating methods with + incomplete information are included. This package is initially designed for the + scoring system in a high school project showcase to rank student research projects, + where each judge can only evaluate a set of projects in a limited time period. + See Langville, A. N. and Meyer, C. D. (2012), Who is Number 1: The Science of + Rating and Ranking, Princeton University Press , and + Gou, J. and Wu, S. (2020), A Judging System for Project Showcase: Rating and Ranking + with Incomplete Information, Technical Report.' + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=raincin + url_git: '' +rainette: + version: 0.3.1.1 + title: The Reinert Method for Textual Data Clustering + maintainer: Julien Barnier + description: |- + An R implementation of the Reinert text clustering method. For more + details about the algorithm see the included vignettes or Reinert (1990) + . + date_publication: '2023-03-28' + bug_reports: https://github.com/juba/rainette/issues + url: https://juba.github.io/rainette/ + url_cran: https://CRAN.R-project.org/package=rainette + url_git: '' +RainfallErosivityFactor: + version: 1.0.0 + title: The Rainfall-Runoff Erosivity Factor + maintainer: Dione Pereira Cardoso + description: Determination of rainfall-runoff erosivity factor. + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RainfallErosivityFactor + url_git: '' +rainfarmr: + version: '0.1' + title: Stochastic Precipitation Downscaling with the RainFARM Method + maintainer: Jost von Hardenberg + description: An implementation of the RainFARM (Rainfall Filtered Autoregressive + Model) stochastic precipitation downscaling method (Rebora et al. (2006) ). + Adapted for climate downscaling according to D'Onofrio et al. (2018) + and for complex topography as in Terzago et al. (2018) . + The RainFARM method is based on the extrapolation to small scales of the Fourier + spectrum of a large-scale precipitation field, using a fixed logarithmic slope + and random phases at small scales, followed by a nonlinear transformation of the + resulting linearly correlated stochastic field. RainFARM allows to generate ensembles + of spatially downscaled precipitation fields which conserve precipitation at large + scales and whose statistical properties are consistent with the small-scale statistics + of observed precipitation, based only on knowledge of the large-scale precipitation + field. + date_publication: '2019-04-09' + bug_reports: https://github.com/jhardenberg/rainfarmr + url: '' + url_cran: https://CRAN.R-project.org/package=rainfarmr + url_git: https://github.com/jhardenberg/rainfarmr +rairtable: + version: 0.1.2 + title: Efficient Wrapper for the 'Airtable' API + maintainer: Matthew Rogers + description: Efficient CRUD interface for the 'Airtable' API , + supporting batch requests and parallel encoding of large data sets. + date_publication: '2023-04-02' + bug_reports: https://github.com/matthewjrogers/rairtable/issues + url: https://matthewjrogers.github.io/rairtable/ + url_cran: https://CRAN.R-project.org/package=rairtable + url_git: '' +RaJIVE: + version: '1.0' + title: Robust Angle Based Joint and Individual Variation Explained + maintainer: Erica Ponzi + description: 'A robust alternative to the aJIVE (angle based Joint and Individual + Variation Explained) method (Feng et al 2018: ) + for the estimation of joint and individual components in the presence of outliers + in multi-source data. It decomposes the multi-source data into joint, individual + and residual (noise) contributions. The decomposition is robust to outliers and + noise in the data. The method is illustrated in Ponzi et al (2021) .' + date_publication: '2021-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RaJIVE + url_git: '' +rakeR: + version: 0.2.1 + title: Easy Spatial Microsimulation (Raking) in R + maintainer: Phil Mike Jones + description: |- + Functions for performing spatial microsimulation ('raking') + in R. + date_publication: '2017-10-10' + bug_reports: https://github.com/philmikejones/rakeR/issues + url: https://philmikejones.github.io/rakeR/ + url_cran: https://CRAN.R-project.org/package=rakeR + url_git: '' +ralger: + version: 2.2.4 + title: Easy Web Scraping + maintainer: Mohamed El Fodil Ihaddaden + description: The goal of 'ralger' is to facilitate web scraping in R. + date_publication: '2021-03-17' + bug_reports: https://github.com/feddelegrand7/ralger/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ralger + url_git: https://github.com/feddelegrand7/ralger +RALSA: + version: 1.5.5 + title: R Analyzer for Large-Scale Assessments + maintainer: Plamen V. Mirazchiyski + description: |- + Download, prepare and analyze data from large-scale assessments and + surveys with complex sampling and assessment design (see 'Rutkowski', + 2010 ). Such studies are, for example, + international assessments like 'TIMSS', 'PIRLS' and 'PISA'. A graphical + interface is available for the non-technical user.The package includes + functions to covert the original data from 'SPSS' into 'R' data sets + keeping the user-defined missing values, merge data from different + respondents and/or countries, generate variable dictionaries, modify + data, produce descriptive statistics (percentages, means, percentiles, + benchmarks) and multivariate statistics (correlations, linear + regression, binary logistic regression). The number of supported + studies and analysis types will increase in future. For a general + presentation of the package, see 'Mirazchiyski', 2021a + (). For detailed technical aspects of + the package, see 'Mirazchiyski', 2021b (). + date_publication: '2025-02-24' + bug_reports: '' + url: https://ralsa.ineri.org/ + url_cran: https://CRAN.R-project.org/package=RALSA + url_git: '' +RamanMP: + version: '1.0' + title: Analysis and Identification of Raman Spectra of Microplastics + maintainer: Veronica Nava + description: Pre-processing and polymer identification of Raman spectra of plastics. + Pre-processing includes normalisation functions, peak identification based on + local maxima, smoothing process and removal of spectral region of no interest. + Polymer identification can be performed using Pearson correlation coefficient + or Euclidean distance (Renner et al. (2019), ), + and the comparison can be done with a user-defined database or with the database + already implemented in the package, which currently includes 356 spectra, with + several spectra of plastic colorants. + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RamanMP + url_git: '' +Ramble: + version: 0.1.1 + title: Parser Combinator for R + maintainer: Chapman Siu + description: |- + Parser generator for R using combinatory parsers. It + is inspired by combinatory parsers developed in Haskell. + date_publication: '2016-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ramble + url_git: https://github.com/chappers/Ramble +rAmCharts: + version: 2.1.16 + title: JavaScript Charts Tool + maintainer: Benoit Thieurmel + description: |- + Provides an R interface for using 'AmCharts' Library. Based on + 'htmlwidgets', it provides a global architecture to generate 'JavaScript' source + code for charts. Most of classes in the library have their equivalent in R + with S4 classes; for those classes, not all properties have been referenced but + can easily be added in the constructors. Complex properties (e.g. 'JavaScript' + object) can be passed as named list. See examples at + + and for + more information about the library. The package includes the free version + of 'AmCharts' Library. Its only limitation is a small link to the web site + displayed on your charts. If you enjoy this library, do not hesitate to refer + to this page to purchase a licence, + and thus support its creators and get a period of Priority Support. See also + for more information about 'AmCharts' company. + date_publication: '2025-01-13' + bug_reports: https://github.com/datastorm-open/rAmCharts/issues/ + url: https://datastorm-open.github.io/introduction_ramcharts/ + url_cran: https://CRAN.R-project.org/package=rAmCharts + url_git: '' +rAmCharts4: + version: 1.6.0 + title: Interface to the JavaScript Library 'amCharts 4' + maintainer: Stéphane Laurent + description: 'Creates JavaScript charts. The charts can be included in ''Shiny'' + apps and R markdown documents, or viewed from the R console and ''RStudio'' viewer. + Based on the JavaScript library ''amCharts 4'' and the R packages ''htmlwidgets'' + and ''reactR''. Currently available types of chart are: vertical and horizontal + bar chart, radial bar chart, stacked bar chart, vertical and horizontal Dumbbell + chart, line chart, scatter chart, range area chart, gauge chart, boxplot chart, + pie chart, and 100% stacked bar chart.' + date_publication: '2022-09-22' + bug_reports: https://github.com/stla/rAmCharts4/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rAmCharts4 + url_git: https://github.com/stla/rAmCharts4 +ramchoice: + version: '2.2' + title: |- + Revealed Preference and Attention Analysis in Random Limited + Attention Models + maintainer: Xinwei Ma + description: It is widely documented in psychology, economics and other disciplines + that socio-economic agent may not pay full attention to all available alternatives, + rendering standard revealed preference theory invalid. This package implements + the estimation and inference procedures of Cattaneo, Ma, Masatlioglu and Suleymanov + (2020) and Cattaneo, Cheung, Ma, and Masatlioglu (2022) , + which utilizes standard choice data to partially identify and estimate a decision + maker's preference and attention. For inference, several simulation-based critical + values are provided. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ramchoice + url_git: '' +RAMClustR: + version: 1.3.1 + title: |- + Mass Spectrometry Metabolomics Feature Clustering and + Interpretation + maintainer: Helge Hecht + description: 'A feature clustering algorithm for non-targeted mass spectrometric + metabolomics data. This method is compatible with gas and liquid chromatography + coupled mass spectrometry, including indiscriminant tandem mass spectrometry data + .' + date_publication: '2023-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RAMClustR + url_git: https://github.com/cbroeckl/RAMClustR +ramcmc: + version: 0.1.2 + title: Robust Adaptive Metropolis Algorithm + maintainer: Jouni Helske + description: |- + Function for adapting the shape of the random walk Metropolis proposal + as specified by robust adaptive Metropolis algorithm by Vihola (2012) . + The package also includes fast functions for rank-one Cholesky update and downdate. + These functions can be used directly from R or the corresponding C++ header files + can be easily linked to other R packages. + date_publication: '2021-10-06' + bug_reports: https://github.com/helske/ramcmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ramcmc + url_git: '' +rameritrade: + version: 0.1.5 + title: '''TD Ameritrade'' API Interface for R' + maintainer: Anthony Balentine + description: |- + Use R to interface with the 'TD Ameritrade' API . + Functions include authentication, trading, price requests, account information, and option + chains. A user will need a TD brokerage account and TD Ameritrade developer app. See README + for authentication process and examples. + date_publication: '2021-02-22' + bug_reports: https://github.com/exploringfinance/rameritrade/issues + url: https://exploringfinance.github.io/rameritrade/ + url_cran: https://CRAN.R-project.org/package=rameritrade + url_git: '' +ramify: + version: 0.3.3 + title: Additional Matrix Functionality + maintainer: Brandon Greenwell + description: |- + Additional matrix functionality for R including: (1) wrappers for + the base matrix function that allow matrices to be created from character + strings and lists (the former is especially useful for creating block + matrices), (2) better printing of large matrices via the generic "pretty" + print function, and (3) a number of convenience functions for users more + familiar with other scientific languages like 'Julia', 'Matlab'/'Octave', or + 'Python'+'NumPy'. + date_publication: '2016-12-17' + bug_reports: https://github.com/bgreenwell/ramify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ramify + url_git: https://github.com/bgreenwell/ramify +ramlegacy: + version: 0.2.0 + title: Download and Read RAM Legacy Stock Assessment Database + maintainer: Kshitiz Gupta + description: |- + Contains functions to download, cache and read in 'Excel' version of the + RAM Legacy Stock Assessment Data Base, an online compilation of stock assessment + results for commercially exploited marine populations from around the world. + The database is named after Dr. Ransom A. Myers whose original stock-recruitment database, + is no longer being updated. More information about the database can be found at + . Ricard, D., Minto, C., Jensen, O.P. and Baum, J.K. (2012) . + date_publication: '2019-05-16' + bug_reports: https://github.com/ropensci/ramlegacy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ramlegacy + url_git: https://github.com/ropensci/ramlegacy +RAMP: + version: 2.0.2 + title: Regularized Generalized Linear Models with Interaction Effects + maintainer: Yang Feng + description: |- + Provides an efficient procedure for fitting the entire solution + path for high-dimensional regularized quadratic generalized linear models with + interactions effects under the strong or weak heredity constraint. + date_publication: '2020-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RAMP + url_git: '' +RAMpath: + version: 0.5.1 + title: |- + Structural Equation Modeling Using the Reticular Action Model + (RAM) Notation + maintainer: Zhiyong Zhang + description: We rewrite of RAMpath software developed by John McArdle and Steven + Boker as an R package. In addition to performing regular SEM analysis through + the R package lavaan, RAMpath has unique features. First, it can generate path + diagrams according to a given model. Second, it can display path tracing rules + through path diagrams and decompose total effects into their respective direct + and indirect effects as well as decompose variance and covariance into individual + bridges. Furthermore, RAMpath can fit dynamic system models automatically based + on latent change scores and generate vector field plots based upon results obtained + from a bivariate dynamic system. Starting version 0.4, RAMpath can conduct power + analysis for both univariate and bivariate latent change score models. + date_publication: '2023-08-27' + bug_reports: '' + url: https://nd.psychstat.org + url_cran: https://CRAN.R-project.org/package=RAMpath + url_git: '' +ramps: + version: 0.6.18 + title: Bayesian Geostatistical Modeling with RAMPS + maintainer: Brian J Smith + description: |- + Bayesian geostatistical modeling of Gaussian processes using a + reparameterized and marginalized posterior sampling (RAMPS) algorithm + designed to lower autocorrelation in MCMC samples. Package performance is + tuned for large spatial datasets. + date_publication: '2023-03-13' + bug_reports: '' + url: https://www.jstatsoft.org/v25/i10 + url_cran: https://CRAN.R-project.org/package=ramps + url_git: '' +RaMS: + version: 1.4.3 + title: R Access to Mass-Spec Data + maintainer: William Kumler + description: |- + R-based access to mass-spectrometry (MS) data. While many packages + exist to process MS data, many of these make it difficult to + access the underlying mass-to-charge ratio (m/z), intensity, and + retention time of the files + themselves. This package is designed to format MS data in a tidy fashion and + allows the user perform the plotting and analysis. + date_publication: '2024-10-09' + bug_reports: https://github.com/wkumler/RaMS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RaMS + url_git: https://github.com/wkumler/RaMS +ramsvm: + version: '2.3' + title: Reinforced Angle-Based Multicategory Support Vector Machines + maintainer: Shannon T. Holloway + description: |- + Provides a solution path for Reinforced Angle-based Multicategory + Support Vector Machines, with linear learning, polynomial learning, and + Gaussian kernel learning. C. Zhang, Y. Liu, J. Wang and H. Zhu. (2016) + . + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ramsvm + url_git: '' +randChecks: + version: 0.2.1 + title: |- + Covariate Balance Checks: Randomization Tests and Graphical + Diagnostics + maintainer: Zach Branson + description: Provides randomization tests and graphical diagnostics for assessing + randomized assignment and covariate balance for a binary treatment variable. See + Branson (2021) for details. + date_publication: '2021-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randChecks + url_git: '' +randcorr: + version: '1.0' + title: Generate a Random p x p Correlation Matrix + maintainer: Daniel F. Schmidt + description: Implements the algorithm by Pourahmadi and Wang (2015) + for generating a random p x p correlation matrix. Briefly, the idea is to represent + the correlation matrix using Cholesky factorization and p(p-1)/2 hyperspherical + coordinates (i.e., angles), sample the angles from a particular distribution and + then convert to the standard correlation matrix form. The angles are sampled from + a distribution with pdf proportional to sin^k(theta) (0 < theta < pi, k >= 1) + using the efficient sampling algorithm described in Enes Makalic and Daniel F. + Schmidt (2018) . + date_publication: '2018-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randcorr + url_git: '' +randgeo: + version: 0.3.0 + title: Generate Random 'WKT' or 'GeoJSON' + maintainer: Scott Chamberlain + description: |- + Generate random positions (latitude/longitude), + Well-known text ('WKT') points or polygons, or 'GeoJSON' points or + polygons. + date_publication: '2018-05-18' + bug_reports: https://github.com/ropensci/randgeo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=randgeo + url_git: https://github.com/ropensci/randgeo +RandMeta: + version: 0.1.0 + title: |- + Efficient Numerical Algorithm for Exact Inference in Meta + Analysis + maintainer: Lu Tian + description: A novel numerical algorithm that provides functionality for estimating + the exact 95% confidence interval of the location parameter in the random effects + model, and is much faster than the naive method. Works best when the number of + studies is between 6-20. + date_publication: '2017-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RandMeta + url_git: '' +randnet: + version: '0.7' + title: Random Network Model Estimation, Selection and Parameter Tuning + maintainer: Tianxi Li + description: Model selection and parameter tuning procedures for a class of random + network models. The model selection can be done by a general cross-validation + framework called ECV from Li et. al. (2016) . Several other + model-based and task-specific methods are also included, such as NCV from Chen + and Lei (2016) , likelihood ratio method from Wang and Bickel + (2015) , spectral methods from Le and Levina (2015) . + Many network analysis methods are also implemented, such as the regularized spectral + clustering (Amini et. al. 2013 ) and its degree corrected + version and graphon neighborhood smoothing (Zhang et. al. 2015 ). + It also includes the consensus clustering of Gao et. al. (2014) , + the method of moments estimation of nomination SBM of Li et. al. (2020) , + and the network mixing method of Li and Le (2021) . It also + includes the informative core-periphery data processing method of Miao and Li + (2021) . The work to build and improve this package is partially + supported by the NSF grants DMS-2015298 and DMS-2015134. + date_publication: '2023-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randnet + url_git: '' +rando: + version: 0.2.0 + title: Context Aware Random Numbers + maintainer: Michael Barrowman + description: |- + Provides random number generating functions that + are much more context aware than the built-in functions. The + functions are also much safer, as they check for incompatible + values, and more reproducible. + date_publication: '2021-02-16' + bug_reports: https://github.com/MyKo101/rando/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rando + url_git: https://github.com/MyKo101/rando +random: + version: 0.2.6 + title: True Random Numbers using RANDOM.ORG + maintainer: Dirk Eddelbuettel + description: |- + The true random number service provided by the RANDOM.ORG + website created by Mads Haahr samples atmospheric noise via radio tuned to + an unused broadcasting frequency together with a skew correction algorithm + due to John von Neumann. More background is available in the included + vignette based on an essay by Mads Haahr. In its current form, the package + offers functions to retrieve random integers, randomized sequences and + random strings. + date_publication: '2017-02-05' + bug_reports: '' + url: https://www.random.org + url_cran: https://CRAN.R-project.org/package=random + url_git: '' +random.cdisc.data: + version: 0.3.16 + title: Create Random ADaM Datasets + maintainer: Joe Zhu + description: |- + A set of functions to create random Analysis Data Model + (ADaM) datasets and cached dataset. ADaM dataset specifications are + described by the Clinical Data Interchange Standards Consortium + (CDISC) Analysis Data Model Team. + date_publication: '2024-10-10' + bug_reports: https://github.com/insightsengineering/random.cdisc.data/issues + url: https://insightsengineering.github.io/random.cdisc.data/ + url_cran: https://CRAN.R-project.org/package=random.cdisc.data + url_git: https://github.com/insightsengineering/random.cdisc.data/ +random.polychor.pa: + version: 1.1.4-5 + title: A Parallel Analysis with Polychoric Correlation Matrices + maintainer: Fabio Presaghi + description: The Function performs a parallel analysis using simulated polychoric + correlation matrices. The nth-percentile of the eigenvalues distribution obtained + from both the randomly generated and the real data polychoric correlation matrices + is returned. A plot comparing the two types of eigenvalues (real and simulated) + will help determine the number of real eigenvalues that outperform random data. + The function is based on the idea that if real data are non-normal and the polychoric + correlation matrix is needed to perform a Factor Analysis, then the Parallel Analysis + method used to choose a non-random number of factors should also be based on randomly + generated polychoric correlation matrices and not on Pearson correlation matrices. + Random data sets are simulated assuming or a uniform or a multinomial distribution + or via the bootstrap method of resampling (i.e., random permutations of cases). + Also Multigroup Parallel analysis is made available for random (uniform and multinomial + distribution and with or without difficulty factor) and bootstrap methods. An + option to choose between default or full output is also available as well as a + parameter to print Fit Statistics (Chi-squared, TLI, RMSEA, RMR and BIC) for the + factor solutions indicated by the Parallel Analysis. Also weighted correlation + matrices may be considered for PA. + date_publication: '2023-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=random.polychor.pa + url_git: '' +randomcoloR: + version: 1.1.0.1 + title: Generate Attractive Random Colors + maintainer: Ron Ammar + description: |- + Simple methods to generate attractive random colors. The random + colors are from a wrapper of 'randomColor.js' + . In addition, it also generates + optimally distinct colors based on k-means (inspired by 'IWantHue' + ). + date_publication: '2019-11-24' + bug_reports: https://github.com/ronammar/randomcoloR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=randomcoloR + url_git: '' +randomForest: + version: 4.7-1.2 + title: |- + Breiman and Cutlers Random Forests for Classification and + Regression + maintainer: Andy Liaw + description: Classification and regression based on a forest of trees using random + inputs, based on Breiman (2001) . + date_publication: '2024-09-22' + bug_reports: '' + url: https://www.stat.berkeley.edu/~breiman/RandomForests/ + url_cran: https://CRAN.R-project.org/package=randomForest + url_git: '' +randomForestExplainer: + version: 0.10.1 + title: |- + Explaining and Visualizing Random Forests in Terms of Variable + Importance + maintainer: Yue Jiang + description: A set of tools to help explain which variables are most important in + a random forests. Various variable importance measures are calculated and visualized + in different settings in order to get an idea on how their importance changes + depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski + and Andy J. Minn and Michael S. Lauer (2010) , + Leo Breiman (2001) ). + date_publication: '2020-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomForestExplainer + url_git: https://github.com/ModelOriented/randomForestExplainer +RandomForestsGLS: + version: 0.1.5 + title: Random Forests for Dependent Data + maintainer: Arkajyoti Saha + description: Fits non-linear regression models on dependant data with Generalised + Least Square (GLS) based Random Forest (RF-GLS) detailed in Saha, Basu and Datta + (2021) . + date_publication: '2024-10-02' + bug_reports: https://github.com/ArkajyotiSaha/RandomForestsGLS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RandomForestsGLS + url_git: https://github.com/ArkajyotiSaha/RandomForestsGLS +randomForestSRC: + version: 3.3.3 + title: |- + Fast Unified Random Forests for Survival, Regression, and + Classification (RF-SRC) + maintainer: Udaya B. Kogalur + description: Fast OpenMP parallel computing of Breiman's random forests for univariate, + multivariate, unsupervised, survival, competing risks, class imbalanced classification + and quantile regression. New Mahalanobis splitting for correlated outcomes. Extreme + random forests and randomized splitting. Suite of imputation methods for missing + data. Fast random forests using subsampling. Confidence regions and standard + errors for variable importance. New improved holdout importance. Case-specific + importance. Minimal depth variable importance. Visualize trees on your Safari + or Google Chrome browser. Anonymous random forests for data privacy. + date_publication: '2025-01-16' + bug_reports: https://github.com/kogalur/randomForestSRC/issues/ + url: https://www.randomforestsrc.org/https://ishwaran.org/ + url_cran: https://CRAN.R-project.org/package=randomForestSRC + url_git: '' +randomForestVIP: + version: 0.1.3 + title: Tune Random Forests Based on Variable Importance & Plot Results + maintainer: Kelvyn Bladen + description: |- + Functions for assessing variable relations and associations + prior to modeling with a Random Forest algorithm (although these are + relevant for any predictive model). + Metrics such as partial correlations and variance inflation factors + are tabulated as well as plotted for the user. A function is available + for tuning the main Random Forest hyper-parameter based on model performance + and variable importance metrics. This grid-search technique provides + tables and plots showing the effect of the main hyper-parameter on each + of the assessment metrics. It also returns each of the evaluated models + to the user. The package also provides superior variable importance plots + for individual models. All of the plots are developed so that the + user has the ability to edit and improve further upon the + plots. Derivations and methodology are described in Bladen (2022) + . + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomForestVIP + url_git: https://github.com/KelvynBladen/randomForestVIP +randomGLM: + version: 1.10-1 + title: Random General Linear Model Prediction + maintainer: Peter Langfelder + description: |- + A bagging predictor based on generalized linear models (GLMs) is implemented. The method is published in + Song, Langfelder and Horvath (2013) . + date_publication: '2022-04-10' + bug_reports: '' + url: https://horvath.genetics.ucla.edu/rglm/ + url_cran: https://CRAN.R-project.org/package=randomGLM + url_git: '' +randomizationInference: + version: 1.0.4 + title: Flexible Randomization-Based Inference + maintainer: Joseph J. Lee + description: Allows the user to conduct randomization-based inference for a wide + variety of experimental scenarios. The package leverages a potential outcomes + framework to output randomization-based p-values and null intervals for test statistics + geared toward any estimands of interest, according to the specified null and alternative + hypotheses. Users can define custom randomization schemes so that the randomization + distributions are accurate for their experimental settings. The package also creates + visualizations of randomization distributions and can test multiple test statistics + simultaneously. + date_publication: '2022-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomizationInference + url_git: '' +randomizeBE: + version: 0.3-6 + title: Create a Random List for Crossover Studies + maintainer: D. Labes + description: |- + Contains a function to randomize subjects, patients in groups of + sequences (treatment sequences). + If a blocksize is given, the randomization will be done within blocks. + The randomization may be controlled by a Wald-Wolfowitz runs test. + Functions to obtain the p-value of that test are included. + The package is mainly intended for randomization of bioequivalence studies + but may be used also for other clinical crossover studies. + Contains two helper functions sequences() and williams() to get the sequences + of commonly used designs in BE studies. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomizeBE + url_git: '' +randomizeR: + version: 3.0.2 + title: Randomization for Clinical Trials + maintainer: Ralf-Dieter Hilgers + description: |- + This tool enables the user to choose a randomization procedure + based on sound scientific criteria. It comprises the generation of + randomization sequences as well the assessment of randomization procedures + based on carefully selected criteria. Furthermore, 'randomizeR' provides a + function for the comparison of randomization procedures. + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomizeR + url_git: '' +randomizr: + version: 1.0.0 + title: |- + Easy-to-Use Tools for Common Forms of Random Assignment and + Sampling + maintainer: Alexander Coppock + description: |- + Generates random assignments for common experimental designs and + random samples for common sampling designs. + date_publication: '2023-08-10' + bug_reports: https://github.com/DeclareDesign/randomizr/issues + url: https://declaredesign.org/r/randomizr/ + url_cran: https://CRAN.R-project.org/package=randomizr + url_git: https://github.com/DeclareDesign/randomizr +randomLCA: + version: 1.1-4 + title: Random Effects Latent Class Analysis + maintainer: Ken Beath + description: Fits standard and random effects latent class models. The single level + random effects model is described in Qu et al and the two + level random effects model in Beath and Heller . + Examples are given for their use in diagnostic testing. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomLCA + url_git: '' +randomMachines: + version: 0.1.0 + title: An Ensemble Modeling using Random Machines + maintainer: Mateus Maia + description: A novel ensemble method employing Support Vector Machines (SVMs) as + base learners. This powerful ensemble model is designed for both classification + (Ara A., et. al, 2021) , and regression (Ara A., et. al, + 2021) problems, offering versatility and robust + performance across different datasets and compared with other consolidated methods + as Random Forests (Maia M, et. al, 2021) . + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomMachines + url_git: '' +randomNames: + version: 1.6-0.0 + title: Generate Random Given and Surnames + maintainer: Damian W. Betebenner + description: Function for generating random gender and ethnicity correct first and/or + last names. Names are chosen proportionally based upon their probability of appearing + in a large scale data base of real names. + date_publication: '2024-05-04' + bug_reports: https://github.com/CenterForAssessment/randomNames/issues/ + url: https://centerforassessment.github.io/randomNames/ + url_cran: https://CRAN.R-project.org/package=randomNames + url_git: https://github.com/CenterForAssessment/randomNames/ +RandomProjectionTest: + version: 0.1.4 + title: Two-Sample Test in High Dimensions using Random Projection + maintainer: Juan Ortiz Author + description: Performs the random projection test (Lopes et al., (2011) ) + for the one-sample and two-sample hypothesis testing problem for equality of means + in the high dimensional setting. We are interested in detecting the mean vector + in the one-sample problem or the difference between mean vectors in the two-sample + problem. + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RandomProjectionTest + url_git: '' +randomUniformForest: + version: 1.1.6 + title: |- + Random Uniform Forests for Classification, Regression and + Unsupervised Learning + maintainer: Saip Ciss + description: |- + Ensemble model, for classification, regression + and unsupervised learning, based on a forest of unpruned + and randomized binary decision trees. Each tree is grown + by sampling, with replacement, a set of variables at each node. + Each cut-point is generated randomly, according to the continuous + Uniform distribution. For each tree, data are either bootstrapped + or subsampled. The unsupervised mode introduces clustering, dimension reduction + and variable importance, using a three-layer engine. Random Uniform Forests are mainly + aimed to lower correlation between trees (or trees residuals), to provide a deep analysis + of variable importance and to allow native distributed and incremental learning. + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randomUniformForest + url_git: '' +Randomuseragent: + version: 0.0.1 + title: Filtering and Randomly Sampling Real User-Agent Strings + maintainer: Fangzhou Xie + description: |- + Based on data of real user-agent strings, we can set filtering conditions + and randomly sample user-agent strings from the user-agent string pool. + date_publication: '2021-06-17' + bug_reports: https://github.com/fangzhou-xie/randomuseragent/issues + url: https://fangzhou-xie.github.io/Randomuseragent/index.html + url_cran: https://CRAN.R-project.org/package=Randomuseragent + url_git: https://github.com/fangzhou-xie/Randomuseragent +RandomWalker: + version: 0.2.0 + title: Generate Random Walks Compatible with the 'tidyverse' + maintainer: Steven Sanderson + description: |- + Generates random walks of various types by providing a set of functions + that are compatible with the 'tidyverse'. The functions provided in the package + make it simple to create random walks with a variety of properties, such as + how many simulations to run, how many steps to take, and the distribution of + random walk itself. + date_publication: '2024-10-23' + bug_reports: https://github.com/spsanderson/RandomWalker/issues + url: https://www.spsanderson.com/RandomWalker/ + url_cran: https://CRAN.R-project.org/package=RandomWalker + url_git: https://github.com/spsanderson/RandomWalker +RandPro: + version: 0.2.2 + title: Random Projection with Classification + maintainer: Siddharth R + description: Performs random projection using Johnson-Lindenstrauss (JL) Lemma (see + William B.Johnson and Joram Lindenstrauss (1984) ). + Random Projection is a dimension reduction technique, where the data in the high + dimensional space is projected into the low dimensional space using JL transform. + The original high dimensional data matrix is multiplied with the low dimensional + projection matrix which results in reduced matrix. The projection matrix can be + generated using the projection function that is independent to the original data. + Then finally apply the classification task on the projected data. + date_publication: '2020-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RandPro + url_git: '' +randquotes: + version: 0.1.1 + title: Get Random Quotes from Quotes on Design API + maintainer: AbdulMajedRaja RS + description: |- + Connects to the site + that uses the 'WordPress' built-in REST API + to provide a way for you to grab quotes. + date_publication: '2019-10-25' + bug_reports: https://github.com/amrrs/randquotes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=randquotes + url_git: https://github.com/amrrs/randquotes +randtests: + version: 1.0.2 + title: Testing Randomness in R + maintainer: Frederico Caeiro + description: Provides several non parametric randomness tests for numeric sequences. + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randtests + url_git: '' +randtoolbox: + version: 2.0.5 + title: |- + Toolbox for Pseudo and Quasi Random Number Generation and Random + Generator Tests + maintainer: Christophe Dutang + description: |- + Provides (1) pseudo random generators - general linear congruential generators, + multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister + algorithm () and WELL () + generators); (2) quasi random generators - the Torus algorithm, the + Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some + generator tests - the gap test, the serial test, the poker test, see, e.g., + Gentle (2003) . + Take a look at the Distribution task view of types and tests of random number generators. + The package can be provided without the 'rngWELL' dependency on demand. + Package in Memoriam of Diethelm and Barbara Wuertz. + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=randtoolbox + url_git: https://r-forge.r-project.org/projects/rmetrics/ +RandVar: + version: 1.2.5 + title: Implementation of Random Variables + maintainer: Matthias Kohl + description: Implements random variables by means of S4 classes and methods. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RandVar + url_git: https://r-forge.r-project.org/projects/robast/ +rang: + version: 0.3.0 + title: Reconstructing Reproducible R Computational Environments + maintainer: Chung-hong Chan + description: Resolve the dependency graph of R packages at a specific time point + based on the information from various 'R-hub' web services . + The dependency graph can then be used to reconstruct the R computational environment + with 'Rocker' . + date_publication: '2023-10-08' + bug_reports: https://github.com/gesistsa/rang/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rang + url_git: https://github.com/gesistsa/rang +rangeBuilder: + version: '2.2' + title: |- + Occurrence Filtering, Geographic Standardization and Generation + of Species Range Polygons + maintainer: Pascal Title + description: Provides tools for filtering occurrence records, generating alpha-hull-derived + range polygons and mapping species distributions. + date_publication: '2024-10-30' + bug_reports: https://github.com/ptitle/rangeBuilder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rangeBuilder + url_git: https://github.com/ptitle/rangeBuilder +rangeMapper: + version: 2.0.3 + title: A Platform for the Study of Macro-Ecology of Life History Traits + maintainer: Mihai Valcu + description: Tools for generation of (life-history) traits and diversity maps on + hexagonal or square grids. Valcu et al.(2012) . + date_publication: '2022-10-03' + bug_reports: https://github.com/mpio-be/rangeMapper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rangeMapper + url_git: https://github.com/mpio-be/rangeMapper +rangeModelMetadata: + version: 0.1.5 + title: |- + Provides Templates for Metadata Files Associated with Species + Range Models + maintainer: Cory Merow + description: |- + Range Modeling Metadata Standards (RMMS) address three challenges: + they (i) are designed for convenience to encourage use, (ii) accommodate a wide + variety of applications, and (iii) are extensible to allow the community of range + modelers to steer it as needed. RMMS are based on a data dictionary that specifies + a hierarchical structure to catalog different aspects of the range modeling process. + The dictionary balances a constrained, minimalist vocabulary to improve + standardization with flexibility for users to provide their own values. + Merow et al. (2019) describe the standards in + more detail. Note that users who prefer to use the R package 'ecospat' can obtain it from + . + date_publication: '2023-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rangeModelMetadata + url_git: '' +rangemodelR: + version: 1.0.6 + title: Mid-Domain Effect and Species Richness + maintainer: Aniruddha Marathe + description: |- + Used for generating randomized community matrices under + strict range cohesion. The package can handle data where species occurrence + are recorded across sites ordered along gradients such as elevation and latitude, as well as species occurrences recorded on spatial grids with known geographic coordinates. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rangemodelR + url_git: '' +ranger: + version: 0.17.0 + title: A Fast Implementation of Random Forests + maintainer: Marvin N. Wright + description: |- + A fast implementation of Random Forests, particularly suited for high + dimensional data. Ensembles of classification, regression, survival and + probability prediction trees are supported. Data from genome-wide association + studies can be analyzed efficiently. In addition to data frames, datasets of + class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') + can be directly analyzed. + date_publication: '2024-11-08' + bug_reports: https://github.com/imbs-hl/ranger/issues + url: https://imbs-hl.github.io/ranger/ + url_cran: https://CRAN.R-project.org/package=ranger + url_git: https://github.com/imbs-hl/ranger +RanglaPunjab: + version: 2.3.4 + title: Displays Palette of 5 Colors + maintainer: Sonia Ahluwalia + description: |- + Displays palette of 5 colors based on photos depicting the unique + and vibrant culture of Punjab in Northern India. Since Punjab translates + to ``Land of 5 Rivers'' there are 5 colors per palette. If users need + more than 5 colors, they can merge 2 to 3 palettes to create their own + color-combination, or they can cherry-pick their own custom colors. + Users can view up to 3 palettes together. Users can also list all the + palette choices. And last but not least, users can see the photo that + inspired a particular palette. + date_publication: '2018-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RanglaPunjab + url_git: '' +rangr: + version: 1.0.6 + title: Mechanistic Simulation of Species Range Dynamics + maintainer: Katarzyna Markowska + description: |- + Integrates population dynamics and dispersal into a mechanistic + virtual species simulator. The package can be used to study the effects of + environmental change on population growth and range shifts. It allows for + simple and straightforward definition of population dynamics (including + positive density dependence), extensive possibilities for defining dispersal + kernels, and the ability to generate virtual ecologist data. Learn more about + the 'rangr' at . + date_publication: '2025-02-26' + bug_reports: https://github.com/ropensci/rangr/issues + url: https://docs.ropensci.org/rangr/ + url_cran: https://CRAN.R-project.org/package=rangr + url_git: https://github.com/ropensci/rangr +rank: + version: 0.1.1 + title: Customisable Ranking of Numerical and Categorical Data + maintainer: Sam El-Kamand + description: |- + Provides a flexible alternative to the built-in rank() function called smartrank(). + Optionally rank categorical variables by frequency (instead of in alphabetical order), and control whether ranking is based on descending/ascending order. + smartrank() is suitable for both numerical and categorical data. + date_publication: '2024-12-01' + bug_reports: https://github.com/selkamand/rank/issues + url: https://selkamand.github.io/rank/ + url_cran: https://CRAN.R-project.org/package=rank + url_git: https://github.com/selkamand/rank +RankAggreg: + version: 0.6.6 + title: Weighted Rank Aggregation + maintainer: Vasyl Pihur + description: |- + Performs aggregation of ordered lists based + on the ranks using several different algorithms: + Cross-Entropy Monte Carlo algorithm, Genetic algorithm, and a + brute force algorithm (for small problems). + date_publication: '2020-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RankAggreg + url_git: '' +RankAggregator: + version: 0.0.1 + title: Aggregation of (Partial) Ordinal Rankings + maintainer: Jay Burns + description: |- + Easily compute an aggregate ranking (also called a median ranking or a + consensus ranking) according to the axiomatic approach presented + by Cook et al. (2007). This approach minimises the number of violations + between all candidate consensus rankings and all input (partial) rankings, + and draws on a branch and bound algorithm and a heuristic algorithm to + drastically improve speed. The package also provides an option to bootstrap + a consensus ranking based on resampling input rankings (with + replacement). Input rankings can be either incomplete (partial) or complete. + Reference: Cook, W.D., Golany, B., Penn, M. and Raviv, T. (2007) . + date_publication: '2020-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RankAggregator + url_git: '' +RankAggSIgFUR: + version: 1.0.0 + title: |- + Polynomially Bounded Rank Aggregation under Kemeny's Axiomatic + Approach + maintainer: Rakhi Singh + description: 'Polynomially bounded algorithms to aggregate complete rankings under + Kemeny''s axiomatic framework. ''RankAggSIgFUR'' (pronounced as rank-agg-cipher) + contains two heuristics algorithms: FUR and SIgFUR. For details, please see Badal + and Das (2018) .' + date_publication: '2023-06-19' + bug_reports: https://github.com/prakashvs613/RankAggSIgFUR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RankAggSIgFUR + url_git: https://github.com/prakashvs613/RankAggSIgFUR +Rankcluster: + version: 0.98.0 + title: Model-Based Clustering for Multivariate Partial Ranking Data + maintainer: Quentin Grimonprez + description: |- + Implementation of a model-based clustering algorithm for + ranking data (C. Biernacki, J. Jacques (2013) ). + Multivariate rankings as well as partial rankings are taken + into account. This algorithm is based on an extension of the Insertion + Sorting Rank (ISR) model for ranking data, which is a meaningful and + effective model parametrized by a position parameter (the modal ranking, + quoted by mu) and a dispersion parameter (quoted by pi). The heterogeneity + of the rank population is modelled by a mixture of ISR, whereas conditional + independence assumption is considered for multivariate rankings. + date_publication: '2022-11-12' + bug_reports: https://github.com/modal-inria/Rankcluster/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=Rankcluster + url_git: '' +rankCorr: + version: 1.0.1 + title: |- + Total, Between-, and Within-Cluster Spearman Rank Correlations + for Clustered Data + maintainer: Shengxin Tu + description: Estimates the total, between-, and within-cluster Spearman rank correlations + for continuous and ordinal clustered data. . + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rankCorr + url_git: '' +rankdifferencetest: + version: '2021-11-25' + title: Kornbrot's Rank Difference Test + maintainer: Brett Klamer + description: |- + Implements Kornbrot's rank difference test as described in + . This method is a modified + Wilcoxon signed-rank test which produces consistent and meaningful + results for ordinal or monotonically-transformed data. + date_publication: '2021-11-29' + bug_reports: '' + url: http://brettklamer.com/work/rankdifferencetest + url_cran: https://CRAN.R-project.org/package=rankdifferencetest + url_git: '' +rankdist: + version: 1.1.4 + title: Distance Based Ranking Models + maintainer: Zhaozhi Qian + description: |- + Implements distance based probability models for ranking data. + The supported distance metrics include Kendall distance, Spearman distance, Footrule distance, Hamming distance, + Weighted-tau distance and Weighted Kendall distance. + Phi-component model and mixture models are also supported. + date_publication: '2019-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rankdist + url_git: '' +rankFD: + version: 0.1.1 + title: Rank-Based Tests for General Factorial Designs + maintainer: Frank Konietschke + description: |- + The rankFD() function calculates the Wald-type statistic (WTS) and the ANOVA-type + statistic (ATS) for nonparametric factorial designs, e.g., for count, ordinal or score data + in a crossed design with an arbitrary number of factors. + Brunner, E., Bathke, A. and Konietschke, F. (2018) . + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rankFD + url_git: '' +rankhazard: + version: 1.1.0 + title: Rank-Hazard Plots + maintainer: Nanni Koski + description: Rank-hazard plots Karvanen and Harrell (2009) + visualize the relative importance of covariates in a proportional hazards model. + The key idea is to rank the covariate values and plot the relative hazard as a + function of ranks scaled to interval [0,1]. The relative hazard is plotted in + respect to the reference hazard, which can bee.g. the hazard related to the median + of the covariate. + date_publication: '2016-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rankhazard + url_git: '' +rankICC: + version: 1.0.2 + title: Rank Intraclass Correlation for Clustered Data + maintainer: Shengxin Tu + description: Estimates the rank intraclass correlation coefficient (ICC) for clustered + continuous and ordinal data. See Tu et al. (2023) for details. + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rankICC + url_git: '' +RankingProject: + version: 0.4.0 + title: 'The Ranking Project: Visualizations for Comparing Populations' + maintainer: Jerzy Wieczorek + description: |- + Functions to generate plots and tables for comparing independently- + sampled populations. Companion package to "A Primer on Visualizations + for Comparing Populations, Including the Issue of Overlapping Confidence + Intervals" by Wright, Klein, and Wieczorek (2019) + and "A Joint Confidence Region for an + Overall Ranking of Populations" by Klein, Wright, and Wieczorek (2020) + . + date_publication: '2022-01-28' + bug_reports: https://github.com/civilstat/RankingProject/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RankingProject + url_git: https://github.com/civilstat/RankingProject +rankinma: + version: 0.2.2 + title: Rank in Network Meta-Analysis + maintainer: Enoch Kang + description: A supportive collection of functions for gathering and plotting treatment + ranking metrics after network meta-analysis. + date_publication: '2024-04-01' + bug_reports: '' + url: https://rankinma.shinyapps.io/rankinma/ + url_cran: https://CRAN.R-project.org/package=rankinma + url_git: '' +rankinPlot: + version: 1.1.0 + title: |- + Convenient Plotting for the Modified Rankin Scale and Other + Ordinal Outcome Data + maintainer: Hannah Johns + description: Provides convenient tools for visualising ordinal outcome data following + the "Grotta Bar" approach pioneered by The National Institute of Neurological + Disorders and Stroke rt-PA Stroke Study Group (1995) . + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rankinPlot + url_git: '' +RankPCA: + version: 0.1.0 + title: |- + Rank of Variables Based on Principal Component Analysis for + Mixed Data Types + maintainer: Dr. Sandip Garai + description: Principal Component Analysis (PCA) is a statistical technique used + to reduce the dimensionality of a dataset while preserving as much variability + as possible. By transforming the original variables into a new set of uncorrelated + variables called principal components, PCA helps in identifying patterns and simplifying + the complexity of high-dimensional data. The 'RankPCA' package provides a streamlined + workflow for performing PCA on datasets containing both categorical and continuous + variables. It facilitates data preprocessing, encoding of categorical variables, + and computes PCA to determine the optimal number of principal components based + on a specified variance threshold. The package also computes composite indices + for ranking observations, which can be useful for various analytical purposes. + Garai, S., & Paul, R. K. (2023) . + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RankPCA + url_git: '' +rankrate: + version: 1.2.0 + title: |- + Joint Statistical Models for Preference Learning with Rankings + and Ratings + maintainer: Michael Pearce + description: Statistical tools for the Mallows-Binomial model, the first joint statistical + model for preference learning for rankings and ratings. + date_publication: '2023-08-17' + bug_reports: '' + url: https://pearce790.github.io/rankrate/ + url_cran: https://CRAN.R-project.org/package=rankrate + url_git: '' +RankResponse: + version: 4.0.0 + title: |- + Ranking Responses in a Single Response Question or a Multiple + Response Question + maintainer: Hsiuying Wang + description: |- + Methods for ranking responses of a single response question or a + multiple response question are described in the two papers: + 1. Wang, H. (2008). Ranking Responses in Multiple-Choice Questions. Journal of + Applied Statistics, 35, 465-474. + 2. Wang, H. and Huang, W. H. (2014). Bayesian Ranking Responses in Multiple + Response Questions. Journal of the Royal Statistical Society: Series A + (Statistics in Society), 177, 191-208. . + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RankResponse + url_git: '' +RANKS: + version: '1.1' + title: Ranking of Nodes with Kernelized Score Functions + maintainer: Giorgio Valentini + description: Implementation of Kernelized score functions and other semi-supervised + learning algorithms for node label ranking to analyze biomolecular networks. + RANKS can be easily applied to a large set of different relevant problems in computational + biology, ranging from automatic protein function prediction, to gene disease prioritization + and drug repositioning, and more in general to any bioinformatics problem that + can be formalized as a node label ranking problem in a graph. The modular nature + of the implementation allows to experiment with different score functions and + kernels and to easily compare the results with baseline network-based methods + such as label propagation and random walk algorithms, as well as to enlarge the + algorithmic scheme by adding novel user-defined score functions and kernels. + date_publication: '2022-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RANKS + url_git: '' +ranktreeEnsemble: + version: '0.23' + title: |- + Ensemble Models of Rank-Based Trees with Extracted Decision + Rules + maintainer: Min Lu + description: Fast computing an ensemble of rank-based trees via boosting or random + forest on binary and multi-class problems. It converts continuous gene expression + profiles into ranked gene pairs, for which the variable importance indices are + computed and adopted for dimension reduction. Decision rules can be extracted + from trees. + date_publication: '2024-05-24' + bug_reports: https://github.com/TransBioInfoLab/ranktreeEnsemble/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=ranktreeEnsemble + url_git: https://github.com/TransBioInfoLab/ranktreeEnsemble/ +RANN: + version: 2.6.2 + title: |- + Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 + Metric + maintainer: Gregory Jefferis + description: |- + Finds the k nearest neighbours for every point in a + given dataset in O(N log N) time using Arya and Mount's ANN library + (v1.1.3). There is support for approximate as well as exact searches, + fixed radius searches and 'bd' as well as 'kd' trees. The distance is + computed using the L2 (Euclidean) metric. Please see package 'RANN.L1' + for the same functionality using the L1 (Manhattan, taxicab) metric. + date_publication: '2024-08-25' + bug_reports: https://github.com/jefferislab/RANN/issues + url: https://jefferislab.github.io/RANN/ + url_cran: https://CRAN.R-project.org/package=RANN + url_git: https://github.com/jefferislab/RANN +Rapi: + version: 1.0.6 + title: Interface for Multiple Data Providers 'EDDS' and 'FRED' + maintainer: Sermet Pekin + description: |- + Interface for multiple data sources, such as the + `EDDS` API of the + Central Bank of the Republic of Türkiye and the + `FRED` API of the Federal Reserve Bank. + Both data providers require API keys for access, which users can easily obtain + by creating accounts on their respective websites. + The package provides caching ability with the selection of periods to increase the + speed and efficiency of requests. + It combines datasets requested from different sources, + helping users when the data has common frequencies. + While combining data frames whenever possible, it also keeps all requested data + available as separate data frames to increase efficiency. + date_publication: '2025-01-13' + bug_reports: https://github.com/DataRapi/Rapi/issues + url: https://DataRapi.github.io/Rapi/ + url_cran: https://CRAN.R-project.org/package=Rapi + url_git: https://github.com/DataRapi/Rapi +rapiclient: + version: 0.1.8 + title: Dynamic OpenAPI/Swagger Client + maintainer: Marcel Ramos + description: |- + Access services specified in OpenAPI (formerly Swagger) format. + It is not a code generator. Client is generated dynamically as a list of R + functions. + date_publication: '2024-09-30' + bug_reports: https://github.com/bergant/rapiclient/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rapiclient + url_git: https://github.com/bergant/rapiclient +RApiDatetime: + version: 0.0.9 + title: R API for 'Date' and 'Datetime' + maintainer: Dirk Eddelbuettel + description: |- + Access to the C-level R date and 'datetime' code is provided for + C-level API use by other packages via registration of native functions. + Client packages simply include a single header 'RApiDatetime.h' provided + by this package, and also 'import' it. The R Core group is the original + author of the code made available with slight modifications by this package. + date_publication: '2024-01-24' + bug_reports: https://github.com/eddelbuettel/rapidatetime/issues + url: https://dirk.eddelbuettel.com/code/rapidatetime.html + url_cran: https://CRAN.R-project.org/package=RApiDatetime + url_git: https://github.com/eddelbuettel/rapidatetime +RapidFuzz: + version: '1.0' + title: String Similarity Computation Using 'RapidFuzz' + maintainer: Andre Leite + description: Provides a high-performance interface for calculating string similarities + and distances, leveraging the efficient library 'RapidFuzz' . + This package integrates the 'C++' implementation, allowing 'R' users to access + cutting-edge algorithms for fuzzy matching and text analysis. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RapidFuzz + url_git: +rapidjsonr: + version: 1.2.0 + title: '''Rapidjson'' C++ Header Files' + maintainer: David Cooley + description: Provides JSON parsing capability through the 'Rapidjson' 'C++' header-only + library. + date_publication: '2020-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rapidjsonr + url_git: '' +rapidoc: + version: 9.3.4 + title: |- + Generates 'RapiDoc' Documentation from an 'OpenAPI' + Specification + maintainer: Bruno Tremblay + description: |- + A collection of 'HTML', 'JavaScript', 'CSS' and fonts + assets that generate 'RapiDoc' documentation from an 'OpenAPI' Specification: + . + date_publication: '2023-11-17' + bug_reports: https://github.com/meztez/rapidoc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rapidoc + url_git: https://github.com/meztez/rapidoc +RapidoPGS: + version: 2.3.1 + title: A Fast and Light Package to Compute Polygenic Risk Scores + maintainer: Guillermo Reales + description: 'Quickly computes polygenic scores from GWAS summary statistics of + either case-control or quantitative traits without parameter tuning. Reales,G., + Vigorito, E., Kelemen,M., Wallace,C. (2021) "RápidoPGS: + A rapid polygenic score calculator for summary GWAS data without a test dataset".' + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RapidoPGS + url_git: '' +rapidphylo: + version: 0.1.2 + title: |- + Rapidly Estimates Phylogeny from Large Allele Frequency Data + Using Root Distances Method + maintainer: Arindam RoyChoudhury + description: |- + Rapidly estimates tree-topology from large allele frequency + data using Root Distances Method, under a Brownian Motion Model. See + Peng et al. (2021) . + date_publication: '2023-02-01' + bug_reports: https://github.com/ArindamRoyChoudhury/rapidphylo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rapidphylo + url_git: https://github.com/ArindamRoyChoudhury/rapidphylo +RapidPolygonLookup: + version: 0.1.1 + title: POLYGON LOOKUP USING KD TREES + maintainer: Markus Loecher + description: |- + Facilitates efficient polygon search using kd trees. + Coordinate level spatial data can be aggregated to higher geographical + identities like census blocks, ZIP codes or police district boundaries. + This process requires mapping each point in the given data set to a + particular identity of the desired geographical hierarchy. Unless efficient + data structures are used, this can be a daunting task. The operation + point.in.polygon() from the package sp is computationally expensive. + Here, we exploit kd-trees as efficient nearest neighbor search algorithm + to dramatically reduce the effective number of polygons being searched. + date_publication: '2019-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RapidPolygonLookup + url_git: '' +rapidraker: + version: 0.1.3 + title: Rapid Automatic Keyword Extraction (RAKE) Algorithm + maintainer: Christopher Baker + description: |- + A 'Java' implementation of the RAKE algorithm ('Rose', S., 'Engel', D., + 'Cramer', N. and 'Cowley', W. (2010) ), which can + be used to extract keywords from documents without any training data. + date_publication: '2021-06-02' + bug_reports: https://github.com/crew102/rapidraker/issues + url: https://crew102.github.io/slowraker/articles/rapidraker.html + url_cran: https://CRAN.R-project.org/package=rapidraker + url_git: '' +rapidsplithalf: + version: '0.4' + title: A Fast Permutation-Based Split-Half Reliability Algorithm + maintainer: Sercan Kahveci + description: Accurately estimates the reliability of cognitive tasks using a fast + and flexible permutation-based split-half reliability algorithm that supports + stratified splitting while maintaining equal split sizes. See Kahveci, Bathke, + and Blechert (2022) for details. + date_publication: '2025-01-28' + bug_reports: https://github.com/Spiritspeak/rapidsplit/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=rapidsplithalf + url_git: '' +rapidxmlr: + version: 0.1.0 + title: '''Rapidxml'' C++ Header Files' + maintainer: David Cooley + description: Provides XML parsing capability through the 'Rapidxml' 'C++' header-only + library. + date_publication: '2019-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rapidxmlr + url_git: '' +RApiSerialize: + version: 0.1.4 + title: R API Serialization + maintainer: Dirk Eddelbuettel + description: |- + Access to the internal R serialization code is provided for + use by other packages at the C function level by using the registration of + native function mechanism. Client packages simply include a single header + file RApiSerializeAPI.h provided by this package. This packages builds on + the Rhpc package by Ei-ji Nakama and Junji Nakano which also includes a + (partial) copy of the file src/main/serialize.c from R itself. The R Core + group is the original author of the serialization code made available by + this package. + date_publication: '2024-09-28' + bug_reports: https://github.com/eddelbuettel/rapiserialize/issues + url: https://dirk.eddelbuettel.com/code/rapiserialize.html + url_cran: https://CRAN.R-project.org/package=RApiSerialize + url_git: https://github.com/eddelbuettel/rapiserialize +Rapp: + version: 0.2.0 + title: Easily Build Command Line Applications + maintainer: Tomasz Kalinowski + description: |- + Run simple 'R' scripts as command line applications, with + automatic robust and convenient support for command line arguments. + This package provides 'Rapp', an alternative 'R' front-end similar to + 'Rscript', that enables this. + date_publication: '2024-07-15' + bug_reports: https://github.com/r-lib/Rapp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rapp + url_git: https://github.com/r-lib/Rapp +RAppArmor: + version: 3.2.5 + title: Bindings to AppArmor and Security Related Linux Tools + maintainer: Jeroen Ooms + description: |- + Bindings to kernel methods for enforcing security restrictions. + AppArmor can apply mandatory access control (MAC) policies on a given task + (process) via security profiles with detailed ACL definitions. In addition + this package implements bindings for setting process resource limits (rlimit), + uid, gid, affinity and priority. The high level R function 'eval.secure' + builds on these methods to perform dynamic sandboxing: it evaluates a single + R expression within a temporary fork which acts as a sandbox by enforcing + fine grained restrictions without affecting the main R process. A portable + version of this function is now available in the 'unix' package. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/RAppArmor/issues + url: https://www.jstatsoft.org/v55/i07/https://jeroen.r-universe.dev/RAppArmor + url_cran: https://CRAN.R-project.org/package=RAppArmor + url_git: '' +rappdirs: + version: 0.3.3 + title: |- + Application Directories: Determine Where to Save Data, Caches, + and Logs + maintainer: Hadley Wickham + description: |- + An easy way to determine which directories on the + users computer you should use to save data, caches and logs. A port of + Python's 'Appdirs' () to + R. + date_publication: '2021-01-31' + bug_reports: https://github.com/r-lib/rappdirs/issues + url: https://rappdirs.r-lib.org + url_cran: https://CRAN.R-project.org/package=rappdirs + url_git: https://github.com/r-lib/rappdirs +rapport: + version: '1.1' + title: A Report Templating System + maintainer: Gergely Daróczi + description: |- + Facilitating the creation of reproducible statistical + report templates. Once created, rapport templates can be exported to + various external formats (HTML, LaTeX, PDF, ODT etc.) with pandoc as the + converter backend. + date_publication: '2021-04-11' + bug_reports: https://github.com/rapporter/rapport/issues + url: https://rapporter.github.io/rapport/ + url_cran: https://CRAN.R-project.org/package=rapport + url_git: '' +rapportools: + version: '1.2' + title: |- + Miscellaneous (Stats) Helper Functions with Sane Defaults for + Reporting + maintainer: Gergely Daróczi + description: |- + Helper functions that act as wrappers to more advanced statistical + methods with the advantage of having sane defaults for quick reporting. + date_publication: '2025-02-28' + bug_reports: https://github.com/rapporter/rapportools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rapportools + url_git: '' +rappsflyer: + version: 0.2.0 + title: Work with AppsFlyer API + maintainer: Alexey Seleznev + description: |- + Loading data from AppsFlyer Pull API + . + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rappsflyer + url_git: '' +rapsimng: + version: 0.4.4 + title: APSIM Next Generation + maintainer: Bangyou Zheng + description: |- + The Agricultural Production Systems sIMulator ('APSIM') is a widely + used to simulate the agricultural systems for multiple crops. This package + is designed to create, modify and run 'apsimx' files in the 'APSIM' Next + Generation . + date_publication: '2024-02-02' + bug_reports: https://github.com/byzheng/rapsimng/issues + url: https://rapsimng.bangyou.me/ + url_cran: https://CRAN.R-project.org/package=rapsimng + url_git: https://github.com/byzheng/rapsimng +RAPTOR: + version: 1.0.1 + title: Row and Position Tracheid Organizer + maintainer: Richard L. Peters + description: |- + Performs wood cell anatomical data analyses on spatially explicit xylem (tracheids) datasets + derived from thin sections of woody tissue. The package includes functions for visualisation, + detection and alignment of continuous tracheid radial file (defined as rows) and individual tracheid position + within an annual ring of coniferous species. This package is designed to be used with elaborate cell output, + e.g. as provided with ROXAS (von Arx & Carrer, 2014 ). The package has been validated for Picea abies, + Larix Siberica, Pinus cembra and Pinus sylvestris. + date_publication: '2020-03-09' + bug_reports: '' + url: https://the-hull.github.io/raptor/ + url_cran: https://CRAN.R-project.org/package=RAPTOR + url_git: https://github.com/the-hull/RAPTOR +raptr: + version: 1.0.1 + title: Representative and Adequate Prioritization Toolkit in R + maintainer: Jeffrey O Hanson + description: |- + Biodiversity is in crisis. The overarching aim of conservation + is to preserve biodiversity patterns and processes. To this end, protected + areas are established to buffer species and preserve biodiversity processes. + But resources are limited and so protected areas must be cost-effective. + This package contains tools to generate plans for protected areas + (prioritizations), using spatially explicit targets for biodiversity + patterns and processes. To obtain solutions in a feasible amount of time, + this package uses the commercial 'Gurobi' software (obtained from + ). For more information on using + this package, see Hanson et al. (2018) . + date_publication: '2024-01-28' + bug_reports: https://github.com/jeffreyhanson/raptr/issues + url: https://jeffrey-hanson.com/raptr/ + url_cran: https://CRAN.R-project.org/package=raptr + url_git: https://github.com/jeffreyhanson/raptr +raqs: + version: 1.0.2 + title: Interface to the US EPA Air Quality System (AQS) API + maintainer: Jaehyun Joo + description: |- + Offers functions for fetching JSON data from the US EPA Air Quality + System (AQS) API with options to comply with the API rate limits. + See for + details of the AQS API. + date_publication: '2023-11-20' + bug_reports: https://github.com/HimesGroup/raqs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=raqs + url_git: https://github.com/HimesGroup/raqs +RAQSAPI: + version: 2.0.5 + title: |- + A Simple Interface to the US EPA Air Quality System Data Mart + API + maintainer: Clinton Mccrowey + description: |- + Retrieve air monitoring data and associated metadata from the US + Environmental Protection Agency's Air Quality System service using functions. + See for details about + the US EPA Data Mart API. + date_publication: '2024-06-12' + bug_reports: https://github.com/USEPA/RAQSAPI/issues + url: https://aqs.epa.gov/aqsweb/documents/data_api.html + url_cran: https://CRAN.R-project.org/package=RAQSAPI + url_git: https://github.com/USEPA/RAQSAPI/ +Raquifer: + version: 0.1.0 + title: Estimate the Water Influx into Hydrocarbon Reservoirs + maintainer: Farshad Tabasinejad + description: Generate a table of cumulative water influx into hydrocarbon reservoirs + over time using un-steady and pseudo-steady state models. Van Everdingen, A. F. + and Hurst, W. (1949) . Fetkovich, M. J. (1971) . + Yildiz, T. and Khosravi, A. (2007) . + date_publication: '2020-05-18' + bug_reports: '' + url: https://susaenergy.github.io/Raquifer_ws/ + url_cran: https://CRAN.R-project.org/package=Raquifer + url_git: '' +rar: + version: 0.0.3 + title: Risk-Adjusted Regression + maintainer: Johann Gaebler + description: |- + Perform risk-adjusted regression and sensitivity analysis as + developed in "Mitigating Omitted- and Included-Variable Bias in Estimates of + Disparate Impact" Jung et al. (2024) . + date_publication: '2024-01-24' + bug_reports: https://github.com/jgaeb/rar/issues + url: https://rar.jgaeb.com + url_cran: https://CRAN.R-project.org/package=rar + url_git: https://github.com/jgaeb/rar +rare: + version: 0.1.1 + title: |- + Linear Model with Tree-Based Lasso Regularization for Rare + Features + maintainer: Xiaohan Yan + description: |- + Implementation of an alternating direction method of multipliers + algorithm for fitting a linear model with tree-based lasso regularization, + which is proposed in Algorithm 1 of Yan and Bien (2018) . + The package allows efficient model fitting on the entire 2-dimensional + regularization path for large datasets. The complete set of functions + also makes the entire process of tuning regularization parameters and + visualizing results hassle-free. + date_publication: '2018-08-03' + bug_reports: https://github.com/yanxht/rare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rare + url_git: https://github.com/yanxht/rare +RareComb: + version: '1.1' + title: Combinatorial and Statistical Analyses of Rare Events + maintainer: Vijay Kumar Pounraja + description: A custom implementation of the apriori algorithm and binomial tests + to identify combinations of features (genes, variants etc) significantly enriched + for simultaneous mutations/events from sparse Boolean input, see Vijay Kumar Pounraja, + Santhosh Girirajan (2021). Version 1.1 includes a minor adjustment to the number + of combinations to be considered for multiple testing correction. This updated + version is more conservative in its approach and hence more selective. . + date_publication: '2022-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RareComb + url_git: '' +rareNMtests: + version: '1.2' + title: |- + Ecological and Biogeographical Null Model Tests for Comparing + Rarefaction Curves + maintainer: Luis Cayuela + description: Randomization tests for the statistical comparison of i = two or more + individual-based, sample-based or coverage-based rarefaction curves. The ecological + null hypothesis is that the i samples were all drawn randomly from a single assemblage, + with (necessarily) a single underlying species abundance distribution. The biogeographic + null hypothesis is that the i samples were all drawn from different assemblages + that, nonetheless, share similar species richness and species abundance distributions. + Functions are described in L. Cayuela, N.J. Gotelli & R.K. Colwell (2015) . + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rareNMtests + url_git: '' +rarestR: + version: 1.1.0 + title: Rarefaction-Based Species Richness Estimator + maintainer: Peng Zhao + description: Calculate rarefaction-based alpha- and beta-diversity. Offer parametric + extrapolation to estimate the total expected species in a single community and + the total expected shared species between two communities. Visualize the curve-fitting + for these estimators. + date_publication: '2024-09-26' + bug_reports: https://github.com/pzhaonet/rarestR/issues + url: https://pzhaonet.github.io/rarestr/ + url_cran: https://CRAN.R-project.org/package=rarestR + url_git: https://github.com/pzhaonet/rarestR +RARfreq: + version: 0.1.5 + title: Response Adaptive Randomization with 'Frequentist' Approaches + maintainer: Xiu Huang + description: |- + Provides functions and command-line user interface to generate allocation sequence + by response-adaptive randomization for clinical trials. The package currently supports + two families of frequentist response-adaptive randomization procedures, Doubly Adaptive + Biased Coin Design ('DBCD') and Sequential Estimation-adjusted Urn Model ('SEU'), for + binary and normal endpoints. One-sided proportion (or mean) difference and Chi-square + (or 'ANOVA') hypothesis testing methods are also available in the package to facilitate + the inference for treatment effect. Additionally, the package provides comprehensive and + efficient tools to allow one to evaluate and compare the performance of randomization + procedures and tests based on various criteria. For example, plots for relationship among + assumed treatment effects, sample size, and power are provided. Five allocation functions + for 'DBCD' and six addition rule functions for 'SEU' are implemented to target allocations + such as 'Neyman', 'Rosenberger' Rosenberger et al. (2001) + and 'Urn' allocations. + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RARfreq + url_git: '' +Rarity: + version: 1.3-8 + title: |- + Calculation of Rarity Indices for Species and Assemblages of + Species + maintainer: Boris Leroy + description: Allows calculation of rarity weights for species and indices of rarity + for assemblages of species according to different methods (Leroy et al. 2012, + Insect. Conserv. Divers. 5:159-168 ; Leroy + et al. 2013, Divers. Distrib. 19:794-803 ). + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rarity + url_git: '' +rarms: + version: 1.0.0 + title: Access Data from the USDA ARMS Data API + maintainer: Bowen Chen + description: |- + Interface to easily access data via the United States Department of Agriculture (USDA)'s Agricultural Resource Management Survey (ARMS) + Data API . The downloaded data can be saved for later off-line use. + Also provide relevant information and metadata for each of the input variables needed for sending the data inquery. + date_publication: '2020-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rarms + url_git: '' +rARPACK: + version: 0.11-0 + title: Solvers for Large Scale Eigenvalue and SVD Problems + maintainer: Yixuan Qiu + description: |- + Previously an R wrapper of the 'ARPACK' library + , and now a shell of the + R package 'RSpectra', an R interface to the 'Spectra' library + for solving large scale + eigenvalue/vector problems. The current version of 'rARPACK' + simply imports and exports the functions provided by 'RSpectra'. + New users of 'rARPACK' are advised to switch to the 'RSpectra' package. + date_publication: '2016-03-10' + bug_reports: https://github.com/yixuan/rARPACK/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rARPACK + url_git: https://github.com/yixuan/rARPACK +RARtrials: + version: 0.0.1 + title: Response-Adaptive Randomization in Clinical Trials + maintainer: Chuyao Xu + description: Some response-adaptive randomization methods commonly found in literature + are included in this package. These methods include the randomized play-the-winner + rule for binary endpoint (Wei and Durham (1978) ), the doubly + adaptive biased coin design with minimal variance strategy for binary endpoint + (Atkinson and Biswas (2013) , Rosenberger and Lachin (2015) + ) and maximal power strategy targeting Neyman allocation + for binary endpoint (Tymofyeyev, Rosenberger, and Hu (2007) ) + and RSIHR allocation with each letter representing the first character of the + names of the individuals who first proposed this rule (Youngsook and Hu (2010) + , Bello and Sabo (2016) ), + A-optimal Allocation for continuous endpoint (Sverdlov and Rosenberger (2013) + ), Aa-optimal Allocation for continuous endpoint + (Sverdlov and Rosenberger (2013) ), generalized + RSIHR allocation for continuous endpoint (Atkinson and Biswas (2013) ), + Bayesian response-adaptive randomization with a control group using the Thall + \& Wathen method for binary and continuous endpoints (Thall and Wathen (2007) + ) and the forward-looking Gittins index rule for + binary and continuous endpoints (Villar, Wason, and Bowden (2015) , + Williamson and Villar (2019) ). + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RARtrials + url_git: https://github.com/yayayaoyaoyao/RARtrials +RaschSampler: + version: 0.8-10 + title: Rasch Sampler + maintainer: Patrick Mair + description: MCMC based sampling of binary matrices with fixed margins as used in + exact Rasch model tests. + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RaschSampler + url_git: '' +rasciidoc: + version: 4.1.1 + title: Create Reports Using R and 'asciidoc' + maintainer: Andreas Dominik Cullmann + description: |- + Inspired by Karl Broman`s reader on using 'knitr' + with 'asciidoc' + (), this is + merely a wrapper to 'knitr' and 'asciidoc'. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rasciidoc + url_git: https://gitlab.com/fvafrcu/rasciidoc +rasclass: + version: 0.2.2 + title: Supervised Raster Image Classification + maintainer: Daniel Wiesmann + description: 'Software to perform supervised and pixel based raster image classification. + It has been designed to facilitate land-cover analysis. Five classification algorithms + can be used: Maximum Likelihood Classification, Multinomial Logistic Regression, + Neural Networks, Random Forests and Support Vector Machines. The output includes + the classified raster and standard classification accuracy assessment such as + the accuracy matrix, the overall accuracy and the kappa coefficient. An option + for in-sample verification is available.' + date_publication: '2016-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rasclass + url_git: '' +RaSEn: + version: 3.0.0 + title: Random Subspace Ensemble Classification and Variable Screening + maintainer: Ye Tian + description: We propose a general ensemble classification framework, RaSE algorithm, + for the sparse classification problem. In RaSE algorithm, for each weak learner, + some random subspaces are generated and the optimal one is chosen to train the + model on the basis of some criterion. To be adapted to the problem, a novel criterion, + ratio information criterion (RIC) is put up with based on Kullback-Leibler divergence. + Besides minimizing RIC, multiple criteria can be applied, for instance, minimizing + extended Bayesian information criterion (eBIC), minimizing training error, minimizing + the validation error, minimizing the cross-validation error, minimizing leave-one-out + error. There are various choices of base classifier, for instance, linear discriminant + analysis, quadratic discriminant analysis, k-nearest neighbour, logistic regression, + decision trees, random forest, support vector machines. RaSE algorithm can also + be applied to do feature ranking, providing us the importance of each feature + based on the selected percentage in multiple subspaces. RaSE framework can be + extended to the general prediction framework, including both classification and + regression. We can use the selected percentages of variables for variable screening. + The latest version added the variable screening function for both regression and + classification problems. + date_publication: '2021-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RaSEn + url_git: '' +rassta: + version: 1.0.6 + title: Raster-Based Spatial Stratification Algorithms + maintainer: Bryan A. Fuentes + description: |- + Algorithms for the spatial stratification of landscapes, sampling and modeling of + spatially-varying phenomena. These algorithms offer a simple framework for the stratification + of geographic space based on raster layers representing landscape factors and/or factor scales. + The stratification process follows a hierarchical approach, which is based on first level units + (i.e., classification units) and second-level units (i.e., stratification units). Nonparametric + techniques allow to measure the correspondence between the geographic space and the landscape + configuration represented by the units. These correspondence metrics are useful to define + sampling schemes and to model the spatial variability of environmental phenomena. The + theoretical background of the algorithms and code examples are presented in Fuentes et al. (2022). + . + date_publication: '2024-08-19' + bug_reports: https://github.com/bafuentes/rassta/issues/ + url: https://bafuentes.github.io/rassta/ + url_cran: https://CRAN.R-project.org/package=rassta + url_git: '' +raster: + version: 3.6-31 + title: Geographic Data Analysis and Modeling + maintainer: Robert J. Hijmans + description: Reading, writing, manipulating, analyzing and modeling of spatial data. + This package has been superseded by the "terra" package . + date_publication: '2025-01-16' + bug_reports: https://github.com/rspatial/raster/issues/ + url: https://rspatial.org/raster + url_cran: https://CRAN.R-project.org/package=raster + url_git: '' +rasterbc: + version: 1.0.2 + title: Access Forest Ecology Layers for British Columbia in 2001-2018 + maintainer: Dean Koch + description: |- + R-based access to a large set of data variables relevant to forest ecology in British Columbia (BC), Canada. Layers + are in raster format at 100m resolution in the BC Albers projection, hosted at the Federated Research Data Repository (FRDR) + with . The collection includes: elevation; biogeoclimatic zone; wildfire; cutblocks; forest attributes from + Hansen et al. (2013) and Beaudoin et al. (2017) ; and rasterized + Forest Insect and Disease Survey (FIDS) maps for a number of insect pest species, all covering the period 2001-2018. + Users supply a polygon or point location in the province of BC, and 'rasterbc' will download the overlapping raster tiles + hosted at FRDR, merging them as needed and returning the result in R as a 'SpatRaster' object. Metadata associated with these + layers, and code for downloading them from their original sources can be found in the 'github' repository + . + date_publication: '2023-11-09' + bug_reports: https://github.com/deankoch/rasterbc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rasterbc + url_git: https://github.com/deankoch/rasterbc +rasterdiv: + version: 0.3.6 + title: Diversity Indices for Numerical Matrices + maintainer: Matteo Marcantonio + description: |- + Provides methods to calculate diversity indices on numerical matrices + based on information theory, as described in Rocchini, Marcantonio and Ricotta (2017) , + and Rocchini et al. (2021) . + date_publication: '2024-11-06' + bug_reports: https://github.com/mattmar/rasterdiv/issues + url: https://mattmar.github.io/rasterdiv/ + url_cran: https://CRAN.R-project.org/package=rasterdiv + url_git: '' +rasterDT: + version: 0.3.2 + title: Fast Raster Summary and Manipulation + maintainer: Joshua O'Brien + description: |2- + + Fast alternatives to several relatively slow 'raster' package + functions. For large rasters, the functions run from 5 to + approximately 100 times faster than the 'raster' package functions + they replace. The 'fasterize' package, on which one function in this + package depends, includes an implementation of the scan line + algorithm attributed to Wylie et al. (1967) + . + date_publication: '2022-12-15' + bug_reports: https://github.com/JoshOBrien/rasterDT/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=rasterDT + url_git: https://github.com/JoshOBrien/rasterDT/ +rasterImage: + version: 0.4.0 + title: An Improved Wrapper of image() + maintainer: Martin Seilmayer + description: |- + This is a wrapper function for image(), which makes reasonable + raster plots with nice axis and other useful features. + date_publication: '2019-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rasterImage + url_git: '' +rasterize: + version: '0.1' + title: Rasterize Graphical Output + maintainer: Paul Murrell + description: |- + Provides R functions to selectively rasterize components + of 'grid' output. + date_publication: '2019-03-06' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2018/05/25/2018-05-selective-raster-graphics/ + url_cran: https://CRAN.R-project.org/package=rasterize + url_git: https://github.com/pmur002/rasterize +rasterKernelEstimates: + version: 1.0.2 + title: Kernel Based Estimates on in-Memory Raster Images + maintainer: Jonathan Lisic + description: |- + Performs kernel based estimates on in-memory raster images + from the raster package. These kernel estimates include local means + variances, modes, and quantiles. All results are in the form of + raster images, preserving original resolution and projection attributes. + date_publication: '2021-09-21' + bug_reports: https://github.com/jlisic/rasterKernelEstimates/issues + url: http://meanmean.me/blog/rasterKernel/rasterKernel.html + url_cran: https://CRAN.R-project.org/package=rasterKernelEstimates + url_git: '' +rasterList: + version: 0.5.20 + title: A Raster Where Cells are Generic Objects + maintainer: Emanuele Cordano + description: |- + A S4 class has been created such that complex operations can be + executed on each cell of a raster map. The raster of objects contains a raster map with the addition of a list of generic objects: one + object for each raster cells. It allows to write few lines of R code for complex + map algebra. Two environmental applications about frequency analysis of raster + map of precipitation and creation of a raster map of soil water retention curves + have been presented. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rasterList + url_git: https://github.com/ecor/rasterList +rasterpdf: + version: 0.1.1 + title: Plot Raster Graphics in PDF Files + maintainer: Ilari Scheinin + description: |- + The ability to plot raster graphics in PDF files can be useful + when one needs multi-page documents, but the plots contain so many + individual elements that (the usual) use of vector graphics results in + inconveniently large file sizes. Internally, the package plots each + individual page as a PNG, and then combines them in one PDF file. + date_publication: '2019-11-22' + bug_reports: https://github.com/ilarischeinin/rasterpdf/issues + url: https://ilarischeinin.github.io/rasterpdf + url_cran: https://CRAN.R-project.org/package=rasterpdf + url_git: https://github.com/ilarischeinin/rasterpdf +rasterpic: + version: 0.2.6 + title: Convert Digital Images into 'SpatRaster' Objects + maintainer: Diego Hernangómez + description: |- + Generate 'SpatRaster' objects, as defined by the 'terra' + package, from digital images, using a specified spatial object as a + geographical reference. + date_publication: '2024-12-17' + bug_reports: https://github.com/dieghernan/rasterpic/issues + url: https://dieghernan.github.io/rasterpic/ + url_cran: https://CRAN.R-project.org/package=rasterpic + url_git: https://github.com/dieghernan/rasterpic +rasterVis: + version: 0.51.6 + title: Visualization Methods for Raster Data + maintainer: Oscar Perpinan Lamigueiro + description: Methods for enhanced visualization and interaction with raster data. + It implements visualization methods for quantitative data and categorical data, + both for univariate and multivariate rasters. It also provides methods to display + spatiotemporal rasters, and vector fields. See the website for examples. + date_publication: '2023-11-01' + bug_reports: https://github.com/oscarperpinan/rastervis/issues + url: https://oscarperpinan.github.io/rastervis/ + url_cran: https://CRAN.R-project.org/package=rasterVis + url_git: '' +RAT: + version: 0.3.1 + title: Research Assessment Tools + maintainer: Pedro Cardoso + description: 'Includes algorithms to assess research productivity and patterns, + such as the h-index and i-index. Cardoso et al. (2022) Cardoso, P., Fukushima, + C.S. & Mammola, S. (2022) Quantifying the internationalization and representativeness + in research. Trends in Ecology and Evolution, 37: 725-728.' + date_publication: '2022-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RAT + url_git: '' +Rata: + version: 0.0.2 + title: Automated Test Assembly + maintainer: Xiao Luo + description: |- + Automated test assembly of linear and adaptive tests using the + mixed-integer programming. The full documentation and tutorials are at + . + date_publication: '2019-10-24' + bug_reports: https://github.com/xluo11/Rata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rata + url_git: https://github.com/xluo11/Rata +ratdat: + version: 1.1.0 + title: Portal Project Teaching Database + maintainer: Ethan P. White + description: |- + A simplified version of the Portal Project Database designed for + teaching. It provides a real world example of life-history, population, and + ecological data, with sufficient complexity to teach many aspects of data + analysis and management, but with many complexities removed to allow + students to focus on the core ideas and skills being taught. The full + database (which should be used for research) is available at + . + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ratdat + url_git: '' +ratelimitr: + version: 0.4.1 + title: Rate Limiting for R + maintainer: Tarak Shah + description: Allows to limit the rate at which one or more functions can be called. + date_publication: '2018-10-07' + bug_reports: https://github.com/tarakc02/ratelimitr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ratelimitr + url_git: https://github.com/tarakc02/ratelimitr +ratematrix: + version: 1.2.4 + title: Bayesian Estimation of the Evolutionary Rate Matrix + maintainer: Daniel Caetano + description: The Evolutionary Rate Matrix is a variance-covariance matrix which + describes both the rates of trait evolution and the evolutionary correlation among + multiple traits. This package has functions to estimate these parameters using + Bayesian MCMC. It is possible to test if the pattern of evolutionary correlations + among traits has changed between predictive regimes painted along the branches + of the phylogenetic tree. Regimes can be created a priori or estimated as part + of the MCMC under a joint estimation approach. The package has functions to run + MCMC chains, plot results, evaluate convergence, and summarize posterior distributions. + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ratematrix + url_git: https://github.com/Caetanods/ratematrix +rater: + version: 1.3.1 + title: Statistical Models of Repeated Categorical Rating Data + maintainer: Jeffrey Pullin + description: |- + Fit statistical models based on the Dawid-Skene model - Dawid + and Skene (1979) - to repeated categorical + rating data. Full Bayesian inference for these models is supported + through the Stan modelling language. 'rater' also allows the user to + extract and plot key parameters of these models. + date_publication: '2023-09-11' + bug_reports: https://github.com/jeffreypullin/rater/issues + url: https://jeffreypullin.github.io/rater/ + url_cran: https://CRAN.R-project.org/package=rater + url_git: https://github.com/jeffreypullin/rater +rateratio.test: + version: '1.1' + title: Exact Rate Ratio Test + maintainer: Michael Fay + description: Performs exact rate ratio tests. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rateratio.test + url_git: '' +raters: + version: 2.1.1 + title: |- + A Modification of Fleiss' Kappa in Case of Nominal and Ordinal + Variables + maintainer: Daniele Giardiello + description: The kappa statistic implemented by Fleiss is a very popular index for + assessing the reliability of agreement among multiple observers. It is used both + in the psychological and in the psychiatric field. Other fields of application + are typically medicine, biology and engineering. Unfortunately,the kappa statistic + may behave inconsistently in case of strong agreement between raters, since this + index assumes lower values than it would have been expected. We propose a modification + kappa implemented by Fleiss in case of nominal and ordinal variables. Monte Carlo + simulations are used both to testing statistical hypotheses and to calculating + percentile bootstrap confidence intervals based on proposed statistic in case + of nominal and ordinal data. + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=raters + url_git: '' +ratesci: + version: 0.5.0 + title: |- + Confidence Intervals for Comparisons of Binomial or Poisson + Rates + maintainer: Pete Laud + description: |- + Computes confidence intervals for the rate (or risk) + difference ('RD') or rate ratio (or relative risk, 'RR') for + binomial proportions or Poisson rates, or for odds ratio + ('OR', binomial only). Also confidence intervals for a single + binomial or Poisson rate, and intervals for matched pairs. + Includes skewness-corrected asymptotic score ('SCAS') methods, + which have been developed in Laud (2017) + from Miettinen & Nurminen (1985) and + Gart & Nam (1988) . The same score produces + hypothesis tests analogous to the test for binomial RD and RR by + Farrington & Manning (1990) , or the + McNemar test for paired data. + The package also includes MOVER methods + (Method Of Variance Estimates Recovery) for all contrasts, derived + from the Newcombe method but with options to use equal-tailed + intervals in place of the Wilson score method, + and generalised for Bayesian applications incorporating prior + information. So-called 'exact' methods for strictly conservative + coverage are approximated using continuity corrections, and the amount + of correction can be selected to avoid over-conservative coverage. + Also includes methods for stratified calculations (e.g. meta-analysis), + either assuming fixed effects (matching the CMH test) or incorporating + stratum heterogeneity. + date_publication: '2025-01-10' + bug_reports: https://github.com/petelaud/ratesci/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ratesci + url_git: https://github.com/petelaud/ratesci +RATest: + version: 0.1.10 + title: Randomization Tests + maintainer: Mauricio Olivares + description: A collection of randomization tests, data sets and examples. The current + version focuses on five testing problems and their implementation in empirical + work. First, it facilitates the empirical researcher to test for particular hypotheses, + such as comparisons of means, medians, and variances from k populations using + robust permutation tests, which asymptotic validity holds under very weak assumptions, + while retaining the exact rejection probability in finite samples when the underlying + distributions are identical. Second, the description and implementation of a permutation + test for testing the continuity assumption of the baseline covariates in the sharp + regression discontinuity design (RDD) as in Canay and Kamat (2018) . + More specifically, it allows the user to select a set of covariates and test the + aforementioned hypothesis using a permutation test based on the Cramer-von Misses + test statistic. Graphical inspection of the empirical CDF and histograms for the + variables of interest is also supported in the package. Third, it provides the + practitioner with an effortless implementation of a permutation test based on + the martingale decomposition of the empirical process for testing for heterogeneous + treatment effects in the presence of an estimated nuisance parameter as in Chung + and Olivares (2021) . Fourth, this version + considers the two-sample goodness-of-fit testing problem under covariate adaptive + randomization and implements a permutation test based on a prepivoted Kolmogorov-Smirnov + test statistic. Lastly, it implements an asymptotically valid permutation test + based on the quantile process for the hypothesis of constant quantile treatment + effects in the presence of an estimated nuisance parameter. + date_publication: '2022-09-29' + bug_reports: https://github.com/ignaciomsarmiento/RATest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RATest + url_git: '' +RAthena: + version: 2.6.1 + title: Connect to 'AWS Athena' using 'Boto3' ('DBI' Interface) + maintainer: Dyfan Jones + description: |- + Designed to be compatible with the R package 'DBI' (Database Interface) + when connecting to Amazon Web Service ('AWS') Athena . + To do this 'Python' 'Boto3' Software Development Kit ('SDK') + is used as a driver. + date_publication: '2022-12-20' + bug_reports: https://github.com/DyfanJones/RAthena/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RAthena + url_git: https://github.com/DyfanJones/RAthena +RatingScaleReduction: + version: '1.4' + title: Rating Scale Reduction Procedure + maintainer: Alicja Wolny-Dominiak + description: Describes a new procedure of reducing items in a rating scale called + Rating Scale Reduction (RSR). The new stop criterion in RSR procedure is added + (stop global max). The function order is replaced by sort.list. + date_publication: '2021-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RatingScaleReduction + url_git: '' +RationalExp: + version: 0.2.2 + title: Rationalizing Rational Expectations. Tests and Deviations + maintainer: Christophe Gaillac + description: We implement a test of the rational expectations hypothesis based on + the marginal distributions of realizations and subjective beliefs from D'Haultfoeuille, + Gaillac, and Maurel (2018) . This test can be used in cases + where realizations and subjective beliefs are observed in two different datasets + that cannot be matched, or when they are observed in the same dataset. The package + also computes the estimator of the minimal deviations from rational expectations + than can be rationalized by the data. + date_publication: '2019-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RationalExp + url_git: '' +rationalfun: + version: 0.1-1 + title: Manipulation of Rational Functions + maintainer: Yixuan Qiu + description: |- + Functions to manipulate rational functions, including basic + arithmetic operators, derivatives, and integrals with EXPLICIT forms. + date_publication: '2022-03-05' + bug_reports: https://github.com/yixuan/rationalfun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rationalfun + url_git: https://github.com/yixuan/rationalfun +RationalMatrix: + version: 1.0.0 + title: Exact Matrix Algebra for Rational Matrices + maintainer: Stéphane Laurent + description: |- + Provides functions to deal with matrix algebra for matrices + with rational entries: determinant, rank, image and kernel, inverse, + Cholesky decomposition. All computations are exact. + date_publication: '2023-01-27' + bug_reports: https://github.com/stla/RationalMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RationalMatrix + url_git: https://github.com/stla/RationalMatrix +ratioOfQsprays: + version: 1.1.0 + title: Fractions of Multivariate Polynomials with Rational Coefficients + maintainer: Stéphane Laurent + description: |- + Based on the 'qspray' package, this package introduces the new + type 'ratioOfQsprays'. An object of type 'qspray' represents a multivariate + polynomial with rational coefficients while an object of type + 'ratioOfQsprays', defined by two 'qspray' objects, represents a fraction of + two multivariate polynomials with rational coefficients. Arithmetic + operations for these objects are available, and they always return + irreducible fractions. Other features include: differentiation, + evaluation, conversion to a function, and fine control of the way to print + a 'ratioOfQsprays' object. The 'C++' library 'CGAL' is used to make the + fractions irreducible. + date_publication: '2024-07-28' + bug_reports: https://github.com/stla/ratioOfQsprays/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ratioOfQsprays + url_git: https://github.com/stla/ratioOfQsprays +ratios: + version: 1.2.0 + title: |- + Calculating Ratios Between Two Data Sets and Correction for + Adhering Particles on Plants + maintainer: Solveig Pospiech + description: |- + Calculation of ratios between two data sets containing environmental data like + element concentrations by different methods. Additionally plant element + concentrations can be corrected for adhering particles (soil, airborne dust). + date_publication: '2018-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ratios + url_git: '' +ratlas: + version: 0.1.0 + title: ATLAS Formatting Functions and Templates + maintainer: W. Jake Thompson + description: |- + Provides templates, formatting tools, and 'ggplot2' themes + tailored for the Accessible Teaching, Learning, and Assessment Systems (ATLAS) + organization. These templates facilitate the creation of topic guides and + technical reports, while the formatting functions enable users to customize + numbers and tables to meet specific requirements. Additionally, the themes + ensure a uniform visual style across graphics. + date_publication: '2024-11-06' + bug_reports: https://github.com/atlas-aai/ratlas/issues + url: https://ratlas.netlify.app + url_cran: https://CRAN.R-project.org/package=ratlas + url_git: https://github.com/atlas-aai/ratlas +rATTAINS: + version: 1.0.0 + title: Access EPA 'ATTAINS' Data + maintainer: Michael Schramm + description: |- + An R interface to United States Environmental Protection Agency (EPA) + Assessment, Total Maximum Daily Load (TMDL) Tracking and Implementation System + ('ATTAINS') data. 'ATTAINS' is the EPA database used to track information + provided by states about water quality assessments conducted under federal + Clean Water Act requirements. ATTAINS information and API information is available at . + date_publication: '2023-04-25' + bug_reports: https://github.com/mps9506/rATTAINS/issues + url: https://mps9506.github.io/rATTAINS/ + url_cran: https://CRAN.R-project.org/package=rATTAINS + url_git: https://github.com/mps9506/rATTAINS +rattle: + version: 5.5.1 + title: Graphical User Interface for Data Science in R + maintainer: Graham Williams + description: |- + The R Analytic Tool To Learn Easily (Rattle) provides a + collection of utilities functions for the data scientist. A + Gnome (RGtk2) based graphical interface is included with + the aim to provide a simple and intuitive introduction to R + for data science, allowing a user to quickly load data from a CSV file + (or via ODBC), transform and explore the data, + build and evaluate models, and export models as PMML (predictive + modelling markup language) or as scores. A key aspect of the GUI + is that all R commands are logged and commented through the log tab. + This can be saved as a standalone R script file and as + an aid for the user to + learn R or to copy-and-paste directly into R itself. + Note that RGtk2 and cairoDevice have been archived on CRAN. + See for installation instructions. + date_publication: '2022-03-21' + bug_reports: '' + url: https://rattle.togaware.com/ + url_cran: https://CRAN.R-project.org/package=rattle + url_git: '' +Ravages: + version: 1.1.3 + title: Rare Variant Analysis and Genetic Simulations + maintainer: Ozvan Bocher + description: 'Rare variant association tests: burden tests (Bocher et al. 2019 ) + and the Sequence Kernel Association Test (Bocher et al. 2021 ) + in the whole genome; and genetic simulations.' + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ravages + url_git: '' +ravelRy: + version: 0.1.0 + title: An Interface to the 'Ravelry' API + maintainer: Kaylin Pavlik + description: Provides access to the 'Ravelry' API . + An R wrapper for pulling data from 'Ravelry.com', an organizational tool for crocheters, + knitters, spinners, and weavers. You can retrieve pattern, yarn, author, and shop + information by search or by a given id. + date_publication: '2020-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ravelRy + url_git: '' +raven.rdf: + version: 0.2.0 + title: An R Interface for Raven DataFrames (Beta0) + maintainer: Phil Gaiser + description: |- + Provides an I/O interface between R data.frames and + Raven DataFrames. Defines functions to both read and write DataFrame + files, as well as serialize/deserialize data.frames/DataFrames. + date_publication: '2021-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=raven.rdf + url_git: https://github.com/raven-computing/rdf +RavenR: + version: 2.2.2 + title: Raven Hydrological Modelling Framework R Support and Analysis + maintainer: Robert Chlumsky + description: |- + Utilities for processing input and output files associated with the Raven Hydrological Modelling Framework. Includes various plotting functions, model diagnostics, reading output files into extensible time series format, and support for writing Raven input files. + The 'RavenR' package is also archived at Chlumsky et al. (2020) . + The Raven Hydrologic Modelling Framework method can be referenced with Craig et al. (2020) . + date_publication: '2024-05-07' + bug_reports: https://github.com/rchlumsk/RavenR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RavenR + url_git: https://github.com/rchlumsk/RavenR +rAverage: + version: 0.5-8 + title: |- + Parameter Estimation for the Averaging Model of Information + Integration Theory + maintainer: Davide Massidda + description: Implementation of the R-Average method for parameter estimation of + averaging models of the Anderson's Information Integration Theory by Vidotto, + G., Massidda, D., & Noventa, S. (2010) . + date_publication: '2017-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rAverage + url_git: '' +ravetools: + version: 0.2.1 + title: |- + Signal and Image Processing Toolbox for Analyzing Intracranial + Electroencephalography Data + maintainer: Zhengjia Wang + description: |- + Implemented fast and memory-efficient Notch-filter, + Welch-periodogram, discrete wavelet spectrogram for minutes of + high-resolution signals, fast 3D convolution, image registration, + 3D mesh manipulation; providing fundamental toolbox for intracranial + Electroencephalography (iEEG) pipelines. + Documentation and examples about 'RAVE' project are provided at + , and the paper by John F. Magnotti, + Zhengjia Wang, Michael S. Beauchamp (2020) + ; see 'citation("ravetools")' for + details. + date_publication: '2025-01-24' + bug_reports: https://github.com/dipterix/ravetools/issues + url: https://rave.wiki + url_cran: https://CRAN.R-project.org/package=ravetools + url_git: '' +raw: + version: 0.1.8 + title: R Actuarial Workshops + maintainer: Brian A. Fannin + description: |- + In order to facilitate R instruction for actuaries, we have organized several + sets of publicly available data of interest to non-life actuaries. In addition, we suggest + a set of packages, which most practicing actuaries will use routinely. Finally, there is + an R markdown skeleton for basic reserve analysis. + date_publication: '2021-02-05' + bug_reports: '' + url: http://casact.github.io/raw_package/ + url_cran: https://CRAN.R-project.org/package=raw + url_git: '' +RawHummus: + version: 0.3.3 + title: Raw Data Quality Control Tool for LC-MS System + maintainer: Yonghui Dong + description: |- + Assess LC–MS system performance by visualizing instrument log + files and monitoring raw quality control samples within a project. + date_publication: '2023-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RawHummus + url_git: '' +rawKS: + version: 0.1.0 + title: |- + Easily Get True-Positive Rate and False-Positive Rate and KS + Statistic + maintainer: Jiaxiang Li + description: |- + The Kolmogorov-Smirnov (K-S) statistic is a standard method to measure the model strength for + credit risk scoring models. This package calculates the K–S statistic and + plots the true-positive rate and false-positive rate to measure the model strength. + This package was written with the credit marketer, who uses risk models in + conjunction with his campaigns. The users could read more details from + Thrasher (1992) and 'pyks' . + date_publication: '2020-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rawKS + url_git: '' +raws.profile: + version: 0.1.0 + title: Managing Profiles on Amazon Web Service + maintainer: Samuel Macedo + description: |- + This is an R wrapper from the AWS Command Line Interface that + provides methods to manage the user configuration on Amazon Web Service. You + can create as many profiles as you want, manage them, and delete them. The + profiles created with this tool work with all AWS products such as S3, + Glacier, and EC2. It also provides a function to automatically install + AWS CLI, but you can download it and install it manually if you prefer. + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=raws.profile + url_git: '' +raybevel: + version: 0.2.2 + title: Generates Polygon Straight Skeletons and 3D Bevels + maintainer: Tyler Morgan-Wall + description: |- + Generates polygon straight skeletons and 3D models. + Provides functions to create and visualize interior polygon offsets, + 3D beveled polygons, and 3D roof models. + date_publication: '2025-02-03' + bug_reports: https://github.com/tylermorganwall/raybevel/issues + url: https://www.raybevel.com + url_cran: https://CRAN.R-project.org/package=raybevel + url_git: https://github.com/tylermorganwall/raybevel/ +rayimage: + version: 0.15.1 + title: Image Processing for Simulated Cameras + maintainer: Tyler Morgan-Wall + description: Uses convolution-based techniques to generate simulated camera bokeh, + depth of field, and other camera effects, using an image and an optional depth + map. Accepts both filename inputs and in-memory array representations of images + and matrices. Includes functions to perform 2D convolutions, reorient and resize + images/matrices, add image and text overlays, generate camera vignette effects, + and add titles to images. + date_publication: '2025-02-01' + bug_reports: https://github.com/tylermorganwall/rayimage/issues + url: https://www.rayimage.dev + url_cran: https://CRAN.R-project.org/package=rayimage + url_git: https://github.com/tylermorganwall/rayimage +raymolecule: + version: 0.5.3 + title: Parse and Render Molecular Structures in 3D + maintainer: Tyler Morgan-Wall + description: Downloads and parses 'SDF' (Structural Description Format) and 'PDB' + (Protein Database) files for 3D rendering. + date_publication: '2024-02-22' + bug_reports: https://github.com/tylermorganwall/raymolecule/issues + url: http://www.raymolecule.com/ + url_cran: https://CRAN.R-project.org/package=raymolecule + url_git: https://github.com/tylermorganwall/raymolecule +rayrender: + version: 0.38.10 + title: Build and Raytrace 3D Scenes + maintainer: Tyler Morgan-Wall + description: Render scenes using pathtracing. Build 3D scenes out of spheres, cubes, + planes, disks, triangles, cones, curves, line segments, cylinders, ellipsoids, + and 3D models in the 'Wavefront' OBJ file format or the PLY Polygon File Format. + Supports several material types, textures, multicore rendering, and tone-mapping. + Based on the "Ray Tracing in One Weekend" book series. Peter Shirley (2018) . + date_publication: '2025-02-28' + bug_reports: '' + url: https://www.rayrender.net + url_cran: https://CRAN.R-project.org/package=rayrender + url_git: https://github.com/tylermorganwall/rayrender +rayshader: + version: 0.37.3 + title: Create Maps and Visualize Data in 2D and 3D + maintainer: Tyler Morgan-Wall + description: Uses a combination of raytracing and multiple hill shading methods + to produce 2D and 3D data visualizations and maps. Includes water detection and + layering functions, programmable color palette generation, several built-in textures + for hill shading, 2D and 3D plotting options, a built-in path tracer, 'Wavefront' + OBJ file export, and the ability to save 3D visualizations to a 3D printable format. + date_publication: '2024-02-21' + bug_reports: https://github.com/tylermorganwall/rayshader/issues + url: https://www.rayshader.com + url_cran: https://CRAN.R-project.org/package=rayshader + url_git: https://github.com/tylermorganwall/rayshader +raytracing: + version: 0.6.0 + title: Rossby Wave Ray Tracing + maintainer: Amanda Rehbein + description: |- + Rossby wave ray paths are traced from + a determined source, specified wavenumber, and direction + of propagation. "raytracing" also works with a set of + experiments changing these parameters, making possible the + identification of Rossby wave sources automatically. + The theory used here is based on classical studies, + such as Hoskins and Karoly (1981) , + Karoly (1983) , + Hoskins and Ambrizzi (1993) , + and Yang and Hoskins (1996) . + date_publication: '2022-06-06' + bug_reports: https://github.com/salvatirehbein/raytracing/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=raytracing + url_git: https://github.com/salvatirehbein/raytracing/ +rayvertex: + version: 0.12.0 + title: 3D Software Rasterizer + maintainer: Tyler Morgan-Wall + description: Rasterize images using a 3D software renderer. 3D scenes are created + either by importing external files, building scenes out of the included objects, + or by constructing meshes manually. Supports point and directional lights, anti-aliased + lines, shadow mapping, transparent objects, translucent objects, multiple materials + types, reflection, refraction, environment maps, multicore rendering, bloom, tone-mapping, + and screen-space ambient occlusion. + date_publication: '2025-02-03' + bug_reports: https://github.com/tylermorganwall/rayvertex/issues + url: https://www.rayvertex.com + url_cran: https://CRAN.R-project.org/package=rayvertex + url_git: https://github.com/tylermorganwall/rayvertex +rb3: + version: 0.0.12 + title: Download and Parse Public Data Released by B3 Exchange + maintainer: Wilson Freitas + description: |- + Download and parse public files released by B3 and convert them + into useful formats and data structures common to data analysis + practitioners. + date_publication: '2025-02-18' + bug_reports: https://github.com/ropensci/rb3/issues + url: http://ropensci.github.io/rb3/ + url_cran: https://CRAN.R-project.org/package=rb3 + url_git: https://github.com/ropensci/rb3 +rbacon: + version: 3.3.1 + title: Age-Depth Modelling using Bayesian Statistics + maintainer: Maarten Blaauw + description: An approach to age-depth modelling that uses Bayesian statistics to + reconstruct accumulation histories for deposits, through combining radiocarbon + and other dates with prior information on accumulation rates and their variability. + See Blaauw & Christen (2011). + date_publication: '2024-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbacon + url_git: '' +rBahadur: + version: 1.0.0 + title: |- + Assortative Mating Simulation and Multivariate Bernoulli + Variates + maintainer: Richard Border + description: |- + Simulation of phenotype / genotype data under assortative mating. + Includes functions for generating Bahadur order-2 multivariate Bernoulli + variables with general and diagonal-plus-low-rank correlation structures. + Further details are provided in: Border and Malik (2022) + . + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rBahadur + url_git: https://github.com/rborder/rBahadur +RBaseX: + version: 1.1.2 + title: '''BaseX'' Client' + maintainer: Ben Engbers + description: '''BaseX'' is a XML database engine and a compliant + ''XQuery 3.1'' processor with full support of ''W3C Update Facility''. This package + is a full client-implementation of the client/server protocol for ''BaseX'' and + provides functionalities to create, manipulate and query on XML-data.' + date_publication: '2022-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RBaseX + url_git: https://github.com/BenEngbers/RBaseX +rBayesianOptimization: + version: 1.2.1 + title: Bayesian Optimization of Hyperparameters + maintainer: Yachen Yan + description: A Pure R implementation of Bayesian Global Optimization with Gaussian + Processes. + date_publication: '2024-04-13' + bug_reports: https://github.com/yanyachen/rBayesianOptimization/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rBayesianOptimization + url_git: https://github.com/yanyachen/rBayesianOptimization +rbbnp: + version: 0.1.0 + title: A Bias Bound Approach to Non-Parametric Inference + maintainer: Xinyu DAI + description: |- + A novel bias-bound approach for non-parametric inference is introduced, + focusing on both density and conditional expectation estimation. + It constructs valid confidence intervals that account for the presence of + a non-negligible bias and thus make it possible to perform inference with + optimal mean squared error minimizing bandwidths. + This package is based on Schennach (2020) . + date_publication: '2024-02-01' + bug_reports: '' + url: https://doi.org/10.1093/restud/rdz065 + url_cran: https://CRAN.R-project.org/package=rbbnp + url_git: '' +rbc: + version: 0.1.0 + title: Regression by Composition + maintainer: Daniel Farewell + description: |- + Flexible statistical modelling using a modular framework for + regression, in which groups of transformations are composed together + and act on probability distributions. + date_publication: '2024-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbc + url_git: '' +rbcb: + version: 0.1.14 + title: R Interface to Brazilian Central Bank Web Services + maintainer: Wilson Freitas + description: |- + The Brazilian Central Bank API delivers many datasets which regard economic + activity, regional economy, international economy, public finances, credit + indicators and many more. For more information please see . + These datasets can be accessed through 'rbcb' functions and can be obtained in + different data structures common to R ('tibble', 'data.frame', 'xts', ...). + date_publication: '2024-01-25' + bug_reports: https://github.com/wilsonfreitas/rbcb/issues + url: https://wilsonfreitas.github.io/rbcb/ + url_cran: https://CRAN.R-project.org/package=rbcb + url_git: https://github.com/wilsonfreitas/rbcb +rbcc: + version: 0.1.4 + title: Risk-Based Control Charts + maintainer: Zsolt Tibor Kosztyan + description: Univariate and multivariate versions of risk-based control charts. + Univariate versions of control charts, such as the risk-based version of X-bar, + Moving Average (MA), Exponentially Weighted Moving Average Control Charts (EWMA), + and Cumulative Sum Control Charts (CUSUM) charts. The risk-based version of the + multivariate T2 control chart. Plot and summary functions. Kosztyan et. al. (2016) + . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbcc + url_git: https://github.com/kzst/rbcc +rbch: + version: 0.1-2 + title: |- + Extraction and Analysis of Data from the Bitcoin Cash (BCH) + Blockchain + maintainer: Rucknium + description: |- + Issues RPC-JSON calls to 'bitcoind', the daemon of Bitcoin Cash (BCH), to + extract transaction data from the blockchain. BCH is a fork of Bitcoin that permits + a greater number of transactions per second. A BCH daemon is available under an MIT + license from the Bitcoin Unlimited website . + date_publication: '2024-09-27' + bug_reports: https://github.com/Rucknium/rbch/issues + url: https://www.bitcoinunlimited.info + url_cran: https://CRAN.R-project.org/package=rbch + url_git: https://github.com/Rucknium/rbch +rBDAT: + version: 1.0.0 + title: Implementation of BDAT Tree Taper Fortran Functions + maintainer: Christian Vonderach + description: |- + Implementing the BDAT tree taper Fortran routines, which were + developed for the German National Forest Inventory (NFI), to calculate + diameters, volume, assortments, double bark thickness and biomass for + different tree species based on tree characteristics and sorting information. + See Kublin (2003) for details. + date_publication: '2023-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rBDAT + url_git: https://gitlab.com/vochr/rbdat +RBE3: + version: '1.1' + title: |- + Estimation and Additional Tools for Quantile Generalized Beta + Regression Model + maintainer: Diego Gallardo + description: |- + Provide estimation and data generation tools for the quantile generalized beta + regression model. For details, see Bourguignon, Gallardo and Saulo + The package also provides tools to perform covariates selection. + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RBE3 + url_git: '' +Rbeast: + version: 1.0.1 + title: Bayesian Change-Point Detection and Time Series Decomposition + maintainer: Kaiguang Zhao + description: Interpretation of time series data is affected by model choices. Different + models can give different or even contradicting estimates of patterns, trends, + and mechanisms for the same data--a limitation alleviated by the Bayesian estimator + of abrupt change,seasonality, and trend (BEAST) of this package. BEAST seeks to + improve time series decomposition by forgoing the "single-best-model" concept + and embracing all competing models into the inference via a Bayesian model averaging + scheme. It is a flexible tool to uncover abrupt changes (i.e., change-points, + breakpoints, structural breaks, or join-points), cyclic variations (e.g., seasonality), + and nonlinear trends in time-series observations. BEAST not just tells when changes + occur but also quantifies how likely the detected changes are true. It detects + not just piecewise linear trends but also arbitrary nonlinear trends. BEAST is + applicable to real-valued time series data of all kinds, be it for remote sensing, + economics, climate sciences, ecology, and hydrology. Example applications include + its use to identify regime shifts in ecological data, map forest disturbance and + land degradation from satellite imagery, detect market trends in economic data, + pinpoint anomaly and extreme events in climate data, and unravel system dynamics + in biological data. Details on BEAST are reported in Zhao et al. (2019) . + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rbeast + url_git: https://github.com/zhaokg/Rbeast +rbedrock: + version: 0.3.2 + title: Analysis and Manipulation of Data from Minecraft Bedrock Edition + maintainer: Reed Cartwright + description: Implements an interface to Minecraft (Bedrock Edition) worlds. Supports + the analysis and management of these worlds and game saves. + date_publication: '2023-12-02' + bug_reports: https://github.com/reedacartwright/rbedrock/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rbedrock + url_git: https://github.com/reedacartwright/rbedrock +rbenchmark: + version: 1.0.0 + title: Benchmarking routine for R + maintainer: Wacek Kusnierczyk + description: rbenchmark is inspired by the Perl module Benchmark, andis + intended to facilitate benchmarking of arbitrary R code. Thelibrary consists + of just one function, benchmark, which is asimple wrapper around system.time. Given + a specification ofthe benchmarking process (counts of replications, evaluationenvironment) + and an arbitrary number of expressions, benchmarkevaluates each of the + expressions in the specified environment,replicating the evaluation as + many times as specified, andreturning the results conveniently wrapped + into a data frame. + date_publication: '2012-08-30' + bug_reports: '' + url: http://rbenchmark.googlecode.com + url_cran: https://CRAN.R-project.org/package=rbenchmark + url_git: '' +Rbent: + version: 0.1.0 + title: Robust Bent Line Regression + maintainer: Feipeng Zhang + description: |- + An implementation of robust bent line regression. It can fit the bent line regression and test the existence of change point, + for the paper, "Feipeng Zhang and Qunhua Li (2016). Robust bent line regression, submitted." + date_publication: '2016-06-08' + bug_reports: '' + url: http://arxiv.org/abs/1606.02234 + url_cran: https://CRAN.R-project.org/package=Rbent + url_git: '' +RBesT: + version: 1.8-1 + title: R Bayesian Evidence Synthesis Tools + maintainer: Sebastian Weber + description: |- + Tool-set to support Bayesian evidence synthesis. This + includes meta-analysis, (robust) prior derivation from historical + data, operating characteristics and analysis (1 and 2 sample + cases). Please refer to Weber et al. (2021) + for details on applying this package while Neuenschwander et al. (2010) + and Schmidli et al. (2014) + explain details on the methodology. + date_publication: '2025-01-21' + bug_reports: https://github.com/Novartis/RBesT/issues + url: https://opensource.nibr.com/RBesT/ + url_cran: https://CRAN.R-project.org/package=RBesT + url_git: '' +rBeta2009: + version: 1.0.1 + title: |- + The Beta Random Number and Dirichlet Random Vector Generating + Functions + maintainer: Ching-Wei Cheng + description: |- + Contains functions to generate random numbers + from the beta distribution and random vectors from the + Dirichlet distribution. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rBeta2009 + url_git: '' +RBF: + version: 2.1.1 + title: Robust Backfitting + maintainer: Matias Salibian-Barrera + description: |- + A robust backfitting algorithm for additive models based on (robust) local polynomial + kernel smoothers. It includes both bounded and re-descending (kernel) M-estimators, and + it computes predictions for points outside the training set if desired. See + Boente, Martinez and Salibian-Barrera (2017) and + Martinez and Salibian-Barrera (2021) for details. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RBF + url_git: '' +rbgm: + version: 0.1.0 + title: |- + Tools for 'Box Geometry Model' (BGM) Files and Topology for the + Atlantis Ecosystem Model + maintainer: Michael D. Sumner + description: |- + Facilities for working with Atlantis box-geometry model (BGM) + files. Atlantis is a deterministic, biogeochemical, whole-of-ecosystem model. + Functions are provided to read from BGM files directly, preserving their + internal topology, as well as helper functions to generate spatial data from these + mesh forms. This functionality aims to simplify the creation and modification of box + and geometry as well as the ability to integrate with other data sources. + date_publication: '2020-04-12' + bug_reports: https://github.com/AustralianAntarcticDivision/rbgm/issues/ + url: https://research.csiro.au/atlantis/ + url_cran: https://CRAN.R-project.org/package=rbgm + url_git: '' +rbi: + version: 1.0.0 + title: Interface to 'LibBi' + maintainer: Sebastian Funk + description: |- + Provides a complete interface to 'LibBi', a library for Bayesian + inference (see and Murray, 2015 + for more information). This includes functions + for manipulating 'LibBi' models, for reading and writing 'LibBi' + input/output files, for converting 'LibBi' output to provide traces for use + with the coda package, and for running 'LibBi' to conduct inference. + date_publication: '2023-08-15' + bug_reports: https://github.com/sbfnk/rbi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rbi + url_git: https://github.com/sbfnk/rbi +rbi.helpers: + version: 0.4.0 + title: '''rbi'' Helper Functions' + maintainer: Sebastian Funk + description: |- + Contains a collection of helper functions to use with 'rbi', the R + interface to 'LibBi', described in + Murray et al. (2015) . It contains functions to + adapt the proposal distribution and number of particles in + particle Markov-Chain Monte Carlo, as well as calculating the + Deviance Information Criterion (DIC) and converting between times in 'LibBi' + results and R time/dates. + date_publication: '2023-08-24' + bug_reports: https://github.com/sbfnk/rbi.helpers/issues + url: https://libbi.org + url_cran: https://CRAN.R-project.org/package=rbi.helpers + url_git: https://github.com/sbfnk/rbi +rBiasCorrection: + version: 0.3.4 + title: Correct Bias in DNA Methylation Analyses + maintainer: Lorenz A. Kapsner + description: |- + Implementation of the algorithms (with minor modifications) + to correct bias in quantitative DNA methylation analyses as described + by Moskalev et al. (2011) . Publication: + Kapsner et al. (2021) . + date_publication: '2022-06-20' + bug_reports: https://github.com/kapsner/rBiasCorrection/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rBiasCorrection + url_git: https://github.com/kapsner/rBiasCorrection +rbibutils: + version: '2.3' + title: Read 'Bibtex' Files and Convert Between Bibliography Formats + maintainer: Georgi N. Boshnakov + description: |- + Read and write 'Bibtex' files. Convert between bibliography + formats, including 'Bibtex', 'Biblatex', 'PubMed', 'Endnote', and + 'Bibentry'. Includes a port of the 'bibutils' utilities by Chris + Putnam . Supports all + bibliography formats and character encodings implemented in + 'bibutils'. + date_publication: '2024-10-04' + bug_reports: https://github.com/GeoBosh/rbibutils/issues + url: https://geobosh.github.io/rbibutils/(doc) + url_cran: https://CRAN.R-project.org/package=rbibutils + url_git: https://github.com/GeoBosh/rbibutils(devel) +rbin: + version: 0.2.1 + title: Tools for Binning Data + maintainer: Aravind Hebbali + description: |- + Manually bin data using weight of evidence and information value. Includes other binning + methods such as equal length, quantile and winsorized. Options for combining levels of categorical + data are also available. Dummy variables can be generated based on the bins created using any of + the available binning methods. References: Siddiqi, N. (2006) . + date_publication: '2024-11-05' + bug_reports: https://github.com/rsquaredacademy/rbin/issues + url: https://rbin.rsquaredacademy.com + url_cran: https://CRAN.R-project.org/package=rbin + url_git: https://github.com/rsquaredacademy/rbin +rbioacc: + version: 1.2.1 + title: Inference and Prediction of ToxicoKinetic (TK) Models + maintainer: Virgile Baudrot + description: |- + The MOSAICbioacc application is a turnkey package providing bioaccumulation + factors (BCF/BMF/BSAF) from a toxicokinetic (TK) model fitted to + accumulation-depuration data. It is designed to fulfil the requirements + of regulators when examining applications for market authorization of active + substances. See Ratier et al. (2021) . + date_publication: '2024-02-27' + bug_reports: https://gitlab.in2p3.fr/mosaic-software/rbioacc/-/issues + url: https://gitlab.in2p3.fr/mosaic-software/rbioacc + url_cran: https://CRAN.R-project.org/package=rbioacc + url_git: '' +rbioapi: + version: 0.8.2 + title: User-Friendly R Interface to Biologic Web Services' API + maintainer: Moosa Rezwani + description: |- + Currently fully supports Enrichr, JASPAR, miEAA, PANTHER, + Reactome, STRING, and UniProt! The goal of rbioapi is to provide a + user-friendly and consistent interface to biological databases and + services. In a way that insulates the user from the technicalities of + using web services API and creates a unified and easy-to-use interface + to biological and medical web services. This is an ongoing project; New + databases and services will be added periodically. Feel free to + suggest any databases or services you often use. + date_publication: '2025-02-07' + bug_reports: https://github.com/moosa-r/rbioapi/issues + url: https://rbioapi.moosa-r.com + url_cran: https://CRAN.R-project.org/package=rbioapi + url_git: https://github.com/moosa-r/rbioapi +rbiom: + version: 2.0.13 + title: Read/Write, Analyze, and Visualize 'BIOM' Data + maintainer: Daniel P. Smith + description: |- + A toolkit for working with Biological Observation Matrix ('BIOM') files. + Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and + beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. + Subset based on metadata. Generate visualizations and statistical analyses. + CPU intensive operations are coded in C for speed. + date_publication: '2025-01-24' + bug_reports: https://github.com/cmmr/rbiom/issues + url: https://cmmr.github.io/rbiom/ + url_cran: https://CRAN.R-project.org/package=rbiom + url_git: https://github.com/cmmr/rbiom +rbiouml: + version: '1.11' + title: Interact with BioUML Server + maintainer: Ivan Yevshin + description: Functions for connecting to BioUML server, querying BioUML repository + and launching BioUML analyses. + date_publication: '2021-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbiouml + url_git: '' +rbit: + version: 1.0.0 + title: Binary Indexed Tree + maintainer: Jialun Zhang + description: A simple implementation of Binary Indexed Tree by R. The BinaryIndexedTree + class supports construction of Binary Indexed Tree from a vector, update of a + value in the vector and query for the sum of a interval of the vector. + date_publication: '2018-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbit + url_git: '' +RblDataLicense: + version: 0.2.6 + title: R Interface to 'Bloomberg Data License' + maintainer: Emanuele Guidotti + description: |- + R interface to access prices and market data with the + 'Bloomberg Data License' service from + . + As a prerequisite, a valid Data License from 'Bloomberg' is needed + together with the corresponding SFTP credentials and whitelisting + of the IP from which accessing the service. + This software and its author are in no way affiliated, + endorsed, or approved by 'Bloomberg' or any of its affiliates. + 'Bloomberg' is a registered trademark. + date_publication: '2024-08-22' + bug_reports: https://github.com/eguidotti/RblDataLicense/issues + url: https://rbldatalicense.eguidotti.com + url_cran: https://CRAN.R-project.org/package=RblDataLicense + url_git: '' +Rblpapi: + version: 0.3.15 + title: R Interface to 'Bloomberg' + maintainer: Dirk Eddelbuettel + description: An R Interface to 'Bloomberg' is provided via the 'Blp API'. + date_publication: '2024-09-18' + bug_reports: https://github.com/Rblp/Rblpapi/issues + url: https://dirk.eddelbuettel.com/code/rblpapi.html + url_cran: https://CRAN.R-project.org/package=Rblpapi + url_git: https://github.com/Rblp/Rblpapi +rblt: + version: 0.2.4.7 + title: Bio-Logging Toolbox + maintainer: Sebastien Geiger + description: |- + An R-shiny application to visualize bio-loggers time series at a microsecond precision as Acceleration, Temperature, Pressure, Light intensity. It is possible to link behavioral labels extracted + from 'BORIS' software or manually written in a csv file. + date_publication: '2024-02-19' + bug_reports: https://github.com/sg4r/rblt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rblt + url_git: https://github.com/sg4r/rblt +rbm25: + version: 0.0.3 + title: |- + A Light Wrapper Around the 'BM25' 'Rust' Crate for Okapi BM25 + Text Search + maintainer: David Zimmermann-Kollenda + description: |- + BM25 is a ranking function used by search engines to rank matching documents according to their relevance to a user's search query. + This package provides a light wrapper around the 'BM25' 'rust' crate for Okapi BM25 text search. + For more information, see Robertson et al. (1994) . + date_publication: '2025-01-16' + bug_reports: https://github.com/DavZim/rbm25/issues + url: https://davzim.github.io/rbm25/ + url_cran: https://CRAN.R-project.org/package=rbm25 + url_git: https://github.com/DavZim/rbm25/ +rBMF: + version: '1.1' + title: Boolean Matrix Factorization + maintainer: Abdelmoneim Amer Desouki + description: |- + Provides four boolean matrix factorization (BMF) methods. + BMF has many applications like data mining and categorical data + analysis. BMF is also known as boolean matrix decomposition (BMD) + and was found to be an NP-hard (non-deterministic polynomial-time) + problem. Currently implemented methods are + 'Asso' Miettinen, Pauli and others (2008) + , + 'GreConD' R. Belohlavek, V. Vychodil (2010) + , + 'GreConDPlus' R. Belohlavek, V. Vychodil (2010) + , + 'topFiberM' A. Desouki, M. Roeder, A. Ngonga (2019) + . + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rBMF + url_git: '' +rbmi: + version: 1.4.0 + title: Reference Based Multiple Imputation + maintainer: Craig Gower-Page + description: |- + Implements standard and reference based multiple imputation methods for continuous + longitudinal endpoints (Gower-Page et al. (2022) ). In particular, + this package supports deterministic conditional mean imputation and jackknifing as described + in Wolbers et al. (2022) , Bayesian multiple imputation as described + in Carpenter et al. (2013) , and bootstrapped maximum + likelihood imputation as described in von Hippel and Bartlett (2021) . + date_publication: '2025-02-07' + bug_reports: https://github.com/insightsengineering/rbmi/issues + url: https://insightsengineering.github.io/rbmi/ + url_cran: https://CRAN.R-project.org/package=rbmi + url_git: https://github.com/insightsengineering/rbmi +rbmn: + version: 0.9-6 + title: Handling Linear Gaussian Bayesian Networks + maintainer: Marco Scutari + description: |- + Creation, manipulation, simulation of linear Gaussian Bayesian + networks from text files and more... + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbmn + url_git: '' +RBNZ: + version: 1.1.0 + title: Download Data from the Reserve Bank of New Zealand Website + maintainer: Jasper Watson + description: Provides a convenient way of accessing data published by the Reserve + Bank of New Zealand (RBNZ) on their website, . + A range of financial and economic data is provided in spreadsheet format including + exchange and interest rates, commercial lending statistics, Reserve Bank market + operations, financial institution statistics, household financial data, New Zealand + debt security information, and economic indicators. This package provides a method + to download those spreadsheets and read them directly into R. + date_publication: '2020-07-27' + bug_reports: https://github.com/rntq472/RBNZ/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RBNZ + url_git: '' +rbooster: + version: 1.1.0 + title: AdaBoost Framework for Any Classifier + maintainer: Fatih Saglam + description: |- + This is a simple package which provides a function + that boosts pre-ready or custom-made classifiers. Package + uses Discrete AdaBoost () and Real AdaBoost + () for two class, + SAMME () and + SAMME.R () + for multiclass classification. + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbooster + url_git: '' +Rborist: + version: 0.3-11 + title: |- + Extensible, Parallelizable Implementation of the Random Forest + Algorithm + maintainer: Mark Seligman + description: Scalable implementation of classification and regression forests, as + described by Breiman (2001), . + date_publication: '2025-02-02' + bug_reports: https://github.com/suiji/Arborist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rborist + url_git: https://github.com/suiji/Rborist.CRAN +rbounds: + version: '2.2' + title: |- + Perform Rosenbaum Bounds Sensitivity Tests for Matched and + Unmatched Data + maintainer: Luke J. Keele + description: Takes matched and unmatched data and calculates Rosenbaum bounds for + the treatment effect. Calculates bounds for binary outcome data, Hodges-Lehmann + point estimates, Wilcoxon signed-rank test for matched data and matched IV estimators, + Wilcoxon sum rank test, and for data with multiple matched controls. The sensitivity + analysis methods in this package are documented in Rosenbaum (2002) Observational + Studies, , Springer-Verlag. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbounds + url_git: '' +RBPcurve: + version: '1.2' + title: The Residual-Based Predictiveness Curve + maintainer: Giuseppe Casalicchio + description: |- + The RBP curve is a visual tool to assess the + performance of prediction models. + date_publication: '2017-05-15' + bug_reports: https://github.com/giuseppec/RBPcurve/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RBPcurve + url_git: https://github.com/giuseppec/RBPcurve +rbridge: + version: 1.0.2 + title: Restricted Bridge Estimation + maintainer: Bahadir Yuzbasi + description: Bridge Regression estimation with linear restrictions defined in Yuzbasi + et al. (2019) . Special cases of this approach fit the restricted + LASSO, restricted RIDGE and restricted Elastic Net estimators. + date_publication: '2020-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbridge + url_git: '' +rbscCI: + version: 0.1.1 + title: Blyth-Still-Casella Confidence Interval + maintainer: Shimeng Huang + description: Provides a fast calculation of the Blyth-Still-Casella confidence interval. + The implementation follows the 'StatXact' 9 manual (Cytel 2010) and "Refining + Binomial Confidence Intervals" by George Casella (1986) . + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbscCI + url_git: '' +rbtc: + version: 0.1-7 + title: Bitcoin API + maintainer: Bernhard Pfaff + description: Implementation of the RPC-JSON API for Bitcoin and utility functions + for address creation and content analysis of the blockchain. + date_publication: '2024-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbtc + url_git: '' +RBtest: + version: '1.1' + title: Regression-Based Approach for Testing the Type of Missing Data + maintainer: Serguei Rouzinov + description: |- + The regression-based (RB) approach is a method to test the missing data mechanism. + This package contains two functions that test the type of missing data (Missing Completely + At Random vs Missing At Random) on the basis of the RB approach. The first function applies + the RB approach independently on each variable with missing data, using the completely + observed variables only. The second function tests the missing data mechanism globally + (on all variables with missing data) with the use of all available information. The + algorithm is adapted both to continuous and categorical data. + date_publication: '2020-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RBtest + url_git: '' +rbtt: + version: 0.1.0 + title: |- + Alternative Bootstrap-Based t-Test Aiming to Reduce Type-I Error + for Non-Negative, Zero-Inflated Data + maintainer: Ian Waudby-Smith + description: Tu & Zhou (1999) + showed that comparing the means of populations whose data-generating distributions + are non-negative with excess zero observations is a problem of great importance + in the analysis of medical cost data. In the same study, Tu & Zhou discuss that + it can be difficult to control type-I error rates of general-purpose statistical + tests for comparing the means of these particular data sets. This package allows + users to perform a modified bootstrap-based t-test that aims to better control + type-I error rates in these situations. + date_publication: '2017-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rbtt + url_git: '' +rbw: + version: 0.3.2 + title: Residual Balancing Weights for Marginal Structural Models + maintainer: Xiang Zhou + description: |- + Residual balancing is a robust method of constructing weights for + marginal structural models, which can be used to estimate (a) the average treatment effect in + a cross-sectional observational study, (b) controlled direct/mediator effects in causal mediation + analysis, and (c) the effects of time-varying treatments in panel data (Zhou and Wodtke 2020 + ). This package provides three functions, rbwPoint(), rbwMed(), and rbwPanel(), + that produce residual balancing weights for estimating (a), (b), (c), respectively. + date_publication: '2022-03-01' + bug_reports: https://github.com/xiangzhou09/rbw + url: '' + url_cran: https://CRAN.R-project.org/package=rbw + url_git: https://github.com/xiangzhou09/rbw +RbyExample: + version: 0.0.100 + title: Data for the Book "R by Example" + maintainer: Maria Rizzo + description: |- + Data for the examples and exercises in the book "R by Example". + Jim Albert and Maria Rizzo (2012, ISBN 978-1-4614-1365-3). + date_publication: '2024-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RbyExample + url_git: https://github.com/mariarizzo/RbyExample +RCA: + version: '2.0' + title: Relational Class Analysis + maintainer: Amir Goldberg + description: |- + Relational Class Analysis (RCA) is a method for detecting + heterogeneity in attitudinal data (as described in Goldberg + A., 2011, Am. J. Soc, 116(5)). + date_publication: '2016-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCA + url_git: '' +rcaiman: + version: 1.2.2 + title: CAnopy IMage ANalysis + maintainer: Gastón Mauro Díaz + description: |- + Classify hemispherical + photographs of the plant canopy with algorithms specially developed for + such a task and well documented in + Díaz and Lencinas (2015) and + Díaz and Lencinas (2018) . It supports + non-circular hemispherical photography, such as those acquired with + 15mm lenses or with auxiliary fish-eye lenses attached to mobile devices. + For smartphone-based hemispherical photography see + Díaz (2023) . Most of the functions also + support restricted view photography. + date_publication: '2023-11-14' + bug_reports: https://github.com/GastonMauroDiaz/rcaiman/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcaiman + url_git: '' +RCAL: + version: '2.0' + title: Regularized Calibrated Estimation + maintainer: Zhiqiang Tan + description: Regularized calibrated estimation for causal inference and missing-data + problems with high-dimensional data, based on Tan (2020a) , + Tan (2020b) and Sun and Tan (2020) . + date_publication: '2020-11-05' + bug_reports: '' + url: http://www.stat.rutgers.edu/~ztan + url_cran: https://CRAN.R-project.org/package=RCAL + url_git: '' +RCALI: + version: 0.3.7 + title: Calculation of the Integrated Flow of Particles Between Polygons + maintainer: Jean-Francois Rey + description: |- + Calculate the flow of particles between polygons by two integration methods: + integration by a cubature method and integration on a grid of points. + Annie Bouvier, Kien Kieu, Kasia Adamczyk and Herve Monod (2009) + . + date_publication: '2024-10-22' + bug_reports: '' + url: https://gitlab.paca.inrae.fr/biosp/RCALI + url_cran: https://CRAN.R-project.org/package=RCALI + url_git: '' +Rcan: + version: 1.3.91 + title: Cancer Registry Data Analysis and Visualisation + maintainer: Mathieu Laversanne + description: |- + Tools for basic and advance cancer statistics and graphics. + Groups individual data, merges registry data and population data, calculates age-specific rate, age-standardized rate, cumulative risk, estimated annual percentage rate with standards error. Creates graphics across variable and + time, such as age-specific trends, bar chart and period-cohort trends. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rcan + url_git: https://github.com/timat35/Rcan +Rcapture: + version: 1.4-4 + title: Loglinear Models for Capture-Recapture Experiments + maintainer: Louis-Paul Rivest + description: |- + Estimation of abundance and other demographic parameters for closed + populations, open populations and the robust design in capture-recapture + experiments using loglinear models. + date_publication: '2022-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rcapture + url_git: '' +RCarb: + version: 0.1.6 + title: Dose Rate Modelling of Carbonate-Rich Samples + maintainer: Sebastian Kreutzer + description: Translation of the 'MATLAB' program 'Carb' (Nathan and Mauz 2008 ; + Mauz and Hoffmann 2014) for dose rate modelling for carbonate-rich samples in + the context of trapped charged dating (e.g., luminescence dating) applications. + date_publication: '2022-08-08' + bug_reports: https://github.com/R-Lum/RCarb/issues + url: https://r-lum.github.io/RCarb/ + url_cran: https://CRAN.R-project.org/package=RCarb + url_git: '' +rcarbon: + version: 1.5.1 + title: Calibration and Analysis of Radiocarbon Dates + maintainer: Enrico Crema + description: 'Enables the calibration and analysis of radiocarbon dates, often but + not exclusively for the purposes of archaeological research. It includes functions + not only for basic calibration, uncalibration, and plotting of one or more dates, + but also a statistical framework for building demographic and related longitudinal + inferences from aggregate radiocarbon date lists, including: Monte-Carlo simulation + test (Timpson et al 2014 ), random mark permutation + test (Crema et al 2016 ) and spatial permutation + tests (Crema, Bevan, and Shennan 2017 ).' + date_publication: '2023-08-24' + bug_reports: https://github.com/ahb108/rcarbon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcarbon + url_git: https://github.com/ahb108/rcarbon/ +rcartocolor: + version: 2.1.1 + title: '''CARTOColors'' Palettes' + maintainer: Jakub Nowosad + description: |- + Provides color schemes for maps and other graphics + designed by 'CARTO' as described at . + It includes four types of palettes: aggregation, diverging, qualitative, + and quantitative. + date_publication: '2023-05-13' + bug_reports: https://github.com/Nowosad/rcartocolor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcartocolor + url_git: https://github.com/Nowosad/rcartocolor +Rcatch22: + version: 0.2.3 + title: Calculation of 22 Canonical Time-Series Characteristics + maintainer: Trent Henderson + description: |- + Calculate 22 summary statistics coded in C on time-series vectors to enable + pattern detection, classification, and regression applications in the + feature space as proposed by . + date_publication: '2024-10-02' + bug_reports: https://github.com/hendersontrent/Rcatch22/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=Rcatch22 + url_git: '' +RcausalEGM: + version: 0.3.3 + title: |- + A General Causal Inference Framework by Encoding Generative + Modeling + maintainer: Qiao Liu + description: CausalEGM is a general causal inference framework for estimating causal + effects by encoding generative modeling, which can be applied in both discrete + and continuous treatment settings. A description of the methods is given in Liu + (2022) . + date_publication: '2023-03-28' + bug_reports: https://github.com/SUwonglab/CausalEGM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcausalEGM + url_git: https://github.com/SUwonglab/CausalEGM +rcausim: + version: 0.1.1 + title: Generate Causally-Simulated Data + maintainer: Herdiantri Sufriyana + description: Generate causally-simulated data to serve as ground truth for evaluating + methods in causal discovery and effect estimation. The package provides tools + to assist in defining functions based on specified edges, and conversely, defining + edges based on functions. It enables the generation of data according to these + predefined functions and causal structures. This is particularly useful for researchers + in fields such as artificial intelligence, statistics, biology, medicine, epidemiology, + economics, and social sciences, who are developing a general or a domain-specific + methods to discover causal structures and estimate causal effects. Data simulation + adheres to principles of structural causal modeling. Detailed methodologies and + examples are documented in our vignette, available at . + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcausim + url_git: '' +rCBA: + version: 0.4.3 + title: CBA Classifier + maintainer: Jaroslav Kuchar + description: |- + Provides implementations of a classifier based on the + "Classification Based on Associations" (CBA). It can be used for building + classification models from association rules. Rules are pruned in the order of + precedence given by the sort criteria and a default rule is added. The final + classifier labels provided instances. CBA was originally proposed by Liu, + B. Hsu, W. and Ma, Y. Integrating Classification and Association Rule + Mining. Proceedings KDD-98, New York, 27-31 August. AAAI. pp80-86 (1998, ISBN:1-57735-070-7). + date_publication: '2019-05-29' + bug_reports: https://github.com/jaroslav-kuchar/rCBA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rCBA + url_git: https://github.com/jaroslav-kuchar/rCBA +rcbalance: + version: 1.8.8 + title: Large, Sparse Optimal Matching with Refined Covariate Balance + maintainer: Samuel D. Pimentel + description: |- + Tools for large, sparse optimal matching of treated units + and control units in observational studies. Provisions are + made for refined covariate balance constraints, which include + fine and near-fine balance as special cases. Matches are + optimal in the sense that they are computed as solutions to + network optimization problems rather than greedy algorithms. + See Pimentel, et al.(2015) + and Pimentel (2016), Obs. Studies 2(1):4-23. The rrelaxiv + package, which provides an alternative solver for + the underlying network flow problems, carries an + academic license and is not available on CRAN, but + may be downloaded from Github at + . + date_publication: '2022-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcbalance + url_git: '' +rcbayes: + version: 0.2.0 + title: |- + Estimate Rogers-Castro Migration Age Schedules with Bayesian + Models + maintainer: Jessie Yeung + description: A collection of functions to estimate Rogers-Castro migration age schedules + using 'Stan'. This model which describes the fundamental relationship between + migration and age in the form of a flexible multi-exponential migration model + was most notably proposed in Rogers and Castro (1978) . + date_publication: '2022-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcbayes + url_git: '' +RCBR: + version: 0.6.2 + title: Random Coefficient Binary Response Estimation + maintainer: Roger Koenker + description: |- + Nonparametric maximum likelihood estimation methods + for random coefficient binary response models and some related + functionality for sequential processing of hyperplane arrangements. + See J. Gu and R. Koenker (2020) . + date_publication: '2023-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCBR + url_git: '' +rcbsubset: + version: 1.1.7 + title: Optimal Subset Matching with Refined Covariate Balance + maintainer: Samuel D. Pimentel + description: |- + Tools for optimal subset matching of treated units + and control units in observational studies, with support + for refined covariate balance constraints, (including + fine and near-fine balance as special cases). A close + relative is the 'rcbalance' package. See Pimentel, + et al.(2015) + and Pimentel and Kelz (2020) + . The rrelaxiv + package, which provides an alternative solver for + the underlying network flow problems, carries an + academic license and is not available on CRAN, but + may be downloaded from Github at + . + date_publication: '2022-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcbsubset + url_git: '' +rcc: + version: 1.0.0 + title: Parametric Bootstrapping to Control Rank Conditional Coverage + maintainer: Jean Morrison + description: |- + Functions to implement the parametric and non-parametric bootstrap + confidence interval methods described in Morrison and Simon (2017) . + date_publication: '2017-02-28' + bug_reports: http://github.com/jean997/rcc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcc + url_git: http://github.com/jean997/rcc +rcccd: + version: 0.3.2 + title: Class Cover Catch Digraph Classification + maintainer: Fatih Saglam + description: |- + Fit Class Cover Catch Digraph Classification models that can be + used in machine learning. Pure and proper and random walk approaches are + available. Methods are explained in Priebe et al. (2001) + , Priebe et al. (2003) + , and Manukyan and Ceyhan (2016) + . + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcccd + url_git: '' +rccola: + version: 1.0.2 + title: |- + Safely Manage API Keys and Load Data from a REDCap or Other + Source + maintainer: Shawn Garbett + description: |- + The handling of an API key (misnomer for password) for protected + data can be difficult. This package provides secure convenience functions for + entering / handling API keys and pulling data directly into memory. By default + it will load from REDCap instances, but other sources are injectable via + inversion of control. + date_publication: '2022-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rccola + url_git: https://github.com/spgarbet/rccola +RCCPCA: + version: 0.1.0 + title: '"Retained Component Criterion for Principal Component Analysis"' + maintainer: Dr. Fayed Alshammri + description: The RCC_PCA criterion is a tool to determine the optimal number of + components to retain in PCA;See Alshammri (2021). + date_publication: '2021-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCCPCA + url_git: '' +rcdd: + version: '1.6' + title: Computational Geometry + maintainer: Charles J. Geyer + description: |- + R interface to (some of) cddlib + (). + Converts back and forth between two representations of a convex polytope: + as solution of a set of linear equalities and inequalities and as + convex hull of set of points and rays. + Also does linear programming and redundant generator elimination + (for example, convex hull in n dimensions). All functions can use exact + infinite-precision rational arithmetic. + date_publication: '2023-12-15' + bug_reports: '' + url: https://www.stat.umn.edu/geyer/rcdd/ + url_cran: https://CRAN.R-project.org/package=rcdd + url_git: https://github.com/cjgeyer/rcdd +rcDEA: + version: '1.0' + title: Robust and Conditional Data Envelopment Analysis (DEA) + maintainer: Anna Mergoni + description: |- + With this package we provide an easy method to compute robust and conditional Data Envelopment Analysis (DEA), + Free Disposal Hull (FDH) and Benefit of the Doubt (BOD) scores. + The robust approach is based on the work of Cazals, Florens and Simar (2002) . + The conditional approach is based on Daraio and Simar (2007) . + Besides we provide graphs to help with the choice of m. + We relay on the 'Benchmarking' package to compute the efficiency scores and on the 'np' package to compute non parametric estimation of similarity among units. + date_publication: '2021-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcDEA + url_git: '' +rcdk: + version: 3.8.1 + title: Interface to the 'CDK' Libraries + maintainer: Zachary Charlop-Powers + description: |- + Allows the user to access functionality in the + 'CDK', a Java framework for chemoinformatics. This allows the user to load + molecules, evaluate fingerprints, calculate molecular descriptors and so on. + In addition, the 'CDK' API allows the user to view structures in 2D. + date_publication: '2023-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcdk + url_git: '' +rcdklibs: + version: '2.9' + title: The CDK Libraries Packaged for R + maintainer: Zachary Charlop-Powers + description: |- + An R interface to the Chemistry Development Kit, a Java library + for chemoinformatics. Given the size of the library itself, this package is + not expected to change very frequently. To make use of the CDK within R, it is + suggested that you use the 'rcdk' package. Note that it is possible to directly + interact with the CDK using 'rJava'. However 'rcdk' exposes functionality in a more + idiomatic way. The CDK library itself is released as LGPL and the sources can be + obtained from . + date_publication: '2024-03-03' + bug_reports: '' + url: https://cdk-r.github.io/rcdklibs/ + url_cran: https://CRAN.R-project.org/package=rcdklibs + url_git: '' +RCDT: + version: 1.3.0 + title: Fast 2D Constrained Delaunay Triangulation + maintainer: Stéphane Laurent + description: |- + Performs 2D Delaunay triangulation, constrained or + unconstrained, with the help of the C++ library 'CDT'. A function to + plot the triangulation is provided. The constrained Delaunay + triangulation has applications in geographic information systems. + date_publication: '2023-10-31' + bug_reports: https://github.com/stla/RCDT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RCDT + url_git: https://github.com/stla/RCDT +RCEIM: + version: '0.3' + title: R Cross Entropy Inspired Method for Optimization + maintainer: Alberto Krone-Martins + description: An implementation of a stochastic heuristic method for performing multidimensional + function optimization. The method is inspired in the Cross-Entropy Method. It + does not relies on derivatives, neither imposes particularly strong requirements + into the function to be optimized. Additionally, it takes profit from multi-core + processing to enable optimization of time-consuming functions. + date_publication: '2017-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCEIM + url_git: '' +rcens: + version: 0.1.1 + title: Generate Sample Censoring + maintainer: Daniel Saavedra + description: Provides functions to generate censored samples of type I, II and III, + from any random sample generator. It also supplies the option to create left and + right censorship. Along with this, the generation of samples with interval censoring + is in the testing phase, with two options of fixed length intervals and random + lengths. + date_publication: '2024-03-19' + bug_reports: https://github.com/dlsaavedra/rcens/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcens + url_git: https://github.com/dlsaavedra/rcens +Rcereal: + version: 1.3.2 + title: '"Cereal Headers for R and C++ Serialization"' + maintainer: Wush Wu + description: |- + To facilitate using 'cereal' with R via 'cpp11' or 'Rcpp'. 'cereal' + is a header-only C++11 serialization library. 'cereal' takes arbitrary data + types and reversibly turns them into different representations, such as + compact binary encodings, 'XML', or 'JSON'. 'cereal' was designed to be + fast, light-weight, and easy to extend - it has no external dependencies and + can be easily bundled with other code or used standalone. Please see + for more information. + date_publication: '2024-09-20' + bug_reports: https://github.com/wush978/Rcereal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rcereal + url_git: https://github.com/wush978/Rcereal/ +RcextTools: + version: 0.1.1 + title: |- + Analytical Procedures in Support of Brazilian Public Sector + External Auditing + maintainer: Bruno Melo + description: Set of analytical procedures based on advanced data analysis in support + of Brazil's public sector external control activity. + date_publication: '2017-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcextTools + url_git: http://github.com/brunomssmelo/RcextTools/ +RCGLS: + version: 1.0.3 + title: |- + Download and Open Data Provided by the Copernicus Global Land + Service + maintainer: Willemijn Vroege + description: 'Download and open manifest files provided by the Copernicus Global + Land Service data . The manifest files are + available at: . Also see: . + Before you can download the data, you will first need to register to create a + username and password.' + date_publication: '2020-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCGLS + url_git: '' +rchallenge: + version: 1.3.4 + title: A Simple Data Science Challenge System + maintainer: Adrien Todeschini + description: |- + A simple data science challenge system using R Markdown and 'Dropbox' . + It requires no network configuration, does not depend on external platforms + like e.g. 'Kaggle' and can be easily installed on a personal computer. + date_publication: '2021-03-09' + bug_reports: https://github.com/adrtod/rchallenge/issues + url: https://adrien.tspace.fr/rchallenge/ + url_cran: https://CRAN.R-project.org/package=rchallenge + url_git: https://github.com/adrtod/rchallenge +rchemo: + version: 0.1-3 + title: |- + Dimension Reduction, Regression and Discrimination for + Chemometrics + maintainer: Marion Brandolini-Bunlon + description: |- + Data exploration and prediction with focus on high dimensional data and chemometrics. + The package was initially designed about partial least squares regression and discrimination models and variants, in particular locally weighted PLS models (LWPLS). Then, it has been expanded to many other methods for analyzing high dimensional data. + The name 'rchemo' comes from the fact that the package is orientated to chemometrics, but most of the provided methods are fully generic to other domains. + Functions such as transform(), predict(), coef() and summary() are available. Tuning the predictive models is facilitated by generic functions gridscore() (validation dataset) and gridcv() (cross-validation). Faster versions are also available for models based on latent variables (LVs) (gridscorelv() and gridcvlv()) and ridge regularization (gridscorelb() and gridcvlb()). + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rchemo + url_git: https://github.com/ChemHouse-group/rchemo/ +rcheology: + version: 4.4.2.0 + title: |- + Data on Base and Recommended Packages for Current and Previous + Versions of R + maintainer: David Hugh-Jones + description: Provides a dataset of functions in all base and recommended packages + of R versions 0.50 onwards. + date_publication: '2024-11-11' + bug_reports: https://github.com/hughjonesd/rcheology/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcheology + url_git: https://github.com/hughjonesd/rcheology +RChest: + version: 1.0.3 + title: Locating Distributional Changes in Highly Dependent Time Series + maintainer: Lukas Zierahn + description: |- + Provides algorithms to locate multiple + distributional change-points in piecewise stationary time series. The + algorithms are provably consistent, even in the presence of long-range + dependencies. Knowledge of the number of change-points is not + required. The code is written in Go and interfaced with R. + date_publication: '2021-02-13' + bug_reports: https://github.com/azalk/GoChest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RChest + url_git: https://github.com/azalk/GoChest +RchivalTag: + version: 0.1.9 + title: Analyzing and Interactive Visualization of Archival Tagging Data + maintainer: Robert K. Bauer + description: A set of functions to generate, access and analyze standard data products + from archival tagging data. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RchivalTag + url_git: '' +Rchoice: + version: 0.3-6 + title: |- + Discrete Choice (Binary, Poisson and Ordered) Models with Random + Parameters + maintainer: Mauricio Sarrias + description: An implementation of simulated maximum likelihood method for the estimation + of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with + random parameters for cross-sectional and longitudinal data as presented in Sarrias + (2016) . + date_publication: '2023-03-10' + bug_reports: https://github.com/mauricio1986/Rchoice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rchoice + url_git: https://github.com/mauricio1986/Rchoice +rChoiceDialogs: + version: 1.0.6.1 + title: '''rChoiceDialogs'' Collection' + maintainer: Alex Lisovich + description: Collection of portable choice dialog widgets. + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rChoiceDialogs + url_git: '' +rchroma: + version: 0.1.0 + title: A Client for 'ChromaDB' + maintainer: David Schoch + description: Client for 'ChromaDB', a vector database for storing and querying embeddings. + This package provides a convenient interface to interact with the REST API of + 'ChromaDB' . + date_publication: '2025-02-13' + bug_reports: https://github.com/cynkra/rchroma/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rchroma + url_git: https://github.com/cynkra/rchroma +RChronoModel: + version: '0.4' + title: |- + Post-Processing of the Markov Chain Simulated by ChronoModel or + Oxcal + maintainer: Anne Philippe + description: Provides a list of functions for the statistical analysis and the post-processing + of the Markov Chains simulated by ChronoModel (see + for more information). ChronoModel is a friendly software to construct a chronological + model in a Bayesian framework. Its output is a sampled Markov chain from the + posterior distribution of dates component the chronology. The functions can also + be applied to the analyse of mcmc output generated by Oxcal software. + date_publication: '2017-01-12' + bug_reports: '' + url: http://www.chronomodel.fr + url_cran: https://CRAN.R-project.org/package=RChronoModel + url_git: '' +rciplot: + version: 0.1.1 + title: Plot Jacobson-Truax Reliable Change Indices + maintainer: Maximilian Hagspiel + description: |- + The concept of reliable and clinically significant change + (Jacobson & Truax, 1991) helps you answer the following questions for a + sample with two measurements at different points in time (pre & post): + Which proportion of my sample has a (considering the reliability of the + instrument) probably not-just-by-chance difference in pre- vs. post-scores? + Which proportion of my sample does not only change in a statistically + significant way (see question one), but also in a clinically significant way + (e.g. change from a test score regarded "dysfunctional" to a score regarded + "functional")? + This package allows you to very easily create a scatterplot of your sample + in which the x-axis maps to the pre-scores, the y-axis maps to the + post-scores and several graphical elements (lines, colors) allow you to gain + a quick overview about reliable changes in these scores. + An example of this kind of plot is Figure 2 of Jacobson & Truax (1991). + Referenced article: + Jacobson, N. S., & Truax, P. (1991) . + date_publication: '2023-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rciplot + url_git: https://gitlab.com/REDS1736/rciplot +RCircos: + version: 1.2.2 + title: Circos 2D Track Plot + maintainer: Hongen Zhang + description: 'A simple and flexible way to generate Circos 2D track plot images + for genomic data visualization is implemented in this package. The types of plots + include: heatmap, histogram, lines, scatterplot, tiles and plot items for further + decorations include connector, link (lines and ribbons), and text (gene) label. + All functions require only R graphics package that comes with R base installation.' + date_publication: '2021-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCircos + url_git: https://github.com/hzhanghenry/RCircos +rcites: + version: 1.3.0 + title: R Interface to the Species+ Database + maintainer: Kevin Cazelles + description: A programmatic interface to the Species+ + database via the Species+/CITES Checklist API . + date_publication: '2023-02-12' + bug_reports: https://github.com/ropensci/rcites/issues + url: https://docs.ropensci.org/rcites/ + url_cran: https://CRAN.R-project.org/package=rcites + url_git: https://github.com/ropensci/rcites +RCLabels: + version: 0.1.11 + title: Manipulate Matrix Row and Column Labels with Ease + maintainer: Matthew Heun + description: |- + Functions to assist manipulation of matrix + row and column labels for all types of matrix mathematics + where row and column labels are to be respected. + date_publication: '2025-01-13' + bug_reports: '' + url: https://matthewheun.github.io/RCLabels/ + url_cran: https://CRAN.R-project.org/package=RCLabels + url_git: '' +RClickhouse: + version: 0.6.10 + title: '''Yandex Clickhouse'' Interface for R with Basic ''dplyr'' Support' + maintainer: Christian Hotz-Behofsits + description: |- + 'Yandex Clickhouse' () is a high-performance relational column-store database to enable + big data exploration and 'analytics' scaling to petabytes of data. Methods are + provided that enable working with 'Yandex Clickhouse' databases via + 'DBI' methods and using 'dplyr'/'dbplyr' idioms. + date_publication: '2025-02-26' + bug_reports: https://github.com/IMSMWU/RClickhouse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RClickhouse + url_git: https://github.com/IMSMWU/RClickhouse +RClimacell: + version: 0.1.4 + title: R Wrapper for the 'Climacell' API + maintainer: Nikhil Agarwal + description: |- + 'Climacell' is a weather platform that provides hyper-local forecasts and weather + data. This package enables the user to query the core layers of the + time line interface of the 'Climacell' v4 API . + This package requires a valid API key. See vignettes for instructions on use. + date_publication: '2021-03-23' + bug_reports: https://github.com/nikdata/RClimacell/issues + url: https://nikdata.github.io/RClimacell/ + url_cran: https://CRAN.R-project.org/package=RClimacell + url_git: '' +rclipboard: + version: 0.2.1 + title: Shiny/R Wrapper for 'clipboard.js' + maintainer: Sebastien Bihorel + description: |- + Leverages the functionality of 'clipboard.js', a JavaScript library + for HMTL5-based copy to clipboard from web pages (see + for more information), and provides a reactive copy-to-clipboard UI button + component, called 'rclipButton', and a a reactive copy-to-clipboard UI link + component, called 'rclipLink', for 'shiny' R applications. + date_publication: '2023-11-15' + bug_reports: https://github.com/sbihorel/rclipboard/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=rclipboard + url_git: https://github.com/sbihorel/rclipboard/ +RclusTool: + version: 0.91.6 + title: |- + Graphical Toolbox for Clustering and Classification of Data + Frames + maintainer: Pierre-Alexandre Hebert + description: |- + Graphical toolbox for clustering and classification of data frames. + It proposes a graphical interface to process clustering and classification methods on features + data-frames, and to view initial data as well as resulted cluster or classes. According to the + level of available labels, different approaches are proposed: unsupervised clustering, + semi-supervised clustering and supervised classification. + To assess the processed clusters or classes, the toolbox can import and show some supplementary + data formats: either profile/time series, or images. + These added information can help the expert to label clusters (clustering), or to constrain data + frame rows (semi-supervised clustering), using Constrained spectral embedding algorithm by + Wacquet et al. (2013) and the methodology provided by + Wacquet et al. (2013) . + date_publication: '2024-02-27' + bug_reports: '' + url: mawenzi.univ-littoral.fr/RclusTool + url_cran: https://CRAN.R-project.org/package=RclusTool + url_git: '' +rCMA: + version: 1.1.1 + title: R-to-Java Interface for 'CMA-ES' + maintainer: Wolfgang Konen + description: |- + Tool for providing access to the Java version 'CMAEvolutionStrategy' of + Nikolaus Hansen. 'CMA-ES' is the Covariance Matrix Adaptation Evolution Strategy, + see . + date_publication: '2022-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rCMA + url_git: '' +rcmdcheck: + version: 1.4.0 + title: Run 'R CMD check' from 'R' and Capture Results + maintainer: Gábor Csárdi + description: |- + Run 'R CMD check' from 'R' and capture the results + of the individual checks. Supports running checks in the background, + timeouts, pretty printing and comparing check results. + date_publication: '2021-09-27' + bug_reports: https://github.com/r-Lib/rcmdcheck/issues + url: https://r-lib.github.io/rcmdcheck/ + url_cran: https://CRAN.R-project.org/package=rcmdcheck + url_git: https://github.com/r-Lib/rcmdcheck#readme +Rcmdr: + version: 2.9-5 + title: R Commander + maintainer: John Fox + description: A platform-independent basic-statistics GUI (graphical user interface) + for R, based on the tcltk package. + date_publication: '2024-10-24' + bug_reports: '' + url: https://www.john-fox.ca/RCommander/index.html + url_cran: https://CRAN.R-project.org/package=Rcmdr + url_git: https://github.com/RCmdr-Project/rcmdr +RcmdrMisc: + version: 2.9-1 + title: R Commander Miscellaneous Functions + maintainer: John Fox + description: |2- + + Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R. + date_publication: '2023-09-26' + bug_reports: '' + url: https://socialsciences.mcmaster.ca/jfox/ + url_cran: https://CRAN.R-project.org/package=RcmdrMisc + url_git: '' +RcmdrPlugin.aRnova: + version: 0.0.5 + title: R Commander Plug-in for Repeated-Measures ANOVA + maintainer: Arnaud Travert + description: |- + R Commander plug-in for repeated-measures and mixed-design + ('split-plot') ANOVA. + It adds a new menu entry for repeated measures that allows + to deal with up to three within-subject factors and optionally with + one or several between-subject factors. + It also provides supplementary options to oneWayAnova() and + multiWayAnova() functions, such as choice of ANOVA type, display of + effect sizes and post hoc analysis for multiWayAnova(). + date_publication: '2018-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.aRnova + url_git: '' +RcmdrPlugin.BiclustGUI: + version: 1.1.3.1 + title: '''Rcmdr'' Plug-in GUI for Biclustering' + maintainer: De Troyer Ewoud + description: |- + A plug-in for R Commander ('Rcmdr'). The package is a Graphical + User Interface (GUI) in which several biclustering methods can be executed, + followed by diagnostics and plots of the results. Further, the GUI also has + the possibility to connect the methods to more general diagnostic packages for + biclustering. Biclustering methods from 'biclust', 'fabia', 's4vd', 'iBBiG', + 'isa2', 'BiBitR', 'rqubic' and 'BicARE' are implemented. Additionally, 'superbiclust' and + 'BcDiag' are also implemented to be able to further investigate results. The + GUI also provides a couple of extra utilities to export, save, search through + and plot the results. 'RcmdrPlugin.BiclustGUI' also provides a very specific + framework for biclustering in which new methods, diagnostics and plots can be + added. Scripts were prepared so that R-package developers can freely design + their own dialogs in the GUI which can then be added by the maintainer of + 'RcmdrPlugin.BiclustGUI'. These scripts do not required any knowledge of 'tcltk' + and 'Rcmdr' and are easy to fill in. (Note: rqubic currently requires manual installation through BiocManager::install('rqubic').) + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.BiclustGUI + url_git: '' +RcmdrPlugin.BWS1: + version: 0.2-2 + title: R Commander Plug-in for Case 1 Best-Worst Scaling + maintainer: Hideo Aizaki + description: Adds menu items to the R Commander for implementing case 1 (object + case) best-worst scaling (BWS1) from designing choice sets to measuring preferences + for items. BWS1 is a question-based survey method that constructs various combinations + of items (choice sets) using the experimental designs, asks respondents to select + the best and worst items in each choice set, and then measures preferences for + the items by analyzing the responses. For details on BWS1, refer to Louviere et + al. (2015) . + date_publication: '2024-05-21' + bug_reports: '' + url: https://sites.google.com/view/r4sp/rcmdrplugin + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.BWS1 + url_git: '' +RcmdrPlugin.BWS2: + version: 0.2-2 + title: R Commander Plug-in for Case 2 Best-Worst Scaling + maintainer: Hideo Aizaki + description: Adds menu items for case 2 (profile case) best-worst scaling (BWS2) + to the R Commander. BWS2 is a question-based survey method that constructs profiles + (combinations of attribute levels) using an orthogonal array, asks respondents + to select the best and worst levels in each profile, and measures preferences + for attribute levels by analyzing the responses. For details, see Aizaki and Fogarty + (2019) . + date_publication: '2024-05-21' + bug_reports: '' + url: https://sites.google.com/view/r4sp/rcmdrplugin + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.BWS2 + url_git: '' +RcmdrPlugin.BWS3: + version: 0.2-3 + title: R Commander Plug-in for Case 3 Best-Worst Scaling + maintainer: Hideo Aizaki + description: Adds menu items for case 3 (multi-profile) best-worst scaling (BWS3) + to the R Commander. BWS3 is a question-based survey method that designs various + combinations of attribute levels (profiles), asks respondents to select the best + and worst profiles in each choice set, and then measures preferences for the attribute + levels by analyzing the responses. For details on BWS3, refer to Louviere et al. + (2015) . + date_publication: '2024-05-21' + bug_reports: '' + url: https://sites.google.com/view/r4sp/rcmdrplugin + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.BWS3 + url_git: '' +RcmdrPlugin.cpd: + version: 0.2.0 + title: R Commander Plug-in for Complex Pearson Distributions + maintainer: Silverio Vilchez-Lopez + description: Provides an 'Rcmdr' plug-in based on the 'cpd' package. + date_publication: '2022-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.cpd + url_git: '' +RcmdrPlugin.DCCV: + version: 0.1-5 + title: R Commander Plug-in for Dichotomous Choice Contingent Valuation + maintainer: Hideo Aizaki + description: Adds menu items to the R Commander for parametric analysis of dichotomous + choice contingent valuation (DCCV) data. CV is a question-based survey method + to elicit individuals' preferences for goods and services. This package depends + on functions regarding parametric DCCV analysis in the package DCchoice. See Carson + and Hanemann (2005) for DCCV. + date_publication: '2024-05-21' + bug_reports: '' + url: https://sites.google.com/view/r4sp/rcmdrplugin + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.DCCV + url_git: '' +RcmdrPlugin.DCE: + version: 0.2-3 + title: R Commander Plug-in for Discrete Choice Experiments + maintainer: Hideo Aizaki + description: Adds menu items for discrete choice experiments (DCEs) to the R Commander. + DCE is a question-based survey method that designs various combinations (profiles) + of attribute levels using the experimental designs, asks respondents to select + the most preferred profile in each choice set, and then measures preferences for + the attribute levels by analyzing the responses. For details on DCEs, refer to + Louviere et al. (2000) . + date_publication: '2024-05-21' + bug_reports: '' + url: https://sites.google.com/view/r4sp/rcmdrplugin + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.DCE + url_git: '' +RcmdrPlugin.depthTools: + version: '1.4' + title: R Commander Depth Tools Plug-in + maintainer: Aurora Torrente + description: |- + We provide an Rcmdr plug-in based on the depthTools + package, which implements different robust statistical tools + for the description and analysis of gene expression data based + on the Modified Band Depth, namely, the scale curves for + visualizing the dispersion of one or various groups of samples + (e.g. types of tumors), a rank test to decide whether two + groups of samples come from a single distribution and two + methods of supervised classification techniques, the DS and + TAD methods. + date_publication: '2020-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.depthTools + url_git: '' +RcmdrPlugin.DoE: + version: 0.12-6 + title: R Commander Plugin for (Industrial) Design of Experiments + maintainer: Ulrike Groemping + description: Provides a platform-independent GUI for design of experiments. The + package is implemented as a plugin to the R-Commander, which is a more general + graphical user interface for statistics in R based on tcl/tk. DoE functionality + can be accessed through the menu Design that is added to the R-Commander menus. + date_publication: '2024-10-29' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/DoE/ + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.DoE + url_git: '' +RcmdrPlugin.EACSPIR: + version: 0.2-3 + title: Plugin de R-Commander para el Manual 'EACSPIR' + maintainer: David Leiva + description: Este paquete proporciona una interfaz grafica de usuario (GUI) para + algunos de los procedimientos estadisticos detallados en un curso de 'Estadistica + aplicada a las Ciencias Sociales mediante el programa informatico R' (EACSPIR). + LA GUI se ha desarrollado como un Plugin del programa R-Commander. + date_publication: '2022-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.EACSPIR + url_git: '' +RcmdrPlugin.EBM: + version: 1.0-10 + title: Rcmdr Evidence Based Medicine Plug-in Package + maintainer: Daniel-Corneliu Leucuta + description: Rcmdr plug-in GUI extension for Evidence Based Medicine medical indicators + calculations (Sensitivity, specificity, absolute risk reduction, relative risk, + ...). + date_publication: '2015-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.EBM + url_git: '' +RcmdrPlugin.EcoVirtual: + version: '1.0' + title: Rcmdr EcoVirtual Plugin + maintainer: Alexandre Adalardo de Oliveira + description: A Rcmdr "plug-in" for the EcoVirtual package, designed primarily for + teaching ecological models using simulations. + date_publication: '2016-07-01' + bug_reports: '' + url: http://ecovirtual.ib.usp.br + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.EcoVirtual + url_git: '' +RcmdrPlugin.Export: + version: 0.3-1 + title: Export R Output to LaTeX or HTML + maintainer: Liviu Andronic + description: |- + Export Rcmdr output to LaTeX or HTML code. The + plug-in was originally intended to facilitate exporting Rcmdr + output to formats other than ASCII text and to provide R + novices with an easy-to-use, easy-to-access reference on + exporting R objects to formats suited for printed output. The + package documentation contains several pointers on creating + reports, either by using conventional word processors or + LaTeX/LyX. + date_publication: '2015-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.Export + url_git: '' +RcmdrPlugin.EZR: + version: '1.68' + title: R Commander Plug-in for the EZR (Easy R) Package + maintainer: Yoshinobu Kanda + description: 'EZR (Easy R) adds a variety of statistical functions, including survival + analyses, ROC analyses, metaanalyses, sample size calculation, and so on, to the + R commander. EZR enables point-and-click easy access to statistical functions, + especially for medical statistics. EZR is platform-independent and runs on Windows, + Mac OS X, and UNIX. Its complete manual is available only in Japanese (Chugai + Igakusha, ISBN: 978-4-498-10918-6, Nankodo, ISBN: 978-4-524-26158-1, Ohmsha, ISBN: + 978-4-274-22632-8), but an report that introduced the investigation of EZR was + published in Bone Marrow Transplantation (Nature Publishing Group) as an Open + article. This report can be used as a simple manual. It can be freely downloaded + from the journal website as shown below. This report has been cited in more than + 10,000 scientific articles.' + date_publication: '2024-06-25' + bug_reports: '' + url: https://www.nature.com/articles/bmt2012244.pdfhttps://www.jichi.ac.jp/saitama-sct/SaitamaHP.files/statmedEN.html + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.EZR + url_git: '' +RcmdrPlugin.FactoMineR: + version: '1.8' + title: Graphical User Interface for FactoMineR + maintainer: Francois Husson + description: Rcmdr Plugin for the 'FactoMineR' package. + date_publication: '2023-11-17' + bug_reports: '' + url: http://factominer.free.fr/graphs/RcmdrPlugin.html + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.FactoMineR + url_git: '' +RcmdrPlugin.GWRM: + version: 1.0.2 + title: |- + R Commander Plug-in for Fitting Generalized Waring Regression + Models + maintainer: Silverio Vilchez-Lopez + description: Provides an Rcmdr "plug-in" based on the GWRM package. + date_publication: '2017-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.GWRM + url_git: '' +RcmdrPlugin.HH: + version: 1.1-51 + title: Rcmdr Support for the HH Package + maintainer: Richard M. Heiberger + description: |- + Rcmdr menu support for many of the functions in the HH package. + The focus is on menu items for functions we use in our introductory + courses. + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.HH + url_git: '' +RcmdrPlugin.KMggplot2: + version: 0.2-6 + title: R Commander Plug-in for Data Visualization with 'ggplot2' + maintainer: Triad sou. + description: |- + A GUI front-end for 'ggplot2' supports Kaplan-Meier plot, histogram, + Q-Q plot, box plot, errorbar plot, scatter plot, line chart, pie chart, + bar chart, contour plot, and distribution plot. + date_publication: '2019-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.KMggplot2 + url_git: '' +RcmdrPlugin.MA: + version: 0.0-2 + title: Graphical User Interface for Conducting Meta-Analyses in R + maintainer: A. C. Del Re + description: |- + Easy to use interface for conducting meta-analysis in R. This + package is an Rcmdr-plugin, which allows the user to conduct analyses in a + menu-driven, graphical user interface environment (e.g., CMA, SPSS). It + uses recommended procedures as described in The Handbook of Research + Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009). + date_publication: '2014-09-21' + bug_reports: '' + url: http://acdelre.weebly.com/ + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.MA + url_git: '' +RcmdrPlugin.MPAStats: + version: 1.2.2 + title: R Commander Plug-in for MPA Statistics + maintainer: Andrew Heiss + description: |- + Extends R Commander with a unified menu of new and pre-existing + statistical functions related to public management and policy analysis + statistics. Functions and menus have been renamed according to the + usage in PMGT 630 in the Master of Public Administration program at + Brigham Young University. + date_publication: '2018-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.MPAStats + url_git: '' +RcmdrPlugin.NMBU: + version: 1.8.15 + title: R Commander Plug-in for University Level Applied Statistics + maintainer: Kristian Hovde Liland + description: |- + An R Commander "plug-in" extending functionality of linear models + and providing an interface to Partial Least Squares Regression and Linear and + Quadratic Discriminant analysis. Several statistical summaries are extended, + predictions are offered for additional types of analyses, and extra plots, tests + and mixed models are available. + date_publication: '2024-03-11' + bug_reports: https://github.com/khliland/RcmdrPlugin.NMBU/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.NMBU + url_git: https://github.com/khliland/RcmdrPlugin.NMBU/ +RcmdrPlugin.orloca: + version: 4.8.2 + title: A GUI for Planar Location Problems + maintainer: Manuel Munoz-Marquez + description: A GUI for the orloca package is provided as a Rcmdr plug-in. The package + deals with continuos planar location problems. + date_publication: '2021-05-12' + bug_reports: '' + url: http://knuth.uca.es/orloca/ + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.orloca + url_git: '' +RcmdrPlugin.PcaRobust: + version: 1.1.4 + title: R Commander Plug-in for Robust Principal Component Analysis + maintainer: Achmad Fauzi Bagus F + description: The R commander plug-in for robust principal component analysis. The + Graphical User Interface for Principal Component Analysis (PCA) with Hubert Algorithm + method. + date_publication: '2016-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.PcaRobust + url_git: '' +RcmdrPlugin.RiskDemo: + version: '3.2' + title: R Commander Plug-in for Risk Demonstration + maintainer: Arto Luoma + description: R Commander plug-in to demonstrate various actuarial and financial + risks. It includes valuation of bonds and stocks, portfolio optimization, classical + ruin theory, demography and epidemic. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.RiskDemo + url_git: '' +RcmdrPlugin.RMTCJags: + version: 1.0-2 + title: R MTC Jags 'Rcmdr' Plugin + maintainer: Marcelo Goulart Correia + description: Mixed Treatment Comparison is a methodology to compare directly and/or + indirectly health strategies (drugs, treatments, devices). This package provides + an 'Rcmdr' plugin to perform Mixed Treatment Comparison for binary outcome using + BUGS code from Bristol University (Lu and Ades). + date_publication: '2016-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.RMTCJags + url_git: '' +RcmdrPlugin.ROC: + version: 1.0-19 + title: Rcmdr Receiver Operator Characteristic Plug-in Package + maintainer: Daniel-Corneliu Leucuta + description: Rcmdr GUI extension plug-in for Receiver Operator Characteristic tools + from pROC package. Also it ads a Rcmdr GUI extension for Hosmer and Lemeshow GOF + test from the package ResourceSelection. + date_publication: '2022-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.ROC + url_git: '' +RcmdrPlugin.sos: + version: 0.3-0 + title: Efficiently search the R help pages + maintainer: Liviu Andronic + description: |- + Rcmdr interface to the 'sos' package. The plug-in renders + the 'sos' searching functionality easily accessible via the Rcmdr + menus. It also simplifies the task of performing multiple searches and + subsequently obtaining the union or the intersection of the results. + date_publication: '2013-12-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.sos + url_git: '' +RcmdrPlugin.survival: + version: 1.3-2 + title: R Commander Plug-in for the 'survival' Package + maintainer: John Fox + description: |- + An R Commander plug-in for the survival + package, with dialogs for Cox models, parametric survival regression models, + estimation of survival curves, and testing for differences in survival + curves, along with data-management facilities and a variety of tests, + diagnostics and graphs. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.survival + url_git: '' +RcmdrPlugin.TeachingDemos: + version: 1.2-0 + title: Rcmdr Teaching Demos Plug-in + maintainer: John Fox + description: Provides an Rcmdr "plug-in" based on the TeachingDemos package, and + is primarily for illustrative purposes. + date_publication: '2020-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.TeachingDemos + url_git: '' +RcmdrPlugin.TeachStat: + version: 1.1.3 + title: R Commander Plugin for Teaching Statistical Methods + maintainer: Manuel A. Mosquera Rodríguez + description: |- + R Commander plugin for teaching statistical methods. + It adds a new menu for making easier the teaching of the main concepts about the main statistical methods. + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.TeachStat + url_git: '' +RcmdrPlugin.temis: + version: 0.7.10 + title: Graphical Integrated Text Mining Solution + maintainer: Milan Bouchet-Valat + description: |- + An 'R Commander' plug-in providing an integrated solution to perform + a series of text mining tasks such as importing and cleaning a corpus, and + analyses like terms and documents counts, vocabulary tables, terms + co-occurrences and documents similarity measures, time series analysis, + correspondence analysis and hierarchical clustering. Corpora can be imported + from spreadsheet-like files, directories of raw text files, 'Twitter' queries, + as well as from 'Dow Jones Factiva', 'LexisNexis', 'Europresse' and 'Alceste' files. + date_publication: '2018-06-22' + bug_reports: https://github.com/nalimilan/R.TeMiS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.temis + url_git: https://github.com/nalimilan/R.TeMiS +RcmdrPlugin.UCA: + version: 5.1-2 + title: UCA Rcmdr Plug-in + maintainer: Manuel Munoz-Marquez + description: |- + Some extensions to Rcmdr (R Commander), randomness test, + variance test for one normal sample and predictions using active model, + made by R-UCA project and used in teaching statistics at University of Cadiz (UCA). + date_publication: '2024-09-26' + bug_reports: '' + url: http://knuth.uca.es/RcmdrPlugin.UCA/ + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.UCA + url_git: '' +RcmdrPlugin.WorldFlora: + version: '1.3' + title: R Commander Plug-in for the 'WorldFlora' Package + maintainer: Roeland Kindt + description: An R Commander plug-in for the 'WorldFlora' package. It was mainly + developed to show work flows and scripts for first-time users. + date_publication: '2023-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcmdrPlugin.WorldFlora + url_git: '' +RCMinification: + version: '1.2' + title: Random Coefficient Minification Time Series Models + maintainer: L. Han + description: Data sets, and functions for simulating and fitting nonlinear time + series with minification and nonparametric models. + date_publication: '2023-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCMinification + url_git: '' +RCMsize: + version: 1.0.0 + title: Sample Size Calculation in Reversible Catalytic Models + maintainer: Márcia Graça + description: Sample size and confidence interval calculations in reversible catalytic + models, with applications in malaria research. Further details can be found in + the paper by Sepúlveda and Drakeley (2015, ). + date_publication: '2024-12-02' + bug_reports: https://github.com/marciagraca/RCMsize/issues + url: https://marciagraca.github.io/RCMsize/ + url_cran: https://CRAN.R-project.org/package=RCMsize + url_git: https://github.com/marciagraca/RCMsize +RCNA: + version: '1.0' + title: Robust Copy Number Alteration Detection (RCNA) + maintainer: Matt Bradley + description: |- + Detects copy number alteration events in targeted exon sequencing + data for tumor samples without matched normal controls. The advantage of + this method is that it can be applied to smaller sequencing panels including + evaluations of exon, transcript, gene, or even user specified genetic + regions of interest. Functions in the package include steps for GC-content + correction, calculation of quantile based normal karyotype ranges, + and calculation of feature score. Cutoffs for "normal" quantile and score + are user-adjustable. + date_publication: '2024-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCNA + url_git: '' +rCNV: + version: 1.3.0 + title: Detect Copy Number Variants from SNPs Data + maintainer: Piyal Karunarathne + description: Functions in this package will import filtered variant call format + (VCF) files of SNPs data and generate data sets to detect copy number variants, + visualize them and do downstream analyses with copy number variants(e.g. Environmental + association analyses). + date_publication: '2024-09-20' + bug_reports: https://github.com/piyalkarum/rCNV/issues + url: https://piyalkarum.github.io/rCNV/ + url_cran: https://CRAN.R-project.org/package=rCNV + url_git: '' +rco: + version: 1.0.2 + title: The R Code Optimizer + maintainer: Juan Cruz Rodriguez + description: |- + Automatically apply different strategies to optimize R code. + 'rco' functions take R code as input, and returns R code as output. + date_publication: '2021-04-17' + bug_reports: https://github.com/jcrodriguez1989/rco/issues + url: https://jcrodriguez1989.github.io/rco/ + url_cran: https://CRAN.R-project.org/package=rco + url_git: '' +rcoder: + version: 0.3.0 + title: |- + Lightweight Data Structure for Recoding Categorical Data without + Factors + maintainer: Patrick Anker + description: |- + A data structure and toolkit for documenting and recoding + categorical data that can be shared in other statistical software. + date_publication: '2023-10-06' + bug_reports: https://github.com/nyuglobalties/rcoder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcoder + url_git: https://github.com/nyuglobalties/rcoder +RCognito: + version: 0.1.0 + title: A Simplified Interface for 'Amazon Cognito' + maintainer: Sanjaya J Shetty + description: Simplifies integration with 'Amazon Cognito' () + for R developers, enabling easy management of user authentication, registration, + and password flows. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCognito + url_git: '' +RColetum: + version: 0.2.2 + title: Access your Coletum's Data from API + maintainer: André Smaniotto + description: |- + Get your data (forms, structures, answers) from Coletum + to handle and analyse. + date_publication: '2022-10-20' + bug_reports: https://github.com/geo-sapiens/RColetum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RColetum + url_git: https://github.com/geo-sapiens/RColetum +rcollectadhd: + version: '0.8' + title: Collection of Data Sets Containing ADHD Related Data + maintainer: John Nolan + description: |- + A collection of data sets relating to ADHD (Attention Deficit + Hyperactivity Disorder) which have been sourced from other packages on CRAN + or from publications on other websites such as Kaggle + .The package also includes some simple functions for + analysing data sets. The data sets and descriptions of the data sets may + differ from what is on CRAN or other source websites. The aim of this + package is to bring together data sets from a variety of ADHD research + publications. This package would be useful for those interested in finding + out what research has been done on the topic of ADHD, or those interested in + comparing the results from different existing works. I started this project + because I wanted to put together a collection of the data sets relevant to + ADHD research, which I have a personal interest in. This work was conducted + with the support of my mentor within the Global Talent Mentoring platform. + . + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcollectadhd + url_git: '' +RColorBrewer: + version: 1.1-3 + title: ColorBrewer Palettes + maintainer: Erich Neuwirth + description: |- + Provides color schemes for maps (and other graphics) + designed by Cynthia Brewer as described at http://colorbrewer2.org. + date_publication: '2022-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RColorBrewer + url_git: '' +RColorConesa: + version: 1.0.0 + title: Conesa Colors Palette + maintainer: Pedro Salguero Garcia + description: Provides a collection of palettes designed to integrate with 'ggplot', + reflecting the color schemes associated with 'ConesaLab'. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RColorConesa + url_git: '' +rcolors: + version: 0.1.0 + title: 270 'NCL' Color Tables in R Language + maintainer: Dongdong Kong + description: |- + 'NCL' (NCAR Command Language) is one of the most popular spatial + data mapping tools in meteorology studies, due to its beautiful output + figures with plenty of color palettes designed by experts + . + Here we translate all 'NCL' color palettes into R hexadecimal RGB colors and + provide color selection function, which will help users make a beautiful figure. + date_publication: '2021-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcolors + url_git: '' +Rcompadre: + version: 1.4.0 + title: Utilities for using the 'COM(P)ADRE' Matrix Model Database + maintainer: Owen Jones + description: |- + Utility functions for interacting with the 'COMPADRE' and + 'COMADRE' databases of matrix population models. Described in Jones et + al. (2021) . + date_publication: '2024-10-16' + bug_reports: https://github.com/jonesor/Rcompadre/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rcompadre + url_git: https://github.com/jonesor/Rcompadre +rcompanion: + version: 2.5.0 + title: Functions to Support Extension Education Program Evaluation + maintainer: Salvatore Mangiafico + description: |- + Functions and datasets to support Summary and Analysis of + Extension Program Evaluation in R, and An R + Companion for the Handbook of Biological Statistics. + Vignettes are available at . + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcompanion + url_git: '' +rcompendium: + version: '1.3' + title: Create a Package or Research Compendium Structure + maintainer: Nicolas Casajus + description: |- + Makes easier the creation of R package or research compendium + (i.e. a predefined files/folders structure) so that users can focus on the + code/analysis instead of wasting time organizing files. A full + ready-to-work structure is set up with some additional features: version + control, remote repository creation, CI/CD configuration (check package + integrity under several OS, test code with 'testthat', and build and deploy + website using 'pkgdown'). This package heavily relies on the R packages + 'devtools' and 'usethis' and follows recommendations made by Wickham H. + (2015) and Marwick B. et al. (2018) + . + date_publication: '2023-10-26' + bug_reports: https://github.com/FRBCesab/rcompendium/issues + url: https://frbcesab.github.io/rcompendium/ + url_cran: https://CRAN.R-project.org/package=rcompendium + url_git: https://github.com/FRBCesab/rcompendium +rconfig: + version: 0.3.0 + title: Manage R Configuration at the Command Line + maintainer: Peter Solymos + description: |- + Configuration management using files (YAML, JSON, INI, TXT), + JSON strings, and command line arguments. Command line arguments + can be used to override configuration. Period-separated command line + flags are parsed as hierarchical lists. Environment variables, R global variables, + and configuration values can be substituted. + date_publication: '2023-06-27' + bug_reports: https://github.com/analythium/rconfig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rconfig + url_git: https://github.com/analythium/rconfig +RConics: + version: 1.1.2 + title: Computations on Conics + maintainer: Emanuel Huber + description: Solve some conic related problems (intersection of conics with lines + and conics, arc length of an ellipse, polar lines, etc.). + date_publication: '2025-02-17' + bug_reports: https://github.com/emanuelhuber/RConics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RConics + url_git: https://github.com/emanuelhuber/RConics +rcontroll: + version: 0.1.2 + title: Individual-Based Forest Growth Simulator 'TROLL' + maintainer: Sylvain Schmitt + description: |- + 'TROLL' is coded in C++ and it typically simulates hundreds of + thousands of individuals over hundreds of years. The 'rcontroll' R package + is a wrapper of 'TROLL'. 'rcontroll' includes functions that generate inputs + for simulations and run simulations. Finally, it is possible to analyse + the 'TROLL' outputs through tables, figures, and maps taking advantage of + other R visualisation packages. 'rcontroll' also offers the possibility to + generate a virtual LiDAR point cloud that corresponds to a snapshot of + the simulated forest. + date_publication: '2024-09-30' + bug_reports: https://github.com/sylvainschmitt/rcontroll/issues + url: https://sylvainschmitt.github.io/rcontroll/ + url_cran: https://CRAN.R-project.org/package=rcontroll + url_git: https://github.com/sylvainschmitt/rcontroll +rcorpora: + version: 2.0.1 + title: A Collection of Small Text Corpora of Interesting Data + maintainer: Gábor Csárdi + description: |- + A collection of small text corpora of interesting data. + It contains all data sets from 'dariusk/corpora'. Some examples: + names of animals: birds, dinosaurs, dogs; foods: beer categories, + pizza toppings; geography: English towns, rivers, oceans; + humans: authors, US presidents, occupations; science: elements, + planets; words: adjectives, verbs, proverbs, US president quotes. + date_publication: '2024-06-30' + bug_reports: https://github.com/gaborcsardi/rcorpora/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcorpora + url_git: https://github.com/gaborcsardi/rcorpora +RCPA: + version: 0.2.5 + title: Consensus Pathway Analysis + maintainer: Ha Nguyen + description: 'Provides a set of functions to perform pathway analysis and meta-analysis + from multiple gene expression datasets, as well as visualization of the results. + This package wraps functionality from the following packages: Ritchie et al. (2015) + , Love et al. (2014) , + Robinson et al. (2010) , Korotkevich et al. + (2016) , Efron et al. (2015) , + and Gu et al. (2012) .' + date_publication: '2024-11-06' + bug_reports: https://github.com/tinnlab/RCPA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RCPA + url_git: '' +RCPA3: + version: 1.3.1 + title: Data and Functions for R Companion to Political Analysis 3rd Ed + maintainer: Barry Edwards + description: |- + Bundles the datasets and functions featured in Philip H. + Pollock and Barry C. Edwards, "An R Companion to Political Analysis, 3rd Edition," Thousand Oaks, CA: Sage Publications. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCPA3 + url_git: '' +Rcplex: + version: 0.3-6 + title: R Interface to CPLEX + maintainer: Stefan Theussl + description: R interface to CPLEX solvers for linear, quadratic, and (linear and + quadratic) mixed integer programs. Support for quadratically constrained programming + is available. See the file "INSTALL" for details on how to install the Rcplex + package in Linux/Unix-like and Windows systems. Support for sparse matrices is + provided by an S3-style class "simple_triplet_matrix" from package slam and by + objects from the Matrix package class hierarchy. + date_publication: '2023-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rcplex + url_git: https://R-Forge.R-project.org/projects/rcplex +Rcpp: + version: 1.0.14 + title: Seamless R and C++ Integration + maintainer: Dirk Eddelbuettel + description: |- + The 'Rcpp' package provides R functions as well as C++ classes which + offer a seamless integration of R and C++. Many R data types and objects can be + mapped back and forth to C++ equivalents which facilitates both writing of new + code as well as easier integration of third-party libraries. Documentation + about 'Rcpp' is provided by several vignettes included in this package, via the + 'Rcpp Gallery' site at , the paper by Eddelbuettel and + Francois (2011, ), the book by Eddelbuettel (2013, + ) and the paper by Eddelbuettel and Balamuta (2018, + ); see 'citation("Rcpp")' for details. + date_publication: '2025-01-12' + bug_reports: https://github.com/RcppCore/Rcpp/issues + url: https://www.rcpp.org + url_cran: https://CRAN.R-project.org/package=Rcpp + url_git: https://github.com/RcppCore/Rcpp +Rcpp11: + version: 3.1.2.0.1 + title: R and C++11 + maintainer: Romain Francois + description: |- + Rcpp11 includes a header only C++11 library that facilitates + integration between R and modern C++. + date_publication: '2020-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rcpp11 + url_git: '' +RcppAlgos: + version: 2.9.3 + title: |- + High Performance Tools for Combinatorics and Computational + Mathematics + maintainer: Joseph Wood + description: |- + Provides optimized functions and flexible iterators implemented in + C++ for solving problems in combinatorics and computational mathematics. + Handles various combinatorial objects including combinations, permutations, + integer partitions and compositions, Cartesian products, unordered + Cartesian products, and partition of groups. Utilizes the RMatrix class + from 'RcppParallel' for thread safety. The combination and permutation + functions contain constraint parameters that allow for generation of all + results of a vector meeting specific criteria (e.g. finding all + combinations such that the sum is between two bounds). Capable of + ranking/unranking combinatorial objects efficiently (e.g. retrieve only the + nth lexicographical result) which sets up nicely for parallelization as + well as random sampling. Gmp support permits exploration where the total + number of results is large (e.g. comboSample(10000, 500, n = 4)). + Additionally, there are several high performance number theoretic + functions that are useful for problems common in computational mathematics. + Some of these functions make use of the fast integer division library + 'libdivide'. The primeSieve function is based on the segmented sieve of + Eratosthenes implementation by Kim Walisch. It is also efficient for large + numbers by using the cache friendly improvements originally developed by + Tomás Oliveira. Finally, there is a prime counting function that implements + Legendre's formula based on the work of Kim Walisch. + date_publication: '2025-02-03' + bug_reports: https://github.com/jwood000/RcppAlgos/issues + url: https://gmplib.org/ + url_cran: https://CRAN.R-project.org/package=RcppAlgos + url_git: https://github.com/jwood000/RcppAlgos +RcppAnnoy: + version: 0.0.22 + title: |- + 'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest + Neighbors + maintainer: Dirk Eddelbuettel + description: |- + 'Annoy' is a small C++ library for Approximate Nearest Neighbors + written for efficient memory usage as well an ability to load from / save to + disk. This package provides an R interface by relying on the 'Rcpp' package, + exposing the same interface as the original Python wrapper to 'Annoy'. See + for more on 'Annoy'. 'Annoy' is released + under Version 2.0 of the Apache License. Also included is a small Windows + port of 'mmap' which is released under the MIT license. + date_publication: '2024-01-23' + bug_reports: https://github.com/eddelbuettel/rcppannoy/issues + url: https://dirk.eddelbuettel.com/code/rcpp.annoy.html + url_cran: https://CRAN.R-project.org/package=RcppAnnoy + url_git: https://github.com/eddelbuettel/rcppannoy +RcppAPT: + version: 0.0.10 + title: '''Rcpp'' Interface to the APT Package Manager' + maintainer: Dirk Eddelbuettel + description: |- + The 'APT Package Management System' provides Debian and + Debian-derived Linux systems with a powerful system to resolve package + dependencies. This package offers access directly from R. This can + only work on a system with a suitable 'libapt-pkg-dev' installation + so functionality is curtailed if such a library is not found. + date_publication: '2024-11-29' + bug_reports: https://github.com/eddelbuettel/rcppapt/issues + url: https://dirk.eddelbuettel.com/code/rcpp.apt.html + url_cran: https://CRAN.R-project.org/package=RcppAPT + url_git: https://github.com/eddelbuettel/rcppapt +RcppArmadillo: + version: 14.2.3-1 + title: |- + 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra + Library + maintainer: Dirk Eddelbuettel + description: |- + 'Armadillo' is a templated C++ linear algebra library (by Conrad + Sanderson) that aims towards a good balance between speed and ease of + use. Integer, floating point and complex numbers are supported, as + well as a subset of trigonometric and statistics functions. Various + matrix decompositions are provided through optional integration with + LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the + header files from the templated 'Armadillo' library. Thus users do + not need to install 'Armadillo' itself in order to use + 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed + under Apache License 2; previous releases were under licensed as MPL + 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; + 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed + under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. + date_publication: '2025-02-06' + bug_reports: https://github.com/RcppCore/RcppArmadillo/issues + url: https://dirk.eddelbuettel.com/code/rcpp.armadillo.html + url_cran: https://CRAN.R-project.org/package=RcppArmadillo + url_git: https://github.com/RcppCore/RcppArmadillo +RcppArray: + version: 0.3.0 + title: '''Rcpp'' Meets ''C++'' Arrays' + maintainer: Jon Clayden + description: |- + Interoperability between 'Rcpp' and the 'C++11' array and tuple + types. Linking to this package allows fixed-length 'std::array' objects to + be converted to and from equivalent R vectors, and 'std::tuple' objects + converted to lists, via the as() and wrap() functions. There is also + experimental support for 'std::span' from 'C++20'. + date_publication: '2023-11-08' + bug_reports: https://github.com/jonclayden/RcppArray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppArray + url_git: https://github.com/jonclayden/RcppArray +RcppBDT: + version: 0.2.7 + title: '''Rcpp'' Bindings for the Boost Date_Time Library' + maintainer: Dirk Eddelbuettel + description: |- + Access to Boost Date_Time functionality for dates, + durations (both for days and date time objects), time zones, and + posix time ('ptime') is provided by using 'Rcpp modules'. The + posix time implementation can support high-resolution of up to + nano-second precision by using 96 bits (instead of 64 with R) + to present a 'ptime' object (but this needs recompilation with + a #define set). + date_publication: '2025-01-25' + bug_reports: https://github.com/eddelbuettel/rcppbdt/issues + url: https://dirk.eddelbuettel.com/code/rcpp.bdt.html + url_cran: https://CRAN.R-project.org/package=RcppBDT + url_git: https://github.com/eddelbuettel/rcppbdt +RcppBessel: + version: 1.0.0 + title: Bessel Functions Rcpp Interface + maintainer: Alexios Galanos + description: Exports an 'Rcpp' interface for the Bessel functions in the 'Bessel' + package, which can then be called from the 'C++' code of other packages. For the + original 'Fortran' implementation of these functions see Amos (1995) . + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppBessel + url_git: https://github.com/alexiosg/RcppBessel +RcppBigIntAlgos: + version: 1.1.0 + title: Factor Big Integers with the Parallel Quadratic Sieve + maintainer: Joseph Wood + description: |- + Features the multiple polynomial quadratic sieve (MPQS) algorithm + for factoring large integers and a vectorized factoring function that + returns the complete factorization of an integer. The MPQS is based off of + the seminal work of Carl Pomerance (1984) + along with the modification of multiple polynomials introduced by Peter + Montgomery and J. Davis as outlined by Robert D. Silverman (1987) + . Utilizes the C library + GMP (GNU Multiple Precision Arithmetic). For smaller integers, a simple + Elliptic Curve algorithm is attempted followed by a constrained version of + Pollard's rho algorithm. The Pollard's rho algorithm is the same algorithm + used by the factorize function in the 'gmp' package. + date_publication: '2023-08-16' + bug_reports: https://github.com/jwood000/RcppBigIntAlgos/issues + url: https://gmplib.org/ + url_cran: https://CRAN.R-project.org/package=RcppBigIntAlgos + url_git: https://github.com/jwood000/RcppBigIntAlgos +RcppBlaze: + version: 1.0.1 + title: |- + 'Rcpp' Integration for the 'Blaze' High-Performance 'C++' Math + Library + maintainer: Ching-Chuan Chen + description: |- + Blaze is an open-source, high-performance 'C++' math library for dense and sparse arithmetic. + With its state-of-the-art Smart Expression Template implementation Blaze combines the elegance and + ease of use of a domain-specific language with HPC-grade performance, making it one of the most + intuitive and fastest 'C++' math libraries available. The 'RcppBlaze' package includes the header files + from the 'Blaze' library with disabling some functionalities related to link to the thread and system + libraries which make 'RcppBlaze' be a header-only library. Therefore, users do not need to install + 'Blaze'. + date_publication: '2024-05-08' + bug_reports: https://github.com/Chingchuan-chen/RcppBlaze/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppBlaze + url_git: https://github.com/Chingchuan-chen/RcppBlaze +RcppCCTZ: + version: 0.2.13 + title: '''Rcpp'' Bindings for the ''CCTZ'' Library' + maintainer: Dirk Eddelbuettel + description: |- + 'Rcpp' Access to the 'CCTZ' timezone library is provided. 'CCTZ' is + a C++ library for translating between absolute and civil times using the rules + of a time zone. The 'CCTZ' source code, released under the Apache 2.0 License, + is included in this package. See for more + details. + date_publication: '2024-12-12' + bug_reports: https://github.com/eddelbuettel/rcppcctz/issues + url: https://dirk.eddelbuettel.com/code/rcpp.cctz.html + url_cran: https://CRAN.R-project.org/package=RcppCCTZ + url_git: https://github.com/eddelbuettel/rcppcctz +RcppCensSpatial: + version: 0.3.0 + title: Spatial Estimation and Prediction for Censored/Missing Responses + maintainer: Katherine A. L. Valeriano + description: |- + It provides functions to estimate parameters in linear spatial models with + censored/missing responses via the Expectation-Maximization (EM), the Stochastic + Approximation EM (SAEM), or the Monte Carlo EM (MCEM) algorithm. These algorithms + are widely used to compute the maximum likelihood (ML) estimates in problems with + incomplete data. The EM algorithm computes the ML estimates when a closed expression + for the conditional expectation of the complete-data log-likelihood function is + available. In the MCEM algorithm, the conditional expectation is substituted by a + Monte Carlo approximation based on many independent simulations of the missing data. + In contrast, the SAEM algorithm splits the E-step into simulation and integration + steps. This package also approximates the standard error of the estimates using the + Louis method. Moreover, it has a function that performs spatial prediction in new + locations. + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppCensSpatial + url_git: '' +RcppCGAL: + version: 6.0.1 + title: '''Rcpp'' Integration for ''CGAL''' + maintainer: Eric Dunipace + description: |- + Creates a header only package to link to the 'CGAL' + (Computational Geometry Algorithms Library) + header files in 'Rcpp'. There are a variety of potential uses for + the software such as Hilbert sorting, K-D Tree nearest neighbors, + and convex hull algorithms. For more information about how to use the header files, + see the 'CGAL' documentation at . Currently + downloads version 6.0.1 of the 'CGAL' header files. + date_publication: '2025-01-09' + bug_reports: https://github.com/ericdunipace/RcppCGAL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppCGAL + url_git: https://github.com/ericdunipace/RcppCGAL +RcppClassic: + version: 0.9.13 + title: Deprecated 'classic' 'Rcpp' 'API' + maintainer: Dirk Eddelbuettel + description: |- + The 'RcppClassic' package provides a deprecated C++ library which + facilitates the integration of R and C++. New projects should use the new 'Rcpp' + 'API' in the 'Rcpp' package. + date_publication: '2022-11-21' + bug_reports: https://github.com/eddelbuettel/rcppclassic/issues + url: https://dirk.eddelbuettel.com/code/rcpp.classic.html + url_cran: https://CRAN.R-project.org/package=RcppClassic + url_git: https://github.com/eddelbuettel/rcppclassic +RcppClassicExamples: + version: 0.1.3 + title: Examples using 'RcppClassic' to Interface R and C++ + maintainer: Dirk Eddelbuettel + description: |- + The 'Rcpp' package contains a C++ library that facilitates the + integration of R and C++ in various ways via a rich API. This API was + preceded by an earlier version which has been deprecated since 2010 (but is + still supported to provide backwards compatibility in the package + 'RcppClassic'). This package 'RcppClassicExamples' provides usage examples for + the older, deprecated API. There is also a corresponding package + 'RcppExamples' with examples for the newer, current API which we + strongly recommend as the basis for all new development. + date_publication: '2023-11-30' + bug_reports: https://github.com/eddelbuettel/rcppclassicexamples/issues + url: https://dirk.eddelbuettel.com/code/rcpp.classic.html + url_cran: https://CRAN.R-project.org/package=RcppClassicExamples + url_git: https://github.com/eddelbuettel/rcppclassicexamples +RcppClock: + version: '1.1' + title: Seamless 'Rcpp' Benchmarking + maintainer: Zach DeBruine + description: Time the execution of overlapping or unique 'Rcpp' code chunks using + convenient methods, seamlessly write timing results to an 'RcppClock' object in + the R global environment, and summarize and/or plot the results in R. + date_publication: '2021-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppClock + url_git: '' +RcppCNPy: + version: 0.2.13 + title: Read-Write Support for 'NumPy' Files via 'Rcpp' + maintainer: Dirk Eddelbuettel + description: |- + The 'cnpy' library written by Carl Rogers provides read and write + facilities for files created with (or for) the 'NumPy' extension for 'Python'. + Vectors and matrices of numeric types can be read or written to and from + files as well as compressed files. Support for integer files is available if + the package has been built with as C++11 which should be the default on + all platforms since the release of R 3.3.0. + date_publication: '2024-09-03' + bug_reports: https://github.com/eddelbuettel/rcppcnpy/issues + url: https://dirk.eddelbuettel.com/code/rcpp.cnpy.html + url_cran: https://CRAN.R-project.org/package=RcppCNPy + url_git: https://github.com/eddelbuettel/rcppcnpy +RcppColors: + version: 0.6.0 + title: Color Mappings and 'C++' Header Files for Color Conversion + maintainer: Stéphane Laurent + description: |- + Provides 'C++' header files to deal with color conversion + from some color spaces to hexadecimal with 'Rcpp', and exports some + color mapping functions for usage in R. Also exports functions to + convert colors from the 'HSLuv' color space for usage in R. 'HSLuv' is + a human-friendly alternative to HSL. + date_publication: '2023-10-21' + bug_reports: https://github.com/stla/RcppColors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppColors + url_git: https://github.com/stla/RcppColors +RcppCWB: + version: 0.6.5 + title: '''Rcpp'' Bindings for the ''Corpus Workbench'' (''CWB'')' + maintainer: Andreas Blaette + description: |- + 'Rcpp' Bindings for the C code of the 'Corpus Workbench' ('CWB'), an indexing and query + engine to efficiently analyze large corpora (). 'RcppCWB' is licensed + under the GNU GPL-3, in line with the GPL-3 license of the 'CWB' (). + The 'CWB' relies on 'pcre2' (BSD license, see ) + and 'GLib' (LGPL license, see ). + See the file LICENSE.note for further information. The package includes modified code of the + 'rcqp' package (GPL-2, see ). The original work of the authors + of the 'rcqp' package is acknowledged with great respect, and they are listed as authors of this + package. To achieve cross-platform portability (including Windows), using 'Rcpp' for wrapper code + is the approach used by 'RcppCWB'. + date_publication: '2024-09-23' + bug_reports: https://github.com/PolMine/RcppCWB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppCWB + url_git: https://github.com/PolMine/RcppCWB +RcppDate: + version: 0.0.4 + title: '''date'' C++ Header Library for Date and Time Functionality' + maintainer: Dirk Eddelbuettel + description: |- + A header-only C++ library is provided with support + for dates, time zones, ISO weeks, Julian dates, and Islamic dates. + 'date' offers extensive date and time functionality for the C++11, + C++14 and C++17 standards and was written by Howard Hinnant and released + under the MIT license. A slightly modified version has been accepted + (along with 'tz.h') as part of C++20. This package regroups all + header files from the upstream repository by Howard Hinnant so that + other R packages can use them in their C++ code. At present, few of + the types have explicit 'Rcpp' wrappers though these may be added as + needed. + date_publication: '2024-10-14' + bug_reports: https://github.com/eddelbuettel/rcppdate/issues + url: https://dirk.eddelbuettel.com/code/rcpp.date.html + url_cran: https://CRAN.R-project.org/package=RcppDate + url_git: https://github.com/eddelbuettel/rcppdate +RcppDE: + version: 0.1.8 + title: Global Optimization by Differential Evolution in C++ + maintainer: Dirk Eddelbuettel + description: |- + An efficient C++ based implementation of the 'DEoptim' + function which performs global optimization by differential evolution. + Its creation was motivated by trying to see if the old approximation "easier, + shorter, faster: pick any two" could in fact be extended to achieving all + three goals while moving the code from plain old C to modern C++. The + initial version did in fact do so, but a good part of the gain was due to + an implicit code review which eliminated a few inefficiencies which have + since been eliminated in 'DEoptim'. + date_publication: '2025-02-19' + bug_reports: https://github.com/eddelbuettel/rcppde/issues + url: https://dirk.eddelbuettel.com/code/rcpp.de.html + url_cran: https://CRAN.R-project.org/package=RcppDE + url_git: https://github.com/eddelbuettel/rcppde +RcppDist: + version: 0.1.1 + title: '''Rcpp'' Integration of Additional Probability Distributions' + maintainer: JB Duck-Mayr + description: |- + The 'Rcpp' package provides a C++ library to make it easier + to use C++ with R. R and 'Rcpp' provide functions for a variety of + statistical distributions. Several R packages make functions + available to R for additional statistical distributions. However, + to access these functions from C++ code, a costly call to the R + functions must be made. 'RcppDist' provides a header-only C++ library + with functions for additional statistical distributions that can be + called from C++ when writing code using 'Rcpp' or 'RcppArmadillo'. + Functions are available that return a 'NumericVector' as well as + doubles, and for multivariate or matrix distributions, 'Armadillo' + vectors and matrices. 'RcppDist' provides functions for the following + distributions: the four parameter beta distribution; the location- + scale t distribution; the truncated normal distribution; the + truncated t distribution; a truncated location-scale t distribution; + the triangle distribution; the multivariate normal distribution*; + the multivariate t distribution*; the Wishart distribution*; and + the inverse Wishart distribution*. Distributions marked with an + asterisk rely on 'RcppArmadillo'. + date_publication: '2018-10-28' + bug_reports: https://github.com/duckmayr/RcppDist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppDist + url_git: https://github.com/duckmayr/RcppDist +RcppDynProg: + version: 0.2.1 + title: '''Rcpp'' Dynamic Programming' + maintainer: John Mount + description: Dynamic Programming implemented in 'Rcpp'. Includes example partition + and out of sample fitting applications. Also supplies additional custom coders + for the 'vtreat' package. + date_publication: '2023-08-20' + bug_reports: https://github.com/WinVector/RcppDynProg/issues + url: https://winvector.github.io/RcppDynProg/ + url_cran: https://CRAN.R-project.org/package=RcppDynProg + url_git: https://github.com/WinVector/RcppDynProg/ +RcppEigen: + version: 0.3.4.0.2 + title: |- + 'Rcpp' Integration for the 'Eigen' Templated Linear Algebra + Library + maintainer: Dirk Eddelbuettel + description: |- + R and 'Eigen' integration using 'Rcpp'. + 'Eigen' is a C++ template library for linear algebra: matrices, vectors, + numerical solvers and related algorithms. It supports dense and sparse + matrices on integer, floating point and complex numbers, decompositions of + such matrices, and solutions of linear systems. Its performance on many + algorithms is comparable with some of the best implementations based on + 'Lapack' and level-3 'BLAS'. The 'RcppEigen' package includes the header + files from the 'Eigen' C++ template library. Thus users do not need to + install 'Eigen' itself in order to use 'RcppEigen'. Since version 3.1.1, + 'Eigen' is licensed under the Mozilla Public License (version 2); earlier + version were licensed under the GNU LGPL version 3 or later. 'RcppEigen' + (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under the GNU GPL + version 2 or later, as is the rest of 'Rcpp'. + date_publication: '2024-08-24' + bug_reports: https://github.com/RcppCore/RcppEigen/issues + url: https://dirk.eddelbuettel.com/code/rcpp.eigen.html + url_cran: https://CRAN.R-project.org/package=RcppEigen + url_git: https://github.com/RcppCore/RcppEigen +RcppEnsmallen: + version: 0.2.22.1.1 + title: |- + Header-Only C++ Mathematical Optimization Library for + 'Armadillo' + maintainer: James Joseph Balamuta + description: |- + 'Ensmallen' is a templated C++ mathematical optimization library + (by the 'MLPACK' team) that provides a simple set of abstractions for writing an + objective function to optimize. Provided within are various standard and + cutting-edge optimizers that include full-batch gradient descent techniques, + small-batch techniques, gradient-free optimizers, and constrained optimization. + The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library + and pairs the appropriate header files from 'armadillo' through the + 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor + 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under + 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, + 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under + the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under + similar terms. Note that 'Ensmallen' requires a compiler that supports + 'C++14' and 'Armadillo' 10.8.2 or later. + date_publication: '2024-12-03' + bug_reports: https://github.com/coatless-rpkg/rcppensmallen/issues + url: https://r-pkg.thecoatlessprofessor.com/rcppensmallen/ + url_cran: https://CRAN.R-project.org/package=RcppEnsmallen + url_git: https://github.com/coatless-rpkg/rcppensmallen +RcppExamples: + version: 0.1.9 + title: Examples using 'Rcpp' to Interface R and C++ + maintainer: Dirk Eddelbuettel + description: |- + Examples for Seamless R and C++ integration + The 'Rcpp' package contains a C++ library that facilitates the integration of + R and C++ in various ways. This package provides some usage examples. + Note that the documentation in this package currently does not cover all the + features in the package. The site regroups a large + number of examples for 'Rcpp'. + date_publication: '2019-08-24' + bug_reports: https://github.com/eddelbuettel/rcppexamples/issues + url: http://dirk.eddelbuettel.com/code/rcpp.examples.html + url_cran: https://CRAN.R-project.org/package=RcppExamples + url_git: '' +RcppFarmHash: + version: 0.0.3 + title: Interface to the Google 'FarmHash' Family of Hash Functions + maintainer: Dirk Eddelbuettel + description: |- + The Google 'FarmHash' family of hash functions is used by + the Google 'BigQuery' data warehouse via the 'FARM_FINGERPRINT' + function. This package permits to calculate these hash digest + fingerprints directly from R, and uses the included 'FarmHash' + files written by G. Pike and copyrighted by Google, Inc. + date_publication: '2023-09-09' + bug_reports: https://github.com/eddelbuettel/rcppfarmhash/issues + url: https://dirk.eddelbuettel.com/code/rcpp.farmhash.html + url_cran: https://CRAN.R-project.org/package=RcppFarmHash + url_git: https://github.com/eddelbuettel/rcppfarmhash/ +RcppFastAD: + version: 0.0.4 + title: '''Rcpp'' Bindings to ''FastAD'' Auto-Differentiation' + maintainer: Dirk Eddelbuettel + description: |- + The header-only 'C++' template library 'FastAD' for automatic + differentiation is provided by + this package, along with a few illustrative examples that can all be called + from R. + date_publication: '2024-09-24' + bug_reports: https://github.com/eddelbuettel/rcppfastad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppFastAD + url_git: https://github.com/eddelbuettel/rcppfastad +RcppFastFloat: + version: 0.0.5 + title: |- + 'Rcpp' Bindings for the 'fast_float' Header-Only Library for + Number Parsing + maintainer: Dirk Eddelbuettel + description: |- + Converting ascii text into (floating-point) numeric values is a + very common problem. The 'fast_float' header-only C++ library by Daniel Lemire + does it very well and very fast at up to or over to 1 gigabyte per second as + described in more detail in . 'fast_float' is + licensed under the Apache 2.0 license and provided here for use by other R + packages via a simple 'LinkingTo:' statement. + date_publication: '2025-01-15' + bug_reports: https://github.com/eddelbuettel/rcppfastfloat/issues + url: https://dirk.eddelbuettel.com/code/rcpp.fastfloat.html + url_cran: https://CRAN.R-project.org/package=RcppFastFloat + url_git: https://github.com/eddelbuettel/rcppfastfloat/ +RcppGetconf: + version: 0.0.4 + title: '''Rcpp'' Interface for Querying System Configuration Variables' + maintainer: Dirk Eddelbuettel + description: |- + The 'getconf' command-line tool provided by 'libc' allows + querying of a large number of system variables. This package provides + similar functionality. + date_publication: '2025-01-08' + bug_reports: https://github.com/eddelbuettel/rcppgetconf/issues + url: https://dirk.eddelbuettel.com/code/rcpp.getconf.html + url_cran: https://CRAN.R-project.org/package=RcppGetconf + url_git: https://github.com/eddelbuettel/rcppgetconf +RcppGreedySetCover: + version: 0.1.0 + title: Greedy Set Cover + maintainer: Matthias Kaeding + description: A fast implementation of the greedy algorithm for the set cover problem + using 'Rcpp'. + date_publication: '2018-01-24' + bug_reports: http://github.com/matthiaskaeding/RcppGreedySetCover/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppGreedySetCover + url_git: http://github.com/matthiaskaeding/RcppGreedySetCover +RcppGSL: + version: 0.3.13 + title: '''Rcpp'' Integration for ''GNU GSL'' Vectors and Matrices' + maintainer: Dirk Eddelbuettel + description: |- + 'Rcpp' integration for 'GNU GSL' vectors and matrices + The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for + scientific computing. It is particularly useful for C and C++ programs as it + provides a standard C interface to a wide range of mathematical routines. There + are over 1000 functions in total with an extensive test suite. The 'RcppGSL' + package provides an easy-to-use interface between 'GSL' data structures and + R using concepts from 'Rcpp' which is itself a package that eases the + interfaces between R and C++. This package also serves as a prime example of + how to build a package that uses 'Rcpp' to connect to another third-party + library. The 'autoconf' script, 'inline' plugin and example package can all + be used as a stanza to write a similar package against another library. + date_publication: '2023-01-13' + bug_reports: https://github.com/eddelbuettel/rcppgsl/issues + url: https://dirk.eddelbuettel.com/code/rcpp.gsl.html + url_cran: https://CRAN.R-project.org/package=RcppGSL + url_git: https://github.com/eddelbuettel/rcppgsl +RcppHMM: + version: 1.2.2 + title: Rcpp Hidden Markov Model + maintainer: Roberto A. Cardenas-Ovando + description: Collection of functions to evaluate sequences, decode hidden states + and estimate parameters from a single or multiple sequences of a discrete time + Hidden Markov Model. The observed values can be modeled by a multinomial distribution + for categorical/labeled emissions, a mixture of Gaussians for continuous data + and also a mixture of Poissons for discrete values. It includes functions for + random initialization, simulation, backward or forward sequence evaluation, Viterbi + or forward-backward decoding and parameter estimation using an Expectation-Maximization + approach. + date_publication: '2017-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppHMM + url_git: '' +RcppHNSW: + version: 0.6.0 + title: |- + 'Rcpp' Bindings for 'hnswlib', a Library for Approximate Nearest + Neighbors + maintainer: James Melville + description: |- + 'Hnswlib' is a C++ library for Approximate Nearest Neighbors. + This package provides a minimal R interface by relying on the 'Rcpp' + package. See for more on + 'hnswlib'. 'hnswlib' is released under Version 2.0 of the Apache + License. + date_publication: '2024-02-04' + bug_reports: https://github.com/jlmelville/rcpphnsw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppHNSW + url_git: https://github.com/jlmelville/rcpphnsw +RcppHungarian: + version: '0.3' + title: Solves Minimum Cost Bipartite Matching Problems + maintainer: Justin Silverman + description: |- + Header library and R functions to solve minimum cost bipartite matching problem + using Huhn-Munkres algorithm (Hungarian algorithm; ; + Kuhn (1955) ). + This is a repackaging of code written by Cong Ma in the GitHub repo . + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppHungarian + url_git: https://github.com/jsilve24/RcppHungarian +RcppInt64: + version: 0.0.5 + title: |- + 'Rcpp'-Based Helper Functions to Pass 'Int64' and 'nanotime' + Values Between 'R' and 'C++' + maintainer: Dirk Eddelbuettel + description: |- + 'Int64' values can be created and accessed via the 'bit64' package and its 'integer64' + class which package the 'int64' representation cleverly into a 'double'. The 'nanotime' packages + builds on this to support nanosecond-resolution timestamps. This packages helps conversions between + 'R' and 'C++' via several helper functions provided via a single header file. A complete example + client package is included as an illustration. + date_publication: '2024-04-30' + bug_reports: https://github.com/eddelbuettel/rcppint64/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppInt64 + url_git: https://github.com/eddelbuettel/rcppint64 +RcppJagger: + version: 0.0.2 + title: An R Wrapper for Jagger + maintainer: Shusei Eshima + description: A wrapper for Jagger, a morphological analyzer proposed in Yoshinaga + (2023) . Jagger uses patterns derived from morphological dictionaries + and training data sets and applies them from the beginning of the input. This + simultaneous and deterministic process enables it to effectively perform tokenization, + POS tagging, and lemmatization. + date_publication: '2023-06-08' + bug_reports: https://github.com/Shusei-E/RcppJagger/issues + url: https://shusei-e.github.io/RcppJagger/ + url_cran: https://CRAN.R-project.org/package=RcppJagger + url_git: '' +RcppLbfgsBlaze: + version: 0.1.0 + title: '''L-BFGS'' Algorithm Based on ''Blaze'' for ''R'' and ''Rcpp''' + maintainer: Ching-Chuan Chen + description: |- + The 'L-BFGS' algorithm is a popular optimization algorithm for unconstrained optimization problems. + 'Blaze' is a high-performance 'C++' math library for dense and sparse arithmetic. + This package provides a simple interface to the 'L-BFGS' algorithm and allows users to optimize + their objective functions with 'Blaze' vectors and matrices in 'R' and 'Rcpp'. + date_publication: '2024-05-14' + bug_reports: https://github.com/Chingchuan-chen/RcppLbfgsBlaze/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppLbfgsBlaze + url_git: https://github.com/ChingChuan-Chen/RcppLbfgsBlaze +RcppMagicEnum: + version: 0.0.1 + title: '''Rcpp'' Bindings to ''Magic Enum'' ''C++'' ''Enum'' Support' + maintainer: Dirk Eddelbuettel + description: |- + The header-only modern 'C++' template library 'Magic Enum' for static reflection + of 'enums' (to string, from string, iteration) is provided by this package. More + information about the underlying library can be found at its repository at + . + date_publication: '2024-08-19' + bug_reports: https://github.com/eddelbuettel/rcppmagicenum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppMagicEnum + url_git: https://github.com/eddelbuettel/rcppmagicenum +RcppMeCab: + version: 0.0.1.2 + title: '''rcpp'' Wrapper for ''mecab'' Library' + maintainer: Junhewk Kim + description: |- + R package based on 'Rcpp' for 'MeCab': Yet Another Part-of-Speech and Morphological Analyzer. + The purpose of this package is providing a seamless developing and analyzing environment for CJK texts. + This package utilizes parallel programming for providing highly efficient text preprocessing 'posParallel()' function. + For installation, please refer to README.md file. + date_publication: '2018-07-04' + bug_reports: https://github.com/junhewk/RcppMeCab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppMeCab + url_git: '' +RcppML: + version: 0.3.7 + title: Rcpp Machine Learning Library + maintainer: Zachary DeBruine + description: |- + Fast machine learning algorithms including matrix factorization + and divisive clustering for large sparse and dense matrices. + date_publication: '2021-09-21' + bug_reports: https://github.com/zdebruine/RcppML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppML + url_git: https://github.com/zdebruine/RcppML +RcppMsgPack: + version: 0.2.4 + title: '''MsgPack'' C++ Header Files and Interface Functions for R' + maintainer: Dirk Eddelbuettel + description: |- + 'MsgPack' header files are provided for use by R packages, along + with the ability to access, create and alter 'MsgPack' objects directly from R. + 'MsgPack' is an efficient binary serialization format. It lets you exchange + data among multiple languages like 'JSON' but it is faster and smaller. + Small integers are encoded into a single byte, and typical short strings + require only one extra byte in addition to the strings themselves. This + package provides headers from the 'msgpack-c' implementation for C and + C++(11) for use by R, particularly 'Rcpp'. The included 'msgpack-c' headers + are licensed under the Boost Software License (Version 1.0); the code added + by this package as well the R integration are licensed under the GPL (>= 2). + See the files 'COPYRIGHTS' and 'AUTHORS' for a full list of copyright holders + and contributors to 'msgpack-c'. + date_publication: '2025-01-19' + bug_reports: https://github.com/eddelbuettel/rcppmsgpack/issues + url: https://dirk.eddelbuettel.com/code/rcpp.msgpack.html + url_cran: https://CRAN.R-project.org/package=RcppMsgPack + url_git: https://github.com/eddelbuettel/rcppmsgpack +RcppNLoptExample: + version: 0.0.1 + title: '''Rcpp'' Package Illustrating Header-Only Access to ''NLopt''' + maintainer: Dirk Eddelbuettel + description: |- + An example package which shows use of 'NLopt' functionality from + C++ via 'Rcpp' without requiring linking, and relying just on 'nloptr' thanks + to the exporting API added there by Jelmer Ypma. This package is a fully + functioning, updated, and expanded version of the initial example by + Julien Chiquet at + also containing a large earlier pull request of mine. + date_publication: '2018-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppNLoptExample + url_git: '' +RcppNumerical: + version: 0.6-0 + title: '''Rcpp'' Integration for Numerical Computing Libraries' + maintainer: Yixuan Qiu + description: |- + A collection of open source libraries for numerical computing + (numerical integration, optimization, etc.) and their integration with + 'Rcpp'. + date_publication: '2023-09-06' + bug_reports: https://github.com/yixuan/RcppNumerical/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppNumerical + url_git: https://github.com/yixuan/RcppNumerical +RcppParallel: + version: 5.1.10 + title: Parallel Programming Tools for 'Rcpp' + maintainer: Kevin Ushey + description: |- + High level functions for parallel programming with 'Rcpp'. + For example, the 'parallelFor()' function can be used to convert the work of + a standard serial "for" loop into a parallel one and the 'parallelReduce()' + function can be used for accumulating aggregate or other values. + date_publication: '2025-01-24' + bug_reports: https://github.com/RcppCore/RcppParallel/issues + url: https://rcppcore.github.io/RcppParallel/ + url_cran: https://CRAN.R-project.org/package=RcppParallel + url_git: https://github.com/RcppCore/RcppParallel +RcppProgress: + version: 0.4.2 + title: |- + An Interruptible Progress Bar with OpenMP Support for C++ in R + Packages + maintainer: Karl Forner + description: |- + Allows to display a progress bar in the R + console for long running computations taking place in c++ code, + and support for interrupting those computations even in multithreaded + code, typically using OpenMP. + date_publication: '2020-02-06' + bug_reports: https://github.com/kforner/rcpp_progress/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppProgress + url_git: https://github.com/kforner/rcpp_progress +RcppQuantuccia: + version: 0.1.2 + title: R Bindings to the Calendaring Functionality of 'QuantLib' + maintainer: Dirk Eddelbuettel + description: |- + 'QuantLib' bindings are provided for R using 'Rcpp' via an updated + variant of the header-only 'Quantuccia' project (put together initially by Peter + Caspers) offering an essential subset of 'QuantLib' (and now maintained separately + for the calendaring subset). See the included file 'AUTHORS' for a full list of + contributors to both 'QuantLib' and 'Quantuccia'. + date_publication: '2023-11-29' + bug_reports: https://github.com/eddelbuettel/rcppquantuccia/issues + url: https://dirk.eddelbuettel.com/code/rcpp.quantuccia.html + url_cran: https://CRAN.R-project.org/package=RcppQuantuccia + url_git: https://github.com/eddelbuettel/rcppquantuccia +RcppRedis: + version: 0.2.4 + title: '''Rcpp'' Bindings for ''Redis'' using the ''hiredis'' Library' + maintainer: Dirk Eddelbuettel + description: |- + Connection to the 'Redis' key/value store using the + C-language client library 'hiredis' (included as a fallback) with + 'MsgPack' encoding provided via 'RcppMsgPack' headers. It now also + includes the pub/sub functions from the 'rredis' package. + date_publication: '2023-08-19' + bug_reports: https://github.com/eddelbuettel/rcppredis/issues + url: https://dirk.eddelbuettel.com/code/rcpp.redis.html + url_cran: https://CRAN.R-project.org/package=RcppRedis + url_git: https://github.com/eddelbuettel/rcppredis +RcppRoll: + version: 0.3.1 + title: Efficient Rolling / Windowed Operations + maintainer: Kevin Ushey + description: |- + Provides fast and efficient routines for + common rolling / windowed operations. Routines for the + efficient computation of windowed mean, median, + sum, product, minimum, maximum, standard deviation + and variance are provided. + date_publication: '2024-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppRoll + url_git: '' +RcppSimdJson: + version: 0.1.12 + title: |- + 'Rcpp' Bindings for the 'simdjson' Header-Only Library for + 'JSON' Parsing + maintainer: Dirk Eddelbuettel + description: |- + The 'JSON' format is ubiquitous for data interchange, and the + 'simdjson' library written by Daniel Lemire (and many contributors) provides a + high-performance parser for these files which by relying on parallel 'SIMD' + instruction manages to parse these files as faster than disk speed. See the + paper for more details about 'simdjson'. This + package parses 'JSON' from string, file, or remote URLs under a variety of + settings. + date_publication: '2024-07-07' + bug_reports: https://github.com/eddelbuettel/rcppsimdjson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppSimdJson + url_git: https://github.com/eddelbuettel/rcppsimdjson/ +RcppSMC: + version: 0.2.7 + title: Rcpp Bindings for Sequential Monte Carlo + maintainer: Dirk Eddelbuettel + description: |- + R access to the Sequential Monte Carlo Template Classes + by Johansen is provided. At present, four + additional examples have been added, and the first example from the JSS + paper has been extended. Further integration and extensions are planned. + date_publication: '2023-03-22' + bug_reports: https://github.com/rcppsmc/rcppsmc/issues + url: https://dirk.eddelbuettel.com/code/rcpp.smc.html + url_cran: https://CRAN.R-project.org/package=RcppSMC + url_git: https://github.com/rcppsmc/rcppsmc +RcppSpdlog: + version: 0.0.20 + title: R and C++ Interfaces to 'spdlog' C++ Header Library for Logging + maintainer: Dirk Eddelbuettel + description: |- + The mature and widely-used C++ logging library 'spdlog' by Gabi Melman provides + many desirable features. This package bundles these header files for easy use by R packages + from both their R and C or C++ code. Explicit use via 'LinkingTo:' is also supported. Also + see the 'spdl' package which enhanced this package with a consistent R and C++ interface. + date_publication: '2025-02-01' + bug_reports: https://github.com/eddelbuettel/rcppspdlog/issues + url: https://dirk.eddelbuettel.com/code/rcpp.spdlog.html + url_cran: https://CRAN.R-project.org/package=RcppSpdlog + url_git: https://github.com/eddelbuettel/rcppspdlog +RcppStreams: + version: 0.1.4 + title: |- + 'Rcpp' Integration of the 'Streamulus' 'DSEL' for Stream + Processing + maintainer: Dirk Eddelbuettel + description: |- + The 'Streamulus' (template, header-only) library by + Irit Katriel (at ) + provides a very powerful yet convenient framework for stream + processing. This package connects 'Streamulus' to R by providing + both the header files and all examples. + date_publication: '2025-01-29' + bug_reports: https://github.com/eddelbuettel/rcppstreams/issues + url: http://dirk.eddelbuettel.com/code/rcpp.streams.html + url_cran: https://CRAN.R-project.org/package=RcppStreams + url_git: '' +RcppThread: + version: 2.2.0 + title: R-Friendly Threading in C++ + maintainer: Thomas Nagler + description: |- + Provides a C++11-style thread class and thread pool that can safely + be interrupted from R. See Nagler (2021) . + date_publication: '2025-01-07' + bug_reports: https://github.com/tnagler/RcppThread/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppThread + url_git: https://github.com/tnagler/RcppThread +rcpptimer: + version: 1.2.1 + title: '''Rcpp'' Tic-Toc Timer with ''OpenMP'' Support' + maintainer: Jonathan Berrisch + description: Provides 'Rcpp' bindings for 'cpptimer', a simple tic-toc timer class + for benchmarking 'C++' code . It's not just + simple, it's blazing fast! This sleek tic-toc timer class supports overlapping + timers as well as 'OpenMP' parallelism . It boasts a + nanosecond-level time resolution. We did not find any overhead of the timer itself + at this resolution. Results (with summary statistics) are automatically passed + back to 'R' as a data frame. + date_publication: '2024-09-22' + bug_reports: https://github.com/BerriJ/rcpptimer/issues + url: https://rcpptimer.berrisch.biz + url_cran: https://CRAN.R-project.org/package=rcpptimer + url_git: https://github.com/BerriJ/rcpptimer +RcppTN: + version: 0.2-2 + title: Rcpp-Based Truncated Normal Distribution RNG and Family + maintainer: Jonathan Olmsted + description: |- + R-level and C++-level functionality + to generate random deviates from and calculate moments of a + Truncated Normal distribution using the algorithm of Robert (1995) . + In addition to RNG, functions for calculating moments, densities, + and entropies are provided at both levels. + date_publication: '2017-11-21' + bug_reports: http://github.com/olmjo/RcppTN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppTN + url_git: http://github.com/olmjo/RcppTN +RcppTOML: + version: 0.2.2 + title: '''Rcpp'' Bindings to Parser for "Tom''s Obvious Markup Language"' + maintainer: Dirk Eddelbuettel + description: |- + The configuration format defined by 'TOML' (which expands to + "Tom's Obvious Markup Language") specifies an excellent format + (described at ) suitable for both human editing + as well as the common uses of a machine-readable format. This package + uses 'Rcpp' to connect to the 'toml++' parser written by Mark Gillard + to R. + date_publication: '2023-01-29' + bug_reports: https://github.com/eddelbuettel/rcpptoml/issues + url: http://dirk.eddelbuettel.com/code/rcpp.toml.html + url_cran: https://CRAN.R-project.org/package=RcppTOML + url_git: '' +RcppUUID: + version: 1.2.0 + title: Generating Universally Unique Identificators + maintainer: Dirk Eddelbuettel + description: |- + Using the efficient implementation in the Boost C++ library, functions are + provided to generate vectors of 'Universally Unique Identifiers (UUID)' from R supporting + random (version 4), name (version 5) and time (version 7) 'UUIDs'. The initial repository + was at . + date_publication: '2025-02-12' + bug_reports: https://github.com/eddelbuettel/rcppuuid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppUUID + url_git: https://github.com/eddelbuettel/rcppuuid +RcppXPtrUtils: + version: 0.1.2 + title: XPtr Add-Ons for 'Rcpp' + maintainer: Iñaki Ucar + description: |- + Provides the means to compile user-supplied C++ functions with + 'Rcpp' and retrieve an 'XPtr' that can be passed to other C++ components. + date_publication: '2022-05-24' + bug_reports: https://github.com/Enchufa2/RcppXPtrUtils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RcppXPtrUtils + url_git: https://github.com/Enchufa2/RcppXPtrUtils +RcppXsimd: + version: 7.1.6 + title: Xsimd C++ Header-Only Library Files + maintainer: Marc A. Suchard + description: |- + This header-only library provides modern, portable C++ wrappers for SIMD + intrinsics and parallelized, optimized math implementations (SSE, AVX, NEON, AVX512). + By placing this library in this package, we offer an efficient distribution system for + Xsimd for R packages using CRAN. + date_publication: '2021-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppXsimd + url_git: '' +RcppXts: + version: 0.0.6 + title: Interface the 'xts' API via 'Rcpp' + maintainer: Dirk Eddelbuettel + description: |- + Access to some of the C level functions of the 'xts' package. + In its current state, the package is mostly a proof-of-concept to support + adding useful functions, and does not yet add any of its own. + date_publication: '2022-11-01' + bug_reports: https://github.com/eddelbuettel/rcppxts/issues + url: https://dirk.eddelbuettel.com/code/rcpp.xts.html + url_cran: https://CRAN.R-project.org/package=RcppXts + url_git: https://github.com/eddelbuettel/rcppxts +RcppZiggurat: + version: 0.1.6 + title: |- + 'Rcpp' Integration of Different "Ziggurat" Normal RNG + Implementations + maintainer: Dirk Eddelbuettel + description: |- + The Ziggurat generator for normally distributed random + numbers, originally proposed by Marsaglia and Tsang (2000, + ) has been improved upon a few times + starting with Leong et al (2005, ). + This package provides an aggregation in order to compare different + implementations in order to provide an 'faster but good enough' + alternative for use with R and C++ code. + date_publication: '2020-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RcppZiggurat + url_git: '' +rcprd: + version: 0.0.1 + title: |- + Extraction and Management of Clinical Practice Research Datalink + Data + maintainer: Alexander Pate + description: |- + Simplify the process of extracting and processing Clinical Practice + Research Datalink (CPRD) data in order to build datasets ready for statistical + analysis. This process is difficult in 'R', as the raw data is very large and + cannot be read into the R workspace. 'rcprd' utilises 'RSQLite' to create + 'SQLite' databases which are stored on the hard disk. These are then queried + to extract the required information for a cohort of interest, and create + datasets ready for statistical analysis. The processes follow closely that + from the 'rEHR' package, see Springate et al., (2017) + . + date_publication: '2024-11-13' + bug_reports: '' + url: https://alexpate30.github.io/rcprd/ + url_cran: https://CRAN.R-project.org/package=rcprd + url_git: '' +Rcrawler: + version: 0.1.9-1 + title: Web Crawler and Scraper + maintainer: Salim Khalil + description: Performs parallel web crawling and web scraping. It is designed to + crawl, parse and store web pages to produce data that can be directly used for + analysis application. For details see Khalil and Fakir (2017) . + date_publication: '2018-11-11' + bug_reports: https://github.com/salimk/Rcrawler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rcrawler + url_git: https://github.com/salimk/Rcrawler/ +RCreliability: + version: 0.1.0 + title: Correct Bias in Estimated Regression Coefficients + maintainer: Yu Lu + description: 'This function corrects the bias in estimated regression coefficients + due to classical additive measurement error (i.e., within-person variation) in + logistic regressions under the main study/external reliability study design and + the main study/internal reliability study design. The output includes the naive + and corrected estimators for the regression coefficients; for the variance estimates + of the corrected estimators, the extra variation due to estimating the parameters + in the measurement error model is ignored or taken into account. Reference: Carroll + RJ, Ruppert D, Stefanski L, Crainiceanu CM (2006) .' + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCreliability + url_git: '' +rcrimeanalysis: + version: 0.5.0 + title: An Implementation of Crime Analysis Methods + maintainer: Jamie Spaulding + description: |- + An implementation of functions for the analysis of crime incident or records + management system data. The package implements analysis algorithms scaled for city + or regional crime analysis units. The package provides functions for kernel density + estimation for crime heat maps, geocoding using the 'Google Maps' API, identification + of repeat crime incidents, spatio-temporal map comparison across time intervals, + time series analysis (forecasting and decomposition), detection of optimal parameters + for the identification of near repeat incidents, and near repeat analysis with crime + network linkage. + date_publication: '2023-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcrimeanalysis + url_git: '' +RCriteo: + version: 1.0.2 + title: Loading Criteo Data into R + maintainer: Johannes Burkhardt + description: |- + Aims at loading Criteo online advertising campaign data into R. + Criteo is an online advertising service that enables + advertisers to display commercial ads to web users. The package provides + an authentication process for R with the Criteo API . Moreover, the package features an + interface to query campaign data from the Criteo API. The data can be downloaded + and will be transformed into a R data frame. + date_publication: '2016-07-07' + bug_reports: https://github.com/jburkhardt/RCriteo/issues + url: http://jburkhardt.github.io/RCriteo/ + url_cran: https://CRAN.R-project.org/package=RCriteo + url_git: '' +Rcriticor: + version: '2.0' + title: Pierre-Goldwin Correlogram + maintainer: J.S. Pierre + description: Goldwin-Pierre correlogram. Research of critical periods in the past. + Integrates a time series in a given window. + date_publication: '2018-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rcriticor + url_git: '' +RCRnorm: + version: 0.0.2 + title: |- + An Integrated Regression Model for Normalizing 'NanoString + nCounter' Data + maintainer: Gaoxiang Jia + description: '''NanoString nCounter'' is a medium-throughput platform that measures + gene or microRNA expression levels. Here is a publication that introduces this + platform: Malkov (2009) . Here is the webpage of ''NanoString + nCounter'' where you can find detailed information about this platform . + It has great clinical application, such as diagnosis and prognosis of cancer. + Implements integrated system of random-coefficient hierarchical regression model + to normalize data from ''NanoString nCounter'' platform so that noise from various + sources can be removed.' + date_publication: '2018-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCRnorm + url_git: '' +rcrossref: + version: 1.2.0 + title: Client for Various 'CrossRef' 'APIs' + maintainer: Najko Jahn + description: |- + Client for various 'CrossRef' 'APIs', including 'metadata' search + with their old and newer search 'APIs', get 'citations' in various formats + (including 'bibtex', 'citeproc-json', 'rdf-xml', etc.), convert 'DOIs' + to 'PMIDs', and 'vice versa', get citations for 'DOIs', and get links to + full text of articles when available. + date_publication: '2022-11-11' + bug_reports: https://github.com/ropensci/rcrossref/issues + url: https://docs.ropensci.org/rcrossref/ + url_cran: https://CRAN.R-project.org/package=rcrossref + url_git: https://github.com/ropensci/rcrossref +Rcsdp: + version: 0.1.57.5 + title: R Interface to the CSDP Semidefinite Programming Library + maintainer: Hector Corrada Bravo + description: R interface to the CSDP semidefinite programming library. Installs + version 6.1.1 of CSDP from the COIN-OR website if required. An existing installation + of CSDP may be used by passing the proper configure arguments to the installation + command. See the INSTALL file for further details. + date_publication: '2023-04-10' + bug_reports: https://github.com/hcorrada/rcsdp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rcsdp + url_git: https://github.com/coin-or/Csdp/ +RCSF: + version: 1.0.2 + title: Airborne LiDAR Filtering Method Based on Cloth Simulation + maintainer: Jean-Romain Roussel + description: |- + Cloth Simulation Filter (CSF) is an airborne LiDAR (Light Detection and Ranging) ground + points filtering algorithm which is based on cloth simulation. It tries to simulate the interactions + between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be + determined to generate an approximation of the ground surface . + date_publication: '2020-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCSF + url_git: '' +rcssci: + version: 0.4.0 + title: Visualization of Restricted Cubic Splines + maintainer: Zhiqiang Nie + description: |- + Restricted Cubic Splines were performed to explore the shape of association form of "U, inverted U, + L" shape and test linearity or non-linearity base on "Cox,Logistic,linear,quasipoisson" regression, and auto output Restricted Cubic Splines figures. + rcssci package could automatically draw RCS graphics with Y-axis "OR,HR,RR,beta". + The Restricted Cubic Splines method were based on + Suli Huang (2022) ,Amit Kaura (2019) , + and Harrell Jr (2015, ISBN:978-3-319-19424-0 (Print) 978-3-319-19425-7 (Online)). + date_publication: '2023-02-15' + bug_reports: https://github.com/popnie/RCSsci/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rcssci + url_git: '' +Rcssplot: + version: 1.1.0 + title: Styling of Graphics using Cascading Style Sheets + maintainer: Tomasz Konopka + description: |- + Provides a means to style plots through cascading style sheets. + This separates the aesthetics from the data crunching in plots and charts. + date_publication: '2024-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rcssplot + url_git: https://github.com/tkonopka/Rcssplot +RCT: + version: '1.2' + title: |- + Assign Treatments, Power Calculations, Balances, Impact + Evaluation of Experiments + maintainer: Isidoro Garcia-Urquieta + description: |- + Assists in the whole process of designing and evaluating Randomized Control Trials. + Robust treatment assignment by strata/blocks, that handles misfits; + Power calculations of the minimum detectable treatment effect or minimum populations; + Balance tables of T-test of covariates; + Balance Regression: (treatment ~ all x variables) with F-test of null model; + Impact_evaluation: Impact evaluation regressions. This function + gives you the option to include control_vars, fixed effect variables, + cluster variables (for robust SE), multiple endogenous variables and + multiple heterogeneous variables (to test treatment effect heterogeneity) + summary_statistics: Function that creates a summary statistics table with statistics + rank observations in n groups: Creates a factor variable with n groups. Each group has + a min and max label attach to each category. + Athey, Susan, and Guido W. Imbens (2017) . + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCT + url_git: '' +RCT2: + version: 0.0.1 + title: Designing and Analyzing Two-Stage Randomized Experiments + maintainer: Kosuke Imai + description: |- + Provides various statistical methods for designing and analyzing two-stage randomized controlled + trials using the methods developed by Imai, Jiang, and Malani (2021) and + (2022+) . The package enables the estimation of direct and spillover effects, + conduct hypotheses tests, and conduct sample size calculation for two-stage randomized controlled trials. + date_publication: '2022-10-18' + bug_reports: https://github.com/kosukeimai/RCT2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RCT2 + url_git: https://github.com/kosukeimai/RCT2 +rct3: + version: 1.0.4 + title: Predict Fish Year-Class Strength from Survey Data + maintainer: Colin Millar + description: |- + Predict fish year-class strength by calibration + regression analysis of multiple recruitment index series. + date_publication: '2020-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rct3 + url_git: '' +RCTRecruit: + version: 0.1.24 + title: |- + Non-Parametric Recruitment Prediction for Randomized Clinical + Trials + maintainer: Ioannis Malagaris + description: |- + Accurate prediction of subject recruitment for Randomized Clinical + Trials (RCT) remains an ongoing challenge. Many previous prediction models rely + on parametric assumptions. We present functions for non-parametric RCT + recruitment prediction under several scenarios. + date_publication: '2025-01-15' + bug_reports: https://github.com/imalagaris/RCTRecruit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RCTRecruit + url_git: https://github.com/imalagaris/RCTRecruit +RCTrep: + version: 1.2.0 + title: |- + Validation of Estimates of Treatment Effects in Observational + Data + maintainer: Lingjie Shen + description: Validates estimates of (conditional) average treatment effects obtained + using observational data by a) making it easy to obtain and visualize estimates + derived using a large variety of methods (G-computation, inverse propensity score + weighting, etc.), and b) ensuring that estimates are easily compared to a gold + standard (i.e., estimates derived from randomized controlled trials). 'RCTrep' + offers a generic protocol for treatment effect validation based on four simple + steps, namely, set-selection, estimation, diagnosis, and validation. 'RCTrep' + provides a simple dashboard to review the obtained results. The validation approach + is introduced by Shen, L., Geleijnse, G. and Kaptein, M. (2023) . + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCTrep + url_git: https://github.com/duolajiang/RCTrep +RCTS: + version: 0.2.4 + title: Clustering Time Series While Resisting Outliers + maintainer: Ewoud Heyndels + description: |- + Robust Clustering of Time Series (RCTS) has the functionality to cluster time series using both the classical and the robust interactive fixed effects framework. + The classical framework is developed in Ando & Bai (2017) . The implementation within this package excludes the SCAD-penalty on the estimations of beta. + This robust framework is developed in Boudt & Heyndels (2022) and is made robust against different kinds of outliers. + The algorithm iteratively updates beta (the coefficients of the observable variables), group membership, and the latent factors (which can be common and/or group-specific) along + with their loadings. The number of groups and factors can be estimated if they are unknown. + date_publication: '2023-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCTS + url_git: '' +rcube: + version: '0.5' + title: Simulations and Visualizations of Rubik's Cube (with Mods) + maintainer: Wojciech Rosa + description: Provides simplified methods for managing classic Rubik's cubes and + many other modifications of it (such as NxNxN size cubes, void cubes and 8-coloured + cubes - so called octa cubes). Includes functions of handling special syntax for + managing such cubes; and different approach to plotting 3D cubes without using + external libraries (for example 'OpenGL'). + date_publication: '2019-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rcube + url_git: '' +RCurl: + version: 1.98-1.16 + title: General Network (HTTP/FTP/...) Client Interface for R + maintainer: CRAN Team + description: |- + A wrapper for 'libcurl' + Provides functions to allow one to compose general HTTP requests + and provides convenient functions to fetch URIs, get & post + forms, etc. and process the results returned by the Web server. + This provides a great deal of control over the HTTP/FTP/... + connection and the form of the request while providing a + higher-level interface than is available just using R socket + connections. Additionally, the underlying implementation is + robust and extensive, supporting FTP/FTPS/TFTP (uploads and + downloads), SSL/HTTPS, telnet, dict, ldap, and also supports + cookies, redirects, authentication, etc. + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCurl + url_git: '' +Rcurvep: + version: 1.3.1 + title: Concentration-Response Data Analysis using Curvep + maintainer: Jui-Hua Hsieh + description: An R interface for processing concentration-response datasets using + Curvep, a response noise filtering algorithm. The algorithm was described in the + publications (Sedykh A et al. (2011) and Sedykh A (2016) + ). Other parametric fitting approaches (e.g., + Hill equation) are also adopted for ease of comparison. 3-parameter Hill equation + from 'tcpl' package (Filer D et al., ) and + 4-parameter Hill equation from Curve Class2 approach (Wang Y et al., ) + are available. Also, methods for calculating the confidence interval around the + activity metrics are also provided. The methods are based on the bootstrap approach + to simulate the datasets (Hsieh J-H et al. ). The simulated + datasets can be used to derive the baseline noise threshold in an assay endpoint. + This threshold is critical in the toxicological studies to derive the point-of-departure + (POD). + date_publication: '2024-01-09' + bug_reports: https://github.com/moggces/Rcurvep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rcurvep + url_git: https://github.com/moggces/Rcurvep +RCytoGPS: + version: 1.2.7 + title: Using Cytogenetics Data in R + maintainer: Kevin R. Coombes + description: |- + Defines classes and methods to process text-based + cytogenetics using the CytoGPS web site, then import the results + into R for further analysis and graphing. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RCytoGPS + url_git: http://oompa.r-forge.r-project.org/ +RCzechia: + version: 1.12.3 + title: Spatial Objects of the Czech Republic + maintainer: Jindra Lacko + description: Administrative regions and other spatial objects of the Czech Republic. + date_publication: '2024-11-26' + bug_reports: https://github.com/jlacko/RCzechia/issues + url: https://rczechia.jla-data.net + url_cran: https://CRAN.R-project.org/package=RCzechia + url_git: '' +Rd2md: + version: 1.0.1 + title: Markdown Reference Manuals + maintainer: Julian Busch + description: |- + Native R only allows PDF exports of reference manuals. + The 'Rd2md' package converts the package documentation files into + markdown files and combines them into a markdown version of the package + reference manual. + date_publication: '2024-06-17' + bug_reports: https://github.com/quantsch/rd2md/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rd2md + url_git: https://github.com/quantsch/rd2md +Rd2roxygen: + version: '1.16' + title: Convert Rd to 'Roxygen' Documentation + maintainer: Yihui Xie + description: |- + Functions to convert Rd to 'roxygen' documentation. It can parse an + Rd file to a list, create the 'roxygen' documentation and update the original + R script (e.g. the one containing the definition of the function) + accordingly. This package also provides utilities that can help developers + build packages using 'roxygen' more easily. The 'formatR' package can be used + to reformat the R code in the examples sections so that the code will be + more readable. + date_publication: '2024-04-15' + bug_reports: https://github.com/yihui/Rd2roxygen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rd2roxygen + url_git: https://github.com/yihui/Rd2roxygen +rD3plot: + version: 1.1.26 + title: |- + Interactive Networks, Timelines, Barplots, Galleries with + 'D3.js' + maintainer: Modesto Escobar + description: Creates interactive analytic graphs with 'R'. It joins the data analysis + power of R and the visualization libraries of JavaScript in one package. The package + provides interactive networks, timelines, barplots, image galleries and evolving + networks. Graphs are represented as 'D3.js' graphs embedded in a web page ready + for its interactive analysis and exploration. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rD3plot + url_git: '' +rda: + version: 1.2-1 + title: Shrunken Centroids Regularized Discriminant Analysis + maintainer: Valentin Todorov + description: |- + Provides functions implementing the shrunken centroids regularized discriminant analysis for + classification purpose in high dimensional data. The method is described in + Guo at al. (2013) . + date_publication: '2023-02-02' + bug_reports: https://github.com/valentint/rda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rda + url_git: https://github.com/valentint/rda +rdacca.hp: + version: 1.1-1 + title: Hierarchical and Variation Partitioning for Canonical Analysis + maintainer: Jiangshan Lai + description: 'This function conducts variation partitioning and hierarchical partitioning + to calculate the unique, shared (referred as to "common") and individual contributions + of each predictor (or matrix) towards explained variation (R-square and adjusted + R-square) on canonical analysis (RDA,CCA and db-RDA), applying the algorithm of + Lai J.,Zou Y., Zhang J.,Peres-Neto P.(2022) Generalizing hierarchical and variation + partitioning in multiple regression and canonical analyses using the rdacca.hp + R package.Methods in Ecology and Evolution,13: 782-788 .' + date_publication: '2024-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdacca.hp + url_git: https://github.com/laijiangshan/rdacca.hp +rdaisi: + version: 0.1.3 + title: R Client for the Daisi Microservice Platform + maintainer: Eric Hare + description: |- + Connect, execute, and parse results from the Daisi Microservice Platform . The rdaisi client + includes a set of functionality that allows remote execution of microservices directly from R. + Daisis allow R users to access a wide variety of Python functionality and interact with them natively. + date_publication: '2022-07-20' + bug_reports: '' + url: https://www.daisi.io/ + url_cran: https://CRAN.R-project.org/package=rdaisi + url_git: '' +rdatacite: + version: 0.5.4 + title: Client for the 'DataCite' API + maintainer: Bianca Kramer + description: |- + Client for the web service methods provided by 'DataCite' + (), including functions to interface with + their 'RESTful' search API. The API is backed by 'Elasticsearch', + allowing expressive queries, including faceting. + date_publication: '2023-02-05' + bug_reports: https://github.com/ropensci/rdatacite/issues + url: https://docs.ropensci.org/rdatacite/ + url_cran: https://CRAN.R-project.org/package=rdatacite + url_git: https://github.com/ropensci/rdatacite +rDataPipeline: + version: 0.60.0 + title: Functions to Interact with the 'FAIR Data Pipeline' + maintainer: Ryan Field + description: |- + R implementation of the 'FAIR Data Pipeline API'. The 'FAIR Data + Pipeline' is intended to enable tracking of provenance of FAIR (findable, + accessible and interoperable) data used in epidemiological modelling. + date_publication: '2024-10-08' + bug_reports: https://github.com/FAIRDataPipeline/rDataPipeline/issues + url: https://www.fairdatapipeline.org/rDataPipeline/ + url_cran: https://CRAN.R-project.org/package=rDataPipeline + url_git: https://github.com/FAIRDataPipeline/rDataPipeline +rdataretriever: + version: 3.1.1 + title: R Interface to the Data Retriever + maintainer: Henry Senyondo + description: |- + Provides an R interface to the Data Retriever + via the Data Retriever's + command line interface. The Data Retriever automates the + tasks of finding, downloading, and cleaning public datasets, + and then stores them in a local database. + date_publication: '2024-07-25' + bug_reports: https://github.com/ropensci/rdataretriever/issues + url: https://docs.ropensci.org/rdataretriever/(website) + url_cran: https://CRAN.R-project.org/package=rdataretriever + url_git: https://github.com/ropensci/rdataretriever/ +rdbnomics: + version: 0.6.4 + title: Download DBnomics Data + maintainer: Sebastien Galais + description: |- + R access to hundreds of millions data series from DBnomics API + (). + date_publication: '2020-10-25' + bug_reports: https://git.nomics.world/dbnomics/rdbnomics/-/issues + url: https://git.nomics.world/dbnomics/rdbnomics + url_cran: https://CRAN.R-project.org/package=rdbnomics + url_git: '' +rdd: + version: '0.57' + title: Regression Discontinuity Estimation + maintainer: Drew Dimmery + description: |- + Provides the tools to undertake estimation in + Regression Discontinuity Designs. Both sharp and fuzzy designs are + supported. Estimation is accomplished using local linear regression. + A provided function will utilize Imbens-Kalyanaraman optimal + bandwidth calculation. A function is also included to test the + assumption of no-sorting effects. + date_publication: '2016-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdd + url_git: '' +rddapp: + version: 1.3.2 + title: Regression Discontinuity Design Application + maintainer: Felix Thoemmes + description: |- + Estimation of both single- and multiple-assignment Regression Discontinuity Designs + (RDDs). Provides both parametric (global) and non-parametric (local) estimation choices for + both sharp and fuzzy designs, along with power analysis and assumption checks. + Introductions to the underlying logic and analysis of RDDs are in + Thistlethwaite, D. L., Campbell, D. T. (1960) and + Lee, D. S., Lemieux, T. (2010) . + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rddapp + url_git: '' +rddensity: + version: '2.6' + title: Manipulation Testing Based on Density Discontinuity + maintainer: Xinwei Ma + description: 'Density discontinuity testing (a.k.a. manipulation testing) is commonly + employed in regression discontinuity designs and other program evaluation settings + to detect perfect self-selection (manipulation) around a cutoff where treatment/policy + assignment changes. This package implements manipulation testing procedures using + the local polynomial density estimators: rddensity() to construct test statistics + and p-values given a prespecified cutoff, rdbwdensity() to perform data-driven + bandwidth selection, and rdplotdensity() to construct density plots.' + date_publication: '2024-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rddensity + url_git: '' +rddi: + version: 0.1.1 + title: R Interface to DDI Codebook 2.5 + maintainer: Daniel Woulfin + description: A direct interface to the underlying XML representation of DDI Codebook + 2.5 with flexible API creation. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rddi + url_git: '' +rddtools: + version: 1.6.0 + title: Toolbox for Regression Discontinuity Design ('RDD') + maintainer: Bastiaan Quast + description: |- + Set of functions for Regression Discontinuity Design ('RDD'), for + data visualisation, estimation and testing. + date_publication: '2022-01-10' + bug_reports: https://github.com/bquast/rddtools/issues + url: https://qua.st/rddtools/ + url_cran: https://CRAN.R-project.org/package=rddtools + url_git: '' +rde: + version: 0.1.0 + title: Reproducible Data Embedding + maintainer: Stefan Kloppenborg + description: |- + Allows caching of raw data directly in R code. This allows R + scripts and R Notebooks to be shared and re-run on a machine without access + to the original data. Cached data is encoded into an ASCII string that can + be pasted into R code. When the code is run, the data is automatically + loaded from the cached version if the original data file is unavailable. + Works best for small datasets (a few hundred observations). + date_publication: '2018-07-02' + bug_reports: https://github.com/kloppen/rde/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rde + url_git: https://github.com/kloppen/rde +rDEA: + version: 1.2-8 + title: Robust Data Envelopment Analysis (DEA) for R + maintainer: Jaak Simm + description: Data Envelopment Analysis for R, estimating robust DEA scores without + and with environmental variables and doing returns-to-scale tests. + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rDEA + url_git: https://github.com/jaak-s/rDEA +rdecision: + version: 1.3.0 + title: Decision Analytic Modelling in Health Economics + maintainer: Andrew Sims + description: |- + Classes and functions for modelling health care interventions + using decision trees and semi-Markov models. Mechanisms are provided for + associating an uncertainty distribution with each source variable and for + ensuring transparency of the mathematical relationships between variables. + The package terminology follows Briggs "Decision Modelling for Health + Economic Evaluation" (2006, ISBN:978-0-19-852662-9). + date_publication: '2025-02-10' + bug_reports: https://github.com/ajsims1704/rdecision/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdecision + url_git: https://github.com/ajsims1704/rdecision +rDecode: + version: 0.1.0 + title: Descent-Based Calibrated Optimal Direct Estimation + maintainer: Chi Seng Pun + description: Algorithms for solving a self-calibrated l1-regularized quadratic programming + problem without parameter tuning. The algorithm, called DECODE, can handle high-dimensional + data without cross-validation. It is found useful in high dimensional portfolio + selection (see Pun (2018) ) and large precision + matrix estimation and sparse linear discriminant analysis (see Pun and Hadimaja + (2019) ). + date_publication: '2019-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rDecode + url_git: '' +rdeps: + version: '0.2' + title: Identify External Packages Used in a Project + maintainer: Nicolas Casajus + description: |- + Screens all '.R', '.Rmd', and '.qmd' files to extract the name of + packages used in a project. This package detects packages called with + 'library(foo)', 'require(foo)', and 'foo::bar()' and adds these + dependencies in the DESCRIPTION file in the sections Depends, Imports, and + Suggests. + date_publication: '2024-02-02' + bug_reports: https://github.com/frbcesab/rdeps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdeps + url_git: https://github.com/frbcesab/rdeps +rdflib: + version: 0.2.9 + title: Tools to Manipulate and Query Semantic Data + maintainer: Carl Boettiger + description: |- + The Resource Description Framework, or 'RDF' is a widely used + data representation model that forms the cornerstone of the + Semantic Web. 'RDF' represents data as a graph rather than + the familiar data table or rectangle of relational databases. + The 'rdflib' package provides a friendly and concise user interface + for performing common tasks on 'RDF' data, such as reading, writing + and converting between the various serializations of 'RDF' data, + including 'rdfxml', 'turtle', 'nquads', 'ntriples', and 'json-ld'; + creating new 'RDF' graphs, and performing graph queries using 'SPARQL'. + This package wraps the low level 'redland' R package which + provides direct bindings to the 'redland' C library. Additionally, + the package supports the newer and more developer friendly + 'JSON-LD' format through the 'jsonld' package. The package + interface takes inspiration from the Python 'rdflib' library. + date_publication: '2024-08-17' + bug_reports: https://github.com/ropensci/rdflib/issues + url: https://docs.ropensci.org/rdflib/ + url_cran: https://CRAN.R-project.org/package=rdflib + url_git: https://github.com/ropensci/rdflib +rdfp: + version: 0.1.4 + title: An Implementation of the 'DoubleClick for Publishers' API + maintainer: Steven M. Mortimer + description: |- + Functions to interact with the 'Google DoubleClick for Publishers (DFP)' API + (recently renamed to + 'Google Ad Manager'). This package is automatically compiled from the API WSDL + (Web Service Description Language) files to dictate how the API is structured. + Theoretically, all API actions are possible using this package; however, care + must be taken to format the inputs correctly and parse the outputs correctly. + Please see the 'Google Ad Manager' API reference + and this package's website for more + information, documentation, and examples. + date_publication: '2019-06-05' + bug_reports: https://github.com/StevenMMortimer/rdfp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdfp + url_git: https://github.com/StevenMMortimer/rdfp +RDHonest: + version: 1.0.1 + title: Honest Inference in Regression Discontinuity Designs + maintainer: Michal Kolesár + description: |- + Honest and nearly-optimal confidence intervals in fuzzy and sharp + regression discontinuity designs and for inference at a point based on local + linear regression. The implementation is based on Armstrong and Kolesár (2018) + , and Kolesár and Rothe (2018) + . Supports covariates, clustering, and weighting. + date_publication: '2024-12-16' + bug_reports: https://github.com/kolesarm/RDHonest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RDHonest + url_git: https://github.com/kolesarm/RDHonest +rdhs: + version: 0.8.1 + title: |- + API Client and Dataset Management for the Demographic and Health + Survey (DHS) Data + maintainer: OJ Watson + description: |- + Provides a client for (1) querying the DHS API for survey indicators + and metadata (), (2) identifying surveys + and datasets for analysis, (3) downloading survey datasets from the DHS website, + (4) loading datasets and associate metadata into R, and (5) extracting variables + and combining datasets for pooled analysis. + date_publication: '2023-11-21' + bug_reports: https://github.com/ropensci/rdhs/issues + url: https://docs.ropensci.org/rdhs/ + url_cran: https://CRAN.R-project.org/package=rdhs + url_git: '' +rdi: + version: 1.0.0 + title: Repertoire Dissimilarity Index + maintainer: Christopher Bolen + description: |- + Methods for calculation and visualization of the Repertoire + Dissimilarity Index. Citation: Bolen and Rubelt, et al (2017) + . + date_publication: '2018-05-07' + bug_reports: https://bitbucket.org/cbolen1/rdicore/issues + url: http://rdi.readthedocs.io + url_cran: https://CRAN.R-project.org/package=rdi + url_git: '' +Rdiagnosislist: + version: 1.4.0 + title: Manipulate SNOMED CT Diagnosis Lists + maintainer: Anoop D. Shah + description: |- + Functions and methods for manipulating 'SNOMED CT' + concepts. The package contains functions for loading the 'SNOMED CT' + release into a convenient R environment, selecting 'SNOMED CT' + concepts using regular expressions, and navigating the 'SNOMED CT' + ontology. It provides the 'SNOMEDconcept' S3 class for a vector of + 'SNOMED CT' concepts (stored as 64-bit integers) and the + 'SNOMEDcodelist' S3 class for a table of concepts IDs with + descriptions. The package can be used to construct sets of + 'SNOMED CT' concepts for research (). + For more information about 'SNOMED CT' visit + . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rdiagnosislist + url_git: '' +rdian: + version: 0.1.1 + title: Client Library for The Guardian + maintainer: Oliver Keyes + description: |- + A client library for 'The Guardian' (https://www.guardian.com/) + and their API, this package allows users to search for Guardian articles and + retrieve both the content and metadata. + date_publication: '2016-02-05' + bug_reports: https://github.com/ironholds/rdian + url: '' + url_cran: https://CRAN.R-project.org/package=rdian + url_git: https://github.com/ironholds/rdian +Rdice: + version: 1.0.0 + title: A Collection of Functions to Experiment Dice Rolls + maintainer: 'Gennaro Tedesco:' + description: |- + A collection of functions to simulate + dice rolls and the like. In particular, experiments and exercises can + be performed looking at combinations and permutations of values in dice + rolls and coin flips, together with the corresponding frequencies of + occurrences. When applying each function, the user has to input the + number of times (rolls, flips) to toss the dice. Needless to say, the more + the tosses, the more the frequencies approximate the actual probabilities. + Moreover, the package provides functions to generate non-transitive sets + of dice (like Efron's) and to check whether a given set of dice is non-transitive + with given probability. + date_publication: '2016-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rdice + url_git: '' +RDieHarder: + version: 0.2.6 + title: R Interface to the 'DieHarder' RNG Test Suite + maintainer: Dirk Eddelbuettel + description: |- + The 'RDieHarder' package provides an R interface to + the 'DieHarder' suite of random number generators and tests that + was developed by Robert G. Brown and David Bauer, extending + earlier work by George Marsaglia and others. The 'DieHarder' + library code is included. + date_publication: '2024-01-12' + bug_reports: https://github.com/eddelbuettel/rdieharder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RDieHarder + url_git: https://github.com/eddelbuettel/rdieharder +Rdimtools: + version: 1.1.2 + title: Dimension Reduction and Estimation Methods + maintainer: Kisung You + description: |- + We provide linear and nonlinear dimension reduction techniques. + Intrinsic dimension estimation methods for exploratory analysis are also provided. + For more details on the package, see the paper by You and Shung (2022) . + date_publication: '2022-12-15' + bug_reports: https://github.com/kisungyou/Rdimtools/issues + url: https://www.kisungyou.com/Rdimtools/ + url_cran: https://CRAN.R-project.org/package=Rdimtools + url_git: '' +rdist: + version: 0.0.5 + title: Calculate Pairwise Distances + maintainer: Nello Blaser + description: A common framework for calculating distance matrices. + date_publication: '2020-05-04' + bug_reports: https://github.com/blasern/rdist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdist + url_git: https://github.com/blasern/rdist +Rdistance: + version: 3.0.0 + title: Distance-Sampling Analyses for Density and Abundance Estimation + maintainer: Trent McDonald + description: |- + Distance-sampling analyses estimate density and + abundance of organisms in ecology when detection probability declines with + increasing distance from the observers. Distance-sampling is popular + in most branches of ecology and especially when + organisms are observed from aerial platforms (e.g., airplane or drone), + surface vessels (e.g., boat or truck), or along walking transects. + Rdistance analyzes data collected on both point and line transects, + estimates overall (study area) and site-level (transect or point) + density, and allows users to specify regression-like formula (similar + to lm or glm) for covariates. A large suite of classical, + parametric detection functions are + included along with some uncommon parametric + functions (e.g., Gamma, negative exponential) and non-parametric + smoothed distance functions. Custom (user-defined) detection functions + can be implemented (see vignette). Measurement unit integrity is + enforced with internal unit conversion when necessary. + The help files and vignettes have been + vetted by multiple authors and tested in workshop + settings. + date_publication: '2023-06-13' + bug_reports: https://github.com/tmcd82070/Rdistance/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rdistance + url_git: https://github.com/tmcd82070/Rdistance/wiki +rdiversity: + version: 2.2.0 + title: |- + Measurement and Partitioning of Similarity-Sensitive + Biodiversity + maintainer: Richard Reeve + description: |- + Provides a framework for the measurement and partitioning of + the (similarity-sensitive) biodiversity of a metacommunity and its + constituent subcommunities. Richard Reeve, et al. (2016) + . + date_publication: '2022-05-06' + bug_reports: https://github.com/boydorr/rdiversity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdiversity + url_git: https://github.com/boydorr/rdiversity +rdlearn: + version: 0.1.1 + title: |- + Safe Policy Learning under Regression Discontinuity Design with + Multiple Cutoffs + maintainer: Kentaro Kawato + description: |- + Implements safe policy learning under regression discontinuity designs + with multiple cutoffs, based on Zhang et al. (2022) . + The learned cutoffs are guaranteed to perform no worse than the existing + cutoffs in terms of overall outcomes. The 'rdlearn' package also includes + features for visualizing the learned cutoffs relative to the baseline and + conducting sensitivity analyses. + date_publication: '2025-01-29' + bug_reports: https://github.com/kkawato/rdlearn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdlearn + url_git: https://github.com/kkawato/rdlearn +rdlocrand: + version: '1.0' + title: Local Randomization Methods for RD Designs + maintainer: Gonzalo Vazquez-Bare + description: 'The regression discontinuity (RD) design is a popular quasi-experimental + design for causal inference and policy evaluation. Under the local randomization + approach, RD designs can be interpreted as randomized experiments inside a window + around the cutoff. This package provides tools to perform randomization inference + for RD designs under local randomization: rdrandinf() to perform hypothesis testing + using randomization inference, rdwinselect() to select a window around the cutoff + in which randomization is likely to hold, rdsensitivity() to assess the sensitivity + of the results to different window lengths and null hypotheses and rdrbounds() + to construct Rosenbaum bounds for sensitivity to unobserved confounders. See Cattaneo, + Titiunik and Vazquez-Bare (2016) + for further methodological details.' + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdlocrand + url_git: '' +RDM: + version: 0.1.1 + title: Quantify Dependence using Rearranged Dependence Measures + maintainer: Christopher Strothmann + description: |- + Estimates the rearranged dependence measure ('RDM') of two continuous random variables for different underlying measures. + Furthermore, it provides a method to estimate the (SI)-rearrangement copula using empirical checkerboard copulas. + It is based on the theoretical results presented in Strothmann et al. (2022) and Strothmann (2021) . + date_publication: '2023-02-24' + bug_reports: https://github.com/ChristopherStrothmann/RDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RDM + url_git: https://github.com/ChristopherStrothmann/RDM +RDML: + version: '1.0' + title: |- + Importing Real-Time Thermo Cycler (qPCR) Data from RDML Format + Files + maintainer: Konstantin A. Blagodatskikh + description: |- + Imports real-time thermo cycler (qPCR) data from Real-time PCR + Data Markup Language (RDML) and transforms to the appropriate formats of + the 'qpcR' and 'chipPCR' packages. Contains a dendrogram visualization + for the structure of RDML object and GUI for RDML editing. + date_publication: '2019-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RDML + url_git: https://github.com/kablag/RDML +rdmulti: + version: '1.1' + title: Analysis of RD Designs with Multiple Cutoffs or Scores + maintainer: Gonzalo Vazquez-Bare + description: 'The regression discontinuity (RD) design is a popular quasi-experimental + design for causal inference and policy evaluation. The ''rdmulti'' package provides + tools to analyze RD designs with multiple cutoffs or scores: rdmc() estimates + pooled and cutoff specific effects for multi-cutoff designs, rdmcplot() draws + RD plots for multi-cutoff designs and rdms() estimates effects in cumulative cutoffs + or multi-score designs. See Cattaneo, Titiunik and Vazquez-Bare (2020) + for further methodological details.' + date_publication: '2023-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdmulti + url_git: '' +rdnb: + version: 0.1-5 + title: |- + R Interface to the 'Deutsche Nationalbibliothek (German National + Library) API' + maintainer: Christian Graul + description: |- + A wrapper for the 'Deutsche Nationalbibliothek (German National + Library) API', available at . + The German National Library is the German central archival library, + collecting, archiving, bibliographically classifying all German and + German-language publications, foreign publications about Germany, + translations of German works, and the works of German-speaking emigrants + published abroad between 1933 and 1945. + date_publication: '2022-05-12' + bug_reports: https://github.com/chgrl/rdnb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdnb + url_git: https://github.com/chgrl/rdnb +RDnp: + version: '1.3' + title: Robust Test for Complete Independence in High-Dimensions + maintainer: Hasan BULUT + description: 'Test Statistics for Independence in High-Dimensional Datasets. This + package consists of two functions to perform the complete independence test based + on test statistics proposed by Bulut (unpublished yet) and suggested by Najarzadeh + (2021) . The Bulut''s statistic is not sensitive + to outliers in high-dimensional data, unlike one of Najarzadeh (2021) . + So, the Bulut''s statistic can be performed robustly by using RDnp function.' + date_publication: '2021-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RDnp + url_git: '' +rdomains: + version: 0.2.1 + title: Get the Category of Content Hosted by a Domain + maintainer: Gaurav Sood + description: |- + Get the category of content hosted by a domain. Use Shallalist , + Virustotal (which provides access to lots of services) , + Alexa , DMOZ , University Domain list + or validated machine learning + classifiers based on Shallalist data to learn about the kind of content hosted by a domain. + date_publication: '2022-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdomains + url_git: '' +RDota2: + version: 0.1.6 + title: An R Steam API Client for Valve's Dota2 + maintainer: Theo Boutaris + description: |- + An R API Client for Valve's Dota2. RDota2 can be easily used + to connect to the Steam API and retrieve data for Valve's popular video + game Dota2. You can find out more about Dota2 at + . + date_publication: '2016-10-30' + bug_reports: https://github.com/LyzandeR/RDota2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RDota2 + url_git: https://github.com/LyzandeR/RDota2 +rdoxygen: + version: 1.0.0 + title: Create Doxygen Documentation for Source Code + maintainer: Clemens Schmid + description: |- + Create doxygen documentation for source code in R packages. + Includes a RStudio Addin, that allows to trigger the doxygenize process. + date_publication: '2017-05-25' + bug_reports: https://github.com/nevrome/rdoxygen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdoxygen + url_git: https://github.com/nevrome/rdoxygen +RDP: + version: 0.3.0 + title: The Ramer-Douglas-Peucker Algorithm + maintainer: Robert Dahl Jacobsen + description: |- + Pretty fast implementation of the Ramer-Douglas-Peucker algorithm for reducing the number of points on a 2D curve. + Urs Ramer (1972), "An iterative procedure for the polygonal approximation of plane curves" . + David H. Douglas and Thomas K. Peucker (1973), "Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature" . + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RDP + url_git: https://github.com/robertdj/RDP +Rdpack: + version: 2.6.2 + title: Update and Manipulate Rd Documentation Objects + maintainer: Georgi N. Boshnakov + description: |- + Functions for manipulation of R documentation objects, + including functions reprompt() and ereprompt() for updating 'Rd' + documentation for functions, methods and classes; 'Rd' macros for + citations and import of references from 'bibtex' files for use in + 'Rd' files and 'roxygen2' comments; 'Rd' macros for evaluating and + inserting snippets of 'R' code and the results of its evaluation or + creating graphics on the fly; and many functions for manipulation of + references and Rd files. + date_publication: '2024-11-15' + bug_reports: https://github.com/GeoBosh/Rdpack/issues + url: https://geobosh.github.io/Rdpack/(doc) + url_cran: https://CRAN.R-project.org/package=Rdpack + url_git: https://github.com/GeoBosh/Rdpack(devel) +rdpower: + version: '2.2' + title: Power Calculations for RD Designs + maintainer: Gonzalo Vazquez-Bare + description: 'The regression discontinuity (RD) design is a popular quasi-experimental + design for causal inference and policy evaluation. The ''rdpower'' package provides + tools to perform power, sample size and MDE calculations in RD designs: rdpower() + calculates the power of an RD design, rdsampsi() calculates the required sample + size to achieve a desired power and rdmde() calculates minimum detectable effects. + See Cattaneo, Titiunik and Vazquez-Bare (2019) + for further methodological details.' + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdpower + url_git: '' +rdracor: + version: 1.0.4 + title: Access to the 'DraCor' API + maintainer: Ivan Pozdniakov + description: 'Provide an interface for ''Drama Corpora Project'' (''DraCor'') API: + .' + date_publication: '2024-09-26' + bug_reports: https://github.com/dracor-org/rdracor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdracor + url_git: https://github.com/dracor-org/rdracor +rdrobust: + version: '2.2' + title: |- + Robust Data-Driven Statistical Inference in + Regression-Discontinuity Designs + maintainer: Sebastian Calonico + description: "Regression-discontinuity (RD) designs are quasi-experimental research + designs popular in social, behavioral and natural sciences. The RD design is usually + employed to study the (local) causal effect of a treatment, intervention or policy. + This package provides tools for data-driven graphical and analytical statistical + inference in RD\tdesigns: rdrobust() to construct local-polynomial point estimators + and robust confidence intervals for average treatment effects at the \tcutoff + in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection + for the different procedures implemented, and rdplot() to conduct exploratory + data analysis (RD plots)." + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdrobust + url_git: '' +Rdrw: + version: 1.0.2 + title: Univariate and Multivariate Damped Random Walk Processes + maintainer: Hyungsuk Tak + description: We provide a toolbox to fit and simulate a univariate or multivariate + damped random walk process that is also known as an Ornstein-Uhlenbeck process + or a continuous-time autoregressive model of the first order, i.e., CAR(1) or + CARMA(1, 0). This process is suitable for analyzing univariate or multivariate + time series data with irregularly-spaced observation times and heteroscedastic + measurement errors. When it comes to the multivariate case, the number of data + points (measurements/observations) available at each observation time does not + need to be the same, and the length of each time series can vary. The number of + time series data sets that can be modeled simultaneously is limited to ten in + this version of the package. We use Kalman-filtering to evaluate the resulting + likelihood function, which leads to a scalable and efficient computation in finding + maximum likelihood estimates of the model parameters or in drawing their posterior + samples. Please pay attention to loading the data if this package is used for + astronomical data analyses; see the details in the manual. Also see Hu and Tak + (2020) . + date_publication: '2020-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rdrw + url_git: '' +rdryad: + version: 1.0.0 + title: Access for Dryad Web Services + maintainer: Scott Chamberlain + description: |- + Interface to the Dryad "Solr" API, their "OAI-PMH" service, and + fetch datasets. Dryad () is a curated host of + data underlying scientific publications. + date_publication: '2020-06-25' + bug_reports: https://github.com/ropensci/rdryad/issues + url: https://docs.ropensci.org/rdryad + url_cran: https://CRAN.R-project.org/package=rdryad + url_git: https://github.com/ropensci/rdryad +RDS: + version: 0.9-10 + title: Respondent-Driven Sampling + maintainer: Mark S. Handcock + description: |- + Provides functionality for carrying out estimation + with data collected using Respondent-Driven Sampling. This includes + Heckathorn's RDS-I and RDS-II estimators as well as Gile's Sequential + Sampling estimator. The package is part of the "RDS Analyst" suite of + packages for the analysis of respondent-driven sampling data. + See Gile and Handcock (2010) , + Gile and Handcock (2015) and + Gile, Beaudry, Handcock and Ott (2018) . + date_publication: '2024-09-06' + bug_reports: '' + url: https://hpmrg.org + url_cran: https://CRAN.R-project.org/package=RDS + url_git: '' +Rdsdp: + version: 1.0.5.2.1 + title: R Interface to DSDP Semidefinite Programming Library + maintainer: Zhisu Zhu + description: R interface to DSDP semidefinite programming library. The DSDP software + is a free open source implementation of an interior-point method for semidefinite + programming. It provides primal and dual solutions, exploits low-rank structure + and sparsity in the data, and has relatively low memory requirements for an interior-point + method. + date_publication: '2023-05-19' + bug_reports: '' + url: https://www.mcs.anl.gov/hs/software/DSDP + url_cran: https://CRAN.R-project.org/package=Rdsdp + url_git: '' +rdss: + version: 1.0.14 + title: |- + Companion Datasets and Functions for Research Design in the + Social Sciences + maintainer: Graeme Blair + description: 'Helper functions to accompany the Blair, Coppock, and Humphreys (2022) + "Research Design in the Social Sciences: Declaration, Diagnosis, and Redesign" + . ''rdss'' includes datasets, helper functions, + and plotting components to enable use and replication of the book.' + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdss + url_git: '' +RDSsamplesize: + version: 0.5.0 + title: RDS Sample Size Estimation and Power Calculation + maintainer: Yibo Wang + description: Provides functionality for carrying out sample size estimation and + power calculation in Respondent-Driven Sampling. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RDSsamplesize + url_git: '' +RDStreeboot: + version: '1.0' + title: RDS Tree Bootstrap Method + maintainer: Aaron J. Baraff + description: A tree bootstrap method for estimating uncertainty in respondent-driven + samples (RDS). Quantiles are estimated by multilevel resampling in such a way + that preserves the dependencies of and accounts for the high variability of the + RDS process. + date_publication: '2016-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RDStreeboot + url_git: '' +Rdta: + version: 1.0.1 + title: Data Transforming Augmentation for Linear Mixed Models + maintainer: Hyungsuk Tak + description: We provide a toolbox to fit univariate and multivariate linear mixed + models via data transforming augmentation. Users can also fit these models via + typical data augmentation for a comparison. It returns either maximum likelihood + estimates of unknown model parameters (hyper-parameters) via an EM algorithm or + posterior samples of those parameters via MCMC. Also see Tak et al. (2019) . + date_publication: '2024-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rdta + url_git: '' +rdtLite: + version: '1.4' + title: Provenance Collector + maintainer: Barbara Lerner + description: |- + Defines functions that can be used to collect provenance as + an 'R' script executes or during a console session. The output is a text + file in 'PROV-JSON' format. + date_publication: '2022-08-08' + bug_reports: https://github.com/End-to-end-provenance/rdtLite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdtLite + url_git: https://github.com/End-to-end-provenance/rdtLite +Rduino: + version: '0.1' + title: A Microcontroller Interface + maintainer: Peter Hoff + description: Functions for connecting to and interfacing with an 'Arduino' or similar + device. Functionality includes uploading of sketches, setting and reading digital + and analog pins, and rudimentary servo control. This project is not affiliated + with the 'Arduino' company, . + date_publication: '2017-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rduino + url_git: '' +Rduinoiot: + version: 0.1.0 + title: '''Arduino Iot Cloud API'' R Client' + maintainer: Flavio Leccese + description: Easily interact with the 'Arduino Iot Cloud API' , + managing devices, things, properties and data. + date_publication: '2022-09-14' + bug_reports: https://github.com/FlavioLeccese92/Rduinoiot/issues/ + url: https://flavioleccese92.github.io/Rduinoiot/ + url_cran: https://CRAN.R-project.org/package=Rduinoiot + url_git: '' +Rdune: + version: 1.1.1 + title: '''Creates Color Palettes Inspired by Dune''' + maintainer: Nicholas Vietto + description: Enables the use of color palettes inspired by the 'Dune' movies. These + palettes are compatible with 'ggplot2'. See Wickham (2016) + for more details on 'ggplot2'. + date_publication: '2024-07-29' + bug_reports: https://github.com/nvietto/Rdune/issues + url: https://nvietto.github.io/Rdune/ + url_cran: https://CRAN.R-project.org/package=Rdune + url_git: https://github.com/nvietto/Rdune +rdwd: + version: 1.8.0 + title: |- + Select and Download Climate Data from 'DWD' (German Weather + Service) + maintainer: Berry Boessenkool + description: |- + Handle climate data from the 'DWD' ('Deutscher Wetterdienst', see + for more information). + Choose observational time series from meteorological stations with 'selectDWD()'. + Find raster data from radar and interpolation according to . + Download (multiple) data sets with progress bars and no re-downloads through 'dataDWD()'. + Read both tabular observational data and binary gridded datasets with 'readDWD()'. + date_publication: '2023-06-17' + bug_reports: https://github.com/brry/rdwd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rdwd + url_git: https://github.com/brry/rdwd +rdwplus: + version: 1.0.1 + title: Inverse Distance Weighted Percent Land Use for Streams + maintainer: Alan Pearse + description: Compute spatially explicit land-use metrics for stream survey sites + in GRASS GIS and R as an open-source implementation of IDW-PLUS (Inverse Distance + Weighted Percent Land Use for Streams). The package includes functions for preprocessing + digital elevation and streams data, and one function to compute all the spatially + explicit land use metrics described in Peterson et al. (2011) + and previously implemented by Peterson and Pearse (2017) + in ArcGIS-Python as IDW-PLUS. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rdwplus + url_git: '' +re: + version: 0.1.0 + title: '''Python'' Style Regular Expression Functions' + maintainer: Garrett Shipley + description: |- + A comprehensive set of regular expression functions based on those found in 'Python' + without relying on 'reticulate'. It provides functions that intend to (1) make it easier for + users familiar with 'Python' to work with regular expressions, (2) reduce the complexity often + associated with regular expressions code, (3) and enable users to write more readable and + maintainable code that relies on regular expression-based pattern matching. + date_publication: '2024-09-02' + bug_reports: https://github.com/pythonicr/re/issues + url: https://pythonicr.github.io/re/ + url_cran: https://CRAN.R-project.org/package=re + url_git: https://github.com/pythonicr/re +re2: + version: 0.1.4 + title: R Interface to Google RE2 (C++) Regular Expression Library + maintainer: Girish Palya + description: |- + Pattern matching, extraction, replacement and other string + processing operations using Google's RE2 + regular-expression engine. Consistent interface (similar to 'stringr'). + RE2 uses finite-automata based techniques, and offers a + fast and safe alternative to backtracking regular-expression engines + like those used in 'stringr', 'stringi' and other PCRE implementations. + date_publication: '2025-01-19' + bug_reports: https://github.com/girishji/re2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=re2 + url_git: https://github.com/girishji/re2 +Reacnorm: + version: 0.2.1 + title: Perform a Partition of Variance of Reaction Norms + maintainer: Pierre de Villemereuil + description: 'Partitions the phenotypic variance of a plastic trait, studied through + its reaction norm. The variance partition distinguishes between the variance arising + from the average shape of the reaction norms (V_Plas) and the (additive) genetic + variance . The latter is itself separated into an environment-blind component + (V_G/V_A) and the component arising from plasticity (V_GxE/V_AxE). The package + also provides a way to further partition V_Plas into aspects (slope/curvature) + of the shape of the average reaction norm (pi-decomposition) and partition V_Add + (gamma-decomposition) and V_AxE (iota-decomposition) into the impact of genetic + variation in the reaction norm parameters. Reference: de Villemereuil & Chevin + (2025) .' + date_publication: '2025-01-27' + bug_reports: https://github.com/devillemereuil/reacnorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Reacnorm + url_git: '' +react: + version: 2024.1.0 + title: Reactivity Helper for 'shiny' + maintainer: Romain François + description: |- + Tools to help with 'shiny' reactivity. The 'react' object offers + an alternative way to call reactive expressions to better identify them + in the server code. + date_publication: '2024-02-02' + bug_reports: https://github.com/tadascience/react/issues + url: https://react.tada.science/ + url_cran: https://CRAN.R-project.org/package=react + url_git: https://github.com/tadascience/react +reactable: + version: 0.4.4 + title: Interactive Data Tables for R + maintainer: Greg Lin + description: |- + Interactive data tables for R, based on the 'React Table' + JavaScript library. Provides an HTML widget that can be used in 'R Markdown' + or 'Quarto' documents, 'Shiny' applications, or viewed from an R console. + date_publication: '2023-03-12' + bug_reports: https://github.com/glin/reactable/issues + url: https://glin.github.io/reactable/ + url_cran: https://CRAN.R-project.org/package=reactable + url_git: https://github.com/glin/reactable +reactable.extras: + version: 0.2.1 + title: Extra Features for 'reactable' Package + maintainer: Recle Vibal + description: |- + Enhanced functionality for 'reactable' in 'shiny' applications, offering interactive and dynamic data table capabilities with ease. + With 'reactable.extras', easily integrate a range of functions and components to enrich your 'shiny' apps and facilitate user-friendly data exploration. + date_publication: '2024-10-29' + bug_reports: https://github.com/Appsilon/reactable.extras/issues + url: https://appsilon.github.io/reactable.extras/ + url_cran: https://CRAN.R-project.org/package=reactable.extras + url_git: https://github.com/Appsilon/reactable.extras +reactablefmtr: + version: 2.0.0 + title: Streamlined Table Styling and Formatting for Reactable + maintainer: Kyle Cuilla + description: |- + Provides various features to streamline and enhance the styling of interactive + reactable tables with easy-to-use and highly-customizable functions and themes. + Apply conditional formatting to cells with data bars, color scales, color tiles, + and icon sets. Utilize custom table themes inspired by popular websites such + and bootstrap themes. Apply sparkline line & bar charts + (note this feature requires the 'dataui' package which can be downloaded from + ). + Increase the portability and reproducibility of reactable tables by embedding images + from the web directly into cells. Save the final table output as a static image or + interactive file. + date_publication: '2022-03-16' + bug_reports: https://github.com/kcuilla/reactablefmtr/issues + url: https://kcuilla.github.io/reactablefmtr/ + url_cran: https://CRAN.R-project.org/package=reactablefmtr + url_git: https://github.com/kcuilla/reactablefmtr +reactCheckbox: + version: 1.0.0 + title: Checkbox Group Input for 'Shiny' + maintainer: Stéphane Laurent + description: |- + Provides a checkbox group input for usage in a 'Shiny' + application. The checkbox group has a head checkbox allowing to check + or uncheck all the checkboxes in the group. The checkboxes are + customizable. + date_publication: '2023-03-01' + bug_reports: https://github.com/stla/reactCheckbox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reactCheckbox + url_git: https://github.com/stla/reactCheckbox +reactlog: + version: 1.1.1 + title: Reactivity Visualizer for 'shiny' + maintainer: Barret Schloerke + description: |- + Building interactive web applications with R is incredibly easy + with 'shiny'. Behind the scenes, 'shiny' builds a reactive graph that can + quickly become intertwined and difficult to debug. 'reactlog' + (Schloerke 2019) provides a visual insight into + that black box of 'shiny' reactivity by constructing a directed dependency + graph of the application's reactive state at any time point in a reactive + recording. + date_publication: '2022-09-26' + bug_reports: https://github.com/rstudio/reactlog/issues + url: https://rstudio.github.io/reactlog/ + url_cran: https://CRAN.R-project.org/package=reactlog + url_git: https://github.com/rstudio/reactlog +reactR: + version: 0.6.1 + title: React Helpers + maintainer: Kent Russell + description: |- + Make it easy to use 'React' in R with 'htmlwidget' scaffolds, + helper dependency functions, an embedded 'Babel' 'transpiler', + and examples. + date_publication: '2024-09-14' + bug_reports: https://github.com/react-R/reactR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reactR + url_git: https://github.com/react-R/reactR +ReacTran: + version: 1.4.3.1 + title: Reactive Transport Modelling in 1d, 2d and 3d + maintainer: Karline Soetaert + description: |- + Routines for developing models that describe reaction and advective-diffusive transport in one, two or three dimensions. + Includes transport routines in porous media, in estuaries, and in bodies with variable shape. + date_publication: '2017-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReacTran + url_git: '' +ReAD: + version: 1.0.1 + title: |- + Powerful Replicability Analysis of Genome-Wide Association + Studies + maintainer: Yan Li + description: A robust and powerful approach is developed for replicability analysis + of two Genome-wide association studies (GWASs) accounting for the linkage disequilibrium + (LD) among genetic variants. The LD structure in two GWASs is captured by a four-state + hidden Markov model (HMM). The unknowns involved in the HMM are estimated by an + efficient expectation-maximization (EM) algorithm in combination with a non-parametric + estimation of functions. By incorporating information from adjacent locations + via the HMM, this approach identifies the entire clusters of genotype-phenotype + associated signals, improving the power of replicability analysis while effectively + controlling the false discovery rate. + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReAD + url_git: '' +read.gb: + version: '2.2' + title: Open GenBank Files + maintainer: Robin Mercier + description: Opens complete record(s) with .gb extension from the NCBI/GenBank Nucleotide + database and returns a list containing shaped record(s). These kind of files contains + detailed records of DNA samples (locus, organism, type of sequence, source of + the sequence...). An example of record can be found at . + date_publication: '2021-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=read.gb + url_git: '' +read.gt3x: + version: 1.2.0 + title: Parse 'ActiGraph' 'GT3X'/'GT3X+' 'Accelerometer' Data + maintainer: Tuomo Nieminen + description: |- + Implements a high performance C++ parser + for 'ActiGraph' 'GT3X'/'GT3X+' data format (with extension '.gt3x') + for 'accelerometer' samples. Activity samples can be easily read into a + matrix or data.frame. This allows for storing the raw 'accelerometer' + samples in the original binary format to reserve space. + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=read.gt3x + url_git: '' +readABF: + version: 1.0.2 + title: Loads Axon Binary Files + maintainer: Stanislav Syekirin + description: Loads Axon Binary Files (both 'ABF' and 'ABF2') created by Axon Instruments/Molecular + Devices software such as 'pClamp'. + date_publication: '2020-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=readABF + url_git: '' +readabs: + version: 0.4.16 + title: |- + Download and Tidy Time Series Data from the Australian Bureau of + Statistics + maintainer: Matt Cowgill + description: |- + Downloads, imports, and tidies time series data from the + Australian Bureau of Statistics . + date_publication: '2024-05-27' + bug_reports: https://github.com/mattcowgill/readabs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readabs + url_git: https://github.com/mattcowgill/readabs +readapra: + version: 0.2.1 + title: |- + Download and Tidy Data from the Australian Prudential Regulation + Authority + maintainer: Jarrod van der Wal + description: |- + Download the latest data from the Australian Prudential Regulation + Authority and import it into R as a tidy data + frame. + date_publication: '2025-02-23' + bug_reports: https://github.com/javanderwal/readapra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readapra + url_git: https://github.com/javanderwal/readapra +readbitmap: + version: 0.1.5 + title: |- + Simple Unified Interface to Read Bitmap Images + (BMP,JPEG,PNG,TIFF) + maintainer: Gregory Jefferis + description: |- + Identifies and reads Windows BMP, JPEG, PNG, and TIFF format bitmap + images. Identification defaults to the use of the magic number embedded in + the file rather than the file extension. Reading of JPEG and PNG image + depends on libjpg and libpng libraries. See file INSTALL for details if + necessary. + date_publication: '2018-06-27' + bug_reports: https://github.com/jefferis/readbitmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readbitmap + url_git: https://github.com/jefferis/readbitmap +readBrukerFlexData: + version: 1.9.3 + title: Reads Mass Spectrometry Data in Bruker *flex Format + maintainer: Sebastian Gibb + description: |- + Reads data files acquired by Bruker Daltonics' matrix-assisted + laser desorption/ionization-time-of-flight mass spectrometer of the *flex + series. + date_publication: '2024-10-02' + bug_reports: https://github.com/sgibb/readBrukerFlexData/issues/ + url: https://strimmerlab.github.io/software/maldiquant/ + url_cran: https://CRAN.R-project.org/package=readBrukerFlexData + url_git: https://github.com/sgibb/readBrukerFlexData/ +readbulk: + version: 1.1.4 + title: Read and Combine Multiple Data Files + maintainer: Pascal J. Kieslich + description: |- + Combine multiple data files from a common directory. + The data files will be read into R and bound together, creating a + single large data.frame. A general function is provided along with + a specific function for data that was collected using the open-source + experiment builder 'OpenSesame' . + date_publication: '2024-01-08' + bug_reports: https://github.com/pascalkieslich/readbulk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readbulk + url_git: https://github.com/pascalkieslich/readbulk +ReadDIM: + version: 0.2.11 + title: Read ESA SNAP Processed Raster Format in R + maintainer: Subhadip Datta + description: It helps you to read (.dim) images with CRS directly into R programming. + One can import both Sentinel 1 and 2 images or any processed data with this software. + date_publication: '2023-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReadDIM + url_git: '' +reader: + version: 1.0.6 + title: Suite of Functions to Flexibly Read Data from Files + maintainer: Nicholas Cooper + description: A set of functions to simplify reading data from files. The main function, + reader(), should read most common R datafile types without needing any parameters + except the filename. Other functions provide simple ways of handling file paths + and extensions, and automatically detecting file format and structure. + date_publication: '2017-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reader + url_git: '' +readHAC: + version: '1.0' + title: Read Acoustic HAC Format + maintainer: Kasper Kristensen + description: Read Acoustic HAC format. + date_publication: '2017-02-02' + bug_reports: https://github.com/kaskr/HAC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readHAC + url_git: https://github.com/kaskr/HAC +readit: + version: 1.0.0 + title: Effortlessly Read Any Rectangular Data + maintainer: Ryan Price + description: |2- + + Providing just one primary function, 'readit' uses a set of reasonable + heuristics to apply the appropriate reader function to the given file path. + As long as the data file has an extension, and the data is (or can be + coerced to be) rectangular, readit() can probably read it. + date_publication: '2018-03-13' + bug_reports: https://github.com/ryapric/readit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readit + url_git: https://github.com/ryapric/readit +readJDX: + version: 0.6.4 + title: Import Data in the JCAMP-DX Format + maintainer: Bryan A. Hanson + description: Import data written in the JCAMP-DX format. This is an instrument-independent + format used in the field of spectroscopy. Examples include IR, NMR, and Raman + spectroscopy. See the vignette for background and supported formats. The official + JCAMP-DX site is . + date_publication: '2023-11-18' + bug_reports: https://github.com/bryanhanson/readJDX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readJDX + url_git: https://github.com/bryanhanson/readJDX +readMDTable: + version: 0.3.1 + title: Read Markdown Tables into Tibbles + maintainer: Jordan Bradford + description: |- + Efficient reading of raw markdown tables into tibbles. Designed to + accept content from strings, files, and URLs with the ability to extract + and read multiple tables from markdown for analysis. + date_publication: '2025-01-25' + bug_reports: https://github.com/jrdnbradford/readMDTable/issues + url: https://jrdnbradford.github.io/readMDTable/ + url_cran: https://CRAN.R-project.org/package=readMDTable + url_git: https://github.com/jrdnbradford/readMDTable +readme2vignette: + version: 0.1.0 + title: Convert README to Vignette During Package Installation + maintainer: Mao Kobayashi + description: Convert README.md to vignettes when installing packages without vignettes. + date_publication: '2024-06-26' + bug_reports: https://github.com/indenkun/readme2vignette/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readme2vignette + url_git: https://github.com/indenkun/readme2vignette +readmet: + version: 1.7.1 + title: Read some less Popular Formats Used in Meteorology + maintainer: Clemens Druee + description: 'Contains tools for reading and writing data from or to files in the + formats: akterm, dmna, Scintec Format-1, and Campbell Scientific TOA5.' + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=readmet + url_git: '' +readmission: + version: 0.1.0 + title: Hospital Readmission Data for Patients with Diabetes + maintainer: Simon Couch + description: |- + Clinical care data from 130 U.S. hospitals in the years 1999-2008 + adapted from the study Strack et al. (2014) . + Each row describes an "encounter" with a patient with diabetes, including + variables on demographics, medications, patient history, diagnostics, + payment, and readmission. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=readmission + url_git: '' +readMLData: + version: 0.9-7 + title: |- + Reading Machine Learning Benchmark Data Sets in Different + Formats + maintainer: Petr Savicky + description: |- + Functions for reading data sets in different formats + for testing machine learning tools are provided. This allows to run + a loop over several data sets in their original form, for example + if they are downloaded from UCI Machine Learning Repository. + The data are not part of the package and have to be downloaded + separately. + date_publication: '2015-01-13' + bug_reports: '' + url: http://www.cs.cas.cz/~savicky/readMLData + url_cran: https://CRAN.R-project.org/package=readMLData + url_git: '' +readmoRe: + version: 0.2-15 + title: Utilities for Importing and Manipulating Biomedical Data Files + maintainer: Vidal Fey + description: |- + Tools to read various file types into one list of data structures, usually, but not limited to, data frames. + Excel files are read sheet-wise, i.e., all or a selection of sheets can be read. Field delimiters and decimal + separators are determined automatically. + date_publication: '2025-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=readmoRe + url_git: '' +readMzXmlData: + version: 2.8.3 + title: Reads Mass Spectrometry Data in mzXML Format + maintainer: Sebastian Gibb + description: Functions for reading mass spectrometry data in mzXML format. + date_publication: '2023-08-19' + bug_reports: https://github.com/sgibb/readMzXmlData/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=readMzXmlData + url_git: https://strimmerlab.github.io/software/maldiquant/https://github.com/sgibb/readMzXmlData/ +readNSx: + version: 0.0.5 + title: Read 'Blackrock-Microsystems' Files ('NEV', 'NSx') + maintainer: Zhengjia Wang + description: |- + Loads 'Blackrock' neural signal + data files into the memory, provides utility tools to extract the data into + common formats such as plain-text 'tsv' and 'HDF5'. + date_publication: '2024-09-03' + bug_reports: https://github.com/dipterix/readNSx/issues + url: http://dipterix.org/readNSx/ + url_cran: https://CRAN.R-project.org/package=readNSx + url_git: '' +readobj: + version: 0.4.1 + title: Fast Reader for 'Wavefront' OBJ 3D Scene Files + maintainer: Gregory Jefferis + description: |- + Wraps 'tiny_obj_loader' C++ library for reading the 'Wavefront' OBJ + 3D file format including both mesh objects and materials files. The + resultant R objects are either structured to match the 'tiny_obj_loader' + internal data representation or in a form directly compatible with the 'rgl' + package. + date_publication: '2021-07-03' + bug_reports: https://github.com/jefferis/readobj/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readobj + url_git: https://github.com/jefferis/readobj +readODS: + version: 2.3.2 + title: Read and Write ODS Files + maintainer: Chung-hong Chan + description: Read ODS (OpenDocument Spreadsheet) into R as data frame. Also support + writing data frame into ODS file. + date_publication: '2025-01-13' + bug_reports: https://github.com/ropensci/readODS/issues + url: https://docs.ropensci.org/readODS/ + url_cran: https://CRAN.R-project.org/package=readODS + url_git: https://github.com/ropensci/readODS +readOffice: + version: 0.2.2 + title: Read Text Out of Modern Office Files + maintainer: Mark Ewing + description: |- + Reads in text from 'unstructured' modern Microsoft Office files (XML based files) such as Word and PowerPoint. + This does not read in structured data (from Excel or Access) as there are many other great packages to that do so already. + date_publication: '2017-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=readOffice + url_git: '' +readr: + version: 2.1.5 + title: Read Rectangular Text Data + maintainer: Jennifer Bryan + description: |- + The goal of 'readr' is to provide a fast and friendly way to + read rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed + to flexibly parse many types of data found in the wild, while still + cleanly failing when data unexpectedly changes. + date_publication: '2024-01-10' + bug_reports: https://github.com/tidyverse/readr/issues + url: https://readr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=readr + url_git: https://github.com/tidyverse/readr +readrba: + version: 0.1.11 + title: Download and Tidy Data from the Reserve Bank of Australia + maintainer: Matt Cowgill + description: |- + Download up-to-date data from the Reserve Bank of Australia + in a tidy data frame. Package includes functions to download current and + historical statistical tables + () and forecasts + (). Data + includes a broad range of Australian macroeconomic and financial time + series. + date_publication: '2024-09-27' + bug_reports: https://github.com/MattCowgill/readrba/issues + url: https://mattcowgill.github.io/readrba/index.html + url_cran: https://CRAN.R-project.org/package=readrba + url_git: '' +readroper: + version: 0.9.3 + title: Simply Read ASCII Single and Multicard Polling Datasets + maintainer: Sam Petulla + description: A convenient way to read fixed-width ASCII polling datasets from providers + like the Roper Center . + date_publication: '2020-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=readroper + url_git: '' +readsdmx: + version: 0.3.1 + title: Read SDMX-XML Data + maintainer: Matthew de Queljoe + description: |- + Read Statistical Data and Metadata Exchange (SDMX) XML data. + This the main transmission format used in official statistics. Data can be imported from + local SDMX-ML files or a SDMX web-service and will be read in 'as is' into a dataframe object. + The 'RapidXML' C++ library is used to parse the XML data. + date_publication: '2023-09-02' + bug_reports: https://github.com/mdequeljoe/readsdmx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readsdmx + url_git: https://github.com/mdequeljoe/readsdmx +readsdr: + version: 0.3.0 + title: Translate Models from System Dynamics Software into 'R' + maintainer: Jair Andrade + description: |- + The goal of 'readsdr' is to bridge the design capabilities from + specialised System Dynamics software with the powerful numerical tools + offered by 'R' libraries. The package accomplishes this goal by parsing + 'XMILE' files ('Vensim' and 'Stella') models into 'R' objects to construct + networks (graph theory); 'ODE' functions for 'Stan'; and inputs to simulate + via 'deSolve' as described in Duggan (2016) . + date_publication: '2024-04-05' + bug_reports: https://github.com/jandraor/readsdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readsdr + url_git: '' +readsparse: + version: 0.1.5-8 + title: |- + Read and Write Sparse Matrices in 'SVMLight' and 'LibSVM' + Formats + maintainer: David Cortes + description: |- + Read and write labelled sparse matrices in text format as used by + software such as 'SVMLight', 'LibSVM', 'ThunderSVM', 'LibFM', 'xLearn', 'XGBoost', 'LightGBM', + and others. Supports labelled data for regression, classification (binary, multi-class, multi-label), + and ranking (with 'qid' field), and can handle header metadata and comments in files. + date_publication: '2025-02-17' + bug_reports: https://github.com/david-cortes/readsparse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readsparse + url_git: https://github.com/david-cortes/readsparse +readstata13: + version: 0.10.1 + title: Import 'Stata' Data Files + maintainer: Sebastian Jeworutzki + description: Function to read and write the 'Stata' file format. + date_publication: '2023-02-21' + bug_reports: https://github.com/sjewo/readstata13/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readstata13 + url_git: https://github.com/sjewo/readstata13 +readtext: + version: '0.91' + title: Import and Handling for Plain and Formatted Text Files + maintainer: Kenneth Benoit + description: |- + Functions for importing and handling text files and formatted text + files with additional meta-data, such including '.csv', '.tab', '.json', '.xml', + '.html', '.pdf', '.doc', '.docx', '.rtf', '.xls', '.xlsx', and others. + date_publication: '2024-02-23' + bug_reports: https://github.com/quanteda/readtext/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readtext + url_git: https://github.com/quanteda/readtext +readtextgrid: + version: 0.1.2 + title: Read in a 'Praat' 'TextGrid' File + maintainer: Tristan Mahr + description: |- + 'Praat' is a widely + used tool for manipulating, annotating and analyzing speech and + acoustic data. It stores annotation data in a format called a + 'TextGrid'. This package provides a way to read these + files into R. + date_publication: '2024-03-07' + bug_reports: https://github.com/tjmahr/readtextgrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=readtextgrid + url_git: https://github.com/tjmahr/readtextgrid +readxl: + version: 1.4.4 + title: Read Excel Files + maintainer: Jennifer Bryan + description: |- + Import excel files into R. Supports '.xls' via the embedded + 'libxls' C library and '.xlsx' via + the embedded 'RapidXML' C++ library . + Works on Windows, Mac and Linux without external dependencies. + date_publication: '2025-02-27' + bug_reports: https://github.com/tidyverse/readxl/issues + url: https://readxl.tidyverse.org + url_cran: https://CRAN.R-project.org/package=readxl + url_git: https://github.com/tidyverse/readxl +ready4: + version: 0.1.18 + title: Develop and Use Modular Health Economic Models + maintainer: Matthew Hamilton + description: |- + A template model module, tools to help find model modules + derived from this template and a programming syntax to use these + modules in health economic analyses. These elements are the + foundation for a prototype software framework for developing living + and transferable models and using those models in reproducible health + economic analyses. The software framework is extended by other R + libraries. For detailed documentation about the framework and how to + use it visit . For a background to the + methodological issues that the framework is attempting to help solve, + see Hamilton et al. (2024) . + date_publication: '2024-09-30' + bug_reports: '' + url: https://ready4-dev.github.io/ready4/ + url_cran: https://CRAN.R-project.org/package=ready4 + url_git: https://github.com/ready4-dev/ready4 +realtest: + version: 0.2.3 + title: 'Where Expectations Meet Reality: Realistic Unit Testing' + maintainer: Marek Gagolewski + description: |2- + + A framework for unit testing for realistic minimalists, + where we distinguish between expected, acceptable, current, fallback, + ideal, or regressive behaviour. It can also be used for monitoring + third-party software projects for changes. + date_publication: '2023-05-16' + bug_reports: https://github.com/gagolews/realtest/issues + url: https://realtest.gagolewski.com + url_cran: https://CRAN.R-project.org/package=realtest + url_git: https://github.com/gagolews/realtest +realTimeloads: + version: 1.0.0 + title: |- + Analyte Flux and Load from Estimates of Concentration and + Discharge + maintainer: Daniel Livsey + description: Flux (mass per unit time) and Load (mass) are computed from timeseries + estimates of analyte concentration and discharge. Concentration timeseries are + computed from regression between surrogate and user-provided analyte. Uncertainty + in calculations is estimated using bootstrap resampling. Code for the processing + of acoustic backscatter from horizontally profiling acoustic Doppler current profilers + is provided. All methods detailed in Livsey et al (2020) , + Livsey et al (2023) , and references therein. + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=realTimeloads + url_git: '' +RealVAMS: + version: 0.4-6 + title: Multivariate VAM Fitting + maintainer: Andrew Karl + description: Fits a multivariate value-added model (VAM), see Broatch, Green, and + Karl (2018) and Broatch and Lohr (2012) , + with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood + approach, Wolfinger (1993) , is used for the estimation + of this joint generalized linear mixed model. The inner loop of the pseudo-likelihood + routine (estimation of a linear mixed model) occurs in the framework of the EM + algorithm presented by Karl, Yang, and Lohr (2013) . + This material is based upon work supported by the National Science Foundation + under grants DRL-1336027 and DRL-1336265. + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RealVAMS + url_git: '' +ream: + version: 1.0-5 + title: |- + Density, Distribution, and Sampling Functions for Evidence + Accumulation Models + maintainer: Raphael Hartmann + description: |- + Calculate the probability density functions (PDFs) for two threshold evidence + accumulation models (EAMs). These are defined using the following Stochastic + Differential Equation (SDE), dx(t) = v(x(t),t)*dt+D(x(t),t)*dW, where x(t) is + the accumulated evidence at time t, v(x(t),t) is the drift rate, D(x(t),t) is + the noise scale, and W is the standard Wiener process. The boundary conditions + of this process are the upper and lower decision thresholds, represented by b_u(t) + and b_l(t), respectively. Upper threshold b_u(t) > 0, while lower threshold b_l(t) < 0. + The initial condition of this process x(0) = z where b_l(t) < z < b_u(t). We + represent this as the relative start point w = z/(b_u(0)-b_l(0)), defined as + a ratio of the initial threshold location. This package generates the PDF using + the same approach as the 'python' package it is based upon, 'PyBEAM' by Murrow and Holmes + (2023) . First, it converts the SDE model into the + forwards Fokker-Planck equation dp(x,t)/dt = d(v(x,t)*p(x,t))/dt-0.5*d^2(D(x,t)^2*p(x,t))/dx^2, + then solves this equation using the Crank-Nicolson method to determine p(x,t). Finally, + it calculates the flux at the decision thresholds, f_i(t) = 0.5*d(D(x,t)^2*p(x,t))/dx + evaluated at x = b_i(t), where i is the relevant decision threshold, either upper (i = u) + or lower (i = l). The flux at each thresholds f_i(t) is the PDF for each threshold, + specifically its PDF. We discuss further details of this approach in this package + and 'PyBEAM' publications. Additionally, one can calculate the cumulative distribution + functions of and sampling from the EAMs. + date_publication: '2024-09-26' + bug_reports: https://github.com/RaphaelHartmann/ream/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ream + url_git: https://github.com/RaphaelHartmann/ream +reappraised: + version: 0.1.1 + title: |- + Statistical Tools for Assessing Publication Integrity of Groups + of Trials + maintainer: Mark Bolland + description: |- + Takes user-provided baseline data from groups of randomised controlled data and + assesses whether the observed distribution of baseline p-values, numbers of participants + in each group, or categorical variables are consistent with the expected distribution, as + an aid to the assessment of integrity concerns in published randomised controlled trials. + References (citations in PubMed format in details of each function): + Bolland MJ, Avenell A, Gamble GD, Grey A. (2016) . + Bolland MJ, Gamble GD, Avenell A, Grey A, Lumley T. (2019) + . + Bolland MJ, Gamble GD, Avenell A, Grey A. (2019) . + Bolland MJ, Gamble GD, Grey A, Avenell A. (2020) . + Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2021) + . + Bolland MJ, Gamble GD, Avenell A, Grey A. (2021) . + Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2023) + . + Carlisle JB, Loadsman JA. (2017) . + Carlisle JB. (2017) . + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reappraised + url_git: '' +Rearrangement: + version: '2.1' + title: |- + Monotonize Point and Interval Functional Estimates by + Rearrangement + maintainer: Ivan Fernandez-Val + description: |- + The rearrangement operator (Hardy, + Littlewood, and Polya 1952) for univariate, bivariate, and + trivariate point estimates of monotonic functions. The package + additionally provides a function that creates simultaneous + confidence intervals for univariate functions and applies the + rearrangement operator to these confidence intervals. + date_publication: '2016-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rearrangement + url_git: '' +rearrr: + version: 0.3.4 + title: Rearranging Data + maintainer: Ludvig Renbo Olsen + description: |- + Arrange data by a set of methods. Use rearrangers to reorder + data points and mutators to change their values. From basic utilities, + to centering the greatest value, to swirling in 3-dimensional space, + 'rearrr' enables creativity when plotting and experimenting with data. + date_publication: '2024-02-07' + bug_reports: https://github.com/ludvigolsen/rearrr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rearrr + url_git: https://github.com/ludvigolsen/rearrr +reasonabletools: + version: '0.1' + title: Clean Water Quality Data for NPDES Reasonable Potential Analyses + maintainer: Matthew Reusswig + description: Functions for cleaning and summarising water quality data for use in + National Pollutant Discharge Elimination Service (NPDES) permit reasonable potential + analyses and water quality-based effluent limitation calculations. Procedures + are based on those contained in the "Technical Support Document for Water Quality-based + Toxics Control", United States Environmental Protection Agency (1991). + date_publication: '2020-11-05' + bug_reports: https://github.com/mattreusswig/reasonabletools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reasonabletools + url_git: https://github.com/mattreusswig/reasonabletools +REAT: + version: 3.0.3 + title: Regional Economic Analysis Toolbox + maintainer: Thomas Wieland + description: Collection of models and analysis methods used in regional and urban + economics and (quantitative) economic geography, e.g. measures of inequality, + regional disparities and convergence, regional specialization as well as accessibility + and spatial interaction models. + date_publication: '2021-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REAT + url_git: '' +REBayes: + version: '2.56' + title: Empirical Bayes Estimation and Inference + maintainer: Roger Koenker + description: |- + Kiefer-Wolfowitz maximum likelihood estimation for mixture models + and some other density estimation and regression methods based on convex + optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical + Bayes Mixture Methods, Journal of Statistical Software, 82, 1--26, + . + date_publication: '2024-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REBayes + url_git: '' +rebib: + version: 0.5.0 + title: Convert and Aggregate Bibliographies + maintainer: Abhishek Ulayil + description: |- + Authors working with 'LaTeX' articles use the built-in bibliography + options and 'BibTeX' files. While this might work with 'LaTeX', it does not + function well with Web articles. As a way out, 'rebib' offers tools to + convert and combine bibliographies from both sources. + date_publication: '2024-10-15' + bug_reports: https://github.com/Abhi-1U/rebib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rebib + url_git: https://github.com/Abhi-1U/rebib +rebird: + version: 1.3.0 + title: R Client for the eBird Database of Bird Observations + maintainer: Sebastian Pardo + description: |- + A programmatic client for the eBird database + (), including functions for searching for bird + observations by geographic location (latitude, longitude), eBird + hotspots, location identifiers, by notable sightings, by region, and by + taxonomic name. + date_publication: '2021-09-20' + bug_reports: https://github.com/ropensci/rebird/issues + url: https://docs.ropensci.org/rebird/ + url_cran: https://CRAN.R-project.org/package=rebird + url_git: https://github.com/ropensci/rebird +rebmix: + version: 2.16.0 + title: Finite Mixture Modeling, Clustering & Classification + maintainer: Marko Nagode + description: Random univariate and multivariate finite mixture model generation, + estimation, clustering, latent class analysis and classification. Variables can + be continuous, discrete, independent or dependent and may follow normal, lognormal, + Weibull, gamma, Gumbel, binomial, Poisson, Dirac, uniform or circular von Mises + parametric families. + date_publication: '2024-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rebmix + url_git: '' +rebus: + version: 0.1-3 + title: Build Regular Expressions in a Human Readable Way + maintainer: Richard Cotton + description: |- + Build regular expressions piece by piece using human readable code. + This package is designed for interactive use. For package development, use + the rebus.* dependencies. + date_publication: '2017-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rebus + url_git: '' +rebus.base: + version: 0.0-3 + title: Core Functionality for the 'rebus' Package + maintainer: Richard Cotton + description: |- + Build regular expressions piece by piece using human readable code. + This package contains core functionality, and is primarily intended to be + used by package developers. + date_publication: '2017-04-25' + bug_reports: https://github.com/richierocks/rebus.base/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rebus.base + url_git: https://github.com/richierocks/rebus.base +rebus.datetimes: + version: 0.0-2 + title: Date and Time Extensions for the 'rebus' Package + maintainer: Richard Cotton + description: |- + Build regular expressions piece by piece using human readable code. + This package contains date and time functionality, and is primarily intended + to be used by package developers. + date_publication: '2022-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rebus.datetimes + url_git: '' +rebus.numbers: + version: 0.0-1 + title: Numeric Extensions for the 'rebus' Package + maintainer: Richard Cotton + description: |- + Build regular expressions piece by piece using human readable code. + This package contains number-related functionality, and is primarily intended + to be used by package developers. + date_publication: '2015-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rebus.numbers + url_git: '' +rebus.unicode: + version: 0.0-2 + title: Unicode Extensions for the 'rebus' Package + maintainer: Richard Cotton + description: |- + Build regular expressions piece by piece using human readable code. + This package contains Unicode functionality, and is primarily intended to be + used by package developers. + date_publication: '2017-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rebus.unicode + url_git: '' +RECA: + version: '1.7' + title: |- + Relevant Component Analysis for Supervised Distance Metric + Learning + maintainer: Nan Xiao + description: |- + Relevant Component Analysis (RCA) tries to find a linear + transformation of the feature space such that the effect of irrelevant + variability is reduced in the transformed space. + date_publication: '2019-05-17' + bug_reports: https://github.com/nanxstats/RECA/issues + url: https://nanx.me/RECA/ + url_cran: https://CRAN.R-project.org/package=RECA + url_git: https://github.com/nanxstats/RECA +recalibratiNN: + version: 0.3.2 + title: Quantile Recalibration for Regression Models + maintainer: Carolina Musso + description: 'Enables the diagnostics and enhancement of regression model calibration.It + offers both global and local visualization tools for calibration diagnostics and + provides one recalibration method: Torres R, Nott DJ, Sisson SA, Rodrigues T, + Reis JG, Rodrigues GS (2024) . The method leverages + on Probabilistic Integral Transform (PIT) values to both evaluate and perform + the calibration of statistical models. For a more detailed description of the + package, please refer to the bachelor''s thesis available bellow.' + date_publication: '2025-01-19' + bug_reports: https://github.com/cmusso86/recalibratiNN/issues + url: https://bdm.unb.br/handle/10483/38504 + url_cran: https://CRAN.R-project.org/package=recalibratiNN + url_git: https://github.com/cmusso86/recalibratiNN +recapr: + version: 0.4.4 + title: Two Event Mark-Recapture Experiment + maintainer: Matt Tyers + description: |- + Tools are provided for estimating, testing, and simulating + abundance in a two-event (Petersen) mark-recapture experiment. Functions are + given to calculate the Petersen, Chapman, and Bailey estimators and associated + variances. However, the principal utility is a set of functions to simulate + random draws from these estimators, and use these to conduct hypothesis + tests and power calculations. Additionally, a set of functions are provided + for generating confidence intervals via bootstrapping. Functions are also + provided to test abundance estimator consistency under complete or partial + stratification, and to calculate stratified or partially stratified estimators. + Functions are also provided to calculate recommended sample sizes. + Referenced methods can be found in Arnason et al. (1996) , + Bailey (1951) , + Bailey (1952) , + Chapman (1951) NAID:20001644490, + Cohen (1988) ISBN:0-12-179060-6, + Darroch (1961) , and + Robson and Regier (1964) . + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recapr + url_git: '' +RecAssoRules: + version: '1.0' + title: |- + Recursive Mining for Frequent Pattern and Confident Association + Rules + maintainer: Louis Raimbault + description: Provides functions allowing the user to recursively extract frequent + patterns and confident rules according to indicators of minimal support and minimal + confidence. These functions are described in "Recursive Association Rule Mining" + Abdelkader Mokkadem, Mariane Pelletier, Louis Raimbault (2020) . + date_publication: '2020-12-04' + bug_reports: https://github.com/LouisRaimbault/RecAssoRules-R + url: '' + url_cran: https://CRAN.R-project.org/package=RecAssoRules + url_git: https://github.com/LouisRaimbault/RecAssoRules-R +receptiviti: + version: 0.1.8 + title: Text Analysis Through the 'Receptiviti' API + maintainer: Kent English + description: |- + Send text to the API to be scored + by all available frameworks. + date_publication: '2024-03-29' + bug_reports: https://github.com/Receptiviti/receptiviti-r/issues + url: https://receptiviti.github.io/receptiviti-r/ + url_cran: https://CRAN.R-project.org/package=receptiviti + url_git: https://github.com/Receptiviti/receptiviti-r +recexcavAAR: + version: 0.3.0 + title: 3D Reconstruction of Archaeological Excavations + maintainer: Clemens Schmid + description: A toolset for 3D reconstruction and analysis of excavations. It provides + methods to reconstruct natural and artificial surfaces based on field measurements. + This allows to spatially contextualize documented subunits and features. Intended + to be part of a 3D visualization workflow. + date_publication: '2017-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recexcavAAR + url_git: https://github.com/ISAAKiel/recexcavAAR +recforest: + version: 1.0.0 + title: Random Survival Forest for Recurrent Events + maintainer: Juliette Murris + description: Analyze recurrent events with right-censored data and the potential + presence of a terminal event (that prevents further occurrences, like death). + 'recofest' extends the random survival forest algorithm, adapting splitting rules + and node estimators to handle complexities of recurrent events. The methodology + is fully described in Murris, J., Bouaziz, O., Jakubczak, M., Katsahian, S., & + Lavenu, A. (2024) (). + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recforest + url_git: '' +rechaRge: + version: 1.0.0 + title: HydroBudget – Groundwater Recharge Model + maintainer: Yannick Marcon + description: |- + HydroBudget is a spatially distributed + groundwater recharge model that computes a superficial water + budget on grid cells with outputs aggregated into monthly time steps. + It was developed as an accessible and computationally affordable model + to simulate groundwater recharge over large areas (thousands of km2, + regional-scale watersheds) and for long time periods (decades), in cold + and humid climates. Model algorithms are based on the research of + Dubois, E. et al. (2021a) and + Dubois, E. et al. (2021b) . + date_publication: '2024-05-14' + bug_reports: https://github.com/gwrecharge/rechaRge/issues/ + url: https://gwrecharge.github.io/rechaRge-book/ + url_cran: https://CRAN.R-project.org/package=rechaRge + url_git: https://github.com/gwrecharge/rechaRge/ +rechonest: + version: '1.2' + title: R Interface to Echo Nest API + maintainer: Mukul Chaware + description: |- + The 'Echo nest' is the industry's leading + music intelligence company, providing developer with deepest understanding of + music content and music fans. This package can be used to access artist's data + including songs, blogs, news, reviews etc. Song's data including audio summary, + style, danceability, tempo etc can also be accessed. + date_publication: '2016-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rechonest + url_git: https://github.com/mukul13/rechonest +recipes: + version: 1.1.1 + title: Preprocessing and Feature Engineering Steps for Modeling + maintainer: Max Kuhn + description: |- + A recipe prepares your data for modeling. We provide an + extensible framework for pipeable sequences of feature engineering + steps provides preprocessing tools to be applied to data. Statistical + parameters for the steps can be estimated from an initial data set and + then applied to other data sets. The resulting processed output can + then be used as inputs for statistical or machine learning models. + date_publication: '2025-02-12' + bug_reports: https://github.com/tidymodels/recipes/issues + url: https://recipes.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=recipes + url_git: https://github.com/tidymodels/recipes +reclin2: + version: 0.5.0 + title: Record Linkage Toolkit + maintainer: Jan van der Laan + description: |- + Functions to assist in performing probabilistic record linkage and + deduplication: generating pairs, comparing records, em-algorithm for + estimating m- and u-probabilities + (I. Fellegi & A. Sunter (1969) , + T.N. Herzog, F.J. Scheuren, & W.E. Winkler (2007), + "Data Quality and Record Linkage Techniques", ISBN:978-0-387-69502-0), + forcing one-to-one matching. Can also be + used for pre- and post-processing for machine learning methods for record + linkage. Focus is on memory, CPU performance and flexibility. + date_publication: '2024-02-09' + bug_reports: https://github.com/djvanderlaan/reclin2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reclin2 + url_git: https://github.com/djvanderlaan/reclin2 +recluster: + version: '2.9' + title: Ordination Methods for the Analysis of Beta-Diversity Indices + maintainer: Leonardo Dapporto + description: "The analysis of different aspects of biodiversity requires specific + algorithms.\nFor example, in regionalisation analyses, the high frequency of ties + and zero values in\ndissimilarity matrices produced by Beta-diversity turnover + produces hierarchical\ncluster dendrograms whose topology and bootstrap supports + are affected by the order of\nrows in the original matrix. Moreover, visualisation + of biogeographical regionalisation\ncan be facilitated by a combination of hierarchical + clustering and multi-dimensional\nscaling. The recluster package provides robust + techniques to visualise and analyse\npattern of biodiversity and to improve occurrence + data for cryptic taxa.\nOther functions \trelated to recluster (e.g. the biodecrypt + family) are currently\navailable in GitHub at ." + date_publication: '2020-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recluster + url_git: https://github.com/leondap/recluster +recmap: + version: 1.0.17 + title: Compute the Rectangular Statistical Cartogram + maintainer: Christian Panse + description: |- + Implements the RecMap MP2 construction heuristic + . + This algorithm draws maps according to a given statistical + value, e.g., election results, population, or epidemiological data. + The basic idea of the RecMap algorithm is that each map region, + e.g., different countries, is represented by a rectangle. + The area of each rectangle represents the statistical value given + as input (maintain zero cartographic error). + C++ is used to implement the computationally intensive tasks. + The vignette included in this package provides documentation + about the usage of the recmap algorithm. + date_publication: '2023-09-23' + bug_reports: https://github.com/cpanse/recmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=recmap + url_git: '' +recmetrics: + version: 0.1.0 + title: Psychometric Evaluation Using Relative Excess Correlations + maintainer: R. Noah Padgett + description: Modern results of psychometric theory are implemented to provide users + with a way of evaluating the internal structure of a set of items guided by theory. + These methods are discussed in detail in VanderWeele and Padgett (2024) . + The relative excess correlation matrices will, generally, have numerous negative + entries even if all of the raw correlations between each pair of indicators are + positive. The positive deviations of the relative excess correlation matrix entries + help identify clusters of indicators that are more strongly related to one another, + providing insights somewhat analogous to factor analysis, but without the need + for rotations or decisions concerning the number of factors. A goal similar to + exploratory/confirmatory factor analysis, but 'recmetrics' uses novel methods + that do not rely on assumptions of latent variables or latent variable structures. + date_publication: '2024-02-27' + bug_reports: '' + url: https://noah-padgett.github.io/recmetrics/ + url_cran: https://CRAN.R-project.org/package=recmetrics + url_git: '' +Recocrop: + version: 0.4-1 + title: Estimating Environmental Suitability for Plants + maintainer: Robert J. Hijmans + description: 'The ecocrop model estimates environmental suitability for plants using + a limiting factor approach for plant growth following Hackett (1991) . + The implementation in this package is fast and flexible: it allows for the use + of any (environmental) predictor variable. Predictors can be either static (for + example, soil pH) or dynamic (for example, monthly precipitation).' + date_publication: '2022-10-24' + bug_reports: https://github.com/cropmodels/Recocrop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Recocrop + url_git: https://github.com/cropmodels/Recocrop/ +recodeflow: + version: 0.1.0 + title: Interface Functions for PMML Creation, and Data Recoding + maintainer: Rostyslav Vyuha + description: Contains functions to interface with variables and variable details + sheets, including recoding variables and converting them to PMML. + date_publication: '2021-06-09' + bug_reports: https://github.com/Big-Life-Lab/recodeflow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=recodeflow + url_git: https://github.com/Big-Life-Lab/recodeflow +recogito: + version: 0.2.1 + title: Interactive Annotation of Text and Images + maintainer: Jan Wijffels + description: |- + Annotate text with entities and the relations between them. Annotate areas of interest in images with your labels. + Providing 'htmlwidgets' bindings to the 'recogito' and 'annotorious' libraries. + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recogito + url_git: https://github.com/DIGI-VUB/recogito +recolorize: + version: 0.1.0 + title: Color-Based Image Segmentation + maintainer: Hannah Weller + description: |- + Automatic, semi-automatic, and manual functions for + generating color maps from images. The idea is to simplify + the colors of an image according to a metric that is useful for + the user, using deterministic methods whenever possible. + Many images will be clustered well using the out-of-the-box + functions, but the package also includes a toolbox of functions + for making manual adjustments (layer merging/isolation, blurring, + fitting to provided color clusters or those from another image, etc). + Also includes export methods for other color/pattern analysis packages + (pavo, patternize, colordistance). + date_publication: '2021-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recolorize + url_git: '' +recombinator: + version: 1.0.1 + title: Recombinate Nested Lists to Dataframes + maintainer: Peter Hurford + description: Turns nested lists into data.frames in an orderly manner. + date_publication: '2019-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recombinator + url_git: '' +recometrics: + version: 0.1.6-3 + title: Evaluation Metrics for Implicit-Feedback Recommender Systems + maintainer: David Cortes + description: |- + Calculates evaluation metrics for implicit-feedback recommender systems + that are based on low-rank matrix factorization models, given the fitted model + matrices and data, thus allowing to compare models from a variety of libraries. + Metrics include P@K (precision-at-k, for top-K recommendations), R@K (recall at k), + AP@K (average precision at k), NDCG@K (normalized discounted cumulative gain at k), + Hit@K (from which the 'Hit Rate' is calculated), RR@K (reciprocal rank at k, from + which the 'MRR' or 'mean reciprocal rank' is calculated), ROC-AUC (area under the + receiver-operating characteristic curve), and PR-AUC (area under the + precision-recall curve). + These are calculated on a per-user basis according to the ranking of items induced + by the model, using efficient multi-threaded routines. Also provides functions + for creating train-test splits for model fitting and evaluation. + date_publication: '2023-02-19' + bug_reports: https://github.com/david-cortes/recometrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=recometrics + url_git: https://github.com/david-cortes/recometrics +recommenderlab: + version: 1.0.6 + title: Lab for Developing and Testing Recommender Algorithms + maintainer: Michael Hahsler + description: |- + Provides a research infrastructure to develop and evaluate + collaborative filtering recommender algorithms. This includes a sparse + representation for user-item matrices, many popular algorithms, top-N recommendations, + and cross-validation. Hahsler (2022) . + date_publication: '2023-09-20' + bug_reports: https://github.com/mhahsler/recommenderlab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=recommenderlab + url_git: https://github.com/mhahsler/recommenderlab +recommenderlabBX: + version: 0.2-0 + title: Book-Crossing Dataset (BX) for 'recommenderlab' + maintainer: Michael Hahsler + description: Provides the Book-Crossing Dataset for the package recommenderlab. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recommenderlabBX + url_git: https://github.com/mhahsler/recommenderlabBX +recommenderlabJester: + version: 0.2-0 + title: Jester Dataset for 'recommenderlab' + maintainer: Michael Hahsler + description: Provides the Jester Dataset for package recommenderlab. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recommenderlabJester + url_git: https://github.com/mhahsler/recommenderlabJester +Recon: + version: 0.3.0.0 + title: Computational Tools for Economics + maintainer: Pedro Cavalcante Oliveira + description: Implements solutions to canonical models of Economics such as Monopoly + Profit Maximization, Cournot's Duopoly, Solow (1956, ) growth + model and Mankiw, Romer and Weil (1992, ) growth model. + date_publication: '2019-07-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Recon + url_git: '' +reconstructKM: + version: 0.3.0 + title: Reconstruct Individual-Level Data from Published KM Plots + maintainer: Ryan Sun + description: Functions for reconstructing individual-level data (time, status, arm) + from Kaplan-MEIER curves published in academic journals (e.g. NEJM, JCO, JAMA). + The individual-level data can be used for re-analysis, meta-analysis, methodology + development, etc. This package was used to generate the data for commentary such + as Sun, Rich, & Wei (2018) . Please see the vignette + for a quickstart guide. + date_publication: '2020-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reconstructKM + url_git: '' +reconstructr: + version: 2.0.4 + title: Session Reconstruction and Analysis + maintainer: Os Keyes + description: |- + Functions to reconstruct sessions from web log or other user trace data + and calculate various metrics around them, producing tabular, + output that is compatible with 'dplyr' or 'data.table' centered processes. + date_publication: '2022-02-18' + bug_reports: https://github.com/Ironholds/reconstructr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reconstructr + url_git: https://github.com/Ironholds/reconstructr +recorder: + version: 0.8.2 + title: Toolkit to Validate New Data for a Predictive Model + maintainer: Lars Kjeldgaard + description: |- + A lightweight toolkit to validate new observations when computing + their predictions with a predictive model. The validation process + consists of two steps: (1) record relevant statistics and meta data of the + variables in the original training data for the predictive model and + (2) use these data to run a set of basic validation tests on the new set of + observations. + date_publication: '2019-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recorder + url_git: https://github.com/smaakage85/recorder +RecordLinkage: + version: 0.4-12.4 + title: Record Linkage Functions for Linking and Deduplicating Data Sets + maintainer: Murat Sariyar + description: |- + Provides functions for linking and deduplicating data sets. + Methods based on a stochastic approach are implemented as well as + classification algorithms from the machine learning domain. For details, + see our paper "The RecordLinkage Package: Detecting Errors in Data" + Sariyar M / Borg A (2010) . + date_publication: '2022-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RecordLinkage + url_git: '' +Records: + version: '1.0' + title: Record Values and Record Times + maintainer: Magdalena Chrapek + description: |- + Functions for generating k-record values and k-record + times + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Records + url_git: '' +RecordTest: + version: 2.2.0 + title: Inference Tools in Time Series Based on Record Statistics + maintainer: Jorge Castillo-Mateo + description: |- + Statistical tools based on the probabilistic properties of the + record occurrence in a sequence of independent and identically distributed + continuous random variables. In particular, tools to prepare a time series + as well as distribution-free trend and change-point tests and graphical + tools to study the record occurrence. Details about the implemented tools + can be found in Castillo-Mateo et al. (2023a) + and Castillo-Mateo et al. (2023b) . + date_publication: '2023-08-07' + bug_reports: https://github.com/JorgeCastilloMateo/RecordTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RecordTest + url_git: https://github.com/JorgeCastilloMateo/RecordTest +recosystem: + version: 0.5.1 + title: Recommender System using Matrix Factorization + maintainer: Yixuan Qiu + description: |- + R wrapper of the 'libmf' library + for recommender + system using matrix factorization. It is typically used to + approximate an incomplete matrix using the product of two + matrices in a latent space. Other common names for this task + include "collaborative filtering", "matrix completion", + "matrix recovery", etc. High performance multi-core parallel + computing is supported in this package. + date_publication: '2023-05-05' + bug_reports: https://github.com/yixuan/recosystem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=recosystem + url_git: https://github.com/yixuan/recosystem +rectpacker: + version: 1.0.0 + title: Rectangle Packing + maintainer: Mike Cheng + description: |- + Rectangle packing is a packing problem where rectangles are placed + into a larger rectangular region (without overlapping) in order to maximise + the use space. Rectangles are packed using the skyline heuristic as discussed + in Lijun et al (2011) 'A Skyline-Based Heuristic for the 2D Rectangular Strip + Packing Problem' . A function is also + included for determining a good small-sized box for containing a given + set of rectangles. + date_publication: '2024-12-05' + bug_reports: https://github.com/coolbutuseless/rectpacker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rectpacker + url_git: https://github.com/coolbutuseless/rectpacker +recurrentpseudo: + version: 1.0.0 + title: |- + Creates Pseudo-Observations and Analysis for Recurrent Event + Data + maintainer: Julie Kjærulff Furberg + description: |- + Computation of one-, two- and three-dimensional + pseudo-observations based on recurrent events and terminal events. + Generalised linear models are fitted using generalised estimating + equations. Technical details on the bivariate procedure can be found + in "Bivariate pseudo-observations for recurrent event analysis with + terminal events" (Furberg et al., 2021) . + date_publication: '2022-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recurrentpseudo + url_git: https://github.com/JulieKFurberg/recurrentpseudo +recurse: + version: 1.4.0 + title: Computes Revisitation Metrics for Trajectory Data + maintainer: Chloe Bracis + description: Computes revisitation metrics for trajectory data, such as the number + of revisitations for each location as well as the time spent for that visit and + the time since the previous visit. Also includes functions to plot data. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=recurse + url_git: '' +red: + version: 1.6.1 + title: IUCN Redlisting Tools + maintainer: Vasco V. Branco + description: Includes algorithms to facilitate the assessment of extinction risk + of species according to the IUCN (International Union for Conservation of Nature, + see for more information) red list criteria. + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=red + url_git: '' +reda: + version: 0.5.4 + title: Recurrent Event Data Analysis + maintainer: Wenjie Wang + description: |- + Contains implementations of recurrent event data analysis routines + including (1) survival and recurrent event data simulation from + stochastic process point of view by the thinning method + proposed by Lewis and Shedler (1979) + and the inversion method introduced in Cinlar (1975, ISBN:978-0486497976), + (2) the mean cumulative function (MCF) estimation by the + Nelson-Aalen estimator of the cumulative hazard rate function, + (3) two-sample recurrent event responses comparison with the pseudo-score + tests proposed by Lawless and Nadeau (1995) , + (4) gamma frailty model with spline rate function following + Fu, et al. (2016) . + date_publication: '2022-07-08' + bug_reports: https://github.com/wenjie2wang/reda/issues + url: https://wwenjie.org/reda + url_cran: https://CRAN.R-project.org/package=reda + url_git: https://github.com/wenjie2wang/reda +ReDaMoR: + version: 0.8.2 + title: Relational Data Modeler + maintainer: Patrice Godard + description: |- + The aim of this package is to manipulate relational + data models in R. + It provides functions to create, modify and export data models + in json format. + It also allows importing models created + with 'MySQL Workbench' (). + These functions are accessible through a graphical user + interface made with 'shiny'. + Constraints such as types, keys, uniqueness and mandatory fields are + automatically checked and corrected when editing a model. + Finally, real data can be confronted to a model to check their compatibility. + date_publication: '2025-02-21' + bug_reports: https://github.com/patzaw/ReDaMoR/issues + url: https://patzaw.github.io/ReDaMoR/ + url_cran: https://CRAN.R-project.org/package=ReDaMoR + url_git: https://github.com/patzaw/ReDaMoR/ +REdaS: + version: 0.9.4 + title: |- + Companion Package to the Book 'R: Einführung durch angewandte + Statistik' + maintainer: Marco Johannes Maier + description: 'Provides functions used in the ''R: Einführung durch angewandte Statistik'' + (second edition).' + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REdaS + url_git: '' +redatam: + version: 2.1.1 + title: Import 'REDATAM' Files + maintainer: Mauricio Vargas Sepulveda + description: |- + Import 'REDATAM' formats into R via the 'Open REDATAM' C++ library. + The full context of this project and details about the implementation are + available in (Open Access). + date_publication: '2025-02-20' + bug_reports: https://github.com/litalbarkai/open-redatam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=redatam + url_git: https://github.com/litalbarkai/open-redatam +redatamx: + version: 1.1.0 + title: R Interface to 'Redatam' Library + maintainer: Jaime Salvador + description: |- + Provides an API to work with 'Redatam' (see ) + databases in both formats: 'RXDB' (new format) and 'DICX' (old format) and running + 'Redatam' programs written in 'SPC' language. It's a wrapper around 'Redatam' + core and provides functions to open/close a database (redatam_open()/redatam_close()), + list entities and variables from the database (redatam_entities(), redatam_variables()) + and execute a 'SPC' program and gets the results as data frames + (redatam_query(), redatam_run()). + date_publication: '2024-12-23' + bug_reports: https://github.com/ideasybits/redatamx4r/issues + url: https://ideasybits.github.io/redatamx4r/ + url_cran: https://CRAN.R-project.org/package=redatamx + url_git: https://github.com/ideasybits/redatamx4r/ +redbookperu: + version: 0.0.3 + title: |- + Access and Analyze Data from the Red Book of Endemic Plants of + Peru + maintainer: Paul E. Santos Andrade + description: Provides access to and analysis of data from "The Red Book of Endemic + Plants of Peru" (León, B., Roque, J., Ulloa, C., Jorgensen, P.M., Pitman, N., + Cano, A. 2006) . This package offers comprehensive + taxonomic, geographic, and conservation information about Peru's endemic plant + species. It includes functions to verify species inclusion, obtain updated taxonomic + details, and explore the dataset. + date_publication: '2024-07-02' + bug_reports: https://github.com/PaulESantos/redbookperu/issues + url: https://paulesantos.github.io/redbookperu/ + url_cran: https://CRAN.R-project.org/package=redbookperu + url_git: https://github.com/PaulESantos/redbookperu +redcapAPI: + version: 2.10.0 + title: Interface to 'REDCap' + maintainer: Shawn Garbett + description: |- + Access data stored in 'REDCap' databases using the Application + Programming Interface (API). 'REDCap' (Research Electronic Data CAPture; + , Harris, et al. (2009) , + Harris, et al. (2019) ) is + a web application for building and managing online surveys and databases + developed at Vanderbilt University. The API allows users to access data + and project meta data (such as the data dictionary) from the web + programmatically. The 'redcapAPI' package facilitates the process of + accessing data with options to prepare an analysis-ready data set + consistent with the definitions in a database's data dictionary. + date_publication: '2024-10-17' + bug_reports: https://github.com/vubiostat/redcapAPI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=redcapAPI + url_git: https://github.com/vubiostat/redcapAPI +REDCapCAST: + version: 25.1.1 + title: REDCap Metadata Casting and Castellated Data Handling + maintainer: Andreas Gammelgaard Damsbo + description: |- + Casting metadata for REDCap database creation and handling of + castellated data using repeated instruments and longitudinal projects in + 'REDCap'. Keeps a focused data export approach, by allowing to only export + required data from the database. Also for casting new REDCap databases based + on datasets from other sources. + Originally forked from the R part of 'REDCapRITS' by Paul Egeler. + See . + 'REDCap' (Research Electronic Data Capture) is a secure, web-based software + platform designed to support data capture for research studies, providing + 1) an intuitive interface for validated data capture; 2) audit trails for + tracking data manipulation and export procedures; 3) automated export + procedures for seamless data downloads to common statistical packages; and + 4) procedures for data integration and interoperability with external + sources (Harris et al (2009) ; + Harris et al (2019) ). + date_publication: '2025-01-29' + bug_reports: https://github.com/agdamsbo/REDCapCAST/issues + url: https://agdamsbo.github.io/REDCapCAST/ + url_cran: https://CRAN.R-project.org/package=REDCapCAST + url_git: https://github.com/agdamsbo/REDCapCAST +REDCapDM: + version: 0.9.9 + title: '''REDCap'' Data Management' + maintainer: João Carmezim + description: REDCap Data Management - REDCapDM is an R package that allows users + to manage data exported directly from REDCap or using an API connection. This + package includes several functions designed for pre-processing data, generating + reports of queries such as outliers or missing values, and following up on the + identified queries. 'REDCap' (Research Electronic Data CAPture; ) + is a web application developed at Vanderbilt University, designed for creating + and managing online surveys and databases and the REDCap API is an interface that + allows external applications to connect to REDCap remotely, and is used to programmatically + retrieve or modify project data or settings within REDCap, such as importing or + exporting data. + date_publication: '2024-05-06' + bug_reports: https://github.com/bruigtp/REDCapDM/issues + url: https://bruigtp.github.io/REDCapDM/ + url_cran: https://CRAN.R-project.org/package=REDCapDM + url_git: '' +REDCapExporter: + version: 0.3.1 + title: Automated Construction of R Data Packages from REDCap Projects + maintainer: Peter DeWitt + description: |- + Export all data, including metadata, from a REDCap (Research + Electronic Data Capture) Project via the REDCap API + . + The exported (meta)data will be processed and formatted into a stand alone R + data package which can be installed and shared between researchers. Several + default reports are generated as vignettes in the resulting package. + date_publication: '2024-11-06' + bug_reports: '' + url: http://www.peteredewitt.com/REDCapExporter/ + url_cran: https://CRAN.R-project.org/package=REDCapExporter + url_git: https://github.com/dewittpe/REDCapExporter +REDCapR: + version: 1.4.0 + title: Interaction Between R and REDCap + maintainer: Will Beasley + description: |- + Encapsulates functions to streamline calls from R to the REDCap + API. REDCap (Research Electronic Data CAPture) is a web application for + building and managing online surveys and databases developed at Vanderbilt + University. The Application Programming Interface (API) offers an avenue + to access and modify data programmatically, improving the capacity for + literate and reproducible programming. + date_publication: '2025-01-11' + bug_reports: https://github.com/OuhscBbmc/REDCapR/issues + url: https://ouhscbbmc.github.io/REDCapR/ + url_cran: https://CRAN.R-project.org/package=REDCapR + url_git: https://github.com/OuhscBbmc/REDCapR +REDCapTidieR: + version: 1.2.1 + title: Extract 'REDCap' Databases into Tidy 'Tibble's + maintainer: Richard Hanna + description: Convert 'REDCap' exports into tidy tables for easy handling of 'REDCap' + repeat instruments and event arms. + date_publication: '2024-12-09' + bug_reports: https://github.com/CHOP-CGTInformatics/REDCapTidieR/issues + url: https://chop-cgtinformatics.github.io/REDCapTidieR/ + url_cran: https://CRAN.R-project.org/package=REDCapTidieR + url_git: https://github.com/CHOP-CGTInformatics/REDCapTidieR +redcas: + version: 0.1.1 + title: An Interface to the Computer Algebra System 'REDUCE' + maintainer: Martin Gregory + description: '''REDUCE'' is a portable general-purpose computer algebra system supporting + scalar, vector, matrix and tensor algebra, symbolic differential and integral + calculus, arbitrary precision numerical calculations and output in ''LaTeX'' format. + ''REDUCE'' is based on ''Lisp'' and is available on the two dialects ''Portable + Standard Lisp'' (''PSL'') and ''Codemist Standard Lisp'' (''CSL''). The ''redcas'' + package provides an interface for executing arbitrary ''REDUCE'' code interactively + from ''R'', returning output as character vectors. ''R'' code and ''REDUCE'' code + can be interspersed. It also provides a specialized function for calling the ''REDUCE'' + feature for solving systems of equations, returning the output as an ''R'' object + designed for the purpose. A further specialized function uses ''REDUCE'' features + to generate ''LaTeX'' output and post-processes this for direct use in ''LaTeX'' + documents, e.g. using ''Sweave''.' + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=redcas + url_git: '' +redditadsR: + version: 0.1.0 + title: Get Reddit Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from reddit Ads using + the 'Windsor.ai' API . + date_publication: '2022-10-31' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=redditadsR + url_git: '' +RedditExtractoR: + version: 3.0.9 + title: Reddit Data Extraction Toolkit + maintainer: Ivan Rivera + description: A collection of tools for extracting structured data from . + date_publication: '2023-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RedditExtractoR + url_git: '' +reddPrec: + version: 2.0.3 + title: Reconstruction of Daily Data - Precipitation + maintainer: Roberto Serrano-Notivoli + description: |- + Applies quality control to daily precipitation observations; + reconstructs the original series by estimating precipitation in missing values; and + creates gridded datasets of daily precipitation. + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reddPrec + url_git: '' +REddyProc: + version: 1.3.3 + title: Post Processing of (Half-)Hourly Eddy-Covariance Measurements + maintainer: Thomas Wutzler + description: |- + Standard and extensible Eddy-Covariance data post-processing + (Wutzler et al. (2018) ) + includes + uStar-filtering, gap-filling, and flux-partitioning. + The Eddy-Covariance (EC) micrometeorological technique quantifies continuous + exchange fluxes of gases, energy, and momentum between an ecosystem and the atmosphere. + It is important for understanding ecosystem dynamics and upscaling exchange fluxes. + (Aubinet et al. (2012) ). + This package inputs pre-processed (half-)hourly data and supports further processing. + First, a quality-check and filtering is performed based on the relationship between + measured flux and friction + velocity (uStar) to discard biased data + (Papale et al. (2006) ). + Second, gaps in the data are filled based on information from environmental conditions + (Reichstein et al. (2005) ). + Third, the net flux of carbon dioxide is partitioned + into its gross fluxes in and out of the ecosystem by night-time + based and day-time based approaches + (Lasslop et al. (2010) ). + date_publication: '2024-01-25' + bug_reports: '' + url: https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWeb + url_cran: https://CRAN.R-project.org/package=REddyProc + url_git: https://github.com/bgctw/REddyProc +REddyProcNCDF: + version: 1.1.4 + title: Reading Data from NetCDF Files for 'REddyProc' + maintainer: Thomas Wutzler + description: Extension to 'REddyProc' that allows reading data from netCDF files. + date_publication: '2018-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REddyProcNCDF + url_git: https://github.com/bgctw/REddyProcNCDF +REDI: + version: 1.0.0 + title: Robust Exponential Decreasing Index + maintainer: Alexia Grenouillat + description: |- + Implementation of the Robust Exponential Decreasing Index (REDI), + proposed in the article by Issa Moussa, Arthur Leroy et al. (2019) + . + The REDI represents a measure of cumulated workload, robust to missing data, + providing control of the decreasing influence of workload over time. + Various functions are provided to format data, compute REDI, and + visualise results in a simple and convenient way. + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REDI + url_git: '' +ReDirection: + version: 1.0.1 + title: Predict Dominant Direction of Reactions of a Biochemical Network + maintainer: Siddhartha Kundu + description: |- + Biologically relevant, yet mathematically sound constraints are used + to compute the propensity and thence infer the dominant direction of reactions + of a generic biochemical network. The reactions must be unique and their + number must exceed that of the reactants,i.e., reactions >= reactants + 2. + 'ReDirection', computes the null space of a user-defined stoichiometry + matrix. The spanning non-zero and unique reaction vectors (RVs) are + combinatorially summed to generate one or more subspaces recursively. + Every reaction is represented as a sequence of identical components + across all RVs of a particular subspace. The terms are evaluated with + (biologically relevant bounds, linear maps, tests of convergence, descriptive + statistics, vector norms) and the terms are classified into forward-, reverse- + and equivalent-subsets. Since, these are mutually exclusive the probability + of occurrence is binary (all, 1; none, 0). + The combined propensity of a reaction is the p1-norm of the + sub-propensities, i.e., sum of the products of the probability and maximum + numeric value of a subset (least upper bound, greatest lower bound). This, + if strictly positive is the probable rate constant, is used to infer dominant + direction and annotate a reaction as "Forward (f)", "Reverse (b)" or + "Equivalent (e)". + The inherent computational complexity (NP-hard) per iteration suggests + that a suitable value for the number of reactions is around 20. + Three functions comprise ReDirection. These are check_matrix() and + reaction_vector() which are internal, and calculate_reaction_vector() + which is external. + date_publication: '2021-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReDirection + url_git: '' +RedisBaseContainer: + version: 1.0.1 + title: The Container for the DockerParallel Package + maintainer: Jiefei Wang + description: |2- + + Providing the container for the DockerParallel package. + date_publication: '2021-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RedisBaseContainer + url_git: '' +Rediscover: + version: 0.3.2 + title: Identify Mutually Exclusive Mutations + maintainer: Juan A. Ferrer-Bonsoms + description: |- + An optimized method for identifying mutually + exclusive genomic events. Its main contribution is a + statistical analysis based on the Poisson-Binomial + distribution that takes into account that some samples + are more mutated than others. See [Canisius, Sander, John WM Martens, + and Lodewyk FA Wessels. (2016) "A novel independence test for + somatic alterations in cancer shows that + biology drives mutual exclusivity but chance explains + most co-occurrence." Genome biology 17.1 : 1-17. ]. + The mutations matrices are sparse matrices. The method developed takes + advantage of the advantages of this type of matrix to save + time and computing resources. + date_publication: '2023-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rediscover + url_git: '' +redist: + version: 4.2.0 + title: Simulation Methods for Legislative Redistricting + maintainer: Christopher T. Kenny + description: |- + Enables researchers to sample redistricting plans from a pre-specified + target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo + algorithms. The package allows for the implementation of various constraints in + the redistricting process such as geographic compactness and population parity + requirements. Tools for analysis such as computation of various summary statistics + and plotting functionality are also included. The package implements the SMC + algorithm of McCartan and Imai (2023) , the enumeration + algorithm of Fifield, Imai, Kawahara, and Kenny (2020) , + the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) , + the Merge-split/Recombination algorithms of Carter et al. (2019) + and DeFord et al. (2021) , and the Short-burst + optimization algorithm of Cannon et al. (2020) . + date_publication: '2024-01-13' + bug_reports: https://github.com/alarm-redist/redist/issues + url: https://alarm-redist.org/redist/ + url_cran: https://CRAN.R-project.org/package=redist + url_git: '' +redistmetrics: + version: 1.0.7 + title: Redistricting Metrics + maintainer: Christopher T. Kenny + description: |- + Reliable and flexible tools for scoring redistricting plans using + common measures and metrics. These functions provide key direct access to + tools useful for non-simulation analyses of redistricting plans, such as for + measuring compactness or partisan fairness. Tools are designed to work with + the 'redist' package seamlessly. + date_publication: '2023-12-12' + bug_reports: https://github.com/alarm-redist/redistmetrics/issues + url: http://alarm-redist.org/redistmetrics/ + url_cran: https://CRAN.R-project.org/package=redistmetrics + url_git: https::/github.com/alarm-redist/redistmetrics/ +redistverse: + version: 0.1.0 + title: Easily Install and Load Redistricting Software + maintainer: Christopher T. Kenny + description: |- + Easy installation, loading, and control of packages for redistricting + data downloading, spatial data processing, simulation, analysis, and + visualization. This package makes it easy to install and load multiple + 'redistverse' packages at once. The 'redistverse' is developed and maintained + by the Algorithm-Assisted Redistricting Methodology (ALARM) Project. + For more details see . + date_publication: '2024-06-18' + bug_reports: https://github.com/alarm-redist/redistverse/issues + url: https://alarm-redist.org/redistverse/ + url_cran: https://CRAN.R-project.org/package=redistverse + url_git: https://github.com/alarm-redist/redistverse +redland: + version: 1.0.17-18 + title: RDF Library Bindings in R + maintainer: Matthew B. Jones + description: |- + Provides methods to parse, query and serialize information + stored in the Resource Description Framework (RDF). RDF is described at . + This package supports RDF by implementing an R interface to the Redland RDF C library, + described at . In brief, RDF provides a structured graph + consisting of Statements composed of Subject, Predicate, and Object Nodes. + date_publication: '2024-02-24' + bug_reports: https://github.com/ropensci/redland-bindings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=redland + url_git: https://github.com/ropensci/redland-bindings/tree/master/R/redlandhttps://github.com/ropensci/redland-bindings/tree/master/R +redlistr: + version: 1.0.4 + title: Tools for the IUCN Red List of Ecosystems and Species + maintainer: Calvin Lee + description: |- + A toolbox created by members of the International Union for + Conservation of Nature (IUCN) Red List of Ecosystems Committee for + Scientific Standards. Primarily, it is a set of tools suitable for + calculating the metrics required for making assessments of species and + ecosystems against the IUCN Red List of Threatened Species and the + IUCN Red List of Ecosystems categories and criteria. See the IUCN + website for detailed guidelines, the criteria, publications and other + information. + date_publication: '2023-10-03' + bug_reports: https://github.com/red-list-ecosystem/redlistr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=redlistr + url_git: https://github.com/red-list-ecosystem/redlistr +rEDM: + version: 1.15.4 + title: Empirical Dynamic Modeling ('EDM') + maintainer: Joseph Park + description: An implementation of 'EDM' algorithms based on research software developed + for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented + with 'Rcpp' wrappers around the 'cppEDM' library. It implements the 'simplex' + projection method from Sugihara & May (1990) , the 'S-map' + algorithm from Sugihara (1994) , convergent cross + mapping described in Sugihara et al. (2012) , and, + 'multiview embedding' described in Ye & Sugihara (2016) . + date_publication: '2024-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rEDM + url_git: '' +Redmonder: + version: 0.2.0 + title: Microsoft(r)-Inspired Color Palettes + maintainer: Pedro Mac Dowell Innecco + description: |- + Provide color schemes for maps (and other graphics) based on the + color palettes of several Microsoft(r) products. Forked from 'RColorBrewer' v1.1-2. + date_publication: '2017-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Redmonder + url_git: '' +redoc: + version: 2.0.0.75 + title: Generates 'Redoc' Documentation from an 'OpenAPI' Specification + maintainer: Bruno Tremblay + description: |- + A collection of 'HTML', 'JavaScript', 'CSS' and fonts + assets that generate 'Redoc' documentation from an 'OpenAPI' Specification: + . + date_publication: '2023-11-17' + bug_reports: https://github.com/meztez/redoc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=redoc + url_git: https://github.com/meztez/redoc +redux: + version: 1.1.4 + title: R Bindings to 'hiredis' + maintainer: Rich FitzJohn + description: |- + A 'hiredis' wrapper that includes support for + transactions, pipelining, blocking subscription, serialisation of + all keys and values, 'Redis' error handling with R errors. + Includes an automatically generated 'R6' interface to the full + 'hiredis' API. Generated functions are faithful to the + 'hiredis' documentation while attempting to match R's argument + semantics. Serialisation must be explicitly done by the user, but + both binary and text-mode serialisation is supported. + date_publication: '2023-11-30' + bug_reports: https://github.com/richfitz/redux/issues + url: '' + url_cran: https://CRAN.R-project.org/package=redux + url_git: https://github.com/richfitz/redux +REEMtree: + version: 0.90.5 + title: |- + Regression Trees with Random Effects for Longitudinal (Panel) + Data + maintainer: Wenbo Jing + description: |- + A data mining approach for longitudinal and clustered data, + which combines the structure of mixed effects model with tree-based + estimation methods. See Sela, R.J. and Simonoff, J.S. (2012) RE-EM + trees: a data mining approach for longitudinal and clustered data + . + date_publication: '2023-10-24' + bug_reports: '' + url: http://pages.stern.nyu.edu/~jsimonof/REEMtree/ + url_cran: https://CRAN.R-project.org/package=REEMtree + url_git: '' +ref.ICAR: + version: 2.0.2 + title: |- + Objective Bayes Intrinsic Conditional Autoregressive Model for + Areal Data + maintainer: Erica M. Porter + description: |- + Implements an objective Bayes intrinsic conditional autoregressive + prior. This model provides an objective Bayesian approach for modeling spatially + correlated areal data using an intrinsic conditional autoregressive prior on a vector of + spatial random effects. + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ref.ICAR + url_git: '' +REFA: + version: 0.1.0 + title: Robust Exponential Factor Analysis + maintainer: Jiaqi Hu + description: A robust alternative to the traditional principal component estimator + is proposed within the framework of factor models, known as Robust Exponential + Factor Analysis, specifically designed for the modeling of high-dimensional datasets + with heavy-tailed distributions. The algorithm estimates the latent factors and + the loading by minimizing the exponential squared loss function. To determine + the appropriate number of factors, we propose a modified rank minimization technique, + which has been shown to significantly enhance finite-sample performance. + date_publication: '2023-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REFA + url_git: '' +RefBasedMI: + version: 0.2.0 + title: |- + Reference-Based Imputation for Longitudinal Clinical Trials with + Protocol Deviation + maintainer: Matteo Quartagno + description: |- + Imputation of missing numerical outcomes for a longitudinal trial + with protocol deviations. + The package uses distinct treatment arm-based assumptions for the unobserved data, following + the general algorithm of Carpenter, Roger, and Kenward (2013) , and the causal model + of White, Royes and Best (2020) . + Sensitivity analyses to departures from these assumptions can be done by the + Delta method of Roger. + The program uses the same algorithm as the 'mimix' 'Stata' package written by Suzie Cro, + with additional coding for the causal model and delta method. + The reference-based methods are jump to reference (J2R), + copy increments in reference (CIR), copy reference (CR), + and the causal model, all of which must specify the reference treatment arm. + Other methods are + missing at random (MAR) and the last mean carried forward (LMCF). + Individual-specific imputation methods + (and their reference groups) can be specified. + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RefBasedMI + url_git: https://github.com/UCL/RefBasedMI +refer: + version: 0.1.0 + title: Create Object References + maintainer: Christopher Mann + description: |- + Allows users to easily create references to R objects then + 'dereference' when needed or modify in place without using reference + classes, environments, or active bindings as workarounds. Users can + also create expression references that allow subsets of any object to + be referenced or expressions containing references to multiple + objects. + date_publication: '2021-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=refer + url_git: '' +referenceIntervals: + version: 1.3.1 + title: Reference Intervals + maintainer: Daniel Finnegan + description: |- + This is a collection of tools to allow the medical professional to + calculate appropriate reference ranges (intervals) with confidence intervals around + the limits for diagnostic purposes. + date_publication: '2024-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=referenceIntervals + url_git: '' +REffectivePred: + version: 1.0.1 + title: Pandemic Prediction Model in an SIRS Framework + maintainer: Razvan Romanescu + description: |- + A suite of methods to fit and predict case count data using + a compartmental SIRS (Susceptible – Infectious – Recovered – Susceptible) + model, based on an assumed specification of the effective reproduction + number. The significance of this approach is that it relates epidemic + progression to the average number of contacts of infected individuals, + which decays as a function of the total susceptible fraction remaining + in the population. The main functions are pred.curve(), which computes + the epidemic curve for a set of parameters, and estimate.mle(), which + finds the best fitting curve to observed data. The easiest way to pass + arguments to the functions is via a config file, which contains input + settings required for prediction, and the package offers two methods, + navigate_to_config() which points the user to the configuration file, + and re_predict() for starting the fit-predict process. The main model was published in + Razvan G. Romanescu et al. . + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REffectivePred + url_git: '' +refineR: + version: 1.6.2 + title: Reference Interval Estimation using Real-World Data + maintainer: Tatjana Ammer + description: |- + Indirect method for the estimation of reference intervals using + Real-World Data ('RWD'). It takes routine measurements of diagnostic + tests, containing pathological and non-pathological samples as input + and uses sophisticated statistical methods to derive a model describing + the distribution of the non-pathological samples. This distribution can + then be used to derive reference intervals. Furthermore, the package + offers functions for printing and plotting the results of the algorithm. + See ?refineR for a more comprehensive description of the features. + Version 1.0 of the algorithm is described in detail in 'Ammer et al. (2021)' + . Additional guidance on the usage of + the algorithm is given in 'Ammer et al. (2023)' . + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=refineR + url_git: '' +refinr: + version: 0.3.3 + title: Cluster and Merge Similar Values Within a Character Vector + maintainer: Chris Muir + description: |- + These functions take a character vector as input, identify and + cluster similar values, and then merge clusters together so their values + become identical. The functions are an implementation of the key collision + and ngram fingerprint algorithms from the open source tool Open Refine + . More info on key collision and ngram fingerprint + can be found here . + date_publication: '2023-11-12' + bug_reports: https://github.com/ChrisMuir/refinr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=refinr + url_git: https://github.com/ChrisMuir/refinr +refitME: + version: 1.2.2 + title: Measurement Error Modelling using MCEM + maintainer: Jakub Stoklosa + description: 'Fits measurement error models using Monte Carlo Expectation Maximization + (MCEM). For specific details on the methodology, see: Greg C. G. Wei & Martin + A. Tanner (1990) A Monte Carlo Implementation of the EM Algorithm and the Poor + Man''s Data Augmentation Algorithms, Journal of the American Statistical Association, + 85:411, 699-704 For more examples on measurement + error modelling using MCEM, see the ''RMarkdown'' vignette: "''refitME'' R-package + tutorial".' + date_publication: '2021-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=refitME + url_git: '' +reflectR: + version: 2.1.3 + title: Automatic Scoring of the Cognitive Reflection Test + maintainer: Giuseppe Corbelli + description: |- + A tool for researchers and psychologists to automatically code open-ended responses to the Cognitive Reflection Test (CRT), a widely used class of tests in cognitive science and psychology for assessing an individual's propensity to override an incorrect gut response and engage in further reflection to find a correct answer. This package facilitates the standardization of Cognitive Reflection Test responses analysis across large datasets in cognitive psychology, decision-making, and related fields. By automating the coding process, it not only reduces manual effort but also aims to reduce the variability introduced by subjective interpretation of open-ended responses, contributing to a more consistent and reliable analysis. 'reflectR' supports automatic coding and machine scoring for the original English-language version of CRT (Frederick, 2005) , as well as for CRT4 and CRT7, 4- and 7-item versions, respectively (Toplak et al., 2014) , for the CRT-long version built via Item Response Theory by Primi and colleagues (2016) , and for CRT-2 by Thomson & Oppenheimer (2016) . + Note: While 'reflectR' draws inspiration from the principles and scientific literature underlying the different versions of the Cognitive Reflection Test, it has been independently developed and does not hold any affiliation with any of the original authors. + The development of this package benefited significantly from the kind insight and suggestion provided by Dr. Keela Thomson, whose contribution is gratefully acknowledged. + Additional gratitude is extended to Dr. Paolo Giovanni Cicirelli, Prof. Marinella Paciello, Dr. Carmela Sportelli, and Prof. Francesca D'Errico, who not only contributed to the manual multi-rater coding of CRT-2 items but also profoundly influenced the understanding of the importance and practical relevance of cognitive reflection within personality, social, and cognitive psychology research. + Acknowledgment is also due to the European project STERHEOTYPES (STudying European Racial Hoaxes and sterEOTYPES) for funding the data collection that produced the datasets initially used for manual multi-rater coding of CRT-2 items. + date_publication: '2024-05-15' + bug_reports: https://github.com/g-corbelli/reflectR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reflectR + url_git: https://github.com/g-corbelli/reflectR +reflimR: + version: 1.0.6 + title: Reference Limit Estimation Using Routine Laboratory Data + maintainer: Georg Hoffmann + description: Uses an indirect method based on truncated quantile-quantile plots + to estimate reference limits from routine laboratory data. The principle of the + method was developed by Robert G Hoffmann (1963) + and modified by Georg Hoffmann and colleagues (2015) , + (2020) , and (2022) . + date_publication: '2024-01-10' + bug_reports: https://github.com/reflim/reflimR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reflimR + url_git: https://github.com/reflim/reflimR +RefManageR: + version: 1.4.0 + title: Straightforward 'BibTeX' and 'BibLaTeX' Bibliography Management + maintainer: Mathew W. McLean + description: |- + Provides tools for importing and working with bibliographic + references. It greatly enhances the 'bibentry' class by providing a class + 'BibEntry' which stores 'BibTeX' and 'BibLaTeX' references, supports 'UTF-8' + encoding, and can be easily searched by any field, by date ranges, and by + various formats for name lists (author by last names, translator by full names, + etc.). Entries can be updated, combined, sorted, printed in a number of styles, + and exported. 'BibTeX' and 'BibLaTeX' '.bib' files can be read into 'R' and + converted to 'BibEntry' objects. Interfaces to 'NCBI Entrez', 'CrossRef', and + 'Zotero' are provided for importing references and references can be created + from locally stored 'PDF' files using 'Poppler'. Includes functions for citing + and generating a bibliography with hyperlinks for documents prepared with + 'RMarkdown' or 'RHTML'. + date_publication: '2022-09-30' + bug_reports: https://github.com/ropensci/RefManageR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RefManageR + url_git: https://github.com/ropensci/RefManageR/ +reformulas: + version: 0.4.0 + title: Machinery for Processing Random Effect Formulas + maintainer: Ben Bolker + description: Takes formulas including random-effects components (formatted as in + 'lme4', 'glmmTMB', etc.) and processes them. Includes various helper functions. + date_publication: '2024-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reformulas + url_git: https://github.com/bbolker/reformulas +refreg: + version: 0.1.1 + title: Conditional Multivariate Reference Regions + maintainer: Oscar Lado-Baleato + description: |- + An R package for estimating conditional multivariate reference regions. + The reference region is non parametrically estimated using a kernel density estimator. + Covariates effects on the multivariate response means vector and variance-covariance + matrix, thus on the region shape, are estimated by flexible additive predictors. + Continuous covariates non linear effects might be estimated using penalized splines smoothers. + Confidence intervals for the covariates estimated effects might be derived from + bootstrap resampling. Kernel density bandwidth can be estimated with different methods, including + a method that optimize the region coverage. Numerical, and graphical, summaries + can be obtained by the user in order to evaluate reference region performance with real data. + Full mathematical details can be found in and . + date_publication: '2022-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=refreg + url_git: '' +refreshr: + version: 0.1.0 + title: |- + Work with Refreshable Datasets that Update their Data + Automatically + maintainer: Joachim Zuckarelli + description: |- + Connects dataframes/tables with a remote data source. Raw data downloaded + from the data source can be further processed and transformed using data preparation + code that is also baked into the dataframe/table. Refreshable dataframes can + be shared easily (e.g. as R data files). Their users do not need to care about + the inner workings of the data update mechanisms. + date_publication: '2022-03-01' + bug_reports: https://github.com/jsugarelli/refreshr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=refreshr + url_git: https://github.com/jsugarelli/refreshr/ +refseqR: + version: 1.1.5 + title: |- + Common Computational Operations Working with RefSeq Entries + (GenBank) + maintainer: Jose V. Die + description: |- + Fetches NCBI data (RefSeq database) and provides an environment to + extract information at the level of gene, mRNA or protein accessions. + date_publication: '2024-10-30' + bug_reports: https://github.com/jdieramon/refseqR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=refseqR + url_git: https://github.com/jdieramon/refseqR +refset: + version: 0.1.1 + title: Subsets with Reference Semantics + maintainer: '"David Hugh-Jones"' + description: |- + Provides subsets with reference semantics, i.e. subsets + which automatically reflect changes in the original object, and which + optionally update the original object when they are changed. + date_publication: '2017-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=refset + url_git: http://github.com/hughjonesd/refset +refuge: + version: 0.3.3 + title: Locate Trans and Intersex-Friendly Toilets + maintainer: Evan Odell + description: |- + Access the 'Refuge' API, a web-application for locating trans and + intersex-friendly restrooms, including unisex and accessible restrooms. + Includes data on the location of restrooms, along with directions, + comments, user ratings and amenities. Coverage is global, but data is + most comprehensive in the United States. + See for full API documentation. + date_publication: '2021-01-11' + bug_reports: https://github.com/evanodell/refuge/issues + url: https://docs.evanodell.com/refuge + url_cran: https://CRAN.R-project.org/package=refuge + url_git: '' +refugees: + version: 2024.6.0 + title: UNHCR Refugee Population Statistics Database + maintainer: Hisham Galal + description: |- + The Refugee Population Statistics Database published by + The Office of The United Nations High Commissioner for Refugees (UNHCR) + contains information about forcibly displaced populations + spanning more than 70 years of statistical activities. + It covers displaced populations such as refugees, asylum-seekers and + internally displaced people, including their demographics. + Stateless people are also included, most of who have never been displaced. + The database also reflects the different types of solutions + for displaced populations such as repatriation or resettlement. + More information on the data and methodology can be found on + the UNHCR Refugee Data Finder . + date_publication: '2024-10-19' + bug_reports: https://github.com/PopulationStatistics/refugees/issues + url: https://populationstatistics.github.io/refugees/ + url_cran: https://CRAN.R-project.org/package=refugees + url_git: https://github.com/PopulationStatistics/refugees +refund: + version: 0.1-37 + title: Regression with Functional Data + maintainer: Julia Wrobel + description: |- + Methods for regression for functional + data, including function-on-scalar, scalar-on-function, and + function-on-function regression. Some of the functions are applicable to + image data. + date_publication: '2024-09-20' + bug_reports: https://github.com/refunders/refund/issues + url: '' + url_cran: https://CRAN.R-project.org/package=refund + url_git: https://github.com/refunders/refund +refund.shiny: + version: '1.0' + title: Interactive Plotting for Functional Data Analyses + maintainer: Julia Wrobel + description: Produces Shiny applications for different types of popular functional + data analyses. The functional data analyses are implemented in the refund package, + then refund.shiny reads in the refund object and implements an object-specific + set of plots based on the object class using S3. + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=refund.shiny + url_git: '' +RegAssure: + version: 1.0.0 + title: Streamlined Integration of Regression Assumption + maintainer: Nicolás Rubio García + description: |- + It streamlines the evaluation of regression model + assumptions, enhancing result reliability. With integrated tools for + assessing key aspects like linearity, homoscedasticity, and more. It's + a valuable asset for researchers and analysts working with regression + models. + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RegAssure + url_git: '' +regclass: + version: '1.6' + title: Tools for an Introductory Class in Regression and Modeling + maintainer: Adam Petrie + description: 'Contains basic tools for visualizing, interpreting, and building regression + models. It has been designed for use with the book Introduction to Regression + and Modeling with R by Adam Petrie, Cognella Publishers, ISBN: 978-1-63189-250-9 + .' + date_publication: '2020-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regclass + url_git: '' +RegCombin: + version: 0.4.1 + title: Partially Linear Regression under Data Combination + maintainer: Christophe Gaillac + description: We implement linear regression when the outcome of interest and some + of the covariates are observed in two different datasets that cannot be linked, + based on D'Haultfoeuille, Gaillac, Maurel (2022) . The package + allows for common regressors observed in both datasets, and for various shape + constraints on the effect of covariates on the outcome of interest. It also provides + the tools to perform a test of point identification. See the associated vignette + for + theory and code examples. + date_publication: '2023-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RegCombin + url_git: '' +regda: + version: '1.0' + title: Regularised Discriminant Analysis + maintainer: Michail Tsagris + description: 'Regularised discriminant analysis functions. The classical regularised + discriminant analysis proposed by Friedman in 1989, including cross-validation, + of which the linear and quadratic discriminant analyses are special cases. Further, + the regularised maximum likelihood linear discriminant analysis, including cross-validation. + References: Friedman J.H. (1989): "Regularized Discriminant Analysis". Journal + of the American Statistical Association 84(405): 165--175. . + Friedman J., Hastie T. and Tibshirani R. (2009). "The elements of statistical + learning", 2nd edition. Springer, Berlin. . Tsagris + M., Preston S. and Wood A.T.A. (2016). "Improved classification for compositional + data using the alpha-transformation". Journal of Classification, 33(2): 243--261. + .' + date_publication: '2023-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regda + url_git: '' +RegDDM: + version: '1.0' + title: Generalized Linear Regression with DDM + maintainer: Zekai Jin + description: |- + Drift-Diffusion Model (DDM) has been widely used to model binary + decision-making tasks, and many research studies the relationship between + DDM parameters and other characteristics of the subject. This package uses + 'RStan' to perform generalized liner regression analysis over DDM parameters + via a single Bayesian Hierarchical model. Compared to estimating DDM + parameters followed by a separate regression model, 'RegDDM' reduces bias + and improves statistical power. + date_publication: '2024-12-05' + bug_reports: https://github.com/biorabbit/RegDDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RegDDM + url_git: https://github.com/biorabbit/RegDDM +regDIF: + version: 1.1.1 + title: Regularized Differential Item Functioning + maintainer: William Belzak + description: |- + Performs regularization of differential item functioning (DIF) parameters + in item response theory (IRT) models (Belzak & Bauer, 2020) + using a penalized expectation-maximization + algorithm. + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regDIF + url_git: '' +REGENT: + version: 1.0.6 + title: Risk Estimation for Genetic and Environmental Traits + maintainer: Daniel Crouch + description: Produces population distribution of disease risk and statistical risk + categories, and predicts risks for individuals with genotype information. + date_publication: '2015-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REGENT + url_git: '' +regexPipes: + version: 0.0.1 + title: Wrappers Around 'base::grep()' for Use with Pipes + maintainer: Billy Buchanan + description: |- + Provides wrappers around base::grep() where the first argument + is standardized to take the data object. This makes it less of a pain to use + regular expressions with 'magrittr' or other pipe operators. + date_publication: '2016-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regexPipes + url_git: '' +regexSelect: + version: 1.0.0 + title: Regular Expressions in 'shiny' Select Lists + maintainer: Jonathan Sidi + description: |- + 'shiny' extension that adds regular expression filtering capabilities to + the choice vector of the select list. + date_publication: '2017-09-22' + bug_reports: https://github.com/yonicd/regexSelect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regexSelect + url_git: https://github.com/yonicd/regexSelect +reghelper: + version: 1.1.2 + title: Helper Functions for Regression Analysis + maintainer: Jeffrey Hughes + description: |- + A set of functions used to automate commonly used methods in + regression analysis. This includes plotting interactions, and calculating + simple slopes, standardized coefficients, regions of significance + (Johnson & Neyman, 1936; cf. Spiller et al., 2012), etc. See the reghelper + documentation for more information, documentation, and examples. + date_publication: '2023-09-02' + bug_reports: https://github.com/jeff-hughes/reghelper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reghelper + url_git: https://github.com/jeff-hughes/reghelper +regional: + version: 0.4.4 + title: Intra- and Inter-Regional Similarity + maintainer: Jakub Nowosad + description: |- + Calculates intra-regional and inter-regional similarities based on user-provided + spatial vector objects (regions) and spatial raster objects (cells with values). + Implemented metrics include inhomogeneity, isolation + (Haralick and Shapiro (1985) , + Jasiewicz et al. (2018) ), + and distinction (Nowosad (2021) ). + date_publication: '2024-05-09' + bug_reports: https://github.com/Nowosad/regional/issues + url: https://jakubnowosad.com/regional/ + url_cran: https://CRAN.R-project.org/package=regional + url_git: '' +regioncode: + version: 0.1.2 + title: Convert Region Names and Division Codes of China Over Years + maintainer: Yue Hu + description: A tool to conquer the difficulties to convert various region names + and administration division codes of Chinese regions. The current version enables + seamlessly converting Chinese regions' formal names, common-used names, and codes + between each other at the city level from 1986 to 2019. + date_publication: '2024-03-10' + bug_reports: https://github.com/sammo3182/regioncode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regioncode + url_git: '' +regions: + version: 0.1.8 + title: Processing Regional Statistics + maintainer: Daniel Antal + description: |- + Validating sub-national statistical typologies, re-coding across + standard typologies of sub-national statistics, and making valid aggregate + level imputation, re-aggregation, re-weighting and projection down to + lower hierarchical levels to create meaningful data panels and time series. + date_publication: '2021-06-21' + bug_reports: https://github.com/rOpenGov/regions + url: https://regions.dataobservatory.eu/ + url_cran: https://CRAN.R-project.org/package=regions + url_git: '' +registr: + version: 2.1.0 + title: Curve Registration for Exponential Family Functional Data + maintainer: Julia Wrobel + description: |- + A method for performing joint registration and functional principal + component analysis for curves (functional data) that are generated from exponential family distributions. This + mainly implements the algorithms described in 'Wrobel et al. (2019)' and further adapts them to potentially + incomplete curves where (some) curves are not observed from the beginning and/or until the end of the common domain. Curve registration + can be used to better understand patterns in functional data by separating curves into phase and amplitude variability. + This software handles both binary and continuous functional data, and is + especially applicable in accelerometry and wearable technology. + date_publication: '2022-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=registr + url_git: '' +registry: + version: 0.5-1 + title: Infrastructure for R Package Registries + maintainer: David Meyer + description: Provides a generic infrastructure for creating and using registries. + date_publication: '2019-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=registry + url_git: '' +RegKink: + version: 0.1.0 + title: Regression Kink with a Time-Varying Threshold + maintainer: Lixiong Yang + description: An algorithm is proposed to estimate regression kink model proposed + by the paper, Lixiong Yang and Jen-Je Su (2018) . + date_publication: '2021-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RegKink + url_git: '' +reglogit: + version: 1.2-7 + title: Simulation-Based Regularized Logistic Regression + maintainer: Robert B. Gramacy + description: |- + Regularized (polychotomous) logistic regression + by Gibbs sampling. The package implements subtly different + MCMC schemes with varying efficiency depending on the data type + (binary v. binomial, say) and the desired estimator (regularized maximum + likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a + unified interface. For details, see Gramacy & Polson (2012 ). + date_publication: '2023-04-25' + bug_reports: '' + url: https://bobby.gramacy.com/r_packages/reglogit/ + url_cran: https://CRAN.R-project.org/package=reglogit + url_git: '' +regmed: + version: 2.1.0 + title: Regularized Mediation Analysis + maintainer: Jason Sinnwell + description: Mediation analysis for multiple mediators by penalized structural equation + models with different types of penalties depending on whether there are multiple + mediators and only one exposure and one outcome variable (using sparse group lasso) + or multiple exposures, multiple mediators, and multiple outcome variables (using + lasso, L1, penalties). + date_publication: '2023-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regmed + url_git: '' +regmedint: + version: 1.0.1 + title: |- + Regression-Based Causal Mediation Analysis with Interaction and + Effect Modification Terms + maintainer: Yi Li + description: This is an extension of the regression-based causal mediation analysis + first proposed by Valeri and VanderWeele (2013) and Valeri + and VanderWeele (2015) ). It supports including + effect measure modification by covariates(treatment-covariate and mediator-covariate + product terms in mediator and outcome regression models) as proposed by Li et + al (2023) . It also accommodates the original + 'SAS' macro and 'PROC CAUSALMED' procedure in 'SAS' when there is no effect measure + modification. Linear and logistic models are supported for the mediator model. + Linear, logistic, loglinear, Poisson, negative binomial, Cox, and accelerated + failure time (exponential and Weibull) models are supported for the outcome model. + date_publication: '2024-01-13' + bug_reports: https://github.com/kaz-yos/regmedint/issues + url: https://kaz-yos.github.io/regmedint/ + url_cran: https://CRAN.R-project.org/package=regmedint + url_git: '' +regmhmm: + version: 1.0.0 + title: '''regmhmm'' Fits Hidden Markov Models with Regularization' + maintainer: Man Chong Leong + description: Designed for longitudinal data analysis using Hidden Markov Models + (HMMs). Tailored for applications in healthcare, social sciences, and economics, + the main emphasis of this package is on regularization techniques for fitting + HMMs. Additionally, it provides an implementation for fitting HMMs without regularization, + referencing Zucchini et al. (2017, ISBN:9781315372488). + date_publication: '2023-12-04' + bug_reports: https://github.com/HenryLeongStat/regmhmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regmhmm + url_git: https://github.com/HenryLeongStat/regmhmm +regMMD: + version: 0.0.1 + title: |- + Robust Regression and Estimation Through Maximum Mean + Discrepancy Minimization + maintainer: Pierre Alquier + description: |- + The functions in this package compute robust estimators by minimizing a kernel-based distance known as MMD (Maximum Mean Discrepancy) between the sample and a statistical model. Recent works proved that these estimators enjoy a universal consistency property, and are extremely robust to outliers. Various optimization algorithms are implemented: stochastic gradient is available for most models, but the package also allows gradient descent in a few models for which an exact formula is available for the gradient. In terms of distribution fit, a large number of continuous and discrete distributions are available: Gaussian, exponential, uniform, gamma, Poisson, geometric, etc. In terms of regression, the models available are: linear, logistic, gamma, beta and Poisson. + Alquier, P. and Gerber, M. (2024) + Cherief-Abdellatif, B.-E. and Alquier, P. (2022) . + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regMMD + url_git: '' +regnet: + version: 1.0.2 + title: Network-Based Regularization for Generalized Linear Models + maintainer: Jie Ren + description: |- + Network-based regularization has achieved success in variable selection for + high-dimensional biological data due to its ability to incorporate correlations among + genomic features. This package provides procedures of network-based variable selection + for generalized linear models (Ren et al. (2017) and + Ren et al.(2019) ). Continuous, binary, and survival response + are supported. Robust network-based methods are available for continuous and survival + responses. + date_publication: '2025-02-10' + bug_reports: https://github.com/jrhub/regnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regnet + url_git: https://github.com/jrhub/regnet +regplot: + version: '1.1' + title: Enhanced Regression Nomogram Plot + maintainer: Roger Marshall + description: |- + A function to plot a regression nomogram of regression + objects. Covariate distributions are superimposed on nomogram scales and the plot + can be animated to allow on-the-fly changes to distribution representation and to + enable outcome calculation. + date_publication: '2020-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regplot + url_git: '' +regport: + version: 0.3.0 + title: Regression Model Processing Port + maintainer: Shixiang Wang + description: |- + Provides R6 classes, methods and utilities to construct, + analyze, summarize, and visualize regression models. + date_publication: '2022-05-10' + bug_reports: https://github.com/ShixiangWang/regport/issues + url: https://shixiangwang.github.io/regport/ + url_cran: https://CRAN.R-project.org/package=regport + url_git: https://github.com/ShixiangWang/regport +regr.easy: + version: 1.0.2 + title: Easy Linear, Quadratic and Cubic Regression Models + maintainer: Wagner Martins dos Santos + description: Focused on linear, quadratic and cubic regression models, it has a + function for calculating the models, obtaining a list with their parameters, and + a function for making the graphs for the respective models. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regr.easy + url_git: '' +regrap: + version: 1.0.1 + title: Reverse Graphical Approaches + maintainer: Jiangtao Gou + description: The graphical approach is proposed as a general framework for clinical + trial designs involving multiple hypotheses, where decisions are made only based + on the observed marginal p-values. A reverse graphical approach starts from a + set of singleton graphs, and gradually add vertices into graphs until rejection + of a set of hypotheses is made. See Gou, J. (2020). Reverse graphical approaches + for multiple test procedures. Technical Report. + date_publication: '2020-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regrap + url_git: '' +RegrCoeffsExplorer: + version: 1.2.0 + title: |- + Efficient Visualization of Regression Coefficients for Lm(), + Glm(), and Glmnet() Objects + maintainer: Vadim Tyuryaev + description: The visualization tool offers a nuanced understanding of regression + dynamics, going beyond traditional per-unit interpretation of continuous variables + versus categorical ones. It highlights the impact of unit changes as well as larger + shifts like interquartile changes, acknowledging the distribution of empirical + data. Furthermore, it generates visualizations depicting alterations in Odds Ratios + for predictors across minimum, first quartile, median, third quartile, and maximum + values, aiding in comprehending predictor-outcome interplay within empirical data + distributions, particularly in logistic regression frameworks. + date_publication: '2025-02-01' + bug_reports: '' + url: https://vadimtyuryaev.github.io/RegrCoeffsExplorer/ + url_cran: https://CRAN.R-project.org/package=RegrCoeffsExplorer + url_git: '' +regreplaceR: + version: 0.1.0 + title: |- + Match and Replace Strings Based on Named Groups in Regular + Expressions + maintainer: Gwang-Jin Kim + description: |- + An R6 class "Replacer" provided by the package simplifies working with + regex patterns containing named groups. It allows easy retrieval of matched portions + and targeted replacements by group name, improving both code clarity and maintainability. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regreplaceR + url_git: https://github.com/gwangjinkim/regreplaceR +regress: + version: 1.3-21 + title: Gaussian Linear Models with Linear Covariance Structure + maintainer: Karl W Broman + description: |- + Functions to fit Gaussian linear model by maximising the + residual log likelihood where the covariance structure can be + written as a linear combination of known matrices. Can be used + for multivariate models and random effects models. Easy + straight forward manner to specify random effects models, + including random interactions. Code now optimised to use + Sherman Morrison Woodbury identities for matrix inversion in + random effects models. We've added the ability to fit models + using any kernel as well as a function to return the mean and + covariance of random effects conditional on the data (best + linear unbiased predictors, BLUPs). + Clifford and McCullagh (2006) + . + date_publication: '2020-06-18' + bug_reports: https://github.com/kbroman/regress/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regress + url_git: https://github.com/kbroman/regress +regressinator: + version: 0.2.0 + title: Simulate and Diagnose (Generalized) Linear Models + maintainer: Alex Reinhart + description: |- + Simulate samples from populations with known covariate + distributions, generate response variables according to common linear and + generalized linear model families, draw from sampling distributions of + regression estimates, and perform visual inference on diagnostics from model + fits. + date_publication: '2024-08-16' + bug_reports: https://github.com/capnrefsmmat/regressinator/issues + url: https://www.refsmmat.com/regressinator/ + url_cran: https://CRAN.R-project.org/package=regressinator + url_git: https://github.com/capnrefsmmat/regressinator +RegressionFactory: + version: 0.7.4 + title: |- + Expander Functions for Generating Full Gradient and Hessian from + Single-Slot and Multi-Slot Base Distributions + maintainer: Alireza S. Mahani + description: The expander functions rely on the mathematics developed for the Hessian-definiteness + invariance theorem for linear projection transformations of variables, described + in authors' paper, to generate the full, high-dimensional gradient and Hessian + from the lower-dimensional derivative objects. This greatly relieves the computational + burden of generating the regression-function derivatives, which in turn can be + fed into any optimization routine that utilizes such derivatives. The theorem + guarantees that Hessian definiteness is preserved, meaning that reasoning about + this property can be performed in the low-dimensional space of the base distribution. + This is often a much easier task than its equivalent in the full, high-dimensional + space. Definiteness of Hessian can be useful in selecting optimization/sampling + algorithms such as Newton-Raphson optimization or its sampling equivalent, the + Stochastic Newton Sampler. Finally, in addition to being a computational tool, + the regression expansion framework is of conceptual value by offering new opportunities + to generate novel regression problems. + date_publication: '2020-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RegressionFactory + url_git: '' +regressoR: + version: 4.0.3 + title: Regression Data Analysis System + maintainer: Oldemar Rodriguez + description: Perform a supervised data analysis on a database through a 'shiny' + graphical interface. It includes methods such as linear regression, penalized + regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient + boosting, random forest, neural networks, deep learning and support vector machines. + date_publication: '2024-11-15' + bug_reports: https://github.com/PROMiDAT/predictoR/issues + url: https://promidat.website/ + url_cran: https://CRAN.R-project.org/package=regressoR + url_git: '' +regrrr: + version: 0.1.3 + title: |- + Toolkit for Compiling, (Post-Hoc) Testing, and Plotting + Regression Results + maintainer: Rui K. Yang + description: Compiling regression results into a publishable format, conducting + post-hoc hypothesis testing, and plotting moderating effects (the effect of X + on Y becomes stronger/weaker as Z increases). + date_publication: '2021-08-13' + bug_reports: https://github.com/RkzYang/regrrr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regrrr + url_git: '' +regRSM: + version: '0.5' + title: Random Subspace Method (RSM) for Linear Regression + maintainer: Pawel Teisseyre + description: Performs Random Subspace Method (RSM) for high-dimensional linear regression + to obtain variable importance measures. The final model is chosen based on validation + set or Generalized Information Criterion. + date_publication: '2015-09-11' + bug_reports: '' + url: http://www.ipipan.eu/~teisseyrep/SOFTWARE/ + url_cran: https://CRAN.R-project.org/package=regRSM + url_git: '' +RegSDC: + version: 1.0.0 + title: |- + Information Preserving Regression-Based Tools for Statistical + Disclosure Control + maintainer: Øyvind Langsrud + description: 'Implementation of the methods described in the paper with the above + title: Langsrud, Ø. (2019) . The package can be + used to generate synthetic or hybrid continuous microdata, and the relationship + to the original data can be controlled in several ways. A function for replacing + suppressed tabular cell frequencies with decimal numbers is included.' + date_publication: '2025-02-03' + bug_reports: https://github.com/olangsrud/RegSDC/issues + url: https://olangsrud.github.io/RegSDC/ + url_cran: https://CRAN.R-project.org/package=RegSDC + url_git: https://github.com/olangsrud/RegSDC +regsem: + version: 1.9.5 + title: Regularized Structural Equation Modeling + maintainer: Ross Jacobucci + description: |- + Uses both ridge and lasso penalties (and extensions) to penalize + specific parameters in structural equation models. The package offers additional + cost functions, cross validation, and other extensions beyond traditional structural + equation models. Also contains a function to perform exploratory mediation (XMed). + date_publication: '2023-06-02' + bug_reports: https://github.com/Rjacobucci/regsem/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=regsem + url_git: https://github.com/Rjacobucci/regsem/ +regspec: + version: '2.7' + title: Non-Parametric Bayesian Spectrum Estimation for Multirate Data + maintainer: Ben Powell + description: "Computes linear Bayesian spectral estimates from multirate\tdata for + second-order stationary time series. Provides credible intervals and methods for + plotting various spectral estimates. Please see the paper `Should we sample a + time series more frequently?' (doi below) for a full description of and motivation + for the methodology." + date_publication: '2023-09-20' + bug_reports: '' + url: https://doi.org/10.1111/rssa.12210 + url_cran: https://CRAN.R-project.org/package=regspec + url_git: '' +regsubseq: + version: '0.12' + title: Detect and Test Regular Sequences and Subsequences + maintainer: Yanming Di + description: |- + For a sequence of event occurence times, we are interested in + finding subsequences in it that are too "regular". We define regular as being + significantly different from a homogeneous Poisson process. The departure from + the Poisson process is measured using a L1 distance. See Di and Perlman 2007 + for more details. + date_publication: '2014-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regsubseq + url_git: '' +regtomean: + version: '1.2' + title: Regression Toward the Mean + maintainer: Daniela Recchia + description: |- + In repeated measures studies with extreme large or small values it is common + that the subjects measurements on average are closer to the mean of the basic population. + Interpreting possible changes in the mean in such situations can lead to biased results + since the values were not randomly selected, they come from truncated sampling. + This method allows to estimate the range of means where treatment effects are likely to occur + when regression toward the mean is present. + Ostermann, T., Willich, Stefan N. & Luedtke, Rainer. (2008). Regression toward the mean - a detection method for unknown population mean based on Mee and Chua's algorithm. BMC Medical Research Methodology.. + Acknowledgments: We would like to acknowledge "Lena Roth" and "Nico Steckhan" for the package's initial updates (Q3 2024) and continued supervision and guidance. Both have contributed to discussing and integrating these methods into the package, ensuring they are up-to-date and contextually relevant. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=regtomean + url_git: '' +regtools: + version: 1.7.0 + title: Regression and Classification Tools + maintainer: Norm Matloff + description: |- + Tools for linear, nonlinear and nonparametric regression + and classification. Novel graphical methods for assessment + of parametric models using nonparametric methods. One + vs. All and All vs. All multiclass classification, optional + class probabilities adjustment. Nonparametric regression + (k-NN) for general dimension, local-linear option. Nonlinear + regression with Eickert-White method for dealing with + heteroscedasticity. Utilities for converting time series + to rectangular form. Utilities for conversion between + factors and indicator variables. Some code related to + "Statistical Regression and Classification: from Linear + Models to Machine Learning", N. Matloff, 2017, CRC, + ISBN 9781498710916. + date_publication: '2022-03-30' + bug_reports: https://github.com/matloff/regtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=regtools + url_git: https://github.com/matloff/regtools +rehh: + version: 3.2.2 + title: |- + Searching for Footprints of Selection using 'Extended Haplotype + Homozygosity' Based Tests + maintainer: Alexander Klassmann + description: |- + Population genetic data such as 'Single Nucleotide + Polymorphisms' (SNPs) is often used to identify genomic regions + that have been under recent natural or artificial selection + and might provide clues about the molecular mechanisms of adaptation. + One approach, the concept of an 'Extended Haplotype Homozygosity' (EHH), + introduced by (Sabeti 2002) , has given rise to + several statistics designed for whole genome scans. + The package provides functions to compute three of these, + namely: 'iHS' (Voight 2006) for + detecting positive or 'Darwinian' selection within a single population as well as + 'Rsb' (Tang 2007) and + 'XP-EHH' (Sabeti 2007) , targeted + at differential selection between two populations. + Various plotting functions are included to facilitate + visualization and interpretation of these statistics. + date_publication: '2021-09-15' + bug_reports: https://gitlab.com/oneoverx/rehh/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rehh + url_git: https://gitlab.com/oneoverx/rehh +rehh.data: + version: 1.0.0 + title: |- + Data Only: Searching for Footprints of Selection using Haplotype + Homozygosity Based Tests + maintainer: Mathieu Gautier + description: Contains example data for the 'rehh' package. + date_publication: '2016-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rehh.data + url_git: '' +rehydratoR: + version: 0.5.2 + title: Downloads Tweets from a List of Tweet IDs + maintainer: Kevin Coakley + description: |- + Facilitates replication of Twitter-based research by handling + common programming tasks needed when downloading tweets. Specifically, it ensures a + user does not exceed Twitter’s rate limits, and it saves tweets in moderately sized files. + While a user could perform these tasks in their own code, doing so may be beyond the + capabilities of many users. + date_publication: '2019-02-08' + bug_reports: https://github.com/kevincoakley/rehydratoR/issues + url: https://kevincoakley.github.io/rehydratoR/ + url_cran: https://CRAN.R-project.org/package=rehydratoR + url_git: '' +ReinforcementLearning: + version: 1.0.5 + title: Model-Free Reinforcement Learning + maintainer: Nicolas Proellochs + description: |- + Performs model-free reinforcement learning in R. This implementation enables the learning + of an optimal policy based on sample sequences consisting of states, actions and rewards. In + addition, it supplies multiple predefined reinforcement learning algorithms, such as experience + replay. Methodological details can be found in Sutton and Barto (1998) . + date_publication: '2020-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReinforcementLearning + url_git: '' +ReIns: + version: 1.0.15 + title: 'Functions from "Reinsurance: Actuarial and Statistical Aspects"' + maintainer: Tom Reynkens + description: 'Functions from the book "Reinsurance: Actuarial and Statistical Aspects" + (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels .' + date_publication: '2024-12-02' + bug_reports: https://github.com/TReynkens/ReIns/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ReIns + url_git: https://github.com/TReynkens/ReIns +reinstallr: + version: 0.1.5 + title: Search and Install Missing Packages + maintainer: Calli Gross + description: Search R files for not installed packages and run install.packages. + date_publication: '2021-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reinstallr + url_git: https://github.com/calligross/reinstallr/ +reinsureR: + version: 0.1.0 + title: Reinsurance Treaties Application + maintainer: Arnaud Buzzi + description: |- + Application of reinsurance treaties to claims portfolios. + The package creates a class Claims whose objective is to + store claims and premiums, on which different treaties can be applied. + A statistical analysis can then be applied to measure the impact of + reinsurance, producing a table or graphical output. This package can + be used for estimating the impact of reinsurance on several portfolios + or for pricing treaties through statistical analysis. Documentation + for the implemented methods can be found in "Reinsurance: Actuarial + and Statistical Aspects" by Hansjöerg Albrecher, Jan Beirlant, + Jozef L. Teugels (2017, ISBN: 978-0-470-77268-3) and + "REINSURANCE: A Basic Guide to Facultative and Treaty Reinsurance" + by Munich Re (2010) . + date_publication: '2018-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reinsureR + url_git: '' +relaimpo: + version: 2.2-7 + title: Relative Importance of Regressors in Linear Models + maintainer: Ulrike Groemping + description: Provides several metrics for assessing relative importance in linear + models. These can be printed, plotted and bootstrapped. The recommended metric + is lmg, which provides a decomposition of the model explained variance into non-negative + contributions. There is a version of this package available that additionally + provides a new and also recommended metric called pmvd. If you are a non-US user, + you can download this extended version from Ulrike Groempings web site. + date_publication: '2023-10-04' + bug_reports: '' + url: https://prof.bht-berlin.de/groemping/relaimpo/ + url_cran: https://CRAN.R-project.org/package=relaimpo + url_git: '' +relatable: + version: 1.0.0 + title: |- + Functions for Mapping Key-Value Pairs, Many-to-Many, + One-to-Many, and Many-to-One Relations + maintainer: Dominic Jarkey + description: Functions to safely map from a vector of keys to a vector of values, + determine properties of a given relation, or ensure a relation conforms to a given + type, such as many-to-many, one-to-many, injective, surjective, or bijective. + Permits default return values for use similar to a vectorised switch statement, + as well as safely handling large vectors, NAs, and duplicate mappings. + date_publication: '2018-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relatable + url_git: https://github.com/domjarkey/relatable +Relatedness: + version: '2.0' + title: Maximum Likelihood Estimation of Relatedness using EM Algorithm + maintainer: Fabien Laporte + description: Inference of relatedness coefficients from a bi-allelic genotype matrix + using a Maximum Likelihood estimation, Laporte, F., Charcosset, A. and Mary-Huard, + T. (2017) . + date_publication: '2017-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Relatedness + url_git: '' +relations: + version: 0.6-15 + title: Data Structures and Algorithms for Relations + maintainer: Kurt Hornik + description: |- + Data structures and algorithms for k-ary relations with + arbitrary domains, featuring relational algebra, predicate functions, + and fitters for consensus relations. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relations + url_git: '' +relcircle: + version: '1.0' + title: Draw Regulatory Relationships Between Genes + maintainer: Ruilin Li + description: |- + According to the order of the loci on the chromosome, the loci can be + connected according to the interrelationship between them and classified according + to different locus types. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relcircle + url_git: '' +reldist: + version: 1.7-2 + title: Relative Distribution Methods + maintainer: Mark S. Handcock + description: Tools for the comparison of distributions. This includes nonparametric + estimation of the relative distribution PDF and CDF and numerical summaries as + described in "Relative Distribution Methods in the Social Sciences" by Mark S. + Handcock and Martina Morris, Springer-Verlag, 1999, Springer-Verlag, ISBN 0387987789. + date_publication: '2023-02-17' + bug_reports: '' + url: http://www.stat.ucla.edu/~handcock/RelDist/ + url_cran: https://CRAN.R-project.org/package=reldist + url_git: '' +RelDists: + version: 1.0.0 + title: Estimation for some Reliability Distributions + maintainer: Jaime Mosquera + description: |- + Parameters estimation and linear regression models for Reliability + distributions families reviewed by Almalki & Nadarajah (2014) + using Generalized Additive + Models for Location, Scale and Shape, aka GAMLSS by Rigby & Stasinopoulos + (2005) . + date_publication: '2022-12-22' + bug_reports: https://github.com/ousuga/RelDists/issues + url: https://ousuga.github.io/RelDists/ + url_cran: https://CRAN.R-project.org/package=RelDists + url_git: '' +Relectoral: + version: 0.1.0 + title: Electoral Analysis + maintainer: Miguel Rodríguez Asensio + description: 'Functions to obtain an important number of electoral indicators described + in the package, which can be divided into two large sections: The first would + be the one containing the indicators of electoral disproportionality, such as, + Rae index, Loosemore–Hanby index, etc. The second group is intended to study the + dimensions of the party system vote, through the indicators of electoral fragmentation, + polarization, volatility, etc. Moreover, multiple seat allocation simulations + can also be performed based on different allocation systems, such as the D''Hondt + method, Sainte-Laguë, etc. Finally, some of these functions have been built so + that, if the user wishes, the data provided by the Spanish Ministry of Home Office + for different electoral processes held in Spain can be obtained automatically. + All the above will allow the users to carry out deep studies on the results obtained + in any type of electoral process. The methods are described in: Oñate, Pablo and + Ocaña, Francisco A. (1999, ISBN:9788474762815); Ruiz Rodríguez, Leticia M. and + Otero Felipe, Patricia (2011, ISBN:9788474766226).' + date_publication: '2020-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Relectoral + url_git: '' +relevance: + version: '2.1' + title: Calculate Relevance and Significance Measures + maintainer: Werner A. Stahel + description: |- + Calculates relevance and significance values for + simple models and for many types of regression models. + These are introduced in + 'Stahel, Werner A.' (2021) + "Measuring Significance and Relevance instead of p-values." + . + These notions are also applied to replication studies, + as described in the manuscript + 'Stahel, Werner A.' (2022) + "'Replicability': Terminology, Measuring Success, and Strategy" + available in the documentation. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relevance + url_git: '' +relevent: + version: 1.2-1 + title: Relational Event Models + maintainer: Carter T. Butts + description: Tools to fit and simulate realizations from relational event models. + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relevent + url_git: '' +relgam: + version: '1.0' + title: Reluctant Generalized Additive Models + maintainer: Kenneth Tay + description: |- + A method for fitting the entire regularization path of the + reluctant generalized additive model (RGAM) for linear regression, logistic, + Poisson and Cox regression models. See Tay, J. K., and Tibshirani, R., (2019) + for details. + date_publication: '2020-01-13' + bug_reports: '' + url: https://arxiv.org/abs/1912.01808 + url_cran: https://CRAN.R-project.org/package=relgam + url_git: '' +reliabilitydiag: + version: 0.2.1 + title: Reliability Diagrams Using Isotonic Regression + maintainer: Alexander I. Jordan + description: |- + Checking the reliability of predictions via the CORP approach, + which generates provably statistically 'C'onsistent, 'O'ptimally binned, and + 'R'eproducible reliability diagrams using the 'P'ool-adjacent-violators + algorithm. See Dimitriadis, Gneiting, Jordan (2021) . + date_publication: '2022-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reliabilitydiag + url_git: https://github.com/aijordan/reliabilitydiag/ +ReliabilityTheory: + version: 0.3.1 + title: Structural Reliability Analysis + maintainer: Louis Aslett + description: |- + Perform structural reliability analysis, including computation and + simulation with system signatures, Samaniego (2007) + , and survival signatures, Coolen and + Coolen-Maturi (2013) . Additionally + supports parametric and topological inference given system lifetime data, + Aslett (2012) . + date_publication: '2024-09-25' + bug_reports: https://github.com/louisaslett/ReliabilityTheory/issues + url: https://www.louisaslett.com/ + url_cran: https://CRAN.R-project.org/package=ReliabilityTheory + url_git: https://github.com/louisaslett/ReliabilityTheory +ReliaGrowR: + version: 0.1.3 + title: Reliability Growth Analysis + maintainer: Paul Govan + description: Modeling and plotting functions for Reliability Growth Analysis (RGA). + Models include the Duane (1962) , Non-Homogeneous + Poisson Process (NHPP) by Crow (1975) , + Piecewise Weibull NHPP by Guo et al. (2010) , and + Piecewise Weibull NHPP with Change Point Detection based on the 'segmented' package + by Muggeo (2024) . + date_publication: '2024-11-16' + bug_reports: https://github.com/paulgovan/ReliaGrowR/issues + url: https://paulgovan.github.io/ReliaGrowR/ + url_cran: https://CRAN.R-project.org/package=ReliaGrowR + url_git: https://github.com/paulgovan/ReliaGrowR +relimp: + version: 1.0-5 + title: Relative Contribution of Effects in a Regression Model + maintainer: David Firth + description: Functions to facilitate inference on the relative importance of predictors + in a linear or generalized linear model, and a couple of useful Tcl/Tk widgets. + date_publication: '2016-03-30' + bug_reports: '' + url: http://warwick.ac.uk/relimp + url_cran: https://CRAN.R-project.org/package=relimp + url_git: '' +RelimpPCR: + version: 0.3.0 + title: Relative Importance PCA Regression + maintainer: Michael Hernandez + description: 'Performs Principal Components Analysis (also known as PCA) dimensionality + reduction in the context of a linear regression. In most cases, PCA dimensionality + reduction is performed independent of the response variable for a regression. + This captures the majority of the variance of the model''s predictors, but may + not actually be the optimal dimensionality reduction solution for a regression + against the response variable. An alternative method, optimized for a regression + against the response variable, is to use both PCA and a relative importance measure. + This package applies PCA to a given data frame of predictors, and then calculates + the relative importance of each PCA factor against the response variable. It outputs + ordered factors that are optimized for model fit. By performing dimensionality + reduction with this method, an individual can achieve a the same r-squared value + as performing just PCA, but with fewer PCA factors. References: Yuri Balasanov + (2017) .' + date_publication: '2023-06-01' + bug_reports: https://github.com/mhernan88/RelimpPCR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RelimpPCR + url_git: https://github.com/mhernan88/RelimpPCR +relliptical: + version: 1.3.0 + title: The Truncated Elliptical Family of Distributions + maintainer: Katherine A. L. Valeriano + description: |- + It offers random numbers generation from members of the truncated multivariate elliptical family of distribution such as the truncated versions of the Normal, Student-t, Laplace, Pearson VII, Slash, Logistic, among others. Particular distributions can be provided by specifying the density generating function. It also computes the first two moments (covariance matrix as well) for some particular distributions. + References used for this package: Galarza, C. E., Matos, L. A., Castro, L. M., and Lachos, V. H. (2022). Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution. Journal of Multivariate Analysis, 189, 104944 ; Ho, H. J., Lin, T. I., Chen, H. Y., and Wang, W. L. (2012). Some results on the truncated multivariate t distribution. Journal of Statistical Planning and Inference, 142(1), 25-40 ; Valeriano, K. A., Galarza, C. E., and Matos, L. A. (2021). Moments and random number generation for the truncated elliptical family of distributions. Statistics and Computing, 33(1), 32 . + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relliptical + url_git: '' +relMix: + version: 1.4.1 + title: Relationship Inference for DNA Mixtures + maintainer: Guro Dorum + description: |- + Analysis of DNA mixtures involving relatives by computation of likelihood ratios that account for dropout and drop-in, mutations, silent alleles and population + substructure. This is useful in kinship cases, like non-invasive prenatal paternity testing, where deductions about individuals' relationships rely on DNA mixtures, + and in criminal cases where the contributors to a mixed DNA stain may be related. Relationships are represented + by pedigrees and can include kinship between more than two individuals. The main function is relMix() and its graphical user interface relMixGUI(). + The implementation and method is described in Dorum et al. (2017) , Hernandis et al. (2019) + and Kaur et al. (2016) . + date_publication: '2025-01-13' + bug_reports: '' + url: https://gdorum.github.io/relMix/ + url_cran: https://CRAN.R-project.org/package=relMix + url_git: '' +relSim: + version: 1.0.0 + title: Relative Simulator + maintainer: James M. Curran + description: A set of tools to explore the behaviour statistics used for forensic + DNA interpretation when close relatives are involved. The package also offers + some useful tools for exploring other forensic DNA situations. + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relSim + url_git: '' +relsurv: + version: 2.3-2 + title: Relative Survival + maintainer: Damjan Manevski + description: Contains functions for analysing relative survival data, including + nonparametric estimators of net (marginal relative) survival, relative survival + ratio, crude mortality, methods for fitting and checking additive and multiplicative + regression models, transformation approach, methods for dealing with population + mortality tables. Work has been described in Pohar Perme, Pavlic (2018) . + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=relsurv + url_git: '' +rem: + version: 1.3.1 + title: Relational Event Models (REM) + maintainer: Laurence Brandenberger + description: 'Calculate endogenous network effects in event sequences and fit relational + event models (REM): Using network event sequences (where each tie between a sender + and a target in a network is time-stamped), REMs can measure how networks form + and evolve over time. Endogenous patterns such as popularity effects, inertia, + similarities, cycles or triads can be calculated and analyzed over time.' + date_publication: '2018-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rem + url_git: '' +rema: + version: 0.0.1 + title: Rare Event Meta Analysis + maintainer: Brinley N. Zabriskie + description: |- + The rema package implements a permutation-based approach for binary + meta-analyses of 2x2 tables, founded on conditional logistic regression, + that provides more reliable statistical tests when heterogeneity is + observed in rare event data (Zabriskie et al. 2021 ). + To adjust for the effect of heterogeneity, this method conditions on the + sufficient statistic of a proxy for the heterogeneity effect as opposed to + estimating the heterogeneity variance. While this results in the model not + strictly falling under the random-effects framework, it is akin to a + random-effects approach in that it assumes differences in variability due + to treatment. Further, this method does not rely on large-sample + approximations or continuity corrections for rare event data. This method + uses the permutational distribution of the test statistic instead of + asymptotic approximations for inference. The number of observed events + drives the computation complexity for creating this permutational + distribution. Accordingly, for this method to be computationally feasible, + it should only be applied to meta-analyses with a relatively low number of + observed events. To create this permutational distribution, a network + algorithm, based on the work of Mehta et al. (1992) + and Corcoran et al. (2001) , is + employed using C++ and integrated into the package. + date_publication: '2021-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rema + url_git: '' +remaCor: + version: 0.0.18 + title: Random Effects Meta-Analysis for Correlated Test Statistics + maintainer: Gabriel Hoffman + description: Meta-analysis is widely used to summarize estimated effects sizes across + multiple statistical tests. Standard fixed and random effect meta-analysis methods + assume that the estimated of the effect sizes are statistically independent. Here + we relax this assumption and enable meta-analysis when the correlation matrix + between effect size estimates is known. Fixed effect meta-analysis uses the method + of Lin and Sullivan (2009) , and random effects + meta-analysis uses the method of Han, et al. . + date_publication: '2024-02-08' + bug_reports: https://github.com/DiseaseNeurogenomics/remaCor/issues + url: https://diseaseneurogenomics.github.io/remaCor/ + url_cran: https://CRAN.R-project.org/package=remaCor + url_git: '' +remap: + version: 0.3.2 + title: Regional Spatial Modeling with Continuous Borders + maintainer: Jadon Wagstaff + description: |- + Automatically creates separate regression models for different spatial + regions. The prediction surface is smoothed using a regional border smoothing + method. If regional models are continuous, the resulting prediction surface is + continuous across the spatial dimensions, even at region borders. Methodology + is described in Wagstaff and Bean (2023) . + date_publication: '2025-01-09' + bug_reports: https://github.com/jadonwagstaff/remap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=remap + url_git: https://github.com/jadonwagstaff/remap +rematch: + version: 2.0.0 + title: Match Regular Expressions with a Nicer 'API' + maintainer: Gabor Csardi + description: |- + A small wrapper on 'regexpr' to extract the matches and + captured groups from the match of a regular expression to a character + vector. + date_publication: '2023-08-30' + bug_reports: https://github.com/gaborcsardi/rematch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rematch + url_git: https://github.com/gaborcsardi/rematch +rematch2: + version: 2.1.2 + title: Tidy Output from Regular Expression Matching + maintainer: Gábor Csárdi + description: |- + Wrappers on 'regexpr' and 'gregexpr' to return the match + results in tidy data frames. + date_publication: '2020-05-01' + bug_reports: https://github.com/r-lib/rematch2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rematch2 + url_git: https://github.com/r-lib/rematch2#readme +remedy: + version: 0.1.0 + title: '''RStudio'' Addins to Simplify ''Markdown'' Writing' + maintainer: Colin Fay + description: |- + An 'RStudio' addin providing shortcuts for writing in 'Markdown'. This package provides a series of + functions that allow the user to be more efficient when using 'Markdown'. For example, you can select + a word, and put it in bold or in italics, or change the alignment of elements inside you Rmd. The idea + is to map all the functionalities from 'remedy' on keyboard shortcuts, so that it provides an interface + close to what you can find in any other text editor. + date_publication: '2018-12-03' + bug_reports: https://github.com/ThinkR-open/remedy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=remedy + url_git: https://github.com/ThinkR-open/remedy +ReMFPCA: + version: 1.0.0 + title: Regularized Multivariate Functional Principal Component Analysis + maintainer: Hossein Haghbin + description: Methods and tools for implementing regularized multivariate functional + principal component analysis ('ReMFPCA') for multivariate functional data whose + variables might be observed over different dimensional domains. 'ReMFPCA' is an + object-oriented interface leveraging the extensibility and scalability of R6. + It employs a parameter vector to control the smoothness of each functional variable. + By incorporating smoothness constraints as penalty terms within a regularized + optimization framework, 'ReMFPCA' generates smooth multivariate functional principal + components, offering a concise and interpretable representation of the data. For + detailed information on the methods and techniques used in 'ReMFPCA', please refer + to Haghbin et al. (2023) . + date_publication: '2023-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReMFPCA + url_git: https://github.com/haghbinh/ReMFPCA +remify: + version: 3.2.8 + title: Processing and Transforming Relational Event History Data + maintainer: Giuseppe Arena + description: 'Efficiently processes relational event history data and transforms + them into formats suitable for other packages. The primary objective of this package + is to convert event history data into a format that integrates with the packages + in ''remverse'' and is compatible with various analytical tools (e.g., computing + network statistics, estimating tie-oriented or actor-oriented social network models). + Second, it can also transform the data into formats compatible with other packages + out of ''remverse''. The package processes the data for two types of temporal + social network models: tie-oriented modeling framework (Butts, C., 2008, ) + and actor-oriented modeling framework (Stadtfeld, C., & Block, P., 2017, ).' + date_publication: '2025-01-29' + bug_reports: https://github.com/TilburgNetworkGroup/remify/issues + url: https://tilburgnetworkgroup.github.io/remify/ + url_cran: https://CRAN.R-project.org/package=remify + url_git: '' +remindR: + version: 0.0.1 + title: Insert and Extract "Reminders" from Function Comments + maintainer: Bert Gunter + description: |- + Insert/extract text "reminders" into/from function source code + comments or as the "comment" attribute of any object. + The former can be handy in development as reminders of e.g. argument + requirements, expected objects in the calling environment, required options + settings, etc. The latter can be used to provide information of the object and + as simple manual "tooltips" for users, among other things. + date_publication: '2017-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=remindR + url_git: '' +remiod: + version: 1.0.2 + title: Reference-Based Multiple Imputation for Ordinal/Binary Response + maintainer: Tony Wang + description: |- + Reference-based multiple imputation of ordinal and binary responses under Bayesian + framework, as described in Wang and Liu (2022) . Methods for + missing-not-at-random include Jump-to-Reference (J2R), Copy Reference (CR), and Delta + Adjustment which can generate tipping point analysis. + date_publication: '2022-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=remiod + url_git: https://github.com/xsswang/remiod +REMLA: + version: 1.2.0 + title: |- + Robust Expectation-Maximization Estimation for Latent Variable + Models + maintainer: Bryan Ortiz-Torres + description: |- + Traditional latent variable models assume that the population + is homogeneous, meaning that all individuals in the population are + assumed to have the same latent structure. However, this assumption is + often violated in practice given that individuals may differ in their + age, gender, socioeconomic status, and other factors that can affect + their latent structure. The robust expectation maximization (REM) + algorithm is a statistical method for estimating the parameters of a + latent variable model in the presence of population heterogeneity as recommended by + Nieser & Cochran (2023) . The REM algorithm is based on the + expectation-maximization (EM) algorithm, but it allows for the case + when all the data are generated by the assumed data generating model. + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REMLA + url_git: https://github.com/knieser/REM +rEMM: + version: 1.2.1 + title: |- + Extensible Markov Model for Modelling Temporal Relationships + Between Clusters + maintainer: Michael Hahsler + description: |- + Implements TRACDS (Temporal Relationships + between Clusters for Data Streams), a generalization of + Extensible Markov Model (EMM). TRACDS adds a temporal or order model + to data stream clustering by superimposing a dynamically adapting + Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN + data stream clustering). Development of this + package was supported in part by NSF IIS-0948893 and R21HG005912 from + the National Human Genome Research Institute. Hahsler and Dunham (2010) . + date_publication: '2024-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rEMM + url_git: https://github.com/mhahsler/rEMM +remmy: + version: 0.1.0 + title: API Client for 'Lemmy' + maintainer: Long Nguyen + description: |- + An HTTP API client for 'Lemmy' + () in R. Code and documentation are + generated from the official 'JavaScript' client source + (). + date_publication: '2023-07-19' + bug_reports: https://github.com/long39ng/remmy/issues + url: https://long39ng.github.io/remmy/ + url_cran: https://CRAN.R-project.org/package=remmy + url_git: https://github.com/long39ng/remmy +remote: + version: 1.2.1 + title: Empirical Orthogonal Teleconnections in R + maintainer: Tim Appelhans + description: |- + Empirical orthogonal teleconnections in R. + 'remote' is short for 'R(-based) EMpirical Orthogonal TEleconnections'. + It implements a collection of functions to facilitate empirical + orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections + (EOTs) denote a regression based approach to decompose spatio-temporal + fields into a set of independent orthogonal patterns. They are quite + similar to Empirical Orthogonal Functions (EOFs) with EOTs producing + less abstract results. In contrast to EOFs, which are orthogonal in both + space and time, EOT analysis produces patterns that are orthogonal in + either space or time. + date_publication: '2016-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=remote + url_git: '' +remotePARTS: + version: 1.0.4 + title: Spatiotemporal Autoregression Analyses for Large Data Sets + maintainer: Clay Morrow + description: |2- + + These tools were created to test map-scale hypotheses about trends in large + remotely sensed data sets but any data with spatial and temporal variation + can be analyzed. Tests are conducted using the PARTS method for analyzing spatially + autocorrelated time series + (Ives et al., 2021: ). + The method's unique approach can handle extremely large data sets that other + spatiotemporal models cannot, while still appropriately accounting for + spatial and temporal autocorrelation. This is done by partitioning the data + into smaller chunks, analyzing chunks separately and then combining the + separate analyses into a single, correlated test of the map-scale hypotheses. + date_publication: '2023-09-15' + bug_reports: https://github.com/morrowcj/remotePARTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=remotePARTS + url_git: https://github.com/morrowcj/remotePARTS +remotes: + version: 2.5.0 + title: |- + R Package Installation from Remote Repositories, Including + 'GitHub' + maintainer: Gábor Csárdi + description: |- + Download and install R packages stored in 'GitHub', 'GitLab', + 'Bitbucket', 'Bioconductor', or plain 'subversion' or 'git' + repositories. This package provides the 'install_*' functions in + 'devtools'. Indeed most of the code was copied over from 'devtools'. + date_publication: '2024-03-17' + bug_reports: https://github.com/r-lib/remotes/issues + url: https://remotes.r-lib.org + url_cran: https://CRAN.R-project.org/package=remotes + url_git: https://github.com/r-lib/remotes#readme +rempsyc: + version: 0.1.9 + title: Convenience Functions for Psychology + maintainer: Rémi Thériault + description: |- + Make your workflow faster and easier. Easily customizable + plots (via 'ggplot2'), nice APA tables (following the style of the + *American Psychological Association*) exportable to Word (via + 'flextable'), easily run statistical tests or check assumptions, and + automatize various other tasks. + date_publication: '2025-02-01' + bug_reports: https://github.com/rempsyc/rempsyc/issues + url: https://rempsyc.remi-theriault.com + url_cran: https://CRAN.R-project.org/package=rempsyc + url_git: '' +remss: + version: 1.0.1 + title: Refining Evaluation Methodology on Stage System + maintainer: Yi Zhu + description: 'T (extent of the primary tumor), N (absence or presence and extent + of regional lymph node metastasis) and M (absence or presence of distant metastasis) + are three components to describe the anatomical tumor extent. TNM stage is important + in treatment decision-making and outcome predicting. The existing oropharyngeal + Cancer (OPC) TNM stages have not made distinction of the two sub sites of Human + papillomavirus positive (HPV+) and Human papillomavirus negative (HPV-) diseases. + We developed novel criteria to assess performance of the TNM stage grouping schemes + based on parametric modeling adjusting on important clinical factors. These criteria + evaluate the TNM stage grouping scheme in five different measures: hazard consistency, + hazard discrimination, explained variation, likelihood difference, and balance. + The methods are described in Xu, W., et al. (2015) .' + date_publication: '2021-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=remss + url_git: '' +remstats: + version: 3.2.4 + title: Computes Statistics for Relational Event History Data + maintainer: Giuseppe Arena + description: Computes a variety of statistics for relational event models. Relational + event models enable researchers to investigate both exogenous and endogenous factors + influencing the evolution of a time-ordered sequence of events. These models are + categorized into tie-oriented models (Butts, C., 2008, ), + where the probability of a dyad interacting next is modeled in a single step, + and actor-oriented models (Stadtfeld, C., & Block, P., 2017, ), + which first model the probability of a sender initiating an interaction and subsequently + the probability of the sender's choice of receiver. The package is designed to + compute a variety of statistics that summarize exogenous and endogenous influences + on the event stream for both types of models. + date_publication: '2025-01-29' + bug_reports: https://github.com/TilburgNetworkGroup/remstats/issues + url: https://tilburgnetworkgroup.github.io/remstats/ + url_cran: https://CRAN.R-project.org/package=remstats + url_git: '' +remstimate: + version: 2.3.13 + title: |- + Optimization Frameworks for Tie-Oriented and Actor-Oriented + Relational Event Models + maintainer: Giuseppe Arena + description: A comprehensive set of tools designed for optimizing likelihood within + a tie-oriented (Butts, C., 2008, ) or an + actor-oriented modelling framework (Stadtfeld, C., & Block, P., 2017, ) + in relational event networks. The package accommodates both frequentist and Bayesian + approaches. The frequentist approaches that the package incorporates are the Maximum + Likelihood Optimization (MLE) and the Gradient-based Optimization (GDADAMAX). + The Bayesian methodologies included in the package are the Bayesian Sampling Importance + Resampling (BSIR) and the Hamiltonian Monte Carlo (HMC). The flexibility of choosing + between frequentist and Bayesian optimization approaches allows researchers to + select the estimation approach which aligns the most with their analytical preferences. + date_publication: '2025-01-29' + bug_reports: https://github.com/TilburgNetworkGroup/remstimate/issues + url: https://tilburgnetworkgroup.github.io/remstimate/ + url_cran: https://CRAN.R-project.org/package=remstimate + url_git: '' +REN: + version: 0.1.0 + title: Regularization Ensemble for Robust Portfolio Optimization + maintainer: Bonsoo Koo + description: Portfolio optimization is achieved through a combination of regularization + techniques and ensemble methods that are designed to generate stable out-of-sample + return predictions, particularly in the presence of strong correlations among + assets. The package includes functions for data preparation, parallel processing, + and portfolio analysis using methods such as Mean-Variance, James-Stein, LASSO, + Ridge Regression, and Equal Weighting. It also provides visualization tools and + performance metrics, such as the Sharpe ratio, volatility, and maximum drawdown, + to assess the results. + date_publication: '2024-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REN + url_git: '' +rENA: + version: 0.2.7 + title: Epistemic Network Analysis + maintainer: Cody L Marquart + description: 'ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) + is a method used to identify meaningful and quantifiable patterns in discourse + or reasoning. ENA moves beyond the traditional frequency-based assessments by + examining the structure of the co-occurrence, or connections in coded data. Moreover, + compared to other methodological approaches, ENA has the novelty of (1) modeling + whole networks of connections and (2) affording both quantitative and qualitative + comparisons between different network models. Shaffer, D.W., Collier, W., & + Ruis, A.R. (2016).' + date_publication: '2024-02-23' + bug_reports: https://gitlab.com/epistemic-analytics/qe-packages/rENA/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rENA + url_git: https://gitlab.com/epistemic-analytics/qe-packages/rENA +REndo: + version: 2.4.10 + title: |- + Fitting Linear Models with Endogenous Regressors using Latent + Instrumental Variables + maintainer: Raluca Gui + description: |- + Fits linear models with endogenous regressor using latent instrumental variable approaches. + The methods included in the package are Lewbel's (1997) higher moments approach as well as + Lewbel's (2012) heteroscedasticity approach, Park and Gupta's (2012) joint estimation method + that uses Gaussian copula and Kim and Frees's (2007) multilevel generalized + method of moment approach that deals with endogeneity in a multilevel setting. + These are statistical techniques to address the endogeneity problem where no external instrumental variables are needed. + See the publication related to this package in the Journal of Statistical Software for more details: . + Note that with version 2.0.0 sweeping changes were introduced which greatly improve functionality and usability but break backwards compatibility. + date_publication: '2024-07-02' + bug_reports: https://github.com/mmeierer/REndo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=REndo + url_git: https://github.com/mmeierer/REndo +Renext: + version: 3.1-4 + title: Renewal Method for Extreme Values Extrapolation + maintainer: Yann Richet + description: |- + Peaks Over Threshold (POT) or 'methode du renouvellement'. The + distribution for the excesses can be chosen, and heterogeneous data + (including historical data or block data) can be used in a + Maximum-Likelihood framework. + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Renext + url_git: https://github.com/IRSN/Renext +renpow: + version: 0.1-1 + title: Renewable Power Systems and the Environment + maintainer: Miguel F. Acevedo + description: Supports calculations and visualization for renewable power systems + and the environment. Analysis and graphical tools for DC and AC circuits and their + use in electric power systems. Analysis and graphical tools for thermodynamic + cycles and heat engines, supporting efficiency calculations in coal-fired power + plants, gas-fired power plants. Calculations of carbon emissions and atmospheric + CO2 dynamics. Analysis of power flow and demand for the grid, as well as power + models for microgrids and off-grid systems. Provides resource and power generation + for hydro power, wind power, and solar power. + date_publication: '2018-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=renpow + url_git: '' +rentrez: + version: 1.2.3 + title: '''Entrez'' in R' + maintainer: David Winter + description: |- + Provides an R interface to the NCBI's 'EUtils' API, + allowing users to search databases like 'GenBank' + and 'PubMed' + , process the + results of those searches and pull data into their R sessions. + date_publication: '2020-11-10' + bug_reports: https://github.com/ropensci/rentrez/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=rentrez + url_git: https://docs.ropensci.org/rentrez/(website)https://github.com/ropensci/rentrez/ +renv: + version: 1.1.1 + title: Project Environments + maintainer: Kevin Ushey + description: |- + A dependency management toolkit for R. Using 'renv', you can create + and manage project-local R libraries, save the state of these libraries to + a 'lockfile', and later restore your library as required. Together, these + tools can help make your projects more isolated, portable, and reproducible. + date_publication: '2025-02-07' + bug_reports: https://github.com/rstudio/renv/issues + url: https://rstudio.github.io/renv/ + url_cran: https://CRAN.R-project.org/package=renv + url_git: https://github.com/rstudio/renv +Renvlp: + version: 3.4.5 + title: Computing Envelope Estimators + maintainer: Minji Lee + description: Provides a general routine, envMU, which allows estimation of the + M envelope of span(U) given root n consistent estimators of M and U. The routine + envMU does not presume a model. This package implements response envelopes, partial + response envelopes, envelopes in the predictor space, heteroscedastic envelopes, simultaneous + envelopes, scaled response envelopes, scaled envelopes in the predictor space, groupwise + envelopes, weighted envelopes, envelopes in logistic regression, envelopes in + Poisson regression envelopes in function-on-function linear regression, envelope-based + Partial Partial Least Squares, envelopes with non-constant error covariance, + envelopes with t-distributed errors, reduced rank envelopes and reduced rank envelopes + with non-constant error covariance. For each of these model-based routines the + package provides inference tools including bootstrap, cross validation, estimation + and prediction, hypothesis testing on coefficients are included except for weighted + envelopes. Tools for selection of dimension include AIC, BIC and likelihood ratio + testing. Background is available at Cook, R. D., Forzani, L. and Su, Z. (2016) + . Optimization is based on a clockwise coordinate + descent algorithm. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Renvlp + url_git: '' +RenvModule: + version: '1.1' + title: |- + Interface to Allow Full Use of the Environment Modules System + for Unix + maintainer: Jordan Hayes + description: Provides environment modules functionality, which enables use of the + Environment Modules system () from within the + R environment. By default the user's login shell environment (ie. "bash -l") will + be used to initialize the current session. The module function can also; load + or unload specific software, list all the loaded software within the current session, + and list all the applications available for loading from the module system. Lastly, + the module function can remove all loaded software from the current session. + date_publication: '2021-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RenvModule + url_git: '' +renz: + version: 0.2.1 + title: R-Enzymology + maintainer: Juan Carlos Aledo + description: |- + Contains utilities for the analysis of Michaelian kinetic data. Beside the classical linearization + methods (Lineweaver-Burk, Eadie-Hofstee, Hanes-Woolf and Eisenthal-Cornish-Bowden), features include the + ability to carry out weighted regression analysis that, in most cases, substantially improves the estimation + of kinetic parameters (Aledo (2021) ). To avoid data transformation and the potential + biases introduced by them, the package also offers functions to directly fitting data to the Michaelis-Menten + equation, either using ([S], v) or (time, [S]) data. Utilities to simulate substrate progress-curves (making + use of the Lambert W function) are also provided. The package is accompanied of vignettes that aim to orientate + the user in the choice of the most suitable method to estimate the kinetic parameter of an Michaelian enzyme. + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=renz + url_git: '' +repairData: + version: 0.1.0 + title: Open Repair Alliance Datasets 2021 + maintainer: Peter Baumgartner + description: |- + The complete data set of open repair data, full compliant with the Open Repair Data Standards (ORDS). + It combines the datasets contributed by partner organizations of the Open Repair Alliance (ORA). Last updated: 2021-02-22. + The package also contains via quests enriched datasets on batteries, + printer, mobiles, and tablets. + date_publication: '2021-10-21' + bug_reports: https://github.com/petzi53/repairData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=repairData + url_git: https://github.com/petzi53/repairData +repana: + version: 2.2.1 + title: Repeatable Analysis in R + maintainer: John J. Aponte + description: |- + Set of utilities to facilitate the reproduction of analysis in R. + It allow to make_structure(), clean_structure(), and run and log programs in a + predefined order to allow secondary files, analysis and reports be constructed in + an ordered and reproducible form. + date_publication: '2025-02-21' + bug_reports: https://github.com/johnaponte/repana/issues + url: https://johnaponte.github.io/repana/ + url_cran: https://CRAN.R-project.org/package=repana + url_git: https://github.com/johnaponte/repana +RepaymentPlan: + version: 0.1.0 + title: Calculation of Mortgage Plan or Repayment Plan + maintainer: Gourav Kumar Vani + description: The function RepaymentPlan() calculates repayment schedule for repayment/mortgage + plans. + date_publication: '2019-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RepaymentPlan + url_git: '' +repeated: + version: 1.1.10 + title: Non-Normal Repeated Measurements Models + maintainer: Bruce Swihart + description: |- + Various functions to fit models for non-normal repeated + measurements, such as Binary Random Effects Models with Two Levels of Nesting, + Bivariate Beta-binomial Regression Models, Marginal Bivariate Binomial Regression Models, + Cormack capture-recapture models, Continuous-time Hidden Markov Chain Models, + Discrete-time Hidden Markov Chain Models, + Changepoint Location Models using a Continuous-time Two-state Hidden Markov Chain, + generalized nonlinear autoregression models, multivariate Gaussian copula models, + generalized non-linear mixed models with one random effect, + generalized non-linear mixed models using h-likelihood for one random effect, + Repeated Measurements Models for Counts with Frailty or Serial Dependence, + Repeated Measurements Models for Continuous Variables with Frailty or Serial Dependence, + Ordinal Random Effects Models with Dropouts, marginal homogeneity models for square + contingency tables, correlated negative binomial models with Kalman update. + References include Lindsey's text books, + JK Lindsey (2001) and JK Lindsey (1999) . + date_publication: '2024-10-02' + bug_reports: https://github.com/swihart/repeated/issues + url: https://www.commanster.eu/rcode.html + url_cran: https://CRAN.R-project.org/package=repeated + url_git: '' +RepeatedHighDim: + version: 2.3.0 + title: Methods for High-Dimensional Repeated Measures Data + maintainer: Klaus Jung + description: |- + A toolkit for the analysis of high-dimensional repeated measurements, providing functions + for outlier detection, differential expression analysis, gene-set tests, and binary random data generation. + date_publication: '2024-04-25' + bug_reports: '' + url: https://software.klausjung-lab.de + url_cran: https://CRAN.R-project.org/package=RepeatedHighDim + url_git: '' +repec: + version: 0.1.0 + title: Access RePEc Data Through API + maintainer: Christian Alexander Mongeau Ospina + description: |- + Utilities for accessing RePEc (Research Papers in Economics) + through a RESTful API. You can request a code and get detailed + information at the following page: . + date_publication: '2018-08-31' + bug_reports: https://github.com/chrMongeau/repec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=repec + url_git: https://github.com/chrMongeau/repec +repello: + version: 1.0.1 + title: Reports from Trello in R + maintainer: Andrew Guide + description: |- + Creates reports from Trello, a collaborative, project organization + and list-making application. + Reports are created by comparing individual Trello board + cards from two different points in time and documenting any changes made + to the cards. + date_publication: '2021-01-14' + bug_reports: https://github.com/thomasgstewart/repello/issues + url: '' + url_cran: https://CRAN.R-project.org/package=repello + url_git: https://github.com/thomasgstewart/repello +RepertoiR: + version: 0.0.1 + title: Repertoire Graphical Visualization + maintainer: Ido Hasson + description: |- + Visualization platform for T cell receptor repertoire + analysis output results. It includes comparison of sequence frequency + among samples, network of similar sequences and convergent + recombination source between species. Currently repertoire analysis is + in early stage of development and requires new approaches for + repertoire data examination and assessment as we intend to develop. + No publication is available yet (will be available in the near + future), Efroni (2021) . + date_publication: '2021-10-25' + bug_reports: https://github.com/systemsbiomed/RepertoiR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RepertoiR + url_git: https://github.com/systemsbiomed/RepertoiR +repfdr: + version: 1.2.3 + title: Replicability Analysis for Multiple Studies of High Dimension + maintainer: Ruth Heller + description: |- + Estimation of Bayes and local Bayes false discovery rates for + replicability analysis (Heller & Yekutieli, 2014 ; + Heller at al., 2015 ). + date_publication: '2017-09-28' + bug_reports: https://github.com/barakbri/repfdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=repfdr + url_git: https://github.com/barakbri/repfdr +replacer: + version: 1.0.2 + title: A Value Replacement Utility + maintainer: Bandur Dragos + description: |- + Updates values within csv format data files using a custom, User-built + csv format lookup file. Based on 'data.table' package. + date_publication: '2022-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=replacer + url_git: '' +REPLesentR: + version: 0.4.1 + title: Presentations in the REPL + maintainer: Sebastian Warnholz + description: |- + Create presentations and display them inside the R 'REPL' + (Read-Eval-Print loop), aka the R console. Presentations can be written in + 'RMarkdown' or any other text format. A set of convenient navigation options + as well as code evaluation during a presentation is provided. It is great + for tech talks with live coding examples and tutorials. While this is not a + replacement for standard presentation formats, it's old-school looks might + just be what sets it apart. This project has been inspired by the + 'REPLesent' project for presentations in the 'Scala' 'REPL'. + date_publication: '2019-11-26' + bug_reports: https://github.com/wahani/REPLesentR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=REPLesentR + url_git: '' +Replicate: + version: 1.2.0 + title: Statistical Metrics for Multisite Replication Studies + maintainer: Maya B. Mathur + description: |- + For a multisite replication project, computes the consistency metric P_orig, which is + the probability that the original study would observe an estimated effect size as extreme or more extreme + than it actually did, if in fact the original study were statistically consistent with the replications. Other + recommended metrics are: (1) the probability of a true effect of scientifically meaningful size in the same direction as the estimate + the original study; and (2) the probability of a true effect of meaningful size in the direction opposite + the original study's estimate. These two can be computed using the package \code{MetaUtility::prop_stronger}. + Additionally computes older metrics used in replication projects (namely expected agreement in "statistical significance" between an original study and replication studies as well + as prediction intervals for the replication estimates). See Mathur and VanderWeele (under review; ) + for details. + date_publication: '2019-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Replicate + url_git: '' +replicateBE: + version: 1.1.3 + title: Average Bioequivalence with Expanding Limits (ABEL) + maintainer: Helmut Schütz + description: |- + Performs comparative bioavailability calculations for Average + Bioequivalence with Expanding Limits (ABEL). Implemented are 'Method A' / + 'Method B' and the detection of outliers. If the design allows, assessment + of the empiric Type I Error and iteratively adjusting alpha to control the + consumer risk. Average Bioequivalence - optionally with a tighter (narrow + therapeutic index drugs) or wider acceptance range (South Africa: Cmax) - + is implemented as well. + date_publication: '2022-05-02' + bug_reports: https://github.com/Helmut01/replicateBE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=replicateBE + url_git: https://github.com/Helmut01/replicateBE +replicatedpp2w: + version: 0.1-5 + title: Two-Way ANOVA-Like Method to Analyze Replicated Point Patterns + maintainer: Marcelino de la Cruz + description: Test for effects of both individual factors and their interaction + on replicated spatial patterns in a two factorial design, as explained in Ramon + et al. (2016) . + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=replicatedpp2w + url_git: '' +ReplicationSuccess: + version: 1.3.3 + title: Design and Analysis of Replication Studies + maintainer: Samuel Pawel + description: |- + Provides utilities for the design and analysis of replication + studies. Features both traditional methods based on statistical + significance and more recent methods such as the sceptical p-value; + Held L. (2020) , Held et al. (2022) + , Micheloud et al. (2023) . + Also provides related methods including the harmonic mean chi-squared + test; Held, L. (2020) , and intrinsic + credibility; Held, L. (2019) . Contains + datasets from five large-scale replication projects. + date_publication: '2024-10-22' + bug_reports: https://github.com/crsuzh/ReplicationSuccess/issues/ + url: https://crsuzh.github.io/ReplicationSuccess/ + url_cran: https://CRAN.R-project.org/package=ReplicationSuccess + url_git: '' +Repliscope: + version: 1.1.1 + title: Replication Timing Profiling using DNA Copy Number + maintainer: Dzmitry G Batrakou + description: 'Create, Plot and Compare Replication Timing Profiles. The method is + described in Muller et al., (2014) .' + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Repliscope + url_git: '' +repmis: + version: '0.5' + title: Miscellaneous Tools for Reproducible Research + maintainer: Christopher Gandrud + description: |- + Tools to load 'R' packages + and automatically generate BibTeX files citing them as well as load and + cache plain-text and 'Excel' formatted data stored on 'GitHub', and + from other sources. + date_publication: '2016-02-07' + bug_reports: https://github.com/christophergandrud/repmis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=repmis + url_git: '' +repmod: + version: 0.1.7 + title: Create Report Table from Different Objects + maintainer: David Hervas Marin + description: |- + Tools for generating descriptives and report tables for different models, + data.frames and tables and exporting them to different formats. + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=repmod + url_git: '' +repo: + version: 2.1.5 + title: A Data-Centered Data Flow Manager + maintainer: Francesco Napolitano + description: |- + A data manager meant to avoid manual storage/retrieval of + data to/from the file system. It builds one (or more) centralized + repository where R objects are stored with rich annotations, + including corresponding code chunks, and easily searched and + retrieved. See Napolitano (2017) for further + information. + date_publication: '2020-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=repo + url_git: '' +RepoGenerator: + version: 0.0.1 + title: |- + Generates a Project and Repo for Easy Initialization of a + Workshop + maintainer: Jared P. Lander + description: Generates a project and repo for easy initialization of a GitHub repo + for R workshops. The repo includes a README with instructions to ensure that all + users have the needed packages, an 'RStudio' project with the right directories + and the proper data. The repo can then be used for hosting code taught during + the workshop. + date_publication: '2018-06-19' + bug_reports: https://github.com/jaredlander/RepoGenerator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RepoGenerator + url_git: https://github.com/jaredlander/RepoGenerator +repolr: + version: '3.4' + title: Repeated Measures Proportional Odds Logistic Regression + maintainer: Nick Parsons + description: Fits linear models to repeated ordinal scores using GEE methodology. + date_publication: '2016-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=repolr + url_git: '' +report: + version: 0.6.1 + title: Automated Reporting of Results and Statistical Models + maintainer: Rémi Thériault + description: |- + The aim of the 'report' package is to bridge the gap between + R’s output and the formatted results contained in your manuscript. + This package converts statistical models and data frames into textual + reports suited for publication, ensuring standardization and quality + in results reporting. + date_publication: '2025-02-07' + bug_reports: https://github.com/easystats/report/issues + url: https://easystats.github.io/report/ + url_cran: https://CRAN.R-project.org/package=report + url_git: '' +reporter: + version: 1.4.4 + title: Creates Statistical Reports + maintainer: David Bosak + description: |- + Contains functions to create regulatory-style statistical reports. + Originally designed to create tables, listings, and figures for the + pharmaceutical, biotechnology, and medical device industries, these + reports are generalized enough that they could be used in any industry. + Generates text, rich-text, PDF, HTML, and Microsoft Word file formats. + The package specializes + in printing wide and long tables with automatic page wrapping and splitting. + Reports can be produced with a minimum of function calls, and without + relying on other table packages. The package supports titles, footnotes, + page header, page footers, spanning headers, page by variables, + and automatic page numbering. + date_publication: '2024-03-19' + bug_reports: https://github.com/dbosak01/reporter/issues + url: https://reporter.r-sassy.org + url_cran: https://CRAN.R-project.org/package=reporter + url_git: https://github.com/dbosak01/reporter +repoRter.nih: + version: 0.1.4 + title: R Interface to the 'NIH RePORTER Project' API + maintainer: '"Michael Barr, ACAS, MAAA, CPCU"' + description: |- + Methods to easily build requests in the non-standard JSON + schema required by the National Institute of Health (NIH)'s 'RePORTER + Project API' . + Also retrieve and process result sets as either a ragged or flattened 'tibble'. + date_publication: '2023-01-15' + bug_reports: https://github.com/bikeactuary/repoRter.nih/issues + url: '' + url_cran: https://CRAN.R-project.org/package=repoRter.nih + url_git: https://github.com/bikeactuary/repoRter.nih +ReporterScore: + version: 0.1.9 + title: |- + Generalized Reporter Score-Based Enrichment Analysis for Omics + Data + maintainer: Chen Peng + description: |- + Inspired by the classic 'RSA', we developed the improved 'Generalized Reporter + Score-based Analysis (GRSA)' method, implemented in the R package 'ReporterScore', along + with comprehensive visualization methods and pathway databases. 'GRSA' is a threshold-free + method that works well with all types of biomedical features, such as genes, chemical compounds, + and microbial species. Importantly, the 'GRSA' supports multi-group and longitudinal experimental + designs, because of the included multi-group-compatible statistical methods. + date_publication: '2024-11-28' + bug_reports: https://github.com/Asa12138/ReporterScore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ReporterScore + url_git: https://github.com/Asa12138/ReporterScore +reportfactory: + version: 0.4.0 + title: |- + Lightweight Infrastructure for Handling Multiple R Markdown + Documents + maintainer: Tim Taylor + description: |- + Provides an infrastructure for handling multiple R Markdown + reports, including automated curation and time-stamping of outputs, + parameterisation and provision of helper functions to manage dependencies. + date_publication: '2021-08-09' + bug_reports: https://github.com/reconverse/reportfactory/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reportfactory + url_git: https://github.com/reconverse/reportfactory +reportr: + version: 1.3.0 + title: A General Message and Error Reporting System + maintainer: Jon Clayden + description: Provides a system for reporting messages, which provides certain useful + features over the standard R system, such as the incorporation of output consolidation, + message filtering, assertions, expression substitution, automatic generation of + stack traces for debugging, and conditional reporting based on the current "output + level". + date_publication: '2018-10-26' + bug_reports: https://github.com/jonclayden/reportr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reportr + url_git: https://github.com/jonclayden/reportr +reportReg: + version: 0.3.0 + title: An Easy Way to Report Regression Analysis + maintainer: Zhicheng Du + description: |- + Provides an easy way to report the results of regression analysis, including: + 1. Proportional hazards regression from function 'coxph' of package 'survival'; + 2. Conditional logistic regression from function 'clogit' of package 'survival'; + 3. Ordered logistic regression from function 'polr' of package 'MASS'; + 4. Binary logistic regression from function 'glm' of package 'stats'; + 5. Linear regression from function 'lm' of package 'stats'; + 6. Risk regression model for survival analysis with competing risks from function 'FGR' of package 'riskRegression'; + 7. Multilevel model from function 'lme' of package 'nlme'. + date_publication: '2018-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reportReg + url_git: '' +reportRmd: + version: 0.1.1 + title: Tidy Presentation of Clinical Reporting + maintainer: Lisa Avery + description: |- + Streamlined statistical reporting in 'Rmarkdown' environments. + Facilitates the automated reporting of descriptive statistics, multiple + univariate models, multivariable models and tables combining these outputs. + Plotting functions include customisable survival curves, forest plots from + logistic and ordinal regression and bivariate comparison plots. + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reportRmd + url_git: '' +reportROC: + version: '3.6' + title: An Easy Way to Report ROC Analysis + maintainer: Zhicheng Du + description: |- + Provides an easy way to report the results of ROC analysis, including: + 1. an ROC curve. + 2. the value of Cutoff, AUC (Area Under Curve), ACC (accuracy), + SEN (sensitivity), SPE (specificity), + PLR (positive likelihood ratio), NLR (negative likelihood ratio), + PPV (positive predictive value), NPV (negative predictive value), + PPA (percentage of positive accordance), NPA (percentage of negative accordance), TPA (percentage of total accordance), + KAPPA (kappa value). + date_publication: '2022-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reportROC + url_git: '' +ReportSubtotal: + version: 0.1.2 + title: Adds Subtotals to Data Reports + maintainer: Yoni Aboody + description: Adds subtotal rows / sections (a la the 'SAS' 'Proc Tabulate' All option) + to a Group By output by running a series of Group By functions with partial sets + of the same variables and combining the results with the original. Can be used + to add comprehensive information to a data report or to quickly aggregate Group + By outputs used to gain a greater understanding of data. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReportSubtotal + url_git: '' +reporttools: + version: 1.1.3 + title: Generate "LaTeX"" Tables of Descriptive Statistics + maintainer: Kaspar Rufibach + description: These functions are especially helpful when writing reports of data + analysis using "Sweave". + date_publication: '2021-10-12' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=reporttools + url_git: '' +REPPlab: + version: 0.9.6 + title: |- + R Interface to 'EPP-Lab', a Java Program for Exploratory + Projection Pursuit + maintainer: Daniel Fischer + description: |- + An R Interface to 'EPP-lab' v1.0. 'EPP-lab' is a Java program for + projection pursuit using genetic algorithms written by Alain Berro and S. Larabi + Marie-Sainte and is included in the package. + date_publication: '2023-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REPPlab + url_git: '' +REPPlabShiny: + version: 0.4.2 + title: '''REPPlab'' via a Shiny Application' + maintainer: Klaus Nordhausen + description: Performs exploratory projection pursuit via 'REPPlab' (Daniel Fischer, + Alain Berro, Klaus Nordhausen & Anne Ruiz-Gazen (2019) ) + using a Shiny app. + date_publication: '2023-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REPPlabShiny + url_git: '' +repr: + version: 1.1.7 + title: Serializable Representations + maintainer: Philipp Angerer + description: |- + String and binary representations of objects for several formats / + mime types. + date_publication: '2024-03-22' + bug_reports: https://github.com/IRkernel/repr/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=repr + url_git: https://github.com/IRkernel/repr/ +represent: + version: 1.0.1 + title: Determine How Representative Two Multidimensional Data Sets are + maintainer: Harmen Draisma + description: 'Compute the values of various parameters evaluating how similar two + multidimensional datasets'' structures are in multidimensional space, as described + in: Jouan-Rimbaud, D., Massart, D. L., Saby, C. A., Puel, C. (1998), . + The computed parameters evaluate three properties, namely, the direction of the + data sets, the variance-covariance of the data points, and the location of the + data sets'' centroids. The package contains workhorse function jrparams(), as + well as two helper functions Mboxtest() and JRsMahaldist(), and four example data + sets.' + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=represent + url_git: '' +representr: + version: 0.1.5 + title: Create Representative Records After Entity Resolution + maintainer: Andee Kaplan + description: An implementation of Kaplan, Betancourt, Steorts (2022) + that creates representative records for use in downstream tasks after entity resolution + is performed. Multiple methods for creating the representative records (data sets) + are provided. + date_publication: '2023-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=representr + url_git: '' +represtools: + version: 0.1.3 + title: Reproducible Research Tools + maintainer: Brian Fannin + description: |- + Reproducible research tools automates the creation of an analysis directory structure and work flow. There are R markdown + skeletons which encapsulate typical analytic work flow steps. Functions will create appropriate modules which may + pass data from one step to another. + date_publication: '2019-10-03' + bug_reports: https://github.com/PirateGrunt/represtools/issues + url: https://pirategrunt.com/represtools/ + url_cran: https://CRAN.R-project.org/package=represtools + url_git: '' +reprex: + version: 2.1.1 + title: Prepare Reproducible Example Code via the Clipboard + maintainer: Jennifer Bryan + description: |- + Convenience wrapper that uses the 'rmarkdown' package to + render small snippets of code to target formats that include both code + and output. The goal is to encourage the sharing of small, + reproducible, and runnable examples on code-oriented websites, such as + and , or in email. The + user's clipboard is the default source of input code and the default + target for rendered output. 'reprex' also extracts clean, runnable R + code from various common formats, such as copy/paste from an R + session. + date_publication: '2024-07-06' + bug_reports: https://github.com/tidyverse/reprex/issues + url: https://reprex.tidyverse.org + url_cran: https://CRAN.R-project.org/package=reprex + url_git: https://github.com/tidyverse/reprex +reproducer: + version: 0.5.3 + title: Reproduce Statistical Analyses and Meta-Analyses + maintainer: Lech Madeyski + description: |- + Includes data analysis and meta-analysis functions (e.g., to + calculate effect sizes and 95% Confidence Intervals (CI) on Standardised + Effect Sizes (d) for AB/BA cross-over repeated-measures experimental + designs), data presentation functions (e.g., density curve overlaid on + histogram),and the data sets analyzed in different research papers in + software engineering (e.g., related to software defect prediction or multi- + site experiment concerning the extent to which structured abstracts were + clearer and more complete than conventional abstracts) to streamline + reproducible research in software engineering. + date_publication: '2023-10-18' + bug_reports: '' + url: https://madeyski.e-informatyka.pl/reproducible-research/ + url_cran: https://CRAN.R-project.org/package=reproducer + url_git: '' +reproducible: + version: 2.1.2 + title: Enhance Reproducibility of R Code + maintainer: Eliot J B McIntire + description: |- + A collection of high-level, machine- and OS-independent tools + for making reproducible and reusable content in R. + The two workhorse functions are Cache() and prepInputs(). Cache() + allows for nested caching, is robust to environments and objects with + environments (like functions), and deals with some classes of + file-backed R objects e.g., from terra and raster packages. + Both functions have been developed to + be foundational components of data retrieval + and processing in continuous workflow situations. In both functions, + efforts are made to make the first and subsequent calls of functions have + the same result, but faster at subsequent times by way of checksums + and digesting. Several features are still under development, including + cloud storage of cached objects allowing for sharing between users. Several + advanced options are available, see ?reproducibleOptions(). + date_publication: '2024-12-12' + bug_reports: https://github.com/PredictiveEcology/reproducible/issues + url: https://reproducible.predictiveecology.org + url_cran: https://CRAN.R-project.org/package=reproducible + url_git: https://github.com/PredictiveEcology/reproducible +reproducibleRchunks: + version: 1.0.3 + title: Automated Reproducibility Checks for R Markdown Documents + maintainer: Andreas M. Brandmaier + description: Provide reproducible R chunks in R Markdown document that automatically + check computational results for reproducibility. This is achieved by creating + json files storing metadata about computational results. A comprehensive tutorial + to the package is available as preprint by Brandmaier & Peikert (2024, ). + date_publication: '2025-02-26' + bug_reports: https://github.com/brandmaier/reproducibleRchunks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reproducibleRchunks + url_git: '' +reproj: + version: 0.7.0 + title: Coordinate System Transformations for Generic Map Data + maintainer: Michael D. Sumner + description: |- + Transform coordinates from a specified source to a specified + target map projection. This uses the 'PROJ' library directly, by wrapping the + 'PROJ' package which leverages 'libproj', otherwise the 'proj4' package. The 'reproj()' + function is generic, methods may be added to remove the need for an explicit + source definition. If 'proj4' is in use 'reproj()' handles the requirement for + conversion of angular units where necessary. This is for use primarily to + transform generic data formats and direct leverage of the underlying + 'PROJ' library. (There are transformations that aren't possible with 'PROJ' and + that are provided by the 'GDAL' library, a limitation which users of this + package should be aware of.) The 'PROJ' library is available at + . + date_publication: '2024-06-11' + bug_reports: https://github.com/hypertidy/reproj/issues + url: https://hypertidy.github.io/reproj/ + url_cran: https://CRAN.R-project.org/package=reproj + url_git: https://github.com/hypertidy/reproj +repsd: + version: 1.0.1 + title: Root Expected Proportion Squared Difference for Detecting DIF + maintainer: Anthony William Raborn + description: |- + Root Expected Proportion Squared Difference (REPSD) is a nonparametric + differential item functioning (DIF) method that (a) allows practitioners + to explore for DIF related to small, fine-grained focal groups of examinees, + and (b) compares the focal group directly to the composite group that will be + used to develop the reported test score scale. Using your provided response + matrix with a column that identifies focal group membership, this package + provides the REPSD values, a simulated null distribution of possible REPSD + values, and the simulated p-values identifying items possibly displaying DIF + without requiring enormous sample sizes. + date_publication: '2023-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=repsd + url_git: '' +REPTILE: + version: '1.0' + title: Regulatory DNA Element Prediction + maintainer: Yupeng He + description: Predicting regulatory DNA elements based on epigenomic signatures. + This package is more of a set of building blocks than a direct solution. REPTILE + regulatory prediction pipeline is built on this R package. See + for more information. + date_publication: '2016-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REPTILE + url_git: https://github.com/yupenghe/REPTILE +repurrrsive: + version: 1.1.0 + title: Examples of Recursive Lists and Nested or Split Data Frames + maintainer: Jennifer Bryan + description: |- + Recursive lists in the form of R objects, 'JSON', and 'XML', + for use in teaching and examples. Examples include color palettes, + Game of Thrones characters, 'GitHub' users and repositories, music + collections, and entities from the Star Wars universe. Data from the + 'gapminder' package is also included, as a simple data frame and in + nested and split forms. + date_publication: '2022-12-17' + bug_reports: https://github.com/jennybc/repurrrsive/issues + url: https://jennybc.github.io/repurrrsive/ + url_cran: https://CRAN.R-project.org/package=repurrrsive + url_git: https://github.com/jennybc/repurrrsive +reqres: + version: 0.2.5 + title: Powerful Classes for HTTP Requests and Responses + maintainer: Thomas Lin Pedersen + description: |- + In order to facilitate parsing of http requests and creating + appropriate responses this package provides two classes to handle a lot of + the housekeeping involved in working with http exchanges. The infrastructure + builds upon the 'rook' specification and is thus well suited to be combined + with 'httpuv' based web servers. + date_publication: '2022-08-19' + bug_reports: https://github.com/thomasp85/reqres/issues + url: https://reqres.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=reqres + url_git: https://github.com/thomasp85/reqres#reqres +REQS: + version: 0.8-13 + title: R/EQS Interface + maintainer: Patrick Mair + description: 'Contains the function run.eqs() which calls an EQS script file, executes + the EQS estimation, and, finally, imports the results as R objects. These two + steps can be performed separately: call.eqs() calls and executes EQS, whereas + read.eqs() imports existing EQS outputs as objects into R. It requires EQS 6.2 + (build 98 or higher).' + date_publication: '2022-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=REQS + url_git: '' +request: + version: 0.1.0 + title: High Level 'HTTP' Client + maintainer: Scott Chamberlain + description: |- + High level and easy 'HTTP' client for 'R'. Provides functions for + building 'HTTP' queries, including query parameters, body requests, headers, + authentication, and more. + date_publication: '2016-01-03' + bug_reports: https://github.com/sckott/request/issues + url: '' + url_cran: https://CRAN.R-project.org/package=request + url_git: https://github.com/sckott/request +Require: + version: 1.0.1 + title: Installing and Loading R Packages for Reproducible Workflows + maintainer: Eliot J B McIntire + description: |- + A single key function, 'Require' that makes rerun-tolerant + versions of 'install.packages' and `require` for CRAN packages, packages + no longer on CRAN (i.e., archived), specific versions of packages, + and GitHub packages. This approach is developed to create reproducible + workflows that are flexible and fast enough to use while in development stages, + while able to build snapshots once a stable package collection is found. + As with other functions in a reproducible workflow, this package + emphasizes functions that return the same result whether it is + the first or subsequent times running the function, with subsequent times being + sufficiently fast that they can be run every time without undue waiting burden on + the user or developer. + date_publication: '2024-08-17' + bug_reports: https://github.com/PredictiveEcology/Require/issues + url: https://Require.predictiveecology.org + url_cran: https://CRAN.R-project.org/package=Require + url_git: https://github.com/PredictiveEcology/Require +requiRements: + version: 0.0.3 + title: Helper Package to Install Packages for R + maintainer: Jonathan M. Mang + description: |- + Helper function to install packages for R using an external + 'requirements.txt' or a string containing diverse packages from + several resources like Github or CRAN. + date_publication: '2023-02-24' + bug_reports: https://github.com/joundso/requirements/issues + url: '' + url_cran: https://CRAN.R-project.org/package=requiRements + url_git: https://github.com/joundso/requirements +requireR: + version: 1.0.0.1 + title: R Source Code Modularizer + maintainer: Peter van den Berg + description: |- + Modularizes source code. Keeps the global environment clean, + explicifies interdependencies. Inspired by 'RequireJS'. + date_publication: '2017-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=requireR + url_git: '' +rerandPower: + version: 0.0.1 + title: |- + Power and Sample Size Calculations for Completely Randomized and + Rerandomized Experiments + maintainer: Zach Branson + description: Computes the power resulting from completely randomized and rerandomized + experiments with two groups. Furthermore, computes the sample size necessary to + obtain a desired level of power for completely randomized and rerandomized experiments. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rerandPower + url_git: '' +rerddap: + version: 1.2.0 + title: General Purpose Client for 'ERDDAP™' Servers + maintainer: Roy Mendelssohn + description: |- + General purpose R client for 'ERDDAP™' servers. Includes + functions to search for 'datasets', get summary information on + 'datasets', and fetch 'datasets', in either 'csv' or 'netCDF' format. + 'ERDDAP™' information: + . + date_publication: '2024-12-11' + bug_reports: https://github.com/ropensci/rerddap/issues + url: https://docs.ropensci.org/rerddap/ + url_cran: https://CRAN.R-project.org/package=rerddap + url_git: https://github.com/ropensci/rerddap +rerddapXtracto: + version: 1.2.2 + title: Extracts Environmental Data from 'ERDDAP™' Web Services + maintainer: Roy Mendelssohn + description: |- + Contains three functions that access + environmental data from any 'ERDDAP™' data web service. The rxtracto() function extracts + data along a trajectory for a given "radius" around the point. The + rxtracto_3D() function extracts data in a box. The rxtractogon() function + extracts data in a polygon. All of those three function use the 'rerddap' package + to extract the data, and should work with any 'ERDDAP™' server. + There are also two functions, plotBBox() and plotTrack() that use the 'plotdap' + package to simplify the creation of maps of the data. + date_publication: '2025-02-25' + bug_reports: https://github.com/rmendels/rerddapXtracto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rerddapXtracto + url_git: https://github.com/rmendels/rerddapXtracto +reReg: + version: 1.4.7 + title: Recurrent Event Regression + maintainer: Sy Han (Steven) Chiou + description: A comprehensive collection of practical and easy-to-use tools for regression + analysis of recurrent events, with or without the presence of a (possibly) informative + terminal event described in Chiou et al. (2023) . The + modeling framework is based on a joint frailty scale-change model, that includes + models described in Wang et al. (2001) , Huang + and Wang (2004) , Xu et al. (2017) , + and Xu et al. (2019) as special cases. The implemented + estimating procedure does not require any parametric assumption on the frailty + distribution. The package also allows the users to specify different model forms + for both the recurrent event process and the terminal event. + date_publication: '2024-10-07' + bug_reports: https://github.com/stc04003/reReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reReg + url_git: https://github.com/stc04003/reReg +resample: + version: '0.6' + title: Resampling Functions + maintainer: Tim Hesterberg + description: |- + Bootstrap, permutation tests, and jackknife, + featuring easy-to-use syntax. + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=resample + url_git: '' +resampledata: + version: 0.3.2 + title: Data Sets for Mathematical Statistics with Resampling in R + maintainer: Albert Y. Kim + description: |- + Package of data sets from "Mathematical Statistics + with Resampling in R" (1st Ed. 2011, 2nd Ed. 2018) by Laura Chihara and Tim Hesterberg. + date_publication: '2024-11-05' + bug_reports: https://github.com/rudeboybert/resampledata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=resampledata + url_git: https://github.com/rudeboybert/resampledata +resampledata3: + version: '1.0' + title: |- + Data Sets for "Mathematical Statistics with Resampling and R" + (3rd Ed) + maintainer: Tim Hesterberg + description: |- + Data sets for Chihara and Hesterberg (2022, ISBN: 978-1-119-87404-1) + "Mathematical Statistics with Resampling in R" (3rd Ed). + date_publication: '2022-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=resampledata3 + url_git: https://github.com/lchihara/MathStatsResamplingR +resde: + version: '1.1' + title: Estimation in Reducible Stochastic Differential Equations + maintainer: Oscar Garcia + description: |- + Maximum likelihood estimation for univariate reducible + stochastic differential equation models. Discrete, possibly noisy + observations, not necessarily evenly spaced in time. Can fit + multiple individuals/units with global and local parameters, by + fixed-effects or mixed-effects methods. Ref.: Garcia, O. (2019) + "Estimating reducible stochastic differential equations by + conversion to a least-squares problem", Computational Statistics + 34(1): 23-46, . + date_publication: '2023-05-19' + bug_reports: https://github.com/ogarciav/resde/issues + url: '' + url_cran: https://CRAN.R-project.org/package=resde + url_git: https://github.com/ogarciav/resde/ +resemble: + version: 2.2.3 + title: Memory-Based Learning in Spectral Chemometrics + maintainer: Leonardo Ramirez-Lopez + description: |2- + + Functions for dissimilarity analysis and memory-based learning + (MBL, a.k.a local modeling) in complex spectral data sets. + Most of these functions are based on the methods presented in + Ramirez-Lopez et al. (2013) . + date_publication: '2024-02-16' + bug_reports: https://github.com/l-ramirez-lopez/resemble/issues + url: http://l-ramirez-lopez.github.io/resemble/ + url_cran: https://CRAN.R-project.org/package=resemble + url_git: '' +reservoir: + version: 1.1.5 + title: |- + Tools for Analysis, Design, and Operation of Water Supply + Storages + maintainer: Sean Turner + description: |- + Measure single-storage water supply system performance using resilience, + reliability, and vulnerability metrics; assess storage-yield-reliability + relationships; determine no-fail storage with sequent peak analysis; optimize + release decisions for water supply, hydropower, and multi-objective reservoirs + using deterministic and stochastic dynamic programming; generate inflow + replicates using parametric and non-parametric models; evaluate inflow + persistence using the Hurst coefficient. + date_publication: '2016-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reservoir + url_git: '' +reservoirnet: + version: 0.2.0 + title: Reservoir Computing and Echo State Networks + maintainer: Thomas Ferte + description: |- + A simple user-friendly library based on the 'python' module 'reservoirpy'. + It provides a flexible interface to implement efficient Reservoir + Computing (RC) architectures with a particular focus on Echo State Networks + (ESN). Some of its features are: offline and online training, parallel implementation, + sparse matrix computation, fast spectral initialization, advanced learning + rules (e.g. Intrinsic Plasticity) etc. It also makes possible to easily create + complex architectures with multiple reservoirs (e.g. deep reservoirs), readouts, + and complex feedback loops. Moreover, graphical tools are included to easily + explore hyperparameters. Finally, it includes several tutorials exploring + time series forecasting, classification and hyperparameter tuning. For more information + about 'reservoirpy', please see Trouvain et al. (2020) . + This package was developed in the framework of the University of Bordeaux’s IdEx + "Investments for the Future" program / RRI PHDS. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reservoirnet + url_git: https://github.com/reservoirpy +reservr: + version: 0.0.3 + title: |- + Fit Distributions and Neural Networks to Censored and Truncated + Data + maintainer: Alexander Rosenstock + description: |- + Define distribution families and fit them to + interval-censored and interval-truncated data, where the truncation + bounds may depend on the individual observation. The defined + distributions feature density, probability, sampling and fitting + methods as well as efficient implementations of the log-density log + f(x) and log-probability log P(x0 <= X <= x1) for use in 'TensorFlow' + neural networks via the 'tensorflow' package. Allows training + parametric neural networks on interval-censored and interval-truncated + data with flexible parameterization. Applications include Claims + Development in Non-Life Insurance, e.g. modelling reporting delay + distributions from incomplete data, see Bücher, Rosenstock (2022) + . + date_publication: '2024-06-24' + bug_reports: https://github.com/AshesITR/reservr/issues + url: https://ashesitr.github.io/reservr/ + url_cran: https://CRAN.R-project.org/package=reservr + url_git: https://github.com/AshesITR/reservr +RESET: + version: 1.0.0 + title: Reconstruction Set Test + maintainer: H. Robert Frost + description: |- + Contains logic for sample-level variable set scoring using randomized reduced rank reconstruction error. + Frost, H. Robert (2023) "Reconstruction Set Test (RESET): a computationally efficient method for + single sample gene set testing based on randomized reduced rank reconstruction error" . + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RESET + url_git: '' +resevol: + version: 0.3.4.0 + title: |- + Simulate Agricultural Production and Evolution of Pesticide + Resistance + maintainer: A. Bradley Duthie + description: |- + Simulates individual-based models of agricultural pest management + and the evolution of pesticide resistance. Management occurs on a spatially + explicit landscape that is divided into an arbitrary number of farms that + can grow one of up to 10 crops and apply one of up to 10 pesticides. Pest + genomes are modelled in a way that allows for any number of pest traits with + an arbitrary covariance structure that is constructed using an evolutionary + algorithm in the mine_gmatrix() function. Simulations are then run using the + run_farm_sim() function. This package thereby allows for highly mechanistic + social-ecological models of the evolution of pesticide resistance under + different types of crop rotation and pesticide application regimes. + date_publication: '2023-11-30' + bug_reports: https://github.com/bradduthie/resevol/issues + url: https://bradduthie.github.io/resevol/ + url_cran: https://CRAN.R-project.org/package=resevol + url_git: '' +reshape: + version: 0.8.9 + title: Flexibly Reshape Data + maintainer: Hadley Wickham + description: |- + Flexibly restructure and aggregate data using + just two functions: melt and cast. + date_publication: '2022-04-12' + bug_reports: '' + url: http://had.co.nz/reshape + url_cran: https://CRAN.R-project.org/package=reshape + url_git: '' +reshape2: + version: 1.4.4 + title: 'Flexibly Reshape Data: A Reboot of the Reshape Package' + maintainer: Hadley Wickham + description: |- + Flexibly restructure and aggregate data using just two + functions: melt and 'dcast' (or 'acast'). + date_publication: '2020-04-09' + bug_reports: https://github.com/hadley/reshape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reshape2 + url_git: https://github.com/hadley/reshape +RESI: + version: 1.2.4 + title: Robust Effect Size Index (RESI) Estimation + maintainer: Megan Jones + description: Summarize model output using a robust effect size index. The index + is introduced in Vandekar, Tao, & Blume (2020) . + date_publication: '2024-01-16' + bug_reports: https://github.com/statimagcoll/RESI/issues + url: https://statimagcoll.github.io/RESI/ + url_cran: https://CRAN.R-project.org/package=RESI + url_git: https://github.com/statimagcoll/RESI +RESIDE: + version: 0.3.2 + title: Rapid Easy Synthesis to Inform Data Extraction + maintainer: Ryan Field + description: |- + Developed to assist researchers with planning analysis, + prior to obtaining data from Trusted Research Environments (TREs) also known as safe havens. + With functionality to export and import marginal distributions as well as synthesise data, both with + and without correlations from these marginal distributions. Using a multivariate cumulative distribution (COPULA). + Additionally the International Stroke Trial (IST) is included as an example dataset under ODC-By licence + Sandercock et al. (2011) , + Sandercock et al. (2011) . + date_publication: '2024-10-17' + bug_reports: '' + url: https://hehta.github.io/RESIDE/ + url_cran: https://CRAN.R-project.org/package=RESIDE + url_git: '' +ResidentialEnergyConsumption: + version: 1.1.0 + title: Residential Energy Consumption Data + maintainer: Konstantin Hopf + description: |- + Datasets with energy consumption data of different data measurement frequencies. + The data stems from several publicly funded research projects of the Chair of Information + Systems and Energy Efficient Systems at the University of Bamberg. + date_publication: '2021-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ResidentialEnergyConsumption + url_git: '' +resilience: + version: 2024.1.2 + title: Predictors of Resilience to a Stressor in a Single-Arm Study + maintainer: Ravi Varadhan + description: Studies of resilience in older adults employ a single-arm design where + everyone experiences the stressor. The simplistic approach of regressing change + versus baseline yields biased estimates due to regression-to-the-mean. This package + provides a method to correct the bias. It also allows covariates to be included. + The method implemented in the package is described in Varadhan, R., Zhu, J., and + Bandeen-Roche, K (2023), Biostatistics (To appear). + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=resilience + url_git: '' +ResIN: + version: 2.0.0 + title: Response Item Networks + maintainer: Philip Warncke + description: Contains various tools to perform and visualize Response Item Networks + ('ResIN's'). 'ResIN' binarizes ordered-categorical and qualitative response choices + from (survey) data, calculates pairwise associations and maps the location of + each item response as a node in a force-directed network. Please refer to + for more details. + date_publication: '2024-10-04' + bug_reports: https://github.com/pwarncke77/ResIN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ResIN + url_git: https://github.com/pwarncke77/ResIN +ResistorArray: + version: 1.0-32 + title: Electrical Properties of Resistor Networks + maintainer: Robin K. S. Hankin + description: Electrical properties of resistor networks using matrix methods. + date_publication: '2019-01-29' + bug_reports: https://github.com/RobinHankin/ResistorArray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ResistorArray + url_git: https://github.com/RobinHankin/ResistorArray.git +reslife: + version: 0.2.1 + title: |- + Calculate Mean Residual Life (MRL) and Related Values for + Different Distributions + maintainer: Andrew Crawford + description: |- + A pair of functions for calculating mean residual life (MRL) + , median residual life, and percentile residual life using the outputs of + either the 'flexsurv' package or parameters + provided by the user. Input information about the distribution, the given + 'life' value, the percentile, and the type of residual life, + and the function will return your desired values. For the 'flexsurv' option, + the function allows the user to input their own data for making predictions. + This function is based on Jackson (2016) . + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reslife + url_git: https://github.com/an-crawford/reslife +reslr: + version: 0.1.1 + title: Modelling Relative Sea Level Data + maintainer: Maeve Upton + description: |- + The Bayesian modelling of relative sea-level data + using a comprehensive approach that incorporates + various statistical models within a unifying framework. + Details regarding each statistical models; + linear regression (Ashe et al 2019) , + change point models (Cahill et al 2015) , + integrated Gaussian process models (Cahill et al 2015) , + temporal splines (Upton et al 2023) , + spatio-temporal splines (Upton et al 2023) and + generalised additive models (Upton et al 2023) . + This package facilitates data loading, + model fitting and result summarisation. + Notably, it accommodates the inherent measurement errors + found in relative sea-level data across multiple dimensions, + allowing for their inclusion in the statistical models. + date_publication: '2023-06-15' + bug_reports: https://github.com/maeveupton/reslr/issues + url: https://maeveupton.github.io/reslr/ + url_cran: https://CRAN.R-project.org/package=reslr + url_git: https://github.com/maeveupton/reslr +resmush: + version: 0.2.1 + title: Optimize and Compress Image Files with 'reSmush.it' + maintainer: Diego Hernangómez + description: |- + Compress local and online images using the 'reSmush.it' API + service . + date_publication: '2024-12-18' + bug_reports: https://github.com/dieghernan/resmush/issues + url: https://dieghernan.github.io/resmush/ + url_cran: https://CRAN.R-project.org/package=resmush + url_git: https://github.com/dieghernan/resmush +resourcecode: + version: 0.2.1 + title: Access to the 'RESOURCECODE' Hindcast Database + maintainer: Nicolas Raillard + description: |- + Utility functions to download data from the 'RESOURCECODE' + hindcast database of sea-states, time series of sea-state parameters + and time series of 1D and 2D wave spectra. See + for more details about the available + data. Also provides facilities to plot and analyse downloaded data, + such as computing the sea-state parameters from both the 1D and 2D + surface elevation variance spectral density. + date_publication: '2024-12-03' + bug_reports: https://github.com/Resourcecode-project/r-resourcecode/issues + url: https://resourcecode-project.github.io/r-resourcecode/ + url_cran: https://CRAN.R-project.org/package=resourcecode + url_git: https://github.com/Resourcecode-project/r-resourcecode +resourcer: + version: 1.4.0 + title: Resource Resolver + maintainer: Yannick Marcon + description: |- + A resource represents some data or a computation unit. It is + described by a URL and credentials. This package proposes a Resource model + with "resolver" and "client" classes to facilitate the access and the usage of the + resources. + date_publication: '2023-04-25' + bug_reports: https://github.com/obiba/resourcer + url: '' + url_cran: https://CRAN.R-project.org/package=resourcer + url_git: '' +ResourceSelection: + version: 0.3-6 + title: |- + Resource Selection (Probability) Functions for Use-Availability + Data + maintainer: Peter Solymos + description: |- + Resource Selection (Probability) Functions + for use-availability wildlife data + based on weighted distributions as described in + Lele and Keim (2006) , + Lele (2009) , + and Solymos & Lele (2016) . + date_publication: '2023-07-08' + bug_reports: https://github.com/psolymos/ResourceSelection/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ResourceSelection + url_git: https://github.com/psolymos/ResourceSelection +ResPBIBD: + version: 0.1.0 + title: |- + "Resolvable Partially Balanced Incomplete Block Designs + (PBIBDs)" + maintainer: Vinaykumar L.N. + description: A collection of several utility functions related to resolvable and + affine resolvable Partially Balanced Incomplete Block Designs (PBIBDs), have been + developed. In the class of resolvable designs, affine resolvable designs are said + to be optimal, Bailey (1995) . Here, the package contains + three functions to generate and study the characterization properties of these + designs. Developed functions are named as PBIBD1(), PBIBD2() and PBIBD3(), in + which first two functions are used to generate two new series of affine resolvable + PBIBDs and last one is used to generate a new series of resolvable PBIBDs, respectively. In + addition, these functions can also be used to generate design parameters (v, b, + r and k), canonical efficiency factors, variance factor between associates and + average variance factors of the generated designs. Here v is the number of treatments, + b (= b1 + b2, in case of non-proper design) is the number of blocks, r is the + number of replications and k (= k1 + k2; k1 is the size of b1 and k2 is the size + of b2) is the block size. + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ResPBIBD + url_git: '' +RespirAnalyzer: + version: 1.0.2 + title: Analysis Functions of Respiratory Data + maintainer: Xinzheng Dong + description: Provides functions for the complete analysis of respiratory data. Consists + of a set of functions that allow to preprocessing respiratory data, calculate + both regular statistics and nonlinear statistics, conduct group comparison and + visualize the results. Especially, Power Spectral Density ('PSD') (A. Eke (2000) + ), 'MultiScale Entropy(MSE)' ('Madalena Costa(2002)' + ) and 'MultiFractal Detrended Fluctuation Analysis(MFDFA)' + ('Jan W.Kantelhardt' (2002) ) were applied + for the analysis of respiratory data. + date_publication: '2023-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RespirAnalyzer + url_git: '' +respirometry: + version: 2.0.1 + title: Tools for Conducting and Analyzing Respirometry Experiments + maintainer: Matthew A. Birk + description: |- + Provides tools to enable the researcher to more precisely conduct + respirometry experiments. Strong emphasis is on aquatic respirometry. Tools + focus on helping the researcher setup and conduct experiments. Functions for + analysis of resulting respirometry data are also provided. This package + provides tools for intermittent, flow-through, and closed respirometry + techniques. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=respirometry + url_git: '' +responsePatterns: + version: 0.1.1 + title: Screening for Careless Responding Patterns + maintainer: Tomas Rihacek + description: Some survey participants tend to respond carelessly which complicates + data analysis. This package provides functions that make it easier to explore + responses and identify those that may be problematic. See Gottfried et al. (2022) + for more information. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=responsePatterns + url_git: '' +respR: + version: 2.3.3 + title: |- + Import, Process, Analyse, and Calculate Rates from Respirometry + Data + maintainer: Nicholas Carey + description: |- + Provides a structural, reproducible workflow for the + processing and analysis of respirometry data. It contains analytical + functions and utilities for working with oxygen time-series to determine + respiration or oxygen production rates, and to make it easier to report and + share analyses. See Harianto et al. 2019 . + date_publication: '2024-05-10' + bug_reports: '' + url: https://januarharianto.github.io/respR/ + url_cran: https://CRAN.R-project.org/package=respR + url_git: https://github.com/januarharianto/respr +resquin: + version: 0.0.2 + title: Response Quality Indicators for Survey Research + maintainer: Matthias Roth + description: |- + Calculate common survey data quality indicators for multi-item scales + and matrix questions. Currently supports the calculation of + response style indicators and response distribution indicators. + For an overview on response quality indicators see Bhaktha N, + Henning S, Clemens L (2024). 'Characterizing response quality + in surveys with multi-item scales: A unified framework' + . + date_publication: '2024-09-11' + bug_reports: https://github.com/MatRoth/resquin/issues + url: https://matroth.github.io/resquin/ + url_cran: https://CRAN.R-project.org/package=resquin + url_git: https://github.com/MatRoth/resquin +RESS: + version: '1.3' + title: Integrates R and Essentia + maintainer: Ben Waxer + description: Contains three functions that query AuriQ Systems' Essentia Database + and return the results in R. 'essQuery' takes a single Essentia command and captures + the output in R, where you can save the output to a dataframe or stream it directly + into additional analysis. 'read.essentia' takes an Essentia script and captures + the output csv data into R, where you can save the output to a dataframe or stream + it directly into additional analysis. 'capture.essentia' takes a file containing + any number of Essentia commands and captures the output of the specified statements + into R dataframes. Essentia can be downloaded for free at http://www.auriq.com/documentation/source/install/index.html. + date_publication: '2015-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RESS + url_git: '' +restatapi: + version: 0.24.2 + title: Search and Retrieve Data from Eurostat Database + maintainer: Mátyás Mészáros + description: |- + Eurostat is the statistical office of the European Union and provides high quality statistics for Europe. + Large set of the data is disseminated through the Eurostat database (). + The tools are using the REST API with the Statistical Data and Metadata eXchange (SDMX) Web Services + () to search and download data from + the Eurostat database using the SDMX standard. + date_publication: '2025-01-28' + bug_reports: https://github.com/eurostat/restatapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=restatapi + url_git: https://github.com/eurostat/restatapi +restatis: + version: 0.2.0 + title: |- + R Wrapper to Access a Wide Range of Germany's Federal + Statistical System Databases Based on the GENESIS Web Service + RESTful API of the German Federal Statistical Office + (Statistisches Bundesamt/Destatis) + maintainer: Yannik Buhl + description: |- + A RESTful API wrapper for accessing the GENESIS database of + the German Federal Statistical Office (Destatis) as well as its Census + Database and the database of Germany's regional statistics. Supports data + search functions, credential management, result caching, and handling + remote background jobs for large datasets. + date_publication: '2024-07-25' + bug_reports: https://github.com/CorrelAid/restatis/issues + url: https://correlaid.github.io/restatis/ + url_cran: https://CRAN.R-project.org/package=restatis + url_git: https://github.com/CorrelAid/restatis +restaurant: + version: 0.1.0 + title: Restaurant Data for Entity Resolution + maintainer: Rebecca Steorts + description: 'Duplicated restaurant data (pre-processed and formatted) for entity + resolution. This package contains formatted data from a data set that contains + information about different restaurants, with the Zagats portion containing 331 + records and the Fodors portion containing 533 records. The following variables + are included in the data set: id, name, address, city, phone, type. The data set + has a respective gold data set that provides information on which records match + based on id.' + date_publication: '2020-10-22' + bug_reports: https://github.com/resteorts/restaurant/issues + url: '' + url_cran: https://CRAN.R-project.org/package=restaurant + url_git: https://github.com/resteorts/restaurant +restez: + version: 2.1.4 + title: Create and Query a Local Copy of 'GenBank' in R + maintainer: Joel H. Nitta + description: |- + Download large sections of + 'GenBank' and generate a local + SQL-based database. A user can then query this database using 'restez' + functions or through 'rentrez' + wrappers. + date_publication: '2023-10-25' + bug_reports: https://github.com/ropensci/restez/issues + url: https://docs.ropensci.org/restez/ + url_cran: https://CRAN.R-project.org/package=restez + url_git: https://github.com/ropensci/restez +restfulr: + version: 0.0.15 + title: R Interface to RESTful Web Services + maintainer: Michael Lawrence + description: Models a RESTful service as if it were a nested R list. + date_publication: '2022-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=restfulr + url_git: '' +restimizeapi: + version: 1.0.0 + title: Functions for Working with the 'www.estimize.com' Web Services + maintainer: Thomas P. Fuller + description: |- + Provides the user with functions to develop their trading strategy, + uncover actionable trading ideas, and monitor consensus shifts with + crowdsourced earnings and economic estimate data directly from + . Further information regarding the web services this + package invokes can be found at . + date_publication: '2015-05-23' + bug_reports: '' + url: http://coherentlogic.com/middleware-development/r-package-for-the-estimize-com-api?source=cran + url_cran: https://CRAN.R-project.org/package=restimizeapi + url_git: '' +RESTK: + version: 1.0.0 + title: An Implementation of the RESTK Algorithm + maintainer: Sergi Vilardell + description: Implementation of the RESTK algorithm based on Markov's Inequality + from Vilardell, Sergi, Serra, Isabel, Mezzetti, Enrico, Abella, Jaume, Cazorla, + Francisco J. and Del Castillo, J. (2022). "Using Markov's Inequality with Power-Of-k + Function for Probabilistic WCET Estimation". In 34th Euromicro Conference on Real-Time + Systems (ECRTS 2022). Leibniz International Proceedings in Informatics (LIPIcs) + 231 20:1-20:24. . This work has been supported + by the European Research Council (ERC) under the European Union's Horizon 2020 + research and innovation programme (grant agreement No. 772773). + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RESTK + url_git: '' +restoptr: + version: 1.0.6 + title: Ecological Restoration Planning + maintainer: Dimitri Justeau-Allaire + description: |2- + + Flexible framework for ecological restoration planning. It aims to identify priority areas for restoration efforts using optimization algorithms (based on Justeau-Allaire et al. 2021 ). Priority areas can be identified by maximizing landscape indices, such as the effective mesh size (Jaeger 2000 ), or the integral index of connectivity (Pascual-Hortal & Saura 2006 ). Additionally, constraints can be used to ensure that priority areas exhibit particular characteristics (e.g., ensure that particular places are not selected for restoration, ensure that priority areas form a single contiguous network). Furthermore, multiple near-optimal solutions can be generated to explore multiple options in restoration planning. The package leverages the 'Choco-solver' software to perform optimization using constraint programming (CP) techniques (). + date_publication: '2023-08-18' + bug_reports: https://github.com/dimitri-justeau/restoptr/issues + url: https://dimitri-justeau.github.io/restoptr/ + url_cran: https://CRAN.R-project.org/package=restoptr + url_git: '' +RestoreNet: + version: 1.0.1 + title: Random-Effects Stochastic Reaction Networks + maintainer: Luca Del Core + description: |- + A random-effects stochastic model that allows quick detection of + clonal dominance events from clonal tracking data collected in gene therapy studies. Starting from the Ito-type equation describing the dynamics of cells duplication, death and differentiation at clonal level, we first considered its local linear approximation as the base model. + The parameters of the base model, which are inferred using a maximum likelihood approach, + are assumed to be shared across the clones. Although this assumption makes inference easier, + in some cases it can be too restrictive and does not take into account possible scenarios of clonal dominance. + Therefore we extended the base model by introducing random effects for the clones. + In this extended formulation the dynamic parameters are estimated using a tailor-made + expectation maximization algorithm. Further details on the methods can be found in L. Del Core et al., (2022) . + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RestoreNet + url_git: '' +restriktor: + version: 0.6-10 + title: |- + Restricted Statistical Estimation and Inference for Linear + Models + maintainer: Leonard Vanbrabant + description: Allow for easy-to-use testing or evaluating of linear equality and + inequality restrictions about parameters and effects in (generalized) linear statistical + models. + date_publication: '2024-12-19' + bug_reports: '' + url: https://restriktor.org + url_cran: https://CRAN.R-project.org/package=restriktor + url_git: '' +RestRserve: + version: 1.2.3 + title: A Framework for Building HTTP API + maintainer: Dmitry Selivanov + description: |- + Allows to easily create high-performance full featured HTTP APIs from R + functions. Provides high-level classes such as 'Request', 'Response', + 'Application', 'Middleware' in order to streamline server side + application development. Out of the box allows to serve requests using + 'Rserve' package, but flexible enough to integrate with other HTTP servers + such as 'httpuv'. + date_publication: '2024-05-21' + bug_reports: https://github.com/rexyai/RestRserve/issues + url: https://restrserve.org + url_cran: https://CRAN.R-project.org/package=RestRserve + url_git: https://github.com/rexyai/RestRserve +result: + version: 0.1.0 + title: |- + Result Type for Safely Handling Operations that can Succeed or + Fail + maintainer: Soumya Ray + description: |- + Allows wrapping values in success() and failure() types to capture + the result of operations, along with any status codes. Risky expressions can be + wrapped in as_result() and functions wrapped in result() to catch errors + and assign the relevant result types. Monadic functions can be bound together + as pipelines or transaction scripts using then_try(), to gracefully handle + errors at any step. + date_publication: '2023-11-21' + bug_reports: https://github.com/soumyaray/result/issues + url: '' + url_cran: https://CRAN.R-project.org/package=result + url_git: https://github.com/soumyaray/result +resultant: + version: 1.0.0 + title: |- + Utilities for Multivariate Polynomials with Rational + Coefficients + maintainer: Stéphane Laurent + description: |- + Computation of resultant, subresultants, greatest common divisor, + integral division (aka division without remainder) of two multivariate polynomials + with rational coefficients, Sturm-Habicht sequence and square-free + factorization of a multivariate polynomial with rational coefficients. + The computations are performed by the 'C++' library 'CGAL' + (). Resultants have applications in polynomial + systems solving, number theory, and algebraic geometry. The package + also contains some functions computing the number of real roots of a + univariate polynomial with rational coefficients, and a function computing + the division with remainder of two univariate polynomials with rational + coefficients. + date_publication: '2024-07-31' + bug_reports: https://github.com/stla/resultant/issues + url: '' + url_cran: https://CRAN.R-project.org/package=resultant + url_git: https://github.com/stla/resultant +ResultModelManager: + version: 0.5.11 + title: Result Model Manager + maintainer: Jamie Gilbert + description: |- + Database data model management utilities for R packages in the Observational Health Data Sciences and + Informatics program . 'ResultModelManager' provides utility functions to allow package + maintainers to migrate existing SQL database models, export and import results in consistent patterns. + date_publication: '2024-09-19' + bug_reports: https://github.com/OHDSI/ResultModelManager/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ResultModelManager + url_git: https://github.com/OHDSI/ResultModelManager +resumer: + version: 0.0.5 + title: Build Resumes with R + maintainer: Jared Lander + description: Using a CSV, LaTeX and R to easily build attractive resumes. + date_publication: '2021-02-12' + bug_reports: https://github.com/jaredlander/resumer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=resumer + url_git: https://github.com/jaredlander/resumer +resumiR: + version: 1.0.2 + title: |- + Medidas Resumen y Tablas de Frecuencia para Datos Numéricos / + Summary Measures and Frequency Tables for Numerical Data + maintainer: Juan Manuel Solís + description: Permite obtener rápidamente una serie de medidas de resumen y gráficos + para datos numéricos discretos o continuos en series simples. También permite + obtener tablas de frecuencia clásicas y gráficos cuando se desea realizar un análisis + de series agrupadas. Su objetivo es de aplicación didáctica para un curso introductorio + de Bioestadística utilizando el software R, para las carreras de grado las carreras + de grado y otras ofertas educativas de la Facultad de Ciencias Agrarias de la + UNJu / It generates summary measures and graphs for discrete or continuous numerical + data in simple series. It also enables the creation of classic frequency tables + and graphs when analyzing grouped series. Its purpose is for educational application + in an introductory Biostatistics course using the R software, aimed at undergraduate + programs and other educational offerings of the Faculty of Agricultural Sciences + at the National University of Jujuy (UNJu). + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=resumiR + url_git: https://github.com/juanMaSolisJujuy/resumiR +ReSurv: + version: 1.0.0 + title: Machine Learning Models for Predicting Claim Counts + maintainer: Emil Hofman + description: |- + Prediction of claim counts using the feature based development factors introduced in the manuscript Hiabu M., Hofman E. and Pittarello G. (2023) . + Implementation of Neural Networks, Extreme Gradient Boosting, + and Cox model with splines to optimise the partial log-likelihood of proportional hazard models. + date_publication: '2024-11-14' + bug_reports: https://github.com/edhofman/ReSurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ReSurv + url_git: https://github.com/edhofman/ReSurv +retel: + version: 0.1.0 + title: Regularized Exponentially Tilted Empirical Likelihood + maintainer: Eunseop Kim + description: |- + Implements the regularized exponentially tilted empirical + likelihood method. Details of the methods are given in Kim, MacEachern, and + Peruggia (2023) . This work was supported by + the U.S. National Science Foundation under Grants No. SES-1921523 and + DMS-2015552. + date_publication: '2024-01-22' + bug_reports: https://github.com/markean/retel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=retel + url_git: https://github.com/markean/retel +rethinker: + version: 1.1.0 + title: RethinkDB Client + maintainer: Miron B. Kursa + description: Simple, native 'RethinkDB' client. + date_publication: '2017-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rethinker + url_git: https://github.com/mbq/rethinker +rethnicity: + version: 0.2.6 + title: Predicting Ethnic Group from Names + maintainer: Fangzhou Xie + description: |- + Implementation of the race/ethnicity prediction method, described + in "rethnicity: An R package for predicting ethnicity from names" + by Fangzhou Xie (2022) and + "Rethnicity: Predicting Ethnicity from Names" + by Fangzhou Xie (2021) . + date_publication: '2024-10-18' + bug_reports: https://github.com/fangzhou-xie/rethnicity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rethnicity + url_git: https://github.com/fangzhou-xie/rethnicity +reticulate: + version: 1.41.0 + title: Interface to 'Python' + maintainer: Tomasz Kalinowski + description: |- + Interface to 'Python' modules, classes, and functions. When calling + into 'Python', R data types are automatically converted to their equivalent 'Python' + types. When values are returned from 'Python' to R they are converted back to R + types. Compatible with all versions of 'Python' >= 2.7. + date_publication: '2025-02-24' + bug_reports: https://github.com/rstudio/reticulate/issues + url: https://rstudio.github.io/reticulate/ + url_cran: https://CRAN.R-project.org/package=reticulate + url_git: https://github.com/rstudio/reticulate +retimer: + version: 0.1.3 + title: Retime and Analyse Speech Signals + maintainer: Alistair Beith + description: Retime speech signals with a native Waveform Similarity Overlap-Add + (WSOLA) implementation translated from the 'TSM toolbox' by Driedger & Müller + (2014) . + Design retimings and pitch (f0) transformations with tidy data and apply them + via 'Praat' interface. Produce spectrograms, spectra, and amplitude envelopes. + Includes implementation of vocalic speech envelope analysis (fft_spectrum) technique + and example data (mm1) from Tilsen, S., & Johnson, K. (2008) . + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=retimer + url_git: '' +retmort: + version: 1.0.0 + title: |- + Estimate User-Based Tagging Mortality and Tag Loss in + Mark-Recapture Studies + maintainer: Brendan Campbell + description: We provide several avenues to predict and account for user-based mortality + and tag loss during mark-recapture studies. When planning a study on a target + species, the retentionmort_generation() function can be used to produce multiple + synthetic mark-recapture datasets to anticipate the error associated with a planned + field study to guide method development to reduce error. Similarly, if field data + was already collected, the retentionmort() function can be used to predict the + error from already generated data to adjust for user-based mortality and tag loss. + The test_dataset_retentionmort() function will provide an example dataset of how + data should be inputted into the function to run properly. Lastly, the retentionmort_figure() + function can be used on any dataset generated from either model function to produce + an 'rmarkdown' printout of preliminary analysis associated with the model, including + summary statistics and figures. Methods and results pertaining to the formation + of this package can be found in McCutcheon et al. (in review, "Predicting tagging-related + mortality and tag loss during mark-recapture studies"). + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=retmort + url_git: '' +retriever: + version: 0.2.1 + title: |- + Generate Disease-Specific Response Signatures from the + LINCS-L1000 Data + maintainer: Daniel Osorio + description: Generates disease-specific drug-response profiles that are independent + of time, concentration, and cell-line. Based on the cell lines used as surrogates, + the returned profiles represent the unique transcriptional changes induced by + a compound in a given disease. + date_publication: '2021-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=retriever + url_git: '' +retrodesign: + version: 0.2.2 + title: Tools for Type S (Sign) and Type M (Magnitude) Errors + maintainer: Andrew Timm + description: |- + Provides tools for working with Type S (Sign) and + Type M (Magnitude) errors, as proposed in Gelman and Tuerlinckx (2000) + and + Gelman & Carlin (2014) . + In addition to simply calculating the probability of + Type S/M error, the package includes functions for calculating these errors + across a variety of effect sizes for comparison, and recommended sample size + given "tolerances" for Type S/M errors. To improve the speed of these + calculations, closed forms solutions for the probability of a Type S/M error + from Lu, Qiu, and Deng (2018) + are implemented. As of 1.0.0, this includes + support only for simple research designs. See the + package vignette for a fuller exposition on how Type S/M errors arise in + research, and how to analyze them using the type of design analysis proposed + in the above papers. + date_publication: '2024-03-28' + bug_reports: https://github.com/andytimm/retrodesign/issues + url: '' + url_cran: https://CRAN.R-project.org/package=retrodesign + url_git: https://github.com/andytimm/retrodesign +retroharmonize: + version: 0.2.0 + title: Ex Post Survey Data Harmonization + maintainer: Daniel Antal + description: |- + Assist in reproducible retrospective (ex-post) harmonization + of data, particularly individual level survey data, by providing tools + for organizing metadata, standardizing the coding of variables, and + variable names and value labels, including missing values, and + documenting the data transformations, with the help of comprehensive + s3 classes. + date_publication: '2021-11-02' + bug_reports: https://github.com/rOpenGov/retroharmonize/issues + url: https://retroharmonize.dataobservatory.eu/ + url_cran: https://CRAN.R-project.org/package=retroharmonize + url_git: https://github.com/rOpenGov/retroharmonize +retrosheet: + version: 1.1.6 + title: Import Professional Baseball Data from 'Retrosheet' + maintainer: Colin Douglas + description: |- + A collection of tools to import and structure the (currently) single-season + event, game-log, roster, and schedule data available from . + In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse. + This package does the parsing on those files, returning the requested data in the most + practical R structure to use for sabermetric or other analyses. + date_publication: '2024-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=retrosheet + url_git: https://github.com/colindouglas/retrosheet +retry: + version: 0.1.1 + title: Repeated Evaluation + maintainer: Randy Lai + description: Provide simple mechanism to repeatedly evaluate an expression until + either it succeeds or timeout exceeded. It is useful in situations that random + failures could happen. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=retry + url_git: https://github.com/randy3k/retry +ReturnCurves: + version: 1.0.1 + title: Estimation of Return Curves + maintainer: Lídia André + description: Estimates the p-probability return curve proposed by Murphy-Barltrop + et al. (2023) . Implements pointwise and smooth estimation + of the angular dependence function introduced by Wadsworth and Tawn (2013) . + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ReturnCurves + url_git: https://github.com/lidiamandre/ReturnCurves +reutils: + version: 0.2.3 + title: Talk to the NCBI EUtils + maintainer: Gerhard Schöfl + description: |- + An interface to NCBI databases such as PubMed, GenBank, or GEO + powered by the Entrez Programming Utilities (EUtils). The nine EUtils + provide programmatic access to the NCBI Entrez query and database + system for searching and retrieving biological data. + date_publication: '2016-09-03' + bug_reports: https://github.com/gschofl/reutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reutils + url_git: https://github.com/gschofl/reutils +reval: + version: 3.1-0 + title: Argument Table Generation for Sensitivity Analysis + maintainer: Michael C Koohafkan + description: |- + Simplified scenario testing and sensitivity analysis, + redesigned to use packages 'future' and 'furrr'. Provides + functions for generating function argument sets using + one-factor-at-a-time (OFAT) and (sampled) permutations. + date_publication: '2022-06-29' + bug_reports: https://github.com/mkoohafkan/reval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reval + url_git: https://github.com/mkoohafkan/reval +revdbayes: + version: 1.5.5 + title: Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis + maintainer: Paul J. Northrop + description: |- + Provides functions for the Bayesian analysis of extreme value + models. The 'rust' package is + used to simulate a random sample from the required posterior distribution. + The functionality of 'revdbayes' is similar to the 'evdbayes' package + , which uses Markov Chain + Monte Carlo ('MCMC') methods for posterior simulation. In addition, there + are functions for making inferences about the extremal index, using + the models for threshold inter-exceedance times of Suveges and Davison + (2010) and Holesovsky and Fusek (2020) + . Also provided are d,p,q,r functions for + the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') + distributions that deal appropriately with cases where the shape parameter + is very close to zero. + date_publication: '2024-08-18' + bug_reports: https://github.com/paulnorthrop/revdbayes/issues + url: https://paulnorthrop.github.io/revdbayes/ + url_cran: https://CRAN.R-project.org/package=revdbayes + url_git: https://github.com/paulnorthrop/revdbayes +revealedPrefs: + version: 0.4.1 + title: Revealed Preferences and Microeconomic Rationality + maintainer: Julien Boelaert + description: Computation of (direct and indirect) revealed preferences, fast non-parametric + tests of rationality axioms (WARP, SARP, GARP), simulation of axiom-consistent + data, and detection of axiom-consistent subpopulations. Rationality tests follow + Varian (1982) , axiom-consistent subpopulations follow Crawford + and Pendakur (2012) . + date_publication: '2019-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=revealedPrefs + url_git: '' +revealjs: + version: '0.9' + title: R Markdown Format for 'reveal.js' Presentations + maintainer: JJ Allaire + description: |- + R Markdown format for 'reveal.js' presentations, a framework + for easily creating beautiful presentations using HTML. + date_publication: '2017-03-13' + bug_reports: https://github.com/rstudio/revealjs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=revealjs + url_git: https://github.com/rstudio/revealjs +RevEcoR: + version: 0.99.3 + title: Reverse Ecology Analysis on Microbiome + maintainer: Yang Cao + description: |- + An implementation of the reverse ecology framework. Reverse ecology + refers to the use of genomics to study ecology with no a priori assumptions + about the organism(s) under consideration, linking organisms to their + environment. It allows researchers to reconstruct the metabolic networks and + study the ecology of poorly characterized microbial species from their + genomic information, and has substantial potentials for microbial community + ecological analysis. + date_publication: '2016-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RevEcoR + url_git: '' +reveneraR: + version: 1.0.1 + title: Connect to Your 'Revenera' (Formerly 'Revulytics') Data + maintainer: Chris Umphlett + description: |- + Facilitates making a connection to the 'Revenera' + API and executing various queries. You can use it to get + event data and metadata. The 'Revenera' documentation + is available at . This package is + not supported by 'Flexera' (owner of the software). + date_publication: '2025-02-25' + bug_reports: https://github.com/chrisumphlett/reveneraR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=reveneraR + url_git: https://github.com/chrisumphlett/reveneraR +revengc: + version: 1.0.4 + title: Reverse Engineering Summarized Data + maintainer: Samantha Duchscherer + description: Decoupled (e.g. separate averages) and censored (e.g. > 100 species) + variables are continually reported by many well-established organizations (e.g. + World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), + World Bank, and various national censuses). The challenge therefore is to infer + what the original data could have been given summarized information. We present + an R package that reverse engineers decoupled and/or censored count data with + two main functions. The cnbinom.pars function estimates the average and dispersion + parameter of a censored univariate frequency table. The rec function reverse + engineers summarized data into an uncensored bivariate table of probabilities. + date_publication: '2019-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=revengc + url_git: https://github.com/GIST-ORNL/revengc +reverseR: + version: '0.2' + title: Linear Regression Stability to Significance Reversal + maintainer: Andrej-Nikolai Spiess + description: Tests linear regressions for significance reversal through leave-one(multiple)-out. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=reverseR + url_git: '' +revert: + version: 0.0.1 + title: Reversion Mutation Identifier for Sequencing Data + maintainer: Hui Xiao + description: |- + A tool for detecting reversions for a given pathogenic mutation from + next-generation DNA sequencing data. It analyses reads aligned to the locus of the + pathogenic mutation and reports reversion events where secondary mutations have + restored or undone the deleterious effect of the original pathogenic mutation, e.g., + secondary indels complement to a frameshift pathogenic mutation converting the + orignal frameshift mutation into inframe mutaions, deletions or SNVs that replaced + the original pathogenic mutation restoring the open reading frame, SNVs changing the + stop codon caused by the original nonsense SNV into an amino acid, etc. + date_publication: '2023-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=revert + url_git: '' +RevGadgets: + version: 1.2.1 + title: Visualization and Post-Processing of 'RevBayes' Analyses + maintainer: Carrie Tribble + description: Processes and visualizes the output of complex phylogenetic analyses + from the 'RevBayes' phylogenetic graphical modeling software. + date_publication: '2023-11-29' + bug_reports: https://github.com/revbayes/RevGadgets/issues + url: https://revbayes.github.io/tutorials/intro/revgadgets + url_cran: https://CRAN.R-project.org/package=RevGadgets + url_git: https://github.com/revbayes/RevGadgets +revgeo: + version: '0.15' + title: |- + Reverse Geocoding with the Photon Geocoder for OpenStreetMap, + Google Maps, and Bing + maintainer: Michael Hudecheck + description: Function revgeo() allows you to use the Photon geocoder for OpenStreetMap + , Google Maps , and Bing + to reverse geocode coordinate pairs with minimal hassle. + date_publication: '2017-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=revgeo + url_git: '' +ReviewR: + version: 2.3.10 + title: |- + A Light-Weight, Portable Tool for Reviewing Individual Patient + Records + maintainer: David Mayer + description: |- + A portable Shiny tool to explore patient-level electronic health record data + and perform chart review in a single integrated framework. This tool supports + browsing clinical data in many different formats including multiple versions + of the 'OMOP' common data model as well as the 'MIMIC-III' data model. In + addition, chart review information is captured and stored securely via the + Shiny interface in a 'REDCap' (Research Electronic Data Capture) project + using the 'REDCap' API. See the 'ReviewR' website for additional information, + documentation, and examples. + date_publication: '2023-09-01' + bug_reports: https://github.com/thewileylab/ReviewR/issues + url: https://reviewr.thewileylab.org/ + url_cran: https://CRAN.R-project.org/package=ReviewR + url_git: https://github.com/thewileylab/ReviewR/ +revpref: + version: 0.1.0 + title: Tools for Computational Revealed Preference Analysis + maintainer: Khushboo Surana + description: Tools to (i) check consistency of a finite set of consumer demand observations + with a number of revealed preference axioms at a given efficiency level, (ii) + compute goodness-of-fit indices when the data do not obey the axioms, and (iii) + compute power against uniformly random behavior. + date_publication: '2021-07-07' + bug_reports: https://github.com/ksurana21/revpref/issues + url: '' + url_cran: https://CRAN.R-project.org/package=revpref + url_git: https://github.com/ksurana21/revpref +RevSD: + version: 0.1.1 + title: Visualizing the Standard Deviation via Revolution + maintainer: Hieu Nguyen + description: We visualize the standard deviation of a data set as the radius of + a cylinder whose volume equals the total volume of several cylinders made by revolving + the empirical cumulative distribution function about the vertical line through + the mean. For more details see Sarkar and Rashid (2016) . + date_publication: '2024-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RevSD + url_git: '' +revss: + version: 2.0.0 + title: Robust Estimation in Very Small Samples + maintainer: Avraham Adler + description: |- + Implements the estimation techniques described in Rousseeuw & + Verboven (2002) for the location and + scale of very small samples. + date_publication: '2024-06-20' + bug_reports: https://github.com/aadler/revss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=revss + url_git: https://github.com/aadler/revss +Revticulate: + version: 1.0.0 + title: Interaction with "RevBayes" in R + maintainer: Caleb Charpentier + description: Interaction with "RevBayes" via R. Objects created in "RevBayes" can + be passed into the R environment, and many types can be converted into similar + R objects. To download "RevBayes", go to . + date_publication: '2022-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Revticulate + url_git: '' +revtools: + version: 0.4.1 + title: Tools to Support Evidence Synthesis + maintainer: Martin J. Westgate + description: Researchers commonly need to summarize scientific information, a process + known as 'evidence synthesis'. The first stage of a synthesis process (such as + a systematic review or meta-analysis) is to download a list of references from + academic search engines such as 'Web of Knowledge' or 'Scopus'. The traditional + approach to systematic review is then to sort these data manually, first by locating + and removing duplicated entries, and then screening to remove irrelevant content + by viewing titles and abstracts (in that order). 'revtools' provides interfaces + for each of these tasks. An alternative approach, however, is to draw on tools + from machine learning to visualise patterns in the corpus. In this case, you can + use 'revtools' to render ordinations of text drawn from article titles, keywords + and abstracts, and interactively select or exclude individual references, words + or topics. + date_publication: '2019-12-17' + bug_reports: https://github.com/mjwestgate/revtools/issues + url: https://revtools.net + url_cran: https://CRAN.R-project.org/package=revtools + url_git: '' +revulyticsR: + version: 0.0.3 + title: Connect to Your 'Revulytics' Data + maintainer: Chris Umphlett + description: |- + Facilitates making a connection to the + 'Revulytics' API and executing various queries. You can use it to + get event data and metadata. The Revulytics documentation + is available at . This + package is not supported by 'Flexera' (owner of the software). + date_publication: '2020-12-04' + bug_reports: https://github.com/chrisumphlett/revulyticsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=revulyticsR + url_git: https://github.com/chrisumphlett/revulyticsR +rewie: + version: 0.1.0 + title: |- + Data Preparation and Diagnostics for Random Effects Within + Estimator + maintainer: Scott Duxbury + description: |- + Diagnostics and data preparation for random effects within estimator, random effects + within-idiosyncratic estimator, between-within-idiosyncratic model, and cross-classified between model. + Mundlak, Yair (1978) . + Hausman, Jeffrey (1978) . + Allison, Paul (2009) . + Neuhaus, J.M., and J. D. Kalbfleisch (1998) . + date_publication: '2020-06-28' + bug_reports: https://github.com/sduxbury/rewie/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rewie + url_git: https://github.com/sduxbury/rewie +rex: + version: 1.2.1 + title: Friendly Regular Expressions + maintainer: Kevin Ushey + description: |- + A friendly interface for the construction of regular + expressions. + date_publication: '2021-11-26' + bug_reports: https://github.com/kevinushey/rex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rex + url_git: https://github.com/kevinushey/rex +rexer: + version: 1.0.0 + title: Random Exercises and Exams Generator + maintainer: Jose Samos + description: |- + The main purpose of this package is to streamline the + generation of exams that include random elements in exercises. + Exercises can be defined in a table, based on text and figures, and + may contain gaps to be filled with provided options. Exam documents + can be generated in various formats. It allows us to generate a + version for conducting the assessment and another version that + facilitates correction, linked through a code. + date_publication: '2024-03-04' + bug_reports: https://github.com/josesamos/rexer/issues + url: https://josesamos.github.io/rexer/ + url_cran: https://CRAN.R-project.org/package=rexer + url_git: https://github.com/josesamos/rexer +Rexperigen: + version: 0.2.1 + title: R Interface to Experigen + maintainer: Daniel Szeredi + description: |- + Provides convenience functions to communicate with + an Experigen server: Experigen () + is an online framework for creating linguistic experiments, + and it stores the results on a dedicated server. This package can be + used to retrieve the results from the server, and it is especially + helpful with registered experiments, as authentication with the server + has to happen. + date_publication: '2016-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rexperigen + url_git: https://github.com/aquincum/Rexperigen +rexpokit: + version: 0.26.6.14 + title: R Wrappers for EXPOKIT; Other Matrix Functions + maintainer: Nicholas J. Matzke + description: |- + Wraps some of the matrix exponentiation + utilities from EXPOKIT (), + a FORTRAN library that is widely recommended for matrix + exponentiation (Sidje RB, 1998. "Expokit: A Software Package + for Computing Matrix Exponentials." ACM Trans. Math. Softw. + 24(1): 130-156). EXPOKIT includes functions for + exponentiating both small, dense matrices, and large, sparse + matrices (in sparse matrices, most of the cells have value 0). + Rapid matrix exponentiation is useful in phylogenetics when we + have a large number of states (as we do when we are inferring + the history of transitions between the possible geographic + ranges of a species), but is probably useful in other ways as + well. NOTE: In case FORTRAN checks temporarily get rexpokit + archived on CRAN, see archived binaries at GitHub in: + nmatzke/Matzke_R_binaries (binaries install without compilation + of source code). + date_publication: '2023-11-22' + bug_reports: '' + url: http://phylo.wikidot.com/rexpokit + url_cran: https://CRAN.R-project.org/package=rexpokit + url_git: '' +rextendr: + version: 0.3.1 + title: Call Rust Code from R using the 'extendr' Crate + maintainer: Ilia Kosenkov + description: |- + Provides functions to compile and load Rust code from R, similar + to how 'Rcpp' or 'cpp11' allow easy interfacing with C++ code. Also provides + helper functions to create R packages that use Rust code. Under the hood, + the Rust crate 'extendr' is used to do all the heavy lifting. + date_publication: '2023-06-20' + bug_reports: https://github.com/extendr/rextendr/issues + url: https://extendr.github.io/rextendr/ + url_cran: https://CRAN.R-project.org/package=rextendr + url_git: '' +Rfacebook: + version: 0.6.15 + title: Access to Facebook API via R + maintainer: Pablo Barbera + description: Provides an interface to the Facebook API. + date_publication: '2017-05-25' + bug_reports: https://github.com/pablobarbera/Rfacebook/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rfacebook + url_git: https://github.com/pablobarbera/Rfacebook +rfacebookstat: + version: 2.12.0 + title: Load Data from Facebook API Marketing + maintainer: Alexey Seleznev + description: |- + Load data by campaigns, ads, ad sets and insights, ad account and business manager + from Facebook Marketing API into R. For more details see official documents by Facebook + Marketing API . + date_publication: '2025-01-13' + bug_reports: https://github.com/selesnow/rfacebookstat/issues + url: https://selesnow.github.io/rfacebookstat/ + url_cran: https://CRAN.R-project.org/package=rfacebookstat + url_git: '' +rfacts: + version: 0.2.1 + title: R Interface to 'FACTS' on Unix-Like Systems + maintainer: William Michael Landau + description: |- + The 'rfacts' package is an R interface to the + Fixed and Adaptive Clinical Trial Simulator ('FACTS') + on Unix-like systems. It programmatically invokes 'FACTS' to run clinical + trial simulations, and it aggregates simulation output data + into tidy data frames. These capabilities provide end-to-end + automation for large-scale simulation pipelines, and + they enhance computational reproducibility. + For more information on 'FACTS' itself, + please visit . + date_publication: '2022-08-19' + bug_reports: https://github.com/EliLillyCo/rfacts/issues + url: https://elilillyco.github.io/rfacts/ + url_cran: https://CRAN.R-project.org/package=rfacts + url_git: https://github.com/EliLillyCo/rfacts +rfars: + version: 1.2.0 + title: Download and Analyze Crash Data + maintainer: Steve Jackson + description: Download crash data from the National Highway Traffic Safety Administration + and prepare it for research. + date_publication: '2024-04-06' + bug_reports: https://github.com/s87jackson/rfars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rfars + url_git: https://github.com/s87jackson/rfars +Rfast: + version: 2.1.5 + title: A Collection of Efficient and Extremely Fast R Functions + maintainer: Manos Papadakis + description: 'A collection of fast (utility) functions for data analysis. Column + and row wise means, medians, variances, minimums, maximums, many t, F and G-square + tests, many regressions (normal, logistic, Poisson), are some of the many fast + functions. References: a) Tsagris M., Papadakis M. (2018). Taking R to its limits: + 70+ tips. PeerJ Preprints 6:e26605v1 . b) + Tsagris M. and Papadakis M. (2018). Forward regression in R: from the extreme + slow to the extreme fast. Journal of Data Science, 16(4): 771--780. . + c) Chatzipantsiou C., Dimitriadis M., Papadakis M. and Tsagris M. (2020). Extremely + Efficient Permutation and Bootstrap Hypothesis Tests Using Hypothesis Tests Using + R. Journal of Modern Applied Statistical Methods, 18(2), eP2898. . + d) Tsagris M., Papadakis M., Alenazi A. and Alzeley O. (2024). Computationally + Efficient Outlier Detection for High-Dimensional Data Using the MDP Algorithm. + Computation, 12(9): 185. . e) Tsagris M. and + Papadakis M. (2025). Fast and light-weight energy statistics using the R package + Rfast. .' + date_publication: '2025-02-27' + bug_reports: https://github.com/RfastOfficial/Rfast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rfast + url_git: https://github.com/RfastOfficial/Rfast +Rfast2: + version: 0.1.5.2 + title: A Collection of Efficient and Extremely Fast R Functions II + maintainer: Manos Papadakis + description: 'A collection of fast statistical and utility functions for data analysis. + Functions for regression, maximum likelihood, column-wise statistics and many + more have been included. C++ has been utilized to speed up the functions. References: + Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints + 6:e26605v1 .' + date_publication: '2024-03-10' + bug_reports: https://github.com/RfastOfficial/Rfast2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rfast2 + url_git: https://github.com/RfastOfficial/Rfast2 +RFclust: + version: 0.1.2 + title: Random Forest Cluster Analysis + maintainer: Ankur Chakravarthy + description: Tools to perform random forest consensus clustering of different data + types. The package is designed to accept a list of matrices from different assays, + typically from high-throughput molecular profiling so that class discovery may + be jointly performed. For references, please see Tao Shi & Steve Horvath (2006) + & Monti et al (2003) + . + date_publication: '2022-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RFclust + url_git: '' +RfEmpImp: + version: 2.1.8 + title: Multiple Imputation using Chained Random Forests + maintainer: Shangzhi Hong + description: |- + An R package for multiple imputation using chained random forests. + Implemented methods can handle missing data in mixed types of variables by + using prediction-based or node-based conditional distributions constructed + using random forests. For prediction-based imputation, the method based on + the empirical distribution of out-of-bag prediction errors of random forests + and the method based on normality assumption for prediction errors of random + forests are provided for imputing continuous variables. And the method based + on predicted probabilities is provided for imputing categorical variables. + For node-based imputation, the method based on the conditional distribution + formed by the predicting nodes of random forests, and the method based on + proximity measures of random forests are provided. More details of the + statistical methods can be found in Hong et al. (2020) . + date_publication: '2022-10-20' + bug_reports: https://github.com/shangzhi-hong/RfEmpImp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RfEmpImp + url_git: https://github.com/shangzhi-hong/RfEmpImp +rFerns: + version: 5.0.0 + title: Random Ferns Classifier + maintainer: Miron Bartosz Kursa + description: Provides the random ferns classifier by Ozuysal, Calonder, Lepetit + and Fua (2009) , modified for generic and multi-label + classification and featuring OOB error approximation and importance measure as + introduced in Kursa (2014) . + date_publication: '2021-09-22' + bug_reports: https://gitlab.com/mbq/rFerns/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rFerns + url_git: https://gitlab.com/mbq/rFerns +rfieldclimate: + version: 0.1.1 + title: Client for the 'FieldClimate' API + maintainer: Eduard Szöcs + description: |- + Provides functionality to interact with the + 'FieldClimate' API . + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rfieldclimate + url_git: '' +rfigshare: + version: 0.3.8 + title: An R Interface to 'figshare' + maintainer: Carl Boettiger + description: An R interface to 'figshare'. + date_publication: '2022-05-09' + bug_reports: https://github.com/ropensci-archive/rfigshare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rfigshare + url_git: https://github.com/ropensci-archive/rfigshare +rfinterval: + version: 1.0.0 + title: Predictive Inference for Random Forests + maintainer: Haozhe Zhang + description: 'An integrated package for constructing random forest prediction intervals + using a fast implementation package ''ranger''. This package can apply the following + three methods described in Haozhe Zhang, Joshua Zimmerman, Dan Nettleton, and + Daniel J. Nordman (2019) : the out-of-bag prediction + interval, the split conformal method, and the quantile regression forest.' + date_publication: '2019-07-18' + bug_reports: http://github.com/haozhestat/rfinterval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rfinterval + url_git: http://github.com/haozhestat/rfinterval +rfishbase: + version: 5.0.1 + title: R Interface to 'FishBase' + maintainer: Carl Boettiger + description: |- + A programmatic interface to 'FishBase', re-written + based on an accompanying 'RESTful' API. Access tables describing over 30,000 + species of fish, their biology, ecology, morphology, and more. This package also + supports experimental access to 'SeaLifeBase' data, which contains + nearly 200,000 species records for all types of aquatic life not covered by + 'FishBase.' + date_publication: '2025-01-12' + bug_reports: https://github.com/ropensci/rfishbase/issues + url: https://docs.ropensci.org/rfishbase/ + url_cran: https://CRAN.R-project.org/package=rfishbase + url_git: https://github.com/ropensci/rfishbase +RFishBC: + version: 0.2.7 + title: Back-Calculation of Fish Length + maintainer: Derek H. Ogle + description: |- + Helps fisheries scientists collect measurements from calcified + structures and back-calculate estimated lengths at previous ages using + standard procedures and models. This is intended to replace much of the + functionality provided by the now out-dated 'fishBC' software + (). + date_publication: '2023-12-20' + bug_reports: https://github.com/fishR-Core-Team/RFishBC/issues + url: https://fishr-core-team.github.io/RFishBC/ + url_cran: https://CRAN.R-project.org/package=RFishBC + url_git: '' +rfishdraw: + version: 0.1.0 + title: Automatically Generated Fish Drawings via JavaScript + maintainer: Liuyong Ding + description: Automatic generation of fish drawings based on JavaScript library , + including JavaScript code for dynamic generation of fish drawings. + date_publication: '2021-09-08' + bug_reports: https://github.com/Otoliths/rfishdraw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rfishdraw + url_git: https://github.com/Otoliths/rfishdraw +rfisheries: + version: '0.2' + title: '''Programmatic Interface to the ''openfisheries.org'' API''' + maintainer: Karthik Ram + description: |- + A programmatic interface to 'openfisheries.org'. This package is + part of the 'rOpenSci' suite (http://ropensci.org). + date_publication: '2016-02-19' + bug_reports: http://www.github.com/ropensci/rfisheries/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=rfisheries + url_git: http://www.github.com/ropensci/rfisheries +rfishnet2: + version: 0.2.0 + title: Exploratory Data Analysis for FishNet2 Data + maintainer: Kennedy Dorsey + description: |- + Provides data processing and summarization of data from FishNet2.net + in text and graphical outputs. Allows efficient filtering of information and + data cleaning. + date_publication: '2020-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rfishnet2 + url_git: https://github.com/kdors/rfishnet2 +Rfit: + version: 0.27.0 + title: Rank-Based Estimation for Linear Models + maintainer: John Kloke + description: |- + Rank-based (R) estimation and inference for linear models. Estimation + is for general scores and a library of commonly used score + functions is included. + date_publication: '2024-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rfit + url_git: '' +rflashtext: + version: 1.0.0 + title: FlashText Algorithm for Finding and Replacing Words + maintainer: Abraham Jaimes + description: Implementation of the FlashText algorithm, by Singh (2017) . + It can be used to find and replace words in a given text with only one pass over + the document. + date_publication: '2023-06-30' + bug_reports: https://github.com/AbrJA/rflashtext/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rflashtext + url_git: https://github.com/AbrJA/rflashtext +RFlocalfdr: + version: '0.9' + title: Significance Level for Random Forest Impurity Importance Scores + maintainer: Robert Dunne + description: |- + Sets a significance level for Random Forest MDI (Mean Decrease in Impurity, Gini or + sum of squares) variable importance scores, using an empirical Bayes approach. + See Dunne et al. (2022) . + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RFlocalfdr + url_git: '' +RFlocalfdr.data: + version: 0.0.3 + title: Data for the Vignette and Examples in 'RFlocalfdr' + maintainer: Robert Dunne + description: |- + Data for the vignette and examples in 'RFlocalfdr'. Contains a dataset of 1103547 importance values, + and the table of variables used in the random forest splits. The data is Chromosome 22 taken from Auton et al. + (2015) . It also contains a 51 samples by 22283 genes data set taken from + Spira et al. (2004) . + date_publication: '2023-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RFlocalfdr.data + url_git: '' +RFLPtools: + version: '2.0' + title: Tools to Analyse RFLP Data + maintainer: Matthias Kohl + description: Provides functions to analyse DNA fragment samples (i.e. derived from + RFLP-analysis) and standalone BLAST report files (i.e. DNA sequence analysis). + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RFLPtools + url_git: '' +rflsgen: + version: 1.2.2 + title: Neutral Landscape Generator with Targets on Landscape Indices + maintainer: Dimitri Justeau-Allaire + description: |- + Interface to the 'flsgen' neutral landscape generator . It allows to + - Generate fractal terrain; + - Generate landscape structures satisfying user targets over landscape indices; + - Generate landscape raster from landscape structures. + date_publication: '2024-05-21' + bug_reports: https://github.com/dimitri-justeau/rflsgen/issues + url: https://dimitri-justeau.github.io/rflsgen/ + url_cran: https://CRAN.R-project.org/package=rflsgen + url_git: '' +rfm: + version: 0.3.0 + title: Recency, Frequency and Monetary Value Analysis + maintainer: Aravind Hebbali + description: |- + Tools for RFM (recency, frequency and monetary value) analysis. + Generate RFM score from both transaction and customer level data. Visualize the + relationship between recency, frequency and monetary value using heatmap, + histograms, bar charts and scatter plots. Includes a 'shiny' app for + interactive segmentation. References: + i. Blattberg R.C., Kim BD., Neslin S.A (2008) . + date_publication: '2024-02-26' + bug_reports: https://github.com/rsquaredacademy/rfm/issues + url: https://rfm.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=rfm + url_git: https://github.com/rsquaredacademy/rfm +Rfmtool: + version: 5.0.4 + title: Fuzzy Measure Tools + maintainer: Gleb Beliakov + description: |- + Various tools for handling fuzzy measures, calculating Shapley value and interaction index, Choquet and Sugeno integrals, as well as fitting fuzzy measures to empirical data are provided. Construction of fuzzy measures from empirical data is done by solving a linear programming problem by using 'lpsolve' package, whose source in C adapted to the R environment + is included. The description of the basic theory of fuzzy measures is in the manual in the Doc folder in this package. Please refer to the following: + [1] + [2] G. Beliakov, H. Bustince, T. Calvo, 'A Practical Guide to Averaging', Springer, (2016, ISBN: 978-3-319-24753-3). + [3] G. Beliakov, S. James, J-Z. Wu, 'Discrete Fuzzy Measures', Springer, (2020, ISBN: 978-3-030-15305-2). + date_publication: '2024-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rfmtool + url_git: '' +rfoaas: + version: 2.3.2 + title: R Interface to 'FOAAS' + maintainer: Dirk Eddelbuettel + description: R access to the 'FOAAS' (F... Off As A Service) web service is provided. + date_publication: '2022-07-13' + bug_reports: https://github.com/eddelbuettel/rfoaas/issues + url: http://dirk.eddelbuettel.com/code/rfoaas.html + url_cran: https://CRAN.R-project.org/package=rfoaas + url_git: https://github.com/eddelbuettel/rfoaas/ +RFOC: + version: 3.4-10 + title: |- + Graphics for Spherical Distributions and Earthquake Focal + Mechanisms + maintainer: Jonathan M. Lees + description: Graphics for statistics on a sphere, as applied to geological fault + data, crystallography, earthquake focal mechanisms, radiation patterns, ternary + plots and geographical/geological maps. Non-double couple plotting of focal spheres + and source type maps are included for statistical analysis of moment tensors. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RFOC + url_git: '' +rfold: + version: 0.2.0 + title: Working with many R Folders Within an R Package + maintainer: Mohamed El Fodil Ihaddaden + description: |2- + + Allows developers to work with many R folders inside a package. It offers functionalities to transfer R scripts (saved outside the R folder) into + the R folder while making additional checks. + date_publication: '2024-02-12' + bug_reports: https://github.com/feddelegrand7/rfold/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rfold + url_git: https://github.com/feddelegrand7/rfold +Rfolding: + version: '1.0' + title: The Folding Test of Unimodality + maintainer: Alban Siffer + description: |- + The basic algorithm to perform the folding test of unimodality. + Given a dataset X (d dimensional, n samples), the test checks whether the + distribution of the data are rather unimodal or rather multimodal. This + package stems from the following research publication: + Siffer Alban, Pierre-Alain Fouque, Alexandre Termier, and Christine Largouët. + "Are your data gathered?" In Proceedings of the 24th ACM SIGKDD International + Conference on Knowledge Discovery Data Mining, pp. 2210-2218. ACM, 2018. + . + date_publication: '2018-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rfolding + url_git: '' +rfordummies: + version: 0.1.6 + title: Code Examples to Accompany the Book "R for Dummies" + maintainer: Andrie de Vries + description: |- + Contains all the code examples in the book "R for Dummies" (2nd + edition) by Andrie de Vries and Joris Meys. You can view the table of + contents as well as the sample code for each chapter. + date_publication: '2022-02-25' + bug_reports: https://github.com/rfordummies/rfordummies/issues + url: https://rfordummies.com + url_cran: https://CRAN.R-project.org/package=rfordummies + url_git: '' +Rforestry: + version: 0.10.0 + title: |- + Random Forests, Linear Trees, and Gradient Boosting for + Inference and Interpretability + maintainer: Theo Saarinen + description: |- + Provides fast implementations of Honest Random Forests, + Gradient Boosting, and Linear Random Forests, with an emphasis on inference + and interpretability. Additionally contains methods for variable + importance, out-of-bag prediction, regression monotonicity, and + several methods for missing data imputation. Soren R. Kunzel, + Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon (2019) . + date_publication: '2023-03-25' + bug_reports: https://github.com/forestry-labs/Rforestry/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rforestry + url_git: https://github.com/forestry-labs/Rforestry +RFormatter: + version: 0.1.1 + title: R Source Code Formatter + maintainer: Benjamin Fischer + description: |- + The R Formatter formats R source code. It is very much based on + formatR, but tries to improve it by heuristics. For example, spaces can be + forced around the division operator "/". + date_publication: '2016-05-13' + bug_reports: https://github.com/evolutics/RFormatter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RFormatter + url_git: https://github.com/evolutics/RFormatter +rfPermute: + version: 2.5.2 + title: |- + Estimate Permutation p-Values for Random Forest Importance + Metrics + maintainer: Eric Archer + description: |- + Estimate significance of importance metrics + for a Random Forest model by permuting the response + variable. Produces null distribution of importance + metrics for each predictor variable and p-value of + observed. Provides summary and visualization functions for 'randomForest' + results. + date_publication: '2023-08-23' + bug_reports: https://github.com/EricArcher/rfPermute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rfPermute + url_git: https://github.com/EricArcher/rfPermute +RFplus: + version: 1.3-0 + title: |- + Machine Learning for Merging Satellite and Ground Precipitation + Data + maintainer: Jonnathan Augusto Landi Bermeo + description: A machine learning algorithm that merges satellite and ground precipitation + data using Random Forest for spatial prediction, residual modeling for bias correction, + and quantile mapping for adjustment, ensuring accurate estimates across temporal + scales and regions. + date_publication: '2025-02-24' + bug_reports: https://github.com/Jonnathan-Landi/RFplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RFplus + url_git: https://github.com/Jonnathan-Landi/RFplus +RFPM: + version: '1.1' + title: Floating Percentile Model + maintainer: Brian Church + description: Floating Percentile Model with additional functions for optimizing + inputs and evaluating outputs and assumptions. + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RFPM + url_git: '' +Rfractran: + version: 1.0.1 + title: A 'FRACTRAN' Interpreter and Some Helper Functions + maintainer: Carl Witthoft + description: '''FRACTRAN'' is an obscure yet tantalizing programming language invented + by John Conway of ''Game of Life'' fame. The code consists of a sequence of fractions. + The rules are simple. First, select an integer to initialize the process. Second, + multiply the integer by the first fraction. If an integer results, start again + with the new integer. If not, try the next fraction. Finally, if no such multiplication + yields an integer, terminate the program. For more information, see + .' + date_publication: '2023-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rfractran + url_git: '' +rFSA: + version: 0.9.6 + title: |- + Feasible Solution Algorithm for Finding Best Subsets and + Interactions + maintainer: Joshua Lambert + description: |- + Assists in statistical model building to find optimal and semi-optimal higher order interactions + and best subsets. Uses the lm(), glm(), and other R functions to fit models generated from a feasible + solution algorithm. Discussed in Subset Selection in Regression, A Miller (2002). Applied and explained + for least median of squares in Hawkins (1993) . The feasible solution + algorithm comes up with model forms of a specific type that can have fixed variables, higher order + interactions and their lower order terms. + date_publication: '2020-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rFSA + url_git: '' +Rfssa: + version: 3.1.0 + title: Functional Singular Spectrum Analysis + maintainer: Hossein Haghbin + description: Methods and tools for implementing functional singular spectrum analysis + and related techniques. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rfssa + url_git: https://github.com/haghbinh/Rfssa +rfVarImpOOB: + version: 1.0.3 + title: Unbiased Variable Importance for Random Forests + maintainer: Markus Loecher + description: |- + Computes a novel variable importance for random forests: Impurity reduction importance scores for out-of-bag (OOB) data complementing the existing inbag Gini importance, see also . + The Gini impurities for inbag and OOB data are combined in three different ways, after which the information gain is computed at each split. + This gain is aggregated for each split variable in a tree and averaged across trees. + date_publication: '2022-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rfVarImpOOB + url_git: '' +rfvimptest: + version: 0.1.3 + title: |- + Sequential Permutation Testing of Random Forest Variable + Importance Measures + maintainer: Roman Hornung + description: |- + Sequential permutation testing for statistical + significance of predictors in random forests. The main function + of the package is rfvimptest(), which allows to test for the + statistical significance of predictors in random forests using different + (sequential) permutation test strategies. The advantage of + sequential over conventional permutation tests is that they + are computationally considerably less intensive, as the sequential + procedure is stopped as soon as there is sufficient evidence + for either the null or the alternative hypothesis. + date_publication: '2023-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rfvimptest + url_git: '' +rfviz: + version: 1.0.1 + title: Interactive Visualization Tool for Random Forests + maintainer: Chris Kuchar + description: |- + An interactive data visualization and exploration toolkit + that implements Breiman and Cutler's original random forest Java based + visualization tools in R, for supervised and unsupervised classification and + regression within the algorithm random forest. + date_publication: '2022-02-23' + bug_reports: '' + url: https://www.stat.berkeley.edu/~breiman/RandomForests/cc_graphics.htm + url_cran: https://CRAN.R-project.org/package=rfviz + url_git: '' +rgabriel: + version: '0.9' + title: |- + Gabriel Multiple Comparison Test and Plot the Confidence + Interval on Barplot + maintainer: Miao YU + description: |- + Analyze multi-level one-way + experimental designs where there are unequal sample + sizes and population variance homogeneity can not be assumed. + To conduct the Gabriel test , create two vectors: one for your + observations and one for the factor level of each observation. + The function, rgabriel, conduct the test and save the output as + a vector to input into the gabriel.plot function, which produces + a confidence interval plot for Multiple Comparison. + date_publication: '2022-05-09' + bug_reports: '' + url: http://yufree.github.io/rgabriel/ + url_cran: https://CRAN.R-project.org/package=rgabriel + url_git: https://github.com/yufree/rgabriel +RGAN: + version: 0.1.1 + title: Generative Adversarial Nets (GAN) in R + maintainer: Marcel Neunhoeffer + description: |- + An easy way to get started with Generative Adversarial Nets (GAN) in R. The GAN algorithm was initially + described by Goodfellow et al. 2014 . A GAN can be used to learn the joint distribution of complex data by + comparison. A GAN consists of two neural networks a Generator and a Discriminator, where the two + neural networks play an adversarial minimax game. + Built-in GAN models make the training of GANs in R possible in one line and make it easy to + experiment with different design choices (e.g. different network architectures, value functions, optimizers). + The built-in GAN models work with tabular data (e.g. to produce synthetic data) and image data. + Methods to post-process the output of GAN models to enhance the quality of samples are available. + date_publication: '2022-03-29' + bug_reports: https://github.com/mneunhoe/RGAN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RGAN + url_git: https://github.com/mneunhoe/RGAN +RGAP: + version: 0.1.1 + title: Production Function Output Gap Estimation + maintainer: Sina Streicher + description: The output gap indicates the percentage difference between the actual + output of an economy and its potential. Since potential output is a latent process, + the estimation of the output gap poses a challenge and numerous filtering techniques + have been proposed. 'RGAP' facilitates the estimation of a Cobb-Douglas production + function type output gap, as suggested by the European Commission (Havik et al. + 2014) . To that end, the non-accelerating + wage rate of unemployment (NAWRU) and the trend of total factor productivity (TFP) + can be estimated in two bivariate unobserved component models by means of Kalman + filtering and smoothing. 'RGAP' features a flexible modeling framework for the + appropriate state-space models and offers frequentist as well as Bayesian estimation + techniques. Additional functionalities include direct access to the 'AMECO' + database and automated model selection procedures. See the paper by Streicher + (2022) for details. + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGAP + url_git: '' +rgbif: + version: 3.8.1 + title: Interface to the Global Biodiversity Information Facility API + maintainer: John Waller + description: |- + A programmatic interface to the Web Service methods + provided by the Global Biodiversity Information Facility (GBIF; + ). GBIF is a database + of species occurrence records from sources all over the globe. + rgbif includes functions for searching for taxonomic names, + retrieving information on data providers, getting species occurrence + records, getting counts of occurrence records, and using the GBIF + tile map service to make rasters summarizing huge amounts of data. + date_publication: '2024-09-27' + bug_reports: https://github.com/ropensci/rgbif/issues + url: https://docs.ropensci.org/rgbif/(documentation) + url_cran: https://CRAN.R-project.org/package=rgbif + url_git: https://github.com/ropensci/rgbif(devel) +RGBM: + version: 1.0-11 + title: |- + LS-TreeBoost and LAD-TreeBoost for Gene Regulatory Network + Reconstruction + maintainer: Raghvendra Mall + description: Provides an implementation of Regularized LS-TreeBoost & LAD-TreeBoost + algorithm for Regulatory Network inference from any type of expression data (Microarray/RNA-seq + etc). + date_publication: '2023-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGBM + url_git: '' +Rgbp: + version: 1.1.4 + title: |- + Hierarchical Modeling and Frequency Method Checking on + Overdispersed Gaussian, Poisson, and Binomial Data + maintainer: Joseph Kelly + description: We utilize approximate Bayesian machinery to fit two-level conjugate + hierarchical models on overdispersed Gaussian, Poisson, and Binomial data and + evaluates whether the resulting approximate Bayesian interval estimates for random + effects meet the nominal confidence levels via frequency coverage evaluation. + The data that Rgbp assumes comprise observed sufficient statistic for each random + effect, such as an average or a proportion of each group, without population-level + data. The approximate Bayesian tool equipped with the adjustment for density + maximization produces approximate point and interval estimates for model parameters + including second-level variance component, regression coefficients, and random + effect. For the Binomial data, the package provides an option to produce posterior + samples of all the model parameters via the acceptance-rejection method. The package + provides a quick way to evaluate coverage rates of the resultant Bayesian interval + estimates for random effects via a parametric bootstrapping, which we call frequency + method checking. + date_publication: '2019-12-17' + bug_reports: https://github.com/jyklly/Rgbp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rgbp + url_git: '' +RGCCA: + version: 3.0.3 + title: |- + Regularized and Sparse Generalized Canonical Correlation + Analysis for Multiblock Data + maintainer: Arthur Tenenhaus + description: |- + Multi-block data analysis concerns the analysis of several + sets of variables (blocks) observed on the same group of individuals. + The main aims of the RGCCA package are: to study the relationships + between blocks and to identify subsets of variables of each block + which are active in their relationships with the other blocks. This + package allows to (i) run R/SGCCA and related methods, + (ii) help the user to find out the optimal parameters for R/SGCCA such + as regularization parameters (tau or sparsity), (iii) evaluate the + stability of the RGCCA results and their significance, (iv) build predictive + models from the R/SGCCA. (v) Generic print() + and plot() functions apply to all these functionalities. + date_publication: '2023-12-11' + bug_reports: https://github.com/rgcca-factory/RGCCA/issues + url: https://rgcca-factory.github.io/RGCCA/ + url_cran: https://CRAN.R-project.org/package=RGCCA + url_git: https://github.com/rgcca-factory/RGCCA +RGCxGC: + version: 1.2.0 + title: |- + Preprocessing and Multivariate Analysis of Bidimensional Gas + Chromatography Data + maintainer: Cristian Quiroz-Moreno + description: |- + Toolbox for chemometrics analysis of bidimensional gas + chromatography data. This package import data for common scientific data + format (NetCDF) and fold it to 2D chromatogram. Then, it can perform + preprocessing and multivariate analysis. In the preprocessing algorithms, + baseline correction, smoothing, and peak alignment are available. + While in multivariate analysis, multiway principal component analysis is + incorporated. + date_publication: '2022-12-14' + bug_reports: https://github.com/DanielQuiroz97/RGCxGC/issues + url: https://danielquiroz97.github.io/RGCxGC/ + url_cran: https://CRAN.R-project.org/package=RGCxGC + url_git: https://github.com/DanielQuiroz97/RGCxGC +rgdax: + version: 1.2.1 + title: |- + Wrapper for 'Coinbase Pro (erstwhile GDAX)' Cryptocurrency + Exchange + maintainer: Dheeraj Agarwal + description: |- + Allow access to both public and private end points to Coinbase Pro (erstwhile GDAX) + cryptocurrency exchange. For authenticated flow, users must have valid api, secret and passphrase to be able to connect. + date_publication: '2021-08-03' + bug_reports: https://github.com/DheerajAgarwal/rgdax/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgdax + url_git: https://github.com/DheerajAgarwal/rgdax/ +RGE: + version: '1.0' + title: Response from Genotype to Environment + maintainer: Jose Miguel Cotes Torres + description: 'Compute yield-stability index based on Bayesian methodology, which + is useful for analyze multi-environment trials in plant breeding programs. References: + Cotes Torres JM, Gonzalez Jaimes EP, and Cotes Torres A (2016) + Seleccion de Genotipos con Alta Respuesta y Estabilidad Fenotipica en Pruebas + Regionales: Recuperando el Concepto Biologico.' + date_publication: '2021-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGE + url_git: '' +rgee: + version: 1.1.7 + title: R Bindings for Calling the 'Earth Engine' API + maintainer: Cesar Aybar + description: |- + Earth Engine client library for R. All + of the 'Earth Engine' API classes, modules, and functions are made available. Additional + functions implemented include importing (exporting) of Earth Engine spatial objects, + extraction of time series, interactive map display, assets management interface, + and metadata display. See for further details. + date_publication: '2023-09-27' + bug_reports: https://github.com/r-spatial/rgee/issues/ + url: https://r-spatial.github.io/rgee/ + url_cran: https://CRAN.R-project.org/package=rgee + url_git: https://github.com/r-spatial/rgee/ +rgeedim: + version: 0.2.7 + title: |- + Search, Composite, and Download 'Google Earth Engine' Imagery + with the 'Python' Module 'geedim' + maintainer: Andrew Brown + description: |- + Search, composite, and download 'Google Earth Engine' imagery with 'reticulate' bindings for the 'Python' module 'geedim' by Dugal Harris. Read the 'geedim' documentation here: . + Wrapper functions are provided to make it more convenient to use 'geedim' to download images larger than the 'Google Earth Engine' size limit . + By default the "High Volume" API endpoint is used to download data and this URL can be customized during initialization of the package. + date_publication: '2024-01-18' + bug_reports: https://github.com/brownag/rgeedim/issues + url: https://humus.rocks/rgeedim/ + url_cran: https://CRAN.R-project.org/package=rgeedim + url_git: https://github.com/brownag/rgeedim +rgen: + version: 0.0.1 + title: Random Sampling Distribution C++ Routines for Armadillo + maintainer: James Balamuta + description: |- + Provides popular sampling distributions C++ routines based in + armadillo through a header file approach. + date_publication: '2017-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rgen + url_git: '' +RGenData: + version: '1.0' + title: |- + Generates Multivariate Nonnormal Data and Determines How Many + Factors to Retain + maintainer: John Ruscio + description: |- + The GenDataSample() and GenDataPopulation() functions create, + respectively, a sample or population of multivariate nonnormal data + using methods described in Ruscio and Kaczetow (2008). Both of these + functions call a FactorAnalysis() function to reproduce a correlation + matrix. The EFACompData() function allows users to determine how many + factors to retain in an exploratory factor analysis of an empirical data + set using a method described in Ruscio and Roche (2012). The latter + function uses populations of comparison data created by calling the + GenDataPopulation() function. + . + . + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGenData + url_git: '' +RGENERATE: + version: 1.3.7 + title: Tools to Generate Vector Time Series + maintainer: Emanuele Cordano + description: |- + A method 'generate()' is implemented in this package for the random + generation of vector time series according to models obtained by 'RMAWGEN', + 'vars' or other packages. This package was created to generalize the + algorithms of the 'RMAWGEN' package for the analysis and generation of any + environmental vector time series. + date_publication: '2022-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGENERATE + url_git: https://github.com/ecor/RGENERATE +RGENERATEPREC: + version: 1.2.9 + title: Tools to Generate Daily-Precipitation Time Series + maintainer: Emanuele Cordano + description: |- + The method 'generate()' is extended for spatial multi-site + stochastic generation of daily precipitation. It generates precipitation + occurrence in several sites using logit regression (Generalized Linear + Models) and the approach by D.S. Wilks (1998) . + date_publication: '2022-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGENERATEPREC + url_git: https://github.com/ecor/RGENERATEPREC +RGenetics: + version: '0.1' + title: R packages for genetics research + maintainer: Felix Yanhui Fan + description: R packages for genetics research + date_publication: '2013-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGenetics + url_git: '' +rgenius: + version: 0.1.0 + title: Get 'Genius' API Lyrics + maintainer: Alberto Almuiña + description: |- + Download the lyrics of your favorite songs in text and table formats. + Also search for related songs or song information. + More information: . + date_publication: '2020-05-11' + bug_reports: https://github.com/AlbertoAlmuinha/rgenius/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgenius + url_git: https://github.com/AlbertoAlmuinha/rgenius +rgenoud: + version: 5.9-0.11 + title: R Version of GENetic Optimization Using Derivatives + maintainer: Jasjeet Singh Sekhon + description: A genetic algorithm plus derivative optimizer. + date_publication: '2024-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rgenoud + url_git: https://github.com/JasjeetSekhon/rgenoud +rgeoda: + version: 0.0.11-1 + title: R Library for Spatial Data Analysis + maintainer: Xun Li + description: |- + Provides spatial data analysis functionalities including Exploratory Spatial Data Analysis, + Spatial Cluster Detection and Clustering Analysis, Regionalization, etc. based on the C++ source code + of 'GeoDa', which is an open-source software tool that serves as an introduction to spatial data analysis. + The 'GeoDa' software and its documentation are available at . + date_publication: '2024-12-19' + bug_reports: https://github.com/geodacenter/rgeoda/issues/ + url: https://geodacenter.github.io/rgeoda/ + url_cran: https://CRAN.R-project.org/package=rgeoda + url_git: https://github.com/geodacenter/rgeoda/ +RGeode: + version: 0.1.0 + title: Geometric Density Estimation + maintainer: Lorenzo Rimella + description: Provides the hybrid Bayesian method Geometric Density Estimation. On + the one hand, it scales the dimension of our data, on the other it performs inference. + The method is fully described in the paper "Scalable Geometric Density Estimation" + by Y. Wang, A. Canale, D. Dunson (2016) . + date_publication: '2017-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGeode + url_git: '' +rgeomstats: + version: 0.0.1 + title: Interface to 'Geomstats' + maintainer: Aymeric Stamm + description: |- + Provides an interface to the Python package 'Geomstats' authored by Miolane et + al. (2020) . + date_publication: '2022-11-04' + bug_reports: https://github.com/LMJL-Alea/rgeomstats/issues + url: https://lmjl-alea.github.io/rgeomstats/ + url_cran: https://CRAN.R-project.org/package=rgeomstats + url_git: https://github.com/LMJL-Alea/rgeomstats +rgeopat2: + version: 0.4.0 + title: Additional Functions for 'GeoPAT' 2 + maintainer: Jakub Nowosad + description: |- + Supports analysis of spatial data processed with the 'GeoPAT' 2 + software . + Available features include creation of a grid based on the 'GeoPAT' 2 + grid header file and reading a 'GeoPAT' 2 text outputs. + date_publication: '2023-09-18' + bug_reports: https://github.com/Nowosad/rgeopat2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgeopat2 + url_git: https://github.com/Nowosad/rgeopat2 +rgexf: + version: 0.16.3 + title: Build, Import, and Export GEXF Graph Files + maintainer: George Vega Yon + description: Create, read, and write 'GEXF' (Graph Exchange 'XML' Format) graph + files (used in 'Gephi' and others). Using the 'XML' package, rgexf allows reading + and writing GEXF files, including attributes, 'GEXF' visual attributes (such as + color, size, and position), network dynamics (for both edges and nodes), and edges' + weights. Users can build/handle graphs element-by-element or massively through + data frames, visualize the graph on a web browser through 'gexf-js' (a 'javascript' + library), and interact with the 'igraph' package. + date_publication: '2024-07-01' + bug_reports: https://github.com/gvegayon/rgexf/issues + url: https://gvegayon.github.io/rgexf/ + url_cran: https://CRAN.R-project.org/package=rgexf + url_git: '' +RGF: + version: 1.1.1 + title: Regularized Greedy Forest + maintainer: Lampros Mouselimis + description: Regularized Greedy Forest wrapper of the 'Regularized Greedy Forest' + 'python' package, + which also includes a Multi-core implementation (FastRGF) . + date_publication: '2022-09-12' + bug_reports: https://github.com/RGF-team/rgf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RGF + url_git: https://github.com/RGF-team/rgf/tree/master/R-package +Rgff: + version: 0.1.6 + title: R Utilities for GFF Files + maintainer: Juan Antonio Garcia-Martin + description: R utilities for gff files, either general feature format (GFF3) or + gene transfer format (GTF) formatted files. This package includes functions for + producing summary stats, check for consistency and sorting errors, conversion + from GTF to GFF3 format, file sorting, visualization and plotting of feature hierarchy, + and exporting user defined feature subsets to SAF format. This tool was developed + by the BioinfoGP core facility at CNB-CSIC. + date_publication: '2022-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rgff + url_git: '' +rGhanaCensus: + version: 0.1.0 + title: 2021 Ghana Population and Housing Census Results as Data Frames + maintainer: Ama Owusu-Darko + description: Datasets from the 2021 Ghana Population and Housing Census Results. + Users can access results as 'tidyverse' and 'sf'-Ready Data Frames. The data + in this package is scraped from pdf reports released by the Ghana Statistical + Service website . The package currently + only contains datasets from the literacy and education reports. Namely, school + attendance data for respondents aged 3 years and above. + date_publication: '2022-01-13' + bug_reports: https://github.com/ktemadarko/rGhanaCensus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rGhanaCensus + url_git: https://github.com/ktemadarko/rGhanaCensus +rgho: + version: 3.0.2 + title: Access WHO Global Health Observatory Data from R + maintainer: Kevin Zarca + description: |- + Access WHO Global Health Observatory + () + data from R via the `OData` API + (), + an application program interface providing + a simple query interface to the World + Health Organization's data and statistics content. + date_publication: '2024-01-19' + bug_reports: https://github.com/aphp/rgho/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgho + url_git: '' +RGIFT: + version: 0.1-7 + title: Create Quizzes in GIFT Format + maintainer: Virgilio Gómez-Rubio + description: |- + Implementation of some functions to create quizzes + in the GIFT format. This format is used by several Virtual Learning + Environments such as Moodle. + date_publication: '2024-02-20' + bug_reports: '' + url: https://docs.moodle.org/21/en/GIFT_format + url_cran: https://CRAN.R-project.org/package=RGIFT + url_git: '' +rgl: + version: 1.3.17 + title: 3D Visualization Using OpenGL + maintainer: Duncan Murdoch + description: |- + Provides medium to high level functions for 3D interactive graphics, including + functions modelled on base graphics (plot3d(), etc.) as well as functions for + constructing representations of geometric objects (cube3d(), etc.). Output + may be on screen using OpenGL, or to various standard 3D file formats including + WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF. + date_publication: '2025-01-17' + bug_reports: https://github.com/dmurdoch/rgl/issues + url: https://dmurdoch.github.io/rgl/ + url_cran: https://CRAN.R-project.org/package=rgl + url_git: https://github.com/dmurdoch/rgl +rgl.cry: + version: 0.1.1 + title: '''cry'' and ''rgl'' — Applications in Crystallography' + maintainer: Toshihide Saitou + description: |- + Visualizing crystal structures and selected area electron diffraction (SAED) patterns. It provides functions cry_demo() and dp_demo() to load a file in 'CIF' (Crystallographic Information Framework) formats and display crystal structures and electron diffraction patterns. The function dp_demo() also performs simple simulation of powder X-ray diffraction (PXRD) patterns, and the results can be saved to a file in the working directory. The package has been tested on several platforms, including Linux on 'Crostini' with a Core™ m3-8100Y Chromebook, I found that even on this low-powered platform, the performance was acceptable. + T. Hanashima (2001) + Todd Helmenstine (2019) + Wikipedia contributors (2023) . + date_publication: '2024-06-13' + bug_reports: '' + url: https://saitoutoshihide.github.io/rgl.cry/ + url_cran: https://CRAN.R-project.org/package=rgl.cry + url_git: https://github.com/SaitouToshihide/rgl.cry/ +rgl2gltf: + version: 1.0.7 + title: Read and Write '.gltf' and '.glb' Files + maintainer: Duncan Murdoch + description: |- + The 'glTF' file format is used to describe 3D models. This package + provides read and write functions to work with it. + date_publication: '2024-11-21' + bug_reports: https://github.com/dmurdoch/rgl2gltf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgl2gltf + url_git: https://github.com/dmurdoch/rgl2gltf +rglobi: + version: 0.3.4 + title: Interface to Global Biotic Interactions + maintainer: Jorrit Poelen + description: |- + A programmatic interface to the web service methods + provided by Global Biotic Interactions (GloBI) + (). GloBI provides + access to spatial-temporal species interaction records from + sources all over the world. rglobi provides methods to search + species interactions by location, interaction type, and + taxonomic name. + date_publication: '2023-10-06' + bug_reports: https://github.com/ropensci/rglobi/issues + url: https://docs.ropensci.org/rglobi/ + url_cran: https://CRAN.R-project.org/package=rglobi + url_git: https://github.com/ropensci/rglobi +Rglpk: + version: 0.6-5.1 + title: R/GNU Linear Programming Kit Interface + maintainer: Stefan Theussl + description: |- + R interface to the GNU Linear Programming Kit. + 'GLPK' is open source software for solving large-scale linear programming (LP), + mixed integer linear programming ('MILP') and other related problems. + date_publication: '2024-01-13' + bug_reports: '' + url: https://www.gnu.org/software/glpk/ + url_cran: https://CRAN.R-project.org/package=Rglpk + url_git: https://R-Forge.R-project.org/projects/rglp/ +rglplus: + version: '1.3' + title: Extension of the 'rgl' 3D Visualization Package + maintainer: Danail Obreschkow + description: Provides 3D plotting routines that facilitate the use of the 'rgl' + package and extend its functionality. For example, the routines allow the user + to directly control the camera position & orientation, as well as to generate + 3D movies with a moving observer. + date_publication: '2024-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rglplus + url_git: '' +rgm: + version: 1.0.4 + title: Advanced Inference with Random Graphical Models + maintainer: Francisco Richter + description: Implements state-of-the-art Random Graphical Models (RGMs) for multivariate + data analysis across multiple environments, offering tools for exploring network + interactions and structural relationships. Capabilities include joint inference + across environments, integration of external covariates, and a Bayesian framework + for uncertainty quantification. Applicable in various fields, including microbiome + analysis. Methods based on Vinciotti, V., Wit, E., & Richter, F. (2023). "Random + Graphical Model of Microbiome Interactions in Related Environments." . + date_publication: '2024-03-21' + bug_reports: https://github.com/franciscorichter/rgm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgm + url_git: '' +RGMM: + version: 2.1.0 + title: Robust Mixture Model + maintainer: Antoine Godichon-Baggioni + description: Algorithms for estimating robustly the parameters of a Gaussian, Student, + or Laplace Mixture Model. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGMM + url_git: '' +RGN: + version: 1.0.0 + title: |- + Robust-Gauss Newton (RGN) Optimization of Sum-of-Squares + Objective Function + maintainer: David McInerney + description: |- + Implementation of the Robust Gauss-Newton (RGN) algorithm, + designed for solving optimization problems with a sum of least squares + objective function. For algorithm details please refer to Qin et. al. (2018) + . + date_publication: '2023-09-25' + bug_reports: https://github.com/ClimateAnalytics/RGN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RGN + url_git: https://github.com/ClimateAnalytics/RGN/ +rgnoisefilt: + version: 1.1.2 + title: |- + Elimination of Noisy Samples in Regression Datasets using Noise + Filters + maintainer: Juan Martin + description: Traditional noise filtering methods aim at removing noisy samples from + a classification dataset. This package adapts classic and recent filtering techniques + for use in regression problems, and it also incorporates methods specifically + designed for regression data. In order to do this, it uses approaches proposed + in the specialized literature, such as Martin et al. (2021) [] + and Arnaiz-Gonzalez et al. (2016) []. Thus, the + goal of the implemented noise filters is to eliminate samples with noise in regression + datasets. + date_publication: '2023-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rgnoisefilt + url_git: https://github.com/juanmartinsantos/rgnoisefilt +rgnparser: + version: 0.3.0 + title: Parse Scientific Names + maintainer: Joel H. Nitta + description: |- + Parse scientific names using 'gnparser' + (), written in Go. 'gnparser' + parses scientific names into their component parts; it utilizes + a Parsing Expression Grammar specifically for scientific names. + date_publication: '2023-12-12' + bug_reports: https://github.com/ropensci/rgnparser/issues + url: https://docs.ropensci.org/rgnparser/ + url_cran: https://CRAN.R-project.org/package=rgnparser + url_git: https://github.com/ropensci/rgnparser +Rgof: + version: 3.0.0 + title: 1d Goodness of Fit Tests + maintainer: Wolfgang Rolke + description: |- + Routines that allow the user to run a large number of goodness-of-fit tests. + It allows for data to be continuous or discrete. It includes routines to estimate + the power of the tests and display them as a power graph. + The routine run.studies allows a user to quickly study the power of a new method and + how it compares to some of the standard ones. + date_publication: '2025-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rgof + url_git: '' +rgoogleads: + version: 0.12.0 + title: Loading Data from 'Google Ads API' + maintainer: Alexey Seleznev + description: |- + Interface for loading data from 'Google Ads API', + see . + Package provide function for authorization and loading reports. + date_publication: '2025-01-10' + bug_reports: https://github.com/selesnow/rgoogleads/issues + url: https://selesnow.github.io/rgoogleads/ + url_cran: https://CRAN.R-project.org/package=rgoogleads + url_git: https://github.com/selesnow/rgoogleads +RGoogleAnalyticsPremium: + version: 0.1.1 + title: Unsampled Data in R for Google Analytics Premium Accounts + maintainer: Jalpa Joshi Dave + description: It fires a query to the API to get the unsampled data in R for Google + Analytics Premium Accounts. It retrieves data from the Google drive document and + stores it into the local drive. The path to the excel file is returned by this + package. The user can read data from the excel file into R using read.csv() function. + date_publication: '2015-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGoogleAnalyticsPremium + url_git: '' +rgoogleclassroom: + version: 0.9.1 + title: API Wrapper for Google Classroom and Google Forms + maintainer: Candace Savonen + description: This is a Google Forms and Google Classroom API Wrapper for R for managing + Google Classrooms from R. The documentation for these APIs is here + . + date_publication: '2023-08-09' + bug_reports: https://github.com/datatrail-jhu/rgoogleclassroom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgoogleclassroom + url_git: https://github.com/datatrail-jhu/rgoogleclassroom +RGoogleFit: + version: 0.4.0 + title: R Interface to Google Fit API + maintainer: Marcin Szymanski + description: Provides interface to Google Fit REST API v1 (see ). + date_publication: '2020-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGoogleFit + url_git: '' +RgoogleMaps: + version: 1.5.1 + title: Overlays on Static Maps + maintainer: Markus Loecher + description: |- + Serves two purposes: (i) Provide a + comfortable R interface to query the Google server for static + maps, and (ii) Use the map as a background image to overlay + plots within R. This requires proper coordinate scaling. + date_publication: '2023-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RgoogleMaps + url_git: https://github.com/markusloecher/rgooglemaps/blob/master/rgooglemaps/www/QuickTutorial.html +rgoogleslides: + version: 0.3.2 + title: R Interface to Google Slides + maintainer: Hairizuan Noorazman + description: Previously, when one is working with in the Google Ecosystem (Using + Google Drive etc), there is hardly any good workflow of getting the values calculated + from R and getting that into Google Slides. The normal and easy way out would + be to just copy your work over but when you have a number of analysis to present + with a lot of changes between each environment, it just becomes quite cumbersome. + date_publication: '2020-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rgoogleslides + url_git: '' +rgplates: + version: 0.5.0 + title: R Interface for the GPlates Web Service and Desktop Application + maintainer: Adam T. Kocsis + description: Query functions to the GPlates Desktop Application + and the GPlates Web Service allow users to reconstruct + past positions of geographic entities based on user-selected rotation models without + leaving the R running environment. The online method (GPlates Web Service) makes + the rotation of static plates, coastlines, and a low number of geographic coordinates + available using nothing but an internet connection. The offline method requires + an external installation of the GPlates Desktop Application, but allows the efficient + batch rotation of thousands of coordinates, Simple Features (sf) and Spatial (sp) + objects with custom reconstruction trees and partitioning polygons. Examples of + such plate tectonic models are accessible via the chronosphere . + This R extension is developed under the umbrella of the DFG (Deutsche Forschungsgemeinschaft) + Research Unit TERSANE2 (For 2332, TEmperature Related Stressors in ANcient Extinctions). + date_publication: '2024-09-06' + bug_reports: https://github.com/gplates/rgplates/issues + url: https://gplates.github.io/rgplates/ + url_cran: https://CRAN.R-project.org/package=rgplates + url_git: '' +rgraph6: + version: 2.0-4 + title: Representing Graphs as 'graph6', 'digraph6' or 'sparse6' Strings + maintainer: Michal Bojanowski + description: |- + Encode network data as strings of printable ASCII characters. Implemented + functions include encoding and decoding adjacency matrices, edgelists, igraph, and + network objects to/from formats 'graph6', 'sparse6', and 'digraph6'. The formats and + methods are described in McKay, B.D. and Piperno, A (2014) + . + date_publication: '2024-02-01' + bug_reports: https://github.com/mbojan/rgraph6/issues + url: https://mbojan.github.io/rgraph6/ + url_cran: https://CRAN.R-project.org/package=rgraph6 + url_git: '' +RGraphics: + version: 3.0-2 + title: Data and Functions from the Book R Graphics, Third Edition + maintainer: Paul Murrell + description: Data and Functions from the book R Graphics, Third Edition. There is + a function to produce each figure in the book, plus several functions, classes, + and methods defined in Chapter 8. + date_publication: '2020-06-30' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~paul/RG3e/index.html + url_cran: https://CRAN.R-project.org/package=RGraphics + url_git: '' +RGraphSpace: + version: 1.0.7 + title: A Lightweight Interface Between 'ggplot2' and 'igraph' Objects + maintainer: Mauro Castro + description: Interface to integrate 'igraph' and 'ggplot2' graphics within spatial + maps. 'RGraphSpace' implements new geometric objects using 'ggplot2' prototypes, + customized for representing large 'igraph' objects in a normalized coordinate + system. By scaling shapes and graph elements, 'RGraphSpace' can provide a framework + for layered visualizations. + date_publication: '2024-11-12' + bug_reports: https://github.com/sysbiolab/RGraphSpace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RGraphSpace + url_git: https://github.com/sysbiolab/RGraphSpace +rgrass: + version: 0.5-2 + title: |- + Interface Between 'GRASS' Geographical Information System and + 'R' + maintainer: Steven Pawley + description: An interface between the 'GRASS' geographical information system ('GIS') + and 'R', based on starting 'R' from within the 'GRASS' 'GIS' environment, or running + a free-standing 'R' session in a temporary 'GRASS' location; the package provides + facilities for using all 'GRASS' commands from the 'R' command line. The original + interface package for 'GRASS 5' (2000-2010) is described in Bivand (2000) + and Bivand (2001) . + This was succeeded by 'spgrass6' for 'GRASS 6' (2006-2016) and 'rgrass7' for 'GRASS + 7' (2015-present). The 'rgrass' package modernizes the interface for 'GRASS 8' + while still permitting the use of 'GRASS 7'. + date_publication: '2025-02-14' + bug_reports: https://github.com/osgeo/rgrass/issues/ + url: https://osgeo.github.io/rgrass/ + url_cran: https://CRAN.R-project.org/package=rgrass + url_git: https://github.com/osgeo/rgrass +RGreenplum: + version: 0.1.2 + title: Interface to 'Greenplum' Database + maintainer: Michael Williams + description: |2- + + Fully 'DBI'-compliant interface to 'Greenplum' , + an open-source parallel database. This is an extension of the 'RPostgres' + package . + date_publication: '2018-06-24' + bug_reports: https://github.com/mwillumz/RGreenplum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RGreenplum + url_git: https://github.com/mwillumz/RGreenplum +RGremlinsConjoint: + version: 0.9.1 + title: Estimate the "Gremlins in the Data" Model for Conjoint Studies + maintainer: John Howell + description: |- + The tools and utilities to estimate the model described in "Gremlin's in the + Data: Identifying the Information Content of Research Subjects" (Howell et al. + (2021) ) using conjoint analysis data such as + that collected in Sawtooth Software's 'Lighthouse' or 'Discover' products. + Additional utilities are included for formatting the input data. + date_publication: '2023-09-08' + bug_reports: https://github.com/statuser/RGremlinsConjoint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RGremlinsConjoint + url_git: https://github.com/statuser/RGremlinsConjoint +rGroovy: + version: '1.3' + title: Groovy Language Integration + maintainer: Thomas P. Fuller + description: Integrates the Groovy scripting language with the R Project for Statistical + Computing. + date_publication: '2018-04-01' + bug_reports: '' + url: http://groovy-lang.org/ + url_cran: https://CRAN.R-project.org/package=rGroovy + url_git: '' +RGS: + version: '1.0' + title: Recursive Gradient Scanning Algorithm + maintainer: Shuo Yang + description: |- + Provides a recursive gradient scanning algorithm for + discretizing continuous variables in Logistic and Cox regression + models. This algorithm is especially effective in identifying + optimal cut-points for variables with U-shaped relationships to + 'lnOR' (the natural logarithm of the odds ratio) or 'lnHR' (the + natural logarithm of the hazard ratio), thereby enhancing model + fit, interpretability, and predictive power. By iteratively + scanning and calculating gradient changes, the method accurately + pinpoints critical cut-points within nonlinear relationships, + transforming continuous variables into categorical ones. This + approach improves risk classification and regression analysis + performance, increasing interpretability and practical relevance + in clinical and risk management settings. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RGS + url_git: '' +rgsp: + version: 0.2.0 + title: Repetitive Group Sampling Plan Based on Cpk + maintainer: Muhammad Yaseen + description: Functions to calculate Sample Number and Average Sample Number for + Repetitive Group Sampling Plan Based on Cpk as given in Aslam et al. (2013) (). + date_publication: '2018-10-26' + bug_reports: '' + url: https://myaseen208.github.io/rgsp/ + url_cran: https://CRAN.R-project.org/package=rgsp + url_git: https://github.com/myaseen208/rgsp +rgTest: + version: '0.1' + title: Robust Graph-Based Two-Sample Test + maintainer: Yichuan Bai + description: Useful tools for determining whether two samples are from the same + distribution. Utilizes a robust method to address the problematic structure of + the similarity graph constructed from high-dimensional data. The method is provided + in Yichuan Bai and Lynna Chu (2023) . + date_publication: '2023-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rgTest + url_git: '' +rgtmx: + version: 0.1.4 + title: Manage GTmetrix Tests in R + maintainer: Roman A. Abashin + description: |- + This is a library to access the current API of the web speed test service 'GTmetrix'. + It provides a convenient wrapper to start tests, get reports, and access all kinds of meta data. + For more information about using the API please visit . + date_publication: '2021-11-11' + bug_reports: https://github.com/RomanAbashin/rgtmx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rgtmx + url_git: https://github.com/RomanAbashin/rgtmx +rgugik: + version: 0.4.1 + title: Search and Retrieve Spatial Data from 'GUGiK' + maintainer: Krzysztof Dyba + description: |- + Automatic open data acquisition from resources of Polish Head Office + of Geodesy and Cartography ('Główny Urząd Geodezji i Kartografii') + (). + Available datasets include various types of numeric, raster and vector data, + such as orthophotomaps, digital elevation models (digital terrain models, + digital surface model, point clouds), state register of borders, spatial + databases, geometries of cadastral parcels, 3D models of buildings, and more. + It is also possible to geocode addresses or objects using the geocodePL_get() + function. + date_publication: '2024-05-11' + bug_reports: https://github.com/kadyb/rgugik/issues + url: https://kadyb.github.io/rgugik/ + url_cran: https://CRAN.R-project.org/package=rgugik + url_git: https://github.com/kadyb/rgugik +rGV: + version: 0.0.5 + title: Analysis of Continuous Glucose Monitor Data + maintainer: Evan Olawsky + description: Reads in continuous glucose monitor data of many different formats, + calculates a host of glycemic variability metrics, and plots glucose over time. + date_publication: '2024-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rGV + url_git: '' +rgw: + version: 0.3.0 + title: Goodman-Weare Affine-Invariant Sampling + maintainer: Adam Mantz + description: Implementation of the affine-invariant method of Goodman & Weare (2010) + , a method of producing Monte-Carlo samples from + a target distribution. + date_publication: '2020-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rgw + url_git: https://github.com/abmantz/rgw +RH2: + version: 0.2.4 + title: DBI/RJDBC Interface to H2 Database + maintainer: '"David M. Kaplan"' + description: DBI/RJDBC interface to h2 database. h2 version 1.3.175 is included. + date_publication: '2018-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RH2 + url_git: https://github.com/dmkaplan2000/RH2.git +rhandsontable: + version: 0.3.8 + title: Interface to the 'Handsontable.js' Library + maintainer: Jonathan Owen + description: |- + An R interface to the 'Handsontable' JavaScript library, which is a + minimalist Excel-like data grid editor. See for details. + date_publication: '2021-05-27' + bug_reports: https://github.com/jrowen/rhandsontable/issues + url: http://jrowen.github.io/rhandsontable/ + url_cran: https://CRAN.R-project.org/package=rhandsontable + url_git: '' +RHawkes: + version: '1.0' + title: Renewal Hawkes Process + maintainer: Feng Chen + description: |- + The renewal Hawkes (RHawkes) process (Wheatley, + Filimonov, and Sornette, 2016 ) is + an extension to the classical Hawkes self-exciting point process + widely used in the modelling of clustered event sequence data. + This package provides functions to simulate the RHawkes process + with a given immigrant hazard rate function and offspring birth + time density function, to compute the exact likelihood of a + RHawkes process using the recursive algorithm proposed by Chen and + Stindl (2018) , to compute the + Rosenblatt residuals for goodness-of-fit assessment, and to + predict future event times based on observed event times up to a + given time. A function implementing the linear time RHawkes + process likelihood approximation algorithm proposed in Stindl and + Chen (2021) is also included. + date_publication: '2022-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHawkes + url_git: '' +RHclust: + version: 2.0.0 + title: Vector in Partition + maintainer: Joseph Handwerker + description: Non-parametric clustering of joint pattern multi-genetic/epigenetic + factors. This package contains functions designed to cluster subjects based on + gene features including single nucleotide polymorphisms (SNPs), DNA methylation + (CPG), gene expression (GE), and covariate data. The novel concept follows the + general K-means (Hartigan and Wong (1979) framework but + uses weighted Euclidean distances across the gene features to cluster subjects. + This approach is unique in that it attempts to capture all pairwise interactions + in an effort to cluster based on their complex biological interactions. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHclust + url_git: '' +rhcoclust: + version: 2.0.0 + title: |- + Robust Hierarchical Co-Clustering to Identify Significant + Co-Cluster + maintainer: Md. Bahadur Badsha + description: |- + Here we performs robust hierarchical co-clustering between row and column entities of a data matrix in + absence and presence of outlying observations. It can be used to explore important co-clusters consisting of + important samples and their regulatory significant features. Please see Hasan, Badsha and Mollah (2020) + . + date_publication: '2023-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rhcoclust + url_git: '' +rheroicons: + version: 1.0.0 + title: A Zero Dependency 'SVG' Icon Library for 'Shiny' + maintainer: David Ruvolo + description: |- + An implementation of the 'Heroicons' icon library for 'shiny' + applications and other 'R' web-based projects. You can search, render, + and customize icons without 'CSS' or 'JavaScript' dependencies. + date_publication: '2022-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rheroicons + url_git: '' +rhierbaps: + version: 1.1.4 + title: Clustering Genetic Sequence Data Using the HierBAPS Algorithm + maintainer: Gerry Tonkin-Hill + description: |- + Implements the hierarchical Bayesian analysis of populations structure (hierBAPS) + algorithm of Cheng et al. (2013) for clustering DNA sequences + from multiple sequence alignments in FASTA format. + The implementation includes improved defaults and plotting capabilities + and unlike the original 'MATLAB' version removes singleton SNPs by default. + date_publication: '2022-11-18' + bug_reports: https://github.com/gtonkinhill/rhierbaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rhierbaps + url_git: https://github.com/gtonkinhill/rhierbaps +rhino: + version: 1.10.1 + title: A Framework for Enterprise Shiny Applications + maintainer: Kamil Żyła + description: A framework that supports creating and extending enterprise Shiny applications + using best practices. + date_publication: '2024-09-20' + bug_reports: https://github.com/Appsilon/rhino/issues + url: https://appsilon.github.io/rhino/ + url_cran: https://CRAN.R-project.org/package=rhino + url_git: https://github.com/Appsilon/rhino +rhmc: + version: 1.0.0 + title: Hamiltonian Monte Carlo + maintainer: Victhor Sartório + description: |- + Implements simple Hamiltonian Monte Carlo routines in R for + sampling from any desired target distribution which is continuous + and smooth. See Neal (2017) for further details + on Hamiltonian Monte Carlo. Automatic parameter selection is not + supported. + date_publication: '2018-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rhmc + url_git: '' +RHMS: + version: '1.7' + title: Hydrologic Modelling System for R Users + maintainer: Rezgar Arabzadeh + description: Hydrologic modelling system is an object oriented tool for simulation + and analysis of hydrologic events. The package proposes functions and methods + for construction, simulation, visualization, and calibration of a hydrologic model. + date_publication: '2021-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHMS + url_git: '' +rhnerm: + version: '1.1' + title: Random Heteroscedastic Nested Error Regression + maintainer: Shonosuke Sugasawa + description: Performs the random heteroscedastic nested error regression model described + in Kubokawa, Sugasawa, Ghosh and Chaudhuri (2016) . + date_publication: '2016-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rhnerm + url_git: '' +rhoneycomb: + version: 2.3.4 + title: Analysis of Honeycomb Selection Designs + maintainer: Nikos Antonetsis + description: 'A useful statistical tool for the construction and analysis of Honeycomb + Selection Designs. More information about this type of designs: Fasoula V. (2013) + Fasoula V.A., and Tokatlidis I.S. (2012) + Fasoulas A.C., and Fasoula V.A. (1995) Tokatlidis + I. (2016) Tokatlidis I., and Vlachostergios D. + (2016) .' + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rhoneycomb + url_git: '' +rhoR: + version: 1.3.0.3 + title: Rho for Inter Rater Reliability + maintainer: Cody L Marquart + description: |- + Rho is used to test the generalization of inter rater reliability + (IRR) statistics. Calculating rho starts by generating a large number of + simulated, fully-coded data sets: a sizable collection of hypothetical + populations, all of which have a kappa value below a given threshold -- which + indicates unacceptable agreement. Then kappa is calculated on a sample from + each of those sets in the collection to see if it is equal to or higher than + the kappa in then real sample. If less than five percent of the distribution + of samples from the simulated data sets is greater than actual observed kappa, + the null hypothesis is rejected and one can conclude that if the two raters had + coded the rest of the data, we would have acceptable agreement (kappa above the + threshold). + date_publication: '2020-09-13' + bug_reports: https://gitlab.com/epistemic-analytics/qe-packages/rhoR/-/issues + url: https://rhor.qe-libs.org + url_cran: https://CRAN.R-project.org/package=rhoR + url_git: '' +rhosa: + version: 0.3.0 + title: Higher-Order Spectral Analysis + maintainer: Takeshi Abe + description: Higher-order spectra or polyspectra of time series, such as bispectrum + and bicoherence, have been investigated in abundant literature and applied to + problems of signal detection in a wide range of fields. This package aims to provide + a simple API to estimate and analyze them. The current implementation is based + on Brillinger and Irizarry (1998) for estimating + bispectrum or bicoherence, Lii and Helland (1981) + for cross-bispectrum, and Kim and Powers (1979) + for cross-bicoherence. + date_publication: '2024-05-17' + bug_reports: https://github.com/tabe/rhosa/issues + url: https://tabe.github.io/rhosa/ + url_cran: https://CRAN.R-project.org/package=rhosa + url_git: '' +rhosp: + version: '1.10' + title: 'Side Effect Risks in Hospital : Simulation and Estimation' + maintainer: Christophe Dutang + description: Evaluating risk (that a patient arises a side effect) during hospitalization + is the main purpose of this package. Several methods (Parametric, non parametric + and De Vielder estimation) to estimate the risk constant (R) are implemented in + this package. There are also functions to simulate the different models of this + issue in order to quantify the previous estimators. It is necessary to read at + least the first six pages of the report to understand the topic. + date_publication: '2018-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rhosp + url_git: '' +RHPCBenchmark: + version: 0.1.0 + title: Benchmarks for High-Performance Computing Environments + maintainer: James McCombs + description: |- + Microbenchmarks for determining the run time + performance of aspects of the R programming environment and packages + relevant to high-performance computation. The benchmarks are divided into + three categories: dense matrix linear algebra kernels, sparse matrix linear + algebra kernels, and machine learning functionality. + date_publication: '2017-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHPCBenchmark + url_git: '' +RhpcBLASctl: + version: 0.23-42 + title: Control the Number of Threads on 'BLAS' + maintainer: Ei-ji Nakama + description: |- + Control the number of threads on 'BLAS' (Aka 'GotoBLAS', 'OpenBLAS', 'ACML', 'BLIS' and 'MKL'). + And possible to control the number of threads in 'OpenMP'. + Get a number of logical cores and physical cores if feasible. + date_publication: '2023-02-11' + bug_reports: '' + url: https://prs.ism.ac.jp/~nakama/Rhpc/ + url_cran: https://CRAN.R-project.org/package=RhpcBLASctl + url_git: '' +RHRT: + version: 1.0.1 + title: Heart Rate Turbulence Analysis + maintainer: Valeria Blesius + description: Methods to scan RR interval data for Premature Ventricular Complexes + (PVCs) and parameterise and plot the resulting Heart Rate Turbulence (HRT). The + methodology of HRT analysis is based on the original publication by Schmidt et + al. and extended with suggestions from . + date_publication: '2021-06-29' + bug_reports: https://github.com/VBlesius/RHRT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RHRT + url_git: '' +RHRV: + version: 5.0.0 + title: Heart Rate Variability Analysis of ECG Data + maintainer: Leandro Rodriguez-Linares + description: "Allows users to import data files containing heartbeat\tpositions + in the most broadly used formats, to remove outliers or points with unacceptable + physiological values present in the time series, to plot HRV data, and to perform + time domain, frequency domain and nonlinear HRV analysis. See Garcia et al. (2017) + ." + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHRV + url_git: http://rhrv.r-forge.r-project.org/ +RHSDB: + version: 0.2.0 + title: Ryan-Holm Step-Down Bonferroni or Sidak Procedure + maintainer: Zhicheng Du Developer + description: |- + The Ryan-Holm step-down Bonferroni or Sidak procedure is to control the family-wise (experiment-wise) type I error rate in the multiple comparisons. + This procedure provides the adjusting p-values and adjusting CIs. The methods used in this package are referenced from John Ludbrook (2000) . + date_publication: '2022-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHSDB + url_git: '' +rhub: + version: 2.0.0 + title: Tools for R Package Developers + maintainer: Gábor Csárdi + description: |- + R-hub v2 uses GitHub Actions to run 'R CMD check' and + similar package checks. The 'rhub' package helps you set up + R-hub v2 for your R package, and start running checks. + date_publication: '2024-04-11' + bug_reports: https://github.com/r-hub/rhub/issues + url: https://r-hub.github.io/rhub/ + url_cran: https://CRAN.R-project.org/package=rhub + url_git: https://github.com/r-hub/rhub +RHybridFinder: + version: 0.2.0 + title: Identification of Hybrid Peptides in Immunopeptidomic Analyses + maintainer: Frederic Saab + description: |- + Tool for the analysis Mass Spectrometry (MS) data in the context of + immunopeptidomic analysis for the identification of hybrid + peptides and the predictions of binding affinity of all peptides + using 'netMHCpan' while providing a summary + of the netMHCpan output. 'RHybridFinder' (RHF) is destined for + researchers who are looking to analyze their MS data for the purpose + of identification of potential spliced peptides. This package, + developed mainly in base R, is based on the workflow published by + Faridi et al. in 2018 . + date_publication: '2021-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RHybridFinder + url_git: '' +rhymer: + version: 1.2.0 + title: |- + Wrapper for the 'Datamuse' API to Find Rhyming and Associated + Words + maintainer: Noah Landesberg + description: |- + Wrapper for 'Datamuse' API to find rhyming and other associated words. + This includes words of similar meaning, spelling, or other related words. Learn + more about the 'Datamuse' API here . + date_publication: '2023-01-05' + bug_reports: https://github.com/landesbergn/rhymer/issues + url: https://landesbergn.github.io/rhymer/index.html + url_cran: https://CRAN.R-project.org/package=rhymer + url_git: https://github.com/landesbergn/rhymer +rhype: + version: 0.3.0 + title: Work with Hypergraphs in R + maintainer: Hugh Warden + description: |- + Create and manipulate hypergraph objects. This early version of + rhype allows for the output of matrices associated with the hypergraphs + themselves. It also uses these matrices to calculate hypergraph spectra and + perform spectral comparison. Functionality coming soon includes calculation + of hyperpaths and hypergraph centrality measures. + date_publication: '2022-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rhype + url_git: '' +ri2: + version: 0.4.0 + title: Randomization Inference for Randomized Experiments + maintainer: Alexander Coppock + description: 'Randomization inference procedures for simple and complex randomized + designs, including multi-armed trials, as described in Gerber and Green (2012, + ISBN: 978-0393979954). Users formally describe their randomization procedure and + test statistic. The randomization distribution of the test statistic under some + null hypothesis is efficiently simulated.' + date_publication: '2022-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ri2 + url_git: '' +RI2by2: + version: '1.4' + title: |- + Randomization Inference for Treatment Effects on a Binary + Outcome + maintainer: Joseph Rigdon + description: Computes attributable effects based confidence interval, permutation + test confidence interval, or asymptotic confidence interval for the average treatment + effect on a binary outcome. Methods outlined in further detail in Rigdon and Hudgens + (2015) . + date_publication: '2023-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RI2by2 + url_git: '' +RIA: + version: 1.7.2 + title: Radiomics Image Analysis Toolbox for Medial Images + maintainer: Marton Kolossvary + description: |- + Radiomics image analysis toolbox for 2D and 3D radiological images. RIA supports DICOM, NIfTI, + nrrd and npy (numpy array) file formats. + RIA calculates first-order, gray level co-occurrence matrix, gray level run length matrix and + geometry-based statistics. Almost all calculations are done using vectorized formulas to + optimize run speeds. Calculation of several thousands of parameters only takes minutes + on a single core of a conventional PC. Detailed methodology has been published: Kolossvary + et al. Circ: Cardiovascular Imaging. 2017;10(12):e006843 . + date_publication: '2024-01-08' + bug_reports: '' + url: https://pubmed.ncbi.nlm.nih.gov/29233836/ + url_cran: https://CRAN.R-project.org/package=RIA + url_git: '' +riAFTBART: + version: 0.3.3 + title: |- + A Flexible Approach for Causal Inference with Multiple + Treatments and Clustered Survival Outcomes + maintainer: Fengrui Zhang + description: Random-intercept accelerated failure time (AFT) model utilizing Bayesian + additive regression trees (BART) for drawing causal inferences about multiple + treatments while accounting for the multilevel survival data structure. It also + includes an interpretable sensitivity analysis approach to evaluate how the drawn + causal conclusions might be altered in response to the potential magnitude of + departure from the no unmeasured confounding assumption.This package implements + the methods described by Hu et al. (2022) . + date_publication: '2024-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riAFTBART + url_git: '' +rib: + version: 0.25.3 + title: An Implementation of 'Interactive Brokers' API + maintainer: Luca Billi + description: |- + Allows interaction with 'Interactive Brokers' 'Trader Workstation' + . + Handles the connection over the network and the exchange of messages. + Data is encoded and decoded between user and wire formats. + Data structures and functionality closely mirror the official implementations. + date_publication: '2025-02-10' + bug_reports: https://github.com/lbilli/rib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rib + url_git: https://github.com/lbilli/rib +ribd: + version: 1.7.1 + title: Pedigree-based Relatedness Coefficients + maintainer: Magnus Dehli Vigeland + description: |- + Recursive algorithms for computing various relatedness + coefficients, including pairwise kinship, kappa and identity + coefficients. Both autosomal and X-linked coefficients are computed. + Founders are allowed to be inbred, which enables construction of any + given kappa coefficients, as described in Vigeland (2020) + . In addition to the standard + coefficients, 'ribd' also computes a range of lesser-known + coefficients, including generalised kinship coefficients, multi-person + coefficients and two-locus coefficients (Vigeland, 2023, + ). Many features of 'ribd' are + available through the online app 'QuickPed' at + ; see Vigeland (2022) + . + date_publication: '2025-02-08' + bug_reports: '' + url: https://magnusdv.github.io/pedsuite/ + url_cran: https://CRAN.R-project.org/package=ribd + url_git: https://github.com/magnusdv/ribd +RIbench: + version: 1.0.2 + title: Benchmark Suite for Indirect Methods for RI Estimation + maintainer: Tatjana Ammer + description: |- + The provided benchmark suite enables the automated evaluation and comparison of any existing and novel indirect method for reference interval ('RI') estimation in a systematic way. + Indirect methods take routine measurements of diagnostic tests, containing pathological and non-pathological samples as input and use sophisticated + statistical methods to derive a model describing the distribution of the non-pathological samples, which can then be + used to derive reference intervals. The benchmark suite contains 5,760 simulated test sets with varying difficulty. + To include any indirect method, a custom wrapper function needs to be provided. + The package offers functions for generating the test sets, executing the indirect method and evaluating the results. + See ?RIbench or vignette("RIbench_package") for a more comprehensive description of the features. + A detailed description and application is described in Ammer T., Schuetzenmeister A., Prokosch H.-U., Zierk J., Rank C.M., Rauh M. "RIbench: A Proposed Benchmark for the Standardized Evaluation of Indirect Methods for Reference Interval Estimation". Clinical Chemistry (2022) . + date_publication: '2022-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RIbench + url_git: '' +rice: + version: 1.0.0 + title: Radiocarbon Equations + maintainer: Maarten Blaauw + description: Provides functions for the calibration of radiocarbon dates, as well + as options to calculate different radiocarbon realms (C14 age, F14C, pMC, D14C) + and estimating the effects of contamination or local reservoir offsets (Reimer + and Reimer 2001 ). The methods follow long-established + recommendations such as Stuiver and Polach (1977) + and Reimer et al. (2004) . This package complements + the data package 'rintcal'. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rice + url_git: '' +ricegeneann: + version: 1.0.2 + title: Gene Annotation of Rice (Oryza Sativa L.spp.japonica) + maintainer: Xiang LI + description: |- + Gene annotation of rice (Oryza Sativa L.spp.japonica). + The package is based on the annotation file from the website . + Input gene's name then return some information, including the from position, the end position, + the position type and the chromosome number. + date_publication: '2020-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ricegeneann + url_git: '' +riceidconverter: + version: 1.1.1 + title: Convert Biological ID from RAP or MSU to SYMBOL for Oryza Sativa + maintainer: Xiang LI + description: |- + Convert one biological ID to another of rice (Oryza sativa). + Rice(Oryza sativa) has more than one form gene ID for the genome. + The two main gene ID for rice genome are the RAP (The Rice Annotation Project, , + and the MSU(The Rice Genome Annotation Project, . + All RAP rice gene IDs are of the form Os##g####### as explained on the website . + All MSU rice gene IDs are of the form LOC_Os##g##### as explained on the website . + All SYMBOL rice gene IDs are the unique name on the NCBI(National Center for Biotechnology Information, . + The TRANSCRIPTID, is the transcript id of rice, are of the form Os##t#######. + The researchers usually need to converter between various IDs. Such as converter RAP to SYMBOLS for function searching on NCBI. + There are a lot of websites with the function for converting RAP to MSU or MSU to RA, such as 'ID Converter' . + But it is difficult to convert super multiple IDs on these websites. + The package can convert all IDs between the three IDs (RAP, MSU and SYMBOL) regardless of the number. + date_publication: '2020-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riceidconverter + url_git: '' +riceware: + version: '0.4' + title: A Diceware Passphrase Implementation + maintainer: Francois Michonneau + description: |- + The Diceware method can be used to generate strong passphrases. + In short, you roll a 6-faced dice 5 times in a row, the number obtained is + matched against a dictionary of easily remembered words. By combining together 7 + words thus generated, you obtain a password that is relatively easy to remember, + but would take several millions years (on average) for a powerful computer to guess. + date_publication: '2015-05-21' + bug_reports: https://github.com/fmichonneau/riceware/issues + url: '' + url_cran: https://CRAN.R-project.org/package=riceware + url_git: https://github.com/fmichonneau/riceware +Ricrt: + version: 0.1.0 + title: Randomization Inference of Clustered Randomized Trials + maintainer: Yang Dong + description: |- + Methods for randomization inference in group-randomized trials. Specifically, it can be used to analyze the treatment effect of stratified data with multiple clusters in each stratum with treatment given on cluster level. + User may also input as many covariates as they want to fit the data. Methods are described by Dylan S Small et al., (2012) . + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ricrt + url_git: '' +ricu: + version: 0.5.6 + title: Intensive Care Unit Data with R + maintainer: Nicolas Bennett + description: |- + Focused on (but not exclusive to) data sets hosted on PhysioNet + (), 'ricu' provides utilities for download, setup + and access of intensive care unit (ICU) data sets. In addition to + functions for running arbitrary queries against available data sets, a + system for defining clinical concepts and encoding their representations + in tabular ICU data is presented. + date_publication: '2023-09-04' + bug_reports: https://github.com/eth-mds/ricu/issues + url: https://physionet.org + url_cran: https://CRAN.R-project.org/package=ricu + url_git: https://github.com/eth-mds/ricu +rid: + version: 0.0.1 + title: Multiple Change-Point Detection in Multivariate Time Series + maintainer: Xinyuan Fan + description: "Provides efficient functions for detecting multiple change points + in multidimensional time series. The models can be piecewise constant or polynomial. + Adaptive threshold selection methods are available, see Fan and Wu (2024)\t." + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rid + url_git: '' +RIdeogram: + version: 0.2.2 + title: |- + Drawing SVG Graphics to Visualize and Map Genome-Wide Data on + Idiograms + maintainer: Zhaodong Hao + description: For whole-genome analysis, idiograms are virtually the most intuitive + and effective way to map and visualize the genome-wide information. RIdeogram + was developed to visualize and map whole-genome data on idiograms with no restriction + of species. + date_publication: '2020-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RIdeogram + url_git: '' +ridge: + version: '3.3' + title: |- + Ridge Regression with Automatic Selection of the Penalty + Parameter + maintainer: Steffen Moritz + description: |- + Linear and logistic ridge regression functions. Additionally includes special functions for + genome-wide single-nucleotide polymorphism (SNP) data. More details can be found in + and . + date_publication: '2022-04-11' + bug_reports: https://github.com/SteffenMoritz/ridge/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ridge + url_git: https://github.com/SteffenMoritz/ridge +ridgetorus: + version: 1.0.2 + title: PCA on the Torus via Density Ridges + maintainer: Eduardo García-Portugués + description: |- + Implementation of a Principal Component Analysis (PCA) in the + torus via density ridge estimation. The main function, ridge_pca(), obtains + the relevant density ridge for bivariate sine von Mises and bivariate + wrapped Cauchy distribution models and provides the associated scores and + variance decomposition. Auxiliary functions for evaluating, fitting, and + sampling these models are also provided. The package provides replicability + to García-Portugués and Prieto-Tirado (2023) + . + date_publication: '2023-08-27' + bug_reports: https://github.com/egarpor/ridgetorus + url: '' + url_cran: https://CRAN.R-project.org/package=ridgetorus + url_git: https://github.com/egarpor/ridgetorus +ridgregextra: + version: 0.1.1 + title: Ridge Regression Parameter Estimation + maintainer: Olgun Aydin + description: It is a package that provides alternative approach for finding optimum + parameters of ridge regression. This package focuses on finding the ridge parameter + value k which makes the variance inflation factors closest to 1, while keeping + them above 1 as addressed by Michael Kutner, Christopher Nachtsheim, John Neter, + William Li (2004, ISBN:978-0073108742). Moreover, the package offers end-to-end + functionality to find optimum k value and presents the detailed ridge regression + results. Finally it shows three sets of graphs consisting k versus variance inflation + factors, regression coefficients and standard errors of them. + date_publication: '2023-11-25' + bug_reports: https://github.com/filizkrdg/ridgregextra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ridgregextra + url_git: https://github.com/filizkrdg/ridgregextra +ridigbio: + version: 0.4.1 + title: Interface to the iDigBio Data API + maintainer: Jesse Bennett + description: |- + An interface to iDigBio's search API that allows downloading + specimen records. Searches are returned as a data.frame. Other functions + such as the metadata end points return lists of information. iDigBio is a US + project focused on digitizing and serving museum specimen collections on the + web. See for information on iDigBio. + date_publication: '2024-10-01' + bug_reports: https://github.com/iDigBio/ridigbio/issues + url: https://idigbio.github.io/ridigbio/ + url_cran: https://CRAN.R-project.org/package=ridigbio + url_git: https://github.com/iDigBio/ridigbio +riem: + version: 1.0.0 + title: Accesses Weather Data from the Iowa Environment Mesonet + maintainer: Maëlle Salmon + description: |- + Allows to get weather data from Automated Surface Observing + System (ASOS) stations (airports) in the whole world thanks to the + Iowa Environment Mesonet website. + date_publication: '2025-01-31' + bug_reports: https://github.com/ropensci/riem/issues + url: https://docs.ropensci.org/riem/ + url_cran: https://CRAN.R-project.org/package=riem + url_git: https://github.com/ropensci/riem +Riemann: + version: 0.1.4 + title: Learning with Data on Riemannian Manifolds + maintainer: Kisung You + description: We provide a variety of algorithms for manifold-valued data, including + Fréchet summaries, hypothesis testing, clustering, visualization, and other learning + tasks. See Bhattacharya and Bhattacharya (2012) + for general exposition to statistics on manifolds. + date_publication: '2022-02-28' + bug_reports: https://github.com/kisungyou/Riemann/issues + url: https://kisungyou.com/Riemann/ + url_cran: https://CRAN.R-project.org/package=Riemann + url_git: '' +RiemBase: + version: 0.2.5 + title: Functions and C++ Header Files for Computation on Manifolds + maintainer: Kisung You + description: We provide a number of algorithms to estimate fundamental statistics + including Fréchet mean and geometric median for manifold-valued data. Also, C++ + header files are contained that implement elementary operations on manifolds such + as Sphere, Grassmann, and others. See Bhattacharya and Bhattacharya (2012) + if you are interested in statistics on manifolds, and Absil et al (2007, ISBN:9780691132983) + on computational aspects of optimization on matrix manifolds. + date_publication: '2021-08-21' + bug_reports: https://github.com/kisungyou/RiemBase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RiemBase + url_git: https://github.com/kisungyou/RiemBase +Riex: + version: 1.0.2 + title: IEX Stocks and Market Data + maintainer: Myriam Ibrahim + description: |- + Retrieves efficiently and reliably Investors Exchange ('IEX') stock and market data using 'IEX Cloud API'. The platform is offered by Investors Exchange Group (IEX Group). + Main goal is to leverage 'R' capabilities including existing packages to effectively provide financial and statistical analysis as well as visualization in support of fact-based decisions. + In addition, continuously improve and enhance 'Riex' by applying best practices and being in tune with users' feedback and requirements. + Please, make sure to review and acknowledge Investors Exchange Group (IEX Group) terms and conditions before using 'Riex' (). + date_publication: '2021-04-24' + bug_reports: https://github.com/TheEliteAnalyst/Riex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Riex + url_git: https://github.com/TheEliteAnalyst/Riex +rifle: + version: '1.0' + title: Sparse Generalized Eigenvalue Problem + maintainer: Kean Ming Tan + description: 'Implements the algorithms for solving sparse generalized eigenvalue + problem by Tan, et. al. (2018). Sparse Generalized Eigenvalue Problem: Optimal + Statistical Rates via Truncated Rayleigh Flow. To appear in Journal of the Royal + Statistical Society: Series B. .' + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rifle + url_git: '' +rifreg: + version: 0.1.0 + title: Estimate Recentered Influence Function Regression + maintainer: Samuel Meier + description: |- + Provides functions to compute recentered influence functions + (RIF) of a distributional variable at the mean, quantiles, variance, + gini or any custom functional of interest. The package allows to + regress the RIF on any number of covariates. Generic print, plot and + summary functions are also provided. Reference: Firpo, Sergio, Nicole M. Fortin, and Thomas Lemieux. (2009) . "Unconditional Quantile Regressions.". + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rifreg + url_git: '' +RIFS: + version: 0.1.6 + title: Random Iterated Function System + maintainer: Pavel V. Moskalev + description: Pointwise generation and display of attractors (prefractals) of the + random iterated function system (RIFS) for various combinations of probabilistic + and geometric parameters of some fixed point sets (protofractals), described by + Bukhovets A.G. (2012) . + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RIFS + url_git: '' +Rigma: + version: 0.3.0 + title: Access to the 'Figma' API + maintainer: Alexandros Kouretsis + description: |- + The goal of Rigma is to provide a user friendly client to the + 'Figma' API . It uses the latest + `httr2` for a stable interface with the REST API. More than 20 methods + are provided to interact with 'Figma' files, and teams. Get design + data into R by reading published components and styles, converting and + downloading images, getting access to the full 'Figma' file as a + hierarchical data structure, and much more. Enhance your creativity + and streamline the application development by automating the + extraction, transformation, and loading of design data to your + applications and 'HTML' documents. + date_publication: '2025-02-23' + bug_reports: https://github.com/AleKoure/Rigma/issues + url: https://AleKoure.github.io/Rigma/ + url_cran: https://CRAN.R-project.org/package=Rigma + url_git: https://github.com/AleKoure/Rigma +rigr: + version: 1.0.4 + title: Regression, Inference, and General Data Analysis Tools in R + maintainer: Amy D Willis + description: A set of tools to streamline data analysis. Learning both R and introductory + statistics at the same time can be challenging, and so we created 'rigr' to facilitate + common data analysis tasks and enable learners to focus on statistical concepts. + We provide easy-to-use interfaces for descriptive statistics, one- and two-sample + inference, and regression analyses. 'rigr' output includes key information while + omitting unnecessary details that can be confusing to beginners. Heteroscedasticity-robust + ("sandwich") standard errors are returned by default, and multiple partial F-tests + and tests for contrasts are easy to specify. A single regression function can + fit both linear and generalized linear models, allowing students to more easily + make connections between different classes of models. + date_publication: '2022-09-06' + bug_reports: https://github.com/statdivlab/rigr/issues/ + url: https://statdivlab.github.io/rigr/ + url_cran: https://CRAN.R-project.org/package=rigr + url_git: '' +riingo: + version: 0.3.1 + title: An R Interface to the 'Tiingo' Stock Price API + maintainer: Davis Vaughan + description: |- + Functionality to download stock prices, + cryptocurrency data, and more from the 'Tiingo' API + . + date_publication: '2020-09-12' + bug_reports: https://github.com/business-science/riingo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=riingo + url_git: https://github.com/business-science/riingo +Rilostat: + version: 2.2.0 + title: ILO Open Data via Ilostat Bulk Download Facility + maintainer: David Bescond + description: |- + Tools to download data from the ilostat database + together with search and + manipulation utilities. + date_publication: '2024-09-03' + bug_reports: https://github.com/ilostat/Rilostat/issues + url: https://ilostat.github.io/Rilostat/ + url_cran: https://CRAN.R-project.org/package=Rilostat + url_git: '' +rim: + version: 0.7.0 + title: Interface to 'Maxima', Enabling Symbolic Computation + maintainer: Eric Stemmler + description: |- + An interface to the powerful and fairly complete computer algebra system 'Maxima'. + It can be used to start and control 'Maxima' from within R by entering 'Maxima' commands. + Results from 'Maxima' can be parsed and evaluated in R. + It facilitates outputting results from 'Maxima' in 'LaTeX' and 'MathML'. + 2D and 3D plots can be displayed directly. + This package also registers a 'knitr'-engine enabling 'Maxima' code chunks + to be written in 'RMarkdown' documents. + date_publication: '2024-10-18' + bug_reports: https://github.com/rcst/rim/issues + url: https://rcst.github.io/rim/ + url_cran: https://CRAN.R-project.org/package=rim + url_git: '' +RImageJROI: + version: 0.1.3 + title: Read and Write 'ImageJ' Region of Interest (ROI) Files + maintainer: David C Sterratt + description: |- + Provides functions to read and write 'ImageJ' () + Region of Interest (ROI) files, to plot the ROIs and to convert them to + 'spatstat' () spatial patterns. + date_publication: '2024-08-17' + bug_reports: https://github.com/davidcsterratt/RImageJROI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RImageJROI + url_git: https://github.com/davidcsterratt/RImageJROI +RImagePalette: + version: 0.1.1 + title: Extract the Colors from Images + maintainer: Joel Carlson + description: |- + A pure R implementation of the median cut algorithm. + Extracts the dominant colors from an image, and turns them into + a scale for use in plots or for fun! + date_publication: '2016-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RImagePalette + url_git: '' +RImpact: + version: '1.0' + title: Calculates Measures of Scholarly Impact + maintainer: John Ruscio + description: |- + The metrics() function calculates measures of scholarly impact. + These include conventional measures, such as the number of publications + and the total citations to all publications, as well as modern and + robust metrics based on the vector of citations associated with each + publication, such as the h index and many of its variants or rivals. + These methods are described in Ruscio et al. (2012) + . + date_publication: '2018-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RImpact + url_git: '' +rimu: + version: '0.6' + title: Responses in Multiplex + maintainer: Thomas Lumley + description: Tools for manipulating, exploring, and visualising multiple-response + data, including scored or ranked responses. Conversions to and from factors, lists, + strings, matrices; reordering, lumping, flattening; set operations; tables; frequency + and co-occurrence plots. + date_publication: '2022-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rimu + url_git: '' +rinat: + version: 0.1.9 + title: Access 'iNaturalist' Data Through APIs + maintainer: Stéphane Guillou + description: A programmatic interface to the API provided by the 'iNaturalist' website + to download species occurrence data submitted by + citizen scientists. + date_publication: '2022-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rinat + url_git: https://docs.ropensci.org/rinat/(website)https://github.com/ropensci/rinat(devel) +rineq: + version: 0.3.0 + title: Concentration Index and Decomposition for Health Inequalities + maintainer: Kaspar Meili + description: |- + Relative, generalized, and Erreygers corrected concentration index; plot Lorenz curves; and decompose health + inequalities into contributing factors. The package currently works with (generalized) linear models, survival models, complex survey models, and marginal effects probit models. + originally forked by Brecht Devleesschauwer from the 'decomp' package (no longer on CRAN), 'rineq' is now maintained by Kaspar Walter Meili. Compared to the earlier 'rineq' version on 'github' by Brecht Devleesschauwer (), the regression tree functionality has been removed. + Improvements compared to earlier versions include improved plotting of decomposition and concentration, added functionality to calculate the concentration index with different methods, calculation of robust standard errors, and support for the decomposition analysis using marginal effects probit regression models. The development version is available at . + date_publication: '2025-01-13' + bug_reports: https://github.com/kdevkdev/rineq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rineq + url_git: https://github.com/kdevkdev/rineq +ring: + version: 1.0.6 + title: Circular / Ring Buffers + maintainer: Rich FitzJohn + description: |- + Circular / ring buffers in R and C. There are a couple + of different buffers here with different implementations that + represent different trade-offs. + date_publication: '2024-09-06' + bug_reports: https://github.com/mrc-ide/ring/issues + url: https://mrc-ide.gitub.io/ring + url_cran: https://CRAN.R-project.org/package=ring + url_git: https://github.com/mrc-ide/ring +ringostat: + version: 0.1.5 + title: Load Data from 'Ringostat API' + maintainer: Alexey Seleznev + description: |- + Loading calls data from 'Ringostat API'. + See . + date_publication: '2022-08-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ringostat + url_git: '' +RInside: + version: 0.2.18 + title: C++ Classes to Embed R in C++ (and C) Applications + maintainer: Dirk Eddelbuettel + description: |- + C++ classes to embed R in C++ (and C) applications + A C++ class providing the R interpreter is offered by this package + making it easier to have "R inside" your C++ application. As R itself + is embedded into your application, a shared library build of R is + required. This works on Linux, OS X and even on Windows provided you + use the same tools used to build R itself. Numerous examples are + provided in the nine subdirectories of the examples/ directory of + the installed package: standard, 'mpi' (for parallel computing), 'qt' + (showing how to embed 'RInside' inside a Qt GUI application), 'wt' + (showing how to build a "web-application" using the Wt toolkit), + 'armadillo' (for 'RInside' use with 'RcppArmadillo'), 'eigen' (for + 'RInside' use with 'RcppEigen'), and 'c_interface' for a basic C + interface and 'Ruby' illustration. The examples use 'GNUmakefile(s)' + with GNU extensions, so a GNU make is required (and will use the + 'GNUmakefile' automatically). 'Doxygen'-generated documentation of + the C++ classes is available at the 'RInside' website as well. + date_publication: '2023-02-01' + bug_reports: https://github.com/eddelbuettel/rinside/issues + url: https://dirk.eddelbuettel.com/code/rinside.html + url_cran: https://CRAN.R-project.org/package=RInside + url_git: https://github.com/eddelbuettel/rinside/ +RInSp: + version: 1.2.5 + title: R Individual Specialization + maintainer: Dr. Nicola Zaccarelli + description: |- + Functions to calculate several ecological indices of individual + and population niche width (Araujo's E, clustering and pairwise similarity + among individuals, IS, Petraitis' W, and Roughgarden's WIC/TNW) to assess + individual specialization based on data of resource use. Resource use can + be quantified by counts of categories, measures of mass or length, or + proportions. Monte Carlo resampling procedures are available for hypothesis + testing against multinomial null models. + Details are provided in Zaccarelli et al. (2013) + and associated references. + date_publication: '2022-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RInSp + url_git: '' +rintcal: + version: 1.1.2 + title: Radiocarbon Calibration Curves + maintainer: Maarten Blaauw + description: The IntCal20 radiocarbon calibration curves (Reimer et al. 2020 ) + are provided as a data package, together with previous IntCal curves (IntCal13, + IntCal09, IntCal04, IntCal98), other curves (e.g., NOTCal04 [van der Plicht et + al. 2004], Arnold & Libby 1951) and postbomb curves. Also provided are functions + to copy the curves into memory, and to read, query and plot the data underlying + the IntCal20 curves. + date_publication: '2025-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rintcal + url_git: '' +rIntervalTree: + version: 0.1.0 + title: An Interval Tree Tool for Real Numbers + maintainer: Shuye Pu + description: |- + This tool can be used to build binary interval trees using real number inputs. + The tree supports queries of intervals overlapping a single number or an interval (start, end). + Intervals with same bounds but different names are treated as distinct intervals. + Insertion of intervals is also allowed. Deletion of intervals is not implemented at this point. + See Mark de Berg, Otfried Cheong, Marc van Kreveld, Mark Overmars (2008). Computational Geometry: Algorithms and Applications, for a reference. + date_publication: '2019-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rIntervalTree + url_git: '' +rintimg: + version: 0.1.0 + title: |- + View Images on Full Screen in 'RMarkdown' Documents and 'shiny' + Applications + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to view an image in full screen when clicking on it in 'RMarkdown' documents and 'shiny' applications. + The package relies on the 'JavaScript' library 'intense-images'. See for more information. + date_publication: '2020-09-30' + bug_reports: https://github.com/feddelegrand7/rintimg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rintimg + url_git: https://github.com/feddelegrand7/rintimg +rintrojs: + version: 0.3.4 + title: Wrapper for the 'Intro.js' Library + maintainer: Carl Ganz + description: |- + A wrapper for the 'Intro.js' library (For more info: ). + This package makes it easy to include step-by-step introductions, and clickable hints in a 'Shiny' + application. It supports both static introductions in the UI, and programmatic introductions from + the server-side. + date_publication: '2024-01-11' + bug_reports: https://github.com/carlganz/rintrojs/issues + url: http://rintrojs.carlganz.com + url_cran: https://CRAN.R-project.org/package=rintrojs + url_git: https://github.com/carlganz/rintrojs +rio: + version: 1.2.3 + title: A Swiss-Army Knife for Data I/O + maintainer: Chung-hong Chan + description: |- + Streamlined data import and export by making assumptions that + the user is probably willing to make: 'import()' and 'export()' determine + the data format from the file extension, reasonable defaults are used for + data import and export, web-based import is natively supported (including + from SSL/HTTPS), compressed files can be read directly, and fast import + packages are used where appropriate. An additional convenience function, + 'convert()', provides a simple method for converting between file types. + date_publication: '2024-09-25' + bug_reports: https://github.com/gesistsa/rio/issues + url: https://gesistsa.github.io/rio/ + url_cran: https://CRAN.R-project.org/package=rio + url_git: https://github.com/gesistsa/rio +rioja: + version: 1.0-7 + title: Analysis of Quaternary Science Data + maintainer: Steve Juggins + description: Constrained clustering, transfer functions, and other methods for analysing + Quaternary science data. + date_publication: '2024-09-26' + bug_reports: '' + url: http://www.staff.ncl.ac.uk/stephen.juggins/ + url_cran: https://CRAN.R-project.org/package=rioja + url_git: https://github.com/nsj3/rioja +rioplot: + version: 1.1.1 + title: Turn a Regression Model Inside Out + maintainer: David Melamed + description: Turns regression models inside out. Functions decompose variances and + coefficients for various regression model types. Functions also visualize regression + model objects using techniques developed in Schoon, Melamed, and Breiger (2024) + . + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rioplot + url_git: '' +ripc: + version: 0.3.1 + title: Download and Tidy IPC and CH Data + maintainer: Seth Caldwell + description: |- + Utilities to access Integrated Food Security Phase Classification + (IPC) and Cadre Harmonisé (CH) food security data. Wrapper functions are + available for all of the 'IPC-CH' Public API () + simplified and advanced endpoints to easily download the data in a clean and + tidy format. + date_publication: '2024-06-25' + bug_reports: https://github.com/ocha-dap/ripc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ripc + url_git: https://github.com/ocha-dap/ripc +ripserr: + version: 0.1.1 + title: Calculate Persistent Homology with Ripser-Based Engines + maintainer: Raoul Wadhwa + description: |- + Ports the Ripser and Cubical Ripser + persistent homology calculation engines from + C++. Can be used as a rapid calculation tool in topological + data analysis pipelines. + date_publication: '2020-10-20' + bug_reports: https://github.com/rrrlw/ripserr/issues + url: https://rrrlw.github.io/ripserr/ + url_cran: https://CRAN.R-project.org/package=ripserr + url_git: '' +rirods: + version: 0.2.0 + title: R Client for 'iRODS' + maintainer: Martin Schobben + description: |- + The open sourced data management software 'Integrated + Rule-Oriented Data System' ('iRODS') offers solutions for the whole + data life cycle (). The loosely constructed and + highly configurable architecture of 'iRODS' frees the user from strict + formatting constraints and single-vendor solutions. This package + provides an interface to the 'iRODS' HTTP API, allowing you to manage + your data and metadata in 'iRODS' with R. Storage of annotated files + and R objects in 'iRODS' ensures findability, accessibility, + interoperability, and reusability of data. + date_publication: '2024-03-15' + bug_reports: https://github.com/irods/irods_client_library_rirods/issues + url: https://rirods.irods4r.org + url_cran: https://CRAN.R-project.org/package=rirods + url_git: https://github.com/irods/irods_client_library_rirods +Rirt: + version: 0.0.2 + title: |- + Data Analysis and Parameter Estimation Using Item Response + Theory + maintainer: Xiao Luo + description: |- + Parameter estimation, computation of probability, information, and + (log-)likelihood, and visualization of item/test characteristic curves and + item/test information functions for three uni-dimensional item response theory + models: the 3-parameter-logistic model, generalized partial credit model, + and graded response model. The full documentation and tutorials are at + . + date_publication: '2019-10-23' + bug_reports: https://github.com/xluo11/Rirt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rirt + url_git: https://github.com/xluo11/Rirt +RISCA: + version: 1.0.7 + title: Causal Inference and Prediction in Cohort-Based Analyses + maintainer: Yohann Foucher + description: Numerous functions for cohort-based analyses, either for prediction + or causal inference. For causal inference, it includes Inverse Probability Weighting + and G-computation for marginal estimation of an exposure effect when confounders + are expected. We deal with binary outcomes, times-to-events, competing events, + and multi-state data. For multistate data, semi-Markov model with interval censoring + may be considered, and we propose the possibility to consider the excess of mortality + related to the disease compared to reference lifetime tables. For predictive studies, + we propose a set of functions to estimate time-dependent receiver operating characteristic + (ROC) curves with the possible consideration of right-censoring times-to-events + or the presence of confounders. Finally, several functions are available to assess + time-dependent ROC curves or survival curves from aggregated data. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RISCA + url_git: '' +rise: + version: 1.0.4 + title: Conduct RISE Analysis + maintainer: David Wiley + description: "Implements techniques for educational resource inspection, selection, + and evaluation (RISE) described in Bodily, Nyland, and Wiley (2017)\n.\tAutomates + the process of identifying learning materials that are not effectively supporting + student learning in\ntechnology-mediated courses by synthesizing information about + access to course content and performance on assessments." + date_publication: '2018-10-04' + bug_reports: https://github.com/lumenlearning/rise/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rise + url_git: '' +rIsing: + version: 0.1.0 + title: High-Dimensional Ising Model Selection + maintainer: Pratik Ramprasad + description: |- + Fits an Ising model to a binary dataset using L1 regularized + logistic regression and extended BIC. Also includes a fast lasso logistic + regression function for high-dimensional problems. Uses the 'libLBFGS' + optimization library by Naoaki Okazaki. + date_publication: '2016-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rIsing + url_git: '' +Risk: + version: '1.0' + title: |- + Computes 26 Financial Risk Measures for Any Continuous + Distribution + maintainer: Saralees Nadarajah + description: Computes 26 financial risk measures for any continuous distribution. The + 26 financial risk measures include value at risk, expected shortfall due to Artzner + et al. (1999) , tail conditional median due to + Kou et al. (2013) , expectiles due to Newey and Powell + (1987) , beyond value at risk due to Longin (2001) , + expected proportional shortfall due to Belzunce et al. (2012) , + elementary risk measure due to Ahmadi-Javid (2012) , + omega due to Shadwick and Keating (2002), sortino ratio due to Rollinger and Hoffman + (2013), kappa due to Kaplan and Knowles (2004), Wang (1998)'s + risk measures, Stone (1973)'s risk measures, Luce (1980)'s + risk measures, Sarin (1987)'s + risk measures, Bronshtein and Kurelenkova (2009)'s risk measures. + date_publication: '2017-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Risk + url_git: '' +riskclustr: + version: 0.4.1 + title: Functions to Study Etiologic Heterogeneity + maintainer: Emily C. Zabor + description: A collection of functions related to the study of etiologic heterogeneity + both across disease subtypes and across individual disease markers. The included + functions allow one to quantify the extent of etiologic heterogeneity in the context + of a case-control study, and provide p-values to test for etiologic heterogeneity + across individual risk factors. Begg CB, Zabor EC, Bernstein JL, Bernstein L, + Press MF, Seshan VE (2013) . + date_publication: '2024-01-18' + bug_reports: https://github.com/zabore/riskclustr/issues + url: https://www.emilyzabor.com/riskclustr/ + url_cran: https://CRAN.R-project.org/package=riskclustr + url_git: https://github.com/zabore/riskclustr +riskCommunicator: + version: 1.0.1 + title: G-Computation to Estimate Interpretable Epidemiological Effects + maintainer: Jessica Grembi + description: Estimates flexible epidemiological effect measures including both differences + and ratios using the parametric G-formula developed as an alternative to inverse + probability weighting. It is useful for estimating the impact of interventions + in the presence of treatment-confounder-feedback. G-computation was originally + described by Robbins (1986) and has been described + in detail by Ahern, Hubbard, and Galea (2009) ; Snowden, + Rose, and Mortimer (2011) ; and Westreich et al. (2012) + . + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riskCommunicator + url_git: '' +RiskMap: + version: 0.1.0 + title: Geo-Statistical Modeling of Spatially Referenced Data + maintainer: Emanuele Giorgi + description: 'Provides functions for geo-statistical analysis of both continuous + and count data using maximum likelihood methods. The models implemented in the + package use stationary Gaussian processes with Matern correlation function to + carry out spatial prediction in a geographical area of interest. The underpinning + theory of the methods implemented in the package are found in Diggle and Giorgi + (2019, ISBN: 978-1-138-06102-7).' + date_publication: '2024-06-25' + bug_reports: '' + url: https://claudiofronterre.github.io/RiskMap/ + url_cran: https://CRAN.R-project.org/package=RiskMap + url_git: '' +riskmetric: + version: 0.2.4 + title: Risk Metrics to Evaluating R Packages + maintainer: Eli Miller + description: |- + Facilities for assessing R packages against a number of metrics to + help quantify their robustness. + date_publication: '2024-01-09' + bug_reports: https://github.com/pharmaR/riskmetric/issues + url: https://pharmar.github.io/riskmetric/ + url_cran: https://CRAN.R-project.org/package=riskmetric + url_git: https://github.com/pharmaR/riskmetric +riskParityPortfolio: + version: 0.2.2 + title: Design of Risk Parity Portfolios + maintainer: Daniel P. Palomar + description: |- + Fast design of risk parity portfolios for financial investment. + The goal of the risk parity portfolio formulation is to equalize or distribute + the risk contributions of the different assets, which is missing if we simply + consider the overall volatility of the portfolio as in the mean-variance + Markowitz portfolio. In addition to the vanilla formulation, where the risk + contributions are perfectly equalized subject to no shortselling and budget + constraints, many other formulations are considered that allow for box + constraints and shortselling, as well as the inclusion of additional + objectives like the expected return and overall variance. See vignette for + a detailed documentation and comparison, with several illustrative examples. + The package is based on the papers: + Y. Feng, and D. P. Palomar (2015). SCRIP: Successive Convex Optimization Methods + for Risk Parity Portfolio Design. IEEE Trans. on Signal Processing, vol. 63, + no. 19, pp. 5285-5300. . + F. Spinu (2013), An Algorithm for Computing Risk Parity Weights. + . + T. Griveau-Billion, J. Richard, and T. Roncalli (2013). A fast algorithm for computing + High-dimensional risk parity portfolios. . + date_publication: '2021-06-01' + bug_reports: https://github.com/dppalomar/riskParityPortfolio/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=riskParityPortfolio + url_git: https://github.com/dppalomar/riskParityPortfolio +RiskPortfolios: + version: 2.1.7 + title: Computation of Risk-Based Portfolios + maintainer: David Ardia + description: |- + Collection of functions designed to compute risk-based portfolios as described + in Ardia et al. (2017) and Ardia et al. (2017) . + date_publication: '2021-05-16' + bug_reports: https://github.com/ArdiaD/RiskPortfolios/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RiskPortfolios + url_git: https://github.com/ArdiaD/RiskPortfolios +riskPredictClustData: + version: 0.2.6 + title: Assessing Risk Predictions for Clustered Data + maintainer: Weiliang Qiu + description: 'Assessing and comparing risk prediction rules for clustered data. + The method is based on the paper: Rosner B, Qiu W, and Lee MLT.(2013) .' + date_publication: '2018-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riskPredictClustData + url_git: '' +riskRegression: + version: 2023.12.21 + title: |- + Risk Regression Models and Prediction Scores for Survival + Analysis with Competing Risks + maintainer: Thomas Alexander Gerds + description: |- + Implementation of the following methods for event history analysis. + Risk regression models for survival endpoints also in the presence of competing + risks are fitted using binomial regression based on a time sequence of binary + event status variables. A formula interface for the Fine-Gray regression model + and an interface for the combination of cause-specific Cox regression models. + A toolbox for assessing and comparing performance of risk predictions (risk + markers and risk prediction models). Prediction performance is measured by the + Brier score and the area under the ROC curve for binary possibly time-dependent + outcome. Inverse probability of censoring weighting and pseudo values are used + to deal with right censored data. Lists of risk markers and lists of risk models + are assessed simultaneously. Cross-validation repeatedly splits the data, trains + the risk prediction models on one part of each split and then summarizes and + compares the performance across splits. + date_publication: '2023-12-19' + bug_reports: https://github.com/tagteam/riskRegression/issues + url: '' + url_cran: https://CRAN.R-project.org/package=riskRegression + url_git: https://github.com/tagteam/riskRegression +risks: + version: 0.4.2 + title: Estimate Risk Ratios and Risk Differences using Regression + maintainer: Konrad Stopsack + description: |- + Risk ratios and risk differences are estimated using regression + models that allow for binary, categorical, and continuous exposures and + confounders. Implemented are marginal standardization after fitting logistic + models (g-computation) with delta-method and bootstrap standard errors, + Miettinen's case-duplication approach (Schouten et al. 1993, + ), log-binomial (Poisson) models with empirical + variance (Zou 2004, ), binomial models with starting + values from Poisson models (Spiegelman and Hertzmark 2005, + ), and others. + date_publication: '2023-06-13' + bug_reports: https://github.com/stopsack/risks/issues + url: https://stopsack.github.io/risks/ + url_cran: https://CRAN.R-project.org/package=risks + url_git: '' +riskscores: + version: 1.1.1 + title: Optimized Integer Risk Score Models + maintainer: Hannah Eglinton + description: Implements an optimized approach to learning risk score models, where + sparsity and integer constraints are integrated into the model-fitting process. + date_publication: '2024-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riskscores + url_git: https://github.com/hjeglinton/riskscores +RiskScorescvd: + version: 0.2.0 + title: Cardiovascular Risk Scores Calculator + maintainer: Daniel Perez-Vicencio + description: A tool to calculate Cardiovascular Risk Scores in large data frames. + Cardiovascular risk scores are statistical tools used to assess an individual's + likelihood of developing a cardiovascular disease based on various risk factors, + such as age, gender, blood pressure, cholesterol levels, and smoking. Here we + bring together the six most commonly used in the emergency department. Using 'RiskScorescvd', + you can calculate all the risk scores in an extended dataset in seconds. PCE (ASCVD) + described in Goff, et al (2013) . EDACS + described in Mark DG, et al (2016) . GRACE described + in Fox KA, et al (2006) . HEART is described + in Mahler SA, et al (2017) . SCORE2/OP + described in SCORE2 working group and ESC Cardiovascular risk collaboration (2021) + . TIMI described in Antman EM, et al (2000) . + SCORE2-Diabetes described in SCORE2-Diabetes working group and ESC Cardiovascular + risk collaboration (2023) . SCORE2/OP with CKD + add-on described in Kunihiro M et al (2022) . + date_publication: '2024-06-27' + bug_reports: https://github.com/dvicencio/RiskScorescvd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RiskScorescvd + url_git: https://github.com/dvicencio/RiskScorescvd +risksetROC: + version: 1.0.4.1 + title: Riskset ROC Curve Estimation from Censored Survival Data + maintainer: Paramita Saha-Chaudhuri + description: |- + Compute time-dependent Incident/dynamic accuracy measures + (ROC curve, AUC, integrated AUC )from censored survival data + under proportional or non-proportional hazard assumption of + Heagerty & Zheng (Biometrics, Vol 61 No 1, 2005, PP 92-105). + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=risksetROC + url_git: '' +riskSimul: + version: 0.1.2 + title: |- + Risk Quantification for Stock Portfolios under the T-Copula + Model + maintainer: Wolfgang Hormann + description: Implements efficient simulation procedures to estimate tail loss probabilities + and conditional excess for a stock portfolio. The log-returns are assumed to follow + a t-copula model with generalized hyperbolic or t marginals. + date_publication: '2023-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riskSimul + url_git: '' +riskyr: + version: 0.4.0 + title: Rendering Risk Literacy more Transparent + maintainer: Hansjoerg Neth + description: Risk-related information (like the prevalence of conditions, the sensitivity + and specificity of diagnostic tests, or the effectiveness of interventions or + treatments) can be expressed in terms of frequencies or probabilities. By providing + a toolbox of corresponding metrics and representations, 'riskyr' computes, translates, + and visualizes risk-related information in a variety of ways. Adopting multiple + complementary perspectives provides insights into the interplay between key parameters + and renders teaching and training programs on risk literacy more transparent. + date_publication: '2022-08-15' + bug_reports: https://github.com/hneth/riskyr/issues/ + url: https://riskyr.org/ + url_cran: https://CRAN.R-project.org/package=riskyr + url_git: https://github.com/hneth/riskyr/ +RISmed: + version: 2.3.0 + title: Download Content from NCBI Databases + maintainer: Stephanie Kovalchik + description: |- + A set of tools to extract bibliographic content from the National + Center for Biotechnology Information (NCBI) databases, including PubMed. The + name RISmed is a portmanteau of RIS (for Research Information Systems, a common + tag format for bibliographic data) and PubMed. + date_publication: '2021-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RISmed + url_git: '' +Rita: + version: 1.2.0 + title: Automated Transformations, Normality Testing, and Reporting + maintainer: Daniel Mattei + description: |2- + + Automated performance of common transformations used to fulfill parametric + assumptions of normality and identification of the best performing method + for the user. Output for various normality tests (Thode, 2002) corresponding + to the best performing method and a descriptive statistical report of the + input data in its original units (5-number summary and mathematical moments) + are also presented. Lastly, the Rankit, an empirical normal quantile transformation + (ENQT) (Soloman & Sawilowsky, 2009), is provided to accommodate non-standard + use cases and facilitate adoption. + . + . + date_publication: '2022-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rita + url_git: '' +ritalic: + version: 0.10.1 + title: Interface to the ITALIC Database of Lichen Biodiversity + maintainer: Matteo Conti + description: |- + A programmatic interface to the Web Service methods provided by ITALIC (). + ITALIC is a database of lichen data in Italy and bordering European countries. 'ritalic' includes functions for retrieving information + about lichen scientific names, geographic distribution, ecological data, morpho-functional traits and identification keys. + More information about the data is available at . + The API documentation is available at . + date_publication: '2025-01-07' + bug_reports: https://github.com/plant-data/ritalic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ritalic + url_git: https://github.com/plant-data/ritalic +Ritc: + version: 1.0.2 + title: Isothermal Titration Calorimetry (ITC) Data Analysis + maintainer: Yingyun Liu + description: |- + Implements the simulation and regression of + integrated Isothermal Titration Calorimetry (ITC) data using + the most commonly used one-to-one binding reaction model. + date_publication: '2016-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ritc + url_git: '' +RITCH: + version: 0.1.26 + title: R Parser for the ITCH-Protocol + maintainer: David Zimmermann-Kollenda + description: Allows to efficiently parse, filter, and write binary ITCH Files (Version + 5.0) containing detailed financial transactions as distributed by NASDAQ to an + R data.table. + date_publication: '2024-01-15' + bug_reports: https://github.com/DavZim/RITCH/issues + url: https://davzim.github.io/RITCH/ + url_cran: https://CRAN.R-project.org/package=RITCH + url_git: https://github.com/DavZim/RITCH +ritis: + version: 1.0.0 + title: Integrated Taxonomic Information System Client + maintainer: Scott Chamberlain + description: |- + An interface to the Integrated Taxonomic Information System ('ITIS') + (). Includes functions to work with the 'ITIS' REST + API methods (), as well as the + 'Solr' web service (). + date_publication: '2021-02-02' + bug_reports: https://github.com/ropensci/ritis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ritis + url_git: https://github.com/ropensci/ritis(devel)https://docs.ropensci.org/ritis/(docs) +RItools: + version: 0.3-4 + title: Randomization Inference Tools + maintainer: Jake Bowers + description: Tools for randomization-based inference. Current focus is on the d^2 + omnibus test of differences of means following Hansen and Bowers (2008) + . This test is useful for assessing balance in matched observational studies or + for analysis of outcomes in block-randomized experiments. + date_publication: '2024-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RItools + url_git: '' +riv: + version: 2.0-5 + title: Robust Instrumental Variables Estimator + maintainer: Gabriela Cohen-Freue + description: |- + Finds a robust instrumental variables estimator using a + high breakdown point S-estimator of multivariate location + and scatter matrix. + date_publication: '2018-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=riv + url_git: '' +RiverBuilder: + version: 0.1.1 + title: River Generation for Given Data Sets + maintainer: Gregory Pasternack + description: Generates graphs, CSV files, and coordinates related to river valleys + when calling the riverbuilder() function. + date_publication: '2018-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RiverBuilder + url_git: '' +riverconn: + version: 0.3.31 + title: Fragmentation and Connectivity Indices for Riverscapes + maintainer: Damiano Baldan + description: Indices for assessing riverscape fragmentation, including the Dendritic + Connectivity Index, the Population Connectivity Index, the River Fragmentation + Index, the Probability of Connectivity, and the Integral Index of connectivity. + For a review, see Jumani et al. (2020) and Baldan + et al. (2022) Functions to calculate temporal + indices improvement when fragmentation due to barriers is reduced are also included. + date_publication: '2024-01-23' + bug_reports: https://github.com/damianobaldan/riverconn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=riverconn + url_git: https://github.com/damianobaldan/riverconn +riverdist: + version: 0.17.1 + title: River Network Distance Computation and Applications + maintainer: Matt Tyers + description: |- + Reads river network shape files and computes network distances. + Also included are a variety of computation and graphical tools designed + for fisheries telemetry research, such as minimum home range, kernel density + estimation, and clustering analysis using empirical k-functions with + a bootstrap envelope. Tools are also provided for editing the river + networks, meaning there is no reliance on external software. + date_publication: '2024-11-07' + bug_reports: https://github.com/mbtyers/riverdist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=riverdist + url_git: '' +rivernet: + version: 1.2.3 + title: Read, Analyze and Plot River Networks + maintainer: Peter Reichert + description: |- + Functions for reading, analysing and plotting river networks. + For this package, river networks consist of sections and nodes with associated attributes, + e.g. to characterise their morphological, chemical and biological state. + The package provides functions to read this data from text files, to analyse the network + structure and network paths and regions consisting of sections and nodes that fulfill + prescribed criteria, and to plot the river network and associated properties. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rivernet + url_git: '' +Rivivc: + version: 0.9.1 + title: In Vitro in Vivo Correlation Linear Level "A" + maintainer: Aleksander Mendyk + description: It is devoted to the IVIVC linear level A with numerical deconvolution + method. The latter is working for inequal and incompatible timepoints between + impulse and response curves. A numerical convolution method is also available. + Application domains include pharamaceutical industry QA/QC and R&D together with + academic research. + date_publication: '2022-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rivivc + url_git: '' +rivnet: + version: 0.6.0 + title: Extract and Analyze Rivers from Elevation Data + maintainer: Luca Carraro + description: |- + Seamless extraction of river networks from digital + elevation models data. The package allows analysis of digital + elevation models that can be either externally provided or + downloaded from open source repositories (thus interfacing + with the 'elevatr' package). Extraction is performed via the + 'D8' flow direction algorithm of TauDEM (Terrain Analysis Using + Digital Elevation Models), thus interfacing with the 'traudem' + package. Resulting river networks are compatible with functions + from the 'OCNet' package. See Carraro (2023) + for a presentation of the package. + date_publication: '2025-02-12' + bug_reports: https://github.com/lucarraro/rivnet/issues + url: https://lucarraro.github.io/rivnet/ + url_cran: https://CRAN.R-project.org/package=rivnet + url_git: '' +rivr: + version: 1.2-3 + title: Steady and Unsteady Open-Channel Flow Computation + maintainer: Michael C Koohafkan + description: |- + A tool for undergraduate and graduate courses in open-channel + hydraulics. Provides functions for computing normal and critical depths, + steady-state water surface profiles (e.g. backwater curves) and unsteady flow + computations (e.g. flood wave routing) as described in + Koohafkan MC, Younis BA (2015). "Open-channel computation with R." + The R Journal, 7(2), 249–262. . + date_publication: '2021-01-21' + bug_reports: https://github.com/mkoohafkan/rivr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rivr + url_git: https://github.com/mkoohafkan/rivr +RivRetrieve: + version: 0.1.6 + title: Retrieve Global River Gauge Data + maintainer: Ryan Riggs + description: 'Provides access to global river gauge data from a variety of national-level + river agencies. The package interfaces with the national-level agency websites + to provide access to river gauge locations, river discharge, and river stage. + Currently, the package is available for the following countries: Australia, Brazil, + Canada, Chile, France, Japan, South Africa, the United Kingdom, and the United + States.' + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RivRetrieve + url_git: https://github.com/Ryan-Riggs/RivRetrieve +rix: + version: 0.15.2 + title: Reproducible Data Science Environments with 'Nix' + maintainer: Bruno Rodrigues + description: |- + Simplifies the creation of reproducible data science environments + using the 'Nix' package manager, as described in + Dolstra (2006) . The included `rix()` + function generates a complete description of the environment as a + `default.nix` file, which can then be built using 'Nix'. This results in + project specific software environments with pinned versions of R, packages, + linked system dependencies, and other tools. Additional helpers make it easy + to run R code in 'Nix' software environments for testing and production. + date_publication: '2025-02-15' + bug_reports: https://github.com/ropensci/rix/issues + url: https://docs.ropensci.org/rix/ + url_cran: https://CRAN.R-project.org/package=rix + url_git: '' +rjade: + version: 0.1.1 + title: A Clean, Whitespace-Sensitive Template Language for Writing HTML + maintainer: Jeroen Ooms + description: |- + Jade is a high performance template engine heavily influenced by + Haml and implemented with JavaScript for node and browsers. + date_publication: '2021-04-16' + bug_reports: https://github.com/jeroen/rjade/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjade + url_git: https://github.com/jeroen/rjadehttps://www.npmjs.com/package/jade +rjaf: + version: 0.1.2 + title: |- + Regularized Joint Assignment Forest with Treatment Arm + Clustering + maintainer: Xinyi Zhang + description: 'Personalized assignment to one of many treatment arms via regularized + and clustered joint assignment forests as described in Ladhania, Spiess, Ungar, + and Wu (2023) . The algorithm pools information + across treatment arms: it considers a regularized forest-based assignment algorithm + based on greedy recursive partitioning that shrinks effect estimates across arms; + and it incorporates a clustering scheme that combines treatment arms with consistently + similar outcomes.' + date_publication: '2025-02-16' + bug_reports: https://github.com/wustat/rjaf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjaf + url_git: https://github.com/wustat/rjaf +RJafroc: + version: 2.1.2 + title: Artificial Intelligence Systems and Observer Performance + maintainer: Dev Chakraborty + description: |- + Analyzing the performance of artificial intelligence + (AI) systems/algorithms characterized by a 'search-and-report' + strategy. Historically observer performance has dealt with + measuring radiologists' performances in search tasks, e.g., searching + for lesions in medical images and reporting them, but the implicit + location information has been ignored. The implemented methods apply + to analyzing the absolute and relative performances of AI systems, + comparing AI performance to a group of human readers or optimizing the + reporting threshold of an AI system. In addition to performing historical + receiver operating receiver operating characteristic (ROC) analysis + (localization information ignored), the software also performs + free-response receiver operating characteristic (FROC) + analysis, where lesion localization information is used. A book + using the software has been published: Chakraborty DP: Observer + Performance Methods for Diagnostic Imaging - Foundations, Modeling, + and Applications with R-Based Examples, Taylor-Francis LLC; 2017: + . + Online updates to this book, which use the software, are at + , + and at + . Supported data + collection paradigms are the ROC, FROC and the location ROC (LROC). + ROC data consists of single ratings per images, where a rating is + the perceived confidence level that the image is that of a diseased + patient. An ROC curve is a plot of true positive fraction vs. false + positive fraction. FROC data consists of a variable number (zero or + more) of mark-rating pairs per image, where a mark is the location + of a reported suspicious region and the rating is the confidence + level that it is a real lesion. LROC data consists of a rating and a + location of the most suspicious region, for every image. Four models + of observer performance, and curve-fitting software, are implemented: + the binormal model (BM), the contaminated binormal model (CBM), the + correlated contaminated binormal model (CORCBM), and the radiological + search model (RSM). Unlike the binormal model, CBM, CORCBM and RSM + predict 'proper' ROC curves that do not inappropriately cross the + chance diagonal. Additionally, RSM parameters are related to search + performance (not measured in conventional ROC analysis) and + classification performance. Search performance refers to finding + lesions, i.e., true positives, while simultaneously not finding false + positive locations. Classification performance measures the ability to + distinguish between true and false positive locations. Knowing these + separate performances allows principled optimization of reader or AI + system performance. This package supersedes Windows JAFROC (jackknife + alternative FROC) software V4.2.1, + . Package functions are + organized as follows. Data file related function names are preceded + by 'Df', curve fitting functions by 'Fit', included data sets by 'dataset', + plotting functions by 'Plot', significance testing functions by 'St', + sample size related functions by 'Ss', data simulation functions by + 'Simulate' and utility functions by 'Util'. Implemented are figures of + merit (FOMs) for quantifying performance and functions for visualizing + empirical or fitted operating characteristics: e.g., ROC, FROC, alternative + FROC (AFROC) and weighted AFROC (wAFROC) curves. For fully crossed study + designs significance testing of reader-averaged FOM differences between + modalities is implemented via either Dorfman-Berbaum-Metz or the + Obuchowski-Rockette methods. Also implemented is single treatment analysis, + which allows comparison of performance of a group of radiologists to a + specified value, or comparison of AI to a group of radiologists interpreting + the same cases. Crossed-modality analysis is implemented wherein there are + two crossed treatment factors and the aim is to determined performance in + each treatment factor averaged over all levels of the second factor. Sample + size estimation tools are provided for ROC and FROC studies; these use + estimates of the relevant variances from a pilot study to predict required + numbers of readers and cases in a pivotal study to achieve the desired power. + Utility and data file manipulation functions allow data to be read in any of + the currently used input formats, including Excel, and the results of the + analysis can be viewed in text or Excel output files. The methods are + illustrated with several included datasets from the author's collaborations. + This update includes improvements to the code, some as a result of + user-reported bugs and new feature requests, and others discovered during + ongoing testing and code simplification. + date_publication: '2022-11-08' + bug_reports: '' + url: https://dpc10ster.github.io/RJafroc/ + url_cran: https://CRAN.R-project.org/package=RJafroc + url_git: '' +rjags: + version: 4-16 + title: Bayesian Graphical Models using MCMC + maintainer: Martyn Plummer + description: Interface to the JAGS MCMC library. + date_publication: '2024-08-19' + bug_reports: '' + url: https://mcmc-jags.sourceforge.io + url_cran: https://CRAN.R-project.org/package=rjags + url_git: '' +RJalaliDate: + version: 0.1.0 + title: Handling Jalali Date (Persian / Solar Hijri) + maintainer: Hosein Rabiee + description: |- + Jalali calendar, or solar Hijri, is calendar of Iran and + Afghanistan (). + This package is designed to working with Jalali date. For this + purpose, It defines JalaliDate class that is similar to Date class. + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RJalaliDate + url_git: '' +rJava: + version: 1.0-11 + title: Low-Level R to Java Interface + maintainer: Simon Urbanek + description: Low-level interface to Java VM very much like .C/.Call and friends. + Allows creation of objects, calling methods and accessing fields. + date_publication: '2024-01-26' + bug_reports: https://github.com/s-u/rJava/issues + url: http://www.rforge.net/rJava/ + url_cran: https://CRAN.R-project.org/package=rJava + url_git: '' +rJavaEnv: + version: 0.2.2 + title: '''Java'' Environments for R Projects' + maintainer: Egor Kotov + description: |- + Quickly install 'Java Development Kit (JDK)' without + administrative privileges and set environment variables in current R + session or project to solve common issues with 'Java' environment + management in 'R'. Recommended to users of 'Java'/'rJava'-dependent + 'R' packages such as 'r5r', 'opentripplanner', 'xlsx', 'openNLP', + 'rWeka', 'RJDBC', 'tabulapdf', and many more. 'rJavaEnv' prevents + common problems like 'Java' not found, 'Java' version conflicts, + missing 'Java' installations, and the inability to install 'Java' due + to lack of administrative privileges. 'rJavaEnv' automates the + download, installation, and setup of the 'Java' on a per-project basis + by setting the relevant 'JAVA_HOME' in the current 'R' session or the + current working directory (via '.Rprofile', with the user's consent). + Similar to what 'renv' does for 'R' packages, 'rJavaEnv' allows + different 'Java' versions to be used across different projects, but + can also be configured to allow multiple versions within the same + project (e.g. with the help of 'targets' package). Note: there are a + few extra steps for 'Linux' users, who don't have any 'Java' + previously installed in their system, and who prefer package + installation from source, rather then installing binaries from 'Posit + Package Manager'. See documentation for details. + date_publication: '2024-09-13' + bug_reports: https://github.com/e-kotov/rJavaEnv/issues + url: https://www.ekotov.pro/rJavaEnv/ + url_cran: https://CRAN.R-project.org/package=rJavaEnv + url_git: https://github.com/e-kotov/rJavaEnv +RJcluster: + version: 3.2.4 + title: |- + A Fast Clustering Algorithm for High Dimensional Data Based on + the Gram Matrix Decomposition + maintainer: Rachael Shudde + description: Clustering algorithm for high dimensional data. Assuming that P feature + measurements on N objects are arranged in an N×P matrix X, this package provides + clustering based on the left Gram matrix XX^T. To simulate test data, type "help('simulate_HD_data')" + and to learn how to use the clustering algorithm, type "help('RJclust')". To cite + this package, type 'citation("RJcluster")'. + date_publication: '2022-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RJcluster + url_git: '' +RJDBC: + version: 0.2-10 + title: Provides Access to Databases Through the JDBC Interface + maintainer: Simon Urbanek + description: The RJDBC package is an implementation of R's DBI interface using JDBC + as a back-end. This allows R to connect to any DBMS that has a JDBC driver. + date_publication: '2022-03-24' + bug_reports: '' + url: http://www.rforge.net/RJDBC/ + url_cran: https://CRAN.R-project.org/package=RJDBC + url_git: '' +RJDemetra: + version: 0.2.8 + title: Interface to 'JDemetra+' Seasonal Adjustment Software + maintainer: Alain Quartier-la-Tente + description: |- + Interface around 'JDemetra+' (), the seasonal adjustment software officially + recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. + It offers full access to all options and outputs of 'JDemetra+', including the two leading seasonal adjustment methods + TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS. + date_publication: '2024-12-12' + bug_reports: https://github.com/rjdverse/rjdemetra/issues + url: https://rjdverse.github.io/rjdemetra/ + url_cran: https://CRAN.R-project.org/package=RJDemetra + url_git: https://github.com/rjdverse/rjdemetra +rjdmarkdown: + version: 0.2.2 + title: '''rmarkdown'' Extension for Formatted ''RJDemetra'' Outputs' + maintainer: Alain Quartier-la-Tente + description: |- + Functions to have nice 'rmarkdown' outputs of the + seasonal and trading day adjustment models made with 'RJDemetra'. + date_publication: '2023-10-04' + bug_reports: https://github.com/AQLT/rjdmarkdown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjdmarkdown + url_git: https://github.com/AQLT/rjdmarkdown +rjdqa: + version: 0.1.5 + title: Quality Assessment for Seasonal Adjustment + maintainer: Alain Quartier-la-Tente + description: |- + Add-in to the 'RJDemetra' package on seasonal adjustments. + It allows to produce dashboards to summarise models and quickly check the quality of the seasonal adjustment. + date_publication: '2024-06-15' + bug_reports: https://github.com/AQLT/rjdqa/issues + url: https://aqlt.github.io/rjdqa/ + url_cran: https://CRAN.R-project.org/package=rjdqa + url_git: https://github.com/AQLT/rjdqa +rjdworkspace: + version: 1.1.9 + title: Manipulate 'JDemetra+' Workspaces + maintainer: Tanguy Barthelemy + description: |- + Set of tools to manipulate the 'JDemetra+' workspaces. + Based on the 'RJDemetra' package (which interfaces with version 2 of the 'JDemetra+' (), the seasonal adjustment software officially + recommended to the members of the European Statistical System (ESS) and the European System of Central Banks). + This package provides access to additional workspace manipulation functions such as metadata manipulation, raw paths and wrangling of several workspaces simultaneously. + These additional functionalities are useful as part of a CVS data production chain. + date_publication: '2025-01-21' + bug_reports: https://github.com/InseeFrLab/rjdworkspace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjdworkspace + url_git: https://github.com/InseeFrLab/rjdworkspace +rje: + version: 1.12.1 + title: Miscellaneous Useful Functions for Statistics + maintainer: Robin Evans + description: |- + A series of functions in some way considered useful to the author. These + include methods for subsetting tables and generating indices for arrays, + conditioning and intervening in probability distributions, generating + combinations, fast transformations, and more... + date_publication: '2022-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rje + url_git: '' +rjmcmc: + version: 0.4.5 + title: Reversible-Jump MCMC Using Post-Processing + maintainer: Nick Gelling + description: |- + Performs reversible-jump Markov chain Monte Carlo (Green, 1995) + , specifically the restriction introduced by + Barker & Link (2013) . By utilising + a 'universal parameter' space, RJMCMC is treated as a Gibbs sampling + problem. Previously-calculated posterior distributions are used to + quickly estimate posterior model probabilities. Jacobian matrices are + found using automatic differentiation. For a detailed description of + the package, see Gelling, Schofield & Barker (2019) + . + date_publication: '2019-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rjmcmc + url_git: '' +rjqpd: + version: 0.2.3 + title: The Johnson Quantile-Parameterised Distribution + maintainer: Bobby Ingram + description: |- + Implementation of the Johnson Quantile-Parameterised Distribution in R. + The Johnson Quantile-Parameterised Distribution (J-QPD) is a flexible distribution + system that is parameterised by a symmetric percentile triplet of quantile values + (typically the 10th-50th-90th) along with known support bounds for the distribution. + The J-QPD system was developed by Hadlock and Bickel (2017) . + This package implements the density, quantile, CDF and random number generator functions. + date_publication: '2020-09-25' + bug_reports: https://github.com/bobbyingram/rjqpd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjqpd + url_git: https://github.com/bobbyingram/rjqpd +RJSDMX: + version: 3.5-0 + title: R Interface to SDMX Web Services + maintainer: Attilio Mattiocco + description: |- + Provides functions to retrieve data and metadata from providers + that disseminate data by means of SDMX web services. + SDMX (Statistical Data and Metadata eXchange) is a standard that + has been developed with the aim of simplifying the exchange of + statistical information. + More about the SDMX standard and the SDMX Web Services + can be found at: . + date_publication: '2024-11-07' + bug_reports: https://github.com/amattioc/SDMX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RJSDMX + url_git: https://github.com/amattioc/SDMX/ +rjson: + version: 0.2.23 + title: JSON for R + maintainer: Alex Couture-Beil + description: Converts R object into JSON objects and vice-versa. + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rjson + url_git: https://github.com/alexcb/rjson +rjsoncons: + version: 1.3.1 + title: Query, Pivot, Patch, and Validate 'JSON' and 'NDJSON' + maintainer: Martin Morgan + description: |- + Functions to query (filter or transform), pivot (convert + from array-of-objects to object-of-arrays, for easy import as 'R' + data frame), search, patch (edit), and validate (against 'JSON Schema') + 'JSON' and 'NDJSON' strings, files, or URLs. Query and + pivot support 'JSONpointer', 'JSONpath' or 'JMESpath' + expressions. The implementation uses the 'jsoncons' + header-only library; + the library is easily linked to other packages for direct access + to 'C++' functionality not implemented here. + date_publication: '2024-07-07' + bug_reports: https://github.com/mtmorgan/rjsoncons/issues + url: https://mtmorgan.github.io/rjsoncons/ + url_cran: https://CRAN.R-project.org/package=rjsoncons + url_git: '' +RJSONIO: + version: 1.3-1.9 + title: Serialize R Objects to JSON, JavaScript Object Notation + maintainer: CRAN Team + description: |- + This is a package that allows conversion to and from + data in Javascript object notation (JSON) format. + This allows R objects to be inserted into Javascript/ECMAScript/ActionScript code + and allows R programmers to read and convert JSON content to R objects. + This is an alternative to rjson package. Originally, that was too slow for converting large R objects to JSON + and was not extensible. rjson's performance is now similar to this package, and perhaps slightly faster in some cases. + This package uses methods and is readily extensible by defining methods for different classes, + vectorized operations, and C code and callbacks to R functions for deserializing JSON objects to R. + The two packages intentionally share the same basic interface. This package (RJSONIO) has many additional + options to allow customizing the generation and processing of JSON content. + This package uses libjson rather than implementing yet another JSON parser. The aim is to support + other general projects by building on their work, providing feedback and benefit from their ongoing development. + date_publication: '2023-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RJSONIO + url_git: '' +RJSplot: + version: '2.7' + title: Interactive Graphs with R + maintainer: Carlos Prieto + description: Creates interactive graphs with 'R'. It joins the data analysis power + of R and the visualization libraries of JavaScript in one package. + date_publication: '2021-12-01' + bug_reports: '' + url: https://rjsplot.usal.es + url_cran: https://CRAN.R-project.org/package=RJSplot + url_git: '' +rjstat: + version: 0.4.3 + title: Handle 'JSON-stat' Format in R + maintainer: Aaron Schumacher + description: |- + Handle 'JSON-stat' format () in R. + Not all features are supported, especially the extensive metadata + features of 'JSON-stat'. + date_publication: '2023-09-05' + bug_reports: https://github.com/ajschumacher/rjstat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjstat + url_git: https://github.com/ajschumacher/rjstat +rjtools: + version: 1.0.18 + title: Preparing, Checking, and Submitting Articles to the 'R Journal' + maintainer: Di Cook + description: |- + Create an 'R Journal' 'Rmarkdown' template article, that will + generate html and pdf versions of your paper. Check that the paper folder + has all the required components needed for submission. + Examples of 'R Journal' publications can be found at + . + date_publication: '2025-01-23' + bug_reports: https://github.com/rjournal/rjtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjtools + url_git: https://github.com/rjournal/rjtools +rjwsacruncher: + version: 0.2.1 + title: Interface to the 'JWSACruncher' of 'JDemetra+' + maintainer: Alain Quartier-la-Tente + description: |- + 'JDemetra+' () is the seasonal adjustment software officially recommended + to the members of the European Statistical System and the European System of Central Banks. Seasonal adjustment models performed + with 'JDemetra+' can be stored into workspaces. 'JWSACruncher' () is a console tool that + re-estimates all the multi-processing defined in a workspace and to export the result. 'rjwsacruncher' allows to launch easily the 'JWSACruncher'. + date_publication: '2025-02-07' + bug_reports: https://github.com/AQLT/rjwsacruncher/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rjwsacruncher + url_git: https://github.com/AQLT/rjwsacruncher +rkafkajars: + version: '1.2' + title: External Jars Required for Package 'rkafka' + maintainer: Shruti Gupta + description: The 'rkafkajars' package collects all the external jars required for + the 'rkafka' package. + date_publication: '2021-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rkafkajars + url_git: '' +RKEA: + version: 0.0-6 + title: R/KEA Interface + maintainer: Kurt Hornik + description: |- + An R interface to KEA (Version 5.0). + KEA (for Keyphrase Extraction Algorithm) allows for extracting + keyphrases from text documents. It can be either used for free + indexing or for indexing with a controlled vocabulary. For more + information see . + date_publication: '2015-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKEA + url_git: '' +RKEAjars: + version: 5.0-4 + title: R/KEA Interface Jars + maintainer: Kurt Hornik + description: External jars required for package RKEA. + date_publication: '2019-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKEAjars + url_git: '' +RKEEL: + version: 1.3.4 + title: Using 'KEEL' in R Code + maintainer: Jose M. Moyano + description: |- + 'KEEL' is a popular 'Java' software for a large number of different knowledge data discovery tasks. + This package takes the advantages of 'KEEL' and R, allowing to use 'KEEL' algorithms in simple R code. + The implemented R code layer between R and 'KEEL' makes easy both using 'KEEL' algorithms in R as implementing new algorithms for 'RKEEL' in a very simple way. + It includes more than 100 algorithms for classification, regression, preprocess, association rules and imbalance learning, which allows a more complete experimentation process. + For more information about 'KEEL', see . + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKEEL + url_git: '' +RKEELdata: + version: 1.0.5 + title: Datasets from 'KEEL' for it Use in 'RKEEL' + maintainer: Jose M. Moyano + description: '''KEEL'' is a popular Java software for a large number of different + knowledge data discovery tasks. Furthermore, ''RKEEL'' is a package with a R code + layer between R and ''KEEL'', for using ''KEEL'' in R code. This package includes + the datasets from ''KEEL'' in .dat format for its use in ''RKEEL'' package. For + more information about ''KEEL'', see .' + date_publication: '2018-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKEELdata + url_git: '' +RKelly: + version: '1.0' + title: Translate Odds and Probabilities + maintainer: Arvid Kingl + description: |- + Calculates the Kelly criterion (Kelly, J.L. (1956) ) for bets given quoted prices, model predictions and commissions. + Additionally it contains helper functions to calculate the probabilities for wins and draws in multi-leg games. + date_publication: '2019-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKelly + url_git: '' +rKenyaForex: + version: 0.1.0 + title: Historical Data for Kenya Foreign Exchange Prices + maintainer: Mutua Kilai + description: Exchange rate for Kenya Shilling against other currencies, US DOLLAR, + EURO, STERLING POUND, Tanzania Shilling, Uganda Shilling. + date_publication: '2022-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rKenyaForex + url_git: '' +RKHSMetaMod: + version: '1.1' + title: |- + Ridge Group Sparse Optimization Problem for Estimation of a Meta + Model Based on Reproducing Kernel Hilbert Spaces + maintainer: Halaleh Kamari + description: Estimates the Hoeffding decomposition of an unknown function by solving + ridge group sparse optimization problem based on reproducing kernel Hilbert spaces, + and approximates its sensitivity indices (see Kamari, H., Huet, S. and Taupin, + M.-L. (2019) ). + date_publication: '2019-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKHSMetaMod + url_git: '' +rKIN: + version: 1.0.3 + title: (Kernel) Isotope Niche Estimation + maintainer: Shannon E Albeke + description: |- + Applies methods used to estimate animal homerange, but + instead of geospatial coordinates, we use isotopic coordinates. The estimation + methods include: 1) 2-dimensional bivariate normal kernel utilization density + estimator, 2) bivariate normal ellipse estimator, and 3) minimum convex polygon + estimator, all applied to stable isotope data. Additionally, functions to + determine niche area, polygon overlap between groups and levels (confidence + contours) and plotting capabilities. + date_publication: '2025-02-14' + bug_reports: https://github.com/salbeke/rKIN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rKIN + url_git: https://github.com/salbeke/rKIN +RkMetrics: + version: '1.3' + title: Hybrid Mortality Estimation + maintainer: Titus K Rotich + description: Hybrid Mortality Modelling (HMM) provides a framework in which mortality + around "the accident hump" and at very old ages can be modelled under a single + model. The graphics' codes necessary for visualization of the models' output are + included here. Specifically, the graphics are based on the assumption that, the + mortality rates can be expressed as a function of the area under the curve between + the crude mortality rates plots and the tangential transform of the force of mortality. + date_publication: '2017-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RkMetrics + url_git: '' +rKolada: + version: 0.2.3 + title: Access Data from the 'Kolada' Database + maintainer: Love Hansson + description: Methods for downloading and processing data and metadata from 'Kolada', + the official Swedish regions and municipalities database . + date_publication: '2024-05-14' + bug_reports: https://github.com/lchansson/rKolada/issues + url: https://lchansson.github.io/rKolada/ + url_cran: https://CRAN.R-project.org/package=rKolada + url_git: https://github.com/lchansson/rKolada +rKOMICS: + version: '1.3' + title: Minicircle Sequence Classes (MSC) Analyses + maintainer: Manon Geerts + description: 'This is a analysis toolkit to streamline the analyses of minicircle + sequence diversity in population-scale genome projects. rKOMICS is a user-friendly + R package that has simple installation requirements and that is applicable to + all 27 trypanosomatid genera. Once minicircle sequence alignments are generated, + rKOMICS allows to examine, summarize and visualize minicircle sequence diversity + within and between samples through the analyses of minicircle sequence clusters. + We showcase the functionalities of the (r)KOMICS tool suite using a whole-genome + sequencing dataset from a recently published study on the history of diversification + of the Leishmania braziliensis species complex in Peru. Analyses of population + diversity and structure highlighted differences in minicircle sequence richness + and composition between Leishmania subspecies, and between subpopulations within + subspecies. The rKOMICS package establishes a critical framework to manipulate, + explore and extract biologically relevant information from mitochondrial minicircle + assemblies in tens to hundreds of samples simultaneously and efficiently. This + should facilitate research that aims to develop new molecular markers for identifying + species-specific minicircles, or to study the ancestry of parasites for complementary + insights into their evolutionary history. ***** !! WARNING: this package relies + on dependencies from Bioconductor. For Mac users, this can generate errors when + installing rKOMICS. Install Bioconductor and ComplexHeatmap at advance: install.packages("BiocManager"); + BiocManager::install("ComplexHeatmap") *****.' + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rKOMICS + url_git: '' +RKorAPClient: + version: 1.0.0 + title: '''KorAP'' Web Service Client Package' + maintainer: Marc Kupietz + description: |- + A client package that makes the 'KorAP' web service API accessible from R. + The corpus analysis platform 'KorAP' has been developed as a scientific tool to make + potentially large, stratified and multiply annotated corpora, such as the 'German Reference Corpus DeReKo' + or the 'Corpus of the Contemporary Romanian Language CoRoLa', accessible for linguists to let them verify + hypotheses and to find interesting patterns in real language use. + The 'RKorAPClient' package provides access to 'KorAP' and the corpora behind it for user-created R code, + as a programmatic alternative to the 'KorAP' web user-interface. + You can learn more about 'KorAP' and use it directly on 'DeReKo' at . + date_publication: '2025-02-20' + bug_reports: https://github.com/KorAP/RKorAPClient/issues + url: https://korap.ids-mannheim.de/ + url_cran: https://CRAN.R-project.org/package=RKorAPClient + url_git: https://github.com/KorAP/RKorAPClient/ +rkriging: + version: 1.0.1 + title: Kriging Modeling + maintainer: Chaofan Huang + description: An 'Eigen'-based computationally efficient 'C++' implementation for + fitting various kriging models to data. This research is supported by U.S. National + Science Foundation grant DMS-2310637. + date_publication: '2024-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rkriging + url_git: '' +rkt: + version: '1.7' + title: Mann-Kendall Test, Seasonal and Regional Kendall Tests + maintainer: Aldo Marchetto + description: Contains function rkt which computes the Mann-Kendall test (MK) and + the Seasonal and the Regional Kendall Tests for trend (SKT and RKT) and Theil-Sen's + slope estimator. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rkt + url_git: '' +RKUM: + version: 0.1.1.1 + title: Robust Kernel Unsupervised Methods + maintainer: Md Ashad Alam + description: |- + Robust kernel center matrix, robust kernel cross-covariance operator for kernel unsupervised methods, kernel canonical correlation analysis, + influence function of identifying significant outliers or atypical objects from multimodal datasets. Alam, M. A, Fukumizu, K., Wang Y.-P. (2018) . + Alam, M. A, Calhoun, C. D., Wang Y.-P. (2018) . + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RKUM + url_git: '' +rkvo: + version: '0.1' + title: Read Key/Value Pair Observations + maintainer: Vehbi Sinan Tunalioglu + description: |- + This package provides functionality to read files + containing observations which consist of arbitrary key/value + pairs. + date_publication: '2014-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rkvo + url_git: '' +Rlab: + version: '4.0' + title: Functions and Datasets Required for ST370 Class + maintainer: Dennis Boos + description: Provides functions and datasets required for the ST 370 course at North + Carolina State University. + date_publication: '2022-05-04' + bug_reports: '' + url: https://www4.stat.ncsu.edu/~bmasmith/NewST370WEB/rlab/rlab.html + url_cran: https://CRAN.R-project.org/package=Rlab + url_git: '' +Rlabkey: + version: 3.4.1 + title: Data Exchange Between R and 'LabKey' Server + maintainer: Cory Nathe + description: |- + The 'LabKey' client library for R makes it easy for R users to + load live data from a 'LabKey' Server, , + into the R environment for analysis, provided users have permissions + to read the data. It also enables R users to insert, update, and + delete records stored on a 'LabKey' Server, provided they have appropriate + permissions to do so. + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rlabkey + url_git: '' +rLakeAnalyzer: + version: 1.11.4.1 + title: Lake Physics Tools + maintainer: Luke Winslow + description: |- + Standardized methods for calculating common important derived + physical features of lakes including water density based based on + temperature, thermal layers, thermocline depth, lake number, Wedderburn + number, Schmidt stability and others. + date_publication: '2019-06-09' + bug_reports: https://github.com/GLEON/rLakeAnalyzer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rLakeAnalyzer + url_git: '' +rlandfire: + version: 1.0.0 + title: Interface to 'LANDFIRE Product Service' API + maintainer: Mark Buckner + description: Provides access to a suite of geospatial data layers for wildfire management, + fuel modeling, ecology, natural resource management, climate, conservation, etc., + via the 'LANDFIRE' () Product Service ('LFPS') + API. + date_publication: '2024-03-15' + bug_reports: https://github.com/bcknr/rlandfire/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rlandfire + url_git: https://github.com/bcknr/rlandfire +rlang: + version: 1.1.5 + title: Functions for Base Types and Core R and 'Tidyverse' Features + maintainer: Lionel Henry + description: |- + A toolbox for working with base types, core R features + like the condition system, and core 'Tidyverse' features like tidy + evaluation. + date_publication: '2025-01-17' + bug_reports: https://github.com/r-lib/rlang/issues + url: https://rlang.r-lib.org + url_cran: https://CRAN.R-project.org/package=rlang + url_git: https://github.com/r-lib/rlang +rlas: + version: 1.8.0 + title: |- + Read and Write 'las' and 'laz' Binary File Formats Used for + Remote Sensing Data + maintainer: Jean-Romain Roussel + description: Read and write 'las' and 'laz' binary file formats. The LAS file format + is a public file format for the interchange of 3-dimensional point cloud data + between data users. The LAS specifications are approved by the American Society + for Photogrammetry and Remote Sensing . + The LAZ file format is an open and lossless compression scheme for binary LAS + format versions 1.0 to 1.4 . + date_publication: '2024-07-16' + bug_reports: https://github.com/r-lidar/rlas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rlas + url_git: https://github.com/r-lidar/rlas +rlc: + version: 0.5.0 + title: Create Interactive Linked Charts with Minimal Code + maintainer: Svetlana Ovchinnikova + description: |- + An easy-to-use tool to employ interactivity in every-day exploratory analysis. It contains + a collection of most commonly used types of charts (such as scatter plots, line plots, heatmaps, bar charts), + which can be linked to each other or to other interactive elements with just few lines of code. + date_publication: '2023-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rlc + url_git: '' +rlcv: + version: 1.0.0 + title: Robust Likelihood Cross Validation Bandwidth Selection + maintainer: Ximing Wu + description: Robust likelihood cross validation bandwidth for uni- and multi-variate + kernel densities. It is robust against fat-tailed distributions and/or outliers. + Based on "Robust Likelihood Cross-Validation for Kernel Density Estimation," Wu + (2019) . + date_publication: '2022-03-07' + bug_reports: '' + url: https://sites.google.com/tamu.edu/ximingwu/ + url_cran: https://CRAN.R-project.org/package=rlcv + url_git: '' +rLDCP: + version: 1.0.2 + title: Text Generation from Data + maintainer: Patricia Conde-Clemente + description: Linguistic Descriptions of Complex Phenomena (LDCP) is an architecture + and methodology that allows us to model complex phenomena, interpreting input + data, and generating automatic text reports customized to the user needs (see + and ). The proposed + package contains a set of methods that facilitates the development of LDCP systems. + It main goal is increasing the visibility and practical use of this research line. + date_publication: '2017-11-10' + bug_reports: '' + url: http://phedes.com/rLDCP + url_cran: https://CRAN.R-project.org/package=rLDCP + url_git: '' +rle: + version: 0.9.2 + title: Common Functions for Run-Length Encoded Vectors + maintainer: Pavel N. Krivitsky + description: Common 'base' and 'stats' methods for 'rle' objects, aiming to make + it possible to treat them transparently as vectors. + date_publication: '2020-09-25' + bug_reports: https://github.com/statnet/rle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rle + url_git: '' +RLeafAngle: + version: '1.0' + title: |- + Estimates, Plots and Evaluates Leaf Angle Distribution + Functions, Calculates Extinction Coefficients + maintainer: Wei-Min Wang + description: |- + Leaf angle distribution is described by a number of functions + (e.g. ellipsoidal, Beta and rotated ellipsoidal). The parameters of leaf angle + distributions functions are estimated through different empirical relationship. + This package includes estimations of parameters of different leaf angle + distribution function, plots and evaluates leaf angle distribution functions, + calculates extinction coefficients given leaf angle distribution. + Reference: Wang(2007). + date_publication: '2017-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RLeafAngle + url_git: '' +rleafmap: + version: 0.2.1 + title: Interactive Maps with R and Leaflet + maintainer: Francois Keck + description: |- + Display spatial data with interactive maps powered by the open- + source JavaScript library 'Leaflet' (see ). Maps can be + rendered in a web browser or displayed in the HTML viewer pane of 'RStudio'. + This package is designed to be easy to use and can create complex maps with + vector and raster data, web served map tiles and interface elements. + date_publication: '2023-10-20' + bug_reports: '' + url: http://www.francoiskeck.fr/rleafmap/ + url_cran: https://CRAN.R-project.org/package=rleafmap + url_git: https://github.com/fkeck/rleafmap +rlecuyer: + version: 0.3-8 + title: R Interface to RNG with Multiple Streams + maintainer: Hana Sevcikova + description: |- + Provides an interface to the C implementation of the + random number generator with multiple independent streams + developed by L'Ecuyer et al (2002). The main purpose of this + package is to enable the use of this random number generator in + parallel R applications. + date_publication: '2023-12-02' + bug_reports: '' + url: http://www.iro.umontreal.ca/~lecuyer/myftp/papers/streams00.pdf + url_cran: https://CRAN.R-project.org/package=rlecuyer + url_git: '' +rlemon: + version: 0.2.1 + title: R Access to LEMON Graph Algorithms + maintainer: Josh Errickson + description: |- + Allows easy access to the LEMON Graph Library set of algorithms, written in C++. + See the LEMON project page at . + Current LEMON version is 1.3.1. + date_publication: '2023-02-06' + bug_reports: https://github.com/josherrickson/rlemon/issues/ + url: https://errickson.net/rlemon/ + url_cran: https://CRAN.R-project.org/package=rlemon + url_git: '' +RLescalation: + version: 1.0.2 + title: Optimal Dose Escalation Using Deep Reinforcement Learning + maintainer: Kentaro Matsuura + description: |- + An implementation to compute an optimal dose escalation rule + using deep reinforcement learning in phase I oncology trials + (Matsuura et al. (2023) ). + The dose escalation rule can directly optimize the percentages of correct + selection (PCS) of the maximum tolerated dose (MTD). + date_publication: '2025-02-08' + bug_reports: https://github.com/MatsuuraKentaro/RLescalation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RLescalation + url_git: https://github.com/MatsuuraKentaro/RLescalation +rless: + version: 0.1.1 + title: Leaner Style Sheets + maintainer: Jonas Vaclavek + description: |- + Converts LESS to CSS. + It uses V8 engine, where LESS parser is run. Functions for + LESS text, file or folder conversion are provided. + This work was supported by a junior grant research project by + Czech Science Foundation 'GACR' no. 'GJ18-04150Y'. + date_publication: '2019-07-31' + bug_reports: https://github.com/ciirc-kso/rless/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rless + url_git: https://github.com/ciirc-kso/rless +rlfsm: + version: 1.1.2 + title: |- + Simulations and Statistical Inference for Linear Fractional + Stable Motions + maintainer: Dmitry Otryakhin + description: Contains functions for simulating the linear fractional stable motion + according to the algorithm developed by Mazur and Otryakhin + based on the method from Stoev and Taqqu (2004) , + as well as functions for estimation of parameters of these processes introduced + by Mazur, Otryakhin and Podolskij (2018) , and also different + related quantities. + date_publication: '2022-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rlfsm + url_git: https://gitlab.com/Dmitry_Otryakhin/Tools-for-parameter-estimation-of-the-linear-fractional-stable-motion +rLFT: + version: 1.0.1 + title: Processing Linear Features + maintainer: Shannon E Albeke + description: |- + Assists in the manipulation and processing of linear features with the help of the 'sf' package. + Makes use of linear referencing to extract data from most shape files. + Reference for this packages methods: Albeke, S.E. et al. (2010) . + date_publication: '2021-09-24' + bug_reports: https://gitlab.com/albekeecoinfolab/rlft/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rLFT + url_git: '' +Rlgt: + version: 0.2-2 + title: Bayesian Exponential Smoothing Models with Trend Modifications + maintainer: Christoph Bergmeir + description: |- + An implementation of a number of Global Trend models for time series forecasting + that are Bayesian generalizations and extensions of some Exponential Smoothing models. + The main differences/additions include 1) nonlinear global trend, 2) Student-t error + distribution, and 3) a function for the error size, so heteroscedasticity. The methods + are particularly useful for short time series. When tested on the well-known M3 dataset, + they are able to outperform all classical time series algorithms. The models are fitted + with MCMC using the 'rstan' package. + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rlgt + url_git: https://github.com/cbergmeir/Rlgt +Rlibeemd: + version: 1.4.3 + title: |- + Ensemble Empirical Mode Decomposition (EEMD) and Its Complete + Variant (CEEMDAN) + maintainer: Jouni Helske + description: |- + An R interface for libeemd (Luukko, Helske, Räsänen, 2016) , + a C library of highly efficient parallelizable functions for performing the ensemble empirical mode decomposition (EEMD), + its complete variant (CEEMDAN), the regular empirical mode decomposition (EMD), and bivariate EMD (BEMD). + Due to the possible portability issues CRAN version no longer supports OpenMP, you can install OpenMP-supported version + from GitHub: . + date_publication: '2023-09-05' + bug_reports: https://github.com/helske/Rlibeemd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rlibeemd + url_git: '' +Rlibkdv: + version: '1.1' + title: |- + A Versatile Kernel Density Visualization Library for Geospatial + Analytics (Heatmap) + maintainer: Bojian Zhu + description: |- + Unlock the power of large-scale geospatial analysis, + quickly generate high-resolution kernel density visualizations, + supporting advanced analysis tasks such as bandwidth-tuning and spatiotemporal analysis. + Regardless of the size of your dataset, our library delivers efficient and accurate results. + Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu, Reynold Cheng (2023) . + Tsz Nam Chan, Rui Zang, Pak Lon Ip, Leong Hou U, Jianliang Xu (2023) . + Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu (2022) . + Tsz Nam Chan, Pak Lon Ip, Kaiyan Zhao, Leong Hou U, Byron Choi, Jianliang Xu (2022) . + Tsz Nam Chan, Pak Lon Ip, Leong Hou U, Byron Choi, Jianliang Xu (2022) . + Tsz Nam Chan, Pak Lon Ip, Leong Hou U, Byron Choi, Jianliang Xu (2022) . + Tsz Nam Chan, Pak Lon Ip, Leong Hou U, Weng Hou Tong, Shivansh Mittal, Ye Li, Reynold Cheng (2021) . + Tsz Nam Chan, Zhe Li, Leong Hou U, Jianliang Xu, Reynold Cheng (2021) . + Tsz Nam Chan, Reynold Cheng, Man Lung Yiu (2020) . + Tsz Nam Chan, Leong Hou U, Reynold Cheng, Man Lung Yiu, Shivansh Mittal (2020) . + Tsz Nam Chan, Man Lung Yiu, Leong Hou U (2019) . + date_publication: '2023-10-21' + bug_reports: https://github.com/bojianzhu/Rlibkdv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rlibkdv + url_git: https://github.com/bojianzhu/Rlibkdv +rlibkriging: + version: 0.9-1 + title: Kriging Models using the 'libKriging' Library + maintainer: Yann Richet + description: |- + Interface to 'libKriging' 'C++' library that should + provide most standard Kriging / Gaussian process regression features + (like in 'DiceKriging', 'kergp' or 'RobustGaSP' packages). + 'libKriging' relies on Armadillo linear algebra library (Apache 2 license) by Conrad Sanderson, + 'lbfgsb_cpp' is a 'C++' port around by Pascal Have of 'lbfgsb' library (BSD-3 license) by + Ciyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales used for hyperparameters optimization. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rlibkriging + url_git: https://github.com/libKriging +rliger: + version: 2.1.0 + title: Linked Inference of Genomic Experimental Relationships + maintainer: Yichen Wang + description: Uses an extension of nonnegative matrix factorization to identify shared + and dataset-specific factors. See Welch J, Kozareva V, et al (2019) , + and Liu J, Gao C, Sodicoff J, et al (2020) for + more details. + date_publication: '2024-10-29' + bug_reports: https://github.com/welch-lab/liger/issues + url: https://welch-lab.github.io/liger/ + url_cran: https://CRAN.R-project.org/package=rliger + url_git: '' +Rlinkedin: + version: '0.2' + title: Access to the LinkedIn API via R + maintainer: Michael Piccirilli + description: |- + A series of functions that allow users + to access the 'LinkedIn' API to get information about connections, + search for people and jobs, share updates with their network, + and create group discussions. For more information about using + the API please visit . + date_publication: '2016-10-30' + bug_reports: https://github.com/mpiccirilli/Rlinkedin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rlinkedin + url_git: https://github.com/mpiccirilli/Rlinkedin +rlinkedinads: + version: 0.2.0 + title: Load Data from 'Linkedin Advertising API' + maintainer: Alexey Seleznev + description: |- + Get data from 'Linkedin Advertising API' . + You can load ad account hierarchy (accounts, users, campaign groups, campaigns and creatives) and + also you can load ad analytics data from your 'Linkedin' Ad account. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rlinkedinads + url_git: '' +Rlinsolve: + version: 0.3.2 + title: Iterative Solvers for (Sparse) Linear System of Equations + maintainer: Kisung You + description: |- + Solving a system of linear equations is one of the most fundamental + computational problems for many fields of mathematical studies, such as + regression problems from statistics or numerical partial differential equations. + We provide basic stationary iterative solvers such as Jacobi, Gauss-Seidel, + Successive Over-Relaxation and SSOR methods. Nonstationary, also known as + Krylov subspace methods are also provided. Sparse matrix computation is also supported + in that solving large and sparse linear systems can be manageable using 'Matrix' package + along with 'RcppArmadillo'. For a more detailed description, see a book by Saad (2003) + . + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rlinsolve + url_git: '' +rlist: + version: 0.4.6.2 + title: A Toolbox for Non-Tabular Data Manipulation + maintainer: Kun Ren + description: |- + Provides a set of functions for data manipulation with + list objects, including mapping, filtering, grouping, sorting, + updating, searching, and other useful functions. Most functions + are designed to be pipeline friendly so that data processing with + lists can be chained. + date_publication: '2021-09-03' + bug_reports: https://github.com/renkun-ken/rlist/issues + url: https://renkun-ken.github.io/rlist/ + url_cran: https://CRAN.R-project.org/package=rlist + url_git: https://github.com/renkun-ken/rlist +rlistings: + version: 0.2.10 + title: Clinical Trial Style Data Readout Listings + maintainer: Joe Zhu + description: |- + Listings are often part of the submission of clinical trial + data in regulatory settings. We provide a framework for the specific + formatting features often used when displaying large datasets in that + context. + date_publication: '2025-01-09' + bug_reports: https://github.com/insightsengineering/rlistings/issues + url: https://insightsengineering.github.io/rlistings/ + url_cran: https://CRAN.R-project.org/package=rlistings + url_git: https://github.com/insightsengineering/rlistings/ +rlmDataDriven: + version: 0.4.0 + title: Robust Regression with Data Driven Tuning Parameter + maintainer: You-Gan Wang + description: Data driven approach for robust regression estimation in homoscedastic + and heteroscedastic context. See Wang et al. (2007), + regarding homoscedastic framework. + date_publication: '2019-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rlmDataDriven + url_git: '' +rlme: + version: '0.5' + title: |- + Rank-Based Estimation and Prediction in Random Effects Nested + Models + maintainer: Yusuf Bilgic + description: |- + Estimates robust rank-based fixed effects and predicts robust + random effects in two- and three- level random effects nested models. + The methodology is described in Bilgic & Susmann (2013) . + date_publication: '2018-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rlme + url_git: '' +Rlof: + version: 1.1.3 + title: R Parallel Implementation of Local Outlier Factor(LOF) + maintainer: Yingsong Hu + description: 'R parallel implementation of Local Outlier Factor(LOF) which uses + multiple CPUs to significantly speed up the LOF computation for large datasets. + (Note: The overall performance depends on the computers especially the number + of the cores).It also supports multiple k values to be calculated in parallel, + as well as various distance measures in addition to the default Euclidean distance.' + date_publication: '2022-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rlof + url_git: '' +rlog: + version: 0.1.0 + title: A Simple, Opinionated Logging Utility + maintainer: Mark Sellors + description: |- + A very lightweight package that writes out log messages in an opinionated way. + Simpler and lighter than other logging packages, 'rlog' provides a compact feature set that + focuses on getting the job done in a Unix-like way. + date_publication: '2021-02-24' + bug_reports: https://github.com/sellorm/rlog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rlog + url_git: https://github.com/sellorm/rlog +RLogicalOps: + version: '0.1' + title: Process Logical Operations + maintainer: Sunny Kumar + description: |- + Processing logical operations such as AND/OR/NOT operations + dynamically. It also handles nesting in the operations. + date_publication: '2016-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RLogicalOps + url_git: '' +RLoptimal: + version: 1.2.1 + title: Optimal Adaptive Allocation Using Deep Reinforcement Learning + maintainer: Kentaro Matsuura + description: |- + An implementation to compute an optimal adaptive allocation rule + using deep reinforcement learning in a dose-response study + (Matsuura et al. (2022) ). + The adaptive allocation rule can directly optimize a performance metric, + such as power, accuracy of the estimated target dose, or mean absolute error + over the estimated dose-response curve. + date_publication: '2025-01-13' + bug_reports: https://github.com/MatsuuraKentaro/RLoptimal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RLoptimal + url_git: https://github.com/MatsuuraKentaro/RLoptimal +RLRsim: + version: 3.1-8 + title: |- + Exact (Restricted) Likelihood Ratio Tests for Mixed and Additive + Models + maintainer: Fabian Scheipl + description: |- + Rapid, simulation-based exact (restricted) likelihood ratio tests + for testing the presence of variance components/nonparametric terms for + models fit with nlme::lme(),lme4::lmer(), lmeTest::lmer(), gamm4::gamm4(), + mgcv::gamm() and SemiPar::spm(). + date_publication: '2022-03-16' + bug_reports: https://github.com/fabian-s/RLRsim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RLRsim + url_git: https://github.com/fabian-s/RLRsim +RLT: + version: 3.2.6 + title: Reinforcement Learning Trees + maintainer: Ruoqing Zhu + description: |- + Random forest with a variety of additional features for regression, classification and survival analysis. + The features include: parallel computing with OpenMP, embedded model for selecting the splitting variable, + based on Zhu, Zeng & Kosorok (2015) , subject weight, variable weight, + tracking subjects used in each tree, etc. + date_publication: '2023-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RLT + url_git: '' +rLTP: + version: 0.1.4 + title: R Interface to the 'LTP'-Cloud Service + maintainer: Tong He + description: |- + R interface to the 'LTP'-Cloud service for Natural Language Processing + in Chinese (http://www.ltp-cloud.com/). + date_publication: '2017-05-29' + bug_reports: https://github.com/hetong007/rLTP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rLTP + url_git: https://github.com/hetong007/rLTP +RLumCarlo: + version: 0.1.9 + title: Monte-Carlo Methods for Simulating Luminescence Phenomena + maintainer: Sebastian Kreutzer + description: |- + A collection of functions to simulate luminescence production in + dosimetric materials using Monte Carlo methods. Implemented are models for + delocalised transitions (e.g., Chen and McKeever (1997) ), + localised transitions (e.g., Pagonis et al. (2019) ) + and tunnelling transitions (Jain et al. (2012) + and Pagonis et al. (2019) ). + Supported stimulation methods are thermal luminescence (TL), + continuous-wave optically stimulated luminescence (CW-OSL), + linearly-modulated optically stimulated luminescence (LM-OSL), + linearly-modulated infrared stimulated luminescence (LM-IRSL), + and isothermal luminescence (ITL or ISO-TL). + date_publication: '2022-08-08' + bug_reports: https://github.com/R-Lum/RLumCarlo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RLumCarlo + url_git: '' +RLumModel: + version: 0.2.10 + title: |- + Solving Ordinary Differential Equations to Understand + Luminescence + maintainer: Johannes Friedrich + description: A collection of functions to simulate luminescence signals in quartz + and Al2O3 based on published models. + date_publication: '2022-02-22' + bug_reports: https://github.com/R-Lum/RLumModel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RLumModel + url_git: '' +RLumShiny: + version: 0.2.3 + title: '''Shiny'' Applications for the R Package ''Luminescence''' + maintainer: Christoph Burow + description: |- + A collection of 'shiny' applications for the R package + 'Luminescence'. These mainly, but not exclusively, include applications for + plotting chronometric data from e.g. luminescence or radiocarbon dating. It + further provides access to bootstraps tooltip and popover functionality and + contains the 'jscolor.js' library with a custom 'shiny' output binding. + date_publication: '2022-01-31' + bug_reports: https://github.com/tzerk/RLumShiny/issues + url: https://tzerk.github.io/RLumShiny/ + url_cran: https://CRAN.R-project.org/package=RLumShiny + url_git: '' +rly: + version: 1.7.4 + title: Tools to Create Formal Language Parser + maintainer: Marek Jagielski + description: R implementation of the common parsing tools 'lex' and 'yacc'. + date_publication: '2022-05-08' + bug_reports: https://github.com/systemincloud/rly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rly + url_git: https://github.com/systemincloud/rly +RM.weights: + version: '2.0' + title: |- + Weighted Rasch Modeling and Extensions using Conditional Maximum + Likelihood + maintainer: Sara Viviani + description: Rasch model and extensions for survey data, using Conditional Maximum + likelihood (CML). Carlo Cafiero, Sara Viviani, Mark Nord (2018) . + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RM.weights + url_git: '' +RM2006: + version: 0.1.1 + title: RiskMetrics 2006 Methodology + maintainer: Carlos Trucios + description: Estimation of the conditional covariance matrix using the RiskMetrics + 2006 methodology of Zumbach (2007) . + date_publication: '2020-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RM2006 + url_git: '' +rma.exact: + version: 0.1.0 + title: Exact Confidence Intervals for Random Effects Meta-Analyses + maintainer: Haben Michael + description: Compute an exact CI for the population mean under a random effects + model. The routines implement the algorithm described in Michael, Thronton, Xie, + and Tian (2017) . + date_publication: '2017-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rma.exact + url_git: '' +rmacrostrat: + version: 1.0.0 + title: Fetch Geologic Data from the 'Macrostrat' Platform + maintainer: Lewis A. Jones + description: |- + Work with the 'Macrostrat' () Web Service + (v.2, ) to fetch geological data relevant to + the spatial and temporal distribution of sedimentary, igneous, and + metamorphic rocks as well as data extracted from them. + date_publication: '2024-10-18' + bug_reports: https://github.com/palaeoverse/rmacrostrat/issues + url: https://rmacrostrat.palaeoverse.org + url_cran: https://CRAN.R-project.org/package=rmacrostrat + url_git: https://github.com/UW-Macrostrat/macrostrat/issues +RMaCzek: + version: 1.6.0 + title: Czekanowski's Diagrams + maintainer: Krzysztof Bartoszek + description: Allows for production of Czekanowski's Diagrams with clusters. See + K. Bartoszek, A. Vasterlund (2020) and K. Bartoszek, + Y. Luo (2023) . + date_publication: '2024-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMaCzek + url_git: '' +rmake: + version: 1.1.0 + title: Makefile Generator for R Analytical Projects + maintainer: Michal Burda + description: |- + Creates and maintains a build process for complex analytic tasks in R. + Package allows to easily generate Makefile for the (GNU) 'make' tool, which drives the build process + by (in parallel) executing build commands in order to update results accordingly to given dependencies + on changed data or updated source files. + date_publication: '2018-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmake + url_git: '' +RMallow: + version: '1.1' + title: Fit Multi-Modal Mallows' Models to Ranking Data + maintainer: Erik Gregory + description: |- + An EM algorithm to fit Mallows' Models to full or partial rankings, with or without ties. + Based on Adkins and Flinger (1998) . + date_publication: '2020-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMallow + url_git: '' +Rmalschains: + version: 0.2-10 + title: |- + Continuous Optimization using Memetic Algorithms with Local + Search Chains (MA-LS-Chains) + maintainer: Christoph Bergmeir + description: |- + An implementation of an algorithm family for continuous + optimization called memetic algorithms with local search chains + (MA-LS-Chains), as proposed in Molina et al. (2010) and Molina et al. (2011) . Rmalschains is further discussed in Bergmeir et al. (2016) . Memetic algorithms are hybridizations of genetic + algorithms with local search methods. They are especially suited + for continuous optimization. + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rmalschains + url_git: '' +rmapshaper: + version: 0.5.0 + title: Client for 'mapshaper' for 'Geospatial' Operations + maintainer: Andy Teucher + description: |- + Edit and simplify 'geojson', 'Spatial', and 'sf' + objects. This is wrapper around the 'mapshaper' 'JavaScript' library + by Matthew Bloch to perform + topologically-aware polygon simplification, as well as other + operations such as clipping, erasing, dissolving, and converting + 'multi-part' to 'single-part' geometries. + date_publication: '2023-04-11' + bug_reports: https://github.com/ateucher/rmapshaper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmapshaper + url_git: https://github.com/ateucher/rmapshaper +rmapzen: + version: 0.5.1 + title: Client for 'Mapzen' and Related Map APIs + maintainer: Tarak Shah + description: |- + Provides an interface to 'Mapzen'-based APIs (including + geocode.earth, Nextzen, and NYC GeoSearch) for geographic search + and geocoding, isochrone calculation, and vector data to draw map tiles. + See for more information. The original + Mapzen has gone out of business, but 'rmapzen' can be set up to work with + any provider who implements the Mapzen API. + date_publication: '2023-10-17' + bug_reports: https://github.com/tarakc02/rmapzen/issues + url: https://tarakc02.github.io/rmapzen/ + url_cran: https://CRAN.R-project.org/package=rmapzen + url_git: '' +rmarchingcubes: + version: 0.1.3 + title: Calculate 3D Contour Meshes Using the Marching Cubes Algorithm + maintainer: S. H. Wilks + description: |- + A port of the C++ routine for applying the marching cubes algorithm written by + Thomas Lewiner et al. (2012) into an R package. + The package supplies the contour3d() function, which takes a 3-dimensional array of voxel + data and calculates the vertices, vertex normals, and faces for a 3d mesh representing + the contour(s) at a given level. + date_publication: '2021-06-16' + bug_reports: https://github.com/shwilks/rmarchingcubes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmarchingcubes + url_git: https://github.com/shwilks/rmarchingcubes +rmargint: + version: 2.0.3 + title: Robust Marginal Integration Procedures + maintainer: Alejandra Martinez + description: |- + Three robust marginal integration procedures for additive models based on local + polynomial kernel smoothers. As a preliminary estimator of the multivariate + function for the marginal integration procedure, a first approach uses local + constant M-estimators, a second one uses local polynomials of order 1 over all the + components of covariates, and the third one uses M-estimators based on local + polynomials but only in the direction of interest. For this last approach, + estimators of the derivatives of the additive functions can be obtained. All three + procedures can compute predictions for points outside the training set if desired. + See Boente and Martinez (2017) for details. + date_publication: '2023-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmargint + url_git: '' +RMariaDB: + version: 1.3.4 + title: Database Interface and MariaDB Driver + maintainer: Kirill Müller + description: |- + Implements a DBI-compliant interface to MariaDB + () and MySQL () + databases. + date_publication: '2025-02-24' + bug_reports: https://github.com/r-dbi/RMariaDB/issues + url: https://rmariadb.r-dbi.org + url_cran: https://CRAN.R-project.org/package=RMariaDB + url_git: https://github.com/r-dbi/RMariaDB +RmarineHeatWaves: + version: 0.17.0 + title: Detect Marine Heat Waves and Marine Cold Spells + maintainer: Albertus J. Smit + description: |- + Given a time series of daily temperatures, the package provides tools + to detect extreme thermal events, including marine heat waves, and to + calculate the exceedances above or below specified threshold values. + It outputs the properties of all detected events and exceedances. + date_publication: '2018-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RmarineHeatWaves + url_git: https://github.com/ajsmit/RmarineHeatWaves +RMark: + version: 3.0.0 + title: R Code for Mark Analysis + maintainer: Jeff Laake + description: |- + An interface to the software package MARK that constructs input + files for MARK and extracts the output. MARK was developed by Gary White + and is freely available at + but is not open source. + date_publication: '2022-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMark + url_git: '' +rmarkdown: + version: '2.29' + title: Dynamic Documents for R + maintainer: Yihui Xie + description: Convert R Markdown documents into a variety of formats. + date_publication: '2024-11-04' + bug_reports: https://github.com/rstudio/rmarkdown/issues + url: https://pkgs.rstudio.com/rmarkdown/ + url_cran: https://CRAN.R-project.org/package=rmarkdown + url_git: https://github.com/rstudio/rmarkdown +rmass2: + version: 0.0.0.2 + title: |- + Repeated Measures with Attrition: Sample Sizes and Power Levels + for 2 Groups + maintainer: Soumya Sahu + description: 'For the calculation of sample size or power in a two-group repeated + measures design, accounting for attrition and accommodating a variety of correlation + structures for the repeated measures; details of the method can be found in the + scientific paper: Donald Hedeker, Robert D. Gibbons, Christine Waternaux (1999) + .' + date_publication: '2023-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmass2 + url_git: '' +RMAT: + version: 0.2.0 + title: Random Matrix Analysis Toolkit + maintainer: Ali Taqi + description: Simulate random matrices and ensembles and compute their eigenvalue + spectra and dispersions. + date_publication: '2021-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMAT + url_git: '' +rmatio: + version: 0.19.0 + title: Read and Write 'Matlab' Files + maintainer: Stefan Widgren + description: |- + Read and write 'Matlab' MAT files from R. The 'rmatio' + package supports reading MAT version 4, MAT version 5 and MAT + compressed version 5. The 'rmatio' package can write version 5 MAT + files and version 5 files with variable compression. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmatio + url_git: https://github.com/stewid/rmatio +RMAWGEN: + version: 1.3.7 + title: Multi-Site Auto-Regressive Weather GENerator + maintainer: Emanuele Cordano + description: |- + S3 and S4 functions are implemented for spatial multi-site + stochastic generation of daily time series of temperature and + precipitation. These tools make use of Vector AutoRegressive models (VARs). + The weather generator model is then saved as an object and is calibrated by + daily instrumental "Gaussianized" time series through the 'vars' package + tools. Once obtained this model, it can it can be used for weather + generations and be adapted to work with several climatic monthly time + series. + date_publication: '2019-12-12' + bug_reports: '' + url: https://docs.google.com/file/d/0B66otCUk3Bv6V3RPbm1mUG4zVHc/edit + url_cran: https://CRAN.R-project.org/package=RMAWGEN + url_git: https://github.com/ecor/RMAWGEN +rmBayes: + version: 0.1.16 + title: Performing Bayesian Inference for Repeated-Measures Designs + maintainer: Zhengxiao Wei + description: |- + A Bayesian credible interval is interpreted with respect to posterior probability, + and this interpretation is far more intuitive than that of a frequentist confidence interval. + However, standard highest-density intervals can be wide due to between-subjects variability and tends + to hide within-subject effects, rendering its relationship with the Bayes factor less clear + in within-subject (repeated-measures) designs. + This urgent issue can be addressed by using within-subject intervals in within-subject designs, + which integrate four methods including the Wei-Nathoo-Masson (2023) , + the Loftus-Masson (1994) , + the Nathoo-Kilshaw-Masson (2018) , + and the Heck (2019) interval estimates. + date_publication: '2024-02-19' + bug_reports: https://github.com/zhengxiaoUVic/rmBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmBayes + url_git: https://github.com/zhengxiaoUVic/rmBayes +RMBC: + version: 0.1.0 + title: Robust Model Based Clustering + maintainer: Juan Domingo Gonzalez + description: |- + A robust clustering algorithm (Model-Based) similar to Expectation + Maximization for finite mixture normal distributions is implemented, + its main advantage is that the estimator is resistant to outliers, + that means that results of parameter estimation are still correct when there + are atypical values in the sample + (see Gonzalez, Maronna, Yohai and Zamar (2021) + ). + date_publication: '2021-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMBC + url_git: '' +RMCC: + version: 0.1.1 + title: Airborne LiDAR Filtering Method Based on Multiscale Curvature + maintainer: Jean-Romain Roussel + description: |- + Multiscale Curvature Classification of ground returns in 3-D LiDAR + point clouds, designed for forested environments. 'RMCC' is a porting to R of the + 'MCC-lidar' method by Evans and Hudak (2007) . + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMCC + url_git: '' +rmcfs: + version: 1.3.6 + title: |- + The MCFS-ID Algorithm for Feature Selection and Interdependency + Discovery + maintainer: Michal Draminski + description: MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) + is a Monte Carlo method-based tool for feature selection. It also allows for the + discovery of interdependencies between the relevant features. MCFS-ID is particularly + suitable for the analysis of high-dimensional, 'small n large p' transactional + and biological data. M. Draminski, J. Koronacki (2018) . + date_publication: '2024-08-19' + bug_reports: '' + url: https://home.ipipan.waw.pl/m.draminski/mcfs.html + url_cran: https://CRAN.R-project.org/package=rmcfs + url_git: '' +rmcmc: + version: 0.1.1 + title: Robust Markov Chain Monte Carlo Methods + maintainer: Matthew M. Graham + description: |- + Functions for simulating Markov chains using the Barker proposal + to compute Markov chain Monte Carlo (MCMC) estimates of expectations with + respect to a target distribution on a real-valued vector space. The Barker + proposal, described in Livingstone and Zanella (2022) + , is a gradient-based MCMC algorithm inspired by the + Barker accept-reject rule. It combines the robustness of simpler MCMC + schemes, such as random-walk Metropolis, with the efficiency of + gradient-based methods, such as the Metropolis adjusted Langevin algorithm. + The key function provided by the package is sample_chain(), which allows + sampling a Markov chain with a specified target distribution as its + stationary distribution. The chain is sampled by generating proposals and + accepting or rejecting them using a Metropolis-Hasting acceptance rule. + During an initial warm-up stage, the parameters of the proposal distribution + can be adapted, with adapters available to both: tune the scale of the + proposals by coercing the average acceptance rate to a target value; tune + the shape of the proposals to match covariance estimates under the target + distribution. As well as the default Barker proposal, the package also + provides implementations of alternative proposal distributions, such as + (Gaussian) random walk and Langevin proposals. Optionally, if 'BridgeStan's + R interface , + available on GitHub , is installed, + then 'BridgeStan' can be used to specify the target distribution to sample + from. + date_publication: '2025-02-04' + bug_reports: https://github.com/UCL/rmcmc/issues + url: http://github-pages.ucl.ac.uk/rmcmc/ + url_cran: https://CRAN.R-project.org/package=rmcmc + url_git: https://github.com/UCL/rmcmc +rmcorr: + version: 0.7.0 + title: Repeated Measures Correlation + maintainer: Laura R. Marusich + description: |- + Compute the repeated measures correlation, a statistical technique + for determining the overall within-individual relationship among paired measures + assessed on two or more occasions, first introduced by Bland and Altman (1995). + Includes functions for diagnostics, p-value, effect size with confidence + interval including optional bootstrapping, as well as graphing. Also includes + several example datasets. For more details, see the web documentation + and the + original paper: Bakdash and Marusich (2017) . + date_publication: '2024-07-26' + bug_reports: https://github.com/lmarusich/rmcorr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmcorr + url_git: https://github.com/lmarusich/rmcorr +rmda: + version: '1.6' + title: Risk Model Decision Analysis + maintainer: Marshall Brown + description: Provides tools to evaluate the value of using a risk prediction instrument + to decide treatment or intervention (versus no treatment or intervention). Given + one or more risk prediction instruments (risk models) that estimate the probability + of a binary outcome, rmda provides functions to estimate and display decision + curves and other figures that help assess the population impact of using a risk + model for clinical decision making. Here, "population" refers to the relevant + patient population. Decision curves display estimates of the (standardized) net + benefit over a range of probability thresholds used to categorize observations + as 'high risk'. The curves help evaluate a treatment policy that recommends treatment + for patients who are estimated to be 'high risk' by comparing the population impact + of a risk-based policy to "treat all" and "treat none" intervention policies. Curves + can be estimated using data from a prospective cohort. In addition, rmda can + estimate decision curves using data from a case-control study if an estimate of + the population outcome prevalence is available. Version 1.4 of the package provides + an alternative framing of the decision problem for situations where treatment + is the standard-of-care and a risk model might be used to recommend that low-risk + patients (i.e., patients below some risk threshold) opt out of treatment. Confidence + intervals calculated using the bootstrap can be computed and displayed. A wrapper + function to calculate cross-validated curves using k-fold cross-validation is + also provided. + date_publication: '2018-07-17' + bug_reports: '' + url: http://mdbrown.github.io/rmda/ + url_cran: https://CRAN.R-project.org/package=rmda + url_git: https://github.com/mdbrown/rmda +RmdConcord: + version: '0.3' + title: Concordances for 'R Markdown' + maintainer: Duncan Murdoch + description: |- + Supports concordances in 'R Markdown' + documents. This currently allows the original source + location in the '.Rmd' file of errors detected by 'HTML tidy' + to be found more easily, and potentially allows forward + and reverse search in 'HTML' and 'LaTeX' documents + produced from 'R Markdown'. The 'LaTeX' support + has been included in the most recent development + version of the 'patchDVI' package. + date_publication: '2023-12-10' + bug_reports: https://github.com/dmurdoch/RmdConcord/issues + url: https://dmurdoch.github.io/RmdConcord/ + url_cran: https://CRAN.R-project.org/package=RmdConcord + url_git: https://github.com/dmurdoch/RmdConcord +rmdfiltr: + version: 0.1.5 + title: '''Lua''-Filters for R Markdown' + maintainer: Frederik Aust + description: |- + A collection of 'Lua' filters that extend the functionality + of R Markdown templates (e.g., count words or post-process citations). + date_publication: '2024-10-22' + bug_reports: https://github.com/crsh/rmdfiltr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmdfiltr + url_git: https://github.com/crsh/rmdfiltr +rmdformats: + version: 1.0.4 + title: HTML Output Formats and Templates for 'rmarkdown' Documents + maintainer: Julien Barnier + description: |- + HTML formats and templates for 'rmarkdown' documents, with some extra + features such as automatic table of contents, lightboxed figures, dynamic + crosstab helper. + date_publication: '2022-05-17' + bug_reports: https://github.com/juba/rmdformats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmdformats + url_git: https://github.com/juba/rmdformats +rmdHelpers: + version: 1.3.1 + title: Helper Functions for Rmd Documents + maintainer: Mark Peterson + description: A series of functions to aid in repeated tasks for Rmd documents. All + details are to my personal preference, though I am happy to add flexibility if + there are use cases I am missing. I will continue updating with new functions + as I add utility functions for myself. + date_publication: '2024-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmdHelpers + url_git: '' +rmdl: + version: 0.1.0 + title: Language to Manage Many Models + maintainer: Anish S. Shah + description: |- + A system for describing and manipulating the many models that are + generated in causal inference and data analysis projects, as based on the + causal theory and criteria of Austin Bradford Hill (1965) + . This system includes the addition of + formal attributes that modify base `R` objects, including terms and + formulas, with a focus on variable roles in the "do-calculus" of modeling, + as described in Pearl (2010) . For example, the + definition of exposure, outcome, and interaction are implicit in the roles + variables take in a formula. These premises allow for a more fluent modeling + approach focusing on variable relationships, and assessing effect + modification, as described by VanderWeele and Robins (2007) + . The essential goal is to help + contextualize formulas and models in causality-oriented workflows. + date_publication: '2024-05-02' + bug_reports: https://github.com/shah-in-boots/rmdl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmdl + url_git: https://github.com/shah-in-boots/rmdl +rmdpartials: + version: 0.5.8 + title: Partial 'rmarkdown' Documents to Prettify your Reports + maintainer: Ruben Arslan + description: |2- + + Use 'rmarkdown' partials, also know as child documents in + 'knitr', so you can make components for HTML, PDF, and Word documents. + The package provides various helper functions to make certain functions easier. + You may want to use this package, if you want to flexibly summarise objects + using a combination of figures, tables, text, and HTML widgets. + Unlike HTML widgets, the output is Markdown and can hence be turn into other + output formats than HTML. + date_publication: '2020-06-04' + bug_reports: https://github.com/rubenarslan/rmdpartials/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmdpartials + url_git: https://github.com/rubenarslan/rmdpartials +rmdplugr: + version: 0.4.1 + title: Plugins for R Markdown Formats + maintainer: Johan Larsson + description: |- + Formats for R Markdown that undo modifications by + 'pandoc' and 'rmarkdown' to original 'latex' templates, such as + smaller margins, paragraph spacing, and compact titles. In addition, + enhancements such as author blocks with affiliations and + headers and footers are introduced. All of this functionality is built + around plugins that modify the default 'pandoc' template without relying on + custom templates. + date_publication: '2020-01-09' + bug_reports: https://github.com/jolars/rmdplugr/issues + url: https://jolars.github.io/rmdplugr/ + url_cran: https://CRAN.R-project.org/package=rmdplugr + url_git: https://github.com/jolars/rmdplugr +rmdwc: + version: 0.3.0 + title: Count Words, Chars and Non-Whitespace Chars in R Markdown Docs + maintainer: Sigbert Klinke + description: If you are using R Markdown documents then you have sometimes restrictions + about the size of the documents, e.g. number of words, number of characters or + non-whitespace characters. rmdcount() computes these counts with and without code + chunks and returns the result as data frame. + date_publication: '2022-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmdwc + url_git: '' +rMEA: + version: 1.2.2 + title: Synchrony in Motion Energy Analysis (MEA) Time-Series + maintainer: Johann R. Kleinbub + description: 'A suite of tools useful to read, visualize and export bivariate motion + energy time-series. Lagged synchrony between subjects can be analyzed through + windowed cross-correlation. Surrogate data generation allows an estimation of + pseudosynchrony that helps to estimate the effect size of the observed synchronization. + Kleinbub, J. R., & Ramseyer, F. T. (2020). rMEA: An R package to assess nonverbal + synchronization in motion energy analysis time-series. Psychotherapy research, + 1-14. .' + date_publication: '2022-02-17' + bug_reports: https://github.com/kleinbub/rMEA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rMEA + url_git: https://github.com/kleinbub/rMEAhttps://psync.ch +RmecabKo: + version: 0.1.6.2 + title: An 'Rcpp' Interface for Eunjeon Project + maintainer: Junhewk Kim + description: |- + An 'Rcpp' interface for Eunjeon project . + The 'mecab-ko' and 'mecab-ko-dic' is based on a C++ library, + and part-of-speech tagging with them is useful when the spacing of source Korean text is not correct. + This package provides part-of-speech tagging and tokenization function for Korean text. + date_publication: '2018-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RmecabKo + url_git: '' +RMediation: + version: 1.2.2 + title: Mediation Analysis Confidence Intervals + maintainer: Davood Tofighi + description: |- + We provide functions to compute confidence intervals for a well-defined nonlinear function of the model parameters (e.g., product of k coefficients) in single--level and + multilevel structural equation models. It also computes a chi-square test statistic for a function of indirect effects. + 'Tofighi', D. and 'MacKinnon', D. P. (2011). 'RMediation' An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692--700. . + 'Tofighi', D. (2020). Bootstrap Model-Based Constrained Optimization Tests of Indirect Effects. Frontiers in Psychology, 10, 2989. . + date_publication: '2023-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMediation + url_git: '' +rmerec: + version: 0.1.1 + title: MEREC - Method Based on the Removal Effects of Criteria + maintainer: Lucas Sebastião de Paula + description: Implementation of the MEthod based on the Removal Effects of Criteria + - MEREC- a new objective weighting method for determining criteria weights for + Multiple Criteria Decision Making problems, created by Mehdi Keshavarz-Ghorabaee + (2021) . Given a decision matrix, the function return + the Merec´s weight vector and all intermediate matrix/vectors used to calculate + it. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmerec + url_git: https://github.com/lucassp/rmerec +rmeta: + version: '3.0' + title: Meta-Analysis + maintainer: Thomas Lumley + description: |- + Functions for simple fixed and random effects + meta-analysis for two-sample comparisons and cumulative + meta-analyses. Draws standard summary plots, funnel plots, and + computes summaries and tests for association and heterogeneity. + date_publication: '2018-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmeta + url_git: '' +rmetalog: + version: 1.0.3 + title: The Metalog Distribution + maintainer: Isaac Faber + description: |- + Implementation of the metalog distribution in R. + The metalog distribution is a modern, highly flexible, data-driven distribution. + Metalogs are developed by Keelin (2016) . + This package provides functions to build these distributions from raw data. + Resulting metalog objects are then useful for exploratory and probabilistic analysis. + date_publication: '2021-01-25' + bug_reports: https://github.com/isaacfab/rmetalog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmetalog + url_git: '' +rmfanova: + version: 0.1.0 + title: Repeated Measures Functional Analysis of Variance + maintainer: Lukasz Smaga + description: The provided package implements the statistical tests for the functional + repeated measures analysis problem (Kurylo and Smaga, 2023, ). + These procedures enable us to verify the overall hypothesis regarding equality, + as well as hypotheses for pairwise comparisons (i.e., post hoc analysis) of mean + functions corresponding to repeated experiments. + date_publication: '2023-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmfanova + url_git: '' +RMFM: + version: 1.1.0 + title: Robust Matrix Factor Model + maintainer: Wei Liu + description: We introduce a robust matrix factor model that explicitly incorporates + tail behavior and employs a mean-shift term to avoid efficiency losses through + pre-centering of observed matrices. More details on the methods related to our + paper are currently under submission. A full reference to the paper will be provided + in future versions once the paper is published. + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMFM + url_git: '' +rmgarch: + version: 1.3-9 + title: Multivariate GARCH Models + maintainer: Alexios Galanos + description: Feasible multivariate GARCH models including DCC, GO-GARCH and Copula-GARCH. + date_publication: '2022-02-05' + bug_reports: '' + url: http://www.unstarched.net + url_cran: https://CRAN.R-project.org/package=rmgarch + url_git: https://github.com/alexiosg/rmgarch +rMIDAS: + version: 1.0.0 + title: Multiple Imputation with Denoising Autoencoders + maintainer: Thomas Robinson + description: A tool for multiply imputing missing data using 'MIDAS', a deep learning + method based on denoising autoencoder neural networks (see Lall and Robinson, + 2022; ). This algorithm offers significant accuracy and + efficiency advantages over other multiple imputation strategies, particularly + when applied to large datasets with complex features. Alongside interfacing with + 'Python' to run the core algorithm, this package contains functions for processing + data before and after model training, running imputation model diagnostics, generating + multiple completed datasets, and estimating regression models on these datasets. + For more information see Lall and Robinson (2023) . + date_publication: '2023-10-11' + bug_reports: https://github.com/MIDASverse/rMIDAS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rMIDAS + url_git: https://github.com/MIDASverse/rMIDAS +rminer: + version: 1.4.8 + title: Data Mining Classification and Regression Methods + maintainer: Paulo Cortez + description: 'Facilitates the use of data mining algorithms in classification and + regression (including time series forecasting) tasks by presenting a short and + coherent set of functions. Versions: 1.4.8 improved help, several warning and + error code fixes (more stable version, all examples run correctly); 1.4.7 improved + Importance function and examples, minor error fixes; 1.4.6 / 1.4.5 / 1.4.4 new + automated machine learning (AutoML) and ensembles, via improved fit(), mining() + and mparheuristic() functions, and new categorical preprocessing, via improved + delevels() function; 1.4.3 new metrics (e.g., macro precision, explained variance), + new "lssvm" model and improved mparheuristic() function; 1.4.2 new "NMAE" metric, + "xgboost" and "cv.glmnet" models (16 classification and 18 regression models); + 1.4.1 new tutorial and more robust version; 1.4 - new classification and regression + models, with a total of 14 classification and 15 regression methods, including: + Decision Trees, Neural Networks, Support Vector Machines, Random Forests, Bagging + and Boosting; 1.3 and 1.3.1 - new classification and regression metrics; 1.2 - + new input importance methods via improved Importance() function; 1.0 - first version.' + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rminer + url_git: '' +rminizinc: + version: 0.0.8 + title: R Interface to 'MiniZinc' + maintainer: Akshit Achara + description: |- + Constraint optimization, or constraint programming, is the name given to identifying + feasible solutions out of a very large set of candidates, where the problem can be modeled in terms + of arbitrary constraints. 'MiniZinc' is a free and open-source constraint modeling language. + Constraint satisfaction and discrete optimization problems can be formulated in a high-level + modeling language. Models are compiled into an intermediate representation that is understood by a + wide range of solvers. 'MiniZinc' itself provides several solvers, for instance 'GeCode'. R users + can use the package to solve constraint programming problems without using 'MiniZinc' directly, + modify existing 'MiniZinc' models and also create their own models. + date_publication: '2021-10-15' + bug_reports: https://github.com/acharaakshit/RMiniZinc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rminizinc + url_git: https://github.com/acharaakshit/RMiniZinc +rminqa: + version: 0.2.2 + title: Derivative-Free Optimization in R using C++ + maintainer: Yi Pan + description: |- + Perform derivative-free optimization algorithms in R using C++. + A wrapper interface is provided to call C function of the 'bobyqa' implementation + (See ). + date_publication: '2023-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rminqa + url_git: '' +rmio: + version: 0.4.0 + title: Provides 'mio' C++11 Header Files + maintainer: Florian Privé + description: |- + Provides header files of 'mio', a cross-platform C++11 header-only + library for memory mapped file IO . + date_publication: '2022-02-17' + bug_reports: https://github.com/privefl/rmio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmio + url_git: https://github.com/privefl/rmio +Rmisc: + version: 1.5.1 + title: Ryan Miscellaneous + maintainer: Ryan M. Hope + description: |- + Contains many functions useful for data analysis + and utility operations. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rmisc + url_git: '' +Rmixmod: + version: 2.1.10 + title: Classification with Mixture Modelling + maintainer: Quentin Grimonprez + description: |- + Interface of 'MIXMOD' software for supervised, unsupervised and + semi-supervised classification with mixture modelling . + date_publication: '2023-12-13' + bug_reports: https://github.com/mixmod/mixmod/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rmixmod + url_git: '' +RMixpanel: + version: 0.7-1 + title: API for Mixpanel + maintainer: Meinhard Ploner + description: Provides an interface to many endpoints of Mixpanel's Data Export, + Engage and JQL API. The R functions allow for event and profile data export as + well as for segmentation, retention, funnel and addiction analysis. Results are + always parsed into convenient R objects. Furthermore it is possible to load and + update profiles. + date_publication: '2018-10-23' + bug_reports: '' + url: http://www.mixpanel.com + url_cran: https://CRAN.R-project.org/package=RMixpanel + url_git: https://github.com/ploner/RMixpanel +RMixtComp: + version: 4.1.4 + title: Mixture Models with Heterogeneous and (Partially) Missing Data + maintainer: Quentin Grimonprez + description: |- + Mixture Composer (Biernacki (2015) ) is a project to perform clustering using mixture models with + heterogeneous data and partially missing data. Mixture models are fitted using a SEM algorithm. + It includes 8 models for real, categorical, counting, functional and ranking data. + date_publication: '2023-06-18' + bug_reports: https://github.com/modal-inria/MixtComp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RMixtComp + url_git: https://github.com/modal-inria/MixtComp +RMixtCompIO: + version: 4.0.11 + title: |- + Minimal Interface of the C++ 'MixtComp' Library for Mixture + Models with Heterogeneous and (Partially) Missing Data + maintainer: Quentin Grimonprez + description: |- + Mixture Composer is a project to build mixture models with + heterogeneous data sets and partially missing data management. + It includes models for real, categorical, counting, functional and ranking data. + This package contains the minimal R interface of the C++ 'MixtComp' library. + date_publication: '2023-10-03' + bug_reports: https://github.com/modal-inria/MixtComp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RMixtCompIO + url_git: https://github.com/modal-inria/MixtComp +RMixtCompUtilities: + version: 4.1.6 + title: Utility Functions for 'MixtComp' Outputs + maintainer: Quentin Grimonprez + description: |- + Mixture Composer is a project to build mixture models with + heterogeneous data sets and partially missing data management. This package contains graphical, getter and some utility + functions to facilitate the analysis of 'MixtComp' output. + date_publication: '2023-09-22' + bug_reports: https://github.com/modal-inria/MixtComp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RMixtCompUtilities + url_git: https://github.com/modal-inria/MixtComp +RMKdiscrete: + version: '0.2' + title: Sundry Discrete Probability Distributions + maintainer: Robert M. Kirkpatrick + description: Sundry discrete probability distributions and helper functions. + date_publication: '2022-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMKdiscrete + url_git: '' +rmlnomogram: + version: 0.1.2 + title: Construct Explainable Nomogram for a Machine Learning Model + maintainer: Herdiantri Sufriyana + description: Construct an explainable nomogram for a machine learning (ML) model + to improve availability of an ML prediction model in addition to a computer application, + particularly in a situation where a computer, a mobile phone, an internet connection, + or the application accessibility are unreliable. This package enables a nomogram + creation for any ML prediction models, which is conventionally limited to only + a linear/logistic regression model. This nomogram may indicate the explainability + value per feature, e.g., the Shapley additive explanation value, for each individual. + However, this package only allows a nomogram creation for a model using categorical + without or with single numerical predictors. Detailed methodologies and examples + are documented in our vignette, available at . + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmlnomogram + url_git: '' +RMLPCA: + version: 0.0.1 + title: Maximum Likelihood Principal Component Analysis + maintainer: Renan Santos Barbosa + description: |- + R implementation of Maximum Likelihood Principal Component Analysis + The main idea of this package is to have an alternative way of PCA for + subspace modeling that considers measurement errors. + More details can be found in Peter D. Wentzell (2009) + . + date_publication: '2020-11-05' + bug_reports: https://github.com/renanestatcamp/RMLPCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RMLPCA + url_git: https://github.com/renanestatcamp/RMLPCA +RMM: + version: 0.1.0 + title: Revenue Management Modeling + maintainer: Chul Kim + description: The RMM fits Revenue Management Models using the RDE(Robust Demand + Estimation) method introduced in the paper by , one + of the customer choice-based Revenue Management Model. Furthermore, it is possible + to select a multinomial model as well as a conditional logit model as a model + of RDE. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMM + url_git: '' +RMOA: + version: 1.1.0 + title: Connect R with MOA for Massive Online Analysis + maintainer: Jan Wijffels + description: |- + Connect R with MOA (Massive Online Analysis - + ) to build classification models and + regression models on streaming data or out-of-RAM data. + Also streaming recommendation models are made available. + date_publication: '2022-07-17' + bug_reports: '' + url: http://www.bnosac.be + url_cran: https://CRAN.R-project.org/package=RMOA + url_git: https://github.com/jwijffels/RMOA +RMOAjars: + version: 1.2.0 + title: External jars Required for Package RMOA + maintainer: Jan Wijffels + description: |- + External jars required for package RMOA. RMOA is a framework to + build data stream models on top of MOA (Massive Online Analysis - + ). The jar files are put in this R package, the modelling logic can be found in the RMOA package. + date_publication: '2022-07-17' + bug_reports: '' + url: https://moa.cms.waikato.ac.nz/ + url_cran: https://CRAN.R-project.org/package=RMOAjars + url_git: https://github.com/jwijffels/RMOA +Rmodule: + version: '1.0' + title: |- + Automated Markov Chain Monte Carlo for Arbitrarily Structured + Correlation Matrices + maintainer: John Hughes + description: |- + Supports automated Markov chain Monte Carlo for arbitrarily structured correlation + matrices. The user supplies data, a correlation matrix in symbolic form, the current state + of the chain, a function that computes the log likelihood, and a list of prior distributions. + The package's flagship function then carries out a parameter-at-a-time update of all correlation + parameters, and returns the new state. The method is presented in Hughes (2023), in preparation. + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rmodule + url_git: '' +Rmolt: + version: 1.0.0 + title: Graphic Visualization of the Birds' Molt + maintainer: Martin Bozon + description: Graphical visualization of the birds' molt to facilitate the creation + of molting graph for passerines having 9 (Rmolt(data,9)) or 10 primaries (Rmolt(data,10)), + and also only for the 10 first primaries (Rmolt(data,"10_0")). + date_publication: '2022-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rmolt + url_git: '' +Rmonize: + version: 1.1.0 + title: Support Retrospective Harmonization of Data + maintainer: Guillaume Fabre + description: |- + Functions to support rigorous retrospective data harmonization + processing, evaluation, and documentation across datasets from different + studies based on Maelstrom Research guidelines. The package includes the + core functions to evaluate and format the main inputs that define the + harmonization process, apply specified processing rules to generate + harmonized data, diagnose processing errors, and summarize and evaluate + harmonized outputs. The main inputs that define the processing are a + DataSchema (list and definitions of harmonized variables to be generated) + and Data Processing Elements (processing rules to be applied to generate + harmonized variables from study-specific variables). The main outputs of + processing are harmonized datasets, associated metadata, and tabular and + visual summary reports. As described in + Maelstrom Research guidelines for rigorous retrospective data + harmonization (Fortier I and al. (2017) ). + date_publication: '2024-05-01' + bug_reports: https://github.com/maelstrom-research/Rmonize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rmonize + url_git: https://github.com/maelstrom-research/Rmonize/ +rmonocypher: + version: 0.1.8 + title: Easy Encryption of R Objects using Strong Modern Cryptography + maintainer: Mike Cheng + description: |- + Encrypt R objects to a raw vector or file using modern cryptographic + techniques. Password-based key derivation is with 'Argon2' (). + Objects are serialized and then encrypted using 'XChaCha20-Poly1305' () + which follows RFC 8439 for authenticated encryption (). + Cryptographic functions are provided by the included 'monocypher' 'C' library (). + date_publication: '2025-01-31' + bug_reports: https://github.com/coolbutuseless/rmonocypher/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmonocypher + url_git: https://github.com/coolbutuseless/rmonocypher +rmoo: + version: 0.2.0 + title: Multi-Objective Optimization in R + maintainer: Francisco Benitez + description: |- + The 'rmoo' package is a framework for multi- and many-objective + optimization, which allows researchers and users versatility + in parameter configuration, as well as tools for analysis, replication + and visualization of results. The 'rmoo' package was built as a fork of + the 'GA' package by Luca Scrucca(2017) and + implementing the Non-Dominated Sorting Genetic Algorithms proposed + by K. Deb's. + date_publication: '2022-09-24' + bug_reports: https://github.com/Evolutionary-Optimization-Laboratory/rmoo/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=rmoo + url_git: https://github.com/Evolutionary-Optimization-Laboratory/rmoo/ +RMOPI: + version: '1.1' + title: Risk Management and Optimization for Portfolio Investment + maintainer: Wei Ling + description: Provides functions for risk management and portfolio investment of + securities with practical tools for data processing and plotting. Moreover, it + contains functions which perform the COS Method, an option pricing method based + on the Fourier-cosine series (Fang, F. (2008) ). + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMOPI + url_git: '' +Rmosek: + version: 1.3.5 + title: The R to MOSEK Optimization Interface + maintainer: Henrik A. Friberg + description: |- + This is a meta-package designed to support the + installation of Rmosek (>= 6.0) and bring the optimization + facilities of MOSEK (>= 6.0) to the R-language. The interface + supports large-scale optimization of many kinds: Mixed-integer + and continuous linear, second-order cone, exponential cone and + power cone optimization, as well as continuous semidefinite + optimization. Rmosek and the R-language are open-source + projects. MOSEK is a proprietary product, but unrestricted + trial and academic licenses are available. + date_publication: '2019-08-01' + bug_reports: '' + url: http://www.mosek.com/ + url_cran: https://CRAN.R-project.org/package=Rmosek + url_git: '' +rMOST: + version: 1.0.1 + title: Estimates Pareto-Optimal Solution for Hiring with 3 Objectives + maintainer: Chelsea Song + description: |- + Estimates Pareto-optimal solution for personnel selection + with 3 objectives using Normal Boundary Intersection (NBI) algorithm + introduced by Das and Dennis (1998) . + Takes predictor intercorrelations and predictor-objective relations as + input and generates a series of solutions containing predictor weights + as output. Accepts between 3 and 10 selection predictors. Maximum 2 + objectives could be adverse impact objectives. Partially modeled after + De Corte (2006) TROFSS Fortran program + and updated from + 'ParetoR' package described in Song et al. (2017) + . For details, see Study 3 of Zhang et al. (2023). + date_publication: '2023-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rMOST + url_git: '' +rmp: + version: '2.2' + title: Rounded Mixture Package + maintainer: Antonio Canale + description: Performs univariate probability mass function estimation via Bayesian + nonparametric mixtures of rounded kernels as in Canale and Dunson (2011) . + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmp + url_git: '' +Rmpfr: + version: 1.0-0 + title: Interface R to MPFR - Multiple Precision Floating-Point Reliable + maintainer: Martin Maechler + description: |- + Arithmetic (via S4 classes and methods) for + arbitrary precision floating point numbers, including transcendental + ("special") functions. To this end, the package interfaces to + the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library + which itself is based on the 'GMP' (GNU Multiple Precision) Library. + date_publication: '2024-11-18' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=386 + url: '' + url_cran: https://CRAN.R-project.org/package=Rmpfr + url_git: https://rmpfr.r-forge.r-project.org/ +Rmpi: + version: 0.7-3.3 + title: Interface (Wrapper) to MPI (Message-Passing Interface) + maintainer: Hao Yu + description: |- + An interface (wrapper) to MPI. It also + provides interactive R manager and worker environment. + date_publication: '2025-01-13' + bug_reports: '' + url: https://fisher.stats.uwo.ca/faculty/yu/Rmpi/ + url_cran: https://CRAN.R-project.org/package=Rmpi + url_git: '' +RMPSH: + version: 1.1.1 + title: Recursive Modified Pattern Search on Hyper-Rectangle + maintainer: Priyam Das + description: 'Optimization of any Black-Box/Non-Convex Function on Hyper-Rectangular + Parameter Space. It uses a Variation of Pattern Search Technique. Described in + the paper : Das (2016) .' + date_publication: '2020-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMPSH + url_git: '' +rmpw: + version: 0.0.5 + title: Causal Mediation Analysis Using Weighting Approach + maintainer: Xu Qin + description: We implement causal mediation analysis using the methods proposed by + Hong (2010) and Hong, Deutsch & Hill (2015) . It + allows the estimation and hypothesis testing of causal mediation effects through + ratio of mediator probability weights (RMPW). This strategy conveniently relaxes + the assumption of no treatment-by-mediator interaction while greatly simplifying + the outcome model specification without invoking strong distributional assumptions. + We also implement a sensitivity analysis by extending the RMPW method to assess + potential bias in the presence of omitted pretreatment or posttreatment covariates. + The sensitivity analysis strategy was proposed by Hong, Qin, and Yang (2018) . + date_publication: '2024-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmpw + url_git: '' +rMR: + version: 1.1.0 + title: |- + Importing Data from Loligo Systems Software, Calculating + Metabolic Rates and Critical Tensions + maintainer: Tyler L. Moulton + description: Analysis of oxygen consumption data generated by Loligo (R) Systems + respirometry equipment. The package includes a function for loading data output + by Loligo's 'AutoResp' software (get.witrox.data()), functions for calculating + metabolic rates over user-specified time intervals, extracting critical points + from data using broken stick regressions based on Yeager and Ultsch (), + and easy functions for converting between different units of barometric pressure. + date_publication: '2018-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rMR + url_git: '' +rms: + version: 7.0-0 + title: Regression Modeling Strategies + maintainer: Frank E Harrell Jr + description: "Regression modeling, testing, estimation, validation,\ngraphics, prediction, + and typesetting by storing enhanced model design\nattributes in the fit. 'rms' + is a collection of functions that\nassist with and streamline modeling. It also + contains functions for\nbinary and ordinal logistic regression models, ordinal + models for\ncontinuous Y with a variety of distribution families, and the Buckley-James\nmultiple + regression model for right-censored responses, and implements\npenalized maximum + likelihood estimation for logistic and ordinary\nlinear models. 'rms' works with + almost any regression model, but it\nwas especially written to work with binary + or ordinal regression\nmodels, Cox regression, accelerated failure time models,\nordinary + linear models,\tthe Buckley-James model, generalized least\nsquares for serially + or spatially correlated observations, generalized\nlinear models, and quantile + regression." + date_publication: '2025-01-17' + bug_reports: '' + url: https://hbiostat.org/R/rms/ + url_cran: https://CRAN.R-project.org/package=rms + url_git: https://github.com/harrelfe/rms +rmsb: + version: 1.1-1 + title: Bayesian Regression Modeling Strategies + maintainer: Frank Harrell + description: A Bayesian companion to the 'rms' package, 'rmsb' provides Bayesian + model fitting, post-fit estimation, and graphics. It implements Bayesian regression + models whose fit objects can be processed by 'rms' functions such as 'contrast()', + 'summary()', 'Predict()', 'nomogram()', and 'latex()'. The fitting function currently + implemented in the package is 'blrm()' for Bayesian logistic binary and ordinal + regression with optional clustering, censoring, and departures from the proportional + odds assumption using the partial proportional odds model of Peterson and Harrell + (1990) . + date_publication: '2024-07-08' + bug_reports: '' + url: https://hbiostat.org/R/rmsb/ + url_cran: https://CRAN.R-project.org/package=rmsb + url_git: '' +RMSD: + version: 0.1.0 + title: Refined Modified Stahel-Donoho Estimators for Outlier Detection + maintainer: Kazumi Wada + description: |2- + + A function for multivariate outlier detection named Modified Stahel-Donoho (MSD) estimators is contained. The function is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. + The function is called the single core version in Wada & Tsubaki (2013) and evaluated with other methods in Wada, Kawano & Tsubaki (2020) . + date_publication: '2023-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMSD + url_git: '' +RMSDp: + version: 0.1.1 + title: |- + Refined Modified Stahel-Donoho (MSD) Estimators for Outlier + Detection (Parallel Version) + maintainer: Kazumi Wada + description: A parallel function for multivariate outlier detection named modified + Stahel-Donoho estimators is contained in this package. The function RMSDp() is + for elliptically distributed datasets and recognizes outliers based on Mahalanobis + distance. This function is for higher dimensional datasets that cannot be handled + by a single core function RMSD() included in 'RMSD' package. See Wada and Tsubaki + (2013) for the detail of the algorithm. + date_publication: '2024-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMSDp + url_git: '' +rmsfact: + version: 0.0.3 + title: Amazing Random Facts About the World's Greatest Hacker + maintainer: Dirk Eddelbuettel + description: |- + Display a randomly selected quote about Richard M. Stallman + based on the collection in the 'GNU Octave' function 'fact()' which was + aggregated by Jordi Gutiérrez Hermoso based on the (now defunct) site + stallmanfacts.com (which is accessible only via ). + date_publication: '2016-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmsfact + url_git: '' +rmsfuns: + version: 1.0.0.1 + title: |- + Quickly View Data Frames in 'Excel', Build Folder Paths and + Create Date Vectors + maintainer: Nico Katzke + description: |- + Contains several useful navigation helper functions, including easily building + folder paths, quick viewing dataframes in 'Excel', creating date vectors and changing the + console prompt to reflect time. + date_publication: '2020-05-05' + bug_reports: https://github.com/nicktz/rmsfuns/issues + url: https://rmsfuns.nfkatzke.com + url_cran: https://CRAN.R-project.org/package=rmsfuns + url_git: '' +RMSNumpress: + version: 1.0.1 + title: '''Rcpp'' Bindings to Native C++ Implementation of MS Numpress' + maintainer: Justin Sing + description: '''Rcpp'' bindings to the native C++ implementation of MS Numpress, + that provides two compression schemes for numeric data from mass spectrometers. + The library provides implementations of 3 different algorithms, 1 designed to + compress first order smooth data like retention time or M/Z arrays, and 2 for + compressing non smooth data with lower requirements on precision like ion count + arrays. Refer to the publication (Teleman et al., (2014) ) + for more details.' + date_publication: '2021-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMSNumpress + url_git: '' +RMSS: + version: 1.1.2 + title: Robust Multi-Model Subset Selection + maintainer: Anthony Christidis + description: |- + Efficient algorithms for generating ensembles of robust, sparse and diverse models via robust + multi-model subset selection (RMSS). The robust ensembles are generated by minimizing the sum of + the least trimmed square loss of the models in the ensembles under constraints for the size of + the models and the sharing of the predictors. Tuning parameters for the robustness, sparsity and + diversity of the robust ensemble are selected by cross-validation. + date_publication: '2024-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMSS + url_git: '' +Rmst: + version: 0.0.3 + title: Computerized Adaptive Multistage Testing + maintainer: Xiao Luo + description: |- + Assemble the panels of computerized adaptive multistage testing by the + bottom-up and the top-down approach, and simulate the administration of the assembled + panels. The full documentation and tutorials are at . + Reference: Luo and Kim (2018) . + date_publication: '2019-11-12' + bug_reports: https://github.com/xluo11/Rmst/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rmst + url_git: https://github.com/xluo11/Rmst +rmstBayespara: + version: 0.1.0 + title: Bayesian Restricted Mean Survival Time for Cluster Effect + maintainer: Keisuke Hanada + description: |- + The parametric Bayes analysis for the + restricted mean survival time (RMST) with cluster effect, + as described in Hanada and Kojima (2024) . + Bayes estimation with random-effect and frailty-effect can be applied to + several parametric models useful in survival time analysis. + The RMST under these parametric models can be computed from + the obtained posterior samples. + date_publication: '2024-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmstBayespara + url_git: '' +rmstcompsens: + version: 0.1.5 + title: Comparing Restricted Mean Survival Time as Sensitivity Analysis + maintainer: Kentaro Ueno + description: 'Performs two-sample comparisons using the restricted mean survival + time (RMST) when survival curves end at different time points between groups. + This package implements a sensitivity approach that allows the threshold timepoint + tau to be specified after the longest survival time in the shorter survival group. + Two kinds of between-group contrast estimators (the difference in RMST and the + ratio of RMST) are computed: Uno et al(2014), Uno + et al(2022), Ueno and Morita(2023).' + date_publication: '2023-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rmstcompsens + url_git: '' +rmt: + version: '1.0' + title: Restricted Mean Time in Favor of Treatment + maintainer: Lu Mao + description: Contains inferential and graphical routines for comparing two treatment + arms in terms of the restricted mean time in favor of treatment. + date_publication: '2021-05-25' + bug_reports: '' + url: https://sites.google.com/view/lmaowisc/ + url_cran: https://CRAN.R-project.org/package=rmt + url_git: '' +RMT4DS: + version: 0.0.1 + title: Computation of Random Matrix Models + maintainer: Xiucai Ding + description: We generate random variables following general Marchenko-Pastur distribution + and Tracy-Widom distribution. We compute limits and distributions of eigenvalues + and generalized components of spiked covariance matrices. We give estimation of + all population eigenvalues of spiked covariance matrix model. We give tests of + population covariance matrix. We also perform matrix denoising for signal-plus-noise + model. + date_publication: '2022-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMT4DS + url_git: '' +RMThreshold: + version: '1.1' + title: |- + Signal-Noise Separation in Random Matrices by using Eigenvalue + Spectrum Analysis + maintainer: Uwe Menzel + description: An algorithm which can be used to determine an objective threshold + for signal-noise separation in large random matrices (correlation matrices, mutual + information matrices, network adjacency matrices) is provided. The package makes + use of the results of Random Matrix Theory (RMT). The algorithm increments a suppositional + threshold monotonically, thereby recording the eigenvalue spacing distribution + of the matrix. According to RMT, that distribution undergoes a characteristic + change when the threshold properly separates signal from noise. By using the algorithm, + the modular structure of a matrix - or of the corresponding network - can be unraveled. + date_publication: '2016-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMThreshold + url_git: '' +RMTL: + version: 0.9.9 + title: Regularized Multi-Task Learning + maintainer: Han Cao + description: Efficient solvers for 10 regularized multi-task learning algorithms + applicable for regression, classification, joint feature selection, task clustering, + low-rank learning, sparse learning and network incorporation. Based on the accelerated + gradient descent method, the algorithms feature a state-of-art computational complexity + O(1/k^2). Sparse model structure is induced by the solving the proximal operator. + The detail of the package is described in the paper of Han Cao and Emanuel Schwarz + (2018) . + date_publication: '2022-05-02' + bug_reports: https://github.com/transbioZI/RMTL/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=RMTL + url_git: https://github.com/transbioZI/RMTL/ +RMTstat: + version: 0.3.1 + title: |- + Distributions, Statistics and Tests Derived from Random Matrix + Theory + maintainer: Evan Biederstedt + description: |2- + + Functions for working with the Tracy-Widom laws and other distributions + related to the eigenvalues of large Wishart matrices. + The tables for computing the Tracy-Widom densities and distribution + functions were computed by functions were computed by Momar Dieng's MATLAB package "RMLab". This package is part of a collaboration between Iain Johnstone, Zongming Ma, Patrick Perry, and Morteza Shahram. + date_publication: '2022-04-12' + bug_reports: https://github.com/evanbiederstedt/RMTstat + url: '' + url_cran: https://CRAN.R-project.org/package=RMTstat + url_git: https://github.com/evanbiederstedt/RMTstat +rMultiNet: + version: '0.1' + title: Multi-Layer Networks Analysis + maintainer: Chenyu Ren + description: Provides two general frameworks to generate a multi-layer network. + This also provides several methods to reveal the embedding of both nodes and layers. + The reference paper can be found from the URL mentioned below. Ting Li, Zhongyuan + Lyu, Chenyu Ren, Dong Xia (2023) . + date_publication: '2023-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rMultiNet + url_git: '' +rmumps: + version: 5.2.1-30 + title: Wrapper for MUMPS Library + maintainer: Serguei Sokol + description: |- + Some basic features of 'MUMPS' (Multifrontal Massively Parallel + sparse direct Solver) are wrapped in a class whose methods can be used + for sequentially solving a sparse linear system (symmetric or not) + with one or many right hand sides (dense or sparse). + There is a possibility to do separately symbolic analysis, + LU (or LDL^t) factorization and system solving. + Third part ordering libraries are included and can be used: 'PORD', 'METIS', 'SCOTCH'. + 'MUMPS' method was first described in Amestoy et al. (2001) + and Amestoy et al. (2006) . + date_publication: '2024-06-14' + bug_reports: https://github.com/sgsokol/rmumps/issues + url: http://www.mumps-solver.org/ + url_cran: https://CRAN.R-project.org/package=rmumps + url_git: https://github.com/sgsokol/rmumps/ +rmutil: + version: 1.1.10 + title: |- + Utilities for Nonlinear Regression and Repeated Measurements + Models + maintainer: Bruce Swihart + description: |- + A toolkit of functions for nonlinear regression and repeated + measurements not to be used by itself but called by other Lindsey packages such + as 'gnlm', 'stable', 'growth', 'repeated', and 'event' + (available at ). + date_publication: '2022-10-27' + bug_reports: https://github.com/swihart/rmutil/issues + url: https://www.commanster.eu/rcode.html + url_cran: https://CRAN.R-project.org/package=rmutil + url_git: '' +RMVL: + version: 1.1.0.1 + title: Mappable Vector Library for Handling Large Datasets + maintainer: Vladimir Dergachev + description: Mappable vector library provides convenient way to access large datasets. + Use all of your data at once, with few limits. Memory mapped data can be shared + between multiple R processes. Access speed depends on storage medium, so solid + state drive is recommended, preferably with PCI Express (or M.2 nvme) interface + or a fast network file system. The data is memory mapped into R and then accessed + using usual R list and array subscription operators. Convenience functions are + provided for merging, grouping and indexing large vectors and data.frames. The + layout of underlying MVL files is optimized for large datasets. The vectors are + stored to guarantee alignment for vector intrinsics after memory map. The package + is built on top of libMVL, which can be used as a standalone C library. libMVL + has simple C API making it easy to interchange datasets with outside programs. + Large MVL datasets are distributed via Academic Torrents . + date_publication: '2024-09-14' + bug_reports: '' + url: https://academictorrents.com/collection/mvl-datasets + url_cran: https://CRAN.R-project.org/package=RMVL + url_git: https://github.com/volodya31415/RMVL +rMVP: + version: 1.4.0 + title: |- + Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS + Tool + maintainer: Xiaolei Liu + description: |- + A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can + (1) effectively process large data, + (2) rapidly evaluate population structure, + (3) efficiently estimate variance components several algorithms, + (4) implement parallel-accelerated association tests of markers three methods, + (5) globally efficient design on GWAS process computing, + (6) enhance visualization of related information. + 'rMVP' contains three models GLM (Alkes Price (2006) ), MLM (Jianming Yu (2006) ) + and FarmCPU (Xiaolei Liu (2016) ); variance components estimation methods EMMAX + (Hyunmin Kang (2008) ;), FaSTLMM (method: Christoph Lippert (2011) , + R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) and + 'SUPER': Qishan Wang and Feng Tian (2014) ), and HE regression + (Xiang Zhou (2017) ). + date_publication: '2025-01-22' + bug_reports: https://github.com/xiaolei-lab/rMVP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rMVP + url_git: https://github.com/xiaolei-lab/rMVP +rmweather: + version: 0.2.62 + title: |- + Tools to Conduct Meteorological Normalisation and Counterfactual + Modelling for Air Quality Data + maintainer: Stuart K. Grange + description: |- + An integrated set of tools to allow data users to conduct + meteorological normalisation and counterfactual modelling for air quality + data. The meteorological normalisation technique uses predictive random + forest models to remove variation of pollutant concentrations so trends and + interventions can be explored in a robust way. For examples, see + Grange et al. (2018) and + Grange and Carslaw (2019) . The random + forest models can also be used for counterfactual or business as usual (BAU) + modelling by using the models to predict, from the model's perspective, the + future. For an example, see Grange et al. (2021) . + date_publication: '2025-02-21' + bug_reports: https://github.com/skgrange/rmweather/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmweather + url_git: https://github.com/skgrange/rmweather +RMX: + version: 0.1-6 + title: Rasch Models -- eXtensions + maintainer: Rainer W. Alexandrowicz + description: |- + Extend Rasch and Item Response Theory (IRT) analyses by providing + tools for post-processing the output from five major IRT packages + (i.e., 'eRm', 'psychotools', 'ltm', 'mirt', and 'TAM'). + The current version provides the plotPIccc() function, which + extracts from the return object of the originating package all + information required to draw an extended Person-Item-Map (PIccc), + showing any combination of + * category characteristic curves (CCCs), + * threshold characteristic curves (TCCs), + * item characteristic curves (ICCs), + * category information functions (CIFs), + * item information functions (IIFs), + * test information function (TIF), and the + * standard error curve (S.E.). + for uni- and multidimensional models (as far as supported by each + package). It allows for selecting dimensions, items, and categories + to plot and offers numerous options to adapt the output. The return + object contains all calculated values for further processing. + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RMX + url_git: '' +RMySQL: + version: 0.11.0 + title: Database Interface and 'MySQL' Driver for R + maintainer: Jeroen Ooms + description: |- + Legacy 'DBI' interface to 'MySQL' / 'MariaDB' based on old code + ported from S-PLUS. A modern 'MySQL' client written in 'C++' is available + from the 'RMariaDB' package. + date_publication: '2025-02-08' + bug_reports: https://github.com/r-dbi/rmysql/issues + url: https://r-dbi.r-universe.dev/RMySQLhttps://downloads.mariadb.org/connector-c/ + url_cran: https://CRAN.R-project.org/package=RMySQL + url_git: '' +rmytarget: + version: 2.4.0 + title: Load Data from 'MyTarget API v2 and v3' + maintainer: Alexey Seleznev + description: |- + Allows work with 'MyTarget Statistics API v2' + and + 'MyTarget Statistics API v3' + load data by ads, campaigns, agency clients and statistic from + your ads account. + date_publication: '2021-10-20' + bug_reports: '' + url: https://selesnow.github.io/rmytarget/ + url_cran: https://CRAN.R-project.org/package=rmytarget + url_git: '' +rmzqc: + version: 0.5.4 + title: Creation, Reading and Validation of 'mzqc' Files + maintainer: Chris Bielow + description: |- + Reads, writes and validates 'mzQC' files. The 'mzQC' format is a + standardized file format for the exchange, transmission, and archiving of + quality metrics derived from biological mass spectrometry data, as defined + by the HUPO-PSI (Human Proteome Organisation - Proteomics Standards Initiative) + Quality Control working group. + See for details. + date_publication: '2024-04-16' + bug_reports: https://github.com/MS-Quality-hub/rmzqc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rmzqc + url_git: https://github.com/MS-Quality-hub/rmzqc +rnaCrosslinkOO: + version: 0.1.4 + title: Analysis of RNA Crosslinking Data + maintainer: Jonathan Price + description: Analysis of RNA crosslinking data for RNA structure prediction. The + package is suitable for the analysis of RNA structure cross-linking data and chemical + probing data. + date_publication: '2024-07-10' + bug_reports: https://github.com/JLP-BioInf/rnaCrosslinkOO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rnaCrosslinkOO + url_git: '' +rnames: + version: 1.0.1 + title: Recursive Display of Items in Nested Lists + maintainer: Diego Ciccia + description: Recursive display of names and paths of all the items nested within + sublists of a list object. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rnames + url_git: '' +RNAmf: + version: 1.0.0 + title: Recursive Non-Additive Emulator for Multi-Fidelity Data + maintainer: Junoh Heo + description: Performs RNA emulation and active learning proposed by Heo and Sung + (2024) for multi-fidelity computer experiments. + The RNA emulator is particularly useful when the simulations with different fidelity + level are nonlinearly correlated. The hyperparameters in the model are estimated + by maximum likelihood estimation. + date_publication: '2024-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNAmf + url_git: '' +Rnanoflann: + version: 0.0.3 + title: Extremely Fast Nearest Neighbor Search + maintainer: Manos Papadakis + description: Finds the k nearest neighbours for every point in a given dataset using + Jose Luis' 'nanoflann' library. There is support for exact searches, fixed radius + searches with 'kd' trees and two distances, the 'Euclidean' and 'Manhattan'. For + more information see . Also, the 'nanoflann' + library is exported and ready to be used via the linking to mechanism. + date_publication: '2024-05-17' + bug_reports: https://github.com/ManosPapadakis95/Rnanoflann/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rnanoflann + url_git: https://github.com/ManosPapadakis95/Rnanoflann +RNAseqNet: + version: 0.1.5 + title: |- + Log-Linear Poisson Graphical Model with Hot-Deck Multiple + Imputation + maintainer: Nathalie Vialaneix + description: |- + Infer log-linear Poisson Graphical Model with an auxiliary data + set. Hot-deck multiple imputation method is used to improve the reliability + of the inference with an auxiliary dataset. Standard log-linear Poisson + graphical model can also be used for the inference and the Stability + Approach for Regularization Selection (StARS) is implemented to drive the + selection of the regularization parameter. The method is fully described in + . + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNAseqNet + url_git: '' +RNAseqQC: + version: 0.2.1 + title: Quality Control for RNA-Seq Data + maintainer: Frederik Ziebell + description: Functions for semi-automated quality control of bulk RNA-seq data. + date_publication: '2024-07-15' + bug_reports: https://github.com/frederikziebell/RNAseqQC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RNAseqQC + url_git: https://github.com/frederikziebell/RNAseqQC +rnassqs: + version: 0.6.3 + title: Access Data from the NASS 'Quick Stats' API + maintainer: Nicholas Potter + description: |- + Interface to access data via the United States Department of + Agriculture's National Agricultural Statistical Service (NASS) 'Quick Stats' + web API . Convenience functions + facilitate building queries based on available parameters and valid parameter + values. This product uses the NASS API but is not endorsed or certified by NASS. + date_publication: '2024-08-30' + bug_reports: https://github.com/ropensci/rnassqs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rnassqs + url_git: https://docs.ropensci.org/rnassqs/(website)https://github.com/ropensci/rnassqs/ +rnaturalearth: + version: 1.0.1 + title: World Map Data from Natural Earth + maintainer: Philippe Massicotte + description: Facilitates mapping by making natural earth map data from + more easily available to R users. + date_publication: '2023-12-15' + bug_reports: https://github.com/ropensci/rnaturalearth/issues + url: https://docs.ropensci.org/rnaturalearth/ + url_cran: https://CRAN.R-project.org/package=rnaturalearth + url_git: https://github.com/ropensci/rnaturalearth +rnaturalearthdata: + version: 1.0.0 + title: World Vector Map Data from Natural Earth Used in 'rnaturalearth' + maintainer: Philippe Massicotte + description: Vector map data from . Access functions + are provided in the accompanying package 'rnaturalearth'. + date_publication: '2024-02-09' + bug_reports: https://github.com/ropensci/rnaturalearthdata/issues + url: https://docs.ropensci.org/rnaturalearthdata/ + url_cran: https://CRAN.R-project.org/package=rnaturalearthdata + url_git: https://github.com/ropensci/rnaturalearthdata +RnavGraphImageData: + version: 0.0.4 + title: Image Data Used in the Loon Package Demos + maintainer: Adrian Waddell + description: Image data used as examples in the loon R package. + date_publication: '2018-05-15' + bug_reports: '' + url: http://waddella.github.io/loon/ + url_cran: https://CRAN.R-project.org/package=RnavGraphImageData + url_git: '' +rnbp: + version: 0.2.1 + title: Wrapper for the National Bank of Poland API + maintainer: Ryszard Szymanski + description: |- + Use the API through R. Retrieve + currency exchange rates and gold prices data published by the + National Bank of Poland in form of convenient R objects. + date_publication: '2021-06-07' + bug_reports: https://github.com/szymanskir/rnbp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rnbp + url_git: '' +RNCBIEUtilsLibs: + version: '0.9' + title: EUtils libraries for use in the R environment. + maintainer: Martin Schumann + description: |- + Provides the libraries of the EUtils operations for the + RNCBI package. + date_publication: '2010-06-25' + bug_reports: '' + url: https://code.google.com/p/rncbi/ + url_cran: https://CRAN.R-project.org/package=RNCBIEUtilsLibs + url_git: '' +RNCEP: + version: 1.0.11 + title: Obtain, Organize, and Visualize NCEP Weather Data + maintainer: Michael U. Kemp + description: Contains functions to retrieve, organize, and visualize weather data + from the NCEP/NCAR Reanalysis () + and NCEP/DOE Reanalysis II () + datasets. Data are queried via the Internet and may be obtained for a specified + spatial and temporal extent or interpolated to a point in space and time. We + also provide functions to visualize these weather data on a map. There are also + functions to simulate flight trajectories according to specified behavior using + either NCEP wind data or data specified by the user. + date_publication: '2025-01-23' + bug_reports: '' + url: https://psl.noaa.gov/data/gridded/index.htmlhttps://sites.google.com/site/michaelukemp/home + url_cran: https://CRAN.R-project.org/package=RNCEP + url_git: '' +rncl: + version: 0.8.7 + title: An Interface to the Nexus Class Library + maintainer: Francois Michonneau + description: |- + An interface to the Nexus Class Library which allows parsing + of NEXUS, Newick and other phylogenetic tree file formats. It provides + elements of the file that can be used to build phylogenetic objects + such as ape's 'phylo' or phylobase's 'phylo4(d)'. This functionality + is demonstrated with 'read_newick_phylo()' and 'read_nexus_phylo()'. + date_publication: '2023-01-08' + bug_reports: https://github.com/fmichonneau/rncl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rncl + url_git: https://github.com/fmichonneau/rncl +RND: + version: '1.2' + title: Risk Neutral Density Extraction Package + maintainer: Kam Hamidieh + description: Extract the implied risk neutral density from options using various + methods. + date_publication: '2017-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RND + url_git: '' +rNeighborGWAS: + version: 1.2.4 + title: Testing Neighbor Effects in Marker-Based Regressions + maintainer: Yasuhiro Sato + description: To incorporate neighbor genotypic identity into genome-wide association + studies, the package provides a set of functions for variation partitioning and + association mapping. The theoretical background of the method is described in + Sato et al. (2021) . + date_publication: '2021-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rNeighborGWAS + url_git: '' +rNeighborQTL: + version: 1.1.2 + title: |- + Interval Mapping for Quantitative Trait Loci Underlying Neighbor + Effects + maintainer: Yasuhiro Sato + description: To enable quantitative trait loci mapping of neighbor effects, this + package extends a single-marker regression to interval mapping. The theoretical + background of the method is described in Sato et al. (2021) . + date_publication: '2021-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rNeighborQTL + url_git: '' +RNentropy: + version: 1.2.3 + title: |- + Entropy Based Method for the Detection of Significant Variation + in Gene Expression Data + maintainer: Federico Zambelli + description: |- + An implementation of a method based on information theory devised + for the identification of genes showing a significant variation of expression + across multiple conditions. Given expression estimates from any number of + RNA-Seq samples and conditions it identifies genes or transcripts with a + significant variation of expression across all the conditions studied, + together with the samples in which they are over- or under-expressed. + Zambelli et al. (2018) . + date_publication: '2022-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNentropy + url_git: '' +rneos: + version: 0.4-0 + title: XML-RPC Interface to NEOS + maintainer: Bernhard Pfaff + description: Within this package the XML-RPC API to NEOS + is implemented. This enables the user to pass optimization problems to NEOS and + retrieve results within R. + date_publication: '2020-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rneos + url_git: '' +Rnest: + version: '1.0' + title: Next Eigenvalue Sufficiency Test + maintainer: P.-O. Caron + description: Determine the number of dimensions to retain in exploratory factor + analysis. The main function, nest(), returns the solution and the plot(nest()) + returns a plot. + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rnest + url_git: '' +rnetcarto: + version: 0.2.6 + title: |- + Fast Network Modularity and Roles Computation by Simulated + Annealing (Rgraph C Library Wrapper for R) + maintainer: Daniel B. Stouffer + description: Provides functions to compute the modularity and modularity-related + roles in networks. It is a wrapper around the rgraph library (Guimera & Amaral, + 2005, ). + date_publication: '2023-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rnetcarto + url_git: '' +RNetCDF: + version: 2.9-2 + title: Interface to 'NetCDF' Datasets + maintainer: Milton Woods + description: |- + An interface to the 'NetCDF' file formats designed by Unidata + for efficient storage of array-oriented scientific data and descriptions. + Most capabilities of 'NetCDF' version 4 are supported. Optional conversions + of time units are enabled by 'UDUNITS' version 2, also from Unidata. + date_publication: '2024-03-25' + bug_reports: https://github.com/mjwoods/RNetCDF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RNetCDF + url_git: https://github.com/mjwoods/RNetCDFhttps://www.unidata.ucar.edu/software/netcdf/https://www.unidata.ucar.edu/software/udunits/ +RNetLogo: + version: 1.0-4 + title: |- + Provides an Interface to the Agent-Based Modelling Platform + 'NetLogo' + maintainer: Jan C. Thiele + description: Interface to use and access Wilensky's 'NetLogo' (Wilensky 1999) from + R using either headless (no GUI) or interactive GUI mode. Provides functions to + load models, execute commands, and get values from reporters. Mostly analogous + to the 'NetLogo' 'Mathematica' Link . + date_publication: '2017-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNetLogo + url_git: http://rnetlogo.r-forge.r-project.org/ +RNewsflow: + version: 1.2.8 + title: Tools for Comparing Text Messages Across Time and Media + maintainer: Kasper Welbers + description: |- + A collection of tools for measuring the similarity of text messages and tracing the flow of messages over + time and across media. + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNewsflow + url_git: '' +RNeXML: + version: 2.4.11 + title: Semantically Rich I/O for the 'NeXML' Format + maintainer: Carl Boettiger + description: |- + Provides access to phyloinformatic data in 'NeXML' format. The + package should add new functionality to R such as the possibility to + manipulate 'NeXML' objects in more various and refined way and compatibility + with 'ape' objects. + date_publication: '2023-02-01' + bug_reports: https://github.com/ropensci/RNeXML/issues + url: https://docs.ropensci.org/RNeXML/ + url_cran: https://CRAN.R-project.org/package=RNeXML + url_git: https://github.com/ropensci/RNeXML +RNGforGPD: + version: 1.1.0 + title: Random Number Generation for Generalized Poisson Distribution + maintainer: Ruizhe Chen + description: |- + Generation of univariate and multivariate data that follow the generalized + Poisson distribution. The details of the univariate part are explained in + Demirtas (2017) , and the multivariate part is + an extension of the correlated Poisson data generation routine that was introduced in + Yahav and Shmueli (2012) . + date_publication: '2020-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNGforGPD + url_git: '' +rngtools: + version: 1.5.2 + title: Utility Functions for Working with Random Number Generators + maintainer: Renaud Gaujoux + description: |- + Provides a set of functions for working with + Random Number Generators (RNGs). In particular, a generic + S4 framework is defined for getting/setting the current RNG, or RNG data + that are embedded into objects for reproducibility. + Notably, convenient default methods greatly facilitate the way current + RNG settings can be changed. + date_publication: '2021-09-20' + bug_reports: https://github.com/renozao/rngtools/issues + url: https://renozao.github.io/rngtools/ + url_cran: https://CRAN.R-project.org/package=rngtools + url_git: '' +rngWELL: + version: 0.10-10 + title: Toolbox for WELL Random Number Generators + maintainer: Christophe Dutang + description: |- + It is a dedicated package to WELL pseudo random generators, + which were introduced in Panneton et al. (2006), ``Improved Long-Period + Generators Based on Linear Recurrences Modulo 2'', see . + But this package is not intended to be used directly, you are strongly __encouraged__ + to use the 'randtoolbox' package, which depends on this package. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rngWELL + url_git: '' +RNHANES: + version: 1.1.0 + title: Facilitates Analysis of CDC NHANES Data + maintainer: Herb Susmann + description: |- + Tools for downloading and analyzing CDC NHANES data, with a focus + on analytical laboratory data. + date_publication: '2016-11-29' + bug_reports: https://github.com/silentspringinstitute/RNHANES/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RNHANES + url_git: http://github.com/silentspringinstitute/RNHANES +RNifti: + version: 1.8.0 + title: Fast R and C++ Access to NIfTI Images + maintainer: Jon Clayden + description: |- + Provides very fast read and write access to images stored in the + NIfTI-1, NIfTI-2 and ANALYZE-7.5 formats, with seamless synchronisation + of in-memory image objects between compiled C and interpreted R code. Also + provides a simple image viewer, and a C/C++ API that can be used by other + packages. Not to be confused with 'RNiftyReg', which performs image + registration and applies spatial transformations. + date_publication: '2025-02-22' + bug_reports: https://github.com/jonclayden/RNifti/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RNifti + url_git: https://github.com/jonclayden/RNifti +RNiftyReg: + version: 2.8.4 + title: Image Registration Using the 'NiftyReg' Library + maintainer: Jon Clayden + description: |- + Provides an 'R' interface to the 'NiftyReg' image registration tools + . Linear and nonlinear registration + are supported, in two and three dimensions. + date_publication: '2024-09-30' + bug_reports: https://github.com/jonclayden/RNiftyReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RNiftyReg + url_git: https://github.com/jonclayden/RNiftyReg +Rnightly: + version: 0.1.0 + title: A Wrapper of the 'JavaScript' Library 'Nightly' + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to implement a dark/light toggle mode in 'shiny' using the 'Nightly' 'JavaScript' library. + The default mode is dark/light however the user can also specify other colours. + date_publication: '2020-06-25' + bug_reports: https://github.com/feddelegrand7/Rnightly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rnightly + url_git: https://github.com/feddelegrand7/Rnightly +rnmamod: + version: 0.4.0 + title: Bayesian Network Meta-Analysis with Missing Participants + maintainer: Loukia Spineli + description: |- + A comprehensive suite of functions to perform and visualise + pairwise and network meta-analysis with aggregate binary or continuous + missing participant outcome data. The package covers core Bayesian one-stage + models implemented in a systematic review with multiple interventions, + including fixed-effect and random-effects network meta-analysis, + meta-regression, evaluation of the consistency assumption via the + node-splitting approach and the unrelated mean effects model, and + sensitivity analysis. Missing participant outcome data are addressed in all + models of the package. The robustness to primary analysis results can + also be investigated using a novel intuitive index. Methods to evaluate the + transitivity assumption quantitatively are provided. The package also offers + a rich, user-friendly visualisation toolkit that aids in appraising and + interpreting the results thoroughly and preparing the manuscript for journal + submission. The visualisation tools comprise the network plot, forest plots, + panel of diagnostic plots, heatmaps on the extent of missing participant + outcome data in the network, league heatmaps on estimation and prediction, + rankograms, Bland-Altman plot, leverage plot, deviance scatterplot, heatmap + of robustness, barplot of Kullback-Leibler divergence, heatmap of comparison + dissimilarities and dendrogram of comparison clustering. The package also + allows the user to export the results to an Excel file at the working + directory. + date_publication: '2024-03-24' + bug_reports: https://github.com/LoukiaSpin/rnmamod/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rnmamod + url_git: https://github.com/LoukiaSpin/rnmamod +Rnmr1D: + version: 1.3.2 + title: |- + Perform the Complete Processing of a Set of Proton Nuclear + Magnetic Resonance Spectra + maintainer: Daniel Jacob + description: Perform the complete processing of a set of proton nuclear magnetic + resonance spectra from the free induction decay (raw data) and based on a processing + sequence (macro-command file). An additional file specifies all the spectra to + be considered by associating their sample code as well as the levels of experimental + factors to which they belong. More detail can be found in Jacob et al. (2017) + . + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rnmr1D + url_git: https://github.com/INRA/Rnmr1D +rnn: + version: 1.9.0 + title: Recurrent Neural Network + maintainer: Bastiaan Quast + description: Implementation of a Recurrent Neural Network architectures in native + R, including Long Short-Term Memory (Hochreiter and Schmidhuber, ), + Gated Recurrent Unit (Chung et al., ) and vanilla RNN. + date_publication: '2023-04-22' + bug_reports: https://github.com/bquast/rnn/issues + url: https://qua.st/rnn/ + url_cran: https://CRAN.R-project.org/package=rnn + url_git: https://github.com/bquast/rnn +rnndescent: + version: 0.1.6 + title: |- + Nearest Neighbor Descent Method for Approximate Nearest + Neighbors + maintainer: James Melville + description: |- + The Nearest Neighbor Descent method for finding approximate + nearest neighbors by Dong and co-workers (2010) + . Based on the 'Python' package + 'PyNNDescent' . + date_publication: '2024-05-14' + bug_reports: https://github.com/jlmelville/rnndescent/issues + url: https://jlmelville.github.io/rnndescent/ + url_cran: https://CRAN.R-project.org/package=rnndescent + url_git: https://github.com/jlmelville/rnndescent +rnnmf: + version: 0.3.0 + title: Regularized Non-Negative Matrix Factorization + maintainer: Steven E. Pav + description: |- + A proof of concept implementation of regularized non-negative matrix factorization optimization. + A non-negative matrix factorization factors non-negative matrix Y approximately as L R, for non-negative + matrices L and R of reduced rank. This package supports such factorizations with weighted objective and + regularization penalties. Allowable regularization penalties include L1 and L2 penalties on L and R, + as well as non-orthogonality penalties. This package provides multiplicative update algorithms, which are + a modification of the algorithm of Lee and Seung (2001) + , as well + as an additive update derived from that multiplicative update. See also Pav (2004) . + date_publication: '2024-11-04' + bug_reports: https://github.com/shabbychef/rnnmf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rnnmf + url_git: https://github.com/shabbychef/rnnmf +rNOMADS: + version: 2.5.3 + title: |- + An R Interface to the NOAA Operational Model Archive and + Distribution System + maintainer: Daniel C. Bowman + description: An interface to the National Oceanic and Atmospheric Administration's + Operational Model Archive and Distribution System (NOMADS, see + for more information) that allows R users to quickly and efficiently download + global and regional weather model data for processing. rNOMADS currently supports + a variety of models ranging from global weather data to an altitude of over 40 + km, to high resolution regional weather models, to wave and sea ice models. rNOMADS + can retrieve binary data in grib format as well as import ascii data directly + into R by interfacing with the GrADS-DODS system. + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rNOMADS + url_git: +RNOmni: + version: 1.0.1.2 + title: Rank Normal Transformation Omnibus Test + maintainer: Zachary McCaw + description: Inverse normal transformation (INT) based genetic association testing. + These tests are recommend for continuous traits with non-normally distributed + residuals. INT-based tests robustly control the type I error in settings where + standard linear regression does not, as when the residual distribution exhibits + excess skew or kurtosis. Moreover, INT-based tests outperform standard linear + regression in terms of power. These tests may be classified into two types. In + direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), + phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines + D-INT and I-INT into a single robust and statistically powerful approach. See + McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the + rank-based inverse normal transformation for quantitative trait analysis in genome-wide + association studies" . + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RNOmni + url_git: '' +rnpn: + version: 1.2.9.0 + title: Interface to the National 'Phenology' Network 'API' + maintainer: Jeff Switzer + description: |- + Programmatic interface to the + Web Service methods provided by the National 'Phenology' Network + (), which includes data on various life history + events that occur at specific times. + date_publication: '2024-08-19' + bug_reports: https://github.com/usa-npn/rnpn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rnpn + url_git: https://github.com/usa-npn/rnpn +rnr: + version: 0.2.1 + title: Rosenbaum and Rubin Sensitivity + maintainer: Jongbin Jung + description: |- + Apply sensitivity analysis for offline policy evaluation, as + implemented in Jung et al. (2017) based + on Rosenbaum and Rubin (1983) . + date_publication: '2018-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rnr + url_git: '' +rnrfa: + version: 2.1.0.6 + title: UK National River Flow Archive Data from R + maintainer: Ilaria Prosdocimi + description: |- + Utility functions to retrieve data from the UK National River + Flow Archive (, terms and conditions: + ). The package + contains R wrappers to the UK NRFA data temporary-API. There are + functions to retrieve stations falling in a bounding box, to generate + a map and extracting time series and general information. The package + is fully described in Vitolo et al (2016) "rnrfa: An R package to + Retrieve, Filter and Visualize Data from the UK National River Flow + Archive" + . + date_publication: '2024-06-19' + bug_reports: https://github.com/ilapros/rnrfa/issues + url: https://ilapros.github.io/rnrfa/ + url_cran: https://CRAN.R-project.org/package=rnrfa + url_git: '' +Rnumerai: + version: 3.0.1 + title: Interface to the Numerai Machine Learning Tournament API + maintainer: Eric Hare + description: |- + Routines to interact with the Numerai Machine Learning Tournament + API . The functionality includes the ability to automatically download the + current tournament data, submit predictions, and to get information for your + user. + date_publication: '2022-09-14' + bug_reports: https://github.com/Omni-Analytics-Group/Rnumerai/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rnumerai + url_git: https://github.com/Omni-Analytics-Group/Rnumerai +Rnvd3: + version: 1.0.0 + title: An Incomplete Wrapper of the 'nvd3' JavaScript Library + maintainer: Stéphane Laurent + description: Creates JavaScript charts with the 'nvd3' library. So far only the + multibar chart, the horizontal multibar chart, the line chart and the line chart + with focus are available. + date_publication: '2021-09-02' + bug_reports: https://github.com/stla/Rnvd3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rnvd3 + url_git: https://github.com/stla/Rnvd3 +roadoi: + version: 0.7.3 + title: Find Free Versions of Scholarly Publications via Unpaywall + maintainer: Najko Jahn + description: |- + This web client interfaces Unpaywall , formerly + oaDOI, a service finding free full-texts of academic papers by linking DOIs with + open access journals and repositories. It provides unified access to various data sources + for open access full-text links including Crossref and the Directory of Open Access + Journals (DOAJ). API usage is free and no registration is required. + date_publication: '2024-09-26' + bug_reports: https://github.com/ropensci/roadoi/issues/ + url: https://docs.ropensci.org/roadoi/ + url_cran: https://CRAN.R-project.org/package=roadoi + url_git: https://github.com/ropensci/roadoi/ +roads: + version: 1.2.0 + title: Road Network Projection + maintainer: Sarah Endicott + description: |- + Iterative least cost path and minimum spanning tree methods for projecting + forest road networks. The methods connect a set of target points to an existing + road network using 'igraph' to identify least cost routes. + The cost of constructing a road segment between adjacent pixels is determined + by a user supplied weight raster and a weight function; options include the + average of adjacent weight raster values, and a function of the elevation + differences between adjacent cells that penalizes steep grades. These road + network projection methods are intended for integration into R workflows and + modelling frameworks used for forecasting forest change, and can be applied + over multiple time-steps without rebuilding a graph at each time-step. + date_publication: '2024-06-27' + bug_reports: https://github.com/LandSciTech/roads/issues + url: https://landscitech.github.io/roads/ + url_cran: https://CRAN.R-project.org/package=roads + url_git: https://github.com/LandSciTech/roads +roahd: + version: 1.4.3 + title: Robust Analysis of High Dimensional Data + maintainer: Aymeric Stamm + description: |- + A collection of methods for the robust analysis of univariate and + multivariate functional data, possibly in high-dimensional cases, and hence + with attention to computational efficiency and simplicity of use. See the R + Journal publication of Ieva et al. (2019) for an + in-depth presentation of the 'roahd' package. See Aleman-Gomez et al. (2021) + for details about the concept of depthgram. + date_publication: '2021-11-04' + bug_reports: https://github.com/astamm/roahd/issues + url: https://astamm.github.io/roahd/ + url_cran: https://CRAN.R-project.org/package=roahd + url_git: https://github.com/astamm/roahd +ROAuth: + version: 0.9.6 + title: R Interface For OAuth + maintainer: Pablo Barbera + description: Provides an interface to the OAuth 1.0 specificationallowing + users to authenticate via OAuth to theserver of their choice. + date_publication: '2015-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROAuth + url_git: '' +RobAStBase: + version: 1.2.7 + title: Robust Asymptotic Statistics + maintainer: Matthias Kohl + description: Base S4-classes and functions for robust asymptotic statistics. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobAStBase + url_git: https://r-forge.r-project.org/projects/robast/ +RobAStRDA: + version: 1.2.2 + title: |- + Interpolation Grids for Packages of the 'RobASt' - Family of + Packages + maintainer: Peter Ruckdeschel + description: |- + Includes 'sysdata.rda' file for packages of the 'RobASt' - family of packages; is + currently used by package 'RobExtremes' only. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobAStRDA + url_git: https://r-forge.r-project.org/projects/robast/ +robber: + version: 0.2.4 + title: |- + Using Block Model to Estimate the Robustness of Ecological + Network + maintainer: Saint-Clair Chabert-Liddell + description: |- + Implementation of a variety of methods to compute + the robustness of ecological interaction networks with binary interactions + as described in . In particular, using the Stochastic + Block Model and its bipartite counterpart, the Latent Block Model to put a + parametric model on the network, allows the comparison of the robustness of + networks differing in species richness and number of interactions. It also + deals with networks that are partially sampled and/or with missing values. + date_publication: '2024-02-07' + bug_reports: https://github.com/Chabert-Liddell/robber/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robber + url_git: https://github.com/Chabert-Liddell/robber +robCompositions: + version: 2.4.1 + title: Compositional Data Analysis + maintainer: Matthias Templ + description: |- + Methods for analysis of compositional data including robust + methods (), imputation of missing values (), methods to replace + rounded zeros (, , ), + count zeros (), + methods to deal with essential zeros (), (robust) outlier + detection for compositional data, (robust) principal component analysis for + compositional data, (robust) factor analysis for compositional data, (robust) + discriminant analysis for compositional data (Fisher rule), robust regression + with compositional predictors, functional data analysis () and p-splines (), + contingency () + and compositional tables (, , ) + and (robust) Anderson-Darling normality tests for + compositional data as well as popular log-ratio transformations (addLR, cenLR, + isomLR, and their inverse transformations). In addition, visualisation and + diagnostic tools are implemented as well as high and low-level plot functions + for the ternary diagram. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robCompositions + url_git: '' +robcor: + version: 0.1-6.1 + title: Robust Correlations + maintainer: Paul Smirnov + description: |- + Robust pairwise correlations based on estimates of scale, + particularly on "FastQn" one-step M-estimate. + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robcor + url_git: '' +roben: + version: 0.1.2 + title: |- + Robust Bayesian Variable Selection for Gene-Environment + Interactions + maintainer: Jie Ren + description: |- + Gene-environment (G×E) interactions have important implications to elucidate the + etiology of complex diseases beyond the main genetic and environmental effects. + Outliers and data contamination in disease phenotypes of G×E studies have been commonly + encountered, leading to the development of a broad spectrum of robust penalization methods. + Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing + studies. We develop a robust Bayesian variable selection method for G×E interaction + studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and + outliers in the response variable while conducting variable selection by accounting for + structural sparsity. In particular, the spike-and-slab priors have been imposed on both + individual and group levels to identify important main and interaction effects. An efficient + Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo + algorithms of the proposed and alternative methods are efficiently implemented in C++. + date_publication: '2025-02-10' + bug_reports: https://github.com/jrhub/roben/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roben + url_git: https://github.com/jrhub/roben +RobExtremes: + version: 1.3.2 + title: Optimally Robust Estimation for Extreme Value Distributions + maintainer: Peter Ruckdeschel + description: |- + Optimally robust estimation for extreme value distributions using S4 classes and + methods (based on packages 'distr', 'distrEx', 'distrMod', 'RobAStBase', and + 'ROptEst'); the underlying theoretic results can be found in Ruckdeschel and + Horbenko, (2013 and 2012), \doi{10.1080/02331888.2011.628022} and + \doi{10.1007/s00184-011-0366-4}. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobExtremes + url_git: https://r-forge.r-project.org/projects/robast/ +robfilter: + version: 4.1.5 + title: Robust Time Series Filters + maintainer: Roland Fried + description: |- + Implementations for several robust procedures that allow for (online) + extraction of the signal of univariate or multivariate time series by + applying robust regression techniques to a moving time window are provided. + Included are univariate filtering procedures based on repeated-median + regression as well as hybrid and trimmed filters derived from it; + see Schettlinger et al. (2006) . The adaptive + online repeated median by Schettlinger et al. (2010) + and the slope comparing adaptive repeated median by Borowski and Fried (2013) + choose the width of the moving time + window adaptively. Multivariate versions are also provided; see + Borowski et al. (2009) for a multivariate + online adaptive repeated median and Borowski (2012) + for a multivariate slope comparing adaptive repeated median. Furthermore, + a repeated-median based filter with automatic outlier replacement and + shift detection is provided; see Fried (2004) . + date_publication: '2024-07-16' + bug_reports: '' + url: https://msnat.statistik.tu-dortmund.de/en/team/chair/ + url_cran: https://CRAN.R-project.org/package=robfilter + url_git: '' +robflreg: + version: '1.2' + title: Robust Functional Linear Regression + maintainer: Ufuk Beyaztas + description: Functions for implementing robust methods for functional linear regression. + In the functional linear regression, we consider scalar-on-function linear regression + and function-on-function linear regression. More details, see Beyaztas, U., and + Shang, H. L. (2021) and Beyaztas, U., and Shang, H. L. (2022) + . + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robflreg + url_git: '' +RobGARCHBoot: + version: 1.2.0 + title: Robust Bootstrap Forecast Densities for GARCH Models + maintainer: Carlos Trucios + description: Bootstrap forecast densities for GARCH (Generalized Autoregressive + Conditional Heteroskedastic) returns and volatilities using the robust residual-based + bootstrap procedure of Trucios, Hotta and Ruiz (2017) . + date_publication: '2020-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobGARCHBoot + url_git: '' +robin: + version: 2.0.0 + title: ROBustness in Network + maintainer: Valeria Policastro + description: Assesses the robustness of the community structure of a network found + by one or more community detection algorithm to give indications about their reliability. + It detects if the community structure found by a set of algorithms is statistically + significant and compares the different selected detection algorithms on the same + network. robin helps to choose among different community detection algorithms + the one that better fits the network of interest. Reference in Policastro V., + Righelli D., Carissimo A., Cutillo L., De Feis I. (2021) . + date_publication: '2025-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robin + url_git: https://github.com/ValeriaPolicastro/robin +RobinCar: + version: 0.3.2 + title: |- + Robust Inference for Covariate Adjustment in Randomized Clinical + Trials + maintainer: Marlena Bannick + description: |- + Performs robust estimation and inference when using covariate adjustment and/or covariate-adaptive randomization in randomized clinical trials. + Ting Ye, Jun Shao, Yanyao Yi, Qinyuan Zhao (2023) . + Ting Ye, Marlena Bannick, Yanyao Yi, Jun Shao (2023) . + Ting Ye, Jun Shao, Yanyao Yi (2023) . + Marlena Bannick, Jun Shao, Jingyi Liu, Yu Du, Yanyao Yi, Ting Ye (2024) . + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobinCar + url_git: '' +RobinHood: + version: 1.7.0 + title: Interface for the RobinHood.com No Commission Investing Platform + maintainer: Joseph Blubaugh + description: Execute API calls to the RobinHood investing + platform. Functionality includes accessing account data and current holdings, + retrieving investment statistics and quotes, placing and canceling orders, getting + market trading hours, searching investments by popular tag, and interacting with + watch lists. + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobinHood + url_git: https://github.com/JestonBlu/RobinHood +robis: + version: 2.11.3 + title: Ocean Biodiversity Information System (OBIS) Client + maintainer: Pieter Provoost + description: Client for the Ocean Biodiversity Information System (). + date_publication: '2022-09-24' + bug_reports: https://github.com/iobis/robis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robis + url_git: https://github.com/iobis/robis +RobKF: + version: 1.0.2 + title: Innovative and/or Additive Outlier Robust Kalman Filtering + maintainer: Daniel Grose + description: Implements a series of robust Kalman filtering approaches. It implements + the additive outlier robust filters of Ruckdeschel et al. (2014) + and Agamennoni et al. (2018) , the innovative outlier + robust filter of Ruckdeschel et al. (2014) , as well as the innovative + and additive outlier robust filter of Fisch et al. (2020) . + date_publication: '2021-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobKF + url_git: '' +RobLox: + version: 1.2.3 + title: |- + Optimally Robust Influence Curves and Estimators for Location + and Scale + maintainer: Matthias Kohl + description: |- + Functions for the determination of optimally robust influence curves and + estimators in case of normal location and/or scale (see Chapter 8 in Kohl (2005) + ). + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobLox + url_git: http://robast.r-forge.r-project.org/ +RobLoxBioC: + version: 1.2.3 + title: Infinitesimally Robust Estimators for Preprocessing -Omics Data + maintainer: Matthias Kohl + description: |- + Functions for the determination of optimally robust influence curves and + estimators for preprocessing omics data, in particular gene expression data (Kohl + and Deigner (2010), ). + date_publication: '2025-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobLoxBioC + url_git: https://r-forge.r-project.org/projects/robast/ +RoBMA: + version: 3.4.0 + title: Robust Bayesian Meta-Analyses + maintainer: František Bartoš + description: |- + A framework for estimating ensembles of meta-analytic and meta-regression models + (assuming either presence or absence of the effect, heterogeneity, + publication bias, and moderators). The RoBMA framework uses Bayesian model-averaging to + combine the competing meta-analytic models into a model ensemble, weights + the posterior parameter distributions based on posterior model probabilities + and uses Bayes factors to test for the presence or absence of the + individual components (e.g., effect vs. no effect; Bartoš et al., 2022, + ; Maier, Bartoš & Wagenmakers, 2022, + ). Users can define a wide range of prior distributions for + + the effect size, heterogeneity, publication bias (including selection models and PET-PEESE), + and moderator components. The package provides convenient functions for summary, visualizations, and + fit diagnostics. + date_publication: '2025-02-04' + bug_reports: https://github.com/FBartos/RoBMA/issues + url: https://fbartos.github.io/RoBMA/ + url_cran: https://CRAN.R-project.org/package=RoBMA + url_git: '' +robmed: + version: 1.2.1 + title: (Robust) Mediation Analysis + maintainer: Andreas Alfons + description: Perform mediation analysis via the fast-and-robust bootstrap test ROBMED + (Alfons, Ates & Groenen, 2022a; ), as well as various + other methods. Details on the implementation and code examples can be found in + Alfons, Ates, and Groenen (2022b) . Further discussion + on robust mediation analysis can be found in Alfons & Schley (2024) . + date_publication: '2025-02-08' + bug_reports: https://github.com/aalfons/robmed/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robmed + url_git: https://github.com/aalfons/robmed +robmedExtra: + version: 0.1.1 + title: Extra Functionality for (Robust) Mediation Analysis + maintainer: Andreas Alfons + description: This companion package extends the package 'robmed' (Alfons, Ates & + Groenen, 2022b; ) in various ways. Most notably, it + provides a graphical user interface for the robust bootstrap test ROBMED (Alfons, + Ates & Groenen, 2022a; ) to make the method more + accessible to less proficient 'R' users, as well as functions to export the results + as a table in a 'Microsoft Word' or 'Microsoft Powerpoint' document, or as a 'LaTeX' + table. Furthermore, the package contains a 'shiny' app to compare various bootstrap + procedures for mediation analysis on simulated data. + date_publication: '2024-11-03' + bug_reports: https://github.com/aalfons/robmedExtra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robmedExtra + url_git: https://github.com/aalfons/robmedExtra +robmixglm: + version: 1.2-4 + title: Robust Generalized Linear Models (GLM) using Mixtures + maintainer: Ken Beath + description: Robust generalized linear models (GLM) using a mixture method, as described + in Beath (2018) . This assumes that the data + are a mixture of standard observations, being a generalised linear model, and + outlier observations from an overdispersed generalized linear model. The overdispersed + linear model is obtained by including a normally distributed random effect in + the linear predictor of the generalized linear model. + date_publication: '2024-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robmixglm + url_git: '' +RobMixReg: + version: 1.1.0 + title: Robust Mixture Regression + maintainer: Wennan Chang + description: |- + Finite mixture models are a popular technique for modelling unobserved heterogeneity or to approximate general distribution functions in a semi-parametric way. They are used in a lot of different areas such as astronomy, biology, economics, marketing or medicine. + This package is the implementation of popular robust mixture regression methods based on different algorithms including: fleximix, finite mixture models and latent class regression; CTLERob, component-wise adaptive trimming likelihood estimation; mixbi, bi-square estimation; mixL, Laplacian distribution; mixt, t-distribution; TLE, trimmed likelihood estimation. + The implemented algorithms includes: CTLERob stands for Component-wise adaptive Trimming Likelihood Estimation based mixture regression; mixbi stands for mixture regression based on bi-square estimation; mixLstands for mixture regression based on Laplacian distribution; TLE stands for Trimmed Likelihood Estimation based mixture regression. For more detail of the algorithms, please refer to below references. + Reference: Chun Yu, Weixin Yao, Kun Chen (2017) . + NeyKov N, Filzmoser P, Dimova R et al. (2007) . + Bai X, Yao W. Boyer JE (2012) . + Wennan Chang, Xinyu Zhou, Yong Zang, Chi Zhang, Sha Cao (2020) . + date_publication: '2020-08-05' + bug_reports: https://github.com/changwn/RobMixReg/issues + url: https://changwn.github.io/RobMixReg/ + url_cran: https://CRAN.R-project.org/package=RobMixReg + url_git: '' +robnptests: + version: 1.1.0 + title: Robust Nonparametric Two-Sample Tests for Location/Scale + maintainer: Sermad Abbas + description: |- + Implementations of several robust nonparametric two-sample tests + for location or scale differences. The test statistics are based on robust + location and scale estimators, e.g. the sample median or the Hodges-Lehmann estimators + as described in Fried & Dehling (2011) . + The p-values can be computed via the permutation principle, the randomization principle, or by using + the asymptotic distributions of the test statistics under the null hypothesis, which ensures + (approximate) distribution independence of the test decision. To test for a difference in + scale, we apply the tests for location difference to transformed observations; see Fried (2012) . + Random noise on a small range can be added to the original observations in order to + hold the significance level on data from discrete distributions. + The location tests assume homoscedasticity and the scale tests require the + location parameters to be zero. + date_publication: '2023-02-13' + bug_reports: https://github.com/s-abbas/robnptests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robnptests + url_git: https://github.com/s-abbas/robnptests +roboBayes: + version: '1.2' + title: Robust Online Bayesian Monitoring + maintainer: Shannon T. Holloway + description: An implementation of Bayesian online changepoint detection (Adams and + MacKay (2007) ) with an option for probability based outlier + detection and removal (Wendelberger et. al. (2021) ). Building + on the independent multivariate constant mean model implemented in the 'R' package + 'ocp', this package models multivariate data as multivariate normal about a linear + trend, defined by user input covariates, with an unstructured error covariance. + Changepoints are identified based on a probability threshold for windows of points. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roboBayes + url_git: '' +robomit: + version: 1.0.7 + title: Robustness Checks for Omitted Variable Bias + maintainer: Sergei Schaub + description: 'Robustness checks for omitted variable bias. The package includes + robustness checks proposed by Oster (2019). The ''robomit'' package computes i) + the bias-adjusted treatment correlation or effect and ii) the degree of selection + on unobservables relative to observables (with respect to the treatment variable) + that would be necessary to eliminate the result based on the framework by Oster + (2019). The code is based on the ''psacalc'' command in ''Stata''. Additionally, + ''robomit'' offers a set of sensitivity analysis and visualization functions. + See Oster, E. 2019. . Additionally, see Diegert, + P., Masten, M. A., & Poirier, A. (2022) for a recent discussion of the topic: + .' + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robomit + url_git: '' +robotoolbox: + version: '1.4' + title: Client for the 'KoboToolbox' API + maintainer: Ahmadou Dicko + description: |- + Suite of utilities for accessing and manipulating + data from the 'KoboToolbox' API. 'KoboToolbox' is a robust + platform designed for field data collection in various disciplines. + This package aims to simplify the process of fetching and handling + data from the API. Detailed documentation for the 'KoboToolbox' API + can be found at . + date_publication: '2024-12-19' + bug_reports: https://gitlab.com/dickoa/robotoolbox/-/issues + url: https://dickoa.gitlab.io/robotoolbox + url_cran: https://CRAN.R-project.org/package=robotoolbox + url_git: https://gitlab.com/dickoa/robotoolbox +robotstxt: + version: 0.7.15 + title: |- + A 'robots.txt' Parser and 'Webbot'/'Spider'/'Crawler' + Permissions Checker + maintainer: Pedro Baltazar + description: |- + Provides functions to download and parse 'robots.txt' files. + Ultimately the package makes it easy to check if bots + (spiders, crawler, scrapers, ...) are allowed to access specific + resources on a domain. + date_publication: '2024-08-29' + bug_reports: https://github.com/ropensci/robotstxt/issues + url: https://docs.ropensci.org/robotstxt/ + url_cran: https://CRAN.R-project.org/package=robotstxt + url_git: https://github.com/ropensci/robotstxt +RobPC: + version: '1.4' + title: Robust Panel Clustering Algorithm + maintainer: Hasan Bulut + description: Performs both classical and robust panel clustering by applying Principal + Component Analysis (PCA) for dimensionality reduction and clustering via standard + K-Means or Trimmed K-Means. The method is designed to ensure stable and reliable + clustering, even in the presence of outliers. Suitable for analyzing panel data + in domains such as economic research, financial time-series, healthcare analytics, + and social sciences. The package allows users to choose between classical K-Means + for standard clustering and Trimmed K-Means for robust clustering, making it a + flexible tool for various applications. For this package, we have benefited from + the studies Rencher (2003), Wang and Lu (2021) , + Cuesta-Albertos et al. (1997) . + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobPC + url_git: '' +RobPer: + version: 1.2.3 + title: Robust Periodogram and Periodicity Detection Methods + maintainer: Jonathan Rathjens + description: 'Calculates periodograms based on (robustly) fitting periodic functions + to light curves (irregularly observed time series, possibly with measurement accuracies, + occurring in astroparticle physics). Three main functions are included: RobPer() + calculates the periodogram. Outlying periodogram bars (indicating a period) can + be detected with betaCvMfit(). Artificial light curves can be generated using + the function tsgen(). For more details see the corresponding article: Thieler, + Fried and Rathjens (2016), Journal of Statistical Software 69(9), 1-36, .' + date_publication: '2022-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobPer + url_git: '' +robqda: + version: '1.0' + title: Robust Quadratic Discriminant Analysis + maintainer: Michail Tsagris + description: 'The minimum covariance determinant estimator is used to perform robust + quadratic discriminant analysis, including cross-validation. References: Friedman + J., Hastie T. and Tibshirani R. (2009). "The elements of statistical learning", + 2nd edition. Springer, Berlin. .' + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robqda + url_git: '' +robreg3S: + version: '0.3' + title: |- + Three-Step Regression and Inference for Cellwise and Casewise + Contamination + maintainer: Andy Leung + description: Three-step regression and inference for cellwise and casewise contamination. + date_publication: '2015-12-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robreg3S + url_git: '' +robregcc: + version: '1.1' + title: Robust Regression with Compositional Covariates + maintainer: Aditya Mishra + description: 'We implement the algorithm estimating the parameters of the robust + regression model with compositional covariates. The model simultaneously treats + outliers and provides reliable parameter estimates. Publication reference: Mishra, + A., Mueller, C.,(2019) .' + date_publication: '2020-07-25' + bug_reports: '' + url: https://arxiv.org/abs/1909.04990 + url_cran: https://CRAN.R-project.org/package=robregcc + url_git: https://github.com/amishra-stats/robregcc +RobRegression: + version: 0.1.0 + title: Robust Multivariate Regression + maintainer: Antoine Godichon-Baggioni + description: Robust methods for estimating the parameters of multivariate Gaussian + linear models. + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobRegression + url_git: '' +RoBSA: + version: 1.0.2 + title: Robust Bayesian Survival Analysis + maintainer: František Bartoš + description: |- + A framework for estimating ensembles of parametric survival models + with different parametric families. The RoBSA framework uses Bayesian + model-averaging to combine the competing parametric survival models into + a model ensemble, weights the posterior parameter distributions based on + posterior model probabilities and uses Bayes factors to test for the + presence or absence of the individual predictors or preference for a + parametric family (Bartoš, Aust & Haaf, 2022, ). + The user can define a wide range of informative priors for all parameters + of interest. The package provides convenient functions for summary, visualizations, + fit diagnostics, and prior distribution calibration. + date_publication: '2023-05-30' + bug_reports: https://github.com/FBartos/RoBSA/issues + url: https://fbartos.github.io/RoBSA/ + url_cran: https://CRAN.R-project.org/package=RoBSA + url_git: '' +robsel: + version: 0.1.0 + title: Robust Selection Algorithm + maintainer: Chau Tran + description: An implementation of algorithms for estimation of the graphical lasso + regularization parameter described in Pedro Cisneros-Velarde, Alexander Petersen + and Sang-Yun Oh (2020) . + date_publication: '2021-05-25' + bug_reports: https://github.com/dddlab/robust-selection/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robsel + url_git: '' +robservable: + version: 0.2.2 + title: Import an Observable Notebook as HTML Widget + maintainer: Julien Barnier + description: |- + Allows loading and displaying an Observable notebook (online JavaScript + notebooks powered by ) as an HTML Widget in an R + session, 'shiny' application or 'rmarkdown' document. + date_publication: '2022-06-28' + bug_reports: https://github.com/juba/robservable/issues + url: https://juba.github.io/robservable/ + url_cran: https://CRAN.R-project.org/package=robservable + url_git: '' +robslopes: + version: 1.1.3 + title: Fast Algorithms for Robust Slopes + maintainer: Jakob Raymaekers + description: |- + Fast algorithms for the Theil-Sen estimator, + Siegel's repeated median slope estimator, and Passing-Bablok regression. + The implementation is based on algorithms by + Dillencourt et. al (1992) and Matousek et. al (1998) . + The implementations are detailed in + Raymaekers (2023) and + Raymaekers J., Dufey F. (2022) . + All algorithms run in quasilinear time. + date_publication: '2023-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robslopes + url_git: '' +RobStatTM: + version: 1.0.11 + title: 'Robust Statistics: Theory and Methods' + maintainer: Matias Salibian-Barrera + description: 'Companion package for the book: "Robust Statistics: Theory and Methods, + second edition", . This package contains + code that implements the robust estimators discussed in the recent second edition + of the book above, as well as the scripts reproducing all the examples in the + book.' + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobStatTM + url_git: '' +robStepSplitReg: + version: 1.1.0 + title: Robust Stepwise Split Regularized Regression + maintainer: Anthony Christidis + description: |- + Functions to perform robust stepwise split regularized regression. The approach first + uses a robust stepwise algorithm to split the variables into the models of an ensemble. + An adaptive robust regularized estimator is then applied to each subset of predictors + in the models of an ensemble. + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robStepSplitReg + url_git: '' +robsurvey: + version: '0.7' + title: Robust Survey Statistics Estimation + maintainer: Tobias Schoch + description: |- + Robust (outlier-resistant) estimators of finite population + characteristics like of means, totals, ratios, regression, etc. Available + methods are M- and GM-estimators of regression, weight reduction, + trimming, and winsorization. The package extends the 'survey' + package. + date_publication: '2024-08-22' + bug_reports: https://github.com/tobiasschoch/robsurvey/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robsurvey + url_git: https://github.com/tobiasschoch/robsurvey +RoBTT: + version: 1.3.1 + title: Robust Bayesian T-Test + maintainer: František Bartoš + description: |- + An implementation of Bayesian model-averaged t-tests that allows + users to draw inferences about the presence versus absence of an effect, + variance heterogeneity, and potential outliers. The 'RoBTT' package estimates + ensembles of models created by combining competing hypotheses and applies + Bayesian model averaging using posterior model probabilities. Users can + obtain model-averaged posterior distributions and inclusion Bayes factors, + accounting for uncertainty in the data-generating process + (Maier et al., 2024, ). The package also + provides a truncated likelihood version of the model-averaged t-test, + enabling users to exclude potential outliers without introducing bias + (Godmann et al., 2024, ). Users can specify + a wide range of informative priors for all parameters of interest. + The package offers convenient functions for summary, visualization, + and fit diagnostics. + date_publication: '2024-11-10' + bug_reports: https://github.com/FBartos/RoBTT/issues + url: https://fbartos.github.io/RoBTT/ + url_cran: https://CRAN.R-project.org/package=RoBTT + url_git: '' +robumeta: + version: '2.1' + title: Robust Variance Meta-Regression + maintainer: Zachary Fisher + description: Functions for conducting robust variance estimation (RVE) meta-regression + using both large and small sample RVE estimators under various weighting schemes. + These methods are distribution free and provide valid point estimates, standard + errors and hypothesis tests even when the degree and structure of dependence between + effect sizes is unknown. Also included are functions for conducting sensitivity + analyses under correlated effects weighting and producing RVE-based forest plots. + date_publication: '2023-03-28' + bug_reports: https://github.com/zackfisher/robumeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robumeta + url_git: https://github.com/zackfisher/robumeta +robust: + version: 0.7-5 + title: Port of the S+ "Robust Library" + maintainer: Valentin Todorov + description: |- + Methods for robust statistics, a state of the art in the early + 2000s, notably for robust regression and robust multivariate analysis. + date_publication: '2024-08-17' + bug_reports: https://github.com/valentint/robust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robust + url_git: https://github.com/valentint/robust +robust2sls: + version: 0.2.2 + title: Outlier Robust Two-Stage Least Squares Inference and Testing + maintainer: Jonas Kurle + description: |- + An implementation of easy tools for outlier robust inference in + two-stage least squares (2SLS) models. The user specifies a reference + distribution against which observations are classified as outliers or not. + After removing the outliers, adjusted standard errors are automatically + provided. Furthermore, several statistical tests for the false outlier + detection rate can be calculated. The outlier removing algorithm can be + iterated a fixed number of times or until the procedure converges. The + algorithms and robust inference are described in more detail in Jiao (2019) + . + date_publication: '2023-01-11' + bug_reports: https://github.com/jkurle/robust2sls/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robust2sls + url_git: https://github.com/jkurle/robust2sls +RobustAFT: + version: 1.4-7 + title: |- + Truncated Maximum Likelihood Fit and Robust Accelerated Failure + Time Regression for Gaussian and Log-Weibull Case + maintainer: A. Randriamiharisoa + description: |- + R functions for the computation of the truncated maximum + likelihood and the robust accelerated failure time regression + for gaussian and log-Weibull case. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustAFT + url_git: '' +RobustANOVA: + version: 0.3.0 + title: |- + Robust One-Way ANOVA Tests under Heteroscedasticity and + Nonnormality + maintainer: Gamze Guven + description: Robust tests (RW, RPB and RGF) are provided for testing the equality + of several long-tailed symmetric (LTS) means when the variances are unknown and + arbitrary. RW, RPB and RGF tests are robust versions of Welch's F test proposed + by Welch (1951) , parametric bootstrap test proposed by Krishnamoorthy + et. al (2007) ; and generalized F test proposed + by Weerahandi (1995) ;, respectively. These tests are based + on the modified maximum likelihood (MML) estimators proposed by Tiku(1967, 1968) + , . + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustANOVA + url_git: '' +robustarima: + version: 0.2.7 + title: Robust ARIMA Modeling + maintainer: Stephen Kaluzny + description: |- + Functions for fitting a linear regression model with ARIMA + errors using a filtered tau-estimate. + The methodology is described in Maronna et al (2017, ISBN:9781119214687). + date_publication: '2024-09-23' + bug_reports: https://github.com/spkaluzny/robustarima/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robustarima + url_git: https://github.com/spkaluzny/robustarima +robustbase: + version: 0.99-4-1 + title: Basic Robust Statistics + maintainer: Martin Maechler + description: |- + "Essential" Robust Statistics. + Tools allowing to analyze data with robust methods. This includes + regression methodology including model selections and multivariate + statistics where we strive to cover the book "Robust Statistics, + Theory and Methods" by 'Maronna, Martin and Yohai'; Wiley 2006. + date_publication: '2024-09-27' + bug_reports: https://R-forge.R-project.org/tracker/?atid=302&group_id=59 + url: '' + url_cran: https://CRAN.R-project.org/package=robustbase + url_git: https://robustbase.R-forge.R-project.org/ +RobustBayesianCopas: + version: '2.0' + title: Robust Bayesian Copas Selection Model + maintainer: Ray Bai + description: Fits the robust Bayesian Copas (RBC) selection model of Bai et al. + (2020) for correcting and quantifying publication bias in univariate + meta-analysis. Also fits standard random effects meta-analysis and the Copas-like + selection model of Ning et al. (2017) . + date_publication: '2021-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustBayesianCopas + url_git: '' +robustbetareg: + version: 0.3.0 + title: Robust Beta Regression + maintainer: Felipe Queiroz + description: |- + Robust estimators for the beta regression, useful for modeling + bounded continuous data. Currently, four types of robust estimators are supported. + They depend on a tuning constant which may be fixed or selected by a + data-driven algorithm also implemented in the package. Diagnostic tools + associated with the fitted model, such as the residuals and goodness-of-fit + statistics, are implemented. Robust Wald-type tests are available. More details + about robust beta regression are described in Maluf et al. (2022) . + date_publication: '2022-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustbetareg + url_git: '' +RobustBF: + version: 0.2.0 + title: Robust Solution to the Behrens-Fisher Problem + maintainer: Gamze Guven + description: Robust tests (RW and RF) are provided for testing the equality of two + long-tailed symmetric (LTS) means when the variances are unknown and arbitrary. + RW test is a robust version of Welch's two sample t test and the RF is a robust + fiducial based test. The RW and RF tests are proposed using the adaptive modified + maximum likelihood (AMML) estimators derived by Tiku and Surucu (2009) + and Donmez (2010) . + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustBF + url_git: '' +robustBLME: + version: 0.1.3 + title: Robust Bayesian Linear Mixed-Effects Models using ABC + maintainer: Erlis Ruli + description: Bayesian robust fitting of linear mixed effects models through weighted + likelihood equations and approximate Bayesian computation as proposed by Ruli + et al. (2017) . + date_publication: '2018-01-30' + bug_reports: https://github.com/erlisR/robustBLME/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robustBLME + url_git: https://github.com/erlisR/robustBLME +RobustCalibration: + version: 0.5.5 + title: Robust Calibration of Imperfect Mathematical Models + maintainer: Mengyang Gu + description: 'Implements full Bayesian analysis for calibrating mathematical models + with new methodology for modeling the discrepancy function. It allows for emulation, + calibration and prediction using complex mathematical model outputs and experimental + data. See the reference: Mengyang Gu and Long Wang, 2018, Journal of Uncertainty + Quantification; Mengyang Gu, Fangzheng Xie and Long Wang, 2022, Journal of Uncertainty + Quantification; Mengyang Gu, Kyle Anderson and Erika McPhillips, 2023, Technometrics.' + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustCalibration + url_git: '' +robustcov: + version: '0.1' + title: |- + Collection of Robust Covariance and (Sparse) Precision Matrix + Estimators + maintainer: Yunyi Shen + description: Collection of methods for robust covariance and (sparse) precision + matrix estimation based on Loh and Tan (2018) . + date_publication: '2021-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustcov + url_git: '' +robustDA: + version: '1.2' + title: Robust Mixture Discriminant Analysis + maintainer: Charles Bouveyron + description: Robust mixture discriminant analysis (RMDA), proposed in Bouveyron + & Girard, 2009 , allows to build a robust supervised + classifier from learning data with label noise. The idea of the proposed method + is to confront an unsupervised modeling of the data with the supervised information + carried by the labels of the learning data in order to detect inconsistencies. + The method is able afterward to build a robust classifier taking into account + the detected inconsistencies into the labels. + date_publication: '2020-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustDA + url_git: '' +robusTest: + version: 1.1.0 + title: Calibrated Correlation and Two-Sample Tests + maintainer: Olivier Bouaziz + description: |- + Implementation of corrected two-sample tests. A corrected version of the Pearson and Kendall correlation tests, + the Mann-Whitney (Wilcoxon) rank sum test, the Wilcoxon signed rank test and a variance test are implemented. + The package also proposes a test for the median and an independence test between two continuous variables of Kolmogorov-Smirnov's type. + All these corrected tests are asymptotically calibrated in the sense that the probability of rejection under the null hypothesis is + asymptotically equal to the level of the test. See for more details on the statistical tests. + date_publication: '2024-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robusTest + url_git: '' +robustETM: + version: '1.0' + title: Robust Methods using Exponential Tilt Model + maintainer: Chuan Hong + description: Testing homogeneity for generalized exponential tilt model. This package + includes a collection of functions for (1) implementing methods for testing homogeneity + for generalized exponential tilt model; and (2) implementing existing methods + under comparison. + date_publication: '2016-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustETM + url_git: '' +robustfa: + version: 1.1-0 + title: Object Oriented Solution for Robust Factor Analysis + maintainer: Frederic Bertrand + description: |- + Outliers virtually exist in any datasets of any application field. + To avoid the impact of outliers, we need to use robust estimators. + Classical estimators of multivariate mean and covariance matrix are + the sample mean and the sample covariance matrix. Outliers will + affect the sample mean and the sample covariance matrix, and thus + they will affect the classical factor analysis which depends on + the classical estimators (Pison, G., Rousseeuw, P.J., Filzmoser, + P. and Croux, C. (2003) ). + So it is necessary to use the robust estimators of the sample + mean and the sample covariance matrix. There are several robust + estimators in the literature: Minimum Covariance Determinant estimator, + Orthogonalized Gnanadesikan-Kettenring, Minimum Volume Ellipsoid, + M, S, and Stahel-Donoho. + The most direct way to make multivariate analysis more robust is to replace + the sample mean and the sample covariance matrix of the classical estimators + to robust estimators (Maronna, R.A., Martin, D. and Yohai, V. (2006) + ) (Todorov, V. and Filzmoser, P. (2009) + ), which is our choice of robust factor + analysis. We created an object oriented solution for robust factor + analysis based on new S4 classes. + date_publication: '2023-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustfa + url_git: '' +RobustGaSP: + version: 0.6.6 + title: Robust Gaussian Stochastic Process Emulation + maintainer: Mengyang Gu + description: |- + Robust parameter estimation and prediction of Gaussian stochastic + process emulators. It allows for robust parameter estimation and prediction using + Gaussian stochastic process emulator. It also implements the parallel partial + Gaussian stochastic process emulator for computer model with massive outputs + See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics; + Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics. + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustGaSP + url_git: '' +robustHD: + version: 0.8.1 + title: Robust Methods for High-Dimensional Data + maintainer: Andreas Alfons + description: |- + Robust methods for high-dimensional data, in particular linear + model selection techniques based on least angle regression and sparse + regression. Specifically, the package implements robust least angle + regression (Khan, Van Aelst & Zamar, 2007; ), + (robust) groupwise least angle regression (Alfons, Croux & Gelper, 2016; + ), and sparse least trimmed squares + regression (Alfons, Croux & Gelper, 2013; ). + date_publication: '2024-06-30' + bug_reports: https://github.com/aalfons/robustHD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=robustHD + url_git: https://github.com/aalfons/robustHD +RobustIV: + version: 0.2.5 + title: Robust Instrumental Variable Methods in Linear Models + maintainer: Zijian Guo + description: Inference for the treatment effect with possibly invalid instrumental + variables via TSHT('Guo et al.' (2016) ) and SearchingSampling('Guo' + (2021) ), which are effective for both low- and high-dimensional + covariates and instrumental variables; test of endogeneity in high dimensions + ('Guo et al.' (2016) ). + date_publication: '2022-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustIV + url_git: https://github.com/zijguo/RobustIV +RobustLinearReg: + version: 1.2.0 + title: Robust Linear Regressions + maintainer: Santiago I. Hurtado + description: Provides an easy way to compute the Theil Sehn Regression method and + also the Siegel Regression Method which are both robust methods base on the median + of slopes between all pairs of data. In contrast with the least squared linear + regression, these methods are not sensitive to outliers. Theil, H. (1992) , + Sen, P. K. (1968) . + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustLinearReg + url_git: '' +robustlm: + version: 0.1.0 + title: Robust Variable Selection with Exponential Squared Loss + maintainer: Jin Zhu + description: Computationally efficient tool for performing variable selection and + obtaining robust estimates, which implements robust variable selection procedure + proposed by Wang, X., Jiang, Y., Wang, S., Zhang, H. (2013) . + Users can enjoy the near optimal, consistent, and oracle properties of the procedures. + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustlm + url_git: '' +robustlmm: + version: 3.3-1 + title: Robust Linear Mixed Effects Models + maintainer: Manuel Koller + description: |- + Implements the Robust Scoring Equations estimator to fit linear + mixed effects models robustly. + Robustness is achieved by modification of the scoring equations + combined with the Design Adaptive Scale approach. + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustlmm + url_git: https://github.com/kollerma/robustlmm +robustmatrix: + version: 0.1.3 + title: Robust Matrix-Variate Parameter Estimation + maintainer: Marcus Mayrhofer + description: Robust covariance estimation for matrix-valued data and data with Kronecker-covariance + structure using the Matrix Minimum Covariance Determinant (MMCD) estimators and + outlier explanation using and Shapley values. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustmatrix + url_git: '' +robustmeta: + version: 1.2-1 + title: |- + Robust Inference for Meta-Analysis with Influential Outlying + Studies + maintainer: Hisashi Noma + description: Robust inference methods for fixed-effect and random-effects models + of meta-analysis are implementable. The robust methods are developed using the + density power divergence that is a robust estimating criterion developed in machine + learning theory, and can effectively circumvent biases and misleading results + caused by influential outliers. The density power divergence is originally introduced + by Basu et al. (1998) , and the meta-analysis methods + are developed by Noma et al. (2022) . + date_publication: '2023-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustmeta + url_git: '' +RobustPrediction: + version: 0.1.7 + title: Robust Tuning and Training for Cross-Source Prediction + maintainer: Yuting He + description: 'Provides robust parameter tuning and model training for predictive + models applied across data sources where the data distribution varies slightly + from source to source. This package implements three primary tuning methods: cross-validation-based + internal tuning, external tuning, and the ''RobustTuneC'' method. External tuning + includes a conservative option where parameters are tuned internally on the training + data and validating on an external dataset, providing a slightly pessimistic estimate. + It supports Lasso, Ridge, Random Forest, Boosting, and Support Vector Machine + classifiers. Currently, only binary classification is supported. The response + variable must be the first column of the dataset and a factor with exactly two + levels. The tuning methods are based on the paper by Nicole Ellenbach, Anne-Laure + Boulesteix, Bernd Bischl, Kristian Unger, and Roman Hornung (2021) "Improved Outcome + Prediction Across Data Sources Through Robust Parameter Tuning" .' + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustPrediction + url_git: https://github.com/Yuting-He/RobustPrediction +robustrank: + version: 2024.1-28 + title: Robust Rank-Based Tests + maintainer: Youyi Fong + description: Implements two-sample tests for paired data with missing values (Fong, + Huang, Lemos and McElrath 2018, Biostatics, ) + and modified Wilcoxon-Mann-Whitney two sample location test, also known as the + Fligner-Policello test. + date_publication: '2024-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustrank + url_git: '' +RobustRankAggreg: + version: 1.2.1 + title: Methods for Robust Rank Aggregation + maintainer: Raivo Kolde + description: |- + Methods for aggregating ranked lists, especially lists of + genes. It implements the Robust Rank Aggregation Kolde et al (2012) + and some other simple algorithms + for the task. RRA method uses a probabilistic model for aggregation that + is robust to noise and also facilitates the calculation of significance + probabilities for all the elements in the final ranking. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RobustRankAggreg + url_git: '' +robustrao: + version: 1.0-5 + title: An Extended Rao-Stirling Diversity Index to Handle Missing Data + maintainer: Maria del Carmen Calatrava Moreno + description: "A collection of functions to compute the Rao-Stirling diversity index\n(Porter + and Rafols, 2009) and its extension to\nacknowledge + missing data (i.e.,\tuncategorized references) by calculating its\ninterval of + uncertainty using\tmathematical optimization as proposed in Calatrava\net al. + (2016) .\nThe Rao-Stirling diversity index is a + well-established bibliometric indicator\nto measure the interdisciplinarity of + scientific publications. Apart from the\nobligatory dataset of publications with + their respective references and\ta\ntaxonomy of disciplines that categorizes references + as well as a measure of\nsimilarity between the disciplines, the Rao-Stirling + diversity index requires\na complete categorization of all references of a publication + into disciplines.\nThus, it fails for a incomplete categorization; in this case, + the robust\nextension has to be used, which encodes the uncertainty caused by + missing\nbibliographic data as an uncertainty interval.\nClassification / ACM + - 2012: Information systems ~ Similarity measures,\nTheory of computation ~ Quadratic\tprogramming, + Applied computing ~ Digital\nlibraries and archives." + date_publication: '2020-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustrao + url_git: https://gitlab.com/mc.calatrava.moreno/robustrao.git +robustreg: + version: 0.1-11 + title: Robust Regression Functions + maintainer: Ian M. Johnson + description: Linear regression functions using Huber and bisquare psi functions. + Optimal weights are calculated using IRLS algorithm. + date_publication: '2019-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustreg + url_git: '' +robustsae: + version: 0.1.0 + title: Robust Bayesian Small Area Estimation + maintainer: Jiyoun Myung + description: Functions for Robust Bayesian Small Area Estimation. + date_publication: '2016-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustsae + url_git: '' +robustsur: + version: 0.0-7 + title: Robust Estimation for Seemingly Unrelated Regression Models + maintainer: Claudio Agostinelli + description: Data sets are often corrupted by outliers. When data are multivariate + outliers can be classified as case-wise or cell-wise. The latters are particularly + challenge to handle. We implement a robust estimation procedure for Seemingly + Unrelated Regression Models which is able to cope well with both type of outliers. + Giovanni Saraceno, Fatemah Alqallaf, Claudio Agostinelli (2021) . + date_publication: '2021-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustsur + url_git: '' +robustvarComp: + version: 0.1-7 + title: Robust Estimation of Variance Component Models + maintainer: Claudio Agostinelli + description: Robust Estimation of Variance Component Models by classic and composite + robust procedures. The composite procedures are robust against outliers generated + by the Independent Contamination Model. + date_publication: '2022-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustvarComp + url_git: '' +robustX: + version: 1.2-7 + title: '''eXtra'' / ''eXperimental'' Functionality for Robust Statistics' + maintainer: Martin Maechler + description: |- + Robustness -- 'eXperimental', 'eXtraneous', or 'eXtraordinary' + Functionality for Robust Statistics. Hence methods which are not well established, + often related to methods in package 'robustbase'. Amazingly, 'BACON()', originally by + Billor, Hadi, and Velleman (2000) + has become established in places. The "barrow wheel" `rbwheel()` is from + Stahel and Mächler (2009) . + date_publication: '2023-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=robustX + url_git: '' +robvis: + version: 0.3.0 + title: Visualize the Results of Risk-of-Bias (ROB) Assessments + maintainer: Luke McGuinness + description: |- + Helps users in quickly visualizing risk-of-bias + assessments performed as part of a systematic review. It allows users to + create weighted bar-plots of the distribution of risk-of-bias judgments + within each bias domain, in addition to traffic-light plots of the + specific domain-level judgments for each study. The resulting figures are + of publication quality and are formatted according the risk-of-bias + assessment tool use to perform the assessments. Currently, the supported + tools are ROB2.0 (for randomized controlled trials; Sterne et al (2019) + ), ROBINS-I (for non-randomised studies of + interventions; Sterne et al (2016) ), and QUADAS-2 + (for diagnostic accuracy studies; Whiting et al (2011) + ). + date_publication: '2019-11-22' + bug_reports: https://github.com/mcguinlu/robvis + url: '' + url_cran: https://CRAN.R-project.org/package=robvis + url_git: https://github.com/mcguinlu/robvis +Robyn: + version: 3.11.1 + title: |- + Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing + Science + maintainer: Bernardo Lares + description: Semi-Automated Marketing Mix Modeling (MMM) aiming to reduce human + bias by means of ridge regression and evolutionary algorithms, enables actionable + decision making providing a budget allocation and diminishing returns curves and + allows ground-truth calibration to account for causation. + date_publication: '2024-06-27' + bug_reports: https://github.com/facebookexperimental/Robyn/issues + url: https://facebookexperimental.github.io/Robyn/ + url_cran: https://CRAN.R-project.org/package=Robyn + url_git: https://github.com/facebookexperimental/Robyn +ROCaggregator: + version: 1.0.1 + title: Aggregate Multiple ROC Curves into One Global ROC + maintainer: Pedro Mateus + description: |- + Aggregates multiple Receiver Operating Characteristic (ROC) curves + obtained from different sources into one global ROC. Additionally, it’s + also possible to calculate the aggregated precision-recall (PR) curve. + date_publication: '2021-08-10' + bug_reports: https://gitlab.com/UM-CDS/general-tools/rocaggregator/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ROCaggregator + url_git: https://gitlab.com/UM-CDS/general-tools/rocaggregator +rocbc: + version: 3.1.0 + title: |- + Statistical Inference for Box-Cox Based Receiver Operating + Characteristic Curves + maintainer: Benjamin Brewer + description: Generation of Box-Cox based ROC curves and several aspects of inferences + and hypothesis testing. Can be used when inferences for one biomarker (Bantis + LE, Nakas CT, Reiser B. (2018)) are of interest or + when comparisons of two correlated biomarkers (Bantis LE, Nakas CT, Reiser B. + (2021)) are of interest. Provides inferences and comparisons + around the AUC, the Youden index, the sensitivity at a given specificity level + (and vice versa), the optimal operating point of the ROC curve (in the Youden + sense), and the Youden based cutoff. + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rocbc + url_git: '' +rocc: + version: '1.3' + title: ROC Based Classification + maintainer: Martin Lauss + description: Functions for a classification method based on receiver operating characteristics + (ROC). Briefly, features are selected according to their ranked AUC value in the + training set. The selected features are merged by the mean value to form a meta-gene. + The samples are ranked by their meta-gene value and the meta-gene threshold that + has the highest accuracy in splitting the training samples is determined. A new + sample is classified by its meta-gene value relative to the threshold. In the + first place, the package is aimed at two class problems in gene expression data, + but might also apply to other problems. + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rocc + url_git: '' +roccv: + version: '1.2' + title: ROC for Cross Validation Results + maintainer: Ben Sherwood + description: Cross validate large genetic data while specifying clinical variables + that should always be in the model using the function cv(). An ROC plot from the + cross validation data with AUC can be obtained using rocplot(), which also can + be used to compare different models. Framework was built to handle genetic data, + but works for any data. + date_publication: '2019-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roccv + url_git: '' +rOCEAN: + version: '1.0' + title: Two-Way Feature Set Testing for Multi-Omics + maintainer: Mitra Ebrahimpoor + description: For any two way feature-set from a pair of pre-processed omics data, + 3 different true discovery proportions (TDP), namely pairwise-TDP, column-TDP + and row-TDP are calculated. Due to embedded closed testing procedure, the choice + of feature-sets can be changed infinite times and even after seeing the data without + any change in type I error rate. For more details refer to Ebrahimpoor et al., + (2024) . + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rOCEAN + url_git: '' +ROCFTP.MMS: + version: 1.0.0 + title: Perfect Sampling + maintainer: Majid Nabipoor + description: The algorithm provided in this package generates perfect sample for + unimodal or multimodal posteriors. Read Once Coupling From The Past, with Metropolis-Multishift + is used to generate a perfect sample for a given posterior density based on the + two extreme starting paths, minimum and maximum of the most interest range of + the posterior. It uses the monotone random operation of multishift coupler which + allows to sandwich all of the state space in one point. It means both Markov Chains + starting from the maximum and minimum will be coalesced. The generated sample + is independent from the starting points. It is useful for mixture distributions + too. The output of this function is a real value as an exact draw from the posterior + distribution. + date_publication: '2022-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROCFTP.MMS + url_git: https://github.com/nabipoor/ROCFTP.MMS +ROCit: + version: 2.1.2 + title: Performance Assessment of Binary Classifier with Visualization + maintainer: Md Riaz Ahmed Khan + description: Sensitivity (or recall or true positive rate), false positive rate, + specificity, precision (or positive predictive value), negative predictive value, + misclassification rate, accuracy, F-score- these are popular metrics for assessing + performance of binary classifier for certain threshold. These metrics are calculated + at certain threshold values. Receiver operating characteristic (ROC) curve is + a common tool for assessing overall diagnostic ability of the binary classifier. + Unlike depending on a certain threshold, area under ROC curve (also known as AUC), + is a summary statistic about how well a binary classifier performs overall for + the classification task. ROCit package provides flexibility to easily evaluate + threshold-bound metrics. Also, ROC curve, along with AUC, can be obtained using + different methods, such as empirical, binormal and non-parametric. ROCit encompasses + a wide variety of methods for constructing confidence interval of ROC curve and + AUC. ROCit also features the option of constructing empirical gains table, which + is a handy tool for direct marketing. The package offers options for commonly + used visualization, such as, ROC curve, KS plot, lift plot. Along with in-built + default graphics setting, there are rooms for manual tweak by providing the necessary + values as function arguments. ROCit is a powerful tool offering a range of things, + yet it is very easy to use. + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROCit + url_git: '' +rock: + version: 0.8.1 + title: Reproducible Open Coding Kit + maintainer: Gjalt-Jorn Peters + description: |- + The Reproducible Open Coding Kit ('ROCK', and this package, 'rock') + was developed to facilitate reproducible and open coding, specifically + geared towards qualitative research methods. Although it is a + general-purpose toolkit, three specific applications have been + implemented, specifically an interface to the 'rENA' package that + implements Epistemic Network Analysis ('ENA'), means to process notes + from Cognitive Interviews ('CIs'), and means to work with decentralized + construct taxonomies ('DCTs'). The 'ROCK' and this 'rock' package are described + in the ROCK book and more information, such as tutorials, + is available at . + date_publication: '2024-01-21' + bug_reports: https://gitlab.com/r-packages/rock/-/issues + url: https://rock.opens.science + url_cran: https://CRAN.R-project.org/package=rock + url_git: '' +rockchalk: + version: 1.8.157 + title: Regression Estimation and Presentation + maintainer: Paul E. Johnson + description: |- + A collection of functions for interpretation and presentation + of regression analysis. These functions are used + to produce the statistics lectures in + . Includes regression + diagnostics, regression tables, and plots of interactions and + "moderator" variables. The emphasis is on "mean-centered" and + "residual-centered" predictors. The vignette 'rockchalk' offers a + fairly comprehensive overview. The vignette 'Rstyle' has advice + about coding in R. The package title 'rockchalk' refers to our + school motto, 'Rock Chalk Jayhawk, Go K.U.'. + date_publication: '2022-08-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rockchalk + url_git: '' +rocker: + version: 0.3.1 + title: Database Interface Class + maintainer: Nikolaus Pawlowski + description: |- + 'R6' class interface for handling relational database connections using 'DBI' package as backend. + The class allows handling of connections to e.g. PostgreSQL, MariaDB and SQLite. + The purpose is having an intuitive object allowing straightforward handling of SQL databases. + date_publication: '2022-08-20' + bug_reports: https://github.com/nikolaus77/rocker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rocker + url_git: https://github.com/nikolaus77/rocker +ROCket: + version: 1.0.1 + title: Simple and Fast ROC Curves + maintainer: Daniel Lazar + description: |- + A set of functions for receiver operating characteristic (ROC) curve + estimation and area under the curve (AUC) calculation. + All functions are designed to work with aggregated data; + nevertheless, they can also handle raw samples. + In 'ROCket', we distinguish two types of ROC curve representations: + 1) parametric curves - the true positive rate (TPR) and the false positive rate (FPR) + are functions of a parameter (the score), + 2) functions - TPR is a function of FPR. + There are several ROC curve estimation methods available. An introduction to + the mathematical background of the implemented methods (and much more) can be found in + de Zea Bermudez, Gonçalves, Oliveira & Subtil (2014) + and Cai & Pepe (2004) . + date_publication: '2021-02-17' + bug_reports: https://github.com/da-zar/ROCket/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ROCket + url_git: https://github.com/da-zar/ROCket +RockFab: + version: 1.2.1 + title: Rock Fabric and Strain Analysis Tools + maintainer: Jeffrey R. Webber + description: Provides functions to complete three-dimensional rock fabric and strain + analyses following the Rf Phi, Fry, and normalized Fry methods. Also allows for + plotting of results and interactive 3D visualization functionality. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RockFab + url_git: '' +rockr: + version: 1.0.0 + title: '''Rock'' R Server Client' + maintainer: Yannick Marcon + description: |- + Connector to the REST API of a 'Rock' R server, to perform operations + on a remote R server session, or administration tasks. See 'Rock' documentation at + . + date_publication: '2021-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rockr + url_git: '' +rockx: + version: 0.1.0 + title: Easily Import Data from Your 'ODK-X Sync Endpoint' + maintainer: Emil Rossing + description: Provides helper functions for authenticating and retrieving data from + your 'ODK-X Sync Endpoint'. This is an early release intended for testing and + feedback. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rockx + url_git: '' +roclang: + version: 0.2.2 + title: |- + Functions for Diffusing Function Documentations into 'Roxygen' + Comments + maintainer: Xiurui Zhu + description: Efficient diffusing of content across function documentations. Sections, + parameters or dot parameters are extracted from function documentations and turned + into valid Rd character strings, which are ready to diffuse into the 'roxygen' + comments of another function by inserting inline code. + date_publication: '2023-05-26' + bug_reports: https://github.com/zhuxr11/roclang/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roclang + url_git: https://github.com/zhuxr11/roclang +rocNIT: + version: '1.0' + title: Non-Inferiority Test for Paired ROC Curves + maintainer: Zhicheng Du + description: |2- + + Non-inferiority test and diagnostic test are very important in clinical trails. + This package is to get a p value from the non-inferiority test for ROC curves from diagnostic test. + date_publication: '2016-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rocNIT + url_git: '' +rocnp: + version: 0.1.0 + title: Work with Romanian Personal Numeric Codes PNC / CNP + maintainer: Dragoș Moldovan-Grünfeld + description: |- + A set of tools for working with Romanian personal numeric codes. + The core is a validation function which applies several verification + criteria to assess the validity of numeric codes. This is accompanied by + functionality for extracting the different components of a personal numeric + code. A personal numeric code is issued to all Romanian residents either at + birth or when they obtain a residence permit. + date_publication: '2021-11-05' + bug_reports: https://github.com/dragosmg/rocnp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rocnp + url_git: https://github.com/dragosmg/rocnp +ROCnReg: + version: 1.0-9 + title: ROC Curve Inference with and without Covariates + maintainer: Maria Xose Rodriguez-Alvarez + description: Estimates the pooled (unadjusted) Receiver Operating Characteristic + (ROC) curve, the covariate-adjusted ROC (AROC) curve, and the covariate-specific/conditional + ROC (cROC) curve by different methods, both Bayesian and frequentist. Also, it + provides functions to obtain ROC-based optimal cutpoints utilizing several criteria. + Based on Erkanli, A. et al. (2006) ; Faraggi, D. (2003) + ; Gu, J. et al. (2008) ; Inacio + de Carvalho, V. et al. (2013) ; Inacio de Carvalho, V., + and Rodriguez-Alvarez, M.X. (2022) ; Janes, H., and Pepe, + M.S. (2009) ; Pepe, M.S. (1998) ; + Rodriguez-Alvarez, M.X. et al. (2011a) ; Rodriguez-Alvarez, + M.X. et al. (2011a) . Please see Rodriguez-Alvarez, + M.X. and Inacio, V. (2021) for more details. + date_publication: '2024-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROCnReg + url_git: '' +rococo: + version: 1.1.9 + title: Robust Rank Correlation Coefficient and Test + maintainer: Ulrich Bodenhofer + description: |- + Provides the robust gamma rank correlation coefficient as introduced by + Bodenhofer, Krone, and Klawonn (2013) + along with a permutation-based rank correlation test. + The rank correlation coefficient and the test are explicitly + designed for dealing with noisy numerical data. + date_publication: '2024-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rococo + url_git: https://github.com/UBod/rococo +ROCpsych: + version: '1.3' + title: Compute and Compare Diagnostic Test Statistics Across Groups + maintainer: Shenghai Dai + description: Functions for (1) computing diagnostic test statistics (sensitivity, + specificity, etc.) from confusion matrices with adjustment for various base rates + or known prevalence based on McCaffrey et al (2003) , + (2) computing optimal cut-off scores with different criteria including maximizing + sensitivity, maximizing specificity, and maximizing the Youden Index from Youden + (1950) , + and (3) displaying and comparing classification statistics and area under the + receiver operating characteristic (ROC) curves or area under the curves (AUC) + across consecutive categories for ordinal variables. + date_publication: '2020-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROCpsych + url_git: '' +ROCR: + version: 1.0-11 + title: Visualizing the Performance of Scoring Classifiers + maintainer: Felix G.M. Ernst + description: |- + ROC graphs, sensitivity/specificity curves, lift charts, + and precision/recall plots are popular examples of trade-off + visualizations for specific pairs of performance measures. ROCR is a + flexible tool for creating cutoff-parameterized 2D performance curves + by freely combining two from over 25 performance measures (new + performance measures can be added using a standard interface). + Curves from different cross-validation or bootstrapping runs can be + averaged by different methods, and standard deviations, standard + errors or box plots can be used to visualize the variability across + the runs. The parameterization can be visualized by printing cutoff + values at the corresponding curve positions, or by coloring the + curve according to cutoff. All components of a performance plot can + be quickly adjusted using a flexible parameter dispatching + mechanism. Despite its flexibility, ROCR is easy to use, with only + three commands and reasonable default values for all optional + parameters. + date_publication: '2020-05-02' + bug_reports: https://github.com/ipa-tys/ROCR/issues + url: http://ipa-tys.github.io/ROCR/ + url_cran: https://CRAN.R-project.org/package=ROCR + url_git: '' +ROCSI: + version: 0.1.0 + title: Receiver Operating Characteristic Based Signature Identification + maintainer: Xin Huang + description: Optimal linear combination predictive signatures for maximizing the + area between two Receiver Operating Characteristic (ROC) curves (treatment vs. + control). + date_publication: '2022-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROCSI + url_git: '' +ROCsurf: + version: 0.1.1 + title: ROC Surface Analysis Under the Three-Class Problems + maintainer: Ertan Akgenç + description: Receiver Operating Characteristic (ROC) analysis is performed assuming + samples are from the proposed distributions. In addition, the volume under the + ROC surface and true positive fractions values are evaluated by ROC surface analysis. + date_publication: '2024-07-24' + bug_reports: https://github.com/ErtanSU/ROCsurf/issues + url: https://ertansu.github.io/ROCsurf/ + url_cran: https://CRAN.R-project.org/package=ROCsurf + url_git: https://github.com/ErtanSU/ROCsurf +rocsvm.path: + version: 0.1.0 + title: The Entire Solution Paths for ROC-SVM + maintainer: Seung Jun Shin + description: 'We develop the entire solution paths for ROC-SVM presented by Rakotomamonjy. + The ROC-SVM solution path algorithm greatly facilitates the tuning procedure for + regularization parameter, lambda in ROC-SVM by avoiding grid search algorithm + which may be computationally too intensive. For more information on the ROC-SVM, + see the report in the ROC Analysis in AI workshop(ROCAI-2004) : Hernàndez-Orallo, + José, et al. (2004) .' + date_publication: '2018-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rocsvm.path + url_git: '' +rocTree: + version: 1.1.1 + title: |- + Receiver Operating Characteristic (ROC)-Guided Classification + and Survival Tree + maintainer: Sy Han Chiou + description: Receiver Operating Characteristic (ROC)-guided survival trees and ensemble + algorithms are implemented, providing a unified framework for tree-structured + analysis with censored survival outcomes. A time-invariant partition scheme on + the survivor population was considered to incorporate time-dependent covariates. + Motivated by ideas of randomized tests, generalized time-dependent ROC curves + were used to evaluate the performance of survival trees and establish the optimality + of the target hazard/survival function. The optimality of the target hazard function + motivates us to use a weighted average of the time-dependent area under the curve + (AUC) on a set of time points to evaluate the prediction performance of survival + trees and to guide splitting and pruning. A detailed description of the implemented + methods can be found in Sun et al. (2019) . + date_publication: '2020-08-01' + bug_reports: http://github.com/stc04003/rocTree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rocTree + url_git: http://github.com/stc04003/rocTree +RODBC: + version: 1.3-26 + title: ODBC Database Access + maintainer: Brian Ripley + description: An ODBC database interface. + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RODBC + url_git: '' +RODBCDBI: + version: 0.1.1 + title: Provides Access to Databases Through the ODBC Interface + maintainer: Nagi Teramo + description: |- + An implementation of R's DBI interface using ODBC package as a + back-end. This allows R to connect to any DBMS that has a ODBC driver. + date_publication: '2016-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RODBCDBI + url_git: '' +rodd: + version: 0.2-1 + title: Optimal Discriminating Designs + maintainer: Roman Guchenko + description: A collection of functions for numerical construction of optimal discriminating + designs. At the current moment T-optimal designs (which maximize the lower bound + for the power of F-test for regression model discrimination), KL-optimal designs + (for lognormal errors) and their robust analogues can be calculated with the package. + date_publication: '2016-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rodd + url_git: '' +rODE: + version: 0.99.6 + title: |- + Ordinary Differential Equation (ODE) Solvers Written in R Using + S4 Classes + maintainer: Alfonso R. Reyes + description: |- + Show physics, math and engineering students how an ODE solver + is made and how effective R classes can be for the construction of + the equations that describe natural phenomena. Inspiration for this work + comes from the book on "Computer Simulations in Physics" + by Harvey Gould, Jan Tobochnik, and Wolfgang Christian. + Book link: . + date_publication: '2017-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rODE + url_git: https://github.com/f0nzie/rODE +rodeo: + version: 0.8.2 + title: A Code Generator for ODE-Based Models + maintainer: David Kneis + description: |- + Provides an R6 class and several utility methods to + facilitate the implementation of models based on ordinary + differential equations. The heart of the package is a code generator + that creates compiled 'Fortran' (or 'R') code which can be passed to + a numerical solver. There is direct support for solvers contained + in packages 'deSolve' and 'rootSolve'. + date_publication: '2024-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rodeo + url_git: https://github.com/dkneis/rodeo +rofanova: + version: 1.0.0 + title: Robust Functional Analysis of Variance + maintainer: Fabio Centofanti + description: |- + Implements the robust functional analysis of variance (RoFANOVA), described in Centofanti et al. (2021) . + It allows testing mean differences among groups of functional data by being robust against the presence of outliers. + date_publication: '2022-01-21' + bug_reports: https://github.com/unina-sfere/rofanova/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rofanova + url_git: https://github.com/unina-sfere/rofanova +roger: + version: 1.5-1 + title: Automated Grading of R Scripts + maintainer: Vincent Goulet + description: |- + Tools for grading the coding style and documentation of R + scripts. This is the R component of Roger the Omni Grader, an + automated grading system for computer programming projects based on + Unix shell scripts; see . The + package also provides an R interface to the shell scripts. Inspired by + the lintr package. + date_publication: '2023-10-24' + bug_reports: https://gitlab.com/roger-project/roger-rpkg/-/issues + url: https://roger-project.gitlab.io + url_cran: https://CRAN.R-project.org/package=roger + url_git: '' +Rogue: + version: 2.1.6 + title: Identify Rogue Taxa in Sets of Phylogenetic Trees + maintainer: Martin R. Smith + description: |- + Rogue ("wildcard") taxa are leaves with uncertain phylogenetic + position. + Their position may vary from tree to tree under inference methods that yield a + tree set (e.g. bootstrapping, Bayesian tree searches, maximum parsimony). + The presence of rogue taxa in a tree set can potentially remove all + information from a consensus tree. The information content of a consensus + tree - a function of its resolution and branch support values - can often be + increased by removing rogue taxa. + 'Rogue' provides an explicitly information-theoretic approach to rogue + detection (Smith 2022) , + and an interface to 'RogueNaRok' (Aberer et al. 2013) + . + date_publication: '2023-11-29' + bug_reports: https://github.com/ms609/Rogue/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=Rogue + url_git: https://github.com/ms609/Rogue/ +ROI: + version: 1.0-1 + title: R Optimization Infrastructure + maintainer: Stefan Theussl + description: |- + The R Optimization Infrastructure ('ROI') + is a sophisticated framework for handling optimization problems in R. + Additional information can be found on the 'ROI' homepage . + date_publication: '2023-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI + url_git: https://roi.r-forge.r-project.org/ +ROI.models.globalOptTests: + version: 1.1-2 + title: '''ROI'' Optimization Problems Based on ''globalOptTests''' + maintainer: Florian Schwendinger + description: |- + A collection of non-linear optimization problems with box bounds + transformed into 'ROI' optimization problems. + This package provides a wrapper around the 'globalOptTests' + which provides a collection of global optimization problems. + More information can be found in the 'README' file. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.models.globalOptTests + url_git: '' +ROI.models.miplib: + version: 1.0-0 + title: '''ROI'' Access to ''MIPLIB'' 2010 Benchmark Instances' + maintainer: Florian Schwendinger + description: |- + The mixed integer programming library 'MIPLIB' (see ) + is commonly used to compare the performance of mixed integer optimization solvers. + This package provides functions to access 'MIPLIB' from the + 'R' Optimization Infrastructure ('ROI'). More information about 'MIPLIB' + can be found in the paper by Koch et al. available at + . + The 'README.md' file illustrates how to use this package. + date_publication: '2020-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.models.miplib + url_git: http://R-Forge.R-project.org/projects/roi +ROI.models.netlib: + version: 1.1-2 + title: '''ROI'' Optimization Problems Based on ''NETLIB-LP''' + maintainer: Florian Schwendinger + description: |- + A collection of 'ROI' optimization problems based on the 'NETLIB-LP' collection. + 'Netlib' is a software repository, which amongst many other software for scientific computing contains a collection of linear programming problems. The purpose of this package is to make + this problems easily accessible from 'R' as 'ROI' optimization problems. + date_publication: '2023-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.models.netlib + url_git: '' +ROI.plugin.alabama: + version: 1.0-2 + title: '''alabama'' Plug-in for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the R Optimization Infrastructure ('ROI') package + with the 'alabama' solver for solving nonlinear optimization problems. + date_publication: '2023-07-07' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.alabama + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.alabama +ROI.plugin.clarabel: + version: '0.3' + title: '''clarabel'' Plug-in for the ''R'' Optimization Infrastructure' + maintainer: Benjamin Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the 'clarabel' solver for solving convex cone problems. + More information about 'clarabel' can be found at + . + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.clarabel + url_git: https://gitlab.com/roigrp/solver/roi.plugin.clarabel +ROI.plugin.cplex: + version: 0.3-0 + title: ROI Plug-in CPLEX + maintainer: Stefan Theussl + description: |- + Enhances the R Optimization Infrastructure (ROI) package by registering + the 'CPLEX' commercial solver. It allows for solving mixed integer quadratically + constrained programming (MIQPQC) problems as well as all + variants/combinations of LP, QP, QCP, IP. + date_publication: '2017-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.cplex + url_git: http://R-Forge.R-project.org/projects/roi +ROI.plugin.deoptim: + version: 1.0-2 + title: |- + 'DEoptim' and 'DEoptimR' Plugin for the 'R' Optimization + Interface + maintainer: Florian Schwendinger + description: |- + Enhances the R Optimization Infrastructure ('ROI') package + with the 'DEoptim' and 'DEoptimR' package. 'DEoptim' is + used for unconstrained optimization and 'DEoptimR' for + constrained optimization. + date_publication: '2023-07-25' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.deoptim + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.deoptim +ROI.plugin.ecos: + version: 1.0-2 + title: '''ECOS'' Plugin for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the Embedded Conic Solver ('ECOS') for solving conic optimization problems. + date_publication: '2023-07-06' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.ecos + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.ecos +ROI.plugin.glpk: + version: 1.0-0 + title: '''ROI'' Plug-in ''GLPK''' + maintainer: Stefan Theussl + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package by registering + the free 'GLPK' solver. It allows for solving mixed integer linear programming ('MILP') + problems as well as all variants/combinations of 'LP', 'IP'. + date_publication: '2020-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.glpk + url_git: http://roi.r-forge.r-project.org/ +ROI.plugin.highs: + version: 1.0-3 + title: '''HiGHS'' Plugin for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the quadratic solver 'HiGHS'. More information about + 'HiGHS' can be found at . + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.highs + url_git: '' +ROI.plugin.ipop: + version: 1.0-0 + title: '''ipop'' Plug-in for the ''R'' Optimization Interface' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + by registering the 'ipop' solver from package 'kernlab'. + date_publication: '2020-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.ipop + url_git: http://roi.r-forge.r-project.org/ +ROI.plugin.lpsolve: + version: 1.0-2 + title: '''lp_solve'' Plugin for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the 'lp_solve' solver. + date_publication: '2023-07-07' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.lpsolve + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.lpsolve +ROI.plugin.msbinlp: + version: 1.0-1 + title: |- + 'Multi-Solution' Binary Linear Problem Plug-in for the 'R' + Optimization Interface + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the possibility to obtain multiple solutions for linear + problems with binary variables. The main function is copied + (with small modifications) from the relations package. + date_publication: '2023-07-07' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.msbinlp + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.msbinlp +ROI.plugin.neos: + version: 1.0-2 + title: '''NEOS'' Plug-in for the ''R'' Optimization Interface' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with a connection to the 'neos' server. 'ROI' optimization + problems can be directly be sent to the 'neos' server + and solution obtained in the typical 'ROI' style. + date_publication: '2023-11-25' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.neos + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.neos +ROI.plugin.nloptr: + version: 1.0-1 + title: '''nloptr'' Plug-in for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the R Optimization Infrastructure ('ROI') package + with the 'NLopt' solver for solving nonlinear optimization problems. + date_publication: '2023-07-06' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.nloptr + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.nloptr +ROI.plugin.optimx: + version: 1.0-1 + title: '''optimx'' Plug-in for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the R Optimization Infrastructure ('ROI') package + with the 'optimx' package. + date_publication: '2023-07-06' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.optimx + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.optimx +ROI.plugin.osqp: + version: 1.0-2 + title: '''osqp'' Plugin for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the quadratic solver 'OSQP'. More information about + 'OSQP' can be found at . + date_publication: '2024-07-18' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.osqp + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.osqp +ROI.plugin.qpoases: + version: 1.0-3 + title: '''qpOASES'' Plugin for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the quadratic solver 'qpOASES'. More information about + 'qpOASES' can be found at . + date_publication: '2023-07-07' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.qpoases + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.qpoases +ROI.plugin.quadprog: + version: 1.0-1 + title: '''quadprog'' Plug-in for the ''R'' Optimization Infrastructure' + maintainer: Stefan Theussl + description: |- + Enhances the R Optimization Infrastructure ('ROI') package + by registering the 'quadprog' solver. It allows for solving quadratic programming (QP) + problems. + date_publication: '2023-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.quadprog + url_git: http://roi.r-forge.r-project.org/ +ROI.plugin.scs: + version: 1.1-2 + title: '''SCS'' Plug-in for the ''R'' Optimization Infrastructure' + maintainer: Florian Schwendinger + description: |- + Enhances the 'R' Optimization Infrastructure ('ROI') package + with the 'SCS' solver for solving convex cone problems. + date_publication: '2023-07-07' + bug_reports: '' + url: https://roigrp.gitlab.io + url_cran: https://CRAN.R-project.org/package=ROI.plugin.scs + url_git: https://gitlab.com/roigrp/solver/ROI.plugin.scs +ROI.plugin.symphony: + version: 1.0-0 + title: '''SYMPHONY'' Plug-in for the ''R'' Optimization Interface' + maintainer: Stefan Theussl + description: |- + Enhances the R Optimization Infrastructure ('ROI') package by registering + the 'SYMPHONY' open-source solver from the COIN-OR suite. It allows for + solving mixed integer linear programming (MILP) problems as well as all + variants/combinations of LP, IP. + date_publication: '2020-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROI.plugin.symphony + url_git: http://roi.r-forge.r-project.org/ +rolap: + version: 2.5.1 + title: Obtaining Star Databases from Flat Tables + maintainer: Jose Samos + description: |- + Data in multidimensional systems is obtained from operational + systems and is transformed to adapt it to the new structure. + Frequently, the operations to be performed aim to transform a flat + table into a ROLAP (Relational On-Line Analytical Processing) star + database. The main objective of the package is to allow the definition + of these transformations easily. The implementation of the + multidimensional database obtained can be exported to work with + multidimensional analysis tools on spreadsheets or relational + databases. + date_publication: '2024-01-10' + bug_reports: https://github.com/josesamos/rolap/issues + url: https://josesamos.github.io/rolap/ + url_cran: https://CRAN.R-project.org/package=rolap + url_git: https://github.com/josesamos/rolap +roll: + version: 1.1.7 + title: Rolling and Expanding Statistics + maintainer: Jason Foster + description: Fast and efficient computation of rolling and expanding statistics + for time-series data. + date_publication: '2024-04-05' + bug_reports: https://github.com/jasonjfoster/roll/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roll + url_git: https://github.com/jasonjfoster/roll +rollama: + version: 0.2.0 + title: Communicate with 'Ollama' to Run Large Language Models Locally + maintainer: Johannes B. Gruber + description: |- + Wraps the 'Ollama' API, which can be used to + communicate with generative large language models locally. + date_publication: '2024-12-06' + bug_reports: https://github.com/JBGruber/rollama/issues + url: https://jbgruber.github.io/rollama/ + url_cran: https://CRAN.R-project.org/package=rollama + url_git: https://github.com/JBGruber/rollama +rollbar: + version: 0.1.0 + title: Error Tracking and Logging + maintainer: Andrew Kane + description: Reports errors and messages to Rollbar, the error tracking platform + . + date_publication: '2016-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rollbar + url_git: '' +rolldown: + version: '0.1' + title: R Markdown Output Formats for Storytelling + maintainer: Yihui Xie + description: |- + R Markdown output formats based on JavaScript libraries such as + 'Scrollama' () for storytelling. + date_publication: '2019-07-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rolldown + url_git: '' +rollinglda: + version: 0.1.3 + title: Construct Consistent Time Series from Textual Data + maintainer: Jonas Rieger + description: A rolling version of the Latent Dirichlet Allocation, see Rieger et + al. (2021) . By a sequential approach, + it enables the construction of LDA-based time series of topics that are consistent + with previous states of LDA models. After an initial modeling, updates can be + computed efficiently, allowing for real-time monitoring and detection of events + or structural breaks. + date_publication: '2023-11-28' + bug_reports: https://github.com/JonasRieger/rollinglda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rollinglda + url_git: https://github.com/JonasRieger/rollinglda +rollmatch: + version: 2.0.3 + title: Rolling Entry Matching + maintainer: Rob Chew + description: Functions to perform propensity score matching on rolling entry interventions + for which a suitable "entry" date is not observed for nonparticipants. For more + details, please reference Witman et al. (2018) . + date_publication: '2024-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rollmatch + url_git: https://github.com/RTIInternational/rollmatch +rollup: + version: 0.1.0 + title: A Tidy Grouping Set Aggregation + maintainer: Ju Young Ahn + description: A Tidy implementation of 'grouping sets', 'rollup' and 'cube' - extensions + of the 'group_by' clause that allow for computing multiple 'group_by' clauses + in a single statement. For more detailed information on these functions, please + refer to "Enhanced Aggregation, Cube, Grouping and Rollup" . + date_publication: '2024-08-29' + bug_reports: '' + url: https://juyoungahn.github.io/rollup/ + url_cran: https://CRAN.R-project.org/package=rollup + url_git: '' +rollupTree: + version: 0.2.0 + title: Perform Recursive Computations + maintainer: James Steven Jenkins + description: Mass rollup for a Bill of Materials is an example of a class of computations + in which elements are arranged in a tree structure and some property of each element + is a computed function of the corresponding values of its child elements. Leaf + elements, i.e., those with no children, have values assigned. In many cases, the + combining function is simple arithmetic sum; in other cases (e.g., mass properties), + the combiner may involve other information such as the geometric relationship + between parent and child, or statistical relations such as root-sum-of-squares + (RSS). This package implements a general function for such problems. It is adapted + to specific recursive computations by functional programming techniques; the caller + passes a function as the update parameter to rollup() (or, at a lower level, passes + functions as the get, set, combine, and override parameters to update_prop()) + at runtime to specify the desired operations. The implementation relies on graph-theoretic + algorithms from the 'igraph' package of Csárdi, et al. (2006 ). + date_publication: '2025-02-04' + bug_reports: https://github.com/jsjuni/rollupTree/issues + url: https://jsjuni.github.io/rollupTree/ + url_cran: https://CRAN.R-project.org/package=rollupTree + url_git: https://github.com/jsjuni/rollupTree +roloc: + version: 0.1-2 + title: Convert Colour Specification to Colour Name + maintainer: Paul Murrell + description: Functions to convert an R colour specification to a colour name. The + user can select and create different lists of colour names and different colour + metrics for the conversion. + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roloc + url_git: '' +rolocISCCNBS: + version: '0.1' + title: |- + A Colour List and Colour Metric Based on the ISCC-NBS System of + Color Designation + maintainer: Paul Murrell + description: A colour list and colour metric based on the ISCC-NBS System of Color + Designation for use with the 'roloc' package for converting colour specifications + to colour names. + date_publication: '2018-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rolocISCCNBS + url_git: '' +rolog: + version: 0.9.20 + title: Query 'SWI'-'Prolog' from R + maintainer: Matthias Gondan + description: This R package connects to SWI-Prolog, , + so that R can send deterministic and non-deterministic queries to prolog (consult, + query/submit, once, findall). + date_publication: '2025-02-15' + bug_reports: https://github.com/mgondan/rolog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rolog + url_git: https://github.com/mgondan/rolog +ROlogit: + version: 0.1.2 + title: Fit Rank-Ordered Logit (RO-Logit) Model + maintainer: Ning Yilin + description: |- + Implements the rank-ordered logit (RO-logit) model for stratified + analysis of continuous outcomes introduced by + Tan et al. (2017) . Model diagnostics based on + the heuristic residuals and estimates in linear scales are available from + the package, and outcomes with ties are supported. + date_publication: '2018-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROlogit + url_git: '' +rolr: + version: 1.0.0 + title: Finding Optimal Three-Group Splits Based on a Survival Outcome + maintainer: Pingping Qu + description: |- + Provides fast procedures for exploring all pairs of + cutpoints of a single covariate with respect to survival and determining + optimal cutpoints using a hierarchical method and various ordered logrank tests. + date_publication: '2017-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rolr + url_git: '' +RolWinMulCor: + version: 1.2.0 + title: Subroutines to Estimate Rolling Window Multiple Correlation + maintainer: Josue M. Polanco-Martinez + description: 'Rolling Window Multiple Correlation (''RolWinMulCor'') estimates the + rolling (running) window correlation for the bi- and multi-variate cases between + regular (sampled on identical time points) time series, with especial emphasis + to ecological data although this can be applied to other kinds of data sets. ''RolWinMulCor'' + is based on the concept of rolling, running or sliding window and is useful to + evaluate the evolution of correlation through time and time-scales. ''RolWinMulCor'' + contains six functions. The first two focus on the bi-variate case: (1) rolwincor_1win() + and (2) rolwincor_heatmap(), which estimate the correlation coefficients and the + their respective p-values for only one window-length (time-scale) and considering + all possible window-lengths or a band of window-lengths, respectively. The second + two functions: (3) rolwinmulcor_1win() and (4) rolwinmulcor_heatmap() are designed + to analyze the multi-variate case, following the bi-variate case to visually display + the results, but these two approaches are methodologically different. That is, + the multi-variate case estimates the adjusted coefficients of determination instead + of the correlation coefficients. The last two functions: (5) plot_1win() and (6) + plot_heatmap() are used to represent graphically the outputs of the four aforementioned + functions as simple plots or as heat maps. The functions contained in ''RolWinMulCor'' + are highly flexible since these contains several parameters to control the estimation + of correlation and the features of the plot output, e.g. to remove the (linear) + trend contained in the time series under analysis, to choose different p-value + correction methods (which are used to address the multiple comparison problem) + or to personalise the plot outputs. The ''RolWinMulCor'' package also provides + examples with synthetic and real-life ecological time series to exemplify its + use. Methods derived from H. Abdi. (2007) , + R. Telford (2013) , and J. M. Polanco-Martinez (2020) .' + date_publication: '2021-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RolWinMulCor + url_git: '' +RolWinWavCor: + version: 0.4.0 + title: |- + Estimate Rolling Window Wavelet Correlation Between Two Time + Series + maintainer: Josué M. Polanco-Martínez + description: Estimates and plots as a heat map the rolling window wavelet correlation + (RWWC) coefficients statistically significant (within the 95% CI) between two + regular (evenly spaced) time series. 'RolWinWavCor' also plots at the same graphic + the time series under study. The 'RolWinWavCor' was designed for financial time + series, but this software can be used with other kinds of data (e.g., climatic, + ecological, geological, etc). The functions contained in 'RolWinWavCor' are highly + flexible since these contains some parameters to personalize the time series under + analysis and the heat maps of the rolling window wavelet correlation coefficients. + Moreover, we have also included a data set (named EU_stock_markets) that contains + nine European stock market indices to exemplify the use of the functions contained + in 'RolWinWavCor'. Methods derived from Polanco-Martínez et al (2018) ). + date_publication: '2023-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RolWinWavCor + url_git: '' +ROMDB: + version: 0.1.0 + title: Get 'OMDB' API Multiple Information + maintainer: Alberto Almuiña + description: 'Load multiple movies, series, actors, directors etc from ''OMDB'' + API. More information in: .' + date_publication: '2020-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROMDB + url_git: https://github.com/AlbertoAlmuinha/ROMDB +romic: + version: 1.1.3 + title: R for High-Dimensional Omic Data + maintainer: Sean Hackett + description: Represents high-dimensional data as tables of features, samples and + measurements, and a design list for tracking the meaning of individual variables. + Using this format, filtering, normalization, and other transformations of a dataset + can be carried out in a flexible manner. 'romic' takes advantage of these transformations + to create interactive 'shiny' apps for exploratory data analysis such as an interactive + heatmap. + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=romic + url_git: '' +RonFHIR: + version: 0.4.0 + title: Read and Search Interface to the 'HL7 FHIR' REST API + maintainer: Sander Laverman + description: R on FHIR is an easy to use wrapper around the 'HL7 FHIR' REST API + (STU 3 and R4). It provides tools to easily read and search resources on a FHIR + server and brings the results into the R environment. R on FHIR is based on the + FhirClient of the official 'HL7 FHIR .NET API', also made by Firely. + date_publication: '2020-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RonFHIR + url_git: '' +Rook: + version: '1.2' + title: HTTP Web Server for R + maintainer: Evan Biederstedt + description: An HTTP web server for R with a documented API to interface between + R and the server. The documentation contains the Rook specification and details + for building and running Rook applications. To get started, be sure and read the + 'Rook' help file first. + date_publication: '2022-11-07' + bug_reports: https://github.com/evanbiederstedt/rook/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rook + url_git: https://github.com/evanbiederstedt/rook +ROOPSD: + version: 0.3.9 + title: R Object Oriented Programming for Statistical Distribution + maintainer: Yoann Robin + description: |- + Statistical distribution in OOP (Object Oriented Programming) way. + This package proposes a R6 class interface to classic statistical + distribution, and new distributions can be easily added with the + class AbstractDist. A useful point is the generic fit() method for + each class, which uses a maximum likelihood estimation to find the + parameters of a dataset, see, e.g. Hastie, T. and al (2009) + . Furthermore, the rv_histogram class + gives a non-parametric fit, with the same accessors that for the + classic distribution. Finally, three random generators useful to + build synthetic data are given: a multivariate normal generator, an + orthogonal matrix generator, and a symmetric positive definite + matrix generator, see Mezzadri, F. (2007) + . + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROOPSD + url_git: https://github.com/yrobink/ROOPSD +roots: + version: '1.0' + title: Reconstructing Ordered Ontogenic Trajectories + maintainer: Wajid Jawaid + description: |- + A set of tools to reconstruct ordered ontogenic trajectories from + single cell RNAseq data. + date_publication: '2017-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roots + url_git: '' +RootsExtremaInflections: + version: 1.2.1 + title: Finds Roots, Extrema and Inflection Points of a Curve + maintainer: Demetris T. Christopoulos + description: |- + Implementation of Taylor Regression Estimator (TRE), + Tulip Extreme Finding Estimator (TEFE), Bell Extreme Finding Estimator (BEFE), + Integration Extreme Finding Estimator (IEFE) and + Integration Root Finding Estimator (IRFE) for roots, extrema and inflections of a curve . + Christopoulos, DT (2019) . + Christopoulos, DT (2016) . + Christopoulos, DT (2016) . + Christopoulos, DT (2014) . + date_publication: '2019-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RootsExtremaInflections + url_git: '' +rootSolve: + version: 1.8.2.4 + title: |- + Nonlinear Root Finding, Equilibrium and Steady-State Analysis of + Ordinary Differential Equations + maintainer: Karline Soetaert + description: |- + Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). + Includes routines that: (1) generate gradient and jacobian matrices (full and banded), + (2) find roots of non-linear equations by the 'Newton-Raphson' method, + (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running, + (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations + by numerical differencing (using the method-of-lines approach). + Includes fortran code. + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rootSolve + url_git: '' +rope: + version: '1.0' + title: Model Selection with FDR Control of Selected Variables + maintainer: Jonatan Kallus + description: |- + Selects one model with variable selection FDR controlled at a + specified level. A q-value for each potential variable is also returned. The + input, variable selection counts over many bootstraps for several levels of + penalization, is modeled as coming from a beta-binomial mixture + distribution. + date_publication: '2017-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rope + url_git: '' +ropenblas: + version: 0.3.0 + title: Download, Compile and Link 'OpenBLAS' Library with R + maintainer: Pedro Rafael D. Marinho + description: The 'ropenblas' package () is useful + for users of any 'GNU/Linux' distribution. It will be possible to download, compile + and link the 'OpenBLAS' library () with the R language, + always by the same procedure, regardless of the 'GNU/Linux' distribution used. + With the 'ropenblas' package it is possible to download, compile and link the + latest version of the 'OpenBLAS' library even the repositories of the 'GNU/Linux' + distribution used do not include the latest versions of 'OpenBLAS'. If of interest, + older versions of the 'OpenBLAS' library may be considered. Linking R with an + optimized version of 'BLAS' () may improve the computational + performance of R code. The 'OpenBLAS' library is an optimized implementation of + 'BLAS' that can be easily linked to R with the 'ropenblas' package. + date_publication: '2022-08-29' + bug_reports: https://github.com/prdm0/ropenblas/issues + url: https://prdm0.github.io/ropenblas/ + url_cran: https://CRAN.R-project.org/package=ropenblas + url_git: https://github.com/prdm0/ropenblas +ROpenCVLite: + version: 4.90.2 + title: Helper Package for Installing OpenCV with R + maintainer: Simon Garnier + description: |- + Installs 'OpenCV' for use by other packages. 'OpenCV' + is library of programming functions mainly aimed at real-time computer + vision. This 'Lite' version installs the stable base version of 'OpenCV' and + some of its experimental externally contributed modules. It does not provide + R bindings directly. + date_publication: '2024-08-01' + bug_reports: https://github.com/swarm-lab/ROpenCVLite/issues + url: https://swarm-lab.github.io/ROpenCVLite/ + url_cran: https://CRAN.R-project.org/package=ROpenCVLite + url_git: https://github.com/swarm-lab/ROpenCVLite +ropendata: + version: 0.1.0 + title: Query and Download 'Rapid7' 'Cybersecurity' Data Sets + maintainer: Bob Rudis + description: |- + 'Rapid7' collects 'cybersecurity' data and makes it available via + their 'Open Data' portal which has an API. Tools are + provided to assist in querying for available data sets and downloading any + data set authorized to a free, registered account. + date_publication: '2019-02-08' + bug_reports: https://github.com/brudis-r7/ropendata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ropendata + url_git: https://github.com/brudis-r7/ropendata +ROpenDota: + version: 0.1.2 + title: Access OpenDota Services in R + maintainer: Rosdyana Kusuma + description: Provides a client for the API of OpenDota. OpenDota is a web service + which is provide DOTA2 real time data. Data is collected through the Steam WebAPI. + With ROpenDota you can easily grab the latest DOTA2 statistics in R programming + such as latest match on official international competition, analyzing your or + enemy performance to learn their strategies,etc. Please see + for more information. + date_publication: '2018-06-13' + bug_reports: https://github.com/rosdyana/ROpenDota/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ROpenDota + url_git: https://github.com/rosdyana/ROpenDota +ROpenFIGI: + version: 0.2.8 + title: R Interface to OpenFIGI + maintainer: Ruokun Huang + description: |- + Provide a simple interface to Bloomberg's OpenFIGI API. Please + see for API details and registration. You may be + eligible to have an API key to accelerate your loading process. + date_publication: '2016-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROpenFIGI + url_git: https://github.com/HuangRicky/ROpenFIGI +ropenmeteo: + version: '0.1' + title: Wrappers for 'Open-Meteo' API + maintainer: Quinn Thomas + description: Wrappers for the Application Programming Interface from the + project along with helper functions. The project streamlines + access to a range of publicly historical and forecast meteorology data from agencies + across the world. + date_publication: '2024-09-02' + bug_reports: https://github.com/flare-forecast/ropenmeteo/issues + url: http://flare-forecast.org/ropenmeteo/ + url_cran: https://CRAN.R-project.org/package=ropenmeteo + url_git: '' +ropensecretsapi: + version: 1.0.1 + title: R Package for the OpenSecrets.org API + maintainer: Thomas P. Fuller + description: An R package for the OpenSecrets.org web services API. + date_publication: '2014-10-27' + bug_reports: '' + url: http://coherentlogic.com/r-package-for-the-opensecrets-org-api?source=cran + url_cran: https://CRAN.R-project.org/package=ropensecretsapi + url_git: '' +ROpenWeatherMap: + version: '1.1' + title: R Interface to OpenWeatherMap API + maintainer: Mukul Chaware + description: |- + OpenWeatherMap (OWM) is a service providing weather related data. + This package can be used to access current weather data for one location or several locations. + It can also be used to forecast weather for 5 days with data for every 3 hours. + date_publication: '2016-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROpenWeatherMap + url_git: '' +roperators: + version: 1.3.14 + title: Additional Operators to Help you Write Cleaner R Code + maintainer: Ben Wiseman + description: |- + Provides string arithmetic, reassignment operators, logical operators + that handle missing values, and extra logical operators such as floating point + equality and all or nothing. The intent is to allow R users to write code that + is easier to read, write, and maintain while providing a friendlier experience + to new R users from other language backgrounds (such as 'Python') who are used + to concepts such as x += 1 and 'foo' + 'bar'. + Includes operators for not in, easy floating point comparisons, === equivalent, and SQL-like + like operations (), etc. + We also added in some extra helper functions, such as OS checks, pasting + in Oxford comma format, and functions to get the first, last, nth, or most common + element of a vector or word in a string. + date_publication: '2023-07-20' + bug_reports: '' + url: https://benwiseman.github.io/roperators/ + url_cran: https://CRAN.R-project.org/package=roperators + url_git: https://github.com/BenWiseman/roperators +ropercenter: + version: 0.3.2 + title: Reproducible Data Retrieval from the Roper Center Data Archive + maintainer: Frederick Solt + description: |- + Reproducible, programmatic retrieval of datasets from the + Roper Center data archive. The Roper Center for Public Opinion + Research maintains the largest + archive of public opinion data in existence, but researchers using + these datasets are caught in a bind. The Center's terms and conditions + bar redistribution of downloaded datasets, but to ensure that one's + work can be reproduced, assessed, and built upon by others, one must + provide access to the raw data one employed. The `ropercenter` + package cuts this knot by providing registered users with programmatic, + reproducible access to Roper Center datasets from within R. + date_publication: '2023-07-02' + bug_reports: https://github.com/fsolt/ropercenter/issues + url: https://fsolt.org/ropercenter/ + url_cran: https://CRAN.R-project.org/package=ropercenter + url_git: https://github.com/fsolt/ropercenter +Ropj: + version: 0.3-5 + title: Import Origin(R) Project Files + maintainer: Ivan Krylov + description: |- + Read the data from Origin(R) project files ('*.opj') + . + No write support is planned. + date_publication: '2024-03-14' + bug_reports: https://github.com/aitap/Ropj/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Ropj + url_git: https://github.com/aitap/Ropj +ROptEst: + version: 1.3.5 + title: Optimally Robust Estimation + maintainer: Matthias Kohl + description: |- + R infrastructure for optimally robust estimation in general smoothly + parameterized models using S4 classes and methods as described Kohl, M., + Ruckdeschel, P., and Rieder, H. (2010), , and in + Rieder, H., Kohl, M., and Ruckdeschel, P. (2008), . + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROptEst + url_git: http://robast.r-forge.r-project.org/ +roptim: + version: 0.1.6 + title: General Purpose Optimization in R using C++ + maintainer: Yi Pan + description: |- + Perform general purpose optimization in R using C++. A unified + wrapper interface is provided to call C functions of the five optimization + algorithms ('Nelder-Mead', 'BFGS', 'CG', 'L-BFGS-B' and 'SANN') underlying + optim(). + date_publication: '2022-08-06' + bug_reports: https://github.com/ypan1988/roptim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roptim + url_git: https://github.com/ypan1988/roptim/ +ROptimus: + version: 3.0.0 + title: A Parallel General-Purpose Adaptive Optimisation Engine + maintainer: Aleksandr B. Sahakyan + description: |- + A general-purpose optimisation engine that supports + i) Monte Carlo optimisation with Metropolis criterion [Metropolis et al. (1953) , Hastings (1970) ] + and Acceptance Ratio Simulated Annealing [Kirkpatrick et al. (1983) , Černý (1985) ] + on multiple cores, and ii) Acceptance Ratio Replica Exchange Monte + Carlo Optimisation. In each case, the system pseudo-temperature is + dynamically adjusted such that the observed acceptance ratio is kept + near to the desired (fixed or changing) acceptance ratio. + date_publication: '2023-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROptimus + url_git: https://github.com/SahakyanLab/ROptimus +roptions: + version: 1.0.3 + title: Option Strategies and Valuation + maintainer: Anurag Agrawal + description: Collection of tools to develop options strategies, value option contracts + using the Black-Scholes-Merten option pricing model and calculate the option Greeks. + Hull, John C. "Options, Futures, and Other Derivatives" (1997, ISBN:0-13-601589-1). + Fischer Black, Myron Scholes (1973) "The Pricing of Options and Corporate Liabilities" + . + date_publication: '2020-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roptions + url_git: '' +ROptSpace: + version: 0.2.3 + title: Matrix Reconstruction from a Few Entries + maintainer: Kisung You + description: Matrix reconstruction, also known as matrix completion, is the task + of inferring missing entries of a partially observed matrix. This package provides + a method called OptSpace, which was proposed by Keshavan, R.H., Oh, S., and Montanari, + A. (2009) for a case under low-rank assumption. + date_publication: '2021-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROptSpace + url_git: '' +ROracle: + version: 1.3-1.1 + title: OCI Based Oracle Database Interface for R + maintainer: Rajendra S. Pingte + description: |- + Oracle Database interface (DBI) driver for R. + This is a DBI-compliant Oracle driver based on the OCI. + date_publication: '2021-11-10' + bug_reports: '' + url: http://www.oracle.com + url_cran: https://CRAN.R-project.org/package=ROracle + url_git: '' +rorcid: + version: 0.7.0 + title: Interface to the 'Orcid.org' API + maintainer: Scott Chamberlain + description: |- + Client for the 'Orcid.org' API (). + Functions included for searching for people, searching by 'DOI', + and searching by 'Orcid' 'ID'. + date_publication: '2021-01-20' + bug_reports: https://github.com/ropensci/rorcid/issues + url: https://docs.ropensci.org/rorcid/(docs) + url_cran: https://CRAN.R-project.org/package=rorcid + url_git: https://github.com/ropensci/rorcid(devel) +rorqual.morpho: + version: 0.1.1 + title: Morphological Allometry of Rorquals + maintainer: Max Czapanskiy + description: |- + Predicts morphological parameters of rorquals (e.g. body mass, + flipper length, maximum engulfment capacity) from body length using + allometric equations from Kahane-Rapport and Goldbogen (2018) + . + date_publication: '2020-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rorqual.morpho + url_git: '' +ROSE: + version: 0.0-4 + title: Random Over-Sampling Examples + maintainer: Nicola Lunardon + description: |- + Functions to deal with binary classification + problems in the presence of imbalanced classes. Synthetic balanced samples are + generated according to ROSE (Menardi and Torelli, 2013). + Functions that implement more traditional remedies to the class imbalance + are also provided, as well as different metrics to evaluate a learner accuracy. + These are estimated by holdout, bootstrap or cross-validation methods. + date_publication: '2021-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ROSE + url_git: '' +Rosenbrock: + version: 0.1.0 + title: |- + Extended Rosenbrock-Type Densities for Markov Chain Monte Carlo + (MCMC) Sampler Benchmarking + maintainer: Martin Wiegand + description: |- + New Markov chain Monte Carlo (MCMC) samplers new to be thoroughly tested + and their performance accurately assessed. This requires densities + that offer challenging properties to the novel sampling algorithms. + One such popular problem is the Rosenbrock function. However, while its + shape lends itself well to a benchmark problem, no codified multivariate expansion + of the density exists. We have developed an extension to this class of distributions + and supplied densities and direct sampler functions to assess the performance + of novel MCMC algorithms. The functions are introduced in "An n-dimensional Rosenbrock + Distribution for MCMC Testing" by Pagani, Wiegand and Nadarajah (2019) . + date_publication: '2020-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rosenbrock + url_git: '' +roseRF: + version: 0.1.0 + title: |- + ROSE Random Forests for Robust Semiparametric Efficient + Estimation + maintainer: Elliot H. Young + description: |- + ROSE (RObust Semiparametric Efficient) random forests for robust + semiparametric efficient estimation in partially parametric models (containing + generalised partially linear models). + Details can be found in the paper by Young and Shah (2024) . + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roseRF + url_git: '' +rosetta: + version: 0.3.12 + title: Parallel Use of Statistical Packages in Teaching + maintainer: Gjalt-Jorn Peters + description: |- + When teaching statistics, it can often be desirable to + uncouple the content from specific software packages. To ease such + efforts, the Rosetta Stats website () allows + comparing analyses in different packages. This package is the companion + to the Rosetta Stats website, aiming to provide functions that produce + output that is similar to output from other statistical packages, thereby + facilitating 'software-agnostic' teaching of statistics. + date_publication: '2023-03-05' + bug_reports: https://gitlab.com/r-packages/rosetta/-/issues + url: https://r-packages.gitlab.io/rosetta/ + url_cran: https://CRAN.R-project.org/package=rosetta + url_git: '' +rosetteApi: + version: 1.14.4 + title: '''Rosette'' API' + maintainer: Seth Gransky + description: |- + 'Rosette' is an API for multilingual text analysis and information + extraction. More information can be found at . + date_publication: '2020-06-17' + bug_reports: https://developer.rosette.com/support-ticket + url: https://developer.rosette.com + url_cran: https://CRAN.R-project.org/package=rosetteApi + url_git: '' +rosm: + version: 0.3.0 + title: Plot Raster Map Tiles from Open Street Map and Other Sources + maintainer: Dewey Dunnington + description: |- + Download and plot Open Street Map , + Bing Maps and other tiled map sources. Use to create + basemaps quickly and add hillshade to vector-based maps. + date_publication: '2023-08-27' + bug_reports: https://github.com/paleolimbot/rosm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rosm + url_git: https://github.com/paleolimbot/rosm +rosmium: + version: 0.1.0 + title: Bindings for 'Osmium Tool' + maintainer: Daniel Herszenhut + description: |- + Allows one to use 'Osmium Tool' + () from R. 'Osmium' is a + multipurpose command line tool that enables one to manipulate and + analyze OpenStreetMap files through several different commands. + Currently, this package does not aim to offer functions that cover the + entire 'Osmium' API, instead making available functions that wrap only + a very limited set of its features. + date_publication: '2023-11-27' + bug_reports: https://github.com/ipeaGIT/rosmium/issues + url: https://ipeagit.github.io/rosmium/ + url_cran: https://CRAN.R-project.org/package=rosmium + url_git: https://github.com/ipeaGIT/rosmium +rospca: + version: 1.1.1 + title: Robust Sparse PCA using the ROSPCA Algorithm + maintainer: Tom Reynkens + description: |- + Implementation of robust sparse PCA using the ROSPCA algorithm + of Hubert et al. (2016) . + date_publication: '2024-12-02' + bug_reports: https://github.com/TReynkens/rospca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rospca + url_git: https://github.com/TReynkens/rospca +rosv: + version: 0.5.1 + title: |- + Client to Access and Operate on the 'Open Source Vulnerability' + API + maintainer: Allen OBrien + description: |- + Connect, query, and operate on information available from the + 'Open Source Vulnerability' database . Although 'CRAN' + has vulnerabilities listed, these are few compared to projects such as + 'PyPI'. With tighter integration between 'R' and 'Python', having an + 'R' specific package to access details about vulnerabilities from + various sources is a worthwhile enterprise. + date_publication: '2023-12-04' + bug_reports: https://github.com/al-obrien/rosv/issues + url: https://al-obrien.github.io/rosv/ + url_cran: https://CRAN.R-project.org/package=rosv + url_git: https://github.com/al-obrien/rosv +rotasym: + version: 1.1.5 + title: Tests for Rotational Symmetry on the Hypersphere + maintainer: Eduardo García-Portugués + description: |- + Implementation of the tests for rotational symmetry on the + hypersphere proposed in García-Portugués, Paindaveine and Verdebout (2020) + . The package also implements the + proposed distributions on the hypersphere, based on the tangent-normal + decomposition, and allows for the replication of the data application + considered in the paper. + date_publication: '2023-08-19' + bug_reports: https://github.com/egarpor/rotasym + url: '' + url_cran: https://CRAN.R-project.org/package=rotasym + url_git: https://github.com/egarpor/rotasym +rotationForest: + version: 0.1.3 + title: Fit and Deploy Rotation Forest Models + maintainer: Michel Ballings + description: |- + Fit and deploy rotation forest models ("Rodriguez, J.J., Kuncheva, + L.I., 2006. Rotation forest: A new classifier ensemble method. IEEE Trans. + Pattern Anal. Mach. Intell. 28, 1619-1630 ") for binary classification. + Rotation forest is an ensemble method where each base classifier (tree) is + fit on the principal components of the variables of random partitions of + the feature set. + date_publication: '2017-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rotationForest + url_git: '' +rotations: + version: 1.6.5 + title: Working with Rotation Data + maintainer: Bryan Stanfill + description: |- + Tools for working with rotational data, including + simulation from the most commonly used distributions on SO(3), + methods for different Bayes, mean and median type estimators for + the central orientation of a sample, confidence/credible + regions for the central orientation based on those estimators and + a novel visualization technique for rotation data. Most recently, + functions to identify potentially discordant (outlying) values + have been added. References: Bingham, Melissa A. and Nordman, Dan J. and Vardeman, Steve B. (2009), + Bingham, Melissa A and Vardeman, Stephen B and Nordman, Daniel J (2009), + Bingham, Melissa A and Nordman, Daniel J and Vardeman, Stephen B (2010), + Leon, C.A. and Masse, J.C. and Rivest, L.P. (2006), + Hartley, R and Aftab, K and Trumpf, J. (2011), + Stanfill, Bryan and Genschel, Ulrike and Hofmann, Heike (2013), + Maonton, Jonathan (2004), + Mardia, KV and Jupp, PE (2000, ISBN:9780471953333), + Rancourt, D. and Rivest, L.P. and Asselin, J. (2000), + Chang, Ted and Rivest, Louis-Paul (2001), + Fisher, Nicholas I. (1996, ISBN:0521568900). + date_publication: '2023-12-08' + bug_reports: https://github.com/stanfill/rotationsC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rotations + url_git: https://github.com/stanfill/rotationsC +rotatogram: + version: 0.1.3 + title: A Non-Axis-Dominant Association Plotting Tool + maintainer: Noah Haber + description: 'A rotatogram is a method of displaying an association which is axis + non-dominant. This is achieved in two ways: First, the method of estimating the + slope and intercept uses the least-products method rather than more typical least + squared error for the "dependent" variable. The least products method has no "dependent" + variable and is scale independent. Second, the plot is rotated such that the resulting + regression line is vertical, reducing the suggestion that the vertical axis is + the dominant one. The slope can be read relative to either axis equally.' + date_publication: '2023-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rotatogram + url_git: '' +rotl: + version: 3.1.0 + title: Interface to the 'Open Tree of Life' API + maintainer: Francois Michonneau + description: |- + An interface to the 'Open Tree of Life' API to retrieve + phylogenetic trees, information about studies used to assemble the + synthetic tree, and utilities to match taxonomic names to 'Open Tree + identifiers'. The 'Open Tree of Life' aims at assembling a + comprehensive phylogenetic tree for all named species. + date_publication: '2023-06-15' + bug_reports: https://github.com/ropensci/rotl/issues + url: https://docs.ropensci.org/rotl/ + url_cran: https://CRAN.R-project.org/package=rotl + url_git: https://github.com/ropensci/rotl +rotor: + version: 0.3.7 + title: Log Rotation and Conditional Backups + maintainer: Stefan Fleck + description: |- + Conditionally rotate or back-up files based on + their size or the date of the last backup; inspired by the 'Linux' + utility 'logrotate'. + date_publication: '2022-10-11' + bug_reports: https://github.com/s-fleck/rotor/issues + url: https://s-fleck.github.io/rotor/ + url_cran: https://CRAN.R-project.org/package=rotor + url_git: '' +roughnet: + version: 1.0.1 + title: Visualize Networks using 'roughjs' + maintainer: David Schoch + description: Visualize networks using the 'javascript' library 'roughjs'. This allows + to draw sketchy, hand-drawn-like networks. + date_publication: '2022-12-06' + bug_reports: https://github.com/schochastics/roughnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roughnet + url_git: https://github.com/schochastics/roughnet/ +RoughSets: + version: 1.3-8 + title: Data Analysis Using Rough Set and Fuzzy Rough Set Theories + maintainer: Christoph Bergmeir + description: |- + Implementations of algorithms for data analysis based on the + rough set theory (RST) and the fuzzy rough set theory (FRST). We not only + provide implementations for the basic concepts of RST and FRST but also + popular algorithms that derive from those theories. The methods included in the + package can be divided into several categories based on their functionality: + discretization, feature selection, instance selection, rule induction and + classification based on nearest neighbors. RST was introduced by Zdzisław + Pawlak in 1982 as a sophisticated mathematical tool to model and process + imprecise or incomplete information. By using the indiscernibility relation for + objects/instances, RST does not require additional parameters to analyze the + data. FRST is an extension of RST. The FRST combines concepts of vagueness and + indiscernibility that are expressed with fuzzy sets (as proposed by Zadeh, in + 1965) and RST. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RoughSets + url_git: https://github.com/janusza/RoughSets +roughsf: + version: 1.0.0 + title: Visualize Spatial Data using 'roughjs' + maintainer: David Schoch + description: Draw maps using the 'javascript' library 'roughjs'. This allows to + draw sketchy, hand-drawn-like maps. + date_publication: '2022-10-04' + bug_reports: https://github.com/schochastics/roughsf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roughsf + url_git: https://github.com/schochastics/roughsf +round: + version: 0.21-0.2 + title: Rounding to Decimal Digits + maintainer: Martin Maechler + description: |- + Decimal rounding is non-trivial in binary arithmetic. ISO + standard round to even is more rare than typically assumed as most decimal fractions + are not exactly representable in binary. Our 'roundX()' versions explore differences + between current and potential future versions of round() in R. + Further, provides (some partly related) C99 math lib functions not in base R. + date_publication: '2024-01-10' + bug_reports: https://gitlab.com/mmaechler/round/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=round + url_git: https://gitlab.com/mmaechler/round/ +RoundAndRound: + version: 0.0.1 + title: Plot Objects Moving in Orbits + maintainer: Lele Shu + description: Visualize the objects in orbits in 2D and 3D. The packages is under + developing to plot the orbits of objects in polar coordinate system. See the examples + in demo. + date_publication: '2019-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RoundAndRound + url_git: '' +roundhouse: + version: 0.0.2 + title: Random Chuck Norris Facts + maintainer: Brandon Greenwell + description: |- + R functions for generating and/or displaying random Chuck Norris + facts. Based on data from the 'Internet Chuck Norris database' ('ICNDb'). + date_publication: '2020-09-24' + bug_reports: https://github.com/bgreenwell/roundhouse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roundhouse + url_git: https://github.com/bgreenwell/roundhouse +roundwork: + version: 0.0.1 + title: Rounding Infrastructure + maintainer: Lukas Jung + description: |- + Flexible rounding functions for use in error detection. They were + outsourced from the 'scrutiny' package. + date_publication: '2024-09-25' + bug_reports: https://github.com/lhdjung/roundwork/issues + url: https://lhdjung.github.io/roundwork/ + url_cran: https://CRAN.R-project.org/package=roundwork + url_git: https://github.com/lhdjung/roundwork/ +roundyh: + version: 0.1.0 + title: Round Dataframe + maintainer: Duan Yuanheng + description: |- + A simple rounding function. The default round() function in R + uses the IEC 60559 standard and therefore it rounds 0.5 to 0 and rounds + -1.5 to -2. The roundx() function accounts for this and helps + to round 0.5 up to 1. + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=roundyh + url_git: '' +Routliers: + version: 0.0.0.3 + title: Robust Outliers Detection + maintainer: Marie Delacre + description: |- + Detecting outliers using robust methods, + i.e. the Median Absolute Deviation (MAD) for univariate outliers; Leys, Ley, Klein, Bernard, & Licata (2013) + and the Mahalanobis-Minimum Covariance Determinant (MMCD) for multivariate outliers; Leys, C., Klein, O., Dominicy, Y. & Ley, C. (2018) . + There is also the more known but less robust Mahalanobis distance method, only for comparison purposes. + date_publication: '2019-05-23' + bug_reports: https://github.com/mdelacre/Routliers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Routliers + url_git: '' +routr: + version: 0.4.1 + title: A Simple Router for HTTP and WebSocket Requests + maintainer: Thomas Lin Pedersen + description: |- + In order to make sure that web request ends up in the correct + handler function a router is often used. 'routr' is a package implementing a + simple but powerful routing functionality for R based servers. It is a fully + functional 'fiery' plugin, but can also be used with other 'httpuv' based + servers. + date_publication: '2022-08-19' + bug_reports: https://github.com/thomasp85/routr/issues + url: https://routr.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=routr + url_git: https://github.com/thomasp85/routr#routr +roxut: + version: 0.4.0 + title: Document Unit Tests Roxygen-Style + maintainer: Bryan A. Hanson + description: Much as 'roxygen2' allows one to document functions in the same file + as the function itself, 'roxut' allows one to write the unit tests in the same + file as the function. Once processed, the unit tests are moved to the appropriate + directory. Currently supports 'testthat' and 'tinytest' frameworks. The 'roxygen2' + package provides much of the infrastructure. + date_publication: '2021-08-22' + bug_reports: https://github.com/bryanhanson/roxut/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roxut + url_git: https://github.com/bryanhanson/roxut +roxy.shinylive: + version: 1.0.0 + title: A 'roxygen2' Extension for 'Shinylive' + maintainer: Pawel Rucki + description: |- + An extension for 'roxygen2' to embed 'Shinylive' applications + in the package documentation. + date_publication: '2024-11-21' + bug_reports: https://github.com/insightsengineering/roxy.shinylive/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roxy.shinylive + url_git: https://github.com/insightsengineering/roxy.shinylive/ +roxygen2: + version: 7.3.2 + title: In-Line Documentation for R + maintainer: Hadley Wickham + description: |- + Generate your Rd documentation, 'NAMESPACE' file, and + collation field using specially formatted comments. Writing + documentation in-line with code makes it easier to keep your + documentation up-to-date as your requirements change. 'roxygen2' is + inspired by the 'Doxygen' system for C++. + date_publication: '2024-06-28' + bug_reports: https://github.com/r-lib/roxygen2/issues + url: https://roxygen2.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=roxygen2 + url_git: https://github.com/r-lib/roxygen2 +roxygen2md: + version: 1.0.1 + title: '''Roxygen'' to ''Markdown''' + maintainer: Kirill Müller + description: Converts elements of 'roxygen' documentation to 'markdown'. + date_publication: '2024-02-18' + bug_reports: https://github.com/r-lib/roxygen2md/issues + url: https://roxygen2md.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=roxygen2md + url_git: https://github.com/r-lib/roxygen2md +roxyglobals: + version: 1.0.0 + title: '''Roxygen2'' Global Variable Declarations' + maintainer: Anthony North + description: Generate utils::globalVariables() from 'roxygen2' @global and @autoglobal + tags. + date_publication: '2023-08-21' + bug_reports: https://github.com/anthonynorth/roxyglobals/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roxyglobals + url_git: https://github.com/anthonynorth/roxyglobals +roxylint: + version: 0.1.0 + title: Lint 'roxygen2'-Generated Documentation + maintainer: Doug Kelkhoff + description: |- + Provides formatting linting to 'roxygen2' tags. Linters report + 'roxygen2' tags that do not conform to a standard style. These linters + can be a helpful check for building more consistent documentation and + to provide reminders about best practices or checks for typos. Default + linting suites are provided for common style guides such as the one + followed by the 'tidyverse', though custom linters can be registered by + other packages or be custom-tailored to a specific package. + date_publication: '2024-02-19' + bug_reports: https://github.com/openpharma/roxylint/issues + url: https://openpharma.github.io/roxylint/ + url_cran: https://CRAN.R-project.org/package=roxylint + url_git: https://github.com/openpharma/roxylint +roxytest: + version: 0.0.2 + title: Various Tests with 'roxygen2' + maintainer: Mikkel Meyer Andersen + description: |- + Various tests as 'roxygen2' roclets: e.g. 'testthat' and 'tinytest' tests. + Also other static analysis tools as checking parameter documentation consistency and others. + date_publication: '2023-01-11' + bug_reports: https://github.com/mikldk/roxytest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=roxytest + url_git: '' +roxytypes: + version: 0.1.2 + title: Typed Parameter Tags for Integration with 'roxygen2' + maintainer: Doug Kelkhoff + description: |- + Provides typed parameter documentation tags for integration + with 'roxygen2'. Typed parameter tags provide a consistent interface for + annotating expected types for parameters and returned values. Tools for + converting from existing styles are also provided to easily adapt projects + which implement typed documentation by convention rather than tag. Use the + default format or provide your own. + date_publication: '2024-10-15' + bug_reports: https://github.com/openpharma/roxytypes/issues + url: https://openpharma.github.io/roxytypes/ + url_cran: https://CRAN.R-project.org/package=roxytypes + url_git: https://github.com/openpharma/roxytypes +rPACI: + version: 0.2.2 + title: Placido Analysis of Corneal Irregularity + maintainer: Darío Ramos-López + description: Analysis of corneal data obtained from a Placido disk corneal topographer + with calculation of irregularity indices. This package performs analyses of corneal + data obtained from a Placido disk corneal topographer, with the calculation of + the Placido irregularity indices and the posterior analysis. The package is intended + to be easy to use by a practitioner, providing a simple interface and yielding + easily interpretable results. A corneal topographer is an ophthalmic clinical + device that obtains measurements in the cornea (the anterior part of the eye). + A Placido disk corneal topographer makes use of the Placido disk [Rowsey et al. + (1981)], which produce a circular pattern + of measurement nodes. The raw information measured by such a topographer is used + by practitioners to analyze curvatures, to study optical aberrations, or to diagnose + specific conditions of the eye (e.g. keratoconus, an important corneal disease). + The rPACI package allows the calculation of the corneal irregularity indices described + in [Castro-Luna et al. (2020)], [Ramos-Lopez + et al. (2013)], and [Ramos-Lopez et al. (2011)]. + It provides a simple interface to read corneal topography data files as exported + by a typical Placido disk topographer, to compute the irregularity indices mentioned + before, and to display summary plots that are easy to interpret for a clinician. + date_publication: '2021-11-04' + bug_reports: https://github.com/dariorlual/rPACI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rPACI + url_git: https://github.com/dariorlual/rPACI/ +rPackedBar: + version: 0.2.2 + title: Packed Bar Charts with 'plotly' + maintainer: Adam Spannbauer + description: Packed bar charts are a variation of treemaps for visualizing skewed + data. The concept was introduced by Xan Gregg at 'JMP'. + date_publication: '2019-06-17' + bug_reports: https://github.com/AdamSpannbauer/rPackedBar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rPackedBar + url_git: https://github.com/AdamSpannbauer/rPackedBar +rpact: + version: 4.1.0 + title: Confirmatory Adaptive Clinical Trial Design and Analysis + maintainer: Friedrich Pahlke + description: Design and analysis of confirmatory adaptive clinical trials with continuous, + binary, and survival endpoints according to the methods described in the monograph + by Wassmer and Brannath (2016) . This includes + classical group sequential as well as multi-stage adaptive hypotheses tests that + are based on the combination testing principle. + date_publication: '2024-09-27' + bug_reports: https://github.com/rpact-com/rpact/issues + url: https://www.rpact.org + url_cran: https://CRAN.R-project.org/package=rpact + url_git: https://github.com/rpact-com/rpact +Rpadrino: + version: 0.0.5 + title: Interact with the 'PADRINO' IPM Database + maintainer: Sam Levin + description: |- + 'PADRINO' houses textual representations of + Integral Projection Models which can be converted from their + table format into full kernels to reproduce or extend an + already published analysis. 'Rpadrino' is an R interface to this database. For + more information on Integral Projection Models, see Easterling et al. (2000) + , Merow et al. (2013) + , Rees et al. (2014) , + and Metcalf et al. (2015) . See Levin et al. (2021) + for more information on 'ipmr', the engine that powers model reconstruction + . + date_publication: '2023-09-22' + bug_reports: https://github.com/padrinoDB/Rpadrino/issues + url: https://padrinoDB.github.io/Rpadrino/ + url_cran: https://CRAN.R-project.org/package=Rpadrino + url_git: https://github.com/padrinoDB/Rpadrino +rPAex: + version: 1.0.5 + title: |- + Automatic Detection of Experimental Unit in Precision + Agriculture + maintainer: Felipe de Mendiburu + description: A part of precision agriculture is linked to the spectral image obtained + from the cameras. With the image information of the agricultural experiment, the + included functions facilitate the collection of spectral data associated with + the experimental units. Some designs generated in R are linked to the images, + which allows the use of the information of each pixel of the image in the experimental + unit and the treatment. Tables and images are generated for the analysis of the + precision agriculture experiment during the entire vegetative period of the crop. + date_publication: '2023-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rPAex + url_git: '' +rpaleoclim: + version: 1.0.1 + title: Download Paleoclimate Data from 'PaleoClim' + maintainer: Joe Roe + description: |2- + + 'PaleoClim' (Brown et al. 2019, + ) is a set of free, high resolution paleoclimate + surfaces covering the whole globe. It includes data on surface temperature, + precipitation and the standard bioclimatic variables commonly used in + ecological modelling, derived from the 'HadCM3' general circulation model and + downscaled to a spatial resolution of up to 2.5 minutes. Simulations are + available for key time periods from the Late Holocene to mid-Pliocene. Data on + current and Last Glacial Maximum climate is derived from 'CHELSA' (Karger et + al. 2017, ) and reprocessed by 'PaleoClim' to + match their format; it is available at up to 30 seconds resolution. This + package provides a simple interface for downloading 'PaleoClim' data in R, + with support for caching and filtering retrieved data by period, resolution, + and geographic extent. + date_publication: '2023-08-09' + bug_reports: https://github.com/joeroe/rpaleoclim/issues + url: https://rpaleoclim.joeroe.io + url_cran: https://CRAN.R-project.org/package=rpaleoclim + url_git: https://github.com/joeroe/rpaleoclim +RPANDA: + version: '2.4' + title: Phylogenetic ANalyses of DiversificAtion + maintainer: Hélène Morlon + description: |- + Implements macroevolutionary analyses on phylogenetic trees. See + Morlon et al. (2010) , Morlon et al. (2011) + , Condamine et al. (2013) , + Morlon et al. (2014) , Manceau et al. (2015) , + Lewitus & Morlon (2016) , Drury et al. (2016) , + Manceau et al. (2016) , Morlon et al. (2016) , Clavel & Morlon (2017) , + Drury et al. (2017) , Lewitus & Morlon (2017) , + Drury et al. (2018) , Clavel et al. (2019) , Maliet et al. (2019) , + Billaud et al. (2019) , Lewitus et al. (2019) , + Aristide & Morlon (2019) , Maliet et al. (2020) , Drury et al. (2021) , + Perez-Lamarque & Morlon (2022) , Perez-Lamarque et al. (2022) , Mazet et al. (2023) , Drury et al. (2024) . + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPANDA + url_git: https://github.com/hmorlon/PANDA +rpanel: + version: 1.1-5.2 + title: Simple Interactive Controls for R using the 'tcltk' Package + maintainer: Adrian Bowman + description: |- + A set of functions to build simple + GUI controls for R functions. These are built on the 'tcltk' package. + Uses could include changing a parameter on a graph by animating it + with a slider or a "doublebutton", up to more sophisticated control + panels. + Some functions for specific graphical tasks, referred to as 'cartoons', + are provided. + date_publication: '2023-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpanel + url_git: '' +rPanglaoDB: + version: 0.2.1 + title: |- + Download and Merge Single-Cell RNA-Seq Data from the PanglaoDB + Database + maintainer: Daniel Osorio + description: Download and merge labeled single-cell RNA-seq data from the PanglaoDB + into a Seurat object. + date_publication: '2021-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rPanglaoDB + url_git: https://github.com/dosorio/rPanglaoDB/ +rpart: + version: 4.1.24 + title: Recursive Partitioning and Regression Trees + maintainer: Beth Atkinson + description: |- + Recursive partitioning for classification, + regression and survival trees. An implementation of most of the + functionality of the 1984 book by Breiman, Friedman, Olshen and Stone. + date_publication: '2025-01-07' + bug_reports: https://github.com/bethatkinson/rpart/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rpart + url_git: https://github.com/bethatkinson/rpart +rpart.LAD: + version: 0.1.3 + title: Least Absolute Deviation Regression Trees + maintainer: Stephan Dlugosz + description: |- + Recursive partitioning for least absolute deviation regression trees. Another algorithm from the 1984 book by + Breiman, Friedman, Olshen and Stone in addition to the 'rpart' package (Breiman, Friedman, Olshen, Stone (1984, ISBN:9780412048418). + date_publication: '2023-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpart.LAD + url_git: '' +rpart.plot: + version: 3.1.2 + title: 'Plot ''rpart'' Models: An Enhanced Version of ''plot.rpart''' + maintainer: Stephen Milborrow + description: |- + Plot 'rpart' models. Extends plot.rpart() and text.rpart() + in the 'rpart' package. + date_publication: '2024-02-26' + bug_reports: '' + url: http://www.milbo.org/rpart-plot/index.html + url_cran: https://CRAN.R-project.org/package=rpart.plot + url_git: '' +rpartScore: + version: 1.0-2 + title: Classification Trees for Ordinal Responses + maintainer: Giuliano Galimberti + description: |- + Recursive partitioning methods to build + classification trees for ordinal responses within the CART + framework. Trees are grown using the Generalized Gini + impurity function, where the misclassification costs are given + by the absolute or squared differences in scores assigned to + the categories of the response. Pruning is based on the total + misclassification rate or on the total misclassification cost. + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpartScore + url_git: '' +RPatternJoin: + version: 1.0.0 + title: String Similarity Joins for Hamming and Levenshtein Distances + maintainer: Daniil Matveev + description: |- + This project is a tool for words edit similarity joins (a.k.a. all-pairs similarity search) under small (< 3) edit distance constraints. + It works for Levenshtein/Hamming distances and words from any alphabet. + The software was originally developed for joining amino-acid/nucleotide sequences from Adaptive Immune Repertoires, + where the number of words is relatively large (10^5-10^6) and the average length of words is relatively small (10-100). + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPatternJoin + url_git: '' +rPBK: + version: 0.2.4 + title: |- + Inference and Prediction of Generic Physiologically-Based + Kinetic Models + maintainer: Virgile Baudrot + description: |- + Fit and simulate any kind of + physiologically-based kinetic ('PBK') models whatever the number of compartments. + Moreover, it allows to account for any link between pairs of compartments, as + well as any link of each of the compartments with the external medium. Such + generic PBK models have today applications in pharmacology (PBPK models) to + describe drug effects, in toxicology and ecotoxicology (PBTK models) to describe + chemical substance effects. In case of exposure to a parent compound (drug or + chemical) the 'rPBK' package allows to consider metabolites, whatever their number + and their phase (I, II, ...). Last but not least, package 'rPBK' can also be used for + dynamic flux balance analysis (dFBA) to deal with metabolic networks. See also + Charles et al. (2022) . + date_publication: '2024-02-26' + bug_reports: https://gitlab.in2p3.fr/mosaic-software/rPBK/-/issues + url: https://gitlab.in2p3.fr/mosaic-software/rPBK/ + url_cran: https://CRAN.R-project.org/package=rPBK + url_git: '' +rpca: + version: 0.2.3 + title: |- + RobustPCA: Decompose a Matrix into Low-Rank and Sparse + Components + maintainer: Maciek Sykulski + description: Suppose we have a data matrix, which is the superposition of a low-rank + component and a sparse component. Candes, E. J., Li, X., Ma, Y., & Wright, J. + (2011). Robust principal component analysis?. Journal of the ACM (JACM), 58(3), + 11. prove that we can recover each component individually under some suitable + assumptions. It is possible to recover both the low-rank and the sparse components + exactly by solving a very convenient convex program called Principal Component + Pursuit; among all feasible decompositions, simply minimize a weighted combination + of the nuclear norm and of the L1 norm. This package implements this decomposition + algorithm resulting with Robust PCA approach. + date_publication: '2015-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpca + url_git: '' +rpcss: + version: 0.1.0 + title: |- + Constitution of Core Collections by Principal Component Scoring + Strategy + maintainer: J. Aravind + description: |- + Generate a Core Collection with Principal Component Scoring + Strategy (PCSS) using qualitative and/or quantitative trait data according + to Hamon and Noirot (1990) , + Noirot et al. (1996) and Noirot et al. (2003) + . + date_publication: '2025-02-17' + bug_reports: https://github.com/aravind-j/rpcss/issues + url: https://aravind-j.github.io/rpcss/ + url_cran: https://CRAN.R-project.org/package=rpcss + url_git: https://github.com/aravind-j/rpcss +Rpdb: + version: 2.3.4 + title: Read, Write, Visualize and Manipulate PDB Files + maintainer: Leonard Mada + description: |- + Provides tools to read, write, visualize Protein Data Bank (PDB) files and + perform some structural manipulations. + date_publication: '2023-09-28' + bug_reports: https://github.com/discoleo/Rpdb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rpdb + url_git: https://github.com/discoleo/Rpdb +rPDBapi: + version: 2.1.1 + title: A Comprehensive Interface for Accessing the Protein Data Bank + maintainer: Selcuk Korkmaz + description: |- + Streamlines the interaction with the 'RCSB' Protein Data Bank ('PDB') . This interface offers an intuitive and + powerful tool for searching and retrieving a diverse range of data types from the 'PDB'. It includes advanced functionalities like + BLAST and sequence motif queries. Built upon the existing XML-based API of the 'PDB', it simplifies the creation of custom requests, + thereby enhancing usability and flexibility for researchers. + date_publication: '2024-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rPDBapi + url_git: '' +RPDTest: + version: 0.0.2 + title: |- + A New Type of Test Statistic and Method for Multinomial + Goodness-of-Fit Test + maintainer: Renkang Liu + description: Performs multinomial goodness-of-fit test on multinomially distributed + data using the Randomized phi-divergence test statistics. Details of this kind + of statistics can be found at Nikita Puchkin, Vladimir Ulyanov (2023) . + date_publication: '2024-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPDTest + url_git: '' +RpeakChrom: + version: 1.1.0 + title: |- + Tools for Chromatographic Column Characterization and Modelling + Chromatographic Peak + maintainer: Manuel David Peris Diaz + description: The quantitative measurement and detection of molecules in HPLC should + be carried out by an accurate description of chromatographic peaks. In this package + non-linear fitting using a modified Gaussian model with a parabolic variance (PVMG) + has been implemented to obtain the retention time and height at the peak maximum. + This package also includes the traditional Van Deemter approach and two alternatives + approaches to characterize chromatographic column. + date_publication: '2017-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RpeakChrom + url_git: '' +RPEGLMEN: + version: 1.1.2 + title: |- + Gamma and Exponential Generalized Linear Models with Elastic Net + Penalty + maintainer: Anthony Christidis + description: |- + Implements the fast iterative shrinkage-thresholding algorithm + (FISTA) algorithm to fit a Gamma distribution with an elastic net + penalty as described in Chen, Arakvin and Martin (2018) + . An implementation for the case of the + exponential distribution is also available, with details available + in Chen and Martin (2018) . + date_publication: '2023-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPEGLMEN + url_git: '' +RPEIF: + version: 1.2.4 + title: |- + Computation and Plots of Influence Functions for Risk and + Performance Measures + maintainer: Anthony Christidis + description: |- + Computes the influence functions time series of the returns for the risk and + performance measures as mentioned in Chen and Martin (2018) + , as well as in Zhang et al. (2019) + . Also evaluates estimators influence + functions at a set of parameter values and plots them to display the shapes of + the influence functions. + date_publication: '2021-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPEIF + url_git: '' +RPEnsemble: + version: '0.5' + title: Random Projection Ensemble Classification + maintainer: Timothy I. Cannings + description: Implements the methodology of "Cannings, T. I. and Samworth, R. J. + (2017) Random-projection ensemble classification, J. Roy. Statist. Soc., Ser. + B. (with discussion), 79, 959--1035". The random projection ensemble classifier + is a general method for classification of high-dimensional data, based on careful + combination of the results of applying an arbitrary base classifier to random + projections of the feature vectors into a lower-dimensional space. The random + projections are divided into non-overlapping blocks, and within each block the + projection yielding the smallest estimate of the test error is selected. The random + projection ensemble classifier then aggregates the results of applying the base + classifier on the selected projections, with a data-driven voting threshold to + determine the final assignment. + date_publication: '2021-02-24' + bug_reports: '' + url: https://arxiv.org/abs/1504.04595 + url_cran: https://CRAN.R-project.org/package=RPEnsemble + url_git: '' +RPESE: + version: 1.2.5 + title: Estimates of Standard Errors for Risk and Performance Measures + maintainer: Anthony Christidis + description: |- + Estimates of standard errors of popular risk and performance + measures for asset or portfolio returns using methods as described in + Chen and Martin (2021) . + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPESE + url_git: '' +RPEXE.RPEXT: + version: 0.0.2 + title: Reduced Piecewise Exponential Estimate/Test Software + maintainer: Gang Han + description: This reduced piecewise exponential survival software implements the + likelihood ratio test and backward elimination procedure in Han, Schell, and Kim + (2012 , 2014 ), and Han + et al. (2016 ). Inputs to the program can be either times + when events/censoring occur or the vectors of total time on test and the number + of events. Outputs of the programs are times and the corresponding p-values in + the backward elimination. Details about the model and implementation are given + in Han et al. 2014. This program can run in R version 3.2.2 and above. + date_publication: '2020-05-21' + bug_reports: https://github.com/hangangtrue/RPEXE.RPEXT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RPEXE.RPEXT + url_git: https://github.com/hangangtrue/RPEXE.RPEXT +rpf: + version: 1.0.14 + title: Response Probability Functions + maintainer: Joshua Pritikin + description: |- + Factor out logic + and math common to Item Factor Analysis fitting, diagnostics, and + analysis. It is envisioned as core support code suitable for more + specialized IRT packages to build upon. Complete access to optimized C + functions are made available with R_RegisterCCallable(). + This software is described in Pritikin & Falk (2020) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpf + url_git: https://github.com/jpritikin/rpf +RPhosFate: + version: 1.0.4 + title: Soil and Chemical Substance Emission and Transport Model + maintainer: Gerold Hepp + description: |- + An enhanced version of the semi-empirical, spatially distributed + emission and transport model PhosFate implemented in 'R' and 'C++'. It + currently supports suspended solids (SS) and particulate phosphorus (PP). A + major feature is the allocation of substance loads entering surface waters + to their sources of origin, which is a basic requirement for the + identification of critical source areas and in consequence a cost-effective + implementation of mitigation measures. References: Hepp et al. (2022) + ; Hepp and Zessner (2019) + ; Kovacs (2013) + . + date_publication: '2023-10-07' + bug_reports: https://github.com/gisler/RPhosFate/issues + url: https://gisler.github.io/RPhosFate/ + url_cran: https://CRAN.R-project.org/package=RPhosFate + url_git: '' +Rphylopars: + version: 0.3.10 + title: |- + Phylogenetic Comparative Tools for Missing Data and + Within-Species Variation + maintainer: Eric W. Goolsby + description: Tools for performing phylogenetic comparative methods for datasets + with with multiple observations per species (intraspecific variation or measurement + error) and/or missing data (Goolsby et al. 2017). Performs ancestral state reconstruction + and missing data imputation on the estimated evolutionary model, which can be + specified as Brownian Motion, Ornstein-Uhlenbeck, Early-Burst, Pagel's lambda, + kappa, or delta, or a star phylogeny. + date_publication: '2024-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rphylopars + url_git: https://github.com/ericgoolsby/Rphylopars/wiki +rphylopic: + version: 1.5.0 + title: Get Silhouettes of Organisms from PhyloPic + maintainer: William Gearty + description: |- + Work with the PhyloPic Web Service () + to fetch silhouette images of organisms. Includes functions for adding + silhouettes to both base R plots and ggplot2 plots. + date_publication: '2024-09-04' + bug_reports: https://github.com/palaeoverse/rphylopic/issues + url: https://rphylopic.palaeoverse.org + url_cran: https://CRAN.R-project.org/package=rphylopic + url_git: https://github.com/palaeoverse/rphylopic +rpinterest: + version: 0.3.1 + title: Access Pinterest API + maintainer: Colin FAY + description: |- + Get information (boards, pins and + users) from the Pinterest + API. + date_publication: '2016-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpinterest + url_git: '' +rpivotTable: + version: 0.3.0 + title: |- + Build Powerful Pivot Tables and Dynamically Slice & Dice your + Data + maintainer: Enzo Martoglio + description: |- + Build powerful pivot tables (aka Pivot Grid, Pivot Chart, Cross-Tab) + and dynamically slice & dice / drag 'n' drop your data. 'rpivotTable' is a + wrapper of 'pivottable', a powerful open-source Pivot Table library implemented + in 'JavaScript' by Nicolas Kruchten. Aligned to 'pivottable' v2.19.0. + date_publication: '2018-01-30' + bug_reports: '' + url: http://smartinsightsfromdata.github.io + url_cran: https://CRAN.R-project.org/package=rpivotTable + url_git: https://github.com/smartinsightsfromdata +rplanes: + version: 0.1.0 + title: Plausibility Analysis of Epidemiological Signals + maintainer: VP Nagraj + description: Provides functionality to prepare data and analyze plausibility of + both forecasted and reported epidemiological signals. The functions implement + a set of plausibility algorithms that are agnostic to geographic and time resolutions + and are calculated independently then presented as a combined score. + date_publication: '2024-07-17' + bug_reports: '' + url: https://signaturescience.github.io/rplanes/ + url_cran: https://CRAN.R-project.org/package=rplanes + url_git: '' +rplec: + version: 0.1.3 + title: Placental Epigenetic Clock to Estimate Aging by DNA Methylation + maintainer: Herdiantri Sufriyana + description: Placental epigenetic clock to estimate aging based on gestational age + using DNA methylation levels, so called placental epigenetic clock (PlEC). We + developed a PlEC for the 2024 Placental Clock DREAM Challenge (). + Our PlEC achieved the top performance based on an independent test set. PlEC can + be used to identify accelerated/decelerated aging of placenta for understanding + placental dysfunction-related conditions, e.g., great obstetrical syndromes including + preeclampsia, fetal growth restriction, preterm labor, preterm premature rupture + of the membranes, late spontaneous abortion, and placental abruption. Detailed + methodologies and examples are documented in our vignette, available at . + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rplec + url_git: '' +rplotengine: + version: 1.0-9 + title: R as a Plotting Engine + maintainer: Pedro-Pablo Garrido Abenza + description: |- + Generate basic charts either by custom applications, or from a small script launched from the system console, or within the R console. Two ASCII text files are necessary: + (1) The graph parameters file, which name is passed to the function 'rplotengine()'. + The user can specify the titles, choose the type of the graph, graph output formats + (e.g. png, eps), proportion of the X-axis and Y-axis, position of the legend, + whether to show or not a grid at the background, etc. + (2) The data to be plotted, which name is specified as a parameter ('data_filename') + in the previous file. This data file has a tabulated format, with a single character + (e.g. tab) between each column. Optionally, the file could include data columns for + showing confidence intervals. + date_publication: '2023-03-13' + bug_reports: '' + url: http://www.umh.es + url_cran: https://CRAN.R-project.org/package=rplotengine + url_git: '' +rpls: + version: 0.6.0 + title: Robust Partial Least Squares + maintainer: Peter Filzmoser + description: A robust Partial Least-Squares (PLS) method is implemented that is + robust to outliers in the residuals as well as to leverage points. A specific + weighting scheme is applied which avoids iterations, and leads to a highly efficient + robust PLS estimator. + date_publication: '2020-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpls + url_git: '' +rplum: + version: 0.5.1 + title: Bayesian Age-Depth Modelling of Cores Dated by Pb-210 + maintainer: Maarten Blaauw + description: An approach to age-depth modelling that uses Bayesian statistics to + reconstruct accumulation histories for 210Pb-dated deposits using prior information. + It can combine 210Pb, radiocarbon, and other dates in the chronologies. See Aquino + et al. (2018) . Note that parts of the code underlying + 'rplum' are derived from the 'rbacon' package by the same authors, and there remains + a degree of overlap between the two packages. + date_publication: '2024-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rplum + url_git: '' +rpm: + version: 0.7-3 + title: Modeling of Revealed Preferences Matchings + maintainer: Mark S. Handcock + description: Statistical estimation of revealed preference models from data collected + on bipartite matchings. The models are for matchings within a bipartite population + where individuals have utility for people based on known and unknown characteristics. + People can form a partnership or remain unpartnered. The model represents both + the availability of potential partners of different types and preferences of individuals + for such people. The software estimates preference parameters based on sample + survey data on partnerships and population composition. The simulation of matchings + and goodness-of-fit are considered. See Goyal, Handcock, Jackson, Rendall and + Yeung (2022) . + date_publication: '2024-04-18' + bug_reports: https://github.com/handcock/rpm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rpm + url_git: https://github.com/handcock/rpm +RPMG: + version: 2.2-7 + title: |- + Graphical User Interface (GUI) for Interactive R Analysis + Sessions + maintainer: Jonathan M. Lees + description: Really Poor Man's Graphical User Interface, used to create interactive + R analysis sessions with simple R commands. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPMG + url_git: '' +RPMM: + version: '1.25' + title: Recursively Partitioned Mixture Model + maintainer: E. Andres Houseman + description: |2- + + Recursively Partitioned Mixture Model for Beta and Gaussian Mixtures. + This is a model-based clustering algorithm that returns a hierarchy + of classes, similar to hierarchical clustering, but also similar to + finite mixture models. + date_publication: '2017-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPMM + url_git: '' +rpmodel: + version: 1.2.3 + title: P-Model + maintainer: Benjamin Stocker + description: |- + Implements the P-model + (Stocker et al., 2020 ), + predicting acclimated parameters of the enzyme kinetics of C3 photosynthesis, + assimilation, and dark respiration rates as a function of the environment + (temperature, CO2, vapour pressure deficit, light, atmospheric pressure). + date_publication: '2024-06-27' + bug_reports: https://github.com/geco-bern/rpmodel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rpmodel + url_git: https://github.com/geco-bern/rpmodel +rpms: + version: 0.5.1 + title: Recursive Partitioning for Modeling Survey Data + maintainer: Daniell Toth + description: |- + Functions to allow users to build and analyze design consistent + tree and random forest models using survey data from a complex sample + design. The tree model algorithm can fit a linear model to survey data + in each node obtained by recursively partitioning the data. The splitting + variables and selected splits are obtained using a randomized permutation + test procedure which adjusted for complex sample design features used to + obtain the data. Likewise the model fitting algorithm produces + design-consistent coefficients to any specified least squares linear model + between the dependent and independent variables used in the end nodes. + The main functions return the resulting binary tree or random forest as + an object of "rpms" or "rpms_forest" type. The package also provides methods + modeling a "boosted" tree or forest model and a tree model for zero-inflated + data as well as a number of functions and methods available for use with + these object types. + date_publication: '2021-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpms + url_git: '' +rpnf: + version: 1.0.5 + title: Point and Figure Package + maintainer: Sascha Herrmann + description: |- + A set of functions to analyze and print the development of a + commodity using the Point and Figure (P&F) approach. A P&F processor can be used + to calculate daily statistics for the time series. These statistics can be used + for deeper investigations as well as to create plots. Plots can be generated as + well known X/O Plots in plain text format, and additionally in a more graphical + format. + date_publication: '2016-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpnf + url_git: '' +Rpoet: + version: 1.1.0 + title: '''PoetryDB'' API Wrapper' + maintainer: Aaron Schlegel + description: |2- + + Wrapper for the 'PoetryDB' API that allows for interaction and data extraction from the + database in an R interface. The 'PoetryDB' API is a database of poetry and poets implemented with 'MongoDB' to + enable developers and poets to easily access one of the most comprehensive poetry databases currently available. + date_publication: '2019-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rpoet + url_git: '' +RPointCloud: + version: 0.8.0 + title: Visualizing Topological Loops and Voids + maintainer: Kevin R. Coombes + description: |- + Visualizations to explain the results of a topological + data analysis. The goal of topological data analysis is to identify + persistent topological structures, such as loops (topological circles) + and voids (topological spheres), in data sets. The output of an + analysis using the 'TDA' package is a Rips diagram (named after the + mathematician Eliyahu Rips). The goal of 'RPointCloud' is to fill in + these holes in the data by providing tools to visualize the features + that help explain the structures found in the Rips diagram. See McGee + and colleagues (2024) . + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPointCloud + url_git: http://oompa.r-forge.r-project.org/ +Rpolyhedra: + version: 0.5.6 + title: Polyhedra Database + maintainer: Alejandro Baranek + description: A polyhedra database scraped from various sources as R6 objects and + 'rgl' visualizing capabilities. + date_publication: '2024-11-06' + bug_reports: https://github.com/ropensci/Rpolyhedra/issues + url: https://docs.ropensci.org/Rpolyhedra/ + url_cran: https://CRAN.R-project.org/package=Rpolyhedra + url_git: https://github.com/ropensci/Rpolyhedra +Rpoppler: + version: 0.1-3 + title: PDF Tools Based on Poppler + maintainer: Kurt Hornik + description: |- + PDF tools based on the Poppler PDF rendering library. + See for more information on Poppler. + date_publication: '2024-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rpoppler + url_git: '' +rportfolio: + version: 0.0.3 + title: Portfolio Theory + maintainer: Anurag Agrawal + description: Collection of tools to calculate portfolio performance metrics. Portfolio + performance is a key measure for investors. These metrics are important to analyse + how effectively their money has been invested. This package uses portfolio theories + to give investor tools to evaluate their portfolio performance. For more information + see, Markowitz, H.M. (1952), . Analysis of Investments & + Management of Portfolios [2012, ISBN:978-8131518748]. + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rportfolio + url_git: '' +rpostgis: + version: 1.6.0 + title: R Interface to a 'PostGIS' Database + maintainer: Adrian Cidre Gonzalez + description: |- + Provides an interface between R and 'PostGIS'-enabled + 'PostgreSQL' databases to transparently transfer spatial + data. Both vector (points, lines, polygons) and raster data are + supported in read and write modes. Also provides convenience + functions to execute common procedures in 'PostgreSQL/PostGIS'. + date_publication: '2024-12-06' + bug_reports: https://github.com/Cidree/rpostgis/issues + url: https://cidree.github.io/rpostgis/ + url_cran: https://CRAN.R-project.org/package=rpostgis + url_git: https://github.com/Cidree/rpostgis +RPostgres: + version: 1.4.8 + title: C++ Interface to PostgreSQL + maintainer: Kirill Müller + description: |- + Fully DBI-compliant C++-backed interface to PostgreSQL + , an open-source relational database. + date_publication: '2025-02-25' + bug_reports: https://github.com/r-dbi/RPostgres/issues + url: https://rpostgres.r-dbi.org + url_cran: https://CRAN.R-project.org/package=RPostgres + url_git: https://github.com/r-dbi/RPostgres +RPostgreSQL: + version: 0.7-7 + title: R Interface to the 'PostgreSQL' Database System + maintainer: Tomoaki Nishiyama + description: |- + Database interface and 'PostgreSQL' driver for 'R'. + This package provides a Database Interface 'DBI' compliant + driver for 'R' to access 'PostgreSQL' database systems. + In order to build and install this package from source, 'PostgreSQL' + itself must be present your system to provide 'PostgreSQL' functionality + via its libraries and header files. These files are provided as + 'postgresql-devel' package under some Linux distributions. + On 'macOS' and 'Microsoft Windows' system the attached 'libpq' library source will be used. + date_publication: '2024-09-30' + bug_reports: '' + url: https://www.postgresql.org + url_cran: https://CRAN.R-project.org/package=RPostgreSQL + url_git: https://github.com/tomoakin/RPostgreSQL +rPowerSampleSize: + version: 1.0.2 + title: |- + Sample Size Computations Controlling the Type-II Generalized + Family-Wise Error Rate + maintainer: Pierre Lafaye de Micheaux + description: The significance of mean difference tests in clinical trials is established + if at least r null hypotheses are rejected among m that are simultaneously tested. + This package enables one to compute necessary sample sizes for single-step (Bonferroni) + and step-wise procedures (Holm and Hochberg). These three procedures control the + q-generalized family-wise error rate (probability of making at least q false rejections). + Sample size is computed (for these single-step and step-wise procedures) in a + such a way that the r-power (probability of rejecting at least r false null hypotheses, + i.e. at least r significant endpoints among m) is above some given threshold, + in the context of tests of difference of means for two groups of continuous endpoints + (variables). Various types of structure of correlation are considered. It is also + possible to analyse data (i.e., actually test difference in means) when these + are available. The case r equals 1 is treated in separate functions that were + used in Lafaye de Micheaux et al. (2014) . + date_publication: '2018-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rPowerSampleSize + url_git: '' +RPPanalyzer: + version: 1.4.9 + title: |- + Reads, Annotates, and Normalizes Reverse Phase Protein Array + Data + maintainer: Torsten Schoeps + description: |- + Reads in sample description and slide description files and + annotates the expression values taken from GenePix results files + (text file format used by many microarray scanner and software providers). + After normalization data can be visualized as boxplot, heatmap or dotplot. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPPanalyzer + url_git: '' +RPPASPACE: + version: 1.0.10 + title: |- + Reverse-Phase Protein Array Super Position and Concentration + Evaluation + maintainer: James M. Melott + description: 'Provides tools for the analysis of reverse-phase protein arrays (RPPAs), + which are also known as ''tissue lysate arrays'' or simply ''lysate arrays''. + The package''s primary purpose is to input a set of quantification files representing + dilution series of samples and control points taken from scanned RPPA slides and + determine a relative log concentration value for each valid dilution series present + in each slide and provide graphical visualization of the input and output data + and their relationships. Other optional features include generation of quality + control scores for judging the quality of the input data, spatial adjustment of + sample points based on controls added to the slides, and various types of normalization + of calculated values across a set of slides. The package was derived from a previous + package named SuperCurve. For a detailed description of data inputs and outputs, + usage information, and a list of related papers describing methods used in the + package please review the vignette ''Guide_to_RPPASPACE''. ''RPPA SPACE: an R + package for normalization and quantitation of Reverse-Phase Protein Array data''. + Bioinformatics Nov 15;38(22):5131-5133. .' + date_publication: '2023-10-19' + bug_reports: '' + url: https://pubmed.ncbi.nlm.nih.gov/36205581 + url_cran: https://CRAN.R-project.org/package=RPPASPACE + url_git: https://github.com/MD-Anderson-Bioinformatics/rppaspace +rpql: + version: 0.8.1 + title: Regularized PQL for Joint Selection in GLMMs + maintainer: Francis Hui + description: Performs joint selection in Generalized Linear Mixed Models (GLMMs) + using penalized likelihood methods. Specifically, the Penalized Quasi-Likelihood + (PQL) is used as a loss function, and penalties are then augmented to perform + simultaneous fixed and random effects selection. Regularized PQL avoids the need + for integration (or approximations such as the Laplace's method) during the estimation + process, and so the full solution path for model selection can be constructed + relatively quickly. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpql + url_git: '' +rPraat: + version: 1.3.2-1 + title: Interface to Praat + maintainer: Tomas Boril + description: Read, write and manipulate 'Praat' TextGrid, PitchTier, Pitch, IntensityTier, + Formant, Sound, and Collection files . + date_publication: '2021-02-27' + bug_reports: https://github.com/bbTomas/rPraat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rPraat + url_git: https://github.com/bbTomas/rPraat/ +rpredictit: + version: 0.1.0 + title: Interface to the 'PredictIt' API + maintainer: Daniel Kovtun + description: |- + Wrapper to retrieve market data, explore available markets, and plot historical price data from the 'PredictIt' public API (). + The package comes with a demo 'shiny' application for illustrating example use cases. + License to use data made available via the API is for non-commercial use and 'PredictIt' is the sole source of such data. + date_publication: '2022-07-19' + bug_reports: https://github.com/danielkovtun/rpredictit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rpredictit + url_git: https://github.com/danielkovtun/rpredictit +rPref: + version: 1.4.0 + title: Database Preferences and Skyline Computation + maintainer: Patrick Roocks + description: |- + Routines to select and visualize the maxima for a given strict + partial order. This especially includes the computation of the Pareto + frontier, also known as (Top-k) Skyline operator (see Börzsönyi, et al. + (2001) ), and some generalizations + known as database preferences (see Kießling (2002) + ). + date_publication: '2023-01-30' + bug_reports: '' + url: https://www.p-roocks.de/rpref/ + url_cran: https://CRAN.R-project.org/package=rPref + url_git: '' +RPregression: + version: 0.1.0 + title: A Simple Regression and Plotting Tool + maintainer: Raghav Puri + description: Perform a regression analysis, generate a regression table, create + a scatter plot, and download the results. It uses 'stargazer' for generating regression + tables and 'ggplot2' for creating plots. With just two lines of code, you can + perform a regression analysis, visualize the results, and save the output. It + is part of my make R easy project where one doesn't need to know how to use various + packages in order to get results and makes it easily accessible to beginners. + This is a part of my make R easy project. Help from 'ChatGPT' was taken. References + were Wickham (2016) . + date_publication: '2024-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPregression + url_git: '' +RPresto: + version: 1.4.7 + title: DBI Connector to Presto + maintainer: Jarod G.R. Meng + description: |- + Implements a 'DBI' compliant interface to Presto. Presto is + an open source distributed SQL query engine for running interactive + analytic queries against data sources of all sizes ranging from + gigabytes to petabytes: . + date_publication: '2025-01-08' + bug_reports: https://github.com/prestodb/RPresto/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RPresto + url_git: https://github.com/prestodb/RPresto +rprev: + version: 1.0.5 + title: Estimating Disease Prevalence from Registry Data + maintainer: Stuart Lacy + description: |- + Estimates disease prevalence for a given index date using existing + registry data extended with Monte Carlo simulations following the method of Crouch et al (2014) . + date_publication: '2021-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rprev + url_git: https://github.com/stulacy/rprev-dev +rprime: + version: 0.1.2 + title: Functions for Working with 'Eprime' Text Files + maintainer: Tristan Mahr + description: |- + 'Eprime' is a set of programs for administering + psychological experiments by computer. This package provides functions + for loading, parsing, filtering and exporting data in the text files + produced by 'Eprime' experiments. + date_publication: '2020-09-24' + bug_reports: https://github.com/tjmahr/rprime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rprime + url_git: https://github.com/tjmahr/rprime +rprintf: + version: 0.2.1 + title: Adaptive Builder for Formatted Strings + maintainer: Kun Ren + description: |- + Provides a set of functions to facilitate building formatted strings + under various replacement rules: C-style formatting, variable-based formatting, + and number-based formatting. C-style formatting is basically identical to built-in + function 'sprintf'. Variable-based formatting allows users to put variable names + in a formatted string which will be replaced by variable values. Number-based + formatting allows users to use index numbers to represent the corresponding + argument value to appear in the string. + date_publication: '2015-09-09' + bug_reports: https://github.com/renkun-ken/rprintf/issues + url: http://renkun.me/rprintf + url_cran: https://CRAN.R-project.org/package=rprintf + url_git: https://github.com/renkun-ken/rprintf +RprobitB: + version: 1.1.4 + title: Bayesian Probit Choice Modeling + maintainer: Lennart Oelschläger + description: |2- + + Bayes estimation of probit choice models, both in the cross-sectional and + panel setting. The package can analyze binary, multivariate, ordered, and + ranked choices, as well as heterogeneity of choice behavior among deciders. + The main functionality includes model fitting via Markov chain Monte Carlo m + ethods, tools for convergence diagnostic, choice data simulation, in-sample + and out-of-sample choice prediction, and model selection using information + criteria and Bayes factors. The latent class model extension facilitates + preference-based decider classification, where the number of latent classes + can be inferred via the Dirichlet process or a weight-based updating + heuristic. This allows for flexible modeling of choice behavior without the + need to impose structural constraints. + For a reference on the method see Oelschlaeger and Bauer (2021) + . + date_publication: '2024-02-26' + bug_reports: https://github.com/loelschlaeger/RprobitB/issues + url: https://loelschlaeger.de/RprobitB/ + url_cran: https://CRAN.R-project.org/package=RprobitB + url_git: https://github.com/loelschlaeger/RprobitB +RProbSup: + version: '3.0' + title: Calculates Probability of Superiority + maintainer: John Ruscio + description: |- + The A() function calculates the A statistic, a nonparametric + measure of effect size for two independent groups that’s also known as + the probability of superiority (Ruscio, 2008), along with its standard + error and a confidence interval constructed using bootstrap methods + (Ruscio & Mullen, 2012). Optional arguments can be specified to + calculate variants of the A statistic developed for other research + designs (e.g., related samples, more than two independent groups or + related samples; Ruscio & Gera, 2013). + . + . + . + date_publication: '2020-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RProbSup + url_git: '' +Rprofet: + version: 3.1.1 + title: WOE Transformation and Scorecard Builder + maintainer: Thomas Brandenburger + description: Performs all steps in the credit scoring process. This package allows + the user to follow all the necessary steps for building an effective scorecard. + It provides the user functions for coarse binning of variables, Weights of Evidence + (WOE) transformation, variable clustering, custom binning, visualization, and + scaling of logistic regression coefficients. The results will generate a scorecard + that can be used as an effective credit scoring tool to evaluate risk. For complete + details on the credit scoring process, see Siddiqi (2005, ISBN:047175451X). + date_publication: '2024-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rprofet + url_git: '' +rprofile: + version: 0.4.0 + title: |- + Load Both User-Global and Project-Specific R Profile + Configurations + maintainer: Konrad Rudolph + description: |- + Use rprofile::load() inside a project '.Rprofile' file to ensure that the user-global '.Rprofile' is + loaded correctly regardless of its location, and other common resources (in particular 'renv') are also set up + correctly. + date_publication: '2023-11-01' + bug_reports: https://github.com/klmr/rprofile/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rprofile + url_git: '' +rprojroot: + version: 2.0.4 + title: Finding Files in Project Subdirectories + maintainer: Kirill Müller + description: |- + Robust, reliable and flexible paths to files below + a project root. The 'root' of a project is defined as a directory that + matches a certain criterion, e.g., it contains a certain regular file. + date_publication: '2023-11-05' + bug_reports: https://github.com/r-lib/rprojroot/issues + url: https://rprojroot.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=rprojroot + url_git: https://github.com/r-lib/rprojroot +rprojtree: + version: 1.0.0 + title: Create Folders and Files Structure for Data Science Projects + maintainer: Miguel Conde + description: Use JSON templates to create folders and files structure for data science + projects. Includes customized templates and accepts your own as JSON files. + date_publication: '2022-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rprojtree + url_git: https://github.com/miguel-conde/rprojtree +RProtoBuf: + version: 0.4.23 + title: R Interface to the 'Protocol Buffers' 'API' (Version 2 or 3) + maintainer: Dirk Eddelbuettel + description: |- + Protocol Buffers are a way of encoding structured data in an + efficient yet extensible format. Google uses Protocol Buffers for almost all + of its internal 'RPC' protocols and file formats. Additional documentation + is available in two included vignettes one of which corresponds to our 'JSS' + paper (2016, . A sufficiently recent version of + 'Protocol Buffers' library is required; currently version 3.3.0 from 2017 + is the stated minimum. + date_publication: '2025-01-14' + bug_reports: https://github.com/eddelbuettel/rprotobuf/issues + url: https://dirk.eddelbuettel.com/code/rprotobuf.html + url_cran: https://CRAN.R-project.org/package=RProtoBuf + url_git: https://github.com/eddelbuettel/rprotobuf +RPscoring: + version: 0.1.0 + title: Relative Placement Algorithm + maintainer: Daphna Harel + description: Implementation of the relative placement algorithm widely used in the + scoring of Lindy Hop and West Coast Swing dance contests. + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPscoring + url_git: '' +rpsftm: + version: 1.2.9 + title: Rank Preserving Structural Failure Time Models + maintainer: Simon Bond + description: Implements methods described by the paper Robins and Tsiatis (1991) + . These use g-estimation to estimate the causal + effect of a treatment in a two-armed randomised control trial where non-compliance + exists and is measured, under an assumption of an accelerated failure time model + and no unmeasured confounders. + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rpsftm + url_git: '' +RPtests: + version: 0.1.5 + title: |- + Goodness of Fit Tests for High-Dimensional Linear Regression + Models + maintainer: Rajen Shah + description: |- + Performs goodness of fits tests for both high and low-dimensional linear models. + It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity. + In addition one can test the significance of potentially large groups of variables, and also + produce p-values for the significance of individual variables in high-dimensional linear + regression. + date_publication: '2021-07-10' + bug_reports: '' + url: https://rss.onlinelibrary.wiley.com/doi/10.1111/rssb.12234 + url_cran: https://CRAN.R-project.org/package=RPtests + url_git: '' +rptR: + version: 0.9.22 + title: Repeatability Estimation for Gaussian and Non-Gaussian Data + maintainer: Martin Stoffel + description: |- + Estimating repeatability (intra-class + correlation) from Gaussian, binary, proportion and Poisson data. + date_publication: '2019-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rptR + url_git: '' +RPublica: + version: 0.1.3 + title: ProPublica API Client + maintainer: Thomas J. Leeper + description: Client for accessing data journalism APIs from ProPublica . + date_publication: '2015-12-22' + bug_reports: https://github.com/rOpenGov/RPublica/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RPublica + url_git: https://github.com/rOpenGov/RPublica +RPushbullet: + version: 0.3.4 + title: R Interface to the Pushbullet Messaging Service + maintainer: Dirk Eddelbuettel + description: |- + An R interface to the Pushbullet messaging service which + provides fast and efficient notifications (and file transfer) between + computers, phones and tablets. An account has to be registered at the + site site to obtain a (free) API key. + date_publication: '2021-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RPushbullet + url_git: '' +rpyANTs: + version: 0.0.4 + title: An Alternative Advanced Normalization Tools ('ANTs') + maintainer: Zhengjia Wang + description: |- + Provides portable access from 'R' to biomedical image processing toolbox + 'ANTs' by Avants et al. (2009) via seamless + integration with the 'Python' implementation 'ANTsPy'. Allows biomedical + images to be processed in 'Python' and analyzed in 'R', and vice versa + via shared memory. See 'citation("rpyANTs")' for more reference information. + date_publication: '2024-12-17' + bug_reports: https://github.com/dipterix/rpyANTs/issues + url: http://dipterix.org/rpyANTs/ + url_cran: https://CRAN.R-project.org/package=rpyANTs + url_git: '' +RPyGeo: + version: 1.0.0 + title: ArcGIS Geoprocessing via Python + maintainer: Alexander Brenning + description: |- + Provides access to ArcGIS geoprocessing tools by building an + interface between R and the ArcPy Python side-package via the + reticulate package. + date_publication: '2018-11-14' + bug_reports: https://github.com/fapola/RPyGeo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RPyGeo + url_git: https://github.com/fapola/RPyGeo +rpymat: + version: 0.1.7 + title: Easy to Configure an Isolated 'Python' Environment + maintainer: Zhengjia Wang + description: |- + Aims to create a single isolated 'Miniconda' + and 'Python' environment for reproducible pipeline scripts. + The package provides utilities to run system command within the 'conda' + environment, making it easy to install, launch, manage, and stop + 'Jupyter-lab'. + date_publication: '2023-08-22' + bug_reports: https://github.com/dipterix/rpymat/issues + url: http://dipterix.org/rpymat/ + url_cran: https://CRAN.R-project.org/package=rpymat + url_git: https://github.com/dipterix/rpymat +rqcanon: + version: 0.1.0 + title: Canonical Quantile Regression + maintainer: Stephen Portnoy + description: 'A quantile regression method for multivariate data to find linear + combinations of explanatory and response variables generalizing canonical correlation. + The package consists of functions, rqcan() for fitting the coefficients, and summary.rqcan(), + which calls a bootstrap function. For details, see the help files for rqcan() + and summary.rqcan(), and the reference: Portnoy (2022) .' + date_publication: '2024-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rqcanon + url_git: '' +rQCC: + version: 2.22.12 + title: Robust Quality Control Chart + maintainer: Chanseok Park + description: Constructs various robust quality control charts based on the median + or Hodges-Lehmann estimator (location) and the median absolute deviation (MAD) + or Shamos estimator (scale). The estimators used for the robust control charts + are all unbiased with a sample of finite size. For more details, see Park, Kim + and Wang (2022) . In addition, using this R + package, the conventional quality control charts such as X-bar, S, R, p, np, u, + c, g, h, and t charts are also easily constructed. This work was supported by + the National Research Foundation of Korea (NRF) grant funded by the Korea government + (MSIT) (No. 2022R1A2C1091319). + date_publication: '2022-12-22' + bug_reports: https://GitHub.com/AppliedStat/R/issues + url: https://AppliedStat.GitHub.io/R/ + url_cran: https://CRAN.R-project.org/package=rQCC + url_git: '' +rqdatatable: + version: 1.3.3 + title: '''rquery'' for ''data.table''' + maintainer: John Mount + description: |- + Implements the 'rquery' piped Codd-style query algebra using 'data.table'. This allows + for a high-speed in memory implementation of Codd-style data manipulation tools. + date_publication: '2023-08-21' + bug_reports: https://github.com/WinVector/rqdatatable/issues + url: https://winvector.github.io/rqdatatable/ + url_cran: https://CRAN.R-project.org/package=rqdatatable + url_git: https://github.com/WinVector/rqdatatable/ +RQdeltaCT: + version: 1.3.2 + title: |- + Relative Quantification of Gene Expression using Delta Ct + Methods + maintainer: Daniel Zalewski + description: The commonly used methods for relative quantification of gene expression + levels obtained in real-time PCR (Polymerase Chain Reaction) experiments are the + delta Ct methods, encompassing 2^-dCt and 2^-ddCt methods, originally proposed + by Kenneth J. Livak and Thomas D. Schmittgen (2001) . + The main idea is to normalise gene expression values using endogenous control + gene, present gene expression levels in linear form by using the 2^-(value)^ transformation, + and calculate differences in gene expression levels between groups of samples + (or technical replicates of a single sample). The 'RQdeltaCT' package offers functions + that cover both methods for comparison of either independent groups of samples + or groups with paired samples, together with importing expression datasets, performing + multi-step quality control of data, enabling numerous data visualisations, enrichment + of the standard workflow with additional useful analyses (correlation analysis, + Receiver Operating Characteristic analysis, logistic regression), and conveniently + export obtained results in table and image formats. The package has been designed + to be friendly to non-experts in R programming. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RQdeltaCT + url_git: +RQEntangle: + version: 0.1.3 + title: Quantum Entanglement of Bipartite System + maintainer: Kwan-Yuet Ho + description: |- + It computes the Schmidt decomposition of bipartite quantum systems, discrete or continuous, + and their respective entanglement metrics. See Artur Ekert, Peter L. Knight (1995) + for more details. + date_publication: '2019-01-04' + bug_reports: https://github.com/stephenhky/RQEntangle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RQEntangle + url_git: https://github.com/stephenhky/RQEntangle +rqlm: + version: 2.3-1 + title: |- + Modified Poisson and Least-Squares Regressions for Binary + Outcome and Their Generalizations + maintainer: Hisashi Noma + description: Modified Poisson and least-squares regression analyses for binary outcomes + of Zou (2004) and Cheung (2007) + have been standard multivariate analysis methods to estimate risk ratio and risk + difference in clinical and epidemiological studies. This R package involves an + easy-to-handle function to implement these analyses by simple commands. Missing + data analysis tools (multiple imputation) are also involved. In addition, recent + studies have shown the ordinary robust variance estimator possibly has serious + bias under small or moderate sample size situations for these methods. This package + also provides computational tools to calculate alternative accurate confidence + intervals (Noma and Gosho (2024) ). + date_publication: '2025-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rqlm + url_git: '' +rqPen: + version: 4.1.3 + title: Penalized Quantile Regression + maintainer: Ben Sherwood + description: Performs penalized quantile regression with LASSO, elastic net, SCAD + and MCP penalty functions including group penalties. In addition, offers a group + penalty that provides consistent variable selection across quantiles. Provides + a function that automatically generates lambdas and evaluates different models + with cross validation or BIC, including a large p version of BIC. Below URL provides + a link to a work in progress vignette. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rqPen + url_git: https://github.com/bssherwood/rqpen/blob/master/ignore/rqPenArticle.pdf +rQSAR: + version: 1.0.0 + title: |- + QSAR Modeling with Multiple Algorithms: MLR, PLS, and Random + Forest + maintainer: Oche Ambrose George + description: Quantitative Structure-Activity Relationship (QSAR) modeling is a valuable + tool in computational chemistry and drug design, where it aims to predict the + activity or property of chemical compounds based on their molecular structure. + In this vignette, we present the 'rQSAR' package, which provides functions for + variable selection and QSAR modeling using Multiple Linear Regression (MLR), Partial + Least Squares (PLS), and Random Forest algorithms. + date_publication: '2024-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rQSAR + url_git: '' +rqti: + version: 0.3.0 + title: Create Tests According to QTI 2.1 Standard + maintainer: Andrey Shevandrin + description: Create tests and tasks compliant with the Question & Test Interoperability + (QTI) information model version 2.1. Input sources are Rmd/md description files + or S4-class objects. Output formats include standalone zip or xml files. Supports + the generation of basic task types (single and multiple choice, order, pair association, + matching tables, filling gaps and essay) and provides a comprehensive set of attributes + for customizing tests. + date_publication: '2024-07-19' + bug_reports: https://github.com/shevandrin/rqti/issues + url: https://shevandrin.github.io/rqti/ + url_cran: https://CRAN.R-project.org/package=rqti + url_git: https://github.com/shevandrin/rqti +Rquake: + version: 2.5-1 + title: Seismic Hypocenter Determination + maintainer: Jonathan M. Lees + description: Non-linear inversion for hypocenter estimation and analysis of seismic + data collected continuously, or in trigger mode. The functions organize other + functions from 'RSEIS' and 'GEOmap' to help researchers pick, locate, and store + hypocenters for detailed seismic investigation. Error ellipsoids and station influence + are estimated via jackknife analysis. References include Iversen, E. S., and + J. M. Lees (1996). + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rquake + url_git: '' +RQuantLib: + version: 0.4.24 + title: R Interface to the 'QuantLib' Library + maintainer: Dirk Eddelbuettel + description: |- + The 'RQuantLib' package makes parts of 'QuantLib' accessible from R + The 'QuantLib' project aims to provide a comprehensive software framework + for quantitative finance. The goal is to provide a standard open source library + for quantitative analysis, modeling, trading, and risk management of financial + assets. + date_publication: '2024-07-31' + bug_reports: https://github.com/eddelbuettel/rquantlib/issues + url: https://dirk.eddelbuettel.com/code/rquantlib.html + url_cran: https://CRAN.R-project.org/package=RQuantLib + url_git: https://github.com/eddelbuettel/rquantlib +Rquefts: + version: 1.2-4 + title: |- + Quantitative Evaluation of the Native Fertility of Tropical + Soils + maintainer: Robert J. Hijmans + description: An implementation of the QUEFTS (Quantitative Evaluation of the Native + Fertility of Tropical Soils) model. The model (1) estimates native nutrient (N, + P, K) supply of soils from a few soil chemical properties; and (2) computes crop + yield given that supply, crop parameters, fertilizer application, and crop attainable + yield. See Janssen et al. (1990) for the technical + details and Sattari et al. (2014) for a recent + evaluation and improvements. + date_publication: '2024-10-23' + bug_reports: https://github.com/cropmodels/Rquefts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rquefts + url_git: '' +rquery: + version: 1.4.99 + title: Relational Query Generator for Data Manipulation at Scale + maintainer: John Mount + description: |- + A piped query generator based on Edgar F. Codd's relational + algebra, and on production experience using 'SQL' and 'dplyr' at big data + scale. The design represents an attempt to make 'SQL' more teachable by + denoting composition by a sequential pipeline notation instead of nested + queries or functions. The implementation delivers reliable high + performance data processing on large data systems such as 'Spark', + databases, and 'data.table'. Package features include: data processing trees + or pipelines as observable objects (able to report both columns + produced and columns used), optimized 'SQL' generation as an explicit + user visible table modeling step, plus explicit query reasoning and checking. + date_publication: '2023-08-20' + bug_reports: https://github.com/WinVector/rquery/issues + url: https://winvector.github.io/rquery/ + url_cran: https://CRAN.R-project.org/package=rquery + url_git: https://github.com/WinVector/rquery/ +rquest: + version: 1.0.3 + title: Hypothesis Tests for Quantiles and Quantile-Based Measures + maintainer: Shenal Dedduwakumara + description: |- + Functions to conduct hypothesis tests and derive confidence intervals + for quantiles, linear combinations of quantiles, + ratios of dependent linear combinations and differences + and ratios of all of the above for comparisons between independent samples. + Additionally, quantile-based measures of inequality are also considered. + date_publication: '2025-01-09' + bug_reports: https://github.com/shenal-dkumara/rquest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rquest + url_git: https://github.com/shenal-dkumara/rquest +rr: + version: 1.4.2 + title: Statistical Methods for the Randomized Response Technique + maintainer: Graeme Blair + description: |- + Enables researchers to conduct multivariate statistical analyses + of survey data with randomized response technique items from several designs, + including mirrored question, forced question, and unrelated question. This + includes regression with the randomized response as the outcome and logistic + regression with the randomized response item as a predictor. In addition, + tools for conducting power analysis for designing randomized response items + are included. The package implements methods described in Blair, Imai, and Zhou + (2015) ''Design and Analysis of the Randomized Response Technique,'' Journal + of the American Statistical Association + . + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rr + url_git: '' +rr2: + version: 1.1.1 + title: R2s for Regression Models + maintainer: Anthony Ives + description: |- + Three methods to calculate R2 for models with correlated errors, + including Phylogenetic GLS, Phylogenetic Logistic Regression, Linear Mixed + Models (LMMs), and Generalized Linear Mixed Models (GLMMs). See details in + Ives 2018 . + date_publication: '2023-08-21' + bug_reports: https://github.com/arives/rr2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rr2 + url_git: https://github.com/arives/rr2 +Rramas: + version: 0.1-6 + title: Matrix Population Models + maintainer: Marcelino de la Cruz + description: Analyzes and predicts from matrix population models (Caswell 2006) + . + date_publication: '2019-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rramas + url_git: '' +rrandvec: + version: 1.0.0 + title: Generate Random Vectors Whose Components Sum Up to One + maintainer: Jakob Bossek + description: A single method implementing multiple approaches to generate pseudo-random + vectors whose components sum up to one (see, e.g., Maziero (2015) ). + The components of such vectors can for example be used for weighting objectives + when reducing multi-objective optimisation problems to a single-objective problem + in the socalled weighted sum scalarisation approach. + date_publication: '2023-03-30' + bug_reports: https://github.com/jakobbossek/rrandvec/issues + url: https://jakobbossek.github.io/rrandvec/ + url_cran: https://CRAN.R-project.org/package=rrandvec + url_git: https://github.com/jakobbossek/rrandvec +rrapply: + version: 1.2.7 + title: Revisiting Base Rapply + maintainer: Joris Chau + description: The minimal 'rrapply'-package contains a single function rrapply(), + providing an extended implementation of 'R'-base rapply() by allowing to recursively + apply a function to elements of a nested list based on a general condition function + and including the possibility to prune or aggregate nested list elements from + the result. In addition, special arguments can be supplied to access the name, + location, parents and siblings in the nested list of the element under evaluation. + The rrapply() function builds upon rapply()'s native 'C' implementation and requires + no other package dependencies. + date_publication: '2024-06-26' + bug_reports: https://github.com/JorisChau/rrapply/issues + url: https://jorischau.github.io/rrapply/ + url_cran: https://CRAN.R-project.org/package=rrapply + url_git: https://github.com/JorisChau/rrapply +rrat: + version: 1.0.0 + title: Robust Regression with Asymmetric Heavy-Tail Noise Distributions + maintainer: Yi He + description: Implementation of Robust Regression tailored to deal with Asymmetric + noise Distribution, which was originally proposed by Takeuchi & Bengio & Kanamori + (2002) . In addition, this implementation is extended + as introducing potential feature regularization by LASSO etc. + date_publication: '2019-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rrat + url_git: '' +RRate: + version: '1.0' + title: Estimating Replication Rate for Genome-Wide Association Studies + maintainer: Wei Jiang + description: Replication Rate (RR) is the probability of replicating a statistically + significant association in genome-wide association studies. This R-package provide + the estimation method for replication rate which makes use of the summary statistics + from the primary study. We can use the estimated RR to determine the sample size + of the replication study, and to check the consistency between the results of + the primary study and those of the replication study. + date_publication: '2016-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRate + url_git: '' +Rraven: + version: 1.0.14 + title: Connecting R and 'Raven' Sound Analysis Software + maintainer: Marcelo Araya-Salas + description: A tool to exchange data between R and 'Raven' sound analysis software + (Cornell Lab of Ornithology). Functions work on data formats compatible with the + R package 'warbleR'. + date_publication: '2024-08-19' + bug_reports: https://github.com/maRce10/Rraven/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rraven + url_git: https://github.com/maRce10/Rraven +rrBLUP: + version: 4.6.3 + title: Ridge Regression and Other Kernels for Genomic Selection + maintainer: Jeffrey Endelman + description: Software for genomic prediction with the RR-BLUP mixed model (Endelman + 2011, ). One application is to estimate marker + effects by ridge regression; alternatively, BLUPs can be calculated based on an + additive relationship matrix or a Gaussian kernel. + date_publication: '2023-12-10' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=rrBLUP + url_git: '' +RRBoost: + version: '0.2' + title: A Robust Boosting Algorithm + maintainer: Xiaomeng Ju + description: 'An implementation of robust boosting algorithms for regression in + R. This includes the RRBoost method proposed in the paper "Robust Boosting for + Regression Problems" (Ju X and Salibian-Barrera M. 2020) . + It also implements previously proposed boosting algorithms in the simulation section + of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) ) + and Robloss (Lutz et al. (2008) ).' + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRBoost + url_git: '' +rrcov: + version: 1.7-6 + title: Scalable Robust Estimators with High Breakdown Point + maintainer: Valentin Todorov + description: |- + Robust Location and Scatter Estimation and Robust + Multivariate Analysis with High Breakdown Point: + principal component analysis (Filzmoser and Todorov (2013), ), + linear and quadratic discriminant analysis (Todorov and Pires (2007)), + multivariate tests (Todorov and Filzmoser (2010) ), + outlier detection (Todorov et al. (2010) ). + See also Todorov and Filzmoser (2009) , + Todorov and Filzmoser (2010) and + Boudt et al. (2019) . + date_publication: '2024-08-19' + bug_reports: https://github.com/valentint/rrcov/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rrcov + url_git: https://github.com/valentint/rrcov +rrcov3way: + version: 0.5-0 + title: |- + Robust Methods for Multiway Data Analysis, Applicable also for + Compositional Data + maintainer: Valentin Todorov + description: |- + Provides methods for multiway data analysis by means of Parafac + and Tucker 3 models. Robust versions (Engelen and Hubert (2011) ) and versions + for compositional data are also provided (Gallo (2015) , Di Palma et al. (2018) ). + Several optimization methods alternative to ALS are available + (Simonacci and Gallo (2019) , Simonacci and Gallo (2020) ). + date_publication: '2024-02-06' + bug_reports: https://github.com/valentint/rrcov3way/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rrcov3way + url_git: https://github.com/valentint/rrcov3way +rrcovHD: + version: 0.3-1 + title: Robust Multivariate Methods for High Dimensional Data + maintainer: Valentin Todorov + description: |- + Robust multivariate methods for high dimensional data including + outlier detection (Filzmoser and Todorov (2013) ), + robust sparse PCA (Croux et al. (2013) , Todorov and Filzmoser (2013) ), + robust PLS (Todorov and Filzmoser (2014) ), + and robust sparse classification (Ortner et al. (2020) ). + date_publication: '2024-08-17' + bug_reports: https://github.com/valentint/rrcovHD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rrcovHD + url_git: https://github.com/valentint/rrcovHD +rrcovNA: + version: 0.5-2 + title: |- + Scalable Robust Estimators with High Breakdown Point for + Incomplete Data + maintainer: Valentin Todorov + description: |- + Robust Location and Scatter Estimation and Robust + Multivariate Analysis with High Breakdown Point for Incomplete + Data (missing values) (Todorov et al. (2010) ). + date_publication: '2024-08-17' + bug_reports: https://github.com/valentint/rrcovNA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rrcovNA + url_git: https://github.com/valentint/rrcovNA +Rrdap: + version: 1.0.7 + title: RDAP Server Querying + maintainer: Brad Cable + description: Queries data from RDAP servers. + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rrdap + url_git: '' +rrecsys: + version: 0.9.7.3.1 + title: Environment for Evaluating Recommender Systems + maintainer: Ludovik Çoba + description: 'Processes standard recommendation datasets (e.g., a user-item rating + matrix) as input and generates rating predictions and lists of recommended items. + Standard algorithm implementations which are included in this package are the + following: Global/Item/User-Average baselines, Weighted Slope One, Item-Based + KNN, User-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according + to the standard offline evaluation methodology (Shani, et al. (2011) ) + for recommender systems using measures such as MAE, RMSE, Precision, Recall, F1, + AUC, NDCG, RankScore and coverage measures. The package (Coba, et al.(2017) ) is intended for rapid prototyping of recommendation + algorithms and education purposes.' + date_publication: '2019-06-09' + bug_reports: https://github.com/ludovikcoba/rrecsys/issues + url: https://rrecsys.inf.unibz.it/ + url_cran: https://CRAN.R-project.org/package=rrecsys + url_git: '' +rredlist: + version: 1.0.0 + title: '''IUCN'' Red List Client' + maintainer: William Gearty + description: |- + 'IUCN' Red List () client. + The 'IUCN' Red List is a global list of threatened and endangered species. + Functions cover all of the Red List 'API' routes. An 'API' key is required. + date_publication: '2025-01-31' + bug_reports: https://github.com/ropensci/rredlist/issues + url: https://docs.ropensci.org/rredlist/ + url_cran: https://CRAN.R-project.org/package=rredlist + url_git: https://github.com/ropensci/rredlist +RRedshiftSQL: + version: 0.1.2 + title: R Interface to the 'Redshift' Database + maintainer: Michael Treadwell + description: Superclasses 'PostgreSQL' connection to help enable full 'dplyr' functionality + on 'Redshift'. + date_publication: '2016-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRedshiftSQL + url_git: '' +rrefine: + version: 2.1.0 + title: r Client for OpenRefine API + maintainer: VP Nagraj + description: '''OpenRefine'' (formerly ''Google Refine'') is a popular, open source + data cleaning software. This package enables users to programmatically trigger + data transfer between R and ''OpenRefine''. Available functionality includes project + import, export and deletion.' + date_publication: '2022-11-15' + bug_reports: https://github.com/vpnagraj/rrefine/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rrefine + url_git: https://github.com/vpnagraj/rrefine +rreg: + version: 0.2.1 + title: Visualization for Norwegian Health Quality Registries + maintainer: Yusman Kamaleri + description: Assists for presentation and visualization of data from the Norwegian + Health Quality Registries following the standardization based on the requirement + specified by the National Service for Health Quality Registries. This requirement + can be accessed from (). + Unfortunately the website is only available in Norwegian. + date_publication: '2018-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rreg + url_git: '' +rrepast: + version: 0.8.0 + title: Invoke 'Repast Simphony' Simulation Models + maintainer: Antonio Prestes Garcia + description: |- + An R and Repast integration tool for running individual-based + (IbM) simulation models developed using 'Repast Simphony' Agent-Based framework + directly from R code supporting multicore execution. This package + integrates 'Repast Simphony' models within R environment, making easier + the tasks of running and analyzing model output data for + automated parameter calibration and for carrying out uncertainty and + sensitivity analysis using the power of R environment. + date_publication: '2020-02-19' + bug_reports: https://github.com/antonio-pgarcia/RRepast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rrepast + url_git: https://github.com/antonio-pgarcia/rrepast +Rrepest: + version: 1.5.4 + title: |- + An Analyzer of International Large Scale Assessments in + Education + maintainer: Rodolfo Ilizaliturri + description: An easy way to analyze international large-scale assessments and surveys + in education or any other dataset that includes replicated weights (Balanced Repeated + Replication (BRR) weights, Jackknife replicate weights,...) while also allowing + for analysis with multiply imputed variables (plausible values). It supports the + estimation of univariate statistics (e.g. mean, variance, standard deviation, + quantiles), frequencies, correlation, linear regression and any other model already + implemented in R that takes a data frame and weights as parameters. It also includes options + to prepare the results for publication, following the table formatting standards + of the Organization for Economic Cooperation and Development (OECD). + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rrepest + url_git: '' +rres: + version: '1.1' + title: Realized Relatedness Estimation and Simulation + maintainer: Bowen Wang + description: Functions for studying realized genetic relatedness between people. + Users will be able to simulate inheritance patterns given pedigree structures, + generate SNP marker data given inheritance patterns, and estimate realized relatedness + between pairs of individuals using SNP marker data. See Wang (2017) . + This work was supported by National Institutes of Health grants R37 GM-046255. + date_publication: '2018-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rres + url_git: '' +RRF: + version: 1.9.4.1 + title: Regularized Random Forest + maintainer: Houtao Deng + description: |- + Feature Selection with Regularized Random Forest. This + package is based on the 'randomForest' package by Andy Liaw. + The key difference is the RRF() function that builds a + regularized random forest. Fortran original by Leo Breiman + and Adele Cutler, R port by Andy Liaw and Matthew Wiener, + Regularized random forest for classification by Houtao Deng, + Regularized random forest for regression by Xin Guan. + Reference: Houtao Deng (2013) . + date_publication: '2024-11-04' + bug_reports: '' + url: https://sites.google.com/site/houtaodeng/rrf + url_cran: https://CRAN.R-project.org/package=RRF + url_git: '' +RRI: + version: '1.1' + title: Residual Randomization Inference for Regression Models + maintainer: Panos Toulis + description: Testing and inference for regression models using residual randomization + methods. The basis of inference is an invariance assumption on the regression + errors, e.g., clustered errors, or doubly-clustered errors. + date_publication: '2019-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRI + url_git: '' +rriskDistributions: + version: 2.1.2 + title: Fitting Distributions to Given Data or Known Quantiles + maintainer: Matthias Greiner + description: |- + Collection of functions for fitting distributions to given data or + by known quantiles. Two main functions fit.perc() and fit.cont() provide + users a GUI that allows to choose a most appropriate distribution without + any knowledge of the R syntax. Note, this package is a part of the 'rrisk' + project. + date_publication: '2017-03-24' + bug_reports: '' + url: http://www.bfr.bund.de/cd/52158 + url_cran: https://CRAN.R-project.org/package=rriskDistributions + url_git: '' +rrMixture: + version: 0.1-2 + title: Reduced-Rank Mixture Models + maintainer: Suyeon Kang + description: We implement full-ranked, rank-penalized, and adaptive nuclear norm + penalized estimation methods using multivariate mixture models proposed by Kang, + Chen, and Yao (2022+). + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rrMixture + url_git: '' +RRMLRfMC: + version: 0.4.0 + title: Reduced-Rank Multinomial Logistic Regression for Markov Chains + maintainer: Pei Wang + description: |- + Fit the reduced-rank multinomial logistic regression model for Markov + chains developed by Wang, Abner, Fardo, Schmitt, Jicha, Eldik and Kryscio + (2021) in R. It combines the ideas of multinomial + logistic regression in Markov chains and reduced-rank. It is very useful in + a study where multi-states model is assumed and each transition among the + states is controlled by a series of covariates. The key advantage is to + reduce the number of parameters to be estimated. The final coefficients for + all the covariates and the p-values for the interested covariates will be + reported. The p-values for the whole coefficient matrix can be calculated by + two bootstrap methods. + date_publication: '2021-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRMLRfMC + url_git: '' +RRNA: + version: '1.2' + title: Secondary Structure Plotting for RNA + maintainer: Jonathan Price + description: Functions for creating and manipulating RNA secondary structure plots. + date_publication: '2024-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRNA + url_git: '' +rrnni: + version: 0.1.1 + title: Manipulate with RNNI Tree Space + maintainer: Jiří C. Moravec + description: 'Calculate RNNI distance between and manipulate with ranked trees. + RNNI stands for Ranked Nearest Neighbour Interchange and is an extension of the + classical NNI space (space of trees created by the NNI moves) to ranked trees, + where internal nodes are ordered according to their heights (usually assumed to + be times). The RNNI distance takes the tree topology into account, as standard + NNI does, but also penalizes changes in the order of internal nodes, i.e. changes + in the order of times of evolutionary events. For more information about the RNNI + space see: Gavryushkin et al. (2018) , Collienne + & Gavryushkin (2021) , Collienne et al. (2021) + , and Collienne (2021) .' + date_publication: '2023-08-25' + bug_reports: https://github.com/biods/rrnni/issues + url: https://rrnni.biods.org/ + url_cran: https://CRAN.R-project.org/package=rrnni + url_git: '' +rroad: + version: 0.0.5 + title: Road Condition Analysis + maintainer: Viliam Simko + description: |- + Computation of the International Roughness Index (IRI) given a + longitudinal road profile. The IRI can be calculated for a single road segment + or for a sequence of segments with a fixed length (e. g. 100m). For the latter, + an overlap of the segments can be selected. The IRI and likewise the algorithms + for its determination are defined in Sayers, Michael W; Gillespie, Thomas D; + Queiroz, Cesar A.V. 1986. The International Road Roughness Experiment (IRRE) : + establishing correlation and a calibration standard for measurements. World + Bank technical paper; no. WTP 45. Washington, DC : The World Bank. (ISBN + 0-8213-0589-1) available from . + date_publication: '2018-02-21' + bug_reports: http://github.com/vsimko/rroad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rroad + url_git: http://github.com/vsimko/rroad +rrpack: + version: 0.1-13 + title: Reduced-Rank Regression + maintainer: Kun Chen + description: |- + Multivariate regression methodologies including + classical reduced-rank regression (RRR) + studied by Anderson (1951) and + Reinsel and Velu (1998) , + reduced-rank regression via adaptive nuclear norm penalization + proposed by Chen et al. (2013) and + Mukherjee et al. (2015) , + robust reduced-rank regression (R4) proposed by + She and Chen (2017) , + generalized/mixed-response reduced-rank regression (mRRR) proposed by + Luo et al. (2018) , + row-sparse reduced-rank regression (SRRR) proposed by + Chen and Huang (2012) , + reduced-rank regression with a sparse singular value decomposition (RSSVD) + proposed by Chen et al. (2012) + and sparse and orthogonal factor regression (SOFAR) proposed by + Uematsu et al. (2019) . + date_publication: '2022-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rrpack + url_git: '' +RRphylo: + version: 2.8.1 + title: Phylogenetic Ridge Regression Methods for Comparative Studies + maintainer: Silvia Castiglione + description: Functions for phylogenetic analysis (Castiglione et al., 2018 ). + The functions perform the estimation of phenotypic evolutionary rates, identification + of phenotypic evolutionary rate shifts, quantification of direction and size of + evolutionary change in multivariate traits, the computation of ontogenetic shape + vectors and test for morphological convergence. + date_publication: '2024-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRphylo + url_git: '' +RRPP: + version: 2.1.2 + title: |- + Linear Model Evaluation with Randomized Residuals in a + Permutation Procedure + maintainer: Michael Collyer + description: |- + Linear model calculations are made for many random versions of data. + Using residual randomization in a permutation procedure, sums of squares are + calculated over many permutations to generate empirical probability distributions + for evaluating model effects. Additionally, coefficients, statistics, fitted values, and residuals generated over many + permutations can be used for various procedures including pairwise tests, prediction, classification, and + model comparison. This package should provide most tools one could need for the analysis of + high-dimensional data, especially in ecology and evolutionary biology, but certainly other fields, as well. + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRPP + url_git: https://github.com/mlcollyer/RRPP +rrr: + version: 1.0.0 + title: Reduced-Rank Regression + maintainer: Chris Addy + description: Reduced-rank regression, diagnostics and graphics. + date_publication: '2016-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rrr + url_git: http://github.com/chrisaddy/rrr +RRreg: + version: 0.7.5 + title: Correlation and Regression Analyses for Randomized Response Data + maintainer: Daniel W. Heck + description: |2- + + Univariate and multivariate methods to analyze randomized response + (RR) survey designs (e.g., Warner, S. L. (1965). Randomized response: A + survey technique for eliminating evasive answer bias. Journal of the + American Statistical Association, 60, 63–69, ). + Besides univariate estimates of true proportions, RR variables can be used + for correlations, as dependent variable in a logistic regression (with or + without random effects), or as predictors in a linear regression + (Heck, D. W., & Moshagen, M. (2018). RRreg: An R package for correlation and + regression analyses of randomized response data. Journal of Statistical + Software, 85(2), 1–29, ). For simulations and + the estimation of statistical power, RR data can be generated according to + several models. The implemented methods also allow to test the link between + continuous covariates and dishonesty in cheating paradigms such as the + coin-toss or dice-roll task (Moshagen, M., & Hilbig, B. E. (2017). + The statistical analysis of cheating paradigms. Behavior Research Methods, + 49, 724–732, ). + date_publication: '2022-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRreg + url_git: https://github.com/danheck/RRreg +RRRR: + version: 1.1.1 + title: Online Robust Reduced-Rank Regression Estimation + maintainer: Yangzhuoran Fin Yang + description: |- + Methods for estimating online robust reduced-rank regression. + The Gaussian maximum likelihood estimation method is described in Johansen, S. (1991) . + The majorisation-minimisation estimation method is partly described in Zhao, Z., & Palomar, D. P. (2017) . + The description of the generic stochastic successive upper-bound minimisation method + and the sample average approximation can be found in Razaviyayn, M., Sanjabi, M., & Luo, Z. Q. (2016) . + date_publication: '2023-02-24' + bug_reports: https://github.com/FinYang/RRRR/issues/ + url: https://pkg.yangzhuoranyang.com/RRRR/ + url_cran: https://CRAN.R-project.org/package=RRRR + url_git: https://github.com/FinYang/RRRR +rrscale: + version: '1.0' + title: Robust Re-Scaling to Better Recover Latent Effects in Data + maintainer: Gregory Hunt + description: 'Non-linear transformations of data to better discover latent effects. + Applies a sequence of three transformations (1) a Gaussianizing transformation, + (2) a Z-score transformation, and (3) an outlier removal transformation. A publication + describing the method has the following citation: Gregory J. Hunt, Mark A. Dane, + James E. Korkola, Laura M. Heiser & Johann A. Gagnon-Bartsch (2020) "Automatic + Transformation and Integration to Improve Visualization and Discovery of Latent + Effects in Imaging Data", Journal of Computational and Graphical Statistics, .' + date_publication: '2020-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rrscale + url_git: '' +rrtable: + version: 0.3.0 + title: Reproducible Research with a Table of R Codes + maintainer: Keon-Woong Moon + description: |- + Makes documents containing plots and tables from a table of R codes. + Can make "HTML", "pdf('LaTex')", "docx('MS Word')" and "pptx('MS Powerpoint')" documents with or without R code. + In the package, modularized 'shiny' app codes are provided. These modules are intended for reuse across applications. + date_publication: '2022-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rrtable + url_git: '' +RRTCS: + version: 0.0.4 + title: Randomized Response Techniques for Complex Surveys + maintainer: Beatriz Cobo Rodríguez + description: |- + Point and interval estimation of linear parameters with data + obtained from complex surveys (including stratified and clustered samples) + when randomization techniques are used. The randomized response technique + was developed to obtain estimates that are more valid when studying + sensitive topics. Estimators and variances for 14 randomized response + methods for qualitative variables and 7 randomized response methods for + quantitative variables are also implemented. In addition, some data sets + from surveys with these randomization methods are included in the package. + date_publication: '2021-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RRTCS + url_git: '' +rrum: + version: 0.2.1 + title: |- + Bayesian Estimation of the Reduced Reparameterized Unified Model + with Gibbs Sampling + maintainer: James Joseph Balamuta + description: |- + Implementation of Gibbs sampling algorithm for Bayesian Estimation + of the Reduced Reparameterized Unified Model ('rrum'), described by + Culpepper and Hudson (2017) . + date_publication: '2023-11-29' + bug_reports: https://github.com/tmsalab/rrum/issues + url: https://tmsalab.github.io/rrum/ + url_cran: https://CRAN.R-project.org/package=rrum + url_git: https://github.com/tmsalab/rrum +RSA: + version: 0.10.6 + title: Response Surface Analysis + maintainer: Felix Schönbrodt + description: |- + Advanced response surface analysis. The main function RSA computes + and compares several nested polynomial regression models (full second- or + third-order polynomial, shifted and rotated squared difference model, + rising ridge surfaces, basic squared difference model, asymmetric or + level-dependent congruence effect models). The package provides plotting + functions for 3d wireframe surfaces, interactive 3d plots, and contour plots. + Calculates many surface parameters (a1 to a5, principal axes, stationary point, + eigenvalues) and provides standard, robust, or bootstrapped standard errors + and confidence intervals for them. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSA + url_git: '' +RSADBE: + version: '1.0' + title: |- + Data related to the book "R Statistical Application Development + by Example" + maintainer: Prabhanjan Tattar + description: |- + The package contains all the data sets related to the book + written by the maintainer of the package. + date_publication: '2013-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSADBE + url_git: '' +rsae: + version: '0.3' + title: Robust Small Area Estimation + maintainer: Tobias Schoch + description: |- + Empirical best linear unbiased prediction (EBLUP) and + robust prediction of the area-level means under the basic unit-level + model. The model can be fitted by maximum likelihood or a (robust) + M-estimator. Mean square prediction error is computed by a parametric + bootstrap. + date_publication: '2024-02-06' + bug_reports: https://github.com/tobiasschoch/rsae/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsae + url_git: https://github.com/tobiasschoch/rsae +rSAFE: + version: 0.1.4 + title: Surrogate-Assisted Feature Extraction + maintainer: Alicja Gosiewska + description: 'Provides a model agnostic tool for white-box model trained on features + extracted from a black-box model. For more information see: Gosiewska et al. (2020) + .' + date_publication: '2022-08-13' + bug_reports: https://github.com/ModelOriented/rSAFE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rSAFE + url_git: https://github.com/ModelOriented/rSAFE +RSAGA: + version: 1.4.2 + title: SAGA Geoprocessing and Terrain Analysis + maintainer: Alexander Brenning + description: |- + Provides access to geocomputing and terrain analysis + functions of the geographical information system (GIS) 'SAGA' (System + for Automated Geoscientific Analyses) from within R by running the + command line version of SAGA. This package furthermore provides + several R functions for handling ASCII grids, including a flexible + framework for applying local functions (including predict methods of + fitted models) and focal functions to multiple grids. SAGA GIS is + available under GPL-2 / LGPL-2 licences from + . + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSAGA + url_git: https://github.com/r-spatial/RSAGA +Rsagacmd: + version: 0.4.3 + title: Linking R with the Open-Source 'SAGA-GIS' Software + maintainer: Steven Pawley + description: |- + Provides an R scripting interface to the open-source 'SAGA-GIS' + (System for Automated Geoscientific Analyses Geographical Information + System) software. 'Rsagacmd' dynamically generates R functions for every + 'SAGA-GIS' geoprocessing tool based on the user's currently installed + 'SAGA-GIS' version. These functions are contained within an S3 object + and are accessed as a named list of libraries and tools. This structure + facilitates an easier scripting experience by organizing the large number + of 'SAGA-GIS' geoprocessing tools (>700) by their respective library. + Interactive scripting can fully take advantage of code autocompletion tools + (e.g. in 'RStudio'), allowing for each tools syntax to be quickly + recognized. Furthermore, the most common types of spatial data (via the + 'terra', 'sp', and 'sf' packages) along with non-spatial data are + automatically passed from R to the 'SAGA-GIS' command line tool for + geoprocessing operations, and the results are loaded as the appropriate R + object. Outputs from individual 'SAGA-GIS' tools can also be chained using + pipes from the 'magrittr' and 'dplyr' packages to combine complex + geoprocessing operations together in a single statement. 'SAGA-GIS' is + available under a GPLv2 / LGPLv2 licence from + including Windows x86/x64 + and macOS binaries. SAGA-GIS is also included in Debian/Ubuntu default software + repositories. Rsagacmd has currently been tested on 'SAGA-GIS' versions + from 2.3.1 to 9.5.1 on Windows, Linux and macOS. + date_publication: '2024-09-08' + bug_reports: https://github.com/stevenpawley/Rsagacmd/issues + url: https://stevenpawley.github.io/Rsagacmd/ + url_cran: https://CRAN.R-project.org/package=Rsagacmd + url_git: '' +rsample: + version: 1.2.1 + title: General Resampling Infrastructure + maintainer: Hannah Frick + description: |- + Classes and functions to create and summarize different types + of resampling objects (e.g. bootstrap, cross-validation). + date_publication: '2024-03-25' + bug_reports: https://github.com/tidymodels/rsample/issues + url: https://rsample.tidymodels.org + url_cran: https://CRAN.R-project.org/package=rsample + url_git: https://github.com/tidymodels/rsample +Rsampling: + version: 0.1.1 + title: Ports the Workflow of "Resampling Stats" Add-in to R + maintainer: Paulo Prado + description: |- + Resampling Stats (http://www.resample.com) is an add-in for + running randomization tests in Excel worksheets. The workflow is (1) to define + a statistic of interest that can be calculated from a data table, (2) to + randomize rows ad/or columns of a data table to simulate a null hypothesis + and (3) and to score the value of the statistic from many randomizations. The + relative frequency distribution of the statistic in the simulations is then + used to infer the probability of the observed value be generated by the null + process (probability of Type I error). This package intends to translate this + logic for R for teaching purposes. Keeping the original workflow is favored over + performance. + date_publication: '2016-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rsampling + url_git: '' +rsat: + version: 0.1.21 + title: Dealing with Multiplatform Satellite Images + maintainer: Unai Pérez - Goya + description: Downloading, customizing, and processing time series of satellite images + for a region of interest. 'rsat' functions allow a unified access to multispectral + images from Landsat, MODIS and Sentinel repositories. 'rsat' also offers capabilities + for customizing satellite images, such as tile mosaicking, image cropping and + new variables computation. Finally, 'rsat' covers the processing, including cloud + masking, compositing and gap-filling/smoothing time series of images (Militino + et al., 2018 and Militino et al., 2019 ). + date_publication: '2024-02-03' + bug_reports: https://github.com/ropensci/rsat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsat + url_git: https://github.com/ropensci/rsat +RSAtools: + version: 0.1.1 + title: Advanced Response Surface Analysis + maintainer: Fernando Núñez-Regueiro + description: Provides tools for response surface analysis, using a comparative framework + that identifies best-fitting solutions across 37 families of polynomials. Many + of these tools are based upon and extend the 'RSA' package, by testing a larger + scope of polynomials (+27 families), more diverse response surface probing techniques + (+acceleration points), more plots (+line of congruence, +line of incongruence, + both with extrema), and other useful functions for exporting results. + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSAtools + url_git: '' +rsatscan: + version: 1.0.8 + title: |- + Tools, Classes, and Methods for Interfacing with 'SaTScan' + Stand-Alone Software + maintainer: Scott Hostovich + description: |- + 'SaTScan'(TM) is software for finding regions in + Time, Space, or Time-Space that have excess risk, based on scan statistics, and + uses Monte Carlo hypothesis testing to generate P-values for these regions. The + 'rsatscan' package provides functions for writing R data frames in + 'SaTScan'-readable formats, for setting 'SaTScan' parameters, for running 'SaTScan' in + the OS, and for reading the files that 'SaTScan' creates. + date_publication: '2024-06-26' + bug_reports: '' + url: https://www.satscan.org + url_cran: https://CRAN.R-project.org/package=rsatscan + url_git: '' +RSauceLabs: + version: 0.1.6 + title: R Wrapper for 'SauceLabs' REST API + maintainer: John Harrison + description: |- + Retrieve, update, delete job information from . Poll the 'SauceLabs' services + current status and access supported platforms. Send and retrieve files from 'SauceLabs' and manage tunnels associated + with 'SauceConnect'. + date_publication: '2016-09-27' + bug_reports: https://github.com/johndharrison/RSauceLabs/issues + url: http://johndharrison.github.io/RSauceLabs/ + url_cran: https://CRAN.R-project.org/package=RSauceLabs + url_git: '' +RSBJson: + version: 1.1.2 + title: |- + Handle R Requests from R Service Bus Applications with JSON + Payloads + maintainer: Tobias Verbeke + description: |- + Package to Handle R Requests from R Service Bus Applications with JSON Payloads in a generic way. + The incoming request is encoded as a string (character vector of length one) containing + the JSON file passed through by the client. + date_publication: '2020-06-16' + bug_reports: '' + url: https://www.rservicebus.io + url_cran: https://CRAN.R-project.org/package=RSBJson + url_git: '' +RSC: + version: 2.0.4 + title: Robust and Sparse Correlation Matrix + maintainer: Luca Coraggio + description: Performs robust and sparse correlation matrix estimation. Robustness + is achieved based on a simple robust pairwise correlation estimator, while sparsity + is obtained based on thresholding. The optimal thresholding is tuned via cross-validation. + See Serra, Coretto, Fratello and Tagliaferri (2018) . + date_publication: '2023-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSC + url_git: '' +rSCA: + version: '3.1' + title: An R Package for Stepwise Cluster Analysis + maintainer: Xiuquan (Xander) Wang + description: A statistical tool for multivariate modeling and clustering using stepwise + cluster analysis. The modeling output of rSCA is constructed as a cluster tree + to represent the complicated relationships between multiple dependent and independent + variables. A free tool (named rSCA Tree Generator) for visualizing the cluster + tree from rSCA is also released and it can be downloaded at . + date_publication: '2020-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rSCA + url_git: '' +RSCAT: + version: 1.1.3 + title: Shadow-Test Approach to Computerized Adaptive Testing + maintainer: Bingnan Jiang + description: |- + As an advanced approach to computerized adaptive testing (CAT), + shadow testing (van der Linden(2005) ) dynamically + assembles entire shadow tests as a part of + selecting items throughout the testing process. + Selecting items from shadow tests guarantees the compliance of all content + constraints defined by the blueprint. 'RSCAT' is an R package for the + shadow-test approach to CAT. The objective of + 'RSCAT' is twofold: 1) Enhancing the effectiveness of shadow-test CAT simulation; + 2) Contributing to the academic and scientific community for CAT research. + RSCAT is currently designed for dichotomous items based on the three-parameter logistic (3PL) model. + date_publication: '2021-10-12' + bug_reports: https://github.com/act-org/RSCAT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSCAT + url_git: '' +rscc: + version: 0.2.1 + title: R Source Code Similarity Evaluation by Variable/Function Names + maintainer: Sigbert Klinke + description: |- + Evaluates R source codes by variable and/or functions names. Similar source codes should deliver similarity coefficients near one. Since neither the frequency nor the order of the used names is considered, a manual inspection of the R source code is required to check for similarity. Possible use cases include detection of code clones for improving + software quality and of plagiarism amongst students' assignments. + date_publication: '2022-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rscc + url_git: https://github.com/sigbertklinke/rscc(developmentversion) +RScelestial: + version: 1.0.4 + title: |- + Scelestial: Steiner Tree Based Single-Cell Lineage Tree + Inference + maintainer: Mohammad Hadi Foroughmand Araabi + description: |2- + + Scelestial infers a lineage tree from single-cell DNA mutation matrix. + It generates a tree with approximately maximum parsimony through + a Steiner tree approximation algorithm. + date_publication: '2023-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RScelestial + url_git: '' +RSclient: + version: 0.7-10 + title: Client for Rserve + maintainer: Simon Urbanek + description: Client for Rserve, allowing to connect to Rserve instances and issue + commands. + date_publication: '2023-11-28' + bug_reports: '' + url: http://www.rforge.net/RSclient/ + url_cran: https://CRAN.R-project.org/package=RSclient + url_git: '' +Rsconctdply: + version: 0.1.3 + title: Deploys Multiple 'Shiny' Apps using Configuration File + maintainer: Sai Chimata + description: Provides a tool for mass deployment of shiny apps to 'RStudio Connect' + or 'Shiny Server'. Multiple user accounts and servers can be configured for deployment. + date_publication: '2018-12-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rsconctdply + url_git: '' +rsconnect: + version: 1.3.4 + title: |- + Deploy Docs, Apps, and APIs to 'Posit Connect', 'shinyapps.io', + and 'RPubs' + maintainer: Aron Atkins + description: |- + Programmatic deployment interface for 'RPubs', + 'shinyapps.io', and 'Posit Connect'. Supported content types include R + Markdown documents, Shiny applications, Plumber APIs, plots, and + static web content. + date_publication: '2025-01-22' + bug_reports: https://github.com/rstudio/rsconnect/issues + url: https://rstudio.github.io/rsconnect/ + url_cran: https://CRAN.R-project.org/package=rsconnect + url_git: https://github.com/rstudio/rsconnect +rscontract: + version: 0.1.2 + title: Generic implementation of the 'RStudio' connections contract + maintainer: Nathan Stephens + description: |- + Provides a generic implementation of the 'RStudio' connection contract to + make it easier for database connections, and other type of connections, opened + via R packages integrate with the connections pane inside the 'RStudio' interactive + development environment (IDE). + date_publication: '2020-12-15' + bug_reports: https://github.com/rstudio/rscontract/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rscontract + url_git: https://github.com/rstudio/rscontract +rscopus: + version: 0.6.6 + title: Scopus Database 'API' Interface + maintainer: John Muschelli + description: |- + Uses Elsevier 'Scopus' API + to download + information about authors and their citations. + date_publication: '2019-09-17' + bug_reports: https://github.com/muschellij2/rscopus/issues + url: https://dev.elsevier.com/sc_apis.html + url_cran: https://CRAN.R-project.org/package=rscopus + url_git: https://github.com/muschellij2/rscopus +rscorecard: + version: 0.30.0 + title: |- + A Method to Download Department of Education College Scorecard + Data + maintainer: Benjamin Skinner + description: |- + A method to download Department of Education College + Scorecard data using the public API + . It is based on + the 'dplyr' model of piped commands to select and filter data in a + single chained function call. An API key from the U.S. Department of + Education is required. + date_publication: '2024-10-23' + bug_reports: https://github.com/btskinner/rscorecard/issues + url: https://www.btskinner.io/rscorecard/ + url_cran: https://CRAN.R-project.org/package=rscorecard + url_git: '' +RSDA: + version: 3.2.1 + title: R to Symbolic Data Analysis + maintainer: Oldemar Rodriguez + description: Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday + in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the + data table for a concept (second order statistical unit). This package implements, + to the symbolic case, certain techniques of automatic classification, as well + as some linear models. + date_publication: '2023-11-10' + bug_reports: '' + url: https://oldemarrodriguez.com/ + url_cran: https://CRAN.R-project.org/package=RSDA + url_git: '' +rsdepth: + version: 0.1-22 + title: |- + Ray Shooting Depth (i.e. RS Depth) Functions for Bivariate + Analysis + maintainer: Mudassir Shabbir + description: Ray Shooting Depth functions are provided for bivariate analysis. This + mainly includes functions for computing the bivariate depth as well as RS median. + Drawing functions for depth bags are also provided. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsdepth + url_git: '' +rSDI: + version: 0.2.1 + title: |- + Spatial Dispersion Index (SDI) Family of Metrics for + Spatial/Geographic Networks + maintainer: Mehmet Gençer + description: 'Spatial Dispersion Index (SDI) is a generalized measurement index, + or rather a family of indices to evaluate spatial dispersion of movements/flows + in a network in a problem neutral way as described in: Gencer (2023) . + This package computes and optionally visualizes this index with minimal hassle.' + date_publication: '2024-05-30' + bug_reports: https://github.com/ehengirmen/rSDI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rSDI + url_git: https://github.com/ehengirmen/rSDI +RSDK: + version: 1.0.1 + title: Sudoku with R + maintainer: EL KHMISSI Mohamed + description: This is a sudoku game package with a shiny application for playing + . + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSDK + url_git: '' +rsdmx: + version: 0.6-5 + title: Tools for Reading SDMX Data and Metadata + maintainer: Emmanuel Blondel + description: |- + Set of classes and methods to read data and metadata documents + exchanged through the Statistical Data and Metadata Exchange (SDMX) framework, + currently focusing on the SDMX XML standard format (SDMX-ML). + date_publication: '2025-02-27' + bug_reports: https://github.com/opensdmx/rsdmx/issues + url: https://sdmx.org + url_cran: https://CRAN.R-project.org/package=rsdmx + url_git: https://github.com/opensdmx/rsdmx +rsdNE: + version: 1.1.0 + title: Response Surface Designs with Neighbour Effects (rsdNE) + maintainer: Ashutosh Dalal + description: |- + Response surface designs with neighbour effects are suitable for experimental situations + where it is expected that the treatment combination administered to one experimental unit + may affect the response on neighboring units as well as the response on the unit to which it is applied. + Integrating these effects in the response surface model improves the experiment's precision + (Jaggi, S., Sarika and Sharma, V.K. (2010); + Verma A., Jaggi S., Varghese, E.,Varghese, C.,Bhowmik, A., Datta, A. and Hemavathi M. (2021)). + This package includes sym(), asym1(), asym2() functions that generates response surface designs which are rotatable under a + polynomial model of a given order without interaction term incorporating neighbour effects. + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsdNE + url_git: '' +RSE: + version: '1.3' + title: Number of Newly Discovered Rare Species Estimation + maintainer: Youhua Chen + description: |- + A Bayesian-weighted estimator and two unweighted estimators are + developed to estimate the number of newly found rare species in additional + ecological samples. Among these methods, the Bayesian-weighted estimator + and an unweighted (Chao-derived) estimator are of high accuracy and + recommended for practical applications. + Technical details of the proposed estimators have been well described + in the following paper: Shen TJ, Chen YH (2018) A Bayesian + weighted approach to predicting the number of newly discovered + rare species. Conservation Biology, In press. + date_publication: '2018-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSE + url_git: '' +rSEA: + version: 2.1.2 + title: Simultaneous Enrichment Analysis + maintainer: Mitra Ebrahimpoor + description: 'SEA performs simultaneous feature-set testing for (gen)omics data. + It tests the unified null hypothesis and controls the family-wise error rate for + all possible pathways. The unified null hypothesis is defined as: "The proportion + of true features in the set is less than or equal to a threshold." Family-wise + error rate control is provided through use of closed testing with Simes test. + There are some practical functions to play around with the pathways of interest.' + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rSEA + url_git: '' +rseedcalc: + version: '1.3' + title: |- + Estimating the Proportion of Genetically Modified Seeds in + Seedlots via Multinomial Group Testing + maintainer: Kevin Wright + description: |- + Estimate the percentage of seeds in a seedlot that contain stacks + of genetically modified traits. Estimates are calculated using a + multinomial group testing model with maximum likelihood estimation of the + parameters. + date_publication: '2015-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rseedcalc + url_git: '' +RSEIS: + version: 4.2-4 + title: Seismic Time Series Analysis Tools + maintainer: Jonathan M. Lees + description: Multiple interactive codes to view and analyze seismic data, via spectrum + analysis, wavelet transforms, particle motion, hodograms. Includes general time-series + tools, plotting, filtering, interactive display. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSEIS + url_git: '' +RSelenium: + version: 1.7.9 + title: R Bindings for 'Selenium WebDriver' + maintainer: Ju Yeong Kim + description: |- + Provides a set of R bindings for the 'Selenium 2.0 WebDriver' + (see + for more information) using the 'JsonWireProtocol' (see + for more + information). 'Selenium 2.0 WebDriver' allows driving a web browser + natively as a user would either locally or on a remote machine using + the Selenium server it marks a leap forward in terms of web browser + automation. Selenium automates web browsers (commonly referred to as + browsers). Using RSelenium you can automate browsers locally or + remotely. + date_publication: '2022-09-02' + bug_reports: https://github.com/ropensci/RSelenium/issues + url: https://docs.ropensci.org/RSelenium/ + url_cran: https://CRAN.R-project.org/package=RSelenium + url_git: '' +rsem: + version: 0.5.1 + title: |- + Robust Structural Equation Modeling with Missing Data and + Auxiliary Variables + maintainer: Zhiyong Zhang + description: A robust procedure is implemented to estimate means and covariance + matrix of multiple variables with missing data using Huber weight and then to + estimate a structural equation model. + date_publication: '2023-08-26' + bug_reports: '' + url: https://bigdatalab.nd.edu + url_cran: https://CRAN.R-project.org/package=rsem + url_git: '' +RSentiment: + version: 2.2.2 + title: Analyse Sentiment of English Sentences + maintainer: Subhasree Bose + description: |- + Analyses sentiment of a sentence in English and assigns score to it. It can classify sentences to the following categories of sentiments:- Positive, Negative, very Positive, very negative, + Neutral. For a vector of sentences, it counts the number of sentences in each + category of sentiment.In calculating the score, negation and various degrees + of adjectives are taken into consideration. It deals only with English sentences. + date_publication: '2018-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSentiment + url_git: '' +Rserve: + version: 1.8-15 + title: Versatile R Server + maintainer: Simon Urbanek + description: |- + Rserve acts as a socket server (TCP/IP or local sockets) + which allows binary requests to be sent to R. Every + connection has a separate workspace and working + directory. Client-side implementations are available + for popular languages such as C/C++ and Java, allowing + any application to use facilities of R without the need of + linking to R code. Rserve supports remote connection, + user authentication and file transfer. A simple R client + is included in this package as well. In addition, it can + also act as a secure WebSockets and HTTP/HTTPS server. + date_publication: '2024-12-17' + bug_reports: https://github.com/s-u/Rserve + url: https://www.rforge.net/Rserve/ + url_cran: https://CRAN.R-project.org/package=Rserve + url_git: '' +rsetse: + version: 0.5.0 + title: Strain Elevation Tension Spring Embedding + maintainer: Jonathan Bourne + description: |- + An R implementation for the Strain Elevation and + Tension embedding algorithm from Bourne (2020) + . The package embeds graphs and + networks using the Strain Elevation and Tension embedding (SETSe) + algorithm. SETSe represents the network as a physical system, where + edges are elastic, and nodes exert a force either up or down based on + node features. SETSe positions the nodes vertically such that the + tension in the edges of a node is equal and opposite to the force it + exerts for all nodes in the network. The resultant structure can then + be analysed by looking at the node elevation and the edge strain and + tension. This algorithm works on weighted and unweighted networks as + well as networks with or without explicit node features. Edge + elasticity can be created from existing edge weights or kept as a + constant. + date_publication: '2021-06-11' + bug_reports: https://github.com/JonnoB/rSETSe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsetse + url_git: https://github.com/JonnoB/rSETSe +rsf: + version: 0.3.0 + title: Report of Statistical Findings in 'bookdown' + maintainer: Derek Chiu + description: |- + A report of statistical findings (RSF) project template is + generated using a 'bookdown' format. 'YAML' fields can be further + customized. Additional helper functions provide extra features to the + RSF. + date_publication: '2022-09-15' + bug_reports: https://github.com/dchiu911/rsf/issues + url: https://dchiu911.github.io/rsf/ + url_cran: https://CRAN.R-project.org/package=rsf + url_git: https://github.com/dchiu911/rsf/ +rSFA: + version: '1.5' + title: Slow Feature Analysis + maintainer: Martin Zaefferer + description: |- + Slow Feature Analysis (SFA), ported to R based on + 'matlab' implementations of SFA: 'SFA toolkit' 1.0 by Pietro Berkes and 'SFA toolkit' + 2.8 by Wolfgang Konen. + date_publication: '2022-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rSFA + url_git: '' +Rsfar: + version: 0.0.1 + title: Seasonal Functional Autoregressive Models + maintainer: Hossein Haghbin + description: 'This is a collection of functions designed for simulating, estimating + and forecasting seasonal functional autoregressive time series of order one. These + methods are addressed in the manuscript: .' + date_publication: '2021-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rsfar + url_git: https://github.com/haghbinh/Rsfar +Rsgf: + version: 1.0.0 + title: SGF (Smart Game File) File Format Import + maintainer: Brad Cable + description: Import SGF (Smart Game File) into R. + date_publication: '2021-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rsgf + url_git: '' +RSGHB: + version: 1.2.2 + title: |- + Functions for Hierarchical Bayesian Estimation: A Flexible + Approach + maintainer: Jeff Dumont + description: 'Functions for estimating models using a Hierarchical Bayesian (HB) + framework. The flexibility comes in allowing the user to specify the likelihood + function directly instead of assuming predetermined model structures. Types of + models that can be estimated with this code include the family of discrete choice + models (Multinomial Logit, Mixed Logit, Nested Logit, Error Components Logit and + Latent Class) as well ordered response models like ordered probit and ordered + logit. In addition, the package allows for flexibility in specifying parameters + as either fixed (non-varying across individuals) or random with continuous distributions. + Parameter distributions supported include normal, positive/negative log-normal, + positive/negative censored normal, and the Johnson SB distribution. Kenneth Train''s + Matlab and Gauss code for doing Hierarchical Bayesian estimation has served as + the basis for a few of the functions included in this package. These Matlab/Gauss + functions have been rewritten to be optimized within R. Considerable code has + been added to increase the flexibility and usability of the code base. Train''s + original Gauss and Matlab code can be found here: + See Train''s chapter on HB in Discrete Choice with Simulation here: ; + and his paper on using HB with non-normal distributions here: . + The authors would also like to thank the invaluable contributions of Stephane + Hess and the Choice Modelling Centre: .' + date_publication: '2019-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSGHB + url_git: https://github.com/RSGInc/RSGHB +rSHAPE: + version: 0.3.2 + title: Simulated Haploid Asexual Population Evolution + maintainer: Jonathan Dench + description: "In silico experimental evolution offers a cost-and-time effective + means to test evolutionary hypotheses. Existing evolutionary simulation tools + focus on simulations in a limited experimental framework, and tend to report on + only the results presumed of interest by the tools designer. The R-package for + Simulated Haploid Asexual Population Evolution ('rSHAPE') addresses these concerns + by implementing a robust simulation framework that outputs complete population + demographic and genomic information for in silico evolving communities. Allowing + more than 60 parameters to be specified, 'rSHAPE'\tsimulates evolution across + discrete time-steps for an evolving community of haploid asexual populations with + binary state genomes. These settings are for the current state of 'rSHAPE' and + future steps will be to increase the breadth of evolutionary conditions permitted. + \ At present, most effort was placed into permitting varied growth models to be + simulated (such as constant size, exponential growth, and logistic growth) as + well as various fitness landscape models to reflect the evolutionary landscape + (e.g.: Additive, House of Cards - Stuart Kauffman and Simon Levin (1987) , + NK - Stuart A. Kauffman and Edward D. Weinberger (1989) , + Rough Mount Fuji - Neidhart, Johannes and Szendro, Ivan G and Krug, Joachim (2014) + ). This package includes numerous functions though + users will only need defineSHAPE(), runSHAPE(), shapeExperiment() and summariseExperiment(). + \ All other functions are called by these main functions and are likely only to + be on interest for someone wishing to develop 'rSHAPE'. Simulation results will + be stored in files which are exported to the directory referenced by the shape_workDir + option (defaults to tempdir() but do change this by passing a folderpath argument + for workDir when calling defineSHAPE() if you plan to make use of your results + beyond your current session). 'rSHAPE' will generate numerous replicate simulations + for your defined range of experimental parameters. The experiment will be built + under the experimental working directory (i.e.: referenced by the option shape_workDir + set using defineSHAPE() ) where individual replicate simulation results will be + stored as well as processed results which I have made in an effort to facilitate + analyses by automating collection and processing of the potentially thousands + of files which will be created. On that note, 'rSHAPE' implements a robust and + flexible framework with highly detailed output at the cost of computational efficiency + and potentially requiring significant disk space (generally gigabytes but up to + tera-bytes for very large simulation efforts). So, while 'rSHAPE' offers a single + framework in which we can simulate evolution and directly compare the impacts + of a wide range of parameters, it is not as quick to run as other in silico simulation + tools which focus on a single scenario with limited output. There you have it, + 'rSHAPE' offers you a less restrictive in silico evolutionary playground than + other tools and I hope you enjoy testing your hypotheses." + date_publication: '2019-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rSHAPE + url_git: '' +rshift: + version: 3.1.1 + title: Paleoecology Functions for Regime Shift Analysis + maintainer: Alex H. Room + description: |- + Contains a variety of functions, based around + regime shift analysis of paleoecological data. + Citations: + Rodionov() from Rodionov (2004) + Lanzante() from Lanzante (1996) + Hellinger_trans from Numerical Ecology, Legendre & Legendre (ISBN 9780444538680) + rolling_autoc from Liu, Gao & Wang (2018) + Sample data sets lake_data & lake_RSI processed from Bush, Silman & Urrego (2004) + Sample data set January_PDO from NOAA: . + date_publication: '2024-09-09' + bug_reports: https://github.com/alexhroom/rshift/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rshift + url_git: https://github.com/alexhroom/rshift +rsi: + version: 0.3.2 + title: Efficiently Retrieve and Process Satellite Imagery + maintainer: Michael Mahoney + description: |- + Downloads spatial data from spatiotemporal asset catalogs + ('STAC'), computes standard spectral indices from the Awesome Spectral + Indices project (Montero et al. (2023) ) + against raster data, and glues the outputs together into predictor bricks. + Methods focus on interoperability with the broader spatial ecosystem; + function arguments and outputs use classes from 'sf' and 'terra', and data + downloading functions support complex 'CQL2' queries using 'rstac'. + date_publication: '2025-01-22' + bug_reports: https://github.com/Permian-Global-Research/rsi/issues + url: https://permian-global-research.github.io/rsi/ + url_cran: https://CRAN.R-project.org/package=rsi + url_git: https://github.com/Permian-Global-Research/rsi +rsides: + version: '0.1' + title: SIDES-Based Subgroup Search Algorithms + maintainer: Alex Dmitrienko + description: R implementation of SIDES-based subgroup search algorithms (Lipkovich + et al. (2017) ). + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsides + url_git: '' +RSiena: + version: 1.4.7 + title: Siena - Simulation Investigation for Empirical Network Analysis + maintainer: Tom A.B. Snijders + description: |- + The main purpose of this package is to perform simulation-based + estimation of stochastic actor-oriented models for longitudinal network + data collected as panel data. Dependent variables can be single or + multivariate networks, which can be directed, non-directed, or two-mode; + and associated actor variables. + There are also functions for testing parameters and checking goodness of fit. + An overview of these models is given in Snijders (2017), + . + date_publication: '2024-02-21' + bug_reports: https://github.com/stocnet/rsiena/issues + url: https://www.stats.ox.ac.uk/~snijders/siena/ + url_cran: https://CRAN.R-project.org/package=RSiena + url_git: '' +RsimMosaic: + version: 1.0.3 + title: R Simple Image Mosaic Creation Library + maintainer: Alberto Krone-Martins + description: Provides a way to transform an image into a mosaic composed from a + set of smaller images (tiles). It also contains a simple function for creating + the tiles from a folder of images directly through R, without the need of any + external code. At this moment only the JPEG format is supported, either as input + (image and tiles) or output (mosaic transformed image). + date_publication: '2017-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RsimMosaic + url_git: '' +rsimsum: + version: 0.13.0 + title: Analysis of Simulation Studies Including Monte Carlo Error + maintainer: Alessandro Gasparini + description: |- + Summarise results from simulation studies and compute Monte Carlo + standard errors of commonly used summary statistics. This package is modelled + on the 'simsum' user-written command in 'Stata' (White I.R., 2010 + ), further extending + it with additional performance measures and functionality. + date_publication: '2024-03-03' + bug_reports: https://github.com/ellessenne/rsimsum/issues + url: https://ellessenne.github.io/rsimsum/ + url_cran: https://CRAN.R-project.org/package=rsimsum + url_git: https://github.com/ellessenne/rsimsum +rsinaica: + version: 1.1.0 + title: Download Data from Mexico's Air Quality Information System + maintainer: Diego Valle-Jones + description: |- + Easy-to-use functions for downloading air quality data from + the Mexican National Air Quality Information System (SINAICA). Allows + you to query pollution and meteorological parameters from more than a + hundred monitoring stations located throughout Mexico. See + for more information. + date_publication: '2024-06-21' + bug_reports: https://github.com/diegovalle/rsinaica/issues + url: https://hoyodesmog.diegovalle.net/rsinaica/ + url_cran: https://CRAN.R-project.org/package=rsinaica + url_git: https://github.com/diegovalle/rsinaica +RSizeBiased: + version: 0.1.0 + title: Hypothesis Testing Based on R-Size Biased Samples + maintainer: Dimitrios Bagkavos + description: Provides functions and examples for testing hypothesis about the population + mean and variance on samples drawn by r-size biased sampling schemes. + date_publication: '2021-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSizeBiased + url_git: '' +RSKC: + version: 2.4.2 + title: Robust Sparse K-Means + maintainer: Yumi Kondo + description: This RSKC package contains a function RSKC which runs the robust sparse + K-means clustering algorithm. + date_publication: '2016-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSKC + url_git: '' +rskey: + version: 0.4.4 + title: Create Custom 'Rstudio' Keyboard Shortcuts + maintainer: Berry Boessenkool + description: |- + Create custom keyboard shortcuts to examine code selected in the 'Rstudio' editor. + F3 can for example yield 'str(selection)' and F7 open the source + code of CRAN and base package functions on 'github'. + date_publication: '2020-06-05' + bug_reports: https://github.com/brry/rskey/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rskey + url_git: '' +rslp: + version: 0.2.0 + title: A Stemming Algorithm for the Portuguese Language + maintainer: Daniel Falbel + description: Implements the "Stemming Algorithm for the Portuguese Language" . + date_publication: '2020-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rslp + url_git: https://github.com/dfalbel/rslp +rslurm: + version: 0.6.2 + title: Submit R Calculations to a 'Slurm' Cluster + maintainer: Erick Verleye + description: |- + Functions that simplify submitting R scripts to a 'Slurm' + workload manager, in part by automating the division of embarrassingly + parallel calculations across cluster nodes. + date_publication: '2023-02-24' + bug_reports: https://github.com/earthlab/rslurm/issues + url: https://www.earthdatascience.org/rslurm/ + url_cran: https://CRAN.R-project.org/package=rslurm + url_git: '' +rsm: + version: 2.10.5 + title: Response-Surface Analysis + maintainer: Russell Lenth + description: |- + Provides functions to generate response-surface designs, + fit first- and second-order response-surface models, + make surface plots, obtain the path of steepest ascent, + and do canonical analysis. A good reference on these methods + is Chapter 10 of Wu, C-F J and Hamada, M (2009) + "Experiments: Planning, Analysis, and Parameter Design Optimization" + ISBN 978-0-471-69946-0. An early version of the package is + documented in Journal of Statistical Software . + date_publication: '2024-06-09' + bug_reports: https://github.com/rvlenth/rsm/issues + url: https://rvlenth.github.io/rsm/ + url_cran: https://CRAN.R-project.org/package=rsm + url_git: https://github.com/rvlenth/rsm +RSmallTelescopes: + version: 1.0.4 + title: Empirical Small Telescopes Analysis + maintainer: John Ruscio + description: |- + We provide functions to perform an empirical small telescopes + analysis. This package contains 2 functions, SmallTelescopes() and + EstimatePower(). Users only need to call SmallTelescopes() to conduct + the analysis. For more information on small telescopes analysis see + Uri Simonsohn (2015) . + date_publication: '2021-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSmallTelescopes + url_git: '' +RSmartlyIO: + version: 0.1.3 + title: |- + Loading Facebook and Instagram Advertising Data from + 'Smartly.io' + maintainer: Johannes Burkhardt + description: |- + Aims at loading Facebook and Instagram advertising data from + 'Smartly.io' into R. 'Smartly.io' is an online advertising service that enables + advertisers to display commercial ads on social media networks (see for more information). + The package offers an interface to query the 'Smartly.io' API and loads data directly into R for further data processing and data analysis. + date_publication: '2019-01-21' + bug_reports: https://github.com/rstats-lab/RSmartlyIO/issues + url: https://app.smartly.io + url_cran: https://CRAN.R-project.org/package=RSmartlyIO + url_git: https://github.com/rstats-lab/RSmartlyIO +rsmatch: + version: 0.2.1 + title: Matching Methods for Time-Varying Observational Studies + maintainer: Sean Kent + description: |- + Implements popular methods for matching in time-varying + observational studies. Matching is difficult in this scenario because + participants can be treated at different times which may have an + influence on the outcomes. The core methods include: "Balanced Risk + Set Matching" from Li, Propert, and Rosenbaum (2011) + and "Propensity Score Matching with + Time-Dependent Covariates" from Lu (2005) + . Some functions use the + 'Gurobi' optimization back-end to improve the optimization problem + speed; the 'gurobi' R package and associated software can be + downloaded from after obtaining a license. + date_publication: '2024-02-20' + bug_reports: https://github.com/skent259/rsmatch/issues + url: https://skent259.github.io/rsmatch/ + url_cran: https://CRAN.R-project.org/package=rsmatch + url_git: https://github.com/skent259/rsmatch +rsmatrix: + version: 0.2.9 + title: Matrices for Repeat-Sales Price Indexes + maintainer: Steve Martin + description: |- + Calculate the matrices in + Shiller (1991, ) that serve as the + foundation for many repeat-sales price indexes. + date_publication: '2024-12-14' + bug_reports: https://github.com/marberts/rsmatrix/issues + url: https://marberts.github.io/rsmatrix/ + url_cran: https://CRAN.R-project.org/package=rsmatrix + url_git: https://github.com/marberts/rsmatrix +Rsmlx: + version: 2024.1.0 + title: R Speaks 'Monolix' + maintainer: Chloe Bracis + description: |- + Provides methods for model building and model evaluation of mixed effects models using + 'Monolix' . 'Monolix' is a software tool for nonlinear mixed effects + modeling that must have been installed in order to use 'Rsmlx'. + Among other tasks, 'Rsmlx' provides a powerful tool for automatic PK model building, performs + statistical tests for model assessment, bootstrap simulation and likelihood profiling for + computing confidence intervals. 'Rsmlx' also proposes several automatic covariate search methods for + mixed effects models. + date_publication: '2024-06-10' + bug_reports: '' + url: https://monolix.lixoft.com/rsmlx/ + url_cran: https://CRAN.R-project.org/package=Rsmlx + url_git: '' +rsnell: + version: '0.1' + title: Snell Scoring + maintainer: Paul F. Petrowski + description: The Snell scoring procedure, implemented in R. This procedure was first + described by E.J Snell (1964) and was later used by Tong + et al (1977) in dairy. + date_publication: '2023-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsnell + url_git: https://github.com/pfpetrowski/rsnell +RSNNS: + version: 0.4-17 + title: |- + Neural Networks using the Stuttgart Neural Network Simulator + (SNNS) + maintainer: Christoph Bergmeir + description: |- + The Stuttgart Neural Network Simulator (SNNS) is a library + containing many standard implementations of neural networks. This + package wraps the SNNS functionality to make it available from + within R. Using the 'RSNNS' low-level interface, all of the + algorithmic functionality and flexibility of SNNS can be accessed. + Furthermore, the package contains a convenient high-level + interface, so that the most common neural network topologies and + learning algorithms integrate seamlessly into R. + date_publication: '2023-11-30' + bug_reports: https://github.com/cbergmeir/RSNNS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSNNS + url_git: https://github.com/cbergmeir/RSNNS +rsocialwatcher: + version: 0.1.1 + title: '''Facebook Marketing API'' Social Watcher' + maintainer: Robert Marty + description: Facilitates querying data from the ‘Facebook Marketing API', particularly + for social science research . + Data from the 'Facebook Marketing API' has been used for a variety of social science + applications, such as for poverty estimation (Marty and Duhaut (2024) ), + disease surveillance (Araujo et al. (2017) ), and + measuring migration (Alexander, Polimis, and Zagheni (2020) ). + The package facilitates querying the number of Facebook daily/monthly active users + for multiple location types (e.g., from around a specific coordinate to an administrative + region) and for a number of attribute types (e.g., interests, behaviors, education + level, etc). The package supports making complex queries within one API call and + making multiple API calls across different locations and/or parameters. + date_publication: '2024-05-06' + bug_reports: https://github.com/worldbank/rsocialwatcher/issues + url: https://worldbank.github.io/rsocialwatcher/ + url_cran: https://CRAN.R-project.org/package=rsocialwatcher + url_git: '' +RSocrata: + version: 1.7.15-1 + title: Download or Upload 'Socrata' Data Sets + maintainer: '"Gene Leynes"' + description: |- + Provides easier interaction with + 'Socrata' open data portals . + Users can provide a 'Socrata' data set resource URL, + or a 'Socrata' Open Data API (SODA) web query, + or a 'Socrata' "human-friendly" URL, + returns an R data frame. Converts dates to 'POSIX' + format and manages throttling by 'Socrata'. + Users can upload data to 'Socrata' portals directly + from R. + date_publication: '2023-08-31' + bug_reports: https://github.com/Chicago/RSocrata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSocrata + url_git: https://github.com/Chicago/RSocrata +rsofun: + version: 5.0.0 + title: The P-Model and BiomeE Modelling Framework + maintainer: Benjamin Stocker + description: |- + Implements the Simulating Optimal FUNctioning framework for + site-scale simulations of ecosystem processes, including model + calibration. It contains 'Fortran 90' modules for the P-model (Stocker + et al. (2020) ), SPLASH + (Davis et al. (2017) ) + and BiomeE (Weng et al. (2015) + ). + date_publication: '2024-11-28' + bug_reports: https://github.com/geco-bern/rsofun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsofun + url_git: https://github.com/geco-bern/rsofun +rsoi: + version: 0.5.6 + title: Import Various Northern and Southern Hemisphere Climate Indices + maintainer: Sam Albers + description: |- + Downloads Southern Oscillation Index, Oceanic Nino + Index, North Pacific Gyre Oscillation data, North Atlantic Oscillation + and Arctic Oscillation. Data sources are described in the help files for each function. + date_publication: '2023-11-16' + bug_reports: '' + url: https://boshek.github.io/rsoi/ + url_cran: https://CRAN.R-project.org/package=rsoi + url_git: https://github.com/boshek/rsoi/ +Rsolnp: + version: '1.16' + title: General Non-Linear Optimization + maintainer: Alexios Ghalanos + description: General Non-linear Optimization Using Augmented Lagrange Multiplier + Method. + date_publication: '2015-12-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rsolnp + url_git: '' +rsolr: + version: 0.0.13 + title: R to Solr Interface + maintainer: Michael Lawrence + description: |- + A comprehensive R API for querying Apache Solr databases. + A Solr core is represented as a data frame or list that + supports Solr-side filtering, sorting, + transformation and aggregation, all through the familiar + base R API. Queries are processed + lazily, i.e., a query is only sent to the database when + the data are required. + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsolr + url_git: '' +Rsomoclu: + version: 1.7.6 + title: Somoclu + maintainer: Shichao Gao + description: Somoclu is a massively parallel implementation of self-organizing maps. It + exploits multicore CPUs and it can be accelerated by CUDA. The topology of the + map can be planar or toroid and the grid of neurons can be rectangular or hexagonal + . Details refer to (Peter Wittek, et al (2017)) . + date_publication: '2022-09-26' + bug_reports: https://github.com/peterwittek/somoclu/issues + url: https://peterwittek.github.io/somoclu/ + url_cran: https://CRAN.R-project.org/package=Rsomoclu + url_git: '' +RSP: + version: '0.4' + title: '''shiny'' Applications for Statistical and Psychometric Analysis' + maintainer: Eren Can Aybek + description: |- + Toolbox with 'shiny' applications for widely used psychometric + methods. Those methods include following analysis: Item analysis, item response theory calibration, principal component analysis, + confirmatory factor analysis - structural equation modeling, generating simulated data. + References: + Chalmers (2012, ); + Revelle (2022, ); + Rosseel (2012, ); + Magis & Raiche (2012, ); + Magis & Barrada (2017, ). + date_publication: '2023-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSP + url_git: '' +rspa: + version: 0.2.8 + title: Adapt Numerical Records to Fit (in)Equality Restrictions + maintainer: Mark van der Loo + description: |- + Minimally adjust the values of numerical records in a data.frame, such + that each record satisfies a predefined set of equality and/or inequality + constraints. The constraints can be defined using the 'validate' package. + The core algorithms have recently been moved to the 'lintools' package, + refer to 'lintools' for a more basic interface and access to a version + of the algorithm that works with sparse matrices. + date_publication: '2022-12-22' + bug_reports: https://github.com/markvanderloo/rspa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rspa + url_git: https://github.com/markvanderloo/rspa +rSPARCS: + version: 0.1.1 + title: Sites, Population, and Records Cleaning Skills + maintainer: Wangjian Zhang + description: Data cleaning including 1) generating datasets for time-series and + case-crossover analyses based on raw hospital records, 2) linking individuals + to an areal map, 3) picking out cases living within a buffer of certain size surrounding + a site, etc. For more information, please refer to Zhang W,etc. (2018) . + date_publication: '2023-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rSPARCS + url_git: '' +rsparkling: + version: 0.2.19 + title: R Interface for H2O Sparkling Water + maintainer: Jakub Hava + description: |- + An extension package for 'sparklyr' that provides an R interface to + H2O Sparkling Water machine learning library (see for more information). + date_publication: '2020-01-28' + bug_reports: http://jira.h2o.ai + url: '' + url_cran: https://CRAN.R-project.org/package=rsparkling + url_git: https://github.com/h2oai/sparkling-water/tree/master/r +rsparse: + version: 0.5.3 + title: Statistical Learning on Sparse Matrices + maintainer: Dmitriy Selivanov + description: |- + Implements many algorithms for statistical learning on + sparse matrices - matrix factorizations, matrix completion, + elastic net regressions, factorization machines. + Also 'rsparse' enhances 'Matrix' package by providing methods for + multithreaded matrix products and native slicing of + the sparse matrices in Compressed Sparse Row (CSR) format. + List of the algorithms for regression problems: + 1) Elastic Net regression via Follow The Proximally-Regularized Leader (FTRL) + Stochastic Gradient Descent (SGD), as per McMahan et al(, ) + 2) Factorization Machines via SGD, as per Rendle (2010, ) + List of algorithms for matrix factorization and matrix completion: + 1) Weighted Regularized Matrix Factorization (WRMF) via Alternating Least + Squares (ALS) - paper by Hu, Koren, Volinsky (2008, ) + 2) Maximum-Margin Matrix Factorization via ALS, paper by Rennie, Srebro + (2005, ) + 3) Fast Truncated Singular Value Decomposition (SVD), Soft-Thresholded SVD, + Soft-Impute matrix completion via ALS - paper by Hastie, Mazumder + et al. (2014, ) + 4) Linear-Flow matrix factorization, from 'Practical linear models for + large-scale one-class collaborative filtering' by Sedhain, Bui, Kawale et al + (2016, ISBN:978-1-57735-770-4) + 5) GlobalVectors (GloVe) matrix factorization via SGD, paper by Pennington, + Socher, Manning (2014, ) + Package is reasonably fast and memory efficient - it allows to work with large + datasets - millions of rows and millions of columns. This is particularly useful + for practitioners working on recommender systems. + date_publication: '2025-02-17' + bug_reports: https://github.com/dselivanov/rsparse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsparse + url_git: https://github.com/dselivanov/rsparse +Rspc: + version: 1.2.2 + title: Nelson Rules for Control Charts + maintainer: Stanislav Matousek (MSD) + description: 'Implementation of Nelson rules for control charts in ''R''. The ''Rspc'' + implements some Statistical Process Control methods, namely Levey-Jennings type + of I (individuals) chart, Shewhart C (count) chart and Nelson rules (as described + in Montgomery, D. C. (2013) Introduction to statistical quality control. Hoboken, + NJ: Wiley.). Typical workflow is taking the time series, specify the control limits, + and list of Nelson rules you want to evaluate. There are several options how to + modify the rules (one sided limits, numerical parameters of rules, etc.). Package + is also capable of calculating the control limits from the data (so far only for + i-chart and c-chart are implemented).' + date_publication: '2018-07-30' + bug_reports: https://github.com/Merck/SPC_Package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rspc + url_git: '' +rSPDE: + version: 2.4.0 + title: |- + Rational Approximations of Fractional Stochastic Partial + Differential Equations + maintainer: David Bolin + description: Functions that compute rational approximations of fractional elliptic + stochastic partial differential equations. The package also contains functions + for common statistical usage of these approximations. The main references for + rSPDE are Bolin, Simas and Xiong (2023) for + the covariance-based method and Bolin and Kirchner (2020) + for the operator-based rational approximation. These can be generated by the citation + function in R. + date_publication: '2024-12-02' + bug_reports: https://github.com/davidbolin/rSPDE/issues + url: https://davidbolin.github.io/rSPDE/ + url_cran: https://CRAN.R-project.org/package=rSPDE + url_git: '' +RSpectra: + version: 0.16-2 + title: Solvers for Large-Scale Eigenvalue and SVD Problems + maintainer: Yixuan Qiu + description: |- + R interface to the 'Spectra' library + for large-scale eigenvalue and SVD + problems. It is typically used to compute a few + eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, + which is usually more efficient than eigen() if k << n. This package + provides the 'eigs()' function that does the similar job as in 'Matlab', + 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function + to calculate the largest k singular values and corresponding + singular vectors of a real matrix. The matrix to be computed on can be + dense, sparse, or in the form of an operator defined by the user. + date_publication: '2024-07-18' + bug_reports: https://github.com/yixuan/RSpectra/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSpectra + url_git: https://github.com/yixuan/RSpectra +rSpectral: + version: 1.0.0.10 + title: Spectral Modularity Clustering + maintainer: Anatoly Sorokin + description: |- + Implements the network clustering algorithm described in + Newman (2006) . The complete + iterative algorithm comprises of two steps. In the first step, the + network is expressed in terms of its leading eigenvalue and + eigenvector and recursively partition into two communities. + Partitioning occurs if the maximum positive + eigenvalue is greater than the tolerance (10e-5) for the current + partition, and if it results in a positive contribution to the + Modularity. + Given an initial separation using the leading eigen step, 'rSpectral' + then continues to maximise for the change in Modularity using a + fine-tuning step - or variate thereof. The first stage here is to + find the node which, when moved from one community to another, + gives the maximum change in Modularity. This node’s community is + then fixed and we repeat the process until all nodes have been moved. + The whole process is repeated from this new state until the change + in the Modularity, between the new and old state, is less than the + predefined tolerance. + A slight variant of the fine-tuning step, which can improve speed + of the calculation, is also provided. Instead of moving each node + into each community in turn, we only consider moves of neighbouring + nodes, found in different communities, to the community of the + current node of interest. The two steps process is repeatedly + applied to each new community found, subdivided each community + into two new communities, until we are unable to find any division + that results in a positive change in Modularity. + date_publication: '2023-01-18' + bug_reports: https://github.com/cmclean5/rSpectral/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=rSpectral + url_git: https://github.com/cmclean5/rSpectral +RSpincalc: + version: 1.0.2 + title: |- + Conversion Between Attitude Representations of DCM, Euler + Angles, Quaternions, and Euler Vectors + maintainer: Jose Gama + description: |- + Conversion between attitude representations: DCM, Euler angles, Quaternions, and Euler vectors. + Plus conversion between 2 Euler angle set types (xyx, yzy, zxz, xzx, yxy, zyz, xyz, yzx, zxy, xzy, yxz, zyx). + Fully vectorized code, with warnings/errors for Euler angles (singularity, out of range, invalid angle order), + DCM (orthogonality, not proper, exceeded tolerance to unity determinant) and Euler vectors(not unity). + Also quaternion and other useful functions. + Based on SpinCalc by John Fuller and SpinConv by Paolo de Leva. + date_publication: '2015-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSpincalc + url_git: '' +rspiro: + version: '0.5' + title: Implementation of Spirometry Equations + maintainer: Theodore Lytras + description: |- + Implementation of various spirometry equations + in R, currently the GLI-2012 (Global Lung Initiative; + Quanjer et al. 2012 ), + the race-neutral GLI global 2022 (Global Lung Initiative; + Bowerman et al. 2023 ), the + NHANES3 (National Health and Nutrition Examination Survey; + Hankinson et al. 1999 ) + and the JRS 2014 (Japanese Respiratory Society; Kubota + et al. 2014 ) equations. + Also the GLI-2017 diffusing capacity equations + are implemented. + Contains user-friendly functions to calculate predicted + and LLN (Lower Limit of Normal) values for different + spirometric parameters such as FEV1 (Forced Expiratory + Volume in 1 second), FVC (Forced Vital Capacity), etc, + and to convert absolute spirometry measurements + to percent (%) predicted and z-scores. + date_publication: '2024-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rspiro + url_git: '' +rspm: + version: 0.6.1 + title: '''RStudio'' Package Manager' + maintainer: Iñaki Ucar + description: |- + Enables binary package installations on Linux distributions. + Provides access to 'RStudio' public repositories at + , and transparent management of + system requirements without administrative privileges. Currently supported + distributions are 'CentOS' / 'RHEL' 7-9, and several 'RHEL' derivatives + ('Rocky Linux', 'AlmaLinux', 'Oracle Linux', and 'Amazon Linux'), + 'openSUSE' / 'SLES' 15.4-5, 'Debian' 11-12, and 'Ubuntu' LTS 20-22. + date_publication: '2024-10-29' + bug_reports: https://github.com/cran4linux/rspm/issues + url: https://cran4linux.github.io/rspm/ + url_cran: https://CRAN.R-project.org/package=rspm + url_git: '' +Rspotify: + version: 0.1.2 + title: Access to Spotify API + maintainer: Tiago Mendes Dantas + description: Provides an interface to the Spotify API . + date_publication: '2018-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rspotify + url_git: '' +rsppfp: + version: 1.0.4 + title: R's Shortest Path Problem with Forbidden Subpaths + maintainer: Melina Vidoni + description: |- + An implementation of functionalities to transform directed graphs that are bound to a set of + known forbidden paths. There are several transformations, following the rules provided by Villeneuve + and Desaulniers (2005) , and Hsu et al. (2009) . + The resulting graph is generated in a data-frame format. See rsppfp website for more information, + documentation an examples. + date_publication: '2019-02-19' + bug_reports: https://github.com/melvidoni/rsppfp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsppfp + url_git: https://github.com/melvidoni/rsppfp +rsprite2: + version: 0.2.1 + title: |- + Identify Distributions that Match Reported Sample Parameters + (SPRITE) + maintainer: Lukas Wallrich + description: |- + The SPRITE algorithm creates possible distributions of discrete responses + based on reported sample parameters, such as mean, standard deviation and range + (Heathers et al., 2018, ). This package implements it, + drawing heavily on the code for Nick Brown's 'rSPRITE' Shiny app . + In addition, it supports the modeling of distributions based on multi-item (Likert-type) + scales and the use of restrictions on the frequency of particular responses. + date_publication: '2023-07-06' + bug_reports: https://github.com/LukasWallrich/rsprite2/issues + url: https://lukaswallrich.github.io/rsprite2/ + url_cran: https://CRAN.R-project.org/package=rsprite2 + url_git: '' +rsq: + version: '2.7' + title: R-Squared and Related Measures + maintainer: Dabao Zhang + description: Calculate generalized R-squared, partial R-squared, and partial correlation + coefficients for generalized linear (mixed) models (including quasi models with + well defined variance functions). + date_publication: '2024-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsq + url_git: '' +RSQL: + version: 0.2.2 + title: |- + Database Agnostic Package to Generate and Process 'SQL' Queries + in R + maintainer: Alejandro Baranek + description: Allows the user to generate and execute select, insert, update and + delete 'SQL' queries the underlying database without having to explicitly write + 'SQL' code. + date_publication: '2023-08-19' + bug_reports: https://github.com/rOpenStats/RSQL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSQL + url_git: https://github.com/rOpenStats/RSQL +RSQLite: + version: 2.3.9 + title: SQLite Interface for R + maintainer: Kirill Müller + description: |- + Embeds the SQLite database engine in R and provides an + interface compliant with the DBI package. The source for the SQLite + engine and for various extensions in a recent version is included. + System libraries will never be consulted because this package relies + on static linking for the plugins it includes; this also ensures a + consistent experience across all installations. + date_publication: '2024-12-03' + bug_reports: https://github.com/r-dbi/RSQLite/issues + url: https://rsqlite.r-dbi.org + url_cran: https://CRAN.R-project.org/package=RSQLite + url_git: https://github.com/r-dbi/RSQLite +RSqlParser: + version: '1.5' + title: Parse 'SQL' Statements + maintainer: Subhasree Bose + description: Parser for 'SQL' statements. Currently, it supports parsing of only + 'SELECT' statements. + date_publication: '2020-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSqlParser + url_git: '' +RsqMed: + version: '1.1' + title: |- + Total Mediation Effect Size Measure for High-Dimensional + Mediators + maintainer: Tianzhong Yang + description: An implementation of calculating the R-squared measure as a total mediation + effect size measure and its confidence interval for moderate- or high-dimensional + mediator models. It gives an option to filter out non-mediators using variable + selection methods. The original R package is directly related to the paper Yang + et al (2021) "Estimation of mediation effect for high-dimensional omics mediators + with application to the Framingham Heart Study" . The new + version contains a choice of using cross-fitting, which is computationally faster. + The details of the cross-fitting method are available in the paper Xu et al (2023) + "Speeding up interval estimation for R2-based mediation effect of high-dimensional + mediators via cross-fitting" . + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RsqMed + url_git: '' +RSquaredMI: + version: 0.2.0 + title: R-Squared with Multiply Imputed Data + maintainer: Julian D. Karch + description: Provides R-squared values and standardized regression coefficients + for linear models applied to multiply imputed datasets as obtained by 'mice'. + Confidence intervals, zero-order correlations, and alternative adjusted R-squared + estimates are also available. The methods are described in Van Ginkel and Karch + (2024) and in Van Ginkel (2020) . + date_publication: '2024-12-05' + bug_reports: https://github.com/karchjd/RsquaredMI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSquaredMI + url_git: https://github.com/karchjd/RsquaredMI +rSRD: + version: 0.1.8 + title: Sum of Ranking Differences Statistical Test + maintainer: Jochen Staudacher + description: |- + We provide an implementation for Sum of Ranking Differences (SRD), + a novel statistical test introduced by Héberger (2010) + . The test allows the comparison of + different solutions through a reference by first performing a rank + transformation on the input, then calculating and comparing the distances + between the solutions and the reference - the latter is measured in the + L1 norm. The reference can be an external benchmark (e.g. an established + gold standard) or can be aggregated from the data. The calculated distances, + called SRD scores, are validated in two ways, see Héberger and Kollár-Hunek + (2011) . A randomization test (also called permutation + test) compares the SRD scores of the solutions to the SRD scores of randomly + generated rankings. The second validation option is cross-validation that + checks whether the rankings generated from the solutions come from the same + distribution or not. For a detailed analysis about the cross-validation + process see Sziklai, Baranyi and Héberger (2021) + . The package offers a wide array of + features related to SRD including the computation of the SRD scores, + validation options, input preprocessing and plotting tools. + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rSRD + url_git: '' +Rssa: + version: '1.1' + title: A Collection of Methods for Singular Spectrum Analysis + maintainer: Anton Korobeynikov + description: |- + Methods and tools for Singular Spectrum Analysis including decomposition, + forecasting and gap-filling for univariate and multivariate time series. + General description of the methods with many examples can be found in the book + Golyandina (2018, ). + See 'citation("Rssa")' for details. + date_publication: '2024-09-05' + bug_reports: https://github.com/asl/rssa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rssa + url_git: https://github.com/asl/rssa +RSSampling: + version: '1.0' + title: Ranked Set Sampling + maintainer: Busra Sevinc + description: Ranked set sampling (RSS) is introduced as an advanced method for data + collection which is substantial for the statistical and methodological analysis + in scientific studies by McIntyre (1952) (reprinted in 2005) . + This package introduces the first package that implements the RSS and its modified + versions for sampling. With 'RSSampling', the researchers can sample with basic + RSS and the modified versions, namely, Median RSS, Extreme RSS, Percentile RSS, + Balanced groups RSS, Double RSS, L-RSS, Truncation-based RSS, Robust extreme RSS. + The 'RSSampling' also allows imperfect ranking using an auxiliary variable (concomitant) + which is widely used in the real life applications. Applicants can also use this + package for parametric and nonparametric inference such as mean, median and variance + estimation, regression analysis and some distribution-free tests where the the + samples are obtained via basic RSS. + date_publication: '2018-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSSampling + url_git: '' +RsSimulx: + version: '2024.1' + title: Extension of 'lixoftConnectors' for 'Simulx' + maintainer: Chloe Bracis + description: Provides useful tools which supplement the use of 'Simulx' software + and 'R' connectors ('Monolix Suite'). 'Simulx' is an easy, efficient and flexible + application for clinical trial simulations. You need 'Simulx' software to be installed + in order to use 'RsSimulx' package. Among others tasks, 'RsSimulx' provides the + same functions as package 'mlxR' does with a compatibility with 'Simulx' software. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RsSimulx + url_git: '' +RSSL: + version: 0.9.7 + title: |- + Implementations of Semi-Supervised Learning Approaches for + Classification + maintainer: Jesse Krijthe + description: |- + A collection of implementations of semi-supervised classifiers + and methods to evaluate their performance. The package includes implementations + of, among others, Implicitly Constrained Learning, Moment Constrained Learning, + the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic + Likelihood estimation, S4VM and WellSVM. + date_publication: '2023-12-07' + bug_reports: https://github.com/jkrijthe/RSSL + url: '' + url_cran: https://CRAN.R-project.org/package=RSSL + url_git: https://github.com/jkrijthe/RSSL +RSSOP: + version: '1.1' + title: |- + Simulation of Supply Reservoir Systems using Standard Operation + Policy + maintainer: Rezgar Arabzadeh + description: Reservoir Systems Standard Operation Policy. A system for simulation + of supply reservoirs. It proposes functionalities for plotting and evaluation + of supply reservoirs systems. + date_publication: '2016-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSSOP + url_git: '' +RSStest: + version: '1.0' + title: Testing the Equality of Two Means Using RSS and MRSS + maintainer: Fikri Gökpınar + description: |- + Testing the equality of two means using Ranked Set Sampling + and Median Ranked Set Sampling are provided under normal distribution. Data generation functions are also given RSS and MRSS. + Also, data generation functions are given under imperfect ranking data for Ranked Set Sampling and Median Ranked Set Sampling. + Ozdemir Y.A., Ebegil M., & Gokpinar F. (2019), + Ozdemir Y.A., Ebegil M., & Gokpinar F. (2017), . + date_publication: '2023-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSStest + url_git: '' +RSSthemes: + version: 1.0.0 + title: RSS Palettes and Themes + maintainer: Nicola Rennie + description: |- + Defines colour palettes and themes for Royal Statistical + Society (RSS) publications, including Significance magazine. Palettes and + themes are supported in both base R and 'ggplot2' graphics, and are intended + to be used by authors submitting to RSS publications. + date_publication: '2023-08-29' + bug_reports: https://github.com/nrennie/RSSthemes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RSSthemes + url_git: https://github.com/nrennie/RSSthemes +rstac: + version: 1.0.1 + title: Client Library for SpatioTemporal Asset Catalog + maintainer: Felipe Carvalho + description: |- + Provides functions to access, search and download spacetime earth + observation data via SpatioTemporal Asset Catalog (STAC). This package + supports the version 1.0.0 (and older) of the STAC specification + (). + For further details see Simoes et al. (2021) . + date_publication: '2024-07-18' + bug_reports: https://github.com/brazil-data-cube/rstac/issues + url: https://brazil-data-cube.github.io/rstac/ + url_cran: https://CRAN.R-project.org/package=rstac + url_git: '' +rstack: + version: 1.0.1 + title: Stack Data Type as an 'R6' Class + maintainer: Gábor Csárdi + description: |- + An extremely simple stack data type, implemented with 'R6' + classes. The size of the stack increases as needed, and the amortized + time complexity is O(1). The stack may contain arbitrary objects. + date_publication: '2023-08-30' + bug_reports: https://github.com/gaborcsardi/rstack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rstack + url_git: https://github.com/gaborcsardi/rstack#readme +rstackdeque: + version: 1.1.1 + title: Persistent Fast Amortized Stack and Queue Data Structures + maintainer: Shawn T. O'Neil + description: |- + Provides fast, persistent (side-effect-free) stack, queue and + deque (double-ended-queue) data structures. While deques include a superset + of functionality provided by queues, in these implementations queues are + more efficient in some specialized situations. See the documentation for + rstack, rdeque, and rpqueue for details. + date_publication: '2015-04-13' + bug_reports: https://github.com/oneilsh/rstackdeque/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rstackdeque + url_git: https://github.com/oneilsh/rstackdeque +rstan: + version: 2.32.6 + title: R Interface to Stan + maintainer: Ben Goodrich + description: |- + User-facing R functions are provided to parse, compile, test, + estimate, and analyze Stan models by accessing the header-only Stan library + provided by the 'StanHeaders' package. The Stan project develops a probabilistic + programming language that implements full Bayesian statistical inference + via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' + approximation, and (optionally penalized) maximum likelihood estimation via + optimization. In all three cases, automatic differentiation is used to quickly + and accurately evaluate gradients without burdening the user with the need to + derive the partial derivatives. + date_publication: '2024-03-05' + bug_reports: https://github.com/stan-dev/rstan/issues/ + url: https://mc-stan.org/rstan/ + url_cran: https://CRAN.R-project.org/package=rstan + url_git: '' +rstanarm: + version: 2.32.1 + title: Bayesian Applied Regression Modeling via Stan + maintainer: Ben Goodrich + description: |- + Estimates previously compiled regression models using the 'rstan' + package, which provides the R interface to the Stan C++ library for Bayesian + estimation. Users specify models via the customary R syntax with a formula and + data.frame plus some additional arguments for priors. + date_publication: '2024-01-18' + bug_reports: https://github.com/stan-dev/rstanarm/issues + url: https://mc-stan.org/rstanarm/ + url_cran: https://CRAN.R-project.org/package=rstanarm + url_git: '' +rstanbdp: + version: 0.0.3 + title: Bayesian Deming Regression for Method Comparison + maintainer: Giorgio Pioda + description: |- + Regression methods to quantify the relation + between two measurement methods are provided by this package. The + focus is on a Bayesian Deming regressions family. With a Bayesian + method the Deming regression can be run in a traditional fashion or + can be run in a robust way just decreasing the degree of freedom + d.f. of the sampling distribution. With d.f. = 1 an extremely robust + Cauchy distribution can be sampled. Moreover, models for dealing + with heteroscedastic data are also provided. For reference see + G. Pioda (2024) . + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rstanbdp + url_git: '' +rstanemax: + version: 0.1.9 + title: Emax Model Analysis with 'Stan' + maintainer: Kenta Yoshida + description: Perform sigmoidal Emax model fit using 'Stan' in a formula notation, + without writing 'Stan' model code. + date_publication: '2025-02-17' + bug_reports: https://github.com/yoshidk6/rstanemax/issues + url: https://yoshidk6.github.io/rstanemax/ + url_cran: https://CRAN.R-project.org/package=rstanemax + url_git: https://github.com/yoshidk6/rstanemax +rstantools: + version: 2.4.0 + title: Tools for Developing R Packages Interfacing with 'Stan' + maintainer: Jonah Gabry + description: |- + Provides various tools for developers of R packages interfacing + with 'Stan' , including functions to set up the required + package structure, S3 generics and default methods to unify function naming + across 'Stan'-based R packages, and vignettes with recommendations for + developers. + date_publication: '2024-01-31' + bug_reports: https://github.com/stan-dev/rstantools/issues + url: https://mc-stan.org/rstantools/ + url_cran: https://CRAN.R-project.org/package=rstantools + url_git: '' +RStata: + version: 1.1.1 + title: A Bit of Glue Between R and Stata + maintainer: Luca Braglia + description: |- + A simple R -> Stata interface allowing the user to + execute Stata commands (both inline and from a .do file) + from R. + date_publication: '2016-10-27' + bug_reports: http://github.com/lbraglia/RStata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RStata + url_git: http://github.com/lbraglia/RStata +rstatix: + version: 0.7.2 + title: Pipe-Friendly Framework for Basic Statistical Tests + maintainer: Alboukadel Kassambara + description: |- + Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, + for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. + The output of each test is automatically transformed into a tidy data frame to facilitate visualization. + Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. + Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs + (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. + It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and + 'Cramer V' for the association between categorical variables. + The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances. + date_publication: '2023-02-01' + bug_reports: https://github.com/kassambara/rstatix/issues + url: https://rpkgs.datanovia.com/rstatix/ + url_cran: https://CRAN.R-project.org/package=rstatix + url_git: '' +rstatscn: + version: 1.1.3 + title: R Interface for China National Data + maintainer: Xuehui YANG + description: |- + R interface for china national data , + some convenient functions for accessing the national data are provided. + date_publication: '2019-04-25' + bug_reports: http://www.bagualu.net/wordpress/rstatscn-the-r-interface-for-china-national-data + url: http://www.bagualu.net/ + url_cran: https://CRAN.R-project.org/package=rstatscn + url_git: '' +Rstg: + version: 0.0.1 + title: 'STG : Feature Selection using STochastic Gates' + maintainer: Yutaro Yamada + description: '''STG'' is a method for feature selection in neural network. The procedure + is based on probabilistic relaxation of the l0 norm of features, or the count + of the number of selected features. The framework simultaneously learns either + a nonlinear regression or classification function while selecting a small subset + of features. Read more: Yamada et al. (2020) .' + date_publication: '2021-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rstg + url_git: '' +rstiefel: + version: 1.0.1 + title: |- + Random Orthonormal Matrix Generation and Optimization on the + Stiefel Manifold + maintainer: Peter Hoff + description: Simulation of random orthonormal matrices from linear and quadratic + exponential family distributions on the Stiefel manifold. The most general type + of distribution covered is the matrix-variate Bingham-von Mises-Fisher distribution. + Most of the simulation methods are presented in Hoff(2009) "Simulation of the + Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate + and Relational Data" . The package also includes + functions for optimization on the Stiefel manifold based on algorithms described + in Wen and Yin (2013) "A feasible method for optimization with orthogonality constraints" + . + date_publication: '2021-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rstiefel + url_git: '' +RStoolbox: + version: 1.0.2.1 + title: Remote Sensing Data Analysis + maintainer: Konstantin Mueller + description: |- + Toolbox for remote sensing image processing and analysis such as + calculating spectral indexes, principal component transformation, unsupervised + and supervised classification or fractional cover analyses. + date_publication: '2025-02-03' + bug_reports: https://github.com/bleutner/RStoolbox/issues + url: https://bleutner.github.io/RStoolbox/ + url_cran: https://CRAN.R-project.org/package=RStoolbox + url_git: https://github.com/bleutner/RStoolbox +rstpm2: + version: 1.6.6.1 + title: Smooth Survival Models, Including Generalized Survival Models + maintainer: Mark Clements + description: R implementation of generalized survival models (GSMs), smooth accelerated + failure time (AFT) models and Markov multi-state models. For the GSMs, g(S(t|x))=eta(t,x) + for a link function g, survival S at time t with covariates x and a linear predictor + eta(t,x). The main assumption is that the time effect(s) are smooth . + For fully parametric models with natural splines, this re-implements Stata's 'stpm2' + function, which are flexible parametric survival models developed by Royston and + colleagues. We have extended the parametric models to include any smooth parametric + smoothers for time. We have also extended the model to include any smooth penalized + smoothers from the 'mgcv' package, using penalized likelihood. These models include + left truncation, right censoring, interval censoring, gamma frailties and normal + random effects , and copulas. For the smooth AFTs, S(t|x) + = S_0(t*eta(t,x)), where the baseline survival function S_0(t)=exp(-exp(eta_0(t))) + is modelled for natural splines for eta_0, and the time-dependent cumulative acceleration + factor eta(t,x)=\int_0^t exp(eta_1(u,x)) du for log acceleration factor eta_1(u,x). + The Markov multi-state models allow for a range of models with smooth transitions + to predict transition probabilities, length of stay, utilities and costs, with + differences, ratios and standardisation. + date_publication: '2024-12-21' + bug_reports: https://github.com/mclements/rstpm2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rstpm2 + url_git: https://github.com/mclements/rstpm2 +rStrava: + version: 1.3.2 + title: Access the 'Strava' API + maintainer: Marcus W. Beck + description: Functions to access data from the 'Strava v3 API' . + date_publication: '2024-10-23' + bug_reports: https://github.com/fawda123/rStrava/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rStrava + url_git: '' +rstream: + version: 1.3.7 + title: Streams of Random Numbers + maintainer: Josef Leydold + description: Unified object oriented interface for multiple independent streams + of random numbers from different sources. + date_publication: '2022-10-19' + bug_reports: '' + url: https://statmath.wu.ac.at/arvag/ + url_cran: https://CRAN.R-project.org/package=rstream + url_git: '' +rstudio.prefs: + version: 0.1.9 + title: Set 'RStudio' Preferences + maintainer: Daniel D. Sjoberg + description: |- + As of 'RStudio' v1.3, the preferences in the Global Options + dialog (and a number of other preferences that aren’t) are now saved + in simple, plain-text JSON files. This package provides an interface + for working with these 'RStudio' JSON preference files to easily make + modifications without using the point-and-click option menus. This is + particularly helpful when working on teams to ensure a unified + experience across machines and utilizing settings for best practices. + date_publication: '2022-07-16' + bug_reports: https://github.com/ddsjoberg/rstudio.prefs/issues + url: https://www.danieldsjoberg.com/rstudio.prefs/index.html + url_cran: https://CRAN.R-project.org/package=rstudio.prefs + url_git: https://github.com/ddsjoberg/rstudio.prefs +rstudioapi: + version: 0.17.1 + title: Safely Access the RStudio API + maintainer: Kevin Ushey + description: |- + Access the RStudio API (if available) and provide informative error + messages when it's not. + date_publication: '2024-10-22' + bug_reports: https://github.com/rstudio/rstudioapi/issues + url: https://rstudio.github.io/rstudioapi/ + url_cran: https://CRAN.R-project.org/package=rstudioapi + url_git: https://github.com/rstudio/rstudioapi +rsubgroup: + version: '1.1' + title: Subgroup Discovery and Analytics + maintainer: Martin Atzmueller + description: |- + A collection of efficient and effective tools and + algorithms for subgroup discovery and analytics. The package + integrates an R interface to the org.vikamine.kernel library + of the VIKAMINE system implementing + subgroup discovery, pattern mining and analytics in Java. + date_publication: '2021-02-23' + bug_reports: '' + url: https://rsubgroup.org + url_cran: https://CRAN.R-project.org/package=rsubgroup + url_git: '' +rsurface: + version: 1.1.0 + title: |- + Design of Rotatable Central Composite Experiments and Response + Surface Analysis + maintainer: Timothy Schwinghamer + description: |- + Produces tables with the level of replication (number of replicates) and the + experimental uncoded values of the quantitative factors to be used for rotatable Central + Composite Design (CCD) experimentation and a 2-D contour plot of the corresponding + variance of the predicted response according to + Mead et al. (2012) design_ccd(), and analyzes + CCD data with response surface methodology ccd_analysis(). A rotatable CCD + provides values of the variance of the predicted response that are concentrically + distributed around the average treatment combination used in the experimentation, which + with uniform precision (implied by the use of several replicates at the average + treatment combination) improves greatly the search and finding of an optimum response. + These properties of a rotatable CCD represent undeniable advantages over the classical + factorial design, as discussed by Panneton et al. (1999) and + Mead et al. (2012) among others. + date_publication: '2018-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsurface + url_git: '' +Rsurrogate: + version: '3.2' + title: |- + Robust Estimation of the Proportion of Treatment Effect + Explained by Surrogate Marker Information + maintainer: Layla Parast + description: Provides functions to estimate the proportion of treatment effect on + the primary outcome that is explained by the treatment effect on the surrogate + marker. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rsurrogate + url_git: '' +rsurv: + version: 0.0.2 + title: Random Generation of Survival Data + maintainer: Fabio Demarqui + description: Random generation of survival data from a wide range of regression + models, including accelerated failure time (AFT), proportional hazards (PH), proportional + odds (PO), accelerated hazard (AH), Yang and Prentice (YP), and extended hazard + (EH) models. The package 'rsurv' also stands out by its ability to generate survival + data from an unlimited number of baseline distributions provided that an implementation + of the quantile function of the chosen baseline distribution is available in R. + Another nice feature of the package 'rsurv' lies in the fact that linear predictors + are specified via a formula-based approach, facilitating the inclusion of categorical + variables and interaction terms. The functions implemented in the package 'rsurv' + can also be employed to simulate survival data with more complex structures, such + as survival data with different types of censoring mechanisms, survival data with + cure fraction, survival data with random effects (frailties), multivariate survival + data, and competing risks survival data. Details about the R package 'rsurv' can + be found in Demarqui (2024) . + date_publication: '2024-10-25' + bug_reports: https://github.com/fndemarqui/rsurv/issues + url: https://fndemarqui.github.io/rsurv/ + url_cran: https://CRAN.R-project.org/package=rsurv + url_git: https://github.com/fndemarqui/rsurv +RSurveillance: + version: 0.2.1 + title: Design and Analysis of Disease Surveillance Activities + maintainer: Rohan Sadler + description: |- + A range of functions for the design and + analysis of disease surveillance activities. These functions were + originally developed for animal health surveillance activities but can be + equally applied to aquatic animal, wildlife, plant and human health + surveillance activities. Utilities are included for sample size calculation + and analysis of representative surveys for disease freedom, risk-based + studies for disease freedom and for prevalence estimation. + This package is based on Cameron A., Conraths F., Frohlich A., Schauer B., + Schulz K., Sergeant E., Sonnenburg J., Staubach C. (2015). R package of + functions for risk-based surveillance. Deliverable 6.24, WP 6 - Decision + making tools for implementing risk-based surveillance, Grant Number + no. 310806, RISKSUR (). + Many of the 'RSurveillance' functions are incorporated into the 'epitools' + website: Sergeant, ESG, 2019. Epitools epidemiological calculators. + Ausvet Pty Ltd. Available at: . + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RSurveillance + url_git: https://github.com/roStats/RSurveillance +rsurveycto: + version: 0.2.1 + title: Interact with Data on 'SurveyCTO' + maintainer: Jake Hughey + description: |- + 'SurveyCTO' is a platform for mobile data collection in offline settings. + The 'rsurveycto' R package uses the 'SurveyCTO' REST API + + to read datasets and forms from a 'SurveyCTO' server into R as 'data.table's + and to download file attachments. The package also has limited support to + write datasets to a server. + date_publication: '2024-09-03' + bug_reports: '' + url: https://agency-fund.github.io/rsurveycto/ + url_cran: https://CRAN.R-project.org/package=rsurveycto + url_git: https://github.com/agency-fund/rsurveycto +rsvd: + version: 1.0.5 + title: Randomized Singular Value Decomposition + maintainer: N. Benjamin Erichson + description: |- + Low-rank matrix decompositions are fundamental tools and widely used for data + analysis, dimension reduction, and data compression. Classically, highly accurate + deterministic matrix algorithms are used for this task. However, the emergence of + large-scale data has severely challenged our computational ability to analyze big data. + The concept of randomness has been demonstrated as an effective strategy to quickly produce + approximate answers to familiar problems such as the singular value decomposition (SVD). + The rsvd package provides several randomized matrix algorithms such as the randomized + singular value decomposition (rsvd), randomized principal component analysis (rpca), + randomized robust principal component analysis (rrpca), randomized interpolative + decomposition (rid), and the randomized CUR decomposition (rcur). In addition several plot + functions are provided. + date_publication: '2021-04-16' + bug_reports: https://github.com/erichson/rSVD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsvd + url_git: https://github.com/erichson/rSVD +rsvddpd: + version: 1.0.0 + title: |- + Robust Singular Value Decomposition using Density Power + Divergence + maintainer: Subhrajyoty Roy + description: |- + Computing singular value decomposition with robustness is a challenging task. + This package provides an implementation of computing robust SVD using density power + divergence (). It combines the idea of robustness and efficiency in estimation + based on a tuning parameter. It also provides utility functions to simulate various + scenarios to compare performances of different algorithms. + date_publication: '2021-10-27' + bug_reports: https://github.com/subroy13/rsvddpd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsvddpd + url_git: https://github.com/subroy13/rsvddpd +rsvg: + version: 2.6.1 + title: |- + Render SVG Images into PDF, PNG, (Encapsulated) PostScript, or + Bitmap Arrays + maintainer: Jeroen Ooms + description: |- + Renders vector-based svg images into high-quality custom-size + bitmap arrays using 'librsvg2'. The resulting bitmap can be written to + e.g. png, jpeg or webp format. In addition, the package can convert + images directly to various formats such as pdf or postscript. + date_publication: '2024-09-20' + bug_reports: https://github.com/ropensci/rsvg/issues + url: https://docs.ropensci.org/rsvg/ + url_cran: https://CRAN.R-project.org/package=rsvg + url_git: https://github.com/ropensci/rsvg +rswipl: + version: 9.3.18 + title: Embed 'SWI'-'Prolog' + maintainer: Matthias Gondan + description: Interface to 'SWI'-'Prolog', . This package + is normally not loaded directly, please refer to package 'rolog' instead. The + purpose of this package is to provide the 'Prolog' runtime on systems that do + not have a software installation of 'SWI'-'Prolog'. + date_publication: '2025-01-07' + bug_reports: https://github.com/mgondan/rswipl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rswipl + url_git: https://github.com/mgondan/rswipl +Rsymphony: + version: 0.1-33 + title: SYMPHONY in R + maintainer: Kurt Hornik + description: An R interface to the SYMPHONY solver for mixed-integer linear programs. + date_publication: '2021-12-28' + bug_reports: '' + url: https://projects.coin-or.org/SYMPHONY + url_cran: https://CRAN.R-project.org/package=Rsymphony + url_git: https://R-Forge.R-project.org/projects/rsymphony +rsyncrosim: + version: 2.0.1 + title: The R Interface to 'SyncroSim' + maintainer: Katie Birchard + description: |- + 'SyncroSim' is a generalized framework for managing scenario-based + datasets (). 'rsyncrosim' provides an interface to + 'SyncroSim'. Simulation models can be added to 'SyncroSim' in order to + transform these datasets, taking advantage of general features such as + defining scenarios of model inputs, running Monte Carlo simulations, and + summarizing model outputs. 'rsyncrosim' requires 'SyncroSim' 2.3.5 or higher + (API documentation: ). + date_publication: '2024-10-14' + bug_reports: https://github.com/syncrosim/rsyncrosim/issues/ + url: https://syncrosim.github.io/rsyncrosim/ + url_cran: https://CRAN.R-project.org/package=rsyncrosim + url_git: '' +rsyntax: + version: 0.1.4 + title: |- + Extract Semantic Relations from Text by Querying and Reshaping + Syntax + maintainer: Kasper Welbers + description: |- + Various functions for querying and reshaping dependency trees, + as for instance created with the 'spacyr' or 'udpipe' packages. + This enables the automatic extraction of useful semantic relations from texts, + such as quotes (who said what) and clauses (who did what). Method proposed in + Van Atteveldt et al. (2017) . + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rsyntax + url_git: '' +rsyslog: + version: 1.0.3 + title: Interface to the 'syslog' System Logger + maintainer: Aaron Jacobs + description: |- + Functions to write messages to the 'syslog' system logger API, + available on all 'POSIX'-compatible operating systems. Features include + tagging messages with a priority level and application type, as well as + masking (hiding) messages below a given priority level. + date_publication: '2023-05-08' + bug_reports: https://github.com/atheriel/rsyslog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rsyslog + url_git: https://github.com/atheriel/rsyslog +rt: + version: 1.1.0 + title: Interface to the 'Request Tracker' API + maintainer: Bryce Mecum + description: |- + Provides a programmatic interface to the 'Request Tracker' (RT) + HTTP API . 'RT' is a popular + ticket tracking system. + date_publication: '2021-05-15' + bug_reports: https://github.com/nceas/rt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rt + url_git: https://github.com/nceas/rt +rt.test: + version: 1.18.7.9 + title: Robustified t-Test + maintainer: Chanseok Park + description: Performs one-sample t-test based on robustified statistics using median/MAD + (TA) and Hodges-Lehmann/Shamos (TB). For more details, see Park and Wang (2018). + This work was partially supported by the National Research Foundation of Korea + (NRF) grant funded by the Korea government (No. NRF-2017R1A2B4004169). + date_publication: '2018-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rt.test + url_git: https://github.com/statpnu/R-package +rt3: + version: 0.1.2 + title: Tic-Tac-Toe Package for R + maintainer: Johan Jordaan + description: Play the classic game of tic-tac-toe (naughts and crosses). + date_publication: '2016-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rt3 + url_git: '' +rTableICC: + version: 1.0.9 + title: Random Generation of Contingency Tables + maintainer: Haydar Demirhan + description: Contains functions for random generation of R x C and 2 x 2 x K contingency + tables. In addition to the generation of contingency tables over predetermined + intraclass-correlated clusters, it is possible to generate contingency tables + without intraclass correlations under product multinomial, multinomial, and Poisson + sampling plans. It also consists of a function for generation of random data from + a given discrete probability distribution function. See Demirhan (2016) + for more information. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rTableICC + url_git: '' +rtables: + version: 0.6.11 + title: Reporting Tables + maintainer: Joe Zhu + description: |- + Reporting tables often have structure that goes beyond simple + rectangular data. The 'rtables' package provides a framework for + declaring complex multi-level tabulations and then applying them to + data. This framework models both tabulation and the resulting tables + as hierarchical, tree-like objects which support sibling sub-tables, + arbitrary splitting or grouping of data in row and column dimensions, + cells containing multiple values, and the concept of contextual + summary computations. A convenient pipe-able interface is provided for + declaring table layouts and the corresponding computations, and then + applying them to data. + date_publication: '2025-01-10' + bug_reports: https://github.com/insightsengineering/rtables/issues + url: https://insightsengineering.github.io/rtables/ + url_cran: https://CRAN.R-project.org/package=rtables + url_git: https://github.com/insightsengineering/rtables +rtables.officer: + version: 0.0.2 + title: Exporting Tools for 'rtables' + maintainer: Joe Zhu + description: |- + Designed to create and display complex tables with R, the 'rtables' R package allows + cells in an 'rtables' object to contain any high-dimensional data structure, which can then be + displayed with cell-specific formatting instructions. Additionally, the 'rtables.officer' + package supports export formats related to the Microsoft Office software suite, including + Microsoft Word ('docx') and Microsoft PowerPoint ('pptx'). + date_publication: '2025-01-17' + bug_reports: https://github.com/insightsengineering/rtables.officer/issues + url: https://insightsengineering.github.io/rtables.officer/ + url_cran: https://CRAN.R-project.org/package=rtables.officer + url_git: https://github.com/insightsengineering/rtables.officer +rtabulator: + version: 0.1.2 + title: R Bindings for 'Tabulator JS' + maintainer: Stefan Kuethe + description: |- + Provides R bindings for 'Tabulator JS' . + Makes it a breeze to create highly customizable interactive tables in 'rmarkdown' documents + and 'shiny' applications. It includes filtering, grouping, editing, input validation, + history recording, column formatters, packaged themes and more. + date_publication: '2024-09-23' + bug_reports: https://github.com/eodaGmbH/rtabulator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtabulator + url_git: https://github.com/eodaGmbH/rtabulatorhttps://eodagmbh.github.io/rtabulator/ +Rtapas: + version: '1.2' + title: Random Tanglegram Partitions + maintainer: Mar Llaberia-Robledillo + description: |- + Applies a given global-fit method to random partial tanglegrams of a fixed size + to identify the associations, terminals, and nodes that maximize phylogenetic + (in)congruence. It also includes functions to compute more easily the confidence + intervals of classification metrics and plot results, reducing computational time. + See Llaberia-Robledillo et al., (2023) . + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rtapas + url_git: '' +rtape: + version: '2.2' + title: |- + Manage and manipulate large collections of R objects stored as + tape-like files + maintainer: Miron B. Kursa + description: |- + Storing huge data in RData format causes problems because + of the necessity to load the whole file to the memory in order + to access and manipulate objects inside such file; rtape is a + simple solution to this problem. The package contains several + wrappers of R built-in serialize/unserialize mechanism allowing + user to quickly append objects to a tape-like file and later + iterate over them requiring only one copy of each stored object + to reside in memory a time. + date_publication: '2012-07-31' + bug_reports: '' + url: http://mbq.me/rtape + url_cran: https://CRAN.R-project.org/package=rtape + url_git: '' +Rtauchen: + version: '1.0' + title: Discretization of AR(1) Processes + maintainer: David Zarruk Valencia + description: Discretize AR(1) process following Tauchen (1986) . + A discrete Markov chain that approximates in the sense of weak convergence a continuous-valued + univariate Autoregressive process of first order is generated. It is a popular + method used in economics and in finance. + date_publication: '2016-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rtauchen + url_git: https://github.com/davidzarruk/Rtauchen +RTaxometrics: + version: 3.2.1 + title: Taxometric Analysis + maintainer: John Ruscio + description: We provide functions to perform taxometric analyses. This package contains + 46 functions, but only 5 should be called directly by users. CheckData() should + be run prior to any taxometric analysis to ensure that the data are appropriate + for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample + of data. RunCCFIProfile() performs a series of taxometric analyses to generate + a CCFI profile. CreateData() generates a sample of categorical or dimensional + data. ClassifyCases() assigns cases to groups using the base-rate classification + method. + date_publication: '2023-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTaxometrics + url_git: '' +RTCC: + version: 0.1.1 + title: Detecting Trait Clustering in Environmental Gradients + maintainer: Mateu Menendez-Serra + description: |- + The Randomized Trait Community Clustering method (Triado-Margarit et al., 2019, + ) is a statistical approach which allows to determine whether + if an observed trait clustering pattern is related to an increasing environmental constrain. + The method 1) determines whether exists or not a trait clustering on the sampled communities + and 2) assess if the observed clustering signal is related or not to an increasing environmental + constrain along an environmental gradient. Also, when the effect of the environmental gradient + is not linear, allows to determine consistent thresholds on the community assembly based on trait-values. + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTCC + url_git: '' +rTCRBCRr: + version: 0.1.1 + title: Repertoire Analysis of the Detected Clonotype + maintainer: Lizhong Ding + description: |- + The 'TRUST4' or 'MiXCR' is used to identify the clonotypes. + The goal of 'rTCRBCRr' is to process the results from these clonotyping tools, + and analyze the clonotype repertoire metrics based on chain names and IGH isotypes. + The manuscript is still under preparation for publication for now. + The references describing the methods in this package will be added later. + date_publication: '2022-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rTCRBCRr + url_git: '' +RTD: + version: 0.4.1 + title: Simple TD API Client + maintainer: Aki Ariga + description: |2- + + Upload R data.frame to Arm Treasure Data, see . + You can execute database or table handling for resources on Arm Treasure Data. + date_publication: '2020-07-26' + bug_reports: https://github.com/treasure-data/RTD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RTD + url_git: https://github.com/treasure-data/RTD +RTDE: + version: 0.2-2 + title: Robust Tail Dependence Estimation + maintainer: Christophe Dutang + description: Robust tail dependence estimation for bivariate models. This package + is based on two papers by the authors:'Robust and bias-corrected estimation of + the coefficient of tail dependence' and 'Robust and bias-corrected estimation + of probabilities of extreme failure sets'. This work was supported by a research + grant (VKR023480) from VILLUM FONDEN and an international project for scientific + cooperation (PICS-6416). + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTDE + url_git: '' +rtdists: + version: 0.11-5 + title: Response Time Distributions + maintainer: Henrik Singmann + description: |- + Provides response time distributions (density/PDF, + distribution function/CDF, quantile function, and random + generation): (a) Ratcliff diffusion model (Ratcliff & + McKoon, 2008, ) based on C + code by Andreas and Jochen Voss and (b) linear ballistic + accumulator (LBA; Brown & Heathcote, 2008, + ) with different + distributions underlying the drift rate. + date_publication: '2022-01-07' + bug_reports: https://github.com/rtdists/rtdists/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtdists + url_git: https://github.com/rtdists/rtdists/ +rtematres: + version: '0.2' + title: The rtematres API package + maintainer: Claas-Thido Pfaff + description: Exploit controlled vocabularies organized on tematres servers. + date_publication: '2013-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtematres + url_git: https://github.com/cpfaff/rtematres +rtemps: + version: 0.8.0 + title: R Templates for Reproducible Data Analyses + maintainer: John Zobolas + description: |- + A collection of R Markdown templates for nicely structured, reproducible + data analyses in R. The templates have embedded examples on how to write + citations, footnotes, equations and use colored message/info boxes, how to + cross-reference different parts/sections in the report, provide a nice + table of contents (toc) with a References section and proper R session + information as well as examples using DT tables and ggplot2 graphs. + The bookdown Lite template theme supports code folding. + date_publication: '2020-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtemps + url_git: https://github.com/bblodfon/rtemps +rTensor: + version: 1.4.8 + title: Tools for Tensor Analysis and Decomposition + maintainer: Koki Tsuyuzaki + description: |- + A set of tools for creation, manipulation, and modeling + of tensors with arbitrary number of modes. A tensor in the context of data + analysis is a multidimensional array. rTensor does this by providing a S4 + class 'Tensor' that wraps around the base 'array' class. rTensor + provides common tensor operations as methods, including matrix unfolding, + summing/averaging across modes, calculating the Frobenius norm, and taking + the inner product between two tensors. Familiar array operations are + overloaded, such as index subsetting via '[' and element-wise operations. + rTensor also implements various tensor decomposition, including CP, GLRAM, + MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements + transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some + auxiliary functions include the Khatri-Rao product, Kronecker product, and + the Hadamard product for a list of matrices. + date_publication: '2021-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rTensor + url_git: https://github.com/rikenbit/rTensor +rTensor2: + version: 2.0.0 + title: MultiLinear Algebra + maintainer: Kyle Caudle + description: A set of tools for basic tensor operators. A tensor in the context + of data analysis in a multidimensional array. The tools in this package rely on + using any discrete transformation (e.g. Fast Fourier Transform (FFT)). Standard + tools included are the Eigenvalue decomposition of a tensor, the QR decomposition + and LU decomposition. Other functionality includes the inverse of a tensor and + the transpose of a symmetric tensor. Functionality in the package is outlined + in Kernfeld et al. (2015) . + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rTensor2 + url_git: '' +rTephra: + version: '0.1' + title: Tephra Transport Modeling + maintainer: Jake Anderson + description: Models and displays tephra transport through custom (windy, turbulent, + heterogeneous) atmosphere over custom topography. Includes a Lagrangian (particle-tracking) + tephra transport model and a function to save snapshots of model as png files. + date_publication: '2018-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rTephra + url_git: '' +rtern: + version: 0.1.2 + title: A Ternary Conditional Operator for R + maintainer: Gethin Davies + description: A small language extension for succinct conditional assignment using + `?` and `:`, emulating the conditional ternary operator syntax using in C, Java, + JavaScript and other languages. + date_publication: '2022-01-24' + bug_reports: https://github.com/grddavies/rtern/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtern + url_git: https://github.com/grddavies/rtern +RTextTools: + version: 1.4.3 + title: Automatic Text Classification via Supervised Learning + maintainer: Loren Collingwood + description: |- + A machine learning package for automatic text classification + that makes it simple for novice users to get started with machine + learning, while allowing experienced users to easily experiment + with different settings and algorithm combinations. The package + includes eight algorithms for ensemble classification (svm, slda, + boosting, bagging, random forests, glmnet, decision trees, neural + networks), comprehensive analytics, and thorough documentation. + date_publication: '2020-04-26' + bug_reports: '' + url: http://www.rtexttools.com/ + url_cran: https://CRAN.R-project.org/package=RTextTools + url_git: '' +rtf: + version: 0.4-14.1 + title: Rich Text Format (RTF) Output + maintainer: Michael E. Schaffer + description: A set of R functions to output Rich Text Format (RTF) files with high + resolution tables and graphics that may be edited with a standard word processor + such as Microsoft Word. + date_publication: '2020-03-22' + bug_reports: https://github.com/schaffman5/rtf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtf + url_git: https://github.com/schaffman5/rtf +RTFA: + version: 0.1.0 + title: Robust Factor Analysis for Tensor Time Series + maintainer: Lingxiao Li + description: Tensor Factor Models (TFM) are appealing dimension reduction tools + for high-order tensor time series, and have wide applications in economics, finance + and medical imaging. We propose an one-step projection estimator by minimizing + the least-square loss function, and further propose a robust estimator with an + iterative weighted projection technique by utilizing the Huber loss function. + The methods are discussed in Barigozzi et al. (2022) , and Barigozzi + et al. (2023) . + date_publication: '2023-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTFA + url_git: '' +rTG: + version: 1.0.4 + title: Methods to Analyse Seasonal Radial Tree Growth Data + maintainer: Jernej Jevsenak + description: |- + Methods for comparing different regression algorithms for + describing the temporal dynamics of secondary tree growth (xylem and + phloem). Users can compare the accuracy of the most common fitting methods + usually used to analyse xylem and phloem data, i.e., Gompertz function, + Double Gompertz function, General Additive Models (GAMs); and an algorithm + newly introduced to the field, i.e., Bayesian Regularised Neural Networks + (brnn). The core function of the package is XPSgrowth(), while the results + can be interpreted using implemented generic S3 methods, such as plot() and + summary(). + date_publication: '2025-02-28' + bug_reports: https://github.com/jernejjevsenak/rTG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rTG + url_git: https://github.com/jernejjevsenak/rTG +rtgstat: + version: 0.3.4 + title: Client for 'TGStat API' + maintainer: Alexey Seleznev + description: |- + Allow function for using 'TGStat Stat API' and + 'TGStat Search API', for more details see . + 'TGStat' provide telegram channel analytics data. + date_publication: '2024-10-25' + bug_reports: https://github.com/selesnow/rtgstat/issues + url: https://selesnow.github.io/rtgstat/ + url_cran: https://CRAN.R-project.org/package=rtgstat + url_git: '' +Rthingsboard: + version: 0.2.7 + title: '''ThingsBoard'' API' + maintainer: David Dorchies + description: The goal of 'Rthingsboard' is to provide interaction with the API of + 'ThingsBoard' (), an open-source IoT platform for device + management, data collection, processing and visualization. + date_publication: '2022-01-19' + bug_reports: https://github.com/DDorch/Rthingsboard/issues + url: https://ddorch.github.io/Rthingsboard/ + url_cran: https://CRAN.R-project.org/package=Rthingsboard + url_git: https://github.com/DDorch/Rthingsboard#readme +rticles: + version: '0.27' + title: Article Formats for R Markdown + maintainer: Christophe Dervieux + description: |- + A suite of custom R Markdown formats and templates for + authoring journal articles and conference submissions. + date_publication: '2024-04-06' + bug_reports: https://github.com/rstudio/rticles/issues + url: https://pkgs.rstudio.com/rticles/ + url_cran: https://CRAN.R-project.org/package=rticles + url_git: https://github.com/rstudio/rticles +rticulate: + version: 2.0.1 + title: Articulatory Data Processing in R + maintainer: Stefano Coretta + description: |- + A tool for processing Articulate + Assistant Advanced™ (AAA) ultrasound tongue imaging data and Carstens AG500/1 electro-magnetic articulographic data. + date_publication: '2025-02-20' + bug_reports: https://github.com/stefanocoretta/rticulate/issues + url: https://stefanocoretta.github.io/rticulate/ + url_cran: https://CRAN.R-project.org/package=rticulate + url_git: https://github.com/stefanocoretta/rticulate +rtiddlywiki: + version: 0.1.0 + title: R Interface for 'TiddlyWiki' + maintainer: Bangyou Zheng + description: '''TiddlyWiki'' is a unique non-linear notebook for capturing, organising + and sharing complex information. ''rtiddlywiki'' is a R interface of ''TiddlyWiki'' + to create new tiddler from Rmarkdown file, and then put + into a local ''TiddlyWiki'' node.js server if it is available.' + date_publication: '2022-07-05' + bug_reports: https://github.com/byzheng/rtiddlywiki/issues + url: https://rtiddlywiki.bangyou.me/ + url_cran: https://CRAN.R-project.org/package=rtiddlywiki + url_git: https://github.com/byzheng/rtiddlywiki +rtide: + version: 0.0.11 + title: Tide Heights + maintainer: Luke Miller + description: |- + Calculates tide heights based on tide station harmonics. It + includes the harmonics data for 637 US stations. The harmonics data + was converted from + , + NOAA web site data processed by David Flater for 'XTide'. The code to + calculate tide heights from the harmonics is based on 'XTide'. + date_publication: '2024-11-20' + bug_reports: https://github.com/millerlp/rtide/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtide + url_git: https://github.com/millerlp/rtide +rties: + version: 5.0.0 + title: Modeling Interpersonal Dynamics + maintainer: Emily Butler + description: |- + The name of this package grew out of our research on temporal interpersonal + emotion systems (TIES), hence 'rties'. It provides tools for using a set of models to + investigate temporal processes in bivariate (e.g., dyadic) systems. The general approach + is to model, one dyad at a time, the dynamics of a variable that is assessed repeatedly + from both partners, extract the parameter estimates for each dyad, and then use those + parameter estimates as input to a latent profile analysis to extract groups of dyads with + qualitatively distinct dynamics. Finally, the profile memberships can be used to either + predict, or be predicted by, another variable of interest. Currently, 2 models are supported: + 1) inertia-coordination, and 2) a coupled-oscillator. Extended documentation is provided + in vignettes. Theoretical background can be found in Butler (2011) + and Butler & Barnard (2019) . + date_publication: '2020-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rties + url_git: '' +RTIGER: + version: 2.1.0 + title: HMM-Based Model for Genotyping and Cross-Over Identification + maintainer: Rafael Campos-Martin + description: Our method integrates information from all sequenced samples, thus + avoiding loss of alleles due to low coverage. Moreover, it increases the statistical + power to uncover sequencing or alignment errors . + date_publication: '2023-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTIGER + url_git: '' +rtika: + version: 2.7.0 + title: R Interface to 'Apache Tika' + maintainer: Sasha Goodman + description: Extract text or metadata from over a thousand file types, using Apache + Tika . Get either plain text or structured XHTML content. + date_publication: '2023-05-04' + bug_reports: https://github.com/ropensci/rtika/issues/ + url: https://docs.ropensci.org/rtika/ + url_cran: https://CRAN.R-project.org/package=rtika + url_git: https://github.com/ropensci/rtika/ +rtiktoken: + version: 0.0.6 + title: |- + A Byte-Pair-Encoding (BPE) Tokenizer for OpenAI's Large Language + Models + maintainer: David Zimmermann-Kollenda + description: A thin wrapper around the tiktoken-rs crate, allowing to encode text + into Byte-Pair-Encoding (BPE) tokens and decode tokens back to text. This is useful + to understand how Large Language Models (LLMs) perceive text. + date_publication: '2024-11-06' + bug_reports: https://github.com/DavZim/rtiktoken/issues + url: https://davzim.github.io/rtiktoken/ + url_cran: https://CRAN.R-project.org/package=rtiktoken + url_git: https://github.com/DavZim/rtiktoken/ +rtip: + version: 1.1.1 + title: |- + Inequality, Welfare and Poverty Indices and Curves using the + EU-SILC Data + maintainer: Angel Berihuete + description: R tools to measure and compare inequality, welfare and poverty using + the EU statistics on income and living conditions surveys. + date_publication: '2018-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtip + url_git: '' +rtist: + version: 1.0.0 + title: A Color Palette Generator + maintainer: Tomas Okal + description: Color palettes from famous artists and paintings. + date_publication: '2020-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtist + url_git: '' +rtk: + version: 0.2.6.1 + title: Rarefaction Tool Kit + maintainer: Paul Saary + description: Rarefy data, calculate diversity and plot the results. + date_publication: '2020-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtk + url_git: '' +rtkore: + version: 1.6.12 + title: '''STK++'' Core Library Integration to ''R'' using ''Rcpp''' + maintainer: Serge Iovleff + description: |- + 'STK++' is a collection of C++ classes + for statistics, clustering, linear algebra, arrays (with an 'Eigen'-like API), + regression, dimension reduction, etc. The integration of the library to 'R' is + using 'Rcpp'. The 'rtkore' package includes the header files from the 'STK++' + core library. All files contain only template classes and/or inline functions. + 'STK++' is licensed under the GNU LGPL version 2 or later. 'rtkore' (the 'stkpp' + integration into 'R') is licensed under the GNU GPL version 2 or later. See file + LICENSE.note for details. + date_publication: '2024-06-02' + bug_reports: https://sourceforge.net/projects/stkpp/ + url: http://www.stkpp.org + url_cran: https://CRAN.R-project.org/package=rtkore + url_git: '' +RTL: + version: 1.3.7 + title: Risk Tool Library - Trading, Risk, Analytics for Commodities + maintainer: Philippe Cote + description: |- + A toolkit for Commodities 'analytics', risk management and + trading professionals. Includes functions for API calls to + , , + and . + date_publication: '2025-02-26' + bug_reports: https://github.com/risktoollib/RTL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RTL + url_git: https://github.com/risktoollib/RTL +RTLknitr: + version: 1.0.0 + title: Right to Left Dynamic Documents Using 'knitr' + maintainer: Foad Esmaeili + description: 'Provide seamless support for right-to-left (RTL) languages, such as + Persian and Arabic, in R Markdown documents and ''LaTeX'' output. It includes + functions and hooks that enable easy integration of RTL language content, allowing + users to create documents that adhere to RTL writing conventions. For in-depth + insights into dynamic documents and the ''knitr'' package, consider referring + to Xie, Y (2014) .' + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTLknitr + url_git: https://github.com/FoadEsmaeili5/RTLknitr +rtlr: + version: 0.1.0 + title: Print Right-to-Left Languages Correctly + maintainer: Matan Hakim + description: |- + Convenience functions to make some common tasks with right-to-left string + printing easier, more convenient and with no need to remember long Unicode + characters. Specifically helpful for right-to-left languages such as Arabic, + Persian and Hebrew. + date_publication: '2023-04-04' + bug_reports: https://github.com/matanhakim/rtlr/issues + url: https://matanhakim.github.io/rtlr/ + url_cran: https://CRAN.R-project.org/package=rtlr + url_git: https://github.com/matanhakim/rtlr +rTLsDeep: + version: 0.0.5 + title: Post-Hurricane Damage Severity Classification from TLS and AI + maintainer: Caio Hamamura + description: Terrestrial laser scanning (TLS) data processing and post-hurricane + damage severity classification at the individual tree level using deep Learning. + Further details were published in Klauberg et al. (2023) . + date_publication: '2023-03-31' + bug_reports: https://github.com/carlos-alberto-silva/rTLsDeep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rTLsDeep + url_git: https://github.com/carlos-alberto-silva/rTLsDeep +RTMB: + version: '1.7' + title: '''R'' Bindings for ''TMB''' + maintainer: Kasper Kristensen + description: Native 'R' interface to 'TMB' (Template Model Builder) so models can + be written entirely in 'R' rather than 'C++'. Automatic differentiation, to any + order, is available for a rich subset of 'R' features, including linear algebra + for dense and sparse matrices, complex arithmetic, Fast Fourier Transform, probability + distributions and special functions. 'RTMB' provides easy access to model fitting + and validation following the principles of Kristensen, K., Nielsen, A., Berg, + C. W., Skaug, H., & Bell, B. M. (2016) and Thygesen, + U.H., Albertsen, C.M., Berg, C.W. et al. (2017) . + date_publication: '2025-01-10' + bug_reports: https://github.com/kaskr/RTMB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RTMB + url_git: https://github.com/kaskr/RTMB +rtmpt: + version: 2.0-2 + title: Fitting (Exponential/Diffusion) RT-MPT Models + maintainer: Raphael Hartmann + description: "Fit (exponential or diffusion) response-time extended multinomial + processing tree (RT-MPT) models\nby Klauer and\tKellen (2018) + and Klauer, Hartmann, and Meyer-Grant (submitted).\nThe RT-MPT class not only + incorporate\tfrequencies like traditional multinomial processing tree (MPT) models,\nbut + also latencies. This enables it\tto estimate process completion times and encoding + plus motor execution times\nnext to the process probabilities\tof traditional + MPTs. 'rtmpt' is a hierarchical Bayesian framework and posterior\nsamples are + sampled using a Metropolis-within-Gibbs sampler (for exponential RT-MPTs) or Hamiltonian-within-Gibbs\nsampler + (for diffusion RT-MPTs)." + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtmpt + url_git: '' +rtms: + version: 0.2.0 + title: R Toolkit for Mass Spectrometry + maintainer: Nathaniel Twarog + description: |- + Quickly imports, processes, analyzes, and visualizes mass-spectrometric + data. Includes functions for easily extracting specific data and measurements + from large (multi-gigabyte) raw Bruker data files, as well as a set of S3 object + classes for manipulating and measuring mass spectrometric peaks and plotting + peaks and spectra using the 'ggplot2' package. + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtms + url_git: '' +Rtnmin: + version: 2016-7.7 + title: Truncated Newton Function Minimization with Bounds Constraints + maintainer: John C Nash + description: |- + Truncated Newton function minimization with bounds constraints + based on the 'Matlab'/'Octave' codes of Stephen Nash. + date_publication: '2016-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rtnmin + url_git: '' +rtodoist: + version: 0.1.0 + title: Create and Manage Todolist using 'Todoist.com' API + maintainer: Cervan Girard + description: |- + Allows you to interact with the API of the "Todoist" platform. + 'Todoist' provides an online task manager service for teams. + date_publication: '2020-05-14' + bug_reports: https://github.com/ThinkR-open/rtodoist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtodoist + url_git: https://github.com/ThinkR-open/rtodoist +rtoot: + version: 0.3.5 + title: Collecting and Analyzing Mastodon Data + maintainer: David Schoch + description: 'An implementation of calls designed to collect and organize Mastodon + data via its Application Program Interfaces (API), which can be found at the following + URL: .' + date_publication: '2024-10-30' + bug_reports: https://github.com/gesistsa/rtoot/issues + url: https://gesistsa.github.io/rtoot/ + url_cran: https://CRAN.R-project.org/package=rtoot + url_git: https://github.com/gesistsa/rtoot/ +rtop: + version: 0.6-9 + title: Interpolation of Data with Variable Spatial Support + maintainer: Jon Olav Skøien + description: Data with irregular spatial support, such as runoff related data or + data from administrative units, can with 'rtop' be interpolated to locations without + observations with the top-kriging method. A description of the package is given + by Skøien et al (2014) . + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtop + url_git: '' +rTorch: + version: 0.4.2 + title: R Bindings to 'PyTorch' + maintainer: Alfonso R. Reyes + description: |- + 'R' implementation and interface of the Machine Learning platform + 'PyTorch' developed in 'Python'. It requires a 'conda' + environment with 'torch' and 'torchvision' Python packages to provide + 'PyTorch' functions, methods and classes. The key object in 'PyTorch' is the + tensor which is in essence a multidimensional array. These tensors are fairly + flexible in performing calculations in CPUs as well as 'GPUs' to accelerate + tensor operations. + date_publication: '2020-10-12' + bug_reports: https://github.com/f0nzie/rTorch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rTorch + url_git: https://github.com/f0nzie/rTorch +rTPC: + version: 1.0.4 + title: Fitting and Analysing Thermal Performance Curves + maintainer: Daniel Padfield + description: Helps to fit thermal performance curves (TPCs). 'rTPC' contains 26 + model formulations previously used to fit TPCs and has helper functions to set + sensible start parameters, upper and lower parameter limits and estimate parameters + useful in downstream analyses, such as cardinal temperatures, maximum rate and + optimum temperature. See Padfield et al. (2021) . + date_publication: '2023-08-17' + bug_reports: https://github.com/padpadpadpad/rTPC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rTPC + url_git: https://github.com/padpadpadpad/rTPC +rtpcr: + version: 2.0.1 + title: qPCR Data Analysis + maintainer: Ghader Mirzaghaderi + description: Various methods are employed for statistical analysis and graphical + presentation of real-time PCR (quantitative PCR or qPCR) data. 'rtpcr' handles + amplification efficiency calculation, statistical analysis and graphical representation + of real-time PCR data based on up to two reference genes. By accounting for amplification + efficiency values, 'rtpcr' was developed using a general calculation method described + by Ganger et al. (2017) and Taylor et al. (2019) + , covering both the Livak and Pfaffl methods. + Based on the experimental conditions, the functions of the 'rtpcr' package use + t-test (for experiments with a two-level factor), analysis of variance (ANOVA), + analysis of covariance (ANCOVA) or analysis of repeated measure data to calculate + the fold change (FC, Delta Delta Ct method) or relative expression (RE, Delta + Ct method). The functions further provide standard errors and confidence intervals + for means, apply statistical mean comparisons and present significance. To facilitate + function application, different data sets were used as examples and the outputs + were explained. ‘rtpcr’ package also provides bar plots using various controlling + arguments. The 'rtpcr' package is user-friendly and easy to work with and provides + an applicable resource for analyzing real-time PCR data. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtpcr + url_git: https://github.com/mirzaghaderi/rtpcr +Rtrack: + version: 2.0.3 + title: Spatial Navigation Strategy Analysis + maintainer: Rupert Overall + description: |- + A toolkit for the analysis of paths from spatial tracking experiments and calculation of goal-finding strategies. + This package is centered on an approach using machine learning for path classification. + date_publication: '2023-12-11' + bug_reports: https://github.com/rupertoverall/Rtrack/issues + url: https://rupertoverall.net/Rtrack/ + url_cran: https://CRAN.R-project.org/package=Rtrack + url_git: https://github.com/rupertoverall/Rtrack +RTransferEntropy: + version: 0.2.21 + title: |- + Measuring Information Flow Between Time Series with Shannon and + Renyi Transfer Entropy + maintainer: David Zimmermann + description: Measuring information flow between time series with Shannon and Rényi + transfer entropy. See also Dimpfl and Peter (2013) + and Dimpfl and Peter (2014) for theory and + applications to financial time series. Additional references can be found in the + theory part of the vignette. + date_publication: '2023-02-01' + bug_reports: https://github.com/BZPaper/RTransferEntropy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RTransferEntropy + url_git: https://github.com/BZPaper/RTransferEntropy +rtrek: + version: 0.5.1 + title: Data Analysis Relating to Star Trek + maintainer: Matthew Leonawicz + description: |- + Provides datasets related to the Star Trek fictional universe and functions for working with the data. + The package also provides access to real world datasets based on the televised series and other related licensed media productions. + It interfaces with the Star Trek API (STAPI) (), + Memory Alpha (), and Memory Beta () + to retrieve data, metadata and other information relating to Star Trek. + It also contains several local datasets covering a variety of topics. + The package also provides functions for working with data from other Star Trek-related + R data packages containing larger datasets not stored in 'rtrek'. + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/rtrek/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtrek + url_git: https://github.com/leonawicz/rtrek +rtrend: + version: 0.1.5 + title: Trend Estimating Tools + maintainer: Dongdong Kong + description: |- + The traditional linear regression trend, Modified Mann-Kendall (MK) + non-parameter trend and bootstrap trend are included in this package. Linear + regression trend is rewritten by '.lm.fit'. MK trend is rewritten by 'Rcpp'. + Finally, those functions are about 10 times faster than previous version + in R. + Reference: + Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for + autocorrelated data. Journal of hydrology, 204(1-4), 182-196. + . + date_publication: '2024-01-11' + bug_reports: https://github.com/rpkgs/rtrend/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtrend + url_git: https://github.com/rpkgs/rtrend +rtrends: + version: 0.1.0 + title: Analyze Download Logs from the CRAN RStudio Mirror + maintainer: Avi Blinder + description: |- + Analyze download logs from the CRAN RStudio mirror + (). + This CRAN mirror is the default one used in RStudio. + The available data is the result of parsed and anonymised raw log data from + that CRAN mirror. + date_publication: '2016-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rtrends + url_git: '' +RTriangle: + version: 1.6-0.14 + title: Triangle - A 2D Quality Mesh Generator and Delaunay Triangulator + maintainer: David C. Sterratt + description: |- + This is a port of Jonathan Shewchuk's Triangle library to + R. From his description: "Triangle generates exact Delaunay + triangulations, constrained Delaunay triangulations, conforming + Delaunay triangulations, Voronoi diagrams, and high-quality + triangular meshes. The latter can be generated with no small or + large angles, and are thus suitable for finite element analysis." + date_publication: '2024-09-05' + bug_reports: https://github.com/davidcsterratt/RTriangle/issues + url: http://www.cs.cmu.edu/~quake/triangle.html + url_cran: https://CRAN.R-project.org/package=RTriangle + url_git: https://github.com/davidcsterratt/RTriangle +rtrim: + version: 2.3.0 + title: Trends and Indices for Monitoring Data + maintainer: Patrick Bogaart + description: |- + The TRIM model is widely used for estimating growth and decline of + animal populations based on (possibly sparsely available) count data. The + current package is a reimplementation of the original TRIM software developed + at Statistics Netherlands by Jeroen Pannekoek. See + + for more information about TRIM. + date_publication: '2024-06-21' + bug_reports: https://github.com/SNStatComp/rtrim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtrim + url_git: https://github.com/SNStatComp/rtrim +rTRIPLEXCWFlux: + version: 0.2.0 + title: Carbon-Water Coupled Model + maintainer: Shulan Sun + description: A carbon-water coupled model (TRIPLEX-CW-Flux) is based on two well-established + models, TRIPLEX-Flux model and Penman–Monteith model, integrates soil water and + water vapor pressure deficits into the stomata conductance submodule to estimate + net ecosystem production and evapotranspiration in forest ecosystems.. + date_publication: '2022-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rTRIPLEXCWFlux + url_git: https://github.com/ShulanSun/rTRIPLEX_CW_Flux +rTRNG: + version: 4.23.1-2 + title: Advanced and Parallel Random Number Generation via 'TRNG' + maintainer: Riccardo Porreca + description: |- + Embeds sources and headers from Tina's Random + Number Generator ('TRNG') C++ library. Exposes some functionality for + easier access, testing and benchmarking into R. Provides examples of + how to use parallel RNG with 'RcppParallel'. The methods and + techniques behind 'TRNG' are illustrated in the package vignettes and + examples. Full documentation is available in Bauke (2021) + . + date_publication: '2022-03-14' + bug_reports: https://github.com/miraisolutions/rTRNG/issues + url: https://mirai-solutions.ch + url_cran: https://CRAN.R-project.org/package=rTRNG + url_git: https://github.com/miraisolutions/rTRNG#readme +Rtropical: + version: 1.2.1 + title: |- + Data Analysis Tools over Space of Phylogenetic Trees Using + Tropical Geometry + maintainer: Houjie Wang + description: 'Process phylogenetic trees with tropical support vector machine and + principal component analysis defined with tropical geometry. Details about tropical + support vector machine are available in : Tang, X., Wang, H. & Yoshida, R. (2020) + . Details about tropical principle component analysis are available + in : Page, R., Yoshida, R. & Zhang L. (2020) + and Yoshida, R., Zhang, L. & Zhang, X. (2019) .' + date_publication: '2021-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rtropical + url_git: https://github.com/HoujieWang/Rtropical +rtry: + version: 1.1.0 + title: Preprocessing Plant Trait Data + maintainer: Olee Hoi Ying Lam + description: |- + Designed to support the application of plant trait data providing easy applicable functions + for the basic steps of data preprocessing, e.g. data import, data exploration, selection of columns + and rows, excluding trait data according to different attributes, geocoding, long- to wide-table + transformation, and data export. 'rtry' was initially developed as part of the TRY R project to + preprocess trait data received via the TRY database. + date_publication: '2023-08-09' + bug_reports: https://github.com/MPI-BGC-Functional-Biogeography/rtry/issues + url: https://www.try-db.org/TryWeb/Home.php + url_cran: https://CRAN.R-project.org/package=rtry + url_git: https://github.com/MPI-BGC-Functional-Biogeography/rtry +rts: + version: 1.1-14 + title: Raster Time Series Analysis + maintainer: Babak Naimi + description: This framework aims to provide classes and methods for manipulating + and processing of raster time series data (e.g. a time series of satellite images). + date_publication: '2023-10-01' + bug_reports: '' + url: https://r-gis.net/ + url_cran: https://CRAN.R-project.org/package=rts + url_git: '' +rts2: + version: 0.7.7 + title: Real-Time Disease Surveillance + maintainer: Sam Watson + description: |- + Supports modelling real-time case data to facilitate the real-time + surveillance of infectious diseases and other point phenomena. The package provides automated computational grid generation over + an area of interest with methods to map covariates between geographies, model fitting including spatially aggregated case counts, + and predictions and visualisation. Both Bayesian and maximum likelihood methods are provided. Log-Gaussian Cox Processes are described by + Diggle et al. (2013) and we provide both the low-rank approximation for Gaussian processes + described by Solin and Särkkä (2020) and Riutort-Mayol et al (2023) and the + nearest neighbour Gaussian process described by Datta et al (2016) . 'cmdstanr' can be downloaded at . + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rts2 + url_git: '' +RTSA: + version: 0.2.2 + title: |- + 'Trial Sequential Analysis' for Error Control and Inference in + Sequential Meta-Analyses + maintainer: Anne Lyngholm Soerensen + description: |- + Frequentist sequential meta-analysis based on + 'Trial Sequential Analysis' (TSA) in programmed in Java by the Copenhagen + Trial Unit (CTU). The primary function is the calculation of group + sequential designs for meta-analysis to be used for planning and analysis of + both prospective and retrospective sequential meta-analyses to preserve + type-I-error control under sequential testing. 'RTSA' includes tools for + sample size and trial size calculation for meta-analysis and core + meta-analyses methods such as fixed-effect and random-effects models and + forest plots. TSA is described in Wetterslev et. al (2008) + . The methods for deriving the + group sequential designs are based on Jennison and Turnbull (1999, + ISBN:9780849303166). + date_publication: '2023-11-23' + bug_reports: https://github.com/AnneLyng/RTSA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RTSA + url_git: https://github.com/AnneLyng/RTSA +rtsdata: + version: 0.1.4 + title: R Time Series Intelligent Data Storage + maintainer: Irina Kapler + description: |- + A tool that allows to download and save historical time series data + for future use offline. The intelligent updating functionality will only download + the new available information; thus, saving you time and Internet bandwidth. + It will only re-download the full data-set if any inconsistencies are detected. + This package supports following data provides: 'Yahoo' (finance.yahoo.com), + 'FRED' (fred.stlouisfed.org), 'Quandl' (data.nasdaq.com), + 'AlphaVantage' (www.alphavantage.co), 'Tiingo' (www.tiingo.com). + date_publication: '2023-09-25' + bug_reports: https://bitbucket.org/rtsvizteam/rtsdata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtsdata + url_git: https://bitbucket.org/rtsvizteam/rtsdata +RtsEva: + version: 1.0.0 + title: Performs the Transformed-Stationary Extreme Values Analysis + maintainer: Alois Tilloy + description: |- + Adaptation of the 'Matlab' 'tsEVA' toolbox developed by Lorenzo Mentaschi + available here: + . It contains an implementation of the + Transformed-Stationary (TS) methodology for non-stationary extreme + value Analysis (EVA) as described in Mentaschi et al. (2016) . + In synthesis this approach consists in: + (i) transforming a non-stationary time series into a + stationary one to which the stationary extreme value theory can be applied; and + (ii) reverse-transforming the result into a non-stationary extreme + value distribution. + 'RtsEva' offers several options for trend estimation (mean, extremes, seasonal) + and contains multiple plotting functions displaying different aspects + of the non-stationarity of extremes. + date_publication: '2024-06-24' + bug_reports: https://github.com/Alowis/RtsEva/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RtsEva + url_git: https://github.com/r-lib/devtools +Rtsne: + version: '0.17' + title: |- + T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut + Implementation + maintainer: Jesse Krijthe + description: |- + An R wrapper around the fast T-distributed Stochastic + Neighbor Embedding implementation by Van der Maaten (see for more information on the original implementation). + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rtsne + url_git: https://github.com/jkrijthe/Rtsne +rtson: + version: '1.3' + title: Typed JSON + maintainer: Alexandre Maurel + description: |- + TSON, short for Typed JSON, is a binary-encoded serialization of + JSON like document that support JavaScript typed data (https://github.com/tercen/TSON). + date_publication: '2016-08-26' + bug_reports: https://github.com/tercen/TSON/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtson + url_git: https://github.com/tercen/TSON +rtsplot: + version: 0.1.5 + title: Time Series Plot + maintainer: Irina Kapler + description: |- + A fast and elegant time series visualization package. In addition to the + standard R plot types, this package supports candle sticks, open-high-low-close, and + volume plots. Useful for visualizing any time series data, e.g., stock prices and + technical indicators. + date_publication: '2023-09-24' + bug_reports: https://bitbucket.org/rtsvizteam/rtsplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rtsplot + url_git: https://bitbucket.org/rtsvizteam/rtsplot +Rttf2pt1: + version: 1.3.12 + title: '''ttf2pt1'' Program' + maintainer: Winston Chang + description: |- + Contains the program 'ttf2pt1', for use with the + 'extrafont' package. This product includes software developed by the 'TTF2PT1' + Project and its contributors. + date_publication: '2023-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rttf2pt1 + url_git: https://github.com/wch/Rttf2pt1 +RTTWebClient: + version: 0.1.3 + title: Web Client to 'TickTrader' + maintainer: Yury Maisiayonak + description: R Web Client to 'TickTrader' platform. Provides you access to 'TickTrader' + platform through Web API . + date_publication: '2022-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RTTWebClient + url_git: '' +Rtumblr: + version: 0.1.0 + title: Collecting and Analyzing 'Tumblr' Data + maintainer: David Schoch + description: 'An implementation of calls designed to collect ''Tumblr'' data via + its Application Program Interfaces (API), which can be found at the following + URL: .' + date_publication: '2023-04-05' + bug_reports: https://github.com/schochastics/Rtumblr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rtumblr + url_git: https://github.com/schochastics/Rtumblr/ +Rtwalk: + version: 1.8.0 + title: The R Implementation of the 't-walk' MCMC Algorithm + maintainer: J Andres Christen + description: |- + The 't-walk' is a general-purpose MCMC sampler for + arbitrary continuous distributions that requires no tuning. + date_publication: '2015-09-18' + bug_reports: '' + url: http://www.cimat.mx/~jac/twalk/ + url_cran: https://CRAN.R-project.org/package=Rtwalk + url_git: '' +rtweet: + version: 2.0.0 + title: Collecting Twitter Data + maintainer: Lluís Revilla Sancho + description: |- + An implementation of calls designed to collect and organize + Twitter data via Twitter's REST and stream Application Program + Interfaces (API), which can be found at the following URL: + . + date_publication: '2024-02-24' + bug_reports: https://github.com/ropensci/rtweet/issues + url: https://docs.ropensci.org/rtweet/ + url_cran: https://CRAN.R-project.org/package=rtweet + url_git: https://github.com/ropensci/rtweet/ +rTwig: + version: 1.3.0 + title: Realistic Quantitative Structure Models + maintainer: Aidan Morales + description: Real Twig is a method to correct branch overestimation in quantitative + structure models. Overestimated cylinders are correctly tapered using measured + twig diameters of corresponding tree species. Supported quantitative structure + modeling software includes 'TreeQSM', 'SimpleForest', 'Treegraph', and 'aRchi'. + Also included is a novel database of twig diameters and tools for fractal analysis + of point clouds. + date_publication: '2024-11-21' + bug_reports: https://github.com/aidanmorales/rTwig/issues + url: https://aidanmorales.github.io/rTwig/ + url_cran: https://CRAN.R-project.org/package=rTwig + url_git: https://github.com/aidanmorales/rTwig +Rtwobitlib: + version: 0.3.6 + title: '''2bit'' ''C'' Library' + maintainer: Hervé Pagès + description: |- + A trimmed down copy of the "kent-core source tree" + turned into a 'C' library for manipulation of '.2bit' files. + See + for a quick overview of the '2bit' format. The "kent-core source tree" + can be found here: . + Only the '.c' and '.h' files from the source tree that are related + to manipulation of '.2bit' files were kept. Note that the package + is primarily useful to developers of other R packages who wish + to use the '2bit' 'C' library in their own 'C'/'C++' code. + date_publication: '2024-04-24' + bug_reports: https://github.com/hpages/Rtwobitlib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rtwobitlib + url_git: https://github.com/hpages/Rtwobitlib +rtype: + version: 0.1-1 + title: A strong type system for R + maintainer: Kun Ren + description: |- + A strong type system for R which supports + symbol declaration and assignment with type checking + and condition checking. + date_publication: '2014-08-15' + bug_reports: https://github.com/renkun-ken/rtype/issues + url: http://renkun.me/rtype + url_cran: https://CRAN.R-project.org/package=rtype + url_git: https://github.com/renkun-ken/rtype +rtypeform: + version: 2.1.1 + title: Interface to 'typeform' Results + maintainer: Colin Gillespie + description: |- + An R interface to the 'typeform' + application program interface. Also provides functions for + downloading your results. + date_publication: '2025-01-29' + bug_reports: https://github.com/csgillespie/rtypeform/issues + url: http://csgillespie.github.io/rtypeform/ + url_cran: https://CRAN.R-project.org/package=rtypeform + url_git: https://github.com/csgillespie/rtypeform +rubias: + version: 0.3.4 + title: |- + Bayesian Inference from the Conditional Genetic Stock + Identification Model + maintainer: Eric C. Anderson + description: |- + Implements Bayesian inference for the conditional genetic + stock identification model. It allows inference of mixed fisheries and also + simulation of mixtures to predict accuracy. A full description of the underlying + methods is available in a recently published article in the + Canadian Journal of Fisheries and Aquatic Sciences: . + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rubias + url_git: '' +rucm: + version: '0.6' + title: Implementation of Unobserved Components Model (UCM) + maintainer: Kaushik Roy Chowdhury + description: |- + Unobserved Components Models (introduced in Harvey, A. (1989), + Forecasting, structural time series models and the Kalman filter, Cambridge + New York: Cambridge University Press) decomposes a time series into + components such as trend, seasonal, cycle, and the regression effects due + to predictor series which captures the salient features of the series to + predict its behavior. + date_publication: '2015-11-06' + bug_reports: https://github.com/kaushikrch/rucm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rucm + url_git: '' +rucrdtw: + version: 0.1.6 + title: R Bindings for the UCR Suite + maintainer: Philipp Boersch-Supan + description: |- + R bindings for functions from the UCR Suite by Rakthanmanon et al. (2012) , which enables ultrafast subsequence + search for a best match under Dynamic Time Warping and Euclidean Distance. + date_publication: '2023-12-11' + bug_reports: https://github.com/pboesu/rucrdtw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rucrdtw + url_git: https://github.com/pboesu/rucrdtw +rugarch: + version: 1.5-3 + title: Univariate GARCH Models + maintainer: Alexios Galanos + description: ARFIMA, in-mean, external regressors and various GARCH flavors, with + methods for fit, forecast, simulation, inference and plotting. + date_publication: '2024-09-22' + bug_reports: '' + url: http://www.unstarched.net + url_cran: https://CRAN.R-project.org/package=rugarch + url_git: https://github.com/alexiosg/rugarch +ruijter: + version: 0.1.3 + title: Technical Data Sets by Ruijter et al. (2013) + maintainer: Ramiro Magno + description: |- + The real-time quantitative polymerase chain reaction + (qPCR) technical data sets by Ruijter et al. (2013) + : (i) the four-point 10-fold dilution + series; (ii) 380 replicates; and (iii) the competimer data set. These + three data sets can be used to benchmark qPCR methods. Original data set + is available at + . + This package fixes incorrect annotations in the original data sets. + date_publication: '2024-04-22' + bug_reports: https://github.com/ramiromagno/ruijter/issues + url: https://rmagno.eu/ruijter/ + url_cran: https://CRAN.R-project.org/package=ruijter + url_git: https://github.com/ramiromagno/ruijter +ruimtehol: + version: 0.3.2 + title: Learn Text 'Embeddings' with 'Starspace' + maintainer: Jan Wijffels + description: |- + Wraps the 'StarSpace' library + allowing users to calculate word, sentence, article, document, webpage, link and entity 'embeddings'. + By using the 'embeddings', you can perform text based multi-label classification, + find similarities between texts and categories, do collaborative-filtering based recommendation + as well as content-based recommendation, find out relations between entities, calculate + graph 'embeddings' as well as perform semi-supervised learning and multi-task learning on plain text. + The techniques are explained in detail in the paper: 'StarSpace: Embed All The Things!' by Wu et al. (2017), available at . + date_publication: '2024-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ruimtehol + url_git: https://github.com/bnosac/ruimtehol +ruin: + version: 0.1.1 + title: Simulation of Various Risk Processes + maintainer: Iegor Rudnytskyi + description: |- + A (not yet exhaustive) collection of common models of risk + processes in actuarial science, represented as formal S4 classes. Each class + (risk model) has a simulator of its path, and a plotting function. Further, + a Monte-Carlo estimator of a ruin probability for a finite time is + implemented, using a parallel computation. Currently, the package extends + two classical risk models Cramer-Lundberg and Sparre Andersen models by + including capital injections, that are positive jumps (see Breuer L. and + Badescu A.L. (2014) ). The intent of the + package is to provide a user-friendly interface for ruin processes' + simulators, as well as a solid and extensible structure for future + extensions. + date_publication: '2018-07-30' + bug_reports: http://github.com/irudnyts/ruin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ruin + url_git: http://github.com/irudnyts/ruin +ruler: + version: 0.3.0 + title: Tidy Data Validation Reports + maintainer: Evgeni Chasnovski + description: |- + Tools for creating data validation pipelines and + tidy reports. This package offers a framework for exploring and + validating data frame like objects using 'dplyr' grammar of data + manipulation. + date_publication: '2023-03-28' + bug_reports: https://github.com/echasnovski/ruler/issues + url: https://echasnovski.github.io/ruler/ + url_cran: https://CRAN.R-project.org/package=ruler + url_git: https://github.com/echasnovski/ruler +rules: + version: 1.0.2 + title: Model Wrappers for Rule-Based Models + maintainer: Emil Hvitfeldt + description: |- + Bindings for additional models for use with the 'parsnip' + package. Models include prediction rule ensembles (Friedman and + Popescu, 2008) , C5.0 rules (Quinlan, 1992 + ISBN: 1558602380), and Cubist (Kuhn and Johnson, 2013) + . + date_publication: '2023-03-08' + bug_reports: https://github.com/tidymodels/rules/issues + url: https://rules.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=rules + url_git: https://github.com/tidymodels/rules +RulesTools: + version: 0.1.1 + title: Preparing, Analyzing, and Visualizing Association Rules + maintainer: Nikolett Toth + description: Streamlines data preprocessing, analysis, and visualization for association + rule mining. Designed to work with the 'arules' package, features include discretizing + data frames, generating rule set intersections, and visualizing rules with heatmaps + and Euler diagrams. 'RulesTools' also includes a dataset on Brook trout detection + from Nolan et al. (2022) . + date_publication: '2025-01-28' + bug_reports: https://github.com/nikolett0203/RulesTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RulesTools + url_git: https://github.com/nikolett0203/RulesTools +rUM: + version: 2.0.0 + title: R Templates from the University of Miami + maintainer: Raymond Balise + description: |- + This holds some r markdown and quarto templates and a template to + create a research project in "R Studio". + date_publication: '2024-06-02' + bug_reports: https://github.com/RaymondBalise/rUM/issues + url: https://raymondbalise.github.io/rUM/ + url_cran: https://CRAN.R-project.org/package=rUM + url_git: https://github.com/RaymondBalise/rUM +rumidas: + version: 0.1.2 + title: |- + Univariate GARCH-MIDAS, Double-Asymmetric GARCH-MIDAS and + MEM-MIDAS + maintainer: Vincenzo Candila + description: Adds the MIxing-Data Sampling (MIDAS, Ghysels et al. (2007) ) + components to a variety of GARCH and MEM (Engle (2002) , + Engle and Gallo (2006) , and Amendola et al. + (2024) ) models, with the aim of predicting the + volatility with additional low-frequency (that is, MIDAS) terms. The estimation + takes place through simple functions, which provide in-sample and (if present) + and out-of-sample evaluations. 'rumidas' also offers a summary tool, which synthesizes + the main information of the estimated model. There is also the possibility of + generating one-step-ahead and multi-step-ahead forecasts. + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rumidas + url_git: '' +ruminate: + version: 0.3.1 + title: A Pharmacometrics Data Transformation and Analysis Tool + maintainer: John Harrold + description: Exploration of pharmacometrics data involves both general tools (transformation + and plotting) and specific techniques (non-compartmental analysis). This kind + of exploration is generally accomplished by utilizing different packages. The + purpose of 'ruminate' is to create a 'shiny' interface to make these tools more + broadly available while creating reproducible results. + date_publication: '2025-01-10' + bug_reports: https://github.com/john-harrold/ruminate/issues + url: https://ruminate.ubiquity.tools/ + url_cran: https://CRAN.R-project.org/package=ruminate + url_git: '' +runcharter: + version: 0.2.0 + title: |- + Automatically Plot, Analyse and Revises Limits of Multiple Run + Charts + maintainer: John MacKintosh + description: |- + Plots multiple run charts, finds successive signals of + improvement, and revises medians when each signal occurs. Finds runs + above, below, or on both sides of the median, and returns a plot and + a data.table summarising original medians and any revisions, for all + groups within the supplied data. + date_publication: '2021-11-09' + bug_reports: https://github.com/johnmackintosh/runcharter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=runcharter + url_git: https://github.com/johnmackintosh/runcharter +runDRT: + version: 0.1.0 + title: Run Doubly Ranked Tests + maintainer: Mark J. Meyer + description: |- + Doubly ranked tests are nonparametric tests for grouped functional and multivariate data. + The testing procedure first ranks a matrix (or three dimensional array) of data by column (if a matrix) or by cell (across the third dimension if an array). + By default, it calculates a sufficient statistic for the subject's order within the sample using the observed ranks, taken over the columns or cells. + Depending on the number of groups, G, the summarized ranks are then analyzed using either a Wilcoxon Rank Sum test (G = 2) or a Kruskal-Wallis (G greater than 2). + date_publication: '2024-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=runDRT + url_git: '' +runes: + version: 0.1.0 + title: Convert Strings to Elder Futhark Runes + maintainer: Bryan Jenks + description: Convert a string of text characters to Elder Futhark Runes . + date_publication: '2020-05-29' + bug_reports: https://github.com/tallguyjenks/runes + url: '' + url_cran: https://CRAN.R-project.org/package=runes + url_git: '' +runExamplesWrapper: + version: '1.0' + title: Wrapper for 'run_examples()' + maintainer: Barry Zeeberg + description: Captures errors encountered when running 'run_examples()', and processes + and archives them. The function 'run_examples()' within the 'devtools' package + allows batch execution of all of the examples within a given package. This is + much more convenient than testing each example manually. However, a major inconvenience + is that if an error is encountered, the program stops and does not complete testing + the remaining examples. Also, there is not a systematic record of the results, + namely which package functions had no examples, which had examples that failed, + and which had examples that succeeded. The current package provides the missing + functionality. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=runExamplesWrapper + url_git: '' +runexp: + version: 0.2.1 + title: Softball Run Expectancy using Markov Chains and Simulation + maintainer: Annie Sauer + description: |- + Implements two methods of estimating runs scored in a softball + scenario: (1) theoretical expectation using discrete Markov chains and (2) empirical + distribution using multinomial random simulation. Scores are based on player-specific input + probabilities (out, single, double, triple, walk, and homerun). Optional inputs include probability + of attempting a steal, probability of succeeding in an attempted steal, and an indicator of whether + a player is "fast" (e.g. the player could stretch home). These probabilities may be + calculated from common player statistics that are publicly available on team's webpages. + Scores are evaluated based on a nine-player lineup and may be used to compare lineups, + evaluate base scenarios, and compare the offensive potential of individual players. + Manuscript forthcoming. See Bukiet & Harold (1997) for + implementation of discrete Markov chains. + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=runexp + url_git: '' +RUnit: + version: 0.4.33 + title: R Unit Test Framework + maintainer: Roman Zenka + description: |- + R functions implementing a standard Unit Testing + framework, with additional code inspection and report + generation tools. + date_publication: '2024-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RUnit + url_git: '' +runjags: + version: 2.2.2-4 + title: |- + Interface Utilities, Model Templates, Parallel Computing Methods + and Additional Distributions for MCMC Models in JAGS + maintainer: Matthew Denwood + description: |- + User-friendly interface utilities for MCMC models via + Just Another Gibbs Sampler (JAGS), facilitating the use of parallel + (or distributed) processors for multiple chains, automated control + of convergence and sample length diagnostics, and evaluation of the + performance of a model using drop-k validation or against simulated + data. Template model specifications can be generated using a standard + lme4-style formula interface to assist users less familiar with the + BUGS syntax. A JAGS extension module provides additional distributions + including the Pareto family of distributions, the DuMouchel prior and + the half-Cauchy prior. + date_publication: '2024-03-10' + bug_reports: https://github.com/ku-awdc/runjags/issues + url: '' + url_cran: https://CRAN.R-project.org/package=runjags + url_git: https://github.com/ku-awdc/runjags +runMCMCbtadjust: + version: 1.1.2 + title: |- + Runs Monte Carlo Markov Chain - With Either 'JAGS', 'nimble' or + 'greta' - While Adjusting Burn-in and Thinning Parameters + maintainer: Frédéric Gosselin + description: |- + The function runMCMC_btadjust() returns a mcmc.list object which is the output of a + Markov Chain Monte Carlo obtained - from either 'JAGS', 'nimble' or 'greta' - + after adjusting burn-in and thinning parameters to meet pre-specified criteria + in terms of convergence & effective sample size. Used with 'nimble', runMCMC_btadjust() + allows extra calculations (e.g. information criteria for model comparison and goodness-of-fit + p-values for model diagnosis). + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=runMCMCbtadjust + url_git: '' +runner: + version: 0.4.4 + title: Running Operations for Vectors + maintainer: Dawid Kałędkowski + description: |- + Lightweight library for rolling windows operations. Package enables + full control over the window length, window lag and a time indices. With a runner + one can apply any R function on a rolling windows. The package eases work with + equally and unequally spaced time series. + date_publication: '2024-03-03' + bug_reports: https://github.com/gogonzo/runner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=runner + url_git: '' +runonce: + version: 0.2.3 + title: Run Once and Save Result + maintainer: Florian Privé + description: |- + Package 'runonce' helps automating the saving of long-running code + to help running the same code multiple times. If you run some long-running + code once, it saves the result in a file on disk. Then, if the result + already exists, i.e. if the code has already been run and its output has + already been saved, it just reads the result from the stored file instead + of running the code again. + date_publication: '2021-10-02' + bug_reports: https://github.com/privefl/runonce/issues + url: '' + url_cran: https://CRAN.R-project.org/package=runonce + url_git: https://github.com/privefl/runonce +runstats: + version: 1.1.0 + title: Fast Computation of Running Statistics for Time Series + maintainer: Marta Karas + description: |- + Provides methods for fast computation of running sample + statistics for time series. These include: (1) mean, (2) + standard deviation, and (3) variance over a fixed-length window + of time-series, (4) correlation, (5) covariance, and (6) + Euclidean distance (L2 norm) between short-time pattern and + time-series. Implemented methods utilize Convolution Theorem to + compute convolutions via Fast Fourier Transform (FFT). + date_publication: '2019-11-14' + bug_reports: https://github.com/martakarass/runstats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=runstats + url_git: https://github.com/martakarass/runstats +Runuran: + version: '0.40' + title: R Interface to the 'UNU.RAN' Random Variate Generators + maintainer: Josef Leydold + description: |- + Interface to the 'UNU.RAN' library for Universal Non-Uniform RANdom variate generators. + Thus it allows to build non-uniform random number generators from quite arbitrary + distributions. In particular, it provides an algorithm for fast numerical inversion + for distribution with given density function. + In addition, the package contains densities, distribution functions and quantiles + from a couple of distributions. + date_publication: '2024-10-04' + bug_reports: '' + url: https://statmath.wu.ac.at/unuran/ + url_cran: https://CRAN.R-project.org/package=Runuran + url_git: https://github.com/unuran/Runuran/ +rush: + version: 0.1.2 + title: Rapid Parallel and Distributed Computing + maintainer: Marc Becker + description: |- + Parallel computing with a network of local and remote + workers. Fast exchange of results between the workers through a + 'Redis' database. Key features include task queues, local caching, and + sophisticated error handling. + date_publication: '2024-11-06' + bug_reports: https://github.com/mlr-org/rush/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rush + url_git: https://github.com/mlr-org/rush +rusk: + version: 0.1.1 + title: |- + Beautiful Graphical Representation of Multiplication Tables on a + Modular Circle + maintainer: Vincent Guyader + description: By placing on a circle 10 points numbered from 1 to 10, and connecting + them by a straight line to the point corresponding to its multiplication by 2. + (1 must be connected to 1 * 2 = 2, point 2 must be set to 2 * 2 = 4, point 3 to + 3 * 2 = 6 and so on). You will obtain an amazing geometric figure that complicates + and beautifies itself by varying the number of points and the multiplication table + you use. + date_publication: '2018-05-27' + bug_reports: https://github.com/ThinkR-open/rusk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rusk + url_git: https://github.com/ThinkR-open/rusk +rusquant: + version: 1.1.4 + title: Quantitative Trading Framework + maintainer: Vyacheslav Arbuzov + description: Collection of functions to retrieve financial data from various sources, + including brokerage and exchange platforms, financial websites, and data providers. + Includes functions to retrieve account information, portfolio information, and + place/cancel orders from different brokers. Additionally, allows users to download + historical data such as earnings, dividends, stock splits. + date_publication: '2024-09-16' + bug_reports: https://github.com/arbuzovv/rusquant/issues + url: https://rusquant.ru + url_cran: https://CRAN.R-project.org/package=rusquant + url_git: '' +rust: + version: 1.4.3 + title: Ratio-of-Uniforms Simulation with Transformation + maintainer: Paul J. Northrop + description: |- + Uses the generalized ratio-of-uniforms (RU) method to simulate + from univariate and (low-dimensional) multivariate continuous distributions. + The user specifies the log-density, up to an additive constant. The RU + algorithm is applied after relocation of mode of the density to zero, and + the user can choose a tuning parameter r. For details see Wakefield, Gelfand + and Smith (1991) , Efficient generation of random + variates via the ratio-of-uniforms method, Statistics and Computing (1991) + 1, 129-133. A Box-Cox variable transformation can be used to make the input + density suitable for the RU method and to improve efficiency. In the + multivariate case rotation of axes can also be used to improve efficiency. + From version 1.2.0 the 'Rcpp' package + can be used to improve efficiency. + date_publication: '2024-08-17' + bug_reports: https://github.com/paulnorthrop/rust/issues + url: https://paulnorthrop.github.io/rust/ + url_cran: https://CRAN.R-project.org/package=rust + url_git: https://github.com/paulnorthrop/rust +rutifier: + version: 1.0.4 + title: Chilean Rol Unico Tributario + maintainer: Mauricio Santelices + description: A RUT (Rol Unico Tributario) is an unique and personal identification + number implemented in Chile to identify citizens and taxpayers. Rutifier allows + to validate if a RUT exist or not and change between the different formats a RUT + can have. + date_publication: '2020-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rutifier + url_git: '' +rutledge: + version: 0.1.1 + title: Real-Time PCR Data Sets by Rutledge et al. (2004) + maintainer: Ramiro Magno + description: |- + Real-time quantitative polymerase chain reaction (qPCR) data + by Rutledge et al. (2004) in tidy format. The + data comprises a six-point, ten-fold dilution series, repeated in five + independent runs, for two different amplicons. In each run, each standard + concentration is replicated four times. For the original raw data file see + the Supplementary Data section: + . + date_publication: '2024-04-22' + bug_reports: https://github.com/ramiromagno/rutledge/issues + url: https://rmagno.eu/rutledge/ + url_cran: https://CRAN.R-project.org/package=rutledge + url_git: https://github.com/ramiromagno/rutledge +ruv: + version: 0.9.7.1 + title: Detect and Remove Unwanted Variation using Negative Controls + maintainer: Johann Gagnon-Bartsch + description: Implements the 'RUV' (Remove Unwanted Variation) algorithms. These + algorithms attempt to adjust for systematic errors of unknown origin in high-dimensional + data. The algorithms were originally developed for use with genomic data, especially + microarray data, but may be useful with other types of high-dimensional data as + well. These algorithms were proposed in Gagnon-Bartsch and Speed (2012) , + Gagnon-Bartsch, Jacob and Speed (2013), and Molania, et. al. (2019) . The + algorithms require the user to specify a set of negative control variables, as + described in the references. The algorithms included in this package are 'RUV-2', + 'RUV-4', 'RUV-inv', 'RUV-rinv', 'RUV-I', and RUV-III', along with various supporting + algorithms. + date_publication: '2019-08-30' + bug_reports: '' + url: http://www-personal.umich.edu/~johanngb/ruv/ + url_cran: https://CRAN.R-project.org/package=ruv + url_git: '' +RVA: + version: 0.0.5 + title: RNAseq Visualization Automation + maintainer: Xingpeng Li + description: Automate downstream visualization & pathway analysis in RNAseq analysis. + 'RVA' is a collection of functions that efficiently visualize RNAseq differential + expression analysis result from summary statistics tables. It also utilize the + Fisher's exact test to evaluate gene set or pathway enrichment in a convenient + and efficient manner. + date_publication: '2021-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RVA + url_git: https://github.com/THERMOSTATS/RVA +RVAideMemoire: + version: 0.9-83-7 + title: Testing and Plotting Procedures for Biostatistics + maintainer: Maxime HERVE + description: Contains miscellaneous functions useful in biostatistics, mostly univariate + and multivariate testing procedures with a special emphasis on permutation tests. + Many functions intend to simplify user's life by shortening existing procedures + or by implementing plotting functions that can be used with as many methods from + different packages as possible. + date_publication: '2023-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RVAideMemoire + url_git: '' +rvalues: + version: 0.7.1 + title: R-Values for Ranking in High-Dimensional Settings + maintainer: Nicholas Henderson + description: |- + A collection of functions for computing "r-values" from various + kinds of user input such as MCMC output or a list of effect size estimates + and associated standard errors. Given a large collection of measurement units, + the r-value, r, of a particular unit is a reported percentile that may be + interpreted as the smallest percentile at which the unit should be placed in the + top r-fraction of units. + date_publication: '2021-03-11' + bug_reports: '' + url: https://doi.org/10.1111/rssb.12131 + url_cran: https://CRAN.R-project.org/package=rvalues + url_git: '' +Rvcg: + version: '0.24' + title: Manipulations of Triangular Meshes Based on the 'VCGLIB' API + maintainer: Stefan Schlager + description: |- + Operations on triangular meshes based on 'VCGLIB'. This package + integrates nicely with the R-package 'rgl' to render the meshes processed by + 'Rvcg'. The Visualization and Computer Graphics Library (VCG for short) is + an open source portable C++ templated library for manipulation, processing + and displaying with OpenGL of triangle and tetrahedral meshes. The library, + composed by more than 100k lines of code, is released under the GPL license, + and it is the base of most of the software tools of the Visual Computing Lab of + the Italian National Research Council Institute ISTI , + like 'metro' and 'MeshLab'. The 'VCGLIB' source is pulled from trunk + and patched to work with options + determined by the configure script as well as to work with the header files + included by 'RcppEigen'. + date_publication: '2024-09-20' + bug_reports: https://github.com/zarquon42b/Rvcg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rvcg + url_git: https://github.com/zarquon42b/Rvcg +rvcheck: + version: 0.2.1 + title: R/Package Version Check + maintainer: Guangchuang Yu + description: Check latest release version of R and R package (both in 'CRAN', 'Bioconductor' + or 'Github'). + date_publication: '2021-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rvcheck + url_git: https://github.com/GuangchuangYu/rvcheck +RVCompare: + version: 0.1.8 + title: Compare Real Valued Random Variables + maintainer: Etor Arza + description: A framework with tools to compare two random variables via stochastic + dominance. See the README.md at for a + quick start guide. It can compute the Cp and Cd of two probability distributions + and the Cumulative Difference Plot as explained in E. Arza (2022) . + Uses bootstrap or DKW-bounds to compute the confidence bands of the cumulative + distributions. These two methods are described in B. Efron. (1979) + and P. Massart (1990) . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RVCompare + url_git: '' +rvec: + version: 0.0.7 + title: Vector Representing a Random Variable + maintainer: John Bryant + description: |- + Random vectors, called rvecs. An rvec holds + multiple draws, but tries to behave like a standard + R vector, including working well in data frames. Rvecs are + useful for working with output from a simulation or + a Bayesian analysis. + date_publication: '2024-09-15' + bug_reports: https://github.com/bayesiandemography/rvec/issues + url: https://bayesiandemography.github.io/rvec/ + url_cran: https://CRAN.R-project.org/package=rvec + url_git: https://github.com/bayesiandemography/rvec +Rveg: + version: 0.1.6 + title: Digitization of Phytosociological Relevés + maintainer: Přemysl Král + description: |- + Simple and fast tool for transforming phytosociological + vegetation data into digital form for the following analysis. + Danihelka, Chrtek, and Kaplan (2012, ISSN:00327786). + Hennekens, and Schaminée (2001) . + Tichý (2002) . + Wickham, François, Henry, Müller (2022) . + date_publication: '2024-11-22' + bug_reports: '' + url: https://plant-ecology-lab-czu.com/rveg/ + url_cran: https://CRAN.R-project.org/package=Rveg + url_git: '' +RVenn: + version: 1.1.0 + title: Set Operations for Many Sets + maintainer: Turgut Yigit Akyol + description: |- + Set operations for many sets. The base functions for set operations + in R can be used for only two sets. This package uses 'purr' to find the + union, intersection and difference of three or more sets. This package also + provides functions for pairwise set operations among several sets. Further, + based on 'ggplot2' and 'ggforce', a Venn diagram can be drawn for two or + three sets. For bigger data sets, a clustered heatmap showing presence/absence + of the elements of the sets can be drawn based on the 'pheatmap' package. + Finally, enrichment test can be applied to two sets whether an overlap is + statistically significant or not. + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RVenn + url_git: '' +RVerbalExpressions: + version: 0.1.1 + title: Create Regular Expressions Easily + maintainer: Tyler Littlefield + description: |- + Build regular expressions using grammar and functionality inspired + by . Usage of the %>% is encouraged to + build expressions in a chain-like fashion. + date_publication: '2024-03-20' + bug_reports: https://github.com/VerbalExpressions/RVerbalExpressions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RVerbalExpressions + url_git: https://github.com/VerbalExpressions/RVerbalExpressions +rversions: + version: 2.1.2 + title: Query 'R' Versions, Including 'r-release' and 'r-oldrel' + maintainer: Gábor Csárdi + description: |- + Query the main 'R' 'SVN' repository to find the + versions 'r-release' and 'r-oldrel' refer to, and also all previous + 'R' versions and their release dates. + date_publication: '2022-08-31' + bug_reports: https://github.com/r-hub/rversions/issues + url: https://r-hub.github.io/rversions/ + url_cran: https://CRAN.R-project.org/package=rversions + url_git: https://github.com/r-hub/rversions +rvertnet: + version: 0.8.4 + title: Search 'Vertnet', a 'Database' of Vertebrate Specimen Records + maintainer: Dave Slager + description: |- + Retrieve, map and summarize data from the 'VertNet.org' + archives (). Functions allow searching by many + parameters, including 'taxonomic' names, places, and dates. In addition, + there is an interface for conducting spatially delimited searches, and + another for requesting large 'datasets' via email. + date_publication: '2024-02-15' + bug_reports: https://github.com/ropensci/rvertnet/issues + url: https://docs.ropensci.org/rvertnet/ + url_cran: https://CRAN.R-project.org/package=rvertnet + url_git: https://github.com/ropensci/rvertnet +rvest: + version: 1.0.4 + title: Easily Harvest (Scrape) Web Pages + maintainer: Hadley Wickham + description: |- + Wrappers around the 'xml2' and 'httr' packages to make it + easy to download, then manipulate, HTML and XML. + date_publication: '2024-02-12' + bug_reports: https://github.com/tidyverse/rvest/issues + url: https://rvest.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=rvest + url_git: https://github.com/tidyverse/rvest +rvg: + version: 0.3.4 + title: R Graphics Devices for 'Office' Vector Graphics Output + maintainer: David Gohel + description: |- + Vector Graphics devices for 'Microsoft PowerPoint' and + 'Microsoft Excel'. Functions extending package 'officer' are provided to + embed 'DrawingML' graphics into 'Microsoft PowerPoint' presentations and + 'Microsoft Excel' workbooks. + date_publication: '2024-08-27' + bug_reports: https://github.com/davidgohel/rvg/issues + url: https://ardata-fr.github.io/officeverse/ + url_cran: https://CRAN.R-project.org/package=rvg + url_git: '' +rvHPDT: + version: '4.0' + title: |- + Calling Haplotype-Based and Variant-Based Pedigree + Disequilibrium Test for Rare Variants in Pedigrees + maintainer: Wei Guo + description: To detecting rare variants for binary traits using general pedigrees, + the pedigree disequilibrium tests are proposed by collapsing rare haplotypes/variants + with/without weights. To run the test, MERLIN is needed in Linux for haplotyping. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rvHPDT + url_git: '' +RViennaCL: + version: 1.7.1.8 + title: '''ViennaCL'' C++ Header Files' + maintainer: Charles Determan Jr + description: |- + 'ViennaCL' is a free open-source linear algebra library + for computations on many-core architectures (GPUs, MIC) and + multi-core CPUs. The library is written in C++ and supports 'CUDA', + 'OpenCL', and 'OpenMP' (including switches at runtime). + I have placed these libraries in this package as a more efficient + distribution system for CRAN. The idea is that you can write a package + that depends on the 'ViennaCL' library and yet you do not need to + distribute a copy of this code with your package. + date_publication: '2019-05-28' + bug_reports: http://github.com/cdeterman/RViennaCL/issues/new + url: '' + url_cran: https://CRAN.R-project.org/package=RViennaCL + url_git: http://github.com/cdeterman/RViennaCL +rviewgraph: + version: 1.4.2 + title: Animated Graph Layout Viewer + maintainer: Alun Thomas + description: |- + Provides 'Java' graphical user interfaces + for viewing, manipulating and plotting graphs. + Graphs may be directed or undirected. + date_publication: '2023-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rviewgraph + url_git: '' +rvif: + version: '2.0' + title: |- + Collinearity Detection using Redefined Variance Inflation Factor + and Graphical Methods + maintainer: R. Salmerón + description: The detection of troubling approximate collinearity in a multiple linear + regression model is a classical problem in Econometrics. The objective of this + package is to detect it using the variance inflation factor redefined and the + scatterplot between the variance inflation factor and the coefficient of variation. + For more details see Salmerón R., García C.B. and García J. (2018) , + Salmerón, R., Rodríguez, A. and García C. (2020) , + Salmerón, R., García, C.B, Rodríguez, A. and García, C. (2022) , + Salmerón, R., García, C.B. and García, J. (2024) + and Salmerón, R., García, C.B, García J. (2023, working paper) . + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rvif + url_git: http://colldetreat.r-forge.r-project.org/ +rvinecopulib: + version: 0.7.1.1.1 + title: High Performance Algorithms for Vine Copula Modeling + maintainer: Thomas Nagler + description: |- + Provides an interface to 'vinecopulib', a C++ library for vine + copula modeling. The 'rvinecopulib' package implements the core features of the + popular 'VineCopula' package, in particular inference algorithms for both vine + copula and bivariate copula models. Advantages over 'VineCopula' are a sleeker + and more modern API, improved performances, especially in high dimensions, + nonparametric and multi-parameter families, and the ability to model discrete + variables. The 'rvinecopulib' package includes 'vinecopulib' as header-only + C++ library (currently version 0.7.1). Thus users do not need to install + 'vinecopulib' itself in order to use 'rvinecopulib'. Since their initial + releases, 'vinecopulib' is licensed under the MIT License, and 'rvinecopulib' + is licensed under the GNU GPL version 3. + date_publication: '2025-02-10' + bug_reports: https://github.com/vinecopulib/rvinecopulib/issues + url: https://vinecopulib.github.io/rvinecopulib/ + url_cran: https://CRAN.R-project.org/package=rvinecopulib + url_git: '' +RVIpkg: + version: 0.3.2 + title: Regional Vulnerability Index + maintainer: Si Gao + description: The Regional Vulnerability Index (RVI), a statistical measure of brain + structural abnormality, quantifies an individual's similarity to the expected + pattern (effect size) of deficits in schizophrenia (Kochunov P, Fan F, Ryan MC, + et al. (2020) ). + date_publication: '2023-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RVIpkg + url_git: '' +rvisidata: + version: 1.0.0 + title: |- + Wrapper for 'Visidata', an Interactive Multitool for Tabular + Data + maintainer: Paul Klemm + description: Open any data frame with 'visidata', a terminal-based spreadsheet application + . + date_publication: '2024-05-14' + bug_reports: https://github.com/paulklemm/rvisidata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rvisidata + url_git: https://github.com/paulklemm/rvisidata +rvkstat: + version: 3.2.0 + title: R Interface to API 'vk.com' + maintainer: Alexey Seleznev + description: "Load data from vk.com api about your communiti users and views,\nads + performance, post on user wall and etc.\tFor more information\nsee API Documentation + ." + date_publication: '2021-10-18' + bug_reports: https://github.com/selesnow/rvkstat/issues + url: https://selesnow.github.io/rvkstat/ + url_cran: https://CRAN.R-project.org/package=rvkstat + url_git: '' +rvmethod: + version: 0.1.2 + title: Radial Velocity Method for Detecting Exoplanets + maintainer: Parker Holzer + description: |- + Has various functions designed to implement the + Hermite-Gaussian Radial Velocity (HGRV) estimation approach of + Holzer et al. (2020) , which is a particular application of the radial + velocity method for detecting exoplanets. The overall approach consists + of four sequential steps, each of which has a function in this package: + (1) estimate the template spectrum with the function estimate_template(), + (2) find absorption features in the estimated template with the function + findabsorptionfeatures(), (3) fit Gaussians to the absorption features + with the function Gaussfit(), (4) apply the HGRV with simple linear + regression by calling the function hgrv(). This package is meant to be + open source. But please cite the paper Holzer et al. (2020) when + publishing results that use this package. + date_publication: '2020-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rvmethod + url_git: '' +rvMF: + version: 0.1.0 + title: |- + Fast Generation of von Mises-Fisher Distributed Pseudo-Random + Vectors + maintainer: Seungwoo Kang + description: Generates pseudo-random vectors that follow an arbitrary von Mises-Fisher + distribution on a sphere. This method is fast and efficient when generating a + large number of pseudo-random vectors. Functions to generate random variates and + compute density for the distribution of an inner product between von Mises-Fisher + random vector and its mean direction are also provided. Details are in Kang and + Oh (2024) . + date_publication: '2024-03-27' + bug_reports: https://github.com/seungwoo-stat/rvMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rvMF + url_git: https://github.com/seungwoo-stat/rvMF +rwa: + version: 0.0.3 + title: Perform a Relative Weights Analysis + maintainer: Martin Chan + description: |- + Perform a Relative Weights Analysis (RWA) (a.k.a. Key Drivers Analysis) as per the method described + in Tonidandel & LeBreton (2015) , with its original roots in Johnson (2000) . In essence, RWA decomposes + the total variance predicted in a regression model into weights that accurately reflect the proportional + contribution of the predictor variables, which addresses the issue of multi-collinearity. In typical scenarios, + RWA returns similar results to Shapley regression, but with a significant advantage on computational performance. + date_publication: '2020-11-24' + bug_reports: https://github.com/martinctc/rwa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rwa + url_git: https://github.com/martinctc/rwa +rwalkr: + version: 0.5.7 + title: API to Melbourne Pedestrian Data + maintainer: Earo Wang + description: |- + Provides API to Melbourne pedestrian and weather data + in tidy data form. + date_publication: '2022-11-15' + bug_reports: https://github.com/earowang/rwalkr/issues + url: https://pkg.earo.me/rwalkr/ + url_cran: https://CRAN.R-project.org/package=rwalkr + url_git: '' +rwarrior: + version: 0.4.1 + title: R Warrior - An AI Programming Game + maintainer: Rick M Tankard + description: |- + A port of Ruby Warrior. + Teaches R programming in a fun and interactive way. + date_publication: '2022-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rwarrior + url_git: '' +Rwave: + version: 2.6-5 + title: Time-Frequency Analysis of 1-D Signals + maintainer: Jonathan M. Lees + description: |- + A set of R functions which provide an + environment for the Time-Frequency analysis of 1-D signals (and + especially for the wavelet and Gabor transforms of noisy + signals). It was originally written for Splus by Rene Carmona, + Bruno Torresani, and Wen L. Hwang, first at the University of + California at Irvine and then at Princeton University. Credit + should also be given to Andrea Wang whose functions on the + dyadic wavelet transform are included. Rwave is based on the + book: "Practical Time-Frequency Analysis: Gabor and Wavelet + Transforms with an Implementation in S", by Rene Carmona, Wen + L. Hwang and Bruno Torresani (1998, eBook ISBN:978008053942), Academic Press. + date_publication: '2022-10-21' + bug_reports: '' + url: https://carmona.princeton.edu/TFbook/tfbook.html + url_cran: https://CRAN.R-project.org/package=Rwave + url_git: https://r-forge.r-project.org/projects/rwave/ +rwavelet: + version: 0.4.1 + title: Wavelet Analysis + maintainer: Navarro Fabien + description: Perform wavelet analysis (orthogonal,translation invariant, tensorial, + 1-2-3d transforms, thresholding, block thresholding, linear,...) with applications + to data compression or denoising/regression. The core of the code is a port of + 'MATLAB' Wavelab toolbox written by D. Donoho, A. Maleki and M. Shahram (). + date_publication: '2020-12-12' + bug_reports: https://github.com/fabnavarro/rwavelet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rwavelet + url_git: https://github.com/fabnavarro/rwavelet +rwc: + version: '1.12' + title: Random Walk Covariance Models + maintainer: Ephraim Hanks + description: Code to facilitate simulation and inference when connectivity is defined + by underlying random walks. Methods for spatially-correlated pairwise distance + data are especially considered. This provides core code to conduct analyses similar + to that in Hanks and Hooten (2013) . + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rwc + url_git: '' +Rwclust: + version: 0.1.0 + title: Random Walk Clustering on Weighted Graphs + maintainer: Carson Sprock + description: Implements the random walk clustering algorithm for weighted graphs + as found in Harel and Koren (2001) . + date_publication: '2022-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rwclust + url_git: '' +rWCVP: + version: 1.2.4 + title: |- + Generating Summaries, Reports and Plots from the World Checklist + of Vascular Plants + maintainer: Matilda Brown + description: |- + A companion to the World Checklist of + Vascular Plants (WCVP). It includes functions to generate maps and species lists, as + well as match names to the WCVP. For more details and to cite the package, see: + Brown M.J.M., Walker B.E., Black N., Govaerts R., Ondo I., Turner R., Nic Lughadha E. (in press). + "rWCVP: A companion R package to the World Checklist of Vascular Plants". New Phytologist. + date_publication: '2023-02-16' + bug_reports: https://github.com/matildabrown/rWCVP/issues + url: https://matildabrown.github.io/rWCVP/ + url_cran: https://CRAN.R-project.org/package=rWCVP + url_git: https://github.com/matildabrown/rWCVP +RWDataPlyr: + version: 0.6.4 + title: Read and Manipulate Data from 'RiverWare' + maintainer: Alan Butler + description: |- + A tool to read and manipulate data generated from 'RiverWare'(TM) + simulations. 'RiverWare' and 'RiverSMART' + generate data in "rdf", "csv", and "nc" format. This package provides an + interface to read, aggregate, and summarize data from one or more + simulations in a 'dplyr' pipeline. + date_publication: '2020-04-17' + bug_reports: https://github.com/BoulderCodeHub/RWDataPlyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RWDataPlyr + url_git: https://github.com/BoulderCodeHub/RWDataPlyr +RweaveExtra: + version: 1.1-0 + title: Sweave Drivers with Extra Tricks Up their Sleeve + maintainer: Vincent Goulet + description: |- + Weave and tangle drivers for Sweave extending the + standard drivers. RweaveExtraLatex and RtangleExtra provide options + to completely ignore code chunks on weaving, tangling, or both. + Chunks ignored on weaving are not parsed, yet are written out + verbatim on tangling. Chunks ignored on tangling may be evaluated as + usual on weaving, but are completely left out of the tangled + scripts. The driver RtangleExtra also provides an option to specify + the extension of the file name (or remove it entirely) when + splitting is selected on tangling. + date_publication: '2024-02-20' + bug_reports: https://gitlab.com/vigou3/rweaveextra/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RweaveExtra + url_git: https://gitlab.com/vigou3/rweaveextra +rwebstat: + version: 1.1.1 + title: Download Data from the Webstat API + maintainer: Vincent Guegan + description: |- + Access the Webstat API, download data and metadata from more than 35000 time series + from the Banque de France statistics web portal. Access requires a free client ID easily available + from the API portal . + date_publication: '2023-06-07' + bug_reports: https://developer.webstat.banque-france.fr/contact + url: https://developer.webstat.banque-france.fr + url_cran: https://CRAN.R-project.org/package=rwebstat + url_git: '' +RWeka: + version: 0.4-46 + title: R/Weka Interface + maintainer: Kurt Hornik + description: |- + An R interface to Weka (Version 3.9.3). + Weka is a collection of machine learning algorithms for data mining + tasks written in Java, containing tools for data pre-processing, + classification, regression, clustering, association rules, and + visualization. Package 'RWeka' contains the interface code, the + Weka jar is in a separate package 'RWekajars'. For more information + on Weka see . + date_publication: '2023-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWeka + url_git: '' +RWekajars: + version: 3.9.3-2 + title: R/Weka Interface Jars + maintainer: Kurt Hornik + description: External jars required for package 'RWeka'. + date_publication: '2019-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWekajars + url_git: '' +rwfec: + version: '0.2' + title: R Wireless, Forward Error Correction + maintainer: Alberto Gutierrez + description: Communications simulation package supporting forward error correction. + date_publication: '2015-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rwfec + url_git: '' +RWgraph: + version: 1.0.0 + title: Random Walks on Graphs Representing a Transactional Network + maintainer: Mafalda Sá Ferreira + description: Random walk functions to extract new variables based on clients transactional + behaviour. For more details, see Eddin et al. (2021) and + Oliveira et al. (2021) . + date_publication: '2023-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWgraph + url_git: '' +rwhatsapp: + version: 0.2.4 + title: Import and Handling for 'WhatsApp' Chat Logs + maintainer: Johannes Gruber + description: |- + A straightforward, easy-to-use and robust parsing package which aims to + digest history files from the popular messenger service 'WhatsApp' in all locales + and from all devices. + date_publication: '2022-01-05' + bug_reports: https://github.com/JBGruber/rwhatsapp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rwhatsapp + url_git: https://github.com/JBGruber/rwhatsapp +Rwhois: + version: 1.0.16 + title: WHOIS Server Querying + maintainer: Brad Cable + description: Queries data from WHOIS servers. + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Rwhois + url_git: '' +rwicc: + version: 0.1.3 + title: Regression with Interval-Censored Covariates + maintainer: Douglas Morrison + description: Provides functions to simulate and analyze data for a regression model + with an interval censored covariate, as described in Morrison et al. (2021) . + date_publication: '2022-03-09' + bug_reports: https://github.com/d-morrison/rwicc/issues + url: https://d-morrison.github.io/rwicc/ + url_cran: https://CRAN.R-project.org/package=rwicc + url_git: https://github.com/d-morrison/rwicc +RWiener: + version: 1.3-3 + title: Wiener Process Distribution Functions + maintainer: Dominik Wabersich + description: |- + Provides Wiener process distribution functions, + namely the Wiener first passage time density, CDF, quantile and random + functions. Additionally supplies a modelling function (wdm) and further + methods for the resulting object. + date_publication: '2020-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWiener + url_git: https://github.com/yeagle/RWiener +RWildbook: + version: 0.9.3 + title: Interface for the 'Wildbook' Wildlife Data Management Framework + maintainer: Simon Bonner + description: |- + Provides an interface with the 'Wildbook' mark-recapture ecological database framework. It + helps users to pull data from the 'Wildbook' framework and format data for further analysis + with mark-recapture applications like 'Program MARK' (which can be accessed via the 'RMark' package in 'R'). + Further information on the 'Wildbook' framework is available at: . + date_publication: '2018-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWildbook + url_git: '' +rWishart: + version: 0.1.2 + title: Random Wishart Matrix Generation + maintainer: Ben Barnard + description: |- + An expansion of R's 'stats' random wishart matrix generation. + This package allows the user to generate singular, Uhlig and Harald (1994) + , and pseudo wishart, Diaz-Garcia, et al.(1997) + , matrices. In addition the user can generate + wishart matrices with fractional degrees of freedom, Adhikari (2008) + , commonly used in volatility + modeling. Users can also use this package to create random covariance matrices. + date_publication: '2019-11-19' + bug_reports: '' + url: https://rwishart.bearstatistics.com + url_cran: https://CRAN.R-project.org/package=rWishart + url_git: '' +rwisp: + version: 1.0.5 + title: WISP Multiple Criteria Sorting Method + maintainer: Bernardo Silva + description: Implementation of the Integrated Simple Weighted Sum Product Method + (WISP), a multiple criteria sorting method create by Dragisa Stanujkic (2021) + . + date_publication: '2023-06-30' + bug_reports: https://github.com/dioubernardo/rwisp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rwisp + url_git: https://github.com/dioubernardo/rwisp +rwlifetable: + version: 0.1.0-6 + title: Estimation of Life Tables Using Rolling Windows + maintainer: Jose M. Pavía + description: |- + Estimates life tables, specifically (crude) death rates and (raw and graduated) death probabilities, using rolling windows in one (e.g., age), two (e.g., age and time) or three (e.g., age, time and income) dimensions. The package can also be utilised for summarising statistics and smoothing continuous variables through rolling windows in other domains, such as estimating averages of self-positioning ideology in political science. + Acknowledgements: + The authors wish to thank Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Generalitat Valenciana (grants HIECPU/2023/2, Conselleria de Hacienda, Economía y Administración Pública, and CIGE/2023/7, Conselleria de Educación, Cultura, Universidades y Empleo) for supporting this research. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rwlifetable + url_git: '' +RWmisc: + version: 0.1.2 + title: Miscellaneous Spatial Functions + maintainer: Rob Williams + description: |- + Contains convenience functions for working with spatial data across + multiple UTM zones, raster-vector operations common in the analysis of + conflict data, and converting degrees, minutes, and seconds latitude and + longitude coordinates to decimal degrees. + date_publication: '2022-02-14' + bug_reports: https://github.com/jayrobwilliams/RWmisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RWmisc + url_git: https://github.com/jayrobwilliams/RWmisc +RWNN: + version: '0.4' + title: Random Weight Neural Networks + maintainer: Søren B. Vilsen + description: Creation, estimation, and prediction of random weight neural networks + (RWNN), Schmidt et al. (1992) , including popular + variants like extreme learning machines, Huang et al. (2006) , + sparse RWNN, Zhang et al. (2019) , and deep + RWNN, Henríquez et al. (2018) . It further allows + for the creation of ensemble RWNNs like bagging RWNN, Sui et al. (2021) , + boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) . + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWNN + url_git: '' +Rwofost: + version: 0.8-3 + title: WOFOST Crop Growth Simulation Model + maintainer: Robert J. Hijmans + description: An implementation of the WOFOST ("World Food Studies") crop growth + model. WOFOST is a dynamic simulation model that uses daily weather data, and + crop, soil and management parameters to simulate crop growth and development. + See De Wit et al. (2019) for a recent review + of the history and use of the model. + date_publication: '2021-10-01' + bug_reports: https://github.com/cropmodels/Rwofost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rwofost + url_git: '' +rworkflows: + version: 1.0.6 + title: Test, Document, Containerise, and Deploy R Packages + maintainer: Brian Schilder + description: |- + Reproducibility is essential to the progress of research, + yet achieving it remains elusive even in computational fields. + Continuous Integration (CI) platforms offer a powerful way to launch automated workflows + to check and document code, but often require considerable time, effort, + and technical expertise to setup. We therefore developed the rworkflows suite + to make robust CI workflows easy and freely accessible to all R package developers. + rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, + 2) an R package to quickly implement a standardised workflow, and + 3) a centrally maintained GitHub Action. + date_publication: '2025-01-23' + bug_reports: https://github.com/neurogenomics/rworkflows/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rworkflows + url_git: https://github.com/neurogenomics/rworkflows +rworldmap: + version: 1.3-8 + title: Mapping Global Data + maintainer: Andy South + description: Enables mapping of country level and gridded user datasets. + date_publication: '2023-10-16' + bug_reports: https://github.com/AndySouth/rworldmap/issues + url: https://groups.google.com/forum/#!forum/rworldmap + url_cran: https://CRAN.R-project.org/package=rworldmap + url_git: https://github.com/AndySouth/rworldmap/ +rworldxtra: + version: '1.01' + title: Country boundaries at high resolution. + maintainer: Andy South + description: High resolution vector country boundaries derived fromNatural + Earth data, can be plotted in rworldmap. + date_publication: '2012-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rworldxtra + url_git: '' +RWsearch: + version: 5.2.0 + title: |- + Lazy Search in R Packages, Task Views, CRAN, the Web. All-in-One + Download + maintainer: Patrice Kiener + description: Search by keywords in R packages, task views, CRAN, the web and display + the results in the console or in txt, html or pdf files. Download the package + documentation (html index, README, NEWS, pdf manual, vignettes, source code, binaries) + with a single instruction. Visualize the package dependencies and CRAN checks. + Compare the package versions, unload and install the packages and their dependencies + in a safe order. Explore CRAN archives. Use the above functions for task view + maintenance. Access web search engines from the console thanks to 80+ bookmarks. + All functions accept standard and non-standard evaluation. + date_publication: '2024-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RWsearch + url_git: '' +rwstats: + version: '0.1' + title: Chinese Character Frequency in Real World + maintainer: Yitao Ma + description: |- + It contains Chinese character frequency data based on + news data from 2017 to 2019. Source of these news include Sina, China daily and Tencent. + date_publication: '2019-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rwstats + url_git: '' +Rwtss: + version: 0.9.2 + title: Client for Web Time-Series Service + maintainer: Felipe Souza + description: |- + Allows remote access to satellite image time + series provided by the web time series service (WTSS) available + at servers such as . + The functions include listing the data sets available in WTSS servers, + describing the contents of a data set, and retrieving a time series + based on spatial location and temporal filters. + date_publication: '2022-04-25' + bug_reports: https://github.com/e-sensing/Rwtss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Rwtss + url_git: https://github.com/e-sensing/Rwtss/ +rwty: + version: 1.0.2 + title: R We There Yet? Visualizing MCMC Convergence in Phylogenetics + maintainer: Dan Warren + description: |- + Implements various tests, visualizations, and metrics + for diagnosing convergence of MCMC chains in phylogenetics. It implements + and automates many of the functions of the AWTY package in the R + environment. + date_publication: '2019-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rwty + url_git: '' +rwunderground: + version: 0.1.8 + title: R Interface to Weather Underground API + maintainer: Eric Hare + description: |- + Tools for getting historical weather information and forecasts + from wunderground.com. Historical weather and forecast data includes, but + is not limited to, temperature, humidity, windchill, wind speed, dew point, + heat index. Additionally, the weather underground weather API also includes + information on sunrise/sunset, tidal conditions, satellite/webcam imagery, + weather alerts, hurricane alerts and historical high/low temperatures. + date_publication: '2018-05-01' + bug_reports: https://github.com/alshum/rwunderground/issues + url: http://www.wunderground.com/weather/api + url_cran: https://CRAN.R-project.org/package=rwunderground + url_git: https://github.com/ALShum/rwunderground +RXKCD: + version: 1.9.2 + title: Get XKCD Comic from R + maintainer: Paolo Sonego + description: |- + Visualize your favorite XKCD comic strip directly from + R. XKCD web comic content is provided under the Creative + Commons Attribution-NonCommercial 2.5 License. + date_publication: '2020-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RXKCD + url_git: '' +RxnSim: + version: 1.0.4 + title: Functions to Compute Chemical and Chemical Reaction Similarity + maintainer: Varun Giri + description: 'Methods to compute chemical similarity between two or more reactions + and molecules. Allows masking of chemical substructures for weighted similarity + computations. Uses packages ''rCDK'' and ''fingerprint'' for cheminformatics functionality. + Methods for reaction similarity and sub-structure masking are as described in: + Giri et al. (2015) .' + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RxnSim + url_git: '' +rxode2: + version: 3.0.4 + title: Facilities for Simulating from ODE-Based Models + maintainer: Matthew L. Fidler + description: |- + Facilities for running simulations from ordinary + differential equation ('ODE') models, such as pharmacometrics and other + compartmental models. A compilation manager translates the ODE model + into C, compiles it, and dynamically loads the object code into R for + improved computational efficiency. An event table object facilitates + the specification of complex dosing regimens (optional) and sampling + schedules. NB: The use of this package requires both C and + Fortran compilers, for details on their use with R please see + Section 6.3, Appendix A, and Appendix D in the "R Administration and + Installation" manual. Also the code is mostly released under GPL. The + 'VODE' and 'LSODA' are in the public domain. The information is available + in the inst/COPYRIGHTS. + date_publication: '2025-02-14' + bug_reports: https://github.com/nlmixr2/rxode2/issues/ + url: https://nlmixr2.github.io/rxode2/ + url_cran: https://CRAN.R-project.org/package=rxode2 + url_git: https://github.com/nlmixr2/rxode2/ +rxode2ll: + version: 2.0.13 + title: Log-Likelihood Functions for 'rxode2' + maintainer: Matthew L. Fidler + description: |- + Provides the log-likelihoods with gradients from 'stan' + (Carpenter et al (2015), ) needed + for generalized log-likelihood estimation in 'nlmixr2' + (Fidler et al (2019) ). This is + split of to reduce computational burden of recompiling 'rxode2' + (Wang, Hallow and James (2016) ) which runs + the 'nlmixr2' models during estimation. + date_publication: '2024-12-15' + bug_reports: https://github.com/nlmixr2/rxode2ll/issues/ + url: https://nlmixr2.github.io/rxode2ll/ + url_cran: https://CRAN.R-project.org/package=rxode2ll + url_git: https://github.com/nlmixr2/rxode2ll/ +rxSeq: + version: 0.99.3 + title: Combined Total and Allele Specific Reads Sequencing Study + maintainer: Vasyl Zhabotynsky + description: Analysis of combined total and allele specific reads from the reciprocal + cross study with RNA-seq data. + date_publication: '2016-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rxSeq + url_git: '' +RXshrink: + version: '2.3' + title: |- + Maximum Likelihood Shrinkage using Generalized Ridge or Least + Angle Regression + maintainer: Bob Obenchain + description: |- + Functions are provided to calculate and display ridge TRACE Diagnostics for a + variety of alternative Shrinkage Paths. While all methods focus on Maximum Likelihood + estimation of unknown true effects under normal distribution-theory, some estimates are + modified to be Unbiased or to have "Correct Range" when estimating either [1] the noncentrality + of the F-ratio for testing that true Beta coefficients are Zeros or [2] the "relative" MSE + Risk (i.e. MSE divided by true sigma-square, where the "relative" variance of OLS is known.) + The eff.ridge() function implements the "Efficient Shrinkage Path" introduced in Obenchain + (2022) . This "p-Parameter" Shrinkage-Path always passes through the + vector of regression coefficient estimates Most-Likely to achieve the overall Optimal + Variance-Bias Trade-Off and is the shortest Path with this property. Functions eff.aug() and + eff.biv() augment the calculations made by eff.ridge() to provide plots of the bivariate + confidence ellipses corresponding to any of the p*(p-1) possible ordered pairs of shrunken + regression coefficients. Functions for plotting TRACE Diagnostics now have more options. + date_publication: '2023-08-07' + bug_reports: '' + url: http://localcontrolstatistics.org + url_cran: https://CRAN.R-project.org/package=RXshrink + url_git: '' +rxylib: + version: 0.2.14 + title: Import XY-Data into R + maintainer: Sebastian Kreutzer + description: |- + Provides access to the 'xylib' C library for to import xy + data from powder diffraction, spectroscopy and other experimental methods. + date_publication: '2024-08-27' + bug_reports: https://github.com/R-Lum/rxylib/issues + url: https://r-lum.github.io/rxylib/ + url_cran: https://CRAN.R-project.org/package=rxylib + url_git: '' +Ryacas: + version: 1.1.5 + title: R Interface to the 'Yacas' Computer Algebra System + maintainer: Mikkel Meyer Andersen + description: Interface to the 'yacas' computer algebra system (). + date_publication: '2023-01-16' + bug_reports: https://github.com/r-cas/ryacas/issues + url: http://www.yacas.org + url_cran: https://CRAN.R-project.org/package=Ryacas + url_git: https://github.com/r-cas/ryacas +Ryacas0: + version: 0.4.4 + title: Legacy 'Ryacas' (Interface to 'Yacas' Computer Algebra System) + maintainer: Mikkel Meyer Andersen + description: A legacy version of 'Ryacas', an interface to the 'yacas' computer + algebra system (). + date_publication: '2023-01-12' + bug_reports: https://github.com/r-cas/ryacas0/issues + url: http://www.yacas.org + url_cran: https://CRAN.R-project.org/package=Ryacas0 + url_git: https://github.com/r-cas/ryacas0 +ryandexdirect: + version: 3.6.2 + title: Load Data From 'Yandex Direct' + maintainer: Alexey Seleznev + description: |- + Load data from 'Yandex Direct' API V5 + into R. + Provide function for load lists of campaings, ads, keywords and other + objects from 'Yandex Direct' account. Also you can load statistic from + API 'Reports Service' . + And allows keyword bids management. + date_publication: '2023-03-17' + bug_reports: https://github.com/selesnow/ryandexdirect/issues + url: https://selesnow.github.io/ryandexdirect/ + url_cran: https://CRAN.R-project.org/package=ryandexdirect + url_git: '' +RYandexTranslate: + version: '1.0' + title: R Interface to Yandex Translate API + maintainer: Mukul Chaware + description: |- + 'Yandex Translate' (https://translate.yandex.com/) is a statistical machine translation system. + The system translates separate words, complete texts, and webpages. + This package can be used to detect language from text and to translate it to supported target language. + For more info: https://tech.yandex.com/translate/doc/dg/concepts/About-docpage/ . + date_publication: '2016-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RYandexTranslate + url_git: https://github.com/mukul13/RYandexTranslate +rym: + version: 1.0.6 + title: R Interface to Yandex Metrica API + maintainer: Alexey Seleznev + description: "Allows work with 'Management API' for load counters, segments, filters,\nuser + permissions and goals list from Yandex Metrica, 'Reporting API' allows you to + get\ninformation about the statistics of site visits and other data without\nusing + the web interface, 'Logs API' allows to receive non-aggregated data and\n'Compatible + with Google Analytics Core Reporting API v3' allows\nreceive information about + site traffic and other data using field names\nfrom Google Analytics Core API.\tFor + more information see official\ndocuments ." + date_publication: '2023-03-17' + bug_reports: https://github.com/selesnow/rym/issues + url: https://selesnow.github.io/rym/ + url_cran: https://CRAN.R-project.org/package=rym + url_git: '' +rYoutheria: + version: 1.0.3 + title: Access to the YouTheria Mammal Trait Database + maintainer: Tom August + description: |- + A programmatic interface to web-services of YouTheria. YouTheria is + an online database of mammalian trait data . + date_publication: '2016-04-12' + bug_reports: |2- + + https://github.com/biologicalrecordscentre/rYoutheria/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rYoutheria + url_git: https://github.com/BiologicalRecordsCentre/rYoutheria +rytstat: + version: 0.3.2 + title: Work with 'YouTube API' + maintainer: Alexey Seleznev + description: |- + Provide function for get data from 'YouTube Data API' + , 'YouTube Analytics API' + and + 'YouTube Reporting API' . + date_publication: '2024-05-31' + bug_reports: https://github.com/selesnow/rytstat/issues + url: https://selesnow.github.io/rytstat/docs/ + url_cran: https://CRAN.R-project.org/package=rytstat + url_git: '' +rYWAASB: + version: '0.2' + title: Simultaneous Selection by Trait and WAASB Index + maintainer: Ali Arminian + description: This tool proposes a new ranking algorithm that utilizes a "Y*WAASB" + biplot generated by the 'metan'. The aim of the current package is to effectively + distinguish the top-ranked genotypes in MET (Multi-Environmental Trials). For + a detailed explanation of the process of obtaining "WAASB", "WAASBY" indices, + and a "Y*WAASB" biplot, refer to the manual included in this package as well as + the study by Olivoto & Lúcio (2020) . In this context, + "WAASB" refers to the "Weighted Average of Absolute Scores" provided by Olivoto + et al. (2019) , which quantifies the stability + of genotypes across different environments using linear mixed-effect models. To + run the package, you need to extract the "WAASB" and "WAASBY" coefficients using + the 'metan' and apply them. This tool utilizes PCA (Principal Component Analysis) + and differentiates the entries which may be genotypes, hybrids, varieties, etc + using "WAASB", "WAASBY", and a combination of the specified trait and WAASB index. + date_publication: '2024-09-30' + bug_reports: https://github.com/abeyran/rYWAASB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=rYWAASB + url_git: https://github.com/abeyran/rYWAASB +RZabbix: + version: 0.1.0 + title: R Module for Working with the 'Zabbix API' + maintainer: Marcin Kosinski + description: R interface to the 'Zabbix API' data . + Enables easy and direct communication with 'Zabbix API' from 'R'. + date_publication: '2016-04-26' + bug_reports: https://github.com/MarcinKosinski/RZabbix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=RZabbix + url_git: '' +rzentra: + version: 0.1.0 + title: Client for the 'ZENTRA Cloud' API + maintainer: Eduard Szöcs + description: |- + Provides functionality to read settings, statuses and readings of + weather stations from the 'ZENTRA Cloud' API + . + date_publication: '2020-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=rzentra + url_git: '' +RZigZag: + version: 0.2.1 + title: Zig-Zag Sampler + maintainer: Joris Bierkens + description: Implements the Zig-Zag algorithm (Bierkens, Fearnhead, Roberts, 2016) + applied and Bouncy Particle Sampler for + a Gaussian target and Student distribution. + date_publication: '2019-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RZigZag + url_git: '' +rzmq: + version: 0.9.15 + title: R Bindings for 'ZeroMQ' + maintainer: Jeroen Ooms + description: Interface to the 'ZeroMQ' lightweight messaging kernel (see + for more information). + date_publication: '2024-12-16' + bug_reports: https://github.com/ropensci/rzmq/issues + url: https://docs.ropensci.org/rzmq/https://ropensci.r-universe.dev/rzmq + url_cran: https://CRAN.R-project.org/package=rzmq + url_git: '' +RZooRoH: + version: 0.3.2.1 + title: |- + Partitioning of Individual Autozygosity into Multiple + Homozygous-by-Descent Classes + maintainer: Tom Druet + description: |- + Functions to identify Homozygous-by-Descent (HBD) segments associated with runs of homozygosity (ROH) and to + estimate individual autozygosity (or inbreeding coefficient). HBD segments and autozygosity are assigned to multiple HBD classes + with a model-based approach relying on a mixture of exponential distributions. The rate of the exponential distribution is distinct + for each HBD class and defines the expected length of the HBD segments. These HBD classes are therefore related to the age of the + segments (longer segments and smaller rates for recent autozygosity / recent common ancestor). The functions allow to estimate the + parameters of the model (rates of the exponential distributions, mixing proportions), to estimate global and local autozygosity + probabilities and to identify HBD segments with the Viterbi decoding. The method is fully described in Druet and Gautier (2017) + . + date_publication: '2023-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=RZooRoH + url_git: '' +s2: + version: 1.1.7 + title: Spherical Geometry Operators Using the S2 Geometry Library + maintainer: Edzer Pebesma + description: |- + Provides R bindings for Google's s2 library for geometric calculations on + the sphere. High-performance constructors and exporters provide high compatibility + with existing spatial packages, transformers construct new geometries from existing + geometries, predicates provide a means to select geometries based on spatial + relationships, and accessors extract information about geometries. + date_publication: '2024-07-17' + bug_reports: https://github.com/r-spatial/s2/issues + url: https://r-spatial.github.io/s2/ + url_cran: https://CRAN.R-project.org/package=s2 + url_git: https://github.com/r-spatial/s2 +s20x: + version: 3.1-40 + title: |- + Functions for University of Auckland Course STATS 201/208 Data + Analysis + maintainer: James Curran + description: |- + A set of functions used in teaching STATS 201/208 Data Analysis at + the University of Auckland. The functions are designed to make parts of R more + accessible to a large undergraduate population who are mostly not statistics + majors. + date_publication: '2023-08-21' + bug_reports: https://github.com/STATS-UOA/s20x/issues + url: '' + url_cran: https://CRAN.R-project.org/package=s20x + url_git: https://github.com/STATS-UOA/s20x +s2dv: + version: 2.1.0 + title: A Set of Common Tools for Seasonal to Decadal Verification + maintainer: Ariadna Batalla + description: |- + The advanced version of package 's2dverification'. It is + intended for 'seasonal to decadal' (s2d) climate forecast verification, but + it can also be used in other kinds of forecasts or general climate analysis. + This package is specially designed for the comparison between the experimental + and observational datasets. The functionality of the included functions covers + from data retrieval, data post-processing, skill scores against observation, + to visualization. Compared to 's2dverification', 's2dv' is more compatible + with the package 'startR', able to use multiple cores for computation and + handle multi-dimensional arrays with a higher flexibility. The CDO version used + in development is 1.9.8. + date_publication: '2024-10-13' + bug_reports: https://earth.bsc.es/gitlab/es/s2dv/-/issues + url: https://earth.bsc.es/gitlab/es/s2dv/ + url_cran: https://CRAN.R-project.org/package=s2dv + url_git: '' +s2net: + version: 1.0.7 + title: The Generalized Semi-Supervised Elastic-Net + maintainer: Juan C. Laria + description: Implements the generalized semi-supervised elastic-net. This method + extends the supervised elastic-net problem, and thus it is a practical solution + to the problem of feature selection in semi-supervised contexts. Its mathematical + formulation is presented from a general perspective, covering a wide range of + models. We focus on linear and logistic responses, but the implementation could + be easily extended to other losses in generalized linear models. We develop a + flexible and fast implementation, written in 'C++' using 'RcppArmadillo' and integrated + into R via 'Rcpp' modules. See Culp, M. 2013 + for references on the Joint Trained Elastic-Net. + date_publication: '2024-03-31' + bug_reports: https://github.com/jlaria/s2net/issues + url: '' + url_cran: https://CRAN.R-project.org/package=s2net + url_git: https://github.com/jlaria/s2net +s3: + version: 1.1.0 + title: Download Files from 'AWS S3' + maintainer: Cole Brokamp + description: Download files hosted on 'AWS S3' (Amazon Web Services Simple Storage + Service; ) to a local directory based on their URI. + Avoid downloading files that are already present locally. Allow for customization + of where to store downloaded files. + date_publication: '2024-09-04' + bug_reports: https://github.com/brokamp-group/s3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=s3 + url_git: https://github.com/brokamp-group/s3 +s3.resourcer: + version: 1.1.2 + title: S3 Resource Resolver + maintainer: Yannick Marcon + description: |- + A S3 resource is provided by Amazon Web Services S3 or a S3-compatible object store (such as Minio). + The resource can be a tidy file to be downloaded from the object store, or a data lake (such as Delta Lake) + Parquet file to be read by Apache Spark. + date_publication: '2025-01-18' + bug_reports: https://github.com/obiba/s3.resourcer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=s3.resourcer + url_git: '' +s3fs: + version: 0.1.7 + title: '''Amazon Web Service S3'' File System' + maintainer: Dyfan Jones + description: |- + Access 'Amazon Web Service Simple Storage Service' ('S3') + as if it were a file system. Interface based on the R package 'fs'. + date_publication: '2024-08-29' + bug_reports: https://github.com/DyfanJones/s3fs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=s3fs + url_git: https://github.com/DyfanJones/s3fs +S4DM: + version: 0.0.1 + title: Small Sample Size Species Distribution Modeling + maintainer: Brian S. Maitner + description: Implements a set of distribution modeling methods that are suited to + species with small sample sizes (e.g., poorly sampled species or rare species). + While these methods can also be used on well-sampled taxa, they are united by + the fact that they can be utilized with relatively few data points. More details + on the currently implemented methodologies can be found in Drake and Richards + (2018) , Drake (2015) , and + Drake (2014) . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=S4DM + url_git: '' +s4vd: + version: 1.1-1 + title: |- + Biclustering via Sparse Singular Value Decomposition + Incorporating Stability Selection + maintainer: Martin Sill + description: |- + The main function s4vd() performs a biclustering via sparse + singular value decomposition with a nested stability selection. + The results is an biclust object and thus all methods of the + biclust package can be applied. + date_publication: '2015-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=s4vd + url_git: '' +S7: + version: 0.2.0 + title: |- + An Object Oriented System Meant to Become a Successor to S3 and + S4 + maintainer: Hadley Wickham + description: |- + A new object oriented programming system designed to be a + successor to S3 and S4. It includes formal class, generic, and method + specification, and a limited form of multiple dispatch. It has been + designed and implemented collaboratively by the R Consortium + Object-Oriented Programming Working Group, which includes + representatives from R-Core, 'Bioconductor', 'Posit'/'tidyverse', and + the wider R community. + date_publication: '2024-11-07' + bug_reports: https://github.com/RConsortium/S7/issues + url: https://rconsortium.github.io/S7/ + url_cran: https://CRAN.R-project.org/package=S7 + url_git: https://github.com/RConsortium/S7 +saasCNV: + version: 0.3.4 + title: |- + Somatic Copy Number Alteration Analysis Using Sequencing and SNP + Array Data + maintainer: Zhongyang Zhang + description: |- + Perform joint segmentation on two signal dimensions derived from + total read depth (intensity) and allele specific read depth (intensity) for + whole genome sequencing (WGS), whole exome sequencing (WES) and SNP array data. + date_publication: '2016-05-18' + bug_reports: '' + url: https://zhangz05.u.hpc.mssm.edu/saasCNV/ + url_cran: https://CRAN.R-project.org/package=saasCNV + url_git: '' +sabre: + version: 0.4.3 + title: Spatial Association Between Regionalizations + maintainer: Jakub Nowosad + description: |- + Calculates a degree of spatial association between regionalizations + or categorical maps using the information-theoretical V-measure + (Nowosad and Stepinski (2018) ). It also + offers an R implementation of the MapCurve method + (Hargrove et al. (2006) ). + date_publication: '2022-08-17' + bug_reports: https://github.com/Nowosad/sabre/issues + url: https://jakubnowosad.com/sabre/ + url_cran: https://CRAN.R-project.org/package=sabre + url_git: '' +sac: + version: 1.0.2 + title: Semiparametric Analysis of Change-Point + maintainer: Zhong Guan + description: |- + Semiparametric empirical likelihood ratio + based tests of change-point with one-change or epidemic alternatives + with data-based model diagnostic are contained. + date_publication: '2021-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sac + url_git: '' +saccadr: + version: 0.1.3 + title: Extract Saccades via an Ensemble of Methods Approach + maintainer: Alexander Pastukhov + description: |- + A modular and extendable approach to extract (micro)saccades from gaze samples via an ensemble of methods. + Although there is an agreement about a general definition of a saccade, the more specific details are harder to agree upon. + Therefore, there are numerous algorithms that extract saccades based on various heuristics, which differ in the assumptions about velocity, + acceleration, etc. The package uses three methods (Engbert and Kliegl (2003) , + Otero-Millan et al. (2014), and Nyström and Holmqvist (2010) ) + to label individual samples and then applies a majority vote approach to identify saccades. The package includes three + methods but can be extended via custom functions. It also uses a modular approach to compute velocity and + acceleration from noisy samples. Finally, you can obtain methods votes per gaze sample instead of saccades. + date_publication: '2023-09-06' + bug_reports: https://github.com/alexander-pastukhov/saccadr/issues/ + url: https://alexander-pastukhov.github.io/saccadr/ + url_cran: https://CRAN.R-project.org/package=saccadr + url_git: https://github.com/alexander-pastukhov/saccadr/ +sacRebleu: + version: 0.2.0 + title: Metrics for Assessing the Quality of Generated Text + maintainer: Philipp Koch + description: |- + Implementation of the BLEU-Score in 'C++' to evaluate the + quality of generated text. The BLEU-Score, introduced by Papineni et al. (2002) + , is a metric for evaluating the quality of + generated text. It is based on the n-gram overlap between the generated + text and reference texts. Additionally, the package provides some smoothing + methods as described in Chen and Cherry (2014) . + date_publication: '2025-01-22' + bug_reports: https://github.com/LazerLambda/sacRebleu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sacRebleu + url_git: https://github.com/LazerLambda/sacRebleu +sad: + version: 0.1.3 + title: Verify the Scale, Anisotropy and Direction of Weather Forecasts + maintainer: Sebastian Buschow + description: 'Implementation of the wavelet-based spatial verification method of + Buschow and Friederichs "SAD: Verifying the Scale, Anisotropy and Direction of + precipitation forecasts" (2020, submitted to QJRMS). Forecasts and Observations + are transformed by a decimated or redundant dual-tree complex wavelet transform + to analyze the spatial scale, degree of anisotropy and preferred direction in + each field. These structural attributes are compared by a series of scores. An + experimental algorithm for the correction of these errors is included as well.' + date_publication: '2020-11-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sad + url_git: '' +SADEG: + version: 1.0.0 + title: Stability Analysis in Differentially Expressed Genes + maintainer: Babak Khorsand + description: We analyzed the nucleotide composition of genes with a special emphasis + on stability of DNA sequences. Besides, in a variety of different organisms unequal + use of synonymous codons, or codon usage bias, occurs which also show variation + among genes in the same genome. Seemingly, codon usage bias is affected by both + selective constraints and mutation bias which allows and enables us to examine + and detect changes in these two evolutionary forces between genomes or along one + genome. Therefore, we determined the codon adaptation index (CAI), effective number + of codons (ENC) and codon usage analysis with calculation of the relative synonymous + codon usage (RSCU), and subsequently predicted the translation efficiency and + accuracy through GC-rich codon usages. Furthermore, we estimated the relative + stability of the DNA sequence following calculation of the average free energy + (Delta G) and Dimer base-stacking energy level. + date_publication: '2017-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SADEG + url_git: '' +SADISA: + version: '1.2' + title: |- + Species Abundance Distributions with Independent-Species + Assumption + maintainer: Rampal S. Etienne + description: 'Computes the probability of a set of species abundances of a single + or multiple samples of individuals with one or more guilds under a mainland-island + model. One must specify the mainland (metacommunity) model and the island (local) + community model. It assumes that species fluctuate independently. The package + also contains functions to simulate under this model. See Haegeman, B. & R.S. + Etienne (2017). A general sampling formula for community structure data. Methods + in Ecology & Evolution 8: 1506-1519 .' + date_publication: '2019-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SADISA + url_git: '' +sadists: + version: 0.2.5 + title: Some Additional Distributions + maintainer: Steven E. Pav + description: |- + Provides the density, distribution, quantile and generation functions of some obscure probability + distributions, including the doubly non-central t, F, Beta, and Eta distributions; + the lambda-prime and K-prime; the upsilon distribution; the (weighted) sum of + non-central chi-squares to a power; the (weighted) sum of log non-central chi-squares; + the product of non-central chi-squares to powers; the product of doubly non-central + F variables; the product of independent normals. + date_publication: '2023-08-21' + bug_reports: https://github.com/shabbychef/sadists/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sadists + url_git: https://github.com/shabbychef/sadists +sads: + version: 0.6.3 + title: Maximum Likelihood Models for Species Abundance Distributions + maintainer: Paulo I. Prado + description: |- + Maximum likelihood tools to fit and compare models of species + abundance distributions and of species rank-abundance distributions. + date_publication: '2024-01-16' + bug_reports: https://github.com/piLaboratory/sads/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sads + url_git: https://github.com/piLaboratory/sads +sae: + version: '1.3' + title: Small Area Estimation + maintainer: Yolanda Marhuenda + description: Functions for small area estimation. + date_publication: '2020-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sae + url_git: '' +sae.projection: + version: 0.1.2 + title: Small Area Estimation Using Model-Assisted Projection Method + maintainer: Ridson Al Farizal P + description: Combines information from two independent surveys using a model-assisted + projection method. Designed for survey sampling scenarios where a large sample + collects only auxiliary information (Survey 1) and a smaller sample provides data + on both variables of interest and auxiliary variables (Survey 2). Implements a + working model to generate synthetic values of the variable of interest by fitting + the model to Survey 2 data and predicting values for Survey 1 based on its auxiliary + variables (Kim & Rao, 2012) . + date_publication: '2025-02-18' + bug_reports: https://github.com/Alfrzlp/sae.projection/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sae.projection + url_git: https://github.com/Alfrzlp/sae.projection +sae.prop: + version: 0.1.2 + title: |- + Small Area Estimation using Fay-Herriot Models with Additive + Logistic Transformation + maintainer: M. Rijalus Sholihin + description: Implements Additive Logistic Transformation (alr) for Small Area Estimation + under Fay Herriot Model. Small Area Estimation is used to borrow strength from + auxiliary variables to improve the effectiveness of a domain sample size. This + package uses Empirical Best Linear Unbiased Prediction (EBLUP). The Additive Logistic + Transformation (alr) are based on transformation by Aitchison J (1986). The covariance + matrix for multivariate application is based on covariance matrix used by Esteban + M, Lombardía M, López-Vizcaíno E, Morales D, and Pérez A . + The non-sampled models are modified area-level models based on models proposed + by Anisa R, Kurnia A, and Indahwati I , with univariate + model using model-3, and multivariate model using model-1. The MSE are estimated + using Parametric Bootstrap approach. For non-sampled cases, MSE are estimated + using modified approach proposed by Haris F and Ubaidillah A . + date_publication: '2023-10-15' + bug_reports: https://github.com/mrijalussholihin/sae.prop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sae.prop + url_git: https://github.com/mrijalussholihin/sae.prop +sae2: + version: 1.2-1 + title: 'Small Area Estimation: Time-Series Models' + maintainer: Robert Fay + description: |- + Time series area-level models for small area estimation. + The package supplements the functionality of the sae package. + Specifically, it includes EBLUP fitting of the original Rao-Yu model, + which in the original form did not have a spatial component. The + package also offers a modified ('dynamic') version of the Rao-Yu model, + replacing the assumption of stationarity. Both univariate and + multivariate applications are supported. Of particular note is the + allowance for covariance of the area-level sample estimates over time, + as encountered in rotating panel designs such as the U.S. National + Crime Victimization Survey or present in a time-series of 5-year + estimates from the American Community Survey. Key references to the + methods include + J.N.K. Rao and I. Molina (2015, ISBN:9781118735787), + J.N.K. Rao and M. Yu (1994) , and + R.E. Fay and R.A. Herriot (1979) . + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sae2 + url_git: '' +saeBest: + version: 0.1.0 + title: |- + Selecting Auxiliary Variables in Small Area Estimation (SAE) + Model + maintainer: Sheerin Dahwan Aziz + description: Select best combination of auxiliary variables with certain criterion. + date_publication: '2021-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeBest + url_git: '' +saebnocov: + version: 0.1.0 + title: |- + Small Area Estimation using Empirical Bayes without Auxiliary + Variable + maintainer: Siti Rafika Fiandasari + description: |- + Estimates the parameter of small area in binary data without + auxiliary variable using Empirical Bayes technique, mainly from Rao + and Molina (2015,ISBN:9781118735787) with book entitled "Small Area Estimation Second Edition". + This package provides another option of direct estimation using weight. + This package also features alpha and beta parameter estimation on calculating process of small area. + Those methods are Newton-Raphson and Moment which based on Wilcox (1979) + and Kleinman (1973) . + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saebnocov + url_git: '' +saeczi: + version: 0.2.0 + title: Small Area Estimation for Continuous Zero Inflated Data + maintainer: Josh Yamamoto + description: |- + Provides functionality to fit a zero-inflated estimator for small area estimation. + This estimator is a combines a linear mixed effects regression model and a logistic + mixed effects regression model via a two-stage modeling approach. The estimator's mean + squared error is estimated via a parametric bootstrap method. Chandra and others + (2012, ) introduce and describe this estimator and mean + squared error estimator. White and others (2024+, ) describe the + applicability of this estimator to estimation of forest attributes and further assess the + estimator's properties. + date_publication: '2024-06-06' + bug_reports: '' + url: https://harvard-ufds.github.io/saeczi/ + url_cran: https://CRAN.R-project.org/package=saeczi + url_git: '' +saeeb: + version: 0.1.0 + title: Small Area Estimation for Count Data + maintainer: Rizki Ananda Fauziah + description: Provides small area estimation for count data type and gives option + whether to use covariates in the estimation or not. By implementing Empirical + Bayes (EB) Poisson-Gamma model, each function returns EB estimators and mean squared + error (MSE) estimators for each area. The EB estimators without covariates are + obtained using the model proposed by Clayton & Kaldor (1987) , + the EB estimators with covariates are obtained using the model proposed by Wakefield + (2006) and the MSE estimators are obtained + using Jackknife method by Jiang et. al. (2002) . + date_publication: '2020-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeeb + url_git: '' +saeHB: + version: 0.2.2 + title: Small Area Estimation using Hierarchical Bayesian Method + maintainer: Zaza Yuda Perwira + description: Provides several functions for area level of small area estimation + using hierarchical Bayesian (HB) methods with several univariate distributions + for variables of interest. The dataset that is used in every function is generated + accordingly in the Example. The 'rjags' package is employed to obtain parameter + estimates. Model-based estimators involve the HB estimators which include the + mean and the variation of mean. For the reference, see Rao and Molina (2015) . + date_publication: '2023-11-08' + bug_reports: https://github.com/zazaperwira/saeHB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB + url_git: https://github.com/zazaperwira/saeHB +saeHB.ME: + version: 1.0.1 + title: |- + Small Area Estimation with Measurement Error using Hierarchical + Bayesian Method + maintainer: Muhammad Rifqi Mubarak + description: 'Implementation of small area estimation using Hierarchical Bayesian + (HB) Method when auxiliary variable measured with error. The ''rjags'' package + is employed to obtain parameter estimates. For the references, see Rao and Molina + (2015) , Ybarra and Lohr (2008) , + and Ntzoufras (2009, ISBN-10: 1118210352).' + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.ME + url_git: '' +saeHB.ME.beta: + version: 1.1.0 + title: SAE with Measurement Error using HB under Beta Distribution + maintainer: Ratih Rodliyah + description: 'Implementation of Small Area Estimation (SAE) using Hierarchical Bayesian + (HB) Method when auxiliary variable measured with error under Beta Distribution. + The ''rjags'' package is employed to obtain parameter estimates. For the references, + see J.N.K & Molina (2015) , Ybarra and Sharon (2008) + , and Ntzoufras (2009, ISBN-10: 1118210352).' + date_publication: '2023-07-08' + bug_reports: https://github.com/ratihrodliyah/saeHB.ME.beta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.ME.beta + url_git: https://github.com/ratihrodliyah/saeHB.ME.beta +saeHB.panel: + version: 0.1.1 + title: |- + Small Area Estimation using Hierarchical Bayesian Method for Rao + Yu Model + maintainer: Velia Tri Marliana + description: We designed this package to provide several functions for area level + of small area estimation using hierarchical Bayesian (HB) method. This package + provides model using panel data for variable interest.This package also provides + a dataset produced by a data generation. The 'rjags' package is employed to obtain + parameter estimates. Model-based estimators involves the HB estimators which include + the mean and the variation of mean. For the reference, see Rao and Molina (2015). + date_publication: '2022-05-10' + bug_reports: https://github.com/Veliatrimarliana/saeHB.panel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.panel + url_git: https://github.com/Veliatrimarliana/saeHB.panel +saeHB.panel.beta: + version: 0.1.5 + title: |- + Small Area Estimation using HB for Rao Yu Model under Beta + Distribution + maintainer: Dian Rahmawati Salis + description: |- + Several functions are provided for small area estimation at + the area level using the hierarchical bayesian (HB) method with panel + data under beta distribution for variable interest. This package also + provides a dataset produced by data generation. The 'rjags' package is + employed to obtain parameter estimates. Model-based estimators involve + the HB estimators, which include the mean and the variation of the + mean. For the reference, see Rao and Molina (2015, ISBN: + 978-1-118-73578-7). + date_publication: '2024-09-04' + bug_reports: https://github.com/DianRahmawatiSalis/saeHB.panel.beta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.panel.beta + url_git: https://github.com/DianRahmawatiSalis/saeHB.panel.beta +saeHB.spatial: + version: 0.1.1 + title: Small Area Estimation Hierarchical Bayes For Spatial Model + maintainer: Arina Mana Sikana + description: Provides several functions and datasets for area level of Small Area + Estimation under Spatial Model using Hierarchical Bayesian (HB) Method. Model-based + estimators include the HB estimators based on a Spatial Fay-Herriot model with + univariate normal distribution for variable of interest.The 'rjags' package is + employed to obtain parameter estimates. For the reference, see Rao and Molina + (2015) . + date_publication: '2024-11-22' + bug_reports: https://github.com/arinams/saeHB.spatial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.spatial + url_git: https://github.com/arinams/saeHB.spatial +saeHB.twofold: + version: 0.1.2 + title: Hierarchical Bayes Twofold Subarea Level Model SAE + maintainer: Reyhan Saadi + description: We designed this package to provides several functions for area and + subarea level of small area estimation under Twofold Subarea Level Model using + hierarchical Bayesian (HB) method with Univariate Normal distribution for variables + of interest. Some dataset simulated by a data generation are also provided. The + 'rjags' package is employed to obtain parameter estimates using Gibbs Sampling + algorithm. Model-based estimators involves the HB estimators which include the + mean, the variation of mean, and the quantile. For the reference, see Rao and + Molina (2015) , Torabi and Rao (2014) , + Leyla Mohadjer et al.(2007) , + and Erciulescu et al.(2019) . + date_publication: '2024-11-28' + bug_reports: https://github.com/reymath99/saeHB.twofold/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.twofold + url_git: https://github.com/reymath99/saeHB.twofold +saeHB.unit: + version: 0.1.0 + title: Basic Unit Level Model using Hierarchical Bayesian Approach + maintainer: Ridson Al Farizal P + description: Small area estimation unit level models (Battese-Harter-Fuller model) + with a Bayesian Hierarchical approach. See also Rao & Molina (2015, ISBN:978-1-118-73578-7) + and Battese et al. (1988) . + date_publication: '2023-10-15' + bug_reports: https://github.com/Alfrzlp/saeHB.unit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.unit + url_git: https://github.com/Alfrzlp/saeHB.unit +saeHB.ZIB: + version: 0.1.1 + title: |- + Small Area Estimation using Hierarchical Bayesian under Zero + Inflated Binomial Distribution + maintainer: Rizqina Rahmati + description: Provides function for area level of small area estimation using hierarchical + Bayesian (HB) method with Zero-Inflated Binomial distribution for variables of + interest. Some dataset produced by a data generation are also provided. The 'rjags' + package is employed to obtain parameter estimates. Model-based estimators involves + the HB estimators which include the mean and the variation of mean. + date_publication: '2022-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeHB.ZIB + url_git: '' +saekernel: + version: 0.1.1 + title: |- + Small Area Estimation Non-Parametric Based Nadaraya-Watson + Kernel + maintainer: Wicak Surya Hasani + description: Propose an area-level, non-parametric regression estimator based on + Nadaraya-Watson kernel on small area mean. Adopt a two-stage estimation approach + proposed by Prasad and Rao (1990). Mean Squared Error (MSE) estimators are not + readily available, so resampling method that called bootstrap is applied. This + package are based on the model proposed in Two stage non-parametric approach for + small area estimation by Pushpal Mukhopadhyay and Tapabrata Maiti(2004) . + date_publication: '2021-06-04' + bug_reports: https://github.com/wicaksh/saekernel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saekernel + url_git: https://github.com/wicaksh/saekernel +saeME: + version: 1.3.1 + title: Small Area Estimation with Measurement Error + maintainer: Muhammad Rifqi Mubarak + description: A set of functions and datasets implementation of small area estimation + when auxiliary variable is measured with error. These functions provide a empirical + best linear unbiased prediction (EBLUP) estimator and mean squared error (MSE) + estimator of the EBLUP. These models were developed by Ybarra and Lohr (2008) + . + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeME + url_git: '' +saemix: + version: '3.3' + title: |- + Stochastic Approximation Expectation Maximization (SAEM) + Algorithm + maintainer: Emmanuelle Comets + description: 'The ''saemix'' package implements the Stochastic Approximation EM + algorithm for parameter estimation in (non)linear mixed effects models. The SAEM + algorithm (i) computes the maximum likelihood estimator of the population parameters, + without any approximation of the model (linearisation, quadrature approximation,...), + using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, + (ii) provides standard errors for the maximum likelihood estimator (iii) estimates + the conditional modes, the conditional means and the conditional standard deviations + of the individual parameters, using the Hastings-Metropolis algorithm (see Comets + et al. (2017) ). Many applications of SAEM in agronomy, + animal breeding and PKPD analysis have been published by members of the Monolix + group. The full PDF documentation for the package including references about the + algorithm and examples can be downloaded on the github of the IAME research institute + for ''saemix'': .' + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saemix + url_git: '' +saeMSPE: + version: '1.4' + title: Computing MSPE Estimates in Small Area Estimation + maintainer: Peiwen Xiao + description: Compute various common mean squared predictive error (MSPE) estimators, + as well as several existing variance component predictors as a byproduct, for + FH model (Fay and Herriot, 1979) and NER model (Battese et al., 1988) in small + area estimation. + date_publication: '2024-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeMSPE + url_git: '' +saens: + version: 0.1.2 + title: |- + Small Area Estimation with Cluster Information for Estimation of + Non-Sampled Areas + maintainer: Ridson Al Farizal P + description: Implementation of small area estimation (Fay-Herriot model) with EBLUP + (Empirical Best Linear Unbiased Prediction) Approach for non-sampled area estimation + by adding cluster information and assuming that there are similarities among particular + areas. See also Rao & Molina (2015, ISBN:978-1-118-73578-7) and Anisa et al. (2013) + . + date_publication: '2024-11-18' + bug_reports: https://github.com/Alfrzlp/sae-ns/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saens + url_git: https://github.com/Alfrzlp/sae-ns +saePseudo: + version: 0.1.0 + title: Small Area Estimation using Averaging Pseudo Area Level Model + maintainer: Darin Huwaida + description: |- + Provides function for small area estimation at area level + using averaging pseudo area level model for variables of interest. + A dataset produced by data generation is also provided. This package + estimates small areas at the village level and then aggregates them + to the sub-district, region, and provincial levels. + date_publication: '2024-06-04' + bug_reports: https://github.com/darinhuwaidaa/saePseudo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saePseudo + url_git: https://github.com/darinhuwaidaa/saePseudo +saeRobust: + version: 0.5.0 + title: Robust Small Area Estimation + maintainer: Sebastian Warnholz + description: |- + Methods to fit robust alternatives to commonly used models used in + Small Area Estimation. The methods here used are based on best linear + unbiased predictions and linear mixed models. At this time available models + include area level models incorporating spatial and temporal correlation in + the random effects. + date_publication: '2024-03-15' + bug_reports: https://github.com/wahani/saeRobust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saeRobust + url_git: '' +saery: + version: '2.0' + title: Small Area Estimation for Rao and Yu Model + maintainer: Perez Agustin + description: Functions to calculate EBLUPs (Empirical Best Linear Unbiased Predictor) + estimators and their MSEs (Mean Squared Errors). Estimators are based on an area-level + linear mixed model introduced by Rao and Yu (1994) . The + REML (Residual Maximum Likelihood) method is used for fitting the model. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saery + url_git: '' +saeSim: + version: 0.11.0 + title: Simulation Tools for Small Area Estimation + maintainer: Sebastian Warnholz + description: |- + Tools for the simulation of data in the context of small area + estimation. Combine all steps of your simulation - from data generation + over drawing samples to model fitting - in one object. This enables easy + modification and combination of different scenarios. You can store your + results in a folder or start the simulation in parallel. + date_publication: '2022-02-07' + bug_reports: https://github.com/wahani/saeSim/issues + url: https://wahani.github.io/saeSim/ + url_cran: https://CRAN.R-project.org/package=saeSim + url_git: '' +saeTrafo: + version: 1.0.4 + title: Transformations for Unit-Level Small Area Models + maintainer: Nora Würz + description: |- + The aim of this package is to offer new methodology for unit-level + small area models under transformations and limited population auxiliary + information. In addition to this new methodology, the widely used nested + error regression model without transformations (see "An Error-Components + Model for Prediction of County Crop Areas Using Survey and Satellite Data" + by Battese, Harter and Fuller (1988) ) + and its well-known uncertainty estimate (see "The estimation of the mean + squared error of small-area estimators" by Prasad and Rao (1990) + ) are provided. In this package, the + log transformation and the data-driven log-shift transformation are + provided. If a transformation is selected, an appropriate method is chosen + depending on the respective input of the population data: Individual + population data (see "Empirical best prediction under a nested error model + with log transformation" by Molina and Martín (2018) + ) but also aggregated population data (see + "Estimating regional income indicators under transformations and access to + limited population auxiliary information" by Würz, Schmid and Tzavidis + ) can be entered. Especially under limited data access, new + methodologies are provided in saeTrafo. Several options are available to + assess the used model and to judge, present and export its results. For a + detailed description of the package and the methods used see the + corresponding vignette. + date_publication: '2024-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saeTrafo + url_git: https://github.com/NoraWuerz/saeTrafo +SAEval: + version: 1.0.0 + title: Small Area Estimation Evaluation + maintainer: Andrea Fasulo + description: Allows users to produce diagnostic procedures and graphic tools for + the evaluation of Small Area estimators. + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAEval + url_git: '' +SAFARI: + version: 0.1.0 + title: Shape Analysis for AI-Reconstructed Images + maintainer: Esteban Fernandez Morales + description: |- + Provides functionality for image processing and shape analysis in + the context of reconstructed medical images generated by deep learning-based + methods or standard image processing algorithms and produced from different + medical imaging types, such as X-ray, Computational Tomography (CT), + Magnetic Resonance Imaging (MRI), and pathology imaging. Specifically, + offers tools to segment regions of interest and to extract quantitative + shape descriptors for applications in signal processing, + statistical analysis and modeling, and machine learning. + date_publication: '2021-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAFARI + url_git: https://github.com/estfernandez/SAFARI +SAFD: + version: '2.1' + title: Statistical Analysis of Fuzzy Data + maintainer: Asun Lubiano + description: |- + The aim of the package is to provide some basic functions + for doing statistics with one dimensional Fuzzy Data (in the + form of polygonal fuzzy numbers). In particular, the package + contains functions for the basic operations on the class of + fuzzy numbers (sum, scalar product, mean, median, Hukuhara difference) + as well as for calculating (Bertoluzza) distance and sample variance. + Moreover a function to simulate fuzzy random variables and bootstrap tests + for the equality of means is included. Version 2.1 fixes some bugs + of previous versions. + date_publication: '2019-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAFD + url_git: '' +safejoin: + version: 0.2.0 + title: Perform "Safe" Table Joins + maintainer: Sam Edwardes + description: The goal of 'safejoin' is to guarantee that when performing joins extra + rows are not added to your data. 'safejoin' provides a wrapper around 'dplyr::left_join' + that will raise an error when extra rows are unexpectedly added to your data. + This can be useful when working with data where you expect there to be a many + to one relationship but you are not certain the relationship holds. + date_publication: '2024-06-02' + bug_reports: https://github.com/SamEdwardes/safejoin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=safejoin + url_git: https://github.com/SamEdwardes/safejoin +safer: + version: 0.2.1 + title: Encrypt and Decrypt Strings, R Objects and Files + maintainer: KS Srikanth + description: A consistent interface to encrypt and decrypt strings, R objects and + files using symmetric and asymmetric key encryption. + date_publication: '2018-07-24' + bug_reports: https://github.com/talegari/safer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=safer + url_git: https://github.com/talegari/safer +safestats: + version: 0.8.7 + title: Safe Anytime-Valid Inference + maintainer: Alexander Ly + description: |- + Functions to design and apply tests that are anytime valid. The + functions can be used to design hypothesis tests in the prospective/randomised + control trial setting or in the observational/retrospective setting. The + resulting tests remain valid under both optional stopping and optional + continuation. The current version includes safe t-tests and safe tests of + two proportions. For details on the theory of safe tests, see + Grunwald, de Heide and Koolen (2019) "Safe Testing" , + for details on safe logrank tests see ter Schure, Perez-Ortiz, Ly and Grunwald + (2020) "The Safe Logrank Test: Error Control under Continuous Monitoring with + Unlimited Horizon" and Turner, Ly and Grunwald (2021) + "Safe Tests and Always-Valid Confidence Intervals for contingency tables and + beyond" for details on safe contingency table tests. + date_publication: '2022-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=safestats + url_git: '' +safetensors: + version: 0.1.2 + title: Safetensors File Format + maintainer: Daniel Falbel + description: |- + A file format for storing tensors that is secure (doesn't allow for + code execution), fast and simple to implement. 'safetensors' also enables cross + language and cross frameworks compatibility making it an ideal format for + storing machine learning model weights. + date_publication: '2023-09-12' + bug_reports: https://github.com/mlverse/safetensors/issues + url: https://mlverse.github.io/safetensors/ + url_cran: https://CRAN.R-project.org/package=safetensors + url_git: https://github.com/mlverse/safetensors +safetyCharts: + version: 0.3.0 + title: Charts for Monitoring Clinical Trial Safety + maintainer: Jeremy Wildfire + description: Contains chart code for monitoring clinical trial safety. Charts can + be used as standalone output, but are also designed for use with the 'safetyGraphics' + package, which makes it easy to load data and customize the charts using an interactive + web-based interface created with Shiny. + date_publication: '2022-03-22' + bug_reports: https://github.com/SafetyGraphics/safetyCharts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=safetyCharts + url_git: https://github.com/SafetyGraphics/safetyCharts +safetyData: + version: 1.0.0 + title: Clinical Trial Data + maintainer: Jeremy Wildfire + description: Example clinical trial data sets formatted for easy use in R. + date_publication: '2021-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=safetyData + url_git: '' +safetyGraphics: + version: 2.1.1 + title: Interactive Graphics for Monitoring Clinical Trial Safety + maintainer: Jeremy Wildfire + description: A framework for evaluation of clinical trial safety. Users can interactively + explore their data using the included 'Shiny' application. + date_publication: '2022-12-14' + bug_reports: https://github.com/SafetyGraphics/safetyGraphics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=safetyGraphics + url_git: https://github.com/SafetyGraphics/safetyGraphics +SafeVote: + version: 1.0.1 + title: Election Vote Counting with Safety Features + maintainer: Clark Thomborson + description: |- + Fork of 'vote_2.3-2', Raftery et al. (2021) + , with additional support + for stochastic experimentation. + date_publication: '2024-10-05' + bug_reports: '' + url: https://cthombor.github.io/SafeVote/ + url_cran: https://CRAN.R-project.org/package=SafeVote + url_git: '' +sageR: + version: 0.6.1 + title: Applied Statistics for Economics and Management with R + maintainer: Frederic Bertrand + description: |- + Datasets and functions for the book "Statistiques pour l’économie et la gestion", "Théorie et applications en entreprise", F. Bertrand, Ch. Derquenne, G. Dufrénot, F. Jawadi and M. Maumy, C. Borsenberger editor, (2021, ISBN:9782807319448, De Boeck Supérieur, Louvain-la-Neuve). + The first chapter of the book is dedicated to an introduction to statistics and their world. + The second chapter deals with univariate exploratory statistics and graphics. + The third chapter deals with bivariate and multivariate exploratory statistics and graphics. + The fourth chapter is dedicated to data exploration with Principal Component Analysis. + The fifth chapter is dedicated to data exploration with Correspondance Analysis. + The sixth chapter is dedicated to data exploration with Multiple Correspondance Analysis. + The seventh chapter is dedicated to data exploration with automatic clustering. + The eighth chapter is dedicated to an introduction to probability theory and classical probability distributions. + The ninth chapter is dedicated to an estimation theory, one-sample and two-sample tests. + The tenth chapter is dedicated to an Gaussian linear model. + The eleventh chapter is dedicated to an introduction to time series. + The twelfth chapter is dedicated to an introduction to probit and logit models. + Various example datasets are shipped with the package as well as some new functions. + date_publication: '2023-03-23' + bug_reports: https://github.com/fbertran/sageR/issues/ + url: https://fbertran.github.io/homepage/ + url_cran: https://CRAN.R-project.org/package=sageR + url_git: https://github.com/fbertran/sageR/ +SAGM: + version: 1.0.0 + title: Spatial Autoregressive Graphical Model + maintainer: Sjoerd Hermes + description: Implements the methodological developments found in Hermes, van Heerwaarden, + and Behrouzi (2023) , and allows for the statistical + modeling of asymmetric between-location effects, as well as within-location effects + using spatial autoregressive graphical models. The package allows for the generation + of spatial weight matrices to capture asymmetric effects for strip-type intercropping + designs, although it can handle any type of spatial data commonly found in other + sciences. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAGM + url_git: '' +SAGMM: + version: 0.2.4 + title: |- + Clustering via Stochastic Approximation and Gaussian Mixture + Models + maintainer: Andrew T. Jones + description: Computes clustering by fitting Gaussian mixture models (GMM) via stochastic + approximation following the methods of Nguyen and Jones (2018) . + It also provides some test data generation and plotting functionality to assist + with this process. + date_publication: '2019-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAGMM + url_git: '' +sahpm: + version: 1.0.1 + title: Variable Selection using Simulated Annealing + maintainer: Arnab Maity + description: Highest posterior model is widely accepted as a good model among available + models. In terms of variable selection highest posterior model is often the true + model. Our stochastic search process SAHPM based on simulated annealing maximization + method tries to find the highest posterior model by maximizing the model space + with respect to the posterior probabilities of the models. This package currently + contains the SAHPM method only for linear models. The codes for GLM will be added + in future. + date_publication: '2022-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sahpm + url_git: '' +sAIC: + version: 1.0.1 + title: Akaike Information Criterion for Sparse Estimation + maintainer: Shuichi Kawano + description: Computes the Akaike information criterion for the generalized linear + models (logistic regression, Poisson regression, and Gaussian graphical models) + estimated by the lasso. + date_publication: '2022-10-18' + bug_reports: '' + url: https://doi.org/10.1214/16-EJS1179 + url_cran: https://CRAN.R-project.org/package=sAIC + url_git: '' +SailoR: + version: '1.2' + title: |- + An Extension of the Taylor Diagram to Two-Dimensional Vector + Data + maintainer: Santos J. González-Rojí + description: A new diagram for the verification of vector variables (wind, current, + etc) generated by multiple models against a set of observations is presented in + this package. It has been designed as a generalization of the Taylor diagram to + two dimensional quantities. It is based on the analysis of the two-dimensional + structure of the mean squared error matrix between model and observations. The + matrix is divided into the part corresponding to the relative rotation and the + bias of the empirical orthogonal functions of the data. The full set of diagnostics + produced by the analysis of the errors between model and observational vector + datasets comprises the errors in the means, the analysis of the total variance + of both datasets, the rotation matrix corresponding to the principal components + in observation and model, the angle of rotation of model-derived empirical orthogonal + functions respect to the ones from observations, the standard deviation of model + and observations, the root mean squared error between both datasets and the squared + two-dimensional correlation coefficient. See the output of function UVError() + in this package. + date_publication: '2020-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SailoR + url_git: '' +SAiVE: + version: 1.0.6 + title: |- + Functions Used for SAiVE Group Research, Collaborations, and + Publications + maintainer: Ghislain de Laplante + description: |- + Holds functions developed by the University of Ottawa's SAiVE + (Spatio-temporal Analysis of isotope Variations in the Environment) + research group with the intention of facilitating the re-use of code, + foster good code writing practices, and to allow others to benefit + from the work done by the SAiVE group. Contributions are welcome via + the 'GitHub' repository by group members as well as non-members. + date_publication: '2024-05-03' + bug_reports: https://github.com/UO-SAiVE/SAiVE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SAiVE + url_git: https://github.com/UO-SAiVE/SAiVE +SAKERNAS: + version: 0.1.0 + title: A National Labor Force Survey of Indonesia + maintainer: Fadhlul Mubarak + description: Surveys to collect employment data so as to obtain data estimates on + the number of employed people, the number of unemployed, and other employment + indicators. + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAKERNAS + url_git: '' +salad: + version: '1.2' + title: Simple Automatic Differentiation + maintainer: Hervé Perdry + description: |- + Handles both vector and matrices, using a flexible S4 class for automatic differentiation. + The method used is forward automatic differentiation. Many functions and methods have been defined, + so that in most cases, functions written without automatic differentiation in mind can be + used without change. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=salad + url_git: '' +SALES: + version: 1.0.2 + title: |- + The (Adaptive) Elastic Net and Lasso Penalized Sparse Asymmetric + Least Squares (SALES) and Coupled Sparse Asymmetric Least + Squares (COSALES) using Coordinate Descent and Proximal + Gradient Algorithms + maintainer: Yuwen Gu + description: |- + A coordinate descent algorithm for computing the solution paths of + the sparse and coupled sparse asymmetric least squares, including the + (adaptive) elastic net and Lasso penalized SALES and COSALES regressions. + date_publication: '2022-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SALES + url_git: https://github.com/knightgu/SALES +salesforcer: + version: 1.0.2 + title: An Implementation of 'Salesforce' APIs Using Tidy Principles + maintainer: Steven M. Mortimer + description: |- + Functions connecting to the 'Salesforce' Platform APIs (REST, SOAP, + Bulk 1.0, Bulk 2.0, Metadata, Reports and Dashboards) + . + "API" is an acronym for "application programming interface". Most all calls + from these APIs are supported as they use CSV, XML or JSON data that can be + parsed into R data structures. For more details please see the 'Salesforce' + API documentation and this package's website + for more information, + documentation, and examples. + date_publication: '2024-11-06' + bug_reports: https://github.com/StevenMMortimer/salesforcer/issues + url: https://stevenmmortimer.github.io/salesforcer/ + url_cran: https://CRAN.R-project.org/package=salesforcer + url_git: https://github.com/StevenMMortimer/salesforcer +salso: + version: 0.3.42 + title: Search Algorithms and Loss Functions for Bayesian Clustering + maintainer: David B. Dahl + description: The SALSO algorithm is an efficient randomized greedy search method + to find a point estimate for a random partition based on a loss function and posterior + Monte Carlo samples. The algorithm is implemented for many loss functions, including + the Binder loss and a generalization of the variation of information loss, both + of which allow for unequal weights on the two types of clustering mistakes. Efficient + implementations are also provided for Monte Carlo estimation of the posterior + expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) + . + date_publication: '2024-09-16' + bug_reports: https://github.com/dbdahl/salso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=salso + url_git: https://github.com/dbdahl/salso +SALTSampler: + version: 1.1.0 + title: Efficient Sampling on the Simplex + maintainer: Scott Vander Wiel + description: |- + The SALTSampler package facilitates Monte Carlo Markov Chain (MCMC) + sampling of random variables on a simplex. A Self-Adjusting Logit Transform + (SALT) proposal is used so that sampling is still efficient even in difficult + cases, such as those in high dimensions or with parameters that differ by orders + of magnitude. Special care is also taken to maintain accuracy even when some + coordinates approach 0 or 1 numerically. Diagnostic and graphic functions are + included in the package, enabling easy assessment of the convergence and mixing + of the chain within the constrained space. + date_publication: '2017-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SALTSampler + url_git: '' +salty: + version: 0.1.1 + title: Turn Clean Data into Messy Data + maintainer: Matthew Lincoln + description: |- + Take real or simulated data and salt it with errors commonly + found in the wild, such as pseudo-OCR errors, Unicode problems, numeric + fields with nonsensical punctuation, bad dates, etc. + date_publication: '2024-08-31' + bug_reports: https://github.com/mdlincoln/salty/issues + url: '' + url_cran: https://CRAN.R-project.org/package=salty + url_git: https://github.com/mdlincoln/salty +SAM: + version: 1.1.3 + title: Sparse Additive Modelling + maintainer: Haoming Jiang + description: |- + Computationally efficient tools for high dimensional predictive + modeling (regression and classification). SAM is short for sparse + additive modeling, and adopts the computationally efficient basis + spline technique. We solve the optimization problems by various + computational algorithms including the block coordinate descent + algorithm, fast iterative soft-thresholding algorithm, and newton method. + The computation is further accelerated by warm-start and active-set tricks. + date_publication: '2021-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAM + url_git: '' +samadb: + version: 0.3.0 + title: South Africa Macroeconomic Database API + maintainer: Sebastian Krantz + description: |- + An R API providing access to a relational database with macroeconomic time series data for South Africa, + obtained from the South African Reserve Bank (SARB) and Statistics South Africa (STATSSA), and updated on a weekly basis + via the EconData platform and automated scraping of the SARB and STATSSA websites. + The database is maintained at the Department of Economics at Stellenbosch University. + date_publication: '2024-05-24' + bug_reports: https://github.com/Stellenbosch-Econometrics/SAMADB-Issues/issues + url: '' + url_cran: https://CRAN.R-project.org/package=samadb + url_git: '' +SAMBA: + version: 0.9.0 + title: |- + Selection and Misclassification Bias Adjustment for Logistic + Regression Models + maintainer: Alexander Rix + description: |2- + + Health research using data from electronic health records (EHR) has gained + popularity, but misclassification of EHR-derived disease status and lack of + representativeness of the study sample can result in substantial bias in + effect estimates and can impact power and type I error for association + tests. Here, the assumed target of inference is the relationship between + binary disease status and predictors modeled using a logistic regression + model. 'SAMBA' implements several methods for obtaining bias-corrected + point estimates along with valid standard errors as proposed in Beesley and + Mukherjee (2020) , currently under review. + date_publication: '2020-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAMBA + url_git: '' +sambia: + version: 0.1.0 + title: A Collection of Techniques Correcting for Sample Selection Bias + maintainer: Norbert Krautenbacher + description: A collection of various techniques correcting statistical models for + sample selection bias is provided. In particular, the resampling-based methods + "stochastic inverse-probability oversampling" and "parametric inverse-probability + bagging" are placed at the disposal which generate synthetic observations for + correcting classifiers for biased samples resulting from stratified random sampling. + For further information, see the article Krautenbacher, Theis, and Fuchs (2017) + . The methods may be used for further purposes where + weighting and generation of new observations is needed. + date_publication: '2018-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sambia + url_git: '' +samc: + version: 4.0.0 + title: Spatial Absorbing Markov Chains + maintainer: Andrew Marx + description: |- + Implements functions for working with absorbing Markov chains. The + implementation is based on the framework described in "Toward a unified + framework for connectivity that disentangles movement and mortality in space + and time" by Fletcher et al. (2019) , which applies + them to spatial ecology. This framework incorporates both resistance and + absorption with spatial absorbing Markov chains (SAMC) to provide several + short-term and long-term predictions for metrics related to connectivity in + landscapes. Despite the ecological context of the framework, this package + can be used in any application of absorbing Markov chains. + date_publication: '2024-10-30' + bug_reports: https://github.com/andrewmarx/samc/issues/ + url: https://andrewmarx.github.io/samc/ + url_cran: https://CRAN.R-project.org/package=samc + url_git: '' +SAME: + version: 0.1.0 + title: Seamless Adaptive Multi-Arm Multi-Stage Enrichment + maintainer: Chengxue Zhong + description: |- + Design a Bayesian seamless multi-arm biomarker-enriched phase II/III + design with the survival endpoint with allowing sample size re-estimation. + James M S Wason, Jean E Abraham, Richard D Baird, Ioannis Gournaris, Anne-Laure Vallier, James D Brenton, Helena M Earl, Adrian P Mander (2015) . + Guosheng Yin, Nan Chen, J. Jack Lee (2018) . + Ying Yuan, Beibei Guo, Mark Munsell, Karen Lu, Amir Jazaeri (2016) . + date_publication: '2023-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAME + url_git: '' +SAMGEP: + version: 0.1.0-1 + title: A Semi-Supervised Method for Prediction of Phenotype Event Times + maintainer: Yuri Ahuja + description: A novel semi-supervised machine learning algorithm to predict phenotype + event times using Electronic Health Record (EHR) data. + date_publication: '2021-01-06' + bug_reports: https://github.com/celehs/SAMGEP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SAMGEP + url_git: https://github.com/celehs/SAMGEP +samon: + version: 4.0.2 + title: Sensitivity Analysis for Missing Data + maintainer: Aidan McDermott + description: In a clinical trial with repeated measures designs, outcomes are often + taken from subjects at fixed time-points. The focus of the trial may be to compare + the mean outcome in two or more groups at some pre-specified time after enrollment. + In the presence of missing data auxiliary assumptions are necessary to perform + such comparisons. One commonly employed assumption is the missing at random assumption + (MAR). The 'samon' package allows the user to perform a (parameterized) sensitivity + analysis of this assumption. In particular it can be used to examine the sensitivity + of tests in the difference in outcomes to violations of the MAR assumption. The + sensitivity analysis can be performed under two scenarios, a) where the data exhibit + a monotone missing data pattern (see the samon() function), and, b) where in addition + to a monotone missing data pattern the data exhibit intermittent missing values + (see the samonIM() function). + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samon + url_git: '' +sampbias: + version: 2.0.0 + title: Evaluating Geographic Sampling Bias in Biological Collections + maintainer: Alexander Zizka + description: 'Evaluating the biasing impact of geographic features such as airports, + cities, roads, rivers in datasets of coordinates based biological collection datasets, + by Bayesian estimation of the parameters of a Poisson process. Enables also spatial + visualization of sampling bias and includes a set of convenience functions for + publication level plotting. Also available as ''shiny'' app. The reference for + the methodology is: Zizka et al. (2020) .' + date_publication: '2024-02-06' + bug_reports: https://github.com/azizka/sampbias/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sampbias + url_git: https://github.com/azizka/sampbias +sampcompR: + version: 0.2.6 + title: Comparing and Visualizing Differences Between Surveys + maintainer: Bjoern Rohr + description: Easily analyze and visualize differences between samples (e.g., benchmark + comparisons, nonresponse comparisons in surveys) on three levels. The comparisons + can be univariate, bivariate or multivariate. On univariate level the variables + of interest of a survey and a comparison survey (i.e. benchmark) are compared, + by calculating one of several difference measures (e.g., relative difference in + mean), and an average difference between the surveys. On bivariate level a function + can calculate significant differences in correlations for the surveys. And on + multivariate levels a function can calculate significant differences in model + coefficients between the surveys of comparison. All of those differences can be + easily plotted and outputted as a table. For more detailed information on the + methods and example use see Rohr, B., Silber, H., & Felderer, B. (2024). Comparing + the Accuracy of Univariate, Bivariate, and Multivariate Estimates across Probability + and Nonprobability Surveys with Population Benchmarks. Sociological Methodology + . + date_publication: '2024-12-08' + bug_reports: '' + url: https://bjoernrohr.github.io/sampcompR/ + url_cran: https://CRAN.R-project.org/package=sampcompR + url_git: '' +sampledatasets: + version: 0.1.0 + title: A Collection of Sample Datasets + maintainer: Renzo Caceres Rossi + description: |- + Provides a collection of sample datasets + on various fields such as automotive performance and safety data to historical demographics and socioeconomic indicators, as well as recreational data. + It serves as a resource for researchers and analysts seeking to perform analyses and derive insights from classic data sets in R. + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sampledatasets + url_git: https://github.com/lightbluetitan/sampledatasets +sampler: + version: 0.2.4 + title: Sample Design, Drawing & Data Analysis Using Data Frames + maintainer: Michael Baldassaro + description: Determine sample sizes, draw samples, and conduct data analysis using + data frames. It specifically enables you to determine simple random sample sizes, + stratified sample sizes, and complex stratified sample sizes using a secondary + variable such as population; draw simple random samples and stratified random + samples from sampling data frames; determine which observations are missing from + a random sample, missing by strata, duplicated within a dataset; and perform data + analysis, including proportions, margins of error and upper and lower bounds for + simple, stratified and cluster sample designs. + date_publication: '2019-09-15' + bug_reports: https://github.com/mbaldassaro/sampler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sampler + url_git: https://github.com/mbaldassaro/sampler +sampleSelection: + version: 1.2-12 + title: Sample Selection Models + maintainer: Arne Henningsen + description: |- + Two-step + and maximum likelihood estimation + of Heckman-type sample selection models: + standard sample selection models (Tobit-2), + endogenous switching regression models (Tobit-5), + sample selection models with binary dependent outcome variable, + interval regression with sample selection (only ML estimation), + and endogenous treatment effects models. + These methods are described in the three vignettes + that are included in this package + and in econometric textbooks such as + Greene (2011, Econometric Analysis, 7th edition, Pearson). + date_publication: '2020-12-15' + bug_reports: '' + url: http://www.sampleSelection.org + url_cran: https://CRAN.R-project.org/package=sampleSelection + url_git: '' +samplesize: + version: 0.2-4 + title: Sample Size Calculation for Various t-Tests and Wilcoxon-Test + maintainer: Ralph Scherer + description: Computes sample size for Student's t-test and for the Wilcoxon-Mann-Whitney + test for categorical data. The t-test function allows paired and unpaired (balanced + / unbalanced) designs as well as homogeneous and heterogeneous variances. The + Wilcoxon function allows for ties. + date_publication: '2016-12-24' + bug_reports: https://github.com/shearer/samplesize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=samplesize + url_git: https://github.com/shearer/samplesize +SampleSize4ClinicalTrials: + version: 0.2.3 + title: |- + Sample Size Calculation for the Comparison of Means or + Proportions in Phase III Clinical Trials + maintainer: Hongchao Qi + description: There are four categories of Phase III clinical trials according to + different research goals, including (1) Testing for equality, (2) Superiority + trial, (3) Non-inferiority trial, and (4) Equivalence trial. This package aims + to help researchers to calculate sample size when comparing means or proportions + in Phase III clinical trials with different research goals. + date_publication: '2021-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SampleSize4ClinicalTrials + url_git: '' +samplesize4surveys: + version: 4.1.1 + title: Sample Size Calculations for Complex Surveys + maintainer: Hugo Andres Gutierrez Rojas + description: |- + Computes the required sample size for estimation of totals, means + and proportions under complex sampling designs. + date_publication: '2020-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samplesize4surveys + url_git: '' +samplesizeCMH: + version: 0.0.3 + title: |- + Power and Sample Size Calculation for the + Cochran-Mantel-Haenszel Test + maintainer: Paul Egeler + description: |2- + + Calculates the power and sample size for Cochran-Mantel-Haenszel tests. + There are also several helper functions for working with probability, + odds, relative risk, and odds ratio values. + date_publication: '2023-12-12' + bug_reports: https://github.com/pegeler/samplesizeCMH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=samplesizeCMH + url_git: https://github.com/pegeler/samplesizeCMH +SampleSizeDiagnostics: + version: 0.1.0 + title: Choosing Sample Size for Evaluating a Diagnostic Test + maintainer: Mohamed Kamal + description: Calculates the sample size needed for evaluating a diagnostic test + based on sensitivity, specificity, prevalence, and desired precision. Based on + Buderer (1996) . + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SampleSizeDiagnostics + url_git: '' +samplesizeestimator: + version: 1.0.0 + title: Calculate Sample Size for Various Scenarios + maintainer: R Amala + description: |- + Calculates sample size for various scenarios, such as sample size + to estimate population proportion with stated absolute or relative + precision, testing a single proportion with a reference value, to estimate + the population mean with stated absolute or relative precision, testing + single mean with a reference value and sample size for comparing two + unpaired or independent means, comparing two paired means, the sample size + For case control studies, estimating the odds ratio with stated precision, + testing the odds ratio with a reference value, estimating relative risk with + stated precision, testing relative risk with a reference value, testing + a correlation coefficient with a specified value, etc. + . + date_publication: '2023-10-10' + bug_reports: https://forms.gle/NcznwYU9yx5HdJu29 + url: '' + url_cran: https://CRAN.R-project.org/package=samplesizeestimator + url_git: '' +samplesizelogisticcasecontrol: + version: 2.0.2 + title: Sample Size and Power Calculations for Case-Control Studies + maintainer: William Wheeler + description: To determine sample size or power for case-control studies to be analyzed + using logistic regression. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samplesizelogisticcasecontrol + url_git: '' +SampleSizeMeans: + version: 1.2.3 + title: Sample Size Calculations for Normal Means + maintainer: Patrick Bélisle + description: |- + Sample size requirements calculation + using three different Bayesian criteria in the + context of designing an experiment to estimate a normal mean or + the difference between two normal means. Functions for + calculation of required sample sizes for the Average Length + Criterion, the Average Coverage Criterion and the Worst Outcome + Criterion in the context of normal means are provided. + Functions for both the fully Bayesian and the mixed + Bayesian/likelihood approaches are provided. + For reference see Joseph L. and Bélisle P. (1997) . + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SampleSizeMeans + url_git: '' +SampleSizeProportions: + version: 1.1.3 + title: |- + Calculating Sample Size Requirements when Estimating the + Difference Between Two Binomial Proportions + maintainer: Patrick Bélisle + description: |- + Sample size requirements calculation + using three different Bayesian criteria in the + context of designing an experiment to estimate the difference + between two binomial proportions. Functions for calculation of + required sample sizes for the Average Length Criterion, the + Average Coverage Criterion and the Worst Outcome Criterion in + the context of binomial observations are provided. In all + cases, estimation of the difference between two binomial + proportions is considered. Functions for both the fully + Bayesian and the mixed Bayesian/likelihood approaches are + provided. + For reference see Joseph L., du Berger R. and Bélisle P. (1997) + . + date_publication: '2023-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SampleSizeProportions + url_git: '' +SampleSizeSingleArmSurvival: + version: 0.1.0 + title: Calculate Sample Size for Single-Arm Survival Studies + maintainer: Mohamed Kamal + description: Provides methods to calculate sample size for single-arm survival studies + using the arcsine transformation, incorporating uniform accrual and exponential + survival assumptions. Includes functionality for detailed numerical integration + and simulation. This method is based on Nagashima et al. (2021) . + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SampleSizeSingleArmSurvival + url_git: '' +sampleVADIR: + version: 1.0.0 + title: Draw Stratified Samples from the VADIR Database + maintainer: Trevor Swanson + description: Affords researchers the ability to draw stratified samples from the + U.S. Department of Veteran's Affairs/Department of Defense Identity Repository + (VADIR) database according to a variety of population characteristics. The VADIR + database contains information for all veterans who were separated from the military + after 1980. The central utility of the present package is to integrate data cleaning + and formatting for the VADIR database with the stratification methods described + by Mahto (2019) . Data from + VADIR are not provided as part of this package. + date_publication: '2021-10-27' + bug_reports: https://github.com/tswanson222/sampleVADIR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sampleVADIR + url_git: https://github.com/tswanson222/sampleVADIR +samplezoo: + version: 1.2.1 + title: Generate Samples with a Variety of Probability Distributions + maintainer: Nicholas Vietto + description: Simplifies the process of generating samples from a variety of probability + distributions, allowing users to quickly create data frames for demonstrations, + troubleshooting, or teaching purposes. Data is available in multiple sizes—small, + medium, and large. For more information, refer to the package documentation. + date_publication: '2025-02-21' + bug_reports: https://github.com/nvietto/samplezoo/issues + url: https://nvietto.github.io/samplezoo/ + url_cran: https://CRAN.R-project.org/package=samplezoo + url_git: https://github.com/nvietto/samplezoo +sampling: + version: '2.10' + title: Survey Sampling + maintainer: Alina Matei + description: Functions to draw random samples using different sampling schemes are + available. Functions are also provided to obtain (generalized) calibration weights, + different estimators, as well some variance estimators. + date_publication: '2023-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sampling + url_git: '' +SamplingBigData: + version: 1.0.0 + title: Sampling Methods for Big Data + maintainer: Jonathan Lisic + description: Select sampling methods for probability samples using large data sets. This + includes spatially balanced sampling in multi-dimensional spaces with any prescribed + inclusion probabilities. All implementations are written in C with efficient data + structures such as k-d trees that easily scale to several million rows on a modern + desktop computer. + date_publication: '2018-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SamplingBigData + url_git: https://github.com/jlisic/SamplingBigData +samplingbook: + version: 1.2.4 + title: Survey Sampling Procedures + maintainer: Juliane Manitz + description: Sampling procedures from the book 'Stichproben - Methoden und praktische + Umsetzung mit R' by Goeran Kauermann and Helmut Kuechenhoff (2010). + date_publication: '2021-04-02' + bug_reports: https://github.com/jmanitz/samplingbook/issues + url: https://www.samplingbook.manitz.org + url_cran: https://CRAN.R-project.org/package=samplingbook + url_git: '' +samplingDataCRT: + version: '1.0' + title: |- + Sampling Data Within Different Study Designs for Cluster + Randomized Trials + maintainer: Diana Trutschel + description: |- + Package provides the possibility to sampling complete datasets + from a normal distribution to simulate cluster randomized trails for different study designs. + date_publication: '2017-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samplingDataCRT + url_git: '' +samplingin: + version: 1.1.1 + title: Dynamic Survey Sampling Solutions + maintainer: Choerul Afifanto + description: |- + A robust solution employing the SRS (Simple Random Sampling), + systematic and PPS (Probability Proportional to Size) sampling + methods, ensuring a methodical and representative selection of data. + Seamlessly allocate predetermined allocations to smaller levels. + date_publication: '2024-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samplingin + url_git: '' +samplingR: + version: 1.0.1 + title: Sampling and Estimation Methods + maintainer: Javier Estévez + description: Functions to take samples of data, sample size estimation and getting + useful estimators such as total, mean, proportion about its population using simple + random, stratified, systematic and cluster sampling. + date_publication: '2023-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samplingR + url_git: '' +SamplingStrata: + version: 1.5-4 + title: |- + Optimal Stratification of Sampling Frames for Multipurpose + Sampling Surveys + maintainer: Giulio Barcaroli + description: 'In the field of stratified sampling design, this package offers an + approach for the determination of the best stratification of a sampling frame, + the one that ensures the minimum sample cost under the condition to satisfy precision + constraints in a multivariate and multidomain case. This approach is based on + the use of the genetic algorithm: each solution (i.e. a particular partition in + strata of the sampling frame) is considered as an individual in a population; + the fitness of all individuals is evaluated applying the Bethel-Chromy algorithm + to calculate the sampling size satisfying precision constraints on the target + estimates. Functions in the package allows to: (a) analyse the obtained results + of the optimisation step; (b) assign the new strata labels to the sampling frame; + (c) select a sample from the new frame accordingly to the best allocation. Functions + for the execution of the genetic algorithm are a modified version of the functions + in the ''genalg'' package. M.Ballin, G.Barcaroli (2020) "R + package SamplingStrata: new developments and extension to Spatial Sampling".' + date_publication: '2022-11-15' + bug_reports: https://github.com/barcaroli/SamplingStrata/issues + url: https://barcaroli.github.io/SamplingStrata/ + url_cran: https://CRAN.R-project.org/package=SamplingStrata + url_git: https://github.com/barcaroli/SamplingStrata/ +samplingVarEst: + version: '1.5' + title: Sampling Variance Estimation + maintainer: Emilio Lopez Escobar + description: Functions to calculate some point estimators and estimate their variance + under unequal probability sampling without replacement. Single and two-stage sampling + designs are considered. Some approximations for the second-order inclusion probabilities + (joint inclusion probabilities) are available (sample and population based). A + variety of Jackknife variance estimators are implemented. Almost every function + is written in C (compiled) code for faster results. The functions incorporate + some performance improvements for faster results with large datasets. + date_publication: '2023-01-14' + bug_reports: '' + url: https://www.quantos.mx/ + url_cran: https://CRAN.R-project.org/package=samplingVarEst + url_git: '' +samplr: + version: 1.0.1 + title: Compare Human Performance to Sampling Algorithms + maintainer: Lucas Castillo + description: Understand human performance from the perspective of sampling, both + looking at how people generate samples and how people use the samples they have + generated. A longer overview and other resources can be found at . + date_publication: '2024-08-19' + bug_reports: https://github.com/lucas-castillo/samplr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=samplr + url_git: https://github.com/lucas-castillo/samplr +samplrData: + version: 1.0.0 + title: Datasets from the SAMPLING Project + maintainer: Lucas Castillo + description: Contains human behaviour datasets collected by the SAMPLING project + (). + date_publication: '2024-06-13' + bug_reports: https://github.com/lucas-castillo/samplrData/issues + url: https://lucas-castillo.github.io/samplrData/ + url_cran: https://CRAN.R-project.org/package=samplrData + url_git: https://github.com/lucas-castillo/samplrData +SAMprior: + version: 2.0.0 + title: Self-Adapting Mixture (SAM) Priors + maintainer: Peng Yang + description: |- + Implementation of the SAM prior and generation of its + operating characteristics for dynamically borrowing information + from historical data. For details, please refer to Yang et al. (2023) + . + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAMprior + url_git: '' +sampsizeval: + version: 1.0.0.0 + title: Sample Size for Validation of Risk Models with Binary Outcomes + maintainer: Menelaos Pavlou + description: Estimation of the required sample size to validate a risk model for + binary outcomes, based on the sample size equations proposed by Pavlou et al. + (2021) . For precision-based sample size calculations, + the user is required to enter the anticipated values of the C-statistic and outcome + prevalence, which can be obtained from a previous study. The user also needs to + specify the required precision (standard error) for the C-statistic, the calibration + slope and the calibration in the large. The calculations are valid under the assumption + of marginal normality for the distribution of the linear predictor. + date_publication: '2021-05-28' + bug_reports: https://github.com/mpavlou/sampsizeval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sampsizeval + url_git: https://github.com/mpavlou/sampsizeval +samr: + version: '3.0' + title: 'SAM: Significance Analysis of Microarrays' + maintainer: Rob Tibshirani + description: Significance Analysis of Microarrays for differential expression analysis, + RNAseq data and related problems. + date_publication: '2018-10-16' + bug_reports: '' + url: https://statweb.stanford.edu/~tibs/SAM + url_cran: https://CRAN.R-project.org/package=samr + url_git: '' +sams: + version: 0.4.3 + title: Merge-Split Samplers for Conjugate Bayesian Nonparametric Models + maintainer: David B. Dahl + description: |- + Markov chain Monte Carlo samplers for posterior simulations of conjugate Bayesian nonparametric + mixture models. Functionality is provided for Gibbs sampling as in Algorithm 3 of Neal (2000) + , restricted Gibbs merge-split sampling as described in Jain & Neal + (2004) , and sequentially-allocated merge-split sampling , as well as + summary and utility functions. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sams + url_git: '' +SAMtool: + version: 1.8.0 + title: Stock Assessment Methods Toolkit + maintainer: Quang Huynh + description: |- + Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. + 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, + model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation. + date_publication: '2024-11-07' + bug_reports: https://github.com/Blue-Matter/SAMtool/issues + url: https://openmse.com + url_cran: https://CRAN.R-project.org/package=SAMtool + url_git: https://github.com/Blue-Matter/SAMtool +SAMTx: + version: 0.3.0 + title: |- + Sensitivity Assessment to Unmeasured Confounding with Multiple + Treatments + maintainer: Jiayi Ji + description: 'A sensitivity analysis approach for unmeasured confounding in observational + data with multiple treatments and a binary outcome. This approach derives the + general bias formula and provides adjusted causal effect estimates in response + to various assumptions about the degree of unmeasured confounding. Nested multiple + imputation is embedded within the Bayesian framework to integrate uncertainty + about the sensitivity parameters and sampling variability. Bayesian Additive + Regression Model (BART) is used for outcome modeling. The causal estimands are + the conditional average treatment effects (CATE) based on the risk difference. For + more details, see paper: Hu L et al. (2020) A flexible sensitivity analysis approach + for unmeasured confounding with multiple treatments and a binary outcome with + application to SEER-Medicare lung cancer data .' + date_publication: '2021-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAMTx + url_git: '' +SAMUR: + version: '1.1' + title: |- + Stochastic Augmentation of Matched Data Using Restriction + Methods + maintainer: Alireza S. Mahani + description: |- + Augmenting a matched data set by generating multiple stochastic, matched samples from the data using a + multi-dimensional histogram constructed from dropping the input matched data into a multi-dimensional grid built on + the full data set. The resulting stochastic, matched sets will likely provide a collectively higher coverage of the full + data set compared to the single matched set. Each stochastic match is without duplication, thus allowing downstream + validation techniques such as cross-validation to be applied to each set without concern for overfitting. + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAMUR + url_git: '' +samurais: + version: 0.1.0 + title: |- + Statistical Models for the Unsupervised Segmentation of + Time-Series ('SaMUraiS') + maintainer: Florian Lecocq + description: |- + Provides a variety of original and flexible user-friendly + statistical latent variable models and unsupervised learning algorithms to + segment and represent time-series data (univariate or multivariate), and + more generally, longitudinal data, which include regime changes. + 'samurais' is built upon the following packages, each of them is an + autonomous time-series segmentation approach: Regression with Hidden + Logistic Process ('RHLP'), Hidden Markov Model Regression ('HMMR'), + Multivariate 'RHLP' ('MRHLP'), Multivariate 'HMMR' ('MHMMR'), Piece-Wise + regression ('PWR'). For the advantages/differences of each of them, the + user is referred to our mentioned paper references. + date_publication: '2019-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=samurais + url_git: https://github.com/fchamroukhi/SaMUraiS +sand: + version: 2.0.0 + title: Statistical Analysis of Network Data with R, 2nd Edition + maintainer: Eric Kolaczyk + description: |- + Data sets and code blocks for the book 'Statistical Analysis of + Network Data with R, 2nd Edition'. + date_publication: '2020-07-02' + bug_reports: https://github.com/kolaczyk/sand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sand + url_git: https://github.com/kolaczyk/sand +sandbox: + version: 0.2.1 + title: Probabilistic Numerical Modelling of Sediment Properties + maintainer: Michael Dietze + description: |- + A flexible framework for definition and application of time/depth- + based rules for sets of parameters for single grains that can be used to + create artificial sediment profiles. Such profiles can be used for virtual + sample preparation and synthetic, for instance, luminescence measurements. + date_publication: '2022-02-25' + bug_reports: https://github.com/coffeemuggler/sandbox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sandbox + url_git: '' +sandwich: + version: 3.1-1 + title: Robust Covariance Matrix Estimators + maintainer: Achim Zeileis + description: |- + Object-oriented software for model-robust covariance matrix estimators. Starting out from the basic + robust Eicker-Huber-White sandwich covariance methods include: heteroscedasticity-consistent (HC) + covariances for cross-section data; heteroscedasticity- and autocorrelation-consistent (HAC) + covariances for time series data (such as Andrews' kernel HAC, Newey-West, and WEAVE estimators); + clustered covariances (one-way and multi-way); panel and panel-corrected covariances; + outer-product-of-gradients covariances; and (clustered) bootstrap covariances. All methods are + applicable to (generalized) linear model objects fitted by lm() and glm() but can also be adapted + to other classes through S3 methods. Details can be found in Zeileis et al. (2020) , + Zeileis (2004) and Zeileis (2006) . + date_publication: '2024-09-15' + bug_reports: https://sandwich.R-Forge.R-project.org/contact.html + url: '' + url_cran: https://CRAN.R-project.org/package=sandwich + url_git: https://sandwich.R-Forge.R-project.org/ +SanFranBeachWater: + version: 0.1.0 + title: |- + Downloads and Tidies the San Francisco Public Utilities + Commission Beach Water Quality Monitoring Program Data + maintainer: Robert Myles McDonnell + description: |2- + + Downloads and tidies the San Francisco Public Utilities Commission Beach Water Quality Monitoring Program data. Data sets can be downloaded per beach, or the raw data can be downloaded. See . + date_publication: '2017-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SanFranBeachWater + url_git: '' +SangerTools: + version: 1.0.2 + title: Tools for Population Health Management Analytics + maintainer: Asif Laldin + description: |- + Created for population health analytics and monitoring. + The functions in this package work best when working with patient level Master Patient Index-like datasets . + Built to be used by NHS bodies and other health service providers. + date_publication: '2022-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SangerTools + url_git: '' +sanic: + version: 0.0.2 + title: Solving Ax = b Nimbly in C++ + maintainer: Nikolas Kuschnig + description: |- + Routines for solving large systems of linear equations and + eigenproblems in R. Direct and iterative solvers from the Eigen C++ library + are made available. Solvers include Cholesky, LU, QR, and Krylov subspace + methods (Conjugate Gradient, BiCGSTAB). Dense and sparse problems are + supported. + date_publication: '2023-08-23' + bug_reports: https://github.com/nk027/sanic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sanic + url_git: https://github.com/nk027/sanic +sanitizers: + version: 0.1.1 + title: |- + C/C++ Source Code to Trigger Address and Undefined Behaviour + Sanitizers + maintainer: Dirk Eddelbuettel + description: |- + Recent gcc and clang compiler versions provide functionality to + test for memory violations and other undefined behaviour; this is often + referred to as "Address Sanitizer" (or 'ASAN') and "Undefined Behaviour + Sanitizer" ('UBSAN'). The Writing R Extension manual describes this in some + detail in Section 4.3 title "Checking Memory Access". + + This feature has to be enabled in the corresponding binary, eg in R, which + is somewhat involved as it also required a current compiler toolchain which + is not yet widely available, or in the case of Windows, not available at all + (via the common Rtools mechanism). + + As an alternative, pre-built Docker containers such as the Rocker container + 'r-devel-san' or the multi-purpose container 'r-debug' can be used. + + This package then provides a means of testing the compiler setup as the + known code failures provides in the sample code here should be detected + correctly, whereas a default build of R will let the package pass. + + The code samples are based on the examples from the Address Sanitizer + Wiki at . + date_publication: '2023-06-11' + bug_reports: https://github.com/eddelbuettel/sanitizers/issues + url: https://dirk.eddelbuettel.com/code/sanitizers.html + url_cran: https://CRAN.R-project.org/package=sanitizers + url_git: https://github.com/eddelbuettel/sanitizers +sanityTracker: + version: 0.1.0 + title: Keeps Track of all Performed Sanity Checks + maintainer: Marsel Scheer + description: |- + During the preparation of data set(s) one usually performs + some sanity checks. The idea is that irrespective of where the + checks are performed, they are centralized by this package in order + to list all at once with examples if a check failed. + date_publication: '2020-04-22' + bug_reports: https://github.com/MarselScheer/sanityTracker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sanityTracker + url_git: https://github.com/MarselScheer/sanityTracker +sanketphonetictranslator: + version: 0.1.0 + title: Phonetic Transliteration Between Hindi and English + maintainer: Sanket Gharat + description: Facilitate phonetic transliteration between different languages. With + support for both Hindi and English, this package provides a way to convert text + between Hindi and English dataset. Whether you're working with multilingual data + or need to convert dataset for analysis or presentation purposes, it offers a + simple and efficient solution and harness the power of phonetic transliteration + in your projects with this versatile package. + date_publication: '2024-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sanketphonetictranslator + url_git: '' +sankey: + version: 1.0.2 + title: Illustrate the Flow of Information or Material + maintainer: Gábor Csárdi + description: Plots that illustrate the flow of information or material. + date_publication: '2017-10-22' + bug_reports: https://github.com/gaborcsardi/sankey/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sankey + url_git: https://github.com/gaborcsardi/sankey#readme +sankeywheel: + version: 0.1.0 + title: Create Dependency Wheels and Sankey Diagrams + maintainer: Zhenxing Cheng + description: By binding R functions and the 'Highcharts' + charting library, 'sankeywheel' package provides a simple way to draw dependency + wheels and sankey diagrams. + date_publication: '2019-10-24' + bug_reports: https://github.com/czxa/sankeywheel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sankeywheel + url_git: https://github.com/czxa/sankeywheel +sanon: + version: '1.6' + title: Stratified Analysis with Nonparametric Covariable Adjustment + maintainer: Atsushi Kawaguchi + description: There are several functions to implement the method for analysis in + a randomized clinical trial with strata with following key features. A stratified + Mann-Whitney estimator addresses the comparison between two randomized groups + for a strictly ordinal response variable. The multivariate vector of such stratified + Mann-Whitney estimators for multivariate response variables can be considered + for one or more response variables such as in repeated measurements and these + can have missing completely at random (MCAR) data. Non-parametric covariance adjustment + is also considered with the minimal assumption of randomization. The p-value for + hypothesis test and confidence interval are provided. + date_publication: '2020-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sanon + url_git: '' +SANple: + version: 0.1.1 + title: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo + maintainer: Francesco Denti + description: |- + Estimate Bayesian nested mixture models via Markov Chain Monte Carlo methods. Specifically, the package implements the common atoms model (Denti et al., 2023), its finite version (D'Angelo et al., 2023), and a hybrid finite-infinite model. + All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyzing the results of the fitting procedure. + References: + Denti, Camerlenghi, Guindani, Mira (2023) , + D’Angelo, Canale, Yu, Guindani (2023) . + date_publication: '2024-06-02' + bug_reports: https://github.com/laura-dangelo/SANple/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SANple + url_git: https://github.com/laura-dangelo/SANple +sansa: + version: 0.0.1 + title: Synthetic Data Generation for Imbalanced Learning in 'R' + maintainer: Murtaza Nasir + description: Machine learning is widely used in information-systems design. Yet, + training algorithms on imbalanced datasets may severely affect performance on + unseen data. For example, in some cases in healthcare, financial, or internet-security + contexts, certain sub-classes are difficult to learn because they are underrepresented + in training data. This 'R' package offers a flexible and efficient solution based + on a new synthetic average neighborhood sampling algorithm ('SANSA'), which, in + contrast to other solutions, introduces a novel “placement” parameter that can + be tuned to adapt to each datasets unique manifestation of the imbalance. More + information about the algorithm's parameters can be found at Nasir et al. (2022) + . + date_publication: '2022-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sansa + url_git: '' +santaR: + version: 1.2.4 + title: Short Asynchronous Time-Series Analysis + maintainer: Arnaud Wolfer + description: |- + A graphical and automated pipeline for the analysis + of short time-series in R ('santaR'). This approach is designed to accommodate asynchronous + time sampling (i.e. different time points for different individuals), + inter-individual variability, noisy measurements and large numbers of variables. + Based on a smoothing splines functional model, 'santaR' is able to detect variables + highlighting significantly different temporal trajectories between study groups. + Designed initially for metabolic phenotyping, 'santaR' is also suited for other Systems Biology + disciplines. Command line and graphical analysis (via a 'shiny' application) enable fast and + parallel automated analysis and reporting, intuitive visualisation and comprehensive plotting + options for non-specialist users. + date_publication: '2024-03-07' + bug_reports: https://github.com/adwolfer/santaR/issues/new + url: https://adwolfer.github.io/santaR/ + url_cran: https://CRAN.R-project.org/package=santaR + url_git: https://github.com/adwolfer/santaR +santoku: + version: 1.0.0 + title: A Versatile Cutting Tool + maintainer: David Hugh-Jones + description: |- + A tool for cutting data into intervals. Allows singleton intervals. + Always includes the whole range of data by default. Flexible labelling. + Convenience functions for cutting by quantiles etc. Handles dates, times, units + and other vectors. + date_publication: '2024-06-04' + bug_reports: https://github.com/hughjonesd/santoku/issues + url: https://hughjonesd.github.io/santoku/ + url_cran: https://CRAN.R-project.org/package=santoku + url_git: https://github.com/hughjonesd/santoku +SANvi: + version: 0.1.1 + title: Fitting Shared Atoms Nested Models via Variational Bayes + maintainer: Francesco Denti + description: |- + An efficient tool for fitting the nested common and shared atoms models using variational Bayes approximate inference for fast computation. Specifically, the package implements the common atoms model (Denti et al., 2023), its finite version (D'Angelo et al., 2023), and a hybrid finite-infinite model. + All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyze the results of the fitting procedure. + References: + Denti, Camerlenghi, Guindani, Mira (2023) , + D’Angelo, Canale, Yu, Guindani (2023) . + date_publication: '2024-05-15' + bug_reports: https://github.com/fradenti/SANvi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SANvi + url_git: https://github.com/fradenti/SANvi +sanzo: + version: 0.1.0 + title: Color Palettes Based on the Works of Sanzo Wada + maintainer: Jacqueline Maasch + description: |- + Inspired by the art and color research of Sanzo Wada (1883-1967), + his "Dictionary Of Color Combinations" (2011, ISBN:978-4861522475), and the + interactive site by Dain M. Blodorn Kim , + this package brings Wada's color combinations to R for easy use in data + visualizations. This package honors 60 of Wada's color combinations: + 20 duos, 20 trios, and 20 quads. + date_publication: '2020-01-12' + bug_reports: https://github.com/jmaasch/sanzo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sanzo + url_git: https://github.com/jmaasch/sanzo +saotd: + version: 0.3.1 + title: Sentiment Analysis of Twitter Data + maintainer: Evan Munson + description: |- + This analytic is an in initial foray into sentiment analysis. + This analytic will allow a user to access the Twitter API (once they create + their own developer account), ingest tweets of their interest, clean / tidy + data, perform topic modeling if interested, compute sentiment scores + utilizing the Bing Lexicon, and output visualizations. + date_publication: '2023-09-04' + bug_reports: https://github.com/evan-l-munson/saotd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saotd + url_git: https://github.com/evan-l-munson/saotd +SAP: + version: '1.0' + title: Statistical Analysis and Programming + maintainer: Hasan Bulut + description: |- + The Hypothesis tests for the means of independent or paired groups. + This package investigates the normality assumption automatically. + Then, it tests the hypothesis tests for two independent or paired group means + by using parametric or non-parametric tests. It uses the Shapiro-Wilk test to + test the normality assumption. For independent two groups, If data comes from + the normal distribution, the package uses the Z or t-test according to whether + variances are known. For paired groups, it uses paired t-test under normal data + sets. If data does not come from the normal distribution, the package uses the + Wilcoxon test for independent and paired cases. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAP + url_git: '' +sapevom: + version: 0.2.0 + title: Group Ordinal Method for Multiple Criteria Decision-Making + maintainer: Raquel Coutinho + description: 'Implementation of SAPEVO-M, a Group Ordinal Method for Multiple Criteria + Decision-Making (MCDM). SAPEVO-M is an acronym for Simple Aggregation of Preferences + Expressed by Ordinal Vectors Group Decision Making. This method provides alternatives + ranking given decision makers'' preferences: criteria preferences and alternatives + preferences for each criterion.This method is described in Gomes et al. (2020) + .' + date_publication: '2021-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sapevom + url_git: '' +sapfluxnetr: + version: 0.1.4 + title: Working with 'Sapfluxnet' Project Data + maintainer: Victor Granda + description: |- + Access, modify, aggregate and plot data from the 'Sapfluxnet' project + (), the first global database of sap flow measurements. + date_publication: '2023-01-25' + bug_reports: https://github.com/sapfluxnet/sapfluxnetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sapfluxnetr + url_git: https://github.com/sapfluxnet/sapfluxnetr +sapo: + version: 0.8.0 + title: Spatial Association of Different Types of Polygon + maintainer: Lucas da Cunha Godoy + description: |- + In ecology, spatial data is often represented using polygons. These + polygons can represent a variety of spatial entities, such as ecological + patches, animal home ranges, or gaps in the forest canopy. Researchers often + need to determine if two spatial processes, represented by these polygons, are + independent of each other. For instance, they might want to test if the home + range of a particular animal species is influenced by the presence of a + certain type of vegetation. To address this, Godoy et al. (2022) + () developed conditional Monte Carlo + tests. These tests are designed to assess spatial independence while taking + into account the shape and size of the polygons. + date_publication: '2024-10-11' + bug_reports: https://github.com/lcgodoy/sapo/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=sapo + url_git: https://github.com/lcgodoy/sapo/ +SAPP: + version: 1.0.9-1 + title: Statistical Analysis of Point Processes + maintainer: Masami Saga + description: Functions for statistical analysis of point processes. + date_publication: '2023-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAPP + url_git: '' +saqgetr: + version: 0.2.21 + title: Import Air Quality Monitoring Data in a Fast and Easy Way + maintainer: Stuart K. Grange + description: |- + A collection of tools to access prepared air quality monitoring + data files from web servers with ease and speed. Air quality data are + sourced from open and publicly accessible repositories and can be found in + these locations: + + and . The web + server space has been provided by Ricardo Energy & Environment. + date_publication: '2021-01-12' + bug_reports: https://github.com/skgrange/saqgetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=saqgetr + url_git: https://github.com/skgrange/saqgetr +SAR: + version: 1.0.3 + title: Smart Adaptive Recommendations + maintainer: Hong Ooi + description: '''Smart Adaptive Recommendations'' (SAR) is the name of a fast, scalable, + adaptive algorithm for personalized recommendations based on user transactions + and item descriptions. It produces easily explainable/interpretable recommendations + and handles "cold item" and "semi-cold user" scenarios. This package provides + two implementations of ''SAR'': a standalone implementation, and an interface + to a web service in Microsoft''s ''Azure'' cloud: . + The former allows fast and easy experimentation, and the latter provides robust + scalability and extra features for production use.' + date_publication: '2020-10-07' + bug_reports: https://github.com/hongooi73/SAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SAR + url_git: https://github.com/hongooi73/SAR +sara4r: + version: 0.1.0 + title: |- + An R-GUI for Spatial Analysis of Surface Runoff using the + NRCS-CN Method + maintainer: Rafael Hernandez-Guzman + description: |- + A Graphical user interface to calculate the rainfall-runoff relation using the Natural Resources Conservation Service - Curve Number method (NRCS-CN method) but include modifications by Hawkins et al., (2002) about the Initial Abstraction. This GUI follows the programming logic of a previously published software (Hernandez-Guzman et al., 2011). It is a raster-based GIS tool that outputs runoff estimates from Land use/land cover and hydrologic soil group maps. + This package has already been published in Journal of Hydroinformatics (Hernandez-Guzman et al., 2021) but it is under constant development at the Institute about Natural Resources Research (INIRENA) from the Universidad Michoacana de San Nicolas de Hidalgo and represents a collaborative effort between the Hydro-Geomatic Lab (INIRENA) with the Environmental Management Lab (CIAD, A.C.). + date_publication: '2023-10-26' + bug_reports: '' + url: https://hydro-geomatic-lab.com/ + url_cran: https://CRAN.R-project.org/package=sara4r + url_git: '' +sarima: + version: 0.9.3 + title: Simulation and Prediction with Seasonal ARIMA Models + maintainer: Georgi N. Boshnakov + description: |- + Functions, classes and methods for time series modelling with ARIMA + and related models. The aim of the package is to provide consistent + interface for the user. For example, a single function autocorrelations() + computes various kinds of theoretical and sample autocorrelations. This is + work in progress, see the documentation and vignettes for the current + functionality. Function sarima() fits extended multiplicative seasonal + ARIMA models with trends, exogenous variables and arbitrary roots on the + unit circle, which can be fixed or estimated (for the algebraic basis for + this see , a paper on the methodology is being prepared). + date_publication: '2024-03-26' + bug_reports: https://github.com/GeoBosh/sarima/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sarima + url_git: https://geobosh.github.io/sarima/(doc)https://github.com/GeoBosh/sarima(devel) +saros: + version: 1.5.1 + title: Semi-Automatic Reporting of Ordinary Surveys + maintainer: Stephan Daus + description: |- + Offers a systematic way for conditional reporting of figures and tables for many + (and bivariate combinations of) variables, typically from survey data. + Contains interactive 'ggiraph'-based + () plotting functions and + data frame-based summary tables (bivariate significance tests, + frequencies/proportions, unique open ended responses, etc) with + many arguments for customization, and extensions possible. Uses a global + options() system for neatly reducing redundant code. + Also contains tools for immediate saving of objects and returning a hashed link to the object, + useful for creating download links to high resolution images upon rendering in 'Quarto'. + Suitable for highly customized reports, primarily intended for survey + research. + date_publication: '2025-02-12' + bug_reports: https://github.com/NIFU-NO/saros/issues + url: https://nifu-no.github.io/saros/ + url_cran: https://CRAN.R-project.org/package=saros + url_git: https://github.com/NIFU-NO/saros +saros.base: + version: 1.0.0 + title: Base Tools for Semi-Automatic Reporting of Ordinary Surveys + maintainer: Stephan Daus + description: |- + Scaffold an entire web-based report using template chunks, based on a small chapter overview and a dataset. + Highly adaptable with prefixes, suffixes, translations, etc. Also contains tools for password-protecting, + e.g. for each organization's report on a website. Developed for the common case of a survey across multiple organizations/sites + where each organization wants to obtain results for their organization compared with everyone else. + See 'saros' () for tools used for authors in the drafted reports. + date_publication: '2025-01-10' + bug_reports: https://github.com/NIFU-NO/saros.base/issues + url: https://nifu-no.github.io/saros.base/ + url_cran: https://CRAN.R-project.org/package=saros.base + url_git: https://github.com/NIFU-NO/saros.base +SARP.compo: + version: 0.1.8 + title: Network-Based Interpretation of Changes in Compositional Data + maintainer: Emmanuel Curis + description: |- + Provides a set of functions to interpret changes in + compositional data based on a network representation of all pairwise ratio + comparisons: computation of all pairwise ratio, construction of a + p-value matrix of all pairwise tests of these ratios between + conditions, conversion of this matrix to a network. + date_publication: '2024-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SARP.compo + url_git: '' +SARP.moodle: + version: 1.0.4 + title: XML Output Functions for Easy Creation of Moodle Questions + maintainer: Emmanuel Curis + description: |- + Provides a set of basic functions for creating Moodle XML + output files suited for importing questions in Moodle (a learning + management system, see for more information). + date_publication: '2023-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SARP.moodle + url_git: '' +sarp.snowprofile: + version: 1.3.2 + title: Snow Profile Analysis for Snowpack and Avalanche Research + maintainer: Pascal Haegeli + description: |- + Analysis and plotting tools for snow profile data produced from manual snowpack + observations and physical snowpack models. The functions in this package support snowpack + and avalanche research by reading various formats of data (including CAAML, SMET, + generic csv, and outputs from the snow cover model SNOWPACK), manipulate the data, and + produce graphics such as stratigraphy and time series profiles. Package developed by + the Simon Fraser University Avalanche Research Program . + Graphics apply visualization concepts from Horton, Nowak, and Haegeli (2020, + ). + date_publication: '2023-03-08' + bug_reports: '' + url: http://www.avalancheresearch.ca + url_cran: https://CRAN.R-project.org/package=sarp.snowprofile + url_git: '' +sarp.snowprofile.alignment: + version: 2.0.2 + title: Snow Profile Alignment, Aggregation, and Clustering + maintainer: Florian Herla + description: |- + Snow profiles describe the vertical (1D) stratigraphy of layered + snow with different layer characteristics, such as grain type, hardness, + deposition date, and many more. Hence, they represent a data format similar + to multivariate time series containing categorical, ordinal, and numerical + data types. Use this package to align snow profiles by matching their + individual layers based on Dynamic Time Warping (DTW). The aligned profiles + can then be assessed with an independent, global similarity measure that is + geared towards avalanche hazard assessment. Finally, through exploiting data + aggregation and clustering methods, the similarity measure provides the + foundation for grouping and summarizing snow profiles according to similar + hazard conditions. In particular, this package allows for averaging large + numbers of snow profiles with DTW Barycenter Averaging and thereby + facilitates the computation of individual layer distributions and summary + statistics that are relevant for avalanche forecasting purposes. + For more background information refer to Herla, Horton, Mair, + and Haegeli (2021) , Herla, Mair, and Haegeli + (2022) , and Horton, Herla, and Haegeli (2024) + . + date_publication: '2024-08-25' + bug_reports: '' + url: https://avalancheresearch.ca/ + url_cran: https://CRAN.R-project.org/package=sarp.snowprofile.alignment + url_git: '' +sarp.snowprofile.pyface: + version: 0.1.3 + title: '''python'' Modules from Snowpack and Avalanche Research' + maintainer: Florian Herla + description: |2- + + The development of post-processing functionality for simulated snow profiles + by the snow and avalanche community is often done in 'python'. This package + aims to make these tools accessible to 'R' users. Currently integrated modules + contain functions to calculate dry snow layer instabilities in support of + avalache hazard assessments following the publications of Richter, Schweizer, + Rotach, and Van Herwijnen (2019) , and Mayer, + Van Herwijnen, Techel, and Schweizer (2022) . + date_publication: '2022-11-01' + bug_reports: '' + url: http://www.avalancheresearch.ca + url_cran: https://CRAN.R-project.org/package=sarp.snowprofile.pyface + url_git: '' +sars: + version: 1.3.7 + title: |- + Fit and Compare Species-Area Relationship Models Using + Multimodel Inference + maintainer: Thomas J. Matthews + description: |- + Implements the basic elements of the multi-model + inference paradigm for up to twenty species-area relationship models (SAR), using simple + R list-objects and functions, as in Triantis et al. 2012 . + The package is scalable and users can easily create their own model and data objects. Additional + SAR related functions are provided. + date_publication: '2024-10-03' + bug_reports: https://github.com/txm676/sars/issues + url: https://txm676.github.io/sars/ + url_cran: https://CRAN.R-project.org/package=sars + url_git: https://github.com/txm676/sars +sarsop: + version: 0.6.15 + title: Approximate POMDP Planning Software + maintainer: Carl Boettiger + description: |- + A toolkit for Partially Observed Markov Decision Processes (POMDP). Provides + bindings to C++ libraries implementing the algorithm SARSOP (Successive Approximations + of the Reachable Space under Optimal Policies) and described in Kurniawati et al (2008), + . This package also provides a high-level interface + for generating, solving and simulating POMDP problems and their solutions. + date_publication: '2024-06-25' + bug_reports: https://github.com/boettiger-lab/sarsop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sarsop + url_git: https://github.com/boettiger-lab/sarsop +sas7bdat: + version: '0.8' + title: sas7bdat Reverse Engineering Documentation + maintainer: Matt Shotwell + description: Documentation and prototypes for the earliest (circa 2010) open-source + effort to reverse engineer the sas7bdat file format. The package includes a prototype + reader for sas7bdat files. However, newer packages may contain more robust readers + for sas7bdat files. + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sas7bdat + url_git: '' +SAScii: + version: 1.0.2 + title: |- + Import ASCII Files Directly into R using Only a 'SAS' Input + Script + maintainer: Anthony Joseph Damico + description: Using any importation code designed for 'SAS' users to read ASCII files + into 'sas7bdat' files, this package parses through the INPUT block of a '.sas' + syntax file to design the parameters needed for a 'read.fwf()' function call. This + allows the user to specify the location of the ASCII (often a '.dat') file and + the location of the 'SAS' syntax file, and then load the data frame directly into + R in just one step. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAScii + url_git: https://github.com/ajdamico/SAScii +SASdates: + version: 0.1.0 + title: Convert the Dates to 'SAS' Formats + maintainer: Mahesh Divakaran + description: |- + Converts the dates to different 'SAS' date formats. In 'SAS' dates are a special case of + numeric values. Each day is assigned a specific numeric value, starting from January 1, 1960. + This date is assigned the date value 0, and the next date has a date value of 1 and so on. + The previous days to this date are represented by -1 , -2 and so on. With this approach, + 'SAS' can represent any date in the future or any date in the past. There are many date + formats used in 'SAS' to represent date-time. Here, we try to develop functions which will + convert the date to different 'SAS' date formats. + date_publication: '2022-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SASdates + url_git: '' +sasfunclust: + version: 1.0.0 + title: Sparse and Smooth Functional Clustering + maintainer: Fabio Centofanti + description: Implements the sparse and smooth functional clustering (SaS-Funclust) + method (Centofanti et al. (2021) ) that aims to classify a sample + of curves into homogeneous groups while jointly detecting the most informative + portions of domain. + date_publication: '2021-04-02' + bug_reports: https://github.com/unina-sfere/sasfunclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sasfunclust + url_git: https://github.com/unina-sfere/sasfunclust +sasLM: + version: 0.10.5 + title: '''SAS'' Linear Model' + maintainer: Kyun-Seop Bae + description: |- + This is a core implementation of 'SAS' procedures for linear models - GLM, REG, ANOVA, TTEST, FREQ, and UNIVARIATE. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that. + Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0). + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sasLM + url_git: '' +SASmarkdown: + version: 0.8.2 + title: '''SAS'' Markdown' + maintainer: Doug Hemken + description: Settings and functions to extend the 'knitr' 'SAS' engine. + date_publication: '2023-03-10' + bug_reports: https://github.com/Hemken/SASmarkdown/issues + url: https://www.ssc.wisc.edu/~hemken/SASworkshops/sas.html#writing-sas-documentation + url_cran: https://CRAN.R-project.org/package=SASmarkdown + url_git: '' +SASmixed: + version: 1.0-4 + title: Data sets from "SAS System for Mixed Models" + maintainer: Steven Walker + description: |- + Data sets and sample lmer analyses corresponding + to the examples in Littell, Milliken, Stroup and Wolfinger + (1996), "SAS System for Mixed Models", SAS Institute. + date_publication: '2014-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SASmixed + url_git: '' +sasr: + version: 0.1.4 + title: '''SAS'' Interface' + maintainer: Liming Li + description: |- + Provides a 'SAS' interface, through + 'SASPy'() and + 'reticulate'(). This package + helps you create 'SAS' sessions, execute 'SAS' code in remote 'SAS' + servers, retrieve execution results and log, and exchange datasets + between 'SAS' and 'R'. It also helps you to install 'SASPy' and + create a configuration file for the connection. Please review the + 'SASPy' license file as instructed so that you comply with its + separate and independent license. + date_publication: '2025-02-27' + bug_reports: https://github.com/insightsengineering/sasr/issues + url: https://insightsengineering.github.io/sasr/latest-tag/ + url_cran: https://CRAN.R-project.org/package=sasr + url_git: https://github.com/insightsengineering/sasr/ +sass: + version: 0.4.9 + title: Syntactically Awesome Style Sheets ('Sass') + maintainer: Carson Sievert + description: |- + An 'SCSS' compiler, powered by the 'LibSass' library. With this, + R developers can use variables, inheritance, and functions to generate + dynamic style sheets. The package uses the 'Sass CSS' extension language, + which is stable, powerful, and CSS compatible. + date_publication: '2024-03-15' + bug_reports: https://github.com/rstudio/sass/issues + url: https://rstudio.github.io/sass/ + url_cran: https://CRAN.R-project.org/package=sass + url_git: https://github.com/rstudio/sass +sassy: + version: 1.2.5 + title: Makes 'R' Easier for Everyone + maintainer: David Bosak + description: |- + A meta-package that aims to make 'R' easier for everyone, + especially programmers who have a background in 'SAS®' software. + This set of packages brings many useful concepts to 'R', including + data libraries, data dictionaries, formats + and format catalogs, a data step, and a traceable log. The 'flagship' + package is a reporting package that can output in text, rich text, 'PDF', + 'HTML', and 'DOCX' file formats. + date_publication: '2024-05-30' + bug_reports: https://github.com/dbosak01/sassy/issues + url: https://r-sassy.org + url_cran: https://CRAN.R-project.org/package=sassy + url_git: https://github.com/dbosak01/sassy +satdad: + version: '1.1' + title: |- + Sensitivity Analysis Tools for Dependence and Asymptotic + Dependence + maintainer: Cécile Mercadier + description: 'Tools for analyzing tail dependence in any sample or in particular + theoretical models. The package uses only theoretical and non parametric methods, + without inference. The primary goals of the package are to provide: (a)symmetric + multivariate extreme value models in any dimension; theoretical and empirical + indices to order tail dependence; theoretical and empirical graphical methods + to visualize tail dependence.' + date_publication: '2023-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=satdad + url_git: '' +sate: + version: 2.3.0 + title: Scientific Analysis of Trial Errors (SATE) + maintainer: Barry Edwards + description: |- + Bundles functions used to analyze the harmfulness of trial errors in criminal trials. + Functions in the Scientific Analysis of Trial Errors ('SATE') package help users estimate the + probability that a jury will find a defendant guilty given jurors' preferences for a guilty + verdict and the uncertainty of that estimate. Users can also compare actual and hypothetical + trial conditions to conduct harmful error analysis. The relationship between individual jurors' + verdict preferences and the probability that a jury returns a guilty verdict has been studied + by Davis (1973) ; MacCoun & Kerr (1988) , + and Devine et el. (2001) , among others. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sate + url_git: '' +satellite: + version: 1.0.5 + title: Handling and Manipulating Remote Sensing Data + maintainer: Florian Detsch + description: |- + Herein, we provide a broad variety of functions which are useful + for handling, manipulating, and visualizing satellite-based remote sensing + data. These operations range from mere data import and layer handling (eg + subsetting), over Raster* typical data wrangling (eg crop, extend), to more + sophisticated (pre-)processing tasks typically applied to satellite imagery + (eg atmospheric and topographic correction). This functionality is + complemented by a full access to the satellite layers' metadata at any + stage and the documentation of performed actions in a separate log file. + Currently available sensors include Landsat 4-5 (TM), 7 (ETM+), and 8 + (OLI/TIRS Combined), and additional compatibility is ensured for the Landsat + Global Land Survey data set. + date_publication: '2024-02-10' + bug_reports: https://github.com/environmentalinformatics-marburg/satellite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=satellite + url_git: https://github.com/environmentalinformatics-marburg/satellite +satin: + version: 1.1.0 + title: Visualisation and Analysis of Ocean Data Derived from Satellites + maintainer: Héctor Villalobos + description: With 'satin' functions, visualisation, data extraction and further + analysis like producing climatologies from several images, and anomalies of satellite + derived ocean data can be easily done. Reading functions can import a user defined + geographical extent of data stored in netCDF files. Currently supported ocean + data sources include NASA's Oceancolor web page , + sensors VIIRS-SNPP; MODIS-Terra; MODIS-Aqua; and SeaWiFS. Available variables + from this source includes chlorophyll concentration, sea surface temperature (SST), + and several others. Data sources specific for SST that can be imported too includes + Pathfinder AVHRR and + GHRSST . In addition, ocean productivity data produced + by Oregon State University + can also be handled previous conversion from HDF4 to HDF5 format. Many other + ocean variables can be processed by importing netCDF data files from two European + Union's Copernicus Marine Service databases , namely + Global Ocean Physical Reanalysis and Global Ocean Biogeochemistry Hindcast. + date_publication: '2022-09-22' + bug_reports: https://github.com/hvillalo/satin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=satin + url_git: https://github.com/hvillalo/satin +satres: + version: 1.1.1 + title: Grouping Satellite Bands by Spectral and Spatial Resolution + maintainer: Jose Samos + description: |- + Given raster files directly downloaded from various websites, + it generates a raster structure where it merges them if they are tiles + of the same scene and classifies them according to their spectral and + spatial resolution for easy access by name. + date_publication: '2024-01-09' + bug_reports: https://github.com/josesamos/satres/issues + url: https://josesamos.github.io/satres/ + url_cran: https://CRAN.R-project.org/package=satres + url_git: https://github.com/josesamos/satres +SaturnCoefficient: + version: '1.4' + title: Statistical Evaluation of UMAP Dimensionality Reductions + maintainer: Davide Chicco + description: |- + A metric expressing the quality of a UMAP layout. This is a + package that contains the Saturn_coefficient() function that reads an + input matrix, its dimensionality reduction produced by UMAP, and + evaluates the quality of this dimensionality reduction by producing a + real value in the [0; 1] interval. We call this real value Saturn + coefficient. A higher value means better dimensionality reduction; a + lower value means worse dimensionality reduction. + Reference: Davide Chicco et al. "The Saturn coefficient for evaluating + the quality of UMAP dimensionality reduction results" (2025, in preparation). + date_publication: '2025-02-14' + bug_reports: https://github.com/davidechicco/SaturnCoefficient_R_package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SaturnCoefficient + url_git: https://github.com/davidechicco/SaturnCoefficient_R_package +saturnin: + version: 1.1.1 + title: Spanning Trees Used for Network Inference + maintainer: Loïc Schwaller + description: Bayesian inference of graphical model structures using spanning trees. + date_publication: '2015-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saturnin + url_git: '' +SAutomata: + version: 0.1.0 + title: Inference and Learning in Stochastic Automata + maintainer: Muhammad Kashif Hanif + description: Machine learning provides algorithms that can learn from data and make + inferences or predictions. Stochastic automata is a class of input/output devices + which can model components. This work provides implementation an inference algorithm + for stochastic automata which is similar to the Viterbi algorithm. Moreover, we + specify a learning algorithm using the expectation-maximization technique and + provide a more efficient implementation of the Baum-Welch algorithm for stochastic + automata. This work is based on Inference and learning in stochastic automata + was by Karl-Heinz Zimmermann(2017) . + date_publication: '2018-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SAutomata + url_git: '' +SAVER: + version: 1.1.2 + title: Single-Cell RNA-Seq Gene Expression Recovery + maintainer: Mo Huang + description: |- + An implementation of a regularized regression prediction and + empirical Bayes method to recover the true gene expression profile in + noisy and sparse single-cell RNA-seq data. See Huang M, et al (2018) + for more details. + date_publication: '2019-11-13' + bug_reports: https://github.com/mohuangx/SAVER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SAVER + url_git: https://github.com/mohuangx/SAVER +savonliquide: + version: 0.2.0 + title: Accessibility Toolbox for 'R' Users + maintainer: Mohamed El Fodil Ihaddaden + description: Provides a toolbox that allows the user to implement accessibility + related concepts. + date_publication: '2021-02-22' + bug_reports: https://github.com/feddelegrand7/savonliquide/issues + url: '' + url_cran: https://CRAN.R-project.org/package=savonliquide + url_git: https://github.com/feddelegrand7/savonliquide +savvyr: + version: 0.1.1 + title: |- + Survival Analysis for AdVerse Events with VarYing Follow-Up + Times + maintainer: Thomas Kuenzel + description: |- + The SAVVY (Survival Analysis for AdVerse Events with VarYing Follow-Up Times) + project is a consortium of academic and pharmaceutical + industry partners that aims to improve the analyses of adverse event (AE) + data in clinical trials through the use of survival techniques appropriately + dealing with varying follow-up times and competing events, see + Stegherr, Schmoor, Beyersmann, et al. (2021) . + Although statistical methodologies have advanced, + in AE analyses often the incidence proportion, the incidence density or a + non-parametric Kaplan-Meier estimator are used, which either ignore censoring or + competing events. This package contains functions to easily conduct the + proposed improved AE analyses. + date_publication: '2024-06-10' + bug_reports: https://github.com/openpharma/savvyr/issues + url: https://openpharma.github.io/savvyr/ + url_cran: https://CRAN.R-project.org/package=savvyr + url_git: '' +sawnuti: + version: 0.1.1 + title: Comparing Sequences with Non-Uniform Time Intervals + maintainer: Alexander Murph + description: 'The SAWNUTI algorithm performs sequence comparison for finite sequences + of discrete events with non-uniform time intervals. Further description of the + algorithm can be found in the paper: A. Murph, A. Flynt, B. R. King (2021). Comparing + finite sequences of discrete events with non-uniform time intervals, Sequential + Analysis, 40(3), 291-313. .' + date_publication: '2021-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sawnuti + url_git: '' +saws: + version: 0.9-7.0 + title: |- + Small-Sample Adjustments for Wald Tests Using Sandwich + Estimators + maintainer: Michael P. Fay + description: Tests coefficients with sandwich estimator of variance and with small + samples. Regression types supported are gee, linear regression, and conditional + logistic regression. + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=saws + url_git: '' +sazedR: + version: 2.0.2 + title: |- + Parameter-Free Domain-Agnostic Season Length Detection in Time + Series + maintainer: Tiago Santos + description: |- + Spectral and Average Autocorrelation Zero Distance Density + ('sazed') is a method for estimating the season length of a + seasonal time series. 'sazed' is aimed at practitioners, as it employs only + domain-agnostic preprocessing and does not depend on parameter tuning or + empirical constants. The computation of 'sazed' relies on the efficient + autocorrelation computation methods suggested by Thibauld Nion (2012, URL: + ) and by + Bob Carpenter (2012, URL: + ). + date_publication: '2020-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sazedR + url_git: https://github.com/mtoller/autocorr_season_length_detection/ +SBAGM: + version: 0.1.0 + title: Search Best ARIMA, GARCH, and MS-GARCH Model + maintainer: Rajeev Ranjan Kumar + description: Get the most appropriate autoregressive integrated moving average, + generalized auto-regressive conditional heteroscedasticity and Markov switching + GARCH model. For method details see Haas M, Mittnik S, Paolella MS (2004). , + Bollerslev T (1986). . + date_publication: '2020-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBAGM + url_git: '' +SBCK: + version: 1.0.0 + title: Statistical Bias Correction Kit + maintainer: Yoann Robin + description: |- + Implementation of several recent multivariate bias correction + methods with a unified interface to facilitate their use. A + description and comparison between methods can be found + in . + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBCK + url_git: https://github.com/yrobink/SBCK +sbd: + version: 0.1.0 + title: Size Biased Distributions + maintainer: Marcus Rowcliffe + description: |- + Fitting and plotting parametric or non-parametric size-biased + non-negative distributions, with optional covariates if parametric. + Rowcliffe, M. et al. (2016) . + date_publication: '2024-06-04' + bug_reports: https://github.com/MarcusRowcliffe/sbd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sbd + url_git: https://github.com/MarcusRowcliffe/sbd +sbde: + version: 1.0-1 + title: Semiparametric Bayesian Density Estimation + maintainer: Surya Tokdar + description: |- + Offers Bayesian semiparametric density estimation + and tail-index estimation for heavy tailed data, by + using a parametric, tail-respecting transformation + of the data to the unit interval and then modeling + the transformed data with a purely nonparametric + logistic Gaussian process density prior. Based on + Tokdar et al. (2022) . + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sbde + url_git: '' +SBdecomp: + version: '1.2' + title: Estimation of the Proportion of SB Explained by Confounders + maintainer: Layla Parast + description: 'Uses parametric and nonparametric methods to quantify the proportion + of the estimated selection bias (SB) explained by each observed confounder when + estimating propensity score weighted treatment effects. Parast, L and Griffin, + BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal + Treatment Effect Estimates". Statistics in Medicine, 39(18): 2447- 2476 .' + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBdecomp + url_git: '' +sbfc: + version: 1.0.3 + title: Selective Bayesian Forest Classifier + maintainer: Viktoriya Krakovna + description: |- + An MCMC algorithm for simultaneous feature selection and classification, + and visualization of the selected features and feature interactions. + An implementation of SBFC by Krakovna, Du and Liu (2015), . + date_publication: '2022-01-15' + bug_reports: https://github.com/vkrakovna/sbfc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sbfc + url_git: https://github.com/vkrakovna/sbfc +sbgcop: + version: '0.980' + title: |- + Semiparametric Bayesian Gaussian Copula Estimation and + Imputation + maintainer: Peter Hoff + description: |- + Estimation and inference for parameters in a Gaussian copula model, + treating the univariate marginal distributions as nuisance + parameters as described in Hoff (2007) . + This package also provides a + semiparametric imputation procedure for missing multivariate + data. + date_publication: '2018-05-29' + bug_reports: '' + url: http://pdhoff.github.io/ + url_cran: https://CRAN.R-project.org/package=sbgcop + url_git: '' +SBI: + version: 0.1.2 + title: Simple Blinding Index for Randomized Controlled Trials + maintainer: David Petroff + description: 'Computes a simple blinding index for randomized controlled trials + introduced in Petroff, Bacak, Dagres, Dilk, Wachter: A simple blinding index for + randomized controlled trials. Contemp Clin Trials Commun. 2024 Nov 26;42:101393. + . PMID: 39686958.' + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBI + url_git: '' +sBIC: + version: 0.2.0 + title: Computing the Singular BIC for Multiple Models + maintainer: Luca Weihs + description: |- + Computes the sBIC for various singular model collections including: + binomial mixtures, factor analysis models, Gaussian mixtures, + latent forests, latent class analyses, and reduced rank regressions. + date_publication: '2016-10-01' + bug_reports: https://github.com/Lucaweihs/sBIC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sBIC + url_git: https://github.com/Lucaweihs/sBIC +SBICgraph: + version: 1.0.0 + title: Structural Bayesian Information Criterion for Graphical Models + maintainer: Quang Nguyen + description: |- + This is the implementation of the novel structural Bayesian information criterion by Zhou, 2020 (under review). + In this method, the prior structure is modeled and incorporated into the Bayesian information criterion framework. + Additionally, we also provide the implementation of a two-step algorithm to generate the candidate model pool. + date_publication: '2021-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBICgraph + url_git: '' +sbl: + version: 0.1.0 + title: |- + Sparse Bayesian Learning for QTL Mapping and Genome-Wide + Association Studies + maintainer: Meiyue Wang + description: Implements sparse Bayesian learning method for QTL mapping and genome-wide + association studies. + date_publication: '2018-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sbl + url_git: '' +sbm: + version: 0.4.7 + title: Stochastic Blockmodels + maintainer: Julien Chiquet + description: |- + A collection of tools and functions to adjust a variety of stochastic blockmodels (SBM). + Supports at the moment Simple, Bipartite, 'Multipartite' and Multiplex SBM (undirected or directed with Bernoulli, Poisson or Gaussian emission laws on the edges, and possibly covariate for Simple and Bipartite SBM). See Léger (2016) , 'Barbillon et al.' (2020) and 'Bar-Hen et al.' (2020) . + date_publication: '2024-09-16' + bug_reports: https://github.com/GrossSBM/sbm/issues + url: https://grosssbm.github.io/sbm/ + url_cran: https://CRAN.R-project.org/package=sbm + url_git: '' +SBmedian: + version: 0.1.1 + title: Scalable Bayes with Median of Subset Posteriors + maintainer: Kisung You + description: Median-of-means is a generic yet powerful framework for scalable and + robust estimation. A framework for Bayesian analysis is called M-posterior, which + estimates a median of subset posterior measures. For general exposition to the + topic, see the paper by Minsker (2015) . + date_publication: '2021-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBmedian + url_git: '' +sbmSDP: + version: '0.2' + title: |- + Semidefinite Programming for Fitting Block Models of Equal Block + Sizes + maintainer: Arash A. Amini + description: An ADMM implementation of SDP-1, a semidefinite programming relaxation + of the maximum likelihood estimator for fitting a block model. SDP-1 has a tendency + to produce equal-sized blocks and is ideal for producing a form of network histogram + approximating a nonparametric graphon model. Alternatively, it can be used for + community detection. (This is experimental code, proceed with caution.) + date_publication: '2015-06-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sbmSDP + url_git: '' +SBMSplitMerge: + version: 1.1.1 + title: Inference for a Generalised SBM with a Split Merge Sampler + maintainer: Matthew Ludkin + description: 'Inference in a Bayesian framework for a generalised stochastic block + model. The generalised stochastic block model (SBM) can capture group structure + in network data without requiring conjugate priors on the edge-states. Two sampling + methods are provided to perform inference on edge parameters and block structure: + a split-merge Markov chain Monte Carlo algorithm and a Dirichlet process sampler. + Green, Richardson (2001) ; Neal (2000) ; + Ludkin (2019) .' + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBMSplitMerge + url_git: '' +SBMTrees: + version: '1.2' + title: |- + Sequential Imputation with Bayesian Trees Mixed-Effects Models + for Longitudinal Data + maintainer: Jungang Zou + description: Implements a sequential imputation framework using Bayesian Mixed-Effects + Trees ('SBMTrees') for handling missing data in longitudinal studies. The package + supports a variety of models, including non-linear relationships and non-normal + random effects and residuals, leveraging Dirichlet Process priors for increased + flexibility. Key features include handling Missing at Random (MAR) longitudinal + data, imputation of both covariates and outcomes, and generating posterior predictive + samples for further analysis. The methodology is designed for applications in + epidemiology, biostatistics, and other fields requiring robust handling of missing + data in longitudinal settings. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBMTrees + url_git: '' +SBN: + version: 1.0.0 + title: Generate Stochastic Branching Networks + maintainer: Finnbar Lee + description: Generate Stochastic Branching Networks ('SBNs'). Used to model the + branching structure of rivers. + date_publication: '2022-01-17' + bug_reports: '' + url: https://flee598.github.io/SBN/ + url_cran: https://CRAN.R-project.org/package=SBN + url_git: '' +sbo: + version: 0.5.0 + title: Text Prediction via Stupid Back-Off N-Gram Models + maintainer: Valerio Gherardi + description: Utilities for training and evaluating text predictors based on Stupid + Back-Off N-gram models (Brants et al., 2007, ). + date_publication: '2020-12-05' + bug_reports: https://github.com/vgherard/sbo/issues + url: https://vgherard.github.io/sbo/ + url_cran: https://CRAN.R-project.org/package=sbo + url_git: https://github.com/vgherard/sbo +sboost: + version: 0.1.2 + title: Machine Learning with AdaBoost on Decision Stumps + maintainer: Jadon Wagstaff + description: |- + Creates classifier for binary outcomes using Adaptive Boosting + (AdaBoost) algorithm on decision stumps with a fast C++ implementation. + For a description of AdaBoost, see Freund and Schapire (1997) + . This type of classifier is nonlinear, but + easy to interpret and visualize. Feature vectors may be a combination of + continuous (numeric) and categorical (string, factor) elements. Methods + for classifier assessment, predictions, and cross-validation also included. + date_publication: '2022-05-26' + bug_reports: https://github.com/jadonwagstaff/sboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sboost + url_git: https://github.com/jadonwagstaff/sboost +sbrl: + version: '1.4' + title: Scalable Bayesian Rule Lists Model + maintainer: Hongyu Yang + description: An efficient implementation of Scalable Bayesian Rule Lists Algorithm, + a competitor algorithm for decision tree algorithms; see Hongyu Yang, Cynthia + Rudin, Margo Seltzer (2017) . + It builds from pre-mined association rules and have a logical structure identical + to a decision list or one-sided decision tree. Fully optimized over rule lists, + this algorithm strikes practical balance between accuracy, interpretability, and + computational speed. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sbrl + url_git: '' +SBSDiff: + version: 0.1.0 + title: Satorra-Bentler Scaled Chi-Squared Difference Test + maintainer: Frank D. Mann + description: Calculates a Satorra-Bentler scaled chi-squared difference test between + nested models that were estimated using maximum likelihood (ML) with robust standard + errors, which cannot be calculated the traditional way. For details see Satorra + & Bentler (2001) and Satorra & Bentler (2010) . + This package may be particularly helpful when used in conjunction with 'Mplus' + software, specifically when implementing the complex survey option. In such cases, + the model estimator in 'Mplus' defaults to ML with robust standard errors. + date_publication: '2018-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SBSDiff + url_git: '' +sbtools: + version: 1.3.2 + title: USGS ScienceBase Tools + maintainer: David Blodgett + description: |- + Tools for interacting with U.S. Geological Survey ScienceBase + interfaces. ScienceBase is a data cataloging and + collaborative data management platform. Functions included for querying + ScienceBase, and creating and fetching datasets. + date_publication: '2024-03-21' + bug_reports: https://github.com/DOI-USGS/sbtools/issues + url: https://doi-usgs.github.io/sbtools/ + url_cran: https://CRAN.R-project.org/package=sbtools + url_git: https://github.com/DOI-USGS/sbtools +sbw: + version: 1.1.9 + title: Stable Balancing Weights for Causal Inference and Missing Data + maintainer: Jose R. Zubizarreta + description: Implements the Stable Balancing Weights by Zubizarreta (2015) . + These are the weights of minimum variance that approximately balance the empirical + distribution of the observed covariates. For an overview, see Chattopadhyay, Hase + and Zubizarreta (2020) . To solve the optimization problem + in 'sbw', the default solver is 'quadprog', which is readily available through + CRAN. The solver 'osqp' is also posted on CRAN. To enhance the performance of + 'sbw', users are encouraged to install other solvers such as 'gurobi' and 'Rmosek', + which require special installation. For the installation of gurobi and pogs, please + follow the instructions at + and . + date_publication: '2024-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sbw + url_git: '' +SC.MEB: + version: '1.1' + title: |- + Spatial Clustering with Hidden Markov Random Field using + Empirical Bayes + maintainer: Yi Yang + description: Spatial clustering with hidden markov random field fitted via EM algorithm, + details of which can be found in Yi Yang (2021) . + It is not only computationally efficient and scalable to the sample size increment, + but also is capable of choosing the smoothness parameter and the number of clusters + as well. + date_publication: '2021-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SC.MEB + url_git: '' +SC2API: + version: 1.0.0 + title: Blizzard SC2 API Wrapper + maintainer: Samuel Morrissette + description: A wrapper for Blizzard's Starcraft II (a 2010 real-time strategy game) + Application Programming Interface (API). All documented API calls are implemented + in an easy-to-use and consistent manner. + date_publication: '2020-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SC2API + url_git: '' +sc2sc: + version: 0.0.1-14 + title: Spatial Transfer of Statistics among Spanish Census Sections + maintainer: Jose M. Pavía + description: |- + Transfers/imputes statistics among Spanish spatial polygons (census sections or postal code areas) from different moments in time (2001-2023) without need of spatial files, just linking statistics to the ID codes of the spatial units. + The data available in the census sections of a partition/division (cartography) into force in a moment of time is transferred to the census sections of another partition/division employing the geometric approach (also known as areal weighting or polygon overlay). + References: + Goerlich (2022) . + Pavía and Cantarino (2017a, b) , . + Pérez and Pavía (2024a, b) , . + Acknowledgements: + The authors wish to thank Consellería de Educación, Universidades y Empleo, Generalitat Valenciana (grant AICO/2021/257), Ministerio de Economía e Innovación (grant PID2021-128228NB-I00) and Fundación Mapfre for supporting this research. + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sc2sc + url_git: '' +sca: + version: 0.9-2 + title: Simple Component Analysis + maintainer: Martin Maechler + description: |- + Simple Component Analysis (SCA) often provides much more + interpretable components than Principal Components (PCA) while still + representing much of the variability in the data. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sca + url_git: '' +scaffolder: + version: 0.0.1 + title: |- + Scaffolding Interfaces to Packages in Other Programming + Languages + maintainer: Yuan Tang + description: |- + Comprehensive set of tools for scaffolding R + interfaces to modules, classes, functions, and documentations + written in other programming languages, such as 'Python'. + date_publication: '2020-03-20' + bug_reports: https://github.com/terrytangyuan/scaffolder/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scaffolder + url_git: https://github.com/terrytangyuan/scaffolder +scagnostics: + version: 0.2-6 + title: Compute scagnostics - scatterplot diagnostics + maintainer: Simon Urbanek + description: Calculates graph theoretic scagnostics. Scagnostics describe various + measures of interest for pairs of variables, based on their appearance on a scatterplot. They + are useful tool for discovering interesting or unusual scatterplots from a scatterplot + matrix, without having to look at every individual plot. + date_publication: '2022-03-16' + bug_reports: '' + url: https://www.rforge.net/scagnostics/ + url_cran: https://CRAN.R-project.org/package=scagnostics + url_git: '' +scalablebayesm: + version: '0.2' + title: |- + Distributed Markov Chain Monte Carlo for Bayesian Inference in + Marketing + maintainer: Federico Bumbaca + description: |- + Estimates unit-level and population-level parameters from a hierarchical model in marketing applications. The package includes: + Hierarchical Linear Models with a mixture of normals prior and covariates, + Hierarchical Multinomial Logits with a mixture of normals prior and covariates, + Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates. For more details, see Bumbaca, F. (Rico), Misra, S., & Rossi, P. E. (2020) "Scalable Target Marketing: Distributed Markov Chain Monte Carlo for Bayesian Hierarchical Models". Journal of Marketing Research, 57(6), 999-1018. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scalablebayesm + url_git: '' +scaleAlign: + version: 1.0.0.0 + title: |- + Scale Alignment for Between-Items Multidimensional Rasch Family + Models + maintainer: Leah Feuerstahler + description: |- + Scale alignment is a new procedure for rescaling dimensions of + between-items multidimensional Rasch family models so that dimensions scores + can be compared directly (Feuerstahler & Wilson, 2019; under review) + . This package includes functions for implementing + delta-dimensional alignment (DDA) and logistic regression alignment (LRA) + for dichotomous or polytomous data. This function also includes a wrapper + for models fit using the 'TAM' package. + date_publication: '2020-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scaleAlign + url_git: '' +scaleboot: + version: 1.0-1 + title: Approximately Unbiased P-Values via Multiscale Bootstrap + maintainer: Hidetoshi Shimodaira + description: |- + Calculating approximately unbiased (AU) p-values + from multiscale bootstrap probabilities. See + Shimodaira (2004) , + Shimodaira (2008) , + Terada ans Shimodaira (2017) , and + Shimodaira and Terada (2019) . + date_publication: '2019-12-04' + bug_reports: '' + url: http://stat.sys.i.kyoto-u.ac.jp/prog/scaleboot/ + url_cran: https://CRAN.R-project.org/package=scaleboot + url_git: '' +Scalelink: + version: '1.0' + title: Create Scale Linkage Scores + maintainer: Chris Charlton + description: Perform a 'probabilistic' linkage of two data files using a scaling + procedure using the methods described in Goldstein, H., Harron, K. and Cortina-Borja, + M. (2017) . + date_publication: '2019-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Scalelink + url_git: '' +scales: + version: 1.3.0 + title: Scale Functions for Visualization + maintainer: Thomas Lin Pedersen + description: |- + Graphical scales map data to aesthetics, and provide methods + for automatically determining breaks and labels for axes and legends. + date_publication: '2023-11-28' + bug_reports: https://github.com/r-lib/scales/issues + url: https://scales.r-lib.org + url_cran: https://CRAN.R-project.org/package=scales + url_git: https://github.com/r-lib/scales +ScaleSpikeSlab: + version: '1.0' + title: Scalable Spike-and-Slab + maintainer: Niloy Biswas + description: A scalable Gibbs sampling implementation for high dimensional Bayesian + regression with the continuous spike-and-slab prior. Niloy Biswas, Lester Mackey + and Xiao-Li Meng, "Scalable Spike-and-Slab" (2022) . + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ScaleSpikeSlab + url_git: '' +scalpel: + version: 1.0.3 + title: Processes Calcium Imaging Data + maintainer: Ashley Petersen + description: 'Identifies the locations of neurons, and estimates their calcium concentrations + over time using the SCALPEL method proposed in Petersen, Ashley; Simon, Noah; + Witten, Daniela. SCALPEL: Extracting neurons from calcium imaging data. Ann. Appl. + Stat. 12 (2018), no. 4, 2430--2456. . .' + date_publication: '2021-02-03' + bug_reports: '' + url: www.ajpete.com/software + url_cran: https://CRAN.R-project.org/package=scalpel + url_git: '' +scalreg: + version: 1.0.1 + title: Scaled Sparse Linear Regression + maintainer: Tingni Sun + description: Algorithms for fitting scaled sparse linear regression and estimating + precision matrices. + date_publication: '2019-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scalreg + url_git: '' +scam: + version: 1.2-18 + title: Shape Constrained Additive Models + maintainer: Natalya Pya + description: |- + Generalized additive models under shape + constraints on the component functions of the linear predictor. + Models can include multiple shape-constrained (univariate + and bivariate) and unconstrained terms. Routines of the + package 'mgcv' are used to set up the model matrix, print, + and plot the results. Multiple smoothing parameter + estimation by the Generalized Cross Validation or similar. + See Pya and Wood (2015) + for an overview. A broad selection of shape-constrained + smoothers, linear functionals of smooths with shape constraints, + and Gaussian models with AR1 residuals. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scam + url_git: '' +scan: + version: 0.63.0 + title: |- + Single-Case Data Analyses for Single and Multiple Baseline + Designs + maintainer: Juergen Wilbert + description: |- + A collection of procedures for analysing, visualising, + and managing single-case data. These include piecewise linear regression + models, multilevel models, overlap indices ('PND', 'PEM', 'PAND', 'PET', 'tau-u', + 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions + support outlier detection, handling missing values, scaling, and custom transformations. + An export function helps to generate + html, word, and latex tables in a publication friendly style. More details can be + found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2025) + . + date_publication: '2025-03-01' + bug_reports: https://github.com/jazznbass/scan/issues + url: https://jazznbass.github.io/scan-Book/ + url_cran: https://CRAN.R-project.org/package=scan + url_git: https://github.com/jazznbass/scan/ +scAnnotate: + version: '0.3' + title: |- + An Automated Cell Type Annotation Tool for Single-Cell + RNA-Sequencing Data + maintainer: Xuekui Zhang + description: 'An entirely data-driven cell type annotation tools, which requires + training data to learn the classifier, but not biological knowledge to make subjective + decisions. It consists of three steps: preprocessing training and test data, model + fitting on training data, and cell classification on test data. See Xiangling + Ji,Danielle Tsao, Kailun Bai, Min Tsao, Li Xing, Xuekui Zhang.(2022) + for more details.' + date_publication: '2024-03-14' + bug_reports: '' + url: https://doi.org/10.1101/2022.02.19.481159 + url_cran: https://CRAN.R-project.org/package=scAnnotate + url_git: '' +scanstatistics: + version: 1.1.1 + title: Space-Time Anomaly Detection using Scan Statistics + maintainer: Paul Romer Present + description: |- + Detection of anomalous space-time clusters using the scan + statistics methodology. Focuses on prospective surveillance of data streams, + scanning for clusters with ongoing anomalies. Hypothesis testing is made + possible by Monte Carlo simulation. Allévius (2018) . + date_publication: '2023-01-26' + bug_reports: https://github.com/promerpr/scanstatistics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scanstatistics + url_git: https://github.com/promerpr/scanstatistics +scape: + version: 2.3.5 + title: Statistical Catch-at-Age Plotting Environment + maintainer: Arni Magnusson + description: |- + Import, plot, and diagnose results from statistical + catch-at-age models, used in fisheries stock assessment. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scape + url_git: https://github.com/arni-magnusson/scape +scaper: + version: 0.1.0 + title: |- + Single Cell Transcriptomics-Level Cytokine Activity Prediction + and Estimation + maintainer: Azka Javaid + description: 'Generates cell-level cytokine activity estimates using relevant information + from gene sets constructed with the ''CytoSig'' and the ''Reactome'' databases + and scored using the modified ''Variance-adjusted Mahalanobis (VAM)'' framework + for single-cell RNA-sequencing (scRNA-seq) data. ''CytoSig'' database is described + in: Jiang at al., (2021) . ''Reactome'' database + is described in: Gillespie et al., (2021) . The ''VAM'' + method is outlined in: Frost (2020) .' + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scaper + url_git: '' +scapesClassification: + version: 1.0.0 + title: User-Defined Classification of Raster Surfaces + maintainer: Gerald H. Taranto + description: |- + Series of algorithms to translate users' mental models of seascapes, + landscapes and, more generally, of geographic features into computer representations + (classifications). Spaces and geographic objects are classified with user-defined + rules taking into account spatial data as well as spatial relationships among + different classes and objects. + date_publication: '2022-03-16' + bug_reports: https://github.com/ghTaranto/scapesClassification/issues + url: https://ghtaranto.github.io/scapesClassification/ + url_cran: https://CRAN.R-project.org/package=scapesClassification + url_git: https://github.com/ghTaranto/scapesClassification +scapGNN: + version: 0.1.4 + title: |- + Graph Neural Network-Based Framework for Single Cell Active + Pathways and Gene Modules Analysis + maintainer: Xudong Han + description: It is a single cell active pathway analysis tool based on the graph + neural network (F. Scarselli (2009) ; Thomas N. + Kipf (2017) ) to construct the gene-cell association network, + infer pathway activity scores from different single cell modalities data, integrate + multiple modality data on the same cells into one pathway activity score matrix, + identify cell phenotype activated gene modules and parse association networks + of gene modules under multiple cell phenotype. In addition, abundant visualization + programs are provided to display the results. + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scapGNN + url_git: '' +scar: + version: 0.2-2 + title: |- + Shape-Constrained Additive Regression: a Maximum Likelihood + Approach + maintainer: Yining Chen + description: 'Computes the maximum likelihood estimator of the generalised additive + and index regression with shape constraints. Each additive component function + is assumed to obey one of the nine possible shape restrictions: linear, increasing, + decreasing, convex, convex increasing, convex decreasing, concave, concave increasing, + or concave decreasing. For details, see Chen and Samworth (2016) .' + date_publication: '2022-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scar + url_git: '' +scaRabee: + version: 1.1-4 + title: Optimization Toolkit for Pharmacokinetic-Pharmacodynamic Models + maintainer: Sebastien Bihorel + description: |- + A port of the Scarabee toolkit originally written as a + Matlab-based application. scaRabee provides a framework for simulation and optimization + of pharmacokinetic-pharmacodynamic models at the individual and population level. + It is built on top of the neldermead package, which provides the direct search + algorithm proposed by Nelder and Mead for model optimization. + date_publication: '2022-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scaRabee + url_git: '' +scatr: + version: 1.0.1 + title: Create Scatter Plots with Marginal Density or Box Plots + maintainer: Ravi Selker + description: |- + Allows you to make clean, good-looking scatter plots with the option to + easily add marginal density or box plots on the axes. It is also available as a module for 'jamovi' + (see for more information). 'Scatr' is based on the + 'cowplot' package by Claus O. Wilke and the 'ggplot2' package by Hadley Wickham. + date_publication: '2017-12-05' + bug_reports: https://github.com/raviselker/scatr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scatr + url_git: https://github.com/raviselker/scatr +scatterbar: + version: 0.1.0 + title: Scattered Stacked Bar Chart Plots + maintainer: Dee Velazquez + description: Provides a powerful and flexible tool for visualizing proportional + data across spatially resolved contexts. By combining the concepts of scatter + plots and stacked bar charts, 'scatterbar' allows users to create scattered bar + chart plots, which effectively display the proportions of different categories + at each (x, y) location. This visualization is particularly useful for applications + where understanding the distribution of categories across spatial coordinates + is essential. This package features automatic determination of optimal scaling + factors based on data, customizable scaling and padding options for both x and + y axes, flexibility to specify custom colors for each category, options to customize + the legend title, and integration with 'ggplot2' for robust and high-quality visualizations. + For more details, see Velazquez et al. (2024) . + date_publication: '2024-11-25' + bug_reports: https://github.com/JEFworks-Lab/scatterbar/issues + url: http://jef.works/scatterbar/ + url_cran: https://CRAN.R-project.org/package=scatterbar + url_git: https://github.com/JEFworks-Lab/scatterbar +scatterD3: + version: 1.0.1 + title: D3 JavaScript Scatterplot from R + maintainer: Julien Barnier + description: |- + Creates 'D3' 'JavaScript' scatterplots from 'R' with interactive + features : panning, zooming, tooltips, etc. + date_publication: '2021-10-06' + bug_reports: https://github.com/juba/scatterD3/issues + url: https://juba.github.io/scatterD3/ + url_cran: https://CRAN.R-project.org/package=scatterD3 + url_git: '' +ScatterDensity: + version: 0.0.4 + title: Density Estimation and Visualization of 2D Scatter Plots + maintainer: Michael Thrun + description: The user has the option to utilize the two-dimensional density estimation + techniques called smoothed density published by Eilers and Goeman (2004) , + and pareto density which was evaluated for univariate data by Thrun, Gehlert and + Ultsch, 2020 . Moreover, it provides visualizations + of the density estimation in the form of two-dimensional scatter plots in which + the points are color-coded based on increasing density. Colors are defined by + the one-dimensional clustering technique called 1D distribution cluster algorithm + (DDCAL) published by Lux and Rinderle-Ma (2023) . + date_publication: '2023-10-09' + bug_reports: https://github.com/Mthrun/ScatterDensity/issues + url: https://www.deepbionics.org/ + url_cran: https://CRAN.R-project.org/package=ScatterDensity + url_git: '' +scattermore: + version: '1.2' + title: Scatterplots with More Points + maintainer: Mirek Kratochvil + description: |- + C-based conversion of large scatterplot data to rasters plus other + operations such as data blurring or data alpha blending. Speeds up + plotting of data with millions of points. + date_publication: '2023-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scattermore + url_git: '' +scatterpie: + version: 0.2.4 + title: Scatter Pie Plot + maintainer: Guangchuang Yu + description: Creates scatterpie plots, especially useful for plotting pies on a + map. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scatterpie + url_git: '' +scatterplot3d: + version: 0.3-44 + title: 3D Scatter Plot + maintainer: Uwe Ligges + description: Plots a three dimensional (3D) point cloud. + date_publication: '2023-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scatterplot3d + url_git: '' +scatterPlotMatrix: + version: 0.3.0 + title: '`htmlwidget` for a Scatter Plot Matrix' + maintainer: David Chazalviel + description: Create a scatter plot matrix, using `htmlwidgets` package and `d3.js`. + date_publication: '2024-06-17' + bug_reports: https://ifpen-gitlab.appcollaboratif.fr/detocs/scatterplotmatrix/-/issues + url: https://ifpen-gitlab.appcollaboratif.fr/detocs/scatterplotmatrix + url_cran: https://CRAN.R-project.org/package=scatterPlotMatrix + url_git: '' +SCBiclust: + version: 1.0.1 + title: |- + Identifies Mean, Variance, and Hierarchically Clustered + Biclusters + maintainer: Erika S. Helgeson + description: Identifies a bicluster, a submatrix of the data such that the features + and observations within the submatrix differ from those not contained in submatrix, + using a two-step method. In the first step, observations in the bicluster are identified + to maximize the sum of weighted between cluster feature differences. The method + is described in Helgeson et al. (2020) . 'SCBiclust' can + be used to identify biclusters which differ based on feature means, feature variances, + or more general differences. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCBiclust + url_git: '' +scBio: + version: 0.1.6 + title: |- + Single Cell Genomics for Enhancing Cell Composition Inference + from Bulk Genomics Data + maintainer: Amit Frishberg + description: Cellular population mapping (CPM) a deconvolution algorithm in which + single-cell genomics is required in only one or a few samples, where in other + samples of the same tissue, only bulk genomics is measured and the underlying + fine resolution cellular heterogeneity is inferred. + date_publication: '2020-05-20' + bug_reports: https://github.com/amitfrish/scBio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scBio + url_git: https://github.com/amitfrish/scBio +SCBmeanfd: + version: 1.2.2 + title: Simultaneous Confidence Bands for the Mean of Functional Data + maintainer: David Degras + description: Statistical methods for estimating and inferring the mean of functional + data. The methods include simultaneous confidence bands, local polynomial fitting, bandwidth + selection by plug-in and cross-validation, goodness-of-fit tests for parametric + models, equality tests for two-sample problems, and plotting functions. + date_publication: '2016-12-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCBmeanfd + url_git: '' +scBSP: + version: 1.0.0 + title: |- + A Fast Tool for Single-Cell Spatially Variable Genes + Identifications on Large-Scale Data + maintainer: Jinpu Li + description: |- + Identifying spatially variable genes is critical in linking molecular cell functions + with tissue phenotypes. This package utilizes a granularity-based dimension-agnostic tool, + single-cell big-small patch (scBSP), implementing sparse matrix operation and KD tree + methods for distance calculation, for the identification of spatially variable genes on + large-scale data. The detailed description of this method is available at Wang, J. + and Li, J. et al. 2023 (Wang, J. and Li, J. (2023), ). + date_publication: '2024-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scBSP + url_git: '' +scbursts: + version: '1.6' + title: Single Channel Bursts Analysis + maintainer: Blair Drummond + description: Provides tools to import and export from several existing pieces of + ion-channel analysis software such as 'TAC', 'QUB', 'SCAN', and 'Clampfit', implements + procedures such as dwell-time correction and defining bursts with a critical time, + and provides tools for analysis of bursts, such as tools for sorting and plotting. + date_publication: '2019-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scbursts + url_git: '' +scCAN: + version: 1.0.5 + title: Single-Cell Clustering using Autoencoder and Network Fusion + maintainer: Bang Tran + description: A single-cell Clustering method using 'Autoencoder' and Network fusion + ('scCAN') Bang Tran (2022) for segregating the + cells from the high-dimensional 'scRNA-Seq' data. The software automatically determines + the optimal number of clusters and then partitions the cells in a way such that + the results are robust to noise and dropouts. 'scCAN' is fast and it supports + Windows, Linux, and Mac OS. + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scCAN + url_git: '' +scCATCH: + version: 3.2.2 + title: |- + Single Cell Cluster-Based Annotation Toolkit for Cellular + Heterogeneity + maintainer: Xin Shao + description: An automatic cluster-based annotation pipeline based on evidence-based + score by matching the marker genes with known cell markers in tissue-specific + cell taxonomy reference database for single-cell RNA-seq data. See Shao X, et + al (2020) for more details. + date_publication: '2023-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scCATCH + url_git: https://github.com/ZJUFanLab/scCATCH +sccca: + version: 0.1.1 + title: Single-Cell Correlation Based Cell Type Annotation + maintainer: Mohamed Soudy + description: Performing cell type annotation based on cell markers from a unified + database. The approach utilizes correlation-based approach combined with association + analysis using Fisher-exact and phyper statistical tests (Upton, Graham JG. (1992) + ). + date_publication: '2024-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sccca + url_git: '' +SCCI: + version: '1.2' + title: |- + Stochastic Complexity-Based Conditional Independence Test for + Discrete Data + maintainer: Alexander Marx + description: An efficient implementation of SCCI using 'Rcpp'. SCCI is short for + the Stochastic Complexity-based Conditional Independence criterium (Marx and Vreeken, + 2019). SCCI is an asymptotically unbiased and L2 consistent estimator of (conditional) + mutual information for discrete data. + date_publication: '2019-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCCI + url_git: '' +scclust: + version: 0.2.5 + title: Size-Constrained Clustering + maintainer: Fredrik Savje + description: |- + Provides wrappers for 'scclust', a C library for computationally efficient + size-constrained clustering with near-optimal performance. + See for more information. + date_publication: '2024-07-31' + bug_reports: https://github.com/fsavje/scclust-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scclust + url_git: https://github.com/fsavje/scclust-R +sccore: + version: 1.0.5 + title: Core Utilities for Single-Cell RNA-Seq + maintainer: Evan Biederstedt + description: Core utilities for single-cell RNA-seq data analysis. Contained within + are utility functions for working with differential expression (DE) matrices and + count matrices, a collection of functions for manipulating and plotting data via + 'ggplot2', and functions to work with cell graphs and cell embeddings. Graph-based + methods include embedding kNN cell graphs into a UMAP , + collapsing vertices of each cluster in the graph, and propagating graph labels. + date_publication: '2024-02-23' + bug_reports: https://github.com/kharchenkolab/sccore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sccore + url_git: https://github.com/kharchenkolab/sccore +sccr: + version: '2.1' + title: The Self-Consistent, Competing Risks (SC-CR) Algorithms + maintainer: Alicja Wolny-Dominiak + description: The SC-SR Algorithm is used to calculate fully non-parametric and self-consistent + estimators of the cause-specific failure probabilities in the presence of interval-censoring + and possible making of the failure cause in a competing risks environment. In + the version 2.0 the function creating the probability matrix from double-censored + data is added. + date_publication: '2020-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sccr + url_git: '' +SCCS: + version: '1.7' + title: The Self-Controlled Case Series Method + maintainer: '"Yonas Ghebremichael Weldeselassie"' + description: |- + Various self-controlled case series models used to investigate + associations between time-varying exposures such as vaccines or + other drugs or non drug exposures and an adverse event can be + fitted. Detailed information on the self-controlled case series + method and its extensions with more examples can be found in + Farrington, P., Whitaker, H., and Ghebremichael Weldeselassie, Y. + (2018, ISBN: 978-1-4987-8159-6. Self-controlled Case Series studies: + A modelling Guide with R. Boca Raton: Chapman & Hall/CRC Press) + and . + date_publication: '2024-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCCS + url_git: '' +scCustomize: + version: 3.0.1 + title: |- + Custom Visualizations & Functions for Streamlined Analyses of + Single Cell Sequencing + maintainer: Samuel Marsh + description: 'Collection of functions created and/or curated to aid in the visualization + and analysis of single-cell data using ''R''. ''scCustomize'' aims to provide + 1) Customized visualizations for aid in ease of use and to create more aesthetic + and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces + of code in scRNA-seq analysis with a single or group of functions. For citation + please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined + Analyses of Single Cell Sequencing" RRID:SCR_024675.' + date_publication: '2024-12-18' + bug_reports: https://github.com/samuel-marsh/scCustomize/issues + url: https://samuel-marsh.github.io/scCustomize/ + url_cran: https://CRAN.R-project.org/package=scCustomize + url_git: https://github.com/samuel-marsh/scCustomize +SCDA: + version: 0.0.2 + title: Spatially-Clustered Data Analysis + maintainer: Paolo Maranzano + description: |- + Contains functions for statistical data analysis based on spatially-clustered techniques. + The package allows estimating the spatially-clustered spatial regression models presented in Cerqueti, Maranzano \& Mattera (2024), "Spatially-clustered spatial autoregressive models + with application to agricultural market concentration in Europe", arXiv preprint 2407.15874 . + Specifically, the current release allows the estimation of the spatially-clustered linear regression model (SCLM), the spatially-clustered spatial autoregressive model (SCSAR), + the spatially-clustered spatial Durbin model (SCSEM), and the spatially-clustered linear regression model with spatially-lagged exogenous covariates (SCSLX). + From release 0.0.2, the library contains functions to estimate spatial clustering based on Adiajacent Matrix K-Means (AMKM) as described in Zhou, Liu \& Zhu (2019), "Weighted adjacent matrix for K-means clustering", Multimedia Tools and Applications, 78 (23) . + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCDA + url_git: '' +SCDB: + version: 0.5.1 + title: |- + Easily Access and Maintain Time-Based Versioned Data + (Slowly-Changing-Dimension) + maintainer: Rasmus Skytte Randløv + description: |- + A collection of functions that enable easy access and updating of a database of data over time. + More specifically, the package facilitates type-2 history for data-warehouses and provides a number + of Quality of life improvements for working on SQL databases with R. + For reference see Ralph Kimball and Margy Ross (2013, ISBN 9781118530801). + date_publication: '2025-02-27' + bug_reports: https://github.com/ssi-dk/SCDB/issues + url: https://ssi-dk.github.io/SCDB/ + url_cran: https://CRAN.R-project.org/package=SCDB + url_git: https://github.com/ssi-dk/SCDB +scDECO: + version: 0.1.0 + title: Estimating Dynamic Correlation + maintainer: Anderson Bussing + description: Implementations for two different Bayesian models of differential co-expression. + scdeco.cop() fits the bivariate Gaussian copula model from Zichen Ma, Shannon + W. Davis, Yen-Yi Ho (2023) , while scdeco.pg() fits the + bivariate Poisson-Gamma model from Zhen Yang, Yen-Yi Ho (2022) . + date_publication: '2024-06-04' + bug_reports: https://github.com/YenYiHo-Lab/scDECO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scDECO + url_git: https://github.com/YenYiHo-Lab/scDECO +SCdeconR: + version: 1.0.0 + title: |- + Deconvolution of Bulk RNA-Seq Data using Single-Cell RNA-Seq + Data as Reference + maintainer: Yuanhang Liu + description: Streamlined workflow from deconvolution of bulk RNA-seq data to downstream + differential expression and gene-set enrichment analysis. Provide various visualization + functions. + date_publication: '2024-03-22' + bug_reports: '' + url: https://liuy12.github.io/SCdeconR/ + url_cran: https://CRAN.R-project.org/package=SCdeconR + url_git: https://github.com/Liuy12/SCdeconR/ +scdensity: + version: 1.0.3 + title: Shape-Constrained Kernel Density Estimation + maintainer: Mark A. Wolters + description: |- + Implements methods for obtaining kernel density estimates + subject to a variety of shape constraints (unimodality, bimodality, + symmetry, tail monotonicity, bounds, and constraints on the number of + inflection points). Enforcing constraints can eliminate unwanted waves or + kinks in the estimate, which improves its subjective appearance and can + also improve statistical performance. The main function scdensity() is + very similar to the density() function in 'stats', allowing + shape-restricted estimates to be obtained with little effort. The + methods implemented in this package are described in Wolters and Braun + (2017) , Wolters (2012) + , and Hall and Huang (2002) + . + See the scdensity() help for for full citations. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scdensity + url_git: '' +scDHA: + version: 1.2.2 + title: Single-Cell Decomposition using Hierarchical Autoencoder + maintainer: Ha Nguyen + description: |- + Provides a fast and accurate pipeline for single-cell analyses. + The 'scDHA' software package can perform clustering, dimension reduction and visualization, classification, and time-trajectory inference on single-cell data (Tran et.al. (2021) ). + date_publication: '2024-04-02' + bug_reports: https://github.com/duct317/scDHA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scDHA + url_git: https://github.com/duct317/scDHA +scdhlm: + version: 0.7.3 + title: Estimating Hierarchical Linear Models for Single-Case Designs + maintainer: James Pustejovsky + description: |- + Provides a set of tools for estimating hierarchical linear + models and effect sizes based on data from single-case designs. + Functions are provided for calculating standardized mean difference effect sizes that + are directly comparable to standardized mean differences estimated from between-subjects randomized experiments, + as described in Hedges, Pustejovsky, and Shadish (2012) ; + Hedges, Pustejovsky, and Shadish (2013) ; + Pustejovsky, Hedges, and Shadish (2014) ; + and Chen, Pustejovsky, Klingbeil, and Van Norman (2023) . + Includes an interactive web interface. + date_publication: '2024-02-25' + bug_reports: https://github.com/jepusto/scdhlm/issues + url: https://jepusto.github.io/scdhlm/ + url_cran: https://CRAN.R-project.org/package=scdhlm + url_git: '' +scDiffCom: + version: 1.0.0 + title: |- + Differential Analysis of Intercellular Communication from + scRNA-Seq Data + maintainer: Cyril Lagger + description: |- + Analysis tools to investigate changes in intercellular + communication from scRNA-seq data. Using a Seurat object as input, + the package infers which cell-cell interactions are present in the dataset + and how these interactions change between two conditions of interest + (e.g. young vs old). It relies on an internal database of ligand-receptor + interactions (available for human, mouse and rat) that have been gathered + from several published studies. Detection and differential analyses + rely on permutation tests. The package also contains several tools + to perform over-representation analysis and visualize the results. See + Lagger, C. et al. (2023) for a full + description of the methodology. + date_publication: '2023-11-03' + bug_reports: '' + url: https://cyrillagger.github.io/scDiffCom/ + url_cran: https://CRAN.R-project.org/package=scDiffCom + url_git: '' +scDIFtest: + version: 0.1.1 + title: Item-Wise Score-Based DIF Detection + maintainer: Dries Debeer + description: |- + Detection of item-wise Differential Item Functioning (DIF) + in fitted 'mirt', 'multipleGroup' or 'bfactor' models + using score-based structural change tests. Under the hood + the sctest() function from the 'strucchange' package is used. + date_publication: '2020-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scDIFtest + url_git: '' +scdtb: + version: 0.2.0 + title: Single Case Design Tools + maintainer: Mackson Ncube + description: |- + In some situations where researchers would like to demonstrate + causal effects, it is hard to obtain a sample size that would allow for a + well-powered randomized controlled trial. Single case designs are experimental + designs that can be used to demonstrate causal effects with only one participant + or with only a few participants. The 'scdtb' package provides a suite of tools + for analyzing data from studies that use single case designs. The nap() function + can be used to compute the nonoverlap of all pairs as outlined by the What + Works Clearinghouse (2022) . The + package also offers the mixed_model_analysis() and cross_lagged() functions + which implement mixed effects models and cross lagged analyses as described + in Maric & van der Werff (2020) . The + randomization_test() function implements randomization tests based on methods + presented in Onghena (2020) . The scdtb() 'shiny' + application can be used to upload single case design data and access various + 'scdtb' tools for plotting and analysis. + date_publication: '2024-09-20' + bug_reports: https://github.com/mightymetrika/scdtb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scdtb + url_git: https://github.com/mightymetrika/scdtb +scellpam: + version: 1.4.6.2 + title: |- + Applying Partitioning Around Medoids to Single Cell Data with + High Number of Cells + maintainer: Juan Domingo + description: |- + PAM (Partitioning Around Medoids) algorithm application to samples of single cell sequencing techniques + with a high number of cells (as many as the computer memory allows). The package uses a binary format to + store matrices (either full, sparse or symmetric) in files written in the disk that can contain any data type + (not just double) which allows its manipulation when memory is sufficient to load them as int or float, but not + as double. The PAM implementation is done in parallel, using several/all the cores of the machine, if it has them. + This package shares a great part of its code with packages 'jmatrix' and 'parallelpam' but their functionality is + included here so there is no need to install them. + date_publication: '2024-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scellpam + url_git: '' +SCEM: + version: 1.1.0 + title: Splitting-Coalescence-Estimation Method + maintainer: Kyung Serk Cho + description: 'We introduce improved methods for statistically assessing birth seasonality + and intra-annual variation. The first method we propose is a new idea that uses + a nonparametric clustering procedure to group individuals with similar time series + data and estimate birth seasonality based on the clusters. One can use the function + SCEM() to implement this method. The second method estimates input parameters + for use with a previously-developed parametric approach (Tornero et al., 2013). + The relevant code for this approach is makeFits_OLS(), while makeFits_initial() + is the code to implement the same method but with given initial conditions for + two parameters. The latter can be used to show the disadvantage of the existing + approach. One can use the function makeFits() to generate parametric birth seasonality + estimates using either initialization. Detailed description can be found here: + Chazin Hannah, Soudeep Deb, Joshua Falk, and Arun Srinivasan. (2019) "New Statistical + Approaches to Intra-Individual Isotopic Analysis and Modeling Birth Seasonality + in Studies of Herd Animals." .' + date_publication: '2021-09-02' + bug_reports: https://github.com/kserkcho/SCEM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SCEM + url_git: https://github.com/kserkcho/SCEM +scenes: + version: 0.1.0 + title: Switch Between Alternative 'shiny' UIs + maintainer: Jon Harmon + description: |- + Sometimes it is useful to serve up alternative 'shiny' UIs + depending on information passed in the request object, such as the value of + a cookie or a query parameter. This packages facilitates such switches. + date_publication: '2023-01-13' + bug_reports: https://github.com/r4ds/scenes/issues + url: https://r4ds.github.io/scenes/ + url_cran: https://CRAN.R-project.org/package=scenes + url_git: https://github.com/r4ds/scenes +SCEnt: + version: 0.0.1 + title: |- + Single Cell Entropy Analysis of Gene Heterogeneity in Cell + Populations + maintainer: Hugh Warden + description: |- + Analyse single cell RNA sequencing data using entropy to + calculate heterogeneity and homogeneity of genes amongst the cell + population. From the work of Michael J. Casey, Ruben J. Sanchez-Garcia + and Ben D. MacArthur. + date_publication: '2021-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCEnt + url_git: '' +SCEPtER: + version: 0.2-4 + title: Stellar CharactEristics Pisa Estimation gRid + maintainer: Matteo Dell'Omodarme + description: |- + A pipeline for estimating the stellar + age, mass, and radius given observational + effective temperature, [Fe/H], and astroseismic + parameters. The results are obtained adopting a maximum likelihood + technique over a grid of pre-computed stellar models, as + described in Valle et al. (2014) . + date_publication: '2021-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCEPtER + url_git: '' +SCEPtERbinary: + version: 0.1-1 + title: Stellar CharactEristics Pisa Estimation gRid for Binary Systems + maintainer: Matteo Dell'Omodarme + description: SCEPtER pipeline for estimating the stellar age for double-lined detached + binary systems. The observational constraints adopted in the recovery are the + effective temperature, the metallicity [Fe/H], the mass, and the radius of the + two stars. The results are obtained adopting a maximum likelihood technique over + a grid of pre-computed stellar models. + date_publication: '2014-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCEPtERbinary + url_git: '' +SCFMonitor: + version: 0.3.5 + title: |- + Clear Monitor and Graphing Software Processing Gaussian .log + File + maintainer: Pengjun Guo + description: Self-Consistent Field(SCF) calculation method is one of the most important + steps in the calculation methods of quantum chemistry. Ehrenreich, H., & Cohen, + M. H. (1959). However, the most prevailing software + in this area, 'Gaussian''s SCF convergence process is hard to monitor, especially + while the job is still running, causing researchers difficulty in knowing whether + the oscillation has started or not, wasting time and energy on useless configurations + or abandoning the jobs that can actually work. M.J. Frisch, G.W. Trucks, H.B. + Schlegel et al. (2016). 'SCFMonitor' enables 'Gaussian' + quantum chemistry calculation software users to easily read the 'Gaussian' .log + files and monitor the SCF convergence and geometry optimization process with little + effort and clear, beautiful, and clean outputs. It can generate graphs using 'tidyverse' + to let users check SCF convergence and geometry optimization processes in real-time. + The software supports processing .log files remotely using with rbase::url(). + This software is a suitcase for saving time and energy for the researchers, supporting + multiple versions of 'Gaussian'. + date_publication: '2024-09-18' + bug_reports: https://github.com/AzuleneG/SCFMonitor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SCFMonitor + url_git: https://github.com/AzuleneG/SCFMonitor +scGate: + version: 1.6.2 + title: |- + Marker-Based Cell Type Purification for Single-Cell Sequencing + Data + maintainer: Massimo Andreatta + description: 'A common bioinformatics task in single-cell data analysis is to purify + a cell type or cell population of interest from heterogeneous datasets. ''scGate'' + automatizes marker-based purification of specific cell populations, without requiring + training data or reference gene expression profiles. Briefly, ''scGate'' takes + as input: i) a gene expression matrix stored in a ''Seurat'' object and ii) a + “gating model” (GM), consisting of a set of marker genes that define the cell + population of interest. The GM can be as simple as a single marker gene, or a + combination of positive and negative markers. More complex GMs can be constructed + in a hierarchical fashion, akin to gating strategies employed in flow cytometry. + ''scGate'' evaluates the strength of signature marker expression in each cell + using the rank-based method ''UCell'', and then performs k-nearest neighbor (kNN) + smoothing by calculating the mean ''UCell'' score across neighboring cells. kNN-smoothing + aims at compensating for the large degree of sparsity in scRNA-seq data. Finally, + a universal threshold over kNN-smoothed signature scores is applied in binary + decision trees generated from the user-provided gating model, to annotate cells + as either “pure” or “impure”, with respect to the cell population of interest. + See the related publication Andreatta et al. (2022) .' + date_publication: '2024-04-23' + bug_reports: https://github.com/carmonalab/scGate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scGate + url_git: https://github.com/carmonalab/scGate +SCGLR: + version: '3.0' + title: Supervised Component Generalized Linear Regression + maintainer: Guillaume Cornu + description: |2- + + An extension of the Fisher Scoring Algorithm to combine PLS regression with GLM + estimation in the multivariate context. Covariates can also be grouped in themes. + date_publication: '2018-09-28' + bug_reports: https://github.com/SCnext/SCGLR/issues + url: https://scnext.github.io/SCGLR + url_cran: https://CRAN.R-project.org/package=SCGLR + url_git: https://github.com/SCnext/SCGLR +scGOclust: + version: 0.2.1 + title: |- + Measuring Cell Type Similarity with Gene Ontology in Single-Cell + RNA-Seq + maintainer: Yuyao Song + description: Traditional methods for analyzing single cell RNA-seq datasets focus + solely on gene expression, but this package introduces a novel approach that goes + beyond this limitation. Using Gene Ontology terms as features, the package allows + for the functional profile of cell populations, and comparison within and between + datasets from the same or different species. Our approach enables the discovery + of previously unrecognized functional similarities and differences between cell + types and has demonstrated success in identifying cell types' functional correspondence + even between evolutionarily distant species. + date_publication: '2024-01-24' + bug_reports: https://github.com/Papatheodorou-Group/scGOclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scGOclust + url_git: https://github.com/Papatheodorou-Group/scGOclust +scgwr: + version: 0.1.2-21 + title: Scalable Geographically Weighted Regression + maintainer: Daisuke Murakami + description: Fast and regularized version of GWR for large dataset, detailed in + Murakami, Tsutsumida, Yoshida, Nakaya, and Lu (2019) . + date_publication: '2021-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scgwr + url_git: '' +sched: + version: 1.0.3 + title: Request Scheduler + maintainer: Pierrick Roger + description: 'Offers classes and functions to contact web servers while enforcing + scheduling rules required by the sites. The URL class makes it easy to construct + a URL by providing parameters as a vector. The Request class allows to describes + SOAP (Simple Object Access Protocol) or standard requests: URL, method (POST or + GET), header, body. The Scheduler class controls the request frequency for each + server address by mean of rules (Rule class). The RequestResult class permits + to get the request status to handle error cases and the content.' + date_publication: '2024-10-02' + bug_reports: https://gitlab.com/cnrgh/databases/r-sched/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sched + url_git: https://gitlab.com/cnrgh/databases/r-sched +schemr: + version: 0.3.1 + title: Convert Images to Usable Color Schemes + maintainer: Stuart Morrison + description: A fast and adaptable tool to convert photos and images into usable + colour schemes for data visualisation. Contains functionality to extract colour + palettes from images, as well for the conversion of images between colour spaces. + date_publication: '2025-01-22' + bug_reports: https://github.com/stuart-morrison/schemr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=schemr + url_git: https://github.com/stuart-morrison/schemr +schoenberg: + version: 2.0.3 + title: Tools for 12-Tone Musical Composition + maintainer: Jeffrey A. Dahlke + description: Functions for creating and manipulating 12-tone (i.e., dodecaphonic) + musical matrices using Arnold Schoenberg's (1923) serialism technique. This package + can generate random 12-tone matrices and can generate matrices using a pre-determined + sequence of notes. + date_publication: '2024-01-28' + bug_reports: https://github.com/jadahlke/schoenberg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=schoenberg + url_git: '' +scholar: + version: 0.2.4 + title: Analyse Citation Data from Google Scholar + maintainer: Guangchuang Yu + description: |- + Provides functions to extract citation data from Google + Scholar. Convenience functions are also provided for comparing + multiple scholars and predicting future h-index values. + date_publication: '2022-08-09' + bug_reports: https://github.com/YuLab-SMU/scholar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scholar + url_git: https://github.com/YuLab-SMU/scholar +SchoolDataIT: + version: 0.2.3 + title: |- + Retrieve, Harmonise and Map Open Data Regarding the Italian + School System + maintainer: Leonardo Cefalo + description: |- + Compiles and displays the available data sets regarding the Italian school system, with a focus on the infrastructural aspects. + Input datasets are downloaded from the web, with the aim of updating everything to real time. + The functions are divided in four main modules, namely + 'Get', to scrape raw data from the web + 'Util', various utilities needed to process raw data + 'Group', to aggregate data at the municipality or province level + 'Map', to visualize the output datasets. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SchoolDataIT + url_git: https://github.com/lcef97/SchoolDataIT +schoolmath: + version: 0.4.2 + title: Functions and Datasets for Math Used in School + maintainer: Jörg große Schlarmann + description: Contains functions and datasets for math taught in school. A main focus + is set to prime-calculation. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=schoolmath + url_git: '' +schoRsch: + version: '1.11' + title: Tools for Analyzing Factorial Experiments + maintainer: Roland Pfister + description: 'Offers a helping hand to psychologists and other behavioral scientists + who routinely deal with experimental data from factorial experiments. It includes + several functions to format output from other R functions according to the style + guidelines of the APA (American Psychological Association). This formatted output + can be copied directly into manuscripts to facilitate data reporting. These features + are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box + outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious + technician at the Department of Psychology III, University of Wuerzburg. For details + on the implemented methods, see Roland Pfister and Markus Janczyk (2016) .' + date_publication: '2024-11-19' + bug_reports: '' + url: https://www.tqmp.org/RegularArticles/vol12-2/p147/index.html + url_cran: https://CRAN.R-project.org/package=schoRsch + url_git: '' +schrute: + version: 1.0.1 + title: The Entire Transcript from the Office in Tidy Format + maintainer: Brad Lindblad + description: |- + The complete scripts from the American version of the Office + television show in tibble format. Use this package to analyze and have + fun with text from the best series of all time. + date_publication: '2022-09-29' + bug_reports: https://github.com/bradlindblad/schrute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=schrute + url_git: https://github.com/bradlindblad/schrute +schtools: + version: 0.4.1 + title: Schloss Lab Tools for Reproducible Microbiome Research + maintainer: Kelly Sovacool + description: |- + A collection of useful functions and example code created and + used by the Schloss Lab for reproducible microbiome research. Perform + common tasks like read files created by mothur , + tidy up your microbiome data, and format R Markdown documents for + publication. See the website + for more information, documentation, and examples. + date_publication: '2023-08-21' + bug_reports: https://github.com/SchlossLab/schtools/issues + url: http://www.schlosslab.org/schtools/ + url_cran: https://CRAN.R-project.org/package=schtools + url_git: https://github.com/SchlossLab/schtools +schumaker: + version: 1.2.1 + title: Schumaker Shape-Preserving Spline + maintainer: Stuart Baumann + description: |- + This is a shape preserving spline + which is guaranteed to be monotonic and concave or convex if the + data is monotonic and concave or convex. It does not use any + optimisation and is therefore quick and smoothly converges to a + fixed point in economic dynamics problems including value function + iteration. It also automatically gives the first two derivatives + of the spline and options for determining behaviour when evaluated + outside the interpolation domain. + date_publication: '2021-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=schumaker + url_git: '' +schwabr: + version: 0.1.3 + title: '''Schwab API'' Interface' + maintainer: Anthony Trevisan + description: |- + Use R to interface with the 'Charles Schwab Trade API' . + Functions include authentication, trading, price requests, account information, and option + chains. A user will need a Schwab brokerage account and Schwab Individual Developer app. See README + for authentication process and examples. + date_publication: '2025-02-24' + bug_reports: https://github.com/altanalytics/schwabr/issues + url: https://altanalytics.github.io/schwabr/ + url_cran: https://CRAN.R-project.org/package=schwabr + url_git: '' +SCI: + version: 1.0-2 + title: Standardized Climate Indices Such as SPI, SRI or SPEI + maintainer: Lukas Gudmundsson + description: |- + Functions for generating Standardized Climate Indices (SCI). + SCI is a transformation of (smoothed) climate (or environmental) + time series that removes seasonality and forces the data to + take values of the standard normal distribution. SCI was + originally developed for precipitation. In this case it is + known as the Standardized Precipitation Index (SPI). + date_publication: '2016-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCI + url_git: '' +SCIBER: + version: 0.2.2 + title: Single-Cell Integrator and Batch Effect Remover + maintainer: Dailin Gan + description: Remove batch effects by projecting query batches into the reference + batch space. + date_publication: '2023-05-02' + bug_reports: https://github.com/RavenGan/SCIBER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SCIBER + url_git: https://github.com/RavenGan/SCIBER +scico: + version: 1.5.0 + title: Colour Palettes Based on the Scientific Colour-Maps + maintainer: Thomas Lin Pedersen + description: |- + Colour choice in information visualisation is important in order to + avoid being mislead by inherent bias in the used colour palette. The 'scico' + package provides access to the perceptually uniform and colour-blindness + friendly palettes developed by Fabio Crameri and released under the + "Scientific Colour-Maps" moniker. The package contains 24 different palettes + and includes both diverging and sequential types. + date_publication: '2023-08-14' + bug_reports: https://github.com/thomasp85/scico/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scico + url_git: https://github.com/thomasp85/scico +scicomptools: + version: 1.1.0 + title: Tools Developed by the NCEAS Scientific Computing Support Team + maintainer: Angel Chen + description: |- + Set of tools to import, summarize, wrangle, and visualize data. + These functions were originally written based on the needs of the + various synthesis working groups that were supported by the + National Center for Ecological Analysis and Synthesis (NCEAS). + These tools are meant to be useful inside and + outside of the context for which they were designed. + date_publication: '2024-10-31' + bug_reports: https://github.com/NCEAS/scicomptools/issues + url: https://nceas.github.io/scicomptools/ + url_cran: https://CRAN.R-project.org/package=scicomptools + url_git: https://github.com/NCEAS/scicomptools +scidesignR: + version: 1.0.0 + title: |- + Data Sets from Design and Analysis of Experiments and + Observational Studies using R + maintainer: Nathan Taback + description: Data used in Taback, N. (2022). Design and Analysis of Experiments + and Observational Studies using R. Chapman & Hall/CRC. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scidesignR + url_git: '' +scientific: + version: '2025.0' + title: |- + Two Highly Customizable 'rmarkdown' Themes for Scientific + Reports + maintainer: Obinna Obianom + description: Offers 'markdown' output formats designed with various styles, allowing + users to generate HTML reports tailored for scientific or machine learning showcase. + The output has a contemporary appearance with vibrant visuals, providing numerous + styles for effective highlighting. Created using the 'tufte' + package code as a starting point. + date_publication: '2025-02-02' + bug_reports: https://github.com/oobianom/scientific/issues + url: https://scientific.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=scientific + url_git: '' +scientoText: + version: '0.1' + title: Text & Scientometric Analytics + maintainer: Ashraf Uddin + description: It involves bibliometric indicators calculation from bibliometric data.It + also deals pattern analysis using the text part of bibliometric data.The bibliometric + data are obtained from mainly Web of Science and Scopus. + date_publication: '2016-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scientoText + url_git: '' +scifigure: + version: '0.2' + title: |- + Visualize 'Reproducibility' and 'Replicability' in a Comparison + of Scientific Studies + maintainer: Prasad Patil + description: |- + Users may specify what fundamental qualities of a new study have + or have not changed in an attempt to reproduce or replicate an + original study. A comparison of the differences is visualized. + Visualization approach follows 'Patil', 'Peng', and + 'Leek' (2016) . + date_publication: '2019-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scifigure + url_git: '' +scimo: + version: 0.0.2 + title: Extra Recipes Steps for Dealing with Omics Data + maintainer: Antoine BICHAT + description: |- + Omics data (e.g. transcriptomics, proteomics, + metagenomics...) offer a detailed and multi-dimensional perspective + on the molecular components and interactions within complex biological + (eco)systems. Analyzing these data requires adapted procedures, which + are implemented as steps according to the 'recipes' package. + date_publication: '2024-06-07' + bug_reports: https://github.com/abichat/scimo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scimo + url_git: https://github.com/abichat/scimo +SCINA: + version: 1.2.0 + title: A Semi-Supervised Category Identification and Assignment Tool + maintainer: Ze Zhang + description: An automatic cell type detection and assignment algorithm for single + cell RNA-Seq and Cytof/FACS data. 'SCINA' is capable of assigning cell type identities + to a pool of cells profiled by scRNA-Seq or Cytof/FACS data with prior knowledge + of markers, such as genes and protein symbols that are highly or lowly expressed + in each category. See Zhang Z, et al (2019) for more + details. + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCINA + url_git: http://lce.biohpc.swmed.edu/scina/https://github.com/jcao89757/SCINA +scINSIGHT: + version: 0.1.4 + title: Interpretation of Heterogeneous Single-Cell Gene Expression Data + maintainer: Kun Qian + description: We develop a novel matrix factorization tool named 'scINSIGHT' to jointly + analyze multiple single-cell gene expression samples from biologically heterogeneous + sources, such as different disease phases, treatment groups, or developmental + stages. Given multiple gene expression samples from different biological conditions, + 'scINSIGHT' simultaneously identifies common and condition-specific gene modules + and quantify their expression levels in each sample in a lower-dimensional space. + With the factorized results, the inferred expression levels and memberships of + common gene modules can be used to cluster cells and detect cell identities, and + the condition-specific gene modules can help compare functional differences in + transcriptomes from distinct conditions. Please also see Qian K, Fu SW, Li HW, + Li WV (2022) . + date_publication: '2022-05-29' + bug_reports: '' + url: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02649-3 + url_cran: https://CRAN.R-project.org/package=scINSIGHT + url_git: https://github.com/Vivianstats/scINSIGHT +SCIntRuler: + version: 0.99.6 + title: Guiding the Integration of Multiple Single-Cell RNA-Seq Datasets + maintainer: Yue Lyu + description: The accumulation of single-cell RNA-seq ('scRNA-seq') studies highlights + the potential benefits of integrating multiple datasets. By augmenting sample + sizes and enhancing analytical robustness, integration can lead to more insightful + biological conclusions. However, challenges arise due to the inherent diversity + and batch discrepancies within and across studies. 'SCIntRuler', a novel R package, + addresses these challenges by guiding the integration of multiple 'scRNA-seq' + datasets. + date_publication: '2024-07-12' + bug_reports: https://github.com/yuelyu21/SCIntRuler/issues + url: https://yuelyu21.github.io/SCIntRuler/ + url_cran: https://CRAN.R-project.org/package=SCIntRuler + url_git: https://github.com/yuelyu21/SCIntRuler +sciplot: + version: 1.2-0 + title: Scientific Graphing Functions for Factorial Designs + maintainer: Manuel Morales + description: |- + A collection of functions that creates graphs with error + bars for data collected from one-way or higher factorial + designs. + date_publication: '2020-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sciplot + url_git: '' +scipub: + version: 1.2.3 + title: Summarize Data for Scientific Publication + maintainer: David Pagliaccio + description: |- + Create and format tables and APA statistics for + scientific publication. This includes making a 'Table 1' + to summarize demographics across groups, correlation tables + with significance indicated by stars, and extracting formatted + statistical summarizes from simple tests for in-text notation. + The package also includes functions for Winsorizing data based + on a Z-statistic cutoff. + date_publication: '2024-03-09' + bug_reports: https://github.com/dpagliaccio/scipub/issues + url: https://dpagliaccio.github.io/scipub/ + url_cran: https://CRAN.R-project.org/package=scipub + url_git: https://github.com/dpagliaccio/scipub +sciRmdTheme: + version: '0.1' + title: Upgraded 'Rmarkdown' Themes for Scientific Writing + maintainer: Obinna Obianom + description: A set of 'Rmarkdown' themes for creating scientific and professional + documents. Simple interface with features to ease navigation across the page and + sub-pages. + date_publication: '2022-06-30' + bug_reports: https://github.com/oobianom/sciRmdTheme + url: '' + url_cran: https://CRAN.R-project.org/package=sciRmdTheme + url_git: https://github.com/oobianom/sciRmdTheme +scISR: + version: 0.1.1 + title: Single-Cell Imputation using Subspace Regression + maintainer: Duc Tran + description: |- + Provides an imputation pipeline for single-cell RNA sequencing data. + The 'scISR' method uses a hypothesis-testing technique to identify zero-valued entries that are most likely affected by dropout events and estimates the dropout values using a subspace regression model (Tran et.al. (2022) ). + date_publication: '2022-06-30' + bug_reports: https://github.com/duct317/scISR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scISR + url_git: https://github.com/duct317/scISR +scistreer: + version: 1.2.0 + title: Maximum-Likelihood Perfect Phylogeny Inference at Scale + maintainer: Teng Gao + description: Fast maximum-likelihood phylogeny inference from noisy single-cell + data using the 'ScisTree' algorithm by Yufeng Wu (2019) . + 'scistreer' provides an 'R' interface and improves speed via 'Rcpp' and 'RcppParallel', + making the method applicable to massive single-cell datasets (>10,000 cells). + date_publication: '2023-06-15' + bug_reports: '' + url: https://kharchenkolab.github.io/scistreer/ + url_cran: https://CRAN.R-project.org/package=scistreer + url_git: https://github.com/kharchenkolab/scistreer +scitb: + version: 0.2.1 + title: Provides Some Useful Functions for Making Statistical Tables + maintainer: Qiang Liu + description: |- + You can use the functions provided by the package to make various statistical tables, + such as baseline data tables. Creates 'Table 1', i.e., a description of the baseline patient + characteristics, which is essential in every medical research. + Supports both continuous and categorical variables, as well as + p-values and standardized mean differences. + This method was described by Mary L McHugh (2013) . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scitb + url_git: '' +scITD: + version: 1.0.4 + title: Single-Cell Interpretable Tensor Decomposition + maintainer: Jonathan Mitchel + description: |- + Single-cell Interpretable Tensor Decomposition (scITD) employs the + Tucker tensor decomposition to extract multicell-type gene expression patterns + that vary across donors/individuals. This tool is geared for use with single-cell + RNA-sequencing datasets consisting of many source donors. The method has a wide + range of potential applications, including the study of inter-individual variation + at the population-level, patient sub-grouping/stratification, and the analysis + of sample-level batch effects. Each "multicellular process" that is extracted + consists of (A) a multi cell type gene loadings matrix and (B) a + corresponding donor scores vector indicating the level at which the corresponding + loadings matrix is expressed in each donor. Additional methods are implemented + to aid in selecting an appropriate number of factors and to evaluate stability + of the decomposition. Additional tools are provided for downstream analysis, + including integration of gene set enrichment analysis and ligand-receptor analysis. + Tucker, L.R. (1966) . Unkel, S., Hannachi, A., Trendafilov, N. T., & Jolliffe, I. T. (2011) . Zhou, G., & Cichocki, A. (2012) . + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scITD + url_git: '' +SciViews: + version: 0.9-13.1 + title: SciViews - Main package + maintainer: Philippe Grosjean + description: |- + Functions to install SciViews additions to R, and more + tools. + date_publication: '2019-11-16' + bug_reports: https://github.com/SciViews/SciViews/issues + url: http://www.sciviews.org/SciViews-R + url_cran: https://CRAN.R-project.org/package=SciViews + url_git: https://github.com/SciViews/SciViews +scLink: + version: 1.0.1 + title: |- + Inferring Functional Gene Co-Expression Networks from Single + Cell Data + maintainer: Wei Vivian Li + description: Uses statistical network modeling to understand the co-expression relationships + among genes and to construct sparse gene co-expression networks from single-cell + gene expression data. + date_publication: '2020-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scLink + url_git: '' +sclr: + version: 0.3.1 + title: Scaled Logistic Regression + maintainer: Arseniy Khvorov + description: |2- + + Maximum likelihood estimation of the scaled logit model parameters + proposed in Dunning (2006) . + date_publication: '2020-03-02' + bug_reports: '' + url: https://khvorov45.github.io/sclr/ + url_cran: https://CRAN.R-project.org/package=sclr + url_git: '' +sClust: + version: '1.0' + title: R Toolbox for Unsupervised Spectral Clustering + maintainer: Emilie Poisson-Caillault + description: Toolbox containing a variety of spectral clustering tools functions. + Among the tools available are the hierarchical spectral clustering algorithm, + the Shi and Malik clustering algorithm, the Perona and Freeman algorithm, the + non-normalized clustering, the Von Luxburg algorithm, the Partition Around Medoids + clustering algorithm, a multi-level clustering algorithm, recursive clustering + and the fast method for all clustering algorithm. As well as other tools needed + to run these algorithms or useful for unsupervised spectral clustering. This toolbox + aims to gather the main tools for unsupervised spectral classification. See + for more information and documentation. + date_publication: '2021-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sClust + url_git: '' +SCMA: + version: 1.3.1 + title: Single-Case Meta-Analysis + maintainer: Tamal Kumar De + description: Perform meta-analysis of single-case experiments, including calculating + various effect size measures (SMD, PND, PEM and NAP) and probability combining + (additive and multiplicative method), as discussed in Bulte and Onghena (2013) + . + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCMA + url_git: '' +scMappR: + version: 1.0.11 + title: Single Cell Mapper + maintainer: Dustin Sokolowski + description: 'The single cell mapper (scMappR) R package contains a suite of bioinformatic + tools that provide experimentally relevant cell-type specific information to a + list of differentially expressed genes (DEG). The function "scMappR_and_pathway_analysis" + reranks DEGs to generate cell-type specificity scores called cell-weighted fold-changes. + Users input a list of DEGs, normalized counts, and a signature matrix into this + function. scMappR then re-weights bulk DEGs by cell-type specific expression from + the signature matrix, cell-type proportions from RNA-seq deconvolution and the + ratio of cell-type proportions between the two conditions to account for changes + in cell-type proportion. With cwFold-changes calculated, scMappR uses two approaches + to utilize cwFold-changes to complete cell-type specific pathway analysis. The + "process_dgTMatrix_lists" function in the scMappR package contains an automated + scRNA-seq processing pipeline where users input scRNA-seq count data, which is + made compatible for scMappR and other R packages that analyze scRNA-seq data. + We further used this to store hundreds up regularly updating signature matrices. + The functions "tissue_by_celltype_enrichment", "tissue_scMappR_internal", and + "tissue_scMappR_custom" combine these consistently processed scRNAseq count data + with gene-set enrichment tools to allow for cell-type marker enrichment of a generic + gene list (e.g. GWAS hits). Reference: Sokolowski,D.J., Faykoo-Martinez,M., Erdman,L., + Hou,H., Chan,C., Zhu,H., Holmes,M.M., Goldenberg,A. and Wilson,M.D. (2021) Single-cell + mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially + expressed genes. NAR Genomics and Bioinformatics. 3(1). Iqab011. .' + date_publication: '2023-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scMappR + url_git: '' +scModels: + version: 1.0.4 + title: Fitting Discrete Distribution Models to Count Data + maintainer: Lisa Amrhein + description: |- + Provides functions for fitting discrete distribution models to count data. + Included are the Poisson, the negative binomial, the Poisson-inverse gaussian and, most importantly, + a new implementation of the Poisson-beta distribution (density, distribution and quantile + functions, and random number generator) together with a needed new implementation of + Kummer's function (also: confluent hypergeometric function of the first kind). Three + different implementations of the Gillespie algorithm allow data simulation based on the + basic, switching or bursting mRNA generating processes. Moreover, likelihood functions for + four variants of each of the three aforementioned distributions are also available. + The variants include one population and two population mixtures, both with and without + zero-inflation. The package depends on the 'MPFR' libraries () which need to be installed separately + (see description at ). + This package is supplement to the paper "A mechanistic model for the negative binomial distribution of single-cell mRNA counts" + by Lisa Amrhein, Kumar Harsha and Christiane Fuchs (2019) available on bioRxiv. + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scModels + url_git: '' +scOntoMatch: + version: 0.1.1 + title: |- + Aligning Ontology Annotation Across Single Cell Datasets with + 'scOntoMatch' + maintainer: Yuyao Song + description: 'Unequal granularity of cell type annotation makes it difficult to + compare scRNA-seq datasets at scale. Leveraging the ontology system for defining + cell type hierarchy, ''scOntoMatch'' aims to align cell type annotations to make + them comparable across studies. The alignment involves two core steps: first is + to trim the cell type tree within each dataset so each cell type does not have + descendants, and then map cell type labels cross-studies by direct matching and + mapping descendants to ancestors. Various functions for plotting cell type trees + and manipulating ontology terms are also provided. In the Single Cell Expression + Atlas hosted at EBI, a compendium of datasets with curated ontology labels are + great inputs to this package.' + date_publication: '2023-10-27' + bug_reports: https://github.com/Papatheodorou-Group/scOntoMatch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scOntoMatch + url_git: https://github.com/Papatheodorou-Group/scOntoMatch +scoper: + version: 1.3.0 + title: Spectral Clustering-Based Method for Identifying B Cell Clones + maintainer: Susanna Marquez + description: |- + Provides a computational framework for identification of B cell clones from + Adaptive Immune Receptor Repertoire sequencing (AIRR-Seq) data. Three main + functions are included (identicalClones, hierarchicalClones, and spectralClones) + that perform clustering among sequences of BCRs/IGs (B cell receptors/immunoglobulins) + which share the same V gene, J gene and junction length. + Nouri N and Kleinstein SH (2018) . + Nouri N and Kleinstein SH (2019) . + Gupta NT, et al. (2017) . + date_publication: '2023-10-06' + bug_reports: https://bitbucket.org/kleinstein/scoper/issues + url: https://scoper.readthedocs.io + url_cran: https://CRAN.R-project.org/package=scoper + url_git: '' +scopr: + version: 0.3.5 + title: Read Ethoscope Data + maintainer: Quentin Geissmann + description: |- + Handling of behavioural data from the Ethoscope platform + (Geissmann, Garcia Rodriguez, Beckwith, French, Jamasb and Gilestro (2017) ). + Ethoscopes () are an open source/open hardware framework made of + interconnected raspberry pis () designed to quantify the behaviour of multiple + small animals in a distributed and real-time fashion. The default tracking algorithm records primary variables + such as xy coordinates, dimensions and speed. + This package is part of the rethomics framework . + date_publication: '2025-01-28' + bug_reports: https://github.com/rethomics/scopr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scopr + url_git: https://github.com/rethomics/scopr +SCOPRO: + version: 0.1.0 + title: Score Projection Between in 'Vivo' and in 'Vitro' Datasets + maintainer: Gabriele Lubatti + description: Assigns a score projection from 0 to 1 between a given in 'vivo' stage + and each single cluster from an in 'vitro' dataset. The score is assigned based + on the the fraction of specific markers of the in 'vivo' stage that are conserved + in the in 'vitro' clusters . + date_publication: '2022-08-23' + bug_reports: https://github.com/ScialdoneLab/SCOPRO/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SCOPRO + url_git: '' +SCOR: + version: 1.1.2 + title: Spherically Constrained Optimization Routine + maintainer: Debsurya De + description: 'A non convex optimization package that optimizes any function under + the criterion, combination of variables are on the surface of a unit sphere, as + described in the paper : Das et al. (2019) .' + date_publication: '2023-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCOR + url_git: https://github.com/synx21/SCOR +score: + version: 1.0.2 + title: A Package to Score Behavioral Questionnaires + maintainer: Jaejoon Song + description: Provides routines for scoring behavioral questionnaires. Includes scoring + procedures for the 'International Physical Activity Questionnaire (IPAQ)' . + Compares physical functional performance to the age- and gender-specific normal + ranges. + date_publication: '2015-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=score + url_git: '' +scorecard: + version: 0.4.4 + title: Credit Risk Scorecard + maintainer: Shichen Xie + description: |- + The `scorecard` package makes the development of credit risk scorecard + easier and efficient by providing functions for some common tasks, + such as data partition, variable selection, woe binning, scorecard scaling, + performance evaluation and report generation. These functions can also used + in the development of machine learning models. + The references including: + 1. Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: + Development and Implementation Using SAS. + 2. Siddiqi, N. (2006, ISBN: 9780471754510). Credit risk scorecards. + Developing and Implementing Intelligent Credit Scoring. + date_publication: '2024-04-13' + bug_reports: https://github.com/ShichenXie/scorecard/issues + url: http://shichen.name/scorecard/ + url_cran: https://CRAN.R-project.org/package=scorecard + url_git: https://github.com/ShichenXie/scorecard +scorecardModelUtils: + version: 0.0.1.0 + title: Credit Scorecard Modelling Utils + maintainer: Arya Poddar + description: Provides infrastructure functionalities such as missing value treatment, + information value calculation, GINI calculation etc. which are used for developing + a traditional credit scorecard as well as a machine learning based model. The + functionalities defined are standard steps for any credit underwriting scorecard + development, extensively used in financial domain. + date_publication: '2019-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scorecardModelUtils + url_git: '' +scoredec: + version: 0.1.2 + title: S-Core Graph Decomposition + maintainer: Christos Adam + description: |- + S-Core Graph Decomposition algorithm for graphs. This is a method + for decomposition of a weighted graph, as proposed by Eidsaa and + Almaas (2013) . The high speed and the low + memory usage make it suitable for large graphs. + date_publication: '2024-11-20' + bug_reports: https://github.com/cadam00/scoredec/issues + url: https://cadam00.github.io/scoredec/ + url_cran: https://CRAN.R-project.org/package=scoredec + url_git: https://github.com/cadam00/scoredec +ScoreEB: + version: 0.1.1 + title: Score Test Integrated with Empirical Bayes for Association Study + maintainer: Wenlong Ren + description: Perform association test within linear mixed model framework using + score test integrated with Empirical Bayes for genome-wide association study. + Firstly, score test was conducted for each marker under linear mixed model framework, + taking into account the genetic relatedness and population structure. And then + all the potentially associated markers were selected with a less stringent criterion. + Finally, all the selected markers were placed into a multi-locus model to identify + the true quantitative trait nucleotide. + date_publication: '2021-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ScoreEB + url_git: '' +scorematchingad: + version: 0.1.1 + title: Score Matching Estimation by Automatic Differentiation + maintainer: Kassel Liam Hingee + description: Hyvärinen's score matching (Hyvärinen, 2005) + is a useful estimation technique when the normalising constant for a probability + distribution is difficult to compute. This package implements score matching estimators + using automatic differentiation in the 'CppAD' library + and is designed for quickly implementing score matching estimators for new models. + Also available is general robustification (Windham, 1995) . + Already in the package are estimators for directional distributions (Mardia, Kent + and Laha, 2016) and the flexible Polynomially-Tilted + Pairwise Interaction model for compositional data. The latter estimators perform + well when there are zeros in the compositions (Scealy and Wood, 2023) , + even many zeros (Scealy, Hingee, Kent, and Wood, 2024) . + A partial interface to CppAD's ADFun objects is also available. + date_publication: '2025-01-08' + bug_reports: https://github.com/kasselhingee/scorematchingad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scorematchingad + url_git: https://github.com/kasselhingee/scorematchingad +scorepeak: + version: 0.1.2 + title: Peak Functions for Peak Detection in Univariate Time Series + maintainer: Shota Ochi + description: Provides peak functions, which enable us to detect peaks in time series. + The methods implemented in this package are based on Girish Keshav Palshikar (2009) + . + date_publication: '2019-08-21' + bug_reports: https://github.com/ShotaOchi/scorepeak/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scorepeak + url_git: https://github.com/ShotaOchi/scorepeak +ScorePlus: + version: '0.1' + title: Implementation of SCORE, SCORE+ and Mixed-SCORE + maintainer: Shengming Luo + description: Implementation of community detection algorithm SCORE in the paper + J. Jin (2015) , and SCORE+ in J. Jin, Z. Ke and S. Luo (2018) + . Membership estimation algorithm called Mixed-SCORE in J. Jin, + Z. Ke and S. Luo (2017) . + date_publication: '2019-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ScorePlus + url_git: '' +scoring: + version: '0.6' + title: Proper Scoring Rules + maintainer: Ed Merkle + description: Evaluating probabilistic forecasts via proper scoring rules. scoring + implements the beta, power, and pseudospherical families of proper scoring rules, + along with ordered versions of the latter two families. Included among these + families are popular rules like the Brier (quadratic) score, logarithmic score, + and spherical score. For two-alternative forecasts, also includes functionality + for plotting scores that one would obtain under specific scoring rules. + date_publication: '2018-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scoring + url_git: '' +scoringfunctions: + version: '1.0' + title: A Collection of Scoring Functions for Assessing Point Forecasts + maintainer: Hristos Tyralis + description: |- + Implements multiple consistent scoring functions + (Gneiting T (2011) ) for assessing point + forecasts and point predictions. Detailed documentation of scoring + functions' properties is included for facilitating interpretation of + results. + date_publication: '2024-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scoringfunctions + url_git: '' +scoringRules: + version: 1.1.3 + title: |- + Scoring Rules for Parametric and Simulated Distribution + Forecasts + maintainer: Fabian Krueger + description: |- + Dictionary-like reference for computing scoring rules in a wide + range of situations. Covers both parametric forecast distributions (such as + mixtures of Gaussians) and distributions generated via simulation. Further + details can be found in the package vignettes , + . + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scoringRules + url_git: https://github.com/FK83/scoringRules +scoringutils: + version: 2.0.0 + title: Utilities for Scoring and Assessing Predictions + maintainer: Nikos Bosse + description: |- + Facilitate the evaluation of forecasts in a convenient + framework based on data.table. It allows user to to check their forecasts + and diagnose issues, to visualise forecasts and missing data, to transform + data before scoring, to handle missing forecasts, to aggregate scores, and + to visualise the results of the evaluation. The package mostly focuses on + the evaluation of probabilistic forecasts and allows evaluating several + different forecast types and input formats. Find more information about the + package in the Vignettes as well as in the accompanying paper, + . + date_publication: '2024-10-31' + bug_reports: https://github.com/epiforecasts/scoringutils/issues + url: https://doi.org/10.48550/arXiv.2205.07090 + url_cran: https://CRAN.R-project.org/package=scoringutils + url_git: https://github.com/epiforecasts/scoringutils +SCORNET: + version: 0.1.1 + title: Semi-Supervised Calibration of Risk with Noisy Event Times + maintainer: Yuri Ahuja + description: A consistent, semi-supervised, non-parametric survival curve estimator + optimized for efficient use of Electronic Health Record (EHR) data with a limited + number of current status labels. See van der Laan and Robins (1997) . + date_publication: '2021-01-04' + bug_reports: https://github.com/celehs/SCORNET/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SCORNET + url_git: https://github.com/celehs/SCORNET +SCORPION: + version: 1.0.2 + title: |- + Single Cell Oriented Reconstruction of PANDA Individual + Optimized Networks + maintainer: Daniel Osorio + description: Constructs gene regulatory networks from single-cell gene expression + data using the PANDA (Passing Attributes between Networks for Data Assimilation) + algorithm. + date_publication: '2024-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCORPION + url_git: '' +SCORPIUS: + version: 1.0.9 + title: |- + Inferring Developmental Chronologies from Single-Cell RNA + Sequencing Data + maintainer: Robrecht Cannoodt + description: |- + An accurate and easy tool for performing linear trajectory inference on + single cells using single-cell RNA sequencing data. In addition, 'SCORPIUS' + provides functions for discovering the most important genes with respect to + the reconstructed trajectory, as well as nice visualisation tools. + Cannoodt et al. (2016) . + date_publication: '2023-08-07' + bug_reports: https://github.com/rcannood/SCORPIUS/issues + url: http://rcannood.github.io/SCORPIUS/ + url_cran: https://CRAN.R-project.org/package=SCORPIUS + url_git: https://github.com/rcannood/SCORPIUS +ScottKnott: + version: 1.3-2 + title: The ScottKnott Clustering Algorithm + maintainer: Ivan Bezerra Allaman + description: Perform the balanced (Scott and Knott, 1974) and unbalanced + Scott & Knott algorithm. + date_publication: '2023-08-30' + bug_reports: '' + url: https://lec.pro.br/software/pac-r/scottknott + url_cran: https://CRAN.R-project.org/package=ScottKnott + url_git: https://github.com/ivanalaman/ScottKnott +ScottKnottESD: + version: 2.0.3 + title: The Scott-Knott Effect Size Difference (ESD) Test + maintainer: Chakkrit Tantithamthavorn + description: The Scott-Knott Effect Size Difference (ESD) test is a mean comparison + approach that leverages a hierarchical clustering to partition the set of treatment + means (e.g., means of variable importance scores, means of model performance) + into statistically distinct groups with non-negligible difference [Tantithamthavorn + et al., (2018) ]. + date_publication: '2018-05-08' + bug_reports: https://github.com/klainfo/ScottKnottESD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ScottKnottESD + url_git: https://github.com/klainfo/ScottKnottESD +scout: + version: 1.0.4 + title: |- + Implements the Scout Method for Covariance-Regularized + Regression + maintainer: Daniela M. Witten + description: 'Implements the Scout method for regression, described in "Covariance-regularized + regression and classification for high-dimensional problems", by Witten and Tibshirani + (2008), Journal of the Royal Statistical Society, Series B 71(3): 615-636.' + date_publication: '2015-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scout + url_git: '' +scoutbaR: + version: 0.0.1 + title: A Spotlight 'React' Widget for 'shiny' Apps + maintainer: David Granjon + description: |- + Creates a contextual menu that can be triggered with keyboard shortcuts or programmatically. + This can replace traditional sidebars or navigation bars, thereby enhancing the + user experience with lighter user interfaces. + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scoutbaR + url_git: '' +SCOUTer: + version: 1.0.0 + title: Simulate Controlled Outliers + maintainer: Alba Gonzalez Cebrian + description: |- + Using principal component analysis as a base model, 'SCOUTer' + offers a new approach to simulate outliers in a simple and precise way. + The user can generate new observations defining them by a pair of well-known + statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2) + statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer' + returns a new set of observations with the desired target properties. + Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and + Alberto Ferrer (2020). + date_publication: '2020-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCOUTer + url_git: '' +SCperf: + version: 1.1.1 + title: |- + Functions for Planning and Managing Inventories in a Supply + Chain + maintainer: Marlene Marchena + description: Implements different inventory models, the bullwhip effect and other + supply chain performance variables. Marchena Marlene (2010) . + date_publication: '2018-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCperf + url_git: '' +scperturbR: + version: 0.1.0 + title: E-Statistics for Seurat Objects + maintainer: Stefan Peidli + description: |- + R version of 'scperturb' tool for single-cell perturbation + analysis. Contains wrappers for performing E-statistics for Seurat objects. + More details on the method can be found in Peidli et al. (2023) + and in Székely and Rizzo (2004). + date_publication: '2023-03-01' + bug_reports: https://github.com/sanderlab/scPerturb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scperturbR + url_git: https://github.com/sanderlab/scPerturb/tree/master/package_r +scpi: + version: 3.0.0 + title: |- + Prediction Intervals for Synthetic Control Methods with Multiple + Treated Units and Staggered Adoption + maintainer: Filippo Palomba + description: Implementation of prediction and inference procedures for Synthetic + Control methods using least square, lasso, ridge, or simplex-type constraints. + Uncertainty is quantified with prediction intervals as developed in Cattaneo, + Feng, and Titiunik (2021) + for a single treated unit and in Cattaneo, Feng, Palomba, and Titiunik (2023) + for multiple treated units and staggered adoption. + More details about the software implementation can be found in Cattaneo, Feng, + Palomba, and Titiunik (2024) . + date_publication: '2025-01-31' + bug_reports: '' + url: https://nppackages.github.io/scpi/ + url_cran: https://CRAN.R-project.org/package=scpi + url_git: '' +scPloidy: + version: 0.6.2 + title: Infer Ploidy of Single Cells + maintainer: Fumihiko Takeuchi + description: |- + Compute ploidy of single cells (or nuclei) + based on single-cell (or single-nucleus) + ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) + data . + date_publication: '2024-04-28' + bug_reports: https://github.com/fumi-github/scPloidy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scPloidy + url_git: '' +scplot: + version: 0.5.1 + title: Plot Function for Single-Case Data Frames + maintainer: Juergen Wilbert + description: |- + Add-on for the 'scan' package that creates plots + from single-case data frames ('scdf'). It includes functions for styling + single-case plots, adding phase-based lines to indicate various statistical + parameters, and predefined themes for presentations and publications. More + information and in depth examples can be found in the online book + "Analyzing Single-Case Data with R and 'scan" + Jürgen Wilbert (2025) . + date_publication: '2025-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scplot + url_git: '' +scpoisson: + version: 0.0.1 + title: Single Cell Poisson Probability Paradigm + maintainer: Yue Pan + description: |- + Useful to visualize the Poissoneity (an independent Poisson statistical framework, + where each RNA measurement for each cell comes from its own independent Poisson distribution) of + Unique Molecular Identifier (UMI) based single cell RNA sequencing (scRNA-seq) data, and explore + cell clustering based on model departure as a novel data representation. + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scpoisson + url_git: '' +SCpubr: + version: 2.0.2 + title: |- + Generate Publication Ready Visualizations of Single Cell + Transcriptomics Data + maintainer: Enrique Blanco-Carmona + description: |- + A system that provides a streamlined way of generating + publication ready plots for known Single-Cell transcriptomics data in + a “publication ready” format. This is, the goal is to automatically + generate plots with the highest quality possible, that can be used + right away or with minimal modifications for a research article. + date_publication: '2023-10-11' + bug_reports: https://github.com/enblacar/SCpubr/issues/ + url: https://enblacar.github.io/SCpubr-book/ + url_cran: https://CRAN.R-project.org/package=SCpubr + url_git: https://github.com/enblacar/SCpubr/ +scqe: + version: 1.0.0 + title: Stability Controlled Quasi-Experimentation + maintainer: Kirsten Landsiedel + description: |- + Functions to implement the stability controlled + quasi-experiment (SCQE) approach to study the effects of + newly adopted treatments that were not assigned at random. This package + contains tools to help users avoid making statistical assumptions that rely + on infeasible assumptions. Methods developed in Hazlett (2019) + . + date_publication: '2021-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scqe + url_git: '' +scquantum: + version: 1.0.0 + title: |- + Estimate Ploidy and Absolute Copy Number from Single Cell + Sequencing + maintainer: Alexander Davis + description: Given bincount data from single-cell copy number profiling (segmented + or unsegmented), estimates ploidy, and uses the ploidy estimate to scale the data + to absolute copy numbers. Uses the modular quantogram proposed by Kendall (1986) + , modified by weighting segments according + to confidence, and quantifying confidence in the estimate using a theoretical + quantogram. Includes optional fused-lasso segmentation with the algorithm in Johnson + (2013) , using the implementation from glmgen + by Arnold, Sadhanala, and Tibshirani. + date_publication: '2022-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scquantum + url_git: '' +scR: + version: 0.4.0 + title: Estimate Vapnik-Chervonenkis Dimension and Sample Complexity + maintainer: Perry Carter + description: 'We provide a suite of tools for estimating the sample complexity of + a chosen model through theoretical bounds and simulation. The package incorporates + methods for estimating the Vapnik-Chervonenkis dimension (VCD) of a chosen algorithm, + which can be used to estimate its sample complexity. Alternatively, we provide + simulation methods to estimate sample complexity directly. For more details, see + Carter, P & Choi, D (2024). "Learning from Noise: Applying Sample Complexity for + Political Science Research" .' + date_publication: '2024-12-23' + bug_reports: https://github.com/pjesscarter/scR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scR + url_git: https://github.com/pjesscarter/scR +scraEP: + version: '1.2' + title: Scrape the Web with Extra Power + maintainer: Julien Boelaert + description: Tools for scraping information from webpages and other XML contents, + using XPath or CSS selectors. + date_publication: '2021-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scraEP + url_git: '' +scrapeR: + version: 0.1.8 + title: |- + These Functions Fetch and Extract Text Content from Specified + Web Pages + maintainer: Mathieu Dubeau + description: The 'scrapeR' package utilizes functions that fetch and extract text + content from specified web pages. It handles HTTP errors and parses HTML efficiently. + The package can handle hundreds of websites at a time using the scrapeR_in_batches() + command. + date_publication: '2024-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scrapeR + url_git: '' +scrappy: + version: 0.0.1 + title: A Simple Web Scraper + maintainer: Roberto Villegas-Diaz + description: |- + A group of functions to scrape data from different websites, for + academic purposes. + date_publication: '2021-01-09' + bug_reports: https://github.com/villegar/scrappy/issues/ + url: https://villegar.github.io/scrappy/ + url_cran: https://CRAN.R-project.org/package=scrappy + url_git: https://github.com/villegar/scrappy/ +ScreenClean: + version: 1.0.1 + title: Screen and clean variable selection procedures + maintainer: Qi Zhang + description: |- + Routines for a collection of screen-and-clean type + variable selection procedures, including UPS and GS. + date_publication: '2012-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ScreenClean + url_git: '' +ScreeNOT: + version: 0.1.0 + title: |- + 'ScreeNOT': MSE-Optimal Singular Value Thresholding in + Correlated Noise + maintainer: Elad Romanov + description: |- + Optimal hard thresholding of singular values. The procedure adaptively estimates the best singular value threshold under unknown noise characteristics. The threshold chosen by 'ScreeNOT' is optimal (asymptotically, in the sense of minimum Frobenius error) under the the so-called "Spiked model" of a low-rank matrix observed in additive noise. In contrast to previous works, the noise is not assumed to be i.i.d. or white; it can have an essentially arbitrary and unknown correlation structure, across either rows, columns or both. 'ScreeNOT' is proposed to practitioners as a mathematically solid alternative to Cattell's ever-popular but vague Scree Plot heuristic from 1966. + If you use this package, please cite our paper: David L. Donoho, Matan Gavish and Elad Romanov (2023). "ScreeNOT: Exact MSE-optimal singular value thresholding in correlated noise." Annals of Statistics, 2023 (To appear). . + date_publication: '2023-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ScreeNOT + url_git: '' +screenshot: + version: 0.9.1 + title: Take Screenshots (Screen Capture) from R Command + maintainer: Toshikazu Matsumura + description: Take screenshots from R command and locate an image position. + date_publication: '2024-05-30' + bug_reports: '' + url: https://matutosi.github.io/screenshot/ + url_cran: https://CRAN.R-project.org/package=screenshot + url_git: https://github.com/matutosi/screenshot +scregclust: + version: 0.2.0 + title: |- + Reconstructing the Regulatory Programs of Target Genes in + scRNA-Seq Data + maintainer: Felix Held + description: |- + Implementation of the scregclust algorithm + described in Larsson, Held, et al. (2024) + which reconstructs regulatory programs of target genes in scRNA-seq data. + Target genes are clustered into modules and each module is associated with a linear + model describing the regulatory program. + date_publication: '2024-12-06' + bug_reports: https://github.com/scmethods/scregclust/issues + url: https://scmethods.github.io/scregclust/ + url_cran: https://CRAN.R-project.org/package=scregclust + url_git: https://github.com/scmethods/scregclust/ +scribe: + version: 0.3.0 + title: Command Argument Parsing + maintainer: Jordan Mark Barbone + description: |- + A base dependency solution with basic argument parsing for use with + 'Rscript'. + date_publication: '2023-10-21' + bug_reports: https://github.com/jmbarbone/scribe/issues + url: https://jmbarbone.github.io/scribe/ + url_cran: https://CRAN.R-project.org/package=scribe + url_git: https://github.com/jmbarbone/scribe +scrime: + version: 1.3.5 + title: Analysis of High-Dimensional Categorical Data Such as SNP Data + maintainer: Holger Schwender + description: |- + Tools for the analysis of high-dimensional data developed/implemented + at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME). + Main focus is on SNP data. But most of the functions can also be applied to other + types of categorical data. + date_publication: '2018-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scrime + url_git: '' +SCRIP: + version: 1.0.0 + title: An Accurate Simulator for Single-Cell RNA Sequencing Data + maintainer: Fei Qin + description: |- + We provide a comprehensive scheme that is capable of simulating Single Cell RNA Sequencing data for various parameters of Biological Coefficient of Variation, + busting kinetics, differential expression (DE), cell or sample groups, cell trajectory, batch effect and other experimental designs. + 'SCRIP' proposed and compared two frameworks with Gamma-Poisson and Beta-Gamma-Poisson models for simulating Single Cell RNA Sequencing data. + Other reference is available in Zappia et al. (2017) . + date_publication: '2021-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCRIP + url_git: https://github.com/thecailab/SCRIP +script: + version: 0.1.3 + title: Identify Script Name + maintainer: Tim Bergsma + description: |- + Identifies the name of the current script + in a variety of contexts, e.g. interactively or + when sourced. Attempts to support RStudio environment. + Based on + and . + date_publication: '2024-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=script + url_git: '' +scriptexec: + version: 0.3.1 + title: Execute Native Scripts + maintainer: Sagie Gur-Ari + description: Run complex native scripts with a single command, similar to system + commands. + date_publication: '2019-04-12' + bug_reports: https://github.com/sagiegurari/scriptexec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scriptexec + url_git: https://github.com/sagiegurari/scriptexec +scriptloc: + version: 1.0.0 + title: Get the Location of the R Script that is Being Sourced/Executed + maintainer: Naren Chandran Sakthivel + description: Provides functions to retrieve the location of R scripts loaded through + the source() function or run from the command line using the Rscript command. + This functionality is analogous to the Bash shell's ${BASH_SOURCE[0]}. Users can + first set the project root's path relative to the script path and then all subsequent + paths relative to the root. This system ensures that all paths lead to the same + location regardless of where any script is executed/loaded from without resorting + to the use of setwd() at the top of the scripts. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scriptloc + url_git: '' +ScriptMapR: + version: 0.0.3 + title: R Script Visualization in Cytoscape + maintainer: Raphaël Bonnet + description: Displays the content of a R script into the 'Cytoscape' network-visualization + app . + date_publication: '2020-09-24' + bug_reports: https://github.com/peyronlab/ScriptMapR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ScriptMapR + url_git: '' +scriptName: + version: 1.0.1 + title: Determine a Script's Filename from Within the Script Itself + maintainer: Thomas Sibley + description: |- + A small set of functions wrapping up the call stack and command + line inspection needed to determine a running script's filename from + within the script itself. + date_publication: '2019-06-19' + bug_reports: https://github.com/MullinsLab/scriptName/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scriptName + url_git: https://github.com/MullinsLab/scriptName +scriptuRs: + version: 0.1.0 + title: Complete Text of the LDS Scriptures + maintainer: Andrew Heiss + description: |- + Full text, in data frames containing one row per verse, of the + Standard Works of The Church of Jesus Christ of Latter-day Saints (LDS). + These are the Old Testament, (KJV), the New Testament (KJV), the Book of + Mormon, the Doctrine and Covenants, and the Pearl of Great Price. + date_publication: '2019-01-09' + bug_reports: https://github.com/andrewheiss/scriptuRs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scriptuRs + url_git: https://github.com/andrewheiss/scriptuRs +scrm: + version: 1.7.5 + title: Simulating the Evolution of Biological Sequences + maintainer: Dirk Metzler + description: |- + A coalescent simulator that allows the rapid simulation of + biological sequences under neutral models of evolution, see + Staab et al. (2015) . + Different to other coalescent based simulations, + it has an optional approximation parameter that + allows for high accuracy while maintaining a linear run time cost for long + sequences. It is optimized for simulating massive data sets as produced by Next- + Generation Sequencing technologies for up to several thousand sequences. + date_publication: '2024-01-08' + bug_reports: https://github.com/scrm/scrm-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scrm + url_git: https://github.com/scrm/scrm-r +ScRNAIMM: + version: '0.1' + title: |- + Performing Single-Cell RNA-Seq Imputation by Using Mean/Median + Imputation + maintainer: Mohamed Soudy + description: Performing single-cell imputation in a way that preserves the biological + variations in the data. The package clusters the input data to do imputation for + each cluster, and do a distribution check using the Anderson-Darling normality + test to impute dropouts using mean or median (Yazici, B., & Yolacan, S. (2007) + ). + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ScRNAIMM + url_git: '' +scRNAstat: + version: 0.1.1 + title: A Pipeline to Process Single Cell RNAseq Data + maintainer: Yonghe Xia + description: |- + A pipeline that can process single or multiple Single Cell RNAseq + samples primarily specializes in Clustering and Dimensionality Reduction. + Meanwhile we use common cell type marker genes for T cells, B cells, Myeloid cells, + Epithelial cells, and stromal cells (Fiboblast, Endothelial cells, Pericyte, + Smooth muscle cells) to visualize the Seurat clusters, to facilitate labeling + them by biological names. Once users named each cluster, they can evaluate the + quality of them again and find the de novo marker genes also. + date_publication: '2021-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scRNAstat + url_git: '' +scRNAtools: + version: '1.0' + title: Single Cell RNA Sequencing Data Analysis Tools + maintainer: Qian Yang + description: We integrated the common analysis methods utilized in single cell RNA + sequencing data, which included cluster method, principal components analysis + (PCA), the filter of differentially expressed genes, pathway enrichment analysis + and correlated analysis methods. + date_publication: '2018-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scRNAtools + url_git: '' +scrobbler: + version: 1.0.3 + title: Download 'Scrobbles' from 'Last.fm' + maintainer: Conor Neilson + description: |- + 'Last.fm' is a music platform focussed on building a + detailed profile of a users listening habits. It does this by 'scrobbling' (recording) + every track you listen to on other platforms ('spotify', 'youtube', 'soundcloud' etc) + and transferring them to your 'Last.fm' database. This allows 'Last.fm' to act as a + complete record of your entire listening history. 'scrobbler' provides helper functions + to download and analyse your listening history in R. + date_publication: '2023-10-15' + bug_reports: https://github.com/condwanaland/scrobbler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scrobbler + url_git: https://github.com/condwanaland/scrobbler +scrollrevealR: + version: 0.2.0 + title: |- + Animate 'shiny' Elements when They Scroll into View using the + 'scrollrevealjs' Library + maintainer: Mohamed El Fodil Ihaddaden + description: |- + Allows the user to animate 'shiny' elements when scrolling to view them. + The animations are activated using the 'scrollrevealjs' library. See for more information. + date_publication: '2020-10-14' + bug_reports: https://github.com/feddelegrand7/scrollrevealR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scrollrevealR + url_git: https://github.com/feddelegrand7/scrollrevealR +scROSHI: + version: 1.0.0.0 + title: Robust Supervised Hierarchical Identification of Single Cells + maintainer: Lars Bosshard + description: 'Identifying cell types based on expression profiles is a pillar of + single cell analysis. ''scROSHI'' identifies cell types based on expression profiles + of single cell analysis by utilizing previously obtained cell type specific gene + sets. It takes into account the hierarchical nature of cell type relationship + and does not require training or annotated data. A detailed description of the + method can be found at: Prummer, Bertolini, Bosshard, Barkmann, Yates, Boeva, + The Tumor Profiler Consortium, Stekhoven, and Singer (2022) .' + date_publication: '2023-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scROSHI + url_git: '' +SCRT: + version: 1.3.1 + title: Single-Case Randomization Tests + maintainer: Tamal Kumar De + description: Design single-case phase, alternation and multiple-baseline experiments, + and conduct randomization tests on data gathered by means of such designs, as + discussed in Bulte and Onghena (2013) . + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCRT + url_git: '' +scrutiny: + version: 0.5.0 + title: Error Detection in Science + maintainer: Lukas Jung + description: |- + Test published summary statistics for consistency + (Brown and Heathers, 2017, ; + Allard, 2018, ; + Heathers and Brown, 2019, ). + The package also provides infrastructure for implementing new + error detection techniques. + date_publication: '2024-09-22' + bug_reports: https://github.com/lhdjung/scrutiny/issues + url: https://lhdjung.github.io/scrutiny/ + url_cran: https://CRAN.R-project.org/package=scrutiny + url_git: https://github.com/lhdjung/scrutiny/ +scrypt: + version: 0.1.6 + title: Key Derivation Functions for R Based on Scrypt + maintainer: Bob Jansen + description: |- + Functions for working with the scrypt key derivation functions + originally described by Colin Percival + and in Percival and Josefsson + (2016) . Scrypt is a password-based key derivation + function created by Colin Percival. The algorithm was specifically designed + to make it costly to perform large-scale custom hardware attacks by + requiring large amounts of memory. + date_publication: '2023-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scrypt + url_git: https://github.com/bobjansen/rscrypt +scryr: + version: 1.0.0 + title: An Interface to the 'Scryfall' API + maintainer: Caio Lente + description: |- + A simple, light, and robust interface between R and + the 'Scryfall' card data API . + date_publication: '2022-01-28' + bug_reports: '' + url: https://curso-r.github.io/scryr/ + url_cran: https://CRAN.R-project.org/package=scryr + url_git: https://github.com/curso-r/scryr +scs: + version: 3.2.4 + title: Splitting Conic Solver + maintainer: Florian Schwendinger + description: |- + Solves convex cone programs via operator splitting. Can solve: + linear programs ('LPs'), second-order cone programs ('SOCPs'), semidefinite programs + ('SDPs'), exponential cone programs ('ECPs'), and power cone programs ('PCPs'), or + problems with any combination of those cones. 'SCS' uses 'AMD' (a set of routines for permuting sparse matrices prior to factorization) and 'LDL' (a sparse 'LDL' factorization and solve package) from 'SuiteSparse' (). + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scs + url_git: https://github.com/FlorianSchwendinger/scs +scSorter: + version: 0.0.2 + title: Implementation of 'scSorter' Algorithm + maintainer: Jun Li + description: |- + Implements the algorithm described in + Guo, H., and Li, J., "scSorter: assigning cells to known cell types according to known marker genes". + Cluster cells to known cell types based on marker genes specified for each cell type. + date_publication: '2021-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scSorter + url_git: '' +scSpatialSIM: + version: 0.1.3.4 + title: A Point Pattern Simulator for Spatial Cellular Data + maintainer: Fridley Lab + description: Single cell resolution data has been valuable in learning about tissue + microenvironments and interactions between cells or spots. This package allows + for the simulation of this level of data, be it single cell or ‘spots’, in both + a univariate (single metric or cell type) and bivariate (2 or more metrics or + cell types) ways. As more technologies come to marker, more methods will be developed + to derive spatial metrics from the data which will require a way to benchmark + methods against each other. Additionally, as the field currently stands, there + is not a gold standard method to be compared against. We set out to develop an + R package that will allow users to simulate point patterns that can be biologically + informed from different tissue domains, holes, and varying degrees of clustering/colocalization. + The data can be exported as spatial files and a summary file (like 'HALO'). . + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scSpatialSIM + url_git: https://github.com/FridleyLab/scSpatialSIM +scTenifoldKnk: + version: 1.0.1 + title: |- + In-Silico Knockout Experiments from Single-Cell Gene Regulatory + Networks + maintainer: Daniel Osorio + description: A workflow based on 'scTenifoldNet' to perform in-silico knockout experiments + using single-cell RNA sequencing (scRNA-seq) data from wild-type (WT) control + samples as input. First, the package constructs a single-cell gene regulatory + network (scGRN) and knocks out a target gene from the adjacency matrix of the + WT scGRN by setting the gene’s outdegree edges to zero. Then, it compares the + knocked out scGRN with the WT scGRN to identify differentially regulated genes, + called virtual-knockout perturbed genes, which are used to assess the impact of + the gene knockout and reveal the gene’s function in the analyzed cells. + date_publication: '2021-01-22' + bug_reports: https://github.com/cailab-tamu/scTenifoldKnk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scTenifoldKnk + url_git: https://github.com/cailab-tamu/scTenifoldKnk +scTenifoldNet: + version: '1.3' + title: Construct and Compare scGRN from Single-Cell Transcriptomic Data + maintainer: Daniel Osorio + description: A workflow based on machine learning methods to construct and compare + single-cell gene regulatory networks (scGRN) using single-cell RNA-seq (scRNA-seq) + data collected from different conditions. Uses principal component regression, + tensor decomposition, and manifold alignment, to accurately identify even subtly + shifted gene expression programs. See for more + details. + date_publication: '2021-10-29' + bug_reports: https://github.com/cailab-tamu/scTenifoldNet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scTenifoldNet + url_git: https://github.com/cailab-tamu/scTenifoldNet +SCtools: + version: 0.3.3.1 + title: Extensions for Synthetic Controls Analysis + maintainer: Bruno Castanho Silva + description: Extends the functionality of the package 'Synth' as detailed in Abadie, + Diamond, and Hainmueller (2011) . Includes generating + and plotting placebos, post/pre-MSPE (Mean Squared Prediction Error) significance + tests and plots, and calculating average treatment effects for multiple treated + units. + date_publication: '2025-01-27' + bug_reports: https://github.com/bcastanho/SCtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SCtools + url_git: '' +sctransform: + version: 0.4.1 + title: Variance Stabilizing Transformations for Single Cell UMI Data + maintainer: Saket Choudhary + description: |- + A normalization method for single-cell UMI count data using a + variance stabilizing transformation. The transformation is based on a + negative binomial regression model with regularized parameters. As part of the + same regression framework, this package also provides functions for + batch correction, and data correction. See Hafemeister and Satija (2019) + , and Choudhary and Satija (2022) + for more details. + date_publication: '2023-10-19' + bug_reports: https://github.com/satijalab/sctransform/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sctransform + url_git: https://github.com/satijalab/sctransform +scuba: + version: 1.11-1 + title: Diving Calculations and Decompression Models + maintainer: Adrian Baddeley + description: |- + Code for describing and manipulating scuba diving profiles + (depth-time curves) and decompression models, + for calculating the predictions of decompression models, + for calculating maximum no-decompression time and decompression tables, + and for performing mixed gas calculations. + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scuba + url_git: '' +scUtils: + version: 0.1.0 + title: Utility Functions for Single-Cell RNA Sequencing Data + maintainer: Felix Frauhammer + description: |- + Analysis of single-cell RNA sequencing data can be simple and + clear with the right utility functions. This package collects such functions, + aiming to fulfill the following criteria: + code clarity over performance (i.e. plain R code instead of C code), + most important analysis steps over completeness + (analysis 'by hand', not automated integration etc.), + emphasis on quantitative visualization (intensity-coded color scale, etc.). + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=scUtils + url_git: '' +scutr: + version: 0.2.0 + title: Balancing Multiclass Datasets for Classification Tasks + maintainer: Keenan Ganz + description: Imbalanced training datasets impede many popular classifiers. To balance + training data, a combination of oversampling minority classes and undersampling + majority classes is useful. This package implements the SCUT (SMOTE and Cluster-based + Undersampling Technique) algorithm as described in Agrawal et. al. (2015) . + Their paper uses model-based clustering and synthetic oversampling to balance + multiclass training datasets, although other resampling methods are provided in + this package. + date_publication: '2023-11-17' + bug_reports: https://github.com/s-kganz/scutr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=scutr + url_git: https://github.com/s-kganz/scutr +SCVA: + version: 1.3.1 + title: Single-Case Visual Analysis + maintainer: Tamal Kumar De + description: Make graphical representations of single case data and transform graphical + displays back to raw data, as discussed in Bulte and Onghena (2013) . + The package also includes tools for visually analyzing single-case data, by displaying + central location, variability and trend. + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SCVA + url_git: '' +sda: + version: 1.3.8 + title: Shrinkage Discriminant Analysis and CAT Score Variable Selection + maintainer: Korbinian Strimmer + description: |- + Provides an efficient framework for + high-dimensional linear and diagonal discriminant analysis with + variable selection. The classifier is trained using James-Stein-type + shrinkage estimators and predictor variables are ranked using + correlation-adjusted t-scores (CAT scores). Variable selection error + is controlled using false non-discovery rates or higher criticism. + date_publication: '2021-11-21' + bug_reports: '' + url: https://strimmerlab.github.io/software/sda/ + url_cran: https://CRAN.R-project.org/package=sda + url_git: '' +SDaA: + version: 0.1-5 + title: 'Sampling: Design and Analysis' + maintainer: Tobias Verbeke + description: |- + Functions and Datasets from Lohr, S. (1999), Sampling: + Design and Analysis, Duxbury. + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SDaA + url_git: '' +sdafilter: + version: 1.0.0 + title: Symmetrized Data Aggregation + maintainer: Lilun Du + description: 'We develop a new class of distribution free multiple testing rules + for false discovery rate (FDR) control under general dependence. A key element + in our proposal is a symmetrized data aggregation (SDA) approach to incorporating + the dependence structure via sample splitting, data screening and information + pooling. The proposed SDA filter first constructs a sequence of ranking statistics + that fulfill global symmetry properties, and then chooses a data driven threshold + along the ranking to control the FDR. For more information, see the website below + and the accompanying paper: Du et al. (2020), "False Discovery Rate Control Under + General Dependence By Symmetrized Data Aggregation", .' + date_publication: '2020-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdafilter + url_git: '' +sdam: + version: 1.1.4 + title: Social Dynamics and Complexity in the Ancient Mediterranean + maintainer: Antonio Rivero Ostoic + description: Provides digital tools for performing analyses within Social Dynamics + and complexity in the Ancient Mediterranean (SDAM), which is a research group + based at the Department of History and Classical Studies at Aarhus University. + date_publication: '2022-09-05' + bug_reports: https://github.com/sdam-au/sdam/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=sdam + url_git: https://github.com/sdam-au/sdam/ +sdamr: + version: 0.2.0 + title: 'Statistics: Data Analysis and Modelling' + maintainer: Maarten Speekenbrink + description: |- + Data sets and functions to support the books "Statistics: Data + analysis and modelling" by Speekenbrink, M. (2021) + and "An R companion to + Statistics: data analysis and modelling" by Speekenbrink, M. (2021) + . All datasets + analysed in these books are provided in this package. In addition, the + package provides functions to compute sample statistics (variance, + standard deviation, mode), create raincloud and enhanced Q-Q plots, and + expand Anova results into omnibus tests and tests of individual + contrasts. + date_publication: '2022-11-16' + bug_reports: '' + url: https://mspeekenbrink.github.io/sdam-r/ + url_cran: https://CRAN.R-project.org/package=sdamr + url_git: '' +SDAR: + version: 0.9-55 + title: Stratigraphic Data Analysis + maintainer: John R. Ortiz + description: |- + A fast, consistent tool for plotting and facilitating the analysis of stratigraphic + and sedimentological data. Taking advantage of the flexible plotting tools available in R, + 'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for + outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness, + lithology, samples, sedimentary structures, colors, fossil content, bioturbation index, + gamma ray logs) (Johnson, 1992, ). + date_publication: '2020-10-21' + bug_reports: '' + url: https://doi.org/10.25573/data.13118426.v2 + url_cran: https://CRAN.R-project.org/package=SDAR + url_git: '' +SDAResources: + version: 0.1.1 + title: |- + Datasets and Functions for 'Sampling: Design and Analysis, 3rd + Edition' + maintainer: Yan Lu + description: |- + Includes all the datasets of 'Sampling: Design and Analysis' + (3rd edition by Sharon Lohr) in R format and additional functions for + analyzing and graphing probability samples. + date_publication: '2021-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SDAResources + url_git: '' +sdcHierarchies: + version: 0.21.0 + title: Create and (Interactively) Modify Nested Hierarchies + maintainer: Bernhard Meindl + description: |- + Provides functionality to generate, (interactively) modify (by adding, removing and renaming nodes) and convert nested hierarchies between different formats. + These tree like structures can be used to define for example complex hierarchical tables used for statistical disclosure control. + date_publication: '2024-01-10' + bug_reports: https://github.com/bernhard-da/sdcHierarchies/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sdcHierarchies + url_git: https://github.com/bernhard-da/sdcHierarchies +sdcLog: + version: 0.5.0 + title: |- + Tools for Statistical Disclosure Control in Research Data + Centers + maintainer: Matthias Gomolka + description: |- + Tools for researchers to explicitly show that their results + comply to rules for statistical disclosure control imposed by research + data centers. These tools help in checking descriptive statistics and + models and in calculating extreme values that are not individual data. + Also included is a simple function to create log files. The methods + used here are described in the "Guidelines for the checking of output + based on microdata research" by Bond, Brandt, and de Wolf (2015) + . + date_publication: '2022-03-19' + bug_reports: https://github.com/matthiasgomolka/sdcLog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sdcLog + url_git: https://github.com/matthiasgomolka/sdcLog +sdcMicro: + version: 5.7.8 + title: |- + Statistical Disclosure Control Methods for Anonymization of Data + and Risk Estimation + maintainer: Matthias Templ + description: |- + Data from statistical agencies and other institutions are mostly + confidential. This package, introduced in Templ, Kowarik and Meindl (2017) , can be used for the generation of anonymized + (micro)data, i.e. for the creation of public- and scientific-use files. + The theoretical basis for the methods implemented can be found in Templ (2017) . + Various risk estimation and anonymization methods are included. Note that the package + includes a graphical user interface published in Meindl and Templ (2019) that allows to use various methods of this + package. + date_publication: '2024-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdcMicro + url_git: https://github.com/sdcTools/sdcMicro +SDCNway: + version: 1.0.1 + title: Tools to Evaluate Disclosure Risk + maintainer: John Riddles + description: |- + Tools for calculating disclosure risk measures for microdata, + including record-level and file-level measures. The record-level disclosure + risk is estimated primarily using exhaustive tabulation. The file-level + disclosure risk is estimated by fitting loglinear models on the observed + sample counts in cells formed by key variables and their interactions. + Funded by the National Center for Education Statistics. See Skinner and + Shlomo (2008) for a description of the + file-level risk measures and the loglinear model approach. + date_publication: '2020-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SDCNway + url_git: '' +sdcSpatial: + version: 0.5.2 + title: Statistical Disclosure Control for Spatial Data + maintainer: Edwin de Jonge + description: |- + Privacy protected raster maps + can be created from spatial point data. Protection + methods include smoothing of dichotomous variables by de Jonge and de Wolf (2016) + , continuous variables by de Wolf and + de Jonge (2018) , suppressing + revealing values and a generalization of the quad tree method by + Suñé, Rovira, Ibáñez and Farré (2017) . + date_publication: '2022-03-24' + bug_reports: https://github.com/edwindj/sdcSpatial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sdcSpatial + url_git: https://github.com/edwindj/sdcSpatial +sdcTable: + version: 0.32.6 + title: Methods for Statistical Disclosure Control in Tabular Data + maintainer: Bernhard Meindl + description: |- + Methods for statistical disclosure control in + tabular data such as primary and secondary cell suppression as described for example + in Hundepol et al. (2012) are covered in this package. + date_publication: '2023-08-11' + bug_reports: https://github.com/sdcTools/userSupport/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sdcTable + url_git: https://github.com/sdcTools/sdcTable +sde: + version: 2.0.18 + title: Simulation and Inference for Stochastic Differential Equations + maintainer: Stefano Maria Iacus + description: |- + Companion package to the book Simulation and Inference for + Stochastic Differential Equations With R Examples, ISBN + 978-0-387-75838-1, Springer, NY. + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sde + url_git: '' +SDEFSR: + version: 0.7.22 + title: Subgroup Discovery with Evolutionary Fuzzy Systems + maintainer: Angel M. Garcia + description: |- + Implementation of evolutionary fuzzy systems for the data mining task called + "subgroup discovery". In particular, the algorithms presented in this package are: + M. J. del Jesus, P. Gonzalez, F. Herrera, M. Mesonero (2007) + M. J. del Jesus, P. Gonzalez, F. Herrera (2007) + C. J. Carmona, P. Gonzalez, M. J. del Jesus, F. Herrera (2010) + C. J. Carmona, V. Ruiz-Rodado, M. J. del Jesus, A. Weber, M. Grootveld, P. González, D. Elizondo (2015) + It also provide a Shiny App to ease the analysis. The algorithms work with data sets provided in + KEEL, ARFF and CSV format and also with data.frame objects. + date_publication: '2021-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SDEFSR + url_git: https://github.com/SIMIDAT/SDEFSR +sdetorus: + version: 0.1.10 + title: Statistical Tools for Toroidal Diffusions + maintainer: Eduardo García-Portugués + description: |- + Implementation of statistical methods for the estimation of + toroidal diffusions. Several diffusive models are provided, most of them + belonging to the Langevin family of diffusions on the torus. Specifically, + the wrapped normal and von Mises processes are included, which can be seen + as toroidal analogues of the Ornstein-Uhlenbeck diffusion. A collection of + methods for approximate maximum likelihood estimation, organized in four + blocks, is given: (i) based on the exact transition probability density, + obtained as the numerical solution to the Fokker-Plank equation; (ii) based + on wrapped pseudo-likelihoods; (iii) based on specific analytic + approximations by wrapped processes; (iv) based on maximum likelihood of + the stationary densities. The package allows the replicability of the + results in García-Portugués et al. (2019) . + date_publication: '2024-03-01' + bug_reports: https://github.com/egarpor/sdetorus + url: '' + url_cran: https://CRAN.R-project.org/package=sdetorus + url_git: https://github.com/egarpor/sdetorus +SDGdetector: + version: 2.7.3 + title: Detect SDGs and Targets in Text + maintainer: Yingjie Li + description: Identify 17 Sustainable Development Goals and associated 169 targets + in text. + date_publication: '2023-05-23' + bug_reports: https://github.com/Yingjie4Science/SDGdetector/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SDGdetector + url_git: https://github.com/Yingjie4Science/SDGdetector +SDLfilter: + version: 2.3.3 + title: Filtering and Assessing the Sample Size of Tracking Data + maintainer: Takahiro Shimada + description: Functions to filter GPS/Argos locations, as well as assessing the sample + size for the analysis of animal distributions. The filters remove temporal and + spatial duplicates, fixes located at a given height from estimated high tide line, + and locations with high error as described in Shimada et al. (2012) + and Shimada et al. (2016) . Sample size for the + analysis of animal distributions can be assessed by the conventional area-based + approach or the alternative probability-based approach as described in Shimada + et al. (2021) . + date_publication: '2023-11-10' + bug_reports: https://github.com/TakahiroShimada/SDLfilter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SDLfilter + url_git: https://github.com/TakahiroShimada/SDLfilter +sdm: + version: 1.2-55 + title: Species Distribution Modelling + maintainer: Babak Naimi + description: |- + An extensible framework for developing species distribution + models using individual and community-based approaches, generate ensembles of + models, evaluate the models, and predict species potential distributions in + space and time. For more information, please check the following paper: + Naimi, B., Araujo, M.B. (2016) . + date_publication: '2025-01-11' + bug_reports: '' + url: https://www.biogeoinformatics.org + url_cran: https://CRAN.R-project.org/package=sdm + url_git: '' +SDModels: + version: 1.0.4 + title: Spectrally Deconfounded Models + maintainer: Markus Ulmer + description: Screen for and analyze non-linear sparse direct effects in the presence + of unobserved confounding using the spectral deconfounding techniques (Ćevid, + Bühlmann, and Meinshausen (2020), Guo, Ćevid, + and Bühlmann (2022) ). These methods have been shown to + be a good estimate for the true direct effect if we observe many covariates, e.g., + high-dimensional settings, and we have fairly dense confounding. Even if the assumptions + are violated, it seems like there is not much to lose, and the deconfounded models + will, in general, estimate a function closer to the true one than classical least + squares optimization. 'SDModels' provides functions SDAM() for Spectrally Deconfounded + Additive Models (Scheidegger, Guo, and Bühlmann (2025) ) + and SDForest() for Spectrally Deconfounded Random Forests (Ulmer, Scheidegger, + and Bühlmann (2025) ). + date_publication: '2025-02-19' + bug_reports: https://github.com/markusul/SDModels/issues + url: https://markusul.github.io/SDModels/ + url_cran: https://CRAN.R-project.org/package=SDModels + url_git: '' +sdmpredictors: + version: 0.2.15 + title: Species Distribution Modelling Predictor Datasets + maintainer: Salvador Fernandez + description: |- + Terrestrial and marine predictors for species distribution modelling + from multiple sources, including WorldClim ,, + ENVIREM , Bio-ORACLE + and MARSPEC . + date_publication: '2023-08-23' + bug_reports: https://github.com/lifewatch/sdmpredictors/issues + url: http://lifewatch.github.io/sdmpredictors/ + url_cran: https://CRAN.R-project.org/package=sdmpredictors + url_git: '' +sdmTMB: + version: 0.6.0 + title: Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB' + maintainer: Sean C. Anderson + description: |- + Implements spatial and spatiotemporal GLMMs (Generalized Linear + Mixed Effect Models) using 'TMB', 'fmesher', and the SPDE (Stochastic Partial + Differential Equation) Gaussian Markov random field approximation to + Gaussian random fields. One common application is for spatially explicit + species distribution models (SDMs). + See Anderson et al. (2024) . + date_publication: '2024-05-30' + bug_reports: https://github.com/pbs-assess/sdmTMB/issues + url: https://pbs-assess.github.io/sdmTMB/ + url_cran: https://CRAN.R-project.org/package=sdmTMB + url_git: https://github.com/pbs-assess/sdmTMB +SDMtune: + version: 1.3.2 + title: Species Distribution Model Selection + maintainer: Sergio Vignali + description: |- + User-friendly framework that enables the training and the + evaluation of species distribution models (SDMs). The package implements + functions for data driven variable selection and model tuning and includes + numerous utilities to display the results. All the functions used to select + variables or to tune model hyperparameters have an interactive real-time + chart displayed in the 'RStudio' viewer pane during their execution. + date_publication: '2024-12-16' + bug_reports: https://github.com/ConsBiol-unibern/SDMtune/issues + url: https://consbiol-unibern.github.io/SDMtune/ + url_cran: https://CRAN.R-project.org/package=SDMtune + url_git: '' +sdmvspecies: + version: 0.3.2 + title: Create Virtual Species for Species Distribution Modelling + maintainer: Xiaoquan Kong + description: |- + A software package help user to create virtual species for species distribution modelling. It includes + several methods to help user to create virtual species distribution map. + Those maps can be used for Species Distribution Modelling (SDM) study. SDM use + environmental data for sites of occurrence of a species to predict all the sites + where the environmental conditions are suitable for the species to persist, and + may be expected to occur. + date_publication: '2015-12-30' + bug_reports: https://github.com/howl-anderson/sdmvspecies/issues + url: http://www.sdmserialsoftware.org/sdmvspecies/ + url_cran: https://CRAN.R-project.org/package=sdmvspecies + url_git: '' +SDPDmod: + version: 0.0.5 + title: Spatial Dynamic Panel Data Modeling + maintainer: Rozeta Simonovska + description: |- + Spatial model calculation for static and dynamic panel data models, weights matrix creation and Bayesian model comparison. + Bayesian model comparison methods were described by 'LeSage' (2014) . + The 'Lee'-'Yu' transformation approach is described in 'Yu', 'De Jong' and 'Lee' (2008) , 'Lee' and 'Yu' (2010) and 'Lee' and 'Yu' (2010) . + date_publication: '2024-04-13' + bug_reports: https://github.com/RozetaSimonovska/SDPDmod/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=SDPDmod + url_git: '' +sdpdth: + version: '0.2' + title: M-Estimator for Threshold Spatial Dynamic Panel Data Model + maintainer: Junyue Wu + description: M-estimator for threshold and non-threshold spatial dynamic panel data + model. Yang, Z (2018) . Wu, J., Matsuda, Y + (2021) . + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdpdth + url_git: '' +sdPrior: + version: 1.0-0 + title: |- + Scale-Dependent Hyperpriors in Structured Additive + Distributional Regression + maintainer: Nadja Klein + description: |- + Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend + on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) . + date_publication: '2018-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdPrior + url_git: '' +sdprisk: + version: 1.1-6 + title: |- + Measures of Risk for the Compound Poisson Risk Process with + Diffusion + maintainer: Benjamin Baumgartner + description: |- + Based on the compound Poisson risk process that is perturbed by + a Brownian motion, saddlepoint approximations to some measures of risk are + provided. Various approximation methods for the probability of ruin are + also included. Furthermore, exact values of both the risk measures as well + as the probability of ruin are available if the individual claims follow + a hypo-exponential distribution (i. e., if it can be represented as a sum + of independent exponentially distributed random variables with different + rate parameters). For more details see Gatto and Baumgartner (2014) + . + date_publication: '2019-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdprisk + url_git: '' +SDPrism2D: + version: 0.1.1 + title: Visualizing the Standard Deviation as the Size of a Prism + maintainer: Hieu Nguyen + description: We visualize the standard deviation of a data set as the size of a + prism whose volume equals the total volume of several prisms made from the Empirical + Cumulative Distribution Function. + date_publication: '2022-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SDPrism2D + url_git: '' +sdrt: + version: 1.0.0 + title: |- + Estimating the Sufficient Dimension Reduction Subspaces in Time + Series + maintainer: Tharindu P. De Alwis + description: The sdrt() function is designed for estimating subspaces for Sufficient + Dimension Reduction (SDR) in time series, with a specific focus on the Time Series + Central Mean subspace (TS-CMS). The package employs the Fourier transformation + method proposed by Samadi and De Alwis (2023) + and the Nadaraya-Watson kernel smoother method proposed by Park et al. (2009) + for estimating the TS-CMS. The package provides + tools for estimating distances between subspaces and includes functions for selecting + model parameters using the Fourier transformation method. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdrt + url_git: '' +sdsfun: + version: 0.7.0 + title: Spatial Data Science Complementary Features + maintainer: Wenbo Lv + description: |- + Wrapping and supplementing commonly used functions in the R ecosystem related to spatial data science, + while serving as a basis for other packages maintained by Wenbo Lv. + date_publication: '2025-01-13' + bug_reports: https://github.com/stscl/sdsfun/issues + url: https://stscl.github.io/sdsfun/ + url_cran: https://CRAN.R-project.org/package=sdsfun + url_git: https://github.com/stscl/sdsfun +SDT: + version: 1.0.0 + title: Self-Determination Theory Measures + maintainer: Ali Uenlue + description: |- + Functions for self-determination motivation theory (SDT) to compute + measures of motivation internalization, motivation simplex structure, and of + the original and adjusted self-determination or relative autonomy index. SDT + was introduced by Deci and Ryan (1985) . See + package?SDT for an overview. + date_publication: '2018-01-18' + bug_reports: '' + url: http://www.meb.edu.tum.de + url_cran: https://CRAN.R-project.org/package=SDT + url_git: '' +sdtm.oak: + version: 0.1.1 + title: SDTM Data Transformation Engine + maintainer: Rammprasad Ganapathy + description: |- + An Electronic Data Capture system (EDC) and Data Standard agnostic + solution that enables the pharmaceutical programming community to develop + Clinical Data Interchange Standards Consortium (CDISC) + Study Data Tabulation Model (SDTM) datasets in R. The reusable algorithms + concept in 'sdtm.oak' provides a framework for modular programming and can + potentially automate the conversion of raw clinical data to SDTM through + standardized SDTM specifications. SDTM is one of the required standards for data + submission to the Food and Drug Administration (FDA) in the United States and + Pharmaceuticals and Medical Devices Agency (PMDA) in Japan. SDTM standards + are implemented following the SDTM Implementation Guide as defined by + CDISC . + date_publication: '2024-11-12' + bug_reports: https://github.com/pharmaverse/sdtm.oak/issues/ + url: https://pharmaverse.github.io/sdtm.oak/ + url_cran: https://CRAN.R-project.org/package=sdtm.oak + url_git: '' +sdtmchecks: + version: 1.0.0 + title: |- + Data Quality Checks for Study Data Tabulation Model (SDTM) + Datasets + maintainer: Will Harris + description: A series of checks to identify common issues in Study Data Tabulation + Model (SDTM) datasets. These checks are intended to be generalizable, actionable, + and meaningful for analysis. + date_publication: '2024-07-12' + bug_reports: https://github.com/pharmaverse/sdtmchecks/issues + url: https://pharmaverse.github.io/sdtmchecks/ + url_cran: https://CRAN.R-project.org/package=sdtmchecks + url_git: https://github.com/pharmaverse/sdtmchecks +sdtmval: + version: 0.4.1 + title: Validate SDTM Domains + maintainer: Stephen Knapp + description: |- + Provides a set of tools to assist statistical programmers + in validating Study Data Tabulation Model (SDTM) domain data sets. + Statistical programmers are required to validate that a SDTM data set domain + has been programmed correctly, per the SDTM Implementation Guide (SDTMIG) by + 'CDISC' (), + study specification, and study protocol using a process called double + programming. Double programming involves two different programmers + independently converting the raw electronic data cut (EDC) data into a SDTM + domain data table and comparing their results to ensure accurate + standardization of the data. One of these attempts is termed 'production' + and the other 'validation'. Generally, production runs are the official + programs for submittals and these are written in 'SAS'. Validation runs can + be programmed in another language, in this case 'R'. + date_publication: '2023-10-23' + bug_reports: https://github.com/skgithub14/sdtmval/issues + url: https://skgithub14.github.io/sdtmval/ + url_cran: https://CRAN.R-project.org/package=sdtmval + url_git: https://github.com/skgithub14/sdtmval +sdwd: + version: 1.0.5 + title: Sparse Distance Weighted Discrimination + maintainer: Boxiang Wang + description: Formulates a sparse distance weighted discrimination (SDWD) for high-dimensional + classification and implements a very fast algorithm for computing its solution + path with the L1, the elastic-net, and the adaptive elastic-net penalties. More + details about the methodology SDWD is seen on Wang and Zou (2016) (). + date_publication: '2020-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sdwd + url_git: '' +SE.EQ: + version: '1.0' + title: SE-Test for Equivalence + maintainer: Thomas Hoffelder + description: |- + Implements the SE-test for equivalence + according to Hoffelder et al. (2015) . + The SE-test for equivalence is a multivariate two-sample equivalence test. + Distance measure of the test is the sum of standardized differences + between the expected values or in other words: the sum of effect sizes (SE) + of all components of the two multivariate samples. + The test is an asymptotically valid test for normally distributed data + (see Hoffelder et al.,2015). + The function SE.EQ() implements the SE-test for equivalence + according to Hoffelder et al. (2015). + The function SE.EQ.dissolution.profiles() implements a variant + of the SE-test for equivalence for similarity analyses of dissolution + profiles as mentioned in Suarez-Sharp et al.(2020) + ). The equivalence margin used in + SE.EQ.dissolution.profiles() is analogically defined as for the T2EQ + approach according to Hoffelder (2019) ) + by means of a systematic shift in location + of 10 [\% of label claim] of both dissolution profile populations. + SE.EQ.dissolution.profiles() checks whether the weighted mean of the + differences of the expected values of both dissolution profile populations + is statistically significantly smaller than 10 [\% of label claim]. The + weights are built up by the inverse variances. + date_publication: '2020-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SE.EQ + url_git: '' +SEA: + version: 2.0.1 + title: Segregation Analysis + maintainer: Yuan-Ming Zhang + description: A few major genes and a series of polygene are responsive for each + quantitative trait. Major genes are individually identified while polygene is + collectively detected. This is mixed major genes plus polygene inheritance analysis + or segregation analysis (SEA). In the SEA, phenotypes from a single or multiple + bi-parental segregation populations along with their parents are used to fit all + the possible models and the best model of the trait for population phenotypic + distributions is viewed as the model of the trait. There are fourteen types of + population combinations available. Zhang Yuan-Ming, Gai Jun-Yi, Yang Yong-Hua + (2003, ). + date_publication: '2022-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEA + url_git: '' +seacarb: + version: 3.3.3 + title: Seawater Carbonate Chemistry + maintainer: Jean-Pierre Gattuso + description: Calculates parameters of the seawater carbonate system and assists + the design of ocean acidification perturbation experiments. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seacarb + url_git: '' +SEAGLE: + version: 1.0.1 + title: |- + Scalable Exact Algorithm for Large-Scale Set-Based + Gene-Environment Interaction Tests + maintainer: Jocelyn Chi + description: |2- + + The explosion of biobank data offers immediate opportunities for + gene-environment (GxE) interaction studies of complex diseases because of the + large sample sizes and rich collection in genetic and non-genetic information. + However, the extremely large sample size also introduces new computational + challenges in GxE assessment, especially for set-based GxE variance component (VC) + tests, a widely used strategy to boost overall GxE signals and to evaluate the + joint GxE effect of multiple variants from a biologically meaningful unit + (e.g., gene). + We present 'SEAGLE', a Scalable Exact AlGorithm for Large-scale Set-based + GxE tests, to permit GxE VC test scalable to biobank data. 'SEAGLE' employs modern + matrix computations to achieve the same “exact” results as the original GxE VC + tests, and does not impose additional assumptions nor relies on approximations. + 'SEAGLE' can easily accommodate sample sizes in the order of 10^5, is implementable + on standard laptops, and does not require specialized equipment. + The accompanying manuscript for this package can be found at Chi, Ipsen, Hsiao, + Lin, Wang, Lee, Lu, and Tzeng. (2021+) . + date_publication: '2021-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEAGLE + url_git: https://github.com/jocelynchi/SEAGLE +SEAHORS: + version: 1.8.0 + title: Spatial Exploration of ArcHaeological Objects in R Shiny + maintainer: Sebastien Plutniak + description: 'An R ''Shiny'' application dedicated to the intra-site spatial analysis + of piece-plotted archaeological remains, making the two and three-dimensional + spatial exploration of archaeological data as user-friendly as possible. Documentation + about ''SEAHORS'' is provided by the vignette included in this package and by + the companion scientific paper: Royer, Discamps, Plutniak, Thomas (2023, PCI Archaeology, + ).' + date_publication: '2023-06-23' + bug_reports: https://github.com/AurelienRoyer/SEAHORS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SEAHORS + url_git: https://github.com/AurelienRoyer/SEAHORS +sealasso: + version: 0.1-3 + title: Standard Error Adjusted Adaptive Lasso + maintainer: Wei Qian + description: Standard error adjusted adaptive lasso (SEA-lasso) is a version of + the adaptive lasso, which incorporates OLS standard error to the L1 penalty weight. + This method is intended for variable selection under linear regression settings + (n > p). This new weight assignment strategy is especially useful when the collinearity + of the design matrix is a concern. + date_publication: '2022-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sealasso + url_git: '' +seAMLess: + version: 0.1.1 + title: |- + A Single Cell Transcriptomics Based Deconvolution Pipeline for + Leukemia + maintainer: E Onur Karakaslar + description: Given a bulk transcriptomic (RNA-seq) sample of an Myeloid Leukemia + patient calculates immune composition and drug resistance for different small-molecule + inhibitors. Published in . + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seAMLess + url_git: https://github.com/eonurk/seAMLess +searcher: + version: 0.0.7 + title: Query Search Interfaces + maintainer: James Balamuta + description: |- + Provides a search interface to look up terms + on 'Google', 'Bing', 'DuckDuckGo', 'Startpage', 'Ecosia', 'rseek', + 'Twitter', 'StackOverflow', 'RStudio Community', 'GitHub', and 'BitBucket'. + Upon searching, a browser window will open with the aforementioned search + results. + date_publication: '2024-02-04' + bug_reports: https://github.com/coatless-rpkg/searcher/issues + url: https://r-pkg.thecoatlessprofessor.com/searcher/ + url_cran: https://CRAN.R-project.org/package=searcher + url_git: https://github.com/coatless-rpkg/searcher +SearchTrees: + version: 0.5.5 + title: Spatial Search Trees + maintainer: Gabriel Becker + description: |- + The QuadTree data structure is useful for fast, + neighborhood-restricted lookups. We use it to implement fast k-Nearest + Neighbor and Rectangular range lookups in 2 dimenions. The + primary target is high performance interactive graphics. + date_publication: '2022-10-03' + bug_reports: https://github.com/gmbecker/SearchTrees/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SearchTrees + url_git: https://github.com/gmbecker/SearchTrees +SEARS: + version: 0.1.0 + title: |- + Seamless Dose Escalation/Expansion with Adaptive Randomization + Scheme + maintainer: Chia-Wei Hsu + description: A seamless design that combines phase I dose escalation based on toxicity + with phase II dose expansion and dose comparison based on efficacy. + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEARS + url_git: '' +seas: + version: 0.6-0 + title: Seasonal Analysis and Graphics, Especially for Climatology + maintainer: Mike Toews + description: |- + Capable of deriving seasonal statistics, such as "normals", and + analysis of seasonal data, such as departures. This package also has + graphics capabilities for representing seasonal data, including boxplots for + seasonal parameters, and bars for summed normals. There are many specific + functions related to climatology, including precipitation normals, + temperature normals, cumulative precipitation departures and precipitation + interarrivals. However, this package is designed to represent any + time-varying parameter with a discernible seasonal signal, such as found + in hydrology and ecology. + date_publication: '2022-05-02' + bug_reports: https://github.com/mwtoews/seas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seas + url_git: https://github.com/mwtoews/seas +season: + version: 0.3.15 + title: Seasonal Analysis of Health Data + maintainer: Adrian Barnett + description: Routines for the seasonal analysis of health data, including regression + models, time-stratified case-crossover, plotting functions and residual checks, + see Barnett and Dobson (2010) ISBN 978-3-642-10748-1. Thanks to Yuming Guo for + checking the case-crossover code. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=season + url_git: '' +seasonal: + version: 1.10.0 + title: R Interface to X-13-ARIMA-SEATS + maintainer: Christoph Sax + description: |- + Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment + software by the US Census Bureau. It offers full access to almost all + options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model + search, outlier detection and support for user defined holiday variables, + such as Chinese New Year or Indian Diwali. A graphical user interface can be + used through the 'seasonalview' package. Uses the X-13-binaries from the + 'x13binary' package. + date_publication: '2024-10-19' + bug_reports: https://github.com/christophsax/seasonal/issues + url: http://www.seasonal.website + url_cran: https://CRAN.R-project.org/package=seasonal + url_git: '' +seasonalityPlot: + version: 1.3.1 + title: Seasonality Variation Plots of Stock Prices and Cryptocurrencies + maintainer: Satoshi Kume + description: |- + The price action at any given time is determined by investor + sentiment and market conditions. Although there is no established principle, + over a long period of time, things often move with a certain periodicity. + This is sometimes referred to as anomaly. + The seasonPlot() function in this package calculates and visualizes the + average value of price movements over a year for any given period. + In addition, the monthly increase or decrease in price movement is + represented with a colored background. + This seasonPlot() function can use the same symbols as the 'quantmod' package + (e.g. ^IXIC, ^DJI, SPY, BTC-USD, and ETH-USD etc). + date_publication: '2024-09-25' + bug_reports: https://github.com/kumeS/seasonalityPlot/issues + url: https://kumes.github.io/seasonalityPlot/ + url_cran: https://CRAN.R-project.org/package=seasonalityPlot + url_git: https://github.com/kumeS/seasonalityPlot +seasonalview: + version: 1.0.0 + title: Graphical User Interface for Seasonal Adjustment + maintainer: Christoph Sax + description: |- + A graphical user interface to the 'seasonal' package and + 'X-13ARIMA-SEATS', the U.S. Census Bureau's seasonal adjustment software. + date_publication: '2024-10-22' + bug_reports: https://github.com/christophsax/seasonalview/issues + url: http://www.seasonal.website + url_cran: https://CRAN.R-project.org/package=seasonalview + url_git: '' +seastests: + version: 0.15.4 + title: Seasonality Tests + maintainer: Daniel Ollech + description: |- + An overall test for seasonality of a given time + series in addition to a set of individual seasonality tests as + described by Ollech and Webel (forthcoming): An overall seasonality + test. Bundesbank Discussion Paper. + date_publication: '2021-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seastests + url_git: '' +SeaVal: + version: 1.2.0 + title: Validation of Seasonal Weather Forecasts + maintainer: Claudio Heinrich-Mertsching + description: |- + Provides tools for processing and evaluating seasonal weather forecasts, + with an emphasis on tercile forecasts. We follow the World Meteorological Organization's + "Guidance on Verification of Operational Seasonal Climate Forecasts", + S.J.Mason (2018, ISBN: 978-92-63-11220-0, URL: ). + The development was supported by the European Union’s Horizon 2020 research and innovation + programme under grant agreement no. 869730 (CONFER). + A comprehensive online tutorial is available at . + date_publication: '2024-06-14' + bug_reports: '' + url: https://seasonalforecastingengine.github.io/SeaValDoc/ + url_cran: https://CRAN.R-project.org/package=SeaVal + url_git: https://github.com/SeasonalForecastingEngine/SeaVal +seawaveQ: + version: 2.0.2 + title: SEAWAVE-Q Model + maintainer: Karen R. Ryberg + description: A model and utilities for analyzing trends in chemical concentrations + in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and + other ancillary variables. See Ryberg and York, 2020, . + date_publication: '2020-12-15' + bug_reports: '' + url: https://doi.org/10.3133/ofr20201082 + url_cran: https://CRAN.R-project.org/package=seawaveQ + url_git: '' +SeBR: + version: 1.0.0 + title: Semiparametric Bayesian Regression Analysis + maintainer: Dan Kowal + description: |- + Monte Carlo and MCMC sampling algorithms for semiparametric + Bayesian regression analysis. These models feature a nonparametric + (unknown) transformation of the data paired with widely-used + regression models including linear regression, spline regression, + quantile regression, and Gaussian processes. The transformation + enables broader applicability of these key models, including for + real-valued, positive, and compactly-supported data with challenging + distributional features. The samplers prioritize computational + scalability and, for most cases, Monte Carlo (not MCMC) sampling for + greater efficiency. Details of the methods and algorithms are provided + in Kowal and Wu (2023) . + date_publication: '2023-07-03' + bug_reports: https://github.com/drkowal/SeBR/issues + url: https://drkowal.github.io/SeBR/ + url_cran: https://CRAN.R-project.org/package=SeBR + url_git: https://github.com/drkowal/SeBR +SECFISH: + version: 0.1.7 + title: Disaggregate Variable Costs + maintainer: Isabella Bitetto + description: These functions were developed within SECFISH project (Strengthening + regional cooperation in the area of fisheries data collection-Socio-economic + data collection for fisheries, aquaculture and the processing industry at EU level). + They are aimed at identifying correlations between costs and transversal variables + by metier using individual vessel data and for disaggregating variable costs from fleet + segment to metier level. + date_publication: '2019-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SECFISH + url_git: '' +SECP: + version: 0.1.5 + title: Statistical Estimation of Cluster Parameters + maintainer: Pavel V. Moskalev + description: Estimating parameters of site clusters on 2D & 3D square lattice with + various lattice sizes, relative fractions of open sites (occupation probability), + iso- & anisotropy, von Neumann & Moore (1,d)-neighborhoods, described by Moskalev + P.V. et al. (2011) . + date_publication: '2022-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SECP + url_git: '' +secr: + version: 5.2.0 + title: Spatially Explicit Capture-Recapture + maintainer: Murray Efford + description: |- + Functions to estimate the density and size of a spatially + distributed animal population sampled with an array of passive detectors, + such as traps, or by searching polygons or transects. Models incorporating + distance-dependent detection are fitted by maximizing the likelihood. + Tools are included for data manipulation and model selection. + date_publication: '2025-01-24' + bug_reports: '' + url: https://www.otago.ac.nz/density/ + url_cran: https://CRAN.R-project.org/package=secr + url_git: https://github.com/MurrayEfford/secr/ +secrdesign: + version: 2.9.2 + title: Sampling Design for Spatially Explicit Capture-Recapture + maintainer: Murray Efford + description: Tools for designing spatially explicit capture-recapture studies of + animal populations. This is primarily a simulation manager for package 'secr'. + Extensions in version 2.5.0 include costing and evaluation of detector spacing. + date_publication: '2024-09-27' + bug_reports: '' + url: https://www.otago.ac.nz/density/ + url_cran: https://CRAN.R-project.org/package=secrdesign + url_git: https://github.com/MurrayEfford/secrdesign/ +secret: + version: 1.1.0 + title: Share Sensitive Information in R Packages + maintainer: Gábor Csárdi + description: |- + Allow sharing sensitive information, for example passwords, + 'API' keys, etc., in R packages, using public key cryptography. + date_publication: '2020-05-07' + bug_reports: https://github.com/gaborcsardi/secret/issues + url: '' + url_cran: https://CRAN.R-project.org/package=secret + url_git: https://github.com/gaborcsardi/secret#readme +secretbase: + version: 1.0.4 + title: Cryptographic Hash, Extendable-Output and Base64 Functions + maintainer: Charlie Gao + description: |- + Fast and memory-efficient streaming hash functions and base64 + encoding / decoding. Hashes strings and raw vectors directly. Stream hashes + files which can be larger than memory, as well as in-memory objects through + R's serialization mechanism. Implementations include the SHA-256, SHA-3 and + 'Keccak' cryptographic hash functions, SHAKE256 extendable-output function + (XOF), and 'SipHash' pseudo-random function. + date_publication: '2025-01-16' + bug_reports: https://github.com/shikokuchuo/secretbase/issues + url: https://shikokuchuo.net/secretbase/ + url_cran: https://CRAN.R-project.org/package=secretbase + url_git: https://github.com/shikokuchuo/secretbase/ +secrettext: + version: 0.1.0 + title: Encrypt Text Using a Shifting Substitution Cipher + maintainer: Danielle Quinn + description: Encrypt text using a simple shifting substitution cipher with setcode(), + providing two numeric keys used to define the encryption algorithm. The resulting + text can be decoded using decode() function and the two numeric keys specified + during encryption. + date_publication: '2020-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=secrettext + url_git: '' +secrlinear: + version: 1.2.4 + title: Spatially Explicit Capture-Recapture for Linear Habitats + maintainer: Murray Efford + description: Tools for spatially explicit capture-recapture analysis of animal populations + in linear habitats, extending package 'secr'. + date_publication: '2024-10-22' + bug_reports: '' + url: https://www.otago.ac.nz/density/ + url_cran: https://CRAN.R-project.org/package=secrlinear + url_git: https://github.com/MurrayEfford/secrlinear/ +secsse: + version: 3.1.0 + title: |- + Several Examined and Concealed States-Dependent Speciation and + Extinction + maintainer: Rampal S. Etienne + description: |- + Simultaneously infers state-dependent diversification across + two or more states of a single or multiple traits while accounting for the + role of a possible concealed trait. See Herrera-Alsina et al. (2019) + . + date_publication: '2024-04-30' + bug_reports: https://github.com/rsetienne/secsse/issues + url: https://rsetienne.github.io/secsse/ + url_cran: https://CRAN.R-project.org/package=secsse + url_git: https://github.com/rsetienne/secsse +sectorgap: + version: 0.1.0 + title: Consistent Economic Trend Cycle Decomposition + maintainer: Sina Streicher + description: Determining potential output and the output gap - two inherently unobservable + variables - is a major challenge for macroeconomists. 'sectorgap' features a flexible + modeling and estimation framework for a multivariate Bayesian state space model + identifying economic output fluctuations consistent with subsectors of the economy. + The proposed model is able to capture various correlations between output and + a set of aggregate as well as subsector indicators. Estimation of the latent states + and parameters is achieved using a simple Gibbs sampling procedure and various + plotting options facilitate the assessment of the results. For details on the + methodology and an illustrative example, see Streicher (2024) . + date_publication: '2024-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sectorgap + url_git: '' +secure: + version: '0.6' + title: Sequential Co-Sparse Factor Regression + maintainer: Aditya Mishra + description: Sequential factor extraction via co-sparse unit-rank estimation (SeCURE). + date_publication: '2021-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=secure + url_git: '' +secuTrialR: + version: 1.3.3 + title: |- + Handling of Data from the Clinical Data Management System + 'secuTrial' + maintainer: Alan G. Haynes + description: |- + Seamless and standardized interaction with data + exported from the clinical data management system (CDMS) + 'secuTrial'. + The primary data export the package works with is a standard non-rectangular export. + date_publication: '2024-05-30' + bug_reports: https://github.com/SwissClinicalTrialOrganisation/secuTrialR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=secuTrialR + url_git: https://github.com/SwissClinicalTrialOrganisation/secuTrialR +sedproxy: + version: 0.7.5 + title: Simulation of Sediment Archived Climate Proxy Records + maintainer: Andrew Dolman + description: |- + Proxy forward modelling for sediment archived climate proxies such + as Mg/Ca, d18O or Alkenones. The user provides a hypothesised "true" past climate, + such as output from a climate model, and details of the sedimentation rate and + sampling scheme of a sediment core. Sedproxy returns simulated proxy records. + Implements the methods described in Dolman and Laepple (2018) + . + date_publication: '2023-02-26' + bug_reports: '' + url: https://earthsystemdiagnostics.github.io/sedproxy/ + url_cran: https://CRAN.R-project.org/package=sedproxy + url_git: https://github.com/EarthSystemDiagnostics/sedproxy +see: + version: 0.10.0 + title: Model Visualisation Toolbox for 'easystats' and 'ggplot2' + maintainer: Indrajeet Patil + description: |- + Provides plotting utilities supporting packages in the 'easystats' + ecosystem () and some extra themes, + geoms, and scales for 'ggplot2'. Color scales are based on + . + References: Lüdecke et al. (2021) . + date_publication: '2025-01-22' + bug_reports: https://github.com/easystats/see/issues + url: https://easystats.github.io/see/ + url_cran: https://CRAN.R-project.org/package=see + url_git: '' +seeclickfixr: + version: 1.1.0 + title: Access Data from the SeeClickFix Web API + maintainer: Justin de Benedictis-Kessner + description: |- + Provides a wrapper to access data from the SeeClickFix + web API for R. SeeClickFix is a central platform employed by many cities + that allows citizens to request their city's services. This package + creates several functions to work with all the built-in calls to the + SeeClickFix API. Allows users to download service request data from + numerous locations in easy-to-use dataframe format manipulable in + standard R functions. + date_publication: '2016-12-07' + bug_reports: https://github.com/justindbk/seeclickfixr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seeclickfixr + url_git: '' +seecolor: + version: 0.2.0 + title: View Colors Used in R Objects in the Console + maintainer: Shangchen Song + description: Output colors used in literal vectors, palettes and plot objects (ggplot). + date_publication: '2023-02-24' + bug_reports: https://github.com/lovestat/seecolor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seecolor + url_git: https://github.com/lovestat/seecolor +SeedCalc: + version: 1.0.0 + title: Seed Germination and Seedling Growth Indexes + maintainer: Laercio Junio da Silva + description: 'Functions to calculate seed germination and seedling emergence and + growth indexes. The main indexes for germination and seedling emergence, considering + the time for seed germinate are: T10, T50 and T90, in Farooq et al. (2005) <10.1111/j.1744-7909.2005.00031.x>; + and MGT, in Labouriau (1983). Considering the germination speed are: Germination + Speed Index, in Maguire (1962), Mean Germination Rate, in Labouriau (1983); considering + the homogeneity of germination are: Coefficient of Variation of the Germination + Time, in Carvalho et al. (2005) <10.1590/S0100-84042005000300018>, and Variance + of Germination, in Labouriau (1983); Uncertainty, in Labouriau and Valadares (1976) + ; and Synchrony, in Primack (1980). The main seedling indexes + are Growth, in Sako (2001), Uniformity, in Sako (2001) and Castan et al. (2018) + ; and Vigour, in Medeiros and Pereira (2018) + .' + date_publication: '2018-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeedCalc + url_git: '' +seedCCA: + version: '3.1' + title: Seeded Canonical Correlation Analysis + maintainer: Jae Keun Yoo + description: Functions for dimension reduction through the seeded canonical correlation + analysis are provided. A classical canonical correlation analysis (CCA) is one + of useful statistical methods in multivariate data analysis, but it is limited + in use due to the matrix inversion for large p small n data. To overcome this, + a seeded CCA has been proposed in Im, Gang and Yoo (2015) \doi{10.1002/cem.2691}. + The seeded CCA is a two-step procedure. The sets of variables are initially reduced + by successively projecting cov(X,Y) or cov(Y,X) onto cov(X) and cov(Y), respectively, + without loss of information on canonical correlation analysis, following Cook, + Li and Chiaromonte (2007) \doi{10.1093/biomet/asm038} and Lee and Yoo (2014) \doi{10.1111/anzs.12057}. + Then, the canonical correlation is finalized with the initially-reduced two sets + of variables. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seedCCA + url_git: '' +seededlda: + version: 1.4.2 + title: Seeded Sequential LDA for Topic Modeling + maintainer: Kohei Watanabe + description: |- + Seeded Sequential LDA can classify sentences of texts into pre-define topics with a small number of seed words (Watanabe & Baturo, 2023) . + Implements Seeded LDA (Lu et al., 2010) and Sequential LDA (Du et al., 2012) with the distributed LDA algorithm (Newman, et al., 2009) for parallel computing. + date_publication: '2025-01-08' + bug_reports: https://github.com/koheiw/seededlda/issues + url: https://koheiw.github.io/seededlda/ + url_cran: https://CRAN.R-project.org/package=seededlda + url_git: https://github.com/koheiw/seededlda +SeedImbibition: + version: 0.1.0 + title: Seed Imbibition Percentage + maintainer: Tanuj Misra + description: Imbibition causes seeds to expand, which results in the seed coat or + testa being broken. Seed germination begins with imbibition. Imbibition aids in + the transport of water into the developing ovules. Imbibition is required during + the first stages of root water absorption. + date_publication: '2024-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeedImbibition + url_git: '' +SeedMaker: + version: 1.0.0 + title: Generate a Collection of Seeds from a Single Seed + maintainer: Hollins Showalter + description: |- + A mechanism for easily generating and organizing a collection of + seeds from a single seed, which may be subsequently used to ensure + reproducibility in processes/pipelines that utilize multiple random + components (e.g., trial simulation). + date_publication: '2025-01-17' + bug_reports: https://github.com/hdhshowalter/SeedMaker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SeedMaker + url_git: https://github.com/hdhshowalter/SeedMaker +SeedMatchR: + version: 1.1.1 + title: Find Matches to Canonical SiRNA Seeds in Genomic Features + maintainer: Tareian Cazares + description: |- + On-target gene knockdown using siRNA ideally results from binding + fully complementary regions in mRNA transcripts to induce cleavage. + Off-target siRNA gene knockdown can occur through several modes, one being + a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated + off-target effects occur when the ~8 nucleotides at the 5’ end of the guide + strand, called a seed region, bind the 3’ untranslated regions of mRNA, + causing reduced translation. Experiments using siRNA knockdown paired with + RNA-seq can be used to detect siRNA sequences with potential off-target + effects driven by the seed region. 'SeedMatchR' provides tools for exploring + and detecting potential seed-mediated off-target effects of siRNA in RNA-seq + experiments. 'SeedMatchR' is designed to extend current differential + expression analysis tools, such as 'DESeq2', by annotating results with + predicted seed matches. Using publicly available data, we demonstrate the + ability of 'SeedMatchR' to detect cumulative changes in differential gene + expression attributed to siRNA seed regions. + date_publication: '2023-10-24' + bug_reports: '' + url: https://tacazares.github.io/SeedMatchR/ + url_cran: https://CRAN.R-project.org/package=SeedMatchR + url_git: '' +seedr: + version: 0.3.0 + title: Hydro and Thermal Time Seed Germination Models in R + maintainer: Fernández-Pascual Eduardo + description: |- + Analysis of seed germination data + using the physiological time modelling approach. Includes functions + to fit hydrotime and thermal-time models with the traditional approaches + of Bradford (1990) + and Garcia-Huidobro (1982) . + Allows to fit models to grouped datasets, + i.e. datasets containing multiple species, seedlots or experiments. + date_publication: '2020-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seedr + url_git: https://github.com/efernandezpascual/seedr +seedreg: + version: 1.0.3 + title: |- + Regression Analysis for Seed Germination as a Function of + Temperature + maintainer: Gabriel Danilo Shimizu + description: 'Regression analysis using common models in seed temperature studies, + such as the Gaussian model (Martins, JF, Barroso, AAM, & Alves, PLCA (2017) ), + quadratic (Nunes, AL, Sossmeier, S, Gotz, AP, & Bispo, NB (2018) ) + and others with potential for use, such as those implemented in the ''drc'' package + (Ritz, C, Baty, F, Streibig, JC, & Gerhard, D (2015). ), + in the estimation of the ideal and cardinal temperature for the occurrence of + plant seed germination. The functions return graphs with the equations automatically.' + date_publication: '2022-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seedreg + url_git: '' +seeds: + version: 0.9.1 + title: Estimate Hidden Inputs using the Dynamic Elastic Net + maintainer: Tobias Newmiwaka + description: |- + Algorithms to calculate the hidden inputs of systems of differential equations. + These hidden inputs can be interpreted as a control that tries to minimize the + discrepancies between a given model and taken measurements. The idea is + also called the Dynamic Elastic Net, as proposed in the paper "Learning (from) the errors of a systems biology model" + (Engelhardt, Froelich, Kschischo 2016) . + To use the experimental SBML import function, the 'rsbml' package is required. For installation I refer to the official 'rsbml' page: . + date_publication: '2020-07-14' + bug_reports: https://github.com/Newmi1988/seeds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seeds + url_git: https://github.com/Newmi1988/seeds +SeedVigorIndex: + version: 0.1.0 + title: Seed Vigor Index + maintainer: Tanuj Misra + description: Seed vigor is defined as the sum total of those properties of the seed + which determine the level of activity and performance of the seed or seed lot + during germination and seedling emergence. Testing for vigor becomes more important + for carryover seeds, especially if seeds were stored under unknown conditions + or under unfavorable storage conditions. Seed vigor testing is also used as indicator + of the storage potential of a seed lot and in ranking various seed lots with different + qualities. The vigour index is calculated using the equation given by (Ling et + al. 2014) . + date_publication: '2024-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeedVigorIndex + url_git: '' +seer: + version: 1.1.8 + title: Feature-Based Forecast Model Selection + maintainer: Thiyanga Talagala + description: A novel meta-learning framework for forecast model selection using + time series features. Many applications require a large number of time series + to be forecast. Providing better forecasts for these time series is important + in decision and policy making. We propose a classification framework which selects + forecast models based on features calculated from the time series. We call this + framework FFORMS (Feature-based FORecast Model Selection). FFORMS builds a mapping + that relates the features of time series to the best forecast model using a random + forest. 'seer' package is the implementation of the FFORMS algorithm. For more + details see our paper at . + date_publication: '2022-10-01' + bug_reports: https://github.com/thiyangt/seer/issues + url: https://thiyangt.github.io/seer/ + url_cran: https://CRAN.R-project.org/package=seer + url_git: '' +SEERaBomb: + version: '2019.2' + title: SEER and Atomic Bomb Survivor Data Analysis Tools + maintainer: Tomas Radivoyevitch + description: |- + Creates SEER (Surveillance, Epidemiology and End Results) and + A-bomb data binaries from ASCII sources and provides tools for estimating + SEER second cancer risks. Methods are described in . + date_publication: '2019-12-12' + bug_reports: '' + url: http://epbi-radivot.cwru.edu/SEERaBomb/SEERaBomb.html + url_cran: https://CRAN.R-project.org/package=SEERaBomb + url_git: '' +seewave: + version: 2.2.3 + title: Sound Analysis and Synthesis + maintainer: Jerome Sueur + description: Functions for analysing, manipulating, displaying, editing and synthesizing + time waves (particularly sound). This package processes time analysis (oscillograms + and envelopes), spectral content, resonance quality factor, entropy, cross correlation + and autocorrelation, zero-crossing, dominant frequency, analytic signal, frequency + coherence, 2D and 3D spectrograms and many other analyses. See Sueur et al. (2008) + and Sueur (2018) . + date_publication: '2023-10-19' + bug_reports: '' + url: https://rug.mnhn.fr/seewave/ + url_cran: https://CRAN.R-project.org/package=seewave + url_git: '' +segclust2d: + version: 0.3.3 + title: Bivariate Segmentation/Clustering Methods and Tools + maintainer: Remi Patin + description: |- + Provides two methods for segmentation and joint segmentation/clustering of + bivariate time-series. Originally intended for ecological segmentation + (home-range and behavioural modes) but easily applied on other series, + the package also provides tools for analysing outputs from R packages 'moveHMM' and 'marcher'. + The segmentation method is a bivariate extension of Lavielle's method available in 'adehabitatLT' + (Lavielle, 1999 and 2005 ). + This method rely on dynamic programming for efficient segmentation. + The segmentation/clustering method alternates steps of dynamic programming with an Expectation-Maximization algorithm. + This is an extension of Picard et al (2007) method + (formerly available in 'cghseg' package) to the bivariate case. + The method is fully described in Patin et al (2018) . + date_publication: '2024-04-24' + bug_reports: https://github.com/rpatin/segclust2d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=segclust2d + url_git: https://github.com/rpatin/segclust2d +SegCorr: + version: '1.2' + title: Detecting Correlated Genomic Regions + maintainer: Eleni Ioanna Delatola + description: |- + Performs correlation matrix segmentation and applies a test + procedure to detect highly correlated regions in gene expression. + date_publication: '2017-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SegCorr + url_git: '' +segen: + version: 1.1.0 + title: Sequence Generalization Through Similarity Network + maintainer: Giancarlo Vercellino + description: Proposes an application for sequence prediction generalizing the similarity + within the network of previous sequences. + date_publication: '2022-08-15' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/segen + url_cran: https://CRAN.R-project.org/package=segen + url_git: '' +SegEnvIneq: + version: '1.2' + title: Environmental Inequality Indices Based on Segregation Measures + maintainer: Mihai Tivadar + description: |- + A set of segregation-based indices and randomization methods to + make robust environmental inequality assessments, as described in + Schaeffer and Tivadar (2019) "Measuring Environmental Inequalities: + Insights from the Residential Segregation Literature" + . + date_publication: '2024-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SegEnvIneq + url_git: '' +segmag: + version: 1.2.4 + title: Determine Event Boundaries in Event Segmentation Experiments + maintainer: Frank Papenmeier + description: |- + Contains functions that help to determine event + boundaries in event segmentation experiments by bootstrapping a critical + segmentation magnitude under the null hypothesis that all key presses were + randomly distributed across the experiment. Segmentation magnitude is + defined as the sum of Gaussians centered at the times of the segmentation + key presses performed by the participants. Within a participant, the maximum + of the overlaid Gaussians is used to prevent an excessive influence of a + single participant on the overall outcome (e.g. if a participant is pressing + the key multiple times in succession). Further functions are included, such + as plotting the results. + date_publication: '2016-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=segmag + url_git: '' +segmented: + version: 2.1-4 + title: |- + Regression Models with Break-Points / Change-Points Estimation + (with Possibly Random Effects) + maintainer: Vito M. R. Muggeo + description: |- + Fitting regression models where, in addition to possible linear terms, one or more covariates have segmented (i.e., broken-line or piece-wise linear) or stepmented (i.e. piece-wise constant) effects. Multiple breakpoints for the same variable are allowed. + The estimation method is discussed in Muggeo (2003, ) and + illustrated in Muggeo (2008, ). An approach for hypothesis testing is presented + in Muggeo (2016, ), and interval estimation for the breakpoint is discussed in Muggeo (2017, ). + Segmented mixed models, i.e. random effects in the change point, are discussed in Muggeo (2014, ). + Estimation of piecewise-constant relationships and changepoints (mean-shift models) is + discussed in Fasola et al. (2018, ). + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=segmented + url_git: '' +segmenTier: + version: 0.1.2 + title: Similarity-Based Segmentation of Multidimensional Signals + maintainer: Rainer Machne + description: |- + A dynamic programming solution to segmentation based on + maximization of arbitrary similarity measures within segments. + The general idea, theory and this implementation are described in + Machne, Murray & Stadler (2017) . + In addition to the core algorithm, the package provides time-series + processing and clustering functions as described in the publication. + These are generally applicable where a `k-means` clustering yields + meaningful results, and have been specifically developed for + clustering of the Discrete Fourier Transform of periodic gene + expression data (`circadian' or `yeast metabolic oscillations'). + This clustering approach is outlined in the supplemental material of + Machne & Murray (2012) ), and here + is used as a basis of segment similarity measures. Notably, the + time-series processing and clustering functions can also be used as + stand-alone tools, independent of segmentation, e.g., for + transcriptome data already mapped to genes. + date_publication: '2019-02-18' + bug_reports: https://github.com/raim/segmenTier/issues + url: '' + url_cran: https://CRAN.R-project.org/package=segmenTier + url_git: https://github.com/raim/segmenTier +segmentr: + version: 0.2.0 + title: Segment Data With Maximum Likelihood + maintainer: Thales Mello + description: |- + Given a likelihood provided by the user, this package applies it + to a given matrix dataset in order to find change points in the data that + maximize the sum of the likelihoods of all the segments. This package provides + a handful of algorithms with different time complexities and assumption compromises + so the user is able to choose the best one for the problem at hand. The implementation + of the segmentation algorithms in this package are based on the paper by Bruno M. de Castro, + Florencia Leonardi (2018) . The Berlin + weather sample dataset was provided by Deutscher Wetterdienst . + You can find all the references in the Acknowledgments section of this package's + repository via the URL below. + date_publication: '2019-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=segmentr + url_git: https://github.com/thalesmello/segmentr +segmetric: + version: 0.3.0 + title: Metrics for Assessing Segmentation Accuracy for Geospatial Data + maintainer: Michelle Picoli + description: |- + A system that computes metrics to assess the segmentation + accuracy of geospatial data. These metrics calculate the discrepancy + between segmented and reference objects, and indicate the segmentation + accuracy. For more details on choosing evaluation metrics, we + suggest seeing Costa et al. (2018) and + Jozdani et al. (2020) . + date_publication: '2023-01-10' + bug_reports: https://github.com/michellepicoli/segmetric/issues + url: https://michellepicoli.github.io/segmetric/ + url_cran: https://CRAN.R-project.org/package=segmetric + url_git: '' +segMGarch: + version: '1.2' + title: |- + Multiple Change-Point Detection for High-Dimensional GARCH + Processes + maintainer: Karolos Korkas + description: Implements a segmentation algorithm for multiple change-point detection + in high-dimensional GARCH processes. It simultaneously segments GARCH processes + by identifying 'common' change-points, each of which can be shared by a subset + or all of the component time series as a change-point in their within-series and/or + cross-sectional correlation structure. + date_publication: '2019-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=segMGarch + url_git: '' +segRDA: + version: 1.0.2 + title: Modeling Non-Continuous Linear Responses of Ecological Data + maintainer: Danilo C Vieira + description: 'Tools for modeling non-continuous linear responses of ecological communities + to environmental data. The package is straightforward through three steps: (1) + data ordering (function OrdData()), (2) split-moving-window analysis (function + SMW()) and (3) piecewise redundancy analysis (function pwRDA()). Relevant references + include Cornelius and Reynolds (1991) and Legendre and Legendre + (2012, ISBN: 9780444538697).' + date_publication: '2019-07-31' + bug_reports: https://github.com/DaniloCVieira/segRDA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=segRDA + url_git: https://github.com/DaniloCVieira/segRDA +segregation: + version: 1.1.0 + title: Entropy-Based Segregation Indices + maintainer: Benjamin Elbers + description: |- + Computes segregation indices, including the Index of Dissimilarity, + as well as the information-theoretic indices developed by + Theil (1971) , namely + the Mutual Information Index (M) and Theil's Information Index (H). + The M, further described by Mora and Ruiz-Castillo (2011) + and Frankel and Volij (2011) , + is a measure of segregation that is highly decomposable. The package provides + tools to decompose the index by units and groups (local segregation), + and by within and between terms. The package also provides a method to decompose + differences in segregation as described by Elbers (2021) . + The package includes standard error estimation by bootstrapping, which also corrects for + small sample bias. The package also contains functions for visualizing segregation patterns. + date_publication: '2023-12-02' + bug_reports: https://github.com/elbersb/segregation/issues + url: https://elbersb.github.io/segregation/ + url_cran: https://CRAN.R-project.org/package=segregation + url_git: '' +segregatr: + version: 0.4.0 + title: Segregation Analysis for Variant Interpretation + maintainer: Magnus Dehli Vigeland + description: |- + An implementation of the full-likelihood Bayes factor (FLB) + for evaluating segregation evidence in clinical medical genetics. The + method was introduced by Thompson et al. (2003) . + This implementation supports custom penetrance values and liability + classes, and allows visualisations and robustness analysis as + presented in Ratajska et al. (2023) . See also the + online app 'shinyseg', , which + offers interactive segregation analysis with many additional features + (Carrizosa et al. (2024) ). + date_publication: '2024-06-28' + bug_reports: https://github.com/magnusdv/segregatr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=segregatr + url_git: https://github.com/magnusdv/segregatr +segtest: + version: 1.0.2 + title: Tests for Segregation Distortion in Polyploids + maintainer: David Gerard + description: |- + Provides a suite of tests for + segregation distortion in F1 polyploid populations (for + now, just tetraploids). This is under different assumptions of + meiosis. Details of these methods are described in + Gerard et al. (2025) . + This material is based upon work supported by the + National Science Foundation under Grant No. 2132247. The + opinions, findings, and conclusions or recommendations expressed + are those of the author and do not necessarily reflect the views + of the National Science Foundation. + date_publication: '2025-01-16' + bug_reports: https://github.com/dcgerard/segtest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=segtest + url_git: https://github.com/dcgerard/segtest +seguid: + version: 0.1.0 + title: Sequence Globally Unique Identifier (SEGUID) Checksums + maintainer: Henrik Bengtsson + description: Implementation of the original Sequence Globally Unique Identifier + (SEGUID) algorithm [Babnigg and Giometti (2006) ] + and SEGUID v2 (), which extends SEGUID v1 with support + for linear, circular, single- and double-stranded biological sequences, e.g. DNA, + RNA, and proteins. + date_publication: '2024-03-04' + bug_reports: https://github.com/seguid/seguid-r/issues + url: https://www.seguid.org/ + url_cran: https://CRAN.R-project.org/package=seguid + url_git: '' +sehrnett: + version: 0.1.0 + title: A Very Nice Interface to 'WordNet' + maintainer: Chung-hong Chan + description: A very nice interface to Princeton's 'WordNet' without 'rJava' dependency. + 'WordNet' data is not included. Princeton University makes 'WordNet' available + to research and commercial users free of charge provided the terms of their license + () are followed, and + proper reference is made to the project using an appropriate citation (). + date_publication: '2023-03-02' + bug_reports: https://github.com/chainsawriot/sehrnett/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sehrnett + url_git: https://github.com/chainsawriot/sehrnett +SEI: + version: 0.2.0 + title: Calculating Standardised Indices + maintainer: Sam Allen + description: Convert a time series of observations to a time series of standardised + indices that can be used to monitor variables on a common and probabilistically + interpretable scale. The indices can be aggregated and rescaled to different time + scales, visualised using plot capabilities, and calculated using a range of distributions. + This includes flexible non-parametric and non-stationary methods. + date_publication: '2024-08-27' + bug_reports: '' + url: https://noeliaof.github.io/SEI/ + url_cran: https://CRAN.R-project.org/package=SEI + url_git: https://github.com/noeliaof/SEI +SEIRfansy: + version: 1.1.1 + title: Extended Susceptible-Exposed-Infected-Recovery Model + maintainer: Michael Kleinsasser + description: |- + Extended Susceptible-Exposed-Infected-Recovery Model for + handling high false negative rate and symptom based administration of + diagnostic tests. . + date_publication: '2021-09-27' + bug_reports: https://github.com/umich-biostatistics/SEIRfansy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SEIRfansy + url_git: https://github.com/umich-biostatistics/SEIRfansy +seismic: + version: '1.1' + title: Predict Information Cascade by Self-Exciting Point Process + maintainer: Qingyuan Zhao + description: An implementation of self-exciting point process model for information + cascades, which occurs when many people engage in the same acts after observing + the actions of others (e.g. post resharings on Facebook or Twitter). It provides + functions to estimate the infectiousness of an information cascade and predict + its popularity given the observed history. See + for more information and datasets. + date_publication: '2022-05-20' + bug_reports: '' + url: http://snap.stanford.edu/seismic/ + url_cran: https://CRAN.R-project.org/package=seismic + url_git: '' +seismicRoll: + version: 1.1.5 + title: Fast Rolling Functions for Seismology using 'Rcpp' + maintainer: Gillian Sharer + description: |- + Fast versions of seismic analysis functions that 'roll' over a + vector of values. See the 'RcppRoll' package for alternative + versions of basic statistical functions such as rolling mean, + median, etc. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seismicRoll + url_git: '' +sejmRP: + version: 1.3.4 + title: |- + An Information About Deputies and Votings in Polish Diet from + Seventh to Eighth Term of Office + maintainer: Piotr Smuda + description: |- + Set of functions that access information about deputies and votings + in Polish diet from webpage . The package was developed + as a result of an internship in MI2 Group - , Faculty + of Mathematics and Information Science, Warsaw University of Technology. + date_publication: '2017-03-28' + bug_reports: http://github.com/mi2-warsaw/sejmRP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sejmRP + url_git: '' +Sejong: + version: '0.01' + title: KoNLP static dictionaries and Sejong project resources. + maintainer: Heewon Jeon + description: Sejong(http://www.sejong.or.kr/) corpus andHannanum(http://semanticweb.kaist.ac.kr/home/index.php/HanNanum)dictionaries + for KoNLP + date_publication: '2012-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sejong + url_git: https://github.com/haven-jeon/Sejong +SEL: + version: 1.0-4 + title: Semiparametric Elicitation + maintainer: Bjoern Bornkamp + description: |- + Implements a method for fitting a bounded probability + distribution to quantiles (for example stated by an expert), + see Bornkamp and Ickstadt (2009) for details. For this + purpose B-splines are used, and the density is obtained by + penalized least squares based on a Brier entropy penalty. The + package provides methods for fitting the distribution as well + as methods for evaluating the underlying density and cdf. In + addition methods for plotting the distribution, drawing random + numbers and calculating quantiles of the obtained distribution + are provided. + date_publication: '2023-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEL + url_git: '' +selcorr: + version: '1.0' + title: Post-Selection Inference for Generalized Linear Models + maintainer: Marco Cattaneo + description: |- + Calculates (unconditional) post-selection confidence intervals + and p-values for the coefficients of (generalized) linear models. + date_publication: '2021-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=selcorr + url_git: '' +Select: + version: '1.4' + title: Determines Species Probabilities Based on Functional Traits + maintainer: Daniel Laughlin + description: |- + The objective of these functions is to derive a species assemblage + that satisfies a functional trait profile. Restoring resilient ecosystems + requires a flexible framework for selecting assemblages that are based on the + functional traits of species. However, current trait-based models have been + limited to algorithms that can only select species by optimising specific trait + values, and could not elegantly accommodate the common desire among restoration + ecologists to produce functionally diverse assemblages. We have solved this + problem by applying a non-linear optimisation algorithm that optimises Rao Q, + a closed-form functional trait diversity index that incorporates species + abundances, subject to other linear constraints. This framework generalises + previous models that only optimised the entropy of the community, and can + optimise both functional diversity and entropy simultaneously. This package + can also be used to generate experimental assemblages to test the effects + of community-level traits on community dynamics and ecosystem function. The + method is based on theory discussed in Laughlin (2014, Ecology Letters) + . + date_publication: '2018-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Select + url_git: '' +selectapref: + version: 0.1.2 + title: Analysis of Field and Laboratory Foraging + maintainer: Jason Richardson + description: Provides indices such as Manly's alpha, foraging ratio, and Ivlev's + selectivity to allow for analysis of dietary selectivity and preference. Can accommodate + multiple experimental designs such as constant prey number of prey depletion. + Please contact the package maintainer with any publications making use of this + package in an effort to maintain a repository of dietary selections studies. + date_publication: '2020-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=selectapref + url_git: '' +SelectBoost: + version: 2.2.2 + title: |- + A General Algorithm to Enhance the Performance of Variable + Selection Methods in Correlated Datasets + maintainer: Frederic Bertrand + description: An implementation of the selectboost algorithm (Bertrand et al. 2020, + 'Bioinformatics', ), which is a general algorithm + that improves the precision of any existing variable selection method. This algorithm + is based on highly intensive simulations and takes into account the correlation + structure of the data. It can either produce a confidence index for variable selection + or it can be used in an experimental design planning perspective. + date_publication: '2022-11-30' + bug_reports: https://github.com/fbertran/SelectBoost/issues/ + url: https://fbertran.github.io/SelectBoost/ + url_cran: https://CRAN.R-project.org/package=SelectBoost + url_git: https://github.com/fbertran/SelectBoost/ +selection.index: + version: 1.2.0 + title: Analysis of Selection Index in Plant Breeding + maintainer: Zankrut Goyani + description: The aim of most plant breeding programmes is simultaneous improvement + of several characters. An objective method involving simultaneous selection for + several attributes then becomes necessary. It has been recognised that most rapid + improvements in the economic value is expected from selection applied simultaneously + to all the characters which determine the economic value of a plant, and appropriate + assigned weights to each character according to their economic importance, heritability + and correlations between characters. So the selection for economic value is a + complex matter. If the component characters are combined together into an index + in such a way that when selection is applied to the index, as if index is the + character to be improved, most rapid improvement of economic value is expected. + Such an index was first proposed by Smith (1937 ) + based on the Fisher's (1936 ) "discriminant + function" Dabholkar (1999 ). + In this package selection index is calculated based on the Smith (1937) selection + index method. + date_publication: '2023-09-19' + bug_reports: https://github.com/zankrut20/selection.index/issues + url: '' + url_cran: https://CRAN.R-project.org/package=selection.index + url_git: https://github.com/zankrut20/selection.index +SelectionBias: + version: 2.0.0 + title: |- + Calculates Bounds for the Selection Bias for Binary Treatment + and Outcome Variables + maintainer: Stina Zetterstrom + description: |- + Computes bounds and sensitivity parameters as part of sensitivity + analysis for selection bias. Different bounds are provided: the SV (Smith + and VanderWeele), AF (assumption-free) bound, GAF (generalized + AF), and CAF (counterfactual AF) bounds. The calculation of the sensitivity + parameters for the SV and GAF bounds assume an additional dependence + structure in form of a generalized M-structure. The bounds can be + calculated for any structure as long as the necessary assumptions hold. See + Smith and VanderWeele (2019) , + Zetterstrom and Waernbaum (2022) and + Zetterstrom (2024) . + date_publication: '2024-03-27' + bug_reports: https://github.com/stizet/SelectionBias/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SelectionBias + url_git: https://github.com/stizet/SelectionBias +selectiongain: + version: 2.0.710 + title: |- + A Tool for Calculation and Optimization of the Expected Gain + from Multi-Stage Selection + maintainer: Xuefei Mi + description: |- + Multi-stage selection is practiced in numerous fields of life + and social sciences and particularly in breeding. A special characteristic of + multi-stage selection is that candidates are evaluated in successive stages + with increasing intensity and effort, and only a fraction of the superior + candidates is selected and promoted to the next stage. For the optimum design + of such selection programs, the selection gain plays a crucial role. It can be + calculated by integration of a truncated multivariate normal (MVN) distribution. + While mathematical formulas for calculating the selection gain and the variance + among selected candidates were developed long time ago, solutions for numerical + calculation were not available. This package can also be used for optimizing + multi-stage selection programs for a given total budget and different costs of + evaluating the candidates in each stage. + date_publication: '2022-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=selectiongain + url_git: '' +selectiveInference: + version: 1.2.5 + title: Tools for Post-Selection Inference + maintainer: Rob Tibshirani + description: |- + New tools for post-selection inference, for use with forward + stepwise regression, least angle regression, the lasso, and the many means + problem. The lasso function implements Gaussian, logistic and Cox survival + models. + date_publication: '2019-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=selectiveInference + url_git: '' +selectMeta: + version: 1.0.8 + title: Estimation of Weight Functions in Meta Analysis + maintainer: Kaspar Rufibach + description: Publication bias, the fact that studies identified for inclusion in + a meta analysis do not represent all studies on the topic of interest, is commonly + recognized as a threat to the validity of the results of a meta analysis. One + way to explicitly model publication bias is via selection models or weighted probability + distributions. In this package we provide implementations of several parametric + and nonparametric weight functions. The novelty in Rufibach (2011) is the proposal + of a non-increasing variant of the nonparametric weight function of Dear & Begg + (1992). The new approach potentially offers more insight in the selection process + than other methods, but is more flexible than parametric approaches. To maximize + the log-likelihood function proposed by Dear & Begg (1992) under a monotonicity + constraint we use a differential evolution algorithm proposed by Ardia et al (2010a, + b) and implemented in Mullen et al (2009). In addition, we offer a method to compute + a confidence interval for the overall effect size theta, adjusted for selection + bias as well as a function that computes the simulation-based p-value to assess + the null hypothesis of no selection as described in Rufibach (2011, Section 6). + date_publication: '2015-07-03' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=selectMeta + url_git: '' +selectr: + version: 0.4-2 + title: Translate CSS Selectors to XPath Expressions + maintainer: Simon Potter + description: |- + Translates a CSS3 selector into an equivalent XPath + expression. This allows us to use CSS selectors when working with + the XML package as it can only evaluate XPath expressions. Also + provided are convenience functions useful for using CSS selectors on + XML nodes. This package is a port of the Python package 'cssselect' + (). + date_publication: '2019-11-20' + bug_reports: https://github.com/sjp/selectr/issues + url: https://sjp.co.nz/projects/selectr + url_cran: https://CRAN.R-project.org/package=selectr + url_git: '' +selectspm: + version: '0.6' + title: |- + Select Point Pattern Models Based on Minimum Contrast, AIC and + Goodness of Fit + maintainer: Marcelino de la Cruz + description: Fit and selects point pattern models based on minimum contrast, AIC + and and goodness of fit. + date_publication: '2023-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=selectspm + url_git: '' +SeleMix: + version: 1.0.3 + title: Selective Editing via Mixture Models + maintainer: Teresa Buglielli + description: Detection of outliers and influential errors using a latent variable + model. + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeleMix + url_git: '' +selenider: + version: 0.4.1 + title: Concise, Lazy and Reliable Wrapper for 'chromote' and 'selenium' + maintainer: Ashby Thorpe + description: |- + A user-friendly wrapper for web automation, using either + 'chromote' or 'selenium'. Provides a simple and consistent API to make + web scraping and testing scripts easy to write and understand. + Elements are lazy, and automatically wait for the website to be valid, + resulting in reliable and reproducible code, with no visible impact on + the experience of the programmer. + date_publication: '2025-01-12' + bug_reports: https://github.com/ashbythorpe/selenider/issues + url: https://ashbythorpe.github.io/selenider/ + url_cran: https://CRAN.R-project.org/package=selenider + url_git: https://github.com/ashbythorpe/selenider +selenium: + version: 0.1.4 + title: Low-Level Browser Automation Interface + maintainer: Ashby Thorpe + description: |- + An implementation of 'W3C WebDriver 2.0' + (), allowing interaction + with a 'Selenium Server' () + instance from 'R'. Allows a web browser to be automated from 'R'. + date_publication: '2024-09-23' + bug_reports: https://github.com/ashbythorpe/selenium-r/issues + url: https://ashbythorpe.github.io/selenium-r/ + url_cran: https://CRAN.R-project.org/package=selenium + url_git: https://github.com/ashbythorpe/selenium-r +seleniumPipes: + version: 0.3.7 + title: R Client Implementing the W3C WebDriver Specification + maintainer: John Harrison + description: |- + The W3C WebDriver specification defines a way for out-of-process + programs to remotely instruct the behaviour of web browsers. It is detailed + at . This package provides + an R client implementing the W3C specification. + date_publication: '2016-10-01' + bug_reports: https://github.com/johndharrison/seleniumPipes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seleniumPipes + url_git: https://github.com/johndharrison/seleniumPipes +SELF: + version: 0.1.1 + title: |- + A Structural Equation Embedded Likelihood Framework for Causal + Discovery + maintainer: Jie Qiao + description: 'Provides the SELF criteria to learn causal structure. Please cite + "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational + Embedded Likelihood Framework for Causal Discovery. AAAI. 2018."' + date_publication: '2017-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SELF + url_git: '' +selfingTree: + version: '0.2' + title: |- + Genotype Probabilities in Intermediate Generations of Inbreeding + Through Selfing + maintainer: Frank Technow + description: |- + A probability tree allows to compute probabilities of + complex events, such as genotype probabilities in intermediate generations of inbreeding + through recurrent self-fertilization (selfing). This package implements functionality to compute + probability trees for two- and three-marker genotypes in the F2 to F7 selfing + generations. The conditional probabilities are derived automatically + and in symbolic form. The package also provides functionality to + extract and evaluate the relevant probabilities. + date_publication: '2014-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=selfingTree + url_git: '' +sem: + version: 3.1-16 + title: Structural Equation Models + maintainer: Zhenghua Nie + description: |- + Functions for fitting general linear structural + equation models (with observed and latent variables) using the RAM approach, + and for fitting structural equations in observed-variable models by two-stage least squares. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sem + url_git: '' +semantic.assets: + version: 1.1.0 + title: Assets for 'shiny.semantic' + maintainer: Jakub Nowicki + description: Style sheets and JavaScript assets for 'shiny.semantic' package. + date_publication: '2024-01-08' + bug_reports: https://github.com/Appsilon/semantic.assets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semantic.assets + url_git: https://github.com/Appsilon/semantic.assets +semantic.dashboard: + version: 0.2.1 + title: Dashboard with Fomantic UI Support for Shiny + maintainer: Developers Appsilon + description: It offers functions for creating dashboard with Fomantic UI. + date_publication: '2021-11-09' + bug_reports: https://github.com/Appsilon/semantic.dashboard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semantic.dashboard + url_git: '' +semaphore: + version: 1.0.2 + title: Shared Memory Atomic Operations + maintainer: Daniel P. Smith + description: |- + Implements named semaphores from the 'boost' 'C++' library + . A semaphore object is shared amongst several + processes. This integer value can be safely incremented or decremented by + each processes. Processes can also wait (blocking) for the value to become + non-zero. + date_publication: '2024-11-13' + bug_reports: https://github.com/cmmr/semaphore/issues + url: https://cmmr.github.io/semaphore/ + url_cran: https://CRAN.R-project.org/package=semaphore + url_git: https://github.com/cmmr/semaphore +Semblance: + version: 1.1.0 + title: A Data-Driven Similarity Kernel on Probability Spaces + maintainer: Divyansh Agarwal + description: We present a rank-based Mercer kernel to compute a pair-wise similarity + metric corresponding to informative representation of data. We tailor the development + of a kernel to encode our prior knowledge about the data distribution over a probability + space. The philosophical concept behind our construction is that objects whose + feature values fall on the extreme of that feature’s probability mass distribution + are more similar to each other, than objects whose feature values lie closer to + the mean. Semblance emphasizes features whose values lie far away from the mean + of their probability distribution. The kernel relies on properties empirically + determined from the data and does not assume an underlying distribution. The use + of feature ranks on a probability space ensures that Semblance is computational + efficacious, robust to outliers, and statistically stable, thus making it widely + applicable algorithm for pattern analysis. The output from the kernel is a square, + symmetric matrix that gives proximity values between pairs of observations. + date_publication: '2019-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Semblance + url_git: '' +SEMdeep: + version: 1.0.0 + title: |- + Structural Equation Modeling with Deep Neural Network and + Machine Learning + maintainer: Barbara Tarantino + description: "Training and validation of a custom (or data-driven) Structural\nEquation + Models using layer-wise Deep Neural Networks or node-wise\nMachine Learning algorithms, + which extend the fitting procedures of\nthe\t'SEMgraph' R package ." + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEMdeep + url_git: https://github.com/BarbaraTarantino/SEMdeep +semdrw: + version: 0.1.0 + title: '''SEM Shiny''' + maintainer: Kartikeya Bolar + description: Interactive 'shiny' application for working with Structural Equation + Modelling technique. Runtime examples are provided in the package function as + well as at . + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semdrw + url_git: '' +semds: + version: 0.9-6 + title: Structural Equation Multidimensional Scaling + maintainer: Patrick Mair + description: Fits a structural equation multidimensional scaling (SEMDS) model for + asymmetric and three-way input dissimilarities. It assumes that the dissimilarities + are measured with errors. The latent dissimilarities are estimated as factor scores + within an SEM framework while the objects are represented in a low-dimensional + space as in MDS. + date_publication: '2018-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semds + url_git: '' +semEff: + version: 0.7.2 + title: |- + Automatic Calculation of Effects for Piecewise Structural + Equation Models + maintainer: Mark V. Murphy + description: |- + Automatically calculate direct, indirect, and total effects for + piecewise structural equation models, comprising lists of fitted models + representing structured equations (Lefcheck, 2016 ). + Confidence intervals are provided via bootstrapping. + date_publication: '2024-09-12' + bug_reports: https://github.com/murphymv/semEff/issues + url: https://murphymv.github.io/semEff/ + url_cran: https://CRAN.R-project.org/package=semEff + url_git: https://github.com/murphymv/semEff +semfindr: + version: 0.1.8 + title: Influential Cases in Structural Equation Modeling + maintainer: Shu Fai Cheung + description: |- + Sensitivity analysis in structural equation modeling using + influence measures and diagnostic plots. Support leave-one-out casewise + sensitivity analysis presented by Pek and MacCallum (2011) + and approximate casewise influence + using scores and casewise likelihood. + date_publication: '2024-04-08' + bug_reports: https://github.com/sfcheung/semfindr/issues + url: https://sfcheung.github.io/semfindr/ + url_cran: https://CRAN.R-project.org/package=semfindr + url_git: '' +semgram: + version: 0.1.0 + title: Extracting Semantic Motifs from Textual Data + maintainer: Oscar Stuhler + description: 'A framework for extracting semantic motifs around entities in textual + data. It implements an entity-centered semantic grammar that distinguishes six + classes of motifs: actions of an entity, treatments of an entity, agents acting + upon an entity, patients acted upon by an entity, characterizations of an entity, + and possessions of an entity. Motifs are identified by applying a set of extraction + rules to a parsed text object that includes part-of-speech tags and dependency + annotations - such as those generated by ''spacyr''. For further reference, see: + Stuhler (2022) .' + date_publication: '2022-05-31' + bug_reports: https://github.com/omstuhler/semgram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semgram + url_git: https://github.com/omstuhler/semgram +SEMgraph: + version: 1.2.3 + title: |- + Network Analysis and Causal Inference Through Structural + Equation Modeling + maintainer: Barbara Tarantino + description: |- + Estimate networks and causal relationships in complex systems through + Structural Equation Modeling. This package also includes functions for importing, + weight, manipulate, and fit biological network models within the + Structural Equation Modeling framework as outlined in the Supplementary Material of + Grassi M, Palluzzi F, Tarantino B (2022) . + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEMgraph + url_git: https://github.com/fernandoPalluzzi/SEMgraph +semhelpinghands: + version: 0.1.12 + title: Helper Functions for Structural Equation Modeling + maintainer: Shu Fai Cheung + description: |- + An assortment of helper functions for doing structural equation + modeling, mainly by 'lavaan' for now. Most of them are time-saving functions + for common tasks in doing structural equation modeling and reading the + output. This package is not for functions that implement advanced statistical + procedures. It is a light-weight package for simple functions that do simple + tasks conveniently, with as few dependencies as possible. + date_publication: '2024-11-02' + bug_reports: https://github.com/sfcheung/semhelpinghands/issues + url: https://sfcheung.github.io/semhelpinghands/ + url_cran: https://CRAN.R-project.org/package=semhelpinghands + url_git: '' +semiArtificial: + version: 2.4.1 + title: Generator of Semi-Artificial Data + maintainer: Marko Robnik-Sikonja + description: |- + Contains methods to generate and evaluate semi-artificial data sets. + Based on a given data set different methods learn data properties using machine learning algorithms and + generate new data with the same properties. + The package currently includes the following data generators: + i) a RBF network based generator using rbfDDA() from package 'RSNNS', + ii) a Random Forest based generator for both classification and regression problems + iii) a density forest based generator for unsupervised data + Data evaluation support tools include: + a) single attribute based statistical evaluation: mean, median, standard deviation, skewness, kurtosis, medcouple, L/RMC, KS test, Hellinger distance + b) evaluation based on clustering using Adjusted Rand Index (ARI) and FM + c) evaluation based on classification performance with various learning models, e.g., random forests. + date_publication: '2021-09-23' + bug_reports: '' + url: http://lkm.fri.uni-lj.si/rmarko/software/ + url_cran: https://CRAN.R-project.org/package=semiArtificial + url_git: '' +semicmprskcoxmsm: + version: 0.2.0 + title: |- + Use Inverse Probability Weighting to Estimate Treatment Effect + for Semi Competing Risks Data + maintainer: Yiran Zhang + description: Use inverse probability weighting methods to estimate treatment effect + under marginal structure model (MSM) for the transition hazard of semi competing + risk data, i.e. illness death model. We implement two specific such models, the + usual Markov illness death structural model and the general Markov illness death + structural model. We also provide the predicted three risks functions from the + marginal structure models. Zhang, Y. and Xu, R. (2022) . + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semicmprskcoxmsm + url_git: '' +SemiCompRisks: + version: '3.4' + title: |- + Hierarchical Models for Parametric and Semi-Parametric Analyses + of Semi-Competing Risks Data + maintainer: Kyu Ha Lee + description: 'Hierarchical multistate models are considered to perform the analysis + of independent/clustered semi-competing risks data. The package allows to choose + the specification for model components from a range of options giving users substantial + flexibility, including: accelerated failure time or proportional hazards regression + models; parametric or non-parametric specifications for baseline survival functions + and cluster-specific random effects distribution; a Markov or semi-Markov specification + for terminal event following non-terminal event. While estimation is mainly performed + within the Bayesian paradigm, the package also provides the maximum likelihood + estimation approach for several parametric models. The package also includes functions + for univariate survival analysis as complementary analysis tools.' + date_publication: '2021-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SemiCompRisks + url_git: '' +semicontMANOVA: + version: 0.1-8 + title: |- + Multivariate ANalysis of VAriance with Ridge Regularization for + Semicontinuous High-Dimensional Data + maintainer: Elena Sabbioni + description: Implements Multivariate ANalysis Of VAriance (MANOVA) parameters' inference + and test with regularization for semicontinuous high-dimensional data. The method + can be applied also in presence of low-dimensional data. The p-value can be obtained + through asymptotic distribution or using a permutation procedure. The package + gives also the possibility to simulate this type of data. Method is described + in Elena Sabbioni, Claudio Agostinelli and Alessio Farcomeni (2024) . + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semicontMANOVA + url_git: '' +SEMID: + version: 0.4.1 + title: Identifiability of Linear Structural Equation Models + maintainer: Nils Sturma + description: |- + Provides routines to check identifiability or non-identifiability + of linear structural equation models as described in Drton, Foygel, and + Sullivant (2011) , Foygel, Draisma, and Drton (2012) + , and other works. The routines are based on the graphical + representation of structural equation models. + date_publication: '2023-07-19' + bug_reports: https://github.com/Lucaweihs/SEMID/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SEMID + url_git: https://github.com/Lucaweihs/SEMID +semidist: + version: 0.1.0 + title: Measure Dependence Between Categorical and Continuous Variables + maintainer: Zhuoxi Li + description: |- + Semi-distance and mean-variance (MV) index are proposed to measure the dependence between a categorical random variable and a continuous variable. + Test of independence and feature screening for classification problems can be implemented via the two dependence measures. + For the details of the methods, see Zhong et al. (2023) ; + Cui and Zhong (2019) ; + Cui, Li and Zhong (2015) . + date_publication: '2023-11-21' + bug_reports: https://github.com/wzhong41/semidist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semidist + url_git: https://github.com/wzhong41/semidist +SemiEstimate: + version: 1.1.3 + title: Solve Semi-Parametric Estimation by Implicit Profiling + maintainer: Jinhua Su + description: Semi-parametric estimation problem can be solved by two-step Newton-Raphson + iteration. The implicit profiling method is an improved method + of two-step NR iteration especially for the implicit-bundled type of the parametric + part and non-parametric part. This package provides a function semislv() supporting + the above two methods and numeric derivative approximation for unprovided Jacobian + matrix. + date_publication: '2021-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SemiEstimate + url_git: '' +SemiMarkov: + version: 1.4.6 + title: Multi-States Semi-Markov Models + maintainer: Agnieszka Listwon-Krol + description: "Functions for fitting multi-state semi-Markov models to longitudinal + data. A parametric maximum likelihood estimation method adapted to deal with Exponential, + Weibull and Exponentiated Weibull distributions is considered. Right-censoring + can be taken into account and both constant and time-varying covariates can be + included using a Cox proportional model. Reference: A. Krol and P. Saint-Pierre + (2015) \t." + date_publication: '2019-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SemiMarkov + url_git: '' +seminr: + version: 2.3.4 + title: Building and Estimating Structural Equation Models + maintainer: Nicholas Patrick Danks + description: |- + A powerful, easy to syntax for specifying and estimating complex + Structural Equation Models. Models can be estimated using Partial + Least Squares Path Modeling or Covariance-Based Structural Equation + Modeling or covariance based Confirmatory Factor Analysis. Methods described in Ray, Danks, and Valdez (2021). + date_publication: '2024-10-13' + bug_reports: https://github.com/sem-in-r/seminr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seminr + url_git: https://github.com/sem-in-r/seminr +SemiPar: + version: 1.0-4.2 + title: Semiparametic Regression + maintainer: Billy Aung Myint + description: |- + Functions for semiparametric regression analysis, to + complement the book: Ruppert, D., Wand, M.P. and Carroll, R.J. + (2003). Semiparametric Regression. Cambridge University Press. + date_publication: '2018-04-16' + bug_reports: '' + url: http://matt-wand.utsacademics.info/SPmanu.pdf + url_cran: https://CRAN.R-project.org/package=SemiPar + url_git: '' +SemiPar.depCens: + version: 0.1.3 + title: |- + Copula Based Cox Proportional Hazards Models for Dependent + Censoring + maintainer: Negera Wakgari Deresa + description: |- + Copula based Cox proportional hazards models for survival data subject to dependent + censoring. This approach does not assume that the parameter defining the copula is known. The + dependency parameter is estimated with other finite model parameters by maximizing a Pseudo + likelihood function. The cumulative hazard function is estimated via estimating equations + derived based on martingale ideas. Available copula functions include Frank, Gumbel and Normal + copulas. Only Weibull and lognormal models are allowed for the censoring model, even though any + parametric model that satisfies certain identifiability conditions could be used. Implemented + methods are described in the article "Copula based Cox proportional hazards models for dependent + censoring" by Deresa and Van Keilegom (2024) . + date_publication: '2024-08-26' + bug_reports: https://github.com/Nago2020/SemiPar.depCens/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SemiPar.depCens + url_git: https://github.com/Nago2020/SemiPar.depCens +semlbci: + version: 0.11.3 + title: |- + Likelihood-Based Confidence Interval in Structural Equation + Models + maintainer: Shu Fai Cheung + description: |- + Forms likelihood-based confidence intervals + (LBCIs) for parameters in structural equation modeling, + introduced in Cheung and Pesigan (2023) + . Currently + implements the algorithm illustrated by Pek and Wu + (2018) , and supports the robust + LBCI proposed by Falk (2018) + . + date_publication: '2025-01-25' + bug_reports: https://github.com/sfcheung/semlbci/issues + url: https://sfcheung.github.io/semlbci/ + url_cran: https://CRAN.R-project.org/package=semlbci + url_git: '' +semlrtp: + version: 0.1.1 + title: Likelihood Ratio Test P-Values for Structural Equation Models + maintainer: Shu Fai Cheung + description: |- + Computes likelihood ratio test (LRT) p-values + for free parameters in a structural equation model. + Currently supports models fitted by the 'lavaan' package by + Rosseel (2012) . + date_publication: '2024-06-20' + bug_reports: https://github.com/sfcheung/semlrtp/issues + url: https://sfcheung.github.io/semlrtp/ + url_cran: https://CRAN.R-project.org/package=semlrtp + url_git: '' +semmcci: + version: 1.1.4 + title: Monte Carlo Confidence Intervals in Structural Equation Modeling + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Monte Carlo confidence intervals for free and defined parameters + in models fitted in the structural equation modeling package 'lavaan' + can be generated using the 'semmcci' package. + 'semmcci' has three main functions, namely, MC(), MCMI(), and MCStd(). + The output of 'lavaan' is passed as the first argument + to the MC() function or the MCMI() function to generate Monte Carlo confidence intervals. + Monte Carlo confidence intervals for the standardized estimates + can also be generated by passing the output of the MC() function or the MCMI() function + to the MCStd() function. + A description of the package and code examples + are presented in Pesigan and Cheung (2023) . + date_publication: '2024-03-17' + bug_reports: https://github.com/jeksterslab/semmcci/issues + url: https://jeksterslab.github.io/semmcci/ + url_cran: https://CRAN.R-project.org/package=semmcci + url_git: https://github.com/jeksterslab/semmcci +semmcmc: + version: 0.0.6 + title: |- + Bayesian Structural Equation Modeling in Multiple Omics Data + Integration + maintainer: Arnab Maity + description: |- + Provides Markov Chain Monte Carlo (MCMC) routine for the + structural equation modelling described in + Maity et. al. (2020) . This MCMC sampler is + useful when one attempts to perform an integrative survival analysis for multiple + platforms of the Omics data where the response is time to event and the + predictors are different omics expressions for different platforms. + date_publication: '2021-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semmcmc + url_git: '' +semnar: + version: 0.8.2 + title: Constructing and Interacting with Databases of Presentations + maintainer: Ioannis Kosmidis + description: Provides methods for constructing and maintaining a database of presentations + in R. The presentations are either ones that the user gives or gave or presentations + at a particular event or event series. The package also provides a plot method + for the interactive mapping of the presentations using 'leaflet' by grouping them + according to country, city, year and other presentation attributes. The markers + on the map come with popups providing presentation details (title, institution, + event, links to materials and events, and so on). + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semnar + url_git: '' +SemNeT: + version: 1.4.4 + title: Methods and Measures for Semantic Network Analysis + maintainer: Alexander P. Christensen + description: Implements several functions for the analysis of semantic networks + including different network estimation algorithms, partial node bootstrapping + (Kenett, Anaki, & Faust, 2014 ), random walk simulation + (Kenett & Austerweil, 2016 ), + and a function to compute global network measures. Significance tests and plotting + features are also implemented. + date_publication: '2023-08-12' + bug_reports: https://github.com/AlexChristensen/SemNeT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SemNeT + url_git: https://github.com/AlexChristensen/SemNeT +SemNetCleaner: + version: 1.3.4 + title: An Automated Cleaning Tool for Semantic and Linguistic Data + maintainer: Alexander P. Christensen + description: Implements several functions that automates the cleaning and spell-checking + of text data. Also converges, finalizes, removes plurals and continuous strings, + and puts text data in binary format for semantic network analysis. Uses the 'SemNetDictionaries' + package to make the cleaning process more accurate, efficient, and reproducible. + date_publication: '2021-09-16' + bug_reports: https://github.com/AlexChristensen/SemNetCleaner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SemNetCleaner + url_git: https://github.com/AlexChristensen/SemNetCleaner +SemNetDictionaries: + version: 0.2.0 + title: Dictionaries for the 'SemNetCleaner' Package + maintainer: Alexander P. Christensen + description: Implements dictionaries that can be used in the 'SemNetCleaner' package. + Also includes several functions aimed at facilitating the text cleaning analysis + in the 'SemNetCleaner' package. This package is designed to integrate and update + word lists and dictionaries based on each user's individual needs by allowing + users to store and save their own dictionaries. Dictionaries can be added to the + 'SemNetDictionaries' package by submitting user-defined dictionaries to . + date_publication: '2022-01-17' + bug_reports: https://github.com/AlexChristensen/SemNetDictionaries/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SemNetDictionaries + url_git: https://github.com/AlexChristensen/SemNetDictionaries +semnova: + version: 0.1-6 + title: Latent Repeated Measures ANOVA + maintainer: Benedikt Langenberg + description: |- + Latent repeated measures ANOVA (L-RM-ANOVA) is a structural + equation modeling based alternative to traditional repeated measures ANOVA. + L-RM-ANOVA extends the latent growth components approach by + Mayer et al. (2012) and introduces + latent variables to repeated measures analysis. + date_publication: '2020-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semnova + url_git: '' +semPlot: + version: 1.1.6 + title: |- + Path Diagrams and Visual Analysis of Various SEM Packages' + Output + maintainer: Sacha Epskamp + description: Path diagrams and visual analysis of various SEM packages' output. + date_publication: '2022-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semPlot + url_git: https://github.com/SachaEpskamp/semPlot +semPower: + version: 2.1.1 + title: Power Analyses for SEM + maintainer: Morten Moshagen + description: |- + Provides a-priori, post-hoc, and compromise power-analyses + for structural equation models (SEM). + date_publication: '2024-09-29' + bug_reports: https://github.com/moshagen/semPower/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semPower + url_git: https://github.com/moshagen/semPower +semptools: + version: 0.3.1 + title: Customizing Structural Equation Modelling Plots + maintainer: Shu Fai Cheung + description: |- + Most function focus on specific ways to customize a graph. + They use a 'qgraph' output as the first argument, and return a + modified 'qgraph' object. This allows the functions to be chained + by a pipe operator. + date_publication: '2024-11-09' + bug_reports: https://github.com/sfcheung/semptools/issues + url: https://sfcheung.github.io/semptools/ + url_cran: https://CRAN.R-project.org/package=semptools + url_git: '' +SEMsens: + version: 1.5.5 + title: A Tool for Sensitivity Analysis in Structural Equation Modeling + maintainer: Walter Leite + description: |- + Perform sensitivity analysis in structural equation modeling using + meta-heuristic optimization methods (e.g., ant colony optimization and others). + The references for the proposed methods are: + (1) Leite, W., & Shen, Z., Marcoulides, K., Fish, C., & Harring, J. (2022). + + (2) Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017) + ; + (3) Fisk, C., Harring, J., Shen, Z., Leite, W., Suen, K., & Marcoulides, K. + (2022). ; + (4) Socha, K., & Dorigo, M. (2008) . + We also thank Dr. Krzysztof Socha for sharing his research on ant colony optimization + algorithm with continuous domains and associated R code, + which provided the base for the development of this package. + date_publication: '2022-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEMsens + url_git: '' +semsfa: + version: '1.1' + title: Semiparametric Estimation of Stochastic Frontier Models + maintainer: Giancarlo Ferrara + description: 'Semiparametric Estimation of Stochastic Frontier Models following + a two step procedure: in the first step semiparametric or nonparametric regression + techniques are used to relax parametric restrictions of the functional form representing + technology and in the second step variance parameters are obtained by pseudolikelihood + estimators or by method of moments.' + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=semsfa + url_git: '' +semTools: + version: 0.5-6 + title: Useful Tools for Structural Equation Modeling + maintainer: Terrence D. Jorgensen + description: Provides tools for structural equation modeling, many of which extend + the 'lavaan' package; for example, to pool results from multiple imputations, + probe latent interactions, or test measurement invariance. + date_publication: '2022-05-10' + bug_reports: https://github.com/simsem/semTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semTools + url_git: https://github.com/simsem/semTools/wiki +semtree: + version: 0.9.20 + title: Recursive Partitioning for Structural Equation Models + maintainer: Andreas M. Brandmaier + description: |- + SEM Trees and SEM Forests -- an extension of model-based decision + trees and forests to Structural Equation Models (SEM). SEM trees hierarchically + split empirical data into homogeneous groups each sharing similar data patterns + with respect to a SEM by recursively selecting optimal predictors of these + differences. SEM forests are an extension of SEM trees. They are ensembles of + SEM trees each built on a random sample of the original data. By aggregating + over a forest, we obtain measures of variable importance that are more robust + than measures from single trees. A description of the method was published by + Brandmaier, von Oertzen, McArdle, & Lindenberger (2013) + and Arnold, Voelkle, & Brandmaier (2020) . + date_publication: '2024-04-08' + bug_reports: https://github.com/brandmaier/semtree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semtree + url_git: https://github.com/brandmaier/semtree +semver: + version: 0.2.0 + title: '''Semantic Versioning V2.0.0'' Parser' + maintainer: John Harrison + description: |- + Tools and functions for parsing, rendering and operating on + semantic version strings. Semantic versioning is a simple set of rules + and requirements that dictate how version numbers are assigned and + incremented as outlined at . + date_publication: '2017-01-06' + bug_reports: https://github.com/johndharrison/semver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semver + url_git: https://github.com/johndharrison/semver +semverutils: + version: 0.1.0 + title: Semantic Version Utilities + maintainer: Adam Wheeler + description: |- + Semantic Versions allow for standardized management versions. + This package implements semantic versioning handling in R. using R6 to + create a mutable object that can handle deciphering and checking versions. + date_publication: '2020-02-22' + bug_reports: https://github.com/ajwtech/semverutils/issues + url: '' + url_cran: https://CRAN.R-project.org/package=semverutils + url_git: https://github.com/ajwtech/semverutils +sendgridr: + version: 0.6.1 + title: Mail Sender Using 'Sendgrid' Service + maintainer: Chanyub Park + description: |- + Send email using 'Sendgrid' + mail API(v3) . + date_publication: '2022-11-06' + bug_reports: https://github.com/mrchypark/sendgridr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sendgridr + url_git: https://github.com/mrchypark/sendgridr +sendigR: + version: 1.0.0 + title: Enable Cross-Study Analysis of 'CDISC' 'SEND' Datasets + maintainer: Wenxian Wang + description: |- + A system enables cross study Analysis by extracting and filtering study data for + control animals from 'CDISC' 'SEND' Study Repository. + These data types are supported: Body Weights, Laboratory test results and Microscopic findings. + These database types are supported: 'SQLite' and 'Oracle'. + date_publication: '2022-08-18' + bug_reports: https://github.com/phuse-org/sendigR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sendigR + url_git: https://github.com/phuse-org/sendigR +sendmailR: + version: 1.4-0 + title: Send Email Using R + maintainer: Olaf Mersmann + description: |- + Package contains a simple SMTP client with minimal dependencies which + provides a portable solution for sending email, including file attachments and inline html reports, + from within R. SMTP Authentication and SSL/STARTTLS is implemented using curl. + date_publication: '2023-01-12' + bug_reports: https://github.com/olafmersmann/sendmailR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sendmailR + url_git: https://github.com/olafmersmann/sendmailR +sense: + version: 1.1.0 + title: Automatic Stacked Ensemble for Regression Tasks + maintainer: Giancarlo Vercellino + description: Stacked ensemble for regression tasks based on 'mlr3' framework with + a pipeline for preprocessing numeric and factor features and hyper-parameter tuning + using grid or random search. + date_publication: '2024-06-19' + bug_reports: '' + url: https://mlr3.mlr-org.com/ + url_cran: https://CRAN.R-project.org/package=sense + url_git: '' +sensemakr: + version: 0.1.6 + title: Sensitivity Analysis Tools for Regression Models + maintainer: Carlos Cinelli + description: |- + Implements a suite of sensitivity analysis tools + that extends the traditional omitted variable bias framework and makes it easier + to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) . + date_publication: '2024-07-22' + bug_reports: https://github.com/carloscinelli/sensemakr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sensemakr + url_git: https://github.com/carloscinelli/sensemakr +SensIAT: + version: 0.1.1 + title: Sensitivity Analysis for Irregular Assessment Times + maintainer: Andrew Redd + description: |- + Sensitivity analysis for trials with irregular and informative + assessment times, based on a new influence function-based, augmented + inverse intensity-weighted estimator. + date_publication: '2024-11-17' + bug_reports: https://github.com/UofUEpiBio/SensIAT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SensIAT + url_git: https://github.com/UofUEpiBio/SensIAT +sensibo.sky: + version: 1.0.0 + title: |- + Access to 'Sensibo Sky' API V2 for Air Conditioners Remote + Control + maintainer: Gabriele Baldassarre + description: |- + Provides an interface to the 'Sensibo Sky' API which allows to remotely control non-smart air conditioning units. + See for more informations. + date_publication: '2019-06-24' + bug_reports: https://github.com/theclue/sensibo.sky/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sensibo.sky + url_git: https://github.com/theclue/sensibo.sky +sensiPhy: + version: 0.8.5 + title: Sensitivity Analysis for Comparative Methods + maintainer: Gustavo Paterno + description: |- + An implementation of sensitivity analysis for phylogenetic comparative + methods. The package is an umbrella of statistical and graphical methods that + estimate and report different types of uncertainty in PCM: + (i) Species Sampling uncertainty (sample size; influential species and clades). + (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). + (iii) Data uncertainty (intraspecific variation and measurement error). + date_publication: '2020-04-02' + bug_reports: https://github.com/paternogbc/sensiPhy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sensiPhy + url_git: https://github.com/paternogbc/sensiPhy +sensitivity: + version: 1.30.1 + title: |- + Global Sensitivity Analysis of Model Outputs and Importance + Measures + maintainer: Bertrand Iooss + description: A collection of functions for sensitivity analysis of model outputs + (factor screening, global sensitivity analysis and robustness analysis), for variable + importance measures of data, as well as for interpretability of machine learning + models. Most of the functions have to be applied on scalar output, but several + functions support multi-dimensional outputs. + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivity + url_git: '' +sensitivity2x2xk: + version: '1.01' + title: Sensitivity Analysis for 2x2xk Tables in Observational Studies + maintainer: Paul R. Rosenbaum + description: Performs exact or approximate adaptive or nonadaptive Cochran-Mantel-Haenszel-Birch + tests and sensitivity analyses for one or two 2x2xk tables in observational studies. + date_publication: '2015-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivity2x2xk + url_git: '' +sensitivityCalibration: + version: 0.0.1 + title: |- + A Calibrated Sensitivity Analysis for Matched Observational + Studies + maintainer: Bo Zhang + description: |- + Implements the calibrated sensitivity analysis approach for matched observational studies. Our sensitivity analysis framework views matched sets as drawn from a super-population. The unmeasured confounder is modeled as a random variable. We combine matching and model-based covariate-adjustment methods to estimate the treatment effect. The hypothesized unmeasured confounder enters the picture as a missing covariate. We adopt a state-of-art Expectation Maximization (EM) algorithm to handle this missing covariate problem in generalized linear models (GLMs). As our method also estimates the effect of each observed covariate on the outcome and treatment assignment, we are able to calibrate the unmeasured confounder to observed covariates. + Zhang, B., Small, D. S. (2018). . + date_publication: '2018-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivityCalibration + url_git: '' +SensitivityCaseControl: + version: '2.2' + title: Sensitivity Analysis for Case-Control Studies + maintainer: Dylan Small + description: Sensitivity analysis for case-control studies in which some cases may + meet a more narrow definition of being a case compared to other cases which only + meet a broad definition. The sensitivity analyses are described in Small, Cheng, + Halloran and Rosenbaum (2013, "Case Definition and Sensitivity Analysis", Journal + of the American Statistical Association, 1457-1468). The functions sens.analysis.mh + and sens.analysis.aberrant.rank provide sensitivity analyses based on the Mantel-Haenszel + test statistic and aberrant rank test statistic as described in Rosenbaum (1991, + "Sensitivity Analysis for Matched Case Control Studies", Biometrics); see also + Section 1 of Small et al. The function adaptive.case.test provides adaptive inferences + as described in Section 5 of Small et al. The function adaptive.noether.brown + provides a sensitivity analysis for a matched cohort study based on an adaptive + test. The other functions in the package are internal functions. + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SensitivityCaseControl + url_git: '' +sensitivityfull: + version: 1.5.6 + title: Sensitivity Analysis for Full Matching in Observational Studies + maintainer: Paul R. Rosenbaum + description: Sensitivity to unmeasured biases in an observational study that is + a full match. Function senfm() performs tests and function senfmCI() creates + confidence intervals. The method uses Huber's M-statistics, including least squares, + and is described in Rosenbaum (2007, Biometrics) . + date_publication: '2017-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivityfull + url_git: '' +sensitivitymult: + version: 1.0.2 + title: |- + Sensitivity Analysis for Observational Studies with Multiple + Outcomes + maintainer: Paul R. Rosenbaum + description: Sensitivity analysis for multiple outcomes in observational studies. For + instance, all linear combinations of several outcomes may be explored using Scheffe + projections in the comparison() function; see Rosenbaum (2016, Annals of Applied + Statistics) . Alternatively, attention may focus on a + few principal components in the principal() function. The package includes parallel + methods for individual outcomes, including tests in the senm() function and confidence + intervals in the senmCI() function. + date_publication: '2017-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivitymult + url_git: '' +sensitivitymv: + version: 1.4.3 + title: Sensitivity Analysis in Observational Studies + maintainer: Paul R. Rosenbaum + description: The package performs a sensitivity analysis in an observational study + using an M-statistic, for instance, the mean. The main function in the package + is senmv(), but amplify() and truncatedP() are also useful. The method is developed + in Rosenbaum Biometrics, 2007, 63, 456-464, . + date_publication: '2018-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivitymv + url_git: '' +sensitivitymw: + version: '2.1' + title: |- + Sensitivity Analysis for Observational Studies Using Weighted + M-Statistics + maintainer: Paul R. Rosenbaum + description: Sensitivity analysis for tests, confidence intervals and estimates + in matched observational studies with one or more controls using weighted or unweighted + Huber-Maritz M-tests (including the permutational t-test). The method is from + Rosenbaum (2014) Weighted M-statistics with superior design sensitivity in matched + observational studies with multiple controls JASA, 109(507), 1145-1158 . + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensitivitymw + url_git: '' +SensMap: + version: '0.7' + title: Sensory and Consumer Data Mapping + maintainer: Ibtihel Rebhi + description: |- + Provides Sensory and Consumer Data + mapping and analysis . The mapping visualization is made available + from several features : options in dimension reduction methods and prediction models ranging from + linear to non linear regressions. A smoothed version of the map performed using locally weighted regression algorithm + is available. A selection process of map stability is provided. A 'shiny' application is included. + It presents an easy GUI for the implemented functions as well as a comparative tool of fit models + using several criteria. Basic analysis such as characterization of products, + panelists and sessions likewise consumer segmentation are also made available. + date_publication: '2022-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SensMap + url_git: https://github.com/IbtihelRebhi/SensMap +sensmediation: + version: 0.3.1 + title: |- + Parametric Estimation and Sensitivity Analysis of Direct and + Indirect Effects + maintainer: Anita Lindmark + description: We implement functions to estimate and perform sensitivity analysis + to unobserved confounding of direct and indirect effects introduced in Lindmark, + de Luna and Eriksson (2018) and Lindmark (2022) . + The estimation and sensitivity analysis are parametric, based on probit and/or + linear regression models. Sensitivity analysis is implemented for unobserved confounding + of the exposure-mediator, mediator-outcome and exposure-outcome relationships. + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensmediation + url_git: '' +sensobol: + version: 1.1.5 + title: Computation of Variance-Based Sensitivity Indices + maintainer: Arnald Puy + description: It allows to rapidly compute, bootstrap and plot up to fourth-order + Sobol'-based sensitivity indices using several state-of-the-art first and total-order + estimators. Sobol' indices can be computed either for models that yield a scalar + as a model output or for systems of differential equations. The package also provides + a suit of benchmark tests functions and several options to obtain publication-ready + figures of the model output uncertainty and sensitivity-related analysis. An overview + of the package can be found in Puy et al. (2022) . + date_publication: '2024-02-21' + bug_reports: https://github.com/arnaldpuy/sensobol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sensobol + url_git: https://github.com/arnaldpuy/sensobol +SensoMineR: + version: '1.27' + title: Sensory Data Analysis + maintainer: Francois Husson + description: 'Statistical Methods to Analyse Sensory Data. SensoMineR: A package + for sensory data analysis. S. Le and F. Husson (2008).' + date_publication: '2023-11-28' + bug_reports: '' + url: http://sensominer.free.fr + url_cran: https://CRAN.R-project.org/package=SensoMineR + url_git: '' +sensory: + version: '1.1' + title: |- + Simultaneous Model-Based Clustering and Imputation via a + Progressive Expectation-Maximization Algorithm + maintainer: Brian C. Franczak + description: Contains the function CUUimpute() which performs model-based clustering + and imputation simultaneously. + date_publication: '2016-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sensory + url_git: '' +SenSpe: + version: '1.3' + title: Estimating Specificity at Controlled Sensitivity, or Vice Versa + maintainer: Yijian Huang + description: Perform biomarker evaluation and comparison in terms of specificity + at a controlled sensitivity level, or sensitivity at a controlled specificity + level. Point estimation and exact bootstrap of Huang, Parakati, Patil, and Sanda + (2023) for the one- and two-biomarker problems are + implemented. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SenSpe + url_git: '' +sensR: + version: 1.5-3 + title: Thurstonian Models for Sensory Discrimination + maintainer: Dominik Rafacz + description: |- + Provides methods for sensory discrimination methods; + duotrio, tetrad, triangle, 2-AFC, 3-AFC, A-not A, same-different, + 2-AC and degree-of-difference. + This enables the calculation of d-primes, standard errors of + d-primes, sample size and power computations, and + comparisons of different d-primes. Methods for profile likelihood + confidence intervals and plotting are included. Most methods are + described in Brockhoff, P.B. and Christensen, R.H.B. (2010) + . + date_publication: '2023-10-31' + bug_reports: https://github.com/aigorahub/sensR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sensR + url_git: https://github.com/aigorahub/sensR +SenSrivastava: + version: 2015.6.25.1 + title: Datasets from Sen & Srivastava + maintainer: Kjetil B Halvorsen + description: |- + Collection of datasets from Sen & Srivastava: "Regression + Analysis, Theory, Methods and Applications", Springer. Sources + for individual data files are more fully documented in the + book. + date_publication: '2023-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SenSrivastava + url_git: '' +senstrat: + version: 1.0.3 + title: Sensitivity Analysis for Stratified Observational Studies + maintainer: Paul R. Rosenbaum + description: Sensitivity analysis in unmatched observational studies, with or without + strata. The main functions are sen2sample() and senstrat(). See Rosenbaum, P. + R. and Krieger, A. M. (1990), JASA, 85, 493-498, + and Gastwirth, Krieger and Rosenbaum (2000), JRSS-B, 62, 545–555 + . + date_publication: '2017-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=senstrat + url_git: '' +SensusR: + version: 2.3.1 + title: Sensus Analytics + maintainer: Matthew S. Gerber + description: Provides access and analytic functions for Sensus data. + date_publication: '2019-02-01' + bug_reports: '' + url: https://predictive-technology-laboratory.github.io/sensus/ + url_cran: https://CRAN.R-project.org/package=SensusR + url_git: '' +sentencepiece: + version: 0.2.3 + title: Text Tokenization using Byte Pair Encoding and Unigram Modelling + maintainer: Jan Wijffels + description: |- + Unsupervised text tokenizer allowing to perform byte pair encoding and unigram modelling. + Wraps the 'sentencepiece' library which provides a language independent tokenizer to split text in words and smaller subword units. + The techniques are explained in the paper "SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing" by Taku Kudo and John Richardson (2018) . + Provides as well straightforward access to pretrained byte pair encoding models and subword embeddings trained on Wikipedia using 'word2vec', + as described in "BPEmb: Tokenization-free Pre-trained Subword Embeddings in 275 Languages" by Benjamin Heinzerling and Michael Strube (2018) . + date_publication: '2022-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sentencepiece + url_git: https://github.com/bnosac/sentencepiece +sentiment.ai: + version: 0.1.1 + title: Simple Sentiment Analysis Using Deep Learning + maintainer: Ben Wiseman + description: |- + Sentiment Analysis via deep learning and gradient boosting models with a lot of the underlying hassle taken care of to make the process as simple as possible. + In addition to out-performing traditional, lexicon-based sentiment analysis (see ), + it also allows the user to create embedding vectors for text which can be used in other analyses. + GPU acceleration is supported on Windows and Linux. + date_publication: '2022-03-19' + bug_reports: '' + url: https://benwiseman.github.io/sentiment.ai/ + url_cran: https://CRAN.R-project.org/package=sentiment.ai + url_git: https://github.com/BenWiseman/sentiment.ai +SentimentAnalysis: + version: 1.3-5 + title: Dictionary-Based Sentiment Analysis + maintainer: Nicolas Proellochs + description: |- + Performs a sentiment analysis of textual contents in R. This implementation + utilizes various existing dictionaries, such as Harvard IV, or finance-specific + dictionaries. Furthermore, it can also create customized dictionaries. The latter + uses LASSO regularization as a statistical approach to select relevant terms based on + an exogenous response variable. + date_publication: '2023-08-23' + bug_reports: https://github.com/sfeuerriegel/SentimentAnalysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SentimentAnalysis + url_git: https://github.com/sfeuerriegel/SentimentAnalysis +sentimentr: + version: 2.9.0 + title: Calculate Text Polarity Sentiment + maintainer: Tyler Rinker + description: |- + Calculate text polarity sentiment at the sentence level and + optionally aggregate by rows or grouping variable(s). + date_publication: '2021-10-12' + bug_reports: https://github.com/trinker/sentimentr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sentimentr + url_git: https://github.com/trinker/sentimentr +SenTinMixt: + version: 1.0.0 + title: Parsimonious Mixtures of MSEN and MTIN Distributions + maintainer: Salvatore D. Tomarchio + description: |- + Implements parsimonious mixtures of MSEN and MTIN distributions via expectation- + maximization based algorithms for model-based clustering. For each mixture + component, parsimony is reached via the eigen-decomposition of the scale + matrices and by imposing a constraint on the tailedness parameter. This produces + a family of 28 parsimonious mixture models for each distribution. + date_publication: '2021-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SenTinMixt + url_git: '' +sentometrics: + version: 1.0.0 + title: |- + An Integrated Framework for Textual Sentiment Time Series + Aggregation and Prediction + maintainer: Samuel Borms + description: Optimized prediction based on textual sentiment, accounting for the + intrinsic challenge that sentiment can be computed and pooled across texts and + time in various ways. See Ardia et al. (2021) . + date_publication: '2021-08-18' + bug_reports: https://github.com/SentometricsResearch/sentometrics/issues + url: https://sentometrics-research.com/sentometrics/ + url_cran: https://CRAN.R-project.org/package=sentometrics + url_git: '' +sentopics: + version: 0.7.4 + title: Tools for Joint Sentiment and Topic Analysis of Textual Data + maintainer: Olivier Delmarcelle + description: |- + A framework that joins topic modeling and sentiment analysis of + textual data. The package implements a fast Gibbs sampling estimation of + Latent Dirichlet Allocation (Griffiths and Steyvers (2004) + ) and Joint Sentiment/Topic Model (Lin, He, + Everson and Ruger (2012) ). It offers a variety of + helpers and visualizations to analyze the result of topic modeling. The + framework also allows enriching topic models with dates and externally + computed sentiment measures. A flexible aggregation scheme enables the + creation of time series of sentiment or topical proportions from the enriched + topic models. Moreover, a novel method jointly aggregates topic proportions + and sentiment measures to derive time series of topical sentiment. + date_publication: '2024-09-20' + bug_reports: https://github.com/odelmarcelle/sentopics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sentopics + url_git: https://github.com/odelmarcelle/sentopics +sentryR: + version: 1.1.2 + title: Send Errors and Messages to Sentry + maintainer: Joao Santiago + description: |- + Unofficial client for 'Sentry' , + a self-hosted or cloud-based error-monitoring service. It will inform about + errors in real-time, and includes integration with the 'Plumber' package. + date_publication: '2023-12-18' + bug_reports: https://github.com/jcpsantiago/sentryR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sentryR + url_git: https://github.com/jcpsantiago/sentryR +SEofM: + version: 0.1.0 + title: Standard Error of Measurement + maintainer: Zhicheng Du + description: |- + To calculate the standard error of measurement (SEM) to assess the observer variability (inter- and intra-observer variation). + The methods used in this package are referenced from Zoran B. Popović (2017) . + date_publication: '2021-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEofM + url_git: '' +SEPaLS: + version: 0.1.0 + title: Shrinkage for Extreme Partial Least-Squares (SEPaLS) + maintainer: Hadrien Lorenzo + description: |- + Regression context for the Partial Least Squares framework for + Extreme values. Estimations of the Shrinkage for Extreme Partial Least-Squares + (SEPaLS) estimators, an adaptation of the original Partial Least Squares + (PLS) method tailored to the extreme-value framework. + The SEPaLS project is a joint work by Stephane Girard, Hadrien Lorenzo and + Julyan Arbel. + R code to replicate the results of the paper is available at + . + Extremes within PLS was already studied by one of the authors, see M + Bousebeta, G Enjolras, S Girard (2023) . + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SEPaLS + url_git: '' +sEparaTe: + version: 0.3.2 + title: |- + Maximum Likelihood Estimation and Likelihood Ratio Test + Functions for Separable Variance-Covariance Structures + maintainer: Timothy Schwinghamer + description: |- + Maximum likelihood estimation of the parameters + of matrix and 3rd-order tensor normal distributions with unstructured + factor variance covariance matrices, two procedures, and for unbiased + modified likelihood ratio testing of simple and double separability + for variance-covariance structures, two procedures. References: + Dutilleul P. (1999) , + Manceur AM, Dutilleul P. (2013) + , and Manceur AM, Dutilleul + P. (2013) . + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sEparaTe + url_git: '' +separationplot: + version: '1.4' + title: Separation Plots + maintainer: Brian Greenhill + description: 'Visual representations of model fit or predictive success in the form + of "separation plots." See Greenhill, Brian, Michael D. Ward, and Audrey Sacks. + "The separation plot: A new visual method for evaluating the fit of binary models." + American Journal of Political Science 55.4 (2011): 991-1002.' + date_publication: '2023-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=separationplot + url_git: '' +sephora: + version: 0.1.31 + title: Statistical Estimation of Phenological Parameters + maintainer: Inder Tecuapetla-Gómez + description: |- + Provides functions and methods for estimating phenological dates (green up, + start of a season, maturity, senescence, end of a season and dormancy) from (nearly) + periodic Earth Observation time series. These dates are critical points of some + derivatives of an idealized curve which, in turn, is obtained through a functional principal + component analysis-based regression model. Some of the methods implemented here are + based on T. Krivobokova, P. Serra and F. Rosales (2022) . + Methods for handling and plotting Earth observation time series are also provided. + date_publication: '2024-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sephora + url_git: '' +sepkoski: + version: 0.0.1 + title: Sepkoski's Fossil Marine Animal Genera Compendium + maintainer: Lewis A. Jones + description: |- + Stratigraphic ranges of fossil marine animal genera from Sepkoski's + (2002) published compendium. No changes have been made to any taxonomic + names. However, first and last appearance intervals have been updated to be + consistent with stages of the International Geological Timescale. + Functionality for generating a plot of Sepkoski's evolutionary fauna is also + included. For specific details on the compendium see: + Sepkoski, J. J. (2002). A compendium of fossil marine animal genera. + Bulletins of American Paleontology, 363, pp. 1–560 (ISBN 0-87710-450-6). + Access: . + date_publication: '2022-11-23' + bug_reports: https://github.com/LewisAJones/sepkoski/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sepkoski + url_git: https://github.com/LewisAJones/sepkoski +seq2R: + version: 2.0.1 + title: |- + Simple Method to Detect Compositional Changes in Genomic + Sequences + maintainer: Nora M. Villanueva + description: This software is useful for loading '.fasta' or '.gbk' files, and for + retrieving sequences from 'GenBank' dataset . + This package allows to detect differences or asymmetries based on nucleotide + composition by using local linear kernel smoothers. Also, it is possible to draw + inference about critical points (i. e. maximum or minimum points) related with + the derivative curves. Additionally, bootstrap methods have been used for estimating + confidence intervals and speed computational techniques (binning techniques) have + been implemented in 'seq2R'. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seq2R + url_git: '' +SeqAlignR: + version: 0.1.1 + title: Sequence Alignment and Visualization Tool + maintainer: Leonard Persson Norblad + description: |- + Computes the optimal alignment of two character sequences. + Visualizes the result of the alignment in a matrix plot. + Needleman, Saul B.; Wunsch, Christian D. (1970) "A general method applicable to the search for similarities in the amino acid sequence of two proteins" . + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqAlignR + url_git: '' +SeqAlloc: + version: '1.0' + title: Sequential Allocation for Prospective Experiments + maintainer: Xiaoshu Zhu + description: |- + Potential randomization schemes are prospectively evaluated when + units are assigned to treatment arms upon entry into the experiment. The schemes + are evaluated for balance on covariates and on predictability (i.e., how well + could a site worker guess the treatment of the next unit enrolled). + date_publication: '2016-08-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqAlloc + url_git: '' +seqDesign: + version: '1.2' + title: |- + Simulation and Group Sequential Monitoring of Randomized + Two-Stage Treatment Efficacy Trials with Time-to-Event + Endpoints + maintainer: Michal Juraska + description: A modification of the preventive vaccine efficacy trial design of Gilbert, + Grove et al. (2011, Statistical Communications in Infectious Diseases) is implemented, + with application generally to individual-randomized clinical trials with multiple + active treatment groups and a shared control group, and a study endpoint that + is a time-to-event endpoint subject to right-censoring. The design accounts for + the issues that the efficacy of the treatment/vaccine groups may take time to + accrue while the multiple treatment administrations/vaccinations are given; there + is interest in assessing the durability of treatment efficacy over time; and group + sequential monitoring of each treatment group for potential harm, non-efficacy/efficacy + futility, and high efficacy is warranted. The design divides the trial into two + stages of time periods, where each treatment is first evaluated for efficacy in + the first stage of follow-up, and, if and only if it shows significant treatment + efficacy in stage one, it is evaluated for longer-term durability of efficacy + in stage two. The package produces plots and tables describing operating characteristics + of a specified design including an unconditional power for intention-to-treat + and per-protocol/as-treated analyses; trial duration; probabilities of the different + possible trial monitoring outcomes (e.g., stopping early for non-efficacy); unconditional + power for comparing treatment efficacies; and distributions of numbers of endpoint + events occurring after the treatments/vaccinations are given, useful as input + parameters for the design of studies of the association of biomarkers with a clinical + outcome (surrogate endpoint problem). The code can be used for a single active + treatment versus control design and for a single-stage design. + date_publication: '2019-05-22' + bug_reports: https://github.com/mjuraska/seqDesign/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqDesign + url_git: https://github.com/mjuraska/seqDesign +SeqDetect: + version: 1.0.7 + title: Sequence and Latent Process Detector + maintainer: Dalibor Krleža + description: |- + Sequence detector in this package contains a specific automaton model that can be used to learn and detect data and process sequences. + Automaton model in this package is capable of learning and tracing sequences. Automaton model can be found in Krleža, Vrdoljak, Brčić (2019) . + This research has been partly supported under Competitiveness and Cohesion Operational Programme from the European Regional and Development Fund, as part of the Integrated Anti-Fraud System project no. KK.01.2.1.01.0041. This research has also been partly supported by the European Regional Development Fund under the grant KK.01.1.1.01.0009. + date_publication: '2020-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqDetect + url_git: '' +SeqExpMatch: + version: 0.1.0 + title: Sequential Experimental Design via Matching on-the-Fly + maintainer: Adam Kapelner + description: |- + Generates the following sequential two-arm experimental designs: + (1) completely randomized (Bernoulli) + (2) balanced completely randomized + (3) Efron's (1971) Biased Coin + (4) Atkinson's (1982) Covariate-Adjusted Biased Coin + (5) Kapelner and Krieger's (2014) Covariate-Adjusted Matching on the Fly + (6) Kapelner and Krieger's (2021) CARA Matching on the Fly with Differential Covariate Weights (Naive) + (7) Kapelner and Krieger's (2021) CARA Matching on the Fly with Differential Covariate Weights (Stepwise) + and also provides the following types of inference: + (1) estimation (with both Z-style estimators and OLS estimators), + (2) frequentist testing (via asymptotic distribution results and via employing the nonparametric randomization test) and + (3) frequentist confidence intervals (only under the superpopulation sampling assumption currently). Details can be found + in our publication: Kapelner and Krieger "A Matching Procedure for Sequential Experiments that Iteratively Learns which + Covariates Improve Power" (2020) . + date_publication: '2021-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqExpMatch + url_git: https://github.com/kapelner/matching_on_the_fly_designs_R_package_and_paper_repr +SeqFeatR: + version: 0.3.1 + title: A Tool to Associate FASTA Sequences and Features + maintainer: Bettina Budeus + description: Provides user friendly methods for the identification of sequence patterns + that are statistically significantly associated with a property of the sequence. + For instance, SeqFeatR allows to identify viral immune escape mutations for hosts + of given HLA types. The underlying statistical method is Fisher's exact test, + with appropriate corrections for multiple testing, or Bayes. Patterns may be point + mutations or n-tuple of mutations. SeqFeatR offers several ways to visualize the + results of the statistical analyses, see Budeus (2016) . + date_publication: '2019-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqFeatR + url_git: '' +seqgendiff: + version: 1.2.4 + title: RNA-Seq Generation/Modification for Simulation + maintainer: David Gerard + description: |- + Generates/modifies RNA-seq data for use in simulations. We provide + a suite of functions that will add a known amount of signal to a real + RNA-seq dataset. The advantage of using this approach over simulating under + a theoretical distribution is that common/annoying aspects of the data + are more preserved, giving a more realistic evaluation of your method. + The main functions are select_counts(), thin_diff(), thin_lib(), + thin_gene(), thin_2group(), thin_all(), and effective_cor(). See + Gerard (2020) for details on the + implemented methods. + date_publication: '2024-05-15' + bug_reports: https://github.com/dcgerard/seqgendiff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqgendiff + url_git: https://github.com/dcgerard/seqgendiff +seqhandbook: + version: 0.1.1 + title: Miscellaneous Tools for Sequence Analysis + maintainer: Nicolas Robette + description: It provides miscellaneous sequence analysis functions for describing + episodes in individual sequences, measuring association between domains in multidimensional + sequence analysis (see Piccarreta (2017) ), heat + maps of sequence data, Globally Interdependent Multidimensional Sequence Analysis + (see Robette et al (2015) ), smoothing sequences + for index plots (see Piccarreta (2012) ), coding + sequences for Qualitative Harmonic Analysis (see Deville (1982)), measuring stress + from multidimensional scaling factors (see Piccarreta and Lior (2010) ), + symmetrical (or canonical) Partial Least Squares (see Bry (1996)). + date_publication: '2023-04-02' + bug_reports: '' + url: https://nicolas-robette.github.io/seqhandbook/ + url_cran: https://CRAN.R-project.org/package=seqhandbook + url_git: '' +seqHMM: + version: 1.2.6 + title: |- + Mixture Hidden Markov Models for Social Sequence Data and Other + Multivariate, Multichannel Categorical Time Series + maintainer: Jouni Helske + description: |- + Designed for fitting hidden (latent) Markov models and mixture + hidden Markov models for social sequence data and other categorical time series. + Also some more restricted versions of these type of models are available: Markov + models, mixture Markov models, and latent class models. The package supports + models for one or multiple subjects with one or multiple parallel sequences + (channels). External covariates can be added to explain cluster membership in + mixture models. The package provides functions for evaluating and comparing + models, as well as functions for visualizing of multichannel sequence data and + hidden Markov models. Models are estimated using maximum likelihood via the EM + algorithm and/or direct numerical maximization with analytical gradients. All + main algorithms are written in C++ with support for parallel computation. + Documentation is available via several vignettes in this page, and the + paper by Helske and Helske (2019, ). + date_publication: '2023-07-06' + bug_reports: https://github.com/helske/seqHMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqHMM + url_git: '' +seqICP: + version: '1.1' + title: Sequential Invariant Causal Prediction + maintainer: Niklas Pfister + description: Contains an implementation of invariant causal prediction for sequential + data. The main function in the package is 'seqICP', which performs linear sequential + invariant causal prediction and has guaranteed type I error control. For non-linear + dependencies the package also contains a non-linear method 'seqICPnl', which allows + to input any regression procedure and performs tests based on a permutation approach + that is only approximately correct. In order to test whether an individual set + S is invariant the package contains the subroutines 'seqICP.s' and 'seqICPnl.s' + corresponding to the respective main methods. + date_publication: '2017-07-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seqICP + url_git: '' +seqimpute: + version: 2.2.0 + title: Imputation of Missing Data in Sequence Analysis + maintainer: Kevin Emery + description: |- + Multiple imputation of missing data in a dataset using MICT or + MICT-timing methods. The core idea of the algorithms is to fill gaps of + missing data, which is the typical form of missing data in a longitudinal + setting, recursively from their edges. Prediction is based on either a + multinomial or random forest regression model. Covariates and + time-dependent covariates can be included in the model. + date_publication: '2025-01-15' + bug_reports: https://github.com/emerykevin/seqimpute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqimpute + url_git: https://github.com/emerykevin/seqimpute +seqinr: + version: 4.2-36 + title: Biological Sequences Retrieval and Analysis + maintainer: Simon Penel + description: |- + Exploratory data analysis and data visualization + for biological sequence (DNA and protein) data. Seqinr includes + utilities for sequence data management under the ACNUC system + described in Gouy, M. et al. (1984) Nucleic Acids Res. + 12:121-127 . + date_publication: '2023-12-08' + bug_reports: https://github.com/lbbe-software/seqinr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqinr + url_git: https://seqinr.r-forge.r-project.org/ +SeqKat: + version: 0.0.8 + title: Detection of Kataegis + maintainer: Paul C. Boutros + description: Kataegis is a localized hypermutation occurring when a region is enriched + in somatic SNVs. Kataegis can result from multiple cytosine deaminations catalyzed + by the AID/APOBEC family of proteins. This package contains functions to detect + kataegis from SNVs in BED format. This package reports two scores per kataegic + event, a hypermutation score and an APOBEC mediated kataegic score. Yousif, F. + et al.; The Origins and Consequences of Localized and Global Somatic Hypermutation; + Biorxiv 2018 . + date_publication: '2020-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqKat + url_git: '' +SeqMADE: + version: '1.0' + title: |- + Network Module-Based Model in the Differential Expression + Analysis for RNA-Seq + maintainer: Mingli Lei + description: A network module-based generalized linear model for differential expression + analysis with the count-based sequence data from RNA-Seq. + date_publication: '2016-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqMADE + url_git: '' +seqmagick: + version: 0.1.7 + title: Sequence Manipulation Utilities + maintainer: Guangchuang Yu + description: Supports reading and writing sequences for different formats (currently + interleaved and sequential formats for 'FASTA' and 'PHYLIP'), file conversion, + and manipulation (e.g. filter sequences that contain specify pattern, export consensus + sequence from an alignment). + date_publication: '2024-01-09' + bug_reports: https://github.com/YuLab-SMU/seqmagick/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqmagick + url_git: https://github.com/YuLab-SMU/seqmagick +seqminer: + version: '9.7' + title: |- + Efficiently Read Sequence Data (VCF Format, BCF Format, METAL + Format and BGEN Format) into R + maintainer: Xiaowei Zhan + description: Integrate sequencing data (Variant call format, e.g. VCF or BCF) or + meta-analysis results in R. This package can help you (1) read VCF/BCF/BGEN files + by chromosomal ranges (e.g. 1:100-200); (2) read RareMETAL summary statistics + files; (3) read tables from a tabix-indexed files; (4) annotate VCF/BCF files; + (5) create customized workflow based on Makefile. + date_publication: '2024-10-02' + bug_reports: https://github.com/zhanxw/seqminer/issues + url: http://zhanxw.github.io/seqminer/ + url_cran: https://CRAN.R-project.org/package=seqminer + url_git: '' +seqmon: + version: '2.5' + title: Group Sequential Design Class for Clinical Trials + maintainer: Hui Zheng + description: S4 class object for creating and managing group sequential designs. + It calculates the efficacy and futility boundaries at each look. It allows modifying + the design and tracking the design update history. + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seqmon + url_git: '' +SeqNet: + version: 1.1.3 + title: Generate RNA-Seq Data from Gene-Gene Association Networks + maintainer: Tyler Grimes + description: Methods to generate random gene-gene association networks and simulate + RNA-seq data from them, as described in Grimes and Datta (2021) . + Includes functions to generate random networks of any size and perturb them to + obtain differential networks. Network objects are built from individual, overlapping + modules that represent pathways. The resulting network has various topological + properties that are characteristic of gene regulatory networks. RNA-seq data can + be generated such that the association among gene expression profiles reflect + the underlying network. A reference RNA-seq dataset can be provided to model realistic + marginal distributions. Plotting functions are available to visualize a network, + compare two networks, and compare the expression of two genes across multiple + networks. + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SeqNet + url_git: '' +seqSHP: + version: 0.1.1 + title: Building Sequences from SHP Waves + maintainer: Gilbert Ritschard + description: |- + Based on the structure of the SPSS version of the Swiss + Household Panel (SHP) data, provides a function seqFromWaves() + that seeks the data of variables specified by the user in each + of the wave files and collects them as sequences. The function also + matches the sequences with variables from other files such as the + master files of persons (MP) and households (MH), and social origins (SO). + It can also match with activity calendar data (CA). + date_publication: '2024-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seqSHP + url_git: '' +seqtest: + version: 0.1-0 + title: Sequential Triangular Test + maintainer: Takuya Yanagida + description: |- + Sequential triangular test for the arithmetic mean in one- and two- + samples, proportions in one- and two-samples, and the Pearson's correlation + coefficient. + date_publication: '2016-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=seqtest + url_git: '' +seqtrie: + version: 0.2.8 + title: Radix Tree and Trie-Based String Distances + maintainer: Travers Ching + description: 'A collection of Radix Tree and Trie algorithms for finding similar + sequences and calculating sequence distances (Levenshtein and other distance metrics). + This work was inspired by a trie implementation in Python: "Fast and Easy Levenshtein + distance using a Trie." Hanov (2011) .' + date_publication: '2024-05-04' + bug_reports: https://github.com/traversc/seqtrie/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seqtrie + url_git: https://github.com/traversc/seqtrie +sequenceR: + version: 1.0.1 + title: A Simple Sequencer for Data Sonification + maintainer: Benjamin Renard + description: |- + A rudimentary sequencer to define, manipulate and mix sound samples. + The underlying motivation is to sonify data, as demonstrated in the blog , the presentation by Renard and Le Bescond (2022, ) or the poster by Renard et al. (2023, ). + date_publication: '2025-01-13' + bug_reports: https://github.com/benRenard/sequenceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sequenceR + url_git: https://github.com/benRenard/sequenceR +SequenceSpikeSlab: + version: 1.0.1 + title: |- + Exact Bayesian Model Selection Methods for the Sparse Normal + Sequence Model + maintainer: Tim van Erven + description: |- + Contains fast functions to calculate the exact Bayes posterior + for the Sparse Normal Sequence Model, implementing the algorithms + described in Van Erven and Szabo (2021, + ). For general hierarchical + priors, sample sizes up to 10,000 are feasible within half an hour + on a standard laptop. For beta-binomial spike-and-slab priors, a + faster algorithm is provided, which can handle sample sizes of + 100,000 in half an hour. In the implementation, special care has + been taken to assure numerical stability of the methods even for + such large sample sizes. + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SequenceSpikeSlab + url_git: '' +Sequential: + version: 4.3.4 + title: Exact Sequential Analysis for Poisson and Binomial Data + maintainer: Ivair Ramos Silva + description: "Functions to calculate exact critical values, statistical power, expected + time to signal, and required sample sizes for performing exact sequential analysis. + All these\tcalculations can be done for either Poisson or binomial data, for continuous + or group sequential analyses, and for different types of rejection boundaries. + In case of group sequential analyses, the group sizes do not have to be specified + in advance and the alpha spending can be arbitrarily settled." + date_publication: '2024-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sequential + url_git: '' +SequentialDesign: + version: '1.0' + title: |- + Observational Database Study Planning using Exact Sequential + Analysis for Poisson and Binomial Data + maintainer: Judith Maro + description: Functions to be used in conjunction with the 'Sequential' package that + allows for planning of observational database studies that will be analyzed with + exact sequential analysis. This package supports Poisson- and binomial-based data. + The primary function, seq_wrapper(...), accepts parameters for simulation of a + simple exposure pattern and for the 'Sequential' package setup and analysis functions. + The exposure matrix is used to simulate the true and false positive and negative + populations (Green (1983) , Brenner (1993) + ). Functions are then run from the 'Sequential' + package on these populations, which allows for the exploration of outcome misclassification + in data. + date_publication: '2017-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SequentialDesign + url_git: '' +sequoia: + version: 2.11.2 + title: Pedigree Inference from SNPs + maintainer: Jisca Huisman + description: |- + Multi-generational pedigree inference from incomplete data on + hundreds of SNPs, including parentage assignment and sibship clustering. + See Huisman (2017) () for more information. + date_publication: '2024-05-28' + bug_reports: '' + url: https://jiscah.github.io/ + url_cran: https://CRAN.R-project.org/package=sequoia + url_git: '' +sergeant: + version: 0.9.1 + title: Tools to Transform and Query Data with Apache Drill + maintainer: Bob Rudis + description: |- + Apache Drill is a low-latency distributed query engine designed to enable + data exploration and analysis on both relational and non-relational data stores, + scaling to petabytes of data. Methods are provided that enable working with Apache + Drill instances via the REST API, DBI methods + and using 'dplyr'/'dbplyr' idioms. Helper functions are included to facilitate + using official Drill Docker images/containers. + date_publication: '2021-11-29' + bug_reports: https://gitlab.com/hrbrmstr/sergeant/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sergeant + url_git: https://gitlab.com/hrbrmstr/sergeant +serial: + version: '3.0' + title: The Serial Interface Package + maintainer: Martin Seilmayer + description: |- + Enables reading and writing binary and ASCII data to + RS232/RS422/RS485 or any other virtual serial interface of the + computer. + date_publication: '2020-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=serial + url_git: '' +seriation: + version: 1.5.7 + title: Infrastructure for Ordering Objects Using Seriation + maintainer: Michael Hahsler + description: |- + Infrastructure for ordering objects with an implementation of several + seriation/sequencing/ordination techniques to reorder matrices, dissimilarity + matrices, and dendrograms. Also provides (optimally) reordered heatmaps, + color images and clustering visualizations like dissimilarity plots, and + visual assessment of cluster tendency plots (VAT and iVAT). Hahsler et al (2008) . + date_publication: '2024-12-05' + bug_reports: https://github.com/mhahsler/seriation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=seriation + url_git: https://github.com/mhahsler/seriation +serieslcb: + version: 0.4.0 + title: Lower Confidence Bounds for Binomial Series System + maintainer: Edward Schuberg + description: Calculate and compare lower confidence bounds for binomial series system + reliability. The R 'shiny' application, launched by the function launch_app(), + weaves together a workflow of customized simulations and delta coverage calculations + to output recommended lower confidence bound methods. + date_publication: '2019-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=serieslcb + url_git: '' +serocalculator: + version: 1.3.0 + title: Estimating Infection Rates from Serological Data + maintainer: Kristina Lai + description: |- + Translates antibody levels measured in cross-sectional + population samples into estimates of the frequency with which + seroconversions (infections) occur in the sampled populations. + Replaces the previous `seroincidence` package. + date_publication: '2025-01-25' + bug_reports: https://github.com/UCD-SERG/serocalculator/issues + url: https://ucd-serg.github.io/serocalculator/ + url_cran: https://CRAN.R-project.org/package=serocalculator + url_git: https://github.com/UCD-SERG/serocalculator +serosv: + version: 1.0.1 + title: Model Infectious Disease Parameters from Serosurveys + maintainer: Anh Phan Truong Quynh + description: |- + An easy-to-use and efficient tool to estimate infectious diseases parameters using serological data. Implemented models include SIR models (basic_sir_model(), static_sir_model(), mseir_model(), sir_subpops_model()), parametric models (polynomial_model(), fp_model()), nonparametric models (lp_model()), semiparametric models (penalized_splines_model()), hierarchical models (hierarchical_bayesian_model()). + The package is based on the book "Modeling Infectious Disease Parameters Based on Serological and Social Contact Data: A Modern Statistical Perspective" (Hens, Niel & Shkedy, Ziv & Aerts, Marc & Faes, Christel & Damme, Pierre & Beutels, Philippe., 2013) . + date_publication: '2024-10-18' + bug_reports: https://github.com/OUCRU-Modelling/serosv/issues + url: https://oucru-modelling.github.io/serosv/ + url_cran: https://CRAN.R-project.org/package=serosv + url_git: https://github.com/OUCRU-Modelling/serosv +serp: + version: 0.2.5 + title: Smooth Effects on Response Penalty for CLM + maintainer: Ejike R. Ugba + description: |- + Implements a regularization method for cumulative link models using the + Smooth-Effect-on-Response Penalty (SERP). This method allows flexible + modeling of ordinal data by enabling a smooth transition from a general + cumulative link model to a simplified version of the same model. As the + tuning parameter increases from zero to infinity, the subject-specific + effects for each variable converge to a single global effect. + The approach addresses common issues in cumulative link models, such as + parameter unidentifiability and numerical instability, by maximizing a + penalized log-likelihood instead of the standard non-penalized version. + Fitting is performed using a modified Newton's method. Additionally, the + package includes various model performance metrics and descriptive tools. + For details on the implemented penalty method, see + Ugba (2021) and + Ugba et al. (2021) . + date_publication: '2024-11-25' + bug_reports: https://github.com/ejikeugba/serp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=serp + url_git: https://github.com/ejikeugba/serp +serpstatr: + version: 0.3.0 + title: '''Serpstat'' API Wrapper' + maintainer: Alex Danilin + description: |- + The primary goal of 'Serpstat' API + is to reduce manual SEO (search engine optimization) and PPC (pay-per-click) + tasks. You can automate your keywords research or competitors analysis + with this API wrapper. + date_publication: '2024-08-16' + bug_reports: '' + url: https://serpstat.com/api/ + url_cran: https://CRAN.R-project.org/package=serpstatr + url_git: '' +serrsBayes: + version: 0.5-0 + title: Bayesian Modelling of Raman Spectroscopy + maintainer: Matt Moores + description: |- + Sequential Monte Carlo (SMC) algorithms for fitting a generalised additive + mixed model (GAMM) to surface-enhanced resonance Raman spectroscopy (SERRS), + using the method of Moores et al. (2016) . Multivariate + observations of SERRS are highly collinear and lend themselves to a reduced-rank + representation. The GAMM separates the SERRS signal into three components: a + sequence of Lorentzian, Gaussian, or pseudo-Voigt peaks; a smoothly-varying baseline; + and additive white noise. The parameters of each component of the model are estimated + iteratively using SMC. The posterior distributions of the parameters given the observed + spectra are represented as a population of weighted particles. + date_publication: '2021-06-28' + bug_reports: https://github.com/mooresm/serrsBayes/issues + url: https://mooresm.github.io/serrsBayes/ + url_cran: https://CRAN.R-project.org/package=serrsBayes + url_git: https://github.com/mooresm/serrsBayes +servosphereR: + version: 0.1.1 + title: Analyze Data Generated from Syntech Servosphere Trials + maintainer: Jacob T. Wittman + description: |- + Functions that facilitate and speed up the analysis of data + produced by a Syntech servosphere , + which is equipment for studying the movement behavior of arthropods. + This package is designed to make working with data produced from a + servosphere easy for someone new to or unfamiliar with R. The functions + provided in this package fall into three broad-use categories: functions for + cleaning raw data produced by the servosphere software, functions for + deriving movement variables based on position data, and functions for + summarizing movement variables for easier analysis. These functions are + built with functions from the tidyverse package to work efficiently, as a + single servosphere file may consist of hundreds of thousands of rows of data + and a user may wish to analyze hundreds of files at a time. Many of the + movement variables derivable through this package are described in the + following papers: + Otálora-Luna, Fernando; Dickens, Joseph C. (2011) + Party, Virginie; Hanot, Christophe; Busser, Daniela Schmidt; Rochat, Didier; Renou, Michel (2013) + Bell, William J.; Kramer, Ernest (1980) + Becher, Paul G; Guerin, Patrick M. (2009) . + date_publication: '2019-05-14' + bug_reports: http://github.com/wittja01/servosphereR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=servosphereR + url_git: http://github.com/wittja01/servosphereR +servr: + version: '0.32' + title: A Simple HTTP Server to Serve Static Files or Dynamic Documents + maintainer: Yihui Xie + description: |- + Start an HTTP server in R to serve static files, or dynamic + documents that can be converted to HTML files (e.g., R Markdown) under a + given directory. + date_publication: '2024-10-04' + bug_reports: https://github.com/yihui/servr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=servr + url_git: https://github.com/yihui/servr +sesem: + version: 1.0.2 + title: Spatially Explicit Structural Equation Modeling + maintainer: Eric Lamb + description: Structural equation modeling is a powerful statistical approach for + the testing of networks of direct and indirect theoretical causal relationships + in complex data sets with inter-correlated dependent and independent variables. + Here we implement a simple method for spatially explicit structural equation modeling + based on the analysis of variance co-variance matrices calculated across a range + of lag distances. This method provides readily interpreted plots of the change + in path coefficients across scale. + date_publication: '2016-06-10' + bug_reports: '' + url: http://homepage.usask.ca/~egl388/index.html + url_cran: https://CRAN.R-project.org/package=sesem + url_git: '' +SEset: + version: 1.0.1 + title: Computing Statistically-Equivalent Path Models + maintainer: Oisín Ryan + description: |- + Tools to compute and analyze the set of statistically-equivalent (Gaussian, linear) path models which generate the input precision or (partial) correlation matrix. + This procedure is useful for understanding how statistical network models such as the Gaussian Graphical Model (GGM) perform as causal discovery tools. + The statistical-equivalence set of a given GGM expresses the uncertainty we have about the sign, size and direction of directed relationships based on the weights matrix of the GGM alone. + The derivation of the equivalence set and its use for understanding GGMs as causal discovery tools is described by Ryan, O., Bringmann, L.F., & Schuurman, N.K. (2022) . + date_publication: '2022-03-17' + bug_reports: https://github.com/ryanoisin/SEset + url: '' + url_cran: https://CRAN.R-project.org/package=SEset + url_git: '' +SESraster: + version: 0.7.1 + title: Raster Randomization for Null Hypothesis Testing + maintainer: Neander Marcel Heming + description: |- + Randomization of presence/absence species distribution raster + data with or without including spatial structure for calculating + standardized effect sizes and testing null hypothesis. The + randomization algorithms are based on classical algorithms for + matrices (Gotelli 2000, ) implemented for raster + data. + date_publication: '2024-10-22' + bug_reports: https://github.com/HemingNM/SESraster/issues + url: https://hemingnm.github.io/SESraster/ + url_cran: https://CRAN.R-project.org/package=SESraster + url_git: https://github.com/HemingNM/SESraster +sessioninfo: + version: 1.2.3 + title: R Session Information + maintainer: Gábor Csárdi + description: |- + Query and print information about the current R session. It + is similar to 'utils::sessionInfo()', but includes more information + about packages, and where they were installed from. + date_publication: '2025-02-05' + bug_reports: https://github.com/r-lib/sessioninfo/issues + url: https://sessioninfo.r-lib.org + url_cran: https://CRAN.R-project.org/package=sessioninfo + url_git: https://github.com/r-lib/sessioninfo#readme +set: + version: '1.2' + title: Set Operation + maintainer: Zhi Jin + description: |- + More easy to get intersection, union or complementary set and + combinations. + date_publication: '2021-02-26' + bug_reports: https://github.com/yikeshu0611/set/issues + url: '' + url_cran: https://CRAN.R-project.org/package=set + url_git: https://github.com/yikeshu0611/set +setariaviridis: + version: 0.1.0 + title: Field-Collected Data of Green Foxtail + maintainer: Keisuke Ando + description: |- + Setaria viridis (green foxtail) is a common weed. This + package contains measurements from individual branches of a wild + Setaria viridis plant collected near the author's home. The data is + intended for use in data analysis practice. + date_publication: '2025-01-21' + bug_reports: https://github.com/NONONOexe/setariaviridis/issues + url: https://nononoexe.github.io/setariaviridis/ + url_cran: https://CRAN.R-project.org/package=setariaviridis + url_git: https://github.com/NONONOexe/setariaviridis +setartree: + version: 0.2.1 + title: |- + SETAR-Tree - A Novel and Accurate Tree Algorithm for Global Time + Series Forecasting + maintainer: Rakshitha Godahewa + description: The implementation of a forecasting-specific tree-based model that + is in particular suitable for global time series forecasting, as proposed in Godahewa + et al. (2022) . The model uses the concept of Self Exciting + Threshold Autoregressive (SETAR) models to define the node splits and thus, the + model is named SETAR-Tree. The SETAR-Tree uses some time-series-specific splitting + and stopping procedures. It trains global pooled regression models in the leaves + allowing the models to learn cross-series information. The depth of the tree is + controlled by conducting a statistical linearity test as well as measuring the + error reduction percentage at each node split. Thus, the SETAR-Tree requires minimal + external hyperparameter tuning and provides competitive results under its default + configuration. A forest is developed by extending the SETAR-Tree. The SETAR-Forest + combines the forecasts provided by a collection of diverse SETAR-Trees during + the forecasting process. + date_publication: '2023-08-24' + bug_reports: https://github.com/rakshitha123/setartree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=setartree + url_git: https://github.com/rakshitha123/setartree +SetMethods: + version: '4.0' + title: |- + Functions for Set-Theoretic Multi-Method Research and Advanced + QCA + maintainer: Ioana-Elena Oana + description: "Functions for performing set-theoretic multi-method research, QCA + for clustered data, theory evaluation, Enhanced Standard Analysis, indirect calibration, + radar visualisations. Additionally it includes data to replicate the \texamples + in the books by Oana, I.E, C. Q. Schneider, and E. Thomann. Qualitative Comparative + Analysis (QCA) using R: A Beginner's Guide. Cambridge University Press and C. + Q. Schneider and C. Wagemann \"Set Theoretic Methods for the Social Sciences\", + Cambridge University Press." + date_publication: '2023-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SetMethods + url_git: '' +setRNG: + version: 2024.2-1 + title: Set (Normal) Random Number Generator and Seed + maintainer: Paul Gilbert + description: |- + Provides utilities to help set and record the setting of + the seed and the uniform and normal generators used when a random + experiment is run. The utilities can be used in other functions + that do random experiments to simplify recording and/or setting all the + necessary information for reproducibility. + See the vignette and reference manual for examples. + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=setRNG + url_git: http://distr.r-forge.r-project.org/ +sets: + version: 1.0-25 + title: Sets, Generalized Sets, Customizable Sets and Intervals + maintainer: David Meyer + description: |- + Data structures and basic operations for ordinary sets, + generalizations such as fuzzy sets, multisets, and + fuzzy multisets, customizable sets, and intervals. + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sets + url_git: '' +SetTest: + version: 0.3.0 + title: |- + Group Testing Procedures for Signal Detection and + Goodness-of-Fit + maintainer: Hong Zhang + description: |- + It provides cumulative distribution function (CDF), + quantile, p-value, statistical power calculator and random number generator + for a collection of group-testing procedures, including the Higher Criticism + tests, the one-sided Kolmogorov-Smirnov tests, the one-sided Berk-Jones tests, + the one-sided phi-divergence tests, etc. The input are a group of p-values. + The null hypothesis is that they are i.i.d. Uniform(0,1). In the context of + signal detection, the null hypothesis means no signals. In the context of the + goodness-of-fit testing, which contrasts a group of i.i.d. random variables to + a given continuous distribution, the input p-values can be obtained by the CDF + transformation. The null hypothesis means that these random variables follow the + given distribution. For reference, see [1]Hong Zhang, Jiashun Jin and Zheyang Wu. + "Distributions and power of optimal signal-detection statistics in finite case", + IEEE Transactions on Signal Processing (2020) 68, 1021-1033; [2] Hong Zhang and Zheyang Wu. + "The general goodness-of-fit tests for correlated data", Computational Statistics & + Data Analysis (2022) 167, 107379. + date_publication: '2024-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SetTest + url_git: '' +settings: + version: 0.2.7 + title: Software Option Settings Manager for R + maintainer: Mark van der Loo + description: |- + Provides option settings management that goes + beyond R's default 'options' function. With this package, users can define + their own option settings manager holding option names, default values and + (if so desired) ranges or sets of allowed option values that will be + automatically checked. Settings can then be retrieved, altered and reset + to defaults with ease. For R programmers and package developers it offers + cloning and merging functionality which allows for conveniently defining + global and local options, possibly in a multilevel options hierarchy. See + the package vignette for some examples concerning functions, S4 classes, + and reference classes. There are convenience functions to reset par() + and options() to their 'factory defaults'. + date_publication: '2021-05-07' + bug_reports: https://github.com/markvanderloo/settings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=settings + url_git: https://github.com/markvanderloo/settings +settingsSync: + version: 3.0.2 + title: '''Rstudio'' Addin to Sync Settings and Keymaps' + maintainer: André Plancha + description: |- + Provides a 'Rstudio' addin to download, merge and upload 'Rstudio' + settings and keymaps, essentially 'syncing them' at will. It uses 'Google Drive' + as a cloud storage to keep the settings and keymaps files. + date_publication: '2024-06-14' + bug_reports: https://github.com/notPlancha/settingsSync/issues + url: '' + url_cran: https://CRAN.R-project.org/package=settingsSync + url_git: https://github.com/notPlancha/settingsSync +Seurat: + version: 5.2.1 + title: Tools for Single Cell Genomics + maintainer: Rahul Satija + description: A toolkit for quality control, analysis, and exploration of single + cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret + sources of heterogeneity from single cell transcriptomic measurements, and to + integrate diverse types of single cell data. See Satija R, Farrell J, Gennert + D, et al (2015) , Macosko E, Basu A, Satija R, et al (2015) + , Stuart T, Butler A, et al (2019) , + and Hao, Hao, et al (2020) for more details. + date_publication: '2025-01-24' + bug_reports: https://github.com/satijalab/seurat/issues + url: https://satijalab.org/seurat + url_cran: https://CRAN.R-project.org/package=Seurat + url_git: https://github.com/satijalab/seurat +SeuratObject: + version: 5.0.2 + title: Data Structures for Single Cell Data + maintainer: Rahul Satija + description: |- + Defines S4 classes for single-cell genomic data and associated + information, such as dimensionality reduction embeddings, nearest-neighbor + graphs, and spatially-resolved coordinates. Provides data access methods and + R-native hooks to ensure the Seurat object is familiar to other R users. See + Satija R, Farrell J, Gennert D, et al (2015) , + Macosko E, Basu A, Satija R, et al (2015) , + and Stuart T, Butler A, et al (2019) , + Hao Y, Hao S, et al (2021) and + Hao Y, et al (2023) for + more details. + date_publication: '2024-05-08' + bug_reports: https://github.com/satijalab/seurat-object/issues + url: https://satijalab.github.io/seurat-object/ + url_cran: https://CRAN.R-project.org/package=SeuratObject + url_git: https://github.com/satijalab/seurat-object +sevenbridges2: + version: 0.3.0 + title: The 'Seven Bridges Platform' API Client + maintainer: Marko Trifunovic + description: |- + R client and utilities for 'Seven Bridges Platform' API, from 'Cancer Genomics Cloud' + to other 'Seven Bridges' supported platforms. API documentation is hosted publicly + at . + date_publication: '2025-02-24' + bug_reports: https://github.com/sbg/sevenbridges2/issues + url: https://www.sevenbridges.com + url_cran: https://CRAN.R-project.org/package=sevenbridges2 + url_git: https://github.com/sbg/sevenbridges2 +sever: + version: 0.0.7 + title: Customise 'Shiny' Disconnected Screens and Error Messages + maintainer: John Coene + description: Customise 'Shiny' disconnected screens as well as sanitize error messages + to make them clearer and friendlier to the user. + date_publication: '2021-07-14' + bug_reports: https://github.com/JohnCoene/sever/issues + url: https://sever.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=sever + url_git: '' +sewage: + version: 0.2.5 + title: A Light-Weight Data Pipelining Tool + maintainer: Matthew Whalen + description: |- + Provides a simple interface to developing complex data pipelines which can be executed in a single call. + 'sewage' makes it easy to test, debug, and share data pipelines through it's interface and visualizations. + date_publication: '2023-05-22' + bug_reports: https://github.com/mwhalen18/sewage/issues + url: https://mwhalen18.github.io/sewage/ + url_cran: https://CRAN.R-project.org/package=sewage + url_git: https://github.com/mwhalen18/sewage +sf: + version: 1.0-19 + title: Simple Features for R + maintainer: Edzer Pebesma + description: |- + Support for simple features, a standardized way to + encode spatial vector data. Binds to 'GDAL' for reading and writing + data, to 'GEOS' for geometrical operations, and to 'PROJ' for + projection conversions and datum transformations. Uses by default the 's2' + package for spherical geometry operations on ellipsoidal (long/lat) coordinates. + date_publication: '2024-11-05' + bug_reports: https://github.com/r-spatial/sf/issues + url: https://r-spatial.github.io/sf/ + url_cran: https://CRAN.R-project.org/package=sf + url_git: https://github.com/r-spatial/sf +sfadv: + version: 1.0.1 + title: Advanced Methods for Stochastic Frontier Analysis + maintainer: Yann Desjeux + description: |2- + + Stochastic frontier analysis with advanced methods. + In particular, it applies the approach proposed by Latruffe et al. (2017) + to estimate a stochastic frontier with technical + inefficiency effects when one input is endogenous. + date_publication: '2017-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sfadv + url_git: '' +sfaR: + version: 1.0.1 + title: Stochastic Frontier Analysis Routines + maintainer: K Hervé Dakpo + description: |- + Maximum likelihood estimation for stochastic frontier + analysis (SFA) of production (profit) and cost functions. The package + includes the basic stochastic frontier for cross-sectional or pooled + data with several distributions for the one-sided error term (i.e., + Rayleigh, gamma, Weibull, lognormal, uniform, generalized exponential + and truncated skewed Laplace), the latent class stochastic frontier + model (LCM) as described in Dakpo et al. (2021) + , for cross-sectional and pooled data, + and the sample selection model as described in Greene (2010) + , and applied in Dakpo et al. (2021) + . Several possibilities in terms of + optimization algorithms are proposed. + date_publication: '2024-10-29' + bug_reports: https://github.com/hdakpo/sfaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sfaR + url_git: https://github.com/hdakpo/sfaR +sfarrow: + version: 0.4.1 + title: Read/Write Simple Feature Objects ('sf') with 'Apache' 'Arrow' + maintainer: Chris Jochem + description: Support for reading/writing simple feature ('sf') spatial objects from/to + 'Parquet' files. 'Parquet' files are an open-source, column-oriented data storage + format from Apache (), now popular across programming + languages. This implementation converts simple feature list geometries into well-known + binary format for use by 'arrow', and coordinate reference system information + is maintained in a standard metadata format. + date_publication: '2021-10-27' + bug_reports: https://github.com/wcjochem/sfarrow/issues + url: https://wcjochem.github.io/sfarrow/ + url_cran: https://CRAN.R-project.org/package=sfarrow + url_git: https://github.com/wcjochem/sfarrow +sfc: + version: 0.1.0 + title: Substance Flow Computation + maintainer: Hu Sheng + description: |- + Provides a function sfc() to compute the substance flow + with the input files --- "data" and "model". If sample.size is + set more than 1, uncertainty analysis will be executed while + the distributions and parameters are supplied in the file "data". + date_publication: '2016-08-25' + bug_reports: https://github.com/ctfysh/sfc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sfc + url_git: https://github.com/ctfysh/sfc +sfcentral: + version: 0.1.0 + title: Spatial Centrality and Dispersion Statistics + maintainer: Gabriel V. Gaona + description: |- + Computing centrographic statistics (central points, standard + distance, standard deviation ellipse, standard deviation box) for + observations taken at point locations in 2D or 3D. The 'sfcentral' library + was inspired in 'aspace' package but conceived to be used in a spatial + 'tidyverse' context. + date_publication: '2024-03-12' + bug_reports: https://gitlab.com/gavg712/sfcentral/-/issues + url: https://gavg712.gitlab.io/sfcentral/ + url_cran: https://CRAN.R-project.org/package=sfcentral + url_git: https://gitlab.com/gavg712/sfcentral +sfcr: + version: 0.2.1 + title: Simulate Stock-Flow Consistent Models + maintainer: Joao Macalos + description: Routines to write, simulate, and validate stock-flow consistent (SFC) + models. The accounting structure of SFC models are described in Godley and Lavoie + (2007, ISBN:978-1-137-08599-3). The algorithms implemented to solve the models + (Gauss-Seidel and Broyden) are described in Kinsella and O'Shea (2010) + and Peressini and Sullivan (1988, ISBN:0-387-96614-5). + date_publication: '2021-10-11' + bug_reports: https://github.com/joaomacalos/sfcr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sfcr + url_git: https://github.com/joaomacalos/sfcr +sfcurve: + version: 1.0.0 + title: 2x2, 3x3 and Nxn Space-Filling Curves + maintainer: Zuguang Gu + description: |- + Implementation of all possible forms of 2x2 and 3x3 space-filling curves, + i.e., the generalized forms of the Hilbert curve , + the Peano curve and the Peano curve in the + meander type (Figure 5 in ). It can generates nxn curves expanded from + any specific level-1 units. It also implements the H-curve and the three-dimensional Hilbert curve. + date_publication: '2024-09-13' + bug_reports: '' + url: https://jokergoo.github.io/sfcurve/ + url_cran: https://CRAN.R-project.org/package=sfcurve + url_git: https://github.com/jokergoo/sfcurve +sfd: + version: 0.1.0 + title: Space-Filling Design Library + maintainer: Max Kuhn + description: |2- + + A collection of pre-optimized space-filling designs, for up to ten + parameters, is contained here. Functions are provided to access designs + described by Husslage et al (2011) and + Wang and Fang (2005) . The design types + included are Audze-Eglais, MaxiMin, and uniform. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sfd + url_git: '' +sfdct: + version: 0.3.0 + title: Constrained Triangulation for Simple Features + maintainer: Michael D. Sumner + description: |- + Build a constrained high quality Delaunay triangulation from simple + features objects, applying constraints based on input line segments, and + triangle properties including maximum area, minimum internal angle. The + triangulation code in 'RTriangle' uses the method of Cheng, Dey and Shewchuk + (2012, ISBN:9781584887300). For a low-dependency alternative with low-quality + path-based constrained triangulation see and for high-quality configurable + triangulation see . Also consider comparison + with the 'GEOS' lib which since version 3.10.0 includes a low quality + polygon triangulation method that starts with ear clipping and refines to Delaunay. + date_publication: '2024-01-09' + bug_reports: https://github.com/hypertidy/sfdct/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sfdct + url_git: https://github.com/hypertidy/sfdct +sfdep: + version: 0.2.5 + title: Spatial Dependence for Simple Features + maintainer: Dexter Locke + description: An interface to 'spdep' to integrate with 'sf' objects and the 'tidyverse'. + date_publication: '2024-09-13' + bug_reports: '' + url: https://sfdep.josiahparry.com + url_cran: https://CRAN.R-project.org/package=sfdep + url_git: https://github.com/josiahparry/sfdep +sffdr: + version: 1.0.0 + title: |- + Surrogate Functional False Discovery Rates for Genome-Wide + Association Studies + maintainer: Andrew Bass + description: Pleiotropy-informed significance analysis of genome-wide association + studies (GWAS) with surrogate functional false discovery rates (sfFDR). The sfFDR + framework adapts the fFDR to leverage informative data from multiple sets of GWAS + summary statistics to increase power in study while accommodating for linkage + disequilibrium. sfFDR provides estimates of key FDR quantities in a significance + analysis such as the functional local FDR and q-value, and uses these estimates + to derive a functional p-value for type I error rate control and a functional + local Bayes' factor for post-GWAS analyses (e.g., fine mapping and colocalization). + The sfFDR framework is described in Bass and Wallace (2024) . + date_publication: '2024-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sffdr + url_git: https://github.com/ajbass/sffdr +sFFLHD: + version: 0.1.2 + title: Sequential Full Factorial-Based Latin Hypercube Design + maintainer: Collin Erickson + description: |- + Gives design points from a sequential full factorial-based + Latin hypercube design, as described in Duan, Ankenman, Sanchez, + and Sanchez (2015, Technometrics, + ). + date_publication: '2018-05-17' + bug_reports: https://github.com/CollinErickson/sFFLHD/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sFFLHD + url_git: https://github.com/CollinErickson/sFFLHD +sfheaders: + version: 0.4.4 + title: Converts Between R Objects and Simple Feature Objects + maintainer: David Cooley + description: |- + Converts between R and Simple Feature 'sf' objects, without depending + on the Simple Feature library. Conversion functions are available at both the R level, + and through 'Rcpp'. + date_publication: '2024-01-17' + bug_reports: https://github.com/dcooley/sfheaders/issues + url: https://dcooley.github.io/sfheaders/ + url_cran: https://CRAN.R-project.org/package=sfheaders + url_git: '' +sfhelper: + version: 0.2.2.0 + title: Repair Functions for 'sf' Package Objects + maintainer: Mark Ravina + description: A group of functions that support the 'sf' package, focused primarily + on repairing polygons that break when re-projected. + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sfhelper + url_git: '' +sfhotspot: + version: 0.9.1 + title: Hot-Spot Analysis with Simple Features + maintainer: Matt Ashby + description: |- + Identify and understand clusters of points (typically representing + the locations of places or events) stored in simple-features (SF) objects. + This is useful for analysing, for example, hot-spots of crime events. The + package emphasises producing results from point SF data in a single step + using reasonable default values for all other arguments, to aid rapid data + analysis by users who are starting out. Functions available include kernel + density estimation (for details, see Yip (2020) + ), analysis of spatial association (Getis + and Ord (1992) ) and hot-spot + classification (Chainey (2020) ISBN:158948584X). + date_publication: '2025-02-19' + bug_reports: https://github.com/mpjashby/sfhotspot/issues + url: http://pkgs.lesscrime.info/sfhotspot/ + url_cran: https://CRAN.R-project.org/package=sfhotspot + url_git: '' +sfinx: + version: 1.7.99 + title: Straightforward Filtering Index for AP-MS Data Analysis (SFINX) + maintainer: Kevin Titeca + description: |- + The straightforward filtering index (SFINX) identifies true positive + protein interactions in a fast, user-friendly, and highly accurate way. + It is not only useful for the filtering of affinity purification - + mass spectrometry (AP-MS) data, but also for similar types of data + resulting from other co-complex interactomics technologies, such as TAP-MS, + Virotrap and BioID. SFINX can also be used via the website interface at + . + date_publication: '2017-07-19' + bug_reports: '' + url: http://sfinx.ugent.be + url_cran: https://CRAN.R-project.org/package=sfinx + url_git: '' +sfislands: + version: 1.0.0 + title: Streamlines the Process of Fitting Areal Spatial Models + maintainer: Kevin Horan + description: |- + Helpers for addressing the issue of disconnected spatial units. + It allows for convenient adding and removal of neighbourhood connectivity between areal units prior to modelling, with the visual aid of maps. + Post-modelling, it reduces the human workload for extracting, tidying and mapping predictions from areal models. + date_publication: '2024-03-21' + bug_reports: https://github.com/horankev/sfislands/issues + url: https://horankev.github.io/sfislands/ + url_cran: https://CRAN.R-project.org/package=sfislands + url_git: https://github.com/horankev/sfislands +SFM: + version: 0.1.0 + title: A Package for Analyzing Skew Factor Models + maintainer: Guangbao Guo + description: Generates Skew Factor Models data and applies Sparse Online Principal + Component (SOPC) method to estimate model parameters. It includes capabilities + for calculating mean squared error, relative error, and sparsity of the loading + matrix. Additionally, it includes robust regression methods such as adaptive Huber + regression.The philosophy of the package is described in Guo G. (2023) . + date_publication: '2024-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SFM + url_git: '' +sfnetworks: + version: 0.6.5 + title: Tidy Geospatial Networks + maintainer: Lucas van der Meer + description: |- + Provides a tidy approach to spatial network + analysis, in the form of classes and functions that enable a seamless + interaction between the network analysis package 'tidygraph' and the + spatial analysis package 'sf'. + date_publication: '2024-12-06' + bug_reports: https://github.com/luukvdmeer/sfnetworks/issues/ + url: https://luukvdmeer.github.io/sfnetworks/ + url_cran: https://CRAN.R-project.org/package=sfnetworks + url_git: https://github.com/luukvdmeer/sfnetworks +sfo: + version: 0.1.2 + title: San Francisco International Airport Monthly Air Passengers + maintainer: Rami Krispin + description: |- + Provides monthly statistics on the number of monthly air passengers at SFO airport such as operating airline, terminal, geo, etc. + Data source: San Francisco data portal (DataSF) . + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sfo + url_git: '' +SFPL: + version: 1.0.0 + title: Sparse Fused Plackett-Luce + maintainer: Sjoerd Hermes + description: Implements the methodological developments found in Hermes, van Heerwaarden, + and Behrouzi (2024) , and allows for the statistical + modeling of multi-group rank data in combination with object variables. The package + also allows for the simulation of synthetic multi-group rank data. + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SFPL + url_git: '' +SFS: + version: 0.1.4 + title: Similarity-First Search Seriation Algorithm + maintainer: Utz-Uwe Haus + description: An implementation of the Similarity-First Search algorithm (SFS), a + combinatorial algorithm which can be used to solve the seriation problem and to + recognize some structured weighted graphs. The SFS algorithm represents a generalization + to weighted graphs of the graph search algorithm Lexicographic Breadth-First Search + (Lex-BFS), a variant of Breadth-First Search. The SFS algorithm reduces to Lex-BFS + when applied to binary matrices (or, equivalently, unweighted graphs). Hence this + library can be also considered for Lex-BFS applications such as recognition of + graph classes like chordal or unit interval graphs. In fact, the SFS seriation + algorithm implemented in this package is a multisweep algorithm, which consists + in repeating a finite number of SFS iterations (at most n sweeps for a matrix + of size n). If the data matrix has a Robinsonian structure, then the ranking returned + by the multistep SFS algorithm is a Robinson ordering of the input matrix. Otherwise + the algorithm can be used as a heuristic to return a ranking partially satisfying + the Robinson property. + date_publication: '2019-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SFS + url_git: '' +sfsmisc: + version: 1.1-20 + title: Utilities from 'Seminar fuer Statistik' ETH Zurich + maintainer: Martin Maechler + description: |- + Useful utilities ['goodies'] from Seminar fuer Statistik ETH Zurich, + some of which were ported from S-plus in the 1990s. + For graphics, have pretty (Log-scale) axes eaxis(), an enhanced Tukey-Anscombe + plot, combining histogram and boxplot, 2d-residual plots, a 'tachoPlot()', + pretty arrows, etc. + For robustness, have a robust F test and robust range(). + For system support, notably on Linux, provides 'Sys.*()' functions with + more access to system and CPU information. + Finally, miscellaneous utilities such as simple efficient prime numbers, + integer codes, Duplicated(), toLatex.numeric() and is.whole(). + date_publication: '2024-11-05' + bug_reports: https://github.com/mmaechler/sfsmisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sfsmisc + url_git: https://github.com/mmaechler/sfsmisc +sft: + version: 2.2-1 + title: Functions for Systems Factorial Technology Analysis of Data + maintainer: Joe Houpt + description: A series of tools for analyzing Systems Factorial Technology data. This + includes functions for plotting and statistically testing capacity coefficient + functions and survivor interaction contrast functions. Houpt, Blaha, McIntire, + Havig, and Townsend (2013) provide a basic introduction + to Systems Factorial Technology along with examples using the sft R package. + date_publication: '2018-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sft + url_git: '' +sftime: + version: 0.3.0 + title: |- + Classes and Methods for Simple Feature Objects that Have a Time + Column + maintainer: Henning Teickner + description: |- + Classes and methods for spatial objects that have a registered time + column, in particular for irregular spatiotemporal data. The time column can + be of any type, but needs to be ordinal. Regularly laid out spatiotemporal + data (vector or raster data cubes) are handled by package 'stars'. + date_publication: '2024-09-11' + bug_reports: https://github.com/r-spatial/sftime/issues/ + url: https://r-spatial.github.io/sftime/ + url_cran: https://CRAN.R-project.org/package=sftime + url_git: https://github.com/r-spatial/sftime +SFtools: + version: 0.1.0 + title: Space Filling Based Tools for Data Mining + maintainer: Mohamed Laib + description: |- + Contains space filling based tools for + machine learning and data mining. Some functions offer + several computational techniques and deal with the out of + memory for large big data by using the ff package. + date_publication: '2017-06-28' + bug_reports: https://github.com/mlaib/SFtools/issues + url: https://sites.google.com/site/mohamedlaibwebpage/ + url_cran: https://CRAN.R-project.org/package=SFtools + url_git: '' +sftrack: + version: 0.5.4 + title: Modern Classes for Tracking and Movement Data + maintainer: Mathieu Basille + description: |- + Modern classes for tracking and movement data, building + on 'sf' spatial infrastructure, and early theoretical work from + Turchin (1998, ISBN: 9780878938476), and Calenge et al. (2009) + . Tracking data are series of + locations with at least 2-dimensional spatial coordinates (x,y), a + time index (t), and individual identification (id) of the object + being monitored; movement data are made of trajectories, i.e. the + line representation of the path, composed by steps (the + straight-line segments connecting successive locations). 'sftrack' + is designed to handle movement of both living organisms and + inanimate objects. + date_publication: '2023-03-16' + bug_reports: https://github.com/mablab/sftrack/issues + url: https://mablab.org/sftrack/ + url_cran: https://CRAN.R-project.org/package=sftrack + url_git: https://github.com/mablab/sftrack +sg: + version: 0.2.0 + title: '''SendGrid'' Email API Client' + maintainer: Botan Ağın + description: |- + Simple 'SendGrid' Email API client for creating and sending emails. + For more information, visit the official 'SendGrid' Email API documentation: . + date_publication: '2024-09-29' + bug_reports: https://github.com/botan/sg/issues + url: https://botan.github.io/sg/ + url_cran: https://CRAN.R-project.org/package=sg + url_git: https://github.com/botan/sg +sgapi: + version: 1.0.3 + title: |- + Aid Querying 'nomis' and 'Office for National Statistics Open + Geography' APIs + maintainer: Andrew Christy + description: Facilitates extraction of geospatial data from the 'Office for National + Statistics Open Geography' and 'nomis' Application Programming Interfaces (APIs). + Simplifies process of querying 'nomis' datasets + and extracting desired datasets in dataframe format. Extracts area shapefiles + at chosen resolution from 'Office for National Statistics Open Geography' . + date_publication: '2025-01-14' + bug_reports: https://github.com/Defra-Data-Science-Centre-of-Excellence/sgApi/issues + url: https://defra-data-science-centre-of-excellence.github.io/sgapi/ + url_cran: https://CRAN.R-project.org/package=sgapi + url_git: https://github.com/Defra-Data-Science-Centre-of-Excellence/sgapi +sgat: + version: '0.9' + title: Extract Information from Google's "Popular Times" + maintainer: Matias Poullain + description: Once you've identified a real life place, such as a shop, a restaurant, + a bar, etc. use this package to simulate a Google search and retrieve its "Popular + Times" and geographic location information and save them in Comma-Separated Values + files. This package also downloads a list of restaurants and bars of Ushuaia city, + Argentina. + date_publication: '2021-02-26' + bug_reports: https://github.com/matiaspoullain/sgat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgat + url_git: https://github.com/matiaspoullain/sgat +SGB: + version: 1.0.1.1 + title: Simplicial Generalized Beta Regression + maintainer: Monique Graf + description: 'Main properties and regression procedures using a generalization of + the Dirichlet distribution called Simplicial Generalized Beta distribution. It + is a new distribution on the simplex (i.e. on the space of compositions or positive + vectors with sum of components equal to 1). The Dirichlet distribution can be + constructed from a random vector of independent Gamma variables divided by their + sum. The SGB follows the same construction with generalized Gamma instead of Gamma + variables. The Dirichlet exponents are supplemented by an overall shape parameter + and a vector of scales. The scale vector is itself a composition and can be modeled + with auxiliary variables through a log-ratio transformation. Graf, M. (2017, ISBN: + 978-84-947240-0-8). See also the vignette enclosed in the package.' + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SGB + url_git: '' +sGBJ: + version: 0.1.0 + title: Survival Extension of the Generalized Berk-Jones Test + maintainer: Laura Villain + description: |- + Implements an extension of the Generalized Berk-Jones (GBJ) statistic for + survival data, sGBJ. It computes the sGBJ statistic and its p-value for testing + the association between a gene set and a time-to-event outcome with possible + adjustment on additional covariates. Detailed method is available at Villain L, Ferte T, + Thiebaut R and Hejblum BP (2021) . + date_publication: '2021-09-15' + bug_reports: https://github.com/lauravillain/sGBJ/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sGBJ + url_git: https://github.com/lauravillain/sGBJ +sgboost: + version: 0.2.0 + title: Sparse-Group Boosting + maintainer: Fabian Obster + description: |- + Sparse-group boosting to be used in conjunction with the 'mboost' for modeling grouped data. + Applicable to all sparse-group lasso type problems where within-group and between-group sparsity is desired. + Interprets and visualizes individual variables and groups. + date_publication: '2025-02-17' + bug_reports: https://github.com/FabianObster/sgboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgboost + url_git: https://github.com/FabianObster/sgboost +sgd: + version: 1.1.2 + title: Stochastic Gradient Descent for Scalable Estimation + maintainer: Junhyung Lyle Kim + description: |- + A fast and flexible set of tools for large scale estimation. It + features many stochastic gradient methods, built-in models, visualization + tools, automated hyperparameter tuning, model checking, interval estimation, + and convergence diagnostics. + date_publication: '2024-01-31' + bug_reports: https://github.com/airoldilab/sgd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgd + url_git: https://github.com/airoldilab/sgd +sgdGMF: + version: '1.0' + title: |- + Estimation of Generalized Matrix Factorization Models via + Stochastic Gradient Descent + maintainer: Cristian Castiglione + description: Efficient framework to estimate high-dimensional generalized matrix + factorization models using penalized maximum likelihood under a dispersion exponential + family specification. Either deterministic and stochastic methods are implemented + for the numerical maximization. In particular, the package implements the stochastic + gradient descent algorithm with a block-wise mini-batch strategy to speed up the + computations and an efficient adaptive learning rate schedule to stabilize the + convergence. All the theoretical details can be found in Castiglione et al. (2024, + ). Other methods considered for the optimization + are the alternated iterative re-weighted least squares and the quasi-Newton method + with diagonal approximation of the Fisher information matrix discussed in Kidzinski + et al. (2022, ). + date_publication: '2025-02-13' + bug_reports: https://github.com/CristianCastiglione/sgdGMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgdGMF + url_git: https://github.com/CristianCastiglione/sgdGMF +SGDinference: + version: 0.1.0 + title: Inference with Stochastic Gradient Descent + maintainer: Youngki Shin + description: |- + Estimation and inference methods for large-scale mean and quantile regression models via stochastic (sub-)gradient descent (S-subGD) algorithms. + The inference procedure handles cross-sectional data sequentially: + (i) updating the parameter estimate with each incoming "new observation", + (ii) aggregating it as a Polyak-Ruppert average, and + (iii) computing an asymptotically pivotal statistic for inference through random scaling. + The methodology used in the 'SGDinference' package is described in detail in the following papers: + (i) Lee, S., Liao, Y., Seo, M.H. and Shin, Y. (2022) "Fast and robust online inference with stochastic gradient descent via random scaling". + (ii) Lee, S., Liao, Y., Seo, M.H. and Shin, Y. (2023) "Fast Inference for Quantile Regression with Tens of Millions of Observations". + date_publication: '2023-11-16' + bug_reports: https://github.com/SGDinference-Lab/SGDinference/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SGDinference + url_git: https://github.com/SGDinference-Lab/SGDinference/ +sgee: + version: 0.6-0 + title: Stagewise Generalized Estimating Equations + maintainer: Gregory Vaughan + description: Stagewise techniques implemented with Generalized Estimating Equations + to handle individual, group, bi-level, and interaction selection. Stagewise approaches + start with an empty model and slowly build the model over several iterations, + which yields a 'path' of candidate models from which model selection can be performed. + This 'slow brewing' approach gives stagewise techniques a unique flexibility that + allows simple incorporation of Generalized Estimating Equations; see Vaughan, + G., Aseltine, R., Chen, K., Yan, J., (2017) for details. + date_publication: '2018-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgee + url_git: '' +sgeostat: + version: 1.0-27 + title: An Object-Oriented Framework for Geostatistical Modeling in S+ + maintainer: Albrecht Gebhardt + description: |- + An Object-oriented Framework for Geostatistical Modeling in S+ + containing functions for variogram estimation, variogram fitting and kriging + as well as some plot functions. Written entirely in S, therefore works only + for small data sets in acceptable computing time. + date_publication: '2016-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgeostat + url_git: '' +SGL: + version: '1.3' + title: |- + Fit a GLM (or Cox Model) with a Combination of Lasso and Group + Lasso Regularization + maintainer: Noah Simon + description: |- + Fit a regularized generalized linear model via penalized + maximum likelihood. The model is fit for a path of values of + the penalty parameter. Fits linear, logistic and Cox models. + date_publication: '2019-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SGL + url_git: '' +sglasso: + version: 1.2.6 + title: Lasso Method for RCON(V,E) Models + maintainer: Luigi Augugliaro + description: RCON(V, E) models are a kind of restriction of the Gaussian Graphical + Models defined by a set of equality constraints on the entries of the concentration + matrix. 'sglasso' package implements the structured graphical lasso (sglasso) + estimator proposed in Abbruzzo et al. (2014) for the weighted l1-penalized RCON(V, + E) model. Two cyclic coordinate algorithms are implemented to compute the sglasso + estimator, i.e. a cyclic coordinate minimization (CCM) and a cyclic coordinate + descent (CCD) algorithm. + date_publication: '2023-12-03' + bug_reports: '' + url: http://www.unipa.it/persone/docenti/a/luigi.augugliaro + url_cran: https://CRAN.R-project.org/package=sglasso + url_git: '' +sglg: + version: 0.2.2 + title: Fitting Semi-Parametric Generalized log-Gamma Regression Models + maintainer: Carlos Alberto Cardozo Delgado + description: |- + Set of tools to fit a linear multiple or semi-parametric regression + models with the possibility of non-informative random right-censoring. + Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression + or semi-parametric functions, whose non-parametric components may be approximated + by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes + the generalized extreme value and standard normal distributions as important special cases. Inference is based on penalized likelihood and bootstrap methods. + Also, some numerical and graphical devices for diagnostic of the fitted models are offered. + date_publication: '2022-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sglg + url_git: '' +sglr: + version: '0.8' + title: |- + Sequential Generalized Likelihood Ratio Decision Boundaries + Proposed by Shih, Lai, Heyse and Chen (2010, + ) + maintainer: Balasubramanian Narasimhan + description: We provide functions for computing the decision boundaries for pre-licensure + vaccine trials using the Generalized Likelihood Ratio tests proposed by Shih, + Lai, Heyse and Chen (2010, ). + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sglr + url_git: '' +sgmodel: + version: 0.1.2 + title: |- + Solves a Generic Stochastic Growth Model with a Representative + Agent + maintainer: Thomas Vigie + description: |- + It computes the solutions to a generic stochastic growth model for a given set of user supplied parameters. It includes + the solutions to the model, plots of the solution, + a summary of the features of the model, a function that covers different types of consumption preferences, + and a function that computes the moments of a Markov process. + Merton, Robert C (1971) , + Tauchen, George (1986) , + Wickham, Hadley (2009, ISBN:978-0-387-98140-6 ). + date_publication: '2024-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgmodel + url_git: '' +sGMRFmix: + version: 0.3.0 + title: |- + Sparse Gaussian Markov Random Field Mixtures for Anomaly + Detection + maintainer: Koji Makiyama + description: |- + An implementation of sparse Gaussian Markov random field mixtures + presented by Ide et al. (2016) . + It provides a novel anomaly detection method for multivariate noisy sensor data. + It can automatically handle multiple operational modes. + And it can also compute variable-wise anomaly scores. + date_publication: '2018-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sGMRFmix + url_git: '' +sgo: + version: 0.9.2 + title: Simple Geographical Operations (with OSGB36) + maintainer: Carlos Lozano Ruiz + description: |- + Methods focused in performing the OSGB36/ETRS89 transformation + (Great Britain and the Isle of Man only) by using the Ordnance Survey's + OSTN15/OSGM15 transformation model. Calculation of distances and areas from + sets of points defined in any of the supported Coordinated Systems is also + available. + date_publication: '2022-09-23' + bug_reports: https://github.com/clozanoruiz/sgo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgo + url_git: https://github.com/clozanoruiz/sgo +sgof: + version: 2.3.5 + title: Multiple Hypothesis Testing + maintainer: Irene Castro Conde + description: Seven different methods for multiple testing problems. The SGoF-type + methods (see for example, Carvajal Rodríguez et al., 2009 ; de + Uña Álvarez, 2012 ; Castro Conde et al., 2015 ) + and the BH and BY false discovery rate controlling procedures. + date_publication: '2024-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgof + url_git: '' +sgolay: + version: 1.0.3 + title: Efficient Savitzky-Golay Filtering + maintainer: Sergio Oller Moreno + description: |- + Smoothing signals and computing their derivatives is a common + requirement in signal processing workflows. Savitzky-Golay filters are a + established method able to do both (Savitzky and Golay, 1964 ). + This package implements one dimensional Savitzky-Golay filters that can be applied to + vectors and matrices (either row-wise or column-wise). + Vectorization and memory allocations have been profiled to reduce computational + fingerprint. Short filter lengths are implemented in the direct space, while + longer filters are implemented in frequency space, using a Fast Fourier + Transform (FFT). + date_publication: '2023-04-05' + bug_reports: https://github.com/zeehio/sgolay/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgolay + url_git: https://github.com/zeehio/sgolay +SGP: + version: 2.2-0.0 + title: Student Growth Percentiles & Percentile Growth Trajectories + maintainer: Damian W. Betebenner + description: An analytic framework for the calculation of norm- and criterion-referenced + academic growth estimates using large scale, longitudinal education assessment + data as developed in Betebenner (2009) . + date_publication: '2024-10-06' + bug_reports: https://github.com/CenterForAssessment/SGP/issues + url: https://sgp.io + url_cran: https://CRAN.R-project.org/package=SGP + url_git: https://github.com/CenterForAssessment/SGP +SGPdata: + version: 28.0-0.0 + title: Exemplar Data Sets for Student Growth Percentiles (SGP) Analyses + maintainer: Damian W. Betebenner + description: Data sets utilized by the 'SGP' package as exemplars for users to conduct + their own student growth percentiles (SGP) analyses. + date_publication: '2024-07-15' + bug_reports: https://github.com/CenterForAssessment/SGPdata/issues/ + url: https://CenterForAssessment.github.io/SGPdata/ + url_cran: https://CRAN.R-project.org/package=SGPdata + url_git: https://github.com/CenterForAssessment/SGPdata/ +sgPLS: + version: '1.8' + title: Sparse Group Partial Least Square Methods + maintainer: Benoit Liquet + description: Regularized version of partial least square approaches providing sparse, + group, and sparse group versions of partial least square regression models (Liquet, + B., Lafaye de Micheaux, P., Hejblum B., Thiebaut, R. (2016) ). + Version of PLS Discriminant analysis is also provided. + date_publication: '2023-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgPLS + url_git: '' +SGPR: + version: 0.1.2 + title: |- + Sparse Group Penalized Regression for Bi-Level Variable + Selection + maintainer: Gregor Buch + description: |- + Fits the regularization path of regression models + (linear and logistic) with additively combined penalty terms. All + possible combinations with Least Absolute Shrinkage and Selection Operator (LASSO), + Smoothly Clipped Absolute Deviation (SCAD), Minimax Concave Penalty (MCP) and + Exponential Penalty (EP) are supported. This includes Sparse Group LASSO (SGL), + Sparse Group SCAD (SGS), Sparse Group MCP (SGM) and Sparse Group EP (SGE). + For more information, see Buch, G., Schulz, A., Schmidtmann, I., Strauch, K., & Wild, P. S. (2024) . + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SGPR + url_git: '' +sgpv: + version: 1.1.0 + title: Calculate Second-Generation p-Values and Associated Measures + maintainer: Valerie Welty + description: Computation of second-generation p-values as described in Blume et + al. (2018) and Blume et al. (2019) . + There are additional functions which provide power and type I error calculations, + create graphs (particularly suited for large-scale inference usage), and a function + to estimate false discovery rates based on second-generation p-value inference. + date_publication: '2020-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgpv + url_git: '' +sgr: + version: 1.3.1 + title: Sample Generation by Replacement + maintainer: Massimiliano Pastore + description: Sample Generation by Replacement simulations (SGR; Lombardi & Pastore, + 2014; Pastore & Lombardi, 2014). The package can be used to perform fake data + analysis according to the sample generation by replacement approach. It includes + functions for making simple inferences about discrete/ordinal fake data. The package + allows to study the implications of fake data for empirical results. + date_publication: '2022-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgr + url_git: '' +sgraph: + version: 1.1.0 + title: Network Visualization Using 'sigma.js' + maintainer: Thomas Charlon + description: Interactive visualizations of graphs created with the 'igraph' package + using a 'htmlwidgets' wrapper for the 'sigma.js' network visualization v2.4.0 + , enabling to display several thousands of nodes. While + several 'R' packages have been developed to interface 'sigma.js', all were developed + for v1.x.x and none have migrated to v2.4.0 nor are they planning to. This package + builds upon the 'sigmaNet' package, and users familiar with it will recognize + the similar design approach. Two extensions have been added to the classic 'sigma.js' + visualizations by overriding the underlying 'JavaScript' code, enabling to draw + a frame around node labels, and to display labels on multiple lines by parsing + line breaks. Other additional functionalities that did not require overriding + 'sigma.js' code include toggling node visibility when clicked using a node attribute + and highlighting specific edges. 'sigma.js' is currently preparing a stable release + v3.0.0, and this package plans to update to it when it is available. + date_publication: '2024-08-19' + bug_reports: https://gitlab.com/thomaschln/sgraph/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgraph + url_git: https://gitlab.com/thomaschln/sgraph +sgs: + version: 0.3.4 + title: 'Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control' + maintainer: Fabio Feser + description: Implementation of Sparse-group SLOPE (SGS) (Feser and Evangelou (2023) + ) models. Linear and logistic regression models + are supported, both of which can be fit using k-fold cross-validation. Dense and + sparse input matrices are supported. In addition, a general Adaptive Three Operator + Splitting (ATOS) (Pedregosa and Gidel (2018) ) + implementation is provided. Group SLOPE (gSLOPE) (Brzyski et al. (2019) ) + and group-based OSCAR models (Feser and Evangelou (2024) ) + are also implemented. All models are available with strong screening rules (Feser + and Evangelou (2024) ) for computational speed-up. + date_publication: '2025-02-06' + bug_reports: https://github.com/ff1201/sgs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgs + url_git: https://github.com/ff1201/sgs +sgsR: + version: 1.4.5 + title: Structurally Guided Sampling + maintainer: Tristan RH Goodbody + description: |- + Structurally guided sampling (SGS) approaches for airborne laser scanning (ALS; LIDAR). Primary functions provide means + to generate data-driven stratifications & methods for allocating samples. Intermediate functions for calculating and extracting important information + about input covariates and samples are also included. Processing outcomes are intended to help forest and environmental management + practitioners better optimize field sample placement as well as assess and augment existing sample networks in the context of data + distributions and conditions. ALS data is the primary intended use case, however any rasterized remote sensing data can be used, + enabling data-driven stratifications and sampling approaches. + date_publication: '2024-03-03' + bug_reports: https://github.com/tgoodbody/sgsR/issues + url: https://tgoodbody.github.io/sgsR/ + url_cran: https://CRAN.R-project.org/package=sgsR + url_git: https://github.com/tgoodbody/sgsR +sgstar: + version: 0.1.2 + title: Seasonal Generalized Space Time Autoregressive (S-GSTAR) Model + maintainer: M. Yoga Satria Utama + description: |- + A set of function that implements for seasonal multivariate time series analysis based on Seasonal Generalized Space + Time Autoregressive with Seemingly Unrelated Regression (S-GSTAR-SUR) Model by Setiawan(2016). + date_publication: '2021-05-23' + bug_reports: https://github.com/yogasatria30/sgstar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sgstar + url_git: https://github.com/yogasatria30/sgstar +sgt: + version: '2.0' + title: Skewed Generalized T Distribution Tree + maintainer: Carter Davis + description: Density, distribution function, quantile function and random generation + for the skewed generalized t distribution. This package also provides a function + that can fit data to the skewed generalized t distribution using maximum likelihood + estimation. + date_publication: '2015-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sgt + url_git: '' +shades: + version: 1.4.0 + title: Simple Colour Manipulation + maintainer: Jon Clayden + description: Functions for easily manipulating colours, creating colour scales and + calculating colour distances. + date_publication: '2019-08-02' + bug_reports: https://github.com/jonclayden/shades/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shades + url_git: https://github.com/jonclayden/shades +shadowr: + version: 0.0.2 + title: |- + Selenium Plugin to Manage Multi Level Shadow Elements on Web + Page + maintainer: Ricardo Landolt + description: |- + Shadow Document Object Model is a web standard that offers component style and markup encapsulation. + It is a critically important piece of the Web Components story as it ensures that a component will work in any environment even if other CSS or JavaScript is at play on the page. + Custom HTML tags can't be directly identified with selenium tools, because Selenium doesn't provide any way to deal with shadow elements. + Using this plugin you can handle any custom HTML tags. + date_publication: '2022-05-25' + bug_reports: https://github.com/ricilandolt/shadowr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shadowr + url_git: https://github.com/ricilandolt/shadowr +shadowtext: + version: 0.1.4 + title: Shadow Text Grob and Layer + maintainer: Guangchuang Yu + description: |- + Implement shadowtextGrob() for 'grid' and geom_shadowtext() layer for 'ggplot2'. + These functions create/draw text grob with background shadow. + date_publication: '2024-07-18' + bug_reports: https://github.com/GuangchuangYu/shadowtext/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shadowtext + url_git: https://github.com/GuangchuangYu/shadowtext/ +shannon: + version: 0.2.0 + title: Computation of Entropy Measures and Relative Loss + maintainer: Muhammad Imran + description: 'The functions allow for the numerical evaluation of some commonly + used entropy measures, such as Shannon entropy, Rényi entropy, Havrda and Charvat + entropy, and Arimoto entropy, at selected parametric values from several well-known + and widely used probability distributions. Moreover, the functions also compute + the relative loss of these entropies using the truncated distributions. Related + works include: Awad, A. M., & Alawneh, A. J. (1987). Application of entropy to + a life-time model. IMA Journal of Mathematical Control and Information, 4(2), + 143-148. .' + date_publication: '2024-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shannon + url_git: '' +ShapDoE: + version: 1.0.0 + title: |- + Approximation of the Shapley Values Based on Experimental + Designs + maintainer: Liuqing Yang + description: |- + Estimating the Shapley values using the algorithm in + the paper Liuqing Yang, Yongdao Zhou, Haoda Fu, Min-Qian Liu and + Wei Zheng (2024) "Fast Approximation + of the Shapley Values Based on Order-of-Addition Experimental Designs". + You provide the data and define the value function, it retures the + estimated Shapley values based on sampling methods or experimental designs. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShapDoE + url_git: '' +shape: + version: 1.4.6.1 + title: Functions for Plotting Graphical Shapes, Colors + maintainer: Karline Soetaert + description: |- + Functions for plotting graphical shapes + such as ellipses, circles, cylinders, arrows, ... + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shape + url_git: '' +ShapeChange: + version: '1.5' + title: Change-Point Estimation using Shape-Restricted Splines + maintainer: Xiyue Liao + description: In a scatterplot where the response variable is Gaussian, Poisson or + binomial, we consider the case in which the mean function is smooth with a change-point, + which is a mode, an inflection point or a jump point. The main routine estimates + the mean curve and the change-point as well using shape-restricted B-splines. + An optional subroutine delivering a bootstrap confidence interval for the change-point + is incorporated in the main routine. + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShapeChange + url_git: '' +shapefiles: + version: 0.7.2 + title: Read and Write ESRI Shapefiles + maintainer: Ben Stabler + description: Functions to read and write ESRI shapefiles. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shapefiles + url_git: '' +shapeNA: + version: 0.0.2 + title: M-Estimation of Shape for Data with Missing Values + maintainer: Katharina Riemer + description: |- + M-estimators of location and shape following the power family + (Frahm, Nordhausen, Oja (2020) ) are + provided in the case of complete data and also when observations have + missing values together with functions aiding their visualization. + date_publication: '2021-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shapeNA + url_git: '' +ShapePattern: + version: 3.1.0 + title: Tools for Analyzing Shapes and Patterns + maintainer: Tarmo K. Remmel + description: 'This is an evolving and growing collection of tools for the quantification, + assessment, and comparison of shape and pattern. This collection provides tools + for: (1) the spatial decomposition of planar shapes using ''ShrinkShape'' to incrementally + shrink shapes to extinction while computing area, perimeter, and number of parts + at each iteration of shrinking; the spectra of results are returned in graphic + and tabular formats (Remmel 2015) , (2) simulating landscape + patterns, (3) provision of tools for estimating composition and configuration + parameters from a categorical (binary) landscape map (grid) and then simulates + a selected number of statistically similar landscapes. Class-focused pattern metrics + are computed for each simulated map to produce empirical distributions against + which statistical comparisons can be made. The code permits the analysis of single + maps or pairs of maps (Remmel and Fortin 2013) , + (4) counting the number of each first-order pattern element and converting that + information into both frequency and empirical probability vectors (Remmel 2020) + , and (5) computing the porosity of raster patches . + NOTE: This is a consolidation of existing packages (''PatternClass'', ''ShapePattern'') + to begin warehousing all shape and pattern code in a common package. Additional + utility tools for handling data are provided and this package will be added to + as more tools are created, cleaned-up, and documented. Note that all future developments + will appear in this package and that ''PatternClass'' will eventually be archived.' + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShapePattern + url_git: '' +shapeR: + version: 1.0-1 + title: Collection and Analysis of Otolith Shape Data + maintainer: Lisa Anne Libungan + description: |- + Studies otolith shape variation among fish populations. + Otoliths are calcified structures found in the inner ear of teleost fish and their shape has + been known to vary among several fish populations and stocks, making them very useful in taxonomy, + species identification and to study geographic variations. The package extends previously described + software used for otolith shape analysis by allowing the user to automatically extract closed + contour outlines from a large number of images, perform smoothing to eliminate pixel noise described in Haines and Crampton (2000) , + choose from conducting either a Fourier or wavelet see Gençay et al (2001) transform to the outlines and visualize + the mean shape. The output of the package are independent Fourier or wavelet coefficients + which can be directly imported into a wide range of statistical packages in R. The package + might prove useful in studies of any two dimensional objects. + date_publication: '2022-11-21' + bug_reports: '' + url: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0121102 + url_cran: https://CRAN.R-project.org/package=shapeR + url_git: https://github.com/lisalibungan/shapeR +shapes: + version: 1.2.7 + title: Statistical Shape Analysis + maintainer: Ian Dryden + description: |- + Routines for the statistical analysis of landmark + shapes, including Procrustes analysis, graphical displays, principal + components analysis, permutation and bootstrap tests, thin-plate + spline transformation grids and comparing covariance matrices. + See Dryden, I.L. and Mardia, K.V. (2016). Statistical shape analysis, + with Applications in R (2nd Edition), John Wiley and Sons. + date_publication: '2023-02-03' + bug_reports: '' + url: http://www.maths.nottingham.ac.uk/~ild/shapes + url_cran: https://CRAN.R-project.org/package=shapes + url_git: '' +ShapeSelectForest: + version: '1.7' + title: Shape Selection for Landsat Time Series of Forest Dynamics + maintainer: Xiyue Liao + description: Landsat satellites collect important data about global forest conditions. + Documentation about Landsat's role in forest disturbance estimation is available + at the site . By constrained quadratic B-splines, + this package delivers an optimal shape-restricted trajectory to a time series + of Landsat imagery for the purpose of modeling annual forest disturbance dynamics + to behave in an ecologically sensible manner assuming one of seven possible "shapes", + namely, flat, decreasing, one-jump (decreasing, jump up, decreasing), inverted + vee (increasing then decreasing), vee (decreasing then increasing), linear increasing, + and double-jump (decreasing, jump up, decreasing, jump up, decreasing). The main + routine selects the best shape according to the minimum Bayes information criterion + (BIC) or the cone information criterion (CIC), which is defined as the log of + the estimated predictive squared error. The package also provides parameters summarizing + the temporal pattern including year(s) of inflection, magnitude of change, pre- + and post-inflection rates of growth or recovery. In addition, it contains routines + for converting a flat map of disturbance agents to time-series disturbance maps + and a graphical routine displaying the fitted trajectory of Landsat imagery. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShapeSelectForest + url_git: '' +SHAPforxgboost: + version: 0.1.3 + title: SHAP Plots for 'XGBoost' + maintainer: Yang Liu + description: |- + Aid in visual data investigations + using SHAP (SHapley Additive exPlanation) visualization plots for 'XGBoost' and 'LightGBM'. + It provides summary plot, dependence plot, interaction plot, and force plot and relies on + the SHAP implementation provided by 'XGBoost' and 'LightGBM'. + Please refer to 'slundberg/shap' for the original implementation of SHAP in 'Python'. + date_publication: '2023-05-29' + bug_reports: https://github.com/liuyanguu/SHAPforxgboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SHAPforxgboost + url_git: https://github.com/liuyanguu/SHAPforxgboost +shapley: + version: '0.4' + title: Weighted Mean SHAP for Feature Selection in ML Grid and Ensemble + maintainer: E. F. Haghish + description: |- + This R package introduces Weighted Mean SHapley Additive exPlanations (WMSHAP), + an innovative method for calculating SHAP values for a grid of fine-tuned base-learner machine + learning models as well as stacked ensembles, a method not previously available due to the + common reliance on single best-performing models. By integrating the weighted mean + SHAP values from individual base-learners comprising the ensemble or individual + base-learners in a tuning grid search, the package weights SHAP contributions + according to each model's performance, assessed by multiple either R squared + (for both regression and classification models). alternatively, this software + also offers weighting SHAP values based on the area under the precision-recall + curve (AUCPR), the area under the curve (AUC), and F2 measures for binary classifiers. + It further extends this framework to implement weighted confidence intervals for + weighted mean SHAP values, offering a more comprehensive and robust feature importance + evaluation over a grid of machine learning models, instead of solely computing SHAP + values for the best model. This methodology is particularly beneficial for addressing + the severe class imbalance (class rarity) problem by providing a transparent, + generalized measure of feature importance that mitigates the risk of reporting + SHAP values for an overfitted or biased model and maintains robustness under severe + class imbalance, where there is no universal criteria of identifying the absolute + best model. Furthermore, the package implements hypothesis testing to ascertain the + statistical significance of SHAP values for individual features, as well as + comparative significance testing of SHAP contributions between features. Additionally, + it tackles a critical gap in feature selection literature by presenting criteria for + the automatic feature selection of the most important features across a grid of models + or stacked ensembles, eliminating the need for arbitrary determination of the number + of top features to be extracted. This utility is invaluable for researchers analyzing + feature significance, particularly within severely imbalanced outcomes where + conventional methods fall short. Moreover, it is also expected to report democratic + feature importance across a grid of models, resulting in a more comprehensive and + generalizable feature selection. The package further implements a novel method for + visualizing SHAP values both at subject level and feature level as well as a plot + for feature selection based on the weighted mean SHAP ratios. + date_publication: '2024-10-23' + bug_reports: https://github.com/haghish/shapley/issues + url: https://www.sv.uio.no/psi/english/people/academic/haghish/ + url_cran: https://CRAN.R-project.org/package=shapley + url_git: https://github.com/haghish/shapley +ShapleyOutlier: + version: 0.1.2 + title: |- + Multivariate Outlier Explanations using Shapley Values and + Mahalanobis Distances + maintainer: Marcus Mayrhofer + description: |- + Based on Shapley values to explain multivariate outlyingness and to detect and impute cellwise outliers. + Includes implementations of methods described in Mayrhofer and Filzmoser (2023) . + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShapleyOutlier + url_git: '' +ShapleyValue: + version: 0.2.0 + title: Shapley Value Regression for Relative Importance of Attributes + maintainer: Jingyi Liang + description: Shapley Value Regression for calculating the relative importance of + independent variables in linear regression with avoiding the collinearity. + date_publication: '2021-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShapleyValue + url_git: '' +shapper: + version: 0.1.3 + title: Wrapper of Python Library 'shap' + maintainer: Szymon Maksymiuk + description: Provides SHAP explanations of machine learning models. In applied machine + learning, there is a strong belief that we need to strike a balance between interpretability + and accuracy. However, in field of the Interpretable Machine Learning, there are + more and more new ideas for explaining black-box models. One of the best known + method for local explanations is SHapley Additive exPlanations (SHAP) introduced + by Lundberg, S., et al., (2016) The SHAP method is used to + calculate influences of variables on the particular observation. This method is + based on Shapley values, a technique used in game theory. The R package 'shapper' + is a port of the Python library 'shap'. + date_publication: '2020-08-28' + bug_reports: https://github.com/ModelOriented/shapper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shapper + url_git: https://github.com/ModelOriented/shapper +shapr: + version: 1.0.2 + title: Prediction Explanation with Dependence-Aware Shapley Values + maintainer: Martin Jullum + description: |- + Complex machine learning models are often hard to interpret. However, in + many situations it is crucial to understand and explain why a model made a specific + prediction. Shapley values is the only method for such prediction explanation framework + with a solid theoretical foundation. Previously known methods for estimating the Shapley + values do, however, assume feature independence. This package implements methods which accounts for any feature + dependence, and thereby produces more accurate estimates of the true Shapley values. + An accompanying 'Python' wrapper ('shaprpy') is available through the GitHub repository. + date_publication: '2025-02-07' + bug_reports: https://github.com/NorskRegnesentral/shapr/issues + url: https://norskregnesentral.github.io/shapr/ + url_cran: https://CRAN.R-project.org/package=shapr + url_git: https://github.com/NorskRegnesentral/shapr/ +shapviz: + version: 0.9.7 + title: SHAP Visualizations + maintainer: Michael Mayer + description: |- + Visualizations for SHAP (SHapley Additive exPlanations), such + as waterfall plots, force plots, various types of importance plots, + dependence plots, and interaction plots. These plots act on a + 'shapviz' object created from a matrix of SHAP values and a + corresponding feature dataset. Wrappers for the R packages 'xgboost', + 'lightgbm', 'fastshap', 'shapr', 'h2o', 'treeshap', 'DALEX', and + 'kernelshap' are added for convenience. By separating visualization + and computation, it is possible to display factor variables in graphs, + even if the SHAP values are calculated by a model that requires + numerical features. The plots are inspired by those provided by the + 'shap' package in Python, but there is no dependency on it. + date_publication: '2025-01-19' + bug_reports: https://github.com/ModelOriented/shapviz/issues + url: https://modeloriented.github.io/shapviz/ + url_cran: https://CRAN.R-project.org/package=shapviz + url_git: https://github.com/ModelOriented/shapviz +shar: + version: 2.3.1 + title: Species-Habitat Associations + maintainer: Maximilian H.K. Hesselbarth + description: |- + Analyse species-habitat associations in R. Therefore, information about the location + of the species (as a point pattern) is needed together with environmental conditions + (as a categorical raster). To test for significance habitat associations, one of + the two components is randomized. Methods are mainly based on Plotkin et al. (2000) + and Harms et al. (2001) . + date_publication: '2025-01-10' + bug_reports: https://github.com/r-spatialecology/shar/issues/ + url: https://r-spatialecology.github.io/shar/ + url_cran: https://CRAN.R-project.org/package=shar + url_git: '' +SharkDemography: + version: 1.1.0 + title: Shark Demographic Analyses Using Leslie Matrix Models + maintainer: Jonathan Smart + description: |- + Run Leslie Matrix models using Monte Carlo simulations for any specified shark species. + This package was developed during the publication of Smart, JJ, White, WT, Baje, L, et al. (2020) + "Can multi-species shark longline fisheries be managed sustainably using size limits? + Theoretically, yes. Realistically, no".J Appl Ecol. 2020; 57; 1847–1860. + . + date_publication: '2023-11-21' + bug_reports: https://github.com/jonathansmart/SharkDemography/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SharkDemography + url_git: https://github.com/jonathansmart/SharkDemography +sharp: + version: 1.4.6 + title: Stability-enHanced Approaches using Resampling Procedures + maintainer: Barbara Bodinier + description: In stability selection (N Meinshausen, P Bühlmann (2010) ) + and consensus clustering (S Monti et al (2003) ), + resampling techniques are used to enhance the reliability of the results. In this + package, hyper-parameters are calibrated by maximising model stability, which + is measured under the null hypothesis that all selection (or co-membership) probabilities + are identical (B Bodinier et al (2023a) and B Bodinier + et al (2023b) ). Functions are readily implemented + for the use of LASSO regression, sparse PCA, sparse (group) PLS or graphical LASSO + in stability selection, and hierarchical clustering, partitioning around medoids, + K means or Gaussian mixture models in consensus clustering. + date_publication: '2024-02-03' + bug_reports: https://github.com/barbarabodinier/sharp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sharp + url_git: https://github.com/barbarabodinier/sharp +sharpData: + version: '1.4' + title: Data Sharpening + maintainer: W.J. Braun + description: |- + Functions and data sets inspired by data sharpening - + data perturbation to achieve improved performance in + nonparametric estimation, as described in Choi, E., Hall, P. + and Rousson, V. (2000). + Capabilities for enhanced local linear regression function + and derivative estimation are included, as well as an + asymptotically correct iterated data sharpening estimator + for any degree of local polynomial regression estimation. + A cross-validation-based bandwidth selector is included which, + in concert with the iterated sharpener, will often provide + superior performance, according to a median integrated squared + error criterion. Sample data sets are provided to illustrate + function usage. + date_publication: '2021-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sharpData + url_git: '' +SharpeR: + version: 1.4.0 + title: Statistical Significance of the Sharpe Ratio + maintainer: Steven E. Pav + description: |- + A collection of tools for analyzing significance of assets, + funds, and trading strategies, based on the Sharpe ratio and overfit + of the same. Provides density, distribution, quantile and random generation + of the Sharpe ratio distribution based on normal returns, as well + as the optimal Sharpe ratio over multiple assets. Computes confidence intervals + on the Sharpe and provides a test of equality of Sharpe ratios based on + the Delta method. The statistical foundations of the Sharpe can be found in + the author's Short Sharpe Course . + date_publication: '2024-12-18' + bug_reports: https://github.com/shabbychef/SharpeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SharpeR + url_git: https://github.com/shabbychef/SharpeR +sharpeRratio: + version: 1.4.3 + title: Moment-Free Estimation of Sharpe Ratios + maintainer: Damien Challet + description: An efficient moment-free estimator of the Sharpe ratio, or signal-to-noise + ratio, for heavy-tailed data (see ). + date_publication: '2022-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sharpeRratio + url_git: '' +sharpPen: + version: '2.0' + title: Penalized Data Sharpening for Local Polynomial Regression + maintainer: D. Wang + description: |- + Functions and data sets for data sharpening. + Nonparametric regressions are computed subject to smoothness + and other kinds of penalties. + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sharpPen + url_git: '' +sharpr2: + version: 1.1.1.0 + title: Estimating Regulatory Scores and Identifying ATAC-STARR Data + maintainer: Liang He + description: An algorithm for identifying high-resolution driver elements for datasets + from a high-definition reporter assay library. Xinchen Wang, Liang He, Sarah Goggin, + Alham Saadat, Li Wang, Melina Claussnitzer, Manolis Kellis (2017) . + date_publication: '2018-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sharpr2 + url_git: '' +sharx: + version: 1.0-6 + title: Models and Data Sets for the Study of Species-Area Relationships + maintainer: Peter Solymos + description: |- + Hierarchical models for the analysis of species-area + relationships (SARs) by combining several data sets and covariates; + with a global data set combining individual SAR studies; + as described in Solymos and Lele + (2012) . + date_publication: '2024-05-21' + bug_reports: https://github.com/psolymos/sharx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sharx + url_git: https://github.com/psolymos/sharx +shattering: + version: 1.0.7 + title: Estimate the Shattering Coefficient for a Particular Dataset + maintainer: Rodrigo F. de Mello + description: 'The Statistical Learning Theory (SLT) provides the theoretical background + to ensure that a supervised algorithm generalizes the mapping f:X -> Y given f + is selected from its search space bias F. This formal result depends on the Shattering + coefficient function N(F,2n) to upper bound the empirical risk minimization principle, + from which one can estimate the necessary training sample size to ensure the probabilistic + learning convergence and, most importantly, the characterization of the capacity + of F, including its under and overfitting abilities while addressing specific + target problems. In this context, we propose a new approach to estimate the maximal + number of hyperplanes required to shatter a given sample, i.e., to separate every + pair of points from one another, based on the recent contributions by Har-Peled + and Jones in the dataset partitioning scenario, and use such foundation to analytically + compute the Shattering coefficient function for both binary and multi-class problems. + As main contributions, one can use our approach to study the complexity of the + search space bias F, estimate training sample sizes, and parametrize the number + of hyperplanes a learning algorithm needs to address some supervised task, what + is specially appealing to deep neural networks. Reference: de Mello, R.F. (2019) + "On the Shattering Coefficient of Supervised Learning Algorithms" ; + de Mello, R.F., Ponti, M.A. (2018, ISBN: 978-3319949888) "Machine Learning: A + Practical Approach on the Statistical Learning Theory".' + date_publication: '2021-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shattering + url_git: '' +shazam: + version: 1.2.0 + title: Immunoglobulin Somatic Hypermutation Analysis + maintainer: Susanna Marquez + description: |- + Provides a computational framework for analyzing mutations in + immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of + antigen-driven selection pressure, mutational load quantification, building of + somatic hypermutation (SHM) models, and model-dependent distance calculations. + Also includes empirically derived models of SHM for both mice and humans. + Citations: + Gupta and Vander Heiden, et al (2015) , + Yaari, et al (2012) , + Yaari, et al (2013) , + Cui, et al (2016) . + date_publication: '2023-10-02' + bug_reports: https://bitbucket.org/kleinstein/shazam/issues + url: http://shazam.readthedocs.io + url_cran: https://CRAN.R-project.org/package=shazam + url_git: '' +SheetReader: + version: 1.2.1 + title: Parse xlsx Files + maintainer: Felix Henze + description: |- + Uses C++ via the 'Rcpp' package to parse modern Excel files ('.xlsx'). + Memory usage is kept minimal by decompressing only parts of the file at a time, + while employing multiple threads to achieve significant runtime reduction. + Uses and . + date_publication: '2024-05-30' + bug_reports: https://github.com/fhenz/SheetReader-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SheetReader + url_git: https://github.com/fhenz/SheetReader-r +SHELF: + version: 1.12.0 + title: Tools to Support the Sheffield Elicitation Framework + maintainer: Jeremy Oakley + description: |- + Implements various methods for eliciting a probability + distribution for a single parameter from an expert or a group of + experts. The expert provides a small number of probability judgements, + corresponding to points on his or her cumulative distribution + function. A range of parametric distributions can then be fitted and + displayed, with feedback provided in the form of fitted probabilities + and percentiles. For multiple experts, a weighted linear pool can be + calculated. Also includes functions for eliciting beliefs about + population distributions; eliciting multivariate distributions using a + Gaussian copula; eliciting a Dirichlet distribution; eliciting + distributions for variance parameters in a random effects + meta-analysis model; survival extrapolation. R Shiny apps for most of the methods are + included. + date_publication: '2025-03-01' + bug_reports: https://github.com/OakleyJ/SHELF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SHELF + url_git: https://github.com/OakleyJ/SHELF +ShellChron: + version: 0.4.0 + title: Builds Chronologies from Oxygen Isotope Profiles in Shells + maintainer: Niels de Winter + description: |- + Takes as input a stable oxygen isotope (d18O) profile measured in growth direction (D) + through a shell + uncertainties in both variables (d18O_err & D_err). It then models the seasonality + in the d18O record by fitting a combination of a growth and temperature sine wave to year-length chunks of + the data (see Judd et al., (2018) ). This modeling is carried out along a sliding window through the data and yields estimates of + the day of the year (Julian Day) and local growth rate for each data point. Uncertainties in both modeling + routine and the data itself are propagated and pooled to obtain a confidence envelope around the age of + each data point in the shell. The end result is a shell chronology consisting of estimated ages of shell + formation relative to the annual cycle with their uncertainties. All formulae in the package serve this + purpose, but the user can customize the model (e.g. number of days in a year and the mineralogy of the + shell carbonate) through input parameters. + date_publication: '2021-07-05' + bug_reports: https://github.com/nielsjdewinter/ShellChron/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ShellChron + url_git: https://github.com/nielsjdewinter/ShellChron +shelltrace: + version: 3.5.1 + title: Bivalve Growth and Trace Element Accumulation Model + maintainer: Niels J. de Winter + description: |2- + + Contains all the formulae of the growth and trace element uptake model described in the equally-named + Geoscientific Model Development paper (de Winter, 2017, ). The model takes as input a file with X- and Y-coordinates of digitized + growth increments recognized on a longitudinal cross section through the bivalve shell, as well as a BMP file of an elemental map of the + cross section surface with chemically distinct phases separated by phase analysis. It proceeds by a step-by-step process described in + the paper, by which digitized growth increments are used to calculate changes in shell height, shell thickness, shell volume, shell mass + and shell growth rate through the bivalve's life time. Then, results of this growth modelling are combined with the trace element mapping + results to trace the incorporation of trace elements into the bivalve shell. Results of various modelling parameters can be exported in + the form of XLSX files. + date_publication: '2017-10-06' + bug_reports: https://github.com/nielsjdewinter/ShellTrace/issues + url: https://doi.org/10.5194/gmd-2017-137-supplement + url_cran: https://CRAN.R-project.org/package=shelltrace + url_git: https://github.com/nielsjdewinter/ShellTrace +shelter: + version: 0.1.1 + title: Support for Secure API Key Management + maintainer: Shawn Garbett + description: |- + Secure handling of API keys can be difficult. This package provides + secure convenience functions for + entering / handling API keys and opening connections via inversion of control + on those keys. Works seamlessly between production and developer environments. + date_publication: '2024-11-07' + bug_reports: https://github.com/vubiostat/shelter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shelter + url_git: https://github.com/vubiostat/shelter +sherlock: + version: 0.7.0 + title: Graphical Displays for Structured Problem Solving and Diagnosis + maintainer: Gabor Szabo + description: |- + Powerful graphical displays and statistical tools for structured problem solving and diagnosis. + The functions of the 'sherlock' package are especially useful for applying the process of elimination as a problem diagnosis technique. + The 'sherlock' package was designed to seamlessly work with the 'tidyverse' set of packages and provides a collection of graphical displays + built on top of the 'ggplot' and 'plotly' packages, such as different kinds of small multiple plots as well as helper functions such as + adding reference lines, normalizing observations, reading in data or saving analysis results in an Excel file. + References: + David Hartshorne (2019, ISBN: 978-1-5272-5139-7). + Stefan H. Steiner, R. Jock MacKay (2005, ISBN: 0873896467). + date_publication: '2023-06-11' + bug_reports: https://github.com/gaboraszabo/sherlock/issues + url: https://gaboraszabo.github.io/sherlock/ + url_cran: https://CRAN.R-project.org/package=sherlock + url_git: https://github.com/gaboraszabo/sherlock +SherlockHolmes: + version: 1.0.1 + title: Building a Concordance of Terms in a Series of Texts + maintainer: Barry Zeeberg + description: Compute the frequency distribution of a search term in a series of + texts. For example, Arthur Conan Doyle wrote a total of 60 Sherlock Holmes stories, + comprised of 54 short stories and 4 longer novels. I wanted to test my own subjective + impression that, in many of the stories, Sherlock Holmes' popularity was used + as bait to induce the reader to read a story that is essentially not primarily + a Sherlock Holmes story. I used the term "Holmes" as a search pattern, since Watson + would frequently address him by name, or use his name to describe something that + he was doing. My hypothesis is that the frequency distribution of the search pattern + "Holmes" is a good proxy for the degree to which a story is or is not truly a + Sherlock Holmes story. The results are presented in a manuscript that is available + as a vignette and online at . + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SherlockHolmes + url_git: '' +shidashi: + version: 0.1.6 + title: A Shiny Dashboard Template System + maintainer: Zhengjia Wang + description: |- + A template system based on 'AdminLTE3' + () + theme. Comes with default theme that can be easily customized. + Developers can upload modified templates on 'Github', and users can + easily download templates with 'RStudio' project wizard. + The key features of the default template include light and dark theme + switcher, resizing graphs, synchronizing inputs across sessions, + new notification system, fancy progress bars, and card-like flip + panels with back sides, as well as various of 'HTML' tool widgets. + date_publication: '2024-02-17' + bug_reports: https://github.com/dipterix/shidashi/issues + url: https://dipterix.org/shidashi/ + url_cran: https://CRAN.R-project.org/package=shidashi + url_git: https://github.com/dipterix/shidashi +shide: + version: 0.2.1 + title: Date/Time Classes Based on Jalali Calendar + maintainer: Mohsen Mollayi + description: |- + Implements S3 classes for storing dates and date-times based on the Jalali calendar. + The main design goal of 'shide' is consistency with base R's 'Date' and 'POSIXct'. + It provide features such as: date-time parsing, formatting and arithmetic. + date_publication: '2024-07-19' + bug_reports: https://github.com/mmollayi/shide/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shide + url_git: https://github.com/mmollayi/shide +ShiftConvolvePoibin: + version: 1.0.0 + title: Exactly Computing the Tail of the Poisson-Binomial Distribution + maintainer: Andrew Lee + description: An exact method for computing the Poisson-Binomial Distribution (PBD). + The package provides a function for generating a random sample from the PBD, as + well as two distinct approaches for computing the density, distribution, and quantile + functions of the PBD. The first method uses direct-convolution, or a dynamic-programming + approach which is numerically stable but can be slow for a large input due to + its quadratic complexity. The second method is much faster on large inputs thanks + to its use of Fast Fourier Transform (FFT) based convolutions. Notably in this + case the package uses an exponential shift to practically guarantee the relative + accuracy of the computation of an arbitrarily small tail of the PBD -- something + that FFT-based methods often struggle with. This ShiftConvolvePoiBin method is + described in Peres, Lee and Keich (2020) where it is also shown + to be competitive with the fastest implementations for exactly computing the entire + Poisson-Binomial distribution. + date_publication: '2020-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShiftConvolvePoibin + url_git: '' +shiftR: + version: '1.5' + title: Fast Enrichment Analysis via Circular Permutations + maintainer: Andrey A Shabalin + description: |- + Fast enrichment analysis for locally correlated statistics + via circular permutations. + The analysis can be performed at multiple significance thresholds + for both primary and auxiliary data sets with + efficient correction for multiple testing. + date_publication: '2019-03-22' + bug_reports: https://github.com/andreyshabalin/shiftR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shiftR + url_git: https://github.com/andreyshabalin/shiftR +ShiftShareSE: + version: 1.1.0 + title: Inference in Regressions with Shift-Share Structure + maintainer: Michal Kolesár + description: |- + Provides confidence intervals in least-squares regressions when the + variable of interest has a shift-share structure, and in instrumental + variables regressions when the instrument has a shift-share structure. The + confidence intervals implement the AKM and AKM0 methods developed in Adão, + Kolesár, and Morales (2019) . + date_publication: '2022-04-24' + bug_reports: https://github.com/kolesarm/ShiftShareSE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ShiftShareSE + url_git: https://github.com/kolesarm/ShiftShareSE +shinipsum: + version: 0.1.1 + title: Lorem-Ipsum-Like Helpers for Fast Shiny Prototyping + maintainer: Colin Fay + description: |- + Prototype your shiny apps quickly with these + Lorem-Ipsum-like Helpers. + date_publication: '2024-02-09' + bug_reports: https://github.com/Thinkr-open/shinipsum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinipsum + url_git: https://github.com/Thinkr-open/shinipsum +shiny: + version: 1.10.0 + title: Web Application Framework for R + maintainer: Winston Chang + description: |- + Makes it incredibly easy to build interactive web + applications with R. Automatic "reactive" binding between inputs and + outputs and extensive prebuilt widgets make it possible to build + beautiful, responsive, and powerful applications with minimal effort. + date_publication: '2024-12-14' + bug_reports: https://github.com/rstudio/shiny/issues + url: https://shiny.posit.co/ + url_cran: https://CRAN.R-project.org/package=shiny + url_git: https://github.com/rstudio/shiny +shiny.benchmark: + version: 0.1.1 + title: Benchmark the Performance of 'shiny' Applications + maintainer: Douglas Azevedo + description: Compare performance between different versions of a 'shiny' application + based on 'git' references. + date_publication: '2023-01-20' + bug_reports: https://github.com/Appsilon/shiny.benchmark/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.benchmark + url_git: https://github.com/Appsilon/shiny.benchmark +shiny.blueprint: + version: 0.3.0 + title: Palantir's 'Blueprint' for 'Shiny' Apps + maintainer: Jakub Sobolewski + description: |- + Easily use 'Blueprint', the popular 'React' library from Palantir, in your 'Shiny' app. + 'Blueprint' provides a rich set of UI components for creating visually appealing applications + and is optimized for building complex, data-dense web interfaces. + This package provides most components from the underlying library, + as well as special wrappers for some components + to make it easy to use them in 'R' without writing 'JavaScript' code. + date_publication: '2024-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.blueprint + url_git: '' +shiny.destroy: + version: 0.1.0 + title: Create Destroyable Modules in 'Shiny' + maintainer: Ashley Baldry + description: |- + Enables the complete removal of various 'Shiny' components, such + as inputs, outputs and modules. It also aids in the removal of observers that have been + created in dynamically created modules. + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.destroy + url_git: '' +shiny.emptystate: + version: 0.1.0 + title: Empty State Components for 'Shiny' + maintainer: Ryszard Szymański + description: |2- + + Offers a comprehensive solution for managing 'empty states' in 'Shiny' applications. + It provides tools to create both default and customizable components for scenarios where + data is absent or doesn't match user-defined filters. The package prioritizes user experience, + ensuring clarity and consistency even when data is not available to display. + date_publication: '2023-08-17' + bug_reports: https://github.com/Appsilon/shiny.emptystate/issues + url: https://appsilon.github.io/shiny.emptystate/ + url_cran: https://CRAN.R-project.org/package=shiny.emptystate + url_git: https://github.com/Appsilon/shiny.emptystate +shiny.exe: + version: 0.2.0 + title: Launch a Shiny Application without Opening R or RStudio + maintainer: Abdoul Oudouss Diakité + description: Launch an application by a simple click without opening R or RStudio. + The package has 3 functions of which only one is essential in its use, `shiny.exe()`. + It generates a script in the open shiny project then create a shortcut in the + same folder that allows you to launch the app by clicking.If you set `host = 'public'`, + the application will be launched on the public server to which you are connected. + Thus, all other devices connected to the same server will be able to access the + application through the link of your `IPv4` extended by the port. You can stop + the application by leaving the terminal opened by the shortcut. + date_publication: '2023-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.exe + url_git: https://github.com/AODiakite +shiny.fluent: + version: 0.4.0 + title: Microsoft Fluent UI for Shiny Apps + maintainer: Jakub Sobolewski + description: |- + A rich set of UI components for building Shiny applications, + including inputs, containers, overlays, menus, and various utilities. + All components from Fluent UI (the underlying JavaScript library) + are available and have usage examples in R. + date_publication: '2024-05-21' + bug_reports: '' + url: https://appsilon.github.io/shiny.fluent/ + url_cran: https://CRAN.R-project.org/package=shiny.fluent + url_git: https://github.com/appsilon/shiny.fluent +shiny.i18n: + version: 0.3.0 + title: Shiny Applications Internationalization + maintainer: Jakub Nowicki + description: |- + It provides easy internationalization of Shiny + applications. It can be used as standalone translation package + to translate reports, interactive visualizations or + graphical elements as well. + date_publication: '2023-01-16' + bug_reports: https://github.com/Appsilon/shiny.i18n/issues + url: https://appsilon.github.io/shiny.i18n/ + url_cran: https://CRAN.R-project.org/package=shiny.i18n + url_git: https://github.com/Appsilon/shiny.i18n +shiny.info: + version: 0.2.0 + title: '''shiny'' Info' + maintainer: Jakub Nowicki + description: Displays simple diagnostic information of the 'shiny' project in the + user interface of the app. + date_publication: '2020-03-23' + bug_reports: https://github.com/Appsilon/shiny.info/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.info + url_git: '' +shiny.ollama: + version: 0.1.1 + title: |- + R 'shiny' Interface for Chatting with Large Language Models + Offline on Local with 'ollama' + maintainer: Indraneel Chakraborty + description: Chat with large language models on your machine without internet with + complete privacy via 'ollama', powered by R 'shiny' interface. For more information + on 'ollama', visit . + date_publication: '2025-01-27' + bug_reports: https://github.com/ineelhere/shiny.ollama/issues + url: https://www.indraneelchakraborty.com/shiny.ollama/ + url_cran: https://CRAN.R-project.org/package=shiny.ollama + url_git: https://github.com/ineelhere/shiny.ollama +shiny.pwa: + version: 0.2.1 + title: Progressive Web App Support for Shiny + maintainer: Pedro Silva + description: |- + Adds Progressive Web App support for Shiny apps, including + desktop and mobile installations. + date_publication: '2021-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.pwa + url_git: https://github.com/pedrocoutinhosilva/shiny.pwa +shiny.react: + version: 0.4.0 + title: Tools for Using React in Shiny + maintainer: Jakub Sobolewski + description: A toolbox for defining React component wrappers which can be used seamlessly + in Shiny apps. + date_publication: '2024-05-20' + bug_reports: '' + url: https://appsilon.github.io/shiny.react/ + url_cran: https://CRAN.R-project.org/package=shiny.react + url_git: https://github.com/Appsilon/shiny.react +shiny.reglog: + version: 0.5.2 + title: Optional Login and Registration Module System for ShinyApps + maintainer: Michal Kosinski + description: |- + RegLog system provides a set of shiny modules to handle register + procedure for your users, alongside with login, edit credentials and + password reset functionality. + It provides support for popular SQL databases + and optionally googlesheet-based database for easy setup. For email sending + it provides support for 'emayili' and 'gmailr' backends. Architecture makes + customizing usability pretty straightforward. + The authentication system created + with shiny.reglog is designed to be optional: user don't need to be logged-in + to access your application, but when logged-in the user data can be used + to read from and write to relational databases. + date_publication: '2022-08-30' + bug_reports: '' + url: https://statismike.github.io/shiny.reglog/ + url_cran: https://CRAN.R-project.org/package=shiny.reglog + url_git: '' +shiny.router: + version: 0.3.1 + title: Basic Routing for Shiny Web Applications + maintainer: Ryszard Szymański + description: |- + It is a simple router for your Shiny apps. + The router allows you to create dynamic web applications with real-time + User Interface and easily share url to pages within your Shiny apps. + date_publication: '2023-04-18' + bug_reports: https://github.com/Appsilon/shiny.router/issues + url: https://appsilon.github.io/shiny.router/ + url_cran: https://CRAN.R-project.org/package=shiny.router + url_git: https://github.com/Appsilon/shiny.router +shiny.semantic: + version: 0.5.1 + title: Semantic UI Support for Shiny + maintainer: Jakub Nowicki + description: |- + Creating a great user interface for your Shiny apps can be a + hassle, especially if you want to work purely in R and don't want to + use, for instance HTML templates. This package adds support for a + powerful UI library Fomantic UI - (before + Semantic). It also supports universal UI input binding that works with + various DOM elements. + date_publication: '2024-04-05' + bug_reports: https://github.com/Appsilon/shiny.semantic/issues + url: https://appsilon.github.io/shiny.semantic/ + url_cran: https://CRAN.R-project.org/package=shiny.semantic + url_git: https://github.com/Appsilon/shiny.semantic +shiny.tailwind: + version: 0.2.2 + title: '''TailwindCSS'' for Shiny Apps' + maintainer: Kyle Butts + description: |- + Allows 'TailwindCSS' to be used in Shiny apps with just-in-time + compiling, custom css with '@apply' directive, and custom tailwind + configurations. + date_publication: '2022-10-13' + bug_reports: https://github.com/kylebutts/shiny.tailwind/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shiny.tailwind + url_git: https://github.com/kylebutts/shiny.tailwind +shiny.telemetry: + version: 0.3.1 + title: '''Shiny'' App Usage Telemetry' + maintainer: André Veríssimo + description: |- + Enables instrumentation of 'Shiny' apps for tracking user + session events such as input changes, browser type, and session + duration. These events can be sent to any of the available storage + backends and analyzed using the included 'Shiny' app to gain insights + about app usage and adoption. + date_publication: '2024-10-15' + bug_reports: https://github.com/Appsilon/shiny.telemetry/issues + url: https://appsilon.github.io/shiny.telemetry/ + url_cran: https://CRAN.R-project.org/package=shiny.telemetry + url_git: https://github.com/Appsilon/shiny.telemetry +shiny2docker: + version: 0.0.2 + title: Generate Dockerfiles for 'Shiny' Applications + maintainer: Vincent Guyader + description: |- + Automates the creation of Dockerfiles for deploying 'Shiny' applications. + By integrating with 'renv' for dependency management and leveraging Docker-based + solutions, it simplifies the process of containerizing 'Shiny' apps, + ensuring reproducibility and consistency across different environments. + Additionally, it facilitates the setup of CI/CD pipelines for building Docker images + on both GitLab and GitHub. + date_publication: '2025-02-09' + bug_reports: https://github.com/VincentGuyader/shiny2docker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shiny2docker + url_git: https://github.com/VincentGuyader/shiny2docker +shinyAce: + version: 0.4.4 + title: Ace Editor Bindings for Shiny + maintainer: Vincent Nijs + description: |- + Ace editor bindings to enable a rich text editing environment + within Shiny. + date_publication: '2025-02-03' + bug_reports: https://github.com/trestletech/shinyAce/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyAce + url_git: '' +shinyaframe: + version: 1.0.1 + title: |- + 'WebVR' Data Visualizations with 'RStudio Shiny' and 'Mozilla + A-Frame' + maintainer: William Murphy + description: |- + Make R data available in Web-based virtual reality experiences + for immersive, cross-platform data visualizations. Includes the 'gg-aframe' + JavaScript package for a Grammar of Graphics declarative HTML syntax to create + 3-dimensional data visualizations with 'Mozilla A-Frame' . + date_publication: '2017-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyaframe + url_git: '' +shinyalert: + version: 3.1.0 + title: Easily Create Pretty Popup Messages (Modals) in 'Shiny' + maintainer: Dean Attali + description: |- + Easily create pretty popup messages (modals) in 'Shiny'. A modal can + contain text, images, OK/Cancel buttons, an input to get a response from the + user, and many more customizable options. + date_publication: '2024-04-27' + bug_reports: https://github.com/daattali/shinyalert/issues + url: https://daattali.com/shiny/shinyalert-demo/ + url_cran: https://CRAN.R-project.org/package=shinyalert + url_git: https://github.com/daattali/shinyalert +shinyanimate: + version: 0.4.0 + title: Animation for 'shiny' Elements + maintainer: Swechhya Bista + description: An extension of 'animate.css' that allows user to easily add animations + to any UI element in 'shiny' app using the elements id. + date_publication: '2023-10-30' + bug_reports: https://github.com/Swechhya/shinyanimate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyanimate + url_git: https://github.com/Swechhya/shinyanimate +shinyauthr: + version: 1.0.0 + title: '''Shiny'' Authentication Modules' + maintainer: Paul Campbell + description: |- + Add in-app user authentication to 'shiny', + allowing you to secure publicly hosted apps and + build dynamic user interfaces from user information. + date_publication: '2021-07-20' + bug_reports: https://github.com/paulc91/shinyauthr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyauthr + url_git: https://github.com/paulc91/shinyauthr +shinybody: + version: 0.1.3 + title: An Interactive Anatomography Widget for 'shiny' + maintainer: Robert Norberg + description: |- + An 'htmlwidget' of the human body that allows you + to hide/show and assign colors to 79 different body parts. The 'human' + widget is an 'htmlwidget', so it works in Quarto documents, + R Markdown documents, or any other HTML medium. + It also functions as an input/output widget in a 'shiny' app. + date_publication: '2025-01-08' + bug_reports: https://github.com/robert-norberg/shinybody/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinybody + url_git: https://github.com/robert-norberg/shinybody +shinybrms: + version: 1.8.0 + title: Graphical User Interface ('shiny' App) for 'brms' + maintainer: Frank Weber + description: |- + A graphical user interface (GUI) for fitting Bayesian regression + models using the package 'brms' which in turn relies on 'Stan' + (). The 'shinybrms' GUI is a 'shiny' app. + date_publication: '2022-08-05' + bug_reports: https://github.com/fweber144/shinybrms/issues + url: https://fweber144.github.io/shinybrms/ + url_cran: https://CRAN.R-project.org/package=shinybrms + url_git: '' +shinybrowser: + version: 1.0.0 + title: Find Out Information About a User's Web Browser in 'Shiny' + maintainer: Dean Attali + description: |- + Sometimes it's useful to know some information about your user in a 'Shiny' app. The available + information is: browser name (such as 'Chrome' or 'Safari') and version, device type + (mobile or desktop), operating system (such as 'Windows' or 'Mac' or 'Android') and version, + and browser dimensions. + date_publication: '2022-05-18' + bug_reports: https://github.com/daattali/shinybrowser/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinybrowser + url_git: https://github.com/daattali/shinybrowserhttps://daattali.com/shiny/shinybrowser-demo/ +shinyBS: + version: 0.61.1 + title: Twitter Bootstrap Components for Shiny + maintainer: Eric Bailey + description: Adds additional Twitter Bootstrap components to Shiny. + date_publication: '2022-04-17' + bug_reports: https://github.com/ebailey78/shinyBS/issues + url: https://ebailey78.github.io/shinyBS + url_cran: https://CRAN.R-project.org/package=shinyBS + url_git: '' +shinybusy: + version: 0.3.3 + title: Busy Indicators and Notifications for 'Shiny' Applications + maintainer: Victor Perrier + description: |- + Add indicators (spinner, progress bar, gif) in your 'shiny' + applications to show the user that the server is busy. And other tools to let + your users know something is happening (send notifications, reports, ...). + date_publication: '2024-03-09' + bug_reports: https://github.com/dreamRs/shinybusy/issues + url: https://dreamrs.github.io/shinybusy/ + url_cran: https://CRAN.R-project.org/package=shinybusy + url_git: https://github.com/dreamRs/shinybusy +shinyChakraSlider: + version: 0.1.0 + title: Combined Slider and Numeric Input for 'Shiny' + maintainer: Stéphane Laurent + description: 'Provides a combined slider and numeric input for usage in a ''Shiny'' + app. The slider and the numeric input are linked together: each one is updated + when the other one changes. Many styling properties are customizable (e.g. colors + and size).' + date_publication: '2020-08-31' + bug_reports: https://github.com/stla/shinyChakraSlider/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyChakraSlider + url_git: https://github.com/stla/shinyChakraSlider +shinyChakraUI: + version: 1.1.1 + title: A Wrapper of the 'React' Library 'Chakra UI' for 'Shiny' + maintainer: Stéphane Laurent + description: Makes the 'React' library 'Chakra UI' usable in 'Shiny' apps. 'Chakra + UI' components include alert dialogs, drawers (sliding panels), menus, modals, + popovers, sliders, and more. + date_publication: '2022-01-05' + bug_reports: https://github.com/stla/shinyChakraUI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyChakraUI + url_git: https://github.com/stla/shinyChakraUI +shinychat: + version: 0.1.1 + title: Chat UI Component for 'shiny' + maintainer: Joe Cheng + description: |- + Provides a scrolling chat interface with multiline input, suitable + for creating chatbot apps based on Large Language Models (LLMs). Designed to + work particularly well with the 'elmer' R package for calling LLMs. + date_publication: '2024-12-18' + bug_reports: https://github.com/jcheng5/shinychat/issues + url: https://jcheng5.github.io/shinychat/ + url_cran: https://CRAN.R-project.org/package=shinychat + url_git: https://github.com/jcheng5/shinychat +shinyChatR: + version: 1.2.0 + title: R Shiny Chat Module + maintainer: Julian Schmocker + description: |- + Provides an easy-to-use module for adding a chat to a Shiny app. Allows + users to send messages and view messages from other users. + Messages can be stored in a database or a .rds file. + date_publication: '2024-05-25' + bug_reports: '' + url: https://julianschmocker.github.io/shinyChatR/ + url_cran: https://CRAN.R-project.org/package=shinyChatR + url_git: https://github.com/julianschmocker/shinyChatR +shinyCLT: + version: 0.9.4 + title: Central Limit Theorem 'shiny' Application + maintainer: Dominique-Laurent Couturier + description: A 'shiny' application estimating the operating characteristics of the + Student's t-test by Student (1908) , Welch's t-test + by Welch (1947) , and Wilcoxon test by Wilcoxon + (1945) in one-sample or two-sample cases, in settings defined + by the user (conditional distribution, sample size per group, location parameter + per group, nuisance parameter per group), using Monte Carlo simulations Malvin + H. Kalos, Paula A. Whitlock (2008) . + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyCLT + url_git: '' +shinyCohortBuilder: + version: 0.3.1 + title: Modular Cohort-Building Framework for Analytical Dashboards + maintainer: Krystian Igras + description: |- + You can easily add advanced cohort-building component + to your analytical dashboard or simple 'Shiny' app. + Then you can instantly start building cohorts using multiple + filters of different types, filtering datasets, and filtering steps. + Filters can be complex and data-specific, and together + with multiple filtering steps you can use complex filtering rules. + The cohort-building sidebar panel allows you to easily + work with filters, add and remove filtering steps. + It helps you with handling missing values during filtering, + and provides instant filtering feedback with filter feedback plots. + The GUI panel is not only compatible with native shiny + bookmarking, but also provides reproducible R code. + date_publication: '2024-10-14' + bug_reports: https://github.com/r-world-devs/shinyCohortBuilder/issues + url: https://r-world-devs.github.io/shinyCohortBuilder/ + url_cran: https://CRAN.R-project.org/package=shinyCohortBuilder + url_git: https://github.com/r-world-devs/shinyCohortBuilder +shinyCox: + version: 1.1.3 + title: Create 'shiny' Applications for Cox Proportional Hazards Models + maintainer: Harrison Clement + description: |- + Takes one or more fitted Cox proportional hazards models and writes + a 'shiny' application to a directory specified by the user. The 'shiny' + application displays predicted survival curves based on user input, and + contains none of the original data used to create the Cox model or models. + The goal is towards visualization and presentation of predicted survival + curves. + date_publication: '2025-02-01' + bug_reports: https://github.com/harryc598/shinyCox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyCox + url_git: https://github.com/harryc598/shinyCox +shinycroneditor: + version: 1.0.0 + title: '''shiny'' Cron Expression Input Widget' + maintainer: Harmen van der Veer + description: A widget for 'shiny' apps to handle schedule expression input, using + the 'cron-expression-input' JavaScript component. Note that this does not edit + the 'crontab' file, it is just an input element for the schedules. See + for an example implementation. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinycroneditor + url_git: '' +shinycssloaders: + version: 1.1.0 + title: |- + Add Loading Animations to a 'shiny' Output While It's + Recalculating + maintainer: Dean Attali + description: |- + When a 'Shiny' output (such as a plot, table, map, etc.) is recalculating, it remains + visible but gets greyed out. Using 'shinycssloaders', you can add a loading animation ("spinner") + to outputs instead. By wrapping a 'Shiny' output in 'withSpinner()', a spinner will automatically + appear while the output is recalculating. You can also manually show and hide the spinner, or add + a full-page spinner to cover the entire page. + See the demo online at . + date_publication: '2024-07-30' + bug_reports: https://github.com/daattali/shinycssloaders/issues + url: https://daattali.com/shiny/shinycssloaders-demo/ + url_cran: https://CRAN.R-project.org/package=shinycssloaders + url_git: https://github.com/daattali/shinycssloaders +shinycustomloader: + version: 0.9.0 + title: Custom Loader for Shiny Outputs + maintainer: Emi Tanaka + description: A custom css/html or gif/image file for the loading screen in R 'shiny'. + It also can use the marquee to have custom text loading screen. + date_publication: '2018-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinycustomloader + url_git: '' +shinyCyJS: + version: 1.0.0 + title: Create Interactive Network Visualizations in R and 'shiny' + maintainer: Jinhwan Kim + description: |- + Create Interactive Graph (Network) Visualizations. + 'shinyCyJS' can be used in 'Shiny' apps or viewed from 'Rstudio' Viewer. + 'shinyCyJS' includes API to build Graph model like node or edge with customized attributes for R. + 'shinyCyJS' is built with 'cytoscape.js' and 'htmlwidgets' R package. + date_publication: '2023-09-26' + bug_reports: https://github.com/jhk0530/shinyCyJS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyCyJS + url_git: https://github.com/jhk0530/shinyCyJS +shinydashboard: + version: 0.7.2 + title: Create Dashboards with 'Shiny' + maintainer: Winston Chang + description: |- + Create dashboards with 'Shiny'. This package provides + a theme on top of 'Shiny', making it easy to create attractive dashboards. + date_publication: '2021-09-30' + bug_reports: https://github.com/rstudio/shinydashboard + url: http://rstudio.github.io/shinydashboard/ + url_cran: https://CRAN.R-project.org/package=shinydashboard + url_git: '' +shinydashboardPlus: + version: 2.0.5 + title: Add More 'AdminLTE2' Components to 'shinydashboard' + maintainer: David Granjon + description: |- + Extend 'shinydashboard' with 'AdminLTE2' components. + 'AdminLTE2' is a free 'Bootstrap 3' dashboard template available + at . Customize boxes, add timelines and a lot more. + date_publication: '2024-08-18' + bug_reports: https://github.com/RinteRface/shinydashboardPlus/issues + url: https://shinydashboardPlus.rinterface.com/ + url_cran: https://CRAN.R-project.org/package=shinydashboardPlus + url_git: https://github.com/RinteRface/shinydashboardPlus +shinyDatetimePickers: + version: 1.2.0 + title: Some Datetime Pickers for 'Shiny' + maintainer: Stéphane Laurent + description: |- + Provides three types of datetime pickers for usage in a + 'Shiny' UI. A datetime picker is an input field for selecting both a + date and a time. + date_publication: '2024-04-23' + bug_reports: https://github.com/stla/shinyDatetimePickers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyDatetimePickers + url_git: https://github.com/stla/shinyDatetimePickers +shinydbauth: + version: 1.0.0.1 + title: Simple Authentification for 'shiny' Applications + maintainer: Diego Florio + description: |- + Provides a simple authentification mechanism for single 'shiny' applications. + Authentification and password change functionality are performed calling user provided functions that typically access some database backend. + Source code of main applications is protected until authentication is successful. + date_publication: '2023-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinydbauth + url_git: https://github.com/diegoefe/shinydbauth +shinydisconnect: + version: 0.1.1 + title: Show a Nice Message When a 'Shiny' App Disconnects or Errors + maintainer: Dean Attali + description: |- + A 'Shiny' app can disconnect for a variety of reasons: an unrecoverable error occurred in + the app, the server went down, the user lost internet connection, or any other reason + that might cause the 'Shiny' app to lose connection to its server. With 'shinydisconnect', you can + call disonnectMessage() anywhere in a Shiny app's UI to add a nice message when this happens. + Works locally (running Shiny apps within 'RStudio') and on Shiny servers (such as shinyapps.io, + 'RStudio Connect', 'Shiny Server Open Source', 'Shiny Server Pro'). See demo online at + . + date_publication: '2023-08-21' + bug_reports: https://github.com/daattali/shinydisconnect/issues + url: https://daattali.com/shiny/shinydisconnect-demo/ + url_cran: https://CRAN.R-project.org/package=shinydisconnect + url_git: https://github.com/daattali/shinydisconnect +shinydlplot: + version: 0.1.4 + title: Add a Download Button to a 'shiny' Plot or 'plotly' + maintainer: Alex Pickering + description: |- + Add a download button to a 'shiny' plot or 'plotly' that appears when + the plot is hovered. A tooltip, styled to resemble 'plotly' buttons, is displayed + on hover of the download button. The download button can be used to allow users + to download the dataset used for a plot. + date_publication: '2022-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinydlplot + url_git: '' +shinyDND: + version: 0.1.0 + title: Shiny Drag-n-Drop + maintainer: Aaron Hoffer + description: Add functionality to create drag and drop div elements in shiny. + date_publication: '2016-06-23' + bug_reports: https://github.com/ayayron/shinydnd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyDND + url_git: https://github.com/ayayron/shinydnd +shinydrive: + version: 0.1.3 + title: File Sharing Shiny Module + maintainer: Benoit Thieurmel + description: |- + Shiny module for easily sharing files between users. Admin can add, remove, edit and download file. + User can only download file. It's also possible to manage files using R functions directly. + date_publication: '2022-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinydrive + url_git: '' +shinyEffects: + version: 0.2.0 + title: Customize Your Web Apps with Fancy Effects + maintainer: David Granjon + description: |- + Add fancy CSS effects to your 'shinydashboards' or 'shiny' apps. + 100% compatible with 'shinydashboardPlus' and 'bs4Dash'. + date_publication: '2021-05-14' + bug_reports: https://github.com/RinteRface/shinyEffects/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyEffects + url_git: https://github.com/RinteRface/shinyEffects +shinyExprPortal: + version: 1.2.1 + title: |- + A Configurable 'shiny' Portal for Sharing Analysis of Molecular + Expression Data + maintainer: Rafael Henkin + description: Enables deploying configuration file-based 'shiny' apps with minimal + programming for interactive exploration and analysis showcase of molecular expression + data. For exploration, supports visualization of correlations between rows of + an expression matrix and a table of observations, such as clinical measures, and + comparison of changes in expression over time. For showcase, enables visualizing + the results of differential expression from package such as 'limma', co-expression + modules from 'WGCNA' and lower dimensional projections. + date_publication: '2024-07-29' + bug_reports: https://github.com/C4TB/shinyExprPortal/issues + url: https://c4tb.github.io/shinyExprPortal/ + url_cran: https://CRAN.R-project.org/package=shinyExprPortal + url_git: https://github.com/C4TB/shinyExprPortal +shinyFeedback: + version: 0.4.0 + title: Display User Feedback in Shiny Apps + maintainer: Andy Merlino + description: Easily display user feedback in Shiny apps. + date_publication: '2021-09-23' + bug_reports: https://github.com/merlinoa/shinyFeedback/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyFeedback + url_git: https://github.com/merlinoa/shinyFeedback +shinyFiles: + version: 0.9.3 + title: A Server-Side File System Viewer for Shiny + maintainer: Thomas Lin Pedersen + description: |- + Provides functionality for client-side navigation of + the server side file system in shiny apps. In case the app is running + locally this gives the user direct access to the file system without the + need to "download" files to a temporary location. Both file and folder + selection as well as file saving is available. + date_publication: '2022-08-19' + bug_reports: https://github.com/thomasp85/shinyFiles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyFiles + url_git: https://github.com/thomasp85/shinyFiles +shinyfilter: + version: 0.1.1 + title: Use Interdependent Filters on Table Columns in Shiny Apps + maintainer: Joachim Zuckarelli + description: |- + Allows to connect 'selectizeInputs' widgets as filters to a 'reactable' table. + As known from spreadsheet applications, column filters are interdependent, so each + filter only shows the values that are really available at the moment based on + the current selection in other filters. Filter values currently not available + (and also those being available) can be shown via popovers or tooltips. + date_publication: '2021-05-10' + bug_reports: https://github.com/jsugarelli/shinyfilter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyfilter + url_git: https://github.com/jsugarelli/shinyfilter/ +shinyfullscreen: + version: 1.1.0 + title: Display 'HTML' Elements on Full Screen in 'Shiny' Apps + maintainer: Etienne Bacher + description: |- + In 'Shiny' apps, it is sometimes useful to see a plot or a + table in full screen. Using 'Shinyfullscreen', you can easily designate + the 'HTML' elements that can be displayed on fullscreen and use buttons to + trigger the fullscreen view. + date_publication: '2021-01-11' + bug_reports: https://github.com/etiennebacher/shinyfullscreen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyfullscreen + url_git: https://github.com/etiennebacher/shinyfullscreen +shinyGizmo: + version: 0.4.2 + title: Custom Components for Shiny Applications + maintainer: Krystian Igras + description: |- + Provides useful UI components and input widgets for 'Shiny' + applications. The offered components allow to apply non-standard + operations and view to your 'Shiny' application, but also help to + overcome common performance issues. + date_publication: '2023-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyGizmo + url_git: '' +shinyglide: + version: 0.1.4 + title: Glide Component for Shiny Applications + maintainer: Julien Barnier + description: |- + Insert Glide JavaScript component into Shiny applications for + carousel or assistant-like user interfaces. + date_publication: '2023-02-15' + bug_reports: https://github.com/juba/shinyglide/issues + url: https://juba.github.io/shinyglide/ + url_cran: https://CRAN.R-project.org/package=shinyglide + url_git: https://github.com/juba/shinyglide +shinyGovstyle: + version: 0.1.0 + title: Custom Gov Style Inputs for Shiny + maintainer: Ross Wyatt + description: |- + Collection of 'shiny' application styling that are the based + on the GOV.UK Design System. See + for details. + date_publication: '2024-09-12' + bug_reports: https://github.com/moj-analytical-services/shinyGovstyle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyGovstyle + url_git: https://github.com/moj-analytical-services/shinyGovstyle +shinyHeatmaply: + version: 0.2.0 + title: Deploy 'heatmaply' using 'shiny' + maintainer: Jonathan Sidi + description: Access functionality of the 'heatmaply' package through 'Shiny UI'. + date_publication: '2020-04-06' + bug_reports: https://github.com/yonicd/shinyHeatmaply/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyHeatmaply + url_git: https://github.com/yonicd/shinyHeatmaply +shinyhelper: + version: 0.3.2 + title: Easily Add Markdown Help Files to 'shiny' App Elements + maintainer: Chris Mason-Thom + description: |- + Creates a lightweight way to add markdown helpfiles to 'shiny' apps, + using modal dialog boxes, with no need to observe each help button separately. + date_publication: '2019-11-09' + bug_reports: https://github.com/cwthom/shinyhelper/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyhelper + url_git: '' +shinyhttr: + version: 1.1.0 + title: Progress Bars for Downloads in 'shiny' Apps + maintainer: Athos Damiani + description: |- + Modifies the progress() function from 'httr' package to let it + send output to progressBar() function from 'shinyWidgets' package. + It is just a tweak at the original functions from 'httr' package to + make it smooth for 'shiny' developers. + date_publication: '2020-07-16' + bug_reports: https://github.com/curso-r/shinyhttr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyhttr + url_git: https://github.com/curso-r/shinyhttr +shinyHugePlot: + version: 0.3.0 + title: Efficient Plotting of Large-Sized Data + maintainer: Junta Tagusari + description: |- + A tool to plot data with a large sample size using 'shiny' and 'plotly'. + Relatively small samples are obtained from the original data using a specific algorithm. + The samples are updated according to a user-defined x range. + Jonas Van Der Donckt, Jeroen Van Der Donckt, Emiel Deprost (2022) . + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyHugePlot + url_git: '' +shinyInvoice: + version: 0.0.5 + title: Shiny App - Generate a Pdf Invoice with 'Rmarkdown' + maintainer: Fernando Roa + description: |- + Generate an invoice containing a header with invoice number and businesses details. The invoice table contains + any of: salary, one-liner costs, grouped costs. Under the table signature and bank account details appear. + Pages are numbered when more than one. Source .json and .Rmd files are editable in the app. A .csv file with raw data can be downloaded. + This package includes functions for getting exchange rates between currencies based on + 'quantmod' (Ryan and Ulrich, 2023 ). + date_publication: '2024-04-01' + bug_reports: https://github.com/fernandoroa/invoice-public/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyInvoice + url_git: https://github.com/fernandoroa/invoice-public +shinyIRT: + version: '0.1' + title: Item Response Theory Analysis with a 'shiny' Application + maintainer: Huseyin Yildiz + description: Performing Item Response Theory analysis such as parameter estimation, + ability estimation, item and model fit analyse, local independence assumption, + dimensionality assumption, characteristic and information curves under various + models with a user friendly 'shiny' interface. + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyIRT + url_git: '' +ShinyItemAnalysis: + version: 1.5.4 + title: Test and Item Analysis via Shiny + maintainer: Patricia Martinkova + description: |- + Package including functions and interactive shiny application + for the psychometric analysis of educational tests, psychological + assessments, health-related and other types of multi-item + measurements, or ratings from multiple raters. + date_publication: '2025-02-08' + bug_reports: https://github.com/patriciamar/ShinyItemAnalysis/issues + url: https://www.ShinyItemAnalysis.org + url_cran: https://CRAN.R-project.org/package=ShinyItemAnalysis + url_git: '' +shinyjqui: + version: 0.4.1 + title: '''jQuery UI'' Interactions and Effects for Shiny' + maintainer: Yang Tang + description: |- + An extension to shiny that brings interactions and animation effects from + 'jQuery UI' library. + date_publication: '2022-02-03' + bug_reports: https://github.com/yang-tang/shinyjqui/issues + url: https://yang-tang.github.io/shinyjqui/ + url_cran: https://CRAN.R-project.org/package=shinyjqui + url_git: https://github.com/yang-tang/shinyjqui +shinyjs: + version: 2.1.0 + title: Easily Improve the User Experience of Your Shiny Apps in Seconds + maintainer: Dean Attali + description: |- + Perform common useful JavaScript operations in Shiny apps that will + greatly improve your apps without having to know any JavaScript. Examples + include: hiding an element, disabling an input, resetting an input back to + its original value, delaying code execution by a few seconds, and many more + useful functions for both the end user and the developer. 'shinyjs' can also + be used to easily call your own custom JavaScript functions from R. + date_publication: '2021-12-23' + bug_reports: https://github.com/daattali/shinyjs/issues + url: https://deanattali.com/shinyjs/ + url_cran: https://CRAN.R-project.org/package=shinyjs + url_git: '' +shinykanban: + version: 0.0.1 + title: Create Kanban Board in Shiny Applications + maintainer: Ugur Dar + description: |- + Provides an interactive Kanban board widget for 'shiny' applications. + It allows users to manage tasks using a drag-and-drop interface and offers customizable styling options. + 'shinykanban' is ideal for project management, task tracking, and agile workflows within 'shiny' apps. + date_publication: '2025-02-03' + bug_reports: https://github.com/ugurdar/shinykanban/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinykanban + url_git: https://github.com/ugurdar/shinykanban +shinyKGode: + version: 1.0.5 + title: |- + An Interactive Application for ODE Parameter Inference Using + Gradient Matching + maintainer: Joe Wandy + description: |- + An interactive Shiny application to perform fast parameter inference on + dynamical systems (described by ordinary differential equations) using gradient matching. + Please see the project page for more details. + date_publication: '2018-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyKGode + url_git: https://github.com/joewandy/shinyKGode +shinyKnobs: + version: 0.1.3 + title: A Collection of Knob Inputs for 'shiny' + maintainer: Patrice Cote + description: A collection of highly configurable, touch-enabled knob input controls + for 'shiny'. These components can be styled to fit in perfectly in any app, and + allow users to set precise values through many input modalities. Users can touch-and-drag, + click-and-drag, scroll their mouse wheel, double click, or use keyboard input. + date_publication: '2020-02-13' + bug_reports: https://github.com/cotepat/shinyKnobs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyKnobs + url_git: https://github.com/cotepat/shinyKnobs +shinylight: + version: '1.2' + title: Web Interface to 'R' Functions + maintainer: Tim Band + description: |- + Web front end for your 'R' functions producing plots or tables. + If you have a function or set of related functions, you can make them + available over the internet through a web browser. This is the same + motivation as the 'shiny' package, but note that the development of + 'shinylight' is not in any way linked to that of 'shiny' (beyond the use of + the 'httpuv' package). You might prefer 'shinylight' to 'shiny' if you want + a lighter weight deployment with easier horizontal scaling, or if you want + to develop your front end yourself in JavaScript and HTML just using + a lightweight remote procedure call interface to your R code on the + server. + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinylight + url_git: '' +ShinyLink: + version: 0.2.2 + title: '''Shiny'' Based Record Linkage Tool' + maintainer: Yaoxiang Li + description: A bridge is created between existing robust open-source record linkage + algorithms and an urgently needed user-friendly platform that removes financial + and technical barriers, setting a new standard for data interoperability in public + health and bioinformatics. The 'fastLink' algorithms are used for matching. Ted + Enamorado et al. (2019) . + date_publication: '2023-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShinyLink + url_git: '' +shinylive: + version: 0.3.0 + title: Run 'shiny' Applications in the Browser + maintainer: Barret Schloerke + description: |- + Exporting 'shiny' applications with 'shinylive' allows you to + run them entirely in a web browser, without the need for a separate R + server. The traditional way of deploying 'shiny' applications involves + in a separate server and client: the server runs R and 'shiny', and + clients connect via the web browser. When an application is deployed + with 'shinylive', R and 'shiny' run in the web browser (via 'webR'): + the browser is effectively both the client and server for the + application. This allows for your 'shiny' application exported by + 'shinylive' to be hosted by a static web server. + date_publication: '2024-11-12' + bug_reports: https://github.com/posit-dev/r-shinylive/issues + url: https://posit-dev.github.io/r-shinylive/ + url_cran: https://CRAN.R-project.org/package=shinylive + url_git: https://github.com/posit-dev/r-shinylive +shinyloadtest: + version: 1.2.0 + title: Load Test Shiny Applications + maintainer: Barret Schloerke + description: |- + Assesses the number of concurrent users 'shiny' + applications are capable of supporting, and for directing application changes + in order to support a higher number of users. Provides facilities for recording + 'shiny' application sessions, playing recorded sessions against a target + server at load, and analyzing the resulting metrics. + date_publication: '2024-07-19' + bug_reports: https://github.com/rstudio/shinyloadtest/issues + url: https://rstudio.github.io/shinyloadtest/ + url_cran: https://CRAN.R-project.org/package=shinyloadtest + url_git: https://github.com/rstudio/shinyloadtest +shinylogs: + version: 0.2.1 + title: Record Everything that Happens in a 'Shiny' Application + maintainer: Victor Perrier + description: |- + Track and record the use of applications and the user's interactions with 'Shiny' inputs. + Allows to trace the inputs with which the user interacts, the outputs generated, + as well as the errors displayed in the interface. + date_publication: '2022-04-18' + bug_reports: https://github.com/dreamRs/shinylogs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinylogs + url_git: https://github.com/dreamRs/shinylogs +shinyLottie: + version: 1.0.0 + title: |- + Seamlessly Integrate 'Lottie' Animations into 'shiny' + Applications + maintainer: Cameron Howitt + description: 'Easily integrate and control ''Lottie'' animations within ''shiny'' + applications'', without the need for idiosyncratic expression or use of ''JavaScript''. + This includes utilities for generating animation instances, controlling playback, + manipulating animation properties, and more. For more information on ''Lottie'', + see: . Additionally, see the official ''Lottie'' + GitHub repository at .' + date_publication: '2024-06-21' + bug_reports: '' + url: https://camhowitt.github.io/shinyLottie/ + url_cran: https://CRAN.R-project.org/package=shinyLottie + url_git: '' +shinyLP: + version: 1.1.3 + title: Bootstrap Landing Home Pages for Shiny Applications + maintainer: Jasmine Daly + description: |- + Provides functions that wrap HTML Bootstrap + components code to enable the design and layout of informative landing home + pages for Shiny applications. This can lead to a better user experience for + the users and writing less HTML for the developer. + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyLP + url_git: https://github.com/jasdumas/shinyLP +shinymanager: + version: 1.0.410 + title: Authentication Management for 'Shiny' Applications + maintainer: Benoit Thieurmel + description: |- + Simple and secure authentification mechanism for single 'Shiny' applications. + Credentials are stored in an encrypted 'SQLite' database. Source code of main application + is protected until authentication is successful. + date_publication: '2022-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinymanager + url_git: https://github.com/datastorm-open/shinymanager +shinymaterial: + version: 1.2.0 + title: Implement Material Design in Shiny Applications + maintainer: Eric Anderson + description: Allows shiny developers to incorporate UI elements based on Google's + Material design. See for more information. + date_publication: '2020-08-31' + bug_reports: '' + url: https://ericrayanderson.github.io/shinymaterial/ + url_cran: https://CRAN.R-project.org/package=shinymaterial + url_git: '' +shinyMatrix: + version: 0.8.0 + title: Shiny Matrix Input Field + maintainer: Andreas Neudecker + description: Implements a custom matrix input field. + date_publication: '2024-04-10' + bug_reports: '' + url: https://inwtlab.github.io/shiny-matrix/ + url_cran: https://CRAN.R-project.org/package=shinyMatrix + url_git: '' +shinyMergely: + version: 0.2.0 + title: Compare and Merge Two Files with a 'Shiny' App + maintainer: Stéphane Laurent + description: A 'Shiny' app allowing to compare and merge two files, with syntax + highlighting for several coding languages. + date_publication: '2022-01-24' + bug_reports: https://github.com/stla/shinyMergely/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyMergely + url_git: https://github.com/stla/shinyMergely +shinymeta: + version: 0.2.0.3 + title: Export Domain Logic from Shiny using Meta-Programming + maintainer: Carson Sievert + description: Provides tools for capturing logic in a Shiny app and exposing it as + code that can be run outside of Shiny (e.g., from an R console). It also provides + tools for bundling both the code and results to the end user. + date_publication: '2021-11-17' + bug_reports: '' + url: https://rstudio.github.io/shinymeta/ + url_cran: https://CRAN.R-project.org/package=shinymeta + url_git: https://github.com/rstudio/shinymeta +shinymgr: + version: 1.1.0 + title: |- + A Framework for Building, Managing, and Stitching 'shiny' + Modules into Reproducible Workflows + maintainer: Laurence Clarfeld + description: |- + A unifying framework for managing and deploying 'shiny' applications + that consist of modules, where an "app" is a tab-based workflow that guides + a user step-by-step through an analysis. The 'shinymgr' app builder + "stitches" 'shiny' modules together so that outputs from one module serve as + inputs to the next, creating an analysis pipeline that is easy to implement + and maintain. Users of 'shinymgr' apps can save analyses as an RDS file that + fully reproduces the analytic steps and can be ingested into an R Markdown + report for rapid reporting. In short, developers use the 'shinymgr' + framework to write modules and seamlessly combine them into 'shiny' apps, and + users of these apps can execute reproducible analyses that can be + incorporated into reports for rapid dissemination. + date_publication: '2024-05-10' + bug_reports: https://code.usgs.gov/vtcfwru/shinymgr/-/issues + url: https://code.usgs.gov/vtcfwru/shinymgr + url_cran: https://CRAN.R-project.org/package=shinymgr + url_git: '' +shinyMixR: + version: 0.5.0 + title: Interactive 'shiny' Dashboard for 'nlmixr2' + maintainer: Richard Hooijmaijers + description: |- + An R shiny user interface for the 'nlmixr2' (Fidler et al (2019) ) package, + designed to simplify the modeling process for users. Additionally, this package includes supplementary functions + to further enhances the usage of 'nlmixr2'. + date_publication: '2024-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyMixR + url_git: '' +shinyML: + version: 1.0.1 + title: Compare Supervised Machine Learning Models Using Shiny App + maintainer: Jean Bertin + description: |- + Implementation of a shiny app to easily compare supervised machine learning model performances. + You provide the data and configure each model parameter directly on the shiny app. + Different supervised learning algorithms can be tested either on Spark or H2O frameworks to suit your regression and classification tasks. + Implementation of available machine learning models on R has been done by Lantz (2013, ISBN:9781782162148). + date_publication: '2021-02-24' + bug_reports: https://github.com/JeanBertinR/shinyML/issues + url: https://jeanbertinr.github.io/shinyMLpackage/ + url_cran: https://CRAN.R-project.org/package=shinyML + url_git: '' +shinyMobile: + version: 2.0.1 + title: Mobile Ready 'shiny' Apps with Standalone Capabilities + maintainer: David Granjon + description: |- + Develop outstanding 'shiny' apps for 'iOS' and 'Android' as well as beautiful 'shiny' gadgets. + 'shinyMobile' is built on top of the latest 'Framework7' template . + Discover 14 new input widgets (sliders, vertical sliders, stepper, + grouped action buttons, toggles, picker, smart select, ...), 2 themes (light and dark), + 12 new widgets (expandable cards, badges, chips, timelines, gauges, progress bars, ...) + combined with the power of server-side notifications such as alerts, modals, toasts, + action sheets, sheets (and more) as well as 3 layouts (single, tabs and split). + date_publication: '2024-10-04' + bug_reports: https://github.com/RinteRface/shinyMobile/issues + url: https://rinterface.github.io/shinyMobile/ + url_cran: https://CRAN.R-project.org/package=shinyMobile + url_git: https://github.com/RinteRface/shinyMobile +shinymodels: + version: 0.1.1 + title: Interactive Assessments of Models + maintainer: Simon Couch + description: |- + Launch a 'shiny' application for 'tidymodels' results. For + classification or regression models, the app can be used to determine + if there is lack of fit or poorly predicted points. + date_publication: '2024-01-31' + bug_reports: https://github.com/tidymodels/shinymodels/issues + url: https://shinymodels.tidymodels.org + url_cran: https://CRAN.R-project.org/package=shinymodels + url_git: https://github.com/tidymodels/shinymodels +shinyMolBio: + version: '0.2' + title: Molecular Biology Visualization Tools for 'Shiny' Apps + maintainer: Konstantin A. Blagodatskikh + description: |- + Interactive visualization of 'RDML' files via 'shiny' apps. + Package provides (1) PCR plate interface with ability to select + individual tubes and (2) amplification/melting plots with fast hiding and + highlighting individual curves. + date_publication: '2019-08-02' + bug_reports: '' + url: https://kablag.github.io/shinyMolBio/ + url_cran: https://CRAN.R-project.org/package=shinyMolBio + url_git: https://github.com/kablag/shinyMolBio +shinyMonacoEditor: + version: 1.1.0 + title: The 'Monaco' Editor in 'Shiny' + maintainer: Stéphane Laurent + description: A 'Shiny' app including the 'Monaco' editor. The 'Monaco' editor is + the code editor which powers 'VS Code'. It is particularly well developed for + 'JavaScript'. In addition to the 'Monaco' editor features, the app provides prettifiers + and minifiers for multiple languages, 'SCSS' and 'TypeScript' compilers, code + checking for 'C' and 'C++' (requires 'cppcheck'). + date_publication: '2020-10-14' + bug_reports: https://github.com/stla/shinyMonacoEditor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyMonacoEditor + url_git: https://github.com/stla/shinyMonacoEditor +shinyNORRRM: + version: 0.8.6 + title: The Ultimate Igneous Norm + maintainer: Reneé González-Guzmán + description: The computer program is an efficient igneous norm algorithm and rock + classification system written in R but run as shiny app. + date_publication: '2022-06-23' + bug_reports: https://github.com/TheRFrog/shinyNORRRM/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=shinyNORRRM + url_git: https://github.com/TheRFrog/shinyNORRRM +shinyNotes: + version: 0.0.2 + title: Shiny Module for Taking Free-Form Notes + maintainer: Daniel Kovtun + description: |- + An enterprise-targeted scalable and customizable 'shiny' module providing an easy way to incorporate free-form note taking or discussion boards into applications. + The package includes a 'shiny' module that can be included in any 'shiny' application to create a panel containing searchable, editable text broken down by section headers. + Can be used with a local 'SQLite' database, or a compatible remote database of choice. + date_publication: '2023-02-19' + bug_reports: https://github.com/danielkovtun/shinyNotes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyNotes + url_git: https://github.com/danielkovtun/shinyNotes +shinyobjects: + version: 0.2.0 + title: Access Reactive Data Interactively + maintainer: Jake Riley + description: Troubleshooting reactive data in 'shiny' can be difficult. These functions + will convert reactive data frames into functions and load all assigned objects + into your local environment. If you create a dummy input object, as the function + will suggest, you will be able to test your server and ui functions interactively. + date_publication: '2020-07-29' + bug_reports: https://github.com/rjake/shinyobjects/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyobjects + url_git: '' +shinypanel: + version: 0.1.5 + title: Shiny Control Panel + maintainer: Alex Pickering + description: |- + Add shiny inputs with one or more inline buttons that grow and shrink with inputs. + Also add tool tips to input buttons and styling and messages for input validation. + date_publication: '2022-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinypanel + url_git: '' +shinypanels: + version: 0.5.0 + title: Shiny Layout with Collapsible Panels + maintainer: Juan Pablo Marin Diaz + description: |- + Create 'Shiny Apps' with collapsible vertical panels. + This package provides a new visual arrangement for elements on top of 'Shiny'. + Use the expand and collapse capabilities to leverage web applications with + many elements to focus the user attention on the panel of interest. + date_publication: '2020-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinypanels + url_git: http://github.com/datasketch/shinypanels +shinypivottabler: + version: '1.2' + title: Shiny Module to Create Pivot Tables + maintainer: Benoit Thieurmel + description: Shiny Module to create, visualize, customize and export Excel-like + pivot table. + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinypivottabler + url_git: '' +shinyPredict: + version: 0.1.1 + title: Predictions using Shiny + maintainer: Jari Haukka + description: Creates 'shiny' application ('app.R') for making predictions based + on lm(), glm(), or coxph() models. + date_publication: '2021-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyPredict + url_git: '' +shinyQueryBuilder: + version: 0.1.0 + title: Construct Complex Filtering Queries in 'Shiny' + maintainer: Krystian Igras + description: |- + Input widget that allows to construct complex filtering queries in 'Shiny'. + It's a wrapper for 'JavaScript' library 'jQuery-QueryBuilder', check . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyQueryBuilder + url_git: '' +ShinyQuickStarter: + version: 2.0.1 + title: '''RStudio'' Addin for Building Shiny Apps per Drag & Drop' + maintainer: Leon Binder + description: This 'RStudio' addin makes the creation of 'Shiny' and 'ShinyDashboard' + apps more efficient. Besides the necessary folder structure, entire apps can + be created using a drag and drop interface and customized with respect to a specific + use case. The addin allows the export of the required user interface and server + code at any time. By allowing the creation of modules, the addin can be used throughout + the entire app development process. + date_publication: '2021-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShinyQuickStarter + url_git: '' +shinyquiz: + version: 0.0.1 + title: Create Interactive Quizzes in 'shiny' + maintainer: Joseph Marlo + description: Simple and flexible quizzes in 'shiny'. Easily create quizzes from + various pre-built question and choice types or create your own using 'htmltools' + and 'shiny' packages as building blocks. Integrates with larger 'shiny' applications. + Ideal for non-web-developers such as educators, data scientists, and anyone who + wants to assess responses interactively in a small form factor. + date_publication: '2023-12-12' + bug_reports: https://github.com/priism-center/shinyquiz/issues + url: https://priism-center.github.io/shinyquiz/ + url_cran: https://CRAN.R-project.org/package=shinyquiz + url_git: https://github.com/priism-center/shinyquiz +shinyr: + version: 0.4.2 + title: Data Insights Through Inbuilt R Shiny App + maintainer: Jayachandra N + description: It builds dynamic R shiny based dashboards to analyze any CSV files. + It provides simple dashboard design to subset the data, perform exploratory data + analysis and preliminary machine learning (supervised and unsupervised). It also + provides filters based on columns of interest. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyr + url_git: '' +shinyRadioMatrix: + version: 0.2.1 + title: Create a Matrix with Radio Buttons + maintainer: Zsolt Szelepcsényi + description: |- + An input controller for R Shiny: a matrix with radio buttons, + where only one option per row can be selected. + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyRadioMatrix + url_git: '' +shinyRatings: + version: 0.1.0 + title: An Intuitive Way of Providing Star Rating in a 'shiny' App + maintainer: Ronak Shah + description: |- + A simple interface to integrate star ratings into your 'shiny' apps. + It can be used for customer feedback systems, user reviews, or any application that requires user ratings. + 'shinyRatings' offers a straightforward and customisable solution that enhances user engagement and facilitates valuable feedback collection. + date_publication: '2023-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyRatings + url_git: '' +shinyrecipes: + version: 0.1.0 + title: |- + Gadget to Use the Data Preprocessing 'recipes' Package + Interactively + maintainer: Alberto Almuiña + description: |- + This gadget allows you to use the 'recipes' package belonging to 'tidymodels' to carry + out the data preprocessing tasks in an interactive way. Build your 'recipe' by dragging the variables, + visually analyze your data to decide which steps to use, add those steps and preprocess your data. + date_publication: '2020-05-05' + bug_reports: https://github.com/AlbertoAlmuinha/shinyrecipes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyrecipes + url_git: https://github.com/AlbertoAlmuinha/shinyrecipes +shinyreforms: + version: 0.0.1 + title: Add Forms to your 'Shiny' App + maintainer: Piotr Bajger + description: |- + Allows to create modular, reusable 'HTML' + forms which can be embedded in your 'shiny' app with minimal effort. + Features include conditional code execution on form submission, + automatic input validation and input tooltips. + date_publication: '2020-05-12' + bug_reports: https://github.com/piotrbajger/shinyreforms + url: '' + url_cran: https://CRAN.R-project.org/package=shinyreforms + url_git: https://github.com/piotrbajger/shinyreforms +shinyRGL: + version: 0.1.0 + title: Shiny Wrappers for RGL + maintainer: Jeff Allen + description: |- + Shiny wrappers for the RGL package. This package exposes RGL's + ability to export WebGL visualization in a shiny-friendly format. + date_publication: '2013-10-13' + bug_reports: https://github.com/trestletech/shinyRGL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyRGL + url_git: '' +shinySbm: + version: 0.1.5 + title: '''shiny'' Application to Use the Stochastic Block Model' + maintainer: Theodore Vanrenterghem + description: |- + A 'shiny' interface for a simpler use of the 'sbm' R package. + It also contains useful functions to easily explore the 'sbm' package results. + With this package you should be able to use the stochastic block model + without any knowledge in R, get automatic reports and nice visuals, as + well as learning the basic functions of 'sbm'. + date_publication: '2023-09-07' + bug_reports: https://github.com/Jo-Theo/shinySbm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinySbm + url_git: '' +shinyscholar: + version: 0.2.5 + title: A Template for Creating Reproducible 'shiny' Applications + maintainer: Simon E. H. Smart + description: |- + Create a skeleton 'shiny' application with create_template() that is + reproducible, can be saved and meets academic standards for attribution. + Forked from 'wallace'. Code is split into modules that are loaded and linked + together automatically and each call one function. Guidance pages explain + modules to users and flexible logging informs them of any errors. Options + enable asynchronous operations, viewing of source code, interactive maps and + data tables. Use to create complex analytical applications, following best + practices in open science and software development. Includes functions for + automating repetitive development tasks and an example application at + run_shinyscholar() that requires + install.packages("shinyscholar", dependencies = TRUE). A guide to developing + applications can be found on the package website. + date_publication: '2025-02-05' + bug_reports: https://github.com/simon-smart88/shinyscholar/issues + url: https://simon-smart88.github.io/shinyscholar/ + url_cran: https://CRAN.R-project.org/package=shinyscholar + url_git: '' +shinyscreenshot: + version: 0.2.1 + title: Capture Screenshots of Entire Pages or Parts of Pages in 'Shiny' + maintainer: Dean Attali + description: |- + Capture screenshots in 'Shiny' applications. Screenshots can either be + of the entire viewable page, or a specific section of the page. The captured + image is automatically downloaded as a PNG image, or it can also be saved on + the server. Powered by the 'html2canvas' JavaScript library. + date_publication: '2023-08-21' + bug_reports: https://github.com/daattali/shinyscreenshot/issues + url: https://daattali.com/shiny/shinyscreenshot-demo/ + url_cran: https://CRAN.R-project.org/package=shinyscreenshot + url_git: https://github.com/daattali/shinyscreenshot +shinySearchbar: + version: 1.0.0 + title: Shiny Searchbar - An Input Widget for Highlighting Text and More + maintainer: Jesse Norris + description: |- + Add a searchbar widget to your 'Shiny' application. The widget + quickly integrates with any existing element containing text to highlight + matches. Highlighting is done with the 'JavaScript' library 'mark.js'. The + widget includes buttons to cycle through multiple instances of the match and + automatically scroll to the matches in an overflow element (or window). The + widget also displays the total number of matches and which match is currently + being cycled through. The widget is structured as a 'Bootstrap 3' input + group. + date_publication: '2020-06-02' + bug_reports: https://github.com/jes-n/shiny-searchbar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinySearchbar + url_git: https://github.com/jes-n/shiny-searchbar +shinySelect: + version: 1.3.0 + title: A Wrapper of the 'react-select' Library + maintainer: Stéphane Laurent + description: |- + Provides a select control widget for 'Shiny'. It is easily + customizable, and one can easily use HTML in the items and KaTeX to + type mathematics. + date_publication: '2022-11-18' + bug_reports: https://github.com/stla/shinySelect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinySelect + url_git: https://github.com/stla/shinySelect +shinyservicebot: + version: 0.1.0 + title: Servicebot 'Shiny' Integration + maintainer: Bjorn Ole Lindseth + description: Create in-app purchasing and subscriptions through 'Servicebot' payment + using the 'Stripe' framework. + date_publication: '2020-06-30' + bug_reports: https://github.com/capiaas/shinyservicebot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyservicebot + url_git: https://github.com/capiaas/shinyservicebot +shinyShortcut: + version: 0.1.0 + title: Creates an Executable Shortcut for Shiny Applications + maintainer: Ewan Keith + description: |- + Provides function shinyShortcut() that, + when given the base directory of a shiny application, will produce an + executable file that runs the shiny app directly in the user's + default browser. Tested on both windows and unix machines. Inspired + by and borrowing from + . + date_publication: '2017-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyShortcut + url_git: '' +shinySIR: + version: 0.1.2 + title: |- + Interactive Plotting for Mathematical Models of Infectious + Disease Spread + maintainer: Sinead E. Morris + description: Provides interactive plotting for mathematical models of infectious + disease spread. Users can choose from a variety of common built-in ordinary differential + equation (ODE) models (such as the SIR, SIRS, and SIS models), or create their + own. This latter flexibility allows 'shinySIR' to be applied to simple ODEs from + any discipline. The package is a useful teaching tool as students can visualize + how changing different parameters can impact model dynamics, with minimal knowledge + of coding in R. The built-in models are inspired by those featured in Keeling + and Rohani (2008) and Bjornstad (2018) . + date_publication: '2020-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinySIR + url_git: '' +shinystan: + version: 2.6.0 + title: |- + Interactive Visual and Numerical Diagnostics and Posterior + Analysis for Bayesian Models + maintainer: Jonah Gabry + description: |- + A graphical user interface for interactive Markov chain Monte + Carlo (MCMC) diagnostics and plots and tables helpful for analyzing a + posterior sample. The interface is powered by the 'Shiny' web + application framework from 'RStudio' and works with the output of MCMC + programs written in any programming language (and has extended + functionality for 'Stan' models fit using the 'rstan' and 'rstanarm' + packages). + date_publication: '2022-03-03' + bug_reports: https://github.com/stan-dev/shinystan/issues/ + url: https://mc-stan.org/shinystan/ + url_cran: https://CRAN.R-project.org/package=shinystan + url_git: '' +shinyStorePlus: + version: '1.4' + title: |- + Secure in-Browser and Database Storage for 'shiny' Inputs, + Outputs, Views and User Likes + maintainer: Obinna Obianom + description: Store persistent and synchronized data from 'shiny' inputs within the + browser. Refresh 'shiny' applications and preserve user-inputs over multiple sessions. + A database-like storage format is implemented using 'Dexie.js' , + a minimal wrapper for 'IndexedDB'. Transfer browser link parameters to 'shiny' + input or output values. Store app visitor views, likes and followers. + date_publication: '2025-01-14' + bug_reports: https://github.com/oobianom/shinyStorePlus/issues + url: https://shinystoreplus.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=shinyStorePlus + url_git: '' +shinysurveys: + version: 0.2.0 + title: Create and Deploy Surveys in 'Shiny' + maintainer: Jonathan Trattner + description: |- + Easily create and deploy surveys in 'Shiny'. This package includes + a minimalistic framework similar to 'Google Forms' that allows for url-based + user tracking, customizable submit actions, easy survey-theming, and more. + date_publication: '2021-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinysurveys + url_git: '' +shinyTempSignal: + version: 0.0.8 + title: Explore Temporal and Other Phylogenetic Signals + maintainer: Guangchuang Yu + description: Sequences sampled at different time points can be used to infer molecular + phylogenies on natural time scales, but if the sequences records inaccurate sampling + times, that are not the actual sampling times, then it will affect the molecular + phylogenetic analysis. This shiny application helps exploring temporal characteristics + of the evolutionary trees through linear regression analysis and with the ability + to identify and remove incorrect labels. The method was extended to support exploring + other phylogenetic signals under strict and relaxed models. + date_publication: '2024-03-06' + bug_reports: https://github.com/YuLab-SMU/shinyTempSignal/issues + url: https://www.sciencedirect.com/science/article/pii/S167385272400033X + url_cran: https://CRAN.R-project.org/package=shinyTempSignal + url_git: https://github.com/YuLab-SMU/shinyTempSignal +shinytest: + version: 1.6.1 + title: Test Shiny Apps + maintainer: Winston Chang + description: Please see the 'shinytest' to 'shinytest2' migration guide at . + date_publication: '2024-05-30' + bug_reports: https://github.com/rstudio/shinytest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinytest + url_git: https://github.com/rstudio/shinytest +shinytest2: + version: 0.3.2 + title: Testing for Shiny Applications + maintainer: Barret Schloerke + description: Automated unit testing of Shiny applications through a headless 'Chromium' + browser. + date_publication: '2024-04-28' + bug_reports: https://github.com/rstudio/shinytest2/issues + url: https://rstudio.github.io/shinytest2/ + url_cran: https://CRAN.R-project.org/package=shinytest2 + url_git: https://github.com/rstudio/shinytest2 +ShinyTester: + version: 0.1.0 + title: Functions to Minimize Bonehead Moves While Working with 'shiny' + maintainer: Amit Kohli + description: |- + It's my experience that working with 'shiny' is intuitive once you're + into it, but can be quite daunting at first. Several common mistakes are fairly + predictable, and therefore we can control for these. The functions in this + package help match up the assets listed in the UI and the SERVER files, and + Visualize the ad hoc structure of the 'shiny' App. + date_publication: '2017-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShinyTester + url_git: '' +shinythemes: + version: 1.2.0 + title: Themes for Shiny + maintainer: Winston Chang + description: |- + Themes for use with Shiny. Includes several Bootstrap themes + from , which are packaged for use with Shiny + applications. + date_publication: '2021-01-25' + bug_reports: '' + url: https://rstudio.github.io/shinythemes/ + url_cran: https://CRAN.R-project.org/package=shinythemes + url_git: '' +shinyTime: + version: 1.0.3 + title: A Time Input Widget for Shiny + maintainer: Gerhard Burger + description: |- + Provides a time input widget for Shiny. This widget allows intuitive time input in the + '[hh]:[mm]:[ss]' or '[hh]:[mm]' (24H) format by using a separate numeric input for each time + component. The interface with R uses date-time objects. See the project page for more + information and examples. + date_publication: '2022-08-19' + bug_reports: https://github.com/burgerga/shinyTime/issues + url: https://burgerga.github.io/shinyTime/ + url_cran: https://CRAN.R-project.org/package=shinyTime + url_git: https://github.com/burgerga/shinyTime +shinytitle: + version: 0.1.0 + title: Update Browser Window Title in 'shiny' Session + maintainer: Ashley Baldry + description: Enables the ability to change or flash the title of the browser window + during a 'shiny' session. + date_publication: '2021-06-16' + bug_reports: https://github.com/ashbaldry/shinytitle/issues + url: https://ashbaldry.github.io/shinytitle/ + url_cran: https://CRAN.R-project.org/package=shinytitle + url_git: https://github.com/ashbaldry/shinytitle +shinyToastify: + version: 2.0.0 + title: Pretty Notifications for 'Shiny' + maintainer: Stéphane Laurent + description: This is a wrapper of the 'React' library 'React-Toastify'. It allows + to show some notifications (toasts) in 'Shiny' applications. There are options + for the style, the position, the transition effect, and more. + date_publication: '2021-07-31' + bug_reports: https://github.com/stla/shinyToastify/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyToastify + url_git: https://github.com/stla/shinyToastify +shinytoastr: + version: 2.2.0 + title: Notifications from 'Shiny' + maintainer: Gábor Csárdi + description: |- + Browser notifications in 'Shiny' apps, using + 'toastr': . + date_publication: '2023-08-30' + bug_reports: https://github.com/gaborcsardi/shinytoastr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinytoastr + url_git: https://github.com/gaborcsardi/shinytoastr +shinyTree: + version: 0.3.1 + title: jsTree Bindings for Shiny + maintainer: Michael Bell + description: |- + Exposes bindings to jsTree -- a JavaScript library + that supports interactive trees -- to enable a rich, editable trees in + Shiny. + date_publication: '2023-08-07' + bug_reports: https://github.com/shinyTree/shinyTree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyTree + url_git: '' +shinyvalidate: + version: 0.1.3 + title: Input Validation for Shiny Apps + maintainer: Carson Sievert + description: |- + Improves the user experience of Shiny apps by helping to + provide feedback when required inputs are missing, or input values + are not valid. + date_publication: '2023-10-04' + bug_reports: https://github.com/rstudio/shinyvalidate/issues + url: https://rstudio.github.io/shinyvalidate/ + url_cran: https://CRAN.R-project.org/package=shinyvalidate + url_git: https://github.com/rstudio/shinyvalidate +shinyWGD: + version: 1.0.0 + title: '''Shiny'' Application for Whole Genome Duplication Analysis' + maintainer: Jia Li + description: |- + Provides a comprehensive 'Shiny' application for analyzing + Whole Genome Duplication ('WGD') events. + This package provides a user-friendly 'Shiny' web application for + non-experienced researchers to prepare input data and execute command lines + for several well-known 'WGD' analysis tools, including 'wgd', 'ksrates', + 'i-ADHoRe', 'OrthoFinder', and 'Whale'. This package also provides the source code + for experienced researchers to adjust and install the package to their own server. + Key Features + 1) Input Data Preparation + This package allows users to conveniently upload and format their data, + making it compatible with various 'WGD' analysis tools. + 2) Command Line Generation + This package automatically generates the necessary command lines for + selected 'WGD' analysis tools, reducing manual errors and saving time. + 3) Visualization + This package offers interactive visualizations to explore and interpret 'WGD' results, + facilitating in-depth 'WGD' analysis. + 4) Comparative Genomics + Users can study and compare 'WGD' events across different species, + aiding in evolutionary and comparative genomics studies. + 5) User-Friendly Interface + This 'Shiny' web application provides an intuitive and accessible interface, + making 'WGD' analysis accessible to researchers and 'bioinformaticians' of all levels. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shinyWGD + url_git: '' +shinyWidgets: + version: 0.9.0 + title: Custom Inputs Widgets for Shiny + maintainer: Victor Perrier + description: |- + Collection of custom input controls and user interface components for 'Shiny' applications. + Give your applications a unique and colorful style ! + date_publication: '2025-02-21' + bug_reports: https://github.com/dreamRs/shinyWidgets/issues + url: https://dreamrs.github.io/shinyWidgets/ + url_cran: https://CRAN.R-project.org/package=shinyWidgets + url_git: https://github.com/dreamRs/shinyWidgets +ShinyWizard: + version: 1.1.3.11 + title: |- + An Interactive Wizard to Design, Build, and Deploy R Packages + Demo Presentation + maintainer: Rafal Urniaz + description: Design, build, and deploy R packages demo presentations by an interactive + wizard. Set up unique title, logo and themes. Add personalized tabs exposing applicability. + And deploy as a part of a package or an independent app. + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ShinyWizard + url_git: '' +shinyXYpad: + version: 0.2.0 + title: XY Controller for 'Shiny' + maintainer: Stéphane Laurent + description: Provides an XY pad input for the 'Shiny' framework. An XY pad is like + a bivariate slider. It allows to pick up a pair of numbers. + date_publication: '2022-09-27' + bug_reports: https://github.com/stla/shinyXYpad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shinyXYpad + url_git: https://github.com/stla/shinyXYpad +shipunov: + version: 1.17.1 + title: Miscellaneous Functions from Alexey Shipunov + maintainer: ORPHANED + description: |- + A collection of functions for data manipulation, plotting and statistical computing, + to use separately or with the book "Visual Statistics. Use R!": + Shipunov (2020) . + Dr Alexey Shipunov died in December 2022. + Most useful functions: + Bclust(), Jclust() and BootA() which bootstrap hierarchical clustering; + Recode() which does multiple recoding in a fast, simple and flexible way; + Misclass() which outputs confusion matrix even if classes are not concerted; + Overlap() which measures group separation on any projection; + Biarrows() which converts any scatterplot into biplot; + and Pleiad() which is fast and flexible correlogram. + date_publication: '2023-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shipunov + url_git: '' +shock: + version: '1.0' + title: |- + Slope Heuristic for Block-Diagonal Covariance Selection in High + Dimensional Gaussian Graphical Models + maintainer: Melina Gallopin + description: |- + Block-diagonal covariance selection for high dimensional Gaussian + graphical models. The selection procedure is based on the slope heuristics. + date_publication: '2015-12-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shock + url_git: '' +shopifyadsR: + version: 0.1.0 + title: Get 'Shopify' Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from 'Shopify' Ads + using the 'Windsor.ai' API . + date_publication: '2022-11-02' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=shopifyadsR + url_git: '' +shopifyr: + version: 1.0.0 + title: An R Interface to the Shopify API + maintainer: Charlie Friedemann + description: |- + An interface to the Admin API of the E-commerce service Shopify, + (). + date_publication: '2019-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shopifyr + url_git: https://github.com/charliebone/shopifyr/ +shoredate: + version: 1.1.1 + title: Shoreline Dating Coastal Stone Age Sites + maintainer: Isak Roalkvam + description: |- + Provides tools for shoreline dating coastal Stone Age sites. The + implemented method was developed in Roalkvam (2023) + for the Norwegian Skagerrak coast. + Although it can be extended to other areas, this also forms the core area for + application of the package. Shoreline dating is based on the present-day + elevation of a site, a reconstruction of past relative sea-level change, and + empirically derived estimates of the likely elevation of the sites above the + contemporaneous sea-level when they were in use. The geographical and temporal + coverage of the method thus follows from the availability of local geological + reconstructions of shoreline displacement and the degree to which the + settlements to be dated have been located on or close to the shoreline when + they were in use. Methods for numerical treatment and visualisation of the + dates are provided, along with basic tools for visualising and evaluating the + location of sites. + date_publication: '2023-10-24' + bug_reports: https://github.com/isakro/shoredate/issues + url: https://isakro.github.io/shoredate/ + url_cran: https://CRAN.R-project.org/package=shoredate + url_git: https://github.com/isakro/shoredate +shortcuts: + version: 1.4.0 + title: Useful Shortcuts to Interact with 'RStudio' Scripts + maintainer: José Carlos Del Valle + description: Integrates clipboard copied data in R Studio, loads and installs libraries + within a R script and returns all valid arguments of a selected function. + date_publication: '2019-12-17' + bug_reports: https://github.com/jcval94/shortcuts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shortcuts + url_git: https://github.com/jcval94/shortcuts +ShortForm: + version: 0.5.6 + title: Automatic Short Form Creation + maintainer: Anthony Raborn + description: |- + Performs automatic creation of short forms of scales with an + ant colony optimization algorithm and a Tabu search. As implemented in the + package, the ant colony algorithm randomly selects items to build a model of + a specified length, then updates the probability of item selection according + to the fit of the best model within each set of searches. The algorithm + continues until the same items are selected by multiple ants a given number + of times in a row. On the other hand, the Tabu search changes one parameter at + a time to be either free, constrained, or fixed while keeping track of the + changes made and putting changes that result in worse fit in a "tabu" list + so that the algorithm does not revisit them for some number of searches. + See Leite, Huang, & Marcoulides (2008) for + an applied example of the ant colony algorithm, and Marcoulides & Falk (2018) + for an applied example of the Tabu search. + date_publication: '2024-11-27' + bug_reports: https://github.com/AnthonyRaborn/ShortForm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ShortForm + url_git: https://github.com/AnthonyRaborn/ShortForm +shortIRT: + version: 0.1.3 + title: |- + Procedures Based on Item Response Theory Models for the + Development of Short Test Forms + maintainer: Ottavia M. Epifania + description: |- + Implement different Item Response Theory (IRT) based procedures for the development of static short test forms (STFs) from a test. Two main procedures are considered, specifically the typical IRT-based procedure for the development of STF, and a recently introduced procedure (Epifania, Anselmi & Robusto, 2022 ). + The procedures differ in how the most informative items are selected for the inclusion in the STF, either by considering their item information functions without considering any specific level of the latent trait (typical procedure) or by considering their informativeness with respect to specific levels of the latent trait, denoted as theta targets (the newly introduced procedure). Regarding the latter procedure, three methods are implemented for the definition of the theta targets: (i) theta targets are defined by segmenting the latent trait in equal intervals and considering the midpoint of each interval (equal interval procedure, eip), (ii) by clustering the latent trait to obtain unequal intervals and considering the centroids of the clusters as the theta targets (unequal intervals procedure, uip), and (iii) by letting the user set the specific theta targets of interest (user-defined procedure, udp). + For further details on the procedure, please refer to Epifania, Anselmi & Robusto (2022) . + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shortIRT + url_git: '' +shortr: + version: 1.0.0 + title: |- + Optimal Subset Identification in Undirected Weighted Network + Models + maintainer: Loïs Fournier + description: Identifies what optimal subset of a desired number of items should + be retained in a short version of a psychometric instrument to assess the “broadest” + proportion of the construct-level content of the set of items included in the + original version of the said psychometric instrument. Expects a symmetric adjacency + matrix as input (undirected weighted network model). Supports brute force and + simulated annealing combinatorial search algorithms. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shortr + url_git: https://github.com/lfourni2/shortr +shorts: + version: 3.2.0 + title: Short Sprints + maintainer: Mladen Jovanović + description: |- + Create short sprint acceleration-velocity (AVP) and force-velocity (FVP) profiles + and predict kinematic and kinetic variables using the timing-gate split times, laser or + radar gun data, tether devices data, as well as the data provided by the GPS and LPS + monitoring systems. The modeling method utilized in this package is based on the works of + Furusawa K, Hill AV, Parkinson JL (1927) , + Greene PR. (1986) , + Chelly SM, Denis C. (2001) , + Clark KP, Rieger RH, Bruno RF, Stearne DJ. (2017) , + Samozino P. (2018) , + Samozino P. and Peyrot N., et al (2022) , + Clavel, P., et al (2023) , + Jovanovic M. (2023) , and + Jovanovic M., et al (2024) . + date_publication: '2024-05-22' + bug_reports: https://github.com/mladenjovanovic/shorts/issues + url: https://mladenjovanovic.github.io/shorts/ + url_cran: https://CRAN.R-project.org/package=shorts + url_git: '' +shotGroups: + version: 0.8.2 + title: Analyze Shot Group Data + maintainer: Daniel Wollschlaeger + description: |- + Analyzes shooting data with respect to group shape, + precision, and accuracy. This includes graphical methods, + descriptive statistics, and inference tests using standard, + but also non-parametric and robust statistical methods. + Implements distributions for radial error in bivariate normal + variables. Works with files exported by 'OnTarget PC/TDS', + 'Silver Mountain' e-target, 'ShotMarker' e-target, or 'Taran', + as well as with custom data files in text format. + Supports inference from range statistics such as extreme + spread. Includes a set of web-based graphical user interfaces. + date_publication: '2022-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shotGroups + url_git: '' +showimage: + version: 1.0.0 + title: Show an Image on an 'R' Graphics Device + maintainer: Gábor Csárdi + description: |- + Sometimes it is handy to be able to view an image file on an + 'R' graphics device. This package just does that. Currently it supports + 'PNG' files. + date_publication: '2018-01-24' + bug_reports: https://github.com/r-lib/showimage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=showimage + url_git: https://github.com/r-lib/showimage#readme +showtext: + version: 0.9-7 + title: Using Fonts More Easily in R Graphs + maintainer: Yixuan Qiu + description: |- + Making it easy to use various types of fonts ('TrueType', + 'OpenType', Type 1, web fonts, etc.) in R graphs, and supporting most output + formats of R graphics including PNG, PDF and SVG. Text glyphs will be converted + into polygons or raster images, hence after the plot has been created, it no + longer relies on the font files. No external software such as 'Ghostscript' is + needed to use this package. + date_publication: '2024-03-02' + bug_reports: https://github.com/yixuan/showtext/issues + url: '' + url_cran: https://CRAN.R-project.org/package=showtext + url_git: https://github.com/yixuan/showtext +showtextdb: + version: '3.0' + title: Font Files for the 'showtext' Package + maintainer: Yixuan Qiu + description: Providing font files that can be used by the 'showtext' package. + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=showtextdb + url_git: '' +shp2graph: + version: 1-0 + title: |- + Convert a 'SpatialLinesDataFrame' -Class Object to an + 'igraph'-Class Object + maintainer: Binbin Lu + description: |- + Functions for converting and processing network data from a + 'SpatialLinesDataFrame' -Class object to an 'igraph'-Class object. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shp2graph + url_git: '' +shrink: + version: 1.2.3 + title: Global, Parameterwise and Joint Shrinkage Factor Estimation + maintainer: Daniela Dunkler + description: |- + The predictive value of a statistical model can often be improved + by applying shrinkage methods. This can be achieved, e.g., by regularized + regression or empirical Bayes approaches. Various types of shrinkage factors can + also be estimated after a maximum likelihood. While global shrinkage modifies + all regression coefficients by the same factor, parameterwise shrinkage factors + differ between regression coefficients. With variables which are either highly + correlated or associated with regard to contents, such as several columns of a + design matrix describing a nonlinear effect, parameterwise shrinkage factors are + not interpretable and a compromise between global and parameterwise shrinkage, + termed 'joint shrinkage', is a useful extension. A computational shortcut to + resampling-based shrinkage factor estimation based on DFBETA residuals can be + applied. Global, parameterwise and joint shrinkage for models fitted by lm(), + glm(), coxph(), or mfp() is available. + date_publication: '2023-10-31' + bug_reports: https://github.com/biometrician/shrink/issues + url: '' + url_cran: https://CRAN.R-project.org/package=shrink + url_git: https://github.com/biometrician/shrink +ShrinkCovMat: + version: 1.4.0 + title: Shrinkage Covariance Matrix Estimators + maintainer: Anestis Touloumis + description: Provides nonparametric Steinian shrinkage estimators of the covariance + matrix that are suitable in high dimensional settings, that is when the number + of variables is larger than the sample size. + date_publication: '2019-07-30' + bug_reports: http://github.com/AnestisTouloumis/ShrinkCovMat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ShrinkCovMat + url_git: http://github.com/AnestisTouloumis/ShrinkCovMat +shrinkDSM: + version: 0.2.0 + title: |- + Efficient Bayesian Inference for Dynamic Survival Models with + Shrinkage + maintainer: Daniel Winkler + description: |- + Efficient Markov chain Monte Carlo (MCMC) algorithms for fully + Bayesian estimation of dynamic survival models with shrinkage priors. + Details on the algorithms used are provided in Wagner (2011) , + Bitto and Frühwirth-Schnatter (2019) and + Cadonna et al. (2020) . + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shrinkDSM + url_git: '' +shrinkem: + version: 0.2.0 + title: Approximate Bayesian Regularization for Parsimonious Estimates + maintainer: Joris Mulder + description: |- + Approximate Bayesian regularization using Gaussian approximations. The input is a vector of estimates + and a Gaussian error covariance matrix of the key parameters. Bayesian shrinkage is then applied + to obtain parsimonious solutions. The method is described on + Karimova, van Erp, Leenders, and Mulder (2024) . Gibbs samplers are used + for model fitting. The shrinkage priors that are supported are Gaussian (ridge) priors, Laplace + (lasso) priors (Park and Casella, 2008 ), and horseshoe priors + (Carvalho, et al., 2010; ). These priors include an option + for grouped regularization of different subsets of parameters (Meier et al., 2008; + ). F priors are used for the penalty + parameters lambda^2 (Mulder and Pericchi, 2018 ). This correspond to + half-Cauchy priors on lambda (Carvalho, Polson, Scott, 2010 ). + date_publication: '2024-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shrinkem + url_git: '' +shrinkGPR: + version: 1.0.0 + title: |- + Scalable Gaussian Process Regression with Hierarchical Shrinkage + Priors + maintainer: Peter Knaus + description: |- + Efficient variational inference methods for fully Bayesian Gaussian + Process Regression (GPR) models with hierarchical shrinkage priors, + including the triple gamma prior for effective variable selection and + covariance shrinkage in high-dimensional settings. The package leverages normalizing + flows to approximate complex posterior distributions. For details on implementation, + see Knaus (2025) . + date_publication: '2025-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shrinkGPR + url_git: '' +shrinkTVP: + version: 3.0.1 + title: |- + Efficient Bayesian Inference for Time-Varying Parameter Models + with Shrinkage + maintainer: Peter Knaus + description: |- + Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors, both dynamic and static. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) and + Cadonna et al. (2020) and Knaus and Frühwirth-Schnatter (2023) . For details on the package, please see Knaus et al. (2021) . + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shrinkTVP + url_git: '' +shrinkTVPVAR: + version: 0.1.1 + title: |- + Efficient Bayesian Inference for TVP-VAR-SV Models with + Shrinkage + maintainer: Peter Knaus + description: |- + Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter vector autoregressive models with shrinkage priors. Details on the algorithms used are provided in + Cadonna et al. (2020) and Knaus et al. (2021) . + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shrinkTVPVAR + url_git: '' +shroomDK: + version: 0.3.0 + title: Accessing the Flipside Crypto ShroomDK API + maintainer: Carlos Mercado + description: 'Programmatic access to Flipside Crypto data via the Compass RPC API: + . As simple as auto_paginate_query() but + with core functions as needed for troubleshooting. Note, 0.1.1 support deprecated + 2023-05-31.' + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shroomDK + url_git: '' +SHT: + version: 0.1.9 + title: Statistical Hypothesis Testing Toolbox + maintainer: Kisung You + description: We provide a collection of statistical hypothesis testing procedures + ranging from classical to modern methods for non-trivial settings such as high-dimensional + scenario. For the general treatment of statistical hypothesis testing, see the + book by Lehmann and Romano (2005) . + date_publication: '2025-02-27' + bug_reports: https://github.com/kisungyou/SHT/issues + url: https://www.kisungyou.com/SHT/ + url_cran: https://CRAN.R-project.org/package=SHT + url_git: '' +shuffle: + version: 1.0.1 + title: The Shuffle Estimator for Explainable Variance + maintainer: Yuval Benjamini + description: Implementation of the shuffle estimator, a non-parametric estimator + for signal and noise variance under mild noise correlations. + date_publication: '2016-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shuffle + url_git: '' +shuffleCI: + version: 0.1.0 + title: Confidence Intervals Compared via Shuffling + maintainer: Kyle Caudle + description: Scripts and exercises that use card shuffling to teach confidence interval + comparisons for different estimators. + date_publication: '2018-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shuffleCI + url_git: '' +shutterplot: + version: 0.1.0 + title: The R Shutter Plot Package + maintainer: Siddhanta Phuyal + description: |- + Shows the scatter plot along with the fitted regression lines. It + depicts min, max, the three quartiles, mean, and sd for each variable. + It also depicts sd-line, sd-box, r, r-square, prediction boundaries, and regression outliers. + date_publication: '2021-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=shutterplot + url_git: '' +SIAmodules: + version: 0.1.1 + title: Modules for 'ShinyItemAnalysis' + maintainer: Patricia Martinkova + description: |- + Package including additional modules for interactive + 'ShinyItemAnalysis' application for the psychometric analysis of + educational tests, psychological assessments, health-related and other + types of multi-item measurements, or ratings from multiple raters. + date_publication: '2024-04-23' + bug_reports: '' + url: https://www.ShinyItemAnalysis.org + url_cran: https://CRAN.R-project.org/package=SIAmodules + url_git: '' +SIAtools: + version: 0.1.2 + title: '''ShinyItemAnalysis'' Modules Development Toolkit' + maintainer: Jan Netik + description: |- + A comprehensive suite of functions designed for constructing + and managing 'ShinyItemAnalysis' modules, supplemented with detailed + guides, ready-to-use templates, linters, and tests. This package + allows developers to seamlessly create and integrate one or more + modules into their existing packages or to start a new module project + from scratch. + date_publication: '2025-01-30' + bug_reports: '' + url: https://applstat.github.io/SIAtools/ + url_cran: https://CRAN.R-project.org/package=SIAtools + url_git: '' +SIBER: + version: 2.1.9 + title: Stable Isotope Bayesian Ellipses in R + maintainer: Andrew Jackson + description: |- + Fits bi-variate ellipses to stable isotope data using Bayesian + inference with the aim being to describe and compare their isotopic + niche. + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIBER + url_git: '' +SIBERG: + version: 2.0.3 + title: |- + Systematic Identification of Bimodally Expressed Genes Using + RNAseq Data + maintainer: Kevin R. Coombes + description: |- + Provides models to identify bimodally expressed genes from + RNAseq data based on the Bimodality Index. SIBERG models the RNAseq data in + the finite mixture modeling framework and incorporates mechanisms for + dealing with RNAseq normalization. Three types of mixture models are + implemented, namely, the mixture of log normal, negative binomial, or + generalized Poisson distribution. See Tong et al. (2013) + . + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIBERG + url_git: http://oompa.r-forge.r-project.org/ +sicegar: + version: 0.2.4 + title: Analysis of Single-Cell Viral Growth Curves + maintainer: Claus O. Wilke + description: |2- + + Aims to quantify time intensity data by using sigmoidal and + double sigmoidal curves. It fits straight lines, sigmoidal, + and double sigmoidal curves on to time vs intensity data. + Then all the fits are used to make decision on which model + best describes the data. This method was first developed + in the context of single-cell viral growth analysis (for + details, see Caglar et al. (2018) ), + and the package name stands for "SIngle CEll Growth Analysis in R". + date_publication: '2021-05-08' + bug_reports: https://github.com/wilkelab/sicegar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sicegar + url_git: https://github.com/wilkelab/sicegar +siconvr: + version: 0.0.1 + title: Fetch Data from Plataforma +Brasil (SICONV) + maintainer: Fernando Meireles + description: |- + Fetch data on targeted public investments from Plataforma +Brasil (SICONV) , + the responsible system for requests, execution, and monitoring of federal discretionary transfers in Brazil. + date_publication: '2021-05-18' + bug_reports: https://github.com/meirelesff/siconvr/issues + url: https://fmeireles.com/siconvr/ + url_cran: https://CRAN.R-project.org/package=siconvr + url_git: https://github.com/meirelesff/siconvr +sicure: + version: 0.1.0 + title: Single-Index Mixture Cure Models + maintainer: Beatriz Piñeiro-Lamas + description: Single-index mixture cure models allow estimating the probability of + cure and the latency depending on a vector (or functional) covariate, avoiding + the curse of dimensionality. The vector of parameters that defines the model can + be estimated by maximum likelihood. A nonparametric estimator for the conditional + density of the susceptible population is provided. For more details, see Piñeiro-Lamas + (2024) (). + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sicure + url_git: '' +SID: + version: '1.1' + title: Structural Intervention Distance + maintainer: Fred Gruber + description: 'The code computes the structural intervention distance (SID) between + a true directed acyclic graph (DAG) and an estimated DAG. Definition and details + about the implementation can be found in J. Peters and P. Bühlmann: "Structural + intervention distance (SID) for evaluating causal graphs", Neural Computation + 27, pages 771-799, 2015 .' + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SID + url_git: https://github.com/fkgruber/SID_cran +SIDES: + version: '1.18' + title: Subgroup Identification Based on Differential Effect Search + maintainer: Marie-Karelle Riviere + description: Provides function to apply "Subgroup Identification based on Differential + Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) . + date_publication: '2023-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIDES + url_git: '' +sidier: + version: 4.1.0 + title: |- + Substitution and Indel Distances to Infer Evolutionary + Relationships + maintainer: A.J. Muñoz-Pajares + description: Evolutionary reconstruction based on substitutions and insertion-deletion + (indels) analyses in a distance-based framework. + date_publication: '2021-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sidier + url_git: '' +sidrar: + version: 0.2.9 + title: An Interface to IBGE's SIDRA API + maintainer: Renato Prado Siqueira + description: |- + Allows the user to connect with IBGE's (Instituto Brasileiro de + Geografia e Estatistica, see for more information) + SIDRA API in a flexible way. SIDRA is the acronym to "Sistema IBGE de + Recuperacao Automatica" and is the system where IBGE turns available + aggregate data from their researches. + date_publication: '2022-07-12' + bug_reports: https://github.com/rpradosiqueira/sidrar/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=sidrar + url_git: https://github.com/rpradosiqueira/sidrar/ +Sie2nts: + version: 0.1.0 + title: Sieve Methods for Non-Stationary Time Series + maintainer: Xiucai Ding + description: We provide functions for estimation and inference of locally-stationary + time series using the sieve methods and bootstrapping procedure. In addition, + it also contains functions to generate Daubechies and Coiflet wavelet by Cascade + algorithm and to process data visualization. + date_publication: '2023-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sie2nts + url_git: '' +siebanxicor: + version: 1.0.0 + title: Query Data Series from Bank of Mexico + maintainer: 'Noé Palmerin' + description: Allows to retrieve time series of all indicators available in the Bank + of Mexico's Economic Information System (). + date_publication: '2018-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siebanxicor + url_git: '' +SiER: + version: 0.1.0 + title: |- + Signal Extraction Approach for Sparse Multivariate Response + Regression + maintainer: Ruiyan Luo + description: Methods for regression with high-dimensional predictors and univariate + or maltivariate response variables. It considers the decomposition of the coefficient + matrix that leads to the best approximation to the signal part in the response + given any rank, and estimates the decomposition by solving a penalized generalized + eigenvalue problem followed by a least squares procedure. Ruiyan Luo and Xin Qi + (2017) . + date_publication: '2017-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SiER + url_git: '' +siera: + version: 0.1.0 + title: Generate Analysis Results Programmes Using ARS Metadata + maintainer: Malan Bosman + description: |- + Analysis Results Standard (ARS), a foundational standard by CDISC + (Clinical Data Interchange Standards Consortium), provides a logical + data model for metadata describing all components to calculate Analysis Results. + + Using 'siera' package, ARS metadata is ingested (JSON or Excel format), + producing programmes to generate Analysis Results Datasets (ARDs). + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siera + url_git: '' +Sieve: + version: '2.1' + title: Nonparametric Estimation by the Method of Sieves + maintainer: Tianyu Zhang + description: 'Performs multivariate nonparametric regression/classification by the + method of sieves (using orthogonal basis). The method is suitable for moderate + high-dimensional features (dimension < 100). The l1-penalized sieve estimator, + a nonparametric generalization of Lasso, is adaptive to the feature dimension + with provable theoretical guarantees. We also include a nonparametric stochastic + gradient descent estimator, Sieve-SGD, for online or large scale batch problems. + Details of the methods can be found in: .' + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sieve + url_git: '' +sievePH: + version: '1.1' + title: Sieve Analysis Methods for Proportional Hazards Models + maintainer: Michal Juraska + description: 'Implements a suite of semiparametric and nonparametric kernel-smoothed + estimation and testing procedures for continuous mark-specific stratified hazard + ratio (treatment/placebo) models in a randomized treatment efficacy trial with + a time-to-event endpoint. Semiparametric methods, allowing multivariate marks, + are described in Juraska M and Gilbert PB (2013), Mark-specific hazard ratio model + with multivariate continuous marks: an application to vaccine efficacy. Biometrics + 69(2):328-337 , and in Juraska M and Gilbert PB (2016), + Mark-specific hazard ratio model with missing multivariate marks. Lifetime Data + Analysis 22(4):606-25 . Nonparametric kernel-smoothed + methods, allowing univariate marks only, are described in Sun Y and Gilbert PB + (2012), Estimation of stratified mark‐specific proportional hazards models with + missing marks. Scandinavian Journal of Statistics}, 39(1):34-52 , + and in Gilbert PB and Sun Y (2015), Inferences on relative failure rates in stratified + mark-specific proportional hazards models with missing marks, with application + to human immunodeficiency virus vaccine efficacy trials. Journal of the Royal + Statistical Society Series C: Applied Statistics, 64(1):49-73 . + Both semiparametric and nonparametric approaches consider two scenarios: (1) the + mark is fully observed in all subjects who experience the event of interest, and + (2) the mark is subject to missingness-at-random in subjects who experience the + event of interest. For models with missing marks, estimators are implemented based + on (i) inverse probability weighting (IPW) of complete cases (for the semiparametric + framework), and (ii) augmentation of the IPW estimating functions by leveraging + correlations between the mark and auxiliary data to ''impute'' the augmentation + term for subjects with missing marks (for both the semiparametric and nonparametric + framework). The augmented IPW estimators are doubly robust and recommended for + use with incomplete mark data. The semiparametric methods make two key assumptions: + (i) the time-to-event is assumed to be conditionally independent of the mark given + treatment, and (ii) the weight function in the semiparametric density ratio/biased + sampling model is assumed to be exponential. Diagnostic testing procedures for + evaluating validity of both assumptions are implemented. Summary and plotting + functions are provided for estimation and inferential results.' + date_publication: '2024-05-17' + bug_reports: https://github.com/mjuraska/sievePH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sievePH + url_git: https://github.com/mjuraska/sievePH +sievetest: + version: 1.2.3 + title: Laboratory Sieve Test Reporting Functions + maintainer: Petr Matousu + description: Functions for making particle-size analysis. Sieve tests are widely + used to obtain particle-size distribution of powders or granular materials. + date_publication: '2018-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sievetest + url_git: '' +SiFINeT: + version: '1.13' + title: Single Cell Feature Identification with Network Topology + maintainer: Qi Gao + description: 'Cluster-independent method based on topology structure of gene co-expression + network for identifying feature gene sets, extracting cellular subpopulations, + and elucidating intrinsic relationships among these subpopulations. Without prior + cell clustering, SifiNet circumvents potential inaccuracies in clustering that + may influence subsequent analyses. This method is introduced in Qi Gao, Zhicheng + Ji, Liuyang Wang, Kouros Owzar, Qi-Jing Li, Cliburn Chan, Jichun Xie "SifiNet: + a robust and accurate method to identify feature gene sets and annotate cells" + (2024) .' + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SiFINeT + url_git: '' +sift: + version: 0.1.0 + title: Intelligently Peruse Data + maintainer: Scott McKenzie + description: Facilitate extraction of key information from common datasets. + date_publication: '2021-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sift + url_git: '' +sig: + version: 0.0-6 + title: Print Function Signatures + maintainer: Richard Cotton + description: Print function signatures and find overly complicated code. + date_publication: '2022-04-21' + bug_reports: https://bitbucket.org/richierocks/sig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sig + url_git: https://bitbucket.org/richierocks/sig +sigclust: + version: 1.1.0.1 + title: Statistical Significance of Clustering + maintainer: Hanwen Huang + description: |- + SigClust is a statistical method for testing the + significance of clustering results. SigClust can be applied to + assess the statistical significance of splitting a data set + into two clusters. For more than two clusters, SigClust can be + used iteratively. + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sigclust + url_git: '' +SightabilityModel: + version: 1.5.5 + title: Wildlife Sightability Modeling + maintainer: Schwarz Carl James + description: |- + Uses logistic regression to model the probability of detection as a function of covariates. + This model is then used with observational survey data to estimate population size, while + accounting for uncertain detection. See Steinhorst and Samuel (1989). + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SightabilityModel + url_git: https://github.com/jfieberg/SightabilityModel +sigInt: + version: 0.2.0 + title: Estimate the Parameters of a Discrete Crisis-Bargaining Game + maintainer: Casey Crisman-Cox + description: Provides pseudo-likelihood methods for empirically analyzing common + signaling games in international relations as described in Crisman-Cox and Gibilisco + (2019) . + date_publication: '2019-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sigInt + url_git: https://github.com/ccrismancox/sigint +sigmajs: + version: 0.1.5 + title: Interface to 'Sigma.js' Graph Visualization Library + maintainer: John Coene + description: Interface to 'sigma.js' graph visualization library including animations, + plugins and shiny proxies. + date_publication: '2020-06-18' + bug_reports: https://github.com/JohnCoene/sigmajs/issues + url: http://sigmajs.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=sigmajs + url_git: '' +sigminer: + version: 2.3.1 + title: |- + Extract, Analyze and Visualize Mutational Signatures for Genomic + Variations + maintainer: Shixiang Wang + description: |- + Genomic alterations including single nucleotide substitution, + copy number alteration, etc. are the major force for cancer + initialization and development. Due to the specificity of molecular + lesions caused by genomic alterations, we can generate characteristic + alteration spectra, called 'signature' (Wang, Shixiang, et al. (2021) + & Alexandrov, Ludmil B., et al. + (2020) & Steele Christopher D., et al. + (2022) ). This package helps users to + extract, analyze and visualize signatures from genomic alteration + records, thus providing new insight into cancer study. + date_publication: '2024-05-11' + bug_reports: https://github.com/ShixiangWang/sigminer/issues + url: https://shixiangwang.github.io/sigminer/ + url_cran: https://CRAN.R-project.org/package=sigminer + url_git: https://github.com/ShixiangWang/sigminer +sigmoid: + version: 1.4.0 + title: Sigmoid Functions for Machine Learning + maintainer: Bastiaan Quast + description: Several different sigmoid functions are implemented, including a wrapper + function, SoftMax preprocessing and inverse functions. + date_publication: '2022-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sigmoid + url_git: '' +SIGN: + version: 0.1.0 + title: Similarity Identification in Gene Expression + maintainer: Benjamin Haibe-Kains + description: Provides a classification framework to use expression patterns of pathways + as features to identify similarity between biological samples. It provides a new + measure for quantifying similarity between expression patterns of pathways. + date_publication: '2018-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIGN + url_git: '' +Signac: + version: 1.14.0 + title: Analysis of Single-Cell Chromatin Data + maintainer: Tim Stuart + description: |- + A framework for the analysis and exploration of single-cell chromatin data. + The 'Signac' package contains functions for quantifying single-cell chromatin data, + computing per-cell quality control metrics, dimension reduction + and normalization, visualization, and DNA sequence motif analysis. + Reference: Stuart et al. (2021) . + date_publication: '2024-08-21' + bug_reports: https://github.com/stuart-lab/signac/issues + url: https://stuartlab.org/signac + url_cran: https://CRAN.R-project.org/package=Signac + url_git: https://github.com/stuart-lab/signac +SignacX: + version: 2.2.5 + title: |- + Cell Type Identification and Discovery from Single Cell Gene + Expression Data + maintainer: Mathew Chamberlain + description: An implementation of neural networks trained with flow-sorted gene + expression data to classify cellular phenotypes in single cell RNA-sequencing + data. See Chamberlain M et al. (2021) for more + details. + date_publication: '2021-11-18' + bug_reports: https://github.com/mathewchamberlain/SignacX/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SignacX + url_git: https://github.com/mathewchamberlain/SignacX +signal: + version: 1.8-1 + title: Signal Processing + maintainer: Uwe Ligges + description: |- + A set of signal processing functions originally written for 'Matlab' and 'Octave'. + Includes filter generation utilities, filtering functions, + resampling routines, and visualization of filter models. It also + includes interpolation functions. + date_publication: '2024-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=signal + url_git: https://signal.R-forge.R-project.org +signalHsmm: + version: '1.5' + title: Predict Presence of Signal Peptides + maintainer: Michal Burdukiewicz + description: |- + Predicts the presence of signal peptides in eukaryotic protein + using hidden semi-Markov models. The implemented algorithm can be accessed from + both the command line and GUI. + date_publication: '2018-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=signalHsmm + url_git: https://github.com/michbur/signalhsmm +signatureSurvival: + version: 1.0.0 + title: Signature Survival Analysis + maintainer: Yuan-De Tan + description: |- + When multiple Cox proportional hazard models are performed on clinical data + (month or year and status) and a set of differential expressions of genes, + the results (Hazard risks, z-scores and p-values) can be used to create gene-expression signatures. + Weights are calculated using the survival p-values of genes and are utilized to calculate expression + values of the signature across the selected genes in all patients in a cohort. A Single or multiple + univariate or multivariate Cox proportional hazard survival analyses of the patients in one cohort + can be performed by using the gene-expression signature and visualized using our survival plots. + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=signatureSurvival + url_git: '' +signed.backbones: + version: 0.91.5 + title: Extract the Signed Backbones of Weighted Networks + maintainer: Furkan Gursoy + description: |- + Extract the signed backbones of intrinsically dense weighted networks based on the significance filter and vigor filter as described in the following paper. Please cite it if you find this software useful in your work. + Furkan Gursoy and Bertan Badur. "Extracting the signed backbone of intrinsically dense weighted networks." Journal of Complex Networks. . + date_publication: '2021-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=signed.backbones + url_git: '' +signibox: + version: '1.0' + title: Statistical Significance Marks on Boxplots + maintainer: Louis-Marvin Sander + description: Add significance marks to any R Boxplot, including a given significance + niveau. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=signibox + url_git: '' +SignifReg: + version: '4.3' + title: |- + Consistent Significance Controlled Variable Selection in + Generalized Linear Regression + maintainer: Adriano Zanin Zambom + description: Provides significance controlled variable selection algorithms with + different directions (forward, backward, stepwise) based on diverse criteria (AIC, + BIC, adjusted r-square, PRESS, or p-value). The algorithm selects a final model + with only significant variables defined as those with significant p-values after + multiple testing correction such as Bonferroni, False Discovery Rate, etc. See + Zambom and Kim (2018) . + date_publication: '2022-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SignifReg + url_git: '' +signnet: + version: 1.0.5 + title: Methods to Analyse Signed Networks + maintainer: David Schoch + description: |- + Methods for the analysis of signed networks. This includes + several measures for structural balance as introduced by Cartwright + and Harary (1956) , blockmodeling algorithms + from Doreian (2008) , various + centrality indices, and projections of signed two-mode networks + introduced by Schoch (2020) . + date_publication: '2025-02-05' + bug_reports: https://github.com/schochastics/signnet/issues + url: https://schochastics.github.io/signnet/ + url_cran: https://CRAN.R-project.org/package=signnet + url_git: https://github.com/schochastics/signnet +signs: + version: 0.1.2 + title: Insert Proper Minus Signs + maintainer: Benjamin E. Wolfe + description: |- + Provides convenience functions to replace hyphen-minuses (ASCII 45) + with proper minus signs (Unicode character 2212). The true minus matches + the plus symbol in width, line thickness, and height above the baseline. + It was designed for mathematics, looks better in presentation, + and is understood properly by screen readers. + date_publication: '2020-01-16' + bug_reports: https://github.com/BenjaminWolfe/signs/issues + url: https://benjaminwolfe.github.io/signs + url_cran: https://CRAN.R-project.org/package=signs + url_git: '' +SigOptR: + version: 0.0.1 + title: R API Wrapper for SigOpt + maintainer: Alexandra Johnson + description: Interfaces with the 'SigOpt' API. More info at . + date_publication: '2017-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SigOptR + url_git: '' +sigora: + version: 3.1.1 + title: Signature Overrepresentation Analysis + maintainer: Witold Wolski + description: |2- + + Pathway Analysis is statistically linking observations on + the molecular level to biological processes or pathways on + the systems(i.e., organism, organ, tissue, cell) level. + Traditionally, pathway analysis methods regard pathways + as collections of single genes and treat all genes in a pathway + as equally informative. However, this can lead to identifying + spurious pathways as statistically significant since components + are often shared amongst pathways. SIGORA seeks to avoid this + pitfall by focusing on genes or gene pairs that are (as a combination) + specific to a single pathway. + In relying on such pathway gene-pair signatures (Pathway-GPS), + SIGORA inherently uses the status of other genes in the + experimental context to identify the most relevant pathways. + The current version allows for pathway analysis of human + and mouse datasets. In addition, it contains pre-computed + Pathway-GPS data for pathways in the KEGG and Reactome + pathway repositories and mechanisms for extracting GPS + for user-supplied repositories. + date_publication: '2021-11-30' + bug_reports: https://github.com/wolski/sigora/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sigora + url_git: https://github.com/wolski/sigora +sigQC: + version: 0.1.24 + title: Quality Control Metrics for Gene Signatures + maintainer: Andrew Dhawan + description: Provides gene signature quality control metrics in publication ready + plots. Namely, enables the visualization of properties such as expression, variability, + correlation, and comparison of methods of standardisation and scoring metrics. + date_publication: '2024-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sigQC + url_git: '' +sigr: + version: 1.1.5 + title: Succinct and Correct Statistical Summaries for Reports + maintainer: John Mount + description: |- + Succinctly and correctly format statistical summaries of + various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). + This package also includes empirical tests, such as Monte Carlo and bootstrap distribution estimates. + date_publication: '2023-08-20' + bug_reports: https://github.com/WinVector/sigr/issues + url: https://winvector.github.io/sigr/ + url_cran: https://CRAN.R-project.org/package=sigr + url_git: https://github.com/WinVector/sigr/ +SigTree: + version: 1.10.6 + title: |- + Identify and Visualize Significantly Responsive Branches in a + Phylogenetic Tree + maintainer: John R. Stevens + description: Provides tools to identify and visualize branches in a phylogenetic + tree that are significantly responsive to some intervention, taking as primary + inputs a phylogenetic tree (of class phylo) and a data frame (or matrix) of corresponding + tip (OTU) labels and p-values. + date_publication: '2017-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SigTree + url_git: '' +sigugr: + version: 1.0.0 + title: Workflow for Geographic Data + maintainer: Jose Samos + description: |- + Streamlines geographic data transformation, storage and + publication, simplifying data preparation and enhancing + interoperability across formats and platforms. + date_publication: '2024-12-23' + bug_reports: https://github.com/josesamos/sigugr/issues + url: https://josesamos.github.io/sigugr/ + url_cran: https://CRAN.R-project.org/package=sigugr + url_git: https://github.com/josesamos/sigugr +SIHR: + version: 2.1.0 + title: Statistical Inference in High Dimensional Regression + maintainer: Zijian Guo + description: |- + The goal of SIHR is to provide inference procedures in the high-dimensional generalized linear regression setting for: + (1) linear functionals , + (2) conditional average treatment effects, + (3) quadratic functionals , + (4) inner product, + (5) distance. + date_publication: '2024-04-24' + bug_reports: https://github.com/zywang0701/SIHR/issues + url: https://zywang0701.github.io/SIHR/ + url_cran: https://CRAN.R-project.org/package=SIHR + url_git: '' +siie: + version: 0.4.0 + title: Superior Identification Index and Its Extensions + maintainer: Tian-Yuan Huang + description: |- + Calculate superior identification index and its extensions. + Measure the performance of journals based on how well they could + identify the top papers by any index (e.g. citation indices) according to Huang & Yang. + (2022) . These methods could be extended to + evaluate other entities such as institutes, countries, etc. + date_publication: '2023-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siie + url_git: '' +siland: + version: 3.0.2 + title: Spatial Influence of Landscape + maintainer: Martin Olivier + description: 'Method to estimate the spatial influence scales of landscape variables + on a response variable. The method is based on Chandler and Hepinstall-Cymerman + (2016) Estimating the spatial scales of landscape effects on abundance, Landscape + ecology, 31: 1383-1394, .' + date_publication: '2023-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siland + url_git: '' +SILFS: + version: 0.1.0 + title: Subgroup Identification with Latent Factor Structure + maintainer: Fuxin Wang + description: 'In various domains, many datasets exhibit both high variable dependency + and group structures, which necessitates their simultaneous estimation. This package + provides functions for two subgroup identification methods based on penalized + functions, both of which utilize factor model structures to adapt to data with + cross-sectional dependency. The first method is the Subgroup Identification with + Latent Factor Structure Method (SILFSM) we proposed. By employing Center-Augmented + Regularization and factor structures, the SILFSM effectively eliminates data dependencies + while identifying subgroups within datasets. For this model, we offer optimization + functions based on two different methods: Coordinate Descent and our newly developed + Difference of Convex-Alternating Direction Method of Multipliers (DC-ADMM) algorithms; + the latter can be applied to cases where the distance function in Center-Augmented + Regularization takes L1 and L2 forms. The other method is the Factor-Adjusted + Pairwise Fusion Penalty (FA-PFP) model, which incorporates factor augmentation + into the Pairwise Fusion Penalty (PFP) developed by Ma, S. and Huang, J. (2017) + . Additionally, we provide a function for the + Standard CAR (S-CAR) method, which does not consider the dependency and is for + comparative analysis with other approaches. Furthermore, functions based on the + Bayesian Information Criterion (BIC) of the SILFSM and the FA-PFP method are also + included in ''SILFS'' for selecting tuning parameters. For more details of Subgroup + Identification with Latent Factor Structure Method, please refer to He et al. + (2024) .' + date_publication: '2024-07-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SILFS + url_git: '' +SILGGM: + version: 1.0.0 + title: |- + Statistical Inference of Large-Scale Gaussian Graphical Model in + Gene Networks + maintainer: Rong Zhang + description: |- + Provides a general framework to perform statistical inference of each gene pair + and global inference of whole-scale gene pairs in gene networks using the well known + Gaussian graphical model (GGM) in a time-efficient manner. We focus on the high-dimensional + settings where p (the number of genes) is allowed to be far larger than n (the number of subjects). + Four main approaches are supported in this package: (1) the bivariate nodewise scaled Lasso + (Ren et al (2015) ) (2) the de-sparsified nodewise scaled Lasso + (Jankova and van de Geer (2017) ) (3) the de-sparsified + graphical Lasso (Jankova and van de Geer (2015) ) (4) the GGM + estimation with false discovery rate control (FDR) using scaled Lasso or Lasso + (Liu (2013) ). Windows users should install 'Rtools' before the + installation of this package. + date_publication: '2017-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SILGGM + url_git: '' +silicate: + version: 0.7.1 + title: |- + Common Forms for Complex Hierarchical and Relational Data + Structures + maintainer: Michael D. Sumner + description: |- + Generate common data forms for complex data suitable for conversions and + transmission by decomposition as paths or primitives. Paths are sequentially-linked records, + primitives are basic atomic elements and both can model many forms and be grouped into hierarchical + structures. The universal models 'SC0' (structural) and 'SC' (labelled, relational) are composed of + edges and can represent any hierarchical form. Specialist models 'PATH', 'ARC' and 'TRI' provide the + most common intermediate forms used for converting from one form to another. The methods are + inspired by the simplicial complex and + provide intermediate forms that relate spatial data structures to this mathematical construct. + date_publication: '2023-01-06' + bug_reports: https://github.com/hypertidy/silicate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=silicate + url_git: https://github.com/hypertidy/silicate +SillyPutty: + version: 0.4.1 + title: Silly Putty Clustering + maintainer: Kevin R. Coombes + description: |- + Implements a simple, novel clustering algorithm based on + optimizing the silhouette width. See + for details. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SillyPutty + url_git: http://oompa.r-forge.r-project.org/ +SILM: + version: 1.0.0 + title: Simultaneous Inference for Linear Models + maintainer: Xianyang Zhang + description: Simultaneous inference procedures for high-dimensional linear models + as described by Zhang, X., and Cheng, G. (2017) . + date_publication: '2019-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SILM + url_git: '' +silp: + version: 1.0.0 + title: |- + Conditional Process Analysis (CPA) via Structural Equation + Modeling (SEM) Approach + maintainer: Yi-Hsuan Tseng + description: |- + Provides Reliability-Adjusted Product Indicator (RAPI) method to estimate effects among latent variables, thus allowing for more precise definition and analysis of mediation and moderation models. Our simulation studies reveal that while 'silp' may exhibit instability with smaller sample sizes and lower reliability scores (e.g., N = 100, omega = 0.7), implementing nearest positive definite matrix correction and bootstrap confidence interval estimation can significantly ameliorate this volatility. When these adjustments are applied, 'silp' achieves estimations akin in quality to those derived from latent moderated structural equations (LMS). In conclusion, the 'silp' package is a valuable tool for researchers seeking to explore complex relational structures between variables without resorting to commercial software. + Hsiao et al.(2018) + Kline & Moosbrugger(2000) + Cheung et al.(2021). + date_publication: '2024-08-23' + bug_reports: https://github.com/TomBJJJ/silp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=silp + url_git: https://github.com/TomBJJJ/silp +sim.BA: + version: 0.1.0 + title: Simulation-Based Bias Analysis for Observational Studies + maintainer: Rishi Desai + description: |- + Allows user to conduct a simulation based quantitative + bias analysis using covariate structures generated with individual-level + data to characterize the bias arising from unmeasured confounding. Users + can specify their desired data generating mechanisms to simulate data + and quantitatively summarize findings in an end-to-end application + using this package. + date_publication: '2024-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sim.BA + url_git: '' +Sim.DiffProc: + version: '4.9' + title: Simulation of Diffusion Processes + maintainer: Arsalane Chouaib Guidoum + description: It provides users with a wide range of tools to simulate, estimate, + analyze, and visualize the dynamics of stochastic differential systems in both + forms Ito and Stratonovich. Statistical analysis with parallel Monte Carlo and + moment equations methods of SDEs . Enabled many searchers + in different domains to use these equations to modeling practical problems in + financial and actuarial modeling and other areas of application, e.g., modeling + and simulate of first passage time problem in shallow water using the attractive + center (Boukhetala K, 1996) ISBN:1-56252-342-2. + date_publication: '2024-03-06' + bug_reports: https://github.com/acguidoum/Sim.DiffProc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Sim.DiffProc + url_git: https://github.com/acguidoum/Sim.DiffProc +Sim.PLFN: + version: '1.0' + title: Simulation of Piecewise Linear Fuzzy Numbers + maintainer: Abbas Parchami + description: 'The definition of fuzzy random variable and the methods of simulation + from fuzzy random variables are two challenging statistical problems in three + recent decades. This package is organized based on a special definition of fuzzy + random variable and simulate fuzzy random variable by Piecewise Linear Fuzzy Numbers + (PLFNs); see Coroianua et al. (2013) for details + about PLFNs. Some important statistical functions are considered for obtaining + the membership function of main statistics, such as mean, variance, summation, + standard deviation and coefficient of variance. Some of applied advantages of + ''Sim.PLFN'' package are: (1) Easily generating / simulation a random sample + of PLFN, (2) drawing the membership functions of the simulated PLFNs or the membership + function of the statistical result, and (3) Considering the simulated PLFNs for + arithmetic operation or importing into some statistical computation. Finally, + it must be mentioned that ''Sim.PLFN'' package works on the basis of ''FuzzyNumbers'' + package.' + date_publication: '2017-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sim.PLFN + url_git: '' +sim1000G: + version: '1.40' + title: |- + Genotype Simulations for Rare or Common Variants Using + Haplotypes from 1000 Genomes + maintainer: Apostolos Dimitromanolakis + description: Generates realistic simulated genetic data in families or unrelated + individuals. + date_publication: '2019-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sim1000G + url_git: '' +sim2Dpredictr: + version: 0.1.1 + title: Simulate Outcomes Using Spatially Dependent Design Matrices + maintainer: Justin Leach + description: |- + Provides tools for simulating spatially dependent predictors (continuous or binary), + which are used to generate scalar outcomes in a (generalized) linear model framework. Continuous + predictors are generated using traditional multivariate normal distributions or Gauss Markov random + fields with several correlation function approaches (e.g., see Rue (2001) + and Furrer and Sain (2010) ), while binary predictors are generated using + a Boolean model (see Cressie and Wikle (2011, ISBN: 978-0-471-69274-4)). Parameter vectors + exhibiting spatial clustering can also be easily specified by the user. + date_publication: '2023-04-03' + bug_reports: https://github.com/jmleach-bst/sim2Dpredictr + url: '' + url_cran: https://CRAN.R-project.org/package=sim2Dpredictr + url_git: https://github.com/jmleach-bst/sim2Dpredictr +simaerep: + version: 0.6.0 + title: Find Clinical Trial Sites Under-Reporting Adverse Events + maintainer: Bjoern Koneswarakantha + description: |- + Monitoring of Adverse Event (AE) reporting in clinical trials is + important for patient safety. Sites that are under-reporting AEs can be detected + using Bootstrap-based simulations that simulate overall AE reporting. Based on the + simulation an AE under-reporting probability is assigned to each site in a + given trial (Koneswarakantha 2021 ). + date_publication: '2024-09-30' + bug_reports: '' + url: https://openpharma.github.io/simaerep/ + url_cran: https://CRAN.R-project.org/package=simaerep + url_git: https://github.com/openpharma/simaerep/ +SimBIID: + version: 0.2.1 + title: Simulation-Based Inference Methods for Infectious Disease Models + maintainer: Trevelyan J. McKinley + description: |- + Provides some code to run simulations of state-space models, and then + use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) + algorithm of Toni et al. (2009) and a bootstrap particle + filter based particle Markov chain Monte Carlo (PMCMC) algorithm + (Andrieu et al., 2010 ). + Also provides functions to plot and summarise the outputs. + date_publication: '2021-02-04' + bug_reports: https://github.com/tjmckinley/SimBIID/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SimBIID + url_git: https://github.com/tjmckinley/SimBIID +simboot: + version: 0.2-8 + title: Simultaneous Inference for Diversity Indices + maintainer: Ralph Scherer + description: Provides estimation of simultaneous bootstrap and asymptotic confidence + intervals for diversity indices, namely the Shannon and the Simpson index. Several + pre--specified multiple comparison types are available to choose. Further user--defined + contrast matrices are applicable. In addition, simboot estimates adjusted as well + as unadjusted p--values for two of the three proposed bootstrap methods. Further + simboot allows for comparing biological diversities of two or more groups while + simultaneously testing a user-defined selection of Hill numbers of orders q, which + are considered as appropriate and useful indices for measuring diversity. + date_publication: '2024-02-09' + bug_reports: https://github.com/shearer/simboot/issues + url: http://shearer.github.io/simboot/ + url_cran: https://CRAN.R-project.org/package=simboot + url_git: https://github.com/shearer/simboot +simCAT: + version: 1.0.1 + title: Implements Computerized Adaptive Testing Simulations + maintainer: Alexandre Jaloto + description: Computerized Adaptive Testing simulations with dichotomous and polytomous + items. Selects items with Maximum Fisher Information method or randomly, with + or without constraints (content balancing and item exposure control). Evaluates + the simulation results in terms of precision, item exposure, and test length. + Inspired on Magis & Barrada (2017) . + date_publication: '2024-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simCAT + url_git: https://github.com/alexandrejaloto/simCAT +simcausal: + version: 0.5.7 + title: Simulating Longitudinal Data with Causal Inference Applications + maintainer: Fred Gruber + description: |- + A flexible tool for simulating complex longitudinal data using + structural equations, with emphasis on problems in causal inference. + Specify interventions and simulate from intervened data generating + distributions. Define and evaluate treatment-specific means, the average + treatment effects and coefficients from working marginal structural models. + User interface designed to facilitate the conduct of transparent and + reproducible simulation studies, and allows concise expression of complex + functional dependencies for a large number of time-varying nodes. See the + package vignette for more information, documentation and examples. + date_publication: '2024-10-19' + bug_reports: https://github.com/osofr/simcausal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simcausal + url_git: https://github.com/osofr/simcausal +simcdm: + version: 0.1.2 + title: Simulate Cognitive Diagnostic Model ('CDM') Data + maintainer: James Joseph Balamuta + description: |- + Provides efficient R and 'C++' routines to simulate cognitive diagnostic + model data for Deterministic Input, Noisy "And" Gate ('DINA') and + reduced Reparameterized Unified Model ('rRUM') from + Culpepper and Hudson (2017) , + Culpepper (2015) , and + de la Torre (2009) . + date_publication: '2023-11-29' + bug_reports: https://github.com/tmsalab/simcdm/issues + url: https://tmsalab.github.io/simcdm/ + url_cran: https://CRAN.R-project.org/package=simcdm + url_git: https://github.com/tmsalab/simcdm +SimComp: + version: '3.3' + title: Simultaneous Comparisons for Multiple Endpoints + maintainer: Mario Hasler + description: Simultaneous tests and confidence intervals are provided for one-way + experimental designs with one or many normally distributed, primary response variables + (endpoints). Differences (Hasler and Hothorn, 2011 ) + or ratios (Hasler and Hothorn, 2012 ) of means + can be considered. Various contrasts can be chosen, unbalanced sample sizes are + allowed as well as heterogeneous variances (Hasler and Hothorn, 2008 ) + or covariance matrices (Hasler, 2014 ). + date_publication: '2019-08-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimComp + url_git: '' +SimCop: + version: 0.7.0 + title: Simulate from Arbitrary Copulae + maintainer: Berwin A. Turlach + description: |- + Provides a framework to generating random variates from + arbitrary multivariate copulae, while concentrating on + (bivariate) extreme value copulae. Particularly useful if + the multivariate copulae are not available in closed + form. + date_publication: '2017-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimCop + url_git: '' +SimCorMultRes: + version: 1.9.0 + title: Simulates Correlated Multinomial Responses + maintainer: Anestis Touloumis + description: Simulates correlated multinomial responses conditional on a marginal + model specification. + date_publication: '2023-07-11' + bug_reports: https://github.com/AnestisTouloumis/SimCorMultRes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SimCorMultRes + url_git: https://github.com/AnestisTouloumis/SimCorMultRes +SimCorrMix: + version: 0.1.1 + title: |- + Simulation of Correlated Data with Multiple Variable Types + Including Continuous and Count Mixture Distributions + maintainer: Allison Cynthia Fialkowski + description: |- + Generate continuous (normal, non-normal, or mixture distributions), binary, ordinal, + and count (regular or zero-inflated, Poisson or Negative Binomial) variables with a specified + correlation matrix, or one continuous variable with a mixture distribution. This package can + be used to simulate data sets that mimic real-world clinical or genetic data sets (i.e., + plasmodes, as in Vaughan et al., 2009 ). The methods + extend those found in the 'SimMultiCorrData' R package. Standard normal variables with an + imposed intermediate correlation matrix are transformed to generate the desired distributions. + Continuous variables are simulated using either Fleishman (1978)'s third order + or Headrick (2002)'s fifth order + polynomial transformation method (the power method + transformation, PMT). Non-mixture distributions require the user to specify mean, variance, + skewness, standardized kurtosis, and standardized fifth and sixth cumulants. Mixture + distributions require these inputs for the component distributions plus the mixing + probabilities. Simulation occurs at the component level for continuous mixture + distributions. The target correlation matrix is specified in terms of correlations with + components of continuous mixture variables. These components are transformed into the + desired mixture variables using random multinomial variables based on the mixing + probabilities. However, the package provides functions to approximate expected correlations + with continuous mixture variables given target correlations with the components. Binary and + ordinal variables are simulated using a modification of ordsample() in package 'GenOrd'. + Count variables are simulated using the inverse CDF method. There are two simulation + pathways which calculate intermediate correlations involving count variables differently. + Correlation Method 1 adapts Yahav and Shmueli's 2012 method and + performs best with large count variable means and positive correlations or small means and + negative correlations. Correlation Method 2 adapts Barbiero and Ferrari's 2015 + modification of the 'GenOrd' package and performs best under the + opposite scenarios. The optional error loop may be used to improve the accuracy of the + final correlation matrix. The package also contains functions to calculate the + standardized cumulants of continuous mixture distributions, check parameter inputs, + calculate feasible correlation boundaries, and summarize and plot simulated variables. + date_publication: '2018-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimCorrMix + url_git: https://github.com/AFialkowski/SimCorrMix +simcross: + version: '0.6' + title: Simulate Experimental Crosses + maintainer: Karl W Broman + description: 'Simulate and plot general experimental crosses. The focus is on simulating + genotypes with an aim towards flexibility rather than speed. Meiosis is simulated + following the Stahl model, in which chiasma locations are the superposition of + two processes: a proportion p coming from a process exhibiting no interference, + and the remainder coming from a process following the chi-square model.' + date_publication: '2023-11-29' + bug_reports: https://github.com/kbroman/simcross/issues + url: https://kbroman.org/simcross/ + url_cran: https://CRAN.R-project.org/package=simcross + url_git: https://github.com/kbroman/simcross +simctest: + version: 2.6.1 + title: Safe Implementation of Monte Carlo Tests + maintainer: Axel Gandy + description: Algorithms for the implementation and evaluation of Monte Carlo tests, + as well as for their use in multiple testing procedures. + date_publication: '2024-11-04' + bug_reports: '' + url: https://www.ma.imperial.ac.uk/~agandy/ + url_cran: https://CRAN.R-project.org/package=simctest + url_git: '' +simDAG: + version: 0.2.2 + title: Simulate Data from a DAG and Associated Node Information + maintainer: Robin Denz + description: |- + Simulate complex data from a given directed acyclic graph and information about each individual node. + Root nodes are simply sampled from the specified distribution. Child Nodes are simulated according to + one of many implemented regressions, such as logistic regression, linear + regression, poisson regression and more. Also includes a comprehensive framework for discrete-time + simulation, which can generate even more complex longitudinal data. + date_publication: '2025-02-23' + bug_reports: https://github.com/RobinDenz1/siMDAG/issues + url: https://robindenz1.github.io/simDAG/ + url_cran: https://CRAN.R-project.org/package=simDAG + url_git: https://github.com/RobinDenz1/simDAG +simdata: + version: 0.4.1 + title: Generate Simulated Datasets + maintainer: Michael Kammer + description: |- + Generate simulated datasets from an initial underlying + distribution and apply transformations to obtain realistic data. Implements + the 'NORTA' (Normal-to-anything) approach from Cario and Nelson (1997) + and other data generating mechanisms. Simple network visualization tools + are provided to facilitate communicating the simulation setup. + date_publication: '2024-12-03' + bug_reports: https://github.com/matherealize/simdata/issues + url: https://matherealize.github.io/simdata/ + url_cran: https://CRAN.R-project.org/package=simdata + url_git: https://github.com/matherealize/simdata +simdd: + version: 1.1-2 + title: |- + Simulation of Fisher Bingham and Related Directional + Distributions + maintainer: Kassel Liam Hingee + description: |- + Simulation methods for the Fisher Bingham distribution on the unit sphere, the matrix Bingham distribution on a Grassmann manifold, the matrix Fisher distribution on SO(3), and the bivariate von Mises sine model on the torus. + The methods use an acceptance/rejection simulation algorithm for the Bingham distribution and are described fully by Kent, Ganeiber and Mardia (2018) . + These methods supersede earlier MCMC simulation methods and are more general than earlier simulation methods. + The methods can be slower in specific situations where there are existing non-MCMC simulation methods (see Section 8 of Kent, Ganeiber and Mardia (2018) for further details). + date_publication: '2023-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simdd + url_git: '' +SimDesign: + version: '2.18' + title: Structure for Organizing Monte Carlo Simulation Designs + maintainer: Phil Chalmers + description: |- + Provides tools to safely and efficiently organize and execute + Monte Carlo simulation experiments in R. + The package controls the structure and back-end of Monte Carlo simulation experiments + by utilizing a generate-analyse-summarise workflow. The workflow safeguards against + common simulation coding issues, such as automatically re-simulating non-convergent results, + prevents inadvertently overwriting simulation files, catches error and warning messages + during execution, implicitly supports parallel processing with high-quality random number + generation, and provides tools for managing high-performance computing (HPC) array jobs + submitted to schedulers such as SLURM. For a pedagogical introduction to the package see + Sigal and Chalmers (2016) . For a more in-depth overview of + the package and its design philosophy see Chalmers and Adkins (2020) . + date_publication: '2024-12-14' + bug_reports: '' + url: http://philchalmers.github.io/SimDesign/ + url_cran: https://CRAN.R-project.org/package=SimDesign + url_git: https://github.com/philchalmers/SimDesign/wiki +SimDissolution: + version: 0.1.0 + title: Modeling and Assessing Similarity of Drug Dissolutions Profiles + maintainer: Kathrin Moellenhoff + description: Implementation of a model-based bootstrap approach for testing whether + two formulations are similar. The package provides a function for fitting a pharmacokinetic + model to time-concentration data and comparing the results for all five candidate + models regarding the Residual Sum of Squares (RSS). The candidate set contains + a First order, Hixson-Crowell, Higuchi, Weibull and a logistic model. The assessment + of similarity implemented in this package is performed regarding the maximum deviation + of the profiles. See Moellenhoff et al. (2018) for details. + date_publication: '2019-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimDissolution + url_git: '' +simdistr: + version: 1.0.1 + title: |- + Assessment of Data Trial Distributions According to the + Carlisle-Stouffer Method + maintainer: Bernardo Sousa-Pinto + description: |- + Assessment of the distributions of baseline continuous and categorical + variables in randomised trials. This method is based on the Carlisle-Stouffer + method with Monte Carlo simulations. It calculates p-values for each trial + baseline variable, as well as combined p-values for each trial - these p-values + measure how compatible are distributions of trials baseline variables with + random sampling. This package also allows for graphically plotting the + cumulative frequencies of computed p-values. + Please note that code was partly adapted from Carlisle JB, Loadsman JA. + (2017) . + date_publication: '2019-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simdistr + url_git: '' +simDNAmixtures: + version: 1.0.1 + title: Simulate Forensic DNA Mixtures + maintainer: Maarten Kruijver + description: Mixed DNA profiles can be sampled according to models for probabilistic + genotyping. Peak height variability is modelled using a log normal distribution + or a gamma distribution. Sample contributors may be related according to a pedigree. + date_publication: '2022-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simDNAmixtures + url_git: '' +simecol: + version: 0.8-14 + title: Simulation of Ecological (and Other) Dynamic Systems + maintainer: Thomas Petzoldt + description: |- + An object oriented framework to simulate + ecological (and other) dynamic systems. It can be used for + differential equations, individual-based (or agent-based) and other + models as well. It supports structuring of simulation scenarios (to avoid copy + and paste) and aims to improve readability and re-usability of code. + date_publication: '2021-10-07' + bug_reports: '' + url: http://www.simecol.de/ + url_cran: https://CRAN.R-project.org/package=simecol + url_git: '' +simEd: + version: 2.0.1 + title: Simulation Education + maintainer: Barry Lawson + description: |- + Contains various functions to be used for simulation education, + including simple Monte Carlo simulation functions, queueing simulation + functions, variate generation functions capable of producing independent + streams and antithetic variates, functions for illustrating random variate + generation for various discrete and continuous distributions, and functions + to compute time-persistent statistics. Also contains functions for + visualizing: event-driven details of a single-server queue model; a Lehmer + random number generator; variate generation via acceptance-rejection; and + of generating a non-homogeneous Poisson process via thinning. Also + contains two queueing data sets (one fabricated, one real-world) to + facilitate input modeling. More details on the use of these functions can + be found in Lawson and Leemis (2015) , in + Kudlay, Lawson, and Leemis (2020) , and + in Lawson and Leemis (2021) . + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simEd + url_git: '' +SimEngine: + version: 1.4.0 + title: A Modular Framework for Statistical Simulations in R + maintainer: Avi Kenny + description: An open-source R package for structuring, maintaining, running, and + debugging statistical simulations on both local and cluster-based computing environments.See + full documentation at . + date_publication: '2024-04-04' + bug_reports: https://github.com/Avi-Kenny/SimEngine/issues + url: https://avi-kenny.github.io/SimEngine/ + url_cran: https://CRAN.R-project.org/package=SimEngine + url_git: '' +simer: + version: 1.0.0 + title: Data Simulation for Life Science and Breeding + maintainer: Xiaolei Liu + description: |- + Data simulator including genotype, phenotype, pedigree, + selection and reproduction in R. It simulates most of reproduction process + of animals or plants and provides data for GS (Genomic Selection), + GWAS (Genome-Wide Association Study), and Breeding. + For ADI model, please see Kao C and Zeng Z (2002) . + For build.cov, please see B. D. Ripley (1987) . + date_publication: '2025-02-26' + bug_reports: https://github.com/xiaolei-lab/SIMER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simer + url_git: https://github.com/xiaolei-lab/SIMER +simest: + version: '0.4' + title: Constrained Single Index Model Estimation + maintainer: Arun Kumar Kuchibhotla + description: Estimation of function and index vector in single index model with + and without shape constraints including different smoothness conditions. + date_publication: '2017-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simest + url_git: '' +simET: + version: 1.0.3 + title: |- + Tools for Simulation of Evapotranspiration of Field Crops and + Soil Water Balance + maintainer: Minguo Liu + description: |- + Supports the calculation of meteorological characteristics in + evapotranspiration research and reference crop evapotranspiration, and offers + three models to simulate crop evapotranspiration and soil water balance in + the field, including single crop coefficient and dual crop coefficient, + as well as the Shuttleworth-Wallace model. These calculations main refer to + Allen et al.(1998, ISBN:92-5-104219-5), Teh (2006, ISBN:1-58-112-998-X), and + Liu et al.(2006) . + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simET + url_git: '' +SimEUCartelLaw: + version: 1.0.3 + title: Simulation of Legal Exemption System for European Cartel Law + maintainer: Martin Becker + description: |- + Monte Carlo simulations of a game-theoretic model for the + legal exemption system of the European cartel law are implemented + in order to estimate the (mean) deterrent effect of this system. + The input and output parameters of the simulated cartel + opportunities can be visualized by three-dimensional projections. + A description of the model is given in Moritz et al. (2018) + . + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimEUCartelLaw + url_git: '' +simex: + version: '1.8' + title: SIMEX- And MCSIMEX-Algorithm for Measurement Error Models + maintainer: Wolfgang Lederer + description: |- + Implementation of the SIMEX-Algorithm by Cook & Stefanski (1994) and + MCSIMEX by Küchenhoff, Mwalili & Lesaffre (2006) . + date_publication: '2019-07-31' + bug_reports: https://github.com/wolfganglederer/simex/issues + url: http://wolfganglederer.github.io/simex/ + url_cran: https://CRAN.R-project.org/package=simex + url_git: '' +simexaft: + version: 1.0.7.1 + title: simexaft + maintainer: Juan Xiong + description: Implement of the Simulation-Extrapolation (SIMEX) algorithm for the + accelerated failure time (AFT) with covariates subject to measurement error. + date_publication: '2019-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simexaft + url_git: '' +simExam: + version: 1.0.0 + title: Generate Simulated Data for IRT-Enabled Exams + maintainer: Waldir Leoncio + description: Generates binary test data based on Item Response Theory using the + two-parameter logistic model (Lord, 1980 ). Useful + functions for test equating are included, e.g. functions for generating internal + and external common items between test forms and a function to create a linkage + plans between those forms. Ancillary functions for generating true item and person + parameters as well as for calculating the probability of a person correctly answering + an item are also included. + date_publication: '2019-08-02' + bug_reports: https://github.com/wleoncio/simExam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simExam + url_git: '' +SIMEXBoost: + version: 0.2.0 + title: Boosting Method for High-Dimensional Error-Prone Data + maintainer: Bangxu Qiu + description: 'Implementation of the boosting procedure with the simulation and extrapolation + approach to address variable selection and estimation for high-dimensional data + subject to measurement error in predictors. It can be used to address generalized + linear models (GLM) in Chen (2023) and the accelerated + failure time (AFT) model in Chen and Qiu (2023) . Some + relevant references include Chen and Yi (2021) and Hastie, + Tibshirani, and Friedman (2008, ISBN:978-0387848570).' + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIMEXBoost + url_git: '' +simfam: + version: 1.1.6 + title: Simulate and Model Family Pedigrees with Structured Founders + maintainer: Alejandro Ochoa + description: The focus is on simulating and modeling families with founders drawn + from a structured population (for example, with different ancestries or other + potentially non-family relatedness), in contrast to traditional pedigree analysis + that treats all founders as equally unrelated. Main function simulates a random + pedigree for many generations, avoiding close relatives, pairing closest individuals + according to a 1D geography and their randomly-drawn sex, and with variable children + sizes to result in a target population size per generation. Auxiliary functions + calculate kinship matrices, admixture matrices, and draw random genotypes across + arbitrary pedigree structures starting from the corresponding founder values. The + code is built around the plink FAM table format for pedigrees. Described in Yao + and Ochoa (2022) . + date_publication: '2023-01-09' + bug_reports: https://github.com/OchoaLab/simfam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simfam + url_git: https://github.com/OchoaLab/simfam +simfinapi: + version: 1.0.0 + title: Accessing 'SimFin' Data + maintainer: Matthias Gomolka + description: |- + Through simfinapi, you can intuitively access the 'SimFin' + Web-API () to make 'SimFin' data easily + available in R. To obtain an 'SimFin' API key (and thus to use this + package), you need to register at . + date_publication: '2024-02-28' + bug_reports: https://github.com/matthiasgomolka/simfinapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simfinapi + url_git: https://github.com/matthiasgomolka/simfinapi +simfit: + version: 0.1.0 + title: Test Model Fit with Simulation + maintainer: James Green + description: |- + Simulates data from model objects (e.g., from lm(), glm()), + and plots this along with the original data to compare how well the + simulated data matches the original data to determine model fit. + date_publication: '2021-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simfit + url_git: '' +simFrame: + version: 0.5.4 + title: Simulation Framework + maintainer: Andreas Alfons + description: A general framework for statistical simulation, which allows researchers + to make use of a wide range of simulation designs with minimal programming effort. The + package provides functionality for drawing samples from a distribution or a finite + population, for adding outliers and missing values, as well as for visualization + of the simulation results. It follows a clear object-oriented design and supports + parallel computing to increase computational performance. + date_publication: '2021-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simFrame + url_git: '' +simglm: + version: 0.8.9 + title: Simulate Models Based on the Generalized Linear Model + maintainer: Brandon LeBeau + description: |- + Simulates regression models, + including both simple regression and generalized linear mixed + models with up to three level of nesting. Power simulations that are + flexible allowing the specification of missing data, unbalanced designs, + and different random error distributions are built into the package. + date_publication: '2022-02-07' + bug_reports: https://github.com/lebebr01/simglm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simglm + url_git: https://github.com/lebebr01/simglm +simgof: + version: 1.0.2 + title: Simultaneous Goodness-of-Fits Tests + maintainer: Wolfgang Rolke + description: |- + Routine that allows the user to run several goodness-of-fit tests. + It also combines the tests and returns a properly adjusted family-wise p value. + Details can be found in . + date_publication: '2021-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simgof + url_git: '' +SimHaz: + version: '0.1' + title: |- + Simulated Survival and Hazard Analysis for Time-Dependent + Exposure + maintainer: Nusrat Rabbee + description: Generate power for the Cox proportional hazards model by simulating + survival events data with time dependent exposure status for subjects. A dichotomous + exposure variable is considered with a single transition from unexposed to exposed + status during the subject's time on study. + date_publication: '2015-10-19' + bug_reports: https://github.com/rabbeelab/SimHaz/issues + url: http://www.stat.berkeley.edu/~rabbee/research_webpage.htm + url_cran: https://CRAN.R-project.org/package=SimHaz + url_git: '' +simhelpers: + version: 0.3.1 + title: Helper Functions for Simulation Studies + maintainer: Megha Joshi + description: Calculates performance criteria measures and associated Monte Carlo + standard errors for simulation results. Includes functions to help run simulation + studies, following a general simulation workflow that closely aligns with the + approach described by Morris, White, and Crowther (2019) . + Also includes functions for calculating bootstrap confidence intervals (including + normal, basic, studentized, percentile, bias-corrected, and bias-corrected-and-accelerated) + with tidy output, as well as for extrapolating confidence interval coverage rates + and hypothesis test rejection rates following techniques suggested by Boos and + Zhang (2000) . + date_publication: '2025-01-10' + bug_reports: https://github.com/meghapsimatrix/simhelpers/issues + url: https://meghapsimatrix.github.io/simhelpers/ + url_cran: https://CRAN.R-project.org/package=simhelpers + url_git: '' +SIMICO: + version: 0.2.0 + title: Set-Based Inference for Multiple Interval-Censored Outcomes + maintainer: Jaihee Choi + description: Contains tests for association between a set of genetic variants and + multiple correlated outcomes that are interval censored. Interval-censored data + arises when the exact time of the onset of an outcome of interest is unknown but + known to fall between two time points. + date_publication: '2022-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIMICO + url_git: '' +simIDM: + version: 0.1.0 + title: Simulating Oncology Trials using an Illness-Death Model + maintainer: Alexandra Erdmann + description: |- + Based on the illness-death model a large number of clinical + trials with oncology endpoints progression-free survival (PFS) and + overall survival (OS) can be simulated, see Meller, Beyersmann and + Rufibach (2019) . The simulation set-up allows + for random and event-driven censoring, an arbitrary number of + treatment arms, staggered study entry and drop-out. Exponentially, + Weibull and piecewise exponentially distributed survival times can be + generated. The correlation between PFS and OS can be calculated. + date_publication: '2023-12-11' + bug_reports: https://github.com/insightsengineering/simIDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simIDM + url_git: https://github.com/insightsengineering/simIDM/ +SimilarityMeasures: + version: '1.4' + title: Trajectory Similarity Measures + maintainer: Kevin Toohey + description: |- + Functions to run and assist four + different similarity measures. The similarity + measures included are: longest common + subsequence (LCSS), Frechet distance, edit distance + and dynamic time warping (DTW). Each of these + similarity measures can be calculated from two + n-dimensional trajectories, both in matrix form. + date_publication: '2015-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimilarityMeasures + url_git: '' +Simile: + version: 1.3.4 + title: Interact with Simile Models + maintainer: Jasper Taylor + description: |- + Allows a Simile model saved as a compiled binary to be + loaded, parameterized, executed and interrogated. This version works + with Simile v6 on. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Simile + url_git: '' +SimInf: + version: 9.8.1 + title: |- + A Framework for Data-Driven Stochastic Disease Spread + Simulations + maintainer: Stefan Widgren + description: |- + Provides an efficient and very flexible framework to + conduct data-driven epidemiological modeling in realistic large + scale disease spread simulations. The framework integrates + infection dynamics in subpopulations as continuous-time Markov + chains using the Gillespie stochastic simulation algorithm and + incorporates available data such as births, deaths and movements + as scheduled events at predefined time-points. Using C code for + the numerical solvers and 'OpenMP' (if available) to divide work + over multiple processors ensures high performance when simulating + a sample outcome. One of our design goals was to make the package + extendable and enable usage of the numerical solvers from other R + extension packages in order to facilitate complex epidemiological + research. The package contains template models and can be extended + with user-defined models. For more details see the paper by + Widgren, Bauer, Eriksson and Engblom (2019) + . The package also provides + functionality to fit models to time series data using the + Approximate Bayesian Computation Sequential Monte Carlo + ('ABC-SMC') algorithm of Toni and others (2009) + . + date_publication: '2024-06-21' + bug_reports: https://github.com/stewid/SimInf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SimInf + url_git: https://github.com/stewid/SimInf +simIReff: + version: '1.0' + title: |- + Stochastic Simulation for Information Retrieval Evaluation: + Effectiveness Scores + maintainer: Julián Urbano + description: |- + Provides tools for the stochastic simulation of effectiveness scores to mitigate + data-related limitations of Information Retrieval evaluation research, as described in Urbano and + Nagler (2018) . These tools include: fitting, selection and plotting + distributions to model system effectiveness, transformation towards a prespecified expected value, + proxy to fitting of copula models based on these distributions, and simulation of new evaluation + data from these distributions and copula models. + date_publication: '2018-06-15' + bug_reports: https://github.com/julian-urbano/simIReff/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simIReff + url_git: https://github.com/julian-urbano/simIReff/ +simitation: + version: 0.0.7 + title: Simplified Simulations + maintainer: Srivastav Budugutta + description: Provides tools for generating and analyzing simulation studies. Users + may easily specify all terms of a simulation study, often in a single line of + code. Common univariate and bivariate methods, such as t tests, proportions tests, + and chi squared tests, are integrated. Multivariate studies involving linear or + logistic regression may also be specified with symbolic inputs. The simulation + studies generate data for n observations in each of B experiments. Analyses of + each experiment are integrated, and empirical results across the experiments are + also provided. + date_publication: '2023-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simitation + url_git: '' +simITS: + version: 0.1.1 + title: Analysis via Simulation of Interrupted Time Series (ITS) Data + maintainer: Luke Miratrix + description: |- + Uses simulation to create prediction intervals for + post-policy outcomes in interrupted time series (ITS) designs, + following Miratrix (2020) . This package provides + methods for fitting ITS models with lagged outcomes and variables to + account for temporal dependencies. It then conducts inference via + simulation, simulating a set of plausible counterfactual post-policy + series to compare to the observed post-policy series. This package + also provides methods to visualize such data, and also to incorporate + seasonality models and smoothing and aggregation/summarization. This + work partially funded by Arnold Ventures in collaboration with + MDRC. + date_publication: '2020-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simITS + url_git: '' +SimJoint: + version: 0.3.12 + title: Simulate Joint Distribution + maintainer: Charlie Wusuo Liu + description: Simulate multivariate correlated data given nonparametric marginals + and their joint structure characterized by a Pearson or Spearman correlation matrix. + The simulator engages the problem from a purely computational perspective. It + assumes no statistical models such as copulas or parametric distributions, and + can approximate the target correlations regardless of theoretical feasibility. + The algorithm integrates and advances the Iman-Conover (1982) approach + and the Ruscio-Kaczetow iteration (2008) . Package + functions are carefully implemented in C++ for squeezing computing speed, suitable + for large input in a manycore environment. Precision of the approximation and + computing speed both substantially outperform various CRAN packages to date. Benchmarks + are detailed in function examples. A simple heuristic algorithm is additionally + designed to optimize the joint distribution in the post-simulation stage. The + heuristic demonstrated good potential of achieving the same level of precision + of approximation without the enhanced Iman-Conover-Ruscio-Kaczetow. The package + contains a copy of Permuted Congruential Generator. + date_publication: '2024-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimJoint + url_git: '' +simlandr: + version: 0.4.0 + title: Simulation-Based Landscape Construction for Dynamical Systems + maintainer: Jingmeng Cui + description: |- + A toolbox for constructing potential landscapes for dynamical + systems using Monte Carlo simulation. The method is based on the + potential landscape definition by Wang et al. (2008) + (also see Zhou & Li, 2016 + for further mathematical discussions) and can + be used for a large variety of models. + date_publication: '2025-02-12' + bug_reports: https://github.com/Sciurus365/simlandr/issues + url: https://sciurus365.github.io/simlandr/ + url_cran: https://CRAN.R-project.org/package=simlandr + url_git: https://github.com/Sciurus365/simlandr +SIMle: + version: 0.1.0 + title: Estimation and Inference for General Time Series Regression + maintainer: Xiucai Ding + description: We provide functions for estimation and inference of nonlinear and + non-stationary time series regression using the sieve methods and bootstrapping + procedure. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIMle + url_git: '' +simmer: + version: 4.4.7 + title: Discrete-Event Simulation for R + maintainer: Iñaki Ucar + description: |- + A process-oriented and trajectory-based Discrete-Event Simulation + (DES) package for R. It is designed as a generic yet powerful framework. The + architecture encloses a robust and fast simulation core written in 'C++' with + automatic monitoring capabilities. It provides a rich and flexible R API that + revolves around the concept of trajectory, a common path in the simulation + model for entities of the same type. Documentation about 'simmer' is provided + by several vignettes included in this package, via the paper by Ucar, Smeets + & Azcorra (2019, ), and the paper by Ucar, + Hernández, Serrano & Azcorra (2018, ); + see 'citation("simmer")' for details. + date_publication: '2024-09-28' + bug_reports: https://github.com/r-simmer/simmer/issues + url: https://r-simmer.org + url_cran: https://CRAN.R-project.org/package=simmer + url_git: https://github.com/r-simmer/simmer +simmer.bricks: + version: 0.2.2 + title: Helper Methods for 'simmer' Trajectories + maintainer: Iñaki Ucar + description: Provides wrappers for common activity patterns in 'simmer' trajectories. + date_publication: '2023-07-15' + bug_reports: https://github.com/r-simmer/simmer.bricks/issues + url: https://r-simmer.org + url_cran: https://CRAN.R-project.org/package=simmer.bricks + url_git: https://github.com/r-simmer/simmer.bricks +simmer.plot: + version: 0.1.18 + title: Plotting Methods for 'simmer' + maintainer: Iñaki Ucar + description: A set of plotting methods for 'simmer' trajectories and simulations. + date_publication: '2023-07-17' + bug_reports: https://github.com/r-simmer/simmer.plot/issues + url: https://r-simmer.org + url_cran: https://CRAN.R-project.org/package=simmer.plot + url_git: https://github.com/r-simmer/simmer.plot +simMetric: + version: 0.1.1 + title: |- + Metrics (with Uncertainty) for Simulation Studies that Evaluate + Statistical Methods + maintainer: Rex Parsons + description: Allows users to quickly apply individual or multiple metrics to evaluate + Monte Carlo simulation studies. + date_publication: '2022-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simMetric + url_git: '' +simml: + version: 0.3.0 + title: Single-Index Models with Multiple-Links + maintainer: Hyung Park + description: A major challenge in estimating treatment decision rules from a randomized + clinical trial dataset with covariates measured at baseline lies in detecting + relatively small treatment effect modification-related variability (i.e., the + treatment-by-covariates interaction effects on treatment outcomes) against a relatively + large non-treatment-related variability (i.e., the main effects of covariates + on treatment outcomes). The class of Single-Index Models with Multiple-Links is + a novel single-index model specifically designed to estimate a single-index (a + linear combination) of the covariates associated with the treatment effect modification-related + variability, while allowing a nonlinear association with the treatment outcomes + via flexible link functions. The models provide a flexible regression approach + to developing treatment decision rules based on patients' data measured at baseline. + We refer to Park, Petkova, Tarpey, and Ogden (2020) + and Park, Petkova, Tarpey, and Ogden (2020) (that allows + an unspecified X main effect) for detail of the method. The main function of this + package is simml(). + date_publication: '2021-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simml + url_git: '' +simMP: + version: 0.17.3 + title: |- + Simulate Somatic Mutations in Cancer Genomes from Mutational + Processes + maintainer: Nan Zhou + description: Simulates somatic single base substitutions carried in cancer genomes. + By only providing a human reference genome, substitutions that result from mutational + processes operative in every cancer genome can be generated. + date_publication: '2017-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simMP + url_git: '' +simmr: + version: 0.5.1.217 + title: A Stable Isotope Mixing Model + maintainer: Emma Govan + description: Fits Stable Isotope Mixing Models (SIMMs) and is meant as a longer + term replacement to the previous widely-used package SIAR. SIMMs are used to infer + dietary proportions of organisms consuming various food sources from observations + on the stable isotope values taken from the organisms' tissue samples. However + SIMMs can also be used in other scenarios, such as in sediment mixing or the composition + of fatty acids. The main functions are simmr_load() and simmr_mcmc(). The two + vignettes contain a quick start and a full listing of all the features. The methods + used are detailed in the papers Parnell et al 2010 , + and Parnell et al 2013 . + date_publication: '2024-10-16' + bug_reports: https://github.com/andrewcparnell/simmr/issues + url: https://andrewcparnell.github.io/simmr/ + url_cran: https://CRAN.R-project.org/package=simmr + url_git: https://github.com/andrewcparnell/simmr +SIMMS: + version: 1.3.2 + title: Subnetwork Integration for Multi-Modal Signatures + maintainer: Syed Haider + description: Algorithms to create prognostic biomarkers using biological genesets + or networks. + date_publication: '2022-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIMMS + url_git: '' +simMSM: + version: 1.1.42 + title: Simulation of Event Histories for Multi-State Models + maintainer: Holger Reulen + description: Simulation of event histories with possibly non-linear baseline hazard + rate functions, non-linear (time-varying) covariate effect functions, and dependencies + on the past of the history. Random generation of event histories is performed + using inversion sampling on the cumulative all-cause hazard rate functions. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simMSM + url_git: '' +SimMultiCorrData: + version: 0.2.2 + title: Simulation of Correlated Data with Multiple Variable Types + maintainer: Allison Cynthia Fialkowski + description: |- + Generate continuous (normal or non-normal), binary, ordinal, and count (Poisson or Negative + Binomial) variables with a specified correlation matrix. It can also produce a single continuous + variable. This package can be used to simulate data sets that mimic real-world situations (i.e. + clinical or genetic data sets, plasmodes). All variables are generated from standard normal + variables with an imposed intermediate correlation matrix. Continuous variables are simulated + by specifying mean, variance, skewness, standardized kurtosis, and fifth and sixth standardized + cumulants using either Fleishman's third-order () or Headrick's + fifth-order () polynomial transformation. Binary and + ordinal variables are simulated using a modification of the ordsample() function from 'GenOrd'. + Count variables are simulated using the inverse cdf method. There are two simulation pathways + which differ primarily according to the calculation of the intermediate correlation matrix. In + Correlation Method 1, the intercorrelations involving count variables are determined using a + simulation based, logarithmic correlation correction (adapting Yahav and Shmueli's 2012 method, + ). In Correlation Method 2, the count variables are treated as ordinal + (adapting Barbiero and Ferrari's 2015 modification of GenOrd, ). + There is an optional error loop that corrects the final correlation matrix to be within a + user-specified precision value of the target matrix. The package also includes functions to + calculate standardized cumulants for theoretical distributions or from real data sets, check + if a target correlation matrix is within the possible correlation bounds (given the distributions + of the simulated variables), summarize results (numerically or graphically), to verify valid power + method pdfs, and to calculate lower standardized kurtosis bounds. + date_publication: '2018-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimMultiCorrData + url_git: https://github.com/AFialkowski/SimMultiCorrData +SimNPH: + version: 0.5.6 + title: Simulate Non-Proportional Hazards + maintainer: Tobias Fellinger + description: |- + A toolkit for simulation studies concerning time-to-event endpoints + with non-proportional hazards. 'SimNPH' encompasses functions for simulating + time-to-event data in various scenarios, simulating different trial designs + like fixed-followup, event-driven, and group sequential designs. The package + provides functions to calculate the true values of common summary statistics + for the implemented scenarios and offers common analysis methods for + time-to-event data. Helper functions for running simulations with the + 'SimDesign' package and for aggregating and presenting the results are also + included. Results of the conducted simulation study are available in the + paper: "A Comparison of Statistical Methods for Time-To-Event Analyses in + Randomized Controlled Trials Under Non-Proportional Hazards", + Klinglmüller et al. (2025) . + date_publication: '2025-02-20' + bug_reports: https://github.com/SimNPH/SimNPH/issues/ + url: https://simnph.github.io/SimNPH/ + url_cran: https://CRAN.R-project.org/package=SimNPH + url_git: https://github.com/SimNPH/SimNPH/ +simode: + version: 1.2.2 + title: |- + Statistical Inference for Systems of Ordinary Differential + Equations using Separable Integral-Matching + maintainer: Rami Yaari + description: |- + Implements statistical inference for systems of ordinary differential equations, + that uses the integral-matching criterion and takes advantage of the separability of parameters, + in order to obtain initial parameter estimates for nonlinear least squares optimization. + Dattner & Yaari (2018) . + Dattner et al. (2017) . + Dattner & Klaassen (2015) . + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simode + url_git: '' +simodels: + version: 0.2.0 + title: Flexible Framework for Developing Spatial Interaction Models + maintainer: Robin Lovelace + description: |- + Develop spatial interaction models (SIMs). SIMs predict the + amount of interaction, for example number of trips per day, between + geographic entities representing trip origins and destinations. + Contains functions for creating origin-destination datasets + from geographic input datasets and calculating movement between + origin-destination pairs with constrained, production-constrained, + and attraction-constrained models (Wilson 1979) . + date_publication: '2024-08-22' + bug_reports: https://github.com/robinlovelace/simodels/issues + url: https://robinlovelace.github.io/simodels/ + url_cran: https://CRAN.R-project.org/package=simodels + url_git: https://github.com/robinlovelace/simodels +simPH: + version: 1.3.13 + title: Simulate and Plot Estimates from Cox Proportional Hazards Models + maintainer: Christopher Gandrud + description: |- + Simulates and plots quantities of interest (relative + hazards, first differences, and hazard ratios) for linear coefficients, + multiplicative interactions, polynomials, penalised splines, and + non-proportional hazards, as well as stratified survival curves from Cox + Proportional Hazard models. It also simulates and plots marginal effects + for multiplicative interactions. Methods described in Gandrud (2015) + . + date_publication: '2021-01-10' + bug_reports: https://github.com/christophergandrud/simPH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simPH + url_git: '' +simphony: + version: 1.0.3 + title: Simulating Large-Scale, Rhythmic Data + maintainer: Jake Hughey + description: |- + A tool for simulating rhythmic data: transcriptome data using + Gaussian or negative binomial distributions, and behavioral activity data + using Bernoulli or Poisson distributions. See Singer et al. (2019) + . + date_publication: '2022-08-09' + bug_reports: '' + url: https://simphony.hugheylab.org + url_cran: https://CRAN.R-project.org/package=simphony + url_git: https://github.com/hugheylab/simphony +simplace: + version: 5.1.2 + title: Interface to Use the Modelling Framework 'SIMPLACE' + maintainer: Gunther Krauss + description: |- + Interface to interact with the modelling framework 'SIMPLACE' and to + parse the results of simulations. + date_publication: '2024-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simplace + url_git: https://github.com/gk-crop/simplace_rpkg/ +simplanonym: + version: 0.1.0 + title: Consistent Anonymisation Across Datasets + maintainer: Douglas Kiarelly Godoy de Araujo + description: |- + A simple function that anonymises a list of variables + in a consistent way: anonymised factors are not recycled and + the same original levels receive the same anonymised factor + even if located in different datasets. + date_publication: '2023-01-30' + bug_reports: https://github.com/dkgaraujo/simplanonym/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simplanonym + url_git: https://github.com/dkgaraujo/simplanonym +SIMPLE.REGRESSION: + version: 0.2.1 + title: OLS, Moderated, Logistic, and Count Regressions Made Simple + maintainer: Brian P. O'Connor + description: |- + Provides SPSS- and SAS-like output for least squares multiple regression, + logistic regression, and count variable regressions. Detailed output is also provided for + OLS moderated regression, interaction plots, and Johnson-Neyman + regions of significance. The output includes standardized + coefficients, partial and semi-partial correlations, collinearity diagnostics, + plots of residuals, and detailed information about simple slopes for interactions. + The output for some functions includes Bayes Factors and, if requested, + regression coefficients from Bayesian Markov Chain Monte Carlo analyses. + There are numerous options for model plots. + The REGIONS_OF_SIGNIFICANCE function also provides + Johnson-Neyman regions of significance and plots of interactions for both lm + and lme models. + date_publication: '2025-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIMPLE.REGRESSION + url_git: '' +simpleboot: + version: 1.1-8 + title: Simple Bootstrap Routines + maintainer: Roger D. Peng + description: Simple bootstrap routines. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simpleboot + url_git: https://github.com/rdpeng/simpleboot +simpleCache: + version: 0.4.2 + title: Simply Caching R Objects + maintainer: Nathan Sheffield + description: |- + Provides intuitive functions for caching R objects, encouraging + reproducible, restartable, and distributed R analysis. The user selects a + location to store caches, and then provides nothing more than a cache name + and instructions (R code) for how to produce the R object. Also + provides some advanced options like environment assignments, recreating or + reloading caches, and cluster compute bindings (using the 'batchtools' + package) making it flexible enough for use in large-scale data analysis + projects. + date_publication: '2021-04-17' + bug_reports: https://github.com/databio/simpleCache + url: '' + url_cran: https://CRAN.R-project.org/package=simpleCache + url_git: https://github.com/databio/simpleCache +simplecolors: + version: 0.1.2 + title: Access Color Names Using a Standardized Nomenclature + maintainer: Jake Riley + description: |- + A curated set of colors that are called using + a standardized syntax: saturation + hue + lightness. For example, + "brightblue4" and "mutedred2". Functions exists to return individual colors + by name or to build palettes across or within hues. Most functions allow you + to visualize the palettes in addition to returning the desired hex codes. + date_publication: '2023-08-31' + bug_reports: https://github.com/rjake/simplecolors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simplecolors + url_git: https://github.com/rjake/simplecolors +simpleFDR: + version: '1.1' + title: Simple False Discovery Rate Calculation + maintainer: Stephen Wisser + description: Using the adjustment method from Benjamini & Hochberg (1995) , + this package determines which variables are significant under repeated testing + with a given dataframe of p values and an user defined "q" threshold. It then + returns the original dataframe along with a significance column where an asterisk + denotes a significant p value after FDR calculation, and NA denotes all other + p values. This package uses the Benjamini & Hochberg method specifically as described + in Lee, S., & Lee, D. K. (2018) . + date_publication: '2021-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simpleFDR + url_git: '' +simplegraph: + version: 1.0.1 + title: Simple Graph Data Types and Basic Algorithms + maintainer: Gabor Csardi + description: |- + Simple classic graph algorithms for simple graph classes. + Graphs may possess vertex and edge attributes. 'simplegraph' has + no dependencies and it is written entirely in R, so it is easy to + install. + date_publication: '2023-08-31' + bug_reports: https://github.com/gaborcsardi/simplegraph/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simplegraph + url_git: https://github.com/gaborcsardi/simplegraph +simplegraphdb: + version: 2021.03.10 + title: A Simple Graph Database + maintainer: Michael Silva + description: This is a graph database in 'SQLite'. It is inspired by Denis Papathanasiou's + Python simple-graph project on 'GitHub'. + date_publication: '2021-03-12' + bug_reports: https://github.com/mikeasilva/simplegraphdb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simplegraphdb + url_git: https://github.com/mikeasilva/simplegraphdb +simpleMH: + version: 0.1.1 + title: Simple Metropolis-Hastings MCMC Algorithm + maintainer: Hugo Gruson + description: |- + A very bare-bones interface to use the Metropolis-Hastings Monte + Carlo Markov Chain algorithm. It is suitable for teaching and testing + purposes. + date_publication: '2024-02-06' + bug_reports: https://github.com/Bisaloo/simpleMH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simpleMH + url_git: https://github.com/Bisaloo/simpleMH +simpleMLP: + version: 1.0.0 + title: Simple Multilayer Perceptron Neural Network + maintainer: Cullen Pu + description: |- + Create and train a multilayer perceptron, a type of feedforward, + fully connected neural network. Features 2 ReLU hidden layers. Learn more + about about the activation functions and backpropagation used by this + network in Goodfellow et al. (2016, ISBN: 9780262035613) "Deep Learning". + date_publication: '2021-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simpleMLP + url_git: '' +simpleNeural: + version: 0.1.3 + title: An Easy to Use Multilayer Perceptron + maintainer: David Dernoncourt + description: Trains neural networks (multilayer perceptrons with one hidden layer) + for bi- or multi-class classification. + date_publication: '2020-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simpleNeural + url_git: '' +simplePHENOTYPES: + version: 1.3.0 + title: Simulation of Pleiotropic, Linked and Epistatic Phenotypes + maintainer: Samuel Fernandes + description: The number of studies involving correlated traits and the availability + of tools to handle this type of data has increased considerably in the last decade. + With such a demand, we need tools for testing hypotheses related to single and + multi-trait (correlated) phenotypes based on many genetic settings. Thus, we implemented + various options for simulation of pleiotropy and Linkage Disequilibrium under + additive, dominance and epistatic models. The simulation currently takes a marker + data set as an input and then uses it for simulating multiple traits as described + in Fernandes and Lipka (2020) . + date_publication: '2021-01-20' + bug_reports: https://github.com/samuelbfernandes/simplePHENOTYPES/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simplePHENOTYPES + url_git: https://github.com/samuelbfernandes/simplePHENOTYPES +simpleRCache: + version: 0.3.3 + title: Simple R Cache + maintainer: Augustin Luna + description: |- + Simple result caching in R based on R.cache. The global environment is not + considered when caching results simplifying moving files between multiple instances + of R. Relies on more base functions than R.cache (e.g. cached results are saved using + saveRDS() and readRDS()). + date_publication: '2021-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simpleRCache + url_git: '' +simplermarkdown: + version: 0.0.6 + title: Simple Engine for Generating Reports using R + maintainer: Jan van der Laan + description: |- + Runs R-code present in a pandoc markdown file and + includes the resulting output in the resulting markdown file. This + file can then be converted into any of the output formats + supported by pandoc. The package can also be used as an engine + for writing package vignettes. + date_publication: '2023-03-24' + bug_reports: https://github.com/djvanderlaan/simplermarkdown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simplermarkdown + url_git: https://github.com/djvanderlaan/simplermarkdown +simpleSetup: + version: 0.1.0 + title: Set Up R Source Code Files for Use on Multiple Machines + maintainer: Christopher Gandrud + description: |- + When working across multiple machines and, similarly for + reproducible research, it can be time consuming to ensure that you have + all of the needed packages installed and loaded and that the correct working + directory is set. 'simpleSetup' provides simple functions for making these + tasks more straightforward. + date_publication: '2017-01-24' + bug_reports: https://github.com/christophergandrud/simpleSetup/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simpleSetup + url_git: '' +simpletex: + version: 1.0.4 + title: Mathematical Formulas and Character Recognition + maintainer: Xinyuan Chu + description: |- + By calling the 'SimpleTex' open API implements + text and mathematical formula recognition on the image, and the output formula + can be used directly with 'Markdown' and 'LaTeX'. + date_publication: '2024-07-07' + bug_reports: https://gitlab.com/chuxinyuan/simpletex/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simpletex + url_git: https://gitlab.com/chuxinyuan/simpletex +simplexreg: + version: '1.3' + title: |- + Regression Analysis of Proportional Data Using Simplex + Distribution + maintainer: Peng Zhang + description: |- + Simplex density, distribution, quantile functions as well as random variable + generation of the simplex distribution are given. Regression analysis of proportional data + using various kinds of simplex models is available. In addition, GEE method can be applied + to longitudinal data to model the correlation. Residual analysis is also involved. Some + subroutines are written in C with GNU Scientific Library (GSL) so as to facilitate the + computation. + date_publication: '2016-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simplexreg + url_git: '' +simplextree: + version: 1.0.1 + title: Provides Tools for Working with General Simplicial Complexes + maintainer: Matt Piekenbrock + description: |- + Provides an interface to a Simplex Tree data structure, which is + a data structure aimed at enabling efficient manipulation of simplicial complexes + of any dimension. The Simplex Tree data structure was originally introduced by + Jean-Daniel Boissonnat and Clément Maria (2014) . + date_publication: '2020-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simplextree + url_git: https://github.com/peekxc/simplextree +SimplicialCubature: + version: '1.3' + title: Integration of Functions Over Simplices + maintainer: John P. Nolan + description: |- + Provides methods to integrate functions over m-dimensional simplices + in n-dimensional Euclidean space. There are exact methods for polynomials and + adaptive methods for integrating an arbitrary function. + date_publication: '2021-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimplicialCubature + url_git: '' +simplifyNet: + version: 0.0.1 + title: Network Sparsification + maintainer: Alexander Mercier + description: |- + Network sparsification with a variety of novel and known network sparsification + techniques. All network sparsification techniques reduce the number of edges, not the number + of nodes. Network sparsification is sometimes referred to as network dimensionality reduction. + This package is based on the work of Spielman, D., Srivastava, N. (2009). + Koutis I., Levin, A., Peng, R. (2013). Toivonen, H., Mahler, S., Zhou, F. + (2010). Foti, N., Hughes, J., Rockmore, D. (2011). + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simplifyNet + url_git: '' +SimplyAgree: + version: 0.2.1 + title: Flexible and Robust Agreement and Reliability Analyses + maintainer: Aaron Caldwell + description: Reliability and agreement analyses often have limited software support. + Therefore, this package was created to make agreement and reliability analyses + easier for the average researcher. The functions within this package include simple + tests of agreement, agreement analysis for nested and replicate data, and provide + robust analyses of reliability. In addition, this package contains a set of functions + to help when planning studies looking to assess measurement agreement. + date_publication: '2025-02-24' + bug_reports: https://github.com/arcaldwell49/SimplyAgree/issues + url: https://aaroncaldwell.us/SimplyAgree/ + url_cran: https://CRAN.R-project.org/package=SimplyAgree + url_git: '' +SIMplyBee: + version: 0.4.1 + title: |- + 'AlphaSimR' Extension for Simulating Honeybee Populations and + Breeding Programmes + maintainer: Jana Obšteter + description: |- + An extension of the 'AlphaSimR' package + () for stochastic simulations of + honeybee populations and breeding programmes. 'SIMplyBee' enables simulation of + individual bees that form a colony, which includes a queen, fathers (drones + the queen mated with), virgin queens, workers, and drones. Multiple colony can + be merged into a population of colonies, such as an apiary or a whole country + of colonies. Functions enable operations on castes, colony, or colonies, to + ease 'R' scripting of whole populations. All 'AlphaSimR' functionality with + respect to genomes and genetic and phenotype values is available and further + extended for honeybees, including haplo-diploidy, complementary sex determiner + locus, colony events (swarming, supersedure, etc.), and colony phenotype values. + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIMplyBee + url_git: https://github.com/HighlanderLab/SIMplyBee +simPop: + version: 2.1.3 + title: Simulation of Complex Synthetic Data Information + maintainer: Matthias Templ + description: |- + Tools and methods to simulate populations for surveys based + on auxiliary data. The tools include model-based methods, calibration and + combinatorial optimization algorithms, see Templ, Kowarik and Meindl (2017) ) and + Templ (2017) . The package was developed with support of + the International Household Survey Network, DFID Trust Fund TF011722 and funds + from the World bank. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simPop + url_git: https://github.com/statistikat/simPop +simpr: + version: 0.2.6 + title: Flexible 'Tidyverse'-Friendly Simulations + maintainer: Ethan Brown + description: |- + A general, 'tidyverse'-friendly framework + for simulation studies, design analysis, and power analysis. + Specify data generation, define varying parameters, generate data, + fit models, and tidy model results in a single pipeline, without + needing loops or custom functions. + date_publication: '2023-04-26' + bug_reports: https://github.com/statisfactions/simpr/issues/ + url: https://statisfactions.github.io/simpr/ + url_cran: https://CRAN.R-project.org/package=simpr + url_git: https://github.com/statisfactions/simpr/ +simputation: + version: 0.2.9 + title: Simple Imputation + maintainer: Mark van der Loo + description: |- + Easy to use interfaces to a number of imputation methods + that fit in the not-a-pipe operator of the 'magrittr' package. + date_publication: '2024-12-16' + bug_reports: https://github.com/markvanderloo/simputation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simputation + url_git: https://github.com/markvanderloo/simputation +simqi: + version: 0.1.0 + title: Simulate Quantities of Interest from Regression Models + maintainer: Steve Miller + description: |- + This is an all-encompassing suite to facilitate the simulation of + so-called quantities of interest by way of a multivariate normal distribution + of the regression model's coefficients and variance-covariance matrix. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simqi + url_git: '' +simr: + version: 1.0.7 + title: Power Analysis for Generalised Linear Mixed Models by Simulation + maintainer: Peter Green + description: |- + Calculate power for generalised linear mixed models, using + simulation. Designed to work with models fit using the 'lme4' package. + Described in Green and MacLeod, 2016 . + date_publication: '2023-04-13' + bug_reports: https://github.com/pitakakariki/simr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simr + url_git: https://github.com/pitakakariki/simr +SimRDS: + version: 2.0.0 + title: Simulation of Respondent Driven Samples + maintainer: Ayesha Perera + description: |- + Simulate populations with desired + properties and extract respondent driven samples. To better understand the + usage of the package and the algorithm used, please refer to Perera, A., and + Ramanayake, A. (2019) + . + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimRDS + url_git: '' +simrec: + version: 1.0.1 + title: |- + Simulation of Recurrent Event Data for Non-Constant Baseline + Hazard + maintainer: Federico Marini + description: |- + Simulation of recurrent event data for non-constant baseline + hazard in the total time model with risk-free intervals and possibly a competing event. + Possibility to cut the data to an interim data set. Data can be plotted. + Details about the method can be found in Jahn-Eimermacher, A. et al. (2015) . + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simrec + url_git: https://github.com/federicomarini/simrec +SimReg: + version: '3.4' + title: Similarity Regression + maintainer: Daniel Greene + description: |- + Similarity regression, + evaluating the probability of association between sets of ontological terms + and binary response vector. A no-association model is compared with one in which + the log odds of a true response is linked to the semantic similarity + between terms and a latent characteristic ontological profile - 'Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases', Greene et al 2016 . + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimReg + url_git: '' +simrel: + version: 2.1.0 + title: Simulation of Multivariate Linear Model Data + maintainer: Raju Rimal + description: |- + Researchers have been using simulated data from a multivariate linear model to compare and evaluate different methods, ideas and models. Additionally, teachers and educators have been using a simulation tool to demonstrate and teach various statistical and machine learning concepts. + This package helps users to simulate linear model data with a wide range of properties by tuning few parameters such as relevant latent components. In addition, a shiny app as an 'RStudio' gadget gives users a simple interface for using the simulation function. See more on: Sæbø, S., Almøy, T., Helland, I.S. (2015) and Rimal, R., Almøy, T., Sæbø, S. (2018) . + date_publication: '2021-09-17' + bug_reports: https://github.com/simulatr/simrel/issues + url: https://simulatr.github.io/simrel/ + url_cran: https://CRAN.R-project.org/package=simrel + url_git: '' +simRestore: + version: 1.1.4 + title: |- + Simulate the Effect of Management Policies on Restoration + Efforts + maintainer: Thijs Janzen + description: |- + Simulation methods to study the effect of management policies on + efforts to restore populations back to their original genetic composition. + Allows for single-scenario simulation and for optimization of specific chosen + scenarios. Further information can be found in Hernandez, Janzen and Lavretsky + (2023) . + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simRestore + url_git: '' +SiMRiv: + version: 1.0.7 + title: |- + Simulating Multistate Movements in River/Heterogeneous + Landscapes + maintainer: Miguel Porto + description: |- + Provides functions to generate and analyze spatially-explicit individual-based multistate movements in rivers, + heterogeneous and homogeneous spaces. This is done by incorporating landscape bias on local behaviour, based on + resistance rasters. Although originally conceived and designed to simulate trajectories of species constrained to + linear habitats/dendritic ecological networks (e.g. river networks), the simulation algorithm is built to be + highly flexible and can be applied to any (aquatic, semi-aquatic or terrestrial) organism, independently on the + landscape in which it moves. Thus, the user will be able to use the package to simulate movements either in + homogeneous landscapes, heterogeneous landscapes (e.g. semi-aquatic animal moving mainly along rivers but also using + the matrix), or even in highly contrasted landscapes (e.g. fish in a river network). The algorithm and its input + parameters are the same for all cases, so that results are comparable. Simulated trajectories can then be used as + mechanistic null models (Potts & Lewis 2014, ) to test a variety of 'Movement Ecology' + hypotheses (Nathan et al. 2008, ), including landscape effects (e.g. resources, + infrastructures) on animal movement and species site fidelity, or for predictive purposes (e.g. road mortality risk, + dispersal/connectivity). The package should be relevant to explore a broad spectrum of ecological phenomena, such as + those at the interface of animal behaviour, management, landscape and movement ecology, disease and invasive species + spread, and population dynamics. + date_publication: '2024-09-10' + bug_reports: https://github.com/miguel-porto/SiMRiv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SiMRiv + url_git: https://github.com/miguel-porto/SiMRiv +sims: + version: 0.0.4 + title: Simulate Data from R or 'JAGS' Code + maintainer: Audrey Beliveau + description: |- + Generates data from R or 'JAGS' code for use in simulation + studies. The data are returned as an 'nlist::nlists' object and/or + saved to file as individual '.rds' files. Parallelization is + implemented using the 'future' package. Progress is reported using + the 'progressr' package. + date_publication: '2024-09-18' + bug_reports: https://github.com/poissonconsulting/sims/issues + url: https://poissonconsulting.github.io/sims/ + url_cran: https://CRAN.R-project.org/package=sims + url_git: https://github.com/poissonconsulting/sims +simsalapar: + version: 1.0-12 + title: Tools for Simulation Studies in Parallel + maintainer: Marius Hofert + description: |- + Tools for setting up ("design"), conducting, and evaluating + large-scale simulation studies with graphics and tables, including + parallel computations. + date_publication: '2023-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simsalapar + url_git: '' +simsem: + version: 0.5-16 + title: SIMulated Structural Equation Modeling + maintainer: Terrence D. Jorgensen + description: Provides an easy framework for Monte Carlo simulation in structural + equation modeling, which can be used for various purposes, such as such as model + fit evaluation, power analysis, or missing data handling and planning. + date_publication: '2021-03-28' + bug_reports: '' + url: https://simsem.org/ + url_cran: https://CRAN.R-project.org/package=simsem + url_git: '' +SimSeq: + version: 1.4.0 + title: Nonparametric Simulation of RNA-Seq Data + maintainer: Samuel Benidt + description: RNA sequencing analysis methods are often derived by relying on hypothetical + parametric models for read counts that are not likely to be precisely satisfied + in practice. Methods are often tested by analyzing data that have been simulated + according to the assumed model. This testing strategy can result in an overly + optimistic view of the performance of an RNA-seq analysis method. We develop a + data-based simulation algorithm for RNA-seq data. The vector of read counts simulated + for a given experimental unit has a joint distribution that closely matches the + distribution of a source RNA-seq dataset provided by the user. Users control the + proportion of genes simulated to be differentially expressed (DE) and can provide + a vector of weights to control the distribution of effect sizes. The algorithm + requires a matrix of RNA-seq read counts with large sample sizes in at least two + treatment groups. Many datasets are available that fit this standard. + date_publication: '2015-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimSeq + url_git: '' +simsl: + version: 0.2.1 + title: Single-Index Models with a Surface-Link + maintainer: Hyung Park + description: An implementation of a single-index regression for optimizing individualized + dose rules from an observational study. To model interaction effects between baseline + covariates and a treatment variable defined on a continuum, we employ two-dimensional + penalized spline regression on an index-treatment domain, where the index is defined + as a linear combination of the covariates (a single-index). An unspecified main + effect for the covariates is allowed, which can also be modeled through a parametric + model. A unique contribution of this work is in the parsimonious single-index + parametrization specifically defined for the interaction effect term. We refer + to Park, Petkova, Tarpey, and Ogden (2020) (for the case + of a discrete treatment) and Park, Petkova, Tarpey, and Ogden (2021) "A single-index + model with a surface-link for optimizing individualized dose rules" + for detail of the method. The model can take a member of the exponential family + as a response variable and can also take an ordinal categorical response. The + main function of this package is simsl(). + date_publication: '2021-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simsl + url_git: '' +SimSST: + version: 0.0.5.2 + title: Simulated Stop Signal Task Data + maintainer: Chel Hee Lee + description: 'Stop signal task data of go and stop trials is generated per participant. + The simulation process is based on the generally non-independent horse race model + and fixed stop signal delay or tracking method. Each of go and stop process is + assumed having exponentially modified Gaussian(ExG) or Shifted Wald (SW) distributions. + The output data can be converted to ''BEESTS'' software input data enabling researchers + to test and evaluate various brain stopping processes manifested by ExG or SW + distributional parameters of interest. Methods are described in: Soltanifar M + (2020) , Matzke D, Love J, Wiecki TV, Brown + SD, Logan GD and Wagenmakers E-J (2013) , Logan + GD, Van Zandt T, Verbruggen F, Wagenmakers EJ. (2014) .' + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimSST + url_git: '' +simstandard: + version: 0.6.3 + title: Generate Standardized Data + maintainer: W. Joel Schneider + description: Creates simulated data from structural equation models with standardized + loading. Data generation methods are described in Schneider (2013) . + date_publication: '2021-05-07' + bug_reports: https://github.com/wjschne/simstandard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simstandard + url_git: https://github.com/wjschne/simstandard +simStateSpace: + version: 1.2.9 + title: Simulate Data from State Space Models + maintainer: Ivan Jacob Agaloos Pesigan + description: |- + Provides a streamlined and user-friendly framework + for simulating data in state space models, + particularly when the number of subjects/units (n) exceeds one, + a scenario commonly encountered in social and behavioral sciences. + For an introduction to state space models in social and behavioral sciences, + refer to Chow, Ho, Hamaker, and Dolan (2010) . + date_publication: '2025-02-14' + bug_reports: https://github.com/jeksterslab/simStateSpace/issues + url: https://jeksterslab.github.io/simStateSpace/ + url_cran: https://CRAN.R-project.org/package=simStateSpace + url_git: https://github.com/jeksterslab/simStateSpace +simstudy: + version: 0.8.1 + title: Simulation of Study Data + maintainer: Keith Goldfeld + description: |- + Simulates data sets in order to explore modeling + techniques or better understand data generating processes. The user + specifies a set of relationships between covariates, and generates + data based on these specifications. The final data sets can represent + data from randomized control trials, repeated measure (longitudinal) + designs, and cluster randomized trials. Missingness can be generated + using various mechanisms (MCAR, MAR, NMAR). + date_publication: '2024-07-29' + bug_reports: https://github.com/kgoldfeld/simstudy/issues + url: https://kgoldfeld.github.io/simstudy/ + url_cran: https://CRAN.R-project.org/package=simstudy + url_git: https://github.com/kgoldfeld/simstudy +simsurv: + version: 1.0.0 + title: Simulate Survival Data + maintainer: Sam Brilleman + description: |- + Simulate survival times from standard parametric survival + distributions (exponential, Weibull, Gompertz), 2-component mixture + distributions, or a user-defined hazard, log hazard, cumulative hazard, + or log cumulative hazard function. Baseline covariates can be included + under a proportional hazards assumption. + Time dependent effects (i.e. non-proportional hazards) can be included by + interacting covariates with linear time or a user-defined function of time. + Clustered event times are also accommodated. + The 2-component mixture distributions can allow for a variety of flexible + baseline hazard functions reflecting those seen in practice. + If the user wishes to provide a user-defined + hazard or log hazard function then this is possible, and the resulting + cumulative hazard function does not need to have a closed-form solution. + For details see the supporting paper . + Note that this package is modelled on the 'survsim' package available in + the 'Stata' software (see Crowther and Lambert (2012) + or + Crowther and Lambert (2013) ). + date_publication: '2021-01-13' + bug_reports: https://github.com/sambrilleman/simsurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simsurv + url_git: '' +SimSurvey: + version: 0.1.6 + title: Test Surveys by Simulating Spatially-Correlated Populations + maintainer: Paul Regular + description: |- + Simulate age-structured populations that vary in space and time and + explore the efficacy of a range of built-in or user-defined sampling + protocols to reproduce the population parameters of the known population. + (See Regular et al. (2020) for more + details). + date_publication: '2023-09-19' + bug_reports: https://github.com/PaulRegular/SimSurvey/issues + url: https://paulregular.github.io/SimSurvey/ + url_cran: https://CRAN.R-project.org/package=SimSurvey + url_git: '' +SimSurvNMarker: + version: 0.1.3 + title: Simulate Survival Time and Markers + maintainer: Benjamin Christoffersen + description: |- + Provides functions to simulate from joint survival and marker + models. The user can specific all basis functions of time, random or + deterministic covariates, random or deterministic left-truncation and + right-censoring times, and model parameters. + date_publication: '2022-11-07' + bug_reports: https://github.com/boennecd/SimSurvNMarker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SimSurvNMarker + url_git: https://github.com/boennecd/SimSurvNMarker +simTargetCov: + version: 1.0.1 + title: |- + Data Transformation or Simulation with Empirical Covariance + Matrix + maintainer: Anthony Christidis + description: |- + Transforms or simulates data with a target empirical covariance matrix supplied + by the user. The method to obtain the data with the target empirical covariance + matrix is described in Section 5.1 of Christidis, Van Aelst and Zamar (2019) + . + date_publication: '2020-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simTargetCov + url_git: '' +simtimer: + version: 4.0.0 + title: Datetimes as Integers for Discrete-Event Simulations + maintainer: Adrian Staempfli + description: |- + Handles datetimes as integers for the usage inside + Discrete-Event Simulations (DES). The conversion is made using + the internally generic function as.numeric() of the base + package. DES is described in Simulation Modeling and Analysis + by Averill Law and David Kelton (1999) . + date_publication: '2019-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simtimer + url_git: http://github.com/ims-fhs/simtimer +SimTimeVar: + version: 1.0.0 + title: |- + Simulate Longitudinal Dataset with Time-Varying Correlated + Covariates + maintainer: Maya B. Mathur + description: Flexibly simulates a dataset with time-varying covariates with user-specified + exchangeable correlation structures across and within clusters. Covariates can + be normal or binary and can be static within a cluster or time-varying. Time-varying + normal variables can optionally have linear trajectories within each cluster. + See ?make_one_dataset for the main wrapper function. See Montez-Rath et al. + for methodological details. + date_publication: '2017-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimTimeVar + url_git: '' +simTool: + version: 1.1.7 + title: Conduct Simulation Studies with a Minimal Amount of Source Code + maintainer: Marsel Scheer + description: |- + Tool for statistical simulations that have two components. + One component generates the data and the other one + analyzes the data. The main aims of the package are the reduction + of the administrative source code (mainly loops and management code for the + results) and a simple applicability of the package that allows the user to + quickly learn how to work with it. Parallel computing is + also supported. Finally, convenient functions are provided to summarize the + simulation results. + date_publication: '2020-09-22' + bug_reports: https://github.com/MarselScheer/simTool/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simTool + url_git: https://github.com/MarselScheer/simTool +SimTOST: + version: 1.0.2 + title: |- + Sample Size Estimation for Bio-Equivalence Trials Through + Simulation + maintainer: Thomas Debray + description: |- + Sample size estimation for bio-equivalence trials is supported through a simulation-based approach + that extends the Two One-Sided Tests (TOST) procedure. The methodology provides flexibility in + hypothesis testing, accommodates multiple treatment comparisons, and accounts for correlated endpoints. + Users can model complex trial scenarios, including parallel and crossover designs, intra-subject variability, + and different equivalence margins. Monte Carlo simulations enable accurate estimation of power and type I error + rates, ensuring well-calibrated study designs. The statistical framework builds on established methods for + equivalence testing and multiple hypothesis testing in bio-equivalence studies, as described in Schuirmann (1987) + , Mielke et al. (2018) , Shieh (2022) + , and Sozu et al. (2015) . + Comprehensive documentation and vignettes guide users through implementation and interpretation of results. + date_publication: '2025-02-18' + bug_reports: '' + url: https://smartdata-analysis-and-statistics.github.io/SimTOST/ + url_cran: https://CRAN.R-project.org/package=SimTOST + url_git: '' +simtrait: + version: 1.1.3 + title: Simulate Complex Traits from Genotypes + maintainer: Alejandro Ochoa + description: 'Simulate complex traits given a SNP genotype matrix and model parameters + (the desired heritability, number of causal loci, and either the true ancestral + allele frequencies used to generate the genotypes or the mean kinship for a real + dataset). Emphasis on avoiding common biases due to the use of estimated allele + frequencies. The code selects random loci to be causal, constructs coefficients + for these loci and random independent non-genetic effects, and can optionally + generate random group effects. Traits can follow three models: random coefficients, + fixed effect sizes, and infinitesimal (multivariate normal). GWAS method benchmarking + functions are also provided. Described in Yao and Ochoa (2022) .' + date_publication: '2023-01-06' + bug_reports: https://github.com/OchoaLab/simtrait/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simtrait + url_git: https://github.com/OchoaLab/simtrait +simtrial: + version: 0.4.2 + title: Clinical Trial Simulation + maintainer: Yujie Zhao + description: |- + Provides some basic routines for simulating a + clinical trial. The primary intent is to provide some tools to + generate trial simulations for trials with time to event outcomes. + Piecewise exponential failure rates and piecewise constant + enrollment rates are the underlying mechanism used to simulate + a broad range of scenarios such as those presented in + Lin et al. (2020) . + However, the basic generation of data is done using pipes to allow + maximum flexibility for users to meet different needs. + date_publication: '2024-11-18' + bug_reports: https://github.com/Merck/simtrial/issues + url: https://merck.github.io/simtrial/ + url_cran: https://CRAN.R-project.org/package=simtrial + url_git: https://github.com/Merck/simtrial +simts: + version: 0.2.2 + title: Time Series Analysis Tools + maintainer: Stéphane Guerrier + description: 'A system contains easy-to-use tools as a support for time series analysis + courses. In particular, it incorporates a technique called Generalized Method + of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust + parameter estimation of time series models which is described, for example, in + Guerrier et al. (2013) . More details can also + be found in the paper linked to via the URL below.' + date_publication: '2023-08-31' + bug_reports: https://github.com/SMAC-Group/simts/issues + url: https://arxiv.org/pdf/1607.04543.pdf + url_cran: https://CRAN.R-project.org/package=simts + url_git: https://github.com/SMAC-Group/simts +simuclustfactor: + version: 0.0.3 + title: |- + Simultaneous Clustering and Factorial Decomposition of Three-Way + Datasets + maintainer: Prosper Ablordeppey + description: Implements two iterative techniques called T3Clus and 3Fkmeans, aimed + at simultaneously clustering objects and a factorial dimensionality reduction + of variables and occasions on three-mode datasets developed by Vichi et al. (2007) + . Also, we provide a convex combination of these + two simultaneous procedures called CT3Clus and based on a hyperparameter alpha + (alpha in [0,1], with 3FKMeans for alpha=0 and T3Clus for alpha= 1) also developed + by Vichi et al. (2007) . Furthermore, we implemented + the traditional tandem procedures of T3Clus (TWCFTA) and 3FKMeans (TWFCTA) for + sequential clustering-factorial decomposition (TWCFTA), and vice-versa (TWFCTA) + proposed by P. Arabie and L. Hubert (1996) . + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simuclustfactor + url_git: '' +simukde: + version: 1.3.0 + title: Simulation with Kernel Density Estimation + maintainer: MAKHGAL Ganbold + description: Generates random values from a univariate and multivariate continuous + distribution by using kernel density estimation based on a sample. Duong (2017) + , Christian P. Robert and George Casella (2010 ISBN:978-1-4419-1575-7) + . + date_publication: '2021-05-20' + bug_reports: https://github.com/galaamn/simukde/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simukde + url_git: https://github.com/galaamn/simukde +simulariatools: + version: 2.5.1 + title: Simularia Tools for the Analysis of Air Pollution Data + maintainer: Giuseppe Carlino + description: |- + A set of tools developed at Simularia for Simularia, to help + preprocessing and post-processing of meteorological and air quality data. + date_publication: '2023-11-08' + bug_reports: https://github.com/Simularia/simulariatools/issues + url: https://www.simularia.it/simulariatools/ + url_cran: https://CRAN.R-project.org/package=simulariatools + url_git: https://github.com/Simularia/simulariatools +simulator: + version: 0.2.5 + title: An Engine for Running Simulations + maintainer: Jacob Bien + description: |- + A framework for performing simulations such as those common in + methodological statistics papers. The design principles of this package + are described in greater depth in Bien, J. (2016) "The simulator: An Engine + to Streamline Simulations," which is available at . + date_publication: '2023-02-04' + bug_reports: https://github.com/jacobbien/simulator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=simulator + url_git: https://github.com/jacobbien/simulator +simule: + version: 1.3.0 + title: |- + A Constrained L1 Minimization Approach for Estimating Multiple + Sparse Gaussian or Nonparanormal Graphical Models + maintainer: Beilun Wang + description: 'This is an R implementation of a constrained l1 minimization approach + for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models (SIMULE). + The SIMULE algorithm can be used to estimate multiple related precision matrices. + For instance, it can identify context-specific gene networks from multi-context + gene expression datasets. By performing data-driven network inference from high-dimensional + and heterogenous data sets, this tool can help users effectively translate aggregated + data into knowledge that take the form of graphs among entities. Please run demo(simuleDemo) + to learn the basic functions provided by this package. For further details, please + read the original paper: Beilun Wang, Ritambhara Singh, Yanjun Qi (2017) .' + date_publication: '2018-07-02' + bug_reports: https://github.com/QData/SIMULE + url: '' + url_cran: https://CRAN.R-project.org/package=simule + url_git: https://github.com/QData/SIMULE +simulist: + version: 0.4.0 + title: Simulate Disease Outbreak Line List and Contacts Data + maintainer: Joshua W. Lambert + description: |- + Tools to simulate realistic raw case data for an epidemic in + the form of line lists and contacts using a branching process. + Simulated outbreaks are parameterised with epidemiological parameters + and can have age structured populations, age-stratified + hospitalisation and death risk and time-varying case fatality risk. + date_publication: '2025-01-10' + bug_reports: https://github.com/epiverse-trace/simulist/issues + url: https://epiverse-trace.github.io/simulist/ + url_cran: https://CRAN.R-project.org/package=simulist + url_git: https://github.com/epiverse-trace/simulist +simulMGF: + version: 0.1.1 + title: Simulate SNP Matrix, Phenotype and Genotypic Effects + maintainer: Martin Nahuel Garcia + description: Simulate genotypes in SNP (single nucleotide polymorphisms) Matrix + as random numbers from an uniform distribution, for diploid organisms (coded by + 0, 1, 2), Sikorska et al., (2013) , or half-sib/full-sib + SNP matrix from real or simulated parents SNP data, assuming mendelian segregation. + Simulate phenotypic traits for real or simulated SNP data, controlled by a specific + number of quantitative trait loci and their effects, sampled from a Normal or + an Uniform distributions, assuming a pure additive model. This is useful for testing + association and genomic prediction models or for educational purposes. + date_publication: '2023-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=simulMGF + url_git: https://github.com/mngar/simulMGF +SimVitD: + version: 1.0.3 + title: Simulation Tools for Planning Vitamin D Studies + maintainer: Jason Wyse + description: |- + Simulation tools for planning Vitamin D studies. Individual vitamin D status + profiles are simulated, modelling population heterogeneity in trial arms. + Exposures to infectious agents are generated, with infection depending on vitamin D status. + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SimVitD + url_git: '' +sinaplot: + version: 1.1.0 + title: |- + An Enhanced Chart for Simple and Truthful Representation of + Single Observations over Multiple Classes + maintainer: Nikos Sidiropoulos + description: |- + The sinaplot is a data visualization chart suitable for plotting + any single variable in a multiclass data set. It is an enhanced jitter strip + chart, where the width of the jitter is controlled by the density + distribution of the data within each class. + date_publication: '2017-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sinaplot + url_git: '' +sinar: + version: 0.1.0 + title: Conditional Least Squared (CLS) Method for the Model SINAR(1,1) + maintainer: Gilberto P. Sassi + description: |- + Implementation of the Conditional Least Square (CLS) estimates and + its covariance matrix for the first-order spatial integer-valued + autoregressive model (SINAR(1,1)) proposed by Ghodsi (2012) + . + date_publication: '2020-11-06' + bug_reports: https://github.com/gilberto-sassi/sinar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sinar + url_git: '' +sindyr: + version: 0.2.4 + title: Sparse Identification of Nonlinear Dynamics + maintainer: Rick Dale + description: |- + This implements the Brunton et al (2016; PNAS ) sparse + identification algorithm for finding ordinary differential equations for a measured + system from raw data (SINDy). The package includes a set of additional tools for + working with raw data, with an emphasis on cognitive science applications (Dale + and Bhat, 2018 ). See + for examples and updates. + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sindyr + url_git: '' +sinew: + version: 0.4.0 + title: Package Development Documentation and Namespace Management + maintainer: Jonathan Sidi + description: |- + Manage package documentation and namespaces from the command line. + Programmatically attach namespaces in R and Rmd script, populates + 'Roxygen2' skeletons with information scraped from within functions and + populate the Imports field of the DESCRIPTION file. + date_publication: '2022-03-31' + bug_reports: https://github.com/yonicd/sinew/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sinew + url_git: https://github.com/yonicd/sinew +singcar: + version: 0.1.5 + title: Comparing Single Cases to Small Samples + maintainer: Jonathan Rittmo + description: When comparing single cases to control populations and no parameters + are known researchers and clinicians must estimate these with a control sample. + This is often done when testing a case's abnormality on some variable or testing + abnormality of the discrepancy between two variables. Appropriate frequentist + and Bayesian methods for doing this are here implemented, including tests allowing + for the inclusion of covariates. These have been developed first and foremost + by John Crawford and Paul Garthwaite, e.g. in Crawford and Howell (1998) , + Crawford and Garthwaite (2005) , Crawford and + Garthwaite (2007) and Crawford, Garthwaite and + Ryan (2011) . The package is also equipped with + power calculators for each method. + date_publication: '2023-03-16' + bug_reports: https://github.com/jorittmo/singcar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=singcar + url_git: https://github.com/jorittmo/singcar +SingleCaseES: + version: 0.7.3 + title: A Calculator for Single-Case Effect Sizes + maintainer: James E. Pustejovsky + description: |- + Provides R functions for calculating basic effect size indices for + single-case designs, including several non-overlap measures and parametric + effect size measures, and for estimating the gradual effects model developed + by Swan and Pustejovsky (2018) . + Standard errors and confidence intervals (based on the assumption that the outcome + measurements are mutually independent) are provided for the subset of effect sizes + indices with known sampling distributions. + date_publication: '2024-09-07' + bug_reports: https://github.com/jepusto/SingleCaseES/issues + url: https://jepusto.github.io/SingleCaseES/ + url_cran: https://CRAN.R-project.org/package=SingleCaseES + url_git: '' +singleCellHaystack: + version: 1.0.2 + title: |- + A Universal Differential Expression Prediction Tool for + Single-Cell and Spatial Genomics Data + maintainer: Alexis Vandenbon + description: |- + One key exploratory analysis step in single-cell genomics data analysis + is the prediction of features with different activity levels. For example, we want + to predict differentially expressed genes (DEGs) in single-cell RNA-seq data, + spatial DEGs in spatial transcriptomics data, or differentially accessible + regions (DARs) in single-cell ATAC-seq data. 'singleCellHaystack' predicts differentially + active features in single cell omics datasets without relying on the clustering + of cells into arbitrary clusters. 'singleCellHaystack' uses Kullback-Leibler + divergence to find features (e.g., genes, genomic regions, etc) that are active + in subsets of cells that are non-randomly positioned inside an input space (such as + 1D trajectories, 2D tissue sections, multi-dimensional embeddings, etc). For + the theoretical background of 'singleCellHaystack' we refer to our original paper + Vandenbon and Diez (Nature Communications, 2020) + and our update Vandenbon and Diez (Scientific Reports, 2023) . + date_publication: '2024-01-11' + bug_reports: https://github.com/alexisvdb/singleCellHaystack/issues + url: https://alexisvdb.github.io/singleCellHaystack/ + url_cran: https://CRAN.R-project.org/package=singleCellHaystack + url_git: https://github.com/alexisvdb/singleCellHaystack +singleRcapture: + version: 0.2.3 + title: Single-Source Capture-Recapture Models + maintainer: Maciej Beręsewicz + description: 'Implementation of single-source capture-recapture methods for population + size estimation using zero-truncated, zero-one truncated and zero-truncated one-inflated + Poisson, Geometric and Negative Binomial regression as well as Zelterman''s and + Chao''s regression. Package includes point and interval estimators for the population + size with variances estimated using analytical or bootstrap method. Details can + be found in: van der Heijden et all. (2003) , Böhning + and van der Heijden (2019) , Böhning et al. (2020) Capture-Recapture + Methods for the Social and Medical Sciences or Böhning and Friedl (2021) .' + date_publication: '2025-02-13' + bug_reports: https://github.com/ncn-foreigners/singleRcapture/issues + url: '' + url_cran: https://CRAN.R-project.org/package=singleRcapture + url_git: https://github.com/ncn-foreigners/singleRcapture +singR: + version: 0.1.3 + title: Simultaneous Non-Gaussian Component Analysis + maintainer: Liangkang Wang + description: Implementation of SING algorithm to extract joint and individual non-Gaussian + components from two datasets. SING uses an objective function that maximizes the + skewness and kurtosis of latent components with a penalty to enhance the similarity + between subject scores. Unlike other existing methods, SING does not use PCA for + dimension reduction, but rather uses non-Gaussianity, which can improve feature + extraction. Benjamin B.Risk, Irina Gaynanova (2021) . + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=singR + url_git: '' +sinib: + version: 1.0.0 + title: Sum of Independent Non-Identical Binomial Random Variables + maintainer: Boxiang Liu + description: |- + Density, distribution function, quantile function + and random generation for the sum of independent non-identical + binomial distribution with parameters \code{size} and \code{prob}. + date_publication: '2017-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sinib + url_git: '' +SINRELEF.LD: + version: 1.1.0 + title: |- + Reliability and Relative Efficiency in Locally-Dependent + Measures + maintainer: David Navarro-Gonzalez + description: |- + Implements an approach aimed at assessing the accuracy and + effectiveness of raw scores obtained in scales that contain locally dependent + items. The program uses as input the calibration (structural) item estimates + obtained from fitting extended unidimensional factor-analytic solutions in + which the existing local dependencies are included. Measures of reliability + (Omega) and information are proposed at three levels: (a) total score, (b) + bivariate-doublet, and (c) item-by-item deletion, and are compared to those + that would be obtained if all the items had been locally independent. All the + implemented procedures can be obtained from: (a) linear factor-analytic + solutions in which the item scores are treated as approximately continuous, + and (b) non-linear solutions in which the item scores are treated as + ordered-categorical. A detailed guide can be obtained at the following url. + date_publication: '2024-06-09' + bug_reports: '' + url: https://psico.fcep.urv.cat/utilitats/SINRELEF-LD/ + url_cran: https://CRAN.R-project.org/package=SINRELEF.LD + url_git: '' +SIPDIBGE: + version: 0.2.1 + title: Collection of Household Survey Packages Conducted by IBGE + maintainer: Gabriel Assuncao + description: |- + Provides access to packages developed for downloading, reading and analyzing + microdata from household surveys in Integrated System of Household Surveys - SIPD + conducted by Brazilian Institute of Geography and Statistics - IBGE. + More information can be obtained from the official website . + date_publication: '2024-02-01' + bug_reports: https://github.com/Gabriel-Assuncao/SIPDIBGE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SIPDIBGE + url_git: '' +SIPETool: + version: 0.1.0 + title: SIFT-MS and CPET Data Processor + maintainer: Federico Vivaldi + description: |- + Processor for selected ion flow tube mass spectrometer + (SIFT-MS) output file from breath analysis. It allows the filtering of the SIFT output file (i.e., variation + over time of the target analyte concentration) and the following + analysis for the determination of: maximum, average, and standard deviation + value of target concentration measured at each exhalation, and the + respiratory rate over the measurement. Additionally, it is possible to + align the SIFT-MS data with other on-line techniques such as + cardio pulmonary exercise test (CPET) for a comprehensive + characterization of breath samples. + date_publication: '2023-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIPETool + url_git: '' +SiPhyNetwork: + version: 1.1.0 + title: A Phylogenetic Simulator for Reticulate Evolution + maintainer: Joshua Justison + description: 'A simulator for reticulate evolution under a birth-death-hybridization + process. Here the birth-death process is extended to consider reticulate Evolution + by allowing hybridization events to occur. The general purpose simulator allows + the modeling of three different reticulate patterns: lineage generative hybridization, + lineage neutral hybridization, and lineage degenerative hybridization. Users can + also specify hybridization events to be dependent on a trait value or genetic + distance. We also extend some phylogenetic tree utility and plotting functions + for networks. We allow two different stopping conditions: simulated to a fixed + time or number of taxa. When simulating to a fixed number of taxa, the user can + simulate under the Generalized Sampling Approach that properly simulates phylogenies + when assuming a uniform prior on the root age.' + date_publication: '2023-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SiPhyNetwork + url_git: '' +siplab: + version: '1.6' + title: Spatial Individual-Plant Modelling + maintainer: Oscar Garcia + description: |- + A platform for computing competition indices and experimenting + with spatially explicit individual-based vegetation models. + date_publication: '2022-03-07' + bug_reports: https://github.com/ogarciav/siplab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=siplab + url_git: https://github.com/ogarciav/siplab/ +siqr: + version: 0.8.1 + title: An R Package for Single-Index Quantile Regression + maintainer: Tianhai Zu + description: Single-Index Quantile Regression is effective in some scenarios. We + provides functions that allow users to fit Single-Index Quantile Regression model. + It also provides functions to do prediction, estimate standard errors of the single-index + coefficients via bootstrap, and visualize the estimated univariate function. Please + see W., Y., Y. (2010) for details. + date_publication: '2021-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siqr + url_git: '' +sirad: + version: 2.3-3 + title: |- + Functions for Calculating Daily Solar Radiation and + Evapotranspiration + maintainer: Jedrzej S. Bojanowski + description: Calculating daily global solar radiation at horizontal surface using + several well-known models (i.e. Angstrom-Prescott, Supit-Van Kappel, Hargreaves, + Bristow and Campbell, and Mahmood-Hubbard), and model calibration based on ground-truth + data, and (3) model auto-calibration. The FAO Penmann-Monteith equation to calculate + evapotranspiration is also included. + date_publication: '2016-10-18' + bug_reports: '' + url: http://mars.jrc.ec.europa.eu/mars/Projects/Solar-Radiation-in-MCYFS + url_cran: https://CRAN.R-project.org/package=sirad + url_git: http://sirad.r-forge.r-project.org/ +SIRE: + version: 1.1.0 + title: |- + Finding Feedback Effects in SEM and Testing for Their + Significance + maintainer: Gianmarco Vacca + description: |- + Provides two main functionalities. + 1 - Given a system of simultaneous equation, + it decomposes the matrix of coefficients weighting the endogenous variables + into three submatrices: one includes the subset of coefficients that have a causal nature + in the model, two include the subset of coefficients that have a interdependent nature + in the model, either at systematic level or induced by the correlation between error terms. + 2 - Given a decomposed model, + it tests for the significance of the interdependent relationships acting in the system, + via Maximum likelihood and Wald test, which can be built starting from the function output. + For theoretical reference see Faliva (1992) and + Faliva and Zoia (1994) . + date_publication: '2019-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIRE + url_git: '' +siren: + version: 1.0.5 + title: |- + Hybrid FA-CFA for Controlling Acquiescence in Restricted + Factorial Solutions + maintainer: David Navarro-Gonzalez + description: Performs hybrid multi-stage factor analytic procedure for controlling + acquiescence in restricted solutions (Ferrando & Lorenzo-Seva, 2000 ). + date_publication: '2024-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siren + url_git: '' +SIRmcmc: + version: 1.1.1 + title: |- + Compartmental Susceptible-Infectious-Recovered (SIR) Model of + Community and Household Infection + maintainer: F Scott Dahlgren + description: 'We build an Susceptible-Infectious-Recovered (SIR) model where the + rate of infection is the sum of the household rate and the community rate. We + estimate the posterior distribution of the parameters using the Metropolis algorithm. + Further details may be found in: F Scott Dahlgren, Ivo M Foppa, Melissa S Stockwell, + Celibell Y Vargas, Philip LaRussa, Carrie Reed (2021) "Household transmission + of influenza A and B within a prospective cohort during the 2013-2014 and 2014-2015 + seasons" .' + date_publication: '2024-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIRmcmc + url_git: '' +sirt: + version: 4.1-15 + title: Supplementary Item Response Theory Models + maintainer: Alexander Robitzsch + description: |2- + + Supplementary functions for item response models aiming + to complement existing R packages. The functionality includes among others + multidimensional compensatory and noncompensatory IRT models + (Reckase, 2009, ), + MCMC for hierarchical IRT models and testlet models + (Fox, 2010, ), + NOHARM (McDonald, 1982, ), + Rasch copula model (Braeken, 2011, ; + Schroeders, Robitzsch & Schipolowski, 2014, ), + faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011, + ), + ordinal IRT model (ISOP; Scheiblechner, 1995, ), + DETECT statistic (Stout, Habing, Douglas & Kim, 1996, + ), local structural equation modeling + (LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016, + ). + date_publication: '2024-02-06' + bug_reports: '' + url: https://sites.google.com/view/alexander-robitzsch/software + url_cran: https://CRAN.R-project.org/package=sirt + url_git: https://github.com/alexanderrobitzsch/sirt +SIRthresholded: + version: 1.0.2 + title: Sliced Inverse Regression with Thresholding + maintainer: Clement Weinreich + description: Implements a thresholded version of the Sliced Inverse Regression method + (Li, K. C. (1991) ), which allows to do variable selection. + date_publication: '2023-06-09' + bug_reports: '' + url: https://clement-w.github.io/SIRthresholded/ + url_cran: https://CRAN.R-project.org/package=SIRthresholded + url_git: '' +sirus: + version: 0.3.3 + title: Stable and Interpretable RUle Set + maintainer: Clement Benard + description: 'A regression and classification algorithm based on random forests, + which takes the form of a short list of rules. SIRUS combines the simplicity of + decision trees with a predictivity close to random forests. The core aggregation + principle of random forests is kept, but instead of aggregating predictions, SIRUS + aggregates the forest structure: the most frequent nodes of the forest are selected + to form a stable rule ensemble model. The algorithm is fully described in the + following articles: Benard C., Biau G., da Veiga S., Scornet E. (2021), Electron. + J. Statist., 15:427-505 for classification, and Benard + C., Biau G., da Veiga S., Scornet E. (2021), AISTATS, PMLR 130:937-945 , + for regression. This R package is a fork from the project ranger ().' + date_publication: '2022-06-13' + bug_reports: https://gitlab.com/drti/sirus/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sirus + url_git: https://gitlab.com/drti/sirus +SIS: + version: 0.8-8 + title: Sure Independence Screening + maintainer: Yang Feng + description: |- + Variable selection techniques are essential tools for model + selection and estimation in high-dimensional statistical models. Through this + publicly available package, we provide a unified environment to carry out + variable selection using iterative sure independence screening (SIS) (Fan and Lv (2008)) and all + of its variants in generalized linear models (Fan and Song (2009)) and the Cox proportional hazards + model (Fan, Feng and Wu (2010)). + date_publication: '2020-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SIS + url_git: '' +sisal: + version: '0.49' + title: Sequential Input Selection Algorithm + maintainer: Mikko Korpela + description: |- + Implements the SISAL algorithm by Tikka and Hollmén. It is + a sequential backward selection algorithm which uses a linear + model in a cross-validation setting. Starting from the full + model, one variable at a time is removed based on the + regression coefficients. From this set of models, a + parsimonious (sparse) model is found by choosing the model with + the smallest number of variables among those models where the + validation error is smaller than a threshold. Also implements + extensions which explore larger parts of the search space + and/or use ridge regression instead of ordinary least squares. + date_publication: '2024-10-26' + bug_reports: https://github.com/mvkorpel/sisal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sisal + url_git: https://github.com/mvkorpel/sisal +SISIR: + version: 0.2.3 + title: Select Intervals Suited for Functional Regression + maintainer: Nathalie Vialaneix + description: |- + Interval fusion and selection procedures for regression with + functional inputs. Methods include a semiparametric approach based + on Sliced Inverse Regression (SIR), as described in + (standard ridge and sparse SIR are + also included in the package) and a random forest based approach, + as described in . + date_publication: '2024-08-16' + bug_reports: https://forgemia.inra.fr/sfcb/sisir/-/issues + url: https://forgemia.inra.fr/sfcb/sisir + url_cran: https://CRAN.R-project.org/package=SISIR + url_git: '' +sisireg: + version: 1.1.2 + title: Sign-Simplicity-Regression-Solver + maintainer: Lars Metzner + description: 'Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression + model is a nonparametric statistical model which is based on residual signs and + simplicity assumptions on the regression function. Goal is to calculate the most + parsimonious regression function satisfying the statistical adequacy requirements. + Theory and functions are specified in Metzner (2020, ISBN: 979-8-68239-420-3, + "Trendbasierte Prognostik") and Metzner (2021, ISBN: 979-8-59347-027-0, "Adäquates + Maschinelles Lernen").' + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sisireg + url_git: '' +sistec: + version: 0.2.0 + title: Tools to Analyze 'Sistec' Datasets + maintainer: Samuel Macêdo + description: |- + The Brazilian system for diploma registration and validation on technical and superior + courses are managing by 'Sistec' platform, see . This package provides + tools for Brazilian institutions to update the student's registration and make data analysis + about their situation, retention and drop out. + date_publication: '2020-10-26' + bug_reports: https://github.com/r-ifpe/sistec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sistec + url_git: https://github.com/r-ifpe/sistec +sisti: + version: 0.0.1 + title: Real-Time PCR Data Sets by Sisti et al. (2010) + maintainer: Ramiro Magno + description: |- + This data package contains four datasets of quantitative PCR (qPCR) + amplification curves that were used as supplementary data in the research + article by Sisti et al. (2010), . + The primary dataset comprises a ten-fold dilution series spanning + copy numbers from 3.14 × 10^7 to 3.14 × 10^2, with twelve replicates per + concentration. These samples are based on a pGEM-T Promega plasmid containing + a 104 bp fragment of the mitochondrial gene NADH dehydrogenase 1 (MT-ND1), + amplified using the ND1/ND2 primer pair. The remaining three datasets contain + qPCR results in the presence of specific PCR inhibitors: tannic acid, + immunoglobulin G (IgG), and quercetin, respectively, to assess their effects + on the amplification process. These datasets are useful for researchers + interested in PCR kinetics. The original raw data file is available as + Additional File 1: + . + date_publication: '2024-04-28' + bug_reports: https://github.com/ramiromagno/sisti/issues + url: https://rmagno.eu/sisti/ + url_cran: https://CRAN.R-project.org/package=sisti + url_git: https://github.com/ramiromagno/sisti +sistmr: + version: 0.1.1 + title: |- + A Collection of Utility Function from the Inserm/Inria SISTM + Team + maintainer: Mélanie Huchon + description: Functions common to members of the SISTM team. + date_publication: '2022-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sistmr + url_git: '' +sisVIVE: + version: '1.4' + title: Some Invalid Some Valid Instrumental Variables Estimator + maintainer: Hyunseung Kang + description: Selects invalid instruments amongst a candidate of potentially bad + instruments. The algorithm selects potentially invalid instruments and provides + an estimate of the causal effect between exposure and outcome. + date_publication: '2017-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sisVIVE + url_git: '' +SIT: + version: 0.1.1 + title: Association Measurement Through Sliced Independence Test (SIT) + maintainer: Canyi Chen + description: |- + Computes the sit coefficient between two vectors x and y, + possibly all paired coefficients for a matrix. The reference for the methods implemented here is + Zhang, Yilin, Canyi Chen, and Liping Zhu. 2022. "Sliced Independence Test." Statistica Sinica. . + This package incorporates the Galton peas example. + date_publication: '2024-10-16' + bug_reports: https://github.com/canyi-chen/SIT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SIT + url_git: https://github.com/canyi-chen/SIT +sitar: + version: 1.4.0 + title: |- + Super Imposition by Translation and Rotation Growth Curve + Analysis + maintainer: Tim Cole + description: |- + Functions for fitting and plotting SITAR (Super + Imposition by Translation And Rotation) growth curve models. SITAR is + a shape-invariant model with a regression B-spline mean curve and + subject-specific random effects on both the measurement and age + scales. The model was first described by Lindstrom (1995) + and developed as the SITAR method by Cole + et al (2010) . + date_publication: '2023-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sitar + url_git: https://github.com/statist7/sitar +sitepickR: + version: 0.0.1 + title: Two-Level Sample Selection with Optimal Site Replacement + maintainer: Elena Badillo-Goicoechea + description: Carries out a two-level sample selection where the possibility of an + initially selected site not wanting to participate is anticipated, and the site + is optimally replaced. The procedure aims to reduce bias (and/or loss of external + validity) with respect to the target population. In selecting units and sub-units, + 'sitepickR' uses the cube method developed by 'Deville & Tillé', (2004) + and described in Tillé (2011) . + The cube method is a probability sampling method that is designed to satisfy criteria + for balance between the sample and the population. Recent research has shown that + this method performs well in simulations for studies of educational programs (see + Fay & Olsen (2021, under review). To implement the cube method, 'sitepickR' uses + the sampling R package . To implement + statistical matching, 'sitepickR' uses the 'MatchIt' R package . + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sitepickR + url_git: '' +siteymlgen: + version: 1.0.0 + title: Automatically Generate _site.yml File for 'R Markdown' + maintainer: Adam Cribbs + description: |- + The goal of 'siteymlgen' is to make it easy to organise + the building of your 'R Markdown' website. + The init() function placed within the first code chunk of the index.Rmd + file of an 'R' project directory will initiate the generation of an automatically + written _site.yml file. 'siteymlgen' recommends a specific naming + convention for your 'R Markdown' files. This naming will ensure that + your navbar layout is ordered according to a hierarchy. + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=siteymlgen + url_git: https://github.com/Acribbs/siteymlgen +SITH: + version: 1.1.0 + title: A Spatial Model of Intra-Tumor Heterogeneity + maintainer: Phillip B. Nicol + description: Implements a three-dimensional stochastic model of cancer growth and + mutation similar to the one described in Waclaw et al. (2015) . + Allows for interactive 3D visualizations of the simulated tumor. Provides a comprehensive + summary of the spatial distribution of mutants within the tumor. Contains functions + which create synthetic sequencing datasets from the generated tumor. + date_publication: '2021-01-05' + bug_reports: https://github.com/phillipnicol/SITH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SITH + url_git: https://github.com/phillipnicol/SITH +sitmo: + version: 2.0.2 + title: |- + Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header + Files + maintainer: James Balamuta + description: |- + Provided within are two high quality and fast PPRNGs that may be + used in an 'OpenMP' parallel environment. In addition, there is a generator + for one dimensional low-discrepancy sequence. The objective of this library + to consolidate the distribution of the 'sitmo' (C++98 & C++11), 'threefry' and + 'vandercorput' (C++11-only) engines on CRAN by enabling others to link to the + header files inside of 'sitmo' instead of including a copy of each engine + within their individual package. Lastly, the package contains example + implementations using the 'sitmo' package and three accompanying vignette that + provide additional information. + date_publication: '2021-10-13' + bug_reports: https://github.com/coatless/sitmo/issues + url: http://thecoatlessprofessor.com/projects/sitmo/ + url_cran: https://CRAN.R-project.org/package=sitmo + url_git: https://github.com/coatless/sitmo +sitools: + version: '1.4' + title: Format a number to a string with SI prefix + maintainer: Jonas Stein + description: |- + Format a number (or a list of numbers) to a string (or a + list of strings) with SI prefix. Use SI prefixes as constants + like (4 * milli)^2 + date_publication: '2012-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sitools + url_git: '' +sitree: + version: 0.1-14 + title: Single Tree Simulator + maintainer: Clara Anton Fernandez + description: Framework to build an individual tree simulator. + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sitree + url_git: '' +sitreeE: + version: 0.0-8 + title: Sitree Extensions + maintainer: Clara Anton Fernandez + description: Provides extensions for package 'sitree' for allometric variables, + growth, mortality, recruitment, management, tree removal and external modifiers + functions. + date_publication: '2021-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sitreeE + url_git: '' +sits: + version: 1.5.2 + title: |- + Satellite Image Time Series Analysis for Earth Observation Data + Cubes + maintainer: Gilberto Camara + description: |- + An end-to-end toolkit for land use and land cover classification + using big Earth observation data. Builds satellite image data cubes from cloud collections. + Supports visualization methods for images and time series and + smoothing filters for dealing with noisy time series. + Includes functions for quality assessment of training samples using self-organized maps and + to reduce training samples imbalance. Provides machine learning algorithms including support vector machines, + random forests, extreme gradient boosting, multi-layer perceptrons, + temporal convolution neural networks, and temporal attention encoders. + Performs efficient classification of big Earth observation data cubes and includes + functions for post-classification smoothing based on Bayesian inference. + Enables best practices for estimating area and assessing accuracy of land change. + Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core. + date_publication: '2025-02-12' + bug_reports: https://github.com/e-sensing/sits/issues + url: https://e-sensing.github.io/sitsbook/ + url_cran: https://CRAN.R-project.org/package=sits + url_git: https://github.com/e-sensing/sits/ +sivirep: + version: 1.0.1 + title: Data Wrangling and Automated Reports from 'SIVIGILA' Source + maintainer: Geraldine Gómez-Millán + description: |- + Data wrangling, pre-processing, and generating automated reports + from Colombia's epidemiological surveillance system, + 'SIVIGILA' . It provides a + customizable R Markdown template for analysis and automatic + generation of epidemiological reports that can be adapted to local, + regional, and national contexts. This tool offers a standardized and + reproducible workflow that helps to reduce manual labor and potential + errors in report generation, improving their efficiency and consistency. + date_publication: '2024-12-03' + bug_reports: https://github.com/epiverse-trace/sivirep/issues + url: https://epiverse-trace.github.io/sivirep/ + url_cran: https://CRAN.R-project.org/package=sivirep + url_git: https://github.com/epiverse-trace/sivirep +sivs: + version: 0.2.10 + title: Stable Iterative Variable Selection + maintainer: Mehrad Mahmoudian + description: |- + An iterative feature selection method (manuscript submitted) that + internally utilizes various Machine Learning methods that have embedded + feature reduction in order to shrink down the feature space into a small + and yet robust set. + date_publication: '2023-10-31' + bug_reports: https://github.com/mmahmoudian/sivs/issues + url: https://doi.org/10.1093/bioinformatics/btab501 + url_cran: https://CRAN.R-project.org/package=sivs + url_git: https://github.com/mmahmoudian/sivs +SixSigma: + version: 0.11.1 + title: Six Sigma Tools for Quality Control and Improvement + maintainer: Emilio L. Cano + description: |- + Functions and utilities to perform + Statistical Analyses in the Six Sigma way. + Through the DMAIC cycle (Define, Measure, Analyze, Improve, Control), + you can manage several Quality Management studies: + Gage R&R, Capability Analysis, Control Charts, Loss Function Analysis, + etc. Data frames used in the books "Six Sigma with R" [ISBN 978-1-4614-3652-2] + and "Quality Control with R" [ISBN 978-3-319-24046-6], + are also included in the package. + date_publication: '2023-08-22' + bug_reports: https://github.com/emilopezcano/SixSigma/issues/ + url: https://www.sixsigmawithr.com/ + url_cran: https://CRAN.R-project.org/package=SixSigma + url_git: https://github.com/emilopezcano/SixSigma/ +SizeEstimation: + version: 1.1.1 + title: |- + Estimating the Sizes of Populations at Risk of HIV Infection + from Multiple Data Sources Using a Bayesian Hierarchical Model + maintainer: Kyongwon Kim + description: This function develops an algorithm for presenting a Bayesian hierarchical + model for estimating the sizes of local and national drug injected populations + in Bangladesh. The model incorporates multiple commonly used data sources including + mapping data, surveys, interventions, capture-recapture data, estimates or guesstimates + from organizations, and expert opinion. + date_publication: '2016-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SizeEstimation + url_git: '' +sizeMat: + version: 1.1.2 + title: Estimate Size at Sexual Maturity + maintainer: Josymar Torrejon-Magallanes + description: Estimate morphometric and gonadal size at sexual maturity for organisms, + usually fish and invertebrates. It includes methods for classification based on + relative growth (using principal components analysis, hierarchical clustering, + discriminant analysis), logistic regression (Frequentist or Bayes), parameters + estimation and some basic plots. + date_publication: '2020-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sizeMat + url_git: '' +SiZer: + version: 0.1-8 + title: Significant Zero Crossings + maintainer: Derek Sonderegger + description: |- + Calculates and plots the SiZer map for scatterplot data. A + SiZer map is a way of examining when the p-th derivative of a + scatterplot-smoother is significantly negative, possibly zero or + significantly positive across a range of smoothing bandwidths. + date_publication: '2022-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SiZer + url_git: https://github.com/dereksonderegger/SiZer +sjdbc: + version: 1.6.1 + title: JDBC Driver Interface + maintainer: Joe Roberts + description: Provides a database-independent JDBC interface. + date_publication: '2021-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sjdbc + url_git: '' +sjlabelled: + version: 1.2.0 + title: Labelled Data Utility Functions + maintainer: Daniel Lüdecke + description: |- + Collection of functions dealing with labelled data, like reading and + writing data between R and other statistical software packages like 'SPSS', + 'SAS' or 'Stata', and working with labelled data. This includes easy ways + to get, set or change value and variable label attributes, to convert + labelled vectors into factors or numeric (and vice versa), or to deal with + multiple declared missing values. + date_publication: '2022-04-10' + bug_reports: https://github.com/strengejacke/sjlabelled/issues + url: https://strengejacke.github.io/sjlabelled/ + url_cran: https://CRAN.R-project.org/package=sjlabelled + url_git: '' +sjmisc: + version: 2.8.10 + title: Data and Variable Transformation Functions + maintainer: Daniel Lüdecke + description: |- + Collection of miscellaneous utility functions, supporting data + transformation tasks like recoding, dichotomizing or grouping variables, + setting and replacing missing values. The data transformation functions + also support labelled data, and all integrate seamlessly into a + 'tidyverse'-workflow. + date_publication: '2024-05-13' + bug_reports: https://github.com/strengejacke/sjmisc/issues + url: https://strengejacke.github.io/sjmisc/ + url_cran: https://CRAN.R-project.org/package=sjmisc + url_git: '' +sjPlot: + version: 2.8.17 + title: Data Visualization for Statistics in Social Science + maintainer: Daniel Lüdecke + description: |- + Collection of plotting and table output functions for data + visualization. Results of various statistical analyses (that are commonly used + in social sciences) can be visualized using this package, including simple and + cross tabulated frequencies, histograms, box plots, (generalized) linear models, + mixed effects models, principal component analysis and correlation matrices, + cluster analyses, scatter plots, stacked scales, effects plots of regression + models (including interaction terms) and much more. This package supports + labelled data. + date_publication: '2024-11-29' + bug_reports: https://github.com/strengejacke/sjPlot/issues + url: https://strengejacke.github.io/sjPlot/ + url_cran: https://CRAN.R-project.org/package=sjPlot + url_git: '' +sjSDM: + version: 1.0.6 + title: Scalable Joint Species Distribution Modeling + maintainer: Maximilian Pichler + description: A scalable and fast method for estimating joint Species Distribution + Models (jSDMs) for big community data, including eDNA data. The package estimates + a full (i.e. non-latent) jSDM with different response distributions (including + the traditional multivariate probit model). The package allows to perform variation + partitioning (VP) / ANOVA on the fitted models to separate the contribution of + environmental, spatial, and biotic associations. In addition, the total R-squared + can be further partitioned per species and site to reveal the internal metacommunity + structure, see Leibold et al., . The internal structure + can then be regressed against environmental and spatial distinctiveness, richness, + and traits to analyze metacommunity assembly processes. The package includes + support for accounting for spatial autocorrelation and the option to fit responses + using deep neural networks instead of a standard linear predictor. As described + in Pichler & Hartig (2021) , scalability is achieved + by using a Monte Carlo approximation of the joint likelihood implemented via 'PyTorch' + and 'reticulate', which can be run on CPUs or GPUs. + date_publication: '2024-08-19' + bug_reports: https://github.com/TheoreticalEcology/s-jSDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sjSDM + url_git: https://github.com/TheoreticalEcology/s-jSDM/ +sjstats: + version: 0.19.0 + title: |- + Collection of Convenient Functions for Common Statistical + Computations + maintainer: Daniel Lüdecke + description: |- + Collection of convenient functions for common statistical computations, + which are not directly provided by R's base or stats packages. + This package aims at providing, first, shortcuts for statistical measures, + which otherwise could only be calculated with additional effort + (like Cramer's V, Phi, or effect size statistics like Eta or Omega squared), + or for which currently no functions available. Second, another focus + lies on weighted variants of common statistical measures and tests + like weighted standard error, mean, t-test, correlation, and more. + date_publication: '2024-05-14' + bug_reports: https://github.com/strengejacke/sjstats/issues + url: https://strengejacke.github.io/sjstats/ + url_cran: https://CRAN.R-project.org/package=sjstats + url_git: '' +sjtable2df: + version: 0.0.3 + title: Convert 'sjPlot' HTML-Tables to R 'data.frame' + maintainer: Lorenz A. Kapsner + description: |- + A small set of helper functions to convert 'sjPlot' + HTML-tables to R data.frame objects / knitr::kable-tables. + date_publication: '2023-04-13' + bug_reports: https://github.com/kapsner/sjtable2df/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sjtable2df + url_git: https://github.com/kapsner/sjtable2df +SK4FGA: + version: 0.1.1 + title: Scott-Knott for Forensic Glass Analysis + maintainer: Toby Hayward + description: |- + In forensics, it is common and effective practice to analyse glass fragments from the scene and suspects + to gain evidence of placing a suspect at the crime scene. + This kind of analysis involves comparing the physical and chemical attributes of glass fragments that exist on both the + person and at the crime scene, and assessing the significance in a likeness that they share. + The package implements the Scott-Knott Modification 2 algorithm (SKM2) (Christopher M. Triggs and + James M. Curran and John S. Buckleton and Kevan A.J. Walsh (1997) + "The grouping problem in forensic glass analysis: a divisive approach", Forensic Science International, 85(1), 1--14) + for small sample glass fragment analysis using the refractive index (ri) of a set of glass samples. + It also includes an experimental multivariate analog to the Scott-Knott algorithm for similar analysis on glass samples + with multiple chemical concentration variables and multiple samples of the same item; testing against the Hotellings T^2 + distribution (J.M. Curran and C.M. Triggs and J.R. Almirall and J.S. Buckleton and K.A.J. Walsh (1997) + "The interpretation of elemental composition measurements from forensic + glass evidence", Science & Justice, 37(4), 241--244). + date_publication: '2023-01-30' + bug_reports: https://github.com/tobyhayward13/SCI118UOA_ForensicGlassAnalysis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SK4FGA + url_git: https://github.com/tobyhayward13/SCI118UOA_ForensicGlassAnalysis +SKAT: + version: 2.2.5 + title: SNP-Set (Sequence) Kernel Association Test + maintainer: Seunggeun (Shawn) Lee + description: Functions for kernel-regression-based association tests including Burden + test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics + in a SNP set and efficiently compute SNP-set level p-values. + date_publication: '2023-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SKAT + url_git: '' +skater: + version: 0.1.2 + title: Utilities for SNP-Based Kinship Analysis + maintainer: Stephen Turner + description: |- + Utilities for single nucleotide polymorphism (SNP) based kinship analysis + testing and evaluation. The 'skater' package contains functions for importing, parsing, + and analyzing pedigree data, performing relationship degree inference, benchmarking + relationship degree classification, and summarizing identity by descent (IBD) segment data. + Package functions and methods are described in Turner et al. (2021) "skater: An R package + for SNP-based Kinship Analysis, Testing, and Evaluation" . + date_publication: '2023-01-31' + bug_reports: https://github.com/signaturescience/skater/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skater + url_git: https://github.com/signaturescience/skater +skedastic: + version: 2.0.2 + title: Handling Heteroskedasticity in the Linear Regression Model + maintainer: Thomas Farrar + description: |- + Implements numerous methods for testing for, modelling, and + correcting for heteroskedasticity in the classical linear regression + model. The most novel contribution of the + package is found in the functions that implement the as-yet-unpublished + auxiliary linear variance models and auxiliary nonlinear variance + models that are designed to estimate error variances in a heteroskedastic + linear regression model. These models follow principles of statistical + learning described in Hastie (2009) . + The nonlinear version of the model is estimated using quasi-likelihood + methods as described in Seber and Wild (2003, ISBN: 0-471-47135-6). + Bootstrap methods for approximate confidence intervals for error variances + are implemented as described in Efron and Tibshirani + (1993, ISBN: 978-1-4899-4541-9), including also the expansion technique + described in Hesterberg (2014) . The + wild bootstrap employed here follows the description in Davidson and + Flachaire (2008) . Tuning of + hyper-parameters makes use of a golden section search function that is + modelled after the MATLAB function of Zarnowiec (2022) + . + A methodological description of the algorithm can be found in Fox (2021, + ISBN: 978-1-003-00957-3). + There are 25 different functions that implement hypothesis tests for + heteroskedasticity. These include a test based on Anscombe (1961) + , Ramsey's (1969) + BAMSET Test , the tests of Bickel + (1978) , Breusch and Pagan (1979) + with and without the modification + proposed by Koenker (1981) , Carapeto and + Holt (2003) , Cook and Weisberg (1983) + (including their graphical methods), Diblasi + and Bowman (1997) , Dufour, Khalaf, + Bernard, and Genest (2004) , Evans and + King (1985) and Evans and King (1988) + , Glejser (1969) + as formulated by + Mittelhammer, Judge and Miller (2000, ISBN: 0-521-62394-4), Godfrey and + Orme (1999) , Goldfeld and Quandt + (1965) , Harrison and McCabe (1979) + , Harvey (1976) , + Honda (1989) , Horn (1981) + , Li and Yao (2019) + with and without the modification of + Bai, Pan, and Yin (2016) , Rackauskas and + Zuokas (2007) , Simonoff and Tsai (1994) + with and without the modification of Ferrari, + Cysneiros, and Cribari-Neto (2004) , + Szroeter (1978) , Verbyla (1993) + , White (1980) + , Wilcox and Keselman (2006) + , Yuce (2008) + , and Zhou, + Song, and Thompson (2015) . Besides these + heteroskedasticity tests, there are supporting functions that compute the + BLUS residuals of Theil (1965) , the + conditional two-sided p-values of Kulinskaya (2008) , + and probabilities for the nonparametric trend statistic of Lehmann (1975, + ISBN: 0-816-24996-1). For handling heteroskedasticity, in addition to the + new auxiliary variance model methods, there is a function + to implement various existing Heteroskedasticity-Consistent Covariance + Matrix Estimators from the literature, such as those of White (1980) + , MacKinnon and White (1985) + , Cribari-Neto (2004) + , Cribari-Neto et al. (2007) + , Cribari-Neto and da Silva (2011) + , Aftab and Chang (2016) + , and Li et al. (2017) + . + date_publication: '2024-01-08' + bug_reports: https://github.com/tjfarrar/skedastic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skedastic + url_git: https://github.com/tjfarrar/skedastic +skeletor: + version: 1.0.4 + title: An R Package Skeleton Generator + maintainer: Neal Richardson + description: |- + A tool for bootstrapping new packages with useful defaults, + including a test suite outline that passes checks and helpers for running + tests, checking test coverage, building vignettes, and more. Package + skeletons it creates are set up for pushing your package to + 'GitHub' and using other hosted services for building and test automation. + date_publication: '2017-04-09' + bug_reports: https://github.com/nealrichardson/skeletor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skeletor + url_git: https://github.com/nealrichardson/skeletor +skellam: + version: 0.2.3 + title: Densities and Sampling for the Skellam Distribution + maintainer: Patrick E. Brown + description: |- + Functions for the Skellam distribution, including: density + (pmf), cdf, quantiles and regression. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skellam + url_git: https//r-forge.r-project.org/projects/healthqueues/ +sketch: + version: 1.1.20.3 + title: Interactive Sketches + maintainer: Chun Fung Kwok + description: |- + Creates static / animated / interactive visualisations embeddable + in R Markdown documents. It implements an R-to-JavaScript transpiler and + enables users to write JavaScript applications using the syntax of R. + date_publication: '2024-02-02' + bug_reports: https://github.com/kcf-jackson/sketch + url: '' + url_cran: https://CRAN.R-project.org/package=sketch + url_git: '' +sketcher: + version: 0.1.3 + title: Pencil Sketch Effect + maintainer: Hiroyuki Tsuda + description: |- + An implementation of image processing effects that convert a photo into a line drawing image. + For details, please refer to Tsuda, H. (2020). sketcher: An R package for converting a photo into a sketch style image. + . + date_publication: '2020-05-25' + bug_reports: https://github.com/tsuda16k/sketcher/issues/ + url: https://htsuda.net/sketcher/ + url_cran: https://CRAN.R-project.org/package=sketcher + url_git: '' +sketching: + version: 0.1.2 + title: Sketching of Data via Random Subspace Embeddings + maintainer: Sokbae Lee + description: |- + Construct sketches of data via random subspace embeddings. + For more details, see the following papers. + Lee, S. and Ng, S. (2022). "Least Squares Estimation Using Sketched Data with Heteroskedastic Errors," Proceedings of the 39th International Conference on Machine Learning (ICML22), 162:12498-12520. + Lee, S. and Ng, S. (2020). "An Econometric Perspective on Algorithmic Subsampling," Annual Review of Economics, 12(1): 45–80. + date_publication: '2022-09-07' + bug_reports: https://github.com/sokbae/sketching/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sketching + url_git: https://github.com/sokbae/sketching/ +sketchy: + version: 1.0.5 + title: Create Custom Research Compendiums + maintainer: Marcelo Araya-Salas + description: Provides functions to create and manage research compendiums for data + analysis. Research compendiums are a standard and intuitive folder structure for + organizing the digital materials of a research project, which can significantly + improve reproducibility. The package offers several compendium structure options + that fit different research project as well as the ability of duplicating the + folder structure of existing projects or implementing custom structures. It also + simplifies the use of version control. + date_publication: '2025-01-16' + bug_reports: https://github.com/maRce10/sketchy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sketchy + url_git: https://github.com/maRce10/sketchy +SkewHyperbolic: + version: 0.4-2 + title: The Skew Hyperbolic Student t-Distribution + maintainer: David Scott + description: |- + Functions are provided for the density function, + distribution function, quantiles and random number + generation for the skew hyperbolic + t-distribution. There are also functions that fit + the distribution to data. There are functions for the + mean, variance, skewness, kurtosis and mode of a given + distribution and to calculate moments of any order about + any centre. To assess goodness of fit, there are + functions to generate a Q-Q plot, a P-P plot and a tail plot. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SkewHyperbolic + url_git: https://r-forge.r-project.org/projects/rmetrics/ +skewlmm: + version: 1.1.2 + title: Scale Mixture of Skew-Normal Linear Mixed Models + maintainer: Fernanda L. Schumacher + description: It fits scale mixture of skew-normal linear mixed models using either + an expectation–maximization (EM) type algorithm or its accelerated version (Damped + Anderson Acceleration with Epsilon Monotonicity, DAAREM), including some possibilities + for modeling the within-subject dependence. Details can be found in Schumacher, + Lachos and Matos (2021) . + date_publication: '2024-12-15' + bug_reports: https://github.com/fernandalschumacher/skewlmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skewlmm + url_git: https://github.com/fernandalschumacher/skewlmm +skewMLRM: + version: '1.6' + title: Estimation for Scale-Shape Mixtures of Skew-Normal Distributions + maintainer: Diego Gallardo + description: |- + Provide data generation and estimation tools for the multivariate scale mixtures of normal + presented in Lange and Sinsheimer (1993) , the multivariate scale + mixtures of skew-normal presented in Zeller, Lachos and Vilca (2011) + , the multivariate skew scale mixtures of normal + presented in Louredo, Zeller and Ferreira (2021) + and the multivariate scale mixtures of skew-normal-Cauchy presented in Kahrari et al. (2020) + . + date_publication: '2021-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skewMLRM + url_git: '' +skewsamp: + version: 1.0.0 + title: |- + Estimate Sample Sizes for Group Comparisons with Skewed + Distributions + maintainer: Johannes Brachem + description: |- + Estimate necessary sample sizes for comparing the location + of data from two groups or categories when the distribution of the + data is skewed. The package + offers a non-parametric method for a Wilcoxon Mann-Whitney test of + location shift as well as methods for several generalized linear + models, for instance, Gamma regression. + date_publication: '2021-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skewsamp + url_git: '' +skewt: + version: '1.0' + title: The Skewed Student-t Distribution + maintainer: Robert King + description: |- + Density, distribution function, quantile function and + random generation for the skewed t distribution of Fernandez + and Steel. + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skewt + url_git: '' +skewunit: + version: '1.0' + title: Estimation and Other Tools for Skew-Unit Models + maintainer: Diego Gallardo + description: |- + Provide estimation and data generation tools for the skew-unit family + discussed based on Mukhopadhyay and Brani (1995) . + The family contains extensions for popular distributions such as the ArcSin + discussed in Arnold and Groeneveld (1980) , + triangular, U-quadratic and Johnson-SB proposed in Cortina-Borja (2006) + distributions, among others. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skewunit + url_git: '' +SKFCPD: + version: 0.2.4 + title: Fast Online Changepoint Detection for Temporally Correlated Data + maintainer: Hanmo Li + description: 'Sequential Kalman filter for scalable online changepoint detection + by temporally correlated data. It enables fast single and multiple change points + with missing values. See the reference: Hanmo Li, Yuedong Wang, Mengyang Gu (2023), + .' + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SKFCPD + url_git: '' +Skillings.Mack: + version: '1.10' + title: |- + The Skillings-Mack Test Statistic for Block Designs with Missing + Observations + maintainer: Patchanok Srisuradetchai + description: A generalization of the statistic used in Friedman's ANOVA method and + in Durbin's rank test. This nonparametric statistical test is useful for the data + obtained from block designs with missing observations occurring randomly. A resulting + p-value is based on the chi-squared distribution and Monte Carlo method. + date_publication: '2015-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Skillings.Mack + url_git: '' +skilljaR: + version: 0.1.2 + title: Connect to Your 'Skilljar' Data + maintainer: Chris Umphlett + description: |- + Functions that simplify calls to the 'Skilljar' API. See + for documentation on the 'Skilljar' API. + This package is not supported by 'Skilljar'. + date_publication: '2023-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skilljaR + url_git: '' +skimr: + version: 2.1.5 + title: Compact and Flexible Summaries of Data + maintainer: Elin Waring + description: |- + A simple to use summary function that can be used with pipes + and displays nicely in the console. The default summary statistics may + be modified by the user as can the default formatting. Support for + data frames and vectors is included, and users can implement their own + skim methods for specific object types as described in a vignette. + Default summaries include support for inline spark graphs. + Instructions for managing these on specific operating systems are + given in the "Using skimr" vignette and the README. + date_publication: '2022-12-23' + bug_reports: https://github.com/ropensci/skimr/issues + url: https://docs.ropensci.org/skimr/(website) + url_cran: https://CRAN.R-project.org/package=skimr + url_git: https://github.com/ropensci/skimr/ +skipTrack: + version: 0.1.2 + title: |- + A Bayesian Hierarchical Model that Controls for Non-Adherence in + Mobile Menstrual Cycle Tracking + maintainer: Luke Duttweiler + description: Implements a Bayesian hierarchical model designed to identify skips + in mobile menstrual cycle self-tracking on mobile apps. Future developments will + allow for the inclusion of covariates affecting cycle mean and regularity, as + well as extra information regarding tracking non-adherence. Main methods to be + outlined in a forthcoming paper, with alternative models from Li et al. (2022) + . + date_publication: '2025-01-27' + bug_reports: https://github.com/LukeDuttweiler/skipTrack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skipTrack + url_git: https://github.com/LukeDuttweiler/skipTrack +sklarsomega: + version: 3.0-2 + title: Measuring Agreement Using Sklar's Omega Coefficient + maintainer: John Hughes + description: |- + Provides tools for applying Sklar's Omega (Hughes, 2018) + methodology to nominal scores, ordinal scores, percentages, counts, amounts (i.e., + non-negative real numbers), and balances (i.e., any real number). The framework can + accommodate any number of units, any number of coders, and missingness; and + can be used to measure agreement with a gold standard, intra-coder agreement, + and/or inter-coder agreement. Frequentist inference is supported for all levels + of measurement. Bayesian inference is supported for continuous scores only. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sklarsomega + url_git: '' +skm: + version: 0.1.5.4 + title: Selective k-Means + maintainer: Guang Yang + description: |- + Algorithms for solving selective k-means problem, + which is defined as finding k rows in an m x n matrix such that + the sum of each column minimal is minimized. + In the scenario when m == n and each cell value in matrix is a + valid distance metric, this is equivalent to a k-means problem. + The selective k-means extends the k-means problem in the sense + that it is possible to have m != n, often the case m < n which + implies the search is limited within a small subset of rows. + Also, the selective k-means extends the k-means problem in the + sense that the instance in row set can be instance not seen in + the column set, e.g., select 2 from 3 internet service provider + (row) for 5 houses (column) such that minimize the overall cost + (cell value) - overall cost is the sum of the column minimal of + the selected 2 service provider. + date_publication: '2017-01-23' + bug_reports: http://github.com/gyang274/skm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skm + url_git: http://github.com/gyang274/skm +skmeans: + version: 0.2-18 + title: Spherical k-Means Clustering + maintainer: Kurt Hornik + description: |- + Algorithms to compute spherical k-means partitions. + Features several methods, including a genetic and a fixed-point + algorithm and an interface to the CLUTO vcluster program. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skmeans + url_git: '' +SKNN: + version: '4.1' + title: A Super K-Nearest Neighbor (SKNN) Classification Algorithm + maintainer: Yarong Yang + description: It's a Super K-Nearest Neighbor classification method with using kernel + density to describe weight of the distance between a training observation and + the testing sample. + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SKNN + url_git: '' +skpr: + version: 1.7.1 + title: |- + Design of Experiments Suite: Generate and Evaluate Optimal + Designs + maintainer: Tyler Morgan-Wall + description: Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. + Supports generation and evaluation of blocked and split/split-split/.../N-split + plot designs. Includes parametric and Monte Carlo power evaluation functions, + and supports calculating power for censored responses. Provides a framework to + evaluate power using functions provided in other packages or written by the user. + Includes a Shiny graphical user interface that displays the underlying code used + to create and evaluate the design to improve ease-of-use and make analyses more + reproducible. For details, see Morgan-Wall et al. (2021) . + date_publication: '2024-03-26' + bug_reports: https://github.com/tylermorganwall/skpr/issues + url: https://tylermorganwall.github.io/skpr/ + url_cran: https://CRAN.R-project.org/package=skpr + url_git: https://github.com/tylermorganwall/skpr +skylight: + version: '1.2' + title: A Simple Sky Illuminance Model + maintainer: Koen Hufkens + description: |- + A tool to calculate sky illuminance values (in lux) for both sun and moon. The + model is a verbatim translation of the code by Janiczek and DeYoung (1987) + . + date_publication: '2023-11-04' + bug_reports: https://github.com/bluegreen-labs/skylight/issues + url: '' + url_cran: https://CRAN.R-project.org/package=skylight + url_git: https://github.com/bluegreen-labs/skylight +skyscapeR: + version: 1.0.0 + title: Data Analysis and Visualization for Skyscape Archaeology + maintainer: Silva Fabio + description: Data reduction, visualization and statistical analysis of measurements + of orientation of archaeological structures, following Silva (2020) . + date_publication: '2021-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=skyscapeR + url_git: '' +slackr: + version: 3.3.1 + title: |- + Send Messages, Images, R Objects and Files to 'Slack' + Channels/Users + maintainer: Matt Kaye + description: |- + 'Slack' provides a service for teams to + collaborate by sharing messages, images, links, files and more. + Functions are provided that make it possible to interact with the + 'Slack' platform 'API'. When you need to share information or data + from R, rather than resort to copy/ paste in e-mails or other services + like 'Skype' , you can use this package to + send well-formatted output from multiple R objects and expressions to + all teammates at the same time with little effort. You can also send + images from the current graphics device, R objects, and upload files. + date_publication: '2023-02-26' + bug_reports: https://github.com/mrkaye97/slackr/issues + url: https://mrkaye97.github.io/slackr/ + url_cran: https://CRAN.R-project.org/package=slackr + url_git: https://github.com/mrkaye97/slackr +slam: + version: 0.1-55 + title: Sparse Lightweight Arrays and Matrices + maintainer: Kurt Hornik + description: |- + Data structures and algorithms for sparse arrays and matrices, + based on index arrays and simple triplet representations, respectively. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slam + url_git: '' +slanter: + version: 0.2-0 + title: Slanted Matrices and Ordered Clustering + maintainer: Oren Ben-Kiki + description: Slanted matrices and ordered clustering for better visualization of + similarity data. + date_publication: '2021-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slanter + url_git: '' +slap: + version: 2024.4.1 + title: Simplified Error Handling + maintainer: Romain François + description: |- + Alternative to using withCallingHandlers() in the simple case of catch + and rethrow. The `%!%` operator evaluates the expression on its left hand side, + and if an error occurs, the right hand side is used to construct a new error + that embeds the original error. + date_publication: '2024-04-24' + bug_reports: https://github.com/tadascience/slap/issues + url: https://slap.tada.science + url_cran: https://CRAN.R-project.org/package=slap + url_git: https://github.com/tadascience/slap +slasso: + version: 1.0.0 + title: S-LASSO Estimator for the Function-on-Function Linear Regression + maintainer: Fabio Centofanti + description: Implements the smooth LASSO estimator for the function-on-function + linear regression model described in Centofanti et al. (2020) . + date_publication: '2021-10-15' + bug_reports: https://github.com/unina-sfere/slasso + url: '' + url_cran: https://CRAN.R-project.org/package=slasso + url_git: https://github.com/unina-sfere/slasso +SLBDD: + version: 0.0.4 + title: Statistical Learning for Big Dependent Data + maintainer: Antonio Elias + description: Programs for analyzing large-scale time series data. They include functions + for automatic specification and estimation of univariate time series, for clustering + time series, for multivariate outlier detections, for quantile plotting of many + time series, for dynamic factor models and for creating input data for deep learning + programs. Examples of using the package can be found in the Wiley book 'Statistical + Learning with Big Dependent Data' by Daniel Peña and Ruey S. Tsay (2021). ISBN + 9781119417385. + date_publication: '2022-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLBDD + url_git: '' +slca: + version: 1.3.0 + title: Structural Modeling for Multiple Latent Class Variables + maintainer: Youngsun Kim + description: |- + Provides comprehensive tools for the implementation of Structural Latent Class Models (SLCM), including + Latent Transition Analysis (LTA; Linda M. Collins and Stephanie T. Lanza, 2009) , + Latent Class Profile Analysis (LCPA; Hwan Chung et al., 2010) , and + Joint Latent Class Analysis (JLCA; Saebom Jeon et al., 2017) , and + any other extended models involving multiple latent class variables. + date_publication: '2024-12-13' + bug_reports: https://github.com/kim0sun/slca/issues + url: https://kim0sun.github.io/slca/ + url_cran: https://CRAN.R-project.org/package=slca + url_git: '' +SLCARE: + version: 1.2.0 + title: Semiparametric Latent Class Analysis of Recurrent Events + maintainer: Qi Yu + description: Efficient R package for latent class analysis of recurrent events, + based on the semiparametric multiplicative intensity model by Zhao et al. (2022) + . SLCARE returns estimates for non-functional model parameters + along with the associated variance estimates and p-values. Visualization tools + are provided to depict the estimated functional model parameters and related functional + quantities of interest. SLCARE also delivers a model checking plot to help assess + the adequacy of the fitted model. + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLCARE + url_git: '' +slcm: + version: 0.1.0 + title: Sparse Latent Class Model for Cognitive Diagnosis + maintainer: James Joseph Balamuta + description: |- + Perform a Bayesian estimation of the exploratory + Sparse Latent Class Model for Binary Data + described by Chen, Y., Culpepper, S. A., and Liang, F. (2020) + . + date_publication: '2023-08-12' + bug_reports: https://github.com/tmsalab/slcm/issues + url: https://tmsalab.github.io/slcm/ + url_cran: https://CRAN.R-project.org/package=slcm + url_git: https://github.com/tmsalab/slcm +sld: + version: 1.0.1 + title: |- + Estimation and Use of the Quantile-Based Skew Logistic + Distribution + maintainer: Robert King + description: |- + The skew logistic distribution is a quantile-defined generalisation + of the logistic distribution (van Staden and King 2015). Provides random + numbers, quantiles, probabilities, densities and density quantiles for the distribution. + It provides Quantile-Quantile plots and method of L-Moments estimation + (including asymptotic standard errors) for the distribution. + date_publication: '2022-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sld + url_git: https://github.com/newystats/SLD/ +SLDAssay: + version: '1.8' + title: Software for Analyzing Limiting Dilution Assays + maintainer: Ilana Trumble + description: Calculates maximum likelihood estimate, exact and asymptotic confidence + intervals, and exact and asymptotic goodness of fit p-values for concentration + of infectious units from serial limiting dilution assays. This package uses the + likelihood equation, exact goodness of fit p-values, and exact confidence intervals + described in Meyers et al. (1994) . + This software is also implemented as a web application through the Shiny R package + . + date_publication: '2017-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLDAssay + url_git: '' +sleekts: + version: 1.0.2 + title: 4253H, Twice Smoothing + maintainer: Muntashir-Al-Arefin + description: Compute Time series Resistant Smooth 4253H, twice smoothing method. + date_publication: '2015-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sleekts + url_git: '' +SleepCycles: + version: 1.1.4 + title: Sleep Cycle Detection + maintainer: Christine Blume + description: Sleep cycles are largely detected according to the originally proposed + criteria by Feinberg & Floyd (1979) as + described in Blume & Cajochen (2021) . + date_publication: '2021-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SleepCycles + url_git: '' +sleeperapi: + version: 1.1.2 + title: Wrapper Functions Around 'Sleeper' (Fantasy Sports) API + maintainer: Nick Bultman + description: For those wishing to interact with the 'Sleeper' (Fantasy Sports) API + () without looking too much into its documentation + (found at ), this package offers wrapper functions + around the available API calls to make it easier. + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sleeperapi + url_git: '' +sleepr: + version: 0.3.0 + title: Analyse Activity and Sleep Behaviour + maintainer: Quentin Geissmann + description: |- + Use behavioural variables to score activity and infer sleep from bouts of immobility. + It is primarily designed to score sleep in fruit flies from Drosophila Activity Monitor (TriKinetics) and Ethoscope data. + It implements sleep scoring using the "five-minute rule" (Hendricks et al. (2000) ), + activity classification for Ethoscopes (Geissmann et al. (2017) ) + and a new algorithm to detect when animals are dead. + date_publication: '2018-10-30' + bug_reports: https://github.com/rethomics/sleepr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sleepr + url_git: https://github.com/rethomics/sleepr +sleepwalk: + version: 0.3.2 + title: Interactively Explore Dimension-Reduced Embeddings + maintainer: Svetlana Ovchinnikova + description: |- + A tool to interactively explore the + embeddings created by dimension reduction methods such as + Principal Components Analysis (PCA), Multidimensional Scaling (MDS), + T-distributed Stochastic Neighbour Embedding (t-SNE), + Uniform Manifold Approximation and Projection (UMAP) or any other. + date_publication: '2021-09-16' + bug_reports: https://github.com/anders-biostat/sleepwalk/issues + url: https://anders-biostat.github.io/sleepwalk/ + url_cran: https://CRAN.R-project.org/package=sleepwalk + url_git: '' +sleev: + version: 1.0.5 + title: Semiparametric Likelihood Estimation with Errors in Variables + maintainer: Ran Tao + description: Efficient regression analysis under general two-phase sampling, where + Phase I includes error-prone data and Phase II contains validated data on a subset. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sleev + url_git: '' +SLEMI: + version: 1.0.2 + title: Statistical Learning Based Estimation of Mutual Information + maintainer: Tomasz Jetka + description: The implementation of the algorithm for estimation of mutual information + and channel capacity from experimental data by classification procedures (logistic + regression). Technically, it allows to estimate information-theoretic measures + between finite-state input and multivariate, continuous output. Method described + in Jetka et al. (2019) . + date_publication: '2023-11-19' + bug_reports: https://github.com/TJetka/SLEMI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SLEMI + url_git: https://github.com/TJetka/SLEMI +slendr: + version: 1.0.0 + title: A Simulation Framework for Spatiotemporal Population Genetics + maintainer: Martin Petr + description: |- + A framework for simulating spatially explicit genomic data which + leverages real cartographic information for programmatic and visual encoding + of spatiotemporal population dynamics on real geographic landscapes. Population + genetic models are then automatically executed by the 'SLiM' software by Haller + et al. (2019) behind the scenes, using a custom + built-in simulation 'SLiM' script. Additionally, fully abstract spatial models + not tied to a specific geographic location are supported, and users can also + simulate data from standard, non-spatial, random-mating models. These can be + simulated either with the 'SLiM' built-in back-end script, or using an efficient + coalescent population genetics simulator 'msprime' by Baumdicker et al. (2022) + with a custom-built 'Python' script bundled with the + R package. Simulated genomic data is saved in a tree-sequence format and can be + loaded, manipulated, and summarised using tree-sequence functionality via an R + interface to the 'Python' module 'tskit' by Kelleher et al. (2019) + . Complete model configuration, simulation and + analysis pipelines can be therefore constructed without a need to leave the R + environment, eliminating friction between disparate tools for population genetic + simulations and data analysis. + date_publication: '2024-11-22' + bug_reports: https://github.com/bodkan/slendr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=slendr + url_git: https://github.com/bodkan/slendr +Sleuth2: + version: 2.0-7 + title: |- + Data Sets from Ramsey and Schafer's "Statistical Sleuth (2nd + Ed)" + maintainer: Berwin A Turlach + description: |- + Data sets from Ramsey, F.L. and Schafer, D.W. (2002), "The + Statistical Sleuth: A Course in Methods of Data Analysis (2nd + ed)", Duxbury. + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sleuth2 + url_git: https://r-forge.r-project.org/projects/sleuth2/ +Sleuth3: + version: 1.0-6 + title: |- + Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd + Ed)" + maintainer: Berwin A Turlach + description: |- + Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The + Statistical Sleuth: A Course in Methods of Data Analysis (3rd + ed)", Cengage Learning. + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sleuth3 + url_git: https://r-forge.r-project.org/projects/sleuth2/ +slfm: + version: 1.0.2 + title: |- + Fitting a Bayesian Sparse Latent Factor Model in Gene Expression + Analysis + maintainer: Vinicius Mayrink + description: 'Set of tools to find coherent patterns in gene expression (microarray) + data using a Bayesian Sparse Latent Factor Model (SLFM) . + Considerable effort has been put to build a fast and memory efficient package, + which makes this proposal an interesting and computationally convenient alternative + to study patterns of gene expressions exhibited in matrices. The package contains + the implementation of two versions of the model based on different mixture priors + for the loadings: one relies on a degenerate component at zero and the other uses + a small variance normal distribution for the spike part of the mixture.' + date_publication: '2023-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slfm + url_git: '' +SLFPCA: + version: '3.0' + title: Sparse Logistic Functional Principal Component Analysis + maintainer: Rou Zhong + description: Implementation for sparse logistic functional principal component analysis + (SLFPCA). SLFPCA is specifically developed for functional binary data, and the + estimated eigenfunction can be strictly zero on some sub-intervals, which is helpful + for interpretation. The crucial function of this package is SLFPCA(). + date_publication: '2022-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLFPCA + url_git: '' +slgf: + version: 2.0.0 + title: Bayesian Model Selection with Suspected Latent Grouping Factors + maintainer: Thomas Metzger + description: |- + Implements the Bayesian model selection method with suspected latent + grouping factor methodology of Metzger and Franck (2020), + . SLGF detects latent + heteroscedasticity or group-based regression effects based on the levels of a + user-specified categorical predictor. + date_publication: '2022-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slgf + url_git: '' +SLHD: + version: 2.1-1 + title: Maximin-Distance (Sliced) Latin Hypercube Designs + maintainer: Shan Ba + description: Generate the optimal Latin Hypercube Designs (LHDs) for computer experiments + with quantitative factors and the optimal Sliced Latin Hypercube Designs (SLHDs) + for computer experiments with both quantitative and qualitative factors. Details + of the algorithm can be found in Ba, S., Brenneman, W. A. and Myers, W. R. (2015), + "Optimal Sliced Latin Hypercube Designs," Technometrics. Important function in + this package is "maximinSLHD". + date_publication: '2015-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLHD + url_git: '' +SlicedLHD: + version: '1.0' + title: Sliced Latin Hypercube Designs + maintainer: Baidya Nath Mandal + description: A facility to generate sliced (orthogonal) Latin hypercube designs + with four and five slices. For details about sliced and orthogonal Latin hypercube + designs, see Yang, J. F., Lin, C. D., Qian, P. Z., and Lin, D. K. (2013). "Construction + of sliced orthogonal Latin hypercube designs". Statistica Sinica, 1117-1130, . + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SlicedLHD + url_git: '' +slickR: + version: 0.6.0 + title: |- + Create Interactive Carousels with the 'JavaScript' 'Slick' + Library + maintainer: Jonathan Sidi + description: |- + Create and customize interactive carousels + using the 'Slick' 'JavaScript' library and the + 'htmlwidgets' package. The carousels can contain + plots produced in R, images, 'iframes', videos and + other 'htmlwidgets'. These carousels can be created + directly from the R console, and viewed in the 'RStudio' + internal viewer, in 'Shiny' apps and R Markdown documents. + date_publication: '2022-12-21' + bug_reports: https://github.com/yonicd/slickR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=slickR + url_git: https://github.com/yonicd/slickR +SLIDE: + version: 1.0.0 + title: Single Cell Linkage by Distance Estimation is SLIDE + maintainer: Arjun Panda + description: |- + This statistical method uses the nearest neighbor algorithm to estimate absolute distances between single cells + based on a chosen constellation of surface proteins, with these distances being a measure of the similarity between the + two cells being compared. Based on Sen, N., Mukherjee, G., and Arvin, A.M. (2015) . + date_publication: '2018-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLIDE + url_git: '' +SlideCNA: + version: 0.1.0 + title: Calls Copy Number Alterations from Slide-Seq Data + maintainer: Diane Zhang + description: This takes spatial single-cell-type RNA-seq data (specifically designed + for Slide-seq v2) that calls copy number alterations (CNAs) using pseudo-spatial + binning, clusters cellular units (e.g. beads) based on CNA profile, and visualizes + spatial CNA patterns. Documentation about 'SlideCNA' is included in the the pre-print + by Zhang et al. (2022, ). The package 'enrichR' + (>= 3.0), conditionally used to annotate SlideCNA-determined clusters with gene + ontology terms, can be installed at or with + install_github("wjawaid/enrichR"). + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SlideCNA + url_git: '' +slider: + version: 0.3.2 + title: Sliding Window Functions + maintainer: Davis Vaughan + description: |- + Provides type-stable rolling window functions over any R data + type. Cumulative and expanding windows are also supported. For more + advanced usage, an index can be used as a secondary vector that + defines how sliding windows are to be created. + date_publication: '2024-10-25' + bug_reports: https://github.com/r-lib/slider/issues + url: https://slider.r-lib.org + url_cran: https://CRAN.R-project.org/package=slider + url_git: https://github.com/r-lib/slider +slideview: + version: 0.2.0 + title: Compare Raster Images Side by Side with a Slider + maintainer: Tim Appelhans + description: |- + Create a side-by-side view of raster(image)s with an interactive + slider to switch between regions of the images. This can be especially useful + for image comparison of the same region at different time stamps. + date_publication: '2022-04-11' + bug_reports: '' + url: https://r-spatial.github.io/slideview/ + url_cran: https://CRAN.R-project.org/package=slideview + url_git: '' +SlidingWindows: + version: 0.2.0 + title: Methods for Time Series Analysis + maintainer: Everaldo Freitas Guedes + description: A collection of functions to perform Detrended Fluctuation Analysis + (DFA exponent), GUEDES et al. (2019) , Detrended + cross-correlation coefficient (RHODCCA), GUEDES & ZEBENDE (2019) , + DMCA cross-correlation coefficient and Detrended multiple cross-correlation coefficient + (DMC), GUEDES & SILVA-FILHO & ZEBENDE (2018) , + both with sliding windows approach. + date_publication: '2021-04-11' + bug_reports: https://github.com/efguedes/SlidingWindows + url: '' + url_cran: https://CRAN.R-project.org/package=SlidingWindows + url_git: https://github.com/efguedes/SlidingWindows +slim: + version: 0.1.1 + title: Singular Linear Models for Longitudinal Data + maintainer: Daniel Farewell + description: |- + Fits singular linear models to longitudinal data. Singular linear + models are useful when the number, or timing, of longitudinal observations + may be informative about the observations themselves. They are described + in Farewell (2010) , and are extensions of the + linear increments model to general + longitudinal data. + date_publication: '2017-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slim + url_git: '' +slimrec: + version: 0.1.0 + title: |- + Sparse Linear Method to Predict Ratings and Top-N + Recommendations + maintainer: Srikanth KS + description: |- + Sparse Linear Method(SLIM) predicts ratings and top-n + recommendations suited for sparse implicit positive feedback systems. SLIM + is decomposed into multiple elasticnet optimization problems which are solved + in parallel over multiple cores. The package is based on "SLIM: Sparse Linear + Methods for Top-N Recommender Systems" by Xia Ning and George Karypis . + date_publication: '2017-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slimrec + url_git: '' +slippymath: + version: 0.3.1 + title: Slippy Map Tile Tools + maintainer: Miles McBain + description: |- + Provides functions for performing common tasks when working with + slippy map tile service APIs e.g. Google maps, Open Street Map, Mapbox, Stamen, + among others. Functionality includes converting from latitude and longitude to + tile numbers, determining tile bounding boxes, and compositing tiles to a + georeferenced raster image. + date_publication: '2019-06-28' + bug_reports: https://www.github.com/milesmcbain/slippymath/issues + url: '' + url_cran: https://CRAN.R-project.org/package=slippymath + url_git: https://www.github.com/milesmcbain/slippymath +slm: + version: 1.2.0 + title: Stationary Linear Models + maintainer: Emmanuel Caron + description: 'Provides statistical procedures for linear regression in the general + context where the errors are assumed to be correlated. Different ways to estimate + the asymptotic covariance matrix of the least squares estimators are available. + Starting from this estimation of the covariance matrix, the confidence intervals + and the usual tests on the parameters are modified. The functions of this package + are very similar to those of ''lm'': it contains methods such as summary(), plot(), + confint() and predict(). The ''slm'' package is described in the paper by E. Caron, + J. Dedecker and B. Michel (2019), "Linear regression with stationary errors: the + R package slm", arXiv preprint .' + date_publication: '2020-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slm + url_git: '' +SLModels: + version: 0.1.2 + title: |- + Stepwise Linear Models for Binary Classification Problems under + Youden Index Optimisation + maintainer: Rocio Aznar-Gimeno + description: Stepwise models for the optimal linear combination of continuous variables + in binary classification problems under Youden Index optimisation. Information + on the models implemented can be found at Aznar-Gimeno et al. (2021) . + date_publication: '2022-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLModels + url_git: '' +sloop: + version: 1.0.1 + title: Helpers for 'OOP' in R + maintainer: Hadley Wickham + description: |- + A collection of helper functions designed to help + you to better understand object oriented programming in R, + particularly using 'S3'. + date_publication: '2019-02-17' + bug_reports: https://github.com/r-lib/sloop/issues + url: https://sloop.r-lib.org + url_cran: https://CRAN.R-project.org/package=sloop + url_git: https://github.com/r-lib/sloop +SLOPE: + version: 0.5.2 + title: Sorted L1 Penalized Estimation + maintainer: Johan Larsson + description: |- + Efficient implementations for Sorted L-One Penalized Estimation + (SLOPE): generalized linear models regularized with the sorted L1-norm + (Bogdan et al. 2015). Supported models include + ordinary least-squares regression, binomial regression, multinomial + regression, and Poisson regression. Both dense and sparse predictor + matrices are supported. In addition, the package features predictor + screening rules that enable fast and efficient solutions to high-dimensional + problems. + date_publication: '2025-02-01' + bug_reports: https://github.com/jolars/SLOPE/issues + url: https://jolars.github.io/SLOPE/ + url_cran: https://CRAN.R-project.org/package=SLOPE + url_git: https://github.com/jolars/SLOPE +SLOS: + version: 1.0.1 + title: ICU Length of Stay Prediction and Efficiency Evaluation + maintainer: Joana da Matta + description: |- + Provides tools for predicting ICU length of stay and assessing ICU efficiency. + It is based on the methodologies proposed by Peres et al. (2022, 2023), which utilize data-driven approaches for modeling and validation, offering insights into ICU performance and patient outcomes. References: Peres et al. (2022), Peres et al. (2023). + More information: . + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SLOS + url_git: '' +slouch: + version: 2.1.5 + title: Stochastic Linear Ornstein-Uhlenbeck Comparative Hypotheses + maintainer: Bjørn Tore Kopperud + description: An implementation of a phylogenetic comparative method. It can fit + univariate among-species Ornstein-Uhlenbeck models of phenotypic trait evolution, + where the trait evolves towards a primary optimum. The optimum can be modelled + as a single parameter, as multiple discrete regimes on the phylogenetic tree, + and/or with continuous covariates. See also Hansen (1997) , + Butler & King (2004) , Hansen et al. (2008) . + date_publication: '2024-02-15' + bug_reports: https://github.com/kopperud/slouch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=slouch + url_git: https://github.com/kopperud/slouch +slowraker: + version: 0.1.1 + title: |- + A Slow Version of the Rapid Automatic Keyword Extraction (RAKE) + Algorithm + maintainer: Christopher Baker + description: A mostly pure-R implementation of the RAKE algorithm (Rose, S., Engel, + D., Cramer, N. and Cowley, W. (2010) ), which can + be used to extract keywords from documents without any training data. + date_publication: '2017-11-02' + bug_reports: https://github.com/crew102/slowraker/issues + url: https://crew102.github.io/slowraker/index.html + url_cran: https://CRAN.R-project.org/package=slowraker + url_git: '' +slp: + version: 1.0-5 + title: |- + Discrete Prolate Spheroidal (Slepian) Sequence Regression + Smoothers + maintainer: Wesley Burr + description: |- + Interface for creation of 'slp' class smoother objects for + use in Generalized Additive Models (as implemented by packages + 'gam' and 'mgcv'). + date_publication: '2016-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slp + url_git: '' +SLPresElection: + version: 1.0.0 + title: Presidential Election Data of "Sri Lanka" from 1982 to 2015 + maintainer: Amalan Mahendran + description: |- + Presidential Election data of "Sri Lanka"" is stored in Pdf + files, through Pdf scraping they are converted into data-frames and + stored in this R package. + date_publication: '2023-01-17' + bug_reports: https://github.com/Amalan-ConStat/SLPresElection/issues + url: https://amalan-constat.github.io/SLPresElection/index.html + url_cran: https://CRAN.R-project.org/package=SLPresElection + url_git: https://github.com/Amalan-ConStat/SLPresElection +slr: + version: 1.3.0 + title: Semi-Latin Rectangles + maintainer: Baidya Nath Mandal + description: 'A facility to generate balanced semi-Latin rectangles with any cell + size (preferably up to ten) with given number of treatments, see Uto, N.P. and + Bailey, R.A. (2020). "Balanced Semi-Latin rectangles: properties, existence and + constructions for block size two". Journal of Statistical Theory and Practice, + 14(3), 1-11, . It also provides facility to generate + partially balanced semi-Latin rectangles for cell size 2, 3 and 4 for any number + of treatments.' + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=slr + url_git: '' +SLSEdesign: + version: 0.0.3 + title: |- + Optimal Regression Design under the Second-Order Least Squares + Estimator + maintainer: Chi-Kuang Yeh + description: With given inputs that include number of points, discrete design space, + a measure of skewness, models and parameter value, this package calculates the + objective value, optimal designs and plot the equivalence theory under A- and + D-optimal criteria under the second-order Least squares estimator. This package + is based on the paper "Properties of optimal regression designs under the second-order + least squares estimator" by Chi-Kuang Yeh and Julie Zhou (2021) . + date_publication: '2024-05-29' + bug_reports: https://github.com/chikuang/SLSEdesign/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SLSEdesign + url_git: https://github.com/chikuang/SLSEdesign +SLTCA: + version: 0.1.0 + title: Scalable and Robust Latent Trajectory Class Analysis + maintainer: Teng Fei + description: Conduct latent trajectory class analysis with longitudinal data. Our + method supports longitudinal continuous, binary and count data. For more methodological + details, please refer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable + and robust latent trajectory class analysis using artificial likelihood. Biometrics + . + date_publication: '2020-09-23' + bug_reports: https://github.com/tengfei-emory/SLTCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SLTCA + url_git: '' +slurmR: + version: 0.5-4 + title: A Lightweight Wrapper for 'Slurm' + maintainer: George Vega Yon + description: |- + 'Slurm', Simple Linux Utility for Resource Management + , is a popular 'Linux' based software used to + schedule jobs in 'HPC' (High Performance Computing) clusters. This R package + provides a specialized lightweight wrapper of 'Slurm' with a syntax similar to + that found in the 'parallel' R package. The package also includes a method for + creating socket cluster objects spanning multiple nodes that can be used with + the 'parallel' package. + date_publication: '2023-08-30' + bug_reports: https://github.com/USCbiostats/slurmR/issues + url: https://slurm.schedmd.com/ + url_cran: https://CRAN.R-project.org/package=slurmR + url_git: https://github.com/USCbiostats/slurmR +sm: + version: 2.2-6.0 + title: |- + Smoothing Methods for Nonparametric Regression and Density + Estimation + maintainer: Adrian Bowman + description: |- + This is software linked to the book + 'Applied Smoothing Techniques for Data Analysis - + The Kernel Approach with S-Plus Illustrations' Oxford University Press. + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sm + url_git: '' +smaa: + version: 0.3-3 + title: Stochastic Multi-Criteria Acceptability Analysis + maintainer: Gert van Valkenhoef + description: Implementation of the Stochastic Multi-Criteria Acceptability Analysis + (SMAA) family of Multiple Criteria Decision Analysis (MCDA) methods. Tervonen, + T. and Figueira, J. R. (2008) . + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smaa + url_git: https://github.com/gertvv/rsmaa +smacof: + version: 2.1-7 + title: Multidimensional Scaling + maintainer: Patrick Mair + description: 'Implements the following approaches for multidimensional scaling (MDS) + based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline + MDS on symmetric dissimilarity matrices, MDS with external constraints on the + configuration, individual differences scaling (idioscal, indscal), MDS with spherical + restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, + row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, + permutation tests, MDS biplots, gravity models, unidimensional scaling, drift + vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as + well.' + date_publication: '2024-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smacof + url_git: '' +smacofx: + version: 1.6-1 + title: Flexible Multidimensional Scaling and 'smacof' Extensions + maintainer: Thomas Rusch + description: 'Flexible multidimensional scaling (MDS) methods and extensions to + the package ''smacof''. This package contains various functions, wrappers, methods + and classes for fitting, plotting and displaying a large number of different flexible + MDS models (some as of yet unpublished). These are: Torgerson scaling (Torgerson, + 1958, ISBN:978-0471879459) with powers, Sammon mapping (Sammon, 1969, ) + with ratio and interval optimal scaling, Multiscale MDS (Ramsay, 1977, ) + with ratio and interval optimal scaling, S-stress MDS (ALSCAL; Takane, Young & + De Leeuw, 1977, ) with ratio and interval optimal scaling, + elastic scaling (McGee, 1966, ) with ratio + and interval optimal scaling, r-stress MDS (De Leeuw, Groenen & Mair, 2016, ) + with ratio, interval and non-metric optimal scaling, power-stress MDS (POST-MDS; + Buja & Swayne, 2002 ) with ratio and interval optimal + scaling, restricted power-stress (Rusch, Mair & Hornik, 2021, ) + with ratio and interval optimal scaling, approximate power-stress with ratio optimal + scaling (Rusch, Mair & Hornik, 2021, ), Box-Cox + MDS (Chen & Buja, 2013, ), local MDS + (Chen & Buja, 2009, ), curvilinear component analysis + (Demartines & Herault, 1997, ) and curvilinear distance + analysis (Lee, Lendasse & Verleysen, 2004, ). + There also are experimental models (e.g., sparsified MDS and sparsified POST-MDS). + Some functions are suitably flexible to allow any other sensible combination of + explicit power transformations for weights, distances and input proximities with + implicit ratio, interval or non-metric optimal scaling of the input proximities. + Most functions use a Majorization-Minimization algorithm. Currently the methods + are only available for one-mode data (symmetric dissimilarity matrices).' + date_publication: '2024-09-22' + bug_reports: https://r-forge.r-project.org/tracker/?atid=5375&group_id=2037&func=browse + url: '' + url_cran: https://CRAN.R-project.org/package=smacofx + url_git: https://r-forge.r-project.org/projects/stops/ +smacpod: + version: 2.6.4 + title: Statistical Methods for the Analysis of Case-Control Point Data + maintainer: Joshua French + description: Statistical methods for analyzing case-control point data. Methods + include the ratio of kernel densities, the difference in K Functions, the spatial + scan statistic, and q nearest neighbors of cases. + date_publication: '2024-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smacpod + url_git: '' +smallarea: + version: '0.1' + title: Fits a Fay Herriot Model + maintainer: Abhishek Nandy + description: Inference techniques for Fay Herriot Model. + date_publication: '2015-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smallarea + url_git: '' +SmallCountRounding: + version: 1.2.0 + title: Small Count Rounding of Tabular Data + maintainer: Øyvind Langsrud + description: A statistical disclosure control tool to protect frequency tables in + cases where small values are sensitive. The function PLSrounding() performs small + count rounding of necessary inner cells so that all small frequencies of cross-classifications + to be published (publishable cells) are rounded. This is equivalent to changing + micro data since frequencies of unique combinations are changed. Thus, additivity + and consistency are guaranteed. The methodology is described in Langsrud and Heldal + (2018) . + date_publication: '2025-02-05' + bug_reports: https://github.com/statisticsnorway/ssb-smallcountrounding/issues + url: https://statisticsnorway.github.io/ssb-smallcountrounding/ + url_cran: https://CRAN.R-project.org/package=SmallCountRounding + url_git: https://github.com/statisticsnorway/ssb-smallcountrounding +smallsets: + version: 2.0.0 + title: Visual Documentation for Data Preprocessing + maintainer: Lydia R. Lucchesi + description: |- + Data practitioners regularly use the 'R' and 'Python' programming languages to + prepare data for analyses. Thus, they encode important data preprocessing decisions in + 'R' and 'Python' code. The 'smallsets' package subsequently decodes these decisions into + a Smallset Timeline, a static, compact visualisation of data preprocessing decisions + (Lucchesi et al. (2022) ). The visualisation consists of + small data snapshots of different preprocessing steps. The 'smallsets' package builds this + visualisation from a user's dataset and preprocessing code located in an 'R', 'R Markdown', + 'Python', or 'Jupyter Notebook' file. Users simply add structured comments with snapshot + instructions to the preprocessing code. One optional feature in 'smallsets' requires + installation of the 'Gurobi' optimisation software and 'gurobi' 'R' package, available + from . More information regarding the optional feature and + 'gurobi' installation can be found in the 'smallsets' vignette. + date_publication: '2023-12-05' + bug_reports: '' + url: https://lydialucchesi.github.io/smallsets/ + url_cran: https://CRAN.R-project.org/package=smallsets + url_git: https://github.com/lydialucchesi/smallsets +smallstuff: + version: 1.0.3 + title: Dr. Small's Functions + maintainer: Ellie Small + description: Functions used in courses taught by Dr. Small at Drew University. + date_publication: '2024-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smallstuff + url_git: '' +smam: + version: 0.7.2 + title: Statistical Modeling of Animal Movements + maintainer: Chaoran Hu + description: |- + Animal movement models including Moving-Resting Process + with Embedded Brownian Motion + (Yan et al., 2014, ; + Pozdnyakov et al., 2017, ), + Brownian Motion with Measurement Error + (Pozdnyakov et al., 2014, ), + Moving-Resting-Handling Process with Embedded Brownian Motion + (Pozdnyakov et al., 2020, ), + Moving-Resting Process with Measurement Error + (Hu et al., 2021, ), + Moving-Moving Process with two Embedded Brownian Motions. + date_publication: '2024-01-10' + bug_reports: https://github.com/ChaoranHu/smam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smam + url_git: https://github.com/ChaoranHu/smam +SMARTbayesR: + version: 2.0.0 + title: |- + Bayesian Set of Best Dynamic Treatment Regimes and Sample Size + in SMARTs for Binary Outcomes + maintainer: William Artman + description: |- + Permits determination of a set of + optimal dynamic treatment regimes and sample size for a SMART design + in the Bayesian setting with binary outcomes. Please see Artman (2020) . + date_publication: '2021-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMARTbayesR + url_git: '' +smartDesign: + version: '0.74' + title: Sequential Multiple Assignment Randomized Trial Design + maintainer: Jason Sinnwell + description: SMART trial design, as described by He, J., McClish, D., Sabo, R. (2021) , + includes multiple stages of randomization, where participants are randomized to + an initial treatment in the first stage and then subsequently re-randomized between + treatments in the following stage. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smartDesign + url_git: '' +SmartEDA: + version: 0.3.10 + title: Summarize and Explore the Data + maintainer: Dayanand Ubrangala + description: Exploratory analysis on any input data describing the structure and + the relationships present in the data. The package automatically select the variable + and does related descriptive statistics. Analyzing information value, weight of + evidence, custom tables, summary statistics, graphical techniques will be performed + for both numeric and categorical predictors. + date_publication: '2024-01-30' + bug_reports: https://github.com/daya6489/SmartEDA/issues + url: https://daya6489.github.io/SmartEDA/ + url_cran: https://CRAN.R-project.org/package=SmartEDA + url_git: '' +smarter: + version: 1.0.1 + title: |- + A Collection of Modified R Functions to Make Basic Coding More + Convenient + maintainer: Paul Little + description: A collection of recycled and modified R functions to aid in file manipulation, + data exploration, wrangling, optimization, and object manipulation. Other functions + aid in convenient data visualization, loop progression, software packaging, and + installation. + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smarter + url_git: '' +SmarterPoland: + version: 1.8.1 + title: |- + Tools for Accessing Various Datasets Developed by the Foundation + SmarterPoland.pl + maintainer: Przemyslaw Biecek + description: 'Tools for accessing and processing datasets prepared by the Foundation + SmarterPoland.pl. Among all: access to API of Google Maps, Central Statistical + Office of Poland, MojePanstwo, Eurostat, WHO and other sources.' + date_publication: '2023-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SmarterPoland + url_git: '' +smartmap: + version: 0.1.1 + title: Smartly Create Maps from R Objects + maintainer: Stefan Fleck + description: |- + Preview spatial data as 'leaflet' maps with minimal + effort. smartmap is optimized for interactive use and distinguishes itself + from similar packages because it does not need real spatial ('sp' or 'sf') + objects an input; instead, it tries to automatically coerce everything that + looks like spatial data to sf objects or leaflet maps. It - for example - + supports direct mapping of: a vector containing a single coordinate pair, + a two column matrix, a data.frame with longitude and latitude columns, or + the path or URL to a (possibly compressed) 'shapefile'. + date_publication: '2020-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smartmap + url_git: '' +SmartMeterAnalytics: + version: 1.0.3 + title: Methods for Smart Meter Data Analysis + maintainer: Konstantin Hopf + description: |- + Methods for analysis of energy consumption data (electricity, gas, + water) at different data measurement intervals. The package provides feature extraction + methods and algorithms to prepare data for data mining and machine learning + applications. Deatiled descriptions of the methods and their application can be found + in Hopf (2019, ISBN:978-3-86309-669-4) "Predictive Analytics for Energy Efficiency and + Energy Retailing" and Hopf et al. (2016) + "Enhancing energy efficiency in the residential sector with smart meter data analytics". + date_publication: '2020-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SmartMeterAnalytics + url_git: '' +SMARTp: + version: 0.1.1 + title: Sample Size for SMART Designs in Non-Surgical Periodontal Trials + maintainer: Dipankar Bandyopadhyay + description: Sample size calculation to detect dynamic treatment regime (DTR) effects + based on change in clinical attachment level (CAL) outcomes from a non-surgical + chronic periodontitis treatments study. The experiment is performed under a Sequential + Multiple Assignment Randomized Trial (SMART) design. The clustered tooth (sub-unit) + level CAL outcomes are skewed, spatially-referenced, and non-randomly missing. + The implemented algorithm is available in Xu et al. (2019+) . + date_publication: '2019-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMARTp + url_git: https://github.com/bandyopd/SMARTp +smartsheetr: + version: 0.1.0 + title: |- + Access and Write 'Smartsheet' Data using the 'Smartsheet' API + 2.0 + maintainer: Cole Johanson + description: |- + Interact with the 'Smartsheet' platform through the 'Smartsheet' + API 2.0. . API is an acronym for + application programming interface; the 'Smartsheet' API allows users to + interact with 'Smartsheet' sheets directly within R. + date_publication: '2023-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smartsheetr + url_git: '' +smartsizer: + version: 1.0.3 + title: Power Analysis for a SMART Design + maintainer: William Artman + description: |- + A set of tools for determining the necessary sample size + in order to identify the optimal dynamic treatment regime + in a sequential, multiple assignment, randomized trial (SMART). + Utilizes multiple comparisons with the best methodology + to adjust for multiple comparisons. + Designed for an arbitrary SMART design. Please see Artman (2018) for more details. + date_publication: '2021-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smartsizer + url_git: '' +smartsnp: + version: 1.1.0 + title: Fast Multivariate Analyses of Big Genomic Data + maintainer: Christian Huber + description: Fast computation of multivariate analyses of small (10s to 100s markers) + to big (1000s to 100000s) genotype data. Runs Principal Component Analysis allowing + for centering, z-score standardization and scaling for genetic drift, projection + of ancient samples to modern genetic space and multivariate tests for differences + in group location (Permutation-Based Multivariate Analysis of Variance) and dispersion + (Permutation-Based Multivariate Analysis of Dispersion). + date_publication: '2021-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smartsnp + url_git: '' +SmartSVA: + version: 0.1.3 + title: Fast and Robust Surrogate Variable Analysis + maintainer: Jun Chen + description: Introduces a fast and efficient Surrogate Variable Analysis algorithm + that captures variation of unknown sources (batch effects) for high-dimensional + data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' + package and proposes a revision on it that achieves an order of magnitude faster + running time while trading no accuracy loss in return. + date_publication: '2017-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SmartSVA + url_git: '' +SMASH: + version: 1.0.0 + title: Subclone Multiplicity Allocation and Somatic Heterogeneity + maintainer: Paul Little + description: Cluster user-supplied somatic read counts with corresponding allele-specific + copy number and tumor purity to infer feasible underlying intra-tumor heterogeneity + in terms of number of subclones, multiplicity, and allocation (Little et al. + (2019) ). + date_publication: '2025-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMASH + url_git: '' +smatr: + version: 3.4-8 + title: (Standardised) Major Axis Estimation and Testing Routines + maintainer: Remko Duursma + description: |- + Methods for fitting bivariate lines in + allometry using the major axis (MA) or standardised major axis (SMA), and + for making inferences about such lines. The available methods of inference + include confidence intervals and one-sample tests for slope and elevation, + testing for a common slope or elevation amongst several allometric lines, + constructing a confidence interval for a common slope or elevation, and + testing for no shift along a common axis, amongst several samples. + See Warton et al. 2012 for methods description. + date_publication: '2018-03-18' + bug_reports: '' + url: http://web.maths.unsw.edu.au/~dwarton + url_cran: https://CRAN.R-project.org/package=smatr + url_git: http://www.bitbucket.org/remkoduursma/smatr +smbinning: + version: '0.9' + title: Scoring Modeling and Optimal Binning + maintainer: Herman Jopia + description: |- + A set of functions to build a scoring model from beginning to end, leading the user + to follow an efficient and organized development process, reducing significantly the time + spent on data exploration, variable selection, feature engineering, binning and model selection + among other recurrent tasks. + The package also incorporates monotonic and customized binning, scaling capabilities that + transforms logistic coefficients into points for a better business understanding and + calculates and visualizes classic performance metrics of a classification model. + date_publication: '2019-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smbinning + url_git: '' +SmCCNet: + version: 2.0.3 + title: Sparse Multiple Canonical Correlation Network Analysis Tool + maintainer: Weixuan Liu + description: A canonical correlation based framework (SmCCNet) designed for the + construction of phenotype-specific multi-omics networks. This framework adeptly + integrates single or multiple omics data types along with a quantitative or binary + phenotype of interest. It offers a streamlined setup process that can be tailored + manually or configured automatically, ensuring a flexible and user-friendly experience. + date_publication: '2024-04-16' + bug_reports: '' + url: https://kechrislab.github.io/SmCCNet/ + url_cran: https://CRAN.R-project.org/package=SmCCNet + url_git: https://github.com/KechrisLab/SmCCNet +smcfcs: + version: 1.9.2 + title: |- + Multiple Imputation of Covariates by Substantive Model + Compatible Fully Conditional Specification + maintainer: Jonathan Bartlett + description: |- + Implements multiple imputation of missing covariates by + Substantive Model Compatible Fully Conditional Specification. + This is a modification of the popular FCS/chained equations + multiple imputation approach, and allows imputation of missing + covariate values from models which are compatible with the user + specified substantive model. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smcfcs + url_git: https://github.com/jwb133/smcfcs +SMCRM: + version: 0.0-3 + title: |- + Data Sets for Statistical Methods in Customer Relationship + Management by Kumar and Petersen (2012). + maintainer: Tobias Verbeke + description: |- + Data Sets for Kumar and Petersen (2012). + Statistical Methods in Customer Relationship Management, + Wiley: New York. + date_publication: '2013-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMCRM + url_git: '' +smcryptoR: + version: 0.1.2 + title: ShangMi(SM) Cryptographic Algorithms(SM2/SM3/SM4) + maintainer: Meng Yu + description: |- + Bindings to 'smcrypto' : a 'Rust' + implementation of China's Standards of Encryption Algorithms, which is usually + called 'ShangMi(SM)' algorithms. It contains 'SM3' message digest algorithm, + 'SM2' asymmetric encryption algorithm and 'SM4' symmetric encryption algorithm. + Users can do message hash, encrypt/decrypt, sign/verify, key exchange and more. + date_publication: '2024-03-18' + bug_reports: https://github.com/zhuobie/smcryptoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smcryptoR + url_git: https://github.com/zhuobie/smcryptoR +smcure: + version: '2.1' + title: Fit Semiparametric Mixture Cure Models + maintainer: Chao Cai + description: An R-package for Estimating Semiparametric PH and AFT Mixture Cure + Models. + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smcure + url_git: '' +smd: + version: 0.8.0 + title: Compute Standardized Mean Differences + maintainer: Bradley Saul + description: |- + Computes standardized mean differences and confidence intervals for + multiple data types based on Yang, D., & Dalton, J. E. (2012) + . + date_publication: '2025-02-12' + bug_reports: https://github.com/bsaul/smd/issues + url: https://bsaul.github.io/smd/ + url_cran: https://CRAN.R-project.org/package=smd + url_git: '' +smdata: + version: '1.2' + title: Data to Accompany Smithson & Merkle, 2013 + maintainer: Ed Merkle + description: Contains data files to accompany Smithson & Merkle (2013), Generalized + Linear Models for Categorical and Continuous Limited Dependent Variables. + date_publication: '2018-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smdata + url_git: '' +smdi: + version: 0.3.1 + title: Perform Structural Missing Data Investigations + maintainer: Janick Weberpals + description: 'An easy to use implementation of routine structural missing data diagnostics + with functions to visualize the proportions of missing observations, investigate + missing data patterns and conduct various empirical missing data diagnostic tests. + Reference: Weberpals J, Raman SR, Shaw PA, Lee H, Hammill BG, Toh S, Connolly + JG, Dandreo KJ, Tian F, Liu W, Li J, Hernández-Muñoz JJ, Glynn RJ, Desai RJ. smdi: + an R package to perform structural missing data investigations on partially observed + confounders in real-world evidence studies. JAMIA Open. 2024 Jan 31;7(1):ooae008. + .' + date_publication: '2024-10-04' + bug_reports: https://gitlab-scm.partners.org/janickweberpals/smdi/-/issues + url: https://janickweberpals.gitlab-pages.partners.org/smdi/ + url_cran: https://CRAN.R-project.org/package=smdi + url_git: '' +SMDIC: + version: 0.1.6 + title: Identification of Somatic Mutation-Driven Immune Cells + maintainer: Junwei Han + description: 'A computing tool is developed to automated identify somatic mutation-driven + immune cells. The operation modes including: i) inferring the relative abundance + matrix of tumor-infiltrating immune cells and integrating it with a particular + gene mutation status, ii) detecting differential immune cells with respect to + the gene mutation status and converting the abundance matrix of significant differential + immune cell into two binary matrices (one for up-regulated and one for down-regulated), + iii) identifying somatic mutation-driven immune cells by comparing the gene mutation + status with each immune cell in the binary matrices across all samples, and iv) + visualization of immune cell abundance of samples in different mutation status..' + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMDIC + url_git: '' +smdocker: + version: 0.1.4 + title: |- + Build 'Docker Images' in 'Amazon SageMaker Studio' using 'Amazon + Web Service CodeBuild' + maintainer: Dyfan Jones + description: |- + Allows users to easily build custom 'docker images' from + 'Amazon Web Service Sagemaker' using + 'Amazon Web Service CodeBuild' . + date_publication: '2023-06-07' + bug_reports: https://github.com/DyfanJones/sm-docker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smdocker + url_git: https://github.com/DyfanJones/sm-docker +smer: + version: 0.0.1 + title: Sparse Marginal Epistasis Test + maintainer: Julian Stamp + description: |- + The Sparse Marginal Epistasis Test is a computationally efficient + genetics method which detects statistical epistasis in complex traits; + see Stamp et al. (2025, ) for details. + date_publication: '2025-01-16' + bug_reports: https://github.com/lcrawlab/sme/issues + url: https://lcrawlab.github.io/sme/ + url_cran: https://CRAN.R-project.org/package=smer + url_git: https://github.com/lcrawlab/sme +smerc: + version: 1.8.4 + title: Statistical Methods for Regional Counts + maintainer: Joshua French + description: Implements statistical methods for analyzing the counts of areal data, + with a focus on the detection of spatial clusters and clustering. The package + has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff + and Nagarwalla (1995) and Kulldorff (1997) . + date_publication: '2024-10-24' + bug_reports: https://github.com/jfrench/smerc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smerc + url_git: '' +smetlite: + version: 0.2.10 + title: Read and Write SMET Files + maintainer: Reinhold Koch + description: |- + Simple class to hold contents of a SMET file as specified in + Bavay (2021) . + There numerical meteorological measurements are all based on MKS (SI) units + and timestamp is standardized to UTC time. + date_publication: '2023-11-09' + bug_reports: '' + url: https://baseldatascience.github.io/smetlite/ + url_cran: https://CRAN.R-project.org/package=smetlite + url_git: https://github.com/BaselDataScience/smetlite +SMFilter: + version: 1.0.3 + title: |- + Filtering Algorithms for the State Space Models on the Stiefel + Manifold + maintainer: Yukai Yang + description: Provides the filtering algorithms for the state space models on the + Stiefel manifold as well as the corresponding sampling algorithms for uniform, + vector Langevin-Bingham and matrix Langevin-Bingham distributions on the Stiefel + manifold. + date_publication: '2018-12-12' + bug_reports: https://github.com/yukai-yang/SMFilter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SMFilter + url_git: https://github.com/yukai-yang/SMFilter +smfishHmrf: + version: '0.1' + title: Hidden Markov Random Field for Spatial Transcriptomic Data + maintainer: Qian Zhu + description: Discovery of spatial patterns with Hidden Markov Random Field. This + package is designed for spatial transcriptomic data and single molecule fluorescent + in situ hybridization (FISH) data such as sequential fluorescence in situ hybridization + (seqFISH) and multiplexed error-robust fluorescence in situ hybridization (MERFISH). + The methods implemented in this package are described in Zhu et al. (2018) . + date_publication: '2020-11-03' + bug_reports: https://bitbucket.org/qzhudfci/smfishhmrf-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smfishHmrf + url_git: https://bitbucket.org/qzhudfci/smfishhmrf-r/src/master/ +smfsb: + version: '1.5' + title: Stochastic Modelling for Systems Biology + maintainer: Darren Wilkinson + description: Code and data for modelling and simulation of stochastic kinetic biochemical + network models. It contains the code and data associated with the second and third + editions of the book Stochastic Modelling for Systems Biology, published by Chapman + & Hall/CRC Press. + date_publication: '2024-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smfsb + url_git: '' +smicd: + version: 1.1.5 + title: Statistical Methods for Interval-Censored Data + maintainer: Paul Walter + description: Functions that provide statistical methods for interval-censored (grouped) + data. The package supports the estimation of linear and linear mixed regression + models with interval-censored dependent variables. Parameter estimates are obtained + by a stochastic expectation maximization algorithm. Furthermore, the package enables + the direct (without covariates) estimation of statistical indicators from interval-censored + data via an iterative kernel density algorithm. Survey and Organisation for Economic + Co-operation and Development (OECD) weights can be included into the direct estimation + (see, Walter, P. (2019) ). + date_publication: '2024-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smicd + url_git: '' +smidm: + version: '1.0' + title: Statistical Modelling for Infectious Disease Management + maintainer: Sonja Jäckle + description: Statistical models for specific coronavirus disease 2019 use cases + at German local health authorities. All models of Statistical modelling for infectious + disease management 'smidm' are part of the decision support toolkit in the 'EsteR' + project. More information is published in Sonja Jäckle, Rieke Alpers, Lisa Kühne, + Jakob Schumacher, Benjamin Geisler, Max Westphal "'EsteR' – A Digital Toolkit + for COVID-19 Decision Support in Local Health Authorities" (2022) + and Sonja Jäckle, Elias Röger, Volker Dicken, Benjamin Geisler, Jakob Schumacher, + Max Westphal "A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine + Decisions" (2021) . + date_publication: '2022-08-27' + bug_reports: https://gitlab.cc-asp.fraunhofer.de/ester/smidm/-/issues + url: https://gitlab.cc-asp.fraunhofer.de/ester/smidm + url_cran: https://CRAN.R-project.org/package=smidm + url_git: '' +smile: + version: 1.0.5 + title: 'Spatial Misalignment: Interpolation, Linkage, and Estimation' + maintainer: Lucas da Cunha Godoy + description: |- + Provides functions to estimate, predict and interpolate areal + data. For estimation and prediction we assume areal data is an average + of an underlying continuous spatial process as in Moraga et + al. (2017) , Johnson et al. (2020) + , and Wilson and Wakefield (2020) + . The interpolation methodology is + (mostly) based on Goodchild and Lam (1980, ISSN:01652273). + date_publication: '2024-06-14' + bug_reports: https://github.com/lcgodoy/smile/issues/ + url: https://lcgodoy.me/smile/ + url_cran: https://CRAN.R-project.org/package=smile + url_git: https://github.com/lcgodoy/smile/ +smiles: + version: 0.1-0 + title: Sequential Method in Leading Evidence Synthesis + maintainer: Enoch Kang + description: Trial sequential analysis emerges as an important method in data synthesis + realm. It is necessary to integrate pooling methods and sequential analysis coherently, + as discussed in the Chapter by Thomas, J., Askie, L.M., Berlin, J.A., Elliott, + J.H., Ghersi, D., Simmonds, M., Takwoingi, Y., Tierney, J.F. and Higgins, J.P. + (2019). "Prospective approaches to accumulating evidence". In Cochrane Handbook + for Systematic Reviews of Interventions (eds J.P.T. Higgins, J. Thomas, J. Chandler, + M. Cumpston, T. Li, M.J. Page and V.A. Welch). . + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smiles + url_git: '' +smirnov: + version: 1.0-1 + title: |- + Provides two taxonomic coefficients from E. S. Smirnov + "Taxonomic analysis" (1969) book + maintainer: Alexey Shipunov + description: |- + This tiny package contains one function smirnov() which + calculates two scaled taxonomic coefficients, Txy (coefficient + of similarity) and Txx (coefficient of originality). These two + characteristics may be used for the analysis of similarities + between any number of taxonomic groups, and also for assessing + uniqueness of giving taxon. It is possible to use smirnov() + output as a distance measure: convert it to distance by + "as.dist(1 - smirnov(x))". + date_publication: '2012-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smirnov + url_git: '' +SmithWilsonYieldCurve: + version: 1.1.1 + title: Smith-Wilson Yield Curve Construction + maintainer: Phil Joubert + description: |- + Constructs a yield curve by the Smith-Wilson method from a table of + libor and swap rates. Now updated to take bond coupons and prices + in the same table. + date_publication: '2024-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SmithWilsonYieldCurve + url_git: '' +SMITIDstruct: + version: 0.0.5 + title: |- + Data Structure and Manipulations Tool for Host and Viral + Population + maintainer: Jean-Francois Rey + description: |- + Statistical Methods for Inferring Transmissions of Infectious Diseases from deep sequencing data (SMITID). + It allow sequence-space-time host and viral population data storage, indexation and querying. + date_publication: '2019-06-14' + bug_reports: https://gitlab.paca.inra.fr/SMITID/structR/issues + url: https://informatique-mia.inra.fr/biosp/anr-smitid-project + url_cran: https://CRAN.R-project.org/package=SMITIDstruct + url_git: '' +SMITIDvisu: + version: 0.0.9 + title: |- + Visualize Data for Host and Viral Population from 'SMITIDstruct' + using 'HTMLwidgets' + maintainer: Jean-Francois Rey + description: |- + Visualisation tools for 'SMITIDstruct' package. + Allow to visualize host timeline, transmission tree, index diversities + and variant graph using 'HTMLwidgets'. It mainly using 'D3JS' javascript framework. + date_publication: '2021-02-08' + bug_reports: '' + url: https://informatique-mia.inrae.fr/biosp/anr-smitid-project/ + url_cran: https://CRAN.R-project.org/package=SMITIDvisu + url_git: '' +SMLE: + version: 2.2-2 + title: Joint Feature Screening via Sparse MLE + maintainer: Qianxiang Zang + description: Feature screening is a powerful tool in processing ultrahigh dimensional + data. It attempts to screen out most irrelevant features in preparation for a + more elaborate analysis. Xu and Chen (2014) + proposed an effective screening method SMLE, which naturally incorporates the + joint effects among features in the screening process. This package provides an + efficient implementation of SMLE-screening for high-dimensional linear, logistic, + and Poisson models. The package also provides a function for conducting accurate + post-screening feature selection based on an iterative hard-thresholding procedure + and a user-specified selection criterion. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMLE + url_git: '' +smlePH: + version: 0.1.0 + title: |- + Sieve Maximum Full Likelihood Estimation for the Right-Censored + Proportional Hazards Model + maintainer: Taehwa Choi + description: |- + Fitting the full likelihood proportional hazards model and + extracting the residuals. + date_publication: '2024-05-17' + bug_reports: https://github.com/taehwa015/smlePH/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=smlePH + url_git: https://github.com/taehwa015/smlePH/ +smlmkalman: + version: 0.1.1 + title: Generation and Tracking of Super-Resolution Filamentous Datasets + maintainer: Andrew Buist + description: |- + A pair of functions that allow for the generation and tracking of coordinate data clouds without a time dimension, + primarily for use in super-resolution plant micro-tubule image segmentation. + date_publication: '2022-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smlmkalman + url_git: '' +SMLoutliers: + version: '0.1' + title: Outlier Detection Using Statistical and Machine Learning Methods + maintainer: Siddharth Jain + description: Local Correlation Integral (LOCI) method for outlier identification + is implemented here. The LOCI method developed here is invented in Breunig, et + al. (2000), see . + date_publication: '2017-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMLoutliers + url_git: '' +SMM: + version: 1.0.2 + title: |- + Simulation and Estimation of Multi-State Discrete-Time + Semi-Markov and Markov Models + maintainer: Nicolas Vergne + description: |- + Performs parametric and non-parametric estimation and simulation for multi-state discrete-time semi-Markov processes. + For the parametric estimation, several discrete distributions are considered for the sojourn times: Uniform, Geometric, Poisson, Discrete Weibull and Negative Binomial. The non-parametric estimation concerns the sojourn time distributions, where no assumptions are done on the shape of distributions. + Moreover, the estimation can be done on the basis of one or several sample paths, with or without censoring at the beginning or/and at the end of the sample paths. The implemented methods are described in Barbu, V.S., Limnios, N. (2008) , Barbu, V.S., Limnios, N. (2008) and + Trevezas, S., Limnios, N. (2011) . + Estimation and simulation of discrete-time k-th order Markov chains are also considered. + date_publication: '2020-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMM + url_git: '' +SMMA: + version: 1.0.3 + title: Soft Maximin Estimation for Large Scale Array-Tensor Models + maintainer: Adam Lund + description: Efficient design matrix free procedure for solving a soft maximin problem + for large scale array-tensor structured models, see Lund, Mogensen and Hansen + (2019) . Currently Lasso and SCAD penalized estimation is implemented. + date_publication: '2020-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMMA + url_git: '' +SMME: + version: 1.1.1 + title: Soft Maximin Estimation for Large Scale Heterogeneous Data + maintainer: Adam Lund + description: Efficient procedure for solving the soft maximin problem for large + scale heterogeneous data, see Lund, Mogensen and Hansen (2022) . + Currently Lasso and SCAD penalized estimation is implemented. Note this package + subsumes and replaces the SMMA package. + date_publication: '2023-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMME + url_git: '' +smmR: + version: 1.0.3 + title: Simulation, Estimation and Reliability of Semi-Markov Models + maintainer: Nicolas Vergne + description: |- + Performs parametric and non-parametric estimation and simulation + for multi-state discrete-time semi-Markov processes. For the parametric + estimation, several discrete distributions are considered for the sojourn + times: Uniform, Geometric, Poisson, Discrete Weibull and Negative Binomial. + The non-parametric estimation concerns the sojourn time distributions, + where no assumptions are done on the shape of distributions. Moreover, the + estimation can be done on the basis of one or several sample paths, with or + without censoring at the beginning or/and at the end of the sample paths. + Reliability indicators such as reliability, maintainability, availability, + BMP-failure rate, RG-failure rate, mean time to failure and mean time to + repair are available as well. The implemented methods are described in + Barbu, V.S., Limnios, N. (2008) , + Barbu, V.S., Limnios, N. (2008) and + Trevezas, S., Limnios, N. (2011) . + Estimation and simulation of discrete-time k-th order Markov chains are + also considered. + date_publication: '2021-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smmR + url_git: '' +SMMT: + version: 1.2.0 + title: |- + The Swiss Municipal Data Merger Tool Maps Municipalities Over + Time + maintainer: Valentin Knechtl + description: |- + In Switzerland, the landscape of municipalities is changing rapidly + mainly due to mergers. The Swiss Municipal Data Merger Tool + automatically detects these mutations and maps municipalities over time, i.e. municipalities of an old state + to municipalities of a new state. This functionality is helpful when working + with datasets that are based on different spatial references. The package's idea and use + case is discussed in the following article: . + date_publication: '2024-05-20' + bug_reports: https://github.com/ValValetl/SMMT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SMMT + url_git: https://github.com/ValValetl/SMMT +SMNCensReg: + version: '3.1' + title: |- + Fitting Univariate Censored Regression Model Under the Family of + Scale Mixture of Normal Distributions + maintainer: Aldo M. Garay + description: Fit univariate right, left or interval censored regression model under + the scale mixture of normal distributions. + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMNCensReg + url_git: '' +SMNlmec: + version: 1.0.0 + title: |- + Scale Mixture of Normal Distribution in Linear Mixed-Effects + Model + maintainer: Kelin Zhong + description: Bayesian analysis of censored linear mixed-effects models that replace + Gaussian assumptions with a flexible class of distributions, such as the scale + mixture of normal family distributions, considering a damped exponential correlation + structure which was employed to account for within-subject autocorrelation among + irregularly observed measures. For more details, see Kelin Zhong, Fernanda L. + Schumacher, Luis M. Castro, Victor H. Lachos (2025) . + date_publication: '2025-01-30' + bug_reports: https://github.com/KelinZhong/SMNlmec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SMNlmec + url_git: https://github.com/KelinZhong/SMNlmec +smof: + version: 1.2.2 + title: Scoring Methodology for Ordered Factors + maintainer: Adelchi Azzalini + description: |- + Starting from a given object representing a fitted model + (within a certain set of model classes) whose (non-)linear predictor + includes some ordered factor(s) among the explanatory variables, a new + model is constructed and fitted where each named factor is replaced by a + single numeric score, suitably chosen so that the new variable produces a + fit comparable with the standard methodology based on a set of polynomial + contrasts. Two variants of the present approach have been developed, one in + each of the next references: Azzalini (2023) , (2024) + . + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smof + url_git: '' +smoke: + version: 2.0.1 + title: Small Molecule Octet/BLI Kinetics Experiment + maintainer: Qingan Sun + description: |- + Bio-Layer Interferometry (BLI) is a technology to determine the binding kinetics between biomolecules. BLI signals are small and noisy when small molecules are investigated as ligands (analytes). We develop this package to process and analyze the BLI data acquired on Octet Red96 from Fortebio more accurately. + Sun Q., Li X., et al (2020) . + In this new version, we organize the BLI experiment data and analysis methods into a S4 class with self-explaining structure. + date_publication: '2024-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smoke + url_git: '' +smoof: + version: 1.6.0.3 + title: Single and Multi-Objective Optimization Test Functions + maintainer: Jakob Bossek + description: |- + Provides generators for a high number of both single- and multi- + objective test functions which are frequently used for the benchmarking of + (numerical) optimization algorithms. Moreover, it offers a set of convenient + functions to generate, plot and work with objective functions. + date_publication: '2023-03-10' + bug_reports: https://github.com/jakobbossek/smoof/issues + url: https://jakobbossek.github.io/smoof/ + url_cran: https://CRAN.R-project.org/package=smoof + url_git: https://github.com/jakobbossek/smoof +smooth: + version: 4.1.1 + title: Forecasting Using State Space Models + maintainer: Ivan Svetunkov + description: |- + Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. + The package includes ADAM (Svetunkov, 2023, ), + Exponential Smoothing (Hyndman et al., 2008, ), + SARIMA (Svetunkov & Boylan, 2019 ), + Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, ), + Simple Moving Average (Svetunkov & Petropoulos, 2018 ) + and several simulation functions. It also allows dealing with intermittent demand based on the + iETS framework (Svetunkov & Boylan, 2019, ). + date_publication: '2025-02-03' + bug_reports: https://github.com/config-i1/smooth/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smooth + url_git: https://github.com/config-i1/smooth +smoothedLasso: + version: '1.6' + title: |- + A Framework to Smooth L1 Penalized Regression Operators using + Nesterov Smoothing + maintainer: Georg Hahn + description: We provide full functionality to smooth L1 penalized regression operators + and to compute regression estimates thereof. For this, the objective function + of a user-specified regression operator is first smoothed using Nesterov smoothing + (see Y. Nesterov (2005) ), resulting in a modified + objective function with explicit gradients everywhere. The smoothed objective + function and its gradient are minimized via BFGS, and the obtained minimizer is + returned. Using Nesterov smoothing, the smoothed objective function can be made + arbitrarily close to the original (unsmoothed) one. In particular, the Nesterov + approach has the advantage that it comes with explicit accuracy bounds, both on + the L1/L2 difference of the unsmoothed to the smoothed objective functions as + well as on their respective minimizers (see G. Hahn, S.M. Lutz, N. Laha, C. Lange + (2020) ). A progressive smoothing approach is provided + which iteratively smoothes the objective function, resulting in more stable regression + estimates. A function to perform cross validation for selection of the regularization + parameter is provided. + date_publication: '2021-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smoothedLasso + url_git: '' +smoother: + version: '1.3' + title: Functions Relating to the Smoothing of Numerical Data + maintainer: Nicholas Hamilton + description: |- + A collection of methods for smoothing numerical data, commencing + with a port of the Matlab gaussian window smoothing function. In addition, + several functions typically used in smoothing of financial data are included. + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smoother + url_git: '' +SmoothHazard: + version: 2024.04.10 + title: Estimation of Smooth Hazard Models for Interval-Censored Data + maintainer: Thomas Alexander Gerds + description: |- + Estimation of two-state (survival) models and irreversible illness- + death models with possibly interval-censored, left-truncated and right-censored + data. Proportional intensities regression models can be specified to allow for + covariates effects separately for each transition. We use either a parametric + approach with Weibull baseline intensities or a semi-parametric approach with + M-splines approximation of baseline intensities in order to obtain smooth + estimates of the hazard functions. Parameter estimates are obtained by maximum + likelihood in the parametric approach and by penalized maximum likelihood in the + semi-parametric approach. + date_publication: '2024-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SmoothHazard + url_git: '' +smoothHR: + version: 1.0.5 + title: Smooth Hazard Ratio Curves Taking a Reference Value + maintainer: Artur Araujo + description: |- + Provides flexible hazard ratio curves allowing non-linear + relationships between continuous predictors and survival. + To better understand the effects that each continuous covariate + has on the outcome, results are expressed in terms of hazard + ratio curves, taking a specific covariate value as reference. + Confidence bands for these curves are also derived. + date_publication: '2024-02-25' + bug_reports: https://github.com/arturstat/smoothHR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smoothHR + url_git: https://github.com/arturstat/smoothHR +smoothic: + version: 1.2.0 + title: Variable Selection Using a Smooth Information Criterion + maintainer: Meadhbh O'Neill + description: |- + Implementation of the SIC epsilon-telescope method, either + using single or distributional (multiparameter) regression. Includes classical regression + with normally distributed errors and robust regression, where the errors are from + the Laplace distribution. The "smooth generalized normal distribution" is used, + where the estimation of an additional shape parameter allows the user to move + smoothly between both types of regression. See O'Neill and Burke (2022) + "Robust Distributional Regression with Automatic Variable Selection" for more details. + . This package also contains the data analyses from O'Neill and + Burke (2023). "Variable selection using a smooth information criterion for distributional + regression models". . + date_publication: '2023-08-22' + bug_reports: '' + url: https://meadhbh-oneill.ie/smoothic/ + url_cran: https://CRAN.R-project.org/package=smoothic + url_git: https://github.com/meadhbh-oneill/smoothic +smoothie: + version: 1.0-4 + title: Two-Dimensional Field Smoothing + maintainer: Eric Gilleland + description: Perform two-dimensional smoothing for spatial fields using FFT and + the convolution theorem (see Gilleland 2013, ). + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smoothie + url_git: '' +smoothmest: + version: 0.1-3 + title: Smoothed M-Estimators for 1-Dimensional Location + maintainer: Christian Hennig + description: |- + Some M-estimators for 1-dimensional location (Bisquare, + ML for the Cauchy distribution, and the estimators from + application of the smoothing principle introduced in Hampel, + Hennig and Ronchetti (2011) to the above, the Huber + M-estimator, and the median, main function is smoothm), + and Pitman estimator. + date_publication: '2022-04-27' + bug_reports: '' + url: https://www.unibo.it/sitoweb/christian.hennig/en + url_cran: https://CRAN.R-project.org/package=smoothmest + url_git: '' +smoothr: + version: 1.0.1 + title: Smooth and Tidy Spatial Features + maintainer: Matthew Strimas-Mackey + description: |- + Tools for smoothing and tidying spatial features + (i.e. lines and polygons) to make them more aesthetically pleasing. + Smooth curves, fill holes, and remove small fragments from lines and + polygons. + date_publication: '2023-03-09' + bug_reports: https://github.com/mstrimas/smoothr/issues + url: https://strimas.com/smoothr/ + url_cran: https://CRAN.R-project.org/package=smoothr + url_git: https://github.com/mstrimas/smoothr +smoothROCtime: + version: 0.1.0 + title: Smooth Time-Dependent ROC Curve Estimation + maintainer: Susana Diaz-Coto + description: Computes smooth estimations for the Cumulative/Dynamic and Incident/Dynamic + ROC curves, in presence of right censorship, based on the bivariate kernel density + estimation of the joint distribution function of the Marker and Time-to-event + variables. + date_publication: '2018-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smoothROCtime + url_git: '' +smoothSurv: + version: '2.6' + title: Survival Regression with Smoothed Error Distribution + maintainer: Arnošt Komárek + description: |- + Contains, as a main contribution, a function to fit + a regression model with possibly right, left or interval + censored observations and with the error distribution + expressed as a mixture of G-splines. Core part + of the computation is done in compiled 'C++' written + using the 'Scythe' Statistical Library Version 0.3. + date_publication: '2023-12-13' + bug_reports: '' + url: https://msekce.karlin.mff.cuni.cz/~komarek/ + url_cran: https://CRAN.R-project.org/package=smoothSurv + url_git: '' +smoothtail: + version: 2.0.5 + title: Smooth Estimation of GPD Shape Parameter + maintainer: Kaspar Rufibach + description: Given independent and identically distributed observations X(1), ..., + X(n) from a Generalized Pareto distribution with shape parameter gamma in [-1,0], + offers several estimates to compute estimates of gamma. The estimates are based + on the principle of replacing the order statistics by quantiles of a distribution + function based on a log--concave density function. This procedure is justified + by the fact that the GPD density is log--concave for gamma in [-1,0]. + date_publication: '2016-07-13' + bug_reports: '' + url: http://www.kasparrufibach.ch + url_cran: https://CRAN.R-project.org/package=smoothtail + url_git: '' +SmoothTensor: + version: 0.1.1 + title: A Collection of Smooth Tensor Estimation Methods + maintainer: Chanwoo Lee + description: A list of methods for estimating a smooth tensor with an unknown permutation. + It also contains several multi-variate functions for generating permuted signal + tensors and corresponding observed tensors. For a detailed introduction for the + model and estimation techniques, see the paper by Chanwoo Lee and Miaoyan Wang + (2021) "Smooth tensor estimation with unknown permutations" . + date_publication: '2021-11-16' + bug_reports: '' + url: https://arxiv.org/abs/2111.04681 + url_cran: https://CRAN.R-project.org/package=SmoothTensor + url_git: '' +SmoothWin: + version: 3.0.0 + title: Soft Windowing on Linear Regression + maintainer: Hamed Haselimashhadi + description: The main function in the package utilizes a windowing function in the + form of an exponential weighting function to linear models. The bandwidth and + sharpness of the window are controlled by two parameters. Then, a series of tests + are used to identify the right parameters of the window (see Hamed Haselimashhadi + et al (2019) ). + date_publication: '2019-07-27' + bug_reports: '' + url: http://hamedhaseli.webs.com + url_cran: https://CRAN.R-project.org/package=SmoothWin + url_git: '' +smoothy: + version: 1.0.0 + title: |- + Automatic Estimation of the Most Likely Drug Combination using + Smooth Algorithm + maintainer: Dan Ouchi + description: 'A flexible moving average algorithm for modeling drug exposure in + pharmacoepidemiology studies as presented in the article: Ouchi, D., Giner-Soriano, + M., Gómez-Lumbreras, A., Vedia Urgell, C.,Torres, F., & Morros, R. (2022). "Automatic + Estimation of the Most Likely Drug Combination in Electronic Health Records Using + the Smooth Algorithm : Development and Validation Study." JMIR medical informatics, + 10(11), e37976. .' + date_publication: '2023-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smoothy + url_git: '' +smoots: + version: 1.1.4 + title: Nonparametric Estimation of the Trend and Its Derivatives in TS + maintainer: Dominik Schulz + description: |- + The nonparametric trend and its derivatives in equidistant time + series (TS) with short-memory stationary errors can be estimated. The + estimation is conducted via local polynomial regression using an + automatically selected bandwidth obtained by a built-in iterative plug-in + algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel + smoother is also built-in as a comparison. With version 1.1.0, a linearity + test for the trend function, forecasting methods and backtesting + approaches are implemented as well. + The smoothing methods of the package are described in Feng, Y., Gries, T., + and Fritz, M. (2020) . + date_publication: '2023-09-11' + bug_reports: '' + url: https://wiwi.uni-paderborn.de/en/dep4/feng/https://wiwi.uni-paderborn.de/dep4/gries/ + url_cran: https://CRAN.R-project.org/package=smoots + url_git: '' +smosr: + version: 1.0.1 + title: Acquire and Explore BEC-SMOS L4 Soil Moisture Data in R + maintainer: Tatiana A. Shestakova + description: |- + Provides functions that automate accessing, downloading and exploring Soil Moisture + and Ocean Salinity (SMOS) Level 4 (L4) data developed by Barcelona Expert Center (BEC). + Particularly, it includes functions to search for, acquire, extract, and plot BEC-SMOS L4 soil + moisture data downscaled to ~1 km spatial resolution. Note that SMOS is one of Earth Explorer + Opportunity missions by the European Space Agency (ESA). More information about SMOS + products can be found at . + date_publication: '2023-07-20' + bug_reports: https://github.com/tshestakova/smosr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smosr + url_git: https://github.com/tshestakova/smosr +smotefamily: + version: 1.4.0 + title: |- + A Collection of Oversampling Techniques for Class Imbalance + Problem Based on SMOTE + maintainer: Wacharasak Siriseriwan + description: A collection of various oversampling techniques developed from SMOTE + is provided. SMOTE is a oversampling technique which synthesizes a new minority + instance between a pair of one minority instance and one of its K nearest neighbor. Other + techniques adopt this concept with other criteria in order to generate balanced + dataset for class imbalance problem. + date_publication: '2024-03-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smotefamily + url_git: '' +SMOTEWB: + version: 1.2.0 + title: Imbalanced Resampling using SMOTE with Boosting (SMOTEWB) + maintainer: Fatih Saglam + description: |- + Provides the SMOTE with Boosting (SMOTEWB) algorithm. See + F. Sağlam, M. A. Cengiz (2022) . It is a + SMOTE-based resampling technique which creates synthetic data on the links + between nearest neighbors. SMOTEWB uses boosting weights to determine where + to generate new samples and automatically decides the number of neighbors + for eacg sample. It is robust to noise and outperforms most of the + alternatives according to Matthew Correlation Coefficient metric. + Alternative resampling methods are also available in the package. + date_publication: '2024-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMOTEWB + url_git: '' +smovie: + version: 1.1.6 + title: Some Movies to Illustrate Concepts in Statistics + maintainer: Paul J. Northrop + description: |- + Provides movies to help students to understand statistical + concepts. The 'rpanel' package + is used to create interactive plots that move to illustrate key statistical + ideas and methods. There are movies to: visualise probability distributions + (including user-supplied ones); illustrate sampling distributions of the + sample mean (central limit theorem), the median, the sample maximum + (extremal types theorem) and (the Fisher transformation of the) + product moment correlation coefficient; examine the influence of an + individual observation in simple linear regression; illustrate key concepts + in statistical hypothesis testing. Also provided are dpqr functions for the + distribution of the Fisher transformation of the correlation coefficient + under sampling from a bivariate normal distribution. + date_publication: '2023-12-03' + bug_reports: https://github.com/paulnorthrop/smovie/issues + url: https://paulnorthrop.github.io/smovie/ + url_cran: https://CRAN.R-project.org/package=smovie + url_git: https://github.com/paulnorthrop/smovie/ +smpic: + version: 0.1.0 + title: Creates Images Sized for Social Media + maintainer: Mikkel Freltoft Krogsholm + description: |- + Creates images that are the proper size for social media. Beautiful + plots, charts and graphs wither and die if they are not shared. Social media + is perfect for this but every platform has its own image dimensions. With + 'smpic' you can easily save your plots with the exact dimensions needed for + the different platforms. + date_publication: '2017-10-04' + bug_reports: https://github.com/mikkelkrogsholm/smpic/issues + url: https://makeawebsitehub.com/social-media-image-sizes-cheat-sheet/ + url_cran: https://CRAN.R-project.org/package=smpic + url_git: https://github.com/mikkelkrogsholm/smpic +smplot2: + version: 0.2.5 + title: |- + Create Standalone and Composite Plots in 'ggplot2' for + Publications + maintainer: Seung Hyun Min + description: Provides functions for creating and annotating a composite plot in + 'ggplot2'. Offers background themes and shortcut plotting functions that produce + figures that are appropriate for the format of scientific journals. Some methods + are described in Min and Zhou (2021) . + date_publication: '2025-01-26' + bug_reports: https://github.com/smin95/smplot2/issues + url: https://smin95.github.io/dataviz/ + url_cran: https://CRAN.R-project.org/package=smplot2 + url_git: '' +SMPracticals: + version: 1.4-3.1 + title: Practicals for Use with Davison (2003) Statistical Models + maintainer: Alessandra R. Brazzale + description: |- + Contains the datasets and a few functions for use with + the practicals outlined in Appendix A of the book + Statistical Models (Davison, 2003, Cambridge University Press), + which can be found at . + date_publication: '2024-02-05' + bug_reports: '' + url: doi:10.1017/CBO9780511815850 + url_cran: https://CRAN.R-project.org/package=SMPracticals + url_git: '' +SMR: + version: 2.1.0 + title: Externally Studentized Midrange Distribution + maintainer: Daniel Furtado Ferreira + description: Computes the studentized midrange distribution (pdf, cdf and quantile) + and generates random numbers. + date_publication: '2023-10-07' + bug_reports: https://github.com/bendeivide/SMR/issues + url: https://bendeivide.github.io/SMR/ + url_cran: https://CRAN.R-project.org/package=SMR + url_git: https://github.com/bendeivide/SMR +sms: + version: 2.3.1 + title: Spatial Microsimulation + maintainer: Dimitris Kavroudakis + description: |- + Produce small area population estimates by fitting census data to + survey data. + date_publication: '2015-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sms + url_git: '' +sMSROC: + version: 0.1.2 + title: Assessment of Diagnostic and Prognostic Markers + maintainer: Susana Diaz-Coto + description: Provides estimations of the Receiver Operating Characteristic (ROC) + curve and the Area Under the Curve (AUC) based on the two-stages mixed-subjects + ROC curve estimator (Diaz-Coto et al. (2020) and Diaz-Coto + et al. (2020) ). + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sMSROC + url_git: '' +smss: + version: 1.0-2 + title: |- + Datasets for Agresti and Finlay's "Statistical Methods for the + Social Sciences" + maintainer: Jeffrey B. Arnold + description: |- + Datasets used in "Statistical Methods for the Social Sciences" + (SMSS) by Alan Agresti and Barbara Finlay. + date_publication: '2015-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smss + url_git: '' +sMTL: + version: 0.1.0 + title: Sparse Multi-Task Learning + maintainer: Gabriel Loewinger + description: 'Implements L0-constrained Multi-Task Learning and domain generalization + algorithms. The algorithms are coded in Julia allowing for fast implementations + of the coordinate descent and local combinatorial search algorithms. For more + details, see a preprint of the paper: Loewinger et al., (2022) .' + date_publication: '2023-02-06' + bug_reports: https://github.com/gloewing/sMTL/issues + url: https://rpubs.com/gloewinger/996629 + url_cran: https://CRAN.R-project.org/package=sMTL + url_git: https://github.com/gloewing/sMTL +smurf: + version: 1.1.7 + title: Sparse Multi-Type Regularized Feature Modeling + maintainer: Tom Reynkens + description: Implementation of the SMuRF algorithm of Devriendt et al. (2021) + to fit generalized linear models (GLMs) with multiple types of predictors via + regularized maximum likelihood. + date_publication: '2025-02-23' + bug_reports: https://gitlab.com/TReynkens/smurf/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=smurf + url_git: https://gitlab.com/TReynkens/smurf +SMUT: + version: '1.1' + title: Multi-SNP Mediation Intersection-Union Test + maintainer: Wujuan Zhong + description: Testing the mediation effect of multiple SNPs on an outcome through + a mediator. + date_publication: '2019-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMUT + url_git: '' +SMVar: + version: 1.3.4 + title: Structural Model for Variances + maintainer: Samuel Blanck + description: |- + Implementation of the structural model for variances in order to + detect differentially expressed genes from gene expression data. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SMVar + url_git: '' +smvgraph: + version: 0.1.2 + title: Various Multivariate Graphics with Variable Choice in Shiny Apps + maintainer: Sigbert Klinke + description: |- + Mosaic diagram, scatterplot matrix, Andrews curves, parallel coordinate diagram, radar diagram, + and Chernoff plots as a Shiny app, which allow the order of variables to be changed interactively. + The apps are intended as teaching examples. + date_publication: '2021-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=smvgraph + url_git: '' +sn: + version: 2.1.1 + title: |- + The Skew-Normal and Related Distributions Such as the Skew-t and + the SUN + maintainer: Adelchi Azzalini + description: |- + Build and manipulate probability distributions of the skew-normal + family and some related ones, notably the skew-t and the SUN families. + For the skew-normal and the skew-t distributions, statistical methods are + provided for data fitting and model diagnostics, in the univariate and the + multivariate case. + date_publication: '2023-04-04' + bug_reports: '' + url: http://azzalini.stat.unipd.it/SN/ + url_cran: https://CRAN.R-project.org/package=sn + url_git: '' +sna: + version: '2.8' + title: Tools for Social Network Analysis + maintainer: Carter T. Butts + description: A range of tools for social network analysis, including node and graph-level + indices, structural distance and covariance methods, structural equivalence detection, + network regression, random graph generation, and 2D/3D network visualization. + date_publication: '2024-09-08' + bug_reports: '' + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=sna + url_git: '' +snahelper: + version: 1.4.2 + title: '''RStudio'' Addin for Network Analysis and Visualization' + maintainer: David Schoch + description: |- + 'RStudio' addin which provides a GUI to visualize and analyse networks. + After finishing a session, the code to produce the plot is inserted in the current script. + Alternatively, the function SNAhelperGadget() can be used directly from the console. + Additional addins include the Netreader() for reading network files, Netbuilder() to create + small networks via point and click, and the Componentlayouter() to layout networks with many components manually. + date_publication: '2023-11-16' + bug_reports: https://github.com/schochastics/snahelper/issues + url: https://schochastics.github.io/snahelper/ + url_cran: https://CRAN.R-project.org/package=snahelper + url_git: https://github.com/schochastics/snahelper +Snake: + version: '1.0' + title: Game of Snake + maintainer: Carsten Croonenbroeck + description: Implements snake in R as a programming example, see . + date_publication: '2020-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Snake + url_git: '' +snakecase: + version: 0.11.1 + title: Convert Strings into any Case + maintainer: Malte Grosser + description: A consistent, flexible and easy to use tool to parse and convert strings + into cases like snake or camel among others. + date_publication: '2023-08-27' + bug_reports: https://github.com/Tazinho/snakecase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snakecase + url_git: https://github.com/Tazinho/snakecase +SnakesAndLaddersAnalysis: + version: 2.1.0 + title: Play and Analyse the Game of Snakes and Ladders + maintainer: Hector Haffenden + description: Plays the game of Snakes and Ladders and has tools for analyses. The + tools included allow you to find the average moves to win, frequency of each square, + importance of the snakes and the ladders, the most common square and the plotting + of the game played. + date_publication: '2018-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SnakesAndLaddersAnalysis + url_git: '' +snap: + version: 1.1.0 + title: Simple Neural Application + maintainer: Giancarlo Vercellino + description: A simple wrapper to easily design vanilla deep neural networks using + 'Tensorflow'/'Keras' backend for regression, classification and multi-label tasks, + with some tweaks and tricks (skip shortcuts, embedding, feature selection and + anomaly detection). + date_publication: '2021-06-30' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/snap + url_cran: https://CRAN.R-project.org/package=snap + url_git: '' +snapchatadsR: + version: 0.1.0 + title: Get Snapchat Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Snapchat Ads + using the 'Windsor.ai' API . + date_publication: '2022-10-28' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=snapchatadsR + url_git: '' +snapKrig: + version: 0.0.2 + title: |- + Fast Kriging and Geostatistics on Grids with Kronecker + Covariance + maintainer: Dean Koch + description: |- + Geostatistical modeling and kriging with + gridded data using spatially separable covariance functions (Kronecker + covariances). Kronecker products in these models provide shortcuts for + solving large matrix problems in likelihood and conditional mean, + making 'snapKrig' computationally efficient with large grids. The package + supplies its own S3 grid object class, and a host of methods including + plot, print, Ops, square bracket replace/assign, and more. Our computational + methods are described in Koch, Lele, Lewis (2020) . + date_publication: '2023-05-06' + bug_reports: https://github.com/deankoch/snapKrig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snapKrig + url_git: https://github.com/deankoch/snapKrig +snapshot: + version: 0.1.2 + title: |- + Gadget N-body cosmological simulation code snapshot I/O + utilities + maintainer: Aaron Robotham + description: Functions for reading and writing Gadget N-body snapshots. The Gadget + code is popular in astronomy for running N-body / hydrodynamical cosmological + and merger simulations. To find out more about Gadget see the main distribution + page at www.mpa-garching.mpg.de/gadget/ + date_publication: '2013-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snapshot + url_git: '' +SNBdata: + version: 0.2.1 + title: Download Data from the Swiss National Bank (SNB) + maintainer: Enrico Schumann + description: |- + Download data (tables and datasets) from the Swiss + National Bank (SNB; ), the Swiss + central bank. The package is lightweight and comes with few + dependencies; suggested packages are used only if data is to + be transformed into particular data structures, for instance + into 'zoo' objects. Downloaded data can optionally be + cached, to avoid repeated downloads of the same files. + date_publication: '2023-12-12' + bug_reports: '' + url: http://enricoschumann.net/R/packages/SNBdata/ + url_cran: https://CRAN.R-project.org/package=SNBdata + url_git: '' +snem: + version: 0.1.1 + title: |- + EM Algorithm for Multivariate Skew-Normal Distribution with + Overparametrization + maintainer: Takayuki Kawashima + description: Efficient estimation of multivariate skew-normal distribution in closed + form. + date_publication: '2020-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snem + url_git: '' +snfa: + version: 0.0.1 + title: Smooth Non-Parametric Frontier Analysis + maintainer: Taylor McKenzie + description: |- + Fitting of non-parametric production frontiers for use in efficiency analysis. + Methods are provided for both a smooth analogue of Data Envelopment Analysis (DEA) and a + non-parametric analogue of Stochastic Frontier Analysis (SFA). Frontiers are constructed for + multiple inputs and a single output using constrained kernel smoothing as in + Racine et al. (2009), which allow for the imposition of monotonicity and concavity constraints + on the estimated frontier. + date_publication: '2018-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snfa + url_git: '' +SNFtool: + version: 2.3.1 + title: Similarity Network Fusion + maintainer: Benjamin Brew + description: Similarity Network Fusion takes multiple views of a network and fuses + them together to construct an overall status matrix. The input to our algorithm + can be feature vectors, pairwise distances, or pairwise similarities. The learned + status matrix can then be used for retrieval, clustering, and classification. + date_publication: '2021-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SNFtool + url_git: '' +snha: + version: 0.1.3 + title: Creating Correlation Networks using St. Nicolas House Analysis + maintainer: Detlef Groth + description: |2- + + Create correlation networks using St. Nicolas House Analysis ('SNHA'). + The package can be used for visualizing multivariate data similar to Principal + Component Analysis or Multidimensional Scaling using a ranking approach. + In contrast to 'MDS' and 'PCA', 'SNHA' uses a network approach to explore + interacting variables. + For details see 'Hermanussen et. al. 2021', . + date_publication: '2023-03-14' + bug_reports: https://github.com/mittelmark/snha/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snha + url_git: https://github.com/mittelmark/snha +snn: + version: '1.1' + title: Stabilized Nearest Neighbor Classifier + maintainer: Wei Sun + description: Implement K-nearest neighbor classifier, weighted nearest neighbor + classifier, bagged nearest neighbor classifier, optimal weighted nearest neighbor + classifier and stabilized nearest neighbor classifier, and perform model selection + via 5 fold cross-validation for them. This package also provides functions for + computing the classification error and classification instability of a classification + procedure. + date_publication: '2015-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snn + url_git: '' +snotelr: + version: 1.5.2 + title: Calculate and Visualize 'SNOTEL' Snow Data and Seasonality + maintainer: Koen Hufkens + description: |- + Programmatic interface to the 'SNOTEL' snow data + (). Provides easy downloads of snow + data into your R work space or a local directory. Additional post-processing + routines to extract snow season indexes are provided. + date_publication: '2024-11-20' + bug_reports: https://github.com/bluegreen-labs/snotelr/issues + url: https://bluegreen-labs.github.io/snotelr/ + url_cran: https://CRAN.R-project.org/package=snotelr + url_git: https://github.com/bluegreen-labs/snotelr +snow: + version: 0.4-4 + title: Simple Network of Workstations + maintainer: Luke Tierney + description: Support for simple parallel computing in R. + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snow + url_git: '' +SnowballC: + version: 0.7.1 + title: Snowball Stemmers Based on the C 'libstemmer' UTF-8 Library + maintainer: Milan Bouchet-Valat + description: |- + An R interface to the C 'libstemmer' library that implements + Porter's word stemming algorithm for collapsing words to a common + root to aid comparison of vocabulary. Currently supported languages are + Arabic, Basque, Catalan, Danish, Dutch, English, Finnish, French, German, Greek, + Hindi, Hungarian, Indonesian, Irish, Italian, Lithuanian, Nepali, + Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish, Tamil + and Turkish. + date_publication: '2023-04-25' + bug_reports: https://github.com/nalimilan/R.TeMiS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SnowballC + url_git: https://github.com/nalimilan/R.TeMiS +snowboot: + version: 1.0.2 + title: Bootstrap Methods for Network Inference + maintainer: Vyacheslav Lyubchich + description: Functions for analysis of network objects, which are imported or simulated + by the package. The non-parametric methods of analysis center on snowball and + bootstrap sampling for estimating functions of network degree distribution. For + other parameters of interest, see, e.g., 'bootnet' package. + date_publication: '2020-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snowboot + url_git: '' +snowfall: + version: 1.84-6.3 + title: Easier Cluster Computing (Based on 'snow') + maintainer: Jochen Knaus + description: |- + Usability wrapper around snow for easier development of + parallel R programs. This package offers e.g. extended error + checks, and additional functions. All functions work in + sequential mode, too, if no cluster is present or wished. + Package is also designed as connector to the cluster management + tool sfCluster, but can also used without it. + date_publication: '2023-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snowfall + url_git: '' +snowflakes: + version: 1.0.0 + title: Random Snowflake Generator + maintainer: Svetlana Eden + description: The function generates and plots random snowflakes. Each snowflake + is defined by a given diameter, width of the crystal, color, and random seed. + Snowflakes are plotted in such way that they always remain round, no matter what + the aspect ratio of the plot is. Snowflakes can be created using transparent colors, + which creates a more interesting, somewhat realistic, image. Images of the snowflakes + can be separately saved as svg files and used in websites as static or animated + images. + date_publication: '2017-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snowflakes + url_git: '' +snowFT: + version: 1.6-1 + title: Fault Tolerant Simple Network of Workstations + maintainer: Hana Sevcikova + description: Extension of the snow package supporting fault tolerant and reproducible + applications, as well as supporting easy-to-use parallel programming - only one + function is needed. Dynamic cluster size is also available. + date_publication: '2023-09-21' + bug_reports: '' + url: http://www.stat.washington.edu/hana/parallel/snowFT-doc.pdf + url_cran: https://CRAN.R-project.org/package=snowFT + url_git: '' +snowquery: + version: 1.2.1 + title: Query 'Snowflake' Databases with 'SQL' + maintainer: Dani Mermelstein + description: A wrapper allowing 'SQL' queries to be run on a 'Snowflake' instance + directly from an 'R' script, by using the 'snowflake-connector-python' package + in the background. + date_publication: '2024-10-02' + bug_reports: https://github.com/mermelstein/snowquery/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snowquery + url_git: https://github.com/mermelstein/snowquery +snpAIMeR: + version: 2.1.1 + title: Assess the Diagnostic Power of Genomic Marker Combinations + maintainer: Kim Vertacnik + description: |- + Population genetics package for designing diagnostic panels. + Candidate markers, marker combinations, and different panel sizes are + assessed for how well they can predict the source population of known + samples. Requires a genotype file of candidate markers in STRUCTURE format. + Methods for population cross-validation are described in Jombart (2008) + . + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snpAIMeR + url_git: https://github.com/OksanaVe/snpAIMeR +SNPannotator: + version: 0.2.6.0 + title: |- + Investigating the Functional Characteristics of Selected SNPs + and Their Vicinity Genomic Region + maintainer: Alireza Ani + description: To investigate the functional characteristics of selected SNPs and + their vicinity genomic region. Linked SNPs in moderate to high linkage disequilibrium + (e.g. r2>0.50) with the corresponding index SNPs will be selected for further + analysis. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SNPannotator + url_git: '' +SNPassoc: + version: 2.1-2 + title: SNPs-Based Whole Genome Association Studies + maintainer: Dolors Pelegri + description: |- + Functions to perform most of the common analysis in genome + association studies are implemented. These analyses include descriptive + statistics and exploratory analysis of missing values, calculation of + Hardy-Weinberg equilibrium, analysis of association based on generalized + linear models (either for quantitative or binary traits), and analysis + of multiple SNPs (haplotype and epistasis analysis). Permutation test + and related tests (sum statistic and truncated product) are also + implemented. Max-statistic and genetic risk-allele score exact + distributions are also possible to be estimated. The methods are + described in Gonzalez JR et al., 2007 . + date_publication: '2024-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SNPassoc + url_git: https://github.com/isglobal-brge/SNPassoc +SNPknock: + version: 0.8.2 + title: Knockoffs for Hidden Markov Models and Genetic Data + maintainer: Matteo Sesia + description: |- + Generate knockoffs for genetic data and hidden Markov models. + For more information, see the website below and the accompanying papers: + "Gene hunting with hidden Markov model knockoffs", Sesia et al., Biometrika, 2019, (). + "Multi-resolution localization of causal variants across the genome", Sesia et al., bioRxiv, 2019, (). + date_publication: '2019-05-17' + bug_reports: https://github.com/msesia/snpknock/issues + url: https://msesia.github.io/snpknock + url_cran: https://CRAN.R-project.org/package=SNPknock + url_git: '' +snplinkage: + version: 1.2.0 + title: |- + Single Nucleotide Polymorphisms Linkage Disequilibrium + Visualizations + maintainer: Thomas Charlon + description: Linkage disequilibrium visualizations of up to several hundreds of + single nucleotide polymorphisms (SNPs), annotated with chromosomic positions and + gene names. Two types of plots are available for small numbers of SNPs (<40) and + for large numbers (tested up to 500). Both can be extended by combining other + ggplots, e.g. association studies results, and functions enable to directly visualize + the effect of SNP selection methods, as minor allele frequency filtering and TagSNP + selection, with a second correlation heatmap. The SNPs correlations are computed + on Genotype Data objects from the 'GWASTools' package using the 'SNPRelate' package, + and the plots are customizable 'ggplot2' and 'gtable' objects and are annotated + using the 'biomaRt' package. Usage is detailed in the vignette with example data + and results from up to 500 SNPs of 1,200 scans are in Charlon T. (2019) . + date_publication: '2024-09-09' + bug_reports: https://gitlab.com/thomaschln/snplinkage/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snplinkage + url_git: https://gitlab.com/thomaschln/snplinkage +snplist: + version: 0.18.2 + title: Tools to Create Gene Sets + maintainer: Alexander Sibley + description: A set of functions to create SQL tables of gene and SNP information + and compose them into a SNP Set, for example to export to a PLINK set. + date_publication: '2021-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snplist + url_git: '' +sNPLS: + version: 1.0.27 + title: NPLS Regression with L1 Penalization + maintainer: David Hervas + description: |- + Tools for performing variable selection in three-way data using N-PLS + in combination with L1 penalization, Selectivity Ratio and VIP scores. + The N-PLS model (Rasmus Bro, 1996 ) + is the natural extension of PLS (Partial Least Squares) to N-way structures, and tries + to maximize the covariance between X and Y data arrays. The package also adds + variable selection through L1 penalization, Selectivity Ratio and VIP scores. + date_publication: '2020-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sNPLS + url_git: '' +snpReady: + version: 0.9.6 + title: Preparing Genotypic Datasets in Order to Run Genomic Analysis + maintainer: Italo Granato + description: |- + Three functions to clean, summarize and prepare genomic datasets to Genome + Selection and Genome Association analysis and to estimate population genetic parameters. + date_publication: '2018-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=snpReady + url_git: '' +snpsettest: + version: 0.1.2 + title: A Set-Based Association Test using GWAS Summary Statistics + maintainer: Jaehyun Joo + description: |- + The goal of 'snpsettest' is to provide simple tools that perform + set-based association tests (e.g., gene-based association tests) + using GWAS (genome-wide association study) summary statistics. A + set-based association test in this package is based on the + statistical model described in VEGAS (versatile gene-based + association study), which combines the effects of a set of SNPs + accounting for linkage disequilibrium between markers. This package + uses a different approach from the original VEGAS implementation to + compute set-level p values more efficiently, as described in + . + date_publication: '2023-09-09' + bug_reports: https://github.com/HimesGroup/snpsettest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snpsettest + url_git: https://github.com/HimesGroup/snpsettest +sns: + version: 1.2.2 + title: Stochastic Newton Sampler (SNS) + maintainer: Alireza Mahani + description: 'Stochastic Newton Sampler (SNS) is a Metropolis-Hastings-based, Markov + Chain Monte Carlo sampler for twice differentiable, log-concave probability density + functions (PDFs) where the proposal density function is a multivariate Gaussian + resulting from a second-order Taylor-series expansion of log-density around the + current point. The mean of the Gaussian proposal is the full Newton-Raphson step + from the current point. A Boolean flag allows for switching from SNS to Newton-Raphson + optimization (by choosing the mean of proposal function as next point). This can + be used during burn-in to get close to the mode of the PDF (which is unique due + to concavity). For high-dimensional densities, mixing can be improved via ''state + space partitioning'' strategy, in which SNS is applied to disjoint subsets of + state space, wrapped in a Gibbs cycle. Numerical differentiation is available + when analytical expressions for gradient and Hessian are not available. Facilities + for validation and numerical differentiation of log-density are provided. Note: + Formerly available versions of the MfUSampler can be obtained from the archive + .' + date_publication: '2022-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sns + url_git: '' +SNSchart: + version: 1.4.0 + title: Sequential Normal Scores in Statistical Process Management + maintainer: Luis Benavides + description: |- + The methods discussed in this package are new non-parametric methods + based on sequential normal scores 'SNS' (Conover et al (2017) + ), designed for sequences of observations, + usually time series data, which may occur singly or in batches, + and may be univariate or multivariate. These methods are designed + to detect changes in the process, which may occur as changes in location + (mean or median), changes in scale (standard deviation, or variance), or + other changes of interest in the distribution of the observations, + over the time observed. They usually apply to large data sets, + so computations need to be simple enough to be done in a reasonable + time on a computer, and easily updated as each new observation + (or batch of observations) becomes available. Some examples and more detail + in 'SNS' is presented in the work by Conover et al (2019) . + date_publication: '2021-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SNSchart + url_git: '' +SNSeg: + version: 1.0.3 + title: |- + Self-Normalization(SN) Based Change-Point Estimation for Time + Series + maintainer: Zifeng Zhao + description: |- + Implementations self-normalization (SN) based algorithms for + change-points estimation in time series data. This comprises nested + local-window algorithms for detecting changes in both univariate and + multivariate time series developed in Zhao, Jiang and Shao (2022) + . + date_publication: '2024-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SNSeg + url_git: '' +SNSequate: + version: 1.3-5 + title: |- + Standard and Nonstandard Statistical Models and Methods for Test + Equating + maintainer: Jorge Gonzalez + description: |- + Contains functions to perform various models and + methods for test equating (Kolen and Brennan, 2014 + ; Gonzalez and Wiberg, 2017 + ; von Davier et. al, 2004 + ). It currently implements the traditional mean, linear + and equipercentile equating methods. Both IRT observed-score and true-score + equating are also supported, as well as the mean-mean, mean-sigma, Haebara + and Stocking-Lord IRT linking methods. It also supports newest methods such + that local equating, kernel equating (using Gaussian, logistic, + Epanechnikov, uniform and adaptive kernels) with presmoothing, and IRT + parameter linking methods based on asymmetric item characteristic functions. + Functions to obtain both standard error of equating (SEE) and standard error + of equating differences between two equating functions (SEED) are also + implemented for the kernel method of equating. + date_publication: '2024-04-22' + bug_reports: '' + url: https://www.mat.uc.cl/~jorge.gonzalez/ + url_cran: https://CRAN.R-project.org/package=SNSequate + url_git: '' +SNSFdatasets: + version: 0.1.1 + title: |- + Download Datasets from the Swiss National Science Foundation + (SNF, FNS, SNSF) + maintainer: Enrico Schumann + description: |- + Download and read datasets from the Swiss National + Science Foundation (SNF, FNS, SNSF; ). The + package is lightweight and without dependencies. Downloaded + data can optionally be cached, to avoid repeated downloads of + the same files. There are also utilities for comparing + different versions of datasets, i.e. to report added, removed + and changed entries. + date_publication: '2024-01-31' + bug_reports: '' + url: http://enricoschumann.net/R/packages/SNSFdatasets/ + url_cran: https://CRAN.R-project.org/package=SNSFdatasets + url_git: https://github.com/enricoschumann/SNSFdatasets +snSMART: + version: 0.2.4 + title: Small N Sequential Multiple Assignment Randomized Trial Methods + maintainer: Michael Kleinsasser + description: |- + Consolidated data simulation, sample size calculation and + analysis functions for several snSMART (small sample sequential, + multiple assignment, randomized trial) designs under one library. See + Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M. "A Bayesian + analysis of small n sequential multiple assignment randomized trials + (snSMARTs)." (2018) Statistics in medicine, 37(26), pp.3723-3732 + . + date_publication: '2024-10-16' + bug_reports: https://github.com/sidiwang/snSMART/issues + url: '' + url_cran: https://CRAN.R-project.org/package=snSMART + url_git: https://github.com/sidiwang/snSMART +snvecR: + version: 3.10.0 + title: Calculate Earth’s Obliquity and Precession in the Past + maintainer: Ilja Kocken + description: 'Easily calculate precession and obliquity from an orbital solution + (defaults to ZB18a from Zeebe and Lourens (2019) ) + and assumed or reconstructed values for tidal dissipation (Td) and dynamical ellipticity + (Ed). This is a translation and adaptation of the ''C''-code in the supplementary + material to Zeebe and Lourens (2022) , with further + details on the methodology described in Zeebe (2022) . + The name of the ''C''-routine is ''snvec'', which refers to the key units of computation: + spin vector s and orbit normal vector n.' + date_publication: '2025-03-01' + bug_reports: https://github.com/japhir/snvecR/issues + url: https://japhir.github.io/snvecR/ + url_cran: https://CRAN.R-project.org/package=snvecR + url_git: https://github.com/japhir/snvecR +SNVLFDR: + version: 1.0.1 + title: Empirical Bayes Single Nucleotide Variant Calling + maintainer: Ali Karimnezhad + description: Identifies single nucleotide variants in next-generation sequencing + data by estimating their local false discovery rates. For more details, see Karimnezhad, + A. and Perkins, T. J. (2024) . + date_publication: '2024-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SNVLFDR + url_git: '' +SOAR: + version: 0.99-11 + title: Memory management in R by delayed assignments + maintainer: Bill Venables + description: |- + Allows objects to be stored on disc and automatically + recalled into memory, as required, by delayed assignment. + date_publication: '2013-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOAR + url_git: '' +SOAs: + version: '1.4' + title: Creation of Stratum Orthogonal Arrays + maintainer: Ulrike Groemping + description: Creates stratum orthogonal arrays (also known as strong orthogonal + arrays). These are arrays with more levels per column than the typical orthogonal + array, and whose low order projections behave like orthogonal arrays, when collapsing + levels to coarser strata. Details are described in Groemping (2022) "A unifying + implementation of stratum (aka strong) orthogonal arrays" . + date_publication: '2023-08-10' + bug_reports: https://github.com/bertcarnell/SOAs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SOAs + url_git: https://github.com/bertcarnell/SOAs +sobolnp: + version: 0.1.0 + title: Nonparametric Sobol Estimator with Bootstrap Bandwidth + maintainer: Maikol Solís + description: Algorithm to estimate the Sobol indices using a non-parametric fit + of the regression curve. The bandwidth is estimated using bootstrap to reduce + the finite-sample bias. The package is based on the paper Solís, M. (2018) . + date_publication: '2019-04-29' + bug_reports: https://github.com/maikol-solis/sobolnp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sobolnp + url_git: https://github.com/maikol-solis/sobolnp/ +SobolSequence: + version: '1.0' + title: Sobol Sequences with Better Two-Dimensional Projections + maintainer: Mutsuo Saito + description: |- + R implementation of S. Joe and F. Y. Kuo(2008) + . + The implementation is based on the data file new-joe-kuo-6.21201 + . + date_publication: '2017-07-07' + bug_reports: '' + url: http://web.maths.unsw.edu.au/~fkuo/sobol/ + url_cran: https://CRAN.R-project.org/package=SobolSequence + url_git: '' +soc.ca: + version: 0.8.0 + title: Specific Correspondence Analysis for the Social Sciences + maintainer: Anton Grau Larsen + description: |- + Specific and class specific multiple correspondence analysis on + survey-like data. Soc.ca is optimized to the needs of the social scientist and + presents easily interpretable results in near publication ready quality. + date_publication: '2021-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soc.ca + url_git: https://github.com/Rsoc/soc.ca +socceR: + version: 0.1.1 + title: Evaluating Sport Tournament Predictions + maintainer: Claus Thorn Ekstrøm + description: Functions for evaluating tournament predictions, simulating results + from individual soccer matches and tournaments. See + for more information. + date_publication: '2019-07-03' + bug_reports: https://github.com/ekstroem/socceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=socceR + url_git: https://github.com/ekstroem/socceR +social: + version: '1.0' + title: Social Autocorrelation + maintainer: Tom Pike + description: |- + A set of functions to quantify and visualise + social autocorrelation. + date_publication: '2017-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=social + url_git: '' +socialh: + version: 0.1.1 + title: Rank and Social Hierarchy for Gregarious Animals + maintainer: Julia de Paula Soares Valente + description: |- + Tools developed to facilitate the establishment of the rank and social hierarchy + for gregarious animals by the Si method developed by + Kondo & Hurnik (1990). It is + also possible to determine the number of agonistic interactions between two + individuals, sociometric and dyadics matrix from dataset obtained through + electronic bins. In addition, it is possible plotting the results using a bar plot, box plot, and sociogram. + date_publication: '2022-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=socialh + url_git: '' +socialmixr: + version: 0.4.0 + title: Social Mixing Matrices for Infectious Disease Modelling + maintainer: Sebastian Funk + description: |- + Provides methods for sampling contact matrices from diary + data for use in infectious disease modelling, as discussed in Mossong + et al. (2008) . + date_publication: '2024-10-18' + bug_reports: https://github.com/epiforecasts/socialmixr/issues + url: https://epiforecasts.io/socialmixr/ + url_cran: https://CRAN.R-project.org/package=socialmixr + url_git: https://github.com/epiforecasts/socialmixr +socialranking: + version: 1.2.0 + title: Social Ranking Solutions for Power Relations on Coalitions + maintainer: Felix Fritz + description: The notion of power index has been widely used in literature to evaluate + the influence of individual players (e.g., voters, political parties, nations, + stockholders, etc.) involved in a collective decision situation like an electoral + system, a parliament, a council, a management board, etc., where players may form + coalitions. Traditionally this ranking is determined through numerical evaluation. + More often than not however only ordinal data between coalitions is known. The + package 'socialranking' offers a set of solutions to rank players based on a transitive + ranking between coalitions, including through CP-Majority, ordinal Banzhaf or + lexicographic excellence solution summarized by Tahar Allouche, Bruno Escoffier, + Stefano Moretti and Meltem Öztürk (2020, ). + date_publication: '2024-05-16' + bug_reports: https://github.com/jassler/socialranking/issues + url: '' + url_cran: https://CRAN.R-project.org/package=socialranking + url_git: https://github.com/jassler/socialranking +socialrisk: + version: 0.5.1 + title: |- + Identifying Patient Social Risk from Administrative Health Care + Data + maintainer: Wyatt Bensken + description: |- + Social risks are increasingly becoming a critical component of health + care research. One of the most common ways to identify social needs is by using + ICD-10-CM "Z-codes." This package identifies social risks using varying taxonomies + of ICD-10-CM Z-codes from administrative health care data. The conceptual + taxonomies come from: + Centers for Medicare and Medicaid Services (2021) , + Reidhead (2018) , + A Arons, S DeSilvey, C Fichtenberg, L Gottlieb (2018) . + date_publication: '2023-02-15' + bug_reports: https://github.com/WYATTBENSKEN/multimorbidity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=socialrisk + url_git: https://github.com/WYATTBENSKEN/multimorbidity +sociome: + version: 2.2.5 + title: |- + Operationalizing Social Determinants of Health Data for + Researchers + maintainer: Nik Krieger + description: |- + Accesses raw data via API and calculates social + determinants of health measures for user-specified locations in the + US, returning them in tidyverse- and sf-compatible data frames. + date_publication: '2023-12-06' + bug_reports: https://github.com/ClevelandClinicQHS/sociome/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sociome + url_git: '' +socviz: + version: '1.2' + title: Utility Functions and Data Sets for Data Visualization + maintainer: Kieran Healy + description: Supporting materials for a course and book on data visualization. It + contains utility functions for graphs and several sample data sets. See Healy + (2019) . + date_publication: '2020-06-10' + bug_reports: https://github.com/kjhealy/socviz/issues + url: http://kjhealy.github.io/socviz/ + url_cran: https://CRAN.R-project.org/package=socviz + url_git: '' +sodavis: + version: '1.2' + title: |- + SODA: Main and Interaction Effects Selection for Logistic + Regression, Quadratic Discriminant and General Index Models + maintainer: Yang Li + description: Variable and interaction selection are essential to classification + in high-dimensional setting. In this package, we provide the implementation of + SODA procedure, which is a forward-backward algorithm that selects both main and + interaction effects under logistic regression and quadratic discriminant analysis. + We also provide an extension, S-SODA, for dealing with the variable selection + problem for semi-parametric models with continuous responses. + date_publication: '2018-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sodavis + url_git: '' +sodium: + version: 1.4.0 + title: A Modern and Easy-to-Use Crypto Library + maintainer: Jeroen Ooms + description: |- + Bindings to 'libsodium' : a modern, + easy-to-use software library for encryption, decryption, signatures, password + hashing and more. Sodium uses curve25519, a state-of-the-art Diffie-Hellman + function by Daniel Bernstein, which has become very popular after it was + discovered that the NSA had backdoored Dual EC DRBG. + date_publication: '2024-12-16' + bug_reports: https://github.com/r-lib/sodium/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sodium + url_git: https://docs.ropensci.org/sodium/https://github.com/r-lib/sodium +sofa: + version: 0.4.0 + title: Connector to 'CouchDB' + maintainer: Scott Chamberlain + description: |- + Provides an interface to the 'NoSQL' database 'CouchDB' + (). Methods are provided for managing + databases within 'CouchDB', including creating/deleting/updating/transferring, + and managing documents within databases. One can connect with a local + 'CouchDB' instance, or a remote 'CouchDB' databases such as 'Cloudant'. + Documents can be inserted directly from vectors, lists, data.frames, + and 'JSON'. Targeted at 'CouchDB' v2 or greater. + date_publication: '2020-06-26' + bug_reports: https://github.com/ropensci/sofa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sofa + url_git: https://github.com/ropensci/sofa(devel)https://docs.ropensci.org/sofa(docs) +Sofi: + version: 0.16.4.8 + title: Interfaz interactiva con fines didacticos + maintainer: Jose D. Loera + description: Este paquete tiene la finalidad de ayudar a aprender de una forma interactiva, + teniendo ejemplos y la posibilidad de resolver nuevos al mismo tiempo. Apuntes + de clase interactivos. + date_publication: '2016-04-10' + bug_reports: https://github.com/loerasg/Sofi/issues + url: http://www.sofi.uno/ + url_cran: https://CRAN.R-project.org/package=Sofi + url_git: '' +SOFIA: + version: '1.0' + title: Making Sophisticated and Aesthetical Figures in R + maintainer: Luis Diaz-Garcia + description: Software that leverages the capabilities of Circos by manipulating + data, preparing configuration files, and running the Perl-native Circos directly + from the R environment with minimal user intervention. Circos is a novel software + that addresses the challenges in visualizing genetic data by creating circular + ideograms composed of tracks of heatmaps, scatter plots, line plots, histograms, + links between common markers, glyphs, text, and etc. Please see . + date_publication: '2017-01-22' + bug_reports: '' + url: http://cggl.horticulture.wisc.edu + url_cran: https://CRAN.R-project.org/package=SOFIA + url_git: '' +SoftBart: + version: 1.0.1 + title: Implements the SoftBart Algorithm + maintainer: Antonio R. Linero + description: Implements the SoftBart model of described by Linero and Yang (2018) + , with the optional use of a sparsity-inducing prior to + allow for variable selection. For usability, the package maintains the same style + as the 'BayesTree' package. + date_publication: '2022-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoftBart + url_git: '' +softbib: + version: 0.0.2 + title: Software Bibliographies for R Projects + maintainer: Vincent Arel-Bundock + description: Detect libraries used in a project and automatically create software + bibliographies in 'PDF', 'Word', 'Rmarkdown', and 'BibTeX' formats. + date_publication: '2023-05-12' + bug_reports: https://github.com/vincentarelbundock/softbib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=softbib + url_git: https://github.com/vincentarelbundock/softbib +softclassval: + version: 1.1.0 + title: Soft Classification Performance Measures + maintainer: Claudia Beleites + description: |- + An extension of sensitivity, specificity, positive and negative + predictive value to continuous predicted and reference memberships in + [0, 1]. + date_publication: '2024-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=softclassval + url_git: http://softclassval.r-forge.r-project.org/ +SoftClustering: + version: 2.1.3 + title: Soft Clustering Algorithms + maintainer: G. Peters + description: 'It contains soft clustering algorithms, in particular approaches derived + from rough set theory: Lingras & West original rough k-means, Peters'' refined + rough k-means, and PI rough k-means. It also contains classic k-means and a corresponding + illustrative demo.' + date_publication: '2023-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoftClustering + url_git: '' +softImpute: + version: 1.4-1 + title: Matrix Completion via Iterative Soft-Thresholded SVD + maintainer: Trevor Hastie + description: Iterative methods for matrix completion that use nuclear-norm regularization. + There are two main approaches.The one approach uses iterative soft-thresholded + svds to impute the missing values. The second approach uses alternating least + squares. Both have an 'EM' flavor, in that at each iteration the matrix is completed + with the current estimate. For large matrices there is a special sparse-matrix + class named "Incomplete" that efficiently handles all computations. The package + includes procedures for centering and scaling rows, columns or both, and for computing + low-rank SVDs on large sparse centered matrices (i.e. principal components). + date_publication: '2021-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=softImpute + url_git: '' +SOHPIE: + version: 1.0.6 + title: Statistical Approach via Pseudo-Value Information and Estimation + maintainer: Seungjun Ahn + description: '''SOHPIE'' (pronounced as SOFIE) is a novel pseudo-value regression + approach for differential co-abundance network analysis of microbiome data, which + can include additional clinical covariate in the model. The full methodological + details can be found in Ahn S and Datta S (2023) .' + date_publication: '2023-10-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOHPIE + url_git: '' +SOIL: + version: '1.1' + title: Sparsity Oriented Importance Learning + maintainer: Yi Yang + description: Sparsity Oriented Importance Learning (SOIL) provides a new variable + importance measure for high dimensional linear regression and logistic regression + from a sparse penalization perspective, by taking into account the variable selection + uncertainty via the use of a sensible model weighting. The package is an implementation + of Ye, C., Yang, Y., and Yang, Y. (2017+). + date_publication: '2017-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOIL + url_git: https://github.com/emeryyi/SOIL +soilassessment: + version: 0.3.0 + title: |- + Soil Health Assessment Models for Assessing Soil Conditions and + Suitability + maintainer: Christian Thine Omuto + description: |- + Soil health assessment builds information to improve decision in + soil management. It facilitates assessment of soil conditions for crop suitability [such as those given by FAO + ], + groundwater recharge, fertility, erosion, salinization [], + carbon sequestration, irrigation potential, and status of soil resources. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soilassessment + url_git: '' +soilchemistry: + version: 0.1.0 + title: |- + Computation of Properties Related to Soil Chemical Environment + and Nutrient Availability + maintainer: Bappa Das + description: Facilitates basic and equation-based analyses of some important soil + properties related to soil chemical environment and nutrient availability to plants. + Freundlich H (1907). . Datta SP, Bhadoria PBS (1999). + ."Boron + adsorption and desorption in some acid soils of West Bengal, India". Langmuir + I (1918). "The adsorption of gases on plane surfaces + of glass, mica, and platinum". Khasawneh FE (1971). + "Solution ion activity and plant growth". + date_publication: '2023-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soilchemistry + url_git: '' +SoilConservation: + version: 1.0.1 + title: Soil and Water Conservation + maintainer: Dione Pereira Cardoso + description: 'Includes four functions: RFactor_calc(), RFactor_est(), KFactor() + and SoilLoss(). The rainfall erosivity factors can be calculated or estimated, + and soil erodibility will be estimated by the equation extracted from the monograph. + Soil loss will be estimated by the product of five factors (rainfall erosivity, + soil erodibility, length and steepness slope, cover-management factor and support + practice factor. In the future, additional functions can be included. This efforts + to advance research in soil and water conservation, with fast and accurate results.' + date_publication: '2024-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoilConservation + url_git: '' +soilDB: + version: 2.8.8 + title: Soil Database Interface + maintainer: Andrew Brown + description: A collection of functions for reading soil data from U.S. Department + of Agriculture Natural Resources Conservation Service (USDA-NRCS) and National + Cooperative Soil Survey (NCSS) databases. + date_publication: '2025-02-10' + bug_reports: https://github.com/ncss-tech/soilDB/issues + url: https://ncss-tech.github.io/soilDB/ + url_cran: https://CRAN.R-project.org/package=soilDB + url_git: https://github.com/ncss-tech/soilDB/ +SoilFDA: + version: 0.1.0 + title: Fractal Dimension Analysis of Soil Particle Size Distribution + maintainer: Fehim Jeelani Wani + description: Function for the computation of fractal dimension based on mass of + soil particle size distribution by Tyler & Wheatcraft (1992) . + It also provides functions for calculation of mean weight and geometric mean diameter + of particle size distribution by Perfect et al. (1992) . + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoilFDA + url_git: '' +soilfoodwebs: + version: 1.0.2 + title: Soil Food Web Analysis + maintainer: Robert Buchkowski + description: |- + Analyzing soil food webs or any food web measured at equilibrium. The package + calculates carbon and nitrogen fluxes and stability properties using methods + described by Hunt et al. (1987) , de Ruiter et al. + (1995) , Holtkamp et al. (2011) + , and Buchkowski and Lindo (2021) + . The package can also manipulate the structure + of the food web as well as simulate food webs away from equilibrium and run + decomposition experiments. + date_publication: '2023-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soilfoodwebs + url_git: '' +SoilFunctionality: + version: 0.1.0 + title: Soil Functionality Measurement + maintainer: Tanuj Misra + description: Generally, soil functionality is characterized by its capability to + sustain microbial activity, nutritional element supply, structural stability and + aid for crop production. Since soil functions can be linked to 80% of ecosystem + services, conservation of degraded land should strive to restore not only the + capacity of soil to sustain flora but also ecosystem provisions. The primary ecosystem + services of soil are carbon sequestration, food or biomass production, provision + of microbial habitat, nutrient recycling. However, the actual magnitude of soil + functions provided by agricultural land uses has never been quantified. Nutrient + supply capacity (NSC) is a measure of nutrient dynamics in restored land uses. + Carbon accumulation proficiency (CAP) is a measure of ecosystem carbon sequestration. + Biological activity index (BAI) is the average of responses of all enzyme activities + in treated land over control/reference land. The CAP parameter investigates how + land uses may affect carbon flows, retention, and sequestration. The CAP provides + a signal for C cycles, flows, and the systems' relative operational supremacy. + date_publication: '2024-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoilFunctionality + url_git: '' +SoilHyP: + version: 0.1.7 + title: Soil Hydraulic Properties + maintainer: Ullrich Dettmann + description: |- + Provides functions for (1) soil water retention (SWC) and unsaturated hydraulic conductivity (Ku) (van Genuchten-Mualem (vGM or vG) [1, 2], Peters-Durner-Iden (PDI) [3, 4, 5], Brooks and Corey (bc) [8]), (2) fitting of parameter for SWC and/or Ku using Shuffled Complex Evolution (SCE) optimisation and (3) calculation of soil hydraulic properties (Ku and soil water contents) based on the simplified evaporation method (SEM) [6, 7]. + Main references: + [1] van Genuchten (1980) , + [2] Mualem (1976) , + [3] Peters (2013) , + [4] Iden and Durner (2013) , + [5] Peters (2014) , + [6] Wind G. P. (1966), + [7] Peters and Durner (2008) and + [8] Brooks and Corey (1964). + date_publication: '2023-02-02' + bug_reports: https://bitbucket.org/UlliD/soilhyp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SoilHyP + url_git: '' +soilhypfit: + version: 0.1-7 + title: |- + Modelling of Soil Water Retention and Hydraulic Conductivity + Data + maintainer: Andreas Papritz + description: Provides functions for efficiently estimating properties of the Van + Genuchten-Mualem model for soil hydraulic parameters from possibly sparse soil + water retention and hydraulic conductivity data by multi-response parameter estimation + methods (Stewart, W.E., Caracotsios, M. Soerensen, J.P. (1992) "Parameter estimation + from multi-response data" ). Parameter estimation is + simplified by exploiting the fact that residual and saturated water contents and + saturated conductivity are conditionally linear parameters (Bates, D. M. and + Watts, D. G. (1988) "Nonlinear Regression Analysis and Its Applications" ). + Estimated parameters are optionally constrained by the evaporation characteristic + length (Lehmann, P., Bickel, S., Wei, Z. and Or, D. (2020) "Physical Constraints + for Improved Soil Hydraulic Parameter Estimation by Pedotransfer Functions" ) + to ensure that the estimated parameters are physically valid. Common S3 methods + and further utility functions allow to process, explore and visualise estimation + results. + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soilhypfit + url_git: '' +SoilManageR: + version: 1.0.1 + title: |- + Calculate Soil Management Indicators for Agricultural Practice + Assessment + maintainer: Olivier Heller + description: |- + Calculate numerical agricultural soil management indicators from on a management timeline of an arable field. Currently, indicators for carbon (C) input into the soil system, soil tillage intensity rating (STIR), number of soil cover and living plant cover days, N fertilization and livestock intensity, and plant diversity are implemented. + The functions can also be used independently of the management timeline to calculate some indicators. The package contains tables with reference information for the functions, as well as a '*.xlsx' template to collect the management data. + date_publication: '2024-10-01' + bug_reports: https://gitlab.com/SoilManageR/SoilManageR/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SoilManageR + url_git: https://gitlab.com/SoilManageR/ +soilphysics: + version: '5.0' + title: Soil Physical Analysis + maintainer: Anderson Rodrigo da Silva + description: Basic and model-based soil physical analyses. + date_publication: '2022-06-07' + bug_reports: '' + url: https://arsilva87.github.io/soilphysics/ + url_cran: https://CRAN.R-project.org/package=soilphysics + url_git: '' +SoilR: + version: 1.2.107 + title: Models of Soil Organic Matter Decomposition + maintainer: Carlos A. Sierra + description: |- + Functions for modeling Soil Organic Matter decomposition + in terrestrial ecosystems with linear and nonlinear systems of differential equations. + The package implements + models according to the compartmental system representation described in + Sierra and others (2012) and Sierra and others (2014) + . + date_publication: '2023-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoilR + url_git: '' +SoilSaltIndex: + version: 0.1.0 + title: Soil Salinity Indices Generation using Satellite Data + maintainer: Nobin Chandra Paul + description: |- + The developed function generates soil salinity indices using satellite data, utilizing multiple spectral bands such as Blue, Green, Red, Near-Infrared (NIR), + and Shortwave Infrared (SWIR1, SWIR2). It computes 24 different salinity indices crucial for monitoring and analyzing salt-affected soils efficiently. + For more details see, Rani, et al. (2022). . One of the key features of the developed function is its flexibility. + Users can provide any combination of the required spectral bands, and the function will automatically calculate only the relevant indices based on the available data. + This dynamic capability ensures that users can maximize the utility of their data without the need for all spectral bands, making the package versatile and user-friendly. + Outputs are provided as GeoTIFF file format, facilitating easy integration with GIS workflows. + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoilSaltIndex + url_git: '' +SoilTaxonomy: + version: 0.2.4 + title: |- + A System of Soil Classification for Making and Interpreting Soil + Surveys + maintainer: Andrew Brown + description: |- + Taxonomic dictionaries, formative element lists, and functions related to the maintenance, development and application of U.S. Soil Taxonomy. + Data and functionality are based on official U.S. Department of Agriculture sources including the latest edition of the Keys to Soil Taxonomy. Descriptions and metadata are obtained from the National Soil Information System or Soil Survey Geographic databases. Other sources are referenced in the data documentation. + Provides tools for understanding and interacting with concepts in the U.S. Soil Taxonomic System. Most of the current utilities are for working with taxonomic concepts at the "higher" taxonomic levels: Order, Suborder, Great Group, and Subgroup. + date_publication: '2023-11-16' + bug_reports: https://github.com/ncss-tech/SoilTaxonomy/issues + url: https://ncss-tech.github.io/SoilTaxonomy/ + url_cran: https://CRAN.R-project.org/package=SoilTaxonomy + url_git: https://github.com/ncss-tech/SoilTaxonomy +soiltestcorr: + version: 2.2.1 + title: Soil Test Correlation and Calibration + maintainer: Adrian A. Correndo + description: 'A compilation of functions designed to assist users on the correlation + analysis of crop yield and soil test values. Functions to estimate crop response + patterns to soil nutrient availability and critical soil test values using various + approaches such as: 1) the modified arcsine-log calibration curve (Correndo et + al. (2017) ); 2) the graphical Cate-Nelson quadrants analysis + (Cate & Nelson (1965)), 3) the statistical Cate-Nelson quadrants analysis (Cate + & Nelson (1971) ), 4) the linear-plateau + regression (Anderson & Nelson (1975) ), 5) the quadratic-plateau + regression (Bullock & Bullock (1994) ), + and 6) the Mitscherlich-type exponential regression (Melsted & Peck (1977) ). + The package development stemmed from ongoing work with the Fertilizer Recommendation + Support Tool (FRST) and Feed the Future Innovation Lab for Collaborative Research + on Sustainable Intensification (SIIL) projects.' + date_publication: '2024-07-01' + bug_reports: https://github.com/adriancorrendo/soiltestcorr/issues + url: https://adriancorrendo.github.io/soiltestcorr/ + url_cran: https://CRAN.R-project.org/package=soiltestcorr + url_git: '' +SoilTesting: + version: 0.1.0 + title: Organic Carbon and Plant Available Nutrient Contents in Soil + maintainer: Bappa Das + description: Testing of soil for the contents of organic carbon, and available macro- + and micro-nutrients is a crucial part of soil fertility assessment. This package + computes some routinely tested soil properties viz. organic carbon (C), total + nitrogen (N), available N, mineral N, available phosphorus (P), available potassium + (K), available iron (Fe), available zinc (Zn), available manganese (Mn), available + copper (Cu), and available nickel (Ni) in soil based on laboratory analysis data + obtained by most commonly followed protocols. Besides, it can also draw standard + curves based on absorption/emission vs. concentration data, and give out unknown + concentrations from absorption/emission readings. + date_publication: '2022-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoilTesting + url_git: '' +soiltexture: + version: 1.5.3 + title: |- + Functions for Soil Texture Plot, Classification and + Transformation + maintainer: Julien Moeys + description: '"The Soil Texture Wizard" is a set of R functions designed to produce + texture triangles (also called texture plots, texture diagrams, texture ternary + plots), classify and transform soil textures data. These functions virtually allows + to plot any soil texture triangle (classification) into any triangle geometry + (isosceles, right-angled triangles, etc.). This set of function is expected to + be useful to people using soil textures data from different soil texture classification + or different particle size systems. Many (> 15) texture triangles from all around + the world are predefined in the package. A simple text based graphical user interface + is provided: soiltexture_gui().' + date_publication: '2024-02-16' + bug_reports: https://github.com/julienmoeys/soiltexture/issues + url: '' + url_cran: https://CRAN.R-project.org/package=soiltexture + url_git: https://github.com/julienmoeys/soiltexture +soilwater: + version: 1.0.5 + title: |- + Implementation of Parametric Formulas for Soil Water Retention + or Conductivity Curve + maintainer: Emanuele Cordano + description: |- + It implements parametric formulas of soil + water retention or conductivity curve. At the moment, only Van Genuchten + (for soil water retention curve) and Mualem (for hydraulic conductivity) + were implemented. + See reference (). + date_publication: '2017-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soilwater + url_git: https://github.com/ecor/soilwater +Sojourn.Data: + version: 0.3.0 + title: Supporting Objects for Sojourn Accelerometer Methods + maintainer: Paul R. Hibbing + description: |- + Stores objects (e.g. neural networks) that are needed for + using Sojourn accelerometer methods. For more information, see + Lyden K, Keadle S, Staudenmayer J, & Freedson P (2014) + , Ellingson LD, Schwabacher IJ, + Kim Y, Welk GJ, & Cook DB (2016) , + and Hibbing PR, Ellingson LD, Dixon PM, & Welk GJ (2018) + . + date_publication: '2021-05-03' + bug_reports: https://github.com/paulhibbing/Sojourn.Data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Sojourn.Data + url_git: https://github.com/paulhibbing/Sojourn.Data +sokoban: + version: 0.1.0 + title: Sokoban Game + maintainer: Zhaoliang He + description: Interactively play a game of sokoban ,which has nine game levels.Sokoban + is a type of transport puzzle, in which the player pushes boxes or crates around + in a warehouse, trying to get them to storage locations. + date_publication: '2018-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sokoban + url_git: '' +solaR: + version: '0.46' + title: Radiation and Photovoltaic Systems + maintainer: Oscar Perpiñán Lamigueiro + description: Calculation methods of solar radiation and performance of photovoltaic + systems from daily and intradaily irradiation data sources. + date_publication: '2021-10-19' + bug_reports: https://github.com/oscarperpinan/solar/issues + url: https://oscarperpinan.github.io/solar/ + url_cran: https://CRAN.R-project.org/package=solaR + url_git: '' +solaR2: + version: '0.11' + title: Radiation and Photovoltaic Systems + maintainer: Francisco Delgado-López + description: Provides tools for calculating solar geometry, solar radiation on horizontal + and inclined planes, and simulating the performance of various photovoltaic (PV) + systems. Supports daily and intradaily irradiation data, enabling detailed analysis + of grid-connected and water-pumping PV systems, including shading effects and + solar angle calculations. + date_publication: '2025-01-16' + bug_reports: https://github.com/solarization/solaR2/issues + url: https://solarization.github.io/solaR2/ + url_cran: https://CRAN.R-project.org/package=solaR2 + url_git: '' +solarPos: + version: '1.0' + title: Solar Position Algorithm for Solar Radiation Applications + maintainer: Jasper Van doninck + description: Calculation of solar zenith and azimuth angles. + date_publication: '2016-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=solarPos + url_git: '' +solartime: + version: 0.0.4 + title: |- + Utilities Dealing with Solar Time Such as Sun Position and Time + of Sunrise + maintainer: Thomas Wutzler + description: |- + Provide utilities to work with solar time, + i.e. where noon is exactly when sun culminates. + Provides functions for computing sun position and times of sunrise and sunset. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=solartime + url_git: https://github.com/bgctw/solartime +solitude: + version: 1.1.3 + title: An Implementation of Isolation Forest + maintainer: Komala Sheshachala Srikanth + description: Isolation forest is anomaly detection method introduced by the paper + Isolation based Anomaly Detection (Liu, Ting and Zhou ). + date_publication: '2021-07-29' + bug_reports: https://github.com/talegari/solitude/issues + url: '' + url_cran: https://CRAN.R-project.org/package=solitude + url_git: https://github.com/talegari/solitude +solrad: + version: 1.0.0 + title: |- + Calculating Solar Radiation and Related Variables Based on + Location, Time and Topographical Conditions + maintainer: Bijan Seyednasrollah + description: 'For surface energy models and estimation of solar positions and components + with varying topography, time and locations. The functions calculate solar top-of-atmosphere, + open, diffuse and direct components, atmospheric transmittance and diffuse factors, + day length, sunrise and sunset, solar azimuth, zenith, altitude, incidence, and + hour angles, earth declination angle, equation of time, and solar constant. Details + about the methods and equations are explained in Seyednasrollah, Bijan, Mukesh + Kumar, and Timothy E. Link. ''On the role of vegetation density on net snow cover + radiation at the forest floor.'' Journal of Geophysical Research: Atmospheres + 118.15 (2013): 8359-8374, .' + date_publication: '2018-11-05' + bug_reports: https://github.com/bnasr/solrad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=solrad + url_git: https://github.com/bnasr/solrad/ +solrium: + version: 1.2.0 + title: General Purpose R Interface to 'Solr' + maintainer: Scott Chamberlain + description: |- + Provides a set of functions for querying and parsing data + from 'Solr' () 'endpoints' (local and + remote), including search, 'faceting', 'highlighting', 'stats', and + 'more like this'. In addition, some functionality is included for + creating, deleting, and updating documents in a 'Solr' 'database'. + date_publication: '2021-05-19' + bug_reports: https://github.com/ropensci/solrium/issues + url: https://docs.ropensci.org/solrium/(usermanual) + url_cran: https://CRAN.R-project.org/package=solrium + url_git: https://github.com/ropensci/solrium(devel) +solvebio: + version: 2.15.1 + title: The Official SolveBio API Client + maintainer: Tobi Guennel + description: |- + R language bindings for SolveBio's API. + SolveBio is a biomedical knowledge hub that enables life science + organizations to collect and harmonize the complex, disparate + "multi-omic" data essential for today's R&D and BI needs. + date_publication: '2025-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=solvebio + url_git: https://github.com/solvebio/solvebio-r +SolveSAPHE: + version: 2.1.0 + title: Solver Suite for Alkalinity-PH Equations + maintainer: Jean-Marie Epitalon + description: Universal and robust algorithm for solving the total alkalinity-pH + equation presented in G. Munhoven (2013) and G. + Munhoven (2021) . The total alkalinity-pH equation relates + total alkalinity and pH for a given set of acid-base concentrations in a given + water sample, among which carbonic acid. This package is particularly useful in + marine chemistry involving dissolved inorganic carbon. Original package in Fortran + can be found at . + date_publication: '2021-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SolveSAPHE + url_git: '' +som: + version: 0.3-5.2 + title: Self-Organizing Map + maintainer: Jun Yan + description: Self-Organizing Map (with application in gene clustering). + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=som + url_git: '' +som.nn: + version: 1.4.4 + title: Topological k-NN Classifier Based on Self-Organising Maps + maintainer: Andreas Dominik + description: |- + A topological version of k-NN: An abstract model is build + as 2-dimensional self-organising map. Samples of unknown + class are predicted by mapping them on the SOM and analysing + class membership of neurons in the neighbourhood. + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=som.nn + url_git: '' +soma: + version: 1.2.0 + title: |- + General-Purpose Optimisation with the Self-Organising Migrating + Algorithm + maintainer: Jon Clayden + description: An R implementation of the Self-Organising Migrating Algorithm, a general-purpose, + stochastic optimisation algorithm. The approach is similar to that of genetic + algorithms, although it is based on the idea of a series of ``migrations'' by + a fixed set of individuals, rather than the development of successive generations. + It can be applied to any cost-minimisation problem with a bounded parameter space, + and is robust to local minima. + date_publication: '2022-05-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soma + url_git: https://github.com/jonclayden/soma/ +SomaDataIO: + version: 6.2.0 + title: Input/Output 'SomaScan' Data + maintainer: Caleb Scheidel + description: |- + Load and export 'SomaScan' data via the + 'Standard BioTools, Inc.' structured text file + called an ADAT ('*.adat'). For file format see + . + The package also exports auxiliary functions for + manipulating, wrangling, and extracting relevant + information from an ADAT object once in memory. + date_publication: '2025-02-07' + bug_reports: https://github.com/SomaLogic/SomaDataIO/issues + url: https://somalogic.github.io/SomaDataIO/ + url_cran: https://CRAN.R-project.org/package=SomaDataIO + url_git: '' +somaticflags: + version: 0.1.0 + title: Database of Somatic Flags + maintainer: Sam El-Kamand + description: Database of genes which frequently sustain somatic mutations, but are + unlikely to drive cancer. + date_publication: '2024-07-09' + bug_reports: https://github.com/CCICB/somaticflags/issues + url: '' + url_cran: https://CRAN.R-project.org/package=somaticflags + url_git: https://github.com/CCICB/somaticflags +SOMbrero: + version: 1.4-2 + title: SOM Bound to Realize Euclidean and Relational Outputs + maintainer: Nathalie Vialaneix + description: |- + The stochastic (also called on-line) version of the Self-Organising + Map (SOM) algorithm is provided. Different versions of the + algorithm are implemented, for numeric and relational data and for + contingency tables as described, respectively, in Kohonen (2001) + , Olteanu & Villa-Vialaneix (2005) + and Cottrell et al (2004) + . The package also contains many + plotting features (to help the user interpret the results), can + handle (and impute) missing values and is delivered with a + graphical user interface based on 'shiny'. + date_publication: '2024-01-25' + bug_reports: https://github.com/tuxette/SOMbrero/issues + url: http://sombrero.clementine.wf/ + url_cran: https://CRAN.R-project.org/package=SOMbrero + url_git: '' +someMTP: + version: 1.4.1.1 + title: Some Multiple Testing Procedures + maintainer: livio finos + description: It's a collection of functions for Multiplicity Correction and Multiple + Testing. + date_publication: '2021-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=someMTP + url_git: '' +SOMEnv: + version: 1.1.2 + title: |- + SOM Algorithm for the Analysis of Multivariate Environmental + Data + maintainer: Sabina Licen + description: Analysis of multivariate environmental high frequency data by Self-Organizing + Map and k-means clustering algorithms. By means of the graphical user interface + it provides a comfortable way to elaborate by self-organizing map algorithm rather + big datasets (txt files up to 100 MB ) obtained by environmental high-frequency + monitoring by sensors/instruments. The functions present in the package are based + on 'kohonen' and 'openair' packages implemented by functions embedding Vesanto + et al. (2001) heuristic + rules for map initialization parameters, k-means clustering algorithm and map + features visualization. Cluster profiles visualization as well as graphs dedicated + to the visualization of time-dependent variables Licen et al. (2020) + are provided. + date_publication: '2021-07-26' + bug_reports: https://github.com/SomEnv/somenv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SOMEnv + url_git: https://github.com/SomEnv/somenv +somhca: + version: 0.2.0 + title: Self-Organising Maps Coupled with Hierarchical Cluster Analysis + maintainer: Gianluca Pastorelli + description: |- + Implements self-organising maps combined with hierarchical cluster analysis (SOM-HCA) for clustering and visualization of high-dimensional data. + The package includes functions to estimate the optimal map size based on various quality measures + and to generate a model using the selected dimensions. + It also performs hierarchical clustering on the map nodes to group similar units. + Documentation about the SOM-HCA method is provided in Pastorelli et al. (2024) + . + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=somhca + url_git: '' +SOMMD: + version: 0.1.2 + title: Self Organising Maps for the Analysis of Molecular Dynamics Data + maintainer: Stefano Motta + description: |- + Processes data from Molecular Dynamics simulations using + Self Organising Maps. Features include the ability to read different + input formats. Trajectories can be analysed to identify groups of important + frames. Output visualisation can be generated for maps and pathways. + Methodological details can be found in Motta S et al (2022) + . + I/O functions for xtc format files were implemented using the 'xdrfile' + library available under open source license. The relevant information can + be found in inst/COPYRIGHT. + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOMMD + url_git: '' +sommer: + version: 4.3.7 + title: Solving Mixed Model Equations in R + maintainer: Giovanny Covarrubias-Pazaran + description: Structural multivariate-univariate linear mixed model solver for estimation + of multiple random effects with unknown variance-covariance structures (e.g., + heterogeneous and unstructured) and known covariance among levels of random effects + (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 + ; Maier et al., 2015 ; + Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion + Newton-Raphson and Direct-Inversion Average Information algorithms for the problems + r x r (r being the number of records) or using the Henderson-based average information + algorithm for the problem c x c (c being the number of coefficients to estimate). + Spatial models can also be fitted using the two-dimensional spline functionality + available. + date_publication: '2025-02-03' + bug_reports: https://github.com/covaruber/sommer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sommer + url_git: https://github.com/covaruber/sommer +SOMnmR: + version: 0.3.0 + title: Analysis of Soil Organic Matter using Nuclear Magnetic Resonance + maintainer: Luis Colocho + description: 'Integrates the 13C nuclear magnetic resonance spectra using different + integration ranges. Output depends on the method chosen. For the Molecular Mixing + Model, a measurement of the fitting quality is given by its R-factor. For more + details see: .' + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOMnmR + url_git: https://github.com/LuisCol8/SOMnmR/ +somspace: + version: 1.2.4 + title: Spatial Analysis with Self-Organizing Maps + maintainer: Yannis Markonis + description: Application of the Self-Organizing Maps technique for spatial classification + of time series. The package uses spatial data, point or gridded, to create clusters + with similar characteristics. The clusters can be further refined to a smaller + number of regions by hierarchical clustering and their spatial dependencies can + be presented as complex networks. Thus, meaningful maps can be created, representing + the regional heterogeneity of a single variable. More information and an example + of implementation can be found in Markonis and Strnad (2020, ). + date_publication: '2023-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=somspace + url_git: '' +sonar: + version: 1.0.2 + title: Fundamental Formulas for Sonar + maintainer: Jose Gama + description: |- + Formulas for calculating sound velocity, water pressure, depth, + density, absorption and sonar equations. + date_publication: '2016-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sonar + url_git: '' +SongEvo: + version: 1.0.0 + title: An Individual-Based Model of Bird Song Evolution + maintainer: Raymond Danner + description: Simulates the cultural evolution of quantitative traits of bird song. + 'SongEvo' is an individual- (agent-) based model. 'SongEvo' is spatially-explicit + and can be parameterized with, and tested against, measured song data. Functions + are available for model implementation, sensitivity analyses, parameter optimization, + model validation, and hypothesis testing. + date_publication: '2019-03-05' + bug_reports: https://github.com/raydanner/SongEvo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SongEvo + url_git: '' +sonicLength: + version: 1.4.7 + title: Estimating Abundance of Clones from DNA Fragmentation Data + maintainer: Charles Berry + description: |- + Estimate the abundance of cell clones from the + distribution of lengths of DNA fragments (as created by + sonication, whence `sonicLength'). The algorithm in + "Estimating abundances of retroviral insertion sites from + DNA fragment length data" by Berry CC, Gillet NA, Melamed + A, Gormley N, Bangham CR, Bushman FD. Bioinformatics; + 2012 Mar 15;28(6):755-62 is implemented. The + experimental setting and estimation details are described + in detail there. Briefly, integration of new DNA in a + host genome (due to retroviral infection or gene therapy) + can be tracked using DNA sequencing, potentially allowing + characterization of the abundance of individual cell + clones bearing distinct integration sites. The locations + of integration sites can be determined by fragmenting the + host DNA (via sonication or fragmentase), breaking the + newly integrated DNA at a known sequence, amplifying the + fragments containing both host and integrated DNA, + sequencing those amplicons, then mapping the host + sequences to positions on the reference genome. The + relative number of fragments containing a given position + in the host genome estimates the relative abundance of + cells hosting the corresponding integration site, but + that number is not available and the count of amplicons + per fragment varies widely. However, the expected number + of distinct fragment lengths is a function of the + abundance of cells hosting an integration site at a given + position and a certain nuisance parameter. The algorithm + implicitly estimates that function to estimate the + relative abundance. + date_publication: '2021-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sonicLength + url_git: '' +sonicscrewdriver: + version: 0.0.7 + title: Bioacoustic Analysis and Publication Tools + maintainer: Ed Baker + description: |- + Provides tools for manipulating sound files for bioacoustic + analysis, and preparing analyses these for publication. The package validates + that values are physically possible wherever feasible. + date_publication: '2024-05-11' + bug_reports: https://github.com/edwbaker/SonicScrewdriveR/issues + url: https://sonicscrewdriver.ebaker.me.uk + url_cran: https://CRAN.R-project.org/package=sonicscrewdriver + url_git: https://github.com/edwbaker/SonicScrewdriveR +sonify: + version: 0.0-1 + title: Data Sonification - Turning Data into Sound + maintainer: Stefan Siegert + description: Sonification (or audification) is the process of representing data + by sounds in the audible range. This package provides the R function sonify() + that transforms univariate data, sampled at regular or irregular intervals, into + a continuous sound with time-varying frequency. The ups and downs in frequency + represent the ups and downs in the data. Sonify provides a substitute for R's + plot function to simplify data analysis for the visually impaired. + date_publication: '2017-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sonify + url_git: '' +sooty: + version: 0.1.0 + title: |- + Data Source Catalogues Online for Southern Ocean Ecosystem + Research + maintainer: Michael D. Sumner + description: |- + Obtains lists of files of remote sensing collections for Southern Ocean surface + properties. Commonly used data sources of sea surface temperature, sea ice concentration, and + altimetry products such as sea surface height and sea surface currents are cached in object storage + on the Pawsey Supercomputing Research Centre facility. Functions to retrieve these object storage + catalogues are provided. The catalogues include complete collections of datasets Reynolds et al. (2008) + "NOAA Optimum Interpolation Sea Surface Temperature (OISST) Analysis, Version 2.1" , + Spreen et al. (2008) "Artist Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) + sea ice concentration" . In future releases helpers will be added to identify + particular data collections and target specific dates for earth observation data for reading, as well as + helpers to retrieve data set citation and provenance details. + date_publication: '2024-12-06' + bug_reports: https://github.com/mdsumner/sooty/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sooty + url_git: https://github.com/mdsumner/sooty +SOP: + version: 1.0-1 + title: Generalised Additive P-Spline Regression Models Estimation + maintainer: Maria Xose Rodriguez-Alvarez + description: Generalised additive P-spline regression models estimation using the + separation of overlapping precision matrices (SOP) method. Estimation is based + on the equivalence between P-splines and linear mixed models, and variance/smoothing + parameters are estimated based on restricted maximum likelihood (REML). The package + enables users to estimate P-spline models with overlapping penalties. Based on + the work described in Rodriguez-Alvarez et al. (2015) ; + Rodriguez-Alvarez et al. (2019) , and Eilers and + Marx (1996) . + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOP + url_git: '' +SOPC: + version: 0.1.0 + title: The Sparse Online Principal Component Estimation Algorithm + maintainer: Guangbao Guo + description: The sparse online principal component can not only process the online + data set, but also obtain a sparse solution of the online data set. The philosophy + of the package is described in Guo G. (2022) . + date_publication: '2023-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOPC + url_git: '' +SOPIE: + version: '1.6' + title: Non-Parametric Estimation of the Off-Pulse Interval of a Pulsar + maintainer: Willem Daniel Schutte + description: |- + Provides functions to non-parametrically estimate the off-pulse interval of a source + function originating from a pulsar. The technique is based on a sequential application of P-values + obtained from goodness-of-fit tests for the uniform distribution, such as the Kolmogorov-Smirnov, + Cramer-von Mises, Anderson-Darling and Rayleigh goodness-of-fit tests. + date_publication: '2022-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOPIE + url_git: '' +soptdmaeA: + version: 1.0.0 + title: |- + Sequential Optimal Designs for Two-Colour cDNA Microarray + Experiments + maintainer: Dibaba Bayisa Gemechu + description: Computes sequential A-, MV-, D- and E-optimal or near-optimal block + and row-column designs for two-colour cDNA microarray experiments using the linear + fixed effects and mixed effects models where the interest is in a comparison of + all possible elementary treatment contrasts. The package also provides an optional + method of using the graphical user interface (GUI) R package 'tcltk' to ensure + that it is user friendly. + date_publication: '2017-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soptdmaeA + url_git: '' +soql: + version: 0.1.1 + title: Helps Make Socrata Open Data API Calls + maintainer: '"Zeb Burke-Conte"' + description: Used to construct the URLs and parameters of 'Socrata Open Data API' + calls, using the API's 'SoQL' parameter format. Has + method-chained and sensical syntax. Plays well with pipes. + date_publication: '2016-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=soql + url_git: '' +SOR: + version: 0.23.1 + title: Estimation using Sequential Offsetted Regression + maintainer: Lee McDaniel + description: Estimation for longitudinal data following outcome dependent sampling + using the sequential offsetted regression technique. Includes support for binary, + count, and continuous data. The first regression is a logistic regression, which + uses a known ratio (the probability of being sampled given that the subject/observation + was referred divided by the probability of being sampled given that the subject/observation + was no referred) as an offset to estimate the probability of being referred given + outcome and covariates. The second regression uses this estimated probability + to calculate the mean population response given covariates. + date_publication: '2018-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SOR + url_git: '' +sorcering: + version: 1.1.0 + title: |- + Soil Organic Carbon and CN Ratio Driven Nitrogen Modelling + Framework + maintainer: Marc Scherstjanoi + description: Can be used to model the fate of soil organic carbon and soil organic + nitrogen and to calculate N mineralisation rates. Provides a framework that numerically + solves differential equations of soil organic carbon models based on first-order + kinetics and extends these models to include the nitrogen component. The name + 'sorcering' is an acronym for 'Soil ORganic Carbon & CN Ratio drIven Nitrogen + modellinG framework'. + date_publication: '2024-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sorcering + url_git: '' +sorocs: + version: 0.1.0 + title: A Bayesian Semiparametric Approach to Correlated ROC Surfaces + maintainer: Weimin Zhang + description: A Bayesian semiparametric Dirichlet process mixtures to estimate correlated + receiver operating characteristic (ROC) surfaces and the associated volume under + the surface (VUS) with stochastic order constraints. The reference paper is:Zhen + Chen, Beom Seuk Hwang, (2018) "A Bayesian semiparametric approach to correlated + ROC surfaces with stochastic order constraints". Biometrics, 75, 539-550. . + date_publication: '2020-03-13' + bug_reports: http://github.com/wzhang17/sorocs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sorocs + url_git: http://github.com/wzhang17/sorocs.git +SorptionAnalysis: + version: 0.1.0 + title: Static Adsorption Experiment Plotting and Analysis + maintainer: Aurnov Chattopadhyay + description: 'Provides tools to efficiently analyze and visualize laboratory data + from aqueous static adsorption experiments. The package provides functions to + plot Langmuir, Freundlich, and Temkin isotherms and functions to determine the + statistical conformity of data points to the Langmuir, Freundlich, and Temkin + adsorption models through statistical characterization of the isothermic least + squares regressions lines. Scientific Reference: Dada, A.O, Olalekan, A., Olatunya, + A. (2012) .' + date_publication: '2017-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SorptionAnalysis + url_git: '' +sortable: + version: 0.5.0 + title: Drag-and-Drop in 'shiny' Apps with 'SortableJS' + maintainer: Andrie de Vries + description: |- + Enables drag-and-drop behaviour in Shiny apps, by exposing the + functionality of the 'SortableJS' + JavaScript library as an 'htmlwidget'. + You can use this in Shiny apps and widgets, 'learnr' tutorials as well as + R Markdown. In addition, provides a custom 'learnr' question type - + 'question_rank()' - that allows ranking questions with drag-and-drop. + date_publication: '2023-03-26' + bug_reports: https://github.com/rstudio/sortable/issues + url: https://rstudio.github.io/sortable/ + url_cran: https://CRAN.R-project.org/package=sortable + url_git: '' +SortedEffects: + version: 1.7.0 + title: |- + Estimation and Inference Methods for Sorted Causal Effects and + Classification Analysis + maintainer: Shuowen Chen + description: |- + Implements the estimation and inference methods for sorted causal effects and + classification analysis as in Chernozhukov, Fernandez-Val and Luo (2018) . + date_publication: '2022-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SortedEffects + url_git: https://github.com/shuowencs/SortedEffects +sorvi: + version: 0.8.21 + title: Functions for Finnish Open Data + maintainer: Leo Lahti + description: Misc support functions for rOpenGov and open data downloads. + date_publication: '2023-08-22' + bug_reports: https://github.com/ropengov/sorvi/issues + url: https://ropengov.github.io/sorvi/ + url_cran: https://CRAN.R-project.org/package=sorvi + url_git: https://github.com/ropengov/sorvi +sos: + version: 2.1-8 + title: Search Contributed R Packages, Sort by Package + maintainer: Spencer Graves + description: Search contributed R packages, sort by package. + date_publication: '2024-06-29' + bug_reports: https://github.com/sbgraves237/sos/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sos + url_git: https://github.com/sbgraves237/sos +sotkanet: + version: 0.10.1 + title: Sotkanet Open Data Access and Analysis + maintainer: Leo Lahti + description: |- + Access statistical information on welfare and health in Finland + from the Sotkanet open data portal . + date_publication: '2024-07-10' + bug_reports: https://github.com/ropengov/sotkanet/issues + url: https://ropengov.github.io/sotkanet/ + url_cran: https://CRAN.R-project.org/package=sotkanet + url_git: '' +sotu: + version: 1.0.4 + title: United States Presidential State of the Union Addresses + maintainer: Taylor B. Arnold + description: |- + The President of the United States is constitutionally obligated to provide + a report known as the 'State of the Union'. The report summarizes the current challenges + facing the country and the president's upcoming legislative agenda. While historically + the State of the Union was often a written document, in recent decades it has always + taken the form of an oral address to a joint session of the United States Congress. + This package provides the raw text from every such address with the intention of + being used for meaningful examples of text analysis in R. The corpus is well suited + to the task as it is historically important, includes material intended to be read + and material intended to be spoken, and it falls in the public domain. As the corpus + spans over two centuries it is also a good test of how well various methods hold up + to the idiosyncrasies of historical texts. Associated data about each address, such + as the year, president, party, and format, are also included. + date_publication: '2022-08-17' + bug_reports: https://github.com/statsmaths/sotu/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=sotu + url_git: https://github.com/statsmaths/sotu/ +sound: + version: 1.4.6 + title: A Sound Interface for R + maintainer: Stefan Langenberg + description: Basic functions for dealing with wav files and sound samples. + date_publication: '2023-12-11' + bug_reports: https://github.com/langenbergstefan/sound/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sound + url_git: https://github.com/langenbergstefan/sound +soundClass: + version: 0.0.9.2 + title: Sound Classification Using Convolutional Neural Networks + maintainer: Bruno Silva + description: |- + Provides an all-in-one solution for automatic classification of + sound events using convolutional neural networks (CNN). The main purpose + is to provide a sound classification workflow, from annotating sound events + in recordings to training and automating model usage in real-life + situations. Using the package requires a pre-compiled collection of + recordings with sound events of interest and it can be employed for: + 1) Annotation: create a database of annotated recordings, + 2) Training: prepare train data from annotated recordings and fit CNN models, + 3) Classification: automate the use of the fitted model for classifying + new recordings. By using automatic feature selection and a user-friendly GUI + for managing data and training/deploying models, this package is intended + to be used by a broad audience as it does not require specific expertise in + statistics, programming or sound analysis. Please refer to the vignette for + further information. + Gibb, R., et al. (2019) + Mac Aodha, O., et al. (2018) + Stowell, D., et al. (2019) + LeCun, Y., et al. (2012) . + date_publication: '2022-05-29' + bug_reports: https://github.com/bmsasilva/soundClass/issues + url: '' + url_cran: https://CRAN.R-project.org/package=soundClass + url_git: '' +soundecology: + version: 1.3.3 + title: Soundscape Ecology + maintainer: Luis J. Villanueva-Rivera + description: Functions to calculate indices for soundscape ecology and other ecology + research that uses audio recordings. + date_publication: '2018-03-05' + bug_reports: http://github.com/ljvillanueva/soundecology/issues + url: http://ljvillanueva.github.io/soundecology/ + url_cran: https://CRAN.R-project.org/package=soundecology + url_git: '' +SoundexBR: + version: '1.2' + title: Phonetic-Coding for Portuguese + maintainer: Daniel Marcelino + description: |- + The SoundexBR package provides an algorithm for decoding names + into phonetic codes, as pronounced in Portuguese. The goal is for + homophones to be encoded to the same representation so that they can be + matched despite minor differences in spelling. The algorithm mainly encodes + consonants; a vowel will not be encoded unless it is the first letter. The + soundex code resultant consists of a four digits long string composed by + one letter followed by three numerical digits: the letter is the first + letter of the name, and the digits encode the remaining consonants. + date_publication: '2015-07-14' + bug_reports: http://github.com/danielmarcelino/soundexBR + url: '' + url_cran: https://CRAN.R-project.org/package=SoundexBR + url_git: '' +soundgen: + version: 2.7.2 + title: Sound Synthesis and Acoustic Analysis + maintainer: Andrey Anikin + description: |- + Performs parametric synthesis of sounds with harmonic and noise + components such as animal vocalizations or human voice. Also offers tools + for audio manipulation and acoustic analysis, including pitch tracking, + spectral analysis, audio segmentation, pitch and formant shifting, etc. + Includes four interactive web apps for synthesizing and annotating audio, + manually correcting pitch contours, and measuring formant frequencies. + Reference: Anikin (2019) . + date_publication: '2025-01-22' + bug_reports: '' + url: http://cogsci.se/soundgen.html + url_cran: https://CRAN.R-project.org/package=soundgen + url_git: '' +SoundShape: + version: 1.3.2 + title: Sound Waves Onto Morphometric Data + maintainer: Pedro Rocha + description: Implement a promising, and yet little explored protocol for bioacoustical + analysis, the eigensound method by MacLeod, Krieger and Jones (2013) . + Eigensound is a multidisciplinary method focused on the direct comparison between + stereotyped sounds from different species. 'SoundShape', in turn, provide the + tools required for anyone to go from sound waves to Principal Components Analysis, + using tools extracted from traditional bioacoustics (i.e. 'tuneR' and 'seewave' + packages), geometric morphometrics (i.e. 'geomorph' package) and multivariate + analysis (e.g. 'stats' package). For more information, please see Rocha and Romano + (2021) and check 'SoundShape' repository on GitHub for news and updates . + date_publication: '2024-11-20' + bug_reports: https://github.com/p-rocha/SoundShape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SoundShape + url_git: https://github.com/p-rocha/SoundShape +SoupX: + version: 1.6.2 + title: Single Cell mRNA Soup eXterminator + maintainer: Matthew Daniel Young + description: Quantify, profile and remove ambient mRNA contamination (the "soup") + from droplet based single cell RNA-seq experiments. Implements the method described + in Young et al. (2018) . + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoupX + url_git: https://github.com/constantAmateur/SoupX +sourcetools: + version: 0.1.7-1 + title: Tools for Reading, Tokenizing and Parsing R Code + maintainer: Kevin Ushey + description: |- + Tools for the reading and tokenization of R code. The + 'sourcetools' package provides both an R and C++ interface for the tokenization + of R code, and helpers for interacting with the tokenized representation of R + code. + date_publication: '2023-02-01' + bug_reports: https://github.com/kevinushey/sourcetools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sourcetools + url_git: '' +SouthParkRshiny: + version: 1.0.0 + title: Data and 'Shiny' Application for the Show 'SouthPark' + maintainer: Amalan Mahendran + description: |- + Ratings, votes, swear words and sentiments are analysed for + the show 'SouthPark' through a 'Shiny' application after web scraping + from 'IMDB' and the website . + date_publication: '2024-03-09' + bug_reports: https://github.com/Amalan-ConStat/SouthParkRshiny/issues + url: https://amalan-con-stat.shinyapps.io/SouthParkRshiny/ + url_cran: https://CRAN.R-project.org/package=SouthParkRshiny + url_git: https://github.com/Amalan-ConStat/SouthParkRshiny +sovereign: + version: 1.2.1 + title: State-Dependent Empirical Analysis + maintainer: Tyler J. Pike + description: |- + A set of tools for state-dependent + empirical analysis through both VAR- and local projection-based + state-dependent forecasts, impulse response functions, + historical decompositions, and forecast error variance decompositions. + date_publication: '2022-01-04' + bug_reports: https://github.com/tylerJPike/sovereign/issues + url: https://tylerjpike.github.io/sovereign/ + url_cran: https://CRAN.R-project.org/package=sovereign + url_git: https://github.com/tylerJPike/sovereign +sox: + version: 1.2.1 + title: Structured Learning in Time-Dependent Cox Models + maintainer: Yi Lian + description: Efficient procedures for fitting and cross-validating the structurally-regularized + time-dependent Cox models. + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sox + url_git: '' +SoyNAM: + version: 1.6.2 + title: Soybean Nested Association Mapping Dataset + maintainer: Alencar Xavier + description: |- + Genomic and multi-environmental soybean data. Soybean Nested + Association Mapping (SoyNAM) project dataset funded by the United Soybean Board + (USB). BLUP function formats data for genome-wide prediction and association analysis. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoyNAM + url_git: '' +SoyURT: + version: 1.0.0 + title: USDA Northern Region Uniform Soybean Tests Dataset + maintainer: Matheus Dalsente Krause + description: Data sets used by 'Krause et al. (2022)' . + It comprises phenotypic records obtained from the USDA Northern Region Uniform + Soybean Tests from 1989 to 2019 for maturity groups II and III. In addition, soil + and weather variables are provided for the 591 observed environments (combination + of locations and years). + date_publication: '2022-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SoyURT + url_git: https://github.com/mdkrause/soyurt +sp: + version: 2.2-0 + title: Classes and Methods for Spatial Data + maintainer: Edzer Pebesma + description: |- + Classes and methods for spatial + data; the classes document where the spatial location information + resides, for 2D or 3D data. Utility functions are provided, e.g. for + plotting data as maps, spatial selection, as well as methods for + retrieving coordinates, for subsetting, print, summary, etc. From this + version, 'rgdal', 'maptools', and 'rgeos' are no longer used at all, + see for details. + date_publication: '2025-02-01' + bug_reports: https://github.com/edzer/sp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sp + url_git: https://github.com/edzer/sp/https://edzer.github.io/sp/ +SP2000: + version: 0.2.0 + title: Catalogue of Life Toolkit + maintainer: Liuyong Ding + description: A programmatic interface to , re-written based + on an accompanying 'Species 2000' API. Access tables describing catalogue of the + Chinese known species of animals, plants, fungi, micro-organisms, and more. This + package also supports access to catalogue of life global , + China animal scientific database and catalogue of + life Taiwan . The development of 'SP2000' + package were supported by Biodiversity Survey and Assessment Project of the Ministry + of Ecology and Environment, China <2019HJ2096001006>,Yunnan University's "Double + First Class" Project and Yunnan University's Research Innovation + Fund for Graduate Students <2019227>. + date_publication: '2020-10-26' + bug_reports: https://github.com/Otoliths/SP2000/issues + url: https://otoliths.github.io/SP2000/ + url_cran: https://CRAN.R-project.org/package=SP2000 + url_git: '' +sp23design: + version: 0.9-1 + title: Design and Simulation of Seamless Phase II-III Clinical Trials + maintainer: Balasubramanian Narasimhan + description: Provides methods for generating, exploring and executing seamless Phase + II-III designs of Lai, Lavori and Shih using generalized likelihood ratio statistics. + Includes pdf and source files that describe the entire R implementation with the + relevant mathematical details. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sp23design + url_git: '' +spaa: + version: 0.2.5 + title: SPecies Association Analysis + maintainer: Jinlong Zhang + description: |- + Miscellaneous functions for analysing species association + and niche overlap. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spaa + url_git: https://github.com/helixcn/spaa +spAbundance: + version: 0.2.1 + title: |- + Univariate and Multivariate Spatial Modeling of Species + Abundance + maintainer: Jeffrey Doser + description: Fits single-species (univariate) and multi-species (multivariate) non-spatial + and spatial abundance models in a Bayesian framework using Markov Chain Monte + Carlo (MCMC). Spatial models are fit using Nearest Neighbor Gaussian Processes + (NNGPs). Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand + (2016) and Finley, Datta, and Banerjee (2022) + . Fits single-species and multi-species spatial and + non-spatial versions of generalized linear mixed models (Gaussian, Poisson, Negative + Binomial), N-mixture models (Royle 2004 ) + and hierarchical distance sampling models (Royle, Dawson, Bates (2004) ). + Multi-species spatial models are fit using a spatial factor modeling approach + with NNGPs for computational efficiency. + date_publication: '2024-10-05' + bug_reports: https://github.com/biodiverse/spAbundance/issues + url: https://www.doserlab.com/files/spabundance-webhttps://groups.google.com/g/spocc-spabund-users + url_cran: https://CRAN.R-project.org/package=spAbundance + url_git: '' +SpaCCI: + version: 1.0.3 + title: Spatially Aware Cell-Cell Interaction Analysis + maintainer: Li-Ting Ku + description: Provides tools for analyzing spatial cell-cell interactions based on + ligand-receptor pairs, including functions for local, regional, and global analysis + using spatial transcriptomics data. Integrates with databases like 'CellChat' + , 'CellPhoneDB' , 'Cellinker' + , 'ICELLNET' , + and 'ConnectomeDB' to identify + ligand-receptor pairs, visualize interactions through heatmaps, chord diagrams, + and infer interactions on different spatial scales. + date_publication: '2025-01-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpaCCI + url_git: '' +spacefillr: + version: 0.4.0 + title: Space-Filling Random and Quasi-Random Sequences + maintainer: Tyler Morgan-Wall + description: 'Generates random and quasi-random space-filling sequences. Supports + the following sequences: ''Halton'', ''Sobol'', ''Owen''-scrambled ''Sobol'', ''Owen''-scrambled + ''Sobol'' with errors distributed as blue noise, progressive jittered, progressive + multi-jittered (''PMJ''), ''PMJ'' with blue noise, ''PMJ02'', and ''PMJ02'' with + blue noise. Includes a ''C++'' ''API''. Methods derived from "Constructing Sobol + sequences with better two-dimensional projections" (2012) + S. Joe and F. Y. Kuo, "Progressive Multi-Jittered Sample Sequences" (2018) + Christensen, P., Kensler, A. and Kilpatrick, C., and "A Low-Discrepancy Sampler + that Distributes Monte Carlo Errors as a Blue Noise in Screen Space" (2019) E. + Heitz, B. Laurent, O. Victor, C. David and I. Jean-Claude, .' + date_publication: '2025-02-24' + bug_reports: https://github.com/tylermorganwall/spacefillr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spacefillr + url_git: https://github.com/tylermorganwall/spacefillr +spacejamr: + version: 0.2.1 + title: Simulate Spatial Bernoulli Networks + maintainer: Darren Colby + description: |- + Social network analysis is becoming commonplace in many social + science disciplines, but access to useful network data, especially + among marginalized populations, still remains a formidable challenge. + This package mitigates that problem by providing tools to simulate spatial + Bernoulli networks as proposed in Carter T. Butts + (2002, ISBN:978-0-493-72676-2), "Spatial models of large-scale interpersonal + networks." Using this package, network analysts can simulate a spatial point + process or sequence with a given number of nodes inside a geographical + boundary and estimate the probability of a tie formation between all node + pairs. When simulating a network, an analyst can choose between five spatial + interaction functions. The package also enables quick comparison of summary + statistics for simulated networks and provides simple to use plotting + methods for its classes that return plots which can be further refined with + the 'ggplot2' package. + date_publication: '2022-04-01' + bug_reports: https://github.com/dscolby/spacejamr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spacejamr + url_git: https://github.com/dscolby/spacejamr +spaceNet: + version: '1.2' + title: Latent Space Models for Multidimensional Networks + maintainer: Silvia D'Angelo + description: Latent space models for multivariate networks (multiplex) estimated + via MCMC algorithm. See D Angelo et al. (2018) and D Angelo + et al. (2018) . + date_publication: '2019-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spaceNet + url_git: '' +spacesRGB: + version: 1.7-0 + title: |- + Standard and User-Defined RGB Color Spaces, with Conversion + Between RGB and CIE XYZ and Lab + maintainer: Glenn Davis + description: Standard RGB spaces included are sRGB, 'Adobe' RGB, 'ProPhoto' RGB, + BT.709, and others. User-defined RGB spaces are also possible. There is partial + support for ACES Color workflows. + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spacesRGB + url_git: '' +spacesXYZ: + version: 1.5-1 + title: CIE XYZ and some of Its Derived Color Spaces + maintainer: Glenn Davis + description: |- + Functions for converting among CIE XYZ, xyY, Lab, and Luv. + Calculate Correlated Color Temperature (CCT) and the Planckian and daylight loci. + The XYZs of some standard illuminants and some standard linear chromatic adaptation transforms (CATs) are included. + Three standard color difference metrics are included, plus the forward direction of the 'CIECAM02' color appearance model. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spacesXYZ + url_git: '' +spacetime: + version: 1.3-3 + title: Classes and Methods for Spatio-Temporal Data + maintainer: Edzer Pebesma + description: Classes and methods for spatio-temporal data, including space-time + regular lattices, sparse lattices, irregular data, and trajectories; utility functions + for plotting data as map sequences (lattice or animation) or multiple time series; + methods for spatial and temporal selection and subsetting, as well as for spatial/temporal/spatio-temporal + matching or aggregation, retrieving coordinates, print, summary, etc. + date_publication: '2025-02-13' + bug_reports: https://github.com/edzer/spacetime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spacetime + url_git: https://github.com/edzer/spacetime +SpaceTimeBSS: + version: 0.4-0 + title: Blind Source Separation for Multivariate Spatio-Temporal Data + maintainer: Klaus Nordhausen + description: Simultaneous/joint diagonalization of local autocovariance matrices + to estimate spatio-temporally uncorrelated random fields. + date_publication: '2024-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpaceTimeBSS + url_git: '' +SpaCOAP: + version: '1.2' + title: |- + High-Dimensional Spatial Covariate-Augmented Overdispersed + Poisson Factor Model + maintainer: Wei Liu + description: A spatial covariate-augmented overdispersed Poisson factor model is + proposed to perform efficient latent representation learning method for high-dimensional + large-scale spatial count data with additional covariates. + date_publication: '2024-05-27' + bug_reports: https://github.com/feiyoung/SpaCOAP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpaCOAP + url_git: https://github.com/feiyoung/SpaCOAP +spacyr: + version: 1.3.0 + title: Wrapper to the 'spaCy' 'NLP' Library + maintainer: Kenneth Benoit + description: |- + An R wrapper to the 'Python' 'spaCy' 'NLP' library, + from . + date_publication: '2023-12-08' + bug_reports: https://github.com/quanteda/spacyr/issues + url: https://spacyr.quanteda.io + url_cran: https://CRAN.R-project.org/package=spacyr + url_git: '' +SPADAR: + version: '1.0' + title: Spherical Projections of Astronomical Data + maintainer: Alberto Krone-Martins + description: Provides easy to use functions to create all-sky grid plots of widely + used astronomical coordinate systems (equatorial, ecliptic, galactic) and scatter + plots of data on any of these systems including on-the-fly system conversion. + It supports any type of spherical projection to the plane defined by the 'mapproj' + package. + date_publication: '2017-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPADAR + url_git: '' +spAddins: + version: 0.2.0 + title: A Set of RStudio Addins + maintainer: Vilmantas Gegzna + description: |- + A set of RStudio addins that are designed to be used in + combination with user-defined RStudio keyboard shortcuts. These + addins either: + 1) insert text at a cursor position (e.g. insert + operators %>%, <<-, %$%, etc.), + 2) replace symbols in selected pieces of text (e.g., convert + backslashes to forward slashes which results in stings like + "c:\data\" converted into "c:/data/") or + 3) enclose text with special symbols (e.g., converts "bold" into + "**bold**") which is convenient for editing R Markdown files. + date_publication: '2017-12-14' + bug_reports: https://github.com/GegznaV/spAddins/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spAddins + url_git: https://github.com/GegznaV/spAddins +SpadeR: + version: 0.1.1 + title: Species-Richness Prediction and Diversity Estimation with R + maintainer: Anne Chao + description: Estimation of various biodiversity indices and related (dis)similarity + measures based on individual-based (abundance) data or sampling-unit-based (incidence) + data taken from one or multiple communities/assemblages. + date_publication: '2016-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpadeR + url_git: '' +SpaDES: + version: 2.0.11 + title: |- + Develop and Run Spatially Explicit Discrete Event Simulation + Models + maintainer: Alex M Chubaty + description: |- + Metapackage for implementing a variety of event-based models, with + a focus on spatially explicit models. These include raster-based, + event-based, and agent-based models. The core simulation components + (provided by 'SpaDES.core') are built upon a discrete event simulation (DES; + see Matloff (2011) ch 7.8.3 ) + framework that facilitates modularity, and easily enables the user to + include additional functionality by running user-built simulation modules + (see also 'SpaDES.tools'). Included are numerous tools to visualize rasters + and other maps (via 'quickPlot'), and caching methods for reproducible + simulations (via 'reproducible'). Tools for running simulation experiments are + provided by 'SpaDES.experiment'. Additional functionality is provided by + the 'SpaDES.addins' and 'SpaDES.shiny' packages. + date_publication: '2024-04-17' + bug_reports: https://github.com/PredictiveEcology/SpaDES/issues + url: https://spades.predictiveecology.org + url_cran: https://CRAN.R-project.org/package=SpaDES + url_git: https://github.com/PredictiveEcology/SpaDES +SpaDES.core: + version: 2.1.0 + title: |- + Core Utilities for Developing and Running Spatially Explicit + Discrete Event Models + maintainer: Eliot J B McIntire + description: |- + Provides the core framework for a discrete event system to + implement a complete data-to-decisions, reproducible workflow. + The core components facilitate the development of modular pieces, + and enable the user to include additional functionality by running user-built modules. + Includes conditional scheduling, restart after interruption, packaging of + reusable modules, tools for developing arbitrary automated workflows, + automated interweaving of modules of different temporal resolution, + and tools for visualizing and understanding the within-project dependencies. + The suggested package 'NLMR' can be installed from the repository + (). + date_publication: '2024-06-02' + bug_reports: https://github.com/PredictiveEcology/SpaDES.core/issues + url: https://spades-core.predictiveecology.org/ + url_cran: https://CRAN.R-project.org/package=SpaDES.core + url_git: https://github.com/PredictiveEcology/SpaDES.core +SpaDES.tools: + version: 2.0.7 + title: |- + Additional Tools for Developing Spatially Explicit Discrete + Event Simulation (SpaDES) Models + maintainer: Alex M Chubaty + description: |- + Provides GIS and map utilities, plus additional modeling tools for + developing cellular automata, dynamic raster models, and agent based models + in 'SpaDES'. + Included are various methods for spatial spreading, spatial agents, GIS operations, + random map generation, and others. + See '?SpaDES.tools' for an categorized overview of these additional tools. + The suggested package 'NLMR' can be installed from the following repository: + (). + date_publication: '2024-05-15' + bug_reports: https://github.com/PredictiveEcology/SpaDES.tools/issues + url: https://spades-tools.predictiveecology.org + url_cran: https://CRAN.R-project.org/package=SpaDES.tools + url_git: https://github.com/PredictiveEcology/SpaDES.tools +spaero: + version: 0.6.0 + title: Software for Project AERO + maintainer: Eamon O'Dea + description: |- + Implements methods for anticipating the emergence and eradication + of infectious diseases from surveillance time series. Also provides support + for computational experiments testing the performance of such methods. + date_publication: '2020-09-26' + bug_reports: https://github.com/e3bo/spaero/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=spaero + url_git: '' +spagmix: + version: 0.4-2 + title: |- + Artificial Spatial and Spatio-Temporal Densities on Bounded + Windows + maintainer: Tilman M. Davies + description: Simple utilities to design and generate density functions on bounded + regions in space and space-time, and simulate independent, identically distributed + data therefrom. See Davies & Lawson (2019) + for example. + date_publication: '2024-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spagmix + url_git: '' +spam: + version: 2.11-1 + title: SPArse Matrix + maintainer: Reinhard Furrer + description: |- + Set of functions for sparse matrix algebra. + Differences with other sparse matrix packages are: + (1) we only support (essentially) one sparse matrix format, + (2) based on transparent and simple structure(s), + (3) tailored for MCMC calculations within G(M)RF. + (4) and it is fast and scalable (with the extension package spam64). + Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) ; see 'citation("spam")' for details. + date_publication: '2025-01-20' + bug_reports: https://git.math.uzh.ch/reinhard.furrer/spam/-/issues + url: https://www.math.uzh.ch/pages/spam/ + url_cran: https://CRAN.R-project.org/package=spam + url_git: '' +spam64: + version: 2.10-0 + title: 64-Bit Extension of the SPArse Matrix R Package 'spam' + maintainer: Reinhard Furrer + description: |- + Provides the Fortran code of the R package 'spam' + with 64-bit integers. Loading this package together with the R package + spam enables the sparse matrix class spam to handle huge sparse matrices + with more than 2^31-1 non-zero elements. + Documentation is provided in Gerber, Moesinger and Furrer (2017) . + date_publication: '2023-10-17' + bug_reports: '' + url: https://git.math.uzh.ch/reinhard.furrer/spam + url_cran: https://CRAN.R-project.org/package=spam64 + url_git: '' +spaMM: + version: 4.5.0 + title: Mixed-Effect Models, with or without Spatial Random Effects + maintainer: François Rousset + description: Inference based on models with or without spatially-correlated random + effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). + Variation in residual variance (heteroscedasticity) can itself be represented + by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy + 2014 ), and Markov random field models on irregular grids + (as considered in the 'INLA' package, ), can be fitted, + with distinct computational procedures exploiting the sparse matrix representations + for the latter case and other autoregressive models. Laplace approximations are + used for likelihood or restricted likelihood. Penalized quasi-likelihood and + other variants discussed in the h-likelihood literature (Lee and Nelder 2001 ) + are also implemented. + date_publication: '2024-06-09' + bug_reports: '' + url: https://gitlab.mbb.univ-montp2.fr/francois/spamm-ref + url_cran: https://CRAN.R-project.org/package=spaMM + url_git: '' +spanish: + version: 0.4.2 + title: |- + Translate Quantities from Strings to Integer and Back. Misc + Functions on Spanish Data + maintainer: Jose Manuel Vera Oteo + description: |- + Character vector to numerical translation in Euros from Spanish + spelled monetary quantities. Reverse translation from integer to Spanish. + Upper limit is up to the millions range. Geocoding via Cadastral web site. + date_publication: '2019-05-10' + bug_reports: https://github.com/verajosemanuel/spanish/issues + url: https://ropenspain.github.io/spanish/ + url_cran: https://CRAN.R-project.org/package=spanish + url_git: '' +spanishoddata: + version: 0.1.0 + title: Get Spanish Origin-Destination Data + maintainer: Egor Kotov + description: |- + Gain seamless access to origin-destination (OD) data from the + Spanish Ministry of Transport, hosted at + . + This package simplifies the management of these large datasets by + providing tools to download zone boundaries, handle associated + origin-destination data, and process it efficiently with the 'duckdb' + database interface. Local caching minimizes repeated downloads, + streamlining workflows for researchers and analysts. Extensive + documentation is available at + , offering + guides on creating static and dynamic mobility flow visualizations and + transforming large datasets into analysis-ready formats. + date_publication: '2024-12-18' + bug_reports: https://github.com/rOpenSpain/spanishoddata/issues + url: https://rOpenSpain.github.io/spanishoddata/ + url_cran: https://CRAN.R-project.org/package=spanishoddata + url_git: https://github.com/rOpenSpain/spanishoddata +spANOVA: + version: 0.99.4 + title: Analysis of Field Trials with Geostatistics & Spatial AR Models + maintainer: Castro L. R. + description: 'Perform analysis of variance when the experimental units are spatially + correlated. There are two methods to deal with spatial dependence: Spatial autoregressive + models (see Rossoni, D. F., & Lima, R. R. (2019) ) + and geostatistics (see Pontes, J. M., & Oliveira, M. S. D. (2004) ). + For both methods, there are three multicomparison procedure available: Tukey, + multivariate T, and Scott-Knott.' + date_publication: '2024-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spANOVA + url_git: '' +spant: + version: 3.2.0 + title: MR Spectroscopy Analysis Tools + maintainer: Martin Wilson + description: |- + Tools for reading, visualising and processing Magnetic Resonance + Spectroscopy data. The package includes methods for spectral fitting: Wilson + (2021) and spectral alignment: Wilson (2018) + . + date_publication: '2025-02-14' + bug_reports: https://github.com/martin3141/spant/issues/ + url: https://spantdoc.wilsonlab.co.uk/ + url_cran: https://CRAN.R-project.org/package=spant + url_git: https://github.com/martin3141/spant/ +sparcl: + version: 1.0.4 + title: |- + Perform Sparse Hierarchical Clustering and Sparse K-Means + Clustering + maintainer: Daniela Witten + description: |- + Implements the sparse clustering methods of Witten and + Tibshirani (2010): "A framework for feature selection in + clustering"; published in Journal of the American Statistical + Association 105(490): 713-726. + date_publication: '2018-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparcl + url_git: '' +spark.sas7bdat: + version: '1.4' + title: Read in 'SAS' Data ('.sas7bdat' Files) into 'Apache Spark' + maintainer: Jan Wijffels + description: Read in 'SAS' Data ('.sas7bdat' Files) into 'Apache Spark' from R. + 'Apache Spark' is an open source cluster computing framework available at . + This R package uses the 'spark-sas7bdat' 'Spark' package () + to import and process 'SAS' data in parallel using 'Spark'. Hereby allowing to + execute 'dplyr' statements in parallel on top of 'SAS' data. + date_publication: '2021-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spark.sas7bdat + url_git: https://github.com/bnosac/spark.sas7bdat +sparkavro: + version: 0.3.0 + title: Load Avro file into 'Apache Spark' + maintainer: Aki Ariga + description: |- + Load Avro Files into 'Apache Spark' using 'sparklyr'. This + allows to read files from 'Apache Avro' . + date_publication: '2020-01-10' + bug_reports: https://github.com/chezou/sparkavro + url: '' + url_cran: https://CRAN.R-project.org/package=sparkavro + url_git: '' +sparkbq: + version: 0.1.1 + title: Google 'BigQuery' Support for 'sparklyr' + maintainer: Martin Studer + description: |- + A 'sparklyr' extension package providing an integration with Google 'BigQuery'. + It supports direct import/export where records are directly streamed from/to 'BigQuery'. + In addition, data may be imported/exported via intermediate data extracts on Google 'Cloud Storage'. + date_publication: '2019-12-18' + bug_reports: https://github.com/miraisolutions/sparkbq/issues + url: http://www.mirai-solutions.com + url_cran: https://CRAN.R-project.org/package=sparkbq + url_git: https://github.com/miraisolutions/sparkbq +sparkhail: + version: 0.1.1 + title: A 'Sparklyr' Extension for 'Hail' + maintainer: Samuel Macêdo + description: |- + 'Hail' is an open-source, general-purpose, 'python' based data analysis + tool with additional data types and methods for working with genomic data, see + . 'Hail' is built to scale and has first-class support for + multi-dimensional structured data, like the genomic data in a genome-wide + association study (GWAS). 'Hail' is exposed as a 'python' library, using primitives + for distributed queries and linear algebra implemented in 'scala', 'spark', and + increasingly 'C++'. The 'sparkhail' is an R extension using 'sparklyr' package. + The idea is to help R users to use 'hail' functionalities with the well-know + 'tidyverse' syntax, see . + date_publication: '2019-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparkhail + url_git: '' +sparkline: + version: '2.0' + title: '''jQuery'' Sparkline ''htmlwidget''' + maintainer: Ramnath Vaidyanathan + description: |- + Include interactive sparkline charts + in + all R contexts with the convenience of 'htmlwidgets'. + date_publication: '2016-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparkline + url_git: '' +sparklyr: + version: 1.8.6 + title: R Interface to Apache Spark + maintainer: Edgar Ruiz + description: |- + R interface to Apache Spark, a fast and general + engine for big data processing, see . This + package supports connecting to local and remote Apache Spark clusters, + provides a 'dplyr' compatible back-end, and provides an interface to + Spark's built-in machine learning algorithms. + date_publication: '2024-04-29' + bug_reports: https://github.com/sparklyr/sparklyr/issues + url: https://spark.posit.co/ + url_cran: https://CRAN.R-project.org/package=sparklyr + url_git: '' +sparklyr.flint: + version: 0.2.2 + title: Sparklyr Extension for 'Flint' + maintainer: Edgar Ruiz + description: |- + This sparklyr extension makes 'Flint' time series + library functionalities () easily + accessible through R. + date_publication: '2022-01-11' + bug_reports: https://github.com/r-spark/sparklyr.flint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparklyr.flint + url_git: +sparklyr.nested: + version: 0.0.4 + title: A 'sparklyr' Extension for Nested Data + maintainer: Matt Pollock + description: A 'sparklyr' extension adding the capability to work easily with nested + data. + date_publication: '2023-02-20' + bug_reports: https://github.com/mitre/sparklyr.nested/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparklyr.nested + url_git: '' +sparktex: + version: '0.1' + title: Generate LaTeX sparklines in R + maintainer: Thomas Leeper + description: |- + Generate syntax for use with the sparklines package for + LaTeX. + date_publication: '2013-06-10' + bug_reports: '' + url: http://thomasleeper.com/software.html + url_cran: https://CRAN.R-project.org/package=sparktex + url_git: '' +sparktf: + version: 0.1.0 + title: Interface for 'TensorFlow' 'TFRecord' Files with 'Apache Spark' + maintainer: Kevin Kuo + description: |- + A 'sparklyr' extension that enables reading and writing 'TensorFlow' + TFRecord files via 'Apache Spark'. + date_publication: '2019-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparktf + url_git: '' +sparkwarc: + version: 0.1.6 + title: Load WARC Files into Apache Spark + maintainer: Edgar Ruiz + description: |- + Load WARC (Web ARChive) files into Apache Spark using 'sparklyr'. This + allows to read files from the Common Crawl project . + date_publication: '2022-01-11' + bug_reports: https://github.com/r-spark/sparkwarc + url: '' + url_cran: https://CRAN.R-project.org/package=sparkwarc + url_git: '' +sparkxgb: + version: 0.2.0 + title: Interface for 'XGBoost' on 'Apache Spark' + maintainer: Edgar Ruiz + description: |- + A 'sparklyr' extension that provides an R + interface for 'XGBoost' on 'Apache Spark'. + 'XGBoost' is an optimized distributed gradient boosting library. + date_publication: '2024-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparkxgb + url_git: '' +sparr: + version: 2.3-15 + title: Spatial and Spatiotemporal Relative Risk + maintainer: Tilman M. Davies + description: 'Provides functions to estimate kernel-smoothed spatial and spatio-temporal + densities and relative risk functions, and perform subsequent inference. Methodological + details can be found in the accompanying tutorial: Davies et al. (2018) .' + date_publication: '2024-07-07' + bug_reports: https://github.com/tilmandavies/sparr/issues/ + url: https://tilmandavies.github.io/sparr/ + url_cran: https://CRAN.R-project.org/package=sparr + url_git: https://github.com/tilmandavies/sparr/ +SPARRAfairness: + version: 0.0.0.2 + title: |- + Analysis of Differential Behaviour of SPARRA Score Across + Demographic Groups + maintainer: James Liley + description: The SPARRA risk score (Scottish Patients At Risk of admission and Re-Admission) + estimates yearly risk of emergency hospital admission using electronic health + records on a monthly basis for most of the Scottish population. This package implements + a suite of functions used to analyse the behaviour and performance of the score, + focusing particularly on differential performance over demographically-defined + groups. It includes useful utility functions to plot receiver-operator-characteristic, + precision-recall and calibration curves, draw stock human figures, estimate counterfactual + quantities without the need to re-compute risk scores, to simulate a semi-realistic + dataset. + date_publication: '2024-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPARRAfairness + url_git: '' +sparrpowR: + version: 0.2.8 + title: Power Analysis to Detect Spatial Relative Risk Clusters + maintainer: Ian D. Buller + description: |- + Calculate the statistical power to detect clusters using kernel-based + spatial relative risk functions that are estimated using the 'sparr' package. + Details about the 'sparr' package methods can be found in the tutorial: Davies + et al. (2018) . Details about kernel density estimation + can be found in J. F. Bithell (1990) . More + information about relative risk functions using kernel density estimation can + be found in J. F. Bithell (1991) . + date_publication: '2024-01-23' + bug_reports: https://github.com/machiela-lab/sparrpowR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparrpowR + url_git: https://github.com/machiela-lab/sparrpowR +sparseBC: + version: '1.2' + title: Sparse Biclustering of Transposable Data + maintainer: Kean Ming Tan + description: Implements the sparse biclustering proposal of Tan and Witten (2014), + Sparse biclustering of transposable data. Journal of Computational and Graphical + Statistics 23(4):985-1008. + date_publication: '2019-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseBC + url_git: '' +SparseBiplots: + version: 4.0.1 + title: |- + 'HJ-Biplot' using Different Ways of Penalization Plotting with + 'ggplot2' + maintainer: Mitzi Isabel Cubilla-Montilla + description: '''HJ-Biplot'' is a multivariate method that allow represent multivariate + data on a subspace of low dimension, in such a way that most of the variability + of the information is captured in a few dimensions. This package implements three + new techniques and constructs in each case the ''HJ-Biplot'', adapting restrictions + to reduce weights and / or produce zero weights in the dimensions, based on the + regularization theories. It implements three methods of regularization: Ridge, + LASSO and Elastic Net.' + date_publication: '2021-10-24' + bug_reports: https://github.com/mitzicubillamontilla/SparseBiplots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SparseBiplots + url_git: https://github.com/mitzicubillamontilla/SparseBiplots +SparseChol: + version: 0.3.2 + title: |- + Sparse Matrix C++ Classes Including Sparse Cholesky LDL + Decomposition of Symmetric Matrices + maintainer: Sam Watson + description: |- + 'C++' classes for sparse matrix methods including implementation of sparse LDL decomposition of symmetric matrices and solvers described by Timothy A. Davis (2016) + . Provides a set of C++ classes for basic sparse + matrix specification and linear algebra, and a class to implement sparse LDL decomposition and solvers. See + for details. + date_publication: '2024-12-08' + bug_reports: https://github.com/samuel-watson/SparseChol/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SparseChol + url_git: https://github.com/samuel-watson/SparseChol +sparseCov: + version: 0.0.1 + title: Sparse Covariance Estimation Based on Thresholding + maintainer: Chenxin Jiang + description: A sparse covariance estimator based on different thresholding operators. + date_publication: '2024-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseCov + url_git: https://github.com/chexjiang/sparseCov +SparseDC: + version: 0.1.17 + title: Implementation of SparseDC Algorithm + maintainer: Jun Li + description: |- + Implements the algorithm described in + Barron, M., Zhang, S. and Li, J. 2017, "A sparse differential + clustering algorithm for tracing cell type changes via single-cell + RNA-sequencing data", Nucleic Acids Research, gkx1113, + . This algorithm clusters samples from two + different populations, links the clusters across the conditions and + identifies marker genes for these changes. The package was designed for + scRNA-Seq data but is also applicable to many other data types, just + replace cells with samples and genes with variables. The package also + contains functions for estimating the parameters for SparseDC as outlined + in the paper. We recommend that users further select their marker genes + using the magnitude of the cluster centers. + date_publication: '2018-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SparseDC + url_git: '' +sparseDFM: + version: '1.0' + title: Estimate Dynamic Factor Models with Sparse Loadings + maintainer: Alex Gibberd + description: Implementation of various estimation methods for dynamic factor models + (DFMs) including principal components analysis (PCA) Stock and Watson (2002) , + 2Stage Giannone et al. (2008) , expectation-maximisation + (EM) Banbura and Modugno (2014) , and the novel EM-sparse + approach for sparse DFMs Mosley et al. (2023) . Options to use + classic multivariate Kalman filter and smoother (KFS) equations from Shumway and + Stoffer (1982) or fast univariate KFS + equations from Koopman and Durbin (2000) , and options + for independent and identically distributed (IID) white noise or auto-regressive + (AR(1)) idiosyncratic errors. Algorithms coded in 'C++' and linked to R via 'RcppArmadillo'. + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseDFM + url_git: '' +sparsediscrim: + version: 0.3.0 + title: Sparse and Regularized Discriminant Analysis + maintainer: Max Kuhn + description: |- + A collection of sparse and regularized discriminant analysis + methods intended for small-sample, high-dimensional data sets. The package + features the High-Dimensional Regularized Discriminant Analysis classifier + from Ramey et al. (2017) . Other classifiers include + those from Dudoit et al. (2002) , Pang et + al. (2009) , and Tong et al. (2012) + . + date_publication: '2021-07-01' + bug_reports: '' + url: https://topepo.github.io/sparsediscrim/ + url_cran: https://CRAN.R-project.org/package=sparsediscrim + url_git: https://github.com/topepo/sparsediscrim +sparseEigen: + version: 0.1.0 + title: Computation of Sparse Eigenvectors of a Matrix + maintainer: Daniel P. Palomar + description: |- + Computation of sparse eigenvectors of a matrix (aka sparse PCA) + with running time 2-3 orders of magnitude lower than existing methods and + better final performance in terms of recovery of sparsity pattern and + estimation of numerical values. Can handle covariance matrices as well as + data matrices with real or complex-valued entries. Different levels of + sparsity can be specified for each individual ordered eigenvector and the + method is robust in parameter selection. See vignette for a detailed + documentation and comparison, with several illustrative examples. + The package is based on the paper: + K. Benidis, Y. Sun, P. Babu, and D. P. Palomar (2016). "Orthogonal Sparse PCA + and Covariance Estimation via Procrustes Reformulation," IEEE Transactions on + Signal Processing . + date_publication: '2017-12-20' + bug_reports: https://github.com/dppalomar/sparseEigen/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=sparseEigen + url_git: https://github.com/dppalomar/sparseEigen +sparseFLMM: + version: 0.4.1 + title: |- + Functional Linear Mixed Models for Irregularly or Sparsely + Sampled Data + maintainer: Jona Cederbaum + description: |- + Estimation of functional linear mixed models for irregularly or + sparsely sampled data based on functional principal component analysis. + date_publication: '2021-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseFLMM + url_git: '' +SparseFunClust: + version: 1.0.0 + title: Sparse Functional Clustering + maintainer: Waldir Leoncio + description: |- + Provides a general framework for performing sparse functional + clustering as originally described in Floriello and Vitelli (2017) + , with the possibility of jointly handling + data misalignment (see Vitelli, 2019, ). + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SparseFunClust + url_git: '' +sparsegl: + version: 1.1.1 + title: Sparse Group Lasso + maintainer: Daniel J. McDonald + description: |- + Efficient implementation of sparse group lasso with optional + bound constraints on the coefficients; see + . It supports the use of a sparse design + matrix as well as returning coefficient estimates in a sparse matrix. + Furthermore, it correctly calculates the degrees of freedom to allow + for information criteria rather than cross-validation with very large + data. Finally, the interface to compiled code avoids unnecessary + copies and allows for the use of long integers. + date_publication: '2024-08-24' + bug_reports: https://github.com/dajmcdon/sparsegl/issues + url: https://dajmcdon.github.io/sparsegl/ + url_cran: https://CRAN.R-project.org/package=sparsegl + url_git: https://github.com/dajmcdon/sparsegl +SparseGrid: + version: 0.8.2 + title: Sparse grid integration in R + maintainer: Jelmer Ypma + description: SparseGrid is a package to create sparse grids for numerical integration, + based on code from www.sparse-grids.de + date_publication: '2013-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SparseGrid + url_git: '' +sparseHessianFD: + version: 0.3.3.7 + title: Numerical Estimation of Sparse Hessians + maintainer: Michael Braun + description: |- + Estimates Hessian of a scalar-valued function, and returns it + in a sparse Matrix format. The sparsity pattern must be known in advance. The + algorithm is especially efficient for hierarchical models with a large number of + heterogeneous units. See Braun, M. (2017) . + date_publication: '2022-10-19' + bug_reports: https://github.com/braunm/sparseHessianFD/issues/ + url: https://braunm.github.io/sparseHessianFD/ + url_cran: https://CRAN.R-project.org/package=sparseHessianFD + url_git: https://github.com/braunm/sparseHessianFD/ +SparseICA: + version: 0.1.4 + title: Sparse Independent Component Analysis + maintainer: Zihang Wang + description: Provides an implementation of the Sparse ICA method in Wang et al. + (2024) for estimating sparse independent source + components of cortical surface functional MRI data, by addressing a non-smooth, + non-convex optimization problem through the relax-and-split framework. This method + effectively balances statistical independence and sparsity while maintaining computational + efficiency. + date_publication: '2025-01-29' + bug_reports: https://github.com/thebrisklab/SparseICA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SparseICA + url_git: https://github.com/thebrisklab/SparseICA +sparseIndexTracking: + version: 0.1.1 + title: Design of Portfolio of Stocks to Track an Index + maintainer: Daniel P. Palomar + description: |- + Computation of sparse portfolios for financial index tracking, i.e., joint + selection of a subset of the assets that compose the index and computation + of their relative weights (capital allocation). The level of sparsity of the + portfolios, i.e., the number of selected assets, is controlled through a + regularization parameter. Different tracking measures are available, namely, + the empirical tracking error (ETE), downside risk (DR), Huber empirical + tracking error (HETE), and Huber downside risk (HDR). See vignette for a + detailed documentation and comparison, with several illustrative examples. + The package is based on the paper: + K. Benidis, Y. Feng, and D. P. Palomar, "Sparse Portfolios for High-Dimensional + Financial Index Tracking," IEEE Trans. on Signal Processing, vol. 66, no. 1, + pp. 155-170, Jan. 2018. . + date_publication: '2019-06-02' + bug_reports: https://github.com/dppalomar/sparseIndexTracking/issues + url: https://www.danielppalomar.com + url_cran: https://CRAN.R-project.org/package=sparseIndexTracking + url_git: https://github.com/dppalomar/sparseIndexTracking +sparseinv: + version: 0.1.3 + title: Computation of the Sparse Inverse Subset + maintainer: Andrew Zammit-Mangion + description: |- + Creates a wrapper for the 'SuiteSparse' routines + that execute the Takahashi equations. These equations compute the + elements of the inverse of a sparse matrix at locations where the + its Cholesky factor is structurally non-zero. The resulting matrix is known as a + sparse inverse subset. Some helper functions are also implemented. + Support for spam matrices is currently limited and will be implemented + in the future. See Rue and Martino (2007) + and Zammit-Mangion and Rougier (2018) for the + application of these equations to statistics. + date_publication: '2018-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseinv + url_git: '' +sparseLDA: + version: 0.1-9 + title: Sparse Discriminant Analysis + maintainer: Max Kuhn + description: Performs sparse linear discriminant analysis for Gaussians and mixture + of Gaussian models. + date_publication: '2016-09-22' + bug_reports: '' + url: http://www.imm.dtu.dk/~lhc + url_cran: https://CRAN.R-project.org/package=sparseLDA + url_git: https://github.com/topepo/sparselda +SparseLPM: + version: '1.0' + title: |- + The Sparse Latent Position Model for Nonnegative Interaction + Data + maintainer: Riccardo Rastelli + description: Models the nonnegative entries of a rectangular adjacency matrix using + a sparse latent position model, as illustrated in Rastelli, R. (2018) "The Sparse + Latent Position Model for nonnegative weighted networks" . + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SparseLPM + url_git: '' +sparseLRMatrix: + version: 0.1.0 + title: Represent and Use Sparse + Low Rank Matrices + maintainer: Alex Hayes + description: |- + Provides an S4 class for representing and + interacting with sparse plus rank matrices. At the moment the + implementation is quite spare, but the plan is eventually subclass + Matrix objects. + date_publication: '2021-03-02' + bug_reports: https://github.com/RoheLab/sparseLRMatrix/issues + url: https://rohelab.github.io/sparseLRMatrix/ + url_cran: https://CRAN.R-project.org/package=sparseLRMatrix + url_git: https://github.com/RoheLab/sparseLRMatrix +sparseLTSEigen: + version: 0.2.0.1 + title: RcppEigen back end for sparse least trimmed squares regression + maintainer: Andreas Alfons + description: |- + Use RcppEigen to fit least trimmed squares + regression models with an L1 penalty in order to obtain + sparse models. + date_publication: '2020-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseLTSEigen + url_git: '' +SparseM: + version: 1.84-2 + title: Sparse Linear Algebra + maintainer: Roger Koenker + description: |- + Some basic linear algebra functionality for sparse matrices is + provided: including Cholesky decomposition and backsolving as well as + standard R subsetting and Kronecker products. + date_publication: '2024-07-17' + bug_reports: '' + url: http://www.econ.uiuc.edu/~roger/research/sparse/sparse.html + url_cran: https://CRAN.R-project.org/package=SparseM + url_git: '' +sparseMatEst: + version: 1.0.0 + title: Sparse Matrix Estimation and Inference + maintainer: Adam B Kashlak + description: |- + The 'sparseMatEst' package provides functions for estimating sparse + covariance and precision matrices with error control. A false positive + rate is fixed corresponding to the probability of falsely including a matrix + entry in the support of the estimator. It uses the binary search + method outlined in Kashlak and Kong (2019) and in + Kashlak (2019) . + date_publication: '2019-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseMatEst + url_git: '' +SparseMDC: + version: 0.99.5 + title: Implementation of SparseMDC Algorithm + maintainer: Jun Li + description: |- + Implements the algorithm described in + Barron, M., and Li, J. (Not yet published). This algorithm clusters + samples from multiple ordered populations, links the clusters across the + conditions and identifies marker genes for these changes. The package was + designed for scRNA-Seq data but is also applicable to many other data + types, just replace cells with samples and genes with variables. The + package also contains functions for estimating the parameters for SparseMDC + as outlined in the paper. We recommend that users further select their + marker genes using the magnitude of the cluster centers. + date_publication: '2018-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SparseMDC + url_git: '' +SPARSEMODr: + version: 1.2.0 + title: SPAtial Resolution-SEnsitive Models of Outbreak Dynamics + maintainer: Joseph Mihaljevic + description: Implementation of spatially-explicit, stochastic disease models with + customizable time windows that describe how parameter values fluctuate during + outbreaks (e.g., in response to public health or conservation interventions). + date_publication: '2022-07-19' + bug_reports: https://github.com/NAU-CCL/SPARSEMODr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SPARSEMODr + url_git: https://github.com/NAU-CCL/SPARSEMODr +SparseMSE: + version: 2.0.1 + title: '''Multiple Systems Estimation for Sparse Capture Data''' + maintainer: Lax Chan + description: 'Implements the routines and algorithms developed and analysed in "Multiple + Systems Estimation for Sparse Capture Data: Inferential Challenges when there + are Non-Overlapping Lists" Chan, L, Silverman, B. W., Vincent, K (2019) . + This package explicitly handles situations where there are pairs of lists which + have no observed individuals in common. It deals correctly with parameters whose + estimated values can be considered as being negative infinity. It also addresses + other possible issues of non-existence and non-identifiability of maximum likelihood + estimates.' + date_publication: '2019-12-15' + bug_reports: '' + url: https://arxiv.org/abs/1902.05156 + url_cran: https://CRAN.R-project.org/package=SparseMSE + url_git: '' +sparseMVN: + version: 0.2.2 + title: |- + Multivariate Normal Functions for Sparse Covariance and + Precision Matrices + maintainer: Michael Braun + description: |- + Computes multivariate normal (MVN) densities, and + samples from MVN distributions, when the covariance or + precision matrix is sparse. + date_publication: '2021-10-25' + bug_reports: https://github.com/braunm/sparseMVN/issues/ + url: https://braunm.github.io/sparseMVN/ + url_cran: https://CRAN.R-project.org/package=sparseMVN + url_git: https://github.com/braunm/sparseMVN/ +sparsenet: + version: '1.7' + title: Fit Sparse Linear Regression Models via Nonconvex Optimization + maintainer: Trevor Hastie + description: 'Efficient procedure for fitting regularization paths between L1 and + L0, using the MC+ penalty of Zhang, C.H. (2010). Implements + the methodology described in Mazumder, Friedman and Hastie (2011) . + Sparsenet computes the regularization surface over both the family parameter and + the tuning parameter by coordinate descent.' + date_publication: '2024-11-16' + bug_reports: '' + url: https://hastie.su.domains/public/Papers/Sparsenet/Mazumder-SparseNetCoordinateDescent-2011.pdf + url_cran: https://CRAN.R-project.org/package=sparsenet + url_git: '' +sparsepca: + version: 0.1.2 + title: Sparse Principal Component Analysis (SPCA) + maintainer: N. Benjamin Erichson + description: Sparse principal component analysis (SPCA) attempts to find sparse + weight vectors (loadings), i.e., a weight vector with only a few 'active' (nonzero) + values. This approach provides better interpretability for the principal components + in high-dimensional data settings. This is, because the principal components are + formed as a linear combination of only a few of the original variables. This package + provides efficient routines to compute SPCA. Specifically, a variable projection + solver is used to compute the sparse solution. In addition, a fast randomized + accelerated SPCA routine and a robust SPCA routine is provided. Robust SPCA allows + to capture grossly corrupted entries in the data. The methods are discussed in + detail by N. Benjamin Erichson et al. (2018) . + date_publication: '2018-04-11' + bug_reports: https://github.com/erichson/spca/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparsepca + url_git: https://github.com/erichson/spca +sparsepp: + version: '1.22' + title: '''Rcpp'' Interface to ''sparsepp''' + maintainer: Dmitriy Selivanov + description: |- + Provides interface to 'sparsepp' - fast, memory efficient hash map. + It is derived from Google's excellent 'sparsehash' implementation. + We believe 'sparsepp' provides an unparalleled combination of performance and memory usage, + and will outperform your compiler's unordered_map on both counts. + Only Google's 'dense_hash_map' is consistently faster, at the cost of much greater + memory usage (especially when the final size of the map is not known in advance). + date_publication: '2018-09-22' + bug_reports: https://github.com/dselivanov/r-sparsepp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparsepp + url_git: https://github.com/greg7mdp/sparsepp +sparseR: + version: 0.3.1 + title: |- + Variable Selection under Ranked Sparsity Principles for + Interactions and Polynomials + maintainer: Ryan Andrew Peterson + description: |- + An implementation of ranked sparsity methods, including + penalized regression methods such as the sparsity-ranked lasso, its + non-convex alternatives, and elastic net, as well as the sparsity-ranked + Bayesian Information Criterion. As described in Peterson and + Cavanaugh (2022) , ranked + sparsity is a philosophy with methods primarily useful for + variable selection in the presence of prior informational + asymmetry, which occurs in the context of trying to perform variable + selection in the presence of interactions and/or polynomials. Ultimately, + this package attempts to facilitate dealing with cumbersome interactions + and polynomials while not avoiding them entirely. Typically, models + selected under ranked sparsity principles will also be more transparent, + having fewer falsely selected interactions and polynomials than other + methods. + date_publication: '2024-07-17' + bug_reports: '' + url: https://petersonr.github.io/sparseR/ + url_cran: https://CRAN.R-project.org/package=sparseR + url_git: https://github.com/petersonR/sparseR/ +sparsereg: + version: '1.2' + title: |- + Sparse Bayesian Models for Regression, Subgroup Analysis, and + Panel Data + maintainer: Marc Ratkovic + description: 'Sparse modeling provides a mean selecting a small number of non-zero + effects from a large possible number of candidate effects. This package includes + a suite of methods for sparse modeling: estimation via EM or MCMC, approximate + confidence intervals with nominal coverage, and diagnostic and summary plots. The + method can implement sparse linear regression and sparse probit regression. Beyond + regression analyses, applications include subgroup analysis, particularly for + conjoint experiments, and panel data. Future versions will include extensions + to models with truncated outcomes, propensity score, and instrumental variable + analysis.' + date_publication: '2016-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparsereg + url_git: '' +sparseSEM: + version: '4.1' + title: |- + Elastic Net Penalized Maximum Likelihood for Structural Equation + Models with Network GPT Framework + maintainer: Anhui Huang + description: 'Provides elastic net penalized maximum likelihood estimator for structural + equation models (SEM). The package implements `lasso` and `elastic net` (l1/l2) + penalized SEM and estimates the model parameters with an efficient block coordinate + ascent algorithm that maximizes the penalized likelihood of the SEM. Hyperparameters + are inferred from cross-validation (CV). A Stability Selection (STS) function + is also available to provide accurate causal effect selection. The software achieves + high accuracy performance through a `Network Generative Pre-trained Transformer` + (Network GPT) Framework with two steps: 1) pre-trains the model to generate a + complete (fully connected) graph; and 2) uses the complete graph as the initial + state to fit the `elastic net` penalized SEM.' + date_publication: '2024-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseSEM + url_git: '' +sparsestep: + version: 1.0.1 + title: SparseStep Regression + maintainer: Gertjan van den Burg + description: |- + Implements the SparseStep model for solving regression + problems with a sparsity constraint on the parameters. The SparseStep + regression model was proposed in Van den Burg, Groenen, and Alfons (2017) + . In the model, a regularization term is added to the + regression problem which approximates the counting norm of the parameters. + By iteratively improving the approximation a sparse solution to the + regression problem can be obtained. In this package both the standard + SparseStep algorithm is implemented as well as a path algorithm which uses + golden section search to determine solutions with different values for the + regularization parameter. + date_publication: '2021-01-10' + bug_reports: https://github.com/GjjvdBurg/SparseStep + url: https://arxiv.org/abs/1701.06967 + url_cran: https://CRAN.R-project.org/package=sparsestep + url_git: https://github.com/GjjvdBurg/SparseStep +sparsesvd: + version: 0.2-2 + title: Sparse Truncated Singular Value Decomposition (from 'SVDLIBC') + maintainer: Stephanie Evert + description: |- + Wrapper around the 'SVDLIBC' library for (truncated) singular value decomposition of a sparse matrix. + Currently, only sparse real matrices in Matrix package format are supported. + date_publication: '2023-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparsesvd + url_git: https://github.com/lucasmaystre/svdlibc +sparseSVM: + version: 1.1-7 + title: |- + Solution Paths of Sparse High-Dimensional Support Vector Machine + with Lasso or Elastic-Net Regularization + maintainer: Congrui Yi + description: 'Offers a fast algorithm for fitting solution paths of sparse SVM models + with lasso or elastic-net regularization. Reference: Congrui Yi and Jian Huang + (2017) .' + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sparseSVM + url_git: https://github.com/CY-dev/sparseSVM +SparseTSCGM: + version: '4.0' + title: Sparse Time Series Chain Graphical Models + maintainer: Fentaw Abegaz + description: "Computes sparse vector autoregressive \t\t\t\tcoefficients and precision + matrices for time series \t\tchain graphical models. Fentaw Abegaz and Ernst Wit + (2013)\t." + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SparseTSCGM + url_git: '' +sparsevb: + version: 0.1.1 + title: |- + Spike-and-Slab Variational Bayes for Linear and Logistic + Regression + maintainer: Gabriel Clara + description: Implements variational Bayesian algorithms to perform scalable variable + selection for sparse, high-dimensional linear and logistic regression models. + Features include a novel prioritized updating scheme, which uses a preliminary + estimator of the variational means during initialization to generate an updating + order prioritizing large, more relevant, coefficients. Sparsity is induced via + spike-and-slab priors with either Laplace or Gaussian slabs. By default, the heavier-tailed + Laplace density is used. Formal derivations of the algorithms and asymptotic consistency + results may be found in Kolyan Ray and Botond Szabo (JASA 2020) and Kolyan Ray, + Botond Szabo, and Gabriel Clara (NeurIPS 2020). + date_publication: '2025-01-24' + bug_reports: https://gitlab.com/gclara/varpack/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparsevb + url_git: '' +sparsevctrs: + version: 0.2.0 + title: Sparse Vectors for Use in Data Frames + maintainer: Emil Hvitfeldt + description: |- + Provides sparse vectors powered by ALTREP (Alternative + Representations for R Objects) that behave like regular vectors, and + can thus be used in data frames. Also provides tools to convert + between sparse matrices and data frames with sparse columns and + functions to interact with sparse vectors. + date_publication: '2025-01-22' + bug_reports: https://github.com/r-lib/sparsevctrs/issues + url: https://r-lib.github.io/sparsevctrs/ + url_cran: https://CRAN.R-project.org/package=sparsevctrs + url_git: https://github.com/r-lib/sparsevctrs +SparseVFC: + version: 0.1.2 + title: Sparse Vector Field Consensus for Vector Field Learning + maintainer: Jingmeng Cui + description: |- + The sparse vector field consensus + (SparseVFC) algorithm (Ma et al., 2013 ) for robust vector + field learning. Largely translated from the Matlab functions in . + date_publication: '2023-11-09' + bug_reports: https://github.com/Sciurus365/SparseVFC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SparseVFC + url_git: https://github.com/Sciurus365/SparseVFC +sparsio: + version: 1.0.1 + title: I/O Operations with Sparse Matrices + maintainer: Dmitriy Selivanov + description: |- + Fast 'SVMlight' reader and writer. + 'SVMlight' is most commonly used format for storing + sparse matrices (possibly with some target variable) on disk. + For additional information about 'SVMlight' format see . + date_publication: '2020-01-13' + bug_reports: https://github.com/dselivanov/sparsio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparsio + url_git: https://github.com/dselivanov/sparsio +sparta: + version: 1.0.1 + title: Sparse Tables + maintainer: Mads Lindskou + description: Fast Multiplication and Marginalization of Sparse Tables . + date_publication: '2024-11-22' + bug_reports: https://github.com/mlindsk/sparta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sparta + url_git: https://github.com/mlindsk/sparta +SPARTAAS: + version: 1.2.4 + title: |- + Statistical Pattern Recognition and daTing using Archaeological + Artefacts assemblageS + maintainer: Arthur Coulon + description: |- + Statistical pattern recognition and dating using archaeological artefacts assemblages. + Package of statistical tools for archaeology. + hclustcompro()/perioclust(): Bellanger Lise, Coulon Arthur, Husi Philippe (2021, ISBN:978-3-030-60103-4). + mapclust(): Bellanger Lise, Coulon Arthur, Husi Philippe (2021) . + seriograph(): Desachy Bruno (2004) . + cerardat(): Bellanger Lise, Husi Philippe (2012) . + date_publication: '2024-06-27' + bug_reports: '' + url: https://spartaas.gitpages.huma-num.fr/r-package/ + url_cran: https://CRAN.R-project.org/package=SPARTAAS + url_git: '' +sparvaride: + version: 0.1.0 + title: Variance Identification in Sparse Factor Analysis + maintainer: Darjus Hosszejni + description: This is an implementation of the algorithm described in Section 3 of + Hosszejni and Frühwirth-Schnatter (2022) . The + algorithm is used to verify that the counting rule CR(r,1) holds for the sparsity + pattern of the transpose of a factor loading matrix. As detailed in Section 2 + of the same paper, if CR(r,1) holds, then the idiosyncratic variances are generically + identified. If CR(r,1) does not hold, then we do not know whether the idiosyncratic + variances are identified or not. + date_publication: '2023-03-13' + bug_reports: https://github.com/hdarjus/sparvaride/issues + url: https://hdarjus.github.io/sparvaride/ + url_cran: https://CRAN.R-project.org/package=sparvaride + url_git: '' +SPAS: + version: 2025.2.1 + title: Stratified-Petersen Analysis System + maintainer: Carl James Schwarz + description: |- + The Stratified-Petersen Analysis System (SPAS) is designed + to estimate abundance in two-sample capture-recapture experiments + where the capture and recaptures are stratified. This is a generalization + of the simple Lincoln-Petersen estimator. + Strata may be defined in time or in space or both, + and the s strata in which marking takes place + may differ from the t strata in which recoveries take place. + When s=t, SPAS reduces to the method described by + Darroch (1961) . + When s. + Schwarz and Taylor (1998) describe + the use of SPAS in estimating return of salmon stratified by + time and geography. + A related package, BTSPAS, deals with temporal stratification where + a spline is used to model the distribution of the population + over time as it passes the second capture location. + This is the R-version of the (now obsolete) standalone Windows + program of the same name. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPAS + url_git: '' +spass: + version: '1.3' + title: Study Planning and Adaptation of Sample Size + maintainer: Marius Placzek + description: Sample size estimation and blinded sample size reestimation in Adaptive + Study Design. + date_publication: '2020-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spass + url_git: '' +spate: + version: 1.7.5 + title: |- + Spatio-Temporal Modeling of Large Data Using a Spectral SPDE + Approach + maintainer: Fabio Sigrist + description: Functionality for spatio-temporal modeling of large data sets is provided. + A Gaussian process in space and time is defined through a stochastic partial differential + equation (SPDE). The SPDE is solved in the spectral space, and after discretizing + in time and space, a linear Gaussian state space model is obtained. When doing + inference, the main computational difficulty consists in evaluating the likelihood + and in sampling from the full conditional of the spectral coefficients, or equivalently, + the latent space-time process. In comparison to the traditional approach of using + a spatio-temporal covariance function, the spectral SPDE approach is computationally + advantageous. See Sigrist, Kuensch, and Stahel (2015) + for more information on the methodology. This package aims at providing tools + for two different modeling approaches. First, the SPDE based spatio-temporal model + can be used as a component in a customized hierarchical Bayesian model (HBM). + The functions of the package then provide parameterizations of the process part + of the model as well as computationally efficient algorithms needed for doing + inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented + in the package can be used as an algorithm for doing inference without any additional + modeling. The MCMC algorithm supports data that follow a Gaussian or a censored + distribution with point mass at zero. Covariates can be included in the model + through a regression term. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spate + url_git: '' +SpatEntropy: + version: 2.2-4 + title: Spatial Entropy Measures + maintainer: Altieri Linda + description: The heterogeneity of spatial data presenting a finite number of categories + can be measured via computation of spatial entropy. Functions are available for + the computation of the main entropy and spatial entropy measures in the literature. + They include the traditional version of Shannon's entropy (Shannon, 1948 ), + Batty's spatial entropy (Batty, 1974 ), + O'Neill's entropy (O'Neill et al., 1998 ), Li and Reynolds' + contagion index (Li and Reynolds, 1993 ), Karlstrom and + Ceccato's entropy (Karlstrom and Ceccato, 2002 ), + Leibovici's entropy (Leibovici, 2009 ), Parresol + and Edwards' entropy (Parresol and Edwards, 2014 ) and + Altieri's entropy (Altieri et al., 2018, ). Full + references for all measures can be found under the topic 'SpatEntropy'. The package + is able to work with lattice and point data. The updated version works with the + updated 'spatstat' package (>= 3.0-2). + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatEntropy + url_git: '' +SPAtest: + version: 3.1.2 + title: Score Test and Meta-Analysis Based on Saddlepoint Approximation + maintainer: Rounak Dey + description: Performs score test using saddlepoint approximation to estimate the + null distribution. Also prepares summary statistics for meta-analysis and performs + meta-analysis to combine multiple association results. For the latest version, + please check . + date_publication: '2020-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPAtest + url_git: '' +SpatFD: + version: 0.0.1 + title: |- + Functional Geostatistics: Univariate and Multivariate Functional + Spatial Prediction + maintainer: Martha Patricia Bohorquez Castañeda + description: Performance of functional kriging, cokriging, optimal sampling and + simulation for spatial prediction of functional data. The framework of spatial + prediction, optimal sampling and simulation are extended from scalar to functional + data. 'SpatFD' is based on the Karhunen-Loève expansion that allows to represent + the observed functions in terms of its empirical functional principal components. + Based on this approach, the functional auto-covariances and cross-covariances + required for spatial functional predictions and optimal sampling, are completely + determined by the sum of the spatial auto-covariances and cross-covariances of + the respective score components. The package provides new classes of data and + functions for modeling spatial dependence structure among curves. The spatial + prediction of curves at unsampled locations can be carried out using two types + of predictors, and both of them report, the respective variances of the prediction + error. In addition, there is a function for the determination of spatial locations + sampling configuration that ensures minimum variance of spatial functional prediction. + There are also two functions for plotting predicted curves at each location and + mapping the surface at each time point, respectively. References Bohorquez, M., + Giraldo, R., and Mateu, J. (2016) , Bohorquez, + M., Giraldo, R., and Mateu, J. (2016) , Bohorquez + M., Giraldo R. and Mateu J. (2021) . + date_publication: '2024-06-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatFD + url_git: '' +SpatGC: + version: 0.1.0 + title: Bayesian Modeling of Spatial Count Data + maintainer: Mahsa Nadifar + description: Provides a collection of functions for preparing data and fitting Bayesian + count spatial regression models, with a specific focus on the Gamma-Count (GC) + model. The GC model is well-suited for modeling dispersed count data, including + under-dispersed or over-dispersed counts, or counts with equivalent dispersion, + using Integrated Nested Laplace Approximations (INLA). The package includes functions + for generating data from the GC model, as well as spatially correlated versions + of the model. See Nadifar, Baghishani, Fallah (2023) . + date_publication: '2024-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatGC + url_git: https://github.com/mahsanst/SpatGC +spatgeom: + version: 0.3.0 + title: Geometric Spatial Point Analysis + maintainer: Maikol Solís + description: The implementation to perform the geometric spatial point analysis + developed in Hernández & Solís (2022) . It estimates + the geometric goodness-of-fit index for a set of variables against a response + one based on the 'sf' package. The package has methods to print and plot the results. + date_publication: '2023-04-26' + bug_reports: https://github.com/maikol-solis/spatgeom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spatgeom + url_git: https://github.com/maikol-solis/spatgeom +spatgraphs: + version: '3.4' + title: Graph Edge Computations for Spatial Point Patterns + maintainer: Tuomas Rajala + description: |- + Graphs (or networks) and graph component + calculations for spatial locations in 1D, 2D, 3D etc. + date_publication: '2023-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatgraphs + url_git: '' +SpatGRID: + version: 0.1.0 + title: Spatial Grid Generation from Longitude and Latitude List + maintainer: Nobin Chandra Paul + description: |- + The developed function is designed for the generation of spatial grids based on user-specified longitude and latitude coordinates. The function first validates the input longitude and latitude values, + ensuring they fall within the appropriate geographic ranges. It then creates a polygon from the coordinates and determines the appropriate Universal Transverse Mercator zone based on the provided + hemisphere and longitude values. Subsequently, transforming the input Shapefile to the Universal Transverse Mercator projection when necessary. Finally, a spatial grid is generated with the specified interval and saved as a Shapefile. + For method details see, Brus,D.J.(2022).. The function takes into account crucial parameters such as the hemisphere (north or south), desired grid interval, and the output Shapefile path. + The developed function is an efficient tool, simplifying the process of empty spatial grid generation for applications such as, geo-statistical analysis, digital soil mapping product generation, etc. Whether for environmental studies, + urban planning, or any other geo-spatial analysis, this package caters to the diverse needs of users working with spatial data, enhancing the accessibility and ease of spatial data processing and visualization. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatGRID + url_git: '' +spaths: + version: 1.1.3 + title: Shortest Paths Between Points in Grids + maintainer: Christian Düben + description: |- + Shortest paths between points in grids. Optional barriers and custom transition functions. Applications regarding planet Earth, as well as + generally spheres and planes. Optimized for computational performance, customizability, and user friendliness. Graph-theoretical implementation tailored + to gridded data. Currently focused on Dijkstra's (1959) algorithm. Future updates broaden the scope to other least cost path + algorithms and to centrality measures. + date_publication: '2024-07-11' + bug_reports: https://github.com/cdueben/spaths/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spaths + url_git: https://github.com/cdueben/spaths +spatial: + version: 7.3-18 + title: Functions for Kriging and Point Pattern Analysis + maintainer: Brian Ripley + description: Functions for kriging and point pattern analysis. + date_publication: '2025-01-01' + bug_reports: '' + url: http://www.stats.ox.ac.uk/pub/MASS4/ + url_cran: https://CRAN.R-project.org/package=spatial + url_git: '' +SpatialAcc: + version: 0.1-5 + title: Spatial Accessibility Measures + maintainer: Stamatis Kalogirou + description: |- + Provides a set of spatial accessibility measures from a set of locations + (demand) to another set of locations (supply). It aims, among others, + to support research on spatial accessibility to health care facilities. + Includes the locations and some characteristics of major public hospitals in Greece. + date_publication: '2024-04-02' + bug_reports: '' + url: https://stamatisgeoai.eu/ + url_cran: https://CRAN.R-project.org/package=SpatialAcc + url_git: '' +SpatialBSS: + version: 0.14-0 + title: Blind Source Separation for Multivariate Spatial Data + maintainer: Klaus Nordhausen + description: Blind source separation for multivariate spatial data based on simultaneous/joint + diagonalization of (robust) local covariance matrices. This package is an implementation + of the methods described in Bachoc, Genton, Nordhausen, Ruiz-Gazen and Virta (2020) + . + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialBSS + url_git: '' +spatialCovariance: + version: 0.6-9 + title: |- + Computation of Spatial Covariance Matrices for Data on + Rectangles + maintainer: David Clifford + description: Functions that compute the spatial covariance matrix for the matern + and power classes of spatial models, for data that arise on rectangular units. This + code can also be used for the change of support problem and for spatial data that + arise on irregularly shaped regions like counties or zipcodes by laying a fine + grid of rectangles and aggregating the integrals in a form of Riemann integration. + date_publication: '2015-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatialCovariance + url_git: '' +SpatialDDLS: + version: 1.0.3 + title: |- + Deconvolution of Spatial Transcriptomics Data Based on Neural + Networks + maintainer: Diego Mañanes + description: Deconvolution of spatial transcriptomics data based on neural networks + and single-cell RNA-seq data. SpatialDDLS implements a workflow to create neural + network models able to make accurate estimates of cell composition of spots from + spatial transcriptomics data using deep learning and the meaningful information + provided by single-cell RNA-seq data. See Torroja and Sanchez-Cabo (2019) + and Mañanes et al. (2024) to get an overview + of the method and see some examples of its performance. + date_publication: '2024-10-31' + bug_reports: https://github.com/diegommcc/SpatialDDLS/issues + url: https://diegommcc.github.io/SpatialDDLS/ + url_cran: https://CRAN.R-project.org/package=SpatialDDLS + url_git: https://github.com/diegommcc/SpatialDDLS +spatialEco: + version: 2.0-2 + title: Spatial Analysis and Modelling Utilities + maintainer: Jeffrey S. Evans + description: |- + Utilities to support spatial data manipulation, query, sampling + and modelling in ecological applications. Functions include models for species + population density, spatial smoothing, multivariate separability, point process + model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and + analysis, auto-logistic modeling, sampling models, cluster optimization, statistical + exploratory tools and raster-based metrics. + date_publication: '2023-11-17' + bug_reports: https://github.com/jeffreyevans/spatialEco/issues + url: https://jeffreyevans.github.io/spatialEco/ + url_cran: https://CRAN.R-project.org/package=spatialEco + url_git: https://github.com/jeffreyevans/spatialEco +SpatialEpi: + version: 1.2.8 + title: Methods and Data for Spatial Epidemiology + maintainer: Albert Y. Kim + description: Methods and data for cluster detection and disease mapping. + date_publication: '2023-02-22' + bug_reports: https://github.com/rudeboybert/SpatialEpi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialEpi + url_git: https://github.com/rudeboybert/SpatialEpi +SpatialExtremes: + version: 2.1-0 + title: Modelling Spatial Extremes + maintainer: Mathieu Ribatet + description: 'Tools for the statistical modelling of spatial extremes using max-stable + processes, copula or Bayesian hierarchical models. More precisely, this package + allows (conditional) simulations from various parametric max-stable models, analysis + of the extremal spatial dependence, the fitting of such processes using composite + likelihoods or least square (simple max-stable processes only), model checking + and selection and prediction. Other approaches (although not completely in agreement + with the extreme value theory) are available such as the use of (spatial) copula + and Bayesian hierarchical models assuming the so-called conditional assumptions. + The latter approaches is handled through an (efficient) Gibbs sampler. Some key + references: Davison et al. (2012) , Padoan et al. (2010) + , Dombry et al. (2013) .' + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialExtremes + url_git: http://spatialextremes.r-forge.r-project.org/ +SpatialfdaR: + version: 1.0.0 + title: Spatial Functional Data Analysis + maintainer: James Ramsay + description: |2- + + Finite element modeling (FEM) uses meshes of triangles to define surfaces. + A surface within a triangle may be either linear or quadratic. + In the order one case each node in the mesh is associated with a basis + function and the basis is called the order one finite element basis. + In the order two case each edge mid-point is also associated with a basis + function. Functions are provided for smoothing, density function estimation + point evaluation and plotting results. Two papers illustrating the + finite element data analysis are Sangalli, L.M., Ramsay, J.O., + Ramsay, T.O. (2013) and + Bernardi, M.S, Carey, M., Ramsay, J. O., Sangalli, L. + (2018). Modelling + spatial anisotropy via regression with partial differential + regularization Journal of Multivariate Analysis, 167, 15-30. + date_publication: '2022-10-11' + bug_reports: '' + url: http://www.functionaldata.org + url_cran: https://CRAN.R-project.org/package=SpatialfdaR + url_git: '' +SpatialGEV: + version: 1.0.1 + title: Fit Spatial Generalized Extreme Value Models + maintainer: Meixi Chen + description: Fit latent variable models with the GEV distribution as the data likelihood + and the GEV parameters following latent Gaussian processes. The models in this + package are built using the template model builder 'TMB' in R, which has the fast + ability to integrate out the latent variables using Laplace approximation. This + package allows the users to choose in the fit function which GEV parameter(s) + is considered as a spatially varying random effect following a Gaussian process, + so the users can fit spatial GEV models with different complexities to their dataset + without having to write the models in 'TMB' by themselves. This package also offers + methods to sample from both fixed and random effects posteriors as well as the + posterior predictive distributions at different spatial locations. Methods for + fitting this class of models are described in Chen, Ramezan, and Lysy (2024) . + date_publication: '2024-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialGEV + url_git: '' +SpatialGraph: + version: 1.0-4 + title: The SpatialGraph Class and Utilities + maintainer: Javier Garcia-Pintado + description: Provision of the S4 SpatialGraph class built on top of objects provided + by 'igraph' and 'sp' packages, and associated utilities. See the documentation + of the SpatialGraph-class within this package for further description. An example + of how from a few points one can arrive to a SpatialGraph is provided in the function + sl2sg(). + date_publication: '2023-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialGraph + url_git: https://github.com/garciapintado/SpatialGraph +spatialising: + version: 0.6.0 + title: Ising Model for Spatial Data + maintainer: Jakub Nowosad + description: |- + Performs simulations of binary spatial raster data using + the Ising model (Ising (1925) ; + Onsager (1944) ). It allows to set a few + parameters that represent internal and external pressures, and the number + of simulations (Stepinski and Nowosad (2023) ). + date_publication: '2023-11-27' + bug_reports: https://github.com/Nowosad/spatialising/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spatialising + url_git: https://github.com/Nowosad/spatialising +SpatialKDE: + version: 0.8.2 + title: Kernel Density Estimation for Spatial Data + maintainer: Jan Caha + description: |- + Calculate Kernel Density Estimation (KDE) for spatial data. + The algorithm is inspired by the tool 'Heatmap' from 'QGIS'. The method is described by: + Hart, T., Zandbergen, P. (2014) , + Nelson, T. A., Boots, B. (2008) , + Chainey, S., Tompson, L., Uhlig, S.(2008) . + date_publication: '2023-02-18' + bug_reports: '' + url: https://jancaha.github.io/SpatialKDE/index.html + url_cran: https://CRAN.R-project.org/package=SpatialKDE + url_git: https://github.com/JanCaha/SpatialKDE +SpatialKWD: + version: 0.4.1 + title: Spatial KWD for Large Spatial Maps + maintainer: Stefano Gualandi + description: 'Contains efficient implementations of Discrete Optimal Transport algorithms + for the computation of Kantorovich-Wasserstein distances between pairs of large + spatial maps (Bassetti, Gualandi, Veneroni (2020), ). + All the algorithms are based on an ad-hoc implementation of the Network Simplex + algorithm. The package has four main helper functions: compareOneToOne() (to compare + two spatial maps), compareOneToMany() (to compare a reference map with a list + of other maps), compareAll() (to compute a matrix of distances between a list + of maps), and focusArea() (to compute the KWD distance within a focus area). In + non-convex maps, the helper functions first build the convex-hull of the input + bins and pad the weights with zeros.' + date_publication: '2022-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialKWD + url_git: '' +SpatialML: + version: 0.1.7 + title: Spatial Machine Learning + maintainer: Stamatis Kalogirou + description: |- + Implements a spatial extension of the random forest algorithm + (Georganos et al. (2019) ). + Allows for a geographically weighted random forest regression + including a function to find the optical bandwidth. (Georganos + and Kalogirou (2022) ). + date_publication: '2024-04-02' + bug_reports: '' + url: https://stamatisgeoai.eu/ + url_cran: https://CRAN.R-project.org/package=SpatialML + url_git: '' +SpatialNP: + version: 1.1-5 + title: |- + Multivariate Nonparametric Methods Based on Spatial Signs and + Ranks + maintainer: Klaus Nordhausen + description: Test and estimates of location, tests of independence, tests of sphericity + and several estimates of shape all based on spatial signs, symmetrized signs, + ranks and signed ranks. For details, see Oja and Randles (2004) + and Oja (2010) . + date_publication: '2021-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialNP + url_git: '' +SpatialPack: + version: 0.4-1 + title: |- + Tools for Assessment the Association Between Two Spatial + Processes + maintainer: Felipe Osorio + description: |- + Tools to assess the association between two spatial processes. Currently, + several methodologies are implemented: A modified t-test to perform hypothesis testing + about the independence between the processes, a suitable nonparametric correlation + coefficient, the codispersion coefficient, and an F test for assessing the multiple + correlation between one spatial process and several others. Functions for image + processing and computing the spatial association between images are also provided. + Functions contained in the package are intended to accompany Vallejos, R., Osorio, F., + Bevilacqua, M. (2020). Spatial Relationships Between Two Georeferenced Variables: + With Applications in R. Springer, Cham . + date_publication: '2024-09-29' + bug_reports: '' + url: http://spatialpack.mat.utfsm.cl + url_cran: https://CRAN.R-project.org/package=SpatialPack + url_git: '' +SpatialPOP: + version: 0.1.0 + title: |- + Generation of Spatial Data with Spatially Varying Model + Parameter + maintainer: Nobin Chandra Paul + description: |- + A spatial population can be generated based on spatially varying regression model under the assumption that observations are collected from a uniform two-dimensional grid consist of (m * m) lattice points with unit distance between any two neighbouring points. For method details see Chao, Liu., Chuanhua, Wei. and Yunan, Su. (2018).. This spatially generated data can be used to test different issues related to the statistical analysis of spatial data. + This generated spatial data can be utilized in geographically weighted regression analysis for studying the spatially varying relationships among the variables. + date_publication: '2022-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialPOP + url_git: '' +SpatialPosition: + version: 2.1.2 + title: Spatial Position Models + maintainer: Timothée Giraud + description: |- + Computes spatial position models: the potential model as defined + by Stewart (1941) and catchment areas as + defined by Reilly (1931) or Huff (1964) . + date_publication: '2023-09-14' + bug_reports: https://github.com/riatelab/SpatialPosition/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialPosition + url_git: https://github.com/riatelab/SpatialPosition +spatialprobit: + version: 1.0.4 + title: Spatial Probit Models + maintainer: Stefan Wilhelm + description: 'A collection of methods for the Bayesian estimation of Spatial Probit, + Spatial Ordered Probit and Spatial Tobit Models. Original implementations from + the works of ''LeSage and Pace'' (2009, ISBN: 1420064258) were ported and adjusted + for R, as described in ''Wilhelm and de Matos'' (2013) .' + date_publication: '2024-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatialprobit + url_git: '' +SpatialRDD: + version: 0.1.0 + title: |- + Conduct Multiple Types of Geographic Regression Discontinuity + Designs + maintainer: Alexander Lehner + description: Spatial versions of Regression Discontinuity Designs (RDDs) are becoming + increasingly popular as tools for causal inference. However, conducting state-of-the-art + analyses often involves tedious and time-consuming steps. This package offers + comprehensive functionalities for executing all required spatial and econometric + tasks in a streamlined manner. Moreover, it equips researchers with tools for + performing essential placebo and balancing checks comprehensively. The fact that + researchers do not have to rely on 'APIs' of external 'GIS' software ensures replicability + and raises the standard for spatial RDDs. + date_publication: '2023-08-08' + bug_reports: https://github.com/axlehner/SpatialRDD/issues + url: https://axlehner.github.io/SpatialRDD/ + url_cran: https://CRAN.R-project.org/package=SpatialRDD + url_git: '' +spatialreg: + version: 1.3-6 + title: Spatial Regression Analysis + maintainer: Roger Bivand + description: A collection of all the estimation functions for spatial cross-sectional + models (on lattice/areal data using spatial weights matrices) contained up to + now in 'spdep'. These model fitting functions include maximum likelihood methods + for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) + and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975) + . The models are further described by 'Anselin' + (1988) . Spatial two stage least squares and spatial + general method of moment models initially proposed by 'Kelejian' and 'Prucha' + (1998) and (1999) + are provided. Impact methods and MCMC fitting methods proposed by 'LeSage' and + 'Pace' (2009) are implemented for the family of cross-sectional + spatial regression models. Methods for fitting the log determinant term in maximum + likelihood and MCMC fitting are compared by 'Bivand et al.' (2013) , + and model fitting methods by 'Bivand' and 'Piras' (2015) ; + both of these articles include extensive lists of references. A recent review + is provided by 'Bivand', 'Millo' and 'Piras' (2021) . + 'spatialreg' >= 1.1-* corresponded to 'spdep' >= 1.1-1, in which the model fitting + functions were deprecated and passed through to 'spatialreg', but masked those + in 'spatialreg'. From versions 1.2-*, the functions have been made defunct in + 'spdep'. From version 1.3-6, add Anselin-Kelejian (1997) test to `stsls` for residual + spatial autocorrelation . + date_publication: '2024-12-02' + bug_reports: https://github.com/r-spatial/spatialreg/issues/ + url: https://r-spatial.github.io/spatialreg/ + url_cran: https://CRAN.R-project.org/package=spatialreg + url_git: https://github.com/r-spatial/spatialreg/ +SpatialRegimes: + version: '1.1' + title: Spatial Constrained Clusterwise Regression + maintainer: Francesco Vidoli + description: A collection of functions for estimating spatial regimes, aggregations + of neighboring spatial units that are homogeneous in functional terms. The term + spatial regime, therefore, should not be understood as a synonym for cluster. + More precisely, the term cluster does not presuppose any functional relationship + between the variables considered, while the term regime is linked to a regressive + relationship underlying the spatial process. + date_publication: '2022-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialRegimes + url_git: '' +spatialRF: + version: 1.1.4 + title: Easy Spatial Modeling with Random Forest + maintainer: Blas M. Benito + description: 'Automatic generation and selection of spatial predictors for spatial + regression with Random Forest. Spatial predictors are surrogates of variables + driving the spatial structure of a response variable. The package offers two methods + to generate spatial predictors from a distance matrix among training cases: 1) + Moran''s Eigenvector Maps (MEMs; Dray, Legendre, and Peres-Neto 2006 ): + computed as the eigenvectors of a weighted matrix of distances; 2) RFsp (Hengl + et al. ): columns of the distance matrix used as spatial + predictors. Spatial predictors help minimize the spatial autocorrelation of the + model residuals and facilitate an honest assessment of the importance scores of + the non-spatial predictors. Additionally, functions to reduce multicollinearity, + identify relevant variable interactions, tune random forest hyperparameters, assess + model transferability via spatial cross-validation, and explore model results + via partial dependence curves and interaction surfaces are included in the package. + The modelling functions are built around the highly efficient ''ranger'' package + (Wright and Ziegler 2017 ).' + date_publication: '2022-08-19' + bug_reports: https://github.com/BlasBenito/spatialRF/issues/ + url: https://blasbenito.github.io/spatialRF/ + url_cran: https://CRAN.R-project.org/package=spatialRF + url_git: '' +spatialrisk: + version: 0.7.1 + title: Calculating Spatial Risk + maintainer: Martin Haringa + description: |- + Methods for spatial risk calculations. It offers an efficient approach to determine the sum of all observations within a + circle of a certain radius. This might be beneficial for insurers who are required (by a recent European Commission regulation) to determine + the maximum value of insured fire risk policies of all buildings that are partly or fully located within a circle of a radius of 200m. See + Church (1974) for a description of the problem. + date_publication: '2024-02-21' + bug_reports: https://github.com/mharinga/spatialrisk/issues + url: https://mharinga.github.io/spatialrisk/ + url_cran: https://CRAN.R-project.org/package=spatialrisk + url_git: https://github.com/mharinga/spatialrisk +SpatialRoMLE: + version: 0.1.0 + title: Robust Maximum Likelihood Estimation for Spatial Error Model + maintainer: Vural Yildirim + description: 'Provides robust estimation for spatial error model to presence of + outliers in the residuals. The classical estimation methods can be influenced + by the presence of outliers in the data. We proposed a robust estimation approach + based on the robustified likelihood equations for spatial error model (Vural Yildirim + & Yeliz Mert Kantar (2020): Robust estimation approach for spatial error model, + Journal of Statistical Computation and Simulation, ).' + date_publication: '2020-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialRoMLE + url_git: '' +spatialsample: + version: 0.6.0 + title: Spatial Resampling Infrastructure + maintainer: Michael Mahoney + description: |- + Functions and classes for spatial resampling to use with the + 'rsample' package, such as spatial cross-validation (Brenning, 2012) + . The scope of 'rsample' and + 'spatialsample' is to provide the basic building blocks for creating + and analyzing resamples of a spatial data set, but neither package + includes functions for modeling or computing statistics. The resampled + spatial data sets created by 'spatialsample' do not contain much + overhead in memory. + date_publication: '2024-10-02' + bug_reports: https://github.com/tidymodels/spatialsample/issues + url: https://spatialsample.tidymodels.org + url_cran: https://CRAN.R-project.org/package=spatialsample + url_git: https://github.com/tidymodels/spatialsample +spatialTIME: + version: 1.3.4-5 + title: Spatial Analysis of Vectra Immunoflourescent Data + maintainer: Fridley Lab + description: |- + Visualization and analysis of Vectra Immunoflourescent + data. Options for calculating both the univariate and bivariate Ripley's K + are included. Calculations are performed using a permutation-based + approach presented by Wilson et al. . + date_publication: '2024-06-04' + bug_reports: https://github.com/FridleyLab/spatialTIME/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spatialTIME + url_git: https://github.com/FridleyLab/spatialTIME +SpatialTools: + version: 1.0.5 + title: Tools for Spatial Data Analysis + maintainer: Joshua French + description: Tools for spatial data analysis. Emphasis on kriging. Provides functions + for prediction and simulation. Intended to be relatively straightforward, fast, + and flexible. + date_publication: '2023-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialTools + url_git: '' +SpatialVS: + version: '1.1' + title: Spatial Variable Selection + maintainer: Yili Hong + description: Perform variable selection for the spatial Poisson regression model + under the adaptive elastic net penalty. Spatial count data with covariates is + the input. We use a spatial Poisson regression model to link the spatial counts + and covariates. For maximization of the likelihood under adaptive elastic net + penalty, we implemented the penalized quasi-likelihood (PQL) and the approximate + penalized loglikelihood (APL) methods. The proposed methods can automatically + select important covariates, while adjusting for possible spatial correlations + among the responses. More details are available in Xie et al. (2018, ). + The package also contains the Lyme disease dataset, which consists of the disease + case data from 2006 to 2011, and demographic data and land cover data in Virginia. + The Lyme disease case data were collected by the Virginia Department of Health. + The demographic data (e.g., population density, median income, and average age) + are from the 2010 census. Land cover data were obtained from the Multi-Resolution + Land Cover Consortium for 2006. + date_publication: '2018-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialVS + url_git: '' +SpatialVx: + version: 1.0-3 + title: Spatial Forecast Verification + maintainer: Eric Gilleland + description: 'Spatial forecast verification refers to verifying weather forecasts + when the verification set (forecast and observations) is on a spatial field, usually + a high-resolution gridded spatial field. Most of the functions here require the + forecast and observed fields to be gridded and on the same grid. For a thorough + review of most of the methods in this package, please see Gilleland et al. (2009) + and for a tutorial on some of the main functions + available here, see Gilleland (2022) .' + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpatialVx + url_git: '' +spatialwarnings: + version: 3.1.0 + title: Spatial Early Warning Signals of Ecosystem Degradation + maintainer: Alexandre Genin + description: Tools to compute and assess significance of early-warnings signals + (EWS) of ecosystem degradation on raster data sets. EWS are spatial metrics derived + from raster data -- e.g. spatial autocorrelation -- that increase before an ecosystem + undergoes a non-linear transition (Genin et al. (2018) ). + date_publication: '2024-09-06' + bug_reports: https://github.com/spatial-ews/spatialwarnings/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spatialwarnings + url_git: https://github.com/spatial-ews/spatialwarnings +spatialwidget: + version: 0.2.5 + title: Formats Spatial Data for Use in Htmlwidgets + maintainer: David Cooley + description: |- + Many packages use 'htmlwidgets' + for interactive plotting of spatial data. + This package provides functions for converting R objects, such as simple features, + into structures suitable for use in 'htmlwidgets' mapping libraries. + date_publication: '2024-01-22' + bug_reports: '' + url: https://symbolixau.github.io/spatialwidget/articles/spatialwidget.html + url_cran: https://CRAN.R-project.org/package=spatialwidget + url_git: '' +SpatMCA: + version: 1.0.4 + title: Regularized Spatial Maximum Covariance Analysis + maintainer: Wen-Ting Wang + description: |- + Provide regularized maximum covariance analysis incorporating smoothness, + sparseness and orthogonality of couple patterns by using the alternating direction method + of multipliers algorithm. The method can be applied to either regularly or irregularly + spaced data, including 1D, 2D, and 3D (Wang and Huang, 2017 ). + date_publication: '2023-11-21' + bug_reports: https://github.com/egpivo/SpatMCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpatMCA + url_git: https://github.com/egpivo/SpatMCA +SpaTopic: + version: 1.1.0 + title: |- + Topic Inference to Identify Tissue Architecture in Multiplexed + Images + maintainer: Xiyu Peng + description: A novel spatial topic model to integrate both cell type and spatial + information to identify the complex spatial tissue architecture on multiplexed + tissue images without human intervention. The Package implements a collapsed Gibbs + sampling algorithm for inference. 'SpaTopic' is scalable to large-scale image + datasets without extracting neighborhood information for every single cell. For + more details on the methodology, see . + date_publication: '2024-04-22' + bug_reports: https://github.com/xiyupeng/SpaTopic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpaTopic + url_git: https://github.com/xiyupeng/SpaTopic +SpatPCA: + version: 1.3.5 + title: Regularized Principal Component Analysis for Spatial Data + maintainer: Wen-Ting Wang + description: |- + Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigen-functions + by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, ). The + method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D. + date_publication: '2023-11-13' + bug_reports: https://github.com/egpivo/SpatPCA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpatPCA + url_git: https://github.com/egpivo/SpatPCA +spatPomp: + version: 1.0.0 + title: Inference for Spatiotemporal Partially Observed Markov Processes + maintainer: Edward Ionides + description: Inference on panel data using spatiotemporal partially-observed Markov + process (SpatPOMP) models. The 'spatPomp' package extends 'pomp' to include algorithms + taking advantage of the spatial structure in order to assist with handling high + dimensional processes. See Asfaw et al. (2024) + for further description of the package. + date_publication: '2024-11-14' + bug_reports: https://github.com/spatPomp-org/spatPomp/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=spatPomp + url_git: https://github.com/spatPomp-org/spatPomp +SpATS: + version: 1.0-19 + title: Spatial Analysis of Field Trials with Splines + maintainer: Maria Xose Rodriguez-Alvarez + description: Analysis of field trial experiments by modelling spatial trends using + two-dimensional Penalised spline (P-spline) models. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpATS + url_git: '' +spatsoc: + version: 0.2.2 + title: |- + Group Animal Relocation Data by Spatial and Temporal + Relationship + maintainer: Alec L. Robitaille + description: |- + Detects spatial and temporal groups in GPS relocations + (Robitaille et al. (2019) ). It can be + used to convert GPS relocations to gambit-of-the-group format to build + proximity-based social networks In addition, the randomizations + function provides data-stream randomization methods suitable for GPS + data. + date_publication: '2023-09-07' + bug_reports: https://github.com/ropensci/spatsoc/issues + url: https://docs.ropensci.org/spatsoc/ + url_cran: https://CRAN.R-project.org/package=spatsoc + url_git: https://github.com/ropensci/spatsoc +spatstat: + version: 3.3-1 + title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests + maintainer: Adrian Baddeley + description: |- + Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. + Contains over 3000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. + Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. + Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. + Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. + A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. + Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. + date_publication: '2025-01-23' + bug_reports: https://github.com/spatstat/spatstat/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat + url_git: '' +spatstat.data: + version: 3.1-4 + title: Datasets for 'spatstat' Family + maintainer: Adrian Baddeley + description: Contains all the datasets for the 'spatstat' family of packages. + date_publication: '2024-11-15' + bug_reports: https://github.com/spatstat/spatstat.data/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.data + url_git: '' +spatstat.explore: + version: 3.3-4 + title: Exploratory Data Analysis for the 'spatstat' Family + maintainer: Adrian Baddeley + description: |- + Functionality for exploratory data analysis and nonparametric analysis of + spatial data, mainly spatial point patterns, + in the 'spatstat' family of packages. + (Excludes analysis of spatial data on a linear network, + which is covered by the separate package 'spatstat.linnet'.) + Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. + date_publication: '2025-01-08' + bug_reports: https://github.com/spatstat/spatstat.explore/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.explore + url_git: '' +spatstat.geom: + version: 3.3-5 + title: Geometrical Functionality of the 'spatstat' Family + maintainer: Adrian Baddeley + description: |- + Defines spatial data types and supports geometrical operations + on them. Data types include point patterns, windows (domains), + pixel images, line segment patterns, tessellations and hyperframes. + Capabilities include creation and manipulation of data + (using command line or graphical interaction), + plotting, geometrical operations (rotation, shift, rescale, + affine transformation), convex hull, discretisation and + pixellation, Dirichlet tessellation, Delaunay triangulation, + pairwise distances, nearest-neighbour distances, + distance transform, morphological operations + (erosion, dilation, closing, opening), quadrat counting, + geometrical measurement, geometrical covariance, + colour maps, calculus on spatial domains, + Gaussian blur, level sets of images, transects of images, + intersections between objects, minimum distance matching. + (Excludes spatial data on a network, which are supported by + the package 'spatstat.linnet'.) + date_publication: '2025-01-18' + bug_reports: https://github.com/spatstat/spatstat.geom/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.geom + url_git: '' +spatstat.gui: + version: 3.1-0 + title: Interactive Graphics Functions for the 'spatstat' Package + maintainer: Adrian Baddeley + description: |- + Extension to the 'spatstat' package, containing + interactive graphics capabilities. + date_publication: '2024-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatstat.gui + url_git: '' +spatstat.Knet: + version: 3.1-2 + title: Extension to 'spatstat' for Large Datasets on a Linear Network + maintainer: Adrian Baddeley + description: |- + Extension to the 'spatstat' family of packages, for analysing + large datasets of spatial points on a network. The geometrically- + corrected K function is computed using a memory-efficient + tree-based algorithm described by Rakshit, Baddeley and Nair (2019). + date_publication: '2024-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatstat.Knet + url_git: '' +spatstat.linnet: + version: 3.2-5 + title: Linear Networks Functionality of the 'spatstat' Family + maintainer: Adrian Baddeley + description: |- + Defines types of spatial data on a linear network + and provides functionality for geometrical operations, + data analysis and modelling of data on a linear network, + in the 'spatstat' family of packages. + Contains definitions and support for linear networks, including creation of networks, geometrical measurements, topological connectivity, geometrical operations such as inserting and deleting vertices, intersecting a network with another object, and interactive editing of networks. + Data types defined on a network include point patterns, pixel images, functions, and tessellations. + Exploratory methods include kernel estimation of intensity on a network, K-functions and pair correlation functions on a network, simulation envelopes, nearest neighbour distance and empty space distance, relative risk estimation with cross-validated bandwidth selection. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. + Parametric models can be fitted to point pattern data using the function lppm() similar to glm(). Only Poisson models are implemented so far. Models may involve dependence on covariates and dependence on marks. Models are fitted by maximum likelihood. + Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. + Random point patterns on a network can be generated using a variety of models. + date_publication: '2025-01-22' + bug_reports: https://github.com/spatstat/spatstat.linnet/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.linnet + url_git: '' +spatstat.local: + version: 5.1-0 + title: Extension to 'spatstat' for Local Composite Likelihood + maintainer: Adrian Baddeley + description: |- + Extension to the 'spatstat' package, enabling the user + to fit point process models to point pattern data + by local composite likelihood ('geographically weighted + regression'). + date_publication: '2024-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatstat.local + url_git: '' +spatstat.model: + version: 3.3-4 + title: |- + Parametric Statistical Modelling and Inference for the + 'spatstat' Family + maintainer: Adrian Baddeley + description: |- + Functionality for parametric statistical modelling and inference for spatial data, + mainly spatial point patterns, in the 'spatstat' family of packages. + (Excludes analysis of spatial data on a linear network, + which is covered by the separate package 'spatstat.linnet'.) + Supports parametric modelling, formal statistical inference, and model validation. + Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope tests, Dao-Genton test, balanced independent two-stage test), confidence intervals for parameters, and prediction intervals for point counts. Model validation techniques include leverage, influence, partial residuals, added variable plots, diagnostic plots, pseudoscore residual plots, model compensators and Q-Q plots. + date_publication: '2025-01-20' + bug_reports: https://github.com/spatstat/spatstat.model/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.model + url_git: '' +spatstat.random: + version: 3.3-2 + title: Random Generation Functionality for the 'spatstat' Family + maintainer: Adrian Baddeley + description: |- + Functionality for random generation of spatial data in the 'spatstat' family of packages. + Generates random spatial patterns of points according to many simple rules (complete spatial randomness, + Poisson, binomial, random grid, systematic, cell), randomised alteration of patterns + (thinning, random shift, jittering), simulated realisations of random point processes including + simple sequential inhibition, Matern inhibition models, Neyman-Scott cluster processes + (using direct, Brix-Kendall, or hybrid algorithms), + log-Gaussian Cox processes, product shot noise cluster processes + and Gibbs point processes (using Metropolis-Hastings birth-death-shift algorithm, + alternating Gibbs sampler, or coupling-from-the-past perfect simulation). + Also generates random spatial patterns of line segments, + random tessellations, and random images (random noise, random mosaics). + Excludes random generation on a linear network, + which is covered by the separate package 'spatstat.linnet'. + date_publication: '2024-09-18' + bug_reports: https://github.com/spatstat/spatstat.random/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.random + url_git: '' +spatstat.sparse: + version: 3.1-0 + title: Sparse Three-Dimensional Arrays and Linear Algebra Utilities + maintainer: Adrian Baddeley + description: |- + Defines sparse three-dimensional arrays + and supports standard operations on them. + The package also includes utility functions for + matrix calculations that are common in + statistics, such as quadratic forms. + date_publication: '2024-06-21' + bug_reports: https://github.com/spatstat/spatstat.sparse/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.sparse + url_git: '' +spatstat.univar: + version: 3.1-1 + title: |- + One-Dimensional Probability Distribution Support for the + 'spatstat' Family + maintainer: Adrian Baddeley + description: |- + Estimation of one-dimensional probability distributions + including kernel density estimation, weighted empirical cumulative + distribution functions, Kaplan-Meier and reduced-sample estimators + for right-censored data, heat kernels, kernel properties, + quantiles and integration. + date_publication: '2024-11-05' + bug_reports: https://github.com/spatstat/spatstat.univar/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.univar + url_git: '' +spatstat.utils: + version: 3.1-2 + title: Utility Functions for 'spatstat' + maintainer: Adrian Baddeley + description: |- + Contains utility functions for the 'spatstat' family of packages + which may also be useful for other purposes. + date_publication: '2025-01-08' + bug_reports: https://github.com/spatstat/spatstat.utils/issues + url: http://spatstat.org/ + url_cran: https://CRAN.R-project.org/package=spatstat.utils + url_git: '' +spatsurv: + version: 2.0-1 + title: |- + Bayesian Spatial Survival Analysis with Parametric Proportional + Hazards Models + maintainer: Benjamin M. Taylor + description: |- + Bayesian inference for parametric proportional hazards spatial + survival models; flexible spatial survival models. See Benjamin M. Taylor, Barry S. Rowlingson (2017) . + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spatsurv + url_git: '' +SPB: + version: '1.0' + title: Simple Progress Bars for Procedural Coding + maintainer: Fabio Ashtar Telarico + description: Provides a simple progress bar to use for basic and advanced users + that suits all those who prefer procedural programming. It is especially useful + for integration into markdown files thanks to the progress bar's customisable + appearance. + date_publication: '2022-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPB + url_git: '' +spbabel: + version: 0.6.0 + title: Convert Spatial Data Using Tidy Tables + maintainer: Michael D. Sumner + description: |- + Tools to convert from specific formats to more general forms of + spatial data. Using tables to store the actual entities present in spatial + data provides flexibility, and the functions here deliberately + minimize the level of interpretation applied, leaving that for specific + applications. Includes support for simple features, round-trip for 'Spatial' classes and long-form + tables, analogous to 'ggplot2::fortify'. There is also a more 'normal form' representation + that decomposes simple features and their kin to tables of objects, parts, and unique coordinates. + date_publication: '2023-03-12' + bug_reports: https://github.com/mdsumner/spbabel/issues + url: https://mdsumner.github.io/spbabel/ + url_cran: https://CRAN.R-project.org/package=spbabel + url_git: '' +spbal: + version: 1.0.0 + title: Spatially Balanced Sampling Algorithms + maintainer: Phil Davies + description: |- + Encapsulates a number of spatially balanced sampling algorithms, + namely, Balanced Acceptance Sampling (equal, unequal, seed point, panels), Halton frames + (for discretizing a continuous resource), Halton Iterative Partitioning (equal probability) + and Simple Random Sampling. + Robertson, B. L., Brown, J. A., McDonald, T. and Jaksons, P. (2013) . + Robertson, B. L., McDonald, T., Price, C. J. and Brown, J. A. (2017) . + Robertson, B. L., McDonald, T., Price, C. J. and Brown, J. A. (2018) . + Robertson, B. L., van Dam-Bates, P. and Gansell, O. (2021a) . + date_publication: '2024-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spbal + url_git: '' +spBayes: + version: 0.4-8 + title: Univariate and Multivariate Spatial-Temporal Modeling + maintainer: Andrew Finley + description: |- + Fits univariate and multivariate spatio-temporal + random effects models for point-referenced data using Markov chain Monte Carlo (MCMC). Details are given in Finley, Banerjee, and Gelfand (2015) and Finley and Banerjee . + date_publication: '2024-09-23' + bug_reports: '' + url: https://www.finley-lab.com + url_cran: https://CRAN.R-project.org/package=spBayes + url_git: '' +spBayesSurv: + version: 1.1.8 + title: |- + Bayesian Modeling and Analysis of Spatially Correlated Survival + Data + maintainer: Haiming Zhou + description: 'Provides several Bayesian survival models for spatial/non-spatial + survival data: proportional hazards (PH), accelerated failure time (AFT), proportional + odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, + PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), + generalized accelerated failure time (GAFT), and spatially smoothed Polya tree + density estimation. The spatial dependence is modeled via frailties under PH, + AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried + out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information + criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou, + Hanson and Zhang (2020) .' + date_publication: '2024-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spBayesSurv + url_git: '' +spBFA: + version: '1.3' + title: Spatial Bayesian Factor Analysis + maintainer: Samuel I. Berchuck + description: |- + Implements a spatial Bayesian non-parametric factor analysis model + with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC). + Spatial correlation is introduced in the columns of the factor loadings + matrix using a Bayesian non-parametric prior, the probit stick-breaking + process. Areal spatial data is modeled using a conditional autoregressive + (CAR) prior and point-referenced spatial data is treated using a Gaussian + process. The response variable can be modeled as Gaussian, probit, Tobit, or + Binomial (using Polya-Gamma augmentation). Temporal correlation is + introduced for the latent factors through a hierarchical structure and can + be specified as exponential or first-order autoregressive. Full details of + the package can be found in the accompanying vignette. Furthermore, the + details of the package can be found in "Bayesian Non-Parametric Factor + Analysis for Longitudinal Spatial Surfaces", by Berchuck et al (2019), + . The paper is in press at the journal Bayesian Analysis. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spBFA + url_git: '' +spBPS: + version: 0.0-4 + title: |- + Bayesian Predictive Stacking for Scalable Geospatial Transfer + Learning + maintainer: Luca Presicce + description: 'Provides functions for Bayesian Predictive Stacking within the Bayesian + transfer learning framework for geospatial artificial systems, as introduced in + "Bayesian Transfer Learning for Artificially Intelligent Geospatial Systems: A + Predictive Stacking Approach" (Presicce and Banerjee, 2024) . + This methodology enables efficient Bayesian geostatistical modeling, utilizing + predictive stacking to improve inference across spatial datasets. The core functions + leverage ''C++'' for high-performance computation, making the framework well-suited + for large-scale spatial data analysis in parallel and distributed computing environments. + Designed for scalability, it allows seamless application in computationally demanding + scenarios.' + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spBPS + url_git: '' +Spbsampling: + version: 1.3.5 + title: Spatially Balanced Sampling + maintainer: Francesco Pantalone + description: Selection of spatially balanced samples. In particular, the implemented + sampling designs allow to select probability samples well spread over the population + of interest, in any dimension and using any distance function (e.g. Euclidean + distance, Manhattan distance). For more details, Pantalone F, Benedetti R, and + Piersimoni F (2022) , Benedetti R and Piersimoni F + (2017) , and Benedetti R and Piersimoni F (2017) . + The implementation has been done in C++ through the use of 'Rcpp' and 'RcppArmadillo'. + date_publication: '2022-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Spbsampling + url_git: '' +spc: + version: 0.7.1 + title: |- + Statistical Process Control -- Calculation of ARL and Other + Control Chart Performance Measures + maintainer: Sven Knoth + description: |- + Evaluation of control charts by means of + the zero-state, steady-state ARL (Average Run Length) and RL quantiles. + Setting up control charts for given in-control ARL. The control charts + under consideration are one- and two-sided EWMA, CUSUM, and + Shiryaev-Roberts schemes for monitoring the mean or variance of normally + distributed independent data. ARL calculation of the same set of schemes under drift (in the mean) are added. + Eventually, all ARL measures for the multivariate EWMA (MEWMA) are provided. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spc + url_git: '' +spc4sts: + version: 0.6.3 + title: Statistical Process Control for Stochastic Textured Surfaces + maintainer: Anh Tuan Bui + description: |- + Provides statistical process control tools for stochastic + textured surfaces. The current version supports the following tools: + (1) generic modeling of stochastic textured surfaces. + (2) local defect monitoring and diagnostics in stochastic + textured surfaces, which was proposed by Bui and Apley (2018a) + . + (3) global change monitoring in the nature of stochastic + textured surfaces, which was proposed by Bui and Apley (2018b) + . + (4) computation of dissimilarity matrix of stochastic textured + surface images, which was proposed by Bui and Apley (2019b) + . + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spc4sts + url_git: '' +spcadjust: + version: '1.1' + title: Functions for Calibrating Control Charts + maintainer: Axel Gandy + description: |- + Calibration of thresholds of control charts such as + CUSUM charts based on past data, taking estimation error into account. + date_publication: '2016-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spcadjust + url_git: '' +SPCALDA: + version: '1.0' + title: A New Reduced-Rank Linear Discriminant Analysis Method + maintainer: Ning Hao + description: A new reduced-rank LDA method which works for high dimensional multi-class + data. + date_publication: '2015-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPCALDA + url_git: '' +SPCAvRP: + version: '0.4' + title: |- + Sparse Principal Component Analysis via Random Projections + (SPCAvRP) + maintainer: Milana Gataric + description: Implements the SPCAvRP algorithm, developed and analysed in "Sparse + principal component analysis via random projections" Gataric, M., Wang, T. and + Samworth, R. J. (2018) . The algorithm is based on the aggregation + of eigenvector information from carefully-selected random projections of the sample + covariance matrix. + date_publication: '2019-05-03' + bug_reports: '' + url: https://arxiv.org/abs/1712.05630 + url_cran: https://CRAN.R-project.org/package=SPCAvRP + url_git: '' +SPCDAnalyze: + version: 0.1.0 + title: |- + Design and Analyze Studies using the Sequential Parallel + Comparison Design + maintainer: David A. Schoenfeld + description: |- + Programs to find the sample size or power of studies using the + Sequential Parallel Comparison Design (SPCD) and programs to analyze + such studies. This is a clinical trial design where + patients initially on placebo who did not respond are re-randomized between + placebo and active drug in a second phase and the results of the two phases are + pooled. The method of analyzing binary data with this design is described in + Fava,Evins, Dorer and Schoenfeld(2003) , and the + method of analyzing continuous data is described in Chen, Yang, + Hung and Wang (2011) . + date_publication: '2019-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPCDAnalyze + url_git: '' +SPCompute: + version: 1.0.3 + title: Compute Power or Sample Size for GWAS with Covariate Effect + maintainer: Ziang Zhang + description: |- + Fast computation of the required sample size or the + achieved power, for GWAS studies with different types of covariate + effects and different types of covariate-gene dependency structure. + For the detailed description of the methodology, see Zhang (2022) + "Power and Sample Size Computation for Genetic Association Studies + of Binary Traits: Accounting for Covariate Effects" . + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPCompute + url_git: '' +spconf: + version: 1.0.1 + title: Computing Scales of Spatial Smoothing for Confounding Adjustment + maintainer: Kayleigh Keller + description: |- + Computes the effective range of a smoothing matrix, + which is a measure of the distance to which smoothing occurs. + This is motivated by the application of spatial splines for adjusting + for unmeasured spatial confounding in regression models, but the + calculation of effective range can be applied to smoothing + matrices in other contexts. For algorithmic details, see Rainey and Keller + (2024) "spconfShiny: an R Shiny application..." + and Keller and Szpiro (2020) + "Selecting a Scale for Spatial Confounding Adjustment" . + date_publication: '2024-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spconf + url_git: '' +spcosa: + version: 0.4-2 + title: |- + Spatial Coverage Sampling and Random Sampling from Compact + Geographical Strata + maintainer: Dennis Walvoort + description: |- + Spatial coverage sampling and random sampling from compact + geographical strata created by k-means. See Walvoort et al. (2010) + for details. + date_publication: '2023-04-11' + bug_reports: '' + url: https://git.wur.nl/Walvo001/spcosa + url_cran: https://CRAN.R-project.org/package=spcosa + url_git: '' +spcov: + version: '1.3' + title: Sparse Estimation of a Covariance Matrix + maintainer: Jacob Bien + description: |- + Provides a covariance estimator for multivariate normal + data that is sparse and positive definite. Implements the + majorize-minimize algorithm described in Bien, J., and + Tibshirani, R. (2011), "Sparse Estimation of a Covariance + Matrix," Biometrika. 98(4). 807--820. + date_publication: '2022-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spcov + url_git: '' +spCP: + version: '1.3' + title: Spatially Varying Change Points + maintainer: Samuel I. Berchuck + description: |- + Implements a spatially varying change point model with + unique intercepts, slopes, variance intercepts and slopes, and + change points at each location. Inference is within the + Bayesian setting using Markov chain Monte Carlo (MCMC). The + response variable can be modeled as Gaussian (no nugget), + probit or Tobit link and the five spatially varying parameter + are modeled jointly using a multivariate conditional + autoregressive (MCAR) prior. The MCAR is a unique process that + allows for a dissimilarity metric to dictate the local spatial + dependencies. Full details of the package can be found in the accompanying vignette. + Furthermore, the details of the package can be found in the corresponding paper on arXiv + by Berchuck et al (2018): "A spatially varying change points model for monitoring glaucoma + progression using visual field data", . + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spCP + url_git: '' +spcr: + version: 2.1.1 + title: Sparse Principal Component Regression + maintainer: Shuichi Kawano + description: The sparse principal component regression is computed. The regularization + parameters are optimized by cross-validation. + date_publication: '2022-10-16' + bug_reports: '' + url: https://doi.org/10.1016/j.csda.2015.03.016 + url_cran: https://CRAN.R-project.org/package=spcr + url_git: '' +spd: + version: 2.0-1 + title: Semi Parametric Distribution + maintainer: Alexios Ghalanos + description: The Semi Parametric Piecewise Distribution blends the Generalized Pareto + Distribution for the tails with a kernel based interior. + date_publication: '2015-07-03' + bug_reports: '' + url: http://www.unstarched.net + url_cran: https://CRAN.R-project.org/package=spd + url_git: https://bitbucket.org/alexiosg +spData: + version: 2.3.4 + title: Datasets for Spatial Analysis + maintainer: Jakub Nowosad + description: |- + Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. + It includes R data of class sf (defined by the package 'sf'), Spatial ('sp'), and nb ('spdep'). + Unlike other spatial data packages such as 'rnaturalearth' and 'maps', + it also contains data stored in a range of file formats including GeoJSON and GeoPackage, but from version 2.3.4, no longer ESRI Shapefile - use GeoPackage instead. + Some of the datasets are designed to illustrate specific analysis techniques. + cycle_hire() and cycle_hire_osm(), for example, is designed to illustrate point pattern analysis techniques. + date_publication: '2025-01-08' + bug_reports: https://github.com/Nowosad/spData/issues + url: https://jakubnowosad.com/spData/ + url_cran: https://CRAN.R-project.org/package=spData + url_git: '' +spDates: + version: '1.1' + title: Analysis of Spatial Gradients in Radiocarbon Dates + maintainer: Jonas Gregorio de Souza + description: |- + Inspired by space-time regressions often performed to assess + the expansion of the Neolithic from the Near East to Europe (Pinhasi et + al. 2005 ). Test for significant + correlations between the (earliest) radiocarbon dates of archaeological + sites and their respective distances from a hypothetical center of origin. + Both ordinary least squares (OLS) and reduced major axis (RMA) methods + are supported (Russell et al. 2014 ). + It is also possible to iterate over many sites to identify the most likely + origin. + date_publication: '2022-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spDates + url_git: '' +spdep: + version: 1.3-10 + title: 'Spatial Dependence: Weighting Schemes, Statistics' + maintainer: Roger Bivand + description: |- + A collection of functions to create spatial weights matrix + objects from polygon 'contiguities', from point patterns by distance and + tessellations, for summarizing these objects, and for permitting their + use in spatial data analysis, including regional aggregation by minimum + spanning tree; a collection of tests for spatial 'autocorrelation', + including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' + (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' + general cross product statistic, Empirical Bayes estimates and + 'Assunção/Reis' (1999) Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) + and multicoloured + join count statistics, 'APLE' ('Li 'et al.' ) + , local 'Moran's I', 'Gearys C' + ('Anselin' 1995) and + 'Getis/Ord' G ('Ord' and 'Getis' 1995) + , + 'saddlepoint' approximations ('Tiefelsdorf' 2002) + and exact tests + for global and local 'Moran's I' ('Bivand et al.' 2009) + and 'LOSH' local indicators + of spatial heteroscedasticity ('Ord' and 'Getis') + . The implementation of most of + these measures is described in 'Bivand' and 'Wong' (2018) + , with further extensions in 'Bivand' (2022) + . 'Lagrange' multiplier tests for spatial dependence + in linear models are provided ('Anselin et al'. 1996) + , as are 'Rao' score tests for hypothesised + spatial 'Durbin' models based on linear models ('Koley' and 'Bera' 2023) + . A local indicators for categorical data + (LICD) implementation based on 'Carrer et al.' (2021) + and 'Bivand et al.' (2017) + was added in 1.3-7. + From 'spdep' and 'spatialreg' versions >= 1.2-1, the model fitting functions + previously present in this package are defunct in 'spdep' and may be found + in 'spatialreg'. + date_publication: '2025-01-20' + bug_reports: https://github.com/r-spatial/spdep/issues/ + url: https://r-spatial.github.io/spdep/ + url_cran: https://CRAN.R-project.org/package=spdep + url_git: https://github.com/r-spatial/spdep/ +spdesign: + version: 0.0.5 + title: Designing Stated Preference Experiments + maintainer: Erlend Dancke Sandorf + description: 'Contemporary software commonly used to design stated preference experiments + are expensive and the code is closed source. This is a free software package with + an easy to use interface to make flexible stated preference experimental designs + using state-of-the-art methods. For an overview of stated choice experimental + design theory, see e.g., Rose, J. M. & Bliemer, M. C. J. (2014) in Hess S. & Daly. + A. . The package website can be accessed at . + We acknowledge funding from the European Union’s Horizon 2020 research and innovation + program under the Marie Sklodowska-Curie grant INSPiRE (Grant agreement ID: 793163).' + date_publication: '2024-10-18' + bug_reports: '' + url: https://spdesign.edsandorf.me + url_cran: https://CRAN.R-project.org/package=spdesign + url_git: https://github.com/edsandorf/spdesign +spdl: + version: 0.0.5 + title: Easier Use of 'RcppSpdlog' Functions via Wrapper + maintainer: Dirk Eddelbuettel + description: |- + Logging functions in 'RcppSpdlog' provide access to the logging + functionality from the 'spdlog' 'C++' library. This package offers shorter convenience + wrappers for the 'R' functions which match the 'C++' functions, namely via, say, + 'spdl::debug()' at the debug level. The actual formatting is done by the + 'fmt::format()' function from the 'fmtlib' library (that is also 'std::format()' + in 'C++20' or later). + date_publication: '2023-06-18' + bug_reports: https://github.com/eddelbuettel/spdl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spdl + url_git: https://github.com/eddelbuettel/spdl +spdownscale: + version: 0.1.0 + title: Spatial Downscaling Using Bias Correction Approach + maintainer: Rasheed AM + description: Spatial downscaling of climate data (Global Circulation Models/Regional + Climate Models) using quantile-quantile bias correction technique. + date_publication: '2017-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spdownscale + url_git: '' +spduration: + version: 0.17.2 + title: Split-Population Duration (Cure) Regression + maintainer: Andreas Beger + description: |- + An implementation of split-population duration regression models. + Unlike regular duration models, split-population duration models are + mixture models that accommodate the presence of a sub-population that is + not at risk for failure, e.g. cancer patients who have been cured by + treatment. This package implements Weibull and Loglogistic forms for the + duration component, and focuses on data with time-varying covariates. + These models were originally formulated in Boag (1949) and Berkson and Gage + (1952), and extended in Schmidt and Witte (1989). + date_publication: '2024-02-08' + bug_reports: https://github.com/andybega/spduration/issues + url: https://www.andybeger.com/spduration/ + url_cran: https://CRAN.R-project.org/package=spduration + url_git: https://github.com/andybega/spduration +spdynmod: + version: 1.1.6 + title: Spatio-Dynamic Wetland Plant Communities Model + maintainer: Javier Martinez-Lopez + description: |- + A spatio-dynamic modelling package that focuses on three + characteristic wetland plant communities in a semiarid Mediterranean + wetland in response to hydrological pressures from the catchment. The + package includes the data on watershed hydrological pressure and the + initial raster maps of plant communities but also allows for random initial + distribution of plant communities. For more detailed info see: Martinez-Lopez et al. (2015) . + date_publication: '2022-02-04' + bug_reports: https://github.com/javimarlop/spdynmod/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spdynmod + url_git: https://github.com/javimarlop/spdynmod +speakeasyR: + version: 0.1.4 + title: Fast and Robust Multi-Scale Graph Clustering + maintainer: David Connell + description: |- + A graph community detection algorithm that aims to be performant + on large graphs and robust, returning consistent results across runs. + SpeakEasy 2 (SE2), the underlying algorithm, is described in Chris Gaiteri, + David R. Connell & Faraz A. Sultan et al. (2023) + . The core algorithm is written in 'C', + providing speed and keeping the memory requirements low. This implementation + can take advantage of multiple computing cores without increasing memory + usage. SE2 can detect community structure across scales, making it a good + choice for biological data, which often has hierarchical structure. Graphs + can be passed to the algorithm as adjacency matrices using base 'R' + matrices, the 'Matrix' library, 'igraph' graphs, or any data that can be + coerced into a matrix. + date_publication: '2024-09-24' + bug_reports: https://github.com/SpeakEasy-2/speakeasyR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=speakeasyR + url_git: https://github.com/SpeakEasy-2/speakeasyR +speakr: + version: 3.2.4 + title: A Wrapper for the Phonetic Software 'Praat' + maintainer: Stefano Coretta + description: |- + It allows running 'Praat' scripts from R and it provides some + wrappers for basic plotting. It also adds support for literate markdown + tangling. The package is designed to bring reproducible phonetic research + into R. + date_publication: '2024-12-07' + bug_reports: https://github.com/stefanocoretta/speakr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=speakr + url_git: https://github.com/stefanocoretta/speakr +speaq: + version: 2.7.0 + title: |- + Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, + Peak Based Processing, Quantitative Analysis and Visualizations + maintainer: Charlie Beirnaert + description: Makes Nuclear Magnetic Resonance spectroscopy (NMR spectroscopy) data + analysis as easy as possible by only requiring a small set of functions to perform + an entire analysis. 'speaq' offers the possibility of raw spectra alignment and + quantitation but also an analysis based on features whereby the spectra are converted + to peaks which are then grouped and turned into features. These features can be + processed with any number of statistical tools either included in 'speaq' or available + elsewhere on CRAN. More details can be found in Vu et al. (2011) + and Beirnaert et al. (2018) . + date_publication: '2022-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=speaq + url_git: '' +spearmanCI: + version: '1.1' + title: |- + Jackknife Euclidean / Empirical Likelihood Inference for + Spearman's Rho + maintainer: Miguel de Carvalho + description: Functions for conducting jackknife Euclidean / empirical likelihood + inference for Spearman's rho (de Carvalho and Marques (2012) ). + date_publication: '2024-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spearmanCI + url_git: '' +spec: + version: 0.1.9 + title: A Data Specification Format and Interface + maintainer: Tim Bergsma + description: |- + Creates a data specification that describes the columns of a + table (data.frame). Provides methods to read, write, and update the + specification. Checks whether a table matches its specification. See + specification.data.frame(),read.spec(), write.spec(), as.csv.spec(), + respecify.character(), and %matches%.data.frame(). + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spec + url_git: '' +speccurvieR: + version: 0.4.2 + title: Easy, Fast, and Pretty Specification Curve Analysis + maintainer: Zayne Sember + description: |- + Making specification curve analysis easy, fast, and pretty. It + improves upon existing offerings with additional features and 'tidyverse' + integration. Users can easily visualize and evaluate how their models behave + under different specifications with a high degree of customization. For a + description and applications of specification curve analysis see Simonsohn, + Simmons, and Nelson (2020) . + date_publication: '2024-10-09' + bug_reports: https://github.com/zaynesember/speccurvieR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=speccurvieR + url_git: https://github.com/zaynesember/speccurvieR +SpecDetec: + version: 1.0.0 + title: Change Points Detection with Spectral Clustering + maintainer: Luis Uzai + description: Calculate change point based on spectral clustering with the option + to automatically calculate the number of clusters if this information is not available. + date_publication: '2018-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpecDetec + url_git: '' +SpecHelpers: + version: 0.2.7 + title: Spectroscopy Related Utilities + maintainer: Bryan A. Hanson + description: |- + Utility functions for spectroscopy. 1. Functions to simulate + spectra for use in teaching or testing. 2. Functions to process files created by + 'LoggerPro' and 'SpectraSuite' software. + date_publication: '2017-07-26' + bug_reports: https://github.com/bryanhanson/SpecHelpers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SpecHelpers + url_git: https://github.com/bryanhanson/SpecHelpers +SPECIES: + version: 1.2.0 + title: Statistical Package for Species Richness Estimation + maintainer: Ji-Ping Wang + description: Implementation of various methods in estimation of species richness + or diversity in Wang (2011). + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPECIES + url_git: '' +specieschrom: + version: 1.0.0 + title: The Species Chromatogram + maintainer: Loick Kleparski + description: A simple method to display and characterise the multidimensional ecological + niche of a species. The method also estimates the optimums and amplitudes along + each niche dimension. Give also an estimation of the degree of niche overlapping + between species. See Kleparski and Beaugrand (2022) for + further details. + date_publication: '2022-10-17' + bug_reports: https://github.com/loick-klpr/specieschrom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=specieschrom + url_git: https://github.com/loick-klpr/specieschrom +SPECK: + version: 1.0.0 + title: |- + Receptor Abundance Estimation using Reduced Rank Reconstruction + and Clustered Thresholding + maintainer: Azka Javaid + description: 'Surface Protein abundance Estimation using CKmeans-based clustered + thresholding (''SPECK'') is an unsupervised learning-based method that performs + receptor abundance estimation for single cell RNA-sequencing data based on reduced + rank reconstruction (RRR) and a clustered thresholding mechanism. Seurat''s normalization + method is described in: Hao et al., (2021) , Stuart + et al., (2019) , Butler et al., (2018) + and Satija et al., (2015) . Method for the RRR is further + detailed in: Erichson et al., (2019) and Halko et + al., (2009) . Clustering method is outlined in: Song et al., + (2020) and Wang et al., (2011) .' + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPECK + url_git: '' +specklestar: + version: 0.0.1.7 + title: Reduction of Speckle Data from BTA 6-m Telescope + maintainer: Denis Rastegaev + description: A set of functions for obtaining positional parameters and magnitude + difference between components of binary and multiple stellar systems from series + of speckle images. + date_publication: '2018-02-08' + bug_reports: https://github.com/drastega/specklestar/issues + url: https://drastega.github.io/docs/specklestar_vignette.html + url_cran: https://CRAN.R-project.org/package=specklestar + url_git: '' +specr: + version: 1.0.0 + title: Conducting and Visualizing Specification Curve Analyses + maintainer: Philipp K. Masur + description: 'Provides utilities for conducting specification curve analyses (Simonsohn, + Simmons & Nelson (2020, ) or multiverse analyses + (Steegen, Tuerlinckx, Gelman & Vanpaemel, 2016, ) + including functions to setup, run, evaluate, and plot all specifications.' + date_publication: '2023-01-20' + bug_reports: https://github.com/masurp/specr/issues + url: https://masurp.github.io/specr/ + url_cran: https://CRAN.R-project.org/package=specr + url_git: https://github.com/masurp/specr +specs: + version: 1.0.1 + title: Single-Equation Penalized Error-Correction Selector (SPECS) + maintainer: Etienne Wijler + description: |- + Implementation of SPECS, your favourite Single-Equation Penalized Error-Correction Selector developed in + Smeekes and Wijler (2021) . SPECS provides a fully automated estimation procedure for large and potentially + (co)integrated datasets. The dataset in levels is converted to a conditional error-correction model, either by the user or + by means of the functions included in this package, and various specialised forms of penalized regression can be applied to + the model. Automated options for initializing and selecting a sequence of penalties, as well as the construction of penalty + weights via an initial estimator, are available. Moreover, the user may choose from a number of pre-specified deterministic + configurations to further simplify the model building process. + date_publication: '2024-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=specs + url_git: '' +SpecsVerification: + version: 0.5-3 + title: |- + Forecast Verification Routines for Ensemble Forecasts of Weather + and Climate + maintainer: Stefan Siegert + description: |- + A collection of forecast verification routines developed for the SPECS + FP7 project. The emphasis is on comparative verification of ensemble forecasts of weather and climate. + date_publication: '2020-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpecsVerification + url_git: '' +spectacles: + version: 0.5-4 + title: |- + Storing, Manipulating and Analysis Spectroscopy and Associated + Data + maintainer: Pierre Roudier + description: |- + Stores and eases the manipulation of spectra and associated data, + with dedicated classes for spatial and soil-related data. + date_publication: '2023-07-07' + bug_reports: https://github.com/pierreroudier/spectacles/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spectacles + url_git: https://github.com/pierreroudier/spectacles/ +spectator: + version: 0.2.0 + title: Interface to the 'Spectator Earth' API + maintainer: Zivan Karaman + description: |- + Provides interface to the 'Spectator Earth' API , + mainly for obtaining the acquisition plans and satellite overpasses for Sentinel-1, + Sentinel-2, Landsat-8 and Landsat-9 satellites. Current position and trajectory can + also be obtained for a much larger set of satellites. It is also possible to search + the archive for available images over the area of interest for a given (past) period, + get the URL links to download the whole image tiles, or alternatively to download the + image for just the area of interest based on selected spectral bands. + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spectator + url_git: '' +spectr: + version: 1.0.1 + title: Calculate the Periodogram of a Time-Course + maintainer: Jake Hughey + description: |- + Provides a consistent interface to use various methods to calculate + the periodogram and estimate the period of a rhythmic time-course. Methods + include Lomb-Scargle, fast Fourier transform, and three versions of the + chi-square periodogram. See Tackenberg and Hughey (2021) + . + date_publication: '2022-02-07' + bug_reports: '' + url: https://spectr.hugheylab.org + url_cran: https://CRAN.R-project.org/package=spectr + url_git: https://github.com/hugheylab/spectr +spectral: + version: '2.0' + title: Common Methods of Spectral Data Analysis + maintainer: Martin Seilmayer + description: |- + On discrete data spectral analysis is performed by Fourier and Hilbert + transforms as well as with model based analysis called Lomb-Scargle method. + Fragmented and irregularly spaced data can be processed in almost all methods. Both, + FFT as well as LOMB methods take multivariate data and return standardized PSD. + For didactic reasons an analytical approach for deconvolution of noise spectra and + sampling function is provided. + A user friendly interface helps to interpret the results. + date_publication: '2021-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spectral + url_git: '' +spectralAnalysis: + version: 4.3.3 + title: Pre-Process, Visualize and Analyse Spectral Data + maintainer: Adriaan Blommaert + description: |2- + + Infrared, near-infrared and Raman spectroscopic data measured during chemical reactions, provide structural fingerprints by which molecules can be identified and quantified. The application of these spectroscopic techniques as inline process analytical tools (PAT), provides the pharmaceutical and chemical industry with novel tools, allowing to monitor their chemical processes, resulting in a better process understanding through insight in reaction rates, mechanistics, stability, etc. + Data can be read into R via the generic spc-format, which is generally supported by spectrometer vendor software. Versatile pre-processing functions are available to perform baseline correction by linking to the 'baseline' package; noise reduction via the 'signal' package; as well as time alignment, normalization, differentiation, integration and interpolation. Implementation based on the S4 object system allows storing a pre-processing pipeline as part of a spectral data object, and easily transferring it to other datasets. Interactive plotting tools are provided based on the 'plotly' package. + Non-negative matrix factorization (NMF) has been implemented to perform multivariate analyses on individual spectral datasets or on multiple datasets at once. NMF provides a parts-based representation of the spectral data in terms of spectral signatures of the chemical compounds and their relative proportions. + See 'hNMF'-package for references on available methods. The functionality to read in spc-files was adapted from the 'hyperSpec' package. + date_publication: '2024-01-30' + bug_reports: '' + url: https://openanalytics.eu + url_cran: https://CRAN.R-project.org/package=spectralAnalysis + url_git: '' +spectralAnomaly: + version: 0.1.1 + title: Detect Anomalies Using the Spectral Residual Algorithm + maintainer: Allen OBrien + description: |- + Apply the spectral residual algorithm to data, such as a + time series, to detect anomalies. Anomaly scores can be used to determine + outliers based upon a threshold or fed into more sophisticated prediction + models. Methods are based upon "Time-Series Anomaly Detection Service at + Microsoft", Ren, H., Xu, B., Wang, Y., et al., (2019) + . + date_publication: '2024-09-15' + bug_reports: https://github.com/al-obrien/spectralAnomaly/issues + url: https://al-obrien.github.io/spectralAnomaly/ + url_cran: https://CRAN.R-project.org/package=spectralAnomaly + url_git: https://github.com/al-obrien/spectralAnomaly +SpectralClMixed: + version: 1.0.1 + title: Spectral Clustering for Mixed Type Data + maintainer: Cristina Tortora + description: Performs cluster analysis of mixed-type data using Spectral Clustering, + see F. Mbuga and, C. Tortora (2022) . + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpectralClMixed + url_git: '' +spectralGP: + version: 1.3.3 + title: Approximate Gaussian Processes Using the Fourier Basis + maintainer: Chris Paciorek + description: |- + Routines for creating, manipulating, and performing + Bayesian inference about Gaussian processes in + one and two dimensions using the Fourier basis approximation: + simulation and plotting of processes, calculation of + coefficient variances, calculation of process density, + coefficient proposals (for use in MCMC). It uses R environments to + store GP objects as references/pointers. + date_publication: '2015-07-01' + bug_reports: '' + url: http://www.jstatsoft.org/v19/a2 + url_cran: https://CRAN.R-project.org/package=spectralGP + url_git: '' +SpectralMap: + version: '1.0' + title: Diffusion Map and Spectral Map + maintainer: Tianhao Wu + description: Implements the diffusion map method of dimensionality reduction and + spectral method of combining multiple diffusion maps, including creation of the + spectra and visualization of maps. + date_publication: '2016-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpectralMap + url_git: '' +spectralR: + version: 0.1.3 + title: |- + Obtain and Visualize Spectral Reflectance Data for Earth Surface + Polygons + maintainer: Oleh Prylutskyi + description: Tools for obtaining, processing, and visualizing spectral reflectance + data for the user-defined land or water surface classes for visual exploring in + which wavelength the classes differ. Input should be a shapefile with polygons + of surface classes (it might be different habitat types, crops, vegetation, etc.). + The Sentinel-2 L2A satellite mission optical bands pixel data are obtained through + the Google Earth Engine service () and used as + a source of spectral data. + date_publication: '2023-08-24' + bug_reports: https://github.com/olehprylutskyi/spectralR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spectralR + url_git: https://github.com/olehprylutskyi/spectralR/ +Spectran: + version: 1.0.6 + title: Visual and Non-Visual Spectral Analysis of Light + maintainer: Johannes Zauner + description: |- + Analyse light spectra for visual and non-visual (often called + melanopic) needs, wrapped up in a Shiny App. 'Spectran' allows for the import + of spectra in various CSV forms but also provides a wide range of example + spectra and even the creation of own spectral power distributions. The goal of + the app is to provide easy access and a visual overview of the spectral + calculations underlying common parameters used in the field. It is thus ideal + for educational purposes or the creation of presentation ready graphs in + lighting research and application. 'Spectran' uses equations and action spectra + described in CIE S026 (2018) , DIN/TS 5031-100 (2021) + , and ISO/CIE 23539 (2023) + . + date_publication: '2024-07-04' + bug_reports: https://github.com/LiTGde/Spectran/issues + url: https://litgde.github.io/Spectran/ + url_cran: https://CRAN.R-project.org/package=Spectran + url_git: https://github.com/LiTGde/Spectran +spectre: + version: 1.0.2 + title: Predict Regional Community Composition + maintainer: Craig Simpkins + description: |- + Predict regional community composition at a fine spatial + resolution using only sparse biological and environmental data. The package + is based on the DynamicFOAM algorithm described + in Mokany et al. (2011) . + date_publication: '2021-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spectre + url_git: '' +spectrolab: + version: 0.0.19 + title: Class and Methods for Spectral Data + maintainer: Jose Eduardo Meireles + description: Input/Output, processing and visualization of spectra taken with different + spectrometers, including SVC (Spectra Vista), ASD and PSR (Spectral Evolution). + Implements an S3 class spectra that other packages can build on. Provides methods + to access, plot, manipulate, splice sensor overlap, vector normalize and smooth + spectra. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spectrolab + url_git: '' +Spectrum: + version: '1.1' + title: Fast Adaptive Spectral Clustering for Single and Multi-View Data + maintainer: Christopher R John + description: A self-tuning spectral clustering method for single or multi-view data. + 'Spectrum' uses a new type of adaptive density aware kernel that strengthens connections + in the graph based on common nearest neighbours. It uses a tensor product graph + data integration and diffusion procedure to integrate different data sources and + reduce noise. 'Spectrum' uses either the eigengap or multimodality gap heuristics + to determine the number of clusters. The method is sufficiently flexible so that + a wide range of Gaussian and non-Gaussian structures can be clustered with automatic + selection of K. + date_publication: '2020-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Spectrum + url_git: '' +sped: + version: '0.3' + title: Multi-Gene Descent Probabilities + maintainer: Charles J. Geyer + description: |- + Do multi-gene descent probabilities + (Thompson, 1983, ) + and special cases thereof + (Thompson, 1986, ) + including inbreeding and kinship coefficients. But does much more: + probabilities of any set of genes descending from any other + set of genes. + date_publication: '2023-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sped + url_git: '' +spedecon: + version: '0.1' + title: |- + Smoothness-Penalized Deconvolution for Density Estimation Under + Measurement Error + maintainer: David Kent + description: Implements the Smoothness-Penalized Deconvolution method for estimating + a probability density under measurement error of Kent and Ruppert (2023) . + The estimator is formed by computing a histogram of the error-contaminated data, + and then finding an estimate that minimizes a reconstruction error plus a smoothness-inducing + penalty term. The primary function, sped(), takes the data and error distribution, + and returns the estimator as a function. + date_publication: '2024-01-12' + bug_reports: '' + url: https://www.davidjkent.org + url_cran: https://CRAN.R-project.org/package=spedecon + url_git: '' +SPEDInstabR: + version: '2.2' + title: |- + Estimation of the Relative Importance of Factors Affecting + Species Distribution Based on Stability Concept + maintainer: Castor Guisande Gonzalez + description: From output files obtained from the software 'ModestR', the relative + contribution of factors to explain species distribution is depicted using several + plots. A global geographic raster file for each environmental variable may be + also obtained with the mean relative contribution, considering all species present + in each raster cell, of the factor to explain species distribution. Finally, for + each variable it is also possible to compare the frequencies of any variable obtained + in the cells where the species is present with the frequencies of the same variable + in the cells of the extent. + date_publication: '2024-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPEDInstabR + url_git: '' +spEDM: + version: '1.4' + title: Spatial Empirical Dynamic Modeling + maintainer: Wenbo Lv + description: Inferring causal associations in cross-sectional earth system data + through empirical dynamic modeling (EDM), with extensions to convergent cross + mapping from Sugihara et al. (2012) , partial cross + mapping as outlined in Leng et al. (2020) , and + cross mapping cardinality as described in Tao et al. (2023). + date_publication: '2025-02-10' + bug_reports: https://github.com/stscl/spEDM/issues + url: https://stscl.github.io/spEDM/ + url_cran: https://CRAN.R-project.org/package=spEDM + url_git: https://github.com/stscl/spEDM +speech: + version: 0.1.5 + title: Legislative Speeches + maintainer: Nicolas Schmidt + description: |- + Converts the floor speeches of Uruguayan legislators, extracted from the + parliamentary minutes, to tidy data.frame where each observation is the intervention of a single legislator. + date_publication: '2022-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=speech + url_git: https://github.com/Nicolas-Schmidt/speech +speechbr: + version: 2.0.0 + title: |- + Access the Speechs and Speaker's Informations of House of + Representatives of Brazil + maintainer: Douglas Cardoso + description: |- + Scrap speech text and speaker informations of speeches of House of + Representatives of Brazil, and transform in a cleaned tibble. + date_publication: '2022-03-19' + bug_reports: https://github.com/dcardosos/speechbr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=speechbr + url_git: https://github.com/dcardosos/speechbr +speedglm: + version: 0.3-5 + title: Fitting Linear and Generalized Linear Models to Large Data Sets + maintainer: Marco Enea + description: 'Fitting linear models and generalized linear models to large data + sets by updating algorithms, according to the method described in Enea (2009, + ISBN: 9788861294257).' + date_publication: '2023-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=speedglm + url_git: '' +speedyBBT: + version: '1.0' + title: Efficient Bayesian Inference for the Bradley--Terry Model + maintainer: Rowland Seymour + description: |- + A suite of functions that allow a full, fast, and efficient Bayesian treatment of the Bradley--Terry model. + Prior assumptions about the model parameters can be encoded through a multivariate normal prior distribution. + Inference is performed using a latent variable representation of the model. + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=speedyBBT + url_git: '' +speedycode: + version: 0.3.0 + title: |- + Automate Code for Adding Labels, Recoding and Renaming + Variables, and Converting ASCII Files + maintainer: Jacob Harris + description: Label, recode, rename, and convert datasets and ASCII files more efficiently. + 'speedycode' automates the code necessary for labeling variables with the 'labelled' + package, recoding and renaming variables with 'dplyr' syntax, and converting ASCII + files with the 'readroper' package. Most functions require only the name of the + dataset and the code will be automatically written. Some convenience functions + useful for converting ASCII files are also included. + date_publication: '2022-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=speedycode + url_git: '' +speedytax: + version: 1.0.4 + title: Rapidly Import Classifier Results into 'phyloseq' + maintainer: John Quensen + description: Import classification results from the 'RDP Classifier' (Ribosomal + Database Project),' 'USEARCH sintax,' 'vsearch sintax' and the 'QIIME2' (Quantitative + Insights into Microbial Ecology) classifiers into 'phyloseq' tax_table objects. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=speedytax + url_git: '' +spef: + version: 1.0.9 + title: Semiparametric Estimating Functions + maintainer: Sy Han (Steven) Chiou + description: |- + Functions for fitting semiparametric regression models for + panel count survival data. An overview of the package can be found + in Wang and Yan (2011) and + Chiou et al. (2018) . + date_publication: '2020-05-24' + bug_reports: http://github.com/stc04003/spef/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spef + url_git: http://github.com/stc04003/spef +speff2trial: + version: 1.0.5 + title: |- + Semiparametric Efficient Estimation for a Two-Sample Treatment + Effect + maintainer: Michal Juraska + description: Performs estimation and testing of the treatment effect in a 2-group + randomized clinical trial with a quantitative, dichotomous, or right-censored + time-to-event endpoint. The method improves efficiency by leveraging baseline + predictors of the endpoint. The inverse probability weighting technique of Robins, + Rotnitzky, and Zhao (JASA, 1994) is used to provide unbiased estimation when the + endpoint is missing at random. + date_publication: '2022-05-31' + bug_reports: https://github.com/mjuraska/speff2trial/issues + url: '' + url_cran: https://CRAN.R-project.org/package=speff2trial + url_git: https://github.com/mjuraska/speff2trial +SPEI: + version: 1.8.1 + title: |- + Calculation of the Standardized Precipitation-Evapotranspiration + Index + maintainer: Santiago Beguería + description: A set of functions for computing potential evapotranspiration and several + widely used drought indices including the Standardized Precipitation-Evapotranspiration + Index (SPEI). + date_publication: '2023-03-02' + bug_reports: https://github.com/sbegueria/SPEI/issues + url: https://spei.csic.es + url_cran: https://CRAN.R-project.org/package=SPEI + url_git: https://github.com/sbegueria/SPEI +spellcheckr: + version: 0.1.2 + title: Correct the Spelling of a Given Word in the English Language + maintainer: Selva Prabhakaran + description: |- + Corrects the spelling of a given word in English + using a modification of Peter Norvig's spell correct + algorithm (see ) + which handles up to three edits. The algorithm tries to + find the spelling with maximum probability of intended + correction out of all possible candidate corrections from + the original word. + date_publication: '2016-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spellcheckr + url_git: '' +spelling: + version: 2.3.1 + title: Tools for Spell Checking in R + maintainer: Jeroen Ooms + description: |- + Spell checking common document formats including latex, markdown, manual pages, + and description files. Includes utilities to automate checking of documentation and + vignettes as a unit test during 'R CMD check'. Both British and American English are + supported out of the box and other languages can be added. In addition, packages may + define a 'wordlist' to allow custom terminology without having to abuse punctuation. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/spelling/issues + url: https://ropensci.r-universe.dev/spellinghttps://docs.ropensci.org/spelling/ + url_cran: https://CRAN.R-project.org/package=spelling + url_git: '' +spemd: + version: 0.1-1 + title: |- + A Bi-Dimensional Implementation of the Empirical Mode + Decomposition for Spatial Data + maintainer: Pierre Roudier + description: |- + This implementation of the Empirical Mode Decomposition (EMD) works in 2 dimensions simultaneously, and + can be applied on spatial data. It can handle both gridded or un-gridded datasets. + date_publication: '2018-07-01' + bug_reports: https://github.com/pierreroudier/spemd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spemd + url_git: https://github.com/pierreroudier/spemd +sperich: + version: 1.5-9 + title: Auxiliary Functions to Estimate Centers of Biodiversity + maintainer: Maximilian Lange + description: Provides some easy-to-use functions to interpolate species range based + on species occurrences and to estimate centers of biodiversity. + date_publication: '2023-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sperich + url_git: '' +sperrorest: + version: 3.0.5 + title: |- + Perform Spatial Error Estimation and Variable Importance + Assessment + maintainer: Alexander Brenning + description: |- + Implements spatial error estimation and + permutation-based variable importance measures for predictive models + using spatial cross-validation and spatial block bootstrap. + date_publication: '2022-10-16' + bug_reports: https://github.com/giscience-fsu/sperrorest/issues + url: https://giscience-fsu.github.io/sperrorest/ + url_cran: https://CRAN.R-project.org/package=sperrorest + url_git: https://github.com/giscience-fsu/sperrorest +SpeTestNP: + version: 1.1.0 + title: Non-Parametric Tests of Parametric Specifications + maintainer: Hippolyte Boucher + description: |2- + + Performs non-parametric tests of parametric specifications. + Five tests are available. + Specific bandwidth and kernel methods can be chosen along with many other options. + Allows parallel computing to quickly compute p-values based on the bootstrap. + Methods implemented in the package are H.J. Bierens (1982) , + J.C. Escanciano (2006) , + P.L. Gozalo (1997) , + P. Lavergne and V. Patilea (2008) , + P. Lavergne and V. Patilea (2012) , + J.H. Stock and M.W. Watson (2006) , + C.F.J. Wu (1986) , + J. Yin, Z. Geng, R. Li, H. Wang (2010) + and J.X. Zheng (1996) . + date_publication: '2022-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpeTestNP + url_git: https://github.com/HippolyteBoucher/SpeTestNP +SPEV: + version: 1.0.0 + title: Unsmoothed and Smoothed Penalized PCA using Nesterov Smoothing + maintainer: Rebecca Hurwitz + description: We provide functionality to implement penalized PCA with an option + to smooth the objective function using Nesterov smoothing. Two functions are available + to compute a user-specified number of eigenvectors. The function unsmoothed_penalized_EV() + computes a penalized PCA without smoothing and has three parameters (the input + matrix, the Lasso penalty, and the number of desired eigenvectors). The function + smoothed_penalized_EV() computes a smoothed penalized PCA using the same parameters + and additionally requires the specification of a smoothing parameter. Both functions + return a matrix having the desired eigenvectors as columns. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPEV + url_git: '' +spex: + version: 0.7.1 + title: Spatial Extent Tools + maintainer: Michael D. Sumner + description: |- + Functions to produce a fully fledged 'geo-spatial' object extent as a + 'SpatialPolygonsDataFrame'. Also included are functions to generate polygons + from raster data using 'quadmesh' techniques, a round number buffered extent, and + general spatial-extent and 'raster-like' extent helpers missing from the originating + packages. Some latitude-based tools for polar maps are included. + date_publication: '2020-06-20' + bug_reports: https://github.com/mdsumner/spex/issues + url: https://mdsumner.github.io/spex/ + url_cran: https://CRAN.R-project.org/package=spex + url_git: '' +spfa: + version: '1.0' + title: Semi-Parametric Factor Analysis + maintainer: Yang Liu + description: Estimation, scoring, and plotting functions for the semi-parametric + factor model proposed by Liu & Wang (2022) and + Liu & Wang (2023) . Both the conditional densities of observed + responses given the latent factors and the joint density of latent factors are + estimated non-parametrically. Functional parameters are approximated by smoothing + splines, whose coefficients are estimated by penalized maximum likelihood using + an expectation-maximization (EM) algorithm. E- and M-steps can be parallelized + on multi-thread computing platforms that support 'OpenMP'. Both continuous and + unordered categorical response variables are supported. + date_publication: '2023-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spfa + url_git: '' +spfda: + version: 0.9.1 + title: Function-on-Scalar Regression with Group-Bridge Penalty + maintainer: Zhengjia Wang + description: |- + Implements a group-bridge penalized function-on-scalar regression + model proposed by Wang et al. (2020) , to simultaneously + estimate functional coefficient and recover the local sparsity. + date_publication: '2022-03-18' + bug_reports: https://github.com/dipterix/spfda/issues + url: http://dipterix.org/spfda/ + url_cran: https://CRAN.R-project.org/package=spfda + url_git: https://github.com/dipterix/spfda +spfilteR: + version: 2.1.0 + title: |- + Semiparametric Spatial Filtering with Eigenvectors in + (Generalized) Linear Models + maintainer: Sebastian Juhl + description: Tools to decompose (transformed) spatial connectivity matrices and + perform supervised or unsupervised semiparametric spatial filtering in a regression + framework. The package supports unsupervised spatial filtering in standard linear + as well as some generalized linear regression models. + date_publication: '2025-02-21' + bug_reports: https://github.com/sjuhl/spfilteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spfilteR + url_git: https://github.com/sjuhl/spfilteR +spFSR: + version: 2.0.4 + title: |- + Feature Selection and Ranking via Simultaneous Perturbation + Stochastic Approximation + maintainer: David Akman + description: |- + An implementation of feature selection, weighting and ranking via simultaneous perturbation + stochastic approximation (SPSA). The SPSA-FSR algorithm searches for a locally optimal set of + features that yield the best predictive performance using some error measures such as mean + squared error (for regression problems) and accuracy rate (for classification problems). + date_publication: '2023-03-17' + bug_reports: https://github.com/yongkai17/spFSR/issues + url: https://www.featureranking.com/ + url_cran: https://CRAN.R-project.org/package=spFSR + url_git: '' +spFW: + version: 0.1.0 + title: Hierarchical Spatial Finlay-Wilkinson Model + maintainer: Xingche Guo + description: Estimation and Prediction Functions Using Bayesian Hierarchical Spatial + Finlay-Wilkinson Model for Analysis of Multi-Environment Field Trials. + date_publication: '2022-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spFW + url_git: '' +spGARCH: + version: 0.2.2 + title: Spatial ARCH and GARCH Models (spGARCH) + maintainer: Philipp Otto + description: 'A collection of functions to deal with spatial and spatiotemporal + autoregressive conditional heteroscedasticity (spatial ARCH and GARCH models) + by Otto, Schmid, Garthoff (2018, Spatial Statistics) : simulation + of spatial ARCH-type processes (spARCH, exponential spARCH, complex spARCH); quasi-maximum-likelihood + estimation of the parameters of spARCH models and spatial autoregressive models + with spARCH disturbances, diagnostic checks, visualizations.' + date_publication: '2020-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spGARCH + url_git: '' +spgs: + version: 1.0-4 + title: Statistical Patterns in Genomic Sequences + maintainer: Andrew Hart + description: |- + A collection of statistical hypothesis tests and other + techniques for identifying certain spatial relationships/phenomena in + DNA sequences. In particular, it provides tests and graphical methods for determining + whether or not DNA sequences comply with Chargaff's second parity rule + or exhibit purine-pyrimidine parity. In addition, there are functions for + efficiently simulating discrete state space Markov chains and testing + arbitrary symbolic sequences of symbols for the presence of first-order + Markovianness. + Also, it has functions for counting words/k-mers (and cylinder patterns) in + arbitrary symbolic sequences. Functions which take a DNA sequence as input + can handle sequences stored as SeqFastadna objects from the 'seqinr' package. + date_publication: '2023-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spgs + url_git: '' +spgwr: + version: 0.6-37 + title: Geographically Weighted Regression + maintainer: Roger Bivand + description: |- + Functions for computing geographically weighted + regressions are provided, based on work by Chris + Brunsdon, Martin Charlton and Stewart Fotheringham. + date_publication: '2024-06-10' + bug_reports: https://github.com/rsbivand/spgwr/issues + url: https://rsbivand.github.io/spgwr/ + url_cran: https://CRAN.R-project.org/package=spgwr + url_git: https://github.com/rsbivand/spgwr/ +spheredata: + version: 0.1.2 + title: |- + Students' Performance Dataset in Physics Education Research + (SPHERE) + maintainer: Purwoko Haryadi Santoso + description: A multidimensional dataset of students' performance assessment in high + school physics. The SPHERE dataset was collected from 497 students in four public + high schools specifically measuring their conceptual understanding, scientific + ability, and attitude toward physics [see Santoso et al. (2024) ]. + The data collection was conducted using some research based assessments established + by the physics education research community. They include the Force Concept Inventory, + the Force and Motion Conceptual Evaluation, the Rotational and Rolling Motion + Conceptual Survey, the Fluid Mechanics Concept Inventory, the Mechanical Waves + Conceptual Survey, the Thermal Concept Evaluation, the Survey of Thermodynamic + Processes and First and Second Laws, the Scientific Abilities Assessment Rubrics, + and the Colorado Learning Attitudes about Science Survey. Students' attributes + related to gender, age, socioeconomic status, domicile, literacy, physics identity, + and test results administered using teachers' developed items are also reported + in this dataset. + date_publication: '2024-11-18' + bug_reports: https://github.com/santosoph/spheredata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spheredata + url_git: https://github.com/santosoph/spheredata +sphereML: + version: 0.1.0 + title: |- + Analyzing Students' Performance Dataset in Physics Education + Research (SPHERE) using Machine Learning (ML) + maintainer: Purwoko Haryadi Santoso + description: A simple package facilitating ML based analysis for physics education + research (PER) purposes. The implemented machine learning technique is random + forest optimized by item response theory (IRT) for feature selection and genetic + algorithm (GA) for hyperparameter tuning. The data analyzed here has been made + available in the CRAN repository through the 'spheredata' package. The SPHERE + stands for Students' Performance in Physics Education Research (PER). The students + are the eleventh graders learning physics at the high school curriculum. We follow + the stream of multidimensional students' assessment as probed by some research + based assessments in PER. The goal is to predict the students' performance at + the end of the learning process. Three learning domains are measured including + conceptual understanding, scientific ability, and scientific attitude. Furthermore, + demographic backgrounds and potential variables predicting students' performance + on physics are also demonstrated. + date_publication: '2025-02-06' + bug_reports: https://github.com/santosoph/sphereML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sphereML + url_git: https://github.com/santosoph/sphereML +SphereOptimize: + version: 0.1.1 + title: Optimization on a Unit Sphere + maintainer: Yijun Xie + description: A simple tool for numerical optimization on the unit sphere. This is + achieved by combining the spherical coordinating system with L-BFGS-B optimization. + This algorithm is implemented in Kolkiewicz, A., Rice, G., & Xie, Y. (2020) . + date_publication: '2020-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SphereOptimize + url_git: '' +spherepc: + version: 0.1.7 + title: Spherical Principal Curves + maintainer: Jongmin Lee + description: |- + Fitting dimension reduction methods to data lying on two-dimensional sphere. + This package provides principal geodesic analysis, principal circle, principal curves + proposed by Hauberg, and spherical principal curves. Moreover, it offers the method of locally + defined principal geodesics which is underway. The detailed procedures + are described in Lee, J., Kim, J.-H. and Oh, H.-S. (2021) . + Also see Kim, J.-H., Lee, J. and Oh, H.-S. (2020) . + date_publication: '2021-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spherepc + url_git: '' +sphereplot: + version: 1.5.1 + title: Spherical Plotting + maintainer: Aaron Robotham + description: Various functions for creating spherical coordinate system plots via + extensions to rgl. + date_publication: '2022-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sphereplot + url_git: '' +spheresmooth: + version: 0.1.3 + title: Piecewise Geodesic Smoothing for Spherical Data + maintainer: Kwan-Young Bak + description: Fitting a smooth path to a given set of noisy spherical data observed + at known time points. It implements a piecewise geodesic curve fitting method + on the unit sphere based on a velocity-based penalization scheme. The proposed + approach is implemented using the Riemannian block coordinate descent algorithm. + To understand the method and algorithm, one can refer to Bak, K. Y., Shin, J. + K., & Koo, J. Y. (2023) for the case of order + 1. Additionally, this package includes various functions necessary for handling + spherical data. + date_publication: '2024-12-06' + bug_reports: https://github.com/kybak90/spheresmooth/issues + url: https://kybak90.github.io/spheresmooth/ + url_cran: https://CRAN.R-project.org/package=spheresmooth + url_git: https://github.com/kybak90/spheresmooth +SphericalCubature: + version: '1.5' + title: |- + Numerical Integration over Spheres and Balls in n-Dimensions; + Multivariate Polar Coordinates + maintainer: John P. Nolan + description: |- + Provides several methods to integrate functions over the unit + sphere and ball in n-dimensional Euclidean space. Routines for converting to/from + multivariate polar/spherical coordinates are also provided. + date_publication: '2021-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SphericalCubature + url_git: '' +sphet: + version: 2.1-1 + title: |- + Estimation of Spatial Autoregressive Models with and without + Heteroskedastic Innovations + maintainer: Gianfranco Piras + description: Functions for fitting Cliff-Ord-type spatial autoregressive models + with and without heteroskedastic innovations using Generalized Method of Moments + estimation are provided. Some support is available for fitting spatial HAC models, + and for fitting with non-spatial endogeneous variables using instrumental variables. + date_publication: '2024-12-06' + bug_reports: https://github.com/gpiras/sphet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sphet + url_git: https://github.com/gpiras/sphet +sphunif: + version: 1.4.0 + title: Uniformity Tests on the Circle, Sphere, and Hypersphere + maintainer: Eduardo García-Portugués + description: |- + Implementation of uniformity tests on the circle and + (hyper)sphere. The main function of the package is unif_test(), which + conveniently collects more than 35 tests for assessing uniformity on + S^{p-1} = {x in R^p : ||x|| = 1}, p >= 2. The test statistics are + implemented in the unif_stat() function, which allows computing several + statistics for different samples within a single call, thus facilitating + Monte Carlo experiments. Furthermore, the unif_stat_MC() function allows + parallelizing them in a simple way. The asymptotic null distributions of + the statistics are available through the function unif_stat_distr(). The + core of 'sphunif' is coded in C++ by relying on the 'Rcpp' package. + The package also provides several novel datasets and gives the replicability + for the data applications/simulations in García-Portugués et al. (2021) + , García-Portugués et al. (2023) + , García-Portugués et al. (2024) + , and Fernández-de-Marcos and + García-Portugués (2024) . + date_publication: '2024-05-24' + bug_reports: https://github.com/egarpor/sphunif + url: '' + url_cran: https://CRAN.R-project.org/package=sphunif + url_git: https://github.com/egarpor/sphunif +SpiceFP: + version: 0.1.2 + title: Sparse Method to Identify Joint Effects of Functional Predictors + maintainer: Girault Gnanguenon Guesse + description: |- + A set of functions allowing to implement the 'SpiceFP' approach + which is iterative. It involves transformation of functional predictors into + several candidate explanatory matrices (based on contingency tables), to which + relative edge matrices with contiguity constraints are associated. Generalized + Fused Lasso regression are performed in order to identify the best candidate + matrix, the best class intervals and related coefficients at each iteration. + The approach is stopped when the maximal number of iterations is reached or + when retained coefficients are zeros. Supplementary functions allow to get + coefficients of any candidate matrix or mean of coefficients of many candidates. + The methods in this package are describing in Girault Gnanguenon Guesse, + Patrice Loisel, Bénedicte Fontez, Thierry Simonneau, Nadine Hilgert (2021) + "An exploratory penalized regression to identify combined effects of functional + variables -Application to agri-environmental issues" + . + date_publication: '2023-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpiceFP + url_git: '' +SPIChanges: + version: 0.1.0 + title: |- + Improves the Interpretation of the Standardized Precipitation + Index Under Changing Climate Conditions + maintainer: Gabriel Constantino Blain + description: |- + Improves the interpretation of the Standardized Precipitation + Index under changing climate conditions. The package uses the + nonstationary approach proposed in Blain et al. (2022) + to detect trends in rainfall quantities and to + quantify the effect of such trends on the probability of a drought event + occurring. + date_publication: '2025-02-05' + bug_reports: https://github.com/gabrielblain/SPIChanges/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SPIChanges + url_git: https://github.com/gabrielblain/SPIChanges +spider: + version: 1.5.0 + title: Species Identity and Evolution in R + maintainer: Rupert A. Collins + description: Analysis of species limits and DNA barcoding data. Included are functions + for generating important summary statistics from DNA barcode data, assessing specimen + identification efficacy, testing and optimizing divergence threshold limits, assessment + of diagnostic nucleotides, and calculation of the probability of reciprocal monophyly. + Additionally, a sliding window function offers opportunities to analyse information + across a gene, often used for marker design in degraded DNA studies. Further information + on the package has been published in Brown et al (2012) . + date_publication: '2018-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spider + url_git: '' +spiderbar: + version: 0.2.5 + title: Parse and Test Robots Exclusion Protocol Files and Rules + maintainer: Bob Rudis + description: |- + The 'Robots Exclusion Protocol' documents + a set of standards for allowing or excluding robot/spider crawling of different areas of + site content. Tools are provided which wrap The 'rep-cpp' + C++ library for processing these 'robots.txt' files. + date_publication: '2023-02-11' + bug_reports: https://github.com/hrbrmstr/spiderbar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spiderbar + url_git: https://github.com/hrbrmstr/spiderbar +spidR: + version: 1.0.2 + title: Spider Knowledge Online + maintainer: Pedro Cardoso + description: Allows the user to connect with the World Spider Catalogue (WSC; ) + and the World Spider Trait (WST; ) databases. + Also performs several basic functions such as checking names validity, retrieving + coordinate data from the Global Biodiversity Information Facility (GBIF; ), + and mapping. + date_publication: '2021-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spidR + url_git: '' +SPIGA: + version: 1.0.0 + title: |- + Compute SPI Index using the Methods Genetic Algorithm and + Maximum Likelihood + maintainer: Iván Ayala-Bizarro + description: 'Calculate the Standardized Precipitation Index (SPI) for monitoring + drought, using Artificial Intelligence techniques (SPIGA) and traditional numerical + technique Maximum Likelihood (SPIML). For more information see: http://drought.unl.edu/monitoringtools/downloadablespiprogram.aspx.' + date_publication: '2016-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPIGA + url_git: '' +spikes: + version: '1.1' + title: |- + Detecting Election Fraud from Irregularities in Vote-Share + Distributions + maintainer: Arturas Rozenas + description: Applies re-sampled kernel density method to detect vote fraud. It estimates + the proportion of coarse vote-shares in the observed data relative to the null + hypothesis of no fraud. + date_publication: '2016-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spikes + url_git: '' +spikeslab: + version: 1.1.6 + title: |- + Prediction and Variable Selection Using Spike and Slab + Regression + maintainer: Udaya B. Kogalur + description: Spike and slab for prediction and variable selection in linear regression + models. Uses a generalized elastic net for variable selection. + date_publication: '2022-04-26' + bug_reports: '' + url: https://ishwaran.org/ + url_cran: https://CRAN.R-project.org/package=spikeslab + url_git: '' +spikeSlabGAM: + version: 1.1-20 + title: |- + Bayesian Variable Selection and Model Choice for Generalized + Additive Mixed Models + maintainer: Fabian Scheipl + description: |- + Bayesian variable selection, model choice, and regularized + estimation for (spatial) generalized additive mixed regression models + via stochastic search variable selection with spike-and-slab priors. + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spikeSlabGAM + url_git: https://github.com/fabian-s/spikeSlabGAM +Spillover: + version: 0.1.1 + title: Spillover/Connectedness Index Based on VAR Modelling + maintainer: Jilber Urbina + description: A user-friendly tool for estimating both total and directional connectedness + spillovers based on Diebold and Yilmaz (2009, 2012). It also provides the user + with rolling estimation for total and net indices. User can find both orthogonalized + and generalized versions for each kind of measures. See Diebold and Yilmaz (2009, + 2012) find them at and . + date_publication: '2024-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Spillover + url_git: '' +SPINA: + version: 4.1.0 + title: Structure Parameter Inference Approach + maintainer: Johannes W. Dietrich + description: Calculates constant structure parameters of endocrine homeostatic systems + from equilibrium hormone concentrations. Methods and equations have been described + in Dietrich et al. (2012) and Dietrich et al. (2016) + . + date_publication: '2018-03-21' + bug_reports: https://sourceforge.net/p/spina/bugs/ + url: http://spina.sf.net/ + url_cran: https://CRAN.R-project.org/package=SPINA + url_git: '' +spINAR: + version: 0.2.0 + title: (Semi)Parametric Estimation and Bootstrapping of INAR Models + maintainer: Maxime Faymonville + description: Semiparametric and parametric estimation of INAR models including a + finite sample refinement (Faymonville et al. (2022) ) + for the semiparametric setting introduced in Drost et al. (2009) , + different procedures to bootstrap INAR data (Jentsch, C. and Weiß, C.H. (2017) + ) and flexible simulation of INAR data. + date_publication: '2024-04-08' + bug_reports: https://github.com/MFaymon/spINAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spINAR + url_git: https://github.com/MFaymon/spINAR +spinBayes: + version: 0.2.2 + title: |- + Semi-Parametric Gene-Environment Interaction via Bayesian + Variable Selection + maintainer: Jie Ren + description: |- + Many complex diseases are known to be affected by the interactions between + genetic variants and environmental exposures beyond the main genetic and environmental + effects. Existing Bayesian methods for gene-environment (G×E) interaction studies are + challenged by the high-dimensional nature of the study and the complexity of environmental + influences. We have developed a novel and powerful semi-parametric Bayesian variable + selection method that can accommodate linear and nonlinear G×E interactions simultaneously + (Ren et al. (2020) ). Furthermore, the proposed method can conduct + structural identification by distinguishing nonlinear interactions from main effects only + case within Bayesian framework. Spike-and-slab priors are incorporated on both individual + and group level to shrink coefficients corresponding to irrelevant main and interaction + effects to zero exactly. The Markov chain Monte Carlo algorithms of the proposed and + alternative methods are efficiently implemented in C++. + date_publication: '2025-02-10' + bug_reports: https://github.com/jrhub/spinBayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spinBayes + url_git: https://github.com/jrhub/spinBayes +spind: + version: 2.2.1 + title: Spatial Methods and Indices + maintainer: Sam Levin + description: |- + Functions for spatial methods based on generalized estimating equations (GEE) and + wavelet-revised methods (WRM), functions for scaling by wavelet multiresolution regression (WMRR), + conducting multi-model inference, and stepwise model selection. Further, contains functions + for spatially corrected model accuracy measures. + date_publication: '2020-10-30' + bug_reports: https://github.com/levisc8/spind/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spind + url_git: https://github.com/levisc8/spind +spinifex: + version: 0.3.8 + title: |- + Manual Tours, Manual Control of Dynamic Projections of Numeric + Multivariate Data + maintainer: Nicholas Spyrison + description: |- + Data visualization tours animates linear projection + of multivariate data as its basis (ie. orientation) changes. The 'spinifex' + packages generates paths for manual tours by manipulating the contribution of + a single variable at a time Cook & Buja (1997) + . Other types of tours, such as grand + (random walk) and guided (optimizing some objective function) are available + in the 'tourr' package Wickham et al. . + 'spinifex' builds on 'tourr' and can render tours with 'gganimate' and + 'plotly' graphics, and allows for exporting as an .html widget and as an .gif, + respectively. This work is fully discussed in Spyrison & Cook (2020) + . + date_publication: '2025-01-08' + bug_reports: https://github.com/nspyrison/spinifex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spinifex + url_git: https://github.com/nspyrison/spinifex/ +spinner: + version: 1.1.0 + title: An Implementation of Graph Net Architecture Based on 'torch' + maintainer: Giancarlo Vercellino + description: Proposes a 'torch' implementation of Graph Net architecture allowing + different options for message passing and feature embedding. + date_publication: '2023-03-21' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/spinner + url_cran: https://CRAN.R-project.org/package=spinner + url_git: '' +spinyReg: + version: 0.1-0 + title: Sparse Generative Model and Its EM Algorithm + maintainer: Julien Chiquet + description: |- + Implements a generative model that uses a + spike-and-slab like prior distribution obtained by multiplying a + deterministic binary vector. Such a model allows an EM algorithm, + optimizing a type-II log-likelihood. + date_publication: '2015-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spinyReg + url_git: '' +spiralize: + version: 1.1.0 + title: Visualize Data on Spirals + maintainer: Zuguang Gu + description: |- + It visualizes data along an Archimedean spiral , + makes so-called spiral graph or spiral chart. + It has two major advantages for visualization: 1. It is able to visualize data with very long axis with high + resolution. 2. It is efficient for time series data to reveal periodic patterns. + date_publication: '2024-06-18' + bug_reports: '' + url: https://jokergoo.github.io/spiralize/ + url_cran: https://CRAN.R-project.org/package=spiralize + url_git: https://github.com/jokergoo/spiralize +spiritR: + version: 0.1.1 + title: Template for Clinical Trial Protocol + maintainer: Aaron Conway + description: |- + Contains an R Markdown template for a clinical trial + protocol adhering to the SPIRIT statement. The SPIRIT (Standard Protocol + Items for Interventional Trials) statement outlines recommendations for a + minimum set of elements to be addressed in a clinical trial protocol. + Also contains functions to create a xml document from the template and + upload it to clinicaltrials.gov for + trial registration. + date_publication: '2019-08-19' + bug_reports: https://github.com/awconway/spiritR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spiritR + url_git: https://github.com/awconway/spiritR +spiro: + version: 0.2.3 + title: Manage Data from Cardiopulmonary Exercise Testing + maintainer: Simon Nolte + description: |- + Import, process, summarize and visualize raw data from + metabolic carts. See Robergs, Dwyer, and Astorino (2010) for more details on data processing. + date_publication: '2025-02-18' + bug_reports: https://github.com/ropensci/spiro/issues + url: https://docs.ropensci.org/spiro/ + url_cran: https://CRAN.R-project.org/package=spiro + url_git: https://github.com/ropensci/spiro +splancs: + version: 2.01-45 + title: Spatial and Space-Time Point Pattern Analysis + maintainer: Roger Bivand + description: The Splancs package was written as an enhancement to S-Plus for display + and analysis of spatial point pattern data; it has been ported to R and is in + "maintenance mode". + date_publication: '2024-05-27' + bug_reports: https://github.com/rsbivand/splancs/issues + url: https://www.maths.lancs.ac.uk/~rowlings/Splancs/ + url_cran: https://CRAN.R-project.org/package=splancs + url_git: https://github.com/rsbivand/splancs +splash: + version: 1.0.2 + title: Simple Process-Led Algorithms for Simulating Habitats + maintainer: Roberto Villegas-Diaz + description: |- + This program calculates bioclimatic indices and fluxes (radiation, + evapotranspiration, soil moisture) for use in studies of ecosystem function, + species distribution, and vegetation dynamics under changing climate + scenarios. Predictions are based on a minimum of required inputs: latitude, + precipitation, air temperature, and cloudiness. + Davis et al. (2017) . + date_publication: '2022-10-12' + bug_reports: https://github.com/villegar/splash/issues/ + url: https://splash.robertovillegas-diaz.com/ + url_cran: https://CRAN.R-project.org/package=splash + url_git: https://github.com/villegar/splash/ +spldv: + version: 0.1.3 + title: Spatial Models for Limited Dependent Variables + maintainer: Mauricio Sarrias + description: The current version of this package estimates spatial autoregressive + models for binary dependent variables using GMM estimators . + It supports one-step (Pinkse and Slade, 1998) + and two-step GMM estimator along with the linearized GMM estimator proposed by + Klier and McMillen (2008) . It also allows for + either Probit or Logit model and compute the average marginal effects. All these + models are presented in Sarrias and Piras (2023) . + date_publication: '2023-10-11' + bug_reports: https://github.com/gpiras/spldv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spldv + url_git: https://github.com/gpiras/spldv +SPLICE: + version: 1.1.2 + title: |- + Synthetic Paid Loss and Incurred Cost Experience (SPLICE) + Simulator + maintainer: Melantha Wang + description: |- + An extension to the individual claim simulator called 'SynthETIC' + (on CRAN), to simulate the evolution of case estimates of incurred losses + through the lifetime of an insurance claim. The transactional simulation + output now comprises key dates, and both claim payments and revisions of + estimated incurred losses. An initial set of test parameters, designed to + mirror the experience of a real insurance portfolio, were set up and applied + by default to generate a realistic test data set of incurred histories (see + vignette). However, the distributional assumptions used to generate this + data set can be easily modified by users to match their experiences. + Reference: Avanzi B, Taylor G, Wang M (2021) "SPLICE: A Synthetic Paid Loss + and Incurred Cost Experience Simulator" . + date_publication: '2024-02-04' + bug_reports: https://github.com/agi-lab/SPLICE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SPLICE + url_git: https://github.com/agi-lab/SPLICE +splineCox: + version: 0.0.3 + title: |- + A Two-Stage Estimation Approach to Cox Regression Using M-Spline + Function + maintainer: Ren Teranishi + description: |- + Implements a two-stage estimation approach for Cox + regression using five-parameter M-spline functions to model the baseline hazard. It allows + for flexible hazard shapes and model selection based on log-likelihood criteria. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=splineCox + url_git: '' +splines2: + version: 0.5.4 + title: Regression Spline Functions and Classes + maintainer: Wenjie Wang + description: |- + Constructs basis functions of B-splines, M-splines, + I-splines, convex splines (C-splines), periodic splines, + natural cubic splines, generalized Bernstein polynomials, + their derivatives, and integrals (except C-splines) + by closed-form recursive formulas. + It also contains a C++ head-only library integrated with Rcpp. + See Wang and Yan (2021) for details. + date_publication: '2025-02-28' + bug_reports: https://github.com/wenjie2wang/splines2/issues + url: https://wwenjie.org/splines2 + url_cran: https://CRAN.R-project.org/package=splines2 + url_git: https://github.com/wenjie2wang/splines2 +splinetree: + version: 0.2.0 + title: Longitudinal Regression Trees and Forests + maintainer: Anna Neufeld + description: Builds regression trees and random forests for longitudinal or functional + data using a spline projection method. Implements and extends the work of Yu and + Lambert (1999) . This method allows trees + and forests to be built while considering either level and shape or only shape + of response trajectories. + date_publication: '2019-07-18' + bug_reports: https://github.com/anna-neufeld/splinetree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splinetree + url_git: https://github.com/anna-neufeld/splinetree +Splinets: + version: 1.5.1 + title: |- + Functional Data Analysis using Splines and Orthogonal Spline + Bases + maintainer: Krzysztof Podgorski + description: 'Splines are efficiently represented through their Taylor expansion + at the knots. The representation accounts for the support sets and is thus suitable + for sparse functional data. Two cases of boundary conditions are considered: zero-boundary + or periodic-boundary for all derivatives except the last. The periodical splines + are represented graphically using polar coordinates. The B-splines and orthogonal + bases of splines that reside on small total support are implemented. The orthogonal + bases are referred to as ''splinets'' and are utilized for functional data analysis. + Random spline generator is implemented as well as all fundamental algebraic and + calculus operations on splines. The optimal, in the least square sense, functional + fit by ''splinets'' to data consisting of sampled values of functions as well + as splines build over another set of knots is obtained and used for functional + data analysis. The S4-version of the object oriented R is used. , + , .' + date_publication: '2025-01-28' + bug_reports: https://github.com/ranibasna/R-Splinets/issues + url: https://ranibasna.github.io/R-Splinets/ + url_cran: https://CRAN.R-project.org/package=Splinets + url_git: https://github.com/ranibasna/R-Splinets +SPlit: + version: '1.2' + title: Split a Dataset for Training and Testing + maintainer: Akhil Vakayil + description: |- + Procedure to optimally split a dataset for training and testing. + 'SPlit' is based on the method of support points, which is independent of modeling methods. + Please see Joseph and Vakayil (2021) for details. + This work is supported by U.S. National Science Foundation grant DMREF-1921873. + date_publication: '2022-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPlit + url_git: '' +splitfngr: + version: 0.1.2 + title: Combined Evaluation and Split Access of Functions + maintainer: Collin Erickson + description: |2- + + Some R functions, such as optim(), require a function + its gradient passed as separate arguments. When these are + expensive to calculate it may be much faster to calculate + the function (fn) and gradient (gr) together since they often share + many calculations (chain rule). This package allows the user + to pass in a single function that returns both the function + and gradient, then splits (hence 'splitfngr') them + so the results can be accessed + separately. The functions provided allow this to be done with + any number of functions/values, not just for functions and gradients. + date_publication: '2019-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=splitfngr + url_git: '' +SplitGLM: + version: 1.0.5 + title: Split Generalized Linear Models + maintainer: Anthony Christidis + description: |- + Functions to compute split generalized linear models. The approach fits + generalized linear models that split the covariates into groups. The + optimal split of the variables into groups and the regularized estimation + of the coefficients are performed by minimizing an objective function + that encourages sparsity within each group and diversity among them. + Example applications can be found in Christidis et al. (2021) + . + date_publication: '2022-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SplitGLM + url_git: '' +splithalf: + version: 0.8.2 + title: Calculate Task Split Half Reliability Estimates + maintainer: Sam Parsons + description: |- + Estimate the internal consistency of your tasks with a permutation based split-half reliability approach. + Unofficial release name: "I eat stickers all the time, dude!". + date_publication: '2022-08-11' + bug_reports: https://github.com/sdparsons/splithalf + url: '' + url_cran: https://CRAN.R-project.org/package=splithalf + url_git: https://github.com/sdparsons/splithalf +splithalfr: + version: 2.2.2 + title: Estimate Split-Half Reliabilities + maintainer: Thomas Pronk + description: Estimates split-half reliabilities for scoring algorithms of cognitive + tasks and questionnaires. The 'splithalfr' supports researcher-provided scoring + algorithms, with six vignettes illustrating how on included datasets. The package + provides four splitting methods (first-second, odd-even, permutated, Monte Carlo), + the option to stratify splits by task design, a number of reliability coefficients, + and the option to sub-sample data. + date_publication: '2023-09-14' + bug_reports: https://github.com/tpronk/splithalfr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splithalfr + url_git: https://github.com/tpronk/splithalfr +SplitKnockoff: + version: '2.1' + title: Split Knockoffs for Structural Sparsity + maintainer: Yuxuan Chen + description: |- + Split Knockoff is a data adaptive variable selection framework for controlling the + (directional) false discovery rate (FDR) in structural sparsity, where variable + selection on linear transformation of parameters is of concern. This proposed scheme + relaxes the linear subspace constraint to its neighborhood, often known as variable + splitting in optimization. + Simulation experiments can be reproduced following the Vignette. + 'Split Knockoffs' is first defined in Cao et al. (2021) . + date_publication: '2024-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SplitKnockoff + url_git: '' +SplitReg: + version: 1.0.2 + title: Split Regularized Regression + maintainer: Anthony Christidis + description: |- + Functions for computing split regularized estimators defined in Christidis, Lakshmanan, + Smucler and Zamar (2019) . The approach fits linear regression models that + split the set of covariates into groups. The optimal split of the variables into groups and the + regularized estimation of the regression coefficients are performed by minimizing an objective + function that encourages sparsity within each group and diversity among them. + The estimated coefficients are then pooled together to form the final fit. + date_publication: '2020-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SplitReg + url_git: '' +splitSelect: + version: 1.0.3 + title: Best Split Selection Modeling for Low-Dimensional Data + maintainer: Anthony Christidis + description: |- + Functions to generate or sample from all possible splits of features or variables + into a number of specified groups. Also computes the best split selection estimator + (for low-dimensional data) as defined in Christidis, Van Aelst and Zamar (2019) + . + date_publication: '2021-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=splitSelect + url_git: '' +SplitSoftening: + version: 2.1-1 + title: Softening Splits in Decision Trees + maintainer: Jakub Dvorak + description: |- + Allows to produce and use classification trees with soft (probability) splits, + as described in: Dvořák, J. (2019), . + date_publication: '2024-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SplitSoftening + url_git: '' +SplitSplitPlot: + version: 0.0.1 + title: |- + Analysis of Split-Split-Plot Experiments (Analise De + Experimentos Em Parcela Subsubdividida) + maintainer: Alcinei Mistico Azevedo + description: Performs analysis of split-split plot experiments in both completely + randomized and randomized complete block designs. With the results, you can obtain + ANOVA, mean tests, and regression analysis (Este pacote faz a analise de experimentos + em parcela subsubdivididas no delineamento inteiramente casualizado e delineamento + em blocos casualizados. Com resultados e possível obter a ANOVA, testes de medias + e análise de regressao) . + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SplitSplitPlot + url_git: '' +splitstackshape: + version: 1.4.8 + title: Stack and Reshape Datasets After Splitting Concatenated Values + maintainer: Ananda Mahto + description: |- + Online data collection tools like Google Forms often export + multiple-response questions with data concatenated in cells. The + concat.split (cSplit) family of functions splits such data into separate + cells. The package also includes functions to stack groups of columns and + to reshape wide data, even when the data are "unbalanced"---something + which reshape (from base R) does not handle, and which melt and dcast from + reshape2 do not easily handle. + date_publication: '2019-04-21' + bug_reports: http://github.com/mrdwab/splitstackshape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splitstackshape + url_git: http://github.com/mrdwab/splitstackshape +splitTools: + version: 1.0.1 + title: Tools for Data Splitting + maintainer: Michael Mayer + description: |- + Fast, lightweight toolkit for data splitting. Data sets can + be partitioned into disjoint groups (e.g. into training, validation, + and test) or into (repeated) k-folds for subsequent cross-validation. + Besides basic splits, the package supports stratified, grouped as well + as blocked splitting. Furthermore, cross-validation folds for time + series data can be created. See e.g. Hastie et al. (2001) + for the basic background on data + partitioning and cross-validation. + date_publication: '2023-06-06' + bug_reports: https://github.com/mayer79/splitTools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splitTools + url_git: https://github.com/mayer79/splitTools +splm: + version: 1.6-5 + title: Econometric Models for Spatial Panel Data + maintainer: Giovanni Millo + description: ML and GM estimation and diagnostic testing of econometric models for + spatial panel data. + date_publication: '2023-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=splm + url_git: '' +splmm: + version: 1.2.0 + title: Simultaneous Penalized Linear Mixed Effects Models + maintainer: Eli Sun + description: |- + Contains functions that fit linear mixed-effects models + for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection. + The details of the algorithm can be found in Luoying Yang PhD thesis (Yang and Wu 2020). The algorithm implementation + is based on the R package 'lmmlasso'. + Reference: Yang L, Wu TT (2020). Model-Based Clustering of Longitudinal Data in High-Dimensionality. Unpublished thesis. + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=splmm + url_git: '' +splot: + version: 0.5.4 + title: Simplified Plotting for Data Exploration + maintainer: Micah Iserman + description: |- + Automates common plotting tasks to ease data exploration. + Makes density plots (potentially overlaid on histograms), + scatter plots with prediction lines, or bar or line plots with error bars. + For each type, y, or x and y variables can be plotted at levels of other variables, + all with minimal specification. + date_publication: '2023-10-27' + bug_reports: https://github.com/miserman/splot/issues + url: https://miserman.github.io/splot/ + url_cran: https://CRAN.R-project.org/package=splot + url_git: '' +spls: + version: 2.2-3 + title: |- + Sparse Partial Least Squares (SPLS) Regression and + Classification + maintainer: Valentin Todorov + description: |- + Provides functions for fitting a sparse + partial least squares (SPLS) regression and classification + (Chun and Keles (2010) ). + date_publication: '2019-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spls + url_git: '' +splus2R: + version: 1.3-5 + title: Supplemental S-PLUS Functionality in R + maintainer: Stephen Kaluzny + description: |- + Currently there are many functions in S-PLUS that are + missing in R. To facilitate the conversion of S-PLUS packages to R packages, + this package provides some missing S-PLUS functionality in R. + date_publication: '2024-02-18' + bug_reports: https://github.com/spkaluzny/splus2r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splus2R + url_git: https://github.com/spkaluzny/splus2r +splusTimeDate: + version: 2.5.8 + title: Times and Dates from 'S-PLUS' + maintainer: Stephen Kaluzny + description: |- + A collection of classes and methods for working with + times and dates. The code was originally available in 'S-PLUS'. + date_publication: '2024-09-12' + bug_reports: https://github.com/spkaluzny/splusTimeDate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splusTimeDate + url_git: https://github.com/spkaluzny/splusTimeDate +splusTimeSeries: + version: 1.5.7 + title: Time Series from 'S-PLUS' + maintainer: Stephen Kaluzny + description: |- + A collection of classes and methods for working with + indexed rectangular data. The index values can be + calendar (timeSeries class) or numeric (signalSeries class). + Methods are included for aggregation, alignment, merging, and summaries. + The code was originally available in 'S-PLUS'. + date_publication: '2024-09-19' + bug_reports: https://github.com/spkaluzny/splusTimeSeries/issues + url: '' + url_cran: https://CRAN.R-project.org/package=splusTimeSeries + url_git: https://github.com/spkaluzny/splusTimeSeries +splutil: + version: 2022.6.20 + title: Utility Functions for Common Base-R Problems Relating to Lists + maintainer: Richard Aubrey White + description: |- + Utility functions that help with common base-R problems relating to lists. + Lists in base-R are very flexible. This package provides functions to quickly and easily + characterize types of lists. That is, to identify if all elements in a list + are null, data.frames, lists, or fully named lists. Other functionality is provided + for the handling of lists, such as the easy splitting of lists into equally sized + groups, and the unnesting of data.frames within fully named lists. + date_publication: '2022-06-22' + bug_reports: https://github.com/sykdomspulsen-org/splutil/issues + url: https://docs.sykdomspulsen.no/splutil/ + url_cran: https://CRAN.R-project.org/package=splutil + url_git: https://github.com/sykdomspulsen-org/splutil +spm: + version: 1.2.2 + title: Spatial Predictive Modeling + maintainer: Jin Li + description: |- + Introduction to some novel accurate hybrid methods of geostatistical and machine learning methods for spatial predictive modelling. It contains two commonly used geostatistical methods, two machine learning methods, four hybrid methods and two averaging methods. For each method, two functions are provided. One function is for assessing the predictive errors and accuracy of the method based on cross-validation. The other one is for generating spatial predictions using the method. For details please see: Li, J., Potter, A., Huang, Z., Daniell, J. J. and Heap, A. (2010) + Li, J., Heap, A. D., Potter, A., Huang, Z. and Daniell, J. (2011) + Li, J., Heap, A. D., Potter, A. and Daniell, J. (2011) + Li, J., Potter, A., Huang, Z. and Heap, A. (2012) . + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spm + url_git: '' +spm2: + version: 1.1.3 + title: Spatial Predictive Modeling + maintainer: Jin Li + description: An updated and extended version of 'spm' package, by introducing some + further novel functions for modern statistical methods (i.e., generalised linear + models, glmnet, generalised least squares), thin plate splines, support vector + machine, kriging methods (i.e., simple kriging, universal kriging, block kriging, + kriging with an external drift), and novel hybrid methods (228 hybrids plus numerous + variants) of modern statistical methods or machine learning methods with mathematical + and/or univariate geostatistical methods for spatial predictive modelling. For + each method, two functions are provided, with one function for assessing the predictive + errors and accuracy of the method based on cross-validation, and the other for + generating spatial predictions. It also contains a couple of functions for data + preparation and predictive accuracy assessment. + date_publication: '2023-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spm2 + url_git: '' +spMaps: + version: 0.5.0 + title: Europe SpatialPolygonsDataFrame Builder + maintainer: Tatiana Vargas + description: |- + Build custom Europe SpatialPolygonsDataFrame, if you don't know what is + a SpatialPolygonsDataFrame see SpatialPolygons() in 'sp', by example for mapLayout() in 'antaresViz'. + Antares is a powerful software developed by RTE to simulate and study electric power systems + (more information about 'Antares' here: ). + date_publication: '2023-08-31' + bug_reports: https://github.com/rte-antares-rpackage/spMaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spMaps + url_git: https://github.com/rte-antares-rpackage/spMaps +spMC: + version: 0.3.15 + title: Continuous-Lag Spatial Markov Chains + maintainer: Luca Sartore + description: A set of functions is provided for 1) the stratum lengths analysis + along a chosen direction, 2) fast estimation of continuous lag spatial Markov + chains model parameters and probability computing (also for large data sets), + 3) transition probability maps and transiograms drawing, 4) simulation methods + for categorical random fields. More details on the methodology are discussed in + Sartore (2013) and Sartore et al. (2016) . + date_publication: '2023-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spMC + url_git: '' +SPmlficmcm: + version: '1.4' + title: |- + Semiparametric Maximum Likelihood Method for Interactions + Gene-Environment in Case-Mother Control-Mother Designs + maintainer: Moliere Nguile-Makao + description: Implements the method of general semiparametric maximum likelihood + estimation for logistic models in case-mother control-mother designs. + date_publication: '2015-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPmlficmcm + url_git: '' +spmodel: + version: 0.9.0 + title: Spatial Statistical Modeling and Prediction + maintainer: Michael Dumelle + description: Fit, summarize, and predict for a variety of spatial statistical models + applied to point-referenced and areal (lattice) data. Parameters are estimated + using various methods. Additional modeling features include anisotropy, non-spatial + random effects, partition factors, big data approaches, and more. Model-fit statistics + are used to summarize, visualize, and compare models. Predictions at unobserved + locations are readily obtainable. For additional details, see Dumelle et al. (2023) + . + date_publication: '2024-11-06' + bug_reports: https://github.com/USEPA/spmodel/issues + url: https://usepa.github.io/spmodel/ + url_cran: https://CRAN.R-project.org/package=spmodel + url_git: '' +spmoran: + version: 0.3.3 + title: |- + Fast Spatial and Spatio-Temporal Regression using Moran + Eigenvectors + maintainer: Daisuke Murakami + description: 'A collection of functions for estimating spatial and spatio-temporal + regression models. Moran eigenvectors are used as spatial basis functions to efficiently + approximate spatially dependent Gaussian processes (i.e., random effects eigenvector + spatial filtering; see Murakami and Griffith 2015 ). + The implemented models include linear regression with residual spatial dependence, + spatially/spatio-temporally varying coefficient models (Murakami et al., 2017, + 2024; ,), spatially + filtered unconditional quantile regression (Murakami and Seya, 2019 ), + Gaussian and non-Gaussian spatial mixed models through compositionally-warping + (Murakami et al. 2021, ).' + date_publication: '2024-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spmoran + url_git: https://github.com/dmuraka/spmoran +spnaf: + version: 1.1.0 + title: Spatial Network Autocorrelation for Flow Data + maintainer: Youngbin Lee + description: |- + Identify statistically significant flow clusters using the local spatial network autocorrelation statistic G_ij* + proposed by 'Berglund' and 'Karlström' (1999) . + The metric, an extended statistic of 'Getis/Ord' G ('Getis' and 'Ord' 1992) , + detects a group of flows having similar traits in terms of directionality. + You provide OD data and the associated polygon to get results + with several parameters, some of which are defined by spdep package. + date_publication: '2024-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spnaf + url_git: '' +spNetwork: + version: 0.4.4.5 + title: Spatial Analysis on Network + maintainer: Jeremy Gelb + description: |- + Perform spatial analysis on network. + Implement several methods for spatial analysis on network: Network Kernel Density estimation, + building of spatial matrices based on network distance ('listw' objects from 'spdep' package), K functions estimation + for point pattern analysis on network, k nearest neighbours on network, reachable area calculation, and graph generation + References: Okabe et al (2019) ; + Okabe et al (2012, ISBN:978-0470770818);Baddeley et al (2015, ISBN:9781482210200). + date_publication: '2025-01-20' + bug_reports: https://github.com/JeremyGelb/spNetwork/issues + url: https://jeremygelb.github.io/spNetwork/ + url_cran: https://CRAN.R-project.org/package=spNetwork + url_git: '' +SpNMF: + version: 0.1.1 + title: Supervised NMF + maintainer: Yun Cai + description: Non-negative Matrix Factorization(NMF) is a powerful tool for identifying + the key features of microbial communities and a dimension-reduction method. When + we are interested in the differences between the structures of two groups of communities, + supervised NMF(Yun Cai, Hong Gu and Tobby Kenney (2017),) + provides a better way to do this, while retaining all the advantages of NMF -- + such as interpretability, and being based on a simple biological intuition. + date_publication: '2018-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpNMF + url_git: '' +spnn: + version: 1.2.1 + title: Scale Invariant Probabilistic Neural Networks + maintainer: Romin Ebrahimi + description: Scale invariant version of the original PNN proposed by Specht (1990) + with the added functionality of allowing for + smoothing along multiple dimensions while accounting for covariances within the + data set. It is written in the R statistical programming language. Given a data + set with categorical variables, we use this algorithm to estimate the probabilities + of a new observation vector belonging to a specific category. This type of neural + network provides the benefits of fast training time relative to backpropagation + and statistical generalization with only a small set of known observations. + date_publication: '2020-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spnn + url_git: '' +spNNGP: + version: 1.0.1 + title: |- + Spatial Regression Models for Large Datasets using Nearest + Neighbor Gaussian Processes + maintainer: Andrew Finley + description: Fits univariate Bayesian spatial regression models for large datasets + using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee + (2022) , Finley, Datta, Cook, Morton, Andersen, and + Banerjee (2019) , and Datta, Banerjee, Finley, + and Gelfand (2016) . + date_publication: '2024-09-23' + bug_reports: '' + url: https://www.finley-lab.com/ + url_cran: https://CRAN.R-project.org/package=spNNGP + url_git: '' +spocc: + version: 1.2.3 + title: Interface to Species Occurrence Data Sources + maintainer: Hannah Owens + description: |- + A programmatic interface to many species occurrence data sources, + including Global Biodiversity Information Facility ('GBIF'), 'iNaturalist', + 'eBird', Integrated Digitized 'Biocollections' ('iDigBio'), 'VertNet', + Ocean 'Biogeographic' Information System ('OBIS'), and + Atlas of Living Australia ('ALA'). Includes functionality for retrieving + species occurrence data, and combining those data. + date_publication: '2024-03-06' + bug_reports: https://github.com/ropensci/spocc/issues/ + url: https://docs.ropensci.org/spocc/(usermanual) + url_cran: https://CRAN.R-project.org/package=spocc + url_git: https://github.com/ropensci/spocc(devel) +spOccupancy: + version: 0.8.0 + title: |- + Single-Species, Multi-Species, and Integrated Spatial Occupancy + Models + maintainer: Jeffrey Doser + description: Fits single-species, multi-species, and integrated non-spatial and + spatial occupancy models using Markov Chain Monte Carlo (MCMC). Models are fit + using Polya-Gamma data augmentation detailed in Polson, Scott, and Windle (2013) + . Spatial models are fit using either Gaussian + processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. + Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) + and Finley, Datta, and Banerjee (2022) . + Provides functionality for data integration of multiple single-species occupancy + data sets using a joint likelihood framework. Details on data integration are + given in Miller, Pacifici, Sanderlin, and Reich (2019) . + Details on single-species and multi-species models are found in MacKenzie, Nichols, + Lachman, Droege, Royle, and Langtimm (2002) + and Dorazio and Royle , respectively. + date_publication: '2024-12-14' + bug_reports: https://github.com/biodiverse/spOccupancy/issues + url: https://www.doserlab.com/files/spoccupancy-web + url_cran: https://CRAN.R-project.org/package=spOccupancy + url_git: https://github.com/biodiverse/spOccupancy +spoiler: + version: 1.0.0 + title: |- + Blur 'HTML' Elements in 'Shiny' Applications Using + 'Spoiler-Alert.js' + maintainer: Etienne Bacher + description: |- + It can be useful to temporarily hide some text or other HTML elements + in 'Shiny' applications. Building on 'Spoiler-Alert.js', it is possible to select the + elements to hide at startup, to partially reveal them by hovering them, and to + completely show them when clicking on them. + date_publication: '2021-06-07' + bug_reports: https://github.com/etiennebacher/spoiler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spoiler + url_git: https://github.com/etiennebacher/spoiler +spongebob: + version: 0.4.0 + title: 'SpongeBob-Case Converter : spOngEboB-CASe CoNVertER' + maintainer: Jay Qi + description: |- + Convert text (and text in R objects) to Mocking SpongeBob case + and show them + off in fun ways. + CoNVErT TexT (AnD TeXt In r ObJeCtS) To MOCkINg SpoNgebOb CAsE + aND shOw tHem + OFf IN Fun WayS. + date_publication: '2019-03-02' + bug_reports: https://github.com/jayqi/spongebob/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spongebob + url_git: https://github.com/jayqi/spongebob +spongecake: + version: 0.1.2 + title: Transform a Movie into a Synthetic Picture + maintainer: Vincent Guyader + description: Transform a Movie into a Synthetic Picture. A frame every 10 seconds + is summarized into one colour, then every generated colors are stacked together. + date_publication: '2017-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spongecake + url_git: https://github.com/ThinkRstat/spongecake +spooky: + version: 1.4.0 + title: |- + Time Feature Extrapolation Using Spectral Analysis and + Jack-Knife Resampling + maintainer: Giancarlo Vercellino + description: Proposes application of spectral analysis and jack-knife resampling + for multivariate sequence forecasting. The application allows for a fast random + search in a compact space of hyper-parameters composed by Sequence Length and + Jack-Knife Leave-N-Out. + date_publication: '2022-08-13' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/spooky + url_cran: https://CRAN.R-project.org/package=spooky + url_git: '' +spork: + version: 0.3.5 + title: Generalized Label Formatting + maintainer: Tim Bergsma + description: |- + The 'spork' syntax describes + label formatting concisely, supporting + mixed nesting of subscripts and superscripts + to arbitrary depth. It intends to be easy + to read and write in plain text, and easy + to convert to equivalent presentations + in 'plotmath', 'latex', and 'html'. Greek symbols + and a multiplication symbol are explicitly + supported. See ?as_spork and ?as_previews. + date_publication: '2024-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spork + url_git: '' +sport: + version: 0.2.1 + title: Sequential Pairwise Online Rating Techniques + maintainer: Dawid Kałędkowski + description: |- + Calculates ratings for two-player or + multi-player challenges. Methods included in package such as are able to + estimate ratings (players strengths) and their evolution in time, also able to + predict output of challenge. Algorithms are based on Bayesian Approximation + Method, and they don't involve any matrix inversions nor likelihood estimation. + Parameters are updated sequentially, and computation doesn't require any + additional RAM to make estimation feasible. Additionally, base of the package + is written in C++ what makes sport computation even faster. Methods used in the + package refer to Mark E. Glickman (1999) + ; + Mark E. Glickman (2001) ; + Ruby C. Weng, Chih-Jen Lin (2011) ; + W. Penny, Stephen J. Roberts (1999) . + date_publication: '2024-01-08' + bug_reports: https://github.com/gogonzo/sport/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sport + url_git: https://github.com/gogonzo/sport +SPORTSCausal: + version: '1.0' + title: Spillover Time Series Causal Inference + maintainer: Feiyu Yue + description: A time series causal inference model for Randomized Controlled Trial + (RCT) under spillover effect. 'SPORTSCausal' (Spillover Time Series Causal Inference) + separates treatment effect and spillover effect from given responses of experiment + group and control group by predicting the response without treatment. It reports + both effects by fitting the Bayesian Structural Time Series (BSTS) model based + on 'CausalImpact', as described in Brodersen et al. (2015) . + date_publication: '2021-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPORTSCausal + url_git: '' +SportsTour: + version: 0.1.0 + title: |- + Display Tournament Fixtures using Knock Out and Round Robin + Techniques + maintainer: Ankit Tanwar + description: Use of Knock Out and Round Robin Techniques in preparing tournament + fixtures as discussed in the Book Health and Physical Education by 'Dr. V K Sharma'(2018,ISBN:978-93-5272-134-4). + date_publication: '2021-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SportsTour + url_git: '' +sportyR: + version: 2.2.2 + title: Plot Scaled 'ggplot' Representations of Sports Playing Surfaces + maintainer: Ross Drucker + description: |- + Create scaled 'ggplot' representations of playing surfaces. + Playing surfaces are drawn pursuant to rule-book specifications. + This package should be used as a baseline plot for displaying any type of + tracking data. + date_publication: '2024-02-15' + bug_reports: https://github.com/sportsdataverse/sportyR/issues + url: https://sportyr.sportsdataverse.org/ + url_cran: https://CRAN.R-project.org/package=sportyR + url_git: https://github.com/sportsdataverse/sportyR +spotidy: + version: 0.1.0 + title: |- + Providing Convenience Functions to Connect R with the Spotify + API + maintainer: Lennard van Wanrooij + description: |- + Providing convenience functions to connect R with the 'Spotify' application programming interface ('API'). At first it aims to help setting up + the OAuth2.0 Authentication flow. The default output of the get_*() functions is tidy, but optionally the functions could return the raw response from the + 'API' as well. The search_*() and get_*() functions can be combined. See the vignette for more information and examples and the official Spotify for + Developers website for information about the Web 'API'. + date_publication: '2021-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spotidy + url_git: '' +spotifyr: + version: 2.2.5 + title: R Wrapper for the 'Spotify' Web API + maintainer: Daniel Antal + description: |- + An R wrapper for pulling data from the 'Spotify' Web API + in bulk, or post items on a + 'Spotify' user's playlist. + date_publication: '2024-10-24' + bug_reports: https://github.com/charlie86/spotifyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spotifyr + url_git: https://github.com/charlie86/spotifyr +spotoroo: + version: 0.1.5 + title: Spatiotemporal Clustering of Satellite Hot Spot Data + maintainer: Weihao Li + description: An algorithm to cluster satellite hot spot data spatially and temporally. + date_publication: '2024-11-19' + bug_reports: https://github.com/TengMCing/spotoroo/issues + url: https://tengmcing.github.io/spotoroo/ + url_cran: https://CRAN.R-project.org/package=spotoroo + url_git: https://github.com/TengMCing/spotoroo/ +SPOUSE: + version: 0.1.0 + title: Scatter Plots Over-Viewed Using Summary Ellipses + maintainer: Siddhanta Phuyal + description: |- + Summary ellipses superimposed on a scatter plot contain all bi-variate summary + statistics for regression analysis. Furthermore, the outer ellipse flags potential + outliers. Multiple groups can be compared in terms of centers and spreads as illustrated + in the examples. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPOUSE + url_git: '' +SPPcomb: + version: '0.1' + title: Combining Different Spatial Datasets in Cancer Risk Estimation + maintainer: Ming Wang + description: |- + We propose a novel two-step procedure to combine epidemiological + data obtained from diverse sources with the aim to quantify risk factors + affecting the probability that an individual develops certain disease such as + cancer. See Hui Huang, Xiaomei Ma, Rasmus Waagepetersen, Theodore R. Holford, + Rong Wang, Harvey Risch, Lloyd Mueller & Yongtao Guan (2014) A New Estimation Approach + for Combining Epidemiological Data From Multiple Sources, Journal of the American Statistical + Association, 109:505, 11-23, . + date_publication: '2016-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPPcomb + url_git: '' +spphpr: + version: 1.0.0 + title: Spring Phenological Prediction + maintainer: Peijian Shi + description: Predicts the occurrence times (in day-of-year) of spring phenological + events. Three methods, including the accumulated degree days (ADD) method, the + accumulated days transferred to a standardized temperature (ADTS) method, and + the accumulated developmental progress (ADP) method, were used. See Shi et al. + (2017a) and Shi et al. (2017b) + for details. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spphpr + url_git: '' +SpPOP: + version: 0.1.0 + title: |- + Generation of Spatial Population under Different Levels of + Relationships among Variables + maintainer: Nobin Chandra Paul + description: |- + The developed package can be used to generate a spatial population for different + levels of relationships among the dependent and auxiliary variables along with spatially + varying model parameters. A spatial layout is designed as a [0,k-1]x[0,k-1] square region on which observations + are collected at (k x k) lattice points with a unit distance between any two neighbouring points along the horizontal + and vertical axes. For method details see Chao, Liu., Chuanhua, Wei. and Yunan, Su. (2018).. + The generated spatial population can be utilized in Geographically Weighted Regression model based analysis for studying the + spatially varying relationships among the variables. Furthermore, various statistical analysis can be performed on this spatially + generated data. + date_publication: '2023-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpPOP + url_git: '' +spqdep: + version: 0.1.3.5 + title: |- + Testing for Spatial Independence of Cross-Sectional Qualitative + Data + maintainer: Fernando Lopez + description: Testing for Spatial Dependence of Qualitative Data in Cross Section. + The list of functions includes join-count tests, Q test, spatial scan test, similarity + test and spatial runs test. The methodology of these models can be found in + and . + date_publication: '2025-01-08' + bug_reports: https://github.com/f8l5h9/spqdep/issues + url: https://f8l5h9.github.io/spqdep/ + url_cran: https://CRAN.R-project.org/package=spqdep + url_git: '' +spray: + version: 1.0-27 + title: Sparse Arrays and Multivariate Polynomials + maintainer: Robin K. S. Hankin + description: |- + Sparse arrays interpreted as multivariate polynomials. + Uses 'disordR' discipline (Hankin, 2022, + ). To cite the package in + publications please use Hankin (2022) . + date_publication: '2025-01-29' + bug_reports: https://github.com/RobinHankin/spray/issues + url: https://robinhankin.github.io/spray/ + url_cran: https://CRAN.R-project.org/package=spray + url_git: https://github.com/RobinHankin/spray +spreadr: + version: 0.2.0 + title: Simulating Spreading Activation in a Network + maintainer: Cynthia Siew + description: 'The notion of spreading activation is a prevalent metaphor in the + cognitive sciences. This package provides the tools for cognitive scientists and + psychologists to conduct computer simulations that implement spreading activation + in a network representation. The algorithmic method implemented in ''spreadr'' + subroutines follows the approach described in Vitevitch, Ercal, and Adagarla (2011, + Frontiers), who viewed activation as a fixed cognitive resource that could spread + among nodes that were connected to each other via edges or connections (i.e., + a network). See Vitevitch, M. S., Ercal, G., & Adagarla, B. (2011). Simulating + retrieval from a highly clustered network: Implications for spoken word recognition. + Frontiers in Psychology, 2, 369. and Siew, C. S. + Q. (2019). spreadr: A R package to simulate spreading activation in a network. + Behavior Research Methods, 51, 910-929. .' + date_publication: '2021-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spreadr + url_git: '' +SPREDA: + version: '1.1' + title: Statistical Package for Reliability Data Analysis + maintainer: Yili Hong + description: The Statistical Package for REliability Data Analysis (SPREDA) implements + recently-developed statistical methods for the analysis of reliability data. Modern + technological developments, such as sensors and smart chips, allow us to dynamically + track product/system usage as well as other environmental variables, such as temperature + and humidity. We refer to these variables as dynamic covariates. The package contains + functions for the analysis of time-to-event data with dynamic covariates and degradation + data with dynamic covariates. The package also contains functions that can be + used for analyzing time-to-event data with right censoring, and with left truncation + and right censoring. Financial support from NSF and DuPont are acknowledged. + date_publication: '2018-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPREDA + url_git: '' +SPreg: + version: '1.0' + title: Bias Reduction in the Skew-Probit Model for a Binary Response + maintainer: DongHyuk Lee + description: |- + Provides a function for the estimation of parameters + in a binary regression with the skew-probit link function. + Naive MLE, Jeffrey type of prior and Cauchy prior type of penalization are implemented, + as described in DongHyuk Lee and Samiran Sinha (2019+) . + date_publication: '2019-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPreg + url_git: '' +spreval: + version: 1.1.0 + title: Evaluation of Sprinkler Irrigation Uniformity and Efficiency + maintainer: Garry Grabow + description: |- + Processing and analysis of field collected or simulated sprinkler + system catch data (depths) to characterize irrigation uniformity and efficiency using + standard and other measures. Standard measures include the Christiansen coefficient + of uniformity (CU) as found in Christiansen, J.E.(1942, ISBN:0138779295, + "Irrigation by Sprinkling"); and distribution uniformity (DU), potential + efficiency of the low quarter (PELQ), and application efficiency of the low quarter (AELQ) + that are implementations of measures of the same notation in Keller, J. and Merriam, + J.L. (1978) "Farm Irrigation System Evaluation: A Guide for Management" + . spreval::DU.lh is similar to spreval::DU + but is the distribution uniformity of the low half instead of low quarter as in DU. + spreval::PELQT is a version of spreval::PELQ adapted for traveling systems instead + of lateral move or solid-set sprinkler systems. The function spreval::eff is + analogous to the method used to compute application efficiency for furrow irrigation + presented in Walker, W. and Skogerboe, G.V. (1987,ISBN:0138779295, "Surface + Irrigation: Theory and Practice"),that uses piecewise integration of infiltrated + depth compared against soil-moisture deficit (SMD), when the argument "target" + is set equal to SMD. The other functions contained in the package provide + graphical representation of sprinkler system uniformity, and other standard + univariate parametric and non-parametric statistical measures as applied to + sprinkler system catch depths. A sample data set of field test data spreval::catchcan + (catch depths) is provided and is used in examples and vignettes. Agricultural systems + emphasized, but this package can be used for landscape irrigation evaluation, and a + landscape (turf) vignette is included as an example application. + date_publication: '2022-03-23' + bug_reports: https://github.com/glgrabow/spreval/issues + url: https://glgrabow.github.io/spreval/ + url_cran: https://CRAN.R-project.org/package=spreval + url_git: '' +sprex: + version: 1.4.1 + title: Calculate Species Richness and Extrapolation Metrics + maintainer: Eric Archer + description: |- + Calculate species richness functions for rarefaction and + extrapolation. + date_publication: '2016-04-16' + bug_reports: https://github.com/EricArcher/sprex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sprex + url_git: '' +springer: + version: 0.1.9 + title: |- + Sparse Group Variable Selection for Gene-Environment + Interactions in the Longitudinal Study + maintainer: Fei Zhou + description: Recently, regularized variable selection has emerged as a powerful + tool to identify and dissect gene-environment interactions. Nevertheless, in longitudinal + studies with high dimensional genetic factors, regularization methods for G×E + interactions have not been systematically developed. In this package, we provide + the implementation of sparse group variable selection, based on both the quadratic + inference function (QIF) and generalized estimating equation (GEE), to accommodate + the bi-level selection for longitudinal G×E studies with high dimensional genomic + features. Alternative methods conducting only the group or individual level selection + have also been included. The core modules of the package have been developed in + C++. + date_publication: '2024-02-01' + bug_reports: https://github.com/feizhoustat/springer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=springer + url_git: https://github.com/feizhoustat/springer +springpheno: + version: 0.5.0 + title: Spring Phenological Indices + maintainer: Adrienne M. Wootten + description: |- + Computes the extended spring indices (SI-x) and false spring + exposure indices (FSEI). The SI-x indices are standard indices used for + analysis in spring phenology studies. In addition, the FSEI is also from + research on the climatology of false springs and adjusted to include an + early and late false spring exposure index. The indices include the + first leaf index, first bloom index, and false spring exposure indices, + along with all calculations for all functions needed to calculate + each index. The main function returns all indices, but each function can + also be run separately. + Allstadt et al. (2015) + Ault et al. (2015) + Peterson and Abatzoglou (2014) + Schwarz et al. (2006) + Schwarz et al. (2013) . + date_publication: '2021-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=springpheno + url_git: '' +spRingsteen: + version: 0.1.0 + title: All Things Data and Springsteen + maintainer: Joey O'Brien + description: |- + An R data package containing setlists from all Bruce Springsteen concerts over 1973-2021. + Also includes all his song details such as lyrics and albums. Data extracted from: + . + date_publication: '2022-09-15' + bug_reports: https://github.com/obrienjoey/spRingsteen/issues + url: https://obrienjoey.github.io/spRingsteen/ + url_cran: https://CRAN.R-project.org/package=spRingsteen + url_git: https://github.com/obrienjoey/spRingsteen +sprintr: + version: 0.9.0 + title: Sparse Reluctant Interaction Modeling + maintainer: Guo Yu + description: An implementation of a computationally efficient method to fit large-scale + interaction models based on the reluctant interaction selection principle. The + method and its properties are described in greater depth in Yu, G., Bien, J., + and Tibshirani, R.J. (2019) "Reluctant interaction modeling", which is available + at . + date_publication: '2019-08-24' + bug_reports: https://github.com/hugogogo/sprintr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sprintr + url_git: '' +sprtt: + version: 0.2.0 + title: Sequential Probability Ratio Tests Toolbox + maintainer: Meike Steinhilber + description: |- + It is a toolbox for Sequential Probability Ratio Tests (SPRT), Wald (1945) . + SPRTs are applied to the data during the sampling process, ideally after each observation. + At any stage, the test will return a decision to either continue sampling or terminate and accept one of the specified hypotheses. + The seq_ttest() function performs one-sample, two-sample, and paired t-tests for testing one- and two-sided hypotheses (Schnuerch & Erdfelder (2019) ). + The seq_anova() function allows to perform a sequential one-way fixed effects ANOVA (Steinhilber et al. (2023) ). + Learn more about the package by using vignettes "browseVignettes(package = "sprtt")" or go to the website . + date_publication: '2023-07-06' + bug_reports: https://github.com/MeikeSteinhilber/sprtt/issues + url: https://meikesteinhilber.github.io/sprtt/ + url_cran: https://CRAN.R-project.org/package=sprtt + url_git: '' +sps: + version: 0.6.0 + title: Sequential Poisson Sampling + maintainer: Steve Martin + description: |- + Sequential Poisson sampling is a variation of Poisson sampling for + drawing probability-proportional-to-size samples with a given number of + units, and is commonly used for price-index surveys. This package gives + functions to draw stratified sequential Poisson samples according to the + method by Ohlsson (1998, ISSN:0282-423X), as well as other order sample + designs by Rosén (1997, ), and generate + appropriate bootstrap replicate weights according to the generalized + bootstrap method by Beaumont and Patak + (2012, ). + date_publication: '2025-02-09' + bug_reports: https://github.com/marberts/sps/issues + url: https://marberts.github.io/sps/ + url_cran: https://CRAN.R-project.org/package=sps + url_git: https://github.com/marberts/sps +spsComps: + version: 0.3.3.0 + title: '''systemPipeShiny'' UI and Server Components' + maintainer: Le Zhang + description: The systemPipeShiny (SPS) framework comes with many UI and server components. + However, installing the whole framework is heavy and takes some time. If you would + like to use UI and server components from SPS in your own Shiny apps, do not hesitate + to try this package. + date_publication: '2023-07-12' + bug_reports: https://github.com/lz100/spsComps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spsComps + url_git: https://github.com/lz100/spsComps +spselect: + version: 0.0.1 + title: Selecting Spatial Scale of Covariates in Regression Models + maintainer: Lauren Grant + description: Fits spatial scale (SS) forward stepwise regression, SS incremental + forward stagewise regression, SS least angle regression (LARS), and SS lasso models. All + area-level covariates are considered at all available scales to enter a model, + but the SS algorithms are constrained to select each area-level covariate at a + single spatial scale. + date_publication: '2016-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spselect + url_git: '' +spsh: + version: 1.1.0 + title: |- + Estimation and Prediction of Parameters of Various Soil + Hydraulic Property Models + maintainer: Tobias KD Weber + description: |- + Estimates model parameters of soil hydraulic property functions by inverting measured data. A wide range of hydraulic models, weighting schemes, + global optimization algorithms, Markov chain Monte Carlo samplers, and extended statistical analyses of results are provided. + Prediction of soil hydraulic property model parameters and common soil properties using pedotransfer functions is facilitated. + Parameter estimation is based on identically and independentally distributed (weighted) model residuals, and simple model selection criteria (Hoege, M., Woehling, T., and Nowak, W. (2018) ) can be calculated. + The included models are the van Genuchten-Mualem in its unimodal, bimodal and trimodal form, the the Kosugi 2 parametric-Mualem model, and the Fredlund-Xing model. + All models can be extended to account for non-capillary water storage and conductivity (Weber, T.K.D., Durner, W., Streck, T. and Diamantopoulos, E. (2019) . + The isothermal vapour conductivity (Saito, H., Simunek, J. and Mohanty, B.P. (2006) ) is calculated based on + volumetric air space and a selection of different tortuosity models: + (Grable, A.R., Siemer, E.G. (1968) , Lai, S.H., Tiedje J.M., Erickson, E. (1976) , + Moldrup, P., Olesen, T., Rolston, D.E., and Yamaguchi, T. (1997) , Moldrup, P., Olesen, T., Yoshikawa, S., Komatsu, T., and Rolston, D.E. (2004) , + Moldrup, P., Olesen, T., Yoshikawa, S., Komatsu, T., and Rolston, D.E. (2005) , Millington, R.J., Quirk, J.P. (1961) , + Penman, H.L. (1940) , and Xu, X, Nieber, J.L. Gupta, S.C. (1992) ). + date_publication: '2020-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spsh + url_git: '' +SPSL: + version: 0.1-9 + title: Site Percolation on Square Lattices (SPSL) + maintainer: Pavel V. Moskalev + description: |- + Provides basic functionality for labeling + iso- & anisotropic percolation clusters on 2D & 3D square lattices + with various lattice sizes, occupation probabilities, von Neumann & + Moore (1,d)-neighborhoods, and random variables weighting + the percolation lattice sites. + date_publication: '2019-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SPSL + url_git: '' +SPSP: + version: 0.2.0 + title: Selection by Partitioning the Solution Paths + maintainer: Xiaorui (Jeremy) Zhu + description: |- + An implementation of the feature Selection procedure by Partitioning the entire Solution Paths + (namely SPSP) to identify the relevant features rather than using a single tuning parameter. + By utilizing the entire solution paths, this procedure can obtain better selection accuracy than + the commonly used approach of selecting only one tuning parameter based on existing criteria, + cross-validation (CV), generalized CV, AIC, BIC, and extended BIC (Liu, Y., & Wang, P. (2018) + ). It is more stable and accurate (low false positive and + false negative rates) than other variable selection approaches. In addition, it can be flexibly + coupled with the solution paths of Lasso, adaptive Lasso, ridge regression, and other penalized + estimators. + date_publication: '2023-10-22' + bug_reports: https://github.com/XiaoruiZhu/SPSP/issues + url: https://xiaorui.site/SPSP/ + url_cran: https://CRAN.R-project.org/package=SPSP + url_git: https://github.com/XiaoruiZhu/SPSP +spStack: + version: 1.0.1 + title: Bayesian Geostatistics Using Predictive Stacking + maintainer: Soumyakanti Pan + description: |- + Fits Bayesian hierarchical spatial process models for + point-referenced Gaussian, Poisson, binomial, and binary data using stacking + of predictive densities. It involves sampling from analytically available + posterior distributions conditional upon some candidate values of the + spatial process parameters and, subsequently assimilate inference from these + individual posterior distributions using Bayesian predictive stacking. Our + algorithm is highly parallelizable and hence, much faster than traditional + Markov chain Monte Carlo algorithms while delivering competitive predictive + performance. See Zhang, Tang, and Banerjee (2024) + , and, Pan, Zhang, Bradley, and Banerjee + (2024) for details. + date_publication: '2024-10-08' + bug_reports: https://github.com/SPan-18/spStack-dev/issues + url: https://span-18.github.io/spStack-dev/ + url_cran: https://CRAN.R-project.org/package=spStack + url_git: https://github.com/SPan-18/spStack-dev +spsur: + version: 1.0.2.5 + title: Spatial Seemingly Unrelated Regression Models + maintainer: Roman Minguez + description: |- + A collection of functions to test and estimate Seemingly + Unrelated Regression (usually called SUR) models, with spatial structure, by maximum + likelihood and three-stage least squares. The package estimates the + most common spatial specifications, that is, SUR with Spatial Lag of + X regressors (called SUR-SLX), SUR with Spatial Lag Model (called SUR-SLM), + SUR with Spatial Error Model (called SUR-SEM), SUR with Spatial Durbin Model (called SUR-SDM), + SUR with Spatial Durbin Error Model (called SUR-SDEM), + SUR with Spatial Autoregressive terms and Spatial Autoregressive + Disturbances (called SUR-SARAR), SUR-SARAR with Spatial Lag of X + regressors (called SUR-GNM) and SUR with Spatially Independent Model (called SUR-SIM). + The methodology of these models can be found in next references + Minguez, R., Lopez, F.A., and Mur, J. (2022) + Mur, J., Lopez, F.A., and Herrera, M. (2010) + Lopez, F.A., Mur, J., and Angulo, A. (2014) . + date_publication: '2022-10-29' + bug_reports: https://github.com/rominsal/spsur/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spsur + url_git: '' +spsurv: + version: 1.0.0 + title: Bernstein Polynomial Based Semiparametric Survival Analysis + maintainer: Renato Panaro + description: A set of reliable routines to ease semiparametric survival regression + modeling based on Bernstein polynomials. 'spsurv' includes proportional hazards, + proportional odds and accelerated failure time frameworks for right-censored data. + RV Panaro (2020) . + date_publication: '2020-03-31' + bug_reports: https://github.com/rvpanaro/spsurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spsurv + url_git: '' +spsurvey: + version: 5.5.1 + title: Spatial Sampling Design and Analysis + maintainer: Michael Dumelle + description: A design-based approach to statistical inference, with a focus on spatial + data. Spatially balanced samples are selected using the Generalized Random Tessellation + Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources + (point geometries) and infinite resources (linear / linestring and areal / polygon + geometries) and flexibly accommodates a diverse set of sampling design features, + including stratification, unequal inclusion probabilities, proportional (to size) + inclusion probabilities, legacy (historical) sites, a minimum distance between + sites, and two options for replacement sites (reverse hierarchical order and nearest + neighbor). Data are analyzed using a wide range of analysis functions that perform + categorical variable analysis, continuous variable analysis, attributable risk + analysis, risk difference analysis, relative risk analysis, change analysis, and + trend analysis. spsurvey can also be used to summarize objects, visualize objects, + select samples that are not spatially balanced, select panel samples, measure + the amount of spatial balance in a sample, adjust design weights, and more. For + additional details, see Dumelle et al. (2023) . + date_publication: '2024-01-09' + bug_reports: https://github.com/USEPA/spsurvey/issues + url: https://usepa.github.io/spsurvey/ + url_cran: https://CRAN.R-project.org/package=spsurvey + url_git: https://github.com/USEPA/spsurvey +spsUtil: + version: 0.2.2 + title: '''systemPipeShiny'' Utility Functions' + maintainer: Le Zhang + description: The systemPipeShiny (SPS) framework comes with many useful utility + functions. However, installing the whole framework is heavy and takes some time. + If you like only a few useful utility functions from SPS, install this package + is enough. + date_publication: '2021-10-30' + bug_reports: https://github.com/lz100/spsUtil/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spsUtil + url_git: https://github.com/lz100/spsUtil +spTDyn: + version: 2.0.3 + title: Spatially Varying and Spatio-Temporal Dynamic Linear Models + maintainer: K. Shuvo Bakar + description: 'Fits, spatially predicts, and temporally forecasts space-time data + using Gaussian Process (GP): (1) spatially varying coefficient process models + and (2) spatio-temporal dynamic linear models. Bakar et al., (2016). Bakar et + al., (2015).' + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spTDyn + url_git: '' +SpTe2M: + version: 1.0.3 + title: Nonparametric Modeling and Monitoring of Spatio-Temporal Data + maintainer: Kai Yang + description: Spatio-temporal data have become increasingly popular in many research + fields. Such data often have complex structures that are difficult to describe + and estimate. This package provides reliable tools for modeling complicated spatio-temporal + data. It also includes tools of online process monitoring to detect possible change-points + in a spatio-temporal process over time. More specifically, the package implements + the spatio-temporal mean estimation procedure described in Yang and Qiu (2018) + , the spatio-temporal covariance estimation procedure discussed + in Yang and Qiu (2019) , the three-step method for the joint + estimation of spatio-temporal mean and covariance functions suggested by Yang + and Qiu (2022) , the spatio-temporal disease surveillance + method discussed in Qiu and Yang (2021) that can accommodate + the covariate effect, the spatial-LASSO-based process monitoring method proposed + by Qiu and Yang (2023) , and the online spatio-temporal + disease surveillance method described in Yang and Qiu (2020) . + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SpTe2M + url_git: '' +spThin: + version: 0.2.0 + title: |- + Functions for Spatial Thinning of Species Occurrence Records for + Use in Ecological Models + maintainer: Matthew E. Aiello-Lammens + description: |- + A set of functions that can be used to spatially thin + species occurrence data. The resulting thinned data can be used in ecological + modeling, such as ecological niche modeling. + date_publication: '2019-11-15' + bug_reports: https://github.com/mlammens/spThin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=spThin + url_git: '' +spTimer: + version: 3.3.3 + title: Spatio-Temporal Bayesian Modelling + maintainer: K. Shuvo Bakar + description: Fits, spatially predicts and temporally forecasts large amounts of + space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian + Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) + based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) . + date_publication: '2024-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spTimer + url_git: '' +sptotal: + version: 1.0.1 + title: Predicting Totals and Weighted Sums from Spatial Data + maintainer: Matt Higham + description: Performs predictions of totals and weighted sums, or finite population + block kriging, on spatial data using the methods in Ver Hoef (2008) . + The primary outputs are an estimate of the total, mean, or weighted sum in the + region, an estimated prediction variance, and a plot of the predicted and observed + values. This is useful primarily to users with ecological data that are counts + or densities measured on some sites in a finite area of interest. Spatial prediction + for the total count or average density in the entire region can then be done using + the functions in this package. + date_publication: '2022-12-11' + bug_reports: https://github.com/highamm/sptotal/issues + url: https://highamm.github.io/sptotal/index.html + url_cran: https://CRAN.R-project.org/package=sptotal + url_git: '' +spup: + version: 1.4-0 + title: Spatial Uncertainty Propagation Analysis + maintainer: Kasia Sawicka + description: |- + Uncertainty propagation analysis in spatial environmental modelling following methodology + described in Heuvelink et al. (2007) + and Brown and Heuvelink (2007) . The package provides functions + for examining the uncertainty propagation starting from input data and model parameters, + via the environmental model onto model outputs. The functions include uncertainty model specification, + stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. + Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. + Spatial auto-correlation within an attribute and cross-correlation between attributes is accommodated for. + The MC realizations may be used as input to the environmental models called from R, or externally. + date_publication: '2024-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spup + url_git: '' +spuRs: + version: 2.0.2 + title: |- + Functions and Datasets for "Introduction to Scientific + Programming and Simulation Using R" + maintainer: Andrew Robinson + description: Provides functions and datasets from Jones, O.D., R. Maillardet, and + A.P. Robinson. 2014. An Introduction to Scientific Programming and Simulation, + Using R. 2nd Ed. Chapman And Hall/CRC. + date_publication: '2018-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=spuRs + url_git: '' +SPUTNIK: + version: 1.4.2 + title: |- + Spatially Automatic Denoising for Imaging Mass Spectrometry + Toolkit + maintainer: Paolo Inglese + description: |- + Set of tools for peak filtering of mass spectrometry + imaging data based on spatial distribution of signal. Given a + region-of-interest, representing the spatial region where the informative + signal is expected to be localized, a series of filters determine which peak + signals are characterized by an implausible spatial distribution. The filters + reduce the dataset dimension and increase its information vs noise ratio, + improving the quality of the unsupervised analysis results, reducing data + dimension and simplifying the chemical interpretation. + The methods are described in Inglese P. et al (2019) . + date_publication: '2024-04-16' + bug_reports: https://github.com/paoloinglese/SPUTNIK/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SPUTNIK + url_git: https://github.com/paoloinglese/SPUTNIK +SPYvsSPY: + version: 0.1.1 + title: Spy vs. Spy Data + maintainer: Steven E. Pav + description: |- + Data on the Spy vs. Spy comic strip of Mad magazine, created and + written by Antonio Prohias. + date_publication: '2017-10-02' + bug_reports: https://github.com/shabbychef/SPYvsSPY/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SPYvsSPY + url_git: https://github.com/shabbychef/SPYvsSPY +SQI: + version: 0.1.0 + title: Soil Quality Index + maintainer: Dr. Owais Ali Wani + description: The overall performance of soil ecosystem services and productivity + greatly relies on soil health, making it a crucial indicator. The evaluation of + soil physical, chemical, and biological parameters is necessary to determine the + overall soil quality index. In our package, three commonly used methods, including + linear scoring, regression-based, and principal component-based soil quality indexing, + are employed to calculate the soil quality index. This package has been developed + using concept of Bastida et al. (2008) and Doran and Parkin (1994) + . + date_publication: '2023-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SQI + url_git: '' +SQL: + version: 0.1.1 + title: Executes 'SQL' Statements + maintainer: Jean-Luc Lipatz + description: Runs 'SQL' statements on in-memory data frames within a temporary in-memory + 'duckdb' data base. + date_publication: '2023-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SQL + url_git: '' +sqlcaser: + version: 0.2.0 + title: '''SQL'' Case Statement Generator' + maintainer: Leoson Hoay + description: |- + Includes built-in methods for generating long 'SQL' CASE statements, + and other 'SQL' statements that may otherwise be arduous to construct + by hand. The generated statement can easily be concatenated to string + literals to form queries to 'SQL'-like databases, such as when using + the 'RODBC' package. The current methods include casewhen() for building + CASE statements, inlist() for building IN statements, and + updatetable() for building UPDATE statements. + date_publication: '2023-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sqlcaser + url_git: '' +sqldf: + version: 0.4-11 + title: Manipulate R Data Frames Using SQL + maintainer: G. Grothendieck + description: |- + The sqldf() function is typically passed a single argument which + is an SQL select statement where the table names are ordinary R data + frame names. sqldf() transparently sets up a database, imports the + data frames into that database, performs the SQL select or other + statement and returns the result using a heuristic to determine which + class to assign to each column of the returned data frame. The sqldf() + or read.csv.sql() functions can also be used to read filtered files + into R even if the original files are larger than R itself can handle. + 'RSQLite', 'RH2', 'RMySQL' and 'RPostgreSQL' backends are supported. + date_publication: '2017-06-28' + bug_reports: https://github.com/ggrothendieck/sqldf/issues + url: https://groups.google.com/group/sqldf + url_cran: https://CRAN.R-project.org/package=sqldf + url_git: https://github.com/ggrothendieck/sqldf +SQLFormatteR: + version: 0.0.1 + title: Format SQL Queries + maintainer: Morgan Durand + description: |- + A convenient interface for formatting 'SQL' queries directly + within 'R'. It acts as a wrapper around the 'sql_format' Rust crate. + The package allows you to format 'SQL' code with customizable options, + including indentation, case formatting, and more, ensuring your 'SQL' + queries are clean, readable, and consistent. + date_publication: '2025-02-04' + bug_reports: https://github.com/dataupsurge/SQLFormatteR/issues + url: https://dataupsurge.github.io/SQLFormatteR/ + url_cran: https://CRAN.R-project.org/package=SQLFormatteR + url_git: https://github.com/dataupsurge/SQLFormatteR +sqlhelper: + version: 0.2.1 + title: Easier 'SQL' Integration + maintainer: Matthew Roberts + description: Execute files of 'SQL' and manage database connections. 'SQL' statements + and queries may be interpolated with string literals. Execution of individual + statements and queries may be controlled with keywords. Multiple connections may + be defined with 'YAML' and accessed by name. + date_publication: '2024-01-21' + bug_reports: https://github.com/majerr/sqlhelper/issues + url: https://majerr.github.io/sqlhelper/dev/ + url_cran: https://CRAN.R-project.org/package=sqlhelper + url_git: https://github.com/majerr/sqlhelper/ +sqlHelpers: + version: 0.1.2 + title: Collection of 'SQL' Utilities for 'T-SQL' and 'Postgresql' + maintainer: Timothy Conwell + description: |- + Includes functions for interacting with common meta data fields, + writing insert statements, calling functions, and more for 'T-SQL' and 'Postgresql'. + date_publication: '2023-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sqlHelpers + url_git: '' +sqliter: + version: 0.1.0 + title: Connection wrapper to SQLite databases + maintainer: Wilson Freitas + description: |- + sqliter helps users, mainly data munging practioneers, to organize + their sql calls in a clean structure. It simplifies the process of + extracting and transforming data into useful formats. + date_publication: '2014-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sqliter + url_git: https://github.com/wilsonfreitas/sqliter/ +sqliteutils: + version: 0.1.0 + title: Utility Functions for 'SQLite' + maintainer: Bruno Crotman + description: A tool for working with 'SQLite' databases. 'SQLite' has some idiosyncrasies + and limitations that impose some hurdles to the R developer who is using this + database as a repository. For instance, 'SQLite' doesn't have a date type and + 'sqliteutils' has some functions to deal with that. + date_publication: '2021-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sqliteutils + url_git: '' +SQLove: + version: 0.0.4 + title: Execute 'SQL' Scripts in 'R' Containing Multiple Queries + maintainer: Kerns Sam + description: |- + The nature of working with structured query language ('SQL') scripts + efficiently often requires the creation of temporary tables and there + are few clean and simple 'R' 'SQL' execution approaches that allow + you to complete this kind of work with the 'R' environment. This + package seeks to give 'SQL' implementations in 'R' a little love + by deploying functions that allow you to deploy complex 'SQL' + scripts within a typical 'R' workflow. + date_publication: '2023-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SQLove + url_git: '' +sqlparseR: + version: 0.1.0 + title: |- + Wrapper for 'Python' Module 'sqlparse': Parse, Split, and Format + 'SQL' + maintainer: Michael Simmler + description: Wrapper for the non-validating 'SQL' parser 'Python' module 'sqlparse' + . It allows parsing, splitting, and + formatting 'SQL' statements. + date_publication: '2019-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sqlparseR + url_git: '' +SqlRender: + version: 1.19.1 + title: Rendering Parameterized SQL and Translation to Dialects + maintainer: Martijn Schuemie + description: |- + A rendering tool for parameterized SQL that also translates into + different SQL dialects. These dialects include 'Microsoft SQL Server', 'Oracle', + 'PostgreSql', 'Amazon RedShift', 'Apache Impala', 'IBM Netezza', 'Google BigQuery', 'Microsoft PDW', 'Snowflake', + 'Azure Synapse Analytics Dedicated', 'Apache Spark', 'SQLite', and 'InterSystems IRIS'. + date_publication: '2024-11-29' + bug_reports: https://github.com/OHDSI/SqlRender/issues + url: https://ohdsi.github.io/SqlRender/ + url_cran: https://CRAN.R-project.org/package=SqlRender + url_git: https://github.com/OHDSI/SqlRender +sqlscore: + version: 0.1.4 + title: Utilities for Generating SQL Queries from Model Objects + maintainer: William Brannon + description: |- + Provides utilities for generating SQL queries (particularly CREATE + TABLE statements) from R model objects. The most important use case is + generating SQL to score a generalized linear model or related model + represented as an R object, in which case the package handles parsing + formula operators and including the model's response function. + date_publication: '2019-03-17' + bug_reports: https://github.com/wwbrannon/sqlscore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sqlscore + url_git: https://github.com/wwbrannon/sqlscore/ +sqlstrings: + version: 1.0.0 + title: Map 'SQL' Code to R Lists + maintainer: Dejan Prvulovic + description: Provides a helper function, to bulk read 'SQL' code from separate files + and load it into an 'R' list, where the list elements contain the individual statements + and queries as strings. This works by annotating the 'SQL' code with a name comment, + which also will be the name of the list element. + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sqlstrings + url_git: '' +sqltargets: + version: 0.2.1 + title: '''Targets'' Extension for ''SQL'' Queries' + maintainer: David Ranzolin + description: |- + Provides an extension for 'SQL' queries as separate file + within 'targets' pipelines. The shorthand creates two targets, + the query file and the query result. + date_publication: '2024-10-02' + bug_reports: https://github.com/daranzolin/sqltargets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sqltargets + url_git: https://github.com/daranzolin/sqltargets +SQMtools: + version: 1.6.3 + title: Analyze Results Generated by the 'SqueezeMeta' Pipeline + maintainer: Fernando Puente-Sánchez + description: '''SqueezeMeta'' is a versatile pipeline for the automated analysis + of metagenomics/metatranscriptomics data (). + This package provides functions loading ''SqueezeMeta'' results into R, filtering + them based on different criteria, and visualizing the results using basic plots. + The ''SqueezeMeta'' project (and any subsets of it generated by the different + filtering functions) is parsed into a single object, whose different components + (e.g. tables with the taxonomic or functional composition across samples, contig/gene + abundance profiles) can be easily analyzed using other R packages such as ''vegan'' + or ''DESeq2''. The methods in this package are further described in Puente-Sánchez + et al., (2020) .' + date_publication: '2023-09-18' + bug_reports: https://github.com/jtamames/SqueezeMeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SQMtools + url_git: https://github.com/jtamames/SqueezeMeta +SQN: + version: 1.0.6 + title: Subset Quantile Normalization + maintainer: Martin Aryee + description: |- + Normalization based a subset of negative control probes as + described in 'Subset quantile normalization using negative + control features'. Wu Z, Aryee MJ, J Comput Biol. 2010 + Oct;17(10):1385-95 [PMID 20976876]. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SQN + url_git: '' +SQRL: + version: 1.0.2 + title: Enhances Interaction with 'ODBC' Databases + maintainer: Mike Lee + description: |- + Provides simple and powerful interfaces that facilitate interaction + with 'ODBC' data sources. Each data source gets its own unique and dedicated + interface, wrapped around 'RODBC'. Communication settings are remembered + between queries, and are managed silently in the background. The interfaces + support multi-statement 'SQL' scripts, which can be parameterised via + metaprogramming structures and embedded 'R' expressions. + date_publication: '2023-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SQRL + url_git: '' +squant: + version: 1.1.7 + title: Subgroup Identification Based on Quantitative Objectives + maintainer: YAN SUN + description: |- + A subgroup identification method for precision medicine based on + quantitative objectives. This method can handle continuous, binary and + survival endpoint for both prognostic and predictive case. For the + predictive case, the method aims at identifying a subgroup for which + treatment is better than control by at least a pre-specified or + auto-selected constant. For the prognostic case, the method aims at + identifying a subgroup that is at least better than a + pre-specified/auto-selected constant. The derived signature is a linear + combination of predictors, and the selected subgroup are subjects with + the signature > 0. The false discover rate when no true subgroup exists + is controlled at a user-specified level. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=squant + url_git: '' +SQUAREM: + version: '2021.1' + title: |- + Squared Extrapolation Methods for Accelerating EM-Like Monotone + Algorithms + maintainer: Ravi Varadhan + description: |- + Algorithms for accelerating the convergence of slow, + monotone sequences from smooth, contraction mapping such as the + EM algorithm. It can be used to accelerate any smooth, linearly + convergent acceleration scheme. A tutorial style introduction + to this package is available in a vignette on the CRAN download + page or, when the package is loaded in an R session, with + vignette("SQUAREM"). Refer to the J Stat Software article: . + date_publication: '2021-01-13' + bug_reports: '' + url: https://coah.jhu.edu/people/Faculty_personal_Pages/Varadhan.html + url_cran: https://CRAN.R-project.org/package=SQUAREM + url_git: '' +squash: + version: 1.0.9 + title: Color-Based Plots for Multivariate Visualization + maintainer: Aron C. Eklund + description: Functions for color-based visualization of multivariate data, i.e. + colorgrams or heatmaps. Lower-level functions map numeric values to colors, + display a matrix as an array of colors, and draw color keys. Higher-level plotting + functions generate a bivariate histogram, a dendrogram aligned with a color-coded + matrix, a triangular distance matrix, and more. + date_publication: '2020-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=squash + url_git: https://github.com/aroneklund/squash +SqueakR: + version: 1.3.0 + title: An Experiment Interface for 'DeepSqueak' Bioacoustics Research + maintainer: Simon Ogundare + description: |- + Data processing and visualizations for rodent vocalizations exported from + 'DeepSqueak'. These functions are compatible with the 'SqueakR' Shiny Dashboard, + which can be used to visualize experimental results and analyses. + date_publication: '2022-06-28' + bug_reports: '' + url: https://osimon81.github.io/SqueakR/ + url_cran: https://CRAN.R-project.org/package=SqueakR + url_git: https://github.com/osimon81/SqueakR/ +squeezy: + version: 1.1-1 + title: Group-Adaptive Elastic Net Penalised Generalised Linear Models + maintainer: Mirrelijn M. van Nee + description: |- + Fit linear and logistic regression models penalised with group-adaptive elastic net penalties. + The group penalties correspond to groups of covariates defined by a co-data group set. + The method accommodates inclusion of unpenalised covariates and overlapping groups. + See Van Nee et al. (2021) . + date_publication: '2022-05-13' + bug_reports: '' + url: https://arxiv.org/abs/2101.03875 + url_cran: https://CRAN.R-project.org/package=squeezy + url_git: '' +squid: + version: 0.2.1 + title: Statistical Quantification of Individual Differences + maintainer: Hassen Allegue + description: |- + A simulation-based tool made to help researchers to become familiar with + multilevel variations, and to build up sampling designs for their study. + This tool has two main objectives: First, it provides an educational tool useful for students, + teachers and researchers who want to learn to use mixed-effects models. + Users can experience how the mixed-effects model framework can be used to understand + distinct biological phenomena by interactively exploring simulated multilevel data. + Second, it offers research opportunities to those who are already familiar with + mixed-effects models, as it enables the generation of data sets that users may download + and use for a range of simulation-based statistical analyses such as power + and sensitivity analysis of multilevel and multivariate data [Allegue, H., Araya-Ajoy, Y.G., Dingemanse, + N.J., Dochtermann N.A., Garamszegi, L.Z., Nakagawa, S., Reale, D., Schielzeth, H. and Westneat, D.F. (2016) + ]. + date_publication: '2022-01-21' + bug_reports: https://github.com/squid-group/squid/issues + url: https://squid-group.github.io/squid/ + url_cran: https://CRAN.R-project.org/package=squid + url_git: https://github.com/squid-group/squid +sr: + version: 0.1.0 + title: Smooth Regression - The Gamma Test and Tools + maintainer: Wayne Haythorn + description: |- + Finds causal connections in precision data, finds lags and embeddings in + time series, guides training of neural networks and other smooth models, evaluates + their performance, gives a mathematically grounded answer to the over-training + problem. Smooth regression is based on the Gamma test, which measures smoothness + in a multivariate relationship. Causal relations are smooth, noise is not. + 'sr' includes the Gamma test and search techniques that use it. + References: Evans & Jones (2002) , + AJ Jones (2004) . + date_publication: '2023-03-10' + bug_reports: https://github.com/haythorn/sr/issues + url: https://smoothregression.com + url_cran: https://CRAN.R-project.org/package=sr + url_git: https://github.com/haythorn/sr/ +sra: + version: 0.1.4.1 + title: Selection Response Analysis + maintainer: Arnaud Le Rouzic + description: Artificial selection through selective breeding is an efficient way + to induce changes in traits of interest in experimental populations. This package + (sra) provides a set of tools to analyse artificial-selection response datasets. + The data typically feature for several generations the average value of a trait + in a population, the variance of the trait, the population size and the average + value of the parents that were chosen to breed. Sra implements two families of + models aiming at describing the dynamics of the genetic architecture of the trait + during the selection response. The first family relies on purely descriptive (phenomenological) + models, based on an autoregressive framework. The second family provides different + mechanistic models, accounting e.g. for inbreeding, mutations, genetic and environmental + canalization, or epistasis. The parameters underlying the dynamics of the time + series are estimated by maximum likelihood. The sra package thus provides (i) + a wrapper for the R functions mle() and optim() aiming at fitting in a convenient + way a predetermined set of models, and (ii) some functions to plot and analyze + the output of the models. + date_publication: '2024-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sra + url_git: https://github.com/lerouzic/sra +srcpkgs: + version: '0.1' + title: R Source Packages Manager + maintainer: Karl Forner + description: |- + Manage a collection/library of R source packages. Discover, document, load, test + source packages. Enable to use those packages as if they were actually installed. Quickly reload + only what is needed on source code change. Run tests and checks in parallel. + date_publication: '2024-05-15' + bug_reports: https://github.com/kforner/srcpkgs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=srcpkgs + url_git: https://github.com/kforner/srcpkgs +srcr: + version: 1.1.1 + title: Simplify Connections to Database Sources + maintainer: Charles Bailey + description: |- + Connecting to databases requires boilerplate code to specify + connection parameters and to set up sessions properly with the DBMS. + This package provides a simple tool to fill two purposes: abstracting + connection details, including secret credentials, out of your source + code and managing configuration for frequently-used database connections + in a persistent and flexible way, while minimizing requirements on the + runtime environment. + date_publication: '2024-05-12' + bug_reports: https://github.com/baileych/srcr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=srcr + url_git: https://github.com/baileych/srcr +SRCS: + version: '1.1' + title: |- + Statistical Ranking Color Scheme for Multiple Pairwise + Comparisons + maintainer: Pablo J. Villacorta + description: |- + Implementation of the SRCS method for a color-based visualization of the + results of multiple pairwise tests on a large number of problem configurations, proposed in: + I.G. del Amo, D.A. Pelta. SRCS: a technique for comparing multiple algorithms under several + factors in dynamic optimization problems. In: E. Alba, A. Nakib, P. Siarry + (Eds.), Metaheuristics for Dynamic Optimization. Series: Studies in + Computational Intelligence 433, Springer, Berlin/Heidelberg, 2012. + date_publication: '2015-07-02' + bug_reports: '' + url: http://decsai.ugr.es/~pjvi/r-packages.html + url_cran: https://CRAN.R-project.org/package=SRCS + url_git: '' +sRDA: + version: 1.0.0 + title: Sparse Redundancy Analysis + maintainer: Attila Csala + description: |- + Sparse redundancy analysis + for high dimensional (biomedical) data. Directional multivariate analysis + to express the maximum variance in the predicted data set by a linear + combination of variables of the predictive data set. Implemented in a + partial least squares framework, for more details see Csala et al. (2017) . + date_publication: '2017-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sRDA + url_git: '' +sRdpData: + version: 0.1.0 + title: Strategies of Resistance Data Project + maintainer: Harriet Jane Goers + description: Provides you with easy, programmatic access to SRDP data. + date_publication: '2022-03-29' + bug_reports: https://github.com/hgoers/sRdpData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sRdpData + url_git: https://github.com/hgoers/sRdpData +sreg: + version: 1.0.1 + title: Stratified Randomized Experiments + maintainer: Juri Trifonov + description: Estimate average treatment effects (ATEs) in stratified randomized + experiments. 'sreg' is designed to accommodate scenarios with multiple treatments + and cluster-level treatment assignments, and accommodates optimal linear covariate + adjustment based on baseline observable characteristics. 'sreg' computes estimators + and standard errors based on Bugni, Canay, Shaikh (2018) ; + Bugni, Canay, Shaikh, Tabord-Meehan (2024+) ; and + Jiang, Linton, Tang, Zhang (2023+) . + date_publication: '2025-02-06' + bug_reports: https://github.com/jutrifonov/sreg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sreg + url_git: https://github.com/jutrifonov/sreg +sregsurvey: + version: 0.1.3 + title: Semiparametric Model-Assisted Estimation in Finite Populations + maintainer: Carlos Alberto Cardozo Delgado + description: |- + It is a framework to fit semiparametric regression estimators for the total parameter of a finite population when the interest variable is asymmetric distributed. The main references for this package are Sarndal C.E., Swensson B., and Wretman J. (2003,ISBN: 978-0-387-40620-6, "Model Assisted Survey Sampling." Springer-Verlag) + Cardozo C.A, Paula G.A. and Vanegas L.H. (2022) "Generalized log-gamma additive partial linear mdoels with P-spline smoothing", Statistical Papers. + Cardozo C.A and Alonso-Malaver C.E. (2022). "Semi-parametric model assisted estimation in finite populations." In preparation. + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sregsurvey + url_git: '' +srlars: + version: 1.0.1 + title: Split Robust Least Angle Regression + maintainer: Anthony Christidis + description: |- + Functions to perform split robust least angle regression. The approach first uses the + least angle regression algorithm to split the variables into the models of an ensemble + and robust estimates of the correlation between predictors. An elastic net estimator is + then applied to the selected predictors in each model using the imputed data from the + detect deviating cell (DDC) method. + date_publication: '2023-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=srlars + url_git: '' +srm: + version: 0.4-26 + title: Structural Equation Modeling for the Social Relations Model + maintainer: Alexander Robitzsch + description: |2- + + Provides functionality for structural equation modeling for + the social relations model (Kenny & La Voie, 1984; + ; Warner, Kenny, & Soto, 1979, + ). Maximum likelihood + estimation (Gill & Swartz, 2001, ; + Nestler, 2018, ) and + least squares estimation is supported (Bond & Malloy, 2018, + ). + date_publication: '2022-11-03' + bug_reports: '' + url: https://sites.google.com/site/alexanderrobitzsch2/software + url_cran: https://CRAN.R-project.org/package=srm + url_git: https://github.com/alexanderrobitzsch/srm +sRNAGenetic: + version: 0.1.0 + title: Analysis of Small RNA Expression Changes in Hybrid Plants + maintainer: Yu qing Wu + description: The most important function of the R package is the genetic effects + analysis of small RNA in hybrid plants via two methods, and at the same time, + it provides various forms of graph related to data characteristics and expression + analysis. In terms of two classification methods, one is the calculation of the + additive (a) and dominant (d), the other is the evaluation of expression level + dominance by comparing the total expression of the small RNA in progeny with the + expression level in the parent species. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sRNAGenetic + url_git: '' +srp: + version: 1.2.0 + title: Smooth-Rough Partitioning of the Regression Coefficients + maintainer: Hyeyoung Maeng + description: |- + Performs the change-point detection in regression coefficients of linear model + by partitioning the regression coefficients into two classes of smoothness. The change-point and + the regression coefficients are jointly estimated. + date_publication: '2019-04-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=srp + url_git: '' +srppp: + version: 1.0.1 + title: Read the Swiss Register of Plant Protection Products + maintainer: Johannes Ranke + description: |- + Generate data objects from XML versions of the Swiss + Register of Plant Protection Products. An online version of the + register can be accessed at . There is no + guarantee of correspondence of the data read in using this package with that + online version, or with the original registration documents. Also, the + Federal Food Safety and Veterinary Office, coordinating the authorisation of + plant protection products in Switzerland, does not answer requests regarding + this package. + date_publication: '2024-11-01' + bug_reports: https://github.com/agroscope-ch/srppp/issues + url: https://agroscope-ch.github.io/srppp/ + url_cran: https://CRAN.R-project.org/package=srppp + url_git: '' +SRS: + version: 0.2.3 + title: Scaling with Ranked Subsampling + maintainer: Lukas Beule + description: Analysis of species count data in ecology often requires normalization + to an identical sample size. Rarefying (random subsampling without replacement), + which is a popular method for normalization, has been widely criticized for its + poor reproducibility and potential distortion of the community structure. In the + context of microbiome count data, researchers explicitly advised against the use + of rarefying. An alternative to rarefying is scaling with ranked subsampling (SRS). + SRS consists of two steps. In the first step, the total counts for all OTUs (operational + taxonomic units) or species in each sample are divided by a scaling factor chosen + in such a way that the sum of the scaled counts Cscaled equals Cmin. In the second + step, the non-integer Cscaled values are converted into integers by an algorithm + that we dub ranked subsampling. The Cscaled value for each OTU or species is split + into the integer part Cint (Cint = floor(Cscaled)) and the fractional part Cfrac + (Cfrac = Cscaled - Cints). Since the sum of Cint is smaller or equal to Cmin, + additional delta C = Cmin - the sum of Cint counts have to be added to the library + to reach the total count of Cmin. This is achieved as follows. OTUs are ranked + in the descending order of their Cfrac values. Beginning with the OTU of the highest + rank, single count per OTU is added to the normalized library until the total + number of added counts reaches delta C and the sum of all counts in the normalized + library equals Cmin. When the lowest Cfrag involved in picking delta C counts + is shared by several OTUs, the OTUs used for adding a single count to the library + are selected in the order of their Cint values. This selection minimizes the effect + of normalization on the relative frequencies of OTUs. OTUs with identical Cfrag + as well as Cint are sampled randomly without replacement. See Beule & Karlovsky + (2020) for details. + date_publication: '2022-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SRS + url_git: '' +srt: + version: 1.0.4 + title: Read Subtitle Files as Tabular Data + maintainer: Kiernan Nicholls + description: |- + Read 'SubRip' + subtitle files as data frames for easy text analysis or manipulation. + Easily shift numeric timings and export subtitles back into valid + 'SubRip' timestamp format to sync subtitles and audio. + date_publication: '2024-03-11' + bug_reports: https://github.com/k5cents/srt/issues + url: https://k5cents.github.io/srt/ + url_cran: https://CRAN.R-project.org/package=srt + url_git: https://github.com/k5cents/srt +SRTsim: + version: 0.99.7 + title: Simulator for Spatially Resolved Transcriptomics + maintainer: Jiaqiang Zhu + description: 'An independent, reproducible, and flexible Spatially Resolved Transcriptomics + (SRT) simulation framework that can be used to facilitate the development of SRT + analytical methods for a wide variety of SRT-specific analyses. It utilizes spatial + localization information to simulate SRT expression count data in a reproducible + and scalable fashion. Two major simulation schemes are implemented in ''SRTsim'': + reference-based and reference-free.' + date_publication: '2024-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SRTsim + url_git: '' +SRTtools: + version: 1.2.0 + title: Adjust Srt File to Get Better Experience when Watching Movie + maintainer: Jim Chen + description: |- + Srt file is a common subtitle format for videos, it contains subtitle and when the subtitle showed. + This package is for align time of srt file, and also change color, style and position of subtitle in videos, + the srt file will be read as a vector into R, and can be write into srt file after modified using this package. + date_publication: '2019-07-18' + bug_reports: https://github.com/ChiHangChen/SRTtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SRTtools + url_git: https://github.com/ChiHangChen/SRTtools +srvyr: + version: 1.3.0 + title: '''dplyr''-Like Syntax for Summary Statistics of Survey Data' + maintainer: Greg Freedman Ellis + description: |- + Use piping, verbs like 'group_by' and 'summarize', and other + 'dplyr' inspired syntactic style when calculating summary statistics on survey + data using functions from the 'survey' package. + date_publication: '2024-08-19' + bug_reports: https://github.com/gergness/srvyr/issues + url: http://gdfe.co/srvyr/ + url_cran: https://CRAN.R-project.org/package=srvyr + url_git: https://github.com/gergness/srvyr/ +ss3sim: + version: 1.0.3 + title: |- + Fisheries Stock Assessment Simulation Testing with Stock + Synthesis + maintainer: Kelli F. Johnson + description: |- + Develops a framework for fisheries stock assessment simulation + testing with Stock Synthesis (SS) as described in Anderson et al. + (2014) . + date_publication: '2019-11-08' + bug_reports: https://github.com/ss3sim/ss3sim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ss3sim + url_git: https://github.com/ss3sim/ss3sim +ssaBSS: + version: 0.1.1 + title: Stationary Subspace Analysis + maintainer: Markus Matilainen + description: Stationary subspace analysis (SSA) is a blind source separation (BSS) + variant where stationary components are separated from non-stationary components. + Several SSA methods for multivariate time series are provided here (Flumian et + al. (2021); Hara et al. (2010) ) along with + functions to simulate time series with time-varying variance and autocovariance + (Patilea and Raissi(2014) ). + date_publication: '2022-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssaBSS + url_git: '' +ssanv: + version: '1.1' + title: |- + Sample Size Adjusted for Nonadherence or Variability of Input + Parameters + maintainer: Michael P. Fay + description: A set of functions to calculate sample size for two-sample difference + in means tests. Does adjustments for either nonadherence or variability that comes + from using data to estimate parameters. + date_publication: '2015-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssanv + url_git: '' +SSBtools: + version: 1.7.0 + title: Statistics Norway's Miscellaneous Tools + maintainer: Øyvind Langsrud + description: Functions used by other packages from Statistics Norway are gathered. + General data manipulation functions, algorithms for statistical disclosure control + (Langsrud, 2024) and functions for hierarchical + computations by sparse model matrices are included (Langsrud, 2023) . + date_publication: '2025-02-04' + bug_reports: https://github.com/statisticsnorway/ssb-ssbtools/issues + url: https://statisticsnorway.github.io/ssb-ssbtools/ + url_cran: https://CRAN.R-project.org/package=SSBtools + url_git: https://github.com/statisticsnorway/ssb-ssbtools +ssc: + version: 2.1-0 + title: Semi-Supervised Classification Methods + maintainer: Christoph Bergmeir + description: |- + Provides a collection of self-labeled techniques for semi-supervised + classification. In semi-supervised classification, both labeled and unlabeled + data are used to train a classifier. This learning paradigm has obtained promising + results, specifically in the presence of a reduced set of labeled examples. + This package implements a collection of self-labeled techniques to construct a + classification model. This family of techniques enlarges the original labeled set + using the most confident predictions to classify unlabeled data. The techniques + implemented can be applied to classification problems in several domains by the + specification of a supervised base classifier. At low ratios of labeled data, it + can be shown to perform better than classical supervised classifiers. + date_publication: '2019-12-15' + bug_reports: https://github.com/mabelc/SSC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ssc + url_git: https://github.com/mabelc/SSC +sscor: + version: '0.2' + title: Robust Correlation Estimation and Testing Based on Spatial Signs + maintainer: Alexander Duerre + description: Provides the spatial sign correlation and the two-stage spatial sign + correlation as well as a one-sample test for the correlation coefficient. + date_publication: '2016-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sscor + url_git: '' +ssd4mosaic: + version: 1.0.1 + title: Web Application for the SSD Module of the MOSAIC Platform + maintainer: Milena Kaag + description: |- + Web application using 'shiny' for the SSD (Species + Sensitivity Distribution) module of the MOSAIC (MOdeling and + StAtistical tools for ecotoxICology) platform. It estimates the + Hazardous Concentration for x% of the species (HCx) from toxicity + values that can be censored and provides various plotting options for + a better understanding of the results. See our companion paper + Kon Kam King et al. (2014) . + date_publication: '2024-03-19' + bug_reports: https://gitlab.in2p3.fr/mosaic-software/mosaic-ssd/-/issues + url: https://gitlab.in2p3.fr/mosaic-software/mosaic-ssd + url_cran: https://CRAN.R-project.org/package=ssd4mosaic + url_git: '' +ssddata: + version: 1.0.0 + title: Species Sensitivity Distribution Data + maintainer: Rebecca Fisher + description: |- + Reference data sets of species sensitivities to compare the + results of fitting species sensitivity distributions + using software such as 'ssdtools' and 'Burrlioz'. + It consists of 17 primary data sets from + four different Australian and Canadian organizations as well as five + datasets from anonymous sources. It also includes a data set of the + results of fitting various distributions using different software. + date_publication: '2021-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssddata + url_git: '' +SSDforR: + version: 1.5.37 + title: Functions to Analyze Single System Data + maintainer: Charles Auerbach + description: Functions to visually and statistically analyze single system data. + date_publication: '2024-12-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSDforR + url_git: '' +ssdGSA: + version: 0.1.1 + title: Single Sample Directional Gene Set Analysis + maintainer: Xingpeng Li + description: |- + A method that inherits the standard gene set variation analysis (GSVA) method and also provides the option to use summary statistics from any analysis (disease vs healthy, lesional side vs nonlesional side, etc..) input to define the direction of gene sets used for directional gene set score calculation for a given disease. Note to use this package, GSVA(>= 1.52.1) is needed to pre-installed. + Hanzelmann, S., Castelo, R., and Guinney, J. (2013) . + date_publication: '2024-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssdGSA + url_git: '' +SSDM: + version: 0.2.9 + title: Stacked Species Distribution Modelling + maintainer: Sylvain Schmitt + description: |- + Allows to map species richness and endemism based on stacked + species distribution models (SSDM). Individuals SDMs can be created using a + single or multiple algorithms (ensemble SDMs). For each species, an SDM can + yield a habitat suitability map, a binary map, a between-algorithm variance + map, and can assess variable importance, algorithm accuracy, and between- + algorithm correlation. Methods to stack individual SDMs include summing + individual probabilities and thresholding then summing. Thresholding can be + based on a specific evaluation metric or by drawing repeatedly from a Bernoulli + distribution. The SSDM package also provides a user-friendly interface. + date_publication: '2023-10-24' + bug_reports: https://github.com/sylvainschmitt/SSDM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSDM + url_git: https://github.com/sylvainschmitt/SSDM +sSDR: + version: 1.2.0 + title: |- + Tools Developed for Structured Sufficient Dimension Reduction + (sSDR) + maintainer: Yang Liu + description: Performs structured OLS (sOLS) and structured SIR (sSIR). + date_publication: '2016-03-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sSDR + url_git: '' +ssdtools: + version: 2.3.0 + title: Species Sensitivity Distributions + maintainer: Joe Thorley + description: |- + Species sensitivity distributions are cumulative probability + distributions which are fitted to toxicity concentrations for + different species as described by Posthuma et al.(2001) + . The ssdtools package uses Maximum Likelihood to + fit distributions such as the gamma, log-logistic, log-normal and + log-normal log-normal mixture. Multiple distributions can be averaged + using Akaike Information Criteria. Confidence intervals on hazard + concentrations and proportions are produced by bootstrapping. + date_publication: '2025-02-20' + bug_reports: https://github.com/bcgov/ssdtools/issues + url: https://bcgov.github.io/ssdtools/ + url_cran: https://CRAN.R-project.org/package=ssdtools + url_git: https://github.com/bcgov/ssdtools +sse: + version: 0.7-17 + title: Sample Size Estimation + maintainer: Thomas Fabbro + description: Provides functions to evaluate user-defined power functions for a parameter + range, and draws a sensitivity plot. It also provides a resampling procedure for + semi-parametric sample size estimation and methods for adding information to a + Sweave report. + date_publication: '2021-05-19' + bug_reports: http://r-forge.r-project.org/projects/power/ + url: '' + url_cran: https://CRAN.R-project.org/package=sse + url_git: http://r-forge.r-project.org/projects/power/ +SSEparser: + version: 0.1.0 + title: Parse Server-Sent Events + maintainer: Samuel Calderon + description: |- + Functionality to parse server-sent events with a high-level + interface that can be extended for custom applications. + date_publication: '2023-12-14' + bug_reports: https://github.com/calderonsamuel/SSEparser/issues + url: https://calderonsamuel.github.io/SSEparser/ + url_cran: https://CRAN.R-project.org/package=SSEparser + url_git: https://github.com/calderonsamuel/SSEparser +ssev: + version: 0.1.0 + title: Sample Size Computation for Fixed N with Optimal Reward + maintainer: Maurits Kaptein + description: Computes the optimal sample size for various 2-group designs (e.g., + when comparing the means of two groups assuming equal variances, unequal variances, + or comparing proportions) when the aim is to maximize the rewards over the full + decision procedure of a) running a trial (with the computed sample size), and + b) subsequently administering the winning treatment to the remaining N-n units + in the population. Sample sizes and expected rewards for standard t- and z- tests + are also provided. + date_publication: '2019-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssev + url_git: '' +ssfa: + version: 1.2.2 + title: Spatial Stochastic Frontier Analysis + maintainer: Elisa Fusco + description: 'Spatial Stochastic Frontier Analysis (SSFA) is an original method + for controlling the spatial heterogeneity in Stochastic Frontier Analysis (SFA) + models, for cross-sectional data, by splitting the inefficiency term into three + terms: the first one related to spatial peculiarities of the territory in which + each single unit operates, the second one related to the specific production features + and the third one representing the error term.' + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssfa + url_git: '' +ssfit: + version: '1.2' + title: Fitting of Parametric Models using Summary Statistics + maintainer: Christiana Kartsonaki + description: Fits complex parametric models using the method proposed by Cox and + Kartsonaki (2012) without likelihoods. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssfit + url_git: '' +SSGL: + version: '1.0' + title: |- + Spike-and-Slab Group Lasso for Group-Regularized Generalized + Linear Models + maintainer: Ray Bai + description: |- + Fits group-regularized generalized linear models (GLMs) using the spike-and-slab group lasso (SSGL) prior introduced by Bai et al. (2022) and extended to GLMs by Bai (2023) . This package supports fitting the SSGL model for the following GLMs with group sparsity: Gaussian linear regression, binary logistic regression, Poisson regression, negative binomial regression, and gamma regression. + Stand-alone functions for group-regularized negative binomial regression and group-regularized gamma regression are also available, with the option of employing the group lasso penalty of Yuan and Lin (2006) , the group minimax concave penalty (MCP) of Breheny and Huang , or the group smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) . + date_publication: '2023-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSGL + url_git: '' +ssgraph: + version: '1.15' + title: Bayesian Graph Structure Learning using Spike-and-Slab Priors + maintainer: Reza Mohammadi + description: Bayesian estimation for undirected graphical models using spike-and-slab + priors. The package handles continuous, discrete, and mixed data. + date_publication: '2022-12-24' + bug_reports: '' + url: https://www.uva.nl/profile/a.mohammadi + url_cran: https://CRAN.R-project.org/package=ssgraph + url_git: '' +ssh: + version: 0.9.3 + title: Secure Shell (SSH) Client for R + maintainer: Jeroen Ooms + description: |- + Connect to a remote server over SSH to transfer files via SCP, + setup a secure tunnel, or run a command or script on the host while + streaming stdout and stderr directly to the client. + date_publication: '2024-09-19' + bug_reports: https://github.com/ropensci/ssh/issues + url: https://docs.ropensci.org/ssh/https://ropensci.r-universe.dev/ssh + url_cran: https://CRAN.R-project.org/package=ssh + url_git: '' +SSHAARP: + version: 2.0.5 + title: Searching Shared HLA Amino Acid Residue Prevalence + maintainer: Livia Tran + description: Processes amino acid alignments produced by the 'IPD-IMGT/HLA (Immuno + Polymorphism-ImMunoGeneTics/Human Leukocyte Antigen) Database' to identify user-defined + amino acid residue motifs shared across HLA alleles, HLA alleles, or HLA haplotypes, + and calculates frequencies based on HLA allele frequency data. 'SSHAARP' (Searching + Shared HLA Amino Acid Residue Prevalence) uses 'Generic Mapping Tools (GMT)' software + and the 'GMT' R package to generate global frequency heat maps that illustrate + the distribution of each user-defined map around the globe. 'SSHAARP' analyzes + the allele frequency data described by Solberg et al. (2008) , + a global set of 497 population samples from 185 published datasets, representing + 66,800 individuals total. Users may also specify their own datasets, but file + conventions must follow the prebundled Solberg dataset, or the mock haplotype + dataset. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSHAARP + url_git: '' +Sshaped: + version: '1.1' + title: Nonparametric, Tuning-Free Estimation of S-Shaped Functions + maintainer: Yining Chen + description: Estimation of an S-shaped function and its corresponding inflection + point via a least squares approach. A sequential mixed primal-dual based algorithm + is implemented for the fast computation. Details can be found in Feng et al. (2022) + . + date_publication: '2022-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sshaped + url_git: '' +sshicm: + version: 0.1.0 + title: |- + Information Consistency-Based Measures for Spatial Stratified + Heterogeneity + maintainer: Wenbo Lv + description: Spatial stratified heterogeneity (SSH) denotes the coexistence of within-strata + homogeneity and between-strata heterogeneity. Information consistency-based methods + provide a rigorous approach to quantify SSH and evaluate its role in spatial processes, + grounded in principles of geographical stratification and information theory (Bai, + H. et al. (2023) ; Wang, J. et al. (2024) ). + date_publication: '2024-12-03' + bug_reports: https://github.com/stscl/sshicm/issues + url: https://stscl.github.io/sshicm/ + url_cran: https://CRAN.R-project.org/package=sshicm + url_git: https://github.com/stscl/sshicm +sship: + version: 0.9.0 + title: Tool for Secure Shipment of Content + maintainer: Are Edvardsen + description: |- + Convenient tools for exchanging files securely from within R. By + encrypting the content safe passage of files (shipment) can be provided by + common but insecure carriers such as ftp and email. Based on asymmetric + cryptography no management of shared secrets is needed to make a secure + shipment as long as authentic public keys are available. Public keys used + for secure shipments may also be obtained from external providers as part of + the overall process. Transportation of files will require that relevant + services such as ftp and email servers are available. + date_publication: '2022-12-12' + bug_reports: https://github.com/Rapporteket/sship/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sship + url_git: https://github.com/Rapporteket/sship +ssifs: + version: 1.0.4 + title: Stochastic Search Inconsistency Factor Selection + maintainer: Georgios Seitidis + description: Evaluating the consistency assumption of Network Meta-Analysis both + globally and locally in the Bayesian framework. Inconsistencies are located by + applying Bayesian variable selection to the inconsistency factors. The implementation + of the method is described by Seitidis et al. (2023) . + date_publication: '2025-02-04' + bug_reports: https://github.com/georgiosseitidis/ssifs/issues + url: https://georgiosseitidis.github.io/ssifs/ + url_cran: https://CRAN.R-project.org/package=ssifs + url_git: https://github.com/georgiosseitidis/ssifs +SSIMmap: + version: 0.1.1 + title: The Structural Similarity Index Measure for Maps + maintainer: Hui Jeong (Hailyee) Ha + description: |- + Extends the classical SSIM method proposed by 'Wang', 'Bovik', 'Sheikh', and 'Simoncelli'(2004) . + for irregular lattice-based maps and raster images. + The geographical SSIM method incorporates well-developed 'geographically weighted summary statistics'('Brunsdon', 'Fotheringham' and 'Charlton' 2002) + with an adaptive bandwidth kernel function for irregular lattice-based maps. + date_publication: '2023-09-26' + bug_reports: https://github.com/Hailyee-Ha/SSIMmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSIMmap + url_git: https://github.com/Hailyee-Ha/SSIMmap +ssimparser: + version: 0.1.1 + title: Standard Schedules Information Parser + maintainer: Sebastien Thonnard + description: |- + Parse Standard Schedules Information file (types 2 and 3) into a Data Frame. + Can also expand schedules into flights. + date_publication: '2022-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssimparser + url_git: '' +ssize.fdr: + version: '1.3' + title: Sample Size Calculations for Microarray Experiments + maintainer: Megan Orr + description: Functions that calculate appropriate sample sizes for one-sample t-tests, + two-sample t-tests, and F-tests for microarray experiments based on desired power + while controlling for false discovery rates. For all tests, the standard deviations + (variances) among genes can be assumed fixed or random. This is also true for + effect sizes among genes in one-sample and two sample experiments. Functions also + output a chart of power versus sample size, a table of power at different sample + sizes, and a table of critical test values at different sample sizes. + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssize.fdr + url_git: '' +ssizeRNA: + version: 1.3.2 + title: Sample Size Calculation for RNA-Seq Experimental Design + maintainer: Ran Bi + description: |- + We propose a procedure for sample size calculation while + controlling false discovery rate for RNA-seq experimental design. Our + procedure depends on the Voom method proposed for RNA-seq data analysis + by Law et al. (2014) and the sample size + calculation method proposed for microarray experiments by Liu and Hwang + (2007) . We develop a set of functions + that calculates appropriate sample sizes for two-sample t-test for RNA-seq + experiments with fixed or varied set of parameters. The outputs also contain a + plot of power versus sample size, a table of power at different sample sizes, + and a table of critical test values at different sample sizes. + To install this package, please use + 'source("http://bioconductor.org/biocLite.R"); biocLite("ssizeRNA")'. + For R version 3.5 or greater, please use + 'if(!requireNamespace("BiocManager", quietly = TRUE)){install.packages("BiocManager")}; BiocManager::install("ssizeRNA")'. + date_publication: '2019-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssizeRNA + url_git: '' +SSLR: + version: 0.9.3.3 + title: |- + Semi-Supervised Classification, Regression and Clustering + Methods + maintainer: Francisco Jesús Palomares Alabarce + description: |- + Providing a collection of techniques for semi-supervised + classification, regression and clustering. In semi-supervised problem, both labeled and unlabeled + data are used to train a classifier. The package includes a collection of + semi-supervised learning techniques: self-training, co-training, democratic, + decision tree, random forest, 'S3VM' ... etc, with a fairly intuitive interface + that is easy to use. + date_publication: '2021-07-22' + bug_reports: '' + url: https://dicits.ugr.es/software/SSLR/ + url_cran: https://CRAN.R-project.org/package=SSLR + url_git: '' +SSM: + version: 1.0.1 + title: Fit and Analyze Smooth Supersaturated Models + maintainer: Peter Curtis + description: |- + Creates an S4 class "SSM" and defines functions for fitting smooth + supersaturated models, a polynomial model with spline-like behaviour. + Functions are defined for the computation of Sobol indices for sensitivity + analysis and plotting the main effects using FANOVA methods. It also + implements the estimation of the SSM metamodel error using a GP model with + a variety of defined correlation functions. + date_publication: '2017-07-04' + bug_reports: http://github.com/peterrobertcurtis/SSM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSM + url_git: https://github.com/peterrobertcurtis/SSM +ssmn: + version: '1.1' + title: Skew Scale Mixtures of Normal Distributions + maintainer: Luis Benites Sanchez + description: Performs the EM algorithm for regression models using Skew Scale Mixtures + of Normal Distributions. + date_publication: '2016-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssmn + url_git: '' +ssmodels: + version: 1.0.1 + title: Sample Selection Models + maintainer: Fernando de Souza Bastos + description: In order to facilitate the adjustment of the sample selection models + existing in the literature, we created the 'ssmodels' package. Our package allows + the adjustment of the classic Heckman model (Heckman (1976), Heckman (1979) ), + and the estimation of the parameters of this model via the maximum likelihood + method and two-step method, in addition to the adjustment of the Heckman-t models, + introduced in the literature by Marchenko and Genton (2012) + and the Heckman-Skew model introduced in the literature by Ogundimu and Hutton + (2016) . We also implemented functions to adjust the generalized + version of the Heckman model, introduced by Bastos, Barreto-Souza, and Genton + (2021) , that allows the inclusion of covariables + to the dispersion and correlation parameters and a function to adjust the Heckman-BS + model introduced by Bastos and Barreto-Souza (2020) + that uses the Birnbaum-Saunders distribution as a joint distribution of the selection + and primary regression variables. + date_publication: '2022-10-04' + bug_reports: https://github.com/fsbmat-ufv/ssmodels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ssmodels + url_git: '' +ssMousetrack: + version: 1.1.6 + title: |- + Bayesian State-Space Modeling of Mouse-Tracking Experiments via + Stan + maintainer: Antonio Calcagnì + description: Estimates previously compiled state-space modeling for mouse-tracking + experiments using the 'rstan' package, which provides the R interface to the Stan + C++ library for Bayesian estimation. + date_publication: '2023-04-05' + bug_reports: https://github.com/antcalcagni/ssMousetrack/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ssMousetrack + url_git: '' +ssMRCD: + version: 1.1.0 + title: Spatially Smoothed MRCD Estimator + maintainer: Patricia Puchhammer + description: Estimation of the Spatially Smoothed Minimum Regularized Determinant + (ssMRCD) estimator and its usage in an ssMRCD-based outlier detection method as + described in Puchhammer and Filzmoser (2023) + and for sparse robust PCA for multi-source data described in Puchhammer, Wilms + and Filzmoser (2024) . Included are also complementary + visualization and parameter tuning tools. + date_publication: '2024-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssMRCD + url_git: '' +ssmrob: + version: '1.0' + title: Robust Estimation and Inference in Sample Selection Models + maintainer: Mikhail Zhelonkin + description: Package provides a set of tools for robust estimation and inference + for models with sample selectivity and endogenous treatment model. For details, + see Zhelonkin and Ronchetti (2021) . + date_publication: '2021-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssmrob + url_git: '' +ssmsn: + version: 0.2.0 + title: Scale-Shape Mixtures of Skew-Normal Distributions + maintainer: Luis Benites + description: It provides the density and random number generator for the Scale-Shape + Mixtures of Skew-Normal Distributions proposed by Jamalizadeh and Lin (2016) . + date_publication: '2017-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssmsn + url_git: '' +ssMutPA: + version: 0.1.2 + title: Single-Sample Mutation-Based Pathway Analysis + maintainer: Junwei Han + description: A systematic bioinformatics tool to perform single-sample mutation-based + pathway analysis by integrating somatic mutation data with the Protein-Protein + Interaction (PPI) network. In this method, we use local and global weighted strategies + to evaluate the effects of network genes from mutations according to the network + topology and then calculate the mutation-based pathway enrichment score (ssMutPES) + to reflect the accumulated effect of mutations of each pathway. Subsequently, + the ssMutPES profiles are used for unsupervised spectral clustering to identify + cancer subtypes. + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssMutPA + url_git: '' +SSN2: + version: 0.2.1 + title: Spatial Modeling on Stream Networks + maintainer: Michael Dumelle + description: Spatial statistical modeling and prediction for data on stream networks, + including models based on in-stream distance (Ver Hoef, J.M. and Peterson, E.E., + (2010) .) Models are created using moving average + constructions. Spatial linear models, including explanatory variables, can be + fit with (restricted) maximum likelihood. Mapping and other graphical functions + are included. + date_publication: '2024-08-28' + bug_reports: https://github.com/USEPA/SSN2/issues + url: https://usepa.github.io/SSN2/ + url_cran: https://CRAN.R-project.org/package=SSN2 + url_git: '' +SSNbayes: + version: 0.0.3 + title: Bayesian Spatio-Temporal Analysis in Stream Networks + maintainer: Edgar Santos-Fernandez + description: Fits Bayesian spatio-temporal models and makes predictions on stream + networks using the approach by Santos-Fernandez, Edgar, et al. (2022)."Bayesian + spatio-temporal models for stream networks". . In these models, + spatial dependence is captured using stream distance and flow connectivity, while + temporal autocorrelation is modelled using vector autoregression methods. + date_publication: '2023-12-03' + bug_reports: https://github.com/EdgarSantos-Fernandez/SSNbayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSNbayes + url_git: https://github.com/EdgarSantos-Fernandez/SSNbayes +SSNbler: + version: 1.0.1 + title: Assemble 'SSN' Objects + maintainer: Erin Peterson + description: Import, create and assemble data needed to fit spatial-statistical + stream-network models using the 'SSN2' package for 'R'. Streams, observations, + and prediction locations are represented as simple features and specific tools + provided to define topological relationships between features; calculate the hydrologic + distances (with flow-direction preserved) and the spatial additive function used + to weight converging stream segments; and export the topological, spatial, and + attribute information to an `SSN` (spatial stream network) object, which can be + efficiently stored, accessed and analysed in 'R'. A detailed description of methods + used to calculate and format the spatial data can be found in Peterson, E.E. and + Ver Hoef, J.M., (2014) . + date_publication: '2024-09-25' + bug_reports: https://github.com/pet221/SSNbler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSNbler + url_git: https://github.com/pet221/SSNbler +SSOSVM: + version: 0.2.1 + title: Stream Suitable Online Support Vector Machines + maintainer: Andrew Thomas Jones + description: Soft-margin support vector machines (SVMs) are a common class of classification + models. The training of SVMs usually requires that the data be available all at + once in a single batch, however the Stochastic majorization-minimization (SMM) + algorithm framework allows for the training of SVMs on streamed data instead Nguyen, + Jones & McLachlan(2018). This package utilizes + the SMM framework to provide functions for training SVMs with hinge loss, squared-hinge + loss, and logistic loss. + date_publication: '2019-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSOSVM + url_git: '' +SSP: + version: 1.0.1 + title: Simulated Sampling Procedure for Community Ecology + maintainer: Edlin Guerra-Castro + description: |- + Simulation-based sampling protocol (SSP) is an R package design to estimate sampling effort in studies of + ecological communities based on the definition of pseudo-multivariate standard error (MultSE) (Anderson & Santana-Garcon, 2015) and simulation + of ecological data. The theoretical background is described in Guerra-Castro et al. (2020) . + date_publication: '2020-03-28' + bug_reports: https://github.com/edlinguerra/SSP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSP + url_git: https://github.com/edlinguerra/SSP +SSplots: + version: 0.1.2 + title: Stock Status Plots (SSPs) + maintainer: Eldho Varghese + description: Pauly et al. (2008) + created (and coined the name) 'Stock Status Plots' for a UNEP compendium on Large + Marine Ecosystems(LMEs, Sherman and Hempel (2009)). + Stock status plots are bivariate graphs summarizing the status (e.g., developing, + fully exploited, overexploited, etc.), through time, of the multispecies fisheries + of a fished area or ecosystem. This package contains three functions to generate + stock status plots viz., SSplots_pauly() (as per the criteria proposed by Pauly + et al.,2008), SSplots_kleisner() (as per the criteria proposed by Kleisner and + Pauly (2011) and Kleisner et + al. (2013) )and SSplots_EPI() (as per the + criteria proposed by Jayasankar et al.,2021 ). + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSplots + url_git: '' +sspm: + version: 1.0.3 + title: |- + Spatial Surplus Production Model Framework for Northern Shrimp + Populations + maintainer: Valentin Lucet + description: |- + Implement a GAM-based (Generalized Additive Models) spatial surplus + production model (spatial SPM), aimed at modeling northern shrimp population + in Atlantic Canada but potentially to any stock in any location. The package + is opinionated in its implementation of SPMs as it internally makes the choice + to use penalized spatial gams with time lags. However, it also aims to provide + options for the user to customize their model. The methods are described in + Pedersen et al. (2022, ). + date_publication: '2025-02-12' + bug_reports: https://github.com/pedersen-fisheries-lab/sspm/issues + url: https://pedersen-fisheries-lab.github.io/sspm/ + url_cran: https://CRAN.R-project.org/package=sspm + url_git: '' +sspse: + version: 1.1.0-2 + title: |- + Estimating Hidden Population Size using Respondent Driven + Sampling Data + maintainer: Mark S. Handcock + description: |- + Estimate the size of a networked population based on + respondent-driven sampling data. The package is part of the "RDS Analyst" + suite of packages for the analysis of respondent-driven sampling data. + See Handcock, Gile and Mar (2014) , + Handcock, Gile and Mar (2015) , + Kim and Handcock (2021) , and + McLaughlin, et. al. (2023) . + date_publication: '2024-09-06' + bug_reports: '' + url: https://hpmrg.org + url_cran: https://CRAN.R-project.org/package=sspse + url_git: '' +ssr: + version: 0.1.1 + title: Semi-Supervised Regression Methods + maintainer: Enrique Garcia-Ceja + description: An implementation of semi-supervised regression methods including self-learning + and co-training by committee based on Hady, M. F. A., Schwenker, F., & Palm, G. + (2009) . Users can define which set of regressors + to use as base models from the 'caret' package, other packages, or custom functions. + date_publication: '2019-09-02' + bug_reports: https://github.com/enriquegit/ssr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ssr + url_git: https://github.com/enriquegit/ssr +SSRA: + version: 0.1-1 + title: Sakai Sequential Relation Analysis + maintainer: Takuya Yanagida + description: |- + 'Takea Semantic Structure Analysis' (TSSA) and 'Sakai Sequential + Relation Analysis' (SSRA) for polytomous items. Package includes functions for + generating a sequential relation table and a treegram to visualize the + sequential relations between pairs of items. + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSRA + url_git: '' +SSrat: + version: '1.1' + title: |- + Two-Dimensional Sociometric Status Determination with Rating + Scales + maintainer: Hans Landsheer + description: |- + A set of functions for two-dimensional sociometric status + determination with rating scales. For each person assessed, SSrat computes + probability distributions of the total scores for `Sympathy' (S), + `Antipathy' (A), social `Preference' (P) and social `Impact' (I), and + applies a set of criteria for sociometric status categorization. + date_publication: '2018-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSrat + url_git: '' +ssrm.logmer: + version: '0.1' + title: |- + Sample Size Determination for Longitudinal Designs with Binary + Outcome + maintainer: Kush Kapur + description: |- + Provides the necessary sample size for a longitudinal study with binary outcome in order to attain a pre-specified power while strictly maintaining the Type I error rate. + Kapur K, Bhaumik R, Tang XC, Hur K, Reda DJ, Bhaumik D (2014) . + date_publication: '2018-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssrm.logmer + url_git: '' +SSRMST: + version: 0.1.1 + title: Sample Size Calculation using Restricted Mean Survival Time + maintainer: Miki Horiguchi + description: Calculates the power and sample size based on the difference in Restricted + Mean Survival Time. + date_publication: '2017-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSRMST + url_git: '' +ssrn: + version: 0.1.0 + title: Scan Statistics for Railway Network + maintainer: Shinya Uryu + description: |- + Implement the algorithm provided in scan for estimating the + transmission route on railway network using passenger volume. It is a + generalization of the scan statistic approach for railway network to identify + the hot railway route for transmitting infectious diseases. + date_publication: '2020-06-23' + bug_reports: https://github.com/uribo/ssrn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ssrn + url_git: https://github.com/uribo/ssrn +SSRTcalc: + version: 0.3.3 + title: Easy SSRT Calculation + maintainer: Anton Leontyev + description: This is a collection of functions to calculate stop-signal reaction + time (SSRT). Includes functions for both "integration" and "mean" methods; both + fixed and adaptive stop-signal delays are supported (see appropriate functions). + Calculation is based on Verbruggen et al. (2019) + and Verbruggen et al. (2013) . + date_publication: '2021-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSRTcalc + url_git: '' +sss: + version: 0.2.2 + title: Import Files in the Triple-s (Standard Survey Structure) Format + maintainer: Andrie de Vries + description: |- + Tools to import survey files in the '.sss' (triple-s) format. + The package provides the function 'read.sss()' that reads the '.asc' + (or '.csv') and '.sss' files of a triple-s survey data file. + See also . + date_publication: '2024-01-26' + bug_reports: https://github.com/andrie/sss/issues + url: http://andrie.github.io/sss/ + url_cran: https://CRAN.R-project.org/package=sss + url_git: '' +sssc: + version: 1.0.0 + title: Same Species Sample Contamination Detection + maintainer: Tao Jiang + description: |- + Imports Variant Calling Format file into R. It can detect + whether a sample contains contaminant from the same species. + In the first stage of the approach, a change-point detection + method is used to identify copy number variations for filtering. + Next, features are extracted from the data for a support vector + machine model. For log-likelihood calculation, the deviation + parameter is estimated by maximum likelihood method. Using + a radial basis function kernel support vector machine, the + contamination of a sample can be detected. + date_publication: '2018-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sssc + url_git: '' +SSsimple: + version: 0.6.6 + title: State Space Models + maintainer: Dave Zes + description: Simulate, solve state space models. + date_publication: '2019-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SSsimple + url_git: '' +Sstack: + version: 1.0.1 + title: |- + Bootstrap Stacking of Random Forest Models for Heterogeneous + Data + maintainer: Kevin Matlock + description: Generates and predicts a set of linearly stacked Random Forest models + using bootstrap sampling. Individual datasets may be heterogeneous (not all samples + have full sets of features). Contains support for parallelization but the user + should register their cores before running. This is an extension of the method + found in Matlock (2018) . + date_publication: '2018-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sstack + url_git: '' +sstvars: + version: 1.1.4 + title: |- + Toolkit for Reduced Form and Structural Smooth Transition Vector + Autoregressive Models + maintainer: Savi Virolainen + description: |- + Penalized and non-penalized maximum likelihood estimation of smooth + transition vector autoregressive models with various types of transition weight + functions, conditional distributions, and identification methods. Constrained + estimation with various types of constraints is available. Residual based + model diagnostics, forecasting, simulations, and calculation of impulse + response functions, generalized impulse response functions, and generalized + forecast error variance decompositions. See + Heather Anderson, Farshid Vahid (1998) , + Helmut Lütkepohl, Aleksei Netšunajev (2017) , + Markku Lanne, Savi Virolainen (2025) , + Savi Virolainen (2025) . + date_publication: '2025-02-27' + bug_reports: https://github.com/saviviro/sstvars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sstvars + url_git: https://github.com/saviviro/sstvars +SSVS: + version: 2.0.0 + title: Functions for Stochastic Search Variable Selection (SSVS) + maintainer: Sierra Bainter + description: |- + Functions for performing stochastic search variable selection (SSVS) + for binary and continuous outcomes and visualizing the results. + SSVS is a Bayesian variable selection method used to estimate the probability + that individual predictors should be included in a regression model. + Using MCMC estimation, the method samples thousands of regression models + in order to characterize the model uncertainty regarding both the predictor + set and the regression parameters. For details see Bainter, McCauley, Wager, + and Losin (2020) Improving practices for selecting a subset of important + predictors in psychology: An application to predicting pain, Advances in + Methods and Practices in Psychological Science 3(1), 66-80 + . + date_publication: '2022-05-29' + bug_reports: https://github.com/sabainter/SSVS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SSVS + url_git: https://github.com/sabainter/SSVS +ssw: + version: 0.2.1 + title: |- + Striped Smith-Waterman Algorithm for Sequence Alignment using + SIMD + maintainer: Nan Xiao + description: |- + Provides an R interface for 'SSW' (Striped Smith-Waterman) + via its 'Python' binding 'ssw-py'. 'SSW' is a fast 'C' and 'C++' + implementation of the Smith-Waterman algorithm for pairwise sequence + alignment using Single-Instruction-Multiple-Data (SIMD) instructions. + 'SSW' enhances the standard algorithm by efficiently returning alignment + information and suboptimal alignment scores. + The core 'SSW' library offers performance improvements for various + bioinformatics tasks, including protein database searches, + short-read alignments, primary and split-read mapping, + structural variant detection, and read-overlap graph generation. + These features make 'SSW' particularly useful for genomic applications. + Zhao et al. (2013) developed the + original 'C' and 'C++' implementation. + date_publication: '2024-09-18' + bug_reports: https://github.com/nanxstats/ssw-r/issues + url: https://nanx.me/ssw-r/ + url_cran: https://CRAN.R-project.org/package=ssw + url_git: https://github.com/nanxstats/ssw-r +ssym: + version: 1.5.8 + title: Fitting Semi-Parametric log-Symmetric Regression Models + maintainer: Luis Hernando Vanegas + description: Set of tools to fit a semi-parametric regression model suitable for + analysis of data sets in which the response variable is continuous, strictly positive, + asymmetric and possibly, censored. Under this setup, both the median and the skewness + of the response variable distribution are explicitly modeled by using semi-parametric + functions, whose non-parametric components may be approximated by natural cubic + splines or P-splines. Supported distributions for the model error include log-normal, + log-Student-t, log-power-exponential, log-hyperbolic, log-contaminated-normal, + log-slash, Birnbaum-Saunders and Birnbaum-Saunders-t distributions. + date_publication: '2023-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ssym + url_git: '' +st: + version: 1.2.7 + title: Shrinkage t Statistic and Correlation-Adjusted t-Score + maintainer: Korbinian Strimmer + description: |- + Implements the "shrinkage t" statistic + introduced in Opgen-Rhein and Strimmer (2007) and + a shrinkage estimate of the "correlation-adjusted t-score" (CAT score) described + in Zuber and Strimmer (2009) . + It also offers a convenient interface to a number of other regularized + t-statistics commonly employed in high-dimensional case-control studies. + date_publication: '2021-11-27' + bug_reports: '' + url: https://strimmerlab.github.io/software/st/ + url_cran: https://CRAN.R-project.org/package=st + url_git: '' +sta: + version: 0.1.7 + title: Seasonal Trend Analysis for Time Series Imagery in R + maintainer: Inder Tecuapetla-Gomez + description: |- + Efficiently estimate shape parameters of periodic time series + imagery with which a statistical seasonal trend analysis (STA) is subsequently performed. + STA output can be exported in conventional raster formats. + Methods to visualize STA output are also implemented as well as the calculation + of additional basic statistics. STA is based on (R. Eastman, F. Sangermano, + B. Ghimire, H. Zhu, H. Chen, N. Neeti, Y. Cai, E. Machado and S. Crema, 2009) . + date_publication: '2022-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sta + url_git: '' +stabiliser: + version: 1.0.6 + title: Stabilising Variable Selection + maintainer: Robert Hyde + description: A stable approach to variable selection through stability selection + and the use of a permutation-based objective stability threshold. Lima et al (2021) + , Meinshausen and Buhlmann (2010) . + date_publication: '2023-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stabiliser + url_git: '' +stability: + version: 0.6.0 + title: Stability Analysis of Genotype by Environment Interaction (GEI) + maintainer: Muhammad Yaseen + description: Provides functionalities for performing stability analysis of genotype + by environment interaction (GEI) to identify superior and stable genotypes across + diverse environments. It implements Eberhart and Russell’s ANOVA method (1966)(), + Finlay and Wilkinson’s Joint Linear Regression method (1963) (), + Wricke’s Ecovalence (1962, 1964), Shukla’s stability variance parameter (1972) + (), Kang’s simultaneous selection for high yield and + stability (1991) (), Additive Main + Effects and Multiplicative Interaction (AMMI) method and Genotype plus Genotypes + by Environment (GGE) Interaction methods. + date_publication: '2024-09-29' + bug_reports: https://github.com/myaseen208/stability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stability + url_git: '' +StabilityApp: + version: 0.1.0 + title: Stability Analysis App for GEI in Multi-Environment Trials + maintainer: Muhammad Yaseen + description: Provides tools for Genotype by Environment Interaction (GEI) analysis, + using statistical models and visualizations to assess genotype performance across + environments. It helps researchers explore interaction effects, stability, and + adaptability in multi-environment trials, identifying the best-performing genotypes + in different conditions. Which Win Where! + date_publication: '2024-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StabilityApp + url_git: '' +StabilizedRegression: + version: '1.1' + title: Stabilizing Regression and Variable Selection + maintainer: Niklas Pfister + description: Contains an implementation of 'StabilizedRegression', a regression + framework for heterogeneous data introduced in Pfister et al. (2021) . + The procedure uses averaging to estimate a regression of a set of predictors X + on a response variable Y by enforcing stability with respect to a given environment + variable. The resulting regression leads to a variable selection procedure which + allows to distinguish between stable and unstable predictors. The package further + implements a visualization technique which illustrates the trade-off between stability + and predictiveness of individual predictors. + date_publication: '2022-06-30' + bug_reports: https://github.com/NiklasPfister/StabilizedRegression-R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StabilizedRegression + url_git: '' +stabilo: + version: 0.1.1 + title: Stabilometric Signal Quantification + maintainer: Jose Oliveira + description: |2- + + Functions for stabilometric signal quantification. + The input is a data frame containing the x, y coordinates of the center-of-pressure displacement. + Jose Magalhaes de Oliveira (2017) "Statokinesigram normalization method"; + T E Prieto, J B Myklebust, R G Hoffmann, E G Lovett, B M Myklebust (1996) "Measures of postural steadiness: Differences between healthy young and elderly adults"; + L F Oliveira et al (1996) "Calculation of area of stabilometric signals using principal component analisys". + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stabilo + url_git: '' +stable: + version: 1.1.6 + title: |- + Probability Functions and Generalized Regression Models for + Stable Distributions + maintainer: Bruce Swihart + description: |- + Density, distribution, quantile and hazard functions of a + stable variate; generalized regression models for the parameters + of a stable distribution. See the README for how to make equivalent calls + to those of 'stabledist' (i.e., Nolan's 0-parameterization and + 1-parameterization as detailed in Nolan (2020)). + See github for Lambert and Lindsey 1999 JRSS-C journal article, + which details the parameterization of the Buck (1995) stable. + See the Details section of the `?dstable` help file for context and + references. + date_publication: '2022-03-02' + bug_reports: https://github.com/swihart/stable/issues + url: https://www.commanster.eu/rcode.html + url_cran: https://CRAN.R-project.org/package=stable + url_git: '' +stabledist: + version: 0.7-2 + title: Stable Distribution Functions + maintainer: Martin Maechler + description: |- + Density, Probability and Quantile functions, and random number + generation for (skew) stable distributions, using the parametrizations of + Nolan. + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stabledist + url_git: https://r-forge.r-project.org/scm/viewvc.php/pkg/stabledist/?root=rmetrics +StableEstim: + version: '2.3' + title: |- + Estimate the Four Parameters of Stable Laws using Different + Methods + maintainer: Georgi N. Boshnakov + description: |- + Estimate the four parameters of stable laws using maximum + likelihood method, generalised method of moments with + finite and continuum number of points, iterative + Koutrouvelis regression and Kogon-McCulloch method. The + asymptotic properties of the estimators (covariance + matrix, confidence intervals) are also provided. + date_publication: '2024-10-24' + bug_reports: https://github.com/GeoBosh/StableEstim/issues + url: https://geobosh.github.io/StableEstim/(doc) + url_cran: https://CRAN.R-project.org/package=StableEstim + url_git: https://github.com/GeoBosh/StableEstim(devel) +stableGR: + version: '1.2' + title: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo + maintainer: Christina Knudson + description: Practitioners of Bayesian statistics often use Markov chain Monte Carlo + (MCMC) samplers to sample from a posterior distribution. This package determines + whether the MCMC sample is large enough to yield reliable estimates of the target + distribution. In particular, this calculates a Gelman-Rubin convergence diagnostic + using stable and consistent estimators of Monte Carlo variance. Additionally, + this uses the connection between an MCMC sample's effective sample size and the + Gelman-Rubin diagnostic to produce a threshold for terminating MCMC simulation. + Finally, this informs the user whether enough samples have been collected and + (if necessary) estimates the number of samples needed for a desired level of accuracy. + The theory underlying these methods can be found in "Revisiting the Gelman-Rubin + Diagnostic" by Vats and Knudson (2018) . + date_publication: '2022-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stableGR + url_git: '' +stablelearner: + version: 0.1-5 + title: Stability Assessment of Statistical Learning Methods + maintainer: Achim Zeileis + description: |- + Graphical and computational methods that can be used to assess the + stability of results from supervised statistical learning. + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stablelearner + url_git: '' +stablespec: + version: 0.3.0 + title: Stable Specification Search in Structural Equation Models + maintainer: Ridho Rahmadi + description: |- + An exploratory and heuristic approach for specification search in + Structural Equation Modeling. The basic idea is to subsample the original data + and then search for optimal models on each subset. Optimality is defined through + two objectives: model fit and parsimony. As these objectives are conflicting, + we apply a multi-objective optimization methods, specifically NSGA-II, to obtain + optimal models for the whole range of model complexities. From these optimal + models, we consider only the relevant model specifications (structures), i.e., + those that are both stable (occur frequently) and parsimonious and use those to + infer a causal model. + date_publication: '2017-04-05' + bug_reports: https://github.com/rahmarid/stablespec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stablespec + url_git: https://github.com/rahmarid/stablespec +stabm: + version: 1.2.2 + title: Stability Measures for Feature Selection + maintainer: Andrea Bommert + description: |- + An implementation of many measures for the + assessment of the stability of feature selection. Both simple measures + and measures which take into account the similarities between features + are available, see Bommert (2020) . + date_publication: '2023-04-04' + bug_reports: https://github.com/bommert/stabm/issues + url: https://bommert.github.io/stabm/ + url_cran: https://CRAN.R-project.org/package=stabm + url_git: https://github.com/bommert/stabm +stabs: + version: 0.6-4 + title: Stability Selection with Error Control + maintainer: Benjamin Hofner + description: |- + Resampling procedures to assess the stability of selected variables + with additional finite sample error control for high-dimensional variable + selection procedures such as Lasso or boosting. Both, standard stability + selection (Meinshausen & Buhlmann, 2010, ) + and complementary pairs stability selection with improved error bounds + (Shah & Samworth, 2013, ) are + implemented. The package can be combined with arbitrary user specified + variable selection approaches. + date_publication: '2021-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stabs + url_git: https://github.com/hofnerb/stabs +staccuracy: + version: 0.2.2 + title: Standardized Accuracy and Other Model Performance Metrics + maintainer: Chitu Okoli + description: Standardized accuracy (staccuracy) is a framework for expressing accuracy + scores such that 50% represents a reference level of performance and 100% is a + perfect prediction. The 'staccuracy' package provides tools for creating staccuracy + functions as well as some recommended staccuracy measures. It also provides functions + for some classic performance metrics such as mean absolute error (MAE), root mean + squared error (RMSE), and area under the receiver operating characteristic curve + (AUCROC), as well as their winsorized versions when applicable. + date_publication: '2025-02-23' + bug_reports: https://github.com/tripartio/staccuracy/issues + url: https://tripartio.github.io/staccuracy/ + url_cran: https://CRAN.R-project.org/package=staccuracy + url_git: https://github.com/tripartio/staccuracy +stackgbm: + version: 0.1.0 + title: Stacked Gradient Boosting Machines + maintainer: Nan Xiao + description: |- + A minimalist implementation of model stacking by + Wolpert (1992) for boosted tree models. + A classic, two-layer stacking model is implemented, where the first layer + generates features using gradient boosting trees, and the second layer + employs a logistic regression model that uses these features as inputs. + Utilities for training the base models and parameters tuning are provided, + allowing users to experiment with different ensemble configurations easily. + It aims to provide a simple and efficient way to combine multiple + gradient boosting models to improve predictive model performance + and robustness. + date_publication: '2024-04-30' + bug_reports: https://github.com/nanxstats/stackgbm/issues + url: https://nanx.me/stackgbm/ + url_cran: https://CRAN.R-project.org/package=stackgbm + url_git: https://github.com/nanxstats/stackgbm +StackImpute: + version: 0.1.0 + title: Tools for Analysis of Stacked Multiple Imputations + maintainer: Mike Kleinsasser + description: |- + Provides methods for inference using stacked multiple + imputations augmented with weights. The vignette provides example R code for + implementation in general multiple imputation settings. For additional details + about the estimation algorithm, we refer the reader to Beesley, Lauren J and + Taylor, Jeremy M G (2020) “A stacked approach for chained equations multiple + imputation incorporating the substantive model” , + and Beesley, Lauren J and Taylor, Jeremy M G (2021) “Accounting for not-at-random + missingness through imputation stacking” . + date_publication: '2021-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StackImpute + url_git: '' +stacking: + version: 0.2.1 + title: Building Predictive Models with Stacking + maintainer: Akio Onogi + description: Building predictive models with stacking which is a type of ensemble + learning. Learners can be specified from those implemented in 'caret'. For more + information of the package, see Nukui and Onogi (2023) . + date_publication: '2025-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stacking + url_git: '' +stacks: + version: 1.0.5 + title: Tidy Model Stacking + maintainer: Simon Couch + description: |- + Model stacking is an ensemble technique that involves + training a model to combine the outputs of many diverse statistical + models, and has been shown to improve predictive performance in a + variety of settings. 'stacks' implements a grammar for + 'tidymodels'-aligned model stacking. + date_publication: '2024-07-22' + bug_reports: https://github.com/tidymodels/stacks/issues + url: https://stacks.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=stacks + url_git: https://github.com/tidymodels/stacks +stacomiR: + version: 0.6.1 + title: Fish Migration Monitoring + maintainer: Cedric Briand + description: |- + Graphical outputs and treatment for a database of fish pass + monitoring. It is a part of the 'STACOMI' open source project developed in + France by the French Office for Biodiversity institute to centralize + data obtained by fish pass monitoring. This version is available in French and + English. See for more information on + 'STACOMI'. + date_publication: '2024-03-03' + bug_reports: https://forgemia.inra.fr/stacomi/stacomir/-/issues + url: https://forgemia.inra.fr/stacomi/stacomir + url_cran: https://CRAN.R-project.org/package=stacomiR + url_git: '' +stacomirtools: + version: 0.6.0.1 + title: Connection Class for Package stacomiR + maintainer: Cedric Briand + description: |- + S4 class wrappers for the 'ODBC' and Pool DBI connection, also provides some + utilities to paste small datasets to clipboard, rename columns. It is used by the package 'stacomiR' for + connections to the database. Development versions of 'stacomiR' are available in R-forge. + date_publication: '2022-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stacomirtools + url_git: '' +stagedtrees: + version: 2.3.0 + title: Staged Event Trees + maintainer: Gherardo Varando + description: |- + Creates and fits staged event tree probability models, + which are probabilistic graphical models capable of representing + asymmetric conditional independence statements + for categorical variables. + Includes functions to create, plot and fit staged + event trees from data, as well as many efficient structure + learning algorithms. + References: + Carli F, Leonelli M, Riccomagno E, Varando G (2022). + . + Collazo R. A., Görgen C. and Smith J. Q. + (2018, ISBN:9781498729604). + Görgen C., Bigatti A., Riccomagno E. and Smith J. Q. (2018) + . + Thwaites P. A., Smith, J. Q. (2017) . + Barclay L. M., Hutton J. L. and Smith J. Q. (2013) + . + Smith J. Q. and Anderson P. E. (2008) + . + date_publication: '2024-02-14' + bug_reports: https://github.com/stagedtrees/stagedtrees/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stagedtrees + url_git: https://github.com/stagedtrees/stagedtrees +stagePop: + version: 1.1-2 + title: |- + Modelling the Population Dynamics of a Stage-Structured Species + in Continuous Time + maintainer: David Nutter + description: |- + Provides facilities to implement and run population models of + stage-structured species... + date_publication: '2022-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stagePop + url_git: https://github.com/HelenKettle/StagePop +staggered: + version: 1.2.2 + title: Efficient Estimation Under Staggered Treatment Timing + maintainer: Pedro H.C. Sant'Anna + description: |- + Efficiently estimates treatment effects in settings with randomized staggered rollouts, using tools + proposed by Roth and Sant'Anna (2023) . + date_publication: '2025-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=staggered + url_git: '' +StakeholderAnalysis: + version: '1.2' + title: Measuring Stakeholder Influence + maintainer: Lech Kujawski + description: Proposes an original instrument for measuring stakeholder influence + on the development of an infrastructure project that is carried through by a municipality, + drawing on stakeholder classifications (Mitchell, Agle, & Wood, 1997) and input-output + modelling (Hester & Adams, 2013). Mitchell R., Agle B.R., & Wood D.J. + Hester, P.T., & Adams, K.M. (2013) . + date_publication: '2017-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StakeholderAnalysis + url_git: '' +StAMPP: + version: 1.6.3 + title: Statistical Analysis of Mixed Ploidy Populations + maintainer: LW Pembleton + description: |- + Allows users to calculate pairwise Nei's Genetic Distances (Nei 1972), pairwise Fixation + Indexes (Fst) (Weir & Cockerham 1984) and also Genomic Relationship matrixes following Yang et al. (2010) in mixed and single + ploidy populations. Bootstrapping across loci is implemented during Fst calculation to generate confidence intervals and p-values + around pairwise Fst values. StAMPP utilises SNP genotype data of any ploidy level (with the ability to handle missing data) and is coded to + utilise multithreading where available to allow efficient analysis of large datasets. StAMPP is able to handle genotype data from genlight objects + allowing integration with other packages such adegenet. + Please refer to LW Pembleton, NOI Cogan & JW Forster, 2013, Molecular Ecology Resources, 13(5), 946-952. for the appropriate citation and user manual. Thank you in advance. + date_publication: '2021-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StAMPP + url_git: https://github.com/lpembleton/StAMPP +stampr: + version: 0.3.1 + title: Spatial Temporal Analysis of Moving Polygons + maintainer: Jed Long + description: |- + Perform spatial temporal analysis of moving polygons; a + longstanding analysis problem in Geographic Information Systems. Facilitates + directional analysis, distance analysis, and some other simple functionality for + examining spatial-temporal patterns of moving polygons. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stampr + url_git: https://github.com/jedalong/stampr +stan4bart: + version: 0.0-10 + title: |- + Bayesian Additive Regression Trees with Stan-Sampled Parametric + Extensions + maintainer: Vincent Dorie + description: Fits semiparametric linear and multilevel models with non-parametric + additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch + (2010) ) components and Stan (Stan Development Team (2021) + ) sampled parametric ones. Multilevel models can be expressed + using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) ). + date_publication: '2024-09-04' + bug_reports: https://github.com/vdorie/stan4bart/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stan4bart + url_git: https://github.com/vdorie/stan4bart +STAND: + version: '2.0' + title: Statistical Analysis of Non-Detects + maintainer: E. P. Adams + description: |- + Provides functions for the analysis of + occupational and environmental data with non-detects. Maximum + likelihood (ML) methods for censored log-normal data and + non-parametric methods based on the product limit estimate (PLE) + for left censored data are used to calculate all of the + statistics recommended by the American Industrial Hygiene + Association (AIHA) for the complete data case. Functions for + the analysis of complete samples using exact methods are also + provided for the lognormal model. Revised from 2007-11-05 + 'survfit~1'. + date_publication: '2015-09-25' + bug_reports: '' + url: http://www.csm.ornl.gov/esh/statoed/ + url_cran: https://CRAN.R-project.org/package=STAND + url_git: '' +standardize: + version: 0.2.2 + title: Tools for Standardizing Variables for Regression in R + maintainer: Christopher D. Eager + description: |- + Tools which allow regression variables to be placed on similar + scales, offering computational benefits as well as easing interpretation of + regression output. + date_publication: '2021-03-05' + bug_reports: https://github.com/CDEager/standardize/issues + url: '' + url_cran: https://CRAN.R-project.org/package=standardize + url_git: https://github.com/CDEager/standardize +standardlastprofile: + version: 1.0.0 + title: Data Package for BDEW Standard Load Profiles in Electricity + maintainer: Markus Döring + description: |- + Data on standard load profiles from the German Association of + Energy and Water Industries (BDEW Bundesverband der Energie- und + Wasserwirtschaft e.V.) in a tidy format. The data and methodology are + described in VDEW (1999), "Repräsentative VDEW-Lastprofile", + . + The package also offers an interface for generating a standard load profile + over a user-defined period. For the algorithm, see VDEW (2000), + "Anwendung der Repräsentativen VDEW-Lastprofile step-by-step", + . + date_publication: '2023-12-11' + bug_reports: https://github.com/flrd/standardlastprofile/issues + url: https://flrd.github.io/standardlastprofile/ + url_cran: https://CRAN.R-project.org/package=standardlastprofile + url_git: https://github.com/flrd/standardlastprofile +standartox: + version: 0.0.2 + title: Ecotoxicological Information from the Standartox Database + maintainer: Andreas Scharmüller + description: |- + The database offers cleaned, + harmonized and aggregated ecotoxicological test data, which can + be used for assessing effects and risks of chemical concentrations + found in the environment. + date_publication: '2022-08-08' + bug_reports: https://github.com/andschar/standartox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=standartox + url_git: https://github.com/andschar/standartox +standby: + version: 0.2.0 + title: Alerts, Notifications and Loading Screen in 'Shiny' + maintainer: Aravind Hebbali + description: |- + Easily create alerts, notifications, modals, info tips and loading + screens in 'Shiny'. Includes several options to customize alerts and + notifications by including text, icons, images and buttons. When wrapped + around a 'Shiny' output, loading screen is automatically displayed while + the output is being recalculated. + date_publication: '2024-10-28' + bug_reports: https://github.com/rsquaredacademy/standby/issues + url: https://standby.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=standby + url_git: https://github.com/rsquaredacademy/standby +StanHeaders: + version: 2.32.10 + title: C++ Header Files for Stan + maintainer: Ben Goodrich + description: The C++ header files of the Stan project are provided by this package, + but it contains little R code or documentation. The main reference is the vignette. + There is a shared object containing part of the 'CVODES' library, but its functionality + is not accessible from R. 'StanHeaders' is primarily useful for developers who + want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file + to build on the Stan library without incurring unnecessary dependencies. The Stan + project develops a probabilistic programming language that implements full or + approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' + methods and implements (optionally penalized) maximum likelihood estimation via + optimization. The Stan library includes an advanced automatic differentiation + scheme, 'templated' statistical and linear algebra functions that can handle the + automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a + parser for the Stan language. The 'rstan' package provides user-facing R functions + to parse, compile, test, estimate, and analyze Stan models. + date_publication: '2024-07-15' + bug_reports: '' + url: https://mc-stan.org/ + url_cran: https://CRAN.R-project.org/package=StanHeaders + url_git: '' +StanMoMo: + version: 1.2.0 + title: Bayesian Mortality Modelling with 'Stan' + maintainer: Karim Barigou + description: |- + Implementation of popular mortality models using the 'rstan' + package, which provides the R interface to the 'Stan' C++ library for + Bayesian estimation. The package supports well-known models proposed in the + actuarial and demographic literature including the Lee-Carter (1992) + and the Cairns-Blake-Dowd (2006) + models. By a simple call, the user + inputs deaths and exposures and the package outputs the MCMC simulations for + each parameter, the log likelihoods and predictions. Moreover, the package + includes tools for model selection and Bayesian model averaging by leave + future-out validation. + date_publication: '2023-09-23' + bug_reports: https://github.com/kabarigou/StanMoMo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StanMoMo + url_git: https://github.com/kabarigou/StanMoMo +stapler: + version: 0.7.1 + title: Simultaneous Truth and Performance Level Estimation + maintainer: John Muschelli + description: |- + An implementation of Simultaneous Truth and + Performance Level Estimation (STAPLE) . This + method is used when there are multiple raters for an object, typically an + image, and this method fuses these ratings into one rating. It uses an + expectation-maximization method to estimate this rating and the individual + specificity/sensitivity for each rater. + date_publication: '2020-01-09' + bug_reports: https://github.com/muschellij2/stapler/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stapler + url_git: https://github.com/muschellij2/stapler +staplr: + version: 3.2.2 + title: A Toolkit for PDF Files + maintainer: Priyanga Dilini Talagala + description: |- + Provides functions to manipulate PDF files: + fill out PDF forms; + merge multiple PDF files into one; + remove selected pages from a file; + rename multiple files in a directory; + rotate entire pdf document; + rotate selected pages of a pdf file; + Select pages from a file; + splits single input PDF document into individual pages; + splits single input PDF document into parts from given points. + date_publication: '2023-09-18' + bug_reports: https://github.com/pridiltal/staplr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=staplr + url_git: '' +staRdom: + version: 1.1.28 + title: PARAFAC Analysis of EEMs from DOM + maintainer: Matthias Pucher + description: This is a user-friendly way to run a parallel factor (PARAFAC) analysis + (Harshman, 1971) on excitation emission matrix (EEM) data + from dissolved organic matter (DOM) samples (Murphy et al., 2013) . + The analysis includes profound methods for model validation. Some additional functions + allow the calculation of absorbance slope parameters and create beautiful plots. + date_publication: '2023-06-16' + bug_reports: https://github.com/MatthiasPucher/staRdom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=staRdom + url_git: '' +STAREG: + version: 1.0.3 + title: |- + An Empirical Bayes Approach for Replicability Analysis Across + Two Studies + maintainer: Yan Li + description: A robust and powerful empirical Bayesian approach is developed for + replicability analysis of two large-scale experimental studies. The method controls + the false discovery rate by using the joint local false discovery rate based on + the replicability null as the test statistic. An EM algorithm combined with a + shape constraint nonparametric method is used to estimate unknown parameters and + functions. [Li, Y. et al., (2023), ]. + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STAREG + url_git: '' +stargazer: + version: 5.2.3 + title: Well-Formatted Regression and Summary Statistics Tables + maintainer: Marek Hlavac + description: |- + Produces LaTeX code, HTML/CSS code and ASCII text for well-formatted tables that hold + regression analysis results from several models side-by-side, as well as summary + statistics. + date_publication: '2022-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stargazer + url_git: '' +starm: + version: 0.1.0 + title: Spatio-Temporal Autologistic Regression Model + maintainer: Yannis Barboni + description: Estimates the coefficients of the two-time centered autologistic regression + model based on Gegout-Petit A., Guerin-Dubrana L., Li S. "A new centered spatio-temporal + autologistic regression model. Application to local spread of plant diseases." + 2019. , using a grid of binary variables to estimate the spread + of a disease on the grid over the years. + date_publication: '2020-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=starm + url_git: '' +starma: + version: '1.3' + title: |- + Modelling Space Time AutoRegressive Moving Average (STARMA) + Processes + maintainer: Felix Cheysson + description: Statistical functions to identify, estimate and diagnose a Space-Time + AutoRegressive Moving Average (STARMA) model. + date_publication: '2016-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=starma + url_git: '' +starnet: + version: 0.0.7 + title: Stacked Elastic Net + maintainer: Armin Rauschenberger + description: Implements stacked elastic net regression (Rauschenberger 2021, ). + The elastic net generalises ridge and lasso regularisation (Zou 2005, ). + Instead of fixing or tuning the mixing parameter alpha, we combine multiple alpha + by stacked generalisation (Wolpert 1992 ). + date_publication: '2024-09-20' + bug_reports: https://github.com/rauschenberger/starnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=starnet + url_git: https://github.com/rauschenberger/starnet +starry: + version: 0.1.2 + title: Explore Data with Plots and Tables + maintainer: Joe Chelladurai + description: |- + Provides modular functions and applications for quickly generating + plots and tables. Each modular function opens a graphical user interface + providing the user with options to create and customise plots and tables. + date_publication: '2023-01-16' + bug_reports: https://github.com/joe-chelladurai/starry/issues + url: https://joe-chelladurai.github.io/starry/ + url_cran: https://CRAN.R-project.org/package=starry + url_git: '' +stars: + version: 0.6-8 + title: Spatiotemporal Arrays, Raster and Vector Data Cubes + maintainer: Edzer Pebesma + description: |- + Reading, manipulating, writing and plotting + spatiotemporal arrays (raster and vector data cubes) in 'R', using 'GDAL' + bindings provided by 'sf', and 'NetCDF' bindings by 'ncmeta' and 'RNetCDF'. + date_publication: '2025-02-01' + bug_reports: https://github.com/r-spatial/stars/issues/ + url: https://r-spatial.github.io/stars/ + url_cran: https://CRAN.R-project.org/package=stars + url_git: https://github.com/r-spatial/stars/ +starschemar: + version: 1.2.5 + title: Obtaining Stars from Flat Tables + maintainer: Jose Samos + description: |- + Data in multidimensional systems is obtained from operational + systems and is transformed to adapt it to the new structure. + Frequently, the operations to be performed aim to transform a flat + table into a star schema. Transformations can be carried out using + professional extract, transform and load tools or tools intended for + data transformation for end users. With the tools mentioned, this + transformation can be carried out, but it requires a lot of work. The + main objective of this package is to define transformations that allow + obtaining stars from flat tables easily. In addition, it includes + basic data cleaning, dimension enrichment, incremental data refresh + and query operations, adapted to this context. + date_publication: '2024-05-02' + bug_reports: https://github.com/josesamos/starschemar/issues + url: https://josesamos.github.io/starschemar/ + url_cran: https://CRAN.R-project.org/package=starschemar + url_git: https://github.com/josesamos/starschemar +starsExtra: + version: 0.2.8 + title: Miscellaneous Functions for Working with 'stars' Rasters + maintainer: Michael Dorman + description: 'Miscellaneous functions for working with ''stars'' objects, mainly + single-band rasters. Currently includes functions for: (1) focal filtering, (2) + detrending of Digital Elevation Models, (3) calculating flow length, (4) calculating + the Convergence Index, (5) calculating topographic aspect and topographic slope.' + date_publication: '2024-01-13' + bug_reports: https://github.com/michaeldorman/starsExtra/issues/ + url: https://michaeldorman.github.io/starsExtra/ + url_cran: https://CRAN.R-project.org/package=starsExtra + url_git: https://github.com/michaeldorman/starsExtra/ +starsTileServer: + version: 0.1.1 + title: A Dynamic Tile Server for R + maintainer: Bart Kranstauber + description: Makes it possible to serve map tiles for web maps (e.g. leaflet) based + on a function or a stars object without having to render them in advance. This + enables parallelization of the rendering, separating the data source and visualization + location and to provide web services. + date_publication: '2022-08-22' + bug_reports: https://gitlab.com/bartk/starsTileServer/-/issues + url: https://bartk.gitlab.io/starsTileServer + url_cran: https://CRAN.R-project.org/package=starsTileServer + url_git: https://gitlab.com/bartk/starsTileServer +STARTdesign: + version: '1.0' + title: |- + Single to Double Arm Transition Design for Phase II Clinical + Trials + maintainer: Haolun Shi + description: The package is used for calibrating the design parameters for single-to-double + arm transition design proposed by Shi and Yin (2017). The calibration is performed + via numerical enumeration to find the optimal design that satisfies the constraints + on the type I and II error rates. + date_publication: '2017-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STARTdesign + url_git: '' +starter: + version: 0.1.16 + title: Starter Kit for New Projects + maintainer: Daniel D. Sjoberg + description: |- + Get started with new projects by dropping a skeleton of a new + project into a new or existing directory, initialise git repositories, + and create reproducible environments with the 'renv' package. The + package allows for dynamically named files, folders, file content, as + well as the functionality to drop individual template files into + existing projects. + date_publication: '2024-10-15' + bug_reports: https://github.com/ddsjoberg/starter/issues + url: https://www.danieldsjoberg.com/starter/index.html + url_cran: https://CRAN.R-project.org/package=starter + url_git: https://github.com/ddsjoberg/starter +startR: + version: 2.4.0 + title: Automatically Retrieve Multidimensional Distributed Data Sets + maintainer: Victoria Agudetse + description: |- + Tool to automatically fetch, transform and arrange subsets of + multi- dimensional data sets (collections of files) stored in local and/or + remote file systems or servers, using multicore capabilities where possible. + The tool provides an interface to perceive a collection of data sets as a single + large multidimensional data array, and enables the user to request for automatic + retrieval, processing and arrangement of subsets of the large array. Wrapper + functions to add support for custom file formats can be plugged in/out, making + the tool suitable for any research field where large multidimensional data sets + are involved. + date_publication: '2024-09-19' + bug_reports: https://earth.bsc.es/gitlab/es/startR/-/issues + url: https://earth.bsc.es/gitlab/es/startR/ + url_cran: https://CRAN.R-project.org/package=startR + url_git: '' +STARTS: + version: 1.3-8 + title: Functions for the STARTS Model + maintainer: Alexander Robitzsch + description: |2- + + Contains functions for estimating the STARTS model of + Kenny and Zautra (1995, 2001) , + . Penalized maximum likelihood + estimation and Markov Chain Monte Carlo estimation are + also provided, see Luedtke, Robitzsch and Wagner (2018) + . + date_publication: '2022-05-19' + bug_reports: '' + url: https://sites.google.com/site/alexanderrobitzsch2/software + url_cran: https://CRAN.R-project.org/package=STARTS + url_git: https://github.com/alexanderrobitzsch/STARTS +startup: + version: 0.23.0 + title: Friendly R Startup Configuration + maintainer: Henrik Bengtsson + description: Adds support for R startup configuration via '.Renviron.d' and '.Rprofile.d' + directories in addition to '.Renviron' and '.Rprofile' files. This makes it possible + to keep private / secret environment variables separate from other environment + variables. It also makes it easier to share specific startup settings by simply + copying a file to a directory. + date_publication: '2024-12-08' + bug_reports: https://github.com/HenrikBengtsson/startup/issues + url: https://henrikbengtsson.github.io/startup/ + url_cran: https://CRAN.R-project.org/package=startup + url_git: https://github.com/HenrikBengtsson/startup +startupmsg: + version: 1.0.0 + title: Utilities for Start-Up Messages + maintainer: Peter Ruckdeschel + description: Provides utilities to create or suppress start-up messages. + date_publication: '2025-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=startupmsg + url_git: '' +starvars: + version: 1.1.10 + title: |- + Vector Logistic Smooth Transition Models Estimation and + Prediction + maintainer: Andrea Bucci + description: Allows the user to estimate a vector logistic smooth transition autoregressive + model via maximum log-likelihood or nonlinear least squares. It further permits + to test for linearity in the multivariate framework against a vector logistic + smooth transition autoregressive model with a single transition variable. The + estimation method is discussed in Terasvirta and Yang (2014, ). + Also, realized covariances can be constructed from stock market prices or returns, + as explained in Andersen et al. (2001, ). + date_publication: '2022-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=starvars + url_git: https://github.com/andbucci/starvars +starvz: + version: 0.8.2 + title: R-Based Visualization Techniques for Task-Based Applications + maintainer: Lucas Leandro Nesi + description: |- + Performance analysis workflow that combines the power of the R + language (and the tidyverse realm) and many auxiliary tools to + provide a consistent, flexible, extensible, fast, and versatile + framework for the performance analysis of task-based applications + that run on top of the StarPU runtime (with its MPI (Message + Passing Interface) layer for multi-node support). Its goal is to + provide a fruitful prototypical environment to conduct performance + analysis hypothesis-checking for task-based applications that run + on heterogeneous (multi-GPU, multi-core) multi-node HPC + (High-performance computing) platforms. + date_publication: '2024-09-08' + bug_reports: https://github.com/schnorr/starvz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=starvz + url_git: https://github.com/schnorr/starvz +starwarsdb: + version: 0.1.2 + title: |- + Relational Data from the 'Star Wars' API for Learning and + Teaching + maintainer: Garrick Aden-Buie + description: |- + Provides data about the 'Star Wars' movie franchise + in a set of relational tables or as a complete 'DuckDB' database. All + data was collected from the open source 'Star Wars' API + . + date_publication: '2020-11-02' + bug_reports: https://github.com/gadenbuie/starwarsdb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=starwarsdb + url_git: https://github.com/gadenbuie/starwarsdb +STAT: + version: 0.1.0 + title: Interactive Document for Working with Basic Statistical Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of basic statistical analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2019-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STAT + url_git: '' +STAT2: + version: 0.1.0 + title: Interactive Document for Working with Basic Statistical Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of basic statistical analysis + using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package + function as well as at . + date_publication: '2020-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STAT2 + url_git: '' +Stat2Data: + version: 2.0.0 + title: Datasets for Stat2 + maintainer: Robin Lock + description: |- + Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). + The package also includes data for the first edition, Stat2: Building Models for a World of Data + and a few functions for plotting diagnostics. + date_publication: '2019-01-04' + bug_reports: https://github.com/statmanrobin/Stat2Data + url: '' + url_cran: https://CRAN.R-project.org/package=Stat2Data + url_git: https://github.com/statmanrobin/Stat2Data +Statamarkdown: + version: 0.9.2 + title: '''Stata'' Markdown' + maintainer: Doug Hemken + description: Settings and functions to extend the 'knitr' 'Stata' engine. + date_publication: '2023-12-04' + bug_reports: https://github.com/Hemken/Statamarkdown/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Statamarkdown + url_git: '' +statar: + version: 0.7.6 + title: Tools Inspired by 'Stata' to Manipulate Tabular Data + maintainer: Matthieu Gomez + description: |- + A set of tools inspired by 'Stata' to explore data.frames ('summarize', + 'tabulate', 'xtile', 'pctile', 'binscatter', elapsed quarters/month, lead/lag). + date_publication: '2023-08-19' + bug_reports: https://github.com/matthieugomez/statar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statar + url_git: https://github.com/matthieugomez/statar +statBasics: + version: 0.2.2 + title: Basic Functions to Statistical Methods Course + maintainer: Gilberto Sassi + description: 'Basic statistical methods with some modifications for the course Statistical + Methods at Federal University of Bahia (Brazil). All methods in this packages + are explained in the text book of Montgomery and Runger (2010) .' + date_publication: '2024-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statBasics + url_git: '' +statcanR: + version: 0.2.6 + title: Client for Statistics Canada's Open Economic Data + maintainer: Thierry Warin + description: |- + An easy connection with R to Statistics Canada's Web Data Service. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment. + Warin, Le Duc (2019) . + date_publication: '2023-08-17' + bug_reports: https://github.com/warint/statcanR/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=statcanR + url_git: https://github.com/warint/statcanR/ +statcheck: + version: 1.5.0 + title: Extract Statistics from Articles and Recompute P-Values + maintainer: Michele B. Nuijten + description: |- + A "spellchecker" for statistics. It checks whether your + p-values match their accompanying test statistic and degrees of + freedom. statcheck searches for null-hypothesis significance test + (NHST) in APA style (e.g., t(28) = 2.2, p < .05). It recalculates the + p-value using the reported test statistic and degrees of freedom. If + the reported and computed p-values don't match, statcheck will flag + the result as an error. If the reported p-value is statistically + significant and the recomputed one is not, or vice versa, the result + will be flagged as a decision error. You can use statcheck directly + on a string of text, but you can also scan a PDF or HTML file, or even + a folder of PDF and/or HTML files. Statcheck needs an external + program to convert PDF to text: Xpdf. Instructions on where and how to + download this program, how to install statcheck, and more details on + what statcheck can and cannot do can be found in the online manual: + . You can find a + point-and-click web interface to scan PDF or HTML or DOCX articles on + . + date_publication: '2024-02-16' + bug_reports: https://github.com/MicheleNuijten/statcheck/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statcheck + url_git: https://github.com/MicheleNuijten/statcheck +statcodelists: + version: 0.9.2 + title: Use Standardized Statistical Codelists + maintainer: Daniel Antal + description: |- + The goal of statcodelists is to promote the reuse and exchange of statistical + information and related metadata with making the internationally standardized SDMX code + lists available for the R user. SDMX has been published as an ISO International Standard + (ISO 17369). The metadata definitions, including the codelists are updated regularly + according to the standard. The authoritative version of the code lists made available in this + package is . + date_publication: '2022-06-28' + bug_reports: https://github.com/antaldaniel/statcodelists/issues + url: https://statcodelists.dataobservatory.eu + url_cran: https://CRAN.R-project.org/package=statcodelists + url_git: https://github.com/antaldaniel +statcomp: + version: 0.1.0 + title: |- + Statistical Complexity and Information Measures for Time Series + Analysis + maintainer: Sebastian Sippel + description: An implementation of local and global statistical complexity measures + (aka Information Theory Quantifiers, ITQ) for time series analysis based on ordinal + statistics (Bandt and Pompe (2002) ). Several + distance measures that operate on ordinal pattern distributions, auxiliary functions + for ordinal pattern analysis, and generating functions for stochastic and deterministic-chaotic + processes for ITQ testing are provided. + date_publication: '2019-10-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statcomp + url_git: '' +statConfR: + version: 0.2.0 + title: Models of Decision Confidence and Measures of Metacognition + maintainer: Manuel Rausch + description: |- + Provides fitting functions and other tools for decision confidence + and metacognition researchers, including meta-d'/d', often considered to be + the gold standard to measure metacognitive efficiency, and information-theoretic measures of metacognition. + Also allows to fit several static models of decision making and confidence. + date_publication: '2025-02-13' + bug_reports: https://github.com/ManuelRausch/StatConfR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statConfR + url_git: https://github.com/ManuelRausch/StatConfR +STATcubeR: + version: 1.0.0 + title: R Interface for the 'STATcube' REST API and Open Government Data + maintainer: Bernhard Meindl + description: |- + Import data from the 'STATcube' REST API or from the open data + portal of Statistics Austria. This package includes a client for API + requests as well as parsing utilities for data which originates from + 'STATcube'. Documentation about 'STATcubeR' is provided by several vignettes + included in the package as well as on the public 'pkgdown' page at + . + date_publication: '2024-11-29' + bug_reports: https://github.com/statistikat/STATcubeR/issues + url: https://statistikat.github.io/STATcubeR/ + url_cran: https://CRAN.R-project.org/package=STATcubeR + url_git: https://github.com/statistikat/STATcubeR +StatDA: + version: 1.7.11 + title: Statistical Analysis for Environmental Data + maintainer: Peter Filzmoser + description: Statistical analysis methods for environmental data are implemented. + There is a particular focus on robust methods, and on methods for compositional + data. In addition, larger data sets from geochemistry are provided. The statistical + methods are described in Reimann, Filzmoser, Garrett, Dutter (2008, ISBN:978-0-470-98581-6). + date_publication: '2023-06-02' + bug_reports: '' + url: http://cstat.tuwien.ac.at/filz/ + url_cran: https://CRAN.R-project.org/package=StatDA + url_git: '' +StatDataML: + version: 1.0-27 + title: Read and Write StatDataML Files + maintainer: David Meyer + description: Support for reading and writing files in StatDataML---an XML-based + data exchange format. + date_publication: '2023-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StatDataML + url_git: '' +statebins: + version: 1.4.0 + title: Create United States Uniform Cartogram Heatmaps + maintainer: Bob Rudis + description: |- + The 'cartogram' heatmaps generated by the included methods + are an alternative to choropleth maps for the United States + and are based on work by the Washington Post graphics department in their report + on "The states most threatened by trade" + (). + "State bins" preserve as much of the geographic placement of the states as + possible but have the look and feel of a traditional heatmap. Functions are + provided that allow for use of a binned, discrete scale, a continuous scale + or manually specified colors depending on what is needed for the underlying data. + date_publication: '2020-07-08' + bug_reports: https://gitlab.com/hrbrmstr/statebins/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statebins + url_git: https://gitlab.com/hrbrmstr/statebins +StateLevelForest: + version: 0.1.0 + title: Historical State-Level Forest Cover Data in the United States + maintainer: Gates Dupont + description: Provides a unique dataset of historical forest cover across all states + in the United States, spanning from 1907 to 2017, along with 1630 as a reference + year. This dataset is important for understanding environmental changes and land + use trends over time. It includes functionality for easy access of the data. + date_publication: '2023-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StateLevelForest + url_git: '' +states: + version: 0.3.2 + title: Create Panels of Independent States + maintainer: Andreas Beger + description: |- + Create panel data consisting of independent states from 1816 to + the present. The package includes the Gleditsch & Ward (G&W) and Correlates + of War (COW) lists of independent states, as well as helper functions for + working with state panel data and standardizing other data sources to + create country-year/month/etc. data. + date_publication: '2023-09-05' + bug_reports: https://github.com/andybega/states/issues + url: https://www.andybeger.com/states/ + url_cran: https://CRAN.R-project.org/package=states + url_git: https://github.com/andybega/states +statespacer: + version: 0.5.0 + title: State Space Modelling in 'R' + maintainer: Dylan Beijers + description: |- + A tool that makes estimating models in state space form + a breeze. See "Time Series Analysis by State Space Methods" by + Durbin and Koopman (2012, ISBN: 978-0-19-964117-8) for details + about the algorithms implemented. + date_publication: '2023-01-27' + bug_reports: https://github.com/DylanB95/statespacer/issues/ + url: https://DylanB95.github.io/statespacer/ + url_cran: https://CRAN.R-project.org/package=statespacer + url_git: https://github.com/DylanB95/statespacer/ +statforbiology: + version: 0.9.9 + title: Tools for Data Analyses in Biology + maintainer: Andrea Onofri + description: 'Contains several tools for nonlinear regression analyses and general + data analysis in biology and agriculture. Contains also datasets for practicing + and teaching purposes. Supports the blog: Onofri (2024) "Fixing the bridge between + biologists and statisticians" and the book: Onofri + (2024) "Experimental Methods in Agriculture" . + The blog is a collection of short articles aimed at improving the efficiency of + communication between biologists and statisticians, as pointed out in Kozak (2016) + , spreading a better awareness of the potential + usefulness, beauty and limitations of biostatistic.' + date_publication: '2024-10-21' + bug_reports: https://github.com/OnofriAndreaPG/statforbiology/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statforbiology + url_git: https://github.com/OnofriAndreaPG/statforbiology +statgenGWAS: + version: 1.0.10 + title: Genome Wide Association Studies + maintainer: Bart-Jan van Rossum + description: |- + Fast single trait Genome Wide Association Studies (GWAS) following + the method described in Kang et al. (2010), . + One of a series of statistical genetic packages for streamlining the + analysis of typical plant breeding experiments developed by Biometris. + date_publication: '2024-11-15' + bug_reports: https://github.com/Biometris/statgenGWAS/issues + url: https://biometris.github.io/statgenGWAS/index.html + url_cran: https://CRAN.R-project.org/package=statgenGWAS + url_git: https://github.com/Biometris/statgenGWAS/ +statgenGxE: + version: 1.0.9 + title: Genotype by Environment (GxE) Analysis + maintainer: Bart-Jan van Rossum + description: |- + Analysis of multi environment data of plant breeding experiments + following the analyses described in Malosetti, Ribaut, + and van Eeuwijk (2013), . + One of a series of statistical genetic packages for streamlining the analysis of + typical plant breeding experiments developed by Biometris. + Some functions have been created to be used in conjunction with the R + package 'asreml' for the 'ASReml' software, which can be obtained upon + purchase from 'VSN' international (). + date_publication: '2024-09-18' + bug_reports: https://github.com/Biometris/statgenGxE/issues + url: https://biometris.github.io/statgenGxE/index.html + url_cran: https://CRAN.R-project.org/package=statgenGxE + url_git: https://github.com/Biometris/statgenGxE/ +statgenHTP: + version: 1.0.7 + title: High Throughput Phenotyping (HTP) Data Analysis + maintainer: Bart-Jan van Rossum + description: |- + Phenotypic analysis of data coming from high throughput + phenotyping (HTP) platforms, including different types of outlier detection, + spatial analysis, and parameter estimation. The package is being developed + within the EPPN2020 project (). + Some functions have been created to be used in conjunction with the R + package 'asreml' for the 'ASReml' software, which can be obtained upon + purchase from 'VSN' international (). + date_publication: '2024-10-14' + bug_reports: https://github.com/Biometris/statgenHTP/issues + url: https://biometris.github.io/statgenHTP/index.html + url_cran: https://CRAN.R-project.org/package=statgenHTP + url_git: https://github.com/Biometris/statgenHTP/ +statgenIBD: + version: 1.0.8 + title: Calculation of IBD Probabilities + maintainer: Bart-Jan van Rossum + description: |- + For biparental, three and four-way crosses Identity by Descent + (IBD) probabilities can be calculated using Hidden Markov Models and + inheritance vectors following Lander and Green + () and Huang + (). One of a series of statistical genetic + packages for streamlining the analysis of typical plant breeding experiments + developed by Biometris. + date_publication: '2025-02-05' + bug_reports: https://github.com/Biometris/statgenIBD/issues + url: https://biometris.github.io/statgenIBD/index.html + url_cran: https://CRAN.R-project.org/package=statgenIBD + url_git: https://github.com/Biometris/statgenIBD/ +statgenMPP: + version: 1.0.4 + title: QTL Mapping for Multi Parent Populations + maintainer: Bart-Jan van Rossum + description: |- + For Multi Parent Populations (MPP) Identity By Descend (IBD) + probabilities are computed using Hidden Markov Models. These probabilities + are then used in a mixed model approach for QTL Mapping as described in + Li et al. (). + date_publication: '2025-02-11' + bug_reports: https://github.com/Biometris/statgenMPP/issues + url: https://biometris.github.io/statgenMPP/index.html + url_cran: https://CRAN.R-project.org/package=statgenMPP + url_git: https://github.com/Biometris/statgenMPP/ +statgenQTLxT: + version: 1.0.2 + title: Multi-Trait and Multi-Trial Genome Wide Association Studies + maintainer: Bart-Jan van Rossum + description: |- + Fast multi-trait and multi-trail Genome Wide Association Studies + (GWAS) following the method described in Zhou and Stephens. (2014), + . One of a series of statistical genetic packages + for streamlining the analysis of typical plant breeding experiments + developed by Biometris. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statgenQTLxT + url_git: '' +statgenSTA: + version: 1.0.14 + title: Single Trial Analysis (STA) of Field Trials + maintainer: Bart-Jan van Rossum + description: |- + Phenotypic analysis of field trials using mixed models with and + without spatial components. One of a series of statistical genetic packages + for streamlining the analysis of typical plant breeding experiments developed + by Biometris. + Some functions have been created to be used in conjunction with the R + package 'asreml' for the 'ASReml' software, which can be obtained upon + purchase from 'VSN' international (). + date_publication: '2024-10-14' + bug_reports: https://github.com/Biometris/statgenSTA/issues + url: https://biometris.github.io/statgenSTA/index.html + url_cran: https://CRAN.R-project.org/package=statgenSTA + url_git: https://github.com/Biometris/statgenSTA/ +statGraph: + version: 1.0.6 + title: Statistical Methods for Graphs + maintainer: Andre Fujita + description: |- + Contains statistical methods to analyze graphs, such as graph parameter estimation, + model selection based on the Graph Information Criterion, statistical tests to discriminate two or more populations of graphs, + correlation between graphs, and clustering of graphs. + References: Takahashi et al. (2012) , Fujita et al. (2017) , + Fujita et al. (2017) , Fujita et al. (2019) . + date_publication: '2024-09-01' + bug_reports: '' + url: https://www.ime.usp.br/~fujita/software.html + url_cran: https://CRAN.R-project.org/package=statGraph + url_git: '' +staticryptR: + version: 0.1.0 + title: Encrypt HTML Files Using 'staticrypt' + maintainer: Nikita Tkachenko + description: |- + Provides a convenient interface to the 'staticrypt' by Robin Moisson ---'Node.js' package for + adding a password protection layer to static HTML pages. This package can be + integrated into the post-render process of 'quarto' documents to secure them + with a password. + date_publication: '2024-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=staticryptR + url_git: '' +stationaRy: + version: 0.5.1 + title: Detailed Meteorological Data from Stations All Over the World + maintainer: Richard Iannone + description: |- + Acquire hourly meteorological data from stations located all over + the world. There is a wealth of data available, with historic weather data + accessible from nearly 30,000 stations. The available data is automatically + downloaded from a data repository and processed into a 'tibble' for the + exact range of years requested. A relative humidity approximation is + provided using the 'August-Roche-Magnus' formula, which was adapted from + Alduchov and Eskridge (1996) . + date_publication: '2020-01-12' + bug_reports: https://github.com/rich-iannone/stationaRy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stationaRy + url_git: https://github.com/rich-iannone/stationaRy +statip: + version: 0.2.3 + title: |- + Statistical Functions for Probability Distributions and + Regression + maintainer: Paul Poncet + description: |- + A collection of miscellaneous statistical functions for + probability distributions: 'dbern()', 'pbern()', 'qbern()', 'rbern()' for + the Bernoulli distribution, and 'distr2name()', 'name2distr()' for + distribution names; + probability density estimation: 'densityfun()'; + most frequent value estimation: 'mfv()', 'mfv1()'; + other statistical measures of location: 'cv()' (coefficient of variation), + 'midhinge()', 'midrange()', 'trimean()'; + construction of histograms: 'histo()', 'find_breaks()'; + calculation of the Hellinger distance: 'hellinger()'; + use of classical kernels: 'kernelfun()', 'kernel_properties()'; + univariate piecewise-constant regression: 'picor()'. + date_publication: '2019-11-17' + bug_reports: https://github.com/paulponcet/statip/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statip + url_git: https://github.com/paulponcet/statip +statisfactory: + version: 1.0.4 + title: Statistical and Geometrical Tools + maintainer: Adam B. Smith + description: |- + A collection of statistical and geometrical tools + including the aligned rank transform (ART; Higgins et al. + 1990 ; Peterson 2002 + ; Wobbrock et al. 2011 + ), 2-D histograms and + histograms with overlapping bins, a function for making all + possible formulae within a set of constraints, amongst others. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statisfactory + url_git: https://github.com/adamlilith/statisfactory +StatMatch: + version: 1.4.3 + title: Statistical Matching or Data Fusion + maintainer: Marcello D'Orazio + description: Integration of two data sources referred to the same target population + which share a number of variables. Some functions can also be used to impute missing + values in data sets through hot deck imputation methods. Methods to perform statistical + matching when dealing with data from complex sample surveys are available too. + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StatMatch + url_git: https://github.com/marcellodo/StatMatch +statmod: + version: 1.5.0 + title: Statistical Modeling + maintainer: Gordon Smyth + description: A collection of algorithms and functions to aid statistical modeling. + Includes limiting dilution analysis (aka ELDA), growth curve comparisons, mixed + linear models, heteroscedastic regression, inverse-Gaussian probability calculations, + Gauss quadrature and a secure convergence algorithm for nonlinear models. Also + includes advanced generalized linear model functions including Tweedie and Digamma + distributional families, secure convergence and exact distributional calculations + for unit deviances. + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statmod + url_git: '' +statnet: + version: '2019.6' + title: Software Tools for the Statistical Analysis of Network Data + maintainer: Martina Morris + description: |- + Statnet is a collection of packages for statistical network analysis that are + designed to work together because they share common data representations and 'API' + design. They provide an integrated set of tools for the representation, + visualization, analysis, and simulation of many different forms of network data. + This package is designed to make it easy to install and load the + key 'statnet' packages in a single step. Learn more about 'statnet' + at . Tutorials for many packages can be found + at . For an introduction to functions in this package, + type help(package='statnet'). + date_publication: '2019-06-14' + bug_reports: https://github.com/statnet/statnet/issues + url: http://statnet.org + url_cran: https://CRAN.R-project.org/package=statnet + url_git: '' +statnet.common: + version: 4.11.0 + title: |- + Common R Scripts and Utilities Used by the Statnet Project + Software + maintainer: Pavel N. Krivitsky + description: Non-statistical utilities used by the software developed by the Statnet + Project. They may also be of use to others. + date_publication: '2025-01-08' + bug_reports: https://github.com/statnet/statnet.common/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=statnet.common + url_git: '' +statnetWeb: + version: 0.5.8 + title: A Shiny App for Network Modeling with 'statnet' + maintainer: Martina Morris + description: |- + A graphical user interface for cross-sectional network modeling + with the 'statnet' software suite . + date_publication: '2024-07-17' + bug_reports: https://github.com/statnet/statnetWeb/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=statnetWeb + url_git: https://github.com/statnet/statnetWeb +statnipokladna: + version: 0.7.4 + title: Use Data from the Czech Public Finance Database + maintainer: Petr Bouchal + description: |- + Get programmatic access to data from the Czech public + budgeting and accounting database, Státní pokladna + . + date_publication: '2024-08-21' + bug_reports: https://github.com/petrbouchal/statnipokladna/issues + url: https://petrbouchal.xyz/statnipokladna/ + url_cran: https://CRAN.R-project.org/package=statnipokladna + url_git: https://github.com/petrbouchal/statnipokladna +StatPerMeCo: + version: 0.1.0 + title: |- + Statistical Performance Measures to Evaluate Covariance Matrix + Estimates + maintainer: Carlos Trucios + description: Statistical performance measures used in the econometric literature + to evaluate conditional covariance/correlation matrix estimates (MSE, MAE, Euclidean + distance, Frobenius distance, Stein distance, asymmetric loss function, eigenvalue + loss function and the loss function defined in Eq. (4.6) of Engle et al. (2016) + ). Additionally, compute Eq. (3.1) and (4.2) of Li et + al. (2016) to compare the factor loading matrix. + The statistical performance measures implemented have been previously used in, + for instance, Laurent et al. (2012) , Amendola et al. (2015) + and Becker et al. (2015) . + date_publication: '2017-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StatPerMeCo + url_git: '' +statprograms: + version: 0.2.0 + title: Graduate Statistics Program Datasets + maintainer: Brett Klamer + description: A small collection of data on graduate statistics programs from the + United States. + date_publication: '2018-06-17' + bug_reports: '' + url: http://brettklamer.com/work/statprograms/ + url_cran: https://CRAN.R-project.org/package=statprograms + url_git: '' +statpsych: + version: 1.7.0 + title: Statistical Methods for Psychologists + maintainer: Douglas G. Bonett + description: |- + Implements confidence interval and sample size methods that + are especially useful in psychological research. The methods can be + applied in 1-group, 2-group, paired-samples, and multiple-group designs + and to a variety of parameters including means, medians, proportions, + slopes, standardized mean differences, standardized linear contrasts + of means, plus several measures of correlation and association. + Confidence interval and sample size functions are given for single + parameters as well as differences, ratios, and linear contrasts of + parameters. The sample size functions can be used to approximate the + sample size needed to estimate a parameter or function of parameters + with desired confidence interval precision or to perform a variety of + hypothesis tests (directional two-sided, equivalence, superiority, + noninferiority) with desired power. For details see: Statistical Methods + for Psychologists, Volumes 1 – 4, . + date_publication: '2024-12-19' + bug_reports: https://github.com/dgbonett/statpsych/issues + url: https://dgbonett.github.io/statpsych/ + url_cran: https://CRAN.R-project.org/package=statpsych + url_git: https://github.com/dgbonett/statpsych/ +statquotes: + version: 0.3.2 + title: Quotes on Statistics, Data Visualization and Science + maintainer: Michael Friendly + description: |- + Generates a random quotation from a database of quotes on topics + in statistics, data visualization and science. Other functions allow searching + the quotes database by key term tags, or authors or creating a word cloud. + The output is designed to be suitable for use at the console, in Rmarkdown + and LaTeX. + date_publication: '2023-10-10' + bug_reports: https://github.com/friendly/statquotes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statquotes + url_git: https://github.com/friendly/statquotes/ +StatRank: + version: 0.0.6 + title: |- + Statistical Rank Aggregation: Inference, Evaluation, and + Visualization + maintainer: Hossein Azari Soufiani + description: |- + A set of methods to implement Generalized Method of Moments and Maximal + Likelihood methods for Random Utility Models. These methods are meant to + provide inference on rank comparison data. These methods accept full, + partial, and pairwise rankings, and provides methods to break down full or + partial rankings into their pairwise components. Please see Generalized + Method-of-Moments for Rank Aggregation from NIPS 2013 for a description of + some of our methods. + date_publication: '2015-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StatRank + url_git: '' +stats19: + version: 3.3.1 + title: Work with Open Road Traffic Casualty Data from Great Britain + maintainer: Robin Lovelace + description: |- + Tools to help download, process and analyse the UK road collision data collected using the + 'STATS19' form. The datasets are provided as 'CSV' files with detailed road safety information about the + circumstances of car crashes and other incidents on the roads resulting in casualties in Great Britain + from 1979 to present. Tables are available on 'colissions' with the circumstances (e.g. speed limit + of road), information about 'vehicles' involved (e.g. type of vehicle), and 'casualties' (e.g. age). + The statistics relate only to events on public roads that were reported + to the police, and subsequently recorded, using the 'STATS19' collision reporting form. See + the Department for Transport website + for more + information on these datasets. + The package is described in a paper in the Journal of Open Source Software + (Lovelace et al. 2019) . + See + Gilardi et al. (2022) , + Vidal-Tortosa et al. (2021) , and + Tait et al. (2023) for examples of how the data can be used for + methodological and empirical road safety research. + date_publication: '2025-01-15' + bug_reports: https://github.com/ropensci/stats19/issues + url: https://docs.ropensci.org/stats19/ + url_cran: https://CRAN.R-project.org/package=stats19 + url_git: https://github.com/ropensci/stats19 +stats4teaching: + version: 0.1.0 + title: Simulate Pedagogical Statistical Data + maintainer: Cabello Esteban + description: |- + Univariate and multivariate normal data simulation. They also supply a brief summary of the analysis for each experiment/design: + - Independent samples. + - One-way and two-way Anova. + - Paired samples (T-Test & Regression). + - Repeated measures (Anova & Multiple Regression). + - Clinical Assay. + date_publication: '2022-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stats4teaching + url_git: '' +statsearchanalyticsr: + version: 0.1.4 + title: An Interface for the 'STAT Search Analytics' 'API' + maintainer: Ben Woodard + description: Pull data from the 'STAT Search Analytics' API . + It was developed by the Search Discovery team to help analyze keyword ranking + data. + date_publication: '2021-09-28' + bug_reports: https://github.com/searchdiscovery/statsearchanalyticsr/issues + url: https://searchdiscovery.github.io/statsearchanalyticsr/ + url_cran: https://CRAN.R-project.org/package=statsearchanalyticsr + url_git: '' +statsExpressions: + version: 1.6.2 + title: Tidy Dataframes and Expressions with Statistical Details + maintainer: Indrajeet Patil + description: |- + Utilities for producing dataframes with rich details for the + most common types of statistical approaches and tests: parametric, + nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation + analyses, contingency table analyses, and meta-analyses. The functions + are pipe-friendly and provide a consistent syntax to work with tidy + data. These dataframes additionally contain expressions with + statistical details, and can be used in graphing packages. This + package also forms the statistical processing backend for + 'ggstatsplot'. References: Patil (2021) . + date_publication: '2024-12-02' + bug_reports: https://github.com/IndrajeetPatil/statsExpressions/issues + url: https://indrajeetpatil.github.io/statsExpressions/ + url_cran: https://CRAN.R-project.org/package=statsExpressions + url_git: https://github.com/IndrajeetPatil/statsExpressions +statsr: + version: 0.3.0 + title: |- + Companion Software for the Coursera Statistics with R + Specialization + maintainer: Merlise Clyde + description: |- + Data and functions to support Bayesian and frequentist inference and decision making + for the Coursera Specialization "Statistics with R". + See for more information. + date_publication: '2021-01-22' + bug_reports: https://github.com/StatsWithR/statsr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=statsr + url_git: https://github.com/StatsWithR/statsr +statswalesr: + version: 0.2.0 + title: Easily Extract Data from 'StatsWales' + maintainer: Jamie Ralph + description: |- + Download data from 'StatsWales' into R. Removes the need for the user to + write their own loops when parsing data from the 'StatsWales' API. Provides functions + for datasets () and metadata + () endpoints. + date_publication: '2022-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statswalesr + url_git: '' +statVisual: + version: 1.2.1 + title: Statistical Visualization Tools + maintainer: Wenfei Zhang + description: Visualization functions in the applications of translational medicine + (TM) and biomarker (BM) development to compare groups by statistically visualizing + data and/or results of analyses, such as visualizing data by displaying in one + figure different groups' histograms, boxplots, densities, scatter plots, error-bar + plots, or trajectory plots, by displaying scatter plots of top principal components + or dendrograms with data points colored based on group information, or visualizing + volcano plots to check the results of whole genome analyses for gene differential + expression. + date_publication: '2020-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=statVisual + url_git: '' +STB: + version: 0.6.5 + title: Simultaneous Tolerance Bounds + maintainer: Andre Schuetzenmeister + description: |- + Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not. + Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed + (studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology. + date_publication: '2021-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STB + url_git: '' +stbl: + version: 0.1.1 + title: Stabilize Function Arguments + maintainer: Jon Harmon + description: |- + A set of consistent, opinionated functions to quickly check + function arguments, coerce them to the desired configuration, or + deliver informative error messages when that is not possible. + date_publication: '2024-05-23' + bug_reports: https://github.com/jonthegeek/stbl/issues + url: https://jonthegeek.github.io/stbl/ + url_cran: https://CRAN.R-project.org/package=stbl + url_git: https://github.com/jonthegeek/stbl +stcos: + version: 0.3.1 + title: Space-Time Change of Support + maintainer: Andrew M. Raim + description: |- + Spatio-temporal change of support (STCOS) methods are designed for statistical inference + on geographic and time domains which differ from those on which the data were observed. In + particular, a parsimonious class of STCOS models supporting Gaussian outcomes was introduced + by Bradley, Wikle, and Holan . The 'stcos' package contains tools which + facilitate use of STCOS models. + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stcos + url_git: https://github.com/holans/ST-COS +stcov: + version: 0.1.0 + title: Stein's Covariance Estimator + maintainer: Brett Naul + description: |- + Estimates a covariance matrix using Stein's isotonized covariance + estimator, or a related estimator suggested by Haff. + date_publication: '2016-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stcov + url_git: '' +stcpR6: + version: 0.9.8 + title: |- + Sequential Test and Change-Point Detection Algorithms Based on + E-Values / E-Detectors + maintainer: Jaehyeok Shin + description: |- + Algorithms of nonparametric sequential test and online + change-point detection for streams of univariate (sub-)Gaussian, binary, + and bounded random variables, introduced in following publications - + Shin et al. (2024) , + Shin et al. (2021) . + date_publication: '2024-10-08' + bug_reports: https://github.com/shinjaehyeok/stcpR6/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stcpR6 + url_git: https://github.com/shinjaehyeok/stcpR6 +stddiff: + version: '3.1' + title: |- + Calculate the Standardized Difference for Numeric, Binary and + Category Variables + maintainer: Zhicheng Du + description: |- + Contains three main functions including + stddiff.numeric(), stddiff.binary() and stddiff.category(). + These are used to calculate the standardized difference between two groups. + It is especially used to evaluate the balance between two groups + before and after propensity score matching. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stddiff + url_git: '' +stdmod: + version: 0.2.11 + title: Standardized Moderation Effect and Its Confidence Interval + maintainer: Shu Fai Cheung + description: |- + Functions for computing a standardized moderation effect + in moderated regression and forming its confidence interval + by nonparametric bootstrapping as proposed in + Cheung, Cheung, Lau, Hui, and Vong (2022) + . Also includes simple-to-use + functions for computing conditional effects (unstandardized + or standardized) and plotting moderation effects. + date_publication: '2024-09-22' + bug_reports: https://github.com/sfcheung/stdmod/issues + url: https://sfcheung.github.io/stdmod/ + url_cran: https://CRAN.R-project.org/package=stdmod + url_git: '' +stdReg: + version: 3.4.1 + title: Regression Standardization + maintainer: Arvid Sjolander + description: Contains functionality for regression standardization. Four general + classes of models are allowed; generalized linear models, conditional generalized + estimating equation models, Cox proportional hazards models and shared frailty + gamma-Weibull models. Sjolander, A. (2016) . + date_publication: '2021-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stdReg + url_git: '' +stdReg2: + version: 1.0.3 + title: Regression Standardization for Causal Inference + maintainer: Michael C Sachs + description: |- + Contains more modern tools for causal inference using regression + standardization. Four general classes of models are implemented; generalized + linear models, conditional generalized estimating equation models, + Cox proportional hazards models, and shared frailty gamma-Weibull models. + Methodological details are described in Sjölander, A. (2016) . + Also includes functionality for doubly robust estimation for generalized linear models + in some special cases, and the ability to implement custom models. + date_publication: '2025-02-28' + bug_reports: https://github.com/sachsmc/stdReg2/issues/ + url: https://sachsmc.github.io/stdReg2/ + url_cran: https://CRAN.R-project.org/package=stdReg2 + url_git: '' +stdvectors: + version: 0.0.5 + title: C++ Standard Library Vectors in R + maintainer: Marco Giuliano + description: Allows the creation and manipulation of C++ std::vector's in R. + date_publication: '2017-02-21' + bug_reports: https://github.com/digEmAll/stdvectors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stdvectors + url_git: https://github.com/digEmAll/stdvectors +steadyICA: + version: 1.0.1 + title: |- + ICA and Tests of Independence via Multivariate Distance + Covariance + maintainer: Benjamin Risk + description: |- + Functions related to multivariate measures of independence and ICA: + -estimate independent components by minimizing distance covariance; + -conduct a test of mutual independence based on distance covariance; + -estimate independent components via infomax (a popular method but generally performs poorer than mdcovica, ProDenICA, and/or fastICA, but is useful for comparisons); + -order indepedent components by skewness; + -match independent components from multiple estimates; + -other functions useful in ICA. + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=steadyICA + url_git: '' +steepness: + version: 0.3-0 + title: Testing Steepness of Dominance Hierarchies + maintainer: David Leiva + description: |- + The steepness package computes steepness as a + property of dominance hierarchies. Steepness is defined as the + absolute slope of the straight line fitted to the normalized + David's scores. The normalized David's scores can be obtained + on the basis of dyadic dominance indices corrected for chance + or by means of proportions of wins. Given an observed + sociomatrix, it computes hierarchy's steepness and estimates + statistical significance by means of a randomization test. + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=steepness + url_git: '' +SteinIV: + version: 0.1-1 + title: Semi-Parametric Stein-Like Estimator with Instrumental Variables + maintainer: Cedric E Ginestet + description: Routines for computing different types of linear estimators, based + on instrumental variables (IVs), including the semi-parametric Stein-like (SPS) + estimator, originally introduced by Judge and Mittelhammer (2004) . + date_publication: '2016-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SteinIV + url_git: '' +stelfi: + version: 1.0.1 + title: |- + Hawkes and Log-Gaussian Cox Point Processes Using Template Model + Builder + maintainer: Charlotte M. Jones-Todd + description: Fit Hawkes and log-Gaussian Cox process models with extensions. Introduced + in Hawkes (1971) a Hawkes process is a self-exciting temporal + point process where the occurrence of an event immediately increases the chance + of another. We extend this to consider self-inhibiting process and a non-homogeneous + background rate. A log-Gaussian Cox process is a Poisson point process where the + log-intensity is given by a Gaussian random field. We extend this to a joint + likelihood formulation fitting a marked log-Gaussian Cox model. In addition, the + package offers functionality to fit self-exciting spatiotemporal point processes. + Models are fitted via maximum likelihood using 'TMB' (Template Model Builder). + Where included 1) random fields are assumed to be Gaussian and are integrated + over using the Laplace approximation and 2) a stochastic partial differential + equation model, introduced by Lindgren, Rue, and Lindström. (2011) , + is defined for the field(s). + date_publication: '2023-10-24' + bug_reports: https://github.com/cmjt/stelfi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stelfi + url_git: https://github.com/cmjt/stelfi/ +stellaR: + version: 0.3-4 + title: |- + Evolutionary Tracks and Isochrones from Pisa Stellar Evolution + Database + maintainer: Matteo Dell'Omodarme + description: |- + Manages and display stellar tracks and isochrones from + Pisa low-mass database. Includes tools for isochrones + construction and tracks interpolation. + date_publication: '2022-04-11' + bug_reports: '' + url: Thedatabaseisdescribedat:http://astro.df.unipi.it/stellar-models/ + url_cran: https://CRAN.R-project.org/package=stellaR + url_git: '' +StemAnalysis: + version: 0.1.0 + title: |- + Reconstructing Tree Growth and Carbon Accumulation with Stem + Analysis Data + maintainer: Huili Wu + description: |- + Use stem analysis data to reconstructing tree growth and carbon accumulation. Users can independently or in combination perform a number of standard tasks for any tree species. + (i) Age class determination. + (ii) The cumulative growth, mean annual increment, and current annual increment of diameter at breast height (DBH) with bark, tree height, and stem volume with bark are estimated. + (iii) Tree biomass and carbon storage estimation from volume and allometric models are calculated. + (iv) Height-diameter relationship is fitted with nonlinear models, if diameter at breast height (DBH) or tree height are available, which can be used to retrieve tree height and diameter at breast height (DBH). + . + date_publication: '2022-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StemAnalysis + url_git: https://github.com/forestscientist/StemAnalysis +stemmatology: + version: 0.3.2 + title: Stemmatological Analysis of Textual Traditions + maintainer: Jean-Baptiste Camps + description: Explore and analyse the genealogy of textual or musical traditions, + from their variants, with various stemmatological methods, mainly the disagreement-based + algorithms suggested by Camps and Cafiero (2015) . + date_publication: '2019-04-10' + bug_reports: https://github.com/Jean-Baptiste-Camps/stemmatology/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stemmatology + url_git: https://github.com/Jean-Baptiste-Camps/stemmatology +StempCens: + version: 1.1.0 + title: |- + Spatio-Temporal Estimation and Prediction for Censored/Missing + Responses + maintainer: Larissa A. Matos + description: It estimates the parameters of a censored or missing data in spatio-temporal + models using the SAEM algorithm (Delyon et al., 1999). This algorithm is a stochastic + approximation of the widely used EM algorithm and an important tool for models + in which the E-step does not have an analytic form. Besides the expressions obtained + to estimate the parameters to the proposed model, we include the calculations + for the observed information matrix using the method developed by Louis (1982). + To examine the performance of the fitted model, case-deletion measure are provided. + date_publication: '2020-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StempCens + url_git: '' +stencilaschema: + version: 1.0.0 + title: Bindings for Stencila Schema + maintainer: Nokome Bentley + description: Provides R bindings for the Stencila Schema . + This package is primarily aimed at R developers wanting to programmatically generate, + or modify, executable documents. + date_publication: '2021-02-22' + bug_reports: https://github.com/stencila/schema/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stencilaschema + url_git: https://github.com/stencila/schema#readme +stenographer: + version: 1.0.0 + title: Flexible and Customisable Logging System + maintainer: Dereck Mezquita + description: A comprehensive logging framework for R applications that provides + hierarchical logging levels, database integration, and contextual logging capabilities. + The package supports 'SQLite' storage for persistent logs, provides colour-coded + console output for better readability, includes parallel processing support, and + implements structured error reporting with 'JSON' formatting. + date_publication: '2025-01-16' + bug_reports: https://github.com/dereckmezquita/stenographer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stenographer + url_git: https://github.com/dereckmezquita/stenographer +stenR: + version: 0.6.9 + title: Standardization of Raw Discrete Questionnaire Scores + maintainer: Michal Kosinski + description: |- + An user-friendly framework to preprocess raw item + scores of questionnaires into factors or scores and standardize + them. Standardization can be made either by their normalization + in representative sample, or by import of premade scoring table. + date_publication: '2022-08-19' + bug_reports: '' + url: https://statismike.github.io/stenR/ + url_cran: https://CRAN.R-project.org/package=stenR + url_git: '' +StepBeta: + version: 2.1.0 + title: |- + Stepwise Procedure for Beta, Beta-Binomial and Negative Binomial + Regression Models + maintainer: Sergio Garofalo + description: |- + Starting from a Regression Model, it provides a stepwise + procedure to select the linear predictor. + date_publication: '2022-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StepBeta + url_git: '' +STEPCAM: + version: '1.2' + title: ABC-SMC Inference of STEPCAM + maintainer: Thijs Janzen + description: |- + Collection of model estimation, and model plotting functions + related to the STEPCAM family of community assembly models. + STEPCAM is a STEPwise Community Assembly Model that infers + the relative contribution of Dispersal Assembly, Habitat Filtering + and Limiting Similarity from a dataset consisting of the + combination of trait and abundance data. See also for more information. + date_publication: '2016-09-21' + bug_reports: https://github.com/thijsjanzen/STEPCAM + url: '' + url_cran: https://CRAN.R-project.org/package=STEPCAM + url_git: https://github.com/thijsjanzen/STEPCAM +stepcount: + version: 0.3.2 + title: Estimate Step Counts from 'Accelerometry' Data + maintainer: John Muschelli + description: |- + Interfaces the 'stepcount' Python + module to estimate + step counts and other activities from 'accelerometry' data. + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepcount + url_git: '' +stepdownfdp: + version: 1.0.0 + title: A Step-Down Procedure to Control the False Discovery Proportion + maintainer: Arya Ebadi + description: |- + Provides a step-down procedure for controlling the False + Discovery Proportion (FDP) in a competition-based setup, implementing + Dong et al. (2020) . Such setups include target-decoy + competition (TDC) in computational mass spectrometry and the knockoff + construction in linear regression. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepdownfdp + url_git: https://github.com/uni-Arya/stepdownfdp +stepgbm: + version: 1.0.1 + title: |- + Stepwise Variable Selection for Generalized Boosted Regression + Modeling + maintainer: Jin Li + description: 'An introduction to a couple of novel predictive variable selection + methods for generalised boosted regression modeling (gbm). They are based on various + variable influence methods (i.e., relative variable influence (RVI) and knowledge + informed RVI (i.e., KIRVI, and KIRVI2)) that adopted similar ideas as AVI, KIAVI + and KIAVI2 in the ''steprf'' package, and also based on predictive accuracy in + stepwise algorithms. For details of the variable selection methods, please see: + Li, J., Siwabessy, J., Huang, Z. and Nichol, S. (2019) . + Li, J., Alvarez, B., Siwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, + L., Howard, F., Nichol, S. (2017). .' + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepgbm + url_git: '' +StepGWR: + version: 0.1.0 + title: |- + A Hybrid Spatial Model for Prediction and Capturing Spatial + Variation in the Data + maintainer: Nobin Chandra Paul + description: |- + It is a hybrid spatial model that combines the variable selection capabilities of stepwise regression methods with the predictive power of the Geographically + Weighted Regression(GWR) model.The developed hybrid model follows a two-step approach where the stepwise variable selection method is applied first to identify + the subset of predictors that have the most significant impact on the response variable, and then a GWR model is fitted using those selected variables for spatial + prediction at test or unknown locations. For method details,see Leung, Y., Mei, C. L. and Zhang, W. X. (2000)..This hybrid spatial model aims to + improve the accuracy and interpretability of GWR predictions by selecting a subset of relevant variables through a stepwise selection process.This approach is particularly + useful for modeling spatially varying relationships and improving the accuracy of spatial predictions. + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StepGWR + url_git: '' +stepjglm: + version: 0.0.1 + title: Variable Selection for Joint Modeling of Mean and Dispersion + maintainer: Leandro A. Pereira + description: A Package for selecting variables for the joint modeling of mean and + dispersion (including models for mixture experiments) based on hypothesis testing + and the quality of model's fit. In each iteration of the selection process, a + criterion for checking the goodness of fit is used as a filter for choosing the + terms that will be evaluated by a hypothesis test. Pinto & Pereira (2021) . + date_publication: '2021-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepjglm + url_git: '' +stepmixr: + version: 0.1.2 + title: Interface to 'Python' Package 'StepMix' + maintainer: Charles-Édouard Giguère + description: |- + This is an interface for the 'Python' package + 'StepMix'. It is a 'Python' package following the scikit-learn API for + model-based clustering and generalized mixture modeling (latent class/profile + analysis) of continuous and categorical data. 'StepMix' handles missing values + through Full Information Maximum Likelihood (FIML) and provides multiple stepwise + Expectation-Maximization (EM) estimation methods based on pseudolikelihood + theory. Additional features include support for covariates and distal outcomes, + various simulation utilities, and non-parametric bootstrapping, which allows + inference in semi-supervised and unsupervised settings. + date_publication: '2024-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepmixr + url_git: https://github.com/Labo-Lacourse/StepMixr +stepp: + version: 3.2.7 + title: Subpopulation Treatment Effect Pattern Plot (STEPP) + maintainer: Wai-ki Yip + description: |- + A method to explore the treatment-covariate interactions in survival or generalized + linear model (GLM) for continuous, binomial and count data arising from two or more treatment + arms of a clinical trial. A permutation distribution approach to inference is implemented, + based on permuting the covariate values within each treatment group. + date_publication: '2024-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepp + url_git: '' +SteppedPower: + version: 0.3.5 + title: Power Calculation for Stepped Wedge Designs + maintainer: Philipp Mildenberger + description: |- + Tools for power and sample size + calculation as well as design diagnostics for + longitudinal mixed model settings, with a focus on stepped wedge designs. + All calculations are oracle estimates i.e. assume random effect variances + to be known (or guessed) in advance. + The method is introduced in Hussey and Hughes (2007) , + extensions are discussed in Li et al. (2020) . + date_publication: '2024-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SteppedPower + url_git: '' +steppedwedge: + version: 1.0.0 + title: Analyze Data from Stepped Wedge Cluster Randomized Trials + maintainer: Avi Kenny + description: |- + Provide various functions and tools to help fit models for + estimating treatment effects in stepped wedge cluster randomized trials. + Implements methods described in Kenny, Voldal, Xia, and Heagerty (2022) + "Analysis of stepped wedge cluster randomized trials in the presence of a + time-varying treatment effect", . + date_publication: '2025-02-21' + bug_reports: https://github.com/Avi-Kenny/steppedwedge/issues + url: https://avi-kenny.github.io/steppedwedge/ + url_cran: https://CRAN.R-project.org/package=steppedwedge + url_git: https://github.com/Avi-Kenny/steppedwedge +stepPenal: + version: '0.2' + title: Stepwise Forward Variable Selection in Penalized Regression + maintainer: Eleni Vradi + description: Model Selection Based on Combined Penalties. This package implements + a stepwise forward variable selection algorithm based on a penalized likelihood + criterion that combines the L0 with L2 or L1 norms. + date_publication: '2018-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepPenal + url_git: '' +stepPlr: + version: '0.93' + title: |- + L2 Penalized Logistic Regression with Stepwise Variable + Selection + maintainer: Mee Young Park + description: L2 penalized logistic regression for both continuous and discrete predictors, + with forward stagewise/forward stepwise variable selection procedure. + date_publication: '2018-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepPlr + url_git: '' +stepR: + version: 2.1-10 + title: Multiscale Change-Point Inference + maintainer: Pein Florian + description: Allows fitting of step-functions to univariate serial data where neither + the number of jumps nor their positions is known by implementing the multiscale + regression estimators SMUCE, simulataneous multiscale changepoint estimator, (K. + Frick, A. Munk and H. Sieling, 2014) and HSMUCE, heterogeneous + SMUCE, (F. Pein, H. Sieling and A. Munk, 2017) . In addition, + confidence intervals for the change-point locations and bands for the unknown + signal can be obtained. + date_publication: '2024-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepR + url_git: '' +StepReg: + version: 1.5.8 + title: Stepwise Regression Analysis + maintainer: Junhui Li + description: Stepwise regression is a statistical technique used for model selection. + This package streamlines stepwise regression analysis by supporting multiple regression + types, incorporating popular selection strategies, and offering essential metrics. + It enables users to apply multiple selection strategies and metrics in a single + function call, visualize variable selection processes, and export results in various + formats. However, StepReg should not be used for statistical inference unless + the variable selection process is explicitly accounted for, as it can compromise + the validity of the results. This limitation does not apply when StepReg is used + for prediction purposes. We validated StepReg's accuracy using public datasets + within the SAS software environment. Additionally, StepReg features an interactive + Shiny application to enhance usability and accessibility. + date_publication: '2025-02-07' + bug_reports: https://github.com/JunhuiLi1017/StepReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StepReg + url_git: '' +steprf: + version: 1.0.2 + title: Stepwise Predictive Variable Selection for Random Forest + maintainer: Jin Li + description: 'An introduction to several novel predictive variable selection methods + for random forest. They are based on various variable importance methods (i.e., + averaged variable importance (AVI), and knowledge informed AVI (i.e., KIAVI, and + KIAVI2)) and predictive accuracy in stepwise algorithms. For details of the variable + selection methods, please see: Li, J., Siwabessy, J., Huang, Z. and Nichol, S. + (2019) . Li, J., Alvarez, B., Siwabessy, J., Tran, + M., Huang, Z., Przeslawski, R., Radke, L., Howard, F., Nichol, S. (2017). .' + date_publication: '2022-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=steprf + url_git: '' +steps: + version: 1.3.0 + title: Spatially- and Temporally-Explicit Population Simulator + maintainer: Casey Visintin + description: Software to simulate population change across space and time. Visintin + et al. (2020) . + date_publication: '2022-10-04' + bug_reports: https://github.com/steps-dev/steps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=steps + url_git: https://github.com/steps-dev/steps +StepSignalMargiLike: + version: 2.6.0 + title: Step-Wise Signal Extraction via Marginal Likelihood + maintainer: Chu-Lan Michael Kao + description: |- + Provides function to estimate multiple change points + using marginal likelihood method. See the Manual file in data folder for + a detailed description of all functions, and a walk through tutorial. + For more information of the method, please see Du, Kao and Kou (2016) + . + date_publication: '2018-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StepSignalMargiLike + url_git: '' +stepSplitReg: + version: 1.0.4 + title: Stepwise Split Regularized Regression + maintainer: Anthony Christidis + description: |- + Functions to perform stepwise split regularized regression. The approach first + uses a stepwise algorithm to split the variables into the models with a goodness + of fit criterion, and then regularization is applied to each model. The weights + of the models in the ensemble are determined based on a criterion selected by + the user. + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stepSplitReg + url_git: '' +StepwiseTest: + version: '1.0' + title: |- + Multiple Testing Method to Control Generalized Family-Wise Error + Rate and False Discovery Proportion + maintainer: Kendro Vincent + description: Collection of stepwise procedures to conduct multiple hypotheses testing. + The details of the stepwise algorithm can be found in Romano and Wolf (2007) + and Hsu, Kuan, and Yen (2014) . + date_publication: '2016-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StepwiseTest + url_git: '' +StereoMorph: + version: 1.6.7 + title: Stereo Camera Calibration and Reconstruction + maintainer: Aaron Olsen + description: Functions for the collection of 3D points and curves using a stereo + camera setup. + date_publication: '2022-05-25' + bug_reports: '' + url: https://aaronolsen.github.io/software/stereomorph.html + url_cran: https://CRAN.R-project.org/package=StereoMorph + url_git: '' +stevedata: + version: 1.5.0 + title: |- + Steve's Toy Data for Teaching About a Variety of Methodological, + Social, and Political Topics + maintainer: Steve Miller + description: |- + This is a collection of various kinds of data with broad uses for teaching. + My students, and academics like me who teach the same topics I teach, should find + this useful if their teaching workflow is also built around the R programming + language. The applications are multiple but mostly cluster on topics of statistical + methodology, international relations, and political economy. + date_publication: '2025-01-24' + bug_reports: https://github.com/svmiller/stevedata/issues/ + url: http://svmiller.com/stevedata/ + url_cran: https://CRAN.R-project.org/package=stevedata + url_git: '' +stevedore: + version: 0.9.6 + title: Docker Client + maintainer: Rich FitzJohn + description: |- + Work with containers over the Docker API. Rather than + using system calls to interact with a docker client, using the + API directly means that we can receive richer information from + docker. The interface in the package is automatically generated + using the 'OpenAPI' (a.k.a., 'swagger') specification, and all + return values are checked in order to make them type stable. + date_publication: '2023-07-10' + bug_reports: https://github.com/richfitz/stevedore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stevedore + url_git: https://github.com/richfitz/stevedore +stevemisc: + version: 1.8.0 + title: Steve's Miscellaneous Functions + maintainer: Steve Miller + description: |- + These are miscellaneous functions that I find useful for my research and teaching. + The contents include themes for plots, functions for simulating + quantities of interest from regression models, functions for simulating various + forms of fake data for instructional/research purposes, and many more. All told, the functions + provided here are broadly useful for data organization, data presentation, data recoding, + and data simulation. + date_publication: '2024-08-23' + bug_reports: https://github.com/svmiller/stevemisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stevemisc + url_git: '' +stevetemplates: + version: 1.1.0 + title: Steve's R Markdown Templates + maintainer: Steven Miller + description: |- + These are my collection of 'R Markdown' templates, mostly for compilation to PDF. + These are useful for all things academic and professional, if you are using 'R Markdown' + for things like your CV or your articles and manuscripts. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stevetemplates + url_git: '' +stevethemes: + version: 0.1.0 + title: Steve's 'ggplot2' Themes and Related Theme Elements + maintainer: Steve Miller + description: |- + This is a compilation of my preferred themes and + related theme elements for 'ggplot2'. I believe these themes + and theme elements are aesthetically pleasing, both for pedagogical + instruction and for the presentation of applied statistical research to a wide + audience. These themes imply routine use of easily obtained/free fonts, simple + forms of which are included in this package. + date_publication: '2023-01-31' + bug_reports: https://github.com/svmiller/stevethemes/issues + url: http://svmiller.com/stevethemes/ + url_cran: https://CRAN.R-project.org/package=stevethemes + url_git: '' +stfit: + version: 0.99.9 + title: Spatio-Temporal Functional Imputation Tool + maintainer: Weicheng Zhu + description: A general spatiotemporal satellite image imputation method based on + sparse functional data analytic techniques. The imputation method applies and + extends the Functional Principal Analysis by Conditional Estimation (PACE). The + underlying idea for the proposed procedure is to impute a missing pixel by borrowing + information from temporally and spatially contiguous pixels based on the best + linear unbiased prediction. + date_publication: '2022-10-18' + bug_reports: https://github.com/mingsnu/stfit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stfit + url_git: '' +STFTS: + version: 0.1.0 + title: Statistical Tests for Functional Time Series + maintainer: Chi Seng Pun + description: 'A collection of statistical hypothesis tests of functional time series. + While it will include more tests when the related literature are enriched, this + package contains the following key tests: functional stationarity test, functional + trend stationarity test, functional unit root test, to name a few.' + date_publication: '2021-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STFTS + url_git: '' +stgam: + version: 0.0.1.2 + title: |- + Spatially and Temporally Varying Coefficient Models Using + Generalized Additive Models + maintainer: Lex Comber + description: 'A framework for specifying spatially, temporally and spatially-and-temporally + varying coefficient models using Generalized Additive Models with Gaussian Process + smooths. The smooths are parameterised with location and / or time attributes. + Importantly the framework supports the investigation of the presence and nature + of any space-time dependencies in the data, allows the user to evaluate different + model forms (specifications) and to pick the most probable model or to combine + multiple varying coefficient models using Bayesian Model Averaging. For more details + see: Brunsdon et al (2023) , Comber et al + (2023) and Comber et al (2024) .' + date_publication: '2024-07-31' + bug_reports: https://github.com/lexcomber/stgam/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stgam + url_git: https://github.com/lexcomber/stgam +sticky: + version: 0.5.6.1 + title: Persist Attributes Across Data Operations + maintainer: Christopher Brown + description: |- + In base R, object attributes are lost when objects are modified by + common data operations such as subset, filter, slice, append, extract + etc. This packages allows objects to be marked as 'sticky' and have + attributes persisted during these operations or when inserted + into or extracted from list-like or table-like objects. + date_publication: '2020-03-16' + bug_reports: https://github.com/decisionpatterns/sticky/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sticky + url_git: https://github.com/decisionpatterns/stickyhttp://decisionpatterns.com +stickyr: + version: 0.1.2 + title: Data Frames with Persistent Columns and Attributes + maintainer: Mizuki Uchida + description: |- + Provides data frames that hold certain columns and attributes + persistently for data processing in 'dplyr'. + date_publication: '2023-03-26' + bug_reports: https://github.com/UchidaMizuki/stickyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stickyr + url_git: https://github.com/UchidaMizuki/stickyr +STICr: + version: '1.1' + title: |- + Process Stream Temperature, Intermittency, and Conductivity + (STIC) Sensor Data + maintainer: Sam Zipper + description: A collection of functions for processing raw data from Stream Temperature, + Intermittency, and Conductivity (STIC) loggers. 'STICr' (pronounced "sticker") + includes functions for tidying, calibrating, classifying, and doing quality checks + on data from STIC sensors. Some package functionality is described in Wheeler/Zipper + et al. (2023) . + date_publication: '2024-12-02' + bug_reports: https://github.com/HEAL-KGS/STICr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=STICr + url_git: https://github.com/HEAL-KGS/STICr +SticsRFiles: + version: 1.5.0 + title: Read and Modify 'STICS' Input/Output Files + maintainer: Patrice Lecharpentier + description: |- + Manipulating input and output files of the 'STICS' crop + model. Files are either 'JavaSTICS' XML files or text files used by + the model 'fortran' executable. Most basic functionalities are reading + or writing parameter names and values in both XML or text input files, + and getting data from output files. Advanced functionalities include + XML files generation from XML templates and/or spreadsheets, or text + files generation from XML files by using 'xslt' transformation. + date_publication: '2024-11-13' + bug_reports: https://github.com/SticsRPacks/SticsRFiles/issues + url: https://doi.org/10.5281/zenodo.4443206 + url_cran: https://CRAN.R-project.org/package=SticsRFiles + url_git: https://github.com/SticsRPacks/SticsRFiles +stilt: + version: 1.3.0 + title: Separable Gaussian Process Interpolation (Emulation) + maintainer: Kelsey Ruckert + description: Functions for simplified emulation of time series computer model output + in model parameter space using Gaussian processes. Stilt can be used more generally + for Kriging of spatio-temporal fields. There are functions to predict at new parameter + settings, to test the emulator using cross-validation (which includes information + on 95% confidence interval empirical coverage), and to produce contour plots over + 2D slices in model parameter space. + date_publication: '2018-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stilt + url_git: '' +stim: + version: 1.0.0 + title: |- + Incorporating Stability Information into Cross-Sectional + Estimates + maintainer: Anna Wysocki + description: The goal of 'stim' is to provide a function for estimating the Stability + Informed Model. The Stability Informed Model integrates stability information + (how much a variable correlates with itself in the future) into cross-sectional + estimates. Wysocki and Rhemtulla (2022) . + date_publication: '2023-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stim + url_git: '' +stima: + version: 1.2.4 + title: Simultaneous Threshold Interaction Modeling Algorithm + maintainer: Elise Dusseldorp + description: Regression trunk model estimation proposed by Dusseldorp and Meulman + (2004) and Dusseldorp, Conversano, Van Os (2010) , + integrating a regression tree and a multiple regression model. + date_publication: '2023-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stima + url_git: '' +stinepack: + version: '1.5' + title: Stineman, a Consistently Well Behaved Method of Interpolation + maintainer: Tomas Johannesson + description: A consistently well behaved method of interpolation based on piecewise + rational functions using Stineman's algorithm. + date_publication: '2024-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stinepack + url_git: '' +stlARIMA: + version: 0.1.0 + title: STL Decomposition and ARIMA Hybrid Forecasting Model + maintainer: Ronit Jaiswal + description: Univariate time series forecasting with STL decomposition based auto + regressive integrated moving average (ARIMA) hybrid model. For method details + see Xiong T, Li C, Bao Y (2018). . + date_publication: '2021-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stlARIMA + url_git: '' +stlELM: + version: 0.1.1 + title: Hybrid Forecasting Model Based on STL Decomposition and ELM + maintainer: Girish Kumar Jha + description: Univariate time series forecasting with STL decomposition based Extreme + Learning Machine hybrid model. For method details see Xiong T, Li C, Bao Y (2018). + . + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stlELM + url_git: '' +stlnpp: + version: 0.4.0 + title: Spatio-Temporal Analysis of Point Patterns on Linear Networks + maintainer: Mehdi Moradi + description: Statistical analysis of spatio-temporal point processes on linear networks. + This packages provides tools to visualise and analyse spatio-temporal point patterns + on linear networks using first- and second-order summary statistics. + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stlnpp + url_git: '' +stlplus: + version: 0.5.1 + title: Enhanced Seasonal Decomposition of Time Series by Loess + maintainer: Ryan Hafen + description: |- + Decompose a time series into seasonal, trend, and remainder + components using an implementation of Seasonal Decomposition of Time + Series by Loess (STL) that provides several enhancements over the STL + method in the stats package. These enhancements include handling missing + values, providing higher order (quadratic) loess smoothing with automated + parameter choices, frequency component smoothing beyond the seasonal and + trend components, and some basic plot methods for diagnostics. + date_publication: '2016-01-06' + bug_reports: https://github.com/hafen/stlplus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stlplus + url_git: https://github.com/hafen/stlplus +stlTDNN: + version: 0.1.0 + title: STL Decomposition and TDNN Hybrid Time Series Forecasting + maintainer: Girish Kumar Jha + description: Implementation of hybrid STL decomposition based time delay neural + network model for univariate time series forecasting. For method details see Jha + G K, Sinha, K (2014). , Xiong T, Li C, Bao Y (2018). + . + date_publication: '2021-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stlTDNN + url_git: '' +stm: + version: 1.3.7 + title: Estimation of the Structural Topic Model + maintainer: Brandon Stewart + description: |- + The Structural Topic Model (STM) allows researchers + to estimate topic models with document-level covariates. + The package also includes tools for model selection, visualization, + and estimation of topic-covariate regressions. Methods developed in + Roberts et. al. (2014) and + Roberts et. al. (2016) . Vignette + is Roberts et. al. (2019) . + date_publication: '2023-12-01' + bug_reports: https://github.com/bstewart/stm/issues + url: http://www.structuraltopicmodel.com/ + url_cran: https://CRAN.R-project.org/package=stm + url_git: '' +stmCorrViz: + version: '1.3' + title: A Tool for Structural Topic Model Visualizations + maintainer: Antonio Coppola + description: |- + Generates an interactive visualization of topic correlations/ + hierarchy in a Structural Topic Model (STM) of Roberts, Stewart, and Tingley. + The package performs a hierarchical clustering of topics which are then exported + to a JSON object and visualized using D3. + date_publication: '2016-07-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stmCorrViz + url_git: '' +stmgp: + version: 1.0.4.1 + title: |- + Rapid and Accurate Genetic Prediction Modeling for Genome-Wide + Association or Whole-Genome Sequencing Study Data + maintainer: Masao Ueki + description: Rapidly build accurate genetic prediction models for genome-wide association + or whole-genome sequencing study data by smooth-threshold multivariate genetic + prediction (STMGP) method. Variable selection is performed using marginal association + test p-values with an optimal p-value cutoff selected by Cp-type criterion. Quantitative + and binary traits are modeled respectively via linear and logistic regression + models. A function that works through PLINK software (Purcell et al. 2007 , + Chang et al. 2015 ) + is provided. Covariates can be included in regression model. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stmgp + url_git: '' +stmgui: + version: 0.1.6 + title: Shiny Application for Creating STM Models + maintainer: Dan Zangri + description: Provides an application that acts as a GUI for the 'stm' text analysis + package. + date_publication: '2016-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stmgui + url_git: '' +stminsights: + version: 0.4.3 + title: A 'Shiny' Application for Inspecting Structural Topic Models + maintainer: Carsten Schwemmer + description: This app enables interactive validation, interpretation and visualization + of structural topic models from the 'stm' package by Roberts and others (2014) + . It also includes helper functions for model diagnostics + and extracting data from effect estimates. + date_publication: '2024-06-21' + bug_reports: https://github.com/cschwem2er/stminsights/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stminsights + url_git: https://github.com/cschwem2er/stminsights +StMoMo: + version: 0.4.1 + title: Stochastic Mortality Modelling + maintainer: Andres Villegas + description: |- + Implementation of the family of generalised age-period-cohort + stochastic mortality models. This family of models encompasses many models + proposed in the actuarial and demographic literature including the + Lee-Carter (1992) and + the Cairns-Blake-Dowd (2006) models. + It includes functions for fitting mortality models, analysing their + goodness-of-fit and performing mortality projections and simulations. + date_publication: '2018-04-13' + bug_reports: http://github.com/amvillegas/StMoMo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StMoMo + url_git: http://github.com/amvillegas/StMoMo +StMoSim: + version: 3.1.1 + title: Quantile-Quantile Plot with Several Gaussian Simulations + maintainer: Matthias Salvisberg + description: Plots a QQ-Norm Plot with several Gaussian simulations. + date_publication: '2018-11-19' + bug_reports: https://github.com/matthiassalvisberg/StMoSim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StMoSim + url_git: '' +STMotif: + version: 2.0.2 + title: Discovery of Motifs in Spatial-Time Series + maintainer: Heraldo Borges + description: Allow to identify motifs in spatial-time series. A motif is a previously + unknown subsequence of a (spatial) time series with relevant number of occurrences. + For this purpose, the Combined Series Approach (CSA) is used. + date_publication: '2024-02-23' + bug_reports: https://github.com/heraldoborges/STMotif/issues + url: '' + url_cran: https://CRAN.R-project.org/package=STMotif + url_git: https://github.com/heraldoborges/STMotif/wiki +STMr: + version: 0.1.6 + title: Strength Training Manual R-Language Functions + maintainer: Mladen Jovanović + description: |- + Strength training prescription using percent-based approach requires + numerous computations and assumptions. 'STMr' package allow users to estimate + individual reps-max relationships, implement various progression tables, and + create numerous set and rep schemes. The 'STMr' package is originally created as + a tool to help writing Jovanović M. (2020) Strength Training Manual + . + date_publication: '2023-11-02' + bug_reports: https://github.com/mladenjovanovic/STMr/issues + url: https://mladenjovanovic.github.io/STMr/ + url_cran: https://CRAN.R-project.org/package=STMr + url_git: '' +stocc: + version: '1.31' + title: Fit a Spatial Occupancy Model via Gibbs Sampling + maintainer: Devin S. Johnson + description: |- + Fit a spatial-temporal occupancy models using + a probit formulation instead of a traditional logit + model. + date_publication: '2021-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stocc + url_git: '' +StochBlock: + version: 0.1.2 + title: Stochastic Blockmodeling of One-Mode and Linked Networks + maintainer: Aleš Žiberna + description: Stochastic blockmodeling of one-mode and linked networks as implemented + in Škulj and Žiberna (2022) . The optimization + is done via CEM (Classification Expectation Maximization) algorithm that can be + initialized by random partitions or the results of k-means algorithm. The development + of this package is financially supported by the Slovenian Research Agency () + within the research programs P5-0168 and the research projects J7-8279 (Blockmodeling + multilevel and temporal networks) and J5-2557 (Comparison and evaluation of different + approaches to blockmodeling dynamic networks by simulations with application to + Slovenian co-authorship networks). + date_publication: '2023-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StochBlock + url_git: '' +stochLAB: + version: 1.1.2 + title: Stochastic Collision Risk Model + maintainer: Grant Humphries + description: |- + Collision Risk Models for avian fauna (seabird and migratory birds) at + offshore wind farms. The base deterministic model is derived from + Band (2012) . + This was further expanded on by Masden (2015) and code + used here is heavily derived from this work with input from Dr A. Cook at the + British Trust for Ornithology. These collision risk models are useful for + marine ornithologists who are working in the offshore wind industry, particularly + in UK waters. However, many of the species included in the stochastic collision + risk models can also be found in the North Atlantic in the + United States and Canada, and could be applied there. + date_publication: '2022-12-22' + bug_reports: https://github.com/HiDef-Aerial-Surveying/stochLAB/issues + url: https://hidef-aerial-surveying.github.io/stochLAB/ + url_cran: https://CRAN.R-project.org/package=stochLAB + url_git: https://github.com/HiDef-Aerial-Surveying/stochLAB +stochQN: + version: 0.1.2-1 + title: Stochastic Limited Memory Quasi-Newton Optimizers + maintainer: David Cortes + description: |- + Implementations of stochastic, limited-memory quasi-Newton optimizers, + similar in spirit to the LBFGS (Limited-memory Broyden-Fletcher-Goldfarb-Shanno) algorithm, + for smooth stochastic optimization. Implements the following methods: + oLBFGS (online LBFGS) (Schraudolph, N.N., Yu, J. and Guenter, S., 2007 ), + SQN (stochastic quasi-Newton) (Byrd, R.H., Hansen, S.L., Nocedal, J. and Singer, Y., 2016 ), + adaQN (adaptive quasi-Newton) (Keskar, N.S., Berahas, A.S., 2016, ). + Provides functions for easily creating R objects + with partial_fit/predict methods from some given objective/gradient/predict functions. + Includes an example stochastic logistic regression using these optimizers. + Provides header files and registered C routines for using it directly from C/C++. + date_publication: '2021-09-26' + bug_reports: https://github.com/david-cortes/stochQN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stochQN + url_git: https://github.com/david-cortes/stochQN +stochtree: + version: 0.1.1 + title: |- + Stochastic Tree Ensembles (XBART and BART) for Supervised + Learning and Causal Inference + maintainer: Drew Herren + description: |- + Flexible stochastic tree ensemble software. + Robust implementations of Bayesian Additive Regression Trees (BART) + Chipman, George, McCulloch (2010) + for supervised learning and Bayesian Causal Forests (BCF) + Hahn, Murray, Carvalho (2020) + for causal inference. Enables model serialization and parallel sampling + and provides a low-level interface for custom stochastic forest samplers. + date_publication: '2025-02-08' + bug_reports: https://github.com/StochasticTree/stochtree/issues + url: https://stochtree.ai/ + url_cran: https://CRAN.R-project.org/package=stochtree + url_git: https://github.com/StochasticTree/stochtree +stochvol: + version: 3.2.5 + title: |- + Efficient Bayesian Inference for Stochastic Volatility (SV) + Models + maintainer: Darjus Hosszejni + description: Efficient algorithms for fully Bayesian estimation of stochastic volatility + (SV) models with and without asymmetry (leverage) via Markov chain Monte Carlo + (MCMC) methods. Methodological details are given in Kastner and Frühwirth-Schnatter + (2014) and Hosszejni and Kastner (2019) ; + the most common use cases are described in Hosszejni and Kastner (2021) + and Kastner (2016) and the package examples. + date_publication: '2024-10-28' + bug_reports: https://github.com/gregorkastner/stochvol/issues + url: https://gregorkastner.github.io/stochvol/ + url_cran: https://CRAN.R-project.org/package=stochvol + url_git: '' +stochvolTMB: + version: 0.3.0 + title: Likelihood Estimation of Stochastic Volatility Models + maintainer: Jens Wahl + description: |- + Parameter estimation for stochastic volatility models using maximum likelihood. The latent log-volatility is + integrated out of the likelihood using the Laplace approximation. The models are fitted via 'TMB' (Template Model + Builder) (Kristensen, Nielsen, Berg, Skaug, and Bell (2016) ). + date_publication: '2025-01-31' + bug_reports: https://github.com/JensWahl/stochvolTMB/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stochvolTMB + url_git: https://github.com/JensWahl/stochvolTMB +stockAnalyst: + version: 1.0.1 + title: Equity Valuation using Methods of Fundamental Analysis + maintainer: MaheshP Kumar + description: |- + Methods of Fundamental Analysis for Valuation of Equity included here serve as a quick reference for undergraduate courses on Stock Valuation and Chartered Financial Analyst Levels 1 and 2 Readings on Equity Valuation. + Jerald E. Pinto (“Equity Asset Valuation (4th Edition)”, 2020, ISBN: 9781119628194). + Chartered Financial Analyst Institute ("Chartered Financial Analyst Program Curriculum 2020 Level I Volumes 1-6. (Vol. 4, pp. 445-491)", 2019, ISBN: 9781119593577). + Chartered Financial Analyst Institute ("Chartered Financial Analyst Program Curriculum 2020 Level II Volumes 1-6. (Vol. 4, pp. 197-447)", 2019, ISBN: 9781119593614). + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stockAnalyst + url_git: '' +StockDistFit: + version: 1.0.0 + title: Fit Stock Price Distributions + maintainer: Brian Njuguna + description: 'The ''StockDistFit'' package provides functions for fitting probability + distributions to stock price data. The package uses maximum likelihood estimation + to find the best-fitting distribution for a given stock. It also offers a function + to fit several distributions to one or more assets and compare the distribution + with the Akaike Information Criterion (AIC) and then pick the best distribution. + References are as follows: Siew et al. (2008) + and Benth et al. (2008) .' + date_publication: '2023-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StockDistFit + url_git: '' +stockR: + version: 1.0.76 + title: Identifying Stocks in Genetic Data + maintainer: Scott D. Foster + description: 'Provides a mixture model for clustering individuals (or sampling groups) + into stocks based on their genetic profile. Here, sampling groups are individuals + that are sure to come from the same stock (e.g. breeding adults or larvae). The + mixture (log-)likelihood is maximised using the EM-algorithm after finding good + starting values via a K-means clustering of the genetic data. Details can be found + in: Foster, S. D.; Feutry, P.; Grewe, P. M.; Berry, O.; Hui, F. K. C. & Davies + (2020) .' + date_publication: '2023-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stockR + url_git: '' +stocks: + version: 1.1.4 + title: Stock Market Analysis + maintainer: Dane R. Van Domelen + description: Functions for analyzing stocks or other investments. Main features + are loading and aligning historical data for ticker symbols, calculating performance + metrics for individual funds or portfolios (e.g. annualized growth, maximum drawdown, + Sharpe/Sortino ratio), and creating graphs. C++ code is used to improve processing + speed where possible. + date_publication: '2018-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stocks + url_git: '' +stodom: + version: 0.0.1 + title: Estimating Consistent Tests for Stochastic Dominance + maintainer: Sergei Schaub + description: Stochastic dominance tests help ranking different distributions. The + package implements the consistent test for stochastic dominance by Barrett and + Donald (2003) . Specifically, it implements Barrett + and Donald's Kolmogorov-Smirnov type tests for first- and second-order stochastic + dominance based on bootstrapping 2 and 1. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stodom + url_git: '' +stoichcalc: + version: 1.1-5 + title: R Functions for Solving Stoichiometric Equations + maintainer: Peter Reichert + description: |- + Given a list of substance compositions, a list of substances + involved in a process, and a list of constraints in addition to mass + conservation of elementary constituents, the package contains functions + to build the substance composition matrix, to analyze the uniqueness of + process stoichiometry, and to calculate stoichiometric coefficients if + process stoichiometry is unique. + (See Reichert, P. and Schuwirth, N., A generic framework for deriving + process stoichiometry in enviromental models, Environmental Modelling + and Software 25, 1241-1251, 2010 for more details.) + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stoichcalc + url_git: '' +stokes: + version: 1.2-3 + title: The Exterior Calculus + maintainer: Robin K. S. Hankin + description: |- + Provides functionality for working with tensors, alternating + forms, wedge products, Stokes's theorem, and related concepts + from the exterior calculus. Uses 'disordR' discipline + (Hankin, 2022, ). The + canonical reference would be M. Spivak + (1965, ISBN:0-8053-9021-9) "Calculus on Manifolds". To cite + the package in publications please use Hankin (2022) + . + date_publication: '2025-01-22' + bug_reports: https://github.com/RobinHankin/stokes/issues + url: https://robinhankin.github.io/stokes/ + url_cran: https://CRAN.R-project.org/package=stokes + url_git: https://github.com/RobinHankin/stokes +STOPES: + version: '0.2' + title: Selection Threshold Optimized Empirically via Splitting + maintainer: Marinela Capanu + description: Implements variable selection procedures for low to moderate size generalized + linear regressions models. It includes the STOPES functions for linear regression + (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated + data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling + based optimization methods for generalized linear regression models (Marinela + Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable + selection for generalized linear models). + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STOPES + url_git: '' +stopp: + version: 0.2.4 + title: |- + Spatio-Temporal Point Pattern Methods, Model Fitting, + Diagnostics, Simulation, Local Tests + maintainer: Nicoletta D'Angelo + description: Toolbox for different kinds of spatio-temporal analyses to be performed + on observed point patterns, following the growing stream of literature on point + process theory. This R package implements functions to perform different kinds + of analyses on point processes, proposed in the papers (Siino, Adelfio, and Mateu + 2018; Siino et al. 2018; + Adelfio et al. 2020; D’Angelo, Adelfio, and Mateu + 2021; D’Angelo, Adelfio, and Mateu 2022; + D’Angelo, Adelfio, and Mateu 2023). The main topics + include modeling, statistical inference, and simulation issues on spatio-temporal + point processes on Euclidean space and linear networks. + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stopp + url_git: '' +stoppingrule: + version: 0.5.2 + title: Create and Evaluate Stopping Rules for Safety Monitoring + maintainer: Michael J. Martens + description: Provides functions for creating, displaying, and evaluating stopping + rules for safety monitoring in clinical studies. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stoppingrule + url_git: '' +stops: + version: 1.8-2 + title: Structure Optimized Proximity Scaling + maintainer: Thomas Rusch + description: Methods that use flexible variants of multidimensional scaling (MDS) + which incorporate parametric nonlinear distance transformations and trade-off + the goodness-of-fit fit with structure considerations to find optimal hyperparameters, + also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, + 2023,). The package contains various functions, + wrappers, methods and classes for fitting, plotting and displaying different 1-way + MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. + These cover essentially the functionality of the package smacofx, including Torgerson + (classical) scaling with power transformations of dissimilarities, SMACOF MDS + with powers of dissimilarities, Sammon mapping with powers of dissimilarities, + elastic scaling with powers of dissimilarities, spherical SMACOF with powers of + dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress + MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling + powers of dissimilarities and configuration distances, Sammon mapping powers of + dissimilarities and configuration distances, power stress MDS (POST-MDS), approximate + power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), + curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling + and (power) multidimensional distance analysis (experimental models from smacofx + influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters + based on goodness-of-fit fit only (i.e., no structure considerations). The package + further contains functions for optimization, specifically the adaptive Luus-Jaakola + algorithm and a wrapper for Bayesian optimization with treed Gaussian process + with jumps to linear models, and functions for various c-structuredness indices. + date_publication: '2024-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stops + url_git: https://r-forge.r-project.org/projects/stops/ +stopwords: + version: '2.3' + title: Multilingual Stopword Lists + maintainer: Kenneth Benoit + description: Provides multiple sources of stopwords, for use in text analysis and + natural language processing. + date_publication: '2021-10-28' + bug_reports: https://github.com/quanteda/stopwords/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stopwords + url_git: https://github.com/quanteda/stopwords +Storm: + version: '1.2' + title: Write Storm Bolts in R using the Storm Multi-Language Protocol. + maintainer: Allen Day + description: |- + Storm is a distributed real-time computation system. Similar to how + Hadoop provides a set of general primitives for doing batch processing, Storm + provides a set of general primitives for doing real-time computation. + + Storm includes a "Multi-Language" (or "Multilang") Protocol to allow + implementation of Bolts and Spouts in languages other than Java. This R + extension provides implementations of utility functions to allow an application + developer to focus on application-specific functionality rather than Storm/R + communications plumbing. + date_publication: '2015-01-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Storm + url_git: '' +StormR: + version: 0.2.1 + title: |- + Analyzing the Behaviour of Wind Generated by Tropical Storms and + Cyclones + maintainer: Thomas Arsouze + description: |- + Set of functions to quantify and map the + behaviour of winds generated by tropical storms and cyclones in space + and time. It includes functions to compute and analyze fields such as the maximum sustained wind field, power dissipation index and duration of exposure to winds above a given threshold. It also includes functions to map the trajectories as well as characteristics of the storms. + date_publication: '2024-07-24' + bug_reports: https://github.com/umr-amap/StormR/issues/new/choose + url: https://umr-amap.github.io/StormR/ + url_cran: https://CRAN.R-project.org/package=StormR + url_git: '' +storr: + version: 1.2.5 + title: Simple Key Value Stores + maintainer: Rich FitzJohn + description: |- + Creates and manages simple key-value stores. These can + use a variety of approaches for storing the data. This package + implements the base methods and support for file system, in-memory + and DBI-based database stores. + date_publication: '2020-12-01' + bug_reports: https://github.com/richfitz/storr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=storr + url_git: https://github.com/richfitz/storr +stortingscrape: + version: 0.3.0 + title: Access Data from the Norwegian Parliament API + maintainer: Martin Søyland + description: |- + Functions for retrieving general and specific data from the Norwegian Parliament, + through the Norwegian Parliament API at . + date_publication: '2024-01-18' + bug_reports: https://github.com/martigso/stortingscrape/issues + url: https://martigso.github.io/stortingscrape/ + url_cran: https://CRAN.R-project.org/package=stortingscrape + url_git: https://github.com/martigso/stortingscrape +stoRy: + version: 0.2.2 + title: Download, Explore, and Analyze Literary Theme Ontology Data + maintainer: Paul Sheridan + description: |- + Download, explore, and analyze Literary Theme Ontology themes + and thematically annotated story data. To learn more about the project + visit and + . + date_publication: '2023-06-13' + bug_reports: https://github.com/theme-ontology/stoRy/issues + url: https://www.themeontology.org/ + url_cran: https://CRAN.R-project.org/package=stoRy + url_git: https://github.com/theme-ontology/stoRy +storywranglr: + version: 0.2.0 + title: Explore Twitter Trends with the 'Storywrangler' API + maintainer: Christopher Belanger + description: |- + An interface to explore trends in Twitter data using the + 'Storywrangler' Application Programming Interface (API), which can be found + here: . + date_publication: '2021-08-13' + bug_reports: https://github.com/chris31415926535/storywranglr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=storywranglr + url_git: https://github.com/chris31415926535/storywranglr +stosim: + version: 0.0.15 + title: |- + Stochastic Simulator for Reliability Modeling of Repairable + Systems + maintainer: Jacob Ormerod + description: A toolkit for Reliability Availability and Maintainability (RAM) modeling + of industrial process systems. + date_publication: '2023-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stosim + url_git: '' +STPGA: + version: 5.2.1 + title: Selection of Training Populations by Genetic Algorithm + maintainer: Deniz Akdemir + description: Combining Predictive Analytics and Experimental Design to Optimize + Results. To be utilized to select a test data calibrated training population in + high dimensional prediction problems and assumes that the explanatory variables + are observed for all of the individuals. Once a "good" training set is identified, + the response variable can be obtained only for this set to build a model for predicting + the response in the test set. The algorithms in the package can be tweaked to + solve some other subset selection problems. + date_publication: '2018-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STPGA + url_git: '' +stplanr: + version: 1.2.2 + title: Sustainable Transport Planning + maintainer: Robin Lovelace + description: |- + Tools for transport planning with an emphasis on spatial + transport data and non-motorized modes. + The package was originally developed to support the 'Propensity to Cycle Tool', a publicly available strategic cycle network planning tool + (Lovelace et al. 2017) , but has since been + extended to support public transport routing and accessibility analysis + (Moreno-Monroy et al. 2017) and + routing with locally hosted routing engines such as 'OSRM' + (Lowans et al. 2023) . + The main functions are for creating and manipulating geographic "desire + lines" from origin-destination (OD) data (building on the 'od' + package); calculating routes on the transport network locally and via + interfaces to routing services such as + (Desjardins et al. 2021) ; + and calculating route segment attributes such as bearing. The package + implements the 'travel flow aggregration' method described in Morgan + and Lovelace (2020) and the + 'OD jittering' method described in Lovelace et al. (2022) + . + Further information on the package's aim and scope can be found in the + vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) + , and in a paper outlining the landscape of + open source software for geographic methods in transport planning + (Lovelace, 2021) . + date_publication: '2024-08-22' + bug_reports: https://github.com/ropensci/stplanr/issues + url: https://docs.ropensci.org/stplanr/ + url_cran: https://CRAN.R-project.org/package=stplanr + url_git: https://github.com/ropensci/stplanr +stpm: + version: 1.7.12 + title: |- + Stochastic Process Model for Analysis of Longitudinal and + Time-to-Event Outcomes + maintainer: Ilya Y. Zhbannikov + description: |- + Utilities to estimate parameters of the models with survival functions + induced by stochastic covariates. Miscellaneous functions for data preparation + and simulation are also provided. For more information, see: + (i)"Stochastic model for analysis of longitudinal data on aging and mortality" + by Yashin A. et al. (2007), + Mathematical Biosciences, 208(2), 538-551, ; + (ii) "Health decline, aging and mortality: how are they related?" + by Yashin A. et al. (2007), + Biogerontology 8(3), 291(302), . + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stpm + url_git: '' +stpp: + version: 2.0-8 + title: Space-Time Point Pattern Simulation, Visualisation and Analysis + maintainer: Edith Gabriel + description: Many of the models encountered in applications of point process methods + to the study of spatio-temporal phenomena are covered in 'stpp'. This package + provides statistical tools for analyzing the global and local second-order properties + of spatio-temporal point processes, including estimators of the space-time inhomogeneous + K-function and pair correlation function. It also includes tools to get static + and dynamic display of spatio-temporal point patterns. See Gabriel et al (2013) + . + date_publication: '2024-06-28' + bug_reports: https://github.com/stpp-GitHub-community + url: '' + url_cran: https://CRAN.R-project.org/package=stpp + url_git: '' +stpphawkes: + version: 0.2.1 + title: Missing Data for Marked Hawkes Process + maintainer: J. Derek Tucker + description: |- + Estimation of model parameters for marked Hawkes process. + Accounts for missing data in the estimation of the parameters. + Technical details found in (Tucker et al., 2019 ). + date_publication: '2023-08-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stpphawkes + url_git: '' +stppSim: + version: 1.3.4 + title: Spatiotemporal Point Patterns Simulation + maintainer: Monsuru Adepeju + description: |- + Generates artificial point patterns marked by their + spatial and temporal signatures. The resulting point cloud + may exhibit inherent interactions between both signatures. + The simulation integrates microsimulation + (Holm, E., (2017)) + and agent-based models (Bonabeau, E., (2002)), + beginning with the configuration of movement characteristics for + the specified agents (referred to as 'walkers') and their interactions + within the simulation environment. These interactions + (Quaglietta, L. and Porto, M., (2019)) + result in specific spatiotemporal patterns that can be visualized, + analyzed, and used for various analytical purposes. + Given the growing scarcity of detailed spatiotemporal data + across many domains, this package provides an alternative data source + for applications in social and life sciences. + date_publication: '2024-07-24' + bug_reports: https://github.com/Manalytics/stppSim/issues/new/choose + url: '' + url_cran: https://CRAN.R-project.org/package=stppSim + url_git: https://github.com/MAnalytics/stppSim +stR: + version: '0.7' + title: Seasonal Trend Decomposition Using Regression + maintainer: Rob Hyndman + description: |- + Methods for decomposing seasonal data: STR (a Seasonal-Trend + time series decomposition procedure based on Regression) and Robust STR. In + some ways, STR is similar to Ridge Regression and Robust STR can be related to + LASSO. They allow for multiple seasonal components, multiple linear covariates + with constant, flexible and seasonal influence. Seasonal patterns (for both + seasonal components and seasonal covariates) can be fractional and flexible + over time; moreover they can be either strictly periodic or have a more + complex topology. The methods provide confidence intervals for the estimated + components. The methods can also be used for forecasting. + date_publication: '2024-07-28' + bug_reports: https://github.com/robjhyndman/stR/issues + url: https://pkg.robjhyndman.com/stR/ + url_cran: https://CRAN.R-project.org/package=stR + url_git: https://github.com/robjhyndman/stR +str2str: + version: 1.0.0 + title: Convert R Objects from One Structure to Another + maintainer: David Disabato + description: |- + Offers a suite of functions for converting to and from + (atomic) vectors, matrices, data.frames, and (3D+) arrays as well + as lists of these objects. It is an alternative to the base R + as..() functions (e.g., as.data.frame.array()) that + provides more useful and/or flexible restructuring of R objects. + To do so, it only works with common structuring of R objects (e.g., + data.frames with only atomic vector columns). + date_publication: '2023-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=str2str + url_git: '' +StrainRanking: + version: '1.2' + title: Ranking of Pathogen Strains + maintainer: Samuel Soubeyrand + description: Regression-based ranking of pathogen strains with respect to their + contributions to natural epidemics, using demographic and genetic data sampled + in the curse of the epidemics. This package also includes the GMCPIC test. + date_publication: '2017-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StrainRanking + url_git: '' +strand: + version: 0.2.0 + title: A Framework for Investment Strategy Simulation + maintainer: Jeff Enos + description: |- + Provides a framework for performing discrete (share-level) simulations of + investment strategies. Simulated portfolios optimize exposure to an input signal subject + to constraints such as position size and factor exposure. For background see L. Chincarini + and D. Kim (2010, ISBN:978-0-07-145939-6) "Quantitative Equity Portfolio Management". + date_publication: '2020-11-19' + bug_reports: https://github.com/strand-tech/strand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=strand + url_git: https://github.com/strand-tech/strand +stranslate: + version: 0.1.3 + title: Simple Translation Between Different Languages + maintainer: Sigbert Klinke + description: |- + Message translation is often managed with 'po' files and the 'gettext' programme, + but sometimes another solution is needed. In contrast to 'po' files, a more flexible approach + is used as in the Fluent project with R Markdown snippets. + The key-value approach allows easier handling of the translated messages. + date_publication: '2024-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stranslate + url_git: https://github.com/sigbertklinke/stranslate(developmentversion) +strap: + version: 1.6-1 + title: Stratigraphic Tree Analysis for Palaeontology + maintainer: Graeme T. Lloyd + description: Functions for the stratigraphic analysis of phylogenetic trees. + date_publication: '2024-05-06' + bug_reports: https://github.com/graemetlloyd/strap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=strap + url_git: https://github.com/graemetlloyd/strap +strat: + version: '0.1' + title: An Implementation of the Stratification Index + maintainer: Xiang Zhou + description: |- + An implementation of the stratification index proposed by Zhou (2012) . + The package provides two functions, srank, which returns stratum-specific + information, including population share and average percentile rank; and strat, + which returns the stratification index and its approximate standard error. + When a grouping factor is specified, strat also provides a detailed decomposition + of the overall stratification into between-group and within-group components. + date_publication: '2016-11-23' + bug_reports: https://github.com/xiangzhou09/strat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=strat + url_git: https://github.com/xiangzhou09/strat +strata: + version: 1.4.0 + title: Simple Framework for Simple Automation + maintainer: Alexander Senetcky + description: |- + Build a project framework for users with + access to only the most basic of automation tools. + date_publication: '2025-02-03' + bug_reports: https://github.com/asenetcky/strata/issues + url: https://asenetcky.github.io/strata/ + url_cran: https://CRAN.R-project.org/package=strata + url_git: https://github.com/asenetcky/strata +strata.MaxCombo: + version: 0.0.1 + title: Stratified Max-Combo Test + maintainer: Yuwen Liu + description: Non-proportional hazard (NPH) is commonly observed in immuno-oncology + studies, where the survival curves of the treatment and control groups show delayed + separation. To properly account for NPH, several statistical methods have been + developed. One such method is Max-Combo test, which is a straightforward and flexible + hypothesis testing method that can simultaneously test for constant, early, middle, + and late treatment effects. However, the majority of the Max-Combo test performed + in clinical studies are unstratified, ignoring the important prognostic stratification + factors. To fill this gap, we have developed an R package for stratified Max-Combo + testing that accounts for stratified baseline factors. Our package explores various + methods for calculating combined test statistics, estimating joint distributions, + and determining the p-values. + date_publication: '2023-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=strata.MaxCombo + url_git: '' +stratallo: + version: 2.2.1 + title: Optimum Sample Allocation in Stratified Sampling + maintainer: Wojciech Wójciak + description: |- + Functions in this package provide solution to classical problem in + survey methodology - an optimum sample allocation in stratified sampling. In + this context, the optimum allocation is in the classical Tschuprow-Neyman's + sense and it satisfies additional lower or upper bounds restrictions imposed + on sample sizes in strata. There are few different algorithms available to + use, and one them is based on popular sample allocation method that applies + Neyman allocation to recursively reduced set of strata. + This package also provides the function that computes a solution to the + minimum cost allocation problem, which is a minor modification of the + classical optimum sample allocation. This problem lies in the determination + of a vector of strata sample sizes that minimizes total cost of the survey, + under assumed fixed level of the stratified estimator's variance. As in the + case of the classical optimum allocation, the problem of minimum cost + allocation can be complemented by imposing upper-bounds constraints on sample + sizes in strata. + date_publication: '2023-11-26' + bug_reports: https://github.com/wwojciech/stratallo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stratallo + url_git: https://github.com/wwojciech/stratallo +stratamatch: + version: 0.1.9 + title: Stratification and Matching for Large Observational Data Sets + maintainer: Rachael C. Aikens + description: |- + A pilot matching design to automatically + stratify and match large datasets. The manual_stratify() function allows + users to manually stratify a dataset based on categorical variables of + interest, while the auto_stratify() function does automatically by + allocating a held-aside (pilot) data set, fitting a prognostic score + (see Hansen (2008) ) on the pilot set, and stratifying the data set based + on prognostic score quantiles. The strata_match() function then does optimal + matching of the data set in parallel within strata. + date_publication: '2022-03-31' + bug_reports: https://github.com/raikens1/stratamatch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stratamatch + url_git: https://github.com/raikens1/stratamatch +stratastats: + version: '0.2' + title: Stratified Analysis of 2x2 Contingency Tables + maintainer: Gianmarco Alberti + description: Offers a comprehensive approach for analysing stratified 2x2 contingency + tables. It facilitates the calculation of odds ratios, 95% confidence intervals, + and conducts chi-squared, Cochran-Mantel-Haenszel, Mantel-Haenszel, and Breslow-Day-Tarone + tests. The package is particularly useful in fields like epidemiology and social + sciences where stratified analysis is essential. The package also provides interpretative + insights into the results, aiding in the understanding of statistical outcomes. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stratastats + url_git: '' +stratbr: + version: '1.2' + title: Optimal Stratification in Stratified Sampling + maintainer: Jose Brito + description: |- + An Optimization Algorithm Applied to + Stratification Problem.This function aims + at constructing optimal strata with an optimization algorithm + based on a global optimisation technique called Biased + Random Key Genetic Algorithms. + date_publication: '2017-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stratbr + url_git: '' +strategicplayers: + version: '1.1' + title: Strategic Players + maintainer: Miles Ott + description: |- + Identifies individuals in a social network who should be the intervention + subjects for a network intervention in which you have a group of targets, a + group of avoiders, and a group that is neither. + date_publication: '2024-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=strategicplayers + url_git: '' +Strategy: + version: 1.0.1 + title: Generic Framework to Analyze Trading Strategies + maintainer: Julian Busch + description: |- + Users can build and test customized quantitative trading strategies. Some quantitative trading strategies are already implemented, e.g. various moving-average filters with trend following approaches. + The implemented class called "Strategy" allows users to access several methods to analyze performance figures, plots and backtest the strategies. + Furthermore, custom strategies can be added, a generic template is available. The custom strategies require a certain input and output so they can be called from the Strategy-constructor. + date_publication: '2017-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Strategy + url_git: '' +stratEst: + version: 1.1.6 + title: Strategy Estimation + maintainer: Fabian Dvorak + description: Variants of strategy estimation (Dal Bo & Frechette, 2011, ), + including the model with parameters for the choice probabilities of the strategies + (Breitmoser, 2015, ), and the model with individual + level covariates for the selection of strategies by individuals (Dvorak & Fehrler, + 2018, ). + date_publication: '2022-11-29' + bug_reports: https://github.com/fdvorak/stratEst/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stratEst + url_git: https://github.com/fdvorak/stratEst +StrathE2E2: + version: 3.3.0 + title: End-to-End Marine Food Web Model + maintainer: Michael Heath + description: |- + A dynamic model of + the big-picture, whole ecosystem effects of hydrodynamics, + temperature, nutrients, and fishing on continental shelf marine + food webs. The package is described in: Heath, M.R., + Speirs, D.C., Thurlbeck, I. and Wilson, R.J. (2020) + StrathE2E2: An R package + for modelling the dynamics of marine food webs and + fisheries. 8pp. + date_publication: '2021-01-22' + bug_reports: '' + url: https://marineresourcemodelling.gitlab.io/ + url_cran: https://CRAN.R-project.org/package=StrathE2E2 + url_git: https://gitlab.com/MarineResourceModelling/StrathE2E/StrathE2E2 +stratification: + version: 2.2-7 + title: Univariate Stratification of Survey Populations + maintainer: Louis-Paul Rivest + description: |- + Univariate stratification of survey populations with a generalization of the + Lavallee-Hidiroglou method of stratum construction. The generalized method takes into account + a discrepancy between the stratification variable and the survey variable. The determination + of the optimal boundaries also incorporate, if desired, an anticipated non-response, a take-all + stratum for large units, a take-none stratum for small units, and a certainty stratum to ensure + that some specific units are in the sample. The well known cumulative root frequency rule of + Dalenius and Hodges and the geometric rule of Gunning and Horgan are also implemented. + date_publication: '2022-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stratification + url_git: '' +StratifiedBalancing: + version: 0.3.0 + title: Stratified Covariate Balancing + maintainer: Amr ElRafey + description: Performs Stratified Covariate Balancing with Markov blanket feature + selection and use of synthetic cases. See Alemi et al. (2016) . + date_publication: '2019-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StratifiedBalancing + url_git: '' +StratifiedMedicine: + version: 1.0.5 + title: Stratified Medicine + maintainer: Thomas Jemielita + description: |- + A toolkit for stratified medicine, subgroup identification, and precision medicine. + Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate + models (counterfactual patient-level quantities, such as the conditional average treatment effect), + (3) subgroup identification models (find subsets of patients with similar treatment effects), + and (4) treatment effect estimation and inference (for the overall population and discovered + subgroups). These tools can be customized and are directly used in PRISM + (patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019 + . This package is in beta and will be continually updated. + date_publication: '2022-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StratifiedMedicine + url_git: https://github.com/thomasjemielita/StratifiedMedicine +StratifiedRF: + version: 0.2.2 + title: Builds Trees by Sampling Variables in Groups + maintainer: David Cortes + description: |- + Random Forest-like tree ensemble that works with groups of predictor variables. When building a tree, a number of variables is taken randomly from each group separately, thus ensuring that it considers variables from each group for the splits. Useful when rows contain information about different things (e.g. user information and product information) and it's not sensible to make a prediction with information from only one group of variables, or when there are far more variables from one group than the other and it's desired to have groups appear evenly on trees. + Trees are grown using the C5.0 algorithm rather than the usual CART algorithm. Supports parallelization (multithreaded), missing values in predictors, and categorical variables (without doing One-Hot encoding in the processing). Can also be used to create a regular (non-stratified) Random Forest-like model, but made up of C5.0 trees and with some additional control options. + As it's built with C5.0 trees, it works only for classification (not for regression). + date_publication: '2017-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StratifiedRF + url_git: '' +StratifiedSampling: + version: 0.4.2 + title: Different Methods for Stratified Sampling + maintainer: Raphael Jauslin + description: Integrating a stratified structure in the population in a sampling + design can considerably reduce the variance of the Horvitz-Thompson estimator. + We propose in this package different methods to handle the selection of a balanced + sample in stratified population. For more details see Raphaël Jauslin, Esther + Eustache and Yves Tillé (2021) . The package propose + also a method based on optimal transport and balanced sampling, see Raphaël Jauslin + and Yves Tillé . + date_publication: '2025-01-31' + bug_reports: https://github.com/RJauslin/StratifiedSampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StratifiedSampling + url_git: https://github.com/RJauslin/StratifiedSampling +stratifiedyh: + version: 0.1.0 + title: Stratified Sampling and Labeling of Data in R + maintainer: Duan Yuanheng + description: Provides functions for stratified sampling and assigning custom labels + to data, ensuring randomness within groups. The package supports various sampling + methods such as stratified, cluster, and systematic sampling. It allows users + to apply transformations and customize the sampling process. This package can + be useful for statistical analysis and data preparation tasks. + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stratifiedyh + url_git: '' +stratifyR: + version: 1.0-4 + title: Optimal Stratification of Univariate Populations + maintainer: Karuna G. Reddy + description: The stratification of univariate populations under stratified sampling + designs is implemented according to Khan et al. (2002) + and Khan et al. (2015) in this library. It + determines the Optimum Strata Boundaries (OSB) and Optimum Sample Sizes (OSS) + for the study variable, y, using the best-fit frequency distribution of a survey + variable (if data is available) or a hypothetical distribution (if data is not + available). The method formulates the problem of determining the OSB as mathematical + programming problem which is solved by using a dynamic programming technique. + If a dataset of the population is available to the surveyor, the method estimates + its best-fit distribution and determines the OSB and OSS under Neyman allocation + directly. When the dataset is not available, stratification is made based on the + assumption that the values of the study variable, y, are available as hypothetical + realizations of proxy values of y from recent surveys. Thus, it requires certain + distributional assumptions about the study variable. At present, it handles stratification + for the populations where the study variable follows a continuous distribution, + namely, Pareto, Triangular, Right-triangular, Weibull, Gamma, Exponential, Uniform, + Normal, Log-normal and Cauchy distributions. + date_publication: '2025-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stratifyR + url_git: '' +StratigrapheR: + version: 1.3.1 + title: Integrated Stratigraphy + maintainer: Sebastien Wouters + description: |- + Includes bases for litholog generation: graphical functions + based on R base graphics, interval management functions and svg importation + functions among others. Also include stereographic projection functions, + and other functions made to deal with large datasets while keeping options + to get into the details of the data. + When using for publication please cite + Sebastien Wouters, Anne-Christine Da Silva, Frederic Boulvain and + Xavier Devleeschouwer, 2021. The R Journal 13:2, 153-178. + The palaeomagnetism functions are based on: + Tauxe, L., 2010. Essentials of Paleomagnetism. University of California + Press. ; + Allmendinger, R. W., Cardozo, N. C., and Fisher, D., 2013, Structural + Geology Algorithms: Vectors & Tensors: Cambridge, England, Cambridge + University Press, 289 pp.; + Cardozo, N., and Allmendinger, R. W., 2013, Spherical projections + with OSXStereonet: Computers & Geosciences, v. 51, no. 0, p. 193 - 205, + . + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StratigrapheR + url_git: '' +StratPal: + version: 0.3.1 + title: Stratigraphic Paleobiology Modeling Pipelines + maintainer: Niklas Hohmann + description: |- + The fossil record is a joint expression of ecological, taphonomic, + evolutionary, and stratigraphic processes (Holland and Patzkowsky, 2012, ISBN:978-0226649382). + This package allowing to simulate biological processes in the time domain + (e.g., trait evolution, fossil abundance), and examine how their expression + in the rock record (stratigraphic domain) is influenced based on + age-depth models, ecological niche models, and taphonomic effects. + Functions simulating common processes used in modeling trait evolution or + event type data such as first/last occurrences are provided and can be used + standalone or as part of a pipeline. The package comes with example + data sets and tutorials in several vignettes, which can be used as a + template to set up one's own simulation. + date_publication: '2025-02-20' + bug_reports: https://github.com/MindTheGap-ERC/StratPal/issues + url: https://mindthegap-erc.github.io/StratPal/ + url_cran: https://CRAN.R-project.org/package=StratPal + url_git: https://github.com/MindTheGap-ERC/StratPal +StratSel: + version: '1.3' + title: Strategic Selection Estimator + maintainer: Lucas Leemann + description: Provides functions to estimate a strategic selection estimator. A strategic + selection estimator is an agent error model in which the two random components + are not assumed to be orthogonal. In addition this package provides generic functions + to print and plot objects of its class as well as the necessary functions to create + tables for LaTeX. There is also a function to create dyadic data sets. + date_publication: '2018-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StratSel + url_git: '' +STraTUS: + version: 1.1.2 + title: |- + Enumeration and Uniform Sampling of Transmission Trees for a + Known Phylogeny + maintainer: Matthew Hall + description: For a single, known pathogen phylogeny, provides functions for enumeration + of the set of compatible epidemic transmission trees, and for uniform sampling + from that set. Optional arguments allow for incomplete sampling with a known number + of missing individuals, multiple sampling, and known infection time limits. Always + assumed are a complete transmission bottleneck and no superinfection or reinfection. + See Hall and Colijn (2019) for methodology. + date_publication: '2020-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STraTUS + url_git: http://github.com/mdhall272/STraTUS/ +straweib: + version: '1.1' + title: Stratified Weibull Regression Model + maintainer: Xiangdong Gu + description: |- + The main function is icweib(), which fits a stratified Weibull + proportional hazards model for left censored, right censored, interval censored, + and non-censored survival data. We parameterize the Weibull regression model + so that it allows a stratum-specific baseline hazard function, but where the + effects of other covariates are assumed to be constant across strata. + Please refer to Xiangdong Gu, David Shapiro, Michael D. Hughes and + Raji Balasubramanian (2014) for more details. + date_publication: '2019-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=straweib + url_git: '' +strawr: + version: 0.0.92 + title: Fast Implementation of Reading/Dump for .hic Files + maintainer: Neva Cherniavsky Durand + description: API for fast data extraction for .hic files that provides programmatic + access to the matrices. It doesn't store the pointer data for all the matrices, + only the one queried, and currently we are only supporting matrices (not vectors). + date_publication: '2024-07-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=strawr + url_git: https://github.com/aidenlab/straw/tree/master/R +stray: + version: 0.1.1 + title: Anomaly Detection in High Dimensional and Temporal Data + maintainer: Priyanga Dilini Talagala + description: |2- + + This is a modification of 'HDoutliers' package. The 'HDoutliers' algorithm is a powerful + unsupervised algorithm for detecting anomalies in high-dimensional data, with a + strong theoretical foundation. However, it suffers from some limitations that + significantly hinder its performance level, under certain circumstances. This package + implements the algorithm proposed in Talagala, Hyndman and Smith-Miles (2019) + for detecting anomalies in high-dimensional data + that addresses these limitations of 'HDoutliers' algorithm. We define an anomaly as an observation that deviates markedly from the majority + with a large distance gap. An approach based on extreme value theory is used + for the anomalous threshold calculation. + date_publication: '2020-06-29' + bug_reports: https://github.com/pridiltal/stray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stray + url_git: '' +STREAK: + version: 1.0.0 + title: |- + Receptor Abundance Estimation using Feature Selection and Gene + Set Scoring + maintainer: Azka Javaid + description: 'Performs receptor abundance estimation for single cell RNA-sequencing + data using a supervised feature selection mechanism and a thresholded gene set + scoring procedure. Seurat''s normalization method is described in: Hao et al., + (2021) , Stuart et al., (2019) , + Butler et al., (2018) and Satija et al., (2015) . + Method for reduced rank reconstruction and rank-k selection is detailed in: Javaid + et al., (2022) . Gene set scoring procedure is + described in: Frost et al., (2020) . Clustering method + is outlined in: Song et al., (2020) and Wang + et al., (2011) .' + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STREAK + url_git: '' +stream: + version: 2.0-2 + title: Infrastructure for Data Stream Mining + maintainer: Michael Hahsler + description: A framework for data stream modeling and associated data mining tasks + such as clustering and classification. The development of this package was supported + in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et + al (2017) . + date_publication: '2024-04-21' + bug_reports: https://github.com/mhahsler/stream/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stream + url_git: https://github.com/mhahsler/stream +streambugs: + version: '1.4' + title: |- + Parametric Ordinary Differential Equations Model of Growth, + Death, and Respiration of Macroinvertebrate and Algae Taxa + maintainer: Nele Schuwirth + description: |- + Numerically solve and plot solutions of a parametric ordinary + differential equations model of growth, death, and respiration of + macroinvertebrate and algae taxa dependent on pre-defined environmental + factors. The model (version 1.0) is introduced in Schuwirth, N. and + Reichert, P., (2013) . This package includes + model extensions and the core functions introduced and used in + Schuwirth, N. et al. (2016) , + Kattwinkel, M. et al. (2016) , + Mondy, C. P., and Schuwirth, N. (2017) , + and Paillex, A. et al. (2017) . + date_publication: '2023-11-29' + bug_reports: https://gitlab.com/NeleSchuwirth/streambugs/-/issues + url: https://www.eawag.ch/en/department/siam/projects/streambugs/ + url_cran: https://CRAN.R-project.org/package=streambugs + url_git: '' +streamDAG: + version: 1.5-9 + title: Analytical Methods for Stream DAGs + maintainer: Ken Aho + description: 'Provides indices and tools for directed acyclic graphs (DAGs), particularly + DAG representations of intermittent streams. A detailed introduction to the package + can be found in the publication: "Non-perennial stream networks as directed acyclic + graphs: The R-package streamDAG" (Aho et al., 2023) , + and in the introductory package vignette.' + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=streamDAG + url_git: '' +streamDepletr: + version: 0.2.0 + title: Estimate Streamflow Depletion Due to Groundwater Pumping + maintainer: Sam Zipper + description: |- + Implementation of analytical models for estimating streamflow + depletion due to groundwater pumping, and other related tools. Functions + are broadly split into two groups: (1) analytical streamflow depletion + models, which estimate streamflow depletion for a single stream reach + resulting from groundwater pumping; and (2) depletion apportionment + equations, which distribute estimated streamflow depletion among multiple + stream reaches within a stream network. See Zipper et al. (2018) + for more information on depletion apportionment equations and Zipper et + al. (2019) for more information on analytical + depletion functions, which combine analytical models and depletion apportionment + equations. + date_publication: '2023-07-19' + bug_reports: https://github.com/FoundrySpatial/streamDepletr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=streamDepletr + url_git: https://github.com/FoundrySpatial/streamDepletr +StreamMetabolism: + version: 1.1.3 + title: Calculate Single Station Metabolism from Diurnal Oxygen Curves + maintainer: Stephen A Sefick Jr. + description: I provide functions to calculate Gross Primary Productivity, Net Ecosystem + Production, and Ecosystem Respiration from single station diurnal Oxygen curves. + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StreamMetabolism + url_git: https://github.com/ssefick/StreamMetabolism +streamMOA: + version: 1.3-1 + title: Interface for MOA Stream Clustering Algorithms + maintainer: Michael Hahsler + description: 'Interface for data stream clustering algorithms implemented in the + MOA (Massive Online Analysis) framework (Albert Bifet, Geoff Holmes, Richard Kirkby, + Bernhard Pfahringer (2010). MOA: Massive Online Analysis, Journal of Machine Learning + Research 11: 1601-1604).' + date_publication: '2024-04-20' + bug_reports: https://github.com/mhahsler/streamMOA + url: '' + url_cran: https://CRAN.R-project.org/package=streamMOA + url_git: '' +streamR: + version: 0.4.5 + title: Access to Twitter Streaming API via R + maintainer: Pablo Barbera + description: |- + Functions to access Twitter's filter, sample, and user streams, and to + parse the output into data frames. + date_publication: '2018-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=streamR + url_git: '' +streamy: + version: 0.1.0 + title: Inline Asynchronous Generator Results into Documents + maintainer: Simon Couch + description: |- + Given a 'coro' asynchronous generator instance that produces text, + write that text into a document selection in 'RStudio' and 'Positron'. This + is particularly helpful for streaming large language model responses into + the user's editor. + date_publication: '2025-02-11' + bug_reports: https://github.com/simonpcouch/streamy/issues + url: https://simonpcouch.github.io/streamy/ + url_cran: https://CRAN.R-project.org/package=streamy + url_git: https://github.com/simonpcouch/streamy +streetscape: + version: 1.0.5 + title: Collect and Investigate Street Views for Urban Science + maintainer: Xiaohao Yang + description: |- + A collection of functions to search and download street view imagery + ('Mapilary' ) and + to extract, quantify, and visualize visual features. Moreover, there are + functions provided to generate Qualtrics survey in TXT format using + the collection of street views for various research purposes. + date_publication: '2025-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=streetscape + url_git: '' +StReg: + version: '1.1' + title: Student's t Regression Models + maintainer: Niraj Poudyal + description: |- + It contains functions to estimate multivariate Student's t dynamic and static regression models for given degrees of freedom and lag length. Users can also specify the trends and dummies of any kind in matrix form. + Poudyal, N., and Spanos, A. (2022) . + Spanos, A. (1994) . + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StReg + url_git: '' +stressaddition: + version: 3.1.0 + title: Modelling Tri-Phasic Concentration-Response Relationships + maintainer: Sebastian Henz + description: |- + The stress addition approach is an alternative to the traditional + concentration addition or effect addition models. It allows the modelling + of tri-phasic concentration-response relationships either as single toxicant + experiments, in combination with an environmental stressor or as mixtures of + two toxicants. See Liess et al. (2019) + and Liess et al. (2020) . + date_publication: '2020-11-03' + bug_reports: '' + url: https://git.ufz.de/oekotox/stressaddition + url_cran: https://CRAN.R-project.org/package=stressaddition + url_git: '' +stressor: + version: 0.2.0 + title: Algorithms for Testing Models under Stress + maintainer: Sam Haycock + description: |- + Traditional model evaluation metrics fail to capture model + performance under less than ideal conditions. This package employs + techniques to evaluate models "under-stress". This includes testing + models' extrapolation ability, or testing accuracy on specific + sub-samples of the overall model space. Details describing stress-testing + methods in this package are provided in + Haycock (2023) . The other primary contribution of + this package is provided to R users access to the 'Python' library 'PyCaret' + for quick and easy access to auto-tuned + machine learning models. + date_publication: '2024-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stressor + url_git: '' +stressr: + version: 1.0.0 + title: Fetch and plot financial stress index and component data. + maintainer: Matt Barry + description: |- + Forms queries to submit to the Cleveland Federal Reserve Bank web + site's financial stress index data site. Provides query functions for both + the composite stress index and the components data. By default the download + includes daily time series data starting September 25, 1991. The functions + return a class of either type easing or cfsi which contain a list of items + related to the query and its graphical presentation. The list includes the + time series data as an xts object. The package provides four lattice time + series plots to render the time series data in a manner similar to the + bank's own presentation. + date_publication: '2014-06-30' + bug_reports: https://github.com/mrbcuda/stressr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stressr + url_git: https://github.com/mrbcuda/stressr +StressStrength: + version: 1.0.2 + title: |- + Computation and Estimation of Reliability of Stress-Strength + Models + maintainer: Alessandro Barbiero + description: Reliability of (normal) stress-strength models and for building two-sided + or one-sided confidence intervals according to different approximate procedures. + date_publication: '2016-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StressStrength + url_git: '' +strex: + version: 2.0.1 + title: Extra String Manipulation Functions + maintainer: Rory Nolan + description: |- + There are some things that I wish were easier with the + 'stringr' or 'stringi' packages. The foremost of these is the + extraction of numbers from strings. 'stringr' and 'stringi' make you + figure out the regular expression for yourself; 'strex' takes care of + this for you. There are many other handy functionalities in 'strex'. + Contributions to this package are encouraged; it is intended as a + miscellany of string manipulation functions that cannot be found in + 'stringi' or 'stringr'. + date_publication: '2024-10-03' + bug_reports: https://github.com/rorynolan/strex/issues + url: https://rorynolan.github.io/strex/ + url_cran: https://CRAN.R-project.org/package=strex + url_git: https://github.com/rorynolan/strex +strider: + version: '1.3' + title: Strided Iterator and Range + maintainer: Tim Keitt + description: |- + The strided iterator adapts multidimensional buffers to work with + the C++ standard library and range-based for-loops. Given a pointer or iterator + into a multidimensional data buffer, one can generate an iterator range using + make_strided to construct strided versions of the standard library's begin and + end. For constructing range-based for-loops, a strided_range class is provided. + These help authors to avoid integer-based indexing, which in some cases can impede + algorithm performance and introduce indexing errors. This library exists + primarily to expose the header file to other R projects. + date_publication: '2020-06-03' + bug_reports: https://github.com/thk686/strider/issues + url: '' + url_cran: https://CRAN.R-project.org/package=strider + url_git: https://github.com/thk686/strider +String2AdjMatrix: + version: 0.1.0 + title: Creates an Adjacency Matrix from a List of Strings + maintainer: Tom Drake + description: |- + Takes a list of character strings and forms an adjacency matrix for + the times the specified characters appear together in the strings provided. For + use in social network analysis and data wrangling. Simple package, comprised of + three functions. + date_publication: '2018-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=String2AdjMatrix + url_git: '' +string2path: + version: 0.2.0 + title: Rendering Font into 'data.frame' + maintainer: Hiroaki Yutani + description: |- + Extract glyph information from font data, and translate the + outline curves to flattened paths or tessellated polygons. The converted + data is returned as a 'data.frame' in easy-to-plot format. + date_publication: '2025-02-08' + bug_reports: https://github.com/yutannihilation/string2path/issues + url: https://yutannihilation.github.io/string2path/ + url_cran: https://CRAN.R-project.org/package=string2path + url_git: https://github.com/yutannihilation/string2path +stringdist: + version: 0.9.15 + title: |- + Approximate String Matching, Fuzzy Text Search, and String + Distance Functions + maintainer: Mark van der Loo + description: |- + Implements an approximate string matching version of R's native + 'match' function. Also offers fuzzy text search based on various string + distance measures. Can calculate various string distances based on edits + (Damerau-Levenshtein, Hamming, Levenshtein, optimal sting alignment), qgrams (q- + gram, cosine, jaccard distance) or heuristic metrics (Jaro, Jaro-Winkler). An + implementation of soundex is provided as well. Distances can be computed between + character vectors while taking proper care of encoding or between integer + vectors representing generic sequences. This package is built for speed and + runs in parallel by using 'openMP'. An API for C or C++ is exposed as well. + Reference: MPJ van der Loo (2014) . + date_publication: '2025-01-10' + bug_reports: https://github.com/markvanderloo/stringdist/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stringdist + url_git: https://github.com/markvanderloo/stringdist +stringfish: + version: 0.16.0 + title: Alt String Implementation + maintainer: Travers Ching + description: Provides an extendable, performant and multithreaded 'alt-string' implementation + backed by 'C++' vectors and strings. + date_publication: '2023-11-28' + bug_reports: https://github.com/traversc/stringfish/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stringfish + url_git: https://github.com/traversc/stringfish +stringformattr: + version: 0.1.2 + title: Dynamic String Formatting + maintainer: Alexander Hoyle + description: |- + Pass named and unnamed character vectors into specified positions + in strings. This represents an attempt to replicate some of python's string + formatting. + date_publication: '2017-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stringformattr + url_git: '' +stringi: + version: 1.8.4 + title: Fast and Portable Character String Processing Facilities + maintainer: Marek Gagolewski + description: |- + A collection of character string/text/natural language + processing tools for pattern searching (e.g., with 'Java'-like regular + expressions or the 'Unicode' collation algorithm), random string generation, + case mapping, string transliteration, concatenation, sorting, padding, + wrapping, Unicode normalisation, date-time formatting and parsing, + and many more. They are fast, consistent, convenient, and - + thanks to 'ICU' (International Components for Unicode) - + portable across all locales and platforms. Documentation about 'stringi' is + provided via its website at and + the paper by Gagolewski (2022, ). + date_publication: '2024-05-06' + bug_reports: https://github.com/gagolews/stringi/issues + url: https://stringi.gagolewski.com/ + url_cran: https://CRAN.R-project.org/package=stringi + url_git: https://github.com/gagolews/stringi +stringmagic: + version: 1.1.2 + title: Character String Operations and Interpolation, Magic Edition + maintainer: Laurent R Berge + description: Performs complex string operations compactly and efficiently. Supports + string interpolation jointly with over 50 string operations. Also enhances regular + string functions (like grep() and co). See an introduction at . + date_publication: '2024-04-30' + bug_reports: https://github.com/lrberge/stringmagic/issues + url: https://lrberge.github.io/stringmagic/ + url_cran: https://CRAN.R-project.org/package=stringmagic + url_git: https://github.com/lrberge/stringmagic +stringr: + version: 1.5.1 + title: Simple, Consistent Wrappers for Common String Operations + maintainer: Hadley Wickham + description: |- + A consistent, simple and easy to use set of wrappers around + the fantastic 'stringi' package. All function and argument names (and + positions) are consistent, all functions deal with "NA"'s and zero + length vectors in the same way, and the output from one function is + easy to feed into the input of another. + date_publication: '2023-11-14' + bug_reports: https://github.com/tidyverse/stringr/issues + url: https://stringr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=stringr + url_git: https://github.com/tidyverse/stringr +stringstatic: + version: 0.1.2 + title: Dependency-Free String Operations + maintainer: Alexander Rossell Hayes + description: |- + Provides drop-in replacements for functions from the + 'stringr' package, with the same user interface. These functions have + no external dependencies and can be copied directly into your package + code using the 'staticimports' package. + date_publication: '2023-07-12' + bug_reports: https://github.com/rossellhayes/stringstatic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=stringstatic + url_git: https://github.com/rossellhayes/stringstatic +stringx: + version: 0.2.9 + title: Replacements for Base String Functions Powered by 'stringi' + maintainer: Marek Gagolewski + description: |- + English is the native language for only 5% of the World population. + Also, only 17% of us can understand this text. Moreover, the Latin alphabet + is the main one for merely 36% of the total. + The early computer era, now a very long time ago, was dominated by the US. + Due to the proliferation of the internet, smartphones, social media, and + other technologies and communication platforms, this is no longer the case. + This package replaces base R string functions (such as grep(), + tolower(), sprintf(), and strptime()) with ones that fully + support the Unicode standards related to natural language and + date-time processing. It also fixes some long-standing inconsistencies, + and introduces some new, useful features. + Thanks to 'ICU' (International Components for Unicode) and 'stringi', + they are fast, reliable, and portable across different platforms. + date_publication: '2025-01-11' + bug_reports: https://github.com/gagolews/stringx/issues + url: https://stringx.gagolewski.com/ + url_cran: https://CRAN.R-project.org/package=stringx + url_git: https://github.com/gagolews/stringx +strip: + version: 1.0.0 + title: Lighten your R Model Outputs + maintainer: Paul Poncet + description: The strip function deletes components of R model outputs that are useless + for specific purposes, such as predict[ing], print[ing], summary[izing], etc. + date_publication: '2018-10-29' + bug_reports: https://github.com/paulponcet/strip/issues + url: '' + url_cran: https://CRAN.R-project.org/package=strip + url_git: https://github.com/paulponcet/strip +stripless: + version: 1.0-3 + title: Structured Trellis Displays Without Strips for Lattice Graphics + maintainer: Bert Gunter + description: |- + For making Trellis-type conditioning plots without strip labels. + This is useful for displaying the structure of results from factorial designs + and other studies when many conditioning variables would clutter the display + with layers of redundant strip labels. Settings of the variables are encoded by + layout and spacing in the trellis array and decoded by a separate legend. The + functionality is implemented by a single S3 generic strucplot() function that + is a wrapper for the Lattice package's xyplot() function. This allows access to + all Lattice graphics capabilities in the usual way. + date_publication: '2016-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stripless + url_git: '' +striprtf: + version: 0.6.0 + title: Extract Text from RTF File + maintainer: Kota Mori + description: Extracts plain text from RTF (Rich Text Format) file. + date_publication: '2023-08-10' + bug_reports: https://github.com/kota7/striprtf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=striprtf + url_git: https://github.com/kota7/striprtf +STRMPS: + version: 0.6.8 + title: |- + Analysis of Short Tandem Repeat (STR) Massively Parallel + Sequencing (MPS) Data + maintainer: Søren B. Vilsen + description: 'Loading, identifying, aggregating, manipulating, and analysing short + tandem repeat regions of massively parallel sequencing data in forensic genetics. + The analyses and framework implemented in this package relies on the papers of + Vilsen et al. (2017) and Vilsen et al. (2018) + . Note: that the parallelisation in the package + relies on mclapply() and, thus, speed-ups will only be seen on UNIX based systems.' + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=STRMPS + url_git: '' +stRoke: + version: 24.10.1 + title: Clinical Stroke Research + maintainer: Andreas Gammelgaard Damsbo + description: |- + A collection of tools for clinical trial data management and + analysis in research and teaching. + The package is mainly collected for personal use, but any use beyond that is encouraged. + This package has migrated functions from 'agdamsbo/daDoctoR', and new functions has been added. + Version follows months and year. See NEWS/Changelog for release notes. + This package includes sampled data from the TALOS trial (Kraglund et al (2018) ). + The win_prob() function is based on work by Zou et al (2022) . + The age_calc() function is based on work by Becker (2020) . + date_publication: '2024-10-25' + bug_reports: https://github.com/agdamsbo/stRoke/issues + url: https://agdamsbo.github.io/stRoke/ + url_cran: https://CRAN.R-project.org/package=stRoke + url_git: https://github.com/agdamsbo/stRoke +StroupGLMM: + version: 0.3.0 + title: |- + R Codes and Datasets for Generalized Linear Mixed Models: Modern + Concepts, Methods and Applications by Walter W. Stroup + maintainer: Muhammad Yaseen + description: R Codes and Datasets for Stroup, W. W. (2012). Generalized Linear Mixed + Models Modern Concepts, Methods and Applications, CRC Press. + date_publication: '2024-10-01' + bug_reports: https://github.com/myaseen208/StroupGLMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=StroupGLMM + url_git: '' +strs: + version: 0.1.0 + title: '''Python'' Style String Functions' + maintainer: Garrett Shipley + description: |- + A comprehensive set of string manipulation functions based on those found in 'Python' + without relying on 'reticulate'. It provides functions that intend to (1) make it easier for + users familiar with 'Python' to work with strings, (2) reduce the complexity often associated + with string operations, (3) and enable users to write more readable and maintainable code + that manipulates strings. + date_publication: '2024-09-02' + bug_reports: https://github.com/pythonicr/strs/issues + url: https://pythonicr.github.io/strs/ + url_cran: https://CRAN.R-project.org/package=strs + url_git: https://github.com/pythonicr/strs +strucchange: + version: 1.5-4 + title: Testing, Monitoring, and Dating Structural Changes + maintainer: Achim Zeileis + description: |- + Testing, monitoring and dating structural changes in (linear) + regression models. strucchange features tests/methods from + the generalized fluctuation test framework as well as from + the F test (Chow test) framework. This includes methods to + fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, + recursive/moving estimates) and F statistics, respectively. + It is possible to monitor incoming data online using + fluctuation processes. + Finally, the breakpoints in regression models with structural + changes can be estimated together with confidence intervals. + Emphasis is always given to methods for visualizing the data. + date_publication: '2024-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=strucchange + url_git: '' +strucchangeRcpp: + version: 1.5-4-1.0.0 + title: 'Testing, Monitoring, and Dating Structural Changes: C++ Version' + maintainer: Dainius Masiliunas + description: |- + A fast implementation with additional experimental features for + testing, monitoring and dating structural changes in (linear) + regression models. 'strucchangeRcpp' features tests/methods from + the generalized fluctuation test framework as well as from + the F test (Chow test) framework. This includes methods to + fit, plot and test fluctuation processes (e.g. cumulative/moving + sum, recursive/moving estimates) and F statistics, respectively. + These methods are described in Zeileis et al. (2002) + . + Finally, the breakpoints in regression models with structural + changes can be estimated together with confidence intervals, + and their magnitude as well as the model fit can be evaluated + using a variety of statistical measures. + date_publication: '2024-10-17' + bug_reports: https://github.com/bfast2/strucchangeRcpp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=strucchangeRcpp + url_git: https://github.com/bfast2/strucchangeRcpp/ +structree: + version: 1.1.7 + title: Tree-Structured Clustering + maintainer: Moritz Berger + description: |- + Tree-structured modelling of categorical predictors (Tutz and Berger (2018), ) or measurement + units (Berger and Tutz (2018), ). + date_publication: '2020-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=structree + url_git: '' +StructuralDecompose: + version: 0.1.1 + title: Decomposes a Level Shifted Time Series + maintainer: Allen Sunny + description: |- + Explains the behavior of a time series by decomposing it into its trend, seasonality and residuals. + It is built to perform very well in the presence of significant level shifts. It is designed to play + well with any breakpoint algorithm and any smoothing algorithm. Currently defaults to 'lowess' for smoothing + and 'strucchange' for breakpoint identification. The package is useful in areas such as trend analysis, time series + decomposition, breakpoint identification and anomaly detection. + date_publication: '2023-02-13' + bug_reports: '' + url: https://allen-1242.github.io/StructuralDecompose/ + url_cran: https://CRAN.R-project.org/package=StructuralDecompose + url_git: '' +StructureMC: + version: '1.0' + title: Structured Matrix Completion + maintainer: Yifu Liu + description: Provides an efficient method to recover the missing block of an approximately + low-rank matrix. Current literature on matrix completion focuses primarily on + independent sampling models under which the individual observed entries are sampled + independently. Motivated by applications in genomic data integration, we propose + a new framework of structured matrix completion (SMC) to treat structured missingness + by design [Cai T, Cai TT, Zhang A (2016) ]. + Specifically, our proposed method aims at efficient matrix recovery when a subset + of the rows and columns of an approximately low-rank matrix are observed. The + main function in our package, smc.FUN(), is for recovery of the missing block + A22 of an approximately low-rank matrix A given the other blocks A11, A12, A21. + date_publication: '2019-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StructureMC + url_git: '' +strvalidator: + version: 2.4.1 + title: Process Control and Validation of Forensic STR Kits + maintainer: Oskar Hansson + description: |- + An open source platform for validation and process control. + Tools to analyze data from internal validation of forensic short tandem + repeat (STR) kits are provided. The tools are developed to provide + the necessary data to conform with guidelines for internal validation + issued by the European Network of Forensic Science Institutes (ENFSI) + DNA Working Group, and the Scientific Working Group on DNA Analysis Methods + (SWGDAM). A front-end graphical user interface is provided. + More information about each function can be found in the + respective help documentation. + date_publication: '2023-07-16' + bug_reports: https://github.com/OskarHansson/strvalidator/issues + url: https://sites.google.com/site/forensicapps/strvalidator + url_cran: https://CRAN.R-project.org/package=strvalidator + url_git: '' +sts: + version: '1.4' + title: |- + Estimation of the Structural Topic and Sentiment-Discourse Model + for Text Analysis + maintainer: Shawn Mankad + description: The Structural Topic and Sentiment-Discourse (STS) model allows researchers + to estimate topic models with document-level metadata that determines both topic + prevalence and sentiment-discourse. The sentiment-discourse is modeled as a document-level + latent variable for each topic that modulates the word frequency within a topic. + These latent topic sentiment-discourse variables are controlled by the document-level + metadata. The STS model can be useful for regression analysis with text data in + addition to topic modeling’s traditional use of descriptive analysis. The method + was developed in Chen and Mankad (2024) . + date_publication: '2025-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sts + url_git: '' +sTSD: + version: 0.2.0 + title: Simulate Time Series Diagnostics + maintainer: Steven Miller + description: |- + These are tools that allow users to do time series diagnostics, primarily + tests of unit root, by way of simulation. While there is nothing necessarily + wrong with the received wisdom of critical values generated decades ago, + simulation provides its own perks. Not only is simulation broadly informative + as to what these various test statistics do and what are their plausible + values, simulation provides more flexibility for assessing unit root by way + of different thresholds or different hypothesized distributions. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sTSD + url_git: '' +stuart: + version: 0.10.2 + title: Subtests Using Algorithmic Rummaging Techniques + maintainer: Martin Schultze + description: |- + Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling. + Schultze (2017) . + date_publication: '2023-06-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stuart + url_git: '' +studentlife: + version: 1.1.0 + title: Tidy Handling and Navigation of the Student-Life Dataset + maintainer: Daniel Fryer + description: |- + Download, navigate and analyse the Student-Life dataset. + The Student-Life dataset contains passive and automatic sensing data + from the phones of a class of 48 Dartmouth college students. + It was collected over a 10 week term. Additionally, the dataset contains ecological + momentary assessment results along with pre-study and post-study mental + health surveys. The intended use is to assess + mental health, academic performance and behavioral trends. + The raw dataset and additional information is + available at . + date_publication: '2020-11-01' + bug_reports: https://github.com/Frycast/studentlife/issues + url: '' + url_cran: https://CRAN.R-project.org/package=studentlife + url_git: https://github.com/Frycast/studentlife +studyStrap: + version: 1.0.0 + title: Study Strap and Multi-Study Learning Algorithms + maintainer: Gabriel Loewinger + description: |- + Implements multi-study learning algorithms such as + merging, the study-specific ensemble (trained-on-observed-studies ensemble) the study strap, + the covariate-matched study strap, covariate-profile similarity weighting, and stacking weights. + Embedded within the 'caret' framework, this package allows for a wide range of + single-study learners (e.g., neural networks, lasso, random forests). + The package offers over 20 default similarity measures and allows for specification of custom + similarity measures for covariate-profile similarity weighting and an accept/reject step. + This implements methods described in Loewinger, Kishida, Patil, and Parmigiani. (2019) + . + date_publication: '2020-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=studyStrap + url_git: '' +StuteTest: + version: 1.0.2 + title: Stute (1997) Linearity Test + maintainer: Diego Ciccia + description: Non-parametric test, originally proposed by Stute (1997) , + that the expectation of a dependent variable Y given an independent variable D + is linear in D. + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=StuteTest + url_git: '' +STV: + version: 1.0.2 + title: Single Transferable Vote Counting + maintainer: John Emerson + description: |- + Implementations of the Single Transferable Vote counting + system. By default, it uses the Cambridge method for surplus allocation + and Droop method for quota calculation. Fractional surplus allocation + and the Hare quota are available as options. + date_publication: '2021-02-01' + bug_reports: https://github.com/jayemerson/STV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=STV + url_git: https://github.com/jayemerson/STV +stxplore: + version: 0.1.0 + title: Exploration of Spatio-Temporal Data + maintainer: Sevvandi Kandanaarachchi + description: |- + A set of statistical tools for spatio-temporal data exploration. + Includes simple plotting functions, covariance calculations and computations + similar to principal component analysis for spatio-temporal data. Can use + both dataframes and stars objects for all plots and computations. For more + details refer 'Spatio-Temporal Statistics with R' (Christopher K. Wikle, + Andrew Zammit-Mangion, Noel Cressie, 2019, ISBN:9781138711136). + date_publication: '2023-02-03' + bug_reports: '' + url: https://sevvandi.github.io/stxplore/ + url_cran: https://CRAN.R-project.org/package=stxplore + url_git: '' +styler: + version: 1.10.3 + title: Non-Invasive Pretty Printing of R Code + maintainer: Lorenz Walthert + description: |- + Pretty-prints R code without changing the user's formatting + intent. + date_publication: '2024-04-07' + bug_reports: https://github.com/r-lib/styler/issues + url: https://styler.r-lib.org + url_cran: https://CRAN.R-project.org/package=styler + url_git: https://github.com/r-lib/styler +stylest2: + version: '0.1' + title: Estimating Speakers of Texts + maintainer: Christian Baehr + description: Estimates the authors or speakers of texts. Methods developed in Huang, + Perry, and Spirling (2020) . The model is built on a + Bayesian framework in which the distinctiveness of each speaker is defined by + how different, on average, the speaker's terms are to everyone else in the corpus + of texts. An optional cross-validation method is implemented to select the subset + of terms that generate the most accurate speaker predictions. Once a set of terms + is selected, the model can be estimated. Speaker distinctiveness and term influence + can be recovered from parameters in the model using package functions. Once fitted, + the model can be used to predict authorship of new texts. + date_publication: '2024-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stylest2 + url_git: '' +stylo: + version: 0.7.5 + title: Stylometric Multivariate Analyses + maintainer: Maciej Eder + description: Supervised and unsupervised multivariate methods, supplemented by GUI + and some visualizations, to perform various analyses in the field of computational + stylistics, authorship attribution, etc. For further reference, see Eder et al. + (2016), . You + are also encouraged to visit the Computational Stylistics Group's website , + where a reasonable amount of information about the package and related projects + are provided. + date_publication: '2024-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=stylo + url_git: https://github.com/computationalstylistics/stylo +subcopem2D: + version: '1.3' + title: Bivariate Empirical Subcopula + maintainer: Arturo Erdely + description: Calculate empirical subcopula and dependence measures from a given + bivariate sample, and Bernstein copula approximations. + date_publication: '2019-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subcopem2D + url_git: '' +subdetect: + version: '1.2' + title: Detect Subgroup with an Enhanced Treatment Effect + maintainer: Shannon T. Holloway + description: |- + A test for the existence of a subgroup with enhanced treatment + effect. And, a sample size calculation procedure for the subgroup + detection test. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subdetect + url_git: '' +subformula: + version: 0.1.0 + title: Create Subformulas of a Formula + maintainer: Jonas Moss + description: |- + A formula 'sub' is a subformula of 'formula' if all the terms + on the right hand side of 'sub' are terms of 'formula' and their left hand + sides are identical. This package aids in the creation of subformulas. + date_publication: '2019-11-15' + bug_reports: https://github.com/JonasMoss/subformula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=subformula + url_git: https://github.com/JonasMoss/subformula +subgroup: + version: '1.1' + title: |- + Methods for exploring treatment effect heterogeneity in subgroup + analysis of clinical trials + maintainer: I. Manjula Schou + description: Produces various measures of expected treatment effect heterogeneity + under an assumption of homogeneity across subgroups. Graphical presentations are + created to compare these expected differences with the observed differences. + date_publication: '2014-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subgroup + url_git: '' +SubgrpID: + version: '0.12' + title: Patient Subgroup Identification for Clinical Drug Development + maintainer: Xin Huang + description: Implementation of Sequential BATTing (bootstrapping and aggregating + of thresholds from trees) for developing threshold-based multivariate (prognostic/predictive) + biomarker signatures. Variable selection is automatically built-in. Final signatures + are returned with interaction plots for predictive signatures. Cross-validation + performance evaluation and testing dataset results are also output. Detail algorithms + are described in Huang et al (2017) . + date_publication: '2024-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SubgrpID + url_git: '' +subgxe: + version: 0.9.0 + title: Combine Multiple GWAS by Using Gene-Environment Interactions + maintainer: Alexander Rix + description: |- + Classical methods for combining summary data from genome-wide + association studies (GWAS) only use marginal genetic effects and power can + be compromised in the presence of heterogeneity. 'subgxe' is a R package + that implements p-value assisted subset testing for association (pASTA), + a method developed by Yu et al. (2019) . pASTA + generalizes association analysis based on subsets by incorporating + gene-environment interactions into the testing procedure. + date_publication: '2019-06-14' + bug_reports: https://github.com/umich-cphds/subgxe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=subgxe + url_git: https://github.com/umich-cphds/subgxe +subincomeR: + version: 0.3.0 + title: Access to Global Sub-National Income Data + maintainer: Pablo García Guzmán + description: |- + Provides access to granular sub-national income data from the + MCC-PIK Database Of Sub-national Economic Output (DOSE). The package + downloads and processes the data from its open repository on 'Zenodo' + (). Functions are provided to + fetch data at multiple geographic levels, match coordinates to + administrative regions, and access associated geometries. + date_publication: '2025-02-16' + bug_reports: https://github.com/pablogguz/subincomeR/issues + url: https://pablogguz.github.io/subincomeR/ + url_cran: https://CRAN.R-project.org/package=subincomeR + url_git: https://github.com/pablogguz/subincomeR +submax: + version: 1.1.1 + title: |- + Effect Modification in Observational Studies Using the Submax + Method + maintainer: Paul R. Rosenbaum + description: Effect modification occurs if a treatment effect is larger or more + stable in certain subgroups defined by observed covariates. The submax or subgroup-maximum + method of Lee et al. (2017) does an overall test and separate + tests in subgroups, correcting for multiple testing using the joint distribution. + date_publication: '2017-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=submax + url_git: '' +SubpathwayLNCE: + version: '1.0' + title: |- + Identify Signal Subpathways Competitively Regulated by LncRNAs + Based on ceRNA Theory + maintainer: Xinrui Shi + description: Identify dysfunctional subpathways competitively regulated by lncRNAs + through integrating lncRNA-mRNA expression profile and pathway topologies. + date_publication: '2016-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SubpathwayLNCE + url_git: '' +subplex: + version: '1.9' + title: Unconstrained Optimization using the Subplex Algorithm + maintainer: Aaron A. King + description: The subplex algorithm for unconstrained optimization, developed by + Tom Rowan. + date_publication: '2024-07-05' + bug_reports: https://github.com/kingaa/subplex/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=subplex + url_git: https://github.com/kingaa/subplex/ +subrank: + version: 0.9.9.3 + title: Computes Copula using Ranks and Subsampling + maintainer: Jerome Collet + description: Estimation of copula using ranks and subsampling. The main feature + of this method is that simulation studies show a low sensitivity to dimension, + on realistic cases. + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subrank + url_git: '' +subsampling: + version: 0.1.1 + title: Optimal Subsampling Methods for Statistical Models + maintainer: Qingkai Dong + description: |- + Balancing computational and statistical efficiency, subsampling techniques offer + a practical solution for handling large-scale data analysis. Subsampling methods + enhance statistical modeling for massive datasets by efficiently drawing + representative subsamples from full dataset based on tailored sampling probabilities. These + probabilities are optimized for specific goals, such as minimizing the variance + of coefficient estimates or reducing prediction error. + date_publication: '2024-11-05' + bug_reports: https://github.com/dqksnow/Subsampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=subsampling + url_git: https://github.com/dqksnow/Subsampling +subscore: + version: '3.3' + title: |- + Computing Subscores in Classical Test Theory and Item Response + Theory + maintainer: Shenghai Dai + description: |- + Functions for computing test subscores using different + methods in both classical test theory (CTT) and item response theory (IRT). This + package enables three types of subscoring methods within the framework of CTT + and IRT, including (1) Wainer's augmentation method (Wainer et. al., 2001) + , (2) Haberman's subscoring methods (Haberman, 2008) + , and (3) Yen's objective performance index (OPI; Yen, 1987) + . + It also includes functions to compute Proportional Reduction + of Mean Squared Errors (PRMSEs) in Haberman's methods which are used to + examine whether test subscores are of added value. In addition, the package includes + a function to assess the local independence assumption of IRT with + Yen's Q3 statistic (Yen, 1984 ; Yen, 1993 + ). + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subscore + url_git: '' +subscreen: + version: 3.0.7 + title: Systematic Screening of Study Data for Subgroup Effects + maintainer: Bodo Kirsch + description: |- + Identifying outcome relevant subgroups has now become as simple as possible! The formerly lengthy and tedious search for the needle in a haystack will be replaced by a single, comprehensive and coherent presentation. + The central result of a subgroup screening is a diagram in which each single dot stands for a subgroup. + The diagram may show thousands of them. The position of the dot in the diagram is determined by the + sample size of the subgroup and the statistical measure of the treatment effect in that subgroup. The + sample size is shown on the horizontal axis while the treatment effect is displayed on the vertical axis. Furthermore, + the diagram shows the line of no effect and the overall study results. For small subgroups, which + are found on the left side of the plot, larger random deviations from the mean study effect are expected, + while for larger subgroups only small deviations from the study mean can be expected to be chance findings. + So for a study with no conspicuous subgroup effects, the dots in the figure are expected to form a + kind of funnel. Any deviations from this funnel shape hint to conspicuous subgroups. + This approach was presented in Muysers (2020) and referenced in Ballarini (2020) . + New to version 3 is the Automatic Screening of one- or MUlti-factorial Subgroups (ASMUS) for documentation of the structured review of subgroup findings. + date_publication: '2022-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subscreen + url_git: '' +subsemble: + version: 0.1.0 + title: An Ensemble Method for Combining Subset-Specific Algorithm Fits + maintainer: Erin LeDell + description: 'The Subsemble algorithm is a general subset ensemble prediction method, + which can be used for small, moderate, or large datasets. Subsemble partitions + the full dataset into subsets of observations, fits a specified underlying algorithm + on each subset, and uses a unique form of k-fold cross-validation to output a + prediction function that combines the subset-specific fits. An oracle result provides + a theoretical performance guarantee for Subsemble. The paper, "Subsemble: An ensemble + method for combining subset-specific algorithm fits" is authored by Stephanie + Sapp, Mark J. van der Laan & John Canny (2014) .' + date_publication: '2022-01-24' + bug_reports: https://github.com/ledell/subsemble/issues + url: '' + url_cran: https://CRAN.R-project.org/package=subsemble + url_git: https://github.com/ledell/subsemble +subspace: + version: 1.0.4 + title: Interface to OpenSubspace + maintainer: Marwan Hassani + description: |- + An interface to 'OpenSubspace', an open source framework for + evaluation and exploration of subspace clustering algorithms in WEKA + (see for more + information). Also performs visualization. + date_publication: '2015-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=subspace + url_git: '' +SubTite: + version: 4.0.5 + title: Subgroup Specific Optimal Dose Assignment + maintainer: Andrew Chapple + description: Chooses subgroup specific optimal doses in a phase I dose finding clinical + trial allowing for subgroup combination and simulates clinical trials under the + subgroup specific time to event continual reassessment method. Chapple, A.G., + Thall, P.F. (2018) . + date_publication: '2021-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SubTite + url_git: '' +SubTS: + version: '1.0' + title: Positive Tempered Stable Distributions and Related Subordinators + maintainer: Michael Grabchak + description: Contains methods for the simulation of positive tempered stable distributions + and related subordinators. Including classical tempered stable, rapidly deceasing + tempered stable, truncated stable, truncated tempered stable, generalized Dickman, + truncated gamma, generalized gamma, and p-gamma. For details, see Dassios et al + (2019) , Dassios et al (2020) , Grabchak + (2021) . + date_publication: '2023-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SubTS + url_git: '' +SubtypeDrug: + version: 0.1.9 + title: Prioritization of Candidate Cancer Subtype Specific Drugs + maintainer: Junwei Han + description: |- + A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. + The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially + expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease + reverse association score based on subpathway, and visualization of results (Castelo (2013) ; Han et al (2019) ; Lamb and Justin (2006) ). Please cite using . + date_publication: '2024-04-17' + bug_reports: https://github.com/hanjunwei-lab/SubtypeDrug/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SubtypeDrug + url_git: '' +SubVis: + version: 2.0.2 + title: |- + Visual Exploration of Protein Alignments Resulting from Multiple + Substitution Matrices + maintainer: Scott Barlowe + description: Substitution matrices are important parameters in protein alignment + algorithms. These matrices represent the likelihood that an amino acid will be + substituted for another during mutation. This tool allows users to apply predefined + and custom matrices and then explore the resulting alignments with interactive + visualizations. 'SubVis' requires the availability of a web browser. + date_publication: '2017-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SubVis + url_git: '' +success: + version: 1.1.0 + title: Survival Control Charts Estimation Software + maintainer: Daniel Gomon + description: |- + Quality control charts for survival outcomes. + Allows users to construct the Continuous Time Generalized + Rapid Response CUSUM (CGR-CUSUM) , + the Biswas & Kalbfleisch (2008) CUSUM, + the Bernoulli CUSUM and the risk-adjusted funnel plot for survival data + . + These procedures can be used to monitor survival processes for a change + in the failure rate. + date_publication: '2024-06-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=success + url_git: https://github.com/d-gomon/success +sudachir: + version: 0.1.0 + title: R Interface to 'Sudachi' + maintainer: Shinya Uryu + description: |- + Interface to 'Sudachi' , + a Japanese morphological analyzer. This is a port of what is available in Python. + date_publication: '2020-11-10' + bug_reports: https://github.com/uribo/sudachir/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sudachir + url_git: https://github.com/uribo/sudachir +suddengains: + version: 0.7.2 + title: Identify Sudden Gains in Longitudinal Data + maintainer: Milan Wiedemann + description: Identify sudden gains based on the three criteria outlined by Tang + and DeRubeis (1999) to a selection of repeated + measures. Sudden losses, defined as the opposite of sudden gains can also be identified. + Two different datasets can be created, one including all sudden gains/losses and + one including one selected sudden gain/loss for each case. It can extract scores + around sudden gains/losses. It can plot the average change around sudden gains/losses + and trajectories of individual cases. + date_publication: '2023-02-28' + bug_reports: https://github.com/milanwiedemann/suddengains/issues + url: https://milanwiedemann.github.io/suddengains/ + url_cran: https://CRAN.R-project.org/package=suddengains + url_git: '' +sudoku: + version: '2.8' + title: Sudoku Puzzle Generator and Solver + maintainer: David Brahm + description: |- + Generates, plays, and solves Sudoku puzzles. The GUI + playSudoku() needs package "tkrplot" if you are not on Windows. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sudoku + url_git: '' +sudokuAlt: + version: 0.2-1 + title: Tools for Making and Spoiling Sudoku Games + maintainer: Bill Venables + description: |- + Tools for making, retrieving, displaying and solving sudoku games. + This package is an alternative to the earlier sudoku-solver package, + 'sudoku'. The present package uses a slightly different algorithm, has a + simpler coding and presents a few more sugar tools, such as plot and print + methods. Solved sudoku games are of some interest in Experimental Design + as examples of Latin Square designs with additional balance constraints. + date_publication: '2019-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sudokuAlt + url_git: '' +SudokuDesigns: + version: 1.1.0 + title: Sudoku as an Experimental Design + maintainer: Ashutosh Dalal + description: Sudoku designs (Bailey et al., 2008) + can be used as experimental designs which tackle one extra source of variation + than conventional Latin square designs. Although Sudoku designs are similar to + Latin square designs, only addition is the region concept. Some very important + functions related to row-column designs as well as block designs along with basic + functions are included in this package. + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SudokuDesigns + url_git: '' +SuessR: + version: 0.1.6 + title: Suess and Laws Corrections for Marine Stable Carbon Isotope Data + maintainer: Casey Clark + description: |- + Generates region-specific Suess and Laws corrections for + stable carbon isotope data from marine organisms collected between 1850 and 2023. Version + 0.1.6 of 'SuessR' contains four built-in regions: the Bering Sea ('Bering Sea'), the + Aleutian archipelago ('Aleutian Islands'), the Gulf of Alaska ('Gulf of Alaska'), and the + subpolar North Atlantic ('Subpolar North Atlantic'). Users can supply their own environmental + data for regions currently not built into the package to generate corrections for those regions. + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SuessR + url_git: '' +sufficientForecasting: + version: 0.1.0 + title: Sufficient Forecasting using Factor Models + maintainer: Jing Fu + description: 'The sufficient forecasting (SF) method is implemented by this package + for a single time series forecasting using many predictors and a possibly nonlinear + forecasting function. Assuming that the predictors are driven by some latent factors, + the SF first conducts factor analysis and then performs sufficient dimension reduction + on the estimated factors to derive predictive indices for forecasting. The package + implements several dimension reduction approaches, including principal components + (PC), sliced inverse regression (SIR), and directional regression (DR). Methods + for dimension reduction are as described in: Fan, J., Xue, L. and Yao, J. (2017) + , Luo, W., Xue, L., Yao, J. and Yu, X. (2022) + and Yu, X., Yao, J. and Xue, L. (2022) .' + date_publication: '2023-02-17' + bug_reports: https://github.com/JingFu1224/sufficientForecasting/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sufficientForecasting + url_git: https://github.com/JingFu1224/sufficientForecasting +sugarbag: + version: 0.1.6 + title: Create Tessellated Hexagon Maps + maintainer: Dianne Cook + description: |- + Create a hexagon tile map display from spatial polygons. Each + polygon is represented by a hexagon tile, placed as close to it's original + centroid as possible, with a focus on maintaining spatial relationship to + a focal point. Developed to aid visualisation and analysis of spatial + distributions across Australia, which can be challenging due to the + concentration of the population on the coast and wide open interior. + date_publication: '2022-11-09' + bug_reports: '' + url: https://srkobakian.github.io/sugarbag/ + url_cran: https://CRAN.R-project.org/package=sugarbag + url_git: https://github.com/srkobakian/sugarbag +sugarglider: + version: 1.0.3 + title: Create Glyph-Maps of Spatiotemporal Data + maintainer: Maliny Po + description: 'Provides ''ggplot2'' extensions to construct glyph-maps for visualizing + seasonality in spatiotemporal data. See the Journal of Statistical Software reference: + Zhang, H. S., Cook, D., Laa, U., Langrené, N., & Menéndez, P. (2024) . + The manuscript for this package is currently under preparation and can be found + on GitHub at .' + date_publication: '2024-10-24' + bug_reports: https://github.com/maliny12/sugarglider/issues + url: https://maliny12.github.io/sugarglider/ + url_cran: https://CRAN.R-project.org/package=sugarglider + url_git: https://github.com/maliny12/sugarglider +suggests: + version: 0.1.0 + title: Declare when Suggested Packages are Needed + maintainer: Owen Jones + description: |- + By adding dependencies to the "Suggests" field of a package's + DESCRIPTION file, and then declaring that they are needed within any + dependent functionality, it is often possible to significantly reduce the + number of "hard" dependencies required by a package. This package provides + a minimal way to declare when a suggested package is needed. + date_publication: '2023-08-08' + bug_reports: https://github.com/owenjonesuob/suggests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=suggests + url_git: https://github.com/owenjonesuob/suggests +sugrrants: + version: 0.2.9 + title: Supporting Graphs for Analysing Time Series + maintainer: Earo Wang + description: |- + Provides 'ggplot2' graphics for analysing time + series data. It aims to fit into the 'tidyverse' and grammar of + graphics framework for handling temporal data. + date_publication: '2024-03-12' + bug_reports: https://github.com/earowang/sugrrants/issues + url: https://pkg.earo.me/sugrrants/ + url_cran: https://CRAN.R-project.org/package=sugrrants + url_git: '' +SumcaVer1: + version: 0.1.0 + title: Mean Square Prediction Error Estimation in Small Area Estimation + maintainer: Mahmoud Torabi + description: Estimation of mean squared prediction error of a small area predictor + is provided. In particular, the recent method of Simple, Unified, Monte-Carlo + Assisted approach for the mean squared prediction error estimation of small area + predictor is provided. We also provide other existing methods of mean squared + prediction error estimation such as jackknife method for the mixed logistic model. + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SumcaVer1 + url_git: '' +sumFREGAT: + version: 1.2.5 + title: Fast Region-Based Association Tests on Summary Statistics + maintainer: Nadezhda M. Belonogova + description: |- + An adaptation of classical region/gene-based association analysis + techniques to the use of summary statistics (P values and effect sizes) + and correlations between genetic variants as input. It is a tool to perform + the most popular and efficient gene-based tests using the results of genome-wide + association (meta-)analyses without having the original genotypes and + phenotypes at hand. + See for details: + Svishcheva et al (2019) Gene-based association tests using GWAS summary + statistics. Bioinformatics. + Belonogova et al (2022) SumSTAAR: A flexible framework for gene-based + association studies using GWAS summary statistics. PLOS Comp Biol. + date_publication: '2022-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sumFREGAT + url_git: '' +summariser: + version: 2.3.0 + title: Easy Calculation and Visualisation of Confidence Intervals + maintainer: Conor Neilson + description: |- + Functions to speed up the exploratory analysis of simple + datasets using 'dplyr'. Functions are provided to do the + common tasks of calculating confidence intervals. + date_publication: '2020-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=summariser + url_git: https://github.com/condwanaland/summariser +SummaryLasso: + version: 1.2.1 + title: Building Polygenic Risk Score Using GWAS Summary Statistics + maintainer: Ting-Huei Chen + description: Shrinkage estimator for polygenic risk prediction models based on summary + statistics of genome-wide association studies. + date_publication: '2019-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SummaryLasso + url_git: '' +summarytools: + version: 1.1.1 + title: Tools to Quickly and Neatly Summarize Data + maintainer: Dominic Comtois + description: |- + Data frame summaries, cross-tabulations, + weight-enabled frequency tables and common descriptive + (univariate) statistics in concise tables available in a + variety of formats (plain ASCII, Markdown and HTML). A good + point-of-entry for exploring data, both for experienced + and new R users. + date_publication: '2025-02-26' + bug_reports: https://github.com/dcomtois/summarytools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=summarytools + url_git: https://github.com/dcomtois/summarytools +summclust: + version: 0.7.2 + title: |- + Module to Compute Influence and Leverage Statistics for + Regression Models with Clustered Errors + maintainer: Alexander Fischer + description: |- + Module to compute cluster specific information for regression models + with clustered errors, including leverage and influence statistics. + Models of type 'lm' and 'fixest'(from the 'stats' and 'fixest' packages) + are supported. 'summclust' implements similar features as the + user-written 'summclust.ado' Stata module (MacKinnon, Nielsen & Webb, 2022; + ). + date_publication: '2023-08-10' + bug_reports: https://github.com/s3alfisc/summclust/issues + url: https://s3alfisc.github.io/summclust/ + url_cran: https://CRAN.R-project.org/package=summclust + url_git: '' +SUMMER: + version: 2.0.0 + title: |- + Small-Area-Estimation Unit/Area Models and Methods for + Estimation in R + maintainer: Zehang R Li + description: Provides methods for spatial and spatio-temporal smoothing of demographic + and health indicators using survey data, with particular focus on estimating and + projecting under-five mortality rates, described in Mercer et al. (2015) , + Li et al. (2019) , Wu et al. (DHS Spatial Analysis + Reports No. 21, 2021), and Li et al. (2023) . + date_publication: '2025-01-07' + bug_reports: https://github.com/richardli/SUMMER/issues + url: https://richardli.github.io/SUMMER/ + url_cran: https://CRAN.R-project.org/package=SUMMER + url_git: https://github.com/richardli/SUMMER +SUMO: + version: 0.1.0 + title: Generating Multi-Omics Datasets + maintainer: Bernard Isekah Osang'ir + description: Designed to generate multi-omics datasets that closely reflect biological + complexity, the package allows for testing, validation, and benchmarking of multi-omics + integrative methods. The simulated data includes one or multiple predefined signals + (latent/unobserved factors), giving users complete control over the data-generated + characteristics. Tini, Giulia, et al (2019) . + date_publication: '2024-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SUMO + url_git: '' +sumR: + version: 0.4.15 + title: Approximate Summation of Series + maintainer: Guido A. Moreira + description: |- + Application of theoretical results which ensure that the summation + of an infinite discrete series is within an arbitrary margin of error of its + true value. The C code under the hood is shared through header files to allow + users to sum their own low level functions as well. Based on the paper by + Braden (1992) . + date_publication: '2023-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sumR + url_git: '' +sumSome: + version: 1.1.0 + title: Permutation True Discovery Guarantee by Sum-Based Tests + maintainer: Anna Vesely + description: It allows to quickly perform permutation-based closed testing by sum-based + global tests, and construct lower confidence bounds for the TDP, simultaneously + over all subsets of hypotheses. As a main feature, it produces simultaneous lower + confidence bounds for the proportion of active voxels in different clusters for + fMRI cluster analysis. Details may be found in Vesely, Finos, and Goeman (2020) + . + date_publication: '2021-11-24' + bug_reports: https://github.com/annavesely/sumSome/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sumSome + url_git: https://github.com/annavesely/sumSome +sunburstR: + version: 2.1.8 + title: Sunburst 'Htmlwidget' + maintainer: Kent Russell + description: |- + Make interactive 'd3.js' sequence sunburst diagrams in R with the + convenience and infrastructure of an 'htmlwidget'. + date_publication: '2023-02-05' + bug_reports: https://github.com/timelyportfolio/sunburstR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sunburstR + url_git: https://github.com/timelyportfolio/sunburstR +suncalc: + version: 0.5.1 + title: |- + Compute Sun Position, Sunlight Phases, Moon Position and Lunar + Phase + maintainer: Benoit Thieurmel + description: |- + Get sun position, sunlight phases (times for sunrise, sunset, dusk, etc.), + moon position and lunar phase for the given location and time. Most calculations are based on the + formulas given in Astronomy Answers articles about position of the sun and the planets : + . + date_publication: '2022-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=suncalc + url_git: https://github.com/datastorm-open/suncalc +SunCalcMeeus: + version: 0.1.2 + title: Sun Position and Daylight Calculations + maintainer: Pedro J. Aphalo + description: |- + Compute the position of the sun, and local solar time using Meeus' + formulae. Compute day and/or night length using different + twilight definitions or arbitrary sun elevation angles. This package is + part of the 'r4photobiology' suite, Aphalo, P. J. (2015) + . Algorithms from Meeus (1998, ISBN:0943396611). + date_publication: '2025-01-09' + bug_reports: https://github.com/aphalo/SunCalcMeeus/issues + url: https://docs.r4photobiology.info/SunCalcMeeus/ + url_cran: https://CRAN.R-project.org/package=SunCalcMeeus + url_git: https://github.com/aphalo/SunCalcMeeus +Sunclarco: + version: 1.0.0 + title: Survival Analysis using Copulas + maintainer: Roel Braekers + description: Survival analysis for unbalanced clusters using Archimedean copulas + (Prenen et al. (2016) ). + date_publication: '2017-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Sunclarco + url_git: '' +sundialr: + version: 0.1.6.2 + title: |- + An Interface to 'SUNDIALS' Ordinary Differential Equation (ODE) + Solvers + maintainer: Satyaprakash Nayak + description: Provides a way to call the functions in 'SUNDIALS' C ODE solving library + (). Currently the serial version + of ODE solver, 'CVODE', sensitivity calculator 'CVODES' and differential algebraic + solver 'IDA' from the 'SUNDIALS' library are implemented. The package requires + ODE to be written as an 'R' or 'Rcpp' function and does not require the 'SUNDIALS' + library to be installed on the local machine. + date_publication: '2025-01-14' + bug_reports: https://github.com/sn248/sundialr/issues + url: http://sn248.github.io/sundialr/ + url_cran: https://CRAN.R-project.org/package=sundialr + url_git: https://github.com/sn248/sundialr +SUNGEO: + version: 1.3.0 + title: 'Sub-National Geospatial Data Archive: Geoprocessing Toolkit' + maintainer: Yuri M. Zhukov + description: Tools for integrating spatially-misaligned GIS datasets. Part of the + Sub-National Geospatial Data Archive System. + date_publication: '2024-05-14' + bug_reports: '' + url: https://www.sungeo.org/ + url_cran: https://CRAN.R-project.org/package=SUNGEO + url_git: https://github.com/zhukovyuri/SUNGEO +SunsVoc: + version: 0.1.2 + title: Constructing Suns-Voc from Outdoor Time-Series I-V Curves + maintainer: Tyler J. Burleyson + description: |2- + + Suns-Voc (or Isc-Voc) curves can provide the current-voltage (I-V) characteristics of the + diode of photovoltaic cells without the effect of series resistance. + Here, Suns-Voc curves can be constructed with outdoor time-series I-V + curves [1,2,3] of full-size photovoltaic (PV) modules instead of having to be measured in the lab. + Time series of four different power loss modes can be calculated based on obtained Isc-Voc curves. + This material is based upon work supported by the U.S. Department of + Energy's Office of Energy Efficiency and Renewable Energy (EERE) under + Solar Energy Technologies Office (SETO) Agreement Number DE-EE0008172. + Jennifer L. Braid is supported by the U.S. Department of Energy (DOE) Office of + Energy Efficiency and Renewable Energy administered by the Oak Ridge + Institute for Science and Education (ORISE) for the DOE. + ORISE is managed by Oak Ridge Associated Universities (ORAU) under DOE + contract number DE-SC0014664. + [1] Wang, M. et al, 2018. + . + [2] Walters et al, 2018 + . + [3] Guo, S. et al, 2016. + . + date_publication: '2021-04-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SunsVoc + url_git: '' +suntools: + version: 1.0.1 + title: Calculate Sun Position, Sunrise, Sunset, Solar Noon and Twilight + maintainer: Adriaan M. Dokter + description: 'Provides a set of convenient functions for calculating sun-related + information, including the sun''s position (elevation and azimuth), and the times + of sunrise, sunset, solar noon, and twilight for any given geographical location + on Earth. These calculations are based on equations provided by the National Oceanic + & Atmospheric Administration (NOAA) + as described in "Astronomical Algorithms" by Jean Meeus (1991, ISBN: 978-0-943396-35-4).' + date_publication: '2024-11-20' + bug_reports: https://github.com/adokter/suntools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=suntools + url_git: https://github.com/adokter/suntools/ +supclust: + version: 1.1-1 + title: Supervised Clustering of Predictor Variables Such as Genes + maintainer: Martin Maechler + description: |- + Methodology for supervised grouping aka "clustering" of + potentially many predictor variables, such as genes etc, implementing + algorithms 'PELORA' and 'WILMA'. + date_publication: '2021-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=supclust + url_git: https://github.com/mmaechler/supclust +super: + version: 0.0.5 + title: Interpreted String Literals + maintainer: Tim Taylor + description: |- + An implementation of interpreted string literals. Based on the + 'glue' package by Hester & Bryan (2024) but + with a focus on efficiency and simplicity at a cost of flexibility. + date_publication: '2025-02-05' + bug_reports: https://github.com/TimTaylor/super/issues + url: https://timtaylor.github.io/super/ + url_cran: https://CRAN.R-project.org/package=super + url_git: '' +superb: + version: 0.95.19 + title: Summary Plots with Adjusted Error Bars + maintainer: Denis Cousineau + description: |- + Computes standard error and confidence interval of various descriptive statistics under + various designs and sampling schemes. The main function, superbPlot(), return a plot. superbData() + returns a dataframe with the statistic and its precision interval so that other plotting package + can be used. See Cousineau and colleagues (2021) + or Cousineau (2017) for a review as well as Cousineau (2005) + , Morey (2008) , Baguley (2012) + , Cousineau & Laurencelle (2016) , + Cousineau & O'Brien (2014) , Calderini & Harding + for specific references. + date_publication: '2024-11-10' + bug_reports: https://github.com/dcousin3/superb/issues/ + url: https://dcousin3.github.io/superb/ + url_cran: https://CRAN.R-project.org/package=superb + url_git: '' +superbiclust: + version: '1.2' + title: |- + Generating Robust Biclusters from a Bicluster Set (Ensemble + Biclustering) + maintainer: Tatsiana Khamiakova + description: |- + Biclusters are submatrices in the data matrix which + satisfy certain conditions of homogeneity. Package contains + functions for generating robust biclusters with respect to the + initialization parameters for a given bicluster solution + contained in a bicluster set in data, the procedure is also + known as ensemble biclustering. The set of biclusters is + evaluated based on the similarity of its elements (the + overlap), and afterwards the hierarchical tree is constructed + to obtain cut-off points for the classes of robust biclusters. + The result is a number of robust (or super) biclusters with + none or low overlap. + date_publication: '2021-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=superbiclust + url_git: '' +SuperCell: + version: 1.0.1 + title: |- + Simplification of scRNA-Seq Data by Merging Together Similar + Cells + maintainer: Leonard Herault + description: Aggregates large single-cell data into metacell dataset by merging + together gene expression of very similar cells. 'SuperCell' uses 'velocyto.R' + + for RNA velocity. We also recommend installing 'scater' Bioconductor package + . + date_publication: '2024-10-25' + bug_reports: https://github.com/GfellerLab/SuperCell/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SuperCell + url_git: '' +supercells: + version: 1.0.0 + title: Superpixels of Spatial Data + maintainer: Jakub Nowosad + description: |- + Creates superpixels based on input spatial data. + This package works on spatial data with one variable (e.g., continuous raster), many variables (e.g., RGB rasters), and spatial patterns (e.g., areas in categorical rasters). + It is based on the SLIC algorithm (Achanta et al. (2012) ), and readapts it to work with arbitrary dissimilarity measures. + date_publication: '2024-02-11' + bug_reports: https://github.com/Nowosad/supercells/issues + url: https://jakubnowosad.com/supercells/ + url_cran: https://CRAN.R-project.org/package=supercells + url_git: '' +supercompress: + version: '1.1' + title: Supervised Compression of Big Data + maintainer: Chaofan Huang + description: A supervised compression method that incorporates the response for + reducing big data to a carefully selected subset. Please see Joseph and Mak (2021) + . This research is supported by a U.S. National Science + Foundation (NSF) grant CMMI-1921646. + date_publication: '2022-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=supercompress + url_git: '' +superdiag: + version: '2.0' + title: |- + A Comprehensive Test Suite for Testing Markov Chain + Nonconvergence + maintainer: Le Bao + description: |- + The 'superdiag' package provides a comprehensive test suite for testing + Markov Chain nonconvergence. It integrates five standard empirical MCMC convergence + diagnostics (Gelman-Rubin, Geweke, Heidelberger-Welch, Raftery-Lewis, and Hellinger + distance) and plotting functions for trace plots and density histograms. The functions + of the package can be used to present all diagnostic statistics and graphs at once + for conveniently checking MCMC nonconvergence. + date_publication: '2020-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=superdiag + url_git: '' +SuperExactTest: + version: 1.1.0 + title: Exact Test and Visualization of Multi-Set Intersections + maintainer: Minghui Wang + description: Identification of sets of objects with shared features is a common + operation in all disciplines. Analysis of intersections among multiple sets is + fundamental for in-depth understanding of their complex relationships. This package + implements a theoretical framework for efficient computation of statistical distributions + of multi-set intersections based upon combinatorial theory, and provides multiple + scalable techniques for visualizing the intersection statistics. The statistical + algorithm behind this package was published in Wang et al. (2015) . + date_publication: '2022-03-23' + bug_reports: https://github.com/mw201608/SuperExactTest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SuperExactTest + url_git: https://github.com/mw201608/SuperExactTest/ +SuperGauss: + version: 2.0.3 + title: |- + Superfast Likelihood Inference for Stationary Gaussian Time + Series + maintainer: Martin Lysy + description: Likelihood evaluations for stationary Gaussian time series are typically + obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number + of time series observations. This package provides a "superfast" O(n log^2 n) + algorithm written in C++, crossing over with Durbin-Levinson around n = 300. Efficient + implementations of the score and Hessian functions are also provided, leading + to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian + Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only + library, to simplify low-level usage in other packages and outside of R. + date_publication: '2022-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SuperGauss + url_git: '' +superheat: + version: 0.1.0 + title: A Graphical Tool for Exploring Complex Datasets Using Heatmaps + maintainer: Rebecca Barter + description: A system for generating extendable and customizable heatmaps for exploring + complex datasets, including big data and data with multiple data types. + date_publication: '2017-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=superheat + url_git: '' +SuperLearner: + version: 2.0-29 + title: Super Learner Prediction + maintainer: Eric Polley + description: |- + Implements the super learner prediction method and contains a + library of prediction algorithms to be used in the super learner. + date_publication: '2024-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SuperLearner + url_git: https://github.com/ecpolley/SuperLearner +superMICE: + version: 1.1.1 + title: SuperLearner Method for MICE + maintainer: Aaron B. Shev + description: |- + Adds a Super Learner ensemble model method (using the 'SuperLearner' package) + to the 'mice' package. Laqueur, H. S., Shev, A. B., Kagawa, R. M. C. (2021) . + date_publication: '2022-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=superMICE + url_git: '' +superml: + version: 0.5.7 + title: |- + Build Machine Learning Models Like Using Python's Scikit-Learn + Library in R + maintainer: Manish Saraswat + description: |- + The idea is to provide a standard interface + to users who use both R and Python for building machine learning models. + This package provides a scikit-learn's fit, predict interface to + train machine learning models in R. + date_publication: '2024-02-18' + bug_reports: https://github.com/saraswatmks/superml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=superml + url_git: https://github.com/saraswatmks/superml +supernova: + version: 3.0.0 + title: Judd, McClelland, & Ryan Formatting for ANOVA Output + maintainer: Adam Blake + description: |- + Produces ANOVA tables in the format used by Judd, McClelland, + and Ryan (2017, ISBN: 978-1138819832) in their introductory textbook, + Data Analysis. This includes proportional reduction in error and + formatting to improve ease the transition between the book and R. + date_publication: '2024-02-07' + bug_reports: https://github.com/UCLATALL/supernova/issues + url: '' + url_cran: https://CRAN.R-project.org/package=supernova + url_git: https://github.com/UCLATALL/supernova +superpc: + version: '1.12' + title: Supervised Principal Components + maintainer: Jean-Eudes Dazard + description: Does prediction in the case of a censored survival outcome, or a regression + outcome, using the "supervised principal component" approach. 'Superpc' is especially + useful for high-dimensional data when the number of features p dominates the number + of samples n (p >> n paradigm), as generated, for instance, by high-throughput + technologies. + date_publication: '2020-10-19' + bug_reports: '' + url: http://www-stat.stanford.edu/~tibs/superpc + url_cran: https://CRAN.R-project.org/package=superpc + url_git: https://github.com/jedazard/superpc +SuperpixelImageSegmentation: + version: 1.0.5 + title: Superpixel Image Segmentation + maintainer: Lampros Mouselimis + description: Image Segmentation using Superpixels, Affinity Propagation and Kmeans + Clustering. The R code is based primarily on the article "Image Segmentation using + SLIC Superpixels and Affinity Propagation Clustering, Bao Zhou, International + Journal of Science and Research (IJSR), 2013" . + date_publication: '2022-02-06' + bug_reports: https://github.com/mlampros/SuperpixelImageSegmentation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SuperpixelImageSegmentation + url_git: https://github.com/mlampros/SuperpixelImageSegmentation +Superpower: + version: 0.2.0 + title: Simulation-Based Power Analysis for Factorial Designs + maintainer: Aaron Caldwell + description: Functions to perform simulations of ANOVA designs of up to three factors. + Calculates the observed power and average observed effect size for all main effects + and interactions in the ANOVA, and all simple comparisons between conditions. + Includes functions for analytic power calculations and additional helper functions + that compute effect sizes for ANOVA designs, observed error rates in the simulations, + and functions to plot power curves. Please see Lakens, D., & Caldwell, A. R. (2021). + "Simulation-Based Power Analysis for Factorial Analysis of Variance Designs". + . + date_publication: '2022-05-17' + bug_reports: https://github.com/arcaldwell49/Superpower/issues + url: https://aaroncaldwell.us/SuperpowerBook/ + url_cran: https://CRAN.R-project.org/package=Superpower + url_git: '' +SuperRanker: + version: 1.2.1 + title: Sequential Rank Agreement + maintainer: Claus Thorn Ekstrøm + description: Tools for analysing the agreement of two or more rankings of the same + items. Examples are importance rankings of predictor variables and risk predictions + of subjects. Benchmarks for agreement are computed based on random permutation + and bootstrap. See Ekstrøm CT, Gerds TA, Jensen, AK (2018). "Sequential rank agreement + methods for comparison of ranked lists." _Biostatistics_, *20*(4), 582-598 + for more information. + date_publication: '2023-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SuperRanker + url_git: '' +superspreading: + version: 0.3.0 + title: |- + Understand Individual-Level Variation in Infectious Disease + Transmission + maintainer: Joshua W. Lambert + description: |- + Estimate and understand individual-level variation in + transmission. Implements density and cumulative compound Poisson + discrete distribution functions ('Kremer et al.' (2021) + ), as well as functions to calculate + infectious disease outbreak statistics given epidemiological + parameters on individual-level transmission; including the probability + of an outbreak becoming an epidemic/extinct ('Kucharski et al.' (2020) + ), or the cluster size + statistics, e.g. what proportion of cases cause X\% of transmission + ('Lloyd-Smith et al.' (2005) ). + date_publication: '2025-01-27' + bug_reports: https://github.com/epiverse-trace/superspreading/issues + url: https://epiverse-trace.github.io/superspreading/ + url_cran: https://CRAN.R-project.org/package=superspreading + url_git: https://github.com/epiverse-trace/superspreading +supervisedPRIM: + version: 2.0.0 + title: |- + Supervised Classification Learning and Prediction using Patient + Rule Induction Method (PRIM) + maintainer: David Shaub + description: |- + The Patient Rule Induction Method (PRIM) is typically + used for "bump hunting" data mining to identify regions with abnormally + high concentrations of data with large or small values. This package + extends this methodology so that it can be applied to binary classification + problems and used for prediction. + date_publication: '2016-10-01' + bug_reports: https://github.com/dashaub/supervisedPRIM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=supervisedPRIM + url_git: https://github.com/dashaub/supervisedPRIM +SupMZ: + version: 0.2.0 + title: Detecting Structural Change with Heteroskedasticity + maintainer: Muhammad Yaseen + description: 'Calculates the sup MZ value to detect the unknown structural break + points under Heteroskedasticity as given in Ahmed et al. (2017) ().' + date_publication: '2020-01-16' + bug_reports: '' + url: https://myaseen208.github.io/SupMZ/ + url_cran: https://CRAN.R-project.org/package=SupMZ + url_git: https://github.com/myaseen208/SupMZ +SuppDists: + version: 1.1-9.8 + title: Supplementary Distributions + maintainer: Thorsten Pohlert + description: |- + Ten distributions supplementing those built into R. + Inverse Gauss, Kruskal-Wallis, Kendall's Tau, Friedman's chi + squared, Spearman's rho, maximum F ratio, the Pearson product + moment correlation coefficient, Johnson distributions, normal + scores and generalized hypergeometric distributions. + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SuppDists + url_git: '' +support.BWS: + version: 0.4-6 + title: Tools for Case 1 Best-Worst Scaling + maintainer: Hideo Aizaki + description: 'Provides basic functions that support an implementation of object + case (Case 1) best-worst scaling: a function for converting a two-level orthogonal + main-effect design/balanced incomplete block design into questions; two functions + for creating a data set suitable for analysis; a function for calculating count-based + scores; a function for calculating shares of preference; and a function for generating + artificial responses to questions. See Louviere et al. (2015) + for details on best-worst scaling, and Aizaki and Fogarty (2023) + for the package.' + date_publication: '2023-03-29' + bug_reports: '' + url: http://lab.agr.hokudai.ac.jp/spmur/http://lab.agr.hokudai.ac.jp/nmvr/ + url_cran: https://CRAN.R-project.org/package=support.BWS + url_git: '' +support.BWS2: + version: 0.4-0 + title: Tools for Case 2 Best-Worst Scaling + maintainer: Hideo Aizaki + description: Provides three basic functions that support an implementation of Case + 2 (profile case) best-worst scaling. The first is to convert an orthogonal main-effect + design into questions, the second is to create a dataset suitable for analysis, + and the third is to calculate count-based scores. For details, see Aizaki and + Fogarty (2019) . + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=support.BWS2 + url_git: '' +support.BWS3: + version: 0.2-1 + title: Tools for Case 3 Best-Worst Scaling + maintainer: Hideo Aizaki + description: Provides basic functions that support an implementation of multi-profile + case (Case 3) best-worst scaling (BWS). Case 3 BWS is a question-based survey + method to elicit people's preferences for attribute levels. Case 3 BWS constructs + various combinations of attribute levels (profiles) and then asks respondents + to select the best and worst profiles in each choice set. A main function creates + a dataset for the analysis from the choice sets and the responses to the questions. + For details on Case 3 BWS, refer to Louviere et al. (2015) . + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=support.BWS3 + url_git: '' +support.CEs: + version: 0.7-0 + title: |- + Basic Functions for Supporting an Implementation of Choice + Experiments + maintainer: Hideo Aizaki + description: Provides basic functions that support an implementation of (discrete) + choice experiments (CEs). CEs is a question-based survey method measuring people's + preferences for goods/services and their characteristics. Refer to Louviere et + al. (2000) for details on CEs, and Aizaki (2012) + for the package. + date_publication: '2023-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=support.CEs + url_git: '' +supportR: + version: 1.4.0 + title: Support Functions for Wrangling and Visualization + maintainer: Nicholas J Lyon + description: |- + Suite of helper functions for data wrangling and visualization. + The only theme for these functions is that they tend towards simple, short, and narrowly-scoped. + These functions are built for tasks that often recur but are not large enough in scope to warrant an ecosystem of interdependent functions. + date_publication: '2024-06-13' + bug_reports: https://github.com/njlyon0/supportR/issues + url: https://njlyon0.github.io/supportR/ + url_cran: https://CRAN.R-project.org/package=supportR + url_git: https://github.com/njlyon0/supportR +sur: + version: 1.0.4 + title: 'Companion to "Statistics Using R: An Integrative Approach"' + maintainer: Daphna Harel + description: 'Access to the datasets and many of the functions used in "Statistics + Using R: An Integrative Approach". These datasets include a subset of the National + Education Longitudinal Study, the Framingham Heart Study, as well as several simulated + datasets used in the examples throughout the textbook. The functions included + in the package reproduce some of the functionality of ''Stata'' that is not directly + available in ''R''. The package also contains a tutorial on basic data frame + management, including how to handle missing data.' + date_publication: '2020-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sur + url_git: '' +surbayes: + version: 0.1.2 + title: Bayesian Analysis of Seemingly Unrelated Regression Models + maintainer: Ethan Alt + description: |- + Implementation of the direct Monte Carlo approach of + Zellner and Ando (2010) + to sample from posterior of + Seemingly Unrelated Regression (SUR) models. In + addition, a Gibbs sampler is implemented that allows + the user to analyze SUR models using the power prior. + date_publication: '2020-08-26' + bug_reports: https://github.com/ethan-alt/surbayes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=surbayes + url_git: https://github.com/ethan-alt/surbayes +sure: + version: 0.2.0 + title: Surrogate Residuals for Ordinal and General Regression Models + maintainer: Brandon Greenwell + description: |- + An implementation of the surrogate approach to residuals and + diagnostics for ordinal and general regression models; for details, see Liu + and Zhang (2017) . These residuals can be + used to construct standard residual plots for model diagnostics (e.g., + residual-vs-fitted value plots, residual-vs-covariate plots, Q-Q plots, etc.). + The package also provides an 'autoplot' function for producing standard + diagnostic plots using 'ggplot2' graphics. The package currently supports + cumulative link models from packages 'MASS', 'ordinal', 'rms', and 'VGAM'. + Support for binary regression models using the standard 'glm' function is also + available. + date_publication: '2017-09-19' + bug_reports: https://github.com/AFIT-R/sure/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sure + url_git: https://github.com/AFIT-R/sure +sureLDA: + version: 0.1.0-1 + title: A Novel Multi-Disease Automated Phenotyping Method for the EHR + maintainer: Yuri Ahuja + description: A statistical learning method to simultaneously predict a range of + target phenotypes using codified and natural language processing (NLP)-derived + Electronic Health Record (EHR) data. See Ahuja et al (2020) JAMIA + for details. + date_publication: '2020-11-10' + bug_reports: https://github.com/celehs/sureLDA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sureLDA + url_git: https://github.com/celehs/sureLDA +SuRF.vs: + version: 1.1.0.1 + title: Subsampling Ranking Forward Selection (SuRF) + maintainer: Toby Kenney + description: 'Performs variable selection based on subsampling, ranking forward + selection. Details of the method are published in Lihui Liu, Hong Gu, Johan Van + Limbergen, Toby Kenney (2020) SuRF: A new method for sparse variable selection, + with application in microbiome data analysis Statistics in Medicine 40 897-919 + . Xo is the matrix of predictor variables. y is the response + variable. Currently only binary responses using logistic regression are supported. + X is a matrix of additional predictors which should be scaled to have sum 1 prior + to analysis. fold is the number of folds for cross-validation. Alpha is the parameter + for the elastic net method used in the subsampling procedure: the default value + of 1 corresponds to LASSO. prop is the proportion of variables to remove in the + each subsample. weights indicates whether observations should be weighted by class + size. When the class sizes are unbalanced, weighting observations can improve + results. B is the number of subsamples to use for ranking the variables. C is + the number of permutations to use for estimating the critical value of the null + distribution. If the ''doParallel'' package is installed, the function can be + run in parallel by setting ncores to the number of threads to use. If the default + value of 1 is used, or if the ''doParallel'' package is not installed, the function + does not run in parallel. display.progress indicates whether the function should + display messages indicating its progress. family is a family variable for the + glm() fitting. Note that the ''glmnet'' package does not permit the use of nonstandard + link functions, so will always use the default link function. However, the glm() + fitting will use the specified link. The default is binomial with logistic regression, + because this is a common use case. pval is the p-value for inclusion of a variable + in the model. Under the null case, the number of false positives will be geometrically + distributed with this as probability of success, so if this parameter is set to + p, the expected number of false positives should be p/(1-p).' + date_publication: '2022-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SuRF.vs + url_git: '' +surface: + version: '0.6' + title: Fitting Hansen Models to Investigate Convergent Evolution + maintainer: Travis Ingram + description: This data-driven phylogenetic comparative method fits stabilizing selection + models to continuous trait data, building on the 'ouch' methodology of Butler + and King (2004) . The main functions fit a series of Hansen + models using stepwise AIC, then identify cases of convergent evolution where multiple + lineages have shifted to the same adaptive peak. For more information see Ingram + and Mahler (2013) . + date_publication: '2024-08-19' + bug_reports: '' + url: https://www.otago.ac.nz/ecoevotago/research/code/index.html + url_cran: https://CRAN.R-project.org/package=surface + url_git: '' +SurfaceTortoise: + version: 2.0.1 + title: Find Optimal Sampling Locations Based on Spatial Covariate(s) + maintainer: Kristin Persson + description: |- + Create sampling designs using the surface reconstruction algorithm. + Original method by: Olsson, D. 2002. A method to optimize soil sampling from + ancillary data. Poster presenterad at: NJF seminar no. 336, + Implementation of Precision Farming in Practical Agriculture, 10-12 + June 2002, Skara, Sweden. + date_publication: '2023-05-09' + bug_reports: https://github.com/kriper0217/SurfaceTortoise/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SurfaceTortoise + url_git: '' +SurfRough: + version: 0.0.1.0 + title: Calculate Surface/Image Texture Indexes + maintainer: Sebastiano Trevisani + description: Methods for the computation of surface/image texture indices using + a geostatistical based approach (Trevisani et al. (2023) ). + It provides various functions for the computation of surface texture indices (e.g., + omnidirectional roughness and roughness anisotropy), including the ones based + on the robust MAD estimator. The kernels included in the software permit also + to calculate the surface/image texture indices directly from the input surface (i.e., + without de-trending) using increments of order 2. It also provides the new radial + roughness index (RRI), representing the improvement of the popular topographic + roughness index (TRI). The framework can be easily extended with ad-hoc surface/image + texture indices. + date_publication: '2024-08-30' + bug_reports: https://github.com/strevisani/SurfRough/issues + url: https://doi.org/10.5281/zenodo.7132160 + url_cran: https://CRAN.R-project.org/package=SurfRough + url_git: https://github.com/strevisani/SurfRough +surreal: + version: 0.0.1 + title: Create Datasets with Hidden Images in Residual Plots + maintainer: James Joseph Balamuta + description: |- + Implements the "Residual (Sur)Realism" algorithm described by + Stefanski (2007) to generate datasets + that reveal hidden images or messages in their residual plots. It offers + both predefined datasets and tools to embed custom text or images + into residual structures. Allowing users to create intriguing visual + demonstrations for teaching model diagnostics. + date_publication: '2024-09-12' + bug_reports: https://github.com/coatless-rpkg/surreal/issues + url: https://r-pkg.thecoatlessprofessor.com/surreal/ + url_cran: https://CRAN.R-project.org/package=surreal + url_git: https://github.com/coatless-rpkg/surreal +Surrogate: + version: 3.3.3 + title: Evaluation of Surrogate Endpoints in Clinical Trials + maintainer: Wim Van Der Elst + description: |- + In a clinical trial, it frequently occurs that the most credible + outcome to evaluate the effectiveness of a new therapy (the true endpoint) is + difficult to measure. In such a situation, it can be an effective strategy to + replace the true endpoint by a (bio)marker that is easier to measure and that + allows for a prediction of the treatment effect on the true endpoint (a + surrogate endpoint). The package 'Surrogate' allows for an evaluation of the + appropriateness of a candidate surrogate endpoint based on the meta-analytic, + information-theoretic, and causal-inference frameworks. Part of this software + has been developed using funding provided from the European Union's Seventh + Framework Programme for research, technological development and demonstration + (Grant Agreement no 602552), the Special Research Fund (BOF) of Hasselt + University (BOF-number: BOF2OCPO3), GlaxoSmithKline Biologicals, Baekeland + Mandaat (HBC.2022.0145), and Johnson & Johnson Innovative Medicine. + date_publication: '2025-02-11' + bug_reports: https://github.com/florianstijven/Surrogate-development/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Surrogate + url_git: https://github.com/florianstijven/Surrogate-development +SurrogateBMA: + version: '1.0' + title: |- + Flexible Evaluation of Surrogate Markers with Bayesian Model + Averaging + maintainer: Yunshan Duan + description: Provides functions to estimate the proportion of treatment effect explained + by the surrogate marker using a Bayesian Model Averaging approach. Duan and Parast + (2023) . + date_publication: '2024-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateBMA + url_git: '' +SurrogateOutcome: + version: '1.1' + title: |- + Estimation of the Proportion of Treatment Effect Explained by + Surrogate Outcome Information + maintainer: Layla Parast + description: Provides functions to estimate the proportion of treatment effect on + a censored primary outcome that is explained by the treatment effect on a censored + surrogate outcome/event. All methods are described in detail in Parast, Tian, + Cai (2020) "Assessing the Value of a Censored Surrogate Outcome" . + The main functions are (1) R.q.event() which calculates the proportion of the + treatment effect (the difference in restricted mean survival time at time t) explained + by surrogate outcome information observed up to a selected landmark time, (2) + R.t.estimate() which calculates the proportion of the treatment effect explained + by primary outcome information only observed up to a selected landmark time, and + (3) IV.event() which calculates the incremental value of the surrogate outcome + information. + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateOutcome + url_git: '' +SurrogateParadoxTest: + version: '2.0' + title: Empirical Testing of Surrogate Paradox Assumptions + maintainer: Emily Hsiao + description: Provides functions to nonparametrically assess assumptions necessary + to prevent the surrogate paradox through hypothesis tests of stochastic dominance, + monotonicity of regression functions, and non-negative residual treatment effects. + More details are available in Hsiao et al 2025 (under review). A tutorial for + this package can be found at . + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateParadoxTest + url_git: '' +SurrogateRank: + version: '1.0' + title: Rank-Based Test to Evaluate a Surrogate Marker + maintainer: Layla Parast + description: Uses a novel rank-based nonparametric approach to evaluate a surrogate + marker in a small sample size setting. Details are described in Parast et al (2024) + . + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateRank + url_git: '' +SurrogateRegression: + version: 0.6.0.1 + title: Surrogate Outcome Regression Analysis + maintainer: Zachary McCaw + description: 'Performs estimation and inference on a partially missing target outcome + (e.g. gene expression in an inaccessible tissue) while borrowing information from + a correlated surrogate outcome (e.g. gene expression in an accessible tissue). + Rather than regarding the surrogate outcome as a proxy for the target outcome, + this package jointly models the target and surrogate outcomes within a bivariate + regression framework. Unobserved values of either outcome are treated as missing + data. In contrast to imputation-based inference, no assumptions are required regarding + the relationship between the target and surrogate outcomes. Estimation in the + presence of bilateral outcome missingness is performed via an expectation conditional + maximization either algorithm. In the case of unilateral target missingness, estimation + is performed using an accelerated least squares procedure. A flexible association + test is provided for evaluating hypotheses about the target regression parameters. + For additional details, see: McCaw ZR, Gaynor SM, Sun R, Lin X: "Leveraging a + surrogate outcome to improve inference on a partially missing target outcome" + .' + date_publication: '2023-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateRegression + url_git: '' +SurrogateRsq: + version: 0.2.1 + title: |- + Goodness-of-Fit Analysis for Categorical Data using the + Surrogate R-Squared + maintainer: Xiaorui (Jeremy) Zhu + description: |- + To assess and compare the models' goodness of fit, R-squared is one of the most + popular measures. For categorical data analysis, however, no universally adopted + R-squared measure can resemble the ordinary least square (OLS) R-squared for + linear models with continuous data. This package implement the surrogate R-squared + measure for categorical data analysis, which is proposed in the study of Dungang Liu, + Xiaorui Zhu, Brandon Greenwell, and Zewei Lin (2022) . It + can generate a point or interval measure of the surrogate R-squared. It can also + provide a ranking measure of the percentage contribution of each variable to the + overall surrogate R-squared. This ranking assessment allows one to check the + importance of each variable in terms of their explained variance. This package can + be jointly used with other existing R packages for variable selection and model + diagnostics in the model-building process. + date_publication: '2023-04-24' + bug_reports: https://github.com/XiaoruiZhu/SurrogateRsq/issues + url: https://xiaorui.site/SurrogateRsq/ + url_cran: https://CRAN.R-project.org/package=SurrogateRsq + url_git: '' +SurrogateSeq: + version: '1.0' + title: |- + Group Sequential Testing of a Treatment Effect Using a Surrogate + Marker + maintainer: Layla Parast + description: 'Provides functions to implement group sequential procedures that allow + for early stopping to declare efficacy using a surrogate marker and the possibility + of futility stopping. More details are available in: Parast, L. and Bartroff, + J (2024) . A tutorial for this package can be found + at .' + date_publication: '2025-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateSeq + url_git: '' +SurrogateTest: + version: '1.3' + title: |- + Early Testing for a Treatment Effect using Surrogate Marker + Information + maintainer: Layla Parast + description: 'Provides functions to test for a treatment effect in terms of the + difference in survival between a treatment group and a control group using surrogate + marker information obtained at some early time point in a time-to-event outcome + setting. Nonparametric kernel estimation is used to estimate the test statistic + and perturbation resampling is used for variance estimation. More details will + be available in the future in: Parast L, Cai T, Tian L (2019) ``Using a Surrogate + Marker for Early Testing of a Treatment Effect" Biometrics, 75(4):1253-1263. .' + date_publication: '2021-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurrogateTest + url_git: '' +surrosurv: + version: 1.1.26 + title: |- + Evaluation of Failure Time Surrogate Endpoints in Individual + Patient Data Meta-Analyses + maintainer: Dan Chaltiel + description: |- + Provides functions for the evaluation of + surrogate endpoints when both the surrogate and the true endpoint are failure + time variables. The approaches implemented are: + (1) the two-step approach (Burzykowski et al, 2001) with a copula model (Clayton, Plackett, Hougaard) at + the first step and either a linear regression of log-hazard ratios at the second + step (either adjusted or not for measurement error); + (2) mixed proportional hazard models estimated via mixed Poisson GLM + (Rotolo et al, 2017 ). + date_publication: '2023-04-14' + bug_reports: https://github.com/Oncostat/surrosurv/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=surrosurv + url_git: https://github.com/Oncostat/surrosurv +surrosurvROC: + version: 0.1.0 + title: Surrogate Survival ROC + maintainer: Yunro Chung + description: Nonparametric and semiparametric estimations of the time-dependent + ROC curve for an incomplete failure time data with surrogate failure time endpoints. + date_publication: '2018-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=surrosurvROC + url_git: '' +surtvep: + version: 1.0.0 + title: |- + Cox Non-Proportional Hazards Model with Time-Varying + Coefficients + maintainer: Lingfeng Luo + description: |- + Fit Cox non-proportional hazards models with time-varying coefficients. + Both unpenalized procedures (Newton and proximal Newton) and penalized procedures + (P-splines and smoothing splines) are included using B-spline basis functions for + estimating time-varying coefficients. For penalized procedures, cross validations, + mAIC, TIC or GIC are implemented to select tuning parameters. Utilities for + carrying out post-estimation visualization, summarization, point-wise confidence + interval and hypothesis testing are also provided. + For more information, see Wu et al. (2022) and + Luo et al. (2023) . + date_publication: '2023-10-17' + bug_reports: https://github.com/UM-KevinHe/surtvep/issues + url: https://um-kevinhe.github.io/surtvep/ + url_cran: https://CRAN.R-project.org/package=surtvep + url_git: https://github.com/UM-KevinHe/surtvep +surv2sampleComp: + version: 1.0-5 + title: |- + Inference for Model-Free Between-Group Parameters for Censored + Survival Data + maintainer: Miki Horiguchi + description: Performs inference of several model-free group contrast measures, which + include difference/ratio of cumulative incidence rates at given time points, quantiles, + and restricted mean survival times (RMST). Two kinds of covariate adjustment procedures + (i.e., regression and augmentation) for inference of the metrics based on RMST + are also included. + date_publication: '2017-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=surv2sampleComp + url_git: '' +survAH: + version: 1.0.0 + title: Survival Data Analysis using Average Hazard + maintainer: Miki Horiguchi + description: Performs two-sample comparisons based on average hazard with survival + weight (AHSW) or general censoring-free incidence rate (CFIR) proposed by Uno + and Horiguchi (2023) . + date_publication: '2023-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survAH + url_git: '' +survAUC: + version: 1.3-0 + title: Estimators of Prediction Accuracy for Time-to-Event Data + maintainer: Frederic Bertrand + description: |- + Provides a variety of functions to estimate + time-dependent true/false positive rates and AUC curves from a + set of censored survival data. + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survAUC + url_git: '' +survAWKMT2: + version: 1.0.1 + title: Two-Sample Tests Based on Differences of Kaplan-Meier Curves + maintainer: Miki Horiguchi + description: Tests for equality of two survival functions based on integrated weighted + differences of two Kaplan-Meier curves. + date_publication: '2022-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survAWKMT2 + url_git: '' +survBootOutliers: + version: '1.0' + title: |- + Concordance Based Bootstrap Methods for Outlier Detection in + Survival Analysis + maintainer: Joao Pinto + description: 'Three new methods to perform outlier detection in a survival context. + In total there are six methods provided, the first three methods are traditional + residual-based outlier detection methods, the second three are the concordance-based. + Package developed during the work on the two following publications: Pinto J., + Carvalho A. and Vinga S. (2015) ; Pinto J.D., Carvalho + A.M., Vinga S. (2015) .' + date_publication: '2018-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survBootOutliers + url_git: https://github.com/jonydog/survBootOutliers +survC1: + version: 1.0-3 + title: |- + C-Statistics for Risk Prediction Models with Censored Survival + Data + maintainer: Hajime Uno + description: Performs inference for C of risk prediction models with censored survival + data, using the method proposed by Uno et al. (2011) . Inference + for the difference in C between two competing prediction models is also implemented. + date_publication: '2021-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survC1 + url_git: '' +survcompare: + version: 0.2.0 + title: |- + Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival + Random Forests + maintainer: Diana Shamsutdinova + description: Performs repeated nested cross-validation for Cox Proportionate Hazards, + Cox Lasso, Survival Random Forest, and their ensemble. Returns internally validated + concordance index, time-dependent area under the curve, Brier score, calibration + slope, and statistical testing of non-linear ensemble outperforming the baseline + Cox model. In this, it helps researchers to quantify the gain of using a more + complex survival model, or justify its redundancy. Equally, it shows the performance + value of the non-linear and interaction terms, and may highlight the need of further + feature transformation. Further details can be found in Shamsutdinova, Stamate, + Roberts, & Stahl (2022) "Combining Cox Model and Tree-Based Algorithms to Boost + Performance and Preserve Interpretability for Health Outcomes" , + where the method is described as Ensemble 1. + date_publication: '2024-10-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survcompare + url_git: '' +SurvCorr: + version: '1.1' + title: Correlation of Bivariate Survival Times + maintainer: Georg Heinze + description: |- + Estimates correlation coefficients with associated + confidence limits for bivariate, partially censored survival times. Uses + the iterative multiple imputation approach proposed + by Schemper, Kaider, Wakounig and Heinze (2013) . Provides a scatterplot function to visualize the bivariate + distribution, either on the original time scale or as copula. + date_publication: '2022-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvCorr + url_git: '' +survCurve: + version: '1.0' + title: Plots Survival Curves Element by Element + maintainer: Melchior Burri + description: |- + Plots survival models from the 'survival' package. Additionally, it + plots curves of multistate models from the 'mstate' package. Typically, a + plot is drawn by the sequence survplot(), confIntArea(), survCurve() and + nrAtRisk(). The separation of the plot in this 4 functions allows for great + flexibility to make a custom plot for publication. + date_publication: '2020-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survCurve + url_git: '' +SurvDisc: + version: 0.1.1 + title: Discrete Time Survival and Longitudinal Data Analysis + maintainer: John Lawrence + description: |- + Various functions for discrete time survival analysis and longitudinal analysis. SIMEX method for correcting for bias for errors-in-variables + in a mixed effects model. Asymptotic mean and variance of different proportional hazards test statistics using different ties methods given two + survival curves and censoring distributions. Score test and Wald test for regression analysis of grouped survival data. Calculation of survival + curves for events defined by the response variable in a mixed effects model crossing a threshold with or without confirmation. + date_publication: '2018-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvDisc + url_git: '' +surveil: + version: 0.3.0 + title: Time Series Models for Disease Surveillance + maintainer: Connor Donegan + description: 'Fits time trend models for routine disease surveillance tasks and + returns probability distributions for a variety of quantities of interest, including + age-standardized rates, period and cumulative percent change, and measures of + health inequality. The models are appropriate for count data such as disease incidence + and mortality data, employing a Poisson or binomial likelihood and the first-difference + (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, + correlated time series models. Inference is completed using Markov chain Monte + Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) + ; Stan Development Team (2021) ; Theil + (1972, ISBN:0-444-10378-3).' + date_publication: '2024-07-08' + bug_reports: '' + url: https://connordonegan.github.io/surveil/ + url_cran: https://CRAN.R-project.org/package=surveil + url_git: https://github.com/ConnorDonegan/surveil/ +surveillance: + version: 1.24.1 + title: |- + Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic + Phenomena + maintainer: Sebastian Meyer + description: |- + Statistical methods for the modeling and monitoring of time series + of counts, proportions and categorical data, as well as for the modeling + of continuous-time point processes of epidemic phenomena. + The monitoring methods focus on aberration detection in count data time + series from public health surveillance of communicable diseases, but + applications could just as well originate from environmetrics, + reliability engineering, econometrics, or social sciences. The package + implements many typical outbreak detection procedures such as the + (improved) Farrington algorithm, or the negative binomial GLR-CUSUM + method of Hoehle and Paul (2008) . + A novel CUSUM approach combining logistic and multinomial logistic + modeling is also included. The package contains several real-world data + sets, the ability to simulate outbreak data, and to visualize the + results of the monitoring in a temporal, spatial or spatio-temporal + fashion. A recent overview of the available monitoring procedures is + given by Salmon et al. (2016) . + For the retrospective analysis of epidemic spread, the package provides + three endemic-epidemic modeling frameworks with tools for visualization, + likelihood inference, and simulation. hhh4() estimates models for + (multivariate) count time series following Paul and Held (2011) + and Meyer and Held (2014) . + twinSIR() models the susceptible-infectious-recovered (SIR) event + history of a fixed population, e.g, epidemics across farms or networks, + as a multivariate point process as proposed by Hoehle (2009) + . twinstim() estimates self-exciting point + process models for a spatio-temporal point pattern of infective events, + e.g., time-stamped geo-referenced surveillance data, as proposed by + Meyer et al. (2012) . + A recent overview of the implemented space-time modeling frameworks + for epidemic phenomena is given by Meyer et al. (2017) + . + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=surveillance + url_git: https://surveillance.R-Forge.R-project.org/ +survELtest: + version: 2.0.1 + title: Comparing Multiple Survival Functions with Crossing Hazards + maintainer: Guo-You Lan + description: Computing the one-sided/two-sided integrated/maximally selected EL + statistics for simultaneous testing, the one-sided/two-sided EL tests for pointwise + testing, and an initial test that precedes one-sided testing to exclude the possibility + of crossings or alternative orderings among the survival functions. + date_publication: '2020-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survELtest + url_git: https://github.com/news11/survELtest +SurvEval: + version: '1.1' + title: Methods for the Evaluation of Survival Models + maintainer: Sean Devlin + description: Provides predictive accuracy tools to evaluate time-to-event survival + models. This includes calculating the concordance probability estimate that incorporates + the follow-up time for a particular study developed by Devlin, Gonen, Heller (2020). + It also evaluates the concordance probability estimate for nested Cox proportional + hazards models using a projection-based approach by Heller and Devlin (under review). + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvEval + url_git: '' +survex: + version: 1.2.0 + title: Explainable Machine Learning in Survival Analysis + maintainer: Mikołaj Spytek + description: |- + Survival analysis models are commonly used in medicine and other areas. Many of them + are too complex to be interpreted by human. Exploration and explanation is needed, but + standard methods do not give a broad enough picture. 'survex' provides easy-to-apply + methods for explaining survival models, both complex black-boxes and simpler statistical models. + They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023) + , SurvLIME described in Kovalev et al., (2020) as well as + extensions of existing ones described in Biecek et al., (2021) . + date_publication: '2023-10-24' + bug_reports: https://github.com/ModelOriented/survex/issues + url: https://modeloriented.github.io/survex/ + url_cran: https://CRAN.R-project.org/package=survex + url_git: '' +survexp.fr: + version: '1.1' + title: Relative Survival, AER and SMR Based on French Death Rates + maintainer: Hugo Varet + description: It computes Relative survival, AER and SMR based on French death rates. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survexp.fr + url_git: '' +survey: + version: 4.4-2 + title: Analysis of Complex Survey Samples + maintainer: '"Thomas Lumley"' + description: Summary statistics, two-sample tests, rank tests, generalised linear + models, cumulative link models, Cox models, loglinear models, and general maximum + pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally + weighted survey samples. Variances by Taylor series linearisation or replicate + weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. + Graphics. PPS sampling without replacement. Small-area estimation. + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survey + url_git: http://r-survey.r-forge.r-project.org/survey/ +surveybootstrap: + version: 0.0.3 + title: Bootstrap with Survey Data + maintainer: Dennis M. Feehan + description: |- + Implements different kinds of bootstraps + to estimate sampling variation from survey data with + complex designs. Includes the rescaled bootstrap + described in Rust and Rao (1996) and + Rao and Wu (1988) . + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=surveybootstrap + url_git: '' +SurveyCC: + version: 0.2.1 + title: Canonical Correlation for Survey Data + maintainer: Raul Cruz-Cano + description: |- + Performs canonical correlation for survey data, including + multiple tests of significance for secondary canonical correlations. + A key feature of this package is that it incorporates survey data structure + directly in a novel test of significance via a sequence of simple linear + regression models on the canonical variates. See reference - Cruz-Cano, + Cohen, and Mead-Morse (2024) "Canonical Correlation Analysis of Survey data: the SurveyCC R package" + The R Journal under review. + date_publication: '2024-07-05' + bug_reports: https://github.com/237triangle/SurveyCC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SurveyCC + url_git: https://github.com/237triangle/SurveyCC +surveyCV: + version: 0.2.0 + title: Cross Validation Based on Survey Design + maintainer: Jerzy Wieczorek + description: |- + Functions to generate K-fold cross validation (CV) folds + and CV test error estimates that take into account + how a survey dataset's sampling design was constructed + (SRS, clustering, stratification, and/or unequal sampling weights). + You can input linear and logistic regression models, along with data and a + type of survey design in order to get an output that can help you determine + which model best fits the data using K-fold cross validation. + Our paper on "K-Fold Cross-Validation for Complex Sample Surveys" + by Wieczorek, Guerin, and McMahon (2022) + + explains why differing how we take folds based on survey design is useful. + date_publication: '2022-03-15' + bug_reports: https://github.com/ColbyStatSvyRsch/surveyCV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=surveyCV + url_git: https://github.com/ColbyStatSvyRsch/surveyCV/ +surveydata: + version: 0.2.7 + title: Tools to Work with Survey Data + maintainer: Andrie de Vries + description: |- + Data obtained from surveys contains information not only about the + survey responses, but also the survey metadata, e.g. the original survey + questions and the answer options. The 'surveydata' package makes it easy to + keep track of this metadata, and to easily extract columns with + specific questions. + date_publication: '2023-03-12' + bug_reports: https://github.com/andrie/surveydata/issues + url: https://andrie.github.io/surveydata/ + url_cran: https://CRAN.R-project.org/package=surveydata + url_git: https://github.com/andrie/surveydata +SurveyDefense: + version: 0.2.0 + title: Survey Defense Tool + maintainer: Philipp Brüggemann + description: This tool is designed to analyze up to 5 Fraud Detection Questions + integrated into a survey, focusing on potential fraudulent participants to clean + the survey dataset from potential fraud. Fraud Detection Questions and further + information available at . + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurveyDefense + url_git: '' +surveydown: + version: 0.8.0 + title: Markdown-Based Surveys Using 'Quarto' and 'shiny' + maintainer: John Paul Helveston + description: |- + Generate surveys using markdown and R code chunks. Surveys + are composed of two files: a survey.qmd 'Quarto' file defining the + survey content (pages, questions, etc), and an app.R file defining a + 'shiny' app with global settings (libraries, database configuration, + etc.) and server configuration options (e.g., conditional skipping / + display, etc.). Survey data collected from respondents is stored in a + 'PostgreSQL' database. Features include controls for conditional skip + logic (skip to a page based on an answer to a question), conditional + display logic (display a question based on an answer to a question), a + customizable progress bar, and a wide variety of question types, + including multiple choice (single choice and multiple choices), + select, text, numeric, multiple choice buttons, text area, and dates. + Because the surveys render into a 'shiny' app, designers can also + leverage the reactive capabilities of 'shiny' to create dynamic and + interactive surveys. + date_publication: '2025-01-27' + bug_reports: https://github.com/surveydown-dev/surveydown/issues + url: https://pkg.surveydown.org + url_cran: https://CRAN.R-project.org/package=surveydown + url_git: '' +surveyexplorer: + version: 0.2.0 + title: Quickly Explore Complex Survey Data + maintainer: Liam Haller + description: |- + Visualize and tabulate single-choice, multiple-choice, matrix-style questions from survey data. + Includes ability to group cross-tabulations, frequency distributions, and plots by categorical variables and + to integrate survey weights. Ideal for quickly uncovering descriptive patterns in survey data. + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=surveyexplorer + url_git: '' +surveygraph: + version: 0.1.2 + title: Network Representations of Attitudes + maintainer: Samuel Unicomb + description: |- + A tool for computing network representations of attitudes, + extracted from tabular data such as sociological surveys. Development of + surveygraph software and training materials was initially funded by the + European Union under the ERC Proof-of-concept programme (ERC, + Attitude-Maps-4-All, project number: 101069264). Views and opinions expressed + are however those of the author(s) only and do not necessarily reflect those + of the European Union or the European Research Council Executive Agency. + Neither the European Union nor the granting authority can be held responsible + for them. + date_publication: '2024-06-04' + bug_reports: https://github.com/surveygraph/surveygraphr/issues + url: https://surveygraph.ie/ + url_cran: https://CRAN.R-project.org/package=surveygraph + url_git: '' +surveynnet: + version: 1.0.0 + title: Neural Network for Complex Survey Data + maintainer: Aaron Cohen + description: |- + The goal of 'surveynnet' is to extend the functionality of 'nnet', + which already supports survey weights, by enabling it to handle clustered + and stratified data. It achieves this by incorporating design effects + through the use of effective sample sizes as outlined by Chen + and Rust (2017), , and performed by + 'deffCR' in the package 'PracTools' (Valliant, Dever, and Kreuter (2018), + ). + date_publication: '2024-12-09' + bug_reports: https://github.com/237triangle/surveynnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=surveynnet + url_git: https://github.com/237triangle/surveynnet +surveyplanning: + version: '4.0' + title: Survey Planning Tools + maintainer: Juris Breidaks + description: Tools for sample survey planning, including sample size calculation, + estimation of expected precision for the estimates of totals, and calculation + of optimal sample size allocation. + date_publication: '2020-05-20' + bug_reports: https://github.com/CSBLatvia/surveyplanning/issues/ + url: https://csblatvia.github.io/surveyplanning/ + url_cran: https://CRAN.R-project.org/package=surveyplanning + url_git: '' +surveyPrev: + version: 1.0.0 + title: |- + Mapping the Prevalence of Binary Indicators using Survey Data in + Small Areas + maintainer: Qianyu Dong + description: Provides a pipeline to perform small area estimation and prevalence + mapping of binary indicators using health and demographic survey data, described + in Fuglstad et al. (2022) and Wakefield et al. + (2020) . + date_publication: '2024-04-10' + bug_reports: https://github.com/richardli/surveyPrev/issues + url: '' + url_cran: https://CRAN.R-project.org/package=surveyPrev + url_git: https://github.com/richardli/surveyPrev +surveysd: + version: 1.3.1 + title: |- + Survey Standard Error Estimation for Cumulated Estimates and + their Differences in Complex Panel Designs + maintainer: Johannes Gussenbauer + description: Calculate point estimates and their standard errors in complex household + surveys using bootstrap replicates. Bootstrapping considers survey design with + a rotating panel. A comprehensive description of the methodology can be found + under . + date_publication: '2022-12-19' + bug_reports: https://github.com/statistikat/surveysd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=surveysd + url_git: https://github.com/statistikat/surveysd +surveytable: + version: 0.9.5 + title: Formatted Survey Estimates + maintainer: Alex Strashny + description: |- + Short and understandable commands that generate tabulated, + formatted, and rounded survey estimates. Mostly a wrapper for the + 'survey' package (Lumley (2004) + ) that identifies + low-precision estimates using the National Center for Health + Statistics (NCHS) presentation standards (Parker et al. (2017) + , + Parker et al. (2023) ). + date_publication: '2024-10-09' + bug_reports: '' + url: https://cdcgov.github.io/surveytable/ + url_cran: https://CRAN.R-project.org/package=surveytable + url_git: https://github.com/CDCgov/surveytable +surveyvoi: + version: 1.0.6 + title: Survey Value of Information + maintainer: Jeffrey O Hanson + description: |- + Decision support tool for prioritizing sites for ecological + surveys based on their potential to improve plans for conserving + biodiversity (e.g. plans for establishing protected areas). Given a set of + sites that could potentially be acquired for conservation management, + it can be used to generate and evaluate plans for surveying additional + sites. Specifically, plans for ecological surveys can be + generated using various conventional approaches (e.g. maximizing expected + species richness, geographic coverage, diversity of sampled environmental + algorithms. After generating such survey plans, they can be evaluated using + conditions) and maximizing value of information. Please note that several + functions depend on the 'Gurobi' optimization software (available from + ). Additionally, the 'JAGS' software (available from + ) is required to fit hierarchical + generalized linear models. For further details, see Hanson et al. (2022) . + date_publication: '2024-02-16' + bug_reports: https://github.com/prioritizr/surveyvoi/issues + url: https://prioritizr.github.io/surveyvoi/ + url_cran: https://CRAN.R-project.org/package=surveyvoi + url_git: '' +survHE: + version: 2.0.2 + title: Survival Analysis in Health Economic Evaluation + maintainer: Gianluca Baio + description: |- + Contains a suite of functions for survival analysis in health economics. + These can be used to run survival models under a frequentist (based on maximum likelihood) + or a Bayesian approach (both based on Integrated Nested Laplace Approximation or Hamiltonian + Monte Carlo). To run the Bayesian models, the user needs to install additional modules + (packages), i.e. 'survHEinla' and 'survHEhmc'. These can be installed using + 'remotes::install_github' from their GitHub repositories: + ( and + respectively). 'survHEinla' is based on the package INLA, which is available for download at + . The user can specify a set of parametric models + using a common notation and select the preferred mode of inference. The results can also be + post-processed to produce probabilistic sensitivity analysis and can be used to export the + output to an Excel file (e.g. for a Markov model, as often done by modellers and + practitioners). . + date_publication: '2024-10-04' + bug_reports: https://github.com/giabaio/survHE/issues + url: https://gianluca.statistica.it/software/survhe/ + url_cran: https://CRAN.R-project.org/package=survHE + url_git: https://github.com/giabaio/survHE +SurvHiDim: + version: 0.1.1 + title: High Dimensional Survival Data Analysis + maintainer: Atanu Bhattacharjee + description: |- + High dimensional time to events data analysis with variable selection technique. + Currently support LASSO, clustering and Bonferroni's correction. + date_publication: '2021-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvHiDim + url_git: '' +survIDINRI: + version: 1.1-2 + title: |- + IDI and NRI for Comparing Competing Risk Prediction Models with + Censored Survival Data + maintainer: Hajime Uno + description: Performs inference for a class of measures to compare competing risk + prediction models with censored survival data. The class includes the integrated + discrimination improvement index (IDI) and category-less net reclassification + index (NRI). + date_publication: '2022-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survIDINRI + url_git: '' +survidm: + version: 1.3.2 + title: Inference and Prediction in an Illness-Death Model + maintainer: Marta Sestelo + description: |- + Newly developed methods for the estimation of several probabilities + in an illness-death model. The package can be used to obtain nonparametric and + semiparametric estimates for: transition probabilities, occupation probabilities, + cumulative incidence function and the sojourn time distributions. + Additionally, it is possible to fit proportional hazards regression models + in each transition of the Illness-Death Model. Several auxiliary + functions are also provided which can be used for marginal + estimation of the survival functions. + date_publication: '2021-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survidm + url_git: '' +SurviMChd: + version: 0.1.2 + title: |- + High Dimensional Survival Data Analysis with Markov Chain Monte + Carlo + maintainer: Atanu Bhattacharjee + description: |- + High dimensional survival data analysis with Markov Chain Monte Carlo(MCMC). + Currently supports frailty data analysis. Allows for Weibull and + Exponential distribution. Includes function for interval censored data. + date_publication: '2024-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurviMChd + url_git: '' +SurvImpute: + version: 0.1.0 + title: Multiple Imputation for Missing Covariates in Time-to-Event Data + maintainer: Qinghua Lian + description: Generates multiple imputed datasets from a substantive model compatible + fully conditional specification model for time-to-event data. Our method assumes + that the censoring process also depends on the covariates with missing values. + Details will be available in an upcoming publication. + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvImpute + url_git: '' +survival: + version: 3.8-3 + title: Survival Analysis + maintainer: Terry M Therneau + description: |- + Contains the core survival analysis routines, including + definition of Surv objects, + Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, + and parametric accelerated failure time models. + date_publication: '2024-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survival + url_git: https://github.com/therneau/survival +survival.svb: + version: 0.0-2 + title: Fit High-Dimensional Proportional Hazards Models + maintainer: Michael Komodromos + description: |- + Implementation of methodology designed to perform: (i) variable + selection, (ii) effect estimation, and (iii) uncertainty quantification, + for high-dimensional survival data. Our method uses a spike-and-slab prior + with Laplace slab and Dirac spike and approximates the corresponding + posterior using variational inference, a popular method in machine learning + for scalable conditional inference. Although approximate, the variational + posterior provides excellent point estimates and good control of the false + discovery rate. For more information see Komodromos et al. (2021) + . + date_publication: '2022-01-17' + bug_reports: https://github.com/mkomod/survival.svb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survival.svb + url_git: https://github.com/mkomod/survival.svb +survivalAnalysis: + version: 0.3.0 + title: High-Level Interface for Survival Analysis and Associated Plots + maintainer: Marcel Wiesweg + description: |- + A high-level interface to perform survival analysis, + including Kaplan-Meier analysis and log-rank tests and Cox regression. + Aims at providing a clear and elegant syntax, support for use in a pipeline, structured output and plotting. + Builds upon the 'survminer' package for Kaplan-Meier plots and provides + a customizable implementation for forest plots. + Kaplan & Meier (1958) + Cox (1972) + Peto & Peto (1972) . + date_publication: '2022-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survivalAnalysis + url_git: '' +SurvivalClusteringTree: + version: 1.1.1 + title: Clustering Analysis Using Survival Tree and Forest Algorithms + maintainer: Lu You + description: An outcome-guided algorithm is developed to identify clusters of samples + with similar characteristics and survival rate. The algorithm first builds a random + forest and then defines distances between samples based on the fitted random forest. + Given the distances, we can apply hierarchical clustering algorithms to define + clusters. Details about this method is described in . + date_publication: '2024-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvivalClusteringTree + url_git: '' +survivalmodels: + version: 0.1.191 + title: Models for Survival Analysis + maintainer: Yohann Foucher + description: Implementations of classical and machine learning models for survival + analysis, including deep neural networks via 'keras' and 'tensorflow'. Each model + includes a separated fit and predict interface with consistent prediction types + for predicting risk or survival probabilities. Models are either implemented from + 'Python' via 'reticulate' , from + code in GitHub packages, or novel implementations using 'Rcpp' . + Neural networks are implemented from the 'Python' package 'pycox' . + date_publication: '2024-03-19' + bug_reports: https://github.com/foucher-y/survivalmodels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survivalmodels + url_git: https://github.com/RaphaelS1/survivalmodels/ +survivalMPL: + version: 0.2-3 + title: Penalised Maximum Likelihood for Survival Analysis Models + maintainer: Dominique-Laurent Couturier + description: |- + Estimate the regression coefficients and the baseline hazard + of proportional hazard Cox models with left, right or interval censored survival data + using maximum penalised likelihood. A 'non-parametric' smooth estimate of the baseline hazard + function is provided. + date_publication: '2022-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survivalMPL + url_git: '' +survivalMPLdc: + version: 0.1.1 + title: |- + Penalised Likelihood for Survival Analysis with Dependent + Censoring + maintainer: Jing Xu + description: Fitting Cox proportional hazard model under dependent right censoring + using copula and maximum penalised likelihood methods. + date_publication: '2020-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survivalMPLdc + url_git: '' +survivalPLANN: + version: '0.1' + title: Neural Networks to Predict Survival + maintainer: Yohann Foucher + description: Several functions and S3 methods to predict survival by using neural + networks. We implemented Partial Logistic Artificial Neural Networks (PLANN) as + proposed by Biganzoli et al. (1998) . + date_publication: '2024-08-20' + bug_reports: https://github.com/chupverse/survivalPLANN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survivalPLANN + url_git: '' +survivalREC: + version: '1.1' + title: |- + Nonparametric Estimation of the Distribution of Gap Times for + Recurrent Events + maintainer: Gustavo Soutinho + description: |- + Provides estimates for the bivariate and trivariate distribution + functions and bivariate and trivariate survival functions for + censored gap times. Two approaches, using existing methodologies, + are considered: (i) the Lin's estimator, which is based on the + extension the Kaplan-Meier estimator of the distribution function + for the first event time and the Inverse Probability of Censoring + Weights for the second time (Lin DY, Sun W, Ying Z (1999) + and (ii) another estimator + based on Kaplan-Meier weights (Una-Alvarez J, Meira-Machado L (2008) + ). + The proposed methods are the landmark estimators based on + subsampling approach, and the estimator based on weighted cumulative + hazard estimator. The package also provides nonparametric estimator + conditional to a given continuous covariate. All these methods have + been submitted to be published. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survivalREC + url_git: '' +survivalROC: + version: 1.0.3.1 + title: Time-Dependent ROC Curve Estimation from Censored Survival Data + maintainer: Paramita Saha-Chaudhuri + description: |- + Compute time-dependent ROC curve from censored survival + data using Kaplan-Meier (KM) or Nearest Neighbor Estimation + (NNE) method of Heagerty, Lumley & Pepe (Biometrics, Vol 56 No + 2, 2000, PP 337-344). + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survivalROC + url_git: '' +survivalSL: + version: 0.97.1 + title: Super Learner for Survival Prediction from Censored Data + maintainer: Yohann Foucher + description: Several functions and S3 methods to construct a super learner in the + presence of censored times-to-event and to evaluate its prognostic capacities. + date_publication: '2025-02-17' + bug_reports: https://github.com/foucher-y/survivalSL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survivalSL + url_git: '' +survivalsvm: + version: 0.0.5 + title: Survival Support Vector Analysis + maintainer: Cesaire Fouodo + description: |- + Performs support vectors analysis for data sets with survival + outcome. Three approaches are available in the package: The regression approach + takes censoring into account when formulating the inequality constraints of + the support vector problem. In the ranking approach, the inequality constraints + set the objective to maximize the concordance index for comparable pairs + of observations. The hybrid approach combines the regression and ranking + constraints in the same model. + date_publication: '2018-02-05' + bug_reports: https://github.com/imbs-hl/survivalsvm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survivalsvm + url_git: https://github.com/imbs-hl/survivalsvm +SurvivalTests: + version: '1.0' + title: Survival Tests for One-Way Layout + maintainer: Osman Dag + description: Performs survival analysis for one-way layout. The package includes + the generalized test for survival ANOVA (Tsui and Weerahandi (1989) + and (Weerahandi, 2004; ISBN:978-0471470175)). It also performs pairwise comparisons + and graphical approaches. Moreover, it assesses the weibullness of data in each + group via test. The package computes mean and confidence interval under Weibull + distribution. + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvivalTests + url_git: '' +survivalVignettes: + version: 0.1.6 + title: Survival Analysis Vignettes and Optional Datasets + maintainer: Elizabeth Atkinson + description: |- + Vignettes for the 'survival' package. Split from the 'survival' + package since the vignettes were getting large. Also, since 'survival' is a + recommended package it cannot make use of other packages outside of + base+recommended (e.g. 'rmarkdown'). + date_publication: '2024-05-03' + bug_reports: https://github.com/bethatkinson/survivalVignettes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survivalVignettes + url_git: https://github.com/bethatkinson/survivalVignettes +survivoR: + version: 2.3.5 + title: Data from all Seasons of Survivor (US) TV Series in Tidy Format + maintainer: Daniel Oehm + description: |- + Datasets detailing the results, castaways, and events of each + season of Survivor for the US, Australia, South Africa, New Zealand, and the + UK. This includes details on the cast, voting history, immunity and reward + challenges, jury votes, boot order, advantage details, and episode ratings. + Use this for analysis of trends and statistics of the game. + date_publication: '2025-01-09' + bug_reports: https://github.com/doehm/survivoR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survivoR + url_git: https://github.com/doehm/survivoR +SurvLong: + version: '1.4' + title: |- + Analysis of Proportional Hazards Model with Sparse Longitudinal + Covariates + maintainer: Shannon T. Holloway + description: |- + Provides kernel weighting methods for estimation of proportional + hazards models with intermittently observed longitudinal covariates. + Cao H., Churpek M. M., Zeng D., and Fine J. P. (2015) + . + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvLong + url_git: '' +SurvMA: + version: 1.6.8 + title: |- + Model Averaging Prediction of Personalized Survival + Probabilities + maintainer: Mengyu Li + description: 'Provide model averaging-based approaches that can be used to predict + personalized survival probabilities. The key underlying idea is to approximate + the conditional survival function using a weighted average of multiple candidate + models. Two scenarios of candidate models are allowed: (Scenario 1) partial linear + Cox model and (Scenario 2) time-varying coefficient Cox model. A reference of + the underlying methods is Li and Wang (2023) .' + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvMA + url_git: +SurvMetrics: + version: 0.5.1 + title: Predictive Evaluation Metrics in Survival Analysis + maintainer: Hong Wang + description: |- + An implementation of popular evaluation metrics that are commonly used in survival prediction including Concordance Index, Brier Score, Integrated Brier Score, + Integrated Square Error, Integrated Absolute Error and Mean Absolute Error. + For a detailed information, see (Ishwaran H, Kogalur UB, Blackstone EH and Lauer MS (2008) ) , + (Moradian H, Larocque D and Bellavance F (2017) ), (Hanpu Zhou, Hong Wang, Sizheng Wang and Yi Zou (2023) ) for different evaluation metrics. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvMetrics + url_git: https://github.com/whcsu/SurvMetrics +SurvMI: + version: 0.1.0 + title: Multiple Imputation Method in Survival Analysis + maintainer: Yiming Chen + description: In clinical trials, endpoints are sometimes evaluated with uncertainty. + Adjudication is commonly adopted to ensure the study integrity. We propose to + use multiple imputation (MI) introduced by Robin (1987) + to incorporate these uncertainties if reasonable event probabilities were provided. + The method has been applied to Cox Proportional Hazard (PH) model, Kaplan-Meier + (KM) estimation and Log-rank test in this package. Moreover, weighted estimations + discussed in Cook (2004) were also implemented + with weights calculated from event probabilities. In conclusion, this package + can handle time-to-event analysis if events presented with uncertainty by different + methods. + date_publication: '2020-07-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvMI + url_git: '' +survminer: + version: 0.5.0 + title: Drawing Survival Curves using 'ggplot2' + maintainer: Alboukadel Kassambara + description: |- + Contains the function 'ggsurvplot()' for drawing easily beautiful + and 'ready-to-publish' survival curves with the 'number at risk' table + and 'censoring count plot'. Other functions are also available to plot + adjusted curves for `Cox` model and to visually examine 'Cox' model assumptions. + date_publication: '2024-10-30' + bug_reports: https://github.com/kassambara/survminer/issues + url: https://rpkgs.datanovia.com/survminer/index.html + url_cran: https://CRAN.R-project.org/package=survminer + url_git: '' +survMisc: + version: 0.5.6 + title: Miscellaneous Functions for Survival Data + maintainer: Chris Dardis + description: |- + A collection of functions to help in the analysis of + right-censored survival data. These extend the methods available in + package:survival. + date_publication: '2022-04-07' + bug_reports: https://github.com/dardisco/survMisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survMisc + url_git: '' +survmixer: + version: '1.3' + title: |- + Design of Clinical Trials with Survival Endpoints Based on + Binary Responses + maintainer: Marta Bofill Roig + description: Sample size and effect size calculations for survival endpoints based + on mixture survival-by-response model. The methods implemented can be found in Bofill, + Shen & Gómez (2021) . + date_publication: '2021-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survmixer + url_git: '' +survML: + version: 1.2.0 + title: Tools for Flexible Survival Analysis Using Machine Learning + maintainer: Charles Wolock + description: |- + Statistical tools for analyzing time-to-event data using + machine learning. Implements survival stacking for conditional + survival estimation, standardized survival function estimation for + current status data, and methods for algorithm-agnostic variable + importance. See Wolock CJ, Gilbert PB, Simon N, + and Carone M (2024) . + date_publication: '2024-10-31' + bug_reports: https://github.com/cwolock/survML/issues + url: https://cwolock.github.io/survML/ + url_cran: https://CRAN.R-project.org/package=survML + url_git: https://github.com/cwolock/survML +survNMA: + version: 1.1-1 + title: Network Meta-Analysis Combining Survival and Count Outcomes + maintainer: Hisashi Noma + description: Network meta-analysis for survival outcome data often involves several + studies only involve dichotomized outcomes (e.g., the numbers of event and sample + sizes of individual arms). To combine these different outcome data, Woods et + al. (2010) proposed a Bayesian approach using complicated + hierarchical models. Besides, frequentist approaches have been alternative standard + methods for the statistical analyses of network meta-analysis, and the methodology + has been well established. We proposed an easy-to-implement method for the network + meta-analysis based on the frequentist framework in Noma and Maruo (2025) . + This package involves some convenient functions to implement the simple synthesis + method. + date_publication: '2025-01-31' + bug_reports: '' + url: https://doi.org/10.1101/2025.01.23.25321051 + url_cran: https://CRAN.R-project.org/package=survNMA + url_git: '' +survobj: + version: 3.1.1 + title: Objects to Simulate Survival Times + maintainer: Aponte John + description: Generate objects that simulate survival times. Random values for the + distributions are generated using the method described by Bender (2003) + and Leemis (1987) in Operations Research, 35(6), 892–894. + date_publication: '2024-08-16' + bug_reports: https://github.com/johnaponte/survobj/issues + url: https://johnaponte.github.io/survobj/ + url_cran: https://CRAN.R-project.org/package=survobj + url_git: https://github.com/johnaponte/survobj +survout: + version: 0.1.0 + title: Excel Conversion of R Surival Analysis Output + maintainer: Xuefei Jia + description: |- + Simple and quick method of exporting the most often used + survival analysis results to an Excel sheet. + date_publication: '2022-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survout + url_git: '' +survParamSim: + version: 0.1.6 + title: Parametric Survival Simulation with Parameter Uncertainty + maintainer: Kenta Yoshida + description: |- + Perform survival simulation with parametric survival model generated from 'survreg' function in 'survival' package. + In each simulation coefficients are resampled from variance-covariance matrix of parameter estimates to + capture uncertainty in model parameters. + Prediction intervals of Kaplan-Meier estimates and hazard ratio of treatment effect can be further calculated using simulated survival data. + date_publication: '2022-06-03' + bug_reports: https://github.com/yoshidk6/survParamSim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survParamSim + url_git: https://github.com/yoshidk6/survParamSim +survPen: + version: 2.0.1 + title: |- + Multidimensional Penalized Splines for (Excess) Hazard Models, + Relative Mortality Ratio Models and Marginal Intensity Models + maintainer: Mathieu Fauvernier + description: |- + Fits (excess) hazard, relative mortality ratio or marginal intensity models with multidimensional penalized splines allowing for + time-dependent effects, non-linear effects and interactions between several continuous covariates. In survival and net survival analysis, in addition to modelling the effect of time (via the baseline hazard), one has often to deal with several continuous covariates and model their functional forms, their time-dependent effects, and their interactions. Model specification becomes therefore a complex problem and penalized regression splines represent an appealing solution to that problem as splines offer the required flexibility while penalization limits overfitting issues. Current implementations of penalized survival models can be slow or unstable and sometimes lack some key features like taking into account expected mortality to provide net survival and excess hazard estimates. In contrast, survPen provides an automated, fast, and stable implementation (thanks to explicit calculation of the derivatives of the likelihood) and offers a unified framework for + multidimensional penalized hazard and excess hazard models. Later versions (>2.0.0) include penalized models for relative mortality ratio, and marginal intensity in recurrent event setting. + survPen may be of interest to those who 1) analyse any kind of time-to-event data: mortality, disease relapse, machinery breakdown, unemployment, etc 2) wish to describe the associated hazard and to understand which predictors impact its dynamics, + 3) wish to model the relative mortality ratio between a cohort and a reference population, 4) wish to describe the marginal intensity for recurrent event data. + See Fauvernier et al. (2019a) for an overview of the package and Fauvernier et al. (2019b) for the method. + date_publication: '2025-01-21' + bug_reports: https://github.com/fauvernierma/survPen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=survPen + url_git: https://github.com/fauvernierma/survPen +survPresmooth: + version: 1.1-12 + title: Presmoothed Estimation in Survival Analysis + maintainer: Ignacio Lopez de Ullibarri + description: Presmoothed estimators of survival, density, cumulative and non-cumulative + hazard functions with right-censored survival data. For details, see Lopez-de-Ullibarri + and Jacome (2013) . + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survPresmooth + url_git: '' +SurvRegCensCov: + version: '1.7' + title: |- + Weibull Regression for a Right-Censored Endpoint with + Interval-Censored Covariate + maintainer: Stanislas Hubeaux + description: The function SurvRegCens() of this package allows estimation of a Weibull + Regression for a right-censored endpoint, one interval-censored covariate, and + an arbitrary number of non-censored covariates. Additional functions allow to + switch between different parametrizations of Weibull regression used by different + R functions, inference for the mean difference of two arbitrarily censored Normal + samples, and estimation of canonical parameters from censored samples for several + distributional assumptions. Hubeaux, S. and Rufibach, K. (2014) . + date_publication: '2023-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvRegCensCov + url_git: '' +survRM2: + version: 1.0-4 + title: Comparing Restricted Mean Survival Time + maintainer: Hajime Uno + description: Performs two-sample comparisons using the restricted mean survival + time (RMST) as a summary measure of the survival time distribution. Three kinds + of between-group contrast metrics (i.e., the difference in RMST, the ratio of + RMST and the ratio of the restricted mean time lost (RMTL)) are computed. It performs + an ANCOVA-type covariate adjustment as well as unadjusted analyses for those measures. + date_publication: '2022-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survRM2 + url_git: '' +survRM2adapt: + version: 1.1.0 + title: |- + Flexible and Coherent Test/Estimation Procedure Based on + Restricted Mean Survival Times + maintainer: Miki Horiguchi + description: Estimates the restricted mean survival time (RMST) with the time window + [0, tau], where tau is adaptively selected from the procedure, proposed by Horiguchi + et al. (2018) . It also estimates the RMST with the time + window [tau1, tau2], where tau1 is adaptively selected from the procedure, proposed + by Horiguchi et al. (2023) . + date_publication: '2023-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survRM2adapt + url_git: '' +survRM2perm: + version: 0.1.0 + title: Permutation Test for Comparing Restricted Mean Survival Time + maintainer: Miki Horiguchi + description: Performs the permutation test using difference in the restricted mean + survival time (RMST) between groups as a summary measure of the survival time + distribution. When the sample size is less than 50 per group, it has been shown + that there is non-negligible inflation of the type I error rate in the commonly + used asymptotic test for the RMST comparison. Generally, permutation tests can + be useful in such a situation. However, when we apply the permutation test for + the RMST comparison, particularly in small sample situations, there are some cases + where the survival function in either group cannot be defined due to censoring + in the permutation process. Horiguchi and Uno (2020) have + examined six workable solutions to handle this numerical issue. It performs permutation + tests with implementation of the six methods outlined in the paper when the numerical + issue arises during the permutation process. The result of the asymptotic test + is also provided for a reference. + date_publication: '2020-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survRM2perm + url_git: '' +survSAKK: + version: 1.3.1 + title: Create Publication Ready Kaplan-Meier Plots + maintainer: Katrin Gysel + description: Incorporate various statistics and layout customization options to + enhance the efficiency and adaptability of the Kaplan-Meier plots. + date_publication: '2024-09-11' + bug_reports: https://github.com/SAKK-Statistics/survSAKK/issues + url: https://sakk-statistics.github.io/survSAKK/ + url_cran: https://CRAN.R-project.org/package=survSAKK + url_git: '' +survSens: + version: 1.1.0 + title: Sensitivity Analysis with Time-to-Event Outcomes + maintainer: Rong Huang + description: Performs a dual-parameter sensitivity analysis of treatment effect + to unmeasured confounding in observational studies with either survival or competing + risks outcomes. Huang, R., Xu, R. and Dulai, P.S.(2020) . + date_publication: '2023-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survSens + url_git: https://github.com/Rong0707/survSens +survsim: + version: 1.1.8 + title: Simulation of Simple and Complex Survival Data + maintainer: David Moriña Soler + description: Simulation of simple and complex survival data including recurrent + and multiple events and competing risks. See Moriña D, Navarro A. (2014) + and Moriña D, Navarro A. (2017) . + date_publication: '2021-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survsim + url_git: '' +survSNP: + version: '0.26' + title: Power Calculations for SNP Studies with Censored Outcomes + maintainer: Alexander Sibley + description: Conduct asymptotic and empirical power and sample size calculations + for Single-Nucleotide Polymorphism (SNP) association studies with right censored + time to event outcomes. + date_publication: '2023-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survSNP + url_git: '' +SurvSparse: + version: '0.1' + title: Survival Analysis with Sparse Longitudinal Covariates + maintainer: Zhuowei Sun + description: 'Survival analysis with sparse longitudinal covariates under right + censoring scheme. Different hazards models are involved. Please cite the manuscripts + corresponding to this package: Sun, Z. et al. (2022) , + Sun, Z. and Cao, H. (2023) and Sun, D. et al. (2023) .' + date_publication: '2023-10-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvSparse + url_git: '' +survSpearman: + version: 1.0.1 + title: Nonparametric Spearman's Correlation for Survival Data + maintainer: Svetlana Eden + description: Nonparametric estimation of Spearman's rank correlation with bivariate + survival (right-censored) data as described in Eden, S.K., Li, C., Shepherd B.E. + (2021), Nonparametric Estimation of Spearman's Rank Correlation with Bivariate + Survival Data, Biometrics (under revision). The package also provides functions + that visualize bivariate survival data and bivariate probability mass function. + date_publication: '2022-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=survSpearman + url_git: '' +survstan: + version: 0.0.7.1 + title: Fitting Survival Regression Models via 'Stan' + maintainer: Fabio Demarqui + description: 'Parametric survival regression models under the maximum likelihood + approach via ''Stan''. Implemented regression models include accelerated failure + time models, proportional hazards models, proportional odds models, accelerated + hazard models, Yang and Prentice models, and extended hazard models. Available + baseline survival distributions include exponential, Weibull, log-normal, log-logistic, + gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. + References: Lawless (2002) ; Bennett (1982) ; + Chen and Wang(2000) ; Demarqui and Mayrink + (2021) .' + date_publication: '2024-04-12' + bug_reports: https://github.com/fndemarqui/survstan/issues + url: https://fndemarqui.github.io/survstan/ + url_cran: https://CRAN.R-project.org/package=survstan + url_git: https://github.com/fndemarqui/survstan +SurvTrunc: + version: 0.2.0 + title: Analysis of Doubly Truncated Data + maintainer: Lior Rennert + description: 'Package performs Cox regression and survival distribution function + estimation when the survival times are subject to double truncation. In case that + the survival and truncation times are quasi-independent, the estimation procedure + for each method involves inverse probability weighting, where the weights correspond + to the inverse of the selection probabilities and are estimated using the survival + times and truncation times only. A test for checking this independence assumption + is also included in this package. The functions available in this package for + Cox regression, survival distribution function estimation, and testing independence + under double truncation are based on the following methods, respectively: Rennert + and Xie (2018) , Shen (2010) , + Martin and Betensky (2005) . When the survival + times are dependent on at least one of the truncation times, an EM algorithm is + employed to obtain point estimates for the regression coefficients. The standard + errors are calculated using the bootstrap method. See Rennert and Xie (2022) . + Both the independent and dependent cases assume no censoring is present in the + data. Please contact Lior Rennert for questions regarding + function coxDT and Yidan Shi for questions + regarding function coxDTdep.' + date_publication: '2022-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SurvTrunc + url_git: '' +SUSENAS: + version: 0.1.0 + title: National Socio-Economic Survey Data Collection Indonesia + maintainer: Fadhlul Mubarak + description: 'Survey to collect data about the social and economic conditions of + Indonesian society. This activity aims to include: As a data source for planning + and evaluating national, sectoral development programs, and providing indicators + for Sustainable Development Goals (TPB), National Medium Term Development Plan + (RPJMN), and Nawacita, GDP/GRDP and annual Integrated Institutional Balance Sheet.' + date_publication: '2024-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SUSENAS + url_git: '' +susieR: + version: 0.12.35 + title: Sum of Single Effects Linear Regression + maintainer: Peter Carbonetto + description: |- + Implements methods for variable selection in linear + regression based on the "Sum of Single Effects" (SuSiE) model, as + described in Wang et al (2020) and Zou et al + (2021) . These methods provide + simple summaries, called "Credible Sets", for accurately + quantifying uncertainty in which variables should be selected. + The methods are motivated by genetic fine-mapping applications, + and are particularly well-suited to settings where variables are + highly correlated and detectable effects are sparse. The fitting + algorithm, a Bayesian analogue of stepwise selection methods + called "Iterative Bayesian Stepwise Selection" (IBSS), is simple + and fast, allowing the SuSiE model be fit to large data sets + (thousands of samples and hundreds of thousands of variables). + date_publication: '2023-02-17' + bug_reports: https://github.com/stephenslab/susieR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=susieR + url_git: https://github.com/stephenslab/susieR +susographql: + version: 0.1.6 + title: Comprehensive Interface to the Survey Solutions 'GraphQL' API + maintainer: Michael Wild + description: |- + Provides a complete suite of tools for interacting + with the Survey Solutions 'GraphQL' API + . This package encompasses + all currently available queries and mutations, including the latest + features for map uploads. It is built on the modern 'httr2' package, + offering a streamlined and efficient interface without relying on + external 'GraphQL' client packages. In addition to core API + functionalities, the package includes a range of helper functions + designed to facilitate the use of available query filters. + date_publication: '2024-01-17' + bug_reports: https://github.com/michael-cw/susographql/issues + url: https://michael-cw.github.io/susographql/ + url_cran: https://CRAN.R-project.org/package=susographql + url_git: '' +SUSY: + version: 0.1.0 + title: Surrogate Synchrony + maintainer: Wolfgang Tschacher + description: Computes synchrony as windowed cross-correlation based on two-dimensional + time series in a text file you can upload. 'SUSY' works as described in Tschacher + & Meier (2020) . + date_publication: '2022-11-24' + bug_reports: https://github.com/wtschacher/SUSY/issues + url: https://wtschacher.github.io/SUSY/ + url_cran: https://CRAN.R-project.org/package=SUSY + url_git: '' +sValues: + version: 0.1.6 + title: Measures of the Sturdiness of Regression Coefficients + maintainer: Carlos Cinelli + description: |- + Implements the s-values proposed by Ed. Leamer. + It provides a context-minimal approach for sensitivity analysis using extreme + bounds to assess the sturdiness of regression coefficients. + date_publication: '2018-07-15' + bug_reports: https://github.com/carloscinelli/sValues + url: '' + url_cran: https://CRAN.R-project.org/package=sValues + url_git: '' +svars: + version: 1.3.11 + title: Data-Driven Identification of SVAR Models + maintainer: Alexander Lange + description: |- + Implements data-driven identification methods for structural vector autoregressive (SVAR) models as described in Lange et al. (2021) . + Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural + impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) ), patterns of GARCH (Normadin, M., Phaneuf, L. (2004) ), + independent component analysis (Matteson, D. S, Tsay, R. S., (2013) ), least dependent innovations (Herwartz, H., Ploedt, M., (2016) ), + smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) ) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) )). + date_publication: '2023-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svars + url_git: '' +svd: + version: 0.5.8 + title: Interfaces to Various State-of-Art SVD and Eigensolvers + maintainer: Anton Korobeynikov + description: R bindings to SVD and eigensolvers (PROPACK, nuTRLan). + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svd + url_git: https://github.com/asl/svd +svDialogs: + version: 1.1.0 + title: |- + 'SciViews' - Standard Dialog Boxes for Windows, MacOS and + Linuxes + maintainer: Philippe Grosjean + description: |- + Quickly construct standard dialog boxes for your GUI, including + message boxes, input boxes, list, file or directory selection, ... In case R + cannot display GUI dialog boxes, a simpler command line version of these + interactive elements is also provided as fallback solution. + date_publication: '2022-05-10' + bug_reports: https://github.com/SciViews/svDialogs/issues + url: https://www.sciviews.org/svDialogs/ + url_cran: https://CRAN.R-project.org/package=svDialogs + url_git: https://github.com/SciViews/svDialogs +svDialogstcltk: + version: 1.0.0 + title: '''SciViews'' - Standard Dialog Boxes using Tcl/Tk' + maintainer: Philippe Grosjean + description: Reimplementation of the 'svDialogs' dialog boxes in Tcl/Tk. + date_publication: '2022-05-10' + bug_reports: https://github.com/SciViews/svDialogstcltk/issues + url: https://www.sciviews.org/svDialogstcltk/ + url_cran: https://CRAN.R-project.org/package=svDialogstcltk + url_git: https://github.com/SciViews/svDialogstcltk +SVDMx: + version: 0.1.0 + title: |- + Child/Child-Adult Mortality-Indexed Model Mortality Age + Schedules + maintainer: Samuel Clark + description: |- + Model age schedules of mortality, nqx, suitable for a life table. This package + implements the SVD-Comp mortality model indexed by either child or child/adult mortality. + Given input value(s) of either 5q0 or (5q0, 45q15), the qx() function generates + single-year 1qx or 5-year 5qx conditional age-specific probabilities of dying. + See Clark (2016) and Clark (2019) . + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SVDMx + url_git: '' +SVDNF: + version: 0.1.11 + title: Discrete Nonlinear Filtering for Stochastic Volatility Models + maintainer: Louis Arsenault-Mahjoubi + description: Implements the discrete nonlinear filter (DNF) of Kitagawa (1987) + to a wide class of stochastic volatility (SV) models with return and volatility + jumps following the work of Bégin and Boudreault (2021) + to obtain likelihood evaluations and maximum likelihood parameter estimates. Offers + several built-in SV models and a flexible framework for users to create customized + models by specifying drift and diffusion functions along with an arrival distribution + for the return and volatility jumps. Allows for the estimation of factor models + with stochastic volatility (e.g., heteroskedastic volatility CAPM) by incorporating + expected return predictors. Also includes functions to compute filtering and prediction + distribution estimates, to simulate data from built-in and custom SV models with + jumps, and to forecast future returns and volatility values using Monte Carlo + simulation from a given SV model. + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SVDNF + url_git: '' +SVEMnet: + version: 1.3.0 + title: Self-Validated Ensemble Models with Elastic Net Regression + maintainer: Andrew T. Karl + description: Implements Self-Validated Ensemble Models (SVEM, Lemkus et al. (2021) + ) using Elastic Net regression via 'glmnet' + (Friedman et al. ). SVEM averages predictions from + multiple models fitted to fractionally weighted bootstraps of the data, tuned + with anti-correlated validation weights. Also implements the randomized permutation + whole model test for SVEM (Karl (2024) ). + \\Code for the whole model test was taken from the supplementary material of Karl + (2024). Development of this package was assisted by 'GPT o1-preview' for code + structure and documentation. + date_publication: '2024-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SVEMnet + url_git: '' +svenssonm: + version: 0.1.0 + title: Svensson's Method + maintainer: Yingyan Zhu + description: |- + Obtain parameters of Svensson's Method, including percentage agreement, + systematic change and individual change. Also, the contingency table can be generated. + Svensson's Method is a rank-invariant nonparametric method for the analysis of ordered scales + which measures the level of change both from systematic and individual aspects. For the details, + please refer to Svensson E. Analysis of systematic and random differences between paired ordinal + categorical data [dissertation]. Stockholm: Almqvist & Wiksell International; 1993. + date_publication: '2017-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svenssonm + url_git: '' +svglite: + version: 2.1.3 + title: An 'SVG' Graphics Device + maintainer: Thomas Lin Pedersen + description: |- + A graphics device for R that produces 'Scalable Vector + Graphics'. 'svglite' is a fork of the older 'RSvgDevice' package. + date_publication: '2023-12-08' + bug_reports: https://github.com/r-lib/svglite/issues + url: https://svglite.r-lib.org + url_cran: https://CRAN.R-project.org/package=svglite + url_git: https://github.com/r-lib/svglite +svgPanZoom: + version: 0.3.4 + title: R 'Htmlwidget' to Add Pan and Zoom to Almost any R Graphic + maintainer: Kent Russell + description: |- + This 'htmlwidget' provides pan and zoom interactivity to R + graphics, including 'base', 'lattice', and 'ggplot2'. The interactivity is + provided through the 'svg-pan-zoom.js' library. Various options to the widget + can tailor the pan and zoom experience to nearly any user desire. + date_publication: '2020-02-15' + bug_reports: https://github.com/timelyportfolio/svgPanZoom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=svgPanZoom + url_git: https://github.com/timelyportfolio/svgPanZoom +svgtools: + version: 1.1.2 + title: Manipulate SVG (Template) Files of Charts + maintainer: Christian Wimmer + description: |- + The purpose of this package is to manipulate SVG files that are templates of charts the user wants to produce. + In vector graphics one copes with x-/y-coordinates of elements (e.g. lines, rectangles, text). Their scale is often dependent on the program that is used to produce the graphics. + In applied statistics one usually has numeric values on a fixed scale (e.g. percentage values between 0 and 100) to show in a chart. + Basically, 'svgtools' transforms the statistical values into coordinates and widths/heights of the vector graphics. + This is done by stackedBar() for bar charts, by linesSymbols() for charts with lines and/or symbols (dot markers) and scatterSymbols() for scatterplots. + date_publication: '2024-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svgtools + url_git: '' +svGUI: + version: 1.0.1 + title: SciViews - Manage GUIs in R + maintainer: Philippe Grosjean + description: |- + The 'SciViews' 'svGUI' package eases the management of Graphical + User Interfaces (GUI) in R. It is independent from any particular GUI widgets + ('Tk', 'Gtk2', native, ...). It centralizes info about GUI elements currently + used, and it dispatches GUI calls to the particular toolkits in use in + function of the context (is R run at the terminal, within a 'Tk' application, + a HTML page?). + date_publication: '2021-04-16' + bug_reports: https://github.com/SciViews/svGUI/issues + url: https://www.sciviews.org/svGUI/ + url_cran: https://CRAN.R-project.org/package=svGUI + url_git: https://github.com/SciViews/svGUI +svgViewR: + version: 1.4.3 + title: 3D Animated Interactive Visualizations Using SVG and WebGL + maintainer: Aaron M Olsen + description: Creates 3D animated, interactive visualizations that can be viewed + in a web browser. + date_publication: '2023-08-28' + bug_reports: '' + url: https://aaronolsen.github.io/tutorials/visualization3d.html + url_cran: https://CRAN.R-project.org/package=svgViewR + url_git: '' +svHttp: + version: 1.0.4 + title: '''SciViews'' - HTTP Server' + maintainer: Philippe Grosjean + description: A simple HTTP server allows to connect GUI clients to R. + date_publication: '2022-05-10' + bug_reports: https://github.com/SciViews/svHttp/issues + url: https://www.sciviews.org/svHttp/ + url_cran: https://CRAN.R-project.org/package=svHttp + url_git: https://github.com/SciViews/svHttp +svIDE: + version: 0.9-54 + title: Functions to Ease Interactions Between R and IDE or Code Editors + maintainer: Philippe Grosjean + description: Function for the GUI API to interact with external IDE/code editors. + date_publication: '2018-06-28' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=194 + url: http://www.sciviews.org/SciViews-R + url_cran: https://CRAN.R-project.org/package=svIDE + url_git: '' +svines: + version: 0.2.4 + title: Stationary Vine Copula Models + maintainer: Thomas Nagler + description: |- + Provides functionality to fit and simulate from stationary vine + copula models for time series, see Nagler et al. (2022) + . + date_publication: '2025-01-15' + bug_reports: https://github.com/tnagler/svines/issues + url: '' + url_cran: https://CRAN.R-project.org/package=svines + url_git: https://github.com/tnagler/svines +svKomodo: + version: 1.0.0 + title: '''SciViews'' - Functions to Interface with Komodo IDE' + maintainer: Philippe Grosjean + description: |- + R-side code to implement an R editor and IDE in Komodo IDE + with the SciViews-K extension. + date_publication: '2022-05-10' + bug_reports: https://github.com/SciViews/svKomodo/issues + url: https://www.sciviews.org/svKomodo/ + url_cran: https://CRAN.R-project.org/package=svKomodo + url_git: https://github.com/SciViews/svKomodo +SVMD: + version: 0.1.0 + title: Spearman Variational Mode Decomposition + maintainer: Dr. Himadri Shekhar Roy + description: In practice, it is difficult to determine the number of decomposition + modes, K, for Variational Mode Decomposition (VMD). To overcome this issue, this + study offers Spearman Variational Mode Decomposition (SVMD), a method that uses + the Spearman correlation coefficient to calculate the ideal mode number. Unlike + the Pearson correlation coefficient, which only returns a perfect value when X + and Y are linearly connected, the Spearman correlation can be calculated without + knowing the probability distributions of X and Y. The Spearman correlation coefficient, + also called Spearman's rank correlation coefficient, is a subset of a wider correlation + coefficient. As VMD decomposes a signal, the Spearman correlation coefficient + between the reconstructed and original sequences rises as the mode number K increases. + Once the signal has been fully decomposed, subsequent increases in K cause the + correlation to gradually level off. When the correlation reaches a specific level, + VMD is said to have adequately decomposed the signal. Numerous experiments revealed + that a threshold of 0.997 produces the best denoising effect, so the threshold + is set at 0.997. This package has been developed using concept of Yang et al. + (2021). + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SVMD + url_git: '' +svMisc: + version: 1.4.3 + title: Miscellaneous Functions for 'SciViews::R' + maintainer: Philippe Grosjean + description: |- + Functions required for the 'SciViews::R' dialect or for general + use: manage a temporary environment attached to the search path, define + synonyms for R functions using aka(), test if 'Aqua', 'Mac', 'Win' ... Show + progress bar, etc. + date_publication: '2024-11-14' + bug_reports: https://github.com/SciViews/svMisc/issues + url: https://www.sciviews.org/svMisc/ + url_cran: https://CRAN.R-project.org/package=svMisc + url_git: https://github.com/SciViews/svMisc +SVMMaj: + version: 0.2.9.3 + title: Implementation of the SVM-Maj Algorithm + maintainer: Hoksan Yip + description: |- + Implements the SVM-Maj algorithm to train data with support vector machine + . + This algorithm uses two efficient updates, one for linear kernel and one + for the nonlinear kernel. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SVMMaj + url_git: '' +svmpath: + version: '0.970' + title: The SVM Path Algorithm + maintainer: Trevor Hastie + description: |- + Computes the entire regularization path for the two-class svm classifier + with essentially the same cost as a single SVM fit. + date_publication: '2020-07-14' + bug_reports: '' + url: http://www.jmlr.org/papers/volume5/hastie04a/hastie04a.pdf + url_cran: https://CRAN.R-project.org/package=svmpath + url_git: '' +SVN: + version: 1.0.1 + title: Statistically Validated Networks + maintainer: Damien Challet + description: Determines networks of significant synchronization between the discrete + states of nodes; see Tumminello et al . + date_publication: '2019-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SVN + url_git: '' +svplots: + version: 0.1.0 + title: Sample Variance Plots (Sv-Plots) + maintainer: Uditha Amarananda Wijesuriya + description: |- + Two versions of sample variance plots, Sv-plot1 and Sv-plot2, will be provided illustrating + the squared deviations from sample variance. Besides indicating the contribution of squared + deviations for the sample variability, these plots are capable of detecting characteristics of the + distribution such as symmetry, skewness and outliers. A remarkable graphical method based on + Sv-plot2 can determine the decision on testing hypotheses over one or two population means. + In sum, Sv-plots will be appealing visualization tools. Complete description of this methodology + can be found in the article, Wijesuriya (2020) . + date_publication: '2021-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svplots + url_git: '' +svrep: + version: 0.7.0 + title: |- + Tools for Creating, Updating, and Analyzing Survey Replicate + Weights + maintainer: Ben Schneider + description: |- + Provides tools for creating and working with survey replicate weights, + extending functionality of the 'survey' package from Lumley (2004) . + Implements bootstrap methods for complex surveys, including the generalized survey bootstrap + as described by Beaumont and Patak (2012) . + Methods are provided for applying nonresponse adjustments to + both full-sample and replicate weights as described by + Rust and Rao (1996) . + Implements methods for sample-based calibration described by Opsomer and Erciulescu (2021) + . + Diagnostic functions are included to compare weights and weighted estimates + from different sets of replicate weights. + date_publication: '2025-02-09' + bug_reports: https://github.com/bschneidr/svrep/issues + url: https://bschneidr.github.io/svrep/ + url_cran: https://CRAN.R-project.org/package=svrep + url_git: https://github.com/bschneidr/svrep +svrpath: + version: 0.1.2 + title: The SVR Path Algorithm + maintainer: Do Hyun Kim + description: Computes the entire solution paths for Support Vector Regression(SVR) + with respect to the regularization parameter, lambda and epsilon in epsilon-intensive + loss function, efficiently. We call each path algorithm svrpath and epspath. See + Wang, G. et al (2008) for details regarding the + method. + date_publication: '2018-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svrpath + url_git: '' +svs: + version: 3.1.1 + title: Tools for Semantic Vector Spaces + maintainer: Koen Plevoets + description: |- + Various tools for semantic vector spaces, such as + correspondence analysis (simple, multiple and discriminant), latent + semantic analysis, probabilistic latent semantic analysis, non-negative + matrix factorization, latent class analysis, EM clustering, logratio + analysis and log-multiplicative (association) analysis. Furthermore, + there are specialized distance measures, plotting functions and some helper + functions. + date_publication: '2024-06-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svs + url_git: '' +svSocket: + version: 1.1.5 + title: '''SciViews'' - Socket Server' + maintainer: Philippe Grosjean + description: A socket server allows to connect clients to R. + date_publication: '2024-02-29' + bug_reports: https://github.com/SciViews/svSocket/issues + url: https://www.sciviews.org/svSocket/ + url_cran: https://CRAN.R-project.org/package=svSocket + url_git: https://github.com/SciViews/svSocket +svSweave: + version: 1.0.0 + title: |- + 'SciViews' - 'Sweave', 'Knitr' and R Markdown Companion + Functions + maintainer: Philippe Grosjean + description: |- + Functions to enumerate and reference figures, tables and equations + in R Markdown documents that do not support these features (thus not + 'bookdown' or 'quarto'. Supporting functions for using 'Sweave' and 'Knitr' + with 'LyX'. + date_publication: '2022-05-10' + bug_reports: https://github.com/SciViews/svSweave/issues + url: https://www.sciviews.org/svSweave/ + url_cran: https://CRAN.R-project.org/package=svSweave + url_git: https://github.com/SciViews/svSweave +svTools: + version: 0.9-5 + title: Wrappers for Tools in Other Packages for IDE Friendliness + maintainer: Philippe Grosjean + description: |- + Set of tools aimed at wrapping some of the functionalities of the + packages tools, utils and codetools into a nicer format so that an IDE can use + them. + date_publication: '2018-06-28' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=194 + url: http://www.sciviews.org/SciViews-R + url_cran: https://CRAN.R-project.org/package=svTools + url_git: '' +svUnit: + version: 1.0.6 + title: '''SciViews'' - Unit, Integration and System Testing' + maintainer: Philippe Grosjean + description: A complete unit test system and functions to implement its GUI part. + date_publication: '2021-04-19' + bug_reports: https://github.com/SciViews/svUnit/issues + url: https://www.sciviews.org/svUnit/ + url_cran: https://CRAN.R-project.org/package=svUnit + url_git: https://github.com/SciViews/svUnit +svWidgets: + version: 0.9-45 + title: Management of GUI Widgets, Windows, and Other GUI Resources + maintainer: Philippe Grosjean + description: High level management of widgets, windows and other graphical resources. + date_publication: '2018-06-28' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=194 + url: http://www.sciviews.org/SciViews-R + url_cran: https://CRAN.R-project.org/package=svWidgets + url_git: '' +svycdiff: + version: 0.1.1 + title: Controlled Difference Estimation for Complex Surveys + maintainer: Stephen Salerno + description: Estimates the population average controlled difference for a given + outcome between levels of a binary treatment, exposure, or other group membership + variable of interest for clustered, stratified survey samples where sample selection + depends on the comparison group. Provides three methods for estimation, namely + outcome modeling and two factorizations of inverse probability weighting. Under + stronger assumptions, these methods estimate the causal population average treatment + effect. Salerno et al., (2024) . + date_publication: '2024-08-20' + bug_reports: https://github.com/salernos/svycdiff/issues + url: https://salernos.github.io/svycdiff/ + url_cran: https://CRAN.R-project.org/package=svycdiff + url_git: https://github.com/salernos/svycdiff +svydiags: + version: '0.7' + title: Regression Model Diagnostics for Survey Data + maintainer: Richard Valliant + description: 'Diagnostics for fixed effects linear and general linear regression + models fitted with survey data. Extensions of standard diagnostics to complex + survey data are included: standardized residuals, leverages, Cook''s D, dfbetas, + dffits, condition indexes, and variance inflation factors as found in Li and Valliant + (Surv. Meth., 2009, 35(1), pp. 15-24; Jnl. of Off. Stat., 2011, 27(1), pp. 99-119; + Jnl. of Off. Stat., 2015, 31(1), pp. 61-75); Liao and Valliant (Surv. Meth., 2012, + 38(1), pp. 53-62; Surv. Meth., 2012, 38(2), pp. 189-202). Variance inflation + factors and condition indexes are also computed for some general linear models + as described in Liao (U. Maryland thesis, 2010).' + date_publication: '2024-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svydiags + url_git: '' +svylme: + version: 1.5-1 + title: Linear Mixed Models for Complex Survey Data + maintainer: Thomas Lumley + description: Linear mixed models for complex survey data, by pairwise composite + likelihood, as described in Lumley & Huang (2023) . Supports + nested and crossed random effects, and correlated random effects as in genetic + models. Allows for multistage sampling and for other designs where pairwise sampling + probabilities are specified or can be calculated. + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svylme + url_git: '' +SvyNom: + version: '1.2' + title: Nomograms for Right-Censored Outcomes from Survey Designs + maintainer: Mithat Gonen + description: |- + Builds, evaluates and validates a nomogram with survey data + and right-censored outcomes. As described in Capanu (2015) + , the package contains functions to create + the nomogram, validate it using bootstrap, as well as produce the + calibration plots. + date_publication: '2022-04-28' + bug_reports: https://github.com/MSKCC-Epi-Bio/SvyNom/issues + url: https://mskcc-epi-bio.github.io/SvyNom/ + url_cran: https://CRAN.R-project.org/package=SvyNom + url_git: https://github.com/MSKCC-Epi-Bio/SvyNom +svyROC: + version: 1.0.0 + title: Estimation of the ROC Curve and the AUC for Complex Survey Data + maintainer: Amaia Iparragirre + description: 'Estimate the receiver operating characteristic (ROC) curve, area under + the curve (AUC) and optimal cut-off points for individual classification taking + into account complex sampling designs when working with complex survey data. Methods + implemented in this package are described in: A. Iparragirre, I. Barrio, I. Arostegui + (2024) ; A. Iparragirre, I. Barrio, J. Aramendi, I. Arostegui + (2022) ; A. Iparragirre, I. Barrio (2024) .' + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svyROC + url_git: '' +svyVarSel: + version: 1.0.1 + title: Variable Selection for Complex Survey Data + maintainer: Amaia Iparragirre + description: 'Fit design-based linear and logistic elastic nets with complex survey + data considering the sampling design when defining training and test sets using + replicate weights. Methods implemented in this package are described in: A. Iparragirre, + T. Lumley, I. Barrio, I. Arostegui (2024) .' + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svyVarSel + url_git: '' +svyVGAM: + version: '1.2' + title: Design-Based Inference in Vector Generalised Linear Models + maintainer: Thomas Lumley + description: Provides inference based on the survey package for the wide range of + parametric models in the 'VGAM' package. + date_publication: '2023-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svyVGAM + url_git: '' +svyweight: + version: 0.1.0 + title: Quick and Flexible Survey Weighting + maintainer: Ben Mainwaring + description: |- + Quickly and flexibly calculates weights for survey data, in order to correct + for survey non-response or other sampling issues. Uses rake weighting, a common technique + also know as rim weighting or iterative proportional fitting. This technique allows for weighting + on multiple variables, even when the interlocked distribution of the two + variables is not known. Interacts with Thomas Lumley's 'survey' package, as described in + Lumley, Thomas (2011, ISBN:978-1-118-21093-2). Adds additional functionality, more adaptable syntax, and error-checking + to the base weighting functionality in 'survey.' + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=svyweight + url_git: '' +swa: + version: 0.8.1 + title: Subsampling Winner Algorithm for Classification + maintainer: Xingye Qiao + description: This algorithm conducts variable selection in the classification setting. + It repeatedly subsamples variables and runs linear discriminant analysis (LDA) + on the subsampled variables. Variables are scored based on the AUC and the t-statistics. + Variables then enter a competition and the semi-finalist variables will be evaluated + in a final round of LDA classification. The algorithm then outputs a list of variable + selected. Qiao, Sun and Fan (2017) . + date_publication: '2017-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swa + url_git: '' +swag: + version: 0.1.0 + title: Sparse Wrapper Algorithm + maintainer: Samuel Orso + description: |- + An algorithm that trains a meta-learning procedure that combines + screening and wrapper methods to find a set of extremely low-dimensional attribute + combinations. This package works on top of the 'caret' package and proceeds in a + forward-step manner. More specifically, it builds and tests learners starting + from very few attributes until it includes a maximal number of attributes by + increasing the number of attributes at each step. Hence, for each fixed number + of attributes, the algorithm tests various (randomly selected) learners and + picks those with the best performance in terms of training error. Throughout, + the algorithm uses the information coming from the best learners at the previous + step to build and test learners in the following step. In the end, it outputs + a set of strong low-dimensional learners. + date_publication: '2020-11-10' + bug_reports: https://github.com/SMAC-Group/SWAG-R-Package/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=swag + url_git: https://github.com/SMAC-Group/SWAG-R-Package/ +swagger: + version: 5.17.14.1 + title: |- + Dynamically Generates Documentation from a 'Swagger' Compliant + API + maintainer: Bruno Tremblay + description: |- + A collection of 'HTML', 'JavaScript', and 'CSS' assets that + dynamically generate beautiful documentation from a 'Swagger' compliant API: + . + date_publication: '2024-06-28' + bug_reports: https://github.com/rstudio/swagger/issues + url: https://rstudio.github.io/swagger/ + url_cran: https://CRAN.R-project.org/package=swagger + url_git: https://github.com/rstudio/swagger +swamp: + version: 1.5.1 + title: |- + Visualization, Analysis and Adjustment of High-Dimensional Data + in Respect to Sample Annotations + maintainer: Martin Lauss + description: 'Collection of functions to connect the structure of the data with + the information on the samples. Three types of associations are covered: 1. linear + model of principal components. 2. hierarchical clustering analysis. 3. distribution + of features-sample annotation associations. Additionally, the inter-relation between + sample annotations can be analyzed. Simple methods are provided for the correction + of batch effects and removal of principal components.' + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swamp + url_git: '' +swaprinc: + version: 1.0.1 + title: Swap Principal Components into Regression Models + maintainer: Mackson Ncube + description: |- + Obtaining accurate and stable estimates of regression coefficients + can be challenging when the suggested statistical model has issues related to + multicollinearity, convergence, or overfitting. One solution is to use + principal component analysis (PCA) results in the regression, as discussed in + Chan and Park (2005) . The swaprinc() package + streamlines comparisons between a raw regression model with the full set of + raw independent variables and a principal component regression model where + principal components are estimated on a subset of the independent variables, + then swapped into the regression model in place of those variables. The + swaprinc() function compares one raw regression model to one principal + component regression model, while the compswap() function compares one raw + regression model to many principal component regression models. Package + functions include parameters to center, scale, and undo centering and scaling, + as described by Harvey and Hansen (2022) + . + Additionally, the package supports using Gifi methods to extract principal + components from categorical variables, as outlined by Rossiter (2021) + . + date_publication: '2023-04-17' + bug_reports: https://github.com/mncube/swaprinc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=swaprinc + url_git: https://github.com/mncube/swaprinc +swaRm: + version: 0.6.0 + title: Processing Collective Movement Data + maintainer: Simon Garnier + description: |- + Function library for processing collective movement data (e.g. fish + schools, ungulate herds, baboon troops) collected from GPS trackers or + computer vision tracking software. + date_publication: '2023-01-11' + bug_reports: https://github.com/swarm-lab/swaRm/issues + url: https://swarm-lab.github.io/swaRm/ + url_cran: https://CRAN.R-project.org/package=swaRm + url_git: https://github.com/swarm-lab/swaRm +swaRmverse: + version: 0.1.1 + title: Swarm Space Creation + maintainer: Marina Papadopoulou + description: |- + Provides a pipeline for the comparative analysis of + collective movement data (e.g. fish schools, bird flocks, baboon troops) by + processing 2-dimensional positional data (x,y,t) from GPS trackers or computer + vision tracking systems, discretizing events of collective motion, calculating + a set of established metrics that characterize each event, and placing the + events in a multi-dimensional swarm space constructed from these metrics. + The swarm space concept, the metrics and data sets included are described in: + Papadopoulou Marina, Furtbauer Ines, O'Bryan Lisa R., Garnier Simon, + Georgopoulou Dimitra G., Bracken Anna M., Christensen Charlotte and King + Andrew J. (2023) . + date_publication: '2024-10-10' + bug_reports: https://github.com/marinapapa/swaRmverse/issues + url: https://marinapapa.github.io/swaRmverse/ + url_cran: https://CRAN.R-project.org/package=swaRmverse + url_git: https://github.com/marinapapa/swaRmverse +swash: + version: 1.1.0 + title: Swash-Backwash Model for the Single Epidemic Wave + maintainer: Thomas Wieland + description: The Swash-Backwash Model for the Single Epidemic Wave was developed + by Cliff and Haggett (2006) to model the velocity + of spread of infectious diseases across space. This package enables the calculation + of the Swash-Backwash Model for user-supplied panel data on regional infections. + The package also provides additional functions for bootstrap confidence intervals, + country comparison, visualization of results, and data management. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swash + url_git: '' +swatches: + version: 0.5.0 + title: Read, Inspect, and Manipulate Color Swatch Files + maintainer: Bob Rudis + description: |- + There are numerous places to create and download color + palettes. These are usually shared in 'Adobe' swatch file formats of + some kind. There is also often the need to use standard palettes + developed within an organization to ensure that aesthetics are carried over + into all projects and output. Now there is a way to read these swatch + files in R and avoid transcribing or converting color values by hand or + or with other programs. This package provides functions to read and + inspect 'Adobe Color' ('ACO'), 'Adobe Swatch Exchange' ('ASE'), 'GIMP Palette' ('GPL'), + 'OpenOffice' palette ('SOC') files and 'KDE Palette' ('colors') files. Detailed + descriptions of 'Adobe Color' and 'Swatch Exchange' file formats as well as other + swatch file formats can be found at + . + date_publication: '2017-12-21' + bug_reports: https://github.com/hrbrmstr/swatches/issues + url: '' + url_cran: https://CRAN.R-project.org/package=swatches + url_git: https://github.com/hrbrmstr/swatches +swCRTdesign: + version: '4.0' + title: Stepped Wedge Cluster Randomized Trial (SW CRT) Design + maintainer: Jim Hughes + description: A set of tools for examining the design and analysis aspects of stepped + wedge cluster randomized trials (SW CRT) based on a repeated cross-sectional sampling + scheme (Hussey MA and Hughes JP (2007) Contemporary Clinical Trials 28:182-191. + ). + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swCRTdesign + url_git: '' +swdft: + version: 1.0.0 + title: Sliding Window Discrete Fourier Transform (SWDFT) + maintainer: Lee F. Richardson + description: |- + Implements the Sliding Window Discrete Fourier Transform (SWDFT). Also provides + statistical methods based on the SWDFT, and graphical tools to display the outputs. + date_publication: '2019-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swdft + url_git: '' +swdpwr: + version: '1.11' + title: Power Calculation for Stepped Wedge Cluster Randomized Trials + maintainer: Jiachen Chen + description: 'To meet the needs of statistical power calculation for stepped wedge + cluster randomized trials, we developed this software. Different parameters can + be specified by users for different scenarios, including: cross-sectional and + cohort designs, binary and continuous outcomes, marginal (GEE) and conditional + models (mixed effects model), three link functions (identity, log, logit links), + with and without time effects (the default specification assumes no-time-effect) + under exchangeable, nested exchangeable and block exchangeable correlation structures. + Unequal numbers of clusters per sequence are also allowed. The methods included + in this package: Zhou et al. (2020) , Li et + al. (2018) . Supplementary documents can be found at: + . + The Shiny app for swdpwr can be accessed at: . + The package also includes functions that perform calculations for the intra-cluster + correlation coefficients based on the random effects variances as input variables + for continuous and binary outcomes, respectively.' + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swdpwr + url_git: '' +sweater: + version: 0.1.8 + title: Speedy Word Embedding Association Test and Extras Using R + maintainer: Chung-hong Chan + description: 'Conduct various tests for evaluating implicit biases in word embeddings: + Word Embedding Association Test (Caliskan et al., 2017), , + Relative Norm Distance (Garg et al., 2018), , Mean + Average Cosine Similarity (Mazini et al., 2019) , SemAxis (An + et al., 2018) , Relative Negative Sentiment Bias (Sweeney & + Najafian, 2019) , and Embedding Coherence Test (Dev + & Phillips, 2019) .' + date_publication: '2023-11-07' + bug_reports: https://github.com/gesistsa/sweater/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sweater + url_git: https://github.com/gesistsa/sweater +sweep: + version: 0.2.5 + title: Tidy Tools for Forecasting + maintainer: Matt Dancho + description: |2- + + Tidies up the forecasting modeling and prediction work flow, + extends the 'broom' package + with 'sw_tidy', 'sw_glance', 'sw_augment', and 'sw_tidy_decomp' functions + for various forecasting models, + and enables converting 'forecast' objects to + "tidy" data frames with 'sw_sweep'. + date_publication: '2023-07-06' + bug_reports: https://github.com/business-science/sweep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sweep + url_git: https://github.com/business-science/sweep +SweepDiscovery: + version: 0.1.1 + title: Selective Sweep Discovery Tool + maintainer: Abhik Sarkar + description: Selective sweep is a biological phenomenon in which genetic variation + between neighboring beneficial mutant alleles is swept away due to the effect + of genetic hitchhiking. Detection of selective sweep is not well acquainted as + well as it is a laborious job. This package is a user friendly approach for detecting + selective sweep in genomic regions. It uses a Random Forest based machine learning + approach to predict selective sweep from VCF files as an input. Input of this + function, train data and new data, can be computed using the project + in 'GitHub'. This package has been developed by using the concept of Pavlidis + and Alachiotis (2017) . + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SweepDiscovery + url_git: '' +sweidnumbr: + version: 1.5.0 + title: Handling of Swedish Identity Numbers + maintainer: Mans Magnusson + description: |- + Structural handling of identity numbers used in the Swedish + administration such as personal identity numbers ('personnummer') and + organizational identity numbers ('organisationsnummer'). + date_publication: '2024-01-13' + bug_reports: https://github.com/rOpenGov/sweidnumbr/issues + url: http://ropengov.github.io/sweidnumbr/ + url_cran: https://CRAN.R-project.org/package=sweidnumbr + url_git: https://github.com/rOpenGov/sweidnumbr +swephR: + version: 0.3.1 + title: High Precision Swiss Ephemeris + maintainer: Ralf Stubner + description: |- + The Swiss Ephemeris (version 2.10.03) is a high precision ephemeris based upon the + DE431 ephemerides from NASA's JPL. It covers the time range 13201 BCE to + 17191 CE. This package uses the semi-analytic theory by Steve Moshier. + For faster and more accurate calculations, the compressed Swiss Ephemeris + data is available in the 'swephRdata' package. To access this data package, + run 'install.packages("swephRdata", repos = "https://rstub.r-universe.dev", + type = "source")'. The size of the 'swephRdata' package is approximately + 115 MB. The user can also use the original JPL DE431 data. + date_publication: '2023-05-08' + bug_reports: https://github.com/rstub/swephR/issues/ + url: https://rstub.github.io/swephR/ + url_cran: https://CRAN.R-project.org/package=swephR + url_git: https://github.com/rstub/swephR/ +swfscAirDAS: + version: 0.3.1 + title: Southwest Fisheries Science Center Aerial DAS Data Processing + maintainer: Sam Woodman + description: |- + Process and summarize aerial survey 'DAS' data (AirDAS) + + collected using an aerial survey program from the + Southwest Fisheries Science Center (SWFSC) + . + PDF files detailing the relevant AirDAS data formats are included in this package. + date_publication: '2024-10-03' + bug_reports: https://github.com/swfsc/swfscAirDAS/issues/ + url: https://swfsc.github.io/swfscAirDAS/ + url_cran: https://CRAN.R-project.org/package=swfscAirDAS + url_git: https://github.com/swfsc/swfscAirDAS/ +swfscDAS: + version: 0.6.3 + title: Processing DAS Data Files + maintainer: Sam Woodman + description: |- + Process and summarize DAS data files. + These files are typically, but do not have to be + DAS data + produced by the Southwest Fisheries Science Center (SWFSC) program 'WinCruz'. + This package standardizes and streamlines basic DAS data processing, + and includes a PDF with the DAS data format requirements expected by the package. + date_publication: '2024-07-03' + bug_reports: https://github.com/swfsc/swfscDAS/issues/ + url: https://swfsc.github.io/swfscDAS/ + url_cran: https://CRAN.R-project.org/package=swfscDAS + url_git: https://github.com/swfsc/swfscDAS/ +swfscMisc: + version: 1.6.5 + title: Miscellaneous Functions for Southwest Fisheries Science Center + maintainer: Eric Archer + description: |- + Collection of conversion, analytical, geodesic, mapping, and + plotting functions. Used to support packages and code written by + researchers at the Southwest Fisheries Science Center of the National + Oceanic and Atmospheric Administration. + date_publication: '2023-09-08' + bug_reports: https://github.com/EricArcher/swfscMisc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=swfscMisc + url_git: https://github.com/EricArcher/swfscMisc +swgee: + version: '1.4' + title: |- + Simulation Extrapolation Inverse Probability Weighted + Generalized Estimating Equations + maintainer: Juan Xiong + description: 'Simulation extrapolation and inverse probability weighted generalized + estimating equations method for longitudinal data with missing observations and + measurement error in covariates. References: Yi, G. Y. (2008) ; + Cook, J. R. and Stefanski, L. A. (1994) ; + Little, R. J. A. and Rubin, D. B. (2002, ISBN:978-0-471-18386-0).' + date_publication: '2019-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swgee + url_git: '' +SWIM: + version: 1.0.0 + title: Scenario Weights for Importance Measurement + maintainer: Silvana M. Pesenti + description: |- + An efficient sensitivity analysis for stochastic models based on + Monte Carlo samples. Provides weights on simulated scenarios from a + stochastic model, such that stressed random variables fulfil given + probabilistic constraints (e.g. specified values for risk measures), + under the new scenario weights. Scenario weights are selected by + constrained minimisation of the relative entropy to the baseline model. + The 'SWIM' package is based on Pesenti S.M., Millossovich P., Tsanakas A. (2019) + "Reverse Sensitivity Testing: What does it take to break the model" + and Pesenti S.M. (2021) + "Reverse Sensitivity Analysis for Risk Modelling" . + date_publication: '2022-01-09' + bug_reports: https://github.com/spesenti/SWIM/issues + url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3515274 + url_cran: https://CRAN.R-project.org/package=SWIM + url_git: https://github.com/spesenti/SWIM +SwimmeR: + version: 0.14.2 + title: Data Import, Cleaning, and Conversions for Swimming Results + maintainer: Greg Pilgrim + description: The goal of the 'SwimmeR' package is to provide means of acquiring, + and then analyzing, data from swimming (and diving) competitions. To that end + 'SwimmeR' allows results to be read in from .html sources, like 'Hy-Tek' real + time results pages, '.pdf' files, 'ISL' results, 'Omega' results, and (on a development + basis) '.hy3' files. Once read in, 'SwimmeR' can convert swimming times (performances) + between the computationally useful format of seconds reported to the '100ths' + place (e.g. 95.37), and the conventional reporting format (1:35.37) used in the + swimming community. 'SwimmeR' can also score meets in a variety of formats with + user defined point values, convert times between courses ('LCM', 'SCM', 'SCY') + and draw single elimination brackets, as well as providing a suite of tools for + working cleaning swimming data. This is a developmental package, not yet mature. + date_publication: '2023-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SwimmeR + url_git: '' +swimplot: + version: 1.2.0 + title: Tools for Creating Swimmers Plots using 'ggplot2' + maintainer: Jessica Weiss + description: Used for creating swimmers plots with functions to customize the bars, + add points, add lines, add text, and add arrows. + date_publication: '2021-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=swimplot + url_git: '' +swipeR: + version: 1.1.0 + title: Carousels using the 'JavaScript' Library 'Swiper' + maintainer: Stéphane Laurent + description: |- + Create carousels using the 'JavaScript' library 'Swiper' and + the package 'htmlwidgets'. The carousels can be displayed in the + 'RStudio' viewer pane, in 'Shiny' applications and in 'R markdown' + documents. The package also provides a 'RStudio' addin allowing to + choose image files and to display them in the viewer pane. + date_publication: '2023-08-26' + bug_reports: https://github.com/stla/swipeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=swipeR + url_git: https://github.com/stla/swipeR +swirl: + version: 2.4.5 + title: Learn R, in R + maintainer: Sean Kross + description: |- + Use the R console as an interactive learning + environment. Users receive immediate feedback as they are guided through + self-paced lessons in data science and R programming. + date_publication: '2020-01-16' + bug_reports: '' + url: http://swirlstats.com + url_cran: https://CRAN.R-project.org/package=swirl + url_git: '' +swirlify: + version: 0.5.3 + title: A Toolbox for Writing 'swirl' Courses + maintainer: Sean Kross + description: |- + A set of tools for writing and sharing interactive courses + to be used with swirl. + date_publication: '2019-05-28' + bug_reports: '' + url: http://swirlstats.com + url_cran: https://CRAN.R-project.org/package=swirlify + url_git: '' +SwissAir: + version: 1.1.6 + title: |- + Air Quality Data of Switzerland for One Year in 30 Min + Resolution + maintainer: Christoph Hofer + description: Ozone, NOx (= Sum of nitrogen monoxide and nitrogen dioxide), nitrogen + monoxide, ambient temperature, dew point, wind speed and wind direction at 3 sites + around lake of Lucerne in Central Switzerland in 30 min time resolution for year + 2004. + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SwissAir + url_git: '' +swissparl: + version: 0.2.2 + title: Interface to the Webservices of the Swiss Parliament + maintainer: David Zumbach + description: |- + Retrieves the most important data on parliamentary activities of the Swiss Federal Assembly via + an open, machine-readable interface (see ). + date_publication: '2021-11-02' + bug_reports: https://github.com/zumbov2/swissparl/issues + url: https://www.parlament.ch/en/services/open-data-webservices + url_cran: https://CRAN.R-project.org/package=swissparl + url_git: '' +switchboard: + version: '0.1' + title: An Agile Widget Engine for Real-Time, Dynamic Visualizations + maintainer: Marc J. Lajeunesse + description: An unsorted collection of visualization widgets rendered in 'Tcl/Tk' + to generate agile dashboards for your iterative simulations. Widgets include progress + bars, counters, eavesdroppers, injectors, switches, and sliders for dynamic manipulation + and visualization of simulation parameters. + date_publication: '2021-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=switchboard + url_git: http://lajeunesse.myweb.usf.edu/https://github.com/mjlajeunesse/https://www.youtube.com/c/LajeunesseLab/ +switchcase: + version: 0.1.1 + title: A Simple and Flexible Switch-Case Construct for the 'R' Language + maintainer: Joachim Zuckarelli + description: Provides a switch-case construct for 'R', as it is known from other + programming languages. It allows to test multiple, similar conditions in an efficient, + easy-to-read manner, so nested if-else constructs can be avoided. The switch-case + construct is designed as an 'R' function that allows to return values depending + on which condition is met and lets the programmer flexibly decide whether or not + to leave the switch-case construct after a case block has been executed. + date_publication: '2020-05-17' + bug_reports: https://github.com/jsugarelli/switchcase/issues + url: '' + url_cran: https://CRAN.R-project.org/package=switchcase + url_git: https://github.com/jsugarelli/switchcase/ +switchr: + version: 0.14.8 + title: |- + Installing, Managing, and Switching Between Distinct Sets of + Installed Packages + maintainer: Gabriel Becker + description: |- + Provides an abstraction for managing, installing, + and switching between sets of installed R packages. This allows users to + maintain multiple package libraries simultaneously, e.g. to maintain + strict, package-version-specific reproducibility of many analyses, or + work within a development/production release paradigm. Introduces a + generalized package installation process which supports multiple repository + and non-repository sources and tracks package provenance. + date_publication: '2023-03-21' + bug_reports: https://github.com/gmbecker/switchr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=switchr + url_git: https://github.com/gmbecker/switchr +switchSelection: + version: 2.0.0 + title: Endogenous Switching and Sample Selection Regression Models + maintainer: Bogdan Potanin + description: Estimate the parameters of multivariate endogenous switching and sample + selection models using methods described in Newey (2009) , + E. Kossova, B. Potanin (2018) , + E. Kossova, L. Kupriianova, B. Potanin (2020) + and E. Kossova, B. Potanin (2022) . + date_publication: '2024-09-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=switchSelection + url_git: '' +SWMPr: + version: 2.5.2 + title: Retrieving, Organizing, and Analyzing Estuary Monitoring Data + maintainer: Marcus W. Beck + description: |- + Tools for retrieving, organizing, and analyzing environmental + data from the System Wide Monitoring Program of the National Estuarine + Research Reserve System . These tools + address common challenges associated with continuous time series data + for environmental decision making. + date_publication: '2025-02-03' + bug_reports: https://github.com/fawda123/SWMPr/issues + url: http://fawda123.github.io/SWMPr/ + url_cran: https://CRAN.R-project.org/package=SWMPr + url_git: '' +SWMPrExtension: + version: 2.2.5.1 + title: Functions for Analyzing and Plotting Estuary Monitoring Data + maintainer: Matt Dornback + description: |- + Tools for performing routine analysis and plotting tasks with environmental + data from the System Wide Monitoring Program of the National Estuarine + Research Reserve System . This package builds + on the functionality of the 'SWMPr' package , + which is used to retrieve and organize the data. The combined set of tools + address common challenges associated with continuous time series data + for environmental decision making, and are intended for use in annual reporting activities. + References: + Beck, Marcus W. (2016) + Rudis, Bob (2014) . + United States Environmental Protection Agency (2015) . + date_publication: '2024-01-11' + bug_reports: https://github.com/NOAA-OCM/SWMPrExtension/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SWMPrExtension + url_git: '' +SWTools: + version: 1.1.0 + title: Helper Tools for Australian Hydrologists + maintainer: Matt Gibbs + description: |- + Functions to speed up work flow for hydrological analysis. + Focused on Australian climate data (SILO climate data), hydrological models (eWater Source) and in particular South Australia ( hydrological data). + date_publication: '2024-10-14' + bug_reports: https://github.com/matt-s-gibbs/swtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SWTools + url_git: https://github.com/matt-s-gibbs/SWTools +sylcount: + version: 0.2-6 + title: Syllable Counting and Readability Measurements + maintainer: Drew Schmidt + description: |- + An English language syllable counter, plus readability score + measure-er. For readability, we support 'Flesch' Reading Ease and + 'Flesch-Kincaid' Grade Level ('Kincaid' 'et al'. 1975) + , + Automated Readability Index ('Senter' and Smith 1967) + , + Simple Measure of Gobbledygook (McLaughlin 1969), + and 'Coleman-Liau' (Coleman and 'Liau' 1975) . The + package has been carefully optimized and should be very efficient, both in + terms of run time performance and memory consumption. The main methods are + 'vectorized' by document, and scores for multiple documents are computed in + parallel via 'OpenMP'. + date_publication: '2023-12-10' + bug_reports: https://github.com/wrathematics/sylcount/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sylcount + url_git: https://github.com/wrathematics/sylcount +syllabifyr: + version: 0.1.1 + title: Syllabifier for CMU Dictionary Transcriptions + maintainer: Josef Fruehwald + description: |- + Implements tidy syllabification of transcription. + Based on @kylebgorman's 'python' implementation . + date_publication: '2020-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=syllabifyr + url_git: '' +syllogi: + version: 1.0.4 + title: Collection of Data Sets for Teaching Purposes + maintainer: Jared Studyvin + description: |- + Collection (syllogi in greek) of real and fictitious data sets for teaching purposes. + The datasets were manually entered by the author from the respective references as listed in the individual dataset documentation. + The fictions datasets are the creation of the author, that he has found useful for teaching statistics. + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=syllogi + url_git: '' +sylly: + version: 0.1-6 + title: Hyphenation and Syllable Counting for Text Analysis + maintainer: Meik Michalke + description: |- + Provides the hyphenation algorithm used for 'TeX'/'LaTeX' and similar software, as proposed by Liang (1983, ). Mainly contains the + function hyphen() to be used for hyphenation/syllable counting of text objects. It was originally developed for and part of the 'koRpus' package, but later + released as a separate package so it's lighter to have this particular functionality available for other packages. Support for various languages needs be added + on-the-fly or by plugin packages (); this package does not include any language specific data. Due to some restrictions + on CRAN, the full package sources are only available from the project homepage. To ask for help, report bugs, request features, or discuss the development of + the package, please subscribe to the koRpus-dev mailing list (). + date_publication: '2020-09-20' + bug_reports: https://github.com/unDocUMeantIt/sylly/issues + url: https://reaktanz.de/?c=hacking&s=sylly + url_cran: https://CRAN.R-project.org/package=sylly + url_git: '' +sylly.en: + version: 0.1-3 + title: 'Language Support for ''sylly'' Package: English' + maintainer: Meik Michalke + description: |- + Adds support for the English language to the 'sylly' + package. Due to some restrictions on CRAN, the full package + sources are only available from the project homepage. To ask + for help, report bugs, suggest feature improvements, or discuss + the global development of the package, please consider + subscribing to the koRpus-dev mailing list + (). + date_publication: '2018-03-19' + bug_reports: https://github.com/unDocUMeantIt/sylly.en/issues + url: http://reaktanz.de/?c=hacking&s=koRpus + url_cran: https://CRAN.R-project.org/package=sylly.en + url_git: '' +sym.arma: + version: '1.0' + title: Autoregressive and Moving Average Symmetric Models + maintainer: Vinicius Quintas Souto Maior + description: 'Functions for fitting the Autoregressive and Moving Average Symmetric + Model for univariate time series introduced by Maior and Cysneiros (2018), . + Fitting method: conditional maximum likelihood estimation. For details see: Wei + (2006), Time Series Analysis: Univariate and Multivariate Methods, Section 7.2.' + date_publication: '2018-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sym.arma + url_git: '' +symbol.equation.gpt: + version: 1.1.4 + title: Simple User Interface to Build Equations and Add Symbols + maintainer: Obinna Obianom + description: Powerful user interface for adding symbols, smileys, arrows, building + mathematical equations using 'LaTeX' or 'r2symbols'. Built for use in development + of 'Markdown' and 'Shiny' Outputs. + date_publication: '2024-07-30' + bug_reports: https://github.com/oobianom/symbol.equation.gpt/issues + url: https://symbols-ui.obi.obianom.com + url_cran: https://CRAN.R-project.org/package=symbol.equation.gpt + url_git: '' +symbolicDA: + version: 0.7-1 + title: Analysis of Symbolic Data + maintainer: Andrzej Dudek + description: |- + Symbolic data analysis methods: importing/exporting data from ASSO XML Files, distance calculation for symbolic data (Ichino-Yaguchi, de Carvalho measure), zoom star plot, 3d interval plot, multidimensional scaling for symbolic interval data, dynamic clustering based on distance matrix, HINoV method for symbolic data, Ichino's feature selection method, principal component analysis for symbolic interval data, decision trees for symbolic data based on optimal split with bagging, boosting and random forest approach (+visualization), kernel discriminant analysis for symbolic data, Kohonen's self-organizing maps for symbolic data, replication and profiling, artificial symbolic data generation. + (Milligan, G.W., Cooper, M.C. (1985) , + Breiman, L. (1996), , + Hubert, L., Arabie, P. (1985), , + Ichino, M., & Yaguchi, H. (1994), , + Rand, W.M. (1971) , + Calinski, T., Harabasz, J. (1974) , + Breckenridge, J.N. (2000) , + Groenen, P.J.F, Winsberg, S., Rodriguez, O., Diday, E. (2006) , + Walesiak, M., Dudek, A. (2008) , + Dudek, A. (2007), ). + date_publication: '2023-02-13' + bug_reports: '' + url: http://keii.ue.wroc.pl/symbolicDA/ + url_cran: https://CRAN.R-project.org/package=symbolicDA + url_git: '' +SymbolicDeterminants: + version: 2.0.0 + title: Symbolic Representation of Matrix Determinant + maintainer: William Fairweather + description: Creates a numeric guide for writing the formula for the determinant + of a square matrix (a detguide) as a function of the elements of the matrix and + writes out that formula, the symbolic representation. + date_publication: '2021-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SymbolicDeterminants + url_git: '' +symbolicQspray: + version: 1.1.0 + title: |- + Multivariate Polynomials with Symbolic Parameters in their + Coefficients + maintainer: Stéphane Laurent + description: |- + Introduces the 'symbolicQspray' objects. Such an object + represents a multivariate polynomial whose coefficients are fractions of + multivariate polynomials with rational coefficients. The package + allows arithmetic on such polynomials. It is based on the 'qspray' and + 'ratioOfQsprays' packages. Some functions for 'qspray' polynomials have + their counterpart for 'symbolicQspray' polynomials. A 'symbolicQspray' + polynomial should not be seen as a polynomial on the field of fractions + of rational polynomials, but should rather be seen as a polynomial with + rational coefficients depending on some parameters, symbolically + represented, with a dependence given by fractions of rational polynomials. + date_publication: '2024-07-28' + bug_reports: https://github.com/stla/symbolicQspray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=symbolicQspray + url_git: https://github.com/stla/symbolicQspray +symDMatrix: + version: 2.1.1 + title: Partitioned Symmetric Matrices + maintainer: Alexander Grueneberg + description: |- + A matrix-like class to represent a symmetric matrix partitioned + into file-backed blocks. + date_publication: '2020-08-02' + bug_reports: https://github.com/QuantGen/symDMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=symDMatrix + url_git: https://github.com/QuantGen/symDMatrix +symengine: + version: 0.2.6 + title: Interface to the 'SymEngine' Library + maintainer: Jialin Ma + description: |2- + + Provides an R interface to 'SymEngine' , + a standalone 'C++' library for fast symbolic manipulation. The package has functionalities + for symbolic computation like calculating exact mathematical expressions, solving + systems of linear equations and code generation. + date_publication: '2024-02-25' + bug_reports: https://github.com/symengine/symengine.R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=symengine + url_git: https://github.com/symengine/symengine.R +symmetry: + version: 0.2.3 + title: Testing for Symmetry of Data and Model Residuals + maintainer: Blagoje Ivanović + description: |- + Implementations of a large number of tests for symmetry and their + bootstrap variants, which can be used for testing the symmetry of random + samples around a known or unknown mean. Functions are also there for testing + the symmetry of model residuals around zero. Currently, the supported models + are linear models and generalized autoregressive conditional + heteroskedasticity (GARCH) models (fitted with the 'fGarch' package). All + tests are implemented using the 'Rcpp' package which ensures great + performance of the code. + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=symmetry + url_git: '' +symmoments: + version: 1.2.1 + title: |- + Symbolic Central and Noncentral Moments of the Multivariate + Normal Distribution + maintainer: Kem Phillips + description: Symbolic central and non-central moments of the multivariate normal + distribution. Computes a standard representation, LateX code, and values at specified + mean and covariance matrices. + date_publication: '2020-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=symmoments + url_git: '' +symphony: + version: 0.1.1 + title: Efficient and Precise Single-Cell Reference Atlas Mapping + maintainer: Joyce Kang + description: Implements the Symphony single-cell reference building and query mapping + algorithms and additional functions described in Kang et al . + date_publication: '2023-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=symphony + url_git: '' +symptomcheckR: + version: 0.1.3 + title: Analyzing and Visualizing Symptom Checker Performance + maintainer: Marvin Kopka + description: |- + Easily analyze and visualize the performance of symptom + checkers. This package can be used to gain comprehensive insights into + the performance of single symptom checkers or the performance of + multiple symptom checkers. It can be used to easily compare these + symptom checkers across several metrics to gain an understanding of + their strengths and weaknesses. The metrics are developed in + Kopka et al. (2023) . + date_publication: '2024-04-16' + bug_reports: https://github.com/ma-kopka/symptomcheckR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=symptomcheckR + url_git: https://github.com/ma-kopka/symptomcheckR +symSEM: + version: '0.4' + title: Symbolic Computation for Structural Equation Models + maintainer: Mike Cheung + description: |- + A collection of functions for symbolic computation using the + 'caracas' package for structural equation models and other + statistical analyses. Among its features is the ability + to calculate the model-implied covariance (and correlation) + matrix and the sampling covariance matrix of variable functions + using the delta method. + date_publication: '2024-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=symSEM + url_git: https://github.com/mikewlcheung/symsem +SymTS: + version: 1.0-2 + title: Symmetric Tempered Stable Distributions + maintainer: Michael Grabchak + description: Contains methods for simulation and for evaluating the pdf, cdf, and + quantile functions for symmetric stable, symmetric classical tempered stable, + and symmetric power tempered stable distributions. + date_publication: '2023-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SymTS + url_git: '' +syn: + version: 0.1.0 + title: Creates Synonyms From Target Words + maintainer: Nicholas Tierney + description: |- + Generates synonyms from a given word drawing from a synonym list + from the 'moby' project . + date_publication: '2019-12-20' + bug_reports: https://github.com/ropenscilabs/syn/issues + url: http://syn.njtierney.com/ + url_cran: https://CRAN.R-project.org/package=syn + url_git: https://github.com/ropenscilabs/syn +synchronicity: + version: 1.3.10 + title: Boost Mutex Functionality in R + maintainer: Michael J. Kane + description: Boost mutex functionality in R. + date_publication: '2024-01-10' + bug_reports: '' + url: http://www.bigmemory.org + url_cran: https://CRAN.R-project.org/package=synchronicity + url_git: '' +synchrony: + version: 0.3.8 + title: |- + Methods for Computing Spatial, Temporal, and Spatiotemporal + Statistics + maintainer: Tarik C. Gouhier + description: |- + Methods for computing spatial, temporal, and spatiotemporal + statistics as described in Gouhier and Guichard (2014) + . These methods include + empirical univariate, bivariate and multivariate + variograms; fitting variogram models; phase locking and synchrony analysis; + generating autocorrelated and cross-correlated matrices. + date_publication: '2019-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=synchrony + url_git: http://github.com/tgouhier/synchrony +SynchWave: + version: 1.1.2 + title: Synchrosqueezed Wavelet Transform + maintainer: Donghoh Kim + description: 'The synchrosqueezed wavelet transform is implemented. The package + is a translation of MATLAB Synchrosqueezing Toolbox, version 1.1 originally developed + by Eugene Brevdo (2012). The C code for curve_ext was authored by Jianfeng Lu, + and translated to Fortran by Dongik Jang. Synchrosqueezing is based on the papers: + [1] Daubechies, I., Lu, J. and Wu, H. T. (2011) Synchrosqueezed wavelet transforms: + An empirical mode decomposition-like tool. Applied and Computational Harmonic + Analysis, 30. 243-261. [2] Thakur, G., Brevdo, E., Fukar, N. S. and Wu, H-T. (2013) + The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness + properties and new paleoclimate applications. Signal Processing, 93, 1079-1094.' + date_publication: '2022-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SynchWave + url_git: '' +SyncMove: + version: 0.1-0 + title: Subsample Temporal Data to Synchronal Events and Compute the MCI + maintainer: Martin Rimmler + description: The function 'syncSubsample' subsamples temporal data of different + entities so that the result only contains synchronal events. The function 'mci' + calculates the Movement Coordination Index (MCI, see reference on help page for + function 'mci') of a data set created with the function 'syncSubsample'. + date_publication: '2015-10-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SyncMove + url_git: '' +SyncRNG: + version: 1.3.3 + title: A Synchronized Tausworthe RNG for R and Python + maintainer: Gertjan van den Burg + description: Generate the same random numbers in R and Python. + date_publication: '2024-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SyncRNG + url_git: '' +SYNCSA: + version: 1.3.4 + title: |- + Analysis of Functional and Phylogenetic Patterns in + Metacommunities + maintainer: Vanderlei Julio Debastiani + description: |- + Analysis of metacommunities based on functional traits and + phylogeny of the community components. The functions that are offered here + implement for the R environment methods that have been available in the + SYNCSA application written in C++ (by Valerio Pillar, available at + ). + date_publication: '2020-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SYNCSA + url_git: '' +SynDI: + version: 0.1.0 + title: Synthetic Data Integration + maintainer: Michael Kleinsasser + description: |- + Regression inference for multiple populations by integrating + summary-level data using stacked imputations. Gu, T., Taylor, J.M.G. and + Mukherjee, B. (2021) A synthetic data integration framework to leverage + external summary-level information from heterogeneous populations + . + date_publication: '2022-05-25' + bug_reports: https://github.com/umich-biostatistics/SynDI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SynDI + url_git: https://github.com/umich-biostatistics/SynDI +SynergyLMM: + version: 1.0.1 + title: Statistical Framework for in Vivo Drug Combination Studies + maintainer: Rafael Romero-Becerra + description: |- + A framework for evaluating drug combination effects in preclinical in vivo studies. + 'SynergyLMM' provides functions to analyze longitudinal tumor growth experiments using linear mixed-effects models, + perform time-dependent analyses of synergy and antagonism, evaluate model diagnostics and performance, + and assess both post-hoc and a priori statistical power. + The calculation of drug combination synergy follows the statistical framework provided by Demidenko and Miller (2019, ). + The implementation and analysis of linear mixed-effect models is based on the methods described by Pinheiro and Bates (2000, ), + and Gałecki and Burzykowski (2013, ). + date_publication: '2025-02-07' + bug_reports: https://github.com/RafRomB/SynergyLMM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SynergyLMM + url_git: https://github.com/RafRomB/SynergyLMM +synlik: + version: 0.1.6 + title: Synthetic Likelihood Methods for Intractable Likelihoods + maintainer: Matteo Fasiolo + description: |- + Framework to perform synthetic likelihood inference + for models where the likelihood function is unavailable or + intractable. + date_publication: '2023-03-02' + bug_reports: '' + url: http://mfasiolo.github.io/synlik_release/ + url_cran: https://CRAN.R-project.org/package=synlik + url_git: '' +synMicrodata: + version: 2.1.0 + title: Synthetic Microdata Generator + maintainer: Hang J. Kim + description: This tool fits a non-parametric Bayesian model called a "hierarchically + coupled mixture model with local dependence (HCMM-LD)" to the original microdata + in order to generate synthetic microdata for privacy protection. The non-parametric + feature of the adopted model is useful for capturing the joint distribution of + the original input data in a highly flexible manner, leading to the generation + of synthetic data whose distributional features are similar to that of the input + data. The package allows the original input data to have missing values and impute + them with the posterior predictive distribution, so no missing values exist in + the synthetic data output. The method builds on the work of Murray and Reiter + (2016) . + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=synMicrodata + url_git: '' +synr: + version: 1.0.0 + title: Explore and Process Synesthesia Consistency Test Data + maintainer: Lowe Wilsson + description: |- + Explore synesthesia + consistency test data, calculate consistency scores, + and classify participant data as valid or invalid. + date_publication: '2024-01-13' + bug_reports: '' + url: https://datalowe.github.io/synr/ + url_cran: https://CRAN.R-project.org/package=synr + url_git: https://github.com/datalowe/synr +syntaxr: + version: 0.8.0 + title: An 'SPSS' Syntax Generator for Multi-Variable Manipulation + maintainer: Alix Lahuec + description: A set of functions for generating 'SPSS' syntax files from the R environment. + date_publication: '2019-04-06' + bug_reports: https://github.com/greenmeen/syntaxr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=syntaxr + url_git: https://github.com/greenmeen/syntaxr +syntenyPlotteR: + version: 1.0.0 + title: Genome Synteny Visualization + maintainer: Marta Farre + description: |- + Draw syntenic relationships between genome assemblies. + There are 3 functions which take a tab delimited file containing alignment data for + syntenic blocks between genomes to produce either a linear alignment plot, + an evolution highway style plot, or a painted ideogram representing syntenic relationships. + There is also a function to convert alignment data in the DESCHRAMBLER/inferCAR format + to the required data structure. + date_publication: '2023-10-03' + bug_reports: https://github.com/Farre-lab/syntenyPlotteR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=syntenyPlotteR + url_git: '' +Synth: + version: 1.1-8 + title: Synthetic Control Group Method for Comparative Case Studies + maintainer: Jens Hainmueller + description: Implements the synthetic control group method for comparative case + studies as described in Abadie and Gardeazabal (2003) and Abadie, Diamond, and + Hainmueller (2010, 2011, 2014). The synthetic control method allows for effect + estimation in settings where a single unit (a state, country, firm, etc.) is exposed + to an event or intervention. It provides a data-driven procedure to construct + synthetic control units based on a weighted combination of comparison units that + approximates the characteristics of the unit that is exposed to the intervention. + A combination of comparison units often provides a better comparison for the unit + exposed to the intervention than any comparison unit alone. + date_publication: '2023-06-02' + bug_reports: '' + url: https://web.stanford.edu/~jhain/ + url_cran: https://CRAN.R-project.org/package=Synth + url_git: '' +synthesis: + version: 1.2.5 + title: Generate Synthetic Data from Statistical Models + maintainer: Ze Jiang + description: Generate synthetic time series from commonly used statistical models, + including linear, nonlinear and chaotic systems. Applications to testing methods + can be found in Jiang, Z., Sharma, A., & Johnson, F. (2019) + and Jiang, Z., Sharma, A., & Johnson, F. (2020) associated + with an open-source tool by Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. + (2020) . + date_publication: '2024-07-07' + bug_reports: https://github.com/zejiang-unsw/synthesis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=synthesis + url_git: https://github.com/zejiang-unsw/synthesis#readme +synthesisr: + version: 0.3.0 + title: Import, Assemble, and Deduplicate Bibliographic Datasets + maintainer: Martin Westgate + description: |- + A critical first step in systematic literature reviews + and mining of academic texts is to identify relevant texts from a range + of sources, particularly databases such as 'Web of Science' or 'Scopus'. + These databases often export in different formats or with different metadata + tags. 'synthesisr' expands on the tools outlined by Westgate (2019) + to import bibliographic data from a range of formats + (such as 'bibtex', 'ris', or 'ciw') in a standard way, and allows merging + and deduplication of the resulting dataset. + date_publication: '2020-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=synthesisr + url_git: '' +synthesizer: + version: 0.4.0 + title: |- + Synthesize Data Based on Empirical Quantile Functions and Rank + Order Matching + maintainer: Mark van der Loo + description: |- + Data is synthesized using a combination of inverse transform + sampling using the empirical quantile functions for each variable, and + then copying the rank order structure from the original dataset. The + syntesizer method has a tunable parameter allowing to gradually move + from realistic and possibly unsafe synthetic data to decorrelated data + of less utility. + date_publication: '2025-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=synthesizer + url_git: https://github.com/markvanderloo/synthesizer +SynthETIC: + version: 1.1.0 + title: Synthetic Experience Tracking Insurance Claims + maintainer: Melantha Wang + description: |- + Creation of an individual claims simulator which generates various + features of non-life insurance claims. An initial set of test parameters, + designed to mirror the experience of an Auto Liability portfolio, were set + up and applied by default to generate a realistic test data set of + individual claims (see vignette). The simulated data set then allows + practitioners to back-test the validity of various reserving models and to + prove and/or disprove certain actuarial assumptions made in claims + modelling. The distributional assumptions used to generate this data set can + be easily modified by users to match their experiences. Reference: Avanzi B, + Taylor G, Wang M, Wong B (2020) "SynthETIC: an individual insurance claim + simulator with feature control" . + date_publication: '2024-01-27' + bug_reports: https://github.com/agi-lab/SynthETIC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=SynthETIC + url_git: https://github.com/agi-lab/SynthETIC +synthpop: + version: 1.9-0 + title: |- + Generating Synthetic Versions of Sensitive Microdata for + Statistical Disclosure Control + maintainer: Beata Nowok + description: A tool for producing synthetic versions of microdata containing confidential + information so that they are safe to be released to users for exploratory analysis. + The key objective of generating synthetic data is to replace sensitive original + values with synthetic ones causing minimal distortion of the statistical information + contained in the data set. Variables, which can be categorical or continuous, + are synthesised one-by-one using sequential modelling. Replacements are generated + by drawing from conditional distributions fitted to the original data using parametric + or classification and regression trees models. Data are synthesised via the function + syn() which can be largely automated, if default settings are used, or with methods + defined by the user. Optional parameters can be used to influence the disclosure + risk and the analytical quality of the synthesised data. For a description of + the implemented method see Nowok, Raab and Dibben (2016) . + Functions to assess identity and attribute disclosure for the original and for + the synthetic data are included in the package, and their use is illustrated in + a vignette on disclosure (Practical Privacy Metrics for Synthetic Data). + date_publication: '2024-12-20' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=synthpop + url_git: '' +SynthTools: + version: 1.0.1 + title: |- + Tools and Tests for Experiments with Partially Synthetic Data + Sets + maintainer: Charlotte Looby + description: A set of functions to support experimentation in the utility of partially + synthetic data sets. All functions compare an observed data set to one or a set + of partially synthetic data sets derived from the observed data to (1) check that + data sets have identical attributes, (2) calculate overall and specific variable + perturbation rates, (3) check for potential logical inconsistencies, and (4) calculate + confidence intervals and standard errors of desired variables in multiple imputed + data sets. Confidence interval and standard error formulas have options for either + synthetic data sets or multiple imputed data sets. For more information on the + formulas and methods used, see Reiter & Raghunathan (2007) . + date_publication: '2020-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SynthTools + url_git: '' +syrup: + version: 0.1.1 + title: Measure Memory and CPU Usage for Parallel R Code + maintainer: Simon Couch + description: |- + Measures memory and CPU usage of R code by regularly taking + snapshots of calls to the system command 'ps'. The package provides an entry + point (albeit coarse) to profile usage of system resources by R code run + in parallel. + date_publication: '2024-07-18' + bug_reports: https://github.com/simonpcouch/syrup/issues + url: https://simonpcouch.github.io/syrup/ + url_cran: https://CRAN.R-project.org/package=syrup + url_git: https://github.com/simonpcouch/syrup +sys: + version: 3.4.3 + title: Powerful and Reliable Tools for Running System Commands in R + maintainer: Jeroen Ooms + description: |- + Drop-in replacements for the base system2() function with fine control + and consistent behavior across platforms. Supports clean interruption, timeout, + background tasks, and streaming STDIN / STDOUT / STDERR over binary or text + connections. Arguments on Windows automatically get encoded and quoted to work + on different locales. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/sys/issues + url: https://jeroen.r-universe.dev/sys + url_cran: https://CRAN.R-project.org/package=sys + url_git: '' +sysAgNPs: + version: 1.0.0 + title: |- + Systematic Quantification of AgNPs to Unleash their Potential + for Applicability + maintainer: Xiting Wang + description: There is variation across AgNPs due to differences in characterization + techniques and testing metrics employed in studies. To address this problem, we + have developed a systematic evaluation framework called 'sysAgNPs'. Within this + framework, Distribution Entropy (DE) is utilized to measure the uncertainty of feature + categories of AgNPs, Proclivity Entropy (PE) assesses the preference of these + categories, and Combination Entropy (CE) quantifies the uncertainty of feature + combinations of AgNPs. Additionally, a Markov chain model is employed to examine + the relationships among the sub-features of AgNPs and to determine a Transition + Score (TS) scoring standard that is based on steady-state probabilities. The 'sysAgNPs' + framework provides metrics for evaluating AgNPs, which helps to unravel their + complexity and facilitates effective comparisons among different AgNPs, thereby + advancing the scientific research and application of these AgNPs. + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sysAgNPs + url_git: https://github.com/xitingwang-ida/sysAgNPs +SyScSelection: + version: 1.0.2 + title: Systematic Scenario Selection for Stress Testing + maintainer: Merlin Kopfmann + description: |- + Quasi-Monte-Carlo algorithm for systematic generation of shock scenarios from an arbitrary multivariate elliptical distribution. The algorithm selects a systematic mesh of arbitrary fineness that approximately evenly covers an isoprobability ellipsoid in d dimensions (Flood, Mark D. & Korenko, George G. (2013) ). + This package is the 'R' analogy to the 'Matlab' code published by Flood & Korenko in above-mentioned paper. + date_publication: '2020-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SyScSelection + url_git: '' +sysfonts: + version: 0.8.9 + title: Loading Fonts into R + maintainer: Yixuan Qiu + description: |- + Loading system fonts and Google Fonts + into R, in order to + support other packages such as 'R2SWF' and 'showtext'. + date_publication: '2024-03-02' + bug_reports: https://github.com/yixuan/sysfonts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=sysfonts + url_git: https://github.com/yixuan/sysfonts +sysid: + version: 1.0.4 + title: System Identification in R + maintainer: Suraj Yerramilli + description: Provides functions for constructing mathematical models of dynamical + systems from measured input-output data. + date_publication: '2017-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=sysid + url_git: '' +syslognet: + version: 0.1.2.1 + title: Send Log Messages to Remote 'syslog' Server + maintainer: Panagiotis Cheilaris + description: |- + Send 'syslog' protocol messages to a remote 'syslog' server + specified by host name and TCP network port. + date_publication: '2020-01-08' + bug_reports: https://github.com/philaris/syslognet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=syslognet + url_git: https://github.com/philaris/syslognet +Sysrecon: + version: 0.1.3 + title: Systematical Metabolic Reconstruction + maintainer: Shilin Ouyang + description: |- + In the past decade, genome-scale metabolic reconstructions have widely been + used to comprehend the systems biology of metabolic pathways within an organism. + Different GSMs are constructed using various techniques that + require distinct steps, but the input data, information conversion and software tools + are neither concisely defined nor mathematically or programmatically formulated + in a context-specific manner.The tool that quantitatively and qualitatively specifies + each reconstruction steps and can generate a template list of reconstruction steps dynamically + selected from a reconstruction step reservoir, constructed based on all available published papers. + date_publication: '2023-02-20' + bug_reports: '' + url: https://oyshilin.github.io/sysrecon/ + url_cran: https://CRAN.R-project.org/package=Sysrecon + url_git: '' +systemfit: + version: 1.1-30 + title: Estimating Systems of Simultaneous Equations + maintainer: Arne Henningsen + description: |- + Econometric estimation of simultaneous + systems of linear and nonlinear equations using Ordinary Least + Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated + Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted + Two-Stage Least Squares (W2SLS), and Three-Stage Least Squares (3SLS) + as suggested, e.g., by Zellner (1962) , + Zellner and Theil (1962) , and + Schmidt (1990) . + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=systemfit + url_git: https://r-forge.r-project.org/projects/systemfit/ +systemfonts: + version: 1.2.1 + title: System Native Font Finding + maintainer: Thomas Lin Pedersen + description: |- + Provides system native access to the font catalogue. As font + handling varies between systems it is difficult to correctly locate + installed fonts across different operating systems. The 'systemfonts' + package provides bindings to the native libraries on Windows, macOS + and Linux for finding font files that can then be used further by e.g. + graphic devices. The main use is intended to be from compiled code but + 'systemfonts' also provides access from R. + date_publication: '2025-01-20' + bug_reports: https://github.com/r-lib/systemfonts/issues + url: https://systemfonts.r-lib.org + url_cran: https://CRAN.R-project.org/package=systemfonts + url_git: https://github.com/r-lib/systemfonts +SystemicR: + version: 0.1.0 + title: Monitoring Systemic Risk + maintainer: Jean-Baptiste Hasse + description: The past decade has demonstrated an increased need to better understand + risks leading to systemic crises. This framework offers scholars, practitioners + and policymakers a useful toolbox to explore such risks in financial systems. + Specifically, this framework provides popular econometric and network measures + to monitor systemic risk and to measure the consequences of regulatory decisions. + These systemic risk measures are based on the frameworks of Adrian and Brunnermeier + (2016) and Billio, Getmansky, Lo and Pelizzon (2012) + . + date_publication: '2020-05-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=SystemicR + url_git: '' +systemicrisk: + version: 0.4.3 + title: Systemic Risk and Network Reconstruction + maintainer: Axel Gandy + description: Analysis of risk through liability matrices. Contains a Gibbs sampler + for network reconstruction, where only row and column sums of the liabilities + matrix as well as some other fixed entries are observed, following the methodology + of Gandy&Veraart (2016) . It also incorporates models + that use a power law distribution on the degree distribution. + date_publication: '2024-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=systemicrisk + url_git: '' +syt: + version: 0.5.0 + title: Young Tableaux + maintainer: Stéphane Laurent + description: |- + Deals with Young tableaux (field of combinatorics). For standard + Young tabeaux, performs enumeration, counting, random generation, the + Robinson-Schensted correspondence, and conversion to and from paths on + the Young lattice. Also performs enumeration and counting of + semistandard Young tableaux, enumeration of skew semistandard Young + tableaux, enumeration of Gelfand-Tsetlin patterns, and computation of + Kostka numbers. + date_publication: '2024-07-23' + bug_reports: https://github.com/stla/syt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=syt + url_git: https://github.com/stla/syt +syuzhet: + version: 1.0.7 + title: Extracts Sentiment and Sentiment-Derived Plot Arcs from Text + maintainer: Matthew Jockers + description: |- + Extracts sentiment and sentiment-derived plot arcs + from text using a variety of sentiment dictionaries conveniently + packaged for consumption by R users. Implemented dictionaries include + "syuzhet" (default) developed in the Nebraska Literary Lab + "afinn" developed by Finn Årup Nielsen, "bing" developed by Minqing Hu + and Bing Liu, and "nrc" developed by Mohammad, Saif M. and Turney, Peter D. + Applicable references are available in README.md and in the documentation + for the "get_sentiment" function. The package also provides a hack for + implementing Stanford's coreNLP sentiment parser. The package provides + several methods for plot arc normalization. + date_publication: '2023-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=syuzhet + url_git: https://github.com/mjockers/syuzhet +T2DFitTailor: + version: 3.0.0 + title: |- + Tailor the Exercise Plans and Visualize the Outcome for T2D + Patients + maintainer: Cheng Liu + description: A system for personalized exercise plan recommendations for T2D (Type + 2 Diabetes) patients based on the primary outcome of HbA1c (Glycated Hemoglobin). + You provide the individual's information, and 'T2DFitTailor' details the exercise + plan and predicts the intervention's effectiveness. + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=T2DFitTailor + url_git: '' +T2EQ: + version: '1.1' + title: Functions for Applying the T^2-Test for Equivalence + maintainer: Thomas Hoffelder + description: |- + Contains functions for applying the T^2-test for equivalence. + The T^2-test for equivalence is a multivariate two-sample equivalence test. + Distance measure of the test is the Mahalanobis distance. + For multivariate normally distributed data the T^2-test for equivalence + is exact and UMPI. + The function T2EQ() implements the T^2-test for equivalence + according to Wellek (2010) . + The function T2EQ.dissolution.profiles.hoffelder() implements a variant + of the T^2-test for equivalence according to Hoffelder (2016) + for the + equivalence comparison of highly variable dissolution profiles. + date_publication: '2016-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=T2EQ + url_git: '' +T2Qv: + version: 0.2.0 + title: Control Qualitative Variables + maintainer: Wilson Rojas-Preciado + description: Covers k-table control analysis using multivariate control charts for + qualitative variables using fundamentals of multiple correspondence analysis and + multiple factor analysis. The graphs can be shown in a flat or interactive way, + in the same way all the outputs can be shown in an interactive shiny panel. + date_publication: '2023-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=T2Qv + url_git: '' +T4cluster: + version: 0.1.2 + title: Tools for Cluster Analysis + maintainer: Kisung You + description: Cluster analysis is one of the most fundamental problems in data science. + We provide a variety of algorithms from clustering to the learning on the space + of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general + exposition to cluster analysis. + date_publication: '2021-08-16' + bug_reports: https://github.com/kisungyou/T4cluster/issues + url: https://kisungyou.com/T4cluster/ + url_cran: https://CRAN.R-project.org/package=T4cluster + url_git: '' +T4transport: + version: 0.1.2 + title: Tools for Computational Optimal Transport + maintainer: Kisung You + description: Transport theory has seen much success in many fields of statistics + and machine learning. We provide a variety of algorithms to compute Wasserstein + distance, barycenter, and others. See Peyré and Cuturi (2019) + for the general exposition to the study of computational optimal transport. + date_publication: '2023-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=T4transport + url_git: '' +tab: + version: 5.1.1 + title: Create Summary Tables for Statistical Reports + maintainer: Dane R. Van Domelen + description: Contains functions for creating various types of summary tables, e.g. + comparing characteristics across levels of a categorical variable and summarizing + fitted generalized linear models, generalized estimating equations, and Cox proportional + hazards models. Functions are available to handle data from simple random samples + as well as complex surveys. + date_publication: '2021-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tab + url_git: '' +tab2xml: + version: 1.0.0 + title: XML Generation from Tables + maintainer: Jose Samos + description: |- + Converting structured data from tables into XML format using + predefined templates ensures consistency and flexibility, making it + ideal for data exchange, reporting, and automated workflows. + date_publication: '2025-02-21' + bug_reports: https://github.com/josesamos/tab2xml/issues + url: https://josesamos.github.io/tab2xml/ + url_cran: https://CRAN.R-project.org/package=tab2xml + url_git: https://github.com/josesamos/tab2xml +Taba: + version: 1.0.0 + title: Taba Robust Correlations + maintainer: Derek Wilus + description: |- + Calculates the robust Taba linear, Taba rank (monotonic), TabWil, and TabWil rank + correlations. Test statistics as well as one sided or two sided p-values are provided + for all correlations. Multiple correlations and p-values can be calculated + simultaneously across multiple variables. In addition, users will have the option to use + the partial, semipartial, and generalized partial correlations; where the partial and + semipartial correlations use linear, logistic, or Poisson regression to modify the specified + variable. + date_publication: '2021-03-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Taba + url_git: '' +tabbycat: + version: 0.18.0 + title: Tabulate and Summarise Categorical Data + maintainer: Oliver Hawkins + description: |- + Functions for tabulating and summarising categorical variables. + Most functions are designed to work with dataframes, and use the 'tidyverse' + idiom of taking the dataframe as the first argument so they work within + pipelines. Equivalent functions that operate directly on vectors are also + provided where it makes sense. This package aims to make exploratory data + analysis involving categorical variables quicker, simpler and more robust. + date_publication: '2023-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tabbycat + url_git: '' +taber: + version: 0.1.2 + title: Split and Recombine Your Data + maintainer: Seth Wenchel + description: Sometimes you need to split your data and work on the two chunks independently + before bringing them back together. 'Taber' allows you to do that with its two + functions. + date_publication: '2020-10-04' + bug_reports: https://github.com/restonslacker/taber/issues + url: '' + url_cran: https://CRAN.R-project.org/package=taber + url_git: https://github.com/restonslacker/taber +tabit: + version: 0.2.1 + title: Simple Tabulation Made Simple + maintainer: Peter Meissner + description: |- + Simple tabulation should be dead simple. + This package is an opinionated approach to easy tabulations while also + providing exact numbers and allowing for re-usability. + This is achieved by providing tabulations as data.frames with columns for + values, optional variable names, frequency counts including and excluding + NAs and percentages for counts including and excluding NAs. Also values are + automatically sorted by in decreasing order of frequency counts to allow for + fast skimming of the most important information. + date_publication: '2020-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tabit + url_git: '' +tablaxlsx: + version: 1.2.5 + title: Write Formatted Tables in Excel Workbooks + maintainer: Jesus Maria Rodriguez Rodriguez + description: For writing tables with custom formats in a Excel file ready to be + distributed. + date_publication: '2023-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tablaxlsx + url_git: '' +table.express: + version: 0.4.2 + title: Build 'data.table' Expressions with Data Manipulation Verbs + maintainer: Alexis Sarda-Espinosa + description: |- + A specialization of 'dplyr' data manipulation verbs that parse and build expressions + which are ultimately evaluated by 'data.table', letting it handle all optimizations. A set of + additional verbs is also provided to facilitate some common operations on a subset of the data. + date_publication: '2023-04-02' + bug_reports: https://github.com/asardaes/table.express/issues + url: https://asardaes.github.io/table.express/ + url_cran: https://CRAN.R-project.org/package=table.express + url_git: https://github.com/asardaes/table.express +table.glue: + version: 0.0.5 + title: Make and Apply Customized Rounding Specifications for Tables + maintainer: Byron Jaeger + description: |- + Translate double and integer valued data into + character values formatted for tabulation in manuscripts + or other types of academic reports. + date_publication: '2024-11-21' + bug_reports: https://github.com/bcjaeger/table.glue/issues + url: '' + url_cran: https://CRAN.R-project.org/package=table.glue + url_git: https://github.com/bcjaeger/table.glue +table1: + version: 1.4.3 + title: Tables of Descriptive Statistics in HTML + maintainer: Benjamin Rich + description: |- + Create HTML tables of descriptive statistics, as one would expect + to see as the first table (i.e. "Table 1") in a medical/epidemiological journal + article. + date_publication: '2023-01-06' + bug_reports: https://github.com/benjaminrich/table1/issues + url: '' + url_cran: https://CRAN.R-project.org/package=table1 + url_git: https://github.com/benjaminrich/table1 +Table1Heatmap: + version: '1.2' + title: Table 1 Heatmap + maintainer: Philip C Schouten + description: |- + Table 1 is the classical way to describe the patients in a + clinical study. The amount of splits in the data in such a table is + limited. Table1Heatmap draws a heatmap of all crosstables that can be + generated with the data. Users can choose between showing the actual + crosstables or direction of effect of associations, and highlight + associations by number of patients or p-values. + v1.2 - fixed "missing "no visible global function definition for .." + date_publication: '2022-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Table1Heatmap + url_git: '' +tablecompare: + version: 0.1.1 + title: Compare Data Frames + maintainer: Ryan Dickerson + description: A toolbox for comparing two data frames. This package is defunct. I + recommend you use the "versus" package instead. + date_publication: '2023-11-14' + bug_reports: https://github.com/eutwt/tablecompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tablecompare + url_git: https://github.com/eutwt/tablecompare +tabledown: + version: 1.0.0 + title: Create Publication Quality Tables and Plots + maintainer: Mushfiqul Anwar Siraji + description: Create publication quality plots and tables for Item Response Theory + and Classical Test theory based item analysis, exploratory and confirmatory factor + analysis. + date_publication: '2024-05-02' + bug_reports: https://github.com/masiraji/tabledown/issues + url: https://masiraji.github.io/tabledown/ + url_cran: https://CRAN.R-project.org/package=tabledown + url_git: '' +tableeasy: + version: 1.1.2 + title: Tables of Clinical Study + maintainer: Jian Hang Zheng + description: Creates some tables of clinical study. 'Table 1' is created by table1() + to describe baseline characteristics, which is essential in every clinical study. + Created by table2(), the function of 'Table 2' is to explore influence factors. + And 'Table 3' created by table3() is able to make stratified analysis. + date_publication: '2022-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tableeasy + url_git: '' +TableHC: + version: 0.1.2 + title: Higher Criticism Test of Two Frequency Counts Tables + maintainer: Alon Kipnis + description: Higher Criticism (HC) test between two frequency tables. Test is based + on an adaptation of the Tukey-Donoho-Jin HC statistic to testing frequency tables + described in Kipnis (2019) . + date_publication: '2020-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TableHC + url_git: '' +tableHTML: + version: 2.1.2 + title: A Tool to Create HTML Tables + maintainer: Theo Boutaris + description: |- + A tool to create and style HTML tables with CSS. These can + be exported and used in any application that accepts HTML (e.g. 'shiny', + 'rmarkdown', 'PowerPoint'). It also provides functions to create CSS files + (which also work with shiny). + date_publication: '2023-04-17' + bug_reports: https://github.com/LyzandeR/tableHTML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tableHTML + url_git: https://github.com/LyzandeR/tableHTML +tableMatrix: + version: 0.82.0 + title: Combines 'data.table' and 'matrix' Classes + maintainer: Petr Lenhard + description: |- + Provides two classes extending 'data.table' class. Simple + 'tableList' class wraps 'data.table' and any additional structures together. + More complex 'tableMatrix' class combines 'data.table' and + 'matrix'. See for more + information and examples. + date_publication: '2018-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tableMatrix + url_git: '' +TableMonster: + version: 1.7.6 + title: Table Monster + maintainer: Grant Izmirlian + description: |- + Provides a user friendly interface to + generation of booktab style tables using 'xtable'. + date_publication: '2025-01-14' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=TableMonster + url_git: '' +tableone: + version: 0.13.2 + title: |- + Create 'Table 1' to Describe Baseline Characteristics with or + without Propensity Score Weights + maintainer: Kazuki Yoshida + description: |- + Creates 'Table 1', i.e., description of baseline patient + characteristics, which is essential in every medical research. + Supports both continuous and categorical variables, as well as + p-values and standardized mean differences. Weighted data are + supported via the 'survey' package. + date_publication: '2022-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tableone + url_git: https://github.com/kaz-yos/tableone +tablerDash: + version: 0.1.5 + title: '''Tabler'' API for ''Shiny''' + maintainer: David Granjon + description: |- + 'R' interface to the 'Tabler' HTML template. See more here . + 'tablerDash' is a light 'Bootstrap 4' dashboard template. There are different + layouts available such as a one page dashboard or a multi page template, + where the navigation menu is contained in the navigation bar. + date_publication: '2024-09-26' + bug_reports: https://github.com/RinteRface/tablerDash/issues + url: https://rinterface.github.io/tablerDash/ + url_cran: https://CRAN.R-project.org/package=tablerDash + url_git: https://github.com/RinteRface/tablerDash/ +tables: + version: 0.9.31 + title: Formula-Driven Table Generation + maintainer: Duncan Murdoch + description: |- + Computes and displays complex tables of summary statistics. + Output may be in LaTeX, HTML, plain text, or an R + matrix for further processing. + date_publication: '2024-08-29' + bug_reports: https://github.com/dmurdoch/tables/issues + url: https://dmurdoch.github.io/tables/ + url_cran: https://CRAN.R-project.org/package=tables + url_git: '' +tablesgg: + version: 0.9-1 + title: Presentation-Quality Tables, Displayed Using 'ggplot2' + maintainer: Richard Raubertas + description: |- + Presentation-quality tables are displayed as plots on an R + graphics device. Although there are other packages that format tables + for display, this package is unique in combining two features: (a) It is + aware of the logical structure of the table being presented, and makes + use of that for automatic layout and styling of the table. This avoids + the need for most manual adjustments to achieve an attractive result. + (b) It displays tables using 'ggplot2' graphics. Therefore a table can + be presented anywhere a graph could be, with no more effort. External + software such as LaTeX or HTML or their viewers is not required. The + package provides a full set of tools to control the style and appearance + of tables, including titles, footnotes and reference marks, horizontal + and vertical rules, and spacing of rows and columns. Methods are included + to display matrices; data frames; tables created by R's ftable(), table(), + and xtabs() functions; and tables created by the 'tables' and 'xtable' + packages. Methods can be added to display other table-like objects. A + vignette is included that illustrates usage and options available in the + package. + date_publication: '2024-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tablesgg + url_git: https://github.com/rrprf/tablesgg +tablespan: + version: 0.2.1 + title: |- + Create Satisficing 'Excel', 'HTML', 'LaTeX', and 'RTF' Tables + using a Simple Formula + maintainer: Jannik H. Orzek + description: |- + Create "good enough" tables with a single formula. 'tablespan' tables + can be exported to 'Excel', 'HTML', 'LaTeX', and 'RTF' by leveraging + the packages 'openxlsx' and 'gt'. See for + an introduction. + date_publication: '2025-01-28' + bug_reports: https://github.com/jhorzek/tablespan/issues + url: https://jhorzek.github.io/tablespan/ + url_cran: https://CRAN.R-project.org/package=tablespan + url_git: https://github.com/jhorzek/tablespan +tablet: + version: 0.6.12 + title: Tabulate Descriptive Statistics in Multiple Formats + maintainer: Tim Bergsma + description: |- + Creates a table of descriptive statistics + for factor and numeric columns in a data frame. Displays + these by groups, if any. Highly customizable, with support + for 'html' and 'pdf' provided by 'kableExtra'. Respects + original column order, column labels, and factor level order. + See ?tablet.data.frame and vignettes. + date_publication: '2024-11-14' + bug_reports: https://github.com/bergsmat/tablet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tablet + url_git: '' +TableToLongForm: + version: 1.3.2 + title: |- + Automatically Convert Hierarchical for-Human Tables to + Machine-Readable LongForm Dataframes + maintainer: Jimmy Oh + description: A wrapper to a set of algorithms designed to recognise positional cues + present in hierarchical for-human Tables (which would normally be interpreted + visually by the human brain) to decompose, then reconstruct the data into machine-readable + LongForm Dataframes. + date_publication: '2019-01-10' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~joh024/Research/TableToLongForm/ + url_cran: https://CRAN.R-project.org/package=TableToLongForm + url_git: '' +tablexlsx: + version: 1.1.0 + title: Export Data Frames to Excel Workbook + maintainer: Damien Dotta + description: Collection of functions that allow to export data frames to excel workbook. + date_publication: '2024-10-16' + bug_reports: https://github.com/ddotta/tablexlsx/issues + url: https://ddotta.github.io/tablexlsx/ + url_cran: https://CRAN.R-project.org/package=tablexlsx + url_git: https://github.com/ddotta/tablexlsx +tabnet: + version: 0.6.0 + title: Fit 'TabNet' Models for Classification and Regression + maintainer: Christophe Regouby + description: |- + Implements the 'TabNet' model by Sercan O. Arik et al. (2019) + with 'Coherent Hierarchical Multi-label + Classification Networks' by Giunchiglia et al. and + provides a consistent interface for fitting and creating predictions. + It's also fully compatible with the 'tidymodels' ecosystem. + date_publication: '2024-06-15' + bug_reports: https://github.com/mlverse/tabnet/issues + url: https://mlverse.github.io/tabnet/ + url_cran: https://CRAN.R-project.org/package=tabnet + url_git: https://github.com/mlverse/tabnet +taboolaR: + version: 0.1.0 + title: Get Data from 'Taboola' via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from 'Taboola' using + the 'Windsor.ai' API . + date_publication: '2022-11-16' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=taboolaR + url_git: '' +tabr: + version: 0.5.1 + title: |- + Music Notation Syntax, Manipulation, Analysis and Transcription + in R + maintainer: Matthew Leonawicz + description: |- + Provides a music notation syntax and a collection of music + programming functions for generating, manipulating, organizing, and analyzing + musical information in R. Music syntax can be entered directly in character + strings, for example to quickly transcribe short pieces of music. The + package contains functions for directly performing various mathematical, + logical and organizational operations and musical transformations on special + object classes that facilitate working with music data and notation. The + same music data can be organized in tidy data frames for a familiar and + powerful approach to the analysis of large amounts of structured music data. + Functions are available for mapping seamlessly between these formats and + their representations of musical information. The package also provides an + API to 'LilyPond' () for transcribing musical + representations in R into tablature ("tabs") and sheet music. 'LilyPond' is + open source music engraving software for generating high quality sheet music + based on markup syntax. The package generates 'LilyPond' files from R code + and can pass them to the 'LilyPond' command line interface to be rendered + into sheet music PDF files or inserted into R markdown documents. The + package offers nominal MIDI file output support in conjunction with + rendering sheet music. The package can read MIDI files and attempts to + structure the MIDI data to integrate as best as possible with the data + structures and functionality found throughout the package. + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/tabr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabr + url_git: https://github.com/leonawicz/tabr +tabshiftr: + version: 0.4.1 + title: Reshape Disorganised Messy Data + maintainer: Steffen Ehrmann + description: |- + Helps the user to build and register schema descriptions of + disorganised (messy) tables. Disorganised tables are tables that are + not in a topologically coherent form, where packages such as 'tidyr' could + be used for reshaping. The schema description documents the arrangement of + input tables and is used to reshape them into a standardised (tidy) output + format. + date_publication: '2023-01-31' + bug_reports: https://github.com/luckinet/tabshiftr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabshiftr + url_git: https://github.com/luckinet/tabshiftr +tabula: + version: 3.2.0 + title: Analysis and Visualization of Archaeological Count Data + maintainer: Nicolas Frerebeau + description: |- + An easy way to examine archaeological count data. This + package provides several tests and measures of diversity: + heterogeneity and evenness (Brillouin, Shannon, Simpson, etc.), + richness and rarefaction (Chao1, Chao2, ACE, ICE, etc.), turnover and + similarity (Brainerd-Robinson, etc.). It allows to easily visualize + count data and statistical thresholds: rank vs abundance plots, + heatmaps, Ford (1962) and Bertin (1977) diagrams, etc. + date_publication: '2025-01-10' + bug_reports: https://github.com/tesselle/tabula/issues + url: https://packages.tesselle.org/tabula/ + url_cran: https://CRAN.R-project.org/package=tabula + url_git: https://github.com/tesselle/tabula +tabulapdf: + version: 1.0.5-5 + title: Extract Tables from PDF Documents + maintainer: Mauricio Vargas Sepulveda + description: |- + Bindings for the 'Tabula' 'Java' + library, which can extract tables from PDF files. This tool can reduce time + and effort in data extraction processes in fields like investigative + journalism. It allows for automatic and manual table extraction, the latter + facilitated through a 'Shiny' interface, enabling manual areas selection\ + with a computer mouse for data retrieval. + date_publication: '2024-11-15' + bug_reports: https://github.com/ropensci/tabulapdf/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=tabulapdf + url_git: https://docs.ropensci.org/tabulapdf/(website)https://github.com/ropensci/tabulapdf/ +tabularaster: + version: 0.7.2 + title: Tidy Tools for 'Raster' Data + maintainer: Michael D. Sumner + description: |- + Facilities to work with vector and raster data in efficient + repeatable and systematic work flow. Missing functionality in existing packages + is included here to allow extraction from raster data with 'simple features' and + 'Spatial' types and to make extraction consistent and straightforward. Extract cell + numbers from raster data and return the cells as a data frame + rather than as lists of matrices or vectors. The functions here allow spatial data + to be used without special handling for the format currently in use. + date_publication: '2023-11-01' + bug_reports: https://github.com/hypertidy/tabularaster/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabularaster + url_git: https://github.com/hypertidy/tabularaster +tabularmaps: + version: 0.1.0 + title: Create Tile-Grid Geographical Maps + maintainer: Shinya Uryu + description: |- + The 'tabularmap' is one of the visualization methods for + efficiently displaying data consisting of multiple elements by tiling them. + When dealing with geospatial, it corrects for differences in visibility + between areas. + date_publication: '2020-08-04' + bug_reports: https://github.com/uribo/tabularmaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabularmaps + url_git: https://github.com/uribo/tabularmaps +tabularMLC: + version: 0.0.3 + title: Tabular Maximum Likelihood Classifier + maintainer: Caio Hamamura + description: |2- + + The maximum likelihood classifier (MLC) is one of the most common classifiers used for + remote sensing imagery. + This package uses 'RcppArmadillo' to provide a fast implementation of the MLC to train + and predict over tabular data (data.frame). + The algorithms were based on Mather (1985) method. + date_publication: '2021-10-05' + bug_reports: https://github.com/caiohamamura/tabularMLC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabularMLC + url_git: https://github.com/caiohamamura/tabularMLC +tabulate: + version: 0.1.0 + title: Pretty Console Output for Tables + maintainer: Daniel Falbel + description: |- + Generates pretty console output for tables allowing for full customization + of cell colors, font type, borders and many others attributes. It also supports 'multibyte' + characters and nested tables. + date_publication: '2022-02-16' + bug_reports: https://github.com/mlverse/tabulate/issues + url: https://mlverse.github.io/tabulate/ + url_cran: https://CRAN.R-project.org/package=tabulate + url_git: https://github.com/mlverse/tabulate +tabulator: + version: 1.0.0 + title: Efficient Tabulation with Stata-Like Output + maintainer: Sean Higgins + description: |- + Efficient tabulation with Stata-like output. + For each unique value of the variable, it shows the number of + observations with that value, proportion of observations with that + value, and cumulative proportion, in descending order of frequency. + Accepts data.table, tibble, or data.frame as input. + Efficient with big data: if you give it a data.table, + tab() uses data.table syntax. + date_publication: '2021-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tabulator + url_git: '' +tabulog: + version: 0.1.1 + title: Parsing Semi-Structured Log Files into Tabular Format + maintainer: Austin Nar + description: |- + Convert semi-structured log files (such as 'Apache' access.log files) + into a tabular format (data.frame) using a standard template system. + date_publication: '2019-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tabulog + url_git: '' +tabuSearch: + version: 1.1.1 + title: Tabu Search Algorithm for Binary Configurations + maintainer: Katarina Domijan + description: Tabu search algorithm for binary configurations. A basic version of + the algorithm as described by Fouskakis and Draper (2007) . + date_publication: '2018-03-25' + bug_reports: https://gitlab.com/domijank/tabuSearch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabuSearch + url_git: '' +tabxplor: + version: 1.2.1 + title: User-Friendly Tables with Color Helpers for Data Exploration + maintainer: Brice Nocenti + description: |- + Make it easy to deal with multiple cross-tables in data exploration, by + creating them, manipulating them, and adding color helpers to highlight + important informations (differences from totals, comparisons between lines or + columns, contributions to variance, confidence intervals, odds ratios, etc.). + All functions are pipe-friendly and render data frames which can be easily + manipulated. In the same time, time-taking operations are done with 'data.table' + to go faster with big dataframes. Tables can be exported with formats and colors + to 'Excel', plot and html. + date_publication: '2024-10-04' + bug_reports: https://github.com/BriceNocenti/tabxplor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tabxplor + url_git: https://github.com/BriceNocenti/tabxplor +tacmagic: + version: 0.3.1 + title: Positron Emission Tomography Time-Activity Curve Analysis + maintainer: Eric Brown + description: |- + To facilitate the analysis of positron emission tomography (PET) + time activity curve (TAC) data, and to encourage open science and + replicability, this package supports data loading and analysis of multiple + TAC file formats. Functions are available to analyze loaded TAC data for + individual participants or in batches. Major functionality includes weighted + TAC merging by region of interest (ROI), calculating models including + standardized uptake value ratio (SUVR) and distribution volume ratio (DVR, + Logan et al. 1996 ), basic plotting + functions and calculation of cut-off values (Aizenstein et al. 2008 + ). Please see the walkthrough vignette for + a detailed overview of 'tacmagic' functions. + date_publication: '2020-12-09' + bug_reports: https://github.com/ropensci/tacmagic + url: '' + url_cran: https://CRAN.R-project.org/package=tacmagic + url_git: https://github.com/ropensci/tacmagic +tactile: + version: 0.2.1 + title: |- + New and Extended Plots, Methods, and Panel Functions for + 'lattice' + maintainer: Johan Larsson + description: |- + Extensions to 'lattice', providing new high-level + functions, methods for existing functions, panel functions, and a theme. + date_publication: '2023-05-24' + bug_reports: https://github.com/jolars/tactile/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tactile + url_git: https://github.com/jolars/tactile +TAD: + version: 1.0.0 + title: Realize the Trait Abundance Distribution + maintainer: Lain Pavot + description: 'This analytical framework is based on an analysis of the shape of + the trait abundance distributions to better understand community assembly processes, + and predict community dynamics under environmental changes. This framework mobilized + a study of the relationship between the moments describing the shape of the distributions: + the skewness and the kurtosis (SKR). The SKR allows the identification of commonalities + in the shape of trait distributions across contrasting communities. Derived from + the SKR, we developed mathematical parameters that summarise the complex pattern + of distributions by assessing (i) the R², (ii) the Y-intercept, (iii) the slope, + (iv) the functional stability of community (TADstab), and, (v) the distance from + specific distribution families (i.e., the distance from the skew-uniform family + a limit to the highest degree of evenness: TADeve).' + date_publication: '2024-11-28' + bug_reports: https://forgemia.inra.fr/urep/data_processing/tad/-/issues + url: https://forgemia.inra.fr/urep/data_processing/tad + url_cran: https://CRAN.R-project.org/package=TAD + url_git: '' +tada: + version: 2024.1.0 + title: Supporting Tools for Tada Science + maintainer: Romain François + description: |- + Suite of tools to support the practice of tada science. It includes an + engaging package roulette that is designed to facilitate learning about + new packages. + date_publication: '2024-02-02' + bug_reports: https://github.com/tadascience/tada/issues + url: https://tada.tada.science/ + url_cran: https://CRAN.R-project.org/package=tada + url_git: https://github.com/tadascience/tada +TAF: + version: 4.2.0 + title: Transparent Assessment Framework for Reproducible Research + maintainer: Arni Magnusson + description: |- + Functions to organize data, methods, and results used in scientific + analyses. A TAF analysis consists of four scripts (data.R, model.R, output.R, + report.R) that are run sequentially. Each script starts by reading files from + a previous step and ends with writing out files for the next step. Convenience + functions are provided to version control the required data and software, run + analyses, clean residues from previous runs, manage files, manipulate tables, + and produce figures. With a focus on stability and reproducible analyses, TAF + is designed to have no package dependencies. TAF forms a base layer for the + 'icesTAF' package and other scientific applications. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TAF + url_git: https://github.com/ices-tools-prod/TAF +TAG: + version: 0.5.1 + title: Transformed Additive Gaussian Processes + maintainer: Li-Hsiang Lin + description: Implement the transformed additive Gaussian (TAG) process and the transformed + approximately additive Gaussian (TAAG) process proposed in Lin and Joseph (2020) + . These functions can be used to model deterministic + computer experiments, obtain predictions at new inputs, and quantify the uncertainty + of the predictions. This research is supported by a U.S. National Science Foundation + grant DMS-1712642 and a U.S. Army Research Office grant W911NF-17-1-0007. + date_publication: '2021-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TAG + url_git: '' +tagcloud: + version: '0.6' + title: Tag Clouds + maintainer: January Weiner + description: Generating Tag and Word Clouds. + date_publication: '2015-07-03' + bug_reports: '' + url: http://logfc.wordpress.com + url_cran: https://CRAN.R-project.org/package=tagcloud + url_git: '' +tagr: + version: 1.0.1 + title: Tagging and Organizing Objects in R + maintainer: Joachim Zuckarelli + description: |2- + + Provides functions for attaching tags to R objects, + searching for objects based on tags, and removing tags from objects. + It also includes a function for removing all tags from an object, as well + as a function for deleting all objects with a specific tag from the R + environment. The package is useful for organizing and managing large + collections of objects in R. + date_publication: '2023-09-03' + bug_reports: https://github.com/jsugarelli/tagr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tagr + url_git: https://github.com/jsugarelli/tagr/ +tagtools: + version: 0.2.0 + title: Work with Data from High-Resolution Biologging Tags + maintainer: Stacy DeRuiter + description: |- + High-resolution movement-sensor tags typically include accelerometers + to measure body posture and sudden movements or changes in speed, + magnetometers to measure direction of travel, and pressure sensors + to measure dive depth in aquatic or marine animals. The sensors in these tags usually sample many times per second. Some tags include sensors for speed, turning rate (gyroscopes), and sound. This package provides software tools to facilitate calibration, processing, and analysis of such data. Tools are provided for: data import/export; + calibration (from raw data to calibrated data in scientific units); + visualization (for example, multi-panel time-series plots); + data processing (such as event detection, calculation of derived metrics like jerk and + dynamic acceleration, dive detection, and dive parameter calculation); and statistical analysis (for example, track reconstruction, a rotation test, and Mahalanobis distance analysis). + date_publication: '2024-06-28' + bug_reports: https://github.com/animaltags/tagtools_r/issues + url: + url_cran: https://CRAN.R-project.org/package=tagtools + url_git: '' +TailClassifier: + version: 0.1.2 + title: Tail Classifier + maintainer: Jialin Zhang (JZ) + description: 'The function TailClassifier() suggests one of the following types + of tail for your discrete data: 1) Power decaying tail; 2) Sub-exponential decaying + tail; and 3) Near-exponential decaying tail. The function also provides an estimate + of the parameter for the classified-distribution as a reference.' + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TailClassifier + url_git: '' +tailDepFun: + version: 1.0.1 + title: Minimum Distance Estimation of Tail Dependence Models + maintainer: Anna Kiriliouk + description: |- + Provides functions implementing minimal distance estimation methods for parametric tail dependence models, as proposed in + Einmahl, J.H.J., Kiriliouk, A., Krajina, A., and Segers, J. (2016) and + Einmahl, J.H.J., Kiriliouk, A., and Segers, J. (2018) . + date_publication: '2021-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tailDepFun + url_git: '' +tailloss: + version: '1.0' + title: |- + Estimate the Probability in the Upper Tail of the Aggregate Loss + Distribution + maintainer: Isabella Gollini + description: 'Set of tools to estimate the probability in the upper tail of the + aggregate loss distribution using different methods: Panjer recursion, Monte Carlo + simulations, Markov bound, Cantelli bound, Moment bound, and Chernoff bound.' + date_publication: '2015-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tailloss + url_git: http://github.com/igollini/tailloss +TailRank: + version: 3.2.2 + title: The Tail-Rank Statistic + maintainer: Kevin R. Coombes + description: |- + Implements the tail-rank statistic for selecting biomarkers + from a microarray data set, an efficient nonparametric test focused + on the distributional tails. See + . + date_publication: '2022-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TailRank + url_git: http://oompa.r-forge.r-project.org/ +tailTransform: + version: 1.0.4 + title: Symmetric Transformation of Tails for Plotting Differences + maintainer: Paul R. Rosenbaum + description: When plotting treated-minus-control differences, after-minus-before + changes, or difference-in-differences, the ttrans() function symmetrically transforms + the positive and negative tails to aid plotting. The package includes an observational + study with three control groups and an unaffected outcome; see Rosenbaum (2020) + . + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tailTransform + url_git: '' +taipan: + version: 0.1.2 + title: Tool for Annotating Images in Preparation for Analysis + maintainer: Stephanie Kobakian + description: |- + A tool to help create shiny apps for selecting and annotating + elements of images. Users must supply images, questions, and answer + choices. The user interface is a dynamic shiny app, that displays the images + and questions and answer choices. The data generated can be saved to a + file that can be used for subsequent analysis. The original purpose was to + annotate still images from tennis video for face recognition and emotion + detection purposes. + date_publication: '2018-09-27' + bug_reports: https://github.com/srkobakian/taipan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=taipan + url_git: https://github.com/srkobakian/taipan +takos: + version: 0.2.0 + title: Analysis of Differential Calorimetry Scans + maintainer: Serena Berretta + description: It includes functions for applying methodologies utilized for single-process + kinetic analysis of solid-state processes were recently summarized and described + in the Recommendation of ICTAC Kinetic Committee. These methods work with the + basic kinetic equation. The Methodologies included refers to Avrami, Friedman, + Kissinger, Ozawa, OFM, Mo, Starink, isoconversional methodology (Vyazovkin) according + to ICATAC Kinetics Committee recommendations as reported in Vyazovkin S, Chrissafis + K, Di Lorenzo ML, et al. ICTAC Kinetics Committee recommendations for collecting + experimental thermal analysis data for kinetic computations. Thermochim Acta. + 2014;590:1-23. . + date_publication: '2020-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=takos + url_git: https://github.com/sere3s/takos +talkr: + version: 0.1.3 + title: Plotting Conversation Data + maintainer: Mark Dingemanse + description: |- + Visualisation, analysis and quality control of conversational data. + Rapid and visual insights into the nature, timing and quality of + time-aligned annotations in conversational corpora. + For more details, see + Dingemanse et al., (2022) . + date_publication: '2024-11-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=talkr + url_git: '' +tall: + version: 0.1.0 + title: Text Analysis for All + maintainer: Massimo Aria + description: |- + An R 'shiny' app designed for diverse text analysis tasks, offering a wide range of methodologies tailored to Natural Language Processing (NLP) needs. + It is a versatile, general-purpose tool for analyzing textual data. + 'tall' features a comprehensive workflow, including data cleaning, preprocessing, statistical analysis, and visualization, all integrated for effective text analysis. + date_publication: '2025-02-06' + bug_reports: https://github.com/massimoaria/tall/issues + url: https://www.k-synth.com/tall/ + url_cran: https://CRAN.R-project.org/package=tall + url_git: https://github.com/massimoaria/tall +TAM: + version: 4.2-21 + title: Test Analysis Modules + maintainer: Alexander Robitzsch + description: |2- + + Includes marginal maximum likelihood estimation and joint maximum + likelihood estimation for unidimensional and multidimensional + item response models. The package functionality covers the + Rasch model, 2PL model, 3PL model, generalized partial credit model, + multi-faceted Rasch model, nominal item response model, + structured latent class model, mixture distribution IRT models, + and located latent class models. Latent regression models and + plausible value imputation are also supported. For details see + Adams, Wilson and Wang, 1997 , + Adams, Wilson and Wu, 1997 , + Formann, 1982 , + Formann, 1992 . + date_publication: '2024-02-19' + bug_reports: '' + url: http://www.edmeasurementsurveys.com/TAM/Tutorials/ + url_cran: https://CRAN.R-project.org/package=TAM + url_git: https://github.com/alexanderrobitzsch/TAM +tame: + version: 0.0.1 + title: |- + Timing, Anatomical, Therapeutic and Chemical Based Medication + Clustering + maintainer: Anna Laksafoss + description: |- + Agglomerative hierarchical clustering with a bespoke distance + measure based on medication similarities in the Anatomical Therapeutic + Chemical Classification System, medication timing and + medication amount or dosage. Tools for summarizing, illustrating and + manipulating the cluster objects are also available. + date_publication: '2023-02-23' + bug_reports: https://github.com/Laksafoss/tame/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tame + url_git: '' +tanaka: + version: 0.4.0 + title: Design Shaded Contour Lines (or Tanaka) Maps + maintainer: Timothée Giraud + description: |- + The Tanaka method enhances the representation of topography on + a map using shaded contour lines. In this simplified implementation of + the method, north-west white contours represent illuminated topography + and south-east black contours represent shaded topography. See Tanaka + (1950) . + date_publication: '2023-11-28' + bug_reports: https://github.com/riatelab/tanaka/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=tanaka + url_git: https://github.com/riatelab/tanaka/ +TANDEM: + version: 1.0.3 + title: |- + A Two-Stage Approach to Maximize Interpretability of Drug + Response Models Based on Multiple Molecular Data Types + maintainer: Nanne Aben + description: A two-stage regression method that can be used when various input data + types are correlated, for example gene expression and methylation in drug response + prediction. In the first stage it uses the upstream features (such as methylation) + to predict the response variable (such as drug response), and in the second stage + it uses the downstream features (such as gene expression) to predict the residuals + of the first stage. In our manuscript (Aben et al., 2016, ), + we show that using TANDEM prevents the model from being dominated by gene expression + and that the features selected by TANDEM are more interpretable. + date_publication: '2019-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TANDEM + url_git: '' +TangledFeatures: + version: 0.1.1 + title: Feature Selection in Highly Correlated Spaces + maintainer: Allen Sunny + description: |- + Feature selection algorithm that extracts features in highly + correlated spaces. The extracted features are meant to be fed into + simple explainable models such as linear or logistic regressions. The + package is useful in the field of explainable modelling as a + way to understand variable behavior. + date_publication: '2023-02-14' + bug_reports: '' + url: https://allen-1242.github.io/TangledFeatures/ + url_cran: https://CRAN.R-project.org/package=TangledFeatures + url_git: '' +TangPoemR: + version: 0.1.0 + title: Write Chinese Tang Poems + maintainer: Yongyuan Liang + description: Write Chinese Tang Poems automatically. + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TangPoemR + url_git: '' +tangram: + version: 0.8.2 + title: The Grammar of Tables + maintainer: Shawn Garbett + description: |- + Provides an extensible formula system to quickly and easily create + production quality tables. The processing steps are a formula parser, + statistical content generation from data as defined by formula, followed by + rendering into a table. Each step of the processing is separate and user + definable thus creating a set of composable building blocks for + highly customizable table generation. A user is not limited by any of the + choices of the package creator other than the formula grammar. For example, + one could chose to add a different S3 rendering function and output a format + not provided in the default package, or possibly one would rather have Gini + coefficients for their statistical content in a resulting table. Routines to + achieve New England Journal of Medicine style, Lancet style and + Hmisc::summaryM() statistics are provided. The package contains rendering + for HTML5, Rmarkdown and an indexing format for use in tracing and tracking + are provided. + date_publication: '2023-01-26' + bug_reports: https://github.com/spgarbet/tangram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tangram + url_git: https://github.com/spgarbet/tangram +tangram.pipe: + version: 1.1.2 + title: Row-by-Row Table Building + maintainer: Andrew Guide + description: |- + Builds tables with customizable rows. Users can specify the type + of data to use for each row, as well as how to handle missing + data and the types of comparison tests to run on the table + columns. + date_publication: '2022-08-17' + bug_reports: https://github.com/thomasgstewart/tangram.pipe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tangram.pipe + url_git: https://github.com/thomasgstewart/tangram.pipe +TapeR: + version: 0.5.3 + title: Flexible Tree Taper Curves Based on Semiparametric Mixed Models + maintainer: Christian Vonderach + description: |- + Implementation of functions for fitting taper curves (a semiparametric + linear mixed effects taper model) to diameter measurements along stems. Further + functions are provided to estimate the uncertainty around the predicted curves, + to calculate timber volume (also by sections) and marginal (e.g., upper) diameters. + For cases where tree heights are not measured, methods for estimating + additional variance in volume predictions resulting from uncertainties in + tree height models (tariffs) are provided. The example data include the taper + curve parameters for Norway spruce used in the 3rd German NFI fitted to 380 trees + and a subset of section-wise diameter measurements of these trees. The functions + implemented here are detailed in Kublin, E., Breidenbach, J., Kaendler, G. (2013) + . + date_publication: '2023-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TapeR + url_git: '' +TapeS: + version: 0.13.3 + title: Tree Taper Curves and Sorting Based on 'TapeR' + maintainer: Christian Vonderach + description: |- + Providing new german-wide 'TapeR' Models and functions for their + evaluation. Included are the most common tree species in Germany (Norway + spruce, Scots pine, European larch, Douglas fir, Silver fir as well as + European beech, Common/Sessile oak and Red oak). Many other species are mapped + to them so that 36 tree species / groups can be processed. Single trees are + defined by species code, one or multiple diameters in arbitrary measuring + height and tree height. The functions then provide information on diameters + along the stem, bark thickness, height of diameters, volume of the total or + parts of the trunk and total and component above-ground biomass. It is also + possible to calculate assortments from the taper curves. Uncertainty + information is provided for diameter, volume and component biomass estimation. + date_publication: '2025-02-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TapeS + url_git: https://gitlab.com/vochr/tapes +tapkee: + version: '1.2' + title: Wrapper for 'tapkee' Dimension Reduction Library + maintainer: Alexey Shipunov + description: |- + Wrapper for using 'tapkee' command line utility, + it allows to run it from inside R and catch the results for further analysis and plotting. + 'Tapkee' is a program for fast dimension reduction, see 'package?tapkee' and + for installation and other details. + date_publication: '2021-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tapkee + url_git: '' +tapLock: + version: 0.2.0 + title: Seamless Single Sign-on for 'shiny' + maintainer: Andres Quintero + description: |- + Swift and seamless Single Sign-On (SSO) integration. Designed + for effortless compatibility with popular Single Sign-On providers + like Google and Microsoft, it streamlines authentication, enhancing + both user experience and application security. Elevate your 'shiny' + applications for a simplified, unified, and secure authentication process. + date_publication: '2024-10-28' + bug_reports: https://github.com/ixpantia/tapLock/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tapLock + url_git: https://github.com/ixpantia/tapLock +tapnet: + version: '0.3' + title: Trait Matching and Abundance for Predicting Bipartite Networks + maintainer: Carsten Dormann + description: Functions to produce, fit and predict from bipartite networks with + abundance, trait and phylogenetic information. Its methods are described in detail + in Benadi, G., Dormann, C.F., Fruend, J., Stephan, R. & Vazquez, D.P. (2021) Quantitative + prediction of interactions in bipartite networks based on traits, abundances, + and phylogeny. The American Naturalist, in press. + date_publication: '2021-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tapnet + url_git: https://github.com/biometry/tapnet +TAQMNGR: + version: 2018.5-1 + title: Manage Tick-by-Tick Transaction Data + maintainer: Fabrizio Cipollini + description: Manager of tick-by-tick transaction data that performs 'cleaning', + 'aggregation' and 'import' in an efficient and fast way. The package engine, written + in C++, exploits the 'zlib' and 'gzstream' libraries to handle gzipped data without + need to uncompress them. 'Cleaning' and 'aggregation' are performed according + to Brownlees and Gallo (2006) . Currently, TAQMNGR + processes raw data from WRDS (Wharton Research Data Service, ). + date_publication: '2018-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TAQMNGR + url_git: '' +TAR: + version: '1.0' + title: Bayesian Modeling of Autoregressive Threshold Time Series Models + maintainer: Hanwen Zhang + description: 'Identification and estimation of the autoregressive threshold models + with Gaussian noise, as well as positive-valued time series. The package provides + the identification of the number of regimes, the thresholds and the autoregressive + orders, as well as the estimation of remain parameters. The package implements + the methodology from the 2005 paper: Modeling Bivariate Threshold Autoregressive + Processes in the Presence of Missing Data .' + date_publication: '2017-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TAR + url_git: '' +tarchetypes: + version: 0.12.0 + title: Archetypes for Targets + maintainer: William Michael Landau + description: |- + Function-oriented Make-like declarative pipelines for + Statistics and data science are supported in the 'targets' R package. + As an extension to 'targets', the 'tarchetypes' package provides + convenient user-side functions to make 'targets' easier to use. + By establishing reusable archetypes for common kinds of + targets and pipelines, these functions help express complicated + reproducible pipelines concisely and compactly. + The methods in this package were influenced by the 'targets' R package. + by Will Landau (2018) . + date_publication: '2025-01-31' + bug_reports: https://github.com/ropensci/tarchetypes/issues + url: https://docs.ropensci.org/tarchetypes/ + url_cran: https://CRAN.R-project.org/package=tarchetypes + url_git: https://github.com/ropensci/tarchetypes +tardis: + version: 0.1.4 + title: |- + Text Analysis with Rules and Dictionaries for Inferring + Sentiment + maintainer: Christopher Belanger + description: |- + Measure text's sentiment with dictionaries and simple rules covering + negations and modifiers. User-supplied dictionaries are supported, including + Unicode emojis and multi-word tokens, so this package can also be used to + study constructs beyond sentiment. + date_publication: '2022-11-18' + bug_reports: https://github.com/chris31415926535/tardis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tardis + url_git: https://github.com/chris31415926535/tardis +targeted: + version: '0.5' + title: Targeted Inference + maintainer: Klaus K. Holst + description: |- + Various methods for targeted and semiparametric inference including + augmented inverse probability weighted (AIPW) estimators for missing data and + causal inference (Bang and Robins (2005) ), + variable importance and conditional average treatment effects (CATE) + (van der Laan (2006) ), + estimators for risk differences and relative risks (Richardson et al. (2017) + ), assumption lean inference for generalized + linear model parameters (Vansteelandt et al. (2022) ). + date_publication: '2024-02-22' + bug_reports: https://github.com/kkholst/targeted/issues + url: '' + url_cran: https://CRAN.R-project.org/package=targeted + url_git: '' +targets: + version: 1.10.1 + title: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines + maintainer: William Michael Landau + description: |- + Pipeline tools coordinate the pieces of computationally + demanding analysis projects. + The 'targets' package is a 'Make'-like pipeline tool for statistics and + data science in R. The package skips costly runtime for tasks + that are already up to date, + orchestrates the necessary computation with implicit parallel computing, + and abstracts files as R objects. If all the current output matches + the current upstream code and data, then the whole pipeline is up + to date, and the results are more trustworthy than otherwise. + The methodology in this package + borrows from GNU 'Make' (2015, ISBN:978-9881443519) + and 'drake' (2018, ). + date_publication: '2025-01-31' + bug_reports: https://github.com/ropensci/targets/issues + url: https://docs.ropensci.org/targets/ + url_cran: https://CRAN.R-project.org/package=targets + url_git: https://github.com/ropensci/targets +Tariff: + version: 1.0.5 + title: Replicate Tariff Method for Verbal Autopsy + maintainer: Zehang Li + description: Implement the Tariff algorithm for coding cause-of-death from verbal + autopsies. The Tariff method was originally proposed in James et al (2011) + and later refined as Tariff 2.0 in Serina, et al. (2015) . + Note that this package was not developed by authors affiliated with the Institute + for Health Metrics and Evaluation and thus unintentional discrepancies may exist + between the this implementation and the implementation available from IHME. + date_publication: '2018-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tariff + url_git: '' +TAShiny: + version: 0.1.0 + title: '''Text Analyzer Shiny''' + maintainer: Kartikeya Bolar + description: Interactive shiny application for working with textmining and text + analytics. Various visualizations are provided. + date_publication: '2018-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TAShiny + url_git: '' +tashu: + version: 0.1.1 + title: Analysis and Prediction of Bicycle Rental Amount + maintainer: Jiwon Min + description: |- + Provides functions for analyzing citizens' bicycle usage pattern and predicting rental amount on specific conditions. + Functions on this package interacts with data on 'tashudata' package, a 'drat' repository. + 'tashudata' package contains rental/return history on public bicycle system('Tashu'), weather for 3 years and bicycle station information. + To install this data package, see the instructions at . + top10_stations(), top10_paths() function visualizes image showing the most used top 10 stations and paths. + daily_bike_rental() and monthly_bike_rental() shows daily, monthly amount of bicycle rental. + create_train_dataset(), create_test_dataset() is data processing function for prediction. + Bicycle rental history from 2013 to 2014 is used to create training dataset and that on 2015 is for test dataset. + Users can make random-forest prediction model by using create_train_model() + and predict amount of bicycle rental in 2015 by using predict_bike_rental(). + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tashu + url_git: '' +tastypie: + version: 0.1.1 + title: Easy Pie Charts + maintainer: Paolo Dalena + description: |- + You only need to type 'why pie charts are bad' on Google to find + thousands of articles full of (valid) reasons why other types of charts + should be preferred over this one. + Therefore, because of the little use due to the reasons already mentioned, + making pie charts (and related) in R is not straightforward, so other + functions are needed to simplify things. + In this R package there are useful functions to make 'tasty' pie charts + immediately by exploiting the many cool templates provided. + date_publication: '2023-09-06' + bug_reports: https://github.com/PaoloDalena/tastypie/issues + url: https://paolodalena.github.io/tastypie/ + url_cran: https://CRAN.R-project.org/package=tastypie + url_git: '' +tatest: + version: '1.0' + title: Two-Group Ta-Test + maintainer: Yuan-De Tan + description: The ta-test is a modified two-sample or two-group t-test of Gosset + (1908). In small samples with less than 15 replicates,the ta-test significantly + reduces type I error rate but has almost the same power with the t-test and hence + can greatly enhance reliability or reproducibility of discoveries in biology and + medicine. The ta-test can test single null hypothesis or multiple null hypotheses + without needing to correct p-values. + date_publication: '2018-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tatest + url_git: '' +tatoo: + version: 1.1.2 + title: Combine and Export Data Frames + maintainer: Stefan Fleck + description: |2- + + Functions to combine data.frames in ways that require additional effort in + base R, and to add metadata (id, title, ...) that can be used for printing and + xlsx export. The 'Tatoo_report' class is provided as a + convenient helper to write several such tables to a workbook, one table per + worksheet. Tatoo is built on top of 'openxlsx', but intimate knowledge of + that package is not required to use tatoo. + date_publication: '2023-03-26' + bug_reports: https://github.com/statistikat/tatoo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tatoo + url_git: https://github.com/statistikat/tatoo +tatooheene: + version: 0.19.0 + title: |- + Technology Appraisal Toolbox for Health Economic Evaluations in + the Netherlands + maintainer: Stijn Peeters + description: |- + Functions to support economic modelling in R based on the methods of the + Dutch guideline for economic evaluations in healthcare , + CBS data , and OECD data . + date_publication: '2024-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tatooheene + url_git: '' +tau: + version: 0.0-26 + title: Text Analysis Utilities + maintainer: Kurt Hornik + description: Utilities for text analysis. + date_publication: '2024-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tau + url_git: '' +tauProcess: + version: 2.1.3 + title: Tau Measure with Right-Censored Data + maintainer: Yi-Cheng Tai + description: |- + A clinically meaningful measures of treatment effects for right-censored data + are provided, based on the concept of Kendall's tau, along with the corresponding inference procedures. + Two plots of tau processes, with the option to account for the cure fraction or not, are available. + The plots of tau processes serve as useful graphical tools for monitoring the relative performances over time. + date_publication: '2023-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tauProcess + url_git: https://github.com/s07308/tauProcess +TauStar: + version: 1.1.7 + title: |- + Efficient Computation and Testing of the Bergsma-Dassios Sign + Covariance + maintainer: Julian D. Karch + description: |- + Computes the t* statistic corresponding to the tau* population + coefficient introduced by Bergsma and Dassios (2014) + and does so in O(n^2) time following the algorithm of Heller and + Heller (2016) building off of the work of Weihs, + Drton, and Leung (2016) . Also allows for + independence testing using the asymptotic distribution of t* as described by + Nandy, Weihs, and Drton (2016) . + date_publication: '2024-12-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TauStar + url_git: '' +tauturri: + version: 0.3.0 + title: Get Data Out of 'Tautulli' (Formerly 'PlexPy') + maintainer: Lukas Burk + description: |- + 'Tautulli' () is a monitoring application for 'Plex' Media Servers + () which collects a lot of data about media items and server + usage such as play counts. This package interacts with the 'Tautulli' API of any + specified server to get said data into R. The 'Tautulli' API documentation is available + at . + date_publication: '2018-07-11' + bug_reports: https://github.com/jemus42/tauturri/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tauturri + url_git: https://github.com/jemus42/tauturri +taxa: + version: 0.4.3 + title: Classes for Storing and Manipulating Taxonomic Data + maintainer: Zachary Foster + description: |- + Provides classes for storing and manipulating taxonomic data. + Most of the classes can be treated like base R vectors (e.g. can be used + in tables as columns and can be named). Vectorized classes can store taxon names + and authorities, taxon IDs from databases, taxon ranks, and other types of + information. More complex classes are provided to store taxonomic trees and + user-defined data associated with them. + date_publication: '2024-02-20' + bug_reports: https://github.com/ropensci/taxa/issues + url: https://docs.ropensci.org/taxa/ + url_cran: https://CRAN.R-project.org/package=taxa + url_git: https://github.com/ropensci/taxa +taxadb: + version: 0.2.1 + title: A High-Performance Local Taxonomic Database Interface + maintainer: Carl Boettiger + description: |- + Creates a local database of many commonly used taxonomic authorities + and provides functions that can quickly query this data. + date_publication: '2023-03-09' + bug_reports: https://github.com/ropensci/taxadb/issues + url: + url_cran: https://CRAN.R-project.org/package=taxadb + url_git: +taxalight: + version: 0.1.5 + title: A Lightweight and Lightning-Fast Taxonomic Naming Interface + maintainer: Carl Boettiger + description: |- + Creates a local Lightning Memory-Mapped Database ('LMDB') + of many commonly used taxonomic authorities + and provides functions that can quickly query this data. + Supported taxonomic authorities include + the Integrated Taxonomic Information System ('ITIS'), + National Center for Biotechnology Information ('NCBI'), + Global Biodiversity Information Facility ('GBIF'), + Catalogue of Life ('COL'), and Open Tree Taxonomy ('OTT'). + Name and identifier resolution using 'LMDB' can + be hundreds of times faster than either relational databases or + internet-based queries. Precise data provenance information for + data derived from naming providers is also included. + date_publication: '2021-09-14' + bug_reports: https://github.com/cboettig/taxalight + url: '' + url_cran: https://CRAN.R-project.org/package=taxalight + url_git: https://github.com/cboettig/taxalight +TaxaNorm: + version: '2.4' + title: Feature-Wise Normalization for Microbiome Sequencing Data + maintainer: Dillon Lloyd + description: A novel feature-wise normalization method based on a zero-inflated + negative binomial model. This method assumes that the effects of sequencing depth + vary for each taxon on their mean and also incorporates a rational link of zero + probability and taxon dispersion as a function of sequencing depth. Ziyue Wang, + Dillon Lloyd, Shanshan Zhao, Alison Motsinger-Reif (2023) . + date_publication: '2023-12-12' + bug_reports: https://github.com/wangziyue57/TaxaNorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TaxaNorm + url_git: https://github.com/wangziyue57/TaxaNorm +TaxicabCA: + version: 0.1.1 + title: Taxicab Correspondence Analysis + maintainer: Jacques Allard + description: 'Computation and visualization of Taxicab Correspondence Analysis, + Choulakian (2006) . Classical correspondence analysis + (CA) is a statistical method to analyse 2-dimensional tables of positive numbers + and is typically applied to contingency tables (Benzecri, J.-P. (1973). L''Analyse + des Donnees. Volume II. L''Analyse des Correspondances. Paris, France: Dunod). Classical + CA is based on the Euclidean distance. Taxicab CA is like classical CA but is + based on the Taxicab or Manhattan distance. For some tables, Taxicab CA gives + more informative results than classical CA.' + date_publication: '2019-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TaxicabCA + url_git: '' +taxize: + version: 0.10.0 + title: Taxonomic Information from Around the Web + maintainer: Zachary Foster + description: |- + Interacts with a suite of web application programming interfaces + (API) for taxonomic tasks, such as getting database specific taxonomic + identifiers, verifying species names, getting taxonomic hierarchies, fetching + downstream and upstream taxonomic names, getting taxonomic synonyms, converting + scientific to common names and vice versa, and more. Some of the services + supported include 'NCBI E-utilities' (), + 'Encyclopedia of Life' (), + 'Global Biodiversity Information Facility' (), + and many more. Links to the API documentation for other supported services are + available in the documentation for their respective functions in this package. + date_publication: '2025-02-07' + bug_reports: https://github.com/ropensci/taxize/issues + url: https://docs.ropensci.org/taxize/(website) + url_cran: https://CRAN.R-project.org/package=taxize + url_git: https://github.com/ropensci/taxize(devel) +taxlist: + version: 0.3.0 + title: Handling Taxonomic Lists + maintainer: Miguel Alvarez + description: |- + Handling taxonomic lists through objects of class 'taxlist'. + This package provides functions to import species lists from 'Turboveg' + () and the possibility to create + backups from resulting R-objects. + Also quick displays are implemented as summary-methods. + date_publication: '2024-07-03' + bug_reports: https://github.com/ropensci/taxlist/issues + url: https://docs.ropensci.org/taxlist/ + url_cran: https://CRAN.R-project.org/package=taxlist + url_git: https://github.com/ropensci/taxlist +taxnames: + version: 0.1.0 + title: Formatting Taxonomic Names in Markdown + maintainer: Miguel Alvarez + description: |- + A collection of functions used to format taxonomic names in Markdown + documents. Those functions work with data structured according to + Alvarez and Luebert (2018) . + date_publication: '2024-07-08' + bug_reports: https://github.com/kamapu/taxnames/issues + url: '' + url_cran: https://CRAN.R-project.org/package=taxnames + url_git: https://github.com/kamapu/taxnames +taxonomizr: + version: 0.10.8 + title: Functions to Work with NCBI Accessions and Taxonomy + maintainer: Scott Sherrill-Mix + description: Functions for assigning taxonomy to NCBI accession numbers and taxon + IDs based on NCBI's accession2taxid and taxdump files. This package allows the + user to download NCBI data dumps and create a local database for fast and local + taxonomic assignment. + date_publication: '2025-02-27' + bug_reports: https://github.com/sherrillmix/taxonomizr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=taxonomizr + url_git: https://github.com/sherrillmix/taxonomizr/ +taylor: + version: 3.2.0 + title: Lyrics and Song Data for Taylor Swift's Discography + maintainer: W. Jake Thompson + description: |- + A comprehensive resource for data on Taylor Swift songs. Data + is included for all officially released studio albums, extended plays + (EPs), and individual singles are included. Data comes from 'Genius' + (lyrics) and 'Spotify' (song characteristics). Additional functions + are included for easily creating data visualizations with color + palettes inspired by Taylor Swift's album covers. + date_publication: '2025-01-07' + bug_reports: https://github.com/wjakethompson/taylor/issues + url: https://taylor.wjakethompson.com + url_cran: https://CRAN.R-project.org/package=taylor + url_git: https://github.com/wjakethompson/taylor +TaylorRussell: + version: 1.2.1 + title: A Taylor-Russell Function for Multiple Predictors + maintainer: Niels Waller + description: 'The Taylor Russell model is a widely used method for assessing test + validity in personnel selection tasks. The three functions in this package extend + this model in a number of notable ways. TR() estimates test validity for a single + selection test via the original Taylor Russell model. It extends this model by + allowing users greater flexibility in argument choice. For example, users can + specify any three of the four parameters (base rate, selection ratio, criterion + validity, and positive predictive value) of the Taylor Russell model and estimate + the remaining parameter (see the help file for examples). The TaylorRussell() + function generalizes the original Taylor Russell model to allow for multiple selection + tests (predictors). To our knowledge, this is the first generalization of the + Taylor Russell model to allow for three or more selection tests (it is also the + first to correctly handle models with two selection tests). TRDemo() is a ''shiny'' + program for illustrating the underlying logic of the Taylor Russell model. Taylor, + HC and Russell, JT (1939) "The relationship of validity coefficients to the practical + effectiveness of tests in selection: Discussion and tables" .' + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TaylorRussell + url_git: '' +tayloRswift: + version: 0.1.0 + title: Color Palettes Generated by Taylor Swift Albums + maintainer: Alex Stephenson + description: For when your colors absolutely should not be excluded from the narrative. + date_publication: '2021-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tayloRswift + url_git: '' +tbd: + version: 0.1.0 + title: Estimation of Causal Effects with Outcomes Truncated by Death + maintainer: Zhixuan Shao + description: Estimation of the survivor average causal effect under outcomes truncated + by death, which requires the existence of a substitution variable. It can be applied + to both experimental and observational data. + date_publication: '2019-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tbd + url_git: https://github.com/KillingVectorField/causal-inference-truncated-by-death +tbea: + version: 1.5.0 + title: Pre- And Post-Processing in Bayesian Evolutionary Analyses + maintainer: Gustavo A. Ballen + description: |- + Functions are provided for prior specification in divergence time + estimation using fossils as well as other kinds of data. It + provides tools for interacting with the input and output of Bayesian + platforms in evolutionary biology such as 'BEAST2', 'MrBayes', 'RevBayes', + or 'MCMCTree'. + It Implements a simple measure similarity between probability + density functions for comparing prior and + posterior Bayesian densities, as well as code for calculating the + combination of distributions using conflation of Hill (2008). Functions for estimating the + origination time in collections of distributions using the x-intercept (e.g., Draper and Smith, 1998) and + stratigraphic intervals (Marshall 2010) are also available. + Hill, T. 2008. "Conflations of probability distributions". Transactions of the American Mathematical Society, 363:3351-3372. , + Draper, N. R. and Smith, H. 1998. "Applied Regression Analysis". 1--706. Wiley Interscience, New York. , + Marshall, C. R. 2010. "Using confidence intervals to quantify the uncertainty in the end-points of stratigraphic ranges". Quantitative Methods in Paleobiology, 291--316. . + date_publication: '2024-07-01' + bug_reports: https://github.com/gaballench/tbea/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tbea + url_git: https://github.com/gaballench/tbea +TBEST: + version: '5.2' + title: Tree Branches Evaluated Statistically for Tightness + maintainer: Guoli Sun + description: Our method introduces mathematically well-defined measures for tightness + of branches in a hierarchical tree. Statistical significance of the findings is + determined, for all branches of the tree, by performing permutation tests, optionally + with generalized Pareto p-value estimation. + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TBEST + url_git: '' +TBFmultinomial: + version: 0.1.3 + title: TBF Methodology Extension for Multinomial Outcomes + maintainer: Rachel Heyard + description: Extends the test-based Bayes factor (TBF) methodology to multinomial + regression models and discrete time-to-event models with competing risks. The + TBF methodology has been well developed and implemented for the generalised linear + model [Held et al. (2015) ] and for the Cox model [Held + et al. (2016) ]. + date_publication: '2018-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TBFmultinomial + url_git: '' +tbl2xts: + version: 1.0.4 + title: Convert Tibbles or Data Frames to Xts Easily + maintainer: Nico Katzke + description: |- + Facilitate the movement between data frames to 'xts'. Particularly + useful when moving from 'tidyverse' to the widely used 'xts' package, which is + the input format of choice to various other packages. It also allows the user + to use a 'spread_by' argument for a character column 'xts' conversion. + date_publication: '2021-01-12' + bug_reports: https://github.com/nicktz/tbl2xts/issues + url: https://tbl2xts.nfkatzke.com + url_cran: https://CRAN.R-project.org/package=tbl2xts + url_git: '' +tbm: + version: 0.3-6 + title: Transformation Boosting Machines + maintainer: Torsten Hothorn + description: Boosting the likelihood of conditional and shift transformation models + as introduced in \doi{10.1007/s11222-019-09870-4}. + date_publication: '2024-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tbm + url_git: http://ctm.R-forge.R-project.org +tboot: + version: 0.2.1 + title: Tilted Bootstrap + maintainer: Nathan Morris + description: Creates simulated clinical trial data with realistic correlation structures + and assumed efficacy levels by using a tilted bootstrap resampling approach. Samples + are drawn from observed data with some samples appearing more frequently than + others. May also be used for simulating from a joint Bayesian distribution along + with clinical trials based on the Bayesian distribution. + date_publication: '2020-12-02' + bug_reports: https://github.com/njm18/tboot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tboot + url_git: https://github.com/njm18/tboot +TBox: + version: 0.1.2 + title: Useful Functions for Programming and Generating Documents + maintainer: Tanguy Barthelemy + description: Tools to help developers and producers manipulate R objects and outputs. + It includes tools for displaying results and objects, and for formatting them + in the correct format. + date_publication: '2024-06-14' + bug_reports: https://github.com/TanguyBarthelemy/TBox/issues + url: https://tanguybarthelemy.github.io/TBox/ + url_cran: https://CRAN.R-project.org/package=TBox + url_git: https://github.com/TanguyBarthelemy/TBox +TBRDist: + version: 1.0.2 + title: Rearrangement Distances Between Unrooted Phylogenetic Trees + maintainer: Martin R. Smith + description: |- + Fast calculation of the Subtree Prune and Regraft (SPR), + Tree Bisection and Reconnection (TBR) and Replug distances between + unrooted trees, using the algorithms of Whidden and + Matsen (2017) . + date_publication: '2020-09-17' + bug_reports: https://github.com/ms609/TBRDist/issues/ + url: https://ms609.github.io/TBRDist/ + url_cran: https://CRAN.R-project.org/package=TBRDist + url_git: https://github.com/ms609/TBRDist/ +tbrf: + version: 0.1.5 + title: Time-Based Rolling Functions + maintainer: Michael Schramm + description: |- + Provides rolling statistical functions based + on date and time windows instead of n-lagged observations. + date_publication: '2020-04-09' + bug_reports: https://github.com/mps9506/tbrf/issues + url: https://mps9506.github.io/tbrf/ + url_cran: https://CRAN.R-project.org/package=tbrf + url_git: '' +TCA: + version: 1.2.1 + title: Tensor Composition Analysis + maintainer: Elior Rahmani + description: Tensor Composition Analysis (TCA) allows the deconvolution of two-dimensional + data (features by observations) coming from a mixture of heterogeneous sources + into a three-dimensional matrix of signals (features by observations by sources). + The TCA framework further allows to test the features in the data for different + statistical relations with an outcome of interest while modeling source-specific + effects; particularly, it allows to look for statistical relations between source-specific + signals and an outcome. For example, TCA can deconvolve bulk tissue-level DNA + methylation data (methylation sites by individuals) into a three-dimensional tensor + of cell-type-specific methylation levels for each individual (i.e. methylation + sites by individuals by cell types) and it allows to detect cell-type-specific + statistical relations (associations) with phenotypes. For more details see Rahmani + et al. (2019) . + date_publication: '2021-02-14' + bug_reports: https://github.com/cozygene/TCA/issues + url: https://www.nature.com/articles/s41467-019-11052-9 + url_cran: https://CRAN.R-project.org/package=TCA + url_git: '' +tcftt: + version: 0.1.0 + title: Two-Sample Tests for Skewed Data + maintainer: Huaiyu Zhang + description: |- + The classical two-sample t-test works well for the normally distributed data or + data with large sample size. The tcfu() and tt() tests implemented in this package provide + better type-I-error control with more accurate power when testing the equality of two-sample + means for skewed populations having unequal variances. These tests are especially useful + when the sample sizes are moderate. The tcfu() uses the Cornish-Fisher expansion to achieve + a better approximation to the true percentiles. The tt() provides transformations of the Welch's + t-statistic so that the sampling distribution become more symmetric. For more technical details, + please refer to Zhang (2019) . + date_publication: '2020-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tcftt + url_git: '' +TCGAretriever: + version: 1.9.1 + title: |- + Retrieve Genomic and Clinical Data from CBioPortal Including + TCGA Data + maintainer: Damiano Fantini + description: The Cancer Genome Atlas (TCGA) is a program aimed at improving our + understanding of Cancer Biology. Several TCGA Datasets are available online. 'TCGAretriever' + helps accessing and downloading TCGA data hosted on 'cBioPortal' via its Web Interface + (see for more information). + date_publication: '2024-01-23' + bug_reports: '' + url: https://www.data-pulse.com/dev_site/TCGAretriever/ + url_cran: https://CRAN.R-project.org/package=TCGAretriever + url_git: '' +tcgaViz: + version: 1.0.2 + title: Visualization Tool for the Cancer Genome Atlas Program (TCGA) + maintainer: Etienne Camenen + description: |- + Differential analysis of tumor tissue immune cell type + abundance based on RNA-seq gene-level expression from The Cancer + Genome Atlas (TCGA; ) database. + date_publication: '2023-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tcgaViz + url_git: '' +TcGSA: + version: 0.12.10 + title: Time-Course Gene Set Analysis + maintainer: Boris P Hejblum + description: |- + Implementation of Time-course Gene Set Analysis (TcGSA), a method for + analyzing longitudinal gene-expression data at the gene set level. Method is + detailed in: Hejblum, Skinner & Thiebaut (2015) . + date_publication: '2022-02-28' + bug_reports: https://github.com/sistm/TcGSA/issues + url: http://sistm.github.io/TcGSA/ + url_cran: https://CRAN.R-project.org/package=TcGSA + url_git: '' +TCHazaRds: + version: 1.1.2 + title: Tropical Cyclone (Hurricane, Typhoon) Spatial Hazard Modelling + maintainer: Julian O'Grady + description: Methods for generating modelled parametric Tropical Cyclone (TC) spatial + hazard fields and time series output at point locations from TC tracks. R's compatibility + to simply use fast 'cpp' code via the 'Rcpp' package and the wide range spatial + analysis tools via the 'terra' package makes it an attractive open source environment + to study 'TCs'. This package estimates TC vortex wind and pressure fields using + parametric equations originally coded up in 'python' by 'TCRM' + and then coded up in 'Cuda' 'cpp' by 'TCwindgen' . + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TCHazaRds + url_git: https://github.com/AusClimateService/TCHazaRds +tci: + version: 0.2.0 + title: Target Controlled Infusion (TCI) + maintainer: Ryan Jarrett + description: Implementation of target-controlled infusion algorithms for compartmental + pharmacokinetic and pharmacokinetic-pharmacodynamic models. Jacobs (1990) ; + Marsh et al. (1991) ; Shafer and Gregg (1993) ; + Schnider et al. (1998) ; Abuhelwa, Foster, + and Upton (2015) ; Eleveld et al. (2018) . + date_publication: '2022-08-15' + bug_reports: https://github.com/jarretrt/tci/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tci + url_git: https://github.com/jarretrt/tci +TCIApathfinder: + version: 1.0.6 + title: Client for the Cancer Imaging Archive REST API + maintainer: Pamela Russell + description: |- + A wrapper for The Cancer Imaging Archive's REST API. The Cancer + Imaging Archive (TCIA) hosts de-identified medical images of cancer + available for public download, as well as rich metadata for each image + series. TCIA provides a REST API for programmatic access to the data. + This package provides simple functions to access each API endpoint. + For more information, see + and TCIA's website. + date_publication: '2019-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TCIApathfinder + url_git: '' +TCIU: + version: 1.2.7 + title: Spacekime Analytics, Time Complexity and Inferential Uncertainty + maintainer: Yueyang Shen + description: |- + Provide the core functionality to transform longitudinal data to + complex-time (kime) data using analytic and numerical techniques, visualize the original + time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression) + and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021) + "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series, + ISBN 978-3-11-069780-3. . + The package includes 18 core functions which can be separated into three groups. + 1) draw longitudinal data, such as Functional magnetic resonance imaging(fMRI) time-series, and forecast or transform the time-series data. + 2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas, + report the corresponding p-values, and visualize the p-values in the 3D brain space. + 3) Laplace transform and kimesurface reconstructions of the fMRI data. + date_publication: '2024-09-15' + bug_reports: https://github.com/SOCR/TCIU/issues + url: https://www.socr.umich.edu/spacekime/ + url_cran: https://CRAN.R-project.org/package=TCIU + url_git: https://github.com/SOCR/TCIU +tcl: + version: 0.2.1 + title: Testing in Conditional Likelihood Context + maintainer: Clemens Draxler + description: |- + An implementation of hypothesis testing in an extended Rasch modeling framework, + including sample size planning procedures and power computations. Provides 4 statistical tests, + i.e., gradient test (GR), likelihood ratio test (LR), Rao score or Lagrange multiplier test (RS), + and Wald test, for testing a number of hypotheses referring to the Rasch model (RM), linear + logistic test model (LLTM), rating scale model (RSM), and partial credit model (PCM). Three + types of functions for power and sample size computations are provided. Firstly, functions to + compute the sample size given a user-specified (predetermined) deviation from the hypothesis + to be tested, the level alpha, and the power of the test. Secondly, functions to evaluate the + power of the tests given a user-specified (predetermined) deviation from the hypothesis to be + tested, the level alpha of the test, and the sample size. Thirdly, functions to evaluate the + so-called post hoc power of the tests. This is the power of the tests given the observed + deviation of the data from the hypothesis to be tested and a user-specified level alpha of the + test. Power and sample size computations are based on a Monte Carlo simulation approach. It is + computationally very efficient. The variance of the random error in computing power and sample + size arising from the simulation approach is analytically derived by using the delta method. + Draxler, C., & Alexandrowicz, R. W. (2015), . + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tcl + url_git: '' +tcltk2: + version: 1.2-11 + title: Tcl/Tk Additions + maintainer: Philippe Grosjean + description: |- + A series of additional Tcl commands and Tk widgets with style + and various functions (under Windows: DDE exchange, access to the + registry and icon manipulation) to supplement the tcltk package + date_publication: '2014-12-20' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=194 + url: http://www.sciviews.org/SciViews-R + url_cran: https://CRAN.R-project.org/package=tcltk2 + url_git: '' +tclust: + version: 2.1-0 + title: Robust Trimmed Clustering + maintainer: Valentin Todorov + description: |- + Provides functions for robust trimmed clustering. The methods are + described in Garcia-Escudero (2008) , + Fritz et al. (2012) , + Garcia-Escudero et al. (2011) and others. + date_publication: '2025-02-19' + bug_reports: https://github.com/valentint/tclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tclust + url_git: https://github.com/valentint/tclust +Tcomp: + version: 1.0.1 + title: Data from the 2010 Tourism Forecasting Competition + maintainer: Peter Ellis + description: The 1311 time series from the tourism forecasting competition conducted + in 2010 and described in Athanasopoulos et al. (2011) . + date_publication: '2018-06-05' + bug_reports: https://github.com/ellisp/Tcomp-r-package/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Tcomp + url_git: '' +tcpl: + version: 3.2.0 + title: ToxCast Data Analysis Pipeline + maintainer: Jason Brown + description: The ToxCast Data Analysis Pipeline ('tcpl') is an R package that manages, + curve-fits, plots, and stores ToxCast data to populate its linked MySQL database, + 'invitrodb'. The package was developed for the chemical screening data curated + by the US EPA's Toxicity Forecaster (ToxCast) program, but 'tcpl' can be used + to support diverse chemical screening efforts. + date_publication: '2024-10-09' + bug_reports: https://github.com/USEPA/CompTox-ToxCast-tcpl/issues + url: https://www.epa.gov/comptox-tools/toxicity-forecasting-toxcast + url_cran: https://CRAN.R-project.org/package=tcpl + url_git: https://github.com/USEPA/CompTox-ToxCast-tcpl +tcplfit2: + version: 0.1.7 + title: A Concentration-Response Modeling Utility + maintainer: Jason Brown + description: The tcplfit2 R package performs basic concentration-response curve + fitting. The original tcplFit() function in the tcpl R package performed basic + concentration-response curvefitting to 3 models. With tcplfit2, the core tcpl + concentration-response functionality has been expanded to process diverse high-throughput + screen (HTS) data generated at the US Environmental Protection Agency, including + targeted ToxCast, high-throughput transcriptomics (HTTr) and high-throughput phenotypic + profiling (HTPP). tcplfit2 can be used independently to support analysis for diverse + chemical screening efforts. + date_publication: '2024-09-23' + bug_reports: https://github.com/USEPA/CompTox-ToxCast-tcplFit2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tcplfit2 + url_git: https://github.com/USEPA/CompTox-ToxCast-tcplFit2 +TCPMOR: + version: '1.0' + title: Two Cut-Points with Maximum Odds Ratio + maintainer: Shuo Yang + description: |- + Enables the computation of the 'two cut-points with maximum odds ratio (OR) + value method' for data analysis, particularly suited for binary classification + tasks. Users can identify optimal cut-points in a continuous variable by + maximizing the odds ratio while maintaining an equal risk level, useful for + tasks such as medical diagnostics, risk assessment, or predictive modeling. + date_publication: '2024-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TCPMOR + url_git: '' +td: + version: 0.0.6 + title: Access to the 'twelvedata' Financial Data API + maintainer: Dirk Eddelbuettel + description: |- + The 'twelvedata' REST service offers access to current and historical + data on stocks, standard as well as digital 'crypto' currencies, and other financial + assets covering a wide variety of course and time spans. See + for details, to create an account, and to request an API key for free-but-capped access + to the data. + date_publication: '2022-01-26' + bug_reports: https://github.com/eddelbuettel/td/issues + url: https://dirk.eddelbuettel.com/code/td.html + url_cran: https://CRAN.R-project.org/package=td + url_git: https://github.com/eddelbuettel/td +TDA: + version: 1.9.4 + title: Statistical Tools for Topological Data Analysis + maintainer: Jisu Kim + description: Tools for Topological Data Analysis. The package focuses on statistical + analysis of persistent homology and density clustering. For that, this package + provides an R interface for the efficient algorithms of the C++ libraries 'GUDHI' + , 'Dionysus' , + and 'PHAT' . This package also implements + methods from Fasy et al. (2014) and Chazal et al. (2015) + for analyzing the statistical significance of persistent + homology features. + date_publication: '2025-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TDA + url_git: '' +TDAkit: + version: 0.1.2 + title: Toolkit for Topological Data Analysis + maintainer: Kisung You + description: Topological data analysis studies structure and shape of the data using + topological features. We provide a variety of algorithms to learn with persistent + homology of the data based on functional summaries for clustering, hypothesis + testing, visualization, and others. We refer to Wasserman (2018) + for a statistical perspective on the topic. + date_publication: '2021-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TDAkit + url_git: '' +TDApplied: + version: 3.0.4 + title: Machine Learning and Inference for Topological Data Analysis + maintainer: Shael Brown + description: |- + Topological data analysis is a powerful tool for finding non-linear global structure + in whole datasets. The main tool of topological data analysis is persistent homology, which computes + a topological shape descriptor of a dataset called a persistence diagram. 'TDApplied' provides + useful and efficient methods for analyzing groups of persistence diagrams with machine learning and statistical inference, + and these functions can also interface with other data science packages to form flexible and integrated + topological data analysis pipelines. + date_publication: '2024-10-29' + bug_reports: https://github.com/shaelebrown/TDApplied/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TDApplied + url_git: https://github.com/shaelebrown/TDApplied +TDAstats: + version: 0.4.1 + title: Pipeline for Topological Data Analysis + maintainer: Raoul Wadhwa + description: |- + A comprehensive toolset for any + useR conducting topological data analysis, specifically via the + calculation of persistent homology in a Vietoris-Rips complex. + The tools this package currently provides can be conveniently split + into three main sections: (1) calculating persistent homology; (2) + conducting statistical inference on persistent homology calculations; + (3) visualizing persistent homology and statistical inference. + The published form of TDAstats can be found in Wadhwa et al. (2018) + . + For a general background on computing persistent homology for + topological data analysis, see Otter et al. (2017) + . + To learn more about how the permutation test is used for + nonparametric statistical inference in topological data analysis, + read Robinson & Turner (2017) . + To learn more about how TDAstats calculates persistent homology, + you can visit the GitHub repository for Ripser, the software that + works behind the scenes at . + This package has been published as Wadhwa et al. (2018) + . + date_publication: '2019-12-12' + bug_reports: https://github.com/rrrlw/TDAstats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TDAstats + url_git: https://github.com/rrrlw/TDAstats +tdata: + version: 0.3.0 + title: Prepare Your Time-Series Data for Further Analysis + maintainer: Ramin Mojab + description: |- + Provides a set of tools for managing time-series data, + with a particular emphasis on defining various frequency types such + as daily and weekly. It also includes functionality for converting + data between different frequencies. + date_publication: '2023-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tdata + url_git: https://github.com/rmojab63/LDT +tdaunif: + version: 0.2.0 + title: Uniform Manifold Samplers for Topological Data Analysis + maintainer: Jason Cory Brunson + description: |- + Uniform random samples from simple manifolds, sometimes with noise, + are commonly used to test topological data analytic (TDA) tools. + This package includes samplers powered by two techniques: analytic + volume-preserving parameterizations, as employed by Arvo (1995) + , and rejection sampling, as employed by + Diaconis, Holmes, and Shahshahani (2013) . + date_publication: '2024-06-17' + bug_reports: https://github.com/tdaverse/tdaunif/issues + url: https://tdaverse.github.io/tdaunif/ + url_cran: https://CRAN.R-project.org/package=tdaunif + url_git: '' +TDAvec: + version: 0.1.4 + title: Vector Summaries of Persistence Diagrams + maintainer: Aleksei Luchinsky + description: |- + Provides tools for computing various vector summaries of persistence diagrams studied in Topological Data Analysis. For improved computational efficiency, + all code for the vector summaries is written in 'C++' using the 'Rcpp' and 'RcppArmadillo' packages. + date_publication: '2025-02-15' + bug_reports: https://github.com/uislambekov/TDAvec/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TDAvec + url_git: https://github.com/uislambekov/TDAvec +TDbook: + version: 0.0.6 + title: |- + Companion Package for the Book "Data Integration, Manipulation + and Visualization of Phylogenetic Trees" by Guangchuang Yu + (2022, ISBN:9781032233574) + maintainer: Guangchuang Yu + description: |- + The companion package that provides all the datasets used in the book + "Data Integration, Manipulation and Visualization of Phylogenetic Trees" by Guangchuang Yu (2022, ISBN:9781032233574). + date_publication: '2022-08-13' + bug_reports: https://github.com/YuLab-SMU/TDbook/issues + url: https://www.amazon.com/Integration-Manipulation-Visualization-Phylogenetic-Computational-ebook/dp/B0B5NLZR1Z/ + url_cran: https://CRAN.R-project.org/package=TDbook + url_git: '' +TDCM: + version: 0.1.0 + title: The Transition Diagnostic Classification Model Framework + maintainer: Michael E. Cotterell + description: |- + Estimate the transition diagnostic classification model (TDCM) + described in Madison & Bradshaw (2018) , a + longitudinal extension of the log-linear cognitive diagnosis model (LCDM) in + Henson, Templin & Willse (2009) . As the LCDM + subsumes many other diagnostic classification models (DCMs), many other DCMs + can be estimated longitudinally via the TDCM. The 'TDCM' package includes + functions to estimate the single-group and multigroup TDCM, summarize + results of interest including item parameters, growth proportions, + transition probabilities, transitional reliability, attribute correlations, + model fit, and growth plots. + date_publication: '2024-02-05' + bug_reports: https://github.com/cotterell/tdcm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TDCM + url_git: https://github.com/cotterell/tdcm +tdcmStan: + version: 3.0.0 + title: Automating the Creation of Stan Code for TDCMs + maintainer: Jeffrey Hoover + description: |- + A collection of functions for automatically creating 'Stan' + code for transition diagnostic classification models (TDCMs) as they are + defined by Madison and Bradshaw (2018) . + This package supports automating the creation of 'Stan' code for TDCMs, + fungible TDCMs (i.e., TDCMs with item parameters constrained to be equal + across all items), and multi-threaded TDCMs. + date_publication: '2024-03-28' + bug_reports: https://github.com/atlas-aai/tdcmStan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tdcmStan + url_git: https://github.com/atlas-aai/tdcmStan +TDCor: + version: 0.1-2 + title: Gene Network Inference from Time-Series Transcriptomic Data + maintainer: Mikael Lucas + description: The Time-Delay Correlation algorithm (TDCor) reconstructs the topology + of a gene regulatory network (GRN) from time-series transcriptomic data. The + algorithm is described in details in Lavenus et al., Plant Cell, 2015. It was + initially developed to infer the topology of the GRN controlling lateral root + formation in Arabidopsis thaliana. The time-series transcriptomic dataset which + was used in this study is included in the package to illustrate how to use it. + date_publication: '2015-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TDCor + url_git: '' +tdigest: + version: 0.4.2 + title: Wicked Fast, Accurate Quantiles Using t-Digests + maintainer: Bob Rudis + description: |- + The t-Digest construction algorithm, by + Dunning et al., (2019) , uses a variant of 1-dimensional + k-means clustering to produce a very compact data structure that allows + accurate estimation of quantiles. This t-Digest data structure can be used + to estimate quantiles, compute other rank statistics or even to estimate + related measures like trimmed means. The advantage of the t-Digest over + previous digests for this purpose is that the t-Digest handles data with + full floating point resolution. The accuracy of quantile estimates produced + by t-Digests can be orders of magnitude more accurate than those produced + by previous digest algorithms. Methods are provided to create and update + t-Digests and retrieve quantiles from the accumulated distributions. + date_publication: '2024-06-19' + bug_reports: https://todo.sr.ht/~hrbrmstr/tdigest + url: https://git.sr.ht/~hrbrmstr/tdigest + url_cran: https://CRAN.R-project.org/package=tdigest + url_git: '' +TDLM: + version: 1.1.0 + title: Systematic Comparison of Trip Distribution Laws and Models + maintainer: Maxime Lenormand + description: The main purpose of this package is to propose a rigorous framework + to fairly compare trip distribution laws and models as described in Lenormand + et al. (2016) . + date_publication: '2025-01-07' + bug_reports: https://github.com/EpiVec/TDLM/issues + url: https://epivec.github.io/TDLM/ + url_cran: https://CRAN.R-project.org/package=TDLM + url_git: '' +TDPanalysis: + version: '1.0' + title: Granier's Sap Flow Sensors (TDP) Analysis + maintainer: Maxime Durand + description: |- + Set of functions designed to help in the + analysis of TDP sensors. Features includes dates and time conversion, weather + data interpolation, daily maximum of tension analysis and calculations required + to convert sap flow density data to sap flow rates at the tree and plot scale (For more information see : Granier (1985) & Granier (1987) ). + date_publication: '2020-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TDPanalysis + url_git: '' +tdr: + version: '0.13' + title: Target Diagram + maintainer: Oscar Perpinan Lamigueiro + description: 'Implementation of target diagrams using ''lattice'' and ''ggplot2'' + graphics. Target diagrams provide a graphical overview of the respective contributions + of the unbiased RMSE and MBE to the total RMSE (Jolliff, J. et al., 2009. "Summary + Diagrams for Coupled Hydrodynamic-Ecosystem Model Skill Assessment." Journal of + Marine Systems 76: 64–82.)' + date_publication: '2018-01-10' + bug_reports: https://github.com/oscarperpinan/tdr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tdr + url_git: http://github.com/oscarperpinan/tdr +tdROC: + version: '2.0' + title: |- + Nonparametric Estimation of Time-Dependent ROC, Brier Score, and + Survival Difference from Right Censored Time-to-Event Data with + or without Competing Risks + maintainer: Xiaoyang Li + description: |- + The tdROC package facilitates the estimation of time-dependent ROC + (Receiver Operating Characteristic) curves and the Area Under the time-dependent + ROC Curve (AUC) in the context of survival data, accommodating scenarios with + right censored data and the option to account for competing risks. In addition + to the ROC/AUC estimation, the package also estimates time-dependent Brier score and + survival difference. Confidence intervals of various estimated quantities can be + obtained from bootstrap. The package also offers plotting functions for visualizing + time-dependent ROC curves. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tdROC + url_git: '' +tdsa: + version: 1.1-0 + title: Time-Dependent Sensitivity Analysis + maintainer: Wee Hao Ng + description: Functions that can be used to calculate time-dependent state and parameter + sensitivities for both continuous- and discrete-time deterministic models. See + Ng et al. (in press) for more information about time-dependent + sensitivity analysis. + date_publication: '2023-09-10' + bug_reports: https://github.com/weehaong/tdsa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tdsa + url_git: https://github.com/weehaong/tdsa +tdsc: + version: 1.0.4 + title: Time Domain Signal Coding + maintainer: Ed Baker + description: Functions for performing time domain signal coding as used in Chesmore + (2001) , and related tasks. This package creates + the standard S-matrix and A-matrix (with variable lag), has tools to convert coding + matrices into distributed matrices, provides published codebooks and allows for + extraction of code sequences. + date_publication: '2023-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tdsc + url_git: '' +TDSTNN: + version: 0.1.0 + title: Time Delay Spatio Temporal Neural Network + maintainer: Mrinmoy Ray + description: STARMA (Space-Time Autoregressive Moving Average) models are commonly + utilized in modeling and forecasting spatiotemporal time series data. However, + the intricate nonlinear dynamics observed in many space-time rainfall patterns + often exceed the capabilities of conventional STARMA models. This R package enables + the fitting of Time Delay Spatio-Temporal Neural Networks, which are adept at + handling such complex nonlinear dynamics efficiently. For detailed methodology, + please refer to Saha et al. (2020) . + date_publication: '2024-05-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TDSTNN + url_git: '' +tdthap: + version: '1.3' + title: TDT Tests for Extended Haplotypes + maintainer: Jing Hua Zhao + description: |- + Functions and examples are provided for Transmission/disequilibrium tests + for extended marker haplotypes, as in + Clayton, D. and Jones, H. (1999) "Transmission/disequilibrium tests + for extended marker haplotypes". Amer. J. Hum. Genet., 65:1161-1169, + . + date_publication: '2023-11-29' + bug_reports: https://github.com/jinghuazhao/R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tdthap + url_git: https://github.com/jinghuazhao/R +TE: + version: 0.3-0 + title: Insertion/Deletion Dynamics for Transposable Elements + maintainer: Xiongtao Dai + description: Provides functions to estimate the insertion and deletion rates of + transposable element (TE) families. The estimation of insertion rate consists + of an improved estimate of the age distribution that takes into account random + mutations, and an adjustment by the deletion rate. A hypothesis test for a uniform + insertion rate is also implemented. This package implements the methods proposed + in Dai et al (2018). + date_publication: '2018-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TE + url_git: '' +tea: + version: '1.1' + title: Threshold Estimation Approaches + maintainer: Johannes Ossberger + description: Different approaches for selecting the threshold in generalized Pareto + distributions. Most of them are based on minimizing the AMSE-criterion or at least + by reducing the bias of the assumed GPD-model. Others are heuristically motivated + by searching for stable sample paths, i.e. a nearly constant region of the tail + index estimator with respect to k, which is the number of data in the tail. The + third class is motivated by graphical inspection. In addition, a sequential testing + procedure for GPD-GoF-tests is also implemented here. + date_publication: '2020-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tea + url_git: '' +TeachHist: + version: 0.2.1 + title: |- + A Collection of Amended Histograms Designed for Teaching + Statistics + maintainer: Carsten Lange + description: |- + Statistics students often have problems understanding + the relation between a random variable's true scale and its z-values. + To allow instructors to better better visualize histograms for these + students, the package provides histograms with two horizontal + axis containing z-values and the true scale of the variable. + The function TeachHistDens() provides a density histogram with two axis. + TeachHistCounts() and TeachHistRelFreq() are variations for count and + relative frequency histograms, respectively. TeachConfInterv() and + TeachHypTest() help instructors to visualize confidence levels + and the results of hypothesis tests. + date_publication: '2023-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TeachHist + url_git: '' +TeachingDemos: + version: '2.13' + title: Demonstrations for Teaching and Learning + maintainer: Greg Snow + description: Demonstration functions that can be used in a classroom to demonstrate + statistical concepts, or on your own to better understand the concepts or the + programming. + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TeachingDemos + url_git: '' +TeachingSampling: + version: 4.1.1 + title: |- + Selection of Samples and Parameter Estimation in Finite + Population + maintainer: Hugo Andres Gutierrez Rojas + description: Allows the user to draw probabilistic samples and make inferences from + a finite population based on several sampling designs. + date_publication: '2020-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TeachingSampling + url_git: '' +teal: + version: 0.16.0 + title: Exploratory Web Apps for Analyzing Clinical Trials Data + maintainer: Dawid Kaledkowski + description: |- + A 'shiny' based interactive exploration framework for + analyzing clinical trials data. 'teal' currently provides a dynamic + filtering facility and different data viewers. 'teal' 'shiny' + applications are built using standard 'shiny' modules. + date_publication: '2025-02-23' + bug_reports: https://github.com/insightsengineering/teal/issues + url: https://insightsengineering.github.io/teal/ + url_cran: https://CRAN.R-project.org/package=teal + url_git: https://github.com/insightsengineering/teal/ +teal.code: + version: 0.6.1 + title: Code Storage and Execution Class for 'teal' Applications + maintainer: Dawid Kaledkowski + description: |- + Introduction of 'qenv' S4 class, that facilitates code + execution and reproducibility in 'teal' applications. + date_publication: '2025-02-14' + bug_reports: https://github.com/insightsengineering/teal.code/issues + url: https://insightsengineering.github.io/teal.code/ + url_cran: https://CRAN.R-project.org/package=teal.code + url_git: https://github.com/insightsengineering/teal.code +teal.data: + version: 0.7.0 + title: Data Model for 'teal' Applications + maintainer: Dawid Kaledkowski + description: |- + Provides a 'teal_data' class as a unified data model for + 'teal' applications focusing on reproducibility and relational data. + date_publication: '2025-01-28' + bug_reports: https://github.com/insightsengineering/teal.data/issues + url: https://insightsengineering.github.io/teal.data/ + url_cran: https://CRAN.R-project.org/package=teal.data + url_git: https://github.com/insightsengineering/teal.data/ +teal.logger: + version: 0.3.2 + title: Logging Setup for the 'teal' Family of Packages + maintainer: Dawid Kaledkowski + description: |- + Utilizing the 'logger' framework to record events within a + package, specific to 'teal' family of packages. Supports logging + namespaces, hierarchical logging, various log destinations, + vectorization, and more. + date_publication: '2025-02-14' + bug_reports: https://github.com/insightsengineering/teal.logger/issues + url: https://insightsengineering.github.io/teal.logger/ + url_cran: https://CRAN.R-project.org/package=teal.logger + url_git: https://github.com/insightsengineering/teal.logger/ +teal.modules.clinical: + version: 0.10.0 + title: '''teal'' Modules for Standard Clinical Outputs' + maintainer: Dawid Kaledkowski + description: |- + Provides user-friendly tools for creating and customizing + clinical trial reports. By leveraging the 'teal' framework, this + package provides 'teal' modules to easily create an interactive panel + that allows for seamless adjustments to data presentation, thereby + streamlining the creation of detailed and accurate reports. + date_publication: '2025-02-28' + bug_reports: https://github.com/insightsengineering/teal.modules.clinical/issues + url: https://insightsengineering.github.io/teal.modules.clinical/ + url_cran: https://CRAN.R-project.org/package=teal.modules.clinical + url_git: https://github.com/insightsengineering/teal.modules.clinical/ +teal.modules.general: + version: 0.4.0 + title: General Modules for 'teal' Applications + maintainer: Dawid Kaledkowski + description: |- + Prebuilt 'shiny' modules containing tools for viewing data, + visualizing data, understanding missing and outlier values within your + data and performing simple data analysis. This extends 'teal' + framework that supports reproducible research and analysis. + date_publication: '2025-02-28' + bug_reports: https://github.com/insightsengineering/teal.modules.general/issues + url: https://insightsengineering.github.io/teal.modules.general/ + url_cran: https://CRAN.R-project.org/package=teal.modules.general + url_git: https://github.com/insightsengineering/teal.modules.general/ +teal.reporter: + version: 0.4.0 + title: Reporting Tools for 'shiny' Modules + maintainer: Dawid Kaledkowski + description: |- + Prebuilt 'shiny' modules containing tools for the generation + of 'rmarkdown' reports, supporting reproducible research and analysis. + date_publication: '2025-01-24' + bug_reports: https://github.com/insightsengineering/teal.reporter/issues + url: https://insightsengineering.github.io/teal.reporter/ + url_cran: https://CRAN.R-project.org/package=teal.reporter + url_git: https://github.com/insightsengineering/teal.reporter +teal.slice: + version: 0.6.0 + title: Filter Module for 'teal' Applications + maintainer: Dawid Kaledkowski + description: |- + Data filtering module for 'teal' applications. Allows for + interactive filtering of data stored in 'data.frame' and + 'MultiAssayExperiment' objects. Also displays filtered and unfiltered + observation counts. + date_publication: '2025-02-03' + bug_reports: https://github.com/insightsengineering/teal.slice/issues + url: https://insightsengineering.github.io/teal.slice/ + url_cran: https://CRAN.R-project.org/package=teal.slice + url_git: https://github.com/insightsengineering/teal.slice/ +teal.transform: + version: 0.6.0 + title: |- + Functions for Extracting and Merging Data in the 'teal' + Framework + maintainer: Dawid Kaledkowski + description: |- + A standardized user interface for column selection, that + facilitates dataset merging in 'teal' framework. + date_publication: '2025-02-12' + bug_reports: https://github.com/insightsengineering/teal.transform/issues + url: https://insightsengineering.github.io/teal.transform/ + url_cran: https://CRAN.R-project.org/package=teal.transform + url_git: https://github.com/insightsengineering/teal.transform/ +teal.widgets: + version: 0.4.3 + title: '''shiny'' Widgets for ''teal'' Applications' + maintainer: Dawid Kaledkowski + description: |- + Collection of 'shiny' widgets to support 'teal' applications. + Enables the manipulation of application layout and plot or table + settings. + date_publication: '2025-01-31' + bug_reports: https://github.com/insightsengineering/teal.widgets/issues + url: https://insightsengineering.github.io/teal.widgets/ + url_cran: https://CRAN.R-project.org/package=teal.widgets + url_git: https://github.com/insightsengineering/teal.widgets +tealeaves: + version: 1.0.6 + title: Solve for Leaf Temperature Using Energy Balance + maintainer: Chris Muir + description: Implements models of leaf temperature using energy balance. It uses + units to ensure that parameters are properly specified and transformed before + calculations. It allows separate lower and upper surface conductances to heat + and water vapour, so sensible and latent heat loss are calculated for each surface + separately as in Foster and Smith (1986) . + It's straightforward to model leaf temperature over environmental gradients such + as light, air temperature, humidity, and wind. It can also model leaf temperature + over trait gradients such as leaf size or stomatal conductance. Other references + are Monteith and Unsworth (2013, ISBN:9780123869104), Nobel (2009, ISBN:9780123741431), + and Okajima et al. (2012) . + date_publication: '2022-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tealeaves + url_git: '' +TEAM: + version: 0.1.0 + title: Multiple Hypothesis Testing on an Aggregation Tree Method + maintainer: John Pura + description: |- + An implementation of the TEAM algorithm to identify local differences + between two (e.g. case and control) independent, univariate distributions, as + described in J Pura, C Chan, and J Xie (2019) . The algorithm + is based on embedding a multiple-testing procedure on a hierarchical structure + to identify high-resolution differences between two distributions. The + hierarchical structure is designed to identify strong, short-range differences + at lower layers and weaker, but long-range differences at increasing layers. + TEAM yields consistent layer-specific and overall false discovery rate control. + date_publication: '2019-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TEAM + url_git: '' +teamcolors: + version: 0.0.4 + title: Color Palettes for Pro Sports Teams + maintainer: Benjamin S. Baumer + description: |- + Provides color palettes corresponding to professional and amateur, + sports teams. These can be useful in creating data graphics that are themed + for particular teams. + date_publication: '2020-01-22' + bug_reports: https://github.com/beanumber/teamcolors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=teamcolors + url_git: http://github.com/beanumber/teamcolors +teamr: + version: 0.0.1 + title: Send Formatted Messages, Images and Objects to Microsoft 'Teams' + maintainer: Michael Yan + description: |- + Package of wrapper functions using R6 class to send requests to + Microsoft 'Teams' through webhooks. + When you need to share information or data from R to 'Teams', rather than copying/pasting, you + can use this package to send well-formatted output from multiple R objects. + date_publication: '2019-07-18' + bug_reports: https://github.com/wwwjk366/teamr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=teamr + url_git: https://github.com/wwwjk366/teamr +tectonicr: + version: 0.4.6 + title: Analyzing the Orientation of Maximum Horizontal Stress + maintainer: Tobias Stephan + description: |- + Models the direction of the maximum horizontal stress using + relative plate motion parameters. Statistical algorithms to evaluate + the modeling results compared with the observed data. Provides plots + to visualize the results. Methods described in Stephan et al. (2023) + and Wdowinski (1998) + . + date_publication: '2025-03-01' + bug_reports: https://github.com/tobiste/tectonicr/issues + url: https://tobiste.github.io/tectonicr/ + url_cran: https://CRAN.R-project.org/package=tectonicr + url_git: '' +teda: + version: 0.1.1 + title: |- + An Implementation of the Typicality and Eccentricity Data + Analysis Framework + maintainer: David Ciar + description: |- + The typicality and eccentricity data analysis (TEDA) framework was + put forward by Angelov (2013) . It has been further developed into multiple + different techniques since, and provides a non-parametric way of determining how + similar an observation, from a process that is not purely random, is to other + observations generated by the process. This package provides code to use the + batch and recursive TEDA methods that have been published. + date_publication: '2017-01-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=teda + url_git: '' +tehtuner: + version: 0.3.0 + title: Fit and Tune Models to Detect Treatment Effect Heterogeneity + maintainer: Jack Wolf + description: |- + Implements methods to fit Virtual Twins models (Foster et al. + (2011) ) for identifying subgroups with differential + effects in the context of clinical trials while controlling the probability + of falsely detecting a differential effect when the conditional average + treatment effect is uniform across the study population using parameter + selection methods proposed in Wolf et al. (2022) + . + date_publication: '2023-04-01' + bug_reports: https://github.com/jackmwolf/tehtuner/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tehtuner + url_git: https://github.com/jackmwolf/tehtuner +teigen: + version: 2.2.2 + title: |- + Model-Based Clustering and Classification with the Multivariate + t Distribution + maintainer: Jeffrey L. Andrews + description: Fits mixtures of multivariate t-distributions (with eigen-decomposed + covariance structure) via the expectation conditional-maximization algorithm under + a clustering or classification paradigm. + date_publication: '2018-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=teigen + url_git: '' +Tejapi: + version: 1.0.1 + title: API Wrapper for Taiwan Economic Journal Data Service + maintainer: Peter Young + description: Functions for interacting directly with the Taiwan Economic Journal + API to offer data in R. For more information go to . + date_publication: '2018-11-04' + bug_reports: https://api.tej.com.tw + url: https://api.tej.com.tw + url_cran: https://CRAN.R-project.org/package=Tejapi + url_git: '' +telefit: + version: 1.0.3 + title: |- + Estimation and Prediction for Remote Effects Spatial Process + Models + maintainer: Joshua Hewitt + description: Implementation of the remote effects spatial process (RESP) model for + teleconnection. The RESP model is a geostatistical model that allows a spatially-referenced + variable (like average precipitation) to be influenced by covariates defined on + a remote domain (like sea surface temperatures). The RESP model is introduced + in Hewitt et al. (2018) . Sample code for working with + the RESP model is available at . + This material is based upon work supported by the National Science Foundation + under grant number AGS 1419558. Any opinions, findings, and conclusions or recommendations + expressed in this material are those of the authors and do not necessarily reflect + the views of the National Science Foundation. + date_publication: '2020-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=telefit + url_git: '' +telegram: + version: 0.6.0 + title: R Wrapper Around the Telegram Bot API + maintainer: Luca Braglia + description: R wrapper around the Telegram Bot API (http://core.telegram.org/bots/api) + to access Telegram's messaging facilities with ease (e.g. you send messages, images, + files from R to your smartphone). + date_publication: '2016-09-17' + bug_reports: http://github.com/lbraglia/telegram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=telegram + url_git: http://github.com/lbraglia/telegram +telegram.bot: + version: 3.0.0 + title: Develop a 'Telegram Bot' with R + maintainer: Ernest Benedito + description: |- + Provides a pure interface for the 'Telegram Bot API' + . In addition to the pure API + implementation, it features a number of tools to make the development of + 'Telegram' bots with R easy and straightforward, providing an easy-to-use + interface that takes some work off the programmer. + date_publication: '2022-09-07' + bug_reports: https://github.com/ebeneditos/telegram.bot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=telegram.bot + url_git: https://github.com/ebeneditos/telegram.bot +telemetR: + version: '1.0' + title: Filter and Analyze Generalised Telemetry Data from Organisms + maintainer: Taylor Spaulding + description: |- + Analyze telemetry datasets generalized to allow + any technology. The filtering steps check for false positives caused by + reflected transmissions from surfaces and false pings from other noise + generating equipment. The filters are based on JSATS filtering algorithms + found in package 'filteRjsats' + but have been generalized to allow the user to define many of the filtering + variables. Additionally, this package contains scripts used to help identify + an optimal maximum blanking period as defined in Capello et al (2015) + . The functions were written according to + their manuscript description, but have not been reviewed by the authors for + accuracy. It is included here as is, without warranty. + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=telemetR + url_git: '' +telescope: + version: 0.2-0 + title: Bayesian Mixtures with an Unknown Number of Components + maintainer: Gertraud Malsiner-Walli + description: Fits Bayesian finite mixtures with an unknown number of components + using the telescoping sampler and different component distributions. For more + details see Frühwirth-Schnatter et al. (2021) . + date_publication: '2025-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=telescope + url_git: '' +TELP: + version: 1.0.2 + title: |- + Social Representation Theory Application: The Free Evocation of + Words Technique + maintainer: Gabriel Henrique Oliveira Assuncao + description: |- + Using The Free Evocation of Words Technique method with some functions, this package will make a + social representation and other analysis. The Free Evocation of Words Technique consists of collecting a number of words evoked by a subject facing exposure to an inducer term. The purpose of this technique is to understand the relationships created between words evoked by the individual and the inducer term. This technique is included in the theory of social representations, therefore, on the information transmitted by an individual, seeks to create a profile that define a social group. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TELP + url_git: '' +telraamStats: + version: 1.1.2 + title: |- + Retrieval and Visualization of Mobility Data from 'Telraam' + Sensors + maintainer: Ketsia Guichard + description: |- + Streamline the processing of 'Telraam' data, sourced from open data + mobility sensors. These tools range from data retrieval (without the need for + API knowledge) to data visualization, including data preprocessing. + date_publication: '2024-05-27' + bug_reports: https://github.com/KetsiaGuichard/telraamStats/issues/ + url: https://annuaire.agistaterre.org/telraamStats/ + url_cran: https://CRAN.R-project.org/package=telraamStats + url_git: '' +TempCont: + version: 0.1.0 + title: Temporal Contributions on Trends using Mixed Models + maintainer: Marcos Fernández-Martínez + description: |- + Method to estimate the effect of the trend in predictor variables on the observed trend + of the response variable using mixed models with temporal autocorrelation. See Fernández-Martínez et + al. (2017 and 2019) . + date_publication: '2019-03-19' + bug_reports: https://github.com/burriach/tempcont/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TempCont + url_git: https://github.com/burriach/tempcont +tempdisagg: + version: 1.1.1 + title: |- + Methods for Temporal Disaggregation and Interpolation of Time + Series + maintainer: Christoph Sax + description: |- + Temporal disaggregation methods are used to disaggregate and + interpolate a low frequency time series to a higher frequency series, where + either the sum, the mean, the first or the last value of the resulting + high frequency series is consistent with the low frequency series. Temporal + disaggregation can be performed with or without one or more high frequency + indicator series. Contains the methods of Chow-Lin, Santos-Silva-Cardoso, + Fernandez, Litterman, Denton and Denton-Cholette, summarized in Sax and + Steiner (2013) . Supports most R time series + classes. + date_publication: '2023-08-08' + bug_reports: https://github.com/christophsax/tempdisagg + url: '' + url_cran: https://CRAN.R-project.org/package=tempdisagg + url_git: '' +temperatureresponse: + version: '0.2' + title: Temperature Response + maintainer: Etienne Low-Decarie + description: Fits temperature response models to rate measurements taken at different + temperatures. Etienne Low-Decarie,Tobias G. Boatman, Noah Bennett,Will Passfield,Antonio + Gavalas-Olea,Philipp Siegel, Richard J. Geider (2017) + . + date_publication: '2018-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=temperatureresponse + url_git: https://github.com/low-decarie/temperatureresponse +templateICAr: + version: 0.9.1 + title: |- + Estimate Brain Networks and Connectivity with ICA and Empirical + Priors + maintainer: Amanda Mejia + description: |- + Implements the template ICA (independent components analysis) model + proposed in Mejia et al. (2020) and the + spatial template ICA model proposed in proposed in Mejia et al. (2022) + . Both models estimate subject-level + brain as deviations from known population-level networks, which are + estimated using standard ICA algorithms. Both models employ an + expectation-maximization algorithm for estimation of the latent brain + networks and unknown model parameters. Includes direct support for 'CIFTI', + 'GIFTI', and 'NIFTI' neuroimaging file formats. + date_publication: '2024-11-21' + bug_reports: https://github.com/mandymejia/templateICAr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=templateICAr + url_git: https://github.com/mandymejia/templateICAr +templates: + version: 0.4.0 + title: A System for Working with Templates + maintainer: Sebastian Warnholz + description: |- + Provides tools to work with template code and text in R. It aims to + provide a simple substitution mechanism for R-expressions inside these + templates. Templates can be written in other languages like 'SQL', can + simply be represented by characters in R, or can themselves be R-expressions + or functions. + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=templates + url_git: '' +templr: + version: 0.2-0 + title: MASCOTNUM Algorithms Template Tools + maintainer: Yann Richet + description: |- + Helper functions for MASCOTNUM algorithm template, for design of numerical experiments practice: + algorithm template parser to support MASCOTNUM specification , + 'ask & tell' decoupling injection (inspired by ) + to use "crimped" algorithms (like uniroot(), optim(), ...) from outside R, + basic template examples: Brent algorithm for 1 dim root finding and L-BFGS-B from base optim(). + date_publication: '2022-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=templr + url_git: https://github.com/MASCOTNUM/templr +Temporal: + version: 0.3.0.1 + title: Parametric Time to Event Analysis + maintainer: Zachary McCaw + description: Performs maximum likelihood based estimation and inference on time + to event data, possibly subject to non-informative right censoring. FitParaSurv() + provides maximum likelihood estimates of model parameters and distributional characteristics, + including the mean, median, variance, and restricted mean. CompParaSurv() compares + the mean, median, and restricted mean survival experiences of two treatment groups. + Candidate distributions include the exponential, gamma, generalized gamma, log-normal, + and Weibull. + date_publication: '2023-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Temporal + url_git: '' +TemporalGSSA: + version: 1.0.1 + title: |- + Outputs Temporal Profile of Molecules from Stochastic Simulation + Algorithm Generated Datasets + maintainer: Siddhartha Kundu + description: |- + The data that is generated from independent and consecutive 'GillespieSSA' runs for a generic biochemical network + is formatted as rows and constitutes an observation. The first column of each row is the computed timestep for each run. Subsequent + columns are used for the number of molecules of each participating molecular species or "metabolite" of a generic biochemical network. + In this way 'TemporalGSSA', is a wrapper for the R-package 'GillespieSSA'. The number of observations must be at least 30. + This will generate data that is statistically significant. 'TemporalGSSA', transforms this raw data into a simulation time-dependent and metabolite-specific + trial. Each such trial is defined as a set of linear models (n >= 30) between a timestep and number of molecules for a metabolite. Each linear model + is characterized by coefficients such as the slope, arbitrary constant, etc. The user must enter an integer from 1-4. + These specify the statistical modality utilized to compute a representative timestep (mean, median, random, all). + These arguments are mandatory and will be checked. Whilst, the numeric indicator "0" indicates suitability, + "1" prompts the user to revise and re-enter their data. An optional logical argument controls the output to the + console with the default being "TRUE" (curtailed) whilst "FALSE" (verbose). The coefficients of each linear model are averaged (mean slope, mean constant) + and are incorporated into a metabolite-specific linear regression model as the dependent variable. The independent variable is the representative timestep + chosen previously. The generated data is the imputed molecule number for an in silico experiment with (n >=30) + observations. These steps can be replicated with multiple set of observations. The generated "technical + replicates" can be statistically evaluated (mean, standard deviation) and will constitute simulation time-dependent molecules for each metabolite. + For SSA-generated datasets with varying simulation times 'TemporalGSSA' will generate a simulation time-dependent trajectory for each metabolite + of the biochemical network under study. The relevant publication with the mathematical derivation of the algorithm is + (2022, Journal of Bioinformatics and Computational Biology) . The algorithm has been deployed in the following publications + (2021, Heliyon) and (2016, Journal of Theoretical Biology) . + date_publication: '2022-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TemporalGSSA + url_git: '' +tempR: + version: 0.10.1.1 + title: Temporal Sensory Data Analysis + maintainer: J.C. Castura + description: Analysis and visualization of data from temporal sensory methods, including + for temporal check-all-that-apply (TCATA) and temporal dominance of sensations + (TDS). Methods are mainly from manuscripts by Castura, J.C., Antúnez, L., Giménez, + A., and Ares, G. (2016) , Castura, Baker, + and Ross (2016) , and Pineau et al. (2009) + . + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tempR + url_git: '' +TempStable: + version: 0.2.2 + title: |- + A Collection of Methods to Estimate Parameters of Different + Tempered Stable Distributions + maintainer: Till Massing + description: |2- + + A collection of methods to estimate parameters of different tempered stable + distributions (TSD). Currently, there are seven different tempered stable + distributions to choose from: Tempered stable subordinator distribution, + classical TSD, generalized classical TSD, normal TSD, modified TSD, rapid + decreasing TSD, and Kim-Rachev TSD. + The package also provides functions to compute density and probability + functions and tools to run Monte Carlo simulations. + This package has already been used for the estimation of tempered stable + distributions (Massing (2023) ). + The following references form the theoretical background for various functions + in this package. References for each function are explicitly listed in its + documentation: + Bianchi et al. (2010) + Bianchi et al. (2011) + Carrasco (2017) + Feuerverger (1981) + Hansen et al. (1996) + Hansen (1982) + Hofert (2011) + Kawai & Masuda (2011) + Kim et al. (2008) + Kim et al. (2009) + Kim et al. (2010) + Kuechler & Tappe (2013) + Rachev et al. (2011) . + date_publication: '2023-10-24' + bug_reports: https://github.com/TMoek/TempStable/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TempStable + url_git: https://github.com/TMoek/TempStable +tempted: + version: 0.1.1 + title: |- + Temporal Tensor Decomposition, a Dimensionality Reduction Tool + for Longitudinal Multivariate Data + maintainer: Pixu Shi + description: TEMPoral TEnsor Decomposition (TEMPTED), is a dimension reduction method + for multivariate longitudinal data with varying temporal sampling. It formats + the data into a temporal tensor and decomposes it into a summation of low-dimensional + components, each consisting of a subject loading vector, a feature loading vector, + and a continuous temporal loading function. These loadings provide a low-dimensional + representation of subjects or samples and can be used to identify features associated + with clusters of subjects or samples. TEMPTED provides the flexibility of allowing + subjects to have different temporal sampling, so time points do not need to be + binned, and missing time points do not need to be imputed. + date_publication: '2024-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tempted + url_git: https://github.com/pixushi/tempted +Tendril: + version: 2.0.4 + title: Compute and Display Tendril Plots + maintainer: Stefano Borini + description: |- + Compute the coordinates to produce a tendril plot. + In the tendril plot, each tendril (branch) represents a type of events, + and the direction of the tendril is dictated by on which treatment arm the + event is occurring. If an event is occurring on the first of the two + specified treatment arms, the tendril bends in a clockwise direction. + If an event is occurring on the second of the treatment arms, the + tendril bends in an anti-clockwise direction. + Ref: Karpefors, M and Weatherall, J., "The Tendril Plot - a novel visual summary + of the incidence, significance and temporal aspects of adverse events in + clinical trials" - JAMIA 2018; 25(8): 1069-1073 . + date_publication: '2020-02-11' + bug_reports: https://github.com/Karpefors/Tendril/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Tendril + url_git: https://github.com/Karpefors/Tendril +tenispolaR: + version: 0.1.4 + title: Provides ZENIT-POLAR Substitution Cipher Method of Encryption + maintainer: Adelmo Filho + description: Implementation of ZENIT-POLAR substitution cipher method of encryption + using by default the TENIS-POLAR cipher. This last cipher of encryption became + famous through the collection of Brazilian books "Os Karas" by the author Pedro + Bandeira. For more details, see "A Cryptographic Dictionary" (GC&CS, 1944). + date_publication: '2019-03-08' + bug_reports: https://github.com/adelmofilho/tenispolaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tenispolaR + url_git: https://github.com/adelmofilho/tenispolaR +tenm: + version: 0.5.1 + title: Temporal Ecological Niche Models + maintainer: Luis Osorio-Olvera + description: |- + Implements methods and functions to calibrate + time-specific niche models (multi-temporal calibration), letting users + execute a strict calibration and selection process of niche models based + on ellipsoids, as well as functions to project the potential distribution in + the present and in global change scenarios.The 'tenm' package has functions + to recover information that may be lost or overlooked while applying a data + curation protocol. This curation involves preserving occurrences that may + appear spatially redundant (occurring in the same pixel) but originate from + different time periods. A novel aspect of this package is that it might + reconstruct the fundamental niche more accurately than mono-calibrated + approaches. The theoretical background of the package can be found in + Peterson et al. (2011). + date_publication: '2024-07-23' + bug_reports: https://github.com/luismurao/tenm/issues + url: https://luismurao.github.io/tenm/ + url_cran: https://CRAN.R-project.org/package=tenm + url_git: '' +tensor: + version: '1.5' + title: Tensor product of arrays + maintainer: Jonathan Rougier + description: The tensor product of two arrays is notionally an outerproduct + of the arrays collapsed in specific extents by summingalong the appropriate + diagonals. + date_publication: '2012-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensor + url_git: '' +tensorA: + version: 0.36.2.1 + title: Advanced Tensor Arithmetic with Named Indices + maintainer: K. Gerald van den Boogaart + description: |- + Provides convenience functions for advanced + linear algebra with tensors and computation with data sets of + tensors on a higher level abstraction. It includes Einstein and + Riemann summing conventions, dragging, co- and contravariate + indices, parallel computations on sequences of tensors. + date_publication: '2023-12-13' + bug_reports: '' + url: http://www.stat.boogaart.de/tensorA/ + url_cran: https://CRAN.R-project.org/package=tensorA + url_git: '' +tensorBF: + version: 1.0.2 + title: Bayesian Tensor Factorization + maintainer: Suleiman A Khan + description: Bayesian Tensor Factorization for decomposition of tensor data sets + using the trilinear CANDECOMP/PARAFAC (CP) factorization, with automatic component + selection. The complete data analysis pipeline is provided, including functions + and recommendations for data normalization and model definition, as well as missing + value prediction and model visualization. The method performs factorization for + three-way tensor datasets and the inference is implemented with Gibbs sampling. + date_publication: '2018-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensorBF + url_git: '' +tensorBSS: + version: 0.3.9 + title: Blind Source Separation Methods for Tensor-Valued Observations + maintainer: Joni Virta + description: 'Contains several utility functions for manipulating tensor-valued + data (centering, multiplication from a single mode etc.) and the implementations + of the following blind source separation methods for tensor-valued data: ''tPCA'', + ''tFOBI'', ''tJADE'', k-tJADE'', ''tgFOBI'', ''tgJADE'', ''tSOBI'', ''tNSS.SD'', + ''tNSS.JD'', ''tNSS.TD.JD'', ''tPP'' and ''tTUCKER''.' + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensorBSS + url_git: '' +TensorClustering: + version: 1.0.2 + title: Model-Based Tensor Clustering + maintainer: Kai Deng + description: 'Performs model-based tensor clustering methods including Tensor Gaussian + Mixture Model (TGMM), Tensor Envelope Mixture Model (TEMM) by Deng and Zhang (2021) + , Doubly-Enhanced EM (DEEM) algorithm by Mai, Zhang, + Pan and Deng (2021) .' + date_publication: '2021-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TensorClustering + url_git: '' +TensorComplete: + version: 0.2.0 + title: Tensor Noise Reduction and Completion Methods + maintainer: Chanwoo Lee + description: Efficient algorithms for tensor noise reduction and completion. This + package includes a suite of parametric and nonparametric tools for estimating + tensor signals from noisy, possibly incomplete observations. The methods allow + a broad range of data types, including continuous, binary, and ordinal-valued + tensor entries. The algorithms employ the alternating optimization. The detailed + algorithm description can be found in the following three references. + date_publication: '2023-04-14' + bug_reports: '' + url: ChanwooLeeandMiaoyanWang.Tensordenoisingandcompletionbasedonordinalobservations.ICML + url_cran: https://CRAN.R-project.org/package=TensorComplete + url_git: '' +tensorEVD: + version: 0.1.4 + title: |- + A Fast Algorithm to Factorize High-Dimensional Tensor Product + Matrices + maintainer: Marco Lopez-Cruz + description: |- + Here we provide tools for the computation and factorization of high-dimensional + tensor products that are formed by smaller matrices. The methods are based on + properties of Kronecker products (Searle 1982, p. 265, ISBN-10: 0470009616). + We evaluated this methodology by benchmark testing and illustrated its use in + Gaussian Linear Models ('Lopez-Cruz et al., 2024') . + date_publication: '2024-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensorEVD + url_git: https://github.com/MarcooLopez/tensorEVD +tensorflow: + version: 2.16.0 + title: R Interface to 'TensorFlow' + maintainer: Tomasz Kalinowski + description: |- + Interface to 'TensorFlow' , + an open source software library for numerical computation using data + flow graphs. Nodes in the graph represent mathematical operations, + while the graph edges represent the multidimensional data arrays + (tensors) communicated between them. The flexible architecture allows + you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop, + server, or mobile device with a single 'API'. 'TensorFlow' was originally + developed by researchers and engineers working on the Google Brain Team + within Google's Machine Intelligence research organization for the + purposes of conducting machine learning and deep neural networks research, + but the system is general enough to be applicable in a wide variety + of other domains as well. + date_publication: '2024-04-15' + bug_reports: https://github.com/rstudio/tensorflow/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tensorflow + url_git: https://github.com/rstudio/tensorflow +tensorMiss: + version: 1.1.1 + title: Handle Missing Tensor Data with C++ Integration + maintainer: Zetai Cen + description: |- + To handle higher-order tensor data. See Kolda and Bader (2009) for details on tensor. While existing packages on tensor data extend the base 'array' class to some data classes, this package serves as an alternative resort to handle tensor only as 'array' class. + Some functionalities related to missingness are also supported. + date_publication: '2024-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensorMiss + url_git: '' +TensorPreAve: + version: 1.1.0 + title: |- + Rank and Factor Loadings Estimation in Time Series Tensor Factor + Models + maintainer: Weilin Chen + description: |- + A set of functions to estimate rank and factor loadings of time series tensor factor models. A tensor is a multidimensional array. To analyze high-dimensional tensor time series, factor model is a major dimension reduction tool. 'TensorPreAve' provides functions to estimate the rank of core tensors and factor loading spaces of tensor time series. More specifically, a pre-averaging method that accumulates information from tensor fibres is used to estimate the factor loading spaces. The estimated directions corresponding to the strongest factors are then used for projecting the data for a potentially improved re-estimation of the factor loading spaces themselves. A new rank estimation method is also implemented to utilizes correlation information from the projected data. + See Chen and Lam (2023) for more details. + date_publication: '2023-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TensorPreAve + url_git: https://github.com/William-Chenwl/TensorPreAve +tensorregress: + version: '5.1' + title: Supervised Tensor Decomposition with Side Information + maintainer: Jiaxin Hu + description: Implement the alternating algorithm for supervised tensor decomposition + with interactive side information. Details can be found in the publication Hu, + Jiaxin, Chanwoo Lee, and Miaoyan Wang. "Generalized Tensor Decomposition with + features on multiple modes." Journal of Computational and Graphical Statistics, + Vol. 31, No. 1, 204-218, 2022 . + date_publication: '2023-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensorregress + url_git: '' +tensorsparse: + version: '3.0' + title: Multiway Clustering via Tensor Block Models + maintainer: Yuchen Zeng + description: Implements the multiway sparse clustering approach of M. Wang and Y. + Zeng, "Multiway clustering via tensor block models". Advances in Neural Information + Processing System 32 (NeurIPS), 715-725, 2019. + date_publication: '2020-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tensorsparse + url_git: '' +TensorTest2D: + version: 1.1.2 + title: Fitting Second-Order Tensor Data + maintainer: Mark Chen + description: |- + An implementation of fitting generalized linear models on + second-order tensor type data. The functions within this package mainly focus on + parameter estimation, including parameter coefficients and standard deviation. + date_publication: '2024-07-25' + bug_reports: https://github.com/yuting1214/TensorTest2D/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TensorTest2D + url_git: https://github.com/yuting1214/TensorTest2D +TensorTools: + version: 1.0.0 + title: Multilinear Algebra + maintainer: Kyle Caudle + description: A set of tools for basic tensor operators. A tensor in the context + of data analysis in a multidimensional array. The tools in this package rely on + using any discrete transformation (e.g. Fast Fourier Transform (FFT)). Standard + tools included are the Eigenvalue decomposition of a tensor, the QR decomposition + and LU decomposition. Other functionality includes the inverse of a tensor and + the transpose of a symmetric tensor. Functionality in the package is outlined + in Kernfeld, E., Kilmer, M., and Aeron, S. (2015) . + date_publication: '2024-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TensorTools + url_git: '' +tensorTS: + version: 1.0.2 + title: Factor and Autoregressive Models for Tensor Time Series + maintainer: Zebang Li + description: |- + Factor and autoregressive models for matrix and tensor valued time series. We provide functions for estimation, simulation and prediction. The models are discussed in + Li et al (2021) , Chen et al (2020) , + Chen et al (2020) , and Xiao et al (2020) . + date_publication: '2024-04-27' + bug_reports: https://github.com/ZeBang/tensorTS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tensorTS + url_git: https://github.com/zebang/tensorTS +tensr: + version: 1.0.1 + title: Covariance Inference and Decompositions for Tensor Datasets + maintainer: David Gerard + description: |- + A collection of functions for Kronecker structured covariance + estimation and testing under the array normal model. For estimation, + maximum likelihood and Bayesian equivariant estimation procedures are + implemented. For testing, a likelihood ratio testing procedure is + available. This package also contains additional functions for manipulating + and decomposing tensor data sets. This work was partially supported by NSF + grant DMS-1505136. Details of the methods are described in + Gerard and Hoff (2015) and + Gerard and Hoff (2016) . + date_publication: '2018-08-15' + bug_reports: http://github.com/dcgerard/tensr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tensr + url_git: '' +TEQR: + version: 6.0-0 + title: Target Equivalence Range Design + maintainer: M. Suzette Blanchard + description: The TEQR package contains software to calculate the operating characteristics + for the TEQR and the ACT designs.The TEQR (toxicity equivalence range) design + is a toxicity based cumulative cohort design with added safety rules. The ACT + (Activity constrained for toxicity) design is also a cumulative cohort design + with additional safety rules. The unique feature of this design is that dose is + escalated based on lack of activity rather than on lack of toxicity and is de-escalated + only if an unacceptable level of toxicity is experienced. + date_publication: '2016-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TEQR + url_git: '' +tergm: + version: 4.2.1 + title: |- + Fit, Simulate and Diagnose Models for Network Evolution Based on + Exponential-Family Random Graph Models + maintainer: Pavel N. Krivitsky + description: An integrated set of extensions to the 'ergm' package to analyze and + simulate network evolution based on exponential-family random graph models (ERGM). + 'tergm' is a part of the 'statnet' suite of packages for network analysis. See + Krivitsky and Handcock (2014) and Carnegie, Krivitsky, + Hunter, and Goodreau (2015) . + date_publication: '2024-10-08' + bug_reports: https://github.com/statnet/tergm/issues + url: https://statnet.org + url_cran: https://CRAN.R-project.org/package=tergm + url_git: '' +tergmLite: + version: 2.6.1 + title: |- + Fast Simulation of Simple Temporal Exponential Random Graph + Models + maintainer: Samuel M. Jenness + description: |- + Provides functions for the computationally efficient simulation of + dynamic networks estimated with the statistical framework of temporal + exponential random graph models, implemented in the 'tergm' package. + date_publication: '2022-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tergmLite + url_git: '' +tergo: + version: 0.1.8 + title: Style Your Code Fast + maintainer: Konrad Pagacz + description: |- + Provides a set of functions + that allow users for styling their R code according to + the 'tidyverse' style guide. The package uses a native + Rust implementation to ensure the highest performance. + Learn more about 'tergo' at . + date_publication: '2025-02-05' + bug_reports: https://github.com/kpagacz/tergo/issues + url: https://rtergo.pagacz.io + url_cran: https://CRAN.R-project.org/package=tergo + url_git: https://github.com/kpagacz/tergo +term: + version: 0.3.6 + title: Create, Manipulate and Query Parameter Terms + maintainer: Joe Thorley + description: |- + Creates, manipulates, queries and repairs vectors of + parameter terms. Parameter terms are the labels used to reference + values in vectors, matrices and arrays. They represent the names in + coefficient tables and the column names in 'mcmc' and 'mcmc.list' + objects. + date_publication: '2025-01-21' + bug_reports: https://github.com/poissonconsulting/term/issues + url: https://poissonconsulting.github.io/term/ + url_cran: https://CRAN.R-project.org/package=term + url_git: https://github.com/poissonconsulting/term +terminaldigits: + version: 0.1.0 + title: Tests of Uniformity and Independence for Terminal Digits + maintainer: Josh McCormick + description: |- + Implements simulated tests for the hypothesis that terminal digits are uniformly + distributed (chi-squared goodness-of-fit) and the hypothesis that terminal digits + are independent from preceding digits (several tests of independence for r x c + contingency tables). Also, for a number of distributions, implements Monte Carlo + simulations for type I errors and power for the test of independence. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=terminaldigits + url_git: '' +tern: + version: 0.9.7 + title: Create Common TLGs Used in Clinical Trials + maintainer: Joe Zhu + description: |- + Table, Listings, and Graphs (TLG) library for common outputs + used in clinical trials. + date_publication: '2025-01-17' + bug_reports: https://github.com/insightsengineering/tern/issues + url: https://insightsengineering.github.io/tern/ + url_cran: https://CRAN.R-project.org/package=tern + url_git: https://github.com/insightsengineering/tern/ +tern.gee: + version: 0.1.5 + title: |- + Tables and Graphs for Generalized Estimating Equations (GEE) + Model Fits + maintainer: Joe Zhu + description: |- + Generalized estimating equations (GEE) are a popular choice + for analyzing longitudinal binary outcomes. This package provides an + interface for fitting GEE, currently for logistic regression, within + the 'tern' framework (Zhu, + Sabanés Bové et al., 2023) and tabulate results easily using 'rtables' + (Becker, Waddell et al., + 2023). It builds on 'geepack' (Højsgaard, + Halekoh and Yan, 2006) for the actual GEE model fitting. + date_publication: '2024-08-23' + bug_reports: https://github.com/insightsengineering/tern.gee/issues + url: https://insightsengineering.github.io/tern.gee/ + url_cran: https://CRAN.R-project.org/package=tern.gee + url_git: https://github.com/insightsengineering/tern.gee/ +tern.mmrm: + version: 0.3.2 + title: Tables and Graphs for Mixed Models for Repeated Measures (MMRM) + maintainer: Joe Zhu + description: |- + Mixed models for repeated measures (MMRM) are a popular + choice for analyzing longitudinal continuous outcomes in randomized + clinical trials and beyond; see for example Cnaan, Laird and Slasor + (1997) + . + This package provides an interface for fitting MMRM within the 'tern' + framework by Zhu et al. + (2023) and tabulate results easily using 'rtables' + by Becker et al. (2023). + It builds on 'mmrm' by + Sabanés Bové et al. (2023) for the actual MMRM computations. + date_publication: '2024-09-23' + bug_reports: https://github.com/insightsengineering/tern.mmrm/issues + url: https://insightsengineering.github.io/tern.mmrm/ + url_cran: https://CRAN.R-project.org/package=tern.mmrm + url_git: https://github.com/insightsengineering/tern.mmrm +tern.rbmi: + version: 0.1.4 + title: Create Interface for 'RBMI' and 'tern' + maintainer: Joe Zhu + description: |- + 'RBMI' implements standard and reference based multiple imputation + methods for continuous longitudinal endpoints (Gower-Page et al. (2022) + ). This package provides an interface for 'RBMI' + uses the 'tern' framework by Zhu + et al. (2023) and tabulate results easily using 'rtables' + by Becker et al. (2023). + date_publication: '2024-11-26' + bug_reports: https://github.com/insightsengineering/tern.rbmi/issues + url: https://insightsengineering.github.io/tern.rbmi/ + url_cran: https://CRAN.R-project.org/package=tern.rbmi + url_git: https://github.com/insightsengineering/tern.rbmi +Ternary: + version: 2.3.3 + title: Create Ternary and Holdridge Plots + maintainer: Martin R. Smith + description: |- + Plots ternary diagrams (simplex plots / Gibbs triangles) and + Holdridge life zone plots using the + standard graphics functions. + Allows custom annotation, interpolating, contouring and scaling of plotting + region. + Includes a 'Shiny' user interface for point-and-click ternary plotting. + An alternative to 'ggtern', which uses the 'ggplot2' family of plotting + functions. + date_publication: '2024-08-27' + bug_reports: https://github.com/ms609/Ternary/issues/ + url: https://ms609.github.io/Ternary/ + url_cran: https://CRAN.R-project.org/package=Ternary + url_git: https://github.com/ms609/Ternary/ +ternvis: + version: '1.2' + title: |- + Visualisation, Verification and Calibration of Ternary + Probabilistic Forecasts + maintainer: Tim Jupp + description: A suite of functions for visualising ternary probabilistic forecasts, + as discussed in the paper by Jupp (2012) . + date_publication: '2019-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ternvis + url_git: '' +terra: + version: 1.8-29 + title: Spatial Data Analysis + maintainer: Robert J. Hijmans + description: Methods for spatial data analysis with vector (points, lines, polygons) + and raster (grid) data. Methods for vector data include geometric operations such + as intersect and buffer. Raster methods include local, focal, global, zonal and + geometric operations. The predict and interpolate methods facilitate the use of + regression type (interpolation, machine learning) models for spatial prediction, + including with satellite remote sensing data. Processing of very large files is + supported. See the manual and tutorials on to get started. + 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and + easier to use). + date_publication: '2025-02-26' + bug_reports: https://github.com/rspatial/terra/issues/ + url: https://rspatial.org/ + url_cran: https://CRAN.R-project.org/package=terra + url_git: '' +terrainmeshr: + version: 0.1.0 + title: Triangulate and Simplify 3D Terrain Meshes + maintainer: Tyler Morgan-Wall + description: Provides triangulations of regular height fields, based on the methods + described in "Fast Polygonal Approximation of Terrains and Height Fields" Michael + Garland and Paul S. Heckbert (1995) + using code from the 'hmm' library written by Michael Fogleman . + date_publication: '2020-04-29' + bug_reports: https://www.github.com/tylermorganwall/terrainmeshr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=terrainmeshr + url_git: https://www.github.com/tylermorganwall/terrainmeshr +terrainr: + version: 0.7.5 + title: Landscape Visualizations in R and 'Unity' + maintainer: Michael Mahoney + description: |- + Functions for the retrieval, manipulation, and visualization + of 'geospatial' data, with an aim towards producing '3D' landscape + visualizations in the 'Unity' '3D' rendering engine. Functions are + also provided for retrieving elevation data and base map tiles from + the 'USGS' National Map . + date_publication: '2023-10-04' + bug_reports: https://github.com/ropensci/terrainr/issues + url: https://docs.ropensci.org/terrainr/ + url_cran: https://CRAN.R-project.org/package=terrainr + url_git: https://github.com/ropensci/terrainr +TesiproV: + version: 0.9.2 + title: |- + Calculation of Reliability and Failure Probability in Civil + Engineering + maintainer: Konstantin Nille-Hauf + description: 'Calculate the failure probability of civil engineering problems with + Level I up to Level III Methods. Have fun and enjoy. References: Spaethe (1991, + ISBN:3-211-82348-4) "Die Sicherheit tragender Baukonstruktionen", AU,BECK (2001) + "Estimation of small failure probabilities in high dimensions by subset simulation." + , Breitung (1989) "Asymptotic approximations + for probability integrals." .' + date_publication: '2022-03-25' + bug_reports: '' + url: https://www.hochschule-biberach.de/transfer/forschung/institut-fuer-konstruktiven-ingenieurbau + url_cran: https://CRAN.R-project.org/package=TesiproV + url_git: '' +TESS: + version: 2.1.2 + title: |- + Diversification Rate Estimation and Fast Simulation of + Reconstructed Phylogenetic Trees under Tree-Wide + Time-Heterogeneous Birth-Death Processes Including + Mass-Extinction Events + maintainer: Sebastian Hoehna + description: Simulation of reconstructed phylogenetic trees under tree-wide time-heterogeneous + birth-death processes and estimation of diversification parameters under the same + model. Speciation and extinction rates can be any function of time and mass-extinction + events at specific times can be provided. Trees can be simulated either conditioned + on the number of species, the time of the process, or both. Additionally, the + likelihood equations are implemented for convenience and can be used for Maximum + Likelihood (ML) estimation and Bayesian inference. + date_publication: '2022-04-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TESS + url_git: '' +tessellation: + version: 2.3.0 + title: Delaunay and Voronoï Tessellations + maintainer: Stéphane Laurent + description: |- + Delaunay and Voronoï tessellations, with emphasis on the + two-dimensional and the three-dimensional cases (the package provides + functions to plot the tessellations for these cases). Delaunay + tessellations are computed in C with the help of the 'Qhull' library + . + date_publication: '2023-12-18' + bug_reports: https://github.com/stla/tessellation/issues + url: https://stla.github.io/tessellation/ + url_cran: https://CRAN.R-project.org/package=tessellation + url_git: https://github.com/stla/tessellation +tesselle: + version: 1.5.0 + title: Easily Install and Load 'tesselle' Packages + maintainer: Nicolas Frerebeau + description: |- + Easy install and load key packages from the 'tesselle' suite + in a single step. The 'tesselle' suite is a collection of packages for + research and teaching in archaeology. These packages focus on + quantitative analysis methods developed for archaeology. The + 'tesselle' packages are designed to work seamlessly together and to + complement general-purpose and other specialized statistical packages. + These packages can be used to explore and analyze common data types in + archaeology: count data, compositional data and chronological data. + Learn more about 'tesselle' at . + date_publication: '2024-12-10' + bug_reports: https://github.com/tesselle/tesselle/issues + url: https://packages.tesselle.org/tesselle/ + url_cran: https://CRAN.R-project.org/package=tesselle + url_git: https://github.com/tesselle/tesselle +tesseract: + version: 5.2.2 + title: Open Source OCR Engine + maintainer: Jeroen Ooms + description: |- + Bindings to 'Tesseract': + a powerful optical character recognition (OCR) engine that supports over 100 languages. + The engine is highly configurable in order to tune the detection algorithms and + obtain the best possible results. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/tesseract/issues + url: https://docs.ropensci.org/tesseract/https://ropensci.r-universe.dev/tesseract + url_cran: https://CRAN.R-project.org/package=tesseract + url_git: '' +test2norm: + version: 0.3.0 + title: Normative Standards for Cognitive Tests + maintainer: Anya Umlauf + description: |- + Package test2norm contains functions to generate formulas for + normative standards applied to cognitive tests. It takes raw test scores + (e.g., number of correct responses) and converts them to scaled scores and + demographically adjusted scores, using methods described in Heaton et al. + (2003) & Heaton et al. (2009, + ISBN:9780199702800). The scaled scores are calculated as quantiles of the + raw test scores, scaled to have the mean of 10 and standard deviation of 3, + such that higher values always correspond to better performance on the test. + The demographically adjusted scores are calculated from the residuals of a + model that regresses scaled scores on demographic predictors (e.g., age). + The norming procedure makes use of the mfp2() function from the 'mfp2' + package to explore nonlinear associations between cognition and demographic + variables. + date_publication: '2024-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=test2norm + url_git: '' +TestAnaAPP: + version: 1.1.2 + title: A 'shiny' App for Test Analysis and Visualization + maintainer: Youxiang Jiang + description: This application provides exploratory and confirmatory factor analysis, + classical test theory, unidimensional and multidimensional item response theory, + and continuous item response model analysis, through the 'shiny' interactive interface. + In addition, it offers rich functionalities for visualizing and downloading results. + Users can download figures, tables, and analysis reports via the interactive interface. + date_publication: '2024-11-09' + bug_reports: https://github.com/jiangyouxiang/TestAnaAPP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TestAnaAPP + url_git: https://github.com/jiangyouxiang/TestAnaAPP +testarguments: + version: 0.0.1 + title: Test (Multiple) Arguments of a User-Defined Prediction Algorithm + maintainer: Matthew Sainsbury-Dale + description: Finding the best values for user-specified arguments of a prediction + algorithm can be difficult, particularly if there is an interaction between argument + levels. This package automates the testing of any user-defined prediction algorithm + over an arbitrary number of arguments. It includes functions for testing the algorithm + over the given arguments with respect to an arbitrary number of user-defined diagnostics, + visualising the results of these tests, and finding the optimal argument combinations + with respect to each diagnostic. + date_publication: '2021-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testarguments + url_git: '' +testassay: + version: 0.1.1 + title: |- + A Hypothesis Testing Framework for Validating an Assay for + Precision + maintainer: Michael C Sachs + description: |- + A common way of validating a biological assay for is through a + procedure, where m levels of an analyte are measured with n replicates at each + level, and if all m estimates of the coefficient of variation (CV) are less + than some prespecified level, then the assay is declared validated for precision + within the range of the m analyte levels. Two limitations of this procedure are: + there is no clear statistical statement of precision upon passing, and it is + unclear how to modify the procedure for assays with constant standard deviation. + We provide tools to convert such a procedure into a set of m hypothesis tests. + This reframing motivates the m:n:q procedure, which upon completion delivers + a 100q% upper confidence limit on the CV. Additionally, for a post-validation + assay output of y, the method gives an ``effective standard deviation interval'' + of log(y) plus or minus r, which is a 68% confidence interval on log(mu), where + mu is the expected value of the assay output for that sample. Further, the m:n:q + procedure can be straightforwardly applied to constant standard deviation assays. + We illustrate these tools by applying them to a growth inhibition assay. This is + an implementation of the methods described in Fay, Sachs, and Miura (2018) + . + date_publication: '2020-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testassay + url_git: '' +testCompareR: + version: 1.1.1 + title: |- + Comparing Two Diagnostic Tests with Dichotomous Results using + Paired Data + maintainer: Kyle J. Wilson + description: |- + Provides a method for comparing the results of two binary diagnostic tests using paired data. + Users can rapidly perform descriptive and inferential statistics in a single function call. Options permit users to select which parameters they are interested in comparing and methods for correction for multiple comparisons. + Confidence intervals are calculated using the methods with the best coverage. Hypothesis tests use the methods with the best asymptotic performance. A summary of the methods is available in Roldán-Nofuentes (2020) . + This package is targeted at clinical researchers who want to rapidly and effectively compare results from binary diagnostic tests. + date_publication: '2024-11-20' + bug_reports: https://github.com/Kajlinko/testCompareR/issues + url: https://kajlinko.github.io/testCompareR/ + url_cran: https://CRAN.R-project.org/package=testCompareR + url_git: https://github.com/Kajlinko/testCompareR +TestCor: + version: 0.0.2.2 + title: |- + FWER and FDR Controlling Procedures for Multiple Correlation + Tests + maintainer: Gannaz Irene + description: |2- + + Different multiple testing procedures for correlation tests are implemented. These procedures were shown to theoretically control asymptotically the Family Wise Error Rate (Roux (2018) ) or the False Discovery Rate (Cai & Liu (2016) ). The package gather four test statistics used in correlation testing, four FWER procedures with either single step or stepdown versions, and four FDR procedures. + date_publication: '2020-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestCor + url_git: '' +testcorr: + version: 0.2.0 + title: Testing Zero Correlation + maintainer: Violetta Dalla + description: Computes the test statistics for examining the significance of autocorrelation + in univariate time series, cross-correlation in bivariate time series, Pearson + correlations in multivariate series and test statistics for i.i.d. property of + univariate series given in Dalla, Giraitis and Phillips (2020), . + date_publication: '2021-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testcorr + url_git: '' +testdat: + version: 0.4.2 + title: Data Unit Testing for R + maintainer: Danny Smith + description: |- + Test your data! An extension of the 'testthat' unit testing + framework with a family of functions and reporting tools for checking + and validating data frames. + date_publication: '2023-09-04' + bug_reports: https://github.com/socialresearchcentre/testdat/issues + url: https://socialresearchcentre.github.io/testdat/ + url_cran: https://CRAN.R-project.org/package=testdat + url_git: https://github.com/socialresearchcentre/testdat +TestDataImputation: + version: '2.3' + title: Missing Item Responses Imputation for Test and Assessment Data + maintainer: Shenghai Dai + description: |- + Functions for imputing missing item responses for dichotomous and + polytomous test and assessment data. This package enables missing imputation + methods that are suitable for test and assessment data, including: + listwise (LW) deletion (see De Ayala et al. 2001 ), + treating as incorrect (IN, see Lord, 1974 ; + Mislevy & Wu, 1996 ; + Pohl et al., 2014 ), person mean imputation (PM), + item mean imputation (IM), two-way (TW) and response function (RF) imputation, + (see Sijtsma & van der Ark, 2003 ), + logistic regression (LR) imputation, predictive mean matching (PMM), and expectation–maximization (EM) + imputation (see Finch, 2008 ). + date_publication: '2021-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestDataImputation + url_git: '' +TestDesign: + version: 1.7.0 + title: |- + Optimal Test Design Approach to Fixed and Adaptive Test + Construction + maintainer: Seung W. Choi + description: |- + Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and + van der Linden (2018) to construct fixed, adaptive, and parallel tests. + Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', + 'highs', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see . + date_publication: '2024-08-22' + bug_reports: https://github.com/choi-phd/TestDesign/issues/ + url: https://choi-phd.github.io/TestDesign/(documentation) + url_cran: https://CRAN.R-project.org/package=TestDesign + url_git: '' +TestDimorph: + version: 0.5.8 + title: |- + Analysis of the Interpopulation Difference in Degree of Sexual + Dimorphism Using Summary Statistics + maintainer: Bassam A. Abulnoor + description: Offers a solution for the unavailability of raw data in most anthropological + studies by facilitating the calculations of several sexual dimorphism related + analyses using the published summary statistics of metric data (mean, standard + deviation and sex specific sample size) as illustrated by the works of Relethford, + J. H., & Hodges, D. C. (1985) , Greene, D. L. (1989) + and Konigsberg, L. W. (1991) . + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestDimorph + url_git: '' +testDriveR: + version: 0.5.3 + title: Teaching Data for Statistics and Data Science + maintainer: Christopher Prener + description: |- + Provides data sets for teaching statistics and data science courses. + It includes a sample of data from John Edmund Kerrich's famous + coinflip experiment. These are data that I used for statistics. The package + also contains an R Markdown template with the required formatting for + assignments in my former courses. + date_publication: '2025-02-02' + bug_reports: https://github.com/chris-prener/testDriveR/issues + url: https://chris-prener.github.io/testDriveR/ + url_cran: https://CRAN.R-project.org/package=testDriveR + url_git: https://github.com/chris-prener/testDriveR +testequavar: + version: 0.1.5 + title: Bootstrap Tests for Equality of 2, 3, or 4 Population Variances + maintainer: Dexter Cahoy + description: |- + Tests the hypothesis that variances are homogeneous or not using bootstrap. The procedure uses a variance-based statistic, and is derived from a normal-theory test. + The test equivalently expressed the hypothesis as a function of the log contrasts of the population variances. A box-type acceptance region is constructed to test the hypothesis. See Cahoy (2010) \doi{10.1016/j.csda.2010.04.012}. + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testequavar + url_git: '' +tester: + version: 0.2.0 + title: Tests and Checks Characteristics of R Objects + maintainer: Frederic Bertrand + description: Allows users to test characteristics of common R objects. + date_publication: '2024-04-04' + bug_reports: https://github.com/fbertran/tester/issues/ + url: https://fbertran.github.io/tester/ + url_cran: https://CRAN.R-project.org/package=tester + url_git: https://github.com/fbertran/tester/ +testex: + version: 0.2.0 + title: Add Tests to Examples + maintainer: Doug Kelkhoff + description: |- + Add tests in-line in examples. Provides standalone functions for + facilitating easier test writing in Rd files. However, a more familiar + interface is provided using 'roxygen2' tags. Tools are also provided for + facilitating package configuration and use with 'testthat'. + date_publication: '2024-04-14' + bug_reports: '' + url: https://dgkf.github.io/testex/ + url_cran: https://CRAN.R-project.org/package=testex + url_git: https://github.com/dgkf/testex +testforDEP: + version: 0.2.0 + title: Dependence Tests for Two Variables + maintainer: En-shuo Hsu + description: Provides test statistics, p-value, and confidence intervals based on + 9 hypothesis tests for dependence. + date_publication: '2017-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testforDEP + url_git: '' +TestFunctions: + version: 0.2.2 + title: |- + Test Functions for Simulation Experiments and Evaluating + Optimization and Emulation Algorithms + maintainer: Collin Erickson + description: |- + Test functions are often used to test computer code. + They are used in optimization to test algorithms and in + metamodeling to evaluate model predictions. This package provides + test functions that can be used for any purpose. + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestFunctions + url_git: '' +TestGardener: + version: 3.3.5 + title: Information Analysis for Test and Rating Scale Data + maintainer: James Ramsay + description: |- + Develop, evaluate, and score multiple choice examinations, + psychological scales, questionnaires, and similar types of data involving + sequences of choices among one or more sets of answers. + This version of the package should be considered as brand new. Almost all + of the functions have been changed, including their argument list. + See the file NEWS.Rd in the Inst folder for more information. + Using the package does not require any formal statistical knowledge + beyond what would be provided by a first course in statistics in a + social science department. There the user would encounter the concept + of probability and how it is used to model data and make decisions, + and would become familiar with basic mathematical and statistical notation. + Most of the output is in graphical form. + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestGardener + url_git: '' +TestGenerator: + version: 0.3.3 + title: Integration Unit Tests for Pharmacoepidemiological Studies + maintainer: Cesar Barboza + description: Push a sample population for unit testing on data mapped to the Observational + Medical Outcomes Partnership (OMOP) Common Data Model. + date_publication: '2024-11-08' + bug_reports: https://github.com/darwin-eu/TestGenerator/issues + url: https://darwin-eu.github.io/TestGenerator/ + url_cran: https://CRAN.R-project.org/package=TestGenerator + url_git: https://github.com/darwin-eu/TestGenerator +TestIndVars: + version: 0.1.0 + title: |- + Testing the Independence of Variables for Specific Covariance + Structures + maintainer: Mina Norouzirad + description: Test the nullity of covariances, in a set of variables, using a simple + univariate procedure. See Marques, Diago, Norouzirad, Bispo (2023) . + date_publication: '2024-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestIndVars + url_git: https://github.com/mnrzrad/TestIndVars +TestingSimilarity: + version: '1.1' + title: |- + Bootstrap Test for the Similarity of Dose Response Curves + Concerning the Maximum Absolute Deviation + maintainer: Kathrin Moellenhoff + description: Provides a bootstrap test which decides whether two dose response curves + can be assumed as equal concerning their maximum absolute deviation. A plenty + of choices for the model types are available, which can be found in the 'DoseFinding' + package, which is used for the fitting of the models. See + for details. + date_publication: '2019-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestingSimilarity + url_git: '' +testit: + version: '0.13' + title: A Simple Package for Testing R Packages + maintainer: Yihui Xie + description: |- + Provides two convenience functions assert() and test_pkg() to + facilitate testing R packages. + date_publication: '2021-04-14' + bug_reports: https://github.com/yihui/testit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=testit + url_git: https://github.com/yihui/testit +TestScorer: + version: 1.7.2 + title: |- + GUI for Entering Test Items and Obtaining Raw and Transformed + Scores + maintainer: Manel Salamero + description: |- + GUI for entering test items and obtaining raw + and transformed scores. The results are shown on the + console and can be saved to a tabular text file for further + statistical analysis. The user can define his own tests and + scoring procedures through a GUI. + date_publication: '2016-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestScorer + url_git: '' +TestsSymmetry: + version: 1.0.0 + title: Tests for Symmetry when the Center of Symmetry is Unknown + maintainer: Jiaojiao Zhou + description: Provides functionality of a statistical testing implementation whether + a dataset comes from a symmetric distribution when the center of symmetry is unknown, + including Wilcoxon test and sign test procedure. In addition, sample size determination + for both tests is provided. The Wilcoxon test procedure is described in Vexler + et al. (2023) , + and the sign test is outlined in Gastwirth (1971) . + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TestsSymmetry + url_git: '' +testthat: + version: 3.2.3 + title: Unit Testing for R + maintainer: Hadley Wickham + description: |- + Software testing is important, but, in part because it is + frustrating and boring, many of us avoid it. 'testthat' is a testing + framework for R that is easy to learn and use, and integrates with + your existing 'workflow'. + date_publication: '2025-01-13' + bug_reports: https://github.com/r-lib/testthat/issues + url: https://testthat.r-lib.org + url_cran: https://CRAN.R-project.org/package=testthat + url_git: https://github.com/r-lib/testthat +testthatmulti: + version: 0.1.0 + title: Testing for R Packages with Multiple Attempts for Noisy Tests + maintainer: Collin Erickson + description: |- + Runs tests using the 'testthat' package but allows for multiple + attempts for a single test. This is useful for noisy or flaky tests + that generally pass but can fail due to occasional random errors, + such as numeric instability or using random data. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testthatmulti + url_git: '' +testthis: + version: 1.1.1 + title: Utils and 'RStudio' Addins to Make Testing Even More Fun + maintainer: Stefan Fleck + description: |- + Utility functions and 'RStudio' addins for writing, + running and organizing automated tests. Integrates tightly with the + packages 'testthat', 'devtools' and 'usethis'. Hotkeys can be + assigned to the 'RStudio' addins for running tests in a single file or + to switch between a source file and the associated test file. In + addition, testthis provides function to manage and run tests in + subdirectories of the test/testthat directory. + date_publication: '2020-04-12' + bug_reports: https://github.com/s-fleck/testthis/issues + url: https://s-fleck.github.io/testthis + url_cran: https://CRAN.R-project.org/package=testthis + url_git: '' +testtwice: + version: 1.0.3 + title: Testing One Hypothesis Twice in Observational Studies + maintainer: Paul R. Rosenbaum + description: Tests one hypothesis with several test statistics, correcting for multiple + testing. The central function in the package is testtwice(). In a sensitivity + analysis, the method has the largest design sensitivity of its component tests. The + package implements the method and examples in Rosenbaum, P. R. (2012) + Testing one hypothesis twice in observational studies. Biometrika, 99(4), 763-774. + date_publication: '2020-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=testtwice + url_git: '' +tetraclasse: + version: 0.1.21 + title: Satisfaction Analysis using Tetraclasse Model and Llosa Matrix + maintainer: vincent guyader + description: The satisfaction Analysis using the tetraclasse model from Sylvie Llosa. + Llosa (1997) . + date_publication: '2017-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tetraclasse + url_git: '' +tetragon: + version: 1.3.0 + title: |- + Automatic Sequence Prediction by Expansion of the Distance + Matrix + maintainer: Giancarlo Vercellino + description: Each sequence is predicted by expanding the distance matrix. The compact + set of hyper-parameters is tuned through random search. + date_publication: '2022-08-13' + bug_reports: '' + url: https://rpubs.com/giancarlo_vercellino/tetragon + url_cran: https://CRAN.R-project.org/package=tetragon + url_git: '' +tetrascatt: + version: 0.1.1 + title: Acoustic Scattering for Complex Shapes by Using the DWBA + maintainer: Juan Domingo Gonzalez + description: |- + Uses the Distorted Wave Born Approximation (DWBA) to compute the + acoustic backward scattering, the geometry of the object is formed by a + volumetric mesh, composed of tetrahedrons. This computation is done efficiently + through an analytical 3D integration that allows for a solution which is + expressed in terms of elementary functions for each tetrahedron. + It is important to note that this method is only valid for objects whose + acoustic properties, such as density and sound speed, do not vary significantly + compared to the surrounding medium. (See Lavia, Cascallares and Gonzalez, J. D. (2023). + TetraScatt model: Born approximation for the estimation of acoustic dispersion of + fluid-like objects of arbitrary geometries. arXiv preprint ). + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tetrascatt + url_git: '' +tetRys: + version: '1.2' + title: Game of 'tetRys' + maintainer: Carsten Croonenbroeck + description: A game inspired by 'Tetris'. Opens a plot window device and starts + a game of 'tetRys' in it. Steer the tetrominos with the arrow keys, press Pause + to pause and Esc to end the game. + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tetRys + url_git: '' +Tex4exams: + version: 0.1.2 + title: Generating 'Sweave' Code for 'R/exams' Questions in Mathematics + maintainer: Qingwen Hu + description: When using the R package 'exams' to write mathematics questions in + 'Sweave' files, the output of a lot of R functions need to be adjusted for display + in mathematical formulas. Specifically, the functions were accumulated when writing + questions for the topics of the mathematics courses College Algebra, Precalculus, + Calculus, Differential Equations, Introduction to Probability, and Linear Algebra. The + output of the developed functions can be used in 'Sweave' files. + date_publication: '2023-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tex4exams + url_git: '' +TeXCheckR: + version: 0.8.1 + title: Parses LaTeX Documents for Errors + maintainer: Hugh Parsonage + description: Checks LaTeX documents and .bib files for typing errors, such as spelling + errors, incorrect quotation marks. Also provides useful functions for parsing + and linting bibliography files. + date_publication: '2024-02-04' + bug_reports: https://github.com/HughParsonage/TeXCheckR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TeXCheckR + url_git: https://github.com/HughParsonage/TeXCheckR +TexExamRandomizer: + version: 1.2.7 + title: Personalizes and Randomizes Exams Written in 'LaTeX' + maintainer: Alejandro Gonzalez Recuenco + description: |- + Randomizing exams with 'LaTeX'. + If you can compile your main document with 'LaTeX', the program should be able to compile the randomized + versions without much extra effort when creating the document. + date_publication: '2024-01-23' + bug_reports: https://github.com/alexrecuenco/TexExamRandomizer/issues + url: https://alexrecuenco.github.io/TexExamRandomizer/ + url_cran: https://CRAN.R-project.org/package=TexExamRandomizer + url_git: https://github.com/alexrecuenco/TexExamRandomizer +texmex: + version: 2.4.9 + title: Statistical Modelling of Extreme Values + maintainer: Harry Southworth + description: |- + Statistical extreme value modelling of threshold excesses, maxima + and multivariate extremes. Univariate models for threshold excesses and maxima + are the Generalised Pareto, and Generalised Extreme Value model respectively. + These models may be fitted by using maximum (optionally penalised-)likelihood, + or Bayesian estimation, and both classes of models may be fitted with covariates + in any/all model parameters. Model diagnostics support the fitting process. + Graphical output for visualising fitted models and return level estimates is + provided. For serially dependent sequences, the intervals declustering algorithm + of Ferro and Segers (2003) is provided, with + diagnostic support to aid selection of threshold and declustering horizon. + Multivariate modelling is performed via the conditional approach of Heffernan + and Tawn (2004) , with graphical tools for + threshold selection and to diagnose estimation convergence. + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=texmex + url_git: https://github.com/harrysouthworth/texmex +texor: + version: 1.5.3 + title: Converting 'LaTeX' 'R Journal' Articles into 'RJ-web-articles' + maintainer: Abhishek Ulayil + description: |- + Articles in the 'R Journal' were first authored in 'LaTeX', which performs + admirably for 'PDF' files but is less than ideal for modern online interfaces. + The 'texor' package does all the transitional chores and conversions necessary + to move to the online versions. + date_publication: '2024-12-13' + bug_reports: https://github.com/Abhi-1U/texor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=texor + url_git: https://github.com/Abhi-1U/texor +TExPosition: + version: 2.6.10.1 + title: Two-Table ExPosition + maintainer: Derek Beaton + description: An extension of ExPosition for two table analyses, specifically, discriminant + analyses. + date_publication: '2019-01-31' + bug_reports: http://code.google.com/p/exposition-family/issues/list + url: '' + url_cran: https://CRAN.R-project.org/package=TExPosition + url_git: '' +texPreview: + version: 2.1.0 + title: Compile and Preview Snippets of 'LaTeX' + maintainer: Jonathan Sidi + description: |- + Compile snippets of 'LaTeX' directly into images + from the R console to view in the 'RStudio' viewer pane, Shiny apps + and 'RMarkdown' documents. + date_publication: '2024-01-24' + bug_reports: https://github.com/yonicd/texPreview/issues + url: '' + url_cran: https://CRAN.R-project.org/package=texPreview + url_git: https://github.com/yonicd/texPreview +texreg: + version: 1.39.4 + title: Conversion of R Regression Output to LaTeX or HTML Tables + maintainer: Philip Leifeld + description: Converts coefficients, standard errors, significance stars, and goodness-of-fit + statistics of statistical models into LaTeX tables or HTML tables/MS Word documents + or to nicely formatted screen output for the R console for easy model comparison. + A list of several models can be combined in a single table. The output is highly + customizable. New model types can be easily implemented. Details can be found + in Leifeld (2013), JStatSoft .) + date_publication: '2024-07-24' + bug_reports: https://github.com/leifeld/texreg/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=texreg + url_git: https://github.com/leifeld/texreg/ +text: + version: 1.3.0 + title: |- + Analyses of Text using Transformers Models from HuggingFace, + Natural Language Processing and Machine Learning + maintainer: Oscar Kjell + description: Link R with Transformers from Hugging Face to transform text variables + to word embeddings; where the word embeddings are used to statistically test the + mean difference between set of texts, compute semantic similarity scores between + texts, predict numerical variables, and visual statistically significant words + according to various dimensions etc. For more information see . + date_publication: '2024-12-05' + bug_reports: https://github.com/OscarKjell/text/issues/ + url: https://r-text.org/ + url_cran: https://CRAN.R-project.org/package=text + url_git: https://github.com/OscarKjell/text/ +text.alignment: + version: 0.1.4 + title: Text Alignment with Smith-Waterman + maintainer: Jan Wijffels + description: |- + Find similarities between texts using the Smith-Waterman algorithm. The algorithm performs local sequence alignment and determines similar regions between two strings. + The Smith-Waterman algorithm is explained in the paper: "Identification of common molecular subsequences" by T.F.Smith and M.S.Waterman (1981), available at . + This package implements the same logic for sequences of words and letters instead of molecular sequences. + date_publication: '2023-09-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=text.alignment + url_git: https://github.com/DIGI-VUB/text.alignment +text2map: + version: 0.2.0 + title: R Tools for Text Matrices, Embeddings, and Networks + maintainer: Dustin Stoltz + description: |- + This is a collection of functions optimized for working with + with various kinds of text matrices. Focusing on + the text matrix as the primary object - represented + either as a base R dense matrix or a 'Matrix' package sparse + matrix - allows for a consistent and intuitive interface + that stays close to the underlying mathematical foundation + of computational text analysis. In particular, the package + includes functions for working with word embeddings, + text networks, and document-term matrices. Methods developed in + Stoltz and Taylor (2019) , + Taylor and Stoltz (2020) , + Taylor and Stoltz (2020) , and + Stoltz and Taylor (2021) . + date_publication: '2024-04-11' + bug_reports: https://gitlab.com/culturalcartography/text2map/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=text2map + url_git: https://gitlab.com/culturalcartography/text2map +text2sdg: + version: 1.1.1 + title: Detecting UN Sustainable Development Goals in Text + maintainer: Dominik S. Meier + description: The United Nations’ Sustainable Development Goals (SDGs) have become + an important guideline for organisations to monitor and plan their contributions + to social, economic, and environmental transformations. The 'text2sdg' package + is an open-source analysis package that identifies SDGs in text using scientifically + developed query systems, opening up the opportunity to monitor any type of text-based + data, such as scientific output or corporate publications. For more information + regarding the methodology see Meier, Mata & Wulff (2022) . + date_publication: '2023-03-17' + bug_reports: https://github.com/dwulff/text2sdg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=text2sdg + url_git: https://github.com/dwulff/text2sdg +text2sdgData: + version: 0.1.1 + title: Contains the Trained 'text2sdg' Ensemble Model Data + maintainer: Dominik S. Meier + description: This is a companion package for the 'text2sdg' package. It contains + the trained ensemble models needed by the 'detect_sdg' function from the 'text2sdg' + package. See Wulff, Meier and Mata (2023) and Meier, Wulff + and Mata (2021) for reference. + date_publication: '2023-03-17' + bug_reports: https://github.com/psychobas/text2sdgData/issues + url: '' + url_cran: https://CRAN.R-project.org/package=text2sdgData + url_git: https://github.com/psychobas/text2sdgData +text2speech: + version: 1.0.0 + title: Text to Speech Conversion + maintainer: Howard Baek + description: |- + Converts text into speech using various text-to-speech (TTS) engines and provides an unified interface for accessing their functionality. + With this package, users can easily generate audio files of spoken words, phrases, or sentences from plain text data. The package supports multiple TTS engines, + including Google's 'Cloud Text-to-Speech API', 'Amazon Polly', Microsoft's 'Cognitive Services Text to Speech REST API', and a free TTS engine called 'Coqui TTS'. + date_publication: '2023-07-19' + bug_reports: https://github.com/jhudsl/text2speech/issues + url: '' + url_cran: https://CRAN.R-project.org/package=text2speech + url_git: https://github.com/jhudsl/text2speech +text2vec: + version: 0.6.4 + title: Modern Text Mining Framework for R + maintainer: Dmitriy Selivanov + description: |- + Fast and memory-friendly tools for text vectorization, topic + modeling (LDA, LSA), word embeddings (GloVe), similarities. This package + provides a source-agnostic streaming API, which allows researchers to perform + analysis of collections of documents which are larger than available RAM. All + core functions are parallelized to benefit from multicore machines. + date_publication: '2023-11-09' + bug_reports: https://github.com/dselivanov/text2vec/issues + url: http://text2vec.org + url_cran: https://CRAN.R-project.org/package=text2vec + url_git: '' +textab: + version: 1.0.1 + title: Create Highly-Customized 'LaTeX' Tables + maintainer: Bradley Setzler + description: Generate 'LaTeX' tables directly from R. It builds 'LaTeX' tables in + blocks in the spirit of 'ggplot2' using the '+' and '/' operators for concatenation + in the vertical and horizontal dimensions, respectively. It exports tables in + the 'LaTeX' tabular environment using '.tex' code. It can compile '.tex' code + to 'PDF' automatically. + date_publication: '2023-04-25' + bug_reports: https://github.com/setzler/textab/issues + url: https://setzler.github.io/textab/ + url_cran: https://CRAN.R-project.org/package=textab + url_git: '' +textanalyzer: + version: 0.2.0 + title: '''textanalyzer'', an R Package to Analyze Text' + maintainer: Pushker Ravindra + description: It analyzes text to create a count of top n-grams, including tokens + (one-word), bigrams(two-word), and trigrams (three-word), while removing all stopwords. + It also plots the n-grams and corresponding counts as a bar chart. + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textanalyzer + url_git: '' +textAnnotatoR: + version: 0.1.4 + title: Interactive Text Annotation Tool with 'shiny' GUI + maintainer: Chao Liu + description: |- + A comprehensive text annotation tool built with 'shiny'. Provides an + interactive graphical user interface for coding text documents, + managing code hierarchies, creating memos, and analyzing coding patterns. + Features include code co-occurrence analysis, visualization of coding patterns, + comparison of multiple coding sets, and export capabilities. Supports + collaborative qualitative research through standardized annotation formats + and analysis tools. + date_publication: '2024-11-12' + bug_reports: https://github.com/chaoliu-cl/textAnnotatoR/issues + url: http://liu-chao.site/textAnnotatoR/ + url_cran: https://CRAN.R-project.org/package=textAnnotatoR + url_git: https://github.com/chaoliu-cl/textAnnotatoR +textBoxPlacement: + version: '1.0' + title: |- + Compute a Non-Overlapping Layout of Text Boxes to Label Multiple + Overlain Plots + maintainer: Barry Zeeberg + description: Compute a non-overlapping layout of text boxes to label multiple overlain + curves. For each curve, iteratively search for an adjacent x,y position for the + text box that does not overlap with the other curves. If this process fails, then + offsets are computed to add to the y values for each curve, that results in sufficient + space to add all of the text labels. + date_publication: '2023-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textBoxPlacement + url_git: '' +textcat: + version: 1.0-9 + title: N-Gram Based Text Categorization + maintainer: Kurt Hornik + description: Text categorization based on n-grams. + date_publication: '2024-11-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textcat + url_git: '' +textclean: + version: 0.9.3 + title: Text Cleaning Tools + maintainer: Tyler Rinker + description: |- + Tools to clean and process text. Tools are geared at checking for substrings that + are not optimal for analysis and replacing or removing them (normalizing) with more + analysis friendly substrings (see Sproat, Black, Chen, Kumar, Ostendorf, & Richards + (2001) ) or extracting them into new variables. For + example, emoticons are often used in text but not always easily handled by analysis + algorithms. The replace_emoticon() function replaces emoticons with word + equivalents. + date_publication: '2018-07-23' + bug_reports: https://github.com/trinker/textclean/issues + url: '' + url_cran: https://CRAN.R-project.org/package=textclean + url_git: https://github.com/trinker/textclean +textdata: + version: 0.4.5 + title: Download and Load Various Text Datasets + maintainer: Emil Hvitfeldt + description: |- + Provides a framework to download, parse, and store text + datasets on the disk and load them when needed. Includes various + sentiment lexicons and labeled text data sets for classification and + analysis. + date_publication: '2024-05-28' + bug_reports: https://github.com/EmilHvitfeldt/textdata/issues + url: https://emilhvitfeldt.github.io/textdata/ + url_cran: https://CRAN.R-project.org/package=textdata + url_git: https://github.com/EmilHvitfeldt/textdata +texteffect: + version: '0.3' + title: |- + Discovering Latent Treatments in Text Corpora and Estimating + Their Causal Effects + maintainer: Christian Fong + description: |- + Implements the approach described in Fong and Grimmer (2016) for + automatically discovering latent treatments from a corpus and estimating the average marginal component effect (AMCE) of + each treatment. The data is divided into a training and test set. The supervised Indian Buffet Process (sibp) is used + to discover latent treatments in the training set. The fitted model is then applied to the test set to infer the values + of the latent treatments in the test set. Finally, Y is regressed on the latent treatments in the test set to estimate + the causal effect of each treatment. + date_publication: '2019-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=texteffect + url_git: '' +texter: + version: 0.1.9 + title: An Easy Text and Sentiment Analysis Library + maintainer: Simi Kafaru + description: |- + Implement text and sentiment analysis with 'texter'. + Generate sentiment scores on text data and also visualize sentiments. + 'texter' allows you to quickly generate insights on your data. + It includes support for lexicons such as 'NRC' and 'Bing'. + date_publication: '2021-09-20' + bug_reports: https://github.com/simmieyungie/texter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=texter + url_git: https://github.com/simmieyungie/texter +TextForecast: + version: 0.1.3 + title: |- + Regression Analysis and Forecasting Using Textual Data from a + Time-Varying Dictionary + maintainer: Lucas Godeiro + description: Provides functionalities based on the paper "Time Varying Dictionary + and the Predictive Power of FED Minutes" (Lima, 2018) . + It selects the most predictive terms, that we call time-varying dictionary using + supervised machine learning techniques as lasso and elastic net. + date_publication: '2022-04-25' + bug_reports: https://github.com/lucasgodeiro/TextForecast/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TextForecast + url_git: https://github.com/lucasgodeiro/TextForecast +textgRid: + version: 1.0.1 + title: Praat TextGrid Objects in R + maintainer: Patrick Reidy + description: |- + The software application Praat can be used to annotate + waveform data (e.g., to mark intervals of interest or to label events). + (See for more information about Praat.) + These annotations are stored in a Praat TextGrid object, which consists of + a number of interval tiers and point tiers. An interval tier consists of + sequential (i.e., not overlapping) labeled intervals. A point tier consists + of labeled events that have no duration. The 'textgRid' package provides + S4 classes, generics, and methods for accessing information that is stored + in Praat TextGrid objects. + date_publication: '2016-09-21' + bug_reports: https://github.com/patrickreidy/textgRid + url: www.praat.org + url_cran: https://CRAN.R-project.org/package=textgRid + url_git: '' +textile: + version: 0.1.4 + title: Textile Images + maintainer: Anh Bui + description: |- + Contains real images of the same textile material + with/without local defects, which were used in + Bui and Apley (2018) . + date_publication: '2021-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textile + url_git: '' +textir: + version: 2.0-5 + title: Inverse Regression for Text Analysis + maintainer: Matt Taddy + description: 'Multinomial (inverse) regression inference for text documents and + associated attributes. For details see: Taddy (2013 JASA) Multinomial Inverse + Regression for Text Analysis and Taddy (2015, AoAS), Distributed + Multinomial Regression, . A minimalist partial least squares + routine is also included. Note that the topic modeling capability of earlier + ''textir'' is now a separate package, ''maptpx''.' + date_publication: '2018-02-11' + bug_reports: '' + url: http://taddylab.com + url_cran: https://CRAN.R-project.org/package=textir + url_git: '' +textmineR: + version: 3.0.5 + title: Functions for Text Mining and Topic Modeling + maintainer: Tommy Jones + description: |- + An aid for text mining in R, with a syntax that + should be familiar to experienced R users. Provides a wrapper for several + topic models that take similarly-formatted input and give similarly-formatted + output. Has additional functionality for analyzing and diagnostics for + topic models. + date_publication: '2021-06-28' + bug_reports: https://github.com/TommyJones/textmineR/issues + url: https://www.rtextminer.com/ + url_cran: https://CRAN.R-project.org/package=textmineR + url_git: '' +TextMiningGUI: + version: '0.3' + title: Text Mining GUI Interface + maintainer: Conrado Reyes + description: Graphic interface for text analysis, implement a few methods such as + biplots, correspondence analysis, co-occurrence, clustering, topic models, correlations + and sentiments. + date_publication: '2021-04-17' + bug_reports: '' + url: https://c0reyes.github.io/TextMiningGUI/ + url_cran: https://CRAN.R-project.org/package=TextMiningGUI + url_git: '' +textometry: + version: 0.1.6 + title: Textual Data Analysis Package Used by the TXM Software + maintainer: Matthieu Decorde + description: |- + Statistical exploration of textual corpora using several methods + from French 'Textometrie' (new name of 'Lexicometrie') and French 'Data Analysis' schools. + It includes methods for exploring irregularity of distribution of lexicon features across + text sets or parts of texts (Specificity analysis); multi-dimensional exploration (Factorial analysis), etc. + Those methods are used in the TXM software. + date_publication: '2022-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textometry + url_git: '' +textplot: + version: 0.2.2 + title: Text Plots + maintainer: Jan Wijffels + description: |- + Visualise complex relations in texts. This is done by providing functionalities for displaying + text co-occurrence networks, text correlation networks, dependency relationships as well as text clustering and semantic text 'embeddings'. + Feel free to join the effort of providing interesting text visualisations. + date_publication: '2022-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textplot + url_git: https://github.com/bnosac/textplot +textpress: + version: 1.0.0 + title: A Lightweight and Versatile NLP Toolkit + maintainer: Jason Timm + description: A simple Natural Language Processing (NLP) toolkit focused on search-centric + workflows with minimal dependencies. The package offers key features for web scraping, + text processing, corpus search, and text embedding generation via the 'HuggingFace + API' . + date_publication: '2024-10-14' + bug_reports: https://github.com/jaytimm/textpress/issues + url: https://jaytimm.github.io/textpress/ + url_cran: https://CRAN.R-project.org/package=textpress + url_git: https://github.com/jaytimm/textpress +textrank: + version: 0.3.1 + title: Summarize Text by Ranking Sentences and Finding Keywords + maintainer: Jan Wijffels + description: |- + The 'textrank' algorithm is an extension of the 'Pagerank' algorithm for text. The algorithm allows to summarize text by calculating how sentences are related to one another. This is done by looking at overlapping terminology used in sentences in order to set up links between sentences. The resulting sentence network is next plugged into the 'Pagerank' algorithm which identifies the most important sentences in your text and ranks them. + In a similar way 'textrank' can also be used to extract keywords. A word network is constructed by looking if words are following one another. On top of that network the 'Pagerank' algorithm is applied to extract relevant words after which relevant words which are following one another are combined to get keywords. + More information can be found in the paper from Mihalcea, Rada & Tarau, Paul (2004) . + date_publication: '2020-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textrank + url_git: https://github.com/bnosac/textrank +textrar: + version: 0.8.0 + title: Interface to 'TexTra' from R + maintainer: Toshikazu Matsumura + description: |- + A wrapper for the 'TexTra' API , + a web service for translating texts between different languages. + 'TexTra' API account is required to use the service. + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textrar + url_git: https://github.com/matutosi/textrar +textrecipes: + version: 1.0.7 + title: Extra 'Recipes' for Text Processing + maintainer: Emil Hvitfeldt + description: |- + Converting text to numerical features requires specifically + created procedures, which are implemented as steps according to the + 'recipes' package. These steps allows for tokenization, filtering, + counting (tf and tfidf) and feature hashing. + date_publication: '2025-01-24' + bug_reports: https://github.com/tidymodels/textrecipes/issues + url: https://textrecipes.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=textrecipes + url_git: https://github.com/tidymodels/textrecipes +textreg: + version: 0.1.5 + title: n-Gram Text Regression, aka Concise Comparative Summarization + maintainer: Luke Miratrix + description: |- + Function for sparse regression on raw text, regressing a labeling + vector onto a feature space consisting of all possible phrases. + date_publication: '2018-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textreg + url_git: '' +textreuse: + version: 0.1.5 + title: Detect Text Reuse and Document Similarity + maintainer: Lincoln Mullen + description: |- + Tools for measuring similarity among documents and detecting + passages which have been reused. Implements shingled n-gram, skip n-gram, + and other tokenizers; similarity/dissimilarity functions; pairwise + comparisons; minhash and locality sensitive hashing algorithms; and a + version of the Smith-Waterman local alignment algorithm suitable for + natural language. + date_publication: '2020-05-15' + bug_reports: https://github.com/ropensci/textreuse/issues + url: https://docs.ropensci.org/textreuse + url_cran: https://CRAN.R-project.org/package=textreuse + url_git: https://github.com/ropensci/textreuse +textshape: + version: 1.7.5 + title: Tools for Reshaping Text + maintainer: Tyler Rinker + description: Tools that can be used to reshape and restructure text data. + date_publication: '2024-04-01' + bug_reports: https://github.com/trinker/textshape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=textshape + url_git: https://github.com/trinker/textshape +textshaping: + version: 1.0.0 + title: |- + Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text + Shaping + maintainer: Thomas Lin Pedersen + description: |- + Provides access to the text shaping functionality in the + 'HarfBuzz' library and the bidirectional algorithm in the 'Fribidi' + library. 'textshaping' is a low-level utility package mainly for + graphic devices that expands upon the font tool-set provided by the + 'systemfonts' package. + date_publication: '2025-01-20' + bug_reports: https://github.com/r-lib/textshaping/issues + url: '' + url_cran: https://CRAN.R-project.org/package=textshaping + url_git: https://github.com/r-lib/textshaping +textstem: + version: 0.1.4 + title: Tools for Stemming and Lemmatizing Text + maintainer: Tyler Rinker + description: |- + Tools that stem and lemmatize text. Stemming is a process that removes + endings such as affixes. Lemmatization is the process of grouping inflected + forms together as a single base form. + date_publication: '2018-04-09' + bug_reports: http://github.com/trinker/textstem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=textstem + url_git: http://github.com/trinker/textstem +textTinyR: + version: 1.1.8 + title: Text Processing for Small or Big Data Files + maintainer: Lampros Mouselimis + description: It offers functions for splitting, parsing, tokenizing and creating + a vocabulary for big text data files. Moreover, it includes functions for building + a document-term matrix and extracting information from those (term-associations, + most frequent terms). It also embodies functions for calculating token statistics + (collocations, look-up tables, string dissimilarities) and functions to work with + sparse matrices. Lastly, it includes functions for Word Vector Representations + (i.e. 'GloVe', 'fasttext') and incorporates functions for the calculation of (pairwise) + text document dissimilarities. The source code is based on 'C++11' and exported + in R through the 'Rcpp', 'RcppArmadillo' and 'BH' packages. + date_publication: '2023-12-04' + bug_reports: https://github.com/mlampros/textTinyR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=textTinyR + url_git: https://github.com/mlampros/textTinyR +textTools: + version: 0.1.0 + title: Functions for Text Cleansing and Text Analysis + maintainer: Timothy Conwell + description: |- + A framework for text cleansing and analysis. Conveniently prepare and process large amounts of text for analysis. + Includes various metrics for word counts/frequencies that scale efficiently. Quickly + analyze large amounts of text data using a text.table (a data.table created with one word (or unit of text analysis) per row, similar to the tidytext format). + Offers flexibility to efficiently work with text data stored in vectors as well as text data formatted as a text.table. + date_publication: '2021-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=textTools + url_git: '' +textutils: + version: 0.4-1 + title: Utilities for Handling Strings and Text + maintainer: Enrico Schumann + description: |- + Utilities for handling character vectors + that store human-readable text (either plain or with + markup, such as HTML or LaTeX). The package provides, + in particular, functions that help with the + preparation of plain-text reports, e.g. for expanding + and aligning strings that form the lines of such + reports. The package also provides generic functions for + transforming R objects to HTML and to plain text. + date_publication: '2024-04-01' + bug_reports: '' + url: http://enricoschumann.net/R/packages/textutils/ + url_cran: https://CRAN.R-project.org/package=textutils + url_git: https://github.com/enricoschumann/textutils +tf: + version: 0.3.4 + title: S3 Classes and Methods for Tidy Functional Data + maintainer: Fabian Scheipl + description: |- + Defines S3 vector data types for vectors of functional data + (grid-based, spline-based or functional principal components-based) with all + arithmetic and summary methods, derivation, integration and smoothing, + plotting, data import and export, and data wrangling, such as re-evaluating, + subsetting, sub-assigning, zooming into sub-domains, or extracting functional + features like minima/maxima and their locations. + The implementation allows including such vectors in data frames for joint + analysis of functional and scalar variables. + date_publication: '2024-05-22' + bug_reports: https://github.com/tidyfun/tf/issues + url: https://tidyfun.github.io/tf/ + url_cran: https://CRAN.R-project.org/package=tf + url_git: https://github.com/tidyfun/tf/ +TFactSR: + version: 0.99.0 + title: |- + Enrichment Approach to Predict Which Transcription Factors are + Regulated + maintainer: Atsushi Fukushima + description: |- + R implementation of 'TFactS' to predict which are the + transcription factors (TFs), regulated in a biological condition based on + lists of differentially expressed genes (DEGs) obtained from transcriptome + experiments. This package is based on the 'TFactS' concept by + Essaghir et al. (2010) and expands + it. It allows users to perform 'TFactS'-like enrichment approach. The + package can import and use the original catalogue file from the 'TFactS' + as well as users' defined catalogues of interest that are not supported + by 'TFactS' (e.g., Arabidopsis). + date_publication: '2023-08-31' + bug_reports: '' + url: https://afukushima.github.io/TFactSR/ + url_cran: https://CRAN.R-project.org/package=TFactSR + url_git: '' +tfaddons: + version: 0.10.0 + title: Interface to 'TensorFlow SIG Addons' + maintainer: Turgut Abdullayev + description: |- + 'TensorFlow SIG Addons' is a repository + of community contributions that conform to well-established API patterns, + but implement new functionality not available in core 'TensorFlow'. + 'TensorFlow' natively supports a large number of operators, layers, metrics, + losses, optimizers, and more. However, in a fast moving field like Machine Learning, + there are many interesting new developments that cannot be integrated into + core 'TensorFlow' (because their broad applicability is not yet clear, or + it is mostly used by a smaller subset of the community). + date_publication: '2020-06-02' + bug_reports: https://github.com/henry090/tfaddons/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfaddons + url_git: https://github.com/henry090/tfaddons +tfarima: + version: 0.3.2 + title: Transfer Function and ARIMA Models + maintainer: Jose L. Gallego + description: Building customized transfer function and ARIMA models with multiple + operators and parameter restrictions. Functions for model identification, model + estimation (exact or conditional maximum likelihood), model diagnostic checking, + automatic outlier detection, calendar effects, forecasting and seasonal adjustment. + See Bell and Hillmer (1983) , Box, Jenkins, + Reinsel and Ljung , Box, Pierce and Newbold (1987) , + Box and Tiao (1975) , Chen and Liu (1993) + . + date_publication: '2022-05-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tfarima + url_git: https://github.com/gallegoj/tfarima +tfautograph: + version: 0.3.2 + title: Autograph R for 'Tensorflow' + maintainer: Tomasz Kalinowski + description: Translate R control flow expressions into 'Tensorflow' graphs. + date_publication: '2021-09-17' + bug_reports: https://github.com/t-kalinowski/tfautograph/issues + url: https://t-kalinowski.github.io/tfautograph/ + url_cran: https://CRAN.R-project.org/package=tfautograph + url_git: '' +tfCox: + version: 0.1.0 + title: Fits Piecewise Polynomial with Data-Adaptive Knots in Cox Model + maintainer: Jiacheng Wu + description: In Cox's proportional hazard model, covariates are modeled as linear + function and may not be flexible. This package implements additive trend filtering + Cox proportional hazards model as proposed in Jiacheng Wu & Daniela Witten (2019) + "Flexible and Interpretable Models for Survival Data", Journal of Computational + and Graphical Statistics, . The fitted functions + are piecewise polynomial with adaptively chosen knots. + date_publication: '2019-08-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tfCox + url_git: '' +tfdatasets: + version: 2.17.0 + title: Interface to 'TensorFlow' Datasets + maintainer: Tomasz Kalinowski + description: |- + Interface to 'TensorFlow' Datasets, a high-level library for + building complex input pipelines from simple, re-usable pieces. + See for additional + details. + date_publication: '2024-07-16' + bug_reports: https://github.com/rstudio/tfdatasets/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfdatasets + url_git: https://github.com/rstudio/tfdatasets +tfdeploy: + version: 0.6.1 + title: Deploy 'TensorFlow' Models + maintainer: Daniel Falbel + description: |- + Tools to deploy 'TensorFlow' models across + multiple services. Currently, it provides a local server for testing 'cloudml' + compatible services. + date_publication: '2019-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tfdeploy + url_git: '' +tfer: + version: '1.3' + title: Forensic Glass Transfer Probabilities + maintainer: James Curran + description: Statistical interpretation of forensic glass transfer (Simulation of + the probability distribution of recovered glass fragments). + date_publication: '2020-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tfer + url_git: '' +tfestimators: + version: 1.9.2 + title: Interface to 'TensorFlow' Estimators + maintainer: Tomasz Kalinowski + description: |- + Interface to 'TensorFlow' Estimators + , a high-level + API that provides implementations of many different model types + including linear models and deep neural networks. + date_publication: '2021-08-09' + bug_reports: https://github.com/rstudio/tfestimators/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfestimators + url_git: https://github.com/rstudio/tfestimators +tfevents: + version: 0.0.4 + title: Write Events for 'TensorBoard' + maintainer: Daniel Falbel + description: |- + Provides a convenient way to log scalars, images, audio, and histograms in the 'tfevent' record file format. + Logged data can be visualized on the fly using 'TensorBoard', a web based tool that focuses on visualizing the training + progress of machine learning models. + date_publication: '2024-06-27' + bug_reports: https://github.com/mlverse/tfevents/issues + url: https://mlverse.github.io/tfevents/ + url_cran: https://CRAN.R-project.org/package=tfevents + url_git: https://github.com/mlverse/tfevents +tfhub: + version: 0.8.1 + title: Interface to 'TensorFlow' Hub + maintainer: Tomasz Kalinowski + description: |- + 'TensorFlow' Hub is a library for the publication, discovery, and + consumption of reusable parts of machine learning models. A module is a + self-contained piece of a 'TensorFlow' graph, along with its weights and + assets, that can be reused across different tasks in a process known as + transfer learning. Transfer learning train a model with a smaller dataset, + improve generalization, and speed up training. + date_publication: '2021-12-19' + bug_reports: https://github.com/rstudio/tfhub/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfhub + url_git: https://github.com/rstudio/tfhub +tfio: + version: 0.4.1 + title: Interface to 'TensorFlow IO' + maintainer: Yuan Tang + description: Interface to 'TensorFlow IO', Datasets and filesystem extensions maintained + by `TensorFlow SIG-IO` . + date_publication: '2019-12-19' + bug_reports: https://github.com/tensorflow/io/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfio + url_git: https://github.com/tensorflow/io +TFisher: + version: 0.2.0 + title: Optimal Thresholding Fisher's P-Value Combination Method + maintainer: Hong Zhang + description: |- + We provide the cumulative distribution function (CDF), + quantile, and statistical power calculator for a collection of + thresholding Fisher's p-value combination methods, including Fisher's + p-value combination method, truncated product method and, in particular, soft-thresholding + Fisher's p-value combination method which is proven to be optimal in some + context of signal detection. The p-value calculator for the omnibus version + of these tests are also included. For reference, please see Hong Zhang and Zheyang Wu. "TFisher Tests: Optimal and Adaptive Thresholding for Combining p-Values", submitted. + date_publication: '2018-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TFisher + url_git: '' +TFM: + version: 0.2.0 + title: Sparse Online Principal Component for Truncated Factor Model + maintainer: Guangbao Guo + description: The Truncated Factor Model is a statistical model designed to handle + specific data structures in data analysis. This R package focuses on the Sparse + Online Principal Component Estimation method, which is used to calculate data + such as the loading matrix and specific variance matrix for truncated data, thereby + better explaining the relationship between common factors and original variables. + Additionally, the R package also provides other equations for comparison with + the Sparse Online Principal Component Estimation method.The philosophy of the + package is described in thesis. (2023) . + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TFM + url_git: '' +TFMPvalue: + version: 0.0.9 + title: |- + Efficient and Accurate P-Value Computation for Position Weight + Matrices + maintainer: Ge Tan + description: |- + In putative Transcription Factor Binding Sites (TFBSs) + identification from sequence/alignments, + we are interested in the significance of certain match score. + TFMPvalue provides the accurate calculation of P-value with + score threshold for Position Weight Matrices, + or the score with given P-value. + It is an interface to code originally made available by + Helene Touzet and Jean-Stephane Varre, 2007, + Algorithms Mol Biol:2, 15. . + date_publication: '2022-10-21' + bug_reports: https://github.com/ge11232002/TFMPvalue/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TFMPvalue + url_git: https://github.com/ge11232002/TFMPvalue +tfNeuralODE: + version: 0.1.0 + title: Create Neural Ordinary Differential Equations with 'tensorflow' + maintainer: Shayaan Emran + description: |- + Provides a framework for the creation and use of Neural ordinary + differential equations with the 'tensorflow' and 'keras' packages. + The idea of Neural ordinary differential equations comes from + Chen et al. (2018) , and + presents a novel way of learning and solving differential systems. + date_publication: '2023-10-16' + bug_reports: https://github.com/semran9/tfNeuralODE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfNeuralODE + url_git: https://github.com/semran9/tfNeuralODE +tfplot: + version: 2021.6-1 + title: Time Frame User Utilities + maintainer: Paul Gilbert + description: |- + Utilities for simple manipulation and quick + plotting of time series data. These utilities use the 'tframe' package + which provides a programming kernel for time series. Extensions to + 'tframe' provided in 'tframePlus' can also be used. See the Guide + vignette for examples. + date_publication: '2021-06-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tfplot + url_git: http://tsanalysis.r-forge.r-project.org/ +tfprobability: + version: 0.15.1 + title: Interface to 'TensorFlow Probability' + maintainer: Tomasz Kalinowski + description: |- + Interface to 'TensorFlow Probability', a 'Python' library built on 'TensorFlow' + that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', 'GPU'). + 'TensorFlow Probability' includes a wide selection of probability distributions and bijectors, probabilistic layers, + variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD. + date_publication: '2022-09-01' + bug_reports: https://github.com/rstudio/tfprobability/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfprobability + url_git: https://github.com/rstudio/tfprobability +tframe: + version: 2015.12-1.1 + title: Time Frame Coding Kernel + maintainer: Paul Gilbert + description: |- + A kernel of functions for programming + time series methods in a way that is relatively independently of the + representation of time. Also provides plotting, time windowing, + and some + other utility functions which are specifically intended for time series. + See the Guide distributed as a vignette, or ?tframe.Intro for more + details. (User utilities are in package tfplot.) + date_publication: '2019-05-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tframe + url_git: http://tsanalysis.r-forge.r-project.org/ +tframePlus: + version: 2024.2-1 + title: Time Frame Coding Kernel Extensions + maintainer: Paul Gilbert + description: Extensions and additional 'tframe' utilities. + date_publication: '2024-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tframePlus + url_git: http://tsanalysis.r-forge.r-project.org/ +TFRE: + version: 0.1.0 + title: |- + A Tuning-Free Robust and Efficient Approach to High-Dimensional + Regression + maintainer: Yunan Wu + description: 'Provide functions to estimate the coefficients in high-dimensional + linear regressions via a tuning-free and robust approach. The method was published + in Wang, L., Peng, B., Bradic, J., Li, R. and Wu, Y. (2020), "A Tuning-free Robust + and Efficient Approach to High-dimensional Regression", Journal of the American + Statistical Association, 115:532, 1700-1714(JASA’s discussion paper), . + See also Wang, L., Peng, B., Bradic, J., Li, R. and Wu, Y. (2020), "Rejoinder + to “A tuning-free robust and efficient approach to high-dimensional regression". + Journal of the American Statistical Association, 115, 1726-1729, ; + Peng, B. and Wang, L. (2015), "An Iterative Coordinate Descent Algorithm for High-Dimensional + Nonconvex Penalized Quantile Regression", Journal of Computational and Graphical + Statistics, 24:3, 676-694, ; Clémençon, S., + Colin, I., and Bellet, A. (2016), "Scaling-up empirical risk minimization: optimization + of incomplete u-statistics", The Journal of Machine Learning Research, 17(1):2682–2717; + Fan, J. and Li, R. (2001), "Variable Selection via Nonconcave Penalized Likelihood + and its Oracle Properties", Journal of the American Statistical Association, 96:456, + 1348-1360, .' + date_publication: '2024-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TFRE + url_git: '' +tfrmt: + version: 0.1.3 + title: Applies Display Metadata to Analysis Results Datasets + maintainer: Becca Krouse + description: |- + Creates a framework to store and apply display metadata to Analysis + Results Datasets (ARDs). The use of 'tfrmt' allows users to define table + format and styling without the data, and later apply the format to the data. + date_publication: '2024-10-15' + bug_reports: https://github.com/GSK-Biostatistics/tfrmt/issues + url: https://GSK-Biostatistics.github.io/tfrmt/ + url_cran: https://CRAN.R-project.org/package=tfrmt + url_git: https://github.com/GSK-Biostatistics/tfrmt +tfrmtbuilder: + version: 0.1.0 + title: '''shiny'' App Companion to the ''tfrmt'' Package' + maintainer: Becca Krouse + description: |- + Provides an interactive interface to the 'tfrmt' package. Users + can import, modify, and export tables and templates with little to no code. + date_publication: '2024-10-11' + bug_reports: https://github.com/GSK-Biostatistics/tfrmtbuilder/issues + url: https://gsk-biostatistics.github.io/tfrmtbuilder/ + url_cran: https://CRAN.R-project.org/package=tfrmtbuilder + url_git: https://github.com/GSK-Biostatistics/tfrmtbuilder +tfruns: + version: 1.5.3 + title: Training Run Tools for 'TensorFlow' + maintainer: Tomasz Kalinowski + description: |- + Create and manage unique directories for each 'TensorFlow' + training run. Provides a unique, time stamped directory for each run + along with functions to retrieve the directory of the latest run or + latest several runs. + date_publication: '2024-04-19' + bug_reports: https://github.com/rstudio/tfruns/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tfruns + url_git: https://github.com/rstudio/tfruns +TFunHDDC: + version: 1.0.1 + title: Clustering of Functional Data via Mixtures of t-Distributions + maintainer: Cristina Anton + description: |- + Extension of 'funHDDC' Schmutz et al. (2018) + for cases including + outliers by fitting t-distributions for robust groups. 'TFunHDDC' can cluster + univariate or multivariate data produced by the 'fda' package for data using + a b-splines or Fourier basis. + date_publication: '2023-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TFunHDDC + url_git: '' +tgamtheme: + version: 0.1.0 + title: Globe and Mail Graphics Theme for 'ggplot2' + maintainer: Tom Cardoso + description: Theme and colour palettes for The Globe and Mail's graphics. Includes + colour and fill scale functions, colour palette helpers and a Globe-styled 'ggplot2' + theme object. + date_publication: '2021-02-05' + bug_reports: https://github.com/globeandmail/tgamtheme/issues + url: https://globeandmail.github.io/tgamtheme/ + url_cran: https://CRAN.R-project.org/package=tgamtheme + url_git: https://github.com/globeandmail/tgamtheme +tgcd: + version: '2.7' + title: Thermoluminescence Glow Curve Deconvolution + maintainer: Jun Peng + description: |- + Deconvolving thermoluminescence glow curves according to various + kinetic models (first-order, second-order, general-order, and mixed-order) using + a modified Levenberg-Marquardt algorithm (More, 1978) . + It provides the possibility of setting constraints or fixing any of parameters. + It offers an interactive way to initialize parameters by clicking with a mouse on + a plot at positions where peak maxima should be located. The optimal estimate is + obtained by "trial-and-error". It also provides routines for simulating first-order, + second-order, and general-order glow peaks. + date_publication: '2023-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tgcd + url_git: '' +tggd: + version: 0.1.1 + title: |- + The Standard Distribution Functions for the Truncated + Generalised Gamma Distribution + maintainer: Aaron Robotham + description: Density, distribution function, quantile function and random generation + for the Truncated Generalised Gamma Distribution (also in log10(x) and ln(x) space). + date_publication: '2015-12-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tggd + url_git: '' +tglkmeans: + version: 0.5.5 + title: Efficient Implementation of K-Means++ Algorithm + maintainer: Aviezer Lifshitz + description: |- + Efficient implementation of K-Means++ algorithm. For more + information see (1) "kmeans++ the advantages of the k-means++ + algorithm" by David Arthur and Sergei Vassilvitskii (2007), + Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete + algorithms, Society for Industrial and Applied Mathematics, + Philadelphia, PA, USA, pp. 1027-1035, and (2) "The Effectiveness of + Lloyd-Type Methods for the k-Means Problem" by Rafail Ostrovsky, Yuval + Rabani, Leonard J. Schulman and Chaitanya Swamy + . + date_publication: '2024-05-15' + bug_reports: https://github.com/tanaylab/tglkmeans/issues + url: https://tanaylab.github.io/tglkmeans/ + url_cran: https://CRAN.R-project.org/package=tglkmeans + url_git: https://github.com/tanaylab/tglkmeans +tgp: + version: 2.4-23 + title: Bayesian Treed Gaussian Process Models + maintainer: Robert B. Gramacy + description: |- + Bayesian nonstationary, semiparametric nonlinear regression + and design by treed Gaussian processes (GPs) with jumps to the limiting + linear model (LLM). Special cases also implemented include Bayesian + linear models, CART, treed linear models, stationary separable and + isotropic GPs, and GP single-index models. Provides 1-d and 2-d plotting functions + (with projection and slice capabilities) and tree drawing, designed for + visualization of tgp-class output. Sensitivity analysis and + multi-resolution models are supported. Sequential experimental + design and adaptive sampling functions are also provided, including ALM, + ALC, and expected improvement. The latter supports derivative-free + optimization of noisy black-box functions. For details and tutorials, + see Gramacy (2007) and Gramacy & Taddy (2010) + . + date_publication: '2024-09-03' + bug_reports: '' + url: https://bobby.gramacy.com/r_packages/tgp/ + url_cran: https://CRAN.R-project.org/package=tgp + url_git: '' +tgram: + version: 0.2-3 + title: Compute and Plot Tracheidograms + maintainer: Marcelino de la Cruz + description: Functions to compute and plot tracheidograms, as in De Soto et al. + (2011) . + date_publication: '2017-11-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tgram + url_git: '' +TGS: + version: 1.0.1 + title: Rapid Reconstruction of Time-Varying Gene Regulatory Networks + maintainer: Saptarshi Pyne + description: |- + Rapid advancements in high-throughput gene sequencing + technologies have resulted in genome-scale time-series datasets. + Uncovering the underlying temporal sequence of gene regulatory events + in the form of time-varying gene regulatory networks demands + accurate and computationally efficient algorithms. Such an + algorithm is 'TGS'. It is proposed in Saptarshi Pyne, Alok Ranjan + Kumar, and Ashish Anand. Rapid reconstruction of time-varying + gene regulatory networks. IEEE/ACM Transactions on Computational + Biology and Bioinformatics, 17(1):278{291, Jan-Feb 2020. The TGS + algorithm is shown to consume only 29 minutes for a microarray + dataset with 4028 genes. This package provides an implementation + of the TGS algorithm and its variants. + date_publication: '2020-05-07' + bug_reports: https://github.com/sap01/TGS/issues + url: https://www.biorxiv.org/content/early/2018/06/14/272484 + url_cran: https://CRAN.R-project.org/package=TGS + url_git: https://github.com/sap01/TGS +TGST: + version: '1.0' + title: Targeted Gold Standard Testing + maintainer: Yizhen Xu + description: Functions for implementing the targeted gold standard (GS) testing. + You provide the true disease or treatment failure status and the risk score, tell + 'TGST' the availability of GS tests and which method to use, and it returns the + optimal tripartite rules. Please refer to Liu et al. (2013) + for more details. + date_publication: '2020-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TGST + url_git: '' +tgstat: + version: 2.3.28 + title: Amos Tanay's Group High Performance Statistical Utilities + maintainer: Aviezer Lifshitz + description: |- + A collection of high performance utilities to compute + distance, correlation, auto correlation, clustering and other tasks. + Contains graph clustering algorithm described in "MetaCell: analysis + of single-cell RNA-seq data using K-nn graph partitions" (Yael Baran, + Akhiad Bercovich, Arnau Sebe-Pedros, Yaniv Lubling, Amir Giladi, Elad + Chomsky, Zohar Meir, Michael Hoichman, Aviezer Lifshitz & Amos Tanay, + 2019 ). + date_publication: '2024-09-23' + bug_reports: https://github.com/tanaylab/tgstat/issues + url: https://tanaylab.github.io/tgstat/ + url_cran: https://CRAN.R-project.org/package=tgstat + url_git: '' +tgver: + version: 0.3.0 + title: Turing Geovisualization Engine R package + maintainer: Layik Hama + description: Turing Geovisualization Engine R package for geospatial visualization + and analysis. + date_publication: '2022-09-30' + bug_reports: https://github.com/tgve/tgver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tgver + url_git: https://github.com/tgve/tgver +TH.data: + version: 1.1-3 + title: TH's Data Archive + maintainer: Torsten Hothorn + description: |- + Contains data sets used in other packages Torsten Hothorn + maintains. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TH.data + url_git: '' +thaipdf: + version: 0.1.2 + title: R Markdown to PDF in Thai Language + maintainer: Kittipos Sirivongrungson + description: |- + Provide R Markdown templates and LaTeX preamble + which are necessary for creating PDF from R Markdown documents in Thai language. + date_publication: '2022-04-22' + bug_reports: https://github.com/Lightbridge-KS/thaipdf/issues + url: https://lightbridge-ks.github.io/thaipdf/ + url_cran: https://CRAN.R-project.org/package=thaipdf + url_git: '' +thames: + version: 0.1.1 + title: Truncated Harmonic Mean Estimator of the Marginal Likelihood + maintainer: Nicholas J. Irons + description: |- + Implements the truncated harmonic mean estimator (THAMES) + of the reciprocal marginal likelihood using posterior samples and + unnormalized log posterior values via reciprocal importance sampling. + Metodiev, Perrot-Dockès, Ouadah, Irons, & Raftery (2023) . + date_publication: '2023-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=thames + url_git: '' +thankr: + version: 1.0.0 + title: Find Out Who Maintains the Packages you Use + maintainer: Dirk Schumacher + description: |- + Find out who maintains the packages you use in + your current session or in your package library and + maybe say 'thank you'. + date_publication: '2017-04-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=thankr + url_git: '' +ThankYouStars: + version: 0.2.0 + title: Give your Dependencies Stars on GitHub! + maintainer: Naoto Koshimizu + description: A tool for starring GitHub repositories. + date_publication: '2017-11-12' + bug_reports: https://github.com/ksmzn/ThankYouStars/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ThankYouStars + url_git: https://github.com/ksmzn/ThankYouStars +theft: + version: 0.6.3 + title: Tools for Handling Extraction of Features from Time Series + maintainer: Trent Henderson + description: |- + Consolidates and calculates different sets of time-series features from multiple + 'R' and 'Python' packages including 'Rcatch22' Henderson, T. (2021) , + 'feasts' O'Hara-Wild, M., Hyndman, R., and Wang, E. (2021) , + 'tsfeatures' Hyndman, R., Kang, Y., Montero-Manso, P., Talagala, T., Wang, E., Yang, Y., and O'Hara-Wild, M. (2020) + , 'tsfresh' Christ, M., Braun, N., Neuffer, J., + and Kempa-Liehr A.W. (2018) , 'TSFEL' Barandas, M., et al. (2020) + , and 'Kats' Facebook Infrastructure Data Science (2021) + . + date_publication: '2024-10-03' + bug_reports: https://github.com/hendersontrent/theft/issues + url: https://hendersontrent.github.io/theft/ + url_cran: https://CRAN.R-project.org/package=theft + url_git: '' +theftdlc: + version: 0.1.2 + title: Analyse and Interpret Time Series Features + maintainer: Trent Henderson + description: |- + Provides a suite of functions for analysing, interpreting, and visualising + time-series features calculated from different feature sets from the 'theft' package. + Implements statistical learning methodologies described in Henderson, T., + Bryant, A., and Fulcher, B. (2023) . + date_publication: '2024-10-04' + bug_reports: https://github.com/hendersontrent/theftdlc/issues + url: https://hendersontrent.github.io/theftdlc/ + url_cran: https://CRAN.R-project.org/package=theftdlc + url_git: '' +theiaR: + version: 0.4.0 + title: Download and Manage Data from Theia + maintainer: Xavier Laviron + description: |- + Provides a simple interface to search available data provided by + Theia (), download it, and manage it. Data can be downloaded + based on a search result or from a cart file downloaded from Theia website. + date_publication: '2020-11-19' + bug_reports: https://github.com/norival/theiaR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=theiaR + url_git: https://github.com/norival/theiaR +thematic: + version: 0.1.6 + title: |- + Unified and Automatic 'Theming' of 'ggplot2', 'lattice', and + 'base' R Graphics + maintainer: Carson Sievert + description: |- + Theme 'ggplot2', 'lattice', and 'base' graphics based on a + few choices, including foreground color, background color, accent + color, and font family. Fonts that aren't available on the system, but + are available via download on 'Google Fonts', can be automatically + downloaded, cached, and registered for use with the 'showtext' and + 'ragg' packages. + date_publication: '2024-07-29' + bug_reports: https://github.com/rstudio/thematic/issues + url: https://rstudio.github.io/thematic/ + url_cran: https://CRAN.R-project.org/package=thematic + url_git: https://github.com/rstudio/thematic +themis: + version: 1.0.3 + title: Extra Recipes Steps for Dealing with Unbalanced Data + maintainer: Emil Hvitfeldt + description: |- + A dataset with an uneven number of cases in each class is + said to be unbalanced. Many models produce a subpar performance on + unbalanced datasets. A dataset can be balanced by increasing the + number of minority cases using SMOTE 2011 , + BorderlineSMOTE 2005 and ADASYN 2008 + . Or by decreasing the + number of majority cases using NearMiss 2003 + or Tomek + link removal 1976 . + date_publication: '2025-01-23' + bug_reports: https://github.com/tidymodels/themis/issues + url: https://themis.tidymodels.org + url_cran: https://CRAN.R-project.org/package=themis + url_git: https://github.com/tidymodels/themis +TheOpenAIR: + version: 0.1.0 + title: Integrate 'OpenAI' Large Language Models into Your 'R' Workflows + maintainer: Ulrich Matter + description: Utilizing the 'OpenAI' API as the back end (), + 'TheOpenAIR' offers 'R' wrapper functions for the 'ChatGPT' endpoint and several + high-level functions that enable the integration of 'ChatGPT' capabilities in + diverse data-related tasks, such as data cleansing and automated analytics script + generation. + date_publication: '2023-04-27' + bug_reports: '' + url: http://openair-lib.org/ + url_cran: https://CRAN.R-project.org/package=TheOpenAIR + url_git: '' +theorytools: + version: 0.1.0 + title: FAIR Theory Construction + maintainer: Caspar J. Van Lissa + description: |- + An integrated suite of tools for creating, maintaining, and reusing + FAIR (Findable, Accessible, Interoperable, Reusable) theories. + Designed to support transparent and collaborative theory development, + the package enables users to formalize theories, + track changes with version control, + assess pre-empirical coherence, + and derive testable hypotheses. + Aligning with open science principles and workflows, + 'theorytools' facilitates the systematic improvement of theoretical frameworks + and enhances their discoverability and usability. + date_publication: '2025-01-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=theorytools + url_git: https://github.com/cjvanlissa/theorytools +ThermalSampleR: + version: 0.1.2 + title: |- + Calculate Sample Sizes Required for Critical Thermal Limits + Experiments + maintainer: Clarke JM van Steenderen + description: |- + We present a range of simulations to aid researchers in determining appropriate sample sizes when performing critical + thermal limits studies (e.g. CTmin/CTmin experiments). A number of wrapper functions are provided for plotting and summarising outputs + from these simulations. This package is presented in van Steenderen, C.J.M., Sutton, G.F., Owen, C.A., Martin, G.D., and Coetzee, J.A. Sample size assessments for thermal physiology studies: An R + package and R Shiny application. 2023. Physiological Entomology. . The GUI version of this package is available on the R Shiny online server at: + , or it is accessible via GitHub at . We would like + to thank Grant Duffy (University of Otago, Dundedin, New Zealand) for granting us permission to use the source code for the Test of Total Equivalency function. + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThermalSampleR + url_git: '' +Thermimage: + version: 4.1.3 + title: Thermal Image Analysis + maintainer: Glenn J. Tattersall + description: |- + A collection of functions and routines for inputting thermal + image video files, plotting and converting binary raw data into estimates of + temperature. First published 2015-03-26. Written primarily for research purposes + in biological applications of thermal images. v1 included the base calculations + for converting thermal image binary values to temperatures. v2 included additional + equations for providing heat transfer calculations and an import function for thermal + image files (v2.2.3 fixed error importing thermal image to windows OS). v3. Added numerous + functions for converting thermal image, videos, rewriting and exporting. + v3.1. Added new functions to convert files. v3.2. Fixed the various functions related to finding frame times. + v4.0. fixed an error in atmospheric attenuation constants, affecting raw2temp and temp2raw functions. + Recommend update for use with long distance calculations. v.4.1.3 changed to frameLocates to reflect change to as.character() to format(). + date_publication: '2021-09-27' + bug_reports: https://github.com/gtatters/Thermimage/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Thermimage + url_git: https://github.com/gtatters/Thermimage +ThermIndex: + version: 0.2.0 + title: Calculate Thermal Indexes + maintainer: Francisco Jablinski Castelhano + description: Calculates several thermal comfort indexes using temperature, wind + speed and relative humidity values, calculating indexes such as Humidex, windchill, + Discomfort Index and others. + date_publication: '2017-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThermIndex + url_git: '' +thermocouple: + version: 1.0.2 + title: Temperature Measurement with Thermocouples, RTD and IC Sensors + maintainer: Jose Gama + description: |- + Temperature measurement data, equations and methods for thermocouples, + wire RTD, thermistors, IC thermometers, bimetallic strips and the ITS-90. + date_publication: '2015-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=thermocouple + url_git: '' +TheSFACE: + version: 0.1.0 + title: The Subtype Free Average Causal Effect + maintainer: Amit Sasson + description: Estimation of the SF-ACE, a Causal Inference estimand proposed in the + paper "The Subtype-Free Average Causal Effect For Heterogeneous Disease Etiology" + (soon on arXiv). + date_publication: '2022-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TheSFACE + url_git: '' +thestats: + version: 0.1.0 + title: R Package for Exploring Turkish Higher Education Statistics + maintainer: Olgun Aydin + description: A user-friendly R data package that is intended to make Turkish higher + education statistics more accessible. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=thestats + url_git: https://github.com/analyticsresearchlab/thestats +thgenetics: + version: 0.4-2 + title: Genetic Rare Variants Tests + maintainer: Thomas Hoffmann + description: A step-up test for genetic rare variants in a gene or in a pathway. + The method determines an optimal grouping of rare variants analytically. The method + has been described in Hoffmann TJ, Marini NJ, and Witte JS (2010) . + date_publication: '2018-04-18' + bug_reports: '' + url: http://sites.google.com/site/thomashoffmannproject/https://doi.org/10.1371/journal.pone.0013584 + url_cran: https://CRAN.R-project.org/package=thgenetics + url_git: '' +thief: + version: '0.3' + title: Temporal Hierarchical Forecasting + maintainer: Rob Hyndman + description: |- + Methods and tools for generating forecasts at different temporal + frequencies using a hierarchical time series approach. + date_publication: '2018-01-24' + bug_reports: https://github.com/robjhyndman/thief/issues + url: http://pkg.robjhyndman.com/thief + url_cran: https://CRAN.R-project.org/package=thief + url_git: https://github.com/robjhyndman/thief +thinkr: + version: '0.16' + title: Tools for Cleaning Up Messy Files + maintainer: Vincent Guyader + description: |- + Some tools for cleaning up messy 'Excel' files to be suitable + for R. People who have been working with 'Excel' for years built more + or less complicated sheets with names, characters, formats that are + not homogeneous. To be able to use them in R nowadays, we built a set + of functions that will avoid the majority of importation problems and + keep all the data at best. + date_publication: '2022-08-22' + bug_reports: https://github.com/Thinkr-open/thinkr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=thinkr + url_git: https://github.com/Thinkr-open/thinkr +this.path: + version: 2.6.0 + title: Get Executing Script's Path + maintainer: Iris Simmons + description: |- + Determine the path of the executing script. Compatible + with several popular GUIs: 'Rgui', 'RStudio', 'Positron', + 'VSCode', 'Jupyter', 'Emacs', and 'Rscript' (shell). Compatible + with several functions and packages: 'source()', + 'sys.source()', 'debugSource()' in 'RStudio', + 'compiler::loadcmp()', 'utils::Sweave()', 'box::use()', + 'knitr::knit()', 'plumber::plumb()', 'shiny::runApp()', + 'package:targets', and 'testthat::source_file()'. + date_publication: '2024-12-18' + bug_reports: https://github.com/ArcadeAntics/this.path/issues + url: '' + url_cran: https://CRAN.R-project.org/package=this.path + url_git: https://github.com/ArcadeAntics/this.path +ThomasJeffersonUniv: + version: 0.1.3 + title: Handy Tools for TJU/TJUH Employees + maintainer: Tingting Zhan + description: |- + Functions for admin needs of employees of + Thomas Jefferson University and Thomas Jefferson + University Hospital, Philadelphia, PA. + date_publication: '2024-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThomasJeffersonUniv + url_git: '' +thor: + version: 1.1.6 + title: Interface to 'LMDB' + maintainer: Rich FitzJohn + description: |- + Key-value store, implemented as a wrapper around 'LMDB'; + the "lightning memory-mapped database" . + 'LMDB' is a transactional key value store that uses a memory map + for efficient access. This package wraps the entire 'LMDB' + interface (except duplicated keys), and provides objects for + transactions and cursors. + date_publication: '2024-09-16' + bug_reports: https://github.com/richfitz/thor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=thor + url_git: https://github.com/richfitz/thor +thorn: + version: 0.2.0 + title: '''HTMLwidgets'' Displaying Some ''WebGL'' Shaders' + maintainer: Stéphane Laurent + description: Creates some 'WebGL' shaders. They can be used as the background of + a 'Shiny' app. They also can be visualized in the 'RStudio' viewer pane or included + in 'Rmd' documents, but this is pretty useless, besides contemplating them. + date_publication: '2020-11-12' + bug_reports: https://github.com/stla/thorn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=thorn + url_git: https://github.com/stla/thorn +THREC: + version: 1.0.0 + title: Tree Height Response Calibration for Swedish Forests + maintainer: Friday Nwabueze Ogana + description: A tool that allows users to estimate tree height in the long-term forest + experiments in Sweden. It utilizes the multilevel nonlinear mixed-effect height + models developed for the forest experiments and consists of four functions for + the main species, other conifer species, and other broadleaves. Each function + within the system returns a data frame that includes the input data and the estimated + heights for any missing values. Ogana et al. (2023) \n + Arias-Rodil et al. (2015) . + date_publication: '2023-12-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=THREC + url_git: '' +thredds: + version: 0.1-4 + title: Crawler for Navigating THREDDS Catalogs + maintainer: Emmanuel Blondel + description: |- + Provides a crawler for programmatically navigating THREDDS Data Server () + catalogs, and access dataset metadata and resources. + date_publication: '2023-09-01' + bug_reports: '' + url: https://www.unidata.ucar.edu/software/tds/ + url_cran: https://CRAN.R-project.org/package=thredds + url_git: https://github.com/BigelowLab/thredds +threeBrain: + version: 1.2.0 + title: Your Advanced 3D Brain Visualization + maintainer: Zhengjia Wang + description: |- + A fast, interactive cross-platform, and easy to share + 'WebGL'-based 3D brain viewer that visualizes 'FreeSurfer' and/or + 'AFNI/SUMA' surfaces. The viewer widget can be either standalone or + embedded into 'R-shiny' applications. The standalone version only require + a web browser with 'WebGL2' support (for example, 'Chrome', 'Firefox', + 'Safari'), and can be inserted into any websites. The 'R-shiny' + support allows the 3D viewer to be dynamically generated from reactive user + inputs. Please check the publication by Wang, Magnotti, Zhang, + and Beauchamp (2023, ) for electrode + localization. This viewer has been fully adopted by 'RAVE' + , an interactive toolbox to + analyze 'iEEG' data by Magnotti, Wang, and Beauchamp (2020, + ). Please check + 'citation("threeBrain")' for details. + date_publication: '2024-11-07' + bug_reports: https://github.com/dipterix/threeBrain/issues + url: https://dipterix.org/threeBrain/ + url_cran: https://CRAN.R-project.org/package=threeBrain + url_git: https://github.com/dipterix/threeBrain +ThreeGroups: + version: '0.21' + title: |- + ML Estimator for Baseline-Placebo-Treatment (Three-Group) + Experiments + maintainer: Holger L. Kern + description: Implements the Maximum Likelihood estimator for baseline, placebo, + and treatment groups (three-group) experiments with non-compliance proposed by + Gerber, Green, Kaplan, and Kern (2010). + date_publication: '2015-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThreeGroups + url_git: '' +threejs: + version: 0.3.3 + title: Interactive 3D Scatter Plots, Networks and Globes + maintainer: B. W. Lewis + description: |- + Create interactive 3D scatter plots, network plots, and + globes using the 'three.js' visualization library (). + date_publication: '2020-01-21' + bug_reports: https://github.com/bwlewis/rthreejs/issues + url: https://bwlewis.github.io/rthreejs + url_cran: https://CRAN.R-project.org/package=threejs + url_git: '' +threesixtygiving: + version: 0.2.2 + title: Download Charitable Grants from the '360Giving' Platform + maintainer: Evan Odell + description: |- + Access open data from , a + database of charitable grant giving in the UK operated by '360Giving'. + The package provides functions to search and retrieve data on charitable + grant giving, and process that data into tidy formats. It relies on the + '360Giving' data standard, described at + . + date_publication: '2020-12-02' + bug_reports: https://github.com/evanodell/threesixtygiving/issues + url: https://docs.evanodell.com/threesixtygiving + url_cran: https://CRAN.R-project.org/package=threesixtygiving + url_git: https://github.com/evanodell/threesixtygiving +ThreeWay: + version: 1.1.3 + title: Three-Way Component Analysis + maintainer: Paolo Giordani + description: Component analysis for three-way data arrays by means of Candecomp/Parafac, + Tucker3, Tucker2 and Tucker1 models. + date_publication: '2015-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThreeWay + url_git: '' +ThreeWiseMonkeys: + version: 0.1.0 + title: |- + The Japanese Pictorial Maxim "See No Evil, Hear No Evil, Speak + No Evil" + maintainer: Greg Pilgrim + description: Does nothing useful, but perhaps does that nothing in an entertaining + or informative fashion. + date_publication: '2020-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThreeWiseMonkeys + url_git: '' +threewords: + version: 0.1.0 + title: Represent Precise Coordinates in Three Words + maintainer: Oliver Keyes + description: |- + A connector to the 'What3Words' (http://what3words.com/) service, which represents each 3m by 3m square on earth + with a unique trio of English-language words. + date_publication: '2015-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=threewords + url_git: '' +threg: + version: 1.0.3 + title: Threshold Regression + maintainer: Tao Xiao + description: Fit a threshold regression model based on the first-hitting-time of + a boundary by the sample path of a Wiener diffusion process. The threshold regression + methodology is well suited to applications involving survival and time-to-event + data. + date_publication: '2015-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=threg + url_git: '' +thregI: + version: 1.0.4 + title: |- + Threshold Regression for Interval-Censored Data with a Cure Rate + Option + maintainer: Man-Hua Chen + description: Fit a threshold regression model for Interval Censored Data based on + the first-hitting-time of a boundary by the sample path of a Wiener diffusion + process. The threshold regression methodology is well suited to applications involving + survival and time-to-event data. + date_publication: '2017-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=thregI + url_git: '' +Thresher: + version: 1.1.4 + title: Threshing and Reaping for Principal Components + maintainer: Kevin R. Coombes + description: |- + Defines the classes used to identify + outliers (threshing) and compute the number of significant principal + components and number of clusters (reaping) in a joint application + of PCA and hierarchical clustering. See Wang et al., 2018, + . + date_publication: '2024-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Thresher + url_git: http://oompa.r-forge.r-project.org/ +ThresholdROC: + version: 2.9.4 + title: Optimum Threshold Estimation + maintainer: Sara Perez-Jaume + description: Functions that provide point and interval estimations of optimum thresholds + for continuous diagnostic tests. The methodology used is based on minimizing an + overall cost function in the two- and three-state settings. We also provide functions + for sample size determination and estimation of diagnostic accuracy measures. + We also include graphical tools. The statistical methodology used here can be + found in Perez-Jaume et al (2017) and in Skaltsa et + al (2010, 2012) , . + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThresholdROC + url_git: '' +ThresholdROCsurvival: + version: 1.2.1 + title: |- + Diagnostic Ability Assessment with Right-Censored Data at a + Fixed Time t + maintainer: Sara Perez-Jaume + description: We focus on the diagnostic ability assessment of medical tests when + the outcome of interest is the status (alive or dead) of the subjects at a certain + time-point t. This binary status is determined by right-censored times to event + and it is unknown for those subjects censored before t. Here we provide three + methods (unknown status exclusion, imputation of censored times and using time-dependent + ROC curves) to evaluate the diagnostic ability of binary and continuous tests + in this context. Two references for the methods used here are Skaltsa et al. (2010) + and Heagerty et al. (2000) . + date_publication: '2024-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ThresholdROCsurvival + url_git: '' +threshr: + version: 1.0.6 + title: Threshold Selection and Uncertainty for Extreme Value Analysis + maintainer: Paul J. Northrop + description: |- + Provides functions for the selection of thresholds for use in + extreme value models, based mainly on the methodology in + Northrop, Attalides and Jonathan (2017) . + It also performs predictive inferences about future extreme values, + based either on a single threshold or on a weighted average of inferences + from multiple thresholds, using the 'revdbayes' package + . + At the moment only the case where the data can be treated as + independent identically distributed observations is considered. + date_publication: '2024-07-17' + bug_reports: https://github.com/paulnorthrop/threshr/issues + url: https://paulnorthrop.github.io/threshr/ + url_cran: https://CRAN.R-project.org/package=threshr + url_git: https://github.com/paulnorthrop/threshr +thriftr: + version: 1.1.7 + title: Apache Thrift Client Server + maintainer: Marek Jagielski + description: |- + Pure R implementation of Apache Thrift. + This library doesn't require any code generation. + To learn more about Thrift go to . + date_publication: '2022-05-10' + bug_reports: https://github.com/systemincloud/thriftr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=thriftr + url_git: https://github.com/systemincloud/thriftr +thunder: + version: 1.1.3 + title: |- + Computation and Visualisation of Atmospheric Convective + Parameters + maintainer: Bartosz Czernecki + description: |- + Allow to compute and visualise convective parameters commonly + used in the operational prediction of severe convective storms. Core algorithm + is based on a highly optimized 'C++' code linked into 'R' via 'Rcpp'. Highly + efficient engine allows to derive thermodynamic and kinematic parameters from + large numerical datasets such as reanalyses or operational Numerical Weather + Prediction models in a reasonable amount of time. Package has been developed + since 2017 by research meteorologists specializing in severe thunderstorms. + The most relevant methods used in the package based on the following publications + Stipanuk (1973) , + McCann et al. (1994) , + Bunkers et al. (2000) , + Corfidi et al. (2003) , + Showalter (1953) , + Coffer et al. (2019) , + Gropp and Davenport (2019) , + Czernecki et al. (2019) , + Taszarek et al. (2020) , + Sherburn and Parker (2014) , + Romanic et al. (2022) . + date_publication: '2023-11-11' + bug_reports: https://github.com/bczernecki/thunder/issues/ + url: https://bczernecki.github.io/thundeR/ + url_cran: https://CRAN.R-project.org/package=thunder + url_git: '' +ThurMod: + version: 1.1.11 + title: Thurstonian CFA and Thurstonian IRT Modeling + maintainer: Markus Thomas Jansen + description: |- + Fit Thurstonian forced-choice models (CFA (simple and factor) and IRT) in R. This package allows for the analysis of item response modeling (IRT) as well as confirmatory factor analysis (CFA) in the Thurstonian framework. Currently, estimation can be performed by 'Mplus' and 'lavaan'. References: + Brown & Maydeu-Olivares (2011) ; + Jansen, M. T., & Schulze, R. (in review). The Thurstonian linked block design: Improving Thurstonian modeling for paired comparison and ranking data.; + Maydeu-Olivares & Böckenholt (2005) . + date_publication: '2023-09-19' + bug_reports: https://github.com/MarkusTJansen/ThurMod/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ThurMod + url_git: https://github.com/MarkusTJansen/ThurMod +thurstonianIRT: + version: 0.12.5 + title: Thurstonian IRT Models + maintainer: Paul-Christian Bürkner + description: |- + Fit Thurstonian Item Response Theory (IRT) models in R. This + package supports fitting Thurstonian IRT models and its extensions using + 'Stan', 'lavaan', or 'Mplus' for the model estimation. Functionality for + extracting results, making predictions, and simulating data is provided as + well. References: + Brown & Maydeu-Olivares (2011) ; + Bürkner et al. (2019) . + date_publication: '2024-04-17' + bug_reports: https://github.com/paul-buerkner/thurstonianIRT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=thurstonianIRT + url_git: https://github.com/paul-buerkner/thurstonianIRT +tibble: + version: 3.2.1 + title: Simple Data Frames + maintainer: Kirill Müller + description: |- + Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the traditional + data frame. + date_publication: '2023-03-20' + bug_reports: https://github.com/tidyverse/tibble/issues + url: https://tibble.tidyverse.org/ + url_cran: https://CRAN.R-project.org/package=tibble + url_git: https://github.com/tidyverse/tibble +tibbletime: + version: 0.1.9 + title: Time Aware Tibbles + maintainer: Davis Vaughan + description: |- + Built on top of the 'tibble' package, 'tibbletime' is an extension + that allows for the creation of time aware tibbles. Some immediate + advantages of this include: the ability to perform time-based subsetting + on tibbles, quickly summarising and aggregating results by time periods, + and creating columns that can be used as 'dplyr' time-based groups. + date_publication: '2024-12-03' + bug_reports: https://github.com/business-science/tibbletime/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tibbletime + url_git: https://github.com/business-science/tibbletime +tibblify: + version: 0.3.1 + title: Rectangle Nested Lists + maintainer: Maximilian Girlich + description: |- + A tool to rectangle a nested list, that is to convert it into + a tibble. This is done automatically or according to a given + specification. A common use case is for nested lists coming from + parsing JSON files or the JSON response of REST APIs. It is supported + by the 'vctrs' package and therefore offers a wide support of vector + types. + date_publication: '2024-01-11' + bug_reports: https://github.com/mgirlich/tibblify/issues + url: https://mgirlich.github.io/tibblify/ + url_cran: https://CRAN.R-project.org/package=tibblify + url_git: https://github.com/mgirlich/tibblify +tican: + version: 1.0.1 + title: Plot and Analyse Time-Intensity Data + maintainer: Samuel James Tingle + description: |- + Plots and analyzes time-intensity curve data, such as data from + (contrast-enhanced) ultrasound. Values such as peak intensity, time to + peak and area under the curve are calculated. + date_publication: '2024-08-28' + bug_reports: https://github.com/sjtingle/tican/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tican + url_git: https://github.com/sjtingle/tican +tictactoe: + version: 0.2.2 + title: Tic-Tac-Toe Game + maintainer: Kota Mori + description: |2- + + Implements tic-tac-toe game to play on console, either with human or AI players. + Various levels of AI players are trained through the Q-learning algorithm. + date_publication: '2017-05-26' + bug_reports: https://github.com/kota7/tictactoe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tictactoe + url_git: https://github.com/kota7/tictactoe +tictoc: + version: 1.2.1 + title: |- + Functions for Timing R Scripts, as Well as Implementations of + "Stack" and "StackList" Structures + maintainer: Sergei Izrailev + description: |- + Code execution timing functions 'tic' and 'toc' that + can be nested. One can record all timings while a complex script is + running, and examine the values later. It is also possible to instrument + the timing calls with custom callbacks. In addition, this package provides + class 'Stack', implemented as a vector, and class 'StackList', which is a + stack implemented as a + list, both of which support operations 'push', 'pop', 'first_element', + 'last_element' and 'clear'. + date_publication: '2024-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tictoc + url_git: https://github.com/jabiru/tictoc +TideCurves: + version: 0.0.5 + title: Analysis and Prediction of Tides + maintainer: Moritz Mueller-Navarra + description: |- + Tidal analysis of evenly spaced observed time series (time step 1 to 60 min) with or + without shorter gaps using the harmonic representation of inequalities. + The analysis should preferably cover an observation period of at least 19 years. + For shorter periods low frequency constituents are not taken into account, in accordance with the Rayleigh-Criterion. + The main objective of this package is to synthesize or predict a tidal time series. + date_publication: '2021-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TideCurves + url_git: '' +TideHarmonics: + version: 0.1-1 + title: Harmonic Analysis of Tides + maintainer: Alec Stephenson + description: |- + Implements harmonic analysis of tidal and sea-level data. + Over 400 harmonic tidal constituents can be estimated, all with + daily nodal corrections. Time-varying mean sea-levels can also + be used. + date_publication: '2017-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TideHarmonics + url_git: '' +Tides: + version: '2.1' + title: Quasi-Periodic Time Series Characteristics + maintainer: Tom Cox + description: Calculate Characteristics of Quasi-Periodic Time Series, e.g. Estuarine + Water Levels. + date_publication: '2018-08-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tides + url_git: '' +TideTables: + version: 0.0.3 + title: Tide Analysis and Prediction of Predominantly Semi-Diurnal Tides + maintainer: Moritz Mueller-Navarra + description: |- + Tide analysis and prediction of predominantly semi-diurnal tides + with two high waters and two low waters during one lunar day (~24.842 hours, + ~1.035 days). The analysis should preferably cover an observation period of at + least 19 years. For shorter periods, for example, the nodal cycle can not be + taken into account, which particularly affects the height calculation. The main + objective of this package is to produce tide tables. + date_publication: '2020-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TideTables + url_git: '' +tidier: + version: 0.2.0 + title: Enhanced 'mutate' + maintainer: Srikanth Komala Sheshachala + description: Provides 'Apache Spark' style window aggregation for R dataframes and + remote 'dbplyr' tables via 'mutate' in 'dplyr' flavour. + date_publication: '2023-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidier + url_git: https://github.com/talegari/tidier +tidyAML: + version: 0.0.5 + title: Automatic Machine Learning with 'tidymodels' + maintainer: Steven Sanderson + description: The goal of this package will be to provide a simple interface for + automatic machine learning that fits the 'tidymodels' framework. The intention + is to work for regression and classification problems with a simple verb framework. + date_publication: '2024-03-12' + bug_reports: https://github.com/spsanderson/tidyAML/issues + url: https://www.spsanderson.com/tidyAML/ + url_cran: https://CRAN.R-project.org/package=tidyAML + url_git: https://github.com/spsanderson/tidyAML +tidybayes: + version: 3.0.7 + title: Tidy Data and 'Geoms' for Bayesian Models + maintainer: Matthew Kay + description: |- + Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models + ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided + to help extract tidy data frames of draws from Bayesian models and that generate point + summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for + common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus + densities), and fit curves with multiple, arbitrary uncertainty bands. + date_publication: '2024-09-15' + bug_reports: https://github.com/mjskay/tidybayes/issues + url: https://mjskay.github.io/tidybayes/ + url_cran: https://CRAN.R-project.org/package=tidybayes + url_git: https://github.com/mjskay/tidybayes/ +tidyBdE: + version: 0.3.8 + title: Download Data from Bank of Spain + maintainer: Diego H. Herrero + description: |- + Tools to download data series from 'Banco de España' ('BdE') + on 'tibble' format. 'Banco de España' is the national central bank + and, within the framework of the Single Supervisory Mechanism ('SSM'), + the supervisor of the Spanish banking system along with the European + Central Bank. This package is in no way sponsored endorsed or + administered by 'Banco de España'. + date_publication: '2024-12-20' + bug_reports: https://github.com/rOpenSpain/tidyBdE/issues + url: https://ropenspain.github.io/tidyBdE/ + url_cran: https://CRAN.R-project.org/package=tidyBdE + url_git: https://github.com/rOpenSpain/tidyBdE +tidybins: + version: 0.1.1 + title: Make Tidy Bins + maintainer: Harrison Tietze + description: Multiple ways to bin numeric columns with a tidy output. Wraps a variety + of existing binning methods into one function, and includes a new method for binning + by equal value, which is useful for sales data. Provides a function to automatically + summarize the properties of the binned columns. + date_publication: '2024-06-12' + bug_reports: https://github.com/Harrison4192/tidybins/issues + url: https://harrison4192.github.io/tidybins/ + url_cran: https://CRAN.R-project.org/package=tidybins + url_git: https://github.com/Harrison4192/tidybins +tidyboot: + version: 0.1.1 + title: Tidyverse-Compatible Bootstrapping + maintainer: Mika Braginsky + description: |- + Compute arbitrary non-parametric bootstrap statistics on data in + tidy data frames. + date_publication: '2018-03-14' + bug_reports: http://github.com/langcog/tidyboot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyboot + url_git: https://github.com/langcog/tidyboot +tidycat: + version: 0.1.2 + title: Expand Tidy Output for Categorical Parameter Estimates + maintainer: Guy J. Abel + description: Create additional rows and columns on broom::tidy() output to allow + for easier control on categorical parameter estimates. + date_publication: '2021-08-02' + bug_reports: https://github.com/guyabel/tidycat/issues/ + url: https://guyabel.github.io/tidycat/ + url_cran: https://CRAN.R-project.org/package=tidycat + url_git: '' +tidyCDISC: + version: 0.2.1 + title: |- + Quick Table Generation & Exploratory Analyses on ADaM-Ish + Datasets + maintainer: Aaron Clark + description: |- + Provides users a quick exploratory dive into common + visualizations without writing a single line of code given the users + data follows the Analysis Data Model (ADaM) standards put forth by the + Clinical Data Interchange Standards Consortium (CDISC) + . Prominent modules/ features of the + application are the Table Generator, Population Explorer, and the + Individual Explorer. The Table Generator allows users to drag and drop + variables and desired statistics (frequencies, means, ANOVA, t-test, + and other summary statistics) into bins that automagically create + stunning tables with validated information. The Population Explorer + offers various plots to visualize general trends in the population + from various vantage points. Plot modules currently include scatter + plot, spaghetti plot, box plot, histogram, means plot, and bar plot. + Each plot type allows the user to plot uploaded variables against one + another, and dissect the population by filtering out certain subjects. + Last, the Individual Explorer establishes a cohesive patient + narrative, allowing the user to interact with patient metrics (params) + by visit or plotting important patient events on a timeline. All + modules allow for concise filtering & downloading bulk outputs into + html or pdf formats to save for later. + date_publication: '2023-03-16' + bug_reports: https://github.com/Biogen-Inc/tidyCDISC/issues + url: https://Biogen-Inc.github.io/tidyCDISC/ + url_cran: https://CRAN.R-project.org/package=tidyCDISC + url_git: https://github.com/Biogen-Inc/tidyCDISC/ +tidycensus: + version: 1.7.1 + title: |- + Load US Census Boundary and Attribute Data as 'tidyverse' and + 'sf'-Ready Data Frames + maintainer: Kyle Walker + description: |- + An integrated R interface to several United States Census Bureau + APIs () and the US Census Bureau's + geographic boundary files. Allows R users to return Census and ACS data as + tidyverse-ready data frames, and optionally returns a list-column with feature geometry for mapping + and spatial analysis. + date_publication: '2025-01-31' + bug_reports: https://github.com/walkerke/tidycensus/issues + url: https://walker-data.com/tidycensus/ + url_cran: https://CRAN.R-project.org/package=tidycensus + url_git: '' +tidychangepoint: + version: 1.0.0 + title: A Tidy Framework for Changepoint Detection Analysis + maintainer: Benjamin S. Baumer + description: |- + Changepoint detection algorithms for R are widespread but have + different interfaces and reporting conventions. + This makes the comparative analysis of results difficult. + We solve this problem by providing a tidy, unified interface for several + different changepoint detection algorithms. + We also provide consistent numerical and graphical reporting leveraging + the 'broom' and 'ggplot2' packages. + date_publication: '2025-01-31' + bug_reports: '' + url: https://beanumber.github.io/tidychangepoint/ + url_cran: https://CRAN.R-project.org/package=tidychangepoint + url_git: '' +tidycharts: + version: 0.1.3 + title: Generate Tidy Charts Inspired by 'IBCS' + maintainer: Bartosz Sawicki + description: |- + There is a wide range of R packages created for data visualization, but still, there was no simple and easily accessible way to create clean and transparent charts - up to now. The 'tidycharts' package enables the user to generate charts compliant with International Business Communication Standards ('IBCS'). + It means unified bar widths, colors, chart sizes, etc. Creating homogeneous reports has never been that easy! Additionally, users can apply semantic notation to indicate different data scenarios (plan, budget, forecast). What's more, it is possible to customize the charts by creating a personal color pallet with the possibility of switching to default options after the experiments. + We wanted the package to be helpful in writing reports, so we also made joining charts in a one, clear image possible. + All charts are generated in SVG format and can be shown in the 'RStudio' viewer pane or exported to HTML output of 'knitr'/'markdown'. + date_publication: '2022-01-18' + bug_reports: '' + url: https://mi2datalab.github.io/tidycharts/ + url_cran: https://CRAN.R-project.org/package=tidycharts + url_git: https://github.com/MI2DataLab/tidycharts +tidyclust: + version: 0.2.4 + title: A Common API to Clustering + maintainer: Emil Hvitfeldt + description: |- + A common interface to specifying clustering models, in the + same style as 'parsnip'. Creates unified interface across different + functions and computational engines. + date_publication: '2025-01-27' + bug_reports: https://github.com/tidymodels/tidyclust/issues + url: https://tidyclust.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=tidyclust + url_git: https://github.com/tidymodels/tidyclust +tidycmprsk: + version: 1.1.0 + title: Competing Risks Estimation + maintainer: Daniel D. Sjoberg + description: |- + Provides an intuitive interface for working with the + competing risk endpoints. The package wraps the 'cmprsk' package, and + exports functions for univariate cumulative incidence estimates and + competing risk regression. Methods follow those introduced in Fine and + Gray (1999) . + date_publication: '2024-08-17' + bug_reports: https://github.com/MSKCC-Epi-Bio/tidycmprsk/issues + url: https://mskcc-epi-bio.github.io/tidycmprsk/ + url_cran: https://CRAN.R-project.org/package=tidycmprsk + url_git: https://github.com/MSKCC-Epi-Bio/tidycmprsk +tidycode: + version: 0.1.1 + title: Analyze Lines of R Code the Tidy Way + maintainer: Lucy D'Agostino McGowan + description: |- + Analyze lines of R code using tidy principles. This allows you to + input lines of R code and output a data frame with one row per function + included. Additionally, it facilitates code classification via included lexicons. + date_publication: '2019-12-10' + bug_reports: https://github.com/LucyMcGowan/tidycode/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidycode + url_git: https://github.com/LucyMcGowan/tidycode +tidycomm: + version: 0.4.1 + title: Data Modification and Analysis for Communication Research + maintainer: Julian Unkel + description: |- + Provides convenience functions for common data + modification and analysis tasks in communication research. This + includes functions for univariate and bivariate data analysis, index + generation and reliability computation, and intercoder reliability + tests. All functions follow the style and syntax of the tidyverse, and + are construed to perform their computations on multiple variables at + once. Functions for univariate and bivariate data analysis comprise + summary statistics for continuous and categorical variables, as well + as several tests of bivariate association including effect sizes. + Functions for data modification comprise index generation and + automated reliability analysis of index variables. Functions for + intercoder reliability comprise tests of several intercoder + reliability estimates, including simple and mean pairwise percent + agreement, Krippendorff's Alpha (Krippendorff 2004, ISBN: + 9780761915454), and various Kappa coefficients (Brennan & Prediger + 1981 ; Cohen 1960 ; Fleiss 1971 ). + date_publication: '2024-02-22' + bug_reports: https://github.com/joon-e/tidycomm/issues + url: https://joon-e.github.io/tidycomm/ + url_cran: https://CRAN.R-project.org/package=tidycomm + url_git: '' +TidyConsultant: + version: 0.1.1 + title: Tidy Consultant Universe + maintainer: Harrison Tietze + description: |- + Loads the 5 packages in the Tidy Consultant Universe. This collection of packages is useful for anyone doing data science, + data analysis, or quantitative consulting. The functions in these packages range from data cleaning, data validation, data binning, statistical modeling, and file exporting. + date_publication: '2024-06-07' + bug_reports: https://github.com/Harrison4192/TidyConsultant/issues + url: https://harrison4192.github.io/TidyConsultant/ + url_cran: https://CRAN.R-project.org/package=TidyConsultant + url_git: https://github.com/Harrison4192/TidyConsultant +tidycountries: + version: 0.1.0 + title: |- + Access and Manipulate Comprehensive Country Level Data in Tidy + Format + maintainer: Dennis Irorere + description: |- + A comprehensive and user-friendly interface for accessing, manipulating, + and analyzing country-level data from around the world. It allows users to retrieve detailed + information on countries, including names, regions, continents, populations, currencies, calling codes, + and more, all in a tidy data format. The package is designed to work seamlessly within + the 'tidyverse' ecosystem, making it easy to filter, arrange, and visualize country-level data in R. + date_publication: '2024-10-27' + bug_reports: https://github.com/denironyx/tidycountries/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidycountries + url_git: https://github.com/denironyx/tidycountries +tidyCpp: + version: 0.0.7 + title: Tidy C++ Header-Only Definitions for Parts of the C API of R + maintainer: Dirk Eddelbuettel + description: |- + Core parts of the C API of R are wrapped in a C++ namespace via a set + of inline functions giving a tidier representation of the underlying data structures + and functionality using a header-only implementation without additional dependencies. + date_publication: '2023-12-02' + bug_reports: https://github.com/eddelbuettel/tidycpp/issues + url: https://dirk.eddelbuettel.com/code/tidycpp.html + url_cran: https://CRAN.R-project.org/package=tidyCpp + url_git: https://github.com/eddelbuettel/tidycpp +tidycwl: + version: 1.0.7 + title: Tidy Common Workflow Language Tools and Workflows + maintainer: Soner Koc + description: |- + The Common Workflow Language is an + open standard for describing data analysis workflows. This package takes + the raw Common Workflow Language workflows encoded in JSON or 'YAML' + and turns the workflow elements into tidy data frames or lists. + A graph representation for the workflow can be constructed and visualized + with the parsed workflow inputs, outputs, and steps. Users can embed the + visualizations in their 'Shiny' applications, and export them + as HTML files or static images. + date_publication: '2022-05-03' + bug_reports: https://github.com/sbg/tidycwl/issues + url: https://sbg.github.io/tidycwl/ + url_cran: https://CRAN.R-project.org/package=tidycwl + url_git: https://github.com/sbg/tidycwl +tidydann: + version: 1.0.0 + title: |- + Add the 'dann' Model and the 'sub_dann' Model to the Tidymodels + Ecosystem + maintainer: Greg McMahan + description: |- + Provides model specifications, tuning parameters for models in + 'dann' package. Models based on Hastie (1996) + . + date_publication: '2023-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidydann + url_git: '' +tidydatatutor: + version: 0.1.0 + title: Send Your R Code to 'Tidy Data Tutor' + maintainer: Sean Kross + description: |- + Visualize your 'Tidyverse' data analysis pipelines via the + 'Tidy Data Tutor'() web application. + date_publication: '2021-12-10' + bug_reports: https://github.com/seankross/tidydatatutor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidydatatutor + url_git: https://github.com/seankross/tidydatatutor +tidydelta: + version: 0.1.0 + title: Estimation of Standard Errors using Delta Method + maintainer: Javier Martinez-Rodriguez + description: |- + Delta Method implementation to estimate standard errors with known + asymptotic properties within the 'tidyverse' workflow. The Delta Method is a + statistical tool that approximates an estimator’s behaviour using a Taylor + Expansion. For a comprehensive explanation, please refer to Chapter 3 of van + der Vaart (1998, ISBN: 9780511802256). + date_publication: '2024-07-18' + bug_reports: https://github.com/JavierMtzRdz/tidydelta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidydelta + url_git: https://github.com/JavierMtzRdz/tidydelta +tidyDenovix: + version: 2.1.0 + title: |- + Cleans Spectrophotometry Data Obtained from the Denovix DS-11 + Instrument + maintainer: Tingwei Adeck + description: Cleans spectrophotometry data obtained from the Denovix instrument. + The package also provides an option to normalize the data in order to compare + the quality of the samples obtained. + date_publication: '2024-01-18' + bug_reports: https://github.com/AlphaPrime7/tidyDenovix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyDenovix + url_git: https://github.com/AlphaPrime7/tidyDenovix +TidyDensity: + version: 1.5.0 + title: Functions for Tidy Analysis and Generation of Random Data + maintainer: Steven Sanderson + description: |- + To make it easy to generate random numbers based upon the underlying stats + distribution functions. All data is returned in a tidy and structured + format making working with the data simple and straight forward. Given that the + data is returned in a tidy 'tibble' it lends itself to working with the rest of the + 'tidyverse'. + date_publication: '2024-05-28' + bug_reports: https://github.com/spsanderson/TidyDensity/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TidyDensity + url_git: https://github.com/spsanderson/TidyDensity +tidydice: + version: 1.0.0 + title: Simulates Dice Rolls and Coin Flips + maintainer: Roland Krasser + description: |- + Utils for basic statistical experiments, that can be used for teaching + introductory statistics. Each experiment generates a tibble. + Dice rolls and coin flips are simulated using sample(). + The properties of the dice can be changed, like the number of sides. + A coin flip is simulated using a two sided dice. + Experiments can be combined with the pipe-operator. + date_publication: '2023-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidydice + url_git: https://github.com/rolkra/tidydice +tidydr: + version: 0.0.5 + title: Unify Dimensionality Reduction Results + maintainer: Guangchuang Yu + description: Dimensionality reduction (DR) is widely used in many domain for analyzing + and visualizing high-dimensional data. 'tidydr' provides uniform output and is + compatible with multiple methods, including 'prcomp', 'mds', 'Rtsne'. etc. + date_publication: '2023-03-08' + bug_reports: https://github.com/YuLab-SMU/tidydr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidydr + url_git: https://github.com/YuLab-SMU/tidydr/ +tidyedgar: + version: 1.0.1 + title: Tidy Fundamental Financial Data from 'SEC's 'EDGAR' 'API' + maintainer: Gerard Gimenez-Adsuar + description: Streamline the process of accessing fundamental financial data from + the United States Securities and Exchange Commission's ('SEC') Electronic Data + Gathering, Analysis, and Retrieval system ('EDGAR') 'API' , + transforming it into a tidy, analysis-ready format. + date_publication: '2024-02-09' + bug_reports: '' + url: https://gerardgimenezadsuar.github.io/tidyedgar/ + url_cran: https://CRAN.R-project.org/package=tidyedgar + url_git: '' +tidyEdSurvey: + version: 0.1.3 + title: Integration of 'dplyr' and 'ggplot2' with 'EdSurvey' + maintainer: Blue Webb + description: Takes objects of class edsurvey.data.frame and converts them to a data.frame + within the calling environment of 'dplyr' and 'ggplot2' functions. Additionally, + for plotting with 'ggplot2', users can map aesthetics to subject scales and all + plausible values will be used. This package supports student level data; to work + with school or teacher level data, see '?EdSurvey::getData'. + date_publication: '2024-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidyEdSurvey + url_git: '' +tidyEmoji: + version: 0.1.1 + title: Discovers Emoji from Text + maintainer: Youzhi Yu + description: |- + Unicodes are not friendly to work with, and not all Unicodes are + Emoji per se, making obtaining Emoji statistics a difficult task. This + tool can help your experience of working with Emoji as smooth as possible, + as it has the 'tidyverse' style. + date_publication: '2023-08-19' + bug_reports: https://github.com/PursuitOfDataScience/tidyEmoji/issues + url: https://pursuitofdatascience.github.io/tidyEmoji/ + url_cran: https://CRAN.R-project.org/package=tidyEmoji + url_git: '' +tidyestimate: + version: 1.1.1 + title: A Tidy Implementation of 'ESTIMATE' + maintainer: Kai Aragaki + description: |- + The 'ESTIMATE' package infers tumor purity from expression data as a + function of immune and stromal infiltrate, but requires writing of intermediate + files, is un-pipeable, and performs poorly when presented with modern datasets + with current gene symbols. 'tidyestimate' a fast, tidy, modern reimagination of + 'ESTIMATE' (2013) . + date_publication: '2023-08-21' + bug_reports: https://github.com/KaiAragaki/tidyestimate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyestimate + url_git: https://github.com/KaiAragaki/tidyestimate +tidyfast: + version: 0.4.0 + title: Fast Tidying of Data + maintainer: Tyson Barrett + description: |- + Tidying functions built on 'data.table' + to provide quick and efficient data manipulation with + minimal overhead. + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidyfast + url_git: '' +tidyfinance: + version: 0.4.3 + title: Tidy Finance Helper Functions + maintainer: Christoph Scheuch + description: |- + Helper functions for empirical research in financial + economics, addressing a variety of topics covered in Scheuch, Voigt, + and Weiss (2023) . The package is designed to + provide shortcuts for issues extensively discussed in the book, + facilitating easier application of its concepts. For more information + and resources related to the book, visit + . + date_publication: '2024-12-17' + bug_reports: https://github.com/tidy-finance/r-tidyfinance/issues + url: https://www.tidy-finance.org/r/ + url_cran: https://CRAN.R-project.org/package=tidyfinance + url_git: https://github.com/tidy-finance/r-tidyfinance +tidyfit: + version: 0.7.3 + title: Regularized Linear Modeling with Tidy Data + maintainer: Johann Pfitzinger + description: An extension to the 'R' tidy data environment for automated machine + learning. The package allows fitting and cross validation of linear regression + and classification algorithms on grouped data. + date_publication: '2025-01-17' + bug_reports: '' + url: https://tidyfit.residualmetrics.com + url_cran: https://CRAN.R-project.org/package=tidyfit + url_git: https://github.com/jpfitzinger/tidyfit +tidyformula: + version: 0.1.0 + title: Build Formulas Using Tidy Selection Helpers + maintainer: Damian Pavlyshyn + description: Provides the function 'tidyformula()', which translates formulas containing + 'tidyselect'-style selection helpers. It expands these helpers by evaluating 'dplyr::select()' + with the relevant selection helper and a supplied data frame. The package contains + methods for traversing abstract syntax trees from Wickham, Hadley (2019) . + date_publication: '2023-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidyformula + url_git: '' +tidyfst: + version: 1.8.1 + title: Tidy Verbs for Fast Data Manipulation + maintainer: Tian-Yuan Huang + description: |- + A toolkit of tidy data manipulation verbs with 'data.table' as the backend. + Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', + 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. + This package is an extension of 'data.table'. While enjoying a tidy syntax, + it also wraps combinations of efficient functions to facilitate frequently-used data operations. + date_publication: '2024-09-16' + bug_reports: https://github.com/hope-data-science/tidyfst/issues + url: https://hope-data-science.github.io/tidyfst/ + url_cran: https://CRAN.R-project.org/package=tidyfst + url_git: https://github.com/hope-data-science/tidyfst +tidyft: + version: 0.9.20 + title: Fast and Memory Efficient Data Operations in Tidy Syntax + maintainer: Tian-Yuan Huang + description: |- + Tidy syntax for 'data.table', using modification by reference whenever possible. + This toolkit is designed for big data analysis in high-performance desktop or laptop computers. + The syntax of the package is similar or identical to 'tidyverse'. + It is user friendly, memory efficient and time saving. For more information, + check its ancestor package 'tidyfst'. + date_publication: '2024-09-22' + bug_reports: https://github.com/hope-data-science/tidyft/issues + url: https://hope-data-science.github.io/tidyft/ + url_cran: https://CRAN.R-project.org/package=tidyft + url_git: https://github.com/hope-data-science/tidyft +tidygam: + version: 1.0.0 + title: Tidy Prediction and Plotting of Generalised Additive Models + maintainer: Stefano Coretta + description: |- + Provides functions that compute predictions from Generalised + Additive Models (GAMs) fitted with 'mgcv' and return them as a tibble. + These can be plotted with a generic plot()-method that uses 'ggplot2' or + plotted as any other data frame. The main function is predict_gam(). + date_publication: '2024-12-18' + bug_reports: https://github.com/stefanocoretta/tidygam/issues + url: https://stefanocoretta.github.io/tidygam/ + url_cran: https://CRAN.R-project.org/package=tidygam + url_git: https://github.com/stefanocoretta/tidygam +tidygapminder: + version: 0.1.1 + title: Easily Tidy Gapminder Datasets + maintainer: Anicet Ebou + description: |- + A toolset that allows you to easily import and tidy data sheets retrieved + from Gapminder data web tools. It will therefore contribute to reduce the time + used in data cleaning of Gapminder indicator data sheets as they are very messy. + date_publication: '2020-02-04' + bug_reports: https://github.com/ebedthan/tidygapminder/issues + url: https://ebedthan.github.io/tidygapminder + url_cran: https://CRAN.R-project.org/package=tidygapminder + url_git: '' +tidygate: + version: 1.0.14 + title: Interactively Gate Points + maintainer: Stefano Mangiola + description: |- + Interactively gate points on a scatter plot. Interactively drawn gates are + recorded and can be applied programmatically to reproduce results exactly. Programmatic gating is + based on the package gatepoints by Wajid Jawaid (who is also an author of this package). + date_publication: '2024-09-17' + bug_reports: https://github.com/stemangiola/tidygate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidygate + url_git: https://github.com/stemangiola/tidygate +tidygenomics: + version: 0.1.2 + title: Tidy Verbs for Dealing with Genomic Data Frames + maintainer: Constantin Ahlmann-Eltze + description: |- + Handle genomic data within data frames just as you would with 'GRanges'. + This packages provides method to deal with genomic intervals the "tidy-way" which makes + it simpler to integrate in the the general data munging process. The API is inspired by the + popular 'bedtools' and the genome_join() method from the 'fuzzyjoin' package. + date_publication: '2019-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidygenomics + url_git: https://github.com/const-ae/tidygenomics +tidygeocoder: + version: 1.0.5 + title: Geocoding Made Easy + maintainer: Jesse Cambon + description: An intuitive interface for getting data from geocoding services. + date_publication: '2021-11-02' + bug_reports: https://github.com/jessecambon/tidygeocoder/issues + url: https://jessecambon.github.io/tidygeocoder/ + url_cran: https://CRAN.R-project.org/package=tidygeocoder + url_git: https://github.com/jessecambon/tidygeocoder +tidygeoRSS: + version: 0.0.1 + title: Tidy GeoRSS + maintainer: Robert Myles McDonnell + description: |2- + + In order to easily integrate geoRSS data into analysis, + 'tidygeoRSS' parses 'geo' feeds and returns + tidy simple features data frames. + date_publication: '2020-06-14' + bug_reports: https://github.com/RobertMyles/tidygeoRSS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidygeoRSS + url_git: https://github.com/RobertMyles/tidygeoRSS +tidygraph: + version: 1.3.1 + title: A Tidy API for Graph Manipulation + maintainer: Thomas Lin Pedersen + description: |- + A graph, while not "tidy" in itself, can be thought of as two + tidy data frames describing node and edge data respectively. + 'tidygraph' provides an approach to manipulate these two virtual data + frames using the API defined in the 'dplyr' package, as well as + provides tidy interfaces to a lot of common graph algorithms. + date_publication: '2024-01-30' + bug_reports: https://github.com/thomasp85/tidygraph/issues + url: https://tidygraph.data-imaginist.com + url_cran: https://CRAN.R-project.org/package=tidygraph + url_git: https://github.com/thomasp85/tidygraph +tidyHeatmap: + version: 1.11.6 + title: A Tidy Implementation of Heatmap + maintainer: Stefano Mangiola + description: |- + This is a tidy implementation for heatmap. At the + moment it is based on the (great) package 'ComplexHeatmap'. The goal + of this package is to interface a tidy data frame with this powerful + tool. Some of the advantages are: Row and/or columns colour + annotations are easy to integrate just specifying one parameter + (column names). Custom grouping of rows is easy to specify providing + a grouped tbl. For example: df %>% group_by(...). Labels size + adjusted by row and column total number. Default use of Brewer and + Viridis palettes. + date_publication: '2025-02-08' + bug_reports: https://github.com/stemangiola/tidyHeatmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyHeatmap + url_git: https://github.com/stemangiola/tidyHeatmap +tidyheatmaps: + version: 0.2.1 + title: Heatmaps from Tidy Data + maintainer: Jan Broder Engler + description: The goal of 'tidyheatmaps' is to simplify the generation of publication-ready + heatmaps from tidy data. By offering an interface to the powerful 'pheatmap' package, + it allows for the effortless creation of intricate heatmaps with minimal code. + date_publication: '2024-02-29' + bug_reports: https://github.com/jbengler/tidyheatmaps/issues + url: https://jbengler.github.io/tidyheatmaps/ + url_cran: https://CRAN.R-project.org/package=tidyheatmaps + url_git: https://github.com/jbengler/tidyheatmaps +tidyhte: + version: 1.0.2 + title: Tidy Estimation of Heterogeneous Treatment Effects + maintainer: Drew Dimmery + description: |- + Estimates heterogeneous treatment effects using tidy semantics + on experimental or observational data. Methods are based on the doubly-robust + learner of Kennedy (n.d.) . You provide a simple + recipe for what machine learning algorithms to use in estimating the nuisance + functions and 'tidyhte' will take care of cross-validation, estimation, model + selection, diagnostics and construction of relevant quantities of interest about + the variability of treatment effects. + date_publication: '2023-08-14' + bug_reports: https://github.com/ddimmery/tidyhte/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyhte + url_git: https://github.com/ddimmery/tidyhtehttps://ddimmery.github.io/tidyhte/index.html +tidyhydat: + version: 0.7.0 + title: Extract and Tidy Canadian 'Hydrometric' Data + maintainer: Sam Albers + description: |- + Provides functions to access historical and real-time national 'hydrometric' + data from Water Survey of Canada data sources ( and + ) and then applies tidy data principles. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/tidyhydat/issues/ + url: https://docs.ropensci.org/tidyhydat/ + url_cran: https://CRAN.R-project.org/package=tidyhydat + url_git: https://github.com/ropensci/tidyhydat/ +tidyindex: + version: 0.1.0 + title: A Tidy Data Pipeline to Construct, Compare, and Analyse Indexes + maintainer: H. Sherry Zhang + description: |- + Construct and analyse indexes in a pipeline tidy workflow. + 'tidyindex' contains modules for transforming variables, aggregating + variables across time, reducing data dimension through weighting, and + fitting distributions. A manuscript describing the methodology can be + found at . + date_publication: '2023-11-16' + bug_reports: https://github.com/huizezhang-sherry/tidyindex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyindex + url_git: https://github.com/huizezhang-sherry/tidyindex +tidyjson: + version: 0.3.2 + title: Tidy Complex 'JSON' + maintainer: Cole Arendt + description: Turn complex 'JSON' data into tidy data frames. + date_publication: '2023-01-07' + bug_reports: https://github.com/colearendt/tidyjson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyjson + url_git: https://github.com/colearendt/tidyjson +tidylda: + version: 0.0.5 + title: Latent Dirichlet Allocation Using 'tidyverse' Conventions + maintainer: Tommy Jones + description: |- + Implements an algorithm for Latent Dirichlet + Allocation (LDA), Blei et at. (2003) , + using style conventions from the 'tidyverse', + Wickham et al. (2019), + and 'tidymodels', Kuhn et al.. + Fitting is done via collapsed Gibbs sampling. + Also implements several novel features for LDA such as guided models and + transfer learning based on ongoing and, as yet, unpublished research. + date_publication: '2024-04-22' + bug_reports: https://github.com/TommyJones/tidylda/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidylda + url_git: https://github.com/TommyJones/tidylda/ +tidyllm: + version: 0.3.1 + title: Tidy Integration of Large Language Models + maintainer: Eduard Brüll + description: A tidy interface for integrating large language model (LLM) APIs such + as 'Claude', 'Openai', 'Groq','Mistral' and local models via 'Ollama' into R workflows. + The package supports text and media-based interactions, interactive message history, + batch request APIs, and a tidy, pipeline-oriented interface for streamlined integration + into data workflows. Web services are available at , + , , and . + date_publication: '2025-02-24' + bug_reports: https://github.com/edubruell/tidyllm/issues + url: https://edubruell.github.io/tidyllm/ + url_cran: https://CRAN.R-project.org/package=tidyllm + url_git: '' +tidylo: + version: 0.2.0 + title: Weighted Tidy Log Odds Ratio + maintainer: Julia Silge + description: |- + How can we measure how the usage or frequency of some + feature, such as words, differs across some group or set, such as + documents? One option is to use the log odds ratio, but the log odds + ratio alone does not account for sampling variability; we haven't + counted every feature the same number of times so how do we know which + differences are meaningful? Enter the weighted log odds, which + 'tidylo' provides an implementation for, using tidy data principles. + In particular, here we use the method outlined in Monroe, Colaresi, + and Quinn (2008) to weight the log odds ratio + by a prior. By default, the prior is estimated from the data itself, + an empirical Bayes approach, but an uninformative prior is also + available. + date_publication: '2022-03-22' + bug_reports: https://github.com/juliasilge/tidylo/issues + url: https://juliasilge.github.io/tidylo/ + url_cran: https://CRAN.R-project.org/package=tidylo + url_git: https://github.com/juliasilge/tidylo +tidylog: + version: 1.1.0 + title: Logging for 'dplyr' and 'tidyr' Functions + maintainer: Benjamin Elbers + description: Provides feedback about 'dplyr' and 'tidyr' operations. + date_publication: '2024-05-08' + bug_reports: https://github.com/elbersb/tidylog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidylog + url_git: https://github.com/elbersb/tidylog/ +tidyLPA: + version: 1.1.0 + title: |- + Easily Carry Out Latent Profile Analysis (LPA) Using Open-Source + or Commercial Software + maintainer: Joshua M Rosenberg + description: |- + An interface to the 'mclust' package to easily + carry out latent profile analysis ("LPA"). Provides functionality to + estimate commonly-specified models. Follows a tidy approach, in that + output is in the form of a data frame that can subsequently be + computed on. Also has functions to interface to the commercial 'MPlus' + software via the 'MplusAutomation' package. + date_publication: '2021-11-17' + bug_reports: https://github.com/data-edu/tidyLPA/issues + url: https://data-edu.github.io/tidyLPA/ + url_cran: https://CRAN.R-project.org/package=tidyLPA + url_git: '' +tidyMC: + version: 1.0.0 + title: Monte Carlo Simulations Made Easy and Tidy + maintainer: Stefan Linner + description: |- + Framework to run Monte Carlo simulations over a parameter grid. + Allows to parallelize the simulations. + Generates plots and 'LaTeX' tables + summarizing the results from the simulation. + date_publication: '2024-01-11' + bug_reports: https://github.com/stefanlinner/tidyMC/issues + url: https://stefanlinner.github.io/tidyMC/ + url_cran: https://CRAN.R-project.org/package=tidyMC + url_git: https://github.com/stefanlinner/tidyMC +tidymodels: + version: 1.3.0 + title: Easily Install and Load the 'Tidymodels' Packages + maintainer: Max Kuhn + description: |- + The tidy modeling "verse" is a collection of packages for + modeling and statistical analysis that share the underlying design + philosophy, grammar, and data structures of the tidyverse. + date_publication: '2025-02-21' + bug_reports: https://github.com/tidymodels/tidymodels/issues + url: https://tidymodels.tidymodels.org + url_cran: https://CRAN.R-project.org/package=tidymodels + url_git: https://github.com/tidymodels/tidymodels +tidymodlr: + version: 1.0.0 + title: An R6 Class to Perform Analysis on Long Tidy Data + maintainer: David Hammond + description: Transforms long data into a matrix form to allow for ease of input + into modelling packages for regression, principal components, imputation or machine + learning. It does this by pivoting on user defined columns, generating a key-value + table for variable names to ensure one-to-one mappings are preserved. It is particularly + useful when the indicator names in the columns are long descriptive strings, for + example "Energy imports, net (% of energy use)". High level analysis wrapper functions + for correlation and principal components analysis are provided. + date_publication: '2024-08-26' + bug_reports: https://github.com/david-hammond/tidymodlr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidymodlr + url_git: https://github.com/david-hammond/tidymodlr +TidyMultiqc: + version: 1.0.3 + title: Converts 'MultiQC' Reports into Tidy Data Frames + maintainer: Michael Milton + description: |- + Provides the means to convert 'multiqc_data.json' files, + produced by the wonderful 'MultiQC' tool, into tidy data frames for downstream + analysis in R. This analysis might involve cohort analysis, quality control visualisation, + change-point detection, statistical process control, clustering, or any other + type of quality analysis. + date_publication: '2022-09-25' + bug_reports: https://github.com/multimeric/TidyMultiqc/issues + url: https://multimeric.github.io/TidyMultiqc/ + url_cran: https://CRAN.R-project.org/package=TidyMultiqc + url_git: https://github.com/multimeric/TidyMultiqc +tidync: + version: 0.4.0 + title: A Tidy Approach to 'NetCDF' Data Exploration and Extraction + maintainer: Michael Sumner + description: |- + Tidy tools for 'NetCDF' data sources. Explore the contents of a + 'NetCDF' source (file or URL) presented as variables organized by grid with a + database-like interface. The hyper_filter() interactive function translates the + filter value or index expressions to array-slicing form. No data is read until + explicitly requested, as a data frame or list of arrays via hyper_tibble() or + hyper_array(). + date_publication: '2024-08-17' + bug_reports: https://github.com/ropensci/tidync/issues + url: https://docs.ropensci.org/tidync/ + url_cran: https://CRAN.R-project.org/package=tidync + url_git: '' +tidypaleo: + version: 0.1.3 + title: Tidy Tools for Paleoenvironmental Archives + maintainer: Dewey Dunnington + description: |- + Provides a set of functions with a common framework for age-depth model management, + stratigraphic visualization, and common statistical transformations. The focus of the + package is stratigraphic visualization, for which 'ggplot2' components are provided + to reproduce the scales, geometries, facets, and theme elements commonly used in + publication-quality stratigraphic diagrams. Helpers are also provided to reproduce + the exploratory statistical summaries that are frequently included on + stratigraphic diagrams. See Dunnington et al. (2021) . + date_publication: '2023-01-18' + bug_reports: https://github.com/paleolimbot/tidypaleo/issues + url: https://paleolimbot.github.io/tidypaleo/ + url_cran: https://CRAN.R-project.org/package=tidypaleo + url_git: https://github.com/paleolimbot/tidypaleo +tidyplate: + version: 2.2.0 + title: Transform Microplate Data into Tibbles + maintainer: Shubham Dutta + description: |- + The goal of 'tidyplate' is to help researchers convert + different types of microplates into tibbles which can be used in data + analysis. It accepts xlsx and csv files formatted in a specific way as + input. It supports all types of standard microplate formats such as + 6-well, 12-well, 24-well, 48-well, 96-well, 384-well, and, 1536-well + plates. + date_publication: '2024-12-07' + bug_reports: https://github.com/shubhamdutta26/tidyplate/issues + url: https://www.shubhamdutta.com/tidyplate/ + url_cran: https://CRAN.R-project.org/package=tidyplate + url_git: https://github.com/shubhamdutta26/tidyplate +tidyplots: + version: 0.2.1 + title: Tidy Plots for Scientific Papers + maintainer: Jan Broder Engler + description: The goal of 'tidyplots' is to streamline the creation of publication-ready + plots for scientific papers. It allows to gradually add, remove and adjust plot + components using a consistent and intuitive syntax. + date_publication: '2025-01-19' + bug_reports: https://github.com/jbengler/tidyplots/issues + url: https://jbengler.github.io/tidyplots/ + url_cran: https://CRAN.R-project.org/package=tidyplots + url_git: https://github.com/jbengler/tidyplots +tidyplus: + version: 0.2.0 + title: Additional 'tidyverse' Functions + maintainer: Ayla Pearson + description: |- + Provides functions such as str_crush(), add_missing_column(), + coalesce_data() and drop_na_all() that complement 'tidyverse' functionality + or functions that provide alternative behaviors such as if_else2() + and str_detect2(). + date_publication: '2025-01-24' + bug_reports: https://github.com/poissonconsulting/tidyplus/issues + url: https://poissonconsulting.github.io/tidyplus/ + url_cran: https://CRAN.R-project.org/package=tidyplus + url_git: https://github.com/poissonconsulting/tidyplus +tidypmc: + version: '2.0' + title: Parse Full Text XML Documents from PubMed Central + maintainer: Chris Stubben + description: |- + Parse XML documents from the Open Access subset of Europe PubMed Central + including section paragraphs, tables, captions and references. + date_publication: '2024-08-27' + bug_reports: https://github.com/ropensci/tidypmc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidypmc + url_git: https://github.com/ropensci/tidypmc +tidyposterior: + version: 1.0.1 + title: Bayesian Analysis to Compare Models using Resampling Statistics + maintainer: Max Kuhn + description: |- + Bayesian analysis used here to answer the question: "when + looking at resampling results, are the differences between models + 'real'?" To answer this, a model can be created were the performance + statistic is the resampling statistics (e.g. accuracy or RMSE). These + values are explained by the model types. In doing this, we can get + parameter estimates for each model's affect on performance and make + statistical (and practical) comparisons between models. The methods + included here are similar to Benavoli et al (2017) + . + date_publication: '2023-10-11' + bug_reports: https://github.com/tidymodels/tidyposterior/issues + url: https://tidyposterior.tidymodels.org + url_cran: https://CRAN.R-project.org/package=tidyposterior + url_git: https://github.com/tidymodels/tidyposterior +tidypredict: + version: 0.5.1 + title: Run Predictions Inside the Database + maintainer: Emil Hvitfeldt + description: |- + It parses a fitted 'R' model object, and returns a formula in + 'Tidy Eval' code that calculates the predictions. It works with + several databases back-ends because it leverages 'dplyr' and 'dbplyr' + for the final 'SQL' translation of the algorithm. It currently + supports lm(), glm(), randomForest(), ranger(), earth(), + xgb.Booster.complete(), cubist(), and ctree() models. + date_publication: '2024-12-19' + bug_reports: https://github.com/tidymodels/tidypredict/issues + url: https://tidypredict.tidymodels.org + url_cran: https://CRAN.R-project.org/package=tidypredict + url_git: https://github.com/tidymodels/tidypredict +tidyprompt: + version: 0.0.1 + title: Prompt Large Language Models and Enhance Their Functionality + maintainer: Luka Koning + description: |- + Easily construct prompts and associated logic for interacting with + large language models (LLMs). + 'tidyprompt' introduces the concept of prompt wraps, which are building + blocks that you can use to quickly turn a simple prompt into a complex + one. Prompt wraps do not just modify the prompt text, but also add + extraction and validation functions that will be applied to the response + of the LLM. This ensures that the user gets the desired output. + 'tidyprompt' can add various features to prompts and their evaluation + by LLMs, such as structured output, automatic feedback, retries, reasoning + modes, autonomous R function calling, and R code generation and evaluation. + It is designed to be compatible with any LLM provider that offers + chat completion. + date_publication: '2025-01-08' + bug_reports: https://github.com/tjarkvandemerwe/tidyprompt/issues + url: https://tjarkvandemerwe.github.io/tidyprompt/ + url_cran: https://CRAN.R-project.org/package=tidyprompt + url_git: https://github.com/tjarkvandemerwe/tidyprompt +tidyquant: + version: 1.0.11 + title: Tidy Quantitative Financial Analysis + maintainer: Matt Dancho + description: |- + Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' + package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' + and 'PerformanceAnalytics' package + functions and returns the objects in the tidy 'tibble' format. The main + advantage is being able to use quantitative functions with the 'tidyverse' + functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See + the 'tidyquant' website for more information, documentation and examples. + date_publication: '2025-02-13' + bug_reports: https://github.com/business-science/tidyquant/issues + url: https://business-science.github.io/tidyquant/ + url_cran: https://CRAN.R-project.org/package=tidyquant + url_git: https://github.com/business-science/tidyquant +tidyquery: + version: 0.2.4 + title: Query 'R' Data Frames with 'SQL' + maintainer: Ian Cook + description: |- + Use 'SQL' 'SELECT' statements to query 'R' data + frames. + date_publication: '2023-01-14' + bug_reports: https://github.com/ianmcook/tidyquery/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyquery + url_git: https://github.com/ianmcook/tidyquery +tidyr: + version: 1.3.1 + title: Tidy Messy Data + maintainer: Hadley Wickham + description: |- + Tools to help to create tidy data, where each column is a + variable, each row is an observation, and each cell contains a single + value. 'tidyr' contains tools for changing the shape (pivoting) and + hierarchy (nesting and 'unnesting') of a dataset, turning deeply + nested lists into rectangular data frames ('rectangling'), and + extracting values out of string columns. It also includes tools for + working with missing values (both implicit and explicit). + date_publication: '2024-01-24' + bug_reports: https://github.com/tidyverse/tidyr/issues + url: https://tidyr.tidyverse.org + url_cran: https://CRAN.R-project.org/package=tidyr + url_git: https://github.com/tidyverse/tidyr +tidyrates: + version: 0.0.1 + title: Tidy Epidemiological Rates + maintainer: Raphael Saldanha + description: Compute age-adjusted rates by direct and indirect methods and other + epidemiological indicators in a tidy way, wrapping functions from the 'epitools' + package. + date_publication: '2024-03-19' + bug_reports: '' + url: https://rfsaldanha.github.io/tidyrates/ + url_cran: https://CRAN.R-project.org/package=tidyrates + url_git: '' +tidyREDCap: + version: 1.1.2 + title: Helper Functions for Working with 'REDCap' Data + maintainer: Raymond Balise + description: |- + Helper functions for processing 'REDCap' data in R. 'REDCap' is a + web-enabled application for building and managing surveys and databases + developed at Vanderbilt University. + date_publication: '2024-09-16' + bug_reports: https://github.com/RaymondBalise/tidyREDCap/issues + url: https://raymondbalise.github.io/tidyREDCap/index.html + url_cran: https://CRAN.R-project.org/package=tidyREDCap + url_git: '' +tidyrgee: + version: 0.1.0 + title: '''tidyverse'' Methods for ''Earth Engine''' + maintainer: Zack Arno + description: |- + Provides 'tidyverse' methods for wrangling + and analyzing 'Earth Engine' data. These methods help the user with filtering, + joining and summarising 'Earth Engine' image collections. + date_publication: '2022-09-15' + bug_reports: https://github.com/r-tidy-remote-sensing/tidyrgee/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=tidyrgee + url_git: https://github.com/r-tidy-remote-sensing/tidyrgee +tidyRSS: + version: 2.0.7 + title: Tidy RSS for R + maintainer: Robert Myles McDonnell + description: |2- + + With the objective of including data from RSS feeds into your analysis, + 'tidyRSS' parses RSS, Atom and JSON feeds and returns a tidy data frame. + date_publication: '2023-03-05' + bug_reports: https://github.com/RobertMyles/tidyrss/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyRSS + url_git: https://github.com/RobertMyles/tidyrss +tidyrules: + version: 0.2.7 + title: |- + Utilities to Retrieve Rulelists from Model Fits, Filter, Prune, + Reorder and Predict on Unseen Data + maintainer: Srikanth Komala Sheshachala + description: Provides a framework to work with decision rules. Rules can be extracted + from supported models, augmented with (custom) metrics using validation data, + manipulated using standard dataframe operations, reordered and pruned based on + a metric, predict on unseen (test) data. Utilities include; Creating a rulelist + manually, Exporting a rulelist as a SQL case statement and so on. The package + offers two classes; rulelist and ruleset based on dataframe. + date_publication: '2024-06-29' + bug_reports: https://github.com/talegari/tidyrules/issues + url: https://talegari.github.io/tidyrules/ + url_cran: https://CRAN.R-project.org/package=tidyrules + url_git: https://github.com/talegari/tidyrules +tidysdm: + version: 0.9.5 + title: Species Distribution Models with Tidymodels + maintainer: Andrea Manica + description: |- + Fit species distribution models (SDMs) using the 'tidymodels' framework, + which provides a standardised interface to define models and process their + outputs. 'tidysdm' expands 'tidymodels' by providing methods for spatial objects, + models and metrics specific to SDMs, + as well as a number of specialised functions to process occurrences + for contemporary and palaeo datasets. The full + functionalities of the package are described + in Leonardi et al. (2023) . + date_publication: '2024-06-23' + bug_reports: https://github.com/EvolEcolGroup/tidysdm/issues + url: https://evolecolgroup.github.io/tidysdm/ + url_cran: https://CRAN.R-project.org/package=tidysdm + url_git: https://github.com/EvolEcolGroup/tidysdm +tidyselect: + version: 1.2.1 + title: Select from a Set of Strings + maintainer: Lionel Henry + description: |- + A backend for the selecting functions of the 'tidyverse'. It + makes it easy to implement select-like functions in your own packages + in a way that is consistent with other 'tidyverse' interfaces for + selection. + date_publication: '2024-03-11' + bug_reports: https://github.com/r-lib/tidyselect/issues + url: https://tidyselect.r-lib.org + url_cran: https://CRAN.R-project.org/package=tidyselect + url_git: https://github.com/r-lib/tidyselect +tidySEM: + version: 0.2.7 + title: Tidy Structural Equation Modeling + maintainer: Caspar J. van Lissa + description: |- + A tidy workflow for generating, estimating, reporting, + and plotting structural equation models using 'lavaan', 'OpenMx', or + 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs + are represented as 'tidy' data, making them easy to customize. + Includes functionality to estimate latent class analyses. + date_publication: '2024-06-04' + bug_reports: https://github.com/cjvanlissa/tidySEM/issues + url: https://cjvanlissa.github.io/tidySEM/ + url_cran: https://CRAN.R-project.org/package=tidySEM + url_git: '' +tidyseurat: + version: 0.8.0 + title: Brings Seurat to the Tidyverse + maintainer: Stefano Mangiola + description: |- + It creates an invisible layer that allow to see the 'Seurat' object + as tibble and interact seamlessly with the tidyverse. + date_publication: '2024-01-10' + bug_reports: https://github.com/stemangiola/tidyseurat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyseurat + url_git: https://github.com/stemangiola/tidyseurat +tidysmd: + version: 0.2.0 + title: Tidy Standardized Mean Differences + maintainer: Malcolm Barrett + description: |- + Tidy standardized mean differences ('SMDs'). 'tidysmd' uses + the 'smd' package to calculate standardized mean differences for + variables in a data frame, returning the results in a tidy format. + date_publication: '2023-05-26' + bug_reports: https://github.com/r-causal/tidysmd/issues + url: https://r-causal.github.io/tidysmd/ + url_cran: https://CRAN.R-project.org/package=tidysmd + url_git: https://github.com/r-causal/tidysmd +tidysq: + version: 1.2.3 + title: Tidy Processing and Analysis of Biological Sequences + maintainer: Dominik Rafacz + description: A tidy approach to analysis of biological sequences. All processing + and data-storage functions are heavily optimized to allow the fastest and most + efficient data storage. + date_publication: '2025-01-07' + bug_reports: https://github.com/BioGenies/tidysq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidysq + url_git: https://github.com/BioGenies/tidysq +tidystats: + version: 0.6.2 + title: Save Output of Statistical Tests + maintainer: Willem Sleegers + description: |- + Save the output of statistical tests in an organized file that can + be shared with others or used to report statistics in scientific papers. + date_publication: '2024-07-14' + bug_reports: https://github.com/WillemSleegers/tidystats/issues + url: https://willemsleegers.github.io/tidystats/ + url_cran: https://CRAN.R-project.org/package=tidystats + url_git: '' +tidystopwords: + version: 0.9.1 + title: Customisable Stop-Words in 110 Languages + maintainer: Maciej Eder + description: Functions to generate stop-word lists in 110 languages, in a way consistent + across all the languages supported. The generated lists are based on the morphological + tagset from the Universal Dependencies. + date_publication: '2021-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidystopwords + url_git: '' +tidystringdist: + version: 0.1.4 + title: String Distance Calculation with Tidy Data Principles + maintainer: Colin Fay + description: |- + Calculation of string distance following the tidy + data principles. Built on top of the 'stringdist' package. + date_publication: '2019-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidystringdist + url_git: '' +tidytable: + version: 0.11.2 + title: Tidy Interface to 'data.table' + maintainer: Mark Fairbanks + description: |- + A tidy interface to 'data.table', + giving users the speed of 'data.table' while using tidyverse-like syntax. + date_publication: '2024-12-11' + bug_reports: https://github.com/markfairbanks/tidytable/issues + url: https://markfairbanks.github.io/tidytable/ + url_cran: https://CRAN.R-project.org/package=tidytable + url_git: https://github.com/markfairbanks/tidytable +tidyterra: + version: 0.7.0 + title: '''tidyverse'' Methods and ''ggplot2'' Helpers for ''terra'' Objects' + maintainer: Diego Hernangómez + description: |- + Extension of the 'tidyverse' for 'SpatRaster' and + 'SpatVector' objects of the 'terra' package. It includes also new + 'geom_' functions that provide a convenient way of visualizing 'terra' + objects with 'ggplot2'. + date_publication: '2025-02-03' + bug_reports: https://github.com/dieghernan/tidyterra/issues + url: https://dieghernan.github.io/tidyterra/ + url_cran: https://CRAN.R-project.org/package=tidyterra + url_git: https://github.com/dieghernan/tidyterra +tidytext: + version: 0.4.2 + title: Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools + maintainer: Julia Silge + description: |- + Using tidy data principles can make many text mining tasks + easier, more effective, and consistent with tools already in wide use. + Much of the infrastructure needed for text mining with tidy data + frames already exists in packages like 'dplyr', 'broom', 'tidyr', and + 'ggplot2'. In this package, we provide functions and supporting data + sets to allow conversion of text to and from tidy formats, and to + switch seamlessly between tidy tools and existing text mining + packages. + date_publication: '2024-04-10' + bug_reports: https://github.com/juliasilge/tidytext/issues + url: https://juliasilge.github.io/tidytext/ + url_cran: https://CRAN.R-project.org/package=tidytext + url_git: https://github.com/juliasilge/tidytext +tidytidbits: + version: 0.3.2 + title: A Collection of Tools and Helpers Extending the Tidyverse + maintainer: Marcel Wiesweg + description: |- + A selection of various tools to extend a data analysis workflow based on the 'tidyverse' packages. + This includes high-level data frame editing methods (in the style of 'mutate'/'mutate_at'), some methods in the style of + 'purrr' and 'forcats', 'lookup' methods for dict-like lists, a generic method for lumping a data frame by a given count, + various low-level methods for special treatment of 'NA' values, 'python'-style tuple-assignment and 'truthy'/'falsy' checks, + saving to PDF and PNG from a pipe and various small utilities. + date_publication: '2022-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tidytidbits + url_git: '' +tidytlg: + version: 0.1.5 + title: Create TLGs using the 'tidyverse' + maintainer: Konrad Pagacz + description: |- + Generate tables, listings, and graphs (TLG) using 'tidyverse.' + Tables can be created functionally, using a standard TLG process, or by + specifying table and column metadata to create generic analysis summaries. + The 'envsetup' package can also be leveraged to create environments for table + creation. + date_publication: '2024-06-15' + bug_reports: https://github.com/pharmaverse/tidytlg/issues + url: https://pharmaverse.github.io/tidytlg/main/ + url_cran: https://CRAN.R-project.org/package=tidytlg + url_git: https://github.com/pharmaverse/tidytlg +tidytransit: + version: 1.7.0 + title: Read, Validate, Analyze, and Map GTFS Feeds + maintainer: Flavio Poletti + description: 'Read General Transit Feed Specification (GTFS) zipfiles into a list + of R dataframes. Perform validation of the data structure against the specification. + Analyze the headways and frequencies at routes and stops. Create maps and perform + spatial analysis on the routes and stops. Please see the GTFS documentation here + for more detail: .' + date_publication: '2024-10-18' + bug_reports: https://github.com/r-transit/tidytransit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidytransit + url_git: https://github.com/r-transit/tidytransit +tidytreatment: + version: 0.3.1 + title: Tidy Methods for Bayesian Treatment Effect Models + maintainer: Joshua J Bon + description: Functions for extracting tidy data from Bayesian treatment effect models, + in particular BART, but extensions are possible. Functionality includes extracting + tidy posterior summaries as in 'tidybayes' , + estimating (average) treatment effects, common support calculations, and plotting + useful summaries of these. + date_publication: '2025-01-10' + bug_reports: https://github.com/bonStats/tidytreatment/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidytreatment + url_git: https://github.com/bonStats/tidytreatment +tidytree: + version: 0.4.6 + title: A Tidy Tool for Phylogenetic Tree Data Manipulation + maintainer: Guangchuang Yu + description: Phylogenetic tree generally contains multiple components including + node, edge, branch and associated data. 'tidytree' provides an approach to convert + tree object to tidy data frame as well as provides tidy interfaces to manipulate + tree data. + date_publication: '2023-12-12' + bug_reports: https://github.com/YuLab-SMU/tidytree/issues + url: https://www.amazon.com/Integration-Manipulation-Visualization-Phylogenetic-Computational-ebook/dp/B0B5NLZR1Z/ + url_cran: https://CRAN.R-project.org/package=tidytree + url_git: '' +tidytuesdayR: + version: 1.1.2 + title: Access the Weekly 'TidyTuesday' Project Dataset + maintainer: Jon Harmon + description: |- + 'TidyTuesday' is a project by the 'Data Science Learning + Community' in which they post a weekly dataset in a public data + repository () for + people to analyze and visualize. This package provides the tools to + easily download this data and the description of the source. + date_publication: '2024-09-09' + bug_reports: https://github.com/dslc-io/tidytuesdayR/issues + url: https://dslc-io.github.io/tidytuesdayR/ + url_cran: https://CRAN.R-project.org/package=tidytuesdayR + url_git: https://github.com/dslc-io/tidytuesdayR +tidyUSDA: + version: 0.4.1 + title: |- + A Minimal Tool Set for Gathering USDA Quick Stat Data for + Analysis and Visualization + maintainer: Brad Lindblad + description: |- + Provides a consistent API to pull United States Department of + Agriculture census and survey data from the National Agricultural + Statistics Service (NASS) QuickStats service. + date_publication: '2023-10-25' + bug_reports: '' + url: https://bradlindblad.github.io/tidyUSDA/ + url_cran: https://CRAN.R-project.org/package=tidyUSDA + url_git: https://github.com/bradlindblad/tidyUSDA/ +tidyverse: + version: 2.0.0 + title: Easily Install and Load the 'Tidyverse' + maintainer: Hadley Wickham + description: |- + The 'tidyverse' is a set of packages that work in harmony + because they share common data representations and 'API' design. This + package is designed to make it easy to install and load multiple + 'tidyverse' packages in a single step. Learn more about the + 'tidyverse' at . + date_publication: '2023-02-22' + bug_reports: https://github.com/tidyverse/tidyverse/issues + url: https://tidyverse.tidyverse.org + url_cran: https://CRAN.R-project.org/package=tidyverse + url_git: https://github.com/tidyverse/tidyverse +tidyvpc: + version: 1.5.2 + title: VPC Percentiles and Prediction Intervals + maintainer: James Craig + description: |- + Perform a Visual Predictive Check (VPC), while accounting for + stratification, censoring, and prediction correction. Using piping from + 'magrittr', the intuitive syntax gives users a flexible and powerful method + to generate VPCs using both traditional binning and a new binless approach + Jamsen et al. (2018) with Additive Quantile + Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS) + prediction correction. + date_publication: '2024-11-21' + bug_reports: https://github.com/certara/tidyvpc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidyvpc + url_git: https://github.com/certara/tidyvpc +tidywater: + version: 0.7.0 + title: Water Quality Models for Drinking Water Treatment Processes + maintainer: Sierra Johnson + description: |- + Provides multiple water chemistry-based models and published empirical models in one standard format. + Functions can be chained together to model a complete treatment process and are designed to work in a 'tidyverse' workflow. + Models are primarily based on these sources: + Benjamin, M. M. (2002, ISBN:147862308X), + Crittenden, J. C., Trussell, R., Hand, D., Howe, J. K., & Tchobanoglous, G., Borchardt, J. H. (2012, ISBN:9781118131473), + USEPA. (2001) . + date_publication: '2025-01-22' + bug_reports: https://github.com/BrownandCaldwell-Public/tidywater/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tidywater + url_git: https://github.com/BrownandCaldwell-Public/tidywater +tidywikidatar: + version: 0.5.9 + title: Explore 'Wikidata' Through Tidy Data Frames + maintainer: Giorgio Comai + description: Query 'Wikidata' API + with ease, get tidy data frames in response, and cache data in a local database. + date_publication: '2024-07-29' + bug_reports: https://github.com/EDJNet/tidywikidatar/issues + url: https://edjnet.github.io/tidywikidatar/ + url_cran: https://CRAN.R-project.org/package=tidywikidatar + url_git: https://github.com/EDJNet/tidywikidatar +tidyxl: + version: 1.0.10 + title: Read Untidy Excel Files + maintainer: Duncan Garmonsway + description: |- + Imports non-tabular from Excel files into R. Exposes cell content, + position and formatting in a tidy structure for further manipulation. + Tokenizes Excel formulas. Supports '.xlsx' and '.xlsm' via the embedded + 'RapidXML' C++ library . Does not support + '.xlsb' or '.xls'. + date_publication: '2023-12-21' + bug_reports: https://github.com/nacnudus/tidyxl/issues + url: https://nacnudus.github.io/tidyxl/ + url_cran: https://CRAN.R-project.org/package=tidyxl + url_git: https://github.com/nacnudus/tidyxl +tiff: + version: 0.1-12 + title: Read and Write TIFF Images + maintainer: Simon Urbanek + description: Functions to read, write and display bitmap images stored in the TIFF + format. It can read and write both files and in-memory raw vectors, including + native image representation. + date_publication: '2023-11-28' + bug_reports: '' + url: https://www.rforge.net/tiff/ + url_cran: https://CRAN.R-project.org/package=tiff + url_git: '' +tigerhitteR: + version: 1.1.0 + title: Pre-Process of Time Series Data Set in R + maintainer: Will Kuan + description: |- + Pre-process for discrete time series data set which is not continuous at the column + of 'date'. Refilling records of missing 'date' and other columns to the hollow data set so that + final data set is able to be dealt with time series analysis. + date_publication: '2016-10-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tigerhitteR + url_git: https://github.com/Willdata/tigerhitteR +TIGERr: + version: 1.0.0 + title: |- + Technical Variation Elimination with Ensemble Learning + Architecture + maintainer: Siyu Han + description: |2- + + The R implementation of TIGER. + TIGER integrates random forest algorithm into an innovative ensemble learning architecture. Benefiting from this advanced architecture, TIGER is resilient to outliers, free from model tuning and less likely to be affected by specific hyperparameters. + TIGER supports targeted and untargeted metabolomics data and is competent to perform both intra- and inter-batch technical variation removal. TIGER can also be used for cross-kit adjustment to ensure data obtained from different analytical assays can be effectively combined and compared. + Reference: Han S. et al. (2022) . + date_publication: '2022-01-06' + bug_reports: https://github.com/HAN-Siyu/TIGER/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TIGERr + url_git: '' +tigers: + version: 0.1-3 + title: Integration of Geography, Environment, and Remote Sensing + maintainer: Emmanuel Paradis + description: 'Handling and manipulation polygons, coordinates, and other geographical + objects. The tools include: polygon areas, barycentric and trilinear coordinates + (Hormann and Floater, 2006, ), convex hull for polygons + (Graham and Yao, 1983, ), polygon triangulation + (Toussaint, 1991, ), great circle and geodesic distances, + Hausdorff distance, and reduced major axis.' + date_publication: '2024-01-31' + bug_reports: https://github.com/emmanuelparadis/tigers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tigers + url_git: https://github.com/emmanuelparadis/tigers +tigerstats: + version: 0.3.2 + title: R Functions for Elementary Statistics + maintainer: Homer White + description: |- + A collection of data sets and functions that are useful in the + teaching of statistics at an elementary level to students who may have + little or no previous experience with the command line. The functions for + elementary inferential procedures follow a uniform interface for user + input. Some of the functions are instructional applets that can only be + run on the R Studio integrated development environment with package + 'manipulate' installed. Other instructional applets are Shiny apps + that may be run locally. In teaching the package is used alongside of + package 'mosaic', 'mosaicData' and 'abd', which are therefore listed as + dependencies. + date_publication: '2020-06-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tigerstats + url_git: '' +tigger: + version: 1.1.0 + title: Infers Novel Immunoglobulin Alleles from Sequencing Data + maintainer: Susanna Marquez + description: |- + Infers the V genotype of an individual from immunoglobulin (Ig) + repertoire sequencing data (AIRR-Seq, Rep-Seq). Includes detection of + any novel alleles. This information is then used to correct existing V + allele calls from among the sample sequences. + Citations: + Gadala-Maria, et al (2015) , + Gadala-Maria, et al (2019) . + date_publication: '2023-10-10' + bug_reports: https://bitbucket.org/kleinstein/tigger/issues + url: http://tigger.readthedocs.io + url_cran: https://CRAN.R-project.org/package=tigger + url_git: '' +tightClust: + version: '1.1' + title: Tight Clustering + maintainer: Chi Song + description: The functions needed to perform tight clustering Algorithm. + date_publication: '2018-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tightClust + url_git: '' +tightenBlock: + version: 0.1.7 + title: |- + Tightens an Observational Block Design by Balanced Subset + Matching + maintainer: Paul Rosenbaum + description: 'Tightens an observational block design into a smaller design with + either smaller or fewer blocks while controlling for covariates. The method uses + fine balance, optimal subset matching (Rosenbaum, 2012 ) + and two-criteria matching (Zhang et al 2023 ). The + main function is tighten(). The suggested ''rrelaxiv'' package for solving minimum + cost flow problems: (i) derives from Bertsekas and Tseng (1988) , + (ii) is not available on CRAN due to its academic license, (iii) may be downloaded + from GitHub at , (iv) is not essential + to use the package.' + date_publication: '2023-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tightenBlock + url_git: '' +tigreBrowserWriter: + version: 0.1.5 + title: '''tigreBrowser'' Database Writer' + maintainer: Antti Honkela + description: |- + Write modelling results into a database for + 'tigreBrowser', a web-based tool for browsing figures and summary + data of independent model fits, such as Gaussian process models + fitted for each gene or other genomic element. The browser is + available at . + date_publication: '2018-06-07' + bug_reports: https://github.com/PROBIC/tigreBrowserWriter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tigreBrowserWriter + url_git: https://github.com/PROBIC/tigreBrowserWriter +tigris: + version: '2.1' + title: Load Census TIGER/Line Shapefiles + maintainer: Kyle Walker + description: |- + Download TIGER/Line shapefiles from the United States Census Bureau + () + and load into R as 'sf' objects. + date_publication: '2024-01-24' + bug_reports: https://github.com/walkerke/tigris/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tigris + url_git: https://github.com/walkerke/tigris +tiktokadsR: + version: 0.1.0 + title: Access to TikTok Ads via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect marketing data from TikTok Ads using the 'Windsor.ai' API + . + date_publication: '2022-10-18' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=tiktokadsR + url_git: '' +tikzDevice: + version: 0.12.6 + title: R Graphics Output in LaTeX Format + maintainer: Ralf Stubner + description: |- + Provides a graphics output device for R that records plots + in a LaTeX-friendly format. The device transforms plotting + commands issued by R functions into LaTeX code blocks. When + included in a LaTeX document, these blocks are interpreted with + the help of 'TikZ'---a graphics package for TeX and friends + written by Till Tantau. Using the 'tikzDevice', the text of R + plots can contain LaTeX commands such as mathematical formula. + The device also allows arbitrary LaTeX code to be inserted into + the output stream. + date_publication: '2023-11-29' + bug_reports: https://github.com/daqana/tikzDevice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tikzDevice + url_git: https://github.com/daqana/tikzDevice +tiledb: + version: 0.30.2 + title: |- + Modern Database Engine for Complex Data Based on + Multi-Dimensional Arrays + maintainer: Isaiah Norton + description: |- + The modern database 'TileDB' introduces a powerful on-disk + format for storing and accessing any complex data based on multi-dimensional + arrays. It supports dense and sparse arrays, dataframes and key-values stores, + cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, + encryption and checksum filters, uses a fully multi-threaded implementation, + supports parallel I/O, data versioning ('time travel'), metadata and groups. + It is implemented as an embeddable cross-platform C++ library with APIs from + several languages, and integrations. This package provides the R support. + date_publication: '2024-10-04' + bug_reports: https://github.com/TileDB-Inc/TileDB-R/issues + url: https://tiledb-inc.github.io/TileDB-R/ + url_cran: https://CRAN.R-project.org/package=tiledb + url_git: https://github.com/TileDB-Inc/TileDB-R +tilegramsR: + version: 0.2.0 + title: R Spatial Data for Tilegrams + maintainer: Bhaskar Karambelkar + description: |- + R spatial objects for Tilegrams. + Tilegrams are tiled maps where the region size is proportional to + the certain characteristics of the dataset. + date_publication: '2017-03-29' + bug_reports: https://github.com/bhaskarvk/tilegramsR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tilegramsR + url_git: https://github.com/bhaskarvk/tilegramsR +tilemaps: + version: 0.2.0 + title: Generate Tile Maps + maintainer: Kaelyn Rosenberg + description: |- + Implements an algorithm for generating maps, known as tile maps, + in which each region is represented by a single tile of the same shape and + size. The algorithm was first proposed in "Generating Tile Maps" by Graham + McNeill and Scott Hale (2017) . Functions allow + users to generate, plot, and compare square or hexagon tile maps. + date_publication: '2020-07-10' + bug_reports: https://github.com/kaerosen/tilemaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tilemaps + url_git: https://github.com/kaerosen/tilemaps +tiler: + version: 0.3.2 + title: Create Geographic and Non-Geographic Map Tiles + maintainer: Matthew Leonawicz + description: |- + Creates geographic map tiles from geospatial map files or + non-geographic map tiles from simple image files. This package provides a + tile generator function for creating map tile sets for use with packages + such as 'leaflet'. In addition to generating map tiles based on a common + raster layer source, it also handles the non-geographic edge case, producing + map tiles from arbitrary images. These map tiles, which have a + non-geographic, simple coordinate reference system (CRS), can also be used + with 'leaflet' when applying the simple CRS option. Map tiles can be created + from an input file with any of the following extensions: tif, grd and nc for + spatial maps and png, jpg and bmp for basic images. This package requires + 'Python' and the 'gdal' library for 'Python'. 'Windows' users are + recommended to install 'OSGeo4W' () as an + easy way to obtain the required 'gdal' support for 'Python'. + date_publication: '2024-09-11' + bug_reports: https://github.com/ropensci/tiler/issues + url: https://docs.ropensci.org/tiler/ + url_cran: https://CRAN.R-project.org/package=tiler + url_git: https://github.com/ropensci/tiler +tilting: + version: 1.1.1 + title: Variable Selection via Tilted Correlation Screening Algorithm + maintainer: Haeran Cho + description: Implements an algorithm for variable selection in high-dimensional + linear regression using the "tilted correlation", a new way of measuring the contribution + of each variable to the response which takes into account high correlations among + the variables in a data-driven way. + date_publication: '2016-12-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tilting + url_git: '' +timbeR: + version: 2.0.1 + title: Calculate Wood Volumes from Taper Functions + maintainer: Sergio Costa + description: 'Functions for estimation of wood volumes, number of logs, diameters + along the stem and heights at which certain diameters occur, based on taper functions + and other parameters. References: McTague, J. P., & Weiskittel, A. (2021). .' + date_publication: '2022-04-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timbeR + url_git: '' +timbr: + version: 0.2.2 + title: Forest/Tree Data Frames + maintainer: Mizuki Uchida + description: |- + Provides data frames for forest or tree data structures. You can + create forest data structures from data frames and process them based on + their hierarchies. + date_publication: '2023-04-29' + bug_reports: https://github.com/UchidaMizuki/timbr/issues + url: https://uchidamizuki.github.io/timbr/ + url_cran: https://CRAN.R-project.org/package=timbr + url_git: https://github.com/UchidaMizuki/timbr +time.slots: + version: 0.2.0 + title: Display Data in a Weekly Calendar View + maintainer: Mukti Rathod + description: |- + Generate weekly timetables as a ggplot2 layer. Add + informative timeslots with elements such as title, key-value pairs, or + colour to reveal trends. + date_publication: '2022-04-22' + bug_reports: https://bitbucket.org/annalectnz/time.slots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=time.slots + url_git: https://bitbucket.org/annalectnz/time.slots +timechange: + version: 0.3.0 + title: Efficient Manipulation of Date-Times + maintainer: Vitalie Spinu + description: |- + Efficient routines for manipulation of date-time objects while + accounting for time-zones and daylight saving times. The package includes + utilities for updating of date-time components (year, month, day etc.), + modification of time-zones, rounding of date-times, period addition and + subtraction etc. Parts of the 'CCTZ' source code, released under the Apache + 2.0 License, are included in this package. See + for more details. + date_publication: '2024-01-18' + bug_reports: https://github.com/vspinu/timechange/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timechange + url_git: https://github.com/vspinu/timechange/ +timeDate: + version: '4041.110' + title: Rmetrics - Chronological and Calendar Objects + maintainer: Georgi N. Boshnakov + description: |- + The 'timeDate' class fulfils the conventions of the ISO 8601 + standard as well as of the ANSI C and POSIX standards. Beyond + these standards it provides the "Financial Center" concept + which allows to handle data records collected in different time + zones and mix them up to have always the proper time stamps with + respect to your personal financial center, or alternatively to the GMT + reference time. It can thus also handle time stamps from historical + data records from the same time zone, even if the financial + centers changed day light saving times at different calendar + dates. + date_publication: '2024-09-22' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://geobosh.github.io/timeDateDoc/(doc) + url_cran: https://CRAN.R-project.org/package=timeDate + url_git: https://r-forge.r-project.org/scm/viewvc.php/pkg/timeDate/?root=rmetrics(devel) +timedelay: + version: 1.0.11 + title: |- + Time Delay Estimation for Stochastic Time Series of + Gravitationally Lensed Quasars + maintainer: Hyungsuk Tak + description: We provide a toolbox to estimate the time delay between the brightness + time series of gravitationally lensed quasar images via Bayesian and profile likelihood + approaches. The model is based on a state-space representation for irregularly + observed time series data generated from a latent continuous-time Ornstein-Uhlenbeck + process. Our Bayesian method adopts scientifically motivated hyper-prior distributions + and a Metropolis-Hastings within Gibbs sampler, producing posterior samples of + the model parameters that include the time delay. A profile likelihood of the + time delay is a simple approximation to the marginal posterior distribution of + the time delay. Both Bayesian and profile likelihood approaches complement each + other, producing almost identical results; the Bayesian way is more principled + but the profile likelihood is easier to implement. A new functionality is added + in version 1.0.9 for estimating the time delay between doubly-lensed light curves + observed in two bands. See also Tak et al. (2017) , Tak + et al. (2018) , Hu and Tak (2020) . + date_publication: '2020-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timedelay + url_git: '' +TimeDepFrail: + version: 0.0.1 + title: Time Dependent Shared Frailty Cox Model + maintainer: Alessandra Ragni + description: 'Fits time-dependent shared frailty Cox model (specifically the adapted + Paik et al.''s Model) based on the paper "Centre-Effect on Survival After Bone + Marrow Transplantation: Application of Time-Dependent Frailty Models", by C.M. + Wintrebert, H. Putter, A.H. Zwinderman and J.C. van Houwelingen (2004) .' + date_publication: '2025-01-17' + bug_reports: '' + url: https://alessandragni.github.io/TimeDepFrail/ + url_cran: https://CRAN.R-project.org/package=TimeDepFrail + url_git: '' +timedeppar: + version: 1.0.3 + title: Infer Constant and Stochastic, Time-Dependent Model Parameters + maintainer: Peter Reichert + description: |- + Infer constant and stochastic, time-dependent parameters to consider intrinsic stochasticity of a dynamic model and/or to analyze model structure modifications that could reduce model deficits. + The concept is based on inferring time-dependent parameters as stochastic processes in the form of Ornstein-Uhlenbeck processes jointly with inferring constant model parameters and parameters of the Ornstein-Uhlenbeck processes. + The package also contains functions to sample from and calculate densities of Ornstein-Uhlenbeck processes. + References: + Tomassini, L., Reichert, P., Kuensch, H.-R. Buser, C., Knutti, R. and Borsuk, M.E. (2009), A smoothing algorithm for estimating stochastic, continuous-time model parameters and its application to a simple climate model, Journal of the Royal Statistical Society: Series C (Applied Statistics) 58, 679-704, + Reichert, P., and Mieleitner, J. (2009), Analyzing input and structural uncertainty of nonlinear dynamic models with stochastic, time-dependent parameters. Water Resources Research, 45, W10402, + Reichert, P., Ammann, L. and Fenicia, F. (2021), Potential and challenges of investigating intrinsic uncertainty of hydrological models with time-dependent, stochastic parameters. Water Resources Research 57(8), e2020WR028311, + Reichert, P. (2022), timedeppar: An R package for inferring stochastic, time-dependent model parameters, in preparation. + date_publication: '2023-08-28' + bug_reports: https://gitlab.com/p.reichert/timedeppar/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timedeppar + url_git: https://gitlab.com/p.reichert/timedeppar +timeDF: + version: 0.9.1 + title: Subset and Flag Data Frames with Times by the Use of Periods + maintainer: Toshihiro Umehara + description: Data frames with time information are subset and flagged with period + information. Data frames with times are dealt as timeDF objects and periods are + represented as periodDF objects. + date_publication: '2024-04-29' + bug_reports: https://github.com/niceume/timeDF + url: '' + url_cran: https://CRAN.R-project.org/package=timeDF + url_git: https://github.com/niceume/timeDF +timeEL: + version: 0.9.1 + title: Time to Event Analysis via Empirical Likelihood Inference + maintainer: Paul Blanche + description: |- + Computation of t-year survival probabilities and t-year + risks with right censored survival data. The Kaplan-Meier estimator + is used to provide estimates for data without competing risks and + the Aalen-Johansen estimator is used when there are competing risks. + Confidence intervals and p-values are obtained using either usual + Wald-type inference or empirical likelihood inference, as described + in Thomas and Grunkemeier (1975) + and Blanche (2020) . Functions for + both one-sample and two-sample inference are provided. Unlike Wald-type + inference, empirical likelihood inference always leads to consistent + conclusions, in terms of statistical significance, when comparing + two risks (or survival probabilities) via either a ratio or a difference. + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timeEL + url_git: '' +timeLineGraphics: + version: '1.0' + title: |- + HTML with Horizontal Strips Symbolizing Events in a Person's + Life + maintainer: Barry Zeeberg + description: Produce an HTML page containing horizontal strips that symbolize events + in a person's lsife. Since this is entirely a visualization, the image + will show the basic use to show a timeline of events. The image + shows how to correlate two timelines of events. A brief description is available + at . + date_publication: '2023-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timeLineGraphics + url_git: '' +timelineS: + version: 0.1.1 + title: Timeline and Time Duration-Related Tools + maintainer: Dahee Lee + description: An easy tool for plotting annotated timelines, grouped timelines, and + exploratory graphics (boxplot/histogram/density plot/scatter plot/line plot). + Filter, summarize date data by duration and convert to calendar units. + date_publication: '2016-08-22' + bug_reports: https://github.com/daheelee/timelineS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timelineS + url_git: https://github.com/daheelee/timelineS +timeordered: + version: 1.0.1 + title: Time-Ordered and Time-Aggregated Network Analyses + maintainer: Benjamin Wong Blonder + description: 'Approaches for incorporating time into network analysis. Methods include: + construction of time-ordered networks (temporal graphs); shortest-time and shortest-path-length + analyses; resource spread calculations; data resampling and rarefaction for null + model construction; reduction to time-aggregated networks with variable window + sizes; application of common descriptive statistics to these networks; vector + clock latencies; and plotting functionalities. The package supports .' + date_publication: '2024-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timeordered + url_git: '' +timeperiodsR: + version: 0.7.3 + title: Simple Definition Of Time Intervals + maintainer: Alexey Seleznev + description: Simple definition of time intervals for the current, previous, and + next week, month, quarter and year. + date_publication: '2024-01-23' + bug_reports: https://github.com/selesnow/timeperiodsR/issues + url: https://selesnow.github.io/timeperiodsR/ + url_cran: https://CRAN.R-project.org/package=timeperiodsR + url_git: '' +timeplyr: + version: 1.0.0 + title: Fast Tidy Tools for Date and Date-Time Manipulation + maintainer: Nick Christofides + description: |- + A set of fast tidy functions for wrangling, completing and + summarising date and date-time data. It combines 'tidyverse' syntax + with the efficiency of 'data.table' and speed of 'collapse'. + date_publication: '2025-02-03' + bug_reports: https://github.com/NicChr/timeplyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timeplyr + url_git: '' +timeR: + version: 1.2.0 + title: Time Your Codes + maintainer: Yifu Yan + description: Provides a 'timeR' class that makes timing codes easier. One can create + 'timeR' objects and use them to record all timings, and extract recordings as + data frame for later use. + date_publication: '2020-06-22' + bug_reports: https://github.com/yusuzech/timeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timeR + url_git: https://github.com/yusuzech/timeR +timereg: + version: 2.0.6 + title: Flexible Regression Models for Survival Data + maintainer: Thomas Scheike + description: |- + Programs for Martinussen and Scheike (2006), `Dynamic Regression + Models for Survival Data', Springer Verlag. Plus more recent developments. + Additive survival model, semiparametric proportional odds model, fast + cumulative residuals, excess risk models and more. Flexible competing risks + regression including GOF-tests. Two-stage frailty modelling. PLS for the + additive risk model. Lasso in the 'ahaz' package. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timereg + url_git: https://github.com/scheike/timereg +timeROC: + version: '0.4' + title: Time-Dependent ROC Curve and AUC for Censored Survival Data + maintainer: Paul Blanche + description: Estimation of time-dependent ROC curve and area under time dependent + ROC curve (AUC) in the presence of censored data, with or without competing risks. + Confidence intervals of AUCs and tests for comparing AUCs of two rival markers + measured on the same subjects can be computed, using the iid-representation of + the AUC estimator. Plot functions for time-dependent ROC curves and AUC curves + are provided. Time-dependent Positive Predictive Values (PPV) and Negative Predictive + Values (NPV) can also be computed. See Blanche et al. (2013) + and references therein for the details of the methods implemented in the package. + date_publication: '2019-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timeROC + url_git: '' +timeSeries: + version: '4041.111' + title: Financial Time Series Objects (Rmetrics) + maintainer: Georgi N. Boshnakov + description: |- + 'S4' classes and various tools for financial time series: + Basic functions such as scaling and sorting, subsetting, + mathematical operations and statistical functions. + date_publication: '2024-09-22' + bug_reports: https://r-forge.r-project.org/projects/rmetrics + url: https://geobosh.github.io/timeSeriesDoc/(doc) + url_cran: https://CRAN.R-project.org/package=timeSeries + url_git: https://r-forge.r-project.org/scm/viewvc.php/pkg/timeSeries/?root=rmetrics(devel) +timeSeriesDataSets: + version: 0.1.0 + title: Time Series Data Sets + maintainer: Renzo Caceres Rossi + description: |- + Provides a diverse collection of time series datasets + spanning various fields such as economics, finance, energy, healthcare, and more. + Designed to support time series analysis in R by offering datasets from + multiple disciplines, making it a valuable resource for researchers and analysts. + date_publication: '2024-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timeSeriesDataSets + url_git: https://github.com/lightbluetitan/timeseriesdatasets_R +timeseriesdb: + version: 1.0.0-1.1.2 + title: |- + A Time Series Database for Official Statistics with R and + PostgreSQL + maintainer: Matthias Bannert + description: Archive and manage times series data from official statistics. The + 'timeseriesdb' package was designed to manage a large catalog of time series from + official statistics which are typically published on a monthly, quarterly or yearly + basis. Thus timeseriesdb is optimized to handle updates caused by data revision + as well as elaborate, multi-lingual meta information. + date_publication: '2022-03-23' + bug_reports: https://github.com/mbannert/timeseriesdb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timeseriesdb + url_git: https://github.com/mbannert/timeseriesdb +timetk: + version: 2.9.0 + title: A Tool Kit for Working with Time Series + maintainer: Matt Dancho + description: |2- + + Easy visualization, wrangling, and feature engineering of time series data for + forecasting and machine learning prediction. Consolidates and extends time series functionality + from packages including 'dplyr', 'stats', 'xts', 'forecast', 'slider', 'padr', 'recipes', and 'rsample'. + date_publication: '2023-10-31' + bug_reports: https://github.com/business-science/timetk/issues + url: https://business-science.github.io/timetk/ + url_cran: https://CRAN.R-project.org/package=timetk + url_git: https://github.com/business-science/timetk +timetools: + version: 1.15.3 + title: |- + Seasonal/Sequential (Instants/Durations, Even or not) Time + Series + maintainer: Vladislav Navel + description: 'Objects to manipulate sequential and seasonal time series. Sequential + time series based on time instants and time durations are handled. Both can be + regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* + format are used for dates and times. The following classes are provided : ''POSIXcti'', + ''POSIXctp'', ''TimeIntervalDataFrame'', ''TimeInstantDataFrame'', ''SubtimeDataFrame'' + ; methods to switch from a class to another and to modify the time support of + series (hourly time series to daily time series for instance) are also defined. + Tools provided can be used for instance to handle environmental monitoring data + (not always produced on a regular time base).' + date_publication: '2023-08-29' + bug_reports: '' + url: https://sourceforge.net/projects/timetools/ + url_cran: https://CRAN.R-project.org/package=timetools + url_git: '' +TimeVarConcurrentModel: + version: '1.0' + title: Concurrent Multivariate Models with Time-Varying Coefficients + maintainer: Chance Vandergeugten + description: Provides a hypothesis test and variable selection algorithm for use + in time-varying, concurrent regression models. The hypothesis test function is + also accompanied by a plotting function which will show the estimated beta(s) + and confidence band(s) from the hypothesis test. The hypothesis test function + helps the user identify significant covariates within the scope of a time-varying + concurrent model. The plots will show the amount of area that falls outside the + confidence band(s) which is used for the test statistic within the hypothesis + test. + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TimeVarConcurrentModel + url_git: '' +timevarcorr: + version: 0.1.1 + title: Time Varying Correlation + maintainer: Alexandre Courtiol + description: |2- + + Computes how the correlation between 2 time-series changes over time. + To do so, the package follows the method from Choi & Shin (2021) . + It performs a non-parametric kernel smoothing (using a common bandwidth) of all underlying components required for the computation of a correlation coefficient (i.e., x, y, x^2, y^2, xy). + An automatic selection procedure for the bandwidth parameter is implemented. + Alternative kernels can be used (Epanechnikov, box and normal). + Both Pearson and Spearman correlation coefficients can be estimated and change in correlation over time can be tested. + date_publication: '2023-11-07' + bug_reports: https://github.com/courtiol/timevarcorr/issues + url: https://courtiol.github.io/timevarcorr/ + url_cran: https://CRAN.R-project.org/package=timevarcorr + url_git: https://github.com/courtiol/timevarcorr +timevis: + version: 2.1.0 + title: Create Interactive Timeline Visualizations in R + maintainer: Dean Attali + description: |- + Create rich and fully interactive timeline visualizations. + Timelines can be included in Shiny apps or R markdown documents. + 'timevis' includes an extensive API to manipulate a timeline after creation, + and supports getting data out of the visualization into R. Based on the + 'vis.js' Timeline JavaScript library. + date_publication: '2022-11-03' + bug_reports: https://github.com/daattali/timevis/issues + url: '' + url_cran: https://CRAN.R-project.org/package=timevis + url_git: https://github.com/daattali/timevis +TimeVizPro: + version: 1.0.1 + title: 'Dynamic Data Explorer: Visualize and Forecast with ''TimeVizPro''' + maintainer: Leila Marvian Mashhad + description: |- + Unleash the power of time-series data visualization with ease using our package. Designed with simplicity + in mind, it offers three key features through the 'shiny' package output. The first tab shows time- series + charts with forecasts, allowing users to visualize trends and changes effortlessly. The second one displays + Averages per country presented in tables with accompanying sparklines, providing a quick and attractive + overview of the data. The last tab presents A customizable world map colored based on user-defined + variables for any chosen number of countries, offering an advanced visual approach to understanding + geographical data distributions. This package operates with just a few simple arguments, enabling users + to conduct sophisticated analyses without the need for complex programming skills. Transform your + time-series data analysis experience with our user-friendly tool. + date_publication: '2024-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TimeVizPro + url_git: '' +TimeVTree: + version: 0.3.1 + title: |- + Survival Analysis of Time Varying Coefficients Using a + Tree-Based Approach + maintainer: Euyhyun Lee + description: |- + Estimates time varying regression effects under Cox type models in + survival data using classification and regression tree. The codes in this package were + originally written in S-Plus for the paper "Survival Analysis with Time-Varying Regression + Effects Using a Tree-Based Approach," by Xu, R. and Adak, S. (2002) , Biometrics, 58: 305-315. + Development of this package was supported by NIH grants AG053983 and AG057707, + and by the UCSD Altman Translational Research Institute, NIH grant UL1TR001442. + The content is solely the responsibility of the authors and does not necessarily + represent the official views of the NIH. + The example data are from the Honolulu Heart Program/Honolulu Asia Aging Study (HHP/HAAS). + date_publication: '2018-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TimeVTree + url_git: '' +TIMP: + version: 1.13.6 + title: |- + Fitting Separable Nonlinear Models in Spectroscopy and + Microscopy + maintainer: Joris Snellenburg + description: |- + A problem solving environment (PSE) for fitting separable + nonlinear models to measurements arising in physics and chemistry + experiments, as described by Mullen & van Stokkum (2007) + for its use in fitting time resolved + spectroscopy data, and as described by Laptenok et al. (2007) + for its use in fitting Fluorescence + Lifetime Imaging Microscopy (FLIM) data, in the study of Förster + Resonance Energy Transfer (FRET). `TIMP` also serves as the + computation backend for the `GloTarAn` software, a graphical user + interface for the package, as described in Snellenburg et al. (2012) + . + date_publication: '2022-12-12' + bug_reports: https://github.com/glotaran/TIMP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TIMP + url_git: https://github.com/glotaran/TIMP +timsac: + version: 1.3.8-4 + title: Time Series Analysis and Control Package + maintainer: Masami Saga + description: |- + Functions for statistical analysis, prediction and control of time + series based mainly on Akaike and Nakagawa (1988) . + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=timsac + url_git: '' +Tinflex: + version: '2.4' + title: A Universal Non-Uniform Random Number Generator + maintainer: Josef Leydold + description: |- + A universal non-uniform random number generator + for quite arbitrary distributions with piecewise twice + differentiable densities. + date_publication: '2023-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tinflex + url_git: '' +tinkr: + version: 0.2.0 + title: Cast '(R)Markdown' Files to 'XML' and Back Again + maintainer: Zhian N. Kamvar + description: |- + Parsing '(R)Markdown' files with numerous regular expressions can + be fraught with peril, but it does not have to be this way. Converting + '(R)Markdown' files to 'XML' using the 'commonmark' package allows + in-memory editing via of 'markdown' elements via 'XPath' through the + extensible 'R6' class called 'yarn'. These modified 'XML' representations + can be written to '(R)Markdown' documents via an 'xslt' stylesheet which + implements an extended version of 'GitHub'-flavoured 'markdown' so that you + can tinker to your hearts content. + date_publication: '2023-03-28' + bug_reports: https://github.com/ropensci/tinkr/issues + url: https://docs.ropensci.org/tinkr/ + url_cran: https://CRAN.R-project.org/package=tinkr + url_git: https://github.com/ropensci/tinkr +tinsel: + version: 0.0.1 + title: Transform Functions using Decorators + maintainer: Nathan Teetor + description: |- + Instead of nesting function calls, annotate and transform + functions using "#." comments. + date_publication: '2016-11-17' + bug_reports: https://github.com/nteetor/tinsel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinsel + url_git: https://github.com/nteetor/tinsel +tint: + version: 0.1.4 + title: '''tint'' is not ''Tufte''' + maintainer: Dirk Eddelbuettel + description: |- + A 'tufte'-alike style for 'rmarkdown'. + A modern take on the 'Tufte' design for pdf and html vignettes, + building on the 'tufte' package with additional contributions + from the 'knitr' and 'ggtufte' package, and also acknowledging + the key influence of 'envisioned css'. + date_publication: '2022-11-01' + bug_reports: https://github.com/eddelbuettel/tint/issues + url: https://dirk.eddelbuettel.com/code/tint.html + url_cran: https://CRAN.R-project.org/package=tint + url_git: https://github.com/eddelbuettel/tint/ +tinter: + version: 0.1.0 + title: Generate a Monochromatic Palette + maintainer: Sebastian Dalgarno + description: Generate a palette of tints, shades or both from a single colour. + date_publication: '2020-04-17' + bug_reports: https://github.com/poissonconsulting/tinter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinter + url_git: https://github.com/poissonconsulting/tinter +tintin: + version: '0.2' + title: Tintin Palette Generator + maintainer: Mauricio Vargas Sepulveda + description: |- + Palettes generated from Tintin covers. There is one palette per + cover, with a total of 24 palettes of 5 colours each. Includes functions to + interpolate colors in order to create more colors based on the provided + palettes.The data is based on Cyr, et al. (2004) + and Wikipedia . + date_publication: '2024-08-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tintin + url_git: '' +tinyarray: + version: 2.4.2 + title: Expression Data Analysis and Visualization + maintainer: Xiaojie Sun + description: The Gene Expression Omnibus () and + The Cancer Genome Atlas () are widely used medical + public databases. Our platform integrates routine analysis and visualization tools + for expression data to provide concise and intuitive data analysis and presentation. + date_publication: '2024-06-13' + bug_reports: https://github.com/xjsun1221/tinyarray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinyarray + url_git: https://github.com/xjsun1221/tinyarray +tinycodet: + version: 0.5.4 + title: Functions to Help in your Coding Etiquette + maintainer: Tony Wilkes + description: |- + Adds some functions to help in your coding etiquette. + 'tinycodet' primarily focuses on 4 aspects. + 1) Safer decimal (in)equality testing, + standard-evaluated alternatives to with() and aes(), + and other functions for safer coding. + 2) A new package import system, + that attempts to combine the benefits of using a package without attaching it, + with the benefits of attaching a package. + 3) Extending the string manipulation capabilities of the 'stringi' R package. + 4) Reducing repetitive code. + Besides linking to 'Rcpp', 'tinycodet' has only one other dependency, namely 'stringi'. + date_publication: '2025-01-09' + bug_reports: https://github.com/tony-aw/tinycodet/issues/ + url: https://tony-aw.github.io/tinycodet/ + url_cran: https://CRAN.R-project.org/package=tinycodet + url_git: https://github.com/tony-aw/tinycodet/ +tinylabels: + version: 0.2.4 + title: Lightweight Variable Labels + maintainer: Marius Barth + description: |- + Assign, extract, or remove variable labels from R vectors. + Lightweight and dependency-free. + date_publication: '2023-09-02' + bug_reports: https://github.com/mariusbarth/tinylabels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinylabels + url_git: https://github.com/mariusbarth/tinylabels +tinylens: + version: 0.1.0 + title: Minimal Implementation of Functional Lenses + maintainer: Albert Wang + description: |- + Provides utilities to create and use lenses to simplify data + manipulation. Lenses are composable getter/setter pairs that provide a + functional approach to manipulating deeply nested data structures, e.g., + elements within list columns in data frames. The implementation is based on + the earlier 'lenses' R package , + which was inspired by the Haskell 'lens' package by Kmett (2012) + , one of the most widely referenced + implementations of lenses. For additional background and history on the + theory of lenses, see the 'lens' package wiki: + . + date_publication: '2024-12-09' + bug_reports: https://github.com/arbelt/tinylens/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinylens + url_git: https://github.com/arbelt/tinylens +tinyplot: + version: 0.3.0 + title: Lightweight Extension of the Base R Graphics System + maintainer: Grant McDermott + description: |- + Lightweight extension of the base R graphics system, with support + for automatic legends, facets, themes, and various other enhancements. + date_publication: '2025-02-05' + bug_reports: https://github.com/grantmcdermott/tinyplot/issues + url: https://grantmcdermott.com/tinyplot/ + url_cran: https://CRAN.R-project.org/package=tinyplot + url_git: '' +tinyProject: + version: 0.6.1 + title: A Lightweight Template for Data Analysis Projects + maintainer: Francois Guillem + description: |- + Creates useful files and folders for data + analysis projects and provides functions to manage data, + scripts and output files. Also provides a project + template for 'Rstudio'. + date_publication: '2019-06-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tinyProject + url_git: '' +tinyscholar: + version: 0.1.7 + title: Get and Show Personal 'Google Scholar' Profile + maintainer: Shixiang Wang + description: |- + Provides functions to get personal 'Google Scholar' + profile data from web API and show it in table or figure format. + date_publication: '2022-08-09' + bug_reports: https://github.com/ShixiangWang/tinyscholar/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinyscholar + url_git: https://github.com/ShixiangWang/tinyscholar +tinysnapshot: + version: 0.0.8 + title: Snapshots for Unit Tests using the 'tinytest' Framework + maintainer: Vincent Arel-Bundock + description: Snapshots for unit tests using the 'tinytest' framework for R. Includes + expectations to test base R and 'ggplot2' plots as well as console output from + print(). + date_publication: '2025-01-21' + bug_reports: https://github.com/vincentarelbundock/tinysnapshot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinysnapshot + url_git: https://github.com/vincentarelbundock/tinysnapshot +tinyspotifyr: + version: 0.2.2 + title: Tinyverse R Wrapper for the 'Spotify' Web API + maintainer: Troy Hernandez + description: |- + An R wrapper for the 'Spotify' Web API + . + date_publication: '2021-02-24' + bug_reports: https://github.com/TroyHernandez/tinyspotifyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinyspotifyr + url_git: https://github.com/TroyHernandez/tinyspotifyr +tinytable: + version: 0.7.0 + title: |- + Simple and Configurable Tables in 'HTML', 'LaTeX', 'Markdown', + 'Word', 'PNG', 'PDF', and 'Typst' Formats + maintainer: Vincent Arel-Bundock + description: Create highly customized tables with this simple and dependency-free + package. Data frames can be converted to 'HTML', 'LaTeX', 'Markdown', 'Word', + 'PNG', 'PDF', or 'Typst' tables. The user interface is minimalist and easy to + learn. The syntax is concise. 'HTML' tables can be customized using the flexible + 'Bootstrap' framework, and 'LaTeX' code with the 'tabularray' package. + date_publication: '2025-01-24' + bug_reports: https://github.com/vincentarelbundock/tinytable/issues + url: https://vincentarelbundock.github.io/tinytable/ + url_cran: https://CRAN.R-project.org/package=tinytable + url_git: '' +tinytest: + version: 1.4.1 + title: Lightweight and Feature Complete Unit Testing Framework + maintainer: Mark van der Loo + description: |- + Provides a lightweight (zero-dependency) and easy to use + unit testing framework. Main features: install tests with + the package. Test results are treated as data that can be stored and + manipulated. Test files are R scripts interspersed with test commands, that + can be programmed over. Fully automated build-install-test sequence for + packages. Skip tests when not run locally (e.g. on CRAN). Flexible and + configurable output printing. Compare computed output with output stored + with the package. Run tests in parallel. Extensible by other packages. + Report side effects. + date_publication: '2023-02-22' + bug_reports: https://github.com/markvanderloo/tinytest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinytest + url_git: https://github.com/markvanderloo/tinytest +tinytest2JUnit: + version: 1.1.2 + title: Convert 'tinytest' Output to JUnit XML + maintainer: Lennart Tuijnder + description: |- + Unit testing is a solid component of automated CI/CD pipelines. + 'tinytest' - a lightweight, zero-dependency alternative to 'testthat' was developed. + To be able to integrate 'tinytests' results into common CI/CD systems the test results from + tinytest need to be caputred and converted to JUnit XML format. + 'tinytest2JUnit' enables this conversion while staying also lightweight + and only have 'tinytest' as its dependency. + date_publication: '2024-05-30' + bug_reports: https://github.com/openanalytics/tinytest2JUnit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinytest2JUnit + url_git: https://github.com/openanalytics/tinytest2JUnit +tinytex: + version: '0.56' + title: |- + Helper Functions to Install and Maintain TeX Live, and Compile + LaTeX Documents + maintainer: Yihui Xie + description: |- + Helper functions to install and maintain the 'LaTeX' distribution + named 'TinyTeX' (), a lightweight, cross-platform, + portable, and easy-to-maintain version of 'TeX Live'. This package also + contains helper functions to compile 'LaTeX' documents, and install missing + 'LaTeX' packages automatically. + date_publication: '2025-02-26' + bug_reports: https://github.com/rstudio/tinytex/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinytex + url_git: https://github.com/rstudio/tinytex +tinythemes: + version: 0.0.2 + title: Lightweight Repackaging of 'Themes' for 'ggplot2' + maintainer: Dirk Eddelbuettel + description: |- + Themes for 'ggplot2' are a convenient way to style plots. The 'hrbrthemes' package + contains a particularly nice one, but brings along a significant tail of dependencies. So this + (currently experimental) package brings along just the 'theme_ipsum_rc' theme using the 'Roboto' + 'Condensed' font. Should the font not be installed on your system, see the help in the package + 'hrbrthemes' on how to install 'Roboto Condensed'. + date_publication: '2024-03-04' + bug_reports: https://github.com/eddelbuettel/tinythemes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tinythemes + url_git: https://github.com/eddelbuettel/tinythemes +tinytiger: + version: 0.0.9 + title: Lightweight Interface to TIGER/Line Shapefiles + maintainer: Christopher T. Kenny + description: |- + Download geographic shapes from the United States Census Bureau + TIGER/Line Shapefiles . + Functions support downloading and reading in geographic boundary data. + All downloads can be set up with a cache to avoid multiple downloads. + Data is available back to 2000 for most geographies. + date_publication: '2024-06-04' + bug_reports: https://github.com/alarm-redist/tinytiger/issues + url: https://alarm-redist.org/tinytiger/ + url_cran: https://CRAN.R-project.org/package=tinytiger + url_git: https://github.com/alarm-redist/tinytiger +tip: + version: 0.1.0 + title: Bayesian Clustering Using the Table Invitation Prior (TIP) + maintainer: Charles W. Harrison + description: Cluster data without specifying the number of clusters using the Table + Invitation Prior (TIP) introduced in the paper "Clustering Gene Expression Using + the Table Invitation Prior" by Charles W. Harrison, Qing He, and Hsin-Hsiung Huang + (2022) . TIP is a Bayesian prior that uses pairwise + distance and similarity information to cluster vectors, matrices, or tensors. + date_publication: '2022-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tip + url_git: '' +tipa: + version: 1.0.8 + title: Tau-Independent Phase Analysis for Circadian Time-Course Data + maintainer: Jake Hughey + description: |- + Accurately estimates phase shifts by accounting for period + changes and for the point in the circadian cycle at which the stimulus occurs. + See Tackenberg et al. (2018) . + date_publication: '2023-08-21' + bug_reports: '' + url: https://tipa.hugheylab.org + url_cran: https://CRAN.R-project.org/package=tipa + url_git: https://github.com/hugheylab/tipa +TipDatingBeast: + version: 1.1-0 + title: Using Tip Dates with Phylogenetic Trees in BEAST + maintainer: Camilo Khatchikian + description: |- + Assists performing tip-dating of phylogenetic trees with BEAST + BEAST is a popular software for phylogenetic analysis. + The package assists the implementation of various phylogenetic tip- + dating tests using BEAST. It contains two main functions. + The first one allows preparing date randomization analyses, + which assess the temporal signal of a data set. + The second function allows performing leave-one-out analyses, + which test for the consistency between independent calibration sequences + and allow pinpointing those leading to potential bias. + The included tutorial provides detailed step-by-step instructions. + An expanded description of the package can be found in article: + Rieux, A. and Khatchikian, C.E. (2017), + TIPDATINGBEAST: an R package to assist the implementation of phylogenetic + tip-dating tests using BEAST. Molecular Ecology Resources, 17: 608-613. + . + date_publication: '2019-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TipDatingBeast + url_git: '' +tipitaka: + version: 0.1.2 + title: Data and Tools for Analyzing the Pali Canon + maintainer: Dan Zigmond + description: |- + Provides access to the complete Pali Canon, or + Tipitaka, the canonical scripture for Theravadin Buddhists + worldwide. Based on the Chattha Sangayana Tipitaka version + 4 (Vipassana Research Institute, 1990). + date_publication: '2021-03-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tipitaka + url_git: '' +tipmap: + version: 0.5.2 + title: Tipping Point Analysis for Bayesian Dynamic Borrowing + maintainer: Christian Stock + description: Tipping point analysis for clinical trials that employ Bayesian dynamic + borrowing via robust meta-analytic predictive (MAP) priors. Further functions + facilitate expert elicitation of a primary weight of the informative component + of the robust MAP prior and computation of operating characteristics. Intended + use is the planning, analysis and interpretation of extrapolation studies in pediatric + drug development, but applicability is generally wider. + date_publication: '2023-08-14' + bug_reports: https://github.com/Boehringer-Ingelheim/tipmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tipmap + url_git: https://github.com/Boehringer-Ingelheim/tipmap +tippy: + version: 0.1.0 + title: Add Tooltips to 'R markdown' Documents or 'Shiny' Apps + maintainer: John Coene + description: '''Htmlwidget'' of ''Tippyjs'' to add tooltips to ''Shiny'' apps and + ''R markdown'' documents.' + date_publication: '2021-01-11' + bug_reports: https://github.com/JohnCoene/tippy/issues + url: https://tippy.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=tippy + url_git: '' +tipr: + version: 1.0.2 + title: Tipping Point Analyses + maintainer: Lucy D'Agostino McGowan + description: |- + The strength of evidence provided by epidemiological and + observational studies is inherently limited by the potential for + unmeasured confounding. We focus on three key quantities: the + observed bound of the confidence interval closest to the null, the + relationship between an unmeasured confounder and the outcome, for + example a plausible residual effect size for an unmeasured continuous + or binary confounder, and the relationship between an unmeasured + confounder and the exposure, for example a realistic mean difference + or prevalence difference for this hypothetical confounder between + exposure groups. Building on the methods put forth by Cornfield et al. + (1959), Bross (1966), Schlesselman (1978), Rosenbaum & Rubin (1983), + Lin et al. (1998), Lash et al. (2009), Rosenbaum (1986), Cinelli & + Hazlett (2020), VanderWeele & Ding (2017), and Ding & VanderWeele + (2016), we can use these quantities to assess how an unmeasured + confounder may tip our result to insignificance. + date_publication: '2024-02-06' + bug_reports: https://github.com/r-causal/tipr/issues + url: https://r-causal.github.io/tipr/ + url_cran: https://CRAN.R-project.org/package=tipr + url_git: https://github.com/r-causal/tipr +TiPS: + version: 1.2.3 + title: Trajectories and Phylogenies Simulator + maintainer: Gonche Danesh + description: Generates stochastic time series and genealogies associated with a + population dynamics model. Times series are simulated using the Gillespie exact + and approximate algorithms and a new algorithm we introduce that uses both approaches + to optimize the time execution of the simulations. Genealogies are simulated from + a trajectory using a backwards-in-time based approach. Methods are described in + Danesh G et al (2022) . + date_publication: '2023-05-23' + bug_reports: https://gitlab.in2p3.fr/ete/tips/-/issues + url: https://gitlab.in2p3.fr/ete/tips/ + url_cran: https://CRAN.R-project.org/package=TiPS + url_git: '' +tipsae: + version: 1.0.3 + title: |- + Tools for Handling Indices and Proportions in Small Area + Estimation + maintainer: Silvia De Nicolò + description: It allows for mapping proportions and indicators defined on the unit + interval. It implements Beta-based small area methods comprising the classical + Beta regression models, the Flexible Beta model and Zero and/or One Inflated extensions + (Janicki 2020 ). Such methods, developed within + a Bayesian framework through Stan , come equipped with a + set of diagnostics and complementary tools, visualizing and exporting functions. + A Shiny application with a user-friendly interface can be launched to further + simplify the process. For further details, refer to De Nicolò and Gardini (2024 + ). + date_publication: '2024-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tipsae + url_git: '' +tis: + version: '1.39' + title: Time Indexes and Time Indexed Series + maintainer: Brian Salzer + description: |- + Functions and S3 classes for time indexes and time indexed + series, which are compatible with FAME frequencies. + date_publication: '2021-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tis + url_git: '' +TITAN2: + version: 2.4.3 + title: Threshold Indicator Taxa Analysis + maintainer: David Kahle + description: |- + Uses indicator species scores across binary partitions of + a sample set to detect congruence in taxon-specific changes of abundance + and occurrence frequency along an environmental gradient as evidence of + an ecological community threshold. Relevant references include Baker and King + (2010) , King and Baker (2010) + , and Baker and King (2013) . + date_publication: '2023-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TITAN2 + url_git: '' +titanic: + version: 0.1.0 + title: Titanic Passenger Survival Data Set + maintainer: Paul Hendricks + description: |- + This data set provides information on the fate of passengers on + the fatal maiden voyage of the ocean liner "Titanic", summarized according + to economic status (class), sex, age and survival. Whereas the base R + Titanic data found by calling data("Titanic") is an array resulting from + cross-tabulating 2201 observations, these data sets are the individual + non-aggregated observations and formatted in a machine learning context + with a training sample, a testing sample, and two additional data sets + that can be used for deeper machine learning analysis. These data sets + are also the data sets downloaded from the Kaggle competition and thus + lowers the barrier to entry for users new to R or machine learing. + date_publication: '2015-08-31' + bug_reports: https://github.com/paulhendricks/titanic/issues + url: '' + url_cran: https://CRAN.R-project.org/package=titanic + url_git: https://github.com/paulhendricks/titanic +TITEgBOIN: + version: 0.4.0 + title: Time-to-Event Dose-Finding Design for Multiple Toxicity Grades + maintainer: Jing Zhu + description: 'In some phase I trials, the design goal is to find the dose associated + with a certain target toxicity rate or the dose with a certain weighted sum of + rates of various toxicity grades. ''TITEgBOIN'' provides the set up and calculations + needed to run a dose-finding trial using bayesian optimal interval (BOIN) (Yuan + et al. (2016) ), generalized bayesian optimal + interval (gBOIN) (Mu et al. (2019) ), time-to-event bayesian + optimal interval (TITEBOIN) (Lin et al. (2020) ) + and time-to-event generalized bayesian optimal interval (TITEgBOIN) (Takeda et + al. (2022) ) designs. ''TITEgBOIN'' can conduct tasks: run + simulations and get operating characteristics; determine the dose for the next + cohort; select maximum tolerated dose (MTD). These functions allow customization + of design characteristics to vary sample size, cohort sizes, target dose limiting + toxicity (DLT) rates or target normalized equivalent toxicity score (ETS) rates + to account for discrete toxicity score, and incorporate safety and/or stopping + rules.' + date_publication: '2025-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TITEgBOIN + url_git: '' +titeIR: + version: 0.1.0 + title: Isotonic Designs for Phase 1 Trials with Late-Onset Toxicities + maintainer: Lee McDaniel + description: Functions to design phase 1 trials using an isotonic regression based + design incorporating time-to-event information. Simulation and design functions + are available, which incorporate information about followup and DLTs, and apply + isotonic regression to devise estimates of DLT probability. + date_publication: '2018-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=titeIR + url_git: '' +titrationCurves: + version: 0.1.0 + title: |- + Acid/Base, Complexation, Redox, and Precipitation Titration + Curves + maintainer: David Harvey + description: |- + A collection of functions to plot acid/base titration + curves (pH vs. volume of titrant), complexation titration curves + (pMetal vs. volume of EDTA), redox titration curves (potential + vs.volume of titrant), and precipitation titration curves (either + pAnalyte or pTitrant vs. volume of titrant). Options include the + titration of mixtures, the ability to overlay two or more + titration curves, and the ability to show equivalence points. + date_publication: '2016-02-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=titrationCurves + url_git: '' +TKCat: + version: 1.1.11 + title: Tailored Knowledge Catalog + maintainer: Patrice Godard + description: |- + Facilitate the management of data from knowledge + resources that are frequently used alone or together + in research environments. + In 'TKCat', knowledge resources are manipulated as modeled database (MDB) + objects. These objects provide access to the data tables along with a general + description of the resource and a detail data model documenting the + tables, their fields and their relationships. + These MDBs are then gathered in catalogs that can be easily + explored an shared. + Finally, 'TKCat' provides tools to easily subset, filter and combine MDBs and + create new catalogs suited for specific needs. + date_publication: '2024-07-03' + bug_reports: https://github.com/patzaw/TKCat/issues + url: https://patzaw.github.io/TKCat/ + url_cran: https://CRAN.R-project.org/package=TKCat + url_git: https://github.com/patzaw/TKCat/ +tkImgR: + version: 0.0.5 + title: Simple Image Viewer for R Using the 'tcltk' Package + maintainer: Filipe Campelo + description: A 'Tcl/Tk' Graphical User Interface (GUI) to display images than can + be zoomed and panned using the mouse and keyboard shortcuts. 'tkImgR' read and + write different image formats (PPM/PGM, PNG and GIF) using the standard 'Tcl/Tk' + distribution (>=8.6), but other formats (JPEG, TIFF, CR2) can be handled using + the 'tkImg' package for 'Tcl/Tk'. + date_publication: '2022-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tkImgR + url_git: '' +tkrplot: + version: 0.0-27 + title: TK Rplot + maintainer: Luke Tierney + description: Simple mechanism for placing R graphics in a Tk widget. + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tkrplot + url_git: '' +tkRplotR: + version: 0.1.7 + title: Display Resizable Plots + maintainer: Filipe Campelo + description: Display a plot in a Tk canvas. + date_publication: '2021-06-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tkRplotR + url_git: '' +tLagInterim: + version: '1.0' + title: Interim Monitoring of Clinical Trials with Time-Lagged Outcome + maintainer: Shannon T. Holloway + description: |- + Implements inverse and augmented inverse probability weighted + estimators for common treatment effect parameters at an interim analysis + with time-lagged outcome that may not be available for all enrolled subjects. + Produces estimators, standard errors, and information that can be used to + compute stopping boundaries using software that assumes that the + estimators/test statistics have independent increments. + Tsiatis, A. A. and Davidian, M., (2022) . + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tLagInterim + url_git: '' +tLagPropOdds: + version: '1.9' + title: |- + Proportional Odds Model with Censored, Time-Lagged Categorical + Outcome + maintainer: Shannon T. Holloway + description: |- + Implements a semiparametric estimator for the odds ratio model with + censored, time-lagged, ordered categorical outcome in a randomized clinical + trial that incorporates baseline and time-dependent information. + Tsiatis, A. A. and Davidian, M. (2021) . + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tLagPropOdds + url_git: '' +tlars: + version: 1.0.1 + title: |- + The T-LARS Algorithm: Early-Terminated Forward Variable + Selection + maintainer: Jasin Machkour + description: |- + Computes the solution path of the Terminating-LARS (T-LARS) algorithm. The T-LARS algorithm + is a major building block of the T-Rex selector (see R package 'TRexSelector'). + The package is based on the papers Machkour, Muma, and Palomar (2022) , Efron, Hastie, Johnstone, + and Tibshirani (2004) , and Tibshirani (1996) . + date_publication: '2024-02-24' + bug_reports: https://github.com/jasinmachkour/tlars/issues + url: https://arxiv.org/abs/2110.06048 + url_cran: https://CRAN.R-project.org/package=tlars + url_git: https://github.com/jasinmachkour/tlars +Tlasso: + version: 1.0.2 + title: |- + Non-Convex Optimization and Statistical Inference for Sparse + Tensor Graphical Models + maintainer: Xiang Lyu + description: An optimal alternating optimization algorithm for estimation of precision + matrices of sparse tensor graphical models, and an efficient inference procedure + for support recovery of the precision matrices. + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tlasso + url_git: '' +TLCAR: + version: 0.1.0 + title: |- + Computation of Topp-Leone Cauchy Rayleigh (TLCAR ) + distribution's properties + maintainer: Jude Mahoulé Bogninou + description: Provides a comprehensive suite of statistical tools for analyzing, + simulating, and computing properties of the Topp-Leone Cauchy Rayleigh (TLCAR) + distribution, a versatile distribution amalgamating features of the Topp-Leone, + Cauchy, and Rayleigh distributions, ideal for modeling intricate, heterogeneous + data across scientific domains. See Atchadé, M.N., Bogninou, M.J., and Djibril, + A.M. (2023) and Atchadé, M.N., Bogninou, M.J., + and Djibril, A.M. (2024) for further insights. + date_publication: '2024-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TLCAR + url_git: '' +tldr: + version: 0.4.0 + title: |- + T Loux Doing R: Functions to Simplify Data Analysis and + Reporting + maintainer: Travis Loux + description: |- + Gives a number of functions to aid common data + analysis processes and reporting statistical results in an 'RMarkdown' file. + Data analysis functions combine multiple base R functions used to describe + simple bivariate relationships into a single, easy to use function. + Reporting functions will return character strings to report p-values, + confidence intervals, and hypothesis test and regression results. Strings + will be LaTeX-formatted as necessary and will knit pretty in an 'RMarkdown' + document. The package also provides wrappers function in the 'tableone' + package to make the results knit-able. + date_publication: '2024-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tldr + url_git: '' +TLIC: + version: '0.4' + title: The LIC for T Distribution Regression Analysis + maintainer: Guangbao Guo + description: This comprehensive toolkit for T-distributed regression is designated + as "TLIC" (The LIC for T Distribution Regression Analysis) analysis. It is predicated + on the assumption that the error term adheres to a T-distribution. The philosophy + of the package is described in Guo G. (2020) . + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TLIC + url_git: '' +tlm: + version: 0.2.0 + title: |- + Effects under Linear, Logistic and Poisson Regression Models + with Transformed Variables + maintainer: Jose Barrera-Gomez + description: |- + Computation of effects under linear, logistic and Poisson regression + models with transformed variables. Logarithm and power transformations are allowed. + Effects can be displayed both numerically and graphically in both the original + and the transformed space of the variables. The methods are described in Barrera-Gomez + and Basagana (2015) . + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tlm + url_git: '' +TLMoments: + version: 0.7.5.3 + title: Calculate TL-Moments and Convert Them to Distribution Parameters + maintainer: Jona Lilienthal + description: |- + Calculates empirical TL-moments (trimmed L-moments) of arbitrary + order and trimming, and converts them to distribution parameters. + date_publication: '2022-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TLMoments + url_git: '' +tlrmvnmvt: + version: 1.1.2 + title: Low-Rank Methods for MVN and MVT Probabilities + maintainer: Jian Cao + description: "Implementation of the classic Genz algorithm and a novel tile-low-rank + algorithm for computing\trelatively high-dimensional multivariate normal (MVN) + and Student-t (MVT) probabilities.\nReferences used for this package:\nFoley, + James, Andries van Dam, Steven Feiner, and John Hughes.\n\"Computer Graphics: + Principle and Practice\". Addison-Wesley\nPublishing Company. Reading, Massachusetts + (1987, ISBN:0-201-84840-6 1);\nGenz, A., \"Numerical computation of multivariate\nnormal + probabilities,\" Journal of Computational and\nGraphical Statistics, 1, 141-149 + (1992) ;\nCao, J., Genton, M. G., Keyes, D. + E., & Turkiyyah, G. M. \"Exploiting Low\nRank Covariance Structures for Computing + High-Dimensional Normal and Student-\nt Probabilities,\" Statistics and Computing, + 31.1, 1-16 (2021)\n;\nCao, J., Genton, M. G., + Keyes, D. E., & Turkiyyah, G. M. \"tlrmvnmvt:\nComputing High-Dimensional Multivariate + Normal and Student-t Probabilities\nwith Low-Rank Methods in R,\" Journal of Statistical + Software, 101.4,\n1-25 (2022) ." + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tlrmvnmvt + url_git: '' +tls: + version: 0.1.0 + title: Tools of Total Least Squares in Error-in-Variables Models + maintainer: Yan Li + description: |- + Functions for point and interval estimation in + error-in-variables models via total least squares or + generalized total least squares method. See Golub and Van + Loan (1980) , Gleser (1981) + , Ivan Markovsky + and Huffel (2007) for + more information. + date_publication: '2018-10-06' + bug_reports: https://github.com/LiYanStat/tls/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tls + url_git: https://github.com/LiYanStat/tls +tm: + version: 0.7-16 + title: Text Mining Package + maintainer: Kurt Hornik + description: A framework for text mining applications within R. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tm + url_git: https://tm.r-forge.r-project.org/ +tm.plugin.alceste: + version: 1.1.2 + title: |- + Import Texts from Files in the 'Alceste' Format Using the 'tm' + Text Mining Framework + maintainer: Milan Bouchet-Valat + description: |- + Provides a 'tm' Source to create corpora from + a corpus prepared in the format used by the 'Alceste' application (i.e. + a single text file with inline meta-data). It is able to import both + text contents and meta-data (starred) variables. + date_publication: '2025-02-28' + bug_reports: https://github.com/nalimilan/R.TeMiS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tm.plugin.alceste + url_git: https://github.com/nalimilan/R.TeMiS +tm.plugin.dc: + version: 0.2-10 + title: Text Mining Distributed Corpus Plug-in + maintainer: Stefan Theussl + description: |- + A plug-in for the text mining framework tm to support text mining + in a distributed way. The package provides a convenient interface for + handling distributed corpus objects based on distributed list objects. + date_publication: '2020-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tm.plugin.dc + url_git: '' +tm.plugin.europresse: + version: '1.4' + title: |- + Import Articles from 'Europresse' Using the 'tm' Text Mining + Framework + maintainer: Milan Bouchet-Valat + description: |- + Provides a 'tm' Source to create corpora from + articles exported from the 'Europresse' content provider as + HTML files. It is able to read both text content and meta-data + information (including source, date, title, author and pages). + date_publication: '2016-08-23' + bug_reports: https://r-forge.r-project.org/tracker/?group_id=1437 + url: '' + url_cran: https://CRAN.R-project.org/package=tm.plugin.europresse + url_git: https://r-forge.r-project.org/projects/r-temis/ +tm.plugin.factiva: + version: '1.8' + title: |- + Import Articles from 'Factiva' Using the 'tm' Text Mining + Framework + maintainer: Milan Bouchet-Valat + description: |- + Provides a 'tm' Source to create corpora from + articles exported from the Dow Jones 'Factiva' content provider as + XML or HTML files. It is able to read both text content and meta-data + information (including source, date, title, author, subject, + geographical coverage, company, industry, and various + provider-specific fields). + date_publication: '2019-10-19' + bug_reports: https://github.com/nalimilan/R.TeMiS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tm.plugin.factiva + url_git: https://github.com/nalimilan/R.TeMiS +tm.plugin.koRpus: + version: 0.4-2 + title: Full Corpus Support for the 'koRpus' Package + maintainer: m.eik michalke + description: |- + Enhances 'koRpus' text object classes and methods to also support large + corpora. Hierarchical ordering of corpus texts into arbitrary categories will + be preserved. Provided classes and methods also improve the ability of using + the 'koRpus' package together with the 'tm' package. To ask for help, report + bugs, suggest feature improvements, or discuss the global development of the + package, please subscribe to the koRpus-dev mailing list + (). + date_publication: '2021-05-18' + bug_reports: https://github.com/unDocUMeantIt/tm.plugin.koRpus/issues + url: https://reaktanz.de/?c=hacking&s=koRpus + url_cran: https://CRAN.R-project.org/package=tm.plugin.koRpus + url_git: '' +tm.plugin.lexisnexis: + version: 1.4.1 + title: |- + Import Articles from 'LexisNexis' Using the 'tm' Text Mining + Framework + maintainer: Milan Bouchet-Valat + description: |- + Provides a 'tm' Source to create corpora from + articles exported from the 'LexisNexis' content provider as + HTML files. It is able to read both text content and meta-data + information (including source, date, title, author and pages). + Note that the file format is highly unstable: there is no warranty + that this package will work for your corpus, and you may have + to adjust the code to adapt it to your particular format. + date_publication: '2019-10-19' + bug_reports: https://github.com/nalimilan/R.TeMiS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tm.plugin.lexisnexis + url_git: https://github.com/nalimilan/R.TeMiS +tm.plugin.mail: + version: 0.3-1 + title: Text Mining E-Mail Plug-in + maintainer: Kurt Hornik + description: |- + A plug-in for the tm text mining framework providing mail handling + functionality. + date_publication: '2024-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tm.plugin.mail + url_git: '' +tm1r: + version: 1.1.8 + title: The Integration Between 'IBM COGNOS TM1' and R + maintainer: Muhammed Ali Onder + description: Useful functions to connect to 'TM1' + instance from R via REST API. With the functions in the package, data can be imported + from 'TM1' via mdx view or native view, data can be sent to 'TM1', processes and + chores can be executed, and cube and dimension metadata information can be taken. + date_publication: '2020-12-09' + bug_reports: https://github.com/muhammedalionder/tm1r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tm1r + url_git: https://github.com/muhammedalionder/tm1r +tmap: + version: '4.0' + title: Thematic Maps + maintainer: Martijn Tennekes + description: |- + Thematic maps are geographical maps in which spatial data + distributions are visualized. This package offers a flexible, + layer-based, and easy to use approach to create thematic maps, such as + choropleths and bubble maps. + date_publication: '2025-01-27' + bug_reports: https://github.com/r-tmap/tmap/issues + url: https://r-tmap.github.io/tmap/ + url_cran: https://CRAN.R-project.org/package=tmap + url_git: https://github.com/r-tmap/tmap +tmap.cartogram: + version: '0.1' + title: Extension to 'tmap' for Creating Cartograms + maintainer: Martijn Tennekes + description: Provides new layer functions to 'tmap' for creating various types of + cartograms. A cartogram is a type of thematic map in which geographic areas are + resized or distorted based on a quantitative variable, such as population. The + goal is to make the area sizes proportional to the selected variable while preserving + geographic positions as much as possible. + date_publication: '2025-02-03' + bug_reports: https://github.com/r-tmap/tmap.cartogram/issues + url: https://r-tmap.github.io/tmap.cartogram/ + url_cran: https://CRAN.R-project.org/package=tmap.cartogram + url_git: https://github.com/r-tmap/tmap.cartogram +tmaptools: + version: '3.2' + title: Thematic Map Tools + maintainer: Martijn Tennekes + description: Set of tools for reading and processing spatial data. The aim is to + supply the workflow to create thematic maps. This package also facilitates 'tmap', + the package for visualizing thematic maps. + date_publication: '2025-01-13' + bug_reports: https://github.com/r-tmap/tmaptools/issues + url: https://r-tmap.github.io/tmaptools/ + url_cran: https://CRAN.R-project.org/package=tmaptools + url_git: https://github.com/r-tmap/tmaptools +TMB: + version: 1.9.16 + title: |- + Template Model Builder: A General Random Effect Tool Inspired by + 'ADMB' + maintainer: Kasper Kristensen + description: |- + With this tool, a user should be able to quickly implement + complex random effect models through simple C++ templates. The package combines + 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector + library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain + an efficient implementation of the applied Laplace approximation with exact + derivatives. Key features are: Automatic sparseness detection, parallelism + through 'BLAS' and parallel user templates. + date_publication: '2025-01-08' + bug_reports: https://github.com/kaskr/adcomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TMB + url_git: https://github.com/kaskr/adcomp/wiki +tmbstan: + version: 1.0.91 + title: MCMC Sampling from 'TMB' Model Object using 'Stan' + maintainer: Kasper Kristensen + description: Enables all 'rstan' functionality for a 'TMB' model object, in particular + MCMC sampling and chain visualization. Sampling can be performed with or without + Laplace approximation for the random effects. This is demonstrated in Monnahan + & Kristensen (2018) . + date_publication: '2023-08-26' + bug_reports: https://github.com/kaskr/tmbstan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tmbstan + url_git: '' +TmCalculator: + version: 1.0.3 + title: Melting Temperature of Nucleic Acid Sequences + maintainer: Junhui Li + description: This tool is extended from methods in Bio.SeqUtils.MeltingTemp of python. + The melting temperature of nucleic acid sequences can be calculated in three method, + the Wallace rule (Thein & Wallace (1986) ), + empirical formulas based on G and C content (Marmur J. (1962) , + Schildkraut C. (2010) , Wetmur J G (1991) , + Untergasser,A. (2012) , von Ahsen N (2001) ) + and nearest neighbor thermodynamics (Breslauer K J (1986) , + Sugimoto N (1996) , Allawi H (1998) , + SantaLucia J (2004) , Freier S (1986) + , Xia T (1998) , Chen JL (2012) + , Bommarito S (2000) , Turner + D H (2010) , Sugimoto N (1995) , + Allawi H T (1997) , Santalucia N (2005) ), + and it can also be corrected with salt ions and chemical compound (SantaLucia + J (1996) , SantaLucia J(1998) , + Owczarzy R (2004) , Owczarzy R (2008) ). + date_publication: '2022-02-21' + bug_reports: https://github.com/JunhuiLi1017/TmCalculator/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TmCalculator + url_git: '' +tmcn: + version: 0.2-13 + title: A Text Mining Toolkit for Chinese + maintainer: Jian Li + description: |- + A Text mining toolkit for Chinese, which includes facilities for + Chinese string processing, Chinese NLP supporting, encoding detecting and + converting. Moreover, it provides some functions to support 'tm' package + in Chinese. + date_publication: '2019-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmcn + url_git: '' +TMDb: + version: '1.1' + title: Access to TMDb API + maintainer: Andrea Capozio + description: Provides an R-interface to the TMDb API (see TMDb API on ). + The Movie Database (TMDb) is a popular user editable database for movies and TV + shows (see ). + date_publication: '2020-03-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TMDb + url_git: '' +Tmisc: + version: 1.0.1 + title: Turner Miscellaneous + maintainer: Stephen Turner + description: |- + Miscellaneous utility functions for data manipulation, + data tidying, and working with gene expression data. + date_publication: '2023-08-23' + bug_reports: '' + url: https://stephenturner.github.io/Tmisc/ + url_cran: https://CRAN.R-project.org/package=Tmisc + url_git: https://github.com/stephenturner/Tmisc +TML: + version: 2.3.0 + title: Tropical Geometry Tools for Machine Learning + maintainer: David Barnhill + description: 'Suite of tropical geometric tools for use in machine learning applications. + These methods may be summarized in the following references: Yoshida, et al. (2022) + , Barnhill et al. (2023) , + Barnhill and Yoshida (2023) , Aliatimis et al. (2023) + , Yoshida et al. (2022) , + and Yoshida et al. (2019) .' + date_publication: '2024-07-29' + bug_reports: https://github.com/barnhilldave/TML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TML + url_git: https://github.com/barnhilldave/TML +tmle: + version: 2.0.1.1 + title: Targeted Maximum Likelihood Estimation + maintainer: Susan Gruber + description: Targeted maximum likelihood estimation of point treatment effects (Targeted + Maximum Likelihood Learning, The International Journal of Biostatistics, 2(1), + 2006. This version automatically estimates the additive treatment effect among + the treated (ATT) and among the controls (ATC). The tmle() function calculates + the adjusted marginal difference in mean outcome associated with a binary point + treatment, for continuous or binary outcomes. Relative risk and odds ratio estimates + are also reported for binary outcomes. Missingness in the outcome is allowed, + but not in treatment assignment or baseline covariate values. The population + mean is calculated when there is missingness, and no variation in the treatment + assignment. The tmleMSM() function estimates the parameters of a marginal structural + model for a binary point treatment effect. Effect estimation stratified by a binary + mediating variable is also available. An ID argument can be used to identify repeated + measures. Default settings call 'SuperLearner' to estimate the Q and g portions + of the likelihood, unless values or a user-supplied regression function are passed + in as arguments. + date_publication: '2024-05-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmle + url_git: '' +tmod: + version: 0.50.13 + title: |- + Feature Set Enrichment Analysis for Metabolomics and + Transcriptomics + maintainer: January Weiner + description: |- + Methods and feature set definitions for feature or gene set + enrichment analysis in transcriptional and metabolic profiling data. + Package includes tests for enrichment based on ranked lists of features, + functions for visualisation and multivariate functional analysis. See Zyla et al (2019) + . + date_publication: '2023-03-31' + bug_reports: '' + url: https://tmod.online + url_cran: https://CRAN.R-project.org/package=tmod + url_git: https://github.com/january3/tmod/ +tmplate: + version: 0.0.3 + title: Code Generation Based on Templates + maintainer: Mario A. Martinez Araya + description: Define general templates with tags that can be replaced by content + depending on arguments and objects to modify the final output of the document. + date_publication: '2021-07-20' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=tmplate + url_git: '' +tmpm: + version: 1.0.3 + title: Trauma Mortality Prediction Model + maintainer: Cody Moore + description: |- + Trauma Mortality prediction for ICD-9, ICD-10, and AIS lexicons in + long or wide format based on Dr. Alan Cook's tmpm mortality model. + date_publication: '2016-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmpm + url_git: '' +tmsens: + version: 0.3.1 + title: Sensitivity Analysis Using the Trimmed Means Estimator + maintainer: Audinga-Dea Hazewinkel + description: Sensitivity analysis using the trimmed means estimator. + date_publication: '2024-08-29' + bug_reports: https://github.com/dea-hazewinkel/tmsens/issues + url: https://dea-hazewinkel.github.io/tmsens/ + url_cran: https://CRAN.R-project.org/package=tmsens + url_git: https://github.com/dea-hazewinkel/tmsens +tmt: + version: 0.3.4-0 + title: Estimation of the Rasch Model for Multistage Tests + maintainer: Jan Steinfeld + description: Provides conditional maximum likelihood (CML) item parameter estimation + of both sequential and cumulative deterministic multistage designs (Zwitser & + Maris, 2015, ) and probabilistic sequential and + cumulative multistage designs (Steinfeld & Robitzsch, 2021, ). + Supports CML item parameter estimation of conventional linear designs and additional + functions for the likelihood ratio test (Andersen, 1973, ) + as well as functions for simulating various types of multistage designs. + date_publication: '2024-05-03' + bug_reports: https://github.com/jansteinfeld/tmt/issues + url: https://jansteinfeld.github.io/tmt/ + url_cran: https://CRAN.R-project.org/package=tmt + url_git: https://github.com/jansteinfeld/tmt +TMTI: + version: 1.0.3 + title: Too Many, Too Improbable (TMTI) Test Procedures + maintainer: Phillip B. Mogensen + description: Methods for computing joint tests, controlling the Familywise Error + Rate (FWER) and getting lower bounds on the number of false hypotheses in a set. + The methods implemented here are described in Mogensen and Markussen (2021) . + date_publication: '2024-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TMTI + url_git: '' +tmvmixnorm: + version: 1.1.1 + title: Sampling from Truncated Multivariate Normal and t Distributions + maintainer: Ting Fung (Ralph) Ma + description: 'Efficient sampling of truncated multivariate (scale) mixtures of normals + under linear inequality constraints is nontrivial due to the analytically intractable + normalizing constant. Meanwhile, traditional methods may subject to numerical + issues, especially when the dimension is high and dependence is strong. Algorithms + proposed by Li and Ghosh (2015) are adopted + for overcoming difficulties in simulating truncated distributions. Efficient rejection + sampling for simulating truncated univariate normal distribution is included in + the package, which shows superiority in terms of acceptance rate and numerical + stability compared to existing methods and R packages. An efficient function for + sampling from truncated multivariate normal distribution subject to convex polytope + restriction regions based on Gibbs sampler for conditional truncated univariate + distribution is provided. By extending the sampling method, a function for sampling + truncated multivariate Student''s t distribution is also developed. Moreover, + the proposed method and computation remain valid for high dimensional and strong + dependence scenarios. Empirical results in Li and Ghosh (2015) + illustrated the superior performance in terms of various criteria (e.g. mixing + and integrated auto-correlation time).' + date_publication: '2020-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmvmixnorm + url_git: '' +tmvnsim: + version: 1.0-2 + title: Truncated Multivariate Normal Simulation + maintainer: Samsiddhi Bhattacharjee + description: |- + Importance sampling from the truncated multivariate normal using the GHK (Geweke-Hajivassiliou-Keane) simulator. + Unlike Gibbs sampling which can get stuck in one truncation sub-region depending on initial values, this package allows + truncation based on disjoint regions that are created by truncation of absolute values. The GHK algorithm uses simple Cholesky + transformation followed by recursive simulation of univariate truncated normals hence there are also no convergence issues. + Importance sample is returned along with sampling weights, based on which, one can calculate integrals over truncated regions + for multivariate normals. + date_publication: '2016-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmvnsim + url_git: '' +tmvtnorm: + version: '1.6' + title: Truncated Multivariate Normal and Student t Distribution + maintainer: Stefan Wilhelm + description: |- + Random number generation for the truncated multivariate normal and Student t distribution. + Computes probabilities, quantiles and densities, + including one-dimensional and bivariate marginal densities. Computes first and second moments (i.e. mean and covariance matrix) for the double-truncated multinormal case. + date_publication: '2023-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmvtnorm + url_git: '' +tmvtnsim: + version: 0.1.3 + title: Truncated Multivariate Normal and t Distribution Simulation + maintainer: Kaifeng Lu + description: |- + Simulation of random vectors from truncated multivariate normal + and t distributions based on the algorithms proposed by Yifang Li and Sujit K. Ghosh (2015) . + date_publication: '2022-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tmvtnsim + url_git: '' +tna: + version: 0.4.0 + title: Transition Network Analysis (TNA) + maintainer: Sonsoles López-Pernas + description: |- + Provides tools for performing Transition Network Analysis (TNA) to + study relational dynamics, including functions for building and plotting TNA + models, calculating centrality measures, and identifying dominant events and + patterns. TNA statistical techniques (e.g., bootstrapping and permutation + tests) ensure the reliability of observed insights and confirm that + identified dynamics are meaningful. See (Saqr et al., 2025) + for more details on TNA. + date_publication: '2025-03-01' + bug_reports: https://github.com/sonsoleslp/tna/issues/ + url: http://sonsoles.me/tna/ + url_cran: https://CRAN.R-project.org/package=tna + url_git: https://github.com/sonsoleslp/tna/ +TNC: + version: 0.1.0 + title: Temporal Network Centrality (TNC) Measures + maintainer: Moritz Hanke + description: Node centrality measures for temporal networks. Available measures + are temporal degree centrality, temporal closeness centrality and temporal betweenness + centrality defined by Kim and Anderson (2012) . + Applying the REN algorithm by Hanke and Foraita (2017) + when calculating the centrality measures keeps the computational running time + linear in the number of graph snapshots. Further, all methods can run in parallel + up to the number of nodes in the network. + date_publication: '2017-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TNC + url_git: '' +tnet: + version: 3.0.16 + title: Weighted, Two-Mode, and Longitudinal Networks Analysis + maintainer: Tore Opsahl + description: Binary ties limit the richness of network analyses as relations are + unique. The two-mode structure contains a number of features lost when projection + it to a one-mode network. Longitudinal datasets allow for an understanding of + the causal relationship among ties, which is not the case in cross-sectional datasets + as ties are dependent upon each other. + date_publication: '2020-02-24' + bug_reports: '' + url: http://toreopsahl.com/tnet/ + url_cran: https://CRAN.R-project.org/package=tnet + url_git: '' +tnl.Test: + version: 0.1.0 + title: Non-Parametric Tests for the Two-Sample Problem + maintainer: Ihab Abusaif + description: |- + Performing the hypothesis tests for the two + sample problem based on order statistics and power comparisons. + Calculate the test statistic, density, distribution function, + quantile function, random number generation and others. + date_publication: '2023-12-12' + bug_reports: https://github.com/ihababusaif/tnl.Test/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tnl.Test + url_git: https://github.com/ihababusaif/tnl.Test +TNRS: + version: 0.3.6 + title: Taxonomic Name Resolution Service + maintainer: Brian Maitner + description: Provides access to the Taxonomic Name Resolution Service + through R. The user supplies plant taxonomic names and the package returns resolved + taxonomic names along with information on decisions. Optionally, the package + can also be used to parse taxonomic names. + date_publication: '2024-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TNRS + url_git: '' +tntpr: + version: 1.2.1 + title: Data Analysis Tools Customized for TNTP + maintainer: Dustin Pashouwer + description: |- + An assortment of functions and templates customized to meet + the needs of data analysts at the non-profit organization TNTP. + Includes functions for branded colors and plots, credentials management, + repository set-up, and other common analytic tasks. + date_publication: '2024-11-26' + bug_reports: '' + url: https://tntp.github.io/tntpr/ + url_cran: https://CRAN.R-project.org/package=tntpr + url_git: https://github.com/tntp/tntpr +toastui: + version: 0.3.4 + title: Interactive Tables, Calendars and Charts for the Web + maintainer: Victor Perrier + description: |- + Create interactive tables, calendars and charts with 'TOAST UI' libraries to + integrate in 'shiny' applications or 'rmarkdown' 'HTML' documents. + date_publication: '2024-09-18' + bug_reports: https://github.com/dreamRs/toastui/issues + url: https://dreamrs.github.io/toastui/ + url_cran: https://CRAN.R-project.org/package=toastui + url_git: '' +TOC: + version: 0.0-6 + title: Total Operating Characteristic Curve and ROC Curve + maintainer: Ali Santacruz + description: 'Construction of the Total Operating Characteristic (TOC) Curve and + the Receiver (aka Relative) Operating Characteristic (ROC) Curve for spatial and + non-spatial data. The TOC method is a modification of the ROC method which measures + the ability of an index variable to diagnose either presence or absence of a characteristic. + The diagnosis depends on whether the value of an index variable is above a threshold. + Each threshold generates a two-by-two contingency table, which contains four entries: + hits (H), misses (M), false alarms (FA), and correct rejections (CR). While ROC + shows for each threshold only two ratios, H/(H + M) and FA/(FA + CR), TOC reveals + the size of every entry in the contingency table for each threshold (Pontius Jr., + R.G., Si, K. 2014. ).' + date_publication: '2023-02-09' + bug_reports: https://github.com/amsantac/TOC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TOC + url_git: https://github.com/amsantac/TOC +todor: + version: 0.1.2 + title: Find All TODO Comments and More + maintainer: Dominik Krzemiński + description: This is a simple addin to 'RStudio' that finds all 'TODO', 'FIX ME', + 'CHANGED' etc. comments in your project and shows them as a markers list. + date_publication: '2021-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=todor + url_git: '' +togglr: + version: 0.2.1 + title: '''Toggl.com'' Api for ''Rstudio''' + maintainer: Vincent Guyader + description: Use the time tracker api through R. + date_publication: '2024-02-19' + bug_reports: https://github.com/ThinkR-open/togglr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=togglr + url_git: https://github.com/ThinkR-open/togglr +TOHM: + version: '1.4' + title: Testing One Hypothesis Multiple Times + maintainer: Sara Algeri + description: Approximations of global p-values when testing hypothesis in presence + of non-identifiable nuisance parameters. The method relies on the Euler characteristic + heuristic and the expected Euler characteristic is efficiently computed by in + Algeri and van Dyk (2018) . + date_publication: '2021-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TOHM + url_git: '' +tokenbrowser: + version: 0.1.5 + title: Create Full Text Browsers from Annotated Token Lists + maintainer: Kasper Welbers + description: |- + Create browsers for reading full texts from a token list format. + Information obtained from text analyses (e.g., topic modeling, word scaling) + can be used to annotate the texts. + date_publication: '2020-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tokenbrowser + url_git: '' +tokenizers: + version: 0.3.0 + title: Fast, Consistent Tokenization of Natural Language Text + maintainer: Lincoln Mullen + description: |- + Convert natural language text into tokens. Includes tokenizers for + shingled n-grams, skip n-grams, words, word stems, sentences, paragraphs, + characters, shingled characters, lines, Penn Treebank, regular + expressions, as well as functions for counting characters, words, and sentences, + and a function for splitting longer texts into separate documents, each with + the same number of words. The tokenizers have a consistent interface, and + the package is built on the 'stringi' and 'Rcpp' packages for fast + yet correct tokenization in 'UTF-8'. + date_publication: '2022-12-22' + bug_reports: https://github.com/ropensci/tokenizers/issues + url: https://docs.ropensci.org/tokenizers/ + url_cran: https://CRAN.R-project.org/package=tokenizers + url_git: https://github.com/ropensci/tokenizers +tokenizers.bpe: + version: 0.1.3 + title: Byte Pair Encoding Text Tokenization + maintainer: Jan Wijffels + description: Unsupervised text tokenizer focused on computational efficiency. Wraps + the 'YouTokenToMe' library which is an + implementation of fast Byte Pair Encoding (BPE) . + date_publication: '2023-09-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tokenizers.bpe + url_git: https://github.com/bnosac/tokenizers.bpe +tolerance: + version: 3.0.0 + title: Statistical Tolerance Intervals and Regions + maintainer: Derek S. Young + description: Statistical tolerance limits provide the limits between which we can + expect to find a specified proportion of a sampled population with a given level + of confidence. This package provides functions for estimating tolerance limits + (intervals) for various univariate distributions (binomial, Cauchy, discrete Pareto, + exponential, two-parameter exponential, extreme value, hypergeometric, Laplace, + logistic, negative binomial, negative hypergeometric, normal, Pareto, Poisson-Lindley, + Poisson, uniform, and Zipf-Mandelbrot), Bayesian normal tolerance limits, multivariate + normal tolerance regions, nonparametric tolerance intervals, tolerance bands for + regression settings (linear regression, nonlinear regression, nonparametric regression, + and multivariate regression), and analysis of variance tolerance intervals. Visualizations + are also available for most of these settings. + date_publication: '2024-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tolerance + url_git: '' +tomba: + version: 1.0.1 + title: Official R Library for Tomba Email Finder + maintainer: Abedrahim Ben rebia + description: |- + Email Finder R Client Library. + Search emails are based on the website You give one domain name and it returns all the email addresses found on the internet. + Email Finder generates or retrieves the most likely email address from a domain name, a first name and a last name. + Email verify checks the deliverability of a given email address, verifies if it has been found in our database, and returns their sources. + date_publication: '2021-11-02' + bug_reports: https://github.com/tomba-io/r/issues + url: https://tomba.io/ + url_cran: https://CRAN.R-project.org/package=tomba + url_git: https://github.com/tomba-io/r +tomledit: + version: 0.1.0 + title: Parse, Read, and Edit 'TOML' + maintainer: Josiah Parry + description: |- + A toolkit for working with 'TOML' files in R while preserving + formatting, comments, and structure. 'tomledit' enables serialization of R + objects such as lists, data.frames, numeric, logical, and date vectors. + date_publication: '2025-02-13' + bug_reports: '' + url: https://josiahparry.github.io/tomledit/ + url_cran: https://CRAN.R-project.org/package=tomledit + url_git: '' +tongfen: + version: 0.3.5 + title: Make Data Based on Different Geographies Comparable + maintainer: Jens von Bergmann + description: Several functions to allow comparisons of data across different geographies, + in particular for Canadian census data from different censuses. + date_publication: '2022-04-28' + bug_reports: https://github.com/mountainMath/tongfen/issues + url: https://mountainmath.github.io/tongfen/ + url_cran: https://CRAN.R-project.org/package=tongfen + url_git: https://github.com/mountainMath/tongfen +toolbox: + version: 0.1.1 + title: List, String, and Meta Programming Utility Functions + maintainer: Timothy Conwell + description: |- + Includes functions for mapping named lists to function arguments, random strings, + pasting and combining rows together across columns, etc. + date_publication: '2022-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=toolbox + url_git: '' +toolmaRk: + version: 0.0.1 + title: Tests for Same-Source of Toolmarks + maintainer: Jeremy Hadler + description: Implements two tests for same-source of toolmarks. The chumbley_non_random() + test follows the paper "An Improved Version of a Tool Mark Comparison Algorithm" + by Hadler and Morris (2017) . This is an extension + of the Chumbley score as previously described in "Validation of Tool Mark Comparisons + Obtained Using a Quantitative, Comparative, Statistical Algorithm" by Chumbley + et al (2010) . fixed_width_no_modeling() + is based on correlation measures in a diamond shaped area of the toolmark as described + in Hadler (2017). + date_publication: '2018-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=toolmaRk + url_git: '' +tools4uplift: + version: 1.0.0 + title: Tools for Uplift Modeling + maintainer: Mouloud Belbahri + description: 'Uplift modeling aims at predicting the causal effect of an action + such as a marketing campaign on a particular individual. In order to simplify + the task for practitioners in uplift modeling, we propose a combination of tools + that can be separated into the following ingredients: i) quantization, ii) visualization, + iii) variable selection, iv) parameters estimation and, v) model validation. For + more details, see .' + date_publication: '2021-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tools4uplift + url_git: '' +ToolsForCoDa: + version: 1.1.0 + title: Multivariate Tools for Compositional Data Analysis + maintainer: Jan Graffelman + description: Provides functions for multivariate analysis with compositional data. + Includes a function for doing compositional canonical correlation analysis. This + analysis requires two data matrices of compositions, which can be adequately transformed + and used as entries in a specialized program for canonical correlation analysis, + that is able to deal with singular covariance matrices. The methodology is described + in Graffelman et al. (2017) . Functions for log-ratio principal + component analysis with condition number computations and log-ratio discriminant + analysis have been added to the package. + date_publication: '2025-01-09' + bug_reports: '' + url: http://www-eio.upc.edu/~jan/ + url_cran: https://CRAN.R-project.org/package=ToolsForCoDa + url_git: '' +toolStability: + version: 0.1.2 + title: Tool for Stability Indices Calculation + maintainer: Tien-Cheng Wang + description: |- + Tools to calculate stability indices with parametric, + non-parametric and probabilistic approaches. The basic data format requirement for 'toolStability' is a data frame with 3 columns including numeric trait values, genotype,and environmental labels. Output format of each function is the dataframe with chosen stability index for each genotype. + Function "table_stability" offers the summary table of all stability indices in this package. + This R package toolStability is part of the main publication: + Wang, Casadebaig and Chen (2023) . + Analysis pipeline for main publication can be found on github: . + Sample dataset in this package is derived from another publication: + Casadebaig P, Zheng B, Chapman S et al. (2016) . + For detailed documentation of dataset, please see on Zenodo . + Indices used in this package are from: + Döring TF, Reckling M (2018) . + Eberhart SA, Russell WA (1966) . + Eskridge KM (1990) . + Finlay KW, Wilkinson GN (1963) . + Hanson WD (1970) Genotypic stability. . + Lin CS, Binns MR (1988) . + Nassar R, Hühn M (1987). + Pinthus MJ (1973) . + Römer T (1917). + Shukla GK (1972). + Wricke G (1962). + date_publication: '2023-03-13' + bug_reports: https://github.com/Illustratien/toolStability/issues + url: https://illustratien.github.io/toolStability/ + url_cran: https://CRAN.R-project.org/package=toolStability + url_git: https://github.com/Illustratien/toolStability +TooManyCellsR: + version: 0.1.1.0 + title: An R Wrapper for 'TooManyCells' + maintainer: Gregory W. Schwartz + description: An R wrapper for using 'TooManyCells', a command line program for clustering, + visualizing, and quantifying cell clade relationships. See + for more details. + date_publication: '2019-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TooManyCellsR + url_git: '' +toOrdinal: + version: 1.3-0.0 + title: Cardinal to Ordinal Number & Date Conversion + maintainer: Damian W. Betebenner + description: Language specific cardinal to ordinal number conversion. + date_publication: '2022-02-24' + bug_reports: https://github.com/centerforassessment/toOrdinal/issues/ + url: https://centerforassessment.github.io/toOrdinal/ + url_cran: https://CRAN.R-project.org/package=toOrdinal + url_git: https://github.com/centerforassessment/toOrdinal/ +Toothnroll: + version: '1.11' + title: Dental Tissues Landmarking Measuring and Mapping + maintainer: Antonio Profico + description: |- + Two- and three-dimensional morphometric maps of enamel and + dentine thickness and multivariate analysis. + Volume calculation of dental materials. + Principal component analysis of thickness maps with + associated morphometric map variations. + date_publication: '2024-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Toothnroll + url_git: '' +topChef: + version: 0.2.0 + title: Top Chef Data + maintainer: Levitz Carly E + description: |- + Several datasets which describe the chef contestants in Top Chef, + the challenges that they compete in, and the results of those challenges. + This data is useful for practicing data wrangling, graphing, and analyzing + how each season of Top Chef played out. + date_publication: '2024-06-21' + bug_reports: https://github.com/celevitz/topChef/issues + url: '' + url_cran: https://CRAN.R-project.org/package=topChef + url_git: https://github.com/celevitz/topChef +TopDom: + version: 0.10.1 + title: |- + An Efficient and Deterministic Method for Identifying + Topological Domains in Genomes + maintainer: Henrik Bengtsson + description: The 'TopDom' method identifies topological domains in genomes from + Hi-C sequence data (Shin et al., 2016 ). The authors + published an implementation of their method as an R script (two different versions; + also available in this package). This package originates from those original + 'TopDom' R scripts and provides help pages adopted from the original 'TopDom' + PDF documentation. It also provides a small number of bug fixes to the original + code. + date_publication: '2021-05-06' + bug_reports: https://github.com/HenrikBengtsson/TopDom/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TopDom + url_git: https://github.com/HenrikBengtsson/TopDom +topdowntimeratio: + version: 0.1.0 + title: Top-Down Time Ratio Segmentation for Coordinate Trajectories + maintainer: Danielle McCool + description: |- + Data collected on movement behavior is often in the form of time- + stamped latitude/longitude coordinates sampled from the underlying movement + behavior. These data can be compressed into a set of segments via the Top- + Down Time Ratio Segmentation method described in Meratnia and de By (2004) + which, with some loss of information, + can both reduce the size of the data as well as provide corrective smoothing + mechanisms to help reduce the impact of measurement error. This is an + improvement on the well-known Douglas-Peucker algorithm for segmentation + that operates not on the basis of perpendicular distances. Top-Down Time + Ratio segmentation allows for disparate sampling time intervals by + calculating the distance between locations and segments with respect to + time. Provided a trajectory with timestamps, tdtr() returns a set of straight- + line segments that can represent the full trajectory. McCool, Lugtig, + and Schouten (2022) describe this method as + implemented here in more detail. + date_publication: '2022-09-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=topdowntimeratio + url_git: '' +topicdoc: + version: 0.1.1 + title: Topic-Specific Diagnostics for LDA and CTM Topic Models + maintainer: Doug Friedman + description: |- + Calculates topic-specific diagnostics (e.g. mean token length, exclusivity) for + Latent Dirichlet Allocation and Correlated Topic Models fit using the 'topicmodels' package. + For more details, see Chapter 12 in Airoldi et al. (2014, ISBN:9781466504080), + pp 262-272 Mimno et al. (2011, ISBN:9781937284114), and Bischof et al. (2014) . + date_publication: '2022-07-17' + bug_reports: https://github.com/doug-friedman/topicdoc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=topicdoc + url_git: https://github.com/doug-friedman/topicdoc +topiclabels: + version: 0.2.0 + title: Automated Topic Labeling with Language Models + maintainer: Jonas Rieger + description: Leveraging (large) language models for automatic topic labeling. The + main function converts a list of top terms into a label for each topic. Hence, + it is complementary to any topic modeling package that produces a list of top + terms for each topic. While human judgement is indispensable for topic validation + (i.e., inspecting top terms and most representative documents), automatic topic + labeling can be a valuable tool for researchers in various scenarios. + date_publication: '2024-10-21' + bug_reports: https://github.com/PetersFritz/topiclabels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=topiclabels + url_git: https://github.com/PetersFritz/topiclabels +topicmodels: + version: 0.2-17 + title: Topic Models + maintainer: Bettina Grün + description: |- + Provides an interface to the C code for Latent Dirichlet + Allocation (LDA) models and Correlated Topics Models + (CTM) by David M. Blei and co-authors and the C++ code + for fitting LDA models using Gibbs sampling by Xuan-Hieu + Phan and co-authors. + date_publication: '2024-08-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=topicmodels + url_git: '' +topicmodels.etm: + version: 0.1.0 + title: Topic Modelling in Embedding Spaces + maintainer: Jan Wijffels + description: |- + Find topics in texts which are semantically embedded using techniques like word2vec or Glove. + This topic modelling technique models each word with a categorical distribution whose natural parameter is the inner product between a word embedding and an embedding of its assigned topic. + The techniques are explained in detail in the paper 'Topic Modeling in Embedding Spaces' by Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei (2019), available at . + date_publication: '2021-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=topicmodels.etm + url_git: '' +topics: + version: 0.21.0 + title: |- + Creating and Significance Testing Language Features for + Visualisation + maintainer: Oscar Kjell + description: Implements differential language analysis with statistical tests and + offers various language visualization techniques for n-grams and topics. It also + supports the 'text' package. For more information, visit + and . + date_publication: '2024-11-23' + bug_reports: https://github.com/theharmonylab/topics/issues + url: https://r-topics.org/ + url_cran: https://CRAN.R-project.org/package=topics + url_git: '' +TopicScore: + version: 0.0.1 + title: The Topic SCORE Algorithm to Fit Topic Models + maintainer: Minzhe Wang + description: |- + Provides implementation of the "Topic SCORE" algorithm that is + proposed by Tracy Ke and Minzhe Wang. The singular value decomposition + step is optimized through the usage of svds() function in 'RSpectra' + package, on a 'dgRMatrix' sparse matrix. Also provides a column-wise + error measure in the word-topic matrix A, and an algorithm for + recovering the topic-document matrix W given A and D based on + quadratic programming. + The details about the techniques are explained in the paper "A new SVD approach to optimal topic estimation" by Tracy Ke and Minzhe Wang (2017) . + date_publication: '2019-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TopicScore + url_git: '' +TopKLists: + version: 1.0.8 + title: Inference, Aggregation and Visualization for Top-K Ranked Lists + maintainer: Bastian Pfeifer + description: For multiple ranked input lists (full or partial) representing the + same set of N objects, the package 'TopKLists' offers + (1) statistical inference on the lengths of informative top-k lists, (2) stochastic + aggregation of full or partial lists, and (3) graphical tools for the statistical + exploration of input lists, and for the visualization of aggregation results. + Note that RGtk2 and gWidgets2RGtk2 have been archived on CRAN. See + for installation instructions. + date_publication: '2022-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TopKLists + url_git: http://topklists.r-forge.r-project.org +TopKSignal: + version: '1.0' + title: |- + A Convex Optimization Tool for Signal Reconstruction from + Multiple Ranked Lists + maintainer: Bastian Pfeifer Maintainer + description: A mathematical optimization procedure in combination with statistical + bootstrap for the estimation of the latent signals (sometimes called scores) informing + the global consensus ranking (often named aggregation ranking). To solve mid/large-scale + problems, users should install the 'gurobi' optimiser (available from ). + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TopKSignal + url_git: '' +topoDistance: + version: 1.0.2 + title: Calculating Topographic Paths and Distances + maintainer: Ian Wang + description: A toolkit for calculating topographic distances and identifying and + plotting topographic paths. Topographic distances can be calculated along shortest + topographic paths (Wang (2009) ), weighted + topographic paths (Zhan et al. (1993) ), and topographic + least cost paths (Wang and Summers (2010) ). + Functions can map topographic paths on colored or hill shade maps and plot topographic + cross sections (elevation profiles) for the paths. + date_publication: '2022-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=topoDistance + url_git: '' +topologyGSA: + version: 1.5.0 + title: Gene Set Analysis Exploiting Pathway Topology + maintainer: Gabriele Sales + description: |- + Using Gaussian graphical models we propose a novel approach to + perform pathway analysis using gene expression. Given the + structure of a graph (a pathway) we introduce two statistical + tests to compare the mean and the concentration matrices between + two groups. Specifically, these tests can be performed on the + graph and on its connected components (cliques). The package is + based on the method described in Massa M.S., Chiogna M., Romualdi + C. (2010) . + date_publication: '2023-09-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=topologyGSA + url_git: '' +toposort: + version: 1.0.0 + title: Topological Sorting Algorithms + maintainer: Taras Zakharko + description: |- + Flexible and ergonomic topological sorting implementation for + R. Supports a variety of input data encoding (lists of edges or + adjacency matrices, graphs edge direction), stable sort variants as + well as cycle detection with detailed diagnosis. + date_publication: '2023-03-08' + bug_reports: https://github.com/tzakharko/toposort/issues + url: '' + url_cran: https://CRAN.R-project.org/package=toposort + url_git: https://github.com/tzakharko/toposort +topr: + version: 2.0.2 + title: Create Custom Plots for Viewing Genetic Association Results + maintainer: Thorhildur Juliusdottir + description: A collection of functions for visualizing,exploring and annotating + genetic association results.Association results from multiple traits can be viewed + simultaneously along with gene annotation, over the entire genome (Manhattan plot) + or in the more detailed regional view. + date_publication: '2024-06-19' + bug_reports: https://github.com/totajuliusd/topr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=topr + url_git: https://github.com/totajuliusd/topr +toprdata: + version: 1.0.2 + title: Gene and Exon Data from Ensembl + maintainer: Thorhildur Juliusdottir + description: Gene and exon information from Ensembl genome builds GRCh38.p13 (104) + and GRCh37 (v40) to use with the 'topr' package. + date_publication: '2023-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=toprdata + url_git: '' +topsis: + version: '1.0' + title: TOPSIS method for multiple-criteria decision making (MCDM) + maintainer: Mahmoud Mosalman Yazdi + description: Evaluation of alternatives based on multiple criteria using TOPSIS + method. + date_publication: '2013-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=topsis + url_git: '' +TopSisWM: + version: 1.0.2 + title: Multi-Criteria Method for Decision (TOPSIS) + maintainer: Wagner Martins dos Santos + description: Assists in the TOPSIS analysis process, designed to return at the end + of the answer of the TOPSIS multicriteria analysis, a ranking table with the + best option as the analysis proposes. TOPSIS is basically a technique developed + by Hwang and Yoon in 1981, starting from the point that the best alternative should + be closest to the positive ideal solution and farthest from the negative one, + based on several criteria to result in the best benefit. (LIU, H. et al., 2019) + . + date_publication: '2022-09-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TopSisWM + url_git: '' +tor: + version: 1.1.3 + title: Import Multiple Files From a Single Directory at Once + maintainer: Mauro Lepore + description: |- + The goal of tor (to-R) is to help you to import multiple + files from a single directory at once, and to do so as quickly, + flexibly, and simply as possible. + date_publication: '2024-07-14' + bug_reports: https://github.com/maurolepore/tor/issues + url: https://maurolepore.github.io/tor/ + url_cran: https://CRAN.R-project.org/package=tor + url_git: https://github.com/maurolepore/tor +torch: + version: 0.14.2 + title: Tensors and Neural Networks with 'GPU' Acceleration + maintainer: Daniel Falbel + description: |- + Provides functionality to define and train neural networks similar to + 'PyTorch' by Paszke et al (2019) but written entirely in R + using the 'libtorch' library. Also supports low-level tensor operations and + 'GPU' acceleration. + date_publication: '2025-02-14' + bug_reports: https://github.com/mlverse/torch/issues + url: https://torch.mlverse.org/docs + url_cran: https://CRAN.R-project.org/package=torch + url_git: https://github.com/mlverse/torch +torchaudio: + version: 0.3.1 + title: R Interface to 'pytorch''s 'torchaudio' + maintainer: Sigrid Keydana + description: |- + Provides access to datasets, models and processing + facilities for deep learning in audio. + date_publication: '2023-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=torchaudio + url_git: '' +torchdatasets: + version: 0.3.1 + title: Ready to Use Extra Datasets for Torch + maintainer: Daniel Falbel + description: |- + Provides datasets in a format that can be easily consumed by torch 'dataloaders'. + Handles data downloading from multiple sources, caching and pre-processing so + users can focus only on their model implementations. + date_publication: '2024-06-20' + bug_reports: https://github.com/mlverse/torchdatasets/issues + url: https://mlverse.github.io/torchdatasets/ + url_cran: https://CRAN.R-project.org/package=torchdatasets + url_git: https://github.com/mlverse/torchdatasets +torchopt: + version: 0.1.4 + title: Advanced Optimizers for Torch + maintainer: Gilberto Camara + description: |- + Optimizers for 'torch' deep learning library. These + functions include recent results published in the literature and are + not part of the optimizers offered in 'torch'. Prospective users + should test these optimizers with their data, since performance + depends on the specific problem being solved. The packages includes + the following optimizers: (a) 'adabelief' by Zhuang et al (2020), + ; (b) 'adabound' by Luo et al.(2019), + ; (c) 'adahessian' by Yao et al.(2021) + ; (d) 'adamw' by Loshchilov & Hutter (2019), + ; (e) 'madgrad' by Defazio and Jelassi (2021), + ; (f) 'nadam' by Dozat (2019), + ; (g) 'qhadam' by + Ma and Yarats(2019), ; (h) 'radam' by Liu et al. + (2019), ; (i) 'swats' by Shekar and Sochee (2018), + ; (j) 'yogi' by Zaheer et al.(2019), + . + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=torchopt + url_git: https://github.com/e-sensing/torchopt/ +torchvision: + version: 0.6.0 + title: Models, Datasets and Transformations for Images + maintainer: Daniel Falbel + description: |- + Provides access to datasets, models and preprocessing + facilities for deep learning with images. Integrates seamlessly + with the 'torch' package and it's 'API' borrows heavily from + 'PyTorch' vision package. + date_publication: '2024-06-14' + bug_reports: https://github.com/mlverse/torchvision/issues + url: https://torchvision.mlverse.org + url_cran: https://CRAN.R-project.org/package=torchvision + url_git: https://github.com/mlverse/torchvision +torchvisionlib: + version: 0.5.0 + title: Additional Operators for Image Models + maintainer: Daniel Falbel + description: |- + Implements additional operators for computer vision models, including + operators necessary for image segmentation and object detection deep learning + models. + date_publication: '2024-02-15' + bug_reports: https://github.com/mlverse/torchvisionlib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=torchvisionlib + url_git: https://github.com/mlverse/torchvisionlib +TORDs: + version: 1.0.0 + title: Third Order Rotatable Designs (TORDs) + maintainer: Ashutosh Dalal + description: 'Third order response surface designs (M. Hemavathi, Shashi Shekhar, + Eldho Varghese, Seema Jaggi, Bikas Sinha & Nripes Kumar Mandal (2022) ."Theoretical + developments in response surface designs: an informative review and further thoughts") + are classified into two types viz., designs which are suitable for sequential + experimentation and designs for non-sequential experimentation (M. Hemavathi, + Eldho Varghese, Shashi Shekhar & Seema Jaggi (2022)." + Sequential asymmetric third order rotatable designs (SATORDs)"). The sequential + experimentation approach involves conducting the trials step by step whereas, + in the non-sequential experimentation approach, the entire runs are executed in + one go.This package contains functions named STORDs() and NSTORDs() for generating + sequential/non-sequential TORDs given in Das, M. N., and V. L. Narasimham (1962). + . "Construction of rotatable designs through balanced + incomplete block designs" along with the randomized layout. It also contains another + function named Pred3.var() for generating the variance of predicted response as + well as the moment matrix based on a third order response surface model.' + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TORDs + url_git: '' +tornado: + version: 0.1.3 + title: Plots for Model Sensitivity and Variable Importance + maintainer: Rob Carnell + description: Draws tornado plots for model sensitivity to univariate changes. Implements + methods for many modeling methods including linear models, generalized linear + models, survival regression models, and arbitrary machine learning models in the + caret package. Also draws variable importance plots. + date_publication: '2024-01-21' + bug_reports: https://github.com/bertcarnell/tornado/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tornado + url_git: https://github.com/bertcarnell/tornado +tosca: + version: 0.3-2 + title: Tools for Statistical Content Analysis + maintainer: Lars Koppers + description: 'A framework for statistical analysis in content analysis. In addition + to a pipeline for preprocessing text corpora and linking to the latent Dirichlet + allocation from the ''lda'' package, plots are offered for the descriptive analysis + of text corpora and topic models. In addition, an implementation of Chang''s intruder + words and intruder topics is provided. Sample data for the vignette is included + in the toscaData package, which is available on gitHub: .' + date_publication: '2021-10-28' + bug_reports: '' + url: https://doi.org/10.5281/zenodo.3591068 + url_cran: https://CRAN.R-project.org/package=tosca + url_git: https://github.com/Docma-TU/tosca +toscmask: + version: 1.2.3 + title: Improved Versions of Base Functions + maintainer: Tobias Schmidt + description: |- + Operators and functions provided by base R sometimes lack some + features found in other programming languages, such as the ability to + concatenate strings using + or to repeat strings using *. This package aims + at providing such functionality without breaking existing code, i.e., only + statements, that would throw errors in pure base R are patched. + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=toscmask + url_git: '' +toscutil: + version: 2.8.0 + title: Utility Functions + maintainer: Tobias Schmidt + description: |- + Base R sometimes requires verbose statements for simple, + often recurring tasks, such as printing text without trailing + space, ending with newline. This package aims at providing + shorthands for such tasks. + date_publication: '2024-06-28' + bug_reports: '' + url: https://toscm.github.io/toscutil/ + url_cran: https://CRAN.R-project.org/package=toscutil + url_git: https://github.com/toscm/toscutil/ +TOSI: + version: 0.3.0 + title: |- + Two-Directional Simultaneous Inference for High-Dimensional + Models + maintainer: Wei Liu + description: |- + A general framework of two directional simultaneous inference + is provided for high-dimensional as well as the fixed dimensional models with manifest + variable or latent variable structure, such as high-dimensional mean models, high- + dimensional sparse regression models, and high-dimensional latent factors models. + It is making the simultaneous inference on a set of parameters from two directions, + one is testing whether the estimated zero parameters indeed are zero and the other is + testing whether there exists zero in the parameter set of non-zero. More details can be + referred to Wei Liu, et al. (2022) . + date_publication: '2023-01-26' + bug_reports: https://github.com/feiyoung/TOSI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TOSI + url_git: https://github.com/feiyoung/TOSI +tosr: + version: 0.1.5 + title: Create the Tree of Science from WoS and Scopus + maintainer: Sebastian Robledo + description: |- + The goal of 'tosr' is to create the Tree of Science from + Web of Science (WoS) and Scopus data. It can read files + from both sources at the same time. More information + can be found in Valencia-Hernández (2020) + . + date_publication: '2025-01-29' + bug_reports: https://github.com/coreofscience/tosr/issues + url: https://coreofscience.github.io/tosr/ + url_cran: https://CRAN.R-project.org/package=tosr + url_git: https://github.com/coreofscience/tosr +TOSTER: + version: 0.8.4 + title: Two One-Sided Tests (TOST) Equivalence Testing + maintainer: Aaron Caldwell + description: 'Two one-sided tests (TOST) procedure to test equivalence for t-tests, + correlations, differences between proportions, and meta-analyses, including power + analysis for t-tests and correlations. Allows you to specify equivalence bounds + in raw scale units or in terms of effect sizes. See: Lakens (2017) .' + date_publication: '2025-02-06' + bug_reports: '' + url: https://aaroncaldwell.us/TOSTERpkg/ + url_cran: https://CRAN.R-project.org/package=TOSTER + url_git: '' +totalcensus: + version: 0.6.6 + title: Extract Decennial Census and American Community Survey Data + maintainer: Guanglai Li + description: |- + Download summary files from Census Bureau + and extract data, in particular high resolution data at + block, block group, and tract level, from decennial census and + American Community Survey 1-year and 5-year estimates. + date_publication: '2021-06-14' + bug_reports: https://github.com/GL-Li/totalcensus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=totalcensus + url_git: https://github.com/GL-Li/totalcensus +TotalCopheneticIndex: + version: 2.0.1 + title: Quantify the Balance of Phylogenetic Trees + maintainer: Martin R. Smith + description: |- + Measures the degree of balance for a given phylogenetic tree by + calculating the Total Cophenetic Index. + Reference: A. Mir, F. Rossello, L. A. Rotger (2013). + A new balance index for phylogenetic trees. + Math. Biosci. 241, 125-136 . + date_publication: '2021-06-23' + bug_reports: https://github.com/ms609/TreeTools/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=TotalCopheneticIndex + url_git: https://github.com/ms609/tci/ +TOU: + version: 0.1.0 + title: Transformed Ornstein-Uhlenbeck Model for Adsorption Kinetics + maintainer: Rogelio Salinas-Gutiérrez + description: Estimates the parameters of a Transformed Ornstein-Uhlenbeck (TOU) + stochastic model for adsorption data and also the parameters of the related pseudo-n-order + (PNO) model, such as the maximum adsorption capacity (qe), the adsorption rate + constant (kn) and the order of the model (n). + date_publication: '2022-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TOU + url_git: '' +touch: + version: 0.1-6 + title: Tools of Utilization and Cost in Healthcare + maintainer: Wenjie Wang + description: |- + R implementation of the software tools developed in the H-CUP + (Healthcare Cost and Utilization Project) + and AHRQ (Agency for Healthcare Research and Quality) + . It currently contains functions for mapping ICD-9 + codes to the AHRQ comorbidity measures and translating ICD-9 + (resp. ICD-10) codes to ICD-10 (resp. ICD-9) codes based on GEM (General + Equivalence Mappings) from CMS (Centers for Medicare and Medicaid + Services). + date_publication: '2022-07-08' + bug_reports: https://github.com/wenjie2wang/touch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=touch + url_git: https://github.com/wenjie2wang/touch +touRnamentofchampions: + version: 0.1.0 + title: Tournament of Champions Data + maintainer: Levitz Carly + description: |- + Several datasets which describe the challenges and results of + competitions in Tournament of Champions. This data is useful for + practicing data wrangling, graphing, and analyzing how each season of + Tournament of Champions played out. + date_publication: '2024-05-28' + bug_reports: https://github.com/celevitz/touRnamentofchampions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=touRnamentofchampions + url_git: https://github.com/celevitz/touRnamentofchampions +tourr: + version: 1.2.4 + title: Tour Methods for Multivariate Data Visualisation + maintainer: Dianne Cook + description: |- + Implements geodesic interpolation and basis + generation functions that allow you to create new tour + methods from R. + date_publication: '2025-02-13' + bug_reports: https://github.com/ggobi/tourr/issues + url: https://ggobi.github.io/tourr/ + url_cran: https://CRAN.R-project.org/package=tourr + url_git: https://github.com/ggobi/tourr +tower: + version: 0.2.0 + title: Easy Middle Ware Library for 'shiny' + maintainer: Andres Quintero + description: |- + The best way to implement middle ware for 'shiny' Applications. 'tower' + is designed to make implementing behavior on top of 'shiny' easy with a layering + model for incoming HTTP requests and server sessions. 'tower' is a very minimal + package with little overhead, it is mainly meant for other package developers + to implement new behavior. + date_publication: '2024-10-21' + bug_reports: https://github.com/ixpantia/tower/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tower + url_git: https://github.com/ixpantia/tower +toweranNA: + version: 0.1.0 + title: A Method for Handling Missing Values in Prediction Applications + maintainer: Norm Matloff + description: |- + Non-imputational method for handling missing values in + a prediction context, meaning that not only are there missing + values in the training dataset, but also some values may be missing + in future cases to be predicted. Based on the notion of regression + averaging (Matloff (2017, ISBN: 9781498710916)). + date_publication: '2023-03-15' + bug_reports: https://github.com/matloff/toweranNA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=toweranNA + url_git: https://github.com/matloff/toweranNA +ToxCrit: + version: '1.0' + title: |- + Calculates Safety Stopping Boundaries for a Single-Arm Trial + using Bayes + maintainer: Lisa-Marie Lanz + description: |- + Computation of stopping boundaries for a single-arm trial using a + Bayesian criterion; i.e., for each m<=n (n= total patient number of the + trial) the smallest number of observed toxicities is calculated + leading to the termination of the trial/accrual according to the specified + criteria. The probabilities of stopping the trial/accrual at and up until + (resp.) the m-th patient (m<=n) is also calculated. This design is more + conservative than the frequentist approach (using Clopper Pearson CIs) + which might be preferred as it concerns safety.See also Aamot et.al.(2010) + "Continuous monitoring of toxicity in clinical trials - simulating the risk + of stopping prematurely" . + date_publication: '2021-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ToxCrit + url_git: '' +toxEval: + version: 1.4.0 + title: |- + Exploring Biological Relevance of Environmental Chemistry + Observations + maintainer: Laura DeCicco + description: Data analysis package for estimating potential biological effects from + chemical concentrations in environmental samples. Included are a set of functions + to analyze, visualize, and organize measured concentration data as it relates + to user-selected chemical-biological interaction benchmark data such as water + quality criteria. The intent of these analyses is to develop a better understanding + of the potential biological relevance of environmental chemistry data. Results + can be used to prioritize which chemicals at which sites may be of greatest concern. + These methods are meant to be used as a screening technique to predict potential + for biological influence from chemicals that ultimately need to be validated with + direct biological assays. A description of the analysis can be found in Blackwell + (2017) . + date_publication: '2024-11-22' + bug_reports: https://github.com/DOI-USGS/toxEval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=toxEval + url_git: '' +toxpiR: + version: 1.3.0 + title: Create ToxPi Prioritization Models + maintainer: Jonathon F Fleming + description: |- + Enables users to build 'ToxPi' prioritization models and provides + functionality within the grid framework for plotting ToxPi graphs. + 'toxpiR' allows for more customization than the 'ToxPi GUI' + () and integration into existing workflows for greater + ease-of-use, reproducibility, and transparency. + toxpiR package behaves nearly identically to the GUI; the package + documentation includes notes about all differences. + The vignettes download example files from + . + date_publication: '2024-09-12' + bug_reports: https://github.com/ToxPi/toxpiR/issues + url: https://toxpi.github.io/toxpiR/ + url_cran: https://CRAN.R-project.org/package=toxpiR + url_git: https://github.com/ToxPi/toxpiR +toxSummary: + version: 1.0.0 + title: Visualize and Summarize Repeat-Dose Toxicology Study Results + maintainer: Yousuf Ali + description: |- + A 'shiny' app that generates plots and summary tables from repeat-dose + toxicology study results to facilitate holistic evaluation of the drug safety of + active pharmaceutical ingredients (API) prior to initiation of clinical trials. + date_publication: '2024-02-27' + bug_reports: https://github.com/phuse-org/toxSummary/issues + url: '' + url_cran: https://CRAN.R-project.org/package=toxSummary + url_git: https://github.com/phuse-org/toxSummary +TP.idm: + version: 1.5.1 + title: |- + Estimation of Transition Probabilities for the Illness-Death + Model + maintainer: Vanesa Balboa-Barreiro + description: Estimation of transition probabilities for the illness-death model. + Both the Aalen-Johansen estimator for a Markov model and a novel non-Markovian + estimator by de Una-Alvarez and Meira-Machado (2015) , + see also Balboa and de Una-Alvarez (2018) , are included. + date_publication: '2023-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TP.idm + url_git: '' +TPAC: + version: 0.2.0 + title: Tissue-Adjusted Pathway Analysis of Cancer (TPAC) + maintainer: H. Robert Frost + description: |- + Contains logic for single sample gene set testing of cancer transcriptomic data with adjustment for normal tissue-specificity. + Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" . + date_publication: '2023-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPAC + url_git: '' +TPACData: + version: 0.1.0 + title: |- + Human Protein Atlas Data for Tissue-Adjusted Pathway Analysis of + Cancer (TPAC) + maintainer: H. Robert Frost + description: |- + Contains summary data on gene expression in normal human tissues from the Human Protein Atlas for use with the + Tissue-Adjusted Pathway Analysis of cancer (TPAC) method. + Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" . + date_publication: '2023-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPACData + url_git: '' +tpAUC: + version: 2.1.1 + title: Estimation and Inference of Two-Way pAUC, pAUC and pODC + maintainer: Xiang Lyu + description: Tools for estimating and inferring two-way partial area under receiver + operating characteristic curves (two-way pAUC), partial area under receiver operating + characteristic curves (pAUC), and partial area under ordinal dominance curves + (pODC). Methods includes Mann-Whitney statistic and Jackknife, etc. + date_publication: '2017-04-09' + bug_reports: '' + url: http://arxiv.org/abs/1508.00298http://www3.stat.sinica.edu.tw/statistica/j27n1/j27n117/j27n117.htmlhttp://www.ncbi.nlm.nih.gov/pubmed/20729218 + url_cran: https://CRAN.R-project.org/package=tpAUC + url_git: '' +tpc: + version: '1.0' + title: Tiered PC Algorithm + maintainer: Ronja Foraita + description: |- + Constraint-based causal discovery using the PC algorithm while + accounting for a partial node ordering, for example a partial temporal ordering + when the data were collected in different waves of a cohort study. + Andrews RM, Foraita R, Didelez V, Witte J (2021) + provide a guide how to use tpc to analyse cohort data. + date_publication: '2023-02-20' + bug_reports: https://github.com/bips-hb/tpc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tpc + url_git: https://github.com/bips-hb/tpc +TPCselect: + version: 0.8.3 + title: Variable Selection via Threshold Partial Correlation + maintainer: Cynthia Shao + description: |- + A threshold partial correlation approach to selecting + important variables in linear models of L. and others (2017) at + , and in partial linear models + of L. and others (2018) at . + This package also extends the PC-simple algorithm of + B. and others (2010) at to + partial linear models. + date_publication: '2023-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPCselect + url_git: '' +TPD: + version: 1.1.0 + title: |- + Methods for Measuring Functional Diversity Based on Trait + Probability Density + maintainer: Carlos P. Carmona + description: |- + Tools to calculate trait probability density functions (TPD) at + any scale (e.g. populations, species, communities). TPD functions are used to compute + several indices of functional diversity, as well as its partition across scales. + These indices constitute a unified framework that incorporates the underlying + probabilistic nature of trait distributions into uni- or multidimensional + functional trait-based studies. See Carmona et al. (2016) for + further information. + date_publication: '2019-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPD + url_git: '' +TPEA: + version: 3.1.0 + title: A Novel Topology-Based Pathway Enrichment Analysis Approach + maintainer: Wei Jiang + description: |- + We described a novel Topology-based pathway enrichment analysis, which integrated the global position of the nodes and the topological property of the pathways in Kyoto Encyclopedia of Genes and Genomes Database. + We also provide some functions to obtain the latest information about pathways to finish pathway enrichment analysis using this method. + date_publication: '2017-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPEA + url_git: '' +TPES: + version: 1.0.0 + title: Tumor Purity Estimation using SNVs + maintainer: Alessio Locallo + description: |- + A bioinformatics tool for the estimation of the tumor purity from sequencing data. + It uses the set of putative clonal somatic single nucleotide variants within copy number neutral + segments to call tumor cellularity. + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPES + url_git: '' +tpfp: + version: 0.0.1 + title: Counts the Number of True Positives and False Positives + maintainer: Issei Tsunoda + description: Calculates the number of true positives and false positives from a + dataset formatted for Jackknife alternative free-response receiver operating characteristic + which is used for statistical analysis which is explained in the book 'Chakraborty' + 'DP' (2017), "Observer Performance Methods for Diagnostic Imaging - Foundations, + Modeling, and Applications with R-Based Examples", Taylor-Francis . + date_publication: '2021-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tpfp + url_git: '' +TPLSr: + version: 1.0.4 + title: Thresholded Partial Least Squares Model for Neuroimaging Data + maintainer: Sangil Lee + description: Uses thresholded partial least squares algorithm to create a regression + or classification model. For more information, see Lee, Bradlow, and Kable . + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TPLSr + url_git: '' +Tplyr: + version: 1.2.1 + title: A Traceability Focused Grammar of Clinical Data Summary + maintainer: Mike Stackhouse + description: A traceability focused tool created to simplify the data manipulation + necessary to create clinical summaries. + date_publication: '2024-02-20' + bug_reports: https://github.com/atorus-research/Tplyr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Tplyr + url_git: https://github.com/atorus-research/Tplyr +tpm: + version: 2.0.2 + title: FHWA TPM Score Calculation Functions + maintainer: Mark Egge + description: Contains functions for calculating the Federal Highway Administration + (FHWA) Transportation Performance Management (TPM) performance measures. Currently, + the package provides methods for the System Reliability and Freight (PM3) performance + measures calculated from travel time data provided by The National Performance + Management Research Data Set (NPMRDS), including Level of Travel Time Reliability + (LOTTR), Truck Travel Time Reliability (TTTR), and Peak Hour Excessive Delay (PHED) + metric scores for calculating statewide reliability performance measures. Implements + . + date_publication: '2024-06-01' + bug_reports: https://github.com/markegge/fhwa_pm3/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tpm + url_git: https://github.com/markegge/fhwa_pm3/ +TPMplt: + version: 0.1.6 + title: Tool-Kit for Dynamic Materials Model and Thermal Processing Maps + maintainer: Chen Zhang + description: |- + Provides a simple approach for constructing dynamic materials + modeling suggested by Prasad and Gegel (1984) . It + can easily generate various processing-maps based on this model as well. The + calculation result in this package contains full materials constants, information + about power dissipation efficiency factor, and rheological properties, can + be exported completely also, through which further analysis and customized + plots will be applicable as well. + date_publication: '2024-10-01' + bug_reports: https://github.com/CubicZebra/TPMplt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TPMplt + url_git: https://github.com/CubicZebra/TPMplt +TPmsm: + version: 1.2.12 + title: Estimation of Transition Probabilities in Multistate Models + maintainer: Artur Araujo + description: |- + Estimation of transition probabilities for the + illness-death model and or the three-state progressive model. + date_publication: '2023-12-07' + bug_reports: https://github.com/arturstat/TPmsm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TPmsm + url_git: https://github.com/arturstat/TPmsm +tpn: + version: '1.9' + title: Truncated Positive Normal Model and Extensions + maintainer: Diego Gallardo + description: |- + Provide data generation and estimation tools for the truncated positive normal (tpn) + model discussed in Gomez, Olmos, Varela and Bolfarine (2018) + , the slash tpn distribution discussed in Gomez, + Gallardo and Santoro (2021) , the bimodal tpn distribution + discussed in Gomez et al. (2022) and the flexible tpn model. + date_publication: '2024-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tpn + url_git: '' +tpr: + version: 0.3-3 + title: Temporal Process Regression + maintainer: Jun Yan + description: |- + Regression models for temporal process responses with + time-varying coefficient. + date_publication: '2022-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tpr + url_git: '' +tpwb: + version: 0.1.0 + title: The Three Parameter Weibull Distribution + maintainer: Atchanut Rattanalertnusorn + description: |- + Density, distribution function, the quantile function, + random generation function, and maximum likelihood estimation. + date_publication: '2024-05-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tpwb + url_git: '' +tqk: + version: 0.1.8 + title: Get Financial Data in Korea + maintainer: Chanyub Park + description: |- + Enables the acquisition of Korean financial market data, + designed to integrate seamlessly with the 'tidyquant' package. + date_publication: '2023-08-29' + bug_reports: https://github.com/mrchypark/tqk/issues + url: https://mrchypark.github.io/tqk/ + url_cran: https://CRAN.R-project.org/package=tqk + url_git: https://github.com/mrchypark/tqk +tr.iatgen: + version: 1.1.0 + title: Translate 'iatgen' Generated QSF Files + maintainer: Michal Kouril + description: |- + Automates translating the instructions of 'iatgen' generated qsf + (Qualtrics survey files) to other languages using either officially + supported or user-supplied translations (for tutorial see Santos + et al., 2023 ). + date_publication: '2024-10-25' + bug_reports: https://github.com/iatgen/tr.iatgen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tr.iatgen + url_git: https://github.com/iatgen/tr.iatgen +TR8: + version: 0.9.23 + title: A Tool for Downloading Functional Traits Data for Plant Species + maintainer: Gionata Bocci + description: |- + Plant ecologists often need to collect "traits" data + about plant species which are often scattered among various + databases: TR8 contains a set of tools which take care of + automatically retrieving some of those functional traits data + for plant species from publicly available databases (The Ecological Flora + of the British Isles, LEDA traitbase, Ellenberg + values for Italian Flora, Mycorrhizal intensity databases, BROT, + PLANTS, Jepson Flora Project). + The TR8 name, inspired by "car plates" jokes, was chosen since + it both reminds of the main object of the package and is + extremely short to type. + date_publication: '2024-09-22' + bug_reports: https://github.com/GioBo/TR8/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TR8 + url_git: https://github.com/GioBo/TR8 +trace: + version: 0.5.0 + title: Tandem Repeat Analysis by Capillary Electrophoresis + maintainer: Zachariah McLean + description: A pipeline for short tandem repeat instability analysis from fragment + analysis data. Inputs of fsa files or peak tables, and a user supplied metadata + data-frame. The package identifies ladders, calls peaks, identifies the modal + peaks, calls repeats, then calculates repeat instability metrics (e.g. expansion + index from Lee et al. (2010) ). + date_publication: '2025-01-16' + bug_reports: '' + url: https://zachariahmclean.github.io/trace/ + url_cran: https://CRAN.R-project.org/package=trace + url_git: '' +TraceAssist: + version: 0.1.0 + title: Nonparametric Trace Regression via Sign Series Representation + maintainer: Chanwoo Lee + description: Efficient method for fitting nonparametric matrix trace regression + model. The detailed description can be found in C. Lee, L. Li, H. Zhang, and + M. Wang (2021). Nonparametric Trace Regression via Sign Series Representation. + . The method employs the aggregation of structured sign series + for trace regression (ASSIST) algorithm. + date_publication: '2021-05-10' + bug_reports: '' + url: https://arxiv.org/abs/2105.01783 + url_cran: https://CRAN.R-project.org/package=TraceAssist + url_git: '' +tracee: + version: 0.0.4 + title: Easily Save Output and Trace it Back to Code + maintainer: Philip Delff + description: Write output (plots and tables) ensuring traceability back to code. + Includes a graphics saver with simple automation of stamping with source, destination + and creation time. A list of plots can be saved at once. A user-friendly selection + of output dimensions for presentations, on-screen inspections, and more available. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tracee + url_git: '' +tracenma: + version: 0.1.1 + title: |- + Database for Developing Transitivity Methodology in Network + Meta-Analysis + maintainer: Loukia Spineli + description: |- + Functions to access the database of 217 data-frames with aggregate + study-level characteristics (that may act as effect modifiers) extracted + from published systematic reviews with network meta-analysis. The database shall + only be used for developing and appraising the methodology to assess + the transitivity assumption quantitatively. + date_publication: '2025-01-25' + bug_reports: https://github.com/LoukiaSpin/tracenma/issues + url: https://loukiaspin.github.io/tracenma/ + url_cran: https://CRAN.R-project.org/package=tracenma + url_git: https://github.com/LoukiaSpin/tracenma +tracer: + version: 1.0.0 + title: Slick Call Stacks + maintainer: Gabor Csardi + description: Better looking call stacks after an error. + date_publication: '2017-01-28' + bug_reports: https://github.com/mangothecat/tracer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tracer + url_git: https://github.com/mangothecat/tracer#readme +tracerer: + version: 2.2.3 + title: Tracer from R + maintainer: Richèl J.C. Bilderbeek + description: |- + 'BEAST2' () is a widely used + Bayesian phylogenetic tool, that uses DNA/RNA/protein data + and many model priors to create a posterior of jointly estimated + phylogenies and parameters. + 'Tracer' () is a GUI tool + to parse and analyze the files generated by 'BEAST2'. + This package provides a way to parse and analyze 'BEAST2' input + files without active user input, but using + R function calls instead. + date_publication: '2023-09-27' + bug_reports: https://github.com/ropensci/tracerer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tracerer + url_git: https://docs.ropensci.org/tracerer/(website)https://github.com/ropensci/tracerer/ +tracheideR: + version: 0.1.1 + title: Standardize Tracheidograms + maintainer: Filipe Campelo + description: |- + Contains functions to standardize tracheid profiles + using the traditional method (Vaganov) and a new method to standardize + tracheidograms based on the relative position of tracheids within tree rings. + date_publication: '2015-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tracheideR + url_git: '' +track2KBA: + version: 1.1.2 + title: Identifying Important Areas from Animal Tracking Data + maintainer: Martin Beal + description: |- + Functions for preparing and analyzing animal tracking data, + with the intention of identifying areas which are potentially important at + the population level and therefore of conservation interest. Areas identified + using this package may be checked against global or regionally-defined criteria, + such as those set by the Key Biodiversity Area program. The method + published herein is described in full in Beal et al. 2021 . + date_publication: '2024-07-01' + bug_reports: https://github.com/BirdLifeInternational/track2kba/issues + url: '' + url_cran: https://CRAN.R-project.org/package=track2KBA + url_git: https://github.com/BirdLifeInternational/track2kba +trackdem: + version: 0.7.2 + title: Particle Tracking and Demography + maintainer: Marjolein Bruijning + description: Obtain population density and body size structure, using video material + or image sequences as input. Functions assist in the creation of image sequences + from videos, background detection and subtraction, particle identification and + tracking. An artificial neural network can be trained for noise filtering. The + goal is to supply accurate estimates of population size, structure and/or individual + behavior, for use in evolutionary and ecological studies. + date_publication: '2024-05-08' + bug_reports: https://github.com/marjoleinbruijning/trackdem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trackdem + url_git: https://github.com/marjoleinbruijning/trackdem +trackdf: + version: 0.3.3 + title: Data Frame Class for Tracking Data + maintainer: Simon Garnier + description: |- + Data frame class for storing collective movement data (e.g. fish + schools, ungulate herds, baboon troops) collected from GPS trackers or + computer vision tracking software. + date_publication: '2024-01-29' + bug_reports: https://github.com/swarm-lab/trackdf/issues + url: https://swarm-lab.github.io/trackdf/ + url_cran: https://CRAN.R-project.org/package=trackdf + url_git: https://github.com/swarm-lab/trackdf +trackdown: + version: 1.1.1 + title: Collaborative Editing of Rmd (or Rnw) Documents in Google Drive + maintainer: Claudio Zandonella Callegher + description: Collaborative writing and editing of R Markdown (or Sweave) documents. + The local .Rmd (or .Rnw) is uploaded as a plain-text file to Google Drive. By + taking advantage of the easily readable Markdown (or LaTeX) syntax and the well-known + online interface offered by Google Docs, collaborators can easily contribute to + the writing and editing process. After integrating all authors’ contributions, + the final document can be downloaded and rendered locally. + date_publication: '2021-12-19' + bug_reports: https://github.com/claudiozandonella/trackdown/issues + url: https://claudiozandonella.github.io/trackdown/ + url_cran: https://CRAN.R-project.org/package=trackdown + url_git: https://github.com/claudiozandonella/trackdown/ +trackeR: + version: 1.6.0 + title: |- + Infrastructure for Running, Cycling and Swimming Data from + GPS-Enabled Tracking Devices + maintainer: Ioannis Kosmidis + description: 'Provides infrastructure for handling running, cycling and swimming + data from GPS-enabled tracking devices within R. The package provides methods + to extract, clean and organise workout and competition data into session-based + and unit-aware data objects of class ''trackeRdata'' (S3 class). The information + can then be visualised, summarised, and analysed through flexible and extensible + methods. Frick and Kosmidis (2017) , which is updated + and maintained as one of the vignettes, provides detailed descriptions of the + package and its methods, and real-data demonstrations of the package functionality.' + date_publication: '2024-01-11' + bug_reports: https://github.com/trackerproject/trackeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trackeR + url_git: https://github.com/trackerproject/trackeR +trackeRapp: + version: '1.2' + title: |- + Interface for the Analysis of Running, Cycling and Swimming Data + from GPS-Enabled Tracking Devices + maintainer: Ioannis Kosmidis + description: |- + Provides an integrated user interface and workflow for + the analysis of running, cycling and swimming data from GPS-enabled + tracking devices through the 'trackeR' R package. + date_publication: '2022-02-15' + bug_reports: https://github.com/trackerproject/trackeRapp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trackeRapp + url_git: https://github.com/trackerproject/trackeRapp +TrackReconstruction: + version: '1.3' + title: |- + Reconstruct Animal Tracks from Magnetometer, Accelerometer, + Depth and Optional Speed Data + maintainer: Brian Battaile + description: Reconstructs animal tracks from magnetometer, accelerometer, depth + and optional speed data. Designed primarily using data from Wildlife Computers + Daily Diary tags deployed on northern fur seals. + date_publication: '2021-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrackReconstruction + url_git: '' +tractor.base: + version: 3.4.2 + title: Read, Manipulate and Visualise Magnetic Resonance Images + maintainer: Jon Clayden + description: |- + Functions for working with magnetic resonance images. Reading and + writing of popular file formats (DICOM, Analyze, NIfTI-1, NIfTI-2, MGH); + interactive and non-interactive visualisation; flexible image manipulation; + metadata and sparse image handling. + date_publication: '2024-02-27' + bug_reports: https://github.com/tractor/tractor/issues + url: https://www.tractor-mri.org.uk + url_cran: https://CRAN.R-project.org/package=tractor.base + url_git: https://github.com/tractor/tractor +trade: + version: 0.8.1 + title: Tools for Trade Practitioners + maintainer: Charles Taragin + description: A collection of tools for trade practitioners, including the ability + to calibrate different consumer demand systems and simulate the effects of tariffs + and quotas under different competitive regimes. These tools are derived from Anderson + et al. (2001) and Froeb et al. (2003) . + date_publication: '2022-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trade + url_git: https://github.com/luciu5/trade +tradepolicy: + version: 0.7.0 + title: Replication of 'An Advanced Guide To Trade Policy Analysis' + maintainer: Mauricio Vargas Sepulveda + description: |- + Datasets from Yotov, et al. (2016, ISBN:978-92-870-4367-2) "An + Advanced Guide to Trade Policy Analysis" and functions to report regression + summaries with clustered robust standard errors. + date_publication: '2024-03-23' + bug_reports: https://github.com/pachadotdev/tradepolicy/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=tradepolicy + url_git: https://github.com/pachadotdev/tradepolicy/ +TRADER: + version: 1.2-6 + title: Tree Ring Analysis of Disturbance Events in R + maintainer: Pavel Fibich + description: Tree Ring Analysis of Disturbance Events in R (TRADER) package provides + functions for disturbance reconstruction from tree-ring data, e.g. boundary line, + absolute increase, growth averaging methods. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TRADER + url_git: https://github.com/pavel-fibich/TRADER +tradestatistics: + version: 5.0.0 + title: Open Trade Statistics API Wrapper and Utility Program + maintainer: Mauricio Vargas + description: |- + Access 'Open Trade Statistics' API from R to download + international trade data. + date_publication: '2024-08-23' + bug_reports: https://github.com/ropensci/tradestatistics/issues/ + url: https://docs.ropensci.org/tradestatistics/ + url_cran: https://CRAN.R-project.org/package=tradestatistics + url_git: '' +Trading: + version: '3.1' + title: |- + Trade Objects, Advanced Correlation & Beta Estimates, Betting + Strategies + maintainer: Tasos Grivas + description: |- + Contains performance analysis metrics of track records including entropy-based + correlation and dynamic beta based on a state/space algorithm. The normalized sample entropy method + has been implemented which produces accurate entropy estimation even on smaller datasets. + On a separate stream, trades from the five major assets classes and also + functionality to use pricing curves, rating tables, Credit Support Annex and add-on tables. The + implementation follows an object oriented logic whereby each trade inherits from + more abstract classes while also the curves/tables are objects. Furthermore, odds calculators + and P&L back-testing functionality has been implemented for the most widely used betting/trading + strategies including martingale, 'DAlembert', 'Labouchere' and Fibonacci. Back testing has also been included for the 'EuroMillions', + the 'EuroJackpot', the UK Lotto, the Set For Life and the UK 'ThunderBall' lotteries. + Furthermore, some basic functionality about climate risk has been included. + date_publication: '2025-02-22' + bug_reports: '' + url: https://openriskcalculator.com/ + url_cran: https://CRAN.R-project.org/package=Trading + url_git: '' +TrafficBDE: + version: 0.1.2 + title: Traffic Predictions Using Neural Networks + maintainer: Kleanthis Koupidis + description: Estimate and return either the traffic speed or the car entries in + the city of Thessaloniki using historical traffic data. It's used in transport + pilot of the 'BigDataEurope' project. There are functions for processing these + data, training a neural network, select the most appropriate model and predict + the traffic speed or the car entries for a selected time date. + date_publication: '2023-03-17' + bug_reports: https://github.com/okgreece/TrafficBDE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TrafficBDE + url_git: https://github.com/okgreece/TrafficBDE +trafo: + version: 1.0.1 + title: Estimation, Comparison and Selection of Transformations + maintainer: Ann-Kristin Kreutzmann + description: |- + Estimation, selection and comparison of several families of + transformations. The families of transformations included in the package are + the following: Bickel-Doksum (Bickel and Doksum 1981 ), + Box-Cox, Dual (Yang 2006 ), + Glog (Durbin et al. 2002 ), + gpower (Kelmansky et al. 2013 ), + Log, Log-shift opt (Feng et al. 2016 ), + Manly, modulus (John and Draper 1980 ), + Neglog (Whittaker et al. 2005 ), + Reciprocal and Yeo-Johnson. The package simplifies to + compare linear models with untransformed and transformed dependent variable + as well as linear models where the dependent variable is transformed with + different transformations. Furthermore, the package employs maximum likelihood + approaches, moments optimization and divergence minimization to estimate the optimal + transformation parameter. + date_publication: '2018-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trafo + url_git: '' +traineR: + version: 2.2.0 + title: Predictive (Classification and Regression) Models Homologator + maintainer: Oldemar Rodriguez R. + description: |- + Methods to unify the different ways of creating predictive models and their different predictive formats for classification and regression. It includes + methods such as K-Nearest Neighbors Schliep, K. P. (2004) , Decision Trees Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone (2017) , + ADA Boosting Esteban Alfaro, Matias Gamez, Noelia García (2013) , Extreme Gradient Boosting Chen & Guestrin (2016) , + Random Forest Breiman (2001) , Neural Networks Venables, W. N., & Ripley, B. D. (2002) , + Support Vector Machines Bennett, K. P. & Campbell, C. (2000) , Bayesian Methods Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (1995) , + Linear Discriminant Analysis Venables, W. N., & Ripley, B. D. (2002) , Quadratic Discriminant Analysis Venables, W. N., & Ripley, B. D. (2002) , + Logistic Regression Dobson, A. J., & Barnett, A. G. (2018) and Penalized Logistic Regression Friedman, J. H., Hastie, T., & Tibshirani, R. (2010) . + date_publication: '2023-11-09' + bug_reports: https://github.com/PROMiDAT/traineR/issues + url: https://promidat.website/ + url_cran: https://CRAN.R-project.org/package=traineR + url_git: https://github.com/PROMiDAT/traineR +trainR: + version: 0.0.1 + title: An Interface to the National Rail Enquiries Systems + maintainer: Roberto Villegas-Diaz + description: |- + The goal of 'trainR' is to provide a simple interface to the + National Rail Enquiries (NRE) systems. There are few data feeds + available, the simplest of them is Darwin, which provides real-time + arrival and departure predictions, platform numbers, delay estimates, + schedule changes and cancellations. Other data feeds provide historical + data, Historic Service Performance (HSP), and much more. 'trainR' + simplifies the data retrieval, so that the users can focus on their + analyses. For more details visit + . + date_publication: '2021-01-20' + bug_reports: https://github.com/villegar/trainR/issues/ + url: https://villegar.github.io/trainR/ + url_cran: https://CRAN.R-project.org/package=trainR + url_git: https://github.com/villegar/trainR/ +trainsplit: + version: '1.2' + title: |- + Split a Dataframe, Tibble, or Data.table into Training and Test + Sets + maintainer: Zhaochen He + description: Split a dataframe, tibble, or data.table into training and test sets. + Return either a list, an index, or directly assign training and test sets into + memory. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trainsplit + url_git: https://github.com/eastnile/trainsplit +traipse: + version: 0.3.0 + title: Shared Tools for Tracking Data + maintainer: Michael Sumner + description: |- + A collection of commonly used tools for animal movement and other tracking + data. Variously distance, angle, bearing, distance-to, bearing-to and speed are + provided for geographic data that can be used directly or within 'tidyverse' + syntax. Distances and bearings are calculated using modern geodesic methods as + provided by Charles F. F. Karney (2013) + via the 'geodist' and 'geosphere' packages. + date_publication: '2022-10-10' + bug_reports: https://github.com/Trackage/traipse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=traipse + url_git: https://github.com/Trackage/traipse +traitstrap: + version: 0.1.0 + title: Bootstrap Trait Values to Calculate Moments + maintainer: Richard J. Telford + description: |- + Calculates trait moments from trait and community data using the + methods developed in Maitner et al (2021) . + date_publication: '2023-05-12' + bug_reports: https://github.com/Plant-Functional-Trait-Course/traitstrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=traitstrap + url_git: https://github.com/Plant-Functional-Trait-Course/traitstrap/ +traj: + version: 2.2.1 + title: Clustering of Functional Data Based on Measures of Change + maintainer: Laurence Boulanger + description: Implements a three-step procedure in the spirit of Leffondre et al. + (2004) to identify clusters of individual longitudinal trajectories. The procedure + involves (1) computing a number of "measures of change" capturing various features + of the trajectories; (2) using a Principal Component Analysis based dimension + reduction algorithm to select a subset of measures and (3) using the k-medoids + or k-means algorithm to identify clusters of trajectories. + date_publication: '2025-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=traj + url_git: '' +trajectories: + version: 0.2-9 + title: Classes and Methods for Trajectory Data + maintainer: Edzer Pebesma + description: Classes and methods for trajectory data, with support for nesting individual + Track objects in track sets (Tracks) and track sets for different entities in + collections of Tracks. Methods include selection, generalization, aggregation, + intersection, simulation, and plotting. + date_publication: '2024-09-04' + bug_reports: https://github.com/edzer/trajectories/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trajectories + url_git: https://github.com/edzer/trajectories +trajmsm: + version: 0.1.3 + title: |- + Marginal Structural Models with Latent Class Growth Analysis of + Treatment Trajectories + maintainer: Awa Diop + description: Implements marginal structural models combined with a latent class + growth analysis framework for assessing the causal effect of treatment trajectories. + Based on the approach described in "Marginal Structural Models with Latent Class + Growth Analysis of Treatment Trajectories" Diop, A., Sirois, C., Guertin, J.R., + Schnitzer, M.E., Candas, B., Cossette, B., Poirier, P., Brophy, J., Mésidor, M., + Blais, C. and Hamel, D., (2023) . + date_publication: '2024-10-05' + bug_reports: https://github.com/awamaeva/R-package-trajmsm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trajmsm + url_git: https://github.com/awamaeva/R-package-trajmsm +trajr: + version: 1.5.1 + title: Animal Trajectory Analysis + maintainer: Jim McLean + description: |- + A toolbox to assist with statistical analysis of animal trajectories. + It provides simple access to algorithms for calculating and assessing a variety of + characteristics such as speed and acceleration, as well as multiple measures of + straightness or tortuosity. Some support is provided for 3-dimensional trajectories. + McLean & Skowron Volponi (2018) . + date_publication: '2023-11-29' + bug_reports: https://github.com/JimMcL/trajr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trajr + url_git: https://github.com/JimMcL/trajr +tram: + version: 1.2-1 + title: Transformation Models + maintainer: Torsten Hothorn + description: |- + Formula-based user-interfaces to specific transformation models + implemented in package 'mlt' (, ). + Available models include Cox models, some parametric + survival models (Weibull, etc.), models for ordered categorical variables, + normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression + (Lohse et al., 2017, ). The underlying theory + is described in Hothorn et al. (2018) . An extension to + transformation models for clustered data is provided (Barbanti and Hothorn, 2022, + ). Multivariate conditional transformation models + (Klein et al, 2022, ) and shift-scale transformation models (Siegfried et al, 2023, + ) can be fitted as well. The package contains an implementation of + a doubly robust score test, described in Kook et al. (2024, ). + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tram + url_git: http://ctm.R-forge.R-project.org +tramicp: + version: 0.1-0 + title: Model-Based Causal Feature Selection for General Response Types + maintainer: Lucas Kook + description: |- + Extends invariant causal prediction (Peters et al., 2016, + ) to generalized linear and transformation models + (Hothorn et al., 2018, ). + The methodology is described in Kook et al. (2023, + ). + date_publication: '2025-01-31' + bug_reports: https://github.com/LucasKook/tramicp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tramicp + url_git: https://github.com/LucasKook/tramicp +TraMineR: + version: 2.2-11 + title: 'Trajectory Miner: a Sequence Analysis Toolkit' + maintainer: Gilbert Ritschard + description: Set of sequence analysis tools for manipulating, describing and rendering + categorical sequences, and more generally mining sequence data in the field of + social sciences. Although this sequence analysis package is primarily intended + for state or event sequences that describe time use or life courses such as family + formation histories or professional careers, its features also apply to many other + kinds of categorical sequence data. It accepts many different sequence representations + as input and provides tools for converting sequences from one format to another. + It offers several functions for describing and rendering sequences, for computing + distances between sequences with different metrics (among which optimal matching), + original dissimilarity-based analysis tools, and functions for extracting the + most frequent event subsequences and identifying the most discriminating ones + among them. A user's guide can be found on the TraMineR web page. + date_publication: '2024-12-08' + bug_reports: '' + url: http://traminer.unige.ch + url_cran: https://CRAN.R-project.org/package=TraMineR + url_git: '' +TraMineRextras: + version: 0.6.8 + title: TraMineR Extension + maintainer: Gilbert Ritschard + description: Collection of ancillary functions and utilities to be used in conjunction + with the 'TraMineR' package for sequence data exploration. Includes, among others, + specific functions such as state survival plots, position-wise group-typical states, + dynamic sequence indicators, and dissimilarities between event sequences. Also + includes contributions by non-members of the TraMineR team such as methods for + polyadic data and for the comparison of groups of sequences. + date_publication: '2024-08-17' + bug_reports: '' + url: http://traminer.unige.ch/ + url_cran: https://CRAN.R-project.org/package=TraMineRextras + url_git: '' +tramME: + version: 1.0.7 + title: Transformation Models with Mixed Effects + maintainer: Balint Tamasi + description: |- + Likelihood-based estimation of mixed-effects transformation models + using the Template Model Builder ('TMB', Kristensen et al., 2016) + . The technical details of transformation models + are given in Hothorn et al. (2018) . Likelihood + contributions of exact, randomly censored (left, right, interval) and + truncated observations are supported. The random effects are assumed to be + normally distributed on the scale of the transformation function, the + marginal likelihood is evaluated using the Laplace approximation, and the + gradients are calculated with automatic differentiation (Tamasi & Hothorn, + 2021) . Penalized smooth shift terms can be + defined using 'mgcv'. + date_publication: '2024-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tramME + url_git: http://ctm.R-forge.R-project.org +tramnet: + version: 0.0-8 + title: Penalized Transformation Models + maintainer: Lucas Kook + description: |- + Partially penalized versions of specific transformation models + implemented in package 'mlt'. Available models include a fully parametric version + of the Cox model, other parametric survival models (Weibull, etc.), models for + binary and ordered categorical variables, normal and transformed-normal (Box-Cox type) + linear models, and continuous outcome logistic regression. Hyperparameter tuning + is facilitated through model-based optimization functionalities from package 'mlrMBO'. + The accompanying vignette describes the methodology used in 'tramnet' in detail. + Transformation models and model-based optimization are described in + Hothorn et al. (2019) and + Bischl et al. (2016) , respectively. + date_publication: '2023-03-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tramnet + url_git: http://ctm.R-forge.R-project.org +TRAMPR: + version: 1.0-10 + title: '''TRFLP'' Analysis and Matching Package for R' + maintainer: Rich FitzJohn + description: |- + Matching terminal restriction fragment length + polymorphism ('TRFLP') profiles between unknown samples and a + database of known samples. 'TRAMPR' facilitates analysis of + many unknown profiles at once, and provides tools for working + directly with electrophoresis output through to generating + summaries suitable for community analyses with R's rich set of + statistical functions. 'TRAMPR' also resolves the issues of + multiple 'TRFLP' profiles within a species, and shared 'TRFLP' + profiles across species. + date_publication: '2022-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TRAMPR + url_git: https://github.com/richfitz/TRAMPR +tramvs: + version: 0.0-7 + title: Optimal Subset Selection for Transformation Models + maintainer: Lucas Kook + description: |- + Greedy optimal subset selection for transformation models + (Hothorn et al., 2018, ) based on the abess + algorithm (Zhu et al., 2020, ). Applicable to + models from packages 'tram' and 'cotram'. Application to shift-scale + transformation models are described in Siegfried et al. (2024, + ). + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tramvs + url_git: http://ctm.R-forge.R-project.org +transDA: + version: 1.0.0 + title: Transformation Discriminant Analysis + maintainer: Jing Li + description: Performs transformation discrimination analysis and non-transformation + discrimination analysis. It also includes functions for Linear Discriminant Analysis, + Quadratic Discriminant Analysis, and Mixture Discriminant Analysis. In the context + of mixture discriminant analysis, it offers options for both common covariance + matrix (common sigma) and individual covariance matrices (uncommon sigma) for + the mixture components. + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=transDA + url_git: '' +transforEmotion: + version: 0.1.5 + title: |- + Sentiment Analysis for Text, Image and Video using Transformer + Models + maintainer: Aleksandar Tomašević + description: Implements sentiment analysis using huggingface + transformer zero-shot classification model pipelines for text and image data. + The default text pipeline is Cross-Encoder's DistilRoBERTa + and default image/video pipeline is Open AI's CLIP . + All other zero-shot classification model pipelines can be implemented using their + model name from . + date_publication: '2024-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=transforEmotion + url_git: '' +Transform: + version: '1.0' + title: Statistical Transformations + maintainer: Osman Dag + description: Performs various statistical transformations; Box-Cox and Log (Box + and Cox, 1964) , Glog (Durbin et al., + 2002) , Neglog (Whittaker et al., + 2005) , Reciprocal (Tukey, 1957), Log Shift + (Feng et al., 2016) , Bickel-Docksum (Bickel and Doksum, + 1981) , Yeo-Johnson (Yeo and Johnson, 2000) , + Square Root (Medina et al., 2019), Manly (Manly, 1976) , + Modulus (John and Draper, 1980) , Dual (Yang, 2006) , + Gpower (Kelmansky et al., 2013) . It also performs + graphical approaches, assesses the success of the transformation via tests and + plots. + date_publication: '2023-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Transform + url_git: '' +transform.hazards: + version: 0.1.1 + title: |- + Transforms Cumulative Hazards to Parameter Specified by ODE + System + maintainer: Pål Christie Ryalen + description: |- + Targets parameters that solve Ordinary Differential + Equations (ODEs) driven by a vector of cumulative hazard functions. + The package provides a method for estimating these parameters using + an estimator defined by a corresponding Stochastic Differential Equation + (SDE) system driven by cumulative hazard estimates. By providing cumulative + hazard estimates as input, the package gives estimates of the parameter as + output, along with pointwise (co)variances derived from an asymptotic + expression. Examples of parameters that can be targeted in this way include + the survival function, the restricted mean survival function, cumulative + incidence functions, among others; see Ryalen, Stensrud, and Røysland (2018) + , and further applications in + Stensrud, Røysland, and Ryalen (2019) + and Ryalen et al. (2021) . + date_publication: '2023-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=transform.hazards + url_git: '' +transformer: + version: 0.2.0 + title: Implementation of Transformer Deep Neural Network with Vignettes + maintainer: Bastiaan Quast + description: Transformer is a Deep Neural Network Architecture based i.a. on the + Attention mechanism (Vaswani et al. (2017) ). + date_publication: '2023-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=transformer + url_git: '' +transformmos: + version: 0.1.0 + title: |- + Transform MOS Values to be Robust for using Rank Based + Statistics + maintainer: Babak Naderi + description: 'Implementation of the transformation of the Mean Opinion Scores (MOS) + to be used before applying the rank based statistical techniques. The method and + its necessity is described in: Babak Naderi, Sebastian Möller (2020) .' + date_publication: '2020-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=transformmos + url_git: '' +transformr: + version: 0.1.5 + title: Polygon and Path Transformations + maintainer: Thomas Lin Pedersen + description: |- + In order to smoothly animate the transformation of polygons and + paths, many aspects needs to be taken into account, such as differing number + of control points, changing center of rotation, etc. The 'transformr' + package provides an extensive framework for manipulating the shapes of + polygons and paths and can be seen as the spatial brother to the 'tweenr' + package. + date_publication: '2024-02-26' + bug_reports: https://github.com/thomasp85/transformr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=transformr + url_git: https://github.com/thomasp85/transformr +transfR: + version: 1.1.0 + title: Transfer of Hydrograph from Gauged to Ungauged Catchments + maintainer: Alban de Lavenne + description: |- + A geomorphology-based hydrological modelling for transferring + streamflow measurements from gauged to ungauged catchments. Inverse + modelling enables to estimate net rainfall from streamflow measurements + following Boudhraâ et al. (2018) . + Resulting net rainfall is then estimated on the ungauged catchments + by spatial interpolation in order to finally simulate streamflow + following de Lavenne et al. (2016) . + date_publication: '2025-02-05' + bug_reports: https://gitlab.irstea.fr/HYCAR-Hydro/transfr/-/issues + url: https://gitlab.irstea.fr/HYCAR-Hydro/transfr + url_cran: https://CRAN.R-project.org/package=transfR + url_git: '' +TransGraph: + version: 1.0.1 + title: Transfer Graph Learning + maintainer: Mingyang Ren + description: |- + Transfer learning, aiming to use auxiliary domains to help improve learning of the target domain of interest when multiple heterogeneous datasets are available, has always been a hot topic in statistical machine learning. The recent transfer learning methods with statistical guarantees mainly focus on the overall parameter transfer for supervised models in the ideal case with the informative auxiliary domains with overall similarity. In contrast, transfer learning for unsupervised graph learning is in its infancy and largely follows the idea of overall parameter transfer as for supervised learning. + In this package, the transfer learning for several complex graphical models is implemented, including Tensor Gaussian graphical models, non-Gaussian directed acyclic graph (DAG), and Gaussian graphical mixture models. Notably, this package promotes local transfer at node-level and subgroup-level in DAG structural learning and Gaussian graphical mixture models, respectively, which are more flexible and robust than the existing overall parameter transfer. As by-products, transfer learning for undirected graphical model (precision matrix) via D-trace loss, transfer learning for mean vector estimation, and single non-Gaussian learning via topological layer method are also included in this package. + Moreover, the aggregation of auxiliary information is an important issue in transfer learning, and this package provides multiple user-friendly aggregation methods, including sample weighting, similarity weighting, and most informative selection. + Reference: + Ren, M., Zhen Y., and Wang J. (2022) "Transfer learning for tensor graphical models". + Ren, M., He X., and Wang J. (2023) "Structural transfer learning of non-Gaussian DAG". + Zhao, R., He X., and Wang J. (2022) "Learning linear non-Gaussian directed acyclic graph with diverging number of nodes". + date_publication: '2023-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TransGraph + url_git: '' +translate.logit: + version: '1.0' + title: Translation of Logit Regression Coefficients into Percentages + maintainer: Nicolas Robette + description: Translation of logit models coefficients into percentages, following + Deauvieau (2010) . + date_publication: '2023-02-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=translate.logit + url_git: '' +translit.uk: + version: 1.0.0 + title: Ukrainian to Latin Transliteration + maintainer: Kyrylo Zakharov + description: Provides a robust and user-friendly solution for transliterating Ukrainian + strings into Latin symbols. + date_publication: '2024-07-08' + bug_reports: https://github.com/Amice13/translit.uk/issues + url: '' + url_cran: https://CRAN.R-project.org/package=translit.uk + url_git: https://github.com/Amice13/translit.uk +transltr: + version: 0.1.0 + title: Support Many Languages in R + maintainer: Jean-Mathieu Potvin + description: |- + An object model for source text and translations. Find and extract + translatable strings. Provide translations and seamlessly retrieve them at + runtime. + date_publication: '2025-02-14' + bug_reports: https://github.com/jeanmathieupotvin/transltr/issues + url: https://transltr.ununoctium.dev + url_cran: https://CRAN.R-project.org/package=transltr + url_git: '' +transmdl: + version: 0.1.0 + title: Semiparametric Transformation Models + maintainer: Fengyu Wen + description: |- + To make the semiparametric transformation models easier to apply in real studies, + we introduce this R package, in which the MLE in transformation models via + an EM algorithm proposed by Zeng D, Lin DY(2007) + and adaptive lasso method in transformation models proposed by Liu XX, Zeng + D(2013) are implemented. + C++ functions are used to compute complex loops. The coefficient vector and + cumulative baseline hazard function can be estimated, along with the + corresponding standard errors and P values. + date_publication: '2021-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=transmdl + url_git: '' +transmem: + version: 0.1.1 + title: Treatment of Membrane-Transport Data + maintainer: Cristhian Paredes + description: |- + Treatment and visualization of membrane (selective) transport + data. Transport profiles involving up to three species are produced as + publication-ready plots and several membrane performance parameters + (e.g. separation factors as defined in Koros et al. (1996) + and non-linear regression parameters + for the equations described in Rodriguez de San Miguel et al. (2014) + ) can be obtained. Many widely used + experimental setups (e.g. membrane physical aging) can be easily studied + through the package's graphical representations. + date_publication: '2020-06-05' + bug_reports: https://github.com/Crparedes/transmem/issues + url: '' + url_cran: https://CRAN.R-project.org/package=transmem + url_git: '' +TransModel: + version: '2.3' + title: Fit Linear Transformation Models for Right Censored Data + maintainer: Jie Zhou + description: A unified estimation procedure for the analysis of right censored data + using linear transformation models. An introduction can be found in Jie Zhou et + al. (2022) . + date_publication: '2022-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TransModel + url_git: '' +TransP: + version: '0.1' + title: Implementation of Transportation Problem Algorithms + maintainer: Somenath Sit + description: |- + Implementation of two transportation problem algorithms. + 1. North West Corner Method + 2. Minimum Cost Method or Least cost method. + For more technical details about the algorithms please refer below URLs. + . + . + date_publication: '2016-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TransP + url_git: https://github.com/Somenath24/TransP +TransPhylo: + version: 1.4.5 + title: Inference of Transmission Tree from a Dated Phylogeny + maintainer: Xavier Didelot + description: |- + Inference of transmission tree from a dated phylogeny. + Includes methods to simulate and analyse outbreaks. + The methodology is described in + Didelot et al. (2014) , + Didelot et al. (2017) . + date_publication: '2021-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TransPhylo + url_git: '' +transplantr: + version: 0.2.0 + title: Audit and Research Functions for Transplantation + maintainer: John Asher + description: |- + A set of vectorised functions to calculate medical equations used in transplantation, + focused mainly on transplantation of abdominal organs. These functions include donor and recipient + risk indices as used by NHS Blood & Transplant, OPTN/UNOS and Eurotransplant, tools for + quantifying HLA mismatches, functions for calculating estimated glomerular filtration rate (eGFR), + a function to calculate the APRI (AST to platelet ratio) score used in initial screening of suitability to receive a + transplant from a hepatitis C seropositive donor and some biochemical unit converter functions. + All functions are designed to work with either US or international units. + References for the equations are provided in the vignettes and function documentation. + date_publication: '2020-02-28' + bug_reports: https://github.com/johnasher/transplantr/issues + url: https://transplantr.txtools.net + url_cran: https://CRAN.R-project.org/package=transplantr + url_git: https://github.com/johnasher/transplantr +transPlotR: + version: 0.0.2 + title: Visualize Transcript Structures in Elegant Way + maintainer: Junjun Lao + description: To visualize the gene structure with multiple isoforms better, I developed + this package to draw different transcript structures easily. + date_publication: '2022-08-30' + bug_reports: https://github.com/junjunlab/transPlotR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=transPlotR + url_git: https://github.com/junjunlab/transPlotR +transport: + version: 0.15-4 + title: Computation of Optimal Transport Plans and Wasserstein Distances + maintainer: Dominic Schuhmacher + description: Solve optimal transport problems. Compute Wasserstein distances (a.k.a. + Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p distances), + return the corresponding transference plans, and display them graphically. Objects + that can be compared include grey-scale images, (weighted) point patterns, and + mass vectors. + date_publication: '2024-09-16' + bug_reports: https://github.com/dschuhmacher/transport/issues + url: https://dschuhm1.pages.gwdg.de/software + url_cran: https://CRAN.R-project.org/package=transport + url_git: '' +transportr: + version: 0.1.0 + title: Transporting Intervention Effects from One Population to Another + maintainer: Nicholas Williams + description: |- + Doubly-robust, non-parametric estimators for the transported average treatment effect from + Rudolph, Williams, Stuart, and Diaz (2023) and the + intent-to-treatment average treatment effect from Rudolph and van der Laan (2017) + . Estimators are fit using cross-fitting and nuisance parameters are + estimated using the Super Learner algorithm. + date_publication: '2025-02-20' + bug_reports: https://github.com/nt-williams/transportr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=transportr + url_git: https://github.com/nt-williams/transportr +TransProR: + version: 1.0.3 + title: Analysis and Visualization of Multi-Omics Data + maintainer: Dongyue Yu + description: A tool for comprehensive transcriptomic data analysis, with a focus + on transcript-level data preprocessing, expression profiling, differential expression + analysis, and functional enrichment. It enables researchers to identify key biological + processes, disease biomarkers, and gene regulatory mechanisms. 'TransProR' is + aimed at researchers and bioinformaticians working with RNA-Seq data, providing + an intuitive framework for in-depth analysis and visualization of transcriptomic + datasets. The package includes comprehensive documentation and usage examples + to guide users through the entire analysis pipeline. The differential expression + analysis methods incorporated in the package include 'limma' (Ritchie et al., + 2015, ; Smyth, 2005, ), + 'edgeR' (Robinson et al., 2010, ), 'DESeq2' + (Love et al., 2014, ), and Wilcoxon tests (Li et + al., 2022, ), providing flexible and robust approaches + to RNA-Seq data analysis. For more information, refer to the package vignettes + and related publications. + date_publication: '2025-02-18' + bug_reports: https://github.com/SSSYDYSSS/TransProR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TransProR + url_git: https://github.com/SSSYDYSSS/TransProRBook +transreg: + version: 1.0.3 + title: |- + Penalised Regression with Multiple Sets of Prior Effects + ('Transfer Learning') + maintainer: Armin Rauschenberger + description: Improves the predictive performance of ridge and lasso regression exploiting + one or more sources of prior information on the importance and direction of effects + (Rauschenberger and others 2023, ). For running + the vignette (optional), install 'fwelnet' from 'GitHub' . + date_publication: '2024-09-27' + bug_reports: https://github.com/rauschenberger/transreg/issues + url: https://rauschenberger.github.io/transreg/ + url_cran: https://CRAN.R-project.org/package=transreg + url_git: https://github.com/rauschenberger/transreg +TransTGGM: + version: 1.0.0 + title: Transfer Learning for Tensor Graphical Models + maintainer: Mingyang Ren + description: |- + Tensor Gaussian graphical models (GGMs) have important applications in numerous areas, which can interpret conditional independence structures within tensor data. Yet, the available tensor data in one single study is often limited due to high acquisition costs. + Although relevant studies can provide additional data, it remains an open question how to pool such heterogeneous data. This package implements a transfer learning framework for tensor GGMs, which takes full advantage of informative auxiliary domains even when non-informative auxiliary domains are present, benefiting from the carefully designed data-adaptive weights. + Reference: + Ren, M., Zhen Y., and Wang J. (2022). "Transfer learning for tensor graphical models" . + date_publication: '2022-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TransTGGM + url_git: '' +transx: + version: 0.0.1 + title: Transform Univariate Time Series + maintainer: Kostas Vasilopoulos + description: |- + Univariate time series operations that follow an opinionated design. + The main principle of 'transx' is to keep the number of observations the same. + Operations that reduce this number have to fill the observations gap. + date_publication: '2020-11-27' + bug_reports: https://github.com/kvasilopoulos/transx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=transx + url_git: https://github.com/kvasilopoulos/transx +trapezoid: + version: 2.0-2 + title: The Trapezoidal Distribution + maintainer: Jeremy Thoms Hetzel + description: |- + The trapezoid package provides 'dtrapezoid', 'ptrapezoid', 'qtrapezoid', + and 'rtrapezoid' functions for the trapezoidal distribution. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trapezoid + url_git: '' +Tratamentos.ad: + version: 0.2.4 + title: Pacote Para Analise De Experimentos Com Testemunhas Adicionais + maintainer: Alcinei Mistico Azevedo + description: |- + Pacote para a analise de experimentos com um ou dois fatores com + testemunhas adicionais conduzidos no delineamento inteiramente + casualizado ou em blocos casualizados. + "Package for the analysis of one or two-way experiments with + additional controls conducted in a completely randomized design + or in a randomized block design". + date_publication: '2022-09-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tratamentos.ad + url_git: '' +traudem: + version: 1.0.3 + title: Use TauDEM + maintainer: Luca Carraro + description: |- + Simple trustworthy utility functions to use TauDEM + (Terrain Analysis Using Digital Elevation Models ) command-line interface. + This package provides a guide to installation of TauDEM and its dependencies GDAL (Geopatial Data Abstraction Library) + and MPI (Message Passing Interface) for different operating systems. + Moreover, it checks that TauDEM and its dependencies are correctly installed and included to the PATH, + and it provides wrapper commands for calling TauDEM methods from R. + date_publication: '2024-04-24' + bug_reports: https://github.com/lucarraro/traudem/issues + url: https://lucarraro.github.io/traudem/ + url_cran: https://CRAN.R-project.org/package=traudem + url_git: https://github.com/lucarraro/traudem +traumar: + version: 1.0.0 + title: Calculate Metrics for Trauma System Performance + maintainer: Nicolas Foss + description: |- + Hospitals, hospital systems, and even trauma systems that provide care to injured patients + may not be aware of robust metrics that can help gauge the efficacy of their programs in saving the lives + of injured patients. 'traumar' provides robust functions driven by the academic literature to + automate the calculation of relevant metrics to individuals desiring to measure the performance of their + trauma center or even a trauma system. 'traumar' also provides some helper functions for the data analysis + journey. Users can refer to the following publications for descriptions of the methods used in 'traumar'. + TRISS methodology, including probability of survival, and the W, M, and Z Scores - Flora (1978) + , Boyd et al. (1987, PMID:3106646), Llullaku et al. (2009) + , Singh et al. (2011) , Baker et al. (1974, PMID:4814394), + and Champion et al. (1989) . For the Relative Mortality Metric, + see Napoli et al. (2017) , Schroeder et al. (2019) + , and Kassar et al. (2016) . + date_publication: '2025-02-21' + bug_reports: https://github.com/bemts-hhs/traumar/issues + url: https://bemts-hhs.github.io/traumar/ + url_cran: https://CRAN.R-project.org/package=traumar + url_git: https://github.com/bemts-hhs/traumar +traveltimeR: + version: 1.2.1 + title: Interface to 'Travel Time' API + maintainer: TravelTime + description: |- + 'Travel Time' API helps users find locations by journey time rather than using ‘as the crow flies’ distance. + Time-based searching gives users more opportunities for personalisation and delivers a more relevant search. + date_publication: '2024-05-09' + bug_reports: https://github.com/traveltime-dev/traveltime-sdk-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=traveltimeR + url_git: https://github.com/traveltime-dev/traveltime-sdk-r +trawl: + version: 0.2.2 + title: Estimation and Simulation of Trawl Processes + maintainer: Almut E. D. Veraart + description: |- + Contains R functions for simulating and estimating integer-valued trawl processes as + described in the article Veraart (2019),"Modeling, simulation and inference for + multivariate time series of counts using trawl processes", Journal of Multivariate Analysis, + 169, pages 110-129, + and for + simulating random vectors from the bivariate negative binomial and the bi- and trivariate + logarithmic series distributions. + date_publication: '2021-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trawl + url_git: '' +TRD: + version: '1.1' + title: Transmission Ratio Distortion + maintainer: Lam Opal Huang + description: Transmission Ratio Distortion (TRD) is a genetic phenomenon where the + two alleles from either parent are not transmitted to the offspring at the expected + 1:1 ratio under Mendelian inheritance, leading to spurious signals in genetic + association studies. Functions in this package are developed to account for this + phenomenon using loglinear model and Transmission Disequilibrium Test (TDT). Some + population information can also be calculated. + date_publication: '2015-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TRD + url_git: '' +trdist: + version: 1.0.1 + title: Univariate Proability Distributions with Truncation + maintainer: Jared Studyvin + description: Truncation of univariate probability distributions. The probability + distribution can come from other packages so long as the function names follow + the standard d, p, q, r naming format. Also other univariate probability distributions + are included. + date_publication: '2024-07-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trdist + url_git: '' +treasury: + version: 0.2.0 + title: Client for US Treasury XML Feed and Published Data + maintainer: Maximilian Muecke + description: |- + Download daily interest rates from the US Treasury XML feed. + Leveraging + , + this package serves as a wrapper, facilitating the retrieval of daily + treasury rates across various categories, including par yield curves, + treasury bills, long-term rates, and real yield curves. + date_publication: '2024-07-05' + bug_reports: https://github.com/m-muecke/treasury/issues + url: https://m-muecke.github.io/treasury/ + url_cran: https://CRAN.R-project.org/package=treasury + url_git: https://github.com/m-muecke/treasury +TreatmentPatterns: + version: 3.0.0 + title: |- + Analyzes Real-World Treatment Patterns of a Study Population of + Interest + maintainer: Maarten van Kessel + description: |- + Computes treatment patterns within a given cohort using the Observational + Medical Outcomes Partnership (OMOP) common data model (CDM). As described + in Markus, Verhamme, Kors, and Rijnbeek (2022) . + date_publication: '2025-02-06' + bug_reports: https://github.com/darwin-eu/TreatmentPatterns/issues + url: https://darwin-eu-dev.github.io/TreatmentPatterns/ + url_cran: https://CRAN.R-project.org/package=TreatmentPatterns + url_git: https://github.com/darwin-eu/TreatmentPatterns +TreatmentSelection: + version: 2.1.1 + title: Evaluate Treatment Selection Biomarkers + maintainer: Marshall Brown + description: A suite of descriptive and inferential methods designed to evaluate + one or more biomarkers for their ability to guide patient treatment recommendations. Package + includes functions to assess the calibration of risk models; and plot, evaluate, + and compare markers. Please see the reference Janes H, Brown MD, Huang Y, et al. + (2014) for further details. + date_publication: '2017-08-11' + bug_reports: '' + url: http://rpubs.com/mdbrown/TreatmentSelection + url_cran: https://CRAN.R-project.org/package=TreatmentSelection + url_git: '' +treats: + version: '1.1' + title: Trees and Traits Simulations + maintainer: Thomas Guillerme + description: A modular package for simulating phylogenetic trees and species traits + jointly. Trees can be simulated using modular birth-death parameters (e.g. changing + starting parameters or algorithm rules). Traits can be simulated in any way designed + by the user. The growth of the tree and the traits can influence each other through + modifiers objects providing rules for affecting each other. Finally, events can + be created to modify both the tree and the traits under specific conditions ( + Guillerme, 2024 ). + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treats + url_git: https://github.com/TGuillerme/treats +TREDesigns: + version: 1.0.1 + title: Ternary Residual Effect Designs + maintainer: Ashutosh Dalal + description: There are some experimental scenarios where each experimental unit + receives a sequence of treatments across multiple periods, and treatment effects + persist beyond the period of application. It focuses on the construction and calculation + of the parametric value of the residual effect designs balanced for carryover + effects, also referred to as crossover designs, change-over designs, or repeated + measurements designs (Aggarwal and Jha, 2010). + The primary objective of the package is to generate a new class of Balanced Ternary + Residual Effect Designs (BTREDs), balanced for carryover effects tailored explicitly + for situations where the number of periods is less than or equal to the number + of treatments. In addition, the package provides four new classes of Partially + Balanced Ternary Residual Effect Designs (PBTREDs), constructed using incomplete + block designs, initial sequences, and rectangular association scheme. In addition, + one extra function is included to help study the parametric properties of a given + residual effect design. + date_publication: '2025-01-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TREDesigns + url_git: '' +tree: + version: 1.0-44 + title: Classification and Regression Trees + maintainer: Brian Ripley + description: Classification and regression trees. + date_publication: '2024-12-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tree + url_git: '' +tree.interpreter: + version: 0.1.1 + title: |- + Random Forest Prediction Decomposition and Feature Importance + Measure + maintainer: Qingyao Sun + description: |- + An R re-implementation of the 'treeinterpreter' package on PyPI + . Each prediction can be + decomposed as 'prediction = bias + feature_1_contribution + ... + + feature_n_contribution'. This decomposition is then used to calculate + the Mean Decrease Impurity (MDI) and Mean Decrease Impurity using + out-of-bag samples (MDI-oob) feature importance measures based on the + work of Li et al. (2019) . + date_publication: '2020-02-05' + bug_reports: https://github.com/nalzok/tree.interpreter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tree.interpreter + url_git: https://github.com/nalzok/tree.interpreter +tree3d: + version: 0.1.2 + title: 3D Tree Models + maintainer: Tyler Morgan-Wall + description: Provides customizable 3D tree models (as 'OBJ' files) for use in data + visualization. Includes both planar and solid tree models, various crown types + (columnar, oval, palm, pyramidal, rounded, spreading, vase, weeping), and options + to change the diameter, height, and color of the tree's crown and trunk. + date_publication: '2023-06-23' + bug_reports: https://github.com/tylermorganwall/tree3d/issues + url: https://tylermorganwall.github.io/tree3d/ + url_cran: https://CRAN.R-project.org/package=tree3d + url_git: '' +treebalance: + version: 1.2.0 + title: Computation of Tree (Im)Balance Indices + maintainer: Luise Kuehn + description: |- + The aim of the 'R' package 'treebalance' is to provide functions for the computation of + a large variety of (im)balance indices for rooted trees. The package accompanies the book + ''Tree balance indices: a comprehensive survey'' by M. Fischer, L. Herbst, S. Kersting, + L. Kuehn and K. Wicke (2023) , , which gives a precise definition for the terms 'balance index' and 'imbalance index' (Chapter 4) + and provides an overview of the terminology in this manual (Chapter 2). For further information + on (im)balance indices, see also Fischer et al. (2021) . + Considering both established and new (im)balance indices, 'treebalance' provides (among + others) functions for calculating the following 18 established indices and index families: the + average leaf depth, the B1 and B2 index, the Colijn-Plazzotta rank, the normal, corrected, + quadratic and equal weights Colless index, the family of Colless-like indices, the family of + I-based indices, the Rogers J index, the Furnas rank, the rooted quartet index, the s-shape + statistic, the Sackin index, the symmetry nodes index, the total cophenetic index and the + variance of leaf depths. Additionally, we include 9 tree shape statistics that satisfy the + definition of an (im)balance index but have not been thoroughly analyzed in terms of tree + balance in the literature yet. These are: the total internal path length, the total path length, + the average vertex depth, the maximum width, the modified maximum difference in widths, the + maximum depth, the maximum width over maximum depth, the stairs1 and the stairs2 index. + As input, most functions of 'treebalance' require a rooted (phylogenetic) tree in 'phylo' format + (as introduced in 'ape' 1.9 in November 2006). 'phylo' is used to store (phylogenetic) trees + with no vertices of out-degree one. For further information on the format we kindly refer the + reader to E. Paradis (2012) . + date_publication: '2023-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treebalance + url_git: '' +treebase: + version: 0.1.5 + title: Discovery, Access and Manipulation of 'TreeBASE' Phylogenies + maintainer: Carl Boettiger + description: |- + Interface to the API for 'TreeBASE' + from 'R.' 'TreeBASE' is a repository of user-submitted phylogenetic + trees (of species, population, or genes) and the data used to create + them. + date_publication: '2024-02-16' + bug_reports: https://github.com/ropensci/treebase/issues + url: https://docs.ropensci.org/treebase/ + url_cran: https://CRAN.R-project.org/package=treebase + url_git: https://github.com/ropensci/treebase +TreeBUGS: + version: 1.5.0 + title: Hierarchical Multinomial Processing Tree Modeling + maintainer: Daniel W. Heck + description: |- + User-friendly analysis of hierarchical multinomial processing tree (MPT) + models that are often used in cognitive psychology. Implements the latent-trait + MPT approach (Klauer, 2010) and the beta-MPT + approach (Smith & Batchelder, 2010) to model + heterogeneity of participants. MPT models are conveniently specified by an + .eqn-file as used by other MPT software and data are provided by a .csv-file + or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored + Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides + tests of heterogeneity and MPT-tailored summaries and plotting functions. + A detailed documentation is available in Heck, Arnold, & Arnold (2018) + and a tutorial on MPT modeling can be found + in Schmidt, Erdfelder, & Heck (2022) . + date_publication: '2023-05-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TreeBUGS + url_git: https://github.com/danheck/TreeBUGS +treeclim: + version: 2.0.7.1 + title: Numerical Calibration of Proxy-Climate Relationships + maintainer: Christian Zang + description: |- + Bootstrapped response and correlation functions, + seasonal correlations and evaluation of reconstruction + skills for use in dendroclimatology and dendroecology, + see Zang and Biondi (2015) . + date_publication: '2024-12-16' + bug_reports: https://github.com/cszang/treeclim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=treeclim + url_git: https://github.com/cszang/treeclim +treeClust: + version: 1.1-7 + title: Cluster Distances Through Trees + maintainer: Sam Buttrey + description: |- + Create a measure of inter-point dissimilarity useful + for clustering mixed data, and, optionally, perform the clustering. + date_publication: '2018-05-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treeClust + url_git: '' +treeDA: + version: 0.0.5 + title: Tree-Based Discriminant Analysis + maintainer: Julia Fukuyama + description: |- + Performs sparse discriminant analysis on a combination of + node and leaf predictors when the predictor variables are + structured according to a tree, as described in Fukuyama et + al. (2017) . + date_publication: '2021-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treeDA + url_git: https://github.com/jfukuyama/treeda +treedater: + version: 0.5.0 + title: |- + Fast Molecular Clock Dating of Phylogenetic Trees with Rate + Variation + maintainer: Erik Volz + description: Functions for estimating times of common ancestry and molecular clock + rates of evolution using a variety of evolutionary models, parametric and nonparametric + bootstrap confidence intervals, methods for detecting outlier lineages, root-to-tip + regression, and a statistical test for selecting molecular clock models. The methods + are described in Volz, E.M. and S.D.W. Frost (2017) . + date_publication: '2020-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treedater + url_git: '' +treeDbalance: + version: 1.0.1 + title: Computation of 3D Tree Imbalance + maintainer: Sophie Kersting + description: |- + The main goal of the R package 'treeDbalance' is to provide + functions for the computation of several measurements of 3D node + imbalance and their respective 3D tree imbalance indices, as well as to + introduce the new 'phylo3D' format for rooted 3D tree objects. + Moreover, it encompasses an example dataset of 3D models of 63 beans + in 'phylo3D' format. Please note that this R package was developed + alongside the project described in the manuscript 'Measuring 3D tree + imbalance of plant models using graph-theoretical approaches' by + M. Fischer, S. Kersting, and L. Kühn (2023) , which + provides precise mathematical definitions of the measurements. + Furthermore, the package contains several helpful functions, for example, + some auxiliary functions for computing the ancestors, descendants, and + depths of the nodes, which ensures that the computations can be done in + linear time. + Most functions of 'treeDbalance' require as input a rooted tree in the + 'phylo3D' format, an extended 'phylo' format (as introduced in the R package + 'ape' 1.9 in November 2006). Such a 'phylo3D' object must have at least + two new attributes next to those required by the 'phylo' format: + 'node.coord', the coordinates of the nodes, as well as 'edge.weight', + the literal weight or volume of the edges. + Optional attributes are 'edge.diam', the diameter of the edges, and + 'edge.length', the length of the edges. For visualization purposes one + can also specify 'edge.type', which ranges from normal cylinder to bud + to leaf, as well as 'edge.color' to change the color of the edge depiction. + This project was supported by the joint research project DIG-IT! + funded by the European Social Fund (ESF), reference: + ESF/14-BM-A55-0017/19, and the Ministry of Education, Science and + Culture of Mecklenburg-Western Pomerania, Germany, as well as by the + the project ArtIGROW, which is a part of the WIR!-Alliance 'ArtIFARM – + Artificial Intelligence in Farming' funded by the German Federal Ministry + of Education and Research (FKZ: 03WIR4805). + date_publication: '2023-08-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treeDbalance + url_git: '' +TreeDep: + version: 0.1.3 + title: Air Pollution Removal by Dry Deposition on Trees + maintainer: Silvestre Garcia de Jalon + description: 'The model estimates air pollution removal by dry deposition on trees. + It also estimates or uses hourly values for aerodynamic resistance, boundary layer + resistance, canopy resistance, stomatal resistance, cuticular resistance, mesophyll + resistance, soil resistance, friction velocity and deposition velocity. It also + allows plotting graphical results for a specific time period. The pollutants are + nitrogen dioxide, ozone, sulphur dioxide, carbon monoxide and particulate matter. + Baldocchi D (1994) . Farquhar GD, von Caemmerer + S, Berry JA (1980) Planta 149: 78-90. Hirabayashi S, Kroll CN, Nowak DJ (2015) + i-Tree Eco Dry Deposition Model. Nowak DJ, Crane DE, Stevens JC (2006) . + US EPA (1999) PCRAMMET User''s Guide. EPA-454/B-96-001. Weiss A, Norman JM (1985) + Agricultural and Forest Meteorology 34: 205—213.' + date_publication: '2018-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TreeDep + url_git: '' +TreeDiagram: + version: 0.1.1 + title: Tree Diagram + maintainer: Wen Tian (Wendy) Wang + description: Visualizing cuts for either axis-align or non axis-align tree methods + (e.g. decision tree, random tessellation process). + date_publication: '2021-03-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TreeDiagram + url_git: '' +treediff: + version: 0.2.1 + title: Testing Differences Between Families of Trees + maintainer: Nathalie Vialaneix + description: |- + Perform test to detect differences in structure between families of + trees. The method is based on cophenetic distances and aggregated + Student's tests. + date_publication: '2024-02-17' + bug_reports: https://forgemia.inra.fr/scales/treediff/-/issues + url: https://forgemia.inra.fr/scales/treediff + url_cran: https://CRAN.R-project.org/package=treediff + url_git: '' +TreeDimensionTest: + version: 0.0.2 + title: Trajectory Presence and Heterogeneity in Multivariate Data + maintainer: Joe Song + description: |- + Testing for trajectory presence and heterogeneity on + multivariate data. Two statistical methods (Tenha & Song 2022) + are implemented. The tree dimension + test quantifies the statistical evidence for trajectory presence. The + subset specificity measure summarizes pattern heterogeneity using the + minimum subtree cover. There is no user tunable parameters for either + method. Examples are included to illustrate how to use the methods on + single-cell data for studying gene and pathway expression dynamics and + pathway expression specificity. + date_publication: '2022-03-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TreeDimensionTest + url_git: '' +TreeDist: + version: 2.9.2 + title: Calculate and Map Distances Between Phylogenetic Trees + maintainer: Martin R. Smith + description: |- + Implements measures of tree similarity, including + information-based generalized Robinson-Foulds distances + (Phylogenetic Information Distance, Clustering Information Distance, + Matching Split Information Distance; Smith 2020) + ; + Jaccard-Robinson-Foulds distances (Bocker et al. 2013) + , + including the Nye et al. (2006) metric ; + the Matching Split Distance (Bogdanowicz & Giaro 2012) + ; + Maximum Agreement Subtree distances; + the Kendall-Colijn (2016) distance , and the + Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. + (1996) . + Includes tools for visualizing mappings of tree space (Smith 2022) + , + for identifying islands of trees (Silva and Wilkinson 2021) + , + for calculating the median of sets of trees, + and for computing the information content of trees and splits. + date_publication: '2025-01-11' + bug_reports: https://github.com/ms609/TreeDist/issues/ + url: https://ms609.github.io/TreeDist/ + url_cran: https://CRAN.R-project.org/package=TreeDist + url_git: https://github.com/ms609/TreeDist/ +treefit: + version: 1.0.3 + title: The First Software for Quantitative Trajectory Inference + maintainer: Kouhei Sutou + description: |- + Perform two types of analysis: 1) checking the + goodness-of-fit of tree models to your single-cell gene expression + data; and 2) deciding which tree best fits your data. + date_publication: '2025-02-09' + bug_reports: https://github.com/hayamizu-lab/treefit-r/issues + url: https://hayamizu-lab.github.io/treefit-r/ + url_cran: https://CRAN.R-project.org/package=treefit + url_git: https://github.com/hayamizu-lab/treefit-r/ +treeheatr: + version: 0.2.1 + title: Heatmap-Integrated Decision Tree Visualizations + maintainer: Trang Le + description: |- + Creates interpretable decision tree visualizations + with the data represented as a heatmap at the tree's leaf nodes. + 'treeheatr' utilizes the customizable 'ggparty' package for + drawing decision trees. + date_publication: '2020-11-19' + bug_reports: https://github.com/trang1618/treeheatr/issues + url: https://trang1618.github.io/treeheatr/index.html + url_cran: https://CRAN.R-project.org/package=treeheatr + url_git: '' +treemap: + version: 2.4-4 + title: Treemap Visualization + maintainer: Martijn Tennekes + description: |- + A treemap is a space-filling visualization of hierarchical + structures. This package offers great flexibility to draw treemaps. + date_publication: '2023-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treemap + url_git: '' +treemapify: + version: 2.5.6 + title: Draw Treemaps in 'ggplot2' + maintainer: David Wilkins + description: Provides 'ggplot2' geoms for drawing treemaps. + date_publication: '2023-09-30' + bug_reports: https://github.com/wilkox/treemapify/issues/ + url: https://wilkox.org/treemapify/ + url_cran: https://CRAN.R-project.org/package=treemapify + url_git: '' +TreeMineR: + version: 1.0.2 + title: Tree-Based Scan Statistics + maintainer: Joshua P. Entrop + description: |- + Implementation of unconditional Bernoulli Scan Statistic developed + by Kulldorff et al. (2003) + for hierarchical tree structures. Tree-based Scan Statistics are an + exploratory method to identify event clusters across the space of a + hierarchical tree. + date_publication: '2024-08-27' + bug_reports: https://github.com/entjos/TreeMineR/issues + url: https://entjos.github.io/TreeMineR/ + url_cran: https://CRAN.R-project.org/package=TreeMineR + url_git: https://github.com/entjos/TreeMineR +treenomial: + version: 1.1.4 + title: Comparison of Trees using a Tree Defining Polynomial + maintainer: Matthew Gould + description: |- + Provides functionality for creation and comparison of polynomials that uniquely + describe trees as introduced in Liu (2019, ). The core method + converts rooted unlabeled phylo objects from 'ape' to the tree defining polynomials + described with coefficient matrices. Additionally, a conversion for rooted binary trees + with binary trait labels is also provided. Once the polynomials of trees are calculated + there are functions to calculate distances, distance matrices and plot different distance + trees from a target tree. Manipulation and conversion to the tree defining polynomials is + implemented in C++ with 'Rcpp' and 'RcppArmadillo'. Furthermore, parallel programming with + 'RcppThread' is used to improve performance converting to polynomials and calculating distances. + date_publication: '2022-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treenomial + url_git: https://github.com/gouldmatt/treenomial +treePlotArea: + version: 2.1.0 + title: |- + Correction Factors for Tree Plot Areas Intersected by Stand + Boundaries + maintainer: Andreas Dominik Cullmann + description: |- + The German national forest inventory uses angle count sampling, + a sampling method first published as `Bitterlich, W.: Die Winkelzählmessung. + Allgemeine Forst- und Holzwirtschaftliche Zeitung, 58. Jahrg., Folge 11/12 + vom Juni 1947` and extended by Grosenbaugh + () + as probability proportional to size sampling. + When plots are located near stand boundaries, their sizes and hence + their probabilities need to be corrected. + date_publication: '2024-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treePlotArea + url_git: https://gitlab.com/fvafrcu/treeplotarea.git +TreeRingShape: + version: 3.0.5 + title: |- + Recording Tree-Ring Shapes of Tree Disks with Manual Digitizing + and Interpolating Model + maintainer: Megumi ISHIDA + description: Record all tree-ring Shapefile of tree disk with GIS soft 'Qgis' and + interpolating model from high resolution tree disk image. + date_publication: '2024-11-15' + bug_reports: https://github.com/ishidamgm/TreeRingShape/issues + url: https://ishidamgm.github.io/TreeRingShape/ + url_cran: https://CRAN.R-project.org/package=TreeRingShape + url_git: https://github.com/ishidamgm/TreeRingShape +TreeSearch: + version: 1.5.1 + title: Phylogenetic Analysis with Discrete Character Data + maintainer: Martin R. Smith + description: |- + Reconstruct phylogenetic trees from discrete data. + Inapplicable character states are handled using the algorithm of Brazeau, + Guillerme and Smith (2019) with the "Morphy" + library, under equal or implied step weights. + Contains a "shiny" user interface for interactive tree search and exploration + of results, including character visualization, rogue taxon detection, + tree space mapping, and cluster consensus trees (Smith 2022a, b) + , . + Profile Parsimony (Faith and Trueman, 2001) , + Successive Approximations (Farris, 1969) + and custom optimality criteria are implemented. + date_publication: '2024-05-23' + bug_reports: https://github.com/ms609/TreeSearch/issues/ + url: https://ms609.github.io/TreeSearch/(doc) + url_cran: https://CRAN.R-project.org/package=TreeSearch + url_git: https://github.com/ms609/TreeSearch/(devel) +treeshap: + version: 0.3.1 + title: |- + Compute SHAP Values for Your Tree-Based Models Using the + 'TreeSHAP' Algorithm + maintainer: Mateusz Krzyzinski + description: |- + An efficient implementation of the 'TreeSHAP' algorithm + introduced by Lundberg et al., (2020) . + It is capable of calculating SHAP (SHapley Additive exPlanations) values + for tree-based models in polynomial time. Currently supported models include + 'gbm', 'randomForest', 'ranger', 'xgboost', 'lightgbm'. + date_publication: '2024-01-22' + bug_reports: https://github.com/ModelOriented/treeshap/issues + url: https://modeloriented.github.io/treeshap/ + url_cran: https://CRAN.R-project.org/package=treeshap + url_git: https://github.com/ModelOriented/treeshap +TreeSim: + version: '2.4' + title: Simulating Phylogenetic Trees + maintainer: Tanja Stadler + description: Simulation methods for phylogenetic trees where (i) all tips are sampled + at one time point or (ii) tips are sampled sequentially through time. (i) For + sampling at one time point, simulations are performed under a constant rate birth-death + process, conditioned on having a fixed number of final tips (sim.bd.taxa()), or + a fixed age (sim.bd.age()), or a fixed age and number of tips (sim.bd.taxa.age()). + When conditioning on the number of final tips, the method allows for shifts in + rates and mass extinction events during the birth-death process (sim.rateshift.taxa()). + The function sim.bd.age() (and sim.rateshift.taxa() without extinction) allow + the speciation rate to change in a density-dependent way. The LTT plots of the + simulations can be displayed using LTT.plot(), LTT.plot.gen() and LTT.average.root(). + TreeSim further samples trees with n final tips from a set of trees generated + by the common sampling algorithm stopping when a fixed number m>>n of tips is + first reached (sim.gsa.taxa()). This latter method is appropriate for m-tip trees + generated under a big class of models (details in the sim.gsa.taxa() man page). + For incomplete phylogeny, the missing speciation events can be added through simulations + (corsim()). (ii) sim.rateshifts.taxa() is generalized to sim.bdsky.stt() for serially + sampled trees, where the trees are conditioned on either the number of sampled + tips or the age. Furthermore, for a multitype-branching process with sequential + sampling, trees on a fixed number of tips can be simulated using sim.bdtypes.stt.taxa(). + This function further allows to simulate under epidemiological models with an + exposed class. The function sim.genespeciestree() simulates coalescent gene trees + within birth-death species trees, and sim.genetree() simulates coalescent gene + trees. + date_publication: '2019-04-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TreeSim + url_git: '' +TreeSimGM: + version: '2.5' + title: |- + Simulating Phylogenetic Trees under General Bellman Harris and + Lineage Shift Model + maintainer: Oskar Hagen + description: 'Provides a flexible simulation tool for phylogenetic trees under a + general model for speciation and extinction. Trees with a user-specified number + of extant tips, or a user-specified stem age are simulated. It is possible to + assume any probability distribution for the waiting time until speciation and + extinction. Furthermore, the waiting times to speciation / extinction may be scaled + in different parts of the tree, meaning we can simulate trees with clade-dependent + diversification processes. At a speciation event, one species splits into two. + We allow for two different modes at these splits: (i) symmetric, where for every + speciation event new waiting times until speciation and extinction are drawn for + both daughter lineages; and (ii) asymmetric, where a speciation event results + in one species with new waiting times, and another that carries the extinction + time and age of its ancestor. The symmetric mode can be seen as an vicariant or + allopatric process where divided populations suffer equal evolutionary forces + while the asymmetric mode could be seen as a peripatric speciation where a mother + lineage continues to exist. Reference: O. Hagen and T. Stadler (2017). TreeSimGM: + Simulating phylogenetic trees under general Bellman Harris models with lineage-specific + shifts of speciation and extinction in R. Methods in Ecology and Evolution. .' + date_publication: '2020-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TreeSimGM + url_git: '' +treesitter: + version: 0.1.0 + title: Bindings to 'Tree-Sitter' + maintainer: Davis Vaughan + description: |- + Provides bindings to 'Tree-sitter', an incremental parsing + system for programming tools. 'Tree-sitter' builds concrete syntax + trees for source files of any language, and can efficiently update + those syntax trees as the source file is edited. It also includes a + robust error recovery system that provides useful parse results even + in the presence of syntax errors. + date_publication: '2024-06-24' + bug_reports: https://github.com/DavisVaughan/r-tree-sitter/issues + url: '' + url_cran: https://CRAN.R-project.org/package=treesitter + url_git: https://github.com/DavisVaughan/r-tree-sitter +treesitter.r: + version: 1.1.0 + title: '''R'' Grammar for ''Tree-Sitter''' + maintainer: Davis Vaughan + description: |- + Provides bindings to an 'R' grammar for 'Tree-sitter', to be + used alongside the 'treesitter' package. 'Tree-sitter' builds concrete + syntax trees for source files of any language, and can efficiently + update those syntax trees as the source file is edited. + date_publication: '2024-09-06' + bug_reports: https://github.com/r-lib/tree-sitter-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=treesitter.r + url_git: https://github.com/r-lib/tree-sitter-r +treesliceR: + version: 1.0.2 + title: |- + To Slice Phylogenetic Trees and Infer Evolutionary Patterns Over + Time + maintainer: Matheus Lima Araujo + description: Provide a range of functions with multiple criteria for cutting phylogenetic + trees at any evolutionary depth. It enables users to cut trees in any orientation, + such as rootwardly (from root to tips) and tipwardly (from tips to its root), + or allows users to define a specific time interval of interest. It can also be + used to create multiple tree pieces of equal temporal width. Moreover, it allows + the assessment of novel temporal rates for various phylogenetic indexes, which + can be quickly displayed graphically. + date_publication: '2024-08-23' + bug_reports: https://github.com/AraujoMat/treesliceR/issues + url: https://araujomat.github.io/treesliceR/ + url_cran: https://CRAN.R-project.org/package=treesliceR + url_git: https://github.com/AraujoMat/treesliceR +treespace: + version: 1.1.4.3 + title: Statistical Exploration of Landscapes of Phylogenetic Trees + maintainer: Michelle Kendall + description: |- + Tools for the exploration of distributions of phylogenetic trees. + This package includes a 'shiny' interface which can be started from R using + treespaceServer(). + For further details see Jombart et al. (2017) . + date_publication: '2023-09-07' + bug_reports: https://github.com/thibautjombart/treespace/issues + url: '' + url_cran: https://CRAN.R-project.org/package=treespace + url_git: https://github.com/thibautjombart/treespace +treestartr: + version: 0.1.0 + title: |- + Generate Starting Trees for Combined Molecular, Morphological + and Stratigraphic Data + maintainer: April Wright + description: |- + Combine a list of taxa with a phylogeny to generate a starting tree for use in + total evidence dating analyses. + date_publication: '2019-01-09' + bug_reports: https://github.com/ropensci/treeStartR/issues + url: https://ropensci.github.io/treeStartR/ + url_cran: https://CRAN.R-project.org/package=treestartr + url_git: '' +treestats: + version: 1.70.5 + title: Phylogenetic Tree Statistics + maintainer: Thijs Janzen + description: |- + Collection of phylogenetic tree statistics, + collected throughout the literature. All functions have been + written to maximize computation speed. The package includes + umbrella functions to calculate all statistics, all balance + associated statistics, or all branching time related statistics. + Furthermore, the 'treestats' package supports summary statistic + calculations on Ltables, provides speed-improved coding of + branching times, Ltable conversion and includes algorithms to + create intermediately balanced trees. Full description can be + found in Janzen (2024) . + date_publication: '2024-08-26' + bug_reports: https://github.com/thijsjanzen/treestats/issues + url: https://thijsjanzen.github.io/treestats/ + url_cran: https://CRAN.R-project.org/package=treestats + url_git: https://github.com/thijsjanzen/treestats +treestructure: + version: 0.1.0 + title: Detect Population Structure Within Phylogenetic Trees + maintainer: Erik Volz + description: Algorithms for detecting population structure from the history of coalescent + events recorded in phylogenetic trees. This method classifies each tip and internal + node of a tree into disjoint sets characterized by similar coalescent patterns. + The methods are described in Volz, E., Wiuf, C., Grad, Y., Frost, S., Dennis, + A., & Didelot, X. (2020) . + date_publication: '2020-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=treestructure + url_git: '' +TreeTools: + version: 1.13.0 + title: Create, Modify and Analyse Phylogenetic Trees + maintainer: Martin R. Smith + description: |- + Efficient implementations of functions for the creation, + modification and analysis of phylogenetic trees. + Applications include: + generation of trees with specified shapes; + tree rearrangement; + analysis of tree shape; + rooting of trees and extraction of subtrees; + calculation and depiction of split support; + plotting the position of rogue taxa (Klopfstein & Spasojevic 2019) + ; + calculation of ancestor-descendant relationships, + of 'stemwardness' (Asher & Smith, 2022) , + and of tree balance (Mir et al. 2013, Lemant et al. 2022) + , ; + artificial extinction (Asher & Smith, 2022) ; + import and export of trees from Newick, Nexus (Maddison et al. 1997) + , + and TNT formats; + and analysis of splits and cladistic information. + date_publication: '2025-01-10' + bug_reports: https://github.com/ms609/TreeTools/issues/ + url: https://ms609.github.io/TreeTools/ + url_cran: https://CRAN.R-project.org/package=TreeTools + url_git: https://github.com/ms609/TreeTools/ +trekcolors: + version: 0.2.0 + title: Star Trek Color Palettes + maintainer: Matthew Leonawicz + description: |- + Provides a dataset of predefined color palettes based on the Star Trek science fiction series, associated color palette functions, + and additional functions for generating customized palettes that are on theme. The package also offers functions for applying + the palettes to plots made using the 'ggplot2' package. + date_publication: '2024-09-12' + bug_reports: https://github.com/leonawicz/trekcolors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trekcolors + url_git: https://github.com/leonawicz/trekcolors +trekfont: + version: 0.9.6 + title: Star Trek Fonts Collection + maintainer: Matthew Leonawicz + description: Provides a collection of true type and open type Star Trek-themed fonts. + date_publication: '2024-09-11' + bug_reports: https://github.com/leonawicz/trekfont/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trekfont + url_git: https://github.com/leonawicz/trekfont +trelliscopejs: + version: 0.2.6 + title: Create Interactive Trelliscope Displays + maintainer: Ryan Hafen + description: Trelliscope is a scalable, flexible, interactive approach to visualizing + data (Hafen, 2013 ). This package provides methods + that make it easy to create a Trelliscope display specification for TrelliscopeJS. + High-level functions are provided for creating displays from within 'tidyverse' + or 'ggplot2' workflows. Low-level functions are also provided for creating new + interfaces. + date_publication: '2021-02-01' + bug_reports: https://github.com/hafen/trelliscopejs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trelliscopejs + url_git: https://github.com/hafen/trelliscopejs +trelloR: + version: 0.8.0 + title: Access the Trello API + maintainer: Jakub Chromec + description: |- + An R client for the Trello API. Supports free-tier features such as + access to private boards, creating and updating cards and other resources, + and downloading data in a structured way. + date_publication: '2023-08-27' + bug_reports: https://github.com/jchrom/trelloR/issues + url: http://jchrom.github.io/trelloR/ + url_cran: https://CRAN.R-project.org/package=trelloR + url_git: https://github.com/jchrom/trelloR +tremendousr: + version: 1.0.0 + title: Easily Send Rewards and Incentives with 'Tremendous' from R + maintainer: Jonathan Trattner + description: |- + A slightly-opinionated R interface for the 'Tremendous' API (). + In addition to supporting GET and POST requests, 'tremendousr' has, dare I say, + tremendously intuitive functions for sending digital rewards and incentives directly from R. + date_publication: '2021-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tremendousr + url_git: '' +TrenchR: + version: 1.1.1 + title: Tools for Microclimate and Biophysical Ecology + maintainer: Lauren Buckley + description: Tools for translating environmental change into organismal response. + Microclimate models to vertically scale weather station data to organismal heights. + The biophysical modeling tools include both general models for heat flows and + specific models to predict body temperatures for a variety of ectothermic taxa. + Additional functions model and temporally partition air and soil temperatures + and solar radiation. Utility functions estimate the organismal and environmental + parameters needed for biophysical ecology. 'TrenchR' focuses on relatively simple + and modular functions so users can create transparent and flexible biophysical + models. Many functions are derived from Gates (1980) + and Campbell and Norman (1988) . + date_publication: '2023-09-13' + bug_reports: https://github.com/trenchproject/TrenchR/issues + url: https://trenchproject.github.io/TrenchR/ + url_cran: https://CRAN.R-project.org/package=TrenchR + url_git: https://github.com/trenchproject/TrenchR +trend: + version: 1.1.6 + title: Non-Parametric Trend Tests and Change-Point Detection + maintainer: Thorsten Pohlert + description: |- + The analysis of environmental data often requires + the detection of trends and change-points. + This package includes tests for trend detection + (Cox-Stuart Trend Test, Mann-Kendall Trend Test, + (correlated) Hirsch-Slack Test, + partial Mann-Kendall Trend Test, multivariate (multisite) + Mann-Kendall Trend Test, (Seasonal) Sen's slope, + partial Pearson and Spearman correlation trend test), + change-point detection (Lanzante's test procedures, + Pettitt's test, Buishand Range Test, + Buishand U Test, Standard Normal Homogeinity Test), + detection of non-randomness (Wallis-Moore Phase Frequency Test, + Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) + and the two sample Robust Rank-Order Distributional Test. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trend + url_git: '' +trendchange: + version: '1.2' + title: Innovative Trend Analysis and Time-Series Change Point Analysis + maintainer: Sandeep Kumar Patakamuri + description: |- + Innovative Trend Analysis is a graphical method to examine the trends in time series data. Sequential Mann-Kendall test uses the intersection of prograde and retrograde series to indicate the possible change point in time series data. Distribution free cumulative sum charts indicate location and significance of the change point in time series. + Zekai, S. (2011). . + Grayson, R. B. et al. (1996). Hydrological Recipes: Estimation Techniques in Australian Hydrology. Cooperative Research Centre for Catchment Hydrology, Australia, p. 125. + Sneyers, S. (1990). On the statistical analysis of series of observations. Technical note no 5 143, WMO No 725 415. Secretariat of the World Meteorological Organization, Geneva, 192 pp. + date_publication: '2022-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trendchange + url_git: '' +trendeval: + version: 0.1.0 + title: Evaluate Trending Models + maintainer: Thibaut Jombart + description: |- + Provides a coherent interface for evaluating models fit with the + trending package. This package is part of the RECON + () toolkit for outbreak analysis. + date_publication: '2023-04-11' + bug_reports: https://github.com/reconverse/trendeval/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trendeval + url_git: https://github.com/reconverse/trendeval +trending: + version: 0.1.0 + title: Model Temporal Trends + maintainer: Thibaut Jombart + description: |- + Provides a coherent interface to multiple modelling tools for + fitting trends along with a standardised approach for generating confidence + and prediction intervals. + date_publication: '2023-04-03' + bug_reports: https://github.com/reconverse/trending/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trending + url_git: https://github.com/reconverse/trending +TrendInTrend: + version: 1.1.3 + title: |- + Odds Ratio Estimation and Power Calculation for the Trend in + Trend Model + maintainer: Ashkan Ertefaie + description: Estimation of causal odds ratio and power calculation given trends + in exposure prevalence and outcome frequencies of stratified data. + date_publication: '2020-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrendInTrend + url_git: '' +TrendLSW: + version: 1.0.2 + title: Wavelet Methods for Analysing Locally Stationary Time Series + maintainer: Euan T. McGonigle + description: |- + Fitting models for, and simulation of, trend locally stationary + wavelet (TLSW) time series models, which take account of time-varying + trend and dependence structure in a univariate time series. The TLSW model, + and its estimation, is described in McGonigle, Killick and Nunes (2022a) + , (2022b) . New users will + likely want to start with the TLSW function. + date_publication: '2024-04-30' + bug_reports: https://github.com/EuanMcGonigle/TrendLSW/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TrendLSW + url_git: https://github.com/EuanMcGonigle/TrendLSW +trendsegmentR: + version: 1.3.0 + title: Linear Trend Segmentation + maintainer: Hyeyoung Maeng + description: |- + Performs the detection of linear trend changes for univariate time series + by implementing the bottom-up unbalanced wavelet transformation proposed by + H. Maeng and P. Fryzlewicz (2023). The estimated number and locations of the + change-points are returned with the piecewise-linear estimator for signal. + date_publication: '2023-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trendsegmentR + url_git: '' +TrendSLR: + version: '1.0' + title: |- + Estimating Trend, Velocity and Acceleration from Sea Level + Records + maintainer: Phil J Watson + description: |- + Analysis of annual average ocean water level time series, providing + improved estimates of trend (mean sea level) and associated real-time velocities and + accelerations. Improved trend estimates are based on singular spectrum analysis + methods. Various gap-filling options are included to accommodate incomplete time + series records. The package also includes a range of diagnostic tools to inspect + the components comprising the original time series which enables expert + interpretation and selection of likely trend components. A wide range of + screen and plot to file options are available in the package. + date_publication: '2019-08-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrendSLR + url_git: '' +TrendTM: + version: 2.0.19 + title: Trend of High-Dimensional Time Series Matrix Estimation + maintainer: Emilie Lebarbier + description: Matrix factorization for multivariate time series with both low rank + and temporal structures. The procedure is the one proposed by Alquier, P. and + Marie, N. Matrix factorization for multivariate time series analysis. Electronic + journal of statistics, 13(2), 4346-4366 (2019). + date_publication: '2023-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrendTM + url_git: '' +Trendtwosub: + version: 0.0.2 + title: Two Sample Order Free Trend Nonparametric Inference + maintainer: Yishi Wang Developer + description: Non-parametric trend comparison of two independent samples with sequential + subsamples. For more details, please refer to Wang, Stapleton, and Chen (2018) + . + date_publication: '2021-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Trendtwosub + url_git: '' +trendyy: + version: 0.1.1 + title: A Tidy Wrapper Around 'gtrendsR' + maintainer: Josiah Parry + description: |- + Access Google Trends information. This package provides a tidy wrapper to the 'gtrendsR' package. + Use four spaces when indenting paragraphs within the Description. + date_publication: '2019-05-20' + bug_reports: https://github.com/josiahparry/trendyy/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trendyy + url_git: https://github.com/josiahparry/trendyy +TRES: + version: 1.1.5 + title: Tensor Regression with Envelope Structure + maintainer: Jing Zeng + description: Provides three estimators for tensor response regression (TRR) and + tensor predictor regression (TPR) models with tensor envelope structure. The three + types of estimation approaches are generic and can be applied to any envelope + estimation problems. The full Grassmannian (FG) optimization is often associated + with likelihood-based estimation but requires heavy computation and good initialization; + the one-directional optimization approaches (1D and ECD algorithms) are faster, + stable and does not require carefully chosen initial values; the SIMPLS-type is + motivated by the partial least squares regression and is computationally the least + expensive. For details of TRR, see Li L, Zhang X (2017) . + For details of TPR, see Zhang X, Li L (2017) . + For details of 1D algorithm, see Cook RD, Zhang X (2016) . + For details of ECD algorithm, see Cook RD, Zhang X (2018) . + For more details of the package, see Zeng J, Wang W, Zhang X (2021) . + date_publication: '2021-10-20' + bug_reports: https://github.com/leozeng15/TRES/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TRES + url_git: https://github.com/leozeng15/TRES +TRexSelector: + version: 1.0.0 + title: |- + T-Rex Selector: High-Dimensional Variable Selection & FDR + Control + maintainer: Jasin Machkour + description: |- + Performs fast variable selection in high-dimensional settings while controlling the + false discovery rate (FDR) at a user-defined target level. The package is based on the paper + Machkour, Muma, and Palomar (2022) . + date_publication: '2024-02-23' + bug_reports: https://github.com/jasinmachkour/TRexSelector/issues + url: https://arxiv.org/abs/2110.06048 + url_cran: https://CRAN.R-project.org/package=TRexSelector + url_git: https://github.com/jasinmachkour/TRexSelector +Tri.Hierarchical.IBDs: + version: 1.0.0 + title: |- + Tri-Hierarchical IBDs (Tri- Hierarchical Incomplete Block + Designs) + maintainer: Ashutosh Dalal + description: Tri-hierarchical incomplete block design is defined as an arrangement + of v treatments each replicated r times in a three system of blocks if, each + block of the first system contains m_1 blocks of second system and each block + of the second system contains m_2 blocks of the third system. Ignoring the first + and second system of blocks, it leaves an incomplete block design with b_3 blocks + of size k_3i units; ignoring first and third system of blocks, it leaves an incomplete + block design with b_2 blocks each of size k_2i units and ignoring the second and + third system of blocks, it leaves an incomplete block design with b_1 blocks each + of size k_1 units. For dealing with experimental circumstances where there are + three nested sources of variation, a tri-hierarchical incomplete block design + can be adopted. Tri - hierarchical incomplete block designs can find application + potential in obtaining mating-environmental designs for breeding trials. To know + more about nested block designs one can refer Preece (1967) . + This package includes series1(), series2(), series3() and series4() functions. + This package generates tri-hierarchical designs with six component designs under + certain parameter restrictions. + date_publication: '2023-08-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tri.Hierarchical.IBDs + url_git: '' +triact: + version: 0.3.0 + title: Analyzing the Lying Behavior of Cows from Accelerometer Data + maintainer: Michael Simmler + description: |- + Assists in analyzing the lying behavior of cows from raw data + recorded with a triaxial accelerometer attached to the hind leg of a cow. Allows + the determination of common measures for lying behavior including total lying duration, the + number of lying bouts, and the mean duration of lying bouts. Further capabilities are the + description of lying laterality and the calculation of proxies for the level of physical + activity of the cow. Reference: Simmler M., Brouwers S. P. (2023) . + date_publication: '2023-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=triact + url_git: '' +TriadSim: + version: 0.3.0 + title: Simulating Triad Genomewide Genotypes + maintainer: Min Shi + description: Simulate genotypes for case-parent triads, case-control, and quantitative + trait samples with realistic linkage diequilibrium structure and allele frequency + distribution. For studies of epistasis one can simulate models that involve specific + SNPs at specific sets of loci, which we will refer to as "pathways". TriadSim + generates genotype data by resampling triad genotypes from existing data. The + details of the method is described in the manuscript under preparation "Simulating + Autosomal Genotypes with Realistic Linkage Disequilibrium and a Spiked in Genetic + Effect" Shi, M., Umbach, D.M., Wise A.S., Weinberg, C.R. + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TriadSim + url_git: '' +TrialEmulation: + version: 0.0.4.2 + title: Causal Analysis of Observational Time-to-Event Data + maintainer: Isaac Gravestock + description: |- + Implements target trial emulation methods to apply randomized + clinical trial design and analysis in an observational setting. Using + marginal structural models, it can estimate intention-to-treat and + per-protocol effects in emulated trials using electronic health + records. A description and application of the method can be found in + Danaei et al (2013) . + date_publication: '2025-02-21' + bug_reports: https://github.com/Causal-LDA/TrialEmulation/issues + url: https://causal-lda.github.io/TrialEmulation/ + url_cran: https://CRAN.R-project.org/package=TrialEmulation + url_git: https://github.com/Causal-LDA/TrialEmulation +trialr: + version: 0.1.6 + title: Clinical Trial Designs in 'rstan' + maintainer: Kristian Brock + description: |- + A collection of clinical trial designs and methods, implemented in + 'rstan' and R, including: the Continual Reassessment Method by O'Quigley et + al. (1990) ; EffTox by Thall & Cook (2004) + ; the two-parameter logistic method of + Neuenschwander, Branson & Sponer (2008) ; and the + Augmented Binary method by Wason & Seaman (2013) ; and + more. We provide functions to aid model-fitting and analysis. + The 'rstan' implementations may also serve as a cookbook to anyone looking + to extend or embellish these models. We hope that this package encourages + the use of Bayesian methods in clinical trials. There is a preponderance of + early phase trial designs because this is where Bayesian methods are used + most. If there is a method you would like implemented, please get in touch. + date_publication: '2023-03-12' + bug_reports: https://github.com/brockk/trialr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trialr + url_git: https://github.com/brockk/trialr +TrialSize: + version: 1.4.1 + title: |- + R Functions for Chapter 3,4,6,7,9,10,11,12,14,15 of Sample Size + Calculation in Clinical Research + maintainer: Vicky Qian Wu + description: |- + Functions and Examples in Sample Size Calculation in + Clinical Research. + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrialSize + url_git: '' +triangle: + version: '1.0' + title: |- + Distribution Functions and Parameter Estimates for the Triangle + Distribution + maintainer: Rob Carnell + description: Provides the "r, q, p, and d" distribution functions for the triangle + distribution. Also includes maximum likelihood estimation of parameters. + date_publication: '2022-12-13' + bug_reports: https://github.com/bertcarnell/triangle/issues + url: https://bertcarnell.github.io/triangle/ + url_cran: https://CRAN.R-project.org/package=triangle + url_git: '' +triangulation: + version: 0.5.0 + title: Determine Position of Observer + maintainer: Mathias Milfeldt + description: |- + Measuring angles between points in a landscape is much easier + than measuring distances. When the location of three points is known the + position of the observer can be determined based solely on the angles between + these points as seen by the observer. This task (known as triangulation) + however requires onerous calculations - these calculations are automated by this + package. + date_publication: '2016-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=triangulation + url_git: '' +triangulr: + version: 1.2.1 + title: High-Performance Triangular Distribution Functions + maintainer: Alvin Nursalim + description: |- + A collection of high-performance functions for the triangular + distribution that consists of the probability density function, cumulative + distribution function, quantile function, random variate generator, moment + generating function, characteristic function, and expected shortfall + function. References: Samuel Kotz, Johan Ren Van Dorp (2004) + and Acerbi, Carlo and Tasche, Dirk. (2002) + . + date_publication: '2021-05-27' + bug_reports: https://github.com/irkaal/triangulr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=triangulr + url_git: https://github.com/irkaal/triangulr/https://irkaal.github.io/triangulr/ +tricolore: + version: 1.2.4 + title: A Flexible Color Scale for Ternary Compositions + maintainer: Jonas Schöley + description: |- + Compositional data consisting of three-parts can be color + mapped with a ternary color scale. Such a scale is provided by + the tricolore packages with options for discrete and continuous + colors, mean-centering and scaling. See + Jonas Schöley (2021) "The centered ternary balance scheme. A technique + to visualize surfaces of unbalanced three-part compositions" + , + Jonas Schöley, Frans Willekens (2017) "Visualizing compositional data + on the Lexis surface" , and + Ilya Kashnitsky, Jonas Schöley (2018) "Regional population structures + at a glance" . + date_publication: '2024-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tricolore + url_git: https://github.com/jschoeley/tricolore +TriDimRegression: + version: 1.0.2 + title: Bayesian Statistics for 2D/3D Transformations + maintainer: Alexander (Sasha) Pastukhov + description: |- + Fits 2D and 3D geometric transformations via 'Stan' probabilistic programming engine ( + Stan Development Team (2021) ). Returns posterior distribution for individual + parameters of the fitted distribution. Allows for computation of LOO and WAIC information criteria + (Vehtari A, Gelman A, Gabry J (2017) ) as well as Bayesian R-squared + (Gelman A, Goodrich B, Gabry J, and Vehtari A (2018) ). + date_publication: '2023-09-13' + bug_reports: https://github.com/alexander-pastukhov/tridim-regression/issues + url: https://alexander-pastukhov.github.io/tridim-regression/ + url_cran: https://CRAN.R-project.org/package=TriDimRegression + url_git: https://github.com/alexander-pastukhov/tridim-regression +triebeard: + version: 0.4.1 + title: '''Radix'' Trees in ''Rcpp''' + maintainer: Os Keyes + description: |- + 'Radix trees', or 'tries', are key-value data structures optimised for efficient lookups, similar in purpose + to hash tables. 'triebeard' provides an implementation of 'radix trees' for use in R programming and in + developing packages with 'Rcpp'. + date_publication: '2023-03-04' + bug_reports: https://github.com/Ironholds/triebeard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=triebeard + url_git: https://github.com/Ironholds/triebeard/ +triggerstrategy: + version: 1.2.0 + title: Trigger Strategy in Clinical Trials + maintainer: Jiangtao Gou + description: |- + The trigger strategy is a general framework for a multistage statistical design with multiple hypotheses, allowing an adaptive selection of interim analyses. The selection of interim stages can be associated with some prespecified endpoints which serve as the trigger. This selection allows us to refine the critical boundaries in hypotheses testing procedures, and potentially increase the statistical power. This package includes several trial designs using the trigger strategy. + See Gou, J. (2023), "Trigger strategy in repeated tests on multiple hypotheses", Statistics in Biopharmaceutical Research, 15(1), 133-140, and Gou, J. (2022), "Sample size optimization and initial allocation of the significance levels in group sequential trials with multiple endpoints", Biometrical Journal, 64(2), 301-311. + date_publication: '2023-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=triggerstrategy + url_git: '' +tRigon: + version: 0.3.3 + title: Toolbox for Integrative Pathomics Analysis + maintainer: David Hoelscher + description: |- + Processing and analysis of pathomics, omics and other medical datasets. + 'tRigon' serves as a toolbox for descriptive and statistical analysis, correlations, + plotting and many other methods for exploratory analysis of high-dimensional datasets. + date_publication: '2024-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tRigon + url_git: '' +trigpoints: + version: 1.0.0 + title: |- + Data Set of Trig Points in Great Britain in British National + Grid Coordinates + maintainer: Phil Mike Jones + description: A complete data set of historic GB trig points in British National + Grid (OSGB36) coordinate reference system. Trig points (aka triangulation stations) + are fixed survey points used to improve the accuracy of map making in Great Britain + during the 20th Century. Trig points are typically located on hilltops so still + serve as a useful navigational aid for walkers and hikers today. + date_publication: '2018-09-21' + bug_reports: https://github.com/philmikejones/trigpoints/issues + url: https://philmikejones.github.io/trigpoints/ + url_cran: https://CRAN.R-project.org/package=trigpoints + url_git: '' +TriMatch: + version: 0.9.9 + title: Propensity Score Matching of Non-Binary Treatments + maintainer: Jason Bryer + description: Propensity score matching for non-binary treatments. + date_publication: '2017-12-06' + bug_reports: https://github.com/jbryer/TriMatch/issues + url: http://jason.bryer.org/TriMatch + url_cran: https://CRAN.R-project.org/package=TriMatch + url_git: http://github.com/jbryer/TriMatch +trimcluster: + version: 0.1-5 + title: Cluster Analysis with Trimming + maintainer: Valentin Todorov + description: Trimmed k-means clustering. The method is described in Cuesta-Albertos + et al. (1997) . + date_publication: '2020-02-09' + bug_reports: '' + url: http://www.homepages.ucl.ac.uk/~ucakche/ + url_cran: https://CRAN.R-project.org/package=trimcluster + url_git: '' +trimetStops: + version: 0.1.0 + title: |- + Information on all of the TriMet Stops in the Portland Metro + Area + maintainer: Grayson White + description: Information on all of the TriMet stops in the Portland Metro Area. + It includes information such as the longitude, latitude, cross street, and direction + of the stop. TriMet has catalogued these stops, 6880 in total. + date_publication: '2020-08-27' + bug_reports: https://github.com/graysonwhite/trimetStops/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trimetStops + url_git: https://github.com/graysonwhite/trimetStops +trimmer: + version: 0.8.1 + title: Trim an Object + maintainer: Lars Kjeldgaard + description: |- + A lightweight toolkit to reduce the size of a list object. The + object is minimized by recursively removing elements from the object + one-by-one. The process is constrained by a reference function call + specified by the user, where the target object is given as an argument. + The procedure will not allow elements to be removed from the object, that + will cause results from the function call to diverge from the function + call with the original object. + date_publication: '2019-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trimmer + url_git: '' +trimr: + version: 1.1.1 + title: An Implementation of Common Response Time Trimming Methods + maintainer: James Grange + description: |- + Provides various commonly-used response time trimming + methods, including the recursive / moving-criterion methods reported by + Van Selst and Jolicoeur (1994). By passing trimming functions raw data files, + the package will return trimmed data ready for inferential testing. + date_publication: '2022-05-05' + bug_reports: https://github.com/JimGrange/trimr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trimr + url_git: https://github.com/JimGrange/trimr +trinROC: + version: '0.7' + title: Statistical Tests for Assessing Trinormal ROC Data + maintainer: Reinhard Furrer + description: |- + Several statistical test functions as well as a function for exploratory data + analysis to investigate classifiers allocating individuals to one of three disjoint and + ordered classes. In a single classifier assessment the discriminatory power is compared + to classification by chance. In a comparison of two classifiers the null hypothesis + corresponds to equal discriminatory power of the two classifiers. + See also "ROC Analysis for Classification and Prediction in Practice" by Nakas, Bantis + and Gatsonis (2023), ISBN 9781482233704. + date_publication: '2024-10-04' + bug_reports: https://git.math.uzh.ch/reinhard.furrer/trinROC/-/issues + url: https://www.math.uzh.ch/pages/trinROC/ + url_cran: https://CRAN.R-project.org/package=trinROC + url_git: '' +TrioSGL: + version: 1.1.0 + title: |- + Trio Model with a Combination of Lasso and Group Lasso + Regularization + maintainer: Timo Stöcker + description: Fit a trio model via penalized maximum likelihood. The model is fit + for a path of values of the penalty parameter. This package is based on Noah Simon, + et al. (2011) . + date_publication: '2017-12-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrioSGL + url_git: '' +trip: + version: 1.10.0 + title: Tracking Data + maintainer: Michael D. Sumner + description: |- + Access and manipulate spatial tracking data, with straightforward + coercion from and to other formats. Filter for speed and create time spent + maps from tracking data. There are coercion methods to convert between 'trip' + and 'ltraj' from 'adehabitatLT', and between 'trip' and 'psp' and 'ppp' from + 'spatstat'. Trip objects can be created from raw or grouped data frames, and + from types in the 'sp', sf', 'amt', 'trackeR', 'mousetrap', and other packages, + Sumner, MD (2011) . + date_publication: '2023-06-29' + bug_reports: https://github.com/Trackage/trip/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trip + url_git: https://github.com/Trackage/trip +tripack: + version: 1.3-9.2 + title: Triangulation of Irregularly Spaced Data + maintainer: Albrecht Gebhardt + description: |- + A constrained two-dimensional Delaunay triangulation package + providing both triangulation and generation of voronoi mosaics of + irregular spaced data. + Please note that most of the functions are now also covered in package + interp, which is a re-implementation from scratch under a free license + based on a different triangulation algorithm. + date_publication: '2024-10-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tripack + url_git: '' +tripEstimation: + version: 0.0-46 + title: |- + Metropolis Sampler and Supporting Functions for Estimating + Animal Movement from Archival Tags and Satellite Fixes + maintainer: Michael D. Sumner + description: |- + Data handling and estimation functions for animal movement + estimation from archival or satellite tags. Helper functions are included + for making image summaries binned by time interval from Markov Chain Monte Carlo + simulations. + date_publication: '2023-04-21' + bug_reports: https://github.com/Trackage/tripEstimation + url: '' + url_cran: https://CRAN.R-project.org/package=tripEstimation + url_git: https://github.com/Trackage/tripEstimation +TripleR: + version: 1.5.4 + title: |- + Social Relation Model (SRM) Analyses for Single or Multiple + Groups + maintainer: Felix Schönbrodt + description: |- + Social Relation Model (SRM) analyses for single or multiple + round-robin groups are performed. These analyses are either based on one + manifest variable, one latent construct measured by two manifest variables, + two manifest variables and their bivariate relations, or two latent + constructs each measured by two manifest variables. Within-group t-tests + for variance components and covariances are provided for single groups. + For multiple groups two types of significance tests are provided: + between-groups t-tests (as in SOREMO) and enhanced standard errors based on + Lashley and Bond (1997) . Handling for missing values is provided. + date_publication: '2022-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TripleR + url_git: '' +triplesmatch: + version: 1.1.0 + title: |- + Match Triples Consisting of Two Controls and a Treated Unit or + Vice Versa + maintainer: Katherine Brumberg + description: |- + Attain excellent covariate balance by matching two treated units + and one control unit or vice versa within strata. Using such triples, as + opposed to also allowing pairs of treated and control units, + allows easier interpretation of the two possible + weights of observations and better insensitivity to unmeasured bias in the test + statistic. Using triples instead of matching in a fixed 1:2 or 2:1 ratio + allows for the match to be feasible in more situations. + The 'rrelaxiv' package, which provides an alternative solver for the underlying + network flow problems, carries an academic license and is not available on CRAN, but + may be downloaded from 'GitHub' at . + The 'Gurobi' commercial optimization software is required to use the two functions + [infsentrip()] and [triplesIP()]. These functions are not essential + to the main purpose of this package. A free academic license can be obtained at + . + The 'gurobi' R package can then be installed following + the instructions at . + date_publication: '2024-07-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=triplesmatch + url_git: '' +triplot: + version: 1.3.0 + title: Explaining Correlated Features in Machine Learning Models + maintainer: Katarzyna Pekala + description: |- + Tools for exploring effects of correlated features in predictive + models. The predict_triplot() function delivers instance-level explanations + that calculate the importance of the groups of explanatory variables. The + model_triplot() function delivers data-level explanations. The generic plot + function visualises in a concise way importance of hierarchical groups of + predictors. All of the the tools are model agnostic, therefore works for any + predictive machine learning models. Find more details in Biecek (2018) + . + date_publication: '2020-07-13' + bug_reports: https://github.com/ModelOriented/triplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=triplot + url_git: https://github.com/ModelOriented/triplot +tripsAndDipR: + version: 0.1.0 + title: |- + Identification of 2n and 3n Samples from Amplicon Sequencing + Data + maintainer: Thomas Delomas + description: |- + Uses read counts for biallelic single nucleotide polymorphisms (SNPs) + to compare the likelihoods for the observed read counts given that a sample is + either diploid or triploid. It allows parameters to be specified to account for + sequencing error rates and allelic bias. For details of the algorithm, please see + Delomas (2019) . + date_publication: '2019-08-28' + bug_reports: https://github.com/delomast/tripsAndDipR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tripsAndDipR + url_git: https://github.com/delomast/tripsAndDipR +triptych: + version: 0.1.3 + title: Diagnostic Graphics to Evaluate Forecast Performance + maintainer: Alexander I. Jordan + description: |- + Overall predictive performance is measured by a mean score + (or loss), which decomposes into miscalibration, discrimination, and + uncertainty components. The main focus is visualization of these distinct + and complementary aspects in joint displays. + See Dimitriadis, Gneiting, Jordan, Vogel (2024) . + date_publication: '2024-06-13' + bug_reports: '' + url: https://aijordan.github.io/triptych/ + url_cran: https://CRAN.R-project.org/package=triptych + url_git: https://github.com/aijordan/triptych/ +triversity: + version: '1.0' + title: Diversity Measures on Tripartite Graphs + maintainer: Robin Lamarche-Perrin + description: Computing diversity measures on tripartite graphs. This package first + implements a parametrized family of such diversity measures which apply on probability + distributions. Sometimes called "True Diversity", this family contains famous + measures such as the richness, the Shannon entropy, the Herfindahl-Hirschman index, + and the Berger-Parker index. Second, the package allows to apply these measures + on probability distributions resulting from random walks between the levels of + tripartite graphs. By defining an initial distribution at a given level of the + graph and a path to follow between the three levels, the probability of the walker's + position within the final level is then computed, thus providing a particular + instance of diversity to measure. + date_publication: '2017-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=triversity + url_git: '' +TRMF: + version: 0.2.1 + title: Temporally Regularized Matrix Factorization + maintainer: Chad Hammerquist + description: Functions to estimate temporally regularized matrix factorizations + (TRMF) for forecasting and imputing values in short but high-dimensional time + series. Uses regularized alternating least squares to compute the factorization, + allows for several types of constraints on matrix factors and natively handles + weighted and missing data. + date_publication: '2024-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TRMF + url_git: '' +tRnslate: + version: 0.0.3 + title: Translate R Code in Source Files + maintainer: Mario A. Martinez Araya + description: Evaluate inline or chunks of R code in template files and replace with + their output modifying the resulting template. + date_publication: '2021-07-13' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=tRnslate + url_git: '' +troopdata: + version: 1.0.2 + title: |- + Tools for Analyzing Cross-National Military Deployment and + Basing Data + maintainer: Michael Flynn + description: These functions generate data frames on troop deployments and military + basing using U.S. Department of Defense data on overseas military deployments. + This package provides functions for pulling country-year troop deployment and + basing data. Subsequent versions will hopefully include cross-national data on + deploying countries. + date_publication: '2024-09-10' + bug_reports: https://github.com/meflynn/troopdata/issues + url: https://meflynn.github.io/troopdata/ + url_cran: https://CRAN.R-project.org/package=troopdata + url_git: https://github.com/meflynn/troopdata +tropAlgebra: + version: 0.1.1 + title: Tropical Algebraic Functions + maintainer: Muhammad Kashif Hanif + description: 'It includes functions like tropical addition, tropical multiplication + for vectors and matrices. In tropical algebra, the tropical sum of two numbers + is their minimum and the tropical product of two numbers is their ordinary sum. + For more information see also I. Simon (1988) Recognizable sets with multiplicities + in the tropical semi ring: Volume 324 Lecture Notes I Computer Science, pages + 107-120 .' + date_publication: '2018-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tropAlgebra + url_git: '' +TropFishR: + version: 1.6.5 + title: Tropical Fisheries Analysis + maintainer: Tobias K. Mildenberger + description: |- + A compilation of fish stock assessment methods for the + analysis of length-frequency data in the context of data-poor + fisheries. Includes methods and examples included in the FAO + Manual by P. Sparre and S.C. Venema (1998), "Introduction to tropical fish + stock assessment" (), + as well as other more recent methods. + date_publication: '2024-10-31' + bug_reports: https://github.com/tokami/TropFishR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TropFishR + url_git: https://github.com/tokami/TropFishR +trotter: + version: '0.6' + title: |- + Pseudo-Vectors Containing All Permutations, Combinations and + Subsets of Objects Taken from a Vector. + maintainer: Richard Ambler + description: |- + Class definitions and constructors for pseudo-vectors containing + all permutations, combinations and subsets of objects taken from a vector. + Simplifies working with structures commonly encountered in combinatorics. + date_publication: '2014-09-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trotter + url_git: '' +trouBBlme4SolveR: + version: 0.1.2 + title: Troubles Solver for 'lme4' + maintainer: Iago Giné-Vázquez + description: The main function of the package aims to update 'lmer()'/'glmer()' + models depending on their warnings, so trying to avoid convergence and singularity + problems. + date_publication: '2024-08-20' + bug_reports: https://gitlab.com/iagogv/troubblme4solver/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trouBBlme4SolveR + url_git: https://gitlab.com/iagogv/troubblme4solver +TroublemakeR: + version: 0.0.1 + title: Generates Spatial Problems in R for 'AMPL' + maintainer: Derek Corcoran + description: |- + Provides methods for generating .dat files for use with the 'AMPL' + software using spatial data, particularly rasters. It includes support for + various spatial data formats and different problem types. By automating the + process of generating 'AMPL' datasets, this package can help streamline + optimization workflows and make it easier to solve complex optimization + problems. The methods implemented in this package are described in detail + in a publication by Fourer et al. (). + date_publication: '2023-04-03' + bug_reports: https://github.com/Sustainscapes/TroublemakeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TroublemakeR + url_git: https://github.com/Sustainscapes/TroublemakeR +TrtCombo.FactorialExp.SR: + version: 4.0.4 + title: |- + Generation of Treatment Combination (in Standard Order) in 2^n + Factorial Experiment + maintainer: Somjit Roy + description: Gives the required 2^n treatment combinations in a 2^n symmetric factorial + experiment in their respective standard order. + date_publication: '2021-05-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrtCombo.FactorialExp.SR + url_git: '' +trtf: + version: 0.4-3 + title: Transformation Trees and Forests + maintainer: Torsten Hothorn + description: |- + Recursive partytioning of transformation models with + corresponding random forest for conditional transformation models + as described in 'Transformation Forests' (Hothorn and Zeileis, 2021, ) + and 'Top-Down Transformation Choice' (Hothorn, 2018, ). + date_publication: '2025-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trtf + url_git: http://ctm.R-forge.R-project.org +trtswitch: + version: 0.1.3 + title: Treatment Switching + maintainer: Kaifeng Lu + description: Implements rank-preserving structural failure time model (RPSFTM), + iterative parameter estimation (IPE), inverse probability of censoring weights + (IPCW), and two-stage estimation (TSE) methods for treatment switching in randomized + clinical trials. + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=trtswitch + url_git: '' +trud: + version: 0.1.0 + title: Query the 'NHS TRUD API' + maintainer: Alasdair Warwick + description: |- + A convenient R interface to the 'National Health Service (NHS) + Technology Reference Update Distribution (TRUD) API'. Retrieve available + releases for items that you are subscribed to and download these with ease. + For more information on the API, see . + date_publication: '2024-07-23' + bug_reports: https://github.com/rmgpanw/trud/issues + url: https://rmgpanw.github.io/trud/ + url_cran: https://CRAN.R-project.org/package=trud + url_git: https://github.com/rmgpanw/trud +truelies: + version: 0.2.0 + title: |- + Bayesian Methods to Estimate the Proportion of Liars in Coin + Flip Experiments + maintainer: David Hugh-Jones + description: |- + Implements Bayesian methods, described in + Hugh-Jones (2019) , for estimating the + proportion of liars in coin flip-style experiments, where subjects + report a random outcome and are paid for reporting a "good" outcome. + date_publication: '2019-08-26' + bug_reports: https://github.com/hughjonesd/truelies/issues + url: '' + url_cran: https://CRAN.R-project.org/package=truelies + url_git: https://github.com/hughjonesd/truelies +TrueSkillThroughTime: + version: 0.1.1 + title: Skill Estimation Based on a Single Bayesian Network + maintainer: Gustavo Landfried + description: |2- + + Most estimators implemented by the video game industry cannot obtain reliable initial estimates nor guarantee comparability between distant estimates. TrueSkill Through Time solves all these problems by modeling the entire history of activities using a single Bayesian network allowing the information to propagate correctly throughout the system. This algorithm requires only a few iterations to converge, allowing millions of observations to be analyzed using any low-end computer. + The core ideas implemented in this project were developed by Dangauthier P, Herbrich R, Minka T, Graepel T (2007). "Trueskill through time: Revisiting the history of chess." . + date_publication: '2023-04-26' + bug_reports: https://github.com/glandfried/TrueSkillThroughTime.R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TrueSkillThroughTime + url_git: https://github.com/glandfried/TrueSkillThroughTime.R +truh: + version: 1.0.0 + title: Two-Sample Nonparametric Testing Under Heterogeneity + maintainer: Nathan Smith + description: |- + Implements the TRUH test statistic for two sample testing under heterogeneity. TRUH incorporates the underlying heterogeneity and imbalance in the samples, and provides a conservative test for the composite null hypothesis that the two samples arise from the + same mixture distribution but may differ with respect to the mixing weights. See Trambak Banerjee, Bhaswar B. Bhattacharya, Gourab Mukherjee Ann. Appl. Stat. 14(4): 1777-1805 (December 2020). for more details. + date_publication: '2021-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=truh + url_git: https://github.com/natesmith07/truh +TrumpetPlots: + version: 0.0.1.1 + title: Visualization of Genetic Association Studies + maintainer: Judit García-González + description: Visualizes the relationship between allele frequency and effect size + in genetic association studies. The input is a data frame containing association + results. The output is a plot with the effect size of risk variants in the Y axis, + and the allele frequency spectrum in the X axis. Corte et al (2023) . + date_publication: '2023-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TrumpetPlots + url_git: '' +truncAIPW: + version: 1.0.1 + title: |- + Doubly Robust Estimation under Covariate-Induced Dependent Left + Truncation + maintainer: Yuyao Wang + description: |- + Doubly robust estimation for the mean of an arbitrarily transformed survival time under covariate-induced dependent left truncation and noninformative right censoring. The functions truncAIPW(), truncAIPW_cen1(), and truncAIPW_cen2() compute the doubly robust estimators under the scenario without censoring and the two censoring scenarios, respectively. The package also contains three simulated data sets 'simu', 'simu_c1', and 'simu_c2', which are used to illustrate the usage of the functions in this package. + Reference: Wang, Y., Ying, A., Xu, R. (2022) "Doubly robust estimation under covariate-induced dependent left truncation" . + date_publication: '2023-08-31' + bug_reports: '' + url: https://arxiv.org/pdf/2208.06836.pdf + url_cran: https://CRAN.R-project.org/package=truncAIPW + url_git: '' +TruncatedNormal: + version: '2.3' + title: Truncated Multivariate Normal and Student Distributions + maintainer: Leo Belzile + description: A collection of functions to deal with the truncated univariate and + multivariate normal and Student distributions, described in Botev (2017) + and Botev and L'Ecuyer (2015) . + date_publication: '2024-07-08' + bug_reports: https://github.com/lbelzile/TruncatedNormal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TruncatedNormal + url_git: '' +truncdist: + version: 1.0-2 + title: Truncated Random Variables + maintainer: Frederick Novomestky + description: |- + A collection of tools to evaluate probability density + functions, cumulative distribution functions, quantile functions + and random numbers for truncated random variables. These functions are + provided to also compute the expected value and variance. Nadarajah + and Kotz (2006) developed most of the functions. QQ plots can be produced. + All the probability functions in the stats, stats4 and evd + packages are automatically available for truncation.. + date_publication: '2016-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=truncdist + url_git: '' +TruncExpFam: + version: 1.2.0 + title: Truncated Exponential Family + maintainer: Waldir Leoncio + description: |- + Handles truncated members from the exponential family of + probability distributions. Contains functions such as rtruncnorm() and + dtruncpois(), which are truncated versions of rnorm() and dpois() from the + stats package that also offer richer output containing, for example, the + distribution parameters. It also provides functions to retrieve the original + distribution parameters from a truncated sample by maximum-likelihood + estimation. + date_publication: '2024-09-26' + bug_reports: https://github.com/ocbe-uio/TruncExpFam/issues + url: https://ocbe-uio.github.io/TruncExpFam/ + url_cran: https://CRAN.R-project.org/package=TruncExpFam + url_git: '' +truncnorm: + version: 1.0-9 + title: Truncated Normal Distribution + maintainer: Olaf Mersmann + description: |- + Density, probability, quantile and random number + generation functions for the truncated normal distribution. + date_publication: '2023-03-20' + bug_reports: https://github.com/olafmersmann/truncnorm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=truncnorm + url_git: https://github.com/olafmersmann/truncnorm +truncnormbayes: + version: 0.0.3 + title: |- + Estimates Moments for a Truncated Normal Distribution using + 'Stan' + maintainer: Peter Solymos + description: |- + Finds the posterior modes for the mean and standard deviation for a + truncated normal distribution with one or two known truncation points. + The method used extends Bayesian methods for parameter estimation for a singly + truncated normal distribution under the Jeffreys prior (see Zhou X, + Giacometti R, Fabozzi FJ, Tucker AH (2014). "Bayesian estimation of truncated + data with applications to operational risk measurement". + ). This package additionally allows for a + doubly truncated normal distribution. + date_publication: '2023-08-23' + bug_reports: https://github.com/mathurlabstanford/truncnormbayes/issues + url: https://mathurlabstanford.github.io/truncnormbayes/ + url_cran: https://CRAN.R-project.org/package=truncnormbayes + url_git: https://github.com/mathurlabstanford/truncnormbayes +truncreg: + version: 0.2-5 + title: Truncated Gaussian Regression Models + maintainer: Yves Croissant + description: Estimation of models for truncated Gaussian variables by maximum likelihood. + date_publication: '2018-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=truncreg + url_git: http://R-Forge.R-project.org/projects/truncreg/ +truncSP: + version: 1.2.2 + title: Semi-parametric estimators of truncated regression models + maintainer: Anita Lindmark + description: Semi-parametric estimation of truncated linear regression models + date_publication: '2014-05-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=truncSP + url_git: '' +trust: + version: 0.1-8 + title: Trust Region Optimization + maintainer: Charles J. Geyer + description: |- + Does local optimization using two derivatives and trust regions. + Guaranteed to converge to local minimum of objective function. + date_publication: '2020-01-10' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/trust/ + url_cran: https://CRAN.R-project.org/package=trust + url_git: '' +trustedtimestamping: + version: 0.2.6 + title: Create Trusted Timestamps of Datasets and Files + maintainer: Peter Muller + description: |- + Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). + The package makes use of a free service provided by . + date_publication: '2019-07-30' + bug_reports: https://github.com/ttspackage/tts/issues + url: '' + url_cran: https://CRAN.R-project.org/package=trustedtimestamping + url_git: '' +trustOptim: + version: 0.8.7.3 + title: |- + Trust Region Optimization for Nonlinear Functions with Sparse + Hessians + maintainer: Michael Braun + description: |- + Trust region algorithm for nonlinear optimization. Efficient when + the Hessian of the objective function is sparse (i.e., relatively few nonzero + cross-partial derivatives). See Braun, M. (2014) . + date_publication: '2021-10-11' + bug_reports: https://github.com/braunm/trustOptim/issues + url: https://braunm.github.io/trustOptim/ + url_cran: https://CRAN.R-project.org/package=trustOptim + url_git: https://github.com/braunm/trustOptim/ +tryCatchLog: + version: 1.3.1 + title: Advanced 'tryCatch()' and 'try()' Functions + maintainer: Juergen Altfeld + description: |- + Advanced tryCatch() and try() functions for better error handling + (logging, stack trace with source code references and support for post-mortem analysis via dump files). + date_publication: '2021-10-25' + bug_reports: https://github.com/aryoda/tryCatchLog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tryCatchLog + url_git: https://github.com/aryoda/tryCatchLog +tryr: + version: 0.1.1 + title: Client/Server Error Handling for HTTP API Frameworks + maintainer: Peter Solymos + description: |- + Differentiate client errors (4xx) + from server errors (5xx) for the 'plumber' and + 'RestRserve' HTTP API frameworks. The package + also includes a built-in logging mechanism + to standard output (STDOUT) or standard error + (STDERR) depending on the log level. + date_publication: '2024-05-25' + bug_reports: https://github.com/analythium/tryr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tryr + url_git: https://github.com/analythium/tryr +TSA: + version: 1.3.1 + title: Time Series Analysis + maintainer: Kung-Sik Chan + description: |- + Contains R functions and datasets detailed in the book + "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan. + date_publication: '2022-07-05' + bug_reports: '' + url: https://stat.uiowa.edu/~kchan/TSA.htm + url_cran: https://CRAN.R-project.org/package=TSA + url_git: '' +tsallisqexp: + version: 0.9-5 + title: Tsallis q-Exp Distribution + maintainer: Christophe Dutang + description: Tsallis distribution also known as the q-exponential family distribution. + Provide distribution d, p, q, r functions, fitting and testing functions. Project + initiated by Paul Higbie and based on Cosma Shalizi's code. + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsallisqexp + url_git: '' +TSANN: + version: 0.1.0 + title: Time Series Artificial Neural Network + maintainer: Md Yeasin + description: |- + The best ANN structure for time series data analysis is a demanding need in the present era. + This package will find the best-fitted ANN model based on forecasting accuracy. + The optimum size of the hidden layers was also determined after determining the number of lags to be included. + This package has been developed using the algorithm of Paul and Garai (2021) . + date_publication: '2021-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSANN + url_git: '' +tsapp: + version: 1.0.4 + title: Time Series, Analysis and Application + maintainer: Rainer Schlittgen + description: Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) + "Angewandte Zeitreihenanalyse mit + R, 4. Auflage" . The package contains the time series and functions used therein. + It was developed over many years teaching courses about time series analysis. + date_publication: '2021-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsapp + url_git: '' +tsbox: + version: 0.4.2 + title: Class-Agnostic Time Series + maintainer: Christoph Sax + description: |- + Time series toolkit with identical behavior for all + time series classes: 'ts','xts', 'data.frame', 'data.table', 'tibble', 'zoo', + 'timeSeries', 'tsibble', 'tis' or 'irts'. Also converts reliably between these classes. + date_publication: '2024-10-22' + bug_reports: https://github.com/ropensci/tsbox/issues + url: https://docs.ropensci.org/tsbox/ + url_cran: https://CRAN.R-project.org/package=tsbox + url_git: https://github.com/ropensci/tsbox +tsBSS: + version: 1.0.0 + title: |- + Blind Source Separation and Supervised Dimension Reduction for + Time Series + maintainer: Markus Matilainen + description: Different estimators are provided to solve the blind source separation + problem for multivariate time series with stochastic volatility and supervised + dimension reduction problem for multivariate time series. Different functions + based on AMUSE and SOBI are also provided for estimating the dimension of the + white noise subspace. The package is fully described in Nordhausen, Matilainen, + Miettinen, Virta and Taskinen (2021) . + date_publication: '2021-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsBSS + url_git: '' +TSCI: + version: 3.0.4 + title: |- + Tools for Causal Inference with Possibly Invalid Instrumental + Variables + maintainer: David Carl + description: |- + Two stage curvature identification with machine learning for causal + inference in settings when instrumental variable regression is not suitable + because of potentially invalid instrumental variables. Based on Guo and + Buehlmann (2022) "Two Stage Curvature Identification with Machine Learning: + Causal Inference with Possibly Invalid Instrumental Variables" + . The vignette is available in Carl, Emmenegger, Bühlmann and Guo (2023) + "TSCI: two stage curvature identification for causal inference with + invalid instruments" . + date_publication: '2023-10-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSCI + url_git: https://github.com/dlcarl/TSCI +TSclust: + version: 1.3.1 + title: Time Series Clustering Utilities + maintainer: Pablo Montero Manso + description: A set of measures of dissimilarity between time series to perform time + series clustering. Metrics based on raw data, on generating models and on the + forecast behavior are implemented. Some additional utilities related to time series + clustering are also provided, such as clustering algorithms and cluster evaluation + metrics. + date_publication: '2020-07-22' + bug_reports: '' + url: http://www.jstatsoft.org/v62/i01/ + url_cran: https://CRAN.R-project.org/package=TSclust + url_git: '' +tscopula: + version: 0.3.9 + title: Time Series Copula Models + maintainer: Alexander McNeil + description: |- + Functions for the analysis of time series using copula models. + The package is based on methodology described in the following references. + McNeil, A.J. (2021) , + Bladt, M., & McNeil, A.J. (2021) , + Bladt, M., & McNeil, A.J. (2022) . + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tscopula + url_git: '' +tscount: + version: 1.4.3 + title: Analysis of Count Time Series + maintainer: Tobias Liboschik + description: Likelihood-based methods for model fitting and assessment, prediction + and intervention analysis of count time series following generalized linear models + are provided. Models with the identity and with the logarithmic link function + are allowed. The conditional distribution can be Poisson or Negative Binomial. + date_publication: '2020-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tscount + url_git: http://tscount.r-forge.r-project.org +TSCS: + version: 0.1.1 + title: Time Series Cointegrated System + maintainer: Tianjian Yang + description: |- + A set of functions to implement Time Series Cointegrated System (TSCS) + spatial interpolation and relevant data visualization. + date_publication: '2017-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSCS + url_git: '' +tsdataleaks: + version: 2.1.1 + title: Exploit Data Leakages in Time Series Forecasting Competitions + maintainer: Thiyanga S. Talagala + description: 'Forecasting competitions are of increasing importance as a mean to + learn best practices and gain knowledge. Data leakage is one of the most common + issues that can often be found in competitions. Data leaks can happen when the + training data contains information about the test data. For example: randomly + chosen blocks of time series are concatenated to form a new time series, scale-shifts, + repeating patterns in time series, white noise is added in the original time + series to form a new time series, etc. ''tsdataleaks'' package can be used to + detect data leakages in a collection of time series.' + date_publication: '2024-02-06' + bug_reports: https://github.com/thiyangt/tsdataleaks/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsdataleaks + url_git: https://github.com/thiyangt/tsdataleaks +tsdb: + version: 1.1-0 + title: Terribly-Simple Data Base for Time Series + maintainer: Enrico Schumann + description: |- + A terribly-simple data base for numeric + time series, written purely in R, so no external + database-software is needed. Series are stored in + plain-text files (the most-portable and enduring file + type) in CSV format. Timestamps are encoded using R's + native numeric representation for 'Date'/'POSIXct', + which makes them fast to parse, but keeps them + accessible with other software. The package provides + tools for saving and updating series in this + standardised format, for retrieving and joining data, + for summarising files and directories, and for + coercing series from and to other data types (such as + 'zoo' series). + date_publication: '2023-02-20' + bug_reports: '' + url: http://enricoschumann.net/R/packages/tsdb/ + url_cran: https://CRAN.R-project.org/package=tsdb + url_git: https://github.com/enricoschumann/tsdb +tsdecomp: + version: '0.2' + title: Decomposition of Time Series Data + maintainer: Javier López-de-Lacalle + description: |- + ARIMA-model-based decomposition of quarterly and + monthly time series data. + The methodology is developed and described, among others, in + Burman (1980) and + Hillmer and Tiao (1982) . + date_publication: '2017-01-04' + bug_reports: '' + url: https://jalobe.com + url_cran: https://CRAN.R-project.org/package=tsdecomp + url_git: '' +TSdeeplearning: + version: 0.1.0 + title: Deep Learning Model for Time Series Forecasting + maintainer: Ronit Jaiswal + description: RNNs are preferred for sequential data like time series, speech, text, + etc. but when dealing with long range dependencies, vanishing gradient problems + account for their poor performance. LSTM and GRU are effective solutions which + are nothing but RNN networks with the abilities of learning both short-term and + long-term dependencies. Their structural makeup enables them to remember information + for a long period without any difficulty. LSTM consists of one cell state and + three gates, namely, forget gate, input gate and output gate whereas GRU comprises + only two gates, namely, reset gate and update gate. This package consists of three + different functions for the application of RNN, LSTM and GRU to any time series + data for its forecasting. For method details see Jaiswal, R. et al. (2022). . + date_publication: '2022-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSdeeplearning + url_git: '' +tsdf: + version: 1.1-8 + title: Two-/Three-Stage Designs for Phase 1&2 Clinical Trials + maintainer: Wenchuan Guo + description: Calculate optimal Zhong's two-/three-stage Phase II designs (see Zhong + (2012) ). Generate Target Toxicity decision table + for Phase I dose-finding (two-/three-stage). This package also allows users to + run dose-finding simulations based on customized decision table. + date_publication: '2020-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsdf + url_git: '' +TSDFGS: + version: '2.0' + title: Training Set Determination for Genomic Selection + maintainer: Jen-Hsiang Ou + description: We propose an optimality criterion to determine the required training + set, r-score, which is derived directly from Pearson's correlation between the + genomic estimated breeding values and phenotypic values of the test set . + This package provides two main functions to determine a good training set and + its size. + date_publication: '2022-06-07' + bug_reports: https://github.com/oumarkme/TSDFGS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSDFGS + url_git: https://github.com/oumarkme/TSDFGS +tsdisagg2: + version: 0.1.0 + title: Time Series Disaggregation + maintainer: Jorge Vieira + description: 'Disaggregates low frequency time series data to higher frequency series. + Implements the following methods for temporal disaggregation: Boot, Feibes and + Lisman (1967) , Chow and Lin (1971) , + Fernandez (1981) and Litterman (1983) .' + date_publication: '2016-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsdisagg2 + url_git: '' +TSdisaggregation: + version: 2.0.0 + title: High-Dimensional Temporal Disaggregation + maintainer: Luke Mosley + description: First - Generates (potentially high-dimensional) high-frequency and + low-frequency series for simulation studies in temporal disaggregation; Second + - a toolkit utilizing temporal disaggregation and benchmarking techniques with + a low-dimensional matrix of indicator series previously proposed in Dagum and + Cholette (2006, ISBN:978-0-387-35439-2) ; and Third - novel techniques proposed + by Mosley, Gibberd and Eckley (2021) for disaggregating low-frequency + series in the presence of high-dimensional indicator matrices. + date_publication: '2022-05-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSdisaggregation + url_git: '' +TSdist: + version: 3.7.1 + title: Distance Measures for Time Series Data + maintainer: Usue Mori + description: A set of commonly used distance measures and some additional functions + which, although initially not designed for this purpose, can be used to measure + the dissimilarity between time series. These measures can be used to perform clustering, + classification or other data mining tasks which require the definition of a distance + measure between time series. U. Mori, A. Mendiburu and J.A. Lozano (2016), . + date_publication: '2022-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSdist + url_git: '' +tsdistributions: + version: 1.0.2 + title: Location Scale Standardized Distributions + maintainer: Alexios Galanos + description: Location-Scale based distributions parameterized in terms of mean, + standard deviation, skew and shape parameters and estimation using automatic differentiation. + Distributions include the Normal, Student and GED as well as their skewed variants + ('Fernandez and Steel'), the 'Johnson SU', and the Generalized Hyperbolic. Also + included is the semi-parametric piece wise distribution ('spd') with Pareto tails + and kernel interior. + date_publication: '2024-08-23' + bug_reports: '' + url: https://www.nopredict.com/packages/tsdistributions + url_cran: https://CRAN.R-project.org/package=tsdistributions + url_git: https://github.com/tsmodels/tsdistributions +TSDT: + version: 1.0.8 + title: Treatment-Specific Subgroup Detection Tool + maintainer: Brian Denton + description: Implements a method for identifying subgroups with superior response + relative to the overall sample. + date_publication: '2025-01-07' + bug_reports: https://github.com/EliLillyCo/CRAN_TSDT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSDT + url_git: https://github.com/EliLillyCo/CRAN_TSDT +tsDyn: + version: 11.0.5.2 + title: Nonlinear Time Series Models with Regime Switching + maintainer: Matthieu Stigler + description: 'Implements nonlinear autoregressive (AR) time series models. For univariate + series, a non-parametric approach is available through additive nonlinear AR. + Parametric modeling and testing for regime switching dynamics is available when + the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition + AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold + cointegration TVECM models with two or three regimes. Tests can be conducted for + TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).' + date_publication: '2024-10-31' + bug_reports: https://github.com/MatthieuStigler/tsDyn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsDyn + url_git: https://github.com/MatthieuStigler/tsDyn/wiki +TSE: + version: 0.1.0 + title: Total Survey Error + maintainer: Joshua Miller + description: 'Calculates total survey error (TSE) for one or more surveys, using + common scale-dependent and/or scale-independent metrics. On TSE, see: Weisberg, + Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) .' + date_publication: '2019-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSE + url_git: '' +TSEAL: + version: 0.1.3 + title: Time Series Analysis Library + maintainer: Iván Velasco + description: |- + The library allows to perform a multivariate time series + classification based on the use of Discrete Wavelet Transform for + feature extraction, a step wise discriminant to select the most + relevant features and finally, the use of a linear or quadratic + discriminant for classification. Note that all these steps can be done + separately which allows to implement new steps. Velasco, I., Sipols, + A., de Blas, C. S., Pastor, L., & Bayona, S. (2023) + . Percival, D. B., & Walden, A. T. + (2000,ISBN:0521640687). Maharaj, E. A., & Alonso, A. M. (2014) + . + date_publication: '2024-07-02' + bug_reports: https://github.com/vg-lab/TSEAL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSEAL + url_git: https://github.com/vg-lab/TSEAL +TSEind: + version: 0.1.0 + title: Total Survey Error (Independent Samples) + maintainer: Joshua Miller + description: 'Calculates total survey error (TSE) for one or more surveys, using + both scale-dependent and scale-independent metrics. Package works directly from + the data set, with no hand calculations required: just upload a properly structured + data set (see TESTIND and its documentation), properly input column names (see + functions documentation), and run your functions. For more on TSE, see: Weisberg, + Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) ; + Biemer, Paul et.al. (2017, ISBN:9781119041672); etc.' + date_publication: '2019-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSEind + url_git: '' +tsensembler: + version: 0.1.0 + title: Dynamic Ensembles for Time Series Forecasting + maintainer: Vitor Cerqueira + description: 'A framework for dynamically combining forecasting models for time + series forecasting predictive tasks. It leverages machine learning models from + other packages to automatically combine expert advice using metalearning and other + state-of-the-art forecasting combination approaches. The predictive methods receive + a data matrix as input, representing an embedded time series, and return a predictive + ensemble model. The ensemble use generic functions ''predict()'' and ''forecast()'' + to forecast future values of the time series. Moreover, an ensemble can be updated + using methods, such as ''update_weights()'' or ''update_base_models()''. A complete + description of the methods can be found in: Cerqueira, V., Torgo, L., Pinto, F., + and Soares, C. "Arbitrated Ensemble for Time Series Forecasting." to appear at: + Joint European Conference on Machine Learning and Knowledge Discovery in Databases. + Springer International Publishing, 2017; and Cerqueira, V., Torgo, L., and Soares, + C.: "Arbitrated Ensemble for Solar Radiation Forecasting." International Work-Conference + on Artificial Neural Networks. Springer, 2017 .' + date_publication: '2020-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsensembler + url_git: https://github.com/vcerqueira/tsensembler +tsentiment: + version: 1.0.5 + title: Fetching Tweet Data for Sentiment Analysis + maintainer: Hakki Sabah + description: |- + Which uses Twitter APIs for the necessary data in sentiment analysis, acts as a middleware with the approved Twitter Application. + A special access key is given to users who subscribe to the application with their Twitter account. With this special access key, the user defined keyword for sentiment analysis can be searched in twitter recent searches and results can be obtained( more information ). + In addition, a service named tsentiment-services has been developed to provide all these operations ( for more information ). + After the successful results obtained and in line with the permissions given by the user, the results of the analysis of the word cloud and bar graph saved in the user folder directory can be seen. In each analysis performed, the previous analysis visual result is deleted and this is the basic information you need to know as a practice rule. + 'tsentiment' package provides a free service that acts as a middleware for easy data extraction from Twitter, and in return, the user rate limit is reduced by 30 requests from the total limit and the remaining requests are used. These 30 requests are reserved for use in application analytics. For information about endpoints, you can refer to the limit information in the "GET search/tweets" row in the Endpoints column in the list at . + date_publication: '2022-11-02' + bug_reports: https://github.com/hakkisabah/tsentiment/issues + url: https://www.tsentiment.com + url_cran: https://CRAN.R-project.org/package=tsentiment + url_git: https://github.com/hakkisabah/tsentiment +TSEntropies: + version: '0.9' + title: Time Series Entropies + maintainer: Jiri Tomcala + description: Computes various entropies of given time series. This is the initial + version that includes ApEn() and SampEn() functions for calculating approximate + entropy and sample entropy. Approximate entropy was proposed by S.M. Pincus in + "Approximate entropy as a measure of system complexity", Proceedings of the National + Academy of Sciences of the United States of America, 88, 2297-2301 (March 1991). + Sample entropy was proposed by J. S. Richman and J. R. Moorman in "Physiological + time-series analysis using approximate entropy and sample entropy", American Journal + of Physiology, Heart and Circulatory Physiology, 278, 2039-2049 (June 2000). This + package also contains FastApEn() and FastSampEn() functions for calculating fast + approximate entropy and fast sample entropy. These are newly designed very fast + algorithms, resulting from the modification of the original algorithms. The calculated + values of these entropies are not the same as the original ones, but the entropy + trend of the analyzed time series determines equally reliably. Their main advantage + is their speed, which is up to a thousand times higher. A scientific article describing + their properties has been submitted to The Journal of Supercomputing and in present + time it is waiting for the acceptance. + date_publication: '2018-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSEntropies + url_git: '' +tseries: + version: 0.10-58 + title: Time Series Analysis and Computational Finance + maintainer: Kurt Hornik + description: Time series analysis and computational finance. + date_publication: '2024-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tseries + url_git: '' +tseriesChaos: + version: 0.1-13.1 + title: Analysis of Nonlinear Time Series + maintainer: Antonio Fabio Di Narzo + description: |- + Routines for the analysis of nonlinear time series. This + work is largely inspired by the TISEAN project, by Rainer + Hegger, Holger Kantz and Thomas Schreiber: + . + date_publication: '2019-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tseriesChaos + url_git: '' +tseriesEntropy: + version: 0.7-2 + title: Entropy Based Analysis and Tests for Time Series + maintainer: Simone Giannerini + description: Implements an Entropy measure of dependence based on the Bhattacharya-Hellinger-Matusita + distance. Can be used as a (nonlinear) autocorrelation/crosscorrelation function + for continuous and categorical time series. The package includes tests for serial + and cross dependence and nonlinearity based on it. Some routines have a parallel + version that can be used in a multicore/cluster environment. The package makes + use of S4 classes. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tseriesEntropy + url_git: '' +TSeriesMMA: + version: 0.1.1 + title: Multiscale Multifractal Analysis of Time Series Data + maintainer: Vishakh Padmakumar + description: |- + Multiscale multifractal analysis (MMA) (Gierałtowski et al., + 2012) is a time series analysis method, + designed to describe scaling properties of fluctuations within the signal + analyzed. The main result of this procedure is the so called Hurst surface + h(q,s) , which is a dependence of the local Hurst exponent h (fluctuation + scaling exponent) on the multifractal parameter q and the scale of observation s + (data window width). + date_publication: '2017-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSeriesMMA + url_git: '' +tseriesTARMA: + version: 0.5-1 + title: |- + Analysis of Nonlinear Time Series Through Threshold + Autoregressive Moving Average Models (TARMA) Models + maintainer: Simone Giannerini + description: 'Routines for nonlinear time series analysis based on Threshold Autoregressive + Moving Average (TARMA) models. It provides functions and methods for: TARMA model + fitting and forecasting, including robust estimators, see Goracci et al. JBES + (2025) ; tests for threshold effects, see Giannerini + et al. JoE (2024) , Goracci et al. Statistica + Sinica (2023) , Angelini et al. (2024) ; unit-root + tests based on TARMA models, see Chan et al. Statistica Sinica (2024) .' + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tseriesTARMA + url_git: '' +TSEtools: + version: 0.2.2 + title: Manage Data from Stock Exchange Markets + maintainer: Ali Saeb + description: Tools to perform some descriptive data analysis for assets. Manage + the portfolio and capital of assets. It also downloads and organizes data from + the Tehran Stock Exchange (TSE). + date_publication: '2023-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSEtools + url_git: '' +TSEwgt: + version: 0.1.0 + title: Total Survey Error Under Multiple, Different Weighting Schemes + maintainer: Joshua Miller + description: 'Calculates total survey error (TSE) for a survey under multiple, different + weighting schemes, using both scale-dependent and scale-independent metrics. Package + works directly from the data set, with no hand calculations required: just upload + a properly structured data set (see TESTWGT and its documentation), properly input + column names (see functions documentation), and run your functions. For more + on TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) + ; Biemer, Paul et.al. (2017, ISBN:9781119041672); etc.' + date_publication: '2019-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSEwgt + url_git: '' +TSF: + version: 0.1.1 + title: |- + Two Stage Forecasting (TSF) for Long Memory Time Series in + Presence of Structural Break + maintainer: Dr. Ranjit Kumar Paul + description: Forecasting of long memory time series in presence of structural break + by using TSF algorithm by Papailias and Dias (2015) . + date_publication: '2017-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSF + url_git: '' +tsfeatures: + version: 1.1.1 + title: Time Series Feature Extraction + maintainer: Rob Hyndman + description: Methods for extracting various features from time series data. The + features provided are those from Hyndman, Wang and Laptev (2013) , + Kang, Hyndman and Smith-Miles (2017) and + from Fulcher, Little and Jones (2013) . Features include + spectral entropy, autocorrelations, measures of the strength of seasonality and + trend, and so on. Users can also define their own feature functions. + date_publication: '2023-08-28' + bug_reports: https://github.com/robjhyndman/tsfeatures/issues + url: https://pkg.robjhyndman.com/tsfeatures/ + url_cran: https://CRAN.R-project.org/package=tsfeatures + url_git: https://github.com/robjhyndman/tsfeatures +tsfgrnn: + version: 1.0.5 + title: Time Series Forecasting Using GRNN + maintainer: Francisco Martinez + description: |- + A general regression neural network (GRNN) is a variant of a + Radial Basis Function Network characterized by a fast single-pass learning. + 'tsfgrnn' allows you to forecast time series using a GRNN model Francisco + Martinez et al. (2019) and Francisco + Martinez et al. (2022) . When the forecasting + horizon is higher than 1, two multi-step ahead forecasting strategies can be used. + The model built is autoregressive, that is, it is only based on the + observations of the time series. You can consult and plot how the + prediction was done. It is also possible to assess the forecasting accuracy + of the model using rolling origin evaluation. + date_publication: '2024-02-15' + bug_reports: https://github.com/franciscomartinezdelrio/tsfgrnn + url: '' + url_cran: https://CRAN.R-project.org/package=tsfgrnn + url_git: https://github.com/franciscomartinezdelrio/tsfgrnn +tsfknn: + version: 0.6.0 + title: Time Series Forecasting Using Nearest Neighbors + maintainer: Francisco Martinez + description: |- + Allows forecasting time series using nearest neighbors regression + Francisco Martinez, Maria P. Frias, Maria D. Perez-Godoy and Antonio J. + Rivera (2019) . When the forecasting horizon + is higher than 1, two multi-step ahead forecasting strategies can be used. + The model built is autoregressive, that is, it is only based on the + observations of the time series. The nearest neighbors used in a prediction + can be consulted and plotted. + date_publication: '2023-12-20' + bug_reports: https://github.com/franciscomartinezdelrio/tsfknn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsfknn + url_git: https://github.com/franciscomartinezdelrio/tsfknn +tsfngm: + version: 0.1.0 + title: Time Series Forecasting using Nonlinear Growth Models + maintainer: Mrinmoy Ray + description: Nonlinear growth models are extremely useful in gaining insight into + the underlying mechanism. These models are generally 'mechanistic,' with parameters + that have biological meaning. This package allows you to fit and forecast time + series data using nonlinear growth models. + date_publication: '2021-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsfngm + url_git: '' +tsgarch: + version: 1.0.3 + title: Univariate GARCH Models + maintainer: Alexios Galanos + description: Multiple flavors of the Generalized Autoregressive Conditional Heteroskedasticity + (GARCH) model with a large choice of conditional distributions. Methods for specification, + estimation, prediction, filtering, simulation, statistical testing and more. Represents + a partial re-write and re-think of 'rugarch', making use of automatic differentiation + for estimation. + date_publication: '2024-10-12' + bug_reports: https://github.com/tsmodels/tsgarch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsgarch + url_git: https://github.com/tsmodels/tsgarch +tsgc: + version: '0.0' + title: Time Series Methods Based on Growth Curves + maintainer: Craig Thamotheram + description: |- + The 'tsgc' package provides comprehensive tools for the analysis and forecasting of epidemic trajectories. + It is designed to model the progression of an epidemic over time while accounting for the various uncertainties + inherent in real-time data. Underpinned by a dynamic Gompertz model, the package adopts a state space approach, + using the Kalman filter for flexible and robust estimation of the non-linear growth pattern commonly observed in + epidemic data. The reinitialization feature enhances the model’s ability to adapt to the emergence of new waves. + The forecasts generated by the package are of value to public health officials and researchers who need to + understand and predict the course of an epidemic to inform decision-making. Beyond its application in public + health, the package is also a useful resource for researchers and practitioners in fields where the trajectories + of interest resemble those of epidemics, such as innovation diffusion. The package includes functionalities for + data preprocessing, model fitting, and forecast visualization, as well as tools for evaluating forecast accuracy. + The core methodologies implemented in 'tsgc' are based on well-established statistical techniques as described in + Harvey and Kattuman (2020) , Harvey and Kattuman (2021) + , and Ashby, Harvey, Kattuman, and Thamotheram (2024) + . + date_publication: '2024-08-26' + bug_reports: https://github.com/Craig-PT/tsgc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsgc + url_git: https://github.com/Craig-PT/tsgc +TSGS: + version: '1.0' + title: Trait Specific Gene Selection using SVM and GA + maintainer: Sudhir Srivastava + description: Obtaining relevant set of trait specific genes from gene expression + data is important for clinical diagnosis of disease and discovery of disease mechanisms + in plants and animals. This process involves identification of relevant genes + and removal of redundant genes as much as possible from a whole gene set. This + package returns the trait specific gene set from the high dimensional RNA-seq + count data by applying combination of two conventional machine learning algorithms, + support vector machine (SVM) and genetic algorithm (GA). GA is used to control + and optimize the subset of genes sent to the SVM for classification and evaluation. + Genetic algorithm uses repeated learning steps and cross validation over number + of possible solution and selects the best. The algorithm selects the set of genes + based on a fitness function that is obtained via support vector machines. Using + SVM as the classifier performance and the genetic algorithm for feature selection, + a set of trait specific gene set is obtained. + date_publication: '2021-09-08' + bug_reports: https://github.com/SudhirSrivastava/TSGS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSGS + url_git: https://github.com/SudhirSrivastava/TSGS +TSGSIS: + version: '0.1' + title: Two Stage-Grouped Sure Independence Screening + maintainer: Yao-Hwei Fang + description: To provide a high dimensional grouped variable selection approach for + detection of whole-genome SNP effects and SNP-SNP interactions, as described in + Fang et al. (2017, under review). + date_publication: '2017-04-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSGSIS + url_git: '' +TSHRC: + version: 0.1-6 + title: Two Stage Hazard Rate Comparison + maintainer: Charles J. Geyer + description: |- + Two-stage procedure compares hazard rate functions, + which may or may not cross each other. + date_publication: '2019-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSHRC + url_git: '' +tsibble: + version: 1.1.6 + title: Tidy Temporal Data Frames and Tools + maintainer: Earo Wang + description: |- + Provides a 'tbl_ts' class (the 'tsibble') for + temporal data in an data- and model-oriented format. The 'tsibble' + provides tools to easily manipulate and analyse temporal data, such as + filling in time gaps and aggregating over calendar periods. + date_publication: '2025-01-30' + bug_reports: https://github.com/tidyverts/tsibble/issues + url: https://tsibble.tidyverts.org + url_cran: https://CRAN.R-project.org/package=tsibble + url_git: '' +tsibbledata: + version: 0.4.1 + title: Diverse Datasets for 'tsibble' + maintainer: Mitchell O'Hara-Wild + description: Provides diverse datasets in the 'tsibble' data structure. These datasets + are useful for learning and demonstrating how tidy temporal data can tidied, visualised, + and forecasted. + date_publication: '2022-09-01' + bug_reports: https://github.com/tidyverts/tsibbledata/issues + url: https://tsibbledata.tidyverts.org/ + url_cran: https://CRAN.R-project.org/package=tsibbledata + url_git: https://github.com/tidyverts/tsibbledata/ +tsibbletalk: + version: 0.1.0 + title: Interactive Graphics for Tsibble Objects + maintainer: Earo Wang + description: |- + A shared tsibble data easily communicates between + htmlwidgets on both client and server sides, powered by 'crosstalk'. A + shiny module is provided to visually explore periodic/aperiodic + temporal patterns. + date_publication: '2020-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsibbletalk + url_git: '' +tsintermittent: + version: '1.10' + title: Intermittent Time Series Forecasting + maintainer: Nikolaos Kourentzes + description: Time series methods for intermittent demand forecasting. Includes Croston's + method and its variants (Moving Average, SBA), and the TSB method. Users can obtain + optimal parameters on a variety of loss functions, or use fixed ones (Kourenztes + (2014) ). Intermittent time series classification + methods and iMAPA that uses multiple temporal aggregation levels are also provided + (Petropoulos & Kourenztes (2015) ). + date_publication: '2022-07-18' + bug_reports: '' + url: https://kourentzes.com/forecasting/2014/06/23/intermittent-demand-forecasting-package-for-r/ + url_cran: https://CRAN.R-project.org/package=tsintermittent + url_git: '' +tsiR: + version: 0.4.3 + title: An Implementation of the TSIR Model + maintainer: Alexander D. Becker + description: An implementation of the time-series Susceptible-Infected-Recovered + (TSIR) model using a number of different fitting options for infectious disease + time series data. The manuscript based on this package can be found here . + The method implemented here is described by Finkenstadt and Grenfell (2000) . + date_publication: '2021-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsiR + url_git: '' +TSLA: + version: 0.1.1 + title: Tree-Guided Rare Feature Selection and Logic Aggregation + maintainer: Jianmin Chen + description: Implementation of the tree-guided feature selection and logic aggregation + approach introduced in Chen et al. (2024) . + The method enables the selection and aggregation of large-scale rare binary features + with a known hierarchical structure using a convex, linearly-constrained regularized + regression framework. The package facilitates the application of this method to + both linear regression and binary classification problems by solving the optimization + problem via the smoothing proximal gradient descent algorithm (Chen et al. (2012) + ). + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSLA + url_git: '' +TSLSTM: + version: 0.1.0 + title: Long Short Term Memory (LSTM) Model for Time Series Forecasting + maintainer: Dr. Ranjit Kumar Paul + description: The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network + (RNN) based architecture that is widely used for time series forecasting. Min-Max + transformation has been used for data preparation. Here, we have used one LSTM + layer as a simple LSTM model and a Dense layer is used as the output layer. Then, + compile the model using the loss function, optimizer and metrics. This package + is based on Keras and TensorFlow modules and the algorithm of Paul and Garai (2021) + . + date_publication: '2022-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSLSTM + url_git: '' +TSLSTMplus: + version: 1.0.6 + title: Long-Short Term Memory for Time-Series Forecasting, Enhanced + maintainer: Jaime Pizarroso Gonzalo + description: The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network + (RNN) based architecture that is widely used for time series forecasting. Customizable + configurations for the model are allowed, improving the capabilities and usability + of this model compared to other packages. This package is based on 'keras' and + 'tensorflow' modules and the algorithm of Paul and Garai (2021) . + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSLSTMplus + url_git: '' +tsLSTMx: + version: 0.1.0 + title: |- + Predict Time Series Using LSTM Model Including Exogenous + Variable to Denote Zero Values + maintainer: Sandip Garai + description: It is a versatile tool for predicting time series data using Long Short-Term + Memory (LSTM) models. It is specifically designed to handle time series with an + exogenous variable, allowing users to denote whether data was available for a + particular period or not. The package encompasses various functionalities, including + hyperparameter tuning, custom loss function support, model evaluation, and one-step-ahead + forecasting. With an emphasis on ease of use and flexibility, it empowers users + to explore, evaluate, and deploy LSTM models for accurate time series predictions + and forecasting in diverse applications. More details can be found in Garai and + Paul (2023) . + date_publication: '2024-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsLSTMx + url_git: '' +tsmarch: + version: 1.0.0 + title: Multivariate ARCH Models + maintainer: Alexios Galanos + description: Feasible Multivariate Generalized Autoregressive Conditional Heteroscedasticity + (GARCH) models including Dynamic Conditional Correlation (DCC), Copula GARCH and + Generalized Orthogonal GARCH with Generalized Hyperbolic distribution. A review + of some of these models can be found in Boudt, Galanos, Payseur and Zivot (2019) + . + date_publication: '2024-11-18' + bug_reports: https://github.com/tsmodels/tsmarch/issues + url: https://www.nopredict.com + url_cran: https://CRAN.R-project.org/package=tsmarch + url_git: https://github.com/tsmodels/tsmarch +tsmethods: + version: 1.0.2 + title: Time Series Methods + maintainer: Alexios Galanos + description: Generic methods for use in a time series probabilistic framework, allowing + for a common calling convention across packages. Additional methods for time series + prediction ensembles and probabilistic plotting of predictions is included. A + more detailed description is available at + which shows the currently implemented methods in the 'tsmodels' framework. + date_publication: '2024-09-22' + bug_reports: '' + url: https://www.nopredict.com/packages/tsmethods + url_cran: https://CRAN.R-project.org/package=tsmethods + url_git: https://github.com/tsmodels/tsmethods +TSMN: + version: 1.0.0 + title: Truncated Scale Mixtures of Normal Distributions + maintainer: Eraldo B. dos Anjos Filho + description: Return the first four moments of the SMN distributions (Normal, Student-t, + Pearson VII, Slash or Contaminated Normal). + date_publication: '2017-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSMN + url_git: '' +tsModel: + version: 0.6-2 + title: Time Series Modeling for Air Pollution and Health + maintainer: Roger D. Peng + description: Tools for specifying time series regression models. + date_publication: '2024-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsModel + url_git: '' +tsmp: + version: 0.4.15 + title: Time Series with Matrix Profile + maintainer: Francisco Bischoff + description: |- + A toolkit implementing the Matrix Profile concept + that was created by CS-UCR + . + date_publication: '2022-08-20' + bug_reports: https://github.com/matrix-profile-foundation/tsmp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsmp + url_git: https://github.com/matrix-profile-foundation/tsmp +TSMSN: + version: 0.0.1 + title: Truncated Scale Mixtures of Skew-Normal Distributions + maintainer: Eraldo B. dos Anjos Filho + description: Return the first four moments, estimation of parameters and sample + of the TSMSN distributions (Skew Normal, Skew t, Skew Slash or Skew Contaminated + Normal). + date_publication: '2019-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSMSN + url_git: '' +tsna: + version: 0.3.5 + title: Tools for Temporal Social Network Analysis + maintainer: Skye Bender-deMoll + description: Temporal SNA tools for continuous- and discrete-time longitudinal networks + having vertex, edge, and attribute dynamics stored in the 'networkDynamic' format. + This work was supported by grant R01HD68395 from the National Institute of Health. + date_publication: '2021-11-01' + bug_reports: https://github.com/statnet/tsna/issues + url: http://statnet.org/ + url_cran: https://CRAN.R-project.org/package=tsna + url_git: '' +tsne: + version: 0.1-3.1 + title: T-Distributed Stochastic Neighbor Embedding for R (t-SNE) + maintainer: Justin Donaldson + description: A "pure R" implementation of the t-SNE algorithm. + date_publication: '2022-03-28' + bug_reports: https://github.com/jdonaldson/rtsne/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsne + url_git: https://github.com/jdonaldson/rtsne/ +tsnet: + version: 0.1.0 + title: |- + Fitting, Comparing, and Visualizing Networks Based on Time + Series Data + maintainer: Björn S. Siepe + description: Fit, compare, and visualize Bayesian graphical vector autoregressive + (GVAR) network models using 'Stan'. These models are commonly used in psychology + to represent temporal and contemporaneous relationships between multiple variables + in intensive longitudinal data. Fitted models can be compared with a test based + on matrix norm differences of posterior point estimates to quantify the differences + between two estimated networks. See also Siepe, Kloft & Heck (2024) . + date_publication: '2024-02-28' + bug_reports: https://github.com/bsiepe/tsnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsnet + url_git: https://github.com/bsiepe/tsnet +tsoutliers: + version: 0.6-10 + title: Detection of Outliers in Time Series + maintainer: Javier López-de-Lacalle + description: |- + Detection of outliers in time series following the + Chen and Liu (1993) procedure. + Innovational outliers, additive outliers, level shifts, + temporary changes and seasonal level shifts are considered. + date_publication: '2024-02-12' + bug_reports: '' + url: https://jalobe.com + url_cran: https://CRAN.R-project.org/package=tsoutliers + url_git: '' +TSP: + version: 1.2-4 + title: Traveling Salesperson Problem (TSP) + maintainer: Michael Hahsler + description: |- + Basic infrastructure and some algorithms for the traveling + salesperson problem (also traveling salesman problem; TSP). + The package provides some simple algorithms and + an interface to the Concorde TSP solver and its implementation of the + Chained-Lin-Kernighan heuristic. The code for Concorde + itself is not included in the package and has to be obtained separately. + Hahsler and Hornik (2007) . + date_publication: '2023-04-04' + bug_reports: https://github.com/mhahsler/TSP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSP + url_git: https://github.com/mhahsler/TSP +tsPI: + version: 1.0.4 + title: |- + Improved Prediction Intervals for ARIMA Processes and Structural + Time Series + maintainer: Jouni Helske + description: |- + Prediction intervals for ARIMA and structural time series + models using importance sampling approach with uninformative priors for model + parameters, leading to more accurate coverage probabilities in frequentist + sense. Instead of sampling the future observations and hidden states of the + state space representation of the model, only model parameters are sampled, + and the method is based solving the equations corresponding to the conditional + coverage probability of the prediction intervals. This makes method relatively + fast compared to for example MCMC methods, and standard errors of prediction + limits can also be computed straightforwardly. + date_publication: '2023-09-04' + bug_reports: https://github.com/helske/tsPI/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsPI + url_git: '' +tspmeta: + version: '1.2' + title: |- + Instance Feature Calculation and Evolutionary Instance + Generation for the Traveling Salesman Problem + maintainer: Bernd Bischl + description: |- + Instance feature calculation and evolutionary instance generation + for the traveling salesman problem. Also contains code to "morph" two TSP + instances into each other. And the possibility to conveniently run a couple + of solvers on TSP instances. + date_publication: '2015-07-08' + bug_reports: https://github.com/berndbischl/tspmeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tspmeta + url_git: https://github.com/berndbischl/tspmeta +TSPred: + version: '5.1' + title: Functions for Benchmarking Time Series Prediction + maintainer: Rebecca Pontes Salles + description: Functions for defining and conducting a time series prediction process + including pre(post)processing, decomposition, modelling, prediction and accuracy + assessment. The generated models and its yielded prediction errors can be used + for benchmarking other time series prediction methods and for creating a demand + for the refinement of such methods. For this purpose, benchmark data from prediction + competitions may be used. + date_publication: '2021-01-21' + bug_reports: https://github.com/RebeccaSalles/TSPred/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSPred + url_git: https://github.com/RebeccaSalles/TSPred/wiki +tspredit: + version: 1.0.787 + title: Time Series Prediction Integrated Tuning + maintainer: Eduardo Ogasawara + description: Prediction is one of the most important activities while working with + time series. There are many alternative ways to model the time series. Finding + the right one is challenging to model them. Most data-driven models (either statistical + or machine learning) demand tuning. Setting them right is mandatory for good predictions. + It is even more complex since time series prediction also demands choosing a data + pre-processing that complies with the chosen model. Many time series frameworks + have features to build and tune models. The package differs as it provides a framework + that seamlessly integrates tuning data pre-processing activities with the building + of models. The package provides functions for defining and conducting time series + prediction, including data pre(post)processing, decomposition, tuning, modeling, + prediction, and accuracy assessment. More information is available at Izau et + al. . + date_publication: '2024-12-04' + bug_reports: '' + url: https://cefet-rj-dal.github.io/daltoolbox/ + url_cran: https://CRAN.R-project.org/package=tspredit + url_git: https://github.com/cefet-rj-dal/daltoolbox +tsqn: + version: 1.0.0 + title: |- + Applications of the Qn Estimator to Time Series (Univariate and + Multivariate) + maintainer: Higor Cotta + description: Time Series Qn is a package with applications of the Qn estimator of + Rousseeuw and Croux (1993) to univariate + and multivariate Time Series in time and frequency domains. More specifically, + the robust estimation of autocorrelation or autocovariance matrix functions from + Ma and Genton (2000, 2001) , + and Cotta (2017) are provided. The robust pseudo-periodogram + of Molinares et. al. (2009) is also given. This + packages also provides the M-estimator of the long-memory parameter d based on + the robustification of the GPH estimator proposed by Reisen et al. (2017) . + date_publication: '2017-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsqn + url_git: '' +TSrepr: + version: 1.1.0 + title: Time Series Representations + maintainer: Peter Laurinec + description: |- + Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. + Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also various normalisation methods (min-max, z-score, Box-Cox, Yeo-Johnson), + and forecasting accuracy measures are implemented. + date_publication: '2020-07-13' + bug_reports: https://github.com/PetoLau/TSrepr/issues + url: https://petolau.github.io/package/ + url_cran: https://CRAN.R-project.org/package=TSrepr + url_git: https://github.com/PetoLau/TSrepr/ +tsriadditive: + version: 1.0.0 + title: Two Stage Residual Inclusion Additive Hazards Estimator + maintainer: Andrew Ying + description: Additive hazards models with two stage residual inclusion method are + fitted under either survival data or competing risks data. The estimator incorporates + an instrumental variable and therefore can recover causal estimand in the presence + of unmeasured confounding under some assumptions. A.Ying, R. Xu and J. Murphy. + (2019) . + date_publication: '2020-04-28' + bug_reports: '' + url: https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8071 + url_cran: https://CRAN.R-project.org/package=tsriadditive + url_git: '' +tsrobprep: + version: 0.3.2 + title: Robust Preprocessing of Time Series Data + maintainer: Michał Narajewski + description: |- + Methods for handling the missing values outliers are introduced in + this package. The recognized missing values and outliers are replaced + using a model-based approach. The model may consist of both autoregressive + components and external regressors. The methods work robust and efficient, + and they are fully tunable. The primary motivation for writing the package + was preprocessing of the energy systems data, e.g. power plant production + time series, but the package could be used with any time series data. For + details, see Narajewski et al. (2021) . + date_publication: '2022-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsrobprep + url_git: '' +TSS.RESTREND: + version: 0.3.1 + title: Time Series Segmentation of Residual Trends + maintainer: Arden Burrell + description: 'Time Series Segmented Residual Trends is a method for the automated + detection of land degradation from remotely sensed vegetation and climate datasets. + TSS-RESTREND incorporates aspects of two existing degradation detection methods: + RESTREND which is used to control for climate variability, and BFAST which is + used to look for structural changes in the ecosystem. The full details of the + testing and justification of the TSS-RESTREND method (version 0.1.02) are published + in Burrell et al., (2017). . The changes to the + method introduced in version 0.2.03 focus on the inclusion of temperature as + an additional climate variable. This allows for land degradation assessment in + temperature limited drylands. A paper that details this work is currently under + review. There are also a number of bug fixes and speed improvements. Version 0.3.0 + introduces additional attribution for eCO2, climate change and climate variability + the details of which are in press in Burrell et al., (2020). The version under + active development and additional example scripts showing how the package can + be applied can be found at .' + date_publication: '2020-08-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSS.RESTREND + url_git: '' +tsSelect: + version: 0.1.8 + title: Execution of Time Series Models + maintainer: Avi Blinder + description: |- + Execution of various time series models and choosing the best one + either by a specific error metric or by picking the best one by majority vote. + The models are based on the "forecast" package, written by Prof. Rob Hyndman. + date_publication: '2016-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsSelect + url_git: '' +tssim: + version: 0.2.7 + title: Simulation of Daily and Monthly Time Series + maintainer: Daniel Ollech + description: |- + Flexible simulation of time series using time series + components, including seasonal, calendar and outlier effects. Main + algorithm described in Ollech, D. (2021) . + date_publication: '2024-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tssim + url_git: '' +TSsmoothing: + version: 0.1.0 + title: |- + Trend Estimation of Univariate and Bivariate Time Series with + Controlled Smoothness + maintainer: L. Leticia Ramirez-Ramirez + description: |- + It performs the smoothing approach provided by penalized least squares for univariate and bivariate time series, as proposed by Guerrero (2007) and Gerrero et al. (2017). + This allows to estimate the time series trend by controlling the amount of resulting (joint) smoothness. + --- + Guerrero, V.M (2007) . + Guerrero, V.M; Islas-Camargo, A. and Ramirez-Ramirez, L.L. (2017) . + date_publication: '2019-07-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSsmoothing + url_git: '' +TSSS: + version: 1.3.4-5 + title: Time Series Analysis with State Space Model + maintainer: Masami Saga + description: |- + Functions for statistical analysis, modeling and simulation of time + series with state space model, based on the methodology in Kitagawa + (2020, ISBN: 978-0-367-18733-0). + date_publication: '2023-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSSS + url_git: '' +TSstudio: + version: 0.1.7 + title: Functions for Time Series Analysis and Forecasting + maintainer: Rami Krispin + description: Provides a set of tools for descriptive and predictive analysis of + time series data. That includes functions for interactive visualization of time + series objects and as well utility functions for automation time series forecasting. + date_publication: '2023-08-09' + bug_reports: https://github.com/RamiKrispin/TSstudio/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TSstudio + url_git: https://github.com/RamiKrispin/TSstudio +TSSVM: + version: 0.1.0 + title: Time Series Forecasting using SVM Model + maintainer: Mrinmoy Ray + description: Implementation and forecasting univariate time series data using the + Support Vector Machine model. Support Vector Machine is one of the prominent machine + learning approach for non-linear time series forecasting. For method details see + Kim, K. (2003) . + date_publication: '2022-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSSVM + url_git: '' +tstests: + version: 1.0.1 + title: Time Series Goodness of Fit and Forecast Evaluation Tests + maintainer: Alexios Galanos + description: Goodness of Fit and Forecast Evaluation Tests for timeseries models. + Includes, among others, the Generalized Method of Moments (GMM) Orthogonality + Test of Hansen (1982), the Nyblom (1989) parameter constancy test, the sign-bias + test of Engle and Ng (1993), and a range of tests for value at risk and expected + shortfall evaluation. + date_publication: '2024-10-24' + bug_reports: '' + url: https://www.nopredict.com/packages/tstests + url_cran: https://CRAN.R-project.org/package=tstests + url_git: https://github.com/tsmodels/tstests +tstools: + version: 0.4.3 + title: A Time Series Toolbox for Official Statistics + maintainer: Stéphane Bisinger + description: |- + Plot official statistics' time series conveniently: automatic + legends, highlight windows, stacked bar chars with positive and + negative contributions, sum-as-line option, two y-axes with automatic + horizontal grids that fit both axes and other popular chart types. + 'tstools' comes with a plethora of defaults to let you plot without + setting an abundance of parameters first, but gives you the + flexibility to tweak the defaults. In addition to charts, 'tstools' + provides a super fast, 'data.table' backed time series I/O that allows + the user to export / import long format, wide format and transposed + wide format data to various file types. + date_publication: '2024-01-18' + bug_reports: https://github.com/KOF-ch/tstools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tstools + url_git: https://github.com/KOF-ch/tstools +TSTutorial: + version: 1.2.7 + title: Fitting and Predict Time Series Interactive Laboratory + maintainer: Alberto Lopez Moreno + description: Interactive laboratory of Time Series based in Box-Jenkins methodology. + date_publication: '2023-09-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSTutorial + url_git: '' +tsutils: + version: 0.9.4 + title: Time Series Exploration, Modelling and Forecasting + maintainer: Nikolaos Kourentzes + description: 'Includes: (i) tests and visualisations that can help the modeller + explore time series components and perform decomposition; (ii) modelling shortcuts, + such as functions to construct lagmatrices and seasonal dummy variables of various + forms; (iii) an implementation of the Theta method; (iv) tools to facilitate the + design of the forecasting process, such as ABC-XYZ analyses; and (v) "quality + of life" functions, such as treating time series for trailing and leading values.' + date_publication: '2023-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsutils + url_git: https://github.com/trnnick/tsutils/ +TSVC: + version: 1.7.2 + title: Tree-Structured Modelling of Varying Coefficients + maintainer: Moritz Berger + description: Fitting tree-structured varying coefficient models (Berger et al. (2019), + ). Simultaneous detection of covariates with varying + coefficients and effect modifiers that induce varying coefficients if they are + present. + date_publication: '2025-01-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TSVC + url_git: '' +tsvio: + version: 1.0.6 + title: Simple Utilities for Tab-Separated-Value (TSV) Files + maintainer: Mary A Rohrdanz + description: 'Utilities for rapidly loading specified rows and/or columns of data + from large tab-separated value (tsv) files (large: e.g. 1 GB file of 10000 x 10000 + matrix). ''tsvio'' is an R wrapper to ''C'' code that creates an index file for + the rows of the tsv file, and uses that index file to collect rows and/or columns + from the tsv file without reading the whole file into memory.' + date_publication: '2023-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsvio + url_git: https://github.com/MD-Anderson-Bioinformatics/tsvio +tsviz: + version: 0.1.0 + title: Easy and Interactive Time Series Visualization + maintainer: Emanuele Fabbiani + description: An 'RStudio' add-in to visualize time series. Time series are searched + in the global environment as data.frame objects with a column of type date and + a column of type numeric. Interactive charts are produced using 'plotly' package. + date_publication: '2019-07-26' + bug_reports: https://github.com/donlelef/tsviz/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tsviz + url_git: https://github.com/donlelef/tsviz +tsvr: + version: 1.0.2 + title: Timescale-Specific Variance Ratio for Use in Community Ecology + maintainer: Daniel C. Reuman + description: 'Tools for timescale decomposition of the classic variance ratio of + community ecology. Tools are as described in Zhao et al (in prep), extending commonly + used methods introduced by Peterson et al (1975) .' + date_publication: '2021-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsvr + url_git: '' +tswge: + version: 2.1.0 + title: Time Series for Data Science + maintainer: Bivin Sadler + description: Accompanies the texts Time Series for Data Science with R by Woodward, + Sadler and Robertson & Applied Time Series Analysis with R, 2nd edition by Woodward, + Gray, and Elliott. It is helpful for data analysis and for time series instruction. + date_publication: '2023-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tswge + url_git: '' +tsxtreme: + version: 0.3.4 + title: Bayesian Modelling of Extremal Dependence in Time Series + maintainer: Thomas Lugrin + description: Characterisation of the extremal dependence structure of time series, + avoiding pre-processing and filtering as done typically with peaks-over-threshold + methods. It uses the conditional approach of Heffernan and Tawn (2004) + which is very flexible in terms of extremal and asymptotic dependence structures, + and Bayesian methods improve efficiency and allow for deriving measures of uncertainty. + For example, the extremal index, related to the size of clusters in time, can + be estimated and samples from its posterior distribution obtained. + date_publication: '2024-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tsxtreme + url_git: '' +TT: + version: '0.98' + title: Display Tree Structured Data using Datatable Widget (DT) + maintainer: Michal Zielaskowski + description: |- + Wrapper of datatable widget, allowing display of data.tree objects. + All arguments of the data.tree become columns and each node is a row. + Adds column with buttons allowing folding and unfolding the levels. + date_publication: '2022-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TT + url_git: '' +TTAinterfaceTrendAnalysis: + version: 1.5.10 + title: Temporal Trend Analysis Graphical Interface + maintainer: David DEVREKER + description: |- + This interface was created to develop a standard procedure + to analyse temporal trend in the framework of the OSPAR convention. + The analysis process run through 4 successive steps : 1) manipulate your data, 2) + select the parameters you want to analyse, 3) build your regulated + time series, 4) perform diagnosis and analysis and 5) read the results. + Statistical analysis call other package function such as Kendall tests + or cusum() function. + date_publication: '2024-01-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TTAinterfaceTrendAnalysis + url_git: '' +ttbary: + version: 0.3-1 + title: Barycenter Methods for Spatial Point Patterns + maintainer: Dominic Schuhmacher + description: Computes a point pattern in R^2 or on a graph that is representative + of a collection of many data patterns. The result is an approximate barycenter + (also known as Fréchet mean or prototype) based on a transport-transform metric. + Possible choices include Optimal SubPattern Assignment (OSPA) and Spike Time metrics. + Details can be found in Müller, Schuhmacher and Mateu (2020) . + date_publication: '2022-11-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ttbary + url_git: '' +ttbbeer: + version: 1.1.0 + title: US Beer Statistics from TTB + maintainer: Jasmine Dumas + description: |- + U.S. Department of the Treasury, Alcohol and Tobacco Tax and + Trade Bureau (TTB) collects data and reports on monthly beer + industry production and operations. This data package includes + a collection of 10 years (2006 - 2015) worth of data on materials + used at U.S. breweries in pounds reported by the Brewer's Report + of Operations and the Quarterly Brewer's Report of Operations + forms, ready for data analysis. This package also includes historical + tax rates on distilled spirits, wine, beer, champagne, and tobacco + products as individual data sets. + date_publication: '2016-08-01' + bug_reports: https://github.com/jasdumas/ttbbeer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ttbbeer + url_git: https://github.com/jasdumas/ttbbeer +TTCA: + version: 0.1.1 + title: Transcript Time Course Analysis + maintainer: Marco Albrecht + description: 'The analysis of microarray time series promises a deeper insight into + the dynamics of the cellular response following stimulation. A common observation + in this type of data is that some genes respond with quick, transient dynamics, + while other genes change their expression slowly over time. The existing methods + for detecting significant expression dynamics often fail when the expression dynamics + show a large heterogeneity. Moreover, these methods often cannot cope with irregular + and sparse measurements. The method proposed here is specifically designed for + the analysis of perturbation responses. It combines different scores to capture + fast and transient dynamics as well as slow expression changes, and performs well + in the presence of low replicate numbers and irregular sampling times. The results + are given in the form of tables including links to figures showing the expression + dynamics of the respective transcript. These allow to quickly recognise the relevance + of detection, to identify possible false positives and to discriminate early and + late changes in gene expression. An extension of the method allows the analysis + of the expression dynamics of functional groups of genes, providing a quick overview + of the cellular response. The performance of this package was tested on microarray + data derived from lung cancer cells stimulated with epidermal growth factor (EGF). + Paper: Albrecht, Marco, et al. (2017).' + date_publication: '2017-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TTCA + url_git: '' +ttcg: + version: 1.0.1 + title: Three-Term Conjugate Gradient for Unconstrained Optimization + maintainer: Hao Chi Kiang + description: Some accelerated three-term conjugate gradient algorithms implemented + purely in R with the same user interface as optim(). The search directions and + acceleration scheme are described in Andrei, N. (2013) , + Andrei, N. (2013) , and Andrei, N (2015) . + Line search is done by a hybrid algorithm incorporating the ideas in Oliveia and + Takahashi (2020) and More and Thuente (1994) . + date_publication: '2021-10-05' + bug_reports: '' + url: https://git.sr.ht/~hckiang/ttcg + url_cran: https://CRAN.R-project.org/package=ttcg + url_git: '' +ttdo: + version: 0.0.10 + title: Extend 'tinytest' with 'diffobj' and 'tinysnapshot' + maintainer: Dirk Eddelbuettel + description: |- + The 'tinytest' package offers a light-weight zero-dependency unit-testing + framework to which this package adds support via the 'diffobj' package for 'diff'-style + textual comparison of R objects, as well as via 'tinysnapshot' package for visual + differences in plots. + date_publication: '2025-01-21' + bug_reports: https://github.com/eddelbuettel/ttdo/issues + url: https://dirk.eddelbuettel.com/code/ttdo.html + url_cran: https://CRAN.R-project.org/package=ttdo + url_git: https://github.com/eddelbuettel/ttdo/ +tth: + version: 4.16-0 + title: TeX-to-HTML/MathML Translators TtH/TtM + maintainer: Achim Zeileis + description: C source code and R wrappers for the tth/ttm TeX-to-HTML/MathML translators. + date_publication: '2024-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tth + url_git: '' +tTOlr: + version: 0.2.3 + title: Likelihood Ratio Statistics for One or Two Sample T-Tests + maintainer: John Maindonald + description: |- + Likelihood ratio and maximum likelihood statistics are provided + that can be used as alternatives to p-values Colquhoun (2017) + . Arguments can be either p-values or t-statistics. + together with degrees of freedom. For the function 'tTOlr', the argument + 'twoSided' has the default 'twoSided = TRUE'. + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tTOlr + url_git: '' +TTR: + version: 0.24.4 + title: Technical Trading Rules + maintainer: Joshua Ulrich + description: A collection of over 50 technical indicators for creating technical + trading rules. The package also provides fast implementations of common rolling-window + functions, and several volatility calculations. + date_publication: '2023-11-28' + bug_reports: https://github.com/joshuaulrich/TTR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TTR + url_git: https://github.com/joshuaulrich/TTR +TTS: + version: '1.1' + title: |- + Master Curve Estimates Corresponding to Time-Temperature + Superposition + maintainer: Antonio Meneses + description: |- + Time-Temperature Superposition analysis is often applied to frequency modulated data obtained by Dynamic + Mechanic Analysis (DMA) and Rheometry in the analytical chemistry and physics + areas. These techniques provide estimates of material mechanical properties + (such as moduli) at different temperatures in a wider range of time. This + package provides the Time-Temperature superposition Master Curve at a referred + temperature by the three methods: the two wider used methods, Arrhenius based + methods and WLF, and the newer methodology based on derivatives procedure. + The Master Curve is smoothed by B-splines basis. The package output is composed + of plots of experimental data, horizontal and vertical shifts, TTS data, and TTS + data fitted using B-splines with bootstrap confidence intervals. + date_publication: '2023-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TTS + url_git: '' +ttScreening: + version: '1.6' + title: |- + Genome-Wide DNA Methylation Sites Screening by Use of Training + and Testing Samples + maintainer: Meredith Ray + description: A screening process utilizing training and testing samples to filter + out uninformative DNA methylation sites. Surrogate variables (SVs) of DNA methylation + are included in the filtering process to explain unknown factor effects. + date_publication: '2018-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ttScreening + url_git: '' +ttservice: + version: 0.4.1 + title: A Service for Tidy Transcriptomics Software Suite + maintainer: Stefano Mangiola + description: It provides generic methods that are used by more than one package, + avoiding conflicts. This package will be imported by 'tidySingleCellExperiment' + and 'tidyseurat'. + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ttservice + url_git: '' +ttt: + version: '1.0' + title: The Table Tool + maintainer: Benjamin Rich + description: |- + Create structured, formatted HTML tables of in a flexible and + convenient way. + date_publication: '2021-05-07' + bug_reports: https://github.com/benjaminrich/ttt/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ttt + url_git: https://github.com/benjaminrich/ttt +tttplot: + version: 1.1.1 + title: Time to Target Plot + maintainer: Carlos A. Martinez + description: |- + Implementation of Time to Target plot based on the work + of Ribeiro and Rosseti (2015) , + that describe a numerical method that gives the probability of + an algorithm A finds a solution at least as good as a given + target value in smaller computation time than algorithm B. + date_publication: '2016-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tttplot + url_git: '' +ttutils: + version: 1.0-1.1 + title: Utility Functions + maintainer: Thorn Thaler + description: Contains some auxiliary functions. + date_publication: '2022-04-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ttutils + url_git: '' +tuber: + version: 0.9.9 + title: Client for the YouTube API + maintainer: Gaurav Sood + description: |- + Get comments posted on YouTube videos, information on how many + times a video has been liked, search for videos with particular content, and + much more. You can also scrape captions from a few videos. To learn more about + the YouTube API, see . + date_publication: '2020-06-11' + bug_reports: http://github.com/soodoku/tuber/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tuber + url_git: http://github.com/soodoku/tuber +tubern: + version: 0.1.0 + title: R Client for the YouTube Analytics and Reporting API + maintainer: Gaurav Sood + description: |- + Get statistics and reports from YouTube. To learn more about + the YouTube Analytics and Reporting API, see . + date_publication: '2017-04-13' + bug_reports: http://github.com/soodoku/tubern/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tubern + url_git: http://github.com/soodoku/tubern +tuckerR.mmgg: + version: 1.5.1 + title: Three-Mode Principal Components Analysis + maintainer: Gustavo Gimenez + description: |- + Performs Three-Mode Principal Components Analysis, + which carries out Tucker Models. + date_publication: '2018-06-14' + bug_reports: https://github.com/gusart/tuckerR_mmgg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tuckerR.mmgg + url_git: https://github.com/gusart/tuckerR_mmgg +TUFLOWR: + version: 0.1.1 + title: Helper Functions for 'TUFLOW FV' Models + maintainer: Matt Gibbs + description: |- + Helper functions for 'TUFLOW FV' models. Current functionality includes reading in and plotting + output POINTS files and generating initial conditions based on point observations. + date_publication: '2023-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TUFLOWR + url_git: +tufte: + version: '0.13' + title: Tufte's Styles for R Markdown Documents + maintainer: Christophe Dervieux + description: |- + Provides R Markdown output formats to use Tufte styles for + PDF and HTML output. + date_publication: '2023-06-22' + bug_reports: https://github.com/rstudio/tufte/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tufte + url_git: https://github.com/rstudio/tufte +tufterhandout: + version: 1.2.1 + title: Tufte-style html document format for rmarkdown + maintainer: Michael C Sachs + description: |- + Custom template and output formats for use with rmarkdown. Produce + Edward Tufte-style handouts in html formats with full support for rmarkdown + features + date_publication: '2015-01-27' + bug_reports: http://github.com/sachsmc/tufterhandout/issues + url: http://sachsmc.github.io/tufterhandout + url_cran: https://CRAN.R-project.org/package=tufterhandout + url_git: '' +tugboat: + version: 0.1.1 + title: Build a Docker Image from a Directory or Project + maintainer: Daniel Molitor + description: |- + Simple utilities to generate a Dockerfile from a directory or + project, build the corresponding Docker image, and push the image to + DockerHub. + date_publication: '2024-12-17' + bug_reports: '' + url: https://www.dmolitor.com/tugboat/ + url_cran: https://CRAN.R-project.org/package=tugboat + url_git: '' +TukeyC: + version: 1.3-42 + title: Conventional Tukey Test + maintainer: Ivan Bezerra Allaman + description: |- + Perform the conventional Tukey test from formula, + lm, aov, aovlist and lmer objects. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TukeyC + url_git: https://github.com/jcfaria/TukeyC +TukeyGH77: + version: 0.1.3 + title: Tukey g-&-h Distribution + maintainer: Tingting Zhan + description: |- + Functions for density, cumulative density, quantile and simulation + of Tukey g-and-h (1977) distributions. The quantile-based + transformation (Hoaglin 1985 ) and its + reverse transformation, as well as the letter-value based estimates + (Hoaglin 1985), are also provided. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TukeyGH77 + url_git: '' +TukeyRegion: + version: 0.1.6.3 + title: Tukey Region and Median + maintainer: Pavlo Mozharovskyi + description: |- + Tukey regions are polytopes in the Euclidean space, viz. + upper-level sets of the Tukey depth function on given data. The bordering + hyperplanes of a Tukey region are computed as well as its vertices, facets, + centroid, and volume. In addition, the Tukey median set, which is the + non-empty Tukey region having highest depth level, and its barycenter + (= Tukey median) are calculated. Tukey regions are visualized in dimension + two and three. For details see Liu, Mosler, and Mozharovskyi + (2019, ). See file LICENSE.note for + additional license information. + date_publication: '2023-04-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TukeyRegion + url_git: '' +tukeytrend: + version: '0.7' + title: Tukeys Trend Test via Multiple Marginal Models + maintainer: Frank Schaarschmidt + description: Provides wrapper functions to the multiple marginal model function + mmm() of package 'multcomp' to implement the trend test of Tukey, Ciminera and + Heyse (1985) for general parametric models. + date_publication: '2020-03-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tukeytrend + url_git: '' +TULIP: + version: 1.0.2 + title: A Toolbox for Linear Discriminant Analysis with Penalties + maintainer: Yuqing Pan + description: Integrates several popular high-dimensional methods based on Linear + Discriminant Analysis (LDA) and provides a comprehensive and user-friendly toolbox + for linear, semi-parametric and tensor-variate classification as mentioned in + Yuqing Pan, Qing Mai and Xin Zhang (2019) . Functions are included + for covariate adjustment, model fitting, cross validation and prediction. + date_publication: '2021-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TULIP + url_git: '' +tumgr: + version: 0.0.4 + title: Tumor Growth Rate Analysis + maintainer: Julia Wilkerson + description: A tool to obtain tumor growth rates from clinical trial patient data. Output + includes individual and summary data for tumor growth rate estimates as well as + optional plots of the observed and predicted tumor quantity over time. + date_publication: '2016-02-04' + bug_reports: '' + url: https://wilkersj.shinyapps.io/tumgrShiny + url_cran: https://CRAN.R-project.org/package=tumgr + url_git: https://github.com/wilkersj/tumgr +tune: + version: 1.3.0 + title: Tidy Tuning Tools + maintainer: Max Kuhn + description: |- + The ability to tune models is important. 'tune' contains + functions and classes to be used in conjunction with other + 'tidymodels' packages for finding reasonable values of + hyper-parameters in models, pre-processing methods, and + post-processing steps. + date_publication: '2025-02-21' + bug_reports: https://github.com/tidymodels/tune/issues + url: https://tune.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=tune + url_git: https://github.com/tidymodels/tune +TunePareto: + version: 2.5.3 + title: Multi-Objective Parameter Tuning for Classifiers + maintainer: Hans Kestler + description: Generic methods for parameter tuning of classification algorithms using + multiple scoring functions (Muessel et al. (2012), ). + date_publication: '2023-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TunePareto + url_git: '' +tuneR: + version: 1.4.7 + title: Analysis of Music and Speech + maintainer: Uwe Ligges + description: |- + Analyze music and speech, extract features like MFCCs, handle wave files and their representation in various ways, read mp3, read midi, perform steps of a transcription, ... + Also contains functions ported from the 'rastamat' 'Matlab' package. + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tuneR + url_git: '' +tuneRanger: + version: '0.7' + title: Tune Random Forest of the 'ranger' Package + maintainer: Philipp Probst + description: Tuning random forest with one line. The package is mainly based on + the packages 'ranger' and 'mlrMBO'. + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tuneRanger + url_git: '' +tuple: + version: 0.4-02 + title: Find every match, or orphan, duplicate, triplicate, or otherreplicated + values + maintainer: Emmanuel Lazaridis + description: Functions to find all matches or non-matches, orphans, andduplicate + or other replicated elements. + date_publication: '2014-10-31' + bug_reports: '' + url: http://statistics.lazaridis.eu + url_cran: https://CRAN.R-project.org/package=tuple + url_git: '' +turboEM: + version: '2021.1' + title: |- + A Suite of Convergence Acceleration Schemes for EM, MM and Other + Fixed-Point Algorithms + maintainer: Ravi Varadhan + description: |- + Algorithms for accelerating the convergence of slow, + monotone sequences from smooth, contraction mapping such as the + EM and MM algorithms. It can be used to accelerate any smooth, + linearly convergent acceleration scheme. A tutorial style + introduction to this package is available in a vignette on the + CRAN download page or, when the package is loaded in an R + session, with vignette("turboEM"). + date_publication: '2021-08-05' + bug_reports: '' + url: https://coah.jhu.edu/people/Faculty_personal_Pages/Varadhan.html + url_cran: https://CRAN.R-project.org/package=turboEM + url_git: '' +turkeyelections: + version: 0.1.2 + title: The Most Comprehensive R Package for Turkish Election Results + maintainer: Ozancan Ozdemir + description: Includes the results of general, local, and presidential elections + held in Turkey between 1995 and 2023, broken down by provinces and overall national + results. It facilitates easy processing of this data and the creation of visual + representations based on these election results. + date_publication: '2024-04-30' + bug_reports: https://github.com/ozancanozdemir/turkeyelections/issues + url: '' + url_cran: https://CRAN.R-project.org/package=turkeyelections + url_git: https://github.com/ozancanozdemir/turkeyelections +turner: + version: 0.1.9 + title: Turn Vectors and Lists of Vectors into Indexed Structures + maintainer: Frederic Bertrand + description: |- + Package designed for working with vectors and lists of vectors, + mainly for turning them into other indexed data structures. + date_publication: '2024-04-04' + bug_reports: https://github.com/fbertran/turner/issues/ + url: https://fbertran.github.io/turner/ + url_cran: https://CRAN.R-project.org/package=turner + url_git: https://github.com/fbertran/turner/ +TurtleGraphics: + version: 1.0-8 + title: Turtle Graphics + maintainer: Barbara Zogala-Siudem + description: |- + An implementation of turtle graphics + . + Turtle graphics comes from Papert's language Logo and has + been used to teach concepts of computer programming. + date_publication: '2018-02-14' + bug_reports: https://github.com/gagolews/TurtleGraphics/issues + url: http://www.gagolewski.com/software/TurtleGraphics/ + url_cran: https://CRAN.R-project.org/package=TurtleGraphics + url_git: '' +Tushare: + version: 0.1.4 + title: Interface to 'Tushare Pro' API + maintainer: Feifei ZHANG + description: |- + Helps the R users to get data from 'Tushare Pro'. + 'Tushare Pro' is a platform as well as a community with a lot of staffs working in financial area. + We support financial data such as stock price, financial report statements and digital coins data. + date_publication: '2022-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Tushare + url_git: '' +tutorial.helpers: + version: 0.3.1 + title: Helper Functions for Creating Tutorials + maintainer: David Kane + description: |- + Helper functions for creating, editing, and testing tutorials + created with the 'learnr' package. Provides a simple method for allowing + students to download their answers to tutorial questions. For examples + of its use, see the 'r4ds.tutorials' package. + date_publication: '2024-12-07' + bug_reports: https://github.com/PPBDS/tutorial.helpers/issues + url: https://ppbds.github.io/tutorial.helpers/ + url_cran: https://CRAN.R-project.org/package=tutorial.helpers + url_git: https://github.com/PPBDS/tutorial.helpers +TUvalues: + version: 0.1.0 + title: |- + Tools for Calculating Allocations in Game Theory using Exact and + Approximated Methods + maintainer: Maria D. Guillen + description: |- + The main objective of cooperative games is to allocate a good among + the agents involved. This package includes the most well-known allocation + rules, i.e., the Shapley value, the Banzhaf value, the egalitarian rule, and + the equal surplus division value. In addition, it considers the point of view + of a priori unions (situations in which agents can form coalitions). For this + purpose, the package includes the Owen value, the Banzhaf-Owen value, and the + corresponding extensions of the egalitarian rules. All these values can be + calculated exactly or estimated by sampling. + date_publication: '2024-09-10' + bug_reports: https://github.com/mariaguilleng/TUvalues/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TUvalues + url_git: https://github.com/mariaguilleng/TUvalues +TUWmodel: + version: 1.1-1 + title: |- + Lumped/Semi-Distributed Hydrological Model for Education + Purposes + maintainer: Alberto Viglione + description: |- + The model, developed at the Vienna University of Technology, is a lumped conceptual rainfall-runoff model, following the structure of the HBV model. + The model can also be run in a semi-distributed fashion and with dual representation of soil layer. + The model runs on a daily or shorter time step and consists of a snow routine, a soil moisture routine and a flow routing routine. + See Parajka, J., R. Merz, G. Bloeschl (2007) Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments, Hydrological Processes, 21, 435-446. + date_publication: '2020-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TUWmodel + url_git: '' +tv: + version: 2.0.2 + title: Tools for Creating Time-Varying Datasets + maintainer: Ethan Heinzen + description: |- + Create a time-varying dataset using features, exposure, and + look back specifications. + date_publication: '2024-02-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tv + url_git: '' +tvem: + version: 1.4.1 + title: Time-Varying Effect Models + maintainer: John J. Dziak + description: Fits time-varying effect models (TVEM). These are a kind of application + of varying-coefficient models in the context of longitudinal data, allowing the + strength of linear, logistic, or Poisson regression relationships to change over + time. These models are described further in Tan, Shiyko, Li, Li & Dierker (2012) + . We thank Kaylee Litson, Patricia Berglund, Yajnaseni + Chakraborti, and Hanjoo Kim for their valuable help with testing the package and + the documentation. The development of this package was part of a research project + supported by National Institutes of Health grants P50 DA039838 from the National + Institute of Drug Abuse and 1R01 CA229542-01 from the National Cancer Institute + and the NIH Office of Behavioral and Social Science Research. Content is solely + the responsibility of the authors and does not necessarily represent the official + views of the funding institutions mentioned above. This software is distributed + in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the + implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + date_publication: '2023-08-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tvem + url_git: '' +tvgarch: + version: 2.4.2 + title: Time Varying GARCH Modelling + maintainer: Susana Campos-Martins + description: Simulation, estimation and inference for univariate and multivariate + TV(s)-GARCH(p,q,r)-X models, where s indicates the number and shape of the transition + functions, p is the ARCH order, q is the GARCH order, r is the asymmetry order, + and 'X' indicates that covariates can be included; see Campos-Martins and Sucarrat + (2024) . In the multivariate case, variances are estimated + equation by equation and dynamic conditional correlations are allowed. The TV + long-term component of the variance as in the multiplicative TV-GARCH model of + Amado and Terasvirta (2013) introduces non-stationarity + whereas the GARCH-X short-term component describes conditional heteroscedasticity. + Maximisation by parts leads to consistent and asymptotically normal estimates. + date_publication: '2024-04-04' + bug_reports: '' + url: https://sites.google.com/site/susanacamposmartins + url_cran: https://CRAN.R-project.org/package=tvgarch + url_git: '' +tvgeom: + version: 1.0.1 + title: The Time-Varying (Right-Truncated) Geometric Distribution + maintainer: Vincent Landau + description: |- + Probability mass (d), distribution (p), quantile (q), and random + number generating (r and rt) functions for the time-varying right-truncated + geometric (tvgeom) distribution. Also provided are functions to calculate the first + and second central moments of the distribution. The tvgeom distribution + is similar to the geometric distribution, but the probability + of success is allowed to vary at each time step, and there are a limited + number of trials. This distribution is essentially a Markov chain, and it + is useful for modeling Markov chain systems with a set + number of time steps. + date_publication: '2019-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tvgeom + url_git: '' +tvm: + version: 0.5.2 + title: Time Value of Money Functions + maintainer: Juan Manuel Truppia + description: Functions for managing cashflows and interest rate curves. + date_publication: '2023-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tvm + url_git: https://bitbucket.org/juancentro/tvm +tvmComp: + version: 1.0.2 + title: Discounting and Compounding Calculations for Various Scenarios + maintainer: MaheshP Kumar + description: |- + Functions for compounding and discounting calculations included here serve as a complete reference for various scenarios of time value of money. + Raymond M. Brooks (“Financial Management,” 2018, ISBN: 9780134730417). + Sheridan Titman, Arthur J. Keown, John D. Martin (“Financial Management: Principles and Applications,” 2017, ISBN: 9780134417219). + Jonathan Berk, Peter DeMarzo, David Stangeland, Andras Marosi (“Fundamentals of Corporate Finance,” 2019, ISBN: 9780134735313). + S. A. Hummelbrunner, Kelly Halliday, Ali R. Hassanlou (“Contemporary Business Mathematics with Canadian Applications,” 2020, ISBN: 9780135285015). + date_publication: '2022-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tvmComp + url_git: '' +tvmediation: + version: 1.1.0 + title: Time Varying Mediation Analysis + maintainer: Donna Coffman + description: |- + Provides functions for estimating mediation effects that vary over + time as described in Cai X, Coffman DL, Piper ME, Li R. + Estimation and inference for the mediation effect in a time-varying mediation model. + BMC Med Res Methodol. 2022;22(1):1-12. + date_publication: '2022-05-25' + bug_reports: https://github.com/dcoffman/tvmediation/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tvmediation + url_git: https://github.com/dcoffman/tvmediation/wiki +TVMM: + version: 3.2.1 + title: Multivariate Tests for the Vector of Means + maintainer: Henrique Jose de Paula Alves + description: 'This is a statistical tool interactive that provides multivariate + statistical tests that are more powerful than traditional Hotelling T2 test and + LRT (likelihood ratio test) for the vector of normal mean populations with and + without contamination and non-normal populations (Henrique J. P. Alves & Daniel + F. Ferreira (2019) ).' + date_publication: '2020-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TVMM + url_git: '' +tvR: + version: 0.3.2 + title: Total Variation Regularization + maintainer: Kisung You + description: |- + Provides tools for denoising noisy signal and images via + Total Variation Regularization. Reducing the total variation of + the given signal is known to remove spurious detail while preserving + essential structural details. For the seminal work on the topic, + see Rudin et al (1992) . + date_publication: '2021-08-22' + bug_reports: https://github.com/kisungyou/tvR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tvR + url_git: https://github.com/kisungyou/tvR +tvReg: + version: 0.5.9 + title: |- + Time-Varying Coefficient for Single and Multi-Equation + Regressions + maintainer: Isabel Casas + description: Fitting time-varying coefficient models for single and multi-equation + regressions, using kernel smoothing techniques. + date_publication: '2023-09-01' + bug_reports: https://github.com/icasas/tvReg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tvReg + url_git: https://github.com/icasas/tvReg +tvthemes: + version: 1.3.3 + title: TV Show Themes and Color Palettes for 'ggplot2' Graphics + maintainer: Ryo Nakagawara + description: |- + Contains various 'ggplot2' themes and color palettes based on TV shows + such as 'Game of Thrones', 'Brooklyn Nine-Nine', 'Avatar: The Last Airbender', + 'Spongebob Squarepants', and more. + date_publication: '2024-02-27' + bug_reports: https://github.com/Ryo-N7/tvthemes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tvthemes + url_git: https://github.com/Ryo-N7/tvthemes +tvtools: + version: 0.0.3 + title: Comprehensive Tools for Panel Data Analysis - 'tvtools' + maintainer: Srivastav Budugutta + description: |- + Longitudinal data offers insights into population changes over + time but often requires a flexible structure, especially with varying + follow-up intervals. Panel data is one way to store such records, though + it adds complexity to analysis. The 'tvtools' package for R simplifies + exploring and analyzing panel data. + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tvtools + url_git: '' +twang: + version: 2.6.1 + title: Toolkit for Weighting and Analysis of Nonequivalent Groups + maintainer: Lane Burgette + description: |- + Provides functions for propensity score + estimating and weighting, nonresponse weighting, and diagnosis + of the weights. + date_publication: '2024-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twang + url_git: '' +twangContinuous: + version: 1.0.0 + title: |- + Toolkit for Weighting and Analysis of Nonequivalent Groups - + Continuous Exposures + maintainer: Donna Coffman + description: |- + Provides functions for propensity score + estimation and weighting for continuous exposures as described in Zhu, Y., + Coffman, D. L., & Ghosh, D. (2015). A boosting algorithm for + estimating generalized propensity scores with continuous treatments. + Journal of Causal Inference, 3(1), 25-40. . + date_publication: '2021-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twangContinuous + url_git: '' +twangMediation: + version: '1.2' + title: Twang Causal Mediation Modeling via Weighting + maintainer: Dan McCaffrey + description: Provides functions for estimating natural direct and indirect effects + for mediation analysis. It uses weighting where the weights are functions of estimates + of the probability of exposure or treatment assignment (Hong, G (2010). + Huber, M. (2014). ). Estimation of probabilities can use + generalized boosting or logistic regression. Additional functions provide diagnostics + of the model fit and weights. The vignette provides details and examples. + date_publication: '2022-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twangMediation + url_git: '' +twangRDC: + version: '1.0' + title: Gradient Boosting for Linkage Failure in FSRDCs + maintainer: Matthew Cefalu + description: |- + Provides functions for gradient boosted weighting to correct linkage + failures or generate comparison groups. + date_publication: '2021-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twangRDC + url_git: '' +twc: + version: 0.0.1 + title: Terrestrial Water Cycle + maintainer: Mijael Rodrigo Vargas Godoy + description: |- + An open-access tool/framework that constitutes the core functions + to analyze terrestrial water cycle data across various spatio-temporal scales. + date_publication: '2024-12-02' + bug_reports: https://github.com/imarkonis/twc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=twc + url_git: https://github.com/imarkonis/twc +twdtw: + version: 1.0-1 + title: Time-Weighted Dynamic Time Warping + maintainer: Victor Maus + description: |- + Implements Time-Weighted Dynamic Time Warping (TWDTW), + a measure for quantifying time series similarity. The TWDTW algorithm, + described in Maus et al. (2016) and + Maus et al. (2019) , is applicable to multi-dimensional + time series of various resolutions. It is particularly suitable for comparing + time series with seasonality for environmental and ecological data analysis, + covering domains such as remote sensing imagery, climate data, hydrology, + and animal movement. The 'twdtw' package offers a user-friendly 'R' interface, + efficient 'Fortran' routines for TWDTW calculations, flexible time weighting + definitions, as well as utilities for time series preprocessing and visualization. + date_publication: '2023-08-08' + bug_reports: https://github.com/vwmaus/twdtw/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=twdtw + url_git: https://github.com/vwmaus/twdtw/ +tweedie: + version: 2.3.5 + title: Evaluation of Tweedie Exponential Family Models + maintainer: Peter K. Dunn + description: Maximum likelihood computations for Tweedie families, including the + series expansion (Dunn and Smyth, 2005; ) and the + Fourier inversion (Dunn and Smyth, 2008; ), and + related methods. + date_publication: '2022-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tweedie + url_git: '' +tweenr: + version: 2.0.3 + title: Interpolate Data for Smooth Animations + maintainer: Thomas Lin Pedersen + description: |- + In order to create smooth animation between states of data, + tweening is necessary. This package provides a range of functions for + creating tweened data that can be used as basis for animation. Furthermore + it adds a number of vectorized interpolaters for common R data + types such as numeric, date and colour. + date_publication: '2024-02-26' + bug_reports: https://github.com/thomasp85/tweenr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=tweenr + url_git: https://github.com/thomasp85/tweenr +tweetcheck: + version: 0.1.0 + title: Parse and Validate Tweet Text + maintainer: Jacob Scott + description: |- + An interface to 'twitter-text', a 'JavaScript' library which + is responsible for determining the length/validity of a tweet and + identifying/linking any URLs or special tags (e.g. mentions or + hashtags) which may be present. + date_publication: '2022-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tweetcheck + url_git: '' +twenty48: + version: 0.2.1 + title: Play a Game of 2048 in the Console + maintainer: Alexander Rossell Hayes + description: |- + Generates a game of 2048 that can be played in the + console. Supports grids of arbitrary sizes, undoing the last move, + and resuming a game that was exited during the current session. + date_publication: '2022-09-13' + bug_reports: https://github.com/rossellhayes/twenty48/issues + url: '' + url_cran: https://CRAN.R-project.org/package=twenty48 + url_git: https://github.com/rossellhayes/twenty48 +twfy: + version: 0.1.0 + title: Drive the API for TheyWorkForYou + maintainer: Will Lowe + description: |- + An R wrapper around the API of TheyWorkForYou, a parliamentary + monitoring site that scrapes and repackages Hansard (the UK's parliamentary + record) and augments it with information from the Register of Members' + Interests, election results, and voting records to provide a unified + source of information about UK legislators and their activities. See + for details. + date_publication: '2017-06-26' + bug_reports: https://github.com/conjugateprior/twfy/issues + url: https://conjugateprior.github.io/twfy + url_cran: https://CRAN.R-project.org/package=twfy + url_git: '' +twig: + version: 1.0.0.0 + title: |- + For Streamlining Decision and Economic Evaluation Models using + Grammar of Modeling + maintainer: Hawre Jalal + description: Provides tools for building decision and cost-effectiveness analysis + models. It enables users to write these models concisely, simulate outcomes—including + probabilistic analyses—efficiently using optimized vectorized processes and parallel + computing, and produce results. The package employs a Grammar of Modeling approach, + inspired by the Grammar of Graphics, to streamline model construction. For an + interactive graphical user interface, see 'DecisionTwig' at . + Comprehensive tutorials and vignettes are available at . + date_publication: '2025-01-16' + bug_reports: https://github.com/hjalal/twig/issues + url: https://www.dashlab.ca/ + url_cran: https://CRAN.R-project.org/package=twig + url_git: '' +twilio: + version: 0.1.0 + title: An Interface to the Twilio API for R + maintainer: Sean Kross + description: |- + The Twilio web service provides an API for computer programs + to interact with telephony. The included functions wrap the SMS and MMS + portions of Twilio's API, allowing users to send and receive text messages + from R. See for more information. + date_publication: '2017-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twilio + url_git: http://github.com/seankross/twilio +twingp: + version: 1.0.0 + title: A Fast Global-Local Gaussian Process Approximation + maintainer: Akhil Vakayil + description: |- + A global-local approximation framework for large-scale Gaussian process modeling. + Please see Vakayil and Joseph (2024) for details. + This work is supported by U.S. NSF grants CMMI-1921646 and DMREF-1921873. + date_publication: '2024-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twingp + url_git: '' +twinning: + version: '1.0' + title: Data Twinning + maintainer: Akhil Vakayil + description: |- + An efficient algorithm for data twinning. This work is supported by U.S. National Science + Foundation grants DMREF-1921873 and CMMI-1921646. + date_publication: '2022-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twinning + url_git: '' +Twitmo: + version: 0.1.2 + title: Twitter Topic Modeling and Visualization for R + maintainer: Andreas Buchmueller + description: |- + Tailored for topic modeling with tweets and fit for visualization tasks in R. + Collect, pre-process and analyze the contents of tweets using + LDA and structural topic models (STM). Comes with visualizing capabilities like tweet and hashtag maps + and built-in support for 'LDAvis'. + date_publication: '2021-12-06' + bug_reports: https://github.com/abuchmueller/Twitmo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Twitmo + url_git: https://github.com/abuchmueller/Twitmo +twitteradsR: + version: 0.1.0 + title: Get Twitter Ads Data via the 'Windsor.ai' API + maintainer: Pablo Sanchez + description: Collect your data on digital marketing campaigns from Twitter Ads + using the 'Windsor.ai' API . + date_publication: '2022-10-27' + bug_reports: '' + url: https://windsor.ai/ + url_cran: https://CRAN.R-project.org/package=twitteradsR + url_git: '' +twitterwidget: + version: 0.1.1 + title: Render a Twitter Status in R Markdown Pages + maintainer: Guido Volpi + description: |- + Include the Twitter status widgets in HTML pages created + using R markdown. The package uses the Twitter javascript APIs to + embed in your document Twitter cards associated to specific statuses. + The main targets are regular HTML pages or dashboards. + date_publication: '2019-07-10' + bug_reports: https://github.com/guivo/twitterwidget/issues + url: '' + url_cran: https://CRAN.R-project.org/package=twitterwidget + url_git: https://github.com/guivo/twitterwidget +twl: + version: '1.0' + title: Two-Way Latent Structure Clustering Model + maintainer: Michael Swanson + description: 'Implementation of a Bayesian two-way latent structure model for integrative + genomic clustering. The model clusters samples in relation to distinct data sources, + with each subject-dataset receiving a latent cluster label, though cluster labels + have across-dataset meaning because of the model formulation. A common scaling + across data sources is unneeded, and inference is obtained by a Gibbs Sampler. The + model can fit multivariate Gaussian distributed clusters or a heavier-tailed modification + of a Gaussian density. Uniquely among integrative clustering models, the formulation + makes no nestedness assumptions of samples across data sources -- the user can + still fit the model if a study subject only has information from one data source. + The package provides a variety of post-processing functions for model examination + including ones for quantifying observed alignment of clusterings across genomic + data sources. Run time is optimized so that analyses of datasets on the order + of thousands of features on fewer than 5 datasets and hundreds of subjects can + converge in 1 or 2 days on a single CPU. See "Swanson DM, Lien T, Bergholtz H, + Sorlie T, Frigessi A, Investigating Coordinated Architectures Across Clusters + in Integrative Studies: a Bayesian Two-Way Latent Structure Model, 2018, , + Cold Spring Harbor Laboratory" at + for model details.' + date_publication: '2018-08-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twl + url_git: '' +twn: + version: 0.2.5 + title: Taxa Waterbeheer Nederland voor R + maintainer: Johan van Tent + description: |- + The TWN-list (Taxa Waterbeheer Nederland) is the Dutch standard for naming + taxons in Dutch Watermanagement. This package makes it easier to use the + TWN-list for ecological analyses. It consists of two parts. First it makes the + TWN-list itself available in R. Second, it has a few functions that make it + easy to perform some basic and often recurring tasks for checking and consulting + taxonomic data from the TWN-list. + date_publication: '2024-11-11' + bug_reports: https://github.com/RedTent/twn/issues + url: https://redtent.github.io/twn/ + url_cran: https://CRAN.R-project.org/package=twn + url_git: '' +TwoArmSurvSim: + version: '0.2' + title: Simulate Survival Data for Randomized Clinical Trials + maintainer: Bo Zhang + description: A system to simulate clinical trials with time to event endpoints. + Event simulation is based on Cox models allowing for covariates in addition to + the treatment or group factor. Specific drop-out rates (separate from administrative + censoring) can be controlled in the simulation. Other features include stratified + randomization, non-proportional hazards, different accrual patterns, and event + projection (timing to reach the target event) based on interim data. + date_publication: '2021-02-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TwoArmSurvSim + url_git: '' +twopartm: + version: 0.1.0 + title: Two-Part Model with Marginal Effects + maintainer: Yajie Duan + description: |- + Fit two-part regression models for zero-inflated data. The models and their components are represented using S4 classes and methods. Average Marginal effects and predictive margins with standard errors and + confidence intervals can be calculated from two-part model objects. Belotti, F., Deb, P., Manning, W. G., & Norton, E. C. (2015) . + date_publication: '2022-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twopartm + url_git: '' +twopexp: + version: 0.1.0 + title: The Two Parameter Exponential Distribution + maintainer: Atchanut Rattanalertnusorn + description: |- + Density, distribution function, quantile function, + and random generation function, maximum likelihood estimation (MLE), + penalized maximum likelihood estimation (PMLE), the quartiles method estimation (QM), + and median rank estimation (MEDRANK) for the two-parameter exponential distribution. + MLE and PMLE are based on Mengjie Zheng (2013). + QM is based on Entisar Elgmati and Nadia Gregni (2016). + MEDRANK is based on Matthew Reid (2022). + date_publication: '2023-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twopexp + url_git: '' +twosamples: + version: 2.0.1 + title: Fast Permutation Based Two Sample Tests + maintainer: Connor Dowd + description: |- + Fast randomization based two sample tests. + Testing the hypothesis that two samples come from the same distribution using randomization to create p-values. Included tests are: Kolmogorov-Smirnov, Kuiper, Cramer-von Mises, Anderson-Darling, Wasserstein, and DTS. The default test (two_sample) is based on the DTS test statistic, as it is the most powerful, and thus most useful to most users. + The DTS test statistic builds on the Wasserstein distance by using a weighting scheme like that of Anderson-Darling. See the companion paper at or for details of that test statistic, and non-standard uses of the package (parallel for big N, weighted observations, one sample tests, etc). We also include the permutation scheme to make test building simple for others. + date_publication: '2023-06-23' + bug_reports: https://github.com/cdowd/twosamples/issues + url: https://twosampletest.com + url_cran: https://CRAN.R-project.org/package=twosamples + url_git: https://github.com/cdowd/twosamples +TwoSampleTest.HD: + version: '1.2' + title: |- + A Two-Sample Test for the Equality of Distributions for + High-Dimensional Data + maintainer: Marta Cousido Rocha + description: For high-dimensional data whose main feature is a large number, p, + of variables but a small sample size, the null hypothesis that the marginal distributions + of p variables are the same for two groups is tested. We propose a test statistic + motivated by the simple idea of comparing, for each of the p variables, the empirical + characteristic functions computed from the two samples. If one rejects this global + null hypothesis of no differences in distributions between the two groups, a set + of permutation p-values is reported to identify which variables are not equally + distributed in both groups. + date_publication: '2023-02-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TwoSampleTest.HD + url_git: '' +twosigma: + version: 1.0.2 + title: DE Analysis for Single-Cell RNA-Sequencing Data + maintainer: Eric Van Buren + description: Implements the TWO-Component Single Cell Model-Based Association Method + (TWO-SIGMA) for gene-level differential expression (DE) analysis and DE-based + gene set testing of single-cell RNA-sequencing datasets. See Van Buren et al. + (2020) and Van Buren et al. (2021) . + date_publication: '2021-12-13' + bug_reports: https://github.com/edvanburen/twosigma/issues + url: '' + url_cran: https://CRAN.R-project.org/package=twosigma + url_git: https://github.com/edvanburen/twosigma +twoStageDesignTMLE: + version: 1.0.1.2 + title: |- + Targeted Maximum Likelihood Estimation for Two-Stage Study + Design + maintainer: Susan Gruber + description: An inverse probability of censoring weighted (IPCW) targeted maximum + likelihood estimator (TMLE) for evaluating a marginal point treatment effect from + data where some variables were collected on only a subset of participants using + a two-stage design (or marginal mean outcome for a single arm study). A TMLE for + conditional parameters defined by a marginal structural model (MSM) is also available. + date_publication: '2025-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twoStageDesignTMLE + url_git: '' +TwoStepCLogit: + version: 1.2.5 + title: 'Conditional Logistic Regression: A Two-Step Estimation Method' + maintainer: Thierry Duchesne + description: |- + Conditional logistic regression with longitudinal follow up and + individual-level random coefficients: A stable and efficient + two-step estimation method. + date_publication: '2016-03-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TwoStepCLogit + url_git: '' +TwoTimeScales: + version: 1.0.0 + title: Analysis of Event Data with Two Time Scales + maintainer: Angela Carollo + description: |- + Analyse time to event data with two time scales by estimating a smooth hazard that varies over two time scales and also, if covariates are available, to estimate a proportional hazards model with such a two-dimensional baseline hazard. + Functions are provided to prepare the raw data for estimation, to estimate and to plot the two-dimensional smooth hazard. + Extension to a competing risks model are implemented. For details about the method please refer to Carollo et al. (2024) . + date_publication: '2024-12-23' + bug_reports: https://github.com/AngelaCar/TwoTimeScales/issues + url: https://angelacar.github.io/TwoTimeScales/ + url_cran: https://CRAN.R-project.org/package=TwoTimeScales + url_git: https://github.com/AngelaCar/TwoTimeScales +twoway: + version: 0.6.3 + title: Analysis of Two-Way Tables + maintainer: Michael Friendly + description: |- + Carries out analyses of two-way tables with one observation per cell, together with graphical displays + for an additive fit and + a diagnostic plot for removable 'non-additivity' via a power transformation of the response. + It implements Tukey's Exploratory Data Analysis (1973) methods, including a + 1-degree-of-freedom test for row*column 'non-additivity', linear in the row and column effects. + date_publication: '2020-06-26' + bug_reports: https://github.com/friendly/twoway/issues + url: '' + url_cran: https://CRAN.R-project.org/package=twoway + url_git: https://github.com/friendly/twoway +TwoWayFEWeights: + version: 2.0.4 + title: |- + Estimation of the Weights Attached to the Two-Way Fixed Effects + Regressions + maintainer: Diego Ciccia + description: |- + Estimates the weights and measure of robustness to treatment effect heterogeneity attached to two-way fixed effects regressions. + Clément de Chaisemartin, Xavier D'Haultfœuille (2020) . + date_publication: '2024-07-26' + bug_reports: https://github.com/chaisemartinPackages/twowayfeweights/issues + url: '' + url_cran: https://CRAN.R-project.org/package=TwoWayFEWeights + url_git: https://github.com/chaisemartinPackages +twowaytests: + version: '1.5' + title: Two-Way Tests in Independent Groups Designs + maintainer: Osman Dag + description: 'Performs two-way tests in independent groups designs. These are two-way + ANOVA, two-way ANOVA under heteroscedasticity: parametric bootstrap based generalized + test and generalized pivotal quantity based generalized test, two-way ANOVA for + medians, trimmed means, M-estimators. The package performs descriptive statistics + and graphical approaches. Moreover, it assesses variance homogeneity and normality + of data in each group via tests and plots. All ''twowaytests'' functions are designed + for two-way layout (Dag et al., 2024, ).' + date_publication: '2024-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twowaytests + url_git: '' +twoxtwo: + version: 0.1.0 + title: Work with Two-by-Two Tables + maintainer: VP Nagraj + description: A collection of functions for data analysis with two-by-two contingency + tables. The package provides tools to compute measures of effect (odds ratio, + risk ratio, and risk difference), calculate impact numbers and attributable fractions, + and perform hypothesis testing. Statistical analysis methods are oriented towards + epidemiological investigation of relationships between exposures and outcomes. + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=twoxtwo + url_git: '' +TWW: + version: 0.1.0 + title: Growth Models + maintainer: Derek Wilus + description: |- + A model for the growth of self-limiting populations using three, four, or five parameter + functions, which have wide applications in a variety of fields. + The dependent variable in a dynamical modeling could be the population size at time x, + where x is the independent variable. In the analysis of quantitative polymerase chain reaction + (qPCR), the dependent variable would be the fluorescence intensity and the independent variable + the cycle number. This package then would calculate the TWW cycle threshold. + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=TWW + url_git: '' +txshift: + version: 0.3.8 + title: |- + Efficient Estimation of the Causal Effects of Stochastic + Interventions + maintainer: Nima Hejazi + description: |- + Efficient estimation of the population-level causal effects of + stochastic interventions on a continuous-valued exposure. Both one-step and + targeted minimum loss estimators are implemented for the counterfactual mean + value of an outcome of interest under an additive modified treatment policy, + a stochastic intervention that may depend on the natural value of the + exposure. To accommodate settings with outcome-dependent two-phase + sampling, procedures incorporating inverse probability of censoring + weighting are provided to facilitate the construction of inefficient and + efficient one-step and targeted minimum loss estimators. The causal + parameter and its estimation were first described by Díaz and van der Laan + (2013) , while the multiply robust + estimation procedure and its application to data from two-phase sampling + designs is detailed in NS Hejazi, MJ van der Laan, HE Janes, PB Gilbert, + and DC Benkeser (2020) . The software package + implementation is described in NS Hejazi and DC Benkeser (2020) + . Estimation of nuisance parameters may be + enhanced through the Super Learner ensemble model in 'sl3', available for + download from GitHub using 'remotes::install_github("tlverse/sl3")'. + date_publication: '2022-02-09' + bug_reports: https://github.com/nhejazi/txshift/issues + url: '' + url_cran: https://CRAN.R-project.org/package=txshift + url_git: https://github.com/nhejazi/txshift +txtplot: + version: 1.0-4 + title: Text Based Plots + maintainer: Bjoern Bornkamp + description: |- + Provides functions to produce rudimentary ascii graphics + directly in the terminal window. Provides a basic plotting + function (and equivalents of curve, density, acf and barplot) + as well as boxplot and image functions. + date_publication: '2020-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=txtplot + url_git: '' +txtq: + version: 0.2.4 + title: A Small Message Queue for Parallel Processes + maintainer: William Michael Landau + description: |- + This queue is a data structure that lets + parallel processes send and receive messages, + and it can help coordinate the work + of complicated parallel tasks. + Processes can push new messages to the queue, + pop old messages, and obtain a + log of all the messages ever pushed. File locking + preserves the integrity of the data even when + multiple processes access the queue simultaneously. + date_publication: '2021-03-27' + bug_reports: https://github.com/wlandau/txtq/issues + url: '' + url_cran: https://CRAN.R-project.org/package=txtq + url_git: https://github.com/wlandau/txtq +typed: + version: 0.0.1 + title: Support Types for Variables, Arguments, and Return Values + maintainer: Antoine Fabri + description: A type system for R. It supports setting variable types in a script + or the body of a function, so variables can't be assigned illegal values. Moreover + it supports setting argument and return types for functions. + date_publication: '2021-03-19' + bug_reports: https://github.com/moodymudskipper/typed/issues + url: '' + url_cran: https://CRAN.R-project.org/package=typed + url_git: https://github.com/moodymudskipper/typed +typehint: + version: 0.1.2 + title: Auto-Check Types, Dimensions, and Values of Function Arguments + maintainer: Joachim Zuckarelli + description: Type hints are special comments within a function body indicating the + intended nature of the function's arguments in terms of data types, dimensions + and permitted values. The actual parameters with which the function is called + are evaluated against these type hint comments at run-time. + date_publication: '2021-08-10' + bug_reports: https://github.com/jsugarelli/typehint/issues + url: '' + url_cran: https://CRAN.R-project.org/package=typehint + url_git: https://github.com/jsugarelli/typehint/ +types: + version: 1.0.0 + title: Type Annotations + maintainer: Jim Hester + description: |- + Provides a simple type annotation for R that is usable in scripts, + in the R console and in packages. It is intended as a convention to allow other + packages to use the type information to provide error checking, + automatic documentation or optimizations. + date_publication: '2016-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=types + url_git: '' +typetracer: + version: 0.2.2 + title: Trace Function Parameter Types + maintainer: Mark Padgham + description: |- + The 'R' language includes a set of defined types, but the language + itself is "absurdly dynamic" (Turcotte & Vitek (2019) + ), and lacks any way to specify which types are + expected by any expression. The 'typetracer' package enables code to be + traced to extract detailed information on the properties of parameters + passed to 'R' functions. 'typetracer' can trace individual functions or + entire packages. + date_publication: '2023-06-26' + bug_reports: https://github.com/mpadge/typetracer/issues + url: https://mpadge.github.io/typetracer/ + url_cran: https://CRAN.R-project.org/package=typetracer + url_git: https://github.com/mpadge/typetracer +tzdb: + version: 0.4.0 + title: Time Zone Database Information + maintainer: Davis Vaughan + description: |- + Provides an up-to-date copy of the Internet Assigned Numbers + Authority (IANA) Time Zone Database. It is updated periodically to + reflect changes made by political bodies to time zone boundaries, UTC + offsets, and daylight saving time rules. Additionally, this package + provides a C++ interface for working with the 'date' library. 'date' + provides comprehensive support for working with dates and date-times, + which this package exposes to make it easier for other R packages to + utilize. Headers are provided for calendar specific calculations, + along with a limited interface for time zone manipulations. + date_publication: '2023-05-12' + bug_reports: https://github.com/r-lib/tzdb/issues + url: https://tzdb.r-lib.org + url_cran: https://CRAN.R-project.org/package=tzdb + url_git: https://github.com/r-lib/tzdb +tzupdater: + version: 0.1.5 + title: Time Zone Database Updater + maintainer: Sebastien Thonnard + description: |- + Download and compile any version of the + IANA Time Zone Database (also known as Olson database) + and make it current in your R session. + Beware: on Windows 'Cygwin' is required! + date_publication: '2023-11-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=tzupdater + url_git: '' +u5mr: + version: 0.1.1 + title: Under-Five Child Mortality Estimation + maintainer: Myo Minn Oo + description: 'Contains functions for calculating under-five child mortality estimates + using the Trussell version of the Brass method (United Nations (1990) + and United Nations (1983) ) + as well as applying the cohort-derived methods by Rajaratnam and colleagues (Rajaratnam + JK, Tran LN, Lopez AD, Murray CJL (2010) "Measuring Under-Five Mortality: Validation + of New Low-Cost Methods" ).' + date_publication: '2021-09-09' + bug_reports: https://github.com/myominnoo/u5mr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=u5mr + url_git: https://github.com/myominnoo/u5mr +UAHDataScienceO: + version: 1.0.0 + title: |- + Educational Outlier Detection Algorithms with Step-by-Step + Tutorials + maintainer: Andriy Protsak Protsak + description: |- + Provides implementations of some of the most important outlier detection algorithms. + Includes a tutorial mode option that shows a description of each algorithm and provides + a step-by-step execution explanation of how it identifies outliers from the given data + with the specified input parameters. References include the works of Azzedine Boukerche, + Lining Zheng, and Omar Alfandi (2020) , Abir Smiti (2020) + , and Xiaogang Su, Chih-Ling Tsai (2011) + . + date_publication: '2025-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UAHDataScienceO + url_git: '' +UAHDataScienceSC: + version: 1.0.0 + title: |- + Learn Supervised Classification Methods Through Examples and + Code + maintainer: Andriy Protsak Protsak + description: |- + Supervised classification methods, which (if asked) can provide + step-by-step explanations of the algorithms used, as described in + PK Josephine et. al., (2021) ; and datasets to + test them on, which highlight the strengths and weaknesses of each technique. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UAHDataScienceSC + url_git: '' +UAHDataScienceSF: + version: 1.0.0 + title: Interactive Statistical Learning Functions + maintainer: Andriy Protsak Protsak + description: |- + An educational toolkit for learning statistical concepts through + interactive exploration. Provides functions for basic statistics (mean, + variance, etc.) and probability distributions with step-by-step explanations + and interactive learning modes. Each function can be used for simple + calculations, detailed learning with explanations, or interactive practice + with feedback. + date_publication: '2025-02-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UAHDataScienceSF + url_git: '' +UAHDataScienceUC: + version: 1.0.1 + title: Learn Clustering Techniques Through Examples and Code + maintainer: Andriy Protsak Protsak + description: |- + A comprehensive educational package combining clustering algorithms with + detailed step-by-step explanations. Provides implementations of both traditional + (hierarchical, k-means) and modern (Density-Based Spatial Clustering of Applications with Noise (DBSCAN), + Gaussian Mixture Models (GMM), genetic k-means) clustering methods + as described in Ezugwu et. al., (2022) . + Includes educational datasets highlighting different clustering challenges, based on + 'scikit-learn' examples (Pedregosa et al., 2011) + . Features detailed + algorithm explanations, visualizations, and weighted distance calculations for + enhanced learning. + date_publication: '2025-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UAHDataScienceUC + url_git: '' +uaparserjs: + version: 0.3.5 + title: Parse 'User-Agent' Strings + maintainer: Bob Rudis + description: |- + Despite there being a section in RFC 7231 + defining a suggested + structure for 'User-Agent' headers this data is notoriously difficult + to parse consistently. Tools are provided that will take in user agent + strings and return structured R objects. This is a 'V8'-backed package + based on the 'ua-parser' project . + date_publication: '2020-05-11' + bug_reports: https://gitlab.com/hrbrmstr/uaparserjs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uaparserjs + url_git: https://gitlab.com/hrbrmstr/uaparserjs +uavRmp: + version: '0.7' + title: UAV Mission Planner + maintainer: Chris Reudenbach + description: The Unmanned Aerial Vehicle Mission Planner provides an easy to use + work flow for planning autonomous obstacle avoiding surveys of ready to fly unmanned + aerial vehicles to retrieve aerial or spot related data. It creates either intermediate + flight control files for the DJI-Litchi supported series or ready to upload control + files for the pixhawk-based flight controller. Additionally it contains some useful + tools for digitizing and data manipulation. + date_publication: '2024-06-07' + bug_reports: https://github.com/gisma/uavRmp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uavRmp + url_git: https://github.com/gisma/uavRmp +ubair: + version: 1.1.0 + title: Effects of External Conditions on Air Quality + maintainer: Imke Voss + description: Analyzes the impact of external conditions on air quality using counterfactual + approaches, featuring methods for data preparation, modeling, and visualization. + date_publication: '2025-01-27' + bug_reports: '' + url: https://gitlab.opencode.de/uba-ki-lab/ubair + url_cran: https://CRAN.R-project.org/package=ubair + url_git: '' +UBayFS: + version: '1.0' + title: A User-Guided Bayesian Framework for Ensemble Feature Selection + maintainer: Anna Jenul + description: The framework proposed in Jenul et al., (2022) , + together with an interactive Shiny dashboard. 'UBayFS' is an ensemble feature + selection technique embedded in a Bayesian statistical framework. The method combines + data and user knowledge, where the first is extracted via data-driven ensemble + feature selection. The user can control the feature selection by assigning prior + weights to features and penalizing specific feature combinations. 'UBayFS' can + be used for common feature selection as well as block feature selection. + date_publication: '2023-03-07' + bug_reports: https://github.com/annajenul/UBayFS/issues + url: https://annajenul.github.io/UBayFS/ + url_cran: https://CRAN.R-project.org/package=UBayFS + url_git: '' +UBCRM: + version: 1.0.3 + title: Simulate and Conduct Dose-Escalation Phase I Studies + maintainer: Christophe Zemmour + description: 'Two Phase I designs are implemented in the package: the classical + 3+3 and the Continual Reassessment Method (). Simulations + tools are also available to estimate the operating characteristics of the methods + with several user-dependent options.' + date_publication: '2024-04-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UBCRM + url_git: '' +ubiquity: + version: 2.1.0 + title: PKPD, PBPK, and Systems Pharmacology Modeling Tools + maintainer: John Harrold + description: 'Complete work flow for the analysis of pharmacokinetic pharmacodynamic + (PKPD), physiologically-based pharmacokinetic (PBPK) and systems pharmacology + models including: creation of ordinary differential equation-based models, pooled + parameter estimation, individual/population based simulations, rule-based simulations + for clinical trial design and modeling assays, deployment with a customizable + ''Shiny'' app, and non-compartmental analysis. System-specific analysis templates + can be generated and each element includes integrated reporting with ''PowerPoint'' + and ''Word''.' + date_publication: '2025-01-07' + bug_reports: https://github.com/john-harrold/ubiquity/issues + url: https://r.ubiquity.tools + url_cran: https://CRAN.R-project.org/package=ubiquity + url_git: '' +UBL: + version: 0.0.9 + title: |- + An Implementation of Re-Sampling Approaches to Utility-Based + Learning for Both Classification and Regression Tasks + maintainer: Paula Branco + description: Provides a set of functions that can be used to obtain better predictive + performance on cost-sensitive and cost/benefits tasks (for both regression and + classification). This includes re-sampling approaches that modify the original + data set biasing it towards the user preferences. + date_publication: '2023-10-07' + bug_reports: https://github.com/paobranco/UBL/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UBL + url_git: https://github.com/paobranco/UBL +ubms: + version: 1.2.7 + title: Bayesian Models for Data from Unmarked Animals using 'Stan' + maintainer: Ken Kellner + description: |- + Fit Bayesian hierarchical models of animal abundance and occurrence + via the 'rstan' package, the R interface to the 'Stan' C++ library. + Supported models include single-season occupancy, dynamic occupancy, and + N-mixture abundance models. Covariates on model parameters are specified + using a formula-based interface similar to package 'unmarked', while also + allowing for estimation of random slope and intercept terms. References: + Carpenter et al. (2017) ; + Fiske and Chandler (2011) . + date_publication: '2024-10-01' + bug_reports: https://github.com/biodiverse/ubms/issues + url: https://biodiverse.github.io/ubms/ + url_cran: https://CRAN.R-project.org/package=ubms + url_git: '' +UBStats: + version: 0.2.2 + title: Basic Statistics + maintainer: Sergio Venturini + description: |- + Basic statistical analyses. The package has been developed + to be used in statistics courses at Bocconi University (Milan, Italy). + Currently, the package includes some exploratory and inferential analyses + usually presented in introductory statistics courses. + date_publication: '2024-08-26' + bug_reports: https://github.com/raffaellapiccarreta/UBStats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UBStats + url_git: '' +uci: + version: 0.3.0 + title: Urban Centrality Index + maintainer: Rafael H. M. Pereira + description: |- + Calculates the Urban Centrality Index (UCI) as in Pereira et al., + (2013) . The UCI measures the + extent to which the spatial organization of a city or region varies + from extreme polycentric to extreme monocentric in a continuous + scale from 0 to 1. Values closer to 0 indicate more polycentric patterns + and values closer to 1 indicate a more monocentric urban form. + date_publication: '2023-09-23' + bug_reports: https://github.com/ipeaGIT/uci/issues + url: https://ipeagit.github.io/uci/ + url_cran: https://CRAN.R-project.org/package=uci + url_git: https://github.com/ipeaGIT/uci +ucie: + version: 1.0.2 + title: Mapping 3D Data into CIELab Color Space + maintainer: Mikaela Koutrouli + description: Returns a data frame with the names of the input data points and hex + colors (or CIELab coordinates). Data can be mapped to colors for use in data visualization. + It optimally maps data points into a polygon that represents the CIELab colour + space. Since Euclidean distance approximates relative perceptual differences in + CIELab color space, the result is a color encoding that aims to capture much of + the structure of the original data. + date_publication: '2022-06-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ucie + url_git: '' +ucimlrepo: + version: 0.0.2 + title: Explore UCI ML Repository Datasets + maintainer: James Joseph Balamuta + description: |- + Find and import datasets from the + University of California Irvine Machine Learning (UCI ML) Repository into R. + Supports working with data from UCI ML repository inside of R scripts, notebooks, + and 'Quarto'/'RMarkdown' documents. Access the UCI ML repository directly at + . + date_publication: '2024-08-31' + bug_reports: https://github.com/coatless-rpkg/ucimlrepo/issues + url: https://r-pkg.thecoatlessprofessor.com/ucimlrepo/ + url_cran: https://CRAN.R-project.org/package=ucimlrepo + url_git: https://github.com/coatless-rpkg/ucimlrepo +uclust: + version: 1.0.0 + title: Clustering and Classification Inference with U-Statistics + maintainer: Gabriela Cybis + description: |- + Clustering and classification inference for high dimension low sample size (HDLSS) + data with U-statistics. The package contains implementations of nonparametric statistical + tests for sample homogeneity, group separation, clustering, and classification of + multivariate data. The methods have high statistical power and are tailored for data + in which the dimension L is much larger than sample size n. See Gabriela B. Cybis, + Marcio Valk and Sílvia RC Lopes (2018) , Marcio + Valk and Gabriela B. Cybis (2020) , Debora Z. Bello, Marcio + Valk and Gabriela B. Cybis (2021) . + date_publication: '2021-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uclust + url_git: '' +ucminf: + version: 1.2.2 + title: General-Purpose Unconstrained Non-Linear Optimization + maintainer: K Hervé Dakpo + description: |- + An algorithm for general-purpose unconstrained non-linear optimization. + The algorithm is of quasi-Newton type with BFGS updating of the inverse + Hessian and soft line search with a trust region type monitoring of the + input to the line search algorithm. The interface of 'ucminf' is + designed for easy interchange with 'optim'. + date_publication: '2024-06-24' + bug_reports: https://github.com/hdakpo/ucminf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ucminf + url_git: https://github.com/hdakpo/ucminf +UComp: + version: 5.0.6 + title: Automatic Univariate Time Series Modelling of many Kinds + maintainer: Diego J. Pedregal + description: |- + Comprehensive analysis and forecasting + of univariate time series using automatic + time series models of many kinds. + Harvey AC (1989) . + Pedregal DJ and Young PC (2002) . + Durbin J and Koopman SJ (2012) . + Hyndman RJ, Koehler AB, Ord JK, and Snyder RD (2008) . + Gómez V, Maravall A (2000) . + Pedregal DJ, Trapero JR and Holgado E (2024) . + date_publication: '2025-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UComp + url_git: '' +UCR.ColumnNames: + version: 0.1.0 + title: |- + Fixes Column Names for Uniform Crime Report "Offenses Known and + Clearance by Arrest" Datasets + maintainer: Jacob Kaplan + description: |- + Changes the column names of the inputted dataset to the correct + names from the Uniform Crime Report codebook for the "Offenses Known and + Clearance by Arrest" datasets from 1998-2014. + date_publication: '2016-09-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UCR.ColumnNames + url_git: '' +UCSCXenaShiny: + version: 2.1.0 + title: Interactive Analysis of UCSC Xena Data + maintainer: Shixiang Wang + description: |- + Provides functions and a Shiny application for downloading, + analyzing and visualizing datasets from UCSC Xena + (), which is a collection of UCSC-hosted public + databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. + date_publication: '2024-05-15' + bug_reports: https://github.com/openbiox/UCSCXenaShiny/issues + url: https://openbiox.github.io/UCSCXenaShiny/ + url_cran: https://CRAN.R-project.org/package=UCSCXenaShiny + url_git: https://github.com/openbiox/UCSCXenaShiny +UCSCXenaTools: + version: 1.4.8 + title: Download and Explore Datasets from UCSC Xena Data Hubs + maintainer: Shixiang Wang + description: |- + Download and explore datasets from UCSC Xena data hubs, which + are a collection of UCSC-hosted public databases such as TCGA, ICGC, + TARGET, GTEx, CCLE, and others. Databases are normalized so they can + be combined, linked, filtered, explored and downloaded. + date_publication: '2022-06-20' + bug_reports: https://github.com/ropensci/UCSCXenaTools/issues + url: https://docs.ropensci.org/UCSCXenaTools/ + url_cran: https://CRAN.R-project.org/package=UCSCXenaTools + url_git: https://github.com/ropensci/UCSCXenaTools +UdderQuarterInfectionData: + version: 1.0.0 + title: Udder Quarter Infection Data + maintainer: Luc Duchateau + description: The udder quarter infection data set contains infection times of individual + cow udder quarters with Corynebacterium bovis (Laevens et al. 1997 ). + Obviously, the four udder quarters are clustered within a cow, and udder quarters + are sampled only approximately monthly, generating interval-censored data. The + data set contains both covariates that change within a cow (e.g., front and rear + udder quarters) and covariates that change between cows (e.g., parity [the number + of previous calvings]). The correlation between udder infection times within a + cow also is of interest, because this is a measure of the infectivity of the agent + causing the disease. Various models have been applied to address the problem of + interdependence for right-censored event times. These models, as applied to this + data set, can be found back in the publications found in the reference list. + date_publication: '2017-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UdderQuarterInfectionData + url_git: '' +udpipe: + version: 0.8.11 + title: |- + Tokenization, Parts of Speech Tagging, Lemmatization and + Dependency Parsing with the 'UDPipe' 'NLP' Toolkit + maintainer: Jan Wijffels + description: |- + This natural language processing toolkit provides language-agnostic + 'tokenization', 'parts of speech tagging', 'lemmatization' and 'dependency + parsing' of raw text. Next to text parsing, the package also allows you to train + annotation models based on data of 'treebanks' in 'CoNLL-U' format as provided + at . The techniques are explained + in detail in the paper: 'Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 + with UDPipe', available at . + The toolkit also contains functionalities for commonly used data manipulations on texts + which are enriched with the output of the parser. Namely functionalities and algorithms + for collocations, token co-occurrence, document term matrix handling, + term frequency inverse document frequency calculations, + information retrieval metrics (Okapi BM25), handling of multi-word expressions, + keyword detection (Rapid Automatic Keyword Extraction, noun phrase extraction, syntactical patterns) + sentiment scoring and semantic similarity analysis. + date_publication: '2023-01-06' + bug_reports: '' + url: https://bnosac.github.io/udpipe/en/index.html + url_cran: https://CRAN.R-project.org/package=udpipe + url_git: https://github.com/bnosac/udpipe +udunits2: + version: 0.13.2.1 + title: Udunits-2 Bindings for R + maintainer: ORPHANED + description: Provides simple bindings to Unidata's udunits library. + date_publication: '2022-03-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=udunits2 + url_git: https://github.com/pacificclimate/Rudunits2https://www.unidata.ucar.edu/software/udunits/ +UEI: + version: 0.1.0 + title: Compute Uniform Error Index + maintainer: Dr. Ranjit Kumar Paul + description: Uniform Error Index is the weighted average of different error measures. + Uniform Error Index utilizes output from different error function and gives more + robust and stable error values. This package has been developed to compute Uniform + Error Index from ten different loss function like Error Square, Square of Square + Error, Quasi Likelihood Error, LogR-Square, Absolute Error, Absolute Square Error + etc. The weights are determined using Principal Component Analysis (PCA) algorithm + of Yeasin and Paul (2024) . + date_publication: '2024-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UEI + url_git: '' +ufRisk: + version: 1.0.7 + title: Risk Measure Calculation in Financial TS + maintainer: Sebastian Letmathe + description: |- + Enables the user to calculate Value at Risk (VaR) and Expected + Shortfall (ES) by means of various parametric and semiparametric + GARCH-type models. For the latter the estimation of the nonparametric scale + function is carried out by means of a data-driven smoothing approach. Model + quality, in terms of forecasting VaR and ES, can be assessed by means of + various backtesting methods such as the traffic light test for VaR and a + newly developed traffic light test for ES. The approaches implemented in + this package are described in e.g. Feng Y., Beran J., Letmathe S. and + Ghosh S. (2020) as well as + Letmathe S., Feng Y. and Uhde A. (2021) + . + date_publication: '2023-10-22' + bug_reports: '' + url: https://wiwi.uni-paderborn.de/en/dep4/feng/ + url_cran: https://CRAN.R-project.org/package=ufRisk + url_git: '' +ufs: + version: 0.5.12 + title: A Collection of Utilities + maintainer: Gjalt-Jorn Peters + description: |- + This is a new version of the 'userfriendlyscience' package, + which has grown a bit unwieldy. Therefore, distinct functionalities + are being 'consciously uncoupled' into different packages. This package + contains the general-purpose tools and utilities (see the + 'behaviorchange' package, the 'rosetta' package, and the + soon-to-be-released 'scd' package for other functionality), and + is the most direct 'successor' of the original 'userfriendlyscience' package. + For example, this package contains a number of basic functions to create + higher level plots, such as diamond plots, to easily plot sampling + distributions, to generate confidence intervals, to plan study sample sizes + for confidence intervals, and to do some basic operations such as + (dis)attenuate effect size estimates. + date_publication: '2024-03-09' + bug_reports: https://gitlab.com/r-packages/ufs/-/issues + url: https://ufs.opens.science + url_cran: https://CRAN.R-project.org/package=ufs + url_git: '' +ugatsdb: + version: 0.2.3 + title: Uganda Time Series Database API + maintainer: Sebastian Krantz + description: |- + An R API providing easy access to a relational database with macroeconomic, + financial and development related time series data for Uganda. + Overall more than 5000 series at varying frequency (daily, monthly, + quarterly, annual in fiscal or calendar years) can be accessed through + the API. The data is provided by the Bank of Uganda, + the Ugandan Ministry of Finance, Planning and Economic Development, + the IMF and the World Bank. The database is being updated once a month. + date_publication: '2022-11-24' + bug_reports: '' + url: https://mepd.finance.go.ug/apps.html + url_cran: https://CRAN.R-project.org/package=ugatsdb + url_git: '' +uGMAR: + version: 3.5.1 + title: |- + Estimate Univariate Gaussian and Student's t Mixture + Autoregressive Models + maintainer: Savi Virolainen + description: |- + Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR), + Student's t Mixture Autoregressive (StMAR), and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models, + quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes. + Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) , + Mika Meitz, Daniel Preve, Pentti Saikkonen (2023) , + Savi Virolainen (2022) . + date_publication: '2024-12-04' + bug_reports: https://github.com/saviviro/uGMAR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uGMAR + url_git: '' +ugomquantreg: + version: 1.0.0 + title: Quantile Regression Modeling for Unit-Gompertz Responses + maintainer: Josmar Mazucheli + description: |- + Unit-Gompertz density, cumulative distribution, quantile functions and random deviate + generation of the unit-Gompertz distribution. In addition, there are a function for fitting the + Generalized Additive Models for Location, Scale and Shape. + date_publication: '2021-06-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ugomquantreg + url_git: '' +UHM: + version: 0.3.0 + title: Unified Zero-Inflated Hurdle Regression Models + maintainer: Taban Baghfalaki + description: Run a Gibbs sampler for hurdle models to analyze data showing an excess + of zeros, which is common in zero-inflated count and semi-continuous models. The + package includes the hurdle model under Gaussian, Gamma, inverse Gaussian, Weibull, + Exponential, Beta, Poisson, negative binomial, logarithmic, Bell, generalized + Poisson, and binomial distributional assumptions. The models described in Ganjali + et al. (2024). + date_publication: '2024-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UHM + url_git: https://github.com/tbaghfalaki/UHM +uHMM: + version: '1.0' + title: Construct an Unsupervised Hidden Markov Model + maintainer: Paul TERNYNCK + description: Construct a Hidden Markov Model with states learnt by unsupervised + classification. + date_publication: '2016-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uHMM + url_git: '' +ui: + version: 0.1.1 + title: Uncertainty Intervals and Sensitivity Analysis for Missing Data + maintainer: Minna Genbaeck + description: Implements functions to derive uncertainty intervals for (i) regression + (linear and probit) parameters when outcome is missing not at random (non-ignorable + missingness) introduced in Genbaeck, M., Stanghellini, E., de Luna, X. (2015) + and Genbaeck, M., Ng, N., Stanghellini, E., de + Luna, X. (2018) ; and (ii) double robust and outcome + regression estimators of average causal effects (on the treated) with possibly + unobserved confounding introduced in Genbaeck, M., de Luna, X. (2018) . + date_publication: '2019-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ui + url_git: '' +uiucthemes: + version: 0.3.1 + title: '''R'' ''Markdown'' Themes for ''UIUC'' Documents and Presentations' + maintainer: James Balamuta + description: |- + A set of custom 'R' 'Markdown' templates for documents and + presentations with the University of Illinois at Urbana-Champaign (UIUC) + color scheme and identity standards. + date_publication: '2020-07-25' + bug_reports: https://github.com/illinois-r/uiucthemes/issues + url: http://thecoatlessprofessor.com/projects/uiucthemes/ + url_cran: https://CRAN.R-project.org/package=uiucthemes + url_git: https://github.com/illinois-r/uiucthemes +uk2us: + version: 0.1.0 + title: Convert Words Between UK and US English + maintainer: Benjamin Davies + description: Functions for converting between UK and US spellings of English words. + date_publication: '2021-02-19' + bug_reports: https://github.com/bldavies/uk2us/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uk2us + url_git: https://github.com/bldavies/uk2us +UKB.COVID19: + version: 0.1.6 + title: |- + UK Biobank COVID-19 Data Processing and Risk Factor Association + Tests + maintainer: Longfei Wang + description: Process UK Biobank COVID-19 test result data for susceptibility, severity + and mortality analyses, perform potential non-genetic COVID-19 risk factor and + co-morbidity association tests. Wang et al. (2021) . + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UKB.COVID19 + url_git: https://github.com/bahlolab/UKB.COVID19 +ukbabynames: + version: 0.3.0 + title: UK Baby Names Data + maintainer: Mine Çetinkaya-Rundel + description: Full listing of UK baby names occurring more than three times per year + between 1974 and 2020, and rankings of baby name popularity by decade from 1904 + to 1994. + date_publication: '2022-03-25' + bug_reports: https://github.com/mine-cetinkaya-rundel/ukbabynames/issues + url: https://mine-cetinkaya-rundel.github.io/ukbabynames/ + url_cran: https://CRAN.R-project.org/package=ukbabynames + url_git: '' +ukbnmr: + version: 3.2.0 + title: |- + Removal of Unwanted Technical Variation from UK Biobank NMR + Metabolomics Biomarker Data + maintainer: Scott C Ritchie + description: |- + A suite of utilities for working with the UK Biobank + Nuclear Magnetic Resonance spectroscopy (NMR) + metabolomics data . + Includes functions for extracting biomarkers from decoded UK Biobank field + data, removing unwanted technical variation from biomarker concentrations, + computing an extended set of lipid, fatty acid, and cholesterol fractions, + and for re-deriving composite biomarkers and ratios after adjusting data + for unwanted biological variation. For further details on methods see + Ritchie SC et al. Sci Data (2023) . + date_publication: '2024-11-14' + bug_reports: https://github.com/sritchie73/ukbnmr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ukbnmr + url_git: '' +ukbtools: + version: 0.11.3 + title: Manipulate and Explore UK Biobank Data + maintainer: Ken Hanscombe + description: |- + A set of tools to create a UK Biobank dataset from a UKB fileset (.tab, .r, .html), + visualize primary demographic data for a sample subset, query ICD diagnoses, + retrieve genetic metadata, read and write standard file formats for genetic analyses. + date_publication: '2019-05-15' + bug_reports: '' + url: https://kenhanscombe.github.io/ukbtools/ + url_cran: https://CRAN.R-project.org/package=ukbtools + url_git: '' +UKFE: + version: 0.4.0 + title: UK Flood Estimation + maintainer: Anthony Hammond + description: 'Functions to implement the methods of the Flood Estimation Handbook + (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently + the package uses NRFA peak flow dataset version 13. Aside from FEH functionality, + further hydrological functions are available. Most of the methods implemented + in this package are described in one or more of the following: "Flood Estimation + Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation + Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional + Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, + ISBN: 978 0 521 01940 8). "Proposal of the extreme rank plot for extreme value + analysis: with an emphasis on flood frequency studies", Hammond (2019, ). + "Making better use of local data in flood frequency estimation", Environment Agency + (2017, ISBN: 978 1 84911 387 8). "Sampling uncertainty of UK design flood estimation" + , Hammond (2021, ). "Improving the FEH statistical procedures + for flood frequency estimation", Environment Agency (2008, ISBN: 978 1 84432 920 + 5). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, + ISBN 0 948540 45 1). Wallingford HydroSolutions, (2016, ). + Data from the UK National River Flow Archive (, terms + and conditions: ).' + date_publication: '2025-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UKFE + url_git: '' +ukgasapi: + version: '0.21' + title: API for UK Energy Market Information + maintainer: Timothy Wong + description: Allows users to access live UK energy market information via various + APIs. + date_publication: '2020-11-06' + bug_reports: https://github.com/timothywong731/ukgasapi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ukgasapi + url_git: '' +UKgrid: + version: 0.1.3 + title: The UK National Electricity Transmission System Dataset + maintainer: Rami Krispin + description: A time series of the national grid demand (high-voltage electric power + transmission network) in the UK since 2011. + date_publication: '2020-07-05' + bug_reports: https://github.com/RamiKrispin/UKgrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UKgrid + url_git: https://github.com/RamiKrispin/UKgrid +uklr: + version: 1.0.2 + title: Client to United Kingdom Land Registry + maintainer: Kostas Vasilopoulos + description: |- + Access data from Land Registry Open Data + through 'SPARQL' queries. 'uklr' + supports the house price index, transaction and price paid data. + date_publication: '2021-05-25' + bug_reports: https://github.com/kvasilopoulos/uklr/issues + url: https://kvasilopoulos.github.io/uklr/ + url_cran: https://CRAN.R-project.org/package=uklr + url_git: https://github.com/kvasilopoulos/uklr/ +ukpolice: + version: 0.2.2 + title: Download Data on UK Police and Crime + maintainer: Evan Odell + description: |- + Downloads data from the 'UK Police' public data API, + the full docs of which are available at . + Includes data on police forces and police force areas, crime reports, + and the use of stop-and-search powers. + date_publication: '2020-08-03' + bug_reports: https://github.com/EvanOdell/ukpolice/issues + url: https://docs.evanodell.com/ukpolice + url_cran: https://CRAN.R-project.org/package=ukpolice + url_git: https://github.com/EvanOdell/ukpolice/ +ulex: + version: 0.1.0 + title: Unique Location Extractor + maintainer: Robert Marty + description: Extracts coordinates of an event location from text based on dictionaries + of landmarks, roads, and areas. Only returns the location of an event of interest + and ignores other location references; for example, if determining the location + of a road traffic crash from the text "crash near [location 1] heading towards + [location 2]", only the coordinates of "location 1" would be returned. Moreover, + accounts for differences in spelling between how a user references a location + and how a location is captured in location dictionaries. + date_publication: '2024-06-17' + bug_reports: '' + url: https://dime-worldbank.github.io/ulex/ + url_cran: https://CRAN.R-project.org/package=ulex + url_git: '' +ulid: + version: 0.4.0 + title: |- + Generate Universally Unique 'Lexicographically' 'Sortable' + Identifiers + maintainer: Dirk Eddelbuettel + description: |- + Universally unique identifiers ('UUIDs') can be sub-optimal for many + uses-cases because they are not the most character efficient way of encoding + 128 bits of randomness; v1/v2 versions are impractical in many environments, + as they require access to a unique, stable MAC address; v3/v5 versions require + a unique seed and produce randomly distributed IDs, which can cause fragmentation + in many data structures; v4 provides no other information than randomness which + can cause fragmentation in many data structures. Providing an alternative, 'ULIDs' + () have 128-bit compatibility with 'UUID', 1.21e+24 + unique 'ULIDs' per millisecond, support standard (text) sorting, canonically encoded + as a 26 character string, as opposed to the 36 character 'UUID', use 'base32' + encoding for better efficiency and readability (5 bits per character), are case + insensitive, have no special characters (i.e. are 'URL' safe) and have a monotonic + sort order (correctly detects and handles the same millisecond). + date_publication: '2024-06-04' + bug_reports: https://github.com/eddelbuettel/ulid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ulid + url_git: https://github.com/eddelbuettel/ulid +ulrb: + version: 0.1.5 + title: |- + Unsupervised Learning Based Definition of Microbial Rare + Biosphere + maintainer: Francisco Pascoal + description: |- + A tool to define rare biosphere. 'ulrb' solves the problem of the + definition of rarity by replacing arbitrary thresholds with an unsupervised machine + learning algorithm (partitioning around medoids, or k-medoids). This algorithm + works for any type of microbiome data, provided there is a species abundance table. + For validation of this method to different species abundance tables see Pascoal et al, 2024 (in peer-review). + This method also works for non-microbiome data. + date_publication: '2024-06-18' + bug_reports: https://github.com/pascoalf/ulrb/issues + url: https://pascoalf.github.io/ulrb/ + url_cran: https://CRAN.R-project.org/package=ulrb + url_git: '' +Ultimixt: + version: '2.1' + title: |- + Bayesian Analysis of Location-Scale Mixture Models using a + Weakly Informative Prior + maintainer: Kaniav Kamary + description: A generic reference Bayesian analysis of unidimensional mixture distributions + obtained by a location-scale parameterisation of the model is implemented. The + including functions simulate and summarize posterior samples for location-scale + mixture models using a weakly informative prior. There is no need to define priors + for scale-location parameters except two hyperparameters in which are associated + with a Dirichlet prior for weights and a simplex. + date_publication: '2017-03-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ultimixt + url_git: '' +ultrapolaRplot: + version: 0.1.1 + title: Plotting Ultrasound Tongue Traces + maintainer: Yana Outkin + description: |- + Plots traced ultrasound tongue imaging data according to a polar coordinate system. + There is currently support for plotting means and standard deviations of each category's trace; + Smoothing Splines Analysis of Variance (SSANOVA) could be implemented as well. The origin of the + polar coordinates may be defined manually or automatically determined based on different + algorithms. + Currently 'ultrapolaRplot' supports ultrasound tongue imaging trace data from 'UltraTrace' + (). 'UltraTrace' is capable of importing data from + Articulate Instruments AAA. + 'read_textgrid.R' is required for opening TextGrids to determine category and alignment + information of ultrasound traces. + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ultrapolaRplot + url_git: '' +umap: + version: 0.2.10.0 + title: Uniform Manifold Approximation and Projection + maintainer: Tomasz Konopka + description: |- + Uniform manifold approximation and projection is a technique + for dimension reduction. The algorithm was described by McInnes and + Healy (2018) in . This package provides an interface + for two implementations. One is written from scratch, including components + for nearest-neighbor search and for embedding. The second implementation + is a wrapper for 'python' package 'umap-learn' (requires separate + installation, see vignette for more details). + date_publication: '2023-02-01' + bug_reports: https://github.com/tkonopka/umap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=umap + url_git: https://github.com/tkonopka/umap +Umatrix: + version: 4.0.1 + title: Visualization of Structures in High-Dimensional Data + maintainer: Jorn Lotsch + description: By gaining the property of emergence through self-organization, the + enhancement of SOMs(self organizing maps) is called Emergent SOM (ESOM). The result + of the projection by ESOM is a grid of neurons which can be visualised as a three + dimensional landscape in form of the Umatrix. Further details can be found in + the referenced publications (see url). This package offers tools for calculating + and visualising the ESOM as well as Umatrix, Pmatrix and UStarMatrix. All the + functionality is also available through graphical user interfaces implemented + in 'shiny'. Based on the recognized data structures, the method can be used to + generate new data. + date_publication: '2024-08-17' + bug_reports: '' + url: http://wscg.zcu.cz/wscg2016/short/A43-full.pdf + url_cran: https://CRAN.R-project.org/package=Umatrix + url_git: '' +umbridge: + version: '1.0' + title: Integration for the UM-Bridge Protocol + maintainer: Linus Seelinger + description: A convenient wrapper for the UM-Bridge protocol. UM-Bridge is a protocol + designed for coupling uncertainty quantification (or statistical / optimization) + software to numerical models. A model is represented as a mathematical function + with optional support for derivatives via Jacobian actions etc. + date_publication: '2022-09-23' + bug_reports: https://github.com/um-bridge + url: '' + url_cran: https://CRAN.R-project.org/package=umbridge + url_git: '' +umiAnalyzer: + version: 1.0.0 + title: |- + Tools for Analyzing Sequencing Data with Unique Molecular + Identifiers + maintainer: Stefan Filges + description: |- + Tools for analyzing sequencing data containing unique + molecular identifiers generated by 'UMIErrorCorrect' + (). + date_publication: '2021-11-25' + bug_reports: https://github.com/sfilges/umiAnalyzer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=umiAnalyzer + url_git: https://github.com/sfilges/umiAnalyzer +Umoments: + version: 1.0.1 + title: Unbiased Central Moment Estimates + maintainer: Inna Gerlovina + description: |- + Calculates one-sample unbiased central moment estimates and + two-sample pooled estimates up to 6th order, including estimates of + powers and products of central moments. Provides the machinery for + obtaining unbiased central moment estimators beyond 6th order by generating + expressions for expectations of raw sample moments and their powers and + products. + Gerlovina and Hubbard (2019) . + date_publication: '2024-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Umoments + url_git: '' +ump: + version: 0.5-8 + title: Uniformly Most Powerful Tests + maintainer: Charles J. Geyer + description: |- + Does uniformly most powerful (UMP) and uniformly most + powerful unbiased (UMPU) tests. At present only distribution implemented + is binomial distribution. Also does fuzzy tests and confidence intervals + (following Geyer and Meeden, 2005, ) + for the binomial + distribution (one-tailed procedures based on UMP test and two-tailed + procedures based on UMPU test). + date_publication: '2017-03-27' + bug_reports: '' + url: http://www.stat.umn.edu/geyer/fuzz/ + url_cran: https://CRAN.R-project.org/package=ump + url_git: '' +Umpire: + version: 2.0.11 + title: Simulating Realistic Gene Expression and Clinical Data + maintainer: Kevin R. Coombes + description: |- + The Ultimate Microrray Prediction, Reality and Inference + Engine (UMPIRE) is a package to facilitate the simulation of realistic + microarray data sets with links to associated outcomes. See Zhang and + Coombes (2012) . Version 2.0 adds the + ability to simulate realistic mixed-typed clinical data. + date_publication: '2025-02-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Umpire + url_git: http://oompa.r-forge.r-project.org/ +umx: + version: 4.21.0 + title: Structural Equation Modeling and Twin Modeling in R + maintainer: Timothy C. Bates + description: |- + Quickly create, run, and report structural equation models, and twin models. + See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS. + Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. + Twin Research and Human Genetics, 22, 27-41. . + date_publication: '2024-11-15' + bug_reports: https://github.com/tbates/umx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=umx + url_git: https://github.com/tbates/umx#readme +UnalR: + version: 1.0.0 + title: Una implementación de funciones de uso interno + maintainer: Jeison Alarcón + description: |- + Una herramienta rápida y consistente para la disposición de microdatos + y la visualización de las cifras y estadísticas oficiales de la Universidad + Nacional de Colombia . Contiene una biblioteca de + funciones gráficas, tanto estáticas como interactivas, que ofrece numerosos + tipos de gráficos con una sintaxis altamente configurable y simple. Entre estos + encontramos la visualización de tablas HTML, series, gráficos de barras y + circulares, mapas, etc. Todo lo anterior apoyado en bibliotecas de JavaScript. + English: A fast and consistent tool for the arrangement of microdata and the + visualization of official figures and statistics from the National University + of Colombia . It includes a library of graphical functions, + both static and interactive, offering numerous types of charts with a highly + configurable and simple syntax. Among these, we find the visualization of HTML + tables, series, bar and pie charts, maps, etc. It provides the capability to + transition from the interactive to the dynamic world and from one library to + another without changing function or syntax. + date_publication: '2024-05-25' + bug_reports: https://github.com/estadisticaun/UnalR/issues + url: https://unal.edu.co + url_cran: https://CRAN.R-project.org/package=UnalR + url_git: https://github.com/estadisticaun/UnalR +unbalhaar: + version: '2.1' + title: Function Estimation via Unbalanced Haar Wavelets + maintainer: Piotr Fryzlewicz + description: |- + Top-down and bottom-up algorithms + for nonparametric function estimation in Gaussian noise using + Unbalanced Haar wavelets. + date_publication: '2022-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unbalhaar + url_git: '' +UncDecomp: + version: 1.0.1 + title: Uncertainty Decomposition + maintainer: Seonghyeon Kim + description: |- + If a procedure consists of several stages and there are several models that can be selected for each stage, + uncertainty of the procedure can be decomposed by stages or models. + This package includes the ANOVA-based method, the cumulative uncertainty-based method, and the balanced decomposition method. + Yongdai Kim et al. (2019) is a related paper which is accessible via the URL below. + date_publication: '2019-11-07' + bug_reports: '' + url: https://www.sciencedirect.com/science/article/pii/S2589915519300082 + url_cran: https://CRAN.R-project.org/package=UncDecomp + url_git: '' +uncertainty: + version: 0.2.0 + title: Uncertainty Estimation and Contribution Analysis + maintainer: Hugo Gasca-Aragon + description: Implements the Gaussian method of first and second order, the Kragten + numerical method and the Monte Carlo simulation method for uncertainty estimation + and analysis. + date_publication: '2018-05-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uncertainty + url_git: '' +uncertainUCDP: + version: 0.5.2 + title: |- + Parametric Mixture Models for Uncertainty Estimation of + Fatalities in UCDP Conflict Data + maintainer: David Randahl + description: Provides functions for estimating uncertainty in the number of fatalities + in the Uppsala Conflict Data Program (UCDP) data. The package implements a parametric + reported-value Gumbel mixture distribution that accounts for the uncertainty in + the number of fatalities in the UCDP data. The model is based on information from + a survey on UCDP coders and how they view the uncertainty of the number of fatalities + from UCDP events. The package provides functions for making random draws of fatalities + from the mixture distribution, as well as to estimate percentiles, quantiles, + means, and other statistics of the distribution. Full details on the survey and + estimation procedure can be found in Vesco et al (2024). + date_publication: '2024-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uncertainUCDP + url_git: '' +uncmbb: + version: 0.2.2 + title: UNC Men's Basketball Match Results Since 1949-1950 Season + maintainer: Jay Lee + description: Dataset contains select attributes for each match result since 1949-1950 + season for UNC men's basketball team. + date_publication: '2021-01-04' + bug_reports: https://github.com/joongsup/uncmbb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uncmbb + url_git: https://github.com/joongsup/uncmbb +uncorbets: + version: 0.1.2 + title: Uncorrelated Bets via Minimum Torsion Algorithm + maintainer: Bernardo Reckziegel + description: |- + Implements Minimum Torsion for portfolio diversification as + described in Meucci, Attilio (2013) . + date_publication: '2024-02-20' + bug_reports: https://github.com/Reckziegel/uncorbets/issues + url: https://reckziegel.github.io/uncorbets/ + url_cran: https://CRAN.R-project.org/package=uncorbets + url_git: https://github.com/Reckziegel/uncorbets +UNCOVER: + version: 1.1.0 + title: |- + Utilising Normalisation Constant Optimisation via Edge Removal + (UNCOVER) + maintainer: Samuel Emerson + description: |- + Model data with a suspected clustering structure (either in + co-variate space, regression space or both) using a Bayesian product model + with a logistic regression likelihood. Observations are represented + graphically and clusters are formed through various edge removals or + additions. Cluster quality is assessed through the log Bayesian evidence of + the overall model, which is estimated using either a Sequential Monte Carlo + sampler or a suitable transformation of the Bayesian Information Criterion + as a fast approximation of the former. The internal Iterated Batch + Importance Sampling scheme (Chopin (2002 )) is + made available as a free standing function. + date_publication: '2023-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UNCOVER + url_git: '' +understandBPMN: + version: 1.1.1 + title: Calculator of Understandability Metrics for BPMN + maintainer: Gert Janssenswillen + description: 'Calculate several understandability metrics of BPMN models. BPMN stands + for business process modelling notation and is a language for expressing business + processes into business process diagrams. Examples of these understandability + metrics are: average connector degree, maximum connector degree, sequentiality, + cyclicity, diameter, depth, token split, control flow complexity, connector mismatch, + connector heterogeneity, separability, structuredness and cross connectivity. + See R documentation and paper on metric implementation included in this package + for more information concerning the metrics.' + date_publication: '2019-09-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=understandBPMN + url_git: '' +undidR: + version: 1.0.1 + title: Difference-in-Differences with Unpoolable Data + maintainer: Eric Jamieson + description: |- + A framework for estimating difference-in-differences with + unpoolable data, based on Karim, Webb, Austin, and Strumpf (2024) + . Supports common or staggered adoption, multiple + groups, and the inclusion of covariates. Also computes p-values for the + aggregate average treatment effect on the treated via the + randomization inference procedure described in MacKinnon and Webb (2020) + . + date_publication: '2025-02-24' + bug_reports: https://github.com/ebjamieson97/undidR/issues + url: https://ebjamieson97.github.io/undidR/ + url_cran: https://CRAN.R-project.org/package=undidR + url_git: https://github.com/ebjamieson97/undidR +unglue: + version: 0.1.0 + title: Extract Matched Substrings Using a Pattern + maintainer: Antoine Fabri + description: Use syntax inspired by the package 'glue' to extract matched substrings + in a more intuitive and compact way than by using standard regular expressions. + date_publication: '2020-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unglue + url_git: '' +ungroup: + version: 1.4.4 + title: |- + Penalized Composite Link Model for Efficient Estimation of + Smooth Distributions from Coarsely Binned Data + maintainer: Marius D. Pascariu + description: |- + Versatile method for ungrouping histograms (binned count data) + assuming that counts are Poisson distributed and that the underlying sequence + on a fine grid to be estimated is smooth. The method is based on the composite + link model and estimation is achieved by maximizing a penalized likelihood. + Smooth detailed sequences of counts and rates are so estimated from the binned + counts. Ungrouping binned data can be desirable for many reasons: Bins can be + too coarse to allow for accurate analysis; comparisons can be hindered when + different grouping approaches are used in different histograms; and the last + interval is often wide and open-ended and, thus, covers a lot of information + in the tail area. Age-at-death distributions grouped in age classes and + abridged life tables are examples of binned data. Because of modest assumptions, + the approach is suitable for many demographic and epidemiological applications. + For a detailed description of the method and applications see + Rizzi et al. (2015) . + date_publication: '2024-01-31' + bug_reports: https://github.com/mpascariu/ungroup/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ungroup + url_git: https://github.com/mpascariu/ungroup +unhcrdown: + version: 0.6.0 + title: UNHCR Branded Templates for R Markdown Documents + maintainer: Cédric Vidonne + description: |- + Create United Nations High Commissioner for Refugees (UNHCR) + branded documents, presentations, and reports using R Markdown templates. + This package provides customized formats that align with UNHCR's official + brand guidelines for creating professional PDF reports, Word documents, + PowerPoint presentations, and HTML outputs. + date_publication: '2025-01-17' + bug_reports: https://github.com/unhcr-dataviz/unhcrdown/issues + url: https://unhcr-dataviz.github.io/unhcrdown/ + url_cran: https://CRAN.R-project.org/package=unhcrdown + url_git: https://github.com/unhcr-dataviz/unhcrdown +unhcrthemes: + version: 0.6.3 + title: UNHCR 'ggplot2' Theme and Colour Palettes + maintainer: Cédric Vidonne + description: |- + A 'ggplot2' theme and color palettes following + the United Nations High Commissioner for Refugees (UNHCR) Data Visualization Guidelines recommendations. + date_publication: '2025-01-16' + bug_reports: https://github.com/unhcr-dataviz/unhcrthemes/issues + url: https://unhcr-dataviz.github.io/unhcrthemes/ + url_cran: https://CRAN.R-project.org/package=unhcrthemes + url_git: https://github.com/unhcr-dataviz/unhcrthemes +unheadr: + version: 0.4.0 + title: Handle Data with Messy Header Rows and Broken Values + maintainer: Luis D. Verde Arregoitia + description: |- + Verb-like functions to work with messy data, often derived from + spreadsheets or parsed PDF tables. Includes functions for unwrapping + values broken up across rows, relocating embedded grouping values, + and to annotate meaningful formatting in spreadsheet files. + date_publication: '2024-05-13' + bug_reports: https://github.com/luisDVA/unheadr/issues + url: https://unheadr.liomys.mx/ + url_cran: https://CRAN.R-project.org/package=unheadr + url_git: https://github.com/luisDVA/unheadr +uni.shrinkage: + version: 1.0.0 + title: Shrinkage Estimation for Univariate Normal Mean + maintainer: Nanami Taketomi + description: Implement a shrinkage estimation for the univariate normal mean based + on a preliminary test (pretest) estimator. This package also provides the confidence + interval based on pivoting the cumulative density function. The methodologies + are published in Taketomi et al.(2024) and Taketomi + et al.(2024-)(under review). + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uni.shrinkage + url_git: '' +uni.survival.tree: + version: '1.5' + title: |- + A Survival Tree Based on Stabilized Score Tests for + High-dimensional Covariates + maintainer: Takeshi Emura + description: |- + A classification (decision) tree is constructed from survival data with high-dimensional covariates. + The method is a robust version of the logrank tree, where the variance is stabilized. + The main function "uni.tree" returns a classification tree for a given survival dataset. + The inner nodes (splitting criterion) are selected by minimizing the P-value of the two-sample the score tests. + The decision of declaring terminal nodes (stopping criterion) is the P-value threshold given by an argument (specified by user). + This tree construction algorithm is proposed by Emura et al. (2021, in review). + date_publication: '2021-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uni.survival.tree + url_git: '' +uniah: + version: '1.2' + title: Unimodal Additive Hazards Model + maintainer: Yunro Chung + description: Nonparametric estimation of a unimodal or U-shape covariate effect + under additive hazards model. + date_publication: '2024-01-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uniah + url_git: '' +Unico: + version: 0.1.0 + title: Unified Cross-Omics Deconvolution + maintainer: Zeyuan Chen + description: |- + UNIfied Cross-Omics deconvolution (Unico) deconvolves + standard 2-dimensional bulk matrices of samples by features into a + 3-dimensional tensors representing samples by features by cell types. + Unico stands out as the first principled model-based deconvolution + method that is theoretically justified for any heterogeneous genomic + data. For more details see Chen and Rahmani et al. (2024) + . + date_publication: '2024-02-26' + bug_reports: https://github.com/cozygene/Unico/issues + url: https://cozygene.github.io/Unico/ + url_cran: https://CRAN.R-project.org/package=Unico + url_git: '' +Unicode: + version: 15.1.0-1 + title: Unicode Data and Utilities + maintainer: Kurt Hornik + description: Data from Unicode 15.1.0 and related utilities. + date_publication: '2023-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Unicode + url_git: '' +unicol: + version: 0.3.0 + title: The Colors of your University + maintainer: Hansjoerg Neth + description: Most universities use specific color combinations to express their + unique brand identity. The 'unicol' package provides the colors and color palettes + of various universities for easy plotting and printing in R. We collect and provide + a diverse range of color palettes for creating scientific visualizations. + date_publication: '2024-05-01' + bug_reports: https://github.com/hneth/unicol/issues + url: https://hneth.github.io/unicol/ + url_cran: https://CRAN.R-project.org/package=unicol + url_git: https://github.com/hneth/unicol/ +UniExactFunTest: + version: 1.0.1 + title: Uniform Exact Functional Tests for Contingency Tables + maintainer: Yiyi Li + description: |- + Testing whether two discrete variables have a functional + relationship under null distributions where the two variables are + statistically independent with fixed marginal counts. + The fast enumeration algorithm was based on (Nguyen et al. 2020) . + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UniExactFunTest + url_git: '' +unifDAG: + version: 1.0.4 + title: Uniform Sampling of Directed Acyclic Graphs + maintainer: Markus Kalisch + description: |- + Uniform sampling of Directed Acyclic Graphs (DAG) using exact + enumeration by relating each DAG to a sequence of outpoints (nodes with no + incoming edges) and then to a composition of integers as suggested by + Kuipers, J. and Moffa, G. (2015) . + date_publication: '2024-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unifDAG + url_git: '' +unifed: + version: 1.1.6 + title: The Unifed Distribution + maintainer: Oscar Alberto Quijano Xacur + description: Probability functions, family for glm() and Stan code for working with + the unifed distribution (Quijano Xacur, 2019; ). + date_publication: '2022-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unifed + url_git: '' +UnifiedDoseFinding: + version: 0.1.10 + title: Dose-Finding Methods for Non-Binary Outcomes + maintainer: Chia-Wei Hsu + description: 'In many phase I trials, the design goal is to find the dose associated + with a certain target toxicity rate. In some trials, the goal can be to find the + dose with a certain weighted sum of rates of various toxicity grades. For others, + the goal is to find the dose with a certain mean value of a continuous response. + This package provides the setup and calculations needed to run a dose-finding + trial with non-binary endpoints and performs simulations to assess design’s operating + characteristics under various scenarios. Three dose finding designs are included + in this package: unified phase I design (Ivanova et al. (2009) ), + Quasi-CRM/Robust-Quasi-CRM (Yuan et al. (2007) , + Pan et al. (2014) ) and generalized BOIN design + (Mu et al. (2018) ). The toxicity endpoints can be handled + with these functions including equivalent toxicity score (ETS), total toxicity + burden (TTB), general continuous toxicity endpoints, with incorporating ordinal + grade toxicity information into dose-finding procedure. These functions allow + customization of design characteristics to vary sample size, cohort sizes, target + dose-limiting toxicity (DLT) rates, discrete or continuous toxicity score, and + incorporate safety and/or stopping rules.' + date_publication: '2022-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UnifiedDoseFinding + url_git: '' +unifir: + version: 0.2.4 + title: A Unifying API for Calling the 'Unity' '3D' Video Game Engine + maintainer: Michael Mahoney + description: |- + Functions for the creation and manipulation of scenes and objects + within the 'Unity' '3D' video game engine (). Specific + focuses include the creation and import of terrain data and 'GameObjects' as + well as scene management. + date_publication: '2024-02-01' + bug_reports: https://github.com/ropensci/unifir/issues + url: https://docs.ropensci.org/unifir/ + url_cran: https://CRAN.R-project.org/package=unifir + url_git: https://github.com/ropensci/unifir +uniformly: + version: 0.5.0 + title: Uniform Sampling + maintainer: Stéphane Laurent + description: |- + Uniform sampling on various geometric shapes, such as + spheres, ellipsoids, simplices. + date_publication: '2023-07-18' + bug_reports: https://github.com/stla/uniformly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uniformly + url_git: https://github.com/stla/uniformly +unigd: + version: 0.1.3 + title: Universal Graphics Device + maintainer: Florian Rupprecht + description: |- + A unified R graphics backend. Render R graphics fast and easy to many common file formats. + Provides a thread safe 'C' interface for asynchronous rendering of R graphics. + date_publication: '2025-02-19' + bug_reports: https://github.com/nx10/unigd/issues + url: https://nx10.github.io/unigd/ + url_cran: https://CRAN.R-project.org/package=unigd + url_git: https://github.com/nx10/unigd +UniIsoRegression: + version: 0.0-0 + title: Unimodal and Isotonic L1, L2 and Linf Regression + maintainer: Zhipeng Xu + description: 'Perform L1 or L2 isotonic and unimodal regression on 1D weighted or + unweighted input vector and isotonic regression on 2D weighted or unweighted input + vector. It also performs L infinity isotonic and unimodal regression on 1D unweighted + input vector. Reference: Quentin F. Stout (2008) . + Spouge, J., Wan, H. & Wilbur, W.(2003) . Q.F. Stout + (2013) .' + date_publication: '2017-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UniIsoRegression + url_git: https://github.com/xzp1995/UniIsoRegression +unikn: + version: 1.0.0 + title: |- + Graphical Elements of the University of Konstanz's Corporate + Design + maintainer: Hansjoerg Neth + description: Define and use graphical elements of corporate design manuals in R. + The 'unikn' package provides color functions (by defining dedicated colors and + color palettes, and commands for finding, changing, viewing, and using them) and + styled text elements (e.g., for marking, underlining, or plotting colored titles). + The pre-defined range of colors and text decoration functions is based on the + corporate design of the University of Konstanz , + but can be adapted and extended for other purposes or institutions. + date_publication: '2024-04-16' + bug_reports: https://github.com/hneth/unikn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unikn + url_git: '' +unine: + version: 0.2.0 + title: Unine Light Stemmer + maintainer: Michaël Benesty + description: |- + Implementation of "light" stemmers for French, German, Italian, Spanish, Portuguese, Finnish, Swedish. + They are based on the same work as the "light" stemmers found in 'SolR' or 'ElasticSearch' . + A "light" stemmer consists in removing inflections only for noun and adjectives. + Indexing verbs for these languages is not of primary importance compared to nouns and adjectives. + The stemming procedure for French is described in (Savoy, 1999) . + date_publication: '2019-04-13' + bug_reports: https://github.com/pommedeterresautee/unine/issues + url: https://pommedeterresautee.github.io/unine/ + url_cran: https://CRAN.R-project.org/package=unine + url_git: https://github.com/pommedeterresautee/unine +UniprotR: + version: 2.4.0 + title: Retrieving Information of Proteins from Uniprot + maintainer: Mohamed Soudy + description: Connect to Uniprot to retrieve information + about proteins using their accession number such information could be name or + taxonomy information, For detailed information kindly read the publication . + date_publication: '2024-03-05' + bug_reports: https://github.com/Proteomicslab57357/UniprotR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UniprotR + url_git: https://github.com/Proteomicslab57357/UniprotR +uniqtag: + version: 1.0.1 + title: Abbreviate Strings to Short, Unique Identifiers + maintainer: Shaun Jackman + description: For each string in a set of strings, determine a unique tag that is + a substring of fixed size k unique to that string, if it has one. If no such unique + substring exists, the least frequent substring is used. If multiple unique substrings + exist, the lexicographically smallest substring is used. This lexicographically + smallest substring of size k is called the "UniqTag" of that string. + date_publication: '2022-06-10' + bug_reports: https://github.com/sjackman/uniqtag/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uniqtag + url_git: https://github.com/sjackman/uniqtag +uniReg: + version: '1.1' + title: Unimodal Penalized Spline Regression using B-Splines + maintainer: Claudia Koellmann + description: |- + Univariate spline regression. It is possible to add the shape constraint of unimodality and predefined or + self-defined penalties on the B-spline coefficients. + date_publication: '2016-06-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uniReg + url_git: '' +unisensR: + version: 0.3.3 + title: Read 'Unisens' Data + maintainer: Martin Penzel + description: Provides the ability to read 'Unisens' data into R. 'Unisens' is a + universal data format for multi sensor data. + date_publication: '2020-04-29' + bug_reports: https://github.com/Unisens/unisensR/issues + url: http://unisens.org/ + url_cran: https://CRAN.R-project.org/package=unisensR + url_git: '' +uniset: + version: 0.3.1 + title: Dynamic Settings File + maintainer: Bernhard Pollner + description: Any package (subsequently called 'target package') is enabled to provide + its users an easily accessible, user-friendly and human readable text file where + key=value pairs (used by functions defined in the target package) can be saved. + This settings file lives in a location defined by the user of the target package, + and its user-defined values remain unchanged even when the author of the target + package is introducing or deleting keys, or when the target package is updated + or re-installed. + date_publication: '2022-03-27' + bug_reports: https://github.com/bpollner/uniset/issues + url: https://bpollner.github.io/uniset/ + url_cran: https://CRAN.R-project.org/package=uniset + url_git: https://github.com/bpollner/uniset +UnitCircle: + version: 0.1.3 + title: Check if Roots of a Polynomial Lie Outside the Unit Circle + maintainer: Jonathan Berrisch + description: The uc.check() function checks whether the roots of a given polynomial + lie outside the Unit circle. You can also easily draw an unit circle. + date_publication: '2018-07-27' + bug_reports: https://github.com/BerriJ/UnitCircle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UnitCircle + url_git: https://github.com/BerriJ/UnitCircle +unitedR: + version: '0.4' + title: Assessment and Evaluation of Formations in United + maintainer: David Schindler + description: |- + United is a software tool which can be downloaded at the following + website . In general, it is + a virtual manager game for football teams. This package contains helpful + functions for determining an optimal formation for a virtual match in + United. E.g. knowing that the opponent has a strong defensive it is + advisable to beat him in the midfield. Furthermore, this package contains + functions for computing the optimal usage of hardness in a game. + date_publication: '2020-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unitedR + url_git: '' +unitizer: + version: 1.4.21 + title: Interactive R Unit Tests + maintainer: Brodie Gaslam + description: |- + Simplifies regression tests by comparing objects produced by test + code with earlier versions of those same objects. If objects are unchanged + the tests pass, otherwise execution stops with error details. If in + interactive mode, tests can be reviewed through the provided interactive + environment. + date_publication: '2024-05-18' + bug_reports: https://github.com/brodieG/unitizer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unitizer + url_git: https://github.com/brodieG/unitizer +unitquantreg: + version: 0.0.6 + title: Parametric Quantile Regression Models for Bounded Data + maintainer: André F. B. Menezes + description: A collection of parametric quantile regression models for bounded data. + At present, the package provides 13 parametric quantile regression models. It + can specify regression structure for any quantile and shape parameters. It also + provides several S3 methods to extract information from fitted model, such as + residual analysis, prediction, plotting, and model comparison. For more computation + efficient the [dpqr]'s, likelihood, score and hessian functions are written in + C++. For further details see Mazucheli et. al (2022) . + date_publication: '2023-09-06' + bug_reports: https://github.com/AndrMenezes/unitquantreg/issues + url: https://andrmenezes.github.io/unitquantreg/ + url_cran: https://CRAN.R-project.org/package=unitquantreg + url_git: '' +units: + version: 0.8-5 + title: Measurement Units for R Vectors + maintainer: Edzer Pebesma + description: |- + Support for measurement units in R vectors, matrices + and arrays: automatic propagation, conversion, derivation + and simplification of units; raising errors in case of unit + incompatibility. Compatible with the POSIXct, Date and difftime + classes. Uses the UNIDATA udunits library and unit database for + unit compatibility checking and conversion. + Documentation about 'units' is provided in the paper by Pebesma, Mailund & + Hiebert (2016, ), included in this package as a + vignette; see 'citation("units")' for details. + date_publication: '2023-11-28' + bug_reports: https://github.com/r-quantities/units/issues + url: https://r-quantities.github.io/units/ + url_cran: https://CRAN.R-project.org/package=units + url_git: https://github.com/r-quantities/units +UnitStat: + version: 1.1.0 + title: Performs Unit Root Test Statistics + maintainer: Ankita Sharma + description: |- + A test to understand the stability of the underlying + stochastic data. Helps the user’s understand whether the random variable under + consideration is stationary or non-stationary without any manual interpretation + of the results. It further ensures to check all the prerequisites and assumptions which + are underlying the unit root test statistics and if the underlying data is found to be non-stationary in all + the 4 lags the function diagnoses the input data and returns with an optimised solution on the same. + date_publication: '2021-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UnitStat + url_git: '' +unittest: + version: 1.7-0 + title: TAP-Compliant Unit Testing + maintainer: Jamie Lentin + description: Concise TAP compliant unit testing package. + Authored tests can be run using CMD check with minimal implementation overhead. + date_publication: '2024-08-16' + bug_reports: https://github.com/ravingmantis/unittest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unittest + url_git: '' +unival: + version: 1.1.0 + title: |- + Assessing Essential Unidimensionality Using External Validity + Information + maintainer: David Navarro-Gonzalez + description: |- + Assess essential unidimensionality using external validity + information using the procedure proposed by Ferrando & Lorenzo-Seva + (2019) . Provides two indices for assessing + differential and incremental validity, both based on a second-order + modelling schema for the general factor. + date_publication: '2021-06-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unival + url_git: '' +univariateML: + version: 1.1.1 + title: Maximum Likelihood Estimation for Univariate Densities + maintainer: Jonas Moss + description: |- + User-friendly maximum likelihood estimation (Fisher (1921) + ) of univariate densities. + date_publication: '2022-01-25' + bug_reports: https://github.com/JonasMoss/univariateML/issues + url: https://jonasmoss.github.io/univariateML/ + url_cran: https://CRAN.R-project.org/package=univariateML + url_git: https://github.com/JonasMoss/univariateML +UniversalCVI: + version: 1.2.0 + title: Hard and Soft Cluster Validity Indices + maintainer: Nathakhun Wiroonsri + description: |- + Algorithms for checking the accuracy of a clustering result with known classes, computing cluster validity indices, and generating plots for comparing them. + The package is compatible with K-means, fuzzy C means, EM clustering, and hierarchical clustering (single, average, and complete linkage). + The details of the indices in this package can be found in: + J. C. Bezdek, M. Moshtaghi, T. Runkler, C. Leckie (2016) , + T. Calinski, J. Harabasz (1974) , + C. H. Chou, M. C. Su, E. Lai (2004) , + D. L. Davies, D. W. Bouldin (1979) , + J. C. Dunn (1973) , + F. Haouas, Z. Ben Dhiaf, A. Hammouda, B. Solaiman (2017) , + M. Kim, R. S. Ramakrishna (2005) , + S. H. Kwon (1998) , + S. H. Kwon, J. Kim, S. H. Son (2021) , + G. W. Miligan (1980) , + M. K. Pakhira, S. Bandyopadhyay, U. Maulik (2004) , + M. Popescu, J. C. Bezdek, T. C. Havens, J. M. Keller (2013) , + S. Saitta, B. Raphael, I. Smith (2007) , + A. Starczewski (2017) , + Y. Tang, F. Sun, Z. Sun (2005) , + N. Wiroonsri (2024) , + N. Wiroonsri, O. Preedasawakul (2023) , + C. H. Wu, C. S. Ouyang, L. W. Chen, L. W. Lu (2015) , + X. Xie, G. Beni (1991) and + Rousseeuw (1987) and Kaufman and Rousseeuw(2009) and + + C. Alok. (2010). + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UniversalCVI + url_git: '' +universals: + version: 0.0.5 + title: S3 Generics for Bayesian Analyses + maintainer: Joe Thorley + description: |- + Provides S3 generic methods and some default implementations + for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) + samples. The purpose of 'universals' is to reduce package + dependencies and conflicts. The 'nlist' package implements many of + the methods for its 'nlist' class. + date_publication: '2022-09-22' + bug_reports: https://github.com/poissonconsulting/universals/issues + url: https://poissonconsulting.github.io/universals/ + url_cran: https://CRAN.R-project.org/package=universals + url_git: https://github.com/poissonconsulting/universals +univOutl: + version: '0.4' + title: Detection of Univariate Outliers + maintainer: Marcello D'Orazio + description: Well known outlier detection techniques in the univariate case. Methods + to deal with skewed distribution are included too. The Hidiroglou-Berthelot (1986) + method to search for outliers in ratios of historical data is implemented as well. + When available, survey weights can be used in outliers detection. + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=univOutl + url_git: https://github.com/marcellodo/univOutl +UnivRNG: + version: 1.2.3 + title: Univariate Pseudo-Random Number Generation + maintainer: Ran Gao + description: Pseudo-random number generation of 17 univariate distributions proposed + by Demirtas. (2005) . + date_publication: '2021-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UnivRNG + url_git: '' +unix: + version: 1.5.9 + title: POSIX System Utilities + maintainer: Jeroen Ooms + description: |- + Bindings to system utilities found in most Unix systems such as + POSIX functions which are not part of the Standard C Library. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/unix/issues + url: https://jeroen.r-universe.dev/unix + url_cran: https://CRAN.R-project.org/package=unix + url_git: '' +unjoin: + version: 0.1.0 + title: Separate a Data Frame by Normalization + maintainer: Michael D. Sumner + description: |- + Separate a data frame in two based on key columns. The function + unjoin() provides an inside-out version of a nested data frame. This is used + to identify duplication and normalize it (in the database sense) by linking + two tables with the redundancy removed. This is a basic requirement for + detecting topology within spatial structures that has motivated the need for + this package as a building block for workflows within more applied projects. + date_publication: '2020-05-13' + bug_reports: https://github.com/hypertidy/unjoin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unjoin + url_git: https://github.com/hypertidy/unjoin +unmarked: + version: 1.5.0 + title: Models for Data from Unmarked Animals + maintainer: Ken Kellner + description: 'Fits hierarchical models of animal abundance and occurrence to data + collected using survey methods such as point counts, site occupancy sampling, + distance sampling, removal sampling, and double observer sampling. Parameters + governing the state and observation processes can be modeled as functions of covariates. + References: Kellner et al. (2023) , Fiske and Chandler + (2011) .' + date_publication: '2025-02-10' + bug_reports: https://github.com/biodiverse/unmarked/issues + url: https://groups.google.com/d/forum/unmarked + url_cran: https://CRAN.R-project.org/package=unmarked + url_git: '' +unmconf: + version: 1.0.0 + title: Modeling with Unmeasured Confounding + maintainer: David Kahle + description: |- + Tools for fitting and assessing Bayesian multilevel regression + models that account for unmeasured confounders. + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unmconf + url_git: '' +UNPaC: + version: 1.1.1 + title: |- + Non-Parametric Cluster Significance Testing with Reference to a + Unimodal Null Distribution + maintainer: Erika S. Helgeson + description: Assess the significance of identified clusters and estimates the true + number of clusters by comparing the explained variation due to the clustering + from the original data to that produced by clustering a unimodal reference distribution + which preserves the covariance structure in the data. The reference distribution + is generated using kernel density estimation and a Gaussian copula framework. + A dimension reduction strategy and sparse covariance estimation optimize this + method for the high-dimensional, low-sample size setting. This method is described + in Helgeson, Vock, and Bair (2021) . + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UNPaC + url_git: '' +unpivotr: + version: 0.6.4 + title: Unpivot Complex and Irregular Data Layouts + maintainer: Duncan Garmonsway + description: |- + Tools for converting data from complex or irregular layouts to a + columnar structure. For example, tables with multilevel column or row + headers, or spreadsheets. Header and data cells are selected by their + contents and position, as well as formatting and comments where available, + and are associated with one other by their proximity in given directions. + Functions for data frames and HTML tables are provided. + date_publication: '2024-11-30' + bug_reports: https://github.com/nacnudus/unpivotr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unpivotr + url_git: https://github.com/nacnudus/unpivotr +UnplanSimon: + version: 0.1.0 + title: |- + Methods for Managing Enrollment Deviation in Simon's Two-Stage + Design + maintainer: Yunhe Liu + description: Methods for managing under- and over-enrollment in Simon's Two-Stage + Design are offered by providing adaptive threshold adjustments and sample size + recalibration. It also includes post-inference analysis tools to support clinical + trial design and evaluation. The package is designed to enhance flexibility and + accuracy in trial design, ensuring better outcomes in oncology and other clinical + studies. Yunhe Liu, Haitao Pan (2024). Submitted. + date_publication: '2024-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UnplanSimon + url_git: '' +unrepx: + version: 1.0-2 + title: Analysis and Graphics for Unreplicated Experiments + maintainer: Russell Lenth + description: |- + Provides half-normal plots, reference plots, and Pareto plots + of effects from an unreplicated experiment, along with various + pseudo-standard-error measures, simulated reference distributions, + and other tools. Many of these methods are described in + Daniel C. (1959) and/or + Lenth R.V. (1989) , but some new + approaches are added and integrated in one package. + date_publication: '2022-08-11' + bug_reports: https://github.com/rvlenth/unrepx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unrepx + url_git: '' +unrtf: + version: 1.4.7 + title: Extract Text from Rich Text Format (RTF) Documents + maintainer: Jeroen Ooms + description: |- + Wraps the 'unrtf' utility to + extract text from RTF files. Supports document conversion to HTML, LaTeX or + plain text. Output in HTML is recommended because 'unrtf' has limited + support for converting between character encodings. + date_publication: '2024-10-26' + bug_reports: https://github.com/ropensci/unrtf/issues + url: https://docs.ropensci.org/unrtf/https://ropensci.r-universe.dev/unrtf + url_cran: https://CRAN.R-project.org/package=unrtf + url_git: '' +unstruwwel: + version: 0.2.2 + title: Detect and Parse Historic Dates + maintainer: Stefanie Schneider + description: Automatically converts language-specific verbal information, e.g., + "1st half of the 19th century," to its standardized numerical counterparts, e.g., + "1801-01-01/1850-12-31." It follows the recommendations of the 'MIDAS' ('Marburger + Informations-, Dokumentations- und Administrations-System'), see . + date_publication: '2025-01-27' + bug_reports: https://github.com/stefanieschneider/unstruwwel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unstruwwel + url_git: https://github.com/stefanieschneider/unstruwwel +unsystation: + version: 0.2.0 + title: Stationarity Test Based on Unsystematic Sub-Sampling + maintainer: Haeran Cho + description: |- + Performs a test for second-order stationarity of time series based + on unsystematic sub-samples. + date_publication: '2018-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=unsystation + url_git: '' +untb: + version: 1.7-7-1 + title: Ecological Drift under the UNTB + maintainer: Robin K. S. Hankin + description: Hubbell's Unified Neutral Theory of Biodiversity. + date_publication: '2024-09-11' + bug_reports: https://github.com/RobinHankin/untb/issues + url: https://robinhankin.github.io/untb/ + url_cran: https://CRAN.R-project.org/package=untb + url_git: https://github.com/RobinHankin/untb +unusualprofile: + version: 0.1.4 + title: Calculates Conditional Mahalanobis Distances + maintainer: W. Joel Schneider + description: |- + Calculates a Mahalanobis distance for every row of a set of + outcome variables (Mahalanobis, 1936 + ). The conditional Mahalanobis + distance is calculated using a conditional covariance matrix (i.e., a + covariance matrix of the outcome variables after controlling for a set + of predictors). Plotting the output of the cond_maha() function can + help identify which elements of a profile are unusual after + controlling for the predictors. + date_publication: '2024-02-14' + bug_reports: https://github.com/wjschne/unusualprofile/issues + url: https://wjschne.github.io/unusualprofile/ + url_cran: https://CRAN.R-project.org/package=unusualprofile + url_git: https://github.com/wjschne/unusualprofile +unvotes: + version: 0.3.0 + title: United Nations General Assembly Voting Data + maintainer: David Robinson + description: |- + Historical voting data of the United Nations General Assembly. This + includes votes for each country in each roll call, as well as descriptions and + topic classifications for each vote. + date_publication: '2021-03-09' + bug_reports: https://github.com/dgrtwo/unvotes/issues + url: '' + url_cran: https://CRAN.R-project.org/package=unvotes + url_git: https://github.com/dgrtwo/unvotes +uotm: + version: 0.1.6 + title: Uncertainty of Time Series Model Selection Methods + maintainer: Heming Deng Developer + description: We propose a new procedure, called model uncertainty variance, which + can quantify the uncertainty of model selection on Autoregressive Moving Average + models. The model uncertainty variance not pay attention to the accuracy of prediction, + but focus on model selection uncertainty and providing more information of the + model selection results. And to estimate the model measures, we propose an simplify + and faster algorithm based on bootstrap method, which is proven to be effective + and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations + and adjustments to the Model Confidence Bounds algorithm, so that it can be applied + to the time series model selection method. The consistency of the algorithm result + is also verified by Monte-Carlo simulation. We propose a new procedure, called + model uncertainty variance, which can quantify the uncertainty of model selection + on Autoregressive Moving Average models. The model uncertainty variance focuses + on model selection uncertainty and providing more information of the model selection + results. To estimate the model uncertainty variance, we propose an simplified + and faster algorithm based on bootstrap method, which is proven to be effective + and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations + and adjustments to the Model Confidence Bounds algorithm, so that it can be applied + to the time series model selection method. The consistency of the algorithm result + is also verified by Monte-Carlo simulation. Please see Li,Y., Luo,Y., Ferrari,D., + Hu,X. and Qin,Y. (2019) Model Confidence Bounds for Variable Selection. Biometrics, + 75:392-403. for more information. + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uotm + url_git: '' +UpAndDownPlots: + version: 0.5.0 + title: Displays Percentage and Absolute Changes + maintainer: Antony Unwin + description: Displays percentage changes by height and absolute changes by area + for up to three nested or non-nested levels. The plots visualise changes in indices + and markets, showing how the changes for sectors or for individual components + contribute to the overall change. Data can be classified by up to three levels + of grouping variables in a layered, hierarchical plot. Each level can be ordered + in several ways including by baseline, by percentage change, and by absolute change. + The vignettes give examples. + date_publication: '2024-04-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UpAndDownPlots + url_git: '' +UPCM: + version: 0.0-3 + title: Uncertainty in Partial Credit Models + maintainer: Gunther Schauberger + description: Provides an extension to the Partial Credit Model and Generalized Partial + Credit Models which allows for an additional person parameter that characterizes + the uncertainty of the person. The method was originally proposed by Tutz and + Schauberger (2020) . + date_publication: '2021-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UPCM + url_git: '' +updateme: + version: 0.1.0 + title: Informative Messages About Outdated Packages + maintainer: Jacob Scott + description: |- + When a package is loaded, the source repository is checked for + new versions and a message is shown in the console indicating whether the + package is out of date. + date_publication: '2024-03-14' + bug_reports: https://github.com/wurli/updateme/issues + url: https://wurli.github.io/updateme/ + url_cran: https://CRAN.R-project.org/package=updateme + url_git: https://github.com/wurli/updateme +updater: + version: 0.1.2 + title: Utilities for Updating R + maintainer: Daniel D. Sjoberg + description: |- + When updating major or minor R versions all packages should + be re-installed. The utilities in this package assist in getting a + user up-and-running again by installing all previously installed R + packages. The package uses 'renv' to install; immediately replenishing + your 'renv' package cache. + date_publication: '2023-09-19' + bug_reports: https://github.com/ddsjoberg/updater/issues + url: https://www.danieldsjoberg.com/updater/ + url_cran: https://CRAN.R-project.org/package=updater + url_git: https://github.com/ddsjoberg/updater +updog: + version: 2.1.5 + title: Flexible Genotyping for Polyploids + maintainer: David Gerard + description: |- + Implements empirical Bayes approaches to genotype + polyploids from next generation sequencing data while + accounting for allele bias, overdispersion, and sequencing + error. The main functions are flexdog() and multidog(), + which allow the specification + of many different genotype distributions. Also provided are functions to + simulate genotypes, rgeno(), and read-counts, rflexdog(), as well as + functions to calculate oracle genotyping error rates, oracle_mis(), and + correlation with the true genotypes, oracle_cor(). These latter two + functions are useful for read depth calculations. Run + browseVignettes(package = "updog") in R for example usage. See + Gerard et al. (2018) and + Gerard and Ferrao (2020) for details + on the implemented methods. + date_publication: '2023-11-29' + bug_reports: https://github.com/dcgerard/updog/issues + url: '' + url_cran: https://CRAN.R-project.org/package=updog + url_git: https://github.com/dcgerard/updog/ +UpDown: + version: 1.2.1 + title: Detecting Group Disturbances from Longitudinal Observations + maintainer: Tom Rohmer + description: Provides an algorithm to detect and characterize disturbances (start, + end dates, intensity) that can occur at different hierarchical levels by studying + the dynamics of longitudinal observations at the unit level and group level based + on Nadaraya-Watson's smoothing curves, but also a shiny app which allows to visualize + the observations and the detected disturbances. Finally the package provides a + dataframe mimicking a pig farming system subsected to disturbances simulated according + to Le et al.(2022) . + date_publication: '2023-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UpDown + url_git: '' +UPG: + version: 0.3.5 + title: |- + Efficient Bayesian Algorithms for Binary and Categorical Data + Regression Models + maintainer: Gregor Zens + description: Efficient Bayesian implementations of probit, logit, multinomial logit + and binomial logit models. Functions for plotting and tabulating the estimation + output are available as well. Estimation is based on Gibbs sampling where the + Markov chain Monte Carlo algorithms are based on the latent variable representations + and marginal data augmentation algorithms described in "Gregor Zens, Sylvia Frühwirth-Schnatter + & Helga Wagner (2023). Ultimate Pólya Gamma Samplers – Efficient MCMC for possibly + imbalanced binary and categorical data, Journal of the American Statistical Association + ". + date_publication: '2024-11-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UPG + url_git: '' +upndown: + version: 0.2.0 + title: Utilities and Design Aids for Up-and-Down Dose-Finding Studies + maintainer: Assaf P. Oron + description: Up-and-Down is the most popular design approach for dose-finding, but + has been severely under-served by the statistical computing community. This is + the first package to address Up-and-Down's needs. For a recent methodological + tutorial on Up-and-Down, see Oron et al. (2022) . + date_publication: '2024-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=upndown + url_git: '' +upsetjs: + version: 1.11.1 + title: |- + 'HTMLWidget' Wrapper of 'UpSet.js' for Exploring Large Set + Intersections + maintainer: Samuel Gratzl + description: |- + 'UpSet.js' is a re-implementation of 'UpSetR' to create interactive set visualizations for more than three sets. + This is a 'htmlwidget' wrapper around the 'JavaScript' library 'UpSet.js'. + date_publication: '2022-07-13' + bug_reports: https://github.com/upsetjs/upsetjs_r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=upsetjs + url_git: https://github.com/upsetjs/upsetjs_r/ +UpSetR: + version: 1.4.0 + title: |- + A More Scalable Alternative to Venn and Euler Diagrams for + Visualizing Intersecting Sets + maintainer: Jake Conway + description: |- + Creates visualizations of intersecting sets using a novel matrix + design, along with visualizations of several common set, element and attribute + related tasks (Conway 2017) . + date_publication: '2019-05-22' + bug_reports: http://github.com/hms-dbmi/UpSetR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UpSetR + url_git: http://github.com/hms-dbmi/UpSetR +UpSetVP: + version: 1.0.0 + title: An Alternative Visualization of VPA and HP in Canonical Analysis + maintainer: Yao Liu + description: 'Using matrix layout to visualize the unique, common, or individual + contribution of each predictor (or matrix of predictors) towards explained variation + on canonical analysis. These contributions were derived from variance partitioning + analysis (VPA) and hierarchical partitioning (HP), applying the algorithm of Lai + J., Zou Y., Zhang J., Peres-Neto P. (2022) Generalizing hierarchical and variation + partitioning in multiple regression and canonical analyses using the rdacca.hp + R package.Methods in Ecology and Evolution, 13: 782-788 .' + date_publication: '2022-05-03' + bug_reports: https://github.com/LiuXYh/UpSetVP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UpSetVP + url_git: https://github.com/LiuXYh/UpSetVP +upstartr: + version: 0.1.2 + title: Utilities Powering the Globe and Mail's Data Journalism Template + maintainer: Tom Cardoso + description: Core functions necessary for using The Globe and Mail's R data journalism + template, 'startr', along with utilities for day-to-day data journalism tasks, + such as reading and writing files, producing graphics and cleaning up datasets. + date_publication: '2024-01-09' + bug_reports: https://github.com/globeandmail/upstartr/issues + url: https://globeandmail.github.io/upstartr/ + url_cran: https://CRAN.R-project.org/package=upstartr + url_git: https://github.com/globeandmail/upstartr +UPSvarApprox: + version: 0.1.4 + title: Approximate the Variance of the Horvitz-Thompson Total Estimator + maintainer: Roberto Sichera + description: |- + Variance approximations for the + Horvitz-Thompson total estimator in Unequal Probability Sampling + using only first-order inclusion probabilities. + See Matei and Tillé (2005) and Haziza, Mecatti and Rao (2008) for details. + date_publication: '2023-08-27' + bug_reports: https://github.com/rhobis/UPSvarApprox/issues + url: '' + url_cran: https://CRAN.R-project.org/package=UPSvarApprox + url_git: '' +uptasticsearch: + version: 1.0.0 + title: Get Data Frame Representations of 'Elasticsearch' Results + maintainer: James Lamb + description: |- + 'Elasticsearch' is an open-source, distributed, document-based datastore + (). + It provides an 'HTTP' 'API' for querying the database and extracting datasets, but that + 'API' was not designed for common data science workflows like pulling large batches of + records and normalizing those documents into a data frame that can be used as a training + dataset for statistical models. 'uptasticsearch' provides an interface for 'Elasticsearch' + that is explicitly designed to make these data science workflows easy and fun. + date_publication: '2025-02-24' + bug_reports: https://github.com/uptake/uptasticsearch/issues + url: '' + url_cran: https://CRAN.R-project.org/package=uptasticsearch + url_git: https://github.com/uptake/uptasticsearch +uptimeRobot: + version: 1.0.0 + title: Access the UptimeRobot Ping API + maintainer: Gabriele Baldassarre + description: |- + Provide a set of wrappers to call all the endpoints of UptimeRobot API + which includes various kind of ping, keep-alive and speed tests. + See for more information. + date_publication: '2015-10-22' + bug_reports: https://github.com/theclue/uptimeRobot/issues + url: https://gabrielebaldassarre.com/r/uptimerobot + url_cran: https://CRAN.R-project.org/package=uptimeRobot + url_git: '' +ura: + version: 1.0.1 + title: Monitoring Rater Reliability + maintainer: Benjamin Goehring + description: Provides researchers with a simple set of diagnostic tools for monitoring + the progress and reliability of raters conducting content coding tasks. Goehring + (2024) + argues that supervisors---especially supervisors of small teams---should utilize + computational tools to monitor reliability in real time. As such, this package + provides easy-to-use functions for calculating inter-rater reliability statistics + and measuring the reliability of one coder compared to the rest of the team. + date_publication: '2024-07-12' + bug_reports: https://github.com/bengoehring/ura/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ura + url_git: https://github.com/bengoehring/ura +urbin: + version: 0.1-14 + title: Unifying Estimation Results with Binary Dependent Variables + maintainer: Arne Henningsen + description: |- + Calculate unified measures + that quantify the effect of a covariate on a binary dependent variable + (e.g., for meta-analyses). + This can be particularly important + if the estimation results are obtained + with different models/estimators + (e.g., linear probability model, logit, probit, ...) + and/or with different transformations of the explanatory variable of interest + (e.g., linear, quadratic, interval-coded, ...). + The calculated unified measures are: + (a) semi-elasticities of linear, quadratic, or interval-coded covariates and + (b) effects of linear, quadratic, interval-coded, or categorical covariates + when a linear or quadratic covariate changes between distinct intervals, + the reference category of a categorical variable + or the reference interval of an interval-coded variable needs to be changed, + or some categories of a categorical covariate + or some intervals of an interval-coded covariate need to be grouped together. + Approximate standard errors of the unified measures are also calculated. + All methods that are implemented in this package + are described in the 'vignette' + "Extracting and Unifying Semi-Elasticities and Effect Sizes + from Studies with Binary Dependent Variables" + that is included in this package. + date_publication: '2024-10-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=urbin + url_git: https://r-forge.r-project.org/projects/urbin/ +urca: + version: 1.3-4 + title: Unit Root and Cointegration Tests for Time Series Data + maintainer: Bernhard Pfaff + description: |- + Unit root and cointegration tests encountered in applied + econometric analysis are implemented. + date_publication: '2024-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=urca + url_git: '' +urlchecker: + version: 1.0.1 + title: Run CRAN URL Checks from Older R Versions + maintainer: Gábor Csárdi + description: |- + Provide the URL checking tools available in R 4.1+ as a + package for earlier versions of R. Also uses concurrent requests so + can be much faster than the serial versions. + date_publication: '2021-11-30' + bug_reports: https://github.com/r-lib/urlchecker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=urlchecker + url_git: https://github.com/r-lib/urlchecker +urlparse: + version: 0.2.0 + title: Fast Simple URL Parser + maintainer: Dyfan Jones + description: |- + A fast and simple 'URL' parser package for 'R'. This package provides + functions to parse 'URLs' into their components, such as scheme, user, password, host, port, + path, query, and fragment. + date_publication: '2025-02-06' + bug_reports: https://github.com/dyfanjones/urlparse/issues + url: https://dyfanjones.r-universe.dev/urlparse + url_cran: https://CRAN.R-project.org/package=urlparse + url_git: https://github.com/dyfanjones/urlparse +urlshorteneR: + version: 1.6.0 + title: |- + R Wrapper for the 'Bit.ly' and 'Is.gd'/'v.gd' URL Shortening + Services + maintainer: John Malc + description: |- + Allows using two URL shortening services, which also provide + expanding and analytic functions. Specifically developed for 'Bit.ly' (which requires OAuth 2.0) and 'is.gd' (no API key). + date_publication: '2025-02-16' + bug_reports: https://github.com/dmpe/urlshorteneR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=urlshorteneR + url_git: https://github.com/dmpe/urlshorteneR +urltools: + version: 1.7.3 + title: Vectorised Tools for URL Handling and Parsing + maintainer: Os Keyes + description: |- + A toolkit for all URL-handling needs, including encoding and decoding, + parsing, parameter extraction and modification. All functions are + designed to be both fast and entirely vectorised. It is intended to be + useful for people dealing with web-related datasets, such as server-side + logs, although may be useful for other situations involving large sets of + URLs. + date_publication: '2019-04-14' + bug_reports: https://github.com/Ironholds/urltools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=urltools + url_git: https://github.com/Ironholds/urltools/ +uroot: + version: 2.1-3 + title: Unit Root Tests for Seasonal Time Series + maintainer: Georgi N. Boshnakov + description: |- + Seasonal unit roots and seasonal stability tests. + P-values based on response surface regressions are available for both tests. + P-values based on bootstrap are available for seasonal unit root tests. + date_publication: '2023-12-15' + bug_reports: https://github.com/GeoBosh/uroot/issues + url: https://geobosh.github.io/uroot/ + url_cran: https://CRAN.R-project.org/package=uroot + url_git: '' +URooTab: + version: 0.1.0 + title: Tabular Reporting of 'EViews' Unit Root Tests + maintainer: Sagiru Mati + description: Conduct unit root tests based on 'EViews' () routines + and report them in tables. 'EViews' (Econometric Views) is a commercial software + for econometrics. + date_publication: '2023-08-30' + bug_reports: https://github.com/sagirumati/URooTab/issues + url: '' + url_cran: https://CRAN.R-project.org/package=URooTab + url_git: https://github.com/sagirumati/URooTab +ursa: + version: 3.11.4 + title: |- + Non-Interactive Spatial Tools for Raster Processing and + Visualization + maintainer: Nikita Platonov + description: 'S3 classes and methods for manipulation with georeferenced raster + data: reading/writing, processing, multi-panel visualization.' + date_publication: '2025-02-20' + bug_reports: https://github.com/nplatonov/ursa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ursa + url_git: https://github.com/nplatonov/ursa +us.census.geoheader: + version: 1.0.2 + title: US 2010 Census SF2 Geographic Header Summary Levels 010-050 + maintainer: Greg Minshall + description: |- + A simple interface to the Geographic Header information + from the "2010 US Census Summary File 2". The entire Summary File 2 + is described at + , + but note that this package only provides access to parts of the + geographic header ('geoheader') of the file. In particular, only + the first 101 columns of the geoheader are included and, more + importantly, only rows with summary levels (SUMLEVs) 010 through 050 + (nation down through county level) are included. In addition to + access to (part of) the geoheader, the package also provides a + decode function that takes a column name and value and, for certain + columns, returns "the meaning" of that column (i.e., a "SUMLEV" + value of 40 means "State"); without a value, the decode function + attempts to describe the column itself. + date_publication: '2020-06-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=us.census.geoheader + url_git: https://gitlab.com/minshall/us-census-geoheader +usa: + version: 0.1.2 + title: Updated US State Facts and Figures + maintainer: Kiernan Nicholls + description: |- + Updated versions of the 1970's "US State Facts and Figures" + objects from the 'datasets' package included with R. The new data is + compiled from a number of sources, primarily from United States Census + Bureau or the relevant federal agency. + date_publication: '2024-03-11' + bug_reports: https://github.com/k5cents/usa/issues + url: https://k5cents.github.io/usa/ + url_cran: https://CRAN.R-project.org/package=usa + url_git: https://github.com/k5cents/usa +USA.state.boundaries: + version: 1.0.1 + title: |- + WGS84 Datum Map of the USA, Including Puerto Rico and the U.S. + Virgin Islands + maintainer: Irucka Embry + description: |- + Contains a WGS84 datum map of the USA, which includes all + Commonwealth and State boundaries & also includes Puerto Rico and the U.S. + Virgin Islands. This map is a reprojection of the NAD83 datum map from the + USGS National Map. This package contains a subset of the data included in + the 'USA.state.boundaries.data' package, which is available in a 'drat' + repository. To install that data package, please follow the instructions at + . + date_publication: '2023-02-10' + bug_reports: https://gitlab.com/iembry/usa.state.boundaries/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=USA.state.boundaries + url_git: https://gitlab.com/iembry/usa.state.boundaries +usaidplot: + version: 2.0.2 + title: Make Graphs with US Agency for International Development Colors + maintainer: Jacob Patterson-Stein + description: Automatically apply the United States Agency for International Development's + color palette and fonts for either discrete or continuous variables. + date_publication: '2024-09-30' + bug_reports: https://github.com/jacobpstein/usaid_plot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=usaidplot + url_git: https://github.com/jacobpstein/usaid_plot +uscoauditlog: + version: 1.0.3 + title: |- + United States Copyright Office Product Management Division SR + Audit Data Dataset Cleaning Algorithms + maintainer: Frederick Liu + description: Intended to be used by the United States Copyright Office Product Management + Division Business Analysts. Include algorithms for the United States Copyright + Office Product Management Division SR Audit Data dataset. The algorithm takes + in the SR Audit Data excel file and reformat the spreadsheet such that the values + and variables fit the format of the online database. Support functions in this + package include clean_str(), which cleans instances of variable AUDIT_LOG; clean_data_to_excel(), + which cleans and output the reorganized SR Audit Data dataset in excel format; + clean_data_to_dataframe(), which cleans and stores the reorganized SR Audit Data + data set to a data frame; format_from_excel(), which reads in the outputted excel + file from the clean_data_to_excel() function and formats and returns the data + as a dictionary that uses FIELD types as keys and NON-FIELD types as the values + of those keys. format_from_dataframe(), which reads in the outputted data frame + from the clean_data_to_dataframe() function and formats and returns the data as + a dictionary that uses FIELD types as keys and NON-FIELD types as the values of + those keys; support_function(), which takes in the dictionary outputted either + from the format_from_dataframe() or format_from_excel() function and returns the + data as a formatted data frame according to the original U.S. Copyright Office + SR Audit Data online database. The main function of this package is clean_format_all(), + which takes in an excel file and returns the formatted data into a new excel and + text file according to the format from the U.S. Copyright Office SR Audit Data + online database. + date_publication: '2022-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uscoauditlog + url_git: '' +usdampr: + version: 1.0.1 + title: Request USDA MPR Historical Data via the 'LMR' API + maintainer: Bowen Chen + description: |- + Interface to easily access data via the United States Department of Agriculture (USDA)'s Livestock Mandatory Reporting ('LMR') + Data API at . The downloaded data can be saved for later off-line use. + Also provide relevant information and metadata for each of the input variables needed for sending the data inquiry. + date_publication: '2021-03-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=usdampr + url_git: https://github.com/cbw1243/usdampr +usdarnass: + version: 0.1.0 + title: USDA NASS Quick Stats API + maintainer: Robert Dinterman + description: |- + An alternative for downloading various United States Department of + Agriculture (USDA) data from through R. + You must sign up for an API token from the mentioned website in order for + this package to work. + date_publication: '2019-06-21' + bug_reports: https://github.com/rdinter/usdarnass/issues + url: '' + url_cran: https://CRAN.R-project.org/package=usdarnass + url_git: https://github.com/rdinter/usdarnass +usdata: + version: 0.3.1 + title: Data on the States and Counties of the United States + maintainer: Mine Çetinkaya-Rundel + description: Demographic data on the United States at the county and state levels + spanning multiple years. + date_publication: '2024-06-02' + bug_reports: https://github.com/OpenIntroStat/usdata/issues + url: https://openintrostat.github.io/usdata/ + url_cran: https://CRAN.R-project.org/package=usdata + url_git: https://github.com/OpenIntroStat/usdata +usdatasets: + version: 0.1.0 + title: A Comprehensive Collection of U.S. Datasets + maintainer: Renzo Caceres Rossi + description: |- + Provides a diverse collection of U.S. datasets + encompassing various fields such as crime, economics, education, finance, energy, healthcare, and more. + It serves as a valuable resource for researchers and analysts seeking to perform in-depth analyses and derive insights from U.S.-specific data. + date_publication: '2024-10-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=usdatasets + url_git: https://github.com/lightbluetitan/usdatasets +usdm: + version: 2.1-7 + title: Uncertainty Analysis for Species Distribution Models + maintainer: Babak Naimi + description: This is a framework that aims to provide methods and tools for assessing + the impact of different sources of uncertainties (e.g.positional uncertainty) + on performance of species distribution models (SDMs).) + date_publication: '2023-09-29' + bug_reports: '' + url: https://r-gis.net/ + url_cran: https://CRAN.R-project.org/package=usdm + url_git: '' +usedist: + version: 0.4.0 + title: Distance Matrix Utilities + maintainer: Kyle Bittinger + description: Functions to re-arrange, extract, and work with distances. + date_publication: '2020-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=usedist + url_git: '' +usedthese: + version: 0.5.0 + title: Summarises Package & Function Usage + maintainer: Carl Goodwin + description: |- + Consistent with 'knitr' syntax highlighting, 'usedthese' adds + a summary table of package & function usage to a Quarto document and + enables aggregation of usage across a website. + date_publication: '2024-06-26' + bug_reports: https://github.com/cgoo4/usedthese/issues + url: https://cgoo4.github.io/usedthese/ + url_cran: https://CRAN.R-project.org/package=usedthese + url_git: https://github.com/cgoo4/usedthese +useful: + version: 1.2.6.1 + title: A Collection of Handy, Useful Functions + maintainer: Jared P. Lander + description: |- + A set of little functions that have been found useful to do little + odds and ends such as plotting the results of K-means clustering, substituting + special text characters, viewing parts of a data.frame, constructing formulas + from text and building design and response matrices. + date_publication: '2023-10-24' + bug_reports: https://github.com/jaredlander/useful/issues + url: '' + url_cran: https://CRAN.R-project.org/package=useful + url_git: https://github.com/jaredlander/useful +usefun: + version: 0.5.2 + title: A Collection of Useful Functions by John + maintainer: John Zobolas + description: |- + A set of general functions that I have used in various + projects and other R packages. Miscellaneous operations on data + frames, matrices and vectors, ROC and PR statistics. + date_publication: '2024-09-14' + bug_reports: https://github.com/bblodfon/usefun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=usefun + url_git: https://github.com/bblodfon/usefun +usemodels: + version: 0.2.0 + title: Boilerplate Code for 'Tidymodels' Analyses + maintainer: Max Kuhn + description: |- + Code snippets to fit models using the tidymodels framework + can be easily created for a given data set. + date_publication: '2022-02-18' + bug_reports: https://github.com/tidymodels/usemodels/issues + url: https://usemodels.tidymodels.org/ + url_cran: https://CRAN.R-project.org/package=usemodels + url_git: https://github.com/tidymodels/usemodels +usethis: + version: 3.1.0 + title: Automate Package and Project Setup + maintainer: Jennifer Bryan + description: |- + Automate package and project setup tasks that are otherwise + performed manually. This includes setting up unit testing, test + coverage, continuous integration, Git, 'GitHub', licenses, 'Rcpp', + 'RStudio' projects, and more. + date_publication: '2024-11-26' + bug_reports: https://github.com/r-lib/usethis/issues + url: https://usethis.r-lib.org + url_cran: https://CRAN.R-project.org/package=usethis + url_git: https://github.com/r-lib/usethis +usfertilizer: + version: 0.1.5 + title: County-Level Estimates of Fertilizer Application in USA + maintainer: Wenlong Liu + description: |- + Compiled and cleaned the county-level estimates of fertilizer, + nitrogen and phosphorus, from 1945 to 2012 in United States of America (USA). The commercial fertilizer data were originally + generated by USGS based on the sales data of commercial fertilizer. The manure data were estimated + based on county-level population data of livestock, poultry, and other animals. + See the user manual for detailed data sources and cleaning methods. + 'usfertilizer' utilized the tidyverse to clean the original data and provide + user-friendly dataframe. Please note that USGS does not endorse this package. Also data from 1986 is not available for now. + date_publication: '2018-04-02' + bug_reports: https://github.com/wenlong-liu/usfertilizer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=usfertilizer + url_git: https://github.com/wenlong-liu/usfertilizer +USgas: + version: 0.1.2 + title: The Demand for Natural Gas in the US + maintainer: Rami Krispin + description: 'Provides an overview of the demand for natural gas in the US by state + and country level. Data source: US Energy Information Administration .' + date_publication: '2023-04-16' + bug_reports: https://github.com/RamiKrispin/USgas/issues + url: '' + url_cran: https://CRAN.R-project.org/package=USgas + url_git: https://github.com/RamiKrispin/USgas +USgrid: + version: 0.1.2 + title: The Demand and Supply for Electricity in the US + maintainer: Rami Krispin + description: 'Provides a set of regular time-series datasets, describing the US + electricity grid. That includes the total demand and supply, and as well as the + demand by energy source (coal, solar, wind, etc.). Source: US Energy Information + Administration (Dec 2019) .' + date_publication: '2021-03-21' + bug_reports: https://github.com/RamiKrispin/USgrid/issues + url: '' + url_cran: https://CRAN.R-project.org/package=USgrid + url_git: https://github.com/RamiKrispin/USgrid +ushr: + version: 0.2.3 + title: Understanding Suppression of HIV + maintainer: Sinead E. Morris + description: Analyzes longitudinal data of HIV decline in patients on antiretroviral + therapy using the canonical biphasic exponential decay model (pioneered, for example, + by work in Perelson et al. (1997) ; and Wu and Ding (1999) + ). Model fitting and parameter estimation + are performed, with additional options to calculate the time to viral suppression. + Plotting and summary tools are also provided for fast assessment of model results. + date_publication: '2020-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ushr + url_git: https://github.com/SineadMorris/ushr +usincometaxes: + version: 0.7.1 + title: Calculate Federal and State Income Taxes in the United States + maintainer: Shane Orr + description: |- + Calculates federal and state income taxes in the United States. It acts as a wrapper + to the NBER's TAXSIM 35 () tax simulator. TAXSIM 35 conducts + the calculations, while 'usincometaxes' prepares the data for TAXSIM 35, sends the data to + TAXSIM 35's server or communicates with the Web Assembly file, retrieves the data, and places it + into a data frame. All without the user worrying about this process. + date_publication: '2024-01-11' + bug_reports: https://github.com/shanejorr/usincometaxes/issues + url: https://shaneorr.io/r/usincometaxes + url_cran: https://CRAN.R-project.org/package=usincometaxes + url_git: https://github.com/shanejorr/usincometaxes +UsingR: + version: 2.0-7 + title: |- + Data Sets, Etc. for the Text "Using R for Introductory + Statistics", Second Edition + maintainer: John Verzani + description: |- + A collection of data sets to accompany the + textbook "Using R for Introductory Statistics," second + edition. + date_publication: '2022-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UsingR + url_git: '' +uskewFactors: + version: '2.0' + title: |- + Model-Based Clustering via Mixtures of Unrestricted Skew-t + Sactor Analyzer Models + maintainer: Paula M. Murray + description: Implements mixtures of unrestricted skew-t factor analyzer models via + the EM algorithm. + date_publication: '2016-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uskewFactors + url_git: '' +usl: + version: 3.0.3 + title: Analyze System Scalability with the Universal Scalability Law + maintainer: Stefan Moeding + description: |- + The Universal Scalability Law (Gunther 2007) + is a model to predict hardware and + software scalability. It uses system capacity as a function of load to + forecast the scalability for the system. + date_publication: '2022-08-28' + bug_reports: https://github.com/smoeding/usl/issues + url: '' + url_cran: https://CRAN.R-project.org/package=usl + url_git: '' +usmap: + version: 0.7.1 + title: US Maps Including Alaska and Hawaii + maintainer: Paolo Di Lorenzo + description: |- + Obtain United States map data frames of varying region types (e.g. county, + state). The map data frames include Alaska and Hawaii conveniently placed to the + bottom left, as they appear in most maps of the US. Convenience functions for plotting + choropleths, visualizing spatial data, and working with FIPS codes are also provided. + date_publication: '2024-03-21' + bug_reports: https://github.com/pdil/usmap/issues + url: https://usmap.dev + url_cran: https://CRAN.R-project.org/package=usmap + url_git: '' +usmapdata: + version: 0.3.0 + title: Mapping Data for 'usmap' Package + maintainer: Paolo Di Lorenzo + description: |- + Provides a container for data used by the 'usmap' package. + The data used by 'usmap' has been extracted into this package so that the + file size of the 'usmap' package can be reduced greatly. The data in this + package will be updated roughly once per year as new map data files are + provided by the US Census Bureau. + date_publication: '2024-05-17' + bug_reports: https://github.com/pdil/usmapdata/issues + url: https://usmap.dev + url_cran: https://CRAN.R-project.org/package=usmapdata + url_git: '' +USP: + version: 0.1.2 + title: U-Statistic Permutation Tests of Independence for all Data Types + maintainer: Thomas B. Berrett + description: Implements various independence tests for discrete, continuous, and + infinite-dimensional data. The tests are based on a U-statistic permutation test, + the USP of Berrett, Kontoyiannis and Samworth (2020) , and shown + to be minimax rate optimal in a wide range of settings. As the permutation principle + is used, all tests have exact, non-asymptotic Type I error control at the nominal + level. + date_publication: '2021-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=USP + url_git: '' +USpopcenters: + version: 0.2.0 + title: United States Centers of Population (Centroids) + maintainer: Nik Krieger + description: |- + Centers of population (centroid) data for census areas in the + United States. + date_publication: '2023-04-25' + bug_reports: https://github.com/NikKrieger/USpopcenters/issues + url: https://www.census.gov/geographies/reference-files/time-series/geo/centers-population.html + url_cran: https://CRAN.R-project.org/package=USpopcenters + url_git: https://github.com/NikKrieger/USpopcenters +ussherR: + version: '1.10' + title: Ussher Data Set Drawn from 1658 Chronology + maintainer: Daniel Eness + description: 'The "ussher" data set is drawn from original chronological textual + historic events. Commonly known as James Ussher''s Annals of the World, the source + text was originally written in Latin in 1650, and published in English translation + in 1658.The data are classified by index, year, epoch (or one of the 7 ancient + "Ages of the World"), Biblical source book if referenced (rarely), as well as + alternate dating mechanisms, such as "Anno Mundi" (age of the world) or "Julian + Period" (dates based upon the Julian calendar). Additional file "usshfull" includes + variables that may be of further interest to historians, such as Southern Kingdom + and Northern Kingdom discrepant dates, and the original amalgamated dating mechanic + used by Ussher in the original text. The raw data can also be called using "usshraw", + as described in: Ussher, J. (1658) .' + date_publication: '2022-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ussherR + url_git: '' +UStatBookABSC: + version: 1.0.0 + title: |- + A Companion Package to the Book "U-Statistics, M-Estimation and + Resampling" + maintainer: Snigdhansu Chatterjee + description: |- + A set of functions leading to multivariate response L1 regression. + This includes functions on computing Euclidean inner products and norms, + weighted least squares estimates on multivariate responses, function to compute + fitted values and residuals. This package is a companion to the book "U-Statistics, + M-estimation and Resampling", by Arup Bose and Snigdhansu Chatterjee, to appear + in 2017 as part of the "Texts and Readings in Mathematics" (TRIM) series of + Hindustan Book Agency and Springer-Verlag. + date_publication: '2016-12-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UStatBookABSC + url_git: '' +ustfd: + version: 0.4.4 + title: API Client for US Treasury Fiscal Data + maintainer: Guillermo Roditi Dominguez + description: Make requests from the US Treasury Fiscal Data API endpoints. + date_publication: '2024-01-28' + bug_reports: https://github.com/groditi/ustfd/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ustfd + url_git: https://github.com/groditi/ustfd +ustyc: + version: 1.0.0 + title: Fetch US Treasury yield curve data. + maintainer: Matt Barry + description: |- + Forms a query to submit for US Treasury yield curve data, posting + this query to the US Treasury web site's data feed service. By default the + download includes data yield data for 12 products from January 1, 1990, + some of which are NA during this span. The caller can pass parameters to + limit the query to a certain year or year and month, but the full download + is not especially large. The download data from the service is in XML + format. The package's main function transforms that XML data into a numeric + data frame with treasury product items (constant maturity yields for 12 kinds + of bills, notes, and bonds) as columns and dates as row names. The function + returns a list which includes an item for this data frame as well as query-related + values for reference and the update date from the service. + date_publication: '2014-06-12' + bug_reports: https://github.com/mrbcuda/ustyc/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ustyc + url_git: https://github.com/mrbcuda/ustyc +utc: + version: 0.1.5 + title: Coordinated Universal Time Transformations + maintainer: Antonio J. Segura + description: 'Three functions are provided: first function changes time from local + to UTC, other changes from UTC to local and third returns difference between local + and UTC. %h+% operator is also provided it adds hours to a time.' + date_publication: '2019-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=utc + url_git: '' +utf8: + version: 1.2.4 + title: Unicode Text Processing + maintainer: Kirill Müller + description: |- + Process and print 'UTF-8' encoded international + text (Unicode). Input, validate, normalize, encode, format, and + display. + date_publication: '2023-10-22' + bug_reports: https://github.com/patperry/r-utf8/issues + url: https://ptrckprry.com/r-utf8/ + url_cran: https://CRAN.R-project.org/package=utf8 + url_git: https://github.com/patperry/r-utf8 +utf8ify: + version: 0.1.0 + title: Format Text Using Unicode + maintainer: Roland Krasser + description: |- + Format text (bold, italic, ...) and numbers using UTF-8. + Offers functions to search for emojis and include them in your text. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=utf8ify + url_git: https://github.com/rolkra/utf8ify +utile.tables: + version: 0.3.0 + title: Build Tables for Publication + maintainer: Eric Finnesgard + description: Functions for building customized ready-to-export tables for publication. + date_publication: '2023-01-24' + bug_reports: https://github.com/efinite/utile.tables/issues + url: https://efinite.github.io/utile.tables/ + url_cran: https://CRAN.R-project.org/package=utile.tables + url_git: '' +utile.tools: + version: 0.3.0 + title: Summarize Data for Publication + maintainer: Eric Finnesgard + description: Tools for formatting and summarizing data for outcomes research. + date_publication: '2023-01-24' + bug_reports: https://github.com/efinite/utile.tools/issues + url: https://efinite.github.io/utile.tools/ + url_cran: https://CRAN.R-project.org/package=utile.tools + url_git: '' +utile.visuals: + version: 0.3.3 + title: Create Visuals for Publication + maintainer: Eric Finnesgard + description: A set of functions to aid in the production of visuals in ggplot2. + date_publication: '2023-01-24' + bug_reports: https://github.com/efinite/utile.visuals/issues + url: https://efinite.github.io/utile.visuals/ + url_cran: https://CRAN.R-project.org/package=utile.visuals + url_git: '' +utility: + version: 1.4.6 + title: Construct, Evaluate and Plot Value and Utility Functions + maintainer: Peter Reichert + description: |- + Construct and plot objective hierarchies and associated value and utility functions. + Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. + Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies. + Get numerical results of the evaluations in standard R data types for further processing. + date_publication: '2023-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=utility + url_git: '' +UtilityFrailtyPH12: + version: '1.0' + title: Implementing EFF-TOX and Monotone Utility Based Phase 12 Trials + maintainer: Andrew G Chapple + description: Contains functions for simulating phase 12 trial designs described + by Chapple and Thall (2019) including simulation and the EFF-TOX trial and simulation + and implementation of the U12 trial. Functions for implementing the EFF-TOX trial + are found in the package 'Phase123'. + date_publication: '2019-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=UtilityFrailtyPH12 + url_git: '' +utilityFunctionTools: + version: 0.1.1 + title: P-Spline Regression for Utility Functions and Derived Measures + maintainer: Sebastian O. Schneider + description: Predicts a smooth and continuous (individual) utility function from + utility points, and computes measures of intensity for risk and higher order risk + measures (or any other measure computed with user-written function) based on this + utility function and its derivatives according to the method introduced in Schneider + (2017) . + date_publication: '2021-03-29' + bug_reports: '' + url: https://www.sebastianoschneider.com + url_cran: https://CRAN.R-project.org/package=utilityFunctionTools + url_git: '' +utilsIPEA: + version: 0.0.6 + title: IPEA Common Functions + maintainer: Gustavo Coelho + description: |- + The most used functions on IPEA (Instituto de Pesquisa Economica Aplicada). + Most of functions deal with brazilian names. + It can guess the women single's name, extract prepositions or extract the first name. + date_publication: '2018-04-20' + bug_reports: http://github.com/ipea/utilsIPEA/issues + url: '' + url_cran: https://CRAN.R-project.org/package=utilsIPEA + url_git: https://github.com/ipea/utilsIPEA +utiml: + version: 0.1.7 + title: Utilities for Multi-Label Learning + maintainer: Adriano Rivolli + description: |- + Multi-label learning strategies and others procedures to support multi- + label classification in R. The package provides a set of multi-label procedures such as + sampling methods, transformation strategies, threshold functions, pre-processing + techniques and evaluation metrics. A complete overview of the matter can be seen in + Zhang, M. and Zhou, Z. (2014) and Gibaja, E. and + Ventura, S. (2015) A Tutorial on Multi-label Learning. + date_publication: '2021-05-31' + bug_reports: https://github.com/rivolli/utiml + url: '' + url_cran: https://CRAN.R-project.org/package=utiml + url_git: https://github.com/rivolli/utiml +utsf: + version: 1.1.0 + title: Univariate Time Series Forecasting + maintainer: Francisco Martinez + description: |- + An engine for univariate time series forecasting using + different regression models in an autoregressive way. The engine + provides an uniform interface for applying the different models. + Furthermore, it is extensible so that users can easily apply their + own regression models to univariate time series forecasting and + benefit from all the features of the engine, such as preprocessings + or estimation of forecast accuracy. + date_publication: '2024-12-10' + bug_reports: https://github.com/franciscomartinezdelrio/utsf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=utsf + url_git: https://github.com/franciscomartinezdelrio/utsf +uuid: + version: 1.2-1 + title: Tools for Generating and Handling of UUIDs + maintainer: Simon Urbanek + description: Tools for generating and handling of UUIDs (Universally Unique Identifiers). + date_publication: '2024-07-29' + bug_reports: https://github.com/s-u/uuid/issues + url: https://www.rforge.net/uuid + url_cran: https://CRAN.R-project.org/package=uuid + url_git: '' +uwedragon: + version: 0.1.0 + title: |- + Data Research, Access, Governance Network : Statistical + Disclosure Control + maintainer: Ben Derrick + description: |- + A tool for checking how much information is disclosed when + reporting summary statistics. + date_publication: '2022-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=uwedragon + url_git: '' +UWHAM: + version: '1.1' + title: Unbinned Weighted Histogram Analysis Method (UWHAM) + maintainer: Zhiqiang Tan + description: |- + A method for estimating log-normalizing constants (or free + energies) and expectations from multiple distributions (such as + multiple generalized ensembles). + date_publication: '2022-05-20' + bug_reports: '' + url: http://www.stat.rutgers.edu/~ztan + url_cran: https://CRAN.R-project.org/package=UWHAM + url_git: '' +uwot: + version: 0.2.3 + title: |- + The Uniform Manifold Approximation and Projection (UMAP) Method + for Dimensionality Reduction + maintainer: James Melville + description: |- + An implementation of the Uniform Manifold Approximation and + Projection dimensionality reduction by McInnes et al. (2018) + . It also provides means to transform new data and + to carry out supervised dimensionality reduction. An implementation of + the related LargeVis method of Tang et al. (2016) + is also provided. This is a complete re-implementation in R (and C++, + via the 'Rcpp' package): no Python installation is required. See the + uwot website () for more + documentation and examples. + date_publication: '2025-02-24' + bug_reports: https://github.com/jlmelville/uwot/issues + url: https://jlmelville.github.io/uwot/ + url_cran: https://CRAN.R-project.org/package=uwot + url_git: https://github.com/jlmelville/uwot +uxr: + version: 0.2.0 + title: User Experience Research + maintainer: Joe Chelladurai + description: |- + Provides convenience functions for user experience research + with an emphasis on quantitative user experience testing and reporting. + The functions are designed to translate statistical approaches to + applied user experience research. + date_publication: '2022-12-25' + bug_reports: https://github.com/joe-chelladurai/uxr/issues + url: https://joe-chelladurai.github.io/uxr/ + url_cran: https://CRAN.R-project.org/package=uxr + url_git: '' +V8: + version: 6.0.1 + title: Embedded JavaScript and WebAssembly Engine for R + maintainer: Jeroen Ooms + description: |- + An R interface to V8 : Google's open source JavaScript + and WebAssembly engine. This package can be compiled either with V8 version 6 + and up or NodeJS when built as a shared library. + date_publication: '2025-02-02' + bug_reports: https://github.com/jeroen/v8/issues + url: https://jeroen.r-universe.dev/V8 + url_cran: https://CRAN.R-project.org/package=V8 + url_git: '' +vaccine: + version: 1.3.0 + title: |- + Statistical Tools for Immune Correlates Analysis of Vaccine + Clinical Trial Data + maintainer: Avi Kenny + description: |- + Various semiparametric and nonparametric statistical tools for + immune correlates analysis of vaccine clinical trial data. This includes + calculation of summary statistics and estimation of risk, vaccine efficacy, + controlled effects (controlled risk and controlled vaccine efficacy), and + mediation effects (natural direct effect, natural indirect effect, + proportion mediated). See Gilbert P, Fong Y, Kenny A, and Carone, M (2022) + and Fay MP and Follmann DA (2023) + . + date_publication: '2025-01-07' + bug_reports: https://github.com/Avi-Kenny/vaccine/issues + url: https://avi-kenny.github.io/vaccine/ + url_cran: https://CRAN.R-project.org/package=vaccine + url_git: '' +vaccineff: + version: 1.0.0 + title: Estimate Vaccine Effectiveness Based on Different Study Designs + maintainer: Zulma M. Cucunubá + description: |- + Provides tools for estimating vaccine effectiveness and + related metrics. The 'vaccineff_data' class manages key features for + preparing, visualizing, and organizing cohort data, as well as + estimating vaccine effectiveness. The results and model performance + are assessed using the 'vaccineff' class. + date_publication: '2024-11-29' + bug_reports: https://github.com/epiverse-trace/vaccineff/issues + url: https://epiverse-trace.github.io/vaccineff/ + url_cran: https://CRAN.R-project.org/package=vaccineff + url_git: https://github.com/epiverse-trace/vaccineff +vachette: + version: 0.40.1 + title: A Method for Visualization of Pharmacometric Models + maintainer: James Craig + description: |- + A method to visualize pharmacometric analyses which are impacted by + covariate effects. Variability-aligned covariate harmonized-effects + and time-transformation equivalent ('vachette') facilitates intuitive + overlays of data and model predictions, allowing for comprehensive + comparison without dilution effects. 'vachette' improves upon previous + methods Lommerse et al. (2021) , enabling its + application to all pharmacometric models and enhancing Visual Predictive + Checks (VPC) by integrating data into cohesive plots that can highlight + model misspecification. + date_publication: '2024-09-19' + bug_reports: https://github.com/certara/vachette/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vachette + url_git: https://github.com/certara/vachette +vacuum: + version: 0.1.0 + title: Tukey's Vacuum Cleaner + maintainer: Ron Sielinski + description: |- + An implementation of three procedures developed by + John Tukey: FUNOP (FUll NOrmal Plot), FUNOR-FUNOM + (FUll NOrmal Rejection-FUll NOrmal Modification), and vacuum cleaner. + Combined, they provide a way to identify, treat, and analyze outliers + in two-way (i.e., contingency) tables, as described in his + landmark paper "The Future of Data Analysis", Tukey, John W. (1962) + . + date_publication: '2020-09-08' + bug_reports: https://github.com/Sielinski/vacuum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vacuum + url_git: https://github.com/Sielinski/vacuum +vader: + version: 0.2.1 + title: Valence Aware Dictionary and sEntiment Reasoner (VADER) + maintainer: Katherine Roehrick + description: |- + A lexicon and rule-based sentiment analysis tool that is specifically + attuned to sentiments expressed in social media, and works well on texts from other + domains. Hutto & Gilbert (2014) . + date_publication: '2020-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vader + url_git: '' +vaersNDvax: + version: 1.0.4 + title: |- + Non-Domestic Vaccine Adverse Event Reporting System (VAERS) + Vaccine Data for Present + maintainer: Irucka Embry + description: |- + Non-Domestic VAERS vaccine data for 01/01/2016 - 06/14/2016. If + you want to explore the full VAERS data for 1990 - Present (data, symptoms, + and vaccines), then check out the 'vaersND' package from the URL below. The + URL and BugReports below correspond to the 'vaersND' package, of which + 'vaersNDvax' is a small subset (2016 only). 'vaersND' is not hosted on CRAN + due to the large size of the data set. To install the Suggested 'vaers' and + 'vaersND' packages, use the following R code: + 'devtools::install_git("https://gitlab.com/iembry/vaers.git", + build_vignettes = TRUE)' and + 'devtools::install_git("https://gitlab.com/iembry/vaersND.git", + build_vignettes = TRUE)'. "VAERS is a national vaccine safety + surveillance program co-sponsored by the US Centers for Disease Control and + Prevention (CDC) and the US Food and Drug Administration (FDA). VAERS is a + post-marketing safety surveillance program, collecting information about + adverse events (possible side effects) that occur after the administration + of vaccines licensed for use in the United States." For more information + about the data, visit . For information about + vaccination/immunization hazards, visit + . + date_publication: '2016-08-09' + bug_reports: https://gitlab.com/iembry/vaersND/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vaersNDvax + url_git: https://gitlab.com/iembry/vaersND +vaersvax: + version: 1.0.5 + title: |- + US Vaccine Adverse Event Reporting System (VAERS) Vaccine Data + for Present + maintainer: Irucka Embry + description: |- + US VAERS vaccine data for 01/01/2018 - 06/14/2018. If you want to + explore the full VAERS data for 1990 - Present (data, symptoms, and + vaccines), then check out the 'vaers' package from the URL below. The URL + and BugReports below correspond to the 'vaers' package, of which 'vaersvax' + is a small subset (2018 only). 'vaers' is not hosted on CRAN due to the + large size of the data set. To install the Suggested 'vaers' and 'vaersND' + packages, use the following R code: + 'devtools::install_git("", + build_vignettes = TRUE)' and + 'devtools::install_git("", + build_vignettes = TRUE)'. "The Vaccine Adverse Event Reporting System (VAERS) + is a national early warning system to detect possible safety problems in + U.S.-licensed vaccines. VAERS is co-managed by the Centers for Disease Control + and Prevention (CDC) and the U.S. Food and Drug Administration (FDA)." For + more information about the data, visit . For + information about + vaccination/immunization hazards, visit + . + date_publication: '2018-08-29' + bug_reports: https://gitlab.com/iembry/vaers/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vaersvax + url_git: https://gitlab.com/iembry/vaers +vagalumeR: + version: 0.1.6 + title: Access to the 'Vagalume' API + maintainer: Bruna Wundervald + description: |- + Provides access to the 'Vagalume' API . + The data extracted is basically lyrics of songs and information about + artists/bands. + date_publication: '2019-02-03' + bug_reports: https://github.com/r-music/vagalumeR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vagalumeR + url_git: https://github.com/r-music/vagalumeR +vagam: + version: '1.1' + title: Variational Approximations for Generalized Additive Models + maintainer: Han Lin Shang + description: Fits generalized additive models (GAMs) using a variational approximations + (VA) framework. In brief, the VA framework provides a fully or at least closed + to fully tractable lower bound approximation to the marginal likelihood of a GAM + when it is parameterized as a mixed model (using penalized splines, say). In doing + so, the VA framework aims offers both the stability and natural inference tools + available in the mixed model approach to GAMs, while achieving computation times + comparable to that of using the penalized likelihood approach to GAMs. See Hui + et al. (2018) . + date_publication: '2019-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vagam + url_git: '' +VAJointSurv: + version: 0.1.1 + title: Variational Approximation for Joint Survival and Marker Models + maintainer: Benjamin Christoffersen + description: |- + Estimates joint marker (longitudinal) and + survival (time-to-event) outcomes using variational approximations. + The package supports multivariate markers allowing for + correlated error terms and multiple types of survival outcomes which may be + left-truncated, right-censored, and recurrent. Time-varying fixed and + random covariate effects are supported along with non-proportional hazards. + date_publication: '2025-01-15' + bug_reports: https://github.com/boennecd/VAJointSurv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VAJointSurv + url_git: https://github.com/boennecd/VAJointSurv +valaddin: + version: 1.0.2 + title: Functional Input Validation + maintainer: Eugene Ha + description: |- + A set of basic tools to transform functions into functions with + input validation checks, in a manner suitable for both programmatic and + interactive use. + date_publication: '2023-10-25' + bug_reports: https://github.com/egnha/valaddin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=valaddin + url_git: https://github.com/egnha/valaddin +valection: + version: 1.0.0 + title: Sampler for Verification Studies + maintainer: Paul C. Boutros + description: |- + A binding for the 'valection' program which offers various ways to + sample the outputs of competing algorithms or parameterizations, and fairly + assess their performance against each other. The 'valection' C library is + required to use this package and can be downloaded from: + . Cooper CI, et al; Valection: Design Optimization for Validation and Verification Studies; Biorxiv 2018; . + date_publication: '2018-02-06' + bug_reports: '' + url: http://labs.oicr.on.ca/boutros-lab/software/valection + url_cran: https://CRAN.R-project.org/package=valection + url_git: '' +valentine: + version: 2025.2.14 + title: Spread the Love for R Packages with Poetry + maintainer: Romain François + description: |- + Uses large language models to create poems about R packages. + Currently contains the roses() function to make "roses are red, ..." style + poems and the prompt() function to only assemble the prompt without submitting + it to the model. + date_publication: '2025-02-09' + bug_reports: https://github.com/tadascience/valentine/issues + url: https://valentine.tada.science/ + url_cran: https://CRAN.R-project.org/package=valentine + url_git: https://github.com/tadascience/valentine +VALERIE: + version: 1.1.0 + title: Visualising Splicing at Single-Cell Resolution + maintainer: Sean Wen + description: Alternative splicing produces a variety of different protein products + from a given gene. 'VALERIE' enables visualisation of alternative splicing events + from high-throughput single-cell RNA-sequencing experiments. 'VALERIE' computes + percent spliced-in (PSI) values for user-specified genomic coordinates corresponding + to alternative splicing events. PSI is the proportion of sequencing reads supporting + the included exon/intron as defined by Shiozawa (2018) . + PSI are inferred from sequencing reads data based on specialised infrastructures + for representing and computing annotated genomic ranges by Lawrence (2013) . + Computed PSI for each single cell are subsequently presented in the form of a + heatmap implemented using the 'pheatmap' package by Kolde (2010) . + Board overview of the mean PSI difference and associated p-values across different + user-defined groups of single cells are presented in the form of a line graph + using the 'ggplot2' package by Wickham (2007) . + date_publication: '2020-07-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VALERIE + url_git: '' +valet: + version: 0.9.0 + title: Provide R Client to the Bank of Canada's Valet API + maintainer: Corey Runkel + description: |- + The Bank of Canada updated their Valet API + , and no R client + currently exists. This provides access to all of Valet's endpoints + and serves responses in wide format easy for researchers to + handle but also provides tools to access API responses as a list. + date_publication: '2022-04-12' + bug_reports: '' + url: runkelcorey.github.io/valet + url_cran: https://CRAN.R-project.org/package=valet + url_git: '' +valhallr: + version: 0.1.0 + title: A Tidy Interface to the 'Valhalla' Routing Engine + maintainer: Christopher Belanger + description: |- + An interface to the 'Valhalla' routing engine’s + application programming interfaces (APIs) for turn-by-turn routing, + isochrones, and origin-destination analyses. Also includes several + user-friendly functions for plotting outputs, and strives to follow + "tidy" design principles. Please note that this package requires + access to a running instance of 'Valhalla', which is open source and + can be downloaded from . + date_publication: '2021-03-09' + bug_reports: https://github.com/chris31415926535/valhallr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=valhallr + url_git: https://github.com/chris31415926535/valhallr +validann: + version: 1.2.1 + title: Validation Tools for Artificial Neural Networks + maintainer: Greer B. Humphrey + description: |- + Methods and tools for analysing and validating the outputs + and modelled functions of artificial neural networks (ANNs) in terms + of predictive, replicative and structural validity. Also provides a + method for fitting feed-forward ANNs with a single hidden layer. + date_publication: '2017-04-20' + bug_reports: http://github.com/gbhumphrey1/validann/issues + url: '' + url_cran: https://CRAN.R-project.org/package=validann + url_git: http://github.com/gbhumphrey1/validann +validata: + version: 0.1.0 + title: Validate Data Frames + maintainer: Harrison Tietze + description: Functions for validating the structure and properties of data frames. + Answers essential questions about a data set after initial import or modification. + What are the unique or missing values? What columns form a primary key? What are + the properties of the numeric or categorical columns? What kind of overlap or + mapping exists between 2 columns? + date_publication: '2021-10-05' + bug_reports: https://github.com/Harrison4192/validata/issues + url: https://harrison4192.github.io/validata/ + url_cran: https://CRAN.R-project.org/package=validata + url_git: https://github.com/Harrison4192/validata +validate: + version: 1.1.5 + title: Data Validation Infrastructure + maintainer: Mark van der Loo + description: |- + Declare data validation rules and data quality indicators; + confront data with them and analyze or visualize the results. + The package supports rules that are per-field, in-record, + cross-record or cross-dataset. Rules can be automatically + analyzed for rule type and connectivity. Supports checks implied + by an SDMX DSD file as well. See also Van der Loo + and De Jonge (2018) , Chapter 6 + and the JSS paper (2021) . + date_publication: '2024-02-14' + bug_reports: https://github.com/data-cleaning/validate/issues + url: '' + url_cran: https://CRAN.R-project.org/package=validate + url_git: https://github.com/data-cleaning/validate +validateIt: + version: 1.2.1 + title: Validating Topic Coherence and Topic Labels + maintainer: Luwei Ying + description: By creating crowd-sourcing tasks that can be easily posted and results + retrieved using Amazon's Mechanical Turk (MTurk) API, researchers can use this + solution to validate the quality of topics obtained from unsupervised or semi-supervised + learning methods, and the relevance of topic labels assigned. This helps ensure + that the topic modeling results are accurate and useful for research purposes. + See Ying and others (2022) . For more information, + please visit . + date_publication: '2023-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=validateIt + url_git: '' +validatesuggest: + version: 0.3.2 + title: Generate Suggestions for Validation Rules + maintainer: Edwin de Jonge + description: |- + Generate suggestions for validation rules + from a reference data set, which can be used as a starting point for domain specific + rules to be checked with package 'validate'. + date_publication: '2023-10-06' + bug_reports: https://github.com/data-cleaning/validatesuggest/issues + url: '' + url_cran: https://CRAN.R-project.org/package=validatesuggest + url_git: https://github.com/data-cleaning/validatesuggest +validatetools: + version: 0.5.2 + title: Checking and Simplifying Validation Rule Sets + maintainer: Edwin de Jonge + description: |- + Rule sets with validation rules may contain redundancies or contradictions. + Functions for finding redundancies and problematic rules are provided, + given a set a rules formulated with 'validate'. + date_publication: '2023-09-30' + bug_reports: https://github.com/data-cleaning/validatetools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=validatetools + url_git: https://github.com/data-cleaning/validatetools +VALIDICLUST: + version: 0.1.0 + title: VALID Inference for Clusters Separation Testing + maintainer: Benjamin Hivert + description: |- + Given a partition resulting from any clustering algorithm, the implemented tests allow valid post-clustering inference by testing if a given variable significantly separates two of the estimated clusters. + Methods are detailed in: Hivert B, Agniel D, Thiebaut R & Hejblum BP (2022). + "Post-clustering difference testing: valid inference and practical considerations", . + date_publication: '2022-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VALIDICLUST + url_git: '' +validmind: + version: 0.1.2 + title: Interface to the 'ValidMind' Platform + maintainer: Andres Rodriguez + description: |- + Deploy, execute, and analyze the results of models hosted on the + 'ValidMind' platform . This package interfaces with the + 'Python' client library in order to allow advanced diagnostics and insight + into trained models all from an 'R' environment. + date_publication: '2024-11-07' + bug_reports: https://github.com/validmind/developer-framework/issues + url: '' + url_cran: https://CRAN.R-project.org/package=validmind + url_git: https://github.com/validmind/developer-framework +valmetrics: + version: 1.0.0 + title: Metrics and Plots for Model Evaluation + maintainer: Kristin Piikki + description: 'Functions for metrics and plots for model evaluation. Based on vectors + of observed and predicted values. Method: Kristin Piikki, Johanna Wetterlind, + Mats Soderstrom and Bo Stenberg (2021). .' + date_publication: '2021-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=valmetrics + url_git: '' +valorate: + version: 1.0-1 + title: Velocity and Accuracy of the LOg-RAnk TEst + maintainer: Victor Trevino + description: |- + The algorithm implemented in this package was + designed to quickly estimates the distribution of the + log-rank especially for heavy unbalanced groups. VALORATE + estimates the null distribution and the p-value of the + log-rank test based on a recent formulation. For a given + number of alterations that define the size of survival + groups, the estimation involves a weighted sum of + distributions that are conditional on a co-occurrence term + where mutations and events are both present. The estimation + of conditional distributions is quite fast allowing the + analysis of large datasets in few minutes + . + date_publication: '2016-10-09' + bug_reports: '' + url: http://bioinformatica.mty.itesm.mx/valorate + url_cran: https://CRAN.R-project.org/package=valorate + url_git: '' +valottery: + version: 0.0.1 + title: Results from the Virginia Lottery Draw Games + maintainer: Clay Ford + description: Historical results for the state of Virginia lottery draw games. Data + were downloaded from https://www.valottery.com/. + date_publication: '2015-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=valottery + url_git: '' +valr: + version: 0.8.3 + title: Genome Interval Arithmetic + maintainer: Kent Riemondy + description: |- + Read and manipulate genome intervals and signals. Provides + functionality similar to command-line tool suites within R, enabling + interactive analysis and visualization of genome-scale data. Riemondy + et al. (2017) . + date_publication: '2025-01-11' + bug_reports: https://github.com/rnabioco/valr/issues + url: https://rnabioco.github.io/valr/ + url_cran: https://CRAN.R-project.org/package=valr + url_git: https://github.com/rnabioco/valr/ +valueEQ5D: + version: 0.7.2 + title: Scoring EQ-5d Descriptive System + maintainer: Sheeja Manchira Krishnan + description: |- + EQ-5D is a standard instrument () that measures the quality of life + often used in clinical and economic evaluations of health care technologies. Both adult versions of EQ-5D (EQ-5D-3L and EQ-5D-5L) + contain a descriptive system and visual analog scale. The descriptive system measures the patient's health in 5 dimensions: + the 5L versions has 5 levels and 3L version has 3 levels. The descriptive system scores are usually converted to index values + using country specific values sets (that incorporates the country preferences). This package allows the calculation of both descriptive system + scores to the index value scores. The value sets for EQ-5D-3L are from the references mentioned in the website + The value sets for EQ-5D-3L for a total of 31 countries are used for the valuation (see the user guide for a complete list of references). + The value sets for EQ-5D-5L are obtained from references mentioned in the and other sources. + The value sets for EQ-5D-5L for a total of 17 countries are used for the valuation (see the user guide for a complete list of references). + The package can also be used to map 5L scores to 3L index values for 10 countries: Denmark, France, Germany, Japan, Netherlands, Spain, Thailand, UK, USA, and Zimbabwe. + The value set and method for mapping are obtained from Van Hout et al (2012) . + date_publication: '2021-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=valueEQ5D + url_git: '' +valuemap: + version: 2.0.4 + title: Making Choropleth Map + maintainer: Huncheol Ha + description: |2- + + You can easily visualize your 'sf' polygons or data.frame with h3 address. + While 'leaflet' package is too raw for data analysis, + this package can save data analysts' efforts & time with pre-set visualize options. + date_publication: '2022-10-06' + bug_reports: https://github.com/Curycu/valuemap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=valuemap + url_git: https://github.com/Curycu/valuemap +valueSetCompare: + version: 1.0.0 + title: Comparing HRQoL Instrument Value Sets + maintainer: Kim Rand + description: |- + The number of countries with multiple Health Related Quality of Life (HRQL) value sets is growing, and this trend is expected to continue. + Each instrument and value set characterizes and values health differently. Identical health states can yield different utility values when valued + using different value sets. The 'valueSetCompare' package facilitates comparisons of HRQoL value sets, enabling both theoretical and empirical comparisons. + For empirical comparisons, it employs a novel simulation-based method by Jiang et al. (2022) , allowing users to investigate + the responsiveness of HRQoL instruments across the entire health spectrum using cross-sectional data with external health anchors. + date_publication: '2024-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=valueSetCompare + url_git: '' +VAM: + version: 1.1.0 + title: Variance-Adjusted Mahalanobis + maintainer: H. Robert Frost + description: Contains logic for cell-specific gene set scoring of single cell RNA + sequencing data. + date_publication: '2023-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VAM + url_git: '' +vamc: + version: 0.2.1 + title: A Monte Carlo Valuation Framework for Variable Annuities + maintainer: Mingyi Jiang + description: |- + Implementation of a Monte Carlo simulation engine for valuing synthetic portfolios of + variable annuities, which reflect realistic features of common annuity contracts in practice. + It aims to facilitate the development and dissemination of research related to the efficient + valuation of a portfolio of large variable annuities. The main valuation methodology was + proposed by Gan (2017) . + date_publication: '2020-02-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vamc + url_git: '' +vampyr: + version: 1.1.1 + title: Factor Analysis Controlling the Effects of Response Bias + maintainer: David Navarro-Gonzalez + description: |- + Vampirize the response biases from a dataset! Performs + factor analysis controlling the effects of social desirability + and acquiescence using the method described in Ferrando, + Lorenzo-Seva & Chico (2009) . + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vampyr + url_git: '' +VancouvR: + version: 0.1.8 + title: Access the 'City of Vancouver' Open Data API + maintainer: Jens von Bergmann + description: |- + Wrapper around the 'City of Vancouver' Open Data API to simplify and standardize access to 'City of Vancouver' open data. + Functionality to list the data catalogue and access data and geographic records. + date_publication: '2024-04-18' + bug_reports: https://github.com/mountainMath/VancouvR/issues + url: https://mountainmath.github.io/VancouvR/ + url_cran: https://CRAN.R-project.org/package=VancouvR + url_git: https://github.com/mountainMath/VancouvR +vandalico: + version: 0.1.0 + title: Evaluation of Presence-Absence Models + maintainer: Alberto Jiménez-Valverde + description: |- + Collection of functions to evaluate presence-absence models. It + comprises functions to adjust discrimination statistics for the + representativeness effect through case-weighting, along with functions for + visualizing the outcomes. Originally outlined in: + Jiménez-Valverde (2022) The uniform AUC: dealing with the + representativeness effect in presence-absence models. Methods Ecol. Evol, + 13, 1224-1236. + date_publication: '2024-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vandalico + url_git: '' +vangogh: + version: 0.1.1 + title: A Vincent Van Gogh Color Palette Generator + maintainer: Cheryl Isabella + description: Palettes generated from Vincent van Gogh's paintings. + date_publication: '2022-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vangogh + url_git: https://github.com/cherylisabella/vangogh +vannstats: + version: 1.5.1.8 + title: Simplified Statistical Procedures for Social Sciences + maintainer: Burrel Vann Jr + description: Simplifies functions assess normality for bivariate and multivariate + statistical techniques. Includes functions designed to replicate plots and tables + that would result from similar calls in 'SPSS', including hst(), box(), qq(), + tab(), cormat(), and residplot(). Also includes simplified formulae, such as mode(), + scatter(), p.corr(), ow.anova(), and rm.anova(). + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vannstats + url_git: '' +vanquish: + version: 1.0.0 + title: Variant Quality Investigation Helper + maintainer: Tao Jiang + description: |- + Imports Variant Calling Format file into R. It can detect + whether a sample contains contaminant from the same species. + In the first stage of the approach, a change-point detection + method is used to identify copy number variations for filtering. + Next, features are extracted from the data for a support vector + machine model. For log-likelihood calculation, the deviation + parameter is estimated by maximum likelihood method. Using + a radial basis function kernel support vector machine, the + contamination of a sample can be detected. + date_publication: '2018-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vanquish + url_git: '' +vapour: + version: 0.10.0 + title: Access to the 'Geospatial Data Abstraction Library' ('GDAL') + maintainer: Michael Sumner + description: |- + Provides low-level access to 'GDAL' functionality. + 'GDAL' is the 'Geospatial Data Abstraction Library' a translator for raster and vector geospatial data formats + that presents a single raster abstract data model and single vector abstract data model to the calling application + for all supported formats . This package is focussed on providing exactly and only what GDAL does, to enable + developing further tools. + date_publication: '2024-06-14' + bug_reports: https://github.com/hypertidy/vapour/issues + url: https://hypertidy.github.io/vapour/ + url_cran: https://CRAN.R-project.org/package=vapour + url_git: https://github.com/hypertidy/vapour +VAR.etp: + version: '1.1' + title: 'VAR Modelling: Estimation, Testing, and Prediction' + maintainer: Jae H. Kim + description: A collection of the functions for estimation, hypothesis testing, prediction + for stationary vector autoregressive models. + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VAR.etp + url_git: '' +VAR.spec: + version: '1.0' + title: |- + Allows Specifying a Bivariate VAR (Vector Autoregression) with + Desired Spectral Characteristics + maintainer: Evangelos Ioannidis + description: The spectral characteristics of a bivariate series (Marginal Spectra, + Coherency- and Phase-Spectrum) determine whether there is a strong presence of + short-, medium-, or long-term fluctuations (components of certain frequencies + in the spectral representation of the series) in each one of them. These are + induced by strong peaks of the marginal spectra of each series at the corresponding + frequencies. The spectral characteristics also determine how strongly these short-, + medium-, or long-term fluctuations of the two series are correlated between the + two series. Information on this is provided by the Coherency spectrum at the corresponding + frequencies. Finally, certain fluctuations of the two series may be lagged to + each other. Information on this is provided by the Phase spectrum at the corresponding + frequencies. The idea in this package is to define a VAR (Vector autoregression) + model with desired spectral characteristics by specifying a number of polynomials, + required to define the VAR. See Ioannidis(2007) . + These are specified via their roots, instead of via their coefficients. This is + an idea borrowed from the Time Series Library of R. Dahlhaus, where it is used + for defining ARMA models for univariate time series. This way, one may e.g. specify + a VAR inducing a strong presence of long-term fluctuations in series 1 and in + series 2, which are weakly correlated, but lagged by a number of time units to + each other, while short-term fluctuations in series 1 and in series 2, are strongly + present only in one of the two series, while they are strongly correlated to each + other between the two series. Simulation from such models allows studying the + behavior of data-analysis tools, such as estimation of the spectra, under different + circumstances, as e.g. peaks in the spectra, generating bias, induced by leakage. + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VAR.spec + url_git: '' +varband: + version: 0.9.0 + title: Variable Banding of Large Precision Matrices + maintainer: Guo Yu + description: Implementation of the variable banding procedure for modeling local + dependence and estimating precision matrices that is introduced in Yu & Bien (2016) + and is available at . + date_publication: '2016-11-07' + bug_reports: http://github.com/hugogogo/varband/issues + url: '' + url_cran: https://CRAN.R-project.org/package=varband + url_git: http://github.com/hugogogo/varband +varbin: + version: 0.2.1 + title: Optimal Binning of Continuous and Categorical Variables + maintainer: Daniel Safai + description: |- + Tool for easy and efficient discretization of continuous and categorical data. + The package calculates the most optimal binning of a given explanatory variable with respect to a + user-specified target variable. The purpose is to assign a unique Weight-of-Evidence value + to each of the calculated binpoints in order to recode the original variable. + The package allows users to impose certain restrictions on the functional form on the resulting + binning while maximizing the overall information value in the original data. + The package is well suited for logistic scoring models where input variables may be subject to + restrictions such as linearity by e.g. regulatory authorities. An excellent source describing in + detail the development of scorecards, and the role of Weight-of-Evidence coding in credit scoring + is (Siddiqi 2006, ISBN: 978–0-471–75451–0). The package utilizes the discrete nature of decision trees and + Isotonic Regression to accommodate the trade-off between flexible functional forms and maximum + information value. + date_publication: '2018-10-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varbin + url_git: '' +varbvs: + version: 2.6-10 + title: |- + Large-Scale Bayesian Variable Selection Using Variational + Methods + maintainer: Peter Carbonetto + description: |- + Fast algorithms for fitting Bayesian variable selection + models and computing Bayes factors, in which the outcome (or + response variable) is modeled using a linear regression or a + logistic regression. The algorithms are based on the variational + approximations described in "Scalable variational inference for + Bayesian variable selection in regression, and its accuracy in + genetic association studies" (P. Carbonetto & M. Stephens, 2012, + ). This software has been applied to large + data sets with over a million variables and thousands of samples. + date_publication: '2023-05-31' + bug_reports: https://github.com/pcarbo/varbvs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=varbvs + url_git: https://github.com/pcarbo/varbvs +varclust: + version: 0.9.4 + title: Variables Clustering + maintainer: Piotr Sobczyk + description: |- + Performs clustering of quantitative variables, + assuming that clusters lie in low-dimensional subspaces. Segmentation of + variables, number of clusters and their dimensions are selected based on + BIC. Candidate models are identified based on many runs of K-means + algorithm with different random initializations of cluster centers. + date_publication: '2019-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varclust + url_git: '' +VARcpDetectOnline: + version: 0.2.0 + title: |- + Sequential Change Point Detection for High-Dimensional VAR + Models + maintainer: Yuhan Tian + description: |- + Implements the algorithm introduced in Tian, Y., and Safikhani, A. (2024) + , "Sequential Change Point Detection in High-dimensional + Vector Auto-regressive Models". This package provides tools for detecting change points + in the transition matrices of VAR models, effectively identifying shifts in temporal + and cross-correlations within high-dimensional time series data. + date_publication: '2025-02-13' + bug_reports: https://github.com/Helloworld9293/VARcpDetectOnline/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VARcpDetectOnline + url_git: https://github.com/Helloworld9293/VARcpDetectOnline +vardiag: + version: 0.2-1 + title: Variogram Diagnostics + maintainer: Edzer Pebesma + description: Interactive variogram diagnostics. + date_publication: '2015-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vardiag + url_git: https://github.com/edzer/vardiag/ +vardpoor: + version: 0.20.1 + title: |- + Variance Estimation for Sample Surveys by the Ultimate Cluster + Method + maintainer: Martins Liberts + description: 'Generation of domain variables, linearization of several non-linear + population statistics (the ratio of two totals, weighted income percentile, relative + median income ratio, at-risk-of-poverty rate, at-risk-of-poverty threshold, Gini + coefficient, gender pay gap, the aggregate replacement ratio, the relative median + income ratio, median income below at-risk-of-poverty gap, income quintile share + ratio, relative median at-risk-of-poverty gap), computation of regression residuals + in case of weight calibration, variance estimation of sample surveys by the ultimate + cluster method (Hansen, Hurwitz and Madow, Sample Survey Methods And Theory, vol. + I: Methods and Applications; vol. II: Theory. 1953, New York: John Wiley and Sons), + variance estimation for longitudinal, cross-sectional measures and measures of + change for single and multistage stage cluster sampling designs (Berger, Y. G., + 2015, ). Several other precision measures are derived + - standard error, the coefficient of variation, the margin of error, confidence + interval, design effect.' + date_publication: '2020-11-30' + bug_reports: https://github.com/CSBLatvia/vardpoor/issues/ + url: https://csblatvia.github.io/vardpoor/ + url_cran: https://CRAN.R-project.org/package=vardpoor + url_git: https://github.com/CSBLatvia/vardpoor/ +VarED: + version: 1.0.0 + title: Variance Estimation using Difference-Based Methods + maintainer: Wenlin Dai + description: Generating functions for both optimal and ordinary difference sequences, + and the difference-based estimation functions. + date_publication: '2017-03-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VarED + url_git: '' +VaRES: + version: 1.0.2 + title: |- + Computes Value at Risk and Expected Shortfall for over 100 + Parametric Distributions + maintainer: Leo Belzile + description: Computes Value at risk and expected shortfall, two most popular measures + of financial risk, for over one hundred parametric distributions, including all + commonly known distributions. Also computed are the corresponding probability + density function and cumulative distribution function. See Chan, Nadarajah and + Afuecheta (2015) for more details. + date_publication: '2023-04-22' + bug_reports: https://github.com/lbelzile/VaRES/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=VaRES + url_git: '' +varEst: + version: 0.1.0 + title: Variance Estimation + maintainer: Sayanti Guha Majumdar + description: Error variance estimation in ultrahigh dimensional datasets with four + different methods, viz. Refitted cross validation, k-fold refitted cross validation, + Bootstrap-refitted cross validation, Ensemble method. + date_publication: '2019-09-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varEst + url_git: '' +varhandle: + version: 2.0.6 + title: Functions for Robust Variable Handling + maintainer: Mehrad Mahmoudian + description: Variables are the fundamental parts of each programming language but + handling them efficiently might be frustrating for programmers. This package contains + some functions to help user (especially data explorers) to make more sense of + their variables and take the most out of variables and hardware resources. These + functions are written and crafted since 2014 with years of experience in statistical + data analysis on high-dimensional data, and for each of them there was a need. + Functions in this package are supposed to be efficient and easy to use, hence + they will be frequently updated to make them more convenient. + date_publication: '2023-09-30' + bug_reports: https://codeberg.org/mehrad/varhandle/issues + url: https://codeberg.org/mehrad/varhandle + url_cran: https://CRAN.R-project.org/package=varhandle + url_git: '' +variability: + version: 0.1.0 + title: Genetic Variability Analysis for Plant Breeding Research + maintainer: Raj Popat + description: Performs analysis of various genetic parameters like genotypic and + phenotypic coefficient of variance, heritability, genetic advance, genetic advance + as a percentage of mean. The package also has functions for genotypic and phenotypic + covariance, correlation and path analysis. Dataset has been added to facilitate + example. For more information refer Singh, R.K. and Chaudhary, B.D. (1977, ISBN:81766330709788176633079). + date_publication: '2020-09-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=variability + url_git: '' +variables: + version: 1.1-1 + title: Variable Descriptions + maintainer: Torsten Hothorn + description: Abstract descriptions of (yet) unobserved variables. + date_publication: '2021-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=variables + url_git: http://ctm.R-forge.R-project.org +VariableScreening: + version: 0.2.1 + title: |- + High-Dimensional Screening for Semiparametric Longitudinal + Regression + maintainer: John Dziak + description: |- + Implements variable screening techniques for ultra-high + dimensional regression settings. Techniques for independent (iid) data, + varying-coefficient models, and longitudinal data are implemented. The package + currently contains three screen functions: screenIID(), screenLD() and screenVCM(), + and six methods for simulating dataset: simulateDCSIS(), simulateLD, simulateMVSIS(), + simulateMVSISNY(), simulateSIRS() and simulateVCM(). The package is based on the work of + Li-Ping ZHU, Lexin LI, Runze LI, and Li-Xing ZHU (2011) , + Runze LI, Wei ZHONG, & Liping ZHU (2012) , + Jingyuan LIU, Runze LI, & Rongling WU (2014) + Hengjian CUI, Runze LI, & Wei ZHONG (2015) , and + Wanghuan CHU, Runze LI and Matthew REIMHERR (2016) . + date_publication: '2022-06-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VariableScreening + url_git: '' +varian: + version: 0.2.2 + title: Variability Analysis in R + maintainer: Joshua F. Wiley + description: |- + Uses a Bayesian model to + estimate the variability in a repeated + measure outcome and use that as an outcome or a predictor + in a second stage model. + date_publication: '2016-02-28' + bug_reports: https://github.com/ElkhartGroup/varian/issues + url: '' + url_cran: https://CRAN.R-project.org/package=varian + url_git: https://github.com/ElkhartGroup/varian +VarianceGamma: + version: 0.4-2 + title: The Variance Gamma Distribution + maintainer: David Scott + description: |- + Provides functions for the variance gamma + distribution. Density, distribution and quantile functions. + Functions for random number generation and fitting of the + variance gamma to data. Also, functions for computing moments + of the variance gamma distribution of any order about any + location. In addition, there are functions for checking the + validity of parameters and to interchange different sets of + parameterizations for the variance gamma distribution. + date_publication: '2023-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VarianceGamma + url_git: '' +variantspark: + version: 0.1.1 + title: A 'Sparklyr' Extension for 'VariantSpark' + maintainer: Samuel Macêdo + description: |- + This is a 'sparklyr' extension integrating 'VariantSpark' and R. 'VariantSpark' is + a framework based on 'scala' and 'spark' to analyze genome datasets, + see . It was tested on datasets with 3000 samples + each one containing 80 million features in either unsupervised clustering approaches + and supervised applications, like classification and regression. The genome datasets + are usually writing in VCF, a specific text file format used + in bioinformatics for storing gene sequence variations. So, 'VariantSpark' is a great + tool for genome research, because it is able to read VCF files, run analyses and return + the output in a 'spark' data frame. + date_publication: '2019-06-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=variantspark + url_git: '' +variationalDCM: + version: 2.0.1 + title: |- + Variational Bayesian Estimation for Diagnostic Classification + Models + maintainer: Keiichiro Hijikata + description: Enables computationally efficient parameters-estimation by variational + Bayesian methods for various diagnostic classification models (DCMs). DCMs are + a class of discrete latent variable models for classifying respondents into latent + classes that typically represent distinct combinations of skills they possess. + Recently, to meet the growing need of large-scale diagnostic measurement in the + field of educational, psychological, and psychiatric measurements, variational + Bayesian inference has been developed as a computationally efficient alternative + to the Markov chain Monte Carlo methods, e.g., Yamaguchi and Okada (2020a) , + Yamaguchi and Okada (2020b) , Yamaguchi (2020) , + Oka and Okada (2023) , and Yamaguchi and Martinez + (2023) . To facilitate their applications, 'variationalDCM' + is developed to provide a collection of recently-proposed variational Bayesian + estimation methods for various DCMs. + date_publication: '2024-03-25' + bug_reports: https://github.com/khijikata/variationalDCM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=variationalDCM + url_git: https://github.com/khijikata/variationalDCM +varImp: + version: '0.4' + title: RF Variable Importance for Arbitrary Measures + maintainer: Philipp Probst + description: Computes the random forest variable importance (VIMP) for the conditional + inference random forest (cforest) of the 'party' package. Includes a function + (varImp) that computes the VIMP for arbitrary measures from the 'measures' package. + For calculating the VIMP regarding the measures accuracy and AUC two extra functions + exist (varImpACC and varImpAUC). + date_publication: '2020-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varImp + url_git: '' +variosig: + version: 0.3-1 + title: Testing Spatial Dependence Using Empirical Variogram + maintainer: Craig Wang + description: Applying Monte Carlo permutation to generate pointwise variogram envelope + and checking for spatial dependence at different scales using permutation test. + Empirical Brown's method and Fisher's method are used to compute overall p-value + for hypothesis test. + date_publication: '2020-02-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=variosig + url_git: '' +vaRiskScore: + version: 1.1.0 + title: VA CVD Risk Score + maintainer: Xiaofei Chen + description: |- + Estimates the predicted 10-year cardiovascular (CVD) risk score (in probability) for women military service + members and veterans by inputting patient profiles. The proposed women CVD risk score improves the accuracy of the + existing American College of Cardiology/American Heart Association CVD risk assessment + tool in predicting long‐term CVD risk for VA women, particularly in young and racial/ethnic + minority women. See the reference: Jeon‐Slaughter, H., Chen, X., Tsai, S., Ramanan, B., & Ebrahimi, R. + (2021) . + date_publication: '2023-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vaRiskScore + url_git: '' +varitas: + version: 0.0.2 + title: Variant Calling in Targeted Analysis Sequencing Data + maintainer: Adam Mills + description: Multi-caller variant analysis pipeline for targeted analysis sequencing + (TAS) data. Features a modular, automated workflow that can start with raw reads + and produces a user-friendly PDF summary and a spreadsheet containing consensus + variant information. + date_publication: '2020-11-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varitas + url_git: '' +varjmcm: + version: 0.1.1 + title: |- + Estimations for the Covariance of Estimated Parameters in Joint + Mean-Covariance Models + maintainer: Naimin Jing + description: |- + The goal of the package is to equip the 'jmcm' package (current version 0.2.1) + with estimations of the covariance of estimated parameters. Two methods are provided. + The first method is to use the inverse of estimated Fisher's information matrix, see + M. Pourahmadi (2000) , M. Maadooliat, M. Pourahmadi and + J. Z. Huang (2013) , and W. Zhang, C. Leng, C. Tang (2015) + . The second method is bootstrap based, see Liu, R.Y. (1988) + for reference. + date_publication: '2020-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varjmcm + url_git: '' +varoc: + version: 0.2.0 + title: Value Added Receiver Operating Characteristics Curve + maintainer: Yunro Chung + description: A continuous version of the receiver operating characteristics (ROC) + curve to visualize and assess the classification and continuity performances of + biomarkers, diagnostic tests, or risk prediction models. + date_publication: '2024-01-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varoc + url_git: '' +varrank: + version: '0.5' + title: |- + Heuristics Tools Based on Mutual Information for Variable + Ranking + maintainer: Annina Cincera + description: A computational toolbox of heuristics approaches for performing variable + ranking and feature selection based on mutual information well adapted for multivariate + system epidemiology datasets. The core function is a general implementation of + the minimum redundancy maximum relevance model. R. Battiti (1994) . + Continuous variables are discretized using a large choice of rule. Variables ranking + can be learned with a sequential forward/backward search algorithm. The two main + problems that can be addressed by this package is the selection of the most representative + variable within a group of variables of interest (i.e. dimension reduction) and + variable ranking with respect to a set of features of interest. + date_publication: '2022-10-12' + bug_reports: '' + url: https://www.math.uzh.ch/pages/varrank/ + url_cran: https://CRAN.R-project.org/package=varrank + url_git: '' +VarRedOpt: + version: 0.1.0 + title: A Framework for Variance Reduction + maintainer: Onur Boyar + description: |- + In order to make it easy to use variance reduction algorithms for any simulation, this framework can help you. + We propose user friendly and easy to extend framework. Antithetic Variates, Inner Control Variates, + Outer Control Variates and Importance Sampling algorithms are available in the framework. User can + write its own simulation function and use the Variance Reduction techniques in this package to + obtain more efficient simulations. An implementation of Asian Option simulation is already + available within the package. See Kemal Dinçer Dingeç & Wolfgang Hörmann (2012) . + date_publication: '2020-12-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VarRedOpt + url_git: '' +VarReg: + version: '2.0' + title: Semi-Parametric Variance Regression + maintainer: Kristy Robledo + description: Methods for fitting semi-parametric mean and variance models, with + normal or censored data. Extended to allow a regression in the location, scale + and shape parameters, and further for multiple regression in each. + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VarReg + url_git: '' +vars: + version: 1.6-1 + title: VAR Modelling + maintainer: Bernhard Pfaff + description: Estimation, lag selection, diagnostic testing, forecasting, causality + analysis, forecast error variance decomposition and impulse response functions + of VAR models and estimation of SVAR and SVEC models. + date_publication: '2024-03-21' + bug_reports: '' + url: https://www.pfaffikus.de + url_cran: https://CRAN.R-project.org/package=vars + url_git: '' +varSel: + version: '0.2' + title: |- + Sequential Forward Floating Selection using Jeffries-Matusita + Distance + maintainer: Michele Dalponte + description: 'Feature selection using Sequential Forward Floating feature Selection + and Jeffries-Matusita distance. It returns a suboptimal set of features to use + for image classification. Reference: Dalponte, M., Oerka, H.O., Gobakken, T., + Gianelle, D. & Naesset, E. (2013). Tree Species Classification in Boreal Forests + With Hyperspectral Data. IEEE Transactions on Geoscience and Remote Sensing, 51, + 2632-2645, .' + date_publication: '2021-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=varSel + url_git: '' +VARSELECTEXPOSURE: + version: 1.0.3 + title: Variable Selection Methods Including an Exposure Variable + maintainer: Alex Martinez + description: Utilizes multiple variable selection methods to estimate Average Treatment + Effect. + date_publication: '2023-04-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VARSELECTEXPOSURE + url_git: '' +VarSelLCM: + version: 2.1.3.1 + title: |- + Variable Selection for Model-Based Clustering of Mixed-Type Data + Set with Missing Values + maintainer: Mohammed Sedki + description: Full model selection (detection of the relevant features and estimation + of the number of clusters) for model-based clustering (see reference here ). + Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing + values can occur and do not necessitate any pre-processing. Shiny application + permits an easy interpretation of the results. + date_publication: '2020-10-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VarSelLCM + url_git: http://varsellcm.r-forge.r-project.org/ +varSelRF: + version: 0.7-8 + title: Variable Selection using Random Forests + maintainer: Ramon Diaz-Uriarte + description: |- + Variable selection from random forests using both + backwards variable elimination (for the selection of small sets + of non-redundant variables) and selection based on the + importance spectrum (somewhat similar to scree plots; for the + selection of large, potentially highly-correlated variables). + Main applications in high-dimensional data (e.g., microarray + data, and other genomics and proteomics applications). + date_publication: '2017-07-10' + bug_reports: '' + url: http://ligarto.org/rdiaz/Software/Software.html + url_cran: https://CRAN.R-project.org/package=varSelRF + url_git: https://github.com/rdiaz02/varSelRF +VARshrink: + version: 0.3.1 + title: Shrinkage Estimation Methods for Vector Autoregressive Models + maintainer: Namgil Lee + description: |2- + + Vector autoregressive (VAR) model is a fundamental and effective approach + for multivariate time series analysis. Shrinkage estimation methods can be + applied to high-dimensional VAR models with dimensionality greater than + the number of observations, contrary to the standard ordinary least squares + method. This package is an integrative package delivering nonparametric, + parametric, and semiparametric methods in a unified and consistent manner, + such as the multivariate ridge regression in Golub, Heath, and Wahba (1979) + , a James-Stein type nonparametric shrinkage method in + Opgen-Rhein and Strimmer (2007) , and + Bayesian estimation methods using noninformative and informative priors + in Lee, Choi, and S.-H. Kim (2016) and + Ni and Sun (2005) . + date_publication: '2019-10-09' + bug_reports: https://github.com/namgillee/VARshrink/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=VARshrink + url_git: https://github.com/namgillee/VARshrink/ +vartest: + version: '1.2' + title: Tests for Variance Homogeneity + maintainer: Osman Dag + description: Performs 20 omnibus tests for testing the composite hypothesis of variance + homogeneity. + date_publication: '2024-05-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vartest + url_git: '' +varTestnlme: + version: 1.3.5 + title: |- + Variance Components Testing for Linear and Nonlinear Mixed + Effects Models + maintainer: Charlotte Baey + description: |- + An implementation of the Likelihood ratio Test (LRT) for testing that, + in a (non)linear mixed effects model, the variances of a subset of the random + effects are equal to zero. There is no restriction on the subset of variances + that can be tested: for example, it is possible to test that all the variances + are equal to zero. Note that the implemented test is asymptotic. + This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'. + Charlotte Baey and Estelle Kuhn (2019) . + date_publication: '2023-09-22' + bug_reports: https://github.com/baeyc/varTestnlme/issues + url: '' + url_cran: https://CRAN.R-project.org/package=varTestnlme + url_git: https://github.com/baeyc/varTestnlme/ +varycoef: + version: 0.3.4 + title: Modeling Spatially Varying Coefficients + maintainer: Jakob A. Dambon + description: |- + Implements a maximum likelihood estimation (MLE) method for + estimation and prediction of Gaussian process-based spatially varying + coefficient (SVC) models (Dambon et al. (2021a) + ). Covariance tapering (Furrer et + al. (2006) ) can be applied such that + the method scales to large data. Further, it implements a joint + variable selection of the fixed and random effects (Dambon et al. + (2021b) ). The package and its + capabilities are described in (Dambon et al. (2021c) ). + date_publication: '2022-09-17' + bug_reports: https://github.com/jakobdambon/varycoef/issues + url: '' + url_cran: https://CRAN.R-project.org/package=varycoef + url_git: https://github.com/jakobdambon/varycoef +vasicek: + version: 0.0.3 + title: Miscellaneous Functions for Vasicek Distribution + maintainer: WenSui Liu + description: |- + Provide a collection of miscellaneous R functions + related to the Vasicek distribution with the intent to make + the lives of risk modelers easier. + date_publication: '2020-11-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vasicek + url_git: https://github.com/statcompute/vasicek +vasicekreg: + version: 1.0.1 + title: Regression Modeling Using Vasicek Distribution + maintainer: Josmar Mazucheli + description: |- + Vasicek density, cumulative distribution, quantile functions and random deviate + generation of Vasicek distribution. In addition, there are two functions for fitting the + Generalized Additive Models for Location Scale and Shape introduced by Rigby and + Stasinopoulos (2005, ). Some functions + are written in C++ using 'Rcpp', developed by Eddelbuettel and Francois (2011, ). + date_publication: '2021-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vasicekreg + url_git: '' +vatcheckapi: + version: 0.1.0 + title: Client for the 'vatcheckapi.com' VAT Validation API + maintainer: Dominik Kukacka + description: An R client for the 'vatcheckapi.com' VAT number validation API. The + API requires registration of an API key. Basic features are free, some require + a paid subscription. You can find the full API documentation at + . + date_publication: '2023-05-10' + bug_reports: '' + url: https://vatcheckapi.com + url_cran: https://CRAN.R-project.org/package=vatcheckapi + url_git: '' +vaultr: + version: 1.2.0 + title: Vault Client for Secrets and Sensitive Data + maintainer: Rich FitzJohn + description: |- + Provides an interface to a 'HashiCorp' vault server over + its http API (typically these are self-hosted; see + ). This allows for secure storage and + retrieval of secrets over a network, such as tokens, passwords and + certificates. Authentication with vault is supported through + several backends including user name/password and authentication via + 'GitHub'. + date_publication: '2023-11-09' + bug_reports: https://github.com/vimc/vaultr/issues + url: https://www.vaccineimpact.org/vaultr/ + url_cran: https://CRAN.R-project.org/package=vaultr + url_git: https://github.com/vimc/vaultr +vaxpmx: + version: 0.0.6 + title: Vaccines Pharmacometrics + maintainer: Julie Dudasova (MSD) + description: |- + Estimate vaccine efficacy (VE) using immunogenicity data. + The inclusion of immunogenicity data in regression models can increase precision in VE. + The methods are described in the publications "Elucidating vaccine efficacy using a correlate of protection, demographics, and logistic regression" and "Improving precision of vaccine efficacy evaluation using immune correlate data in time-to-event models" by Julie Dudasova, Zdenek Valenta, and Jeffrey R. Sachs (2024). + date_publication: '2024-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vaxpmx + url_git: '' +VBel: + version: 1.1.0 + title: |- + Variational Bayes for Fast and Accurate Empirical Likelihood + Inference + maintainer: Jeremy Lim + description: |- + Computes the Gaussian variational approximation of the Bayesian + empirical likelihood posterior. This is an implementation of the function + found in Yu, W., & Bondell, H. D. (2023) . + date_publication: '2024-12-05' + bug_reports: https://github.com/jlimrasc/VBel/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VBel + url_git: https://github.com/jlimrasc/VBel +VBJM: + version: 0.1.0 + title: Variational Inference for Joint Model + maintainer: Jiehuan Sun + description: |- + The shared random effects joint model is one of the most widely used approaches to study the associations between longitudinal biomarkers and a survival outcome and make dynamic risk predictions using the longitudinally measured biomarkers. + One major limitation of joint models is that they could be computationally expensive for complex models where the number of the shared random effects is large. + This package can be used to fit complex multivariate joint models using our newly developed algorithm Jieqi Tu and Jiehuan Sun (2023) , which is based on Gaussian variational approximate inference and is computationally efficient. + date_publication: '2023-09-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VBJM + url_git: '' +VBLPCM: + version: 2.4.9 + title: Variational Bayes Latent Position Cluster Model for Networks + maintainer: Michael Salter-Townshend + description: Fit and simulate latent position and cluster models for network data, + using a fast Variational Bayes approximation developed in Salter-Townshend and + Murphy (2013) . + date_publication: '2023-03-22' + bug_reports: '' + url: https://mststats.github.io/#software + url_cran: https://CRAN.R-project.org/package=VBLPCM + url_git: '' +VBsparsePCA: + version: 0.1.0 + title: The Variational Bayesian Method for Sparse PCA + maintainer: Bo (Yu-Chien) Ning + description: 'Contains functions for a variational Bayesian method for sparse PCA + proposed by Ning (2020) . There are two algorithms: the PX-CAVI + algorithm (if assuming the loadings matrix is jointly row-sparse) and the batch + PX-CAVI algorithm (if without this assumption). The outputs of the main function, + VBsparsePCA(), include the mean and covariance of the loadings matrix, the score + functions, the variable selection results, and the estimated variance of the random + noise.' + date_publication: '2021-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VBsparsePCA + url_git: '' +VBTree: + version: 0.1.1 + title: Vector Binary Tree to Make Your Data Management More Efficient + maintainer: Chen Zhang + description: |- + Vector binary tree provides a new data structure, to + make your data visiting and management more efficient. If the + data has structured column names, it can read these names and + factorize them through specific split pattern, then build the mappings + within double list, vector binary tree, array and tensor mutually, through + which the batched data processing is achievable easily. The methods of + array and tensor are also applicable. Detailed methods are described in + Chen Zhang et al. (2020) . + date_publication: '2024-01-12' + bug_reports: https://github.com/CubicZebra/VBTree/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VBTree + url_git: https://github.com/CubicZebra/VBTree +VBV: + version: 0.6.2 + title: The Generalized Berlin Method for Time Series Decomposition + maintainer: Detlef Steuer + description: |- + Time series decomposition for univariate time series using the + "Verallgemeinerte Berliner Verfahren" (Generalized Berlin Method) as + described in 'Kontinuierliche Messgrößen und Stichprobenstrategien in + Raum und Zeit mit Anwendungen in den Natur-, Umwelt-, Wirtschafts- + und Finanzwissenschaften', by + Hebbel and Steuer, Springer Berlin Heidelberg, 2022 + , or + 'Decomposition of Time Series using the Generalised Berlin + Method (VBV)' by Hebbel and Steuer, in Jan Beran, Yuanhua Feng, Hartmut + Hebbel (Eds.): Empirical Economic and Financial Research - Theory, + Methods and Practice, Festschrift in Honour of Prof. Siegfried Heiler. + Series: Advanced Studies in Theoretical and Applied Econometrics. + Springer 2014, p. 9-40. + date_publication: '2023-01-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VBV + url_git: '' +VC2copula: + version: 0.1.5 + title: |- + Extend the 'copula' Package with Families and Models from + 'VineCopula' + maintainer: Thomas Nagler + description: |- + Provides new classes for (rotated) BB1, BB6, BB7, BB8, and + Tawn copulas, extends the existing Gumbel and Clayton families with + rotations, and allows to set up a vine copula model using the 'copula' API. + Corresponding objects from the 'VineCopula' API can easily be converted. + date_publication: '2024-02-22' + bug_reports: https://github.com/tnagler/VC2copula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VC2copula + url_git: https://github.com/tnagler/VC2copula +VCA: + version: 1.5.1 + title: Variance Component Analysis + maintainer: Andre Schuetzenmeister + description: |2- + + ANOVA and REML estimation of linear mixed models is implemented, once following + Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. + The primary objective of this package is to perform a variance component analysis (VCA) + according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement + Procedures" (2014). There are plotting methods for visualization of an experimental design, + plotting random effects and residuals. For ANOVA type estimation two methods for computing + ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of + variance components can be derived, which is used in estimating confidence intervals. Linear + hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific + values of covariables and with custom weighting schemes for factor variables. See ?VCA for a + more comprehensive description of the features. + date_publication: '2024-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VCA + url_git: '' +vccp: + version: 0.1.1 + title: Vine Copula Change Point Detection in Multivariate Time Series + maintainer: Xin Xiong + description: Implements the Vine Copula Change Point (VCCP) methodology for the + estimation of the number and location of multiple change points in the vine copula + structure of multivariate time series. The method uses vine copulas, various state-of-the-art + segmentation methods to identify multiple change points, and a likelihood ratio + test or the stationary bootstrap for inference. The vine copulas allow for various + forms of dependence between time series including tail, symmetric and asymmetric + dependence. The functions have been extensively tested on simulated multivariate + time series data and fMRI data. For details on the VCCP methodology, please see + Xiong & Cribben (2021). + date_publication: '2021-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vccp + url_git: '' +vcd: + version: 1.4-13 + title: Visualizing Categorical Data + maintainer: David Meyer + description: |- + Visualization techniques, data sets, summary and inference + procedures aimed particularly at categorical data. Special + emphasis is given to highly extensible grid graphics. The + package was package was originally inspired by the book + "Visualizing Categorical Data" by Michael Friendly and is + now the main support package for a new book, + "Discrete Data Analysis with R" by Michael Friendly and + David Meyer (2015). + date_publication: '2024-09-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vcd + url_git: '' +vcdExtra: + version: 0.8-5 + title: '''vcd'' Extensions and Additions' + maintainer: Michael Friendly + description: |- + Provides additional data sets, methods and documentation to complement the 'vcd' package for Visualizing Categorical Data + and the 'gnm' package for Generalized Nonlinear Models. + In particular, 'vcdExtra' extends mosaic, assoc and sieve plots from 'vcd' to handle 'glm()' and 'gnm()' models and + adds a 3D version in 'mosaic3d'. Additionally, methods are provided for comparing and visualizing lists of + 'glm' and 'loglm' objects. This package is now a support package for the book, "Discrete Data Analysis with R" by + Michael Friendly and David Meyer. + date_publication: '2023-08-22' + bug_reports: https://github.com/friendly/vcdExtra + url: https://friendly.github.io/vcdExtra/ + url_cran: https://CRAN.R-project.org/package=vcdExtra + url_git: '' +vcfppR: + version: 0.7.1 + title: Rapid Manipulation of the Variant Call Format (VCF) + maintainer: Zilong Li + description: The 'vcfpp.h' () provides an easy-to-use + 'C++' 'API' of 'htslib', offering full functionality for manipulating Variant + Call Format (VCF) files. The 'vcfppR' package serves as the R bindings of the + 'vcfpp.h' library, enabling rapid processing of both compressed and uncompressed + VCF files. Explore a range of powerful features for efficient VCF data manipulation. + date_publication: '2024-12-26' + bug_reports: https://github.com/Zilong-Li/vcfppR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vcfppR + url_git: https://github.com/Zilong-Li/vcfppR +vcfR: + version: 1.15.0 + title: Manipulate and Visualize VCF Data + maintainer: Brian J. Knaus + description: |- + Facilitates easy manipulation of variant call format (VCF) data. + Functions are provided to rapidly read from and write to VCF files. Once + VCF data is read into R a parser function extracts matrices of data. This + information can then be used for quality control or other purposes. Additional + functions provide visualization of genomic data. Once processing is complete + data may be written to a VCF file (*.vcf.gz). It also may be converted into + other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between + VCF data and familiar R software. + date_publication: '2023-12-08' + bug_reports: '' + url: https://knausb.github.io/vcfR_documentation/ + url_cran: https://CRAN.R-project.org/package=vcfR + url_git: https://github.com/knausb/vcfR +vchartr: + version: 0.1.4 + title: Interactive Charts with the 'JavaScript' 'VChart' Library + maintainer: Victor Perrier + description: |- + Provides an 'htmlwidgets' interface to 'VChart.js'. + 'VChart', more than just a cross-platform charting library, but also an expressive data storyteller. + 'VChart' examples and documentation are available here: . + date_publication: '2025-01-15' + bug_reports: '' + url: https://dreamrs.github.io/vchartr/ + url_cran: https://CRAN.R-project.org/package=vchartr + url_git: '' +vcmeta: + version: 1.4.0 + title: Varying Coefficient Meta-Analysis + maintainer: Douglas G. Bonett + description: |- + Implements functions for varying coefficient meta-analysis methods. + These methods do not assume effect size homogeneity. Subgroup effect size + comparisons, general linear effect size contrasts, and linear models of + effect sizes based on varying coefficient methods can be used to describe + effect size heterogeneity. Varying coefficient meta-analysis methods do not + require the unrealistic assumptions of the traditional fixed-effect and + random-effects meta-analysis methods. + For details see: Statistical Methods for Psychologists, Volume 5, . + date_publication: '2024-07-04' + bug_reports: https://github.com/dgbonett/vcmeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vcmeta + url_git: https://github.com/dgbonett/vcmeta +vcov: + version: 0.0.1 + title: Variance-Covariance Matrices and Standard Errors + maintainer: Michael Chirico + description: Methods for faster extraction (about 5x faster in a few test cases) + of variance-covariance matrices and standard errors from models. Methods in the + 'stats' package tend to rely on the summary method, which may waste time computing + other summary statistics which are summarily ignored. + date_publication: '2017-07-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vcov + url_git: https://github.com/MichaelChirico/vcov +vcPB: + version: 1.1.1 + title: Longitudinal PB Varying-Coefficient Groupwise Disparity Model + maintainer: Sang Kyu Lee + description: Estimating the disparity between two groups based on the extended model + of the Peters-Belson (PB) method. Our model is the first work on the longitudinal + data, and also can set a varying variable to find the complicated association + between other variables and the varying variable. Our work is an extension of + the Peters-Belson method which was originally published in Peters (1941) + and Belson (1956). + date_publication: '2024-03-26' + bug_reports: https://github.com/SangkyuStat/vcPB/issues + url: https://sangkyustat.github.io/vcPB/ + url_cran: https://CRAN.R-project.org/package=vcPB + url_git: https://github.com/SangkyuStat/vcPB +vcpen: + version: '1.9' + title: Penalized Variance Components Analysis + maintainer: Jason Sinnwell + description: Method to perform penalized variance component analysis. + date_publication: '2022-01-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vcpen + url_git: '' +vcr: + version: 1.6.0 + title: Record 'HTTP' Calls to Disk + maintainer: Scott Chamberlain + description: |- + Record test suite 'HTTP' requests and replays them during + future runs. A port of the Ruby gem of the same name + (). Works by hooking into the 'webmockr' + R package for matching 'HTTP' requests by various rules ('HTTP' method, + 'URL', query parameters, headers, body, etc.), and then caching + real 'HTTP' responses on disk in 'cassettes'. Subsequent 'HTTP' requests + matching any previous requests in the same 'cassette' use a cached + 'HTTP' response. + date_publication: '2024-07-23' + bug_reports: https://github.com/ropensci/vcr/issues + url: https://books.ropensci.org/http-testing/ + url_cran: https://CRAN.R-project.org/package=vcr + url_git: https://github.com/ropensci/vcr/ +vcrpart: + version: 1.0-6 + title: |- + Tree-Based Varying Coefficient Regression for Generalized Linear + and Ordinal Mixed Models + maintainer: Reto Burgin + description: Recursive partitioning for varying coefficient generalized linear models + and ordinal linear mixed models. Special features are coefficient-wise partitioning, + non-varying coefficients and partitioning of time-varying variables in longitudinal + regression. A description of a part of this package was published by Burgin and + Ritschard (2017) . + date_publication: '2024-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vcrpart + url_git: '' +vctrs: + version: 0.6.5 + title: Vector Helpers + maintainer: Davis Vaughan + description: |- + Defines new notions of prototype and size that are used to + provide tools for consistent and well-founded type-coercion and + size-recycling, and are in turn connected to ideas of type- and + size-stability useful for analysing function interfaces. + date_publication: '2023-12-01' + bug_reports: https://github.com/r-lib/vctrs/issues + url: https://vctrs.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=vctrs + url_git: https://github.com/r-lib/vctrs +vctsfr: + version: 0.1.1 + title: Visualizing Collections of Time Series Forecasts + maintainer: Francisco Martinez + description: |- + A way of visualizing collections of time series and, optionally + their future values, forecasts for their future values and prediction + intervals for the forecasts. A web-based GUI can be used to display the + information in a collection of time series. + date_publication: '2023-12-07' + bug_reports: https://github.com/franciscomartinezdelrio/vctsfr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vctsfr + url_git: https://github.com/franciscomartinezdelrio/vctsfr +vcvComp: + version: 1.0.2 + title: Comparison of Variance - Covariance Patterns + maintainer: Anne Le Maitre + description: Comparison of variance - covariance patterns using relative principal + component analysis (relative eigenanalysis), as described in Le Maitre and Mitteroecker + (2019) . Also provides functions to compute group + covariance matrices, distance matrices, and perform proportionality tests. A worked + sample on the body shape of cichlid fishes is included, based on the dataset from + Kerschbaumer et al. (2013) . + date_publication: '2020-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vcvComp + url_git: '' +VDAP: + version: 2.0.0 + title: Peptide Array Analysis Tools + maintainer: Cody Moore + description: |- + Analyze Peptide Array Data and characterize peptide + sequence space. Allows for high level visualization of global signal, Quality control based + on replicate correlation and/or relative Kd, calculation of peptide Length/Charge/Kd parameters, + Hits selection based on RFU Signal, and amino acid composition/basic motif recognition with RFU + signal weighting. Basic signal trends can be used to generate peptides that follow the observed + compositional trends. + date_publication: '2016-05-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VDAP + url_git: '' +vdar: + version: 0.1.3-2 + title: Discriminant Analysis Incorporating Individual Uncertainties + maintainer: Solveig Pospiech + description: |- + The qda() function from package 'MASS' is extended to calculate a weighted linear (LDA) and quadratic discriminant analysis (QDA) by changing the group variances and group means based on cell-wise uncertainties. + The uncertainties can be derived e.g. through relative errors for each individual measurement (cell), not only row-wise or column-wise uncertainties. + The method can be applied compositional data (e.g. portions of substances, concentrations) and non-compositional data. + date_publication: '2022-01-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vdar + url_git: '' +vdg: + version: 1.2.3 + title: Variance Dispersion Graphs and Fraction of Design Space Plots + maintainer: Pieter Schoonees + description: |- + Facilities for constructing variance dispersion graphs, fraction- + of-design-space plots and similar graphics for exploring the properties of + experimental designs. The design region is explored via random sampling, which + allows for more flexibility than traditional variance dispersion graphs. A + formula interface is leveraged to provide access to complex model formulae. + Graphics can be constructed simultaneously for multiple experimental designs + and/or multiple model formulae. Instead of using pointwise optimization to + find the minimum and maximum scaled prediction variance curves, which can be + inaccurate and time consuming, this package uses quantile regression as an + alternative. + date_publication: '2024-04-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vdg + url_git: '' +vdiffr: + version: 1.0.8 + title: Visual Regression Testing and Graphical Diffing + maintainer: Lionel Henry + description: |- + An extension to the 'testthat' package that makes it easy to + add graphical unit tests. It provides a Shiny application to manage + the test cases. + date_publication: '2024-10-31' + bug_reports: https://github.com/r-lib/vdiffr/issues + url: https://vdiffr.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=vdiffr + url_git: https://github.com/r-lib/vdiffr +vDiveR: + version: 2.0.1 + title: Visualization of Viral Protein Sequence Diversity Dynamics + maintainer: Pendy Tok + description: |- + To ease the visualization of outputs from Diversity Motif Analyser ('DiMA'; + ). 'vDiveR' allows visualization of the diversity + motifs (index and its variants – major, minor and unique) for elucidation of + the underlying inherent dynamics. Please refer + for more information. + date_publication: '2024-11-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vDiveR + url_git: '' +VDJgermlines: + version: '0.1' + title: Variable, Diversity and Joining Sequences from Various Species + maintainer: Alexander Yermanos + description: Contains variable, diversity, and joining sequences and accompanying + functions that enable both the extraction of and comparison between immune V-D-J + genomic segments from a variety of species. Sources include IMGT from MP Lefranc + (2009) and Vgenerepertoire from publication DN Olivieri + (2014) . + date_publication: '2018-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VDJgermlines + url_git: '' +VDPO: + version: 0.1.0 + title: Working with and Analyzing Functional Data of Varying Lengths + maintainer: Pavel Hernandez + description: |- + Comprehensive set of tools for analyzing and manipulating functional + data with non-uniform lengths. This package addresses two common scenarios in + functional data analysis: Variable Domain Data, where the observation domain + differs across samples, and Partially Observed Data, where observations are + incomplete over the domain of interest. 'VDPO' enhances the flexibility and + applicability of functional data analysis in 'R'. + See Amaro et al. (2024) . + date_publication: '2024-10-21' + bug_reports: '' + url: https://pavel-hernadez-amaro.github.io/VDPO/ + url_cran: https://CRAN.R-project.org/package=VDPO + url_git: '' +VDSM: + version: 0.1.1 + title: Visualization of Distribution of Selected Model + maintainer: Linna Wang + description: Although model selection is ubiquitous in scientific discovery, the + stability and uncertainty of the selected model is often hard to evaluate. How + to characterize the random behavior of the model selection procedure is the key + to understand and quantify the model selection uncertainty. This R package offers + several graphical tools to visualize the distribution of the selected model. For + example, Gplot(), Hplot(), VDSM_scatterplot() and VDSM_heatmap(). To the best + of our knowledge, this is the first attempt to visualize such a distribution. + About what distribution of selected model is and how it work please see Qin,Y.and + Wang,L. (2021) "Visualization of Model Selection Uncertainty" . + date_publication: '2021-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VDSM + url_git: '' +VDSPCalibration: + version: '1.0' + title: |- + Statistical Methods for Designing and Analyzing a Calibration + Study + maintainer: Lu Tian + description: Provides statistical methods for the design and analysis of a calibration + study, which aims for calibrating measurements using two different methods. The + package includes sample size calculation, sample selection, regression analysis + with error-in measurements and change-point regression. The method is described + in Tian, Durazo-Arvizu, Myers, et al. (2014) . + date_publication: '2017-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VDSPCalibration + url_git: '' +vec2dtransf: + version: 1.1.3 + title: 2D Cartesian Coordinate Transformation + maintainer: German Carrillo + description: Applies affine and similarity transformations on vector spatial data + (sp objects). Transformations can be defined from control points or directly from + parameters. If redundant control points are provided Least Squares is applied + allowing to obtain residuals and RMSE. + date_publication: '2023-08-23' + bug_reports: https://github.com/gacarrillor/vec2dtransf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vec2dtransf + url_git: https://github.com/gacarrillor/vec2dtransf +veccompare: + version: 0.1.0 + title: |- + Perform Set Operations on Vectors, Automatically Generating All + n-Wise Comparisons, and Create Markdown Output + maintainer: Jacob Gerard Levernier + description: |- + Automates set operations (i.e., comparisons of overlap) between multiple vectors. + It also contains a function for automating reporting in 'RMarkdown', by generating markdown output for easy analysis, as well as an 'RMarkdown' template for use with 'RStudio'. + date_publication: '2017-09-15' + bug_reports: https://github.com/publicus/r-veccompare/issues + url: '' + url_cran: https://CRAN.R-project.org/package=veccompare + url_git: https://github.com/publicus/r-veccompare +VeccTMVN: + version: 1.2.1 + title: Multivariate Normal Probabilities using Vecchia Approximation + maintainer: Jian Cao + description: 'Under a different representation of the multivariate normal (MVN) + probability, we can use the Vecchia approximation to sample the integrand at a + linear complexity with respect to n. Additionally, both the SOV algorithm from + Genz (92) and the exponential-tilting method from Botev (2017) can be adapted + to linear complexity. The reference for the method implemented in this package + is Jian Cao and Matthias Katzfuss (2024) "Linear-Cost Vecchia Approximation of + Multivariate Normal Probabilities" . Two major + references for the development of our method are Alan Genz (1992) "Numerical Computation + of Multivariate Normal Probabilities" and + Z. I. Botev (2017) "The Normal Law Under Linear Restrictions: Simulation and Estimation + via Minimax Tilting" .' + date_publication: '2024-11-26' + bug_reports: https://github.com/JCatwood/VeccTMVN/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VeccTMVN + url_git: https://github.com/JCatwood/VeccTMVN +VecDep: + version: 0.1.3 + title: Measuring Copula-Based Dependence Between Random Vectors + maintainer: Steven De Keyser + description: |- + Provides functions for estimation (parametric, semi-parametric and non-parametric) + of copula-based dependence coefficients between a finite collection of random vectors, + including phi-dependence measures and Bures-Wasserstein dependence measures. + An algorithm for agglomerative hierarchical variable clustering is also implemented. + Following the articles De Keyser & Gijbels (2024) , + De Keyser & Gijbels (2024) , and De Keyser & Gijbels (2024) + . + date_publication: '2024-11-14' + bug_reports: https://github.com/StevenDeKeyser98/VecDep/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VecDep + url_git: https://github.com/StevenDeKeyser98/VecDep +vecsets: + version: '1.4' + title: Like Set Tools in 'Base' Package but Keeps Duplicate Elements + maintainer: Carl Witthoft + description: |- + The 'base' tools union() intersect(), etc., follow the algebraic definition + that each element of a set must be unique. + Since it's often helpful to compare all elements of two vectors, + this toolset treats every element as unique for counting purposes. + For ease of use, all functions in vecsets have an argument + 'multiple' which, when set to FALSE, + reverts them to the base::sets (alias for all the items) tools functionality. + date_publication: '2023-12-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vecsets + url_git: '' +vectorbitops: + version: 1.1.2 + title: Vector Bitwise Operations + maintainer: Samuel Sapire + description: |- + A tool for fast, efficient bitwise operations along the + elements within a vector. Provides such functionality for AND, OR and + XOR, as well as infix operators for all of the binary bitwise + operations. + date_publication: '2024-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vectorbitops + url_git: '' +VectorCodeR: + version: 0.2.0 + title: Easily Analyze Your Gait Patterns Using Vector Coding Technique + maintainer: zhexuan gu + description: |2- + + Facilitate the analysis of inter-limb and intra-limb coordination in human movement. + It provides functions for calculating the phase angle between two segments, enabling researchers and practitioners to quantify the coordination patterns within and between limbs during various motor tasks. + Needham, R., Naemi, R., & Chockalingam, N. (2014) . + Needham, R., Naemi, R., & Chockalingam, N. (2015) . + Tepavac, D., & Field-Fote, E. C. (2001) . + Park, J.H., Lee, H., Cho, Js. et al. (2021) . + date_publication: '2023-10-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VectorCodeR + url_git: '' +vectorsurvR: + version: 1.3.0 + title: Data Access and Analytical Tools for 'VectorSurv' Users + maintainer: Christina De Cesaris + description: Allows registered 'VectorSurv' users access + to data through the 'VectorSurv API' . Additionally + provides functions for analysis and visualization. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vectorsurvR + url_git: '' +vectorwavelet: + version: 0.1.0 + title: Vector Wavelet Coherence for Multiple Time Series + maintainer: Tunc Oygur + description: |- + New wavelet methodology (vector wavelet coherence) (Oygur, T., Unal, G, 2020 ) + to handle dynamic co-movements of multivariate time series via extending multiple and quadruple wavelet coherence methodologies. + This package can be used to perform multiple wavelet coherence, quadruple wavelet coherence, and n-dimensional vector wavelet coherence analyses. + date_publication: '2021-01-13' + bug_reports: https://github.com/toygur/vectorwavelet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vectorwavelet + url_git: https://github.com/toygur/vectorwavelet +VedicDateTime: + version: 0.1.9 + title: Vedic Calendar System + maintainer: Neeraj Dhanraj Bokde + description: |- + Provides platform for Vedic calendar system having several + functionalities to facilitate conversion between Gregorian and Vedic + calendar systems, and helpful in examining its impact in the + time series analysis domain. + date_publication: '2023-09-20' + bug_reports: https://github.com/prajwalkpatil/VedicDateTime/issues + url: https://www.neerajbokde.in/viggnette/2022-09-05-VedicDateTime + url_cran: https://CRAN.R-project.org/package=VedicDateTime + url_git: '' +veesa: + version: 0.1.6 + title: Pipeline for Explainable Machine Learning with Functional Data + maintainer: Katherine Goode + description: Implements the Variable importance Explainable Elastic Shape Analysis + pipeline for explainable machine learning with functional data inputs. Converts + training and testing data functional inputs to elastic shape analysis principal + components that account for vertical and/or horizontal variability. Computes feature + importance to identify important principal components and visualizes variability + captured by functional principal components. See Goode et al. (2025) + for technical details about the methodology. + date_publication: '2025-01-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=veesa + url_git: '' +vegalite: + version: 0.6.1 + title: |- + Tools to Encode Visualizations with the 'Grammar of + Graphics'-Like 'Vega-Lite' 'Spec' + maintainer: Bob Rudis + description: |- + The 'Vega-Lite' 'JavaScript' framework provides a higher-level grammar + for visual analysis, akin to 'ggplot' or 'Tableau', that generates complete 'Vega' + specifications. Functions exist which enable building a valid 'spec' from scratch + or importing a previously created 'spec' file. Functions also exist to export 'spec' + files and to generate code which will enable plots to be embedded in properly + configured web pages. The default behavior is to generate an 'htmlwidget'. + date_publication: '2016-03-22' + bug_reports: https://github.com/hrbrmstr/vegalite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vegalite + url_git: http://github.com/hrbrmstr/vegalite +vegan: + version: 2.6-10 + title: Community Ecology Package + maintainer: Jari Oksanen + description: |- + Ordination methods, diversity analysis and other + functions for community and vegetation ecologists. + date_publication: '2025-01-29' + bug_reports: https://github.com/vegandevs/vegan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vegan + url_git: https://github.com/vegandevs/vegan +vegan3d: + version: 1.4-0 + title: |- + Static and Dynamic 3D and Editable Interactive Plots for the + 'vegan' Package + maintainer: Jari Oksanen + description: |- + Static and dynamic 3D plots to be used with ordination + results and in diversity analysis, especially with the vegan package. + date_publication: '2025-02-20' + bug_reports: https://github.com/vegandevs/vegan3d/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vegan3d + url_git: https://github.com/vegandevs/vegan3d +vegawidget: + version: 0.5.0 + title: '''Htmlwidget'' for ''Vega'' and ''Vega-Lite''' + maintainer: Ian Lyttle + description: |- + 'Vega' and 'Vega-Lite' parse text in 'JSON' notation to render + chart-specifications into 'HTML'. This package is used to facilitate the + rendering. It also provides a means to interact with signals, events, + and datasets in a 'Vega' chart using 'JavaScript' or 'Shiny'. + date_publication: '2024-01-13' + bug_reports: https://github.com/vegawidget/vegawidget/issues + url: https://vegawidget.github.io/vegawidget/ + url_cran: https://CRAN.R-project.org/package=vegawidget + url_git: https://github.com/vegawidget/vegawidget +vegclust: + version: 2.0.2 + title: Fuzzy Clustering of Vegetation Data + maintainer: Miquel De Cáceres + description: 'A set of functions to: (1) perform fuzzy clustering of vegetation + data (De Caceres et al, 2010) ; (2) to assess + ecological community similarity on the basis of structure and composition (De + Caceres et al, 2013) .' + date_publication: '2022-08-25' + bug_reports: '' + url: https://emf-creaf.github.io/vegclust/ + url_cran: https://CRAN.R-project.org/package=vegclust + url_git: '' +vegdata: + version: 0.9.12 + title: Access Vegetation Databases and Treat Taxonomy + maintainer: Florian Jansen + description: |- + Handling of vegetation data from different sources ( + Turboveg 2.0 ; + the German national repository and others. + Taxonomic harmonization (given appropriate taxonomic lists, + e.g. the German taxonomic standard list "GermanSL", ). + date_publication: '2024-01-29' + bug_reports: '' + url: https://germansl.infinitenature.org + url_cran: https://CRAN.R-project.org/package=vegdata + url_git: '' +vegIndexCalc: + version: 0.1.0 + title: Vegetation Indices (VIs) Calculation for Remote Sensing Analysis + maintainer: Bijoy Chanda + description: It provides a comprehensive toolkit for calculating a suite of common + vegetation indices (VIs) derived from remote sensing imagery. VIs are essential + tools used to quantify vegetation characteristics, such as biomass, leaf area + index (LAI) and photosynthetic activity, which are essential parameters in various + ecological, agricultural, and environmental studies. Applications of this package + include biomass estimation, crop monitoring, forest management, land use and land + cover change analysis and climate change studies. For method details see, Deb,D.,Deb,S.,Chakraborty,D.,Singh,J.P.,Singh,A.K.,Dutta,P.and + Choudhury,A.(2020). Utilizing this R package, + users can effectively extract and analyze critical information from remote sensing + imagery, enhancing their comprehension of vegetation dynamics and their importance + in global ecosystems. The package includes the function vegetation_indices(). + date_publication: '2025-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vegIndexCalc + url_git: '' +vegperiod: + version: 0.4.0 + title: Determine Thermal Vegetation Periods + maintainer: Robert Nuske + description: |- + Collection of common methods to determine growing season length in + a simple manner. Start and end dates of the vegetation periods are calculated + solely based on daily mean temperatures and the day of the year. + date_publication: '2022-11-01' + bug_reports: https://github.com/rnuske/vegperiod/issues + url: https://rnuske.github.io/vegperiod/ + url_cran: https://CRAN.R-project.org/package=vegperiod + url_git: https://github.com/rnuske/vegperiod +vegtable: + version: 0.1.8 + title: Handling Vegetation Data Sets + maintainer: Miguel Alvarez + description: |- + Import and handling data from vegetation-plot databases, especially + data stored in 'Turboveg 2' (). + Also import/export routines for exchange of data with 'Juice' + () are implemented. + date_publication: '2023-03-14' + bug_reports: https://github.com/kamapu/vegtable/issues + url: http://kamapu.github.io/vegtable/ + url_cran: https://CRAN.R-project.org/package=vegtable + url_git: https://github.com/kamapu/vegtable +vein: + version: 1.1.3 + title: Vehicular Emissions Inventories + maintainer: Sergio Ibarra-Espinosa + description: |- + Elaboration of vehicular emissions inventories, + consisting in four stages, pre-processing activity data, preparing + emissions factors, estimating the emissions and post-processing of emissions + in maps and databases. More details in Ibarra-Espinosa et al (2018) . + Before using VEIN you need to know the vehicular composition of your study area, in other words, + the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to + start with the project to download a template to create a structure of directories and scripts. + date_publication: '2024-05-01' + bug_reports: https://github.com/atmoschem/vein/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vein + url_git: https://github.com/atmoschem/vein +vek: + version: 1.0.0 + title: Predicate Helper Functions for Testing Simple Atomic Vectors + maintainer: Sam Semegne + description: |- + Predicate helper functions for testing atomic vectors in R. All functions take + a single argument 'x' and check whether it's of the target type of base-R + atomic vector (i.e. no class extensions nor attributes other than 'names'), + returning TRUE or FALSE. Some additionally check for value (e.g. absence of + missing values, infinities, blank characters, or 'names' attribute; or having + length 1). + date_publication: '2024-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vek + url_git: https://github.com/samsemegne/vek +velociraptr: + version: 1.1.0 + title: Fossil Analysis + maintainer: Andrew A Zaffos + description: Functions for downloading, reshaping, culling, cleaning, and analyzing + fossil data from the Paleobiology Database . + date_publication: '2019-07-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=velociraptr + url_git: '' +vembedr: + version: 0.1.5 + title: Embed Video in HTML + maintainer: Ian Lyttle + description: |- + A set of functions for generating HTML to + embed hosted video in your R Markdown documents or Shiny applications. + date_publication: '2021-12-11' + bug_reports: https://github.com/ijlyttle/vembedr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vembedr + url_git: https://github.com/ijlyttle/vembedr +venn: + version: '1.12' + title: Draw Venn Diagrams + maintainer: Adrian Dusa + description: |- + A close to zero dependency package to draw and display Venn + diagrams up to 7 sets, and any Boolean union of set intersections. + date_publication: '2024-01-08' + bug_reports: https://github.com/dusadrian/venn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=venn + url_git: https://github.com/dusadrian/venn +VennDiagram: + version: 1.7.3 + title: Generate High-Resolution Venn and Euler Plots + maintainer: Paul Boutros + description: A set of functions to generate high-resolution Venn and Euler plots. + Includes handling for several special cases, including two-case scaling, and extensive + customization of plot shape and structure. + date_publication: '2022-04-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VennDiagram + url_git: '' +venneuler: + version: 1.1-4 + title: Venn and Euler Diagrams + maintainer: Simon Urbanek + description: Calculates and displays Venn and Euler Diagrams. + date_publication: '2024-01-14' + bug_reports: '' + url: https://www.rforge.net/venneuler/ + url_cran: https://CRAN.R-project.org/package=venneuler + url_git: '' +vennplot: + version: '1.0' + title: Venn Diagrams in 2D and 3D + maintainer: Zehao Xu + description: Calculate and plot Venn diagrams in 2D and 3D. + date_publication: '2017-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vennplot + url_git: '' +verbaliseR: + version: '0.1' + title: Make your Text Mighty Fine + maintainer: Cara Thompson + description: Turn R analysis outputs into full sentences, by writing vectors into + in-sentence lists, pluralising words conditionally, spelling out numbers if they + are at the start of sentences, writing out dates in full following US or UK style, + and managing capitalisations in tidy data. + date_publication: '2022-09-21' + bug_reports: https://github.com/cararthompson/verbaliseR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=verbaliseR + url_git: https://github.com/cararthompson/verbaliseR +verbalisr: + version: 0.7.2 + title: Describe Pedigree Relationships in Words + maintainer: Magnus Dehli Vigeland + description: |- + Describe in words the genealogical relationship between two + members of a given pedigree, using the algorithm in Vigeland (2022) + . 'verbalisr' is part of the + 'pedsuite' collection of packages for pedigree analysis. For a + demonstration of 'verbalisr', see the online app 'QuickPed' at + . + date_publication: '2025-03-01' + bug_reports: https://github.com/magnusdv/verbalisr/issues + url: https://magnusdv.github.io/pedsuite/ + url_cran: https://CRAN.R-project.org/package=verbalisr + url_git: https://github.com/magnusdv/verbalisr +verhoeff: + version: 0.4.0 + title: Implementation of the 'Verhoeff' Check Digit Algorithm + maintainer: Conor Neilson + description: |- + An implementation of the 'Verhoeff' algorithm for calculating + check digits (Verhoeff, J. (1969) ). + Functions are provided to calculate a check digit given an input number, + calculate and append a check digit to an input number, and validate that a + check digit is correct given an input number. + date_publication: '2021-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=verhoeff + url_git: '' +verification: + version: '1.44' + title: Weather Forecast Verification Utilities + maintainer: Eric Gilleland + description: Utilities for verifying discrete, continuous and probabilistic forecasts, + and forecasts expressed as parametric distributions are included. + date_publication: '2024-11-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=verification + url_git: '' +vermeulen: + version: 0.1.2 + title: Biomarker Data Set by Vermeulen et al. (2009) + maintainer: Ramiro Magno + description: |- + The biomarker data set by Vermeulen et al. (2009) + is provided. The data + source, however, is by Ruijter et al. (2013) + . The original data set may + be downloaded from + . + This data set is for a real-time quantitative polymerase chain reaction + (PCR) experiment that comprises the raw fluorescence data of 24,576 + amplification curves. This data set comprises 59 genes of interest and 5 + reference genes. Each gene was assessed on 366 neuroblastoma complementary + DNA (cDNA) samples and on 18 standard dilution series samples (10-fold + 5-point dilution series x 3 replicates + no template controls (NTC) x 3 + replicates). + date_publication: '2024-04-22' + bug_reports: https://github.com/ramiromagno/vermeulen/issues + url: https://rmagno.eu/vermeulen/ + url_cran: https://CRAN.R-project.org/package=vermeulen + url_git: https://github.com/ramiromagno/vermeulen +versioning: + version: 0.1.0 + title: Settings and File I/O using a Configuration YAML File + maintainer: Nathaniel Henry + description: |- + R data pipelines commonly require reading and writing data to versioned + directories. Each directory might correspond to one step of a multi-step process, + where that version corresponds to particular settings for that step and a chain of + previous steps that each have their own versions. This package creates a configuration + object that makes it easy to read and write versioned data, based on YAML + configuration files loaded and saved to each versioned folder. + date_publication: '2023-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=versioning + url_git: '' +versions: + version: '0.3' + title: Query and Install Specific Versions of Packages on CRAN + maintainer: Nick Golding + description: |- + Installs specified versions of R packages hosted on CRAN and + provides functions to list available versions and the versions of currently + installed packages. These tools can be used to help make R projects and + packages more reproducible. 'versions' fits in the narrow gap between + the 'devtools' install_version() function and the 'checkpoint' package. + devtools::install_version() installs a stated package version from source files + stored on the CRAN archives. However CRAN does not store binary versions of + packages so Windows users need to have RTools installed and Windows and OSX + users get longer installation times. 'checkpoint' uses the Revolution Analytics + MRAN server to install packages (from source or binary) as they were available + on a given date. It also provides a helpful interface to detect the packages + in use in a directory and install all of those packages for a given date. + 'checkpoint' doesn't provide install.packages-like functionality however, and + that's what 'versions' aims to do, by querying MRAN. As MRAN only goes back to + 2014-09-17, 'versions' can't install packages archived before this date. + date_publication: '2016-09-01' + bug_reports: https://github.com/goldingn/versions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=versions + url_git: '' +versionsort: + version: 1.1.0 + title: Sort and Order Version Codes + maintainer: Laura Bakala + description: A lightweight package for sorting version codes in various forms. No + strong dependencies guaranteed. + date_publication: '2022-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=versionsort + url_git: '' +versus: + version: 0.3.0 + title: Compare Data Frames + maintainer: Ryan Dickerson + description: A toolset for interactively exploring the differences between two data + frames. + date_publication: '2024-01-12' + bug_reports: https://github.com/eutwt/versus/issues + url: https://eutwt.github.io/versus/ + url_cran: https://CRAN.R-project.org/package=versus + url_git: https://github.com/eutwt/versus +VertexSimilarity: + version: '0.1' + title: Creates Vertex Similarity Matrix for an Undirected Graph + maintainer: Rishabh Singh + description: |- + Creates Vertex Similarity matrix of an undirected graph based + on the method stated by E. A. Leicht, Petter Holme, AND M. E. J. Newman in + their paper . + date_publication: '2016-01-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VertexSimilarity + url_git: '' +VertexWiseR: + version: 1.2.0 + title: |- + Simplified Vertex-Wise Analyses of Whole-Brain and Hippocampal + Surface + maintainer: Charly Billaud + description: |- + Provides functions to run statistical analyses on + surface-based neuroimaging data, computing measures including cortical + thickness and surface area of the whole-brain and of the hippocampi. + It can make use of 'FreeSurfer', 'fMRIprep' and 'HCP' preprocessed + datasets and 'HippUnfold' hippocampal segmentation outputs for a given + sample by restructuring the data values into a single file. The single + file can then be used by the package for analyses independently from + its base dataset and without need for its access. + date_publication: '2024-12-12' + bug_reports: '' + url: https://cogbrainhealthlab.github.io/VertexWiseR/ + url_cran: https://CRAN.R-project.org/package=VertexWiseR + url_git: '' +VeryLargeIntegers: + version: 0.2.1 + title: Store and Operate with Arbitrarily Large Integers + maintainer: Javier Leiva Cuadrado + description: |- + Multi-precision library that allows to store and operate with arbitrarily big integers without + loss of precision. It includes a large list of tools to work with them, like: + - Arithmetic and logic operators + - Modular-arithmetic operators + - Computer Number Theory utilities + - Probabilistic primality tests + - Factorization algorithms + - Random generators of diferent types of integers. + date_publication: '2023-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VeryLargeIntegers + url_git: '' +vesselr: + version: 0.2.1 + title: Gradient and Vesselness Tools for Arrays and NIfTI Images + maintainer: Jordan D. Dworkin + description: Simple functions for calculating the image gradient, image hessian, + volume ratio filter, and Frangi vesselness filter of 3-dimensional volumes. + date_publication: '2017-04-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vesselr + url_git: https://github.com/jdwor/vesselr +vetiver: + version: 0.2.5 + title: Version, Share, Deploy, and Monitor Models + maintainer: Julia Silge + description: |- + The goal of 'vetiver' is to provide fluent tooling to + version, share, deploy, and monitor a trained model. Functions handle + both recording and checking the model's input data prototype, and + predicting from a remote API endpoint. The 'vetiver' package is + extensible, with generics that can support many kinds of models. + date_publication: '2023-11-16' + bug_reports: https://github.com/rstudio/vetiver-r/issues + url: https://vetiver.rstudio.com + url_cran: https://CRAN.R-project.org/package=vetiver + url_git: https://github.com/rstudio/vetiver-r/ +vetr: + version: 0.2.18 + title: Trust, but Verify + maintainer: Brodie Gaslam + description: |- + Declarative template-based framework for verifying that objects + meet structural requirements, and auto-composing error messages when they do + not. + date_publication: '2024-06-21' + bug_reports: https://github.com/brodieG/vetr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vetr + url_git: https://github.com/brodieG/vetr +VetResearchLMM: + version: 1.0.0 + title: |- + Linear Mixed Models - An Introduction with Applications in + Veterinary Research + maintainer: Muhammad Yaseen + description: R Codes and Datasets for Duchateau, L. and Janssen, P. and Rowlands, + G. J. (1998). Linear Mixed Models. An Introduction with applications in Veterinary + Research. International Livestock Research Institute. + date_publication: '2018-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VetResearchLMM + url_git: https://github.com/MYaseen208/VetResearchLMM +VEwaning: + version: '1.3' + title: Vaccine Efficacy Over Time + maintainer: Shannon T. Holloway + description: |- + Implements methods for inference on potential waning of vaccine + efficacy and for estimation of vaccine efficacy at a user-specified time + after vaccination based on data from a randomized, double-blind, + placebo-controlled vaccine trial in which participants may be unblinded + and placebo subjects may be crossed over to the study vaccine. The + methods also allow adjustment for possible confounding via inverse + probability weighting through specification of models for the trial + entry process, unblinding mechanisms, and the probability an unblinded + placebo participant accepts study vaccine: Tsiatis, A. A. and Davidian, + M. (2021) . + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VEwaning + url_git: '' +VEwaningVariant: + version: '1.4' + title: Vaccine Efficacy Over Time - Variant Aware + maintainer: Shannon T. Holloway + description: Implements methods for inference on potential waning of vaccine efficacy + and for estimation of vaccine efficacy at a user-specified time after vaccination + based on data from a randomized, double-blind, placebo-controlled vaccine trial + in which participants may be unblinded and placebo subjects may be crossed over + to the study vaccine. The methods also for variant stratification and allow adjustment + for possible confounding via inverse probability weighting through specification + of models for the trial entry process, unblinding mechanisms, and the probability + an unblinded placebo participant accepts study vaccine. + date_publication: '2023-12-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VEwaningVariant + url_git: '' +vfinputs: + version: 0.1.0 + title: Visual Filter Inputs for Shiny + maintainer: Rafael Henkin + description: A set of visual input controls for Shiny apps to facilitate filtering + across multiple outputs. + date_publication: '2020-10-13' + bug_reports: https://github.com/rhenkin/vfinputs/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vfinputs + url_git: https://github.com/rhenkin/vfinputs +VFP: + version: 1.4.3 + title: Variance Function Program + maintainer: Andre Schuetzenmeister + description: |- + Variance function estimation for models proposed by W. Sadler in his variance function program + ('VFP', www.aacb.asn.au/AACB/Resources/Variance-Function-Program). Here, the idea is + to fit multiple variance functions to a data set and consequently assess which function reflects + the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship + is of great importance when individual test-results are used for defining follow-up treatment of patients. + date_publication: '2025-01-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VFP + url_git: '' +vfprogression: + version: 0.7.1 + title: Visual Field (VF) Progression Analysis and Plotting Methods + maintainer: Dian Li + description: Realization of published methods to analyze visual field (VF) progression. + Introduction to the plotting methods (designed by author TE) for VF output visualization. + A sample dataset for two eyes, each with 10 follow-ups is included. The VF analysis + methods could be found in -- Musch et al. (1999) , + Nouri-Mahdavi et at. (2012) , Schell et at. (2014) , + Aptel et al. (2015) . + date_publication: '2019-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vfprogression + url_git: '' +VFS: + version: 1.0.2 + title: Vegetated Filter Strip and Erosion Model + maintainer: Sarah Goslee + description: |- + Empirical models for runoff, erosion, and phosphorus loss + across a vegetated filter strip, given slope, soils, climate, and + vegetation (Gall et al., 2018) . + It also includes functions for deriving climate parameters from + measured daily weather data, and for simulating rainfall. Models + implemented include MUSLE (Williams, 1975) and APLE (Vadas et al., + 2009 ). + date_publication: '2018-10-12' + bug_reports: https://github.com/sgoslee/VFS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VFS + url_git: '' +VGAM: + version: 1.1-13 + title: Vector Generalized Linear and Additive Models + maintainer: Thomas Yee + description: |- + An implementation of about 6 major classes of + statistical regression models. The central algorithm is + Fisher scoring and iterative reweighted least squares. + At the heart of this package are the vector generalized linear + and additive model (VGLM/VGAM) classes. VGLMs can be loosely + thought of as multivariate GLMs. VGAMs are data-driven + VGLMs that use smoothing. The book "Vector Generalized + Linear and Additive Models: With an Implementation in R" + (Yee, 2015) gives details of + the statistical framework and the package. Currently only + fixed-effects models are implemented. Many (100+) models and + distributions are estimated by maximum likelihood estimation + (MLE) or penalized MLE. The other classes are RR-VGLMs + (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained + RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs, + RCIMs (row-column interaction models)---these classes perform + constrained and unconstrained quadratic ordination (CQO/UQO) + models in ecology, as well as constrained additive ordination + (CAO). Hauck-Donner effect detection is implemented. + Note that these functions are subject to change; + see the NEWS and ChangeLog files for latest changes. + date_publication: '2025-02-12' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~yee/VGAM/ + url_cran: https://CRAN.R-project.org/package=VGAM + url_git: '' +VGAMdata: + version: 1.1-13 + title: Data Supporting the 'VGAM' Package + maintainer: Thomas Yee + description: |- + Mainly data sets to accompany the VGAM package and + the book "Vector Generalized Linear and + Additive Models: With an Implementation in R" (Yee, 2015) + . + These are used to illustrate vector generalized + linear and additive models (VGLMs/VGAMs), and associated models + (Reduced-Rank VGLMs, Quadratic RR-VGLMs, Row-Column + Interaction Models, and constrained and unconstrained ordination + models in ecology). This package now contains some + old VGAM family functions which have been replaced by newer + ones (often because they are now special cases). + date_publication: '2025-02-06' + bug_reports: '' + url: https://www.stat.auckland.ac.nz/~yee/VGAMdata/ + url_cran: https://CRAN.R-project.org/package=VGAMdata + url_git: '' +VGAMextra: + version: 0.0-7 + title: Additions and Extensions of the 'VGAM' Package + maintainer: Victor Miranda + description: |- + Extending the functionalities of the 'VGAM' package with + additional functions and datasets. At present, 'VGAMextra' + comprises new family functions (ffs) to estimate several time + series models by maximum likelihood using Fisher scoring, + unlike popular packages in CRAN relying on optim(), including + ARMA-GARCH-like models, the Order-(p, d, q) ARIMAX model (non- + seasonal), the Order-(p) VAR model, error correction models + for cointegrated time series, and ARMA-structures with Student-t + errors. For independent data, new ffs to estimate the inverse- + Weibull, the inverse-gamma, the generalized beta of the second + kind and the general multivariate normal distributions are + available. In addition, 'VGAMextra' incorporates new VGLM-links + for the mean-function, and the quantile-function (as an alternative + to ordinary quantile modelling) of several 1-parameter distributions, + that are compatible with the class of VGLM/VGAM family functions. + Currently, only fixed-effects models are implemented. All functions + are subject to change; see the NEWS for further details on the + latest changes. + date_publication: '2025-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VGAMextra + url_git: '' +vglmer: + version: 1.0.6 + title: Variational Inference for Hierarchical Generalized Linear Models + maintainer: Max Goplerud + description: |- + Estimates hierarchical models using variational inference. + At present, it can estimate logistic, linear, and negative binomial models. + It can accommodate models with an arbitrary number of random effects and + requires no integration to estimate. It also provides the ability to improve + the quality of the approximation using marginal augmentation. + Goplerud (2022) and Goplerud (2024) + provide details on the variational algorithms. + date_publication: '2024-11-07' + bug_reports: https://github.com/mgoplerud/vglmer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vglmer + url_git: https://github.com/mgoplerud/vglmer +vhcub: + version: 1.0.0 + title: Virus-Host Codon Usage Co-Adaptation Analysis + maintainer: Ali Mostafa Anwar + description: 'Analyze the co-adaptation of codon usage between a virus and its host, + calculate various codon usage bias measurements as: effective number of codons + (ENc) Novembre (2002) , codon adaptation + index (CAI) Sharp and Li (1987) , relative codon + deoptimization index (RCDI) Puigbò et al (2010) , + similarity index (SiD) Zhou et al (2013) , synonymous + codon usage orderliness (SCUO) Wan et al (2004) and, + relative synonymous codon usage (RSCU) Sharp et al (1986) . + Also, it provides a statistical dinucleotide over- and underrepresentation with + three different models. Implement several methods for visualization of codon usage + as ENc.GC3plot() and PR2.plot().' + date_publication: '2019-11-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vhcub + url_git: '' +vhica: + version: 0.2.8 + title: Vertical and Horizontal Inheritance Consistence Analysis + maintainer: Arnaud Le Rouzic + description: 'The "Vertical and Horizontal Inheritance Consistence Analysis" method + is described in the following publication: "VHICA: a new method to discriminate + between vertical and horizontal transposon transfer: application to the mariner + family within Drosophila" by G. Wallau. et al. (2016) . + The purpose of the method is to detect horizontal transfers of transposable elements, + by contrasting the divergence of transposable element sequences with that of regular + genes.' + date_publication: '2023-03-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vhica + url_git: '' +via: + version: 0.2.0 + title: Virtual Arrays + maintainer: Adam T. Kocsis + description: The base class 'VirtualArray' is defined, which acts as a wrapper around + lists allowing users to fold arbitrary sequential data into n-dimensional, R-style + virtual arrays. The derived 'XArray' class is defined to be used for homogeneous + lists that contain a single class of objects. The 'RasterArray' and 'SfArray' + classes enable the use of stacked spatial data instead of lists. + date_publication: '2023-05-16' + bug_reports: https://github.com/adamkocsis/via + url: '' + url_cran: https://CRAN.R-project.org/package=via + url_git: '' +viafoundry: + version: 1.0.0 + title: R Client for 'Via Foundry' API + maintainer: Alper Kucukural + description: '''Via Foundry'' API provides streamlined tools for interacting with + and extracting data from structured responses, particularly for use cases involving + hierarchical data from Foundry''s API. It includes functions to fetch and parse + process-level and file-level metadata, allowing users to efficiently query and + manipulate nested data structures. Key features include the ability to list all + unique process names, retrieve file metadata for specific or all processes, and + dynamically load or download files based on their type. With built-in support + for handling various file formats (e.g., tabular and non-tabular files) and seamless + integration with API through authentication, this package is designed to enhance + workflows involving large-scale data management and analysis. Robust error handling + and flexible configuration ensure reliable performance across diverse data environments. + Please consult the documentation for the API endpoint for your installation.' + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=viafoundry + url_git: https://github.com/ViaScientific/viafoundry-R-SDK +viafr: + version: 0.3.2 + title: |- + Interface to the 'VIAF' ('Virtual International Authority File') + API + maintainer: Stefanie Schneider + description: Provides direct access to linked names for the same entity across the + world's major name authority files, including national and regional variations + in language, character set, and spelling. For more information go to . + date_publication: '2025-01-27' + bug_reports: https://github.com/stefanieschneider/viafr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=viafr + url_git: https://github.com/stefanieschneider/viafr +VIC5: + version: 0.2.6 + title: The Variable Infiltration Capacity (VIC) Hydrological Model + maintainer: Dongdong Kong + description: |- + The Variable Infiltration Capacity (VIC) model is a macroscale + hydrologic model that solves full water and energy balances, originally + developed by Xu Liang at the University of Washington (UW). + The version of VIC source code used is of 5.0.1 on , + see Hamman et al. (2018). + Development and maintenance of the current official version + of the VIC model at present is led by the UW Hydro (Computational Hydrology + group) in the Department of Civil and Environmental Engineering at UW. VIC is + a research model and in its various forms it has been applied to most of the + major river basins around the world, as well as globally + . + References: "Liang, X., D. P. Lettenmaier, E. F. Wood, and + S. J. Burges (1994), A simple hydrologically based model of land surface water + and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), + 14415-14428, "; + "Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The + Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements + for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, + ". + date_publication: '2023-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VIC5 + url_git: https://github.com/rpkgs/VIC5 +VICatMix: + version: '1.0' + title: Variational Mixture Models for Clustering Categorical Data + maintainer: Jackie Rao + description: A variational Bayesian finite mixture model for the clustering of categorical + data, and can implement variable selection and semi-supervised outcome guiding + if desired. Incorporates an option to perform model averaging over multiple initialisations + to reduce the effects of local optima and improve the automatic estimation of + the true number of clusters. For further details, see the paper by Rao and Kirk + (2024) . + date_publication: '2024-11-27' + bug_reports: https://github.com/j-ackierao/VICatMix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VICatMix + url_git: https://github.com/j-ackierao/VICatMix +vICC: + version: 1.0.0 + title: Varying Intraclass Correlation Coefficients + maintainer: Donald Williams + description: |- + Compute group-specific intraclass correlation coefficients, + Bayesian testing of homogenous within-group variance, and spike-and-slab + model selection to determine which groups share a common within-group + variance in a one-way random effects model <10.31234/osf.io/hpq7w>. + date_publication: '2020-12-08' + bug_reports: https://github.com/donaldRwilliams/vICC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vICC + url_git: '' +vici: + version: 0.7.3 + title: Vaccine Induced Cellular Immunogenicity with Bivariate Modeling + maintainer: Boris Hejblum + description: |- + A shiny app for accurate estimation of vaccine induced immunogenicity + with bivariate linear modeling. Method is detailed in: Lhomme, Hejblum, Lacabaratz, + Wiedemann, Lelievre, Levy, Thiebaut & Richert (2020). Journal of Immunological Methods, + 477:112711. . + date_publication: '2024-02-02' + bug_reports: https://github.com/sistm/vici/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vici + url_git: '' +VicmapR: + version: 0.2.3 + title: Access Victorian Spatial Data Through Web File Services (WFS) + maintainer: Justin Cally + description: |- + Easily interfaces R to spatial datasets available through + the Victorian Government's WFS (Web Feature Service): , + which allows users to read in 'sf' data from these sources. VicmapR uses the lazy querying approach and code developed by Teucher et al. (2021) for the 'bcdata' R package . + date_publication: '2023-06-20' + bug_reports: https://github.com/justincally/VicmapR/issues + url: https://justincally.github.io/VicmapR/ + url_cran: https://CRAN.R-project.org/package=VicmapR + url_git: https://github.com/justincally/VicmapR/ +Vicus: + version: 0.99.0 + title: |- + Exploiting Local Structures to Improve Network-Based Analysis of + Biological Data + maintainer: Koki Tsuyuzaki + description: Compared with the similar graph embedding method such as Laplacian + Eigenmaps, 'Vicus' can exploit more local structures of graph data. For the details + of the methods, see the reference section of 'GitHub' README.md . + date_publication: '2023-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Vicus + url_git: https://github.com/rikenbit/Vicus +video: + version: 0.1.1 + title: '''Shiny'' Extension of ''video.js''' + maintainer: Ashley Baldry + description: |- + Video interactivity within 'shiny' applications using 'video.js'. Enables + the status of the video to be sent from the UI to the server, and allows events + such as playing and pausing the video to be triggered from the server. + date_publication: '2023-02-02' + bug_reports: https://github.com/ashbaldry/video/issues + url: '' + url_cran: https://CRAN.R-project.org/package=video + url_git: https://github.com/ashbaldry/video +vietnamcode: + version: 0.1.1 + title: Convert Vietnam Provincial Codes + maintainer: Anh Le + description: |- + Converts Vietnam's provinces' names and ID + across different formats. Handles diacritics and different spellings. + date_publication: '2016-07-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vietnamcode + url_git: '' +vietnameseConverter: + version: 0.4.0 + title: Convert Vietnamese Encodings + maintainer: Juergen Niedballa + description: Conversion of characters from unsupported Vietnamese character encodings + to Unicode characters. These Vietnamese encodings (TCVN3, VISCII, VPS) are not + natively supported in R and lead to printing of wrong characters and garbled text + (mojibake). This package fixes that problem and provides readable output with + the correct Unicode characters (with or without diacritics). + date_publication: '2021-10-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vietnameseConverter + url_git: https://github.com/jniedballa/vietnameseConverter +ViewPipeSteps: + version: 0.1.0 + title: Create View Tabs of Pipe Chains + maintainer: David Ranzolin + description: |- + Debugging pipe chains often consists of viewing the output after + each step. This package adds RStudio addins and two functions that allow + outputing each or select steps in a convenient way. + date_publication: '2021-12-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ViewPipeSteps + url_git: '' +viewpoly: + version: 0.4.1 + title: |- + A Shiny App to Visualize Genetic Maps and QTL Analysis in + Polyploid Species + maintainer: Cristiane Taniguti + description: |- + Provides a graphical user interface to integrate, visualize and explore results + from linkage and quantitative trait loci analysis, together with genomic information for autopolyploid + species. The app is meant for interactive use and allows users to optionally upload different sources + of information, including gene annotation and alignment files, enabling the exploitation and search for + candidate genes in a genome browser. In its current version, 'VIEWpoly' supports inputs from 'MAPpoly', + 'polymapR', 'diaQTL', 'QTLpoly', 'polyqtlR', 'GWASpoly', and 'HIDECAN' packages. + date_publication: '2024-03-28' + bug_reports: https://github.com/mmollina/viewpoly/issues + url: '' + url_cran: https://CRAN.R-project.org/package=viewpoly + url_git: https://github.com/mmollina/viewpoly +viewscape: + version: 2.0.2 + title: Viewscape Analysis + maintainer: Xiaohao Yang + description: |- + A collection of functions to make R a more effective viewscape analysis + tool for calculating viewscape metrics based on computing the viewable area for + given a point/multiple viewpoints and a digital elevation model.The method of calculating + viewscape metrics implemented in this package are based on the work of + Tabrizian et al. (2020) . The algorithm of computing + viewshed is based on the work of + Franklin & Ray. (1994) . + date_publication: '2024-12-19' + bug_reports: https://github.com/land-info-lab/viewscape/issues + url: '' + url_cran: https://CRAN.R-project.org/package=viewscape + url_git: https://github.com/land-info-lab/viewscape +vigicaen: + version: 0.15.5 + title: '''VigiBase'' Pharmacovigilance Database Toolbox' + maintainer: Charles Dolladille + description: |- + Perform the analysis of the World Health Organization + (WHO) Pharmacovigilance database 'VigiBase' (Extract Case Level version), + + e.g., load data, perform data management, + disproportionality analysis, and descriptive statistics. Intended for + pharmacovigilance routine use or studies. + This package is NOT supported nor reflect the opinion of the WHO, or the + Uppsala Monitoring Centre. + Disproportionality methods are described by Norén et + al (2013) . + date_publication: '2025-02-21' + bug_reports: https://github.com/pharmacologie-caen/vigicaen/issues + url: https://pharmacologie-caen.github.io/vigicaen/ + url_cran: https://CRAN.R-project.org/package=vigicaen + url_git: https://github.com/pharmacologie-caen/vigicaen +VIGoR: + version: 1.1.5 + title: Variational Bayesian Inference for Genome-Wide Regression + maintainer: Akio Onogi + description: Conducts linear regression using variational Bayesian inference, particularly + optimized for genome-wide association mapping and whole-genome prediction which + use a number of DNA markers as the explanatory variables. Provides seven regression + models which select the important variables (i.e., the variables related to response + variables) among the given explanatory variables in different ways (i.e., model + structures). + date_publication: '2024-09-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VIGoR + url_git: '' +viking: + version: 1.0.2 + title: State-Space Models Inference by Kalman or Viking + maintainer: Joseph de Vilmarest + description: Inference methods for state-space models, relying on the Kalman Filter + or on Viking (Variational Bayesian VarIance tracKING). See J. de Vilmarest (2022) + . + date_publication: '2023-10-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=viking + url_git: '' +villager: + version: 2.0.0 + title: A Framework for Designing and Running Agent Based Models + maintainer: Thomas Thelen + description: This is a package for creating and running Agent Based Models (ABM). + It provides a set of base classes with core functionality to allow bootstrapped + models. For more intensive modeling, the supplied classes can be extended to fit + researcher needs. + date_publication: '2024-05-25' + bug_reports: https://github.com/zizroc/villager/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=villager + url_git: https://github.com/zizroc/villager/ +VIM: + version: 6.2.2 + title: Visualization and Imputation of Missing Values + maintainer: Matthias Templ + description: |- + New tools for the visualization of missing and/or imputed values + are introduced, which can be used for exploring the data and the structure of + the missing and/or imputed values. Depending on this structure of the missing + values, the corresponding methods may help to identify the mechanism generating + the missing values and allows to explore the data including missing values. + In addition, the quality of imputation can be visually explored using various + univariate, bivariate, multiple and multivariate plot methods. A graphical user + interface available in the separate package VIMGUI allows an easy handling of + the implemented plot methods. + date_publication: '2022-08-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VIM + url_git: https://github.com/statistikat/VIM +VIMean: + version: 0.1.0 + title: Variability Independent of Mean + maintainer: Zhicheng Du + description: |- + To computed the variability independent of mean (VIM) or variation + independent of mean (VIM). The methodology can be found at + Peter M Rothwell et al. (2010) . + date_publication: '2022-11-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VIMean + url_git: '' +vimp: + version: 2.3.3 + title: Perform Inference on Algorithm-Agnostic Variable Importance + maintainer: Brian D. Williamson + description: |- + Calculate point estimates of and valid confidence intervals for + nonparametric, algorithm-agnostic variable importance measures in high and low dimensions, + using flexible estimators of the underlying regression functions. For more information + about the methods, please see Williamson et al. (Biometrics, 2020), Williamson et al. (JASA, 2021), and Williamson and Feng (ICML, 2020). + date_publication: '2023-08-28' + bug_reports: https://github.com/bdwilliamson/vimp/issues + url: https://bdwilliamson.github.io/vimp/ + url_cran: https://CRAN.R-project.org/package=vimp + url_git: https://github.com/bdwilliamson/vimp +vimpclust: + version: 0.1.0 + title: Variable Importance in Clustering + maintainer: Madalina Olteanu + description: |- + An implementation of methods related to sparse clustering and variable importance + in clustering. The package currently allows to perform sparse k-means clustering with a group + penalty, so that it automatically selects groups of numerical features. It also allows to + perform sparse clustering and variable selection on mixed data (categorical and numerical + features), by preprocessing each categorical feature as a group of numerical features. + Several methods for visualizing and exploring the results are also provided. + M. Chavent, J. Lacaille, A. Mourer and M. Olteanu (2020). + date_publication: '2021-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vimpclust + url_git: '' +VIMPS: + version: '1.0' + title: Calculate Variable Importance with Knock Off Variables + maintainer: Meredith Wallace + description: The variable importance is calculated using knock off variables. Then + output can be provided in numerical and graphical form. Meredith L Wallace (2023) + . + date_publication: '2024-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VIMPS + url_git: '' +vindecodr: + version: 0.1.1 + title: |- + Provides an Interface to the Department of Transportation VIN + Decoder + maintainer: Christopher Burch + description: |- + Provides a programmatic interface in R for the US Department of + Transportation (DOT) National Highway Transportation Safety Administration + (NHTSA) vehicle identification number (VIN) API, located at + . + The API can decode up to 50 vehicle identification numbers in one call, and + provides manufacturer information about the vehicles, including make, model, + model year, and gross vehicle weight rating (GVWR). + date_publication: '2020-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vindecodr + url_git: '' +VineCopula: + version: 2.6.0 + title: Statistical Inference of Vine Copulas + maintainer: Thomas Nagler + description: |- + Provides tools for the statistical analysis of regular vine copula + models, see Aas et al. (2009) and + Dissman et al. (2013) . + The package includes tools for parameter estimation, model selection, + simulation, goodness-of-fit tests, and visualization. Tools for estimation, + selection and exploratory data analysis of bivariate copula models are also + provided. + date_publication: '2024-12-17' + bug_reports: https://github.com/tnagler/VineCopula/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VineCopula + url_git: https://github.com/tnagler/VineCopula +vinereg: + version: 0.11.0 + title: D-Vine Quantile Regression + maintainer: Thomas Nagler + description: |- + Implements D-vine quantile regression models with + parametric or nonparametric pair-copulas. See + Kraus and Czado (2017) and + Schallhorn et al. (2017) . + date_publication: '2025-01-11' + bug_reports: https://github.com/tnagler/vinereg/issues + url: https://tnagler.github.io/vinereg/ + url_cran: https://CRAN.R-project.org/package=vinereg + url_git: '' +violinplotter: + version: 3.0.1 + title: Plotting and Comparing Means with Violin Plots + maintainer: Jefferson Paril + description: Produces violin plots with optional nonparametric (Mann-Whitney test) + and parametric (Tukey's honest significant difference) mean comparison and linear + regression. This package aims to be a simple and quick visualization tool for + comparing means and assessing trends of categorical factors. + date_publication: '2022-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=violinplotter + url_git: '' +vioplot: + version: 0.5.1 + title: Violin Plot + maintainer: S. Thomas Kelly + description: A violin plot is a combination of a box plot and a kernel density plot. + This package allows extensive customisation of violin plots. + date_publication: '2025-02-23' + bug_reports: https://github.com/TomKellyGenetics/vioplot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vioplot + url_git: https://github.com/TomKellyGenetics/vioplot +vip: + version: 0.4.1 + title: Variable Importance Plots + maintainer: Brandon M. Greenwell + description: |- + A general framework for constructing variable importance plots from + various types of machine learning models in R. Aside from some standard model- + specific variable importance measures, this package also provides model- + agnostic approaches that can be applied to any supervised learning algorithm. + These include 1) an efficient permutation-based variable importance measure, + 2) variable importance based on Shapley values (Strumbelj and Kononenko, + 2014) , and 3) the variance-based + approach described in Greenwell et al. (2018) . A + variance-based method for quantifying the relative strength of interaction + effects is also included (see the previous reference for details). + date_publication: '2023-08-21' + bug_reports: https://github.com/koalaverse/vip/issues + url: https://koalaverse.github.io/vip/ + url_cran: https://CRAN.R-project.org/package=vip + url_git: https://github.com/koalaverse/vip/ +vipor: + version: 0.4.7 + title: |- + Plot Categorical Data Using Quasirandom Noise and Density + Estimates + maintainer: Scott Sherrill-Mix + description: |- + Generate a violin point plot, a combination of a violin/histogram + plot and a scatter plot by offsetting points within a category based on their + density using quasirandom noise. + date_publication: '2023-12-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vipor + url_git: '' +viraldomain: + version: 0.0.6 + title: Applicability Domain Methods of Viral Load and CD4 Lymphocytes + maintainer: Juan Pablo Acuña González + description: Provides methods for assessing the applicability domain of models that + predict viral load and CD4 (Cluster of Differentiation 4) lymphocyte counts. These + methods help determine the extent of extrapolation when making predictions. + date_publication: '2024-10-17' + bug_reports: https://github.com/juanv66x/viraldomain/issues + url: '' + url_cran: https://CRAN.R-project.org/package=viraldomain + url_git: https://github.com/juanv66x/viraldomain +viralmodels: + version: 1.3.3 + title: Viral Load and CD4 Lymphocytes Regression Models + maintainer: Juan Pablo Acuña González + description: Provides a comprehensive framework for building, evaluating, and visualizing + regression models for analyzing viral load and CD4 (Cluster of Differentiation + 4) lymphocytes data. It leverages the principles of the tidymodels ecosystem of + Max Kuhn and Hadley Wickham (2020) to offer a user-friendly + experience in model development. This package includes functions for data preprocessing, + feature engineering, model training, tuning, and evaluation, along with visualization + tools to enhance the interpretation of model results. It is specifically designed + for researchers in biostatistics, computational biology, and HIV research who + aim to perform reproducible and rigorous analyses to gain insights into disease + dynamics. The main focus is on improving the understanding of the relationships + between viral load, CD4 lymphocytes, and other relevant covariates to contribute + to HIV research and the visibility of vulnerable seropositive populations. + date_publication: '2025-02-19' + bug_reports: https://github.com/juanv66x/viralmodels/issues + url: '' + url_cran: https://CRAN.R-project.org/package=viralmodels + url_git: https://github.com/juanv66x/viralmodels +viralx: + version: 1.3.0 + title: Explainers for Regression Models in HIV Research + maintainer: Juan Pablo Acuña González + description: A dedicated viral-explainer model tool designed to empower researchers + in the field of HIV research, particularly in viral load and CD4 (Cluster of Differentiation + 4) lymphocytes regression modeling. Drawing inspiration from the 'tidymodels' + framework for rigorous model building of Max Kuhn and Hadley Wickham (2020) , + and the 'DALEXtra' tool for explainability by Przemyslaw Biecek (2020) . + It aims to facilitate interpretable and reproducible research in biostatistics + and computational biology for the benefit of understanding HIV dynamics. + date_publication: '2024-03-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=viralx + url_git: '' +VIRF: + version: 0.1.0 + title: |- + Computation of Volatility Impulse Response Function of + Multivariate Time Series + maintainer: Dr. Ranjit Kumar Paul + description: Computation of volatility impulse response function for multivariate + time series model using algorithm by Jin, Lin and Tamvakis (2012) . + date_publication: '2019-05-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VIRF + url_git: '' +viridis: + version: 0.6.5 + title: Colorblind-Friendly Color Maps for R + maintainer: Simon Garnier + description: |- + Color maps designed to improve graph readability for readers with + common forms of color blindness and/or color vision deficiency. The color + maps are also perceptually-uniform, both in regular form and also when + converted to black-and-white for printing. This package also contains + 'ggplot2' bindings for discrete and continuous color and fill scales. A lean + version of the package called 'viridisLite' that does not include the + 'ggplot2' bindings can be found at + . + date_publication: '2024-01-29' + bug_reports: https://github.com/sjmgarnier/viridis/issues + url: https://sjmgarnier.github.io/viridis/ + url_cran: https://CRAN.R-project.org/package=viridis + url_git: https://github.com/sjmgarnier/viridis/ +viridisLite: + version: 0.4.2 + title: Colorblind-Friendly Color Maps (Lite Version) + maintainer: Simon Garnier + description: |- + Color maps designed to improve graph readability for readers with + common forms of color blindness and/or color vision deficiency. The color + maps are also perceptually-uniform, both in regular form and also when + converted to black-and-white for printing. This is the 'lite' version of the + 'viridis' package that also contains 'ggplot2' bindings for discrete and + continuous color and fill scales and can be found at + . + date_publication: '2023-05-02' + bug_reports: https://github.com/sjmgarnier/viridisLite/issues/ + url: https://sjmgarnier.github.io/viridisLite/ + url_cran: https://CRAN.R-project.org/package=viridisLite + url_git: https://github.com/sjmgarnier/viridisLite/ +virtualPollen: + version: 1.0.1 + title: |- + Simulating Pollen Curves from Virtual Taxa with Different Life + and Niche Traits + maintainer: Blas M. Benito + description: Tools to generate virtual environmental drivers with a given temporal + autocorrelation, and to simulate pollen curves at annual resolution over millennial + time-scales based on these drivers and virtual taxa with different life traits + and niche features. It also provides the means to simulate quasi-realistic pollen-data + conditions by applying simulated accumulation rates and given depth intervals + between consecutive samples. + date_publication: '2022-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=virtualPollen + url_git: https://github.com/BlasBenito/virtualPollen +VirtualPop: + version: 2.0.2 + title: Simulation of Populations by Sampling Waiting-Time Distributions + maintainer: Frans Willekens + description: |- + Constructs a virtual population from fertility and mortality rates for any country, + calendar year and birth cohort in the Human Mortality Database and the Human Fertility Database . Fertility histories are simulated for every individual and their offspring, producing a multi-generation virtual population. + date_publication: '2024-03-18' + bug_reports: https://github.com/willekens/VirtualPop/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VirtualPop + url_git: '' +virtualspecies: + version: '1.6' + title: Generation of Virtual Species Distributions + maintainer: Boris Leroy + description: |- + Provides a framework for generating virtual species distributions, + a procedure increasingly used in ecology to improve species distribution + models. This package integrates the existing methodological approaches + with the objective of generating virtual species distributions with + increased ecological realism. + date_publication: '2023-09-26' + bug_reports: '' + url: https://borisleroy.com/virtualspecies/ + url_cran: https://CRAN.R-project.org/package=virtualspecies + url_git: '' +virtuoso: + version: 0.1.8 + title: Interface to 'Virtuoso' using 'ODBC' + maintainer: Carl Boettiger + description: |- + Provides users with a simple and convenient + mechanism to manage and query a 'Virtuoso' database using the 'DBI' (Data-Base Interface) + compatible 'ODBC' (Open Database Connectivity) interface. + 'Virtuoso' is a high-performance "universal server," which can act + as both a relational database, supporting standard Structured Query + Language ('SQL') queries, while also supporting data following the + Resource Description Framework ('RDF') model for Linked Data. + 'RDF' data can be queried using 'SPARQL' ('SPARQL' Protocol and 'RDF' Query Language) + queries, a graph-based query that supports semantic reasoning. + This allows users to leverage the performance of local or remote 'Virtuoso' servers using + popular 'R' packages such as 'DBI' and 'dplyr', while also providing a + high-performance solution for working with large 'RDF' 'triplestores' from 'R.' + The package also provides helper routines to install, launch, and manage + a 'Virtuoso' server locally on 'Mac', 'Windows' and 'Linux' platforms using + the standard interactive installers from the 'R' command-line. By + automatically handling these setup steps, the package can make using 'Virtuoso' + considerably faster and easier for a most users to deploy in a local + environment. Managing the bulk import of triples + from common serializations with a single intuitive command is another key + feature of this package. Bulk import performance can be tens to + hundreds of times faster than the comparable imports using existing 'R' tools, + including 'rdflib' and 'redland' packages. + date_publication: '2021-11-02' + bug_reports: https://github.com/ropensci/virtuoso/issues + url: '' + url_cran: https://CRAN.R-project.org/package=virtuoso + url_git: https://github.com/ropensci/virtuoso +Virusparies: + version: 1.1.0 + title: Visualize and Process Output from 'VirusHunterGatherer' + maintainer: Ruff Sergej + description: |- + A collection of tools for downstream analysis of + 'VirusHunterGatherer' output. Processing of hittables + and plotting of results, enabling better interpretation, + is made easier with the provided functions. + date_publication: '2024-12-14' + bug_reports: https://github.com/SergejRuff/Virusparies/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Virusparies + url_git: https://github.com/SergejRuff/Virusparies +virustotal: + version: 0.2.2 + title: R Client for the VirusTotal API + maintainer: Gaurav Sood + description: |- + Use VirusTotal, a Google service that analyzes files and URLs + for viruses, worms, trojans etc., provides category of the content hosted by a + domain from a variety of prominent services, provides passive DNS information, + among other things. See for more information. + date_publication: '2021-11-04' + bug_reports: https://github.com/themains/virustotal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=virustotal + url_git: https://github.com/themains/virustotal +visa: + version: 0.1.0 + title: Vegetation Imaging Spectroscopy Analyzer + maintainer: Kang Yu + description: |- + Provides easy-to-use tools for data analysis and visualization for hyperspectral remote sensing (also known as imaging spectroscopy), with + a particular focus on vegetation hyperspectral data analysis. It consists of a set of functions, ranging from the organization of hyperspectral data + in the proper data structure for spectral feature selection, calculation of vegetation index, multivariate analysis, as well as to the visualization + of spectra and results of analysis in the 'ggplot2' style. + date_publication: '2021-04-20' + bug_reports: https://github.com/kang-yu/visa/issues + url: '' + url_cran: https://CRAN.R-project.org/package=visa + url_git: https://github.com/kang-yu/visa +visachartR: + version: 4.0.1 + title: Wrapper for 'Visa Chart Components' + maintainer: Christopher DeMartini + description: |- + Provides a set of wrapper functions for 'Visa Chart Components'. + 'Visa Chart Components' is an accessibility focused, + framework agnostic set of data experience design systems components for the web. + date_publication: '2024-11-16' + bug_reports: https://github.com/visa/visa-chart-components/issues + url: '' + url_cran: https://CRAN.R-project.org/package=visachartR + url_git: https://github.com/visa/visa-chart-components/tree/master/packages/charts-R +visaOTR: + version: 0.1.0 + title: |- + Valid Improved Sparsity A-Learning for Optimal Treatment + Decision + maintainer: Zishu Zhan + description: Valid Improved Sparsity A-Learning (VISA) provides a new method for + selecting important variables involved in optimal treatment regime from a multiply + robust perspective. The VISA estimator achieves its success by borrowing the strengths + of both model averaging (ARM, Yuhong Yang, 2001) + and variable selection (PAL, Chengchun Shi, Ailin Fan, Rui Song and Wenbin Lu, + 2018) . The package is an implementation of Zishu Zhan + and Jingxiao Zhang. (2022+). + date_publication: '2022-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=visaOTR + url_git: '' +VisCollin: + version: 0.1.2 + title: Visualizing Collinearity Diagnostics + maintainer: Michael Friendly + description: |- + Provides methods to calculate diagnostics for multicollinearity among predictors in a linear or + generalized linear model. It also provides methods to visualize those diagnostics following Friendly & Kwan (2009), + "Where’s Waldo: Visualizing Collinearity Diagnostics", . + These include better tabular presentation of collinearity diagnostics that highlight the important numbers, + a semi-graphic tableplot of the diagnostics to make warning and danger levels more salient, + and a "collinearity biplot" of the smallest dimensions of predictor space, where collinearity is most apparent. + date_publication: '2023-09-05' + bug_reports: https://github.com/friendly/VisCollin/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VisCollin + url_git: https://github.com/friendly/VisCollin +viscomp: + version: 1.0.0 + title: Visualize Multi-Component Interventions in Network Meta-Analysis + maintainer: Georgios Seitidis + description: |- + A set of functions providing several visualization tools for exploring the behavior of the components in a network meta-analysis of multi-component (complex) interventions: + - components descriptive analysis + - heat plot of the two-by-two component combinations + - leaving one component combination out scatter plot + - violin plot for specific component combinations' effects + - density plot for components' effects + - waterfall plot for the interventions' effects that differ by a certain component combination + - network graph of components + - rank heat plot of components for multiple outcomes. + The implemented tools are described by Seitidis et al. (2023) . + date_publication: '2023-01-16' + bug_reports: https://github.com/georgiosseitidis/viscomp/issues + url: https://georgiosseitidis.github.io/viscomp/ + url_cran: https://CRAN.R-project.org/package=viscomp + url_git: https://github.com/georgiosseitidis/viscomp +viscomplexr: + version: 1.1.2 + title: Phase Portraits of Functions in the Complex Number Plane + maintainer: Peter Biber + description: |- + Functionality for creating phase portraits of functions in the + complex number plane. Works with R base graphics, whose full + functionality is available. Parallel processing is used for optimum + performance. + date_publication: '2024-11-23' + bug_reports: '' + url: https://peterbiber.github.io/viscomplexr/ + url_cran: https://CRAN.R-project.org/package=viscomplexr + url_git: https://github.com/PeterBiber/viscomplexr/ +VisCov: + version: 1.5.0 + title: Visualizing of Distributions of Covariance Matrices + maintainer: Kristof Meers + description: |- + Visualizing of distributions of covariance matrices. + The package implements the methodology described in Tokuda, T., Goodrich, B., Van Mechelen, I., Gelman, A., & Tuerlinckx, F. (2012) . + date_publication: '2024-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VisCov + url_git: '' +visdat: + version: 0.6.0 + title: Preliminary Visualisation of Data + maintainer: Nicholas Tierney + description: |- + Create preliminary exploratory data visualisations of an entire + dataset to identify problems or unexpected features using 'ggplot2'. + date_publication: '2023-02-02' + bug_reports: https://github.com/ropensci/visdat/issues + url: https://docs.ropensci.org/visdat/ + url_cran: https://CRAN.R-project.org/package=visdat + url_git: https://github.com/ropensci/visdat +ViSe: + version: 0.1.3 + title: Visualizing Sensitivity + maintainer: Erin M. Buchanan + description: Designed to help the user to determine the sensitivity of an proposed + causal effect to unconsidered common causes. Users can create visualizations of + sensitivity, effect sizes, and determine which pattern of effects would support + a causal claim for between group differences. Number needed to treat formula from + Kraemer H.C. & Kupfer D.J. (2006) . + date_publication: '2024-10-10' + bug_reports: '' + url: http://www.aggieerin.com/ViSe/ + url_cran: https://CRAN.R-project.org/package=ViSe + url_git: '' +ViSiElse: + version: 1.2.2 + title: A Visual Tool for Behavior Analysis over Time + maintainer: Elodie Garnier + description: A graphical R package designed to visualize behavioral observations + over time. Based on raw time data extracted from video recorded sessions of experimental + observations, ViSiElse grants a global overview of a process by combining the + visualization of multiple actions timestamps for all participants in a single + graph. Individuals and/or group behavior can easily be assessed. Supplementary + features allow users to further inspect their data by adding summary statistics + (mean, standard deviation, quantile or statistical test) and/or time constraints + to assess the accuracy of the realized actions. + date_publication: '2019-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ViSiElse + url_git: https://github.com/Re2SimLab/ViSiElse +visit: + version: '2.2' + title: |- + Vaccine Phase I Design with Simultaneous Evaluation of + Immunogenicity and Toxicity + maintainer: Chenguang Wang + description: |2- + + Phase I clinical trials are the first step in drug development to test + a new drug or drug combination on humans. Typical designs of Phase I + trials use toxicity as the primary endpoint and aim to find the maximum + tolerable dosage. However, these designs are poorly applicable for the + development of cancer therapeutic vaccines because the expected safety + concerns for these vaccines are not as much as cytotoxic agents. The + primary objectives of a cancer therapeutic vaccine phase I trial thus + often include determining whether the vaccine shows biologic activity + and the minimum dose necessary to achieve a full immune or even clinical + response. This package implements a Bayesian Phase I cancer vaccine + trial design that allows simultaneous evaluation of safety and + immunogenicity outcomes. See Wang et al. (2019) + for further details. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=visit + url_git: '' +VisitorCounts: + version: 2.0.3 + title: Modeling and Forecasting Visitor Counts Using Social Media + maintainer: Robert Bowen + description: |- + Performs modeling and forecasting of park visitor counts + using social media data and (partial) on-site visitor counts. + Specifically, the model is built based on an automatic decomposition + of the trend and seasonal components of the social media-based park visitor counts, + from which short-term forecasts of the visitor counts and percent changes + in the visitor counts can be made. A reference for the underlying model that 'VisitorCounts' uses can be found at + Russell Goebel, Austin Schmaltz, Beth Ann Brackett, Spencer A. Wood, Kimihiro Noguchi (2023) . + date_publication: '2025-01-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VisitorCounts + url_git: '' +vismeteor: + version: 1.8.5 + title: Analysis of Visual Meteor Data + maintainer: Janko Richter + description: |- + Provides a suite of analytical functionalities to process and analyze + visual meteor observations from the Visual Meteor Database + of the International Meteor Organization . + date_publication: '2024-01-16' + bug_reports: https://github.com/jankorichter/vismeteor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vismeteor + url_git: https://github.com/jankorichter/vismeteor +visNetwork: + version: 2.1.2 + title: Network Visualization using 'vis.js' Library + maintainer: Benoit Thieurmel + description: |- + Provides an R interface to the 'vis.js' JavaScript charting + library. It allows an interactive visualization of networks. + date_publication: '2022-09-29' + bug_reports: https://github.com/datastorm-open/visNetwork/issues + url: https://datastorm-open.github.io/visNetwork/ + url_cran: https://CRAN.R-project.org/package=visNetwork + url_git: '' +visOmopResults: + version: 1.0.1 + title: Graphs and Tables for OMOP Results + maintainer: Núria Mercadé-Besora + description: |- + Provides methods to transform omop_result objects into + formatted tables and figures, facilitating the visualisation of study + results working with the Observational Medical Outcomes Partnership + (OMOP) Common Data Model. + date_publication: '2025-02-27' + bug_reports: https://github.com/darwin-eu/visOmopResults/issues + url: https://darwin-eu.github.io/visOmopResults/ + url_cran: https://CRAN.R-project.org/package=visOmopResults + url_git: https://github.com/darwin-eu/visOmopResults +visreg: + version: 2.7.0 + title: Visualization of Regression Models + maintainer: Patrick Breheny + description: Provides a convenient interface for constructing plots to visualize + the fit of regression models arising from a wide variety of models in R ('lm', + 'glm', 'coxph', 'rlm', 'gam', 'locfit', 'lmer', 'randomForest', etc.) + date_publication: '2020-06-04' + bug_reports: '' + url: http://pbreheny.github.io/visreg + url_cran: https://CRAN.R-project.org/package=visreg + url_git: '' +visStatistics: + version: 0.1.1 + title: Automated Visualization of Statistical Tests + maintainer: Sabine Schilling + description: |- + Visualization of the most powerful statistical hypothesis test. + The function vistat() visualizes the statistical hypothesis testing between the + dependent variable (response) varsample and the independent variable (feature) varfactor. + The statistical hypothesis test (including the eventual corresponding post-hoc analysis) with + the highest statistical power fulfilling the assumptions of the corresponding test is chosen based on a decision tree. + A graph displaying the raw data accordingly to the chosen test is generated, the test statistics including eventual + post-hoc-analysis are returned. The automated workflow is especially suited for browser based interfaces to + server-based deployments of R. Implemented tests: lm(), t.test(), wilcox.test(), aov(), kruskal.test(), fisher.test(), chisqu.test(). + Implemented tests to check the normal distribution of standardized residuals: shapiro.test() and ad.test(). + Implemented post-hoc tests: TukeyHSD() for aov() and pairwise.wilcox.test() for kruskal.test(). + For the comparison of averages, the following algorithm is implemented: + If the p-values of the standardized residuals of both shapiro.test() or ad.test() are smaller + than 1-conf.level, kruskal.test() resp. wilcox.test() are performed, otherwise the oneway.test() + and aov() resp. t.test() are performed and displayed. Exception: + If the sample size is bigger than 100, t.test() is always performed and wilcox.test() is never executed + (Lumley et al. (2002) ). + For the test of independence of count data, Cochran's rule (Cochran (1954) ) is implemented: + If more than 20 percent of all cells have a count smaller than 5, fisher.test() is performed and displayed, + otherwise chisqu.test(). In both cases case an additional mosaic plot is generated. + date_publication: '2021-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=visStatistics + url_git: '' +vistime: + version: 1.2.4 + title: Pretty Timelines in R + maintainer: Sandro Raabe + description: |- + A library for creating time based charts, like Gantt or timelines. Possible outputs + include 'ggplot2' diagrams, 'plotly.js' graphs, 'Highcharts.js' widgets and data.frames. Results can be + used in the 'RStudio' viewer pane, in 'RMarkdown' documents or in Shiny apps. In the + interactive outputs created by vistime() and hc_vistime(), you can interact with the + plot using mouse hover or zoom. + date_publication: '2023-10-29' + bug_reports: https://github.com/shosaco/vistime/issues + url: https://shosaco.github.io/vistime/ + url_cran: https://CRAN.R-project.org/package=vistime + url_git: '' +vistla: + version: 2.1.1 + title: Detecting Influence Paths with Information Theory + maintainer: Miron B. Kursa + description: |- + Traces information spread through interactions between features, utilising information theory measures and a higher-order generalisation of the concept of widest paths in graphs. + In particular, 'vistla' can be used to better understand the results of high-throughput biomedical experiments, by organising the effects of the investigated intervention in a tree-like hierarchy from direct to indirect ones, following the plausible information relay circuits. + Due to its higher-order nature, 'vistla' can handle multi-modality and assign multiple roles to a single feature. + date_publication: '2025-02-19' + bug_reports: https://gitlab.com/mbq/vistla/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vistla + url_git: https://gitlab.com/mbq/vistla +visTree: + version: 0.8.1 + title: Visualization of Subgroups for Decision Trees + maintainer: Ashwini Venkatasubramaniam + description: Provides a visualization for characterizing subgroups defined by a + decision tree structure. The visualization simplifies the ability to interpret + individual pathways to subgroups; each sub-plot describes the distribution of + observations within individual terminal nodes and percentile ranges for the associated + inner nodes. + date_publication: '2018-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=visTree + url_git: '' +vistributions: + version: 0.2.0 + title: Visualize Probability Distributions + maintainer: Aravind Hebbali + description: |- + Visualize and compute percentiles/probabilities of normal, t, f, chi square + and binomial distributions. + date_publication: '2024-11-07' + bug_reports: https://github.com/rsquaredacademy/vistributions/issues + url: https://vistributions.rsquaredacademy.com + url_cran: https://CRAN.R-project.org/package=vistributions + url_git: https://github.com/rsquaredacademy/vistributions +VisualDom: + version: 0.8.0 + title: Visualize Dominant Variables in Wavelet Multiple Correlation + maintainer: Josué M. Polanco-Martínez + description: Estimates and plots as a heat map the correlation coefficients obtained + via the wavelet local multiple correlation 'WLMC' (Fernández-Macho 2018) and the + 'dominant' variable/s, i.e., the variable/s that maximizes the multiple correlation + through time and scale (Polanco-Martínez et al. 2020, Polanco-Martínez 2022). + We improve the graphical outputs of WLMC proposing a didactic and useful way to + visualize the 'dominant' variable(s) for a set of time series. The WLMC was designed + for financial time series, but other kinds of data (e.g., climatic, ecological, + etc.) can be used. The functions contained in 'VisualDom' are highly flexible + since these contains several parameters to personalize the time series under analysis + and the heat maps. In addition, we have also included two data sets (named 'rdata_climate' + and 'rdata_Lorenz') to exemplify the use of the functions contained in 'VisualDom'. + Methods derived from Fernández-Macho (2018) , + Polanco-Martínez et al. (2020) and Polanco-Martínez + (2023, in press). + date_publication: '2023-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VisualDom + url_git: '' +visualFields: + version: 1.0.7 + title: Statistical Methods for Visual Fields + maintainer: Ivan Marin-Franch + description: |- + A collection of tools for analyzing the field of vision. It + provides a framework for development and use of innovative methods for + visualization, statistical analysis, and clinical interpretation of + visual-field loss and its change over time. It is intended to be a tool for + collaborative research. The package is described in Marin-Franch and Swanson + (2013) and is part of the Open Perimetry Initiative + (OPI) [Turpin, Artes, and McKendrick (2012) ]. + date_publication: '2025-01-17' + bug_reports: '' + url: https://www.optocom.es + url_cran: https://CRAN.R-project.org/package=visualFields + url_git: '' +visualize: + version: 4.5.0 + title: |- + Graph Probability Distributions with User Supplied Parameters + and Statistics + maintainer: James Balamuta + description: |- + Graphs the pdf or pmf and highlights what area or probability is + present in user defined locations. Visualize is able to provide lower tail, + bounded, upper tail, and two tail calculations. Supports strict and equal + to inequalities. Also provided on the graph is the mean and variance of + the distribution. + date_publication: '2023-11-13' + bug_reports: https://github.com/coatless-rpkg/visualize/issues + url: https://thecoatlessprofessor.com/projects/visualize/ + url_cran: https://CRAN.R-project.org/package=visualize + url_git: https://github.com/coatless-rpkg/visualize +Visualize.CRAN.Downloads: + version: 1.0.3 + title: Visualize Downloads from 'CRAN' Packages + maintainer: Marcelo Ponce + description: Visualize the trends and historical downloads from packages in the + 'CRAN' repository. Data is obtained by using the 'API' to query the database from + the 'RStudio' 'CRAN' mirror. + date_publication: '2023-03-21' + bug_reports: https://github.com/mponce0/Visualize.CRAN.Downloads/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Visualize.CRAN.Downloads + url_git: https://github.com/mponce0/Visualize.CRAN.Downloads +VisualizeSimon2Stage: + version: 0.1.6 + title: Visualize Simon's Two-Stage Design + maintainer: Tingting Zhan + description: |- + To visualize the probabilities of early + termination, fail and success of Simon's two-stage + design. To evaluate and visualize the operating + characteristics of Simon's two-stage design. + date_publication: '2024-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VisualizeSimon2Stage + url_git: '' +visualpred: + version: 0.1.1 + title: Visualization 2D of Binary Classification Models + maintainer: Javier Portela + description: Visual contour and 2D point and contour plots for binary classification + modeling under algorithms such as 'glm', 'rf', 'gbm', 'nnet' and 'svm', presented + over two dimensions generated by 'famd' and 'mca' methods. Package 'FactoMineR' + for multivariate reduction functions and package 'MBA' for interpolation functions + are used. The package can be used to visualize the discriminant power of input + variables and algorithmic modeling, explore outliers, compare algorithm behaviour, + etc. It has been created initially for teaching purposes, but it has also many + practical uses under the 'XAI' paradigm. + date_publication: '2024-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=visualpred + url_git: '' +visvaR: + version: 1.0.0 + title: Shiny-Based Statistical Solutions for Agricultural Research + maintainer: Ramesh Ramasamy + description: Visualize Variance is an intuitive 'shiny' applications tailored for + agricultural research data analysis, including one-way and two-way analysis of + variance, correlation, and other essential statistical tools. Users can easily + upload their datasets, perform analyses, and download the results as a well-formatted + document, streamlining the process of data analysis and reporting in agricultural + research.The experimental design methods are based on classical work by Fisher + (1925) and Scheffe (1959). The correlation visualization approaches follow methods + developed by Wei & Simko (2021) and Friendly (2002) . + date_publication: '2024-11-14' + bug_reports: https://github.com/rameshram96/visvaR/issues + url: https://rameshram96.github.io/visvaR/ + url_cran: https://CRAN.R-project.org/package=visvaR + url_git: https://github.com/rameshram96/visvaR +visvow: + version: 1.3.11 + title: 'Visible Vowels: Visualization of Vowel Variation' + maintainer: Wilbert Heeringa + description: Visualizes vowel variation in f0, F1, F2, F3 and duration. + date_publication: '2024-01-31' + bug_reports: '' + url: https://www.visiblevowels.org/ + url_cran: https://CRAN.R-project.org/package=visvow + url_git: '' +visxhclust: + version: 1.1.0 + title: A Shiny App for Visual Exploration of Hierarchical Clustering + maintainer: Rafael Henkin + description: A Shiny application and functions for visual exploration of hierarchical + clustering with numeric datasets. Allows users to iterative set hyperparameters, + select features and evaluate results through various plots and computation of + evaluation criteria. + date_publication: '2023-03-17' + bug_reports: https://github.com/rhenkin/visxhclust/issues + url: '' + url_cran: https://CRAN.R-project.org/package=visxhclust + url_git: https://github.com/rhenkin/visxhclust +vita: + version: 1.0.0 + title: Variable Importance Testing Approaches + maintainer: Ender Celik + description: |- + Implements the novel testing approach by Janitza et al.(2015) + + for the permutation variable importance measure in a random forest and the + PIMP-algorithm by Altmann et al.(2010) . + Janitza et al.(2015) + do not use the "standard" permutation variable + importance but the cross-validated permutation variable + importance for the novel test approach. The cross-validated + permutation variable importance is not based on the out-of-bag + observations but uses a similar strategy which is inspired by + the cross-validation procedure. The novel test approach can be + applied for classification trees as well as for regression + trees. However, the use of the novel testing approach has not + been tested for regression trees so far, so this routine is + meant for the expert user only and its current state is rather + experimental. + date_publication: '2015-12-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vita + url_git: '' +vitae: + version: 0.6.0 + title: Curriculum Vitae for R Markdown + maintainer: Mitchell O'Hara-Wild + description: Provides templates and functions to simplify the production and maintenance + of curriculum vitae. + date_publication: '2024-06-12' + bug_reports: https://github.com/mitchelloharawild/vitae/issues + url: https://pkg.mitchelloharawild.com/vitae/ + url_cran: https://CRAN.R-project.org/package=vitae + url_git: https://github.com/mitchelloharawild/vitae +vital: + version: 1.1.0 + title: |- + Tidy Analysis Tools for Mortality, Fertility, Migration and + Population Data + maintainer: Rob Hyndman + description: |- + Analysing vital statistics based on tools + consistent with the tidyverse. Tools are provided for data visualization, + lifetable calculations, computing net migration numbers, Lee-Carter + modelling; functional data modelling and forecasting. + date_publication: '2024-06-21' + bug_reports: https://github.com/robjhyndman/vital/issues + url: https://pkg.robjhyndman.com/vital/ + url_cran: https://CRAN.R-project.org/package=vital + url_git: https://github.com/robjhyndman/vital +vitality: + version: '1.3' + title: Fitting Routines for the Vitality Family of Mortality Models + maintainer: David J. Sharrow + description: |- + Provides fitting routines for four versions of the + Vitality family of mortality models. + date_publication: '2018-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vitality + url_git: '' +vivainsights: + version: 0.6.0 + title: Analyze and Visualize Data from 'Microsoft Viva Insights' + maintainer: Martin Chan + description: Provides a versatile range of functions, including exploratory data + analysis, time-series analysis, organizational network analysis, and data validation, + whilst at the same time implements a set of best practices in analyzing and visualizing + data specific to 'Microsoft Viva Insights'. + date_publication: '2025-02-20' + bug_reports: https://github.com/microsoft/vivainsights/issues/ + url: https://microsoft.github.io/vivainsights/ + url_cran: https://CRAN.R-project.org/package=vivainsights + url_git: '' +vivaldi: + version: 1.0.1 + title: Viral Variant Location and Diversity + maintainer: David Gresham + description: |- + Analysis of minor alleles in Illumina sequencing data of viral + genomes. Functions in 'vivaldi' primarily operate on vcf files. + date_publication: '2023-03-21' + bug_reports: https://github.com/GreshamLab/vivaldi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vivaldi + url_git: https://github.com/GreshamLab/vivaldi +vivid: + version: 0.2.9 + title: Variable Importance and Variable Interaction Displays + maintainer: Alan Inglis + description: A suite of plots for displaying variable importance and two-way variable + interaction jointly. Can also display partial dependence plots laid out in a pairs + plot or 'zenplots' style. + date_publication: '2024-07-31' + bug_reports: '' + url: https://alaninglis.github.io/vivid/ + url_cran: https://CRAN.R-project.org/package=vivid + url_git: '' +vivo: + version: 0.2.1 + title: Variable Importance via Oscillations + maintainer: Anna Kozak + description: |- + Provides an easy to calculate local variable importance measure based on Ceteris Paribus profile + and global variable importance measure based on Partial Dependence Profiles. + date_publication: '2020-09-07' + bug_reports: https://github.com/ModelOriented/vivo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vivo + url_git: https://github.com/ModelOriented/vivo +vizdraws: + version: 2.0.0 + title: Visualize Draws from the Prior and Posterior Distributions + maintainer: Ignacio Martinez + description: |- + Interactive visualization for Bayesian prior and posterior distributions. + This package facilitates an animated transition between prior and posterior distributions. + Additionally, it splits the distribution into bars based on the provided 'breaks,' displaying + the probability for each region. If no 'breaks' are provided, it defaults to zero. + date_publication: '2024-01-11' + bug_reports: https://github.com/ignacio82/vizdraws/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vizdraws + url_git: https://github.com/ignacio82/vizdraws/https://vizdraws.martinez.fyi/ +vkR: + version: '0.2' + title: Access to VK API via R + maintainer: Dmitriy Sorokin + description: |- + Provides an interface to the VK API . + VK is the largest European online social networking + service, based in Russia. + date_publication: '2020-09-29' + bug_reports: https://github.com/Dementiy/vkR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vkR + url_git: https://github.com/Dementiy/vkR +VLF: + version: '1.1' + title: |- + Frequency Matrix Approach for Assessing Very Low Frequency + Variants in Sequence Records + maintainer: Taryn B. T. Athey + description: Using frequency matrices, very low frequency variants (VLFs) are assessed + for amino acid and nucleotide sequences. The VLFs are then compared to see if + they occur in only one member of a species, singleton VLFs, or if they occur in + multiple members of a species, shared VLFs. The amino acid and nucleotide VLFs + are then compared to see if they are concordant with one another. Amino acid + VLFs are also assessed to determine if they lead to a change in amino acid residue + type, and potential changes to protein structures. Based on Stoeckle and Kerr + (2012) . + date_publication: '2022-08-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VLF + url_git: '' +VLMC: + version: 1.4-4 + title: Variable Length Markov Chains ('VLMC') Models + maintainer: Martin Maechler + description: |- + Functions, Classes & Methods for estimation, prediction, and + simulation (bootstrap) of Variable Length Markov Chain ('VLMC') Models. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VLMC + url_git: '' +VLMCX: + version: '1.0' + title: Variable Length Markov Chain with Exogenous Covariates + maintainer: Adriano Zanin Zambom Developer + description: Models categorical time series through a Markov Chain when a) covariates + are predictors for transitioning into the next state/symbol and b) when the dependence + in the past states has variable length. The probability of transitioning to the + next state in the Markov Chain is defined by a multinomial regression whose parameters + depend on the past states of the chain and, moreover, the number of states in + the past needed to predict the next state also depends on the observed states + themselves. See Zambom, Kim, and Garcia (2022) . + date_publication: '2024-02-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VLMCX + url_git: '' +VLTimeCausality: + version: 0.1.5 + title: Variable-Lag Time Series Causality Inference Framework + maintainer: Chainarong Amornbunchornvej + description: A framework to infer causality on a pair of time series of real numbers + based on variable-lag Granger causality and transfer entropy. Typically, Granger + causality and transfer entropy have an assumption of a fixed and constant time + delay between the cause and effect. However, for a non-stationary time series, + this assumption is not true. For example, considering two time series of velocity + of person A and person B where B follows A. At some time, B stops tying his shoes, + then running to catch up A. The fixed-lag assumption is not true in this case. + We propose a framework that allows variable-lags between cause and effect in Granger + causality and transfer entropy to allow them to deal with variable-lag non-stationary + time series. Please see Chainarong Amornbunchornvej, Elena Zheleva, and Tanya + Berger-Wolf (2021) when referring to this package in publications. + date_publication: '2024-05-28' + bug_reports: https://github.com/DarkEyes/VLTimeSeriesCausality/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VLTimeCausality + url_git: https://github.com/DarkEyes/VLTimeSeriesCausality +VMDecomp: + version: 1.0.1 + title: Variational Mode Decomposition + maintainer: Lampros Mouselimis + description: '''RcppArmadillo'' implementation for the Matlab code of the ''Variational + Mode Decomposition'' and ''Two-Dimensional Variational Mode Decomposition''. For + more information, see (i) ''Variational Mode Decomposition'' by K. Dragomiretskiy + and D. Zosso in IEEE Transactions on Signal Processing, vol. 62, no. 3, pp. 531-544, + Feb.1, 2014, ; (ii) ''Two-Dimensional Variational + Mode Decomposition'' by Dragomiretskiy, K., Zosso, D. (2015), In: Tai, XC., Bae, + E., Chan, T.F., Lysaker, M. (eds) Energy Minimization Methods in Computer Vision + and Pattern Recognition. EMMCVPR 2015. Lecture Notes in Computer Science, vol + 8932. Springer, .' + date_publication: '2022-07-04' + bug_reports: https://github.com/mlampros/VMDecomp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VMDecomp + url_git: https://github.com/mlampros/VMDecomp +VMDML: + version: 0.1.1 + title: Variational Mode Decomposition Based Machine Learning Models + maintainer: Pankaj Das + description: Application of Variational Mode Decomposition based different Machine + Learning models for univariate time series forecasting. For method details see + (i) K. Dragomiretskiy and D. Zosso (2014) ; (ii) Pankaj + Das (2020) . + date_publication: '2023-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VMDML + url_git: '' +vmdTDNN: + version: 0.1.1 + title: VMD Based Time Delay Neural Network Model + maintainer: Kapil Choudhary + description: Forecasting univariate time series with Variational Mode Decomposition + (VMD) based time delay neural network models.For method details see Konstantin, + D.and Dominique, Z. (2014). . + date_publication: '2022-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vmdTDNN + url_git: '' +vmeasur: + version: 0.1.4 + title: |- + Quantify the Contractile Nature of Vessels Monitored under an + Operating Microscope + maintainer: James JW Hucklesby + description: |- + A variety of tools to allow the quantification of videos of the + lymphatic vasculature taken under an operating microscope. Lymphatic vessels + that have been injected with a variety of blue dyes can be tracked throughout + the video to determine their width over time. Code is optimised + for efficient processing of multiple large video files. Functions to calculate + physiologically relevant parameters and generate graphs from these values + are also included. + date_publication: '2021-11-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vmeasur + url_git: '' +vMF: + version: 0.0.3 + title: Sampling from the von Mises-Fisher Distribution + maintainer: Aristide Houndetoungan + description: Provides fast sampling from von Mises-Fisher distribution using the + method proposed by Andrew T.A Wood (1994) . + date_publication: '2024-03-09' + bug_reports: https://github.com/ahoundetoungan/vMF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vMF + url_git: https://github.com/ahoundetoungan/vMF +vmr: + version: 0.0.6 + title: Virtual Machines for R + maintainer: Jean-François Rey + description: |- + Manage, provision and use Virtual Machines pre-configured for R. + Develop, test and build package in a clean environment. + 'Vagrant' tool and a provider (such as 'Virtualbox') have to be installed. + date_publication: '2023-03-07' + bug_reports: https://gitlab.com/rstuff/vmr/-/issues + url: https://rstuff.gitlab.io/vmr + url_cran: https://CRAN.R-project.org/package=vmr + url_git: https://gitlab.com/rstuff/vmr +vntrs: + version: 0.1.1 + title: Variable Neighborhood Trust Region Search + maintainer: Lennart Oelschläger + description: |- + An implementation of the variable neighborhood trust region + algorithm Bierlaire et al. (2009) "A Heuristic for Nonlinear Global + Optimization" . + date_publication: '2023-12-21' + bug_reports: '' + url: https://loelschlaeger.de/vntrs/ + url_cran: https://CRAN.R-project.org/package=vntrs + url_git: '' +vocaldia: + version: 0.8.4 + title: Create and Manipulate Vocalisation Diagrams + maintainer: Saturnino Luz + description: |- + Create adjacency matrices of vocalisation graphs from + dataframes containing sequences of speech and silence intervals, + transforming these matrices into Markov diagrams, and generating + datasets for classification of these diagrams by 'flattening' them + and adding global properties (functionals) etc. Vocalisation + diagrams date back to early work in psychiatry (Jaffe and Feldstein, + 1970) and social psychology (Dabbs and Ruback, 1987) but have only + recently been employed as a data representation method for machine + learning tasks including meeting segmentation (Luz, 2012) + and classification (Luz, + 2013) . + date_publication: '2022-08-14' + bug_reports: https://git.ecdf.ed.ac.uk/sluzfil/vocaldia/-issues + url: https://git.ecdf.ed.ac.uk/sluzfil/vocaldia + url_cran: https://CRAN.R-project.org/package=vocaldia + url_git: '' +voi: + version: 1.0.3 + title: Expected Value of Information + maintainer: Christopher Jackson + description: Methods to calculate the expected value of information from a decision-analytic + model. This includes the expected value of perfect information (EVPI), partial + perfect information (EVPPI) and sample information (EVSI), and the expected net + benefit of sampling (ENBS). A range of alternative computational methods are + provided under the same user interface. See Heath et al. (2024) , + Jackson et al. (2022) . + date_publication: '2024-09-16' + bug_reports: https://github.com/chjackson/voi/issues + url: https://chjackson.github.io/voi/ + url_cran: https://CRAN.R-project.org/package=voi + url_git: '' +voice: + version: 0.4.21 + title: Tools for Voice Analysis, Speaker Recognition and Mood Inference + maintainer: Zabala Filipe J. + description: |- + Tools for voice analysis, speaker recognition and mood inference. + Gathers 'R' and 'Python' tools to solve problems concerning voice and audio + in general. + date_publication: '2023-04-19' + bug_reports: https://github.com/filipezabala/voice/issues + url: '' + url_cran: https://CRAN.R-project.org/package=voice + url_git: https://github.com/filipezabala/voice +voiceR: + version: 0.1.0 + title: Voice Analytics for Social Scientists + maintainer: Francesc Busquet + description: Simplifies and largely automates practical voice analytics for social + science research. This package offers an accessible and easy-to-use interface, + including an interactive Shiny app, that simplifies the processing, extraction, + analysis, and reporting of voice recording data in the behavioral and social sciences. + The package includes batch processing capabilities to read and analyze multiple + voice files in parallel, automates the extraction of key vocal features for further + analysis, and automatically generates APA formatted reports for typical between-group + comparisons in experimental social science research. A more extensive methodological + introduction that inspired the development of the 'voiceR' package is provided + in Hildebrand et al. 2020 . + date_publication: '2023-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=voiceR + url_git: '' +vol2birdR: + version: 1.0.7 + title: Vertical Profiles of Biological Signals in Weather Radar Data + maintainer: Adriaan M. Dokter + description: |- + 'R' implementation of the 'vol2bird' software for generating vertical profiles + of birds and other biological signals in weather radar data. See Dokter et al. + (2011) for a paper describing the methodology. + date_publication: '2025-02-21' + bug_reports: https://github.com/adokter/vol2birdR/issues + url: https://adriaandokter.com/vol2bird/ + url_cran: https://CRAN.R-project.org/package=vol2birdR + url_git: https://github.com/adokter/vol2birdR/ +volatilityTrader: + version: 1.0.1 + title: High Volatility Environment Option Trading Strategies Graphs + maintainer: MaheshP Kumar + description: |- + Trading Strategies for high Option Volatility environment are represented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. + Guy Cohen (“The Bible of Options Strategies (2nd ed.)”, 2015, ISBN: 9780133964028). + Zura Kakushadze, Juan A. Serur (“151 Trading Strategies”, 2018, ISBN: 9783030027919). + John C. Hull (“Options, Futures, and Other Derivatives (11th ed.)”, 2022, ISBN: 9780136939979). + date_publication: '2022-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=volatilityTrader + url_git: '' +volcano3D: + version: 2.0.9 + title: 3D Volcano Plots and Polar Plots for Three-Class Data + maintainer: Katriona Goldmann + description: |- + Generates interactive plots for analysing and visualising + three-class high dimensional data. It is particularly suited to visualising + differences in continuous attributes such as gene/protein/biomarker + expression levels between three groups. Differential gene/biomarker + expression analysis between two classes is typically shown as a volcano + plot. However, with three groups this type of visualisation is particularly + difficult to interpret. This package generates 3D volcano plots and 3-way + polar plots for easier interpretation of three-class data. + date_publication: '2023-05-17' + bug_reports: https://github.com/KatrionaGoldmann/volcano3D/issues + url: https://katrionagoldmann.github.io/volcano3D/index.html + url_cran: https://CRAN.R-project.org/package=volcano3D + url_git: https://github.com/KatrionaGoldmann/volcano3D +volcanoPlot: + version: 1.0.0 + title: Volcano Plot for Clinical Trial Adverse Events + maintainer: Jeremy Wildfire + description: Interactive adverse event (AE) volcano plot for monitoring clinical + trial safety. This tool allows users to view the overall distribution of AEs in + a clinical trial using standard (e.g. MedDRA preferred term) or custom (e.g. Gender) + categories using a volcano plot similar to proposal by Zink et al. (2013) . + This tool provides a stand-along shiny application and flexible shiny modules + allowing this tool to be used as a part of more robust safety monitoring framework + like the Shiny app from the 'safetyGraphics' R package. + date_publication: '2023-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=volcanoPlot + url_git: '' +volesti: + version: 1.1.2-8 + title: Volume Approximation and Sampling of Convex Polytopes + maintainer: Vissarion Fisikopoulos + description: |- + Provides an R interface for 'volesti' C++ package. 'volesti' computes estimations of volume + of polytopes given by (i) a set of points, (ii) linear inequalities or (iii) Minkowski sum of segments + (a.k.a. zonotopes). There are three algorithms for volume estimation as well as algorithms + for sampling, rounding and rotating polytopes. Moreover, 'volesti' provides algorithms for + estimating copulas useful in computational finance. Methods implemented in 'volesti' are described + in A. Chalkis and V. Fisikopoulos (2022) and references therein. + date_publication: '2024-10-09' + bug_reports: https://github.com/GeomScale/volesti/issues + url: '' + url_cran: https://CRAN.R-project.org/package=volesti + url_git: '' +volker: + version: 3.0.0 + title: |- + High-Level Functions for Tabulating, Charting and Reporting + Survey Data + maintainer: Jakob Jünger + description: |- + Craft polished tables and plots in Markdown reports. + Simply choose whether to treat your data as counts or metrics, + and the package will automatically generate well-designed default tables and plots for you. + Boiled down to the basics, with labeling features and simple interactive reports. + All functions are 'tidyverse' compatible. + date_publication: '2024-12-11' + bug_reports: https://github.com/strohne/volker/issues + url: https://strohne.github.io/volker/ + url_cran: https://CRAN.R-project.org/package=volker + url_git: https://github.com/strohne/volker +volleystat: + version: 0.2.0 + title: Detailed Statistics on Volleyball Matches + maintainer: Viktor Bozhinov + description: |- + Volleyball match statistics of the German volleyball first division league (seasons 2013/2014 to + 2018/2019). The data has been collected from the official volleyball first division homepage + () and contains information on teams, staff, sets, matches, and player-in-match + statistics (extracted automatically from the official match reports). + date_publication: '2019-05-20' + bug_reports: https://github.com/bozhinvi/volleystat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=volleystat + url_git: http://github.com/bozhinvi/volleystat +voluModel: + version: 0.2.2 + title: Modeling Species Distributions in Three Dimensions + maintainer: Hannah L. Owens + description: |- + Facilitates modeling species' ecological niches and + geographic distributions based on occurrences and environments that + have a vertical as well as horizontal component, and projecting models + into three-dimensional geographic space. Working in three dimensions is + useful in an aquatic context when the organisms one wishes to model can + be found across a wide range of depths in the water column. The package + also contains functions to automatically generate marine training + model training regions using machine learning, and interpolate and smooth + patchily sampled environmental rasters using thin plate splines. + Davis Rabosky AR, Cox CL, Rabosky DL, Title PO, Holmes IA, Feldman A, McGuire JA (2016) . + Nychka D, Furrer R, Paige J, Sain S (2021) . + Pateiro-Lopez B, Rodriguez-Casal A (2022) . + date_publication: '2024-08-20' + bug_reports: https://github.com/hannahlowens/voluModel/issues + url: https://hannahlowens.github.io/voluModel/ + url_cran: https://CRAN.R-project.org/package=voluModel + url_git: '' +voronoifortune: + version: '1.0' + title: Voronoi Tessellation by Fortune Algorithm + maintainer: Emmanuel Paradis + description: Fortune's (1987, ) algorithm is a very efficient + method to perform Voronoi tessellation and Delaunay triangulation. This package + is a port of the original code published in the early 1990's by Steven Fortune. + date_publication: '2025-01-08' + bug_reports: https://github.com/emmanuelparadis/voronoifortune/issues + url: '' + url_cran: https://CRAN.R-project.org/package=voronoifortune + url_git: https://github.com/emmanuelparadis/voronoifortune +voronoiTreemap: + version: 0.2.0 + title: Voronoi Treemaps with Added Interactivity by Shiny + maintainer: Alexander Kowarik + description: |- + The d3.js framework with the plugins d3-voronoi-map, d3-voronoi-treemap and d3-weighted-voronoi + are used to generate Voronoi treemaps in R and in a shiny application. + The computation of the Voronoi treemaps are based on Nocaj and Brandes (2012) + . + date_publication: '2019-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=voronoiTreemap + url_git: https://github.com/uRosConf/voronoiTreemap +VorteksExport: + version: 0.1.8 + title: Export Dataframes to 'Vorteks' Software + maintainer: Lansdon Page + description: |- + Export dataframes and automatically start importing into + 'Vorteks'. 'Vorteks Visualization Environment (VVE)' and 'Vorteks Data Manager (VDM)' will start an import. 'Vorteks Processing Environment (VPE)' will start a new project and + add a file reader with the dataframe file already set. + Warning: WINDOWS ONLY. Requires installation of 'Vorteks' software. + date_publication: '2021-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VorteksExport + url_git: '' +vortexRdata: + version: 1.0.5 + title: Example Data for R Package 'vortexR' + maintainer: Carlo Pacioni + description: |- + Contains selected data from two publications, + Campbell 'et' 'al'. (2016) + and 'Pacioni' 'et' 'al'. (2017) . + The data is provided both as raw outputs from the population viability + analysis software 'Vortex' and packaged as R objects. + The R package 'vortexR' uses the raw data provided here to illustrate its + functionality of parsing raw 'Vortex' output into R objects. + date_publication: '2019-02-04' + bug_reports: https://github.com/carlopacioni/vortexR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vortexRdata + url_git: https://github.com/carlopacioni/vortexRdata/ +voson.tcn: + version: 0.5.0 + title: Twitter Conversation Networks and Analysis + maintainer: Bryan Gertzel + description: |- + Collects tweets and metadata for threaded conversations and + generates networks. + date_publication: '2022-08-30' + bug_reports: https://github.com/vosonlab/voson.tcn/issues + url: '' + url_cran: https://CRAN.R-project.org/package=voson.tcn + url_git: https://github.com/vosonlab/voson.tcn +VOSONDash: + version: 0.5.7 + title: User Interface for Collecting and Analysing Social Networks + maintainer: Bryan Gertzel + description: |- + A 'Shiny' application for the interactive visualisation and + analysis of networks that also provides a web interface for collecting + social media data using 'vosonSML'. + date_publication: '2020-07-27' + bug_reports: https://github.com/vosonlab/VOSONDash/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VOSONDash + url_git: https://github.com/vosonlab/VOSONDash +vosonSML: + version: 0.32.7 + title: |- + Collecting Social Media Data and Generating Networks for + Analysis + maintainer: Bryan Gertzel + description: |- + A suite of easy to use functions for collecting social media + data and generating networks for analysis. Supports Twitter, YouTube, + Reddit and web site data sources. + date_publication: '2022-08-16' + bug_reports: https://github.com/vosonlab/vosonSML/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vosonSML + url_git: https://github.com/vosonlab/vosonSML +Voss: + version: 0.1.5 + title: Generic Voss Algorithm (Random Sequential Additions) + maintainer: Pavel V. Moskalev + description: Generating realizations of a fractal Brownian function on uniform 1D + & 2D grid with classic and generic versions of the Voss algorithm (random sequential + additions). + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Voss + url_git: '' +vote: + version: 2.4-3 + title: Election Vote Counting + maintainer: Hana Sevcikova + description: |- + Counting election votes and determining election results by different methods, including + the single transferable vote or ranked choice, approval, score, plurality, condorcet and two-round runoff methods (Raftery et al., 2021 ). + date_publication: '2023-12-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vote + url_git: '' +voteogram: + version: 0.3.2 + title: United States House and Senate Voting Cartogram Generators + maintainer: Bob Rudis + description: |- + 'ProPublica' makes United States + Congress member votes available and has developed their own unique cartogram to visually + represent this data. Tools are provided to retrieve voting data, prepare voting data + for plotting with 'ggplot2', create vote cartograms and theme them. + date_publication: '2023-03-08' + bug_reports: https://github.com/hrbrmstr/voteogram/issues + url: '' + url_cran: https://CRAN.R-project.org/package=voteogram + url_git: https://github.com/hrbrmstr/voteogram +voteSim: + version: 0.1.1 + title: Generate Simulated Data for Voting Rules using Evaluations + maintainer: Antoine Rolland + description: Provide functions to generate random simulated evaluations on candidates + by voters for evaluation-based elections. Functions are based on several models + for continuous or discrete evaluations. + date_publication: '2023-12-19' + bug_reports: '' + url: https://eric.univ-lyon2.fr/arolland/ + url_cran: https://CRAN.R-project.org/package=voteSim + url_git: '' +votesmart: + version: 0.1.2 + title: Wrapper for the Project 'VoteSmart' API + maintainer: Amanda Dobbyn + description: An R interface to the Project 'VoteSmart' + API. + date_publication: '2023-05-01' + bug_reports: https://github.com/decktools/votesmart/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=votesmart + url_git: https://github.com/decktools/votesmart/ +votesys: + version: 0.1.1 + title: |- + Voting Systems, Instant-Runoff Voting, Borda Method, Various + Condorcet Methods + maintainer: Jiang Wu + description: |- + Various methods to count ballots in voting systems are provided. + Functions to check validity of ballots are also provided to ensure flexibility. + date_publication: '2018-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=votesys + url_git: '' +vottrans: + version: '1.0' + title: Voter Transition Analysis + maintainer: Michael Gampmayer + description: Calculates voter transitions comparing two elections, using the function + solve.QP() in package 'quadprog'. + date_publication: '2016-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vottrans + url_git: '' +vov: + version: 0.1.2 + title: CSS Animations for 'shiny' Elements + maintainer: Tyler Littlefield + description: |- + A wrapper around a CSS library called 'vov.css', intended for use + in 'shiny' applications. Simply wrap a UI element in one of the animation + functions to see it move. + date_publication: '2020-08-27' + bug_reports: https://github.com/tyluRp/vov/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vov + url_git: https://github.com/tyluRp/vov +vowels: + version: 1.2-2 + title: Vowel Manipulation, Normalization, and Plotting + maintainer: Tyler Kendall + description: Procedures for the manipulation, normalization, and plotting of phonetic + and sociophonetic vowel formant data. vowels is the backend for the NORM website. + date_publication: '2018-03-05' + bug_reports: '' + url: http://blogs.uoregon.edu/vowels/ + url_cran: https://CRAN.R-project.org/package=vowels + url_git: '' +voxel: + version: 1.3.5 + title: Mass-Univariate Voxelwise Analysis of Medical Imaging Data + maintainer: Angel Garcia de la Garza + description: Functions for the mass-univariate voxelwise analysis of medical imaging + data that follows the NIfTI format. + date_publication: '2018-06-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=voxel + url_git: https://github.com/angelgar/voxel +VoxR: + version: 1.0.0 + title: Trees Geometry and Morphology from Unstructured TLS Data + maintainer: Bastien Lecigne + description: Tools for 3D point cloud voxelisation, projection, geometrical and + morphological description of trees (DBH, height, volume, crown diameter), analyses + of temporal changes between different measurement times, distance based clustering + and visualisation of 3D voxel clouds and 2D projection. Most analyses and algorithms + provided in the package are based on the concept of space exploration and are + described in Lecigne et al. (2018, ). + date_publication: '2020-09-30' + bug_reports: https://github.com/Blecigne/VoxR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VoxR + url_git: https://github.com/Blecigne/VoxR +vpc: + version: 1.2.2 + title: Create Visual Predictive Checks + maintainer: Ron Keizer + description: Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, + showing how certain statistics (percentiles) for observed data compare to those + same statistics for data simulated from a model. The package can generate VPCs + for continuous, categorical, censored, and (repeated) time-to-event data. + date_publication: '2021-01-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vpc + url_git: https://github.com/ronkeizer/vpc +VPdtw: + version: 2.2.1 + title: Variable Penalty Dynamic Time Warping + maintainer: Ethan Bass + description: Variable Penalty Dynamic Time Warping (VPdtw) for aligning chromatographic + signals. With an appropriate penalty this method performs good alignment of chromatographic + data without deforming the peaks (Clifford, D., Stone, G., Montoliu, I., Rezzi + S., Martin F., Guy P., Bruce S., and Kochhar S.(2009) ; + Clifford, D. and Stone, G. (2012) ). + date_publication: '2024-08-29' + bug_reports: https://github.com/ethanbass/VPdtw/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VPdtw + url_git: https://github.com/ethanbass/VPdtw/ +vprr: + version: 0.2.3 + title: Processing and Visualization of Video Plankton Recorder Data + maintainer: Emily O'Grady + description: |- + An oceanographic data processing package for analyzing and visualizing Video + Plankton Recorder data. This package was developed at 'Bedford Institute of Oceanography'. + Functions are designed to process automated image classification output and create organized and + easily portable data products. + date_publication: '2022-07-12' + bug_reports: '' + url: https://eogrady21.github.io/vprr/ + url_cran: https://CRAN.R-project.org/package=vprr + url_git: '' +vrnmf: + version: 1.0.2 + title: Volume-Regularized Structured Matrix Factorization + maintainer: Evan Biederstedt + description: Implements a set of routines to perform structured matrix factorization + with minimum volume constraints. The NMF procedure decomposes a matrix X into + a product C * D. Given conditions such that the matrix C is non-negative and has + sufficiently spread columns, then volume minimization of a matrix D delivers a + correct and unique, up to a scale and permutation, solution (C, D). This package + provides both an implementation of volume-regularized NMF and "anchor-free" NMF, + whereby the standard NMF problem is reformulated in the covariance domain. This + algorithm was applied in Vladimir B. Seplyarskiy Ruslan A. Soldatov, et al. "Population + sequencing data reveal a compendium of mutational processes in the human germ + line". Science, 12 Aug 2021. . This package interacts + with data available through the 'simulatedNMF' package, which is available in + a 'drat' repository. To access this data package, see the instructions at . + The size of the 'simulatedNMF' package is approximately 8 MB. + date_publication: '2022-02-25' + bug_reports: https://github.com/kharchenkolab/vrnmf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vrnmf + url_git: https://github.com/kharchenkolab/vrnmf +vroom: + version: 1.6.5 + title: Read and Write Rectangular Text Data Quickly + maintainer: Jennifer Bryan + description: |- + The goal of 'vroom' is to read and write data (like 'csv', + 'tsv' and 'fwf') quickly. When reading it uses a quick initial + indexing step, then reads the values lazily , so only the data you + actually use needs to be read. The writer formats the data in + parallel and writes to disk asynchronously from formatting. + date_publication: '2023-12-05' + bug_reports: https://github.com/tidyverse/vroom/issues + url: https://vroom.r-lib.org + url_cran: https://CRAN.R-project.org/package=vroom + url_git: https://github.com/tidyverse/vroom +vrtest: + version: '1.2' + title: |- + Variance Ratio Tests and Other Tests for Martingale Difference + Hypothesis + maintainer: Jae H. Kim + description: A collection of statistical tests for martingale difference hypothesis, + including automatic portmanteau test (Escansiano and Lobato, 2009) + and automatic variance ratio test (Kim, 2009) . + date_publication: '2023-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vrtest + url_git: '' +vscc: + version: '0.7' + title: Variable Selection for Clustering and Classification + maintainer: Paul D. McNicholas + description: |- + Performs variable selection/feature reduction under a clustering or + classification framework. In particular, it can be used in an automated fashion + using mixture model-based methods ('teigen' and 'mclust' are currently supported). + Can account for mixtures of non-Gaussian distributions via Manly transform (via 'ManlyMix'). + See Andrews and McNicholas (2014) and Neal and McNicholas (2023) + . + date_publication: '2023-10-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vscc + url_git: '' +vsd: + version: 0.1.0 + title: Graphical Shim for Visual Survival Data Analysis + maintainer: Daniel Camacho + description: Provides a shim command for survival analysis graphic generation. + date_publication: '2021-05-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vsd + url_git: '' +vse4ts: + version: 1.0.0 + title: |- + Identify Memory Patterns in Time Series Using Variance Scale + Exponent + maintainer: Mengyang Zheng + description: |- + Methods for calculating the variance scale exponent to + identify memory patterns in time series data. Includes tests for white + noise, short memory, and long memory. See Fu, H. et al. (2018) + . + date_publication: '2024-07-01' + bug_reports: https://github.com/z-my-cn/vse4ts/issues + url: https://z-my-cn.github.io/vse4ts/ + url_cran: https://CRAN.R-project.org/package=vse4ts + url_git: '' +vsgoftest: + version: 1.0-1 + title: Goodness-of-Fit Tests Based on Kullback-Leibler Divergence + maintainer: Philippe Regnault + description: An implementation of Vasicek and Song goodness-of-fit tests. Several + functions are provided to estimate differential Shannon entropy, i.e., estimate + Shannon entropy of real random variables with density, and test the goodness-of-fit + of some family of distributions, including uniform, Gaussian, log-normal, exponential, + gamma, Weibull, Pareto, Fisher, Laplace and beta distributions; see Lequesne and + Regnault (2020) . + date_publication: '2020-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vsgoftest + url_git: '' +vsmi: + version: 0.1.0 + title: Variable Selection for Multiple Imputed Data + maintainer: Haoyu Yang + description: |- + Penalized weighted least-squares estimate for variable selection on correlated multiply imputed data and penalized estimating equations for generalized linear models with multiple imputation. + Reference: + Li, Y., Yang, H., Yu, H., Huang, H., Shen, Y*. (2023) "Penalized estimating equations for generalized linear models with multiple imputation", . + Li, Y., Yang, H., Yu, H., Huang, H., Shen, Y*. (2023) "Penalized weighted least-squares estimate for variable selection on correlated multiply imputed data", . + date_publication: '2024-05-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vsmi + url_git: '' +VSOLassoBag: + version: 0.99.1 + title: Variable Selection Oriented LASSO Bagging Algorithm + maintainer: Chaoye Wang + description: A wrapped LASSO approach by integrating an ensemble learning strategy + to help select efficient, stable, and high confidential variables from omics-based + data. Using a bagging strategy in combination of a parametric method or inflection + point search method for cut-off threshold determination. This package can integrate + and vote variables generated from multiple LASSO models to determine the optimal + candidates. Luo H, Zhao Q, et al (2020) for + more details. + date_publication: '2023-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VSOLassoBag + url_git: '' +vsp: + version: 0.1.2 + title: Vintage Sparse PCA for Semi-Parametric Factor Analysis + maintainer: Alex Hayes + description: |- + Provides fast spectral estimation of latent factors in random + dot product graphs using the vsp estimator. Under mild assumptions, + the vsp estimator is consistent for (degree-corrected) stochastic + blockmodels, (degree-corrected) mixed-membership stochastic + blockmodels, and degree-corrected overlapping stochastic blockmodels. + date_publication: '2024-11-05' + bug_reports: https://github.com/RoheLab/vsp/issues + url: https://rohelab.github.io/vsp/ + url_cran: https://CRAN.R-project.org/package=vsp + url_git: https://github.com/RoheLab/vsp +vstdct: + version: '0.2' + title: Nonparametric Estimation of Toeplitz Covariance Matrices + maintainer: Karolina Klockmann + description: A nonparametric method to estimate Toeplitz covariance matrices from + a sample of n independently and identically distributed p-dimensional vectors + with mean zero. The data is preprocessed with the discrete cosine matrix and a + variance stabilization transformation to obtain an approximate Gaussian regression + setting for the log-spectral density function. Estimates of the spectral density + function and the inverse of the covariance matrix are provided as well. Functions + for simulating data and a protein data example are included. For details see (Klockmann, + Krivobokova; 2023), . + date_publication: '2023-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vstdct + url_git: '' +vstsr: + version: 1.1.0 + title: Access to 'Azure DevOps' API via R + maintainer: Ashley Baldry + description: |- + Implementation of 'Azure DevOps' API calls. + It enables the extraction of information about repositories, build and release definitions and individual releases. + It also helps create repositories and work items within a project without logging into 'Azure DevOps'. + There is the ability to use any API service with a shell for any non-predefined call. + date_publication: '2021-11-08' + bug_reports: https://github.com/ashbaldry/vstsr/issues + url: https://docs.microsoft.com/en-us/rest/api/azure/devops + url_cran: https://CRAN.R-project.org/package=vstsr + url_git: https://github.com/ashbaldry/vstsr +VSURF: + version: 1.2.0 + title: Variable Selection Using Random Forests + maintainer: Robin Genuer + description: |- + Three steps variable selection procedure based on random forests. + Initially developed to handle high dimensional data (for which number of + variables largely exceeds number of observations), the package is very + versatile and can treat most dimensions of data, for regression and + supervised classification problems. First step is dedicated to eliminate + irrelevant variables from the dataset. Second step aims to select all + variables related to the response for interpretation purpose. Third step + refines the selection by eliminating redundancy in the set of variables + selected by the second step, for prediction purpose. + Genuer, R. Poggi, J.-M. and Tuleau-Malot, C. (2015) + . + date_publication: '2022-12-15' + bug_reports: https://github.com/robingenuer/VSURF/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VSURF + url_git: https://github.com/robingenuer/VSURF +VsusP: + version: 1.0.0 + title: Variable Selection using Shrinkage Priors + maintainer: Nilson Chapagain + description: Bayesian variable selection using shrinkage priors to identify significant + variables in high-dimensional datasets. The package includes methods for determining + the number of significant variables through innovative clustering techniques of + posterior distributions, specifically utilizing the 2-Means and Sequential 2-Means + (S2M) approaches. The package aims to simplify the variable selection process + with minimal tuning required in statistical analysis. + date_publication: '2024-06-25' + bug_reports: https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VsusP + url_git: https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors +vtable: + version: 1.4.8 + title: Variable Table for Variable Documentation + maintainer: Nick Huntington-Klein + description: Automatically generates HTML variable documentation including variable + names, labels, classes, value labels (if applicable), value ranges, and summary + statistics. See the vignette "vtable" for a package overview. + date_publication: '2024-12-21' + bug_reports: https://github.com/NickCH-K/vtable/issues + url: https://nickch-k.github.io/vtable/ + url_cran: https://CRAN.R-project.org/package=vtable + url_git: '' +vtreat: + version: 1.6.5 + title: A Statistically Sound 'data.frame' Processor/Conditioner + maintainer: John Mount + description: |- + A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. + 'vtreat' prepares variables so that data has fewer exceptional cases, making + it easier to safely use models in production. Common problems 'vtreat' defends + against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new + categorical levels (levels seen during application, but not during training). Reference: + "'vtreat': a data.frame Processor for Predictive Modeling", Zumel, Mount, 2016, . + date_publication: '2024-06-12' + bug_reports: https://github.com/WinVector/vtreat/issues + url: https://winvector.github.io/vtreat/ + url_cran: https://CRAN.R-project.org/package=vtreat + url_git: https://github.com/WinVector/vtreat/ +vtree: + version: 5.6.5 + title: Display Information About Nested Subsets of a Data Frame + maintainer: Nick Barrowman + description: A tool for calculating and drawing "variable trees". Variable trees + display information about nested subsets of a data frame. + date_publication: '2022-12-10' + bug_reports: https://github.com/nbarrowman/vtree/issues + url: https://nbarrowman.github.io/vtree + url_cran: https://CRAN.R-project.org/package=vtree + url_git: https://github.com/nbarrowman/vtree +VTShiny: + version: 0.1.0 + title: Interactive Document for Working with Variance Analysis + maintainer: Kartikeya Bolar + description: An interactive document on the topic of variance analysis using 'rmarkdown' + and 'shiny' packages. Runtime examples are provided in the package function as + well as at . + date_publication: '2019-07-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VTShiny + url_git: '' +vtype: + version: '0.8' + title: Estimates the Variable Type in Error Afflicted Data + maintainer: Andreas Schulz + description: Estimates the type of variables in non-quality controlled data. The + prediction is based on a random forest model, trained on over 5000 medical variables + with accuracy of 99%. The accuracy can hardy depend on type and coding style of + data. + date_publication: '2021-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vtype + url_git: '' +vudc: + version: '1.1' + title: Visualization of Univariate Data for Comparison + maintainer: Csaba Farago + description: 'Contains functions for visualization univariate data: ccdplot and + qddplot.' + date_publication: '2016-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vudc + url_git: '' +vueR: + version: 0.6.0 + title: '''Vuejs'' Helpers and ''Htmlwidget''' + maintainer: Kent Russell + description: |- + Make it easy to use 'vue' in R with helper + dependency functions and examples. + date_publication: '2023-10-01' + bug_reports: https://github.com/vue-r/vueR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=vueR + url_git: https://github.com/vue-r/vueR +VulnToolkit: + version: 1.1.4 + title: Analysis of Tidal Datasets + maintainer: Troy Hill + description: Contains functions for analysis and summary of tidal datasets. Also + provides access to tidal data collected by the National Oceanic and Atmospheric + Administration's Center for Operational Oceanographic Products and Services and + the Permanent Service for Mean Sea Level. For detailed description and application + examples, see Hill, T.D. and S.C. Anisfeld (2021) + and Hill, T.D. and S.C. Anisfeld (2015) . + date_publication: '2021-08-02' + bug_reports: https://github.com/troyhill/VulnToolKit/issues + url: '' + url_cran: https://CRAN.R-project.org/package=VulnToolkit + url_git: https://github.com/troyhill/VulnToolkit +VUROCS: + version: '1.0' + title: Volume under the ROC Surface for Multi-Class ROC Analysis + maintainer: Hannes Kazianka + description: Calculates the volume under the ROC surface and its (co)variance for + ordered multi-class ROC analysis as well as certain bivariate ordinal measures + of association. + date_publication: '2020-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VUROCS + url_git: '' +vvauditor: + version: 0.7.0 + title: Creates Assertion Tests + maintainer: Tomer Iwan + description: |- + Offers a comprehensive set of assertion tests to help users validate the integrity of their data. + These tests can be used to check for specific conditions or properties within a dataset and + help ensure that data is accurate and reliable. + The package is designed to make it easy to add quality control checks to data analysis + workflows and to aid in identifying and correcting any errors or inconsistencies in data. + date_publication: '2025-02-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vvauditor + url_git: '' +vvcanvas: + version: 0.0.4 + title: '''Canvas'' LMS API Integration' + maintainer: Tomer Iwan + description: |- + Allow R users to interact with the 'Canvas' Learning Management System (LMS) API (see + for details). + It provides a set of functions to access and manipulate course data, assignments, grades, users, + and other resources available through the 'Canvas' API. + date_publication: '2024-04-29' + bug_reports: '' + url: https://vusaverse.github.io/vvcanvas/ + url_cran: https://CRAN.R-project.org/package=vvcanvas + url_git: https://github.com/vusaverse/vvcanvas +vvconverter: + version: 0.5.10 + title: Apply Transformations to Data + maintainer: Tomer Iwan + description: |- + Provides a set of functions for data transformations. + Transformations are performed on character and numeric data. As the scope of the package is + within Student Analytics, there are functions focused around the academic year. + date_publication: '2024-06-11' + bug_reports: https://github.com/vusaverse/vvconverter/issues + url: https://vusaverse.github.io/vvconverter/ + url_cran: https://CRAN.R-project.org/package=vvconverter + url_git: https://github.com/vusaverse/vvconverter +vvdoctor: + version: 0.0.1 + title: Statistical Test App with R 'shiny' + maintainer: Tomer Iwan + description: |- + Provides a user-friendly R 'shiny' app for performing various statistical tests on datasets. + It allows users to upload data in numerous formats and perform statistical analyses. + The app dynamically adapts its options based on the selected columns and supports both single and multiple column comparisons. + The app's user interface is designed to streamline the process of selecting datasets, columns, and test options, + making it easy for users to explore and interpret their data. The underlying functions for statistical tests are well-organized and can be used independently within other R scripts. + date_publication: '2024-04-27' + bug_reports: '' + url: https://vusaverse.github.io/vvdoctor/ + url_cran: https://CRAN.R-project.org/package=vvdoctor + url_git: https://github.com/vusaverse/vvdoctor +vvfiller: + version: 0.6.7 + title: Fill Data Points + maintainer: Tomer Iwan + description: |- + Provides numerous functions to fill data. + These can be applied either to missing or skewed data. + The functions are designed within the scope of Student Analytics. + date_publication: '2023-01-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vvfiller + url_git: https://github.com/vusaverse/vvfiller +vvmover: + version: 1.6.0 + title: Read and Write Data + maintainer: Tomer Iwan + description: |- + Offers a wide range of functions for reading and writing data in various file formats, + including CSV, RDS, Excel and ZIP files. + Additionally, it provides functions for retrieving metadata associated with files, + such as file size and creation date, making it easy to manage and organize large data sets. + This package is designed to simplify data import and export tasks, + and provide users with a comprehensive set of tools to work with different types of data files. + date_publication: '2024-02-26' + bug_reports: https://github.com/vusaverse/vvmover/issues + url: https://vusaverse.github.io/vvmover/ + url_cran: https://CRAN.R-project.org/package=vvmover + url_git: https://github.com/vusaverse/vvmover +vvsculptor: + version: 0.4.10 + title: Apply Manipulations to Data Frames + maintainer: Tomer Iwan + description: |- + Provides a set of functions for manipulating data frames in accordance with specific business rules. + In addition, it includes wrapper functions for commonly used functions from the popular 'tidyverse' package, + making it easy to integrate these functions into data analysis workflows. + The package is designed to streamline data preprocessing and help users quickly and efficiently + perform data transformations that are specific to their business needs. + date_publication: '2023-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vvsculptor + url_git: '' +vvshiny: + version: 0.1.1 + title: Create Complex Shiny Apps More Easily + maintainer: Corneel Den Hartogh + description: Helper and Wrapper functions for making shiny dashboards more easily. + Functions are made modular and lower level functions are exported as well, so + many use-cases are supported. + date_publication: '2023-07-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=vvshiny + url_git: '' +vvtableau: + version: 0.7.0 + title: R Interface for 'Tableau' Services + maintainer: Tomer Iwan + description: |- + Provides an R interface for interacting with the 'Tableau' Server. + It allows users to perform various operations such as publishing workbooks, refreshing data extracts, + and managing users using the 'Tableau' REST API (see for details). Additionally, + it includes functions to perform manipulations on local 'Tableau' workbooks. + date_publication: '2024-08-29' + bug_reports: '' + url: https://vusaverse.github.io/vvtableau/ + url_cran: https://CRAN.R-project.org/package=vvtableau + url_git: https://github.com/vusaverse/vvtableau +vvtermtime: + version: 0.0.1 + title: Interface for 'Semestry TermTime' Services + maintainer: Tomer Iwan + description: |- + Provides an R interface for interacting with the 'Semestry TermTime' services. + It allows users to retrieve scheduling data from the API. see + for details. + date_publication: '2023-08-07' + bug_reports: '' + url: https://vusaverse.github.io/vvtermtime/ + url_cran: https://CRAN.R-project.org/package=vvtermtime + url_git: https://github.com/vusaverse/vvtermtime +vwline: + version: 0.2-4 + title: Draw Variable-Width Lines + maintainer: Paul Murrell + description: |- + Provides R functions to draw lines and curves with the width + of the curve allowed to vary along the length of the curve. + date_publication: '2024-08-23' + bug_reports: '' + url: https://stattech.wordpress.fos.auckland.ac.nz/2017/05/19/2017-01-variable-width-lines-in-r/ + url_cran: https://CRAN.R-project.org/package=vwline + url_git: https://github.com/pmur002/vwline +VWPre: + version: 1.2.4 + title: Tools for Preprocessing Visual World Data + maintainer: Vincent Porretta + description: |- + Gaze data from the Visual World Paradigm requires significant + preprocessing prior to plotting and analyzing the data. This package + provides functions for preparing visual world eye-tracking data for + statistical analysis and plotting. It can prepare data for linear + analyses (e.g., ANOVA, Gaussian-family LMER, Gaussian-family GAMM) as + well as logistic analyses (e.g., binomial-family LMER and binomial-family GAMM). + Additionally, it contains various plotting functions for creating grand average and + conditional average plots. See the vignette for samples of the functionality. + Currently, the functions in this package are designed for handling data + collected with SR Research Eyelink eye trackers using Sample Reports created + in SR Research Data Viewer. While we would like to add functionality + for data collected with other systems in the future, the current package is + considered to be feature-complete; further updates will mainly entail maintenance + and the addition of minor functionality. + date_publication: '2020-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=VWPre + url_git: '' +W2CWM2C: + version: '2.2' + title: |- + A Graphical Tool for Wavelet (Cross) Correlation and Wavelet + Multiple (Cross) Correlation Analysis + maintainer: Josue M. Polanco-Martinez + description: 'Set of functions that improves the graphical presentations of the + functions: wave.correlation and spin.correlation (waveslim package, Whitcher 2012) + and the wave.multiple.correlation and wave.multiple.cross.correlation (wavemulcor + package, Fernandez-Macho 2012b). The plot outputs (heatmaps) can be displayed + in the screen or can be saved as PNG or JPG images or as PDF or EPS formats. The + W2CWM2C package also helps to handle the (input data) multivariate time series + easily as a list of N elements (times series) and provides a multivariate data + set (dataexample) to exemplify its use. A description of the package was published + in a scientific paper: Polanco-Martinez and Fernandez-Macho (2014), .' + date_publication: '2021-01-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=W2CWM2C + url_git: https://github.com/jomopo/W2CWM2C +W3CMarkupValidator: + version: 0.1-7 + title: R Interface to W3C Markup Validation Services + maintainer: Kurt Hornik + description: |2- + + R interface to a W3C Markup Validation service. + See for more information. + date_publication: '2023-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=W3CMarkupValidator + url_git: '' +WA: + version: '1.0' + title: |- + While-Alive Loss Rate for Recurrent Event in the Presence of + Death + maintainer: Lu Mao + description: Contains inferential and graphical routines for multi-group analysis + of while-alive loss (or event) rate for possibly recurrent nonfatal event in the + presence of death. + date_publication: '2021-11-17' + bug_reports: '' + url: https://sites.google.com/view/lmaowisc/ + url_cran: https://CRAN.R-project.org/package=WA + url_git: '' +wacolors: + version: 0.3.1 + title: Colorblind-Friendly Palettes from Washington State + maintainer: Cory McCartan + description: |- + Color palettes taken from the landscapes and cities of Washington + state. Colors were extracted from a set of photographs, and then combined to + form a set of continuous and discrete palettes. Continuous palettes were + designed to be perceptually uniform, while discrete palettes were chosen to + maximize contrast at several different levels of overall brightness and + saturation. Each palette has been evaluated to ensure colors are + distinguishable by colorblind people. + date_publication: '2022-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wacolors + url_git: https://github.com/CoryMcCartan/wacolors +WACS: + version: 1.1.0 + title: |- + Multivariate Weather-State Approach Conditionally Skew-Normal + Generator + maintainer: Ronan Trépos + description: |- + A multivariate weather generator for daily climate variables based + on weather-states (Flecher et al. (2010) ). + It uses a Markov chain for modeling the succession of weather states. + Conditionally to the weather states, the multivariate variables are modeled using the family + of Complete Skew-Normal distributions. Parameters are estimated on measured series. Must + include the variable 'Rain' and can accept as many other variables as desired. + date_publication: '2020-06-05' + bug_reports: '' + url: https://miat.inrae.fr/site/Ronan_TREPOS + url_cran: https://CRAN.R-project.org/package=WACS + url_git: '' +wactor: + version: 0.0.1 + title: Word Factor Vectors + maintainer: Michael W. Kearney + description: |- + A user-friendly factor-like interface for converting strings of + text into numeric vectors and rectangular data structures. + date_publication: '2019-12-18' + bug_reports: https://github.com/mkearney/wactor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wactor + url_git: https://github.com/mkearney/wactor +waffle: + version: 1.0.2 + title: Create Waffle Chart Visualizations + maintainer: Bob Rudis + description: |- + Square pie charts (a.k.a. waffle charts) can be used + to communicate parts of a whole for categorical quantities. To emulate the + percentage view of a pie chart, a 10x10 grid should be used with each square + representing 1% of the total. Modern uses of waffle charts do not + necessarily adhere to this rule and can be created with a grid of any + rectangular shape. Best practices suggest keeping the number of categories + small, just as should be done when creating pie charts. Tools are provided + to create waffle charts as well as stitch them together, and to use glyphs + for making isotype pictograms. + date_publication: '2023-09-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=waffle + url_git: '' +waiter: + version: 0.2.5 + title: Loading Screen for 'Shiny' + maintainer: John Coene + description: Full screen and partial loading screens for 'Shiny' with spinners, + progress bars, and notifications. + date_publication: '2022-01-03' + bug_reports: https://github.com/JohnCoene/waiter/issues + url: https://waiter.john-coene.com/ + url_cran: https://CRAN.R-project.org/package=waiter + url_git: https://github.com/JohnCoene/waiter +wakefield: + version: 0.3.6 + title: Generate Random Data Sets + maintainer: Tyler Rinker + description: |- + Generates random data sets including: data.frames, lists, + and vectors. + date_publication: '2020-09-13' + bug_reports: https://github.com/trinker/wakefield/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wakefield + url_git: https://github.com/trinker/wakefield +wal: + version: 0.1.1 + title: Read and Write 'wal' Bitmap Image Files and Other 'Quake' Assets + maintainer: Tim Schäfer + description: Read 'Quake' assets including bitmap images and textures in 'wal' file + format. This package also provides support for extracting these assets from 'WAD' + and 'PAK' file archives. It can also read models in 'MDL' and 'MD2' formats. + date_publication: '2024-02-02' + bug_reports: https://github.com/dfsp-spirit/wal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wal + url_git: https://github.com/dfsp-spirit/wal +waldo: + version: 0.6.1 + title: Find Differences Between R Objects + maintainer: Hadley Wickham + description: |- + Compare complex R objects and reveal the key differences. + Designed particularly for use in testing packages where being able to + quickly isolate key differences makes understanding test failures much + easier. + date_publication: '2024-11-07' + bug_reports: https://github.com/r-lib/waldo/issues + url: https://waldo.r-lib.org + url_cran: https://CRAN.R-project.org/package=waldo + url_git: https://github.com/r-lib/waldo +walkboutr: + version: 0.6.0 + title: Generate Walk Bouts from GPS and Accelerometry Data + maintainer: Lauren Blair Wilner + description: Process GPS and accelerometry data to generate walk bouts. A walk bout + is a period of activity with accelerometer movement matching the patterns of walking + with corresponding GPS measurements that confirm travel. The inputs of the 'walkboutr' + package are individual-level accelerometry and GPS data. The outputs of the model + are walk bouts with corresponding times, duration, and summary statistics on the + sample population, which collapse all personally identifying information. These + bouts can be used to measure walking both as an outcome of a change to the built + environment or as a predictor of health outcomes such as a cardioprotective behavior. + Kang B, Moudon AV, Hurvitz PM, Saelens BE (2017) . + date_publication: '2024-01-30' + bug_reports: https://github.com/rwalkbout/walkboutr/issues + url: https://rwalkbout.github.io/walkboutr/ + url_cran: https://CRAN.R-project.org/package=walkboutr + url_git: https://github.com/rwalkbout/walkboutr +walker: + version: 1.0.10 + title: |- + Bayesian Generalized Linear Models with Time-Varying + Coefficients + maintainer: Jouni Helske + description: |- + Efficient Bayesian generalized linear models with time-varying coefficients + as in Helske (2022, ). Gaussian, Poisson, and binomial + observations are supported. The Markov chain Monte Carlo (MCMC) computations are done using + Hamiltonian Monte Carlo provided by Stan, using a state space representation + of the model in order to marginalise over the coefficients for efficient sampling. + For non-Gaussian models, the package uses the importance sampling type estimators based on + approximate marginal MCMC as in Vihola, Helske, Franks (2020, ). + date_publication: '2024-08-30' + bug_reports: https://github.com/helske/walker/issues + url: '' + url_cran: https://CRAN.R-project.org/package=walker + url_git: https://github.com/helske/walker +walkscore: + version: 0.1.2 + title: A Tidy Interface to the 'Walk Score' API + maintainer: Christopher Belanger + description: |- + Easily collect walk scores, bike scores, and transit scores (where + available) from the 'Walk Score' API , + a proprietary API that assigns locations a walkability score between 0 and 100. + date_publication: '2023-03-13' + bug_reports: https://github.com/chris31415926535/walkscore/issues + url: '' + url_cran: https://CRAN.R-project.org/package=walkscore + url_git: https://github.com/chris31415926535/walkscore +walkscoreAPI: + version: '1.2' + title: Walk Score and Transit Score API + maintainer: John Whalen + description: |- + A collection of functions to perform the Application + Programming Interface (API) calls associated with the Walk + Score website (www.walkscore.com) within the R environment. + These functions can be used to query the Walk Score and Transit + Score database for a wide variety of information using R + scripts. This package includes the simple Walk Score and + Transit Score API calls, which return the scores associated + with an input location, as well as calls which return some data + used to calculate the scores. These functions are especially + useful for mass data collection and gathering Walk Score and + Transit Score values for large lists of locations. + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=walkscoreAPI + url_git: '' +wallace: + version: 2.1.3 + title: |- + A Modular Platform for Reproducible Modeling of Species Niches + and Distributions + maintainer: Mary E. Blair + description: |- + The 'shiny' application Wallace is a modular platform for + reproducible modeling of species niches and distributions. Wallace + guides users through a complete analysis, from the acquisition of species + occurrence and environmental data to visualizing model predictions on an + interactive map, thus bundling complex workflows into a single, + streamlined interface. An extensive vignette, which guides users through + most package functionality can be found on the package's GitHub Pages + website: . + date_publication: '2024-07-18' + bug_reports: '' + url: http://wallaceecomod.github.io/wallace/ + url_cran: https://CRAN.R-project.org/package=wallace + url_git: '' +WallomicsData: + version: '1.0' + title: |- + Datasets for Multi-Omics Integration in a Plant Abiotic Stress + Context + maintainer: Sébastien Déjean + description: Datasets from the WallOmics project. Contains phenomics, metabolomics, + proteomics and transcriptomics data collected from two organs of five ecotypes + of the model plant Arabidopsis thaliana exposed to two temperature growth conditions. + Exploratory and integrative analyses of these data are presented in Durufle et + al (2020) and Durufle et al (2020) . + date_publication: '2022-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WallomicsData + url_git: '' +wally: + version: 1.0.10 + title: The Wally Calibration Plot for Risk Prediction Models + maintainer: Paul F. Blanche + description: A prediction model is calibrated if, roughly, for any percentage x + we can expect that x subjects out of 100 experience the event among all subjects + that have a predicted risk of x%. A calibration plot provides a simple, yet useful, + way of assessing the calibration assumption. The Wally plot consists of a sequence + of usual calibration plots. Among the plots contained within the sequence, one + is the actual calibration plot which has been obtained from the data and the others + are obtained from similar simulated data under the calibration assumption. It + provides the investigator with a direct visual understanding of the shape and + sampling variability that are common under the calibration assumption. The original + calibration plot from the data is included randomly among the simulated calibration + plots, similarly to a police lineup. If the original calibration plot is not easily + identified then the calibration assumption is not contradicted by the data. The + method handles the common situations in which the data contain censored observations + and occurrences of competing events. + date_publication: '2019-10-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wally + url_git: '' +walmartAPI: + version: 0.1.5 + title: Walmart Open API Wrapper + maintainer: Emil Hvitfeldt + description: |- + Provides API access to the Walmart Open API , + that contains data about stores, Value of the day and products which + includes names, sale prices, shipping rates and taxonomies. + date_publication: '2018-01-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=walmartAPI + url_git: https://github.com/EmilHvitfeldt/walmartAPI +walrus: + version: 1.0.5 + title: Robust Statistical Methods + maintainer: Jonathon Love + description: |- + A toolbox of common robust statistical tests, including robust + descriptives, robust t-tests, and robust ANOVA. It is also available as a + module for 'jamovi' (see for more information). + Walrus is based on the WRS2 package by Patrick Mair, which is in turn based on + the scripts and work of Rand Wilcox. These analyses are described in depth in + the book 'Introduction to Robust Estimation & Hypothesis Testing'. + date_publication: '2022-09-08' + bug_reports: https://github.com/jamovi/walrus/issues + url: '' + url_cran: https://CRAN.R-project.org/package=walrus + url_git: https://github.com/jamovi/walrus +WALS: + version: 0.2.5 + title: Weighted-Average Least Squares Model Averaging + maintainer: Kevin Huynh + description: |- + Implements Weighted-Average Least Squares model averaging + for negative binomial regression models of Huynh (2024) , + generalized linear models of De Luca, Magnus, Peracchi (2018) + and linear regression models of + Magnus, Powell, Pruefer (2010) , see also + Magnus, De Luca (2016) . Weighted-Average Least Squares + for the linear regression model is based on the original 'MATLAB' code by + Magnus and De Luca , see also + Kumar, Magnus (2013) and + De Luca, Magnus (2011) . + date_publication: '2024-06-21' + bug_reports: https://github.com/kevhuy/WALS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WALS + url_git: https://github.com/kevhuy/WALS +WaMaSim: + version: 1.0.0 + title: |- + Simulate Rehabilitation Strategies for Water Distribution + Systems + maintainer: Christian Foerster + description: The outcome of various rehabilitation strategies for water distribution + systems can be modeled with the Water Management Simulator (WaMaSim). Pipe breaks + and the corresponding damage and rehabilitation costs are simulated. It is mainly + intended to be used as educational tool for the Water Infrastructure Experimental + and Computer Laboratory at ETH Zurich, Switzerland. + date_publication: '2019-05-03' + bug_reports: https://github.com/scheidan/WaMaSim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WaMaSim + url_git: https://github.com/scheidan/WaMaSim +wand: + version: 0.5.0 + title: Retrieve 'Magic' Attributes from Files and Directories + maintainer: Bob Rudis + description: |- + 'MIME' types are shorthand descriptors for + file contents and can be determined from "magic" + bytes in file headers, file contents or intuited + from file extensions. Tools are provided to + perform curated "magic" tests as well as mapping + 'MIME' types from a database of over 1,500 + extension mappings. + date_publication: '2019-07-08' + bug_reports: https://gitlab.com/hrbrmstr/wand/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wand + url_git: http://gitlab.com/hrbrmstr/wand +WAnova: + version: 0.4.0 + title: Welch's Anova from Summary Statistics + maintainer: Niklas Burgard + description: |- + Provides the functions to perform a Welch's one-way Anova with fixed effects + based on summary statistics (sample size, means, standard deviation) and the Games-Howell post hoc test + for multiple comparisons and provides the effect size estimator adjusted omega squared. + In addition sample size estimation can be computed based on Levy's method, and a Monte Carlo + simulation is included to bootstrap residual normality and homoscedasticity + Welch, B. L. (1951) + Kirk, R. E. (1996) + Carroll, R. M., & Nordholm, L. A. (1975) + Albers, C., & Lakens, D. (2018) + Games, P. A., & Howell, J. F. (1976) + Levy, K. J. (1978a) + Show-Li, J., & Gwowen, S. (2014) . + date_publication: '2024-09-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WAnova + url_git: '' +warabandi: + version: 0.1.0 + title: Roster Generation of Turn for Weekdays:'warabandi' + maintainer: Harvinder Singh + description: |- + It generates the roster of turn for an outlet which is flowing + (water) 24X7 or 168 hours towards the area under command or agricutural + area (to be irrigated). The area under command is differentially owned + by different individual farmers. The Outlet runs for free of cost to + irrigate the area under command 24X7. + So, flow time of the outlet has to be divided based on an area owned by + an individual farmer and the location of his land or farm. This roster + is known as 'warabandi' and its generation in agriculture practices is a + very tedious task. Calculations of time in microseconds are more + error-prone, especially whenever it is performed by hands. That division + of flow time for an individual farmer can be calculated by 'warabandi'. + However, it generates a full publishable report for an outlet and all the + farmers who have farms subjected to be irrigated. + It reduces error risk and makes a more reproducible roster. For more + details about warabandi system you can found elsewhere in + Bandaragoda DJ(1995) . + date_publication: '2021-07-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=warabandi + url_git: '' +warbleR: + version: 1.1.34 + title: Streamline Bioacoustic Analysis + maintainer: Marcelo Araya-Salas + description: Functions aiming to facilitate the analysis of the structure of animal + acoustic signals in 'R'. 'warbleR' makes use of the basic sound analysis tools + from the packages 'tuneR' and 'seewave', and offers new tools for explore and + quantify acoustic signal structure. The package allows to organize and manipulate + multiple sound files, create spectrograms of complete recordings or individual + signals in different formats, run several measures of acoustic structure, and + characterize different structural levels in acoustic signals. + date_publication: '2025-01-17' + bug_reports: https://github.com/maRce10/warbleR/issues/ + url: https://marce10.github.io/warbleR/ + url_cran: https://CRAN.R-project.org/package=warbleR + url_git: '' +WARDEN: + version: 0.99.1 + title: |- + Workflows for Health Technology Assessments in R using Discrete + EveNts + maintainer: Javier Sanchez Alvarez + description: |- + Toolkit to support and perform discrete event simulations without + resource constraints in the context of health technology assessments (HTA). + The package focuses on cost-effectiveness modelling and aims to be submission-ready + to relevant HTA bodies in alignment with 'NICE TSD 15' + . + More details an examples can be found in the package website . + date_publication: '2024-12-13' + bug_reports: '' + url: https://jsanchezalv.github.io/WARDEN/ + url_cran: https://CRAN.R-project.org/package=WARDEN + url_git: '' +warehouseTools: + version: 0.1.2 + title: |- + Heuristics for Solving the Traveling Salesman Problem in + Warehouse Layouts + maintainer: Andrzej Dudek + description: |- + Heuristic methods to solve the routing problems in a warehouse management. Package includes several heuristics such as the Midpoint, Return, S-Shape and Semi-Optimal Heuristics for designation of the picker’s route in order picking. The heuristics aim to provide the acceptable travel distances while considering warehouse layout constraints such as aisles and shelves. + It also includes implementation of the COPRAS (COmplex PRoportional ASsessment) method for supporting selection of locations to be visited by the picker in shared storage systems. The package is designed to facilitate more efficient warehouse routing and logistics operations. + see: + Bartholdi, J. J., Hackman, S. T. (2019). "WAREHOUSE & DISTRIBUTION SCIENCE. Release 0.98.1." + The Supply Chain & Logistics Institute. H. Milton Stewart School of Industrial and Systems Engineering. + Georgia Institute of Technology. + . + date_publication: '2024-12-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=warehouseTools + url_git: '' +WARN: + version: 1.2-4 + title: Weaning Age Reconstruction with Nitrogen Isotope Analysis + maintainer: Takumi Tsutaya + description: |- + This estimates precise weaning ages + for a given skeletal population + by analyzing the stable nitrogen isotope ratios of them. + Bone collagen turnover rates estimated anew and + the approximate Bayesian computation (ABC) + were adopted in this package. + date_publication: '2019-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WARN + url_git: '' +warp: + version: 0.2.1 + title: Group Dates + maintainer: Davis Vaughan + description: |- + Tooling to group dates by a variety of periods including: + yearly, monthly, by second, by week of the month, and more. The + groups are defined in such a way that they also represent the distance + between dates in terms of the period. This extracts valuable + information that can be used in further calculations that rely on a + specific temporal spacing between observations. + date_publication: '2023-11-02' + bug_reports: https://github.com/DavisVaughan/warp/issues + url: https://davisvaughan.github.io/warp/ + url_cran: https://CRAN.R-project.org/package=warp + url_git: https://github.com/DavisVaughan/warp +warpMix: + version: 0.1.0 + title: |- + Mixed Effects Modeling with Warping for Functional Data Using + B-Spline + maintainer: Emilie Devijver + description: |- + Mixed effects modeling with warping for functional data using B- + spline. Warping coefficients are considered as random effects, and warping + functions are general functions, parameters representing the projection onto B- + spline basis of a part of the warping functions. Warped data are modelled by a + linear mixed effect functional model, the noise is Gaussian and independent from + the warping functions. + date_publication: '2017-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=warpMix + url_git: '' +washdata: + version: 0.1.4 + title: Urban Water and Sanitation Survey Dataset + maintainer: Ernest Guevarra + description: |- + Urban water and sanitation survey dataset collected by Water and + Sanitation for the Urban Poor (WSUP) with technical support from + Valid International. These citywide surveys have been collecting data + allowing water and sanitation service levels across the entire city to be + characterised, while also allowing more detailed data to be collected in + areas of the city of particular interest. These surveys are intended to + generate useful information for others working in the water and sanitation + sector. Current release version includes datasets collected from a survey + conducted in Dhaka, Bangladesh in March 2017. This survey in Dhaka is one of + a series of surveys to be conducted by WSUP in various + cities in which they operate including Accra, Ghana; Nakuru, Kenya; + Antananarivo, Madagascar; Maputo, Mozambique; and, Lusaka, Zambia. This + package will be updated once the surveys in other cities are completed and + datasets have been made available. + date_publication: '2024-04-12' + bug_reports: https://github.com/katilingban/washdata/issues + url: https://katilingban.io/washdata/ + url_cran: https://CRAN.R-project.org/package=washdata + url_git: https://github.com/katilingban/washdata/ +washeR: + version: 0.1.3 + title: Time Series Outlier Detection + maintainer: Andrea Venturini + description: 'Time series outlier detection with non parametric test. This is a + new outlier detection methodology (washer): efficient for time saving elaboration + and implementation procedures, adaptable for general assumptions and for needing + very short time series, reliable and effective as involving robust non parametric + test. You can find two approaches: single time series (a vector) and grouped time + series (a data frame). For other informations: Andrea Venturini (2011) Statistica + - Universita di Bologna, Vol.71, pp.329-344. For an informal explanation look + at R-bloggers on web.' + date_publication: '2022-09-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=washeR + url_git: '' +washi: + version: 0.2.0 + title: Washington Soil Health Initiative Branding + maintainer: Jadey Ryan + description: |- + Create plots and tables in a consistent style with WaSHI + (Washington Soil Health Initiative) branding. Use 'washi' to easily + style your 'ggplot2' plots and 'flextable' tables. + date_publication: '2023-09-07' + bug_reports: https://github.com/WA-Department-of-Agriculture/washi/issues/ + url: https://wa-department-of-agriculture.github.io/washi/ + url_cran: https://CRAN.R-project.org/package=washi + url_git: https://github.com/WA-Department-of-Agriculture/washi +washr: + version: 1.0.1 + title: |- + Publication Toolkit for Water, Sanitation and Hygiene (WASH) + Data + maintainer: Colin Walder + description: A toolkit to set up an R data package in a consistent structure. Automates + tasks like tidy data export, data dictionary documentation, README and website + creation, and citation management. + date_publication: '2024-11-07' + bug_reports: https://github.com/openwashdata/washr/issues + url: https://openwashdata.github.io/washr/ + url_cran: https://CRAN.R-project.org/package=washr + url_git: '' +WASP: + version: 1.4.4 + title: Wavelet System Prediction + maintainer: Ze Jiang + description: The wavelet-based variance transformation method is used for system + modelling and prediction. It refines predictor spectral representation using Wavelet + Theory, which leads to improved model specifications and prediction accuracy. + Details of methodologies used in the package can be found in Jiang, Z., Sharma, + A., & Johnson, F. (2020) , Jiang, Z., Rashid, M. M., + Johnson, F., & Sharma, A. (2020) , and Jiang, + Z., Sharma, A., & Johnson, F. (2021) . + date_publication: '2024-07-20' + bug_reports: https://github.com/zejiang-unsw/WASP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WASP + url_git: https://github.com/zejiang-unsw/WASP#readme +waspasR: + version: 0.1.5 + title: |- + Tool Kit to Implement a W.A.S.P.A.S. Based Multi-Criteria + Decision Analysis Solution + maintainer: Flavio Barbara + description: |- + Provides a set of functions to implement decision-making systems + based on the W.A.S.P.A.S. method (Weighted Aggregated Sum Product Assessment), + Chakraborty and Zavadskas (2012) . + So this package offers functions that analyze and validate the + raw data, which must be entered in a determined format; + extract specific vectors and matrices from this raw database; + normalize the input data; calculate rankings by intermediate methods; + apply the lambda parameter for the main method; and a function that does + everything at once. The package has an example database called choppers, + with which the user can see how the input data should be organized so that + everything works as recommended by the decision methods based on multiple + criteria that this package solves. Basically, the data are composed of a set + of alternatives, which will be ranked, a set of choice criteria, a matrix + of values for each Alternative-Criterion relationship, a vector of weights + associated with the criteria, since certain criteria are considered more + important than others, as well as a vector that defines each criterion as + cost or benefit, this determines the calculation formula, as there are those + criteria that we want the highest possible value (e.g. durability) + and others that we want the lowest possible value (e.g. price). + date_publication: '2023-06-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=waspasR + url_git: '' +waspr: + version: 1.0.1 + title: Wasserstein Barycenters of Subset Posteriors + maintainer: Jolien Cremers + description: |- + Functions to compute Wasserstein barycenters + of subset posteriors using the swapping algorithm developed by Puccetti, + Rüschendorf and Vanduffel (2020) . The + Wasserstein barycenter is a geometric approach for combining subset + posteriors. It allows for parallel and distributed computation of the + posterior in case of complex models and/or big datasets, thereby increasing + computational speed tremendously. + date_publication: '2023-09-11' + bug_reports: https://github.com/joliencremers/waspr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=waspr + url_git: https://github.com/joliencremers/waspr +watcher: + version: 0.1.2 + title: Watch the File System for Changes + maintainer: Charlie Gao + description: |- + R binding for 'libfswatch', a file system monitoring library. Watch + files, or directories recursively, for changes in the background. Log + activity, or run an R function every time a change event occurs. + date_publication: '2025-02-25' + bug_reports: https://github.com/r-lib/watcher/issues + url: https://watcher.r-lib.org + url_cran: https://CRAN.R-project.org/package=watcher + url_git: https://github.com/r-lib/watcher +waterData: + version: 1.0.8 + title: |- + Retrieval, Analysis, and Anomaly Calculation of Daily Hydrologic + Time Series Data + maintainer: Karen R. Ryberg + description: Imports U.S. Geological Survey (USGS) daily hydrologic data from USGS + web services (see for more information), plots + the data, addresses some common data problems, and calculates and plots anomalies. + date_publication: '2017-04-28' + bug_reports: '' + url: https://pubs.usgs.gov/of/2012/1168/ + url_cran: https://CRAN.R-project.org/package=waterData + url_git: '' +waterfall: + version: 1.0.2 + title: Waterfall Charts + maintainer: '"James P. Howard, II"' + description: |- + Provides support for creating waterfall charts in R + using both traditional base and lattice graphics. + date_publication: '2016-04-03' + bug_reports: https://github.com/howardjp/waterfall/issues + url: https://jameshoward.us/software/waterfall/ + url_cran: https://CRAN.R-project.org/package=waterfall + url_git: https://github.com/howardjp/waterfall +waterfalls: + version: 1.0.0 + title: Create Waterfall Charts using 'ggplot2' Simply + maintainer: Hugh Parsonage + description: A not uncommon task for quants is to create 'waterfall charts'. There + seems to be no simple way to do this in 'ggplot2' currently. This package contains + a single function (waterfall) that simply draws a waterfall chart in a 'ggplot2' + object. Some flexibility is provided, though often the object created will need + to be modified through a theme. + date_publication: '2022-11-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=waterfalls + url_git: https://github.com/hughparsonage/waterfalls +waterquality: + version: 1.0.0 + title: Satellite Derived Water Quality Detection Algorithms + maintainer: Richard Johansen + description: |- + The main purpose of waterquality is to quickly and easily convert + satellite-based reflectance imagery into one or many well-known water quality + algorithms designed for the detection of harmful algal blooms or the following + pigment proxies: chlorophyll-a, blue-green algae (phycocyanin), and turbidity. + Johansen et al. (2019) . + date_publication: '2023-08-07' + bug_reports: https://github.com/RAJohansen/waterquality/issues + url: '' + url_cran: https://CRAN.R-project.org/package=waterquality + url_git: https://github.com/RAJohansen/waterquality +waterYearType: + version: 1.0.1 + title: Sacramento and San Joaquin Valley Water Year Types + maintainer: Sadie Gill + description: |- + Provides Water Year Hydrologic Classification Indices based on measured + unimpaired runoff (in million acre-feet). Data is provided by California Department of Water Resources + and subject to revision. + date_publication: '2019-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=waterYearType + url_git: '' +Wats: + version: 1.0.1 + title: Wrap Around Time Series Graphics + maintainer: Will Beasley + description: |- + Wrap-around Time Series (WATS) plots for interrupted time series + designs with seasonal patterns. + Longitudinal trajectories are shown in both Cartesian and polar coordinates. + In many scenarios, a WATS plot more clearly shows the existence and effect size of + of an intervention. + This package accompanies + "Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs" + by Rodgers, Beasley, & Schuelke (2014) + ; + see 'citation("Wats")' for details. + date_publication: '2023-03-10' + bug_reports: https://github.com/OuhscBbmc/Wats/issues + url: https://ouhscbbmc.github.io/Wats/ + url_cran: https://CRAN.R-project.org/package=Wats + url_git: https://github.com/OuhscBbmc/Wats +watson: + version: '0.6' + title: Fitting and Simulating Mixtures of Watson Distributions + maintainer: Lukas Sablica + description: |- + Tools for fitting and simulating mixtures of Watson distributions. + The random sampling scheme of the package offers two sampling + algorithms that are based of the results of Sablica, Hornik and Leydold (2022) + . + What is more, the package offers a smart tool to combine these two methods, + and based on the selected parameters, it approximates the relative sampling + speed for both methods and picks the faster one. In addition, the package + offers a fitting function for the mixtures of Watson distribution, that + uses the expectation-maximization (EM) algorithm. Special features are + the possibility to use multiple variants of the E-step and M-step, + sparse matrices for the data representation and state of the art methods + for numerical evaluation of needed special functions using the results of + Sablica and Hornik (2022) and + Sablica and Hornik (2024) . + date_publication: '2025-02-19' + bug_reports: https://github.com/lsablica/watson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=watson + url_git: https://github.com/lsablica/watson +wav: + version: 0.1.0 + title: Read and Write WAV Files + maintainer: Daniel Falbel + description: |- + Efficiently read and write Waveform (WAV) audio files . + Support for unsigned 8 bit Pulse-code modulation (PCM), signed 12, 16, 24 and 32 bit + PCM and other encodings. + date_publication: '2022-11-28' + bug_reports: https://github.com/mlverse/wav/issues + url: https://mlverse.github.io/wav/ + url_cran: https://CRAN.R-project.org/package=wav + url_git: https://github.com/mlverse/wav +waveband: + version: 4.7.4 + title: Computes Credible Intervals for Bayesian Wavelet Shrinkage + maintainer: Guy Nason + description: |- + Computes Bayesian wavelet shrinkage credible intervals for + nonparametric regression. + The method uses cumulants to derive Bayesian credible intervals for + wavelet regression estimates. + The first four cumulants of the posterior distribution of the + estimates are expressed in terms of the observed data and integer + powers of the mother wavelet functions. + These powers are closely approximated by linear combinations of + wavelet scaling functions at an appropriate finer scale. + Hence, a suitable modification of the discrete wavelet transform allows + the posterior cumulants to be found efficiently for any data set. + Johnson transformations then yield the credible intervals themselves. + Barber, S., Nason, G.P. and Silverman, B.W. (2002) + . + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=waveband + url_git: '' +waved: + version: '1.3' + title: Wavelet Deconvolution + maintainer: Michael Stewart + description: |- + Makes available code necessary to reproduce figures and + tables in papers on the WaveD method for wavelet deconvolution + of noisy signals as presented in The WaveD Transform in R, + Journal of Statistical Software Volume 21, No. 3, 2007. + date_publication: '2024-02-14' + bug_reports: '' + url: https://www.jstatsoft.org/v21/i02 + url_cran: https://CRAN.R-project.org/package=waved + url_git: '' +WaveletANN: + version: 0.1.2 + title: Wavelet ANN Model + maintainer: Dr. Ranjit Kumar Paul + description: 'The wavelet and ANN technique have been combined to reduce the effect + of data noise. This wavelet-ANN conjunction model is able to forecast time series + data with better accuracy than the traditional time series model. This package + fits hybrid Wavelet ANN model for time series forecasting using algorithm by Anjoy + and Paul (2017) .' + date_publication: '2022-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletANN + url_git: '' +WaveletArima: + version: 0.1.2 + title: Wavelet-ARIMA Model for Time Series Forecasting + maintainer: Dr. Ranjit Kumar Paul + description: Noise in the time-series data significantly affects the accuracy of + the ARIMA model. Wavelet transformation decomposes the time series data into subcomponents + to reduce the noise and help to improve the model performance. The wavelet-ARIMA + model can achieve higher prediction accuracy than the traditional ARIMA model. + This package provides Wavelet-ARIMA model for time series forecasting based on + the algorithm by Aminghafari and Poggi (2012) and Paul and Anjoy (2018) + . + date_publication: '2022-07-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletArima + url_git: '' +WaveletComp: + version: '1.1' + title: Computational Wavelet Analysis + maintainer: Angi Roesch + description: Wavelet analysis and reconstruction of time series, cross-wavelets + and phase-difference (with filtering options), significance with simulation algorithms. + date_publication: '2018-03-18' + bug_reports: '' + url: Guidebookletathttp://www.hs-stat.com/projects/WaveletComp/WaveletComp_guided_tour.pdf + url_cran: https://CRAN.R-project.org/package=WaveletComp + url_git: '' +WaveletETS: + version: 0.1.0 + title: Wavelet Based Error Trend Seasonality Model + maintainer: Dr. Md Yeasin + description: ETS stands for Error, Trend, and Seasonality, and it is a popular time + series forecasting method. Wavelet decomposition can be used for denoising, compression, + and feature extraction of signals. By removing the high-frequency components, + wavelet decomposition can remove noise from the data while preserving important + features. A hybrid Wavelet ETS (Error Trend-Seasonality) model has been developed + for time series forecasting using algorithm of Anjoy and Paul (2017) . + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletETS + url_git: '' +WaveletGARCH: + version: 0.1.1 + title: Fit the Wavelet-GARCH Model to Volatile Time Series Data + maintainer: Dr. Ranjit Kumar Paul + description: Fits the combination of Wavelet-GARCH model for time series forecasting + using algorithm by Paul (2015) . + date_publication: '2020-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletGARCH + url_git: '' +WaveletGBM: + version: 0.1.0 + title: Wavelet Based Gradient Boosting Method + maintainer: Dr. Ranjit Kumar Paul + description: Wavelet decomposition method is very useful for modelling noisy time + series data. Wavelet decomposition using 'haar' algorithm has been implemented + to developed hybrid Wavelet GBM (Gradient Boosting Method) model for time series + forecasting using algorithm by Anjoy and Paul (2017) . + date_publication: '2023-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletGBM + url_git: '' +WaveletKNN: + version: 0.1.0 + title: Wavelet Based K-Nearest Neighbor Model + maintainer: Dr. Md Yeasin + description: The employment of the Wavelet decomposition technique proves to be + highly advantageous in the modelling of noisy time series data. Wavelet decomposition + technique using the "haar" algorithm has been incorporated to formulate a hybrid + Wavelet KNN (K-Nearest Neighbour) model for time series forecasting, as proposed + by Anjoy and Paul (2017) . + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletKNN + url_git: '' +WaveletLSTM: + version: 0.1.0 + title: Wavelet Based LSTM Model + maintainer: Dr. Md Yeasin + description: A wavelet-based LSTM model is a type of neural network architecture + that uses wavelet technique to pre-process the input data before passing it through + a Long Short-Term Memory (LSTM) network. The wavelet-based LSTM model is a powerful + approach that combines the benefits of wavelet analysis and LSTM networks to improve + the accuracy of predictions in various applications. This package has been developed + using the algorithm of Anjoy and Paul (2017) and Paul and Garai (2021) + . + date_publication: '2023-04-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletLSTM + url_git: '' +WaveletML: + version: 0.1.0 + title: Wavelet Decomposition Based Hybrid Machine Learning Models + maintainer: Mr. Sandip Garai + description: Wavelet decomposes a series into multiple sub series called detailed + and smooth components which helps to capture volatility at multi resolution level + by various models. Two hybrid Machine Learning (ML) models (Artificial Neural + Network and Support Vector Regression have been used) have been developed in combination + with stochastic models, feature selection, and optimization algorithms for prediction + of the data. The algorithms have been developed following Paul and Garai (2021) . + date_publication: '2023-04-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletML + url_git: '' +WaveletMLbestFL: + version: 0.1.0 + title: The Best Wavelet Filter-Level for Prepared Wavelet-Based Models + maintainer: Mr. Sandip Garai + description: 'Four filters have been chosen namely ''haar'', ''c6'', ''la8'', and + ''bl14'' (Kindly refer to ''wavelets'' in ''CRAN'' repository for more supported + filters). Levels of decomposition are 2, 3, 4, etc. up to maximum decomposition + level which is ceiling value of logarithm of length of the series base 2. For + each combination two models are run separately. Results are stored in ''input''. + First five metrics are expected to be minimum and last three metrics are expected + to be maximum for a model to be considered good. Firstly, every metric value (among + first five) is searched in every columns and minimum values are denoted as ''MIN'' + and other values are denoted as ''NA''. Secondly, every metric (among last three) + is searched in every columns and maximum values are denoted as ''MAX'' and other + values are denoted as ''NA''. ''output'' contains the similar number of rows (which + is 8) and columns (which is number filter-level combinations) as of ''input''. + Values in ''output'' are corresponding ''NA'', ''MIN'' or ''MAX''. Finally, the + column containing minimum number of ''NA'' values is denoted as the best (''FL''). + In special case, if two columns having equal ''NA'', it has been checked among + these two columns which one is having least ''NA'' in first five rows and has + been inferred as the best. ''FL_metrics_values'' are the corresponding metrics + values. ''WARIGAANbest'' is the data frame (dimension: 1*8) containing different + metrics of the best filter-level combination. More details can be found in Garai + and others (2023) .' + date_publication: '2023-04-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletMLbestFL + url_git: '' +WaveletRF: + version: 0.1.0 + title: Wavelet-RF Hybrid Model for Time Series Forecasting + maintainer: Ranjit Kumar Paul + description: 'The Wavelet Decomposition followed by Random Forest Regression (RF) + models have been applied for time series forecasting. The maximum overlap discrete + wavelet transform (MODWT) algorithm was chosen as it works for any length of the + series. The series is first divided into training and testing sets. In each of + the wavelet decomposed series, the supervised machine learning approach namely + random forest was employed to train the model. This package also provides accuracy + metrics in the form of Root Mean Square Error (RMSE) and Mean Absolute Prediction + Error (MAPE). This package is based on the algorithm of Ding et al. (2021) .' + date_publication: '2022-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletRF + url_git: '' +wavelets: + version: 0.3-0.2 + title: |- + Functions for Computing Wavelet Filters, Wavelet Transforms and + Multiresolution Analyses + maintainer: Eric Aldrich + description: |- + Contains functions for computing and plotting + discrete wavelet transforms (DWT) and maximal overlap discrete + wavelet transforms (MODWT), as well as their inverses. + Additionally, it contains functionality for computing and + plotting wavelet transform filters that are used in the above + decompositions as well as multiresolution analyses. + date_publication: '2020-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wavelets + url_git: '' +WaveletSVR: + version: 0.1.0 + title: Wavelet-SVR Hybrid Model for Time Series Forecasting + maintainer: Ranjit Kumar Paul + description: 'The main aim of this package is to combine the advantage of wavelet + and support vector machine models for time series forecasting. This package also + gives the accuracy measurements in terms of RMSE and MAPE. This package fits the + hybrid Wavelet SVR model for time series forecasting The main aim of this package + is to combine the advantage of wavelet and Support Vector Regression (SVR) models + for time series forecasting. This package also gives the accuracy measurements + in terms of Root Mean Square Error (RMSE) and Mean Absolute Prediction Error (MAPE). + This package is based on the algorithm of Raimundo and Okamoto (2018) .' + date_publication: '2022-01-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaveletSVR + url_git: '' +wavemulcor: + version: 3.1.2 + title: |- + Wavelet Routines for Global and Local Multiple Regression and + Correlation + maintainer: Javier Fernandez-Macho + description: |- + Wavelet routines that calculate single sets of wavelet + multiple regressions and correlations, and cross-regressions and + cross-correlations from a multivariate time series. Dynamic versions + of the routines allow the wavelet local multiple (cross-)regressions + and (cross-)correlations to evolve over time. + date_publication: '2021-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wavemulcor + url_git: '' +waver: + version: 0.3.0 + title: Calculate Fetch and Wave Energy + maintainer: Philippe Marchand + description: |- + Functions for calculating the + fetch (length of open water distance along given directions) + and estimating wave energy from wind and wave monitoring data. + date_publication: '2023-09-24' + bug_reports: https://github.com/pmarchand1/waver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=waver + url_git: https://github.com/pmarchand1/waver +WaverideR: + version: 0.3.2 + title: Extracting Signals from Wavelet Spectra + maintainer: Michiel Arts + description: 'The continuous wavelet transform enables the observation of transient/non-stationary + cyclicity in time-series. The goal of cyclostratigraphic studies is to define + frequency/period in the depth/time domain. By conducting the continuous wavelet + transform on cyclostratigraphic data series one can observe and extract cyclic + signals/signatures from signals. These results can then be visualized and interpreted + enabling one to identify/interpret cyclicity in the geological record, which can + be used to construct astrochronological age-models and identify and interpret + cyclicity in past and present climate systems. The ''WaverideR'' R package builds + upon existing literature and existing codebase. The list of articles which are + relevant can be grouped in four subjects; cyclostratigraphic data analysis,example + data sets,the (continuous) wavelet transform and astronomical solutions. References + for the cyclostratigraphic data analysis articles are: Stephen Meyers (2019) . + Mingsong Li, Linda Hinnov, Lee Kump (2019) Stephen + Meyers (2012) Mingsong Li, Lee R. Kump, Linda A. Hinnov, + Michael E. Mann (2018) . Wouters, S., Crucifix, + M., Sinnesael, M., Da Silva, A.C., Zeeden, C., Zivanovic, M., Boulvain, F., Devleeschouwer, + X. (2022) . Wouters, S., Da Silva, A.-C., + Boulvain, F., and Devleeschouwer, X. (2021) . Huang, + Norden E., Zhaohua Wu, Steven R. Long, Kenneth C. Arnold, Xianyao Chen, and Karin + Blank (2009) . Cleveland, W. S. (1979) + Hurvich, C.M., Simonoff, J.S., and Tsai, C.L. (1998) , + Golub, G., Heath, M. and Wahba, G. (1979) . References for + the example data articles are: Damien Pas, Linda Hinnov, James E. (Jed) Day, Kenneth + Kodama, Matthias Sinnesael, Wei Liu (2018) . Steinhilber, + Friedhelm, Abreu, Jacksiel, Beer, Juerg , Brunner, Irene, Christl, Marcus, Fischer, + Hubertus, HeikkilA, U., Kubik, Peter, Mann, Mathias, Mccracken, K. , Miller, + Heinrich, Miyahara, Hiroko, Oerter, Hans , Wilhelms, Frank. (2012 . + Christian Zeeden, Frederik Hilgen, Thomas Westerhold, Lucas Lourens, Ursula Röhl, + Torsten Bickert (2013) . References for the + (continuous) wavelet transform articles are: Morlet, Jean, Georges Arens, Eliane + Fourgeau, and Dominique Glard (1982a) . J. Morlet, G. + Arens, E. Fourgeau, D. Giard (1982b) . Torrence, C., and + G. P. Compo (1998), + Gouhier TC, Grinsted A, Simko V (2021) . + Angi Roesch and Harald Schmidbauer (2018) . + Russell, Brian, and Jiajun Han (2016). + Gabor, Dennis (1946) . J. Laskar, + P. Robutel, F. Joutel, M. Gastineau, A.C.M. Correia, and B. Levrard, B. (2004) + . Laskar, J., Fienga, A., Gastineau, M., Manche, + H. (2011a) . References for the astronomical + solutions articles are: Laskar, J., Gastineau, M., Delisle, J.-B., Farres, A., + Fienga, A. (2011b . J. Laskar (2019) . + Zeebe, Richard E (2017) . Zeebe, R. E. and Lourens, + L. J. (2019) . Richard E. Zeebe Lucas J. Lourens + (2022) .' + date_publication: '2023-09-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaverideR + url_git: https://github.com/stratigraphy/WaverideR +WaverR: + version: '1.0' + title: Data Estimation using Weighted Averages of Multiple Regressions + maintainer: Olivia Cheronet + description: For multivariate datasets, this function enables the estimation of + missing data using the Weighted AVERage of all possible Regressions using the + data available. + date_publication: '2016-02-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WaverR + url_git: '' +waves: + version: 0.2.5 + title: Vis-NIR Spectral Analysis Wrapper + maintainer: Jenna Hershberger + description: |- + Originally designed application in the context of + resource-limited plant research and breeding programs, 'waves' + provides an open-source solution to spectral data processing and model + development by bringing useful packages together into a streamlined + pipeline. This package is wrapper for functions related to the + analysis of point visible and near-infrared reflectance measurements. + It includes visualization, filtering, aggregation, preprocessing, + cross-validation set formation, model training, and prediction + functions to enable open-source association of spectral and reference + data. This package is documented in a peer-reviewed manuscript in the + Plant Phenome Journal . Specialized + cross-validation schemes are described in detail in Jarquín et al. + (2017) . Example data is from + Ikeogu et al. (2017) . + date_publication: '2023-12-12' + bug_reports: https://github.com/GoreLab/waves/issues + url: '' + url_cran: https://CRAN.R-project.org/package=waves + url_git: https://github.com/GoreLab/waves +WaveSampling: + version: 0.1.4 + title: Weakly Associated Vectors (WAVE) Sampling + maintainer: Raphaël Jauslin + description: |- + Spatial data are generally auto-correlated, meaning that if two + units selected are close to each other, then it is likely that they share the + same properties. For this reason, when sampling in the population it is often + needed that the sample is well spread over space. A new method to draw a sample + from a population with spatial coordinates is proposed. This method is called + wave (Weakly Associated Vectors) sampling. It uses the less correlated vector + to a spatial weights matrix to update the inclusion probabilities vector + into a sample. For more details see Raphaël Jauslin and Yves Tillé (2019) . + date_publication: '2025-02-08' + bug_reports: https://github.com/RJauslin/WaveSampling/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WaveSampling + url_git: https://github.com/RJauslin/WaveSampling +waveslim: + version: 1.8.5 + title: |- + Basic Wavelet Routines for One-, Two-, and Three-Dimensional + Signal Processing + maintainer: Brandon Whitcher + description: |- + Basic wavelet routines for time series (1D), image (2D) and array + (3D) analysis. The code provided here is based on wavelet methodology + developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); + the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as + implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). + All figures in chapters 4-7 of GSW (2001) are reproducible using this package + and R code available at the book website(s) below. + date_publication: '2024-06-04' + bug_reports: '' + url: https://waveslim.blogspot.com + url_cran: https://CRAN.R-project.org/package=waveslim + url_git: '' +wavethresh: + version: 4.7.3 + title: Wavelets Statistics and Transforms + maintainer: Guy Nason + description: |- + Performs 1, 2 and 3D real and complex-valued wavelet transforms, + nondecimated transforms, wavelet packet transforms, nondecimated + wavelet packet transforms, multiple wavelet transforms, + complex-valued wavelet transforms, wavelet shrinkage for + various kinds of data, locally stationary wavelet time series, + nonstationary multiscale transfer function modeling, density + estimation. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wavethresh + url_git: '' +wavScalogram: + version: 1.1.3 + title: Wavelet Scalogram Tools for Time Series Analysis + maintainer: Vicente J. Bolos + description: 'Provides scalogram based wavelet tools for time series analysis: wavelet + power spectrum, scalogram, windowed scalogram, windowed scalogram difference (see + Bolos et al. (2017) ), scale index and windowed + scale index (Benitez et al. (2010) ).' + date_publication: '2024-03-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wavScalogram + url_git: '' +waydown: + version: 1.1.0 + title: |- + Computation of Approximate Potentials for Weakly Non-Gradient + Fields + maintainer: Pablo Rodríguez-Sánchez + description: |- + Computation of approximate potentials for both gradient and non + gradient fields. It is known from physics that only gradient fields, also + known as conservative, have a well defined potential function. Here we + present an algorithm, based on the classical Helmholtz decomposition, to + obtain an approximate potential function for non gradient fields. + More information in + Rodríguez-Sánchez (2020) . + date_publication: '2021-03-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=waydown + url_git: '' +WayFindR: + version: 0.1.2 + title: Computing Graph Structures on WikiPathways + maintainer: Kevin R. Coombes + description: |- + Converts pathways from 'WikiPathways' GPML format into + 'igraph' objects. Includes tools to find all cycles in the + resulting graphs and determine which ones involve negative feedback + (inhibition). + date_publication: '2024-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WayFindR + url_git: http://oompa.r-forge.r-project.org/ +waywiser: + version: 0.6.1 + title: Ergonomic Methods for Assessing Spatial Models + maintainer: Michael Mahoney + description: |- + Assessing predictive models of spatial data can be + challenging, both because these models are typically built for + extrapolating outside the original region represented by training data + and due to potential spatially structured errors, with "hot spots" of + higher than expected error clustered geographically due to spatial + structure in the underlying data. Methods are provided for assessing + models fit to spatial data, including approaches for measuring the + spatial structure of model errors, assessing model predictions at + multiple spatial scales, and evaluating where predictions can be made + safely. Methods are particularly useful for models fit using the + 'tidymodels' framework. Methods include Moran's I ('Moran' (1950) + ), Geary's C ('Geary' (1954) + ), Getis-Ord's G ('Ord' and 'Getis' (1995) + ), agreement coefficients from + 'Ji' and Gallo (2006) (), agreement + metrics from 'Willmott' (1981) () + and 'Willmott' 'et' 'al'. (2012) (), an + implementation of the area of applicability methodology from 'Meyer' + and 'Pebesma' (2021) (), and an + implementation of multi-scale assessment as described in 'Riemann' + 'et' 'al'. (2010) (). + date_publication: '2025-02-17' + bug_reports: https://github.com/ropensci/waywiser/issues + url: https://docs.ropensci.org/waywiser/ + url_cran: https://CRAN.R-project.org/package=waywiser + url_git: https://github.com/ropensci/waywiser +wbacon: + version: 0.6-2 + title: Weighted BACON Algorithms + maintainer: Tobias Schoch + description: |- + The BACON algorithms are methods for multivariate outlier + nomination (detection) and robust linear regression by Billor, Hadi, + and Velleman (2000) . The extension + to weighted problems is due to Beguin and Hulliger (2008) + ; see + also . + date_publication: '2024-09-07' + bug_reports: https://github.com/tobiasschoch/wbacon/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wbacon + url_git: https://github.com/tobiasschoch/wbacon +wbids: + version: 1.0.0 + title: |- + Seamless Access to World Bank International Debt Statistics + (IDS) + maintainer: Teal Emery + description: |- + Access and analyze the World Bank's International Debt Statistics + (IDS) . + IDS provides creditor-debtor relationships between countries, regions, and + institutions. 'wbids' enables users to download, process and work with IDS + series across multiple geographies, counterparts, and time periods. + date_publication: '2025-02-08' + bug_reports: https://github.com/teal-insights/r-wbids/issues + url: https://teal-insights.github.io/r-wbids/ + url_cran: https://CRAN.R-project.org/package=wbids + url_git: https://github.com/teal-insights/r-wbids/ +wbs: + version: 1.4.1 + title: Wild Binary Segmentation for Multiple Change-Point Detection + maintainer: Rafal Baranowski + description: |- + Provides efficient implementation of the Wild Binary Segmentation and Binary + Segmentation algorithms for estimation of the number and locations of + multiple change-points in the piecewise constant function plus Gaussian + noise model. + date_publication: '2024-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wbs + url_git: '' +wbsd: + version: 1.0.0 + title: Wild Bootstrap Size Diagnostics + maintainer: David Preinerstorfer + description: Implements the diagnostic "theta" developed in Poetscher and Preinerstorfer + (2020) "How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?" . + This diagnostic can be used to detect and weed out bootstrap-based procedures + that provably have size equal to one for a given testing problem. The implementation + covers a large variety of bootstrap-based procedures, cf. the above mentioned + article for details. A function for computing bootstrap p-values is provided. + date_publication: '2020-05-14' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wbsd + url_git: '' +wbstats: + version: 1.0.4 + title: |- + Programmatic Access to Data and Statistics from the World Bank + API + maintainer: Jesse Piburn + description: Search and download data from the World Bank Data API. + date_publication: '2020-12-05' + bug_reports: https://github.com/nset-ornl/wbstats/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wbstats + url_git: https://github.com/nset-ornl/wbstats +wbsts: + version: '2.1' + title: Multiple Change-Point Detection for Nonstationary Time Series + maintainer: Karolos Korkas + description: |- + Implements detection for the number and locations of + the change-points in a time series using the Wild Binary Segmentation and + the Locally Stationary Wavelet model of Korkas and Fryzlewicz (2017) . + date_publication: '2020-06-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wbsts + url_git: '' +wbwdi: + version: 1.0.0 + title: Seamless Access to World Bank World Development Indicators (WDI) + maintainer: Christoph Scheuch + description: |- + Access and analyze the World Bank’s World Development Indicators + (WDI) using the corresponding API . + WDI provides more than 24,000 country or region-level indicators for various + contexts. 'wbwdi' enables users to download, process and work with WDI + series across multiple countries, aggregates, and time periods. + date_publication: '2025-02-25' + bug_reports: https://github.com/tidy-intelligence/r-wbwdi/issues + url: https://tidy-intelligence.github.io/r-wbwdi/ + url_cran: https://CRAN.R-project.org/package=wbwdi + url_git: https://github.com/tidy-intelligence/r-wbwdi +wcde: + version: 0.0.7 + title: |- + Download Data from the Wittgenstein Centre Human Capital Data + Explorer + maintainer: Guy J. Abel + description: Download and plot education specific demographic data from the Wittgenstein + Centre for Demography and Human Capital Data Explorer . + date_publication: '2024-02-13' + bug_reports: https://github.com/guyabel/wcde/issues/ + url: https://guyabel.github.io/wcde/ + url_cran: https://CRAN.R-project.org/package=wcde + url_git: '' +WCE: + version: 1.0.3 + title: Weighted Cumulative Exposure Models + maintainer: Marie-Pierre Sylvestre + description: A flexible method for modeling cumulative effects of time-varying exposures, + weighted according to their relative proximity in time, and represented by time-dependent + covariates. The current implementation estimates the weight function in the Cox + proportional hazards model. The function that assigns weights to doses taken in + the past is estimated using cubic regression splines. + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WCE + url_git: '' +wcep: + version: 1.0.2 + title: Survival Analysis for Weighted Composite Endpoints + maintainer: Sarah Rathwell + description: Analyze given data frame with multiple endpoints and return Kaplan-Meier + survival probabilities together with the specified confidence interval. See Nabipoor + M, Westerhout CM, Rathwell S, and Bakal JA (2023) . + date_publication: '2023-12-19' + bug_reports: https://github.com/sarah-0k/wcep + url: '' + url_cran: https://CRAN.R-project.org/package=wcep + url_git: https://github.com/sarah-0k/wcep +WCluster: + version: 1.2.0 + title: Clustering and PCA with Weights, and Data Nuggets Clustering + maintainer: Yajie Duan + description: |- + K-means clustering, hierarchical clustering, and PCA with observational + weights and/or variable weights. It also includes the corresponding functions + for data nuggets which serve as representative samples of large datasets. + Cherasia et al., (2022) . + Amaratunga et al., (2009) . + date_publication: '2023-11-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WCluster + url_git: '' +WCM: + version: 0.2.2 + title: |- + Water Cloud Model (WCM) for the Simulation of Leaf Area Index + (LAI) and Soil Moisture (SM) from Microwave Backscattering + maintainer: Ujjwal Singh + description: Retrieval the leaf area index (LAI) and soil moisture (SM) from microwave + backscattering data using water cloud model (WCM) model . The WCM algorithm attributed + to Pervot et al.(1993) . The authors are grateful + to SAC, ISRO, Ahmedabad for providing financial support to Dr. Prashant K Srivastava + to conduct this research work. + date_publication: '2020-04-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WCM + url_git: '' +Wcompo: + version: '1.0' + title: |- + Semiparametric Proportional Means Regression of Weighted + Composite Endpoint + maintainer: Lu Mao + description: |- + Implements inferential and graphic procedures for the semiparametric proportional + means regression of weighted composite endpoint of recurrent event and death (Mao and Lin, + 2016, ). + date_publication: '2021-11-30' + bug_reports: '' + url: https://sites.google.com/view/lmaowisc/ + url_cran: https://CRAN.R-project.org/package=Wcompo + url_git: '' +wconf: + version: 1.2.0 + title: Weighted Confusion Matrix + maintainer: Alexandru Monahov + description: |- + Allows users to create weighted confusion matrices and accuracy + metrics that help with the model selection process for classification + problems, where distance from the correct category is important. The + package includes several weighting schemes which can be parameterized, as + well as custom configuration options. Furthermore, users can decide + whether they wish to positively or negatively affect the accuracy score + as a result of applying weights to the confusion matrix. Functions are + included to calculate accuracy metrics for imbalanced data. Finally, + 'wconf' integrates well with the 'caret' package, but it can also work + standalone when provided data in matrix form. + References: + Kuhn, M. (2008) "Building Perspective Models in R Using the caret Package" + + Monahov, A. (2021) "Model Evaluation with Weighted Threshold Optimization + (and the mewto R package)" + Monahov, A. (2024) "Improved Accuracy Metrics for Classification with + Imbalanced Data and Where Distance from the Truth Matters, with the wconf R + Package" + Starovoitov, V., Golub, Y. (2020). New Function for Estimating Imbalanced + Data Classification Results. Pattern Recognition and Image Analysis, 295–302 + Van de Velden, M., Iodice D'Enza, A., Markos, A., Cavicchia, C. (2023) + "A general framework for implementing distances for categorical variables" + . + date_publication: '2024-08-17' + bug_reports: '' + url: https://www.alexandrumonahov.eu.org/projects + url_cran: https://CRAN.R-project.org/package=wconf + url_git: '' +wCorr: + version: 1.9.8 + title: Weighted Correlations + maintainer: Paul Bailey + description: Calculates Pearson, Spearman, polychoric, and polyserial correlation + coefficients, in weighted or unweighted form. The package implements tetrachoric + correlation as a special case of the polychoric and biserial correlation as a + specific case of the polyserial. + date_publication: '2023-08-19' + bug_reports: https://github.com/American-Institutes-for-Research/wCorr/issues + url: https://american-institutes-for-research.github.io/wCorr/ + url_cran: https://CRAN.R-project.org/package=wCorr + url_git: '' +wcox: + version: '1.0' + title: |- + Weights to Correct for Outcome Dependent Sampling in Time to + Event Data + maintainer: Vera Arntzen + description: A new inverse probability of selection weighted Cox model to deal with + outcome-dependent sampling in survival analysis. + date_publication: '2023-05-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wcox + url_git: '' +WDI: + version: 2.7.8 + title: World Development Indicators and Other World Bank Data + maintainer: Vincent Arel-Bundock + description: Search and download data from over 40 databases hosted by the World + Bank, including the World Development Indicators ('WDI'), International Debt Statistics, + Doing Business, Human Capital Index, and Sub-national Poverty indicators. + date_publication: '2022-09-25' + bug_reports: '' + url: https://vincentarelbundock.github.io/WDI/ + url_cran: https://CRAN.R-project.org/package=WDI + url_git: '' +wdiEF: + version: 1.0.3 + title: |- + Calculation of the Water Deficit Index (WDI) and the Evaporative + Fraction (EF) on Rasters + maintainer: Gaelle Hamelin + description: |- + Calculates the Water Deficit Index (WDI) and the Evaporative Fraction (EF) using geospatial data, + such as fractional vegetation cover (FVC) and surface-air temperature difference (TS-TA). + Terms like "raster", "CRS" are part of standard geospatial terminology. + date_publication: '2025-02-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wdiEF + url_git: '' +wdm: + version: 0.2.6 + title: Weighted Dependence Measures + maintainer: Thomas Nagler + description: |- + Provides efficient implementations of weighted dependence measures + and related asymptotic tests for independence. Implemented measures are + the Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, and + Hoeffding's D; see, e.g., Nelsen (2006) and + Hollander et al. (2015, ISBN:9780470387375). + date_publication: '2025-01-07' + bug_reports: https://github.com/tnagler/wdm-r/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wdm + url_git: https://github.com/tnagler/wdm-r +wdman: + version: 0.2.6 + title: '''Webdriver''/''Selenium'' Binary Manager' + maintainer: Ju Yeong Kim + description: |- + There are a number of binary files associated with the + 'Webdriver'/'Selenium' project. This package provides functions to download + these binaries and to manage processes involving them. + date_publication: '2022-09-01' + bug_reports: https://github.com/ropensci/wdman/issues + url: https://docs.ropensci.org/wdman/ + url_cran: https://CRAN.R-project.org/package=wdman + url_git: https://github.com/ropensci/wdman +wdnet: + version: 1.2.3 + title: Weighted and Directed Networks + maintainer: Yelie Yuan + description: |- + Assortativity coefficients, centrality measures, + and clustering coefficients for weighted and directed networks. + Rewiring unweighted networks with given assortativity coefficients. + Generating general preferential attachment networks. + date_publication: '2024-03-03' + bug_reports: https://gitlab.com/wdnetwork/wdnet/-/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wdnet + url_git: https://gitlab.com/wdnetwork/wdnet +wdnr.gis: + version: 0.1.5 + title: Pull Spatial Layers from 'WDNR ArcGIS REST API' + maintainer: Paul Frater + description: |- + Functions for finding and pulling data from the + 'Wisconsin Department of Natural Resources ArcGIS REST APIs' + and + . + date_publication: '2023-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wdnr.gis + url_git: '' +wdpar: + version: 1.3.8 + title: Interface to the World Database on Protected Areas + maintainer: Jeffrey O Hanson + description: |- + Fetch and clean data from the World Database on Protected + Areas (WDPA) and the World Database on Other Effective Area-Based + Conservation Measures (WDOECM). Data is obtained from Protected Planet + . To augment data cleaning procedures, + users can install the 'prepr' R package (available at + ). For more information on this + package, see Hanson (2022) . + date_publication: '2024-10-07' + bug_reports: https://github.com/prioritizr/wdpar/issues + url: https://prioritizr.github.io/wdpar/ + url_cran: https://CRAN.R-project.org/package=wdpar + url_git: https://github.com/prioritizr/wdpar +weaana: + version: 0.1.1 + title: Analysis the Weather Data + maintainer: Bangyou Zheng + description: |- + Functions are collected to analyse weather data for agriculture + purposes including to read weather records in multiple formats, + calculate extreme climate index. + date_publication: '2021-09-27' + bug_reports: https://github.com/byzheng/weaana/issues + url: https://weaana.bangyou.me/ + url_cran: https://CRAN.R-project.org/package=weaana + url_git: https://github.com/byzheng/weaana +weakARMA: + version: 1.0.3 + title: Tools for the Analysis of Weak ARMA Models + maintainer: Julien Yves Rolland + description: |- + Numerous time series admit autoregressive moving average (ARMA) + representations, in which the errors are uncorrelated but not necessarily + independent. + These models are called weak ARMA by opposition to the standard ARMA models, + also called strong ARMA models, in which the error terms are supposed to be + independent and identically distributed (iid). + This package allows the study of nonlinear time series models through weak + ARMA representations. + It determines identification, estimation and validation for ARMA models and + for AR and MA models in particular. + Functions can also be used in the strong case. + This package also works on white noises by omitting arguments 'p', 'q', 'ar' + and 'ma'. + See Francq, C. and Zakoïan, J. (1998) and + Boubacar Maïnassara, Y. and Saussereau, B. (2018) + for more details. + date_publication: '2022-04-04' + bug_reports: https://plmlab.math.cnrs.fr/jrolland/weakARMA/-/issues + url: https://plmlab.math.cnrs.fr/jrolland/weakARMA + url_cran: https://CRAN.R-project.org/package=weakARMA + url_git: '' +wearables: + version: 0.8.1 + title: Tools to Read and Convert Wearables Data + maintainer: Peter de Looff + description: |2- + + Package to read Empatica E4 data, perform several transformations, perform signal + processing and analyses, including batch analyses. + date_publication: '2021-12-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wearables + url_git: '' +weatherindices: + version: 0.1.0 + title: Calculate Weather Indices + maintainer: Akhilesh Kumar Gupta + description: Weather indices represent the overall weekly effect of a weather variable + on crop yield throughout the cropping season. This package contains functions + that can convert the weekly weather data into yearly weighted Weather indices + with weights being the correlation coefficient between weekly weather data over + the years and crop yield over the years. This can be done for an individual weather + variable and for two weather variables at a time as the interaction effect. This + method was first devised by Jain, RC, Agrawal R, and Jha, MP (1980), "Effect of + climatic variables on rice yield and its forecast",MAUSAM, 31(4), 591–596, . + Later, the method have been used by various researchers and the latest can found + in Gupta, AK, Sarkar, KA, Dhakre, DS, & Bhattacharya, D (2022), "Weather Based + Potato Yield Modelling using Statistical and Machine Learning Technique",Environment + and Ecology, 40(3B), 1444–1449,. + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weatherindices + url_git: '' +weathermetrics: + version: 1.2.2 + title: Functions to Convert Between Weather Metrics + maintainer: Brooke Anderson + description: |- + Functions to convert between weather metrics, including conversions + for metrics of temperature, air moisture, wind speed, and precipitation. + This package also includes functions to calculate the heat index from + air temperature and air moisture. + date_publication: '2016-05-19' + bug_reports: https://github.com/geanders/weathermetrics/issues + url: '' + url_cran: https://CRAN.R-project.org/package=weathermetrics + url_git: https://github.com/geanders/weathermetrics/ +weatherOz: + version: 1.0.0 + title: An API Client for Australian Weather and Climate Data Resources + maintainer: Rodrigo Pires + description: |- + Provides automated downloading, parsing and formatting of + weather data for Australia through API endpoints provided by the + Department of Primary Industries and Regional Development ('DPIRD') of + Western Australia and by the Science and Technology Division of the + Queensland Government's Department of Environment and Science ('DES'). + As well as the Bureau of Meteorology ('BOM') of the Australian + government precis and coastal forecasts, agriculture bulletin data, + and downloading and importing radar and satellite imagery files. + 'DPIRD' weather data are accessed through public 'APIs' provided by + 'DPIRD', , providing + access to weather station data from the 'DPIRD' weather station + network. Australia-wide weather data are based on data from the + Australian Bureau of Meteorology ('BOM') data and accessed through + 'SILO' (Scientific Information for Land Owners) Jeffrey et al. (2001) + . 'DPIRD' data are made available + under a Creative Commons Attribution 3.0 Licence (CC BY 3.0 AU) + license . + SILO data are released under a Creative Commons Attribution 4.0 + International licence (CC BY 4.0) + . 'BOM' data are (c) + Australian Government Bureau of Meteorology and released under a + Creative Commons (CC) Attribution 3.0 licence or Public Access Licence + ('PAL') as appropriate, see + for further details. + date_publication: '2024-07-26' + bug_reports: https://github.com/ropensci/weatherOz/issues + url: https://docs.ropensci.org/weatherOz/ + url_cran: https://CRAN.R-project.org/package=weatherOz + url_git: https://github.com/ropensci/weatherOz/ +WeatherSentiment: + version: '1.0' + title: Comprehensive Analysis of Tweet Sentiments and Weather Data + maintainer: Leila Marvian Mashhad + description: |- + A comprehensive suite of functions for processing, + analyzing, and visualizing textual data from tweets is offered. + Users can clean tweets, analyze their sentiments, visualize data, + and examine the correlation between sentiments and environmental + data such as weather conditions. Main features include text processing, + sentiment analysis, data visualization, correlation analysis, and + synthetic data generation. Text processing involves cleaning and preparing + tweets by removing textual noise and irrelevant words. Sentiment analysis + extracts and accurately analyzes sentiments from tweet texts using advanced + algorithms. Data visualization creates various charts like word clouds + and sentiment polarity graphs for visual representation of data. Correlation + analysis examines and calculates the correlation between tweet sentiments + and environmental variables such as weather conditions. Additionally, + random tweets can be generated for testing and evaluating the performance + of analyses, empowering users to effectively analyze and interpret 'Twitter' + data for research and commercial purposes. + date_publication: '2024-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WeatherSentiment + url_git: '' +WebAnalytics: + version: 0.9.12 + title: Web Server Log Analysis + maintainer: Greg Hunt + description: Provides Apache and IIS log analytics for transaction performance, + client populations and workload definitions. + date_publication: '2023-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WebAnalytics + url_git: https://github.com/gregfrog/WebAnalytics +webchem: + version: 1.3.0 + title: Chemical Information from the Web + maintainer: Tamás Stirling + description: |- + Chemical information from around the web. This package interacts + with a suite of web services for chemical information. Sources include: Alan + Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver, + ChEBI, Chemical Translation Service, ChemSpider, ETOX, Flavornet, + NIST Chemistry WebBook, OPSIN, PubChem, SRS, Wikidata. + date_publication: '2023-06-09' + bug_reports: https://github.com/ropensci/webchem/issues + url: https://docs.ropensci.org/webchem/ + url_cran: https://CRAN.R-project.org/package=webchem + url_git: https://github.com/ropensci/webchem +webdav: + version: 0.1.4 + title: A Simple Interface for Interacting with 'WebDAV' Servers + maintainer: Andre Leite + description: |- + An easy-to-use interface for interacting with 'WebDAV' servers, + including 'OwnCloud'. It simplifies the use of 'WebDAV' methods such as COPY, MKCOL, MOVE, and others. + With built-in authentication and request handling, it allows for easy + management of files and directories over the 'WebDAV' protocol. + date_publication: '2025-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=webdav + url_git: +webdeveloper: + version: 1.0.5 + title: Functions for Web Development + maintainer: Timothy Conwell + description: |- + Organizational framework for web development in R including functions to + serve static and dynamic content via HTTP methods, includes the html5 package to + create HTML pages, and offers other utility functions for common tasks related + to web development. + date_publication: '2022-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=webdeveloper + url_git: '' +webdriver: + version: 1.0.6 + title: '''WebDriver'' Client for ''PhantomJS''' + maintainer: Gábor Csárdi + description: |- + A client for the 'WebDriver' 'API'. It allows driving a + (probably headless) web browser, and can be used to test web + applications, including 'Shiny' apps. In theory it works with any + 'WebDriver' implementation, but it was only tested with 'PhantomJS'. + date_publication: '2021-01-12' + bug_reports: https://github.com/rstudio/webdriver/issues + url: '' + url_cran: https://CRAN.R-project.org/package=webdriver + url_git: https://github.com/rstudio/webdriver +webexercises: + version: 1.1.0 + title: |- + Create Interactive Web Exercises in 'R Markdown' (Formerly + 'webex') + maintainer: Lisa DeBruine + description: |- + Functions for easily creating interactive web pages using + 'R Markdown' that students can use in self-guided learning. + date_publication: '2023-05-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=webexercises + url_git: https://github.com/psyteachr/webexercises +webfakes: + version: 1.3.2 + title: Fake Web Apps for HTTP Testing + maintainer: Gábor Csárdi + description: |- + Create a web app that makes it easier to test web clients + without using the internet. It includes a web app framework with path + matching, parameters and templates. Can parse various 'HTTP' request + bodies. Can send 'JSON' data or files from the disk. Includes a web + app that implements the 'httpbin.org' web service. + date_publication: '2025-01-11' + bug_reports: https://github.com/r-lib/webfakes/issues + url: https://webfakes.r-lib.org/ + url_cran: https://CRAN.R-project.org/package=webfakes + url_git: https://github.com/r-lib/webfakes +WebGestaltR: + version: 0.4.6 + title: Gene Set Analysis Toolkit WebGestaltR + maintainer: Yuxing Liao + description: The web version WebGestalt supports 12 + organisms, 354 gene identifiers and 321,251 function categories. Users can upload + the data and functional categories with their own gene identifiers. In addition + to the Over-Representation Analysis, WebGestalt also supports Gene Set Enrichment + Analysis and Network Topology Analysis. The user-friendly output report allows + interactive and efficient exploration of enrichment results. The WebGestaltR package + not only supports all above functions but also can be integrated into other pipeline + or simultaneously analyze multiple gene lists. + date_publication: '2023-06-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WebGestaltR + url_git: https://github.com/bzhanglab/WebGestaltR +webglobe: + version: 1.0.3 + title: 3D Interactive Globes + maintainer: Richard Barnes + description: Displays geospatial data on an interactive 3D globe in the web browser. + date_publication: '2020-09-15' + bug_reports: https://github.com/r-barnes/webglobe/ + url: '' + url_cran: https://CRAN.R-project.org/package=webglobe + url_git: https://github.com/r-barnes/webglobe/ +webmap: + version: 1.1.1 + title: Create Interactive Web Maps Using 'The National Map' Services + maintainer: Jason C. Fisher + description: |- + Creates interactive web maps using the 'JavaScript' 'Leaflet' + library with base layers of 'The National Map' ('TNM'). 'TNM' services + provide access to base geospatial information that describes the landscape + of the United States and its territories. This package is dependent on, and + intended to be used with, the 'leaflet' package. + date_publication: '2025-01-16' + bug_reports: https://code.usgs.gov/inl/webmap/-/issues + url: https://rconnect.usgs.gov/INLPO/webmap-main/ + url_cran: https://CRAN.R-project.org/package=webmap + url_git: '' +webmockr: + version: 2.0.0 + title: Stubbing and Setting Expectations on 'HTTP' Requests + maintainer: Scott Chamberlain + description: |- + Stubbing and setting expectations on 'HTTP' requests. + Includes tools for stubbing 'HTTP' requests, including expected + request conditions and response conditions. Match on + 'HTTP' method, query parameters, request body, headers and + more. Can be used for unit tests or outside of a testing + context. + date_publication: '2025-02-11' + bug_reports: https://github.com/ropensci/webmockr/issues + url: https://books.ropensci.org/http-testing/ + url_cran: https://CRAN.R-project.org/package=webmockr + url_git: https://github.com/ropensci/webmockr +webp: + version: 1.3.0 + title: A New Format for Lossless and Lossy Image Compression + maintainer: Jeroen Ooms + description: |- + Lossless webp images are 26% smaller in size compared to PNG. Lossy + webp images are 25-34% smaller in size compared to JPEG. This package reads + and writes webp images into a 3 (rgb) or 4 (rgba) channel bitmap array using + conventions from the 'jpeg' and 'png' packages. + date_publication: '2024-12-16' + bug_reports: https://github.com/jeroen/webp/issues + url: https://jeroen.r-universe.dev/webp + url_cran: https://CRAN.R-project.org/package=webp + url_git: '' +WebPower: + version: 0.9.4 + title: Basic and Advanced Statistical Power Analysis + maintainer: Zhiyong Zhang + description: This is a collection of tools for conducting both basic and advanced + statistical power analysis including correlation, proportion, t-test, one-way + ANOVA, two-way ANOVA, linear regression, logistic regression, Poisson regression, + mediation analysis, longitudinal data analysis, structural equation modeling and + multilevel modeling. It also serves as the engine for conducting power analysis + online at . + date_publication: '2023-10-13' + bug_reports: '' + url: https://webpower.psychstat.org + url_cran: https://CRAN.R-project.org/package=WebPower + url_git: '' +webr: + version: 0.1.5 + title: Data and Functions for Web-Based Analysis + maintainer: Keon-Woong Moon + description: |- + Several analysis-related functions for the book entitled + "Web-based Analysis without R in Your Computer"(written in Korean, ISBN 978-89-5566-185-9) + by Keon-Woong Moon. The main function plot.htest() shows the distribution of statistic for + the object of class 'htest'. + date_publication: '2020-01-26' + bug_reports: https://github.com/cardiomoon/webr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=webr + url_git: https://github.com/cardiomoon/webr +webreadr: + version: 0.4.0 + title: Tools for Reading Formatted Access Log Files + maintainer: Oliver Keyes + description: |- + R is used by a vast array of people for a vast array of purposes + - including web analytics. This package contains functions for consuming and + munging various common forms of request log, including the Common and Combined + Web Log formats and various Amazon access logs. + date_publication: '2016-01-23' + bug_reports: https://github.com/Ironholds/webreadr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=webreadr + url_git: https://github.com/Ironholds/webreadr +webSDM: + version: 1.1-5 + title: Including Known Interactions in Species Distribution Models + maintainer: Giovanni Poggiato + description: A collection of tools to fit and work with trophic Species Distribution + Models. Trophic Species Distribution Models combine knowledge of trophic interactions + with Bayesian structural equation models that model each species as a function + of its prey (or predators) and environmental conditions. It exploits the topological + ordering of the known trophic interaction network to predict species distribution + in space and/or time, where the prey (or predator) distribution is unavailable. + The method implemented by the package is described in Poggiato, Andréoletti, Pollock + and Thuiller (2022) . + date_publication: '2024-06-24' + bug_reports: https://github.com/giopogg/webSDM/issues + url: https://giopogg.github.io/webSDM/ + url_cran: https://CRAN.R-project.org/package=webSDM + url_git: https://github.com/giopogg/webSDM +websearchr: + version: 0.0.3 + title: Access Domains and Search Popular Websites + maintainer: Florian S. Schaffner + description: Functions that allow for accessing domains and a number of search engines. + date_publication: '2018-10-23' + bug_reports: https://github.com/fschaff/websearchr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=websearchr + url_git: https://github.com/fschaff/websearchr +webshot: + version: 0.5.5 + title: Take Screenshots of Web Pages + maintainer: Winston Chang + description: |- + Takes screenshots of web pages, including Shiny applications and R + Markdown documents. + date_publication: '2023-06-26' + bug_reports: https://github.com/wch/webshot/issues + url: https://wch.github.io/webshot/ + url_cran: https://CRAN.R-project.org/package=webshot + url_git: https://github.com/wch/webshot/ +webshot2: + version: 0.1.1 + title: Take Screenshots of Web Pages + maintainer: Winston Chang + description: |- + Takes screenshots of web pages, including Shiny applications + and R Markdown documents. 'webshot2' uses headless Chrome or Chromium + as the browser back-end. + date_publication: '2023-08-11' + bug_reports: https://github.com/rstudio/webshot2/issues + url: https://rstudio.github.io/webshot2/ + url_cran: https://CRAN.R-project.org/package=webshot2 + url_git: https://github.com/rstudio/webshot2 +websocket: + version: 1.4.2 + title: '''WebSocket'' Client Library' + maintainer: Winston Chang + description: |- + Provides a 'WebSocket' client interface for R. + 'WebSocket' is a protocol for low-overhead real-time communication: + . + date_publication: '2024-07-22' + bug_reports: https://github.com/rstudio/websocket/issues + url: '' + url_cran: https://CRAN.R-project.org/package=websocket + url_git: '' +webtrackR: + version: 0.3.1 + title: Preprocessing and Analyzing Web Tracking Data + maintainer: David Schoch + description: Data structures and methods to work with web tracking data. The functions + cover data preprocessing steps, enriching web tracking data with external information + and methods for the analysis of digital behavior as used in several academic papers + (e.g., Clemm von Hohenberg et al., 2023 ; Stier et + al., 2022 ). + date_publication: '2024-04-30' + bug_reports: https://github.com/schochastics/webtrackR/issues + url: https://schochastics.github.io/webtrackR/ + url_cran: https://CRAN.R-project.org/package=webtrackR + url_git: https://github.com/schochastics/webtrackR +webuse: + version: 0.1.3 + title: Import Stata 'webuse' Datasets + maintainer: Jodi Beggs + description: A Stata-style `webuse()` function for importing named datasets from + Stata's online collection. + date_publication: '2018-10-01' + bug_reports: https://github.com/leeper/webuse/issues + url: '' + url_cran: https://CRAN.R-project.org/package=webuse + url_git: https://github.com/leeper/webuse +webutils: + version: 1.2.2 + title: Utility Functions for Developing Web Applications + maintainer: Jeroen Ooms + description: |- + Parses http request data in application/json, multipart/form-data, + or application/x-www-form-urlencoded format. Includes example of hosting + and parsing html form data in R using either 'httpuv' or 'Rhttpd'. + date_publication: '2024-10-04' + bug_reports: https://github.com/jeroen/webutils/issues + url: https://jeroen.r-universe.dev/webutils + url_cran: https://CRAN.R-project.org/package=webutils + url_git: '' +wec: + version: 0.4-1 + title: Weighted Effect Coding + maintainer: Rense Nieuwenhuis + description: Provides functions to create factor variables with contrasts based + on weighted effect coding, and their interactions. In weighted effect coding the + estimates from a first order regression model show the deviations per group from + the sample mean. This is especially useful when a researcher has no directional + hypotheses and uses a sample from a population in which the number of observation + per group is different. + date_publication: '2017-10-31' + bug_reports: '' + url: http://www.ru.nl/sociology/mt/wec/downloads/ + url_cran: https://CRAN.R-project.org/package=wec + url_git: '' +weed: + version: 1.1.2 + title: Wrangler for Emergency Events Database + maintainer: Ram Kripa + description: Makes research involving EMDAT and related datasets easier. These Datasets + are manually filled and have several formatting and compatibility issues. Weed + aims to resolve these with its functions. + date_publication: '2023-10-16' + bug_reports: https://github.com/rammkripa/weed/issues + url: '' + url_cran: https://CRAN.R-project.org/package=weed + url_git: https://github.com/rammkripa/weed +WEGE: + version: 0.1.0 + title: A Metric to Rank Locations for Biodiversity Conservation + maintainer: Harith Farooq + description: |- + Calculates the WEGE (Weighted Endemism including Global + Endangerment index) index for a particular area. Additionally it also + calculates rasters of KBA's (Key Biodiversity Area) criteria (A1a, A1b, A1e, + and B1), Weighted endemism (WE), the EDGE (Evolutionarily Distinct and + Globally Endangered) score, Evolutionary Distinctiveness (ED) and Extinction + risk (ER). Farooq, H., Azevedo, J., Belluardo F., Nanvonamuquitxo, C., + Bennett, D., Moat, J., Soares, A., Faurby, S. & Antonelli, A. (2020) + . + date_publication: '2020-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WEGE + url_git: '' +wehoop: + version: 2.1.0 + title: Access Women's Basketball Play by Play Data + maintainer: Saiem Gilani + description: A utility for working with women's basketball data. A scraping and + aggregating interface for the WNBA Stats API and ESPN's + women's college basketball and WNBA statistics. It provides + users with the capability to access the game play-by-plays, box scores, standings + and results to analyze the data for themselves. + date_publication: '2024-07-21' + bug_reports: https://github.com/sportsdataverse/wehoop/issues + url: https://wehoop.sportsdataverse.org + url_cran: https://CRAN.R-project.org/package=wehoop + url_git: https://github.com/sportsdataverse/wehoop +WeibullFit: + version: 0.1.0 + title: |- + Fits and Plots a Dataset to the Weibull Probability Distribution + Function + maintainer: Thiago Martins + description: 'Provides a single function to fit data of an input data frame into + one of the selected Weibull functions (w2, w3 and it''s truncated versions), calculating + the scale, location and shape parameters accordingly. The resulting plots and + files are saved into the ''folder'' parameter provided by the user. References: + a) John C. Nash, Ravi Varadhan (2011). "Unifying Optimization Algorithms to Aid + Software System Users: optimx for R" .' + date_publication: '2019-07-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WeibullFit + url_git: '' +weibullness: + version: 1.24.1 + title: Goodness-of-Fit Test for Weibull Distribution (Weibullness) + maintainer: Chanseok Park + description: |- + Conducts a goodness-of-fit test for the Weibull distribution (referred to as the weibullness test) and furnishes parameter estimations for both the two-parameter and three-parameter Weibull distributions. Notably, the threshold parameter is derived through correlation from the Weibull plot. Additionally, this package conducts goodness-of-fit assessments for the exponential, Gumbel, and inverse Weibull distributions, accompanied by parameter estimations. + For more details, see Park (2017) , + Park (2018) , and Park (2023) . + This work was supported by the National Research Foundation of Korea (NRF) grants funded by + the Korea government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528). + date_publication: '2024-01-09' + bug_reports: https://github.com/AppliedStat/R/issues + url: https://AppliedStat.GitHub.io/R/ + url_cran: https://CRAN.R-project.org/package=weibullness + url_git: '' +WeibullR: + version: 1.2.1 + title: Weibull Analysis for Reliability Engineering + maintainer: Jacob Ormerod + description: 'Life data analysis in the graphical tradition of Waloddi Weibull. + Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson + (1982, ISBN: 9780471094586), William Q. Meeker and Lois A. Escobar (1998, ISBN: + 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).' + date_publication: '2022-06-25' + bug_reports: '' + url: http://www.openreliability.org/weibull-r-weibull-analysis-on-r/ + url_cran: https://CRAN.R-project.org/package=WeibullR + url_git: '' +WeibullR.ALT: + version: 0.7.2 + title: Accelerated Life Testing Using 'WeibullR' + maintainer: Jacob Ormerod + description: 'Graphical data analysis of accelerated life tests. Methods derived + from Wayne Nelson (1990, ISBN: 9780471522775), William Q. Meeker and Lois A. + Escobar (1998, ISBN: 1-471-14328-6).' + date_publication: '2022-06-28' + bug_reports: '' + url: http://www.openreliability.org/weibull-r-weibull-analysis-on-r/ + url_cran: https://CRAN.R-project.org/package=WeibullR.ALT + url_git: '' +WeibullR.learnr: + version: '0.2' + title: An Interactive Introduction to Life Data Analysis + maintainer: Paul Govan + description: |- + An interactive introduction to Life Data Analysis that depends on 'WeibullR' + by David Silkworth and Jurgen Symynck (2022) , + a R package for Weibull Analysis, and 'learnr' by Garrick Aden-Buie et al. (2023) + , a framework for building interactive learning + modules in R. + date_publication: '2024-11-04' + bug_reports: https://github.com/paulgovan/WeibullR.learnr/issues + url: https://paulgovan.github.io/WeibullR.learnr/ + url_cran: https://CRAN.R-project.org/package=WeibullR.learnr + url_git: https://github.com/paulgovan/WeibullR.learnr +WeibullR.plotly: + version: '0.3' + title: Interactive Weibull Probability Plots + maintainer: Paul Govan + description: |- + Build interactive Weibull Probability + Plots with 'WeibullR' by David Silkworth and Jurgen Symynck (2022) + , an R package for + Weibull analysis, and 'plotly' by Carson Sievert (2020) , + an interactive web-based graphing library. + date_publication: '2024-11-06' + bug_reports: https://github.com/paulgovan/WeibullR.plotly/issues + url: https://paulgovan.github.io/WeibullR.plotly/ + url_cran: https://CRAN.R-project.org/package=WeibullR.plotly + url_git: https://github.com/paulgovan/WeibullR.plotly +WeibullR.shiny: + version: '0.3' + title: A 'Shiny' App for Weibull Analysis + maintainer: Paul Govan + description: |- + A 'Shiny' web application for life data analysis that depends on 'WeibullR' by David Silkworth and Jurgen Symynck (2022) + , an R package for Weibull analysis. + date_publication: '2024-11-13' + bug_reports: https://github.com/paulgovan/WeibullR.shiny/issues + url: https://paulgovan.github.io/WeibullR.shiny/ + url_cran: https://CRAN.R-project.org/package=WeibullR.shiny + url_git: https://github.com/paulgovan/WeibullR.shiny +weibulltools: + version: 2.1.0 + title: Statistical Methods for Life Data Analysis + maintainer: Tim-Gunnar Hensel + description: |- + Provides statistical methods and visualizations that are often + used in reliability engineering. Comprises a compact and easily + accessible set of methods and visualization tools that make the + examination and adjustment as well as the analysis and interpretation + of field data (and bench tests) as simple as possible. + Non-parametric estimators like Median Ranks, + Kaplan-Meier (Abernethy, 2006, ), + Johnson (Johnson, 1964, ), and Nelson-Aalen + for failure probability estimation within samples that contain + failures as well as censored data are included. + The package supports methods like Maximum Likelihood and Rank Regression, + (Genschel and Meeker, 2010, ) + for the estimation of multiple parametric lifetime distributions, + as well as the computation of confidence intervals of quantiles and + probabilities using the delta method related to Fisher's confidence + intervals (Meeker and Escobar, 1998, ) and the + beta-binomial confidence bounds. + If desired, mixture model analysis can be done with segmented regression + and the EM algorithm. + Besides the well-known Weibull analysis, the package also contains + Monte Carlo methods for the correction and completion of imprecisely + recorded or unknown lifetime characteristics. + (Verband der Automobilindustrie e.V. (VDA), 2016, ). + Plots are created statically ('ggplot2') or interactively ('plotly') and + can be customized with functions of the respective visualization package. + The graphical technique of probability plotting as well as the addition + of regression lines and confidence bounds to existing plots are + supported. + date_publication: '2023-04-05' + bug_reports: https://github.com/Tim-TU/weibulltools/issues + url: https://tim-tu.github.io/weibulltools/ + url_cran: https://CRAN.R-project.org/package=weibulltools + url_git: https://github.com/Tim-TU/weibulltools +Weighted.Desc.Stat: + version: '1.0' + title: Weighted Descriptive Statistics + maintainer: Abbas Parchami + description: Weighted descriptive statistics is the discipline of quantitatively + describing the main features of real-valued fuzzy data which usually given from + a fuzzy population. One can summarize this special kind of fuzzy data numerically + or graphically using this package. To interpret some of the properties of one + or several sets of real-valued fuzzy data, numerically summarize is possible by + some weighted statistics which are designed in this package such as mean, variance, + covariance and correlation coefficent. Also, graphically interpretation can be + given by weighted histogram and weighted scatter plot using this package to describe + properties of real-valued fuzzy data set. + date_publication: '2016-02-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Weighted.Desc.Stat + url_git: '' +weightedCL: + version: '0.5' + title: |- + Efficient and Feasible Inference for High-Dimensional Normal + Copula Regression Models + maintainer: Aristidis K. Nikoloulopoulos + description: Estimates high-dimensional multivariate normal copula regression models + with the weighted composite likelihood estimating equations in Nikoloulopoulos + (2022) . It provides autoregressive moving average correlation + structures and binary, ordinal, Poisson, and negative binomial regressions. + date_publication: '2022-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weightedCL + url_git: '' +WeightedCluster: + version: 1.8-1 + title: Clustering of Weighted Data + maintainer: Matthias Studer + description: Clusters state sequences and weighted data. It provides an optimized + weighted PAM algorithm as well as functions for aggregating replicated cases, + computing cluster quality measures for a range of clustering solutions and plotting + (fuzzy) clusters of state sequences. Parametric bootstraps methods to validate + typology of sequences are also provided. Finally, it provides a fuzzy and crisp + CLARA algorithm to cluster large database with sequence analysis. + date_publication: '2024-12-10' + bug_reports: '' + url: http://mephisto.unige.ch/weightedcluster/ + url_cran: https://CRAN.R-project.org/package=WeightedCluster + url_git: '' +WeightedEnsemble: + version: 0.1.0 + title: Weighted Ensemble for Hybrid Model + maintainer: Dr. Md Yeasin + description: The weighted ensemble method is a valuable approach for combining forecasts. + This algorithm employs several optimization techniques to generate optimized weights. + This package has been developed using algorithm of Armstrong (1989) . + date_publication: '2023-04-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WeightedEnsemble + url_git: '' +weightedGCM: + version: 0.1.0 + title: |- + Weighted Generalised Covariance Measure Conditional Independence + Test + maintainer: Cyrill Scheidegger + description: |- + A conditional independence test that can be applied both to + univariate and multivariate random variables. The test is based on a + weighted form of the sample covariance of the residuals after a + nonlinear regression on the conditioning variables. Details are + described in Scheidegger, Hoerrmann and Buehlmann (2021) "The Weighted + Generalised Covariance Measure" . The test is a + generalisation of the Generalised Covariance Measure (GCM) implemented + in the R package 'GeneralisedCovarianceMeasure' by Jonas Peters and + Rajen D. Shah based on Shah and Peters (2020) "The Hardness of + Conditional Independence Testing and the Generalised Covariance + Measure" . + date_publication: '2021-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weightedGCM + url_git: '' +WeightedPortTest: + version: '1.1' + title: Weighted Portmanteau Tests for Time Series Goodness-of-Fit + maintainer: Thomas J. Fisher + description: |- + An implementation of the Weighted Portmanteau Tests described + in "New Weighted Portmanteau Statistics for Time Series Goodness-of-Fit Testing" + published by the Journal of the American Statistical Association, Volume 107, + Issue 498, pages 777-787, 2012. + date_publication: '2023-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WeightedPortTest + url_git: '' +weightedRank: + version: 0.3.7 + title: Sensitivity Analysis Using Weighted Rank Statistics + maintainer: Paul Rosenbaum + description: Performs a sensitivity analysis using weighted rank tests in observational + studies with I blocks of size J; see Rosenbaum (2024) . The + package can perform adaptive inference in block designs; see Rosenbaum (2012) + . The main functions are wgtRank(), wgtRankCI() and + wgtRanktt(). + date_publication: '2024-07-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weightedRank + url_git: '' +WeightedROC: + version: 2020.1.31 + title: Fast, Weighted ROC Curves + maintainer: Toby Dylan Hocking + description: |- + Fast computation of + Receiver Operating Characteristic (ROC) curves + and Area Under the Curve (AUC) + for weighted binary classification problems + (weights are example-specific cost values). + date_publication: '2020-02-01' + bug_reports: https://github.com/tdhock/WeightedROC/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WeightedROC + url_git: https://github.com/tdhock/WeightedROC +weightedScores: + version: 0.9.5.3 + title: Weighted Scores Method for Regression Models with Dependent Data + maintainer: Aristidis K. Nikoloulopoulos + description: The weighted scores method and composite likelihood information criteria + as an intermediate step for variable/correlation selection for longitudinal ordinal + and count data in Nikoloulopoulos, Joe and Chaganty (2011) , + Nikoloulopoulos (2016) and Nikoloulopoulos (2017) . + date_publication: '2020-03-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weightedScores + url_git: '' +WeightedTreemaps: + version: 0.1.4 + title: |- + Generate and Plot Voronoi or Sunburst Treemaps from Hierarchical + Data + maintainer: Michael Jahn + description: |- + Treemaps are a visually appealing graphical representation of + numerical data using a space-filling approach. A plane or 'map' is + subdivided into smaller areas called cells. The cells in the map are + scaled according to an underlying metric which allows to grasp the + hierarchical organization and relative importance of many objects at + once. This package contains two different implementations of treemaps, + Voronoi treemaps and Sunburst treemaps. The Voronoi treemap function + subdivides the plot area in polygonal cells according to the highest + hierarchical level, then continues to subdivide those parental cells + on the next lower hierarchical level, and so on. The Sunburst treemap + is a computationally less demanding treemap that does not require + iterative refinement, but simply generates circle sectors that are + sized according to predefined weights. The Voronoi tesselation is + based on functions from Paul Murrell (2012) + . + date_publication: '2024-12-12' + bug_reports: https://github.com/m-jahn/WeightedTreemaps/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WeightedTreemaps + url_git: https://github.com/m-jahn/WeightedTreemaps +WeightIt: + version: 1.4.0 + title: Weighting for Covariate Balance in Observational Studies + maintainer: Noah Greifer + description: |- + Generates balancing weights for causal effect estimation in observational studies with + binary, multi-category, or continuous point or longitudinal treatments by easing and + extending the functionality of several R packages and providing in-house estimation methods. + Available methods include those that rely on parametric modeling, optimization, and machine learning. Also + allows for assessment of weights and checking of covariate balance by interfacing directly + with the 'cobalt' package. Methods for estimating weighted regression models that take into account + uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how + to install any package 'WeightIt' uses, including those that may not be on CRAN. + date_publication: '2025-02-24' + bug_reports: https://github.com/ngreifer/WeightIt/issues + url: https://ngreifer.github.io/WeightIt/ + url_cran: https://CRAN.R-project.org/package=WeightIt + url_git: https://github.com/ngreifer/WeightIt +weightQuant: + version: 1.0.1 + title: Weights for Incomplete Longitudinal Data and Quantile Regression + maintainer: Viviane Philipps + description: Estimation of observation-specific weights for incomplete longitudinal + data and bootstrap procedure for weighted quantile regressions. See Jacqmin-Gadda, + Rouanet, Mba, Philipps, Dartigues (2020) for details . + date_publication: '2022-01-05' + bug_reports: https://github.com/VivianePhilipps/weightQuant/issues + url: '' + url_cran: https://CRAN.R-project.org/package=weightQuant + url_git: '' +weightr: + version: 2.0.2 + title: Estimating Weight-Function Models for Publication Bias + maintainer: Kathleen M. Coburn + description: |- + Estimates the Vevea and Hedges (1995) + weight-function model. By specifying arguments, users can + also estimate the modified model described in Vevea and Woods (2005), + which may be more practical with small datasets. Users + can also specify moderators to estimate a linear model. + The package functionality allows users to easily extract the + results of these analyses as R objects for other uses. In addition, + the package includes a function to launch both models as + a Shiny application. Although the Shiny application is also available online, + this function allows users to launch it locally if they choose. + date_publication: '2019-07-06' + bug_reports: '' + url: http://faculty.ucmerced.edu/jvevea/ + url_cran: https://CRAN.R-project.org/package=weightr + url_git: '' +weights: + version: 1.0.4 + title: Weighting and Weighted Statistics + maintainer: Josh Pasek + description: 'Provides a variety of functions for producing simple weighted statistics, + such as weighted Pearson''s correlations, partial correlations, Chi-Squared statistics, + histograms, and t-tests. Also now includes some software for quickly recoding + survey data and plotting estimates from interaction terms in regressions (and + multiply imputed regressions) both with and without weights. NOTE: Weighted partial + correlation calculations pulled to address a bug.' + date_publication: '2021-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weights + url_git: '' +WeightSVM: + version: 1.7-16 + title: Subject Weighted Support Vector Machines + maintainer: Tianchen Xu + description: |- + Functions for subject/instance weighted support vector machines (SVM). + It uses a modified version of 'libsvm' and is compatible with package 'e1071'. It also allows user defined kernel matrix. + date_publication: '2024-10-12' + bug_reports: https://github.com/zjph602xtc/wsvm/issues + url: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances + url_cran: https://CRAN.R-project.org/package=WeightSVM + url_git: '' +weird: + version: 1.0.2 + title: |- + Functions and Data Sets for "That's Weird: Anomaly Detection + Using R" by Rob J Hyndman + maintainer: Rob Hyndman + description: |- + All functions and data sets required for the examples in the book + Hyndman (2024) "That's Weird: Anomaly Detection Using R" . + All packages needed to run the examples are also loaded. + date_publication: '2024-01-24' + bug_reports: https://github.com/robjhyndman/weird-package/issues + url: https://pkg.robjhyndman.com/weird-package/ + url_cran: https://CRAN.R-project.org/package=weird + url_git: https://github.com/robjhyndman/weird-package +weirs: + version: '0.25' + title: A Hydraulics Package to Compute Open-Channel Flow over Weirs + maintainer: William Asquith + description: Provides computational support for flow over weirs, such as sharp-crested, + broad-crested, and embankments. Initially, the package supports broad- and sharp-crested + weirs. + date_publication: '2015-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=weirs + url_git: '' +welchADF: + version: 0.3.2 + title: |- + Welch-James Statistic for Robust Hypothesis Testing under + Heterocedasticity and Non-Normality + maintainer: Pablo J. Villacorta + description: |- + Implementation of Johansen's general formulation of Welch-James's statistic with Approximate Degrees of Freedom, which makes it suitable for testing + any linear hypothesis concerning cell means in univariate and multivariate mixed model designs when the data pose non-normality and non-homogeneous variance. Some + improvements, namely trimmed means and Winsorized variances, and bootstrapping for calculating an empirical critical value, have been added to the classical formulation. + The code departs from a previous SAS implementation by L.M. Lix and H.J. Keselman, available at and + published in Keselman, H.J., Wilcox, R.R., and Lix, L.M. (2003) . + date_publication: '2019-09-08' + bug_reports: '' + url: + url_cran: https://CRAN.R-project.org/package=welchADF + url_git: '' +welo: + version: 0.1.4 + title: Weighted and Standard Elo Rates + maintainer: Vincenzo Candila + description: Estimates the standard and weighted Elo (WElo, Angelini et al., 2022 + ) rates. The current version provides Elo and + WElo rates for tennis, according to different systems of weights (games or sets) + and scale factors (constant, proportional to the number of matches, with more + weight on Grand Slam matches or matches played on a specific surface). Moreover, + the package gives the possibility of estimating the (bootstrap) standard errors + for the rates. Finally, the package includes betting functions that automatically + select the matches on which place a bet. + date_publication: '2024-03-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=welo + url_git: '' +WeMix: + version: 4.0.3 + title: |- + Weighted Mixed-Effects Models Using Multilevel Pseudo Maximum + Likelihood Estimation + maintainer: Paul Bailey + description: Run mixed-effects models that include weights at every level. The WeMix + package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical + linear model (HLM). The weights could be inverse selection probabilities, such + as those developed for an education survey where schools are sampled probabilistically, + and then students inside of those schools are sampled probabilistically. Although + mixed-effects models are already available in R, WeMix is unique in implementing + methods for mixed models using weights at multiple levels. Both linear and logit + models are supported. Models may have up to three levels. Random effects are estimated + using the PIRLS algorithm from 'lme4pureR' (Walker and Bates (2013) ). + date_publication: '2023-11-03' + bug_reports: https://github.com/American-Institutes-for-Research/WeMix/issues + url: https://american-institutes-for-research.github.io/WeMix/ + url_cran: https://CRAN.R-project.org/package=WeMix + url_git: '' +wesanderson: + version: 0.3.7 + title: A Wes Anderson Palette Generator + maintainer: Karthik Ram + description: Palettes generated mostly from 'Wes Anderson' movies. + date_publication: '2023-10-31' + bug_reports: https://github.com/karthik/wesanderson/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wesanderson + url_git: https://github.com/karthik/wesanderson +wevid: + version: 0.6.2 + title: |- + Quantifying Performance of a Binary Classifier Through Weight of + Evidence + maintainer: Marco Colombo + description: The distributions of the weight of evidence (log Bayes factor) favouring + case over noncase status in a test dataset (or test folds generated by cross-validation) + can be used to quantify the performance of a diagnostic test (McKeigue (2019), + ). The package can be used with any test dataset + on which you have observed case-control status and have computed prior and posterior + probabilities of case status using a model learned on a training dataset. To quantify + how the predictor will behave as a risk stratifier, the quantiles of the distributions + of weight of evidence in cases and controls can be calculated and plotted. + date_publication: '2019-09-12' + bug_reports: '' + url: http://www.homepages.ed.ac.uk/pmckeigu/preprints/classify/wevidtutorial.html + url_cran: https://CRAN.R-project.org/package=wevid + url_git: '' +weyl: + version: 0.0-6 + title: The Weyl Algebra + maintainer: Robin K. S. Hankin + description: |- + A suite of routines for Weyl algebras. Notation follows + Coutinho (1995, ISBN 0-521-55119-6, "A Primer of Algebraic + D-Modules"). Uses 'disordR' discipline + (Hankin 2022 ). To cite + the package in publications, use Hankin + 2022 . + date_publication: '2025-01-30' + bug_reports: https://github.com/RobinHankin/weyl/issues + url: https://robinhankin.github.io/weyl/ + url_cran: https://CRAN.R-project.org/package=weyl + url_git: https://github.com/RobinHankin/weyl +wfe: + version: 1.9.1 + title: |- + Weighted Linear Fixed Effects Regression Models for Causal + Inference + maintainer: In Song Kim + description: |- + Provides a computationally efficient way of fitting + weighted linear fixed effects estimators for causal + inference with various weighting schemes. Weighted linear + fixed effects estimators can be used to estimate the + average treatment effects under different identification + strategies. This includes stratified randomized + experiments, matching and stratification for + observational studies, first differencing, and + difference-in-differences. The package implements methods + described in Imai and Kim (2017) "When should We Use + Linear Fixed Effects Regression Models for Causal + Inference with Longitudinal Data?", available at + . + date_publication: '2019-04-17' + bug_reports: https://github.com/insongkim/wfe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wfe + url_git: '' +wfg: + version: '0.1' + title: Weighted Fast Greedy Algorithm + maintainer: Han Yu + description: Implementation of Weighted Fast Greedy algorithm for community detection + in networks with mixed types of attributes. + date_publication: '2016-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wfg + url_git: '' +wfindr: + version: 0.1.0 + title: Crossword, Scrabble and Anagram Solver + maintainer: Iaroslav Domin + description: Provides a large English words list and tools to find words by patterns. + In particular, anagram finder and scrabble word finder. + date_publication: '2016-07-03' + bug_reports: https://github.com/idmn/wfindr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wfindr + url_git: https://github.com/idmn/wfindr +wflo: + version: '1.9' + title: |- + Data Set and Helper Functions for Wind Farm Layout Optimization + Problems + maintainer: Carsten Croonenbroeck + description: |- + Provides a convenient data set, a set of helper functions, and a benchmark function for + economically (profit) driven wind farm layout optimization. This enables researchers in the field + of the NP-hard (non-deterministic polynomial-time hard) problem of wind farm layout optimization + to focus on their optimization methodology contribution and also provides a realistic benchmark + setting for comparability among contributions. See Croonenbroeck, Carsten & Hennecke, David (2020) + . + date_publication: '2024-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wflo + url_git: '' +wgaim: + version: 2.0-6 + title: |- + Whole Genome Average Interval Mapping for QTL Detection and + Estimation using ASReml-R + maintainer: Julian Taylor + description: A computationally efficient whole genome approach to detecting and + estimating significant QTL in linkage maps using the flexible linear mixed modelling + functionality of ASReml-R. + date_publication: '2024-08-27' + bug_reports: https://github.com/DrJ001/wgaim/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wgaim + url_git: https://github.com/DrJ001/wgaim +WGCNA: + version: '1.73' + title: Weighted Correlation Network Analysis + maintainer: Peter Langfelder + description: Functions necessary to perform Weighted Correlation Network Analysis + on high-dimensional data as originally described in Horvath and Zhang (2005) + and Langfelder and Horvath (2008) . Includes functions + for rudimentary data cleaning, construction of correlation networks, module identification, + summarization, and relating of variables and modules to sample traits. Also includes + a number of utility functions for data manipulation and visualization. + date_publication: '2024-09-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WGCNA + url_git: '' +wget: + version: 0.0.3 + title: Setting Download Method to 'wget' + maintainer: Guangchuang Yu + description: |- + Provides function, wget_set(), to change the method (default to 'wget -c') using in download.file(). + Using 'wget -c' allowing continued downloading, which is especially useful for slow internet connection and for downloading large files. + User can run wget_unset() to restore previous setting. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wget + url_git: '' +WGScan: + version: '0.1' + title: |- + A Genome-Wide Scan Statistic Framework for Whole-Genome Sequence + Data Analysis + maintainer: Zihuai He + description: Functions for the analysis of whole-genome sequencing studies to simultaneously + detect the existence, and estimate the locations of association signals at genome-wide + scale. The functions allow genome-wide association scan, candidate region scan + and single window test. + date_publication: '2019-05-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WGScan + url_git: '' +WgtEff: + version: 0.1.2 + title: Functions for Weighting Effects + maintainer: Joshua Miller + description: 'Functions for determining the effect of data weights on the variance + of survey data: users will load a data set which has a weights column, and the + package will calculate the design effect (DEFF), weighting loss, root design effect + (DEFT), effective sample size (ESS), and/or weighted margin of error.' + date_publication: '2019-06-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WgtEff + url_git: '' +WH: + version: 1.1.2 + title: Enhanced Implementation of Whittaker-Henderson Smoothing + maintainer: Guillaume Biessy + description: |- + An enhanced implementation of Whittaker-Henderson smoothing for the gradation + of one-dimensional and two-dimensional actuarial tables used to quantify Life Insurance risks. + 'WH' is based on the methods described in Biessy (2023) . + Among other features, it generalizes the original smoothing algorithm to maximum likelihood estimation, + automatically selects the smoothing parameter(s) and extrapolates beyond the range of data. + date_publication: '2024-08-29' + bug_reports: https://github.com/GuillaumeBiessy/WH/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WH + url_git: https://github.com/GuillaumeBiessy/WH +WhatIf: + version: 1.5-10 + title: Software for Evaluating Counterfactuals + maintainer: Soubhik Barari + description: |- + Inferences about counterfactuals are essential for prediction, + answering what if questions, and estimating causal effects. + However, when the counterfactuals posed are too far from the data at + hand, conclusions drawn from well-specified statistical analyses + become based largely on speculation hidden in convenient modeling + assumptions that few would be willing to defend. Unfortunately, + standard statistical approaches assume the veracity of the model + rather than revealing the degree of model-dependence, which makes this + problem hard to detect. WhatIf offers easy-to-apply methods to + evaluate counterfactuals that do not require sensitivity testing over + specified classes of models. If an analysis fails the tests offered + here, then we know that substantive inferences will be sensitive to at + least some modeling choices that are not based on empirical evidence, + no matter what method of inference one chooses to use. WhatIf + implements the methods for evaluating counterfactuals discussed in + Gary King and Langche Zeng, 2006, "The Dangers of Extreme + Counterfactuals," Political Analysis 14 (2) ; + and Gary King and Langche Zeng, 2007, "When Can History Be Our Guide? The + Pitfalls of Counterfactual Inference," International Studies + Quarterly 51 (March) . + date_publication: '2020-11-14' + bug_reports: https://github.com/IQSS/WhatIf/issues + url: https://gking.harvard.edu/whatif + url_cran: https://CRAN.R-project.org/package=WhatIf + url_git: '' +WhatsR: + version: 1.0.4 + title: |- + Parsing, Anonymizing and Visualizing Exported 'WhatsApp' Chat + Logs + maintainer: Julian Kohne + description: |- + Imports 'WhatsApp' chat logs and parses them into + a usable dataframe object. The parser works on chats exported + from Android or iOS phones and on Linux, macOS and Windows. The parser has multiple options for extracting smileys and emojis + from the messages, extracting URLs and domains from the messages, extracting names and types of sent + media files from the messages, extracting timestamps from messages, extracting and anonymizing author + names from messages. Can be used to create anonymized versions of data. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WhatsR + url_git: '' +whatthreewords: + version: 0.1.3 + title: Work with the 'what3words' API for Easy Location Referencing + maintainer: David Smith + description: |- + Use the 'what3words' API + to return three words which + uniquely identify every 3m x 3m square on Earth. It is also possible to + return coordinates from any valid three words location. Supports multiple + languages. + date_publication: '2023-10-02' + bug_reports: '' + url: https://davidasmith.github.io/whatthreewords/ + url_cran: https://CRAN.R-project.org/package=whatthreewords + url_git: '' +wheatmap: + version: 0.2.0 + title: Incrementally Build Complex Plots using Natural Semantics + maintainer: Wanding Zhou + description: Builds complex plots, heatmaps in particular, using natural semantics. + Bigger plots can be assembled using directives such as 'LeftOf', 'RightOf', 'TopOf', + and 'Beneath' and more. Other features include clustering, dendrograms and integration + with 'ggplot2' generated grid objects. This package is particularly designed for + bioinformaticians to assemble complex plots for publication. + date_publication: '2022-02-27' + bug_reports: https://github.com/zwdzwd/wheatmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wheatmap + url_git: https://github.com/zwdzwd/wheatmap +when: + version: 1.0.0 + title: Definition of Date and Time Dimension Tables + maintainer: Jose Samos + description: |- + In Multidimensional Systems the When dimension allows us to + express when the analysed facts have occurred. The purpose of this + package is to provide support for implementing this dimension in the + form of date and time tables for Relational On-Line Analytical Processing + star database systems. + date_publication: '2024-01-09' + bug_reports: https://github.com/josesamos/when/issues + url: https://josesamos.github.io/when/ + url_cran: https://CRAN.R-project.org/package=when + url_git: https://github.com/josesamos/when +where: + version: 1.0.0 + title: Vectorised Substitution and Evaluation + maintainer: Matt Hendtlass + description: |- + Provides a clean syntax for vectorising the use of + Non-Standard Evaluation (NSE), for example in 'ggplot2', 'dplyr', or + 'data.table'. + date_publication: '2024-11-19' + bug_reports: https://github.com/KiwiMateo/where/issues + url: '' + url_cran: https://CRAN.R-project.org/package=where + url_git: https://github.com/KiwiMateo/where +whereami: + version: 0.2.0 + title: Reliably Return the Source and Call Location of a Command + maintainer: Jonathan Sidi + description: |- + Robust and reliable functions to return informative outputs to + console with the run or source location of a command. This can be from + the 'RScript'/R terminal commands or 'RStudio' console, source editor, + 'Rmarkdown' document and a Shiny application. + date_publication: '2022-12-22' + bug_reports: https://github.com/yonicd/whereami/issues + url: '' + url_cran: https://CRAN.R-project.org/package=whereami + url_git: https://github.com/yonicd/whereami +whereport: + version: '0.1' + title: Geolocalization of IATA Codes + maintainer: Giulio Valentino Dalla Riva + description: Retrieve geographical information for airports using their IATA or + ICAO codes. + date_publication: '2017-12-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=whereport + url_git: '' +whippr: + version: 0.1.3 + title: Tools for Manipulating Gas Exchange Data + maintainer: Felipe Mattioni Maturana + description: Set of tools for manipulating gas exchange data from cardiopulmonary + exercise testing. + date_publication: '2024-02-19' + bug_reports: https://github.com/fmmattioni/whippr/issues + url: https://fmmattioni.github.io/whippr/ + url_cran: https://CRAN.R-project.org/package=whippr + url_git: https://github.com/fmmattioni/whippr +whisker: + version: 0.4.1 + title: '{{mustache}} for R, Logicless Templating' + maintainer: Edwin de Jonge + description: Implements 'Mustache' logicless templating. + date_publication: '2022-12-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=whisker + url_git: https://github.com/edwindj/whisker +whitebox: + version: 2.4.0 + title: '''WhiteboxTools'' R Frontend' + maintainer: Andrew Brown + description: 'An R frontend for the ''WhiteboxTools'' library, which is an advanced + geospatial data analysis platform developed by Prof. John Lindsay at the University + of Guelph''s Geomorphometry and Hydrogeomatics Research Group. ''WhiteboxTools'' + can be used to perform common geographical information systems (GIS) analysis + operations, such as cost-distance analysis, distance buffering, and raster reclassification. + Remote sensing and image processing tasks include image enhancement (e.g. panchromatic + sharpening, contrast adjustments), image mosaicing, numerous filtering operations, + simple classification (k-means), and common image transformations. ''WhiteboxTools'' + also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, + watershed delineation, stream network analysis, sink removal), terrain analysis + (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; + hypsometric analysis; multi-scale topographic position analysis), and LiDAR data + processing. Suggested citation: Lindsay (2016) .' + date_publication: '2024-05-27' + bug_reports: https://github.com/opengeos/whiteboxR/issues + url: https://whiteboxr.gishub.org/ + url_cran: https://CRAN.R-project.org/package=whitebox + url_git: https://github.com/opengeos/whiteboxR +whitechapelR: + version: 0.3.0 + title: |- + Advanced Policing Techniques for the Board Game "Letters from + Whitechapel" + maintainer: Mark Ewing + description: |- + Provides a set of functions to make tracking the hidden movements + of the 'Jack' player easier. By tracking every possible path Jack might have + traveled from the point of the initial murder including special movement such + as through alleyways and via carriages, the police can more accurately narrow + the field of their search. Additionally, by tracking all possible hideouts from + round to round, rounds 3 and 4 should have a vastly reduced field of search. + date_publication: '2018-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=whitechapelR + url_git: '' +WhiteLabRt: + version: 1.0.1 + title: |- + Novel Methods for Reproduction Number Estimation, + Back-Calculation, and Forecasting + maintainer: Chad Milando + description: |- + A collection of functions related to novel methods for estimating R(t), + created by the lab of Professor Laura White. Currently implemented methods include + two-step Bayesian back-calculation and now-casting for line-list data with missing reporting delays, + adapted in 'STAN' from Li (2021) , + and calculation of time-varying reproduction number assuming a flux between various adjacent states, adapted into 'STAN' from + Zhou (2021) . + date_publication: '2024-08-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WhiteLabRt + url_git: '' +whitening: + version: 1.4.0 + title: Whitening and High-Dimensional Canonical Correlation Analysis + maintainer: Korbinian Strimmer + description: |- + Implements the whitening methods (ZCA, PCA, Cholesky, + ZCA-cor, and PCA-cor) discussed in Kessy, Lewin, and Strimmer (2018) + "Optimal whitening and decorrelation", , + as well as the whitening approach to canonical correlation analysis allowing + negative canonical correlations described in Jendoubi and Strimmer (2019) + "A whitening approach to probabilistic canonical correlation analysis for omics + data integration", . The package also offers + functions to simulate random orthogonal matrices, compute (correlation) loadings + and explained variation. It also contains four example data sets (extended UCI + wine data, TCGA LUSC data, nutrimouse data, extended pitprops data). + date_publication: '2022-06-07' + bug_reports: '' + url: https://strimmerlab.github.io/software/whitening/ + url_cran: https://CRAN.R-project.org/package=whitening + url_git: '' +whitestrap: + version: 0.0.1 + title: White Test and Bootstrapped White Test for Heteroskedasticity + maintainer: Jorge Lopez Perez + description: Formal implementation of White test of heteroskedasticity and a bootstrapped + version of it, developed under the methodology of Jeong, J., Lee, K. (1999) . + date_publication: '2020-06-04' + bug_reports: https://github.com/jlopezper/whitestrap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=whitestrap + url_git: '' +WhiteStripe: + version: 2.4.3 + title: White Matter Normalization for Magnetic Resonance Images + maintainer: John Muschelli + description: |- + Shinohara (2014) + introduced 'WhiteStripe', an intensity-based normalization of T1 + and T2 images, where normal + appearing white matter performs well, but requires segmentation. + This method performs white matter mean and standard deviation + estimates on data that has been rigidly-registered to the 'MNI' + template and uses histogram-based methods. + date_publication: '2024-05-10' + bug_reports: https://github.com/muschellij2/WhiteStripe/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WhiteStripe + url_git: '' +whitewater: + version: 0.1.3 + title: Parallel Processing Options for Package 'dataRetrieval' + maintainer: Josh Erickson + description: Provides methods for retrieving United States Geological Survey (USGS) + water data using sequential and parallel processing (Bengtsson, 2022 ). + In addition to parallel methods, data wrangling and additional statistical attributes + are provided. + date_publication: '2023-04-01' + bug_reports: https://github.com/joshualerickson/whitewater/issues/ + url: https://joshualerickson.github.io/whitewater/ + url_cran: https://CRAN.R-project.org/package=whitewater + url_git: https://github.com/joshualerickson/whitewater/ +whoa: + version: 0.0.2 + title: Evaluation of Genotyping Error in Genotype-by-Sequencing Data + maintainer: Eric C. Anderson + description: This is a small, lightweight package that lets users investigate the + distribution of genotypes in genotype-by-sequencing (GBS) data where they expect + (by and large) Hardy-Weinberg equilibrium, in order to assess rates of genotyping + errors and the dependence of those rates on read depth. It implements a Markov + chain Monte Carlo (MCMC) sampler using 'Rcpp' to compute a Bayesian estimate of + what we call the heterozygote miscall rate for restriction-associated digest (RAD) + sequencing data and other types of reduced representation GBS data. It also provides + functions to generate plots of expected and observed genotype frequencies. Some + background on these topics can be found in a recent paper "Recent advances in + conservation and population genomics data analysis" by Hendricks et al. (2018) + , and another paper describing the MCMC approach is in + preparation with Gordon Luikart and Thierry Gosselin. + date_publication: '2021-08-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=whoa + url_git: '' +whoami: + version: 1.3.0 + title: |- + Username, Full Name, Email Address, 'GitHub' Username of the + Current User + maintainer: Gábor Csárdi + description: |- + Look up the username and full name of the current user, + the current user's email address and 'GitHub' username, + using various sources of system and configuration information. + date_publication: '2019-03-19' + bug_reports: https://github.com/r-lib/whoami/issues + url: '' + url_cran: https://CRAN.R-project.org/package=whoami + url_git: https://github.com/r-lib/whoami#readme +whomds: + version: 1.1.1 + title: Calculate Results from WHO Model Disability Survey Data + maintainer: Lindsay Lee + description: |- + The Model Disability Survey (MDS) is a World Health Organization (WHO) general population survey + instrument to assess the distribution of disability within a country or + region, grounded in the International Classification of Functioning, + Disability and Health . This package provides fit-for-purpose functions + for calculating and presenting the results from this survey, as used by + the WHO. The package primarily provides functions for implementing + Rasch Analysis (see Andrich (2011) ) to + calculate a metric scale for disability. + date_publication: '2023-09-08' + bug_reports: https://github.com/lindsayevanslee/whomds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=whomds + url_git: https://github.com/lindsayevanslee/whomds +whSample: + version: 0.9.6.2 + title: Utilities for Sampling + maintainer: Paul West + description: |- + Interactive tools for generating random samples. Users select an + .xlsx, .csv, or delimited .txt file with population data and are walked through selecting the + sample type (Simple Random Sample or Stratified), the number of backups + desired, and a "stratify_on" value (if desired). The sample size is determined + using a normal approximation to the hypergeometric distribution based on + Nicholson (1956) . An .xlsx file is created + with the sample and key metadata for reference. It is menu-driven and lets + users pick an output directory. See vignettes for a detailed walk-through. + date_publication: '2021-05-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=whSample + url_git: '' +widals: + version: 0.6.1 + title: Weighting by Inverse Distance with Adaptive Least Squares + maintainer: Dave Zes + description: Computationally easy modeling, interpolation, forecasting of massive + temporal-spacial data. + date_publication: '2019-12-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=widals + url_git: '' +widgetframe: + version: 0.3.1 + title: '''Htmlwidgets'' in Responsive ''iframes''' + maintainer: Bhaskar Karambelkar + description: |- + Provides two functions 'frameableWidget()', and 'frameWidget()'. + The 'frameableWidget()' is used to add extra code to a 'htmlwidget' which + allows is to be rendered correctly inside a responsive 'iframe'. + The 'frameWidget()' is a 'htmlwidget' which displays content of another 'htmlwidget' + inside a responsive 'iframe'. + These functions allow for easier embedding of 'htmlwidgets' in content management systems + such as 'wordpress', 'blogger' etc. + They also allow for separation of widget content from main HTML content where + CSS of the main HTML could interfere with the widget. + date_publication: '2017-12-20' + bug_reports: https://github.com/bhaskarvk/widgetframe/issues + url: https://bhaskarvk.github.io/widgetframe/ + url_cran: https://CRAN.R-project.org/package=widgetframe + url_git: https://github.com/bhaskarvk/widgetframe +widyr: + version: 0.1.5 + title: Widen, Process, then Re-Tidy Data + maintainer: Julia Silge + description: |- + Encapsulates the pattern of untidying data into a wide + matrix, performing some processing, then turning it back into a tidy + form. This is useful for several operations such as co-occurrence + counts, correlations, or clustering that are mathematically convenient + on wide matrices. + date_publication: '2022-09-13' + bug_reports: https://github.com/juliasilge/widyr/issues + url: https://juliasilge.github.io/widyr/ + url_cran: https://CRAN.R-project.org/package=widyr + url_git: https://github.com/juliasilge/widyr +WienR: + version: 0.3-15 + title: |- + Derivatives of the First-Passage Time Density and Cumulative + Distribution Function, and Random Sampling from the (Truncated) + First-Passage Time Distribution + maintainer: Raphael Hartmann + description: "First, we provide functions to calculate the partial derivative of + the first-passage time diffusion probability density function (PDF) and cumulative\ndistribution + function (CDF)\twith respect to the first-passage time t (only for PDF), the upper + barrier a, the drift rate v, the relative starting point w, the\nnon-decision + time t0, the inter-trial variability of the drift rate sv, the inter-trial variability + of the rel. starting point sw, and the inter-trial variability\nof the non-decision + time st0. In addition the PDF and CDF themselves are also provided. Most calculations + are done on the logarithmic scale to make it more stable.\nSince the PDF, CDF, + and their derivatives are represented as infinite series, we give the user the + option to control the approximation errors with the argument\n'precision'. For + the numerical integration we used the C library cubature by Johnson, S. G. (2005-2013) + . Numerical integration is\nrequired whenever + sv, sw, and/or st0 is not zero. Note that numerical integration reduces speed + of the computation and the precision cannot be guaranteed\nanymore. Therefore, + whenever numerical integration is used an estimate of the approximation error + is provided in the output list.\nNote: The large number of contributors (ctb) + is due to copying a lot of C/C++ code chunks from the GNU Scientific Library (GSL).\nSecond, + we provide methods to sample from the first-passage time distribution with or + without user-defined truncation from above. The first method is a new adaptive\nrejection + sampler building on the works of Gilks and Wild (1992; ) + and Hartmann and Klauer (in press). The second method is a rejection\nsampler + provided by Drugowitsch (2016; ). The third method is an + inverse transformation sampler. The fourth method is a\n\"pseudo\" adaptive rejection + sampler that builds on the first method. For more details see the corresponding + help files." + date_publication: '2023-11-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WienR + url_git: '' +wiesbaden: + version: 1.2.10 + title: Access Databases from the Federal Statistical Office of Germany + maintainer: Moritz Marbach + description: Retrieve and import data from different databases of the Federal Statistical + Office of Germany (DESTATIS) using their SOAP XML web service . + date_publication: '2024-07-22' + bug_reports: https://github.com/sumtxt/wiesbaden/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wiesbaden + url_git: https://github.com/sumtxt/wiesbaden/ +wig: + version: 0.1.0 + title: Import WIG Data into R in Long Format + maintainer: Ramiro Magno + description: Import WIG data into R in long format. + date_publication: '2021-10-04' + bug_reports: https://github.com/ramiromagno/wig/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wig + url_git: https://github.com/ramiromagno/wig +wikibooks: + version: 0.2.1 + title: Functions and Datasets of the German WikiBook "GNU R" + maintainer: Joerg grosse Schlarmann (aka Produnis) + description: The german Wikibook "GNU R" introduces R to new users. This package + is a collection of functions and datas used in the german WikiBook "GNU R". + date_publication: '2022-05-10' + bug_reports: '' + url: https://de.wikibooks.org/wiki/GNU_R + url_cran: https://CRAN.R-project.org/package=wikibooks + url_git: '' +WikidataQueryServiceR: + version: 1.0.0 + title: API Client Library for 'Wikidata Query Service' + maintainer: Mikhail Popov + description: |- + An API client for the 'Wikidata Query Service' + . + date_publication: '2020-06-16' + bug_reports: https://github.com/bearloga/WikidataQueryServiceR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WikidataQueryServiceR + url_git: https://github.com/bearloga/WikidataQueryServiceR +WikidataR: + version: 2.3.3 + title: Read-Write API Client Library for Wikidata + maintainer: Thomas Shafee + description: |- + Read from, interogate, and write to Wikidata - + the multilingual, interdisciplinary, semantic knowledgebase. Includes functions to: + read from wikidata (single items, properties, or properties); query wikidata (retrieving + all items that match a set of criterial via Wikidata SPARQL query service); write to + Wikidata (adding new items or statements via QuickStatements); and handle and manipulate + Wikidata objects (as lists and tibbles). Uses the Wikidata and Quickstatements APIs. + date_publication: '2021-11-16' + bug_reports: https://github.com/TS404/WikidataR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WikidataR + url_git: https://github.com/TS404/WikidataR +wikifacts: + version: 0.4.2 + title: Get Facts and Data from Wikipedia and Wikidata + maintainer: Keith McNulty + description: Query Wikidata and get facts from current and historic Wikipedia main + pages. + date_publication: '2021-04-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wikifacts + url_git: '' +wikilake: + version: 0.7.0 + title: Scrape Lake Metadata Tables from Wikipedia + maintainer: Jemma Stachelek + description: Scrape lake metadata tables from Wikipedia . + date_publication: '2023-01-06' + bug_reports: https://github.com/jsta/wikilake/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wikilake + url_git: https://github.com/jsta/wikilake +WikipediR: + version: 1.7.1 + title: A MediaWiki API Wrapper + maintainer: Os Keyes + description: |- + A wrapper for the MediaWiki API, aimed particularly at the + Wikimedia 'production' wikis, such as Wikipedia. It can be used to retrieve + page text, information about users or the history of pages, and elements of + the category tree. + date_publication: '2024-04-05' + bug_reports: https://github.com/Ironholds/WikipediR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WikipediR + url_git: https://github.com/Ironholds/WikipediR/ +wikiprofiler: + version: 0.1.5 + title: '''WikiPathway'' Based Data Integration and Visualization' + maintainer: Guangchuang Yu + description: Queries online 'WikiPathway' graphics and allows mapping user data + (e.g., expression values) on the graph. The package designs a grammar of graphic + syntax that using pipe operator to add graphic layer. + date_publication: '2024-08-26' + bug_reports: https://github.com/YuLab-SMU/wikiprofiler/issues + url: https://yulab-smu.top/contribution-knowledge-mining/ + url_cran: https://CRAN.R-project.org/package=wikiprofiler + url_git: '' +wikitaxa: + version: 0.4.0 + title: Taxonomic Information from 'Wikipedia' + maintainer: Scott Chamberlain + description: |- + 'Taxonomic' information from 'Wikipedia', 'Wikicommons', + 'Wikispecies', and 'Wikidata'. Functions included for getting + taxonomic information from each of the sources just listed, as + well performing taxonomic search. + date_publication: '2020-06-29' + bug_reports: https://github.com/ropensci/wikitaxa/issues + url: https://docs.ropensci.org/wikitaxa + url_cran: https://CRAN.R-project.org/package=wikitaxa + url_git: https://github.com/ropensci/wikitaxa +wikiTools: + version: 1.2.7 + title: Tools for Wikidata and Wikipedia + maintainer: Modesto Escobar + description: A set of wrappers intended to check, read and download information + from the Wikimedia sources. It is specifically created to work with names of celebrities, + in which case their information and statistics can be downloaded. Additionally, + it also builds links and snippets to use in combination with the function gallery() + in netCoin package. + date_publication: '2024-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wikiTools + url_git: '' +wikkitidy: + version: 0.1.14 + title: Tidy Analysis of Wikipedia + maintainer: Michael Falk + description: |- + Access 'Wikipedia' through the several 'MediaWiki' APIs + (), as well as through the + 'XTools' API (). Ensure + your API calls are correct, and receive results in tidy tibbles. + date_publication: '2025-02-13' + bug_reports: https://github.com/wikihistories/wikkitidy/issues + url: https://wikihistories.github.io/wikkitidy/ + url_cran: https://CRAN.R-project.org/package=wikkitidy + url_git: https://github.com/wikihistories/wikkitidy +wilcoxmed: + version: 0.0.1 + title: |- + Computes Values for the 1-Sample Wilcoxon Sign Rank Test for + Medians + maintainer: Dion Kwan + description: |- + An implementation of the 1-Sample Wilcoxon Sign rank test for medians. + It includes 2 functions, W_stat(), which computes the + exact probabilities of the Wilcoxon Sign Rank Test Statistic, W. + The second function, Wilcox.m.test() allows the user to conduct the + 1-Sample Wilcoxon Sign Rank hypothesis test for medians, this also + allows the user to conduct the hypothesis test for the normal approximation, + based on the techniques of Bickel and Doksum (1973, ISBN:013850363X). + date_publication: '2021-01-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wilcoxmed + url_git: '' +wildcard: + version: 1.1.0 + title: Templates for Data Frames + maintainer: William Michael Landau + description: Generate data frames from templates. + date_publication: '2017-09-16' + bug_reports: https://github.com/wlandau/wildcard/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wildcard + url_git: https://github.com/wlandau/wildcard +wildlifeDI: + version: 1.0.0 + title: |- + Calculate Indices of Dynamic Interaction for Wildlife Tracking + Data + maintainer: Jed Long + description: Dynamic interaction refers to spatial-temporal associations in the + movements of two (or more) animals. This package provides tools for calculating + a suite of indices used for quantifying dynamic interaction with wildlife telemetry + data. For more information on each of the methods employed see the references + within. The package (as of version >= 0.3) also has new tools for automating contact + analysis in large tracking datasets. The package (as of version 1.0) uses the + 'move2' class of objects for working with tracking dataset. + date_publication: '2024-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wildlifeDI + url_git: https://github.com/jedalong/wildlifeDI +wildmeta: + version: 0.3.2 + title: Cluster Wild Bootstrapping for Meta-Analysis + maintainer: Megha Joshi + description: Conducts single coefficient tests and multiple-contrast hypothesis + tests of meta-regression models using cluster wild bootstrapping, based on methods + examined in Joshi, Pustejovsky, and Beretvas (2022) . + date_publication: '2023-03-08' + bug_reports: https://github.com/meghapsimatrix/wildmeta/issues + url: https://meghapsimatrix.github.io/wildmeta/index.html + url_cran: https://CRAN.R-project.org/package=wildmeta + url_git: '' +wildpoker: + version: '1.1' + title: Best Hand Analysis for Poker Variants Including Wildcards + maintainer: Bradley Shanrock-Solberg + description: Provides insight into how the best hand for a poker game changes based + on the game dealt, players who stay in until the showdown and wildcards added + to the base game. At this time the package does not support player tactics, so + draw poker variants are not included. + date_publication: '2016-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wildpoker + url_git: '' +wilson: + version: 2.4.2 + title: Web-Based Interactive Omics Visualization + maintainer: Hendrik Schultheis + description: |- + Tool-set of modules for creating web-based applications that use plot based strategies to visualize and analyze multi-omics data. + This package utilizes the 'shiny' and 'plotly' frameworks to provide a user friendly dashboard for interactive plotting. + date_publication: '2021-04-19' + bug_reports: https://github.com/loosolab/wilson/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=wilson + url_git: https://github.com/loosolab/wilson/ +winch: + version: 0.1.1 + title: Portable Native and Joint Stack Traces + maintainer: Kirill Müller + description: |- + Obtain the native stack trace and fuse it with R's + stack trace for easier debugging of R packages with native code. + date_publication: '2024-02-19' + bug_reports: https://github.com/r-prof/winch/issues + url: https://r-prof.github.io/winch/ + url_cran: https://CRAN.R-project.org/package=winch + url_git: https://github.com/r-prof/winch +windAC: + version: 1.2.10 + title: Area Correction Methods + maintainer: Daniel Riser-Espinoza + description: Post-construction fatality monitoring studies at wind facilities are + based on data from searches for bird and bat carcasses in plots beneath turbines. + Bird and bat carcasses can fall outside of the search plot. Bird and bat carcasses + from wind turbines often fall outside of the searched area. To compensate, area + correction (AC) estimations are calculated to estimate the percentage of fatalities + that fall within the searched area versus those that fall outside of it. This + package provides two likelihood based methods and one physics based method (Hull + and Muir (2010) , Huso and Dalthorp (2014) + ) to estimate the carcass fall distribution. There are also + functions for calculating the proportion of area searched within one unit annuli, + log logistic distribution functions, and truncated distribution functions. + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=windAC + url_git: '' +WindCurves: + version: '0.2' + title: Tool to Fit Wind Turbine Power Curves + maintainer: Neeraj Bokde + description: |- + Provides a tool to fit and compare the wind turbine power curves + with successful curve fitting techniques. Facilitates to examine and compare + the performance of a user-defined power curve fitting techniques. + Also, provide features to generate power curve discrete points from a graphical + power curves. Data on the power curves of the wind turbine from major + manufacturers are provided. + date_publication: '2022-05-01' + bug_reports: '' + url: https://www.neerajbokde.in/viggnette/2021-10-14-WindCurves/ + url_cran: https://CRAN.R-project.org/package=WindCurves + url_git: '' +windex: + version: 2.1.0 + title: Analysing Convergent Evolution using the Wheatsheaf Index + maintainer: Kevin Arbuckle + description: 'Analysing convergent evolution using the Wheatsheaf index, described + in Arbuckle et al. (2014) , and some other unrelated + but perhaps useful functions.' + date_publication: '2025-02-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=windex + url_git: '' +windfarmGA: + version: 4.0.0 + title: Genetic Algorithm for Wind Farm Layout Optimization + maintainer: Sebastian Gatscha + description: The genetic algorithm is designed to optimize wind farms of any shape. + It requires a predefined amount of turbines, a unified rotor radius and an average + wind speed value for each incoming wind direction. A terrain effect model can + be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover + raster to approximate surface roughness. + date_publication: '2025-01-18' + bug_reports: https://github.com/YsoSirius/windfarmGA/issues + url: https://ysosirius.github.io/windfarmGA/index.html + url_cran: https://CRAN.R-project.org/package=windfarmGA + url_git: '' +windows.pls: + version: 0.1.0 + title: Segmentation Approaches in Chemometrics + maintainer: Elia Gonzato + description: |- + Evaluation of prediction performance of smaller regions of + spectra for Chemometrics. Segmentation of spectra, evolving dimensions + regions and sliding windows as selection methods. Election of the best + model among those computed based on error metrics. Chen et al.(2017) + . + date_publication: '2023-08-09' + bug_reports: https://github.com/egonzato/windows.pls/issues + url: '' + url_cran: https://CRAN.R-project.org/package=windows.pls + url_git: https://github.com/egonzato/windows.pls +windsoraiR: + version: 0.1.2 + title: Access the 'Windsor.ai' API + maintainer: Novica Nakov + description: Collect multichannel marketing data from sources such as Google analytics, + Facebook Ads, and many others using the 'Windsor.ai' API . + date_publication: '2021-05-10' + bug_reports: https://github.com/windsor-ai/windsoraiR/ + url: '' + url_cran: https://CRAN.R-project.org/package=windsoraiR + url_git: https://github.com/windsor-ai/windsoraiR/ +wINEQ: + version: 1.2.1 + title: Inequality Measures for Weighted Data + maintainer: Sebastian Wójcik + description: Computes inequality measures of a given variable taking into account + weights. Suitable for ratio, interval and ordered scale. Includes Gini, Theil, + Leti index, Palma ratio, 20:20 ratio, Allison and Foster index, Jenkins index, + Cowell and Flechaire index, Abul Naga and Yalcin index, Apouey index, Blair and + Lacy index. Bootstrap provides distribution of inequality measures enabling significance + tests. + date_publication: '2024-09-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wINEQ + url_git: '' +winfapReader: + version: 0.1-5.1 + title: Interact with Peak Flow Data in the United Kingdom + maintainer: Ilaria Prosdocimi + description: Obtain information on peak flow data from the National River Flow Archive + (NRFA) in the United Kingdom, either from the Peak Flow Dataset files + once these have been downloaded to the user's computer or using the NRFA's API. + These files are in a format suitable for direct use in the 'WINFAP' software, + hence the name of the package. + date_publication: '2024-06-19' + bug_reports: https://github.com/ilapros/winfapReader/issues + url: https://ilapros.github.io/winfapReader/ + url_cran: https://CRAN.R-project.org/package=winfapReader + url_git: '' +wingen: + version: 2.1.2 + title: Continuous Mapping of Genetic Diversity + maintainer: Anusha Bishop + description: Generate continuous maps of genetic diversity using moving windows + with options for rarefaction, interpolation, and masking as described in Bishop + et al. (2023) . + date_publication: '2024-05-16' + bug_reports: https://github.com/AnushaPB/wingen/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wingen + url_git: https://github.com/AnushaPB/wingen +winputall: + version: 1.0.1 + title: Variable Input Allocation Among Crops + maintainer: Obafèmi Philippe Koutchade + description: |- + Using a time-varying random parameters model developed in + Koutchade et al., (2024) , this + package allows allocating variable input costs among crops produced by + farmers based on panel data including information on input expenditure + aggregated at the farm level and acreage shares. It also considers in + fairly way the weighting data and can allow integrating time-varying + and time-constant control variables. + date_publication: '2024-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=winputall + url_git: '' +winr: + version: 1.0.0 + title: Randomization-Based Covariance Adjustment of Win Statistics + maintainer: Ann Marie K. Weideman + description: "A multi-visit clinical trial may collect participant responses on + an ordinal scale and may utilize a stratified design, such as randomization within + centers, to assess treatment efficacy across multiple visits. Baseline characteristics + may be strongly associated with the outcome, and adjustment for them can improve + power. The win ratio (ignores ties) and the win odds (accounts for ties) can be + useful when analyzing these types of data from randomized controlled trials. This + package provides straightforward functions for adjustment of the win ratio and + win odds for stratification and baseline covariates, facilitating the comparison + of test and control treatments in multi-visit clinical trials. For additional + information concerning the methodologies and applied examples within this package, + please refer to the following publications:\n1. Weideman, A.M.K., Kowalewski, + E.K., & Koch, G.G. (2024). “Randomization-based covariance adjustment of win ratios + and win odds for \trandomized multi-visit studies with ordinal outcomes.” Journal + of Statistical Research, 58(1), 33–48. .\n2. Kowalewski, + E.K., Weideman, A.M.K., & Koch, G.G. (2023). “SAS macro for randomization-based + methods for covariance and stratified adjustment \tof win ratios and win odds + for ordinal outcomes.” SESUG 2023 Proceedings, Paper 139-2023." + date_publication: '2024-10-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=winr + url_git: '' +WinRatio: + version: '1.0' + title: Win Ratio for Prioritized Outcomes and 95% Confidence Interval + maintainer: Kevin Duarte + description: 'Calculate the win ratio for prioritized outcomes and the 95% confidence + interval based on Bebu and Lachin (2016) . Three + type of outcomes can be analyzed: survival "failure-time" events, repeated survival + "failure-time" events and continuous or ordinal "non-failure time" events that + are captured at specific time-points in the study.' + date_publication: '2020-11-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WinRatio + url_git: '' +WINS: + version: 1.4.3 + title: The R WINS Package + maintainer: Ying Cui + description: Calculate the win statistics (win ratio, net benefit and win odds) + for prioritized multiple endpoints, plot the win statistics and win proportions + over study time if at least one time-to-event endpoint is analyzed, and simulate + datasets with dependent endpoints. The package can handle any type of outcomes + (continuous, ordinal, binary, time-to-event) and allow users to perform stratified + analysis, inverse probability of censoring weighting (IPCW) and inverse probability + of treatment weighting (IPTW) analysis. + date_publication: '2025-01-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WINS + url_git: '' +wintime: + version: 0.3.0 + title: Win Time Methods for Time-to-Event Data in Clinical Trials + maintainer: James Troendle + description: |- + Performs an analysis of time-to-event clinical trial data using various "win time" methods, + including 'ewt', 'ewtr', 'rmt', 'max', 'wtr', 'rwtr', and 'pwt'. These methods are used to calculate and compare + treatment effects on ordered composite endpoints. The package handles event times, event indicators, and treatment + arm indicators and supports calculations on observed and resampled data. Detailed explanations of each method and + usage examples are provided in "Use of win time for ordered composite endpoints in clinical trials," by Troendle et al. + (2024). For more information, see the package documentation or the vignette titled "Introduction to wintime." + date_publication: '2024-10-31' + bug_reports: '' + url: https://pubmed.ncbi.nlm.nih.gov/38417455/ + url_cran: https://CRAN.R-project.org/package=wintime + url_git: '' +WIPF: + version: 0.1.0-1 + title: Weighted Iterative Proportional Fitting + maintainer: Jose M. Pavía + description: |- + Implementation of the weighted iterative proportional fitting (WIPF) procedure for updating/adjusting a N-dimensional array (currently N<=3) given a weight structure and some target marginals. + Acknowledgements: + The author wish to thank Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Fundación Mapfre (grant 'Modelización espacial e intra-anual de la mortalidad en España. Una herramienta automática para el cálculo de productos de vida') for supporting this research. + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WIPF + url_git: '' +wiqid: + version: 0.3.3 + title: Quick and Dirty Estimates for Wildlife Populations + maintainer: Ngumbang Juat + description: Provides simple, fast functions for maximum likelihood and Bayesian + estimates of wildlife population parameters, suitable for use with simulated data + or bootstraps. Early versions were indeed quick and dirty, but optional error-checking + routines and meaningful error messages have been added. Includes single and multi-season + occupancy, closed capture population estimation, survival, species richness and + distance measures. + date_publication: '2022-11-17' + bug_reports: https://github.com/mikemeredith/wiqid/issues + url: https://mmeredith.net/R/wiqid/ + url_cran: https://CRAN.R-project.org/package=wiqid + url_git: '' +wISAM: + version: 0.2.8 + title: Weighted Inbred Strain Association Mapping + maintainer: Robert W. Cort + description: |- + In the course of a genome-wide association study, the situation often arises that some phenotypes are known with greater precision than others. + It could be that some individuals are known to harbor more micro-environmental variance than others. + In the case of inbred strains of model organisms, it could be the case that more organisms were observed from some strains than others, so the strains with more organisms have better-estimated means. + Package 'wISAM' handles this situation by allowing for weighting of each observation according to residual variance. + Specifically, the 'weight' parameter to the function conduct_scan() takes the precision of each observation (one over the variance). + date_publication: '2018-06-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wISAM + url_git: '' +wishmom: + version: 1.1.0 + title: |- + Compute Moments Related to Beta-Wishart and Inverse Beta-Wishart + Distributions + maintainer: Raymond Kan + description: |- + Provides functions for computing moments and coefficients related to the Beta-Wishart and Inverse Beta-Wishart distributions. + It includes functions for calculating the expectation of matrix-valued functions of the Beta-Wishart distribution, + coefficient matrices C_k and H_k, expectation of matrix-valued functions of the inverse Beta-Wishart distribution, + and coefficient matrices \tilde{C}_k and \tilde{H}_k. For more details, refer Hillier and Kan (2024) , + "On the Expectations of Equivariant Matrix-valued Functions of Wishart and Inverse Wishart Matrices". + date_publication: '2024-08-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wishmom + url_git: '' +withdots: + version: 0.1.1 + title: Put ... in a Function's Argument List + maintainer: Nikolas Ivan Krieger + description: |- + Adds ... to a function's argument list so that it can + tolerate non-matching arguments. + date_publication: '2023-04-28' + bug_reports: https://github.com/NikKrieger/withdots/issues + url: '' + url_cran: https://CRAN.R-project.org/package=withdots + url_git: https://github.com/NikKrieger/withdots +wither: + version: 0.1.0 + title: Temporarily Change Project Root + maintainer: Torbjørn Lindahl + description: Lets you temporarily execute an expression or a local block with a + different here() root in the 'here' package. This is useful for sourcing code + in other projects which expect the root directory of here() to be the project + directory of those projects. This may be the case with git submodules for example. + date_publication: '2024-09-12' + bug_reports: https://github.com/torbjorn/wither/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wither + url_git: https://github.com/torbjorn/wither +withr: + version: 3.0.2 + title: Run Code 'With' Temporarily Modified Global State + maintainer: Lionel Henry + description: |- + A set of functions to run code 'with' safely and temporarily + modified global state. Many of these functions were originally a part + of the 'devtools' package, this provides a simple package with limited + dependencies to provide access to these functions. + date_publication: '2024-10-28' + bug_reports: https://github.com/r-lib/withr/issues + url: https://withr.r-lib.org + url_cran: https://CRAN.R-project.org/package=withr + url_git: https://github.com/r-lib/withr#readme +wk: + version: 0.9.4 + title: Lightweight Well-Known Geometry Parsing + maintainer: Dewey Dunnington + description: |- + Provides a minimal R and C++ API for parsing + well-known binary and well-known text representation of + geometries to and from R-native formats. + Well-known binary is compact + and fast to parse; well-known text is human-readable + and is useful for writing tests. These formats are + useful in R only if the information they contain can be + accessed in R, for which high-performance functions + are provided here. + date_publication: '2024-10-11' + bug_reports: https://github.com/paleolimbot/wk/issues + url: https://paleolimbot.github.io/wk/ + url_cran: https://CRAN.R-project.org/package=wk + url_git: https://github.com/paleolimbot/wk +wkb: + version: 0.4-0 + title: Convert Between Spatial Objects and Well-Known Binary Geometry + maintainer: Ian Cook + description: |- + Utility functions to convert between the 'Spatial' classes + specified by the package 'sp', and the well-known binary '(WKB)' + representation for geometry specified by the 'Open Geospatial Consortium'. + Supports 'Spatial' objects of class 'SpatialPoints', + 'SpatialPointsDataFrame', 'SpatialLines', 'SpatialLinesDataFrame', + 'SpatialPolygons', and 'SpatialPolygonsDataFrame'. Supports 'WKB' geometry + types 'Point', 'LineString', 'Polygon', 'MultiPoint', 'MultiLineString', and + 'MultiPolygon'. Includes extensions to enable creation of maps with + 'TIBCO Spotfire'. + date_publication: '2019-12-05' + bug_reports: https://github.com/ianmcook/wkb/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wkb + url_git: '' +wktmo: + version: 1.0.5 + title: Converting Weekly Data to Monthly Data + maintainer: You Li + description: |- + Converts weekly data to monthly data. + Users can use three types of week formats: ISO week, epidemiology week (epi week) and calendar date. + date_publication: '2017-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wktmo + url_git: '' +wkutils: + version: 0.1.3 + title: Utilities for Well-Known Geometry Vectors + maintainer: Dewey Dunnington + description: |- + Provides extra utilities for well-known formats in the + 'wk' package that are outside the scope of that package. Utilities + to parse coordinates from data frames, plot well-known geometry + vectors, extract meta information from well-known geometry vectors, + and calculate bounding boxes are provided. + date_publication: '2023-01-18' + bug_reports: https://github.com/paleolimbot/wkutils/issues + url: https://paleolimbot.github.io/wkutils/ + url_cran: https://CRAN.R-project.org/package=wkutils + url_git: https://github.com/paleolimbot/wkutils +WLogit: + version: '2.1' + title: |- + Variable Selection in High-Dimensional Logistic Regression + Models using a Whitening Approach + maintainer: Wencan Zhu + description: It proposes a novel variable selection approach in classification problem + that takes into account the correlations that may exist between the predictors + of the design matrix in a high-dimensional logistic model. Our approach consists + in rewriting the initial high-dimensional logistic model to remove the correlation + between the predictors and in applying the generalized Lasso criterion. + date_publication: '2023-07-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WLogit + url_git: '' +WLreg: + version: 1.0.0.1 + title: Regression Analysis Based on Win Loss Endpoints + maintainer: Xiaodong Luo + description: |- + Use various regression models for the analysis of win loss endpoints + adjusting for non-binary and multivariate covariates. + date_publication: '2023-08-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WLreg + url_git: '' +WMAP: + version: 1.1.0 + title: Weighted Meta-Analysis with Pseudo-Populations + maintainer: Subharup Guha + description: Implementation of integrative weighting approaches for multiple observational + studies and causal inferences. The package features three weighting approaches, + each representing a special case of the unified weighting framework, introduced + by Guha and Li (2024) , which includes an extension + of inverse probability weights for data integration settings. + date_publication: '2024-11-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WMAP + url_git: '' +wmm: + version: 1.1.1 + title: World Magnetic Model + maintainer: Will Frierson + description: |- + Calculate magnetic field at a given location and time according to + the World Magnetic Model (WMM). Both the main field and secular variation + components are returned. This functionality is useful for physicists and + geophysicists who need orthogonal components from WMM. Currently, this package + supports annualized time inputs between 2000 and 2025. If desired, users can + specify which WMM version to use, e.g., the original WMM2015 release or the + recent out-of-cycle WMM2015 release. Methods used to implement WMM, including + the Gauss coefficients for each release, are described in the following + publications: Chulliat et al (2020) , + Chulliat et al (2019) , + Chulliat et al (2015) , + Maus et al (2010) , + McLean et al (2004) , + and Macmillian et al (2000) . + date_publication: '2021-09-06' + bug_reports: https://github.com/wfrierson/wmm/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wmm + url_git: https://github.com/wfrierson/wmm +wmwm: + version: 1.0.0 + title: Performs Wilcoxon-Mann-Whitney Test with Missing Data + maintainer: Yijin Zeng + description: Performs Wilcoxon-Mann-Whitney test in the presence of missing data + with controlled Type I error regardless of the values of missing data. + date_publication: '2024-07-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wmwm + url_git: '' +wmwpow: + version: 0.1.3 + title: |- + Precise and Accurate Power of the Wilcoxon-Mann-Whitney Rank-Sum + Test for a Continuous Variable + maintainer: Ilana Trumble + description: Power calculator for the two-sample Wilcoxon-Mann-Whitney rank-sum + test for a continuous outcome (Mollan, Trumble, Reifeis et. al., Mar. 2020) + , (Mann and Whitney 1947) , (Shieh, + Jan, and Randles 2006) . + date_publication: '2020-07-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wmwpow + url_git: '' +WMWssp: + version: 0.5.3 + title: Wilcoxon-Mann-Whitney Sample Size Planning + maintainer: Martin Happ + description: |- + Calculates the minimal sample size for the Wilcoxon-Mann-Whitney test + that is needed for a given power and two sided type I error rate. The method works for metric data with and without + ties, count data, ordered categorical data, and even dichotomous data. + But data is needed for the reference group to generate synthetic data for the treatment group based on a relevant effect. + See Happ et al. (2019, ) for details. + date_publication: '2025-02-18' + bug_reports: https://github.com/happma/WMWssp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WMWssp + url_git: https://github.com/happma/WMWssp +wnl: + version: 0.8.2 + title: |- + Minimization Tool for Pharmacokinetic-Pharmacodynamic Data + Analysis + maintainer: Kyun-Seop Bae + description: This is a set of minimization tools (maximum likelihood estimation + and least square fitting) to solve examples in the Johan Gabrielsson and Dan Weiner's + book "Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications" + 5th ed. (ISBN:9198299107). Examples include linear and nonlinear compartmental + model, turn-over model, single or multiple dosing bolus/infusion/oral models, + allometry, toxicokinetics, reversible metabolism, in-vitro/in-vivo extrapolation, + enterohepatic circulation, metabolite modeling, Emax model, inhibitory model, + tolerance model, oscillating response model, enantiomer interaction model, effect + compartment model, drug-drug interaction model, receptor occupancy model, and + rebound phenomena model. + date_publication: '2025-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wnl + url_git: '' +wNNSel: + version: '0.1' + title: |- + Weighted Nearest Neighbor Imputation of Missing Values using + Selected Variables + maintainer: Shahla Faisal + description: |- + New tools for the imputation of missing values in high-dimensional + data are introduced using the non-parametric nearest neighbor methods. It + includes weighted nearest neighbor imputation methods that use specific + distances for selected variables. It includes an automatic procedure of cross + validation and does not require prespecified values of the tuning parameters. + It can be used to impute missing values in high-dimensional data when the sample + size is smaller than the number of predictors. For more information see Faisal + and Tutz (2017) . + date_publication: '2017-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wNNSel + url_git: '' +wnominate: + version: '1.5' + title: Roll Call Analysis Software + maintainer: Jeffrey B. Lewis + description: |- + Estimates Poole and Rosenthal's (1985 , 1991 ) + W-NOMINATE scores from roll call votes supplied though a 'rollcall' + object from the 'pscl' package. + date_publication: '2024-06-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wnominate + url_git: '' +WOAkMedoids: + version: 0.1.0 + title: Whale Optimization Algorithm for K-Medoids Clustering + maintainer: Chenan Huang + description: Implements the Whale Optimization Algorithm(WOA) for k-medoids clustering, + providing tools for effective and efficient cluster analysis in various data sets. + The methodology is based on "The Whale Optimization Algorithm" by Mirjalili and + Lewis (2016) . + date_publication: '2024-08-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WOAkMedoids + url_git: '' +wodds: + version: 0.1.0 + title: Calculates Whisker Odds + maintainer: Alex Hallam + description: |- + Descriptive statistics for large data tend to be low resolution on the tails. + Whisker Odds generate a table of descriptive statistics for large data. This is the same as + letter-values, but with an alternative naming of depths which allow for depths beyond 26. For + a reference to letter-values see 'Heike Hofmann' and 'Hadley Wickham' and 'Karen Kafadar' (2017) . + date_publication: '2022-04-15' + bug_reports: https://github.com/alexhallam/wodds/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wodds + url_git: https://github.com/alexhallam/wodds +woe: + version: '0.2' + title: Computes Weight of Evidence and Information Values + maintainer: Sudarson Mothilal Thoppay + description: Shows the relationship between an independent and dependent variable + through Weight of Evidence and Information Value. + date_publication: '2015-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=woe + url_git: '' +woeBinning: + version: 0.1.6 + title: |- + Supervised Weight of Evidence Binning of Numeric Variables and + Factors + maintainer: Thilo Eichenberg + description: |- + Implements an automated binning of numeric variables and factors with + respect to a dichotomous target variable. + Two approaches are provided: An implementation of fine and coarse classing that + merges granular classes and levels step by step. And a tree-like approach that + iteratively segments the initial bins via binary splits. Both procedures merge, + respectively split, bins based on similar weight of evidence (WOE) values and + stop via an information value (IV) based criteria. + The package can be used with single variables or an entire data frame. It provides + flexible tools for exploring different binning solutions and for deploying them to + (new) data. + date_publication: '2018-07-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=woeBinning + url_git: '' +womblR: + version: 1.0.5 + title: Spatiotemporal Boundary Detection Model for Areal Unit Data + maintainer: Samuel I. Berchuck + description: |- + Implements a spatiotemporal boundary detection model with a dissimilarity + metric for areal data with inference in a Bayesian setting using Markov chain + Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget), + probit or Tobit link and spatial correlation is introduced at each time point + through a conditional autoregressive (CAR) prior. Temporal correlation is introduced + through a hierarchical structure and can be specified as exponential or first-order + autoregressive. Full details of the package can be found in the accompanying vignette. + Furthermore, the details of the package can be found in "Diagnosing Glaucoma + Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method", + by Berchuck et al (2018), . The paper is in press at the Journal of + the American Statistical Association. + date_publication: '2022-09-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=womblR + url_git: '' +WoodburyMatrix: + version: 0.0.3 + title: Fast Matrix Operations via the Woodbury Matrix Identity + maintainer: Michael Bertolacci + description: A hierarchy of classes and methods for manipulating matrices formed + implicitly from the sums of the inverses of other matrices, a situation commonly + encountered in spatial statistics and related fields. Enables easy use of the + Woodbury matrix identity and the matrix determinant lemma to allow computation + (e.g., solving linear systems) without having to form the actual matrix. More + information on the underlying linear algebra can be found in Harville, D. A. (1997) + . + date_publication: '2023-06-19' + bug_reports: https://github.com/mbertolacci/WoodburyMatrix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WoodburyMatrix + url_git: https://github.com/mbertolacci/WoodburyMatrix +WoodSimulatR: + version: 0.6.1 + title: Generate Simulated Sawn Timber Strength Grading Data + maintainer: Andreas Weidenhiller + description: |- + Tools for generating simulated sawn timber + strength grading data with a main focus on statistical simulation based on + covariance matrices. Simulation data + for Norway spruce sawn timber from Austria and reference values of means and + standard deviations of grade determining properties from literature + for a number of European countries are provided, as well. + date_publication: '2023-12-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WoodSimulatR + url_git: '' +woodValuationDE: + version: 1.0.2 + title: Wood Valuation Germany + maintainer: Jasper M. Fuchs + description: |- + Monetary valuation of wood in German forests + (stumpage values), including estimations of harvest quantities, + wood revenues, and harvest costs. The functions are sensitive to + tree species, mean diameter of the harvested trees, stand quality, + and logging method. The functions include estimations for the + consequences of disturbances on revenues and costs. The underlying + assortment tables are taken from Offer and Staupendahl (2018) with + corresponding functions for salable and skidded volume derived in + Fuchs et al. (2023). Wood revenue and harvest cost + functions were taken from v. Bodelschwingh (2018). The consequences + of disturbances refer to Dieter (2001), Moellmann and Moehring + (2017), and Fuchs et al. (2022a, 2022b). For the full references + see documentation of the functions, package README, and Fuchs et + al. (2023). Apart from Dieter (2001) and Moellmann and + Moehring (2017), all functions and factors are based on data from + HessenForst, the forest administration of the Federal State of + Hesse in Germany. + date_publication: '2024-06-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=woodValuationDE + url_git: https://github.com/Forest-Economics-Goettingen/woodValuationDE +wooldridge: + version: 1.4-4 + title: |- + 115 Data Sets from "Introductory Econometrics: A Modern + Approach, 7e" by Jeffrey M. Wooldridge + maintainer: Justin M. Shea + description: |- + Students learning both econometrics and R may find the introduction + to both challenging. The wooldridge data package aims to lighten the task by efficiently + loading any data set found in the text with a single command. Data sets have been + compressed to a fraction of their original size. Documentation files contain page numbers, + the original source, time of publication, and notes from the author suggesting avenues for + further analysis and research. If one needs an introduction to R model syntax, a + vignette contains solutions to examples from chapters of the text. + Data sets are from the 7th edition (Wooldridge 2020, ISBN-13 978-1-337-55886-0), + and are backwards compatible with all previous versions of the text. + date_publication: '2024-12-04' + bug_reports: https://github.com/JustinMShea/wooldridge/issues/ + url: https://justinmshea.github.io/wooldridge/ + url_cran: https://CRAN.R-project.org/package=wooldridge + url_git: '' +worcs: + version: 0.1.17 + title: Workflow for Open Reproducible Code in Science + maintainer: Caspar J. Van Lissa + description: |- + Create reproducible and transparent research projects in 'R'. + This package is based on the Workflow for Open + Reproducible Code in Science (WORCS), a step-by-step procedure based on best + practices for + Open Science. It includes an 'RStudio' project template, several + convenience functions, and all dependencies required to make your project + reproducible and transparent. WORCS is explained in the tutorial paper + by Van Lissa, Brandmaier, Brinkman, Lamprecht, Struiksma, & Vreede (2021). + . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=worcs + url_git: https://github.com/cjvanlissa/worcs +word.alignment: + version: '1.1' + title: |- + Computing Word Alignment Using IBM Model 1 (and Symmetrization) + for a Given Parallel Corpus and Its Evaluation + maintainer: Neda Daneshgar + description: For a given Sentence-Aligned Parallel Corpus, it aligns words for each + sentence pair. It considers one-to-many and symmetrization alignments. Moreover, + it evaluates the quality of word alignment based on this package and some other + software. It also builds an automatic dictionary of two languages based on given + parallel corpus. + date_publication: '2019-04-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=word.alignment + url_git: '' +word2vec: + version: 0.4.0 + title: Distributed Representations of Words + maintainer: Jan Wijffels + description: |- + Learn vector representations of words by continuous bag of words and skip-gram implementations of the 'word2vec' algorithm. + The techniques are detailed in the paper "Distributed Representations of Words and Phrases and their Compositionality" by Mikolov et al. (2013), available at . + date_publication: '2023-10-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=word2vec + url_git: https://github.com/bnosac/word2vec +wordcloud: + version: '2.6' + title: Word Clouds + maintainer: Ian Fellows + description: Functionality to create pretty word clouds, visualize differences and + similarity between documents, and avoid over-plotting in scatter plots with text. + date_publication: '2018-08-24' + bug_reports: '' + url: http://blog.fellstat.com/?cat=11http://www.fellstat.com + url_cran: https://CRAN.R-project.org/package=wordcloud + url_git: '' +wordcloud2: + version: 0.2.1 + title: Create Word Cloud by 'htmlwidget' + maintainer: Dawei Lang + description: |- + A fast visualization tool for creating wordcloud + by using 'wordcloud2.js'. 'wordcloud2.js' is a JavaScript library to create + wordle presentation on 2D canvas or HTML . + date_publication: '2018-01-03' + bug_reports: https://github.com/lchiffon/wordcloud2/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wordcloud2 + url_git: https://github.com/lchiffon/wordcloud2 +wordler: + version: 0.3.1 + title: The 'WORDLE' Game + maintainer: David Smith + description: |- + The 'Wordle' game. Players have six attempts to guess a + five-letter word. After each guess, the player is informed which + letters in their guess are either: anywhere in the word; in the right + position in the word. This can be used to inform the next guess. Can be + played interactively in the console, or programmatically. Based on Josh + Wardle's game . + date_publication: '2022-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wordler + url_git: https://github.com/DavidASmith/wordler +WordListsAnalytics: + version: 0.2.4 + title: Multiple Data Analysis Tools for Property Listing Tasks + maintainer: Sebastian Moreno + description: |- + Application to estimate statistical values using properties provided by a group of individuals to describe + concepts using 'shiny'. It estimates the underlying distribution to generate new descriptive words + Canessa et al. (2023) , applies a new clustering model, and uses simulations to estimate + the probability that two persons describe the same words based on their descriptions + Canessa et al. (2022) . + date_publication: '2024-08-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WordListsAnalytics + url_git: '' +wordmap: + version: 0.9.2 + title: Feature Extraction and Document Classification with Noisy Labels + maintainer: Kohei Watanabe + description: Extract features and classify documents with noisy labels given by + document-meta data or keyword matching Watanabe & Zhou (2020) . + date_publication: '2025-01-07' + bug_reports: https://github.com/koheiw/wordmap/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wordmap + url_git: https://github.com/koheiw/wordmap +wordnet: + version: 0.1-17 + title: WordNet Interface + maintainer: Kurt Hornik + description: |- + An interface to WordNet using the Jawbone Java API to WordNet. + WordNet () is a large lexical database of + English. Nouns, verbs, adjectives and adverbs are grouped into sets of + cognitive synonyms (synsets), each expressing a distinct concept. Synsets + are interlinked by means of conceptual-semantic and lexical relations. + Please note that WordNet(R) is a registered tradename. Princeton + University makes WordNet available to research and commercial users + free of charge provided the terms of their license + () are followed, + and proper reference is made to the project using an appropriate + citation (). + The WordNet database files need to be made available separately, + either via package 'wordnetDicts' from , + installing system packages where available, or direct download from + . + date_publication: '2024-06-08' + bug_reports: '' + url: https://wordnet.princeton.edu/ + url_cran: https://CRAN.R-project.org/package=wordnet + url_git: '' +WordOfMouth: + version: 1.1.0 + title: Estimates Economic Variables for Word-of-Mouth-Campaigns + maintainer: Michael Scholz + description: Methods for estimating profit, profit-maximizing price, demand and + consumer surplus of Word-of-Mouth-campaigns on mean-field networks. + date_publication: '2021-10-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WordOfMouth + url_git: '' +wordpiece: + version: 2.1.3 + title: R Implementation of Wordpiece Tokenization + maintainer: Jonathan Bratt + description: |- + Apply 'Wordpiece' () tokenization to input text, + given an appropriate vocabulary. The 'BERT' () tokenization + conventions are used by default. + date_publication: '2022-03-03' + bug_reports: https://github.com/macmillancontentscience/wordpiece/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wordpiece + url_git: https://github.com/macmillancontentscience/wordpiece +wordpiece.data: + version: 2.0.0 + title: Data for Wordpiece-Style Tokenization + maintainer: Jon Harmon + description: |- + Provides data to be used by the wordpiece algorithm in order to + tokenize text into somewhat meaningful chunks. Included vocabularies were + retrieved from + and + and parsed + into an R-friendly format. + date_publication: '2022-03-03' + bug_reports: https://github.com/macmillancontentscience/wordpiece.data/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wordpiece.data + url_git: https://github.com/macmillancontentscience/wordpiece.data +WordPools: + version: 1.2.0 + title: Word Pools Used in Studies of Learning and Memory + maintainer: Michael Friendly + description: |- + Collects several classical word pools used most often + to provide lists of words in psychological studies of learning and memory. It + provides a simple function, 'pickList' for selecting random samples of words + within given ranges. + date_publication: '2023-08-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WordPools + url_git: '' +wordpredictor: + version: 0.0.5 + title: Develop Text Prediction Models Based on N-Grams + maintainer: Nadir Latif + description: |- + A framework for developing n-gram models for text prediction. + It provides data cleaning, data sampling, extracting tokens from text, + model generation, model evaluation and word prediction. For information on how n-gram models + work we referred to: "Speech and Language Processing" + . For optimizing R code and + using R6 classes we referred to "Advanced R" + . For writing R extensions we referred to + "R Packages", . + date_publication: '2024-10-08' + bug_reports: https://github.com/pakjiddat/word-predictor/issues + url: https://pakjiddat.github.io/word-predictor/ + url_cran: https://CRAN.R-project.org/package=wordpredictor + url_git: https://github.com/pakjiddat/word-predictor +wordPuzzleR: + version: 0.1.1 + title: Word Puzzle Game + maintainer: Xiurui Zhu + description: The word puzzle game requires you to find out the letters in a word + within a limited number of guesses. In each round, if your guess hit any letters + in the word, they reveal themselves. If all letters are revealed before your guesses + run out, you win this game; otherwise you fail. You may run multiple games to + guess different words. + date_publication: '2024-02-25' + bug_reports: https://github.com/zhuxr11/wordPuzzleR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wordPuzzleR + url_git: https://github.com/zhuxr11/wordPuzzleR +WordR: + version: 0.3.6 + title: Rendering Word Documents with R Inline Code + maintainer: Tomas Hovorka + description: Serves for rendering MS Word documents with R inline code and inserting + tables and plots. + date_publication: '2023-01-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WordR + url_git: '' +words: + version: 1.0.1 + title: List of English Words from the Scrabble Dictionary + maintainer: Conor Neilson + description: |- + List of english scrabble words as listed in the OTCWL2014 + . + Words are collated from the 'Word Game Dictionary' . + date_publication: '2021-05-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=words + url_git: '' +wordsalad: + version: 0.2.0 + title: Provide Tools to Extract and Analyze Word Vectors + maintainer: Emil Hvitfeldt + description: |- + Provides access to various word embedding methods (GloVe, + fasttext and word2vec) to extract word vectors using a unified framework to + increase reproducibility and correctness. + date_publication: '2020-09-23' + bug_reports: https://github.com/EmilHvitfeldt/wordsalad/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wordsalad + url_git: https://github.com/EmilHvitfeldt/wordsalad +wordspace: + version: 0.2-8 + title: Distributional Semantic Models in R + maintainer: Stephanie Evert + description: |- + An interactive laboratory for research on distributional semantic models ('DSM', + see for more information). + date_publication: '2022-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wordspace + url_git: http://wordspace.r-forge.r-project.org/ +wordvector: + version: 0.2.0 + title: Word and Document Vector Models + maintainer: Kohei Watanabe + description: Create dense vector representation of words and documents using 'quanteda'. + Currently implements Word2vec (Mikolov et al., 2013) + and Latent Semantic Analysis (Deerwester et al., 1990) . + date_publication: '2025-01-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wordvector + url_git: https://github.com/koheiw/wordvector +workflowr: + version: 1.7.1 + title: A Framework for Reproducible and Collaborative Data Science + maintainer: John Blischak + description: |- + Provides a workflow for your analysis projects by combining + literate programming ('knitr' and 'rmarkdown') and version control + ('Git', via 'git2r') to generate a website containing time-stamped, + versioned, and documented results. + date_publication: '2023-08-23' + bug_reports: https://github.com/workflowr/workflowr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=workflowr + url_git: https://github.com/workflowr/workflowr +workflows: + version: 1.2.0 + title: Modeling Workflows + maintainer: Simon Couch + description: |- + Managing both a 'parsnip' model and its data preparation steps, + such as a model formula or recipe from 'recipes', can often be challenging. + The goal of 'workflows' is to streamline this process by bundling the + model with its data preparation, all within the same object. + date_publication: '2025-02-19' + bug_reports: https://github.com/tidymodels/workflows/issues + url: https://workflows.tidymodels.org + url_cran: https://CRAN.R-project.org/package=workflows + url_git: https://github.com/tidymodels/workflows +workflowsets: + version: 1.1.0 + title: Create a Collection of 'tidymodels' Workflows + maintainer: Simon Couch + description: |- + A workflow is a combination of a model and preprocessors + (e.g, a formula, recipe, etc.) (Kuhn and Silge (2021) + ). In order to try different combinations of + these, an object can be created that contains many workflows. There + are functions to create workflows en masse as well as training them + and visualizing the results. + date_publication: '2024-03-21' + bug_reports: https://github.com/tidymodels/workflowsets/issues + url: https://workflowsets.tidymodels.org + url_cran: https://CRAN.R-project.org/package=workflowsets + url_git: https://github.com/tidymodels/workflowsets +workloopR: + version: 1.1.4 + title: |- + Analysis of Work Loops and Other Data from Muscle Physiology + Experiments + maintainer: Vikram B. Baliga + description: |- + Functions for the import, transformation, and analysis of data + from muscle physiology experiments. The work loop technique is used to + evaluate the mechanical work and power output of muscle. Josephson (1985) + modernized the technique for + application in comparative biomechanics. Although our initial motivation + was to provide functions to analyze work loop experiment data, as we + developed the package we incorporated the ability to analyze data from + experiments that are often complementary to work loops. There are currently + three supported experiment types: work loops, simple twitches, and tetanus + trials. Data can be imported directly from .ddf files or via an object + constructor function. Through either method, data can then be cleaned or + transformed via methods typically used in studies of muscle physiology. + Data can then be analyzed to determine the timing and magnitude of force + development and relaxation (for isometric trials) or the magnitude of work, + net power, and instantaneous power among other things (for work loops). + Although we do not provide plotting functions, all resultant objects are + designed to be friendly to visualization via either base-R plotting or + 'tidyverse' functions. + This package has been peer-reviewed by rOpenSci (v. 1.1.0). + date_publication: '2021-05-06' + bug_reports: https://github.com/ropensci/workloopR/issues/ + url: https://docs.ropensci.org/workloopR/ + url_cran: https://CRAN.R-project.org/package=workloopR + url_git: https://github.com/ropensci/workloopR/ +worldbank: + version: 0.5.0 + title: |- + Client for World Banks's 'Indicators' and 'Poverty and + Inequality Platform (PIP)' APIs + maintainer: Maximilian Mücke + description: |- + Download and search data from the 'World Bank Indicators + API', which provides access to nearly 16,000 time series indicators. + See + + for further details about the API. + date_publication: '2025-01-27' + bug_reports: https://github.com/m-muecke/worldbank/issues + url: https://m-muecke.github.io/worldbank/ + url_cran: https://CRAN.R-project.org/package=worldbank + url_git: https://github.com/m-muecke/worldbank +WorldFlora: + version: 1.14-5 + title: |- + Standardize Plant Names According to World Flora Online + Taxonomic Backbone + maintainer: Roeland Kindt + description: World Flora Online is an online flora of all known plants, available + from . Methods are provided of matching a list + of plant names (scientific names, taxonomic names, botanical names) against a + static copy of the World Flora Online Taxonomic Backbone data that can be downloaded + from the World Flora Online website. The World Flora Online Taxonomic Backbone + is an updated version of The Plant List (), a working + list of plant names that has become static since 2013. + date_publication: '2024-09-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WorldFlora + url_git: '' +worldfootballR: + version: 0.6.2 + title: Extract and Clean World Football (Soccer) Data + maintainer: Jason Zivkovic + description: |- + Allow users to obtain clean and tidy + football (soccer) game, team and player data. Data is collected from a + number of popular sites, including 'FBref', + transfer and valuations data from + 'Transfermarkt' and shooting location + and other match stats data from 'Understat' + and 'fotmob'. It gives users the + ability to access data more efficiently, rather than having to export + data tables to files before being able to complete their analysis. + date_publication: '2022-11-26' + bug_reports: https://github.com/JaseZiv/worldfootballR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=worldfootballR + url_git: https://github.com/JaseZiv/worldfootballR +WorldMapR: + version: 1.1.0 + title: Worldwide or Coordinates-Based Heat Maps + maintainer: Luigi Annicchiarico + description: Easily plot heat maps of the world, based on continuous or categorical + data. Country labels can also be added to the map. + date_publication: '2025-01-28' + bug_reports: https://github.com/Luigi-Annic/WorldMapR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WorldMapR + url_git: https://github.com/Luigi-Annic/WorldMapR/ +worldmet: + version: 0.9.9 + title: |- + Import Surface Meteorological Data from NOAA Integrated Surface + Database (ISD) + maintainer: David Carslaw + description: |- + Functions to import data from more than 30,000 surface + meteorological sites around the world managed by the National Oceanic + and Atmospheric Administration (NOAA) Integrated Surface Database + (ISD, see + ). + date_publication: '2025-01-14' + bug_reports: https://github.com/openair-project/worldmet/issues + url: https://openair-project.github.io/worldmet/ + url_cran: https://CRAN.R-project.org/package=worldmet + url_git: https://github.com/openair-project/worldmet +WormTensor: + version: 0.1.1 + title: |- + A Clustering Method for Time-Series Whole-Brain Activity Data of + 'C. elegans' + maintainer: Kentaro Yamamoto + description: |- + A toolkit to detect clusters from distance matrices. + The distance matrices are assumed to be calculated between the cells of + multiple animals ('Caenorhabditis elegans') from input time-series matrices. + Some functions for generating distance matrices, performing clustering, + evaluating the clustering, and visualizing the results of clustering and + evaluation are available. We're also providing the download function to + retrieve the calculated distance matrices from + 'figshare' . + date_publication: '2024-07-23' + bug_reports: https://github.com/rikenbit/WormTensor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WormTensor + url_git: https://github.com/rikenbit/WormTensor +worrms: + version: 0.4.3 + title: World Register of Marine Species (WoRMS) Client + maintainer: Bart Vanhoorne. + description: |- + Client for World Register of Marine Species + (). Includes functions for each + of the API methods, including searching for names by name, date and + common names, searching using external identifiers, fetching + synonyms, as well as fetching taxonomic children and + taxonomic classification. + date_publication: '2023-06-20' + bug_reports: https://github.com/ropensci/worrms/issues + url: https://docs.ropensci.org/worrms/ + url_cran: https://CRAN.R-project.org/package=worrms + url_git: https://github.com/ropensci/worrms(devel) +worrrd: + version: 0.1.0 + title: Generate Wordsearch and Crossword Puzzles + maintainer: Anthony Pileggi + description: |- + Generate wordsearch and crossword puzzles using + custom lists of words (and clues). Make them easy or hard, + and print them to solve offline with paper and pencil! + date_publication: '2022-10-25' + bug_reports: https://github.com/anthonypileggi/worrrd/issues + url: https://www.stochastic-squirrel.com/worrrd/ + url_cran: https://CRAN.R-project.org/package=worrrd + url_git: https://github.com/anthonypileggi/worrrd +wosr: + version: 0.3.0 + title: Clients to the 'Web of Science' and 'InCites' APIs + maintainer: Christopher Baker + description: |- + R clients to the 'Web of Science' and 'InCites' + APIs, which + allow you to programmatically download publication and citation data + indexed in the 'Web of Science' and 'InCites' databases. + date_publication: '2018-11-02' + bug_reports: https://github.com/vt-arc/wosr/issues + url: https://vt-arc.github.io/wosr/index.html + url_cran: https://CRAN.R-project.org/package=wosr + url_git: '' +WOTPLY: + version: 0.1.0 + title: Plot Connectivity Between Cells from Different Time Points + maintainer: Gabriele Lubatti + description: It shows the connections between selected clusters from the latest + time point and the clusters from all the previous time points. The transition + matrices between time point t and t+1 are obtained from Waddington-OT analysis + . + date_publication: '2022-09-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WOTPLY + url_git: '' +wowa: + version: 1.0.2 + title: Weighted Ordered Weighted Average + maintainer: Gleb Beliakov + description: |- + Introduce weights into Ordered Weighted Averages and extend bivariate means based on n-ary tree construction. Please refer to the following: + G. Beliakov, H. Bustince, and T. Calvo (2016, ISBN: 978-3-319-24753-3), + G. Beliakov(2018) , + G. Beliakov, J.J. Dujmovic (2016) , + J.J. Dujmovic and G. Beliakov (2017) . + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wowa + url_git: '' +woylier: + version: 0.0.9 + title: Alternative Tour Frame Interpolation Method + maintainer: Dianne Cook + description: This method generates a tour path by interpolating between d-D frames + in p-D using Givens rotations. The algorithm arises from the problem of zeroing + elements of a matrix. This interpolation method is useful for showing specific + d-D frames in the tour, as opposed to d-D planes, as done by the geodesic interpolation. + It is useful for projection pursuit indexes which are not s invariant. See more + details in Buj, Cook, Asimov and Hurley (2005) + and Batsaikhan, Cook and Laa (2023) . + date_publication: '2024-10-01' + bug_reports: https://github.com/numbats/woylier/issues + url: https://numbats.github.io/woylier/ + url_cran: https://CRAN.R-project.org/package=woylier + url_git: https://github.com/numbats/woylier +wpa: + version: 1.9.1 + title: Tools for Analysing and Visualising Viva Insights Data + maintainer: Martin Chan + description: |- + Opinionated functions that enable easier and faster + analysis of Viva Insights data. There are three main types of functions in 'wpa': + (i) Standard functions create a 'ggplot' visual or a summary table based on a specific + Viva Insights metric; (2) Report Generation functions generate HTML reports on + a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover + more specific applications (e.g. Subject Line text mining) of Viva Insights data. + This package adheres to 'tidyverse' principles and works well with the pipe syntax. + 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for + simplicity. + date_publication: '2024-06-06' + bug_reports: https://github.com/microsoft/wpa/issues/ + url: https://microsoft.github.io/wpa/ + url_cran: https://CRAN.R-project.org/package=wpa + url_git: https://github.com/microsoft/wpa/ +wPerm: + version: 1.0.1 + title: Permutation Tests + maintainer: Neil A. Weiss + description: |- + Supplies permutation-test alternatives to traditional hypothesis-test + procedures such as two-sample tests for means, medians, and standard deviations; + correlation tests; tests for homogeneity and independence; and more. Suitable for + general audiences, including individual and group users, introductory statistics + courses, and more advanced statistics courses that desire an introduction to + permutation tests. + date_publication: '2015-11-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wPerm + url_git: '' +WPKDE: + version: '0.1' + title: Weighted Piecewise Kernel Density Estimation + maintainer: Kunyu Ye + description: Weighted Piecewise Kernel Density Estimation for large data. + date_publication: '2017-03-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WPKDE + url_git: '' +wpp2008: + version: 1.0-1 + title: World Population Prospects 2008 + maintainer: Hana Sevcikova + description: Data from the United Nation's World Population Prospects 2008 + date_publication: '2014-01-17' + bug_reports: '' + url: http://esa.un.org/wpp/index.htm + url_cran: https://CRAN.R-project.org/package=wpp2008 + url_git: '' +wpp2010: + version: 1.2-0 + title: World Population Prospects 2010 + maintainer: Hana Sevcikova + description: Data from the United Nation's World Population Prospects2010 + date_publication: '2013-05-09' + bug_reports: '' + url: http://esa.un.org/wpp + url_cran: https://CRAN.R-project.org/package=wpp2010 + url_git: '' +wpp2012: + version: 2.2-1 + title: World Population Prospects 2012 + maintainer: Hana Sevcikova + description: Data from the United Nation's World Population Prospects 2012 + date_publication: '2014-08-22' + bug_reports: '' + url: http://esa.un.org/wpp + url_cran: https://CRAN.R-project.org/package=wpp2012 + url_git: '' +wpp2015: + version: 1.1-2 + title: World Population Prospects 2015 + maintainer: Hana Sevcikova + description: Provides data from the United Nation's World Population Prospects 2015. + date_publication: '2019-01-07' + bug_reports: '' + url: http://esa.un.org/wpp + url_cran: https://CRAN.R-project.org/package=wpp2015 + url_git: '' +wpp2017: + version: 1.2-3 + title: World Population Prospects 2017 + maintainer: Hana Sevcikova + description: Provides data from the United Nation's World Population Prospects 2017. + date_publication: '2020-02-10' + bug_reports: '' + url: http://population.un.org/wpp + url_cran: https://CRAN.R-project.org/package=wpp2017 + url_git: '' +wpp2019: + version: 1.1-1 + title: World Population Prospects 2019 + maintainer: Hana Sevcikova + description: Provides data from the United Nation's World Population Prospects 2019. + date_publication: '2020-01-31' + bug_reports: '' + url: http://population.un.org/wpp + url_cran: https://CRAN.R-project.org/package=wpp2019 + url_git: '' +wppExplorer: + version: 2.3-4 + title: Explorer of World Population Prospects + maintainer: Hana Sevcikova + description: Explore data in the 'wpp2019' (or 2017, 2015, ...) package using a + 'shiny' interface. + date_publication: '2020-04-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wppExplorer + url_git: '' +WpProj: + version: 0.2.3 + title: Linear p-Wasserstein Projections + maintainer: Eric Dunipace + description: Performs Wasserstein projections from the predictive distributions + of any model into the space of predictive distributions of linear models. We utilize + L1 penalties to also reduce the complexity of the model space. This package employs + the methods as described in Dunipace, Eric and Lorenzo Trippa (2020) . + date_publication: '2025-02-05' + bug_reports: https://github.com/ericdunipace/WpProj/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WpProj + url_git: https://github.com/ericdunipace/WpProj +wql: + version: 1.0.2 + title: Exploring Water Quality Monitoring Data + maintainer: Jemma Stachelek + description: |- + Functions to assist in the processing and + exploration of data from environmental monitoring programs. + The package name stands for "water quality" and reflects the + original focus on time series data for physical and chemical + properties of water, as well as the biota. Intended for + programs that sample approximately monthly, quarterly or + annually at discrete stations, a feature of many legacy data + sets. Most of the functions should be useful for analysis of + similar-frequency time series regardless of the subject + matter. + date_publication: '2025-01-23' + bug_reports: https://github.com/jsta/wql/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wql + url_git: https://github.com/jsta/wql +WQM: + version: 0.1.4 + title: |- + Wavelet-Based Quantile Mapping for Postprocessing Numerical + Weather Predictions + maintainer: Ze Jiang + description: 'The wavelet-based quantile mapping (WQM) technique is designed to + correct biases in spatio-temporal precipitation forecasts across multiple time + scales. The WQM method effectively enhances forecast accuracy by generating an + ensemble of precipitation forecasts that account for uncertainties in the prediction + process. For a comprehensive overview of the methodologies employed in this package, + please refer to Jiang, Z., and Johnson, F. (2023) . + The package relies on two packages for continuous wavelet transforms: ''WaveletComp'', + which can be installed automatically, and ''wmtsa'', which is optional and available + from the CRAN archive . + Users need to manually install ''wmtsa'' from this archive if they prefer to use + ''wmtsa'' based decomposition.' + date_publication: '2024-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WQM + url_git: '' +wqspt: + version: 1.0.1 + title: Permutation Test for Weighted Quantile Sum Regression + maintainer: Drew Day + description: Implements a permutation test method for the weighted quantile sum + (WQS) regression, building off the 'gWQS' package (Renzetti et al. (2021) ). + Weighted quantile sum regression is a statistical technique to evaluate the effect + of complex exposure mixtures on an outcome (Carrico et al. (2015) ). + The model features a statistical power and Type I error (i.e., false positive) + rate trade-off, as there is a machine learning step to determine the weights that + optimize the linear model fit. This package provides an alternative method based + on a permutation test that should reliably allow for both high power and low false + positive rate when utilizing WQS regression (Day et al. (2022) ). + date_publication: '2023-03-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wqspt + url_git: '' +wqtrends: + version: 1.5.0 + title: Assess Water Quality Trends with Generalized Additive Models + maintainer: Marcus Beck + description: |- + Assess Water Quality Trends for Long-Term Monitoring Data in Estuaries using + Generalized Additive Models following Wood (2017) and Error + Propagation with Mixed-Effects Meta-Analysis following Sera et al. (2019) . + Methods are available for model fitting, assessment of fit, annual and seasonal trend tests, and + visualization of results. + date_publication: '2024-09-04' + bug_reports: https://github.com/tbep-tech/wqtrends/issues + url: + url_cran: https://CRAN.R-project.org/package=wqtrends + url_git: +WR: + version: '1.0' + title: Win Ratio Analysis of Composite Time-to-Event Outcomes + maintainer: Lu Mao + description: |- + Implements various win ratio methodologies for composite endpoints of death and + non-fatal events, including the (stratified) proportional win-fractions (PW) regression models + (Mao and Wang, 2020 ), (stratified) two-sample tests with possibly + recurrent nonfatal event, and sample size calculation for standard win ratio test (Mao et al., + 2021 ). + date_publication: '2021-11-26' + bug_reports: '' + url: https://sites.google.com/view/lmaowisc/ + url_cran: https://CRAN.R-project.org/package=WR + url_git: '' +wrangle: + version: 0.6.4 + title: A Systematic Data Wrangling Idiom + maintainer: Tim Bergsma + description: |- + Supports systematic scrutiny, modification, and integration of + data. The function status() counts rows that have missing values in + grouping columns (returned by na() ), have non-unique combinations of + grouping columns (returned by dup() ), and that are not locally sorted + (returned by unsorted() ). Functions enumerate() and itemize() give + sorted unique combinations of columns, with or without occurrence counts, + respectively. Function ignore() drops columns in x that are present in y, + and informative() drops columns in x that are entirely NA; constant() returns + values that are constant, given a key. Data that have defined unique + combinations of grouping values behave more predictably during merge operations. + date_publication: '2024-03-29' + bug_reports: https://github.com/bergsmat/wrangle/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wrangle + url_git: '' +wrappedtools: + version: 0.9.6 + title: Useful Wrappers Around Commonly Used Functions + maintainer: Andreas Busjahn + description: |- + The main functionalities of 'wrappedtools' are: + adding backticks to variable names; rounding to desired precision + with special case for p-values; + selecting columns based on pattern and storing their position, name, + and backticked name; computing and formatting of descriptive statistics + (e.g. mean±SD), comparing groups and creating publication-ready tables with + descriptive statistics and p-values; creating specialized plots for + correlation matrices. Functions were mainly written for my own daily work or + teaching, but may be of use to others as well. + date_publication: '2024-10-10' + bug_reports: https://github.com/abusjahn/wrappedtools/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wrappedtools + url_git: https://github.com/abusjahn/wrappedtools +wrappr: + version: 0.1.0 + title: A Collection of Helper and Wrapper Functions + maintainer: John Piper + description: |- + Helper functions to easily add functionality to functions. The package can + assign functions to have an lazy evaluation allowing you to save and update the + arguments before and after each function call. You can set a temporary working + directory within functions and wrap console messages around other functions. + date_publication: '2023-05-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wrappr + url_git: '' +wrapr: + version: 2.1.0 + title: Wrap R Tools for Debugging and Parametric Programming + maintainer: John Mount + description: |- + Tools for writing and debugging R code. Provides: + '%.>%' dot-pipe (an 'S3' configurable pipe), unpack/to (R style multiple assignment/return), + 'build_frame()'/'draw_frame()' ('data.frame' example tools), + 'qc()' (quoting concatenate), + ':=' (named map builder), 'let()' (converts non-standard evaluation interfaces to parametric standard + evaluation interfaces, inspired by 'gtools::strmacro()' and 'base::bquote()'), and more. + date_publication: '2023-08-19' + bug_reports: https://github.com/WinVector/wrapr/issues + url: https://winvector.github.io/wrapr/ + url_cran: https://CRAN.R-project.org/package=wrapr + url_git: https://github.com/WinVector/wrapr +wrassp: + version: 1.0.5 + title: Interface to the 'ASSP' Library + maintainer: Markus Jochim + description: |- + A wrapper around Michel Scheffers's 'libassp' (). + The 'libassp' (Advanced Speech Signal Processor) library aims at providing + functionality for handling speech signal files in most common audio formats + and for performing analyses common in phonetic science/speech science. This + includes the calculation of formants, fundamental frequency, root mean + square, auto correlation, a variety of spectral analyses, zero crossing + rate, filtering etc. This wrapper provides R with a large subset of + 'libassp's signal processing functions and provides them to the user in a + (hopefully) user-friendly manner. + date_publication: '2024-01-09' + bug_reports: https://github.com/IPS-LMU/wrassp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wrassp + url_git: https://github.com/IPS-LMU/wrassp +WrensBookshelf: + version: 0.1.0 + title: A Collection of Palettes and Some Functions to Help Use Them + maintainer: Benjamin Uveges + description: A collection of color palettes that were extracted from various books + on my sons(Wren) bookshelf. Also included are a number of functions and wrappers + to utilize them, as well as to subset the palettes to desired number/specific + colors. + date_publication: '2022-08-15' + bug_reports: https://github.com/buveges/WrensBookshelf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WrensBookshelf + url_git: https://github.com/buveges/WrensBookshelf +WRestimates: + version: 0.1.0 + title: Sample Size, Power and CI for the Win Ratio + maintainer: Autumn O'Donnell + description: Calculates non-parametric estimates of the sample size, power and confidence + intervals for the win-ratio. For more detail on the theory behind the methodologies + implemented see Yu, R. X. and Ganju, J. (2022) . + date_publication: '2023-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WRestimates + url_git: '' +wrGraph: + version: 1.3.8 + title: Graphics in the Context of Analyzing High-Throughput Data + maintainer: Wolfgang Raffelsberger + description: |- + Additional options for making graphics in the context of analyzing high-throughput data are available here. + This includes automatic segmenting of the current device (eg window) to accommodate multiple new plots, + automatic checking for optimal location of legends in plots, small histograms to insert as legends, + histograms re-transforming axis labels to linear when plotting log2-transformed data, + a violin-plot function for a wide variety of input-formats, + principal components analysis (PCA) with bag-plots to highlight and compare the center areas for groups of samples, + generic MA-plots (differential- versus average-value plots) , + staggered count plots and generation of mouse-over interactive html pages. + date_publication: '2024-11-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wrGraph + url_git: '' +WRI: + version: 0.2.0 + title: Wasserstein Regression and Inference + maintainer: Xi Liu + description: Implementation of the methodologies described in 1) Alexander Petersen, + Xi Liu and Afshin A. Divani (2021) , including global + F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein + density bands, and 2) Chao Zhang, Piotr Kokoszka and Alexander Petersen (2022) + , including estimation, prediction, and inference of the + Wasserstein autoregressive models. + date_publication: '2022-07-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WRI + url_git: '' +WrightMap: + version: '1.4' + title: IRT Item-Person Map with 'ConQuest' Integration + maintainer: David Torres Irribarra + description: A powerful yet simple graphical tool available in the field of psychometrics + is the Wright Map (also known as item maps or item-person maps), which presents + the location of both respondents and items on the same scale. Wright Maps are + commonly used to present the results of dichotomous or polytomous item response + models. The 'WrightMap' package provides functions to create these plots from + item parameters and person estimates stored as R objects. Although the package + can be used in conjunction with any software used to estimate the IRT model (e.g. + 'TAM', 'mirt', 'eRm' or 'IRToys' in 'R', or 'Stata', 'Mplus', etc.), 'WrightMap' + features special integration with 'ConQuest' to facilitate reading and plotting + its output directly.The 'wrightMap' function creates Wright Maps based on person + estimates and item parameters produced by an item response analysis. The 'CQmodel' + function reads output files created using 'ConQuest' software and creates a set + of data frames for easy data manipulation, bundled in a 'CQmodel' object. The + 'wrightMap' function can take a 'CQmodel' object as input or it can be used to + create Wright Maps directly from data frames of person and item parameters. + date_publication: '2024-09-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WrightMap + url_git: '' +write.snns: + version: 0.0-4.2 + title: Function for exporting data to SNNS pattern files. + maintainer: Manuel Castejon Limas + description: |- + Function for writing a SNNS pattern file from a data.frame + or matrix. + date_publication: '2012-10-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=write.snns + url_git: '' +writer: + version: 0.1.0 + title: Write from Multiple Sources to a Database Table + maintainer: Komala Sheshachala Srikanth + description: |- + Provides unified syntax to write data from lazy 'dplyr' 'tbl' or + 'dplyr' 'sql' query or a dataframe to a database table with modes such as + create, append, insert, update, upsert, patch, delete, overwrite, + overwrite_schema. + date_publication: '2025-02-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=writer + url_git: https://github.com/talegari/writer +writexl: + version: 1.5.1 + title: Export Data Frames to Excel 'xlsx' Format + maintainer: Jeroen Ooms + description: |- + Zero-dependency data frame to xlsx exporter based on 'libxlsxwriter' + . Fast and no Java or Excel required. + date_publication: '2024-10-04' + bug_reports: https://github.com/ropensci/writexl/issues + url: https://ropensci.r-universe.dev/writexlhttps://docs.ropensci.org/writexl/ + url_cran: https://CRAN.R-project.org/package=writexl + url_git: '' +WriteXLS: + version: 6.7.0 + title: |- + Cross-Platform Perl Based R Function to Create Excel 2003 (XLS) + and Excel 2007 (XLSX) Files + maintainer: Marc Schwartz + description: |- + Cross-platform Perl based R function to create Excel 2003 (XLS) and Excel 2007 (XLSX) + files from one or more data frames. Each data frame will be + written to a separate named worksheet in the Excel spreadsheet. + The worksheet name will be the name of the data frame it contains + or can be specified by the user. + date_publication: '2024-07-20' + bug_reports: https://github.com/marcschwartz/WriteXLS/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WriteXLS + url_git: https://github.com/marcschwartz/WriteXLS +wrMisc: + version: 1.15.2 + title: Analyze Experimental High-Throughput (Omics) Data + maintainer: Wolfgang Raffelsberger + description: |- + The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions. + Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc. + Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) + for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). + A group of functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc. + Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values. + Other functions help aligning a matrix or data.frame to a reference using partial matching or to mine an experimental setup to extract patterns of replicate samples. + Many times large experimental datasets need some additional filtering, adequate functions are provided. + Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too. + Batch reading (or writing) of sets of files and combining data to arrays is supported, too. + date_publication: '2024-08-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wrMisc + url_git: '' +wrProteo: + version: 1.13.0 + title: Proteomics Data Analysis Functions + maintainer: Wolfgang Raffelsberger + description: |- + Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data. + Fasta-formatted proteomes (eg from UniProt Consortium ) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted. + Initial results from multiple software for protein (and peptide) quantitation can be imported (to a common format): + MaxQuant (Tyanova et al 2016 ), Dia-NN (Demichev et al 2020 ), + Fragpipe (da Veiga et al 2020 ), ionbot (Degroeve et al 2021 ), + MassChroq (Valot et al 2011 ), + OpenMS (Strauss et al 2021 ), ProteomeDiscoverer (Orsburn 2021 ), + Proline (Bouyssie et al 2020 ), AlphaPept (preprint Strauss et al ) + and Wombat-P (Bouyssie et al 2023 . + Meta-data provided by initial analysis software and/or in sdrf format can be integrated to the analysis. + Quantitative proteomics measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons. + Help is provided to inspect the data graphically to investigate the nature of NA-values via their respective replicate measurements + and to help/confirm the choice of NA-replacement algorithms. + Meta-data in sdrf-format (Perez-Riverol et al 2020 ) or similar tabular formats can be imported and included. + Missing values can be inspected and imputed based on the concept of NA-neighbours or other methods. + Dedicated filtering and statistical testing using the framework of package 'limma' can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events. + Multi-species samples, as frequently used in benchmark-tests (eg Navarro et al 2016 , Ramus et al 2016 ), can be run with special options considering + such sub-groups during normalization and testing. Subsequently, ROC curves (Hand and Till 2001 ) can be constructed to compare multiple analysis approaches. + As detailed example the data-set from Ramus et al 2016 ) quantified by MaxQuant, ProteomeDiscoverer, + and Proline is provided with a detailed analysis of heterologous spike-in proteins. + date_publication: '2024-11-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wrProteo + url_git: '' +WRS2: + version: 1.1-6 + title: A Collection of Robust Statistical Methods + maintainer: Patrick Mair + description: A collection of robust statistical methods based on Wilcox' WRS functions. + It implements robust t-tests (independent and dependent samples), robust ANOVA + (including between-within subject designs), quantile ANOVA, robust correlation, + robust mediation, and nonparametric ANCOVA models based on robust location measures. + date_publication: '2024-03-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WRS2 + url_git: https://r-forge.r-project.org/projects/psychor/ +WRSS: + version: '3.1' + title: Water Resources System Simulator + maintainer: Rezgar Arabzadeh + description: Water resources system simulator is a tool for simulation and analysis + of large-scale water resources systems. 'WRSS' proposes functions and methods + for construction, simulation and analysis of primary storage and hydropower water + resources features (e.g. reservoirs, aquifers, and etc.) based on Standard Operating + Policy (SOP). + date_publication: '2022-05-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WRSS + url_git: '' +wrswoR: + version: 1.1.1 + title: Weighted Random Sampling without Replacement + maintainer: Kirill Müller + description: |- + A collection of implementations of classical and + novel algorithms for weighted sampling without replacement. + date_publication: '2020-07-26' + bug_reports: https://github.com/krlmlr/wrswoR/issues + url: http://krlmlr.github.io/wrswoR + url_cran: https://CRAN.R-project.org/package=wrswoR + url_git: '' +WRTDStidal: + version: 1.1.4 + title: Weighted Regression for Water Quality Evaluation in Tidal Waters + maintainer: Marcus W. Beck + description: |- + An adaptation for estuaries (tidal waters) of weighted regression + on time, discharge, and season to evaluate trends in water quality time series. + Please see Beck and Hagy (2015) for + details. + date_publication: '2023-10-20' + bug_reports: https://github.com/fawda123/WRTDStidal/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WRTDStidal + url_git: '' +wrTopDownFrag: + version: 1.0.2 + title: Internal Fragment Identification from Top-Down Mass Spectrometry + maintainer: Wolfgang Raffelsberger + description: |- + Top-Down mass spectrometry aims to identify entire proteins as well as their (post-translational) modifications or ions bound (eg Chen et al (2018) ). + The pattern of internal fragments (Haverland et al (2017) ) may reveal important information about the original structure of the proteins studied + (Skinner et al (2018) and Li et al (2018) ). + However, the number of possible internal fragments gets huge with longer proteins and subsequent identification of internal fragments remains challenging, + in particular since the the accuracy of measurements with current mass spectrometers represents a limiting factor. + This package attempts to deal with the complexity of internal fragments and allows identification of terminal and internal fragments from deconvoluted mass-spectrometry data. + date_publication: '2020-09-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wrTopDownFrag + url_git: '' +wru: + version: 3.0.3 + title: |- + Who are You? Bayesian Prediction of Racial Category Using + Surname, First Name, Middle Name, and Geolocation + maintainer: Brandon Bertelsen + description: |- + Predicts individual race/ethnicity using surname, first name, + middle name, geolocation, and other attributes, such as gender and + age. The method utilizes Bayes' Rule (with optional measurement error + correction) to compute the posterior probability of each racial + category for any given individual. The package implements methods + described in Imai and Khanna (2016) "Improving Ecological Inference by + Predicting Individual Ethnicity from Voter Registration Records" + Political Analysis and Imai, Olivella, and + Rosenman (2022) "Addressing census data problems in race imputation + via fully Bayesian Improved Surname Geocoding and name supplements" + . The package also incorporates the data + described in Rosenman, Olivella, and Imai (2023) "Race and ethnicity + data for first, middle, and surnames" + . + date_publication: '2024-05-24' + bug_reports: https://github.com/kosukeimai/wru/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wru + url_git: https://github.com/kosukeimai/wru +wsbackfit: + version: 1.0-5 + title: Weighted Smooth Backfitting for Structured Models + maintainer: Javier Roca-Pardinas + description: Non- and semiparametric regression for generalized additive, partial + linear, and varying coefficient models as well as their combinations via smoothed + backfitting. Based on Roca-Pardinas J and Sperlich S (2010) ; + Mammen E, Linton O and Nielsen J (1999) ; Lee YK, + Mammen E, Park BU (2012) . + date_publication: '2021-05-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wsbackfit + url_git: '' +wsjplot: + version: 0.1.0 + title: Style Time Series Plots Like the Wall Street Journal + maintainer: Stephen Lee + description: |- + Easily override the default visual choices in 'ggplot2' to make + your time series plots look more like the Wall Street Journal. Specific + theme design choices include omitting x-axis grid lines and displaying + sparse light grey y-axis grid lines. Additionally, this allows to label + the y-axis scales with your units only displayed on the top-most number, + while also removing the bottom most number (unless specifically + overridden). The goal is visual simplicity, because who has time to waste + looking at a cluttered graph? + date_publication: '2020-10-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wsjplot + url_git: '' +wskm: + version: 1.4.40 + title: Weighted k-Means Clustering + maintainer: He Zhao + description: |- + Entropy weighted k-means (ewkm) by Liping Jing, Michael + K. Ng and Joshua Zhexue Huang (2007) + is a weighted subspace clustering + algorithm that is well suited to very high dimensional data. + Weights are calculated as the importance of a variable with + regard to cluster membership. The two-level variable + weighting clustering algorithm tw-k-means (twkm) by Xiaojun + Chen, Xiaofei Xu, Joshua Zhexue Huang and Yunming Ye (2013) + introduces two types of weights, + the weights on individual variables and the weights on + variable groups, and they are calculated during the clustering + process. The feature group weighted k-means (fgkm) by Xiaojun + Chen, Yunminng Ye, Xiaofei Xu and Joshua Zhexue Huang (2012) + extends this concept by + grouping features and weighting the group in addition to + weighting individual features. + date_publication: '2020-04-05' + bug_reports: https://github.com/SimonYansenZhao/wskm/issues + url: http://english.siat.cas.cn/ + url_cran: https://CRAN.R-project.org/package=wskm + url_git: https://github.com/SimonYansenZhao/wskm +wsprv: + version: 0.1.0 + title: Weighted Selection Probability for Rare Variant Analysis + maintainer: Xianglong Liang + description: A weighted selection probability to locate rare variants associated + with multiple phenotypes. + date_publication: '2021-12-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wsprv + url_git: '' +wsrf: + version: 1.7.30 + title: Weighted Subspace Random Forest for Classification + maintainer: He Zhao + description: |2- + + A parallel implementation of Weighted Subspace Random Forest. The + Weighted Subspace Random Forest algorithm was proposed in the + International Journal of Data Warehousing and Mining by Baoxun Xu, + Joshua Zhexue Huang, Graham Williams, Qiang Wang, and Yunming Ye + (2012) . The algorithm can classify + very high-dimensional data with random forests built using small + subspaces. A novel variable weighting method is used for variable + subspace selection in place of the traditional random variable + sampling.This new approach is particularly useful in building + models from high-dimensional data. + date_publication: '2023-01-06' + bug_reports: https://github.com/SimonYansenZhao/wsrf/issues + url: https://togaware.com + url_cran: https://CRAN.R-project.org/package=wsrf + url_git: https://github.com/SimonYansenZhao/wsrf +wsyn: + version: 1.0.4 + title: |- + Wavelet Approaches to Studies of Synchrony in Ecology and Other + Fields + maintainer: Daniel C. Reuman + description: 'Tools for a wavelet-based approach to analyzing spatial synchrony, + principally in ecological data. Some tools will be useful for studying community + synchrony. See, for instance, Sheppard et al (2016) , + Sheppard et al (2017) , Sheppard et al (2019) .' + date_publication: '2021-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wsyn + url_git: '' +wtest: + version: '3.2' + title: The W-Test for Genetic Interactions Testing + maintainer: Rui Sun + description: |- + Perform the calculation of W-test, diagnostic checking, calculate + minor allele frequency (MAF) and odds ratio. + date_publication: '2019-09-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wtest + url_git: '' +wTO: + version: '2.1' + title: |- + Computing Weighted Topological Overlaps (wTO) & Consensus wTO + Network + maintainer: Deisy Morselli Gysi + description: Computes the Weighted Topological Overlap with positive and negative + signs (wTO) networks given a data frame containing the mRNA count/ expression/ + abundance per sample, and a vector containing the interested nodes of interaction + (a subset of the elements of the full data frame). It also computes the cut-off + threshold or p-value based on the individuals bootstrap or the values reshuffle + per individual. It also allows the construction of a consensus network, based + on multiple wTO networks. The package includes a visualization tool for the networks. More + about the methodology can be found at . + date_publication: '2024-07-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wTO + url_git: '' +WtTopsis: + version: '1.0' + title: Weighted Method for Multiple-Criteria Decision Making + maintainer: zhengyu wu + description: 'Evaluation of alternatives based on multiple criteria using weighted + technique for Order preference by similarity to an ideal solution method. Reference: + Hwang CL. (1981, ISBN:978-3-540-10558-9).' + date_publication: '2021-10-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=WtTopsis + url_git: '' +WufooR: + version: 1.0.1 + title: R Wrapper for the 'Wufoo.com' - The Form Building Service + maintainer: John Malc + description: |- + Allows form managers to download entries from their respondents + using Wufoo JSON API (). Additionally, the Wufoo reports - when public - can be + also acquired programmatically. Note that building new forms within this package + is not supported. + date_publication: '2020-04-11' + bug_reports: https://github.com/dmpe/wufoor/issues + url: '' + url_cran: https://CRAN.R-project.org/package=WufooR + url_git: https://github.com/dmpe/wufoor +wv: + version: 0.1.2 + title: Wavelet Variance + maintainer: Stéphane Guerrier + description: Provides a series of tools to compute and plot quantities related to + classical and robust wavelet variance for time series and regular lattices. More + details can be found, for example, in Serroukh, A., Walden, A.T., & Percival, + D.B. (2000) and Guerrier, S. & Molinari, R. (2016) . + date_publication: '2023-08-31' + bug_reports: https://github.com/SMAC-Group/wv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wv + url_git: https://github.com/SMAC-Group/wv +WVPlots: + version: 1.3.8 + title: Common Plots for Analysis + maintainer: John Mount + description: |- + Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. + Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, + conditioned scatter plot with marginal densities, + box and stem with matching theoretical distribution, and density with matching theoretical distribution. + date_publication: '2024-04-22' + bug_reports: https://github.com/WinVector/WVPlots/issues + url: https://winvector.github.io/WVPlots/ + url_cran: https://CRAN.R-project.org/package=WVPlots + url_git: https://github.com/WinVector/WVPlots +WWGbook: + version: 1.0.2 + title: Functions and Datasets for WWGbook + maintainer: Shu Chen + description: |- + Book is "Linear Mixed Models: A Practical Guide Using + Statistical Software" published in 2006 by Chapman Hall / CRC + Press. + date_publication: '2022-03-02' + bug_reports: '' + url: http://www-personal.umich.edu/~bwest/almmussp.html + url_cran: https://CRAN.R-project.org/package=WWGbook + url_git: '' +wwntests: + version: 1.1.0 + title: Hypothesis Tests for Functional Time Series + maintainer: Mihyun Kim + description: |- + Provides a collection of white noise hypothesis tests for functional time series and related visualizations. + These include tests based on the norms of autocovariance operators that are built under both strong and weak + white noise assumptions. Additionally, tests based on the spectral density operator and on principal component + dimensional reduction are included, which are built under strong white noise assumptions. + Also, this package provides goodness-of-fit tests for functional autoregressive of order 1 models. + These methods are described in Kokoszka et al. (2017) , Characiejus and Rice (2019) + , Gabrys and Kokoszka (2007) , + and Kim et al. (2023) + respectively. + date_publication: '2023-12-01' + bug_reports: https://github.com/veritasmih/wwntests/issues + url: '' + url_cran: https://CRAN.R-project.org/package=wwntests + url_git: '' +wxgenR: + version: 1.4.2 + title: A Stochastic Weather Generator with Seasonality + maintainer: David Woodson + description: |- + A weather generator to simulate precipitation and temperature for regions with seasonality. Users input training data containing precipitation, temperature, and seasonality (up to 26 seasons). Including weather season as a training variable allows users to explore the effects of potential changes in season duration as well as average start- and end-time dates due to phenomena like climate change. Data for training should be a single time series but can originate from station data, basin averages, grid cells, etc. + Bearup, L., Gangopadhyay, S., & Mikkelson, K. (2021). "Hydroclimate Analysis Lower Santa Cruz River Basin Study (Technical Memorandum No ENV-2020-056)." Bureau of Reclamation. + Gangopadhyay, S., Bearup, L. A., Verdin, A., Pruitt, T., Halper, E., & Shamir, E. (2019, December 1). "A collaborative stochastic weather generator for climate impacts assessment in the Lower Santa Cruz River Basin, Arizona." Fall Meeting 2019, American Geophysical Union. . + date_publication: '2024-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=wxgenR + url_git: '' +wyz.code.metaTesting: + version: 1.1.22 + title: Wizardry Code Meta Testing + maintainer: Fabien Gelineau + description: |- + Meta testing is the ability to test a function without having to + provide its parameter values. + Those values will be generated, based on semantic naming of parameters, as + introduced by package 'wyz.code.offensiveProgramming'. + Value generation logic can be completed with your own data types + and generation schemes. This to meet your most specific requirements and to + answer to a wide variety of usages, from general use case to very specific + ones. + While using meta testing, it becomes easier to generate stress test + campaigns, non-regression test campaigns and robustness test campaigns, as + generated tests can be saved and reused from session to session. + Main benefits of using 'wyz.code.metaTesting' is ability to discover valid + and invalid function parameter combinations, ability to infer valid + parameter values, and to provide smart summaries that allows you to focus + on dysfunctional cases. + date_publication: '2023-09-25' + bug_reports: '' + url: https://neonira.github.io/offensiveProgrammingBook_v1.2.2/ + url_cran: https://CRAN.R-project.org/package=wyz.code.metaTesting + url_git: '' +wyz.code.offensiveProgramming: + version: 1.1.24 + title: Wizardry Code Offensive Programming + maintainer: Fabien Gelineau + description: |- + Allows to turn standard R code into offensive programming code. + Provides code instrumentation to ease this change and tools to assist and + accelerate code production and tuning while using offensive programming code + technics. + Should improve code robustness and quality. Function calls can be easily + verified on-demand or in batch mode to assess parameter types and length + conformities. + Should improve coders productivity as offensive programming reduces the code + size due to reduced number of controls all along the call chain. + Should speed up processing as many checks will be reduced to one single check. + date_publication: '2023-09-25' + bug_reports: '' + url: https://neonira.github.io/offensiveProgrammingBook_v1.2.2/ + url_cran: https://CRAN.R-project.org/package=wyz.code.offensiveProgramming + url_git: '' +wyz.code.rdoc: + version: 1.1.19 + title: Wizardry Code Offensive Programming R Documentation + maintainer: Fabien Gelineau + description: |- + Allows to generate on-demand or by batch, any R documentation file, + whatever is kind, data, function, class or package. It populates + documentation sections, either automatically or by considering + your input. Input code could be standard R code or offensive programming code. + Documentation content completeness depends on the type of code you use. With + offensive programming code, expect generated documentation to be fully + completed, from a format and content point of view. With some standard R + code, you will have to activate post processing to fill-in any section that + requires complements. Produced manual page validity is automatically tested + against R documentation compliance rules. Documentation language + proficiency, wording style, and phrasal adjustments remains your job. + date_publication: '2021-10-06' + bug_reports: '' + url: https://neonira.github.io/offensiveProgrammingBook_v1.2.2/ + url_cran: https://CRAN.R-project.org/package=wyz.code.rdoc + url_git: '' +wyz.code.testthat: + version: 1.1.20 + title: Wizardry Code Offensive Programming Test Generation + maintainer: Fabien Gelineau + description: |- + Allows to generate automatically 'testthat' code files from offensive + programming test cases. Generated test files are complete and ready to run. + Using 'wyz.code.testthat' you will earn a lot of time, reduce the number of + errors in test case production, be able to test immediately generated files + without any need to view or modify them, and enter a zero time latency between + code implementation and industrial testing. As with 'testthat', you may + complete provided test cases according to your needs to push testing further, + but this need is nearly void when using 'wyz.code.offensiveProgramming'. + date_publication: '2021-10-06' + bug_reports: '' + url: https://neonira.github.io/offensiveProgrammingBook_v1.2.2/ + url_cran: https://CRAN.R-project.org/package=wyz.code.testthat + url_git: '' +x.ent: + version: 1.1.7 + title: eXtraction of ENTity + maintainer: Tien T. Phan + description: Provides a tool for extracting information (entities and relations + between them) in text datasets. It also emphasizes the results exploration with + graphical displays. It is a rule-based system and works with hand-made dictionaries + and local grammars defined by users. 'x.ent' uses parsing with Perl functions + and JavaScript to define user preferences through a browser and R to display and + support analysis of the results extracted. Local grammars are defined and compiled + with the tool Unitex, a tool developed by University Paris Est that supports multiple + languages. See ?xconfig for an introduction. + date_publication: '2017-05-24' + bug_reports: https://github.com/win-stub/x.ent/issues + url: '' + url_cran: https://CRAN.R-project.org/package=x.ent + url_git: https://github.com/win-stub/x.ent +x12: + version: 1.10.3 + title: |- + Interface to 'X12-ARIMA'/'X13-ARIMA-SEATS' and Structure for + Batch Processing of Seasonal Adjustment + maintainer: Alexander Kowarik + description: The 'X13-ARIMA-SEATS' + methodology and software is a widely used software and developed by the US Census + Bureau. It can be accessed from 'R' with this package and 'X13-ARIMA-SEATS' binaries + are provided by the 'R' package 'x13binary'. + date_publication: '2022-05-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=x12 + url_git: https://github.com/statistikat/x12 +x13binary: + version: 1.1.61 + title: Provide the 'x13ashtml' Seasonal Adjustment Binary + maintainer: Dirk Eddelbuettel + description: |- + The US Census Bureau provides a seasonal adjustment program now + called 'X-13ARIMA-SEATS' building on both earlier programs called X-11 and + X-12 as well as the SEATS program by the Bank of Spain. The US Census Bureau + offers both source and binary versions -- which this package integrates for + use by other R packages. + date_publication: '2024-06-24' + bug_reports: https://github.com/x13org/x13binary/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=x13binary + url_git: https://github.com/x13org/x13binary +x3ptools: + version: 0.0.4 + title: Tools for Working with 3D Surface Measurements + maintainer: Heike Hofmann + description: |- + The x3p file format is specified in ISO standard 5436:2000 to + describe 3d surface measurements. 'x3ptools' allows reading, writing and + basic modifications to the 3D surface measurements. + date_publication: '2024-01-30' + bug_reports: https://github.com/heike/x3ptools/issues + url: https://heike.github.io/x3ptools/ + url_cran: https://CRAN.R-project.org/package=x3ptools + url_git: https://github.com/heike/x3ptools +xadmix: + version: 1.0.0 + title: Subsetting and Plotting Optimized for Admixture Data + maintainer: Lukas Schönmann + description: |- + A few functions which provide a quick way of subsetting + genomic admixture data and generating customizable stacked barplots. + date_publication: '2022-07-08' + bug_reports: https://github.com/SpaceCowboy-71/xadmix/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xadmix + url_git: https://github.com/SpaceCowboy-71/xadmix +xaringan: + version: '0.30' + title: Presentation Ninja + maintainer: Yihui Xie + description: |- + Create HTML5 slides with R Markdown and the JavaScript library + 'remark.js' (). + date_publication: '2024-03-23' + bug_reports: https://github.com/yihui/xaringan/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xaringan + url_git: https://github.com/yihui/xaringan +xaringanExtra: + version: 0.8.0 + title: Extras and Extensions for 'xaringan' Slides + maintainer: Garrick Aden-Buie + description: |- + Extras and extensions for 'xaringan' slides. Navigate your + slides with tile view. Make your slides editable, live! Announce slide + changes with subtle tones. Animate slide transitions with + 'animate.css'. Add tabbed panels to slides with 'panelset'. Use the + 'Tachyons CSS' utility toolkit for rapid slide development. Scribble + on your slides. Add a copy button to your code chunks with + 'clipboard'. Add a logo or top or bottom banner to every slide. + Broadcast slides to stay in sync with remote viewers. Include yourself + in your slides with 'webcam'. Plus a whole lot more! + date_publication: '2024-05-19' + bug_reports: https://github.com/gadenbuie/xaringanExtra/issues + url: https://pkg.garrickadenbuie.com/xaringanExtra/ + url_cran: https://CRAN.R-project.org/package=xaringanExtra + url_git: https://github.com/gadenbuie/xaringanExtra +xaringanthemer: + version: 0.4.3 + title: Custom 'xaringan' CSS Themes + maintainer: Garrick Aden-Buie + description: |- + Create beautifully color-coordinated and customized themes + for your 'xaringan' slides, without writing any CSS. Complete your + slide theme with 'ggplot2' themes that match the font and colors used + in your slides. Customized styles can be created directly in your + slides' 'R Markdown' source file or in a separate external script. + date_publication: '2024-09-15' + bug_reports: https://github.com/gadenbuie/xaringanthemer/issues + url: https://pkg.garrickadenbuie.com/xaringanthemer/ + url_cran: https://CRAN.R-project.org/package=xaringanthemer + url_git: https://github.com/gadenbuie/xaringanthemer +XBRL: + version: 0.99.19.1 + title: |- + Extraction of Business Financial Information from 'XBRL' + Documents + maintainer: Roberto Bertolusso + description: |2- + + Functions to extract business financial information from + an Extensible Business Reporting Language ('XBRL') instance file and the + associated collection of files that defines its 'Discoverable' Taxonomy + Set ('DTS'). + date_publication: '2022-03-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XBRL + url_git: '' +Xcertainty: + version: 1.0.1 + title: Estimating Lengths and Uncertainty from Photogrammetric Imagery + maintainer: K.C. Bierlich + description: Implementation of Bayesian models for estimating object lengths and + morphological relationships between object lengths using photographic data collected + from drones. The Bayesian model is described in "Bayesian approach for predicting + photogrammetric uncertainty in morphometric measurements derived from drones" + (Bierlich et al., 2021, ). + date_publication: '2024-10-26' + bug_reports: https://github.com/MMI-CODEX/Xcertainty/issues + url: '' + url_cran: https://CRAN.R-project.org/package=Xcertainty + url_git: https://github.com/MMI-CODEX/Xcertainty +xdcclarge: + version: 0.1.0 + title: Estimating a (c)DCC-GARCH Model in Large Dimensions + maintainer: Kei Nakagawa + description: |- + Functions for Estimating a (c)DCC-GARCH Model in large dimensions + based on a publication by Engle et,al (2017) and Nakagawa et,al (2018) . + This estimation method is consist of composite likelihood method by Pakel et al. (2014) + and (Non-)linear shrinkage estimation of covariance matrices by Ledoit and Wolf (2004,2015,2016). (, + , ). + date_publication: '2018-07-12' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xdcclarge + url_git: '' +XDNUTS: + version: 1.5.6 + title: |- + Discontinuous Hamiltonian Monte Carlo with Varying Trajectory + Length + maintainer: Paolo Manildo + description: |- + Hamiltonian Monte Carlo for both continuous and discontinuous + posterior distributions with customisable trajectory length + termination criterion. See Nishimura et al. (2020) for + the original Discontinuous Hamiltonian Monte Carlo, + Hoffman et al. (2014) and Betancourt (2016) + for the definition of possible Hamiltonian + Monte Carlo termination criteria. + date_publication: '2025-01-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XDNUTS + url_git: '' +xdvir: + version: 0.1-2 + title: Render 'LaTeX' in Plots + maintainer: Paul Murrell + description: |- + High-level functions to render 'LaTeX' fragments in plots, + including as labels and data symbols in 'ggplot2' plots, plus + low-level functions to + author 'LaTeX' fragments (to produce 'LaTeX' documents), + typeset 'LaTeX' documents (to produce 'DVI' files), + read 'DVI' files (to produce "DVI" objects), + and render "DVI" objects. + date_publication: '2025-02-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xdvir + url_git: '' +xefun: + version: 0.1.5 + title: X-Engineering or Supporting Functions + maintainer: Shichen Xie + description: |- + Miscellaneous functions used for x-engineering (feature engineering) or + for supporting in other packages maintained by 'Shichen Xie'. + date_publication: '2023-08-10' + bug_reports: https://github.com/ShichenXie/xefun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xefun + url_git: https://github.com/ShichenXie/xefun +xega: + version: 0.9.0.0 + title: Extended Evolutionary and Genetic Algorithms + maintainer: Andreas Geyer-Schulz + description: |2- + + Implementation of a scalable, highly configurable, and + e(x)tended architecture for (e)volutionary and (g)enetic (a)lgorithms. + Multiple representations (binary, real-coded, permutation, and + derivation-tree), a rich collection of genetic operators, + as well as an extended processing pipeline are provided + for genetic algorithms (Goldberg, D. E. (1989, ISBN:0-201-15767-5)), + differential evolution (Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) + ), simulated annealing (Aarts, E., and Korst, J. + (1989, ISBN:0-471-92146-7)), grammar-based genetic programming + (Geyer-Schulz (1997, ISBN:978-3-7908-0830-X)), and grammatical evolution + (Ryan, C., O'Neill, M., and Collins, J. J. (2018) ). + All algorithms reuse basic adaptive mechanisms for performance optimization. + Sequential or parallel execution (on multi-core machines, + local clusters, and high performance computing environments) + is available for all algorithms. See + . + date_publication: '2024-03-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xega + url_git: +xegaBNF: + version: 1.0.0.0 + title: |- + Compile a Backus-Naur Form Specification into an R Grammar + Object + maintainer: Andreas Geyer-Schulz + description: |- + Translates a BNF (Backus-Naur Form) specification of a + context-free language into an R grammar object + which consists of the start symbol, the symbol table, + the production table, and a short production table. + The short production table is non-recursive. + The grammar object contains the file name from + which it was generated (without a path). + In addition, it provides functions to determine the type + of a symbol (isTerminal() and isNonterminal()) and functions + to access the production table (rules() and derives()). + For the BNF specification, see Backus, John et al. (1962) + "Revised Report on the Algorithmic Language ALGOL 60". + (ALGOL60 standards page , + html-edition ) + The grammar compiler is based on the APL2 implementation in + Geyer-Schulz, Andreas (1997, ISBN:978-3-7908-0830-X). + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaBNF + url_git: +xegaDerivationTrees: + version: 1.0.0.0 + title: Generating and Manipulating Derivation Trees + maintainer: Andreas Geyer-Schulz + description: |- + Derivation tree operations are needed for implementing + grammar-based genetic programming and grammatical evolution: + Generating of a random derivation trees of a context-free grammar + of bounded depth, decoding a derivation tree, + choosing a random node in a derivation tree, + extracting a tree whose root is a specified node, and + inserting a subtree into a derivation tree at a specified node. + These operations are necessary for the initializiation and + for decoders of a random population of programs, + as well as for implementing crossover and mutation operators. + Depth-bounds are guaranteed by switching to a grammar + without recursive production rules. + For executing the examples, the package 'BNF' is needed. + The basic tree operations of generating, extracting, and + inserting of derivation trees as well as the conditions + for guaranteeing complete derivation trees have been + presented in Geyer-Schulz (1997, ISBN:978-3-7908-0830-X). + The use of random integer vectors for the generation + of derivation trees has been introduced in + Ryan, C., Collins, J. J., and O'Neill, M. (1998) + . + date_publication: '2024-02-13' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaDerivationTrees + url_git: +xegaDfGene: + version: 1.0.0.0 + title: Gene Operations for Real-Coded Genes + maintainer: Andreas Geyer-Schulz + description: |- + Representation-dependent gene level operations + for genetic and evolutionary algorithms with real-coded genes + are collected in this package. The common feature of the gene + operations is that all of them are useful for derivation-free + optimization algorithms. At the moment the package + implements initialization, mutation, crossover, and replication + operations for differential evolution as described in + Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) + . + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaDfGene + url_git: +xegaGaGene: + version: 1.0.0.1 + title: Binary Gene Operations for Genetic Algorithms + maintainer: Andreas Geyer-Schulz + description: |- + Representation-dependent gene level operations of a + genetic algorithm with binary coded genes: + Initialization of random binary genes, several gene maps for + binary genes, several mutation operators, several crossover + operators with 1 and 2 kids, replication + pipelines for 1 and 2 kids, and, last but not least, function + factories for configuration. + See Goldberg, D. E. (1989, ISBN:0-201-15767-5). + For crossover operators, see + Syswerda, G. (1989, ISBN:1-55860-066-3), + Spears, W. and De Jong, K. (1991, ISBN:1-55860-208-9). + For mutation operators, see + Stanhope, S. A. and Daida, J. M. (1996, ISBN:0-18-201-031-7). + date_publication: '2024-02-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaGaGene + url_git: +xegaGeGene: + version: 1.0.0.0 + title: Grammatical Evolution + maintainer: Andreas Geyer-Schulz + description: |- + Grammatical evolution (see O'Neil, M. and + Ryan, C. (2003,ISBN:1-4020-7444-1)) uses decoders to + convert linear (binary or integer genes) into programs. + In addition, automatic determination of codon precision + with a limited rule choice bias is provided. + For a recent survey of grammatical evolution, + see Ryan, C., O'Neill, M., and Collins, J. J. (2018) + . + date_publication: '2024-02-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaGeGene + url_git: +xegaGpGene: + version: 1.0.0.0 + title: Genetic Operations for Grammar-Based Genetic Programming + maintainer: Andreas Geyer-Schulz + description: |- + An implementation of + the representation-dependent gene level operations of grammar-based + genetic programming with genes which are derivation trees + of a context-free grammar: Initialization of a gene with a + complete random derivation tree, decoding of a derivation tree. + Crossover is implemented by exchanging subtrees. Depth-bounds + for the minimal and the maximal depth of the roots of the subtrees + exchanged by crossover can be set. + Mutation is implemented by replacing a subtree by a random subtree. + The depth of the random subtree and the insertion node are + configurable. For details, + see Geyer-Schulz (1997, ISBN:978-3-7908-0830-X). + date_publication: '2024-02-15' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaGpGene + url_git: +xegaPermGene: + version: 1.0.0.0 + title: Operations on Permutation Genes + maintainer: Andreas Geyer-Schulz + description: |- + An implementation of + representation-dependent gene level operations for + genetic algorithms with genes which represent permutations: + initialization of genes, mutation and crossover. + The crossover operation provided is position-based crossover + (Syswerda, G., Chap. 21 in Davis, L. (1991, ISBN:0-442-00173-8). + For mutation, several variants are included: Order-based mutation + (Syswerda, G., Chap. 21 in Davis, L. (1991, ISBN:0-442-00173-8), + randomized Lin-Kernighan heuristics + (Croes, G. A. (1958) and + Lin, S. and Kernighan. B. W. (1973) + ), + and randomized greedy operators. + A random mix operator for mutation selects a mutation variant + randomly. + date_publication: '2024-02-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaPermGene + url_git: +xegaPopulation: + version: 1.0.0.0 + title: Genetic Population Level Functions + maintainer: Andreas Geyer-Schulz + description: |- + This collection of gene representation-independent functions + implements the population layer of extended evolutionary and genetic + algorithms and its support. The population layer consists of functions + for initializing, logging, observing, evaluating a population of genes, + as well as of computing the next population. For parallel evaluation of a + population of genes 4 execution models - named Sequential, MultiCore, + FutureApply, and Cluster - are provided. They are implemented by + configuring the lapply() function. The execution model FutureApply can be + externally configured as recommended by Bengtsson (2021) + . Configurable acceptance rules and cooling + schedules (see Kirkpatrick, S., Gelatt, C. D. J, and Vecchi, M. P. (1983) + , and Aarts, E., and Korst, J. + (1989, ISBN:0-471-92146-7) offer simulated annealing or greedy randomized + approximate search procedure elements. Adaptive crossover and mutation + rates depending on population statistics generalize the approach of + Stanhope, S. A. and Daida, J. M. (1996, ISBN:0-18-201-031-7). + date_publication: '2024-03-04' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaPopulation + url_git: +xegaSelectGene: + version: 1.0.0.0 + title: Selection of Genes and Gene Representation Independent Functions + maintainer: Andreas Geyer-Schulz + description: |- + This collection of gene representation-independent + mechanisms for evolutionary and genetic algorithms contains + four groups of functions: + First, functions for selecting a gene + in a population of genes according to its fitness value + and for adaptive scaling of the fitness values as well as for + performance optimization and measurement offer several + variants for implementing the survival of the fittest. + Second, evaluation functions for + deterministic functions avoid recomputation. + Evaluation of stochastic functions incrementally improve + the estimation of the mean and variance of fitness values + at almost no additional cost. Evaluation functions + for gene repair handle error-correcting decoders. + Third, timing and counting functions for profiling the + algorithm pipeline are provided to assess bottlenecks in + the algorithms. + Fourth, a small collection of problem environments + for function optimization, combinatorial optimization, and + grammar-based genetic programming and grammatical evolution + is provided for tutorial examples. + The methods in the package are described by the following + references: + Baker, James E. (1987, ISBN:978-08058-0158-8), + De Jong, Kenneth A. (1975) + , + Geyer-Schulz, Andreas (1997, ISBN:978-3-7908-0830-X), + Grefenstette, John J. (1987, ISBN:978-08058-0158-8), + Grefenstette, John J. and Baker, James E. + (1989, ISBN:1-55860-066-3), + Holland, John (1975, ISBN:0-472-08460-7), + Lau, H. T. (1986) , + Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) + , + Reynolds, J. C. (1993) , + Schaffer, J. David (1989, ISBN:1-55860-066-3), + Wenstop, Fred (1980) , + Whitley, Darrell (1989, ISBN:1-55860-066-3), + Wickham, Hadley (2019, ISBN:978-815384571). + date_publication: '2024-02-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xegaSelectGene + url_git: +xergm.common: + version: 1.7.8 + title: |- + Common Infrastructure for Extensions of Exponential Random Graph + Models + maintainer: Philip Leifeld + description: Datasets and definitions of generic functions used in dependencies + of the 'xergm' package. + date_publication: '2020-04-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xergm.common + url_git: http://github.com/leifeld/xergm.common +xesreadR: + version: 0.2.3 + title: Read and Write XES Files + maintainer: Gert Janssenswillen + description: Read and write XES Files to create event log objects used by the 'bupaR' + framework. XES (Extensible Event Stream) is the `IEEE` standard for storing and + sharing event data (see + for more info). + date_publication: '2019-03-19' + bug_reports: '' + url: http://www.bupar.net + url_cran: https://CRAN.R-project.org/package=xesreadR + url_git: '' +xfun: + version: '0.51' + title: Supporting Functions for Packages Maintained by 'Yihui Xie' + maintainer: Yihui Xie + description: Miscellaneous functions commonly used in other packages maintained + by 'Yihui Xie'. + date_publication: '2025-02-19' + bug_reports: https://github.com/yihui/xfun/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xfun + url_git: https://github.com/yihui/xfun +xgb2sql: + version: 0.1.2 + title: Convert Trained 'XGBoost' Model to SQL Query + maintainer: Chengjun Hou + description: |- + This tool enables in-database scoring of 'XGBoost' models built in R, by translating trained model objects into SQL query. + 'XGBoost' provides parallel tree boosting (also known as gradient boosting machine, or GBM) algorithms + in a highly efficient, flexible and portable way. GBM algorithm is introduced by Friedman (2001) , + and more details on 'XGBoost' can be found in Chen & Guestrin (2016) . + date_publication: '2019-03-13' + bug_reports: https://github.com/chengjunhou/xgb2sql/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xgb2sql + url_git: https://github.com/chengjunhou/xgb2sql +xgboost: + version: 1.7.8.1 + title: Extreme Gradient Boosting + maintainer: Jiaming Yuan + description: |- + Extreme Gradient Boosting, which is an efficient implementation + of the gradient boosting framework from Chen & Guestrin (2016) . + This package is its R interface. The package includes efficient linear + model solver and tree learning algorithms. The package can automatically + do parallel computation on a single machine which could be more than 10 + times faster than existing gradient boosting packages. It supports + various objective functions, including regression, classification and ranking. + The package is made to be extensible, so that users are also allowed to define + their own objectives easily. + date_publication: '2024-07-24' + bug_reports: https://github.com/dmlc/xgboost/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xgboost + url_git: https://github.com/dmlc/xgboost +xgrove: + version: 0.1-15 + title: Explanation Groves + maintainer: Gero Szepannek + description: Compute surrogate explanation groves for predictive machine learning + models and analyze complexity vs. explanatory power of an explanation according + to Szepannek, G. and von Holt, B. (2023) . + date_publication: '2025-01-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xgrove + url_git: '' +xgxr: + version: 1.1.2 + title: Exploratory Graphics for Pharmacometrics + maintainer: Andrew Stein + description: |- + Supports a structured approach + for exploring PKPD data . It also + contains helper functions for enabling the modeler to follow best R + practices (by appending the program name, figure name location, and + draft status to each plot). In addition, it enables the modeler to + follow best graphical practices (by providing a theme that + reduces chart ink, and by providing time-scale, log-scale, and + reverse-log-transform-scale functions for more readable axes). + Finally, it provides some data checking and summarizing functions for + rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets. + date_publication: '2023-03-22' + bug_reports: https://github.com/Novartis/xgxr/issues + url: https://opensource.nibr.com/xgx/ + url_cran: https://CRAN.R-project.org/package=xgxr + url_git: '' +xhaz: + version: 2.0.2 + title: |- + Excess Hazard Modelling Considering Inappropriate Mortality + Rates + maintainer: Juste Goungounga + description: Fits relative survival regression models with or without proportional + excess hazards and with the additional possibility to correct for background mortality + by one or more parameter(s). These models are relevant when the observed mortality + in the studied group is not comparable to that of the general population or in + population-based studies where the available life tables used for net survival + estimation are insufficiently stratified. In the latter case, the proposed model + by Touraine et al. (2020) can be used. The user + can also fit a model that relaxes the proportional expected hazards assumption + considered in the Touraine et al. excess hazard model. This extension was proposed + by Mba et al. (2020) to allow non-proportional + effects of the additional variable on the general population mortality. In non-population-based + studies, researchers can identify non-comparability source of bias in terms of + expected mortality of selected individuals. An excess hazard model correcting + this selection bias is presented in Goungounga et al. (2019) . + This class of model with a random effect at the cluster level on excess hazard + is presented in Goungounga et al. (2023) . + date_publication: '2024-06-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xhaz + url_git: '' +XICOR: + version: 0.4.1 + title: Association Measurement Through Cross Rank Increments + maintainer: Susan Holmes + description: |- + Computes robust association measures that do not + presuppose linearity. The xi correlation (xicor) is based + on cross correlation between ranked increments. + The reference for the methods implemented here is + Chatterjee, Sourav (2020) + This package includes the Galton peas example. + date_publication: '2023-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XICOR + url_git: '' +XiMpLe: + version: 0.11-3 + title: A Simple XML Tree Parser and Generator + maintainer: Meik Michalke + description: |- + Provides a simple XML tree parser/generator. It includes + functions to read XML files into R objects, get information out of + and into nodes, and write R objects back to XML code. It's not as + powerful as the 'XML' package and doesn't aim to be, but for simple + XML handling it could be useful. It was originally developed for + the R GUI and IDE 'RKWard' , to make plugin + development easier. + date_publication: '2024-07-23' + bug_reports: https://github.com/rkward-community/XiMpLe/issues + url: https://reaktanz.de/?c=hacking&s=XiMpLe + url_cran: https://CRAN.R-project.org/package=XiMpLe + url_git: '' +xkcd: + version: 0.0.6 + title: Plotting ggplot2 Graphics in an XKCD Style + maintainer: Emilio Torres-Manzanera + description: Plotting ggplot2 graphs using the XKCD style. + date_publication: '2018-07-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xkcd + url_git: '' +xkcdcolors: + version: '1.0' + title: Color Names from the XKCD Color Survey + maintainer: Thomas Lumley + description: The XKCD color survey asked participants to name colours. Randall Munroe + published the top thousand(roughly) names and their sRGB hex values. This package + lets you use them. + date_publication: '2016-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xkcdcolors + url_git: '' +XKCDdata: + version: 0.1.0 + title: Get XKCD Comic Data + maintainer: Robert Myles McDonnell + description: Download data from individual XKCD comics, written by Randall Munroe + . + date_publication: '2017-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XKCDdata + url_git: '' +xlcharts: + version: 0.0.2 + title: |- + Create Native 'Excel' Charts and Work with Microsoft 'Excel' + Files + maintainer: Felix Luginbuhl + description: |- + An R interface to the 'OpenPyXL' 'Python' library to create + native 'Excel' charts and work with Microsoft 'Excel' files. + date_publication: '2024-04-22' + bug_reports: https://github.com/lgnbhl/xlcharts/issues + url: https://felixluginbuhl.com/xlcharts/ + url_cran: https://CRAN.R-project.org/package=xlcharts + url_git: '' +XLConnect: + version: 1.2.0 + title: Excel Connector for R + maintainer: Martin Studer + description: Provides comprehensive functionality to read, write and format Excel + data. + date_publication: '2025-02-18' + bug_reports: https://github.com/miraisolutions/xlconnect/issues + url: '' + url_cran: https://CRAN.R-project.org/package=XLConnect + url_git: https://mirai-solutions.chhttps://github.com/miraisolutions/xlconnect +xlcutter: + version: 0.1.1 + title: Parse Batches of 'xlsx' Files Based on a Template + maintainer: Hugo Gruson + description: |- + Parse entire folders of non-rectangular 'xlsx' files into a single + rectangular and tidy 'data.frame' based on a custom template file defining the + column names of the output. + date_publication: '2023-10-22' + bug_reports: https://github.com/Bisaloo/xlcutter/issues + url: https://hugogruson.fr/xlcutter/ + url_cran: https://CRAN.R-project.org/package=xlcutter + url_git: https://github.com/Bisaloo/xlcutter +xlink: + version: 1.0.1 + title: |- + Genetic Association Models for X-Chromosome SNPS on Continuous, + Binary and Survival Outcomes + maintainer: Yi Zhu + description: |- + The expression of X-chromosome undergoes three possible biological processes: X-chromosome + inactivation (XCI), escape of the X-chromosome inactivation (XCI-E),and skewed X-chromosome + inactivation (XCI-S). To analyze the X-linked genetic association for phenotype such as + continuous, binary, and time-to-event outcomes with the actual process unknown, we propose a unified + approach of maximizing the likelihood or partial likelihood over all of the potential biological + processes. The methods are described in Wei Xu, Meiling Hao (2017) . And + also see Dongxiao Han, Meiling Hao, Lianqiang Qu, Wei Xu (2019) . + date_publication: '2019-08-20' + bug_reports: https://github.com/qiuanzhu/xlink/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xlink + url_git: https://github.com/qiuanzhu/xlink +xLLiM: + version: '2.3' + title: High Dimensional Locally-Linear Mapping + maintainer: Emeline Perthame + description: Provides a tool for non linear mapping (non linear regression) using + a mixture of regression model and an inverse regression strategy. The methods + include the GLLiM model (see Deleforge et al (2015) ) + based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame + et al (2016) ) based on a mixture of Generalized + Student distributions. The methods also include BLLiM (see Devijver et al (2017) + ) which is an extension of GLLiM with a sparse block diagonal + structure for large covariance matrices (particularly interesting for transcriptomic + data). + date_publication: '2023-10-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xLLiM + url_git: '' +XLS: + version: 0.1.0 + title: |- + A Modeling Approach that Optimizes Future Errors in Least + Squares + maintainer: Samet Sokel + description: Given the date column as an ascending entry, future errors are included + in the sum of squares of error that should be minimized based on the number of + steps and weights you determine. Thus, it is prevented that the variables affect + each other's coefficients unrealistically. + date_publication: '2022-03-10' + bug_reports: https://github.com/sametsoekel/eXtreme-Least-Squares/issues + url: '' + url_cran: https://CRAN.R-project.org/package=XLS + url_git: '' +xlsx: + version: 0.6.5 + title: Read, Write, Format Excel 2007 and Excel 97/2000/XP/2003 Files + maintainer: Cole Arendt + description: Provide R functions to read/write/format Excel 2007 and Excel 97/2000/XP/2003 + file formats. + date_publication: '2020-11-10' + bug_reports: https://github.com/colearendt/xlsx/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xlsx + url_git: https://github.com/colearendt/xlsx +xlsx2dfs: + version: 0.1.0 + title: Read and Write 'Excel' Sheets into and from List of Data Frames + maintainer: Gwang-Jin Kim + description: Reading and writing sheets of a single 'Excel' file into and from a + list of data frames. Eases I/O of tabular data in bioinformatics while keeping + them in a human readable format. + date_publication: '2019-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xlsx2dfs + url_git: '' +xlsxjars: + version: 0.6.1 + title: Package required POI jars for the xlsx package + maintainer: Adrian A. Dragulescu + description: The xlsxjars package collects all the external jarsrequired + for the xlxs package. This release corresponds to POI3.10.1. + date_publication: '2014-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xlsxjars + url_git: '' +xmap: + version: 0.1.0 + title: Transforming Data Between Statistical Classifications + maintainer: Cynthia A. Huang + description: |- + Provides support for transformations of numeric aggregates + between statistical classifications (e.g. occupation or industry categorisations) using the 'Crossmaps' framework. + Implements classes for representing transformations between a source and target classification + as graph structures, and methods for validating and applying crossmaps to transform + data collected under the source classification into data indexed using the target classification codes. + Documentation about the 'Crossmaps' framework is provided in the included vignettes + and in Huang (2024, ). + date_publication: '2025-01-31' + bug_reports: https://github.com/cynthiahqy/xmap/issues + url: https://cynthiahqy.github.io/xmap/ + url_cran: https://CRAN.R-project.org/package=xmap + url_git: https://github.com/cynthiahqy/xmap +xmeta: + version: 1.3.2 + title: A Toolbox for Multivariate Meta-Analysis + maintainer: Jiajie Chen + description: 'A toolbox for meta-analysis. This package includes: 1,a robust multivariate + meta-analysis of continuous or binary outcomes; 2, a bivariate Egger''s test for + detecting small study effects; 3, Galaxy Plot: A New Visualization Tool of Bivariate + Meta-Analysis Studies; 4, a bivariate T&F method accounting for publication bias + in bivariate meta-analysis, based on symmetry of the galaxy plot. Hong C. et al(2020) + , Chongliang L. et al(2020) .' + date_publication: '2023-09-07' + bug_reports: https://github.com/Penncil/xmeta/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xmeta + url_git: https://github.com/Penncil/xmeta +XML: + version: 3.99-0.18 + title: Tools for Parsing and Generating XML Within R and S-Plus + maintainer: CRAN Team + description: |- + Many approaches for both reading and + creating XML (and HTML) documents (including DTDs), both local + and accessible via HTTP or FTP. Also offers access to an + 'XPath' "interpreter". + date_publication: '2025-01-01' + bug_reports: '' + url: https://www.omegahat.net/RSXML/ + url_cran: https://CRAN.R-project.org/package=XML + url_git: '' +xml2: + version: 1.3.7 + title: Parse XML + maintainer: Jeroen Ooms + description: |- + Bindings to 'libxml2' for working with XML data using a simple, + consistent interface based on 'XPath' expressions. Also supports XML schema + validation; for 'XSLT' transformations see the 'xslt' package. + date_publication: '2025-02-28' + bug_reports: https://github.com/r-lib/xml2/issues + url: https://xml2.r-lib.org + url_cran: https://CRAN.R-project.org/package=xml2 + url_git: '' +XML2R: + version: 0.0.8 + title: Easier XML Data Collection + maintainer: Carson Sievert + description: |- + Helpers for transforming + XML content into number of tables while preserving parent to child + relationships. + date_publication: '2024-06-04' + bug_reports: https://github.com/cpsievert/XML2R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=XML2R + url_git: https://github.com/cpsievert/XML2R +xml2relational: + version: 0.1.1 + title: Converting XML Documents into Relational Data Models + maintainer: Joachim Zuckarelli + description: |- + Import an XML document with nested object structures and convert + it into a relational data model. The result is a set of R dataframes + with foreign key relationships. The data model and the data can be exported as + SQL code of different SQL flavors. + date_publication: '2022-02-10' + bug_reports: https://github.com/jsugarelli/xml2relational/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xml2relational + url_git: https://github.com/jsugarelli/xml2relational/ +xmlconvert: + version: 0.1.2 + title: |- + Comfortably Converting XML Documents to Dataframes and Vice + Versa + maintainer: Joachim Zuckarelli + description: |- + Converts XML documents to R dataframes and dataframes to XML documents. + A wide variety of options allows for different XML formats and flexible control + of the conversion process. Results can be exported to CSV and Excel, if desired. + Also converts XML data to R lists. + date_publication: '2021-03-27' + bug_reports: https://github.com/jsugarelli/xmlconvert/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xmlconvert + url_git: https://github.com/jsugarelli/xmlconvert/ +xmlparsedata: + version: 1.0.5 + title: Parse Data of 'R' Code as an 'XML' Tree + maintainer: Gábor Csárdi + description: |- + Convert the output of 'utils::getParseData()' to an 'XML' + tree, that one can search via 'XPath', and easier to manipulate in + general. + date_publication: '2021-03-06' + bug_reports: https://github.com/r-lib/xmlparsedata/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xmlparsedata + url_git: https://github.com/r-lib/xmlparsedata#readme +xmlr: + version: 0.1.2 + title: Read, Write and Work with 'XML' Data + maintainer: Per Nyfelt + description: '''XML'' package for creating and reading and manipulating ''XML'', + with an object model based on ''Reference Classes''.' + date_publication: '2020-05-12' + bug_reports: https://github.com/Alipsa/xmlr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xmlr + url_git: https://github.com/Alipsa/xmlr +xmlrpc2: + version: '1.1' + title: Implementation of the Remote Procedure Call Protocol ('XML-RPC') + maintainer: Florian Schwendinger + description: |- + The 'XML-RPC' is a remote procedure call protocol + based on 'XML'. The 'xmlrpc2' package is inspired by the 'XMLRPC' + package but uses the 'curl' and 'xml2' packages instead 'RCurl' and 'XML'. + date_publication: '2018-08-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xmlrpc2 + url_git: '' +xmlwriter: + version: 0.1.1 + title: Fast and Elegant XML Generation + maintainer: Edwin de Jonge + description: |- + Provides a fast and elegant interface for generating XML + fragments and documents. It can be used in companion with R packages 'XML' + or 'xml2' to generate XML documents. The fast XML generation is implemented using the + 'Rcpp' package. + date_publication: '2024-09-25' + bug_reports: '' + url: https://edwindj.github.io/xmlwriter/ + url_cran: https://CRAN.R-project.org/package=xmlwriter + url_git: '' +xmpdf: + version: 0.2.1 + title: Edit 'XMP' Metadata and 'PDF' Bookmarks and Documentation Info + maintainer: Trevor L Davis + description: |- + Edit 'XMP' metadata + in a variety of media file formats as well as + edit bookmarks (aka outline aka table of contents) and documentation info entries in 'pdf' files. + Can detect and use a variety of command-line tools to perform these operations such as + 'exiftool' , 'ghostscript' , + and/or 'pdftk' . + date_publication: '2024-03-29' + bug_reports: https://github.com/trevorld/r-xmpdf/issues + url: https://trevorldavis.com/R/xmpdf/dev/ + url_cran: https://CRAN.R-project.org/package=xmpdf + url_git: '' +xmrr: + version: 1.1.1 + title: Generate XMR Control Chart Data from Time-Series Data + maintainer: Alex Zanidean + description: XMRs combine X-Bar control charts and Moving Range control charts. + These functions also will recalculate the reference lines when significant change + has occurred. + date_publication: '2020-06-08' + bug_reports: https://github.com/Zanidean/xmrr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xmrr + url_git: '' +xnet: + version: 0.1.11 + title: Two-Step Kernel Ridge Regression for Network Predictions + maintainer: Joris Meys + description: |- + Fit a two-step kernel ridge regression model for + predicting edges in networks, and carry out cross-validation + using shortcuts for swift and accurate performance assessment + (Stock et al, 2018 ). + date_publication: '2020-02-03' + bug_reports: https://github.com/CenterForStatistics-UGent/xnet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xnet + url_git: https://github.com/CenterForStatistics-UGent/xnet +XNomial: + version: 1.0.4.1 + title: |- + Exact Goodness-of-Fit Test for Multinomial Data with Fixed + Probabilities + maintainer: Bill Engels + description: |- + Tests whether a set of counts fit a given expected ratio. For + example, a genetic cross might be expected to produce four types in the + relative frequencies of 9:3:3:1. To see whether a set of observed counts + fits this expectation, one can examine all possible outcomes with xmulti() or a + random sample of them with xmonte() and find the probability of an observation + deviating from the expectation by at least as much as the observed. As a + measure of deviation from the expected, one can use the log-likelihood + ratio, the multinomial probability, or the classic chi-square statistic. A + histogram of the test statistic can also be plotted and compared with the + asymptotic curve. + date_publication: '2024-11-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XNomial + url_git: '' +xoi: + version: '0.72' + title: Tools for Analyzing Crossover Interference + maintainer: Karl W Broman + description: |- + Analysis of crossover interference in experimental crosses, + particularly regarding the gamma model. See, for example, + Broman and Weber (2000) . + date_publication: '2023-03-22' + bug_reports: https://github.com/kbroman/xoi/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xoi + url_git: https://github.com/kbroman/xoi +xopen: + version: 1.0.1 + title: Open System Files, 'URLs', Anything + maintainer: Gábor Csárdi + description: |- + Cross platform solution to open files, directories or 'URLs' + with their associated programs. + date_publication: '2024-04-25' + bug_reports: https://github.com/r-lib/xopen/issues + url: https://r-lib.github.io/xopen/ + url_cran: https://CRAN.R-project.org/package=xopen + url_git: https://github.com/r-lib/xopen#readme +xpectr: + version: 0.4.3 + title: Generates Expectations for 'testthat' Unit Testing + maintainer: Ludvig Renbo Olsen + description: |- + Helps systematize and ease the process of + building unit tests with the 'testthat' package by providing + tools for generating expectations. + date_publication: '2022-11-18' + bug_reports: https://github.com/ludvigolsen/xpectr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xpectr + url_git: https://github.com/ludvigolsen/xpectr +xplain: + version: 0.2.2 + title: |- + Providing Interactive Interpretations and Explanations of + Statistical Results + maintainer: Joachim Zuckarelli + description: |- + Allows to provide live interpretations and explanations of statistical + functions in R. These interpretations and explanations are shown when the explained function + is called by the user. They can interact with the values of the explained function's actual + results to offer relevant, meaningful insights. The 'xplain' interpretations and explanations + are based on an easy-to-use XML format that allows to include R code to interact with the + returns of the explained function. + date_publication: '2020-07-30' + bug_reports: https://github.com/jsugarelli/xplain/issues + url: https://www.zuckarelli.de/xplain/index.html + url_cran: https://CRAN.R-project.org/package=xplain + url_git: https://github.com/jsugarelli/xplain/ +xplorerr: + version: 0.2.0 + title: Tools for Interactive Data Exploration + maintainer: Aravind Hebbali + description: |- + Tools for interactive data exploration built using 'shiny'. Includes apps for descriptive + statistics, visualizing probability distributions, inferential statistics, linear regression, + logistic regression and RFM analysis. + date_publication: '2024-10-29' + bug_reports: https://github.com/rsquaredacademy/xplorerr/issues + url: https://xplorerr.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=xplorerr + url_git: https://github.com/rsquaredacademy/xplorerr +Xplortext: + version: 1.5.5 + title: Statistical Analysis of Textual Data + maintainer: Ramón Alvarez-Esteban + description: Provides a set of functions devoted to multivariate exploratory statistics + on textual data. Classical methods such as correspondence analysis and agglomerative + hierarchical clustering are available. Chronologically constrained agglomerative + hierarchical clustering enriched with labelled-by-words trees is offered. Given + a division of the corpus into parts, their characteristic words and documents + are identified. Further, accessing to 'FactoMineR' functions is very easy. Two + of them are relevant in textual domain. MFA() addresses multiple lexical table + allowing applications such as dealing with multilingual corpora as well as simultaneously + analyzing both open-ended and closed questions in surveys. See + for examples. + date_publication: '2024-11-13' + bug_reports: '' + url: https://xplortext.unileon.es + url_cran: https://CRAN.R-project.org/package=Xplortext + url_git: '' +xportr: + version: 0.4.2 + title: Utilities to Output CDISC SDTM/ADaM XPT Files + maintainer: Eli Miller + description: |- + Tools to build CDISC compliant data sets and check for CDISC + compliance. + date_publication: '2025-01-07' + bug_reports: https://github.com/atorus-research/xportr/issues + url: https://atorus-research.github.io/xportr/ + url_cran: https://CRAN.R-project.org/package=xportr + url_git: https://github.com/atorus-research/xportr +xpose: + version: 0.4.19 + title: Diagnostics for Pharmacometric Models + maintainer: Benjamin Guiastrennec + description: |- + Diagnostics for non-linear mixed-effects (population) + models from 'NONMEM' . + 'xpose' facilitates data import, creation of numerical run summary + and provide 'ggplot2'-based graphics for data exploration and model + diagnostics. + date_publication: '2025-01-07' + bug_reports: https://github.com/UUPharmacometrics/xpose/issues/ + url: https://uupharmacometrics.github.io/xpose/ + url_cran: https://CRAN.R-project.org/package=xpose + url_git: https://github.com/UUPharmacometrics/xpose/ +xpose.nlmixr2: + version: 0.4.0 + title: |- + Graphical Diagnostics for Pharmacometric Models: Extension to + 'nlmixr2' + maintainer: Justin Wilkins + description: Extension to 'xpose' to support 'nlmixr2'. Provides functions to import + 'nlmixr2' fit data into an 'xpose' data object, allowing the use of 'xpose' for + 'nlmixr2' model diagnostics. + date_publication: '2022-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xpose.nlmixr2 + url_git: '' +xpose.xtras: + version: 0.0.2 + title: Extra Functionality for the 'xpose' Package + maintainer: John Prybylski + description: |- + Adding some at-present missing functionality, or functions + unlikely to be added to the base 'xpose' package. This includes some + diagnostic plots that have been missing in translation from 'xpose4', + but also some useful features that truly extend the capabilities of what + can be done with 'xpose'. These extensions include the concept of a set of + 'xpose' objects, and diagnostics for likelihood-based models. + date_publication: '2024-11-21' + bug_reports: '' + url: https://jprybylski.github.io/xpose.xtras/ + url_cran: https://CRAN.R-project.org/package=xpose.xtras + url_git: https://github.com/jprybylski/xpose.xtras +xpose4: + version: 4.7.3 + title: Diagnostics for Nonlinear Mixed-Effect Models + maintainer: Andrew C. Hooker + description: |- + A model building aid for nonlinear mixed-effects + (population) model analysis using NONMEM, facilitating data set + checkout, exploration and visualization, model diagnostics, candidate + covariate identification and model comparison. The methods are described + in Keizer et al. (2013) , and Jonsson et al. (1999) + . + date_publication: '2024-02-22' + bug_reports: https://github.com/UUPharmacometrics/xpose4/issues + url: https://uupharmacometrics.github.io/xpose4/ + url_cran: https://CRAN.R-project.org/package=xpose4 + url_git: https://github.com/UUPharmacometrics/xpose4 +XR: + version: 0.7.2 + title: A Structure for Interfaces from R + maintainer: John Chambers + description: |- + Support for interfaces from R to other languages, + built around a class for evaluators and a combination of functions, classes and + methods for communication. Will be used through a specific language interface + package. Described in the book "Extending R". + date_publication: '2018-03-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XR + url_git: '' +xray: + version: '0.2' + title: X Ray Vision on your Datasets + maintainer: Pablo Seibelt + description: |- + Tools to analyze datasets previous to any statistical modeling. + Has various functions designed to find inconsistencies and understanding the distribution of the data. + date_publication: '2017-12-08' + bug_reports: https://github.com/sicarul/xray/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xray + url_git: https://github.com/sicarul/xray/ +xrf: + version: 0.2.2 + title: eXtreme RuleFit + maintainer: Karl Holub + description: |- + An implementation of the RuleFit algorithm as described in Friedman & Popescu + (2008) . eXtreme Gradient Boosting ('XGBoost') is used + to build rules, and 'glmnet' is used to fit a sparse linear model on the raw and rule features. The result + is a model that learns similarly to a tree ensemble, while often offering improved interpretability + and achieving improved scoring runtime in live applications. Several algorithms for + reducing rule complexity are provided, most notably hyperrectangle de-overlapping. All algorithms scale to + several million rows and support sparse representations to handle tens of thousands of dimensions. + date_publication: '2022-10-04' + bug_reports: https://github.com/holub008/xrf/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xrf + url_git: https://github.com/holub008/xrf +xRing: + version: 0.1.1 + title: Identify and Measure Tree Rings on X-Ray Micro-Density Profiles + maintainer: Filipe Campelo + description: Contains functions to identify tree-ring borders based on X-ray micro-density + profiles and a Graphical User Interface (GUI) to visualize density profiles and + correct tree-ring borders. Campelo F, Mayer K, Grabner M. (2019) . + date_publication: '2022-04-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xRing + url_git: '' +XRJulia: + version: 0.9.0.1 + title: Structured Interface to Julia + maintainer: John Chambers + description: |- + A Julia interface structured according to the general + form described in package 'XR' and in the book "Extending R". + date_publication: '2024-04-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XRJulia + url_git: '' +xrnet: + version: 1.0.0 + title: Hierarchical Regularized Regression + maintainer: Garrett Weaver + description: |- + Fits hierarchical regularized regression models + to incorporate potentially informative external data, Weaver and Lewinger (2019) . + Utilizes coordinate descent to efficiently fit regularized regression models both with and without + external information with the most common penalties used in practice (i.e. ridge, lasso, elastic net). + Support for standard R matrices, sparse matrices and big.matrix objects. + date_publication: '2024-07-16' + bug_reports: https://github.com/USCbiostats/xrnet/issues + url: https://uscbiostats.github.io/xrnet/ + url_cran: https://CRAN.R-project.org/package=xrnet + url_git: https://github.com/USCbiostats/xrnet +XRPython: + version: '0.8' + title: Structured Interface to 'Python' + maintainer: John Chambers + description: |- + A 'Python' interface structured according to the general + form described in package 'XR' and in the book "Extending R". + date_publication: '2017-10-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XRPython + url_git: '' +XRSCC: + version: '0.2' + title: Statistical Quality Control Simulation + maintainer: Erick Marroquin + description: This is a set of statistical quality control functions, that allows + plotting control charts and its iterations, process capability for variable and + attribute control, highlighting the xrs_gr() function, like a first iteration + for variable chart, meanwhile the we_rules() function detects non random patterns + in sample. + date_publication: '2024-12-06' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=XRSCC + url_git: '' +xslt: + version: 1.5.1 + title: Extensible Style-Sheet Language Transformations + maintainer: Jeroen Ooms + description: |- + An extension for the 'xml2' package to transform XML documents + by applying an 'xslt' style-sheet. + date_publication: '2025-02-27' + bug_reports: https://github.com/ropensci/xslt/issues + url: https://ropensci.r-universe.dev/xslthttps://docs.ropensci.org/xslt/ + url_cran: https://CRAN.R-project.org/package=xslt + url_git: '' +xsp: + version: 0.1.2 + title: The Chi-Square Periodogram + maintainer: Hitoshi Iuchi + description: The circadian period of a time series data is predicted and the statistical + significance of the periodicity are calculated using the chi-square periodogram. + date_publication: '2017-06-08' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xsp + url_git: '' +xSub: + version: 3.0.2 + title: Cross-National Data on Sub-National Violence + maintainer: Yuri Zhukov + description: Tools to download and merge data files on sub-national conflict, violence + and protests from . + date_publication: '2022-06-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xSub + url_git: https://github.com/zhukovyuri/xSub +xtable: + version: 1.8-4 + title: Export Tables to LaTeX or HTML + maintainer: David Scott + description: Coerce data to LaTeX and HTML tables. + date_publication: '2019-04-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xtable + url_git: http://xtable.r-forge.r-project.org/ +xtranat: + version: 0.1.0 + title: Network Metrics Based on Random Walks + maintainer: Fernando DePaolis + description: There are two new network metrics, RWC (random walk centrality) and + CBET (counting betweenness). Also available are the normalized versions of those + metrics. These measures of centrality and betweenness are particularly useful + for the analysis of very dense weighted networks which include loops. Traditional + measures do not work as well for those network characteristics. The main reference + is DePaolis at al (2022) . + date_publication: '2023-03-27' + bug_reports: https://github.com/fdepaolis/xtranat/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xtranat + url_git: https://github.com/fdepaolis/xtranat +xts: + version: 0.14.1 + title: eXtensible Time Series + maintainer: Joshua M. Ulrich + description: Provide for uniform handling of R's different time-based data classes + by extending zoo, maximizing native format information preservation and allowing + for user level customization and extension, while simplifying cross-class interoperability. + date_publication: '2024-10-15' + bug_reports: https://github.com/joshuaulrich/xts/issues + url: https://joshuaulrich.github.io/xts/ + url_cran: https://CRAN.R-project.org/package=xts + url_git: https://github.com/joshuaulrich/xts +xtsum: + version: 0.1.0 + title: Summary Statistics for Panel Data + maintainer: Joao Claudio Macosso + description: Based on 'STATA' xtsum command, it is used to compute summary statistics + for a panel data set. It generates overall, between-group, and within-group statistics + for specified variables in a panel data set, as presented in S. Porter (2023) + , StataCorp (2023) . + date_publication: '2023-12-07' + bug_reports: https://github.com/Macosso/xtsum/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xtsum + url_git: https://github.com/Macosso/xtsum +xtune: + version: 2.0.0 + title: |- + Regularized Regression with Feature-Specific Penalties + Integrating External Information + maintainer: Jingxuan He + description: Extends standard penalized regression (Lasso, Ridge, and Elastic-net) + to allow feature-specific shrinkage based on external information with the goal + of achieving a better prediction accuracy and variable selection. Examples of + external information include the grouping of predictors, prior knowledge of biological + importance, external p-values, function annotations, etc. The choice of multiple + tuning parameters is done using an Empirical Bayes approach. A majorization-minimization + algorithm is employed for implementation. + date_publication: '2023-06-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xtune + url_git: https://github.com/JingxuanH/xtune +xutils: + version: 0.0.2 + title: Utility Functions of Fangzhou Xie + maintainer: Fangzhou Xie + description: |- + This is a collection of some useful functions when dealing with text data. + Currently it only contains a very efficient function of decoding HTML entities + in character vectors by 'Rcpp' routine. + date_publication: '2021-09-06' + bug_reports: https://github.com/fangzhou-xie/xutils/issues + url: https://fangzhou-xie.github.io/xutils/index.html + url_cran: https://CRAN.R-project.org/package=xutils + url_git: https://github.com/fangzhou-xie/xutils +xwf: + version: 0.2-3 + title: Extrema-Weighted Feature Extraction + maintainer: Willem van den Boom + description: Extrema-weighted feature extraction for varying length functional data. + Functional data analysis method that performs dimensionality reduction based on + predefined features and allows for quantile weighting. Method implemented as presented + in van den Boom et al. (2018) . + date_publication: '2020-02-20' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xwf + url_git: '' +xxdi: + version: 1.2.3 + title: Calculate Expertise Indices + maintainer: Nilabhra Rohan Das + description: 'Institutional performance assessment remains a key challenge to a + multitude of stakeholders. Existing indicators such as h-type indicators, g-type + indicators, and many others do not reflect expertise of institutions that defines + their research portfolio. The package offers functionality to compute and visualise + two novel indices: the x-index and the xd-index. The x-index evaluates an institution''s + scholarly expertise within a specific discipline or field, while the xd-index + provides a broader assessment of overall scholarly expertise considering an institution''s + publication pattern and strengths across coarse thematic areas. These indices + offer a nuanced understanding of institutional research capabilities, aiding stakeholders + in research management and resource allocation decisions. Lathabai, H.H., Nandy, + A., and Singh, V.K. (2021) . Nandy, A., Lathabai, + H.H., and Singh, V.K. (2023) .' + date_publication: '2024-08-17' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=xxdi + url_git: '' +xxhashlite: + version: 0.2.2 + title: |- + Extremely Fast Hashing of R Objects, Raw Data and Files using + 'xxHash' Algorithms + maintainer: Mike Cheng + description: |- + Extremely fast hashing of R objects using 'xxHash'. R objects are hashed via + the standard serialization mechanism in R. Raw byte vectors and strings + can be handled directly for compatibility with hashes created on + other systems. This implementation is a wrapper around the 'xxHash' 'C' + library which is available from . + date_publication: '2024-03-12' + bug_reports: https://github.com/coolbutuseless/xxhashlite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xxhashlite + url_git: https://github.com/coolbutuseless/xxhashlite +xxIRT: + version: 2.1.2 + title: Item Response Theory and Computer-Based Testing in R + maintainer: Xiao Luo + description: |- + A suite of psychometric analysis tools for research and operation, including: + (1) computation of probability, information, and likelihood for the 3PL, GPCM, and GRM; + (2) parameter estimation using joint or marginal likelihood estimation method; + (3) simulation of computerized adaptive testing using built-in or customized algorithms; + (4) assembly and simulation of multistage testing. + The full documentation and tutorials are at . + date_publication: '2019-03-22' + bug_reports: https://github.com/xluo11/xxIRT/issues + url: '' + url_cran: https://CRAN.R-project.org/package=xxIRT + url_git: https://github.com/xluo11/xxIRT +yacca: + version: 1.4-2 + title: Yet Another Canonical Correlation Analysis Package + maintainer: Carter T. Butts + description: An alternative canonical correlation/redundancy analysis function, + with associated print, plot, and summary methods. A method for generating helio + plots is also included. + date_publication: '2022-03-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yacca + url_git: '' +yaConsensus: + version: '1.0' + title: Consensus Clustering of Omic Data + maintainer: Stefano Maria Pagnotta + description: Procedures to perform consensus clustering starting from a dissimilarity + matrix or a data matrix. It's allowed to select if the subsampling has to be by + samples or features. In case of computational heavy load, the procedures can run + in parallel. + date_publication: '2021-07-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yaConsensus + url_git: https://github.com/stefanoMP/yaConsensus +yager: + version: 0.1.1 + title: Yet Another General Regression Neural Network + maintainer: WenSui Liu + description: |- + Another implementation of general regression neural network in R + based on Specht (1991) . It is applicable to the + functional approximation or the classification. + date_publication: '2020-10-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yager + url_git: https://github.com/statcompute/yager +yahoofinancer: + version: 0.4.0 + title: Fetch Data from Yahoo Finance API + maintainer: Aravind Hebbali + description: |- + Obtain historical and near real time data related to stocks, index + and currencies from the Yahoo Finance API. This package is community maintained + and is not officially supported by 'Yahoo'. The accuracy of data is only as + correct as provided on . + date_publication: '2024-11-14' + bug_reports: https://github.com/rsquaredacademy/yahoofinancer/issues + url: https://yahoofinancer.rsquaredacademy.com/ + url_cran: https://CRAN.R-project.org/package=yahoofinancer + url_git: https://github.com/rsquaredacademy/yahoofinancer +yaImpute: + version: 1.0-34.1 + title: Nearest Neighbor Observation Imputation and Evaluation Tools + maintainer: Jeffrey S. Evans + description: |- + Performs nearest neighbor-based imputation using one or more alternative + approaches to processing multivariate data. These include methods based on canonical + correlation: analysis, canonical correspondence analysis, and a multivariate adaptation + of the random forest classification and regression techniques of Leo Breiman and Adele + Cutler. Additional methods are also offered. The package includes functions for + comparing the results from running alternative techniques, detecting imputation targets + that are notably distant from reference observations, detecting and correcting + for bias, bootstrapping and building ensemble imputations, and mapping results. + date_publication: '2024-09-21' + bug_reports: https://github.com/jeffreyevans/yaImpute/issues + url: '' + url_cran: https://CRAN.R-project.org/package=yaImpute + url_git: https://github.com/jeffreyevans/yaImpute +YaleToolkit: + version: 4.2.3 + title: Data Exploration Tools from Yale University + maintainer: John W. Emerson + description: |- + This collection of data exploration tools was developed at + Yale University for the graphical exploration of complex + multivariate data; barcode and gpairs now have their own + packages. The big.read.table() function provided here may be + useful for large files when only a subset is needed (but please + see the note in the help page for this function). + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YaleToolkit + url_git: '' +yaml: + version: 2.3.10 + title: Methods to Convert R Data to YAML and Back + maintainer: Shawn Garbett + description: |- + Implements the 'libyaml' 'YAML' 1.1 parser and emitter + () for R. + date_publication: '2024-07-26' + bug_reports: https://github.com/vubiostat/r-yaml/issues + url: '' + url_cran: https://CRAN.R-project.org/package=yaml + url_git: https://github.com/vubiostat/r-yaml/ +yamlet: + version: 1.2.0 + title: Versatile Curation of Table Metadata + maintainer: Tim Bergsma + description: |- + A YAML-based + mechanism for working with table metadata. Supports + compact syntax for creating, modifying, viewing, exporting, + importing, displaying, and plotting metadata coded as column + attributes. The 'yamlet' dialect is valid 'YAML' with + defaults and conventions chosen to improve readability. + See ?yamlet, ?decorate, ?modify, ?io_csv, and ?ggplot.decorated. + date_publication: '2024-11-26' + bug_reports: https://github.com/bergsmat/yamlet/issues + url: '' + url_cran: https://CRAN.R-project.org/package=yamlet + url_git: '' +yamlme: + version: 0.1.2 + title: Writing 'YAML' Headers for 'R-Markdown' Documents + maintainer: Miguel Alvarez + description: |- + Setting layout through 'YAML' headers in 'R-Markdown' documents, + enabling their automatic generation. + Functions and methods may summarize 'R' objects in automatic reports, for + instance check-lists and further reports applied to the packages 'taxlist' + and 'vegtable'. + date_publication: '2022-11-09' + bug_reports: https://github.com/kamapu/yamlme/issues + url: https://kamapu.github.io/rpkg/yamlme/ + url_cran: https://CRAN.R-project.org/package=yamlme + url_git: https://github.com/kamapu/yamlme +yardstick: + version: 1.3.2 + title: Tidy Characterizations of Model Performance + maintainer: Emil Hvitfeldt + description: |- + Tidy tools for quantifying how well model fits to a data set + such as confusion matrices, class probability curve summaries, and + regression metrics (e.g., RMSE). + date_publication: '2025-01-22' + bug_reports: https://github.com/tidymodels/yardstick/issues + url: https://yardstick.tidymodels.org + url_cran: https://CRAN.R-project.org/package=yardstick + url_git: https://github.com/tidymodels/yardstick +yarrr: + version: 0.1.5 + title: 'A Companion to the e-Book "YaRrr!: The Pirate''s Guide to R"' + maintainer: Nathaniel Phillips + description: 'Contains a mixture of functions and data sets referred to in the introductory + e-book "YaRrr!: The Pirate''s Guide to R". The latest version of the e-book is + available for free at .' + date_publication: '2017-04-19' + bug_reports: https://github.com/ndphillips/yarrr/issues + url: www.thepiratesguidetor.com + url_cran: https://CRAN.R-project.org/package=yarrr + url_git: '' +yasp: + version: 0.2.0 + title: String Functions for Compact R Code + maintainer: Tomasz Kalinowski + description: |- + A collection of string functions designed for writing + compact and expressive R code. 'yasp' (Yet Another String Package) is simple, + fast, dependency-free, and written in pure R. The package provides: a + coherent set of abbreviations for paste() from package 'base' with a + variety of defaults, such as p() for "paste" and pcc() for "paste and + collapse with commas"; wrap(), bracket(), and others for wrapping a + string in flanking characters; unwrap() for removing pairs of characters + (at any position in a string); and sentence() for cleaning whitespace + around punctuation and capitalization appropriate for prose sentences. + date_publication: '2018-05-29' + bug_reports: https://github.com/t-kalinowski/yasp/issues + url: '' + url_cran: https://CRAN.R-project.org/package=yasp + url_git: https://github.com/t-kalinowski/yasp +yatah: + version: 1.0.0 + title: Yet Another TAxonomy Handler + maintainer: Antoine Bichat + description: |- + Provides functions to manage taxonomy when lineages are + described with strings and ranks separated with special patterns like + "|*__" or ";*__". + date_publication: '2024-04-13' + bug_reports: https://github.com/abichat/yatah/issues + url: https://abichat.github.io/yatah/ + url_cran: https://CRAN.R-project.org/package=yatah + url_git: https://github.com/abichat/yatah/ +YatchewTest: + version: 1.1.1 + title: |- + Yatchew (1997), De Chaisemartin & D'Haultfoeuille (2024) + Linearity Test + maintainer: Diego Ciccia + description: Test of linearity originally proposed by Yatchew (1997) + and improved by de Chaisemartin & D'Haultfoeuille (2024) + to be robust under heteroskedasticity. + date_publication: '2024-07-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YatchewTest + url_git: '' +YatesAlgo.FactorialExp.SR: + version: 4.0.4 + title: Yates' Algorithm in 2^n Factorial Experiment + maintainer: Somjit Roy + description: Determines the sum of squares of the (2^n)-1 factorial effects in a + 2^n factorial experiment using Yates' algorithm. + date_publication: '2021-04-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YatesAlgo.FactorialExp.SR + url_git: '' +ycevo: + version: 0.2.1 + title: Nonparametric Estimation of the Yield Curve Evolution + maintainer: Yangzhuoran Fin Yang + description: |- + Nonparametric estimation of discount functions and yield curves from + transaction data of coupon paying bonds. + Koo, B., La Vecchia, D., & Linton, O. B. (2021) + describe an application of this package using the Center for Research in + Security Prices (CRSP) Bond Data and document its implementation. + date_publication: '2024-06-05' + bug_reports: https://github.com/bonsook/ycevo/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ycevo + url_git: https://github.com/bonsook/ycevo +YEAB: + version: 1.0.6 + title: Analyze Data from Analysis of Behavior Experiments + maintainer: Emmanuel Alcala + description: |- + Analyze data from behavioral experiments conducted using 'MED-PC' software developed by Med Associates Inc. + Includes functions to fit exponential and hyperbolic models for delay discounting tasks, exponential mixtures for + inter-response times, and Gaussian plus ramp models for peak procedure data, among others. For more details, refer to Alcala et al. (2023) . + date_publication: '2025-01-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YEAB + url_git: '' +yesno: + version: 0.1.3 + title: Ask Yes-No Questions + maintainer: Ayla Pearson + description: Asks Yes-No questions with variable or custom responses. + date_publication: '2024-07-26' + bug_reports: https://github.com/poissonconsulting/yesno/issues + url: https://poissonconsulting.github.io/yesno/ + url_cran: https://CRAN.R-project.org/package=yesno + url_git: https://github.com/poissonconsulting/yesno +yfR: + version: 1.1.0 + title: Downloads and Organizes Financial Data from Yahoo Finance + maintainer: Marcelo Perlin + description: |- + Facilitates download of financial data from Yahoo Finance , + a vast repository of stock price data across multiple financial exchanges. The package offers a local caching system + and support for parallel computation. + date_publication: '2023-02-16' + bug_reports: https://github.com/ropensci/yfR/issues + url: https://docs.ropensci.org/yfR/ + url_cran: https://CRAN.R-project.org/package=yfR + url_git: https://github.com/ropensci/yfR +yhat: + version: 2.0-4 + title: Interpreting Regression Effects + maintainer: Kim Nimon + description: |- + The purpose of this package is to provide methods to interpret multiple + linear regression and canonical correlation results including beta weights,structure coefficients, + validity coefficients, product measures, relative weights, all-possible-subsets regression, + dominance analysis, commonality analysis, and adjusted effect sizes. + date_publication: '2023-10-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yhat + url_git: '' +yhatr: + version: 0.15.1 + title: R Binder for the Yhat API + maintainer: Greg Lamp + description: |- + Deploy, maintain, and invoke models via the Yhat + REST API. + date_publication: '2017-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yhatr + url_git: https://github.com/yhat/yhatr +YieldCurve: + version: '5.1' + title: Modelling and Estimation of the Yield Curve + maintainer: Sergio Salvino Guirreri + description: |- + Modelling the yield curve with some parametric models. + The models implemented are: + Nelson, C.R., and A.F. Siegel (1987) , + Diebold, F.X. and Li, C. (2006) + and Svensson, L.E. (1994) . + The package also includes the data of the term structure of interest rate of Federal Reserve Bank and European Central Bank. + date_publication: '2022-10-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YieldCurve + url_git: '' +yll: + version: 1.0.0 + title: Compute Expected Years of Life Lost (YLL) and Average YLL + maintainer: Antoine Soetewey + description: |- + Compute the standard expected years of life lost (YLL), + as developed by the Global Burden of Disease Study + (Murray, C.J., Lopez, A.D. and World Health Organization, 1996). + The YLL is based on comparing the age of death to an external standard life + expectancy curve. It also computes the average YLL, which highlights premature + causes of death and brings attention to preventable deaths + (Aragon et al., 2008). + date_publication: '2018-11-02' + bug_reports: https://github.com/AntoineSoetewey/yll/issues + url: '' + url_cran: https://CRAN.R-project.org/package=yll + url_git: https://github.com/AntoineSoetewey/yll +ymd: + version: 0.1.4 + title: Parse 'YMD' Format Number or String to Date + maintainer: Xianying Tan + description: |- + Convert 'YMD' format number or string to Date efficiently, using Rust's + standard library. It also provides helper functions to handle Date, e.g., quick + finding the beginning or end of the given period, adding months to Date, etc. + date_publication: '2024-11-26' + bug_reports: https://github.com/shrektan/ymd/issues + url: https://shrektan.github.io/ymd/ + url_cran: https://CRAN.R-project.org/package=ymd + url_git: https://github.com/shrektan/ymd +Ymisc: + version: 0.1.0 + title: Miscellaneous Functions + maintainer: Yoo Ri Hwang + description: |- + The Author's personal R Package that contains miscellaneous functions. + The current version of package contains miscellaneous functions for brain data + to compute Asymmetry Index (AI) and bilateral (L+R) measures and reshape the data. + date_publication: '2023-10-18' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Ymisc + url_git: '' +ymlthis: + version: 0.1.7 + title: Write 'YAML' for 'R Markdown', 'bookdown', 'blogdown', and More + maintainer: Malcolm Barrett + description: |- + Write 'YAML' front matter for R Markdown and related + documents. Work with 'YAML' objects more naturally and write the + resulting 'YAML' to your clipboard or to 'YAML' files related to your + project. + date_publication: '2022-08-05' + bug_reports: https://github.com/r-lib/ymlthis/issues + url: https://ymlthis.r-lib.org + url_cran: https://CRAN.R-project.org/package=ymlthis + url_git: https://github.com/r-lib/ymlthis +ympes: + version: 1.8.0 + title: Collection of Helper Functions + maintainer: Tim Taylor + description: |- + Provides a collection of lightweight helper functions (imps) both + for interactive use and for inclusion within other packages. These include + functions for minimal input assertions, visualising colour palettes, + quoting user input, searching rows of a data frame and capturing string + tokens. + date_publication: '2025-02-05' + bug_reports: https://github.com/TimTaylor/ympes/issues + url: https://timtaylor.github.io/ympes/ + url_cran: https://CRAN.R-project.org/package=ympes + url_git: '' +yodel: + version: 1.0.0 + title: A General Bayesian Model Averaging Helper + maintainer: Richard Payne + description: |- + Provides helper functions to perform Bayesian model averaging + using Markov chain Monte Carlo samples from separate models. Calculates + weights and obtains draws from the model-averaged posterior for quantities + of interest specified by the user. Weight calculations can be done using + marginal likelihoods or log-predictive likelihoods as in Ando, T., & Tsay, + R. (2010) . + date_publication: '2024-04-16' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yodel + url_git: https://github.com/rich-payne/yodel +yorkr: + version: 0.0.42 + title: Analyze Cricket Performances Based on Data from Cricsheet + maintainer: Tinniam V Ganesh + description: |- + Analyzing performances of cricketers and cricket teams + based on 'yaml' match data from Cricsheet . + date_publication: '2024-03-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=yorkr + url_git: https://github.com/tvganesh/yorkr/ +youngSwimmers: + version: 0.0.1 + title: Young Swimmers Dataset + maintainer: Matías Castillo Aguilar + description: Dataset from the young elite swimmers study. + date_publication: '2022-02-14' + bug_reports: https://github.com/NIM-ACh/youngSwimmers/issues/ + url: https://nim-ach.github.io/youngSwimmers/ + url_cran: https://CRAN.R-project.org/package=youngSwimmers + url_git: https://github.com/NIM-ACh/youngSwimmers/ +YPBP: + version: 0.0.1 + title: |- + Yang and Prentice Model with Baseline Distribution Modeled by + Bernstein Polynomials + maintainer: Fabio Demarqui + description: Semiparametric modeling of lifetime data with crossing survival curves + via Yang and Prentice model with baseline hazard/odds modeled with Bernstein polynomials. + Details about the model can be found in Demarqui et al. (2019) . + Model fitting can be carried out via both maximum likelihood and Bayesian approaches. + The package also provides point and interval estimation for the crossing survival + times. + date_publication: '2020-06-29' + bug_reports: https://github.com/fndemarqui/YPBP/issues + url: '' + url_cran: https://CRAN.R-project.org/package=YPBP + url_git: https://github.com/fndemarqui/YPBP +YPInterimTesting: + version: 1.0.3 + title: |- + Interim Monitoring Using Adaptively Weighted Log-Rank Test in + Clinical Trials + maintainer: Daewoo Pak + description: |- + For any spending function specified by the user, this + package provides corresponding boundaries for interim testing using + the adaptively weighted log-rank test developed by Yang and Prentice + (2010 ). + The package uses a re-sampling method to obtain stopping boundaries + at the interim looks.The output consists of stopping boundaries + and observed values of the test statistics at the interim looks, + along with nominal p-values defined as the probability of the test + exceeding the specific observed test statistic value or critical + value, regardless of the test behavior at other looks. + The asymptotic validity of the stopping boundaries is established + in Yang (2018 ). + date_publication: '2019-06-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YPInterimTesting + url_git: '' +YPmodel: + version: '1.4' + title: |- + The Short-Term and Long-Term Hazard Ratio Model for Survival + Data + maintainer: Junlong Sun + description: 'Inference procedures accommodate a flexible range of hazard ratio + patterns with a two-sample semi-parametric model. This model contains the proportional + hazards model and the proportional odds model as sub-models, and accommodates + non-proportional hazards situations to the extreme of having crossing hazards + and crossing survivor functions. Overall, this package has four major functions: + 1) the parameter estimation, namely short-term and long-term hazard ratio parameters; + 2) 95 percent and 90 percent point-wise confidence intervals and simultaneous + confidence bands for the hazard ratio function; 3) p-value of the adaptive weighted + log-rank test; 4) p-values of two lack-of-fit tests for the model. See the included + "read_me_first.pdf" for brief instructions. In this version (1.1), there is no + need to sort the data before applying this package.' + date_publication: '2020-10-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YPmodel + url_git: '' +YPmodelPhreg: + version: 1.0.0 + title: |- + The Short-Term and Long-Term Hazard Ratio Model with + Proportional Adjustment + maintainer: Daewoo Pak + description: |- + Provides covariate-adjusted comparison of two groups of right + censored data, where the binary group variable has separate short-term + and long-term effects on the hazard function, while effects of covariates + such as age, blood pressure, etc. are proportional on the hazard. The model + was studied in Yang and Prentice (2015) and it extends + the two sample version of the short-term and long-term hazard ratio model + proposed in Yang and Prentice (2005) . The model + extends the usual Cox proportional hazards model to allow more flexible + hazard ratio patterns, such as gradual onset of effect, diminishing effect, + and crossing hazard or survival functions. This package provides + the following: 1) point estimates and confidence intervals for model + parameters; 2) point estimate and confidence interval of the average hazard + ratio; and 3) plots of estimated hazard ratio function with point-wise and + simultaneous confidence bands. + date_publication: '2023-07-05' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YPmodelPhreg + url_git: '' +YPPE: + version: 1.0.1 + title: |- + Yang and Prentice Model with Piecewise Exponential Baseline + Distribution + maintainer: Fabio Demarqui + description: Semiparametric modeling of lifetime data with crossing survival curves + via Yang and Prentice model with piecewise exponential baseline distribution. + Details about the model can be found in Demarqui and Mayrink (2019) . + Model fitting carried out via likelihood-based and Bayesian approaches. The package + also provides point and interval estimation for the crossing survival times. + date_publication: '2020-01-09' + bug_reports: https://github.com/fndemarqui/YPPE/issues + url: '' + url_cran: https://CRAN.R-project.org/package=YPPE + url_git: https://github.com/fndemarqui/YPPE +ypr: + version: 0.6.0 + title: Yield Per Recruit + maintainer: Joe Thorley + description: |- + An implementation of equilibrium-based yield per recruit + methods. Yield per recruit methods can used to estimate the optimal + yield for a fish population as described by Walters and Martell (2004) + . The yield can be based on the number of fish + caught (or harvested) or biomass caught for all fish or just large + (trophy) individuals. + date_publication: '2022-08-29' + bug_reports: https://github.com/poissonconsulting/ypr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ypr + url_git: https://github.com/poissonconsulting/ypr +ypssc: + version: 1.1.0 + title: Yeast-Proteome Secondary-Structure Calculator + maintainer: Shashank Kumbhare + description: |- + An extension for 'NetSurfP-2.0' (Klausen et al. (2019) ) + which is specifically designed to analyze the results of bottom-up-proteomics that is + primarily analyzed with 'MaxQuant' (Cox, J., Mann, M. (2008) ). + This tool is designed to process a large number of yeast peptides that produced as a + results of whole yeast cell-proteome digestion and provide a coherent picture of + secondary structure of proteins. + date_publication: '2021-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ypssc + url_git: '' +YRmisc: + version: 0.1.6 + title: Y&R Miscellaneous R Functions + maintainer: Xuanhua (Peter) Yin + description: Miscellaneous functions for data analysis, portfolio management, graphics, + data manipulation, statistical investigation, including descriptive statistics, + creating leading and lagging variables, portfolio return analysis, time series + difference and percentage change calculation, stacking data for higher efficient + analysis. + date_publication: '2020-03-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=YRmisc + url_git: '' +YTAnalytics: + version: 0.2.0 + title: Wrapper for 'YouTube Analytics' API + maintainer: Jake Davis + description: |- + Simplify working with the 'YouTube Analytics' API . Collect + data for your channel including geography, traffic sources, time period, etc. + date_publication: '2024-08-29' + bug_reports: https://github.com/davisj95/YTAnalytics/issues + url: https://davisj95.github.io/YTAnalytics/ + url_cran: https://CRAN.R-project.org/package=YTAnalytics + url_git: https://github.com/davisj95/YTAnalytics +yuima: + version: 1.15.27 + title: The YUIMA Project Package for SDEs + maintainer: Stefano M. Iacus + description: Simulation and Inference for SDEs and Other Stochastic Processes. + date_publication: '2024-02-29' + bug_reports: https://github.com/yuimaproject/yuima/issues + url: https://yuimaproject.com + url_cran: https://CRAN.R-project.org/package=yuima + url_git: '' +yuimaGUI: + version: 1.3.1 + title: A Graphical User Interface for the 'yuima' Package + maintainer: Emanuele Guidotti + description: Provides a graphical user interface for the 'yuima' package. + date_publication: '2022-08-11' + bug_reports: '' + url: https://yuimaproject.com + url_cran: https://CRAN.R-project.org/package=yuimaGUI + url_git: '' +yulab.utils: + version: 0.2.0 + title: Supporting Functions for Packages Maintained by 'YuLab-SMU' + maintainer: Guangchuang Yu + description: Miscellaneous functions commonly used by 'YuLab-SMU'. + date_publication: '2025-01-29' + bug_reports: https://github.com/YuLab-SMU/yulab.utils/issues + url: https://yulab-smu.top/ + url_cran: https://CRAN.R-project.org/package=yulab.utils + url_git: '' +yum: + version: 0.1.0 + title: Utilities to Extract and Process 'YAML' Fragments + maintainer: Gjalt-Jorn Peters + description: |- + Provides a number of functions to facilitate + extracting information in 'YAML' fragments from one or + multiple files, optionally structuring the information + in a 'data.tree'. 'YAML' (recursive acronym for "YAML ain't + Markup Language") is a convention for specifying structured + data in a format that is both machine- and human-readable. + 'YAML' therefore lends itself well for embedding (meta)data + in plain text files, such as Markdown files. This principle + is implemented in 'yum' with minimal dependencies (i.e. only + the 'yaml' packages, and the 'data.tree' package can be + used to enable additional functionality). + date_publication: '2021-07-16' + bug_reports: https://gitlab.com/r-packages/yum/-/issues + url: https://r-packages.gitlab.io/yum + url_cran: https://CRAN.R-project.org/package=yum + url_git: '' +yyjsonr: + version: 0.1.20 + title: Fast 'JSON', 'NDJSON' and 'GeoJSON' Parser and Generator + maintainer: Mike Cheng + description: |- + A fast 'JSON' parser, generator and validator which converts 'JSON', + 'NDJSON' (Newline Delimited 'JSON') and 'GeoJSON' (Geographic 'JSON') data + to/from R objects. The standard R data types are + supported (e.g. logical, numeric, integer) with configurable handling of NULL + and NA values. Data frames, atomic vectors and lists are all supported as data + containers translated to/from 'JSON'. 'GeoJSON' data is read in as + 'simple features' objects. + This implementation wraps the 'yyjson' 'C' library which + is available from . + date_publication: '2024-04-10' + bug_reports: https://github.com/coolbutuseless/yyjsonr/issues + url: https://coolbutuseless.github.io/package/yyjsonr/ + url_cran: https://CRAN.R-project.org/package=yyjsonr + url_git: https://github.com/coolbutuseless/yyjsonr +Z10: + version: 0.1.0 + title: Simple Ecological Statistics from the NEON Network + maintainer: Robert Lee + description: |- + Provides simple statistics from instruments and observations at sites in the NEON network, and acts as a simple interface for v0 of the National Ecological Observatory Network (NEON) API. + Statistics are generated for meteorologic and soil-based observations, and are presented for daily, annual, and one-time observations at all available NEON sites. + Users can also retrieve any dataset publicly hosted by NEON. Metadata for NEON sites and data products can be returned, as well as information on data product availability by site and date. + For more information on NEON, please visit . For detailed data product information, please see the NEON data product catalog at . + date_publication: '2018-11-26' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Z10 + url_git: '' +zalpha: + version: 0.3.0 + title: Run a Suite of Selection Statistics + maintainer: Clare Horscroft + description: A suite of statistics for identifying areas of the genome under selective + pressure. See Jacobs, Sluckin and Kivisild (2016) . + date_publication: '2021-11-27' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zalpha + url_git: '' +zCompositions: + version: 1.5.0-4 + title: |- + Treatment of Zeros, Left-Censored and Missing Values in + Compositional Data Sets + maintainer: Javier Palarea-Albaladejo + description: |- + Principled methods for the imputation of zeros, left-censored and missing data in + compositional data sets (Palarea-Albaladejo and Martin-Fernandez (2015) ). + date_publication: '2024-06-19' + bug_reports: https://github.com/Japal/zCompositions/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zCompositions + url_git: https://github.com/Japal/zCompositions +zctaCrosswalk: + version: 2.0.0 + title: |- + Crosswalk Between 2020 Census ZIP Code Tabulation Areas (ZCTAs), + States and Counties + maintainer: Ari Lamstein + description: |- + Contains the US Census Bureau's 2020 ZCTA to County Relationship + File, as well as convenience functions to translate between States, Counties + and ZIP Code Tabulation Areas (ZCTAs). + date_publication: '2023-04-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zctaCrosswalk + url_git: https://github.com/MarketBridge/zctaCrosswalk +zcurve: + version: 2.4.2 + title: An Implementation of Z-Curves + maintainer: František Bartoš + description: |- + An implementation of z-curves - a method for estimating expected discovery + and replicability rates on the bases of test-statistics of published studies. The package + provides functions for fitting the new density and EM version + (Bartoš & Schimmack, 2020, ), censored observations, + as well as the original density z-curve (Brunner & Schimmack, 2020, ). + Furthermore, the package provides summarizing and plotting functions for the fitted z-curve objects. + See the aforementioned articles for more information about the z-curves, expected discovery + and replicability rates, validation studies, and limitations. + date_publication: '2024-05-28' + bug_reports: https://github.com/FBartos/zcurve/issues + url: https://fbartos.github.io/zcurve/ + url_cran: https://CRAN.R-project.org/package=zcurve + url_git: '' +zdeskR: + version: 0.4.2 + title: Connect to Your 'Zendesk' Data + maintainer: Chris Umphlett + description: |- + Facilitates making a connection to the + 'Zendesk' API and executing various queries. You can use it to + get ticket, ticket metrics, and user data. The 'Zendesk' documentation is + available at . This package is not supported by + 'Zendesk' (owner of the software). + date_publication: '2025-01-23' + bug_reports: https://github.com/chrisumphlett/zdeskR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zdeskR + url_git: https://github.com/chrisumphlett/zdeskR +zeallot: + version: 0.1.0 + title: Multiple, Unpacking, and Destructuring Assignment + maintainer: Nathan Teetor + description: |- + Provides a %<-% operator to perform multiple, + unpacking, and destructuring assignment in R. The + operator unpacks the right-hand side of an assignment + into multiple values and assigns these values to + variables on the left-hand side of the assignment. + date_publication: '2018-01-28' + bug_reports: https://github.com/nteetor/zeallot/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zeallot + url_git: https://github.com/nteetor/zeallot +ZeBook: + version: '1.1' + title: Working with Dynamic Models for Agriculture and Environment + maintainer: Francois Brun + description: R package accompanying the book Working with dynamic models for agriculture + and environment, by Daniel Wallach (INRA), David Makowski (INRA), James W. Jones + (U.of Florida), Francois Brun (ACTA). 3rd edition 2018-09-27. + date_publication: '2018-11-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZeBook + url_git: '' +zebu: + version: 0.2.2.0 + title: Local Association Measures + maintainer: Olivier M. F. Martin + description: 'Implements the estimation of local (and global) association measures: + Lewontin''s D, Ducher''s Z, pointwise mutual information, normalized pointwise + mutual information and chi-squared residuals. The significance of local (and global) + association is accessed using p-values estimated by permutations.' + date_publication: '2023-08-25' + bug_reports: https://github.com/oliviermfmartin/zebu/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zebu + url_git: https://github.com/oliviermfmartin/zebu +zeitgebr: + version: 0.3.5 + title: Analysis of Circadian Behaviours + maintainer: Quentin Geissmann + description: |- + Use behavioural variables to compute period, rhythmicity and other circadian parameters. + Methods include computation of chi square periodograms (Sokolove and Bushell (1978) ), + Lomb-Scargle periodograms (Lomb (1976) , Scargle (1982) , Ruf (1999) ), + and autocorrelation-based periodograms. + date_publication: '2020-04-25' + bug_reports: https://github.com/rethomics/zeitgebr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zeitgebr + url_git: https://github.com/rethomics/zeitgebr +zen4R: + version: '0.10' + title: Interface to 'Zenodo' REST API + maintainer: Emmanuel Blondel + description: |- + Provides an Interface to 'Zenodo' () REST API, + including management of depositions, attribution of DOIs by 'Zenodo' and + upload and download of files. + date_publication: '2024-06-05' + bug_reports: https://github.com/eblondel/zen4R/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zen4R + url_git: https://github.com/eblondel/zen4R +zendeskR: + version: '0.4' + title: Zendesk API Wrapper + maintainer: Tanya Cashorali + description: This package provides an R wrapper for the Zendesk API + date_publication: '2014-02-21' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zendeskR + url_git: '' +zendown: + version: 0.1.0 + title: Access Files from 'Zenodo' Deposits + maintainer: Raphael Saldanha + description: Access, download and locally cache files deposited on 'Zenodo' . + date_publication: '2024-05-21' + bug_reports: https://github.com/rfsaldanha/zendown/issues + url: https://rfsaldanha.github.io/zendown/ + url_cran: https://CRAN.R-project.org/package=zendown + url_git: https://github.com/rfsaldanha/zendown +zenplots: + version: 1.0.6 + title: Zigzag Expanded Navigation Plots + maintainer: Wayne Oldford + description: |- + Graphical tools for visualizing high-dimensional data along a path + of alternating one- and two-dimensional plots. Note that this + includes interactive graphics plots based on 'loon' in turn based on 'tcltk' + (included as part of the standard R distribution). It also requires 'graph' from Bioconductor. + For more detail on use and algorithms, see . + date_publication: '2023-11-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zenplots + url_git: https://github.com/great-northern-diver/zenplots +zenstats: + version: 0.1.2 + title: Statistics from 'Zenodo' Deposits + maintainer: Raphael Saldanha + description: Fetch statistics about views, downloads and data volume from 'Zenodo' + deposits. The package collects a 'Zenodo' () deposit file + information, respecting the website scrapping policies. + date_publication: '2024-05-31' + bug_reports: '' + url: https://rfsaldanha.github.io/zenstats/ + url_cran: https://CRAN.R-project.org/package=zenstats + url_git: '' +zephyr: + version: 0.1.1 + title: Structured Messages and Options + maintainer: Aksel Thomsen + description: |- + Provides a structured framework for consistent user + communication and configuration management for package developers. + date_publication: '2025-01-28' + bug_reports: https://github.com/novonordisk-opensource/zephyr/issues + url: https://novonordisk-opensource.github.io/zephyr/ + url_cran: https://CRAN.R-project.org/package=zephyr + url_git: https://github.com/novonordisk-opensource/zephyr +zeroEQpart: + version: 0.1.0 + title: Zero Order vs (Semi) Partial Correlation Test and CI + maintainer: Dan Richard + description: |- + Uses bootstrap to test zero order correlation being equal to a + partial or semi-partial correlation (one or two tailed). Confidence + intervals for the parameter (zero order minus partial) can also be + determined. Implements the bias-corrected and accelerated bootstrap + method as described in "An Introduction to the Bootstrap" Efron (1983) + <0-412-04231-2>. + date_publication: '2018-09-21' + bug_reports: https://github.com/djrichar92/zeroEQpart/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zeroEQpart + url_git: https://github.com/djrichar92/zeroEQpart +zetadiv: + version: 1.2.1 + title: Functions to Compute Compositional Turnover Using Zeta Diversity + maintainer: Guillaume Latombe + description: |- + Functions to compute compositional turnover using zeta-diversity, + the number of species shared by multiple assemblages. The package includes + functions to compute zeta-diversity for a specific number of + assemblages and to compute zeta-diversity for a range of numbers of + assemblages. It also includes functions to explain how zeta-diversity + varies with distance and with differences in environmental variables + between assemblages, using generalised linear models, linear models + with negative constraints, generalised additive models,shape + constrained additive models, and I-splines. + date_publication: '2022-06-10' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zetadiv + url_git: '' +ZetaSuite: + version: 1.0.1 + title: |- + Analyze High-Dimensional High-Throughput Dataset and Quality + Control Single-Cell RNA-Seq + maintainer: Junhui Li + description: 'The advent of genomic technologies has enabled the generation of two-dimensional + or even multi-dimensional high-throughput data, e.g., monitoring multiple changes + in gene expression in genome-wide siRNA screens across many different cell types + (E Robert McDonald 3rd (2017) and Tsherniak + A (2017) ) or single cell transcriptomics under + different experimental conditions. We found that simple computational methods + based on a single statistical criterion is no longer adequate for analyzing such + multi-dimensional data. We herein introduce ''ZetaSuite'', a statistical package + initially designed to score hits from two-dimensional RNAi screens.We also illustrate + a unique utility of ''ZetaSuite'' in analyzing single cell transcriptomics to + differentiate rare cells from damaged ones (Vento-Tormo R (2018) ). + In ''ZetaSuite'', we have the following steps: QC of input datasets, normalization + using Z-transformation, Zeta score calculation and hits selection based on defined + Screen Strength.' + date_publication: '2022-05-24' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZetaSuite + url_git: '' +zfa: + version: 1.1.0 + title: Zoom-Focus Algorithm + maintainer: Yexian Zhang + description: Performs Zoom-Focus Algorithm (ZFA) to optimize testing regions for + rare variant association tests in exome sequencing data. + date_publication: '2024-01-29' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zfa + url_git: '' +zfit: + version: 0.4.0 + title: Fit Models in a Pipe + maintainer: Magnus Thor Torfason + description: |- + Improve the usage of model fitting functions within a piped + work flow. + date_publication: '2023-08-27' + bug_reports: '' + url: https://torfason.github.io/zfit/ + url_cran: https://CRAN.R-project.org/package=zfit + url_git: https://github.com/torfason/zfit/ +ZIBR: + version: 1.0.2 + title: A Zero-Inflated Beta Random Effect Model + maintainer: Charlie Bushman + description: |- + A two-part zero-inflated Beta regression model with random + effects (ZIBR) for testing the association between microbial abundance + and clinical covariates for longitudinal microbiome data. Eric Z. Chen + and Hongzhe Li (2016) . + date_publication: '2023-10-17' + bug_reports: https://github.com/PennChopMicrobiomeProgram/ZIBR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ZIBR + url_git: https://github.com/PennChopMicrobiomeProgram/ZIBR +zic: + version: 0.9.1 + title: Bayesian Inference for Zero-Inflated Count Models + maintainer: Markus Jochmann + description: |- + Provides MCMC algorithms for the analysis of + zero-inflated count models. The case of stochastic search + variable selection (SVS) is also considered. All MCMC samplers + are coded in C++ for improved efficiency. A data set + considering the demand for health care is provided. + date_publication: '2017-08-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zic + url_git: '' +zigg: + version: 0.0.2 + title: |- + Lightweight Interfaces to the 'Ziggurat' Pseudo Random Number + Generator + maintainer: Dirk Eddelbuettel + description: |- + The 'Ziggurat' pseudo-random number generator (or PRNG), + introduced by Marsaglia and Tsang (2000, ) and + further improved by Leong et al (2005, ), offers + a lightweight and very fast PRNG for the normal, exponential, and uniform + distributions. It is provided here in a small zero-dependency package. It can + be used from R as well as from 'C/C++' code in other packages as is demonstrated + by four included sample packages using four distinct methods to use the PRNG + presented here in client package. The implementation is influenced by our + package 'RcppZiggurat' which offers a comparison among multiple alternative + implementations but presented here in a lighter-weight implementation that is + easier to use by other packages. The PRNGs provided are generally faster than + the ones in base R: on our machine, the relative gains for normal, exponential + and uniform are on the order of 7.4, 5.2 and 4.7 times faster than base R. + However, these generators are of potentially lesser quality and shorter period + so if in doubt use of the base R functions remains the general recommendation. + date_publication: '2025-02-07' + bug_reports: https://github.com/eddelbuettel/zigg/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zigg + url_git: https://github.com/eddelbuettel/zigg +ZillowR: + version: 1.0.0 + title: R Interface to Zillow Real Estate and Mortgage Data API + maintainer: Justin Brantley + description: |- + Zillow, an online real estate company, provides real estate + and mortgage data for the United States through a REST API. The + ZillowR package provides an R function for each API service, making it + easy to make API calls and process the response into convenient, + R-friendly data structures. See + for the Zillow API + Documentation. NOTE: Zillow deprecated their API on 2021-09-30, and + this package is now deprecated as a result. + date_publication: '2022-05-05' + bug_reports: https://gitlab.com/fascinatingfingers/zillowr/-/issues + url: https://fascinatingfingers.gitlab.io/zillowr + url_cran: https://CRAN.R-project.org/package=ZillowR + url_git: https://gitlab.com/fascinatingfingers/zillowr +ZIM: + version: 1.1.0 + title: |- + Zero-Inflated Models (ZIM) for Count Time Series with Excess + Zeros + maintainer: Ming Yang + description: |- + Analyze count time series with excess zeros. + Two types of statistical models are supported: Markov regression by Yang et al. + (2013) and state-space models by Yang et al. + (2015) . They are also known as observation-driven and + parameter-driven models respectively in the time series literature. The functions used for + Markov regression or observation-driven models can also be used to fit ordinary regression models + with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) + assumption. Besides, the package contains some miscellaneous functions to compute density, distribution, + quantile, and generate random numbers from ZIP and ZINB distributions. + date_publication: '2018-08-28' + bug_reports: https://github.com/biostatstudio/ZIM/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ZIM + url_git: https://github.com/biostatstudio/ZIM +ZIM4rv: + version: 0.1.1 + title: |- + Gene‐based Association Tests of Zero‐inflated Count Phenotype + for Rare Variants + maintainer: Xiaomin Liu + description: Gene‐based association tests to model count data with excessive zeros + and rare variants using zero-inflated Poisson/zero-inflated negative Binomial + regression framework. This method was originally described by Fan, Sun, and Li + in Genetic Epidemiology 46(1):73-86 . + date_publication: '2024-12-19' + bug_reports: https://github.com/fanx0037/ZIM4rv/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ZIM4rv + url_git: https://github.com/fanx0037/ZIM4rv +ZINAR1: + version: 0.1.0 + title: |- + Simulates ZINAR(1) Model and Estimates Its Parameters Under + Frequentist Approach + maintainer: João Vitor Ribeiro + description: Generates Realizations of First-Order Integer Valued Autoregressive + Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters + as described in Garay et al. (2021) . + date_publication: '2022-11-02' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZINAR1 + url_git: '' +ZINARp: + version: 0.1.0 + title: Simulate INAR/ZINAR(p) Models and Estimate Its Parameters + maintainer: Tharso Augustus Rossiter Araújo Monteiro + description: Simulation, exploratory data analysis and Bayesian analysis of the + p-order Integer-valued Autoregressive (INAR(p)) and Zero-inflated p-order Integer-valued + Autoregressive (ZINAR(p)) processes, as described in Garay et al. (2020) . + date_publication: '2022-05-09' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZINARp + url_git: '' +zip: + version: 2.3.2 + title: Cross-Platform 'zip' Compression + maintainer: Gábor Csárdi + description: |- + Cross-Platform 'zip' Compression Library. A replacement for + the 'zip' function, that does not require any additional external + tools on any platform. + date_publication: '2025-02-01' + bug_reports: https://github.com/r-lib/zip/issues + url: https://r-lib.github.io/zip/ + url_cran: https://CRAN.R-project.org/package=zip + url_git: https://github.com/r-lib/zip +zipangu: + version: 0.3.3 + title: Japanese Utility Functions and Data + maintainer: Shinya Uryu + description: |- + Some data treated by the Japanese R user require + unique operations and processing. These are caused by address, Kanji, + and traditional year representations. 'zipangu' transforms specific + to Japan into something more general one. + date_publication: '2024-11-07' + bug_reports: https://github.com/uribo/zipangu/issues + url: https://uribo.github.io/zipangu/ + url_cran: https://CRAN.R-project.org/package=zipangu + url_git: https://github.com/uribo/zipangu +ZIPBayes: + version: 1.0.2 + title: Bayesian Methods in the Analysis of Zero-Inflated Poisson Model + maintainer: Qihuang Zhang + description: 'Implementation of zero-inflated Poisson models under Bayesian framework + using data augmentation as discussed in Chapter 5 of Zhang (2020) . + This package is constructed in accommodating four different scenarios: the general + scenario, the scenario with measurement error in responses, the external validation + scenario, and the internal validation scenario.' + date_publication: '2021-11-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZIPBayes + url_git: '' +zipcodeR: + version: 0.3.5 + title: Data & Functions for Working with US ZIP Codes + maintainer: Gavin Rozzi + description: |- + Make working with ZIP codes in R painless with an integrated dataset of U.S. ZIP codes and functions for working with them. + Search ZIP codes by multiple geographies, including state, county, city & across time zones. Also included are functions for relating + ZIP codes to Census data, geocoding & distance calculations. + date_publication: '2022-10-03' + bug_reports: https://github.com/gavinrozzi/zipcodeR/issues/ + url: https://www.gavinrozzi.com/project/zipcoder/ + url_cran: https://CRAN.R-project.org/package=zipcodeR + url_git: https://github.com/gavinrozzi/zipcodeR/ +ZIPFA: + version: 0.8.1 + title: Zero Inflated Poisson Factor Analysis + maintainer: Tianchen Xu + description: |- + Estimation methods for zero-inflated Poisson factor analysis (ZIPFA) on sparse data. + It provides estimates of coefficients in a new type of zero-inflated regression. + It provides a cross-validation method to determine the potential rank of the data in the ZIPFA + and conducts zero-inflated Poisson factor analysis based on the determined rank. + date_publication: '2020-03-31' + bug_reports: https://github.com/zjph602xtc/ZIPFA/issues + url: https://zjph602xtc.github.io/ZIPFA/ + url_cran: https://CRAN.R-project.org/package=ZIPFA + url_git: '' +zipfextR: + version: 1.0.2 + title: Zipf Extended Distributions + maintainer: Ariel Duarte-López + description: |- + Implementation of four extensions of the Zipf distribution: the Marshall-Olkin + Extended Zipf (MOEZipf) Pérez-Casany, M., & Casellas, A. (2013) , the Zipf-Poisson Extreme (Zipf-PE), the + Zipf-Poisson Stopped Sum (Zipf-PSS) and the Zipf-Polylog distributions. + In log-log scale, the two first extensions allow for top-concavity + and top-convexity while the third one only allows for top-concavity. + All the extensions maintain the linearity associated with the Zipf model in the tail. + date_publication: '2020-07-07' + bug_reports: https://github.com/ardlop/zipfextR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zipfextR + url_git: https://github.com/ardlop/zipfextR +zipfR: + version: 0.6-70 + title: Statistical Models for Word Frequency Distributions + maintainer: Stefan Evert + description: |- + Statistical models and utilities for the analysis of word frequency distributions. + The utilities include functions for loading, manipulating and visualizing word frequency + data and vocabulary growth curves. The package also implements several statistical + models for the distribution of word frequencies in a population. (The name of this package + derives from the most famous word frequency distribution, Zipf's law.) + date_publication: '2020-10-11' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zipfR + url_git: https://zipfR.R-Forge.R-project.org/ +ZIPG: + version: '1.1' + title: Zero-Inflated Poisson-Gamma Regression + maintainer: Roulan Jiang + description: We provide a flexible Zero-inflated Poisson-Gamma Model (ZIPG) by connecting + both the mean abundance and the variability to different covariates, and build + valid statistical inference procedures for both parameter estimation and hypothesis + testing. These functions can be used to analyze microbiome count data with zero-inflation + and overdispersion. The model is discussed in Jiang et al (2023) . + date_publication: '2024-02-05' + bug_reports: https://github.com/roulan2000/ZIPG/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ZIPG + url_git: https://github.com/roulan2000/ZIPG +zippeR: + version: 0.1.1 + title: |- + Working with United States ZIP Code and ZIP Code Tabulation Area + Data + maintainer: Christopher Prener + description: |- + Provides a set of functions for working with American postal codes, + which are known as ZIP Codes. These include accessing ZIP Code to ZIP Code + Tabulation Area (ZCTA) crosswalks, retrieving demographic data for ZCTAs, and + tabulating demographic data for three-digit ZCTAs. + date_publication: '2025-02-25' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zippeR + url_git: https://github.com/pfizer-opensource/zippeR +zipR: + version: 0.1.1 + title: Pythonic Zip() for R + maintainer: Leslie Huang + description: Implements Python-style zip for R. Is a more flexible version of cbind. + date_publication: '2019-03-03' + bug_reports: https://github.com/leslie-huang/zipR/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zipR + url_git: https://github.com/leslie-huang/zipR +ZIprop: + version: 0.1.1 + title: |- + Permutations Tests and Performance Indicator for Zero-Inflated + Proportions Response + maintainer: Melina Ribaud + description: 'Permutations tests to identify factor correlated to zero-inflated + proportions response. Provide a performance indicator based on Spearman correlation + to quantify the part of correlation explained by the selected set of factors. + See details for the method at the following preprint e.g.: .' + date_publication: '2021-06-09' + bug_reports: '' + url: https://gitlab.paca.inrae.fr/meribaud/ziprop + url_cran: https://CRAN.R-project.org/package=ZIprop + url_git: '' +zipsae: + version: 1.0.2 + title: Small Area Estimation with Zero-Inflated Model + maintainer: Fadheel Wisnu Utomo + description: This function produces empirical best linier unbiased predictions (EBLUPs) + for Zero-Inflated data and its Relative Standard Error. Small Area Estimation + with Zero-Inflated Model (SAE-ZIP) is a model developed for Zero-Inflated data + that can lead us to overdispersion situation. To handle this kind of situation, + this model is created. The model in this package is based on Small Area Estimation + with Zero-Inflated Poisson model proposed by Dian Christien Arisona (2018). + For the data sample itself, we use combination method between Roberto Benavent + and Domingo Morales (2015) and Sabine Krieg, Harm + Jan Boonstra and Marc Smeets (2016). + date_publication: '2021-06-14' + bug_reports: https://github.com/dheel/zipsae/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zipsae + url_git: https://github.com/dheel/zipsae +ZLAvian: + version: 0.2.0 + title: Zipf's Law of Abbreviation in Animal Vocalisations + maintainer: CD Durrant + description: Assesses evidence for Zipf's Law of Abbreviation in animal vocalisation + using IDs, note class and note duration. The package also provides a web plot + function for visualisation. + date_publication: '2024-05-15' + bug_reports: https://github.com/CDr-er/ZLAvian/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ZLAvian + url_git: https://github.com/CDr-er/ZLAvian +zlib: + version: 1.0.3 + title: Compression and Decompression + maintainer: Semjon Geist + description: The 'zlib' package for R aims to offer an R-based equivalent of 'Python's' + built-in 'zlib' module for data compression and decompression. This package provides + a suite of functions for working with 'zlib' compression, including utilities + for compressing and decompressing data streams, manipulating compressed files, + and working with 'gzip', 'zlib', and 'deflate' formats. + date_publication: '2023-10-18' + bug_reports: https://github.com/sgeist-ionos/R-zlib/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zlib + url_git: https://github.com/sgeist-ionos/R-zlib +zlog: + version: 1.0.2 + title: Z(log) Transformation for Laboratory Measurements + maintainer: Sebastian Gibb + description: |- + Transformation of laboratory measurements into z or z(log)-value + based on given or empirical reference limits as proposed in + Hoffmann et al. 2017 . + date_publication: '2023-01-05' + bug_reports: https://github.com/ampel-leipzig/zlog/issues/ + url: '' + url_cran: https://CRAN.R-project.org/package=zlog + url_git: https://github.com/ampel-leipzig/zlog/ +zmisc: + version: 0.2.3 + title: Vector Look-Ups and Safer Sampling + maintainer: Magnus Thor Torfason + description: |- + A collection of utility functions that facilitate looking up + vector values from a lookup table, annotate values in at table for + clearer viewing, and support a safer approach to vector sampling, + sequence generation, and aggregation. + date_publication: '2023-08-22' + bug_reports: '' + url: https://torfason.github.io/zmisc/ + url_cran: https://CRAN.R-project.org/package=zmisc + url_git: https://github.com/torfason/zmisc/ +zoeppritz: + version: 1.0-9 + title: Seismic Reflection and Scattering Coefficients + maintainer: Jonathan M. Lees + description: Calculate and plot scattering matrix coefficients for plane waves at + interface. + date_publication: '2023-08-19' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zoeppritz + url_git: '' +zoib: + version: '1.6' + title: |- + Bayesian Inference for Beta Regression and Zero-or-One Inflated + Beta Regression + maintainer: Fang Liu + description: Fits beta regression and zero-or-one inflated beta regression and obtains + Bayesian Inference of the model via the Markov Chain Monte Carlo approach implemented + in JAGS. + date_publication: '2023-05-21' + bug_reports: '' + url: https://www3.nd.edu/~fliu2/#tools + url_cran: https://CRAN.R-project.org/package=zoib + url_git: '' +zoid: + version: 1.3.1 + title: Bayesian Zero-and-One Inflated Dirichlet Regression Modelling + maintainer: Eric J. Ward + description: Fits Dirichlet regression and zero-and-one inflated Dirichlet regression + with Bayesian methods implemented in Stan. These models are sometimes referred + to as trinomial mixture models; covariates and overdispersion can optionally be + included. + date_publication: '2024-01-24' + bug_reports: https://github.com/noaa-nwfsc/zoid/issues + url: https://noaa-nwfsc.github.io/zoid/ + url_cran: https://CRAN.R-project.org/package=zoid + url_git: '' +zoltr: + version: 1.0.1 + title: Interface to the 'Zoltar' Forecast Repository API + maintainer: Matthew Cornell + description: |- + 'Zoltar' is a website that provides a repository of model forecast results + in a standardized format and a central location. It supports storing, retrieving, comparing, and analyzing time + series forecasts for prediction challenges of interest to the modeling community. This package provides functions + for working with the 'Zoltar' API, including connecting and authenticating, getting meta information (projects, + models, and forecasts, and truth), and uploading, downloading, and deleting forecast and truth data. + date_publication: '2024-06-27' + bug_reports: https://github.com/reichlab/zoltr/issues + url: http://reichlab.io/zoltr/ + url_cran: https://CRAN.R-project.org/package=zoltr + url_git: https://github.com/reichlab/zoltr +zonebuilder: + version: 0.1.0 + title: Create and Explore Geographic Zoning Systems + maintainer: Robin Lovelace + description: |- + Functions, documentation and example data to help divide + geographic space into discrete polygons (zones). + The package supports new zoning systems that are documented in the + accompanying paper, + "ClockBoard: A zoning system for urban analysis", + by Lovelace et al. (2022) . + The functions are motivated by research into the merits of different zoning systems + (Openshaw, 1977) . A flexible ClockBoard zoning system is + provided, which breaks-up space by concentric rings + and radial lines emanating from a central point. + By default, the diameter of the rings grow according to the triangular number sequence + (Ross & Knott, 2019) with the first 4 doughnuts + (or annuli) measuring 1, 3, 6, and 10 km wide. + These annuli are subdivided into equal segments (12 by default), creating the + visual impression of a dartboard. Zones are labelled according to + distance to the centre and angular distance from North, creating a simple + geographic zoning and labelling system useful for visualising geographic + phenomena with a clearly demarcated central location such as cities. + date_publication: '2025-02-13' + bug_reports: https://github.com/zonebuilders/zonebuilder/issues + url: https://zonebuilders.github.io/zonebuilder/ + url_cran: https://CRAN.R-project.org/package=zonebuilder + url_git: https://github.com/zonebuilders/zonebuilder +zonohedra: + version: 0.4-0 + title: Compute and Plot Zonohedra from Vector Generators + maintainer: Glenn Davis + description: Computes a zonohedron from real vector generators. The package also + computes zonogons (2D zonotopes) and zonosegs (1D zonotopes). An elementary S3 + class for matroids is included, which supports matroids with rank 3, 2, and 1. Optimization + methods are taken from Heckbert (1985) . + date_publication: '2025-02-01' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zonohedra + url_git: '' +zoo: + version: 1.8-13 + title: |- + S3 Infrastructure for Regular and Irregular Time Series (Z's + Ordered Observations) + maintainer: Achim Zeileis + description: |- + An S3 class with methods for totally ordered indexed + observations. It is particularly aimed at irregular time series + of numeric vectors/matrices and factors. zoo's key design goals + are independence of a particular index/date/time class and + consistency with ts and base R by providing methods to extend + standard generics. + date_publication: '2025-02-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zoo + url_git: https://zoo.R-Forge.R-project.org/ +ZooID: + version: 0.2.0 + title: Load, Segment and Classify Zooplankton Images + maintainer: Arick Grootveld + description: |- + This tool provides functions to load, segment and classify zooplankton images. + The image processing algorithms and the machine learning classifiers in this package are (will be, since these have not been added yet) direct ports of + an early 'python' implementation that can be found at . The model weights and datasets (also not added yet) + that are a part of this package can also be found at Arick Grootveld, Eva R. Kozak, Carmen Franco-Gordo (2023) . + date_publication: '2024-01-30' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZooID + url_git: https://github.com/arickGrootveld/ZooID_RPackage +zooimage: + version: 5.5.2 + title: Analysis of Numerical Plankton Images + maintainer: Philippe Grosjean + description: |- + A free (open source) solution for analyzing digital + images of plankton. In combination with ImageJ, a free image analysis + system, it processes digital images, measures individuals, trains for + automatic classification of taxa, and finally, measures plankton samples + (abundances, total and partial size spectra or biomasses, etc.). + date_publication: '2018-06-29' + bug_reports: '' + url: http://www.sciviews.org/zooimage + url_cran: https://CRAN.R-project.org/package=zooimage + url_git: '' +zoolog: + version: 1.1.0 + title: Zooarchaeological Analysis with Log-Ratios + maintainer: Jose M Pozo + description: |- + Includes functions and reference data to + generate and manipulate log-ratios (also known as log size index (LSI) + values) from measurements obtained on zooarchaeological material. Log + ratios are used to compare the relative (rather than the absolute) + dimensions of animals from archaeological contexts + (Meadow 1999, ISBN: 9783896463883). + zoolog is also able to seamlessly integrate data and references + with heterogeneous nomenclature, which is internally managed by a + zoolog thesaurus. + A preliminary version of the zoolog methods was first used by + Trentacoste, Nieto-Espinet, and Valenzuela-Lamas (2018) + . + date_publication: '2022-08-26' + bug_reports: '' + url: https://josempozo.github.io/zoolog/ + url_cran: https://CRAN.R-project.org/package=zoolog + url_git: '' +zoom: + version: 2.0.6 + title: A Spatial Data Visualization Tool + maintainer: Corentin M Barbu + description: |- + You can call zm(), when displaying any active plot to enter an + interactive session to zoom/navigate any plot. The development + version, as well as binary releases can be found at + . + date_publication: '2022-05-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zoom + url_git: https://github.com/cbarbu/R-package-zoom +zoomerjoin: + version: 0.2.0 + title: Superlatively Fast Fuzzy Joins + maintainer: Beniamino Green + description: Empowers users to fuzzily-merge data frames with millions or tens of + millions of rows in minutes with low memory usage. The package uses the locality + sensitive hashing algorithms developed by Datar, Immorlica, Indyk and Mirrokni + (2004) , and Broder (1998) + to avoid having to compare every pair of records in each dataset, resulting in + fuzzy-merges that finish in linear time. + date_publication: '2024-09-24' + bug_reports: https://github.com/beniaminogreen/zoomerjoin/issues + url: https://beniamino.org/zoomerjoin/ + url_cran: https://CRAN.R-project.org/package=zoomerjoin + url_git: https://github.com/beniaminogreen/zoomerjoin +zoomGroupStats: + version: 0.1.0 + title: Analyze Text, Audio, and Video from 'Zoom' Meetings + maintainer: Andrew Knight + description: Provides utilities for processing and analyzing the files that are + exported from a recorded 'Zoom' Meeting. This includes analyzing data captured + through video cameras and microphones, the text-based chat, and meta-data. You + can analyze aspects of the conversation among meeting participants and their emotional + expressions throughout the meeting. + date_publication: '2021-05-13' + bug_reports: '' + url: http://zoomgroupstats.org + url_cran: https://CRAN.R-project.org/package=zoomGroupStats + url_git: '' +zoomr: + version: 0.3.0 + title: Connect to Your 'Zoom' Data + maintainer: Chris Umphlett + description: |- + Facilitates making a connection to the 'Zoom' API and executing + various queries. You can use it to get data on 'Zoom' webinars and 'Zoom' + meetings. The 'Zoom' documentation is available at + . This package is + not supported by 'Zoom' (owner of the software). + date_publication: '2024-02-23' + bug_reports: https://github.com/chrisumphlett/zoomr/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zoomr + url_git: https://github.com/chrisumphlett/zoomr +ZRA: + version: '0.2' + title: Dynamic Plots for Time Series Forecasting + maintainer: David Beiner + description: Combines a forecast of a time series, using the function forecast(), + with the dynamic plots from dygraphs. + date_publication: '2015-08-31' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ZRA + url_git: '' +zscorer: + version: 0.3.1 + title: Child Anthropometry z-Score Calculator + maintainer: Ernest Guevarra + description: |- + A tool for calculating z-scores and centiles for weight-for-age, + length/height-for-age, weight-for-length/height, BMI-for-age, + head circumference-for-age, age circumference-for-age, + subscapular skinfold-for-age, triceps skinfold-for-age based on the + WHO Child Growth Standards. + date_publication: '2019-10-19' + bug_reports: https://github.com/nutriverse/zscorer/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zscorer + url_git: https://github.com/nutriverse/zscorer +Zseq: + version: 0.2.1 + title: Integer Sequence Generator + maintainer: Kisung You + description: Generates well-known integer sequences. 'gmp' package is adopted for + computing with arbitrarily large numbers. Every function has hyperlink to its + corresponding item in OEIS (The On-Line Encyclopedia of Integer Sequences) in + the function help page. For interested readers, see Sloane and Plouffe (1995, + ISBN:978-0125586306). + date_publication: '2022-09-07' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=Zseq + url_git: '' +ztable: + version: 0.2.3 + title: Zebra-Striped Tables in LaTeX and HTML Formats + maintainer: Keon-Woong Moon + description: |- + Makes zebra-striped tables (tables with alternating row colors) + in LaTeX and HTML formats easily from a data.frame, matrix, lm, aov, anova, + glm, coxph, nls, fitdistr, mytable and cbind.mytable objects. + date_publication: '2021-09-28' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ztable + url_git: https://github.com/cardiomoon/ztable +ztpln: + version: 0.1.2 + title: Zero-Truncated Poisson Lognormal Distribution + maintainer: Masatoshi Katabuchi + description: |- + Functions for obtaining the density, random variates + and maximum likelihood estimates of the Zero-truncated Poisson lognormal + distribution and their mixture distribution. + date_publication: '2021-10-09' + bug_reports: https://github.com/mattocci27/ztpln/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ztpln + url_git: https://github.com/mattocci27/ztpln +zTree: + version: 1.0.7 + title: Functions to Import Data from 'z-Tree' into R + maintainer: Oliver Kirchkamp + description: |- + Read '.xls' and '.sbj' files which are written by the + Microsoft Windows program 'z-Tree'. The latter is a software for + developing and carrying out economic experiments + (see for more information). + date_publication: '2021-11-03' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zTree + url_git: '' +ztype: + version: 0.1.0 + title: Run a Ztype Game Loaded with R Functions + maintainer: Vincent Guyader + description: 'How fast can you type R functions on your keyboard? Find out by running + a ''zty.pe'' game: export R functions as instructions to type to destroy opponents + vessels.' + date_publication: '2016-12-23' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=ztype + url_git: '' +ZVCV: + version: 2.1.2 + title: Zero-Variance Control Variates + maintainer: Leah F. South + description: Stein control variates can be used to improve Monte Carlo estimates + of expectations when the derivatives of the log target are available. This package + implements a variety of such methods, including zero-variance control variates + (ZV-CV, Mira et al. (2013) ), regularised ZV-CV + (South et al., 2018 ), control functionals (CF, Oates et al. + (2017) ) and semi-exact control functionals (SECF, South + et al., 2020 ). ZV-CV is a parametric approach that is exact + for (low order) polynomial integrands with Gaussian targets. CF is a non-parametric + alternative that offers better than the standard Monte Carlo convergence rates. + SECF has both a parametric and a non-parametric component and it offers the advantages + of both for an additional computational cost. Functions for applying ZV-CV and + CF to two estimators for the normalising constant of the posterior distribution + in Bayesian statistics are also supplied in this package. The basic requirements + for using the package are a set of samples, derivatives and function evaluations. + date_publication: '2022-11-02' + bug_reports: https://github.com/LeahPrice/ZVCV/issues + url: '' + url_cran: https://CRAN.R-project.org/package=ZVCV + url_git: '' +zyp: + version: 0.11-1 + title: Zhang + Yue-Pilon Trends Package + maintainer: Lee Zeman + description: An efficient implementation of the slope method described by Sen (1968) + plus implementation of prewhitening approaches + to determining trends in climate data described by Zhang, Vincent, Hogg, and Niitsoo + (2000) and Yue, Pilon, Phinney, and Cavadias + (2002) . + date_publication: '2023-03-22' + bug_reports: '' + url: '' + url_cran: https://CRAN.R-project.org/package=zyp + url_git: '' +zzlite: + version: 0.1.2 + title: Lite Wrapper for the 'Zamzar File Conversion' API + maintainer: Frederik Kok Hansen + description: |- + A minor collection of HTTP wrappers for the 'Zamzar File Conversion' + API. The wrappers makes it easy to utilize the API and thus convert + between more than 100 different file formats (ranging from audio files, + images, movie formats, etc., etc.) through an R session. + For specifics regarding the API, please see . + date_publication: '2020-03-18' + bug_reports: https://github.com/fkoh111/zzlite/issues + url: '' + url_cran: https://CRAN.R-project.org/package=zzlite + url_git: '' diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/addendum.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/addendum.html new file mode 100644 index 0000000..9643791 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/addendum.html @@ -0,0 +1,4 @@ +
+
{{.Get "title" | emojify }}
+

{{.Inner | markdownify }}

+
diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/blockquote.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/blockquote.html new file mode 100644 index 0000000..8695e50 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/blockquote.html @@ -0,0 +1,72 @@ + + + + +{{ $.Scratch.Set "bl_author" false }} +{{ $.Scratch.Set "bl_source" false }} +{{ $.Scratch.Set "bl_link" false }} +{{ $.Scratch.Set "bl_title" false }} + +{{ if .IsNamedParams }} + {{ $.Scratch.Set "bl_author" (.Get "author") }} + {{ $.Scratch.Set "bl_source" (.Get "source") }} + {{ $.Scratch.Set "bl_link" (.Get "link") }} + {{ $.Scratch.Set "bl_title" (.Get "title") }} +{{ else }} + +{{ end }} + + + +{{ with $.Scratch.Get "bl_title" }} + +{{ else }} + {{ with $.Scratch.Get "bl_link" }} + {{ range last 1 (split ($.Scratch.Get "bl_link" ) "://") }} + {{ $.Scratch.Set "title_without_protocol" . }} + {{ end }} + {{ range last 1 (split ($.Scratch.Get "title_without_protocol" ) "www.") }} + {{ $.Scratch.Set "title_without_protocol" . }} + {{ end }} + {{ $.Scratch.Set "bl_title" ($.Scratch.Get "title_without_protocol") }} + + + {{ if (gt (len ($.Scratch.Get "title_without_protocol") ) 32) }} + {{ $title := (slicestr ($.Scratch.Get "title_without_protocol") 0 32) }} + {{ $split_by_fw_slash := split $title "/" }} + {{ $count := (sub (len $split_by_fw_slash) 1) }} + + {{ $.Scratch.Set "tempstring" "" }} + {{ range first $count $split_by_fw_slash }} + {{ $.Scratch.Set "tempstring" ( . | printf "%s%s/" ($.Scratch.Get "tempstring") | printf "%s" ) }} + {{ end }} + {{ $.Scratch.Set "bl_title" ( printf "%s..." ($.Scratch.Get "tempstring") | printf "%s" ) }} + {{ end }} + {{ end }} +{{ end }} + +
+

{{ .Inner | markdownify }}

+
+ {{ with $.Scratch.Get "bl_author" }}{{ . }}{{ end }} + — + {{ with $.Scratch.Get "bl_source" }} + {{ . }} + {{ else }} + {{ with $.Scratch.Get "bl_link" }} + + {{ $.Scratch.Get "bl_title" }} + + {{ else }} + {{ with $.Scratch.Get "bl_title" }} + + {{ $.Scratch.Get "bl_title" }} + + {{ end }} + {{ end }} + {{ end }} +
+
diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/codecaption.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/codecaption.html new file mode 100644 index 0000000..f458691 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/codecaption.html @@ -0,0 +1,13 @@ + + + +
+
+ + {{ highlight (trim .Inner "\n\r") (.Get "lang") "linenos=true" }} +
+
+

{{ .Get "caption" | markdownify }}

+
+
diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/gh.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/gh.html new file mode 100644 index 0000000..80909fd --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/gh.html @@ -0,0 +1,6 @@ +{{ $repospec := (.Get 0) }} +{{ $reposplit := split $repospec "/" }} +{{ $org := index $reposplit 0 }} +{{ $repo := index $reposplit 1 }} + +{{ $repospec }} diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/maintenance.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/maintenance.html new file mode 100644 index 0000000..6552988 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/maintenance.html @@ -0,0 +1,6 @@ + +
+
{{ ":warning:" | emojify }} {{ with (.Get 0) | default "Bork Notice" }} {{ . }} {{ end }} {{ ":warning:" | emojify }}
+

This post is currently somewhat borked. Sorry about that.

+

I'm trying to fix it but sometimes things break in unexpected ways.

+
diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/picturefig.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/picturefig.html new file mode 100644 index 0000000..2ac7d73 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/picturefig.html @@ -0,0 +1,30 @@ + + + + + + + + + {{- if or (or (.Get "title") (.Get "caption")) (.Get "attr") -}} +
+ {{ with (.Get "title") -}} +

{{ . }}

+ {{- end -}} + {{- if or (.Get "caption") (.Get "attr") -}}

+ {{- .Get "caption" | markdownify -}} + {{- with .Get "attrlink" }} + + {{- end -}} + {{- .Get "attr" | markdownify -}} + {{- if .Get "attrlink" }}{{ end }}

+ {{- end }} +
+ {{- end }} + diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/pkg.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/pkg.html new file mode 100644 index 0000000..f3b1d03 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/pkg.html @@ -0,0 +1,17 @@ +{{/* Refer to R packages fancily +/* Requires a packages.yml data source and some site params +/* If I get this working right, I'll document it properly, I swear +*/}} + +{{ $pkg := index .Site.Data.packages (.Get 0) }} +{{ $url := $pkg.url_pkgdown | default $pkg.url_git | default $pkg.url_other }} + + +{{ if $pkg.url_cran }} + {{ with .Site.Params.pkg_icon_cran }} {{ . | safeHTML }}{{ end }} +{{ else }} + {{ with .Site.Params.pkg_icon_git }} {{ . | safeHTML }}{{ end }} +{{ end }} +{{ (printf (.Site.Params.pkg_format) (.Get 0)) | safeHTML }} +{{ $pkg.title }} + diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/summary.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/summary.html new file mode 100644 index 0000000..dc290de --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/summary.html @@ -0,0 +1,4 @@ +
+ {{ .Get 0 }} + {{ .Inner | markdownify }} +
diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/trakt.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/trakt.html new file mode 100644 index 0000000..ce0ed4f --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/trakt.html @@ -0,0 +1,4 @@ +{{ $type := (.Get 0) }} +{{ $slug := (.Get 1) }} +{{ $title := (.Get 2) }} +{{ $title }} diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/videofig.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/videofig.html new file mode 100644 index 0000000..eba1a77 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/videofig.html @@ -0,0 +1,28 @@ + + + + + {{- if or (or (.Get "title") (.Get "caption")) (.Get "attr") -}} +
+ {{ with (.Get "title") -}} +

{{ . }}

+ {{- end -}} + {{- if or (.Get "caption") (.Get "attr") -}}

+ {{- .Get "caption" | markdownify -}} + {{- with .Get "attrlink" }} + + {{- end -}} + {{- .Get "attr" | markdownify -}} + {{- if .Get "attrlink" }}{{ end }}

+ {{- end }} +
+ {{- end }} + diff --git a/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/wrapfigure.html b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/wrapfigure.html new file mode 100644 index 0000000..81d3de4 --- /dev/null +++ b/_vendor/github.com/jemus42/jemsugo/layouts/shortcodes/wrapfigure.html @@ -0,0 +1,27 @@ + + + + {{ .Inner }} + + {{- if or (or (.Get "title") (.Get "caption")) (.Get "attr") -}} +
+ {{ with (.Get "title") -}} +

{{ . }}

+ {{- end -}} + {{- if or (.Get "caption") (.Get "attr") -}}

+ {{- .Get "caption" | markdownify -}} + {{- with .Get "attrlink" }} + + {{- end -}} + {{- .Get "attr" | markdownify -}} + {{- if .Get "attrlink" }}{{ end }}

+ {{- end }} +
+ {{- end }} + diff --git a/_vendor/github.com/luizdepra/hugo-coder/archetypes/default.md b/_vendor/github.com/luizdepra/hugo-coder/archetypes/default.md new file mode 100644 index 0000000..c2de8e4 --- /dev/null +++ b/_vendor/github.com/luizdepra/hugo-coder/archetypes/default.md @@ -0,0 +1,6 @@ ++++ +draft = true +date = {{ .Date }} +title = "" +slug = "" ++++ diff --git a/_vendor/github.com/luizdepra/hugo-coder/archetypes/posts.md b/_vendor/github.com/luizdepra/hugo-coder/archetypes/posts.md new file mode 100644 index 0000000..76242f8 --- /dev/null +++ b/_vendor/github.com/luizdepra/hugo-coder/archetypes/posts.md @@ -0,0 +1,12 @@ ++++ +draft = true +date = {{ .Date }} +title = "" +description = "" +slug = "" +authors = [] +tags = [] +categories = [] +externalLink = "" +series = [] ++++ diff --git a/_vendor/github.com/luizdepra/hugo-coder/assets/js/coder.js b/_vendor/github.com/luizdepra/hugo-coder/assets/js/coder.js new file mode 100644 index 0000000..9b46cfc --- /dev/null +++ b/_vendor/github.com/luizdepra/hugo-coder/assets/js/coder.js @@ -0,0 +1,97 @@ +const body = document.body; +const darkModeToggle = document.getElementById('dark-mode-toggle'); +const darkModeMediaQuery = window.matchMedia('(prefers-color-scheme: dark)'); + +// Check if user preference is set, if not check value of body class for light or dark else it means that colorscheme = auto +if (localStorage.getItem("colorscheme")) { + setTheme(localStorage.getItem("colorscheme")); +} else if (body.classList.contains('colorscheme-light') || body.classList.contains('colorscheme-dark')) { + setTheme(body.classList.contains("colorscheme-dark") ? "dark" : "light"); +} else { + setTheme(darkModeMediaQuery.matches ? "dark" : "light"); +} + +if (darkModeToggle) { + darkModeToggle.addEventListener('click', () => { + let theme = body.classList.contains("colorscheme-dark") ? "light" : "dark"; + setTheme(theme); + rememberTheme(theme); + }); +} + +darkModeMediaQuery.addListener((event) => { + setTheme(event.matches ? "dark" : "light"); +}); + +document.addEventListener("DOMContentLoaded", function () { + let node = document.querySelector('.preload-transitions'); + node.classList.remove('preload-transitions'); +}); + +function setTheme(theme) { + body.classList.remove('colorscheme-auto'); + let inverse = theme === 'dark' ? 'light' : 'dark'; + body.classList.remove('colorscheme-' + inverse); + body.classList.add('colorscheme-' + theme); + document.documentElement.style['color-scheme'] = theme; + + function waitForElm(selector) { + return new Promise(resolve => { + if (document.querySelector(selector)) { + return resolve(document.querySelector(selector)); + } + + const observer = new MutationObserver(mutations => { + if (document.querySelector(selector)) { + resolve(document.querySelector(selector)); + observer.disconnect(); + } + }); + + observer.observe(document.body, { + childList: true, + subtree: true + }); + }); + } + + if (theme === 'dark') { + const message = { + type: 'set-theme', + theme: 'github-dark' + }; + waitForElm('.utterances-frame').then((iframe) => { + iframe.contentWindow.postMessage(message, 'https://utteranc.es'); + }) + + } + else { + const message = { + type: 'set-theme', + theme: 'github-light' + }; + waitForElm('.utterances-frame').then((iframe) => { + iframe.contentWindow.postMessage(message, 'https://utteranc.es'); + }) + + } + + function sendMessage(message) { + const iframe = document.querySelector('iframe.giscus-frame'); + if (!iframe) return; + iframe.contentWindow.postMessage({ giscus: message }, 'https://giscus.app'); + } + sendMessage({ + setConfig: { + theme: theme, + }, + }); + + // Create and send event + const event = new Event('themeChanged'); + document.dispatchEvent(event); +} + +function rememberTheme(theme) { + localStorage.setItem('colorscheme', theme); +} diff --git a/_vendor/github.com/luizdepra/hugo-coder/assets/js/purify.min.js b/_vendor/github.com/luizdepra/hugo-coder/assets/js/purify.min.js new file mode 100644 index 0000000..644aca0 --- /dev/null +++ b/_vendor/github.com/luizdepra/hugo-coder/assets/js/purify.min.js @@ -0,0 +1,3 @@ +/*! @license DOMPurify 2.4.1 | (c) Cure53 and other contributors | Released under the Apache license 2.0 and Mozilla Public License 2.0 | 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